analysis/deployment_strategy_2_0.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import math\n",
    "import os\n",
    "import sys\n",
    "sys.path.insert(0,'../src/')\n",
    "import matplotlib.colors as colors\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.ticker as ticker\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from pandas.plotting import register_matplotlib_converters\n",
    "import seaborn as sns\n",
    "from database import SQLiteDatabase\n",
    "from experiment import preliminary_setup\n",
    "import query"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "KWARGS = preliminary_setup()\n",
    "plt.rcParams['axes.xmargin'] = 0\n",
    "plt.rcParams['axes.ymargin'] = 0\n",
    "register_matplotlib_converters()\n",
    "DB_DIRECTORY = KWARGS['database_directory']\n",
    "FIGURES_DIRECTORY = KWARGS['figure_directory']\n",
    "DATABASE = SQLiteDatabase(os.path.join(DB_DIRECTORY,'deployment_strategy_2_0.db'))\n",
    "\n",
    "RBC_REFERENCE_LOAD_SUMMARY = pd.read_csv(os.path.join(KWARGS['summary_directory'], 'rbc_reference_1_load_summary.csv'))\n",
    "\n",
    "RBC_REFERENCE_COST_SUMMARY = pd.read_csv(os.path.join(KWARGS['summary_directory'], 'rbc_reference_1_cost_summary.csv'))\n",
    "RBC_REFERENCE_COST_SUMMARY = RBC_REFERENCE_COST_SUMMARY.rename(columns={'building_id': 'deployment_building_id'})\n",
    "RBC_REFERENCE_COST_SUMMARY['agent_building_id'] = RBC_REFERENCE_COST_SUMMARY['deployment_building_id']\n",
    "\n",
    "NO_TRANSFER_COST_SUMMARY = pd.read_csv(os.path.join(KWARGS['summary_directory'], 'deployment_strategy_1_0_cost_summary.csv'))\n",
    "NO_TRANSFER_COST_SUMMARY = NO_TRANSFER_COST_SUMMARY.rename(columns={'building_id': 'deployment_building_id'})\n",
    "NO_TRANSFER_COST_SUMMARY['agent_building_id'] = NO_TRANSFER_COST_SUMMARY['deployment_building_id']\n",
    "\n",
    "GRID = DATABASE.get_table('grid')\n",
    "GRID = GRID.rename(columns={'building':'deployment_building_id'})\n",
    "GRID['deployment_building_id'] = GRID['deployment_building_id'].str.split('_', expand=True)[1].astype(int)\n",
    "\n",
    "cost_labels = {\n",
    "    'electricity_consumption': r'$D$', \n",
    "    'price': r'$C$', \n",
    "    'carbon_emission': r'$G$',\n",
    "    'zero_net_energy': r'$Z$',\n",
    "    'daily_peak': r'$P$',\n",
    "    'ramping': r'$R$',\n",
    "    'load_factor': r'$1 - L$',\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Building-Level Scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "building_cost_data = DATABASE.query_table(query.get_building_cost_summary())\n",
    "building_cost_data = building_cost_data.rename(columns={'building_id':'agent_building_id'})\n",
    "grid = GRID[['deployment_building_id', 'simulation_group']].drop_duplicates()\n",
    "building_cost_data = grid.merge(building_cost_data, on='simulation_group', how='left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1152x1224 with 68 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "costs = ['zero_net_energy', 'price', 'electricity_consumption', 'carbon_emission']\n",
    "row_count = len(building_cost_data['deployment_building_id'].unique())\n",
    "column_count = len(costs)\n",
    "cmap = 'coolwarm'\n",
    "plot_data = building_cost_data[\n",
    "    (building_cost_data['episode']==building_cost_data['episode'].max())\n",
    "    &(building_cost_data['cost'].isin(costs))\n",
    "].copy()\n",
    "tf_plot_data = plot_data.sort_values(['agent_building_id'])\n",
    "fig, ax = plt.subplots(row_count, column_count, figsize=(4*column_count,1.0*row_count), sharex=False, sharey=False)\n",
    "\n",
    "for i, (ax, ((b, c), c_data)) in enumerate(zip(fig.axes, tf_plot_data.groupby(['deployment_building_id', 'cost']))):\n",
    "    colors = ['grey']*c_data.shape[0]\n",
    "    colors[b - 1] = 'red'\n",
    "    x, y = c_data['agent_building_id'].tolist(), c_data['value'].tolist()\n",
    "    mini_ixs = [i for i in  range(len(x)) if y[i] == min(y)]\n",
    "    patches = ax.bar(x, y, color=colors)\n",
    "    rbc_value = RBC_REFERENCE_COST_SUMMARY[\n",
    "        (RBC_REFERENCE_COST_SUMMARY['agent_building_id']==b) \n",
    "        & (RBC_REFERENCE_COST_SUMMARY['cost']==c)\n",
    "    ]['value'].iloc[0]\n",
    "    ax.axhline(rbc_value, linestyle='--', color='black', clip_on=False)\n",
    "    ax.set_title(f'{b}-{c}')\n",
    "    ax.tick_params('x', which='both', rotation=0)\n",
    "\n",
    "    for i in mini_ixs:\n",
    "        b_x, b_y = [i + 1], [y[i]]\n",
    "        ax.scatter(b_x, b_y, color='green', clip_on=False, marker='v', zorder=100, s=60)\n",
    "\n",
    "    for s in ['right','top']:\n",
    "        ax.spines[s].set_visible(False)\n",
    "\n",
    "    ax.xaxis.set_major_locator(ticker.MultipleLocator(2))\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig(os.path.join(FIGURES_DIRECTORY,f'deployment_strategy_2_0_building_cost_summary.pdf'),bbox_inches='tight',transparent=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- maybe small multiples of bar plots will show the data better?\n",
    "- What is going on with building 7 having really low ZNE on transfer even lower than it's self trained model?\n",
    "- How do these buildings actually compare; what are their similarities? Cluster their daily profile?\n",
    "- If what i have plotted and simulated is correct, you get similar performance if you"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# row_count = 1\n",
    "# column_count = 1\n",
    "# marker_size = 8\n",
    "# edgecolor = 'black'\n",
    "# linewidth = 1\n",
    "\n",
    "\n",
    "# group_columns = ['agent_building_id', 'deployment_building_id']\n",
    "\n",
    "# for c in group_columns:\n",
    "#     summary_data = tf_plot_data[\n",
    "#         (tf_plot_data['cost'].isin(['price', 'zero_net_energy']))\n",
    "#         # (~tf_plot_data['deployment_building_id'].isin([12, 15])) \n",
    "#         # & (~tf_plot_data['agent_building_id'].isin([12, 15]))\n",
    "#     ].copy()\n",
    "#     self_data = summary_data[(summary_data['deployment_building_id'] == summary_data['agent_building_id'])].copy()\n",
    "#     self_data = self_data.rename(columns={'value': 'ref_value'})\n",
    "#     summary_data = summary_data.drop(self_data.index)\n",
    "#     rbc_data = RBC_REFERENCE_COST_SUMMARY.copy()\n",
    "#     rbc_data = rbc_data.rename(columns={'value': 'rbc_value'})\n",
    "#     summary_data = summary_data.merge(self_data[['cost', 'ref_value', c]], on=['cost', c], how='left')\n",
    "#     summary_data = summary_data.merge(rbc_data[['cost', 'rbc_value', 'deployment_building_id']], on=['cost', 'deployment_building_id'], how='left')\n",
    "#     negative_transfer_summary = summary_data.copy()\n",
    "#     negative_transfer_summary['difference'] = negative_transfer_summary['value'] - negative_transfer_summary['rbc_value']\n",
    "#     negative_transfer_summary['polarity'] = negative_transfer_summary['difference']/negative_transfer_summary['difference'].abs()\n",
    "#     negative_transfer_summary = negative_transfer_summary.groupby(['cost', 'deployment_building_id', 'polarity']).size().reset_index(name='count')\n",
    "#     summary_data['difference'] = summary_data['value'] - summary_data['ref_value']\n",
    "#     summary_data = summary_data.groupby(['cost', c,])[['difference']].agg(['mean', 'std'])\n",
    "#     summary_data.columns = ['mean', 'std']\n",
    "#     summary_data = summary_data.reset_index()\n",
    "#     summary_data['polarity'] = '+'\n",
    "#     summary_data.loc[summary_data['mean'] < 0, 'polarity'] = '-'\n",
    "#     summary_data.loc[summary_data['mean'] == 0, 'polarity'] = ':'\n",
    "#     average_summary_data = summary_data.groupby(['cost', 'polarity'])[['mean', 'std']].agg(['count', 'mean'])\n",
    "#     print('Summary grouping:', c)\n",
    "#     # display(negative_transfer_summary)\n",
    "#     display(summary_data)\n",
    "#     display(average_summary_data)\n",
    "\n",
    "# for c, c_data in tf_plot_data.groupby(['cost']):\n",
    "#     for x, t in zip(['agent', 'deployment'], ['Source', 'Target']):\n",
    "#         d_c_data = c_data[c_data['deployment_building_id'] == c_data['agent_building_id']][[\n",
    "#             'deployment_building_id', 'value'\n",
    "#         ]].copy()\n",
    "#         rbc_data = RBC_REFERENCE_COST_SUMMARY[(RBC_REFERENCE_COST_SUMMARY['cost']==c)].copy()\n",
    "#         fig, ax = plt.subplots(row_count, column_count, figsize=(6*column_count, 2.0*row_count))\n",
    "#         sns.stripplot(x=f'{x}_building_id', y='value', data=c_data, ax=ax, color='grey', jitter=False, clip_on=False, size=marker_size*0.9, edgecolor=edgecolor, linewidth=linewidth, label='Target != Source')\n",
    "#         sns.stripplot(x='deployment_building_id', y='value', data=d_c_data,  ax=ax, color='green', jitter=False, clip_on=False, size=marker_size, edgecolor=edgecolor, linewidth=linewidth, marker='D', label='Target = Source')\n",
    "\n",
    "#         if x == 'deployment':\n",
    "#             rbc = sns.stripplot(x='agent_building_id', y='value', data=rbc_data, ax=ax, color='red', jitter=False, clip_on=False, size=marker_size, edgecolor=edgecolor, linewidth=linewidth, marker='^', label='RBC')\n",
    "#         else:\n",
    "#             pass\n",
    "\n",
    "#         for s in ['right','top']:\n",
    "#             ax.spines[s].set_visible(False)\n",
    "\n",
    "#         ax.set_xlabel(f'{t} building')\n",
    "#         ax.set_ylabel(None)\n",
    "#         handles, labels = ax.get_legend_handles_labels()\n",
    "#         unique = [(h, l) for i, (h, l) in enumerate(zip(handles, labels)) if l not in labels[:i]]\n",
    "#         ax.legend(bbox_to_anchor=(1.0,1.0), loc='upper left', framealpha=0, ncol=1, *zip(*unique))\n",
    "#         # ax.legend(loc='upper left', framealpha=0, ncol=1, *zip(*unique))\n",
    "#         building_ids = sorted(c_data[f'{x}_building_id'].unique().tolist())\n",
    "#         ax.xaxis.set_major_locator(ticker.FixedLocator([i - 1 for i in building_ids]))\n",
    "#         ax.set_xticklabels(building_ids)\n",
    "#         ax.set_title(c)\n",
    "\n",
    "#         plt.savefig(os.path.join(FIGURES_DIRECTORY,f'deployment_strategy_2_0_{t.lower()}_building_{c}_cost_summary.pdf'),bbox_inches='tight',transparent=True)\n",
    "#         plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Summary grouping: agent_building_id\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cost</th>\n",
       "      <th>agent_building_id</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>polarity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>1</td>\n",
       "      <td>0.152507</td>\n",
       "      <td>0.098863</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>2</td>\n",
       "      <td>0.114390</td>\n",
       "      <td>0.118158</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>3</td>\n",
       "      <td>0.165417</td>\n",
       "      <td>0.122502</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>4</td>\n",
       "      <td>-0.015400</td>\n",
       "      <td>0.049854</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>5</td>\n",
       "      <td>0.066917</td>\n",
       "      <td>0.090501</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>6</td>\n",
       "      <td>0.110835</td>\n",
       "      <td>0.148247</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>7</td>\n",
       "      <td>0.133688</td>\n",
       "      <td>0.067789</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>8</td>\n",
       "      <td>0.187654</td>\n",
       "      <td>0.135244</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>9</td>\n",
       "      <td>0.202035</td>\n",
       "      <td>0.107254</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>10</td>\n",
       "      <td>0.120147</td>\n",
       "      <td>0.145176</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>11</td>\n",
       "      <td>0.064533</td>\n",
       "      <td>0.125056</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>12</td>\n",
       "      <td>0.000461</td>\n",
       "      <td>0.000361</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>13</td>\n",
       "      <td>0.113801</td>\n",
       "      <td>0.154099</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>14</td>\n",
       "      <td>-0.003308</td>\n",
       "      <td>0.095160</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>15</td>\n",
       "      <td>-0.000386</td>\n",
       "      <td>0.000140</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>16</td>\n",
       "      <td>0.197803</td>\n",
       "      <td>0.148331</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>17</td>\n",
       "      <td>0.106462</td>\n",
       "      <td>0.139369</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>electricity_consumption</td>\n",
       "      <td>1</td>\n",
       "      <td>0.137569</td>\n",
       "      <td>0.095795</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>electricity_consumption</td>\n",
       "      <td>2</td>\n",
       "      <td>0.109669</td>\n",
       "      <td>0.117864</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>electricity_consumption</td>\n",
       "      <td>3</td>\n",
       "      <td>0.164311</td>\n",
       "      <td>0.120710</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>electricity_consumption</td>\n",
       "      <td>4</td>\n",
       "      <td>-0.014066</td>\n",
       "      <td>0.051497</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>electricity_consumption</td>\n",
       "      <td>5</td>\n",
       "      <td>0.058083</td>\n",
       "      <td>0.087671</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>electricity_consumption</td>\n",
       "      <td>6</td>\n",
       "      <td>0.097801</td>\n",
       "      <td>0.144940</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>electricity_consumption</td>\n",
       "      <td>7</td>\n",
       "      <td>0.129889</td>\n",
       "      <td>0.064285</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>electricity_consumption</td>\n",
       "      <td>8</td>\n",
       "      <td>0.178454</td>\n",
       "      <td>0.134720</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>electricity_consumption</td>\n",
       "      <td>9</td>\n",
       "      <td>0.194139</td>\n",
       "      <td>0.105063</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>electricity_consumption</td>\n",
       "      <td>10</td>\n",
       "      <td>0.109659</td>\n",
       "      <td>0.142229</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>electricity_consumption</td>\n",
       "      <td>11</td>\n",
       "      <td>0.063711</td>\n",
       "      <td>0.123641</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>electricity_consumption</td>\n",
       "      <td>12</td>\n",
       "      <td>0.000403</td>\n",
       "      <td>0.000383</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>electricity_consumption</td>\n",
       "      <td>13</td>\n",
       "      <td>0.106059</td>\n",
       "      <td>0.152135</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>price</td>\n",
       "      <td>5</td>\n",
       "      <td>0.113095</td>\n",
       "      <td>0.110148</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>price</td>\n",
       "      <td>6</td>\n",
       "      <td>0.127071</td>\n",
       "      <td>0.171488</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>price</td>\n",
       "      <td>7</td>\n",
       "      <td>0.127583</td>\n",
       "      <td>0.086355</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>price</td>\n",
       "      <td>8</td>\n",
       "      <td>0.197862</td>\n",
       "      <td>0.156924</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>price</td>\n",
       "      <td>9</td>\n",
       "      <td>0.223739</td>\n",
       "      <td>0.144970</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>price</td>\n",
       "      <td>10</td>\n",
       "      <td>0.105391</td>\n",
       "      <td>0.174512</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>price</td>\n",
       "      <td>11</td>\n",
       "      <td>0.093887</td>\n",
       "      <td>0.147293</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>price</td>\n",
       "      <td>12</td>\n",
       "      <td>0.000127</td>\n",
       "      <td>0.000281</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>price</td>\n",
       "      <td>13</td>\n",
       "      <td>0.137707</td>\n",
       "      <td>0.193265</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>price</td>\n",
       "      <td>14</td>\n",
       "      <td>0.002803</td>\n",
       "      <td>0.116027</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>price</td>\n",
       "      <td>15</td>\n",
       "      <td>0.000486</td>\n",
       "      <td>0.000105</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>price</td>\n",
       "      <td>16</td>\n",
       "      <td>0.199202</td>\n",
       "      <td>0.181650</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>price</td>\n",
       "      <td>17</td>\n",
       "      <td>0.089224</td>\n",
       "      <td>0.170133</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>1</td>\n",
       "      <td>0.018133</td>\n",
       "      <td>0.110246</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>2</td>\n",
       "      <td>0.043445</td>\n",
       "      <td>0.119711</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>3</td>\n",
       "      <td>-0.142457</td>\n",
       "      <td>0.100967</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>4</td>\n",
       "      <td>0.060349</td>\n",
       "      <td>0.089258</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>5</td>\n",
       "      <td>0.001109</td>\n",
       "      <td>0.091631</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>6</td>\n",
       "      <td>0.042088</td>\n",
       "      <td>0.109675</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>7</td>\n",
       "      <td>-0.244897</td>\n",
       "      <td>0.054276</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>8</td>\n",
       "      <td>-0.053060</td>\n",
       "      <td>0.111774</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>9</td>\n",
       "      <td>-0.114543</td>\n",
       "      <td>0.107808</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>10</td>\n",
       "      <td>0.080142</td>\n",
       "      <td>0.120662</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>11</td>\n",
       "      <td>0.062935</td>\n",
       "      <td>0.112419</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>12</td>\n",
       "      <td>0.000281</td>\n",
       "      <td>0.000820</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>13</td>\n",
       "      <td>0.041108</td>\n",
       "      <td>0.117621</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>14</td>\n",
       "      <td>0.090835</td>\n",
       "      <td>0.110480</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>15</td>\n",
       "      <td>-0.000222</td>\n",
       "      <td>0.000166</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>16</td>\n",
       "      <td>-0.001065</td>\n",
       "      <td>0.119786</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>17</td>\n",
       "      <td>0.096749</td>\n",
       "      <td>0.110905</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>68 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       cost  agent_building_id      mean       std polarity\n",
       "0           carbon_emission                  1  0.152507  0.098863        +\n",
       "1           carbon_emission                  2  0.114390  0.118158        +\n",
       "2           carbon_emission                  3  0.165417  0.122502        +\n",
       "3           carbon_emission                  4 -0.015400  0.049854        -\n",
       "4           carbon_emission                  5  0.066917  0.090501        +\n",
       "5           carbon_emission                  6  0.110835  0.148247        +\n",
       "6           carbon_emission                  7  0.133688  0.067789        +\n",
       "7           carbon_emission                  8  0.187654  0.135244        +\n",
       "8           carbon_emission                  9  0.202035  0.107254        +\n",
       "9           carbon_emission                 10  0.120147  0.145176        +\n",
       "10          carbon_emission                 11  0.064533  0.125056        +\n",
       "11          carbon_emission                 12  0.000461  0.000361        +\n",
       "12          carbon_emission                 13  0.113801  0.154099        +\n",
       "13          carbon_emission                 14 -0.003308  0.095160        -\n",
       "14          carbon_emission                 15 -0.000386  0.000140        -\n",
       "15          carbon_emission                 16  0.197803  0.148331        +\n",
       "16          carbon_emission                 17  0.106462  0.139369        +\n",
       "17  electricity_consumption                  1  0.137569  0.095795        +\n",
       "18  electricity_consumption                  2  0.109669  0.117864        +\n",
       "19  electricity_consumption                  3  0.164311  0.120710        +\n",
       "20  electricity_consumption                  4 -0.014066  0.051497        -\n",
       "21  electricity_consumption                  5  0.058083  0.087671        +\n",
       "22  electricity_consumption                  6  0.097801  0.144940        +\n",
       "23  electricity_consumption                  7  0.129889  0.064285        +\n",
       "24  electricity_consumption                  8  0.178454  0.134720        +\n",
       "25  electricity_consumption                  9  0.194139  0.105063        +\n",
       "26  electricity_consumption                 10  0.109659  0.142229        +\n",
       "27  electricity_consumption                 11  0.063711  0.123641        +\n",
       "28  electricity_consumption                 12  0.000403  0.000383        +\n",
       "29  electricity_consumption                 13  0.106059  0.152135        +\n",
       "..                      ...                ...       ...       ...      ...\n",
       "38                    price                  5  0.113095  0.110148        +\n",
       "39                    price                  6  0.127071  0.171488        +\n",
       "40                    price                  7  0.127583  0.086355        +\n",
       "41                    price                  8  0.197862  0.156924        +\n",
       "42                    price                  9  0.223739  0.144970        +\n",
       "43                    price                 10  0.105391  0.174512        +\n",
       "44                    price                 11  0.093887  0.147293        +\n",
       "45                    price                 12  0.000127  0.000281        +\n",
       "46                    price                 13  0.137707  0.193265        +\n",
       "47                    price                 14  0.002803  0.116027        +\n",
       "48                    price                 15  0.000486  0.000105        +\n",
       "49                    price                 16  0.199202  0.181650        +\n",
       "50                    price                 17  0.089224  0.170133        +\n",
       "51          zero_net_energy                  1  0.018133  0.110246        +\n",
       "52          zero_net_energy                  2  0.043445  0.119711        +\n",
       "53          zero_net_energy                  3 -0.142457  0.100967        -\n",
       "54          zero_net_energy                  4  0.060349  0.089258        +\n",
       "55          zero_net_energy                  5  0.001109  0.091631        +\n",
       "56          zero_net_energy                  6  0.042088  0.109675        +\n",
       "57          zero_net_energy                  7 -0.244897  0.054276        -\n",
       "58          zero_net_energy                  8 -0.053060  0.111774        -\n",
       "59          zero_net_energy                  9 -0.114543  0.107808        -\n",
       "60          zero_net_energy                 10  0.080142  0.120662        +\n",
       "61          zero_net_energy                 11  0.062935  0.112419        +\n",
       "62          zero_net_energy                 12  0.000281  0.000820        +\n",
       "63          zero_net_energy                 13  0.041108  0.117621        +\n",
       "64          zero_net_energy                 14  0.090835  0.110480        +\n",
       "65          zero_net_energy                 15 -0.000222  0.000166        -\n",
       "66          zero_net_energy                 16 -0.001065  0.119786        -\n",
       "67          zero_net_energy                 17  0.096749  0.110905        +\n",
       "\n",
       "[68 rows x 5 columns]"
      ]
     },
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       "  <thead>\n",
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       "      <th colspan=\"2\" halign=\"left\">mean</th>\n",
       "      <th colspan=\"2\" halign=\"left\">std</th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
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       "      <th>mean</th>\n",
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       "      <th>cost</th>\n",
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       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">carbon_emission</th>\n",
       "      <th>+</th>\n",
       "      <td>14</td>\n",
       "      <td>0.124046</td>\n",
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       "      <th>-</th>\n",
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       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">electricity_consumption</th>\n",
       "      <th>+</th>\n",
       "      <td>14</td>\n",
       "      <td>0.116584</td>\n",
       "      <td>14</td>\n",
       "      <td>0.111960</td>\n",
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       "      <th>-</th>\n",
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       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">price</th>\n",
       "      <th>+</th>\n",
       "      <td>16</td>\n",
       "      <td>0.118919</td>\n",
       "      <td>16</td>\n",
       "      <td>0.130183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-</th>\n",
       "      <td>1</td>\n",
       "      <td>-0.021831</td>\n",
       "      <td>1</td>\n",
       "      <td>0.058768</td>\n",
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       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">zero_net_energy</th>\n",
       "      <th>+</th>\n",
       "      <td>11</td>\n",
       "      <td>0.048834</td>\n",
       "      <td>11</td>\n",
       "      <td>0.099403</td>\n",
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       "    <tr>\n",
       "      <th>-</th>\n",
       "      <td>6</td>\n",
       "      <td>-0.092707</td>\n",
       "      <td>6</td>\n",
       "      <td>0.082463</td>\n",
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      ],
      "text/plain": [
       "                                  mean             std          \n",
       "                                 count      mean count      mean\n",
       "cost                    polarity                                \n",
       "carbon_emission         +           14  0.124046    14  0.114354\n",
       "                        -            3 -0.006364     3  0.048384\n",
       "electricity_consumption +           14  0.116584    14  0.111960\n",
       "                        -            3 -0.005835     3  0.048401\n",
       "price                   +           16  0.118919    16  0.130183\n",
       "                        -            1 -0.021831     1  0.058768\n",
       "zero_net_energy         +           11  0.048834    11  0.099403\n",
       "                        -            6 -0.092707     6  0.082463"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Summary grouping: deployment_building_id\n"
     ]
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cost</th>\n",
       "      <th>deployment_building_id</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>polarity</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>1</td>\n",
       "      <td>0.087626</td>\n",
       "      <td>0.048693</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>2</td>\n",
       "      <td>0.089700</td>\n",
       "      <td>0.040851</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>3</td>\n",
       "      <td>0.132573</td>\n",
       "      <td>0.053157</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>4</td>\n",
       "      <td>0.085142</td>\n",
       "      <td>0.029567</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>5</td>\n",
       "      <td>0.114339</td>\n",
       "      <td>0.021456</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>6</td>\n",
       "      <td>0.068665</td>\n",
       "      <td>0.033624</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>7</td>\n",
       "      <td>0.165602</td>\n",
       "      <td>0.040076</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>8</td>\n",
       "      <td>0.133719</td>\n",
       "      <td>0.046775</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>9</td>\n",
       "      <td>0.124712</td>\n",
       "      <td>0.065241</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>10</td>\n",
       "      <td>0.055936</td>\n",
       "      <td>0.039994</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>11</td>\n",
       "      <td>0.081935</td>\n",
       "      <td>0.026275</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>12</td>\n",
       "      <td>0.277230</td>\n",
       "      <td>0.143430</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>13</td>\n",
       "      <td>0.081044</td>\n",
       "      <td>0.039068</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>14</td>\n",
       "      <td>0.035432</td>\n",
       "      <td>0.013066</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>15</td>\n",
       "      <td>0.063081</td>\n",
       "      <td>0.048561</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>16</td>\n",
       "      <td>0.082057</td>\n",
       "      <td>0.059402</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>carbon_emission</td>\n",
       "      <td>17</td>\n",
       "      <td>0.038764</td>\n",
       "      <td>0.030304</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>electricity_consumption</td>\n",
       "      <td>1</td>\n",
       "      <td>0.075662</td>\n",
       "      <td>0.045564</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>electricity_consumption</td>\n",
       "      <td>2</td>\n",
       "      <td>0.082434</td>\n",
       "      <td>0.040231</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>electricity_consumption</td>\n",
       "      <td>3</td>\n",
       "      <td>0.127065</td>\n",
       "      <td>0.053985</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>electricity_consumption</td>\n",
       "      <td>4</td>\n",
       "      <td>0.077771</td>\n",
       "      <td>0.028485</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>electricity_consumption</td>\n",
       "      <td>5</td>\n",
       "      <td>0.109466</td>\n",
       "      <td>0.022981</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>electricity_consumption</td>\n",
       "      <td>6</td>\n",
       "      <td>0.056692</td>\n",
       "      <td>0.030058</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>electricity_consumption</td>\n",
       "      <td>7</td>\n",
       "      <td>0.158128</td>\n",
       "      <td>0.041395</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>electricity_consumption</td>\n",
       "      <td>8</td>\n",
       "      <td>0.125654</td>\n",
       "      <td>0.046610</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>electricity_consumption</td>\n",
       "      <td>9</td>\n",
       "      <td>0.118784</td>\n",
       "      <td>0.063472</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>electricity_consumption</td>\n",
       "      <td>10</td>\n",
       "      <td>0.049552</td>\n",
       "      <td>0.037100</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>electricity_consumption</td>\n",
       "      <td>11</td>\n",
       "      <td>0.077978</td>\n",
       "      <td>0.027265</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>electricity_consumption</td>\n",
       "      <td>12</td>\n",
       "      <td>0.278188</td>\n",
       "      <td>0.144007</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>electricity_consumption</td>\n",
       "      <td>13</td>\n",
       "      <td>0.073413</td>\n",
       "      <td>0.038019</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>price</td>\n",
       "      <td>5</td>\n",
       "      <td>0.104867</td>\n",
       "      <td>0.058462</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>price</td>\n",
       "      <td>6</td>\n",
       "      <td>0.107189</td>\n",
       "      <td>0.063670</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>price</td>\n",
       "      <td>7</td>\n",
       "      <td>0.133994</td>\n",
       "      <td>0.039496</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>price</td>\n",
       "      <td>8</td>\n",
       "      <td>0.136910</td>\n",
       "      <td>0.073961</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>price</td>\n",
       "      <td>9</td>\n",
       "      <td>0.151938</td>\n",
       "      <td>0.094136</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>price</td>\n",
       "      <td>10</td>\n",
       "      <td>0.081700</td>\n",
       "      <td>0.059410</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>price</td>\n",
       "      <td>11</td>\n",
       "      <td>0.097640</td>\n",
       "      <td>0.060221</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>price</td>\n",
       "      <td>12</td>\n",
       "      <td>0.304910</td>\n",
       "      <td>0.148967</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>price</td>\n",
       "      <td>13</td>\n",
       "      <td>0.105851</td>\n",
       "      <td>0.067774</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>price</td>\n",
       "      <td>14</td>\n",
       "      <td>0.031836</td>\n",
       "      <td>0.040635</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>price</td>\n",
       "      <td>15</td>\n",
       "      <td>0.065142</td>\n",
       "      <td>0.047431</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>price</td>\n",
       "      <td>16</td>\n",
       "      <td>0.121026</td>\n",
       "      <td>0.082944</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>price</td>\n",
       "      <td>17</td>\n",
       "      <td>0.061380</td>\n",
       "      <td>0.054215</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>1</td>\n",
       "      <td>-0.008928</td>\n",
       "      <td>0.038387</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>2</td>\n",
       "      <td>-0.019562</td>\n",
       "      <td>0.032019</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>3</td>\n",
       "      <td>-0.023036</td>\n",
       "      <td>0.096013</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>4</td>\n",
       "      <td>0.033786</td>\n",
       "      <td>0.026026</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>5</td>\n",
       "      <td>0.003667</td>\n",
       "      <td>0.047904</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>6</td>\n",
       "      <td>-0.018787</td>\n",
       "      <td>0.032700</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>7</td>\n",
       "      <td>0.067973</td>\n",
       "      <td>0.159852</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>8</td>\n",
       "      <td>-0.023552</td>\n",
       "      <td>0.062779</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>9</td>\n",
       "      <td>-0.036947</td>\n",
       "      <td>0.081679</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>10</td>\n",
       "      <td>-0.014721</td>\n",
       "      <td>0.021792</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>11</td>\n",
       "      <td>-0.008551</td>\n",
       "      <td>0.026035</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>12</td>\n",
       "      <td>0.057623</td>\n",
       "      <td>0.026895</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>13</td>\n",
       "      <td>-0.019071</td>\n",
       "      <td>0.032837</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>14</td>\n",
       "      <td>0.002860</td>\n",
       "      <td>0.022595</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>15</td>\n",
       "      <td>0.015047</td>\n",
       "      <td>0.010834</td>\n",
       "      <td>+</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>16</td>\n",
       "      <td>-0.021175</td>\n",
       "      <td>0.047137</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>zero_net_energy</td>\n",
       "      <td>17</td>\n",
       "      <td>-0.005697</td>\n",
       "      <td>0.015280</td>\n",
       "      <td>-</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>68 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                       cost  deployment_building_id      mean       std  \\\n",
       "0           carbon_emission                       1  0.087626  0.048693   \n",
       "1           carbon_emission                       2  0.089700  0.040851   \n",
       "2           carbon_emission                       3  0.132573  0.053157   \n",
       "3           carbon_emission                       4  0.085142  0.029567   \n",
       "4           carbon_emission                       5  0.114339  0.021456   \n",
       "5           carbon_emission                       6  0.068665  0.033624   \n",
       "6           carbon_emission                       7  0.165602  0.040076   \n",
       "7           carbon_emission                       8  0.133719  0.046775   \n",
       "8           carbon_emission                       9  0.124712  0.065241   \n",
       "9           carbon_emission                      10  0.055936  0.039994   \n",
       "10          carbon_emission                      11  0.081935  0.026275   \n",
       "11          carbon_emission                      12  0.277230  0.143430   \n",
       "12          carbon_emission                      13  0.081044  0.039068   \n",
       "13          carbon_emission                      14  0.035432  0.013066   \n",
       "14          carbon_emission                      15  0.063081  0.048561   \n",
       "15          carbon_emission                      16  0.082057  0.059402   \n",
       "16          carbon_emission                      17  0.038764  0.030304   \n",
       "17  electricity_consumption                       1  0.075662  0.045564   \n",
       "18  electricity_consumption                       2  0.082434  0.040231   \n",
       "19  electricity_consumption                       3  0.127065  0.053985   \n",
       "20  electricity_consumption                       4  0.077771  0.028485   \n",
       "21  electricity_consumption                       5  0.109466  0.022981   \n",
       "22  electricity_consumption                       6  0.056692  0.030058   \n",
       "23  electricity_consumption                       7  0.158128  0.041395   \n",
       "24  electricity_consumption                       8  0.125654  0.046610   \n",
       "25  electricity_consumption                       9  0.118784  0.063472   \n",
       "26  electricity_consumption                      10  0.049552  0.037100   \n",
       "27  electricity_consumption                      11  0.077978  0.027265   \n",
       "28  electricity_consumption                      12  0.278188  0.144007   \n",
       "29  electricity_consumption                      13  0.073413  0.038019   \n",
       "..                      ...                     ...       ...       ...   \n",
       "38                    price                       5  0.104867  0.058462   \n",
       "39                    price                       6  0.107189  0.063670   \n",
       "40                    price                       7  0.133994  0.039496   \n",
       "41                    price                       8  0.136910  0.073961   \n",
       "42                    price                       9  0.151938  0.094136   \n",
       "43                    price                      10  0.081700  0.059410   \n",
       "44                    price                      11  0.097640  0.060221   \n",
       "45                    price                      12  0.304910  0.148967   \n",
       "46                    price                      13  0.105851  0.067774   \n",
       "47                    price                      14  0.031836  0.040635   \n",
       "48                    price                      15  0.065142  0.047431   \n",
       "49                    price                      16  0.121026  0.082944   \n",
       "50                    price                      17  0.061380  0.054215   \n",
       "51          zero_net_energy                       1 -0.008928  0.038387   \n",
       "52          zero_net_energy                       2 -0.019562  0.032019   \n",
       "53          zero_net_energy                       3 -0.023036  0.096013   \n",
       "54          zero_net_energy                       4  0.033786  0.026026   \n",
       "55          zero_net_energy                       5  0.003667  0.047904   \n",
       "56          zero_net_energy                       6 -0.018787  0.032700   \n",
       "57          zero_net_energy                       7  0.067973  0.159852   \n",
       "58          zero_net_energy                       8 -0.023552  0.062779   \n",
       "59          zero_net_energy                       9 -0.036947  0.081679   \n",
       "60          zero_net_energy                      10 -0.014721  0.021792   \n",
       "61          zero_net_energy                      11 -0.008551  0.026035   \n",
       "62          zero_net_energy                      12  0.057623  0.026895   \n",
       "63          zero_net_energy                      13 -0.019071  0.032837   \n",
       "64          zero_net_energy                      14  0.002860  0.022595   \n",
       "65          zero_net_energy                      15  0.015047  0.010834   \n",
       "66          zero_net_energy                      16 -0.021175  0.047137   \n",
       "67          zero_net_energy                      17 -0.005697  0.015280   \n",
       "\n",
       "   polarity  \n",
       "0         +  \n",
       "1         +  \n",
       "2         +  \n",
       "3         +  \n",
       "4         +  \n",
       "5         +  \n",
       "6         +  \n",
       "7         +  \n",
       "8         +  \n",
       "9         +  \n",
       "10        +  \n",
       "11        +  \n",
       "12        +  \n",
       "13        +  \n",
       "14        +  \n",
       "15        +  \n",
       "16        +  \n",
       "17        +  \n",
       "18        +  \n",
       "19        +  \n",
       "20        +  \n",
       "21        +  \n",
       "22        +  \n",
       "23        +  \n",
       "24        +  \n",
       "25        +  \n",
       "26        +  \n",
       "27        +  \n",
       "28        +  \n",
       "29        +  \n",
       "..      ...  \n",
       "38        +  \n",
       "39        +  \n",
       "40        +  \n",
       "41        +  \n",
       "42        +  \n",
       "43        +  \n",
       "44        +  \n",
       "45        +  \n",
       "46        +  \n",
       "47        +  \n",
       "48        +  \n",
       "49        +  \n",
       "50        +  \n",
       "51        -  \n",
       "52        -  \n",
       "53        -  \n",
       "54        +  \n",
       "55        +  \n",
       "56        -  \n",
       "57        +  \n",
       "58        -  \n",
       "59        -  \n",
       "60        -  \n",
       "61        -  \n",
       "62        +  \n",
       "63        -  \n",
       "64        +  \n",
       "65        +  \n",
       "66        -  \n",
       "67        -  \n",
       "\n",
       "[68 rows x 5 columns]"
      ]
     },
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     "output_type": "display_data"
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th colspan=\"2\" halign=\"left\">mean</th>\n",
       "      <th colspan=\"2\" halign=\"left\">std</th>\n",
       "    </tr>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
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       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cost</th>\n",
       "      <th>polarity</th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>carbon_emission</th>\n",
       "      <th>+</th>\n",
       "      <td>17</td>\n",
       "      <td>0.101033</td>\n",
       "      <td>17</td>\n",
       "      <td>0.045855</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>electricity_consumption</th>\n",
       "      <th>+</th>\n",
       "      <td>17</td>\n",
       "      <td>0.094980</td>\n",
       "      <td>17</td>\n",
       "      <td>0.045139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>price</th>\n",
       "      <th>+</th>\n",
       "      <td>17</td>\n",
       "      <td>0.110640</td>\n",
       "      <td>17</td>\n",
       "      <td>0.067707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">zero_net_energy</th>\n",
       "      <th>+</th>\n",
       "      <td>6</td>\n",
       "      <td>0.030159</td>\n",
       "      <td>6</td>\n",
       "      <td>0.049018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>-</th>\n",
       "      <td>11</td>\n",
       "      <td>-0.018184</td>\n",
       "      <td>11</td>\n",
       "      <td>0.044242</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "                                  mean             std          \n",
       "                                 count      mean count      mean\n",
       "cost                    polarity                                \n",
       "carbon_emission         +           17  0.101033    17  0.045855\n",
       "electricity_consumption +           17  0.094980    17  0.045139\n",
       "price                   +           17  0.110640    17  0.067707\n",
       "zero_net_energy         +            6  0.030159     6  0.049018\n",
       "                        -           11 -0.018184    11  0.044242"
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mQEdHB7m5uViyZAns7Owwc+ZMaGlpoaCgAGvXrkVBQQH27NnzUp/b0qVLsXHjRoSHh2PEiBGor69HQkICTp8+jaSkJLBYrJdqz5sOQRADlJSUDvTu3RvOzs4Qi8W4ceMGAgICcPnyZQiFQoSEhMDHxwfz5s0DjUZDWloaTp48CQ0NDcjlcgwYMAAODg4QCoW4dOkSNmzYAAcHB0RERAAA1qxfA5mTDIiCon6vPF6JmPExUCKUEB4ermiD3Lp1C6GhoTh9+jS8vb072PrBBx/g+PHjCAsLQ2xsLGpqarBv3z5cuHABJ0+eBJ1OV6QlSRJjxoxBeno6IiMjYWBggIqKCqxfvx5Xr15FXFwcCIJAS0sLevXqBRaLhfHjxyv0P2fOHBQVFeGzzz57Sb/EkyGRSNCvXz80Nzdj1KhR0NPTQ3FxMZYtW4bMzEz89NNPL82WGzduaGzZsmXi1KlTmRwOBwBgb29Pc3NzU1q3bt3gvXv33h49enTF0+T90UcfZWzdunWQjo7OMgcHh8xRo0Zdmz9/fi6Px2MsX7588s6dO1cNGTKk2sPDY8rMmTN7//3336cfll9FRYVhWlra/7hcrsTFxeU9d3f3nL///nutSCQiysrKWPv37zdISEjwycnJ+Z+GhoYsMDBw3Jw5c/x9fX3L6+vrtXk83lKgberhg3kPGzYs4f3335+3fPnyAm9v7zvfffddcvuo2x9//OETGBh47aOPPspbunSpwY0bNzS8vb2bKioqjMLCwk49zrMoKyszvnPnzsqqqirloKCghdOnT0/bv3+/1d27d01LS0u/uXPnjnpYWNiC2NjY3O7yeOeddwaqqakJeTzeN0DnUbxnKf+DFBYW/rhq1Sq7nTt3Bq9du3a0t7f3jblz5yYNHDiwwwjohx9+WLB58+bU8PDw2z/99NNNADAzMxNs3rw5EQD69+8/dN68ecG7du06CwB1dXU6BQUF37NYLNLW1nb2qFGjTv/666/XJk2aFNqe57fffutUWlrKLS0tXS6XywknJ6cPVq1aZbt69eoDY8eONaqurl72OM+8O55phJAkyQsAnuscCT6fjw/nfwjCkwAZSbZVtICiwm2xa8HmnZuhpqaGmJgYtLa24tixYygpKcHevXuhpqamGM1TUVGBiooKAgICEBUVBYIgEB4eDk1NTZw61abVKVOmwMbGBnQ6HWw2G6NGjYKqqiqam5vRt29fFBYWIjY2VtEbZ2hoiHHjxqGhoQFVVVXo1asXgoKC0NDQgMDAwB6raD/++GP07dsXvr6+YLFYUFVVRVBQEPz9/XusV/xtpa6uDl8s+gLwbGssd9BwNMC35OP0xdMYPXo00tLS0LdvX9TU1OCff/7Bu+++C0tLS9DpdDQ2NkJVVRUTJkyATCZDeXk5pkyZAlNTU0VP8oQJE6CqqopTp05BQ0MDERERsLe3x7p16yAQCLBq1SrExsbCwcEBDAYDOjo6GDRoEExNTWFvb481a9agsbGxUxkSExNRVFSEESNGKHpqLSwsMHbsWGzfvh15eXkv5VlKJBJ8/PHHGDlyJFxdXcFkMqGpqYk+ffrAzMwM//vf/16KHRRASkoKjhw/AtKN7FLXQnshtsVtA51OR9++feHt7Y3Fixcrrj916hTKysowaNAg+Pn5Keqp4OBg9OnTB3p6ep2O6+jooE+fPggODoaqqipYLBb8/PwwZMgQlJeXw87ODosWLYJYLMawYcPAZrNBp9PR0NAAc3NzjBgxQjFCYmdnh6lTp+LgwYOorKx8ac+tsrISP/30E2JjYzt8a4YMGQKBQIBdu3a9NFveBgiCIJSUlP4cPXq0qqenJ5SUlKCuro7evXvDxcUFS5Ysweeffw5/f3+EhIQodOXr64shQ4agtrYWsbGxHeqbAQMGwN3dHa2trVBWVsambZsgc7vPGQQUbRTSnQRdhQ53d3dFGyQwMBChoaGYP39+B1uzsrKwa9cujB07FhYWFqDT6TAwMMDw4cORn5+PY8eOdUiflJSE5ORkxMTEwNjYGHQ6HSYmJoiJicG5c+dw9epVAMBff/0FABg4cGAH/cfGxmLZsmWor6/Hq8iBAwdQVVWFYcOGgcvlgk6nw9LSEmPHjsXGjRtx9+7dl2bLypUr/RwcHNDuDLajqakJHx8f2u+//97rafM2NTVtLS4u/nbBggXbtbS0mhYvXjx9+vTpgfHx8Qba2tq8IUOGVAPAmDFjLt2+fdv2Ufl5e3uncrlcCQDk5+c7rFu37jzQNjJnbW0tPHDggENZWZm5tbX1Ai6Xuyg7O9uhqKiIExISwquvr2cHBwePXbp0qbOFhUWnYekNGzYknzt3bkl4ePj11NRUe39//y/aRy0vXbrkN3PmzGtMJpP08PC4uWrVKu8Hr39c211dXZutra2zDx8+bHn16lXbPn36XGWxWKS3t3eTtbV17uHDh7udqnvnzh3Hzz///Fz73/b29oL7zz9L+R+ETqfj008/zbl169bmmzdvfkcQBAYPHvxN+6jkw4iPjzcyNTX9lM1mL75y5Yp/fn6+Ufu5iIiIGywWiwSAkpISq5UrV94AgKVLl15tT5OQkOCUlZXlZGhouMjY2HhhTU2NwZ07d7iPuu/j8kqtIeTz+Rg9bjTEjuKODY52CEDWXwa+BR+btm+CSCSCn58fDh48iNOnT8Pe3h6lpaVwc3PrlLebmxskEgny8vLQ3NyM6upq2NraQkNDo+MtCAL+/v64c+cOioqK0P5BuR8GgwEPDw/FdExvb29kZmbC3d0d586dg1D4XKcsP5LKykpkZ2fDycmp0zlPT0+cOnUKEonkpdr0tsLn8zEqdhSkrtJuNUxGkuBb8BF3IA5WVlbIzc2FpqYmHB0doaLyXwdVZmYmvLy8QKfTcevWrW616O3tjdLSUsWUGi8vL5w4cQKXL1+GoaEh9PT0Otnp7e2NwsJCWFhYIDExsdP5hIQEODs7g0brWEWwWCw4Ojri4MGDT/mEnoxr165BRUUFxsbGnc55enq+9JGetxU+n49ZH80C6UFCNkD2yLpZIBDA19cX1dXViqlvBw8ehEQigbOzc6f8PT09UVNTA6lUqjgmk8lQXV0NT8/O31knJyc0NzfDwcEB6enpcHd3B0H8Z1RmZiZ8fHw6HAMALS0tmJub49dff30wyxfGv//+Czs7O6irq3c4ThAEXF1dKYfw+WPHYDD0bGxsOp3w8vLCgQMHcOrUKXh5eXU67+TkBJlMBk1NzU7n/Pz8UFxcjE3bN6HZtrmjM9jOfZ0j7e9BO25ubrhy5UqHDrhDhw7Bycmp0whx+7TnB7Wxd+9eODk5gcHoOLmLyWTC2dlZUR/u3r0bbm5uXerfysrqkcsFeordu3fDxcWl03dHVVUVDg4OOHz48Euzhcfj6ejp6TG7Oqerq0uvr6/XfZb8WSwW+emnn+bEx8cfnTlz5u5z5851FuR90Gg0uVQqJQCgpaWlg10qKiqtD7uWJEkiMDDwUnV19bLq6upldXV1i48fP37U3t5ekJaWtiwwMDB79+7doQEBAZO6uj4wMLBh48aNydnZ2X/QaDT5gQMHjHbv3m1cX1/PHTdu3BxNTc3lN27c8D1//rwfABgaGlacO3fO7DEfRYe5wC8i+uvTll8kEhFcLncRl8tdFBkZOaT9eHV1NfPDDz/0i4iImJWWluYUGxv79wcffPDI9VnffPPNlBUrVuzm8XjfjBkz5qhEIlH8jurq6g/9De+VA8OHDz/eXg4+n79w06ZNnddmPCUv3CEkCGI6QRDXCYK4/qjAA2vXrUW5sByIRueKVpFhW8OjHvW4kHgBTCYTra2tEIvFoNPpIAiiwxSLdmg0Gmg0GsRiMWQyGWg0GpjMLt91MJlMyGQySKXSTg3w+9O0N14YDAbkcrni/vc3al4GYrFYsQ7iQRgMBkiS7LS+gOLpeJSe165bi0pxZdeNBUUm/2mYV8uDTCYDQRCdtCaTyRQalUqlUFZW7jK79uvaHUImkwmJRAKxWPxI/TKZTIjF4k7nH3Ytg8FAa+sj667nQmtr60PL0JXtFE/G49TRa9etRQOtoeOsjU4Zda6bSZJU1IcikUhRDz9Ie50tl8sVx9r//WDjF2irz9vrW5IkH/ruPIiSktJL7bRrbW3tsgxAm4a7WytG8dSMo9PpKg86Q8B/daNcLn+orrr6XjKZTIilYtSj/pH1OxlJKt6Dduh0Omg0WofOWZFI9ETaEIlE3er6/nq5tbX1oe2bl1V/PykPq+9f5ncHAOzt7UuLi4u7vGFRUZHEwsKi6GnzPnTokP4///yjGNlJS0szZbPZdZGRkZV8Pl/v33//5QDA3r17A9zd3XMAQEdHp/bw4cNmALB///5unUcbG5usmTNn9gbaHJr8/HyV4cOHZ924ccMrJSVFAwAyMzNVz5w5o5uWlqYulUqJH3/8MeXrr78+XFJS0smJW7p0qXNTUxMdAK5du6YpFArV3Nzc+Js2bfIdNGjQ0cbGxgWNjY0LWlpaPmtqatI+c+aM7qeffnpi37590UeOHOECgEQiIe6f+ng/N2/e9ODxeIw7d+6o5efn2w0ZMuSuv79/7pkzZ3xFIhGRmpqqXlBQYDt8+PC73ZXZxcUl4/vvvw9r//vBKaNPW34Wi0W2O1/x8fFHACA8PHykra3t0hs3blgvWbJkX2Vl5fKdO3ees7S07FSRq6ioiBobGxW9PWKxWNnZ2bmhqamJfurUKf/uymNqalqwYMECr3vPX7E2s1+/fhmnTp0KLikpUQaApKQk7ZSUFA1DQ0ORWCx+5nUHL9whJEnyT5IkfUiS9NHW1n5o2lkzZ8FU3RQ4jgf6DO7PEKCfpEMHOggNCcXt27cRERGBwMBA5OXlQVdXt8vpbAUFBaDRaLCxsYGmpiZUVVWRnZ3d5cjZ7du3YWVlBTMzM6SmpnZopNwrEzIyMmBl1ba/Y0ZGBszNzZGXlwcHB4dOo44vGhMTE2hqaqK4uLjTuaysLLi5uVFrVJ4Tj9KzQsPH8GgNkzpoaW6BpaUlWltbkZGR0aEhYmVlpQhU5OjoiFu3bnVaWE+SJNLS0qCtra1oaN+5cwcBAQHw8fFBYWFhh17qdto1m5ubCz8/v07nAwICkJOT0+m4XC5Hbm4u+vR55Nrr54KPjw8qKyu7jGKZkZHx0ux4k3mcOnrWzFnQV9J/oro5PT0dGhoaipGxvn37gkajoaioczsqJycH2traHRqDTCYTenp6yM7O7pS+uLgYNBoNJSUlMDY2RlZWVofz97879yMWi5Gfn48pU6Z0U4jnT0REBHJycrr81uTk5CAqKuql2fKW8K1IJGqsqqrqdCIjIwO9e/eGh4dHJ80AbbqSy+VdBjBJT0+HAdcAOtABEU889D0g4gnFe9BOfn4+LCwsoKv738BSv379kJub26mNAQC5ubkYOHBgh2MDBgxAXl5el9+BvLw89O/fHwAQGRnZ5XsjFouRk5OD8PDwbozvWaKjo7v87shkMuTk5LzU+v6bb765UVFRIU1P7xgzsaCgAFlZWfKvv/6689Sax6S2tlZ5xowZU9q3nSgpKTFcv379UTabLV2wYMHWKVOmzGCz2YsJgiDXrl17AQA++uijo7/88stYAwODBTQarbNg7rFly5a4W7du2bPZ7MVmZmYL4+PjDUePHl3xzjvvHB4wYMAcDoezOCwsbG5WVpZWamqqdkBAwHwul7voo48+mvr+++8feDC/06dPO5mbmy/hcDiLoqOjP37nnXf2+/r6Nl67ds138uTJt+5P6+7unvLbb7/5jh8/vmz27Nl/v/fee+/p6ektNTAwWFJSUsJ5MG8AMDIyKnV3d58fEhLyxahRo/4NDAxsWLlyZYq5uXmpiYnJ4j59+sx799139/v6+nZe2/JfmY81NzerstnsJRwOZ9HGjRvt7z//LOV/kNDQ0Oz8/PzFycnJuydPnlzysLRjxoy5duDAgf5cLnfh8ePHOaNGjToSFhb2pZ2d3WdGRkbdrltYvXr1nj179vTlcDiLi4qKuMrKykIAWLhwYUZoaOhVT0/Pz+8FwZlRWVnJcnZ2brGwsMhjs9lLniWoDPGskZsIgrAA8A9Jko+MWuLo6Eg+asifz+dj0PBBqDGp6dwLRwL0E3RoF2njndh3kJqaihs3buDEiRPQ1tbGtGnTUFxcjLq6OowaNQpmZm3OfklJCeLi4hTrTJycnHDnzh0cO3YMJiYmGDx4MDQ1NSGVSnH16lUkJSVh0qRJOH/+PKqqqmBlZYWIiAioqKigtbUV58+fR15eHt577z0UFRXh4MGDCAkJwbVr17B9+3ZER0c//QN9Snbu3Im5c+di6NChMDExAUmSKCwsxNGjRxEXF6f4ULwCdNev+trRnZ75fD6ihkahzqyuSw3TTtCgVagFtiYbTCYTRkZGSE9Ph76+PsRiMQYNGgQ1NTW0tLRg7dq1cHd3R69evbBhwwaYmZmhf//+Ci2eO3cON27cwJgxY2BpaYmsrCzEx8dj69atcHJywrJly3Dp0iUMGjQIOjo6kMlkSE1NRUJCAvT19eHl5YXly5d3KkP7ekUrKysEBARASUkJLS0tOH36NHR0dHDq1KlO05FeFEuXLsXmzZsxePBgsNlsyOVyZGRk4NSpU0hMTOzpgElvjJ6Bh9fR9fX16N2vN8RO4s4jhfd0rVOkg3cnvKuoFz///HNMnDgRQFsk0D59+kAmk2HMmDGKeuru3bvYs2cPCILAuHHjOhxvD5IRExMDS0tLEASB0tJS7N69G1ZWVigqKsKaNWswf/58eHl5wcfHB0wmE5WVldi8eTMiIiLg7e0NBoOBhoYGHDx4EBoaGt1GfHxRxMTEIDMzEwMGDICGhgYkEgmuX7+O1NRUpKendzmtu4d4I/TMZDJnq6mpfR8bG6tqYGAAkiSRm5uLY8eO4dixY2hubsbo0aMxdOhQha7Kysqwa9cuaGtrQy6XY+TIkR3qm8OHD8PPzw+BgYH4a/tfbfX7g7OZSADHAOI2gdiRsbC1bVv+VVxcjEOHDmHTpk0YPnz4f8lJEhEREYpAeGpqahCLxUhOTkZRURHS09OhqvrfYIdUKoWXlxc0NDQQGhoKFosFoVCICxcuQCQS4dq1a6DT6aisrISbmxt8fX3h5eWl0H98fDx8fX2xdevWl/NDPCGNjY2KiNr+/v5gMplobm5GQkICDAwMnnaqaydNZ2Vlfevg4NC5B/0BduzYYfL+++/P1dHRYRgbGzOrq6slFRUV+Oabb9bMnz+/2yAnFI9HVFTUYFVVVdH+/fsfKwDN20JlZaUSh8MR0+l0fPzxxz7x8fF+2dnZfzyPvLOysswcHBwWdnXumRxCgiB2AwgDwAZQBWAJSZKbukv/OA4h0NagHjh8IHgmvP8a1PcqWtwCNFU0IRKJYG5ujrVr18LU1BRAW0jz7777DocPHwZBEIqpGGKxGHK5HMrKypBKpaDRaFBRUYFQKARBEJBIJFBXV4dAIFCEJ29ubsawYcPwwQcfYMWKFThz5gy0tbVRV1cHOp0OJSUliEQiRb7a2tr46aefMHLkUzvnz8yWLVvw1VdfQS6XQyaTQU1NDT///DOGDh3aYzZ1wRvR4AAe3XiOHhbd0Sm8p2FaGg2EhICamhpkMhk8PDywbNky6OjoYP78+bh48aLCIQTa1hrJ5XKoqqoqtqdQV1dHc3OzYtqcjo4OhEIhOBwOFi9erBj1k8lk+PXXX7F9+3aFU9c+lW/s2LGYN29el1OL6uvrYWxsjGnTpiEpKQm6urqKjpY1a9ZATU3tBT3VzpAkiZUrV+LHH3+EiooKBAIBTE1NsXbtWgQFBb00O7rhjdEz8Og6uqysDENGDkGzTfN/jeF7IyJkCgkNZQ1IpVIQBIGpU6di9uzZHa4vLy/H9OnTUVRUBCUlJcjlckilUsjlckUHg7KyskLjX331FRISEnDixAkwGAwQBAGxWAwajQZTU1MsWbIEvr6+KC4uxldffYWMjAyFVoODgxURJdsDhfn5+eHMmTPdTr9+UbS2tmL+/PnYunUrdHV1wefz4enpiY0bN6KrtW49yBuhZ4IgCDqd/j6DwVijp6eH1tZWsNls/Pbbb+jXrx8A4PDhw5g1axYaGxsVupLJZIrpyyRJQkVFBWKxGCwWC0ZGRsjPzwfQNu24SdTUFgn9vvegvVNE2CBUTEslCAKqqqr4+eefMXbs2E62Njc3Y/bs2di/f79Cu7169cLGjRthZGTUKX1tbS1mzJiBEydOKNJHRUVh3bp1HUYfs7KyMG3aNKSlpUFLSwt8Ph/Tpk3D999/3+100leB4uJiTJ06FVeuXIGOjg7q6uowZswY/Prrrx2c4yfgqR1CAGhqaqIvW7bMNS8vj2tqalr31VdfKQK4UDwblEPYNatXr7ZZvnx5LACCxWIJ1q1bt/XBKKZPywtzCJ+Ux3UIgXsbH08cixJ2CaT9pGAmMGHCM8HiLxajqakJbm5uMDTser/HpqYmlJSUoLCwEEwmE15eXsjKykJLSws4HA4IgoCKigqsrKxAp9ORnp6O6upqxWLm+vp6mJiYdAgCwOfzkZ2djQEDBkBXVxdZWVmg0WiKtYP29vZdro152chkMmRlZSlselmjOE/AK2fQ0/IoPfP5fIyZOAal7FKFhg0rDbF86XKYmJiAz+dDT08PXG7HIFGNjY24ceMGWCwW3NzcFAGOAMDOzg66uro4efIkTExM0L9/f0gkEhQWFoLFYsHMzKzL31woFKKoqAhCoRAqKiowMzN76Me1vr4e/v5tU9wrKytRVVUFc3NzPGra94uktbUV2dnZUFdXV0zXfgV4Y/QMPP4sjpjxMSjjlnWom7f8uQVpaWlgsVgICgrqci13OxUVFbh9+zb09PSgqqoKBoOB3NxcNDY2wsjICMbGxrC2tlZoubW1FRcvXgSNRoOBgQHU1dVhamraSevZ2dkwMzODlZWVYup+UlISysvLER4eDjab/YxP6NloampCQUEB2Gx2l4GSXgHeKD07OzuTcXFxUFZWhq2tbSe9kCSJrKwsFBQUQElJCdra2rCzs0NtbS2KiopQXl4Oa2trBAQEAAB4PB4SEhLQ3NwMX19fjJk4BoVahRD3EUPptBIsGyyRfC4ZampqyMzMRFVVFUxNTeHg4PDI9kF9fT2Ki4thYGAAfX39R5aNx+OhtLQUpqamDx1hLikpQV1dHaytrTsFNnqVqaioQFVVFSwtLaGlpfUsWT2TQ0hB8SbxWjqEwD2ncNJYlDaXwkTdBHHb4nq0QXp/I5niqXljGhyP23h+lTT8uFBaf2zeGD0DTzaL41XUNaXbZ+aN0rOLiwv54Bqw50ldXR2CwoJQUF8AKx0rJJ9L7jBKR/FKQDmEFBT3eJhD2PNDWg9BW1sbcdviML7/+FemwUFB8SRQGqZ4E6F0TUEB6OrqIvlcMmbHzKacQQoKitearuMdv0Joa2vjyy++7GkzKCieGkrDFG8ilK4pKNqcwlU/reppMygoKCieiVd6hJCCgoKCgoKCgoKiJ8nMzFQNDQsdlZmZ+VSRbSgoXnVeK4eQz+djxcoVXe5JRkHxukDpmOJNhdI2xdtCXV0d5s2fh7q6up42heIFk5mZqRocHvx5Uk5SRHB48OfP4hTeuXNHjcvlLuJyuYvU1NR+UFdX/77974aGhu4jcT0Fubm5KhMmTOjd/ndCQoKemZnZ/Me9ftq0aUFsNnsxh8NZzGazl3z55Zfu95/ncrmLXF1d37v/WFNTE71Pnz7DdXR0lunr639lbGz8+ddff+38rGWJiooaPHLkyH4AEBkZOWT58uUOz5onRUde+Smj7dwfxOB88nlq3QrFawmlY4o3FUrbFG8L9weTOXbqGLV+8A2m3RlssGpgy/vL6Q0nG9jB4cGfJ51N+t7R0VHwpPk5Ozu3VFdXLwOebNsFgUBAU1VV7XZD+q4oKipSjY+PDwNw/kntvHjxova+ffuib9y48Z21tbWwpKREOTMzUxGmdv/+/QZyuZwoLCy0KS8vVzIyMhIDwLBhw4bU1dVpFRQULNXR0ZHeuHFDY8eOHXZPev+HER8ff+R55kfRxlOPEBIEYUoQxFmCIDIIgrhDEMTHz2pMc3Mz1qxZg/79+6NXr1746KOPkJ6ejrKyMvSN7otCzUJIpklQqFmIgF4BePfddxEbGwsvLy+4ubkhMDAQY8aMgb+/P1xdXeHj44NPPvkEiYmJiI6Ohru7O1xdXeHu7o7Q0FCsW7dOsddbU1MTfv31V/Tq1QseHh6KdCNGjMDZs2exaNEiDB06FGZmZvj4449RVlb2WGWqqqrCJ598AgsLCxgbG2PKlCnIzs5+1kf1VEgkEvz+++9wdXWFgYEBIiIiEB8f3yO2vA3U19fjp59+Qt++fRESEoLRo0ejV0QvFGq16fiu9l0EhgbC1dUVHh4e8Pb2ho+PD3x9feHr64s+ffrA398fHh4e8PDwgIuLC9zc3ODm5qbQZ58+ffDXX39BLBajpKQEixYtUmxG7OXlhdGjR+P48eOIj49HbGwsgoODMXLkSBw4cABy+RN9Wx4KSZLYtm0bfH19YWBggMDAQOzZswcvM4pxV2RkZGDixIkwMjKCpaUlPv/8c9TUPJftfN5KWltbsWnTJkRHRyMkJATvvfcerl69ikuXLrVpu72O1ipEWP8w+Pv7w9vbW6FhDw8PhISEKI55e3tjypQpGDNmTKd6PCwsDL1798aiRYtQUlICoE1nR48exahRo+Dp6amo0319ffHVV1+hqakJMpkMf/75Jzw9PWFgYIDQ0FAcOdJ9++H06dPo378/DAwM4OzsjJ9//hlisfhlPVIAwPXr1zFixAgYGhrCxsYG33zzDRobG1+qDW8yeXl5mDZtGoyNjWFubo65c+eivLwcQqEQP/zwAxwcHGBoaIgBAwYgLCwMampqYLFYUFZWBovFApPJhLq6OkaMGIHk5GRY2Fogm5UNyVQJslnZMDA1wIQJE2BjYwNDQ0PExMQgJSUFABAXFwcLCwuoqqpCVVUVPj4+uHLlSre2kiSJuLg4BAQEwMDAAH5+ftixY8dj1aW1tbX48ssvYWVlBSMjI4wbNw5dRVltbGzEN998o7B3xIgRuH79+tM/4B7kccv8NDzgDDJAAPL+ckaDVZtT+Lymj06ZMiXE0NBwAYfDWeTo6DizsrJSCQC8vLwm+/v7jzcyMvoiMjJy5PHjxzlGRkZfsNnsxf379x/KZDJ/bc9jxIgR/e/lsTgyMnIwAMydO3cEn8/ncLncReHh4SOVlJTkampqLQCwZ88eQ0NDwy+5XO4iDoez+J9//umw/1VeXp6mkpJSq7GxsQgATE1NW/v371/bfn7Dhg1+oaGhl+3s7DJWrFjhAbRtqJ6UlNTrwIEDcTo6OlIA8Pb2blq9evWNB8usqam5PDw8fCSbzV5saGj45b///ssB2kYxLSws5nE4nMUWFhZzz50716mnxcvLa/L8+fO97tlhbmxs/DmHw1lkaGj4ZVFRkbKpqekn27ZtM2lPb2Ji8umOHTtMHsyHoiNPve0EQRCGAAxJkrxJEIQGgBsAhpEkmdHdNQ8Lad7c3IyxY8dCVVUVvr6+UFVVRU5ODhITEyGUCiFzk3Xa4JtIJUCX0xEREQEHBwcIhUIkJiaioqICY8eORVNTE06dOgU+nw8LCwuEhIRAQ0MDubm5OHPmDPT09KClpYV169ZhypQpkMvlqKqqQu/evWFnZ4fm5mYkJiaisLAQvr6+8PDwgFwux+3bt5Gbm4vLly/D0tKy22dUVlYGf39/mJqawsPDAwwGAxkZGUhJScHJkyfh4+PzVM/+aZDJZBgyZAhyc3MREBAAPT09FBUVITExEQsWLMCcOXNelilvTFjzh+m5rq4OMTEx0NfXh5eXF65cuYK07DTAA5APkHfYyFirQAsezh64fPky+vbtq9Cdp6cnGAwGMjMzERQUhKSkJFhZWcHX1xdKSkpIT09HYmIi9PX1oa2tjZKSEqipqYEkSYSHh4PL5aKsrAzx8fFQUlJCREQEjI2NUV1djcTERHh5eWHlypVd7lv4JOH7SZLE9OnTcfLkSQQHB0NfXx/l5eVISkrC2LFj8eOPPz7DU356Ll26hOjoaHh7e8PJyQlisRi3bt1CRUUFrly5AgMDg+dxmzdGz8DDNS0WizF58mS0tLQgICAAWlpaKCgowOnTpyGQCkB4EiAjyQ51NFKB3oG94e7uDpFIhOTkZNy9exdjxoyBkpISbt68iZSUFNDpdPTr1w+Wlpbg8/k4f/48ZDIZBg4ciMzMTKSmpmL79u34+++/cfbsWdjY2ODatWsICQlR1P3JycmoqalBUFAQbt++jcDAQHA4HJSUlCApKQnvv/8+Fi1a1KFM69evx8KFCxEcHAxLS0vU19fjypUrMDIyQnx8/EvZwPvff//FhAkTEBgYCFtbWwgEAly/fh1SqRTJycmK/RRfEm+Unl1cXMidO3ciIiICbm5ucHFxgUwmQ2pqKvLz82FiYgKRSAQ/Pz9oamoiPz8fCQkJkMlkCAsLg6OjI4RCIa5cuYLS0lJoa2ujoLSgS60rZShhzIgx0NHRQXZ2Nq5cuYLIyEgcOnQIVlZWCAoKgqqqKrKzs3HhwgXs2bMHgwYN6mTznDlzsH//fgQHB8PQ0BCVlZVITk5WbD7fHTweD35+fmCz2fD09ISysjKysrJw9epVHD16FL169QLQ1vkdHBwMOp0OHx8fqKqqIjc3F5cuXcL27du7tOlV5WFlPnLkCEJDQ4Gn3HaiK2dQAQnQTtKkWgVavKcdKQT+GyH85ptvkp2dnVsAoH///kPZbHbjrl27znp5eU1uampST0tL+53FYpG2trazo6Kirvz666/XJk2aFLp79+5REonko2+//dbpyJEjXpcuXdohl8sJJyenD2bNmnXCzc2tbuzYsbN5PN7SB+8dHBw81sPDo+D333+/2tDQQG9tbaVxuVxJ+3mRSEQ4OTl9VFNTY2Bra5sVFRWV8t13391uP6+rq/vNgQMHfk5MTDTYtm1beE5Ozu87d+40njt37pTq6upvH1V2TU3N5b1797549OjR4zNnzgw4ffq0T25u7ho7O7sPwsPDb65fv/7StGnTghITE92zsrLW3j+a6uXlNTk8PPz24sWLU83MzL758ccf/3zvvfeKCgsLWfr6+uK5c+f6Z2RkmF68eHHPkSNHuNOnT59WWVm5/Gl+ozeNF7LtBEmSFSRJ3rz37yYAmQCeeqfdLVu2QE1NDcOGDYOJiQl0dXXh5uYGCSQdnUHc+380QLqToLPo8PDwgK6uLoyNjTFmzBiYmZkhMzMTtra28PDwgLGxMWJjY2FmZgYdHR34+flh0qRJqK2tBUmS+PLLL6GhoQEej4fY2Fj4+/tDR0cHpqamGDt2LCwtLaGqqgoOhwN9fX3069cPLi4u+Pzzzx9apoULF8LKygqRkZEwMDAAm81GaGgoevfujVmzZj3to3oqDh8+jDt37mDs2LGwtraGtrY23N3dMX78eCxatIgaNXnOrFu3DoaGhhg0aBBkMhluZ90G4UH85wwCANHmHDZaN+J21m0MHToUFy5cQK9evTBkyBAUFxfj5s2bePfdd1FTUwMHBwcMGTIEhoaG0NPTQ+/evTF06FC0tLSguLhY0XiZMmUK7OzsoK2tDQMDA8hkMrz77rtwdnZWbLw8YcIEJCcn48aNTh13T8zVq1dx+PBhjB8/Hvb29tDW1oaTkxPGjx+PTZs2ITMz85nv8aSQJIkZM2agb9++6NWrF/T09GBoaIioqCiYmJhg6dJO30eKR3D48GE0NjYiJiYGFhYW0NHRgaOjI0QyUccGMqCoo+EOpOekg8ViwcjICKNGjYKdnR2ysrKgr6+P8PBwAMDUqVPh5eUFHR0dWFpaYtKkSSAIAlVVVQgPD0dwcDC++uorhfOUlpaGESNGICgoSFH3jx49GioqKkhKSkJsbCxsbW2hra0NV1dXjB8/Hj/88INipBEAGhoa8MknnyA2Nhaenp7Q1taGpaUlYmJiUFxcjD179rzwZyqVSjFt2jQMHz4c/v7+0NXVhYmJCYYOHQoGg4FffvnlhdvwpvPBBx8gODgYYWFhYLPZ0NfXR//+/aGlpYXa2lqMHDkS5ubm0NHRgY+PD6ZMmQI6nQ5fX1+FtkaMGAEjIyMUVRR1q3WZmwzHEo6BxWIhMDAQgwcPxr59+2BtbY3Ro0cr2jXtI+BTpkyBTCbrYGtaWhq2bduG8ePHw9HREdra2nBwcMC4ceOwf//+h9bX3377LfT19TFw4EAYGRlBT08PwcHBiIyMxHvvvacYYfzll19Ap9MxdOhQhU3+/v4YPnw43nvvPUil0hf0Szx/vvvuO3C53EeW+Ul5qDMI4HmPFMbHxxuZmpp+ymazF1+5csU/Pz/fqP1cRETEDRaLRQJASUmJ1cqVK28AwNKlS6+2p0lISHDKyspyMjQ0XGRsbLywpqbG4M6dO9zOd/oPLy+vgri4uOjhw4cPuHjxot79ziAAsFgsMjc395cff/xxvampadXvv/8eExUVNRgANm7caK6qqtocFhZW98knn2SWl5ebPc0zmD179jUA+OGHH66VlJRYtZfxxx9/vAoAq1evvlJUVGTT3fXHjh0z0NDQaHjvvfeKAMDS0lKkqqoqX7p06Y20tDS3pqYm+i+//BLcp0+f5Ce17W3kuQSVIQjCAoAngO7nQTyCI0eOwMfHRzFaIRAIsGn7JrQ6tXZ0BhU3BRANtDq2YtP2TRAI/uugCQgIUEwZyMjIQEhISKdRECMjI+jo6MDIyAgpKSkwNjaGpqYmTE1NHywbAgMDkZaW1uG4r68vjhw5AomkwzukgCRJ7NmzB35+fp3Oubq6Ijc3F8XFL29f1G3btsHDwwN0esc1y+0OwsGDB1+aLW8D//zzD/z8/CAQCLBr3y7AA5ANkHWpY1l/GfgWfJw6fwpKSkooLS2Fs7MzGhsbYW1tDQ0NDaSnp3c5Yufk5ASRSASBQACJRAJvb28oKSkpzt+5cweurq5QU1PrcJ2SkhLc3NweOpXucdmxYwdcXV2hrKzc4biqqipcXFywa9euZ77Hk5KXl4eysjI4OTl1Oufr64u4uLiXbtPrzqFDh+Dt7Q0are2zIRAIsHHrRsjd5B0byO3cq6Przes71NH31885OTmwsLAAm83ucCmNRoOfn5+i3vXw8EBWVhYcHR1RV1cHGo0Ga2vrTjaqqKjA29u708iehoYGHB0dsXfvXsWxo0ePwsrKCnp6ep3u7eHhgS1btjzpI3pikpOTwWKxYG5u3uE4QRDw9vbG9u3bX7gNbzJSqRSpqalwd3fvdE4kEiEwMFCh53b09fVhZGSE/Px8xTGBQIDSqlLIXGTdar29Hm/XupWVFRgMBgIDAzu1PywsLECj0XDp0qUOx3ft2gVXV1eoqKh0OM5iseDi4oKdO3d2W9Zdu3Z1OevI3t4edXV1io657du3w9vbu5NN5ubmUFZWRnLy69N23rlzJ3x9fTsdd3BwAJ/PR0ZGtxPWHsqMWTOiG2gNnC6dwXbanUJaA2fGrBnRT3Wje3zzzTdTVqxYsZvH430zZsyYoxKJRFGBqaurtz7qepIkMXz48OPV1dXLqqurl/H5/IWbNm1Ketg1v/3229UdO3b8zmKxJBMnTvzw+++/t38wDZ1Ox4wZM+4ePnw4/scff9xw7do1TwDYvn27L4/HM9DU1FzO5XK/E4vFrP/9739effr0qWlsbNQtLCxkPU65CYIgu/r3s2JgYCB2cHDI+Prrr92vX7/us3jx4quPvorimR1CgiDUAewHMIckyU6LHgiCmE4QxHWCIK4/LPKcQCDo0Gi9kHgB9ajv2hlUZI62BgfqcSHxguKwqqqqYg2IWCyGqmrXHReqqqqg0WiQyWSg0WjdplNTU+u0pkRZWRkkSXa71oQkSYhEoi7zpNPpUFVVRXNzczcFe/40NTV1Wz4Wi/VSbXmdeVw9C4VCqKqq4kLiBYhYoq4bEYpM2xoT9aiHWCJGa2sraDQalJWVFQ3b1tbWTk4dAEU6BoMBqVTa6Td+lP6fx+/e2Nj4UG01NTU98z2elObmZqirq3dq7AFt7/P9HUhvO4+r6ZaWlg6/84XEC+DT+G0jgQ9rNA2Qd6ijH7d+vr/eZTKZiv/ar+lqqrNcLu/yPQHa6uz79d7c3Nyp4d2OqqrqS1nD19zc/MLfz7eN+/VcX18PFRUVMBid4+d1VV+2c79GgTatNzIaH6n19nr8QuIFEAQBkiS7vYeKikqnurGxsREsVtdtaVVVVTQ0NHRz87b3s7tvhLq6uuJeD77H96OmpvZaaU4gEHRZFoIgoKam9tTfnvVr1x/TkmvV0E7SpOjOTWmfNirXqlm/dv2xp7rRPcRisbKzs3NDU1MT/dSpU92u1TA1NS1YsGCBFwAsXbpU4Qn369cv49SpU8ElJSXKAJCUlKSdkpKiYWhoKBKLxV0K6sSJE+z+/fvX7N69+4y7u3vqzZs3O6yxu3TpktbmzZvN2v9OTk421dHRqZNIJMTNmzd9zp49u7SxsXFBY2Pjgm+//faPs2fP+hkYGIgDAwOTRo4cOaY9Ympqaqr6vHnzvLuy4Y8//vAFgM8//9zH1NS0oL2Mn332mQ8AzJ8/38/c3Dyvu+cRHR1d2dTUpLVhwwZzACgqKlIWCAQ0AHjvvfcS161bN9bU1PSuvb099cF/DJ7JISQIgok2Z3AnSZIHukpDkuSfJEn6kCTp87CIc15eXh2CrYSGhEIHOsBx4GEvJI4DOtBBaEio4nB2drZipM/U1BRZWVmdLm0PwiEQCMDhcNDS0oKSkhKIRKJOabOysjqNHBYUFMDa2rrbxgeNRoOnpydycnI6naupqYFYLIaNTbcj4c+d3r17d+jxbEculyM/Px9BQUEvzZbXmcfVs7u7O3JychAaEgp1ifojdUw/SYe2XBsioQhGRkaora2FSCRCaWkpSJKEmZlZl8GI6urqIBAIQBAENDQ0OqUxNTVFTk5Ol1NnCgoKuuxdfVLCwsJQWFjY5bm7d+8q1q68TBwcHNDY2NhlSPjs7OwuR+7fVh5X076+vsjNzVX8raijj+Hh2j5B71BH5+TkdKifc3NzO02dAzrW42VlZWAymSgvL4eBgQGqq6u7bLjS6fQupyiTJIm7d+92qOeCgoK6vXdeXh7CwsK6exTPDR8fHxQXF0MoFHY6l5OTg5CQkBduw5vG/Xpms9kgCAKVlZWd0mloaHTZNpBIJCgoKICJyX/t49CQUKiIVB6t9ZP/ab25uRkkSXZZbwsEAlRVVXUa0QsNDcXdu3e7zL6wsPChmvT39+/yXnw+H7W1tXBxcQEABAcHd9kuEQqFKC4ufqmxDZ4Vf3//LsvS0NAAHo+nKPOT4ujoKEg6m/S9VoEWr0un8DmtIWxn1KhRR8LCwr60s7P7zMjIqLNY77F69eo9e/bs6cvhcBYXFRVxlZWVhQCwcOHCjNDQ0Kuenp6fs9nsxTExMTMqKytZzs7OLRYWFnlsNntJeHj4yPvzWrt2rQ+Xy/2ay+UuKikpMfr66687DFcLhUL60qVLR+nq6i7lcrmLzp496/Prr7/+/euvv9poaGjwAwMDFb0TH330UU5NTY3hlStXtA4dOnRIS0ur2dzcfCmbzV4SFRU1W1tbu3MFB6CxsVGVw+EsPnjwYJ/Vq1fvAYB169btPn78eDCHw1l88uTJgHXr1v3d3fPQ0tKS/fjjj38uWbIklsPhLAoMDJxbW1vLBICpU6cWKysrC0ePHv36DHn3MM8SVIYAsBVAHUmScx7nmocFLEhPT8eUKVMwYsQIWFhYAGiLHrV201pInaWde+buLeSmp9Px/rT3FdN+ioqKsGfPHsTGxsLIyAjnzp3DpUuXEBMTAxsbGxAEAZFIhP3790MkEqGhoQFLlizB0qVLYWho2D70DhUVFZAkiYKCAvz999+KtS9Am0O3d+9e/PrrrxgzZky35f3nn38wefJkjB49WhHAoqGhAQcOHMCsWbMeuQbxeVJVVQUXFxf06tULrq6uoNFoEIvFOHPmDBgMBi5cuNBlj/sL4I0JWvAwPV+5cgUfffQRRo0aBW1tbaxesxpy9y6m1t1rRGgVaEFLVQscDgchISHYuXMn7OzsUFhYCFNTU1hYWOCff/5R6BpoG/XdsWMHNDU1UVZWBnV1dYhEIgQFBcHPz0/xG69Zswaurq4IDw8Hg8GAXC7HtWvXcPPmTRw/frzLTo0nCSojEAjg4OAAJycn+Pn5gU6nKwJilJaWIj09/aUE53iQpUuXYuvWrRgxYoQiMEd5eTn279+PXbt2oX///s/jNm+MnoGHa7qkpAQjR45EZGQkHBwcQBAE+Hw+flv3W+d13oCijtYt1sW0d6ZBVVUVJSUliIuLQ0xMDMzNzVFdXY3NmzfD2toagwcPVsy8yMjIwLFjxxTrgPbu3YspU6Zg27ZtsLe3R3NzM6qqqjBq1CiFfouKirB7926oqqoiODgYnp6eoNFokEgkuHDhApqbm3Hjxo0O9Vz//v1RX1+P/v37Q0lJCSRJ4s6dOzhz5gxu3brVqSPwRTB9+nQkJiZi8ODBitGOwsJCHD58GKdPn4aXl9cLt+E+3ig9u7i4kNOmTcOqVaswcuRIxTYo1dXViIuLg0QiwcCBA2Fvb69oGxw+fBjl5eWYPn26QlvFxcWIi4uDnC6HyEHUZXuEdoIGnSIdTJ04FSRJ4siRI+DxeGhpacGYMWMUAegEAgH27NmDsLAwbN68uYO9YrEYTk5OsLCwQFBQEOh0OmQyGa5cuYLs7GxkZWV1O4J47tw5jBgxAiNHjlQ4s83NzTh48CBiYmKwfHlbTI2UlBRERERg6NChHWz6559/EBwcjD///PM5Pf0Xz8PKPHr0aKxYsQJ4yqAyQDdrCZ+zM/gkVFZWKnE4HDGdTsfHH3/sEx8f75ednf3Hy7r/80RTU3N5UlLScldX1xcyJH3p0iWt6OjoT6qrqxczmcyeDXf+CvGwoDLP4hCGALgIIA1Ae/z6BSRJdjt0/rDGBgCcP38eixYtApPJhJqaGkpLSxEZGYnEK4moMqz6rxJuj2B3C2CiraHJ5XIhEAjQ0tICuVyuGGUhCAKmpqbIz8+Hqqoq1NTUUFVVBWVlZWhoaGDlypUIDAxUbC0hEokgEonA4XAgEAggEAhgY2ODkpIScLlcEASB2tpafPfdd48VGGbLli345JNPoKWlBSaTibKyMsybNw9ff/31y3LAFKSmpiI2NhZ1dXXQ09NDaWkpQkNDsX379pe5X9gb0+B4lJ6PHz+OZcuWQU1NDQRBoLiiGKQ72VHHxwFGGgOkmISKigrU1dXB4/GgrKwMkUgELpeLhoYGSKVSxbQfTU1NKCkpoaamBsrKytDT08MPP/yAa9euYe3atSAIAnK5HLq6uqivr4ednR1oNBry8vJgaGiI6upqGBkZYdWqVZ3WLrXzJA4h0NaAHTt2LPLz82FgYIDy8nK4uLggLi5O4cC+bORyOb766iusWbMGxsbGEIvFaGpqwi+//IJx48Y9r9u8MXoGHq3plJQUfPbZZxCLxYrItoGBgbh0/RJabFs61dG0NBoICQF9fX20traiqakJUqkUXC4XcrkcfD4fMpkMDAYDJElCX18ffD4fYrEYenp6UFFRQXV1NaZPn4733nsPFRUVmDdvHvLy8kCj0dDS0gIulwuhUAixWIyFCxdi2LBhGDNmDCorK8HhcFBaWgo/Pz/s2rWr01rFpqYmTJ48GSdPnoS5uTnq6uqgrq7e7dqkF4FYLMaHH36IXbt2wdTUFC0tLZDJZNi4cSMiIyNfig338Ubp2cXFhUxLS8N3332H//3vfzA0NIRMJkN9fT1WrFgBZ2dnTJw4EWKxGFpaWrh79y7kcjlIkoRcLgeHw4FQKIRAIICSkhIkEgmU1JXQaNnYSevEbQLGHGNoaGigpKQEkydPxoIFCzBw4EDcuXMH6urqCj2PHDkS27Zt67KjrLS0FGPHjkVGRgaMjIxQWVkJW1tbxMXFdVtft7Nnzx7Mnj0b6urqUFZWRmlpKWbOnImVK1d2iB8QHx+PadOmgU6nQ01NDSUlJRg3bhx+++23DmvQXwf27t2LDz74oEOZZ8yYge+//769zE/tEAKdncKecgYBYPXq1TbLly+PBUCwWCzBunXrtg4cOPC1jAj4Ih3CmTNnBuzcuXPYe++9t3fVqlXPHjnvDeKFOIRPw6MaG0Db9gi3bt1CS0sLXFxcoKur27bh8cSxKNErgbS/FPQTdHDKONi1dRfU1NSQnJyMiooKuLi4wMfHB9evX8e1a9dgY2ODAQMGKKLVHTt2DC0tLTA1NYWZmRnc3d07rDGSyWRISUlBaWkpioqKoK2tjeHDh0NTUxMtLS24ePEiXFxcEBQU1G0vXVeIxWIkJydDLBYjICAAmpqaT/0MnxWSJHHr1i1UVlbCycnpkR+YF8Ab0+B4HD1LJBLcunULIpEI5ubmmDJ9CioNKiHtLwUzgQm9Yj0MGzgMDg4O0NTUhEQiAY1GA0EQMDMzQ1FREWQyGWpra8Hn82FtbY3c3Fy0trbCysoKpqamcHV17RCM6datWygrK4OOjg5sbGwUI+53795FUVERDA0NFaPd3fGkDmE7GRkZKCoqgrW19SPv8bJoaGjAlStXoKysjKCgoOc9WvnG6Bl4PE2TJIm0tDTw+XzY29srnLiY8TEoZZdCNkAGZgITRtVGmP/hfNDpdNBoNPB4PLDZbJibm6O0tBR3796FqampIlDN2bNnFdPoHB0dkZKSApIk4eHh0WmdUH5+PoqLi1FVVYW6ujo4ODggNDQUTU1NCt3evn0bZWVlsLe3h5WV1UPLVFJSgvT0dHA4nC4DbrwMampqcOPGDWhqasLf379TALCXxBulZxcXF7I9gFFzczMuXboEBoOBoKAgRRAskiRx7do11NXVwc3NDQYGBti9ezfS09PB5XLBYrFQXV0NGxsbxMTEoKmpCYG9A1GgWQBpPynoJ+mw5Fsi6VwScnJy0NLSAh8fnw7BinJzc3H48GGoqalh1KhR4HA4j7Q9OzsbBQUFsLCwgKOj42OXWSKR4NKlSxAKhfDz84OOjk6X6dpHHhsbG+Ht7f1YNr2qPKLMz+QQAvc5hbQGjpZcq6YnnEEKiufBa+UQdgefz8fYSWNR2lwKE3UTxG2Le5mjWgCevpFM0YE3psHxNHp+FXT8OFBaf2zeGD0DVB1N8Wbp+X6H8HlSV1eHoLAgFNQXwErHCsnnkqGr22n/bIpXg2d2CIE2p3DGrBnR69euP0Y5gxSvKy9kH8KXjba2NuK2xWF8//GvbCOaguJRUDqmeFOhtE3xtqCrq4vkc8mYHTObcgbfEhwdHQUXzl3YRzmDFG8qnWMxv8Joa2vjyy++7GkzKCieCUrHFG8qlLYp3hZ0dXWx6qdVPW0GBQUFxXPhtRkhpKCgoKCgoKCgoKCgoHi+9KhDyOfzsWLlCjxsM2QKitcZSuMUrzuUhikoXj/q6uowb/68Lvdipeh5mEzmr+3/XrJkiYuOjs6yM2fO6EZFRQ1WV1f/nsvlLmKz2UsWLFjgBgBRUVGDR44c2e/BfLy8vCbPnz//sfemSUhI0GOz2UueTymef34P8sMPP9jZ2trOBoAFCxa4DRs27LmEXpbJZLCwsJhXWFj4+BEiu+FpfoMPP/xQsRnytm3bTJYsWfJ0m2Z2we7du429vLwmP+l1PTZl9P4ABOeTz1NrTijeOCiNU7zuUBqmoHj9uD/ozbFTx6h1jo9g3759hjweT/l55cdms1tHjRpV8ThpV6xY4fDLL7+M3b179y8RERF1P/zwAwYMGJCwf//+U/v37zeYMGHCp0uXLv3kedn2OrN8+fLbAG4/j7yWLl3qamZmVmppaSl6Hvk9CSkpKXrx8fF+AK4CQGJioml6errF0qVLHzsClkAgoKmqqsq7OhcbG1u2YMECnXPnzumGhYU9do/QUzuEBEGwAFwAoHwvn30kST5WLwGPx8PQ0UNRa1oLciyJu/F30SeyD4w4RtDR0cGIESMwcOBARXj4oqIibN26FZcuXYJAIACDwYCWlhaUlZVRW1sLsVgMiUQCsVgMmUwGFRUVhIaGwtzcHBcuXEBpaSlaWlpAkiTYbDZmz54NQ0NDbN++HUVFRTAxMUFUVBTS0tJw5swZNDc3g8lkwtzcHBKJBEKhEC4uLjA3N8fXX3+N8vJyuLm5Ye7cuS970+AXQmFhIX755RecO3cOmpqaeOeddzBx4sTXbj+iV4mKigqMGDsCdeZ1wFig6EQRBg4fCBszG/D5fDg4OOCdd96BjY0NDh06hIMHD6KwsBBSqRQAwGazYWlpibS0NAgEAsjlcsUmxTKZTBHK393dHStWrICBgYHi3snJydi5cydKS0thYWGBMWPGoKioCIcOHUJFRQVoNBq0tLTQt29fjB8/vlNDISkpCVu2bAGfz4ednR0+/vhjhISEvNTn96TU19dj7dq1OHjwIEiSxPDhwzFr1iyqEfQM8Hg8DBs9DDxTnqKeDusfBhOuCYyNjTFu3DiEhoZCLBbjwIEDOHr0KIRCITw9PSGXy3H69Gm0trZCU1MT/fv3R0VFBZKSkiCRSECSJOzt7aGlpYXy8nIAbT22QqEQcrkcbDYb0dHRsLW1xf79+1FUVARTU1OMHz8ednZ2+OWXX3DmzBm0trZCT08PH3zwAYKCgvDbb7/h3LlzEAqF0NXVxaxZs/D+++932rbidSIzMxOrV6/GlStXoKenh2nTpmHMmDE9tS3FawFBEGZMJnOOiooKgoODMXHiREyePBksFgtnzpzBb7/9hvz8fGhpaUEmk6GlpQWOjo6YM2cO0tPTsWTJEtTX1wMAaDQagoKC4Ofnh3/++QfFxcUQCoVQVlZGSEgInJ2dcfr0aRAEgVGjRsHV1RV//fUX0tLSIBaLQRAE7O3tMWvWLAwePLjTlibNzc3YuHEjdu/eDYlEgoEDB+KDDz7oUKffj0AgwF9//YWdO3dCJBJhwIAB+PDDD2FsbAwAqKqqgoefB6oMq0COIJF7Ihc+QT64nnz9la0PKyoq8NtvvyE+Ph7KysqIjY3F1KlToaam9lLuz+PxlI2MjJ5bsJjy8vLHqnBWrVplu3Llyolbtmz5LSoqqtN+giNHjqycNGmSPD09Xf1h+SQmJjoaGBhEtra2qnzwwQd7vv322zSRSERERUWNyMrKspdKpYzo6OizW7duvXj/dTwej9G/f//xxcXF5jQaTf7JJ5/s/eyzz7JtbW1nf/311wfHjx9fxuVyF/r6+qb8+++//0ZGRg4xNDSs27x5c+L9+cjlcpqbm9vUsrIyM319/fIzZ85sNjAwEA8cOHDgzZs33SUSCdPKyir/0qVLO+h0OmJjYyNOnjwZSqPR5AYGBhVpaWkbysvLlQYPHhxbXl5uJJPJ6FOnTj26YsWK1PvvM3369MD09HSL5OTk3V5eXpNVVFSEd+/etWhubtacNm3a/p9++ukmAIwYMaL/pUuXfKRSKcPb2zslPj7+6IPP7NChQ34TJ068CLSN2I0ZM+YjKyurvIKCAmstLa36y5cv/8HlciXbtm0z+eKLLyZIJBIlPT29msOHD2+1t7fvpJWufoOEhAS9KVOmvCsWi5UAYOHChbs//PDDgtWrV4+ora014HK5i4KDg68mJCSESaVSJS6XazNu3Ljjn3322e2unsX06dMDz5075yUWi5XlcjlNV1e3NjIyMmXlypW3AMDNzW3qwIEDr69YsSLV398/9ddff/UJCws7+TDt3M+zTBltBRBBkqQ7AA8AkQRBBDzqopqaGvSJ6gOeCQ9kJAkQABlJosWuBVV1VTAwMMD69esxc+ZMSCQSXLlyBaNGjUJqaioqKipgb2+v2J9NIpGgpqYGTk5OGDp0KCIiIqCiogI6nY6jR49i3759sLW1RXR0NFxdXSGXy6Gvr49FixYpNmUNDg6GSCTCF198gYyMDPTp0wcDBgwAi8VCWloazMzMEBQUhMuXL2PTpk1gsVjw9fVFdXU1+vTpg+3btz/DI+x5kpOT4eXlhZs3b8Lb2xtGRkb43//+h759+0IkeukdJ28EJSUl6DewH+rM6oBIAAQgHyAHz5iH25m34ePjg5aWFkyePBmDBw/Gli1bkJubCxqNhn79+mHw4MGoqalBWVkZBgwYgJEjR8Le3h5isRhSqRRmZmYYPnw4Ro8erWgQ5OTkAAB+/vlnfPbZZ2CxWAgODgZBEJg9ezbWrFmDu3fvQk9PD3369IG/vz8uXbqEIUOGoKSkRGH76tWr8fnnn0NTUxO+vr5oaWnB8OHD8dNPP/XQ03w0ZWVl8PDwwIEDB+Do6AgnJyccPHgQHh4eKCsr62nzXkt4PB76RvdFjUlNh3pa5CBCdX01WCwWFi1ahG+//RYTJkzArl27YGtrCxcXF+zfvx8HDhxQ6NTR0RHbt29HfX09Ro4cicGDB4PL5SI3NxepqamoqalR7A3Xv39/GBkZKTowPvzwQ0ilUgQHB0NJSQlz585F3759kZmZiejoaAwZMgTKyspYuHAhIiIicODAAZiYmGDYsGEICAjA2rVr4e/vj8bGxp5+pE/F8ePHERQUhPz8fPj6+kJPTw8LFy7EiBEjIJPJetq8VxKCILwYDEa6l5fXByNHjoS5uTl+/fVXhIaG4quvvkJsbCwkEgn8/PygoaGB9PR0sFgsNDQ0ICIiAh9++CFcXFwwbtw49O3bF0pKSkhKSsLOnTsVbQ03NzeIxWKkpaXhl19+gbm5ORwdHbFmzRqMHj0aAoEAvXr1grOzM+rr61FUVIT3338fM2bMwP1bfdXV1cHX1xd//fUXbG1t4ebmhoSEBLi7uyvq9PtpbGxEUFAQ1q1bBysrK3h4eODixYvw8PBAWloaKisrYWVvhUqDSsV7Kx8gR6FmITz8PF7J6aMZGRlwd3fHuXPn4O7uDmtra2zYsAEBAQFoaGjoafNeGHK5nLFgwYL3//jjjz+GDx9e2VWadevWWQIg3dzcmh6WF4/H0yspKVmxffv2337++ecJPB6PMXPmzBA1NTVhRUXF8pycnOUnTpzodfLkSb37r5s5c2Y4QRDg8XjfrF+/fuOyZcsm83g8hrOzc96xY8ds8/PzVeh0ujwzM9MGADIzM22GDh2a++D96+vrDaZNm3autrZ2iYqKiuiDDz7oDQA//vjj2YqKiuU8Hm+pWCxWWrx4sRsAHDlyJDIvL+/bmpqabw4cOLADACZNmhTt7++fVVFRsSIpKemndevWjSovL3/oqASfz9e6e/fu/zZu3Lhm06ZNIwDg22+/dSotLeWWlpYuLy8vX5afn2++atUq2wevvXv3rk1MTEzRfWXgfvjhh2dra2u/VlFREX799ddeADB//vx358+fv7+mpuYbCwuLsmnTpg163N/AxcWlKSUlZXVVVdV3mzZt2vDdd9+NBYC5c+ceMDMzy6uurl528ODBE7GxsUc8PT2vV1dXL/v555+vP+xZlJeXmx0/fnxdcXHxjxMnTkw8dOhQIADk5+erFBUVWS9atCgNAIKCgorS09M7lfthPPUIIdlWqzXf+5N577+Hbmook8kwdPRQiBxEQBT+2x3mXmOj+WQzEq8mYsr4KTh48CD27t2LdevWYeDAgThy5AhiY2Ohra2NP/74A5MnT8aWLVvw7rvvgsvlAgBMTU3h6OiIdevWgcPhYMqUKYqN583NzWFsbIwLFy5g6tSpWL9+PWxtbaGtrY1jx45h8ODBcHNzU9hqZ2eHvXv3orGxEZqamhAKhZg1a5ZiM1tTU1PY2Njg/fffx6BBg7rd/PVVhiRJTJgwAQMGDOiw8a29vT327t2LP/74A/PmzetBC18/+Hw+RowdAamLVOEMAvf+Hw0ICAGOnz6OqROnwtbWFhs2bICLiwvq6+sxY8YMKCkp4ciRI3BxcUFk5H9T5a2srKCjo4Nbt25h/Pjxil5mCwsLGBoa4qOPPsLPP/+M3bt347333lP0rJqamsLBwQG///47nJycMGzYMEWelpaWSEpKwtKlS7Fx40ZkZWUhLi6uy+uXLl2KUaNGwdzc/CU8xSdj3rx5sLS0RHh4uOKYtbU1zp49izlz5mDv3r09aN3rB5/Px9DRQyG0F3ZbT19LvYbxY8Zj69at0NPTw8SJE0EQBPbu3QtVVVUEBATAz88PcrkcR48exYgRI+Dg4KC4h729PXbt2oWKigo4OzsjOjpacc7S0hKJiYkoLi6Gh4cH6uvr0atXL5iamiIrKwsWFhbo1auXIr2NjQ3++ecfZGZmok+fPh1mbbSPMC5fvhwrV6580Y/uuSIWizFp0iSMGDECZmZmAP57H3fu3Indu3djwoQJPWzlqwVBEISysvLu6OhoDXd3d8VxOzs7HDhwAKtWrcLs2bOhrt424HJ/m2Hs2LEgSRIzZsxQfM/bz69ZswZ9+/aFiYkJgLZ618DAADdu3ICjo6Oi47q2thYzZ86ElpZWl/n/888/OHPmDPr06QMAWLx4MTQ1NREVFaWo0y0tLXH58mW89957OH/+fIfyLV++HHQ6HcOGDevwDdDT08OkSZNQwauAwF7Q6b1FNFByvARBvYOQfP7Vmj46bdo0+Pn5wdfXV3Gs/Z3+5ptvXunOyGeBRqPJTE1N89euXRsyfvz4v+8/d+LEib5cLjdAWVlZ9O233/75qNkA4eHh15lMJjlo0KBqHR2dmmPHjhlcvXrVqaKiwoTL5XoDQGtrq8rVq1f1AwICqtqvS09Pt5kyZcoZABg+fHiltrZ23YkTJ/QjIiJy//zzz4ht27bxPDw80tLS0hwrKyuV6uvr2cOGDat68P7q6up1H330UT4AxMTEXN68eXMEgFObNm2y37Vr1wCxWKwkEonU7ty5Uw7gtoGBQWlwcPDUsLCwW19++eWte7Y43bp1y33fvn39AUAqlTIuXbr0UKGGhYXdYjKZ5OjRoyvGjx+vCQAJCQlOWVlZToaGhosAQCwWK9+5c4cLoIMjKxKJ1MzNzVvb/9bS0uJNmjSpFADs7OyKiouL9fLz81VEIpHK/PnzcwHg448/vjR58uTpj/sbBAcH144cOXJCaWmpCY1GI+vr67kPK899v0u3z8LOzi6jfeuT+fPn5y5fvnx8amqq+k8//eTl6el5s30aqZWVVVNDQ4P249yvnWcKKkMQBJ0giFsAqgGcIknyykPS6haVF6HWtLZjZaVIAMj6y8C34GPzzs3w8PDAjh07FNMW2Ww2zMzMkJ6eDkdHR5SXl8PKykrhDLajrKyMgIAAqKmpKZzBdpydnSGVSiGVSmFra4tz586hpqYGAoEALi4d13MSBIGQkBCkpqYiNTUV/v7+CmewHS6XCxsbGxw4cOBJHtsrw9WrV9Ha2tqhoQa0TZHx9/fHpk2besiy15P29VaNVo2K3tkOEACiAL45H5u2b4K6ujqsrKyQmZmJkJAQKCkpQSaTIT09vcspmgEBAWhpaek0cuvl5YWKigps27YN7u7unabZaGlpwcXFRdEIuh9fX1/cuHED9fX1OHDgwEOv37lz51M9lxeJUCjE0aNHERDQeXJCQEAA/v33XwgE1LZRj4tMJsPYSWPBM+U9sp7euXcn3NzcwGKxQBAExGIxcnJyIBKJFE5Z+witvb19h2xoNBqCg4MhlUo7OHft+Pn5oaioCD4+PkhPT4dcLkdLSwtKS0u73Hjezc0NMpkM9zsBQFs9Hhoaiq1btz79Q+khTp48CR0dHYUz2A6DwYCPjw82btzYQ5a90jjR6XRjV1fXDgcJgkBgYCAYDEanelBTUxNubm44f/48nJycOnXuqqqqwt/fH7dvd1y65OHhgcbGRri5uaGqqgq3b9+Gq6urwhlsR11dHZ6ensjMzISHhwf++usvxbkdO3YgMDCw0zRSHx8fpKSkoKKi4zK0LVu2ICAgoFN6e3t73M68jSqjqm7fW0QBBVoFCAoLemVGCouLi5GRkdFp6U3777Vt27YesuylQF68ePHPwsJCiyFDhkTdf2LAgAEJ1dXVy0pKSn6YO3du3qMyelAPNBoNJEkSc+fO3V1dXb2surp6WUNDw4KFCxdmPI5h77zzzt3S0lLzpKQk27CwsBwzM7OSOXPmhBgbGxc/zv2Btumof/zxx/i4uLj1PB7vm169eiW2trYyAeDOnTu/TZ48+Vx6erqZh4fHAoFAQCNJkti4ceO6dnubmpq+HDlyZJcjp+2wWCxp+7/bR97vLRk53p4Pn89fuGnTpqQHr6XRaDKJRKIwnE6nS+87J5fJZE80J7+r32D27Nl9tbW1GysqKpbdvXv3O5lM9liDcA97FiwWS3x/2tDQ0Evfffedf0JCQtAHH3ygKGdTUxOTyWSKH8z7YTyTQ0iSpIwkSQ8AJgD8CILoFCWHIIjpBEFcB4EMsZq468pKkbitsVGPeuTm56KpqQlaWloQCASKSlYoFEJbW7vDsQfR1tZWrMV6wBZoampCIBBAV1cXLS0tEAgE0NTU7OQ8Am0NYaFQCKFQ2O291NXVUVtb202BXm3q6uqgra3d5cuspaX1ynw0XiXa9UwQxPUHoy6uXbcWpc2lj9b4gDaNX0i8AG1tbcjlcoW+ZDIZ5HJ5l2snlJWVwWKx0Nra2uE4nU6HqqoqeDweNDU1u7ytnp5el++EkpISVFVV0dTUhLq6um51rqamBh6P102heo6WlhbQ6XSoqKh0OqeiogImk4nm5uYurqRo535Nl5WXtWn4/tHtThf8V09XVFZALm9b197a2go6nQ51dXUwGG3fPaFQCE1NzW7rGJIku+yoUFJSAovFAp1Oh1wuh1QqhUgkgoqKSpdrm2k0GlRVVbtcV6elpfVaRkitra3t9n3U0tJ6bb87Lxg9dXV1Wnffc4lE0uVF7d/6h7UphEJhh2M0Gg0aGhqg0+mQSqUQCATdBly6vx1TXV0NAJDL5WhsbOzyngwGA5qamp2+wQ0NDV2mT0xOhFxb/shvj6SvBAX1Bfj2u2+7SfRyqaurg6am5hv13j4JBgYG4oSEhN+SkpL8p06dGvy0+Zw9e9ZbIpEQx48f59TX13MiIyMr/f397+zatat3U1MTHQCOHDnCfXAKpqura+7evXv92883NDToRkdHV2lpack0NTXrr1+/7j1lypQCPz+/3H///be/u7t753nMAJqamnR///13KwDYu3evn4uLS159fT0TABwcHJpLSkqUr1275gUAEomESExM1P3ss8+y//333wMikUilrKxM2dXV9c7//ve/iPap8Fu2bDF9mmfRr1+/jFOnTgWXlJQoA0BSUpJ2SkqKxoPpdHV1q06ePMl+WF7W1tZCFoslWL16tQ0A/PrrrwH29vadpswCXf8GLS0tKmw2u4HJZJIff/xxAEmStHv3FrW2tiqim2pqaoqEQqFixOlJnsXChQuT4+Pj+wLA6NGjFT1IN27c4BobG5c/rHwP8ly2nSBJkg/gLNqaEQ+e+5MkSR+QcFJqUQIRT3Q/sZQE6Cfp0IEO9HT04OTkhKKiInA4HNy9excymQyGhobIz8+HoaEhCgoKOszHbycnJ6fLRoNIJEJlZSW4XC6ys7Nhbm4ODoejGCV8kPb7tN+ri7KhqKjotQ0s4+rqiuLi4k4OBtBWdk9Pzx6w6tWmXc8kSfo8+PGfNXMWTNRNgON4uMZPtGk8NCQUeXl5UFVVRV5eWycgk8mEpqZmh3V97dTU1EAikUBDo2Pd1tTUhObmZvj5+aG4uMsOPGRlZSmCNN0Pj8eDVCqFgYEB3NzcUFRU1MXVQGlpKXx8fLopVM+hq6sLDQ0NRWCS+ykvL4eqqir09PS6uJKinfs1bWxkDBN1k8eup5kMpqIxp6amBiaTiYaGBsXaH319fVRUVHRbx9Dp9C41265LPp8PLS0tMJlMaGlpQSwWd+kItbS0oLGxsUvnPz8/Hw+OGL0OeHl5oaCgoMu1goWFha/k+/gKkFFXV0fr7nveVcdR+zljY+Muv/MAkJeXB0NDww7HmpubUVdXh+bmZqiqqsLIyAj5+fldXl9QUABDQ0MUFRXBz68t2jyNRoOTk1OX96yvr0dTUxMsLS07HHdxcekyvZeHFwg+8cj3lpnAhJWOFRZ+tbCbRC8XG5u2IGtdrfEtKCiAs7NzD1j1cnF0dBQcPHjwl3379g1s32LiSdHT06szNTX9cty4cR/NmTNnB5vNlm7YsCHRxMSkwtLS8is2m73kww8/nCAUCjt43mvXrj0nl8sJNpu9eNq0adMXLly4RUdHR3rPrlw1NbUmLpcrGTNmTG5zc7POgAEDuhyt1NHRqfzzzz/D9PT0lra0tKitWbPmvK2trTAkJOSinZ3dksDAwI/NzMzuAoBIJKJNnjz5XTabvdjS0nJhv379ztja2gp37dr1r1Qqpevr6y/W09P7+rvvvhv6NM9i4cKFGaGhoVc9PT0/Z7PZi2NiYmZUVlZ22lrCy8srbf/+/fZd5XE/P/300+YffvhhFIfDWVxYWGiyYcOGf7pK19Vv8Nlnn507f/58IIfDWZSfn2/AYDBaASAmJqaMRqPJORzOopiYmD5Tp07NrqysNOJyuYvmzJnj8yTPwtvbu4nD4VT07ds3+f7jycnJDn379k179BP7D6Irh+qxLiQIDgAJSZJ8giBUAJwE8D1Jkl0+LACws7MjW8QtKOeWA9Ho2JN1r5GhfVcbg/oPwuHDh7FhwwasXbsWjY2NqK2thb6+PiIiIrBu3Tr4+voiNTUVjo6O6NWrl2KELy8vD/v27QMATJ06FRwOBwAgkUhw+PBhMBgMsNlsXLx4EZ9++ikYDAaOHj2K5uZmjBo1StForq2txdatWxUBENavX48RI0bAxsYGQFvvXlJSEiorK3H79u0uRxhfB8aMGYO8vDxER0crevWrq6sRFxeHgwcPIjQ09Hnfsrv+y9cOR0dH8vDhwx2O8fl8DB4xGNXG1Z17a0mAiCegW6yLdye8i+vXr+PSpUsICwvD6dOnMW7cOFhaWuL69eu4du0aJkyYoHD+hEIhdu7cCR6P12GNi1gsxu7du+Hh4YGvvvoK/fv3R3h4OFxcXEAQBEiSxPXr13H27Fmoqalh0qRJHfLct28foqKi8OGHH6KxsREDBgxAREQEnJ2dFdffuHEDKSkpyM/P7zRt+lVg9erV+PXXXzF69GjFyGpLSwv27t2L2bNnY/78+S/y9m+MnoE2TW/duhXDxwxHOefh9XRoQChOnToFJpOJCRMmQE9PD8nJybhy5QrYbDZiYmKgrKyM/fv3Qy6XY/jw4R3qmG3btkEsFkNLS6uTLuPi4mBiYoKcnBz4+/vDx8cHJEli79694PP5mDRpElistm98U1MTtmzZAqFQCBMTE4waNUrRIVhfX48dO3Zg48aNHdbPvi6Eh4dDLBajT58+Cse7tLQUe/fuxcWLF1+Eo/va65nFYm0xNzePGT16tMr93/P2KJ4RERFwc3NT1G8pKSk4f/48Zs6cid9//x3BwcEdpmVmZGTg4MGDmDx5siKSp1gsxv79+6GiooLCwkI4OjqiT58++O233xAaGgpvb29F/unp6Thx4gSio6Nx6tQp3L59W7EWcceOHfjss88wduxYxcifSCTCwYMHMXToUHz//fcdynbo0CHMnDkTY8eO7fANOHz4MAICAnDq/CkU6xZ3++2xE9i9cltQzJ07FydOnMCwYcMU3xc+n4+4uDhFvf6MdNJ0VlbWtw4ODoqeqJ7cdoKiZ7hy5YrW2LFjpxQWFv7c07Y8C5WVlUoODg6Lb9y48Z21tbUQAOrr6xnOzs6f5OXl/e/BrSmysrLMHBwcuuwRehaH0A3AVgB0tI007iFJ8puHXdPe2Bg0YhBqjGr+a2yQAI4BylnKMNU3RXV1NZYuXYro6Gg0Nzdjzpw5SE1NBY1Gg1gshpGREcrLy0Gn0xWVrqmpKerq6lBfXw+ZTKZw0MzMzMBgMFBYWAg1NTVIJBLI5XLFtCZDQ0NUVlaioaEBMpkMZmZmEIlEKCsrg1wuh6GhIfT19ZGTkwOJRAJjY2Po6emhuLgYhoaGOHLkiKJyfx1pbm5GbGwsEhMTYWNjA6FQiOLiYvzyyy+YMmXKi7jla9/gaKcrhxBo+5hFDYlqizL6gMYZdxhwsXNBeXk5OBwOBg4ciD/++APKyspoaGgAh8OBrq4u8vLyIJPJYG5uDgaDoegVlkqloNPpMDMzA5PJREFBATw9PbFp0yYoKSkhMzMT77//Puh0OvT19VFeXg6JRIKmpiZoamqivr4eZmZmUFJSQnFxMYYOHYqFCxcqGpv3X29oaKgYZTt69Cjs7Oxe3sN9AkiSxGeffYZ169bBxsYGBEEgNzcX06dPx48//tjldMXnyBujZ+A/TSs6NoyqO2r4OKCcqQyuNhdisRhr1qxBRkYGfvjhB5iZmUFZWRmZmZmKaaRWVlYQCoWorKwEQRCwtLSEQCBAeXk5ZDIZVFVVoaWlhaqqKpibm4NOp+Pu3bvQ0tJCU1MTWCyWYvSlqqoKcrkc9vb2SExMhIWFBeRyOYqKiqCkpAQ/Pz9cunQJJEl2uO/y5csxd+7cnnysT01dXR2GDx+OO3fuwMrKCk1NTaiqqsLmzZsxdOhTdaA/itdezwRBsJSVlXeTJBlpbW3NotPpKCoqwsqVK9GrVy8MGTJEsQVVYWEhhEIhbGxsUFdXByaTiaqqKjCZTJiYmKCmpgZNTU2QSqUgCAImJiZQUlLC3bt3oaKigqamJtBoNLi4uIAkSeTk5EBVVRXKysrQ0dFBRUWFYgsUiUSCvXv3dlozu3z5cixfvhw2Njag0+nIyclBTEwM1q9fr+hAuZ+ff/4ZixYtgqWlJZSUlJCbm4tBgwZh8+bNaG5uhouXCyq4FR3eWyKegE2TDS5fvPxKOYNAW2f9tGnTcPDgQdjZ2UEikaCgoACLFy/Gp59++jxu8UiHkOLtZO7cud4fffTRnZ7Yi/B5sHz5coeVK1e+ExUVlfD333+fbj/+zz//cDMzM7U//fTTTlN8X4hD+DTc39gYM2EMStmlkPaXgnGKAf0KfUweNxkGBgbo1atXp6kd7SHKGxoaoKqqCjabDTU1NZSWliqme5aVlaG1tRVmZmaIiIgAl8vFhQsX0NDQgNzcXAgEAnh7e2PkyJEAgGvXrqG4uBgmJibw9/dHSUkJLl++jLt378LY2Bhubm6orq4Gn8+Hs7Mz2Gw2+Hw+Kisr4ezsDH9//xfd2HxpZGVl4dKlS1BXV0dUVFSX63qeE2/GA0P3DiHQ5hTGjI9BKacUsv4yME4xYMIzwUczP4JQKISdnR1cXV1BEARaWlpw4cIF1NbWIjs7GxKJBCEhIQgKCsLu3bsV00r19fWhpqaGzMxMVFRUQF9fHx9++GGnaUVyuRyXL19GWVkZzM3NFdtHXLhwQTEVT0dHB4GBgV3udSWTyZCQkABVVVXY2NggNDT0tdB5ZWUlTp06BQDo169ft/t4PWde/QfzBNyv6a7qaU4ZB+9OeBeWlpYICgpSdCQ0NzfjwoULEAqF8Pb2hpqaGo4ePaqY9hUdHQ0ej4cjR44gNTUVpqammDJlCmpqalBcXAxNTU2IRCLFmiEdHR2EhIRAW1sbV69eRUlJiaKeptFoqKiowJ49e1BTU4OAgAAMGDAATCYT2dnZyMrKQl5eHnx8fDB69Ohu13W9Tty6dQs3b96Erq4uIiMjFaOjL4A3Rs8EQdgYGRnlrlq1ClFRUYr11XK5HGfPnsXdu3dhYWEBsViMiooK2NnZITg4GCRJYu3atTh8+DAaGxvh7++PCRMmwM7ODsePH8ft27eRl5cHLpeL+fPnQ1lZGQkJCaDRaOjfvz84HA7Onz+PvLw8CAQCqKiowNjYGP369ety2j7Q5vjHx8dDIpEgPDy8UyChB+Hz+YiPj4dIJELv3r07fAPq6uoQGBqIAq0CSPtJ26aJNlq9ciODD3L37l2cO3cOysrKiIyMfJ6R2ymHkILiHq+cQwj8F5GxtLkUJuomiNsW98p/uOvr67uMcEfxRLwxDY6HOYTA66nxdiitPzZvjJ6Bzpp+3TRM6faZeaP07OLiQqanp/e0GS+duro6BIUFoaC+AFY6r74z+IKhHEIKins8zCHssYVv2traiNsWh/H9x7/yjQwKiqeB0jjF6w6lYQqK1w9dXV0kn0vG7JjZb7sz2B1ykiTfqM4PCopHcU/z8u7OP/XG9M8DbW1tfPnFlz1pAgXFC4XSOMXrDqVhCorXD11dXaz6aVVPm/FKIpVKC2pray319PTKCYJ4edPkKCh6CJIkidraWiOpVNp1KGX0sENIQUFBQUFBQUFB8bJobW3dW1lZOZrH41mhB2fKUVC8RORSqbSgtbV1b3cJ3mqHkM/nY+26tZg1cxY1FYrijYfSO8XrCqVdiudJXV0dvv3uWyz8aiE1nfItxNvbuwXAlp62g4LiVeKt7RlpD5aw8+ROjJ00VhHdjoLiTYTSO8XrCqVdiudJe8CVNXvWICgsCHV1dT1tEgUFBUWP89qNEMrlchw8eBBbtmxBQ0MD9PX18fHHH8PQ0BDbt2/HtWvXIJFIwOVyoaGhgZycHDQ2NkImk0Emk0FHRwehoaH49+S/aLZtBsYChccKERwWjOGDhmPWrFm4efMmTpw4AblcDk9PT9y5cwc3btyAUCiEtrY2Ro8ejXnz5ik2qaWgeFGUl5cjLi4Ot2/fRlNTEwiCgEwmA4PBgKWlJQYNGgQej4f4+HgUFhaiubkZUqkUIpEIdDodJEnCwsICeUV5kLpIgbFA0YkiRA+NhrOdM5SVlTFgwAAMGDAABQUFWLVqFTIyMiASiaCvr49Bgwbho48+6rS1BQXFo2hubsbOnTtx5MgRNDc3w9TUFDExMSgsLER6ejr09PQwbNgw5OTkYPfu3aivr4dEIlHsN6usrAwmkwm+gK/QbuGxQgSHB2Pe7Hl45513cO7cOfzzzz+oqKhATU0NmpubAQCWlpZYuHAhhg0bptgag+LtgCAIJQBz6HT6J0wmE4aGhpgwYQIWLlyIxsZGuPu6o968HhgBZB/PhomVCSaPm4yWlhZkZ2eDz+ejpaUFQqEQEokEmpqacHd3x4wZMyAUCrFnzx6IRCJER0dj4sSJ0NDQgFQqxeHDh7F7926IRCJERkbinXfegYaGBoC2bbPWrVuHjIwMWFhYYObMmXB3dwefz8eWLVtw6tQpqKmpYcKECeByudi0aRNKS0vh7u6OmTNnwsLCokef6f3cvHkT69evR1FREVxdXTFr1ixYWVn1tFkUFBTPyDNvO0EQBB3AdQBlJEkOeljaR4XpfxQSiQQTJkxAcXExgoKCwGKxkJGRgdzcXBAEASaTCWNjY7i6uqKpqQnnz5+HkZERvLy8IJFIcO3aNfB4PMjpcshcZR02bqWdoIGRzgDEUOxBSKfTcePGDfB4PPTp0wdCoRCXLl2CWCyGkpISjh49irCwsKcuz1vKGxPZ61n1/CgSExMxd+5cODk5wczMDLW1tbh69Sr09fVRW1sLNTU18Hg8cLlcMJlM8Hg8+Pv7Q1tbG7m5ucjIyIBMJgNdhQ6JswTyAfIOG4yr56kjNCAUOTk5EAgEqKurg4+PD4yNjVFWVoYbN27A0NAQPB4PO3bswODBg19YWV9j3hg9A89P0xUVFYiJiVE0piUSCa5evYq6ujq4uLjAxsYGPB4PycnJ0NbWhr+/P+h0OlJTU8Hj8cBms1FZWQkxxJA4STptso0UQF1ZHdra2lBRUUFhYSGsra3h4uICkUiEy5cvQyAQICAgAMePH4eSktIzl+kt4bXWM0EQGnQ6/Q6dTjfV1taGn58fWCwWUlNTUVlZiWZxM0h3EojCf3XhMYBIJRDsFww1NTVFu6GyshJWVlZwdHSEQCDApUuXIJVK0bt3bygpKSEnJwcNDQ1ISEjA9OnTFQ4Sk8lEbm4u6uvrkZiYiEuXLmHGjBlwd3eHgYEBeDweUlJSMHPmTGzZsgUGBgawtraGSCRCUlISxGIxAgMDoauri7KyMqSnp2Pnzp0YOHBgDz9dYMWKFfjhhx/g5eUFNpuN8vJypKamYsuWLRg+fHhPm9cdr7WmKSheFs/DIZwHwAeA5ot2CDdu3Ijdu3dj8uTJYDD+G9y8cuUKLl68CB8fH4WDFhcXBy6Xi4iICEW6lpYW/PLHLxA7if9rYLRzr6HBvMPEnPfnQFVVVXHq5MmTaGxsxKhRoyAQCLB+/XpIpVKwWCyUl5dTjY0n442pnF+kQygSiRAaGooRI0bA3NxccbylpQUbNmzAoEGDcOjQIdjb28PGxgZnzpzB1KlTO2xYffv2bRz89yBonjTIBsg66Z1+kg7tu9oYNWQUNm/ejBkzZkBPT0+RhMfjYdOmTRg2bBj+/fdflJSUKDZ3plDwxugZeH6afvfdd8FgMBAeHq44JpfL8ffff8PQ0BBhYWE4deoUGhoaMGLECNBo/61eSEhIQE1NDUoqSyCwF/zXeG+HBOgn6JCnyDGw30CcOnUKvXv3RlBQkCKJTCbDtm3b0NLSgvnz5+OLL7545jK9JbzWemYwGFsBTLKwsMC4ceMUo8MCgQBr/lwDgV33etIu0gZdRoe/vz+uX78OHx8feHt7K5JJpVJs27YNbm5u8PHxAQBcuHABxcXFYLFYnXScmJgIsViMlJQUTJgwAfr6+opzfD4f69evR+/evREQEAAAKC0txZ49ezB9+nSoq6sr0paUlGDv3r0oKyvrcPxlk5KSgj59+mDKlCkdvgPl5eXYvXs3iouLX9X1va+1pikoXhbPtIaQIAgTAAMBbHw+5jycHTt2oG/fvh2cQQBwdHREa2urokHQ0tKCu3fvIiQkRJFGIBDgrx1/Qeoq7ewMou1vMpKE1EWKTds3QSAQKE716tULubm5EIlEUFVVRXBwMAiCgKqqKo4dO/aiikvxFnP69GkYGhp2cAYBQE1NDQEBAbh9+zbEYjHCwsKQkpKC4ODgDs6gQCDA+UvnQbqTnZ1BACAAWX8Z+BZ8bIvbBhcXlw7OIACw2Wy4uLigqqoK5ubm2Ldv34sqLsUbRHV1NVJSUjrUvwBAo9EQHh6OlJQUkCSJlJQUhIeHd2hEA4C3tzeyC7PR6tjaufGOtr9lA2SAB3As4RgIgui0GT2dTkffvn0hEomwfv36519IilcOgiBoAMayWCyEh4d3cAY3bd+EVoeH66nevB68Bh50dHQgFArh6enZIRmDwUBoaChSUlIUxwICAlBcXIzg4OBOOvb398e1a9dgYWHRwRkE2josAMDX11dxLCUlBX5+fp2cPlNTU5ibm2P//v1P8VSeHxs2bICnp2enTkEjIyNYW1tjz549PWQZBQXF8+BZg8r8DOAzPGSjQ4IgphMEcZ0giOvPGgygoaGhU6MVAIRCIdTU1BQjdS0tLVBXV+8wcnch8QLqUf/ftLkujQXkA+SoRz0uJF5QHFZRUYGKiorCSWSz2aDT6YoRQoq3h+ep54dRXV3dbfQ7NpuNxsZG0Ol0aGhooKmpCWw2u0Oadr132QBq555TKGKJUMfvOrACm81GU1MTtLW1UVFR8QwlonhVed6a5vF40NDQAJPJ7HSuXU9yuRxCobBLjV+5dgXQRtcdGQqj2zrw5Jpy0Bi0LtcJstlstLa2orq6+hlLRPGawKLRaEyxWNyhndBeFz5KT/IBcsi15bh67Sr09PQ6OXjAf/ptR0lJCVKptFP9CwBMJhOampodOuraaWpqgo6OTgfddlWPt/Mq1L8lJSXdfpM0NTV73D4KCopn46kdQoIgBgGoJknyxsPSkST5J0mSPiRJ+jzrdAIjIyOUlJR0Oq6qqorm5mZFQAEtLS00Nzd3qLhDQ0KhAx3QTtDa1g10aWzbWkId6CA0JFRxmM/no7W1VbFAvLi4GGKxGI2NjXB0dHymMlG8XjxPPT8Ma2trlJaWdnmuuLgYXC4XJEmipqYGHA6n03vRrnccx0P1Tj9Jh2qrKpSZyt3ei8PhoKKigtL6G8rz1rSJiQkaGxvR0tLS6Vy7nuh0OrS1tVFWVtYpjae7Jwg+8ci6mognwGhiQCwSQyQSdXkvVVVV2NraPmuRKF4PhHK5vEVFRaVDfdheF9JP0B/57SfqCQQHBaOiogISiaRTsuLi4g5OW3NzM5SUlLpslwgEAjQ0NKCxsbHTOT09PfB4PLS2tiqOsdnsLvMB2qZl9nT96+rq2q3TV1VV1eP2UVBQPBvPMkIYDGAIQRB3AcQBiCAIYsdzsaobZs+ejRMnTigcP6BtXcrZs2ehpqaG+Ph4yGQyKCsrw9XVVfE30OY0ToiZACKVAI6h84fhXgODlkrDxDETFWsIpVIpjh8/Dk9PTzCZTFRVVeHy5ctgsVjQ0dGhgspQvBCCg4NBkiRu3OjY31JZWYnr16/Dzs4OBEHg33//hZeXF5KSklBbW6tIp6KiAicbJ9BSaV03hO5bQzhx7EQUFBQgLy+vQ5Lc3FwUFhaCIAgIhUIqqAzFY6GpqYmoqCgcO3ZMUf8CbTM54uPjFdM7/f39cfz48Q7OnFQqxblz5+Dl6gVmOhOIR5fapZ2ggUwhMWzgMDAYDEVU6HZaWloQHx8PgiDw6aefvsjiUrwikCRJyuXyH1paWnDy5ElFh4SqqirenfAu6On0br/9tBM06BTpwMrUCnfu3IGJiQlOnz6N+2MsNDY24uzZswr9ymQynD59Gj4+Pjh37lyHZSYymQwJCQkYOXIk6uvrkZGR0eGWdXV1oNPpOH36tEK3Pj4+uHnzZqdZR7du3UJra2uPB5WZOXMm0tPTOzmtaWlpaGxsxLBhw3rGMAoKiufCMweVAQCCIMIAfPKig8oAwLJly/D333/D0dER6urqyMjIgFAoBIPBAIPBgFwuh7OzM4RCITIzM8FgMODm5gaJRIL09HSQJAkxxIA7OkWuI1IJqDHVAADOzs4gCAKpqakgCALu7u6oq6tDXl4eaDQaDAwMcPbsWSrc8pPzxizwftFRRgsLCzF16lQoKSnB2NgY1dXVKCwshL6+Pqqrq8HlcsHj8cBgMMDhcFBaWgobGxvo6uoiOzsbIpEIYrEYMpoMcnc5yEiyQ2Q9VjYLLnYuyM3NhYeHB65evQoOhwNTU1OUlpaisrISmpqaYDKZOHnyJJydnV9YWV9j3hg9A89P0wKBANOnT0dmZiZcXFwgFotx584dyOVycDgcWFtbo7GxEVlZWQDa6lsmk4k7d+6AxWJBJBKByWSiQdAAuZu8Q12N4wBSAHsre5SVlcHAwEAR2KO97r9z5w5oNBo+/vhjrFy5EgTxRv1ML5LX+kERBEGj0Wj/0Gi0KBqNBicnJ6ioqCAtLQ1mZmbIK86D2FHcUU/HANwCLE0sweFwkJ6eDjqdDjqdDoIg4OjoiKamJuTk5IBGo8Hd3R10Oh25ublwc3PDwYMHsXjxYmzatAmOjo6KKKMuLi44fPgwsrOzER0dDR0dHXC5XNTX16OkpARbtmzBDz/8gIKCAlhbW0MsFuP27dsAAAcHB8U0TKFQiBMnTsDJyannHuw9jh07htjYWFhYWEBbWxuVlZVoamrCiRMn4Orq2tPmdcdrrWkKipfFa+cQAm1z2deuXYvy8nI4OTlhxowZYLFYOHnyJK5du4aGhgbY29tDT08Pt27d6uA0WllZYeTIkVj87WLUGNe0NZKPA2o5aliyYAkGDRqEoqIinDlzBnK5HIGBgcjPz8eRI0dQVVUFX19fjBkzBoMGDaL2t3o63pjK+UU7hMB/Iybt+2OpqKigqakJampqMDQ0RFRUFGpra3H27FkUFhaitLQUEokE5eXlEAqF0NfXx8CBA7Fhywa02LUAUQDjJAP6FfoYGj0UampqiIiIgJWVFUQiEXbv3o3z58+Dz+cjKCgIUVFRGDJkSJfrwSgAvEF6Bp6/pm/duoW4uDjweDx4eHhgzJgxSEtLQ1ZWFnR1dREZGQkej4c///wTJSUlkEqloNFo4PP50NTUhLa2Nm5l3EKTddN/dXWuGrZtbAuEVF5erogCXf5/9s47vqr6/v/Pc2d2bvbeOySEDbJENsiSDSJinVi0auv3p622trW11tbW0TpRlgqiIqjsPRIIMxASQiCBELLHzV733s/vj5gjlyTICATS83w87iNwzrmf8znnvs77fN6f8X7n5ZGeno5er2fcuHE88cQTrYIyKfwsXULPkiR1B/6k0+kmDxs2jBdeeIFhw4ZRXl5Oj749yPXIRYwVqDapcD3vyntvv0dFRQVnzpyhuLiYuro6zp07h8lkwtvbm7vvvpvZs2dTX1/PmjVraGhoYOTIkfTr108+Z3Z2NmvWrKG+vp4RI0bQr18/uSOioaGBb7/9ltOnTxMYGMj06dOxt7dHCMG+ffvYvXs3dnZ2TJs2DWdnZ1avXk1eXh7dunVj4sSJt5X9raqq4quvvuLixYtER0czadKk2z3SepfQtILCzaZDHMKr5VY0oK8Wo9HI7Pmzya3Oxd/Bn5XLVv5syOTy8vJW0ewUrpkuY5xvJz3/HNeqd0XrV02X0TPcnpq+Fu0qur1hupSe4+LiRGpqqtW2srIyBg4bSFZ5FqEuoSTuTGw3WIpCl6BLaVpB4WZxo1FG71gMBgMrl63k/tH3X5UzqKBwJ6PoXeFORdGuQkfi6upK4s5EFs1cpDiDCgoKCj+i+flDui4Gg4EXX3ixs6uhoHBLUPSucKeiaFehI3F1deXNf77Z2dVQUFBQuG34nx0hVFBQUFBQUFBQUFBQ+F9HcQgVFBQUFBQUFBQUFBT+R+lSDqHRaOS1v72G0Wjs7KooKFwXioYVujKKvhW6ImVlZTz36+coKyvr7KooKCgoXBd3xBrCyspK1q5dy/79+yktLcXf35+EhARKS0spLS3Fz8+Pffv2cej4ISxOFr5e9zUzp8wkLS2N2tpa1Go1lZWVcpJZIQRqtRofHx/Cw8OZPHky0dHRVudsaGjgv//9Lzt27ECtVjNt2jTGjh0r78/IyGDZsmWUlJTQr18/5syZIyez72jMZjPr169nw4YNaLVapk+fzuDBg5XcWl0IIQRLly7ln+/8k0b7RlasWoGfhx8+Pj48/vjj3HXXXRiNRt566y127NhBZWUlarUanU6HVqulsbERtVqNn58fd999N9OmTcPLy6vVeaqrq/nuu+9IS0vD2dkZW1tbCgoKcHd357777iMwMNDq+Mt1Pnv2bOzt7W/afSgvL2f58uWcOHGCgIAAFixY0KpOCrcfQgiSk5PZsmUL1dXVWCwWzGYz1dXVGAwGgoKCaGxs1nWNrobVa1Zjr2vWUUREBFFRUVRVVZGbm0tqaipmsxlXV1defvllunXrxrfffktOTg6BgYHcd999uLu7y+c9cOAAW7duxWKxkJCQQFZWFrt27aK2thZJkrC1tWXIkCFMnz4dvV5/U+9DWVkZS5cuJS0tjaCgIBYsWIC/v/9NPadC+zQ0NPDyyy9TWFhIr169mD17Nrt27WLTpk2o1Wrc3NzkZOsBAQGMHTuWsrIy1q5dS0FBAXZ2dvTp0weDwcCuXbvk/K/jxo1j4cKFXLx4kbfffpuvv/uaRrtGPv/yc5L3Nedz/fLLL0lMTMTFxYV58+YRFxfXZh2LiopYunQpp0+fJjw8nAULFsi2Oz8/nyVLlpCVlUV0dDQPPvigrH2A06dPs2zZMoqKiujTpw9z587FwcHhltzbFjIzM1m2bBkFBQX06dOH+++//5bXQUFB4ca5obQTkiSdA6oAM2ASQvS50vHXE9L86NGjPPHEE/j4+BAcHExJSQkpKSlYLBZ69uyJo6MjSUlJNNKIpfuPybfXg+qEimEDh3H69GkKCwuJiYkhNzcXtVpNjx49MJlMHD58GK1Wi9lsZuLEifzud79DkiTOnTvHtGnT0Gg09OrVC7VazdGjR5EkidOnT/P222/zr3/9i/j4eBwcHLhw4QIlJSVs27atw5PHGo1GRo4cSWlpKREREZjNZtLT0+nbty9fffXVbZWf6CrpMl5sR4Xor6+vZ9y4ceSX5ENP5HxrUopEz249ycjIICQkhMzMTEJCQggJCaGwsJCTJ08SEBDAhQsXsFgsREREEBQURH5+PpmZmfz5z3/m3nvvlc9z8uRJHn74Yfz9/fH396e0tJSUlBTCwsIwGAycOHGCRYsWsWDBAsrLy9m0aZOVznNzcykuLr4pOgfYu3cvkyZNIiQkBC8vL4xGI6mpqfzrX//i4Ycf7vDzdRBdRs9wfZpubGxk0aJFnD59mtjYWFQqFQcOHKCuro5u3brh6+tLVlYWp7JOQQ9gHLAebDNsuavPXZw5c4b8/Hy0Wi0WiwVXV1fi4uJoaGjg0KFDmEwm4uLi8PLyoqioiFOnTvH3v/+dIUOG8Mtf/pLMzExiY2NpbGzk4MGDuLm5odVqKS4upkePHjg6OnLu3Dnq6+vZuXPnTctNuHPnTu677z7CwsLw9PTEaDRy8uRJ3n33XR544IGbcs6bQJfRs1ar/T+1Wv163759cXR05OLFi2RkZODu7k5YWBhHjhxBpVJhNpvp2bMnDg4OHDlyhPLycoKDgwkPD5dtpNlsRpIkIiMjCQwMJD8/n1OnTqHVajGpTNRH1//U9jiuwt3ZHXd3dwIDA6mtreXEiRM88sgjvP7661YduT/88ANz584lKioKDw8PSkpKOHXqFEuWLKGpqYlHH32UmJgYXF1dKS4uJjMzky+//JLRo0fz2muv8frrrxMfHy9fX2FhIVu2bLllSeLfeOMNXn31Vbp37y7XoaCggM2bN5OQkHBL6nAVdBlNKyjcTDrCIewjhCi5muOvtbHR0NDAsGHDGDt2LJGRkfL2srIyPv74Yx588EE2b95MXnEejbGNmMeYmx99AWxobnDQCL/4xS/Yt28farWaCRMmyAbZZDKxYsUK/P39yc7O5je/+Q3jx49n2LBh2NnZMWfOHDSa5kFUi8XC2rVrkSSJvLw85s+fb9ULduzYMVJTUzl9+nSHjtzNmzePM2fOMHbsWKt6f/XVV9x///289NJLHXauW0SXMc4d5RA+9thj7Nm/B6mnZKVhaaOE+riax3/xOB988AFz584lNDRU/l5xcTGffPIJQghmz55NcHCwvK+wsJAVK1bw7bff4u/vj8lk4p577mHYsGFWzpzRaGTx4sXMmjULBwcHlixZwkcffURBQQF//vOfb5nO6+rq8Pf3Z/z48YSHh8vbS0tLWbZsGUlJScTExHTY+TqQLqNnuD5Nt4xaT58+XZ6N8d577zF//nx8fHyora1l8fLFlAeVYxljkfWt3qzGcM7Aww88TEpKCjt27KBnz55Wtq6pqYklS5YQHx/PgAEDALh48SJffPEF06ZN4+DBg0ybNg21Ws3y5cvx9/fHw8ODPXv2sGDBAmxtbeV6JiYmUlFRwf79+zvsfrVQVVVFYGAgkydPJiQkRN5eXFzMihUrOHz4MGFhYR1+3ptAl9CzJEl32drabn3iiSfsnJ2d5e0nTpxg27ZtuLi4YGdnR3FxMQ899BC2trZYLBbeeecdhg8fbuVQteh52LBhco7LAwcOkJKSQr2lnoqQCsyjL2l7rAf7THt++dgv5VlDtbW1rFixgvfee49JkyYBUFJSQlhYGDNnzrQaRc7Ly+OLL75ACMG8efPw9vaW9+Xk5PD111/z2WefsWDBAubPn4+Tk5O8PyUlhaNHj3L27FlUqpu7Imjfvn1MmTKlVR1OnDhBcnIy2dnZqNXqm1qHq6RLaFpB4WZzW68h3LZtGx4eHlbOIDSHjO7Xrx979uwh60KWtTMIzX/HQV1kHWhBo9GQnp7OiBEjrBqxGo2GsWPHcvToUQYNGsSyZcvIzMykpKSEMWPGyM4ggEqlYvTo0aSmptKrV69WUyISEhJoaGhg9+7dHXb9RqORb7/9lrvvvrtVvYcNG8Z//vOfDjuXQudQWlrK7qTd0JNWGhZjBaY4E5+s+ARfX18rZxDAw8MDHx8fgoKCrJxBAC8vL+Lj41m9ejUAu3fvxsHBodXInsFgYMCAARw+fBiDwUDfvn357LPPWL16Nf369bslOgf4+uuv5Sncl+Lm5kbPnj157733OvR8Ch2DEIIvvviC4cOHy42/Y8eO0a1bNytn0Bhs/MkZBJDAPNqMMdjI4uWL6d69OzqdjpiYGCtbp9VqGTNmDIcOHZK3+fn5ERUVxerVq7nnnntQq9WUlZVRUFDAkCFDOHjwIHfffbeVMwjQv39/zpw5Q1paWoffhy+//JLAwEArZxCan9Hu3bvzwQcfdPg5FdpHr9c/N3ToUJtLnUGA+Ph47OzsyMvLo7q6mmHDhsk6OXv2LHZ2dq1G15ycnBgyZAgXL16UtyUnJ1PdWG3tDELz3/FQH13P4uWLqa2tBcDOzo4BAwbw73//Wy5j2bJlREZGtppS7OvrS0REBK6urlbOIEBgYCChoaH8/ve/p1+/flaOGED37t0RQrB9+/ZrvWXXzLvvvkufPn1a1SE+Ph6NRsOWLVtueh0UFBQ6jht1CAWwWZKkw5IkPdYRFbqUCxcu4OHh0eY+FxcXTmWdQvQQ1g3pFn40zA2xDSz9Yim2trZtrvHz8vKitrYWT09PLl68SHZ2NmazGU9Pz1bH2tvbo9frWxlAAEmS8PLyIjs7+3outU3y8/NxdnZut96FhYWYTKYOO5/CrcVoNDLnwTmIBGHdWG7hRw3XRdVRXFEsNy4uRaPRtLtGydPTk/PnzwOQm5vbpqYBvL29KS8vB8DHx4ecnBzy8vLw8fFpdawkSXh7e5OVlXX1F3oVZGdn4+bm1uY+T09PMjMzO/R8Ch1DfX091dXVVna6vLy8lTNo1Whu4RKn8JMVn+Du7k5NTU2rc1yqzxbc3NxobGyUz2s0GvHw8ECj0WA0GtvUbsu68Y7WLkBWVla7+vXw8FD0e4tRqVSRPj4+bbZvvL29cXBwoKKiwsrhMhqNrRywFnx9feVASLW1tZRWlVITXtO+rsf81NnRYrd9fHys2gdnzpyxWg94KT4+Pu2O8Lm7u5Ofn99mXVvaITdD45dz5syZdu+Xp6dnh7aFFBQUbj436hAOFkL0onlVyC8lSRp6+QGSJD0mSdIhSZIOXWtkuYCAAIqLi9vcd/DQQUyOpuYztzchQALLGAuV6koqqyvbbFAXFhZiZ2dHUVERfn5+hISEoFarKSoqanVsTU0NDQ0NVFZWttonhKCgoKBVD/GN4OvrS0VFRbv19vLyshrFVLj53IieL+e999/jYu1FGM8VNcw4qLOpY/fe1qNyJpOJ3NzcNr9aVFQkr5fy9/dvU9MABQUFuLi4AM2dEIGBgfj6+pKfn9/qWCEE+fn5rUYrb5SQkBBKS0vb3FdUVERERESHnk/hJ25E0zY2Njg4OFjZaRcXF/Lz89m9dzfllLfdaJZP3uwUllNO7sXcNgMWXarPFkpLS9HpdPJ5DQYDxcXFmEwmDAZDm9o1m803RbsAoaGh7eq3uLhY0e8tRJKkx0wmU0BeXl6b+wsKCqiursbZ2ZmCggJ5u8FgsPr/peTl5WEwGACa7bCBtjui5Ur8pOsWu52fn2/VPggPD6ekpO3VNvn5+Vgsljb3lZSU4OPj02ZdhRAUFhbeFI1fTnh4eLv3q6ioqEPbQgoKCjefG3IIhRAXf/xbBKwB+rVxzIdCiD5CiD4tBvVqGTFiBMXFxZw+fdpqe1lZGaUlpRgsBthA8zhlmxUE1oOT2YnY6Fi2bdvGpWsmTSYTGzdupGfPnuzbt4/58+cTERGBu7s7mzZtshp9s1gsbN68mbi4OI4cOUJ1dbXVqVJSUrC1tWXo0FY+8XXj7OzMlClT2LVrV6t679y5k1/+8pcddi6Fq+NG9Hw5C59YSIBDANJG6YoaVm9SQxkEBVgHwyguLiY/P5/z589z7tw5q32FhYWcOHGCGTNmADB06FCqq6tbTZczGo3s37+f3r17YzQaOXjwIPfffz8zZsxonhZ1C3QOMG3aNPLz8zlz5ozV9pKSEo4ePcrChQs79HwKP3EjmpYkiTlz5rB9+3bMZjMAPXr04OTJk0RFROGCC+rN6ivre7MamzobJCTS09OtbF1TUxObNm2iT5+f4pW1BAeZMWMGO3bskCOSent7s2fPHvr27cvOnTupq6uzOtWBAwcIDw+/KQGRZs6cSU5OTqtRkaKiIo4fP87jjz/e4edUaBshxIdNTU337tmzp7aiosJq34kTJ6itrcXX1xcHBwcrnYSFhckBYC6lsrKSPXv24OfnB8DQwUOxb7T/2baHerMaF1wYOngotbW17N+/n2eeeUY+ZP78+Zw+fbpVh15eXh6ZmZnyNOhLOX/+PFlZWfzpT38iOTm5Vef08ePHkSSJ4cOHX+Xdun4WLVrEoUOHWtXhxIkTmEwmRo0addProKCg0HFcd1AZSZLsAZUQourHf28B/iSE2Njed64nYMGxY8d4/PHH5SijxcXFHD9+HIvFQnx8PBlZGdRG1rYeZbkkKAdNEBsb2yrK6KFDh9DpdO1GGVWr1fTu3dsqymhmZiZvvfWWEmX0+ukyC7w7IqiM0Whk1rxZnHM513q0+0cNcwyiQqLIzs6Wo4wWFBSQlpZmFWU0PDyc4ODgK0YZfeSRR/Dz82szyujx48d56qmn2o0yejN1Dj9FGQ0ODsbb21uJMtoJ3EiU0YyMDGJjY1Gr1XKU0cjISM5dPEdNZE27+lafUEMj6HQ6LBYLLi4uxMfHt4oy6unpSXFx8VVFGdXpdBQWFsqRqG9llNHQ0FC8vLwoLy8nLS1NiTLaSWi12ufVavXfW9a5tXQkuLm5ER4efl1RRlsiOefk5JCWmYZIEG22PdgAupM6BvcfjMlkajfK6Pr165kzZw5RUVG4u7tTWlp63VFGc3NzKSoqUqKMtqbLaFpB4WZyIw5hKM2jgtCcz/BzIcRfrvSd621AV1VVsXbtWpKSkigtLSUgIIAePXrIIyS7knZhDDY2h33+MdKXapMKXZqOsIAwbGxsaOkpbLlelUqFr68v4eHhTJo0qc08hO+99x7bt29Ho9EwdepUxo4dy8CBAwHr/Gz9+/dn9uzZNzUP4YYNG1i/fj06nY7p06czaNCgOzUP4R1Z6bboqCijRqOR2fNnk+OaYx2tbgPYnLLhH3/9ByNHjqSiooJ///vf7Ny5k4qKCjkPoU6no6GhAbVajb+/P3fffTdTp069Yh7C9PR0nJ2dsbGxobCwEDc3N6s8hOXl5fTv3/+W5ttsuRfLli0jNTUVf39/HnroIQICAm7a+TqALqNnuH5NCyE4ePCgnIfQbDZjsViorq7G1taWpENJVIZWtooErT6upnf33sTHx1NZWcnFixc5ceKEPOr3+9//nm7durFmzRo5D+HUqVPl9Xot+Q+3bt2K2WwmISEBf3//Ts1DuGzZMtLS0ggMDOShhx6SR5buELqUniMiIsScOXNa5SHcuHEjarUad3d3UlNTycnJkfMQlpeXy3kIbW1t5TyEu3fvlpdqjB07ltmzZzNx6kQuuF+wip6r26YjuDyYXz35K1JSUnB1dWXevHl069atzToWFxezdOlSMjIyrjkPYWZmJkuXLqW4uJjevXtz//3339Q8sW1x5swZli5dSlFREb169bod8xB2KU0rKNwsbijtxLXSUQ3oy2lpUOe659I0sgntVi3+Jf6sXLaSG53WdyktjWSFG6LLGOeO1POt0vDVomj9qukyegbFRit0LT3HxcWJ1NTUm1Z+WVkZA4cNJNs5m8YRjei26QipCCFxZyKurq437bwK10SX0rSCws3itk47cbUYDAZWLluJf4k/2o87tyGtoHA9KBpW6Moo+lboiri6upK4M5GQihC0i7WKM6igoHDH0iUcQvipwXH/6PuVhobCHYmiYYWujKJvha5Ii1O4aOYixRlUUFC4Y+lSOQsMBgMvvvBiZ1dDQeG6UTSs0JVR9K3QFXF1deXNf77Z2dVQUFBQuG66zAihgoKCgoKCgoKCgoKCwrXR5RxCo9HIa397jRtNGq6gcCtQ9Krwv4Cic4WuSFlZGc/9+jnKyso6uyoKCgoKN8QdOWW0qqqK//znP6Snp+Pn58evfvUrXFxcWLFiBW+//zb1NvV8/uXnONs5Y29vL69V8fX15Ze//CXh4eEA1NbWsnnzZi5evEhQUBCjRo2Sw5I3NTWxc+dOEhMTKSkpISoqioEDB7Ybwa6yspLVq1ezd+9e6uvr6du3L3PmzMHHx+earq2xsZG1a9dy6tQp/P39mT59Oo6Ojtd/s24xFy5c4Ouvv6ampoahQ4cyePDgOzU9RocjhGD//v0cO3YMe3t7qqqq+GjJR9Tb1rNp2yY+/M+H/PDDD+zatYuKigo0Gg1BQUE4OzvLyX4jIyPp1asX99xzDxEREa3KP3r0KMnJyej1ekaPHm0V8r6kpIR///vfXLhwgfDwcJ5++mmcnZ07/DqPHDnCpk2b0Gg0TJ48mcjIyA4/R0chhGDv3r3s3r0be3t7pk2bdrunubjt2bp1KytXrgRg1qxZBAUF8eCjD2KUjGzcupGRd4/k6NGjlJeX4+TkRENDA2azmcDAQJ544gn69u0rl3WpjQ4ODmbkyJHo9XrKysrYuHEjRqOR8PBwampqyMvLw83NjYSEBGxsbNqs26X21c/Pj7CwMBITE9FqtUyZMkV+N7THnWzfhBDs2LGDpKQkHB0dmTFjxjW/n7oSLXZKpVLh6upKYWEhrq6uTJ8+nSNHjvDll19SXFxM3759MZlMrF+/nrq6OsaNG8cTTzzBV199xSt/fYUGuwaWrFjCl599ydGjRzGbzYwZM4aePXsCzW2D1157jYMHD+Lv78/LL79MWFjYFetWWFjI6tWrMRqN9OvXj5EjR6JSXV3/fVpaGt9//z0Wi4Xx48fTvXv3Vse0tFfy8vKIjY1l0qRJt2VO45b7npKSgqenJzNnzsTFxaWzq6Wg0CW5obQTkiQZgI+BOJozS/1CCJHU3vEdEdL8+++/57e//S3Ozs5ERERQVlZGZmYmkiTRRBP0oDlR7HqQjkv0ju+NxWIhLS0NZ2dnSktLGTt2LDNmzODpp5/G398fNzc3CgsLKS4u5oMPPsDe3p6HH36Y2tpaTCYT3bp1w2KxkJGRwaRJk1iyZAkazU++9A8//MDs2bORJAmdTkdUVBRVVVVkZWXxhz/8geeff/6qri0lJYWxY8fi7OyMl5cXRqOR8+fPs3LlSsaOHXtD9+1W8Morr/Dmm28SExODTqcjKyuLwMBA1q9ff6kRvzNaT1fBtei5tLSURx55hIqKCnx9fTlx4gQNlgboSXP+zPXAMbBR2+Di4kJoaCjFxcVkZWVha2tLY2MjarWabt26IYQgMzOToUOH8re//Q2NRkN1dTWPP/44OTk5RERE0NjYSHp6Ovfffz/PPvssH330EW+99RZhYWF4eHhw9uxZSktLeeWVV5g2bVqr+l5P+P76+npmzpxJUlISUVFR8nM3c+ZM3n///atu0NwqysvLGT9+PDk5OYSGhsr37LnnnuOVV1652mK6jJ7hxmx0XV0dEydOpLi4mPj4eFQqFSkpKdRb6pF6Sj/pPAW0QouHhweSJFFaWkpsbCxarZYTJ04QERHB8uXLOXLkCL/61a/w9/fH1dWVoqIiSkpKmDFjBsuXLycqKgqTySR3DAYEBFBUVERpaSnr1q3jrrvusqrf8ePHGTt2LE5OTri7u5OWlkZjYyMJCQlYLBbS09OZN28e77zzTptO3lXat9uS4uJixowZQ3FxMSEhIdTX15Oens7vf//7y99PXUrPbaWduNRORUZG0tDQwMmTJ3Fzc8PFxYXMzEwcHByIjo6mqKiIc+fO4eLiIrc3zpw5g8lkQmgE9ATGARuAYxDsG4yfnx8ZGRkMHDiQ2bNn84tf/AIbGxtiY2OpqakhLS2NX/ziF7z//vtt1vndd9/lxRdfJDo6GltbW86fP4+TkxObN2++ogNvNpv5xS9+wXfffUd0dDSSJHHq1CmGDx/O559/Ljt83333HfPmzSMkJARnZ2cKCgqoqalh06ZN7eZK7AzOnj3LqFGjUKlU+Pn5UVVVRWZmJh988AFz5869lqK6lKYVFG4WN+oQLgX2CCE+liRJB9gJIYztHX+jDmFJSQnDhw9nyJAhDB48WN6em5vLx8s+bnYGxyEniFVvUmM4b+DhBx5GpVKxfPlyYmJiSE5OprGxkVmzZhESEiKXc+rUKTZu3IitrS2Ojo5YLBZmzZolG9LGxkZWr17N/PnzeemllwA4f/48CQkJODk5ERAQwKhRo+TGREVFBStWrGDZsmU/69DV19cTEhLC4MGDiYuLk7fn5OTw9ddfy4m6b1e+/vprnnrqKauktBaLhc2bN+Pp6cklv3uXMc7XoucHH3wQrVbL8OHDefvtt6lqqEJ0F60Sddtn2vPLR38pJ38vKCjgk08+wcPDgwULFrTS4tixY1m0aBHPPPMMxcXFjB8/Xna8ampq+Oyzz5g1axb/+c9/+MUvfoG3t7dcp0OHDrF582a2bNlitR2uzyF8+umn2blzJ5MnT5Y7TBoaGli1ahVPPfUUzzzzzDWVd7OZPHkyRUVFjB49Wr5n1dXVfPbZZ7zzzjttOspt0GX0DDdmo+fNm0d+fj7z589Hp9NRW1vL4mWLKQ0stbLLrAeHMw7069mP06dPM2/ePHlEz2w2s3LlSiIjI9m9ezdTp061stH79u1jz549PPLII9jZ2fHuu+8ybdo0qxGX06dPs3HjRrKzs3FycgKadRgcHMygQYOIj4/nhx9+oLa2lqlTp6JWq4FmG7xy5Uqef/55nnzySatru5J98/Ly4ttvv72ue3arGDFiBE1NTQwfPtzq/fTZZ5+xbNkyxowZ03Jol9JzWw5he3ZqxYoV1NbWEhcXx7BhwxBC8P7779OrVy8GDBggfz8nJ4dPVnyCqpfKKiG9tFGCo/Dogkfx9PRk9erVnD9/nri4OCu7XF1dzUcffcR7773HnDlzrOrWovl58+bJnQxCCHbv3k19fT2JiYntXutf/vIXli5dyowZM9DpdEDzTKc1a9YwYcIEXn/9dbKzs+nZsyczZ860mj2SkpJCcnIy2dnZt8VIocViITo6moiICPr16ydvLyws5IsvvmDPnj1W7aSfoUtpWkHhZnHdXfaSJDkDQ4HFAEKIxis5gx3Bu+++i62tLYMGDZK31dbWsuaHNUg9pZ8aHTT/NY8xYww2snj5YiwWC6NHj+bYsWOMHTsWvV5v1dAAiI6OxsnJCZVKRW5uLuPGjbMyjjqdjpEjR/LWW29hNpsBeP/99wkLC6OsrMzqZQvg7OzMoEGD+Mc//vGz17ZmzRpcXFxaGbnAwEBiY2P58MMPr/Fu3Vr+8Y9/MGTIELmxBKBSqRg+fDg7duwgNze3E2vXuWRlZZGens7dd99Nbm4u5TXlWLpbfnIGofnvOKiPqmfx8sXU1tYC4O3tTb9+/XB3d2+lxVGjRrFixQoKCwvZvXt3q2lF9vb23H333Xz66af069evldPXp08fDAYDb75549HxamtrWbJkCSNHjrQaPdfr9QwfPrxDztGR5ObmsmPHDoYPH251zxwcHBg8ePBVPbMKP9HQ0MCxY8e49957f3IGly/GGGJsZZcZD3XRdexM3MmwYcOspneq1WomTpzIli1bCA8Pb2Wji4qKGDJkCO7u7qSkpBAeHt5q+l1kZCQBAQF89tln8rZvv/0Wg8FAfHw89fX1nDhxgnHjxsnOIICNjQ3Dhg1rU6tvvPFGu/Zt+/btt7V9y8zM5MiRI9x9992t3k8DBw78n9L6lexU7969qa+vl+/TuXPnkCTJqmOstraWtRvWIvWUfnIGAaTmmR4iQbD0i6U0NjZiZ2cntzsutzFjxoxpcxbCP//5TwYMGGA14ixJEoMHDyYzM5OUlJQ2r8tisfD2228zcuRI2RkE0Gq1jBw5kg8//JDGxkbee+894uPjrZxBgISEBOzs7Pjuu++u5XbeNHbs2EFDQ4PV9HEALy8vevXqxTvvvNNJNVNQ6LrcyByuEKAY+FSSpKOSJH0sSZJ9B9WrTU6ePElgYKD8UpMbHcHG5ulIl/cDSWAe/ZNT6O7uTklJCf7+/jQ0NLR5Dr1ej5eXF5Ik4ebm1mq/l5cXdXV1VFZWAnDixAlsbW3x9fW1esG0EBgYSHp6+lVdm5eXV5v7fH19OX78+M+W0ZlkZGS0ufZKp9Ph5+fH6dOnO6FWtwdZWVn4+/vT2NjIqm9WQQLWjYkWLuvEaHEKg4ODqaqqalWup6enPM3R09OzzXVTgYGBVFdXExQU1GbdgoODO+S3uXjxInZ2dm2uSfTz8yMvL4/GxsYbPk9HkZGRgZ+fn1XjqYXAwMD/ab1eDzk5OVgsFnx8fKzssnm0uV27bIm3sGHbBlnnLTg5OaHX69uchllcXCxrubi4uN31nt7e3lw6MnSpfa2oqMDR0dHKuWshMDCQrKwsLp85c/r06Xbtm6+vL5mZmW3W43YgPT2dgICAG3o/dRWuZKckScLX11d23kpKSggICLim9gbjoSGmgcXLF1NcXIynp2e7NqatToS0tLQ2daZWqwkICODUqVNtXldlZSXV1dVttiFcXV1RqVQUFRVx/PhxfH192yzD29v7ttFCWloafn5+bU7d9vf3v+3bQwoKdyI34hBqgF7Ae0KInkAN8MLlB0mS9JgkSYckSTp0oxHmfH19KS4ulv+/e+9uyilvu9EhV6C58VFOOZu3bMbBwYGysrI2jTQ0L2KuqKjAZDJRU1PTan9lZSWSJMmNiYCAABobGyktLcVisbQ6vqSk5KoW7vv5+clO5uWUlZXd9oEuvLy8KC0tbbXdbDZTXFzcZYIXXI+ePT09KSkpYfee3dTqa5vXuF6FXnfv3Q00N3xtbW1bHdriJAYGBlJWViaPWl9KSUkJer2ekpKSNk9XVFSEp6fnVV3HlXB3d6e6upr6+vpW+8rLy3FwcLgtpiK10GJL2rtn7XXOdEU6wka33C+j0XjVdpnxUC5+0nkL9fX11NfXt3IUARwdHWUtOzo6tmlzoNnpu3SKvZ+fHxUVFQByQKe2OihKSkpwd3dv1RC9kn27WhvfWfj6+lJSUtLKyYWrfz/dSVyq5/Lycqt9Hh4e7dopwOo3vlRrcPXtDcZBOeXU1tde0S63BLu7FF9f3zZ1JoSgtLS03d/KwcEBlUola/xSampqaGhowMXFRX5XtEVFRcVtowVfX18u/+1aaOnUV1BQ6FhuxCHMBXKFEAd+/P9XNDuIVgghPhRC9BFC9GnLAF4LTz/9NCUlJXJv7NDBQ3HBBfUmdfPalLYQoN6sxgUX6uvqSUhIYOvWrdTX17cyOEVFRfInKCiIXbt2Wb1EW+byz507V27cPvbYY5w5cwaNRtNqOkdTUxNJSUmt1qO0xezZs8nMzCQ/P99qe2VlJceOHePRRx/92TI6k4ULF5KYmIjJZLLafuTIEUJCQoiJiemkmnUs16Pn+Ph47O3tcXVxxUVyaQ6scRV6HTp4KLW1tezdu7c5iEEbWhw/fjyhoaGEhYWRnJxsVZTZbGbv3r2MHj2avXv3turgOH/+PLm5uR2yts/FxYXRo0e3WuNisVjYs2cPDz/88G0VjTEmJobg4GCOHDlitd1kMpGUlMQTTzzRSTW79XSEjXZyciIwMJDt27f/ZJc3X9kuSxslNNUahgwaYrVr9+7dxMXFcfLkyVY2OjQ0lJ07d1JfX0+PHj1ISUlp1cAtKSnh5MmTzJ8/X942a9Yszp49S15eHg4ODgQFBbFv3z6r71ksFvbu3csjjzzSqrpPPPHEFe1bdHT0z92iTqN37944Ozu3+X7av3//Vb2f7iQu1fPlo8wGg6FdO5WZmSkH2wGIiIigpKSErKws4OrbG6pNKlxwwd/XH7PZzKFDh6wOMZlMbNu2jUWLFrX6+sKFCzlw4ECrzoq0tDRUKpVV7IRL0Wg0zJs3j71797Z6T+zbt4/Jkydjb2/PY489xtGjR1vNOLl48SLnzp1j+vTp7VzYrWXChAkUFxeTnZ1ttb22tpbDhw+zcOHCTqqZgkLX5UaDyuwBHhFCZEiS9ApgL4RoN6RmR0QZ/etf/8rnn39OXFwcERERFBcXszNxJ6K7aD3y8qNxtsuww15nj8ViwWQy4erqyuzZs3n33Xfp1asXHh4eFBQUcPToUX7/+99jMBh49tln5WmjPXv2lEP6GwwGdu7cadW799prr/G3v/2NxsZGIiIiiI6Oprq6mqNHjzJkyBC++OILq7Uq7fH111/z8MMP0717d3x8fCgtLeXIkSO8+OKLVx2ptLNoampi6tSppKSk0L17d2xtbTl79iz5+fns2rXr0tQDt49XcINci55PnTrFQw89REBAAKfPnaYusq5NvbIe9Kf0jB0+lurqapKSkrC3t6eiogJvb2969+6NEIITJ06g1WpZvnw5Tk5O5OTkMG/ePLy9vYmIiKC+vp6UlBSCgoJ47733eO6559i3bx933XUXbm5uZGVlkZKSwrRp0/jjH//Yqr7XE1SmoKCAIUOGoNfriYqKwmw2c/LkSVxdXdm2bVubU/Q6k4yMDIYNG4aPjw9hYWHU1dVx/PhxEhISWLNmTZtT7Nqgy+gZbsxGX7hwgcmTJ2MwGEhISGD3/t1Uh1dbryEEK5076h3R6XT07dsXtVrNkSNHqKysZN26dWzcuJF33nmHnj174unpSUFBAUeOHCEhIYHTp0/Tq1cv2fnr06cPvr6+FBYWcuzYMf7973+zYMECq/qtWbOGhx56iPj4eNmOe3p60rNnT5qamjh58iTe3t5s3rxZDurUQlNTE/fddx/Hjx+X7VtWVhZ5eXmX27fbkhMnTjBixAiCgoIICQmhpqaGlJQUBg0axBdffHHpGrcupee2gsq0ZacOHjxIU1MTQUFBpKSkEBMTQ3R0NNnZ2Rw7dkxubxQVFbEraVe77Q02NAdM8vPww2w2M3r0aD7++GPCw8OJjY2lrq6OpKQkQkND5XQnlyKE4KGHHmLz5s0kJCTg6OjI+fPnOXv2LJs2baJ3797tXmtFRQXDhg2jtraW2NhYOcpoS2qdliUwr776Kv/617/o2bMnbm5uXLx4kdTUVJYvX87EiRM76M7fONu3b2fatGnExMQQEBBAeXk5x44d48EHH+SNN964lqK6lKYVFG4WN+oQ9qA57YQOyAIeEkK0Pc5PxziEAElJSbz55psUFhbi7OzM/fffz0dLPuKi58Wf5vb/2OiQjks46ByQJAkXFxfmzp3L/PnzUalUZGRksGrVKi5cuEBISAhz5syRgxjk5eWxfPly9u3bR11dHT4+PowdO5YXX3xRzlV4KUeOHOGtt97iwIEDWCwWYmJiWLhwIWPGjLmmkZGzZ8/y/vvvy+slH3/8cTmf0e2OxWJhw4YNLFu2jOrqakaOHMmCBQsuXwvUZYzzteq5vLycr776iqSkJI6mHqUuus5Kr5rNGtQn1GhEsyNisViws7NDpVJRU1ODxWLB0dGR6OhoJkyYwPjx462mPldVVbFmzRoSExOxsbFh4sSJDBs2TO6M2LBhA++//z7l5eV4eHjwzDPPMGTIkLaqel0OITT34H7++eesXbsWrVbLrFmzuO+++9qdot3ZlJeXs2TJErZu3YqDgwPz589n3Lhx15Iio8voGW7cRldVVfH3v/+dPXv2YLFYqG2qpTaq9qdpdj82mqUUCb2kR6PR0NTUhEajwd7enilTprBw4ULZIbvURoeGhjJ79myCg4M5ePAg33zzDWVlZfj5+dHQ0CBPTX/llVfaHbHLysri/fffJzU1FR8fH7y8vDhx4gQ6nY45c+YwefLkdqc2t2XfHnrooTan/t2OlJaWsnjxYnbt2oXBYGD+/PmMHj368vdTl9JzWw4hWNsps9ksTyP28vJiypQpHDx4kLVr11JdXY2vry8NDQ2cO3cOs9mMv78/pZWlFPkVWdlv9SY1tqdtGdR3EDNmzGDOnDnY2dmxe/duXnjhBc6fP4/BYOCZZ57h4YcfbtfGCCHYvn07S5YsobS0lEGDBvHoo49e1dT+hoYGvvrqK1avXo3FYmHq1KnMmjWr1ZKDw4cP8+GHH3LhwgXi4+NZuHAhwcHB13OLbyq5ubl88MEHHD58GG9vbx555BEGDhx4rcV0KU0rKNwsbsghvFY6yiFsC6PRyOz5s8l1z6VpZBParVr8S/xZuWxlh72wr7eRrGBFlzHON6LnW6HXG0HR+lXTZfQMHW+jb7XOFd3eMF1Kz+05hDdKWVkZA4cNJNs5m8YRjei26QipCCFxZyKurq4dfj6FG6JLaVpB4WZxe2WKvgEMBgMrl63Ev8Qf7ce3V+NaQeFyFL0q/C+g6FyhK+Lq6krizkRCKkLQLtYqzqCCgsIdT5dxCOGnxsf9o+9XGh0Ktz2KXhX+F1B0rtAVaXEKF81cpDiDCgoKdzxXFTXhTsJgMPDiCy92djUUFK4KRa8K/wsoOlfoiri6uvLmP9/s7GooKCgo3DBdaoRQQUFBQUFBQUFBQUFB4eq5oxxCo9HIa397jRtNcK+gcDuj6FzhTkXRroJC16OsrIznfv1cu0ntFRQU7nzuiCmjLWGYf//q7ymnnF37drFy+Urs7OzYu3cvpaWlREVFER8fjyRJJCcns27dOmxsbJgzZw45OTmcP39eDiHdvXt3/vWvf3H69GlCQkJ4/fXXOXPmDGfOnKG0tBRPT0+io6Pl8hoaGtiwYQOJiYl0794di8VCbm4u3bt3Z9GiRdcVUv/8+fPs3LkTrVbL2LFjlfUHCkBzupNZ82ZRailly44tPLvoWerr64mKiuLMmTMcOHAAX19fHnnkEezt7WlsbGTVqlXs3buX2tpaGhoaqKurIzQ0lFGjRmE2m2lqapLLj4mJoVu3bkDzc3Xw4EHOnz+Pr68v9vb2ZGZm4urqipeXF8uWLUOlUjFmzBg8PDxu+Nry8/PZunUrAKNGjcLb2/uGy1S4fSguLmba7GkUm4vZvH0z36z6BoPBQEpKCpmZmXh4eDBo0CC0Wi0pKSl89dVXqNVq5s6dS2lpKbm5ufj7+xMZGcn27ds5efIkZrOZ8vJy6urq8Pb2Jjg4mMjISHr16kViYiJVVVXEx8cTFRWFxWJh69atfPDBB3h6enLXXXdRUlICNGvd0dGRcePG4eTkdNXXdPHiRbZt29ahz4HCrUGSJFVwcDCLFy8mKCiI4cOHo1KpOH36NPv27aO4uBhJksjPzyc6OpoePXqwZs0aUlJSCAgIYMyYMRw9epQzZ87g5OTEgAEDGDlyJP7+/uzevZu1a9cihGDSpEkMGzYMSZIQQpCYmMipU6fw8/Nj5MiRrfKZnjlzhj179mBra8u4ceNwdnampqaGDRs2UFVVRf/+/YmNjcVisbB9+3bOnz9PWFgYQ4cOvZZ0OB3Gjh07mPvgXErMJfyw+QeSdiUp7RUFhS7IdaedkCQpClh1yaZQ4PdCiH+3953rCWmelZXF448/zsXii1i6W5rz/mwA9wvumOpMuLm54eLiwvnz5/Hw8KCyspKSkhLCwsKorKwkLy8PvV5PU1MTgYGBNDQ0UFBQgIeHB25ubmRnZ9PU1IRWq8Vk+qm8/Px8/P39mTt3Ln/605/k76vVarKzs3F2dkatVlNRUcGKFSuYNm3aVV1PU1MTjz32GF9//TURERGYzWbOnj3L7373O1544YVrujd3KF0mBHRHh+hfsWIFr/79VUSCaE7mvR40qRoigiPIzs5GrVYTEhJCWVkZxcXFjB8/ns2bNyOEICQkhKqqKgoLC3FycqKiogIhBB4eHpSVleHm5oaHhwcXL14kKCiI//u//+PFF1+koaEBHx8fcnJyqKysJDQ0lMLCQqqqqoiJiUGSJM6cOcNzzz3HH//4x2vKqdmCEILf/OY3fPjhh4SHhyNJEpmZmTz++OO88cYb11XmbcQdXfnLuV5Nb926lad+/RSW7pZm7W4A7UktQT5BVFZWEhgYSFlZGUajETs7OwoKCggODsZkMnHx4kWcnZ0JCgrizJkz1NTU4OPjQ1lZGWq1moCAAIqKiqioqMDX15f6+npKS0vx9vbG09OTs2fPEhISQlZWFrW1tYSFhdHY2EhOTg7u7u6YTCa5zOLiYv7+97/zxBNPXPF6LBYLTz/9NEuXLiUyMhKLxUJmZibPPvssf/rTn+50zV6JLnFhkiTF6HS6DQ4ODkHh4eEUFhYCEB4eTnJyMhqNhoaGBoKDg6msrKSoqAiTyYRWq8XOzg4fHx8KCgqorq7GYrEQGBiIRqMhNzcXnU5HbW0tBoNBtqkGg4FPPvmEp59+mrKyMvz9/SkpKaGuro5vvvmGAQMGUF9fz4MPPsjGjRuJiIiQcxtOmzaNNWvW4O/vj52dHWfPniUuLo5z586hUqnw8vIiPz8fGxsb1q1b126OzY6muLiYe++9l8MnDiMShNz28i/2J+VQyp3kFHYJTSso3Gyue4RQCJEB9ACQJEkNXATWdEy1mmloaGD+/PnUmmohAcSYH5PAjoOS9SU4ZTsxbdo07OzssFgsvP/++/j6+vLQQw/Jybh37NjB8ePHWbhwIY2NjSxevJgHHniAoKAgALlX+fDhw8yaNYvQ0FB5+65du3j55ZdxdnZm/vz5cs9yfX09q1atIjAwkKCgIObOnUtGRsZVJXb97W9/y/79+1m0aJGc4L6iooK3336b4OBgZs+e3ZG3UOEOYceOHfzl739B6in9pPPxINSCzJRM+vTow+jRo+Ue4nPnzvH5558TGxvLxIkTZb3n5+ezYsUKJk+ezPr16yktLeWBBx4gMDAQQO51/sUvfsHw4cPp3bu33LhNTU3l+++/x9PTk0cffVROZlxVVcWnn35KQEAAjz766DVf25tvvsk333zDk08+KSccr6mpYfXq1fj5+fHss8/e6O1T6ETS0tJY9NwipJ4SjEG20U2iiYunL7LosUXY29sDsHnzZtLS0nj66afR6/W8++673HvvvSQkJHD8+HHOnTvHokWLWLFiBYMGDeKuu+6S9ZmRkcG6detYuHAheXl5fPvtt8ycOZPx48fz8ccf4+joyMKFC7GxsQGgsrKS5cuXM3jwYGxsbPjuu++YPXs2L7/8MqGhoYwePbrda/rLX/7Cxo0b+eUvfyk/B9XV1SxduhQ/P7+fdSgVOg9Jkmy1Wu3usWPHuvXs2VMeuTt+/Djr16/H19cXd3d3xo4dK9vNixcvsnTpUvr27cuIESOQJImjR4+yb9++Vu/+5cuX4+fnx4wZM4DmDq/9+/czfvx47r77bqZNm2al2XvvvZf09HR+97vfkZ6ezlNPPYVWqwWap2IuXryYu+++m379+gFgMpn49ttvkSSJBQsWyPU/evQoI0aM4MyZM60Szd8M7r33XlIzUpF6SFjGWOTnOndDLn3u6sOhpEN3klOooKDwM3TU/IMRwFkhxPkOKg+Ab775BmOtkfroesxjzD/18/zYWK6JqGHx8sXU1tZSXl5OTU0NEyZMkI08NDdWJk2ahKOjI8nJyfTu3Vt2BgFUKhUjR45Er9fLRrpl+7Bhw1Cr1YwfP95qmpGNjQ0TJ07k4MGDBAQEkJCQwEsvvfSz11NTU8MHH3zAuHHjZGcQwNnZmeHDh/OXv/zl+m+Wwh2L0Wjk2f/3LKKH+OnFCyCBeYwZU7yJzPOZ1NfXy99xdHREpVK10ruPjw+DBg3i9OnTDBs2TO5hbkGlUslTp3x9fa1GOqKjo7FYLEyaNMmqweHo6MioUaN47bXXuNYZBWazmX/84x+MGTNGdgYB7O3tGT16NG+88QYWi+WaylS4fTAajSx4dAH0oJV2GQ+NMY18suITamtrgebpcpMmTcLJyYnU1FT8/Pzo0aMHkiSRmJjI+PHjKSwsRK/XM3DgQCt9RkVFERUVxZEjR4iMjCQmJobDhw9jsVioqKhg6tSpsjMI4OTkxLhx40hMTCQ6OpqIiAjOnTvHkCFDeO2119q9pqamJt566y3Gjh1r9Rw4ODgwcuRI/va3v13zc6BwS5np5+dn06tXL6lFP5IkkZCQgK+vL0VFRVbOIICfnx+DBg2ipqZG1lxSUhL33ntvq3f/1KlT5ZlFLWW7uLjg7Oxs1YEBzZoNDw/nrbfe4osvvmDcuHFW7QxXV1fGjh1LWlqavE2j0TBp0iSKi4upqKiQz9GrVy8MBgOrV6++CbfMmu3bt3PkxBEaYxtbt73GwXnX8wwcNlBZU6ig0IXoKIdwNvBFB5UFNDc03nz3TUxxJsyjza0H/SUwjzZjDDayePlicnJy5GkdLZhMJkpLS+WRu/z8fHkE8FJUKhVhYWEUFBRYbbdYLDQ0NBASEtLqO66urtjY2FBRUUFERASHDh362WvKysrC2dkZZ2fnVvtCQ0NJS0tTGhr/YxiNRmbPn01dVF3zlJw2dM44ZJ23NKwLCgoICAhotT4FkLUcFhaGJEmUlpZa7VepVISGhpKfn2+1vaqqCr1ej7u7e6syAwMDyc3Npa6u7pqur7S0lNraWnx8fFrt8/X1pbq6ulX9FO4MWrRbGVbZrnbNY36y0dXV1RQXF8v29FJ7bLFYKCwsJCQkpF07DVjptkXnFRUV6PX6NkcrQkJCKC4uxmw2y8eHhoaSkpLS7nXl5eUBtLleMDAwkPz8fPk5VLj90Gq1A6Kiohza2ufk5ERAQICVM9hCeHi4rC2z2UxxcXGbs37c3NzQ6/VUVlbK2/Lz84mKimqzPoGBgezatQtvb2+rTrEW2mp76HQ6/P39W2339/e/qrbGjVBWVsbcBXOxJFisncEWpObOn2znbMUpVFDoQtywQyhJkg6YBLTZbSVJ0mOSJB2SJOnQtUSee+/996jWVLfd0JALb3YKyynndOZpuTetBbVajUajoaqqCgA7O7tWx7RgNBpbTcNQqVSo1Worw99CU1MTtbW1slPo4uLys9fk6upKZWUlJpOp1b6KigqcnJy68tqULsH16rk93nv/PXKrc5vXXV2Fznfv3Q2Ara1tu1quqKiw2t9WI6Qtvev1eurr62lsbGx1fHV1NVqt1mpk+2pwcHCgqampTUeyrq4Ok8mEg0ObbTeFW8SN2Ojc6tyrttF79+1Fp9PJ9vRSjUqShI2NDZWVlT+r7RY9t+jc1taWuro6q+BJLVRWVqLT6VCpVFbPxZXstbOzM3V1dTQ0NLTaV1NTg0ajsRqJVLi9MJlM/mVlZW32rDY1NV2VtlQqFTqdTm47XEpjY6P87m/Bzs6uXceooqICLy8vjEZjm7MhWnR5KUIIq/q0UF1dfdMDG736l1cpMZf87HPdOKKRrPIsXv3Lqze1PgoKCreGjhghHAccEUIUtrVTCPGhEKKPEKKPwWC46kIXPrEQPzs/WA+0N2gmQL1ZjQsu3Dv+XiorKzl79qy8W5Ik4uPj2bVrFwAJCQns37+/VcMhLy+P3NzcViOBBQUFSJLEnj17Wp364MGD+Pv7o9Pp2Lt3L//3f//3s9fk5+dHQkIChw8ftr4MIUhKSmL+/Pk/W4ZC53K9em6PhU8sxN/BH/Um9RV1rtqkwgUXhg4eCjRryWg0Wukdmnu29+3bR/fu3dm9ezdms1lev9VCbm4ueXl5eHp6Xn5tqNVqDhw40KoK+/fvZ+bMmW32rF8JOzs77r333nbLnDhx4i1ZD6PQPjdio/0d/NFs1lyVjR46ZCjdunWT7XH37t05duwYVVVVSJIka7Zbt26cPn261chxfX09Bw8epHv37tTX15OcnExCQgL29va4u7u3qbG9e/fKxx88eJD4+HgOHDjAQw891O51GQwGhg0bRnJycqt9SUlJ1/UcKNw6hBDPHDt2rOHyjtzq6mqys7OprKzk3LlzVvtMJhO7du0iPDwcQNZjW+/+5ORk/Pz8rOxqQEAAp06daqXZuro6jh07xnPPPYefnx/Hjx+/vK7s3LmT7t27W20/ffo0jY2N+Pv7y9sqKipITU1l3rx5V38zroOXfvcSYS5hsIErPte6bTpCXUJ56Xc/v1xGQUHh9ue6o4zKBUjSSmCTEOLTnzv2WiPYGY1Gxk0eR1lgWesRFAFsAIczDkwZP4WCggISExNpamqiX79+REVFUVVVxa5du6isrCQkJIRevXqxf/9+KisrGTJkCC4uLpw9e5bExEQcHR1Rq9UMHjwYFxcXsrOzOXToEP7+/mRnZxMUFETv3r3RaDQcP36czMxMBgwYwOHDh+nRowfbtm27qtG9jIwMhgwZQlhYGFFRUZhMJo4fP47ZbGbv3r1XNdJ4h9NlhkA7Ksqo0Whk1gOzOO9yvnWvrABpowRHYWDfgURHR1NeXs7u3bupq6ujsbHRSu9JSUkIIRBCUFpaipubGxaLhUGDBmEwGMjKyuLw4cOMHj2a7du3079/f3x9fSksLGTPnj34+fnJYc579OiBxWLhxIkTVFdXk5iY2MqJvBouXrzIXXfdhaenJ7GxsUDz2t7i4mISExPx8/O74XvYiXQZPcP12ejZ82dz3uW89RpCaLbR68HutB1TJ06VNWQ0GgkJCaFPnz6kp6dz+vRphg4diqurK+vWrcPT0xM3NzdSU1MZOHAggYGBFBcXy/oMDQ1l9+7deHh4MHjwYLKysjhw4ABms5m4uDi6d++OyWTi8OHDFBUV0a9fP5KTk/Hy8kIIgbOzM9u3b29z5LyFc+fOMXDgQPz9/YmJicFisZCamkplZSVJSUnX9RzcIXQJPWu12hd0Ot3Ld999t52vry8FBQUcOHCA2tpaOSJtnz59iIiIoLKyUk5h0tTUxLBhw/Dz8+PChQvs2rWL4OBg+vTpg0ajISUlhZMnT6LX67nnnnvw9PQkNzdXXv+6efNm+vXrh7+/P8XFxRw6dIjp06fz1ltvcezYMUaMGEFMTAyRkZHU19dz7NgxCgoKcHFxoU+fPjg4OHDmzBkOHTokr6P19vYmPz+f5ORk/u///o/nn3/+pt+/srIyuvfuzkXPi222vXTbdIRUhJC4M/FOCCzTJTStoHCzuSGHUJIkeyAHCBVCtD0P4xKupwFtNBqZMnMKBd4FPzWWBWi3anE570KofyhGo5GYmBgWLFiAyWTiL3/5C2fOnEGlUhEcHIxGoyEnJwdoDpAhhCA/P19erxcZGYmPjw8nTpzAZDJha2tLr169WLBgAREREaxdu5YPPviAsrIyVCoVZrMZIQSurq4888wzPPPMM9c01bOgoID//Oc//PDDD+j1embPns3DDz/8vzJ1rssY545MO9HiFF5wu/DTmtkfnUFtqpa4qDg59L6NjQ2TJk3i2WefZeXKlXz00UdUVlYihMBsNssadXV1xdHRkcbGRjQaDVqtlu7du8u6Pnz4MMuXLyc7OxuDwYBGo6G0tBQnJyccHR0pKytDo9EwY8YMHn300TbXvl4tZWVlvP/++6xZ0xyIeOrUqTzxxBNdoQOky+gZrt9Gz54/mwuuFzCNNsna1WzR4JXnRfeY7mRnZ+Pp6cmsWbMICgriz3/+M6dOnUKSJIKCgnB2dqaoqAg/Pz88PDzYv38/JSUlmM1mANlWOzg4EBERQVRUFGlpaVRVVdGzZ0/mz59PVlYWb7zxhpyuws3NDZVKhcViwWw24+Pjw/z585k/f/5VTfksKSnhvffeY+3atajV6g55Du4AuoyeJUka6urqusvf35/Q0FCeeuopOcDL+vXrqayspKmpCYvFgp2dHW5ubpw9exaz2YxGo8HJyYnq6mrq6+vRarV4enoyb948+vfvz+uvv86JEyeQJIlu3brx17/+lUGDBpGcnMy///1vTp48SUBAAE8++STjxo2T2wcXLlzg7bffZuvWrdjZ2fHAAw8wd+5cvvnmGz799FMqKioYMmQIzzzzDOfPn+edd94hKyuLiIgIfvWrXzFkyJBbdv/KysrofVdvclxzfursufOcQehCmlZQuJnc8AjhtXC9DeiWBkeuey5NI5vQbtXiX+LPymUr6Yhpe1dLeXk5/fv3v2Xn66J0GePc0XkIbxedg6L1a6DL6BkUG63QtfQcFxcnUlNTO7sadyxlZWUMHDaQbOdsGkc03onOIHQxTSso3Cw6KsroTcVgMLBy2Ur8S/zRftx5jWQFhZuJonOFOxVFuwoKXQ9XV1cSdyYSUhGCdrH2TnQGFRQUrpI7wiGEnxoc94++X2loKHRZFJ0r3Kko2lVQ6Hq0OIWLZi5SnEEFhS5M6yRmtzEGg4EXX3ixs6uhoHBTUXSucKeiaFdBoevh6urKm/98s7OroaCgcBO5Y0YIFRQUFBQUFBQUFBQUFDqWTncIjUYjr/3tNToiybeCwu2Gom+FOx1FwwoKt4aysjKe+/Vz7Sa5V1BQULhZdOqU0ezsbBY8uoBiczG79u1i5XLrdSdCCDIyMigsLESr1dLU1IS/vz9+fn4cPXoUIQSxsbGcOnUKk8lEjx49OHXqFN988w0Gg4EHH3yQrKwsqqurAeQE2JIkkZCQ0Gaah7KyMrZv305FRQWxsbE0NTVhb29Pjx495GPS0tI4d+6cnEvwUoQQHDlyhKKiIrp160ZgYGDH37hOxmw2c+DAASorK+nVq1dXzsl1Q6SkpPDUr5+i1FzKrsRdba6rKi4uJj09XU6HcvDgQby9vQkNDaWsrAx/f3+Cg4P57rvvSE9Px9vbGx8fH2pqajh9+jQ+Pj5MnToVnU4nPxM9evTAzs4Os9lMSkoK1dXV6PV66uvrCQ4OJiAggOPHj1NZWUlMTAweHh7XdF319fUkJiZiNpsZMGAAjo6OHXjXbh1ms5mkpCSqq6vp06cP7u7unV2l246LFy8y98G5FJuL2blvJ6uWr2pzbWBJSQl79+5tDlXfuzfdu3eXQ+1nZWWxa9cu9Ho9o0aNwt3dnaNHj7J+/Xo0Gg1RUVHY29tjMplwdXWlV69eaLVaTp06RVFREaGhoQQEBLQ6Z2FhIevWrUOtVnPfffdRWlpKRkYGBoOhlV2uq6uTNavRaGhsbKRnz554eXndlPvWmTQ0NMg5eQcMGICTk1NnV6nTOX36NGfOnCEoKIhu3bpZ7TObzSxbtozc3FzGjx9P7969MZlMJCYmUldXh1qtZsWKFbi4uPDHP/4RgL1797JlyxacnZ2ZMWMGMTExJCcnU15eTo8ePfDx8QGa2wPJycns3LkTX19fJk+e3O7vUVZWRp+7+nCh+gLffv8th5IOXfV6vfz8fI4dO4aLiwv9+vVDpWq7rz8zM5PMzEwCAwOJi4u72tvX6QghOHToECUlJcTHx+Pv79/ZVVJQ6Hq0JLG+ng/wLHASSAW+AGyudHx0dLTIyMgQJ06cEFOmTBGSXhL0Q/AHBP0Q3gHe4sCBAyIjI0OsX79eREdHCxcXF+Hk5CRsbGxEUFCQcHR0FDY2NiIwMFB4enoKrVYr/Pz8REhIiNBoNEKr1Qp3d3fh6+srNBqNsLe3F15eXlb7goODhYODg3j66afFqVOnREZGhkhNTRVTp04VOp1O+Pr6Cnt7e6HRaIS/v7/w9fUVXl5e4qWXXhL9+/cXrq6uolu3bsLFxUUMHjxYXLhwQQghxKFDh0RkZKTw8fERsbGxwtHRUdx3332ioqJCdBU2b94s/P39RUBAgIiJiREODg7i4YcfFvX19VdbxA1p7nb6tOj58s/u3btFz549hUqvstJ3QGiArO/jx4+L++67T9jb24vg4GBhY2MjHBwchI+Pj9Dr9cLGxkaEhoYKOzs7odPphMFgkDWt1+uFn5+fsLW1Fba2tkKtVsvHh4WFCUdHRzF9+nTh7e0tfHx8REBAgNBoNMLNzU3Y2toKe3t74ePjI6Kjo4W9vb247777xPHjx62uYf/+/W3+eB988IFwcXERYWFhIjIyUjg6Ooo///nPwmKxXO3vf1vw3XffCR8fHxEUFCTreOHChaKxsfFai+p0HXbkp0XTp06dEo888kgrG+3u6y5ruMWWT548WdjY2AidTicCAgKEk5OT8PHxER988IGIiYkRer1eGAwG4e/vL9RqtbC3txd2dnYiICBA6PV6odPphLOzs9BqtcJgMAgHBwfh6+sr3N3dRUxMjHBychJDhgwR+/fvl231wIEDhVarFR4eHsLT01PodDphb28voqKihIuLixgyZIjIzc0VQgjx7rvvCoPBIIKDg4WPj4/QarXC29tb2Nvbi4ceeuhabNdtz+LFi4Wrq6sICwsTUVFRwtHRUfzhD3+4luez0zXYkZ/IyEgxdOhQ4eLiIrp16ybc3NxE3759xdmzZ4UQQrz33nvC1tZWODo6isDAQKHT6YSnp6fw8PAQgYGBwmAwCI1GI7y8vOR2hEqlatXOsLW1Fb6+viI2NlY4ODiIefPmif379wt/f3/h4OAgAgMDZbv+/PPPt/o9UlJShI2TjdWzZuNkI44fP37FH6u2tlY88MADwsHBQcTGxgo/Pz8RFBQkdu7caXVcfn6+GDZsmDAYDKJbt27C3d1d9O7dW2RmZl6x/NuBpKQkERYWZnV/Z86cKaqqqq62iE7XofJRPnfC57rzEEqS5AfsBWKFEHWSJH0JrBdCLGnvOy05rv7f//t/rN+yHnO8GfOYn5Jwsx78iv1Y8tESZs+ezYABAzhw4ADx8fEMHjwYtVot9+rv378flUrF3Llz8fb2ZsWKFeTm5jJv3jy596i6uprPPvsMX19fhgwZwueff07v3r3p378/RqORr776innz5vHQQw/xhz/8gf379zNz5kx27NhBeXk5U6dOxc7ODmjuWVu9ejXDhg2jf//+cl0SExM5f/48W7ZsoXfv3txzzz3ExcUhSRKNjY1s2bIFJycntm7del33+Xbi+PHjDB06lEmTJhEWFgY097x///339O3bl08//fRqiukyOYHaytnW1NTEuHHjKK0spSGmwVrfGyC4PJhVK1bxpz/9iZycHIYNG8bHH3/M2LFjiY2N5b333qNnz54MHDiQ4uJili1bxvTp0wkNDQWa7/eaNWtwdHRk/PjxJCYmsmfPHh566CG5V/r06dN89dVXzJ492+p7K1eupKCggOnTpxMeHo4kSdTX1/PDDz8QHBzMP/7xD/k62srn9s033/DEE08wY8YMeVTYaDTy9ddf8+tf/5pf/epXN+lOdyzJycmMGTOGKVOmEBwcDEBtbS3r1q1j+PDh/Oc//7mW4rqMnuEnTb/zzju8v/h9RIJopWGvPC/Wfb0Og8HACy+8wI4dOwgODmbcuHHo9XqEEKSlpfHtt9+iUqlkvdXX1/P2228zYsQIevXqhUqloqmpiW3btnH06FEmTJjA8ePHuXDhAqNGjaJnz57yMTt27KCqqorVq1fz5JNPkpSUxAMPPICHhwf//e9/6dOnDwMGDLCyyzk5Obz88ss8//zzTJ8+XR4JLy8v5/PPP6dXr15cvHiRnj17smzZsk697x3BunXrePjhh5kxY4Y88llRUcHXX3/NokWLeP7556+mmC6jZ0mSNPb29k39+vVj0KBBaDQazGYzBw8eJDU1lQ8++IApU6YwadIk+Z195swZvv76a+bOnUtRURFJSUnMnTtXHqkrKSlh6dKl9OnTh7vvvhuAqqoqVq1aRVhYGPfccw/19fWsX7+ezMxMxo4dK4+WNzU1sWnTJk6dOsWLL77Ib3/7W6B5dC8wPBBzvBkxVsjPmrRRQnNCQ87ZHLy9vdu8xtmzZ5Oens748eOxsbFBCEFmZiY//PAD+/fvJzo6GrPZTPfu3fH09GTw4MFoNBosFguHDh3i2LFjZGRktDlb6nbg3Llz9OrVi1GjRhETE4MkSTQ0NLBp0yZ8fHz4/vvvr6aYLqNpBYWbyY2uIdQAtpIkaQA7IO/nvpCdnc3aDWutnUFo/jse8rzymDVvFr6+vtja2mJvb8/dd9+NWq0GQK1WM3jwYADGjRuHt7c3FRUV5ObmMmbMGKupBA4ODsyePZvjx49ja2vL1KlT2bt3L2azGYPBwMSJE/nwww8pKipi7dq1zJw5EyEEJ06csHIGAWpqavDz82PgwIFWdRkyZAgqlYpnn32WqKgo4uPj5alSOp2OsWPHkpKSwtGjR2/wVnc+r7/+Ov369ZOdQWiehjtx4kS+/vpr8vPzO7F2twffffcdBaUFNMQ2tNb3OLjgfoHpc6azc+dOJk6cSGpqKpGRkSQkJJCeno7BYGDIkCGo1WqSkpIYOHCg7NQBso5PnjxJbW0tQ4YMwc/Pj6KiIvmYkydPMnTo0Fbfc3FxYcCAAURERMgatbGxYeLEiezYsYO8vCs/vn/4wx8YNWqU1RRhg8HAvffey1//+ldMJtON38BbwF//+lcGDhwoO4MAdnZ2TJw4kWXLllFaWtp5lbsNKC4u5r8f/RdLgqVNDRf6FjJ7/mwyMzPZuHEjZrOZiRMnotfrmw+TJLp164arq6uV3g4fPkxQUBB9+vSRp7RptVrGjBmDg4MDu3fvZurUqZjNZqKioqyOGTVqFCUlJWzbto3ExETGjRuHr68vqampuLm5MWjQoFZ22WKx8OKLLzJmzBiradEuLi5MmTKFAwcOMGHCBNasWcPFixdv2f29WbzyyiuMHDnSahqss7MzEyZM4O9//zuNjY2dWLtOYaKTkxN33303Gk3z6hi1Ws2AAQNwdnZm4cKFdO/e3eqdfeDAAUaNGoWfnx979+5l8uTJVtM23d3dmTp1KqmpqbR0pjs6OjJ9+nSSk5NpbGzExsaGCRMmYLFYCAwMlMvWarWMHz8ejUbD66+/TkNDQ/MU6wG9McWZfnIGASQQYwVNcU30GtCrzTWF586dY8OGDUyYMAEbG5vmr0kSkZGR9OrVi3/+858ArF+/nrq6Oqv7oFKp6NevH+7u7qxYsaLj73wH8fbbbxMXF0dsbKx8H/V6vdwZmp6e3sk1VFDoOly3QyiEuAj8A8gB8oEKIcTmK33HbDbz4KMPWvc6X8qPRrA8uJzsi9lkZ2e3WgsCYLFYqKmpITIyEmhe52Iymdo81tnZGWdnZ4qKivD29kalUlFRUQGAl5cXarWa3bt34+XlhZ2dHXl5efj6+lo5gwAXLlwgJiamzesKCgoiOTnZylFqQa1WExYWxr59+650a+4I9u3bJ9/zS7GxsSE4OJjk5OROqNXtg9Fo5LV/voYp3oR5dNv6No82k+eVh0kyYTKZOH/+vLym5cKFC1b398KFC21q2sbGBn9/f7kRGx0dzYULF372e3l5eURHR7fartPpCAkJISUlpd1ra2xsJD09nfDw8Fb7vL29EUJw/vz5dr9/O5GUlNSmju3t7fH39+fIkSOdUKvbA7PZzOwHZmNJsGAZY2lTw4yDXPdcHn7iYZycnAgPD5edsUtpamqy0lt2dnab65YkSSI6Opri4mJZ25d3TkiSRFhYGFu3bqWxsVHWd3taBwgMDKSoqIiQkJBW+/z8/GhqaqKhoYHQ0FAOHDjwM3fm9qZlvXBERESrfZ6enmg0GrKysjqhZp2HRqO5+/L1gi2EhIRQWlrayh626KmmpoaGhoY216oFBwdTUVFBfX29vM1gMODs7ExxcTHwk03Nzc21+q5KpZJtz+HDhxk4bCCFvoUwjnaftUKfQgYOG9jKKTxw4AChoaHodLpWdYyIiGDPnj1A83rH4OBg2aG6/Fp27drV5j26Hdi1a1eb7SqNRkN4eDiJiYmdUCsFha7JdTuEkiS5AJOBEMAXsJckaV4bxz0mSdIhSZIOXcy7SIm5pG3jJ3+h2Sms0dWQX5hPbW1tW+dGrVbL+3Q6ndX/L0UIQX19PTqdDpPJRENDg2xAzWYzdXV1GAwG6urq5LLaKqe97dAcZMPW1vaK++/UwBuXYm9v3+411tTUdIlr/Dku1fPlURffe/89qjXV1j29rQpodgob7BvYvXc3er2empoaoLXGrqS52tpaeUSmpqbGqlFwPRqura1t1QlyKWq1Go1GY9UIasFkMlFXV3fbTju6nPZ0LIT4n9HxpVxuowsaCn7WRjeNbKLEUkJFVUW7mrrcJuv1+ivqT61WI0lSKz23UF9fj7Ozcyvb316ZDQ0NCCFoaGhota+pqYmmpiZ0Ol2X+M1VKhV6vV5+j12K2Wymtrb2jr/Gq6VFzyaTaUZVVVWbx9TV1SFJUivttOhJq9ViMploampq9d0WXbWMtkFzJ3Vtba2VbtvTcW1tLU1NTXzy6SdklWe13fEiXwxYxljIKs/i1b+8arXLwcHhis9Tiz12dHRs8xloOe52Djrk6Oh4VdeooKBw49zIlNGRQLYQolgI0QR8Awy8/CAhxIdCiD5CiD5+vn4EOgTCBprXo7SFAM1mDaoKFSPuGcGxY8daveQaGhrQarXs378fQJ76lZSU1Kq4jIwMVCoVnp6epKSk4OPjIxuRlh7Ve+65B7PZTHZ2NgEBAdTV1XHu3Dmrcrp168bBgwdbGda6ujpSU1N5/PHHOXbsGGaz2Wp/WVkZZ8+eZdKkSe1c8J3Dgw8+yKFDh7h83emFCxeoqqpiyJAhnVSzW8eler482uLCJxbia+sL67mivrVbtaiMKiLDI4mPjycpKQmz2UxcXBzHjh2Tna64uDj279/f6n7n5ORQVVVFYGAg9fX1HDlyxGrkJS4ujsTExFbfa5kGdfn2vLw8SktLueuuu9q97pZIjm2NAqekpNCjR487JmLjAw880KaOs7OzEULQr1+/TqpZ53C5jQ5wDPhZG63dqiXAIQC9Vs+5c+coKSmxOsRiscjRLlvuc69evUhKSmrVyK6qquLkyZPExsZy/vx5jEYjvr6+VsdUVlaSnp7Ogw8+iF6vl21/XFwcR44cadMup6Wlcc8993Dw4MFWl3DkyBECAwMpLS2loqJCXg92pyJJEjNmzGjz+Tx+/DgxMTH4+fl1Qs1uPS16BkakpKS0cigaGho4fvw4gwcPliPPttBic1tmvbQ1W+DgwYNERESg1WrlbadOncLW1laOVJyfn09BQYHVtHRonkVy+vRpIiMj+fvrfyfUJRTtVu3PPmuhLqG89LuXrHaNGDGC4uLiVks1hGiOdP7ggw8CMGvWLFJTU+WOxxYaGxtJTU3lgQceaOfknc+DDz7I0aNHsVgsVtuLi4vJyclh/PjxnVQzBYWux40ElekPfAL0BeqAJcAhIcQ77X0nJiZGLF26lEnTJ1HoXQjjse4Z+9H4+Zf4E+wbzLlz57C1taWkpIRhw4bh6+tLQUEB27Ztw83Njby8PCIjI+nTpw+ZmZns2bOH6OhoBgwYgF6vJy0tjT179jBmzBjKy8s5ePAgEydOxNvbm9TUVI4ePcqSJUuIjY1l165dPPPMMwwePBgbGxu2bNnC0KFDiYqKora2loMHD5KTk4ODgwODBg3C29ubvLw89u3bx4wZM3jjjTcYP348OTk59O/fH1dXV7Kzs9m3bx9//OMfefLJJ6/rPt9OVFdXy+s3+/Tpg4ODA6dPnyYpKYklS5YwefLkqymmyyzwbiuojNFoZPS9o6kIrWg9ynKJvh+Z/wh///vfGThwIGlpaZjNZu655x5OnDjBxYsXGT58OG5ubqxatQo3NzeGDBmCvb09p0+fZteuXYwcORJ7e3u2b9+O0WikR48e9O7dG5VKxbFjxzh8+DDh4eH079/f6nt6vR4PDw+GDBmCo6MjmZmZJCYm8sorrzBu3Di5qm0FlWnRdmhoKAkJCahUKk6ePMnx48fZvn07CQkJN/FudxwVFRXcdddd2NjY0Lt3b+zs7MjIyODAgQOsXLmSMWPGXEtxXUbP8JONnjprKhc9Ll7RRq9ctpJDhw7xm9/8BrVazfDhwwkJCcFoNLJr1y6ampooKysjICCAwYMH4+DgwMqVK1GpVIwYMQIPDw9ycnLYtm0bjY2N9O/fn+TkZDQaDfb29owYMQJ3d3dycnLYs2cP8+fP57HHHuP777/nxRdfpFu3bvTr14/ExEQKCwsZPny4bJcTExOZOXMmv/zlL7nrrruIiIige/fuqFQqUlJSOHLkCL179+bEiRN8/PHHTJs2rbNueYeRm5tL//79CQoKIiEhAY1Gw8mTJzl27Bhbt26lV69eV1NMl9Kzl5eX0Gq1DBo0CF9fXwoLC0lMTGTEiBH885//JDQ0FEdHR4YNG4arqysZGRls27aNmJgYoqKi+OGHH0hISJDTTh05coTDhw8TFhbG0KFD0ev1nDx5kr179zJy5EgiIiI4c+YMSUlJ+Pj4UFFRwT333IObmxvnzp1j27ZtmM1mdu7cSd++fSkrK2PgsIFk2me2HikUoNqkIqImgsSdiW2moFi1ahULFy5k4MCBhIeHU1VVRXJyMra2tuzatUtOtfXb3/6WpUuXMmjQIHnNeWJiIkOHDmXJkiVtTie9HWhsbGTUqFEUFxfTv39/nJ2dycrKIjExkddff52HH374aoq5PS9OQeF240ZClAJ/BE7RnHZiOaC/0vEtIc0PHDggfIN9hdRfag6x/EpzqGXtIK0IiQoRBw4cEGlpaeJPf/qTiImJEY6OjsLFxUUYDAYRGxsrBg4cKLy9vYWnp6eIjY0V3t7ewsvLS8TExAhbW1urUOaurq7CwcFB2NvbCwcHB+Hs7Cw8PT3FjBkzxKZNm6xC7X/99deiV69echn29vbC2dlZBAUFiaefflps3bpVLF++XPTt21d4eXmJAQMGiJUrV8ohpBsaGsRbb70lunXrJry9vcWoUaPEli1bRFeiqqpK/PnPfxYRERHC29tb3HfffeLAgQPXUkSnh9btqE97aSf2798vPP08r6jvjIwMsXLlSjF8+HDh7u4up1fR6XRCr9cLV1dX4erqKuLi4kRcXJycfkKn08kh/vV6vdBqtSIyMlJMmDBB+Pr6Cm9vbzF79myxbt068atf/UoEBwcLZ2dn+fnp2bOnmDx5sggNDRUeHh5i+PDhYuXKlW1eQ1tcvHhRPPvssyIwMFD4+vqKRx555I4IXX45RqNRvPLKKyIsLEx4e3uL6dOni8OHD19PUZ2uw478XGqj/UP8hWqA6ooazsjIEF9++aXo1auXsLe3F3q9Xnh6eopf//rX4vjx4+If//iHnCLFxsZGxMbGimnTpgmDwSBrWKPRyGlXPDw8xIIFC8Tzzz8vYmJihIeHh+jfv794//33rfT56aefirCwMGFjYyP0er3w9fUVERERws3NTQwYMECsWrVKtssXLlwQTz31lPD39xcuLi7C1dVVuLu7i0mTJrWr8zuV/Px88etf/1oEBQUJX19f8dBDD4mMjIxrKaLTNdiRn9jYWPHll1+Ku+66S3h5eYk+ffqIpUuXytooLy8XEyZMEA4ODkKv1wsfHx/x17/+Vbz00ksiNDRUODs7y/ZWp9MJPz8/MWrUKKt2ho+Pj5g+fbqIiooS3t7eYsKECWLv3r2isbFRvPbaa8Lb21vo9Xrh4OAgRo0aJU6dOmV1w0tLS0VUXJTQDNRYPWuagRoRFRclSktLr/iD7du3T0yYMEF4e3uLqKgo8be//U3U1NRYHWOxWMTXX38tBg4cKLy8vETv3r3Fp59+Ksxm8xXLvh2or68Xb775poiJiRHe3t5izJgxYseOHddSRKfrUPkonzvhc90jhNfDpSMqRqOR2fNnk+ueS9PIJqte57YSH98OtDVqonDNdJneurZGCFu4E/V9KYrWr5ouo2dQbLRC19JzXFycSE1N7exq/CwtI4XZztk0jmhEt01HSEVIuyODCtdEl9K0gsLN4kbTTlw3BoOBlctW4l/ij/bj27+hoaBwLSj6VrjTUTSsoHBrcHV1JXFnIiEVIWgXaxVnUEFB4ZbTaQ4h/NTguH/0/UpDQ6HLoehb4U5H0bCCwq2hxSlcNHOR4gwqKCjccjQ/f8jNxWAw8OILL3Z2NRQUbgqKvhXudBQNKyjcGlxdXXnzn292djUUFBT+B+nUEUIFBQUFBQUFBQUFBQWFzuOWOYSSJLkWFhdyeTJvBYU7EUXPCl0NRdMKCncmZWVlPPfr5ygrK+vsqigoKNyh3JIoo5IkuaMjGRdCQgwh17wWpSWRbHV1Nd27d8fNzQ0As9lMYmIitbW1+Pn5YTKZKCwsxMXFhT59+qBSqRBCkJ2dTVZWFhqNBg8PD0JDQ9HpdGRnZ8vHh4aGUltbS2FhIV5eXvL8/eLiYkpKSvDz88NsNrcbwa62tpbMzEwMBgNBQUE3fM86gry8PIqKiggJCcHZ2bmzq9PCHR/xS5Ik1x/1HBbsFMyqFauuWs/V1dVkZ2dTVVWFj48Pvr6+ckL0c+fOYTAY8PDwACA4OJjjx49z5swZJEkiPDwcNzc3amtrCQkJQa/Xy+XW19dz7tw57O3t0el0lJWV4eHhQUlJCQ4ODvj7+1/TNbYXrbFF5y4uLgQGBl5TmTcLIQQZGRmYTCZiYmJQq9W38vR3vJ4BJEkKR8cWXAi+HhvdYieFEKhUKkJDQ1GpVGRlZSFJEmazmZqaGkpKSqiurqZHjx6EhYXR1NREVlYWVVVV2NnZERgYSHV1NeXl5QQGBtLU1ER+fj4eHh4IISgpKcHV1ZXy8nIcHR1bJVsvLi7GyckJvV5PRESEnF+tRSNms5no6OhbrZE2KSsrIycnB19fXzw9PTu7Oi10CT23EBcXJ06cOMGZM2eor68nKioKnU5ndUzL72Bvb09NTQ0+Pj7U1NRw9OhRAgICKC4uxmw2M3r0aGxsbDCbzXz33XdkZ2czbtw4oqOjqaurIzMzE0dHR0JCQgCwWCxkZGTQ2NiIEAI7OzsrTbaF2WwmPT0djUZDVFTUVeUHLCsro//g/pyrPEewczAH9hxod/1hJ9vKa6ayspKsrCw8PT3x9fW93mK6lKYVFG4WN+QQSpL0K+BRmh+4j4QQ/778GJVK9UuhFW/RAzXjgA3glefFuq/X/WyDw2Kx8Pbbb/PJJ5+g1+tpbGwEIC4ujri4OFatWoUQAp1OR11dnewASpKERqNh8uTJbN++ncrKStRqNfX19Wi1WpqamtDr9UiShMViwWQyYTab0Wg0uLm5YTQa6dOnDw0NDaSmpuLs7IzRaGTEiBF8/vnn2Nvby3U0mUy89NJLvPfeezg5OVFdXU1kZCQfffQR3bt3v+57eyOcO3eORx55hOTkZFxcXCgrK2POnDm89dZbcqLaTuSONs6SJN2Djg0koGc8sB4M5w1sWLvhikEAGhoa+Otf/8q3336LjY0NtbW1qFQqzGYz9vb21NfXA82av7QRIEmSrG8AlUqFs7MzDQ0NLFiwgMcee4z//ve/LF++HHt7e4xGI0IINBoN9fX1ODs709TURFBQEH/605+IjY29quu83CE0mUz87ne/4/3338fZ2ZnKykqio6P56KOPiI+Pv4472TF89913/OpXv6K6uhqNRoMQgldfffVqExZ3BHe6nl11Ot3yRhrH0QOJcSBtlAgoDWD1Z6t/1kYXFhbyu9/9joMHD6JSqbBYLNjZ2VFfX49KpUKv11NXV4fZbMZkMuHo6Eh1dTUAtra2SJKESqWioaEBaNaZWq3GYDBgNBqxWCy4uLhQUVGBxWLByckJo9Eo27GQkBD+9Kc/ER0dzWeffcZ//vMfbGxsaGxsxNXVlXfffZe6ujqeeeYZampqUKlUSJLEq6++yi9+8Yubem/bo7KykoULF7Ju3TpcXV0pKytj2LBhfPzxx3h5eXVKnS7hjtbz5YSEhAhbW1uKioqwsbGhoaGBF154geeee46KigoWLlzId999h62tLUajERsbG1m7arVatsc6nY76+npiY2NJT09HrVajUqmor69Hr9ejVqvl939oaCgzZszgv//9L9XV1TQ1NdHU1IRWq8XX15d3332XUaNGtarr4sWLeemll5AkSX5W/v3vfzNx4sR2ry8zM5NeA3pRHVZNy/vI8awjxw4eIzQ01OrY28BWXjV1dXU8++yzfPbZZ3IHUN++fVm8eDHBwcHXWlyX0rSCws3iuh1CSZLigJVAP6AR2Ag8IYQ403KMSqV6Ah3/lXpKkmWMpfmxFMB68C7wZu1Xa6/Y4HjzzTdZu3YtM2bMwM3NDYvFQmpqKt9//z0Wi4XJkyfTrVs3VCoVJSUlfPPNN3h4eHDmzBni4+M5cuQI06dPl3vlCgoK+PLLL6mtreX+++8nICAAIQTnz5/nq6++wsbGhsjISPr3788HH3xA3759GTRoEDqdjpqaGjZv3oynpyebN2+W6/jkk0+ybds2xo8fj8FgwGw2k5KSwt69ezly5MgtHy2sqKigW7duxMbG0q9fP7RaLdXV1WzZsoWAgAC+++67W1qfNrhjjbMkSb3RkqzqrVJZ6XkDOGc5s/mHze3qedGiReTm5jJ+/HgcHR1pampi//79JCcn8+STT6LX6zl16hTff/+9rN0pU6YQExODSqWiuLiY1atXExcXx9ChQyktLWXdunVyY3nixIm4urpiNptJTU3lhx9+YM6cOYSEhGA2mzl+/Di7du3iq6++IiAg4Gev9XKHcOHChWzfvt1K58eOHSMxMVHuSb/VbNu2jRkzZjBx4kRCQkKQJImLFy+ydu1a/v73v/Pggw/eimrcyXrWaLXaVLWNOrKpW5NkHmO20nSIMYSVy9sfKaytrWXixIn4+Phw8uRJxo8fT2xsLEeOHCExMZGZM2fi7e2NEIIzZ87w7bffMnPmTNzd3fnss8+ora1lzpw5eHl5YbFYyMzMZM2aNcyePZudO3diMBi4++67WbZsGQkJCQwcOFC2xRs3bpQb6Lt27eKBBx5g9erVTJkyRT5nZmambO/uu+++Vhp54403mD9//i2739A8QjNo0CBMJhPDhw/H1taWhoYG9u3bR0FBAcePH7ca+e8E7lg9X44kSb31ev2hKVOmEBUVhUqloqioiHXr1rFo0SK+/vprVCoVw4YNk3+HHTt2cPToUcaNG8fmzZtlTatUKg4dOsS2bduYNWsWQUFBSJLEmjVrKCwsZObMmbi6umKxWDhx4gTff/89EydOJD4+HkmSuHDhAl999RXx8fGcOHGCDRs2cNddd8l1XbJkCf/v//0/Jk+ejJ+fH0IIsrKy+P7771m9ejUjRoxodX2FhYUEhgfS1K0JMVbIz660UUKXpuPC2QvybJMr2crXX3+dBQsW3KJf5eqYOHEiFy5cYNSoUTg4ONDU1ERycjJpaWmkpqZea7TjLqNpBYWbyY2sIYwBDgghaoUQJmAXMLVlpyRJbkIr3rVyBqH573go8Clg9vzZ7a5XqaqqYtmyZcydO1eeIqpSqejevTt33XUX3t7exMfHo1I1X4K7uzuzZs0iIyODESNGcPLkScaOHUtkZKQ84uLt7c3MmTNRq9Xy9ANJkggODmbixIloNBoOHz7MiRMnCAwM5J577pGnl9jb2zNp0iSOHTtGcnIyAAUFBSxfvpz77rtPNlBqtZpevXrRrVs3/vWvf93A7b0+Pv30Uzw9PRk0aBBarRYABwcHJk2aRFJSEseOHbvldeoK/DhNdJvUS1K10vM4qAipYMb9M9rU8+nTpzl48CDTpk3D0dERAK1Wy5AhQwgODubIkSOoVCpiY2MZMmQImZmZDBs2TO7sAPDw8GDOnDkkJSXR2NiIm5sb06ZNIzU1lQkTJsijk2q1moSEBAYMGMDJkyflbT179iQ+Pp5PP/30mq89Ly+PFStWMHXqVCud9+7dm+jo6E7ROcDvfvc7RowYQWhoqPyM+/n5MWHCBF5++WUsFkun1OsOYpZFbYmwcgZB1vQFtwtXtNHr1q3DycmJhoYGBg4cSFxcHEIIdu3aJTuD0GxjIyIiGDlyJHv27EGv11NRUcH9998vj4ipVCqioqIYMWIEO3bsoKamhkmTJnHmzBm8vLwYNmyYlS2eMmUKxcXFeHh40K1bNxYvXsx9991ndc7IyEiGDRuGo6PjbaOR7du3c+HCBcaNGyePcur1eu655x4kSWL16tW3tD5dGb1e/+rw4cPlTjUAT09PpkyZwp///GcKCgoYM2aM1e8wZswYvLy8OHr0KIMGDSIuLk7+7tGjR5k8eTLBwcFIkkRtbS2nTp1i3rx5sv1VqVQkJCRw1113cf78eVlzAQEBTJo0iYyMDIYMGcIf/vAHuZ4Wi4WXX36ZiRMnylOgJUkiLCyM4cOH8/LLL7e6trKyMnr170VjbONPziCABGKsoCGmgV79e8lrCq9kK3//+9/fVrYyJSWFxMREJk6ciIODA9D8vhw0aBCenp588sknnVxDBYWuyY04hKnAEEmS3CRJsqN5wkIAyI3nAySgtmo8t/BjgyPXPbfdBsexY8fw9PTEycmp1b74+HgqKytbbXd2dsbT0xMHBweqq6vp1q1bq2O8vb2xsbGhpKTEantERASlpaX4+vpy6tSpNr+rVquJjIxk27ZtAOzevZuwsLA2p2FGR0ezcePGVttvNuvXryciIqLV9svrrnD1/KjnffTA2erlKx8AjIc8j7w29ZyUlERkZCQaTessL926dSMrK8vq/1VVVcTFxbU61sXFBVdXV/Ly8gBwcnLCy8urzUACl5cLEBsby969e6/uoi+hRec2Njat9kVHR7Np06ZrLvNGaWpq4tChQ8TExLTaFxAQQG1tLefOnbvl9bpT+FHT71oSLCorZ1A+AEyjTVe00Xv27CEqKors7GzZXpaUlKDT6WTH7FJaNFlYWIiDg4M8enH5MRcvXpRHZbKystq1xTExMWRlZeHt7Y1Wq21zumW3bt0oKipqtT0gIIDq6mpycnLauUM3hy1bthAeHi47GS20OM3r16+/pfXpyphMprvb0o67uzsajYaIiIg2f4e4uDgKCgqsdNfQ0EBhYSGRkZHyttzcXPz8/GSn5VLi4uLIzs622hYaGkp1dTXBwcHs2rVL3p6dnU1dXV2b67xjYmJITk6mqalJ3lZWVsbAYQMp8CmAcbTbvsrzymPgsIEUFhbeUbZy27ZtREVFtfm+jIyMZMOGDZ1QKwWFrs91O4RCiHTgdWAzzdNFjwHmH0v9HQYCGU/7g/USNI1sIrc6l/fef6/Vbp1OZ2UEL6WpqandxdBNTU3yupS2vi+EaPP7ZrMZIYS8hqW9c5vNZnlKz6XrGtuqR2dM/dHr9e3W3WQydfZ0pDuTZj2HtvnybaGlAd2Gnn9Oy5e++Fr0eyVdXX58Wy/OtrY3NTW1CqhwNVxJU52lc5VK9bPPuKL1K9Csaac2Ozha+Bkb3aKLS+2lRqOhqamJtpYitByr0WjkQBttHXPp73olW9yi8ZZ14Fc65+VYLJZO0Yher8dkMrW5r6mpqc1OF4VrQ5KkxyRJOiRJkr49+9Dy+7dFi2YutcEtjuOlv93PabOtNobZbMZisVjZ4ZbnqC39mkwm2da18OpfXiWrPIs2O9tbkMAyxkJWeRZ/e/1vd5StvNIz0tjYeFvVVUGhK3FDaSeEEIuFEL2FEEOBcuA0ABb+gpGzbEDQ3hJFAdqtWvwd/Fn4xMJWu3v27El1dTX5+fmt9h04cKDNF+fFixeprq6moKAAg8HAwYMHWx2TmZmJSqWSp6G2cOzYMfz8/CgtLaV3794cPny41TSKuro60tLSmDJlCgAjRowgNzeX0tLSVudJSUlhzpw57Vz8zWPOnDmcOHGiVd1bprdMnjz5ltfpjqdZz1lswHw9eh4+fDinT5+mpqbGuliLhcOHD1v13B46dAg3NzcOHTrU6hQXLlygoaFBnu6cn59PeXl5my/ItnqEW9bGXCsjR47kwoULbY5EdpbO1Wo148aN4+jRo632paenExoa2ioCpcIlNGv6Ahvgem30+PHjOXHiBNHR0Rw+fBhoTqxtY2NDZmZmq+MPHTpEbGwsHh4eSJLUagSl5Zjw8HBOnDhBQ0MDMTExHDlypF1bHB0dTVZWFnq9njNnzrQq7+DBg21G8ExPTyciIgIfH592Lv7mMG3aNNLS0uQgOi2YzWbS0tKYPXv2La1PV0QI8aEQoo9KpVrSVhvg3Llz2NnZkZ6e3qrjzWQyceTIEYKDg2VNQ/OUxdDQUKslF4GBgZSWllJYWNjqHAcPHmwVwCs1NRVfX1/S0tK477775O3+/v6EhISQnp7eqpwjR44wfvx4K+fypd+9RKhLKNqt2p99dkNdQnn5pZfvKFs5adIk0tPT23xfpqamMnfu3E6qmYJC1+aGHEJJkjx//BtI8/rBzwGEEGU0MohjXGA9rY2WAM0WDf4l/u2GN9fpdLz00kt89tlnpKam0tTUREVFBRs3biQ9PZ3i4mI2bdpERUUFTU1NpKamsnLlSgIDA9m/fz/BwcEkJiayY8cOqquraWho4MiRI3z77bfU1NRw4MAB6uvrqaurIzExkW3btlFSUsLw4cMxGAxUVlaycuVKCgsLMZvNZGdn89lnn/HQQw/J0bscHBz461//yqpVqzh16hQmk4ny8nI2bNhAdXU1Cxe2bkTdbKZPn46HhwfffvstRUVFmM1msrKy+OKLL3jiiSc6JfjHnc4les5qswEtQL1Z3a6evby8eOCBB1i+fDlnz57FbDZTXFzMl19+SU1NDZGRkVRWVrJ161ZSU1Nxc3PjyJEjbN68mcrKSpqamjh+/DhffPEFgwcPlgPHfPnll0yePJmvvvqKtLQ0mpqaMBqN/PDDD6SlpeHi4iJrcuPGjZSWljJv3rxrvn5HR0deffVVVq5cKeu8rKyM9evXU19fz+OPP37d9/ZG+Nvf/sbBgwfZu3cvNTU1NDQ0cOjQIbZs2cJbb73VKXW6U/hR0704RnV7mtZu1V7RRt9zzz34+PhQVlZGenq6rNcRI0awZs0ajhw5QkNDA9XV1ezYsYMDBw4wePBgcnJysFgsrFq1imPHjtHY2EhVVRXbtm0jOTmZPn36EBERwbJly7Czs0Oj0bBq1SorW7xs2TKio6M5cOAARqORP/zhD3z33XccPXqUxsZGqqur2bVrF6mpqVRWVrJv3z5qa2upr6/n4MGDnaaR7t27M3nyZFatWkVOTg5ms5n8/Hy++uorunXrxsiRI295nboqjY2Nrxw5coQdO3ZQVVVFY2MjKSkprF27lg8//JBx48ZZ/Q55eXksX76c6upqvLy8OHXqFJs3b5bbGIGBgWzZskXWktlsJiwsjCVLlnDy5EnZ/m7atIm0tDRUKhV1dXXU19dz4MABNm3ahJubGydPnuSPf/yjVV3ffvttNm/ezKFDh2hoaKCmpoa9e/dy6NAhXnvtNatjXV1dSdyZSGhFKNImqc1nV7VJRWhlKIk7E3F1db2jbGVAQABPPvkkK1euJCsrC7PZTFFREWvXrsXNzY3p06d3dhUVFLomQojr/gB7gDQgBRjRxn5XdGTTDzN/QPAKgj8gNAM1IiQqRBw4cEBkZGRc8fPhhx+KwMBAIUmSUKvVwsHBQTz22GPiv//9r/D39xdqtVpIkiR0Op2QJElotVohSZIIDw8X77zzjhg+fLjQaDTyMYAICAgQ3bp1E2q1WqhUKqHVaoWXl5dwdXUVKpVK+Pn5ieeee04sXLhQeHh4CJVKJUJCQsSLL74oLBaLuJw1a9aIXr16CbVaLQwGg1i0aJEoKSlpddytoqamRvz2t78Vnp6eQqVSiejoaLF48eI2694J3JDmOvPzo54z6YfJSs93/byeT506JV577TUREBAg61Sj0ci/kVqtFhqNRqhUKqHT6YRKpRLOzs5W+m7RqlqtFj179hQfffSRyMjIEB988IFISEgQarVa2NjYCDs7OwEIR0dHoVKphJOTk7j//vtFUlLSzz5vLZ/9+/e3+uG++eYb0bNnT6FWq4WLi4t4+umnRWlpaYeI4npJT08XM2fOFDY2NkKr1Ypx48aJ5OTkW1mFTtfljXwAD3QU0a9Zyy2a1g7SXpWNPn78uHjqqaeEm5ub0Gg0soYjIyNFfHy8vK1F74DQ6XRCq9WK7t27i549e1rp32AwCAcHByFJkvDy8hKenp5CkiTh6Ogo69ne3l7eNm/ePFnXn3/+uejbt6/QaDTCzs5O3H///eLs2bMiPT1dzJgxQ9jY2AidTifGjRsnDh48eBOkcHWYzWbx9ttvi9DQUPl98+qrr4qGhoZOq9MldLomO/ITEREhHnzwQWFvby80Go0YOnSo2LFjhxBCCJPJJP7973+LkJAQIUmSsLGxESqVStja2gobGxsBCI1GI9tgHx8f8Zvf/Eb4+PgIlUolfyc+Pl5+/zs7O4snnnhC7NixQ9x3331Cp9MJtVotdDqdsLGxkTXZFsnJyWLcuHFCq9UKGxsbMXPmTHHq1Kl2f6jS0lIRGRcp1HeprZ5d9V1qERUX1co23wa28qqxWCzik08+EdHR0UKtVgtPT0/x4osvipqamusprtN1qHyUz53wuemJ6eWAHD0JYSz6n+t1vp1pL1m3wjVxR4eA7kp6vhKK1q+aO1rP0LU0rej2hrnj9XwpcXFxIjU1tbOrcdNoCTCT7ZxN44hGdNt0hFSEyCODCkAX07SCws3ihqaMXg2iZbrdUbJ5nzu2oaGgAIqeFboeiqYVFO5MWqaPhlSEoF2sVZxBBQWF6+amO4TwU4PDxeSiNDQU7ngUPSt0NRRNKyjcmbQ4hYtmLlKckbT6HQAAqWZJREFUQQUFhevmljiE0Nzg8PLwUhoaCl0CRc8KXQ1F0woKdyaurq68+c83FWdQQUHhurllDqGCgoKCgoKCgoKCgoLC7cUd7xAajUZe+9trGI3Gzq6KgsINoWhZoauhaFrhTqasrIznfv1cmzlYFRQUFLoSms6uwLVQUVGBJEloNBrq6+sBmD1/NhdrL7IrcRcf//djqqqqcHBwwM/Pj7q6OhoaGtDpdDQ2NmJnZ8fFixdxdXXFxcUFaE67UVFRgUajwcHBwep8Qghyc3ORJAlnZ2cqKiqaQ7NKrYNW1dfXU1lZiZubm1US2euhurqa+vp63Nzc2jzX7YjFYqG0tBQ7Ozvs7e07uzq3JUIIOZF8yz1qyQklSRIz580krzaP7bu3859//wetVouvry/V1dUAqFQqnJycKCoqorq6GoPBgJubGyqVdb+OyWSitLQUs9mMu7s7Op1O3teS883R0dFq+83gTtREeXk5kiQp0yavA4vFgtFoxGKxoFKpkCSJWfNmcbGu2T6vXLYSvV6P0WikqqoKT09PHBwcqKioQKfTUVdXh9FoxNXVFXd3d6uy23p2WqisrKSmpgYbGxssFgslJSXY2Ni0sueX0tjYiNFoxMXFBa1We03XWVNTQ11d3R1ln6Fj31FdgYqKCiwWi9wWuPy9m5OTw/Axw8mpymH95vVs/mEzRUVFuLu7ExQUhCRJWCwW0tPTMZlMxMbGotVqr6itoqIiysvLCQsLQ6P5+eaXEILS0lJsbW2vy4bW1dVRXV2Nq6vrFX9zIQRlZWXodDocHR2v+Ty3I01NTZSXl+Pl5aUTQjR2dn0UFG57fi4vBfAJUASkXrLNFdgCZP741+VqclxER0dfdR60Sz9LliwR3bp1E3q9Xmi1WvmvpJcEfX/Mn9UXgQ6hUqmERqMRNjY28l+1Wi20Wq2cE0ij0QhfX1/x61//WkRERAhbW1uh1+tFnz59xOrVq0VGRoZ47rnnhIODg5xXS6/XC41GI2JiYsQ333wjWigqKhLz5s0TdnZ2wsnJSbi7u4tXX31VmEwmca2kp6eLsWPHChsbG2Fvby9CQkLE0qVLr7mcW4nFYhEffPCBCAgIEA4ODsLGxkZMmDBBnDlzpr2vdHqulY76XIue33jjDREUFCTs7OyEXq8XvXv3Fr169RJ6vb45P6YOay1raaVbrVbb6v9OTk7ilVdeEadOnRInT54UTz75pLCzs5OP0ev1YsKECWL37t1i/vz5cj43R0dHMX/+fHHs2LGrzkN4LZr4z3/+I/z9/WVNTJ48WWRnZ193mTebrVu3ip49e8o5yPr27St27dp1NV/tdB125Od6bPSpU6fECy+8INzc3IRer5dtrKS7xD73Q+gd9VY6bjmu5TstmlWpVMLT01MsXrxYZGRkiH/84x9Wz86gQYPE999/L5YsWSIiIiLkXHF6vV7+2NjYiNGjR4uTJ09a/VjV1dXil7/8pXBycpI/zz33nKirq/vZHzozM1Pce++9wsbGRjg4OIjAwEDx0UcfXY1GOpVrfEd1ugY78tOtW7dWF7hnzx7Rv39/YWNjI2xtbUV0dLT8f3t7e+Hn5yfCw8OvaJPt7OzEkCFDZO22aDo0NFQ4ODgIJycnYTAYxPPPPy/q6+vFxo0bhY+Pj6x5W1tbMWfOHNHU1NTmb2axWMRHH30kAgMDZRt67733itOnT1/hl/6J3NxcMWPGDGFrayscHR2Ft7e3+Oc//9lmLuLVq1eLqKgoYWdnJ2xsbMQ999wjjh49elXnuR2pr68Xzz//vDAYDMLJyUmo1epanU73EeAobgNNKh/lc7t+fjYPoSRJQ4FqYJkQIu7HbX8HyoQQf5Mk6YUfHcL/93POZ0xMjFi7du01OaxJSUk8/fTTjB07lqioKABSUlJYt3EdUk8JMVY0Z5kRIG2UcM5ypun/s3fecVFd6f9/32l0GKp0ATsdBezEXmMSEzWaYkxd8/2aTc8m23676bvZZMs3m2JiisZoosbeO8FeUVARBaRJn6HDwMz5/YFMHAcUCyLkvl+veSnn3rn3nDufe855TnmemgZiYmI4duwYw4YNY8CAAajVai5cuMCaNWuIiooiPz+frKwsHnjgAXr27InJZOLkyZPs3LmTiRMnsmHDBh544AG6d+9OQ0MDR48eZfv27YSGhpKbm8vHH3/MlClT6N+/P56engwZMgQHBweKiorYunUrw4cPZ8GCBW0uZ1ZWFnFxccTGxtK/f3/UajXZ2dls3LiR3//+9zz33HPX9dxuF++//z4ff/wxEyZMwN/fH4PBwOHDh0lOTubo0aP4+fld+ZXOM6R+Ddqq56VLl/Lxxx8zadIkgoKCzHratWsXY8aMYd2WdRAFTMKsZTaCOkXN7FmzCQgIoKqqih07dpCSksKQIUMYPHgwGo2G3NxcVq1axZw5czh//jzHjh3j7rvvxtPTk6qqKnbv3s3p06cBCAoKYsyYMWi1WvR6PTt27MDOzo5vvvnGapbxZuK5/fWvf2XBggWMHz8ef39/6urqOHToEKmpqRw/fpxu3brd0HXbi61btzJjxgzGjRtnrmNOnz7N1q1bWbNmDQkJCVf7epfRM9xYHf33v/+dLVu2MGnSJHx8fDh69ChrN61F6i9hGm/6RdMbwDnDmblPzkWv17Nq1SoCAgKYMmUKlZWV7Ny5k4KCAh599FGOHz/Ojh07eOyxx1i9erXFu3Ps2DESExORJIlJkyZZ/Gbr169HoVAwatQoGhsbOXDgAAcOHKBnz54YjUYSEhKora1lxIgRuLi4oNPp2LlzJ15eXmzZsqXVGb/c3Fz69+9PdHQ0sbGxaDQacnJy2LRpEy+88AKvvvrqTT759qGqqor+/fvj5eVlbqMKCwvZunUrd911F19++eWVX+lSer4yDuHevXuZPHkyo0aNIiwsjIqKCr744guGDBlCXFwcGo2Gc+fOsWT5EkxRJpiIRZ1se9qW6fdNZ+XKlTQ0NNC3b19Gjx6Ns7MzpaWlbNiwAYVCwUMPPYROp2PHjh04Oztz+PBhJk+eTFhYGAqFgvT0dFatWkVsbCyJiYlW+f7ggw/417/+xYQJEwgICMBgMHDkyBGOHTvG0aNH8ff3b7XMZWVlREdHExISwqBBg7Czs+PixYts3ryZBx54gH/84x/mcxctWsRLL73ExIkTCQkJobGxkeTkZJKSkkhKSiIsLOwW/hrtjxCCe+65h6ysLEaNGoWbmxsVFRVs3bq1Pi0t7bTBYIgTQjR2dD5lZO5ErrmHUAiRCFy5gP5e4NtL//8WuO/WZusX/v73vzNhwgRCQ0NRKpXU19ez59AeFP0VvxiDABKICYLykHJMShNVVVUMGDDA3HGWJImgoCBmzZrFgQMHuP/++3F0dEStVqNQKFCpVMTExDB48GB++uknHn30UYKCgpAkCY1Gw6BBgxg8eDBpaWncfffdvPbaa3zzzTdoNBrGjh1rXs7h5eXFtGnTWL58OefPn29zOd977z3CwsIYNGiQOb/du3dn2rRp/PnPfzYvkb2TqKys5N1332XatGkEBAQgSRI2NjYMHTqUXr168dFHH3V0Fjscg8HAv/71L6ZPn05wcLCFngYMGMD6reshml+MQS79OxFMkSZWbVhFTU0Njo6OTJkyBR8fH1xcXLCxsUGSJAICAnj00Uf59NNP2bZtGw8//DCenp4AODo6MmnSJLy9vVGr1fTs2dO8FFKr1XLvvfeSk5PD/v37b1l5dTod//jHP5g+fbq502Jra8vw4cMJCgri3//+9y27163i1VdfZfz48eY6RqlUEh4ezujRo3n99dc7Ont3NMXFxSxdupSZM2fi4+NDTU0N67estzQGoenfSVDRo4IFixag1Wp57LHHSE1NpaqqCicnJ6ZMmYJarebcuXMMHjyYQYMGsWjRIqZNm2bx7gwcOBCNRsOkSZOsfrPJkyfj7OzM7t27iY2NJSoqinfeeQeAzZs3k5eXx5QpU3BxcQHA1dWVe++9l1OnTrXYMW/mgw8+oE+fPgwdOtT87gUGBjJ9+nTefvtt87LuO41vv/0WW1tbizaqW7duTJ8+nWXLlpGRkdHBOby9/O53v2PEiBFERkaiVCrZv38/0dHRDBs2DBsbG2pra9m0YxPE8IsxCOY6ua5vHWs3r6W+vh5PT0/uu+8+nJ2dAXB3d2fWrFkUFxebt6bcd999pKSkEB8fT1RUFCqVCoVCQZ8+fXjggQc4dOgQJ0+etMhjVVUVb731FtOnTycwMNDcrg4ZMoQ+ffpYGHQt8dlnn+Hl5cXIkSOxs7MDwMfHhxkzZvD5559TUFAAgNFo5LXXXuO+++6jR48eSJKEWq0mNjaW+Ph4/vrXv97CJ397OHDgAIcOHeK+++4ze1x1dnZm6tSpNq6urj2BKR2bQxmZO5cbdSrTTQhx8dL/C4B2GfLX6XRkZmbSt29fAGpqaliwaAH6IL1lZ6OZS0ZhfWg9yaeTzSPHl+Pp6YmrqysXL14kKiqKs2fPWh13dnbGy8vL6rvR0dGYTCZUKhUGg4HvvvuOfv36WZ1nY2NDv3792LBhQ5vLunbtWiIiIqzSPTw8cHd3v6Wd9lvFzz//jJ+fn3kPxuWEh4ezatWq25+pO4yUlBScnJys9FRTU8Op9FOISGHZ8WhGAuN4I/ogPQsWLaCmpgZJkhgwYICVZpv3Enp7e1vtC5QkiaioKOzt7UlPT7c4plQqCQ0NZfv27bequOzatYugoCBzJ+lywsPDWbly5S27162guLiYc+fOtVhXhIWFcfToUSorKzsgZ52DvXv30qNHDxwcHKipqeGLb7/AGGFstX5mIui7N2lakiSCg4PNRkmzVpv1HRMTgxDCaka5pqaG6upqc7twOf369aOkpASVSkVRURGRkZGsW7cOgFWrVtG3b1+r2XClUknfvn1Zs2ZNq+Vcs2YN4eHhVumurq74+PiQlJR0rUfVIaxcubLVNqpv377X1UZ1dmprazlw4IDF75ienk5UVBTQtv4Fk6A8uJxGRSP9+vWzmlFWqVRERESYNaxSqYiMjKSllVjNRtjixYst0vfs2YOvr2+r7eq1ZvBXrlxJaGioVbq9vT09e/Zk69atQFPbpFAoWpxtjIyM7JTaWLt2LX369LHan6lQKBgwYICjjY3N9A7KmozMHc9NexkVTTVdq+tOJUl6RpKkw5IkHb5ZT3OJSYno0GEcZ2x9YYsEpvEmhIvg0OFDN3U/GZkruVV6TkxKpFxRbjkzaHUzMI4zokNHYlLrsxcyMjfDbdf0+Fuj6Wttd5D5dXK5nnU6XZu/19b+hZggEC6Cc+fP3ZoMy8jIyNwB3KhBWChJkg/ApX+LWjtRCDFfCBErhIi9Xs99rq6uBAcHc+bMGQAShiXgiivKLcrWTdBLewltam2ws7WzOlxcXIxOp8PHx4fk5GR69+5tdbyiooKiIusiHT9+HIVCQWNjIxqNhkceecS8P+ty6uvrOX36NJMmTWpzWadMmWK1dKQ5P2VlZQwaNKjN17pdDB8+nLy8PFpqdFNSUrjvvvtuf6bamevVc3h4OJWVlRQWFlqkJwxLwKbWBjZwVS0rtyhxxZWEYQkIIThy5IiVZvV6PaWlpRQUFGAwWDpTE0Jw/Phxampq6NWrl8Uxo9HIqVOnGD169DXL0VZGjhxJVlYWFRUVVsdSUlKYOnXqLbvXrcDT05OePXuSlpZmdSw1NZX+/ft3Ga97rXEzdfSQIUM4f/481dXV5vqZjbRJ07H9Y8nMzCQkJKQ5HxZ18rFjx5AkyerdafZa29Jvdvr0aTw8PGhsbMTLy4sTJ05w9913A3Dfffdx5swZTCaTxXeMRiNnzpzhnnvuabWc99xzD5fvRWtGp9Nx8eJFhg8f3up3O5KpU6e22kadOXPmutqozsLler58ls3Ozo6BAwda/I69evUiOTkZaHv/QrFZAXqor6u30lJjYyMnT540a7ixsZETJ060uDf1/PnzCCF45JFHLNKHDh3KxYsXW21X77333quWf+rUqZw6dcoqvaamhnPnzjF27FigqW0SosmT+pWcOHGiU2pjypQppKWl0dhouU3QZDJx5MiRqvr6+mUdlDUZmTueGzUI1wCPXfr/Y8D1eSG4Dl577TU2bdpEamoqNjY2PP7w49il2bXckW6urI9DdGg0J06cYN++fRgMBoQQZGVlsWTJEgYOHMhPP/1EVVUVBoMBk8lEY2Mjx44dY9++fdx///0sWrSIrKwshBAYDAb27dvHvn376NOnD+vWrePvf/87c+bMwWAwsHXrVqqrq4Emt9LLly9n2rRp9OjRo83lfOONN0hNTbXK74oVK/jrX/+Kra3tLXumtwonJyd+//vfs3z5cnJychBCNO3x3LOH9PR0XnrppY7OYoej0Wh44YUXWLZsGZmZmWY9nThxAlOdCcfzjq1qmY3gdN6JJx99EpPJxNq1a7l48SLl5eXU19cjhCAnJ4dFixbx7LPPMmbMGBYvXkxxcTHQtBdlw4YNFBYW0tDQwLlz58zx4HQ6HatXryYgIOCWDjZotVpeeeUVli1bRm5uLkII6urqSExMJCsri+eff/6W3etW8cEHH7B582ZOnTqF0WjEaDRy8uRJtm/fzt/+9reOzt4djaenJzNnzmTp0qXo9XqefPRJHM+1rmnFZgXaLC2Tx07mxx9/JCwsDEdHRyorK1mzZg0NDQ307NmTffv2sX//fmbPns3y5cst3p0DBw5gMBjYsGEDqamp5t8sJSWF9evXU1FRwV133WV2bvWHP/wBgAkTJuDn58fatWut3oPQ0NCrOg969dVXSUtLY8+ePeZ3Lzs7m2XLlvHHP/7xjg2r8thjj1FXV2fRRhUWFrJs2TJmzJhhNsZ/Lfztb39j165dnDhxAqPRyKBBgzh+/DhJSUkolcom/aa3rl9pk4TTeScc1A6UlpayevVq8+BXaWkpS5YswcPDAz8/P8rKyli1ahXh4eEcPHiQ5ORkGhsbMZlMpKWlsWLFCuLi4qyWIjs6OvLHP/6RZcuWkZ2dbW5X9+7dS1paGq+88spVyzh37lyKiorYuXMntbW1AOTn5/Pjjz/ym9/8Bm9vb6BpqfTf/vY3Vq1axfnz5zGZTDQ0NHD48GEOHTrEX/7yl1vxyG8rAwcOJC4ujlWrVpljR5aXl7Ny5cp6nU53DljbsTmUkbmDuZYbUmAJcBFoAHKBJwF3YDtNYSe2AW5tcWl6M2EnwsPDzaEfbGxsLF1C/8XaNfSNhJ2Ii4u7ZtiJ0NBQsXLlStHMrQ47MXHixE4ZduJy99hy2Ilrh52IjY0VAwYMsA45cYWWVSrVVcNOuLi4WISd+N///V/h4OBgEXZiypQpIjExUTz22GPCyclJODo6CicnJ/HYY4+J5OTk2xJ24r777rvjw07079/fHHYiPj5eDjtxHWEn3njjDXPYCYVC0aKmpYGSWdM3E3Zi2LBhLYadsLW1tQg7MX78+BbDTsybN88ccsLFxeWGwk44ODh06rAT77zzjhx2opWwEz4+PkLjoLlqndzWsBOvvfaaOeyEr69vm8NOCCHMYSccHBzMYSfS09NbPf9ycnNzxYwZM24o7MSoUaM6fdiJ11577cqwE/ORw07IH/lz1c81w07cSm7EpfnlNAemV6vVFBQU8OxvnyXXM5eGMQ2ot6nxLfLl7T+/jY+PD35+ftTV1VFXV3dTgenz8vIAcHFxobS0lLFjx7YamL6ysvKaAWDbQmcNTF9WVtaWALqdo0Bt4Hr1LETLgemLiop49vlnyfX4Rcs+BT58+P6H9OnTp8XA9NXV1Wi1Wtzc3FoNTG8ymXB3d7+hwPQ3E3aimebA9A4ODtjb29/UtW4XNxCYvsvoGW6ujm4OTC+EoKKiwkrT/iX+fPvFt5hMJovA9BUVFebA9DqdDnd3d9zd3S2u3dK708yVgel79eolB6ZvgTa2UZ2nQG3gyrATl3NlYPrLf1edTseghEFccL2AYbQBzXYN3XXd+fTfn9KjRw9zYHohBKdOnbquwPR6vZ6QkBA5MH07c1lgehshB6aXkbkmncogvBK9Xs/M2TPJrcrF39GfpQuXXk9H7rq5FZ1kma7T4biVer7dWr4WstbbTJfRM3R+Tcu6vWm6lJ6vZhBei7KyMoaMGEKGLoMQ1xD27tprDmUg06noUpqWkWkvbtrLaEei1WpZunApD497uMM70DIyN4OsZZmuhqxpmc6Mm5sbe3ftZd6MebIxKCMj0+W59pqFOxytVssbr7/R0dmQkblpZC3LdDVkTct0Ztzc3Pjow486OhsyMjIy7U6nniGUkZGRkZGRkZGRkZGRuXG6lEGo1+t57/33uJngyjIyHYWsX5mujqxxmc5EWVkZL738kjmEgYyMjExXpcsYhM0ODBZvWczM2TPlDodMp0LWr0xXR9a4TGei2anMxz9+zJARQ2SjUEZGpmtzrbgUwFdAEZByWdp0IBUwAbFtjXHR1hhX69evF+PHjzfHpXJzcxMKhUI4ODiIsWPHiri4OHO8KrVaLQAhaaRf4gbFIdAgvL29xWeffSa+++470bdvXyFJkjle1d133y327NkjTp06JX7/+98Lf39/oVAohIeHh3B3dxdKpVIAwsbGRqjVajFjxgyxbt06cTXy8/PFM888I5ycnIRSqRSDBg0SGzduvOp37gSaYwn27t1bKBQK0a1bN/GnP/1J1NTUtMftOjzWyq36XE/Mtu3bt4t7771X2NnZCaVSKby8vIRarRYqlUq4ublZxm27LJ4mYI6TqdFozJp0dXUVkiQJjUYjFAqFCAkJEe+88444c+aMSExMFCNGjBC2trZmzatUKuHq6iqeffZZcfz48Wvmt7U4hPn5+eLpp5+20PimTZtuShC3gvLycvHKK68IDw8PoVAoRFhYmPjuu+9ux607XIe38tNWTaemporf/e53olu3buaYgkqlUgwePFh8//334u9//7sIDg4WkiSZY7mitta4vb29+Mtf/iLefPNN4enpKQBzfM1XXnlFnDp1ynzPDRs2iAkTJpjr5NDQUOHm5mbWuIODgzme4ZQpU8Tx48etfqyysjLxwgsvCFdXV6FUKkVUVJT48ccfb1YD7Up9fb14++23hZ+fn1AoFCI4OFj85z//EUajsT1u1+EavJWfPn36iLlz5woXFxehVCpFfHy8uR03mUzis88+E7169RKSJAl7e3tzTEE7Ozsrvbp5u4k33nhDODo6ChsbG7PuwsPDxeTJk4WdnZ1Qq9Vi7NixYt26dea+gEKhEHZ2dkKhUIiYmBjx008/tfjgTSaT+PLLL0Xfvn3NsTh///vfi+rq6lZ/LJPJJL799lvRr18/c//ltddeE5WVlRbnlZSUiHnz5gmtViuUSuVV83GnodPpxIsvvijc3NyEUqkUkZGR4ocffrieS3S4DuWP/OkMn2uGnZAkKQGoAhYKIcIvpfW7ZAx+DrwihDjcFuOzLS7N09LSePTRRxk4cCBqtZqff/6Z8ePH07t3b9LT01m9ejWjR48mMjISk8nEwYMH2b13NyJKwCSaHAwLUGxWII4K1KhRqVSMGzeO0NBQDAYDBw8e5ODBg7i4uDBgwADOnDnDyJEj8fX1pbCwkC1btqBUKpk5cyYZGRmsW7fOHAMoOTkZLy8vq3wXFxczYMAAAgMDiY+Px97enrNnz7Jjxw7++c9/8uijj7blEXUIL7zwAqtWrWLEiBEEBgZSUlJCUlISWq2WHTt2tCle0nXQZVxAt9VFf15eHtOnTyciIoLu3buzbNkyhg4dSkREBF9++SV1xjoaIxoxjTeZ9ctGcM1y5YlHnyAvL49169YRFhaGyWQiLy+P8ePH4+/vT3FxMTt27KC6uhohBKNGjWL9+vXU1tYyYcIEs+YPHTrE4cOH8fPzw8nJiW+//faq8ddact9fVFTEgAEDCAoKIi4uDnt7e9LS0tixYwf//ve/eeSRR27yid4YtbW1DBkyBIVCwZAhQ3B1dSUzM5MdO3bwm9/8hj//+c/tefsuo2dom6aFELz44oukpqZSUlLCwIEDiY2NRaVSkZqaytatW3FycmLcuHEEBwdz8eJFFi1dRH2/eqs6WnVShTAIHBwcuOeee+jevTulpaXs3LmTnJwcRowYwYcffkh6ejqPPPIIcXFxxMTEoFAoOHnyJDt27GD69Om4u7uzd+9ec/tx7tw59u7dy9atW4mLiwOa4rsOHDgQe3t7hgwZgrOzMxkZGezYsYOXX36ZV155pf0f8HViMpmYPHkyFy5cICEhAS8vL/Ly8ti1axcJCQl8/fXXt/qWXUbPkiS529nZlcTExBAfH4+jo6O5TX7//fdJTk5mzZo1jBw5koCAAEpKSti4cSN5eXmoHdTU963HON5oUSdzHGwkGyZOnEhoaCj19fUcPHiQAwcO8Nhjj+Hh4cHRo0fZuXMnsbGxZr2dPXuWzZs3ExoaSkZGBn/4wx/47W9/a5HfV199lR9++IGRI0ea34OkpCQcHR3ZtWtXi/X1n//8Z7766itGjRpFUFAQOp2OPXv2oFAoSEpKwtbWlvLycuLi4nBzc2PQoEE4OTlx7tw5duzYwZ/+9CfmzZt3O36OG6K6upqBAwdiZ2fH4MGDcXFxMb+zL730Eq+++mpbLtNlNC0j055cc8moECIRKLsi7bQQIq09MvSPf/yDIUOGEB8fz65du5g1axZhYWGo1Wr27dvH3XffTXx8PLa2tgCcTDsJMfzS0aDpX9N4E1J/CQMG7r77bqKjo9FoNDg6OjJq1Cji4uJoaGjg559/ZubMmQQEBKBUKvH19eWRRx6hoqKCnJwc+vTpwxNPPEFJSQm+vr58+OGHrebb19eXsWPH4uLiglqtJiwsjGnTpvHSSy9hMNyZcVHPnz/P119/zcyZMwkODkapVNKtWzemTp1Kbm4utzJu5K+V//73v4SHhzNixAj279/PXXfdxdChQzl+/Dg1DTUYI4y/GIPQ9O9EqAip4JvvvyEwMJDHH3+c5ORkUlNTmT17Nt27d0epVOLt7c2DDz6IyWRi0KBB/PjjjxgMBqZNm2ah+ZEjRzJgwAAcHBwoKytj69at112ODz74AD8/P8aMGWPWeHh4ONOmTePFF1/sMI0vXLiQ+vp6pkyZgoeHB0qlkp49ezJr1iw++OADiouLOyRfXZXjx49z+PBhXFxcGDhwIHfddRcODg7Y2NjQu3dvTCYTjz76KD179qS+vp6V61fSGN7YYh1tjDAi1AJ7e3tCQkJQKpV4eXkxffp03Nzc2LVrFykpKXz44YcMGjSIoUOHYm9vj62tLXFxcUyePJkdO3bg4uLCxIkT6dGjB8ePH2fgwIGMGDGCl156yZzvL7/8EqVSyeTJk3Fzc0OlUtG7d29mzpzJX//61ztyCevWrVtJTU1l2rRp+Pj4oFQqCQwM5MEHH2Tt2rWcPHmyo7N4x6JUKl/s3bs348aNQ6vVolKpCA0NZfr06bz00kt8++23zJw5k6CgIHO7B6Bx1FDf7zJjEMx1MlFg49Sk8+Yg7qNHjyYuLo7ExERsbGyoqakhPDyccePGWfQFZs2axcmTJ5k+fTp//OMfqaysNOf1woULfP7558yaNcviPbjvvvsoKipixYoVVuW7ePEi//znP5k1axY9evRAqVTi4eHBPffcQ1VVFUuXLgXgk08+wcHBgYkTJ+Lq6opKpaJv3748+OCD/OEPf6Cqqqqdf4kbZ8GCBUiSxOTJk3F3dze/s7NmzeLNN99Ep9N1dBZlZLoMd9QeQoPBwL59+4iJiSEnJwetVouPjw8AlZWVFBcXExoaCkBNTQ0LFi1AH6RHTBDWY0CXOhxEwZadW6ipqbE4PGDAACoqKoiMjESj0VgcU6lUREdHc/r0aQBcXV3x9fXFxsaGH3/8scW8L1u2jOjoaKt0Hx8fnJ2d2bt37w08kfZn1apVhIaGYmdnZ5GuUCiIiIhgyZIlHZSzrsOWLVvo378/jY2NnD9/npiYGGpqati9bzemKJNlx6MZCYzjjeiD9CxYtAA7Ozu6deuGn5+feTCkGaVSSUxMDBkZGQQGBqJQKOjRo4dVPmJjYzl9+jSRkZGsX7/+usuxbNkyYmJirNJ9fX1xdnZm3759133NW8HSpUuJjIxEkiwfopOTE7169WLdunUdkq+uyqZNmwgPD+fMmTPExsZaHDt79iy9evXCycnJoo6+msZNkSYully0qKMVCoV5AGPjxo0kJSW1qL1+/fpRWlpq7lwPGDDAXG9HRERw5MgRs6G3ZMkSoqKirHSi1WoJDg5m8+bNN/lkbj0//PADoaGhKJVKi3QbGxv69evH8uXLOyhndz4qleqR5tnhy+nWrRsajYa+fftatHt6vZ6s/Czq+tRhHNeyXpkE1T2rWbBogYVe4+LiyMzMBODUqVO0dF8fHx+0Wi1VVVUEBASwbds287HVq1fTr18/7O3tLb6jUCgIDw9vsR1et24dffr0wdHR0TKbkkRERATff/890KShqKgoq++7u7vj5+fH9u3brY7dKSxZsqTFut3FxYWQkBA2btzYQTmTkel6tLtBKEnSM5IkHZYk6fC1RmCNRiPQ1MFtbGy0MNSMRiMqlQqFoinLiUmJ6NC1XHGbbw5MggplBYlJiRaHmq9tY2PT4lfVajWNjY0W55tMJurr61s8v76+vtUleGq1utXvdTQGg8Gqs9GMWq2mrq7uNufozuZ69NxMQ0MDarUak8kENA04JCYlYnS6YmbQ6mZgHGdEh47EpETUanWrv5VGo6GxsRGVSoVarbZqQKHp9zQajWg0mhvSo8FguCM1XldX12q+VCrVHfvu3Slcr6YNBgMqlQqj0Wj13C9Pa2sdbRpvQmiFVR3dfJ36+npMJlOLS9cVCoW5vWj+TvP/FQoFCoXCPHPdGevouro6qwHLZlQqlVw/t0CznoUQvq09O0mSrLSQtDcJtLQ8eGH+YtPx5jq5mcvr95bei8vPa2xstNJbfX19q1szWmuH2/qd+vr6VjV0o23B7eJqeb9T31kZmc5KuxuEQoj5QohYIUSsVqu96rl2dnb06dOHs2fP4u/vz8WLF80jv87Ozmg0GrKzswFIGJaAK64otyib1ve3eHNgAzgbnUkYlmBxKDU1FUdHR06ePGmuyC/LM6dOnSIkJARoapQvXLiAJEmMGzeuxVuNGTPGPDJ9ORUVFeTl5TFo0KCrlr2jGD16NOnp6WZj/HLOnj3LpEmTOiBXdy7Xo+dmBg4cSGpqKhqNBm9vb9LS0kgYloBtnW3TvpSr6Fe5RYkrrsTHxpOTk0NhYaGVXqFJz927dyc7O5uamhqKiopaPCc4OLjp/gkJVsevxZgxYzh16pRVekdrfNKkSZw9e9YqvaGhgbNnzzJ69OgOyFXn4Xo1PXToUNLT0wkJCSE1NdXiWLO+Ghoa2l5HbwRFhaLFOrq+vp7hw4cTFhbGmTNnrL6enZ2NRqPBxcXF/J3mejsjI4OAgAA8PT0BmDBhAmlp1jsd6uvrSU9PZ+TIkdcs++1m0qRJpKenW6WbTCbOnTvXanv0a6ZZz8B3LS2praqqorKy0qrdGzViFMpKJYrNiqvqVbFZgSuuFnpNTU01r2YKCQkhJSXF6qsVFRUUFBTg6enJ+fPnLergMWPGcPbs2Rbb4fT09Bbb4VGjRpnftSs5e/YsEydOBJp039K7U1tba5WPO42JEye2+s6ePXv2jnxnZWQ6K3fUklGA559/ns2bN1NQUEBcXBxLly6ltLQUhULBXXfdxYoVK8jNzcXe3p4nH30Sh3QH2IB1BX6poyGdkKABs2FpMpk4c+YM27dvx2Aw4O7uzqZNm6itrQWaKpotW5qWmPbr1w+9Xs/ixYtxdXUlNTWV119/vcV8v/HGGxw5coQTJ06YO+ylpaWsXLmS5557ztxhudOIi4sjKiqKdevWUV1dDTTNACQmJlJeXs7s2bM7OIedn3nz5vHzzz9z5swZEhISWL9+PYWFhTw1+ymk4xLSJqlF/So3K9FmaZl+73RWrlxJWFgYrq6urF692rxcyWAwsGPHDkpLS8nKyjIvr/nhhx8oLCwEmjTf7PzF2dmZ4uJi7r///usuR7PGLx9EKS0t5aeffuL555/H2dn5pp7TjTJ37lwuXLjAgQMHzLNDFRUVrFq1igkTJtCrV68OyVdXZcSIEdjZ2WFjY8O2bds4e/Yszc7JGhsbUSgULFu2DKPRyJOPPok2U9uqxqVNEhyHbq7dzJpq3tudkZGBr68vw4cP54UXXmDLli1kZGSY75WXl8fKlSsZMWIEACdOnODgwYMMHjyY7OxsNm3axNtvv22eLf/tb3/L2bNnOXTokFkn5eXlrFy5kmnTphEQENDuz+56mTZtGiaTiR07dphnQ2pqati4cSMBAQGMGjWqg3N452IwGN47cOAAycnJZkOrrKyMn376if/93/8lMjLSot1TqVT06t4LcVS0bBReGmDmONwz4R7s7e3N/Ylt27YxduxYAHr16sWePXus+gI//PADkZGRbNiwgUceeQRfX1/zpZsd36xZs8a8p6+hoYGkpCRKSkqYM2eOVflCQ0MZPXo0q1evNvdvGhoa2LdvH3l5eTzzzDMAvPjii5w6dYqjR4+an4Ner2flypU8+uijeHt734Kn3T7MmzePc+fOWb2zq1at4v777ycoKKhjMygj05W4lhtSYAlwEWgAcoEngamX/l8PFAKb2+LStK0uzf/v//5P+Pn5CXd3d+Hk5CTUarXw9PQULi4uwtfXV2i1WuHk5CTs7e2FWq22DDnxF8vQE3PmzBGvv/66cHBwEM7OzsLOzk7Y2tqK7t27i+XLl4tDhw6JyZMnCwcHB+Hn5ydsbW2Fra2t2fW5SqUSNjY2ok+fPuLLL78UV2P//v0iOjpauLq6Cn9/f+Hq6irefPPN9nIPfsuoqqoSTzzxhHB0dBSBgYHC0dFRjBs3TmRnZ7fH7Trcte6t+lxP2IlvvvlG9OjRQ7i6ugqtVitsbGyEVqsVWq32qvp1cnISKpXK7NrfxcXF7Hbfzc1NqNVq4ejoKOzs7MTMmTNFcnKyWLJkifD29hZqtVo4OTmZNW9rayuGDRsmdu7cecNhJ1rS+FtvvdXhGj979qxISEgQzs7OIiAgQDg5OYnnnntO1NfXt/etO1yHt/LTVk0fOHDAHALCzs5O2NnZCa1WK9zc3MQf//hH8cgjjwg7Ozvh6up6zTr6rrvuEvfdd5/QaDRCq9UKjUYjbG1txciRI8WhQ4fM9/zkk09EQECAcHd3F15eXsLR0VGoVCrzO2FjYyMcHBxEt27dhL+/v/j++++tfqzU1FQxePBgC528/PLLwmAw3KwO2o2CggJx9913W9TPDz/8sCgvL2+P23W4Bm/lJyQkRPTv319otVrh7+8vtFqt+H//7/8Jo9EoqqqqxOOPPy4cHR3N9WVzSAmLMECX9CoNlIS91l6oVCqhUqmEs7OzsLW1FU5OTsLb21t4eHgIHx8f4eXlJX73u9+J6Oho4eLiYn4Hmvstv/vd70RDQ4PVg6+pqRFPPfWU+Xd2cnISY8aMEVlZWa3+WHV1deJ///d/zd9xdnYWI0aMEOfOnbM4Lzk5WcTHxwsXFxfh7+8vnJ2dxeuvvy4aGxuvroY7gFOnTomhQ4davLMvvvji9byzHa5D+SN/OsPnmmEnbiVtddMPTbMamZmZmEwm/Pz8yM7OxsHBgYCAAIxGIxkZGZSUlJj3hfzlnb+Q3y2fxrGNKDcr6XaxG0sXLTV7DmtoaODMmTMUFxfTq1cvq9FgvV7PxYsX6datG66urhw8eJCioiJ8fHzo1q0bAQEBLbrib4nMzEwqKyvp3bu3lQOQOxm9Xs+FCxfo1q1be44adhkX0NejZ2gafLlw4QL19fUEBQWRm5uLyWTCzc2NGQ/P4KL3RYzjjKi3qfHK8+K3z/4WGxsbs0v/8+fPYzQaCQkJQaPRcPHixaaXWJLw9/e3ci6QmZlJWloa3t7eaDQaPDw8WgyZ0hLX0npGRgZVVVV3nMbz8vIoKSkhJCQEJyen23HLLqNnuH5Nl5WVUVBQgMFgMHsKbd7XVFVVRU5ODpWVlQgheOPPb1DoW2iuo12zXVn5w0qzJisrK0lNTcVoNBIaGoqrq6vV/YQQZGRkYDKZCAkJobGxkf379wMQHx9vdprUt29f837zlsjJyaGsrIyePXuaQwrd6RQVFZGfn09gYCBubm7tdZsupefw8HCRkpJCVlYWFRUV9OrVy8qBWnO75+bmhl6vx8bGBjs7OwYNH0ShbyHGcUY02zUElwezd9dejEYjycnJZGdnExYWRnx8PNC0TLOhoYG+ffua34HmvoCtrS21tbX06tXLynHMlZSXl5OZmUm3bt3My1CvRUVFBZmZmXh4eODn59fqeRcuXECv17cpH3caze9sjx49rNq6a9ClNC0j017csQbh9aLX65k5eya5Vbn4O/qzdOFS2rrHq6201SCUuSpdpnK+lXq+Hfq9HmStt5kuo2eQ62iZrqXnZoPwRigrK2PIiCFk6DIIcQ1h76697WmIy7QfXUrTMjLtxR23h/BG0Wq1LF24lIfHPdzhnWkZmetF1q9MV0fWuExnws3Njb279jJvxjzZGJSRkenytOyzuJOi1Wp54/U3OjobMjI3hKxfma6OrHGZzoSbmxsfffhRR2dDRkZGpt3pMjOEMjIyMjIyMjIyMjIyMteHbBC2Eb1ez7/+8y/Kyso6OisyMu2KrHWZzoisW5nLkSTJ7WLhRVkPMjIyMm1ANgjbQLMzhOW7lzNkxBC5gZHpsshal+mMyLqVuRxJktzQsKdMWSbrQUZGRqYNXNMglCTpK0mSiiRJSrks7QNJks5IknRCkqSVkiRp2zWXHUifPn0YOHwgmc6ZND7VSJptGn0j+soNjEyXoyWth0aFylqXuaNZvHgxA4dZ6tbd253S0tKOzppMByBJUi5qSomiL3MhzTYNTz9PLl682NFZk5GRkbljacsM4TfAhCvStgLhQohI4CzQJb0E9OnTBzQgxUgwiSbnxZOg2K9Y7ijLdCla03qhTyHhMeGy1mXuSFatWsWb778JMVjolmjw8PGQdfsrQ5KkctT4EY2FHkyRJvyC/CgsLOzYDMrIyMjcoVzTIBRCJAJlV6RtEUI0XvpzP+DfDnnrUF599VXQgKK/AjFB/BLJ5rKOsrwURaYr8OKLL15V6xe7XZS1LnPHodfr+d0ffwfRwESsdEs0BPQIkHX7K+HSMlFnC2OQS/9OBBEtiI6LlvUgIyMj0wK3Yg/hE8DGW3CdOwa9Xs+ajWsgGkzjTdZhTS91ODJdMuWOskynRq/Xs2HrBlnrMp2K5j2DVsZgM5d0W9OrRtbtrwBJktxQk0sUlsag+QRgIhT4FMh6kJGRkWmBmzIIJUn6A9AILL7KOc9IknRYkqTDer3+Zm532/j0s0/BlZY7Gs1IYBhtIEOXwdvvvH0bcyfTkXRGPV8NWesynVHTn372KblVuS13/pu5ZBTKuv0VoOAPuGJ3TT1MlPUgIyMj0xKSEOLaJ0lSELBOCBF+Wdoc4DfAaCFETVtu1q9fP7F69eoby+ltRK/XM2j4IESUaL3DIUCzXUNweTB7d+3Fzc3tdmezs9Jac93p6Cx6vhp6vZ6BwwfS6sg6yFq/Ol1Gz9B5NN08Q5jpnHlV3bIB+tT1kXXbdjqlni8tFz1GFIFX04Nis4Je1b1kPfy66JSalpG53dzQDKEkSROA14B72moMdia0Wi17d++FZJoWw15pM4umdLmDLNPZ0Wq17E/cL2tdplOh1WpZunApyhQlbKBl3W6AXjVy5//XgBCiDAMxHOeqegjSB8l6kJGRkWmBtoSdWALsA/pIkpQrSdKTwMeAE7BVkqTjkiR91s75vO24ubnx4NQHsWpgmkeda+VRZ5mugaurKw9MeUDWukynQqvVsnfX3lZ165ThxP7E/bJufyUIIcpowLs1PQSUBnBozyFZDzIyMjIt0BYvo7OEED5CCLUQwl8IsUAI0VMIESCEiL70mXs7Mnu7efPNNznw8wFUKSpzA6PZrpGXIMl0Od59911Z6zKdDq1Wy4GkAwTqAn8xAjY2LRPNOpsl6/ZXhhCikAbcOU5psx4UmxX0qe3D8UPHZT3IyMjItMKt8DLapdFqtezZtYfgimBUX6rkpXMyXRZZ6zKdEa1Wy7LFy8y6lWe0f91cminsTTJn+IymPYO7ZT3IyMjIXA3ZIGwDzftVpt01Te5oyHRpZK3LdEZk3cpczqU9hUPdjG6yHmRkZGTagGwQthGtVssLv31Bblhkujyy1mU6I7JuZS5HCFHm081H1oOMjIxMG5ANQhkZGRkZGRkZGRkZmV8pndIg1Ov1vPf+e3SWIMoyMi0h61imqyJrW+bXQFlZGS+9/BJlZWUdnRUZGRmZm6LTGYTNAYkXb1nMzNkz5Q6HTKdE1rFMV0XWtsyvgbKyMoaMGMLHP37MkBFDZKNQRkamU6O61gmSJH0F3A0UCSHCL6W9BdwLmIAiYI4QIv9mMyOEIDExkSVLlnDx4kVCQkJ47LHHUKlUzJ8/n0OHDqGr1iEiBcyEzI2ZDBkxBA9nDzQaDWq1Gp1OhxACrVbL9OnT6dOnD0uWLOHYsWMYDAYAPDw8+N///V+mTJmCJEkAnDt3jm+++YaDBw9SV1fX9HBUKlQqFf7+/syYMYOgoCDeeOMNNm/ejI2NDQ899BBPPPEEDg4ObSpffX09CxcuZOHChVRWVjJy5Eief/55goKCbvbR3ZEcPnyYf/7zn6SkpODr68v//M//cM8990hCiCvDBndZDAYDa9asYdWqVVRVVREbG0tsbCyv/v5VDKEGs45HTxyNo8aR6upqlEoldnZ2uLu7ExgYSHJyMjqdDgAnJyeio6NJSUmhsrISOzs7xo8fz9y5c3F3dzffc+XKlfz0009cvHiR2tpahBA4Ojpy//33M3v2bLRabbuWOz8/n//85z9s3rwZW1tbHn74YZ544gns7e3b9b63g7KyMj799FNWrlzJqVOnTtTX1y81mUyfCiF0HZ2320FaWhrffvstqampuLu7M2zYMNLT0zl16hRqtZq0jDQLbQ+5awh2KjtcXV2Jj4/nyJEjlJaWYmtry4QJE7C3tycpKYmamhoqKipoaGjAxsaGUaNG8dvf/hYPDw/zvZu1vWLFCvLz85EkCY1Gg62tLUqlkp49e/L2228THR0NwNatW/n444/Jysqid+/evPDCCwwdOrTVsiUlJfHvf/+bs2fPEhQUxLx58xg7dmx7P9LbjhCCjRs38sknn5CTk0NYWBjPP/88AwcO7OistQsmk4kVK1Ywf/58ioqK6N+/Py+99BIREREcO3aMt99+m71792IwGPDy8mLmzJnk5+dz4MABFAoFer2eoqIiAOzs7HBycuJC/gVMkSZ4EtI2ptEvqh+D+g8iKyvLQjs6nY6XXnqJ9evXYzAYCAgI4B//+Afjx49vMa8XL1401502NjbMmjWLJ598sk39jL179/Lvf/+bM2fO0L17d+bNm8e4ceOszqurqzP3Raqqqhg1ahTPP/883bt3v7kHfZspLi7mv//9L+vWrUOpVDJ9+nSeeeYZnJ2dOzprMjKdDulafXNJkhKAKmDhZQahsxCi4tL/fwuEtiUWYb9+/cTq1atbPf7++++zYcMGBg4ciKenJ3l5eeZKWghBo9SIMdIIEwEJc4wh29O2CIMgODiY8+fPM2TIEPz8/Dh48CBZWVloNBoCAwMZMGAAkiRx7Ngxzp49y4QJE/jb3/7Grl27eO211/D29iY/P58ePXqQnp7OwIEDCQkJQafTsX//fnQ6HVFRUfTt2xeDwcCJEyeQJImff/4ZFxeXq5a9traWMWPGUFpaSkxMDHZ2dpw7d46UlBQ2btzY5Rrir776ildeeYX4+Hj8/f0pKSnh8OHDFBcXzzcYDHO7glF4LT3X19fz5JNPotPpGDBgAA4ODuzfv59T6aeQ+kuICcKsYzaC4zlH7pt0H/n5+ezZswelUklDQwP9+/cnNDSU2tpa9u/fT3FxMZIkcffdd2NjY8Px48fJzs7mhx9+oFu3bsyZM4fKykpiY2Oxs7PjzJkzHD9+HG9vbwoLC3FycmLZsmV069at1bzrdLob1mRKSgojR46kd+/e9O7dG4PBQHJyMiqVisTExE7dWOfl5TF48GC8vLwIDQ0F4OjRo7Vnz57VNzQ0xAkh8jo4izfFtTS9efNm/vSnPxEbG0tQUBA6nY7ExEQ0Gg0RERFs2bkFYrDQtrRJwvm8M3HRcezbtw+tVsuECRPIz89n9+7duLm5MXToULZs2YKnpydxcXGoVCqSk5PJzMzkxx9/JCgoiLq6OubMmYNOp6O4uJhevXpRXV1NeXk5Q4cOxc3NjQsXLnDkyBE++eQTTpw4wVdffUVcXBzdunUjPz+fQ4cO8cYbb/DSSy9Zle2jjz7ivffeIy4uDl9fXwoLCzl06BBPPPEE7777bjs+9dvP888/z/Lly4mLi8PDw4Pc3FwOHTqEXq+fazQaP+/o/N0qwsPDxYkTJ3jooYfYv38/AwYMwNXVlaysLI4cOcLs2bP55ptviIuLIygoiLKyMrZv305dXR3x8fH07t2bqqoqkpKSKC0tJT4+Hjc3N9ZsXIOIFhZ9ETaAQ7oDU++eil6v59ChQ8ycOZNvv/0WHx8fYmNjkSSJ48ePc+bMGf785z/zhz/8wSK/p06dYsSIEfTs2ZM+ffpcVz/jP//5D2+++Sbx8fH4+vpSVFTEwYMHeeyxx/jb3/5mPq+mpobRo0ej1+uJjo7Gzs6O9PR0UlNT2bx5M3Fxce3zY9xiMjIyGDp0KIGBgfTr1w+j0UhKSgpVVVXs3bsXT0/P5lOljsynjExn4ZoGIYAkSUHAumaD8IpjbwCBQohnr3Wdq3U2Tpw4wdy5c3nqqaews7Mzp+t0Ov773/+isFU0jTo3V8DNCFBuUeJ4zpG6ijpmzpzJsmXLePHFF1Gr1XzyySeEhIQwYcIEi/vt3r2bgwcP8p///IeXX36ZCRMmsGrVKh5//HG++eYbZs+ejY+Pj/l8g8HA/PnzGTNmDH379m26tRCsW7eOESNG8I9//OOqZf/b3/7GokWLeOCBB1Aoflmpm5qayvHjx0lLSzPPVnZ2SkpKCA4OZs6cORaj+3V1dXz88cfVVVVVdwshdnVcDm8N1+o8f/3116xatYoZM2agUCiorq7mw/98CDFgGm9qUcfaLC1PPvokFRUVfPnll0yZMoWoqCjzaSaTiaVLl6LT6YiIiCAhIQGAPXv2UFVVxeDBg9m8ebOVzlJSUkhMTCQkJITs7GwiIyP597//3Wreb8YgjI+Px9vbmwEDBvxSPCFYu3YtY8aMseicdDamT59OcXExI0eOtEjftm1b46FDh9bW1dXd30FZuyVcTdO1tbUkJCQwc+ZMfH19zekNDQ3Mnz+f0orSa2r7wakP8uWXXzJnzhx8fX2pqKjgs88+o1evXqjVaiZPnmxRD+7duxedTsd3333H559/zubNmzEYDAQFBeHp6cnWrVt5+umn0Wg05u8UFBTw3XffoVareeqppyxmVvR6PQsWLCAlJYXAwEBz+oULF4iIiODJJ5+0mD2vrq5mwYIF7Nixw+I97Mzs3buX++67jyeeeMKirS0tLeXTTz+ta2xsDBJCFHZgFm8Z4eHh4q233uKFF17g0UcfRa1Wm4/l5+fz1Vdf8fjjj+Pn5weA0Wjk3//+N/feey89evQwn2s0Gvn222/p168f23/eTmN4Y6t9keY6XAjBf//7X3r27Mn991tWCzt37uTAgQNkZmbi7e1tTh88eDAeHh7Exsb+ctk29DNyc3MJDQ210m9NTQ1ffvklW7dupX///gC8++67LFmyhPvvv9+qjUhJSeHUqVOdoi8yYcIETCaT1Yz/5s2bCQ0N5csvv2xOuvMLIyNzB3DDewglSXpHkqQc4GHgzzebkRUrVphHqy7HxsamdWOQpr+N44xU9azCpDJRWlqKt7c36enpGI1G9Ho9w4YNs7rfoEGDMBgMfPrpp3h6elJWVkZoaChFRUX4+/tbGIMAGo2GoUOHkpycfPkzYPDgwXz77bfXLN+CBQsYOHCgRQUMEBoaSlVVFceOHbvmNToLy5cvp3fv3hbGIICtrS1Dhw61t7GxeaaDsnZbWbFiBYMGDUKhUFBTU8P8r+djijJZd5jBrGN9kJ4Fixbg7OxMQECA1TUVCgVDhw7FZDJx4sQJc3p8fDzHjx9n2bJl5nteTlhYGA0NDfTu3ZuSkhJ27txJbW3tLS9zRkYG6enp5iV75uJJEoMGDWrTu3KnUlNTw/r16xk0aJDVsSFDhqgaGxsnS5Jk18JXuwQ7d+7E19fXwhiEJoOwtrEWU+S1tf3Dyh+IjIwkMTERAGdnZyIiIjh16hTDhg2z6ojGxcWRkpJCcXGxuY3Izs4mLi6O5ORkBg4caGEMAnh7e+Pr60u3bt2sltlptVrCwsJYvHixRfr3339PWFiY1VJqBwcHoqKi+Prrr6/zad25LFiwoMW21t3dnb59+wpgRsfkrH344osv6N+/v4UxCODr64ufn595OT40DQw4OjpaGIMASqWSuLg4tidupzGsBWMQrOpwSZIYMGAANjY2VnkaPHgwjY2NFvXhhQsXOH36NDExMZaXbUM/4/vvvyc0NNRKv/b29kRHR1vo96uvvmq1L6LT6SzalTuV0tJSfv755xZnM4cMGcKSJUswmUwdkDMZmc7LDRuEQog/CCECgMXAvNbOkyTpGUmSDkuSdPhqzgXKyspaXA6RmJRIg0NDyxWw+SZNFXGjYyMpqSm4uLhQW1tLY2MjQogW197b2NhgY2ODXq/H2dmZ2tpaXFxcqKmpaXVZRvN1r0wrLy9vtVzN6HS6Fq8rSRJarZbS0tJrXqOzUFpa2up+BxcXF0mhUHi3eLAT0FY9A5SXl5t/88SkRCpUFW3SsQ4diUmJuLm5tWi0ubi4YDAYqKmpMaep1Wrs7e2pqKhoVWcuLi4IIRBCoFKpLL5/qygrK0Or1aJUKq2OabXaTu1gpKqqCrVabdWRhqaOl0KhEEDbNhTfQbRV08115ZUkJiVSY1MDk2iTtktKSyx07eLiQkNDQ4vXvlzXFRUVaDQa7Ozs0Gg01NbWtroX1sXFpUUNAjg6OlJSUmKRVlJSgqOjY4vnOzk5mfePdQVKSkpaXbbt5uZmB7jf3hzdWi7Xs06no6SkpNU23dXV1UKLzf2Alkg/l06jU2ObdZ6YlIirqysNDQ1Wp9na2qJWq8nP/8X1QnMfqCXdXqufUVJS0mqb6+zsTHFxsfnv1voiCoWi0/RF9Ho9jo6OVoNB0PR+GwwGs88IGRmZtnErvIwuBh5o7aAQYr4QIlYIEXs1RxaRkZFcuHDBKj1hWAKKCgVspGmdfos3AeVmJVK5xOBBg8nIyMDHx8fcecjNzbX6SlFREQ0NDcTExJCVlUW3bt3M38vIyGhxdOn8+fNWM4fnz58nPNxqJa0VMTExZGRkWKXX1dWRk5NDRETENa/RWejfv3+LzxwgPT29zmAw/Hybs3TLaKueoWnEtfk3TxiWgNakhQ1cXcdblLjiSsKwBNLT082OYi4nIyMDJycnCy2WlZVhMBjo169fqzorKCigsbERBwcH7Ozs2sWxTPMMZGVlpdWxtr4rdyru7u7Y2dlx8eJFq2OXOnaVQKdzNdhWTYeGhpKZmWlVNyYMS8CmxqbN2jYZTeYletCkZ1dXVzIzM62+ptPpqKurw8/Pj379+lFSUoLBYKC0tBQfHx/Onz/fUnnIyspqtUOYm5trsSQPIDY2ttU6Kycnp0vt8Y6PjycnJ6fFY2lpaZVAp16ucrmemx0ZtdS3MJlMnDt3zmLJpre3N9nZ2TQ2Nlqd7+7mjqZGc111eFpaWosDSAUFBZhMJovVSz179kSn01FRUWF1/vnz5wkLC2u1zLGxseTltbx9OTs7m/j4ePPfUVFRLbYRtbW15OXlXfU+dwoBAQE0NDS0aLxeuHCB7t27Y2tr2wE5k5HpvNyQQShJUq/L/rwXOHOzGXnggQfIyMjg9OnT5jQhRJMzCpMK1UlVyxXxJWNQc1pDN9duZGVl4erqiq+vL5WVlRiNRtauXUtVVZX5K7W1taxZswaFQsFzzz1HcHAweXl5VFZWkp+fj729PTt37rTo+GRlZXHo0CGLfSR6vZ5du3ZZbQxviddff52kpCSLkbqGhgY2b97Mvffea9EodXbGjRuHWq1m7969Fs/w7NmznDx5stFoNH7Wgdm7bTz11FMkJSVRVFSEvb09T895Gs0pTcuDG5ftP3nikSfYv38/dXV1HDlyxKJzUlxczM6dO9Hr9QwePBhoMvZWrVrFo48+yty5c0lMTLSYAWloaGDdunX07NmTHTt2oFQqeeqpp1qdQbkZnJ2dmTNnDps2bbLokOt0uja/K3cqSqWSV199lc2bN1NdXW1Or66uZtWqVdUmk+ldIUSXXacUFRWFj48Pu3btsnivi4uLoYE2aTs+Op6CggLuuusuhBAcOXKEoqIihg8fzsaNGy06w3V1daxcuZKHH34YW1tbnnnmGfbs2UN4eDhr164lIiKC5ORki86tyWQiMTERb29vysrKSElJ+SUbQnD48GGqqqqs9nTdf//9VFVVcfjwYZr31QshSElJIScnh8cee+zWPcgO5umnn+bcuXOcOfNLsy2EYP/+/ZSVlemA9R2Xu1vP888/z7FjxyyMQpPJxO7du1EoFJw7d86sZ3d3d9zd3Vm3bh1Go9F8/sWLF9m3bx8z7puB3Vm7q/ZFmvcQZmRkkJeXx9mzZy36HzU1NaxZswZHR0emTp1qTndycuKJJ55g48aN1NfXm9Pb0s+47777qKmp4dChQ2b9QpOPguzsbB5//HFz2u9//3uSkpKs2ojNmzczderUqzobu1PQaDT89re/ZdOmTRYzvJWVlWzbto033nijA3MnI9M5aYuX0SXACMADKAT+H02LJvrQFHbiAjC3Ld71ruWE48SJEzz33HPY2NiYvYza2NigUCgoLCyk2lAN0fyyZOOSd0YpWcJR40hjYyNGo5GAgACEEOTl5WFvb09jYyN1dXV0794dSZLIysrCxsaGzz77jLi4OMrKynjuuefM+w4VCoV5aV337t2pqalBr9fTs2dPzpw5Y/acmJmZyf/7f/+PV155pQ2PGr788kteeuklAgMDzZ69Ro4cyeLFi7uEO/7Lyc7OZsqUKRQVFREYGEhpaSnV1dUUFBQME0Ls6ej83QqupWeAlStX8vbbbxMQEGD+zasMVU2hUy7X8QZQpijp1b0Xubm5GAwGXF1d0el0SJJESEgINTU15OfnmzsvwcHBKBQKLly4wN13381bb72FUqnkxx9/5G9/+xteXl5oNBqysrKwtbWlqqoKpVLJQw89xO9+97urOg64GacyBoOBJ554grVr19KrVy/zu/Lmm2/y4osv3tA17xSEELzyyivMnz+fXr16UVVVVZWZmamSJOmThoaGVzq799xrabqkpIR58+aRk5ND9+7d0ev15ObmotFoCAoKIuVsirW2NzYZi/Yqe2pqarCxsaF79+7k5+dTVVWFJEn07t2bvLw8Kioq6N69O0qlkqysLCZMmMB7772HStUUIenHH3/k/fffx9bWlsrKSry8vCgqKsLV1RVvb29yc3MJDg5mzZo1FBQUcO+996JUKvHy8iI/Px8HBwfWrFlD7969rcp29uxZ7rnnHqqrq81eGo1GI6tXr7ba19XZ2b9/P/fffz92dnZmL6Nubm6kpKSECCGsp2o7KeHh4SIlJYXNmzfz8MMP4+7ujouLC1lZWfTo0YPPPvuMxx9/nIyMDPz9/SkrK6O0tBRJkrCxsaFXr14UFRVx8eJF8/JEPz8/zl04h4iyrsNVKSoi+0VSVlaGyWRi5cqV/Oc//+H7778nKCgIhUJBRkYGWq2WvXv30rNnT4v8GgwGnn76aVauXGnRz/jzn//Mq6++etWypqenc88991BZWYmfnx9FRUU0NjayatUqCwdfAPPnz+eVV14xz6Slp6czatQoFi9e3OKM5p2I0WjkueeeY9GiRfTu3Ruj0ci5c+d4+eWX+ctf/nJ5+yY7lZGRaQNt8jJ6q2hLB9poNLJ3714KCwsJCgoyV2TJyckkJiay6IdFTQ5kxptQblbiesGVWdNm4e3tjYODA/n5+eTl5REaGsro0aPRarUcOnSI1NRUTp06hUqlYtCgQUyePNncyWjm1KlTpKamUlpailarpbGxEY1Gg4eHB8OGDaO6uppu3bqxa9cubGxsmDhx4nUvu6usrGTTpk1UVVUxZMgQ+vTpc13f70w0jzqfPn0aHx8fxo4di0ql6jKVc1v0DE0zSD///DPV1dVER0fj7u7O1BlTueh9ETFBoNyiJKA0gHsn3kt2djZ+fn74+PigUqkYPHgwe/fuZfv27RiNRsaOHcuwYcNITEwkOTkZf3//FmeYq6qqSExMpLCwEL1ej06no3fv3owfP/5yd9ytcjMGYTOZmZns3r3bHG+uvWMf3k4KCgrYunUrs2fPng1s6SpeGduq6ZSUFM6cOYObmxvDhg3j7NmznDlzBo1Gwz8//icFPgWYxptQbVXhdM6JIXFDGDBgADNmzGDVqlUcOXIEf39/Hn/8ccrLyzlw4ADQFKolNTUVLy8vpk2bZrVEH37RdvMSaA8PD1QqFQaDAR8fH+bMmWPuDBqNRnbs2EF2dja9evVi+PDhVx0IaY6Fe+7cOQIDAxk1alS7zKTfCTQ2NrJt2zby8/Pp06cPQ4YMQeoM7iWvg2aDEJqMrU2bNlFSUkJUVJS5byGE4ODBg+zYsYPCwkLi4+O5++67yc7O5uDBg7i4uKBWq1m3bh11dXWEhYXh4eHBH/7yB4r8ihATBKqtKnpU9OCDdz8wD4Jerp38/Hz+9a9/UVZWxt1338299957VR1mZWWZ+xkTJkzA1dW1TeUVQvDzzz+Tnp5+Tf1WVlayceNGqqurGTp0aIuDJJ2B3Nxctm/fjkqlYvz48VbO7JANQhmZNnHHGYTXQq/XM3P2THKrcvF39GfpwqW3raN5KzrJMl2ncr4ZPXekjtuCrPU202X0DHIdLdO19Hy5QXirKSsrY8iIIWToMghxDWHvrr24ubm1y71kbooupWkZmfbiVjiVua1otVqWLlzKw+MevuM60TIybUXWsUxXRda2zK8BNzc39u7ay7wZ82RjUEZGptOjuvYpdx5arZY3Xpc3Dct0bmQdy3RVZG3L/Bpwc3Pjow8/6uhsyMjIyNw0nW6GUEZGRkZGRkZGRkZGRubWIBuEl9Dr9bz3/nudOnC2jMzlyJqW6WrImpa5lZSVlfHSyy9RVtbpwofKyMjI3FJkg5BfnCAs3rKYmbNnyp0NmU6PrGmZroasaZlbSbNTmI9//JghI4bIRqGMjMyvmk65h7CZn376iQULFlBRUYGXlxdBQUEcOXKEmpoa1Go1w4cP5+WXX2bXrl189tlnlJeXI0kSzs7OGI1G6urqUKvVlFWV0RjeCDMhZ0sOM2fPZOnCpRiNRpYvX86RI0dwcXFhzJgxdOvWjQ8//JDNmzfT0NBAnz59iI+P5+TJkzQ2NnL33XfzyCOP4ODgcNuew5kzZ/j0009JS0ujZ8+ezJ07l/Dw8Nt2f5lbT0VFBR999BG7d+/GYDCgUChQKBQYjUbUajWBgYFotVqKi4s5f/489fX1NDY2Ymtr2xRXrCiXhrAGmAnZm7N58NEH+WHRD2YHH83u+NetW0dFRQUKhQKTyYSPjw/Tpk0jODjYnJeamhqWLFnC6tWrUSgUzJgxg2nTppnjct0OioqK+OKLL9izZw9ubm7MmTOH0aNHX9V1u0zH0uzOf9GiRZw9exaVSkXfvn3x9PRkx44d6HQ61Go1cXFxzJkzh5UrVzYHR0cIgUKhwMbGhjFjxqBQKFi2ahkN4Q1W9XRtbS1Lly7l1KlTODs788YbbzBkyBAAiouLeeaZZ9i5cydCCAICApg/f775+O3i+PHjfP7552RlZREaGsrcuXPp1avXbc3DrxGDwcBrr73GyZMnCQwM5JlnnmHAgAGUlpYSMzCGXI9cxP2CtI1peAd6Myx+GGPHjiUjI4Pt27dTXl6Og4MDvr6+ODk5UV1dTXFxsTme5t133824ceNYsWIFBQUFRERE4Orqyt69e9FoNEyfPh0HBwcWL15MZWUlI0aM4Mknn7RwQFNXV8cPP/zATz/9hCRJ3H///cyYMQNbW9sWy3ThwgU+/fRTc9ihp59+mvj4eItz6uvr+fHHH1mxYgVCCKZOncrMmTNbveadzuHDh5k/fz45OTlERkYyd+5cizZKRkbm5mlLYPqvgLuBIiFE+BXHXgb+AXgKIUqudbNb4dK8mdmzZ3Py5EkGDx6Mu7s7GRkZHD9+HH9/f+Li4qiqqmLfvn3U1NRga2vLkCFDcHJyIj09ndOnT2M0GnF1daWkvAQRLWAi5gCz0iYJnwIfqvXV9OrVi+DgYKqqqjh8+DCVlZWYTCbCwsIIDg5m9+7dqNVqBg4ciFKp5OzZs9TU1JCUlNRiDK1bzTfffMMLL7xAdHQ03t7eFBUVcezYMd577z3mzp3b7ve/AbpMD/5W6vlysrOzmTp1KhqNhkGDBlFSUkJycjIDBgwgICCA/Px8Dh48iKenJ6WlpYSEhFBYWIidnR1arZaUtBSIATFBWAQH717WnR8X/4i9vT2/+c1vyMvLIzIyEhsbG06ePEleXh4xMTGcOnWKSZMmsXDhQoqKihg+fLi5M28ymUhNTcXZ2ZkdO3bg7Ox8y8t/JUeOHGH8+PGEhIQQFBREVVUVx48fZ+zYsXz99dcoFB260KHL6BlunaaFEPzlL39h48aN1NfXEx0dTffu3SkoKGD//v3Y29szaNAgHB0dOXDgABcvXiQqKorc3FwkSSIuLg61Wk1ycjKZmZkYlUaIxqqe7pbfjWp9NeHh4QQEBKDX6zl27Bhz5sxh1qxZDB48GEmSiI+Px8fHh5ycHA4fPswf//hH/vSnP910OdvCRx99xNtvv01MTAweHh4UFBSQnJzM/PnzmTFjxm3Jw3XQZfQsSdK9Go1mVXx8PH5+fpSUlHDs2DHmzp3Lf7/4L+XB5RZ6YgOQDN5u3pSXl2NjY4NWqyUmJgYhBIcPH6aoqIgBAwYQGBhIXl4ehw4dorGxkdjYWLy8vNixYwfdunUjJiaGhoYGjhw5gk6nIyEhAScnJzIyMsjJyWHHjh2EhYVRVlZGQkICRqORfv36AU3xkDUaDYmJiVYeejds2MBDDz1EeHg4fn5+lJWVcezYMebNm8df/vIXoGkm/a677qK+vp5+/fohSRKnT59GoVDw888/dzpvqG+//Tb/+te/iImJwc3Njfz8fE6ePMmiRYuYMmVKWy7RZTQtI9OetMUgTACqgIWXG4SSJAUAXwJ9gQG30yBcvnw57777Lv/zP/9jMRN34cIFfvjhB1588UXUajXHjh0jKSmJ3/zmNxazGampqWzatInK+kqkGOmXjnMzlzrQjucc+Z+n/gd7e3ugabRx/vz59OzZkwkTJrB161bKy8u5//77LTqlO3fuxMXFhfYwFi4nLy+Pfv36MXv2bItg42VlZXzzzTccO3aMkJCQds3DDdBlKuf2MggnTpxIfX09c+bMoa6ujv/+97888cQTeHl5mc/R6XR8+umnjBgxgvLycurr6xk0aBCff/U5Un8J03iTlaalTRJB+iDGjxzP7t27mTZtmkXQ4j179nD+/HmmTZvGV199xbJly/j000/Jz89nzJgxv1xKCNatW8fgwYP5v//7v1te/ssxmUz07NmTAQMGWMx6GwwGFi9ezPvvv8/MmTPbNQ/XoMvoGW6dprdt28Zbb72FXq9n9uzZ+Pr6ApCcnMz+/ft5/PHH0Wg01NXV8a9//YtHH32Us2fPUlhYyIwZM8z1aU1NDR/8+4OmAY7xLdTTG8A505m5T8w119M1NTV88803GAwG6urq+M1vfmMR2Lt5tvnChQvtPmh36tQphg4dyuOPP46Li4s5vaCggMWLF5ORkdFSIO2OpEvoWZIkF5VKlf/444/b+/n5mdOLior4dMGniKjLBoGbuaQnxUkFni6eBAYGMmnSJPMqBCEEa9asQaVSMXnyZABKSkr44osvsLW1xcfHBy8vL0aNGmW+pMlkYsWKFbi5uTF69GgAjh49SkZGBidOnODxxx8nLS2N8ePHW9xn06ZNRERE8MUXX5ivVVVVhb+/P9OmTSMgIMAi/ZtvvmHt2rUMGjSIp59+mhMnTjBx4kSLa27ZsoVevXrx7bff3spH3a4cPnyYCRMmMGfOHJycnMzpeXl5/PDDD+Tm5lqkt0KX0LSMTHtzzaF1IUQi0NLi+n8Cr9FUjd5WFixYwLBhw6yWZXbv3h1fX1/OnDkDwMmTJxk1apTV0rbg4GCqDdUQhbUxCE1/T4Ta3rUsWLSAmpoaADQaDaNGjaKwsBAhBMeOHWPkyJFWMxSDBw9m+/bt7b4nYdGiRYSGhloYg9DkCjsiIoKvv/66Xe8vc+spKCjg4sWLjBgxArVazcmTJ+nXr5+FMQjg6upK//79qa6uJjk5mUGDBrFwyUKIwdoYBJCatJ7rkcsX335BbGyshTEIMHDgQAoKCjAYDMTFxfGf//yH9evXM3ToUMtLSRLDhw9n4cKFmEym9ngMZvbs2UNjYyNhYWEW6RqNhvj4eD755JN2vb/MjbF06VK8vb3p0aOH2RgEOHbsGAkJCeY6OTU1lZCQEPz8/Kzq05qaGj7/+nNElLA2BqHp70lQ3avaop62t7dnwIAB1NTUEBMTY2EMAnh5edGvXz/efvvtdit/M19++SVRUVEWxiCAt7c3vXv3ZsmSJe2eh18pM0JCQsTlxmBNTQ0/rPyhZWMQzHoyRZgo1BUycOBAiyXpkiQxcuRITpw4gdFoBMDDw4OIiAgaGxvJzMy0qisVCgUjRozg2LFj5rTo6GiKioo4dOgQy5cvZ9iwYVb3GTZsGEuWLMFgMJjTf/rpJwIDAy2MQQBHR0f69+/P559/jsFgYMmSJQwfPtzqmkOHDmXFihXU1tZe77PsMD777DNiYmKsjD4/Pz+CgoJYvnx5B+VMRqbrcUNrrSRJuhfIE0Ikt+HcZyRJOixJ0uFb5QSgsrKy1VFVDw8PKisrr3peYlIiJq0JJtH62JEExvFGdOhITEq0ur7JZKK2trbF5Re2trY4OztTXFx83WW7HnJycloN+uzq6kpubm673v/XSHvo+XKKioowmUxm3V5N615eXlRUVNDY2MjxE8epta1teYDDnHloGNOA0cnImbNnrA6rVCq0Wi1VVVV4eHiQnZ2Nvb09dnZ2VudqtVrq6+vbvXORn5+Ph4dHi3sFPTw8yM/Pb9f7/xpoD00XFhYiSRLu7u4W6Vfq+fK/rzyWmJRIhbKi5c67OfNgHNdyPa1UKlt9d7y9vcnKyrqhsl0POTk5rS7Rc3FxkevodkCSpGeAv3Tr1s1ixDgxKREdumvqiUmAFg4fPWx1uHmJ/OWGmqenJxqNBnt7e2xsbKy+4+7uTlVVlXnwTKFQ4OnpSXp6OiqVCkdHR6vvODk5oVAoqKioMKfl5+dbDSw04+bmRm5uLpWVlUiS1OKsmaOjI2q1mvLy8lYKf+eRm5trVYc04+LiItf/MjK3kOs2CCVJsgd+D/y5LecLIeYLIWKFELGtGS/Xi7e3NxcuXGjxWHZ2tnnGzNPTk+zsbKtzhg0ZhqSXmvYMtDa/KUC5WYkrriQMSzAnX7hwwdzZaM3oqqioMC/vaE/Cw8MpKCho8djFixeJiIho1/v/GmkPPV9OQEAACoXCrFsPDw9ycnJaPDcjIwNPT0/s7e3p06sP9vX2sJGralq9TY26Wk1QYJDV4draWsrKynB1dSUnJ4eYmBgMBgM6nc7q3Pz8fNzc3MzL9NqL0NBQsrOzzSPyl5OdnW01cyhz/bSHpnv27InJZLLS7pV18uV/X3ksYVgCLiaXG6qnc3NzaWhoaPXdOXfunJUjjvYgMjKy1U5rQUGB7PyrHRBCzAdeyMjIqLw8PWFYAq64XrOOZANIeomIMOv2s7CwEI1GY2H4ZWdnU1NTQ01NjXkw+nJycnLw8PAwz3w367J5lUZJifVum6KiImxsbCxmt/v169dqe5+fn09kZCRarRZbW1uKioqszikpKUGhULRqYN2JREZGkpeX1+KxgoIC875LGRmZm+dGZgh7AMFAsiRJWYA/cFSSJO9bmbGr8dJLL3Hw4EGryvHQoUPU19fTo0cPoKkz2ezNrhkhBIcOHcLVwRXphIS0SbJuHC7tIdSc1vDko0+aO716vZ6dO3diZ2eHEIKBAweyefNm6urqzF81Go1s27aN2bNnt7un0YcffpicnBzOnj1rkX7+/HnOnz/PY4891q73l7n1uLq6EhUVxfbt26moqCA8PJzc3FzzMuhmMjMzSUtLo7q6mvj4eHbt2sXsWbORkiUUmxUtalqxWYF/iT9vvPwGe/fuNS+xg6a9Lps3b6Zv375UVVVx5MgRXnjhBZ588km2bdtGY2Oj+dz6+np27NjBCy+80O5ePiMiIujduzdJSUlcvt9Zp9Nx4MABXnrppXa9v8yNMWfOHLKysigpKeHEiRPm9Pj4eHbv3m0OGdGnTx90Oh3JyckMHDiQLVu2mGed7e3teWr2UyhOKK5aT9um2VrU04WFhRw9epTu3btz+vRpMjIyLL525swZcnNzefnll9ur+Gaeeuopzpw5YzWAeerUKUpKSpg2bVq75+FXyuqioqK65ORfFjHZ29szcfREpORWBoMvGYOqVBXuzu5s27aNhoYG82GDwcCGDRuIj483G3fp6emcO3cOT09PIiMj2bRpk8XgVV1dHZs3b2bgwIFNtxCCXbt2MXjwYPr06cOzzz7b4n22b9/OvHnzLJb1T548mfr6eo4fP26R7fz8fJKTk3n22WdRKpXMmzePbdu2WcxiNjQ0sH37dp599lnUavUNPtLbz7PPPsuJEyesjMLk5GRqamra6lRGRkamDVzTqQyAJElBwLorvYxeOpYFxN5uL6MffvghX331FT169DAvvygrK8POzo6IiAjKy8tJS0tDo9FQX19P79690Wq1nD171rx8Q6lUUm+qxxRlsvA2ptysxK/YD43U5PQgODiYmpoas/evhoYGHBwc6NWrF2lpaVRWVhIdHY1arSYtLY2BAweyfPny2+Lief/+/UyZMgUvLy88PDwoKysjLy+PVatWkZCQcO0L3H66zAbv9nIqU11dzdSpU8nPz6dfv34IIThz5gze3t5m73a5ublotVoMBgNKpRJbW1t0Oh1+fn6czznfokfGIF0QSxctxcXFhQ8++IAffviBfv36oVQqSU1NRaPR4OPjQ2ZmJq+//jp//OMfMRgMzJw5k8TERLOX0dOnTzN16lS++OILq32I7cHFixcZP3485eXldO/endraWs6cOcO7777Lc8891+73vwZdRs9wazX9448/8u677yKEwMPDg6CgIC5evEhWVhYKhYI+ffrg7OxMSkoKdXV1uLu7o1QqKS4uJjQ01Oz91mAw0CA1WGlauVmJT5EPpjoTNjY2+Pv7U15eTmZmJvPnz2fUqFGEh4ej1+sJCAjA19eXCxcuUFhYyKpVq5g4ceItKee12Lp1KzNmzCAgIABXV1eKiorQ6XRs2LCB/v3735Y8XAddRs+SJIXb2tqeDAwMxNvbG71eT1ZWFp9//jkvvvYiBd4Fv2wbaZ4ZPCFhq7BFkiQcHR2pqqoiLCzM7F3ZZDLh7e1NQEAAeXl5ZkOlT58+uLi4cPLkSYxGI9HR0RiNRk6ePGn2Sm5nZ0dGRgY+Pj5s2rQJd3d3GhoaePTRR9m6dSt9+/Y11/UTJ07k22+/RaWyjAx2+vRpxo0bh52dHT4+PlRUVJCRkcE333zD1KlTAWhsbGTOnDls2LCBvn37IkkSZ86cYcyYMXz33XedyiAEWLt2LY888gjBwcG4uLhQUFBAdXU1mzdvbusKkS6jaRmZ9qQtXkaXACMAD6AQ+H9CiAWXHc+iAwxCaOoo/utf/6KwsJDQ0FBiYmLYsGED6enpeHp6Mm3aNCZOnEh+fj4ffvghp0+fxsXFhd69e1NeXk5FRQVqtZqjKUep6V2DabwJ9TY1/iX+LF24FGdnZ/bv38/x48dxdnZm0KBBjB07ljVr1rB69WoqKioYPnw4w4YN4+eff6ahoYHx48ff9ka+rq6OlStXcu7cOYKCgnjggQfafSnfTdBlKuf2MgihaSR5586d/PDDD1RXV+Pl5YXRaKSiogIHBwdiY2OxtbWluLiY5ORk0tLSMBgM+Pv7ExERwfqt66nsUYmYIFBtVRFQGsDShUst9pzm5uaydetWamtrzQMnHh4eTJw4EaPRaB7VhqYR2Y0bN6JUKpkyZQp9+/Ztl3K3hslkYvv27Rw4cABXV1emT59u5Wing+gyeoZbr+mysjLWrVvHsWPHUKvVxMfHExAQwOrVq0lOTsbFxYX777+fKVOmsHXrVrZt20ZRURF6vR6j0UiPHj144IEHMJlMvP7n16nuVY2YICzqaUdHR3bv3k1aWhp2dna89tpr5qV2Qgi+//57PvjgA2pra5kwYQLvvffeba8fq6qqWLFiBdnZ2fTp04d77723xf1mdwBdSs9hYWHizTff5PTp0/j6+jJ9+nScnJwoKytj4LCBZGozMY4zIm2ScM5wZt4z87jnnnvIzc1l6dKlFBcXo9VqiYiIwN7enpqaGnJycigsLMTBwYHZs2czZMgQVqxYQVFREZGRkXh5ebFz507UajX33Xcf9vb2LF++nMrKSoYOHcpdd91ltbIiJSWF9evXAzBlyhRCQ0NbLVNDQwNr164lNTUVHx8fZsyY0WL4n1OnTrF27VqgaXaxMy9PrqioYPny5eZB0nvuued6DNsupWkZmfaiTTOEt4r27EDfDHq9npmzZ5JblYu/o79Vx7kZnU5n0UmWuSG6TOV8p+oZ2q7p1pC13ma6jJ6h82ta1u1N06X0HB4eLlJSUlo8VlZWxpARQ8jQZRDiGsLeXXs7XYw+mTbRpTQtI9NedGhE5zsFrVbL0oVLeXjcw9fdcZaRuRORNS3T1ZA1LXMrcXNzY++uvcybMU82BmVkZH71qK59yq8DrVbLG6+/0dHZkJG5ZcialulqyJqWuZW4ubnx0YcfdXQ2ZGRkZDoceYZQRkZGRkZGRkZGRkbmV4psEMrIyMjIyMjIyMjIyPxKkQ3CNqLX6/nXf/5FWVlZR2dFRqZdkbUu0xmRdStzOZIkuV0svCjrQUZGRqYNyHsIr8FDDz3EkSNHQANoYUXACgpyCuQN6DJdjmeeeYbdu3ebtb7cfzmFuYWy1mXueEJDQzEqjOAKS72X8v5b7/O73/2uo7Ml0wFIknQf8BMapDJFGe7e7hTnF+Ph4dHRWZORkZG5Y7nmDKEkSV9JklQkSVLKZWl/kSQpT5Kk45c+k9o3mx1Dnz59OH78OBpHDVKMBM9CQ1gD7t7u8qijTJeiT58+JCUloXH4ReuN4Y2y1mXuaMrLy5sChytNSP2bdEsMvP7n1++UOJUytxFJkk6rVKqVKjuV1FyPEQ2efp60Fn5CRkZGRqZtS0a/ASa0kP5PIUT0pc+GW5utjmfevHkolUocXR0xRhgRE0RTNJtJQDR4+XvJHWWZLsGHH36IUqnEQeuAMdJa6x6+HrLWZe5I4uPjMalMKPorftHtRJBiJIrLiykpKenoLMrcRjQaTV+NgwYRLazqsYj+EXI9JiMjI9MK1zQIhRCJwK+uFt26dStKWyVVvaowjjP+Etr0UgNjDDcyZMQQuYGR6fTMnz8fhY2C6t7VLWpdRApZ6zJ3HHq9HkkjQTQYx1vqVkwQEAVefvLA3a8FSZKKG2igvl+9dT02EYiGIXfJ9ZiMjIxMS9yMU5l5kiSduLSk1PWW5egOQK/XgxoawhssG5ZmLnWUM10y5Y6yTKemWeuNEY2y1mU6DXq9npmzZyKiBKbxplZ1K6LkwYxfA5IkuaHGQ0QLy8EB8wk01WNauR6TkZGRaYkbNQg/BXoA0cBF4MPWTpQk6RlJkg5LknRYr9ff4O1uL59+9im48suSk5aQwDDaQIYug7ffefu25k+m4+iMer4astZlOqOmP/3sU3KrcpuWA15Ft0xC1u2vAQV/wJWmmUC5HpORkZG5biQhxLVPkqQgYJ0QIvx6jl1Jv379xOrVq28gm7cXvV7PyPEjqelV03qHQ4Bmu4bg8mD27tore2JsO601152OzqLnq6HX6xl39zjKg8plrd8YXUbP0Hk03TxDmOmcKev21tIp9SxJkhsa9hBFX1kPMlfQKTUtI3O7uaEZQkmSfC77cyrQpdx3abVadm7eCceBDcCVNrPcsMh0EbRaLVvWbZG1LtOp0Gq1LF24lO667q3qlo3Iuv2VIIQow8BQjmOQ6zEZGRmZ66ctYSeWAPuAPpIk5UqS9CTwd0mSTkqSdAIYCbzYzvm87Wi1Wg4kHcDmjI1lh0NuWGS6GM1atztrJ2tdptOg1Wr5cfGPBFcEW+lWtUVFn9o+sm5/RQghymjAh2Ty5HpMRkZG5vpoi5fRWUIIHyGEWgjhL4RYIIR4VAgRIYSIFELcI4S4eDsye7vRarUkbkskuCIY9Ta13LDIdFm0Wi27tuyStS7TqWieKbxStz2qesi6/RVyaaYwkmTOsIl6uR6TkZGRaRs342X0V0Fzh8O/xB/Vlyq5YZHpsshal+mMyLqVuRzz8tFjZPKZvGxYRkZGpi3IBmEbaO5wTLtrmtywyHRpZK3LdEZk3cpcTrNR6GZ0k/UgIyMj0wZkg7CNaLVaXvjtC3LDItPlkbUu0xmRdStzOUKIMp9uPrIeZGRkZNqAbBDKyMjIyMjIyMjIyMj8SrnjDEK9Xs97779HZwmQLCNzJbKGZboasqZlZG6csrIyXnr5JcrKyjo6KzIyMjItouroDFzO8ePHefa3z6JX6Nm6cys//fATWq3WfLysrIyNGzdSXl5OWFgYw4cPR6FQIITg2LFjHDx4kIqKChobGzl37hw6nY7GxkacnZ0JCAhAo9GQl5eHvb09M2bMICYmhi1btnDx4kWCg4MZM2YMGo3GfL+CggL++9//kp2dTVBQEL6+vmzZsoXevXtz3333YWNjgxCCxMREkpKScHR0ZNq0afj5+bVYvlOnTrFu3TqEEEyaNImIiIj2fqR3BCaTiS1btnD48GH+9Kc//Q+wTAhR3NH5utUYjUY2b97Mm++9SbmynB0/72DZ4mUUFBSQmJiIJEmMHDmSnj17AiCE4OjRo6xatYqcnBwaGxsB8PLyonv37tTX11NYWIher6eiooJu3brh7u5OQUEBdnZ2TJo0idGjR6NUKgEwGAxs2rSJHTt20NDQwNChQ7nnnntwdHSkoqKCTZs2UVxcTO/evRk5ciQq1a17/SsqKli+fDl5eXn069ePe+65x+Jd6qxcWa57770XtVrd0dm6rRQUFDBt1jRKTaWs37Ken5b+hJeXl8U5Qgj279/P8ePHcXBwYPz48XTr1g2A7Oxstm3bRkNDAwMHDqSiooL169dz5swZhBDY2tri5OREY2MjBoOBbt268dxzz9GjRw/q6+vZsmUL2dnZ+Pn5MX78eOzs7ABobGxk9+7d7N27l8LCQnr37o2fnx+7du0C4O677yYsLMwin8XFxSxbtoyysjIGDBjA+PHjUSiaxkUrKipYtmwZ+fn5hIaGcs899/xqfuuioiKWLVvGvHnz/ggcBrYIIUwdna9bSVVVFcuXLycnJ4c+ffpw7733YmNjQ319PatXryYtLQ1/f398fX05dOgQOTk5ODk54eLiwoULF7hw4QLBwcFmXSYnJ5OcnIyNjQ1/+MMfmD59OmvXriU1NRUfHx+mT5+Oi4sLZ8+eZeiIoZSKUhYsXMDShUuZMGECktR6vPTc3FxWrFhBVVUVw4YNIyEh4arnNyOE4MCBA+zYsQNbW1umTp1KcHBwi+fW1tayYsUKMjMzCQkJ4f777ze/W50RnU7Hjz/+SFFREVFRUUyaNOmWtnEyMl0eIcRVP8BXQBGQckX6c8AZIBX4+7WuI4Sgb9++Ii0tzepz6tQpMWXKFKGwUQhpoCT4fwjiEfZae5GUlCTS0tLEm2++KRwcHERMTIwYPny4CAwMFCEhIWLDhg0iPj5eeHp6Cm9vb2FjYyM0Go3o2bOnGDp0qPDz8xMajUZoNBoREBAghg4dKkJCQoRSqRRqtVqEhYWJ4cOHi969ewtPT0+xcuVKkZaWJv7nf/5HqNVqER4eLsLCwoRarRbBwcFi+PDhom/fvqJbt25i+/btIi4uTvj5+Ynhw4eLuLg44eTkJN5++21xOQ0NDeLhhx8Wrq6uYvDgwWLIkCHCzc1NTJ8+XRgMBtGVycnJEX379hXdu3cXw4cPF2FhYdUqlapWoVD8RrRBM3fy53I979y5UwQGBgqVveoXDcchNI4a4eLiIoYMGSIGDx4sXFxcxH333ScOHjwo+vfvL+zt7YVWqxWDBw8WUVFRQq1WC5VKJbp37y6GDh0qXF1dhUqlEuHh4WLIkCHC1dVVuLi4CB8fH2FjYyO6desmtm7dKlauXClcXV2FjY2NCAgIEMOGDRMhISHCwcFBzJ07Vzg6OorIyEgxfPhwERISInx9fcXGjRtbfB/T0tLE/v372/wbr127Vjg7O4uoqCiRkJAgevfuLXx9fcXJkyevQyl3HmvWrGlLuTpch7fyc2Ud/emnnwqFjUIQj7leVtgqxFdffWU+Z9++fSI8PFz4+vqKYcOGidjYWOHg4CBefvll8eijjwonJycxcOBAERsbK2xtbYWzs7OwsbERQUFBYtiwYaJ79+7CxsZGhISECI1GI7y8vIRKpRLDhw8Xbm5uom/fviIhIUGEhoYKrVYrvvvuO7Flyxbh7+8vfH19xdChQ0Xfvn2FRqMRtra2Ij4+3vyuzJo1SzQ0NAghhJg/f75wdHQUAwYMEMOHDxdBQUGib9++Ijs7u9XfOiUl5eaFdIfzySefmJ/LsGHDjO7u7hUajSYd8BN3gCZv5hMWFiaEEGLz5s3CxcVFREREiISEBNG3b1/h7e0tvv/+e+Ht7W3WWM+ePYVarRb9+vUz18dqtVpERkaKPn36CJVKJXr06CG8vLyEvb29iIuLE7GxscLGxkbY2tqKnj17ioSEBBEdHS2cnJzEY489JiSNJIhren+kgZKQbCQRFxcnKioqWvw93nrrLeHk5CTi4+PF8OHDha+vr4iPjxelpaVX/R0rKirEiBEjhLe3txg2bJgYOHCgcHZ2Fq+88oowmUwW5/7888/C3d1dhIWFiYSEBBEWFibc3d3Fnj17rnqPO5Xvv/9eODk5iZiYGJGQkCB69OghgoKCRHp6uhB3gA7lj/zpDB9JCNGarQiAJEkJQBWwUAgRfiltJPAHYLIQol6SJC8hRNG1jM9+/fqJ1atXW6X/5z//Yf7X8zFFmjCON4JEU1DZjeCS4cJHf/uIl19+mUcffRR3d3ezIbtnzx6OHTtGUFAQTk5OnD9/npKSEmbOnEn37t3N12+emXvxxRdRq9VUVFTwySefMGvWLIvzUlNT2bFjB++//z7PP/88Tz/9NCqVik8++YQHH3yQoKAgi2uuXbuWyMhIi9G+yspKFi9ezOeff84999wDwJtvvsnixYuZNm2aedakoaGBn376ialTp/LOO+9c69F1SoQQxMbG4ubmxtChQ83PqLS0lC+++KKmrq5ujBBiXwdn84Zp1rMQgilTppBXnEd9v3qM4y7T8AZwyXThN0/8Bnt7ewwGAz/++CNqtZri4mK6d+/O5MmTzbMU1dXVfPXVV4wcORJbW1vWrVvH448/jouLC9D0TLdu3UpRURGRkZFs2rQJLy8vysvLMRgMTJw4kfDwcHMes7OzWbRoETNmzKBXr17m9KNHj3LkyBG2bt1qnmG8HJ1Ox8CBA6/5DLKysoiOjmb69On4+/ub00+cOMG+ffvIysrqlDOFWVlZREVFMWPGDItyJScnc+DAATIzM5vLde1h+07E5XV0ZmYmE++diBQjYRpvMmtasVkBx2Dbxm34+fnx+OOPo1AoGD16tPkdLy8vZ/78+Wi1Wh555BHs7OxYsGABgYGBHDt2jKlTp1ro8dy5c/z00088/vjjLFmyhP79+7Nr1y5mzJhB7969zeedP3+e1atX4+LiQkREBPHx8QDs3LmTnJwcZs2aZZ7Va2hoYPny5cycOZMJEyYwadIkHnnkEas2JC8vj7y8PB588EGL1R3JyckcPHiQzMzMLjtTuGfPHu69914efvhhs/MVIQS7d+9u3LdvX0pdXV1MB2fxpggPDxdbtmwhNDSU+++/36q9X7VqFVOmTCEyMtKcnp2dzZIlSxg7diy7d+/mqaeewmAwsGDBAh555BFOnTpFYWEhDz74oHkGymAwsHDhQuzs7Hj44YcByMjIYOGShRADTMT8/ig3K1GmKLlnwj0sW7bMIr+rV69m7ty5PPzwwzg5OQG/1Pmurq6sW7eu1bI+8sgjnDlzxqI9qampYcmSJbz11ls89thjQFPd3qNHDyZPnmxerQKQnp7Ohg0byMzMNLc3nYGUlBSGDx/OrFmzzKsSAA4dOsTZs2dJT09Xii422y0j0x60JTB9InDlwvdngfeFEPWXzrmmMdgaOp2OzxZ8hjHS+IsxCE3/ToTy4HKee/k5+vfvb27IASRJIioqioqKCkaPHs3hw4fx8fEhLCzMotIHCA0NxdfXl1OnTgFw7NgxwsPDrc4LCwvD09OTt99+m5EjR+Lq6sqxY8cIDQ21MAabr+nl5YWXl5fFUg4nJyeGDh3KP/7xD6BpGeH//d//WS1HVavVjBkzhk8//ZSGhoYbfXx3NIcPHyYvL48hQ4ZYPCN3d3dGjBhhZ2Nj82oHZu+WkZSUREZOBvV9LzMGoenfSVAeUs6CRQuoqalBo9EwbNgw0tPTqaqqYty4cebGG8DBwYExY8Zw4MABDhw4wIgRIywaZ0mSGDVqFBcvXsTX1xcvLy90Oh2SJOHt7W1hDAIEBgYSERFBXl6eRXr//v1Rq9X8/PPPN1X2zz//nPDwcAujCSAyMhInJydaGgDqDHz22WdERERYlSsqKgpHR0fWrFnTQTm7Pej1eh567CGI5hdjEEBq+tsUZWLGwzM4ceIEqampjBgxwuIdd3FxQa1WM3bsWOzs7MjPz6eiogInJydCQkIsjEGAnj17EhISQkZGBiNHjuT48eP06NHDwhgE6NGjB8HBwVRWVhIXFwc01bGHDx9m0qRJFoZbcx378ccf8+GHHzJw4ECrNmTIkCHk5OQQHh5utdQ/KioKBwcH1q5dewue6J3JRx99xMCBAy08cUqSREJCgkqlUvWSJKl/B2bvlvDFF1/Qr1+/Ftt7X19frhwUDwwMJCwsjKSkJMaNG4eTkxNHjhwhJiYGLy8vjh49ysSJEy2WI2o0Gu6++24uXLiAyWSipqaG9VvXQzS/GIM0/Wscb8QYbmTFmhWkp6db3PuDDz5g2LBhZmMQmn6PESNG8PPPP3PhwoUWy1haWsrq1asZM2aMRXtib2/PXXfdZe6PACxcuJDg4GALYxCgV69edO/enUWLFl3jid5Z/N///R/9+/e3MAYBYmNjqa+vBxjVIRmTkelk3KhTmd7AcEmSDkiStFuSpLgbuYher+fBRx/EGGG07HQ0c6lDXdO7hiMnj1BTU2P1fVdXV4QQNDY2UltbS0BAQIv3CgwMpLi4adtacXExgYGBLZ7n4+Njcby4uLjVa/bs2bPFTeKBgYGcOXMGaBopr62ttdpzA02GkRCCkpKSFq/f2Tl9+jT+/v4WDVQzAQEBkiRJkS18rVOh1+t5/c+vY4oyWQ5oNHNpYEMfpDcbhUqlEgcHB7y8vLCxsbG6ZmBgICUlJa1qT6VS4evrS2lpKYGBgdjb2wO0qtPg4GCz9i/Hz8+P8+fPX3eZL+fEiRP4+vq2eMzb25vTp0/f1PU7ihMnTrS6F7gzl6st6PV6Zs6eiS5Ih5ggWtV0Wfcy5r04D29vb6u9OkII9Hq9WZMlJSUEBASY/22J5jo6MDCQqqoqq0G4Zvz9/bG1tTUboLW1tQgh8PDwsDrX09OThoYGTp482eJ9FQoFtra2VoZ/M926devSv/WpU6daLLtCoSAgIMAE9Lv9ubq1JCcnt1pHhYSEtNj+NmuwWTPNdXFVVRVKpbLFUBbe3t4YjUaKi4tZsGgB+iA9TKLF98c43oiIFoydNNaiD5GWltaiTjUaDX5+fpw9e7bFcpw/fx5PT88W9wAGBgZaGJ4nTpzA29u7xev4+PiQkpLS4rE7lZMnT7ZYV0uS1Jze6TUsI3M7uFGDUAW4AYOAV4EfpVZ2PEuS9IwkSYclSTp8pYe6Tz/7lLyavJYrTfMFgIlQoawgMSnR4pCjoyPl5eWoVCqEENjY2LRqXJWUlJhH3ZycnFo9T6/X4+DgYD7u5OREaWlpi+cWFBTg6OjY4r2aK9zme1ZUVFidV11dTUNDQ6dannE9+Pr6tupV7dIzzWvx4B3MlXr+9LNP0dFKx9n8JTCOM6JDR2JSIkIIampqKCsrw2g0Wp3erNXWtCeEoLS0FEdHR0pKSmhoaECSpFY1XVxcbDHi3IxOp8PT0/O6yn8lAQEBrf7GFRUVrXbE7nQCAgJafe/Ly8s7bblaoiVN51blXlPTpvEmSkwlZOdkYzKZrrwmDg4O5mfYXOderT5tPl5SUoJGo2lxEAOa6o7LV1XY2NhgNBqpqqqyOreyshKj0Yi/v3+r70djY2OreaqoqMDHx6fFY12B5oGllrj0/C/e1gzdAi7Xs06nIzAwsNU6qrCwsMW6saSkxKI/0axbOzs7DAaD1eA0NNULAEePHUWHznK1iFUmgYmQX5vP2++8bU729vZu8fcwmUwUFxe3qkUfHx9KS0vNjsmuLMvlA9IBAQHodLoWr6PT6VodHLlT8ff3b1XDl/qcnU7DMjIdwY0ahLnAT6KJg4AJsB6eBYQQ84UQsUKI2Ms9hgI8O/dZAhwDmvaktLaVUYBqiwpFuYJB8YMsDhUVFaFUKjl69CgRERHU1NRw9OhRc8XcTEFBAWfPnjUvp4uJieHIkSOtnvfss8+yY8cODAYDMTExHD161MrdemFhIWfPnrVabtLY2Mi+fft49tlngaZlSw899BBJSUkW5wohSEpK4v777zfP8HQ1Ro4cicFgMM+WNlNfX8/OnTur6+rq/tUxObtxrtTzs3OfJdAxEDZyVQ0rtyhxxZWEYQmcOHECDw8PbGxsOHTokMWpRqOR3bt3ExMTQ0xMDImJiVZLipOTk1Gr1QghOH/+PA0NDdTW1pKens7Fi5ZtX0VFBQcOHKBv374W6dnZ2eTm5jJ27Nibeh7PPPMMx44do7Ky0iI9Ly+PjIwMpk+fflPX7yiuVq7MzMxOW66WaEnT/o7+qLaqrqpp9TY1gU6BeHfzJjk52eJwQ0MDGo2GnTt3YjKZzF5z7e3tOXnypJVxVlpaysmTJwkPD2f37t1ER0dz4sQJq/PKyspISUnBYDCQmZkJNNWxYWFh7Nq1q8U69sEHH2TevHkcOnSoeQmZmbS0NFQq1VV/62nTpl3P4+xUPPvssxw8eNDquZw+fZqKiopqYHfH5OzGuVzPrq6uPP300xw/frzV9v7K1Tvl5eUcOXKE6OhoduzYQWNjIzExMRw4cICGhgb69u1LYmKildZ27NiBl5cXdyXchSuuKDcrr/r+SJskQtxC+OMf/mhOnjt3Lvv27bMy7I4ePYq/v7/VloBmAgIC6N+/PwcOHLBINxqNJCUl8Zvf/Mac9vjjj5OSkmJlRJWUlJCammrea9hZmDt3LkeOWK8gy8zMpKioCKD1jZcyMjJmrulUBkCSpCBg3WVOZeYCvkKIP0uS1BvYDgSKa1ysJacyer2eGY/M4ILrBcu19mDudPiX+BPVL4q9e/fSv39/nJ2dyczM5OzZs7z11lu88847eHh4mDvDdXV1xMfH4+XlRXZ2NkePHkUIQVxcHP7+/hQUFLB//37zHhJPT08uXrzI8ePHeeuttxg/fjzPPPMMycnJDBkyhMLCQk6fPk18fDze3t4UFBSQnJzMn/70J/7+97/j7+9Pjx49qKmpITk5mdjYWJYtW2ZeRqXX6xkxYgR1dXX069cPSZI4ffo0CoWCxMREi30tXY39+/czefJk8/6E8vJysXfv3pr6+vofDAbDU9fSzJ1Ms571ej1TZ0wl3yvferb7knMkx3OOJAxKID09HZVKxXvvvcdTTz1FVVUVwcHBhIWFUVdXx759+6iqqiI2NhYfHx9+/vln6uvrGTx4MI6Ojpw+fZqMjAx69uxJWloaCoWCzz77DJ1Ox+uvv44Qgv79+xMQEEBhYSFHjhwhMjKSM2fO0L9/f9zc3MjNzeXkyZN89NFHJCQktFi2tjqVAXj33Xf58MMPiYmJwd3dnfz8fE6cOMGiRYvMjpU6I++88w4fffTRtcrVJZ3KNC8bzXbLtp7puDTAEVgWyNKFSykqKuKxxx4jKCiIHj16UF1dzfHjxwkLC6OsrIzS0lIiIyOprKxkz549dOvWjZKSEgYMGICvry95eXkcPXqUXr16kZ+fj0qlMu83rK2tJTo6Gm9vb4qKijh69Cgvv/wy3bt357nnnqN379706NGDwsJC9u/fj5eXF7GxsQghOH36NBqNht27d6PVann22WdZvXo10dHRODs7k5WVRXp6OuvXr2f79u3885//NP/WeXl5nDx5ku+++44pU6Z02O/R3gghePrpp1m/fr35uaSlpdWmpqY2NjY2jrk04NtpCQ8PFykpKXz44Ye88847xMTE4OHhYW7Dn3jiCb766isiIyPx8fGhsLCQgwcPmkOY7Ny5E1tbW4YMGUJWVhaZmZnExMRw6tQpXFxciImJQQjBoUOHKC4uJiIiwqzHnw/8jIgS1jPtl9qEkIoQDu05ZLH8tLGxkWnTpnH06FEiIyOxs7MjIyOD3Nxcdu3aRb9+ra9+zMrKYvjw4bi7u9OzZ08MBgMpKSkEBwezYcMGi+0JX3zxBa+++qp5X2RhYSHHjx/nww8/5Mknn2yHX6J9efXVV/n222+Jjo7G1dWV3NxcTp06xYoVKxg1alSXqqNlZNqLtngZXQKMoGkGsBD4f8AimsJRRAMG4BUhxI5r3aw1L6PNewlz3HMsPDQ2G4NLFy7FxcWFgwcP8tNPP6HT6cweAD09PamqquKnn34iKSkJnU5HXV0dZWVlGAwGjEYjarUaFxcXFAqF2bHH2LFjGTVqFOvXrycvL4+ePXtaeCcVQrBhwwbmz5+PTqfD0dERHx8fHB0dCQ0NZe7cufTq1YuysjK+/vprduzYgZOTE7Nnz2bChAlW++bq6+tZtmwZy5cvRwjB/fffz4MPPoitre21Hlunp7CwkPnz57Nv3z527NixpL6+fj6wuzMbg2CpZ71ez/SHppPrmWvhkVG9TY1LpguhPUOxsbFh3LhxTJgwAY1GQ1VVFd9//z2rV6+mvLycxsZGhBDY29vj5eVFY2Mj5eXlVFdXYzKZsLOzQ6PRYDAYUKvVJCQk8Mwzz5g301+4cIH58+dz8GBTHy40NJTf/OY3hIaGcuLECXOMpj59+jBr1qyrLnu8HoMQ4MiRI8yfP9/soOPZZ59tNf5VZ+LyckVERDB37twry9WlOhtXanrm7JnkuOfQOLbRrGnVVhUBpQEsXbjUHCdWp9OxYsUKDh06hKOjI/feey/Dhw/HaDSybds2NmzYQENDA/3796esrIzt27dbLONrdrhlNBpxcXHhoYce4rHHHiMjI4OlS5eSlZVFYGAgM2fONDukKSgoYPHixezZs4eKigo8PDzw9/dHCIFSqeSBBx5g+vTp5jr2kvdMvvrqK0pKShg0aBDPPPOMeXl/G37rLokQgl27dvH111+zfPnyHQaDYZfRaJwvhCjs6LzdLM0GITTFOf7888/JysoiLCyMuXPn0rNnT86dO8dnn31Gamoqvr6+uLm5cfz4cYqLi837vYuKiqisrMTBwYGAgAAMBgPp6elUV1ejVCoZMWIEb7/9Nt999x3Jycn4+/s3zUy/OI/zzuct3h/lFiUh5SHs/3l/i3sRTSYTmzZtYuHChVRWVjJq1CieeOIJXF1dr1neiooKFi5cyKZNm7Czs+Ohhx5iypQpLcbjO3XqFJ9++innzp2jV69ePPvss1c1OO909u3bxxdffEFBQQH9+/dn7ty5zctfu1QdLSPTXrRphvBW0ZpBCL90PnI9cmkY02BhDF651LSjuN5OskyLdJnK+Uo9dwYNtxVZ622my+gZOr+mZd3eNF1Kz5cbhB1BWVkZQ0YMIdMlE8NoA5rtGoLLg9m7a2+LxqBMu9ClNC0j017c6B7CW45Wq2XpwqX4l/ij/vLO7nTIyLSErGGZroasaRmZG8ft/7d373FR1fnjx1+f4eYoVwVNFJGLWmqal7REjbxwsTbTXMM1LcvK/G3bZdvNdmv3+6hH2T66rPlHu2WaaYpamunmpYuaN0BERTEFL3jH23AZEJiBmfP7A5gYASUEZhjez8eDh3DOmZn3Oeftez6fc/mc9u3ZvW03YQVheCz0kM6gEMJpOU2HEH5tfEyNmSqNDtEiSQ4LVyM5LUTDVXUK/zj5j9IZFEI4rZoXljuYv78/r815zdFhCNFgksPC1UhOC9Fw7du358MPPnR0GEIIUSenOkMohBBCCCGEEKL5uHSHMD8/n7nvzq3xDEEhWhLJY+GKJK+Fs8jNzeXlP79c5wPshRDC1TndJaMNUVRUxPbt27l27Ro6nQ6r1UpAQABvzn2TK+VXWLNuDfFj4tHr9XTq1ImuXbtSVFTEzp07OXv2LEFBQfztb3+rGqIYqBiK+9ChQ2RmZhIYGEhUVJRtenJyMv/73/8oKipi1KhRjBs3jqKiIjZt2oTJZCI6Opru3bvb3isrK4tdu3bRrl074uPj8fHxsc27cuUKmzdvxmq1Mnr0aLp06dJs260plJaWsmnTJnJzcxk4cCB33XWXo0NyWkVFRWzdupWDBw8SEBDAsGHDuOOOO9i1axcGg4FevXqRm5vLa/98jTwtj6UrluKn9+POO+/krbfewtfXl/Xr15Oenk5ISAi///3v7Z5paTAY2LlzJ5qmce+999KuXTu2b99OSUkJAwYMIDw83PZ/p6SkhEGDBtnl7a2u28aNGykqKuLee+/l9ttvb5T3bWqFhYVs3LiRa9euERUVRc+ePR0dUotmNpvZuXMnBoOBLl26YDAYKCsrIzIykudeeA6D1cCa9WuYOX0mnTp1wt3dnYyMDDw8PBg8eDBHjhxh//79eHt7ExMTQ3R0tN3z1LKzs9m3bx96vd72TE2TycS3337Ltm3bCAoKYvLkyfTp0weAM2fOsHXrVtzd3YmLi6v1GbDp6emkpaUREBBAXFwcR48eZf/+/bRv3564uLgW/6ig1l6jDQYDmzZtory8nOjoaI4cOcKMZ2Zw1XKV777/jp1bdrJx40a2bdtGcHAwvXv3JiMjgwsXLuDj40N0dDQZGRls3bqVzp078/rrr1NaWsqBAwcICgoiNjbWlqN5eXm899575OTkEBMTQ0JCAkrVPehlfn4+mzZtorS0lBEjRhAREVGvdTKZTGzatImrV69y1113MWjQoDqXvXTpEt9//z0AY8aMoXPnzr9h6znejdpTQoiGq89zCBcBDwKXqz2YfiXQq3IRfyBf07S7bvZhN3rsREMtX76c999/n44dO3Lx4kXatWtHYGAgWdlZWPtZKx4UvgE8DnsQclsIZ8+etRVkTdMIDw/HYrFw6tQphg4dysKFC7l8+TKzZ8/m8uXLdOvWjby8PPLy8nj55ZdJTEzk5MmTeHh4EBISgsFgoLCwEIvFQs+ePfHw8CArK4sJEyYwf/58ZsyYwZYtW+jRowelpaWcPn2aDz74gJkzZ/KPf/yDf//73/To0QOdTkdWVhaPP/448+fPr/Ecw5Zg3bp1PPHEE3Tq1AkfHx9OnjxJnz59WLNmTfWGl8sMAX0r+fz111/z9ttvExgYiLe3NydPnkSn02GxWOjcuTMdOnTg6NGjXCu7Bv2x5bHnL550DOhITk4OmqYRHByMn58f2dnZWK1WpkyZwl//+lc++ugjlixZQmRkJDqdjqNHjwLQvXt32rZty/HjxwkODubs2bOEhobSpk0bjh07xr333st7771HSUlJg4fvX7x4MS+88AIhISHo9XqOHz/O8OHDWbFiBe3atWvQezaHBQsW2B56XrU97r//fpYtW0bbtm3repnL5DM0bo1OSkri5ZdfJiAgAG9vb44fP46bmxu33XYbWaey7PLa4xcPggMrHlIfGBhIQUEBZWVleHp6opQiNDSU/Px8jEYj//rXv4iKiuIvf/kLycnJttp65swZ4uPj2bRpEz4+PgQEBHD69GksFgtDhgyhW7durF27lh49emCxWDh+/Dhz5szh9ddfByoa7xMnTuTQoUOEh4djNBo5deoUnp6e3H777RiNRq5cucKSJUt44IEHGmUbNbfra3R2djZ33HEH33zzTVWNdql8vv6xE2+//TZz58611cWMjAzKdeVwFxUPkN8IKl0R0C6A4OBgzpw5Q2lpKV5eXnTr1o2rV69iMBho06YN3bt3Jycnh8LCQnQ6HX369KGwsBCDwcCyZcvYunUrH3zwAV27dqVt27acOHGCdu3asXPnzlqf9zd//nz+/ve/ExYWhqenJ8eOHWPcuHEsXrzY7iDI9TZu3Mi0adPo0KEDfn5+nDp1isjISNauXUvHjh1ty2maxquvvsrHH39se5bn8ePHefrpp3n//fedvs1RUlLC1KlTa7Sn3nvvPZ599tkbvdSlclqIplKfDuFIoAhYUtUhvG7+B0CBpmlv3uzDGrtD+PPPP/Paa68xceJEEhMTiY+PJywsjIVLF5Ifmo8l1mL3MFj/U/48OuFRFixYQKdOnZg6dSp6vR6oODPw+eefM2HCBHbt2kXnzp0ZMWKErUieOHGClStXotfrGThwYI15X3/9NbNmzcLPzw+TycTatWvR6XR4eHjwwAMP4OHhAcDVq1dZsWIFU6dOZc2aNTz66KN4e3sDFQVv9erVTJ8+nTfeeKPRtlNzOHToECNHjmTSpEm2M60Wi4UtW7bg4eHB1q1bqxZ1meLc0HxOTk7mxRdf5A9/+ANBQUEAlJeXs3btWnJzc7FarUybNo1FXy7CEGKAeGrk8YQHJrB8+XKioqKIiorCYrGwYcMGsrKyuO+++9i/fz9Tpkyxy63ly5fTs2dPRowYQVZWFt9++y0zZswgMDAQgLKyMtavX09ERASvvvpqgzqE27dvZ8KECSQkJNgaI+Xl5WzYsIHIyEhWrlz5m9+zOfz00088+uijJCQk2PZJWVkZ3333HX369OHLL7+s66Uuk8/QeDX67NmzTJw4kQkTJtge7m61Wvnxxx/Zs38PWn+t1vo8+eHJJCYmcu3aNYKCgggJCSEmJgY3NzcAzp07x8qVKxk8eDAGg4Hf/e53ttp67NgxvvrqKx577DG6detm95mHDx9GKcWsWbNsZ/iMRiMrVqxg7ty5TJ8+nTFjxlBcXMyYMWNsn3f+/HmWL1/OtGnTuO222zh79iyrV69m165d9O7d+5a3U3PKyMhgxIgRtdZod3d3tm3bBi6Wz9U7hEuXLmXOnDkkJCTg6+tLcXExny35jNxuuXY1VrdZR8DpAJ6a9hRLly6lV69ejBw50u77fvXq1TzzzDP4+fmRnp7Oxo0biYiIYPLkyZw+fZoVK1aglOLJJ5+0q69r1qwhJyeHq1ev2nIMYP369cycOZOEhATbKKRms5l169YxfPhw/vOf/9S6fpmZmdxzzz1MmDCB0NBQoCLnt23bhslkIikpyXYAfN68ecybN4/JkyfbDswVFxfz1VdfMXv2bF555ZVG3/6N6fHHHyc9PZ0HH3ywRntq+fLljB07tq6XulROC9FUbnpISNO07UCtF9arikozGUhs5LjqZcGCBURHR3PmzBnCwsJ+7Qx2r9YZBFBgibGQ3z2fxcsWo2kaDz/8sK0zCODj48P48eNZvnw5+fn5dl8AAEop2rRpg5eXV415ERER9O3bl7179wLYlsnMzCQuLs5WvADb5aeLFi1i7NixtgY7gF6vJzY2lo8++oiysrIm2mpN48MPP2Tw4MF2l926ubkxatQoDh48yKFDhxwYnXNZsGABI0eOtHU8ANzd3XnwwQfJzc3FbDbzyaJPyA/N/7WhAnZ5/M1333D//feTlJQEVGzr+Ph4ysvL+fHHH4mNja2RWw899BApKSlYLBZSUlKIiYmxNVYAPDw8iI+PZ/PmzQ2+l+bdd98lKirK7si0u7s7sbGxbNiwgXPnzjXofZvau+++y/Dhw+32iYeHB3FxcXz77bdcvHjRgdG1PMuWLaNfv362ziBUXKqYmZ1J+Z3lddbnVWtX0bZtWyIjIyksLLTrDAJ07dqVwYMHk5SUxLhx4+xq67Fjx2xnAqvodDrGjBmDUoqSkhKKi4tt83x9fRk9ejRz587l8OHD7Nu3z64zCNClSxfuuecekpOTAQgJCWHgwIHMmzevkbdY0/vwww8ZNGhQrTU6IyODgwcPOjC6pjd37lxGjx5t6wwuXLqQgrCCGjXWGmslv3s+/130X8rKyrjvvvtqfN/feeedpKWloZTirrvuIjQ0lKysLAoKCggNDcXd3b3W+vrQQw9x7do1li1bZhfbO++8w3333Wf3SApPT0/i4uL48ssvycvLq3WdPvroI9vnV9HpdERHR5OdnU1qaipQ0Ul87733iI2NtbtKo23btsTExPD+++9jsVgaummb3OXLl1mzZk2t7anhw4czd+5cB0YnhGu41WsERgCXNE071hjB/FZHjx4lPDycixcv0rVr1187gzGWmseEKhsdxb2KsbhZar0ErFu3bphMJrp161bjOv+cnBz8/f0JDw+v9R6AHj16kJOTY/u7pKSEjh071nq/SUREBKWlpYSEhNSYFxQUhFKKCxcu1HMrOIfU1NRa7z9zc3MjPDycffv2NX9QTurIkSOEh4fXmN6mTRs6duxIkamIwshC+0ZzlWqN56S9SZSUlNhmubu7061bN8xmc525pdPpKCws5OLFi7XGoNfrCQ4OJjs7u0Hrtn///lrf18vLi9DQUKc9MHDgwIE690nXrl2pftmZuLmDBw/a1YOqBnh+93z7BniVanl9Mfcier2esLAwu85ZlYiICNzd3WvU1pycHNulcNXpdDrCwsLw9/ev0bEPCwsjMzOTtLQ0wsPD6/y86q/r3r07e/bsuek2cDapqal2HfQqbm5uhIWFuXSNtlqtHD16lLCwMLtcvFFboTCikCJzkV2NrRIREWH3fR8REUG7du24fPkyUHFPX131tWPHjvz000920w8ePFjr8t7e3nTq1InMzMxa12vPnj21fu9W5fz+/fuBisuhjUYjwcHBNZbt3LkzpaWlXLlypdbPcAYZGRl06dLF7iB+lYiICNLT0x0QlRCu5VY7hFO4ydlBpdQzSqm9Sqm9jT2anK+vLwUFBej1eg5lHCKPvNoLvC0YIB40P41tP2+rMbuoqAilFNeuXasxT6/XYzabKSgoqPWt8/Pz7YqVp6cnRqOR2i7JLSgoQKfT1fo5JpOJ4uJi/Pz86lgJ51R1309tjEZjrYM3tESNkc9+fn61bitN07h05RJmb3PF/Sw3yGNLjIV8lV9jGaPRWGcOm0wm2/0wer2+1hisViv5+fn4+vo2YM0gICCgznXLy8tz2jxoqXE3hqao0e3bt7fbntt3bq9XfbbEWLD6Wjl77mydo48WFBSgaVqN2qrX62/4GpPJVONAoNFoxNvb+4b1q+o7pvrf1c/8tBSBgYF1bh9XrdFVZ9aUUnh7e2M0Guudi1qcRqm+lO07t9eYXVtOmM1m2zR3d/c666vRaKwxkIu/v3+dy9+o/twobwsLC22va9euHRaLxe4MeZWSkhLMZrNTD87SoUMH8vPz62xPBQQEOCAqIVxLgzuESil3YCJww5uCNE37VNO0wZqmDfb392/ox9Vq4sSJJCUl0a9fP/Lz8vG3+uP2vRvUdVtk5f0B5IOXZ82btLdv306vXr04ffo0ly5dspsXGRnJlStXOHnypO0oYBWTyURycjL9+/e3Tbtw4QJKKQ4fPmy3rNVqJSUlhb59+9ou96tuz549REdH09jbqqk9/fTT7N27l/LycrvpZ86cwWAwEBMT46DIGldj5PPEiRPZtWsXVqvVbvovv/yC3ksPeeC2+cZ57LbZDTejG12Cfx2V9uTJk+Tn5xMSEsLu3btrvCwlJYXw8HD0ej39+/dnx44dNWI4fPgw/v7+REZGNmjdZs6cSUpKSo33PXr0KF5eXtx9990Net+m9uSTT7Jnz55a94mfn59Lj8TYFDV60qRJ7N27F7PZDMDI4SMJIKCi/t4kr92L3LlWdA2DwcDp06ftFikvLyc5OZm2bdvWqK39+vVjx44dNS63P3/+PBcuXMBsNttdTqppGklJSTz22GOMHTuWgoICTp06VePzdu/ebavt5eXlpKWlMXPmzAZsFcdqjTW6qqOglGLatGns3r3blos3ayu4bXZD5Sl6325/r6jJZCIlJcWWE4WFhezfvx9PT0+6dOlCWVkZbm5u/Pzzz7XWE7PZzEsvvWQ3/YknniA5OblGhyc9PZ3Q0NBaz3xDxT5NS0urNefPnz9vG/yoTZs2PPTQQ7ZLn6tLSUkhPj7eqQf86tevHwEBAbW2p5KTk5kxY4aDIhPCddx0UBkApVR34H/VB5VRSsUBr2madl99P6yxB5UpLi5m+vTpmM1m3N3dOXv2LBY3CyW9SrDGWu2P/lV2Bj0yPCgrrijYvXv3pn///litVlJTUzlz5gzff/89e/bs4c033+Tuu+8mNDSU3Nxc9uzZQ1BQEFlZWWiaxrBhw+jevTsGg4Gff/4ZnU5HTEwMXl5eZGZmcvz4cebPn8/s2bPp27cvkZGRlJSU2IYvT0xMZNSoUfj6+tK3b190Oh1Hjhzh3Llz7N69u9GG/28uFouFRx55hIMHDzJo0CB8fX3Jzs5m//79LFu2jHHjxlUt6jI3eDc0n0tLS5kxYwa5ubkMHTqUtm3b2oa2t1qt9O7dm+xz2RgjjDXPFFbmsS5dhypXjBs3jg4dOpCVlUVqaip+fn4sWrSI2bNnExAQwJ133olOp+PAgQNkZmYyduxYgoKCbJ9XdU+WXq8nKyuLw4cP89lnn9G1a9cGDSpTWlpKTEwMly5dYsCAAbbR9Q4ePMh3333HsGHDfvN7NoeSkhLGjBmDwWBgwIABttFRMzIy2LRpE0OGDKnrpS6Tz9B4NVrTNObMmUNqaipDhgyhffv2ZGZmsmvPLhhAnXntdsgNb8+Ke1/NZrNthNDIyEiMRiO7du2iT58+zJw5k2effZa+ffvSs2dPSkpKSEtLw2Aw4O7uzogRI/D39+fEiRMkJyejlMLLy4tevXpx++23U15ezqFDhzCbzezatYv27duzefNmEhISGDBgAGFhYRiNRnbs2AHAuHHjMBqNpKWlMXDgQFatWlXr5aXOzGKxMGnSJNLT0201+tSpU+zbt696jXapfK4+qExubi5RUVF4enrSs2dPvt/2PcYII8RRIxfVJoXvCV+Cg4I5efIkUVFRhIWF2b7vq+4/vXjxIjt27KC0tJTY2Fg8PT3Zu3cvd999N0lJSbi7uzNs2DD0ej1HjhwhLS2NV155hXfeeccuzsLCQqKjoyktLaV///54eXmRlZVFZmYmW7ZsoV+/frWuX9XI0ikpKQwaNIiAgADbo1g+//xzHn74YduyFy5cYNiwYXTo0IE+ffrYDlhfunSJpKQku3tLnVFqaiqxsbH06dOHHj16UFJSwoEDB/D39+enn35qNSNBC9FU6jPKaCIQDQQCl4B/apq2UCm1GEjWNO2/9f2wpnjshMlk4ptvvmHdunW2a+BzDDmU9y3/tdGhARtAd1CHfzt/OnToYLum3s3NDZ1OR9++fZk/f77tzNyRI0f44osvOHLkCEFBQTz66KMMGjQILy8v3njjDdtZkLCwMP785z9z5coVEhMTMZlMxMXF8fzzz9O5c2dOnz7NRx99xJYtW/Dx8WH69OlMnz4dLy8vCgoKWLBgAV999RUWi4Xx48fz3HPPtcjLkaCiwbFq1So+++wzDAYDQ4cO5cUXX7x+iG2XKc63ks9ms5lvv/2WJUuWcOXKFXQ6HQMGDGDAgAEkJSVx6dIlzl0+R+ntpTXyWKUrBt45kLFjx5KYmEheXp7tCPCsWbPw8fGhsLCQVatWsXnzZiwWC9HR0fj4+PDjjz9SVFTEkCFDSEhIIDU1lXXr1lFcXMzQoUOZPn06wcHB5OXlNfixE2azmS+//JLFixdjNBqJjo7mhRdeqPX+JWdiMplYunQpX3zxBYWFhYwaNYoXXnjBbsCGWrhMPkPj1mhN0/jhhx9YtWoVly9fRq/XU1RUxJmLZyjrU2af1xvBI8ODQL9ASktLgYr7pwoLCyktLcXNzY3OnTvz3HPPER8fj5ubG+fPn2fp0qWkpKTQtm1bxo8fz4gRIzh//jzvvvsu586dw93dndGjR/PWW2/h4+PDxx9/zPr16/Hw8GDKlCk89dRTdpfKHT16lHnz5pGcnGx77mBmZiZ79+4lKCiIp59+mkmTJrW4zmCV62v0kCFDeOmll6rXaJfK5+sfO1FYWMjChQtJTEykpKSEMxfPUBhR+OsBZA3cf3BHpSva6Nrg4eGBl5cXpaWllJeX4+bmRps2bSguLqa8vBydTscdd9xhG1SmY8eOPPPMMzzyyCOYTCZeffVVVq5ciclkIjg4mLlz5zJ+/PhaYy0pKeHzzz9n2bJlFBcXM3bsWP70pz/dtKNmtVpZvXo1n376KZcvX2bQoEG8/PLL9O1bY1B48vLy+OSTT1i9ejWapjFx4kRmzZplN5iNMzt9+jTz589ny5YteHt7M23aNKZPn36zZ4O6VE4L0VTqdYawsTRFh7A2+fn5JExP4FzgOcrGlOHxowddr3ZlxZIVt3Qp5q00koWNyxTnps7npsrj+pBcrzeXyWdonhrdlHkteXvLXCqfr+8QXi83N5dh0cPI9svGPNqM50+ehBWEsXvb7hbTSRI35VI5LURTce4nkTaQv78/K5asoOvVrnh81nyNaCEak+SxcEWS18JZtG/fnt3bdhNWEIbHQg/pDAohWi2X7BDCr42OqTFTpbEhWizJY+GKJK+Fs6jqFP5x8h+lMyiEaLXcHR1AU/L39+e1Oa85OgwhbonksXBFktfCWbRv354PP/jQ0WEIIYTDuOwZQiGEEEIIIYQQNyYdQiGEEEIIIYRopaRDKIQQQgghhBCtlHQIhRBCCCGEEKKVkg6hEEIIIYQQQrRS0iEUQgghhBBCiFZKOoRCCCGEEEII0UopTdOa78OUygNy6rl4AJDXhOE0hB/1j785BAJXHR1ENfWJ56qmaXHNEUxT+435fCOS6/XjjPl+1FXyGRqc086Uv86Wt86Us62qPgMopa4BRxwdRyNwpjy6Vc29Li6V00I0lWbtEP4WSqm9mqYNdnQc1TlbTBKPa3DG7SYx3ZyzxeMozrQdnCkWcK54nCmW5uIq6+wq6wGutS5CuBK5ZFQIIYQQQgghWinpEAohhBBCCCFEK+XMHcJPHR1ALZwtJonHNTjjdpOYbs7Z4nEUZ9oOzhQLOFc8zhRLc3GVdXaV9QDXWhchXIbT3kMohBBCCCGEEKJpOfMZQiGEEEIIIYQQTcjhHUKlVJxSKlMpdVwpNaeW+d2UUluVUvuVUgeVUuOaOJ5FSqnLSqmMOuYrpdT8yngPKqUGOjieqZVxHFJK7VZK9XdkPNWWu1spVa6UmtSU8TizeuT2v5VSByp/spRS+dXmWarNW9eIMTU4v5VSjyuljlX+PN5M8dSZ30qpU5XTDyil9jZGPPWMKVopVVBt//yj2rwb7vOWypnqtNTohsdSbTmXqc/Olg8N5Ux5dKtaYx4K0eJpmuawH8ANOAGEA55AOtD7umU+BZ6r/L03cKqJYxoJDAQy6pg/DtgIKOAeIMXB8QwDAip/j3d0PNX26xZgAzDJkTnmqJ/65PZ1yz8PLKr2d5GD8qnW/AbaAycr/w2o/D2gGeKpM7+BU0CgA7ZRNPC/W93nLeXH2eq01OiGx1Jtf7pMfXa2fHCFPGrqdalcxqXyUH7kp6X/OPoM4RDguKZpJzVNMwMrgPHXLaMBvpW/+wEXmjIgTdO2A7k3WGQ8sESrkAz4K6U6OyoeTdN2a5pW9VDoZKBrU8VSn3gqPQ+sBi43ZSxOrj65Xd0UILGpg7qF/I4FftA0Lbcy334Abvlhv86W3/WJ6QZ+6z5vKZyqTkuNbngslVyqPjtbPjSUM+XRrWqNeShES+foDmEX4Gy1v89VTqvu/4DHlFLnqDiS9HzzhFan+sTsKE9RcSTUYZRSXYAJwH8cGYcTqHeeKKVCgTAqjpZWaaOU2quUSlZKPdxkUdZUV9zOkPfX57cGfK+USlNKPdPMsdyrlEpXSm1USvWpnOYM26gptLQ67cz7waE1upXWZ2fOh4Zy+Hf9rWileSiEU3N3dAD1MAVYrGnaB0qpe4GlSqm+mqZZHR2YM1FK3U/Fl8RwB4cyD3hV0zSrUsrBobQYCcDXmqZZqk0L1TTtvFIqHNiilDqkadoJB8XncHXk9/DKbdQR+EEpdbTyyHRT20fF/imqvFduLdCjGT7XmUmdvgknqdHzkPrcojlJHt2qeUgeCuFUHN0hPA+EVPu7a+W06p6i8tI0TdOSlFJtgEAcd5lBfWJuVkqpfsBnQLymaQZHxgIMBlZUFvlAYJxSqlzTtLUOjar5/ZY8SQD+X/UJmqadr/z3pFJqGzCAivu4mlpdcZ+n4t656tO3NUM8deZ3tW10WSn1DRWXNjZ5h1DTNGO13zcopT5WSgXihLWhkbS0Ou10+8GJanRrrM9Olw8N5UR5dKtaYx4K4dQcfcloKtBDKRWmlPKkomF8/YiKZ4DRAEqpO4A2wJVmjdLeOmB65chl9wAFmqblOCoYpVQ3YA0wTdO0LEfFUUXTtDBN07prmtYd+BqY3UqLfH1yG6XU7VQM0pJUbVqAUsqr8vdAIAr4pVmirju/NwMxlbEFADGV05pUXfmtlGqnlPKp+r0ynhuOaNeIMd2mKlsySqkhVNRRA/Xc5y1QS6vTUqPr0Errs1PlQ0M5Ux7dqlaah0I4NYeeIdQ0rVwp9UcqGpZuVIyyeFgp9SawV9O0dcCfgQVKqZeouGfoCU3TtKaKSSmVSMWZkMDK+2H+CXhUxvtfKu6PGQccB4qBGU0VSz3j+QfQAfi4so1armnaYAfGI6h3bkNF43rFdTl9B/CJUspKRWfjXU3TGqVD2ND81jQtVyn1FhWdA4A3NU1ryMArvzWeuvK7E/BN5TR3YLmmaZtuNZ56xjQJeE4pVQ6UAAmV+6/Wfd4YMTmSs9VpqdG3FIvLcbZ8aChnyqNb1RrzUIiWTjVh30oIIYQQQgghhBNz9CWjQgghhBBCCCEcRDqEQgghhBBCCNFKSYdQCCGEEEIIIVop6RAKIYQQQgghRCslHUIhhBBCCCGEaKWkQyiEEEIIIYQQrZR0CIUQQgghhBCilZIOoRBCCCGEEEK0Uv8fCOGW1hl9N8oAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 864x360 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x360 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "row_count = 1\n",
    "column_count = len(tf_plot_data['cost'].unique())\n",
    "marker_size = 8\n",
    "edgecolor = 'black'\n",
    "linewidth = 1\n",
    "group_columns = ['agent_building_id', 'deployment_building_id']\n",
    "\n",
    "for c in group_columns:\n",
    "    summary_data = tf_plot_data.copy()\n",
    "    self_data = summary_data[(summary_data['deployment_building_id'] == summary_data['agent_building_id'])].copy()\n",
    "    self_data = self_data.rename(columns={'value': 'ref_value'})\n",
    "    summary_data = summary_data.drop(self_data.index)\n",
    "    rbc_data = RBC_REFERENCE_COST_SUMMARY.copy()\n",
    "    rbc_data = rbc_data.rename(columns={'value': 'rbc_value'})\n",
    "    summary_data = summary_data.merge(self_data[['cost', 'ref_value', c]], on=['cost', c], how='left')\n",
    "    summary_data = summary_data.merge(rbc_data[['cost', 'rbc_value', 'deployment_building_id']], on=['cost', 'deployment_building_id'], how='left')\n",
    "    negative_transfer_summary = summary_data.copy()\n",
    "    negative_transfer_summary['difference'] = negative_transfer_summary['value'] - negative_transfer_summary['rbc_value']\n",
    "    negative_transfer_summary['polarity'] = negative_transfer_summary['difference']/negative_transfer_summary['difference'].abs()\n",
    "    negative_transfer_summary = negative_transfer_summary.groupby(['cost', 'deployment_building_id', 'polarity']).size().reset_index(name='count')\n",
    "    summary_data['difference'] = summary_data['value'] - summary_data['ref_value']\n",
    "    summary_data = summary_data.groupby(['cost', c,])[['difference']].agg(['mean', 'std'])\n",
    "    summary_data.columns = ['mean', 'std']\n",
    "    summary_data = summary_data.reset_index()\n",
    "    summary_data['polarity'] = '+'\n",
    "    summary_data.loc[summary_data['mean'] < 0, 'polarity'] = '-'\n",
    "    summary_data.loc[summary_data['mean'] == 0, 'polarity'] = ':'\n",
    "    average_summary_data = summary_data.groupby(['cost', 'polarity'])[['mean', 'std']].agg(['count', 'mean'])\n",
    "    print('Summary grouping:', c)\n",
    "    # display(negative_transfer_summary)\n",
    "    display(summary_data)\n",
    "    display(average_summary_data)\n",
    "\n",
    "for x, t in zip(['agent', 'deployment'], ['Source', 'Target']):\n",
    "    fig, _ = plt.subplots(row_count, column_count, figsize=(3.0*column_count, 5.0*row_count), sharey=True, gridspec_kw={'wspace': 0.4})\n",
    "    \n",
    "    for i, (ax, c) in enumerate(zip(fig.axes, cost_labels)):\n",
    "        c_data = tf_plot_data[tf_plot_data['cost']==c].copy()\n",
    "        d_c_data = c_data[c_data['deployment_building_id'] == c_data['agent_building_id']][[\n",
    "            'deployment_building_id', 'value'\n",
    "        ]].copy()\n",
    "        rbc_data = RBC_REFERENCE_COST_SUMMARY[(RBC_REFERENCE_COST_SUMMARY['cost']==c)].copy()\n",
    "        building_ids = sorted(c_data[f'{x}_building_id'].unique().tolist())\n",
    "\n",
    "        sns.stripplot(y=f'{x}_building_id', x='value', data=c_data, ax=ax, color='grey', jitter=False, clip_on=False, size=marker_size*0.9, edgecolor=edgecolor, linewidth=linewidth, orient='h', label='Sources SAC policies -> target')\n",
    "        sns.stripplot(y='deployment_building_id', x='value', data=d_c_data,  ax=ax, color='green', jitter=False, clip_on=False, size=marker_size, edgecolor=edgecolor, linewidth=linewidth, marker='D', orient='h', label='Target\\'s SAC policy')\n",
    "        \n",
    "\n",
    "        if x == 'deployment':\n",
    "            rbc = sns.stripplot(y='agent_building_id', x='value', data=rbc_data, ax=ax, color='red', jitter=False, clip_on=False, size=marker_size, edgecolor=edgecolor, linewidth=linewidth, marker='^', orient='h', label='Target\\'s RBC policy')\n",
    "        else:\n",
    "            pass\n",
    "\n",
    "        ax.fill_betweenx(y=range(-1, len(building_ids) + 1), x1=c_data['value'].min(), x2=1.0, label='KPI below baseline (no battery)', zorder=0, color='black', alpha=0.15)\n",
    "\n",
    "        for s in ['right','top']:\n",
    "            ax.spines[s].set_visible(False)\n",
    "\n",
    "        ax.set_xlabel(None)\n",
    "        ax.set_ylabel(None)\n",
    "\n",
    "        if i == column_count - 1:\n",
    "            handles, labels = ax.get_legend_handles_labels()\n",
    "            unique = [(h, l) for i, (h, l) in enumerate(zip(handles, labels)) if l not in labels[:i]]\n",
    "            ax.legend(bbox_to_anchor=(1.0,1.0), loc='upper left', framealpha=0.4, ncol=1, *zip(*unique))\n",
    "        else:\n",
    "            pass\n",
    "\n",
    "        ax.yaxis.set_major_locator(ticker.FixedLocator([i - 1 for i in building_ids]))\n",
    "        ax.set_yticklabels(building_ids)\n",
    "        ax.set_title(cost_labels[c])\n",
    "\n",
    "    plt.savefig(os.path.join(FIGURES_DIRECTORY,f'deployment_strategy_2_0_{t.lower()}_building_cost_summary.pdf'),bbox_inches='tight',transparent=True)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# row_count = 1\n",
    "# column_count = 1\n",
    "# marker_size = 8\n",
    "# edgecolor = 'black'\n",
    "# linewidth = 1\n",
    "\n",
    "# for c, c_data in tf_plot_data.groupby(['cost']):\n",
    "#     print(c)\n",
    "#     d_c_data = c_data[c_data['deployment_building_id'] == c_data['agent_building_id']][[\n",
    "#         'deployment_building_id', 'value'\n",
    "#     ]].copy()\n",
    "#     s_data = c_data.drop(d_c_data.index)[['agent_building_id', 'value']].copy()\n",
    "#     s_data = s_data.rename(columns={'agent_building_id': 'building_id'})\n",
    "#     s_data['label'] = 'Source'\n",
    "#     t_data = c_data.drop(d_c_data.index)[['deployment_building_id', 'value']].copy()\n",
    "#     t_data = t_data.rename(columns={'deployment_building_id': 'building_id'})\n",
    "#     t_data['label'] = 'Target'\n",
    "#     c_data = pd.concat([s_data, t_data], ignore_index=True, sort=False)\n",
    "#     rbc_data = RBC_REFERENCE_COST_SUMMARY[(RBC_REFERENCE_COST_SUMMARY['cost']==c)].copy()\n",
    "    \n",
    "#     fig, ax = plt.subplots(row_count, column_count, figsize=(12*column_count, 2.0*row_count))\n",
    "#     sns.stripplot(x=f'building_id', y='value', data=c_data, ax=ax, hue='label', jitter=False, dodge=True, clip_on=False, size=marker_size*0.9, edgecolor=edgecolor, linewidth=linewidth)\n",
    "#     sns.stripplot(x='deployment_building_id', y='value', data=d_c_data,  ax=ax, color='green', jitter=False, clip_on=False, size=marker_size*0.9, edgecolor=edgecolor, linewidth=linewidth, marker='D', label='Target = Source')\n",
    "\n",
    "#     if x == 'deployment':\n",
    "#         sns.stripplot(x='agent_building_id', y='value', data=rbc_data, ax=ax, color='red', jitter=False, clip_on=False, size=marker_size, edgecolor=edgecolor, linewidth=linewidth, marker='^', label='RBC')\n",
    "#     else:\n",
    "#         pass\n",
    "\n",
    "#     for s in ['right','top']:\n",
    "#         ax.spines[s].set_visible(False)\n",
    "\n",
    "#     ax.set_xlabel(f'Building')\n",
    "#     ax.set_ylabel(None)\n",
    "#     handles, labels = ax.get_legend_handles_labels()\n",
    "#     unique = [(h, l) for i, (h, l) in enumerate(zip(handles, labels)) if l not in labels[:i]]\n",
    "#     ax.legend(bbox_to_anchor=(0.5, -0.3), loc='upper center', framealpha=0, ncol=4, *zip(*unique))\n",
    "#     building_ids = sorted(c_data[f'building_id'].unique().tolist())\n",
    "#     ax.xaxis.set_major_locator(ticker.FixedLocator([i - 1 for i in building_ids]))\n",
    "#     ax.set_xticklabels(building_ids)\n",
    "#     ax.set_xticks([i - 0.5 for i in building_ids], minor=True)\n",
    "#     ax.grid(visible=True, which='minor', axis='x')\n",
    "\n",
    "#     # plt.savefig(os.path.join(FIGURES_DIRECTORY,f'deployment_strategy_2_0_{t.lower()}_building_{c}_cost_summary.pdf'),bbox_inches='tight',transparent=True)\n",
    "#     plt.show()\n",
    "#     # assert False"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# District-Level Scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "district_cost_data = DATABASE.query_table(query.get_transfer_learning_district_cost_summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"4\" halign=\"left\">difference</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>min</th>\n",
       "      <th>max</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>cost</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>carbon_emission</th>\n",
       "      <td>0.060609</td>\n",
       "      <td>0.145248</td>\n",
       "      <td>0.095143</td>\n",
       "      <td>0.025714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>daily_peak</th>\n",
       "      <td>0.017387</td>\n",
       "      <td>0.239188</td>\n",
       "      <td>0.098307</td>\n",
       "      <td>0.061411</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>electricity_consumption</th>\n",
       "      <td>0.056846</td>\n",
       "      <td>0.137854</td>\n",
       "      <td>0.089380</td>\n",
       "      <td>0.026398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>load_factor</th>\n",
       "      <td>0.007713</td>\n",
       "      <td>0.053377</td>\n",
       "      <td>0.029957</td>\n",
       "      <td>0.012977</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>price</th>\n",
       "      <td>0.054959</td>\n",
       "      <td>0.212763</td>\n",
       "      <td>0.104437</td>\n",
       "      <td>0.044901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ramping</th>\n",
       "      <td>0.168238</td>\n",
       "      <td>0.415085</td>\n",
       "      <td>0.268219</td>\n",
       "      <td>0.070670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>zero_net_energy</th>\n",
       "      <td>-0.111495</td>\n",
       "      <td>0.033246</td>\n",
       "      <td>-0.000943</td>\n",
       "      <td>0.044188</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        difference                              \n",
       "                               min       max      mean       std\n",
       "cost                                                            \n",
       "carbon_emission           0.060609  0.145248  0.095143  0.025714\n",
       "daily_peak                0.017387  0.239188  0.098307  0.061411\n",
       "electricity_consumption   0.056846  0.137854  0.089380  0.026398\n",
       "load_factor               0.007713  0.053377  0.029957  0.012977\n",
       "price                     0.054959  0.212763  0.104437  0.044901\n",
       "ramping                   0.168238  0.415085  0.268219  0.070670\n",
       "zero_net_energy          -0.111495  0.033246 -0.000943  0.044188"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1008x288 with 7 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "column_count_limit = 7\n",
    "costs = district_cost_data['cost'].unique()\n",
    "row_count = math.ceil(len(costs)/column_count_limit)\n",
    "column_count = min(column_count_limit, len(costs))\n",
    "fig, _ = plt.subplots(row_count, column_count, figsize=(column_count*2.0, row_count*4.0), gridspec_kw={'wspace': 0.2}, sharey=True)\n",
    "plot_data = district_cost_data[district_cost_data['episode']==district_cost_data['episode'].max()].copy()\n",
    "plot_data['agent'] = 'SAC'\n",
    "summary_data = plot_data.copy()\n",
    "no_transfer_data = NO_TRANSFER_COST_SUMMARY[\n",
    "    (NO_TRANSFER_COST_SUMMARY['episode']==NO_TRANSFER_COST_SUMMARY['episode'].max()) & (NO_TRANSFER_COST_SUMMARY['scope']=='district')\n",
    "].copy()\n",
    "no_transfer_data = no_transfer_data.rename(columns={'value': 'no_transfer_value'})\n",
    "summary_data = summary_data.merge(no_transfer_data[['cost', 'no_transfer_value']], on=['cost'], how='left')\n",
    "summary_data['difference'] = summary_data['value'] - summary_data['no_transfer_value']\n",
    "summary_data = summary_data.groupby(['cost'])[['difference']].agg(['min', 'max', 'mean', 'std'])\n",
    "display(summary_data)\n",
    "\n",
    "for ax in fig.axes[len(costs):]:\n",
    "    ax.set_visible(False)\n",
    "\n",
    "for i, (ax, c) in enumerate(zip(fig.axes, cost_labels)):\n",
    "    c_data = district_cost_data[district_cost_data['cost']==c].sort_values('source_building_id')\n",
    "    c_data['source_building_id'] = c_data['source_building_id'].astype(str)\n",
    "    sns.barplot(x='value', y='source_building_id', data=c_data, ax=ax, color='grey', clip_on=False)\n",
    "    # sns.scatterplot(x='value', y='source_building_id', data=c_data, ax=ax, color='grey', clip_on=False, s=60)\n",
    "    rbc_value = RBC_REFERENCE_COST_SUMMARY[\n",
    "        (RBC_REFERENCE_COST_SUMMARY['cost']==c) & (RBC_REFERENCE_COST_SUMMARY['scope']=='district')\n",
    "    ]['value'].iloc[0]\n",
    "    no_transfer_value = NO_TRANSFER_COST_SUMMARY[\n",
    "        (NO_TRANSFER_COST_SUMMARY['episode']==NO_TRANSFER_COST_SUMMARY['episode'].max()) & (NO_TRANSFER_COST_SUMMARY['cost']==c) & (NO_TRANSFER_COST_SUMMARY['scope']=='district')\n",
    "    ]['value'].iloc[0]\n",
    "    ax.axvline(1.0, color='black', linestyle='--', label='Baseline (no battery)', clip_on=False)\n",
    "    ax.axvline(rbc_value, color='red', linestyle='--', label='RBC', clip_on=False)\n",
    "    ax.axvline(no_transfer_value, color='blue', linestyle='--', label='SAC (No transfer - DS.1)', clip_on=False)\n",
    "    ax.set_xlabel(None)\n",
    "    ax.set_title(cost_labels[c])\n",
    "\n",
    "    for s in ['right','top']:\n",
    "        ax.spines[s].set_visible(False)\n",
    "\n",
    "    # for j, p in enumerate(ax.patches):\n",
    "    #     # ax.text(c_data['value'].max(), p.get_y() + p.get_height()/2.0, f'{p.get_width():0.2f}', ha='left', va='center')\n",
    "\n",
    "    #     if round(p.get_width(), 2) == c_data['value'].round(2).min():\n",
    "    #         # p.set_hatch('/')\n",
    "    #         p.set_color('green')\n",
    "    #     else:\n",
    "    #         pass\n",
    "    \n",
    "    if i == len(costs) - 1:\n",
    "        ax.legend(\n",
    "            title='Reference policy KPI',\n",
    "            bbox_to_anchor=(0.5, 0.08),\n",
    "            loc='upper center', \n",
    "            bbox_transform=fig.transFigure,\n",
    "            framealpha=0,\n",
    "            ncol=3\n",
    "        )\n",
    "    else:\n",
    "        pass\n",
    "\n",
    "    if i == 0:\n",
    "        ax.set_ylabel(None)\n",
    "    else:\n",
    "        ax.set_ylabel(None)\n",
    "\n",
    "plt.savefig(os.path.join(FIGURES_DIRECTORY,f'deployment_strategy_2_0_district_cost_summary.pdf'),bbox_inches='tight',transparent=True)\n",
    "# plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Save"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "building_cost_data['scope'] = 'building'\n",
    "pd.concat([building_cost_data,], ignore_index=True, sort=False).to_csv(\n",
    "    os.path.join(KWARGS['summary_directory'], 'deployment_strategy_2_0_cost_summary.csv'), index=False\n",
    ")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.7.3 ('env': venv)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
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