{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "ec70952e-52db-4d8d-acbf-cfa03b76e076",
   "metadata": {},
   "source": [
    "# Figure 3: Intersection of errors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "0aea95ca-326b-418d-b9ea-f270c93ec0af",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR 1: PROJ: proj_create_from_database: Open of /srv/conda/envs/notebook/share/proj failed\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "from scipy.interpolate import InterpolatedUnivariateSpline\n",
    "\n",
    "import smpsite as smp\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "549965c2-0bbb-4d28-9ccb-8f2816c2f554",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Unnamed: 1</th>\n",
       "      <th>error_angle_mean</th>\n",
       "      <th>error_angle_median</th>\n",
       "      <th>error_angle_25</th>\n",
       "      <th>error_angle_75</th>\n",
       "      <th>error_angle_95</th>\n",
       "      <th>error_angle_std</th>\n",
       "      <th>error_angle_S2</th>\n",
       "      <th>error_vgp_scatter</th>\n",
       "      <th>...</th>\n",
       "      <th>N</th>\n",
       "      <th>n0</th>\n",
       "      <th>kappa_within_site</th>\n",
       "      <th>site_lat</th>\n",
       "      <th>site_long</th>\n",
       "      <th>outlier_rate</th>\n",
       "      <th>secular_method</th>\n",
       "      <th>kappa_secular</th>\n",
       "      <th>ignore_outliers</th>\n",
       "      <th>total_simulations</th>\n",
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       "      <td>1.591223</td>\n",
       "      <td>11.575765</td>\n",
       "      <td>1.963166</td>\n",
       "      <td>...</td>\n",
       "      <td>20</td>\n",
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       "      <td>0.06</td>\n",
       "      <td>G</td>\n",
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       "      <td>True</td>\n",
       "      <td>5000</td>\n",
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       "      <th>1</th>\n",
       "      <td>1</td>\n",
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       "      <td>1.674369</td>\n",
       "      <td>1.572390</td>\n",
       "      <td>0.992247</td>\n",
       "      <td>2.215238</td>\n",
       "      <td>3.343781</td>\n",
       "      <td>0.893670</td>\n",
       "      <td>3.601998</td>\n",
       "      <td>4.063939</td>\n",
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       "      <td>vandamme</td>\n",
       "      <td>5000</td>\n",
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       "      <td>5.944138</td>\n",
       "      <td>5.464739</td>\n",
       "      <td>3.456442</td>\n",
       "      <td>7.867387</td>\n",
       "      <td>11.994503</td>\n",
       "      <td>3.282057</td>\n",
       "      <td>46.102518</td>\n",
       "      <td>10.720174</td>\n",
       "      <td>...</td>\n",
       "      <td>20</td>\n",
       "      <td>5</td>\n",
       "      <td>50</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.30</td>\n",
       "      <td>G</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>5000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>3.132695</td>\n",
       "      <td>2.916515</td>\n",
       "      <td>1.863807</td>\n",
       "      <td>4.135228</td>\n",
       "      <td>6.335359</td>\n",
       "      <td>1.695366</td>\n",
       "      <td>12.687471</td>\n",
       "      <td>33.488342</td>\n",
       "      <td>...</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "      <td>50</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.20</td>\n",
       "      <td>G</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>5000</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>1.879239</td>\n",
       "      <td>1.752972</td>\n",
       "      <td>1.139824</td>\n",
       "      <td>2.499530</td>\n",
       "      <td>3.687284</td>\n",
       "      <td>0.999187</td>\n",
       "      <td>4.529712</td>\n",
       "      <td>4.391926</td>\n",
       "      <td>...</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "      <td>50</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.10</td>\n",
       "      <td>G</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>5000</td>\n",
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       "      <td>5.429353</td>\n",
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       "      <td>11.850008</td>\n",
       "      <td>3.244385</td>\n",
       "      <td>45.276954</td>\n",
       "      <td>7.106347</td>\n",
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       "      <td>0.38</td>\n",
       "      <td>G</td>\n",
       "      <td>NaN</td>\n",
       "      <td>vandamme</td>\n",
       "      <td>5000</td>\n",
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       "      <th>182</th>\n",
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       "      <td>0</td>\n",
       "      <td>3.113708</td>\n",
       "      <td>2.942645</td>\n",
       "      <td>1.862477</td>\n",
       "      <td>4.105940</td>\n",
       "      <td>6.106538</td>\n",
       "      <td>1.637183</td>\n",
       "      <td>12.375009</td>\n",
       "      <td>2.090176</td>\n",
       "      <td>...</td>\n",
       "      <td>20</td>\n",
       "      <td>5</td>\n",
       "      <td>50</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.24</td>\n",
       "      <td>G</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "      <td>5000</td>\n",
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       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>183</td>\n",
       "      <td>0</td>\n",
       "      <td>2.543727</td>\n",
       "      <td>2.365439</td>\n",
       "      <td>1.538118</td>\n",
       "      <td>3.382425</td>\n",
       "      <td>4.994684</td>\n",
       "      <td>1.353327</td>\n",
       "      <td>8.301677</td>\n",
       "      <td>24.887777</td>\n",
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       "      <td>100</td>\n",
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       "      <td>50</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.12</td>\n",
       "      <td>G</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>5000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>184</td>\n",
       "      <td>0</td>\n",
       "      <td>10.411591</td>\n",
       "      <td>9.415827</td>\n",
       "      <td>5.874237</td>\n",
       "      <td>13.914665</td>\n",
       "      <td>21.893309</td>\n",
       "      <td>6.225964</td>\n",
       "      <td>147.156100</td>\n",
       "      <td>28.764447</td>\n",
       "      <td>...</td>\n",
       "      <td>20</td>\n",
       "      <td>5</td>\n",
       "      <td>50</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.54</td>\n",
       "      <td>G</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "      <td>5000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>185</td>\n",
       "      <td>0</td>\n",
       "      <td>1.702919</td>\n",
       "      <td>1.598605</td>\n",
       "      <td>1.027170</td>\n",
       "      <td>2.254942</td>\n",
       "      <td>3.340235</td>\n",
       "      <td>0.899881</td>\n",
       "      <td>3.709557</td>\n",
       "      <td>3.725128</td>\n",
       "      <td>...</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "      <td>50</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.06</td>\n",
       "      <td>G</td>\n",
       "      <td>NaN</td>\n",
       "      <td>vandamme</td>\n",
       "      <td>5000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>186 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed: 0  Unnamed: 1  error_angle_mean  error_angle_median  \\\n",
       "0             0           0          3.007371            2.812011   \n",
       "1             1           0          1.674369            1.572390   \n",
       "2             2           0          5.944138            5.464739   \n",
       "3             3           0          3.132695            2.916515   \n",
       "4             4           0          1.879239            1.752972   \n",
       "..          ...         ...               ...                 ...   \n",
       "181         181           0          5.895170            5.429353   \n",
       "182         182           0          3.113708            2.942645   \n",
       "183         183           0          2.543727            2.365439   \n",
       "184         184           0         10.411591            9.415827   \n",
       "185         185           0          1.702919            1.598605   \n",
       "\n",
       "     error_angle_25  error_angle_75  error_angle_95  error_angle_std  \\\n",
       "0          1.817102        3.984293        5.972956         1.591223   \n",
       "1          0.992247        2.215238        3.343781         0.893670   \n",
       "2          3.456442        7.867387       11.994503         3.282057   \n",
       "3          1.863807        4.135228        6.335359         1.695366   \n",
       "4          1.139824        2.499530        3.687284         0.999187   \n",
       "..              ...             ...             ...              ...   \n",
       "181        3.436594        7.788003       11.850008         3.244385   \n",
       "182        1.862477        4.105940        6.106538         1.637183   \n",
       "183        1.538118        3.382425        4.994684         1.353327   \n",
       "184        5.874237       13.914665       21.893309         6.225964   \n",
       "185        1.027170        2.254942        3.340235         0.899881   \n",
       "\n",
       "     error_angle_S2  error_vgp_scatter  ...    N  n0  kappa_within_site  \\\n",
       "0         11.575765           1.963166  ...   20   5                 50   \n",
       "1          3.601998           4.063939  ...  100   1                 50   \n",
       "2         46.102518          10.720174  ...   20   5                 50   \n",
       "3         12.687471          33.488342  ...  100   1                 50   \n",
       "4          4.529712           4.391926  ...  100   1                 50   \n",
       "..              ...                ...  ...  ...  ..                ...   \n",
       "181       45.276954           7.106347  ...   20   5                 50   \n",
       "182       12.375009           2.090176  ...   20   5                 50   \n",
       "183        8.301677          24.887777  ...  100   1                 50   \n",
       "184      147.156100          28.764447  ...   20   5                 50   \n",
       "185        3.709557           3.725128  ...  100   1                 50   \n",
       "\n",
       "     site_lat  site_long  outlier_rate  secular_method kappa_secular  \\\n",
       "0        30.0        0.0          0.06               G           NaN   \n",
       "1        30.0        0.0          0.00               G           NaN   \n",
       "2        30.0        0.0          0.30               G           NaN   \n",
       "3        30.0        0.0          0.20               G           NaN   \n",
       "4        30.0        0.0          0.10               G           NaN   \n",
       "..        ...        ...           ...             ...           ...   \n",
       "181      30.0        0.0          0.38               G           NaN   \n",
       "182      30.0        0.0          0.24               G           NaN   \n",
       "183      30.0        0.0          0.12               G           NaN   \n",
       "184      30.0        0.0          0.54               G           NaN   \n",
       "185      30.0        0.0          0.06               G           NaN   \n",
       "\n",
       "     ignore_outliers total_simulations  \n",
       "0               True              5000  \n",
       "1           vandamme              5000  \n",
       "2              False              5000  \n",
       "3              False              5000  \n",
       "4               True              5000  \n",
       "..               ...               ...  \n",
       "181         vandamme              5000  \n",
       "182             True              5000  \n",
       "183            False              5000  \n",
       "184            False              5000  \n",
       "185         vandamme              5000  \n",
       "\n",
       "[186 rows x 21 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('../../outputs/fig3d_5000sim_summary.csv')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "32e0451f-8cd4-428b-b3a5-61905794228e",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_true     = df[(df.n0==5) & (df.ignore_outliers==\"True\")].sort_values(by=\"outlier_rate\")\n",
    "df_false    = df[(df.n0==1) & (df.ignore_outliers==\"False\")].sort_values(by=\"outlier_rate\")\n",
    "df_vandamme = df[(df.n0==1) & (df.ignore_outliers==\"vandamme\")].sort_values(by=\"outlier_rate\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f41d21a3-784e-431e-874b-5c18dbc32d17",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_true[\"error_kappa_theoretical\"] = df_true.apply(lambda row: smp.kappa_theoretical(smp.Params(N=row.N, \n",
    "                                                                                        n0=row.n0 * (1 - row.outlier_rate), \n",
    "                                                                                        kappa_within_site=row.kappa_within_site,\n",
    "                                                                                        site_lat=row.site_lat,\n",
    "                                                                                        site_long=row.site_long, \n",
    "                                                                                        outlier_rate=0.0, \n",
    "                                                                                        secular_method=row.secular_method, \n",
    "                                                                                        kappa_secular=row.kappa_secular)), axis=1, result_type='expand')\n",
    "\n",
    "df_vandamme[\"error_kappa_theoretical\"] = df_vandamme.apply(lambda row: smp.kappa_theoretical(smp.Params(N=row.N, \n",
    "                                                                                            n0=row.n0, \n",
    "                                                                                            kappa_within_site=row.kappa_within_site,\n",
    "                                                                                            site_lat=row.site_lat,\n",
    "                                                                                            site_long=row.site_long, \n",
    "                                                                                            outlier_rate=row.outlier_rate, \n",
    "                                                                                            secular_method=row.secular_method, \n",
    "                                                                                            kappa_secular=row.kappa_secular)), axis=1, result_type='expand')\n",
    "\n",
    "df_true[\"error_angle_theoretical\"] = df_true.apply(lambda row: float(smp.kappa2angular(row.error_kappa_theoretical)), axis=1)\n",
    "df_vandamme[\"error_angle_theoretical\"] = df_vandamme.apply(lambda row: float(smp.kappa2angular(row.error_kappa_theoretical)), axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "44c4710c-efc5-4685-be3c-5acee548df32",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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iYpCXlye1b968GXl5eejXr1+JF+fFzZw5E3q9Hh988AGWLFmCtm3bSnf5mzZtisWLF+ONN95AYWEh5s2bV6F4MzMzsW3bNkRFRcHV1RUAEBAQgC1btqBRo0YwmUzYvHmzxRiNRiPNIIiMjMTSpUuli293d3e8+eab+OKLLwAAmzZtkhIXAKDVavHxxx8DACZOnIhvvvkGfn5+AABvb2989NFHeO+995CVlVXuz/TLL78AADp37lxmv8TERGRnZwMoyvCePHkS48aNszgPCxcuBADk5eVZ7TNbEvMyjvI+qnoryTt37kjPGzduXGq/4seKj6no+OJatWoFDw8PAMDJkyfLiJqIiIjIPv366684deqURZurqysiIyPh4uIiU1RUGiYFqFo0adIE/fv3l2YGmJnvjD+qEv758+dx5swZqFQqvPPOO6X2M2/jFhsb+8i1+2Xp3bs3wsLCrNrVajUGDRoEALhw4YLFsQMHDkh3f817zj/stddeQ8OGDQEAGzZskNr3798vjf3www9LHDtnzpwK/RA1X4TWq1evzH4JCQnS86VLl6JZs2ZWferWrSs9t2Utv3kZR3kfzs7Otn7Mcim+nMPNza3UfsWPFR9T0fEPM5/f0hIHRERERPYqKSkJu3fvtmgzF16uaYWuawql3AFQ7TFlyhTs378fK1euxEsvvYTr16/j2LFj8PHxwahRo8oc+/PPPwMounPdpk2bUvuZEwH5+fl48OBBubc4MU/hLkmjRo0AwGr6t/nOf5MmTdC6desSxyoUCjz77LNYv369xUyB4mNLq8Lq7e2N4ODgclelv3//PgA88oexuZ5A/fr1pUKDDzMvnXB3d7dp27+IiAhEREQ8RrS1W506dZCSkiJ9zYiIiIgcwYMHD7B582arYtQjRowo8UYT2QcmBajajB49Gr6+vjh+/DiuXr0qVWsfN27cI++Am++YGo1G3L1716b3KygoKHesnp6epR5TKov+2xgMBot2cxGVsqaPA0XT74v3L8/Y8tBqtQDwyG36zDMFhg8fXuosAHPioFOnTo8sDukIin+9y/q+KX6s+JiKjn+YeamG+WtGREREZO80Gg2+//57q79fevfujS5dusgTFNmEyweo2qjVakRGRgIAVqxYIe0SYN6ysCzmGQBt27aFKIo2PQIDA6vss5TF1ovkkvpV5QW2eUp6ZmZmmf3MSYGytok5e/YsACAoKKiSopOXefYHgDJrJBQ/VnxMRcc/zDwLpfgyDSIiIiJ7ZTQasXnzZquZtG3btkW/fv1kiopsxaQAVStzAuDLL7/E7du30aFDB3Tr1u2R48xT1BMTE632ObUX5qUKt27dKrOfeVvA4mv7zWPNx0pjS1G/0pjfr7Sq90DREgPzrIyuXbuW2s+cFCirT3GbNm2Cv79/uR8nTpyw9WOWS7t27aQquJcuXSq1n/mYv7+/xTKMio5/mPlr9Kj6D0RERERyE0URu3fvRnJyskW7v78/Ro8eXSNmldZ0TApQterWrRs6duwIvV4P4NEFBs169+4NANDr9di2bdtjv6/5gq0qt88zJzdu375ttf2KmdFoxOHDhwEA3bt3txp769Yt3Lhxo8SxOTk5+PXXX8sdX/v27QEUJVZKY54loFKp0KlTp1LjMMdo60wBjUaDu3fvlvth/n6pKm5ubtL32N69e0vsI4oi9u3bBwAYOHBgpY4vLjc3F+np6QCKkg1ERERE9uzUqVPSDSMzDw8PREZGVnmxaKocTApQtZs/fz7eeecdvPPOO5gwYYJNY7p16yZdgP7tb397ZAG2h++Ge3l5AUCFtvR7lAEDBkjTvUvbfWDp0qXSnXjzUgrzWF9fXwDAP//5zxLHfvbZZ9BoNOWO7+mnnwZQtJODTqcrsY+5VkD79u1LrT1w7tw5iKIIlUqFDh062PTekydPtnnZR0mP0NDQx/68jysqKgoAcPjwYWn7xuK2bNkiJVTMu1xU5niz+Ph4mEwmKJVKKdFAREREZI+uXr2K/fv3W7QplUpERkZKf3+T/WNSgKrdkCFDsGDBAixYsMDm6dGCIGDJkiVQq9W4efMmevTogZiYGIvCbampqVi3bh0GDBiA9957z2K8+eJ19+7dFZqCXxZXV1cpGbBhwwa88sorUlHEgoICfPPNN3jzzTcBFFXjDw4Othj7wQcfAADWrFmDN998Ew8ePABQdGf+n//8Jz755BP4+PiUO77evXtDqVRCr9dLF/8PM88UKB7bw8yZ4CeffNLusr+ZmZlIT0+XHubKtwUFBRbteXl5VmOjoqLQsWNHiKKI8PBwHDx4EEDRjhdbtmzByy+/DKDo+7ektXEVHW9mTih07doVHh4eFTgbRERERFXn7t272Lp1q1X76NGjy6ydRPaHSQFyGCEhIdi1axfq1q2LpKQkjBkzBl5eXvDz84O7uzsCAgIwceJExMbGWo2NioqCi4sLrl+/jqZNm8Lf3x+BgYEIDAx85Dr+xzFz5ky89dZbAIpmBTRs2BB16tSBt7c33njjDRgMBoSFhWHZsmVWY2fNmoWJEycCAL766ivUr18fderUQZ06dfDhhx8iIiICI0eOLHdsXl5eGDZsGABg586dJfYxJwsqs55AdQoKCkK9evWkh7m+w+eff27RPnPmTKuxSqUSO3fuRGBgIFJTU9G/f3+4u7vD3d0dL774InJychAUFIT169eX+N4VHW9m/tqMGzeugmeDiIiIqGrk5eVhw4YNVks8w8LCpCWr5DiYFCCHMmDAAFy/fh2ffvop+vTpA29vb2RlZcHJyQnt27fH1KlTsXPnTnzzzTcW41q1aoXDhw/jueeeQ7169fDgwQOkpKQgJSUFhYWFlRrjF198gUOHDiE8PBwNGjRAXl4ePD09ERYWhpUrV+LAgQMlbkfn5OSE6OhoREdH46mnnoKrqysKCwvRtWtXLFmyBN9//32FY5sxYwYA4Pvvv7eqr1BQUCDVQijrgt88m6Cm7DxQXGBgIC5cuIAPP/wQHTp0gCAIUKlUCA4OxoIFC3Dq1ClpmUdVjE9KSsLJkyfh6upa5hIDIiIiIrkYDAZs2rQJ2dnZFu2dOnVC3759ZYqKKkIQq7LymgPKycmBt7c3srOzbV4Ho9VqkZSUhObNm8PFxaWKIyQqP5PJhNatW+PGjRs4cuSIVGeA7MM//vEPfPTRR5gyZQpWrlwpdzh2hz9riYiI5CWKIn744Qer3ZaaNGmCSZMmQalUyhQZVQRnChDVIk5OTlIhw3//+98yR0PF5efn45tvvoFarcZHH30kdzhEREREVo4ePWqVEPDx8UFERAQTAg6MSQGiWmbs2LEICQnBnj17SqyST/L49ttvkZ6ejjfeeAPNmjWTOxwiIiIiC5cuXUJcXJxFm7OzMyIjI+Hu7i5PUFQpmM4hqmUEQcDSpUuxfft2pKenyx0O/Ze7uzvmzp0r7VBBREREZC9u376NHTt2WLQJgoAXXngB9evXlykqqixMChDVQl26dEGXLl3kDoOKKWlHBCIiIiK5ZWdnY+PGjVbFuQcNGoRWrVrJFBVVJi4fICIiIiIiIis6nQ4bNmxAfn6+RXu3bt0QEhIiU1RU2ZgUICIiIiIiIgsmkwk//PAD7t69a9HeokULDB48GIIgyBQZVTYmBYiIiIiIiMhCbGwsrl69atHm5+eHMWPGQKFQyBQVVQUmBYiIiIiIiEhy9uxZnDx50qLN1dUVkZGRcHFxkSkqqipMChAREREREREAIDk5GT/99JNFm5OTE1588UXUqVNHpqioKjEpQERERERERDAYDNi+fTtMJpNF+/DhwxEYGChPUFTlmBQgIiIiIiIinDhxAtnZ2RZtvXr1QlBQkEwRUXVgUoCIiIiIiKiWy87Oxs8//2zR1qxZM/Tv31+miKi6MClARERERERUy8XGxqKwsFD6tyAIGDJkCLcerAWYFCAiIiIiIqrFUlJScOnSJYu24OBgNGjQQKaIqDoxKUBERERERFRLmUwm7N2716LNxcUFYWFhMkVE1Y1JASIiIiIioloqISEBaWlpFm2hoaFwc3OTKSKqbkwKENVQoaGhEAQBc+fOfaxjjiQwMBCCIGD16tVyh2J3asrXmIiIiKqOVqvFoUOHLNrq1auH7t27yxQRyYFJAbIrc+fOhSAIEAQB7u7uuHPnTql9k5OTpb5xcXHVF6TMtm/fjrlz52L79u1yh1Jj2fM5tufYiIiIyLEcOXIEBQUFFm2DBw+GkxMvE2sTfrXJbhUUFODjjz+WOwy7s337dnz88ccVuihs2rQp2rRpAz8/v8oLrAapjHNcVWyNjV9jIiIiKsv9+/dx+vRpi7a2bduiRYsWMkVEclHKHQBRWVauXIl33nkHrVu3ljuUGiU6OlruEKiK8WtMREREpRFFEfv27YPJZJLaFAoFBg4cKGNUJBfOFCC71KRJE3Tq1AmFhYX461//Knc4REREREQ1xrVr13Djxg2Ltp49e8LX11emiEhOTAqQXXJycsKnn34KANi6davV1CZbGY1GrFy5Es8++yz8/PygVqvRuHFjjBkzplLqEMTFxWHMmDFo3Lgx1Go1/Pz80K9fP6xatQpGo7HEMZMnT4YgCJg8eXKpr7t69WoIgoDAwECL9xIEAWvWrAEArFmzRqqp8Li1FWwpQnfjxg28/vrraNeuHTw8PODm5oZ27drhzTffxM2bN22K+/Dhwxg1ahQaNmwIhUJR5mcuiUajwbx589C+fXu4urqifv36GDp0KA4ePGjza8TFxSEyMhJNmzaFi4sLvL29ERISgs8++wz5+flWfctzjstzrsz0ej2WL1+OwYMHo0GDBlCr1WjYsCF69uyJf/zjH0hKSipXbLZ8jX/44QcMHz4cDRo0gLOzMxo0aIDhw4dj27ZtpY55+Ps3JiYGoaGhqFOnDtzc3NClSxd89dVXFnceiIiIyH4UFhZi3759Fm2enp7o27evTBGR3Lh8gOzW0KFD8cwzz+DIkSOYM2eOVWXUR8nOzsaoUaOkCyWFQgFPT0/8+eefiImJQUxMDGbPno3PP/+8XPG9/fbbWLRoEQBAEAR4e3sjKysLhw4dwqFDh7Bu3Tps374dnp6e5Xr9h5kv2rKzs6HVaqUL3If7VIZly5bhL3/5CwwGAwBArVbDyckJf/zxB/744w+sWrUKMTExGDBgQKmv8fXXX+PNN9+EKIrw9vaGQqF4rBgyMjLQv39/JCQkAACUSiUMBgP27NmDvXv3YvHixWWOLywsxKuvvorly5dLbR4eHsjPz8eZM2dw5swZrFy5Evv27UOzZs0AlO8cV+RcJSUl4bnnnsOlS5cA/O/76P79+0hLS8OpU6eQkZGBL7/8slK//nq9HpMmTcKmTZsAFCXhvL29kZ6ejp9++gk//fQTIiMjsWbNGqhUqlJfZ+bMmVi8eDGcnJzg5eUFjUaD8+fP480338TZs2elBAYRERHZj19++QUZGRkWbf3796+0vyPJ8XCmANm1+fPnAyi647x3797HGjt16lTExcXB2dkZX3/9NXJycpCZmYk7d+7gpZdeAgAsWLAAS5Yseey4vv32WykhMH36dNy5cweZmZnIzs7GokWLoFQqcejQIbz88suP/dql6dWrF9LS0hAREQEAiIiIQFpamsWjV69eFX6f7du3Y/r06QCAOXPmIDk5GRqNBvn5+fjjjz8wZswY5OTk4IUXXij1Lvjdu3fx9ttvIyoqCjdv3kRWVhY0Gg0++OADm+OYNm0aEhISoFarsWTJEuTm5iIzMxPJyckYNWoUZs2ahfv375c6fvbs2Vi+fDkaNGiA7777Dg8ePEBubi40Gg0OHz6MoKAgXLlyBc8//7x0V/txz3FFzlVOTg4GDRqES5cuwdfXF//5z3+QmZmJzMxMaDQaXLlyBQsXLpQSFpX59f/rX/+KTZs2QRAEfPDBB3jw4AEyMjKQnp4uLdfZsGFDmV+vnTt3YtmyZfjiiy+kuNPT0zFt2jQARTUNHjeRR0RERFUrLy8PR48etWgLCAhAx44dZYqI7AGTAmTXevTogdGjRwMA3n//fYiiaNO406dPY+vWrQCAb775Bq+//jrc3NwAAP7+/lixYgXCw8MBAB988AG0Wq3NMWk0Gnz00UcAgMjISCxduhT+/v4AAHd3d7z55pv44osvAACbNm1CfHy8za8tN71ej5kzZwIAlixZgk8//RTNmjWTpqe3adMGmzdvxnPPPYecnBzpcz5Mq9Vi5MiRWLVqFZo0aQKgaKbGE088YVMcp0+flqawf/fdd5gxYwZcXFwAAM2aNcOWLVvQo0cPqy10zC5duoSvv/4abm5uOHDgAF599VXUqVMHAKBSqRAaGoojR44gICAAZ8+exc6dO20/Sf9V0XP1+eef49q1a1Cr1Th48CBefvll6c6/SqVC69at8fbbb+Ott9567NjKkpqaiq+++gpAUSLjH//4B3x8fAAAvr6++Ne//oW3334bAPDFF1/gzz//LPF1MjMzsXTpUrz11lvw8vICANStWxfLli1DcHAwgKLEAhEREdmPgwcPQq/XW7QNHjwYgiDIFBHZAyYFyO598sknUCgUOHfunM0XGRs3bgRQlPk037l82D//+U8AQHp6Og4cOGBzPAcOHJCmXJW2Xvu1115Dw4YNATjWhdGePXuQmpqKBg0aYMqUKaX2mzRpEgBYrUcr7v333y93HOavX5MmTUqMQ6FQlHkXe8WKFRBFEcOGDSs18+3p6YlRo0YBKPtzlKai52rlypUAimZEBAUFPfb7l9fWrVtRWFgIFxcXzJkzp8Q+f//736FWq2EwGBATE1NinyZNmkif7WHPPfccAODChQuVEzQRERFVWGpqKs6dO2fR1qVLFzRu3FiegMhusKYA2b22bdtiypQpWL58OT744AOMGTOmzHXOAKS782FhYXByKjn31a5dOzRu3BipqamIj4/HiBEjbIrH/NpNmjQpdatEhUKBZ599FuvXr3eomQI///wzgKK7wOakRknMGeaUlJQSj7u6uqJr167ljsN8zszF8kry9NNPQ6lUorCw0OqY+XPs2bNHmsVRkry8PAClf46yVORcpaSk4M6dOwBg8/ddZTGf2+7du0t3+B/m6+uLbt264fjx46V+/3bv3r3U/1uNGjUCAKv1ikRERCQPURStluI6OzujX79+MkVE9oRJAXIIc+fOxfr165GYmIglS5bg9ddfL7P/vXv3AOCRmc+AgACkpqZK/W3xOK9dvL8jMF+o6vV63L1795H9NRpNie1169Yt9YLRFracYxcXF9StW7fEOM2fIy8vT7rwL0tpyxDKUpFzlZaWJj031wyoLpX1/VtWAU2lsuhXi7n4IhEREcnrwoULuH37tkXb008/DQ8PD5kiInvC5QPkEBo3biwlAubNm2fThR4Am9dHlWcdVVW+tlzM2ygOHjwYoija9CjJ4+40UJrynjvz5/j3v/9t02coz/aUlXWu5Pr+qInfv0RERGRNr9cjNjbWoq1OnTp46qmnZIqI7A2TAuQw3n//ffj6+uLevXtYuHBhmX3r168PALh161aZ/cwZ03r16tkcR0Vf23wXtazihtnZ2TbHU5nMU+0vXrwoy/ubmc/xwxnt4nQ6HR48eFDiser4HBV5j+LLDZKTkysrJJtU5f8NIiIisj/Hjh2zuqE2aNCgSruJQ46PSQFyGD4+PlJhtIULF5Y5Lb9bt24AirYyNG8397A//vgDqampAIrWR9vK/Nq3b9/G1atXS+xjNBpx+PDhEl/b19cXQNkXZb/88kupx8zT8m3dieFx9O7dG0BRIRrzmnk5mM/xkSNHSv2cR48eLbGeAPC/z/HTTz/ZPKukOFvOcUXOVdOmTaXp+bt27ar02MpiPrfx8fGlJp+ysrIsag8QERGRY8rMzMTJkyct2lq2bIlWrVrJFBHZIyYFyKG88cYbCAgIQG5uLubNm1dqv7FjxwIoumBbvnx5iX0+/PBDAICfnx/69+9vcwwDBgxA3bp1AZS++8DSpUulNeeRkZEWxzp37gwAOHPmTImJgcuXL+OHH34o9f3NxeGysrJsjtlWI0aMkO5iz5o165Fr7auqkFxERAQA4ObNm1izZo3VcZPJVObX/+WXX4YgCMjKysK7775b5nsZDAarxIEt57ii5+qll14CACxfvhwJCQlljn3c2MoSHh4OpVIJrVaL+fPnl9jnk08+gU6ng0qlkrbuJCIiIsezf/9+ackjUHRzYdCgQVweSBaYFCCH4uLiIl2Il3WHNSQkRLqYef311/Htt99KF21paWl4+eWXsWXLFgBFWxO6uLjYHIOrq6sUw4YNG/DKK69IheYKCgrwzTff4M033wRQdHFr3rPdbMSIEfDw8IDBYMCLL76IK1euACi6ON2xYwf69+8Pd3f3Ut+/Q4cOAIqmgv3xxx82x20LFxcXfPfddxAEAWfPnkXv3r2xb98+i/1sk5KSsHTpUoSEhOC7776r1Pc369Gjh7St3auvvoply5ZBp9MBKEoURERE4OTJk3BzcytxfJcuXaSvwZIlSzBmzBicO3dOurtuNBpx/vx5/POf/8QTTzxhtT2PLee4oudq9uzZaNWqFXQ6Hfr164dly5YhJycHQNH3wtWrV/GPf/wDCxYseOzYytK4cWPMmjULQFHNhY8++khKMGRlZeGDDz7A559/DgB4++23y9xZgYiIiOxXYmKi1d8KISEh8PPzkykislsiWcjOzhYBiNnZ2TaP0Wg04u+//y5qNJoqjKx2+Oijj0QAYrNmzUrtU1hYKLZt21YEID0OHz5s1S8rK0t85plnpD5KpVL09fUVBUGQ2mbPnl3uWN966y3pdQRBEH19fUWlUim1hYWFiTk5OSWOXb58uUX8np6eorOzswhAfOqpp8Rvv/221POQkZEh1qtXTxrr5+cnNmvWTGzWrJl48uRJqZ/5s3/00UdWr1HWMVEUxXXr1olubm4W565u3bqiWq22iHvevHkW41atWvXIr5+t0tPTxc6dO0vvpVKpRB8fH+l8L168WGzWrJkIQFy1apXV+MLCQvHNN9+0iNfFxUWsW7euxdcJgPjzzz9bjLX1HFfkXImiKN64cUNs37691MfJyUn09fUVFQqF1DZr1qxyxVbW11in04kvvvii1fs6OTlJbZGRkaJer7caGxUVJQIQo6KiSv3aVeb3QXH8WUtERGQbo9EoLl68WJw7d670+Oyzz/g7lErEmQLkcBQKBT755JNH9vP29sbBgwexYsUKhIaGwtPTE3l5efD390d4eDgOHz4s3REtjy+++AKHDh1CeHg4GjRogLy8PHh6eiIsLAwrV67EgQMHSt22berUqdi9ezeeffZZeHl5obCwEK1bt8a///1vHDlypMyZAr6+vjh69CjGjh2Lxo0bIzs7GykpKUhJSSmzeOHjGD9+PK5fv46///3v6NatGzw8PJCVlQUXFxd06dIFM2fORGxsLN57771Keb+S1K1bFydOnMDHH3+Mtm3bwsnJCUqlEoMHD8aBAwfw2muvlTleoVBg0aJFOHv2LKZPn442bdpAoVAgOzsbvr6+6N27N+bOnYtz585J9QHMHuccV+RctWjRAgkJCfjuu+8QGhoKX19f5OXloUGDBujZsyf++c9/4q233ip3bKVxdnbGpk2bsHXrVgwZMgR169ZFbm4u6tatiyFDhuCHH37A999/D5VKZdPrERERkX05c+YM7t+/b9HWr1+/x5odS7WHIIpVUK3MgeXk5MDb2xvZ2dnS2t1H0Wq1SEpKQvPmzfkfjYioivBnLRER0aOZl7MWv1ng7++Pl19+WSpYTFQcvyuIiIiIiIhqiMOHD1vNHhwyZAgTAlQqfmcQERERERHVAGlpafj1118t2jp06ICmTZvKFBE5AiYFiIiIiIiIHJwoiti7dy+Krw5XKpWPtfU21U5MChARERERETm4y5cvIyUlxaKtT58+8Pb2likichRMChARERERETkwg8GA/fv3W7R5e3ujV69eMkVEjkQpdwC1gSiKKCgokDuMKuHm5gZBEOQOg4iIiIio1jpx4gSys7Mt2gYOHMjthckmTApUg4KCAixYsEDuMKrE7Nmz4e7uLncYRERERES1UnZ2Nn7++WeLtsDAQLRr106miMjRcPkAERERERGRg4qNjUVhYaH0b0EQMHjwYM7mJZsxKUBEREREROSAUlJScOnSJYu24OBgNGjQQKaIyBExKUBERERERORgTCYT9u7da9Hm4uKCsLAwmSIiR8WaAtXAzc0Ns2fPljuMKuHm5iZ3CDVWQUEBjhw5gl9//RVnz57Fr7/+ips3bwIAPvroI8ydO7da4mjatClu3boFABg6dCh++umnUvt+8skn+Nvf/oY6dergwYMH1RJfWSrrHObm5mLhwoXYunUrkpKSoFAo0Lp1a4wdOxavv/46nJ2dq3Q8ERER0cMSEhKQlpZm0RYaGsq/z+mxMSlQDQRBYDE+emynT5/G0KFDZY3hwYMHUkIAKFqzlp2dXep+t2fPngUABAUFVUt8j1IZ5zAlJQWhoaFITk4GUJQI0+l0iI+PR3x8PNavX4+DBw/C19e3SsYTERERPUyr1eLQoUMWbfXq1UP37t1liogcGZcPENkxX19f9OvXD++++y42bNgAf3//an3/X3/9VXpep04d6PV67Nq165H9g4ODqzw2W1XkHBqNRowYMQLJyclo2LAhDhw4gPz8fBQUFGDjxo3w9PREQkICxo8fXyXjiYiIiEpy5MgRqy3PBw8eDCcnXt7R4+NMASI71bdvX2RkZFi0zZkzp1pjMF/k+/n5YfLkyViwYAG2bt2KCRMmWPXNzMyU7oZ37dq1OsMsVUXP4erVq3Hx4kUAwNatW9GzZ08AgJOTEyIiImAymTBu3Djs2bMHBw8eRL9+/Sp1PBEREdHD7t+/j9OnT1u0tW3bFi1atJApInJ0TCWRw5k1axYEQcDo0aMBAHv27MHo0aPRqFEjuLu7o1OnTli8eDFMJpPMkVaMQqGQOwRpOUDXrl0RHh4OANi7dy/y8vKs+hafVWAvMwUqeg7XrFkDAAgLC5Mu6IsbO3YsmjdvDgCIjo6u9PFERERExYmiiH379ln8natQKDBw4EAZoyJHx6QAOZxz584BANq1a4fIyEgMHToUu3btgkajQUFBAS5evIiZM2fik08+kTfQGsB8od+1a1f06NEDjRs3hlarxe7du636mhMIXl5eeOKJJ6o1zqpQUFCA48ePAwCGDBlSYh/zPsAAsH///kodT0RERPSwa9eu4caNGxZtPXv2ZG0iqhAmBcjhnD9/HgCwbNkyHDlyBOvXr0dubi4yMzNx69Yt9O3bFwAwf/58iKIoZ6gOLTMzE0lJSQCKkgLFZ2fExMRY9S+eQBAEofoCrSKXL1+WsvAdOnQotZ/5WFpamsVShYqOJyIiIiqusLAQ+/bts2jz9PSU/vYlKi8mBcihJCYmIjs7G0DR3qwnT57EuHHj4OrqCgAICAjAwoULAQB5eXlITU2t9BhWr14NQRDK/YiLi6v0mKqC+c4/8L8aAeYlBLt374ZGoymxvy31BBzhHN65c0d63rhx41L7FT9WfExFxxMREREV98svv1jdQOjfvz+3NqYKY6FBcigJCQnS86VLl6JZs2ZWferWrSs9r4p1+a6urmjQoEG5xzvKD27zRb6Pj49UuKZv376oV68e7t+/j3379mHUqFEAgJycHGkqmy31BBzhHObm5krPy9rvt/ix4mMqOp6IiIjILC8vD0ePHrVoCwgIQMeOHWWKiGoSJgXIoZjrCdSvX1+ayv6wa9euAQDc3d2ttp8zGo1YsGABli1bhlu3biEgIABTpkzBnDlzoFTa9t8hIiICERER5f8QDsK8HCAoKEhaDqBQKDBy5EgsX74cMTExUlLg7Nmz0lINW2YK1JZzSERERFQZDh48CL1eb9E2ePDgGrFkk+TH5QPkUMwzBYYPH17qLABz4qBTp05WPyhff/11zJkzB8HBwVi8eDEGDBiADz/8EDNmzKjSuB1RacsBzEsIdu3aJf1yMicQPDw80Lp162qMsup4enpKzx/eB7i44seKj6noeCIiIiIASE1Nlf6+NevSpUuZyxOJHgeTAuRQzEmBkJCQUvuYL2aDgoIs2i9evIglS5YgIiICmzZtwrRp07BkyRK8++67WLlyJeLj46sucAeTk5OD69evA7BOCvTr1w/e3t7IycnBgQMHAPzvnHfp0gVOTjXjx0qjRo2k52XVpih+rPiYio4nIiIiEkURe/futWhzdnZGv379ZIqIaqKa8dc71Qr379+XCrGVNUW9tDvcGzduhCiKeOONNyzazf/euHGjTXFs2rQJ/v7+5X6cOHHC5s8sl4SEhFKXA6hUKowYMQIAsHXrVgCWOw/YwhHOYbt27aQEx6VLl0rtZz7m7++POnXqVNp4IiIioosXL+L27dsWbU8//TQ8PDxkiohqItYUIIdhniWgUqnQqVOnEvsUL3j38EyB+Ph4ODk5oVu3bhbtjRs3RuPGjW2eKaDRaHD37t3HDV/y8Howe2ROrJS2HCA8PBzr1q3Djh07kJmZKdVxsKXIIOAY59DNzQ29e/fGsWPHsHfvXrz77rtWfURRlLYGGjhwYKWOJyIiotpNr9cjNjbWoq1OnTp46qmnZIqIairOFCCHYV5L1b59e6jV6lL7iKIIlUpltTf8nTt34OfnV2Ll+kaNGtm8feHkyZMhimK5H6GhoY/1ueVgvvNf2nKAQYMGwd3dHRkZGVi0aBFMJhMA22cKOMo5jIqKAgAcPnwYv/zyi9XxLVu2IDExEQAwadKkSh9PREREtdexY8esdiYaNGhQleyuRbUbkwLkMMwzBcq6G22+w/3kk09aXfwXFBSUmkxwcXGBRqOppEgrT2ZmJtLT06WH+eK7oKDAoj0vL89qbHJyMgRBgCAImDt37mO9b2lLMMxcXV0xZMgQAMCiRYuktnbt2j3W+1SHipzDqKgodOzYEaIoIjw8HAcPHgQAmEwmbNmyBS+//DIAYMiQISWu7avoeCIiIqqdMjMzcfLkSYu2li1bolWrVjJFRDWZwyYFzBc7tjzCwsLkDpcqgXmmQHnqCQBFF/46na7EcVqtFi4uLhUPspIFBQWhXr160uPWrVsAgM8//9yifebMmZX2nvn5+bhy5QqAss+1eRcC88V0586d7TJzXZFzqFQqsXPnTgQGBiI1NRX9+/eHu7s73N3d8eKLLyInJwdBQUFYv359ie9d0fFERERU+4iiiD179sBoNEptTk5OGDRoELcgpCrhsEmBBg0alPkoXrCre/fuMkZKlaGgoABXr14FUPaFqnk2wcP1BAAgICAA6enpJa5Hv3PnTo3b1qX4cojHWXt27tw5m5YDDBs2zGLmha1LBxxNYGAgLly4gA8//BAdOnSAIAhQqVQIDg7GggULcOrUKfj6+lbZeCIiIqpdEhISpHpNZiEhIfDz85MpIqrpBNFcYryGWbhwIWbPng0A+OOPP9CmTRubxuXk5MDb2xvZ2dnw8vKyaYxWq0VSUhKaN29ul3ebqchf//pXfPrppzh+/Dh69eoltaempiIgIABvv/02Fi5cKGOElWvevHn44IMP0KdPHxw7dkzucIgqjD9riYiopsvIyMCSJUtgMBikNnd3d8ycOZO/+6jKOOxMgUdZsWIFAKBPnz42JwSoZouIiIAgCPj6668t2s3/joiIkCOsKnPo0CEAwCeffCJzJERERET0KCaTCdu2bbNICADAc889x4QAVakauSXhiRMncPnyZQDAtGnTZI6G7EXnzp0xffp0LF26FKIoYuDAgYiPj8fSpUsRFRWFkJAQuUOsNDqdDidPnsTgwYPRt29fucMhIiIiokc4fvw4bt++bdEWHBxc4vbQRJWpRiYFzLMEvLy8MGbMGJmjIXvy7bffolmzZli+fDm2b9+ORo0aYe7cuXj//fflDq1SqdVqu9xNgYiIiIis/fnnn4iLi7No8/X1xcCBA+UJiGqVGpcUyMvLw+bNmwEA48aNg5ubm8wRkT1RKpV4//33a1wSgIiIiIgck8FgwLZt26RCz0DRTmujR4+22mKbqCrUuKTAxo0bpS3SbFk6oNPpLLapy8nJqbLYiIiIiIiIijt48CDu379v0danTx80adJEpoiotqlxhQaXL18OoGj9eHBw8CP7f/rpp/D29pYe/M9HRERERETVITExEb/88otFW8OGDfHMM8/IFBHVRjUqKfDbb79J/6lsLTD4/vvvIzs7W3rcunWrKkMkIiIiIiKCVqvFjh07LNqUSiVGjx4NhUIhU1RUG9Wo5QPmWQIuLi4YP368TWPUajXUanVVhkVERERERGRh9+7dVkuX+/fvj3r16skUEdVWNWamgF6vx7p16wAA4eHh8PX1lTkiIiIiIiIia5cuXcLFixct2lq0aFGjtsgmx1FjkgI7duxAeno6ANuXDhAREREREVWnnJwc/PTTTxZtLi4uGDlyJARBkCkqqs1qTFLAvHSgZcuWLMxBRERERER2RxRF7NixA1qt1qJ92LBh8PLykikqqu1qRFLg5s2biI2NBQC89NJLzLAREREREZHdOXPmDBITEy3aOnTogA4dOsgUEVENSQqsXLkSJpMJSqUSkydPljscIiIiIiIiC+np6Thw4IBFm6enJ4YOHSpTRERFHD4pYDKZsHr1agDA0KFD0bBhQ3kDIiIiIiIiKsZoNGLbtm0oLCy0aB85ciRcXV1lioqoiMMnBWJjY5GSkgKABQaJiIiIiMj+HD16FHfu3LFoCwkJwRNPPCFTRET/o5Q7gIoaOHAgRFGUOwwiIiIiIiIrt2/fxrFjxyza/Pz80L9/f5kiIrLk8DMFiIiIiIiI7JFer8e2bdssbmI6OTlh9OjRUKlUMkZG9D9MChAREREREVWBAwcOICMjw6LtmWeeQaNGjWSKiMgakwJERERERESV7Nq1a4iPj7doCwgIQJ8+fWSKiKhkDl9TgGoeURQRExOD77//HmfPnsW9e/egUCjQoEEDNGzYECEhIejbty/69esHLy8vi7FffvklsrKyMGrUKHTp0kWeD/BfcXFxiIuLQ2BgYK3cKrOwsBBHjhzB2bNn8euvv+Ls2bO4fv06RFFEVFSUtGsIERERUU1TUFCAnTt3WrSpVCqMHj0aTk68L0v2hUkBsivmC/ojR45IbUqlEm5ubrh58yYSExNx/PhxLFq0CKtWrbK62P7yyy+RkpKCwMBAu0gKfPzxx3jmmWdqZVLg9u3bLKBDREREtY4oivjxxx+Rl5dn0T5w4EDUqVNHpqiISsc0FdmVSZMm4ciRI1AoFHjnnXdw9epV6HQ6PHjwABqNBufPn8f8+fPRuXNnuUMlG3h6eqJPnz6YNWsW1qxZI3uihoiIiKiqXbhwAZcvX7Zoa9WqFYKDg2WKiByBaDLB+OCeLO/NmQJkN65du4Zdu3YBAObNm4c5c+ZYHFcqlejUqRM6deqE//u//4NGo5EjTLJR06ZNkZ2dDUEQpLaVK1fKGBERERFR1crKysKePXss2lxdXfHcc89Z/E1EZEWvhaiX5/qGMwXIbpw7d056PnLkyEf2d3V1lZ7PnTsXgiAgJSUFADBlyhQIgmDxMEtOTpbakpOTcePGDUyfPh3NmzeHWq1GYGCg1Dc7OxsbN27E+PHj0bFjR9SpUwcuLi5o1qwZxo0bh1OnTlnFZX79jz/+GABw5MgRq1hKWk+flpaGOXPmoHPnzvD29oaLiwtatGiBadOm4ffffy/zXKSkpGDq1KkICAiAWq1GQEAApkyZguvXr1t9XrOxY8dCEAQMHTq0zNe+fv06nJycIAgC4uLiyuxbnHkMERERUW0giiK2b98OnU5n0T5ixAh4eHjIFBU5CpNWA1Gve3THKsCkANml27dvP1Z/Dw8PNGjQQCrc4uXlhQYNGlg8SnLixAl06dIFy5Ytw71796z2i120aBEiIyPx/fff49KlSzAYDACAmzdvYsOGDejVqxe+/vprizHmooju7u4AiorKPBxL8YQGAPz4449o1aoV5s+fjwsXLkCj0UCpVCIpKQkrVqxAUFAQoqOjS/wMJ0+eRMeOHbFy5UqkpqZCoVAgOzsbq1evRnBwMM6cOVPiuFdeeQUAsG/fPty8ebPUc7t8+XKIoojWrVsjNDS01H5EREREtdnJkyelG1RmnTt3Rrt27WSKiByFaDRCLMgFRHnen0kBshvdu3eX7iyb6wnYavbs2UhLS0OTJk0AAF999RXS0tIsHiWZMWMGnnzySZw5cwb5+fnIy8vD/v37peP+/v546623cOrUKWRmZiI3NxcajQaJiYmYNWsWAODtt99GQkKCNKZJkyZIS0vD7NmzAQC9evWyiiUiIkLqf/r0aYSHhyMvLw8zZszA5cuXodFokJeXh5SUFLz22mvQ6/WYOnWq1bY2WVlZCA8PR25uLlq0aIFDhw4hPz8fubm5OH36NJo3b44ZM2aU+NlDQ0PRrl07mEwmrFixosQ+BoNBmtUwffr0sr4ERERERLXW3bt3cejQIYs2b29vDB48WKaIyJGIei1EnVa292dSgOxGYGAgpk2bBgC4ePEi2rZti65du+Ivf/kLVq5ciUuXLkEUKzd9VrduXcTGxqJbt25SW+vWraXnr7zyCr744gv06NEDPj4+AABBENC8eXN8+eWXeO2112A0GrF48eJyxzBz5kzo9Xp88MEHWLJkCdq2bQuFQgGgaF3+4sWL8cYbb6CwsBDz5s2zGPvtt9/izz//hIuLC/bt24ewsDApsdK9e3fExsZKr1USc8Jg5cqVMBqNVsd37tyJu3fvwtnZGVFRUeX+jEREREQ1VWFhIbZt22b1t9SoUaPg4uIiU1TkSERNASDjslsmBciufPfdd/jggw/g7u4OURSRkJCA7777DlOnTkXHjh3h7++Pt99+G3fv3q2U95s5c2aF1ngNGzYMAPDzzz+Xa/z58+dx5swZqFQqvPPOO6X2mzRpEgAgNjbW4hfOli1bAAARERFo2bKl1Tg/Pz+8+uqrpb5uVFQU3NzccPv2bezevdvq+LJlywAA4eHh8PPzs+1DEREREdUicXFxVn+b9urVy6JOFVFpRGMhxII8CM5q2WJgUoDsilKpxD/+8Q+kpqZi7dq1mDZtGjp37gxnZ2cAwL1797Bo0SJ06NABp0+frvD79e7d+5F9EhMTMXv2bAQHB8PHxwcKhUIq3Gcu0ve4NRDMzMkEk8mENm3awN/fv8SHeepZfn4+Hjx4AADQ6/X47bffAADPPPNMqe9RVh0AHx8faSmDOQFglpKSggMHDgDg0gEiIiKikqSkpOD48eMWbfXr10dYWJhMEZGjEbUaoFAPKJ1li4FbEpJd8vb2xoQJEzBhwgQAgFarxc8//4yvv/4au3btQnp6OsLDw3Ht2rUKTcuqX79+mce3bduGyMhIiyqyXl5ecHFxgSAI0Ov1yMzMRH5+frne/86dOwAAo9Fo8+yHgoICAEBGRoY0a6BRo0al9m/cuHGZr/fKK69g1apV2L17N1JTU6X+y5cvl5IVLDBIREREZEmn02H79u0WbQqFAs8//zyUSl5mkW1ETR5EQd5duzhTgByCi4sL+vfvj507d0pr22/fvo29e/dW6HXLWm//4MEDTJ48GTqdDs8++yzi4uJQUFCA7Oxs3L17F2lpadL0/fIyX9S3bdsWoija9DBPRSteX6GsHyKPqsMQEhKCrl27wmg0SgUHjUYjVq1aBQB4+eWXK/IRiYiIiGqkvXv3Iisry6ItLCys1F2viB4mGvQwaQogqOWtPcGkADmc4lPZr1y5UmXvs3v3buTk5MDX1xe7du3CM888Y7WVYGm7GtjK398fQNEShcedbVC3bl0pqWGecVCSso6ZmbcnXLFiBUwmkzRrQK1Ws8AgERER0UP++OMPnDt3zqKtWbNm6NmzpzwBkUMSdVoIhQYIStWjO1chJgXI4RQvDKhWWxbkcHIq+paujF0Kbt26BQBo06YN3NzcSuwTGxtb6nhbYjHXNNDr9di2bdtjxefs7Iwnn3wSQFGBm9KUdcxs3Lhx8PLyws2bN7Fv3z6pvsDzzz/PAoNERERExeTl5WHXrl0Wbc7Ozhg1apT09x/Ro4iiCFN+DkSF/EtN+F1LdiMpKQlXr159ZL81a9ZIz7t27WpxzMvLCwCspnKVh7e3NwDg6tWr0Gqt9w09d+4cvv/++1LH2xJLt27dEBQUBAD429/+hvv375cZU0ZGhsW/X3jhBQDA5s2bkZiYaNX/wYMHWLJkSZmvCQDu7u6YOHEiAGDevHnSTgQsMEhERET0P6IoYteuXVKNJ7MhQ4ZI21cT2cSgg6jVyL50AGBSgOzIb7/9hnbt2mHYsGGIjo5GcnKydMxgMCAhIQFTpkzBF198AaBoLXyfPn0sXqNDhw4AgJiYGGRmZlYonoEDB8LJyQkZGRkYP348UlNTARTd1d+8eTMGDhwIT0/PUsebY/ntt99w4sSJEvsIgoAlS5ZArVbj5s2b6NGjB2JiYix+0aSmpmLdunUYMGAA3nvvPYvxM2fORIMGDaDRaDBo0CAcOXJEmpkQHx+PAQMGoLCw0KbPa15CcOLECRiNxkopMJidnY309HTpYTAYABQV5inenp2dXaH3ISIiIqoOZ8+etbqJ1bZtW3Tu3FmmiMhRiTotYDJC4EwBov9RqVTSevaoqCg0b94carUadevWhVqtRteuXbF69WoARTMEtm3bZjVFa/r06RAEASdOnEC9evXQqFEjBAYGlmuf2FatWuHdd98FAPzwww8ICAiAj48PPDw8EBERAQ8PD3z99deljg8NDUWbNm1gNBrRu3dv1KlTR4olJiZG6hcSEoJdu3ahbt26SEpKwpgxY+Dl5QU/Pz+4u7sjICAAEydOLHGpgq+vL2JiYuDh4YHr168jNDQUHh4e8PT0RPfu3ZGUlIT//Oc/Uv+ydmro0KGDRZKlMgoMjhw5EvXq1ZMe5uTIxo0bLdpHjhxZ4fciIiIiqkoZGRnYt2+fRZu7uzuGDx8ua+V4cjyiKMKUlwtBJd82hMUxKUB2Y9CgQbh27Rq++uorjBkzBu3atYNarUZWVhbc3NzQqlUrvPjii9i4cSPOnDlT4jZ8Tz/9NH766Sf0798f3t7euHv3LlJSUpCSklKumP79738jOjoaISEhcHV1hcFgQMuWLfHXv/4VCQkJZW4FqFQqcfDgQUybNg2BgYHIz8+XYsnLy7PoO2DAAFy/fh2ffvop+vTpA29vb2RlZcHJyQnt27fH1KlTsXPnTnzzzTdW79OnTx9cuHABU6ZMQaNGjVBYWAgfHx+89NJLOHv2LJ544gmp76OmtY0ZMwYAWGCQiIiIqBiTyYRt27ZJsx7NnnvuObi7u8sUFTksnQaiTgM4qx/dtxoIYmVUZKtBcnJy4O3tjezsbGlN+KNotVokJSWhefPmZd6JJZLDsmXLMH36dLRo0QI3btwos++IESPw448/IjIyssx6CURy4M9aIiKSy7Fjx3Do0CGLtuDgYAwfPlymiMiRGbMewJSVDicPb6lNFEWI+blQBbau9ng4U4CoBtNqtfjyyy8BAIMHDy6zb2JiolRg8NVXX63q0IiIiIgcwp9//mm1m5Ovry8GDhwoT0Dk0ESjEWKB/SwdAJgUIHJ4GzduxN///ndcunQJer0eAFBYWIijR4/i2Wefxe+//w4XFxfMmjWr1NfIycnBq6++CpPJhB49eqBv377VFT4RERGR3TIYDPjhhx9gMpmkNkEQMHr0aDg7289FHTkOUa+FqNcDKvtYOgAA8pc6JKIKSUtLw7/+9S/861//giAI8PX1RV5enpQgcHZ2xqpVq9C6tfVUpNmzZ2PLli1IS0uDXq+HUqmUZhYQERER1XYHDx5Eenq6RVufPn3QpEkTmSIiRydqCgCIEJzs5/48kwJEDm748OG4f/8+4uLikJKSgvT0dKhUKrRo0QJhYWF48803S0wIAEB6ejpu3rwJDw8PBAcH45///Ceeeuqpav4ERERERPYnMTERv/zyi0Vbw4YN8cwzz8gUETk60VgIsSAPgrN91UZiocGHVEWhwXvDWkIsNJQwsmYQlCrU/+m63GEQUQ3HQoNERFRdUlNTsXbtWuh0OqlNqVRi+vTpqFevnoyRkSMzFeTBdC8VcPey2sZSzkKDnClQDcRCA2DQyx1GlWFWiYiIiIhqirS0NKxbt84iIQAA/fv3Z0KAKkQsyIMoOMHpoYSA3OxnIQMREREREZGM7t27h7Vr10Kr1Vq0t2nTBiEhITJFRTWBaNDDpMmH4Gw/BQbNmBQgIiIiIqJaLz09HdHR0SgoKLBob9GiBV544QWr6d5Ej0PUaSEUGuxqK0IzJgWIiIiIiKhWy8jIQHR0NPLz8y3aAwMDMXbsWCiVXHVN5SeKIkwFuRAV9vl9xKQAkZ0qKCjAnj17MG/ePDz//PNo1qwZBEGAIAiYO3dutcXRtGlT6X2HDRtWZt9PPvkEgiCgbt261RRd2SrrHObm5mLu3Lno2LEjPDw84O3tje7du2PhwoXS1o9VOZ6IiIiqTlZWFqKjo5Gbm2vR3qRJE0RGRkKlUskUGdUYBh1ErcYulw4ALDRYLQSlqkYX4xOU/EFZFU6fPo2hQ4fKGsODBw9w69Yt6d+xsbHIzs6Gt7d3if3Pnj0LAAgKCqqW+B6lMs5hSkoKQkNDkZycDABwc3ODTqdDfHw84uPjsX79ehw8eBC+vr5VMp6IiIiqTk5ODqKjo5GdnW3R3qhRI4wbNw7OzvY31Zscj6jTAsZCCEoPuUMpEZMC1YDb9VF5+fr6omvXrtLjrbfeQlpaWrW9/6+//io9r1OnDjIyMrBr1y5MmDChzP7BwcHVEp8tKnIOjUYjRowYgeTkZDRs2BDR0dHo378/TCYTtmzZgpdffhkJCQkYP348du/eXenjiYiIqOrk5uYiOjoamZmZFu3+/v6YMGECt7+lSiGKIkx5uXZZS8CMSQEiO9W3b19kZGRYtM2ZM6daYzBf5Pv5+WHy5MlYsGABtm7dWmJSIDMzU7ob3rVr1+oMs1QVPYerV6/GxYsXAQBbt25Fz549AQBOTk6IiIiAyWTCuHHjsGfPHhw8eBD9+vWr1PFERERUNfLz87F27Vo8ePDAor1+/fqYOHEiXF1dZYqMahy9FqJeA8HVXe5ISsWaAuRwZs2aBUEQMHr0aADAnj17MHr0aDRq1Aju7u7o1KkTFi9eDJPJJHOkFaNQKOQOQVoO0LVrV4SHhwMA9u7di7y8PKu+xWcV2MtMgYqewzVr1gAAwsLCpAv64saOHYvmzZsDAKKjoyt9PBEREVU+jUaDtWvX4v79+xbtfn5+mDhxItzc3GSKjGoik6YAMJkgOMn/t31pmBQgh3Pu3DkAQLt27RAZGYmhQ4di165d0Gg0KCgowMWLFzFz5kx88skn8gZaA5gv9Lt27YoePXqgcePG0Gq1JU51NycQvLy88MQTT1RrnFWhoKAAx48fBwAMGTKkxD6CIGDw4MEAgP3791fqeCIiIqp8Wq0Wa9euxd27dy3afX19MWnSJHh42Oeab3JMoskEsSAXgso+CwyaMSlADuf8+fMAgGXLluHIkSNYv349cnNzkZmZiVu3bqFv374AgPnz50MUa3KJx6qVmZmJpKQkAEVJgeKzM2JiYqz6F08g1IR9fC9fvizNNunQoUOp/czH0tLSLJYqVHQ8ERERVS6dTof169fjzz//tGj38fFBVFQUPD09ZYqMaiydFqJeD9jprgNmTAqQQ0lMTJSqw5pMJpw8eRLjxo2T1n0FBARg4cKFAIC8vDykpqZWegyrV6+WtrUrzyMuLq7SY6oK5jv/wP9qBJiXEOzevRsajabE/rbUE3CEc3jnzh3peePGjUvtV/xY8TEVHU9ERESVR6/X4/vvv8ft27ct2r28vDBp0qRSd1YiqgiTtgAAIDjZ92U3Cw2SQ0lISJCeL126FM2aNbPqU7duXel5VazLd3V1RYMGDco93lG2tjFf5Pv4+KBFixYAigr31atXD/fv38e+ffswatQoAEXb+dy4cQOAbfUEHOEcFt+ruKy1hcWPFR9T0fFERERUOQwGAzZu3IibN29atHt4eGDSpEncFpiqhGgshJifC8EB/vZnUoAcirmeQP369aWp7A+7du0aAMDd3R3+/v4Wx4xGIxYsWIBly5bh1q1bCAgIwJQpUzBnzhwolbb9d4iIiEBERET5P4SDMC8HCAoKkpYDKBQKjBw5EsuXL0dMTIyUFDh79qy0VMOWmQK15RwSERGRvAoLC7F582ZpSaSZm5sbJk2aZHEziagyiTotRIMOgof9z0Kx73kMRA8xzxQYPnx4qbMAzImDTp06Wa1tf/311zFnzhwEBwdj8eLFGDBgAD788EPMmDGjSuN2RKUtBzAvIdi1axf0ej2A/yUQPDw80Lp162qMsuoUX1dYUFBQar/ix4qPqeh4IiIiqhij0YiYmBhcv37dot3V1RWTJk1CvXr1ZIqMagOxIB9wUjhErS0mBcihmJMCISEhpfYxX8wGBQVZtF+8eBFLlixBREQENm3ahGnTpmHJkiV49913sXLlSsTHx1dd4A4mJydH+gX6cFKgX79+8Pb2Rk5ODg4cOADgf+e8S5cucLLzNVO2atSokfS8rNoUxY8VH1PR8URERFR+JpMJP/zwA65cuWLRrlarMXHixAotYyR6FNGgh0mbD8HOCwya1Yy/3qlWuH//vlSIrawp6qXd4d64cSNEUcQbb7xh0W7+98aNG22KY9OmTfD39y/348SJEzZ/ZrkkJCSUuhxApVJhxIgRAICtW7cCsNx5wBaOcA7btWsnJTguXbpUaj/zMX9/f9SpU6fSxhMREVH5mEwmbN++Hb///rtFu7OzMyZMmICGDRvKFBnVFqJOC8Ggh6Cy/3oCAGsKkAMxzxJQqVTo1KlTiX2KF7x7eKZAfHw8nJyc0K1bN4v2xo0bo3HjxjbPFNBoNFZ72z4O85R7e2ZOrJS2HCA8PBzr1q3Djh07kJmZKdVxsKXIIOAY59DNzQ29e/fGsWPHsHfvXrz77rtWfURRxL59+wAAAwcOrNTxRERE9PhEUcSuXbtw8eJFi3aVSoXx48cjICBApsioNjEV5EJUKGH/CweKcKYAOQxzrYD27dtDrS55Ks65c+cgiiJUKpXV3vB37tyBn59fiZXrGzVqZPP2hZMnT4YoiuV+hIaGPtbnloP5zn9pywEGDRoEd3d3ZGRkYNGiRTCZTABsnyngKOcwKioKAHD48GH88ssvVse3bNmCxMREAMCkSZMqfTwRERHZThRF/PTTT9LfjGZKpRKRkZFo2rSpPIFRrSLqdRC1GodZOgAwKUAOxDxToKy70eY73E8++aTVxX9BQUGpyQQXFxdoNJpKirTyZGZmIj09XXqYL74LCgos2vPy8qzGJicnQxAECIKAuXPnPtb7lrYEw8zV1RVDhgwBACxatEhqa9eu3WO9T3WoyDmMiopCx44dIYoiwsPDcfDgQQBF0xK3bNmCl19+GQAwZMgQ9OvXr9LHExERkW3Ms+/MNzbMFAoFIiIi0Lx5c5kio9pG1GkAYyEEpUruUGzGpAA5DHPWtzz1BICiC3+dTlfiOK1WCxcXl4oHWcmCgoJQr1496XHr1i0AwOeff27RPnPmzEp7z/z8fKkoT1nn2rwLgfliunPnzqXuCCGnipxDpVKJnTt3IjAwEKmpqejfvz/c3d3h7u6OF198ETk5OQgKCsL69etLfO+KjiciIqJHE0URsbGxVrPynJycMGbMGLRs2VKmyKi2EUURprxcwIESAgCTAuQgCgoKcPXqVQBlX6iaZxM8XE8AAAICApCenl7ievQ7d+6gcePGlRStfSi+HOKpp56yedy5c+dsWg4wbNgwi5kXti4dcDSBgYG4cOECPvzwQ3To0AGCIEClUiE4OBgLFizAqVOn4OvrW2XjiYiIqGxxcXFWRYgFQUB4eDjatGkjU1RUK+m1EPUaCGr7u9lYFkE0lxgnAEWF6ry9vZGdnQ0vLy+bxmi1WiQlJaF58+Z2ebeZivz1r3/Fp59+iuPHj6NXr15Se2pqKgICAvD2229j4cKFMkZYuebNm4cPPvgAffr0wbFjx+QOh6jC+LOWiIgeduzYMRw6dMiiTRAEjB49Gh07dpQpKqqtjNkZMGXeh5OH92OPFUURYn4uVIHWRb6rGmcKUK0REREBQRDw9ddfW7Sb/x0RESFHWFXG/Avyk08+kTkSIiIiosp34sQJq4QAADz33HNMCFC1E00miAW5EJSOsQ1hcdySkGqNzp07Y/r06Vi6dClEUcTAgQMRHx+PpUuXIioqCiEhIXKHWGl0Oh1OnjyJwYMHo2/fvnKHQ0RERFSpTp8+jQMHDli1Dx8+HF26dKn+gIh0Wog6LQQ3T7kjeWxMClCt8u2336JZs2ZYvnw5tm/fjkaNGmHu3Ll4//335Q6tUqnVarvcTYGIiIioon799Vfs2bPHqn3IkCFl7lJFVJVM2gIAAoQStvO2d0wKUK2iVCrx/vvv17gkABEREVFtcO7cOfz4449W7QMGDKhRsz7JsYhGY9HSAWfHWzoAsKYAERERERE5gEuXLmHnzp1W7WFhYRZFpImqm6jTQNTrAZX60Z3tEJMCRERERERk1y5fvowffvgBD2+c9vTTT+Ppp5+WKSqiImJBPiAIEARB7lDKhUkBIiIiIiKyW1evXkVMTIxVQqBXr14IDQ2VJyii/xILDTBp8yGoHXe7ZCYFiIiIiIjILiUlJWHz5s0wmUwW7T169ED//v0d9s4s1RyiTgvBoIegcsx6AgCTAkREREREZIf0ej22bdsGo9Fo0R4cHIxBgwYxIUB2QdTkQVQo5A6jQpgUICIiIiIiu/Pzzz8jNzfXoq1Lly4YNmwYEwJkF0S9DqaCfAjOjrt0AGBSgIiIiIiI7ExmZiZOnDhh0da8eXOMGDGCCQGyG6JeCxgLIShVcodSIUwKEBERERGRXdm/f7/FsgEnJycMGTIETk68fCH7IIoiTHk5gIMnBAAmBYiIiIiIyI4kJibijz/+sGjr3r076tWrJ1NERCXQayHqNBCc1XJHUmFMChARERERkV0wmUzYt2+fRZubmxu3HiS7Y9JqAFGEoFDKHUqFMSlARERERER2IT4+Hvfu3bNoe/bZZ+Hi4tiF3KhmEU0miAV5EJSOuw1hcUwKEBERERGR7AoKCnD48GGLNn9/fwQFBckUEVEpdFqIOi1QA5YOAEwKEBERERGRHTh8+DC0Wq1F2+DBg1lckOyOSVcAQIRQQ743a8anICIiIiIih3X37l38+uuvFm1PPvkkmjVrJlNERCUTjUaI+bk1osCgGZMCREREREQkG1EUsXfvXoiiKLUplUoMGDBAxqiISibqtRD1ekDFpAAREREREVGFXb58GcnJyRZtffr0gbe3tzwBEZVBzM8DBAGCIMgdSqVx/P0TqMYRRRExMTH4/vvvcfbsWdy7dw8KhQINGjRAw4YNERISgr59+6Jfv37w8vKyGPvll18iKysLo0aNQpcuXeT5AP8VFxeHuLg4BAYGYvLkybLGIoe8vDz89NNPOHDgAM6cOYPExETodDrUqVMHXbp0wdixYzFhwgQolfwxREREVFsZDAbs37/fos3b2xu9evWSKSKi0omFBpi0+TVq6QDApADZGfMF/ZEjR6Q2pVIJNzc33Lx5E4mJiTh+/DgWLVqEVatWWV1sf/nll0hJSUFgYKBdJAU+/vhjPPPMM7UyKRAUFITr169L/3Z2doaLiwvu3r2Lffv2Yd++ffjuu+/w008/oV69ejJGSkRERHI5ceIEsrOzLdoGDBgAlUolU0REpRN1WggGPeBRs2axcPkA2ZVJkybhyJEjUCgUeOedd3D16lXodDo8ePAAGo0G58+fx/z589G5c2e5Q6VHMBgMaN++PT7//HP89ttv0Ol0yMnJwZ9//on33nsPCoUCZ86cQXh4uMUaQiIiIqodsrOz8fPPP1u0NWvWDO3bt5cpIqKyiZo8iApFjVo6AHCmANmRa9euYdeuXQCAefPmYc6cORbHlUolOnXqhE6dOuH//u//oNFo5AiTbLR69Wo888wzVj80/f398e9//xs+Pj54//33cezYMRw/fhx9+vSRKVIiIiKSQ2xsLAoLC6V/C4KAwYMH17gLLqoZRL0OJk0BBGcXuUOpdJwpQHbj3Llz0vORI0c+sr+rq6v0fO7cuRAEASkpKQCAKVOmQPhvARDhoUIgycnJUltycjJu3LiB6dOno3nz5lCr1QgMDJT6ZmdnY+PGjRg/fjw6duyIOnXqwMXFBc2aNcO4ceNw6tQpq7jMr//xxx8DAI4cOWIVy+rVq63GpaWlYc6cOejcuTO8vb3h4uKCFi1aYNq0afj999/LPBcpKSmYOnUqAgICoFarERAQgClTpuD69etWn9ds7NixEAQBQ4cOLfO1r1+/DicnJwiCgLi4uDL7FhcaGlrmL/WpU6dKz8+cOWPz6xIREZHju3nzJi5dumTR1rVrV/j7+8sUEVHZRL0WMBggKGve0hYmBcgu3b59+7H6e3h4oEGDBnByKvqW9vLyQoMGDSweJTlx4gS6dOmCZcuW4d69e1br1xYtWoTIyEh8//33uHTpEgwGA4CiX2QbNmxAr1698PXXX1uMMRdFdHd3BwCoVCqrWIonNADgxx9/RKtWrTB//nxcuHABGo0GSqUSSUlJWLFiBYKCghAdHV3iZzh58iQ6duyIlStXIjU1FQqFAtnZ2Vi9ejWCg4NLveB+5ZVXAAD79u3DzZs3Sz23y5cvhyiKaN26NUJDQ0vt97hcXP6XZTUajZX2ukRERGTfTCYT9uzZY9Hm4uKCZ599VqaIiMomiiJM+blADa11waQA2Y3u3btLd5bN9QRsNXv2bKSlpaFJkyYAgK+++gppaWkWj5LMmDEDTz75JM6cOYP8/Hzk5eVZVMD19/fHW2+9hVOnTiEzMxO5ubnQaDRITEzErFmzAABvv/02EhISpDFNmjRBWloaZs+eDQDo1auXVSwRERFS/9OnTyM8PBx5eXmYMWMGLl++DI1Gg7y8PKSkpOC1116DXq/H1KlTER8fbxF/VlYWwsPDkZubixYtWuDQoUPIz89Hbm4uTp8+jebNm2PGjBklfvbQ0FC0a9cOJpMJK1asKLGPwWCQZjVMnz69rC/BYys+66Bjx46V+tpERERkvxISEqz+NgsNDYWbm5tMERE9gkEHUaupcbsOmDEpQHYjMDAQ06ZNAwBcvHgRbdu2RdeuXfGXv/wFK1euxKVLlyq9IF3dunURGxuLbt26SW2tW7eWnr/yyiv44osv0KNHD/j4+AAoWu/WvHlzfPnll3jttddgNBqxePHicscwc+ZM6PV6fPDBB1iyZAnatm0LhUIBAGjatCkWL16MN954A4WFhZg3b57F2G+//RZ//vknXFxcsG/fPoSFhUmJle7duyM2NlZ6rZKYEwYrV64s8W79zp07cffuXTg7OyMqKqrcn/FhBoMBf//73wEALVq04J0BIiKiWkKr1eLQoUMWbfXq1UP37t1liojo0UStBjAZIShqZkk+JgXIrnz33Xf44IMP4O7uDlEUkZCQgO+++w5Tp05Fx44d4e/vj7fffht3796tlPebOXMmPDw8yj1+2LBhAGBVOddW58+fx5kzZ6BSqfDOO++U2m/SpEkAigryFL9437JlCwAgIiICLVu2tBrn5+eHV199tdTXjYqKgpubG27fvo3du3dbHV+2bBkAIDw8HH5+frZ9KBvMmjULFy5cgCAIWLx4MbcdIiIiqiWOHDmCgoICi7bBgwdLS0CJ7I1oMsGUnwtB5Sx3KFWG//vIriiVSvzjH/9Aamoq1q5di2nTpqFz585wdi76T3jv3j0sWrQIHTp0wOnTpyv8fr17935kn8TERMyePRvBwcHw8fGB4r/bkBQv0ve4NRDMzMkEk8mENm3awN/fv8TH4MGDAQD5+fl48OABAECv1+O3334DADzzzDOlvkdZdQB8fHykpQzmBIBZSkoKDhw4AKBylw4sXLgQ/+///T8AwAcffCB9NiIiIqrZ7t+/b/X3W9u2bdGiRQuZIiKygV4LUacFaujSAYBbEpKd8vb2xoQJEzBhwgQARVPNfv75Z3z99dfYtWsX0tPTER4ejmvXrlkUrHtc9evXL/P4tm3bEBkZCZ1OJ7V5eXnBxcUFgiBAr9cjMzMT+fn55Xr/O3fuACgqtGfr7Adzdj0jI0OaNdCoUaNS+zdu3LjM13vllVewatUq7N69G6mpqVL/5cuXS8mKyiow+M0330i1Ft58801phwYiIiKq2URRxL59+2AymaQ2hUKBgQMHyhgV0aOZtBoAIgSn0pfkOjrOFCCH4OLigv79+2Pnzp3S2vbbt29j7969FXrdstbbP3jwAJMnT4ZOp8Ozzz6LuLg4FBQUIDs7G3fv3kVaWpo0fb+8zBf1bdu2hSiKNj3MWyYWr69Q1tZ/j6rDEBISgq5du8JoNEoFB41GI1atWgUAePnllyvyESXffvst3njjDQBFyzYWLVpUKa9LRERE9u/atWu4ceOGRVvPnj3h6+srU0REjyYajRALavbSAYBJAXJAxaeyX7lypcreZ/fu3cjJyYGvry927dqFZ555xmorwdJ2NbCVeS/exMTEx55tULduXSmpYZ5xUJKyjpmZtydcsWIFTCaTNGtArVZXSoHBb775Bq+//jqAooTAN998U+HXJCIiIsdQWFiIffv2WbR5enqib9++MkVEZBtRr4Wo0wHO5Z+Z7AiYFCCHU7wwoFptubbHXKSmMnYpuHXrFgCgTZs2pW6RExsbW+p4W2Ix1zTQ6/XYtm3bY8Xn7OyMJ598EoDl9n4PK+uY2bhx4+Dl5YWbN29i3759Un2B559/vsIFBr/55htphsBf/vIXJgSIiIhqmV9++QUZGRkWbf3795dqRhHZK1FTAPy3llhNxqQA2Y2kpCRcvXr1kf3WrFkjPe/atavFMS8vLwBAVlZWhePx9vYGAFy9ehVardbq+Llz5/D999+XOt6WWLp164agoCAAwN/+9jfcv3+/zJge/oX6wgsvAAA2b96MxMREq/4PHjzAkiVLynxNAHB3d8fEiRMBAPPmzZN2IqhogcHiCYHXX38d3377bYVej4iIiBxLXl4ejh49atEWEBCAjh07yhQRkW1EYyHEgjwINbjAoBmTAmQ3fvvtN7Rr1w7Dhg1DdHQ0kpOTpWMGgwEJCQmYMmUKvvjiCwBFa+H79Olj8RodOnQAAMTExCAzM7NC8QwcOBBOTk7IyMjA+PHjkZqaCqDorv7mzZsxcOBAeHp6ljreHMtvv/2GEydOlNhHEAQsWbIEarUaN2/eRI8ePRATE2OxVU9qairWrVuHAQMG4L333rMYP3PmTDRo0AAajQaDBg3CkSNHpJkJ8fHxGDBgAAoLC236vOYlBCdOnIDRaKxwgcHFixdLCYFZs2bh66+/LvdrERERkWM6ePAg9Hq9RduQIUNq/J1XcnyiVgMYdEANrycAMClAdkSlUknr2aOiotC8eXOo1WrUrVsXarUaXbt2xerVqwEUzRDYtm2b1Z6206dPhyAIOHHiBOrVq4dGjRohMDBQKs73OFq1aoV3330XAPDDDz8gICAAPj4+8PDwQEREBDw8PMq80A0NDUWbNm1gNBrRu3dv1KlTR4olJiZG6hcSEoJdu3ahbt26SEpKwpgxY+Dl5QU/Pz+4u7sjICAAEydOLHGpgq+vL2JiYuDh4YHr168jNDQUHh4e8PT0RPfu3ZGUlIT//Oc/Uv+ydmro0KGDRZKlogUGzTUEAGDjxo2lbrfo7++PWbNmVei9iIiIyP6kpqbi3LlzFm1dunQpc9ckInshavIg/ncr8pqOSQGyG4MGDcK1a9fw1VdfYcyYMWjXrh3UajWysrLg5uaGVq1a4cUXX8TGjRtx5syZEn+hPP300/jpp5/Qv39/eHt74+7du0hJSUFKSkq5Yvr3v/+N6OhohISEwNXVFQaDAS1btsRf//pXJCQklPlLTalU4uDBg5g2bRoCAwORn58vxZKXl2fRd8CAAbh+/To+/fRT9OnTB97e3sjKyoKTkxPat2+PqVOnYufOnSWux+/Tpw8uXLiAKVOmoFGjRigsLISPjw9eeuklnD17Fk888YTU18fHp8zPO2bMGAColAKDxWsp3L17t8xHdnZ2hd6LiIiI7IsoitizZ49Fm7OzM/r16ydTRES2Ew16mDQFEGp4gUEzQayMimw1SE5ODry9vZGdnS2tCX8UrVaLpKQkNG/evMw7sURyWLZsGaZPn44WLVpYbQX0sBEjRuDHH39EZGRkmfUSiOTAn7VERI7j/Pnz2L59u0XbgAED0KtXL3kCInoMprxsmO7/CcHTp9reUxRFiPm5UAW2rrb3NONMAaIaTKvV4ssvvwQADB48uMy+iYmJUoHBV199tapDIyIiohpKp9NZLXusU6cOevToIVNERLYTRRGm/FyICqXcoVQbJgWIHNzGjRvx97//HZcuXZIK+RQWFuLo0aN49tln8fvvv8PFxaXMdfs5OTl49dVXYTKZ0KNHD+4bTEREROV27Ngxq6WSgwYNgkKhkCkiosdg0EHUaiCoa8+sxNqT/iCqodLS0vCvf/0L//rXvyAIAnx9fZGXlyclCJydnbFq1Sq0bm09FWn27NnYsmUL0tLSoNfroVQqpZkFRERERI8rIyMDp06dsmhr2bJliX+HENkjUacFTEYItWimQO35pEQ11PDhw3H//n3ExcUhJSUF6enpUKlUaNGiBcLCwvDmm2+W+os4PT0dN2/ehIeHB4KDg/HPf/4TTz31VDV/AiIiIqop9u/fD6PRKP3byckJgwYNkjEiItuJoghTXi6EWrANYXFMClQDzxVp0Btrbj1HZ4WA3Kn+codRa7Vs2RL/+te/yjV29erV0jaPRERERBVx48YNXLlyxaItJCQEfn5+MkVE9JgMeoh6LQQXV7kjqVZMClQDvVGE3iR3FFWp5iY8iIiIiOjRjEYj9u7da9Hm7u6OZ555RqaIiB6faNBDEGvX0gGAhQaJiIiIiKiC4uPjkZ6ebtH27LPPcgtZciiiTguxFl4i175PTERERERElSY/Px9xcXEWbQ0bNkRQUJA8ARGVg2gyQdTmQ1Cp5A6l2tWIpEBOTg7mz5+PXr16oV69elCr1QgICEBYWBjmzp2LrKwsuUMkIiIiIqqRDh8+DK1Wa9E2ePBgCIIgU0RE5VCoh2jQA7WsyCBQA5IChw8fRuvWrTFnzhycPHkSWVlZcHNzQ2pqKuLi4vDxxx8jOTlZ7jCJHtvq1ashCMIjH7GxsVUaR9OmTaX3GjZsWJl9P/nkEwiCgLp161ZpTLZ68OABVq1ahQkTJqB9+/Zwd3eXkoajRo3Ctm3bbHqd3NxczJ07Fx07doSHhwe8vb3RvXt3LFy4UNr6kYiIqDZKS0vDr7/+atHWsWNHNG3aVKaIiMpH1OsBkwmCk0LuUKqdQ1dQOH78OIYNGwaNRoP+/ftj7ty56NmzJ5ycnKDRaPD7779j27Zt8Pb2ljVOZ4WAmlyMr+jzUVVxcnJCvXr1Sj2uVqur7L0fPHiAW7duSf+OjY1FdnZ2qf+nzp49CwB2M13Q398fhYWF0r9dXFygUqmQmpqK1NRU7NixA0OGDEFMTAzc3NxKfI2UlBSEhoZKyUU3NzfodDrEx8cjPj4e69evx8GDB+Hr61sdH4mIiMhuiKJoVVxQpVKhf//+MkVEVH6iVgMoal9CAHDgpEBBQQEmTZoEjUaD8PBwbN68GU5O/5v44OrqiuDgYAQHB8sYZRFu10cV0aRJE9lmuxTP/NepUwcZGRnYtWsXJkyYUGZ/e/h/BwCFhYUICQnB5MmTMWjQILRo0QIAkJycjHnz5mHFihXYs2cPZsyYgbVr11qNNxqNGDFiBJKTk9GwYUNER0ejf//+MJlM2LJlC15++WUkJCRg/Pjx2L17d3V/PCIiIln9/vvvSElJsWjr06cPvLy8ZIqIqHxEoxGirgCCsvbVEwAcePnA2rVrkZiYCFdXVyxZssQiIUBElcN8ke/n54eXXnoJALB169YS+2ZmZkrJi65du1ZLfI9y6NAh/PLLL3j11VelhAAABAYGYvny5ZgxYwYAYN26dRYzIsxWr16NixcvAij63OY7H05OToiIiMDSpUsBAHv27MHBgwer+uMQERHZDYPBgP3791u0+fj4oGfPnjJFRFQBhXqIBgOgrH31BAAHTgpER0cDAEaOHAk/Pz+Zo6HqNGvWLAiCgNGjRwMouiAbPXo0GjVqBHd3d3Tq1AmLFy+GyWSSOVLHZ14O0LVrV4SHhwMA9u7di7y8PKu+xWcV2MtMgbCwsDKPT506VXoeHx9vdXzNmjXS65T0R87YsWPRvHlzAP/7mURERFQbHD9+HDk5ORZtAwcOhKoWVm4nxyca9IBoglBLbzQ75Kc2r+cFgGeeeQaJiYmYOnUqAgICoFar4e/vj5EjR2LPnj0yR0pV4dy5cwCAdu3aITIyEkOHDsWuXbug0WhQUFCAixcvYubMmfjkk0/kDbQGMF/od+3aFT169EDjxo2h1WpLnCpvTiB4eXnhiSeeqNY4y6v43slGo9HiWEFBAY4fPw4AGDJkSInjBUHA4MGDAcDqbgkREVFNlZ2dLf2ONGvevDnatm0rU0REFSNqCwCFw66srzCHTAokJydLFb9v376NTp06YeXKlbh//z7c3Nxw9+5d7Ny5E0OHDsWrr75a5mvpdDrk5ORYPMi+nT9/HgCwbNkyHDlyBOvXr0dubi4yMzNx69Yt9O3bFwAwf/58iKLjF3i8f/8+goOD4eHhAVdXV7Ro0QITJkyw2g+4smVmZiIpKQlAUVKg+OyMmJgYq/7FEwiOsgVR8XPYsWNHi2OXL1+WZpt06NCh1NcwH0tLS0NGRkblB0lERGRnDhw4YFHIVxAEDBo0yGF+/xMVJxoLIWq1tbaeAOCgSYHMzEzp+aeffgqVSoUNGzYgLy8PmZmZuHnzJsaOHQsAWLJkCb766qtSX+vTTz+Ft7e39GjSpEmVx0/ll5iYiOzsbACAyWTCyZMnMW7cOLi6ugIAAgICsHDhQgBAXl4eUlNTKz0GW7cKLO3xuBfzBQUFOHv2LJydnWEymZCUlIT169cjLCwML730ksUv5cpkvvMP/K9GgHkJwe7du6HRaErsb0s9geo+hyXJysrCp59+CgDo27cv2rRpY3H8zp070vPGjRuX+jrFjxUfQ0REVBMlJyfjt99+s2jr1q0bGjRoIFNERBWk10Ms1AOq2llPAHDQ3QeKrxU3mUxYsmQJIiIipLYmTZpg/fr1uHLlChISEjBv3jz85S9/gVJp/XHff/99vP3229K/c3JymBiwYwkJCdLzpUuXolmzZlZ96tatKz1XVMG2Iq6urhX6xefsbNsPnEaNGuGjjz7C888/jzZt2kCtVsNoNOKXX37BRx99hNjYWKxatQru7u745ptvyh1PacwX+T4+PlKRvr59+6JevXq4f/8+9u3bh1GjRgEo+n9z48YNALbVE6iuc1gak8mEiRMn4s8//4RarS7x/OXm5krPS9uu8OFjxccQERHVNCaTyWoLQldX10fW8CGyZ2Jh0Qz02jzTxSGTAp6entLzJk2aWCQEzJycnPDOO+9gwoQJSE9Px6+//ooePXpY9VOr1VW6zztVLnM9gfr160tT2R927do1AIC7uzv8/S23gzQajViwYAGWLVuGW7duISAgAFOmTMGcOXNKTBqVJCIiosTvuco2cOBADBw40KJNoVCgV69e2LdvH55//nns2LED3333Hd544w20atWqUt/fvBwgKChI+iGpUCgwcuRILF++HDExMVJS4OzZs9JSDVtmClTXOSzNrFmz8OOPPwIAvvvuO3Tu3Fm2WIiIiBzF2bNncffuXYu2sLAwacYmkSMyafJrdT0BwEGXDxSfrltWQZN27dpJzx/eQ5Uck3mmwPDhw0udBWBOHHTq1Mkq4/f6669jzpw5CA4OxuLFizFgwAB8+OGH0tZ0jsLJyQkLFiwAUJS137VrV6W/R2nLAcxLCHbt2iXV9jAnEDw8PNC6detKj6UyzZ49G99++y0AYNGiRdJWiw8rnnwsKCgo9fWKHys+hoiIqCbRaDQ4dOiQRVv9+vXtZschovIQCw0Q9bpaXU8AcNCkQJ06daTEQFnTPIoXmavN00FqEnNSICQkpNQ+5ovZoKAgi/aLFy9KS002bdqEadOmYcmSJXj33XexcuXKEreks2ctW7aUtuNMTEys1NfOycnB9evXAVgnBfr16wdvb2/k5OTgwIEDAP53zrt06QInO97K5f/+7/+kmhOff/453nzzzVL7NmrUSHpeVm2K4seKjyEiIqpJ4uLirOoJDR482K5/7xM9imjQAwYDwKSAYzJPq758+XKpFeYvX74sPTfvJU6O6/79+1Iht7KmqJd2h3vjxo0QRRFvvPGGRbv53xs3brQpjk2bNsHf37/cjxMnTtj8meWSkJBQ6nIAlUqFESNGAAC2bt0KwHLnAVvIcQ7fffddfP755wCAzz77DLNnzy6zf7t27aQ/dC5dulRqP/Mxf39/1KlT57HjIiIisnf379/HmTNnLNratWvHv6/J4Yl6HSDwBrLDLp6YMmUKVq1ahVu3bmHTpk3SbgNmJpMJX3zxBYCi5Qa2XqyQ/TLPElCpVOjUqVOJfYoXvHt4pkB8fDycnJzQrVs3i/bGjRujcePGNs8U0Gg0VuvpHod5yn1F3bhxA+np6QAqP+llTqyUthwgPDwc69atw44dO5CZmSnVcbB1CmF1n8PZs2dLMwQ+++wzvPvuu48c4+bmht69e+PYsWPYu3dviWNEUcS+ffsAwKr+AxERUU2g1Wrxww8/WNyEUygUGDBggIxREVWcKIoQC/Jr/dIBwIFnCvTt2xcvvPACAODVV1/Fpk2bYDAYAAC3bt3C+PHjpYvIf/3rX5zaVAOYawW0b9++1OKQ586dgyiKUKlUVnvL37lzB35+fiVWrm/UqJHN2xdOnjy56IdIOR+hoaGPfI/SZr8UP26+SHVycsLw4cNtit1W5jv/pS0HGDRoENzd3ZGRkYFFixZJO4LYmnyrjnNoVjwhsGDBApsSAmZRUVEAgMOHD+OXX36xOr5lyxZp6cakSZNsfl0iIiJHoNPpsG7dOqSlpVm09+rVC76+vjJFRVRJCg1FOw8wKeC4SQGgaK/zp59+GllZWRg7diw8PT1Rp04dNG3aVJoK/uGHH0p/2JNjMyd5yrobbb7D/eSTT1pd/BcUFJSaTHBxcbFaJyenlJQUhISEYOnSpUhMTJSSBCaTCadOncKQIUOwbds2AMCMGTPQpk0bq9dITk6GIAgQBAFz5859rPcvbQmGmaurK4YMGQKgqFifua14cU978N5770kJgS+++ALvvPPOY42PiopCx44dIYoiwsPDcfDgQQBFX4ctW7bg5ZdfBgAMGTIE/fr1q9zgiYiIZKTX6/H9999b3TTx9fVFnz59ZIqKqPKIBj0EYyFnCsCBlw8ARVvOHT58GCtXrsTatWtx6dIl5ObmonHjxujbty9ef/119OrVS+4wqZKYZwqUp54AUHThn5eXV+I4rVYLFxeXigdZic6cOSOt31Or1fD09ERubi50Op3UZ8qUKfj6668r9X3z8/Nx5coVAGWf6/DwcMTExEjntHPnzqXuCCGHmzdv4rPPPgNQNJti/vz5mD9/fqn9Z8+ebVVnQKlUYufOnQgLC0NycjL69+8PNzc3mEwmaLVaAEXLVNavX191H4SIiKiaGQwGbNy4ETdv3rRo9/T0xIQJE0qcdUnkaES9FiKA2l1NoIhDJwWAoj/2p02bhmnTpskdClWhgoICXL16FUDZF6rm2QQP1xMAgICAAPzxxx/Q6/VWv8zu3LmDJ554ohIjrpgGDRrgm2++wcmTJ3Hu3Dncv38fmZmZcHFxQfPmzdGrVy+89NJL6N27d6mvUTyz/9RTT9n83ufOnbNpOcCwYcOgVqulJIW91e0wfwbz80fVMCgtYRQYGIgLFy5gwYIF+OGHH5CUlASVSoUnn3wSkZGReP311/nHERER1RiFhYXYvHkzkpKSLNrd3d0xadIkFtWlGkEURYiaAghK/g0H1ICkANUObm5uMBqNj+x38eLFUo8FBwdj//79iI+Pt5hBkpqaitTUVERERFRKrJXB1dUVM2fOxMyZM8v9GocPHwYA9OnTB4MHD7Z5XO/evR9Z0wAoultgvltujwIDA236HLbw9PTExx9/jI8//rhSXo+IiMgeGY1GxMTESNsSm7m6umLSpEnSVshEDs+gL1o+oLavmcJyceiaAkSPIyIiAoIgWE23N//bnpICleHQoUMAgE8++UTmSIiIiMjemUwmbNu2TVpCaKZWqzFx4kTUr19fpsiIKp9UT0DBe+QAZwpQLdK5c2dMnz4dS5cuhSiKGDhwIOLj47F06VJERUUhJCRE7hArjU6nw8mTJzF48GD07dtX7nCIiIjIjomiiB07duC3336zaHd2dsaECRPQsGFDmSIjqhqiTgtRcGI9gf9iUoBqlW+//RbNmjXD8uXLsX37djRq1Ahz587F+++/L3dolUqtVtvVbgpERERkn0RRxK5du3DhwgWLdpVKhXHjxiEgIECmyIiqhmgyQdTmQ1Bx1wEzJgWoVlEqlXj//fdrXBKAiIiI6HGJoog9e/ZIhZrNlEolIiMj0axZM5kiI6pChXqIBgMEVze5I7EbrClARERERFTLiKKIAwcOSNsfmzk5OSEiIgLNmzeXKTKiqiXq9RBMRghO9rOVttyYFCAiIiIiqmXi4uJw8uRJizYnJyeMGTMGLVu2lCkqoqonajUQmRCwwKQAEREREVEtcvToURw9etSiTRAEPP/882jbtq1MURFVPdFohKgrYD2BhzApQERERERUS5w4cQKHDx+2ah81ahSefPJJGSIiqkb/rScApbPckdgVJgWIiIiIiGqB06dP48CBA1btI0aMQKdOnWSIiKh6iQY9IIoQnHgZXBzPBhERERFRDXf27Fns2bPHqn3IkCHo2rWrDBERVT9RWwAoeAn8MJ6RSiSKotwhEBHVWPwZS0RUPhcuXMCuXbus2gcMGICQkBAZIiKqfqKxEKJWC4FLB6wwKVAJnP47/cRoNMocCRFRzWX+GevEKX9ERDb77bffsH37dqv2sLAw9OrVq/oDIpKLQQ+xUA+omBR4GP+yqgQqlQoqlQp5eXlyh0JEVGPl5uZKP2+JiOjR/vjjD/zwww9WM6369u2Lp59+WqaoiOQhGvQAinbaIEtMClQCQRDg6emJ7OxsaDQaucMhIqpxNBoNcnJy4OnpyV/mREQ2uHbtGrZs2QKTyWTR3rNnT4SFhckUFZF8TJp8wEkhdxh2SSl3ADWFn58fNBoNbt68CS8vL3h6ekKhUPCPVyKichJFEUajEbm5ucjJyYFarYafn5/cYRER2b2kpCRs3rzZKiHQvXt3DBgwgH+fUq0jFhog6nUQuHSgREwKVBKFQoEmTZogPT0dubm5yMrKkjskIqIaQaVSwcfHB35+flAomOEnIirLzZs3sWHDBhQWFlq0BwUFYciQIUwIUK0kGvSAwQCoXeUOxS4xKVCJFAoFGjRogPr168NgMFhlZ4mI6PE4OTlBpVLxj1giIhvcvn0b69evh8FgsGjv1KkThg8fzp+lVGuJeh0gsJ5AaZgUqAKCIMDZmVNTiIiIiKh6/Pnnn1i3bh30er1Fe/v27TFy5Eju3EK1mqjJh6BkoeLS8KcDEREREZEDu3v3LtauXQudTmfR3qZNGzz//PNMCFCtJhr0RcsHmBQoFX9CEBERERE5qPT0dKxdu9ZqB6yWLVvihRdeYC0WqvVEgx4oNHCmQBmYFCAiIiIickAZGRmIjo5Gfn6+RXvz5s3x4osvQqnkSmGionoCvOwtC88OEREREZGDycrKQnR0NHJzcy3amzZtirFjx0Kl4l1RIlEUIWoKOEvgEZgUICIiIiJyIDk5OYiOjkZ2drZFe+PGjTFu3DgWvCYyM+ghGnQAZ82UiUkBIiIiIiIHkZeXh+joaGRmZlq0+/v7Y/z48VCr1TJFRmR/RIMegrGQMwUegUkBIiIiIiIHUFBQgOjoaDx48MCivX79+pg4cSJcXV1liozIPol6HUTWE3gkniEiIiIiIjun0Wiwdu1a3L9/36K9bt26mDhxItzc3GSKjMg+iSYTRG0+BNbXeCQmBYiIiIiI7FhBQQHWrl2LtLQ0i3ZfX19MmjQJHh4eMkVGZMcK9RD1ekDFGhuPwooLRERERER2Ki8vD2vXrsW9e/cs2r29vTFp0iR4eXnJFBmRfRP1eggmIwQnhdyh2D0mBYiIiIiI7FBubi6io6ORnp5u0e7p6YlJkybBx8dHnsCIHICo1UB0UkCQOxAHwKQAEREREZGdyc7Oxpo1a6x2GfDy8kJUVBTq1KkjU2RE9k80mSDqClhPwEZMChARERER2ZHMzEysWbMG2dnZFu0+Pj6IioriDAGiRzHoIBYaILiy3oYtmBQgIiIiIrIT6enpiI6ORm5urkV73bp1WUOAyEaiQQ+YTBCcWFffFkwKEBERERHZgXv37iE6Ohr5+fkW7fXq1eMuA0SPQdQWAAoWGLQVkwJERERERDL7888/sXbtWmg0Got2f39/TJw4EW5ubjJFRuRYRKMRolYLQcmtCG3FpAARERERkYxSU1Oxbt06aLVai/ZGjRphwoQJcHV1lSkyIgdkrifgxpk1tmJSgIiIiIhIJjdv3sT69euh1+st2ps0aYLx48dDrVbLFBmRYxINekBkPYHHwaQAEREREZEMkpKSsGHDBhgMBov2wMBAREZGwtmZ05+JHpdJkw8oeJn7OHi2iIiIiIiq2fXr17Fp0yYUFhZatD/xxBOIiIiAivurEz020VgIUa+DoGJC7XEwKUBEREREVI2uXLmCLVu2wGg0WrS3bt0aY8aMgVLJP9GJykWvBwwGQM06HI+DP3GIiIiIiKrJ77//jq1bt8JkMlm0t2/fHs8//zwU3EaNqNxMei0gAIIgyB2KQ2FSgIiIiIioGly4cAHbt2+HKIoW7R07dsSoUaPgxMJoRBUisp5AufCMERERERFVsYSEBOzcudOqPSgoCMOHD2dCgKiCRIMeokHPegLlwKQAEREREVEVOnPmDHbv3m3V3q1bNwwdOpRTnYkqgVhoAAoNgIub3KE4HCYFiIiIiIiqyMmTJ7F//36r9qeeegoDBw5kQoCokog6LSA48f9UOTApQERERERUBY4dO4ZDhw5Ztfft2xdhYWG8eCGqJKIoQtQUQODOHeXCs0ZEREREVIlEUURcXByOHj1qdSwsLAxPP/20DFER1WAGPUSDDoKzWu5IHBKTAkRERERElUQURcTGxuLEiRNWxwYMGIBevXrJEBVRzSYWGiAYCyEoPeQOxSExKUBEREREVAlEUcTevXtx+vRpq2NDhgxBSEiIDFER1XyiTgtRcAIX5JQPkwJERERERBUkiiJ+/PFHnD171urY8OHDERwcLENURDWfKIoQtfkQlCq5Q3FYTAoQEREREVWAyWTCzp07cf78eYt2QRAwcuRIdO7cWabIiGoBgw6iXg/BxVXuSBwWkwJEREREROVkNBqxbds2/PbbbxbtgiAgPDwcTz75pEyREdUOol4PwWSEoOClbXnxzBERERERlUNhYSG2bt2KP/74w6LdyckJY8aMQdu2bWWKjKj2EHVaiE4K1hOoACYFiIiIiIgek8FgwObNm3H9+nWLdoVCgYiICLRq1UqmyIhqD9FkgqgrgKBiPYGKYFKAiIiIiOgx6PV6bNy4EUlJSRbtKpUKY8eORYsWLWSKjKiWMeggGvQQXN3ljsShMSlARERERGQjnU6H77//Hjdv3rRod3Z2xrhx49CsWTOZIiOqfUSDHjCZIDgp5A7FoTEpQERERERkA61Wi/Xr1+P27dsW7Wq1GhMmTEBAQIBMkRHVTqJWAyiYEKgoJ7kDICIiIiKyd/n5+VizZo1VQsDV1RVRUVFMCBBVM9FohKjTQFA6yx1KhYiiiNxv/w7diX2yxcCkABERERFRGXJycrB69WqkpaVZtLu7uyMqKgoNGzaUKTKiWsygg2gwAErHLjJouHQauqM/Ie+r92WLgcsHiIiIiIhKkZWVhejoaGRmZlq0e3p6YtKkSfDz85MpMqLaTTToAdEEwcmx73Nr926SOwQmBYiIiIiISpKeno7o6Gjk5uZatPv4+GDSpEnw9fWVKTIiMmnyAYVjX84a79+BPv6I3GEwKUBERERE9LC0tDSsW7cO+fn5Fu1169bFpEmT4OXlJVNkRCQaCyHqdRBUjl1PQLt/CyCa5A6DSQEiIiIiouJu376N9evXQ6vVWrQ3aNAAEydOhLs790QnkpVeDxQWAmpXuSMpN1GvhfbgNrnDAMCkABERERGRJDk5GRs2bIBer7dob9y4McaPHw9XV8e9CCGqKUSDrqiegCDIHUq56Y7vg5iXLXcYAJgUICIiIiICAFy7dg2bN29GYWGhRXtgYCDGjh0LtVotU2REVJxJk+/Quw6IogjN3o1yhyFhUoCIiIiIar3ff/8dW7duhclkub63ZcuWePHFF6FSOe4FCFFNIhYaHL6eQOHV8zAm/SF3GBImBYiIiIioVjt//jx27NgBURQt2tu1a4fw8HAoFAqZIiOih4mG/9YTcHGTO5Ry0+yxn1kCAJMCRERERFSLnTlzBrt377Zq79y5M5577jk4Ofge6EQ1jajTAgIctp6AKfM+9L8clDsMC0wKEBEREVGtdPz4ccTGxlq1d+vWDUOHDnXYiw6imkoURYiaAggOXE9Ac2ArYCx8dMdqxKQAEREREdUqoigiLi4OR48etTrWq1cv9O/fnwkBIntUaIBo0EFwdsyin2KhAdrYrXKHYYVJASIiIiKqNURRxP79+3Hq1CmrY2FhYejbty8TAkR2SjToIZiMDjtTQP/LQYhZ6XKHYYVJASIiIiKqFUwmE3788UckJCRYHRs4cCB69uwpQ1REZCtRp4UIwFHTdmVtQ6hs1bEaI3novWV7ZyIiIiKiamI0GrF9+3ZcunTJ6tjw4cMRHBwsQ1REZCtRFCFq8yEoHXMrwsLEyyi8cr7U4y6Dx1ZjNJaYFCAiIiKiGq2wsBAxMTG4cuWKRbsgCBg9ejQ6dpTvDh0R2cigg6jXQ3BxlTuSctHs3VTqMcG7Lpyf6g/otNUY0f8wKUBERERENZZer8emTZuQmJho0a5QKPDCCy+gbdu2MkVGRI9DNBiK6gkoHO8S1pSbBd3xPaUedxkQDkGpKtpuUQaOd0aJiOj/s3ffcVJV9//4X+feqdth6R0BRQQEAamCAoIoYkVULIkmMYl+1RTzSfl+Uj7J7xvziSWfT3qiMTbsFUVEURQQBAQURKXXZYGt08u95/z+uDPLDruzLMzslN3X8/FYZ/aec+e+t+DOed9z3oeIiFohFArhmWeewf79+xOO22w2XH/99Rg0aFCWIiOiU6XCIShNz8t6AqHlrwDRSPONug2umddkNqATpD0pYBgGqqur4Xa7UVJSku6XJyIiIiI6qUAggKeeegqHDx9OOO50OnHjjTeiX79+WYqMiE6VkjJWTyD/7mkraSK07Pmk7Y7x06F37galVAajSpTSd/XAgQP44IMPsHLlSnz00Uc4ePAgPB5PQ7vdbkeXLl0wYsQIXHDBBbjgggswceJE2PLwh0lERERE+cHr9eLJJ5/EsWPHEo673W7cdNNN6NWrV5YiI6LTEg1b2xG6C7MdySmLbPgQsqoyabs7iwUG4055dB4Oh/H000/j0UcfTdjftbnMRiQSQUVFBQ4fPoxly5YBADp16oQFCxbgO9/5DoYPH55C6EREREREierq6vDkk0+ipqYm4XhRURFuvvlmdOvWLUuREdHpUtEoICWEpmc7lFMWejv5NoT6gLNgO2tU5oJJotVJgUAggD/+8Y948MEHUV1dnZAEKCsrw+jRo9GtWzd07twZnTp1QjAYRE1NDWpra7F9+3Z89dVXUEqhpqYGf/vb3/C3v/0Ns2bNwq9+9Sucf/75bfLFEREREVHHUV1djSeeeCJh5ioAlJSU4JZbbkF5eXmWIiOiVKhQENDzLyFgHNyF6JZ1SdvdlyyAENmvktCqpMDjjz+On/70p6isrIRSCna7HZdccgmuueYaTJgwAWeeeeZJX8Pr9WLDhg1Yvnw5nnnmGezZswdvv/02li1bhmuvvRYPPvgg+vTpk/IXREREREQdz5EjR/Dkk0/C7/cnHO/cuTNuueUWlJaWZikyIkqFMk2ocADCZs92KKcstDR5LQFRVArnlDkZjCY5oVpR0UDTNADA0KFDce+992L+/Pno1KlTShdeu3YtHnnkETz55JMwDAO/+MUv8POf/zyl10wHj8eD0tJS1NfXs1AiERERUR6oqKjAU089hWAwmHC8W7duuPnmm1FUVJSlyIgoVSoUgFF5EKKgCCI2Ls0HMuBFzR2zgXCw2Xb3vFtReNO9DZ8rpaD8XtgHnPyGe7q16rs6fPhwPPPMM/j888/xrW99K+WEAABMmDABjzzyCHbu3Ik77rgDLpcr5dckIiIioo5l3759ePzxx5skBHr16oVbb72VCQGiPKeiEUDJvEoIAEB4xeKkCQEIAdes6zIbUAtatXzgs88+a7MA+vbti7/85S9t9vpERERE1D7t3LkTzz33HAzDSDjer18/3HjjjXA6nVmKjIjSRYWDgJ5fu9cpKRF6u4VtCMdMhd4td3ZBya/vLhERERERgC+//BIvvvgiTNNMOD5o0CBcd911cDgcWYqMiNJFmQZUKARhz69/z9HP1sI8vC9puysHtiFsjEkBIiIiIsorn332GV599dUmW2IPHToU11xzDWw2vsUlahciESgjAuHMr1pvwaXPJW3Tew+EfcT4DEZzcm3+f8xwOIxVq1ahqqoKAwcO5PaDRERERHTa1q9fjyVLljQ5PmLECFxxxRXQ83DbMiJqnoqGASAntu1rLfPIQUQ3rUza7pqdG9sQNpZSUmDfvn3485//DAD46U9/irKysoT2tWvX4tprr8Xhw4cbjp133nl46aWX0K9fv1QuTUREREQdiFIK7733HlatWtWk7bzzzsNll13WsGMWEbUPMujPu3oCobefB5Js8CfchXBOm5vhiE4upf9zvvLKK3jggQfw3nvvNUkIeL1eXHnllTh8+LC1vULs45NPPsFll13WpCAMEREREVFzTNPEa6+91mxCYMKECZg7dy4TAkTtjDKiUNFIXtUTUKEgQu+/mrTdOW0uNHdh5gJqpZT+7/nOO+9ACIErr7yySds//vEPHD16FABw991347XXXsN3v/tdAMC2bdvw+OOPp3JpIiIiIuoAwuEwnnnmGXz66adN2qZNm4ZZs2bl3FRcIkqdikaAaDSvZgqEV70F5fcmbXfNXpDBaFovpe/w7t27AQBjxoxp0vb8889DCIGrrroKf/jDHwAAl19+OY4dO4YXXngBL774Im6//fZULk9ERERE7ZjP58OiRYsSlqIC1vriuXPn4rzzzstSZETU1lQ4BIj8qSeglEJw6bNJ2+0jJ8DWe2AGI2q9lGYKxGcCdO/ePeG4x+PBxo0bAQBf//rXE9quv97afqG5bC8REREREQBUV1fj0UcfbZIQsNlsuP7665kQIGrHlFJQwQCEzZ7tUFrN+GIjzP07krbn2jaEjaU0U8DrtaZGnLg/7OrVq2GaJmw2Gy688MKEtr59+wIAampqUrk0EREREbVTBw8exKJFixAMBhOOFxQU4IYbbkCfPn2yFBkRZYQRtbYizKN6Ai1tQ6h17QXHeVMyGM2pSSkpUFpaipqaGlRUVCQcX7FiBQDg3HPPRWFh84UUXC5XKpcmIiIionboq6++wosvvtikKHWnTp2wcOFClJeXZykyIsoUFY1AmAZEDhbla45ZfQSRde8lbXfNXgCh5e52qSktHxg+fDgAaxeCONM0G+oJXHTRRU3OOXToEICmSw6IiIiIqGPbsGEDnnvuuSYJgZ49e+K2225jQoCog1CREJrf1C83hd55EZBm840OF1zTr8hsQKcopZkCV111FT744AM8+eST6N69Oy644AI8+eST2LdvH4QQuO6665qcs2HDBgBAv379Urk0EREREbUTSimsWLECH374YZO2wYMHY/78+XA48mcaMRGdPiVlrJ5AfvybV9EIQstfTtrunDIHWlFpBiM6dSnNFLjjjjtw9tlnQymFBx54AFdccQVefPFFANZOA2PHjm1yziuvvAIhRJNaA6fq3//+N4QQJ/149913U7oOEREREbUd0zTx+uuvN5sQGDVqFK6//nomBIg6EBX0Q4UCgMOZ7VBaJbzmHaj65PXy3Jfk5jaEjaU0U8DpdGL58uW46667sHjxYkSjUTgcDixYsAB/+tOfmvT/8MMPsW3bNgghcPHFF6dy6QaapqFr164txkhEREREuScSieCFF17Azp07m7RNnToVF154Yd5sR0ZEqVOmCempA2x2CC2l+9cZE2phG0Lb2aNhG3BWBqM5PSklBQCgR48eePHFFxEOh1FTU4Py8vKk2dy+ffvi/fffBwCMGzcu1Us3vObevXvT8lpERERElBl+vx+LFi1qUrBaCIFLL7202RmnRNS+qaAfCPkhCkuyHUqrRHduhbFza9J29+zc3YawsZSTAnFOpxM9e/Zssc/AgQMxcODAdF2SiIiIiPJQTU0NnnrqKdTW1iYct9lsuPbaa3HWWbl/Z42I0kuZJqS3DrA72sUsAa1TVzjOb1p4PxelLSlARERERHQyhw4dwqJFixAIBBKOu91u3HDDDejbt2+WIiOibFJBHxAKADlelC9O1tcg/NGypO2ui6+FsNkzGNHpS1tSwOPx4MUXX8SaNWtQWVmJQCCAf/3rX+jfv39Dn4qKCtTV1cHlcuGMM85I16WJiIiIKA9s374dL774IqLRaMLxsrIyLFy4EF26dMlSZESUTco0ID211iyBPKkjElr+MmBEm2/UbXDNvCazAaUgLUmBP//5z/jZz34Gr9cLwNpWRggBv9+f0O+DDz7AwoUL4XK5cPDgQXTu3Dnlax87dgxjxozBV199BdM00bNnT0yaNAnf+MY3Ut7hgIiIiIjSY+PGjXjjjTegVOLu4z169MDChQtRVFSUpciIKNtUwAeEQ3kzS0CZBkLLXkja7pw4C1pZeQYjSk3KizV++ctf4u6774bH44HD4cCYMWOS9l2wYAF69uyJcDiMl156KdVLAwACgQA2btwIh8MBKSX27NmDp59+GhdddBFuu+02GIbR4vnhcBgejyfhg4iIiIjSQymFFStWYPHixU0SAoMGDcLXvvY1JgSIOjBlGrFaAs68mSUQWb8CsuZo0nbXnPwoMBiXUlJg06ZN+PWvfw0AuOmmm1BZWYl169Ylv5imYf78+VBK4Z133knl0ujVqxd+8Ytf4NNPP0UoFEJNTQ0CgQBWr16NmTNnAgAee+wxfO9732vxdX7729+itLS04YPr2IiIiIjSQ0qJxYsX44MPPmjSdu655+KGG27g9tFEHVzDLAGnK9uhtFqwpW0IBw2DbfDwDEaTOqFOTNmegttuuw3//ve/MWnSJKxatarhuKZpEEJgy5YtGDZsWMI5zz33HG644QacddZZ+OKLL04/8hZIKXH11Vfjtddeg6Zp+PLLLzFkyJBm+4bDYYTD4YbPPR4P+vbti/r6epSU5MdWGERERES5JhKJ4MUXX8SOHTuatE2ZMgXTp0/Pm7uCRNQ2lBGFeeQgAEA43VmOpnWM/TtQ98PrkrYX3flfcE27/JRfVykF5ffCPuDMVMI7LSnNFPjggw8ghMBdd93V6nMGDBgAwKo821Y0TcMDDzwA4HiGOhmn04mSkpKEDyIiIiI6fX6/H0888USzCYFLL70UM2bMYEKAiCD9XqhIGHDkzyyB0NLnkraJ4jI4J87KYDTpkVKhwcOHDwPAKe0lG58i1vjufFsYPHgwunTpgqqqKuzevbtNr0VERERElpqaGjz99NOoqalJOG6z2XD11Vfj7LPPzlJkRJRLlBGF8tZDOF15kySUPg9CK99M2u6acTWEI/+WRKWUFHA4HAiHw022lWlJPJFQVlaWyqWJiIiIKMdUVFRg0aJFTXagcrlcuOGGG9CvX78sRUZEuUb6PFDRMLTismyH0mrhFa9Z9Q+aIzS4Zs3PbEBpktLygT59+gAAPv/881afs2zZMgDWnfy2tGvXLlRVVQEABg4c2KbXIiIiIuroduzYgX//+99NEgKlpaW47bbbmBAgogYqGoH0WbME8oWSEsG3n0/a7hh3IfQuPTIYUfqklBSYPn06lFJ47LHHWtV/9+7dePTRRyGEwMUXX3za1z1ZbUSlFO677z4AVn2BuXPnnva1iIiIiKhlmzZtwjPPPNNk9mj37t1x++23o2vXrlmKjIhykfR7gGgEIo9qCUQ3r4aMFUVsjmvODRmMJr1SSgrcddddsNlsWL16NX75y1+22HfDhg2YNWsWfD4fnE4n7rjjjtO+7r59+3D++efj73//O3bv3t2QJJBSYu3atZgzZw5eeeUVAMAdd9xxSjUPiIiIiKh1lFL48MMP8frrrze5aTNw4EB8/etfR3FxcZaiI6JcpCJhSG993uw2ENfSNoR638GwDxuTwWjSK6WaAmeeeSb+8z//E7/4xS/w61//Gm+99RauueaahvalS5di8eLFWLZsGVasWAEAEELg/vvvR8+ePVMKfP369Vi/fj0Aq3hhcXExvF5vQgHDr3/96/jf//3flK5DRERERE1JKbFkyRJ88sknTdpGjBiBK664ArquZyEyIspl0u8FTAPCXZjtUFrNrNiH6OaPkra7LlmQN8USmyPUyebit8LPf/5z/L//9/8gpUz6zVBKQQiBn//85/jFL36R0vWCwSAeffRRrFmzBps3b8axY8dQW1sLl8uFPn36YNKkSbjtttswefLkU35tj8eD0tJS1NfXc3tCIiIiomZEo1G89NJL+Oqrr5q0TZ48mVsOElGzVCQE48ghCJsdwu7Idjit5vv37xFasqjZNlFQhM5/exvCVZDSNZRSUH4v7APOTOl1TkdakgKAtTzg/vvvx9KlSxEIBBLaHA4HZsyYgZ/97GeYNGlSOi7XZpgUICIiIkrONE0sWrSo2S2fL7nkEowfPz4LURFRPjBrjkHWV+fVjgMqFEDNHbOhgr5m212XLUTRrT9M/TpZTAqktHygsbFjx+LFF1+EYRjYtm0bjh49CtM0UV5ejnPOOQdud36tGSEiIiKiREopvPrqq00SArqu4+qrr8awYcOyFBkR5ToVCVk7DuTRsgEACH34RtKEAISAe/Z1mQ2oDaQtKdDwgjYbRo4cme6XJSIiIqIsUkrh7bffxtatWxOOu1wuXH/99ejfv3+WIiOifCC9HkCaEDZ7tkNpNaUUQkufS9puHzUZeo/832417UkBIiIiImp/Vq9ejY8//jjhmN1ux0033YTevXtnKSoiygcqHLRmCaS47j7Top+vh3mw6VKpOPclCzIYTdtJW1JASokVK1ZgzZo1qKysRCAQwG9+85uEXQYikQgMw4Cu63A6nem6NBERERG1oU2bNmH58uUJxzRNw4IFC5gQIKKTkl4PoFRezRIA0OIsAa1HX9jPze16ea2VlqTAm2++ibvvvht79+5NOP6DH/wgISnw6KOP4q677kJRUREqKipQWJhf60mIiIiIOprt27dj8eLFTY5feeWVGDRoUBYiIqJ8okIBSL8HwpVfNebMYxWIrF+RtN09ewGEpmUuoDaU8lfxyCOPYN68edizZw+UUigvL0eyDQ1uv/12lJWVwefz4ZVXXkn10kRERETUhg4cOIAXXnihyXu72bNnY8SIEVmKiojyhVIK0penswTeeRFQsvlGpxvOC+dlNqA2lFJSYOfOnbjzzjsBANOnT2/YdSAZh8OBa665BkopLFu2LJVLExEREVEbOnbsGBYtWgTDMBKOT548GRMmTMhSVESUV0JBa5aAO79qCahICKHlyW9iu6ZeBq2wOIMRta2UkgJ/+MMfEI1Gcc4552DJkiUYOnToSc+54IILAACbN29O5dJERERE1Ebq6+vx1FNPIRQKJRw/99xzMWPGjCxFRUT5RCkF6a8HFCD0/KpvH/5oGZS3Lmm765LrMxdMBqSUFFi+fDmEELj33nvhcDhadU587dn+/ftTuTQRERERtYFgMIinnnoKHo8n4fiQIUNw+eWXQwiRpciIKK+EgpA+b/7NElAKwbeeTdpuP2ccbH3bVz2VlJICBw4cAACMGjWq1efEiwsGAoFULk1EREREaRaNRrFo0SJUVVUlHO/Tpw/mz58PXdezFBkR5ROlFExfHSBE3s0SMHZ8BnPPF0nbXe1kG8LGUkoKxDPFyQoLNufYsWMAgJKSklQuTURERERpZJomXnjhBRw8eDDheJcuXXDDDTfAbs+vImFElD0qFIDy+/JulgBwkm0Iy3vAMXZaBqPJjJSSAr169QJgbVXTWh988AEAYMCAAalcmoiIiIjSRCmFN954Azt27Eg4XlJSgptuugkFBfn3xp6IskMpBemtAzQBoeXX7CJZV4XwmneStrtmXZt3Mx9aI6WkwNSpU6GUwqJFi1rVv6qqCn//+98hhMD06dNTuTQRERERpcny5cubFIF2uVxYuHAhSktLsxMUEeUlFfRDBfwQrvxLJobefQkwjeYb7Q64ZlyV2YAyJKWkwLe+9S0AwJIlS/DYY4+12PfgwYO49NJLUVVVBV3XG84lIiIiouxZu3YtVq9enXDMZrPhxhtvRLdu3bIUFRHlIyUlpKc2L2cJKCOK0DsvJm13TpoNraRzBiPKnJSSAuPGjcO3v/1tKKXwjW98A/Pnz8fzzz/f0P7ZZ5/hueeew+23346zzjoLn3zyCYQQ+MEPfoDBgwenHDwRERERnb4tW7bg7bffTjgmhMC1116Lvn37ZikqIspXKuiHCgYgXIXZDuWURda9B1lblbTdPad9bUPYmFCnUiWwGaZp4rbbbsOTTz7Z4hY18ct87Wtfw6OPPpqz29l4PB6Ulpaivr6exRCJiIio3dq1axcWLVoEKWXC8Xnz5mH06NFZioqI8pWSEuaRQ1DRMLSComyHc8rq/vPrML7a3GybbcgIlP1/T7TZtaVSCBpAyOdFtyFnttl1kklppgAA6LqOxx9/HC+88AJGjx4NpVSzH8OGDcOiRYvwr3/9K2cTAkREREQdwaFDh/Dcc881SQjMmDGDCQEiOi0q6IcK5WctAWPPl0kTAgDgmnND2q8plULAUKgKKezzA/sCwJFwdsbJaSudeM011+Caa65BRUUFNmzYgKNHj8I0TZSXl2P06NEYNGhQui5FRERERKepuroaixYtQjQaTTg+fvx4TJ48OUtREVE+U6YJ6akDbHYILeX7zhkXXPps0jZRWg7nhJlpuY5UCiETCJqA17AepQKcGlCoA760XOXUpZQU+K//+i8A1h+R2bNnA7C2KZw3b17qkRERERFRWnm9Xjz11FMIBAIJx4cPH47Zs2dzNicRnRYV9AMhP0Rh/i2/lr56hFctTdruuvgaCJv9tF9fKYWQBALG8USAAuAQQJEN0GP/2z1h4lZGpZQU+OUvfwkhBF555ZV0xUNEREREbSAUCuHpp59GXV1dwvEzzjgDV155JRMCRHRalGlCeusAuyMvZwmEV78NRMPNN+o2uGZec8qv2dpEQK5IKSlQXl6Ompoa9OvXL13xEBEREVGaGYaBZ599FkeOHEk43rNnT1x33XXQ9fzaOoyIcocK+oBQACgqzXYopyX8weKkbY7x06F3bt3WrPFEQNAEPNHjiQB7jiYCGksplRPfVrCysjItwRARERFRekkp8fLLL2Pfvn0Jxzt37oyFCxfC6XRmKTIiynfKNCA9tdYsgTycbWQc2gNj59ak7a6Z17Z4vlIKQVOhNqKwLwDs9QOHg0BUWomAMjtQmOMJASDFpMCCBQuglMLzzz+frniIiIiIKE2UUliyZAm++OKLhONFRUW46aabUFiYf3uJE1HuUAEfEA4BTne2Qzkt4Q/eSNqmde0J+7AxTY4rpRBqlAjY5wcqGiUCOjnyIxHQWEpJge9+97s499xz8cQTT+Dxxx9PV0xERERElAYffPABPvnkk4RjTqcTCxcuRKdOnbIUFRG1B8dnCTjzcpaAkibCK99M2u684LKGGgknJgL2NkoEFOj5mQhoLKWaApWVlXjkkUdw++2347bbbsPTTz+NG2+8ESNHjkSnTp1Ouj6NtQiIiIiI2saGDRvwwQcfJBzTdR3XX389evTokaWoiKi9UAEfEAnnbS2B6Nb1kNVHkrY7p85FyFQJNQJMBdg1KxFgy7+aikmllBQYMGBAQ1ZIKYXly5dj+fLlrTpXCAHDMFK5PBERERE1Y9u2bXjzzaZ3wK6++moMGDAg8wERUbuijKg1S8CRn7MEgJaXDmDIuago64eAv/0mAhpLKSkAWMmA5p4TERERUebt3bsXL7/8cpPjl112GYYNG5aFiIiovZF+L1QkDJGnswRk0I/wuuQ3sz0T5sIw23cioLGUkgKPPfZYuuIgIiIiohRVVlbi2WefhWmaCcenTZuGsWPHZikqImpPVDQC5a2HcLrydpZAZO27VoHEZiibA66Js9Jw+zx/pPSl3nrrremKg4iIiIhSUFtbi6effhrhcDjh+JgxYzBt2rQsRUVE7Y30e6GiYWjFZdkO5bSFPlictE2OuRAoLM5cMDmgA0yGICIiImrf/H4/nnrqKfh8voTjZ599Ni699NK8vZtHRLlFRSOQPmuWQL4KHD4IY9snSdvl5MszGE1uYFKAiIiIKI+Fw2EsWrQINTU1Ccf79++Pq6++GprGt3tElB7S7wGiEQhH/iUFQqbCkZBC1XvJtyFUpV2gho/PYFS5oQOtlCAiIiJqX0zTxPPPP4+KioqE4927d8f1118Pm41v9YgoPVQkDOmth3C6sx3KKQmZCvVRoC4CmFKhy5rkuw7ISXMAveP9fzOlr/i222475XOEEHC5XCgtLcWQIUMwYcIEnH322amEQURERNThKKXw6quvYvfu3QnHy8rKsHDhQrhc+Xcnj4hyl/R7AdOAcBdmO5RWSUgGKMCtA649m6EdPZj0HDml4y0dAFJMCvz73/9Oyxq1sWPH4qGHHsLkyZNTfi0iIiKi9s7j8eCNN97Ajh07Eo4XFBTgpptuQnFxxyqSRURtS0VCsVoCuT9LoLlkgFO32rRVLcwS6D8Uqs/gDEWZW1JKCvTr1w9CCAQCARw7dqzhuNPpRKdOnQBYlXDjVXCFEOjSpQtcLhc8Hg/q6+sBAOvXr8e0adPw+OOPY+HChamERERERNRuKaWwadMmLFu2rMkuA3a7HTfeeCPKy8uzFB0RtVfS5wWMaE7PEmgpGQAAiISgrXsn6flyyty2DzJHpVR5Zu/evXjllVdQXFwMh8OB733ve9i0aRP8fj8qKipQUVEBv9+PTZs24d5774XdbkdRURFeeeUV1NbW4sCBA/jd736H4uJiSCnxjW98AwcOHEjX10ZERETUbtTW1uLJJ5/E4sWLmyQENE3DggUL0Lt37yxFR0TtVcMsgRxNCMQLCO7zA9VhwKEBZY4TEgIAtE9WQAR9zb6G0m2QE+ZkINrcJJRS6nRPPnLkCEaPHg2Px4N33nkHEydObLH/mjVrMHPmTBQXF2PTpk3o2bMnAGDTpk2YMmUKQqEQfvjDH+J3v/vd6YaUMo/Hg9LSUtTX16OkpCRrcRAREREB1uyAdevWYfny5YhGo03aCwsLccUVV2DIkCFZiI6I2juz+iiktxZaUWm2Q0lw0pkBJ7A9cCe0LWuabZOjp8G49+E2irR1pATqvT6MHJ75/5enNFPgwQcfRGVlJb7//e+fNCEAABMnTsT3v/99HD16FL///e8bjo8ePRq33XYblFJ4553kUzqIiIiIOpKqqio89thjWLp0abMJgXPPPRd33nknEwJE1CZUOGjNEnAVZDuUBq2dGZCg9hjE1o+TNpsdeOkAkGJS4LXXXoMQArNnz271OZdccgkA4M03E/eHnDPHmq6xd+/eVEIiIiIiyntSSqxatQp/+9vfml1aWVJSghtvvBFXXnkl3O7cL/xFRPlJej2AUhA2e7ZDOb1kQIz20ZsQSjbbpgpLoc69IM3R5peUCg0ePGht5+B0Olt9Trxv/Ny4Xr16AQACgUAqIRERERHltSNHjuC1117D4cOHm20fM2YMLr744lN6/0VEdKpUKADp90C4spt4PNVlAk0o1fKuAxNmA3ZH6oHmsZSSAgUFBQiFQtiwYQPGjh3bqnPWr1/fcG5j8YI58V0LiIiIiDoSwzCwcuVKrFq1ClI2vaPVqVMnzJs3DwMGDMh8cETUoSilIH3ZnSWQcjIgRuz9AlrF7qTtcsrlKUTZPqSUFBgzZgyWLVuG3/72t5g/f/5Jt8CpqqrC/fffDyFEkyTCV199BQDo1q1bKiERERER5Z1Dhw7htddeS9jiOU4IgfHjx2P69Omw27M/hZeIMkMphYgE4mXhVULbCX0btZ5YRb5x35baGrdLXz2MGmvHARFRzfZJHnfT1218brLzVaNHqQBvNLVkQJy2OvksAdVrINTAYaf/4u1ESkmB7373u1i2bBkOHjyICRMm4A9/+AMuvfRSCCES+iml8Oabb+J73/seDhw4ACEE7rzzzoQ+S5cubTZZQERERNReRaNRvP/++1i7di2a2xCqS5cuuOKKK9CnT58sREdEmSSVQsQEIlIhaCj4owpRpSCbSQoATQf7As1TUBBJWpUCThi6QYWDMGtqIHQnRCSF0XiygE7SHD/u1FJLBgAAjCi0NUuTNptTLm/6DeiAUkoKzJs3D9/61rfwj3/8A7t378a8efNQXl6OUaNGNdzxP3r0KDZv3ozq6uqG8+644w7MnXu8wmNlZSVeffVVKKUaCg4SERERtWf79u3D66+/jpqamiZtmqZh8uTJmDp1Kmy2lN6uEVGOOjEJ4IsqRKWCoaxq8E5dwK0LaLEx64lD1xNvxKaDikZhBuug7AqaO//rlohPV0H46pptU0KDnHhpZgPKUSn/lfnb3/6G/v3749e//jVCoRCqqqqwfPnyhD7xzLfT6cQvfvEL/PjHP05oLykpwRdffAEA6N27d6ohEREREeWscDiMd999Fxs2bGi2vUePHrjiiivQo0ePDEdGRG2pNUmAApuATcvOnWslJaS3FioSgigozkoM6aa3UGBQnXM+0JlL1wFAqObmqp2GyspKPP7441i+fDm2bt2K2tpaAFZRnHPOOQczZszArbfeip49e6bjcm3G4/GgtLQU9fX1KCkpyXY4RERE1I7s3LkTb7zxBurr65u06bqOadOmYdKkSdD1VOfMElG2xZMAYVMhZCYmAXQBODQBhwboWUoCnMj01ELVVQMFRRBaSjvX5wZvLez3zIYwjWabjW//f5ATc2eWupRAvdeHkcOHZPzaaUsKtBdMChAREVG6BYNBLFu2DJs3b262vU+fPpg3bx66du2a2cCIKG0aJwGChoLfyO0kQGMy6IdZfQTC7oRoJwVNtXeehe2p/262TbkKEf3fZYAzu9stNpbNpAAXqRERERG1oS+//BJvvvkmfD5fkza73Y7p06fj/PPPh9Ye7swRdSDNJQEiUsFslAQotImcTAI0pqIRyPpqQNPbTUIAALRVi5O2yfNn5lRCINuYFCAiIiJqA36/H2+99RY+//zzZtsHDBiAefPmoVOnThmOjIhOh1QKYROImAoBQyJgWPUBpAK0WBKgKA+SAI0p04RZXwMVNaAVFmU7nLQRB3dB2/tF0nY5eW7Sto4obUmB999/H4899hjWrFmDyspKBINBfPbZZxg27Pi+jytXrsSWLVtQUlKCm266KV2XJiIiIsoZSils3boVb731FoLBYJN2h8OBWbNm4bzzzmuT6uFElDqlFAwJRCUQlbEkQBSIKAVTArqWn0mAxpRSkN46KL8PorB9FBaM01YnnyWguvaGOnN0BqPJfSknBQKBAG699Va8/PLLAI7vNNDcHzld13HXXXdBCIHx48djyJDMr5cgIiIiaisejwdvvvkmtm/f3mz7kCFDMHfuXNYtIsohSqmGwX9UWssBArF6AFEJKNUoCaDnbxLgRCrgg/TWQ7gLINrJ1wQAMA1oHy1J2iwnXwZwuVaClJMCCxYswJIlS6CUwvnnn4+pU6figQceaLbvpEmTMGLECGzduhUvvfRSk60JiYiIiPKRUgqbNm3CsmXLEA6Hm7S73W5ccsklGDFiBGcHEGXRiQmAkGElAIzYccBaCmAXIlYToPmbnflORUIwPTUQdhuErX2tKBeffwxRV5W03eTSgSZS+g145ZVX8Oabb0IIgX/84x/4xje+AQBJkwIAcPXVV2PLli344IMPmBQgIiKivFdbW4s33ngDu3fvbrZ92LBhmDNnDoqK2s96XaJ8IJskAKw6AEZsaYACYBOAXRNw6u03AXAiZRowa2sAU0IUFGY7nLTTVr2RtE2eORro1ieD0eSHlJICjz/+OADgpptuakgInMyYMWMAAF98kbzwAxEREVE+2LZtG1599VVEo9EmbYWFhbjssstw9tlnZyEyoo7lxARAICoRMo8nAABrRwC7JuDSBWwdJAFwIqUUZH0tVDgAUdgOlzEFvNA2rkjaLKdcnrlY8khKSYH169dDCIEFCxa0+pyePXsCAI4dO5bKpYmIiIiyatOmTVi8eHFDPaXGzj33XMyePRtuN7e8ovSQyprmHoger3avawKaAARiHwKNPhcQsecNx0Tjfvk7IDZlYgIgaEiEDCDaKAFg1wCbJuDWBWz2/P1a00166yF99RDuQuTxr0BS2rp3IKJNl3ABgHK4rK0IqYmUkgLV1dUAgN69e5/yuVLKVC5NRERElDUff/wxli5d2uR4SUkJ5s6dy2LKlDYhQ8EflaiPKIRMKwGlCUAqa/p7YwrWoD+uSVIg/iGEdVwDNFgfugbowkoyaMJKKGhITCScyhiyaaqsmT6t6NS4SzRWADBiWgmA2LcDNmElAAp0AVt7KpiXZjIUgPTUQjhdELqe7XDaRItLB8ZcBLi5jKs5KSUFiouLUVNTA4/H0+pzdu3aBQAoLy9P5dJEREREGaeUwsqVK/H+++83aRs1ahQuueQSOJ3OLERG7YkhrcGvJyLhN6y74S5NoMQhTukOv1KqIXmgYA3CZexRATBMQKFxH9XQphQS7iQ3+Tz22FI08UH/yUJWsVcTSV6tcbIjPgOgULSfXQAyQUWjkPXVgBAQdke2w2kbR/ZD27E5abNkgcGkUkoKDBkyBB9//DHWrVuHCy64oFXnvPTSSwCsaXVERERE+UIpheXLl2P16tVN2qZMmYLp06d3yDXKlB5KKQQNxGYFSISltQbebRMoPs3p70II6Cc9lb+z7Z2SEtJbCxUOQytqh3UEYvTVbyZtU526QZ1zfgajyS8pbdB46aWXQimFv/zlLwiFQiftv3TpUrz00ksQQmDuXGZqiIiIKD8opbBkyZJmEwLTp0/HjBkzmBCg0xIxFerCEvt8Jvb6DBwNSQghUOYQKHFosPNuOKVI+uqhvB6IgnY8dV5KaC0kBeSkSwGtfS6ZSIeUkgJ33XUXysrKsHfvXlx99dUNNQZOFAqF8OCDD+Lqq6+GlBI9evTA17/+9VQuTURERJQRUkq89tpr2LBhQ5O2OXPmtHq2JFGcVAq+qMRhv4G9XgMH/SYipkKxTaCTU4PbJphkorSQAR9kfS3gLoDQUhr65TSxfRNEVUXSdnMKb0i3JKXlA2VlZXjqqadwxRVX4O2330a/fv0wbdq0hvZf//rXqKurw+rVq+H3+6GUgt1ux9NPPw2Xy5Vy8ERERERtyTAMvPzyy022UhZCYN68eRg1alR2AqO8o5RC2LSWB9TFigYKWMsDilgdn9qAioYh62sgbDqELaVhX87TVi1O2iYHngP0OiOD0eQfoZrbR+cUvfPOO7j55ptx9OhR60VPyGzGL9GlSxc888wzmDFjRqqXbDMejwelpaWor69HSUn7XXNDRERELYtGo3j++eexc+fOhOOapuGaa67BsGHDshRZxySVgikBUwFmrPK8Hqs6b4ttz5eL4kUD68NW0UBDWUUDXbb83haQcpsyDZg1x6BCQWiF7XjZAACEg7DffTFEKNBss3HTjyAvvj7DQZ06KYF6rw8jh2d+95q0pIwuvvhi7N69G4899ljD9Lq6ujoAQEFBAUaPHo158+bh29/+NoqLi9NxSSIiIqI2Ew6H8cwzz2Dfvn0Jx202G6677jpuOZhmzQ34TQUYpkJEKkQVYJqACatNNrqlpYvYlnS6gFMDnLoGmwbYhLAetcwPvuNFA31RCU9EIiQVbELAbROsEUBtTikF6a2HCvohCtr/2Evb8F7ShIDSbZATL8lwRPknbfNICgoKcOedd+LOO+8EYE23M02T2/IQERFRXgkEAnj66adRUZG4PtXhcOCGG27AgAEDshNYnpKxbfFMhdjA3xrYG9Ia8Edk4oA/vve8iH3oAtCFgKYBzlg1/caDfFNad98NEwgZCqYyG7aws2mADQI2HXDpAg5dNOxpbz02neGaiohpzQqoi0gEDGt7P5cu0MnBGgGUOSrghfTUQbgKIDpAEkpb/UbSNjXqAqCoLHPB5Kk2W1xis9lga+drV4iIiKh98Xq9eOqppxqWRMa5XC4sXLgQffr0yVJkuUk1uqt/4oA/GhvwGzI2E6DRgB9IHPALAThiA/5TXQagawI6AOs/x8+Nx2ao44N1qQAFBU3ElhyI+OwCAbsuEmYY6KJ1CQOprNf2RiS8UYWICTh0oNgmcnZJA7VfKhyEWV8L4bC3+zoCAIDqSoht65I2m1Muz2Aw+asD/KYQERERnVxdXR2efPJJ1NTUJBwvLCzEzTffjO7du2cpstxjVc9XqAlLRM3jA34Vu0d/fMBv3dW3awKuDK/7F7GBvw2xYE6I30peAAFTwRO1IlcK0DU0JAxcNsCpCWtmgXZ8hoEmwKKBlHOUEYVZVwtICeEqzHY4GaF9tAQiSYk8VVwGNXJyhiPKT0wKEBERUYdXXV2NJ554Ah6PJ+F4SUkJbrnlFpSXl2cpstwilYI/lgzwRhQcOuCIDfg1AQiRH1ueaUJAE4BdAxrPLgCOL0eQCvBGFGobDTji9Qs0IRCRx4sGljoEiwZSVikpIT21UOEARGEHKZauFPQWlg7ICXMAmz2DAeWvViUFzjgj/Vs4CCGwa9eutL8uERER0ak4cuQInnzySfj9/oTjnTp1wi233IKysrLsBJZDlFLwGwq1IQlPVMEmgDJn+xwINyxHAHBiwsCIJwwkWDSQcor0eaB8HoiCIrTDf5bNEru3Qhzem7RdTpmbuWDyXKuSAnv37m3Vi8XXXZ24y2Fzx1lshYiIiLLt0KFDeOqppxAKhRKOd+3aFTfffHOH3zVJxdbL14YlPBEFTQAl9o67Vt6midhyhGxHQnScDAUgPbUQTheElh+zddJBW9XCLIE+g6H6D81gNPmtVUmBW2+9tcX2zZs349NPP4VSCmVlZRg9ejS6d+8OpRSOHj2KzZs3o7a2FkIInHvuuTj33HPTEjwRERHR6dq7dy+eeeYZRCKRhOO9evXCwoULUVBQkKXIckMgqlAbNlEftdbLF3fgZABRrlLRCGR9NaBpEHZHtsPJnGgE2sdvJ22Wk+eiw0yZSINWJQUee+yxFtsWLVqEPn364MEHH8RVV13VZNcB0zTx8ssv47777sO2bdtw11134bbbbkstciIiIqLTtGPHDjz//PMwDCPheL9+/XDjjTd26C2Vg4ZCXdhEXcTaUq/IbhXaI6LcokwTZn0NVCQCrbBjzWoSmz+E8HuabVNCg5w0J8MR5beUCg1u2LABd9xxB7p27Yq1a9eiV69ezfbTdR3z58/HlClTMGbMGHznO9/ByJEjMXbs2FQuT0RERHTKtm3bhpdeeglSyoTjgwYNwoIFC2C3d8zCVCFDoT4iUReRMCVQaOeaeaJcpZSC9NcDAR9EQcdKCACAvmpx0jY1YiJQ1jWD0eS/lBadPPzwwzBNEz/96U+TJgQa69mzJ376058iGo3ioYceSuXSRERERKds8+bNePHFF5skBM4++2xcf/31HTIhEDYVjgZM7PcZOBaUcGoCZU6NCQGiHKYCPsj6WsBVANHR/q3WV0N89lHSZhYYPHUpzRRYuXIlAGD8+PGtPmfChAkAgFWrVqVyaSIiIqJTsm7dOrz11ltNjo8cORJXXHEFtA5UoAsAIqaCJyJRG5YIS6DQJlBk72CDC6I8pCIhmJ4aCJsdwtbxdpjX1rwFIc1m21RBEeToaRmOKP+l9Ft07NgxAEA4HG71OfG+8XOJiIiI2tqqVauwfPnyJsfHjh2LSy+9tEPtihRtlAwImUCBXaAzkwFEeUGZBsy6GsAwIQqLsh1OVmir30zaJsddDDhcGYymfUgpJd61q7VWo7msezJLliwBAHTp0iWVSxMRERGdlFIKy5cvbzYhMGnSpA6VEDCktbXgfq+JwwEJIQQ6uzS49I7x9RPlO6UUpKcOKhSAKOiYCQGxfzu0/V8lbZdTLs9gNO1HSkmBiy66CEopPPTQQ1i9evVJ+3/00Ud4+OGHIYTAjBkzUrk0ERERJWFIBaVUtsPIOqUUli5d2uySxYsuuggzZ87sEAkBUyrUhSX2eU0c8puAADo5Bdy29v+1E7Unyu+F9NZBuAs77G572uo3krap7n2hhpybwWjaj5SSAj/+8Y/hcDgQDocxY8YM3Hvvvdi8eXNC8R6lFDZv3ozvfe97mD59OkKhEBwOB3784x+nHDwRERFZDKngjUhU+Azs8RjY6zVRFTThj0oYsuMlCKSUeP3117Fu3bombbNnz8bUqVPbfUJAKoX6sMR+n4mDfgNKAZ0cVjKgvX/tRO2NCgVh1tdAOJ0Qup7tcLLDNKCtST5D3Zw8Fx02W5IioVK8lfDss8/illtugWEYDX9gHA4HOnfuDCEEqqurEYlEAFgJApvNhieeeALXX3996tG3AY/Hg9LSUtTX16OkpCTb4RARESUllULQUPBFrYRAWAKaAFy6gCmBsFQQAByatb1coV2DUxdwaGiXg0JTKmjCSgi8/PLL2LZtW5M+8+bNw+jRo7MQXeZIZf1O1IQl/FEFu2YVEWyPP3OijkBFozBrjkIZEWjuwmyHkzVi80rYH74naXvkgTeAriffES9XSQnUe30YOXxIxq+dcrnK66+/HgMHDsSdd96JjRs3ArCKCR4+fLhJ3/POOw9/+ctfcP7556d6WSIiog5JKYWQCfijEvURhbBp5fZdNoEyW6PBvg4UQEAphbAE6iIK1WETds1KGhTbrbXkLhug5eFgUSmFqAQiUiES+35ETMA0o1j15ks4sGdXQn9N03DVVVdh+PDhWYq47alYMqA2LOGNKtgEUOoQefnzJSKLkhLSWwsVCUEUFGc7nKzSViVfOiCHjs3rhEC2pWUPi/Hjx2PDhg1Yv3493n33XWzZsgW1tbVQSqFz584YMWIEZs6ciXHjxqXjckRERB1O2FQIGAr1EYmgoSAV4NQESk4y6BNCwKWjoZhcVFqJBF/UhBDWaxTZBQpsAi5dwJ6jRedMqRCR1jZ6YVPBbyhEpIIRW7Fo1wBlRPD+ay/gyMF9Cedquo4LL78G3c44E3VhCbsG2DQBu5afCZETKWV9P2pDVjJAYzKAqN2QvnoonweioKhjz4z3e6BtWpG0WU6Zm7lY2qG0bmw5btw4DvyJiIjSJBpLBHijEn5DIWoCDh0osgno2um9O7RrAvbYuVIphE2gOiRRBWuZgUsXKHZYywxcenaWGShlDfYjsURAICoRMoCIUjCVVRDJocWSGLGt9ELBIJa+9AyOVVYkvJbNbsdF865D1z79UR2WMBUgANg0wAYBhw64bQIOXcAmRCxhkFvLK6RSMCUgAZgSMJWVFDKVlSSJSAWfYS0VKbaf/u8GEeUWGQpAemohnG4ILaVScHlP+3gZhBFttk05XJBjWcQ+FWlNChAREVFqTGklAnxRCV9UISwVbMIqDlec5r3kNSHgtqGhCn2kYTaCCV07PhPBFZtFYGujwaZU1hKAiFQIGwp+UyFiWssDAMAmALsuUCSaH/DWVVdh+eKXUVN1NOG4w+nCJddcj+69+jQ5x5DW6wdNBU/0eHkluwbYhLWswqVrCbMK0v31q1iSIz7AbzzYj5oKUakQVYBpAhIq1ifxNTQB6MJKFLXVz4eIMk8ZUcj6WkBoEHZ7tsPJOm3V4qRtcuwMoAPXWkgHJgWIiIiyLF4wMBBV8EQUQrECgW6bVRwwUxy6dcccsJITYRM4ErRG5k4NKIjF47KlVqzQkMeTAEFDImBYyxoMpSBgvbZDEyi0tXyN6mNHsHntauz+qmlBQZe7AJfOvxHl3Xo0e65NE7BpgDVvwKKUgqEAQwKeiEKtMqGgoAvRkJhw6wJO3TrXrlnHm0tUmLLxgP/4cysZYSUkotL62UtYg30pjxfOFrAG+7oQ0DTADgGXsJIAuTSLgYjSTykF6a2HCgchCln4HIf3Qtu1JWkzlw6krlVJgXXr1rVpccBAIIC9e/di2LBhbXYNIiKiXKJiU/f9UQlPVCFoKihlTd8vc2S/UryuCRRoicUKPVGFmohVrNCpCxTbBNw2DU69+YExYH2djWsBBAzrMRKbBaALa3BdaBPQWzk99tjhCmxauwr7dm1vtr2wqBiXzl+IsvIup/Q1CyFgF9ZsAXejZIGMFTU0TKDGOL4EQReAXQjYdcCtC+sOf2zAnzDYV4CCdY7A8bv7mrDu7uuxz7P9Myei3KACPkhvPYS7sGPXEYjRVycvMKg694A6m8vXU9WqpMDEiRNxySWX4Je//GVaawb4/X786U9/woMPPoi77roLP//5z9P22kRERLkobFqzAjwRiYBh3Zl2aQIl9twtDNdcscKIqXA4oqBpEk4hUOSwihU6dAEZW+seMhX8UYWoSiwIaNcECk4yC6A5lYcOYNOalTi4d3fSPsWlZbh0/kKUlHU67a/3RJoQcOoAdKDxzAJDWj+/kGlV/Rei8d19K8EQH/wTEbWGikasOgJ2O4SuZzuc7JMS2uolyZsnXwp08HoL6dCqpECnTp3w1ltvYenSpZg0aRJuvvlmzJ8/H506nd4f3FWrVuHpp5/G888/j7q6Oiil0KXLqWXziYiI8oURqxPgjVgFAyOxgoEFeboOPF6ssNDetFihTTs+FV6PLQNw6wK206yHoJRCxf692LR2FQ4f2Je0n93hxDnnjcXIsRPhdLlO8ys7NTZNWG+kcnTHBiLKL9b2g3VQRhRaYcfefjBOfLEeoqYyabs5mUsH0qFVSYEdO3bgF7/4Bf7xj39g9erV+Oijj3D33XfjwgsvxIQJEzBu3DiMHj0a3bp1g82W+JIejwfbt2/H+vXrsW7dOrz33ns4ePAgAOsP/TnnnIPf//73uOSSS9L/1REREWWJKa0lAf6olQwIxQoGunRrC8D24sRihVGp0nJ3XCmFA3t2YdPaVThacTBpP6fLjeFjzsc5o8dlLBlARNQWpM/TsP0gWbRVyZcOyEEjgJ4DMhdMOyaUUurk3SwHDhzA/fffjyeeeAJ+v996gRP+6BcUFKBTp04IBoOoq6uDlDKhPX658847D/fddx+uu+66nFpD5/F4UFpaivr6epSUsLAHEaVHfI91wFpPrMUfuY44r8WLyRkSMGLF5MKGtWOAYaKhYKDLJuDMsW3ucpVSCnt3foXNa1eh6kjyu0PugkKMGDseZ48aA4fDmcEIiYjST4WDMKqOQNhsEHZHtsPJDUE/7HdfDBEJNdts3PITyBnzMxxU25ESqPf6MHL4kIxf+5SSAnH19fV49tln8fzzz2PNmjUIhZr/QZ2of//+uOyyy3DzzTdj/PjxpxxsJjApQETpEo2tqba2l7MGikCjhACsQaKuWdO24tXQdU0kJA00IZhIyKITB/5GrGheSCqYJmDg+Hp5wPr5xCvSOzSuJ28tKSV2f7UNm9euRm31saT9CouKMfL8iRg6YjRs3KaLiNoBZRowq49CRcLQCri1Xpy28nXYHvlls23KZkf0f5YBRaWZDaoNZTMpcFpbEpaWluKOO+7AHXfcgUgkgvXr1+Ojjz7CwYMHcezYMdTU1MDlcqFr167o2rUrRowYgQsuuAB9+jTdJ5iIqL2IV1kPxfaYt6qsW4NEp24VkhOwKpHL+KOyKppHoCAN1VClvDEhmEhoa2asYJzZzMDfMBVMWEmBeAX5eLV4XRNwCwH9NIrmkUWaJnZ+sRWbPl4NT21N0n5FJaUYNX4SzjznXOg27qhMRO2H9HmgggGIIt6QbKylpQNq9LR2lRDItpT/qjocDkyePBmTJ09ORzxERHlFKoWQYVUf90Qlwqa1HZktlghorsK6LmJFzBMkH1AqpdKSSHBqQIFdg12z9qO3d7C72PGBv9Hozn/YlAhLnHTg7xDgwD/NTMPA9s8/xeaPP4LPU5+0X0mnzhg9fjIGnz0cGitxE1E7I4N+SE8dhLuA2w82dqwC2pcbkjabU1hgMJ2YaiciOkWGjC0LiCp4Y8sClAIcmrVXeXGai8gJIdKSSPAbCvVRE8Dx/dWd+vFEgV0TcOj5nSiQsbv8jaf6h0yJSGzgbyirMn6cLgBbbPs4Dvwzw4hG8eWWTfhs3Rr4fd6k/TqVd8WoCZNxxlnDoHG7KSJqh1Q0CumpAXQdgjOgEmgfJd+GUJV0hho+MYPRtH/87SOitJNKwZTWgNSUgBkboJrKqkweNRUcurWfuU2zBmU2zRqg5eKArLllAfGigS49N/eXbz6RcDzGeOHDfE0UxO/6R6U18I+aVqX/aKM1/o3v+NuEOH7HP0d/z9q7SCSMLzZ/gi0bPkYw4E/ar7xbD4yeOAUDBp/FnxMRtVtKKWv7wUgEooDbDyZQCvrqFnYdmDgHsLGmTDoxKUBEraZi1dXN2J1ns9HgP2oqREwFA4BpAiaOJwIUFERsQBqfzu6NT3tX1l7mNgHoQsBlA1y6lpAssGVhmnt87/WQqeCJSIRasSwgn+iagFsDcjlRoOJ3/WNT/o1YZf/4Ov/Gd/0FEEssCbg0AVue/3zak3AohM83rcfWT9YhHAom7detZ2+MnngB+g4cxJ8dEbV7KuCF9Hm4bKAZYudnEEf2J22XUy7PYDQdA5MCRNQw1fz4gP/44N8aKFqDRVMeb5OwBvRKxdavxwb7uhDQNMABEdurHBCi5am/UlkDblMCnohCrTIb7vLaYwM9h2btg27X4okC0VDhPV3iywKCUQVPbFmAjC0LcLXBsoBck2qiwK6d3s8j/vM34nf9pULIUAjHZpkYsd9JEfudit/1d6b550/pFQoEsGXjx/h84wZEI+Gk/Xr27Y/RE6agV78BTAYQUYegomGYnloIhx2CtVKa0FYtTtom+50J1e/MDEbTMTApQJRFRmwtenyJc8OjSvw88Zg6hb7Nv66MPYlKazAWlbFZAIjd2VfH+2ux6dbxivb2+GAsjVOwtdgA05rrfvw1lYoXhgOCprV+P/616LFt32y6dWfYabOSBPFkga2Ve8KHTYWwqeCPSvij1kBUwJoNUGwTHX7QmSxREG2hRoHbJmKFDI8nCuKzTJps63fClP+4+M/SoQkUaIB2ksQS5Y6A34fP1q/FF5s/gWFEk/brM+AMjJ4wBT369MtgdERE2aVME2Z9LWCYEIVF2Q4n90RC0NYtS9osJ7PAYFtod0mB+++/Hz/5yU8aPldKtdCbKLNOXJseNJR1x72hPfaIxMfGbU1eMzY1P35nPX7nvvm+x4d2Ao0H/MfXW8cH/7lACAG7sGYLnFhUr2FNuakQNBTMEAChoIlYUiA2QHXqx2cX2DXrTnNEWssCvBFprUOX1vfBqQuUcdr5SemagA5r9kRcYqJAQUHBJgTsQsCuW8mA+F1/Ux6fXRKf7cFt/fJfOBTCJ6s/wJefbYRpmkn79R98JkaPn4KuPXtlMDoiotwg/R7A74MoZB2B5mibPoAI+JptU5pu1ROgtGtXSYGvvvoKv/rVr7IdBlECU1pr04OGhNewpkUb6vjadLtIHKjHxcdGDW0cLCWID0ydeuL3JV593lSAL6pQFzmeTbFp1mSEaGxpREdZFpAJLSUKQqaCBgGbJuDilP92qba6CsteeQ6eutqkfc44axhGjZ+M8m7dMxgZEVHuUKGgtf2gyw3Bv4XN0lYlLzCoRk4CSsszGE3H0W6SAlJK3H777QiFQpg4cSLWrFmT7ZCoA4vEpqQHDAVfxCqMphSsNdg2a3BEbUMTVhE8S+JSBFNZReuKODDNiHiiADq/1+3Zvl3b8f6bryIaiTRpE0Jg0NnDMWr8ZHQq75KF6IiIcoMyDWvZgACEnZXzm1V3DGJL8jGcyQKDbabdJAX++Mc/YvXq1Vi4cCEGDx7MpABllGpUqb7xlPT42vRSR+5tWdfRiPiygmwHQtROKKWw+ePV2LBqRZM2TdMw5JyRGDV+EkrKOmc+OCKiHGJtP1gPFQ5AFJZkO5ycpX30FoSSzbapwhKoUVMzHFHH0S7eH+/Zswc/+9nPUF5ejocffhh//vOfsx0SdQCGtGYDBA2rAF7ItLbns2tWIqCIU9KJqJ2KRiL4YOli7Nn+RZO2Lt17YMbl16CkrFMWIiMiyj0q6If01kO4uP1gUkpBW5186YAcPxuwOzIYUMeSUlLgjDPOAAB8//vfx1133ZWWgE7HN7/5Tfj9fvzlL39B165d0/KaxwImTKeEHivEpsf2S09nxfVcYMrGW9FZRdoavmZOr04QLxLYuFJ9RFrF+5yaQBEr1RNRB+Ctr8OyV19AzbEjTdoGnX0Ops6aCxunxhIRAQBUNALpqYGw6RC2dnE/tk2IT96DdnBn0nY5+bIMRtPxpPSbefDgQZimiVGjRqUpnFP3z3/+E8uXL8fMmTNxyy23pO11j4UkQn6zofq7rVGVdrsGODRry614okCPD6a13KjcfuK+86ay7mJLWNXaI6Y1oJXKqn4f79dQDRwCum4VYnNo1hr4E5MjHWEALJtdFqCgC2EtC2C1dCLqQCr278W7i19COBhs0nb+1BkYOW4C/59IRBSjpIT01kFFItCKuGwgqXAQtqcfTNqsevSHGjQigwF1PCklBXr06IFDhw7B7XanK55TcujQIdx3331wu934+9//flqvEQ6HEQ6HGz73eDwArAranZzH98U2pWoYOIdMBb9hDbrjtBNmFDhjSYN4okCPrWdOR9IgXjDNjG3tJWEN+E2F2GDfqr4uG+07L2PLc+LbgOkC0CCgaVb1+3jCQzZ6bcMEwoaCoVTDVnYi/nUiVtAtNlXepse+PiFiX2/+zqqImgphqRCIWssCwrHZFMcr1XO/dCLqWJRS2Lb5E6x57+0mW/06nE5Mn3s1+g4clKXoiIhykwr4oPxeiIKibIeS0/TX/glRU5m03bxgXvL9tiktUkoKjB8/Hi+//DI+//xzjBkzJl0xtdodd9yB+vp6/O53v2tYynCqfvvb37ZqG8OGKtoATtwvHUjcBi0S3zddHd9bvmGg3MwdeJvWaKaBQMMdfhm/w6+s9etRaRWvi8YH/LF+CXE2DPqP7zt/KoNzTQhoArAD1sj/hK/1xISE31DwRBUah9F4yUV8fb1dFwnHdWFtD5cLSYP4soCQoeCLSgQM63MglgTgsgAi6sBMw8Dq5Uvx1ZbNTdrKOpfj4iuvQ1lnbhFFRNSYioRgemohHA4IjTeUkqrYDW3pU0mbVXEZ5EXXZjCgjimlpMB3vvMdvPTSS3j44Ydxww03wJ7BNYRPPfUU3nzzTYwaNQrf//73T/t1fvKTnySc7/F40Ldv31N+nWTboMWdeAc+ZCiYje62NL4DL3E8MdCY3uiOvl0TcGbhbnxCBfckSQMZ2/ZNKiBoKvhisyrisw0Sv47jSzFOJBt9f1Ts/IbPcTzhopCYlFCqcVvieTJJv4hUMJS1dMKpCxRwWQAREQJ+H9597UUcqTjYpK3fGUNw0WVXwOF0ZSEyIqLcpUzT2n7QNCFc2ZlRnReUgu3J30GYRtIu5nX3AIXFGQyqY0opKTB9+nT85Cc/wW9/+1vMnTsXjzzyyGkNqE/V0aNHce+990LXdfzzn/+ELYWiHU6nE06nM43RNe9U7sDbkL9r9kV8xsPxI036NF6KEY4txTCV1VOdcMaJZzcep7e2X9O+oknfAps1a4OIiCzHKivwzqsvwO/zNmkbNWEyxk6+kMlTIqJmSH89EPRDFHAw2xLt42XQtq1P2i4Hnws55fIMRtRxpZQU+K//+i84nU6MHDkS77zzDs444wxMnjwZI0eORKdOnaDreovn//znPz+t6/7Hf/wHqqur8Z3vfAdDhw6Fz+dLaI9EIg3P420OhwMOR+5uY9GR9lA/2VIMIiLKrh3btmDlsjdhGol3b2w2O6ZecjkGDR2WpciIiHKbDAUgPXXW9oO84ZRc0Af9mRaKCwoN5i0/Brj0IiOEOrFi0CnQNC3hLoFS6pTuGpimeVrXvfDCC/HBBx+c0jn33HMP/vCHP5y0n8fjQWlpKTbtr0a3zqWnFR8REVE+klJi/Yfv4bMNa5u0FZWUYtaV81HerUcWIiMiyn3KiMKsPgplRKG5C7IdTk7Tn3kIegu1BMyLb4B5030ZjCj7pATqvT6MHD4k49dO+cb0iTmFFHIMRERElCXhUBDL33gFh/bubtLWs08/zJh3DdwFhVmIjIgo9ymlID11UOEgRCG3H2yJOLAD2rJnkrar0i4wr/52BiOilJICUsqTd2oDK1asaLH9l7/8ZcOOAkxSEBERtay26hiWvfo8PHW1TdqGjRqLiRddDO0kSwKJiDoyFfBB+jwQ7kLuntcSpaA/cT+ETD5j3Lz+XoD1GDKqIyxhJyIioiT27dqO9998FdFG9XgAa4ng5JmXYOjI87IUGRFRflDRCKSnFsJuh2ACtUXaR29C274pabscOgZy4pwMRkQAkwJEREQdklIKm9auwierm9bocRcUYuYV16JH77bfUYiIKJ8pKWF6aq06Atw6r2V+L/Rn/5C0Wek2mDf/uOk2YtTmmBQgIiLqYKKRCD5Yuhh7tn/RpK1L9564+IprUVTCYrtERCcjfR7A7+X2g62gv/wXCE9N0nY56waoPoMyGBHFpbT7QGM1NTV47LHH8O6772Lr1q2oqbF+4J07d8bw4cMxc+ZMfP3rX0fnzp3Tcbk2w90HiIioPfPU1eKd115AzbGjTdoGnz0cF8y6DDa7PQuRERHlFxUOwqg6AmGzQdhzd+vzXCD2fgHbL2+GUM3XpFNlXRG9/2XA3XEL2mZz94G0JAX+/ve/44c//CECgQCApsX94tsUFhQU4MEHH8S3vvWtVC/ZZpgUICKi9qpi/168u/glhIPBhONCCJw/dTpGjJ1wSlsLExF1VMo0YFYdhYqGoXFnlpZJCdtvvg5t15akXYzv3g85flYGg8o9eb0l4f3334+f/exnDYmA0tJSjB49Gj169IBSCkeOHMGmTZtQX18Pv9+P73znO6irq8OPfvSjlIMnIiKik1NKYdumDVjz/rImiXuH04npc69G34GcsklE1BpKKUifByoc4PaDraCtfL3FhIA8Zzzk+RdnMCI6UUozBbZu3YrRo0fDNE307NkTv//97zF//nzYT5h2aBgGXnjhBdx3332oqKiAzWbDpk2bcM4556T8BaQbZwoQEVF7YhoGVi9fiq+2bG7SVta5C2ZddR1KO+X20j4iolwig36YVUcgnC4IG0u0tchXB/t/XA3hq2u2Wek2RP+/54GeAzIaVi7K5kwBLZWT//SnP8E0TXTt2hVr1qzBjTfe2CQhAAA2mw033HAD1qxZg27dusE0TfzpT39K5dJERER0EgGfF288/1SzCYF+g4bgioVfZ0KAiOgUqGgU0lMD6DoTAq2gv/jnpAkBAJBzbmZCIAeklBR47733IITAT37yE/Tr1++k/fv27Yv/+I//gFIKy5cvT+XSRERE1IJjhyvw6lP/wtGKg03aRk+YgllXXgeH05mFyIiI8pNSCtJbCxWJQHO5sx1OzhO7P4e24uWk7aq8B8x538hgRJRMSumtQ4cOAQAmTZrU6nMmT54MAKioqEjl0kRERJTEjs8/w8plb8I0zYTjNpsd0+ZcjjPOGpalyIiI8pcKeCF9HoiComyHkvukCf3x/wfRwkp1Y+F9gJPJlVyQUlJA13UAVs2A1or31bSUJikQERHRCaSUWPfhe9iyYW2TtqKSUsy68jqUd+uehciIiPKbioZhemohHA4IjmNOSnv/ZWh7v0jaLkdOhjrvwswFRC1K6Tc6vmTgVJYCxPu2ZrkBERERtY5hGHj39RebTQj07NsfV950GxMCRESnQZkmzPpawDAhHK5sh5P7PLXQX0xeP07ZHTBu+hHALXBzRkpJgYsvvhhKKTzwwAPYsiX5NhNxn332GX7/+99DCIFZszr2PpRERETpEomE8fbLz2Lfzu1N2oaNHotLr70Rbu6jTUR0ypSUkH4PEPBBuPn/0dbQn/8fiIA3abu87GtA976ZC4hOKqWkwL333gun0wmfz4cpU6bg97//Paqqqpr0q6qqwn//939j6tSp8Pl8cDqduPfee1O5NBEREQEIBYNY8vzTqNi/N+G4pmm4YNZlmDzjEmix5X5ERNQ6SinIUABm9RHIumrA6YbQeGf7ZMT2zdBXvp60XXXtDfOyr2UuIGoVoVQL1R9a4YknnsDXv/714y8oBAYMGIDu3btDCIHKykrs3bsXSikopSCEwL///W/cfPPNKQffFjweD0pLS7FpfzW6dS7NdjhERERJ+X1evPXCItRWH0s4bnc4MPuqBejZt3+WIiMiyk9KKSAcgun3QAX8gCYgnAVMCLSGacD2y5ug7W86ay0u+r3/gRp1QQaDyh9SAvVeH0YOH5Lxa6e8ueYtt9yC8vJyfPvb38ahQ4eglMLu3buxZ88eALF/WDG9evXCP/7xD1x66aWpXpaIiKhD89TVYskLT8NbX5dw3OUuwCXX3ICuPXpmJzAiojylIiFInwcy4AMgINwFLCp4CrTlL7SYEJDnXciEQI5KOSkAAJdddhn27NmDV155Be+++y62bt2KmpoaAEDnzp0xfPhwzJw5E1dddRVstrRckoiIqMOqqTqGt154GgG/L+F4YXExLr12IcrKu2QpMiKi/KOiYUi/D9LnAZSCcLkhuOzq1NQdg/7yX5M2K4cLxo0/zGBAdCpSGqHv378fAFBUVITOnTtj/vz5mD9/floCIyIioqaOHj6EpS89i3AomHC8pKwTLp2/EMWlZdkJjIgoz6hoFDLohfR5ASMK4SqA4A3M06I/9z8QQV/SdvPy24CuvTIYEZ2KlObDDBgwAAMHDsSzzz6brniIiIgoiUP792DJ8083SQh07todl99wKxMCREStoIwoTE8djKoKyLoaCN0GraiECYHTJL78BPpHS5K2q+79IOfcksGI6FSl9JvvdrsRCoUwbty4dMVDREREzdi78yu8t/hlmKaZcLx7rz6YffX1cLq4dzYRUUuUaUKF/JDeOqhwBMLlhCgqyXZY+c2IQn/i/pa73PwfgN2RoYDodKQ0U6B3794A0OQNChEREaXPjs8/w7uvvdjk723vAWdgzrU3MiFARNQCJSWk3wuzqhKy6iigAFFUAmF3Zju0vKctewbaoV1J2+W4mVAjJmYwIjodKSUFZs2aBQBYtWpVWoIhIiKiRFs3rseKt17HiTsIDzzzbMy+8jrYHbz7QkTUHKUUZNBvJQNqjgLSAIpKIJwuCO4wmLqaI9Bf/XvSZuV0w7jxBxkMiE5XSkmBe+65B263Gw888AAOHTqUrpiIiIg6PKUUNq5ZiTXvvd2k7awRozB97lXQuf6ViKgJpRRkKACz+gjMY5VQ0QjgLoJwupkMSCP9mYcgwsGk7eaV3wI6d89gRHS6UkoKDBkyBIsWLUIgEMCECROwaNEiRCKRdMVGRETUISml8PGKd/HJ6g+atI0YOwEXzLoMGvfOJiJqQoWDkLXHrGRAKAhRUAjNXQChMRuQTuLzj6Gveydpu+o1EHLWjRmMiFKR0i2G6dOnAwC6du2KPXv24Oabb8btt9+OIUOGoFOnTtBb2N9TCIHly5encnkiIqJ2R0qJlcvexPatnzZpGzvlQowaPxmCt7qIiBKoaBjS64EM+AClIFxuiBbGIpSCaAS2kxUXvOUngM2eoYAoVSklBVasWJHwxkQphXA4jK1btyY9RwgBpRTf0BAREZ3ANAy8/+ar2LPjyyZtk2ZcgnNGj81CVEREuUtFI5ABH6TPA0jTWiLApVVtSlv6FETlvqTt5sQ5UGfz71U+SelfzNSpUzm4JyIiSoNoJIJ3Xn8Rh/buTjguhMC0OfMwZNiILEVGRJR7lBG1kgF+DxCNWskAe0G2w2r/qiqgv/5I0mblKoR5/b2Zi4fSIuWZAkRERJSacCiIt19+DkcqDiYc13UdMy6/Bv0Hn5mlyIiIcosyDahgANJbBxWNWDsJFLmzHVaHYVv0IEQklLTdvPrbQFnXDEZE6ZBSUmD//v0AgKKiInTu3DktAREREXUkAb8Pb724CDXHjiYct9sdmHXVdejVb0B2AiMiyiHKNKFCAUhfHRAOAw4HtKKSbIfVoYhPV0P75P2k7bLPYMiZCzIYEaVLSqWLBwwYgIEDB+LZZ59NVzxEREQdhre+DoufebxJQsDpcuOy625iQoCICIAKBWFWH4GsPgJICRSWQDhc2Q6rY4mEYXvqdy12MW/9CaCznkM+Sumn5na7EQqFMG7cuHTFQ0RE1CHUVlfhrReeht/nTTheUFSMOdfeiM5dOP2SiDo2ZZqQfg+kpw4QgCgo5taCWaK9+W+IoweTtptTLoc6c3QGI6J0SmmmQO/evQEApmmmJRgiIqKO4FjlYbzx7BNNEgLFpWW4/PpbmBAgog5PRUIwa45C1VVD2B3Q3IVMCGTL0YPQ33wsabMqKIa54J4MBkTpllJSYNasWQCAVatWpSUYIiKi9u7wgX148/knEQoGEo536tIV8264FSVlnbIUGRFR9ikpYXrqYFQdgQoFgYJiCDv3u88apWB76r8hopGkXcxr7wRKWF8un6WUFLjnnnvgdrvxwAMP4NChQ+mKiYiIqF3av2sH3nrpGUQjiW+uuvXsjbkLbkFBUXGWIiMiyj4VDcOsPQZVVwWha9AKizg7IMvEpg+gfZr8BrDsPxTyomsyGBG1hZSSAkOGDMGiRYsQCAQwYcIELFq0CJFI8iwSERFRR7Xry8+x7LUXYBpGwvFe/Qbg0vkL4XJzSy0i6piUlJB+D4yqSqiAPzY7wJntsCgchO3p3ydtVkJYxQU1PYNBUVtIqdDg9OnTAQBdu3bFnj17cPPNN+P222/HkCFD0KlTJ+h68l8QIQSWL1+eyuWJiIjywheffoJV77zV5PiAIWdh+mVXQbexWjMRdUwqGoH01kH6PBAOB0RhUbZDohh98b8gqg4nbZdTr4QaNCKDEbVvSmXv2im9C1mxYgWEOD6lRymFcDiMrVu3Jj1HCAGlVMJ5RERE7dXmj1dj/cqm+zoPOWckps6eC01LadIeEVFeUkpBBXyQnlooIwpRUATB/x/mjsp90N56ImmzKiyFOf+uDAbUPoVNYG0N8O4R4N2jwJIx2YkjpaTA1KlTObgnIiJqhlIK61e+j0/XfdSkbfh552PCRRfzbygRdUgqGj0+O8Buh1bIeio5RSnYnvgdhBFN2sW87v8AxSyMezqqw8B7R60kwIfHAH8ObOSX8kwBIiIiSiSlxOrlS/HlpxubtJ03aSrOm3gBEwJE1OEopaBCAUhPDVQ4DOEuhGhhuTFlh9iwHNrna5O2yzOGQ069MnMB5TmlgO0+4J0jwPIjwMY6IIsrBZrFRYxERERpZBoGPlj6OnZ9ua1J28SLZmH4mPOzEBURUXYp04D01kN66wFdh1ZUku2QqDmhAGxPP5C0WQkB85YfA1zq0aKwCXxcY80GWH4EOBDMdkQtY1KAiIgoDaSU2PH5Z9j40YfweT0JbUIITJ09F2cOPzdL0RERZY8MBSDra6HCAQhXIQSLq+Ys/ZW/Q9QeTdoup18LNXBYBiPKH9Vh4L1jVn2AlVWAzzj5Obki7f8iDx06hMrKSgQCAYwdOxZubrFERETtmFIKu7/6Ap+sXoH62pom7ZquY/rcqzBwyNAsREdElD3KNCD9HkhPHSA0iMJScOVU7tI+WgJ96ZNJ21VxJ5jX3JnBiHJbfFlAvEjgxtrcWxbQWmlJCni9XjzwwAP417/+hYqKiobjW7ZswbBhxzNJzz77LF5++WWUlpbin//8ZzouTURElBVKKRzYswsbVr2P6qNHmu1js9sx68r56N3/jAxHR0SUXSoUhFlfCxUKQLgLODsgx4kvNkB/5Jct9jEX3AMUduxlHxEZWxZwxPrI9WUBrZXyv86dO3dizpw52L17N1SjzRWbK6A0ceJE3HzzzZBS4tZbb8WUKVNSvTwREVHGHT6wD+tXvY8jhw4m7dOjTz9Mmj4b5d26ZzAyIqLsUqZ5fHYAAFFUwtkBue7Qbtj+9wcQZvL57nLIKMjJczMYVO6ojSTuFuBN87KAAh2Y2gWY3i29r3sqUkoKhMNhXHbZZdi1axcKCwtx5513YurUqZg7t/lfmP79++Oiiy7C8uXL8frrrzMpQEREeeVY5WFsWPU+Du7dnbRPl+49Me6CC9G7/xncYYCIOhQVCcH01AEBH4TTDWG3ZzskOpm6Ktgf+j8QAW/SLkq3dajigkoBO3zA8qPWbIBPagGZ5mv0cgEzuwMzuwETygGXDkgJ1Cf/MbSplJICf/vb37Bjxw4UFhZi5cqVGDVq1EnPmTNnDt59912sWbMmlUsTERFlTG11FT5ZtQJ7dnyZtE9Z5y4YO+VCDBhyFpMBRNShKCkh/V5Ibx1gmhAFxRAa/z+Y80IB2B6+B6LqcIvdzK/9DKrfmRkKKjsMCayvBZYdsbYO3B9I/zVGlVlJgJndgbOLkVMzaFJKCrz88ssQQuCee+5pVUIAAEaOHAkA2LFjRyqXJiIianPe+jp88tGH2LltS8ISucaKSkoxZvI0DD57OLQOcheFiChORcPW7AC/F8LphHCxyHheMA3Y/voTaHu/aLnbFd+EnHpFhoLKrJBp7RLwdqWVCKiNpvf13bFlATO6WUsDurnS+/rplFJSYNs2aw/mWbNmtfqc8vJyAEBdXV0qlyYiImozAb8Pm9aswpefbYSUzU8adBcW4bwJU3DWyNHQdT3DERIRZZdSCirghempBQwToqAIgonR/KAU9Kd/D23zyha7mZMug3nVtzMUVGZ4olZ9gKWVwIpjQMBM7+v3dB2fDTAxtiwgH6SUFPB6rUUPpaWlrT4nFAoBAOxcY0RERDkmFAzis/VrsHXjOphG85WEnC4Xzj1/Es4ZPQ42/i0jog5IRSOQ3jpInwfC4YAoLMp2SHQKtLeehL78hRb7yGHjYN7+89ya436ajoasZQFvHwE+qgKiad438NzS4/UBhpXk57cspaRAeXk5KisrceRI81sxNWfLli0AgO7dWY2ZiIhyQzQSwdaN6/DZ+jWIhMPN9rHZ7RgxZjxGjJ0ApyuH5wASEbURa3aAD9JbCxWJcHZAHhLr3oHtuT+02Ef2HgTjrgcAW/4mvvf6rWUBS48AG2uBdOYBXBpwQVcrCTC9G9C9HbwlSCkpMGrUKCxduhTLly9v9RKCf/3rXxBCYPz48alcmoiIKGWGYeDLTzdi09pVCAWbryqk6TqGjRqDUedPhruwMMMREhHlBmVEIT2x2QF2G7Sijr1ffT4S2zfD9o//bLGPKu0C4/v/AxQWZyiq9FAK2OaxkgBvVwJfprmKf49GywIm5dGygNZKKSlw9dVX46233sLf//53fPe730X//v1b7P+rX/0KH3/8MYQQWLBgQSqXJiIiOm1SSmz//FNs/Ggl/F5Ps32EEDhz+Lk4b+IFKCpp/TI5IqL2RoWCMOtroMJBCHchBOuo5J/KfbD9z/chopGkXZTTbSUEuvTKYGCnz1TAhlorCfB2JXAgmN7XH9loWcA5ebosoLVSSgp87Wtfw0MPPYQvv/wS06ZNw5///GdceumlDe1CCEgpsXr1avz3f/83lixZAiEExo0bh3nz5qUcPBER0alQSmH3V9vwyeoPUF9bk7TfoKHDcN6kaSjrXJ7B6IiIcouSEtLngfTUAgIQhSXtemDUbnlqYX/g/0D46pptDmt21DtKUfPN36K+9Gx4jgH1UUAqoLPD+iiPPTqznA8Km8BH1VahwHeOAFXJcxynzCasWQCzewAXd7dmB3QUQiXbY6mVdu3ahcmTJ+Po0aMQQqCgoAB+vx9CCAwcOBBHjhxBIGBNyVRKoVevXlizZg369u2bli8g3TweD0pLS7FpfzW6deadISKi9kAphQO7d2L9qhWoOZa8Dk6/M4Zg7JRpKO/WI4PRERHlHhWNWrUDfB7A6YKwO7IdEiURkVZVfU8U8BjWY338eSgK34dL4fEHUe8oQb29GB57MTyOYtTbi+CxFyNka/3ot9hmJQjKHUBn5/Hn5Q6g3Hk8edDFaT060lBywmcA7x+1CgW+d9T6PF3cOnBhV+CSHlZ9gNIsllGQEqj3+jBy+JCMXzvlpAAAVFZW4pvf/CbefPPNFvvNmjULjz32GHr27JnqJdsMkwJERO3L4QP7sH7l+zhScTBpn559+mHcBRehe+/cTFgTEWWSDPohPTVQ4TCLCWaBqYCdPmuN/JFQ4mDfEwXqjcQkQDDN2+ql0+kmEarD1kyApUeA1VVAuPndgU9Lmd2aCTC7BzC1S+7UB8hmUiCl5QNxPXr0wOLFi/H555/jtddew4YNG3D06FGYpony8nKMHj0aV1xxBcaOHZuOyxEREZ3UscrDWL/qfRzauztpny7de2LcBReid/8zIDgnlog6OGWakP56SE8doOksJpgBhgR2+YHP6oEtsY9tntwe6J8Kr2F97G2+lm8TxTZr0H4oCKQxD4BeLmBWD+CS7sD5nQEb81wJ0pIUiDvnnHNwzjnnpPMliYiITsmRioPYtHYVDuzembRPWecuGDvlQgwYchaTAUREAFQ0DLO+Fgj4IFwFELa0DhMIVgJgp+/44H9LPfC5Bwilc/Sb5+JJhHQYXGQlAWb3sIoG8s99cvzXTkREeU8phYoDe7FpzSocPrAvab+iklKMmTwNg88eDo3TYYmIoJSCCvggPbVQhgFRUAyhcfSUKkMCO05IAGxjAqDNjSoDZne3agQMKsp2NPmDSQEiIspbSins370Tm9euwtHDh5L2cxcW4bwJU3DWyNHQuZUWEREAQJkGpLce0lsPYbNBK+Qo6nREkyQA0rkOnpqnC2BCZysJMKs70NOd7YjyE5MCRESUd6SU2LvjS2xau7rF3QScbjdGjp2I4eeNg82exZLCREQ5RkVCMOtqoEIBLhc4BVEJbPc2SgB4gC/yOAEgYK3jL7UDJXagpNFzAKiJANWxj5pIeiv/ny6XBkzrai0LmNkNKOPGGCnjv34iIsob0jSx84ut2LzuI9TXVCftV1BYhBHjJuDskefB7uC7BSKiOKUUlN8L01MLSAlRWMK11s1QyhoIHwpad/3jSYAvvbmXACixASW6RFn1XpQEqlEa8aIk6kNp1IuSiLfhscTwofDym1FyzmjrHDtQZANOZbVIyGyUKAgfTxZURYCa8PEEQrqTCCU2YGZsWcDULkABR7FpxW8nERHlPMMwsH3rp/h03UfweeqT9isqKcW550/CmcPPhY13vYiIEigjCumpg/TVQzidEK6OO9faZwAVwdhH6ITHIHA4lN3Bf7kDGFEKDCuxtusrjQ3i43fz48+LbIAeDcP2++9C276pxdc0Ft4HOXF0SnG5dKCX2/pojVSSCN2cVhJgdg9riYCdpYDaDN8xERFRzopGIvjys034bP0aBPy+pP1KO5dj1PmTrAKCrBlARNSECgVh1tdAhYMQ7kKIdvz/yogEKkPA4aB1p7+5Qb8nB6bBx3WJJQAaf/R0tbJavpTQH/nlSRMC5qwbIWfdkJ6AT8HpJhHcurU1IWexZAaTAkRElHMi4RA+37QBWz9Zh1Aw+ebGnbt2x+gJkzFgyFDuJkBE1AwlJaTPA+mpBQTyfrmAjE3rjw/uDzUa/B8OWY/HwoDKdqBJdHUCI0oSEwA9WpsAaIb+4p+hf/x2i33kmItg3vC907tAhsWTCJRZTAoQEVHOCAUC2LLxY2zbtAGRcDhpv249e2PUhCnod8ZgiHx+d0tE1IZUNALprYPyeSCcLgh75musGBIImtZHKPY8FPs48XhLbdVh607/4ZA1EyAfdHUmDv5HlgLdnem7+629/xL0Nx9rsY8cNBzGHb8BtPY7M4RSx6QAERFlnd/nxZb1a/HFpxthGNGk/Xr27Y/RE6egV98BTAYQEbVABv2Q9dVQ0ShEQRHEKcymUgqojVp33I+EgKNh67knmjhYDzUayDc38A+agJGrt+zTrJuz6RKAHq62u574dDX0J+5vsY/q2gfGvX8AnLz1Ti1jUoCIiLLGW1+HT9d9hK+2fgppmkn79T1jMEZPmILuvfpkMDoiovyjTBPSXw9ZXwfoOrTC4oa2iASqwtYg/2gYONpowB///Fjs82gHGcyfjkwnAE4k9n4B259/BCGT/91UhaWI/vCPQEnnzAVGeYtJASIiyri6mmps/ng1dm7bAqWSv/MceObZGDV+Mrp075HB6IiI8odSCn5D4UhQ4og3jCM1Xhz1RnDULMDRqJYw4K9NPhGLmtHVaRX86+0GhhYfTwB0z2ACoInqw7A9dA9EOJi0i7I7YNz7ENCjfwYDo3yWtqSAlBLbtm3D7t274fV6YbZwxyfulltuSdfliYgoD1QfPYJNa1dhz/YvkvYRQmDw2cNx7vjJ6FTeJYPRERHlDqUUfFGFyqBEZUCiMmCiMiBxNChxJChxLBR7HjARTHjbrQHI5qg1PxTZgF6u45XxG57HHnu4rKJ3OcXvhe3BuyHqq1rsZn7zv6DOTG3rQepYUk4KBINB/OY3v8E///lPVFdXt/o8IQSTAkREHcSRioPYvHY19u/ekbSPpus4c/i5OHfcRJSUdcpgdEREmRUxFY6FJA7HBvtHAjI2+LcG/vFEQKCjLMhPM7uwBvW93UBPN9DbFXtsNOgvsWc7ylNkRGH70w+hHdrVcrcF90COn5WhoKi9SCkpEAwGMX36dKxbt67F6Z9ERNQxVezfi01rV6Fi/96kfXSbDWefOwYjx45HYXFJ5oIjorwglUJlQGKv10z4CBgKbptAgU2g0CZQaE98XhhrK2j0eeM+Dj39xUqVUqgNKxwOmDjScIdfojJoNjw/EjRRFeL75lR0dcYG/K7EgX6v2LGuTkBrT7VolYL+r19D27a+xW7m9PmQc3jTlU5dSkmBhx9+GB9//DEAYPjw4bjrrrswZswYdO7cmftFExF1YAG/Dx8tf7vFZQJ2hxPnjB6L4WPOh7ugMIPREVGuMaXCIb818N/jNRIG//t9JkInX5V6yuwaUGgTcLeQVHCfmGSIPUYlcCQgcThgojIorTv9sURAvmyXlwkODXBp1jR8d+zDpQNuzXrubHTcrVt948+dJxwvsgE93EAPp9XWkeiv/h366jda7CPPnQLzpvvSt98hdSgpJQWee+45AMCkSZPw3nvvweHI/N6nRESUO5RS2LFtC9a+vwzhUKjZPk63G8PPOx/njB4Hp4vrXok6iqhUOOBLvNu/J/Z4wGcimuHBdFQCdRGFugjv2p9IA1DutKrsxz+6Oq1jBScM8F3NDOhdsc9tvEeYMm3l69Bf/UeLfWT/oTC+ez+gs4Y8nZ6UfnN27doFIQR+9KMfMSFARNTBeevrsOqdJTi4d3ez7QWFRRgxbgLOHnke7PybQdQuhUxr4L/HY54w3d/AQb+EyfF3Vjm12CDf1XTAHz/W1QmUOzigzwXi84+hP/abFvuo8h4wvv8/gKsgQ1FRe5RSUsDhcCAYDKJfv37pioeIiPKMUgrbNn+C9R++h2g00qTd6XZj7KRpOHPEKNhsvItB1B4Eogprjkawo87E7kbT/Sv8Ehz3Z16ZPTawP8mAv9jG2eX5QhzYAdsf74MwjaR9VEERjO//ESjrmsHIqD1K6d3Z0KFD8fHHH6OysjJd8RARUR6pq6nGh2+/gSOHDjTbPmjoMEy8aDbchawZQJTvlFLYWGXguZ1BvLYvDF+Uw/+2VmpT6OECursEergQe5444O/aAdfYt3s1R2F76G6IoC9pF6XbYNz9IFSfQRkMjNqrlJICX/va17B27Vq88MILuOSSS9IVExER5Thpmvhsw1ps/OhDmGbTCmAFRcWYMnMO+g8+MwvREVE6HQtKvLQ7hGd3BbGjvg0q/nVATk2hu0Ohu0Oiu1Ohuwvo4Rbo4dbQw62he2zw726DHRIoxwV9sD18N0TNkRa7mbf/AurscRkKitq7lJIC3/zmN/Hcc8/hiSeewMyZM3HDDTekKy4iIspRVUcq8eHbb6D6aPOzxIaOHI3zp85gEUGiPGZIhfcORfDsziCWH4rAyPKkgG5uDQOK9YSPbm4NIUMhYCj4449R67k/2vR4/PPGz9Nd3FAA6OIS6OES1sDeIdHdbliPNgM9nArd3UAnpw6h2yC4pIoaM6Kw/e8Poe3f3nK3q78LOfmyDAVFHUFK/yc6cOAA/vjHP+Jb3/oWbrrpJrzyyiu48cYbMXToUBQUnLzYBWsREBHlD8MwsGnNSny67iMo1XSEUFxahgtmX4be/QZmIToiSoed9Qae3RnCS3tCOBrM7HYAPQusgf/AEwb/A4p1FNrbpupdxGw5qdBcIsEXVRAAurmtgX8PZ+yuvy2KLgjDpgzANAAFQNMgbDqg2QC9gOv5KTmloD/6K2jb1rXYzZx6JeS82zMUFHUUQjX3zq6VNE2DiP3fTSnV8LxVFxYChpG8cEa2eDwelJaWYtP+anTrXJrtcIiIcsKRQwfw4dtvoK6mukmbEALDzzsfYyZP464CRHnIF5VYvDeMZ3YF8cmxtntvpgmgd2zgP6DElpAA6Fekw23LjxGzikYgg36oYBBKRgHDAJQCNB1C161t4XQbEwB0SvQX/gj9jcda7COHT4Dxvf8BbPYMRUWZJCVQ7/Vh5PAhGb92ynOWGucUUsgvEBFRDopGIli/8n18vml9s+1l5V0w7ZLL0a1n7wxHRo0ppfBlnYkVFWF8fDSKgKEwsrMd03s7MK6bHXaNoxNKpJTCuqNRPLsrhMV7QwimqVSATQB9ipq/29+3SIczj9fIq2gUMuiF9HkBIwpht0PodsDhZgKAUqItf+HkCYG+Q2Dc9d9MCFCbSCkp8NhjLf/yEhFR/jq4dxdWLlsCn6e+SZvQNIwePxmjxk+GzjWxWVEfkVh5OIL3D0WwoiKCyhOmeq+ujOKv2wIotgtM7enAjD4OXNTLgW5ulinvyA4HTLy4K4Rnd4Ww15taJsAmgJl9HLigp6Nh4N+7UG93SShlRCEDfii/ByoagXC6IFzubIdF7YTYuAL6k79rsY/q3APGD/4EuIsyFBV1NCktH2iPuHyAiDq6cCiIte+/g+2ff9Zse5fuPTHtksvRuWu3DEfWsUmlsLXGwHuxJMDGqijM0/gLfm65DdN7OzC9lxOjutig8RZnuxcxFd45GMazu0JYURGBTPGd35BSHdcPduOagS50dbfNWv9coEwTKuiH9NVBhSMQLieE3ZntsKgdETs/he3+b0NEw0n7qIJiRP/vY0DvMzIYGWVDXi8fICKi9mPP9i+xevlSBP1N90bWbTaMnTwNw8eMh6a134FALqkOSXxQEcH7FWF8UBFBdTj1PP6n1QY+rTbw8GcBlDsFLuztxIzeDkzr6UCZkz/X9uTLWgPP7gripd0h1KT4u1NkF7iivxMLBrtxXhfbKdWRyjfKNKFCAUhfPRAKAQ4HRFEJlwhQelXug+3h77WcELDZYdzzEBMC1OaYFCAiIgT8Pnz07lLs2fFls+09+/TDBbPnorRT5wxH1rEYUmFTlYEVFWGsqIjg02oDbTmdrzqs8NLuEF7aHYIugLFdrToEM3o7MbRMb9cDv/aqPiLx2t4wntsZxObq1IsGTuxux4JBLlzWz4UCe/v+fVBSWskArwcIBwC7HWAygNpCXRXsD9wF4atL2kUJAeOO30ANHZO5uKjDYlKAiKgDU0phx+efYe2KdxAOhZq02x0OjJ82A0NHnscBYhupDJix2QARrDwcQV0kO6v6TAV8fDSKj49G8dtNfvQq0BoSBFN6OHJuQBg0FA75TRzwmTjolzjoNxE2FUodGsocAmXOpo8ldgG9na13B6ylJR9VRvHcriCW7A8jlGLRwB4FGq47w4XrBrkwsKT9v1VUSkGFg5DeeqhgANB1iIJiiHb4u0I5IBSA7eF7II4darGbecP3oc6/OENBUUeXtv/Te71evPvuu/j0009RVVWFYDDY4m4EQgg8+uij6bo8ERGdIm99HVa9swQH9+5utr3vGYMx5eJLUVRckuHI2reIqbDhWBQrYomAbbW5tz0vAFQEJJ7aEcJTO0JwaMDE7g7M6O3A9N6OjAwUfVGJAz5rsG8N/q3nB30mDvpNVIVOPXkiAJQmSRg0fdTQySlQ5tBQ6hQZKZ5nSIWQqRAyYD3GPoInfB4yFEKmdawqJPH63hD2++TJL9ACuwbM7uvE9YNcmNrT0S6TJydSSgHhEEy/ByrgBzQBUVDEZAC1HSMK259+BG3vFy12My+5CXL2wgwFRZSGQoNSSvz617/Ggw8+CL/f36pzlFIQQsA007T/TRqx0CARtXdKKWzb/AnWf/geotFIk3an241J02dj0NBzODsgTQ76TLxfEcGKijBWVUbhi6Z/NkB8+v+FvRwodQisiM08SNdWc42dUaJjei8HZvRxYnw3+ylvM6eUQn1ExQb5EgcaDfYP+iUO+syszZhIpsgukiYQOjk0uGxAyACCCQP344P35J/HjhkKRha+5LPLrKKBVw90obOr49SUUJEQpM8DGfABEBAuNwRrpVBbUgr6o7+CvvL1FruZ518M8zu/Bfj72OHkdaHBr33ta3j66aehlIKu6ygvL8fRo0chhECfPn1QW1sLn88qWCWEQJcuXVBQUJBy4EREdOrqaqrx4dtv4MihA822Dxo6DBOnz4a7oDDDkbUvIVPh4yPWTID3D0Ww09M2SfCeBRou6uXARb0dmNLDgRLH8TeRt55V0BDH8kPWR6pb0MXt9pjY7QnikS+DKLQJXNDTjum9nZje24GeBTqUUqgOWYP+A34ThxoN/A/5TRzwyzZJjLQlX1TBF1U46E/tjnwuKLELXDXQhesHuzCic/suGngiFQ1D+ryQfi+glJUM0LlNJ7U9/ZW/nTQhIM86D+Y3/4sJAcq4lGYKvP3225gzZw6EELj11lvx4IMP4tChQxg5cmTCTIDt27fjr3/9K/70pz9h0KBBePXVVzF06NC0fRHpxJkCRNQeSdPEZxvWYuNHHzY7S6ugqBhTZs5B/8FnZiG63KeUNSCsCklUhRSqQxJVIYnqsGx4XhU6/rwmrFLe9q05Dg04v5sdF/V24qJeDpxZemrFAHd5rC0Nlx8MY+3RKKJtML7tXaihOiRTXtdO6XdBDzuuH+zG7L5OuG0dJxEAACoagQz4rGSAaUA43RC29l8vgXKDtuJl2B77TYt9ZO9BMH72KFDIJXsdVTZnCqSUFLj++uvx/PPPY/jw4fjsM2s/688//xwjRoxodnnAG2+8gauuugp9+/bFpk2bUFqae4NuJgWIqL2pOlKJD99+A9VHK5ttHzpyNMZPmwGH05XhyLIrZFqD++pGA/rqkGoywI8/D2fpBnG/Ig0X9XLiot4OTOpuR6E9PXeQfFGJVYejeO9QGMsrIqgM5P8dcGqqT6GGBYPcmD/Ihb5FHe+OuDKisWSAB4hGrWSA3Z7tsKgDEZtXwvY/34eQyTOlqqwroj9/HCjvkcHIKNfk7fKBtWvXQgiBO++8s1X9586di1tvvRWPPfYY/vd//xf/+Z//mcrliYhyUsRU2OM1sbPewE6P9bjLY6I+tkZaAA1bXIlWfA4hEL+n15pzGzorhYDXg4DPC5sag/LienQ1atHNqEE3oxY9Sly4YPZl6N1vYFt8G7ImbCrsjX3/jwRPvIuvGp57c3T6uksHJnW3lgRc2MuBgcVtszVgkV3DJf2cuKSf06ozUWtg+aEI3jsUwSdV0TaZ6UCZ4dSAS/s5sWCwG5N72KF1oOUBcco0oIIBSG8dOlQUwAAAljlJREFUVDQC4XRBFLmzHRZ1MGL357D9+T9aTgi4i2D84I9MCFBWpZQUOHr0KADgzDOPTzfVG63LCofDcDqdCedce+21+Ne//oVXXnmFSQEiymv1EYmd9SZ2egzrsd7AjnoT+30mzJwZUBUCDqs+wB70Tmjp4hR4+Ssbzqr04qwyG84q03FmmQ2ljvxYy1gfkdhRb2JXLPmyo976OeTW9791BpfouKi3Axf1cuD8bo6MT+0WQuCcznac09mOu0cUoiYs8WFFBMsPhfF+RQS14dz7hrp0oE+hjj5FOnoXauhbqKPUqcETkagLK9QlPErURhTqwu17WcPIzjYsGOzClQNcKHPmx7/jdFOmCRXyQ/rqgXAYcDigFXE6NmXBkf2wPXQ3RKTpdr9xSrfBuPsBqH5cukfZlZbFVJ07d254Xlxc3PD86NGj6Nu3b0Lfbt26AQD27t2bjksTEbUppRQqAhK76mODztjgc5fHxNFgfk+3rgorVFVGsboymnC8R4GGoWU2nFmqY2iZDWeV2TCkVE/btPVTIZXC4YBsSLjEZ17srDdxLJS/3/94cb4LezlxYS9Hzk3r7uzUcOVAF64c6IIpFTZVG9Yyg0MRbK3JzBaKhTaBvkUaehfq6Fuko0+hhj5FOvoU6uhbqKPcJU5rBkXQUKhvNnGgUBtLINTFEgjxx/qIavOZJU4NcNkEXLqAS4f12PB57Fjjz21oeN7ZqWFcNzvOKuu4a+SVlFChAKS3HggHAbsDKCxBB5wkQbnAUwv7g/8HwlvbYjfzm7+CGnZ+hoIiSi6lvx7du3fH/v37UVNTk3DM4XAgGo3is88+a5IU2L9/PwAgFEqeNSOitieV6pBTSpOJxKece2KDz9jAc6fHRCAb+4RlUWVAojIQwYqKxOP9ijScWWqzEgaxmQWDS21wneJ2dM0Jmwp7PMe//7saLb1oiy31smFYJxsu6mUtCRjb1Q5HGr5vmaBrAmO72jG2qx0/GgVUBky8fyiC9yoi+PBw5LR3EShzCPQuPGGw32jwX+Y4vUH/ybhtAm6bjh6nuBFSVCp4Igq1CUmDWDIhLBGROD6YTxjQI+ng3m0TcOsCTh38//FpUko1JANUKADY7BBMBlA2hYOwPXwPxJHmd/mJM667G3LinAwFRdSylJICI0aMwP79+7Ft2zZcdNFF1gvabBg9ejTWrVuHxx57DJdddlnCOX//+98BAP3790/l0kTUCvUR6w73bq+B3R4TuzwmdntM7PFYAy2Xbt2NK7QLFNoECmKPhTat4VihXaDAJhL7NXpeZE/83Kbl9jsxT2zK/w6PkXD3f583/6acZ9p+n8R+XwTvHoo0HNMEMKBYb5hZcFZsZsEZJTrszfwu1IVlwt3++Pd/v89sV2vYHRrQza1hVBc7pvdyYFovB3oU5NZsgNPVo0DHDUPcuGGIGxFTYd3RKJYfCuO9E7ZeLHeKhsF+nyJren/ju/7FebJMJc6uCZS7BMpd+RV3e6VMw9pRwOeBCvgBXYcoKIbI8b9B1M6ZBmx/+TG03Vtb7jZzAeSlt2YoKKKTSykpcOGFF+KNN97Au+++m1Bs8KabbsLHH3+MV155BbfccgsWLFiAQCCAJ554Am+//TaEELjiiitSDp6IrDus+7zxAX/jwb+B6pOsAw6ZsQrsaVwv7NTQKLlgJRqKGicX7BocGiAVYCrAlMp6VICpGj2XJ37euF+sTVrPpVIwVPw5YMT6Nnmu0OHu+rc1qeJ71ptY0ui4XQPOKLaSBMUOgd2xZRdVofz8/gsAnZ3WgLDcpaFL7KPx8y6xAWMXl4Zie9vc5c41Dl1gSk8HpvR04BdjrURkfVihi0tDgb39f/2UOcqIQhlRIBqFDAWgjAgQNQBNgygohOC+7pRtSkF/4n5om1e22E2OuQjmwh+C01kol6S0JeGePXswaNAgOJ1O7N27F927dwcAGIaBCRMmYOPGjU3eFCml0L9/f2zcuBGdOnVKLfo2wC0JKRfF11U3Hvjvjj0/4Jft6g4rUaYU2UVsYC/Qxdl0kN/4eSengM47kEQZoZQCDAPKjEJFIlChAJQZtZIAAoBug9Bt1lIB/rOkHKG99ghsL/+lxT5yyCgYP/oL4OhYWwBT6+TtloQDBw7E7t27YZomSkqOV3a12Wx45513cPfdd+P5559HNGoVsRJC4LLLLsNf//rXnEwIEGVbXVjG7vQ3uuPvtab7t+eK2e2NANC3SMPgUhsGl+gYUmrD4FJr2nR8GblSgIL10fhzNPN54+eH9u/FxjUr4fN6rLbY/oPx9q49e2P0+Cko6dTZen0FSFjrwLfXmfiyzsBXdQa217ff3ykBq/7BoFIbzijW0aOg6WC/3KWlpRYCEaWuIQlgRKCiEahg0EoCGI2SADY74HAzCUA5SVv5+kkTAqrnABj3PsSEAOWklGYKtIbX68WOHTtgGAYGDx6csFNBLuJMAWprQcOa7r/He3zwH08E1OTgtl+UnEsHziixBv6DS/WGJMAZJba0bynnra/Dmvffwb6dXzXb7i4swoQLZ2LQ0HNaNW1dKoX9vuOJgu11Br6MFfiL5ElR//j3f0ipjsEltoafwcBiPeNb+hFR61lJAGs5gIqGoYIhKCMCIU0oCAibDuh2KxnAf8qU48SWj2B7+F4IM/nOLKq0C6L/+W+ga6/MBUZ5J29nCrRGcXExzjvvvLS/7saNG7F48WJ88skn2L59O44dOwaPx4OSkhIMHToUl156Kb7zne/kfBKC2qeotAZcVlE/KwGw22Ngj9dEhV+CQ//80skprLv9JbGBf6mOISU29C7U2nxKuWma2LJhLTauWQnTaPqGQwiBc84bhzGTpsHhdLb6dTUhMKDYhgHFNszqe/w8Q1q7MFiJgthjvZW8ylYhxnKnaPi+xwf/Q0qt7z8rthPlvoYkQDQ2EyAUgDIMCNOAEgLCZoewOyBsNvBfNOUTsfcL2P54X8sJAVcBjB/8LxMClNPafKZAW7nrrrvw5z//ueFzl8sFu90Or9fbcKxLly54/fXXMXHixFa/bnymwL83VWJAtzIU2wVKHRpcOjpE0ShqPVMqHPJL7PEasUG/lQDY7TVxwJf7lezdulVoMMfDzJiGKf+N7jjHp/53zlK18UP79mD18qWor6lutr177z6YPGMOyrt1b/NYwqbCbo+Jr+qMhpkFX9Vbuzak43coPuW/cdJlcKmOQaU2dHaygBhRPlFSAmYUKhqFioShwkGoaNSaCSA0CFusHoDePnbkoA7q2CHYf/01iPrm/0YDgNJtML73P1AjWj8WoY6rXcwUkFJixYoVWLNmDSorKxEIBPCb3/wGPXv2bOgTiURgGAZ0XYfzFO5oNef888/HgAEDMGXKFAwdOhRlZWUAAJ/Ph5deegn33Xcfjh07hiuvvBLbt29HaempLQX42vv1gPv4HFqbAEocAiUODSV2gWKHlSwotouGxEGxQ1h97Frs0epfHHveVlu1KaUQkda09EDsI2Qefx400Oj58cdgQh8FqazCW4V2a5u5YrvWsOVcYezrLIpVlS+2aw3Hne14Xa5SCpVBaQ32Y3f893gM7PZag6Fcn2btjk2vPqNExxklOgY1el7q0KCUQsgE/FEFvxH7iCoEDNnw/MTHgJF4LNBMv1xOiLh1YEBJfMB//M5zW0z5P11+rwdrV7yL3V9ta7bd5S7A+GkzMOSckRlLVjp1gbM72XB2p8Q/G0FDYUe9VafgqzorafBVvYFD/ub/cbh0YFCju/2DYomXgSU61/gT5SklJWBEjicBIkGoqHE8CWC3QThdELrOmQDUPvjqYH/w/7SYEAAA87b/ZEKA8kJaZgq8+eabuPvuu7F3796E41u2bMGwYcMaPv/rX/+Ku+66C0VFRaioqEBhYWGql05q2bJlmD17NgDgqaeewsKFC1t1XnymAB76CnAXpzWmAls8URBLKtjjiQSt4bhDE0kH7Q3PTSQM7gNZHoTZNSuZUBRLIBQ1ShgcP3ZCmy2eeLD6uW0CugA0CGjC2qVFF9Ye6BoERPy5ADQg1ic9by2UUqgJK6uqv9dskgAI5ngxNk0A/Yp0nFGsNxn89yjI/PRqpRTCEgicmFAwVMOxiKmga4AurJ+79bzR5/HnDccTP9eEgC32+6ALwKaJ48+FgKbFn1t9rT7I+anm0jSxdeN6bPzoQ0SjkWb7nH3uGIy74EI4Xe4MR3dqvBGJ7fUmdnoMREygT6E1C4BT/onaB2WaVj2AgN9KAhgGhFKxmQA6YHNwm0BqnyIh2H73HWg7P22xm3HNdyHnfSNDQVF7kNczBR555BHccccdiOcWunTpgqqqqmYHbLfffjv+7//9v6irq8Mrr7yCm266KdXLJzVhwoSG5wcPHmyz65yK+KC+MpjtSNIrKoHasEJtQ5G8zIyiBRITBSI2AGycODj+IRr1SUws1IQkPNEcvrUd08UlGgb7g2LF7M4o0dG/SIcjh+6wCiHg0gGXLsCKHq13+MA+rF6+FLVVx5pt79qjFybPnIOuPXo2255rih0axnTVMKarPduhEFGaWLUBIpDBIFTQCxWOAEJAOOwQrgIITeNMAGrfpAnb33520oSAedE1kJffnqGgiFKXUlJg586duPPOOwEA06dPx5/+9CcMHToUWpLMsMPhwDXXXINHHnkEy5Yta9OkwMqVKxueDxo0qM2uQ9mjAJgKJ8ySSDa4z/1BP3B8uv+gkvhdf+v5wNh0f2p/An4fPv5gOXZu29Jsu9PlwrgLpmPoyNGsa0JEWaFMAyocggz4oEJBQJpWYcCCIog2LrZKlDOUgv70A9A+eb/FbnLUVJg3/we4dQblk5SSAn/4wx8QjUYxfPhwLFmyBA6H46TnXHDBBXjkkUewefPmVC7drHA4jMOHD+ONN97Az3/+cwDA4MGDcfnll6f9WkSnyyaAvkXWoH9gsd6wl/oZJTp6Fmgc+HUQUkps2/wJNqxagWgk3Gyfs0aMwvkXTIeroCDD0RFRR6eUAiIhyFAQKuADohEoXYdwOK1CgUQdjLbkcejvPtdiHzloOIzv/hbQ+W+E8ktKv7HLly+HEAL33ntvqxICwPG79vv370/l0glcLhfC4aZvqidPnoxFixa1WNQwHA4nnOvxeNIWF3VcAtYa6oGxu/0Di627/WcU6+hTpMPOOysd2pGKg1j97luoPnqk2fbybt0xeeYcdO/VJ8OREVFHZxULDEL6fFCREAAF4XAAhSXgny7qqLQ1b8H2/7d333F21XX++F+fc26f3tInyZBGQnqjhBajFMWCijSplrWs+1sV1wK7gK6y8oV1V9RdXRAERUBFsYD00EJL741MeiZtkky77Zzz/v1xzi1T7mRmcvt9PR+Py7331M8dTmbu+30+n/fniR/3u40Mb4Txz/8NePO75g9RX04pKbBnzx4AwOzZswe8T6y4YFdX16mcupsRI0YgFAqho6MDnZ2dAIDFixfj7rvvxtixY/vd96677sKdd97Za/mCYW6E3S60RQVtEQttEYFRGD3QKYtG+LV4sJ+cABhbwUrq1FuoqwvvvPYStqxb3ed6j9eL+YsuxNTZ81IOwyIiSjexLEgkBOnqhBXqgjKiEJcbyh9gsUAqeWrD29D/7/Z+t5HKWkS//hOgsiZLrSJKr1NKCsS6OQ9mAoPDh+0iWpWVlady6m6SZz04dOgQHnnkEXz/+9/HwoULcdttt+G73/1uyn2//e1v42tf+1r8fVtbGxobG/GL86swrDYxjWFs6rYTEQvtUcGJiKA9YjlJA0F71HKWOUmEpOVtEUFbVNCRoWJ2Xg3wu+wK/gHnkfzap6PP5X49sczvsgv0dTrtbI/aU9J1RPt4GBY6o4L2qMS3L+aESZ1XockJ9k9zxvc3VdiPMje/LNHJWZaFLetW493XXkY41Hel0YnTZuDMC5YgUFae5dYRUamSaLiPooFeKJ+fBQOJAKjdW+G67xtQppFyG/H4YHz1v4HhjVlsGVF6nVJSYNSoUdi+fTu2bt2KefPmDWifV155BQAwfvz4Uzl1SsOGDcPXv/51nHfeeTj77LPxve99DwsXLsRll13W5/Zer7ff4QUxSin4XYDfpWPEENtmWnYgbScV7ORCm5NEiCUaopakDNoTgT2SAn4FV4778yXPdd9hWCkSCYKOqL2uW0LBsF+HTYEl9rEsASzAeR977SyPPRB7LUnbOPsM4TNUulW3O/5NFa54AoAF/uhUHNy3B8teeg5HDh7oc31NXQMWvf8SjGwcl+WWEVEpihcNDHZCgl0sGkiUgtq7Ha57vwIV7Ei5jWg6jH+8G3LaGVlsGVH6nVJS4Pzzz8e2bdvw6KOP4uqrrz7p9keOHMHPf/5zKKXwvve971ROfVILFy7Eueeei1dffRW/+MUvUiYFsknXFKq9CtVeoBF6rpuTNomEiUI9ch9AiwgEdoLAlOTkgnRLKojz2qUB1R7FAn+UVp0d7Xjn1ZdSzirgdnsw95zzMX3uAmh68fw+IKL8Ey8aGA5COlk0kKhf4SD0P/0c2rOP9ttDAADMG2+FzDo3Sw0jypxT+kvw+c9/Hg888ACefvppPPjgg7jppptSbrt37158/OMfx5EjR+ByufD5z3/+VE49IKNHjwZgT51IpUMpBQVAUz0vcAb9lHmmYWD9ynew6s3XEY1G+tzmtCnTcNaF70dZRfqGURER9cSigUSDIAK1cilcv/5/UK0tJ93c/NjnYV3wscy3iygLTikpsGDBAnzhC1/A//7v/+Kzn/0snn76aVxxxRXx9WvXrsW6devw3HPP4bHHHkMoFIJSCl//+tcxceLEU278yezYsQMAUFFRkfFzERHt3rEdb778HNqOtfa5vrq2HucsuQijx52W5ZYRUalg0UCiITi8H65f/xDa6tcGtLl5/sdgfuwfMtwoouw55T5j9913Hzo7O/HII4/gySefxJNPPhnvhn3ttdfGt4sVI7zxxhvxgx/84JTOaZomNK3/+dxffPFFvPPOOwCACy+88JTOR0TUnxPHWvHmy89hz46+eyW5PV7MW3Q+zpg9n0MFiCgjEkUDOyDhMIsGEg2EEYX2zCPQ/3w/VCQ0oF2smYtg3vBtgMNOqYicclJA13X86le/wkc+8hHcddddWLlyZZ/bTZs2DbfddhuuuuqqUz0l9uzZg4997GP44he/iA984ANoamqKJwj27NmD3/zmN/j3f/93iAhqa2vx1a9+9ZTPSUTUUyQSxuq33sC65W/Bsqw+t5kyYzYWnLsYfmc6ViKidBEjComE7aKBoSBgGiwaSDRAatNyuB6+C2p/84D3sSbOhPHlHwIudwZbRpR9SgYzn+AA7N+/H8uXL8ehQ4dgmibq6uowZ84cTJgwIW3n2LlzJ5qamuLvPR4PKisrEQwG0dnZGV/e1NSEP/zhD5gzZ86Aj93W1oaqqiqs2n2025SEREQxIoLtm9bjnVdeRFdn31WJh40cjXPedzEaRo7KcuuIqJiJaUAiYUiwC1a4CyoatYsGulk0kGhA2lqh//ZH0Jf9bcC7iKbDuugamJ/4IuDxZbBxVMosCzjR3oGZ0ydl/dxpTwpkQyQSwVNPPYWlS5fi7bffxoEDB3DkyBHouo6GhgbMmjULH/3oR3HNNdfA7/cP6thMChBRfw63HMCyl57Fof17+1zvLyvHwvPfh0nTZnBGCyJKC7EsIBK2Zw8IdkAiEUBp9vAAN+9YEg2IZUJb+kfov7sPqqt94LtNmg3zhm9DGrMfqFFpYVIgjzApQER9CXZ24t3XX8aWdav7XK9pGqbPOxNzzjoXHq83u40joqIjIkA0DCuUlAiAgvK4AZeXw5mJBkHt3AT9V3dB27F+wPtIeTXMK/8J1rkfAVikk7Igl0kB9jMjIuqHZZrYuHoFVix7BZFwuM9txoyfgLPfdxGqa+uy3DoiKiYiAhgRSDgMq7MDEg3Z06S53FB+1gkgGrSuduhP/g+0F56Akr5r//TFPP9jMD/1FaCiJoONI8ofA04KvPrqq2k/+fnnn5/2YxIRpcu+Xc1Y9tKzOH70SJ/rK6trcNbiizD2tIkcKkBEQybRKCQSsgsGhkNOwUA3lI/TCBINiQi0t5+D/tt7oY73/Te8L9aYiTBv+A5k8uzMtY0oDw04KXDhhRem9UuvUgqGYaTteERE6dJ+4jjeWvoCdm7b3Od6l9uNOWedhxnzFkJnYS8iGoJEwcBOWKEglBGF6C579gB/INfNIypcLbvhevguaBveHvAu4vXDvPwLsD5wFWcWoJI06G+zLEFARMXKiEax5p1lWPPumzBTJC0nTpuOhecvQVl5RZZbR0SFTkwTEg1DQkFIsBMwohCl2YkAnx/sb0R0CiJh6H/9JbS/PQRlRAe8mzX/fTCuuQWoG5HBxhHlt0EnBfx+Pz760Y/iAx/4ADR2aSOiIiAiaN66CW8tfQGd7W19blM/fATOft/FGDG6McutI6JCJiJAJAQrHHIKBtrBivJ4gEAFWCaA6NSpdcvgevg/oA71PTNQX6RhNIzrvgmZdW4GW0ZUGAacFKioqEB7ezuCwSAef/xxLF26FNdccw2uu+46zJo1K5NtJCLKmNbDh7DspWdxYM+uPtf7/AEsOO9CTJ4+m4lQIhqQXgUDIyEAYtcJ8JexYCBRurQegv7ovdDffX7Au4jugvXBG2B++GbAO7ipy4mK1YCnJAyFQnjqqafwyCOP4LnnnoNhGPEaA9OnT8d1112Ha665BqNGjcpogzONUxISlYZQMIgVb7yCTWtW9DksSimFaXPmY94558Pr45cGIjo5u2BgEFaXUzDQMqHcbsDtZcFAonQyDWgvPA79yf+BCnUNeDdr6nwY138bGNWUwcYRDU0upyQccFIg2eHDh/Hoo4/ikUcewcqVK+0DKQVN03DhhRfi+uuvx8c//nGUlZWlvcGZxqQAUXGzLAub167C8jeWIhwM9rnNqLHjcfbii1DbMCzLrSOiQiPRiF0wMBzsXjDQ44XS9Vw3j6joqO1rof/qB9B2bx3wPlJZC/Pqr8E6+1KAswVRniq4pECyTZs24eGHH8ajjz6KPXv22AdVCn6/H5dffjk+/elP46KLLiqY6bqYFCAqTiKCA3t24a2lz+PooYN9blNeUYmzFn8A4yedXjC/s4gou+JDAyJhu0dAJAxlGhBdh3J7oTgjCVFmdJyA/rv7oL3yR6gBhi+iFKz3fRLmJ/4RKGOBYMpvBZ0USLZ06VI8/PDDePLJJ9HWZhfrUkph+PDhuO666/DDH/4wXafKGCYFiIpHJBzC3p3N2NO8HXt37kBXR3uf2+kuF2YtPAezFpwNl5tTERFRd2JZQDQMiUTsREA0DFgm4HJDudxMBBBlkgi01/8C/fH/gmo/PuDdrPFTYd7wHchpZ2SubURpVDRJgZhQKIQ//elPeOSRR/D888/DMAz4fD50dQ18zE+uMClAVLhEBK2HD2JP83vY07wdB/ftPek0qk2Tp+LMC5agoqo6O40kooIgpglEI7AiIUiwExKJABA7AeDycGgAUaaJQK1dBv3P/wdt+9qB7+Yvh/nJL8N63ycBjf9OqXDkMimQkdR2rL6AUopdcIkoo8KhIPbubMbene9hb/N76OrsGNB+NXUNOHvJRRg9lsWGiMgmpuHUBwhBQp2QqAE7EeCG8gdYLJAoGywT2rsvQPvrQ9B2bxnUrubZl8K86qtAdX2GGkdUnNKaFHjllVfwyCOP4Pe//z3a2+1uuiKCkSNH4rrrrkvnqYioRIkIjh5qifcGOLR/30l7AySrqKrG9HlnYtrseZxikIjsGQOiYUgoCAkHIdEIoDQoD6cPJMqqaATaG3+D/vRDUAf3DGpXGTEOxvXfgpxxZoYaR1TcTjkpsGnTJjzyyCP4zW9+g7179wKwv7QHAgFcfvnluP7667FkyRJ++SaiIbN7A+zAnma7N0Cwq3PA++q6jhGN49DYNAGNTRNRVVPLHkxEJcwuFBiFREKwgl12oUAjCtF0KLcbqqySxcmJsinUBW3pk9CfeQTq+OFB7SpuL8wPfwbWB68H3J4MNZCo+A0pKXDo0CH89re/xSOPPIJVq1YBsP/IapqGxYsXF/SUhESUeyKCIwdb7AKBze/h0IHB9wZobJqIxqYJGNk4Dm4PvygQlTIRSSoU2GH3BjAMwOWCcnugfH4wD0CUZR3HoT//GLTnH4fqPDHo3a2Zi2Bc901g2JgMNI6otAw4KdCzeKBpmvEv6dOnT8d1112Ha6+9FqNGjcpYY4moeIWCXfHeAPt27hh0b4CRjePQ2DQRY5omsDcAEcVnDLDCIUiwy5kxwLJnDHB7oPyBXDeRqDS1HoL+7K+hvfwHqHBw0LtLzTAY134DMv99YLceovQYcFJg2LBh6Oy0v6SLCEaMGIGrr74a1113HWbPnp2p9hFRkRIRHGk5gD3N27Gn+T0cbtk/qN4AldU1GOMMCRjVOI5TCRLlAbtrfgRI/rfc75f2VOtSLE+5uYo1AGJEE4UCI1HECwX6WCiQKKdadkN/+lfQ3vgrlBEd9O4SqID1gatgXno94GdvZKJ0GnBSoKOjA0op+Hw+fOQjH8FFF10EXdexdu1arF078GlCkl1//fVD2o+ICpOIYOf2Ldi5bTP2Nu9AKDjwaUp1lwujGsdhjDMsoKqmNoMtJaKBEssCjAisUNId+W5JgVR7pgr8B7u8x/uoASgF5XaxUCBRHlC7tkD724PQ3nkBSqxB7y/V9TAv/jSsxZ9gMoAoQ5QM8NZcbIrBtJ1YKRiGkbbjpUtbWxuqqqqwavdRDKutynVziIpGZ3sblj7zZ+zfvXPA+1TW1MYLBI4cM5a9AYjyRJ9d80WgXC7A5UnMDZ7yK0aK5f19JRloTyLdxR7FRHlAbVkJ/a8PQlv7xpD2l2FjYH7wBliLLgM83jS3jij/WBZwor0DM6dPyvq5B1VocDBde4mIYnZu24JXn/0rwqH+xw7avQHG24mA0yagspq9AYjyhVgWEAnDioQgwU5IJAKI5RTqS9E1P2V0zqidqCiJQK19A/pffwlt6+ohHcJqnATrspthLVgC6GmdPZ2IUhjwv7SXX345k+0goiJkRKN4a+nz2LRmZcptqmpq4wUC2RuAKL+IaQLRCKxIMJEIAOwx+uyaT0QxlgntnRfsYQK7tw7tEJNmw7zsJsisc1lAkCjLBpwUuOCCCzLZDiIqMkcPHcRLf/0jjrce6bWurKICsxacg8bTJqKyuiYHrSOiVMQ0IdGwXawv2AGJ2kP97DH65UwEEFFCNALtjb9Cf/pXUAf3DOkQ1oxzYH74ZsiUuWluHFGByWGvfPbJIaK0EhFsWPku3n71RVim2Wt90+SpOO+iD8Lr8+egdUTUFzENSDQCCQUTVfuVgvKwRwAR9SHUBe3lP0D/+6+hjh8e9O6iFKwF74d12U2QcadnoIFEhUeCnVBuX07OzaQAEaVNV2cHXv37X7Cn+b1e61wuN85echGmTJ+d1qKlRDQ0YkTtRECwCxIOQqJJiYCyCvbeJaLeOo5Df/4xaM8/BtXZNujdRXfBWnQZzA/dAIwYl4EGEhUmCYcAlw6tojon52dSgIjSYk/ze3jlmT8j2NXZa13dsBF432WXo7q2LgctI6IYMaKQSBgSCsIKd0EZBgQKyuNhIoCIUjt2GPozD0Nb+iRUuP+iwX0Rjw/W4k/AvOTTQO3wDDSQqHCJYUAMA3ptA3sKEFFhMg0D77z2EtaveKfP9TPnn4X5514I3cVfN0S5INGoXSMg1AUrHISKRiGaDuX2AAE/ODKAiFIyotCe/Q30P/0CKhIa9O5SVgnr/VfC/MBVQAVrCBH1JJYFBLug1dRC+csAIzft4Ld0IhqyY0eP4KW//hGthw/2WucvK8eFl34EY8afloOWEZUuEQFiPQLCQVihIJQRheg6lMsDVe7nhIBEdFJq+xroD34f2t7tg95XquthXnIdrAs/DvjLMtA6osInAkhXB7SKSmjl1c6sG7kpNsikABENmohg89qVePPl52EavVOaY0+bhPMvuQz+AL8IEGWaWBZgRp0eAU6xQCMKZRp2IsDthfIxEUBEA9TZDv33P4H28u+hBlkNXYaNgfnBG2Cd+2HA7clQA4mKg4Q6obx+aBU1UJpmJ/VzhEkBIhqUULALrz33N+zctqXXOl3XceaFH8C02fNYTJAoQ8Q07J4ARhQSDkOiIUjUgLJMiNKgXC4otwfKH2AigIgGTgTaO89B/829UCd6TyfcH6txEqzLboa1YAmgM7wgOhmJhgEo6FW1UG53rpvDpAARDdz+3Tux9Omn0NnR3mtdTX0D3vehy1HbMCwHLSMqXmJEAcOAGFFYoS4gGoEYht3vUHeSAD4/lKYxCUBEQ3NoL1wP3wVt3ZuD2s2aNBvmZTdBZp0LViolGhgxDEg4Ar2uASpPpuhmUoCITsoyTaxY9gpWv72sz/XT5szHmecvgSsPMp1EhSxeDyA+XWAQYtpJAUAA3WUnAfxlUKwQSESnyohC+/uv7UKC0fCAd7NmLrKTAVPmZrBxRMVHLIEEu6BV1UAFKnLdnDgmBYioXyeOteLlv/0Jh1v291rn8wdw/iUfxrgJk3LQMqLCJ5YFGJFEPYBwEGI4QwGgoFw6lMsNeP28CUdEaaW2rob+0Peh7XtvwPvIqCYYN3wHcvq8DLaMqHhJsBOqrBxaRXVeDbVlUoCI+iQi2LZxHZa98HdEo5Fe60ePa8KFl34EgfL8yXIS5bvu9QBCkEjISQJYdj0AtwvK44XSdQ4FIKLM6GyD/sSPoS99csC7iNsD8yOfhfXBGwAXewUSDYUVCkK5XXYdAV3PdXO6YVKAiHqJhEN4/fln8N7mDb3WaZqGBee9DzPmn5lXGU6ifGMPBTDs7v/RKKxw0C4sFK8HoDv1AAKsB0BEmScC7a2/Q3/0Xqi21gHvZp1xFowbvgUMH5vBxhEVN4lGAMuEVjMcKg9n5mBSgIi6ObhvD17625/Q0Xai17qqmlq877LLUT98ZA5aRpQbIgJYFgABLAFgAZZlL4+tE4FYpv3aMiGmmXg2DEDBrgegu4AAhwIQUZYd3A3Xr/4D2oa3BryLVNbCvOYWWGddzCKCRKdATBOIhKFV1UHz5+d03UwKEBEAwLIsrH7rdax887U+50mdMmM2zl58Edye/MtuEg2EWBYglhPYS/y1iB3Ux99bJmCagFgQwwRg2stjSYH49oBSAhGF+G1+pQFK2UUAlWI9ACLKLSMK7elfQf/z/VB9DAVMxbzw4zA/9U9AWWUGG0dU/ETsOgJaeRW08vz998SkABGh/cRxvPz0Uzi4b0+vdR6vD+dd9EGcNmVaDlpGNDgiAphGfAo/iYTtcfyWE+Q7wXzs7j5E4gF7IhWmAE0BSrOHyGgK0DQopQEulQj8VXxrIqK8o7ashOuh70Ptbx7wPtboCTBvvBUyeXbmGkZUQqSrA8obsGcb0LRcNyclJgWIStx7mzfi9ef/hki491REI8aMxeIPfhTllVU5aBnRyYlpAmbUnvM3GoGEQokp/BTsYF6zg/h4kK/sIN9+nzgWg3siKgodJ6A//t/QX/3TgHcRjw/mRz8H65JPs5AgUZpIOAS4dOg1tfbwwTyW360jooyJRiJY9tKz2Lp+Ta91SinMW3QBZi08B1oeZzWptNiF+6L2nX+ncB+iEYiZVL3f5WKXfSIqTSLQlv0N+m9/BNV+bMC7WTPOhnH9t4FhYzLYOKLSIoYBMQzotQ1QHl+um3NSTAoQlaDDLfvx0t/+hLZjvasPV1RVY/GHPobho/jlgHKr2/R9kUh8+j6Yhn23X3fZU/e5y6A0xTv9RFS6WnbB9asfQNv47oB3kap6mNd+HdbCi1hIkCiNxLKAYBe0mlqoQHmumzMgTAoQlZDjrUex9t03sXXDWvsXVg8Tp07HovdfCo/Xm4PWUSkTy7KHAUSdJEAomBgGILCHAbh0KI8XSg/kurlERPkhGoH2t4eg//WXAy4kKErBWvxJmJ/8R6CsIsMNJCotInYdAa2iElp5dcFM382kAFEJONxyAGveWYbmrZv6XO/2eLDo/Zdi0rQZWW4ZlSJ7GIB9x9/uBRByegGYUJYJUcoeBqBx+j4iolTU5hV2IcEDOwe8j9U4yS4kOHFm5hpGVMIk1Anl9UOryO/Cgj0xKUBUpEQE+/fsxJq3l2HfrtSVh4eNHI3FH/ooKqtrs9g6KgXiVPeHWHYCoFsvACOpGKBu9wLw+aE0jcMAiIj6034M+mP/Bf31vwx4F/H4YF7+D7AuuoaFBIkyRKJhAAp6VS2Uu7D+nTEpQFRkRAQ7t2/BmreX4XDL/pTb6bqOmQvOxtyzz4Om61lsIeU7EbGn7IMAltjPcJYJIJKYzi/2EMu011umPRTAEgCmvU4EMEwoCASKxQCJiIZCBNobf7ULCXYcH/Bu1qxzYVz3LaBhVObaRlTixDAg4YhdWNDnz3VzBo1JAaIiYZom3tu0HmveWYbjrUdTbuf2eDFt9jxMn7cQgbLCKH5CQ2MH96b9MC07mE8K9uPBvWnYwbtp2nf1Y+tjSQFxkgIigAAKAihlHz8e1StAUwAUlPMMzZkGUNMAt4/FAImIBkMEOLIf2uYVUFtWQtu8Eurw3oHvXl0P49P/Apm/hIUEiTJILIGEuqBV1kAVaJ0OJgWIClw0EsHmdauwbvlb6GxvT7mdP1CG6fMWYtrsefB4839qFBo4MWOBvwkxjUTV/mjEvoNv2skApcSO75MDeaXsLvxKsxcrZ5mm28VxdACahkSwn8CvmEREaSQCHGiGtmUl1JZV9nPrwcEfRilYSz4F8xNfAgKFGaAQFRIJdkIFyqFVFE5hwZ6YFCAqUKFgFzasWo4NK99FOBRMuV1FVTVmLjgbk8+YCVeBjW+iBDvwtwDLsF+bph30R6OJZbFeALGgXtPsYn1uPV7spjD/VBERFSHLhNqzze4FsGUl1JaVUO3HT+2QYyfDvPE2yITp6WkjEfXLCgWh3C67jkABD8dlUoCowHS0t2Hd8rexee1KGNFoyu1qG4Zh1sJzcNqUadAKqPppKbOn5TMBMbsH/pEIIAbEtMfsKxGIUvY0fZpuJwDcnoKqcktEVHKMKNTOjYleAFtXQwU70nJo8fhgfuJLsD5wFaDz6z1RNtg3ZkxoNcOh3J5cN+eU8LcGUYE4fvQI1rz7JrZvXAfLslJuN2JMI2YtXITGpgkF24WpmElsDL+VFPibBiQSBswoxBLANKFgQeCMydc1O/D3uJ1u/bzjT0SU9yIhqPfWQW1eCW3rSqjt66AiobSfxpp9PozrvwnUjUz7sYmob2JZQDgIrboemr8s1805ZUwKEOW5wwf2Y/U7y7Bz2+Z+txt72iTMOvMcjBjdmKWW0UBJNAqJhCDhICQatu/4m7Fq/ACUZt/11zUolytelZ+BPxFRAQl2QG1bE68JoHashzKNjJ1OaobZhQTnLWYhQaIsEgGkqwNaeRW08spcNyctmBQgykMigv27m7H67WXYv3tnyu2UUphw+hmYtfAc1DYMy14D6aSSEwFWKAhlRCG6npiOz8Nq/EREBa39GNTW1Yl6ALu2QEnqnnzpIEpBGifDOvMiWEuuAPycRYgo26SrA8obgFZZXTRDN5kUIMojlmVh57YtWPPOMhw5eCDldrrLhSnTZ2PG/DNRWV2TxRZSf+KJgFAXrHAokQhwe6F8fiYAiIgKmQjU5hXQ3n3eHhKw773Mn1J3QZqmQabMhTVlLmTiLKBApzwjKgYSDgEuHXpNrX2Tp0gwKUCUB0zDwLZN67D2nTdx4lhryu08Xi+mzZ6P6XMXwl9W+OOXikEsEWAFOyGRMBMBRETF5sRRaK//Bforf4Q6uCejpxK3FzJxRiIJMGEG4PVn9JxENDBiGBAjCr12GJSnuKb3ZlKAKIcikTA2r12F9cvfRmdHe8rt/GXlmDHvTEydNRcerzeLLaS+MBFARFTkLBNq/Vt2ImDVqxmrDSC+MsikWXYC4PR5kPFTgQKvYk5UjMQSINQFrboWKlB8w3aYFCDKgXAoiPUr3sGGVe8iHEpdibiyugYzF5yNSWfMhMvFf665ZE8NGO6RCHDZUwEyEUBEVBxaD0J79Snor/4J6mhL2g8vZVVOL4A5kClzIWMncwpBojxnFxZsh1ZeCa28uihn9+JvIaIsikYi2LDqXax5501EwqmTAXXDhmPWwnPQNHkqtCIpYFKImAggIioBRhRq7RvQlz4JtXZZWosFSnU9rCnz7ATAlLmQUU0A/64TFRQJdUJ5fdAqaoqmsGBPTAoQZYFpGNi0dhVWv/U6gl2dKbcb2TgOsxaegzHjTyvKLGQh6JYICIegTIOJACKiYnRoL/RX/gjt9b9AHT+SlkNKw2h7KIBTEwDDxnC6QKICJtEwAAW9qg7KXTyFBXtiUoAogyzLwvaN67Bi2avoaDuRcrtxEydj1sJzMHzUmCy2jmL6TQT4A0wEEBEVi2gE2sqXoS39I7SN75zy4WRUUyIJMHkOUDciDY0konwghgEJR6DXNkD5irvgJ5MCRBkgImjeuhkr3liK461HU2532pRpmHP2eaitb8hi6zJDLAsQC7AEgAVYFkQESFoulgmYBsQ0AQBK1wEoQNcBpaCUZt9RUbCXK5W0HPH3zhvnSUvabuDhOxMBREQlZH+z3Svgjb9CtR8/pUNZYybCuuByWGdeBFTVpad9RJRXxBJIqAtaZQ1UCUwDyqQAURqJCPbu3IHlry/FkYMHUm7X2DQR88+9EPXD8/OOQrdgXiQR1Isd7NsBvwkYJsQ0AMsEJJYEkPh+scBaYgd2AnilKfuwEbHXCuzzJLZM7K/sbROJgthzUiIgljCAAqABmrLHfCnNHrupaYmEAwAr1MVEABFRsQsHob37IrRXnoS2dfUpHUo8PlhnXQzrgsvtaQI5JICoqEmwEypQDq2iqiSG9DIpQJQmLfv24N3XXkbL3t0ptxkxphELzl2MEWPGZrFl3cWCeDFNwDQBid3BN+3lhgnAdJIAseSA2EG6EogkBeaaApRm/7LUNDsQdznLtMQv0L5+lQ7m12s8uZCcPLCs5IX2QxK9Eiyrn4SDpjMRQERUpNTurdCWPgntzaehujpO6VhW0zS7V8BZFwP+4puGjIh6s0JBKLcLelUtVInMDlIan5Iog44easG7ry/Fnh3bU25TN2wEFpy3OKsFBMU0Acvpqm8YTnf5iLPMgBIn6I/dYe8W4Cs7cHaCfXu5fdxcBtEquUfASaq/MtgnIiohwU5obz9r1wpo3nBKhxJ/OaxzLoV1wcch46akqYFEVAgkHAQsC1rNMCi3J9fNyRomBYiG6HjrUaxc9gre27wx5TZVtXWYv+hCNE0+PWPJAInd4TcNe7y+YUDCocTYfct0utpr9hj+2F1yTWPgTEREhUsEasd6OxHw9rNQ4eApHc6aNBvWhZfDWvB+wFvcRcWIqDcr2AUoBb1uGDR/Wa6bk1VMChANUkfbCax88zVsXb/GvtPeh/KKSsw953xMOmMmtDTNZyqWBZgGYNoJADGikEgYMKN2l3/LAiB20K9rgOaKB/9EREQFz7KAE0ehDu+F2rkJ2it/grY3dS+9gZDyaliLPgTzgsuB0aelqaFEVEhEAOnqsIcMVBf/TAN9YVKAaICCnZ1Y/c4b2Lh6BSynen5P/kAZZp91LqbOnAPdNbR/XnbwH6vS7zwiYcCIQExnHWAX2XM5d/69bqeSPxERUQELdkAd3g8c3gd1eB/Uob1QR/ZDHdoLHDkAFQ2n5TTWtAWwLvg4rHmLgRLqIkxE3dkJgXYojw96TR2Ux5frJuUEkwJEJxEJh7D23bewfsU7iEYjfW7j8Xoxc8HZmD53Idye/r9ciFO0Lz59nzPuX4woEI1AjIhz598uAgilAbp99195vAz+iYiocBlRoPWgHfAf3gd1aB9wxH5WR/ad8nSB/ZGqeljnfRjm+R8Dhjdm7DxEVBjEEjsh4AtAr6kvqRoCPTEpQJSCEY1iw6p3seadZQiHQn1u43K5ccaceZg5dyG8Xg9gmbBCXYnp/GLT+HWr7G91n77PMqHg1MbXXXbw7/bYrznon4iICokI0H48HvTj8F6ow/vtLv+H9tkJAavv3nYZaY7SIDPPgXnB5ZBZ5wIud9bOTUT5S0wT0tUJraISWmUNVIn/bmBSgEqeWJZzVx4ALJjRKLZsWIfV776Frq7OPvfRNA1TJk3GzDNmwO/zASeOwnCmvYtPnxffOrmyPxJF/2LT92m6vSjDn5OIiChtwkGorauhWnYlEgCxrv6hrly3DlI7Aub5H4V1/keBuhG5bg4R5RExDCDUBa2iClpVLXvhgkkBKkFiGkA06hTqC9kPS2CZJpp3NWP1unVo7+x7XmOlFCY0NWH2zNmoqKgAoNlBvqYBUFBaIrRnkE9EREVDBDi4G9qa16GteQNqywooI5rrVnUjugsy+zyYF3wcMuMsQOMXfSLqTqJRSDgIraoWWkU1C3I7mBSgoiYigGFAzCgkEoGEgxAjAhiG/QVH1wFdx+79+7Fy9QocP3485bHGj2/CnDnzUVNTk70PQERElCuRENSmFdDWOomAw3tz3aI+ybAxMC+4HNa5Hwaq63PdHCLKUxINQyIRaNX10CqqMjZdeCFiUqDE2UFzFOIUuFNKd4ra6YDmsl8XUAbNrtwftbOA0QgkFLQL+JmGfUdfd0HpLiDgByDYv38fVqx4F0eOHE55zNGjx2DevAWor2/I3gchIiLKhUN77d4Aa9+A2rQ8bdX+00Wq6iENoyENo4DhjbCmLoBMnuP02CMi6puEgxDTgl7bABWoYEKgByYFSkz8zrkRsbNlwSAkGoGyTIjSAAiUiP06VvHe5QHcHqhYQK070+DlwfgbMQ07qWFEIWFnKIBhQFkWRGlQLheU2wPlD8T3MQwDO7ZtxsaNG9DaejTlsYcNG4558xZg5MhR2fgoRERE2ReNQG1ZCW3tG3Yi4MDOnDZHvH5Iw2igYbQT/I+GDBsNaRgD1I8EvKU3fzgRnRor2AUoBb1uGDR/Wa6bk5eYFCgBEguaI04SwHCSAACUyw3l9UHpevcx8AL77rqYsMIhoKvTrqYPe/y80nX7rrvHa1frdLmc3gVOwiAD2bfkoQCIRmGFg5BouNtQAOVyQfkCUJrWa0x/R0cHNm3agK1bNyMcTn3no7a2DvPmLcCYMY3MIhIRUfE5esBOAqx5A2rjO1DhYNZOLUoD6oY7Af8Y+45/wxgn8B8NVNSAU+8QUTqIANLVAeV2Qa9ugPIxqZgKkwJFKF5ILxqBFeqyx9BHDUAhcefc5eq3EJ5SAFwuAC6oHjN0iDO9HsworI4wIJY9pZ5SznAD3T6H23tKQxG6DQUwIpBgyE4IGPZnSR4KkOr7g4igpeUANm5cj927d9mJhRQqKysxd+58NDVNYDKAiIiKhxGF2rYG2trXoda8AW3fexk9nZRVJYL85Dv+DaPtmQBKfOovIso8OyHQDuXxQa+pg/L4ct2kvMakQBEQ0wSMSLyapkTC9jh6EcDltu/ke1IHzoOlnOJ8QI8K+5Y4yQIDVrAT6Gwf1FCE7kMBwpBoCBI1oMSEwBkK4HID3pN/FsMwsH37NmzatAHHjrX2u21FRSVmzpyFSZOmQOOYRCIiKgbHDjtDAl6HWv82VKjvKXZPhVRUw5p+NmTc6Yk7/g2jgEBF2s9FRDRQYomdEPAFoNfUQ7k9uW5S3mNSoACJZTlJgEhiHH3UsLv363bgrAK+rPe+U5qyewT07IUwkKEImguwDHveULGShgL4+xwKkEp7e7szRGALIpH+iyONHj0G06ZN5zABIiIqfKYB9d46aGteh1q7DNruLRk5jdV0BmTWIlgzF0GapnHaPyLKK2KakK5OaBWV0Cpr7BuKdFJMChQAeyx9xJ5SLxKGRIKQaBSwYsGzG8pfZgfleWhAQxEsw04QDOFziAgOHNiPjRvXY8+e3f0OEXC53Jg0aTKmTTsDVVXVg/4sREREeUEEOLIf2paVUGvfgLbuTaiu9vSfpqwS1vSzIDPPhTXjbKCqLu3nICJKBzEMINQFraIKWlVtXhRFLxRMCuShbtMERiOQUBckGrWLA2o6lDtRTK/QJQ9FGKxoNIr33tuGjRs34PjxY/1uW1lZhalTz8CkSZPh8bALERERFRgjCrVrs10bYNsaqO1roI4fyciprLFTnN4A50ImTAd0fl0kovwWG0atVdVCq6guijgpm/hbPgPEsuwMPsSpcgEAzjLnvUDsO/3x7QCIQCwTEgrZMwSYRmJavb5mCChRbW1t2LRpA7Zt24JIJNLvtmPGNGLatOkYPXoMhwgQEVHhaD8GtW0ttO1roLatgWreCBXtf1jcUImvDDL9LFizFsGasQioacjIeYiIMkGiYUgkCq26HlpFFb/zDwGTAilIJAgJeezgXZwAPjl4FyegN01ALDsRYAkAZztLnH2RlAxIJADsa1XsRd0uXAXlcqr3+wNMAjhEBPv374sPEeiP2+3GpElTMHXqGaiqqspSC4mIiIbIsoADO+M9ALRta6BadmX2lGMmQmYugjXrXMjEmZwRgIgKkoSDENOCXlsPFahgQmCImBRIwTpyEEakMx68A8ru1h+/0JT9WgFQmrM49t4poKecbivK2Raq13h5Xrb9i0Yj2LbNnkXgxInj/W5bVVWFqVOnY9KkSXCzyigREeWrcBBqx4ZEAmD7WqjOtoyeUrx+yBlnwpq5CNbMc4C6kRk9HxFRplnBLkAp6HXDoPnLct2cgsakQArK44ZW3n1KHQbw2XPixIn4EIFoNNrvto2NYzFt2nSMGjWa2UEiIso/rQft4D9WC2D3VijTyPhpZeR4WLPOtWcKmDwHYMKciIqACCBdHVBuF/TqBiifP9dNOmURU9BlCFw5KoXApADlDRHBvn17sXHjeuzdu6ffbT0eT3yIQGVlZZZaSEREdBKmAbVnm50A2LbGrglwtCUrpxaPDzJ1vtMbYBEwbExWzktElC12QqAdyuODXlMH5fHluklDJiIImUDQFHg0oMarUOnJTVaASQHKuUgkgm3btmLTpg1oazvR77bV1dWYOnU6Jk6cBLeb4x+JiCjHOtug3luXmBHgvfVQ4WBWTi0uN6TpDMikmbBOXwCZOg8o4C/IRET9EUvshIAvAL2mHqpAez8ZliBoCAwBfLrCSL+Gco8Gr567Hs9MClDOhMNhbNiwDhs2rDvpEIGxY8dh2rTpGDlyFIcIEBFRblgW1P5muwbAe2uhbV8Ltb85a6eXylrIpFmwJs6CTJ4FGTeVQwKIqCSIaUK6OqFVVEKrrIEqwOKoIdNOBmgKKHcpVHk1lLkUdC33sQ2TApR10WgEGzasx/r1a/udUtDj8WDy5NMxdeo0VFRwiAAREWVZZzvUjnV28L99LdSO9VBdHVk5tSgFGT0BMmlWPBGAYWN6zFhERFT8xDCAUBe0iipoVbVQup7rJg2YJXYiIGwCXh2o92mocGvwu5BXNzqZFKCsiUaj2LRpA9atW4NwOPVcyzU1NZg6dTomTJjIIQJERJQdlgW07HQSAOvsJMD+HVAiWTm9eP2QCTPsBMCkWZDTZgBlFSffkYioiEk0CgmHoFXVQquohtJyVIlvkKKWXTjQEiDgUqj3270CPDkcItAfJgUo4wzDwJYtm7B27WoEg6nHWY4dOx5nnDEdI0aMzKvMGRERFaFghz3+f7szDGDH+oxPC5hM6kfawwCcngAyZiKg82sZEVGMRMOQSBRadR20iqq8jw9ihQNDpkBXQKXbHiIQcCloed52/vWhjDFNE1u3bsGaNavQ1dWZcrvx40/DnDnzUFNTk8XWERFRyRABWnYlhgFsXwu1773s9QLQXZCxUxK9ACbOAmqHZeXcRESFSMJBiGlBr62HClTkdULAtARBUxCxBD5NYbhfQ7lbg8+Vv23uiUkBSjvLsrB9+1asXr0SHR2px16OHTsOc+bMQ11dfRZbR0RERS/Yad/5374O2nvOcIDO/me3SScpq7JnBIj1BGiaBngLfx5tIqJME8uCBDuhXG7otQ3QAuW5blJKEdMeIgAFlLkUhvt1lLkVXHlQOHCwmBSgtLEsCzt2bMeqVSvR3p66C+bo0Y2YO3ceGhp4l4SIqGiJAJZpj9W3TMA0nOfYMsN5bS9TpgGI5SxLWmdZPfY1oeLrzMT2hgG1bwfUe2uh9myHEit7H3VUE6yJMyET7Z4AGDEOKJBxr0RE+UKiYSAchlZeaQ8XcHtz3aReRARBwx4i4NGBGq9CpcceIpDPvRlOhkkBOmUigubmHVi1agVOnDiecruRI0dh7tz5GD58RPYaR0REmdPWCtW8Eap5I7TmjVC7twDtx+wg3zJz3bqMEH855LTpkIkz7ETAhBlAGWfIIaLiYgpgWICmAJfK7MQnYgkk2AnoOvTaYVCB8rwrKGg4hQMNC/C7FEYGNJR7NHjztHDgYDEpQEMmIti9exdWrlyOY8daU243fPgIzJ07HyNHjspi64iIKK06TkDt3OQkADZANW+Cam3JdasyTkaOhzVhBmTiTPsx+jRAK5zpsIiITsYUIGoBhpMIENjJALeyl3cBsOxe8tAV4NKcZ2VvdyokGgHCIahAOfSqmrzrHRAy7SkFNQWUu+zCgWUuBb0Ahwj0h0kBGjQRwd69e7By5XIcPXok5Xb19Q2YN28BRo0aXdDdaYiISk6wI54AsJMAm6AO7811qzJOfAGnF8DMRC+A8qpcN4uIKG1SJQA8CvDrgN8NeHXArdmPWI8BQ+xHyADCln2MoCSSBbEeBclJg/7EewdoGrTqemjllXnTO8ASOxEQtgCvBjT4NFR4NPh0FG1Mw6QADZiIYP/+fVi5cjkOHz6Ucru6ujrMmTMfjY1ji/YfDhFR0QgHoXZtTiQAdm6COrAz163KChk+1qkF4DzGTGAvACIqGv31AOgrAaD38b1dV4AnOVb32DFBLEkQSxiETDtZYFh24sASe8iBQlKywEkYSDRq/+3xl9m9Azy+jP8sLBFYThLDFKfsDQSmsyyZUoBfV2jw270C3EUyRKA/TArQgLS0HMDKlcvR0nIg5TbV1TWYO3c+xo0bz2QAEVE+ioSh9myNJwDUzk12cb4sFuXLFfH6Iaed0b0XQAWnwiWik4sFjfncYzwdCYCBUkrBrQA3APTIoxpW94RB2LITBlEL6LQAs92eplyrqIWnvBIuTYfbEuhqcHfhJRbkA/FgPxb4m2J//vi2sJMSmgI0AJpScOmAC/ZMAR5d2euch64UvLq9XalgUoD6dejQQaxcuRz79+9LuU1lZRXmzJmHpqbToOVJtx8iopJnRKH2bu+eANi73a7yXwJk2JgevQAmAjq/9hBR/0SAiBNcRy0Azt1uwAk0nYAzOVxUTrCp4kGnvVxLeq+QvmJ9PRMAsTYmJwA8un2H/1QTAIPl0lSfAaYRjSLa2QmzugxWRS0Mtw9BUxA1gaBpF/CLhfJ2jwIVv5sfC/p73NDvFeh7dQWXBriUHezrPQL95MC/lAL+gSjYv45Hjx7Fn//8Z7z44otYuXIldu3aBcMw0NDQgPnz5+OGG27A5ZdfnutmFqwjR45g1arl2LNnd8ptyssrMGfOPEyYMJHJACKiXGs7BrV5ObTNK6B2bLB7BBjRrDdDlAa43ICu213xdR3QXPYUffFlLkhsndLsYD32Pmkbe50O0Vw9jtfjtXMO8fohjZMgE2cAlbVZ/+xEVFhEEsF/1Ak8Y2PjPRpQ4wTXbi2xfezOtDjPpmUvMyzAQPJda8S7pltJ54NCIqvgPCcnDuIJhKTXyXfekxMAPh0I5DABMBAiAgl2QBOBv74eWkUNlJ7oXmCJnRCIWonnkCGIWHYSxaspuDU72NeTA30o6FriZ6cNsqcBdadEpGfSpSC43W4YRuJuh8/ng67r6OzsjC+79NJL8fvf/x6BQGDAx21ra0NVVRVWrFyLhvr6tLa5ELS2tmLVquXYtWtnym3Kysowe/ZcTJo0hckAIqJcCXZAbVkJbeO7UBvfgbZnW9abILoLMmai3S1//DRI0zS7Or/LnfW2EFHmmZK4I16IYuPfI04gD3ESALp9h92n28G2R7PvVA+ViMBC9yRCciIheZ1pAWZS20R6bxNrY0DL7wRAT2JEIcFOKF8Z9Oo6KP/AYzIRYZCfRQXbU8AwDCxcuBA33ngjLr74Ypx22mkAgJ07d+Lf//3f8cADD+CZZ57BP/zDP+CRRx7JcWvz3/Hjx7Fq1XI0N+9IuY3fH8CsWXMwZcrp0JMyfERElAWRENS2NdA22UkA1bwJyjKzdnrRdMjo0+zAP5YAGDMR8OTX9FFEdOpiAarp3KFOrjAvcO54OzSniFzsDq6u8iNx0KuLPZwq+xpQ6QL8rkRw7U7zXWallD3UfgiHFJF48iD27CqABEAyu3dAJ2BZ9swCldVQgxy+xYRAdhVsT4GXX34ZixcvTrn+C1/4An7+858DAHbv3o3GxsYBHbfUegp0dHRg1aoV2L59K1JdCj6fDzNnzsbpp0+Dy1WweSQiosJiRO1aABvfhbbxHajta7I2HECUAkaOhxUL/pumQcZOBrz+rJyfiLIjOfiPCuKDtmNd6N2afQfdvnNuLxPY28ceEcsZg28llsXucgOJZELPxEE6C7r3rAOQXGTPqwNlrkQPALfG8eSZlOgdEIBWXQfNX5brJtEAFGyE119CAAA+85nPxJMCy5cvH3BSoFSEwyGsXbsaGzdugGn2fafJ6/Vi+vRZmDbtDLjd7ApKRJRRlmXXAdjwjt0bYMtKqHAwK6eW4Y3dEwDjTgf4RY6oaCTPM2/0CP5jgXOVlgiaY1PHDebutIh0SxbEHoaTNIg44+8jTnd5SSocp5RdxL5n0qCvHvwDrQNQKF3si4kV7ARME1pVnd07gEPJCkbBJgVOxudLzHeZKugtRYZhYOPG9Vi7djUikUif27jdbkyfPhNnnDEDHo8nyy0kIioRIsCBndA2OkmATSugOk9k/rT1IyHjp8GKJQDGTwXKKjN+XiLKLEnq7h97iNPtPzZHvE8H/M64dJcaWvCfilLKPl4/21gpEgdRJ1kQtRLvY2PxgUTl/lj1/1gvhgp3+uoA0NCJaUC6OqC8Pmh1w6H8Zez+X2CKNimwdOnS+OsZM2bkriF5wrIsbNu2FatWLUdXV1ef27hcLpxxxgxMnz4TXi/HiBIRpd2R/fZQgI3v2omA40cyejqpboA0TYPVdAakaSpk/DSgsiaj5ySizEoZ/Dt3212xaek0wJ0U/OdDt3nNmRauv/vHZj89Dtxa5uoA0NBIqAsSjUKrqIFWVQPl5g3FQlSUSYHjx4/jrrvuAgCcd955mDJlSsptw+EwwuFw/H1bW1vG25dNIoJdu3ZixYp3ceLE8T63UUrh9NOnYvbsufAPoiooERGdxImj9uwAm961nw/vzejpZOR4WFMXwJq2ADJxFlDTkNHzEVFqse7xyUXjkrvM97U83rNfErPWAUhMXwc7+NeQGO+fHPzHuv7nOvg/FbpSaa03QJkhlgnpbIfyeKEPGwUVKGeSpoAVXVLAsixcd911OHDgALxeL+67775+t7/rrrtw5513Zql12XXgwH4sX/4ODh8+lHKbpqYJmDdvPiorq7LYMiKiIhIJA8cOQR07BNV60H59eD/U1lXQ9r2X0VNL3QhY0xZCpi6ANXUBUDsso+cjKibdAvE+XiPpvdVzm9hKIB6wJ7+NzSUfe99z/vlYYK9rzhj62Gs4D62P/ZL2dxVB8E+FS0JBSDQCraIaWlUtewcUgYKdfSCVr3zlK/jJT34CAHjggQdw880397t9Xz0FGhsbC3r2gdbWo1i+/B3s3bsn5TajRo3G/PkLUV/Pu0hERCmFg0DrQajWg1DHDjmvD0EdOwg4z6r9eNaaI5W1sKYugExzkgDDxuR+3i+iLIsVmjOT5n7v6257X99wk++89wzaewbeKikY11QiYI8H76rvgD0W8Pd1rO6JAf7bpcIilmnXDnB5oFXXQZVV8DouEkXVU+CWW26JJwR+9KMfnTQhANgV9otl/Hx7eztWrlyO997blnKburp6zJ+/EKNHj8liy4iI8owIEOyAaj0EHLMDfTiBf/xuf+tBqK723DYzUA45fX48ESCjJzAJQCUlNpbccKbMi42dd8G5W651D9i1FHfbTx6gp3rNf29EACDhIBCNQCuvhFZZC+UpjviJbEWTFPiXf/kX3HvvvQCA//f//h/++Z//ObcNyqJQKIQ1a1Zi06aNsCyrz20qKioxb94CNDWdxj9wRFTcohGg/RhUWytw/LBzZ7+PoD/Ud9HVXBKPDzJ5dnxIgIw/HdD0XDeLKONid/9jU83Fq86rRGX5Kt2eOi82dp6F5ogyTywL0tUBuFzQ64ZDlVVCaVqum0VpVhRJgW984xu45557AAB33303brnllhy3KDui0Sg2bFiHdevWIBqN9rmN3+/H7NlzMWXKVGj8B0xEhciIAm3HoNpb7ee2Vjvobz/mLD8GtLUm3oc6c93iARPdBZkwwx4OMG0h5LTpAMdmUpGLTTlnprj7X+kCfC476HdzrnminBARIBoGwiGosgro1XVQHt/Jd6SCVPBJgVtuuSXeQ+Duu+/GN77xjRy3KPMsy8KWLZuxevUKBIPBPrdxu92YMWMWzjhjBtzu/iZ+ISLKMiMKtB/vEcy39gjynSRA+zGoro5ctzhtRCnI+Kl2YcBpCyGTZwNef66bRZQRPe/+m5Lotu9y7v5X64DHmWfexbv/RDkVSwRIJAIFAVweqNph0Cqq2TugyBV0UiA5IXDPPffg61//eo5blFkigubmHVi58t2UUydqmoapU6dh5sw58Pv5RZOITpERBSIh5xGGcp4Ty0JQ4ZB9N6HbNkn7dLYnuvO3H8v5OP1ss0ZPgExbaE8TOGUuUFaZvmM7hdasPl67ugVZaTslUZ9id/9jSYDku/9u5+6/35XU9Z93/4nygliWnQhweh0rtxtaZQ2Uzw/l8UK5eHOxFBRsUuCb3/xmPCHwn//5n/jqV7+a4xZl1v79+/Duu2/j6NEjKbeZMGES5s6dj4qKiiy2jIjyjoh9J761BTjaAnW0Beg4AZUUuCMSgoqEgUgwRcDvbGOZuf40eU88PqB2OKR2GKRmOOA8S91wyPhpQPXgZrKxelRVN3sE+4AT5Euiynms0FosEaArIGwBERPociY715EcjKXzJ5Bb8SJ0zp1o3bkD7dGYDMmEWOE/M2kGgOS7/z4d8Gu8+0+Uz8Q0gGgEYkQBKCiPB1p1LTRvAPB4oXTWsik1BTkl4e7duzFu3DgA9p3xhob+p9W75ZZbBlxnoK2tDVVVVXkzJeGRI0ewfPnb2L9/X8ptxoxpxPz5C1FbW5fFlhFRzkRCQOtB4EgLcPQA5OhBqKMtUK0t0I62QGttsRMAdMrEXw6pGWYH+rXDgRr7OR781w4HAhX9Rp+SFNCbTqAfD/yB+PzmyXOba7CD29iUZ7Gx1S6t9zo9OTGQ1A4RQdQJliMW0GUAIROIxOZTl0SSoBB6E/TVFR2wP79b2QXofBoQshKfE7CTIUwSDF4s2RIL/mNT/OkqkXzy6YBX491/okIgRhQSjdg9ADUdyuODCpRB8/oAj4/DA0pcQfYUSK6wb1kWDh482O/2HR2FNx61ra0NK1a8i+bm91Ju09AwDPPnL8TIkaOy2DIiyijLgpw4CjnaAjnaAnWkJR7wq9YW6K0t0NqP5bqVRUHKqyG1w7oH+jUN9mtnOfzlAz+eUzQtaiWKpwGJac9igbuuALdu/wH2aM6c5yp1sD/UO6xKKXicu+ZlAGo8gCWCiJMkCJtAp2m3t0sSAZ8nD3oTxH6WhvOztJy70brq3hU9ltBwa90TIoZlf86wBXQ6yZAThr2OSYIESQr6Yw8kXbexcf9Vuv3schIAdlKgxH94RHlORAAjComGoUwTorugvD5oNfX2dIJuL3vwUFxBJgXGjx+PAuzgMCDBYBdWr16JzZs3pfyMVVVVmDdvIcaNG89/zEQFRASwgp2JgP+o3b1fS7rDrx87CGUauW5qQRN/OVBZA6moASprITU97vLHAv5TqKKcHLRGnIA6FkS5k6ZO03vdyT+1QP9UaUrBp9t3eOEGGgBEnQA6GutN4ATSsW7hbi0RHGai2VbSWPSelejdGlDutnsAdO/V0H9DXJqCSwMCsJMhpZ4kiPWySK76DyA+rMSlAL/T08KjJwf+vPNPVEjsQoERSCQMBYG43NAC5VC+Mrs+gMeb6yZSnirIpECxERG0th5Fc/MObNy4HobRd0AQCAQwZ858TJo0mdMLUk5IrAtpH6+B+A2mPtfHXzvbJN817fa6gL9/mkljwc1QEGr3Vui7N8O1azNce7bAdWQftBIrspcO4isDKmoglTXOc22P907wX2G/T/eUfn3etXaCVo8OVDoJgMT0aYV1Ebs1BbfzJ6U6qTdBNKk3QcQCggbidQw8WmK8+GB0K0Zn2b8P+kqmxIdLpGkseqkkCayk4D827j/2M9Zh//8qczlJFj3xc3f1GHpCRIWjW6FAESi3h4UCadCYFMiRcDiMffv2Yt++Pdi7dy+Cwa6U23o8HsycORvTpk2Hy8X/ZTR0yWNyDcsezxwbWxy/caSQ9Kb7a5W0uNtrlVgWK3ymkrpEa7HlSd2oDTjBgZV09wqJBELs+2msS7WuEt2H9RyMf46NAY8H/WK3FwBUZxtce7bAs2sz3Ls3w7V7M7SWnVBF2qPpVInXnxTEVycF+T2Dffs9snhnI/ZvpNsQgKQEQIVzlz3dQWs+Se5NUOEG6pEIoiMWEDQTj1inllgxObeWSOz1LABoH9vezq8DfrdTjC6eYMjez7HQkgSxuhSpClDGtoklWFwKqHABPlfifbFer0SlSCwTiITtGgFKixcKVF4nEaAzXqDB4RWTJSKCo0ePYu/e3di7dw8OHz500iEQuq5j2rQzMHPmbHi9Q+/mSqUp9oU8lgAAEA9u3Jr9hdGlJapG9wzs+3uNk2438C+dItLty25y4G04QYiR9HkiVqJoW/wszl2wvsdjD6QNSedF4nXyP1EVu9PWdgTePVvg3rUJ+u7NULu2AIdTFwItaG6PXYjI67MDc48P4vbC8vhguu2H5fHZ4xK9Pmheb7xgkf3w2pX540mAajvI9+bHdKnJSbKIZV9TsTuqPbute0o8oEoOoqth9yaIFTCMWE5vAhMIGb3H/5fHxv8r5G0xulwkCSTpd05fU0vGkrKxO/2xhGrs95w7lpxSdl2KWHf/WBKgVK9VomKVKBRoAJoG5fFBq6hmoUBKCyYFMigcDmHfvr3Yu3cP9u3bi2AwOKD9lFKYOHEy5syZh/LygRe5otIUG49rSveCXD3vyLnz9O6mUioe0PdHRHoF7bEkQtRK3Nk1neeQs60kJQ+UkyyIf+lOWp7cI8GrAx4lcB07AG3nZmDnZsiuzbB2boYcSz0taD5RVbXQ64ZDqx8JrX4EtJoGKF/AvoPgBPnK40sE/V6fM97QXgaPt98vGNKjYF2HExQazs81duc4X7pg91W5XiFxB7XGM/hx66VMUwpep6s/ANTBDqRjhRaTZ0woxG7pQ00SCHoH97HfWbFeJ7HfSbFEqp70+8frXH8u2IF+LAHQe5hV4f1MiWjwxDIhoSCUaSQKBVbX2X+3WSiQ0ohJgUGIdWsGkp6TxlJbIjh69DD2792D/fv24OiRw4MqiFhWXoERo8di4uRpqKmpgabsL9vJdz+pdPXs+p88VjQW2FTEpodKUZG7kCml4BrAR7FiyYM+7v5HnOEKLucLfLwInFhQB3cDOzfDbN4Mc+dmGM1bYHWciHfNzSseH/T6EXawXz8Cel3S6/oR0OqG24F9BqmkoLDCDdQ5098lV7UPO3eOY3UlgKTeHSc9QVo2AZAYIhOrrF/ltpNlTACkl0tTcMH+2RabgSQJ2pwkQbyoJJLu3DvXWV+9mRLLeA0SkU0sCxLqAkwTqqwcWqDCmTHAw79XlBFMCqQQNIFjkcS80UlP3V5HQiG07N+Dlv17cHD/XoTDoQGfQ9d1jBgxCmPGNGLM6EZUV1dCKRW/0xkrGBTrLh27yxDLSKgeXygUmEAoFt2KcUn3atyuHt1xY182OT2UTVOq3+tfjCjMfc0wmjfD2LEJRvNmmLu22n9884FS0KrrnSB/ZJ/Bv6qozrsvBcnT35W77DvH0aRx6CdLj8YTrCfZUDCAYyU9KyTu4jIBQOmSKknQ8+8yA30iGgwRAcJBwIhCeQPQ6mvsXn4cGkAZxqRACo1+oKqsR0E1BViWhYOHD2Pn7j1o3rMHBw4dHtRxa6uqMGFsIyaMa8S40aPg7qdwYHJ36dhdTyvpzqeR1GWaCYTCFPv/FqtqHrujqjtdb3064HemiEpOABRyUCMigGnY4+KiEYgRtZ+jEWc+3d7LB7INjGjf+xgRIJrYxzy8H4hGcvb5lb8s3qU/uXu/7iQBtNqGoqkUHKtqX5brhhBlWCxJQEQ0FHYyIAREwoA/AK26HipQzmQAZQ2TAimUu4Byp69yZ1cQ7+3Zg/d27cGOPXsRDA28N4DL5cL40aPiiYDaqqoB7zvQ7tJAehMIUN27PybPrc0kwtAkB/+GJKpHJ3f9L9cT40ljCYB8KsYllgUJByHBTkhXh/3cz2sreXmwA9LVGX8fL1le5PSR46A3TYGraSpcTafDNX4KtMqaXDeLiIiI8oREQpBQCMrrhTZsJJS/HEovwnFYlNeYFEhh36HDWLV9J97btRsHDg+usFhddTUmjGvEhLGNGDdqZFamEUx3AsFwKr6bTkXuWDIheQo7+8SIz1udnDSIFbortUTCyYJ/l7LniPb2uPOvZ+nuv0QjsI62wDx8ANJ+HNLVCSvoBO9dTvDeZ7DfCQl1nrxvd6nSdOhjTrMDf+ehj5sMLcBCoURERNSbRMKQcBDK7YVWNwxaeSWnEqSc4ZWXwqNPPw+fb2CFutwuF8aPGY2J4xpx2thG1FRWZrh1p2YwCQTALtzWVzXl5NcDTSQk5xKSEwl6ciJBDXwquVwZaPDv03sXmcpk8G8FO2EdPgDryAGYhw/AOnwA5pH98WVWgVTOz2tuD1xjJ9mBf9Ppdi+AsRMyXtiPiIiICp8YUbvXpMsNraYeWlkllNuT62ZRiWNSYIjqa2riSYCxo0bCVcTdfE5WuK0vPRMJZo9kgtlj7vnkqeViSYSBDGvIdCIhebq/XAf/IgJpO2YH+0f2x4N+68gBmEdaYB0+AOlsS+s5S53yBezu/+OdHgCnTYU+anzRjPknIiKi7BAjCgkFAU2DVlVn9wzweHPdLCIATAoMmMftxvgxo+3aAGMbUV1Zkesm5bXBJhJEpN+eCJlOJPQM/k2JfY7EmP8yLbPBv5gGrGOH7bv7yXf7j8Tu+LcAkYHXs6DBURXVzrj/0+E6zU4CaMMbWeSHiIiIhkxMAxLssr+TlldBq6iE8vpz3SyibpgU6EdDbS0mOrUBGkeOgF7EvQFyTSkFHXaQPVDpSCRYQLwmQl/Bv9uZY/pUgn8xopD247BOtMJqOwar7Rgk9toZ328dOQDr6CHAMod0DhocrXYY9KTg39V0OrS6EQU9qwMRERHlD7FMe7pjS6CVV0ArrwK8fn7XoLykRFg5LFlbWxuqqqrQvOItNI4dl+vmUJrFEgnx4QzOcABdDTz4F8uEtJ+wg/oTrZC21sTr5MA/toxd+rvTXVC+AOD2QLndUC5P/DVcHntcXXx59/X9b9t9ecpt/AFoAfb0ISIiovQTy7KTAaYJVVYOraIayhdgMoDyGnsKpFBZFsh1EygD+uqRIJYF6WqHdaIVRjyob3WCeiewb7efrROtkI4TpVmF3+uD8pdD85dBBcrsKXP8ZfYj+X3Sa63ndv4yOzDnH0YiIiIqIiIChIOAEYXyBqDV19jJAA5DpALApACVBIlGYB7cC7NlN8z9u2G17IZ5YDfMlt12Rf5S6bbvckOrHwG9YSS02uFQZZVOEF8GzV8ef616vvYHOE0OERERUQ92MiAERMOALwCtuh4qUM5kABUUfssnAHbQLKEu+5dYgQZ/YkRhHd7vBPt77OcDu2Ae2A3rSAsgVq6bmHHKXwatfiS0hpHQY88NI6HV28+qqo5/pIiIiIjSQCIhSDgE5fFCqx8BFaiAYg0yKkCFGf3RKbOOHUZ00ypEN69EdNMqmLu32V3ilYIqr4JWVQutqhaqshZaVQ20ylooZ5nmLFNVtfZd5Cx2BRfLhHXkoHPHf5f9HLvjf2g/YBpZa0suqMqaeJDfPfAfBa1+JFRZBbvmExEREWWQRMKQcBDK7YVWOwxaWQWnK6aCxqRACRARWAf32EkAJxFgtexJtTGk/TjM9uMw9+44+cFd7kQCIZ4wSEomOMvsdTV20beBtLf1kH2HPxb0O3f8zYN7ASM6yJ9AgVCa/Yelj7v89rIRnMKGiIiIKEfEiEKCnfb335p6aGWVA/puS5TvmBQoQmKZMHdvR3TzKkQ3rkR08yrI8SOZOZkRhXX0IKyjBwe0uQqUd0seaJV2jwOYRvyOv9myxx6bVSw8vm6fVauM9bywkyZ6/Qho9aOg1TYwy0xERESUR0QEMA1IKAhoGrSqOmjllVAeb66bRpQ2TAoUAYlGYLy3MT4UwNiyGtLVketm9Um6OiBdHbAO7M51U4bO6R2hKp0APza8orImadiFvUyrrIHy8e4+ERERUT4SEbvgtGUBlgkxndcQKAgECtB0aOVV0Coq2WuTihKTAgXICnbC2LoW0U12LwBj23q74ikNjabbNRLiQX5SUF9Vkwj2K+1tlL+M4/aJiIiICkCvoN+yANNEt6BfaXahbV2D5vECLg+UywXoLrtAs6ZzSmUqakwKpGC1HYOUlwMeX85/AVhtrYhuXo3oxpUwNq+EsXNr6Uyhly6aDq1hFPSRjdBHjoM+ciz0EWOhjxxrV4st0BkXiIiIiEqZiNgzTJnmqQX9ugvQtJx/7yfKBSUikutG5JO2tjZUVVVh23nDUOHS7Gr8voDdBdwXiL9WvgCUN/baed9zfdJreHss6ycINQ/vt3sBbFoFY/MqmPuas/LZVVWdPeygUHsdKAWtfkQ82I8/jxwHbdgojtcnIiIiKlBiRO2x/bGgXywohXjQD12H0nX7+16fQb8OaDqDfqI+8PboyYhAgp12pdF0cnt6JxA8Ppgte2AdbUnvufqiFPTxU+A+fQ7cU+fAffocaNX1EBFIqAtyohVWWyusE62QE8fir60TrZC2Y/brtlZI23E7O5tFWk0DtFjQP2pcIvgfPoZFX4iIiIiKhFgWEAlBohHA5YZyubrf6dfsRACDfqJTw6RArkQjkGgE0n48O+dzueGaOD2eBHBNmQUtUNFrM6UUlL8M8JdBH9F40sOKZULaTySSBE7iwHISB4nkwjFIW+uAkyuqsqZXN//YaxbuIyIiIipeYkQh4RAgAuX1Qa+qtXveutwM+okygEmBIqX8ZXBNnhXvBeCaOD0jd9GVptvT7FXVDmh7iYS6JwycB8SC3jDK7gEwcmyfCQsiIiIiKk4iAoRDkGgY0F3QyiqgyiqgvH57CAARZQyTAkVCVdY4vQDmwj11LvRxk/KyeJ7y+KDXj4RePzLXTSEiIiKiHBMjComEANOE8vqg1Q6D5i/jkFCiLMq/qJEGRGsY5fQCmAvXtLnQR45jdyoiIiIiynsiAkTDkEgYUBq0snKogNMrQNdz3TyiksOkQApa/UgoKwIJBYFIKNfNgd44we4FcPocuKbOhV43PNdNIiIiIiIaMDENSDgEZRqAxwutuh5aoAxwe3lziyiHOCVhD7EpCY9uXouqugYATjG9UBAS6gKc58QjCAkHu79P8RrJ2wW7Ulft111wNZ0O99S5cE2dA/eU2dAqqrP3QyAiIiIiSgO7V0DEHiLgFLTWyipPOkU3EWUP/yUOgNJ0qEA5EChP2zHjvyC7JQ86oVwe6KPGs8I+ERERERUssUy7V4ARBdxeaFV1dq8Aj4+9AojyDJMCOaKUAjxeu4hKZU2um0NEREREdMokGrGnEwSgfH5oNQ12rwCXO8ctI6JUmBQgIiIiIqIhE8sCIiFIJAJ4PNAqa6D5ywCfn70CiAoAkwJERERERDRoYkTtulkAlNcPfVidPYOA25PjlhHRYDApQEREREREA2L3CghDomHA5YZWXgVVVm4nAzQt180joiFgUoCIiIiIiPolRtSuFWBZUD4f9MrhUL6AXR+LiAoakwJERERERNRLbAYBRKOA2w2trBwqUGH3CtD1XDePiNKESQEiIiIiIgLgDA+IhiGRMKBpUF4/tJp6KI+PvQKIihSTAkREREREJS4+laAIlNcLraYBmj8AeHycQYCoyDEpQERERERUgsQ0IOEQlGlA3J5E0UCPj8MDiEoIkwJERERERCWi2+wBmg7lD0ALVED5/FAud66bR0Q5wKQAEREREVERExEgGrHrBEDsOgEVw+zhAW4vhwcQlTgmBYiIiIiIipAYUUgkBGWagNsLrbIGmr8M8PqgNC3XzSOiPMGkABERERFRkRDLdIYHRADdBS1QDuUvt4cH6PzqT0S98TcDEREREVEBs4cHONMIQkF5/dCraqG8fk4jSEQnxaQAEREREVEBklidAMuC8nigVddB8wUAr591AohowJgUICIiIiLKYyICiAAQwLIg0QiUEYW43NDKKqECZXavAE4jSERDwKQAEREREdEp6ha4x1/DeW05zwAgPYJ85zl+IMC+yS8AlL2ZgrNQAUpBeX3QaurtRIDbk8VPSUTFiEkBIiIiIqIBiBfxM6KwO+fHAncnkk8K3GMPBWUH9Zpmr9M0aJoGKOehafZ2zrO9vI/9k9e53BweQERpw6QAEREREVEKYllOIiBiB+keP/TKGkB39R+495EkYCBPRPmISQEiIiIioiRiWXY1/2gEdjV/L7SKBmg+P+DxMbgnoqLCpAARERERlbzEtH4RAHCq+dcnEgGaluMWEhFlBpMCRERERFSS7ESAM62fiJ0IqKq1p/XzeFnNn4hKApMCRERERFQyRAQwonYiwDKh3F5olTVQ/gCUx8dEABGVHCYFiIiIiKjoiRGFREJQpglxe6CVVUIFyqC8PiidX4mJqHTxNyARERERFaVuiQCXG1qgHMpfbicCXO5cN4+IKC8wKUBERERERUNiQwMMA3C5oHwBaIEKOxHg9uS6eUREeYdJASIiIiIqaGIaTiIgCmg6lM8PrbbCrhHg8ea6eUREeY1JASIiIiIqKCICWKY9c0A0YicCPD5o1XVQXh/g9kIpletmEhEVBCYFiIiIiCgnxLIAsQAR52EBlkAkthz2M2BPGQhAoABlP5THB72yxk4EeHxMBBARDQGTAkREREQ0ZBIP5p3gPSnQF8sCIIAl9rMACgIoBQGc4F6zA3ylAZoCdBeUrkFpuvNaBzQNgAI0LbGd0gC3h4kAIqJTxKQAERERUQET07DvsgOJO+72m6Tl8f84QXzyNkjsG3/jvFcqvq8dfMfWK+cQEg/qoWJBu/0MTYemaYDmAnTdDu5j2yZv5wT7UFpiORERZQ2TAkREREQFQkwDMA2IEXXuyAOI30kHFBQQi6njQTcAOM+asgN1pQA4d9sBJyi3d1RJr+PbxV4nLVex5ZrqFuxDafYxiIioIDApQERERJSHxDIBI5YAMO3x9EqDcrvjU+zB5YbSXUlBfe8AnnfeiYioP0wKEBEREeWYWBZgRJ2eACaUWBBNh3K5oPkDUF6/nQBwue1n3oknIqI0YVKAiIiIKIvEsoCkYQBKBKJpULobyuOF8vrtZ5cL0N32WHwiIqIMYVKAiIiIKENExE4AOMMAFMSeUs/lgnK5oZVXQbk9dgLA5WECgIiIso5JASIiIqI06JYAMA27EKCCM+7fDa2sIpEAcHvsWgBEREQ5xr9GRERERH0QywIgTpV/AcSKT/knlpU0/V/StH4ul1MHoArK643XAIDuYsE/IiLKS0wKEBERUdEabGCvIIBSToyv4tPsKaXZd/01DdB0aLoOKB3QdbvLv9LsO/8ul90zgAkAIiIqEEwKEBERUd6R5GDdsuyF8QDfXi7xIB/2M9A7sI9N0xcL7DXVT2CvAKU526pu76HsKf9Y9Z+IiIoNkwJERESUNtLjbnziYQfvEluXFNzb71UimLffdgvooVQiUNedoF7TEkG9psW3Y2BPREQ0cEwKEBER0UnZXe0tpxu+/SyWaQf2YkEpZScEYt3sYwF4crd7aFCasrvZKy0RzMcC91hXfaikfVT3YD+WHCAiIqK0YFKAiIiohNmBfSLY7xb8A1DiTKGn2UG50nT7tcsNzRVwKuvrgKbbAX3PID/+zGCeiIgoHzEpQEREVGTiXfitxEOS7/I74+4l1r1e0+07+roG5XJDuTz2XXyXq3siwAn87e0Z4BMRERUDJgWIiIgKlIgApgGYBsQ0AcuEgjM7Xqx7vlKArkNzeQHdbQf68cBei4/P7zYOn4iIiEoGkwJERER5TizLCf5NiGUAlmXf6YcWv6OveX2AywPl9nTrzg9NZ2E9IiIiSolJASIiojwhlgmYZuLOv1j2nX+lAN0FpevQfJVQHk9iLL/ustfxDj8RERENAZMCREREWSQigBP8i3P3H2IhVmVf6S5Ad0Pzl9vBv+6yu/zrLo7lJyIiorRjUoCIiCgD4uP9LdO+628agEiisJ+uQ3m8UB4flNsd7wkA3ekBQERERJQFTAoQERENUfJd/3jwL7Hx/sld/v2A22tX9tddgK7b3f851p+IiIhyjEkBIiKifvQK/C3TLvQnzpR+zl1/uJK6/MeWxcb7M/gnIiKiPMWkABERlbzugb+VqPCfHPhremKsf7fu/q5EEoCIiIiowDApQEREJSNR3T95aj9AAEDFivy5oPkCiSJ/sen9Yq+JiIiIigiTAkRElJdExC7MZ4fs9mtJeh1/dpZLfM/u+8YCf0FSdX8XNJ8fyuN1uvfr9jh/Bv5ERERUYpgUICIqMmKZgJFU9d4yoZSKx9HdZrQTAWLvpftKEUG3lammwpOe65Jex5YnB/fx/ez/2FPs2ecSST6Xcg6lEsdyHiq+zFmuabE3gKagaRqgnGVuu7hfvMAfA38iIiKiOCYFiIgKVHyOe8uEGEbvue5dbmhllYnx705N/O4Hkb5f93o/wO3EuUsf2yf20kkOKE1LBPd9BPsA7IBf4STbdV+mUiUsiIiIiKhfTAoQEeW53sG/E2mnCv5jFe/7uBvO0JmIiIiIkjEpQESUJ2LBfzwJkBz8u1yA2xMP/pXuZld4IiIiIjplTAoQEWVRYuo7wx7vb5qJbv+6Pa2d8nihPD4ot4fj4ImIiIgoo5gUICJKA7vavQVYzkMsiPMMy16nlLKH2GtJwb/XB+VKCv5dbnvcPRERERFRFjApQESUQjyoj93dtwQiiaAfAJQIBEkF8DTNDuo1DcrldPN3OXf5VawGgDPmn8E/EREREeUYkwJEJSjehb1nFfnEBv2/77cSfco3SVXpE1TKqeziG6RYn+J194P3/dpyAn0nwJfk9wIoJRCxp7aD0hKBvu6C5tIBzWWP8XcC/fh65zU0nQE/ERERERUEJgWIiphYzph104RYBmBZ9p1tpQBN7zewVn0F6H1tmzSVXGLjHvvGp5pDfPo4u7t9UpLASk4YWEkfIjkBYfW9SaokRarXmgalNDvod7mhudyJMfua3n298x5KY6BPREREREWHSQGiAieW1b1wXbwHQNJ89boLmi8A5fH0Cn7jet1t7/G+5/qk95mcI14GEuQPNimgVFLwz0n6iIiIiKh0FWxSoKurC6+88gpWrFiBlStXYsWKFdi9ezcA4Pbbb8cdd9yR2wYSpVE88LfMHhXrYQf2TqCveX2Ay+OMZS+OqvVqIMMEiIiIiIhoSAo2KfDOO+/ggx/8YK6bQZQ2ianqkoJ/iXX31xLT1Xl9dtX65C7vussex86gmYiIiIiIBqFgkwIAUFNTg7lz58YfX/3qV9HS0pLrZlGJS4yVF7ugnb0wUcVeYFewT9omeZy/cqal0wIVUO4egb/uYuBPRERERERpU7BJgfPOOw+tra3dln3rW9/KUWsKn5iGfYca6F44Lv5axQvEFZvBB/HOs8P+idhj+EXErkCvnDWaZv/c4FSy1zQAGpSm7O79Sus78GdBOyIiIiIiyoKCTQroBTxGOpcS1eiTitIlF6RTACynmrv0eEDiRd9iqQEBeleeVyoRFMcTCSqpCr3qO/EQKwTX57PEA/TYmbtXr3fWSfeAPdFIcdqRFLwjuZ3AQIP45Hno45+n537Jn1PTEj8LBvtERERERJRHCjYpQP2LF6YzDHsqOtO0p4FTCkp3A7rTPT1ejd6+Q+3s3SsZkHjfR8Ig6X18vnfLcu60O3PAWwI72xCbG76v4yCRIIgF2EAimRAPqO2p4rTkoFwlB+lw5oxPCs57HNs+bFKigkE8ERERERGVICYFCpyIAKbR7c6/gkCgAS6nIr2vEsrrtYN/lwvQ3adUjf5UBhBIymRD76RAz2C+GIcuEBERERER5VLJJwXC4TDC4XD8fVtbWw5bk1qiMr0T/JsGYp3h49PRBcqgPD7A5Y4Xq8u3ivQqedgAERERERER5VTJJwXuuusu3Hnnnb1XxLrC92UQQe1QAnJxuv3DMiGG4cxHr+wp6VwuaD4/4PZCuT2J4J9V6YmIiIiIiGiQSj4p8O1vfxtf+9rX4u/b2trQ2NgIMQxIsKP7xj3q1/VPBrdLt+7zTtE/twdaeSWUy2O/d7EyPREREREREaVPyScFvF4vvF5vr+WuEWPgqqxMLJBBZAQGtW0fy5yp6U5l3D8RERERERHRyZR8UiAV5fHZ4/OJiIiIiIiIihT7oRMRERERERGVKCYFiIiIiIiIiEoUkwJEREREREREJaqgawocO3YMpmnG31vOFIJdXV04cuRIfLnP50N5eXnW20dERERERESUz5TIYErl55fx48dj165dJ93uhhtuwEMPPTSgY7a1taGqqgonTpxAZfLsA0RERERERERFhsMHiIiIiIiIiEpUQQ8f2LlzZ66bQERERERERFSw2FOAiIiIiIiIqEQxKUBERERERERUopgUICIiIiIiIipRTAoQERERERERlSgmBYiIiIiIiIhKFJMCRERERERERCWKSQEiIiIiIiKiEsWkABEREREREVGJYlKAiIiIiIiIqEQxKUBERERERERUopgUICIiIiIiIipRTAoQERERERERlSgmBYiIiIiIiIhKFJMCRERERERERCWKSQEiIiIiIiKiEsWkABEREREREVGJYlKAiIiIiIiIqEQxKUBERERERERUopgUICIiIiIiIipRTAoQERERERERlSgmBYiIiIiIiIhKFJMCRERERERERCWKSQEiIiIiIiKiEsWkABEREREREVGJYlKAiIiIiIiIqEQxKUBERERERERUopgUICIiIiIiIipRTAoQERERERERlSgmBYiIiIiIiIhKFJMCRERERERERCWKSQEiIiIiIiKiEsWkABEREREREVGJYlKAiIiIiIiIqEQxKUBERERERERUopgUICIiIiIiIipRTAoQERERERERlSgmBYiIiIiIiIhKFJMCRERERERERCWKSQEiIiIiIiKiEsWkABEREREREVGJYlKAiIiIiIiIqEQxKUBERERERERUopgUICIiIiIiIipRTAoQERERERERlSgmBYiIiIiIiIhKFJMCRERERERERCWKSQEiIiIiIiKiEsWkABEREREREVGJYlKAiIiIiIiIqEQxKUBERERERERUopgUICIiIiIiIipRTAoQERERERERlSgmBYiIiIiIiIhKFJMCRERERERERCWKSQEiIiIiIiKiEsWkABEREREREVGJYlKAiIiIiIiIqEQxKUBERERERERUopgUICIiIiIiIipRTAoQERERERERlSgmBYiIiIiIiIhKFJMCRERERERERCWKSQEiIiIiIiKiEsWkABEREREREVGJYlKAiIiIiIiIqEQxKUBERERERERUopgUICIiIiIiIipRTAoQERERERERlSgmBYiIiIiIiIhKFJMCRERERERERCWKSQEiIiIiIiKiEsWkABEREREREVGJYlKAiIiIiIiIqEQxKUBERERERERUopgUICIiIiIiIipRTAoQERERERERlSgmBYiIiIiIiIhKFJMCRERERERERCWKSQEiIiIiIiKiEsWkABEREREREVGJYlKAiIiIiIiIqEQxKUBERERERERUopgUICIiIiIiIipRTAoQERERERERlSgmBYiIiIiIiIhKFJMCRERERERERCWKSQEiIiIiIiKiEsWkABEREREREVGJYlKAiIiIiIiIqEQxKUBERERERERUopgUICIiIiIiIipRTAoQERERERERlSgmBYiIiIiIiIhKFJMCRERERERERCWKSQEiIiIiIiKiEsWkABEREREREVGJYlKAiIiIiIiIqEQVfFKgvb0dd9xxB2bMmIHy8nJUVVVhwYIFuPfeexGJRHLdPCIiIiIiIqK8pUREct2Iodq1axcuvPBC7Ny5EwAQCARgmibC4TAAYM6cOXjxxRdRU1Mz4GO2tbWhqqoKJ06cQGVlZSaaTURERERERJQXCrangGma+PCHP4ydO3di5MiReP7559HZ2Ymuri489thjqKiowKpVq3DttdfmuqlEREREREREealgkwIPPfQQ1q1bBwD4wx/+gPe///0AAE3TcOWVV+LnP/85AOCZZ57Biy++mLN2EhEREREREeWrgk0K/OpXvwIALF68GGeffXav9VdddRWampoAAA8//HBW20ZERERERERUCAoyKdDV1YU33ngDAHDppZf2uY1SCpdccgkA4Lnnnsta24iIiIiIiIgKRUEmBTZt2gTLsgAA06dPT7ldbF1LSwtaW1uz0jYiIiIiIiKiQuHKdQOGYv/+/fHXo0ePTrld8rr9+/ejtra21zbhcDg+WwEAnDhxAoA9CwERERERERFRtlRUVEApldVzFmRSoL29Pf46EAik3C55XfI+ye666y7ceeedvZY3NjaeQguJiIiIiIiIBufQoUNoaGjI6jkLMimQTt/+9rfxta99Lf7++PHjGDduHHbv3o2qqqoctoyKXVtbGxobG7Fnzx5UVlbmujlUxHitUbbwWqNs4bVG2cJrjbIldq15PJ6sn7sgkwIVFRXx111dXSm3S16XvE8yr9cLr9fba3lVVRX/4VNWVFZW8lqjrOC1RtnCa42yhdcaZQuvNcqWbA8dAAq00OCoUaPir/ft25dyu+R1yfsQERERERERUYEmBaZOnQpNs5u+fv36lNvF1o0YMaLPIoNEREREREREpawgkwKBQACLFi0CAPz973/vcxsRwbPPPgsAuOiiiwZ8bK/Xi9tvv73PIQVE6cRrjbKF1xplC681yhZea5QtvNYoW3J5rSkRkayfNQ0eeOABfPazn4VSCm+++SbOPPPMbuufeOIJXHnllQCAF154AUuWLMlFM4mIiIiIiIjyVkH2FACAG264ATNmzICI4BOf+ARefPFFAIBlWfjd736Hz33ucwCASy+9lAkBIiIiIiIioj4UbE8BANi5cycWL16MnTt3ArCHFViWhVAoBACYM2cOXnzxRdTU1OSwlURERERERET5qaCTAgDQ3t6Oe+65B08++SSam5uhaRomT56Mq6++Gl/5yldyMs8jERERERERUSEo+KQAEREREREREQ1NwdYUOJn29nbccccdmDFjBsrLy1FVVYUFCxbg3nvvRSQSOaVjHzx4EF//+tcxZcoU+P1+1NbW4rzzzsP9998P5lhKTyautePHj+Opp57Cv/3bv+Gyyy7DyJEjoZSCUgoPPfRQej8AFYxMXGv79u3Dz372M1xxxRWYOHEi/H4//H4/mpqacPXVV+Oll15K86egQpCJa+2VV17BrbfeiosvvhiTJk1CTU0N3G43hg0bhsWLF+PHP/4xgsFgmj8J5btMfl/r6Qtf+EL8b+n48ePTemzKf5m41u644474NdXfY/v27Wn+NJTPMv17raWlBf/6r/+KefPmoba2Fn6/H+PGjcMll1yC//iP/0A0Gh38QaUI7dy5U8aPHy8ABIAEAgHxer3x93PmzJHW1tYhHXv58uVSV1cXP1Z5ebm4XK74+4suukhCoVCaPxHlq0xdaw8++GD8GD0fDz74YPo/COW9TFxru3fvFqVUt+srEAiI3+/vtuzmm28WwzAy9Mko32Tq99qHPvShbtdVWVmZlJWVdVvW1NQkW7ZsycCnonyUye9rPb388svdft+NGzcuLcelwpCpa+32228XAOJ2u2X48OEpH83Nzen/UJSXMv177bHHHpPKysr48Twej1RVVXX7W3rs2LFBH7fokgKGYciMGTMEgIwcOVKef/55ERExTVMee+wxqaioEABy6aWXDvrYx48flxEjRggAOf300+Xdd98VEZFwOCw/+clPxO12CwD54he/mNbPRPkpk9fagw8+KCNGjJBLL71Ubr31VvnDH/7ApEAJy9S11tzcLABkyZIl8qtf/Ur27dsXP+6GDRvkox/9aPy6u+2229L+uSj/ZPL32o9+9CP58Y9/LCtXrpS2trb48iNHjsiPf/zjeDJq2rRpYppm2j4T5adMXms9dXZ2yoQJE8Ttdsv8+fOZFCgxmbzWYkmBCy64IM2tpkKU6d9rTzzxhGiaJgDkyiuvlFWrVsXXtbe3y2uvvSZf/epXpaOjY9DHLrqkwP333x//Erts2bJe6x999NH4+hdeeGFQx77tttsEgPj9ftmxY0ev9T/4wQ8EgOi6zjsdJSCT11o0Gu21jEmB0pWpa+348eOyYsWKlOsty5JLLrkk3isqGAwOqf1UODL5e+1kfv7zn8eP/frrr6f12JR/snmt/fM//7MAkFtvvVVuuOEGJgVKTCavNSYFKFkmr7X9+/dLTU2NAJCvfvWr6WpyXNElBc477zwBIIsXL+5zvWVZ0tTUJADk+uuvH9Sxx44dKwDkpptu6nN9e3u7lJeXCwD5t3/7t0G3nQpLJq+1vjApULqyfa0le+KJJ+LX3sqVK9N6bMo/ubzW1qxZE7/WHnvssbQem/JPtq61N998UzRNk8mTJ0swGGRSoARl8lpjUoCSZfJa+9a3viUAZMyYMRIOh9PR3G6KqtBgV1cX3njjDQDApZde2uc2SilccsklAIDnnntuwMfesmULdu/e3e+xy8vLcd555w362FR4MnmtESXL9bXm8/nir03TTOuxKb/k+lp77bXX4q8nTJiQ1mNTfsnWtRYOh3HzzTdDRPDzn/+82+8zKg25/r1GpSPT19rDDz8MAPj0pz8Nj8dzCi3tW1ElBTZt2gTLsgAA06dPT7ldbF1LSwtaW1sHdOz169f32r+/Y2/cuHFAx6XClMlrjShZrq+1pUuXAgA8Hg8mT56ctuNS/snFtRYMBrFt2zb84Ac/wNe//nUAwPnnn4/58+ef0nEpv2XrWvvud7+LTZs24TOf+QwuvPDCIbWVClu2rrUNGzZg+vTp8Pv9KC8vx5QpU/C5z30Oq1atGlrDqeBk8lprbm7G/v37AQAXXHABVq1ahSuvvBIjRoyA1+tFY2MjrrrqKrz55ptDbn9RJQViPywAGD16dMrtktcl75POY7e1taGjo2NAx6bCk8lrjShZLq+15uZm/O///i8A4Morr0RlZWVajkv5KVvXWktLS3yarkAggMmTJ+PWW29FOBzGhz/8Yfzxj38c9DGpsGTjWlu1ahXuvvtuDB8+HHfffffgG0lFIVu/144cOYJNmzYhEAggHA5j69atuP/++zFv3jzcdtttgz4eFZ5MXmtbt26Nv37nnXdw5pln4oknnsCJEyfg9/uxd+9ePP7441i0aBHuuuuuIbS+yJIC7e3t8deBQCDldsnrkvfJ1bGp8PB6oGzJ1bUWDAZxxRVXoKurC3V1dUP+I0OFI1vXmq7rGD58OIYPH96tO/cVV1yBu+++G7W1tYM+JhWWTF9rhmHg5ptvhmEY+PGPf4yampqhNZQKXqavtUmTJuHuu+/Gli1bEAqFcPToUXR2duLZZ5/FvHnzICL4/ve/j3vvvXdoH4AKRiavtWPHjsVf33nnnRg+fDj+/ve/o7OzE8ePH8emTZuwZMkSiAi+853v4E9/+tOg219USQEiIjp1hmHgmmuuwYoVK+B2u/Hoo4/2m/UmGoyGhga0tLSgpaUFXV1d2LNnD2699Vb85S9/wcyZM/GLX/wi102kAvcf//EfWL16NS677DJ86lOfynVzqIhde+21+MY3voHJkyfD7XYDsIfbXXTRRXj99dexYMECAMAdd9yBEydO5LKpVMBiwxJir3/3u9/h4osvhqbZofzpp5+Op556CqNGjQJgX2+DVVRJgYqKivjrrq6ulNslr0veJ1fHpsLD64GyJdvXmmma+PSnP40//elPcLlcePTRR3HRRRcN+XhUOHLxe00phTFjxuDf//3f8Zvf/AbRaBRf/OIXsWbNmlM6LuW3TF5rGzduxPe+9z2Ul5fjZz/72dAbSUUhl9/XfD4ffvCDHwAAOjo68OKLL6bluJSfshWHnnvuuTjrrLN6bVNWVoYvfelLAIA1a9bg4MGDAzp2TFElBWLZEQDYt29fyu2S1yXvk85jV1ZWory8fEDHpsKTyWuNKFk2r7VYQuDxxx+Hruv49a9/jU9+8pNDOhYVnlz/Xvv4xz+OcePGwbIsPPDAA2k7LuWfTF5rX/7ylxGJRHDrrbeipqYGHR0d3R6GYQAARCS+LBqNDvGTUL7L9e+1s88+O/56x44daTsu5Z9MXmvJvTWnTp2acrvkdbt27RrQsWOKKikwderUeDeK5NkCeoqtGzFixIDHLiZXkRzIsadNmzag41JhyuS1RpQsW9eaaZq49tpr8dhjj8UTAldeeeXQGk0FKR9+r8W+IG3fvj2tx6X8kslrrbm5GQDw7W9/GxUVFb0ev/nNbwAAu3fvji/76U9/eiofh/JYPvxeo9KQyWtt2rRp0HUdgN3DLhURib/ub7u+FFVSIBAIYNGiRQCAv//9731uIyJ49tlnAWBQXWKnTJmCsWPH9nvszs7O+DzL7G5b3DJ5rREly8a1FksIJPcQuOqqq4beaCpIuf69JiLxgI7DrYpbrq81Kh25vtbeeuut+Oumpqa0HpvySyavNZ/Ph/PPPx9A/9Peb9q0CYCdEBg/fvyAjx9rXFG5//77BYAopeStt97qtf7xxx8XAAJAXnjhhUEd+7bbbhMAEggEpLm5udf6H/7whwJAdF2XLVu2DPUjUIHI5LXWl9ixHnzwwVM+FhWWTF5rhmHIpz71KQEgLpdLHnvssXQ1mwpQpq61aDR60m0eeOCB+LF/9rOfDardVHiy/Tc05oYbbhAAMm7cuLQdk/Jbpq41y7L6XR8KheTMM88UAFJWVibHjh0bbNOpwGTy99rDDz8c33fZsmW91nd2dsqoUaMEgJx11lmDbnvRJQWi0ajMmDFDAMjo0aPjP3DTNOWJJ56QyspKASCXXnppr31vv/32+A+7r6D/+PHjMmLECAEg06ZNk+XLl4uISDgclp/97Gfi8XgEgHzxi1/M6Gek/JDJa01E5PDhw90ese3vu+++bss7Ozsz+TEpD2TqWjMMQ66++up4QuCJJ57IxsehPJapa+3ll1+W8847Tx5++GHZs2dPt3Vbt26Vb37zm+JyuQSATJgwQbq6ujL2GSk/ZPpvaCpMCpSeTF1rS5culSVLlsgjjzzS7fdaJBKRF154QRYsWBDf94c//GFGPyPlh0z+XjNNUxYuXCgApLGxUf7+97+LaZoiIrJp0yZZsmSJABBN0+TFF18cdNuLLikgItLc3Czjx4+P/2ADgYD4fL74+zlz5khra2uv/QbyR2b58uVSV1cX366iokLcbnf8/UUXXSShUCjDn5DyRSavtdj6kz1uv/32zH5IyguZuNZeeeWV+Dq32y3Dhw/v98FeBKUhE9fayy+/3O33ls/nk/r6evH7/d2Wz5o1a9BBHhWuTP4NTYVJgdKUjd9rfr9f6uvru8UFmqbJd77znSx9SsoHmfy9duDAAZk2bVq3a66qqqrbd7lf/OIXQ2p3UdUUiBk/fjzWrl2Lf/u3f8P06dOhlILb7ca8efNwzz334K233kJNTc2Qjj1v3jxs2LABX/3qVzFp0iREo1GUlZXh3HPPxf/93//hmWeegdfrTfMnonyVyWuNKFkmrrXkeW+j0SgOHjzY7yMYDKb7Y1EeysS1Nm/ePDz88MO4+eabMWvWLFRVVeH48ePQNA0TJkzAFVdcgcceewwrVqwY/DhIKlj8G0rZkolrbcaMGbjnnnvwiU98ApMnT4bf78fx48fh9/sxa9Ys/OM//iNWr16N73//+xn6VJSPMvl7bcSIEVi5ciXuueceLFiwAB6PB8FgEOPHj8fNN9+MlStX4nOf+9yQjq1EksoUEhEREREREVHJKMqeAkRERERERER0ckwKEBEREREREZUoJgWIiIiIiIiIShSTAkREREREREQlikkBIiIiIiIiohLFpAARERERERFRiWJSgIiIiIiIiKhEMSlAREREREREVKKYFCAiIiIiIiIqUUwKEBEREREREZUoJgWIiIiK2M6dO6GUglIKDz30UK/1Dz30UHz9zp07s94+IiIiyi0mBYiIiAbgxIkT+OlPf4oPfvCDGD9+PAKBAKqqqjB58mRce+21ePzxx2GaZq6bSURERDQoTAoQERGdxP33348JEybgH//xH/HMM89g165dCAaDaGtrw7Zt2/Doo4/iqquuwsyZM/H6669npU2xu/t33HFHVs5X6m688UYopTB+/PhcN4WIiCitmBQgIiLqxze+8Q187nOfw9GjR+FyufDpT38aTzzxBN5++2289tpruP/++7FkyRIAwMaNG/H+978fv//973Pc6oG78cYbISIQEQa8REREJciV6wYQERHlq5/+9Ke45557AACNjY34y1/+glmzZnXb5txzz8VnPvMZPP7447j++usRDodx7bXXYuLEiZg9e3YOWk1EREQ0cOwpQERE1Iddu3bhlltuAQCUl5fjpZde6pUQSHbllVfiV7/6FQAgEonguuuug4hkpa1EREREQ8WkABERUR/+67/+C6FQCABw++23Y+LEiSfd56qrrsKHPvQhAMD69evx17/+tdc248ePh1IKN954Y7/HSjWGPbZ/zJ133hmvLxB7nOzYyQY6+4CI4Pe//z0+8YlPoLGxET6fDzU1NVi4cCG+973v4fjx4wP+LAcOHMA3v/lNnHHGGaioqIBSCkuXLh1wm5cuXRpv89KlS2FZFn75y19i8eLFGD58ODRN6/YzsCwLL730Em655RYsWrQI9fX1cLvdqK6uxuzZs3HLLbdg9+7dfZ7rjjvugFIqnvDZtWtXr5938v+PZIZh4IEHHsAHP/hBjBo1Cl6vF/X19Tj//PO7XV9ERES5xOEDREREPYgIHn74YQCA3+/H5z73uQHv+0//9E/429/+BgB48MEH8eEPfzgjbcymw4cP4/LLL8cbb7zRbXk4HMa7776Ld999Fz/96U/x1FNP4cwzz+z3WG+99RY+/OEP48iRI2lpWygUwsUXX4wXXngh5Tbf/e53ceedd/ZafuLECaxZswZr1qzB//zP/+DXv/41Lr/88rS067333sNHPvIRbNy4sdvyo0eP4rXXXsNrr72Gn/3sZ/jb3/6GSZMmpeWcREREQ8GkABERUQ8bNmxAa2srAOD8889HVVXVgPddsmQJAoEAurq6MjITwXPPPYdIJIIZM2YAAL74xS/iS1/6Urdtampq0na+zs5OXHDBBdi0aRM8Hg9uuukmfPCDH0RjYyM6Ozvx6quv4j//8z9x8OBBXHrppVi1ahXGjRvX57E6OjrwiU98AqFQCLfeeis+8IEPIBAIYN26dRg5cuSQ2vfNb34Ta9euxUc+8hHceOONGDduHA4ePIi2trb4NoZhYOTIkbj88stx9tln47TTToPP58OePXuwbNky/OxnP0NHRweuueYarFy5ElOnTo3v+6UvfQmf/OQncdttt+Gpp57CqFGj8Oyzz/bbpgMHDmDRokU4ePAgKioq8PnPfx7vf//7MXz4cJw4cQLPPfcc/vu//xvbtm3DJZdcgpUrVw7qGiMiIkonJgWIiIh6WLNmTfz13LlzB7WvruuYNWsW3nzzTRw+fBj79+/HqFGj0ta2yZMnd3s/bNgwTJ8+PW3H7+lb3/oWNm3ahKqqKrzwwguYP39+t/Xnnnsurr32Wpx99tk4cOAAbrvtNjzyyCN9Huvo0aMoLy/H66+/3q0+w4IFC4bcvrVr1+Jf//Vf8d3vfjflNp/97Gdx++23w+12d1s+d+5cfPSjH8VXvvIVnHXWWdi3bx9+8IMfdGv/sGHDMGzYMFRXVwMA3G73SX/en//853Hw4EE0NjZi6dKlOO2007qtv/DCC3HFFVfgvPPOw44dO3DPPffge9/73iA/ORERUXqwpgAREVEPyV3bR4wYMej9hw8fHn999OjRtLQpF44cOYL7778fgN0Fv2dCIGbcuHH413/9VwDA448/jq6urpTH/Jd/+Zd+CzYO1uTJk3H77bf3u8348eN7JQSSjRkzBt/4xjcAAH/+859PqUBkci2Jn/zkJ70SAjFz5szBl7/8ZQDAL3/5yyGfj4iI6FQxKUBERNRDe3t7/HVZWdmg90/eJ7kbe6F59tln48XwPvWpT/W77fnnnw8AiEajWLFiRcrtrr322vQ1EPasD7quD2qftrY2NDc3Y8OGDVi/fj3Wr1+PQCDQbd1QPfXUUwCAQCAQLzqZSuxntn//fuzZs2fI5yQiIjoVHD5ARETUQ0VFRfx1R0fHoPdP3qeysjItbcqF5cuXx18PZsx/S0tLn8vLy8tT3jkfqpkzZw5ou127duGee+7BX/7yF+zatavfbY8cOTLkdsZ+Zl1dXXC5Bv41q6WlBY2NjUM6JxER0algUoCIiKiHurq6+OtUAW5/Dh482OexCs2hQ4eGtF+q4QOxcfnpNJCiis888ww++clP9jusIVkwGBxye9L9MyMiIso0JgWIiIh6SB7zvmrVqkHta5om1q5dCwBoaGhIa5HBbDNNEwDg8Xj6HRLQ05gxY/pcPthu/gNxsmMePXoU11xzDbq6ulBeXo5bbrkFF198MSZMmICqqip4PB4AwEsvvYQlS5YAwCnVFIj9zJqamvDnP/95wPs1NTUN+ZxERESngkkBIiKiHqZPn47a2lq0trbi1VdfxYkTJwY8ZdwLL7wQv+t77rnn9lqvaXY5H8uy+j1OZ2fnIFudfrFeDpFIBHV1dUOeNjCXfve73+H48eMAgCeffBIf+MAH+tzu2LFjaTlf7Gd28OBBnH766YMaQkBERJQLLDRIRETUg1IK1113HQC7K/n//d//DXjf++67L/76xhtv7LU+Vq/gZEHoli1bBnzOTJkzZ0789XPPPZfDlgzdhg0bAAC1tbUpEwJA9/oJfVFKDeh8sZ9ZV1cX3njjjQG2koiIKHeYFCAiIurD//f//X/wer0AgDvvvBPbt28/6T6PPfYY/va3vwEApk2bhssuu6zXNrFu4itXrkzZTX39+vVYt25dv+fy+XwAgHA4fNJ2DdWll14an8rvRz/6EQzDyNi5MiXW5nA4nLJ3RldXFx5++OF+jzPQn/dHP/rR+Ou77757ME0lIiLKCSYFiIiI+tDU1BQP6jo6OrBkyRKsWbMm5fZPPPEEbrjhBgD2GPxHHnkkPlQg2QUXXADAnobut7/9ba/17e3tuPnmm0/avlhX/vfee+/kH2aIRo8ejZtuugkAsGbNGvzDP/xDv4mBQ4cO4f77789Ye4Zi0qRJAOzhGL///e97rTdNE5/97Gexf//+fo8T+3kfOnSo25SVPS1YsAAXXXQRAODpp5/G7bff3u9xd+7c2ed1QERElC0c6EZERJTCP/3TP2HHjh347//+b+zevRvz58/H1VdfjY985CMYN24cotEoNm/ejEcffRQvvvgiADsh8PDDD2Pu3Ll9HvPTn/407rjjDrS1teEzn/kMtm/fjosvvhhKKSxfvhz/+Z//iX379mHOnDn9Fjk855xz0NzcjD//+c/4+c9/jkWLFsXvZldWVmLYsGFp+Rnce++9WLZsGdavX49f/vKXeOutt/D5z38e8+bNQ3l5OY4fP44NGzbghRdewNNPP40ZM2bgs5/9bFrOnQ6f+tSn8J3vfAfhcBg33ngjVq9ejfe///2orKzEhg0bcN9992HFihVYtGhRv939zznnHAB2LYgvfOEL+MpXvoK6urr4sIKJEyfGt33wwQcxf/58HDhwAN/97nfx7LPP4uabb8aMGTPg8/lw9OhRrF27Fn//+9/x0ksv4WMf+xiuvvrqzP4giIiIUhEiIiLq1//8z/9IbW2tAOj3cfrpp8vSpUtPerwnnnhCdF3v8xg+n0+eeOIJueGGGwSAjBs3rs9jrFq1Srxeb5/HuOGGG+LbNTc3x5c/+OCDvY7z4IMPxtc3Nzf3ea6jR4/KJZdcctLPD0AWL17ca/+TfZbBevnll+Pne/nll0+6/S9/+UvRNC1lm6+88kp54YUX+j2maZpy1llnpTxGTzt37pQFCxYM6Gd20003peGnQkRENDQcPkBERHQSX/jCF/Dee+/hvvvuwyWXXILGxkb4fD6Ul5djwoQJuOqqq/Db3/4W69atiw8P6M8VV1yBZcuW4fLLL0dDQwM8Hg8aGxtxww03YPny5bjiiitOeozZs2fjzTffxNVXX42xY8fG6x9kQm1tLZ555hm8+OKLuOmmmzBp0iSUl5fD5XKhtrYWCxYswJe//GU8/fTTeP755zPWjqG66aab8Nprr+FjH/sYGhoa4Ha7MXLkSFxyySV4/PHH8dhjj510akNN0/Dcc8/htttuw6xZs1BeXt5v8cFx48bh7bffxh//+EdcddVVaGpqQiAQgNvtRkNDA8455xx8/etfxyuvvIIHHngg3R+ZiIhowJTIKUzGS0REREREREQFiz0FiIiIiIiIiEoUkwJEREREREREJYpJASIiIiIiIqISxaQAERERERERUYliUoCIiIiIiIioRDEpQERERERERFSimBQgIiIiIiIiKlFMChARERERERGVKCYFiIiIiIiIiEoUkwJEREREREREJYpJASIiIiIiIqISxaQAERERERERUYliUoCIiIiIiIioRDEpQERERERERFSi/n+B3w4jX+r01wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1200x1200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12,12))\n",
    "\n",
    "#sns.lineplot(ax=ax, data=df, x=\"outlier_rate\", y=\"error_angle_mean\", hue=\"ignore_outliers\", lw=5, palette=[\"#e84118\", \"#0097e6\"])\n",
    "\n",
    "sns.lineplot(ax=ax, data=df_false, x=\"outlier_rate\", y=\"error_angle_mean\", lw=3, label=\"No outlier detection \\n $n_0=1$, $N=100$\", color='grey')\n",
    "sns.lineplot(ax=ax, data=df_vandamme,  x=\"outlier_rate\", y=\"error_angle_mean\", lw=5, label=\"Strategy 1 \\n $n_0=1$, $N=100$\", color=\"#e84118\")\n",
    "sns.lineplot(ax=ax, data=df_true,  x=\"outlier_rate\", y=\"error_angle_mean\", lw=5, label=\"Strategy 2 \\n $n_0=5$, $N=20$\", color=\"#0097e6\")\n",
    "\n",
    "# sns.lineplot(ax=ax, data=df_vandamme,  x=\"outlier_rate\", y=\"error_angle_theoretical\", lw=2, label=\"Vandamme Theory\", color=\"#e84118\")\n",
    "# sns.lineplot(ax=ax, data=df_true,  x=\"outlier_rate\", y=\"error_angle_theoretical\", lw=2, label=\"Perfect detection ($n_0=5$)\", color=\"#0097e6\")\n",
    "\n",
    "plt.fill_between(df_vandamme.outlier_rate, df_vandamme.error_angle_25, df_vandamme.error_angle_75, color=\"#e84118\", alpha=0.1)\n",
    "plt.fill_between(df_true.outlier_rate, df_true.error_angle_25, df_true.error_angle_75, color=\"#0097e6\", alpha=0.1)\n",
    "\n",
    "plt.xlabel(\"Outlier rate\", fontsize=20)\n",
    "plt.ylabel(\"Mean error (degrees)\", fontsize=20)\n",
    "plt.yticks(fontsize=18)\n",
    "plt.xticks(np.arange(0, 0.70, 0.1), fontsize=18)\n",
    "plt.xlim(0, 0.6)\n",
    "plt.ylim(0, 8)\n",
    "\n",
    "plt.legend(title=\"Method ($n=100$)\", loc=\"upper left\", fontsize=18, title_fontsize=18)#, labels=[\"Strategy 1 ($n_0=1$)\", \"Strategy 2 ($n_0=5$)\"])\n",
    "ax.spines[['right', 'top']].set_visible(False)\n",
    "\n",
    "# plt.savefig(\"Figure3d.pdf\", format=\"pdf\", bbox_inches='tight')\n",
    "# plt.savefig(\"Figure3d.png\", format=\"png\", bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "80be7f46-dcbf-45cb-b495-73d794272f69",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}