EXPLOLATORY DATA TO DEFINE PROBLEM DEEPLY.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# EXPLOLATORY DATA TO DEFINE THE PROBLEM DEEPLY"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### WHAT THIS IS ABOUT\n",
    "\n",
    "this is a case problem in predicting energy consumption in a competition in Driven Data. for description of the project please check the following site.\n",
    "\n",
    "https://www.drivendata.org/competitions/55/schneider-cold-start/page/111/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Untitled.ipynb\n",
      "cold_start_test.csv\n",
      "consumption_train.csv\n",
      "meta.csv\n",
      "submission_format.csv\n"
     ]
    }
   ],
   "source": [
    "!ls"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "meta_data = pd.read_csv('meta.csv')\n",
    "train_data = pd.read_csv('consumption_train.csv')\n",
    "test_data = pd.read_csv('cold_start_test.csv')\n",
    "submission = pd.read_csv('submission_format.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>series_id</th>\n",
       "      <th>surface</th>\n",
       "      <th>base_temperature</th>\n",
       "      <th>monday_is_day_off</th>\n",
       "      <th>tuesday_is_day_off</th>\n",
       "      <th>wednesday_is_day_off</th>\n",
       "      <th>thursday_is_day_off</th>\n",
       "      <th>friday_is_day_off</th>\n",
       "      <th>saturday_is_day_off</th>\n",
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       "      <td>x-large</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
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       "      <td>True</td>\n",
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       "      <th>2</th>\n",
       "      <td>100006</td>\n",
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       "      <td>False</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
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       "      <th>4</th>\n",
       "      <td>100010</td>\n",
       "      <td>x-small</td>\n",
       "      <td>low</td>\n",
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       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "   series_id  surface base_temperature  monday_is_day_off  tuesday_is_day_off  \\\n",
       "0     100003  x-large              low              False               False   \n",
       "1     100004  x-large              low              False               False   \n",
       "2     100006  x-small              low              False               False   \n",
       "3     100008  x-small              low              False               False   \n",
       "4     100010  x-small              low              False               False   \n",
       "\n",
       "   wednesday_is_day_off  thursday_is_day_off  friday_is_day_off  \\\n",
       "0                 False                False              False   \n",
       "1                 False                False              False   \n",
       "2                 False                False              False   \n",
       "3                 False                False              False   \n",
       "4                 False                False              False   \n",
       "\n",
       "   saturday_is_day_off  sunday_is_day_off  \n",
       "0                 True               True  \n",
       "1                 True               True  \n",
       "2                 True               True  \n",
       "3                 True               True  \n",
       "4                 True               True  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "meta_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
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       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>103088</td>\n",
       "      <td>2014-12-24 00:00:00</td>\n",
       "      <td>101842.233424</td>\n",
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       "      <td>2014-12-24 01:00:00</td>\n",
       "      <td>105878.048906</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>2</th>\n",
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       "      <td>2014-12-24 03:00:00</td>\n",
       "      <td>94473.706203</td>\n",
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       "      <th>4</th>\n",
       "      <td>4</td>\n",
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       "      <td>2014-12-24 04:00:00</td>\n",
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       "   Unnamed: 0  series_id            timestamp    consumption  temperature\n",
       "0           0     103088  2014-12-24 00:00:00  101842.233424          NaN\n",
       "1           1     103088  2014-12-24 01:00:00  105878.048906          NaN\n",
       "2           2     103088  2014-12-24 02:00:00   91619.105008          NaN\n",
       "3           3     103088  2014-12-24 03:00:00   94473.706203          NaN\n",
       "4           4     103088  2014-12-24 04:00:00   96976.755526          NaN"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "train_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
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       "   Unnamed: 0  series_id            timestamp   consumption  temperature\n",
       "0           0     102781  2013-02-27 00:00:00  15295.740389        17.00\n",
       "1           1     102781  2013-02-27 01:00:00  15163.209562        18.25\n",
       "2           2     102781  2013-02-27 02:00:00  15022.264079        18.00\n",
       "3           3     102781  2013-02-27 03:00:00  15370.420458        17.00\n",
       "4           4     102781  2013-02-27 04:00:00  15303.103213        16.90"
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     "execution_count": 7,
     "metadata": {},
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Q0L35T//0T0FAjYrX1dW5b3/7265du3Ypzi69yLBhw8xgskJr1go+K1ascGPGjCn0VMoj0KQFCGxo0m8fnUcAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEKiWgGac18zz1ioIxQYgHDhwIGf3X3vtNTd69OicZXwHf/azn5mHRowYYeaTiUAaAV/AzGOPPZbmdMogUDGBH/7wh27WrFlZ9SvobPPmzVl5ldjxrZBTbFtjx44NPvvbt29fbBWch0CTE2Bdnyb3ltFhBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQACBWgnMmDHDbFoBCMWktWvX5jztySefzHk810FrFYkLLrjAMVA2lxrH8gm0bdvWLHLhhRea+WQiUC2BDh06JJo6ePBgIq8SGb6An0svvdTpc/7o0aNOwQ/6O3PmjNu9e7cbNWpUzq5MnDgx53EOItDcBAhsaG7vKNeDAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCBQMYHhw4ebdRcbgPD444+b9YWZa9asCQbChvtpXzVwdsuWLYni99xzTyKPDAQKETh8+HCiuAZva0UTEgItVaB79+5Zl65nQsELO3fudFolJxpQ1qpVK9ejRw+3evVqt2LFiqzzojvLly93x44di2axjUCzFmjTrK+Oi0MAAQQQMAW+eMtCM59MBBBAAAEEEEAAgeYp8NuX7mueF8ZVIYAAAggggAACCCCAAAIIIIAAAggggAACCCBQA4FOnTo5rXrw0UcfZbUeBiBowGrapJm7169fn7e4ZgLXINhC0o4dO8ziEyZMMPPJRCCtwMsvv5woev755yfyyECgJQlEA3u0QoOCGdKkMWPGuP/+7/92c+fONYu///77rnfv3uYxMhFobgKExzW3d7SJXs+ePXvc9u3bg8i0vXv3Vv0qFNF24MABd+jQoWCJn6p3gAYRQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEECgyQhMnDjR7Ou+ffvMfF+mVV5BE/H03HPPxbPy7j///PNmGc0iTkKgFIEOHTokTj948GAijwwEWpqAVsrRX9qghtDn7/7u78LNxOuvf/3rRB4ZCDRXAQIbmus724Sua9iwYa5nz56uX79+rr6+3nXr1s3lW16tnJenCGn90Oratavr3Lmza926tatFcEU5r4m6EEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAoHICkydPNit/4YUXzHxf5r/8y78kDmkliHhwQzHjqZYtW5aoe9SoUa6QFSUSFZCBgHPuU5/6VMKBFRsSJGTUQKDW96Y+X4v5jNVqD0OHDjXFdu3aZeaTiUBzFGjTHC+Ka6qtwM6dO93u3btdu3btguXP8i2BFl+STb0/evRoVS5CkXFWOnLkiKurq7MOZfIKvc7MiWwggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIBAkxbo06eP2f8lS5a4qVOnmseszKeffjqRPVF7WMcAACAASURBVHDgQLdly5asfA1sPXXqlGvTJt2QP5W1BsPee++9WfXm2jl27JhbtWqVe/bZZ93GjRtddJyXAi+GDBnipkyZ4q677rpgrFiuugo5Vqt20/Rx06ZN7s0338wU1X0gh1JSWOfhw4eDgIFS69yzZ49bu3atC+vTpMNf/epXixpsHV6X6tSfksYFLly4MDyUedU9q2ux0he/+EWngdu5ksby/fa3v3V6hl599dXE/auVRgYPHuzGjRsXzIbfvn37XNV5j+n+UgBS6KO+DRgwIKv8M88842bPnp3pg+73W2+91T344IOud+/eWWWL3UnTj7Nnz7p/+7d/c48++mjWMxg+f3qeS31vo/0v57Onz6BXXnnF7d+/P2NdzL194MCB4H7WZNUKWtD7Pnr06OBVfdc4znDlG92b1mdqrntT58Tf/6hJNbfHjBnj1q9fX/EmDx06FLw3er/1HGis7A033OA6depUUNvhZ1d40le+8hXXt2/fcDfV64kTJ9zLL7/s1JcwySHN813O+zVsO81rrdpN07f4e5LmmdNn7y9/+Uunz73oZ68+ZxSwps/dO++8011zzTVl/a73XU+6Xzm+s8n3CuhD+bXXXvMejx7QA6gPx4suushdeOGFwYdvMRFb0Tprtd2lS5esH7Dqh6J8V69eXasu5Wy3WOemdp05ERrxQX1g6h8BfWDqx3b8HzZ1XVGK+iLTX75glEZ8qTXvWl19Q837QAdajsDet7P/ieX+aznvfS2vlPuulvott+34fRdK8LkXSvBaSQHf/VfJNqkbAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAIGWJBDOrh0fhKrxLRrzkm8Qt6w0aDl+vvLXrVvnunXrluD8z//8T9fQkG6Mh8paKc0gfA0gHjFihDlWJ6xTQQ5r1qwJ/pSnMWI//elPSxr0WKt2w2vK9ar3tHXr1maRbdu2FTyYN6xIg7IHDRoU7mZeV65cGQzezmSk3FA/FcgQT6X0UfepVWe8De1b16L8xYsXewN+NEh44sSJbvny5VaVmTwF6ugvLKcAIA2czzfxcqaCP25cccUVmYCF8Njp06eDZ1b3oPXs6X5funRp8BeWDc8t9jVXP1Sngi/Gjh1rVh9//oq9X8LKK/HsPfTQQ27u3LlhE5nX6dOnuwULFmT2c23o3ujatWuiSFiHBsXX19cnjlsZvntTZd9+++2yBaxYbTe2vCeeeMLNmjUr0S0962nT9u3bzef9+PHjBX0P/Omf/qn5XTN+/HhvVypxv3obixyoVbuRLng3i/2O0mpQ06ZNM+vV54z+op+7Ciz7yU9+kuo3jllpiszcIXApKqCILXDuuee6kSNHpvq7+uqrgwdcH7CdO3cO3vBhw4YFEXZ27Y0zVxGZuonjST9g9dA0l9RSrrOW75ciArVcn/4Z0A/QRx55xPzyUh/1z50+WPWDUgEnYWRwLftP2wgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAALNX2DGjBnmRe7YscPMj2e+99578axgkk/f5J6ayT5tsspq9uV8s2BrkKPG4VgTkOZqW2PEzjvvvGD29FzlfMdq1a6vP/F8TVjsS1pJoNh0ySWXmKfefffdZn6+zF/84hdmEc10X8ukAAQraUWQDh06ZIIVrDK+PN2jCriYM2eOr4iZrxnI40mBSBp3ZgU1xMuWa9/qhyZq1lhLrQrhC2qw2r/pppuc7/PIKh/Nq9Sz51u5RmMBtQpDmnT99debxe6///4g3/oMNU9oIpkKsLCSnpFyJl99GreZNj3//PNm0f/4j/8w861M3euFftdU6n61+hfNq1W70T7k2i70Oyr8nPEFNfjaUmDZF77wBd/hsuQT2FAWxuxK0n7oZp+VvafB2gp40BdVcxioXezKCNkqjX+vpVxnJd8J/cBSgI8iXAtNCqzRj1V9iZAQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEKikwPDhw83qfQM+44V/9rOfxbMys9pPmjQpcayQ8TQvvvhi4vwHH3wwkRfN0ESkhQ5yjJ6vbU3uq5m8C0m1ajdtH6+88kpzwl+d/8YbbxQ0O3m8zTZt2gTBLPF8zZBdyCDj8Pz/9//+X7iZ9VroqgbRkwuZxT16XnTbal8BCRqQX2rSqgA33nhjSdVoJva0q1JUcozgvn37gsmA9f4XmhQw8MwzzxR0WiWfPQVoaWUFK6UZGL1p0yZzRZvZs2c7X/CX1VZTynvppZfM7mpFnHKmb3zjG2Z1vgAkq/Bjjz1mZbtHH33UzLcyfUGAN998s1U8mCyb76gkTTHfUZdddlli5ZpkzXbOwYMH7QNlyiWwoUyQ0WrK/abpC1ORiY09nTx50tvFcvy48VZe5QMt5TqrzBo0p5VK9AOr1KQvLy3FRUIAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAoFICnTp1cloFIZ58Az7j5axVFUaOHBkU883Yn2aw+7Fjx8yB+N/61rfiXcjsa5B5rsCJxYsXu23btrkPPvggeLUCL8LK+vXr59SHNKlW7abpm8rcdttt3hnFFdTQ0NCQtipvOd94qSeeeMJ7jnXg1KlT5kDwefPmWcVT52k1g1LTiBEjsqrQxLUKSMiVxo0b59R3/eUb2K0VQ4pdsUB9KGSlhkqOhczVDxkMHDgwF5mbMGGC032QJlXj2Zs/f77ZFQVu5BoTK+NBgwaZ56rfYSpltZSwDr127NgxuluTbb1vvoCWT3/602XtkxVopAa+973vpWrnxIkT5neMTtazmPYZsb4D9Z2q79Z4qsb9Gm9T+7Vq1+qLlVfMd9S6deu895oCh7SKRvhdv2zZMhd/zqzVZqy+FZtX+jdOsS034/Patm1b9qtTZGJjX7nh4osv9l53OX7ceCuv8oGWcp1VZg2W0NJKJb6kLyz9WFUUZ74fqqpDS3Gl/ZHma5N8BBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQRyCUycODFx+KOPPnIa+JkrnTlzxhww36VLl+C0K664wjw9zYzaGzduNM/1DY7VbPW+QeYrV64MBqlOnTrV9e3bN5gpXa8akHr06FEzsEONWy7xTtWq3Xg/fPsaKL98+XLzcLmCGlT5l770JbONWbNmmfm+TN+98e1vf9t3Sup83a+ffPJJ8KdtayZ+je86ffp0plxYXq9jxozJtKVxkL5Z11WHAmg0MForn8ycOTP4W716dZC3YcOGTD3xDQWI6J4qV1q7dq07fvy4+/jjj522hw4dGgQWVHsspAYZy0MGmzdvDsbZKdDIl5577jnfoUx+tZ49rW6hZ8VKGhOre8lKet+tJItoUv3xe1MDs63kuzeV3xhWgHjttdesbgefse3atTOPlZJpBafJ1/eeRNvSahq5ki9AI36OFdR1zz33xIsFzzXfUQmWIJirmO+oW2+9NVmZc8FntwI5BgwYkPmuHz9+vNu5c6fbv39/ZnWhd955xzy/XJkENpRLMkU9+lLVh6C+7KJ/+oH39ttvB5GFuarp379/rsM1P9a+fXuna1RUoH5g6E9f5rqhm1NqKddZ7ffMt0SXIm71jBw4cCD4sbpgwYLgR5p+rMV/qMT7fNddd8Wz2EcAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAoGwCkydPNuvKN/DTGhgYneyzTZs2iVmS1ZBmus+Xnn766UQR1e0bnxOfTT88WQPMR48eHe4mXjWOSmN6rFnkNdgyX3BHrdpNXIiRIWdr0K2KljOoQfXpfbECBXSskMmQv/vd7yauRDNth8EyiYMFZKiPuif1p+36+vrE2b169XIa9B+Wi75GC99www3R3cy27iPdTwqc8aUhQ4YEg299x2+55RbfodT5YYCG7k8NKNfs8dp+/fXXg8CC1BWVWFDPrMbIaZBxNMlfgUaaSd1K9957r5WdlVfNZ0+rmmgcqZVuv/32RLaCLqxnTx5xC50cvzetIAXdW757s9qBKokL/mOGb7D5Qw895DulpHzfCidvvvlm3nrzfQ/57s1oxb7Vh6zv1Grer9E+1qrdaB9828V+R+kzRcGX8aQVGvSZ7Uv6HtFnoMoV8r3kqy9XPoENuXTKfKxnz57Bh6O+7KJ/+oHXu3fvILJQN40VCaWu6GZS5EtjTvrhoKhA/cDQn27kcvwwamzX3FKus5ruuvejSVGliv5T9KWeESvph4oien0p1/J4vnPIRwABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAgrUCfPn3MovkGfq5ZsyZx3pQpU7LyrFnL169fHwx2zioY27FmcPYNdtYYL2tyUQ1MzTXAPNrkr3/96+huZvuHP/xhZju+Uat24/2w9letWuVdUaDcQQ1h+/fff3+4mfW6cOHCrH3fjoJIrPdRk8pWKx08eDBvUxq0bvVTwQQad5gmafCtVlGwkp6PY8eOWYdS52ki51oPdlegi1ZoyJU0k7oCV+JJ40xPnToVz87s1+LZe/XVVzPtRzf0WRUfJO373Pnnf/7n6KkFbae5NwuqsMyFtcqONdhczcS/F8rV9Gc/+1mzqkWLFpn50UzrOyZ6/LHHHovumtu+FWZ69OiRVb4W96s6UKt2sy7es1PKd9Thw4fNWq2AIKugyvnG81rli8kjsKEYtQqfo2W6fBFqL774YoVbp3oEaiOgH4P6oaV7Xys0KKpU0ZT5kn6oKjrcl9IsjeQ7l3wEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBHIJaMyLNdYr38BPjRGLp6uvvjora8yYMVn74c6uXbvCzcSrBmNa6ZprrrGynW8AqgZNp02a5HfcuHGJ4rmCO2rVbqKTsQyttHHTTTfFcv+wW6mgBtWuwaIa3B9P1sz18TLaf/nll61s9/Wvf93Mr1XmD37wA7Pp3/3ud2a+L1OrKPiCNl544QXfaXnzFdSQZsxa3opKKKCJsRcsWJCqhqeeesos9+6775r5yqzFs6fPiBUrVph96t+/fyZf7501wH/lypU5Z5PPVNAENzQhdPyzP7wM3eO5ZtEPyxXzqvs8ukpQWEe+yaR9Ky2E5+tV72G+AKPvfe970VOCbWtS+Frcr+pMrdpNoMQySv2OOn78eKzGP+zGJyY3C1Upk8CGKkEX2owvuizXj71C26A8Ao1NQCuSaJWPQiO6FKVpRZ/q+o4cOdLYLpP+IIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCDQjgRkzZphX4wsy0ESd1qz1Xbp0yarHN4Nyrslx165dm1WHdjSuRgOLrTR37txEtm/AeKJgJMMaiK0ADN9gyVq1G+lyYlMzxw8aNCiRr4xKBjWEDT766KPhZtbr9u3bs/atnVmzZiWyFXDje98ThauUYQVqKKCjd+/eBfdg2rRp5jlpV7mIn6yB9/FnMF6m0vsDBw50VtCTr91rr73Wd8ibX6tnT4FaVvCOBsEroEGfFWPHjk30W59fo0ePTuQ3lwxrZZ7w2nIdC8uU8vrAAw+Yp2tlFV/yrbQQL79u3bp4Vmbf9x1ofZfW6n6tVbsZJGOjHN9RF110kVGzy7tCjHlShTIJbKgQbKnV6gvS+hA///zzS62a8xFolgKDBw82r+vDDz8088lEAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQKAcAsOHDzersYIMVPCdd95JlLdWPFAhKz/X5LjWsalTpybaU8apU6fM/FtvvdXMLybTCmyoVbu+/nfr1s2dOHHC9ezZ0yxSjaAGNfzNb37TbH/OnDlmfpipmdGtVTy+//3vh0UaxatvpndfQEe+TmvyXGsyXCtoKF9dCijwrZCS79xyHp88eXJB1RW6ukStnz1fkI4CGrT6jZW2bt1qZTeLPF2bFeyjiyvmPi4U5ctf/rJ5Sq5VT+LfMRrnvHjx4kQ9VrBbWOjNN98MN7NeP/vZz2bt1+p+rVW7WRcf2anGd5RWKsr1vke6U/FN+5Og4s3SQLECBw8ezHuqoqWeeeYZpw8QveaKfMpVmWbPj9azcePGXMWDY/qBp5s7bHvVqlVO0VXVSvpAUZs33nhjED2pL+7wb9iwYYGF9WO50P4Vc536ARn1tL5w1Te9X/H+K9BFeTpWjv7revW+aFkaRbldeeWVgZfaUfSr9vUjSe2pjO9P94TvQ7xQ01LLa9UGK7Vt29bKJg8BBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgbIIdOrUyZzENj4ANGzMWnHhzjvvDA9nvVr5GsSu8UvxpHFF69evj2e7b33rW4k8Zbz77rtmfjj5rupL86dKLrzwQrMuK7NW7Vp9Ud7TTz/tunfvbh7esGGDa2hoMI+VO1OrK2iVhXhavnx5zjF4vsGoX/nKV+JV1XRf4xGt9Bd/8RdWdqo834z2hY5ZLDSgIFXniih09OjRgs4qNLCh1s+eVqGZPn166mvU6jH6fG2OSZ/hCqixkgLaBgwYYB0qa16bNm3MPsyfP99sx/qOGTJkiPv2t7+dKK/vIpW3ksbRxtOoUaOCsb7R/Frdr7VqN3rt0e1yfkfpM8P3DCrASOOHfQFI0T5VcrtNJSun7tIE9ANRy+wUmjTAO37etm3bnG/gt1W/PlDq6+sTh95+++2cyz7169cvEf05e/Zsly9qNNFQgRnq75QpU9zSpUu9Z+qDcuTIkcHxlStXlrQ8UTHXecUVVyRsTp8+nYk01A9MaykldVjv55o1a4I/7Zfaf33xWMuPhW3pVRF/uTxVRmnSpEkFLX/1x9PK/vKzn/3MrNP3T4dZmEwEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBIoQuOeee9zcuXOzzgwHdsYHH1sBD76ZszVo1EqaqDR+7L333rOKuh49epj5J0+eNPO7du1q5heTqdUpNFAymmrVbrQP0W0rGETHNUYrbhw9rxLbmr190KBBiap/+ctfevui8XnxpIHRvhnw42Wrtf/zn//cbOqiiy4y80vJ/OSTT5wCRdKmQgMK0tZbjXIaHJ92dv/G8Oxp7KJvlYK4ly9wJV6uKe7nGtf4/PPPV+2SvvOd7yTGrYbBc/FnyPqOueOOO4JnTSs3xMct/8///I85btl6/x944IHENdfqfq1VuwmAP2aU+zsq1zOo917jo5W0EoeCVuL3ga+f5cpnxYZySZa5Hg3Ut5aHspZOijfdq1eveJar1qz1YbRutAMdO3aM7pZ9Wysh6EdYmkH4YeNaNkUrOCiwoJhUzHVa5+ifFkWH6se7L6jB6p/6r5UWCk2yUpu+oIZC61P5PXv2FHNa2c9J++Os7A1TIQIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggECLF7jttttMg/hA0FOnTpnjwnyzkrdv3z71ahDWxKCaBduXXn75Zd+hiubXqt1CL2rBggWFnlJy+S996UtmHQ8++KCZf+jQIfN+qvRExGZn8mR26NDBLOGb1d0sHMsMJzqOZZsm8TItcb8xPHsav5hmrJ8m4W6u6cYbb0wEAYTXWu0gmxtuuCFsOutVwXPxZH3HhM/gxIkT48XNCbMPHDiQKKcMK7ivVvdrrdo1YXJkFvsdpWdw//79OWr+w6Fp06a58847z+n3je99y1tJEQUIbCgCrRqn/Nd//ZfZTDGD2c2Kmkmmfuj7fvDku0RFMZ177rn5ilX0+L59+1zr1q2L+iGlqDVrSR5fh0ux8tWpfP04rnWyotjVp8YYeVxrK9pHAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQKL/AZz/7WbPS5557Liv/rbfeytrXjsa45EpaDSKeli9fHs8yB5Fas2CHJxY77io8P83rxRdfnChWq3YTHcmTofFl1Q4Q0IDTSZMmJXqmvmj8Vzw9++yz8axgv2/fvmZ+S8n8kz/5k5ZyqQVdZ2N59gYMGGAGbEUvJr7SS/RYU97WGOA1a9aYl6BgDgWzVTMpqE6rLcTTww8/HM9ymuk/nrp06RJkTZ48OX7I/fjHP07kaSWceNKqI23atIlnFz02OFFRjoyW+h2l9+348eMuzWT7+r2hlZw0mbz1PZSDt6hDBDYUxVb5k4YOHWo24ouOMgu3gMy6urqcV6mHTj/89cHXGFO3bt283VK0dL5+T5gwIfUHxV/+5V9629JyZNu2bQuisBQNmStSO17J3/7t38azqrq/d+9ep8gwKz322GNWNnkIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCJRVQAPSrTFf8Qk7n3/++US7U6dOTeRFMzRGyErRGZTPnDljzoLe0NBgnVqVvOnTp1d9kK4urNB2V6xY4dauXWuazJ07123dutU8VqlMXzDFK6+8kmjyu9/9biJPY8FaSvrUpz5lXur//d//mflkVlYg7bO3c+dO74oFYQ83btwYbjabVz3bmtDaSvoMqlUwh7UijIIvoqupaED7rl27sroeDcqzgvs++uijxMTZCxcuzKpDO9/5zncSedXISHu/lrsvhbZbqe+odu3aOT2LGjucb6yyDMLJ5DVmt5KJwIZK6hZRtz4IrrzySvNDWz84rKikIpppFqesWrXKdNLFaWC+luTRQ6d/BjZv3uxOnz7t5s2b1+ivXYEFug9Wr14d9Fv/dCxevNjb73hUt1VQHyRWlJ8CPz755JMgslhRuorCUjSk2t69e7dVVRCdp/6FfyNGjDDLVSNTP158wSH60swX+FKNPtIGAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAQMsQ0Ezc8aSBoNEZjpctWxYv4r74xS8m8qIZvXr1iu5mtqOD8Xfs2JHJDzc0NkgDF31J46uspPFE4digUl4XLFhgVR+M67IOVLpdq03l6T3SGCjfZLAa8Hns2DHf6WXP79GjhzmD+t13353VlgJbNHA4nvIFysTLN+X9DRs2mN2/7LLLzPyWnlmrZz7uXl9fH89K7F999dVOYyebS1KQmwKlrKTxobUch/mtb33L6pZ77733Mvm///3vM9vhRvSzxhfcFw3I0nehxsfG0+jRo+NZwX6t7tdatWsiVOE7SmOHNcZ6//795opB8X5pzG70d038eKn7BDaUKljA+fv27Qt+8OnDNv6nHxnPPPOMO+ecc8wHVz8yfZGYBXShWRW96aabzOvRUlwamB9fkke2M2fOdB988IF5Xq0z9cNY/wgosCCa9IGvLwDrnxqVu/fee6PFzW1fRJuWLvIFy+gHsj6o4kk/hhUwUoskH/2TsG7duiAASD9erKTnxYput8qShwACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIBAOQR8A1PDAaEaCBif8Vrtxsc5xfuicU/5VoOwxspEB53G69T+17/+dSu74oP4a9WuebGRTI058yWNpapmevTRRxPN6d45dOhQJt96zy+44IJGOxmsb7Bw5oKK2PDNHK5nhpQUaAzPXiHjYG+//fbkRTTBnBdeeMFNmzbN7LkmPM/3WW2eWMZM3+dbdNJtjW+Op/iKQFZwX3TVovC7MFqPPrN834G1ul9r1W7Uxdqu9HeUJkZfsmRJML49Gjhp9eWuu+6yssuSx6d3WRjTVTJo0KAgcKF169Yu/te1a1fnWzJMM8/XaiB5uiurfqk9e/aYjepDTg9WrqRZ/BXd25iSlpbJ9aGjvo4fP95pwH48KdAgX/TT0qVL46c5LU+joIlcSR9U0eWCwrK+IIvweKmvCvxR2+pf9E8/ODt06OBGjhyZFQCk9z1MPC+hBK8IIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAAC1RTQ4MzoOJaw7XBAqDWoU5O4pknWwNf169dnZjS3xvP4ZuEO22vbtm24mfX64YcfZu2Xe6dW7aa5DmsiWJ2nMVqTJ09OU0VZyowZM8as59lnn83kf/e7381shxtWQER4rNavf/7nf252wVptxCxoZGpi33jSM0hgQ1zlD/u1fvY0Abi1aoE1LlI9Xr58eZMfO6tJnMeOHWu+IQpqKCTQw6ykTJnWd9H3v//9TO0//vGPM9va0HMWXxHICu6Lfk8tWrQoqw7tPPjgg4m8MKNW92ut2g2vO9drNb6jNGZX76UmItc9aiWNSa7UiioENljijSwv+uHQyLpWs+4sXLjQbPvNN9808+OZWqWgsQQ36AvBt+xavN9PPfVUPCvYf/fdd818Zfo+PG6++WbvOdEDDzzwQHQ32Lb+EUoUKiHjnXfeMZdJ81UZLqmm1TisSGTfeeQjgAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIFBOgXvuuSdRXTggNAxwiBZIO1j+hhtuiJ6W2dY4G40PslaC8M3CHZ58ySWXhJtZr1u3bs3aL/dOrdpNcx2ajNU3U7UGcmqQcjWSgmQGDhyYaCoMZtAA8XDMVLSQLyAiWqZW25/5zGfMpvNNZGye5Fww6PaRRx5JHB4yZEgij4w/CNT62fvCF75gvhWa+Nv33NXX15vnNIXMTZs2BZM4W33VuNHGEtSg/t19992Jbuoz5sSJE8Ff/PPG+q7zBfeFwUvWBN2+CeHVmVrdr7VqN/EGGBnV/o7SPTpv3jyjJy64L8wDJWYS2FAiYDVO1wezbkbfKgXV6ENjayP8sR/tlyLA8v0Yj5ZXcIMveilarpLbn8O5swAAIABJREFU+vFZyA+za6+9tuDu+FZlKCUq9fzzzy+4H4Wc4It4y1dH3759nZYu8gVz5Duf4wgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIlCJgDdLUgNBjx465l156KVH1gAEDEnlWRqdOnaxst2bNGqfghngaN25cPCuxr/FTVrrjjjus7LLl1ardtBegmaqt2ct1/siRI52CCqqRfvSjHyWa0b106NAhc/JXjUXTwOLGmqzVTNRXKzghzTX85je/MYtNmTLFzCfTuVo+ey+88IIZgLVy5crgrdFz51u5QWMCS0mVHu9o9W379u1u0KBB1iGnz+dCxo2alZQ5s3///maNCs6wgt1uu+02s7wV8KDJqvUdaKW6ujorO8ir1f1aq3a9ELED1f6Omj59eqwHf9g9fvy4mV9qJoENpQpW6Xz9IOnZs2fVIj6rdFlFNaPlTeLRX6rI+kDM14Dvx1K+88p1PG3EddieL0ghPF6JV98/RZVoK6zz3HPPDTcLetV9MW3aNNe6dWunL1QSAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAALVFPANzF28eHFiUK/GLrVr1y5196zB9hocq7rjaerUqfEsc98asKgxOJpBvZKpVu2mvSa5+saWde3aNVgtIG1dxZYbPHiweercuXPd/PnzE8eKDRBIVFShDI19GzVqlFl7MSthKMjESr7VTayyLTGvFs+eZv0fO3ZsglvP2OjRozP5b7zxRmY7uqExgQroKTYdPHiw2FOLOk+TmPfr1888V8+ABvo3tqSJsq3nU0ElVhBGnz59zEuwgvuWLVvmnn766UR5616MF7LK8B3lgvekWt9RvnHLlXquCGyIPwUV3NcDpg/eDRs2JP5WrFjhdNz3wzbslr6MFcnVktO+ffvMy/dFgJmFG0nm0aNHC+qJ7wMiVyUKBLHSJ598YmUn8hTVHU+V+kAK21EUnp4TfaHp2Qj/tK/nxFpmLTw3fFW0o7V8X3icVwQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEyi2g8T1Dhw7NqlaDD2fNmpWVp52JEycm8nJl3H333YnDW7ZsMWe8b2hoSJS1Mu6//34r29XX17szZ86Yx8qRWat2C+m7Bif70vDhw32Hypave8kKZlEAw65duxLtXHvttYm8xpaxcOFCs0uFroShCYWtyZE1E75vtnWz4RaYWYtn77rrrjOl33zzzax8jRu0BrKr0NVXX51V1rdjjcnU83Lq1CnfKWXN37t3bzCJuVWpvhtWr15tHWoUeffee2+iH8uXL3dLly7Nytf4TQVCWMkaAy1/BafEk5UXL1OL+1V9qFW78evPtV/Md5RWzih0DPrhw4fNblx44YVmfqmZ9p1Vaq2cbwrcd999Tj8YhwwZkvgbM2aMW7BgQRDpquU5fB/OqtgXyWU22gwzfQPyu3Tp0gyvNnlJaQb1R8/SF4j1ZfHwww9Hi3m3rS+PtBHd3kpTHNBzMn78eKdnI/zTvp6TzZs3B/846R8zX9SZmlD0Hys3pMCmCAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggEDZBGbMmJFVlzUAWwU0FqaQdMUVV6QqrrFCaVeC0EBi33ik1q1bFzRLugIhVq1a5Xr37h385epsrdrN1af4sfbt2wcTGcfztb9+/fqqTLo6Z84cq/lEnmZa9w00ThSuYUbfvn294720EkaugbphtxXUEB9oHR578sknw01ePQLVfvY2btwYPC/x7ihop0ePHvFsczUSFdJYwTQre1x//fWJOpXx0EMPmfnlzFTwRLdu3cwqFdTw+uuvm8caS+Y111yTqit6Bn1JAVnWyg9WeWtca7xcte/XsP1atRu2n+a1mO+oP/uzPwvGoOt92rp1a5pm3IABA8xynTp1MvNLzSSwoVTBAs4/efJkqtL6UanB275ldVSJfgCSsgUuuuii7Az2MgJWxKOWJMv3Q9D3w/jWW2/N1F2rDX2w6gPzwIEDwcoOvn5o5QbfqhW+c8hHAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQKBYgREjRqQ6VYO8C0maiT7NQNCZM2cWUq175ZVXvOU7d+7sNIhV44ziKzhoTM6hQ4eCwcY33nijUyDETTfdFKwmoBm64+XjjdSq3Xg/cu1rImPfJMWadHXnzp25Ti/5mDXw26o07SS31rnVzlNQiC/17NnTDRs2LBhwe+LEiWDcl+4jjRF7/PHHncaM+YIaZs+e7So10NbX36aaX61nT++db6WFJ554wuTTe7xhwwbzmFb2yPe5osAqK2m8pD7LNGO9PrcUcKF7Te1plYVypLvuustbje77K6+8sui/2267zVt3uQ5o7LIv0C3ahiaqzpWslR/i5bW6iuzTpGrdr/G+1KrdeD9y7ZfyHaX3WhPKK2BIn7fRpO93BT7ouLVCkO97MVpHsdsENhQrV4XzdMMtXrzYbOmOO+4w81tyJoPX/e/+j370I/Ogfgg+88wziWP6kNIXob7M40krJPi+/ONlq7Wv6PVly5Z5m3v22We9xziAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggEA5BTSLssbY5Eo6nnZVhWg9aYIW8g06jdanbQ2e941T03ENJNc4IwUuaCCqBjrqVSsEKPBBg43XrFkTrzbvfq3azduxWAFNUuwLKKmvr3eapb2SKdd7E7brm1E7PN6YXtXXXINiNQBcA27PO++84B7TfafVHKZNm+a9DM0Q75vE13tSCz5QrWfv9ttvN5VXrlyZc4WRIUOGeJ85X51hQwpu8T2v+izr0KFD8LmlgIswyObIkSPh6SW9/upXv8p5vladKPZv+fLleSeyztl4yoP33Xdf3pL5JiFPs/JDmnbCjlTrfg3bC19r1W7YftrXUr6jtKKUvsP1eavvdY0N1ne8vt/1OexbcWrevHlpu1dwOQIbCiar7glTp041G9TNki/yzDyRzBYpoGhtRbhZSZHD+kBS1LSCGfTBpA8pfRFa6Xe/+52VXfM8BTf4ogUXLlxY8/7RAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAIGWI3DPPffkvNh8x30npwlaqKur853uzdc4tVwTi0ZP9A10jJbRtsYk5Uu1ajdfv+LHt23bFs/K7Pfp0yezXYmNO++8M2e1uYIEcp5Yw4MaiFuufk+aNMmtXr26hlfTNJuu9LO3fft2cwyigrpGjx6dF803TlHjGvOtlPLSSy/lrT9aoG3bttHdRrutoLlKp5tvvjlnEwoiyvfZrqA9X3BJWPlVV10VbqZ6rfT96utErdr19ceXn/Y7Kl/QpVZnyPcdr7YU+FCpVLmaK9XjFlivPgisFF/6wyoT5u3bty/cbLavBHr431rZ+AIVwrMUNa0y1rIxYRlF/za21RrCvun1xRdfjO5mtg8ePJjZZgMBBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgUoLaLLRXEkTkBaT8gUt+CY/TdOWJhbNNTgyTR1hmQ0bNuQd/BqWrWa7xY4j0kBdn43GW+3Zsye8nMxrsW1lKvjjhgYz+yZ8VZFCZj6P113s/tGjR4s9NXOeghvWrl2b2S9mQ+cvWbKkoFPL9b4U1KhRuDH0o5LPXr9+/Yyrdk4BD2mSZo2fPXu2WXT48OFmfpjZ0NDgPTcsE309efJkdLfo7Uq/p5WuXxeuFS9ypSlTpuQ6nDmmgABf0ueZJusuNFXyfs3Vl2q2W+x7nPY76uc//3muS817bPfu3a5v3755y5VSgMCGUvSqdO6wYcPMlg4fPmzmW5n//u//bmU3q7x33323WV1POS8m3/JLadrSPxu5vmzS1FHpMr5/3PTPw9mzZyvdPPUjgAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIBAIaPLQoUOHmhoa1FnKwMAVK1aY9Srz8ccf9x5Lc0D90jgbDRjPNZg+XpdmgdYM/Br8r/OHDBkSL5Jzv1rt3nLLLYl+XH755Yk8K0N99NlbM6mX0la8/Zdffjmeldnv0aNHZrtaG9dff32iqcGDByfy8mWMGDHCnT59OnDNN8N7WJfKrVy50mmyX51faCrn+1Jo29Hy5epH//79o9UG2x07dkzk+TIq8ez5xurNmzfP+cb4Wf2bM2eOOfN/mntF52rMY74Z6rXiR7kme37qqaesyyhLnq6jXP3M16FcAUe+idrjdU6bNi2eldn3TWCdKZBjoxL3a47mMoeq1W4pnwtpvqP0XaXnc8uWLd7fKJmL/uNG+Jmr86rxfVN4yEu8x+xXXOD999832zhy5EhBH/JmJc0oU5FA1frgbkpsWtkjvlqDPmgWLVrk7rjjjrzLxujHhP7pqOTSMeXyzPUjRB+q+ZZAKlc/qAcBBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBozAK/2MSq9435/WmufeO+a67vLNeVS+D1118PBhBq4HaYNAan1HE4Y8aMcfrTwG79KZWj3rCPetWA8c2bNwf937dvn9PEom+99VamiAZHfvrTnw4GHV944YUlX1NYcaXb1SoBGg8VurVu3bqgMUWh/alTp8Iue2ceL7WtTAPOuYsvvji6m9levHhxZruaGwMGDAgMw3u7lPtP50ZdNcHxjh073P79+zOX1LVrV9enTx93ySWXeL0zhfNslPN9ydNUzsPl6sfzzz/vfvKTnxR9T4edLOezp3F6Gq8X/Ywq9FkL+7Vz586segq51xRgdeDAAXfs2LHgngrH4mqcocZQlvOzS/2Voa67qafwOqKfc4W46/rDAfTRe0D5xazUYHmW83616vflVbrdUj8Xop+l4TVY5voMD3+jfPTRR+5///d/3XvvvRc8KzqvnJ+5YT/SvhLYkFaqhuU+/vhjs3V9SadNHTp0SFu00Zfr3r272cdnnnmm4Ehfs6JmlmlF67766qtB1Hf0S1s/AMKkABH9ELQiicMyjfFV/0T5kr5YSQgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIVFNAA3ytQYXl6EOhA02LaVP91wzr+mtoaCimiqLOqWS75XBL+56Woy0B/uAHPzAdNbFtrVIl7m25auxapSc4Ltf7Uqp9ufpRrnp0PeV89srVr1Lr0ThIDeTWHym9QNrPuVw1lvre5apbx8p5v+ZrK3q8ku2Wwyzte6fr6NKlS1W/36OO1jaBDZZKI8tbunSp2SPdvGnTCy+84KZOnZq2uJs5c2bqstUuqAfJSnJasmSJdcibN2XKFO+x5nJg7969iUtR0EKYmtOX9vbt28PLynotZFm8rBPZQQABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQRqLDB37txEDzTjfKdOnRL5ZCCAAAIIINBUBdKPjG+qV9jE+z1//nzzCvSjxBfY8OUvfzlxzvr1692JEycS+VbG448/7h555BHrUKPIU2DD9OnTzb5s2rTJzLcyZesLGrHKN9W8jRs3Jrr+93//94m8WmeEy7uV0o+rr77aPP32228388lEAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBqzgG9M3KJFixpzt+kbAggggAACBQuwYkPBZNU7Yd26dW7WrFlmg88995yZr8wRI0aYA/a/853vuAULFnjP0wEN9ve1mfPEKh+cPHmyGXwxaNAgpwHyvlUdwm42lesM+1vK65AhQ9zy5cuzqlAE77Jly5zuo/r6enfuuee68847L1j2TgEzrVu3Dv7yOWZVWsLO2bNng/ZUxYYNG5z6XGiaMWOG95QJEyZ4j3EAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQaO4CI2bsau6XyPUhgAACCCDQbAUmTpxoXtsNN9xg5pOJAAIIIIBAUxVgxYYqvnNt27ZN1dqBAwfcjTfe6EaOHOktn2vg9+jRo83ztArDqlWrzGMaWK42m0JQgy6gb9++5nUoUwP1dT1WUtBDU7pO6xoKzfPdR7t27XJa4aBnz56uW7durnPnzq5Dhw5BgIMCHRTgoMAG/fXu3dspcGD79u2FNp+q/L59+zLl1Ce1qXs1zSoO4XvqW2Vk4MCBrq6uLlM/GwgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIBAUxA4duyY27JlS6KrQ4cODSaxTRwgAwEEEEAAgSYswIoNVXzzBg8e7K677jp3+PBhs9Xdu3e79evXm8eimSqXK7Vv395deumlTgPX4+mmm25yo0aNcgsXLgzKHD161K1cudI1xRntteKA1W9dtwblr1ixwinIQ4P0Dx065J5//nk3bdq0OEmz31cQyKRJk8xVPNJevEwVOBAGD7zxxhuuoaEh7el5yx05ciRRRveqkn6EK6jiz/7sz4LgC+WdPHnS7dy502k5taVLlybOjWZoBQgSAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIINDUBBYvXmx22ZdvFiYTAQQQQACBJiJAYEMV3ygNDs83CDtfdzRIu0ePHvmKuVdffdX169fPLLdmzRqnv6aexo8f72bPnm0GcOjaxo4d29QvsWz9X7JkifvVr35lRu8W08igQYPc9OnT3YIFC4o5PXFOr169EnlhhoJ90gT8hOWjrwra6dSpUzSLbQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEECgSQjMmjXL7OfnP/95M59MBBBAAAEEmrLAOU258y2t71qpYciQIakuW7P0a9B/sUkrOWjFg8aeduzYUVIXP/744yZxnSVdpHPBihXWkmSl1KvVG9atW1dKFZlztcLGwIEDM/vl2Fi7dm2wYkc56qIOBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQKCaAlu3bjWbmzRpkmvVqpV5jEwEEEAAAQSasgCBDRV497p3717WWhVgcPbs2VQrNUQbnjNnTjCrfjQv37YGl58+fdq1b9/e7d27N1/xxPGDBw8m8vJlFHNOWGebNm3c8ePH3QUXXBBmpXrVdX7yySfBbP5aSaPQVEyfizmn0H5Z5U+dOuU6d+5sHXL79+8P3m9ZyFEBLcr74IMPgr833njDjRs3zjxXmSNHjgzuTW+BAg5s3rzZzZs3r4Az7KJ6bxWwMmLECLsAuQgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIBAIxf46U9/avZQ4wJJCCCAAAIINEcBAhsq8K5q9vnFixcXVfOll14aDCRftmxZMLBcAQ1jxowpqi6dtGDBArdt2zanenMlHdeM/hpcrv4r9erVK3HK+eefn8iLZtxyyy3R3WD78ssvT+RFM4o5J3p+u3bt3IEDB9zKlSvzBjhEr1NBEUpf//rXo9UF2x07dkzkRTOK6XMx50TbDLf79+8fbmZec/X3q1/9aqZcdEOBDF26dAneb1nIUQEtyqurqwv+Ghoa3PPPP58zeKSYwJBoP6LbM2fOdGfOnHEKqBg1alT0UN5tRSJrVRPdw506dcpbngIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAQGMVeOCBB4JxiLNnz3b605hEjY/q0aNHY+0y/UIAAQQQQKAkgVZnNXKe1CIETpw44bZv3+5+//vfZ673sssucwMGDAgGtWcyIxu6PbSCg1IYCBA5bG5qYLr+lFq3bp1q2atizjEbd84dOnQoCOZ46623MkWuuOIK17dv32ZznWm9FPDRtWvXjEO4oWAXeRSSjh075jp06JA4pZi6EpXkyFC777//vtuxY0ewmkRYVNfVp08fd/HFFwcBGWF+c3/92sz1wSX+6/yhJV3qF29ZmHV+XX1D1j47CFRSYO/bm7Kq5/7L4mCnQgLcdxWCpdqcAvH7LizM514owWslBeL3329fuq+SzVE3AggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCBQksAfpqwvqQpObioCmpFfQQz6S5tatWqVOqAhrFMrPoSrPoR5+V6LOcdXp2br10oD+kubmtp1pvXSagvxNHDgwIKDGlSHVnOw0tq1a4uqz6rLylO7vXv3Dv6s4+SVRyA+8K08tVILAukEuP/SOVGqvALcd+X1pLbCBLj/CvOiNAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggEDzFzin+V8iV4gAAlGByZMnR3dL3h41alTJdVABAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCLRcAQIbWu57z5W3UIGNGzcWdeVbt241z+vYsaOZTyYCCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIJBGgMCGNEqUQaCJChw9ejTR8+XLl7s9e/Yk8nNlHDt2zA0cONAsctFFF5n5ZCKAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAmkE2qQpRBkEEGiaAoMHDzY73rNnT7ds2TL3zW9+07Vr184so8wzZ864f/zHf3QTJkwwy6xYscK1atXKPEZm4xb47Uv3Ne4O0jsEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAgRYj0Ors2bNnW8zVcqEItDABBSa0bt0651Vfeuml7rrrrnNXXnmlq6urc3v37nWbN292r776qtu1a5f3XJ23c+dO73EOVEbgazPXBxX/6/yhlWmAWhFAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEKiyACs2VBmc5hCopsA555zjdu/e7bRCgy8peGHp0qW+w2b+BRdc4N566y3zGJkIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggEAhAucUUpiyCCDQ9AR69OgRBDeUq+ezZ892Bw4ccAqaICGAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAqUKMDK5VEHOR6AJCCi44ezZs+6NN95wAwcOLLjHWqFh3rx57vjx427OnDkFn88JCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIICAT6CN7wD5CCDQ/AQaGhrc5s2b3ZkzZ9yHH37otm/f7nbs2OE++OADd+TIEXf48OHgoi+++GJ36aWXuquuuip4bdeuXfPD4IoQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAAAEEEEAAAQQQQAABBBBAoFEIENjQKN4GOoFAdQXOOeccV1dXF/wNGTKkuo3TGgIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggEBE4J7LNJgIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCBQVQECG6rKTWMIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCAQFSCwIarBNgIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCFRVgMCGqnLTGAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCEQFCGyIarCNAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACVRUgsKGq3DSGAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACUQECG6IabCOAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggEBVBQhsqCo3jSGAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggEBUgMCGqAbbCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggUFUBAhuqyk1jCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAgggEBUgsCGqwTYCCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAghUVYDAhqpy0xgCCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAghEBQhsiGqwjQACCCCAAAIIIIAAAggggAACCCBP0UiIAAAgAElEQVSAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAlUVILChqtw0hgACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAlEBAhuiGmwjgAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIBAVQUIbKgqN40hgAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIBAVIDAhqgG2wgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIFBVAQIbqspNYwgggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIBAVILAhqsE2AggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIVFWAwIaqctMYAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIRAUIbIhqsI0AAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAJVFSCwoarcNIYAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAJRAQIbohpsI4AAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAQFUFCGyoKjeNIYAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAQFSAwIaoBtsIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCBQVQECG6rKTWMIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCAQFSCwIarBNgIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCFRVgMCGqnLTGAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCCCAAAIIIIAAAggggAACCEQFCGyIarCNAAIIIIAAAggggAACCCCAAAIIIIAAAggggMD/Z+/+Y6su78WBPz1UaovyaxS97WLBGJgxdN4FYq41mKh4c4OyZdfpMIt6/wBvLiQzIiSLMeD+cLmKZskVc0dnAn84548lE2TLBZdtBJe74XUBtywQIu2uNJlFWgQpFWy/ec5N+z3t+Zy25/T09Jz29UlOzufzfn6/Pgf+et59CBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECJRUoLqkoxmMAAECBAgQIECAAAECBAgQIECAQAkEvnbfCyUYxRAECBAgQIAAAQKTLfD+m49P9hSMT4AAAQIECBAgQIAAAQIECBAgQIBAEQSc2FAERF0QIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAEChQlIbCjMTSsCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgCAISG4qAqAsCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgMIHqwpppRYAAAQIECBAgQIAAAQIECBAgQKByBOoXL6+cyZppxQp0nnxvyNz97oZweJggAb+7CYLV7YgCw393A5X9vzcg4XsiBXL9/iZyTH0TIECAAAECBAgQIECAAAECBAgQIDDxAk5smHhjIxAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQI5BCQ25IARJkCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBCZeQGLDxBsbgQABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEMghILEhB4wwAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgMPECEhsm3tgIBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQA4BiQ05YIQJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBiReQ2DDxxkYgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEcghU54gLEyipQEdHRzh//nyYOXNmmDVrVqivry/p+D09PeHixYuhuro6PX4qJeenpC/AYAQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQITFsBu7en7asvn4XffvvtobGxMSxdujQsXrw4LFy4MOzYsaNkE6yqqgp1dXVh/vz5Yfbs2WHGjBmhs7OzZOMbiAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAtNZwIkN0/ntT9Da29rawqlTp0JNTU1oaGhIf0Yaqru7O6v4woULWbGJCPT19SV2+9lnn416akS+60wcSJAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQLTXEBiwwT9AC5fvhx+85vfjKn32tradBLAggULwpe+9KVw1VVXhXiKQCVe8+bNC8MTFVavXh3efvvtslxOoc6Vts6yxC/CpI4fPx4OHDgw5ISN+vr6cMstt4Tly5cXYQRdECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAw0QISGyZI+IorrhhXzytXrgzPPPNMaGlpGVc/pWzc0dGRldQQx9+3b1+IJyOkUqlSTmfCxpou65wwwCJ1/Nxzz4UtW7bk7O3ZZ58NmzdvzlmugAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACB8hCYGjvNy8NycBZdXV2D94XeHDx4MNx2223pkxviRvpKvwo9GaHS1j1d1jnZ7+XcuXMjJjVM9vyMT4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDA2AUkNozdasw1z549O+a6Y6nY2NgY9u7dO5aqk1rn888/zzl+f39/zrJKK5gu6yzn93LPPfeU8/TMjQABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBPAQkNuSBNdaqM2fOHGvVMddbs2ZNKPeTG6655pqc60mlps5PbbqsM+fLnOSCDz74IMQTTVwECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECEwNgamz27wC3sehQ4fCF198ES5evDjkc+HChXDy5Mnw7LPPjriKm266acTyyS6sra0NcY3Nzc1h7ty56c/KlSvDmTNnJntqRR1/uqyzqGhF7Cz+vpKu+JtzESBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQeQLVlTflyp1xY2NjiCcX1NTUZC1i0aJFYfPmzenP+vXrQ2tra1ad7u7u0NbWFmLdcr1aWlrCkSNHynV6RZvXdFln0cCK1NGOHTuyempqakrH2tvbs8oECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAofwEnNpThO9q5c2eIJx0kXW+88UZSWIzAlBfo7e0NGzduzFrn7373uzCQ3JBVKECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQNkLSGwo01f085//PHFmSX+xPrGiIIEpJvDP//zPWStavXp1aGhoCPE0ExcBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABApUpILGhTN/bvHnzwty5c7NmN2fOnKyYAIGpLnD8+PGwb9++rGX+7Gc/y4oJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQWQLVlTVdsz179uyoCJ2dneEXv/hFOH/+fLjqqqtCY2NjuOuuu0ZtN7xCW1tb+O1vfzvYzw033BBaWlqGVxvy3NvbG956660Q5xDHnj9/foh/VT+VKk0OzeXLl8Mvf/nL8KMf/Si8++67Q/6S/8qVK8NTTz0V7rzzzlBVVTVk3vk+FLLOnp6e8Prrrw96fu1rXwvLli0bMnR/f3/41a9+FX74wx8OmX9Mcon2jz32WFHmHwft6+sL77//fvjpT38aDhw4EP7617+m5xKTZ+LnlltuCffff39igs3ApKNDrFddPbH/lSxdunRgyMHvXbt2hZqamsFnNwQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIVKbAxO5GrkyTspl13Fze3d2d93yWLFmS1e7YsWMhxsd6xQ32ixcvzqp+8uTJsGjRoqz4QCBuQG9vbx94TH9v3bo1bNu2bUis2A9xvo8++mhobW3N2fXBgwfDqlWr0uV79uwJ9957b866oxUUss4bb7wxy+aLL74YTPqISQ8PPPBA4tDxdxBPLBg4tWC883/uuefCli1bco4VC44ePTqi50DjdevWhZ07dw48Fv179+7diX0+/PDDiXFBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQqS0BiQ5m+r7hRf3iCQJxqU1PTqDO+7rrrshIbZs6cOWq7YlSIyRjDr1mzZg0PFfU5noRQV1eXV59r1qwJ8QSHeDpCIVch60xqE0+OiCcnXH/99YnvO9fc4vw3bdoUtm/fnqtKYrwQq8SOMoIdHR0ZT8W9jSdwPPLII1mdxkQdFwECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECU0MgNTWWMfVW8ac//SlxUU888URifLoG48b3fJMaBqziCQ5XXHHFwOOkfJ8+fTrMmDEjr6SGgYk+//zzIddpBgN1Mr/HY5XZz/D7c+fODQ8V7fmhhx7K6mv16tV5nT6S1YEAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJlJSCxoaxex/+fTDxNIOn6p3/6p6TwtI3V19ePuPZ4wsXatWtDc3PziPUmq3DhwoU5h44b+EebdzzNICYsjOX6xje+kbPa1q1bQzwF4cyZM+Ho0aMhjj3W66mnnhpr1bzqxZMgXn311aw2P/vZz7JiAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIVK5AdeVOfWrOvL+/P9x8882hu7s7a4Fx83l1tVc2ALN3795Ep1geN+a/8cYboba2dqB66OvrC/GUgy1btgzGyvEmJhYsW7ZscGrxN/HSSy+FjRs3DsYyb1555ZXw8MMPZ4ay7js7O8O+ffuy4jHx48SJE0N+V/PmzQtvv/12iIkFjY2NWW3mzp0burq6suLFDtx0001ZXb744ouhpqYmKy5AgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEDlCjixoYTv7vTp0yFuUo8b7Id/4kbx3bt3h1Qqlf6L+cOnFTegb9u2bXh4Wj+vWbMmcf3r1q1Lb8zPTGqIFaPt5s2bw8cff5zYbrKDMRkj/j4ykxrinKqqqsKGDRvCrl27Eqf42GOPJcYzg08++WTm4+D9yZMnhyQ1DBaEEBoaGtInOGTG4n1MumlraxseLupzrqSV6OAiQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGBqCUhsKOH7XLFiRXpz/YwZM8Lwz/z588MjjzySOJu1a9dO+EbyxIHLOBhPE0i64mkCO3fuTCoajNXX14dLly4NPpfDzaZNm9LJGCPNJZ7KEBNchl8x0eDy5cvDw0OeW1tbhzzHh9deey2dNJFVkBGIpzfE39/wK1eSxfB6hTzHpJ+kpJV4koWLAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGpJyCxoQLe6TPPPFMBsyztFF944YXEAf/85z8nxocHq6uryya5IZ4wsX379uFTTHz+8Y9/nBj/6KOPEuMxGBMFkq5vfvObSeGs2Pe+972s2EQmNvzrv/5r1ngrV67MOskiq5IAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIVKSCxoQJe2+LFi0P8y/m5TimogCUUfYovv/xyVp/xtIaGhoaseK5ATG44c+ZMruKSxJubm0c9YSJzInfccUfm45juq6qqEuulUoX/858zZ05in+MNdnZ2hqTTJd5+++3xdq09AQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJlKlD4zuYyXdBUnVZ3d3dobGwM77zzzlRd4pjX1d/fH6LH8Ou73/3u8NCozzEZYjKv9evX5zV8riSFvDrJs/LVV1+dZ4vCq69YsSKr8datW0Mp55A1AQECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBCZUoHpCe9f5EIFNmzaFb3/726G3t3dIPD6cOnUq/OEPfwhvvvlmaG9vzyofCKxatSocO3YsLFmyZCA07b5Pnz6duOYHH3wwMV7OwQsXLuQ1vUISG2IiSNJ16dKlUFNTk1Q0JLZv374hz/Hh7NmzWbHxBmLSTtJvPyY2uAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQmLoCEhtK+G4ff/zx0NDQkHPE+++/P2zfvj2d+PDkk0+G559/PrHu0qVLQ67N6okNplgwbshPuubNm5cUnnKx5ubmcPTo0TGvK5VKhaampqykgR/84Adh27Zto/azcePGrDobNmzIio0nEH/PMWln+HXo0KFQSDLH8H48EyBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQvgKp8p3a1JvZ559/PqZFxb+iHxMcDh8+nLP+3r17c5ZN14IFCxZM16WPuu677747q87TTz8dOjo6suKZgVyJD9/61rcyq437fvPmzVl9xASOlpaWrLgAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJTS0BiQxm/z+XLl4cXX3wxcYYPPfRQYnw6B6fzKRajvfeXXnopsUpjY2PYvXt3Vllvb2948MEHQ0x+GH7NnTs3LFq0aHi44Odz584lnk7y3//93wX3GRvW1dWNq73GBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiURqC6NMMYpVCBDRs2hI0bN2Y17+7uDn19fSGVkpuShSOQJVBdXR3Wrl0bXn311ayyRx55JMTP6tWrw+zZs8Pvfve70N7enlVvIPDHP/5x4LYo30nJE7Hj//3f/w2ffvrpqGPEE06OHj2aVW/nzp1h5cqVISZpxCt+x2ShWN9FgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgED5CEhsKJ93kXMmccP5vn37ssrjRu3a2tqseFLg9OnTRf0r+0ljTHZMokfuNxBtkpIaMlsk/cYyy+N9PEGkmKc1xD7ffPPN4cOkn5cuXZoYH2swJjs0NzcPqd7U1BTa2tqGxDwQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDC5Av7c/+T6j2n022+/PbHe+fPnE+NJwV//+tdJ4SkV++ijj6bUeoq5mO985zvj7u7QoUMhniBS7GvOnDnF7jJnf6UcK+ckFBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgMERAYsMQjvJ8+Nvf/pY4sc8++ywxPl2Dp06dmq5LH3Hd8WSP4ac1xJML9uzZE+bOnTti21j47LPPhi+++CK0tLSMWlcFAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQI5CtQnW8D9Usv8OmnnyYO+uUvfzkxnhSsq6tLCldk7Nprr02c9+7du22+T5B56623sqL79+8PS5YsCV1dXaGnpyecOHEitLW1DdZbtGhRuOGGG0Jtbe1gbKJubrnllnD06NGJ6l6/BAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiUuYDEhjJ/QXF6ra2tibNMpcZ+4Mbrr78eNmzYkNhPUnDz5s1J4bKIVVVVJc4jOu3cuTOxLFfw0UcfzVU0ZeKdnZ1Za4lJCwNXTF5YtmxZ+jMQK+V3fGf//u//XvCQ1dXV4brrrgvd3d1D+li7dm14+eWXw8WLF9Pxy5cvhwULFgyp44EAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgckXkNgw+e9gxBk899xzieVNTU0hV2JD0l/AP3jwYOjt7Q01NTWJ/WUGd+zYEZ5//vnMUFndx8SGTZs2Jc7xvffeC8uXLx/TfKNtrqSRMXVQIZXefffdrJl+//vfD9u2bcuKT1Zg3rx54xo6KbGhpaUlfeJEKU6dGNfkNSZAgAABAgQIECBAgACBkgh0nnyvJOMYhECmgN9dpob7Ugn43ZVK2jhJAn5/SSpiBAgQIECAAAECBAgQIECAAAECBAgQIDAWgbH/yf+x9KZOUQXeeeedsGXLlsQ+X3nllcR4DN51112JZU8++WRiPDMYN/tv3LgxM1SW9+vXr0+c14oVK0J/f39iWWYwrjOXbWa9qXAfN/gPv55++umwaNGiEJMeOjo6QjzV4dy5c6GnpyedABNPNxiL4/B+y+n5woUL5TQdcyFAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIIeAxIYcMBMRnjlz5pi67erqCvfcc09YtWpVzvpJm9UHKt97770Dt0O+4ykMe/fuHRIbeIib2OOYlbLZf8mSJQNTz/pevHhxzk35fX19FbXOrMUVEMj1O2pvbw+33XZbaGxsDAsXLgyzZ88OdXV14corrwxXXHFF+kSQeDpG/MQkiCeeeCIcP368gBloQoAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgdwC1bmLlBRb4NZbbw133313OH/+fGLXp06dCgcPHkwsywzGeiNdtbW1oampKcSN68OvNWvWhNWrV4cXXnghXSf+Vfs9e/aERx55ZHjVsn/etWtX4rzjulOpVHjttddCTPKIm/TjaQQ/+clPKuI0imLDxySQdevWhdbW1oK7jqYxMSZ+4nX48OGwfPnygvvTkAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgMCEhsGJErwHTeHj2dzeZzioUOHQkNDw6iz3b9/f1i6dGlivX379oX4qfTr4YcfDlu3bk1M4Ihre+CBByp9iUWb/86dO8Pvf//7cPTo0aL0uWLFirBp06awffv2ovSnEwIECBAgQIAAAQIECBAgUGyB9998vNhd6o8AAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEJkggNUH96nYCBOJJDS0tLWPqOf6V/rjpv9ArnuQQTzwo9+vEiRPjmuKnn35aEesc1yJDSJ9YUaykhoG5xNMb3nnnnYFH3wQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEChIQGJDQWwjN7r22mtHrpBnaUww6O/vH9NJDZldb9u2Lf1X9TNjo903NzeHL774ItTW1obOzs7RqmeVnz17Nis2WqCQNgN9VldXh4sXL4a5c+cOhMb0Hdd56dKlcPXVV+c88WGkjgqZcyFtRprDWMsuX74cZs+enVj9zJkz6fcdLaJjTGiJsY8//jj9OXz4cFi7dm1i2xhctWpV+reZs4ICAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIjO9MzgwAACAASURBVCIgsWEUoEKKU6lUePHFFwtpGpqamtIbyXft2pXeWB4TGu6///6C+oqNtm/fHo4dO5bud6RO4rjxL/ofOXIkxPnH67rrrstqMmfOnKxYZuC+++7LfEzff+UrX8mKZQYKaZPZvqamJnR1dYU9e/aMmuCQuc6YFBGvr3/965ndpe9nzZqVFcsMFDLnQtpkjjlwf9NNNw3cDn6PNN8777xzsF7mTUxkmDdvXvp9R4voGBNaYqy+vj79Wb58efjJT34yYvJIe3t7ZreTcp9k8vd///eTMheDEiBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECCQn0BVf9w575oWAr29veH48ePhL3/5y+B6r7/++rBs2bL0pvbBYMZN/HnEExziNZAIkFGceNvX1xfiJ14zZswIVVVVifUyg4W0yWyfeX/u3Ll0MseHH344GL7xxhvDkiVLpsw6x+oVEz7mz58/6DBwE5Ndokc+V09PT6irq8tqUkhfWZ0UITBWkyIMNald/OPmg+nx/+u5lZM6D4MTIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKJbA//3J+mL1pp+yFoh/kT8mMcTPWK+YlDDWhIaBPuOJDwOnPgzERvsupE2uPq+++uoQTxqIn7FelbbOsXrF0xaGX83NzXknNcQ+4mkOSdeBAwcK6i+pr/HExmoynjG0JUCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECg+AKp4nepRwIEyllg/fr1RZ3e6tWri9qfzggQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQmF4CEhum1/u2WgLh3XffLUjhgw8+SGw3a9asxLggAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIExiIgsWEsSuoQqFCBCxcuZM381VdfDR0dHVnxkQI9PT2hubk5scqCBQsS44IECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAYi4DEhrEoqUOgQgVuvfXWxJk3NjaG3bt3h97e3sTygWBfX1+6Xl1d3UBoyPdrr70WqqqqhsQ8ECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIB+Bqv7+/v58GqhLgEDlCMTEhBkzZow44aampnD33XeHr371q6G+vj50dnaGI0eOhP3794f29vacbWO7tra2nOUKJkbgHzcfTHf8X8+tnJgB9EqAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgxALVJR7PcAQIlFAglUqFU6dOhXhCQ64rJi+0trbmKk6Mz507N3z44YeJZYIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBDIRyCVT2V1CRCoPIGGhoZ0ckOxZr5169bQ1dUVYtKEiwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAuMVsDN5vILaE6gAgZjc0N/fHw4fPhyam5vznnE8oeHZZ58NFy9eDNu2bcu7vQYECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBDIJVCdq0CcAIGpJ7B8+fJw5MiR0NfXFz755JNw/PjxcOLEifDxxx+Hzz77LJw/fz696GuuuSY0NTWFm2++Of1dU1Mz9TCsiAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBshCQ2FAWr8EkCJRWIJVKhfr6+vSnpaWltIMbjQABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAhkCqYx7twQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBkgpIbCgpt8EIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBTAGJDZka7gkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGSCkhsKCm3wQgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFMAYkNmRruCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgZIKSGwoKbfBCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgUwBiQ2ZGu4JECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBkgpIbCgpt8EIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBTAGJDZka7gkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGSCkhsKCm3wQgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFMAYkNmRruCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgZIKSGwoKbfBCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgUwBiQ2ZGu4JECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBkgpIbCgpt8EIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBTAGJDZka7gkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGSCkhsKCm3wQgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFMAYkNmRruCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgZIKSGwoKbfBCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgUwBiQ2ZGu4JECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBkgpIbCgpt8EIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBTAGJDZka7gkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGSCkhsKCm3wQgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFMgerMB/cECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgMD6Br933wvg60JoAAQIECBAgQKCiBN5/8/GKmq/JEiBAgAABAgTKUcCJDeX4VsyJAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhMEwGJDdPkRVsmAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAoRwGJDeX4VsyJAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhME4HqabJOyyRAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMCkCNQvXj4p4xp0egl0nnxvyIL97oZweJhgAb+/CQbWfaKA310ii2CJBIb//ko0rGEIECBAgAABAlNawIkNU/r1WhwBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEChvAYkN5f1+zI4AAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECExpAYkNU/r1WhwBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEChvAYkN5f1+zI4AAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECExpAYkNU/r1WhwBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEChvAYkN5f1+zI4AAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECExpAYkNU/r1WhwBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEChvAYkN5f1+zI4AAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECExpAYkNU/r1WhwBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEChvAYkN5f1+zI4AAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECExpAYkNU/r1WhwBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEChvAYkN5f1+zI4AAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECExpAYkNU/r1WhwBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEChvAYkN5f1+zI4AAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECExpgeopvTqLqxiBjo6OcP78+TBz5swwa9asUF9fX9K59/T0hIsXL4bq6ur0+KmUnJ+SvgCDESBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAwbQXs3p62r758Fn777beHxsbGsHTp0rB48eKwcOHCsGPHjpJNsKqqKtTV1YX58+eH2bNnhxkzZoTOzs6SjW8gAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQITGcBJzZM57c/QWtva2sLp06dCjU1NaGhoSH9GWmo7u7urOILFy5kxSYi0NfXl9jtZ599NuqpEfmuM3EgQQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECExzAYkNE/QDuHz5cvjNb34zpt5ra2vTSQALFiwIX/rSl8JVV10V4ikClXjNmzcvDE9UWL16dXj77bfLcjmFOlfaOssSP8ek4mkZR44cyVGaX/iOO+4IqZSDafJTU5sAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAaQUkNkyQ9xVXXDGunleuXBmeeeaZ0NLSMq5+Stm4o6MjK6khjr9v374QT0aYKhvMp8s6S/nbGRjr3LlzYeHChQOP4/5et25d2Llz57j70QEBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAhMn4E+ZT4BtV1fXuHs9ePBguO2229InN8SN9JV+FXoyQqWte7qsc6LeyyeffFLUrvfv31/U/nRGgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEDxBSQ2FN80nD17tqi9NjY2hr179xa1z4no7PPPP8/ZbX9/f86ySiuYLuucjPcyc+bMyRjWmAQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQITKKAxIYJwJ+Izdlr1qwJ5X5ywzXXXJNTM5WaOj+16bLOnC+zggruu+++CpqtqRIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCYngLV03PZk7PqQ4cOhX/4h38Ily5dGjKBvr6+8Le//S288cYbYcuWLUPKMh9uuumm0NXVlRkqq/va2toQ1/hv//Zv4a9//Wt6bs3NzeHnP/95Wc1zvJOZLuscr1Ox2sff0Msvvxx6e3vz6rKnpyfccccdebVRmQABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACB0gtIbCiheWNjY4gnF9TU1GSNumjRorB58+b0Z/369aG1tTWrTnd3d2hrawuxbrleLS0t4ciRI+U6vaLNa7qss2hg4+go/ntYvnz5OHrQlAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBchZIlfPkpuvcdu7cGVauXJm4/Hiqg4vAdBK4cOHCdFqutRIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCYdgISG8r0lf/85z9PnNmOHTsS44IECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKASBSQ2lOlbmzdvXpg7d27W7ObMmZMVEyBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABApUqUF2pE5+u8z579uyoS+/s7Ay/+MUvwvnz58NVV10VGhsbw1133TVqu+EV2trawm9/+9vBfm644YbQ0tIyvNqQ597e3vDWW2+FOIc49vz588Pq1atDKlWaHJrLly+HX/7yl+FHP/pRePfdd0N3d/fg/FauXBmeeuqpcOedd4aqqqrBeCE3hayzp6cnvP7664OeX/va18KyZcuGDN/f3x9+9atfhR/+8IdD5h+TXKL9Y489VpT5x0H7+vrC+++/H37605+GAwcOhL/+9a/pucTkmfi55ZZbwv3335+YYDMw6egQ61VX+69kwMQ3AQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQL5CdiNnJ9XSWvHzeWZG/PHOviSJUuy2h07dizE+FivuMF+8eLFWdVPnjwZFi1alBUfCCxdujS0t7cPPKa/t27dGrZt2zYkVuyHON9HH300tLa25uz64MGDYdWqVenyPXv2hHvvvTdn3dEKClnnjTfemGXzxRdfDCZ9xKSHBx54IHHo+DvYt29f+hMrjHf+zz33XNiyZUvOsWLB0aNHR/QcaLxu3bqwc+fOgUffBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQyEtAYkNeXKWrHDfqD08QiKM3NTWNOonrrrsuK7Fh5syZo7YrRoWYjDH8mjVr1vBQUZ/jSQh1dXV59blmzZoQT3CIpyMUchWyzqQ28eSIeHLC9ddfn/i+c80tzn/Tpk1h+/btuaokxguxSuwoI9jR0ZHx5JYAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQL5CaTyq652qQT+9Kc/JQ71xBNPJMana/Dy5ct5JzUMWMUTHK644oqBx0n5Pn36dJgxY0ZeSQ0DE33++efD7t27Bx5H/R6P1Uidnzt3bqRiZQQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEBhRQGLDiDyTVxhPE0i6/umf/ikpPG1j9fX1I649nnCxdu3a0NzcPGK9ySpcuHBhzqFXr1496rwfeeSREBMWxnJ94xvfyFlt69at4dixY+HMmTPh6NGjIY491uupp54aa9WC6o1kVFCHGhEgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgUFYC1WU1G5MJ/f394eabbw7d3d1ZGnHzeXW1VzYAs3fv3kSnWB435r/xxhuhtrZ2oHro6+sL8ZSDLVu2DMbK8SYmFixbtmxwavE38dJLL4WNGzcOxjJvXnnllfDwww9nhrLuOzs7w759+7LiMfHjxIkTQ35X8+bNC2+//Xbo6OgIjY2NWW3mzp0burq6suITFYjJG/E6efLkkCFmzZoV4vxvvPHGcMMNNwx510MqeiBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoKwF7JIv4es5ffp0eiN23Kg+/Dp79mzYs2dPGNjEPbw8buDetm3b8PC0fl6zZk3i+tetWxd27tyZVZZKpcLmzZvTxuV4CkBMxogJBcOvqqqqsGHDhnDVVVcl/j4ee+yxURMbnnzyyeHdpp9jskDsP+lqaGhIn+Awf/78IcUx6aatrS0sWrRoSHwiH3L9uxg+5qZNm0JMALr66quHF3kmQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKBMBVJlOq8pOa0VK1aEuLl+xowZWZ+4eTzX5u21a9emN5JPSZQCFxVPE0i64mkCSUkNmXXr6+vDpUuXMkOTfh835CclNWROLJ7KEBNchl8x0eDy5cvDw0OeW1tbhzzHh9deey1nUsNA5Xh6Q/z9Db927do1PFQWz/FEjtmzZ4cnnniiLOZjEgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIjC4gsWF0o0mv8cwzz0z6HMptAi+88ELilP785z8nxocHq6uryya5IZ4wsX379uFTTHz+8Y9/nBj/6KOPEuMx2NfXl1j2zW9+MzE+PPi9731veChMVGLD559/njVWIYGY4BBPoujt7S2kuTYECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECJRQQGJDCbELHWrx4sUh/uX8XKcUFNpvJbd7+eWXs6YfT2toaGjIiucKxOSGM2fO5CouSby5uXnUEyYyJ3LHHXdkPo7pPm7wT7ri6SGFXnPmzCm06YjtvvSlL+Usj+83fvK5rrzyytDf359PE3UJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECixQOE7m0s80ek+XHd3d2hsbAzvvPPOdKdIb1SPHsOv7373u8NDoz7nu1F+1A7zrLB+/fq8WuRKUsirkzwrX3311Xm2KLx6HOvixYvphJNPP/00fapGTEyIn66urvQn3sdTKGJSyp49e0JTU9OIA27evHnEcoUECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECEyuQPXkDj+9Rt+0aVP49re/HXp7e7MWfurUqfCHP/whvPnmm6G9vT2rfCCwatWqcOzYsbBkyZKB0LT7Pn36dOKaH3zwwcR4OQcvXLiQ1/QKSWzIdWLBpUuXQk1Nzajj79u3L6vO2bNns2LFCsQ5jTav6BBPMbn33nvTn/feey+sWLEicQrPP/982Lp1ayhlgkbiRAQJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEEgUcGJDIsvEBB9//PGwfPny0NLSkvW5//77w/bt20NbW1v6L9bHJIhc19KlS3MVTYt43JCfdMWN7tPham5uzmuZqVQq8VSDH/zgB2PqZ+PGjVn1NmzYkBWbzED8dxVPcMh1/ed//meuInECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBCZZQGJDCV/A559/PqbR4l+rj0kOhw8fzll/7969Ocuma8GCBQum69JHXffdd9+dVefpp58OHR0dWfHMwLZt2zIfB++/9a1vDd6Xy01MbNm1a1fidHbs2JEYFyRAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYPIFqid/CmaQSyD+FfoXX3wxJP3F/Iceeih0dXXlajot4/39/aGqqmparn20Rb/00kuhtbU1q1pjY2M6GeDhhx8eUtbb2xv+5V/+Jbz66qtD4vFh7ty5YdGiRVnxcgjEfxePPPJI1lTa29tDX19fiKdXuAgQIECAAAECBAgQIECAAAECBAgQIECAAAECpRboPPleqYc0HoHgd+dHMJkCfn+TqT99x/a7m77v3soJECBAgAABAgSmhoBdvmX+Hjds2JA4w+7u7vRG7cRCQQLDBKqrq8PatWuHRf/vMSYCxISQe+65Jzz44IPppIUrUhjqnwAAIABJREFUr7wyMakhtvjjH/+Y2E85BOM6mpuby2Eq5kCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwBgFnNgwRqjJrLZ69eqwb9++rCnEv6pfW1ubFU8KnD59umz/yn7SfAuJ+Yv8udWiTdLpC5ktkn5jmeXxPp4gUq6nNQzM9ezZswO3Q76d5jGEwwMBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBshFwYkPZvIrcE7n99tsTC8+fP58YTwr++te/TgpPqdhHH300pdZTzMV85zvfGXd3hw4dCrlOEBl35yXooL+/vwSjGIIAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgXwFnNiQr9gk1P/b3/6WOOpnn30W6uvrE8umY/DUqVNlf5rAZLyXeLLH8NMampqawn/8x3+Ehx56KHR3d484rWeffTZs2rQppFKVkQc1Z86cEdejkAABAgQIECBAgAABAgQIECBAgAABAgQIECAw0QLvv/n4RA+hfwIECBAgQIAAAQIECBAgQIAAAQJTSkBiQwW8zk8//TRxll/+8pcT40nBurq6pHBFxq699trEee/evTu0tLQklk3n4FtvvZW1/P3794clS5aErq6u0NPTE06cOBHa2toG6y1atCjccMMNoba2djBWCTfxVIajR48mTrVSEjMSJy9IgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYAoLSGyogJfb2tqaOMt8Nmq//vrrYcOGDYn9JAU3b96cFC6LWFVVVeI8otPOnTsTy3IFH3300VxFUybe2dmZtZaYtDBwxeSFZcuWpT8DsUr9/p//+Z/Eqa9duzYxLkiAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwOQLpCZ/CmYwksBzzz2XWNzU1BRyJTbccsstWW0OHjwYent7s+JJgR07doTnn38+qagsYjGxYdOmTYlzee+99xLjScFomytpJKl+pcbefffdrKl///vfz4pNhcCKFSsSl5FPUk9iB4IECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECEyYgMSGCaMdf8fvvPNO2LJlS2JHr7zySmI8Bu+6667EsieffDIxnhmMm/03btyYGSrL+/Xr1yfOK25s7+/vTyzLDMZ15rLNrDcV7ltaWrKW8fTTT4dFixaFmPTQ0dER4qkO586dCz09PekEmMuXL4/JMavjcQTi7/2DDz4ouId77rknZ9skg5yVFRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgUFIBiQ0l5J45c+aYRuvq6gpxk/aqVaty1h9po/a9996b2C6ewrB3797EspgMEMeslM3+S5YsSVxHDC5evDjnpvy+vr6KWmfOReZRkOt31N7eHm677bbQ2NgYFi5cGGbPnh3q6urClVdeGa644or0iSDxdIz4iUkQTzzxRDh+/HgeI4+9avzNx3k2Nzenx4onb4wlQSWOENvOmzcv7Nu3L3HAAwcOJMYFCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAoDwGJDSV8D7feemuIJw08+OCDiZ/bb789vYl8/vz5OTdpx+meOnVqxFnX1taGpqamxDpr1qxJb+yPG9R7e3vTm8J3796d3sSea2N4YkdlENy1a1fiLOKG/VQqFV5//fX0CQTx9IG4+X3Hjh1hxowZI9omdljhwZgEsm7dunGtIprGxJilS5emf6Mx8aCY19mzZwe7i2PFkzfiO4z/VuJJDvFUiXiaRHyX8Ts+x/f71a9+NcR/L93d3YPtM29iokSuE0wy67knQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGDyBKonb+jpN3LcsN3a2jquhR86dCg0NDSM2sf+/fvTm9CTKsYEhkpLYkhax8MPPxy2bt0aomvS9cADDySFp2Vs586d4fe//304evRoUdYfEw82bdoUtm/fXpT+cnXy6quvhvgp9PrjH/9YaFPtCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAokYATG0oEXYxh4kkNLS0tY+oq/pX+uOm/0OvChQvhtddeK7R5ydqdOHFiXGN9+umnFbHOcS0yhHDu3LmiJTUMzCWe4BBPUyjG9Xd/93fF6Gawj5UrV4a+vr70qQ+DQTcECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECJSlgMSGCXgt1157bVF7jQkG/f39YzqpIXPgbdu2pf+qfmZstPvm5ubwxRdfhNra2tDZ2Tla9azys2fPZsVGCxTSZqDP6urqcPHixTB37tyB0Ji+4zovXboUrr766pwnPozUUSFzLqTNSHMYa9nly5fD7NmzE6ufOXMm/b6jRXSMCS0x9vHHH6c/hw8fDmvXrk1sG4OrVq1K/zZzVhhjQU1NTdESTA4cOBB++9vfhqqqqjGOrhoBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABApMpILFhAvRTqVR48cUXC+q5qakpvZF8165d6Y3lMaHh/vvvL6iv2Gj79u3h2LFjIfY70hXLjx49Go4cOTL4V+6vu+66rCZz5szJimUG7rvvvszH9P1XvvKVrFhmoJA2me3jpviurq6wZ8+eURMcMtcZkyLi9fWvfz2zu/T9rFmzsmKZgULmXEibzDEH7m+66aaB28HvkeZ75513DtbLvImJDPPmzUu/72gRHWNCS4zV19enP8uXLw8/+clPRkweaW9vz+y24Pv4O4+/9/g7HCmZImmAeELDoUOH0u3vuuuupCpiBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiUqUBVf9xJ7JoWAr29veH48ePhL3/5y+B6r7/++rBs2bL0pvbBYMZN/HnEExziNZAIkFGceNvX1xfiJ14zZswY01/OL6RN4uAhhHPnzqWTOT788MPBKjfeeGNYsmTJlFnnWL1iwsf8+fMHHQZuYrJL9Mjn6unpCXV1dVlNCukrq5Mcgfib/eSTT8LJkyfTJ0nEOcQrJmAsWrQo/Ymnbkyn6x83H0wv97+eWzmdlm2tBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECU1jg//5k/RReoKX9f4H4F/ljEkP8jPWqqqoac0LDQJ/xxIr4yecqpE2u/uNG93jSQPyM9aq0dY7VK562MPxqbm7OO6kh9hGTCZKuAwcOFNRfUl/DY/E329DQkP4ML/NMgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMDUEMhv9/nUWLNVEJjWAuvXry/q+levXl3U/nRGgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMD0EpDYML3et9USCO+++25BCh988EFiu1mzZiXGBQkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDAWAYkNY1FSh0CFCly4cCFr5q+++mro6OjIio8U6OnpCc3NzYlVFixYkBgXJECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwFgEJDaMRUkdAhUqcOuttybOvLGxMezevTv09vYmlg8E+/r60vXq6uoGQkO+X3vttVBVVTUk5oEAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQL5CFT19/f359NAXQIEKkcgJibMmDFjxAk3NTWFu+++O3z1q18N9fX1obOzMxw5ciTs378/tLe352wb27W1teUsVzAxAv+4+WC64/96buXEDKBXAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAiUWqC7xeIYjQKCEAqlUKpw6dSrEExpyXTF5obW1NVdxYnzu3Lnhww8/TCwTJECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQD4CqXwqq0uAQOUJNDQ0pJMbijXzrVu3hq6urhCTJlwECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAYr4CdyeMV1J5ABQjE5Ib+/v5w+PDh0NzcnPeM4wkNzz77bLh48WLYtm1b3u01IECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQC6B6lwF4gQITD2B5cuXhyNHjoS+vr7wySefhOPHj4cTJ06Ejz/+OHz22Wfh/Pnz6UVfc801oampKdx8883p75qamqmHYUUECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECJSFgMSGsngNJkGgtAKpVCrU19enPy0tLaUd3GgECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBDIEEhl3LslQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECJRUQGJDSbkNRoAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECGQKSGzI1HBPgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIlFRAYkNJuQ1GgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIZApIbMjUcE+AAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiUVEBiQ0m5DUaAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhkCkhsyNRwT4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECJRUQGJDSbkNRoAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECGQKSGzI1HBPgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIlFRAYkNJuQ1GgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIZApIbMjUcE+AAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiUVEBiQ0m5DUaAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhkCkhsyNRwT4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECJRUQGJDSbkNRoAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECGQKSGzI1HBPgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIlFRAYkNJuQ1GgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIZApIbMjUcE+AAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiUVEBiQ0m5DUaAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhkCkhsyNRwT4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECJRUQGJDSbkNRoAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECGQKSGzI1HBPgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIlFSguqSjGYwAAQIECBAgQIDAJAh87b4XJmFUQxIgQIAAAQIECEyWwPtvPj5ZQxuXAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIECBJzYUACaJgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEBxBCQ2FMdRLwQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEABAhIbCkDThAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECiOQHVxutELAQIECBAgQIAAgcoRqF+8vHIma6YVK9B58r0hc/e7G8LhYYIF/P4mGFj3iQJ+d4ksgiUSGP77K9GwhiFAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoEgCTmwoEqRuCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgfwFJDbkb6YFAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgUCQBiQ1FgtQNAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgkL+AxIb8zbQgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEiiQgsaFIkLohQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE8heQ2JC/mRYECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAkQQkNhQJUjcECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBA/gISG/I304IAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAokoDEhiJB6oYAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBDIX0BiQ/5mWhAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJFEpDYUCRI3RAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQL5C0hsyN9MCwIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKBIAhIbigSpGwIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCB/AYkN+ZtpQYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBRJQGJDkSB1Q4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECOQvILEhfzMtCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgSIJVBepH90QGJdAR0dHOH/+fJg5c2aYNWtWqK+vH1d/+Tbu6ekJFy9eDNXV1enxUyk5P/kaqk+AAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFCBOzeLkRNm6IK3H777aGxsTEsXbo0LF68OCxcuDDs2LGjqGOM1FlVVVWoq/t/7N1/jNT1nTj+F8sCBQsCirZs44LXgzYe2GsxxuIXexVsWpQ2jdXDtmqTgjmhrSnCRT0LNtVe+dFrc2gqtBfI1VK06alI7SG9KhHvPDwNaNOD+NHFCD3FuiAKIsh+85q72c7OvGZ3dnZndmb38Uom834/36/368djBnb+eD3frxFh7NixYdSoUWHw4MHhwIEDnd3iGgECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAj0koAdG3oJUjN/EmhpaQn79u0Lw4YNC+PHj8+8/nS18OjgwYMFwSNHjhTEKhE4efJkstm33nqry10jujvPZEeCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQGOACEhsq9AU4ceJEePTRR0tqffjw4ZkkgNNPPz2cdtpp4b3vfW+IuwjUYxkzZkzIT1SYPXt2eOihh2pyOuU619s8axK/zEHF3TR+9atfhfvuuy9s3769w/dt9OjR4ayzzgqzZs0KcSeQmTNnhvjvSyFAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoHYFJDZU6LMZMmRIj1qeMWNGuOOOO8L06dN71E41b96/f3+HRebZvjdv3hzizggNDQ3ZUF2/D5R51tqHtGnTpjBnzpxOhxWTauJr165dYdWqVZm68d/SY4891ul9LhIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAg0HcC/WOled/5JXtubW1NxrsT3LZtW7jwwgszOzfEhfT1XsrdGaHe5j1Q5lnNzyXu0BBdu0pqKDam+G9pz549xS6LEyBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECDQxwISGyrwARw6dKhXW21qagrxafW1Xt55552iQ2xrayt6rd4uDJR51sLnsnXr1nDGGWf0eChDhw7tcRsaIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgMgKNlWl2YLdaiUXU8Wn1+/btC+PHj69Z3DPPPLPo2Boa+k8OzUCZZ9EPs0oXtm/fHmbNmtVpbzNmzAiXXnppJvnhzTffDDt37gxbtmwJe/fu7fQ+FwkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQqB0BiQ1V/Cwef/zxcMEFF4Tjx4936PXkyZPhlVdeCffdd19YsmRJh2u5J+ecc05obW3NDdXU8fDhw0Oc4/XXXx9eeumlzNimTp0a7r///poaZ08HM1Dm2VOnntwfv+cXXnhh0SYefPDBMHv27FAsYSb+m3r66afDsmXLQkyQOO2004q25QIBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAn0rILGhiv5NTU2ZhdjDhg0r6HXChAlh8eLFmdf8+fPD2rVrC+ocPHgwtLS0hFi3Vsv06dMzT82v1fH11rgGyjx7y6u77Zx99tnJW2KizDPPPFM0oSF7U0x4mDZtWnjooYeyIe8ECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECNSoQEONjmtAD2vNmjVhxowZSYO4q4NCoD8LbN26NcQknvzS3NycSZoptktDfn3nBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAjUh4DEhhr9nO6///7kyO68885kXJBAfxGYNWtWciovvPBCMi5IgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEB9C0hsqNHPb8yYMWH06NEFozv11FMLYgIE+otAS0tLcio7duwIdmpI0ggSIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQqHuBxrqfwQCbwKFDh7qc8YEDB8KvfvWr8Oabb4b3vve9oampKcycObPL+/IrxEXmjz32WHs7H/zgB8P06dPzq3U4P3bsWHjggQdCHEPse+zYsWH27NlVW5R+4sSJ8PDDD4e77747bN++PRw8eLB9fDNmzAi33npruPjii8OgQYPa4+UclDPPo0ePhnvvvbfd86Mf/WiYMmVKh+7b2trCb37zm/CDH/ygw/hjkku0v+GGG3pl/LHTkydPhqeffjr8/Oc/D4888kh46aWXMmOJyTPxdf7554crrrgimWCTHXR0iPUaG3vnv5Kbb74523SH92nTpnU4d0KAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAi/3v3uAAAgAElEQVQQIECAAAECBAgQIECAQP8R6J3VyP3Ho6ZmEheX5y7ML3VwkyZNKrhv9+7dIcZLLXGB/cSJEwuqv/jii2HChAkF8Wxg8uTJYe/evdnTzPvSpUvDsmXLOsR6+ySO97rrrgtr164t2vS2bdvCrFmzMtcffPDBcNlllxWt29WFcub54Q9/uMDm3XffbU/6iEkPV155ZbLr+D3YvHlz5hUr9HT8K1asCEuWLCnaV7ywa9euTj2zN8+bNy+sWbMme9qj9w0bNhTcv3r16oKYAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAEC/UdAYkONfpZxoX5+gkAcanNzc5cjPuusswoSG4YOHdrlfb1RISZj5JdTTjklP9Sr53EnhBEjRnSrzTlz5oS4g0PcHaGcUs48U/fEnSPizglnn3128vMuNrY4/kWLFoWVK1cWq5KMl2OVbCgnuH///pyz8g/jLh+pctVVV6XCYgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQI9BOBhn4yj343jeeeey45pxtvvDEZH6jBEydOdDupIWsVd3AYMmRI9rRP3l977bUwePDgbiU1ZAe6atWqsH79+uxpl+89seqs8cOHD3d2ueRr//Ef/1FQd/To0WHMmDEFcQECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBPqPgMSGGv0s424CqfLpT386FR6wsXHjxnU697jDxdy5c8PUqVM7rddXF88444yiXc+ePbvLcV977bUhJiyUUj73uc8VrbZ06dKwe/fu8Prrr4ddu3aF2Hep5dZbby21aqf1/vu//7vgetx9RCFAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoH8LNPbv6dXf7Nra2sJHPvKRcPDgwYLBx8XnjY0+sizMpk2bkk7xelyYf99994Xhw4dnq4eTJ0+GuMvBkiVL2mO1eBATC6ZMmdI+tPiduOuuu8LChQvbY7kH99xzT7jmmmtyQwXHBw4cCJs3by6Ix8SP559/vsP3Ku6Q8NBDD4X9+/eHpqamgnviLgqtra0F8Z4GfvrTnxY08aUvfalDLO4O8eSTT4Zf//rXYceOHe2ffxxTHOunPvWp8JnPfCZ0lfDSoVEnBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAj0qYAdG6rI/9prr4W4SD0usM9/xYXi69evDw0NDZkn5ucPKy5AX7ZsWX54QJ/PmTMnOf958+ZlFubnJjXEitF28eLF4dVXX03e19fBmIwRvx+5SQ1xTIMGDQoLFiwI69atSw7xhhtuSMZzg7fcckvuafvxiy++2CGpof1CCGH8+PGZHRxyY/E4Jt20tLTkh3t8fujQoYI24o4W8d/KihUrMg6jRo0Ks2bNyiSobNu2LfNvJSaCxOMNGzaEuINFvCeaxX9PCgECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECtS8gsaGKn9F5552XWVw/ePDgkP8aO3ZsZlF2ajhz586tyELyVF/1Eou7CaRKfHL/mjVrUpfaY/Fp/sePH28/r4WDRYsWZZIxOhtL3JUhJrjkl5hocOLEifxwh/O1a9d2OI8nGzduzCQAFFzICcTdG+L3L78US7LIr1fqeUxe2Lt3b0H1mKgQ/62Us8tGvDeOvyubgk4FCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCoqoDEhqpyl9fZHXfcUd6N/fiu73//+8nZ/e53v0vG84ONjY01k9wQd5hYuXJl/hCT5z/+8Y+T8ZdffjkZj8GYNJAqn//851PhgthNN91UEOvtxIa4w0IlSkz6GDJkiOSGSuBqkwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAvCUhs6CXISjYzceLEzJPni+1SUMm+a7Xtn/zkJwVDi7s1jB8/viBeLBCTG15//fVil6sSnzp1apc7TOQO5JOf/GTuaUnHxZIGGhrK/+d/6qmnltR3pSrFnStmzJiR2U0iGnZVLr744q6quE6AAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQB8JNPZRv7rtpkB88nxTU1N45JFHwsyZM7t5d/+q3tbWFqJHfvnGN76RH+ryPCZD9GWZP39+t7ovlqTQrUa6WXnkyJHdvKMy1ePOFsuWLQvvf//7Q8rh2WefDcWSHLZt2xZaW1szCUKVGZ1WCRAgQKDeBA68+FS9Ddl4+4GA710/+BDreAq+f3X84dXx0H3v6vjDM3QCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhUWUBiQxXBFy1aFP76r/86HDt2rKDXffv2hf/8z/8Mv/jFL8LevXsLrmcDs2bNCrt37w6TJk3Khgbc+2uvvZac81VXXZWM13LwyJEj3RpeakF/Vw3ERJBUOX78eBg2bFjqUofY5s2bO5zHk0OHDhXEKhVYunRp+Na3vhW62mFiypQp4d133w2nnXZaMvHl9ttvDytXrqzUMLVLgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgECZAg1l3ue2MgS++c1vhmnTpoXp06cXvK644orMouuWlpbw9ttvh5gEUaxMnjy52KUBEY8L8lNlzJgxqXC/ixXblaDYRGNCQHNzc8Hl7373uwWxVGDhwoUF4QULFhTEKhFYvnx5ZpeGrpIasn3Hei+88EL2tMP7qlWrOpw7IUCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgNgQkNlTxc3jnnXdK6i0+RT8+WX7Hjh1F62/atKnotYF64fTTTx+oU+9y3pdccklBndtuuy3s37+/IJ4bWLZsWe5p+/EXvvCF9uNaO4gJLsWSP06ePFlrwzUeAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgNeoHHAC9QwQNzdYfXq1SH1xPyrr746tLa21vDoqz+0tra2MGjQoOp3XAc93nXXXWHt2rUFI21qagrr1q0L11xzTYdrx44dC1/5ylfChg0bOsTjyejRo8OECRMK4rUUmD9/fvLfTUxsKHX3h1qaj7EQIECAQM8Fnv7FN3veiBYIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoCICdmyoCGvvNbpgwYJkYwcPHgyePp+kEUwINDY2hrlz5yauhHDttddmEkIuvfTScNVVV2WSFt7znvckkxpiA88880yynZ4EY1JKqowYMSIV7jI2e/bsZJ0XXnghGRckQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKDvBCQ29J19yT0XW6Qdn6pfannttddKrVq39SR6FP/ook1q94XcOzZv3pyps3fv3txwh+O4g0gldmuIuyg0Nzd36CuePPzwwwWxUgLvvPNOstr73//+ZFyQAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIG+E5DY0Hf2Jfd80UUXJeu++eabyXgq+Nvf/jYV7lexl19+uV/Npzcn86UvfanHzT3++OOh2A4iPW48hHDqqacWNPPcc88VxEoJDB06NFnt8OHDybggAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJ9JyCxoe/sS+75lVdeSdZ96623kvGBGty3b99AnXqn8447e+Tv1hB3R3jwwQfD6NGjO703Xly+fHl49913w/Tp07us25MKqeSLuHtEOTtxPPvss8mh2LEhySJIgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoE8FGvu0d52XJPDGG28k633gAx9IxlPBESNGpMJ1GXvf+96XHPf69esrvvg+2XGNBx944IGCEW7ZsiVMmjQptLa2hqNHj4bnn38+tLS0tNebMGFC+OAHPxiGDx/eHqv0wYc+9KFkF3FscazdKY899liyeltbWxg0aFDymiABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAn0jYMeGvnHvVq9r165N1m9oKP3ju/fee5NtFAsuXry42KU+jxdbmF7MqbMBX3fddZ1d7hfXDhw4UDCPmLSQLTF5YcqUKeGyyy5rf8XzaiY1xLFceOGF2SF1eF+zZk2H865OYvLCqlWrCqrF3Sm682+moAEBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQqIlD6yviKdK/RrgRWrFiRrNLc3Fx0kfb5559fcM+2bdvCsWPHCuKpwJ133plcGJ6q2xexmNiwaNGiZNdPPfVUMp4KRttykiFSbdVybPv27QXD+/a3v10Q6+vAmDFjkkOISQoxWaHUct999yWr3nzzzcm4IAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECfSsgsaFv/TvtfevWrWHJkiXJOvfcc08yHoMzZ85MXrvllluS8dxgXOy/cOHC3FBNHs+fPz85rvPOO6+kRfBxnsVskw3XcXD69OkFo7/tttvChAkTQkx62L9/f4i7Ohw+fDgcPXo0kwBz4sSJkhwLGu5hYOnSpckWvvjFLybj+cHW1tZw5ZVX5ocz51//+teTcUECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBPpWQGJDFf2HDh1aUm9xcfall14aZs2aVbR+arF6tvJll12WPezwHp98v2nTpg6x7El8In7ss14W+0+aNCk79IL3iRMnFl2Uf/LkybqaZ8HkyggU+x7t3bs3XHjhhaGpqSmcccYZYdSoUWHEiBHhPe95TxgyZEhmR5C4O0Z8xSSIG2+8MezZs6eMEZR+yze+8Y1k5Q0bNoS4k0hnJSZojB07Nlll3rx5YdiwYclrggQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQI9K2AxIYq+n/84x8PcaeBq666Kvm66KKLMovI4+LszZs3Fx3Zvn37il6LF4YPHx6am5uTdebMmZNZ2B8XqB87dizEJIr169dnFrF31meysT4Orlu3LjmCuGC/oaEh3HvvvZkdCOLuA3GecWH84MGDO7VNNljnwZgEEhf296RE05gYM3ny5Mx39KmnnupJc0XvHTNmTJg9e3byetxJJLvLRPzuxmSc+Nm2tLRk/j3FBI1i5a677ip2SZwAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgT4WaOzj/gdU93Fx+Nq1a3s058cffzyMHz++yza2bNmSWYSeqhgTGOotiSE1j2uuuSYsXbo0RNdUufLKK1PhARlbs2ZNePLJJ8OuXbt6Zf7nnXdeWLRoUVi5cmWvtJfbyP3335/ZMSI3lj2On3XcZaI7Zffu3aGx0X913TFTlwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEA1BezYUE3tHvYVd2qYPn16Sa3Ep/THRf/lliNHjoSNGzeWe3vV7nv++ed71Ncbb7xRF/Ps0SRDCIcPH+61pIbsWOIODlu3bs2e9tp7TELoaleSUjt78cUXQ/y3oBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgULsCEhsq8Nm8733v69VWY4JBW1tbSTs15Ha8bNmyzFP1c2NdHU+dOjW8++67Yfjw4eHAgQNdVS+4fujQoYJYV4Fy7sm2GRfBv/3222H06NHZUEnvcZ7Hjx8PI0eOLLrjQ2cNlTPmcu7pbAylXjtx4kQYNWpUsvrrr7+e+byjRXSMCS0x9uqrr2ZeO3bsCHPnzk3eG4OzZs3KfDeLVijzQtyVJI6ju59rtrv4+cb5TJgwIRvyToAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAjQpIbKjAB9PQ0BBWr15dVsvNzc2ZheTr1q3LLCyPCQ1XXHFFWW3Fm1auXBl2794dYrudlXh9165dYefOnSGOP5azzjqr4JZTTz21IJYbuPzyy3NPM8cf+tCHCmK5gXLuyb1/2LBhobW1NTz44INdLoTPnWdMiojls5/9bG5zmeNTTjmlIJYbKGfM5dyT22f2+Jxzzsketr93Nt6LL764vV7uQVz4P2bMmMznHS2iY0xoibFx48ZlXtOmTQs/+9nPOk0e2bt3b26zvXYcxxE/10ceeaTL72+205iEEXdpiN/jOB+FAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIHaFxjUFlfOKwNC4NixY2HPnj3h97//fft8zz777DBlypSii8Dj1yPu4BBLNhGg/eYiBydPngzxFcvgwYPDoEGDitT8U7ice/50d8ejw4cPZ5I5XnjhhfYLH/7wh8OkSZP6zTxL9YqJAWPHjm13yB7EZJfo0Z1y9OjRMGLEiIJbymmroJESAvH7+4c//CE8//zzmd0csrfE7/Cf/dmfZRIysrH+/P6pxdsy0/vXFTP68zTNjQABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYAAJ/O8j6wfQhAfyVOMT7GMSQ3yVWmJSQqkJDdk2444P2V0fsrGu3su5p1ibI0eODHGngfgqtdTbPEv1irst5JepU6d2O6khthF3c0iVuKNCd5MkUu10FYvf3wkTJmReXdV1nQABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACB+hFoqJ+hGikBAr0hMH/+/N5opr2N2bNntx87IECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQHcFJDZ0V0x9AnUusH379rJm8OyzzybvO+WUU5JxQQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECJQiILGhFCV1CNSpwJEjRwpGvmHDhrB///6CeGeBo0ePhqlTpyarnH766cm4IAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBEoRkNhQipI6BOpU4OMf/3hy5E1NTWH9+vXh2LFjyevZ4MmTJzP1RowYkQ11eN+4cWMYNGhQh5gTAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIdEdgUFtbW1t3blCXAIH6EYiJCYMHD+50wM3NzeGSSy4J5557bhg3blw4cOBA2LlzZ9iyZUvYu3dv0XvjfS0tLUWvu1AZgU8t3pZp+F9XzKhMB1olQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgUGWBxir3pzsCBKoo0NDQEPbt2xfiDg3FSkxeWLt2bbHLyfjo0aPDCy+8kLwmSIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAge4INHSnsroECNSfwPjx4zPJDb018qVLl4bW1tYQkyYUAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQI9FTAyuSeCrqfQB0IxOSGtra2sGPHjjB16tRujzju0LB8+fLw9ttvh2XLlnX7fjcQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgmEBjsQviBAj0P4Fp06aFnTt3hpMnT4Y//vGPYc+ePeH5558Pr776anjrrbfCm2++mZn0mWeeGZqbm8NHPvKRzPuwYcP6H4YZESBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQEwISG2riYzAIAtUVaGhoCOPGjcu8pk+fXt3O9UaAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIEcgYacY4cECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgaoKSGyoKrfOCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgVwBiQ25Go4JECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBqgpIbKgqt84IECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBXAGJDbkajgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGqCkhsqCq3zggQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFcAYkNuRqOCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgaoKSGyoKrfOCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgVwBiQ25Go4JECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBqgpIbKgqt84IECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBXAGJDbkajgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGqCkhsqCq3zggQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFcAYkNuRqOCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgaoKSGyoKrfOCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgVwBiQ25Go4JECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBqgpIbKgqt84IECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBXAGJDbkajgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGqCkhsqCq3zggQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFcAYkNuRqOCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgaoKSGyoKrfOCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgVwBiQ25Go4JECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBqgpIbKgqt84IECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBXAGJDbkajgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGqCjRWtTedESBAgAABAgQIECBAgAABAgQIECBQswIfvfz7NTs2AyNAgAABAgQIEOh9gad/8c3eb1SLBAgQIECAAAECBAgQIECAAAECBMoQsGNDGWhuIUCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBHpHQGJD7zhqhQABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEChDQGJDGWhuIUCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBHpHoLF3mtEKAQIECBAgQIAAAQIECBAgQIAAAQL9TWDcxGn9bUrmU8MCB158qsPofP86cDipkIDvXYVgNdupQP73LlvZ/3tZCe+VFCj2/atkn9omQIAAAQIECBAgQIAAAQIECBAgUIqAHRtKUVKHAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQqIiAxIaKsGqUAAECBAgQIECAAPQUmLcAACAASURBVAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKEVAYkMpSuoQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECFRGQ2FARVo0SIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECpQhIbChFSR0CBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgIgISGyrCqlECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgFAGJDaUoqUOAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhUREBiQ0VYNUqAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiUIiCxoRQldQgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGKCEhsqAirRgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFSBCQ2lKKkDgECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFARAYkNFWHVKAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFCKgMSGUpTUIUCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBCoi0FiRVjVKoJsC+/fvD2+++WYYOnRoOOWUU8K4ceO62ULPqh89ejS8/fbbobGxMdN/Q4Ocn56JupsAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKlCVi9XZqTWhUUuOiii0JTU1OYPHlymDhxYjjjjDPCnXfeWcEeOzY9aNCgMGLEiDB27NgwatSoMHjw4HDgwIGOlZwRIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQEUE7NhQEdaB3WhLS0vYt29fGDZsWBg/fnzm1ZnIwYMHCy4fOXKkIFaJwMmTJ5PNvvXWW13uGtHdeSY7EiRAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMAAF5DYUKEvwIkTJ8Kjjz5aUuvDhw/PJAGcfvrp4bTTTgvvfe97Q9xFoB7LmDFjQn6iwuzZs8NDDz1Uk9Mp17ne5lmT+HmD2rNnT3jppZfyor13+olPfCI0Nvovr/dEtUSAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgfwh0Z71fb8z43HPPTT54tzvjiOsOR40alVlzGNezxfNqlLjO64EHHgjx4cHZMnHixHDFFVf02hieeuqp8Nvf/ra9jwsvvDDMnDkz212n721tbeGJJ54IR48eba83evToMHny5DBy5Mj2WLkHzz77bHj66aczt0fzWbNmhejfVemPc+pqztnrhw8fzqyn3bRpU9iyZUvYu3dv9lLmPX4+Z511Vjj//PMz36P43hufVYdOnBAgUBcCVvlW6GMaMmRIj1qeMWNGuOOOO8L06dN71E41b96/f39BUkPsf/PmzSHujNDQ0FDN4VSsr4Eyz4oBJhqOPyLjD8dKlvhv6rHHHqtkF9omQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKAOBa6//vqwdu3aqo48LsDPLz1ddzh37tzMusMJEybkN90r562trUXXeV177bUhNafudnzgwIFw3nnnFdy2e/fuMGnSpIJ4fqCzdYqrV68OCxYsyL+l5POWlpYwderUDvXjovzo0lnpj3PqbL7xWkzSueeee8INN9yQXFeae398mHZ87dq1q8O/w6VLl4ZFixZJcsjFckygnwv0j5XmNfYhdfVHqpThbtu2LcQsw7ijQFxIX++l3J0R6m3eA2Wevf25vPLKK73dZEF7+TuJFFQQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEBgQAo8+eSTVZ93fhJAb6w73LBhQ4i7J8QdBCqx7vD222/v1Cnu5tDTcvz48WQTQ4cOTcZzg7m7NOTGs8cLFy4MPRljagxxp4GuSn+cU2dzXrFiRYhJOjHZpSfr9m677bbMriSXXnppJlGisz5dI0CgfwhIbKjA53jo0KFebbWpqSnELXhqvbzzzjtFh5j/I6xoxTq4MFDmWc2PIvWDr5r964sAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgYEr0Ntr/sqR7M0xxMXklVh3uGrVqk6n9s1vfrPT65W+WMoDdidPntyrw+jNzy01sHqaU0zOiQ+HXrJkSWoqZcc2b96cSZTojeSfsgfhRgIEqiIgsaECzJVYpD1nzpyKZFD25vTPPPPMos11tr1T0Ztq9MJAmWc1+YcPH17x7ir9A7LiE9ABAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIVEbj88ssr0m5njcYF4LmlUusOt27dmttN2cel7HQQF6CfPHmy7D56emOphvfee29Pu6ra/fUyp6eeeiqMHTu2ZJfm5uYwderUEN9LLQsWLCi1qnoECNSpQGOdjrsuh/3444+HCy64IORvKxT/kMesuvvuu6/TTLVzzjkn1HLGWVycHud4/fXXh5deeinzGcU/PPfff39dfl7FBj1Q5lls/pWIx63PduzYEf7whz+EniQ5xHu/+93vhvgDOb/4UZMv4pwAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgSiwYsWKsHDhwlDKIvI//vGPmQXZ+XLr1q0Ln/nMZwrWB+bXe+edd8L73//+/HDR8wcffDBccsklHRIGTpw4EQ4fPhxefPHFsH79+rB27dqi98+aNSszpsbGni0XXbZsWdE+ci/827/9W5g5c2ZuqOaOr7zyyhCTWfrTA5v7ck6bNm0K8eHdnZW4lvSuu+4K06ZNC8OGDSuoGr/TL7/8cli9enUotjPIvn37Cu4TIECgfwn07C9V/7Ko+Gzi1k7xD2HqP+UJEyaExYsXZ17z589P/tCI20O1tLSEWLdWy/Tp08POnTtrdXi9Nq6BMs9eAyuhofiDpTfK+PHjk8189atfTcYFCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAY2AJx94RS1+UVW58UEwjGjRvX65Af+9jHkmsOR44cGeJY4lq2H/3oR+Gv/uqvwrZt25L9/8M//ENmbWLyYgnB+PDmDRs2lFAzhEWLFtXFGsJvf/vbodRkjZImXgOV+mJOcaeGzpIaYkJDfGB2/L52VmLiTfw3uHLlyswrthv/TcV1swoBAgNHoGHgTLV+ZrpmzZowY8aM5IDjrg4KAQJpgaNHjyaTguKPo7grhEKAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGeCLS1tSVvjzsxVKKU0m584PJjjz1WdN3hkiVLQrFxlzLmf//3fy+oFtc4xiSG/LJr165w7Nix/HDNnd922211Mc7uwFV7TnGXhfPOO6/oEOPuC/FB2V0lNaQaiA9Kbm1tzSRFZK931le2jncCBOpbQGJDjX5+999/f3Jkd955ZzIuSIBACN/73veSDD/96U+TcUECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAj0F4Hf/OY3RafSk8SG66+/vqDdG2+8Mdxyyy0F8Rj4+c9/noz3RXD06NFh3rx5ya6/8pWvJOO1HqyVOV199dVFqR555JGwYMGCotdLvRB3JHn33XfDjh07wt///d+Xept6BAjUqYDEhhr94OLT5eMfn/xy6qmn5oecEyAQQojbncWM01SZMmVKKixGgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBfiPQ2NgYZs+enZzP//zP/yTjXQXj7gtxF4b8cskll4S4zjFVbrjhhlS4T2IHDx4MP/zhD5N9b9iwIRw4cCB5rZaDtTCnuJtC9EuVjRs3hpkzZ6YulRWLO5LEHRzi91shQKB/C/hXXmef76FDh7occfxD+6tf/Sq8+eab4b3vfW9oamoq649ES0tLZnuqbDsf/OAHQ8x+66zEHzEPPPBA5o997Hvs2LGZH0rxD0s1Stza6OGHHw5333132L59e4h/wLMlbn116623hosvvjgMGjQoGy7rvZx5Hj16NNx7773tn8tHP/rRkL/gPmbFxqzZH/zgBx3GH5Ncon38wdcb44+TjokATz/9dCY7NmZHvvTSSxmLmDwTX+eff3644oorkgk2WbToEOvVwg+GX/ziF9lhdXiPP5IUAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIDASBT3/602Hz5s0FU33nnXcKYqUEUrsvTJ06NQwbNixz+/Lly8OSJUs6NBXX7cWF78USHzpUrsLJ8OHDw+rVq8PChQsLeosL8Hfu3FkQr/VAX8+p2G4McZ1mXHeoECBAoBwBiQ3lqFXpnri4PHdhfqndTpo0qeC+3bt3hxgvtcQF9hMnTiyo/uKLL4YJEyYUxLOByZMnh71792ZPM+9Lly4Ny5Yt6xDr7ZM43uuuuy6sXbu2aNPbtm0Ls2bNylx/8MEHw2WXXVa0blcXypnnhz/84QKbuEVSNukjJj1ceeWVya7j9yD+2Mz+4Ozp+FesWFHwYzLbcfY7F7NsO/PM1o/bdK1ZsyZ72mfvxewuv/zyPhuTjgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFBNgfhA4N4sqd0XvvOd77R38dWvfjW5Fi3uklDpdYPtg+jiID4E+Prrr08mNsR1cs8++2zBQ4q7aLLPL/flnOIDkYvt1vDQQw/1uY0BECBQvwLVeYx+/fr02cjjQv38BIE4mObm5i7HdNZZZxXUGTp0aEGsEoGYjJFfTjnllPxQr57HnRBickApi/CzHc+ZMydcdNFFISYWlFPKmWfqnrhzRPyBEZNFii3MT40vjv/GG29MXeo0Fq1in/kZsp3e1MXF/fv3d1Gj8pefeuqpZCeLFi1qTxxJVhAkQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAPxL4y7/8y+RsTjvttGS8s2DcdSH7oNzcepdcckn7adyVYfTo0e3n2YPbbrste1gT73HdXHygcKrEHSjqsfTVnB544IEk1+zZs8PIkSOT1wQJECBQioDEhlKU+qDOc889l+y1nMXsyYb6SfDEiRNhxIgRZc0m7uAwZMiQsu7trZtee+21MHjw4GQSS1d9rFq1Kqxfv76rau3Xe2LV3kji4PDhw4lodUPFdmWIu4UoBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQGCgCd9xxR3Kq5TygOO66kF9mzJgRhg0b1iH8gx/8oMN59qSlpSV7WBPvl112WdFxbNq0qei1Wr7QF3O6/fbbkySrV69OxgUJECBQqoDEhlKlqlwv/vFPlU9/+tOp8ICNjRs3rtO5xx0u5s6dG2o1o/KMM84oOv6YvdjVuK+99toQExZKKZ/73OeKVosJALt37w6vv/56iFtrxb5LLbfeemupVStSL+4YkdrdJP4bkv1ZEXKNEiBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQgwJbt25N7rAQ19E1NHR/uWhq14VU4sQVV1yR1Lj55puT8b4M7tixI9n9nDlzQltbW/JarQerOadoFNcYpsqECRNSYTECBAiULND9v1QlN61iOQLxP/1zzz03+eMiLj5vbGwsp9l+eU/MkExtcxUnGxfmHzlyJMSMz5/97Gdh586d4d133w3Lly+veYv4Rz9+Dx566KHMuE+ePBk6y2S85557upzTgQMHwubNmwvqxR+sx48fD8uWLQuTJk0KcVuwKVOmZPret29fQf0YiNuGxfFlXzNnzkzWq1Zw/vz5ya66s5tFsgFBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQI1IlAfEDsrFmzkqMtZzeCYrstXHDBBQV9DB8+PMS1aPllw4YNNZcsMG3atORY49hXrlyZP4W6OK/mnIqt2YwPoFYIECDQUwGJDT0V7Mb9r732WuaPdFyonv9qbW0NcSF2zIpMZbPFP/px8bnyJ4GYIZkq8+bNyyzMjz+Wcku0Xbx4cXj11VdzwzVzHJMxYrJATCzILYMGDQoLFiwI69atyw23H99www3tx8UObrnlluSlF198sWiyzPjx4zM7OOTfGH+YFPvRml+30udHjx5NJmzE5AvZn5XW1z4BAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABApUWGDp0aKddnDhxIqxYsSI0NTUl68W1h/lr0pIV84Kp3RbiGrdiOz/84z/+Y14L/3v6X//1X8l4XwafeOKJZPdLliwJx44dS16r9WC15hTX7KXKpz71qVRYjAABAt0SkNjQLa6eVT7vvPMyf9QHDx4c8l9jx44N1157bbKDmMlWKwvJkwPsg2DMLk2VuKB9zZo1qUvtsXHjxmV2KWgP1MDBokWLMskYnQ3lmmuuSWaKxkSD+OO0s7J27dqCyxs3bgwxaaKzEndwSGVSFkuy6KytSly79dZbk83ed999ybggAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE6kngxhtvDPfee2+HV3yIcnxQ8rnnnhuGDBkS4oL8YuWFF14odqloPD6gN+62kF86ezjzJZdckl89cx7XxtVaiQ/9jUkaqfK1r30tFa75WLXm9C//8i9Ji4suuigZTwUPHDgQuvuq14ST1PzFCBAoLtBY/JIrtSJwxx131MpQamYc3//+95Nj+d3vfpeM5wcbGxszyQ3xR11fl7jDRKlbWP34xz9Obhf28ssvF92hIO4Okiqf//znU+GC2E033VTwIzUmNnT2I7WgkQoE4rxWrVqVbPniiy9OxgUJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQTwIxwSCVZNDVHKZOnRqeeeaZojssdHZ/sV0WPvrRjxa9bdiwYSH2uWvXrg51tm3bltkFIV6vpRIfnjtixIiCIcWHCH/ve98L8aHA9VbqYU4xSefKK68sizZ+t8rZfaSsztxEgECfCNixoU/Yu9fpxIkTM38ki+1S0L3W+kftn/zkJwUTibs1xKzDUktMbnj99ddLrV6RevGHXFc7TOR2/MlPfjL3tKTjYrsyFNsSrJRGTz311FKqVbTOP//zPyfbX758eZc7USRvFCRAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEA/EHjkkUfCzp07y0pqiNNP7bIwd+7cLtu76667knoPPPBAMt6XweHDh4elS5cmh/CJT3wiGa/1YD3MKe7UUG759a9/Xe6t7iNAoE4EJDbUyQd18ODB0NTUFLZu3VonI67cMOM2V9Ejv3zjG9/ID3V5HpMh+rLMnz+/W90XS1LoViPdrDxy5Mhu3lGd6tdee22yo69//evJuCABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgT6u8Dx48fDzJkzy57msWPHQtxlIb/cdNNN+aGC8wsuuKAgFgNLlixJxvs6+K1vfSs5hLgzwJ49e5LXaj3YH+dU6+bGR4BA7wlIbOg9yy5bilmMO3bsCI8//njBa+PGjZksx+bm5k7bmTVrVt3+wex0Yt24+NprryVrX3XVVcl4LQePHDnSreGVk9gQE0FSJf6ALaVs3ry5oNqhQ4cKYtUMbN++Pdnd7NmzQ61tWZYcqCABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQqIDBkyJBw+PDhslvesmVL8t6/+Iu/SMZzgw0NDSGu4cove/fu7dGY8tvrrfM43nXr1iWbO//885PxWg/2xznVurnxESDQewISG3rPssuWvvnNb4Zp06aF6dOnF7yuuOKKsHLlytDS0hLefvvt5FZO2Q4mT56cPRyQ78UW5I8ZM2ZAeEydOrVb84w/VFIJM9/97ndLamfhwoUF9RYsWFAQq2bgi1/8YrK7NWvWJOOCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQqEeBuHtAfLjtyZMnM6+4fm737t3JBILs/EaNGpWpmz3vzvvXvva1gurz5s0LpT6Ut9i6tB/96EcF7dZC4JprrkkO4+DBg2Hr1q3Ja7UerOScij3M+Z133imJJa49jN/fzl4vvvhiSW2pRIBA/xOQ2FDFz7TU/7jjE+djkkPc3aFY2bRpU7FLAzZ++umnD9i5dzXxSy65pKDKbbfdFvbv318Qzw0sW7Ys97T9+Atf+EL7cbUPYvJPzODNLzF5Y/z48flh5wQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEKhbgZEjR2bGHhML4quxsTFMmjQpPPTQQ5nF4cUmNmfOnGKXisbjTg+ptVm333570XvyL0yZMiU/lDlfsmRJMl4LwWJrNWfNmlULwytrDJWa02c/+9nkeB544IFkPBWM39/OXhMmTAjdfQB0qh8xAgTqT6Cx/oY8cEYcd3dYvXp1SD0x/+qrrw6tra0DB6OEmcas1FKzQktorl9Vueuuu8LatWsL5tTU1JTZSis/Q/PYsWPhK1/5StiwYUPBPaNHjw7xh0NflfyxZsdxzz33ZA+9EyBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoN8LxMXh+/btC3EdWH7ZvHlziA+R7c5ar2K7Kqxbty7EB8+WUoYPH160WnwQby0+vDau1YzzSyV1rF+/PhRbs1Z0ojVwoVJzGjNmTHJ2P/3pT8PixYuT1wQJECBQqoDEhlKl+qhe3HYnldgQtzmKW0s1NNh0o48+mrrqNmbpzp07N5mocO2114b4mj17dohbkD3xxBPJH2jZCT/zzDPZw6q/x4zgbdu2JfudPn16Mi5IgAABAgQIECBAgAABAgQIlC9w4MWnyr/ZnQR6KOD710NAt5cl4HtXFpubeknA96+XIDVDgAABAgQIECBAgACBASYQEwWKPUA5Pl1/586dJYsU21WhWLzkhv+v4rJly8KaNWu6e1tV6sd1c6kEkbi27stf/nJdrtWsxJxOP/305Oexa9eucOLEicyOIskKggQIEChBwKr4EpD6ukpccJ4q8an6pZbXXnut1Kp1Wy8meihpgWiT2n0ht3bM0I11Ulmn2XrxB3B3Mniz9/XW+2233ZZsKo5LIUCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwEAUiA9QTpW42PzAgQOpSwWxuJtCpcvatWtDW1tbpbspq/2YIFJsreaqVavKarOvb6rEnAYNGlR0945f/vKXfT1l/RMgUOcCEhvq4AO86KKLkqN88803k/FU8Le//W0q3K9iL7/8cr+aT29O5ktf+lKPm3v88cdDsR/APW68hAZiNmexH4jXXXddCS2oQoAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgf4psHHjxuTEbrnllmQ8Pxh3U6hGee6556rRTVl9FHt4cNyxol4fvFyJOS1evDjpe+WVVybjggQIEChVQGJDqVJ9WO+VV15J9v7WW28l4wM1uG/fvoE69U7nHXf2yP9x0tzcHB588MEwevToTu+NF5cvXx7efffdMH369C7rVrLC3XffnWx+7ty5tq9KyggSIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDBQBC6//PLkVOMuCV0tyo+7KMR61Sg33XRTNbopq4+RI0eGRYsWJe/99re/HYYPH568VsvBSszp6quvLjrlrVu3Fr3mAgECBLoSaOyqgut9L/DGG28kB/GBD3wgGU8FR4wYkQrXZex973tfctzr16/v88X3yYH1cfCBBx4oGMGWLVvCpEmTQmtrazh69Gh4/vnnQ0tLS3u9CRMmhA9+8IM19UNs4cKF7ePLPfjhD3+Ye+qYAAECBAgQIECAAAECBAgQ6IHA07/4Zg/udisBAgQIECBAgAABAgQIECBAgAABAgQI9JVAQ0NDmDdvXjJBYfPmzeGyyy4rOrRiuyjs2LEjTJs2reh9nV2IyRSDBw8uqBLHcuLEiZp9mG18EPCqVasKxn3bbbeFCy+8sCBeD4HenlNMlpgxY0bYtm1bwfRnzZoVjh8/XrOfb8GABQgQqCkBOzbU1MeRHkyxTMj4Q6TUcu+995ZaNVOv2FZB3WqkQpUHDRqUbLmYU7Ly/wWvu+66zi73i2sHDhwomEdMWsiWmEU6ZcqUzA/X+OM1vuJ5LWWXbt++PTvcDu9Tp04N48aN6xBzQoAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgkL4WJQAAIABJREFUQIAAAQIECBAgQIAAgYEocPvttyen3dkT9uMNxXZR+NjHPpZsr5RgNtEiVffhhx9OhWsiFse9bt265Fjiov16LJWY04YNG4pS5K5PLFrJBQIECCQESl8Zn7hZqPICK1asSHbS3NwciiU2nH/++QX3xMy4Y8eOFcRTgTvvvDOZcZiq2xexmNhQbLunp556quQhRdtykiFK7qBGKqaSAuK2WPVULr300uRwf/rTnybjggQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEBhoAvEhsaNHjy6Y9sGDB8P+/fsL4jEQd0+Iuyjkl7lz54ZiDyHOr1vs/Oabb05e+trXvpaM10rwmmuuKRhKyrWgUg0HentO48ePz+zakJry3r17w4QJE0LctUMhQIBAdwQkNnRHq8p1t27dGpYsWZLs9Z577knGY3DmzJnJa7fccksynhuMi/0XLlyYG6rJ4/nz5yfHdd5554W2trbktdxgnGcx29x6/eF4+vTpBdOI22LFHw4x6SH+YI27Ohw+fDgcPXo0kwATf6yW4ljQcAUCLS0tIf6wTpW4s4RCgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAv8rcPfddycpbrzxxmT80UcfTcaXLVuWjHcnGNeopUpc+B7XqtVyefzxxzsMr9gatg6Vavykt+e0ZcuWojOOn/HgwYNDXP9XTjl06FA5t7mHAIE6F5DYUMUPcOjQoSX11traGuIT6jvbtii1WD3b+GWXXZY97PC+atWqsGnTpg6x7ElcxB77rJfF/pMmTcoOveB94sSJRRflxwzAeppnweTKCBT7HsUfDhdeeGFoamoKZ5xxRhg1alQYMWJEeM973hOGDBmS2REkZtzGV/yBGX/Y7tmzp4wR9OyWVKZobLHYdl89683dBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQqF+Bz3/+88nBb9iwIbM7Q/7FRYsW5Ycy53/+53+ejHc3uHTp0uQt//RP/5SM10owrtFsbm6uleH0yjh6e07Dhg0LO3bs6HRscT3nRRddVPLaw2effTace+65Ia5vVAgQGHgCEhuq+Jl//OMfD3Gngauuuir5iv95x0XkY8eOTW7tlB3qvn37sofJ9+HDhxf9gzpnzpzMwv64QP3YsWMhJlGsX78+s4g9tZ1UsoMaCRZb2B7/oDU0NIR77703k9UZdx+I87zzzjszGYD1Ns+ecsckkHnz5vWomWgaE2MmT56c+Y4+9dRTPWqv1Jvj57Zt27Zk9S9/+cvJuCABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQGqkBjY2OYO3ducvq//OUvO8Tjrgm7du3qEIsncb1ZXMvYG2XBggXJZv7u7/4uGa+lYLHdLGppjN0dS2/Padq0aSF/J4j8McU1gNm1h/HB1HEt5/bt20Nch7h169awYsWKTPJD/M5NnTo1+Z3Mb9M5AQL9U6Cxf06rNmcVF4evXbu2R4OLfwDGjx/fZRtxi5/4hyBV4sL+/rC4Pz7JP2ZzFsvMu/LKK1PTH5CxNWvWhCeffLLX/uCfd955IWbqrly5sqKef/u3f5tsP/Ydk1cUAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEOgocMcdd4S4Q0N+iWvqrrjiivZwsV0Tbr755vY6PT0YN25cGD16dDh48GCHpuL5gQMHQrxeq2XChAlhxowZRR/OW6vj7mxclZhT3Ali9+7dRdes5o6nJ+tX33rrrdymHBMg0A8FrAyuow817tQQ/wCUUuJT+ott4VTK/UeOHAkbN24spWqf1nn++ed71P8bb7xRF/Ps0SRDCIcPH+61pIbsWOIODjFbslIl7rRRLBGoJ9/tSo1XuwQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEKgFgbh4vVjZv39/+6ViuyZ0dn/7zd04+M53vpOs/b3vfS8Zr6Xgr3/961oaTq+MpRJzimtW33777dDc3NwrY0w1ctNNN6XCYgQI9CMBiQ0V+DDf97739WqrMcGgra2tpJ0acjtetmxZ5qn6ubGujuM2Pu+++24YPnx4Jhuyq/r51w8dOpQf6vK8nHuyjcZts+Ifw5jR2Z0S53n8+PEwcuTIojs+dNZeOWMu557OxlDqtZggMGrUqGT1119/PfN5R4voGBNaYuzVV1/NvHbs2FF0W7LY4KxZszLfzWTjPQzec889yRbiZxc/N4UAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQLVFohr+SpR3nnnnV5tdvXq1cn2HnnkkUz86NGjBbsoxAvz5s1L3teT4NVXX528/Re/+EVBvCcOPbm3YCD/F4hrKR988MFil0uK92RcPbm32OB6Y06ptocNGxZaWlpCXHfY3TWdqfZiLK4XjO3Ff3exfYUAgf4tILGhAp9vQ0NDKPajoKvuYrba3Llzw7p16zILy+N/xrlbP3V1f/71lStXZrb46SoLLl7ftWtX2LlzZ4jjj+Wss87Kby6ceuqpBbHcwOWXX557mjn+0Ic+VBDLDZRzT+798Y9Va2tr5sdDV38Mc+cZkyJi+exnP5vbXOb4lFNOKYjlBsoZczn35PaZPT7nnHOyh+3vnY334osvbq+XexATGcaMGZP5vKNFdIw/WGIsbu8VX9OmTQs/+9nPOk0e2bt3b26zvXYcx5Iqjz76aCosRoAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgYoLxPV1qXVqna3hKmVQH/jAB5LVulqzl7wphPA3f/M3yUtNTU2ZeHadYH6lSuyiEB9kO3v27PyukusRe+KQujd+VsXmWjCgIoHLLrssZBNC8qs88cQT+aGC89S4YqVSPtvUvbUwp4JJ5gTiusO4pjM+ZHn58uXd3sUhflcef/zxzMOr45rW2J5CgMDAEBjUVqn0wYHhV1ezPHbsWNizZ0/4/e9/3z7us88+O0yZMqVoJlv8esQdHGLJJgK031zk4OTJkyG+Yhk8eHAYNGhQkZp/Cpdzz5/u7nh0+PDhTDLHCy+80H7hwx/+cIhbHRXL2Ku3eZbqFX8cjB07tt0he7B79+6MR/a8lPeYoTtixIiCquW0VdBIkUDu5xKrlPodLNJcvwh/avG2zDz+dcWMfjEfkyBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQjwK5a7h6c11Tb7d74sSJdt7Uer7c6705j/ZOcw5y5xbDnfWXW7ezejnNtx9m5xQTGnqa1NDe6P8d5C65LWVtZO79/XFOufPr7DjO/dChQ+Hll18Or7zySojrEWOJ6xvjQ5jjA5njq7ufdWd9ukaAQP0J/O8j6+tv3EZchkBc1B+TGOKr1BL/8Hb3D0U5PwbKuafYHGJ2Z8zQ606WXr3Ns1SvuNtCfolbM8Ukj+6WYjsoxEzUctorpf9yPpdS2lWHAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECPREodQ1Xd/vo7Xa7Wv/X1fXujr+z+t2ZW3fq5vdZyTl1N5khd2z9cU658+vsOM49m7zQnTWsnbXpGgEC/U+gof9NyYwIEOhMYP78+Z1d7va11BZh3W7EDQQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIDFgBiQ0D9qM38YEqsH379rKm/uyzzybvO+WUU5JxQQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECJQiILGhFCV1CNSpwJEjRwpGvmHDhrB///6CeGeBo0ePhqlTpyarnH766cm4IAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBEoRkNhQipI6BOpU4OMf/3hy5E1NTWH9+vXh2LFjyevZ4MmTJzP1RowYkQ11eN+4cWMYNGhQh5gTAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIdEdgUFtbW1t3blCXAIH6EYiJCYMHD+50wM3NzeGSSy4J5557bhg3blw4cOBA2LlzZ9iyZUvYu3dv0XvjfS0tLUWvu1AZgU8t3pZp+F9XzKhMB1olQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgUGWBxir3pzsCBKoo0NDQEPbt2xfiDg3FSkxeWLt2bbHLyfjo0aPDCy+8kLwmSIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAge4INHSnsroECNSfwPjx4zPJDb018qVLl4bW1tYQkyYUAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQI9FTAyuSeCrqfQB0IxOSGtra2sGPHjjB16tRujzju0LB8+fLw9ttvh2XLlnX7fjcQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgmEBjsQviBAj0P4Fp06aFnTt3hpMnT4Y//vGPYc+ePeH5558Pr776anjrrbfCm2++mZn0mWeeGZqbm8NHPvKRzPuwYcP6H4YZESBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQEwISG2riYzAIAtUVaGhoCOPGjcu8pk+fXt3O9UaAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIEcgYacY4cECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgaoKSGyoKrfOCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgVwBiQ25Go4JECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBqgpIbKgqt84IECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBXAGJDbkajgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGqCkhsqCq3zggQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFcAYkNuRqOCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgaoKSGyoKrfOCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgVwBiQ25Go4JECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBqgpIbKgqt84IECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBXAGJDbkajgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGqCkhsqCq3zggQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFcAYkNuRqOCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgaoKSGyoKrfOCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgVwBiQ25Go4JECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBqgpIbKgqt84IECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBXIHG3JOeHP/2Paf15PbwV2//MXm/dv+XhQOH3H8gvg++D74PuQK+D7ka/n/wffB9yBXwfcjV8P+D74PvQ66A70Ouhv8ffB98H3IFfB9yNfz/4Pvg+5Ar4PuQq+H/B98H34dcAd+HXA3/P/g++D7kCvg+5Gr4/8H3wfchV8D3IVfD/w++D74PuQK+D7ka/n/wffB9yBXwfcjVqPf/H/6/P/y/0DhmdO6UHBMg8H8CdmzwVSBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgT6TGBQW1tbW5/1rmMCBAgQ6JbApxZvy9T/1xUzunWfygQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgRqVcCODbX6yRgXAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAYAAISGwbAh2yKBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwP/P3v3HWFndieM/M4wgIDBQB3XGONAYqOsythZidQymVdztjtKmVRTrV/kHTBY2miIkjWvAprUJottPAs0W2gayVYptspUfdVdpqwQ2sZAasE0DMTIYmbaADCgwIDDzzbm7d3pn7nNn7ty5M3Nn5nWSu/d53uc85znn9Vzaafa8n0OAAAECBAgQIECAAAECBAgQKFUBiQ2l+mSMiwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIDAMBiQ3D4CGbIgECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKFUBiQ2l+mSMiwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIDAMBiQ3D4CGbIgECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKFUBiQ2l+mSMiwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIDAMBiQ3D4CGbIgECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKFUBiQ2l+mSMiwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIDAMBiQ3D4CGbIgECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKFUBiQ2l+mSMiwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIDAMBiQ3D4CGbIgECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKFUBiQ2l+mSMiwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIDAMBiQ3D4CGbIgECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKFUBiQ2l+mSMiwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIDAMBiQ3D4CGbIgECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKFUBiQ2l+mSMiwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIDAMBiQ3D4CGbIgECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKFUBiQ2l+mSMiwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIDAMBiQ3D4CGbIgECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKFUBiQ2l+mSMiwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIDAOBimEwR1MkQIAAgQEWuPm+FwZ4BG5PgAABAn0psOoL/68vux/wvu968vCAj8EACBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECAxlAYkNQ/npDqK5NTU1hdOnT4eRI0eGsWPHhqqqqn4dfUtLSzh37lyoqKhI3b+83GYm/foA3IwAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgWErYPX2sH30pTPxO+64I9TU1ITp06eHqVOnhsmTJ4e1a9f22wDLysrCmDFjwqRJk8L48ePDiBEjwrFjx/rt/m5EgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACB4Sxgx4bh/PT7aO6NjY3hyJEjYdSoUaG6ujr16epWJ0+ezKo+e/ZsVqwvAq2trYndnjlzpttdI3o6z8QbCRIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGCYC0hs6KMfwMWLF8Mbb7yRV++jR49OJQFceeWV4VOf+lS44oorQtxFYDCWiRMnhs6JCg0NDWHbtm0lOZ1CnQfbPEsSP89BxeST3//+9+FnP/tZeP3118P+/fuzrqytrQ333XdfePDBB8PNN98cysttRpOFVGKBqqkzS2xEhkOAAAECxRT40swJxeyu3/v6zd5T/X5PNyRAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAwnAUkNvTR07/ssst61fPs2bPDs88+G+rr63vVT39e3NTUlJXUEO+/ffv2EBenD5XF5sNlnv3520m6V/zNLF++PDz//PNJ1R1ihw8fTrVLt12xYkVYuXJlhzZOCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAoTQGvNe+D59Lc3NzrXnfu3Bluv/321M4NcSH9YC+F7oww2OY9XObZ18/lnXfeCSNGjMgrqSFpLM8880zq304x/i0m9S9GgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEDxBCQ2FM+yvadTp061HxfjoKamJmzdurUYXfVpH5988knO/tva2nLWDbaK4TLPgXoue/fuDXV1dUW5/aRJk0JLS0tR+tIJAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJ9IyCxoQ9cR44cWfRe586dG0p954arrroq57zLy4fOT224zDPnw+zDiosXL4ZZs2blvENtbW3YsGFD2LNnT+oTjxsaGnK2jxVf+MIXuqxXSYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDAwApUDOzth9fdd+3aFW699dZw4cKFDhNvbW0Nf/3rX8PPf/7zsHz58g51mSc33nhjaG5uzgyV1PHo0aNDnOM///M/h/fffz81tvjm/V/+8pclNc7eDma4zLO3ToVcH387ucqhQ4fClClTOlTPnDkzPProoyEmRDzyyCNh06ZNHerjyf79+0NjY2PWtVkNBQgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQGJYCcf3RG2+80W9zv+mmm0JVVVXW/Yo9jr/7u78L1dXVWffJFYgvX37xxRfDtm3bws6dOzs0q6ysDPX19al1Wl/84hcTx5++oNjzSPeb6zuXZ6724gQIECBQmgISG/rxudTU1IS4c8GoUaOy7hoXbC9btiz1WbRoUVi/fn1Wm5MnT5b8Au34h8u+ffuyxj7UAsNlnv353OIfs0m/+ziGS5cupf7t5BpPRUVFeOmll1LVSckNMWko/vtSCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAg0FkgvpA119qlzm2Ldd7W1pbV1WWXXZYV620gvni5rKysy252794dbr/99i7bxPWL27dvT33SDTdv3hzmzZuXPm3/LhXP9gE5IECAAIFBIVA+KEY5zAa5bt26MHv27MRZxwXaCoGhKHD06NHEacVdQGJCUD7lpz/9aWKzmEGsECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIEngrbfeSgr3aaxzYkNzc3Of3K/zfTJvEuvuuOOObpMaMq/JPH7ggQdSSRMxeSKzlIJn5ngcEyBAgMDgEMhvtfDgmMuQGuUvf/nLxPmsXbs2MS5IYLALfPjhh4lTuPXWWxPjScGYAFFXV5dVdfjw4ayYAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAHpkIvSAAAgAElEQVQCBKLAqVOnBhxiIMYQ11vt3Lmz13P/zW9+06GPgZhLhwE4IUCAAIFBKSCxoUQf28SJE0NlZWXW6CZMmJAVEyAwFAT+67/+qyjTuOWWW4rSj04IECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEBgeAvfdd1+/T7SsrKzDPUeOHNnhvFgnMXkhqSxatCgp3CHW0NAQFi5cGGbPnt0h3vnk7bff7hAqBc8OA3JCgAABAoNCoGJQjNIg2wXyyWQ8duxY+NWvfhVOnz4drrjiilBTUxPuuuuu9j7yPWhsbAxvvvlmez/XX399qK+v7/Ly8+fPh1deeSXEMcR7T5o0KcQ/bnL9cdRlZwVUXrx4Mbz66qvhhz/8Ydi9e3c4efJkey/xj6unn3463Hnnnantr9orCjgoZJ4tLS3h5Zdfbve8+eabw4wZMzrcPW7t9etf/zp8//vf7zD+mOQS7Z944omijD/eNG7/9fvf/z787Gc/C6+//np4//33U2OJyTPxExME5s2bl5hgkx50dIjtKip6/x8lY8aMSXfbq+8DBw5kXS8hKItEgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACB/xN47rnnwpIlS0I+yQUffvhhqKury7LbsGFD+Kd/+qdw4cKFrLrMwCeffBKuueaazFCXx1u2bEmt/zt37lyX7ZIqx40blxROre9bv359Yl2c2xtvvBHiy5k7l48//jj8+7//e1i+fHnnqg7npezZYaBOCBAgQKCkBHq/GrmkpjO0BhMXY2cuzM93dtOmTcu6Li72jvF8S1xgP3Xq1Kzmhw4dClOmTMmKpwPTp08Phw8fTp+mvlesWBFWrlzZIVbskzjexx57LOT6YyveL26ZNWfOnNSt4x979957b8HDKGSeN9xwQ5bNpUuX2pM+YtLDAw88kDim+DvYvn176hMb9Hb88Q/HXH9cpn9z+/fv79IzPdCYkbtu3br0acHfMQEm/o+DziVuU5ZvYk78HSRtjfbwww937tY5AQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEUgJx94Su1sVlMlVXV2eeth/HtWlVVVXt58U6+PznPx9Gjx6d+hSrz8cffzyxq+7WgsVEiWXLloUnn3wyrF69un0N2he/+MUO/ZWyZ4eBOiFAgACBkhJI3mOopIY4PAcTF2h3ThCIErW1td2CXHfddVlt8skkzbqogEDSm/HHjh1bQE/5XxJ3Qog7QnSV1NC5t7lz54Y77rgjxMSCQkoh80y6Jv4BF3dOiH8U50pqSBpfHH/847CnJVrFe+ZKauhpf7F9U1NTIZdlXZPrdxL/4I//HvIp8Y/lpPKNb3wjKSxGgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBHgnkWssUd2Loi9IX/W7atClxqPm+4DauQYsJDnEXifgC3ZkzZyb2l0+wvz3zGZM2BAgQIDAwAhIbBsa927v+4Q9/SGxTyGL2xI6GSPDixYthzJgxBc0mvtn/sssuK+jaYl10/PjxMGLEiMQklu7u8fzzz4eNGzd216y9vjdW7Z0kHMTtxYpRYrZyrsSdpN1DOt9z7969iQkbcWu0XFnSnftwToAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgaEskCuRYNWqVT2e9qhRo8KMGTN6fJ0LCBAgQIBAkoDEhiSVEojNnj07cRRf/vKXE+PDNdjd1l1xofz8+fNDXNxeimXy5Mk5h9XQ0NDtuBcsWBBiwkI+5atf/WrOZitWrAgHDhwIJ06cSGXQxnvnW55++ul8m3bb7o033khsE3cviVm+uZIoduzYEWbNmpV47a5duxLjggQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEBhuAvFlvEnli1/8YlJYjAABAgQI9JuAxIZ+o87vRjEb8qabbgonT57MuiAuPq+oqMiKD9fA1q1bE52iR1yYf/bs2dDY2BheeumlsG/fvnDp0qVQSFZpf/vGrbni72Dbtm2pcbe2toY1a9bkHMaLL76Ysy5dcezYsbB9+/b0aft3TPy4cOFCWLlyZZg2bVqYOHFiKoM23vvIkSPt7TIPKisrU+OLY4yfu+66K7O6V8dTpkwJS5cuzdnH+PHjw9q1azvUx11M5syZ0yGWPtmzZ08YN25c+tQ3AQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEhrXAmTNnEuf/3nvvJcYFCRAgQIBAfwlIbOgv6RBCzHSMC8HjQvXOn+bm5rBx48ZQXl6eemN+52HFBehx8bnyN4G5c+f+7STjaOHChamkgNGjR2dEQ8p22bJl4ejRox3ipXISkzHi76Pz1lxxp4LFixeHDRs2JA71iSeeSIxnBp966qnM0/bjQ4cO5UyWqa6uTu3g0N74/w5i0k1MGOmrsnr16tQuG7n6X7JkSWr3hpjgEG2ef/75xKYxqWHmzJmJdYIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAYjgLXXntt4rS/+93vJsYFCRAgQIBAfwlIbOgv6RDCrFmzUovrR4wYETp/Jk2aFBYsWJA4mvnz5/fpQvLEm5Z4sKmpKXGEcTeBdevWJdalg1VVValdCtLnpfAddymIuyR0VR599NEQE1w6l5hocPHixc7hDufr16/vcB5PNm/enEoMyKrICMQdHOLvr3PJlWTRuV2h53GXje5214gJDrnKiRMnJDXkwhEnQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGDYCsS1i0ll//79Ye/evUlVYgQIECBAoF8EJDb0C3PvbvLss8/2roMhePULL7yQOKs//vGPifHOwYqKipJJbog7TMRdCvIpP/rRjxKbffDBB4nxGIy7gySVr33ta0nhrNi3vvWtrFhfJzbEG8bdNeKOEjFZJd+yYsWK1K4XMSFDIUCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGOAmVlZaGurq5j8P/O4subGxsbE+sECRAgQIBAXwtIbOhr4SL0P3Xq1BAXaufapaAItxh0Xfz4xz/OGnNcAF9dXZ0VzxWIyQ3xzf4DWeIfiN3tMJE5vi996UuZp3kdxz9Ek0p5eeH//CdMmJDUZdFjU6ZMCQcPHsy735hw8c477+TdXkMCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgMN4Ef/OAHOacc1ytu3LgxZ70KAgQIECDQVwKFr2zuqxHpN1Hg5MmToaamJuzYsSOxfjgF29raQvToXB5//PHOoW7Pe7IbQLedFdBg0aJFPboqV5JCjzrpYeNx48b18IriNI/POfpMnjw57w4PHz6cyia+6aabwvnz5/O+TkMCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiUosDIkSOLPqz6+vrQ1dq5BQsWpF7G7CWzRafXIQECBAh0IVDRRZ2qIgssXbo0PPjgg4kLro8cORJ+97vfhV/84hchLs7OVebMmRMOHDgQpk2blqvJkI8fP348cY4PPfRQYryUg2fPnu3R8ApJbIgJAknlwoULYdSoUUlVHWLbt2/vcB5PTp06lRUrZiDu0jB9+vScXcY/qpOSW9IX7N+/P1x++eVhz549YebMmemwbwIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECAwqgRdffDHcf//94ZNPPslr3PGFsNdff30YPXp0l+3fe++9MGnSpJxt4vqsurq6VALEtm3bQkyGUAgQIECAQF8KSGzoS91OfX/zm98M1dXVnaJ/O503b15YvXp1KvHhqaeeCs8///zfKjOO4oLvXIvVM5oN2cO4ID+pTJw4MSk85GLxj8W4cD/fUl5eHmpra7MSZr73ve+FlStXdtvNkiVLstosXrw4K1aswMsvvxweeOCBnN1lJiusXbs2JI0vffGsWbPCli1bwr333psO+SZAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMCgEVi+fHmIn56W7tYYxvV28SXLXb2ANt4zJjjcfvvtqdtbi9XTp6A9AQIECPREoLwnjbXtnUC+GZPxLfoxwSEu4M5Vtm7dmqtq2MavvPLKYTv37iZ+9913ZzV55plnQlNTU1Y8M5Ar8SFmAPdF2bhxY86khhUrVqQSejJ3YIgJFjHRZeHChTmHM3fu3LB3796c9SoIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAw1ARaW1u7ndK0adPC0aNHu22XbhDXYpWVlYXdu3enQ74JECBAgEDRBCQ2FI2y+B3FBdxr1qxJ7PiRRx5JjA/nYHcZpsPZ5gc/+EHi9GtqakJMJuhc4nZkDz30UIjJD51LZWVlmDJlSudwr88bGxvDggULEvuJST65kiwqKirCunXrutzFIu7c4PeRSCtIgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMAwFqiqqkqtrVq1alXeCnEHh7jjQ3Nzc97XaEiAAAECBLoTkNjQndAA18c30ieVuL1TPhmVSdeKDT+BuPh//vz5iROPyQQxi/aee+5JJTPEpIXLL788bNq0KbH922+/nRjvbfBzn/tcYhf79+8Pmbs0JDYKIcyYMSOcOHEiV3VikkbOxioIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAwSAXiy2vLy3u2PHTZsmXhwoULYenSpXnNOq5hnDRpUti7d29e7TUiQIAAAQLdCfTsv7m66019nwg0NDQk9hvfqp9vOX78eL5NB207iR65H120yZWokL5q+/btqTaHDx9Oh7K+4w4ifbFbQ/zjNv6h27nEP5JjwkK+JWYBx0SIpJK0+0RSOzECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiUisCWLVvCuXPnwtmzZ/P6fPTRR12+ILarecUX6K5evTp1v3wTHGbNmhV2797dVbfqCBAgQIBAXgISG/JiGthGd9xxR+IATp8+nRhPCv72t79NCg+p2AcffDCk5lPMyTz88MO97m7Xrl0h1w4ive081+/zu9/9bo+7jokQs2fPTrxO8ksiiyABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAiUq8PnPfz6MGjUqjB49Oq/PuHHjQllZWa9mE+8XExwuXboU4stwuyu333576MmLmrvrTz0BAgQIDE8BiQ2D4Ln/9a9/TRzlmTNnEuPDNXjkyJHhOvUu5x3/YOy8W0NtbW2Imbxxy7HuyqpVq1J/oNbX13fXtOD6n/70p1nXxjHGP5ALKfPmzSvkMtcQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgpAQ++eSTARtPeXl56mW4McFh4cKFXY7j61//epf1KgkQIECAQHcCFd01UD/wAnFrqKRy7bXXJoUTY2PGjEmMD8bg1VdfnTjsjRs3hr5cfJ9400EQfOWVV7JG+dprr4Vp06aF5ubm0NLSEt59993Q2NjY3m7KlCnh+uuvT2X4tgf7+WDChAkF3/G6664r+FoXEiBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMDfBGKCw7p168K//Mu/hLq6ur9VZBxt3749tWtDoS+zzejKIQECBAgMUwE7NgyCB79+/frEUcY/FvItL7/8cr5NU+2WLVvWo/b92TjXNlm5nLoa22OPPdZV9ZCoO3bsWNY8YtJCusQtymbMmBHuvffe9k88j/GBLKdOnSr49u+//37B17qQAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBLIF4rqy/fv3Z1f8X2Tv3r0561QQIECAAIHuBPJfGd9dT+r7ROC5555L7Le2tjbkSmy45ZZbsq7ZuXNnKhsyqyIhsHbt2vD8888n1JRGKCY2LF26NHEwPfnDKNoWkgyReOMSDu7evTtrdN/+9rezYqUWOHz4cGo3iULG9eqrryZelispJrGxIAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAh0EIjJDbnW7/3P//xPh7ZOCBAgQIBATwQkNvREq5/b7tixIyxfvjzxri+++GJiPAbvuuuuxLqnnnoqMZ4ZjIv9lyxZkhkqyeNFixYljmvWrFmhra0tsS4zGOeZyzaz3VA4rq+vz5rGM888E6ZMmRJi0kNTU1OIuzp8/PHHqUSC8+fPh4sXL+blmNVxgYGHH3448cp//Md/TIx3FYzJLXFbs85l9uzZQWJDZxXnBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQ6JnAN7/5zcQLxowZkxgXJECAAAEC+QhIbMhHqUhtRo4cmVdPzc3N4Z577glz5szJ2T5psXq68b333ps+7PAdd2HYunVrh1j6JCYDxHsOlsX+06ZNSw8963vq1Kk5F+W3trYOqnlmTa6AQK7fUdwR4fbbbw81NTVh8uTJYfz48SH+YXn55ZeHyy67LLUjSEwEiJ+YBPHkk0+GgwcPFjCC7i9ZsGBBYqO400hMYsknWSV2EJMaYnJLUinlXUiSxitGgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBUhS45pprEod1xRVXJMYFCRAgQIBAPgISG/JRKlKb2267LbVI+6GHHgpJnzvuuCO1iHzSpEmJb5xPD+PIkSPpw8Tv0aNHh9ra2sS6uXPnphb2xwXq8c38MYli48aNqUXsSW+5T+ykRIIbNmxIHElcsF9eXh5efvnl1A4EcfeBOM+1a9eGESNGdGmb2OEgD8YkkIULF/ZqFtE0JgZMnz499RuNCQTFLFVVVaGuri6xy/Xr16eeZ3x+cVeJziUmq8Tx3HTTTTmTGuK/h5kzZ3a+1DkBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQI9FDg+PHjiVccPXo0MS5IgAABAgTyEajIp5E2xRGIi8PjIu3elF27doXq6upuu3jttddSi9CTGsYEhsGWxJA0j0cffTSsWLEiRNek8sADDySFh2Vs3bp14a233gr79+8vyvzjrghLly4Nq1evLkp/sZPf/e53qd0icnW4ZMmSED+xVFZWpr5PnjyZq3mH+DvvvNPh3AkBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIFCbwl7/8JfHCMWPGJMYFCRAgQIBAPgJ2bMhHqUTaxJ0a6uvr8xpNfEt/XPRfaDl79mzYvHlzoZf323Xvvvtur+710UcfDYp59mqSIaR2OihWUkN6LHEHhx07dqRPe/09atSocOjQobz6iQkN+SY1xH8348aNy6tfjQgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDCUBeJLYnu77mv27NmJRPPmzUuMCxIgQIAAgXwEJDbko9TDNldffXUPr+i6eUwwaGtry2unhsyeVq5cmXqrfmasu+O6urpw6dKlMHr06HDs2LHummfVnzp1KivWXaCQa9J9VlRUhHPnzrW/wT8d7+47zvPChQupBe+5dnzoqo9CxlzINV2NId+6ixcvhvHjxyc2P3HiROp5R4voGBNaYixuCRY/e/bsCfPnz0+8NgbnzJmT+m3mbNDDiilTpqTGkesP355019DQkHrG+exw0pN+tSVAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMBgFIjrEOPaubjuq6ysLMQkh56WuC4x10tpq6qqetqd9gQIECBAoF1AYkM7RfEOysvLw5o1awrqsLa2NrWQfMOGDamF5fEPid5kMa5evTocOHAgxH67KrE+vtF/3759IY4/luuuuy7rkgkTJmTFMgP33Xdf5mnq+DOf+UxWLDNQyDWZ18c3/Tc3N4ctW7Z0m+CQOc+YFBHLV77ylczuUsdjx47NimUGChlzIddk3jN9fOONN6YP27+7Gu+dd97Z3i7zICYyTJw4MfW8o0V0jAktMRb/wIyfmTNnhpdeeqnL5JFCEkMyx9H5OI7jzTffTP3+ly5d2rm6y/PKysrUTiVxJ45t27aF9DPu8iKVBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKFGBkSNH9tnIYpJDfBnt3r17u33B7fnz58M999wTnnnmmcTxvP7664lxQQIECBAgkK9AWVtcOa8MC4H4h8XBgwfDn/70p/b5fvrTnw4zZsxILWpvD2YcxJ9H3MEhlnwXibe2tob4iWXEiBGpzM7USRf/p5BrcnX38ccfp5I53nvvvfYmN9xwQ5g2bdqQmWe+XjHhY9KkSe0O6YOY7BI9elJaWlrCmDFjsi4ppK+sTroJxN/uhx9+GA4dOhSOHDnS3jomYlxzzTWp3UwmT56c92+0vYNBePAPy3amRv3fzyVv51aqU7r5vhc6DK1q6swO504IECBAYHALLLvq/+swgS/N7DoZtkPjEjz5zd6Ou5Dd9eThEhylIREgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgMBACcU1d+uXBmfePa5tikkChpampKdTU1GRdHl/m+/d///dZ8XwC1dXVYd26de1Nc4093aChoSE88sgj4bOf/WzqBblnzpxJ7erwwx/+MGzfvj3dLOs7jrGxsTErnk8g15h665nPvbUhQIAAgdIS+N9X1pfWmIymjwTim/BjEkP85FvidlP5JjSk+4x/tCX94ZauT/ou5JqkfmJs3LhxqZ0G4m4D+ZbBNs98veJuC51LzLLtaVJD7CMmESSVmGlbSH9JfeWKxd9u/CM7fhQCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgMF4HDhw+H+Cm0PPnkk3mv74rJC10lMOQaQ3w5rkKAAAECBHorUN7bDlxPgMDgEli0aFFRBxyzdBUCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKD2BiRMntg8qvgB4zZo17efFOPjoo49CfHGtQoAAAQIEeitgx4beCrqewCAT2L17d1i8eHGPR/3OO+8kXjN27NjEuCCBrgSOHdrbVbU6AgQIEBhsAld1HPBv9p7qGHBGgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBISLQ1tbWJzO5+uqr+6Tf5ubmUFVV1d53XDsWX2b7uc99Lpw8ebI93tODpUuXhtWrV/f0sqz2feWZdSMBAgQIECh5ATs2lPwjMkAChQucPXs26+JNmzaFpqamrHhXgZaWllBXV5fY5Morr0yMCxIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGCoCZSXl4fKysqsafX2BbGx32LvphAHef3112eNdcqUKSEmPBw5ciTEBIV8S5z3qlWrwrlz54qS1BDv21ee+c5JOwIECBAoHQE7NpTOszASAkUXuO222xL7rKmpCRs2bAgPPvhgl9uAtba2hv/4j/8ICxYsSOxn8+bNIW5PphAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGC4CMSkgLi2Kn5iqagozlLMuJtC/PRXqa6uTiUoxJ0Xzp8/H/785z+nkh1iwkO6TJo0KZUcce211xZtnum+09995Znu3zcBAgQIDA6B4vy36eCYq1ESGHYCt956a845x2SF+KmtrQ133313uOmmm1Jbjh07dizs27cvvPbaa+Hw4cM5r4/XzZs3L2e9CgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECAxVgbjTQPwMlTJq1KgQd3KIn4EoQ81zIAzdkwABAoNdoKytra1tsE/C+AkQyC3Q1NQU4g4NxSxxS7EPP/xwSP1hXkyfvuzrH5btTHX/38/N7svb6JsAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAvwkMnXTBfiNzIwKDSyBuF5a5NVhvR79ixYoQt/4aStnGvTVxPQECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAEChQtIbCjczpUEBo1ATG6Im7Ps2bMn1NXV9XjccYeGVatWhXPnzoWVK1f2+HoXECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIJdARa4KcQIEhp7AzJkzw759+0Jra2v48MMPw8GDB8O7774bjh49Gs6cORNOnz6dmvRVV10Vamtrw2c/+9nU96hRo4YehhkRIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFASAhIbSuIxGASB/hUoLy8PVVVVqU99fX3/3tzdCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgkCFQnnHskAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECDQrwISG/qV280IECBAgAABAgQIECBAgAABAgQIECBAgJKL5XoAACAASURBVAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBTAGJDZkajgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIF+FZDY0K/cbkaAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhkCkhsyNRwTIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECPSrgMSGfuV2MwIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCBTQGJDpoZjAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoF8FJDb0K7ebESBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABApkCEhsyNRwTIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAEC/SogsaFfud2MAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQyBSQ2JCp4ZgAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBDoVwGJDf3K7WYECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBApoDEhkwNxwQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEC/Ckhs6FduNyNAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQyBSQ2ZGo4JkCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBPpVQGJDv3K7GQECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIJApILEhU8MxAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAg0K8CEhv6ldvNCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgUwBiQ2ZGo4JECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBfhWQ2NCv3G5GgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIZApIbMjUcEyAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAj0q4DEhn7ldjMCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEAgU0BiQ6aGYwIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKBfBSQ29Cu3mxEgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKZAhIbMjUcEyBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAv0qILGhX7ndjAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEMgUkNiQqeGYAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQ6FcBiQ39yu1mBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQKaAxIZMDccECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAvwpU9Ovd3IwAAQIECBAgQIAAAQIECBAgQIAAAQIESlLg5vteKMlxdTeoVV/4f901UU+gzwXuevJwn9/DDQgQIECAAAECBAgQIECAAAECBAgQIECAwFAWsGPDUH665kaAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBEpcQGJDiT8gwyNAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAkNZQGLDUH665kaAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBEpcoKLEx2d4BAgQIECAAAECBAgQIECAAAECBAgQIDAAAlVTZw7AXXt/yy/NnND7Tgawh9/sPdXh7oN9PunJDLV5dZ5Pep6+CRAgQIAAAQIECBAgQIAAAQIECBAgQIAAgcIE7NhQmJurCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgSIISGwoAqIuCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgcIEJDYU5uYqAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoAgCEhuKgKgLAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoDABiQ2FubmKAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKIKAxIYiIOqCAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKExAYkNhbq4iQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEiiAgsaEIiLogQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEChOoKOwyVxEorkBTU1M4ffp0GDlyZBg7dmyoqqoq7g266a2lpSWcO3cuVFRUpO5fXi7npxsy1QQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECiKgNXbRWHUSW8E7rjjjlBTUxOmT58epk6dGiZPnhzWrl3bmy57dG1ZWVkYM2ZMmDRpUhg/fnwYMWJEOHbsWI/60JgAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEChOwY0Nhbq7qQqCxsTEcOXIkjBo1KlRXV6c+XTQPJ0+ezKo+e/ZsVqwvAq2trYndnjlzpttdI3o6z8QbCRIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGCYC0hs6KMfwMWLF8Mbb7yRV++jR49OJQFceeWV4VOf+lS44oorQtxFYDCWiRMnZiUqNDQ0hG3btpXkdAp1HmzzLEn8PAeV/rf0k5/8JLz66qtZv6/Kysrw5S9/OSxevDjceuutobzcRjR50mpGgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoCQEJDb00WO47LLLetXz7Nmzw7PPPhvq6+t71U9/XtzU1JS16Dzef/v27SHujDBUFpwPl3n2528n6V4tLS3h/vvvT/1+kurTsbjjx6ZNm1KfGFuzZk0qySFd75sAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgdIW8GrzPng+zc3Nve51586d4fbbb0/t3BAX0g/2UujOCINt3sNlnn39XHbs2BHGjBnTbVJD0jiWLFkS4o4acacHhQABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACB0heQ2NAHz+jUqVNF7bWmpiZs3bq1qH32RWeffPJJzm7b2tpy1g22iuEyz4F6LmvXrg1z5szp1e3jLg693TWlVwNwMQECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECeQtIbMibKv+GI0eOzL9xni3nzp0bSn3nhquuuirnbMrLh85PbbjMM+fD7MOKmMATd1zIVSorK8OKFSvC5s2bw5o1a8Ls2bNzNU3FH3rooS7rVRIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgMPACQ2e1+cBbdjuCXbt2hUuXLoVz5851+Jw9ezYcOnQorFq1qss+brzxxi7rB7py9OjRIc6xrq4uxAXo8RMXnp84cWKgh1bU+w+XeRYVLY/OLl68GGICT65y5MiR0NzcHFauXBnmzZsXFi9eHN58883Uv6WGhobEyzZt2hQaGxsT6wQJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECgNAYkN/fgcampqQty5YNSoUR0+caH8lClTwrJly0JbW1tYuHBh4qhOnjxZ8ou06+vrw759+1IL0OMi9LjwfOLEiYnzGczB4TLP/nxG//Zv/5Z4u5gg09raGqqrqxPr47+nbdu2hVzJDV/5ylcSrxMkQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKA0BCQ2lMZz6DCKdevWpXY66BD8v5Of//znSWExAoNaICYuLF++PHEOf/nLX0JZWVliXWYwJjcklf3794eWlpakKjECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBEpAQGJDCTyEpCH88pe/TAqHtWvXJsYFCQxmgd///veJw1+xYkVqd5PEyoTgrl27EqIhbN26NTEuSIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDAwAtIbBj4Z5A4gokTJ4bKysqsugkTJmTFBAgMdoG33norcQqPP/54YjxX8NZbb02s+u53v5sYFyRAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYOAFKgZ+CEbQE4FTp0512/zYsWPhV7/6VTh9+nS44oorQk1NTbjrrru6va5zg8bGxvDmm2+293P99deH+vr6zs06nJ8/fz688sorIY4h3nvSpEmhoaEhlJf3Tw7NxYsXw6uvvhp++MMfht27d4eTJ0+2j2/27Nnh6aefDnfeeWcoKytrjxdyUMg8W1pawssvv9zuefPNN4cZM2Z0uH1bW1v49a9/Hb7//e93GH9Mcon2TzzxRFHGH2/a2toa4k4JP/vZz8Lrr78e3n///dRYYvJM/Nxyyy1h3rx5iQk26UFHh9iuoqJ3/1ESfy+dS5xzTPDpSYm/s7q6urB///4Ol8XzaNvb596hUycECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBRFoHerkYsyBJ3kEoiLyzMX5udq1zk+bdq0rOsOHDgQYjzfEheBT506Nav5oUOHwpQpU7Li6cD06dPD4cOH06ep7xUrVoSVK1d2iBX7JI73scceC+vXr8/Z9c6dO8OcOXNS9Vu2bAn33ntvzrbdVRQyzxtuuCHL5tKlS+1JHzHp4YEHHki8dfwdbN++PfWJDXo7/ueeey4sX748571iRUwG6MozffHChQvDunXr0qcFfW/YsCHruuuuuy4rlk/gO9/5Tpg7d25W02jd2wSMrE4FCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBDotYDEhl4T9k0HcaF+5wSBeKfa2tpubxgXhHdOiBg5cmS31xWjQUzG6FzGjh3bOVTU87gTwpgxY3rUZ1z4HndwiLsjFFIKmWfSNXEHgbhzwqc//enE551rbHH8S5cuDatXr87VJDFeiFViRxnBpqamjLPCDpNs8tmdJOlun//855PC4YMPPugyKSfxIkECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBPpcoLzP7+AGBQn84Q9/SLzuySefTIwP1+DFixd7nNSQtoo7OFx22WXp0wH5Pn78eBgxYkSPkhrSA33++efDxo0b06fdfvfGqqvOP/74466qC65LSnYouLMQwrvvvtuby11LgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAfCUhs6CPY3nYbdxNIKl/+8peTwsM2VlVV1eXc4w4X8+fPD3V1dV22G6jKyZMn57x1Q0NDt+NesGBBiAkL+ZSvfvWrOZutWLEiHDhwIJw4cSLs378/xHvnW55++ul8m/ao3fvvv9+j9unG11xzTfqww/fbb7/d4dwJAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKlISCxoTSeQ/so2trawk033RROnjzZHksfxMXnFRUV6dNh/71169ZEpwgTF+afPXs2NDY2hpdeeins27cvXLp0Kaxatark3WJiQfwdbNu2LTXu1tbWsGbNmpzjfvHFF3PWpSuOHTsWtm/fnj5t/46JHxcuXAgrV64M06ZNCxMnTgwzZsxI3fvIkSPt7TIPKisrU+OLY4yfu+66K7O6oOOHH34467r4b6ClpSUrLkCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwNASkNjQj8/z+PHjqYXgcaF6509zc3PYuHFjKC8vT70xv/Ow4gL0uPhc+ZvA3Llz/3aScbRw4cLUwvzRo0dnREPKdtmyZeHo0aMd4qVyEpMxYqJATCzILGVlZWHx4sVhw4YNmeH24yeeeKL9ONfBU089lVh16NChnMky1dXVqR0cOl8YEw5iwkh/lJ/85Cc9vk30UggQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQGDwCEhv68VnNmjUrtbh+xIgRofNn0qRJYcGCBYmjmT9/fr8tJE8cQAkGm5qaEkcVdxNYt25dYl06WFVVldqlIH1eCt9Lly5NJWN0NZZHH300xASXziUmGly8eLFzuMP5+vXrO5zHk82bN4fukgDiDg7x99e55Eqy6Nwu3/P7778/semSJUvC+fPnE+tyBQ8ePJhYNWbMmMS4IAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECAysgsWFg/fO6+7PPPptXu+HU6IUXXkic7h//+MfEeOdgRUVFySQ3xB0mVq9e3XmIiec/+tGPEuMffPBBYjwG4+4gSeVrX/taUjgr9q1vfSsrVuzEhilTpmTdIx24/PLLw8cff5w+zfnd0tISFi1aFKZPn57YJia0KAQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIlJ6AxIbSeyZZI5o6dWqIb87PtUtB1gXDIPDjH/84a5Zxt4bq6uqseK5ATG44ceJErup+idfV1XW7w0TmQL70pS9lnuZ1nGtXhvLywv/5T5gwIa9796RR3EEiVxk/fnx46KGHwjvvvBNiAkPcxSEmOzQ2NoaNGzeGmBgRd2RI2pki3efhw4fTh74JECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECghgcJXNpfQJIbDUE6ePBlqamrCjh07hsN0u5xjW1tbiB6dy+OPP9451O15TIYYyBJ3GOhJyZWk0JM+etp23LhxPb2koPbz5s0LXT2PTZs2hZgIEhMY4i4OMdkhJv0sWLAgSFooiNxFBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBEpCoKIkRjFMBrF06dLw4IMPpt4233nKR44cCb/73e/CL37xiy4Xac+ZMyccOHAgTJs2rXMXw+b8+PHjiXONb/QfbOXs2bM9GnIhiQ0xESSpXLhwIYwaNSqpqkNs+/btHc7jyalTp7JixQh8+OGH4VOf+lRi4kox+tcHAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKlJ2DHhn58Jt/85jfDzJkzQ319fdYnvq1+9erVobGxMZw7dy7EJIhcZfr06bmqhkU8LshPKhMnTkwKD7lY3LWgJ6W8vDzU1tZmXfK9730vK5YUWLJkSVZ48eLFWbFiBOJYm5ubw8KFCwvuLte1n/vc5wru04UECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECPSdgMSGvrPN6vmTTz7JiiUF4lv0Y5LDnj17kqpTsa1bt+asG64VV1555XCderfzvvvuu7PaPPPMM6GpqSkrnhlYuXJl5mn78f33399+3BcH69atCydOnAgrVqwIlZWV3d6ioaEh9e8l7k4Rr00q119/fVJYjAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBARaQ2DDAD6Cr28fdHdasWZPY5JFHHkmMD+dgXNSuJAv84Ac/SKyoqakJGzduzKo7f/58eOihh0JMfuhcYqLBlClTOoeLfh534IiJFXEHh7hLR0x0OHr0aDhy5EjqE8/j7ibxuW/bti21G0ocREtLS+JYrrrqqsS4IAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECAysgsWFg/bu9++LFixPbnDx5MrS2tibWCRLoLFBRURHmz5/fOZw6X7BgQSgrKwv33HNPKpkhJi1cfvnlYdOmTYnt33777cR4Xwbj+GOiQ1VVVaiurk594nnc3aRziYkQSSXOSSFAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoPQEKkpvSEbUWaChoSFs3769czjEt+qPHj06K54UOH78eL+8ZT/p3v0Vi4ke5eVydZK8o02uRIV0+6TfWLou/R13EOmP3RrS9yvk+z//8z+zLqurq0slb2RVCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgMOACVoEP+CPofgB33HFHYqPTp08nxpOCv/3tb5PCQyr2wQcfDKn5FHMyDz/8cK+727VrV8i1g0ivOy9iB//6r/+a1Vsx5p/VqQABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAkURkNhQFMa+7eSvf/1r4g3OnDmTGB+uwSNHjgzXqXc577izR+fdGmpra8OWLVtCZWVll9fGylWrVoVLly6F+vr6btsOdINjx46FkydPZg3jG9/4RlZMgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACB0hCoKI1hGEVXAh999FFi9bXXXpsYTwqOGTMmKTwoY1dffXXiuDdu3DgoFt8nDr4Pg6+88kpW76+99lqYNm1aaG5uDi0tLeHdd98NjY2N7e2mTJkSrr/++jB69Oj22GA4ePzxxxOHWV1dnRgXJECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEBg4AUkNgz8M+h2BOvXr09sU16e/4YbL7/8cli8eHFiP0nBZcuWJYVLIlZWVpY4jui0bt26xLpcwcceeyxX1ZCJx10MOpeYtJAuMXlhxowZqU86Nhi/m5qasnamiPNYs2bNYJyOMRMgQIAAAQIECBAgQIAAAQIEBlzg2KG9Az6GvAZwVcdWv9l7qmNgkJ8NtfmkH8dQnVd6fr4JECBAgAABAgQIECBAgAABAgQIECBAgACBngnkvzK+Z/1qXSSB5557LrGn2trakCux4ZZbbsm6ZufOneH8+fNZ8aTA2rVrw/PPP59UVRKxmNiwdOnSxLHs3Zv//7M12uZKGknsfJAGd+/enTXyb3/721mxwRy4ePFiqKmpSZzCcEheSZy4IAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFBIiCxoYQf1I4dO8Ly5csTR/jiiy8mxmPwrrvuSqx76qmnEuOZwbjYf8mSJZmhkjxetGhR4rhmzZoV2traEusyg3GeuWwz2w2F4/r6+qxpPPPMM2HKlCkhJj3EnQ7irg4ff/xxaGlpSSXAxESBfByzOh6AQBzrZZddlnjnVatWhYoKG9Mk4ggSIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKBEBiQ39+CBGjhyZ192asrOpQgAAIABJREFUm5vDPffcE+bMmZOzfdJi9XTje++9N33Y4TvuwrB169YOsfRJXMQe7zlYFvtPmzYtPfSs76lTp+ZclN/a2jqo5pk1uQICuX5Hhw8fDrfffntqp4PJkyeH8ePHhzFjxoTLL788lSgQdwSJu2PET0yCePLJJ8PBgwcLGEF+l8TEivj7jL//fMs777yTM6kh9rFs2bJ8u9KOAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIEBEvAq836Ev+2228Ldd98dTp8+nXjXI0eOhJ07dybWZQZju67K6NGjQ21tbYgL1zuXuXPnhoaGhvDCCy+k2pw9ezZs2bIlLFiwoHPTkj/fsGFD4rjjvOOi/M2bN4eY5BHf5h8Xzb/00kuDYjeKYsPHJJCFCxeG9evXF9x1NI2JMfETy549e8LMmTML7i/pwphYk/79V1ZWhscffzx8/etfTyVVjB07NpVgERNwTp06FV5//fXw2GOPhZMnTyZ1lYqdOHEiZ50KAgQIECBAgAABAgQIECBAgACBbIHf/+Kb2cFBERms4x4UuAZJgAABAgQIECBAgAABAgQIECBAgAABAgQIEOgXAYkN/cL8vzeJi8N7s7g89rJr165QXV3d7ahfe+21MH369MR227dvD/Ez2Mujjz4aVqxYkZjAEef2wAMPDPYpFm3869atC2+99VbYv39/UfqcNWtWWLp0aVi9enVR+oudZCYpxONnnnkm9SnkBgcOHAgTJ04s5FLXECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECDQzwLl/Xw/t+uFQNypob6+Pq8e4lv646L/QkvcySHueFDq5d133+3VED/66KNBMc9eTTKE1I4VxUpqSI8l7t6wY8eO9GnJfB89ejTE379CgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMDgEJDY0AfP6eqrry5qrzHBoK2tLa+dGjJvvHLlytRb9TNj3R3X1dWFS5cuhdGjR4djx4511zyr/tSpU1mx7gKFXJPus6KiIpw7dy5UVlamQ3l9x3leuHAhjBs3LueOD111VMiYC7mmqzHkW3fx4sUwfvz4xOYnTpxIPe9oER1jQkuMxeSA+NmzZ0+YP39+4rUxOGfOnNRvM2eDHlR85zvf6UHr7KYxkSf+O6mqqsquFCFAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoGQFJDb0waMpLy8Pa9asKajn2tra1ELyDRs2pBaWx4Xa8+bNK6iveNHq1avDgQMHQuy3qxLr4xv99+3bF+L4Y7nuuuuyLpkwYUJWLDNw3333ZZ6mjj/zmc9kxTIDhVyTef2oUaNCc3Nz2LJlS7cJDpnzjEkRsXzlK1/J7C51PHbs2KxYZqCQMRdyTeY908c33nhj+rD9u6vx3nnnne3tMg9iIsPEiRNTzztaRMeY0BJjMTkgfmbOnBleeumlLpNHDh8+nNltwcf33ntv6rfa0NCQdx/xecZ/a3EuMZFHIUCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEBg8AmUtcWV88qwEDh//nw4ePBg+NOf/tQ+309/+tNhxowZqUXt7cGMg/jziDs4xJJOBMioTjxsbW0N8RPLiBEjQllZWWK7zGAh12Ren3n88ccfpxbIv/fee+3hG264IUybNm3IzDNfr5jwMWnSpHaH9EFMdokePSktLS1hzJgxWZcU0ldWJwmB+Bz//Oc/p3YOibtIxPvHUlNTE6ZOnRomT56c928yoftBG/qHZTtTY//v52YP2jkYOAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFMgf99ZX1mxPGQFYhv5I9JDPGTb4lJCfkmNKT7jDs+pHd9SMe6+y7kmlx9jhs3LrXTQNxtIN8y2OaZr1fcbaFzqaur63FSQ+wj7uaQVF5//fWC+kvqKzMWn2P89DQBI7MPxwQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIlL5AeekP0QgJECimwKJFi4rZXWhoaChqfzojQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGB4CUhsGF7P22wJhN27dxek8M477yReN3bs2MS4IAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBPIRkNiQj5I2BAapwNmzZ7NGvmnTptDU1JQV7yrQ0tIS6urqEptceeWViXFBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQI5CMgsSEfJW0IDFKB2267LXHkNTU1YePGjeH8+fOJ9elga2trqt2YMWPSoQ7fmzdvDmVlZR1iTggQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQINATgbK2tra2nlygLQECg0cgJiaMGDGiywHX1taGu+++O9x0002hqqoqHDt2LOzbty+89tpr4fDhwzmvjdc1NjbmrFfRNwL/sGxnquP/fm5239xArwQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgT6WaCin+/ndgQI9KNAeXl5OHLkSIg7NOQqMXlh/fr1uaoT45WVleG9995LrBMkQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBATwTKe9JYWwIEBp9AdXV1KrmhWCNfsWJFaG5uDjFpQiFAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEBvBaxM7q2g6wkMAoGY3NDW1hb27NkT6urqejziuEPDqlWrwrlz58LKlSt7fL0LCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgkEugIleFOAECQ09g5syZYd++faG1tTV8+OGH4eDBg+Hdd98NR48eDWfOnAmnT59OTfqqq64KtbW14bOf/Wzqe9SoUUMPw4wIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECgJAYkNJfEYDIJA/wqUl5eHqqqq1Ke+vr5/b+5uBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQyBAozzh2SIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBDoVwGJDf3K7WYECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBApoDEhkwNxwQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEC/Ckhs6FduNyNAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQyBSQ2ZGo4JkCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBPpVQGJDv3K7GQECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIJApILEhU8MxAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAg0K8CEhv6ldvNCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgUwBiQ2ZGo4JECBAgAABAgQIEPj/2bv/2Krre3H8r5YCtshPLXrpYsvihRlDZxac31iDu1O4MRW2LBsOs0z+Af/AZGYIyS4x1C3XJYBm30TNHWyZ3Fx14v6YYLdcdXeTwB8bZgtsu7sQInSR3gwYLYJAFdpPXmf3dKfnvE97etqenp4+3slJ3+/n6/fjfeCv1/O8CBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKCkAhIbSsptMAIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCBTQGJDpoZ7AgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoKQCEhtKym0wAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIFNAYkOmhnsCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgpAISG0rKbTACBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEAgU0BiQ6aGewIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKCkAhIbSsptMAIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCBTQGJDpoZ7AgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoKQCEhtKym0wAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIFNAYkOmhnsCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgpAISG0rKbTACBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEAgU0BiQ6aGewIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKCkAhIbSsptMAIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCBTQGJDpoZ7AgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoKQCEhtKym0wAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIFNAYkOmhnsCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgpAISG0rKbTACBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEAgU0BiQ6aGewIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKCkAhIbSsptMAIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCBTQGJDpoZ7AgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoKQCNSUdzWAECBAgQIAAAQIECBAgQGAcBd7e0TiOoxuaAAEC4y9w/xMd4z8JMyBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgECWgBMbskA8EiBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAqUTkNhQOmsjESBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAlkCEhuyQDwSIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECpROoKd1QRiJAgAABAgQIECBAgAABAuUl8Pmls8trQmZTkQL/9e75AevyvRvA4WGMBbK/f2M8nO4JECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQlIATG4pi04gAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAYDQGJDaOhqA8CBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgKAGJDUWxaUSAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiMhoDEhtFQ1AcBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQlIDEhqLYNCJAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgRGQ0Biw2go6oMAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAoSkBiQ1FsGhEgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKjIVAzGp3og8BIBTo7O8PFixfDtGnTwowZM0J9ff1IuxxW+8uXL4crV66Empqa1PjV1XJ+hgWoMgECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBIoUsHu7SDjNRk/g3nvvDQ0NDWHx4sVh4cKFYf78+eH5558fvQGG6KmqqirU1dWFefPmhVmzZoUpU6aEM2fODNFKMQECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiMhoATG0ZDUR8DBE6ePBlOnToVpk+fHhYsWJD6DKiQ9dDd3Z0VCeHSpUs5sbEI9Pb2Jnb74YcfDnlqxHDXmTiQIAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBCa5gMSGMfoCXL16NfzqV78qqPfa2tpUEsCNN94YbrjhhnD99deHeIrARLzmzp0bshMVWltbwxtvvFGWyynWeaKtsyzxRzCpd999N+zcuTNcvHgx1UtMoPnOd74T4r+l0bwuXLgQ/v3f/z011pEjR3K6bmxsDGvXrg3r168fMoEnp7EAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIpAYkNY/RFmDp16oh6XrZsWXj66adDS0vLiPopZePOzs6cpIY4fnt7e4gnI1RXV5dyOmM21mRZ55gBjqDjnp6esGLFirB///6cXmJCUFtbW068mEA8jeNzn/tc6OjoGLR5LH/qqadSn1jxwIEDE+rf7KCLU0iAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgRAKVsdO8RFiFDtPV1VVo1bz14sbte+65J3VyQ9xIP9GvYk9GmGjrnizrHI/3smfPnnDdddclJjXE+cyYMWNUphWTIxYuXDhkUkPSYPHf7IMPPphUJEaAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQB4BiQ15YEYSPn/+/Eia57RtaGgI+/bty4mXW+Cjjz7KO6W+vr68ZROtYLKss1zey4ULF0JTU1N46KGHxnxK69ev7z99odjB4gklDz/8cLHNtSNAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAw6QQkNozBK582bdqo97pq1apQ7ic33HTTTXnXXV1dOV+1ybLOvC+zhAXbt28Ps2bNKur0hOFOM54IsWvXrrzNGhsbw8aNG8PWrVtDa2tr3nqx4JVXXgmxPxcBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAkMLVM5u86HXOu41Dhw4EK5duxauXLky4HPp0qVw4sSJsG3btkHnePvttw9aPt6FtbW1Ia6xubk5zJkzJ/VZtmxZOHfu3HhPbVTHnyzrHFW0YXYWk3iqqqrC5s2bh9myuOpdXV15T4SI3+f4HT558mTYsWNHaGtrC2+88UaIp5AcOnQo74DxhInLly/nLVdAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMDfBCQ2lPCb0NDQEOLJBdOnTx/wiRvlm5qawqZNm1KbpdetW5c4q+7u7tTm6sTCMgm2tLSEw4cPh7hRPH7eeeedMHfu3DKZ3ehNY7Ksc/TECu8pntIQ/63ku2KiwWhfn/vc5xK7XLNmTer7nO87vHTp0lSSUmLjEMI3vvGNfEXiBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAj8n4DEhjL8KuzcuTPEkw6Srtdeey0pLEagIgR6e3vzntIQTwE5ffp0KtFgNBd74cKFcOTIkcQuX3755cR4ZjAmKh09ejQz1H+/a9euVLJSf8ANAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQI5AhIbckjKI/DTn/40cSLPP/98YlyQQCUIVFVVJS5j7969qRNA6uvrQ0x+GM3r3/7t3xK7y5eskFR50aJFeZOROjo6kpqIESBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECDwfwISG8r0qzB37twQf6E++5o9e3Z2yDOBihHo6+sbsJZ169aFa9euhZUrV/bH8yU/9FcY5s3TTz+d06KxsTHEZIXhXPF0hqTLKStJKmIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE/i5Q8/dbdxNB4Pz580NO88yZM+FnP/tZuHjxYrj++utDQ0NDuP/++4dsl13h5MmT4Z133unv59Zbbw0tLS3Z1QY89/T0hNdffz3EOcSx582bF1pbW0N1dWlyaK5evRp+/vOfh+9///vh4MGDobu7u39+y5YtC08++WS47777wkg3xxezzsuXL4c9e/b0e37mM58JS5Ys6Z9fvIkb+3/xi1+E733vewPmH5Ncov3jjz8+KvOPY8WTD37729+GH//4x+Gtt94Kf/7zn1Nzickz8XPXXXeF1atXJybYpCcdHWK9mprR+a8kfk/ie5o5c2b40Y9+FOIJDWN5xflnfkfSY23bti19W/Dff/zHf0ys+x//8R9h06ZNiWWCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiEMDq7kUmOiUDcXJ606XqoweIvzWe3O3r06LB+gT5usF+4cGHOUCdOnAhNTU058XRg8eLFoaOjI/2Y+rt169bQ1tY2IDbaD3G+jz76aMj3q/lxvP3794fly5enht67d++AUwCGO59i1nnbbbfl2MTTCNJJHzHp4aGHHkqcSnyf7e3tqU+sMNL5b9++PWzevDnvWLHgyJEjg3qmG8dTFXbu3Jl+HPHfmExTquv3v/994lD/9E//lBgfLBiTZZqbm1NumfWiY/x+jjSZJrNP9wQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQqSaA0P6NfSWIlWkvcCJ2dIBCHbmxsHHIGt9xyS06dadOm5cTGIhCTMbKvGTNmZIdG9TmehBCTAwZLasgecNWqVeHee+8NMbGgmKuYdSa1iZvd48kJMVkkX1JD0vzi/J944omkokFj0SqOmS+pYdDGeQo7OzvzlJR/+Ne//nXiJG+44YbE+FDBr33ta4lV/vd//zcxLkiAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAgSG8r0W/CHP/whcWbFbGZP7KhCglevXg11dXVFrSae4DB16tSi2o5Wo7Nnz4YpU6YkJrEMNcYzzzwTdu/ePVS1/vKRWPV3knBz4cKFhOjECMVTMrKvmDyUPkUju2yo53yJRx999NFQTZUTIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQmLQCEhvK9NUvW7YscWYPPPBAYnyyBuvr6wddetxovmbNmtDc3DxovfEqnD9/ft6hW1tbh5z32rVrQ0xYKOT64he/mLfa1q1bw9GjR8O5c+fCkSNHQhy70OvJJ58stGrZ1evu7s6ZU9LJGjmV8gTuueeePCXCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAjkE6jJVyA+PgJ9fX3hjjvuCEkbruPm85oaryz9Zvbt25foFMvjxvzXXnst1NbWpquH3t7eEE852Lx5c3+sHG9iYsGSJUv6pxa/Ey+88EJ47LHH+mOZNy+99FJ45JFHMkM592fOnAnt7e058Zj4cfz48QHfq7lz54b49e+pAAAgAElEQVQ33ngjdHZ2hoaGhpw2c+bMCV1dXTnxiRaIrtE6+1q/fn12yDMBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAmMo4MSGMcTN7vrs2bMhbqaOG+yzP3Gj+O7du0N1dXXiZuu4Ab2trS27y0n9vGrVqsT1r1u3LrUxPzOpIVaMtps2bQqnT59ObDfewZiMEb8fmUkNcU5VVVVhw4YN4cUXX0yc4uOPP54Yzwxu2bIl87H//sSJEwOSGvoLQggLFixIneCQGYv3Menm5MmT2eEJ9xytk65Lly4lhQuK/cM//ENivaSkksSKggQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQmoYDEhhK+9DvvvDO1uX7KlCkh+zNv3rywdu3axNmsWbOmIjaSJy6uyGA8TSDpiqcJ7Ny5M6moP1ZfXx8+/vjj/udyuNm4cWMqGWOwucRTGWKCS/YVEw2uXr2aHR7wvGvXrgHP8eHVV19NJU3kFGQE4ukN8fuXfeVLssiuV87PMWGkVNdIkiVKNUfjECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEBgvAYkN4yU/jHGffvrpYdSeHFWfffbZxIX+8Y9/TIxnB2tqasomuSGeMLFjx47sKSY+/+AHP0iMv//++4nxGIyngyRdX/rSl5LCObFvfetbObFKSGzIWZQAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQLjIiCxYVzYhzfowoULQ/zl/HynFAyvt8qo/cMf/jBnIfG0hgULFuTE8wVicsO5c+fyFZck3tzcPOQJE5kT+fznP5/5WNB9vpMJqquL/+c/e/bsgsaebJX6+voSl/ypT30qMS5IgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAIxe9spldSge7u7tDQ0BDefvvtko5bjoPFzePRI/v6xje+kR0a8jkmQ4zntX79+mENny9JYVidDLPyzJkzh9lC9WyB//mf/8kOeSZAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBA4P8EakiUTmDjxo3hq1/9aujp6ckZ9NSpU+E3v/lN+MlPfhI6OjpyytOB5cuXh6NHj4ZFixalQ5Pu79mzZxPX/PDDDyfGyzl46dKlYU2vmMSGfKcIfPzxx2H69OlDjt/e3p5T5/z58zkxgRCKeT/cCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECEx2AYkNJfwGfPOb3wwLFizIO+Lq1avDjh07UokPW7ZsCc8880xi3cWLF4d8m9UTG1RYMG7IT7rmzp2bFK64WHNzczhy5EjB66qurg6NjY05CTPf/e53Q1tb25D9PPbYYzl1NmzYkBMTyC8wf/78/IVKCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECExygepJvv6SLv+jjz4qaLz4K/oxweHQoUN56+/bty9v2WQtuPHGGyfr0odc94oVK3LqPPXUU6GzszMnnhnIl/jwla98JbPahLzPlxxUV1dX9HquXLmS2DaetOIiQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCBZQGJDsktZRJcuXRqee+65xLl8/etfT4xP5mC+jeqT2SS99hdeeCF9O+BvQ0ND2L1794BYfOjp6QkPP/xwiMkP2decOXNCU1NTdnjCPceTLJKuPXv2JIULiv3lL39JrFdoUlNiY0ECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECFS6QvLO3whc9kZa3YcOGxOl2d3eH3t7exDJBAtkCNTU1Yc2aNdnh1PPatWtDVVVVePDBB1PJDDFp4brrrguvvPJKYv3f/e53ifGJGGxubs6Zdvy3Vew1bdq0YptqR4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGDSCtRM2pVPoIW3traG9vb2nBnHX9Wvra3NiScFzp49WxG/sp+0tnQsJnrk+xX+dJ3J+jfa5EtUSJskfcfSZem/8QSRSjitIb2epL9HjhxJChcUe+uttxLr3XDDDYlxQQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEQnBiwwT4Ftx7772Js7x48WJiPCn4y1/+MilcUbH333+/otYzmov52te+NuLuDhw4EPKdIDLizsusg5g0VMx18ODBxGbXX399YlyQAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAGJDRPiO/CXv/wlcZ4ffvhhYnyyBk+dOjVZlz7ouuMm/ezTGhobG8PevXvDnDlzBm0bC7dt2xauXbsWWlpahqw70Sps2bIlccrHjh1LjA8V3LVrV06VZcuWhaqqqpy4AAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECfxOoAVH+Ah988EHiJD/xiU8kxpOCdXV1SeEJGbv55psT57179+6K3HyfuNhhBF9//fWc2m+++WZYtGhR6OrqCpcvXw7Hjx8PJ0+e7K/X1NQUbr311lBbW9sfq8Sb5cuXJy4rfpd27NiRWJYvGC2TrslyykXS2sUIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIFCJQXUgldcZXIOlX4OOMqqsLf3179uwZ1iI2bdo0rPqlrJzv1+/zOQ02t0cffXSw4oooO3PmTM46YtJC+orJC0uWLAkrV67s/8TnSk9qiOufO3dummHA32eeeWbAcyEP//qv/5pY7YEHHkiMCxIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAg8DcBJzaU+Tdh+/btiTNsbGzMm9hw1113hSNHjgxot3///tDT0xOmT58+IJ708Pzzz4diNnYn9TUWsZjYsHHjxsQ5vvvuu2Hp0qUFDRtti0mGKKjzMqp08ODBnNl8+9vfDm1tbTnxyRhobW0N7e3tOUvft29fKtEjpyAhEP9tJf2bmTNnTpg5c2ZCCyECBAgQIECAAIFyEfivd8+Xy1TMYxIJ+N5NopdtqQQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQkEDhP/lfUHcqjabA22+/HTZv3pzY5UsvvZQYj8H7778/sWzLli2J8cxg3Oz/2GOPZYbK8n79+vWJ87rzzjtDX19fYllmMK4zn21mvUq4b2lpyVnGU089FZqamkJMeujs7AzxVIcLFy6Ey5cvpxJgrl69WpBjTscTMJAvwWPVqlUpi0KW9NnPfjax2ve///3EuCABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAn8XkNjwd4sxv5s2bVpBY3R1dYUHH3wwLF++PG/9pM3q6corV65M3w74G39RPv4KfdIVkwHimBNls/+iRYuSlpGKLVy4MO+m/N7e3gm1zryLHEZBvu9RR0dHuOeee0JDQ0OYP39+mDVrVqirqwvXXXddmDp1aupEkHg6RvzEJIgnnngiHDt2bBgjj03VOJ+kK869mGuwEz6iRUz2yHfFfzf33ntvzgkp6fpf+cpX0rf+EiBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECCQR6AmT1x4DATuvvvusGLFinDx4sXE3k+dOhX279+fWJYZjPUGu2pra0NjY2OIG9ezr/gr9K2treHZZ59N1bl06VLYu3dvWLt2bXbVsn9+8cUXE+cd111dXR1effXVEJM84ib9eBrByy+/PCFOoxht+JgEsm7durBr166iu46mMTEmfuJ16NChMFhCQNEDhZA6QWLnzp1hxowZOd3E5IUTJ07kxGMgfdJI/E5nX/Hfw+rVq7PD/c9xPfG0j6Qrjhn9/uVf/iV84hOfSFWJyUd79uzpHzOp3dGjR1NJIUllYgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQI/F1AYsPfLcb8Lm4OH8nm8jjBAwcOhAULFgw51zfffDMsXrw4sV57e3uIn4l+PfLII2Hr1q2JCRxxbQ899NBEX+KozT8mCvz617/Oe7LAcAeKSQAbN24MO3bsGG7TIevffvvtobu7e8h6SRXSyQ1JZZ/97GdTJ08klcUkjcGSP+K/2+H82922bVsY7FSRpDmIESBAgAABAgQIlEbg/idyE8BLM7JRCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE8glU5ysQLz+BeFJDS0tLQROLm6rjpv9ir/ir9/HEg3K/jh8/PqIpfvDBBxNinSNaZAipEyuOHDky0m4GtI+nN7z99tsDYiN96O3tLTqpYaixk06AyGwTkz+WLVuWGSrqPiZ8bNq0qai2GhEgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCYjAISG8bgrd98882j2mtMMOjr6yvopIbMgdva2lK/qp8ZG+q+ubk5XLt2LdTW1oYzZ84MVT2n/Pz58zmxoQLFtEn3WVNTE65cuRLmzJmTDhX0N67z448/DjNnzsx74sNgHRUz52LaDDaHQsuuXr0aZs2alVj93LlzqfcdLaJjTGiJsdOnT6c+hw4dCmvWrElsG4PLly9PfTfzVhhmQXX12P2X1NXVNeRs3nnnnWH/m8nsdO/evWNyikXmGO4JECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIVJrA2O0irjSpYawnbs5+7rnnhtHi71UbGxtTG8lffPHF1MbymNCwevXqv1cY5t2OHTvC0aNHQ+x3sCuWx1/0P3z4cEhvLr/llltymsyePTsnlhn48pe/nPmYuv/Upz6VE8sMFNMms/306dND3LQeN5UPleCQuc6YFBGvL3zhC5ndpe6H+nX/YuZcTJuciYUQbr/99pzwYPO97777curHQExkmDt3bup9R4voGBNaYqy+vj71Wbp0aXj55ZcHTR7p6OhI7L/Y4EhOGhlszE9+8pODFfeXxX8z8SSPePJCIVf8zsV/rzEhaOXKlYU0UYcAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgQyBqr64c941KQR6enrCsWPHwp/+9Kf+9cbN3kuWLEltau8PZtzEr0fcsB2vdCJARnHibW9vb4ifeE2ZMiVUVVUl1ssMFtMms33m/YULF1LJHO+9915/+LbbbguLFi2qmHUW6hUTPubNm9fvkL6JyS7RYzjX5cuXQ11dXU6TYvrK6aSMA9Hwv//7v8OpU6f6ZxkTQJqamsKtt96aSgbpLyjBzT9v2p8a5T+3LyvBaIYgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgMPYCf/vJ+rEfxwhlIBB/kT8mMcRPoVdMSig0oSHdZzzxIX3qQzo21N9i2uTrc+bMmSGeNBA/hV4TbZ2FesXTFrKv5ubmYSc1xD7iZv6k66233iqqv6S+yjEWT7BoaWkpx6mZEwECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGKEKiuiFVYBAECBQusX7++4LqFVGxtbS2kmjoECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBBIFJDYkMgiSKByBQ4ePFjU4n7/+98ntpsxY0ZiXJAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKFCEhsKERJHQITVODSpUs5M3/llVdCZ2dnTnywwOXLl0Nzc3NilRtvvDExLkiAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFCBCQ2FKKkDoEJKnD33XcnzryhoSHs3r079PT0JJang729val6dXV16dCAv6+++mqoqqoaEPNAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACB4QhU9fX19Q2ngboECEwcgZiYMGXKlEEn3NjYGFasWBE+/elPh/r6+nDmzJlw+PDh8Oabb4aOjo68bWO7kydP5i1XMDYC/7xpf6rj/9y+bGwG0CsBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBEgvUlHg8wxEgUEKB6urqcOrUqRBPaMh3xeSFXbt25StOjM+ZMye89957iWWCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQGI5A9XAqq0uAwMQTWLBgQSq5YbRmvnXr1tDV1RVi0oSLAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECIxWwM3mkgtoTmAACMbmhr68vHDp0KDQ3Nw97xvGEhm3btoUrV66Etra2YbfXgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAvkEavIViBMgUHkCS5cuDYcPHw69vb3hr3/9azh27Fg4fvx4OH36dPjwww/DxYsXU4u+6aabQmNjY7jjjjtSf6dPn155GFZEgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEBZCEhsKIvXYBIESitQXV0d6uvrU5+WlpbSDm40AgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIZAhUZ9y7JUCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiUVEBiQ0m5DUaAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhkCkhsyNRwT4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECJRUQGJDSbkNRoAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECGQKSGzI1HBPgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIlFRAYkNJuQ1GgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIZApIbMjUcE+AAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiUVEBiQ0m5DUaAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhkCkhsyNRwT4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECJRUQGJDSbkNRoAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECGQKSGzI1HBPgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIlFRAYkNJuQ1GgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIZApIbMjUcE+AAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiUVEBiQ0m5DUaAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhkCkhsyNRwT4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECJRUQGJDSbkNRoAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECGQKSGzI1HBPgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIlFRAYkNJuQ1GgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIZArUZD64J0CAAAECBAgQIECAAAECBAgQIECAAAECBEL4zJefxTABBbb9f///BJx1/inf/0RH/kIlBAgQIECAAAECBAgQIECAAAECBAgQIECgggSc2FBBL9NSCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDARBOQ2DDR3pj5EiBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBChKQ2FBBL9NSCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDARBOomWgTNl8CBAgQIECAAAECBAgQIECAAAECBAgQIFBqgfqFS0s9pPGGIXDmxLuJtT+/dHZiPB38r3fPp29Tf8ut/oDJeSBAgAABAgQIECBAgAABAgQIECBAgAABAhUs4MSGCn65lkaAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBMpdQGJDub8h8yNAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAhUsILGhgl+upREgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgXIXkNhQ7m/I/AgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQAULSGyo4JdraQQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoNwFJDaU+xsyPwIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgUMECEhsq+OVaGgECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKHcBiQ3l/obMjwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIVLCAxIYKfrmWRoAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEyl1AYkO5vyHzI0CAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECFSwgsaGCX66lESBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBcheQ2FDub8j8CBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBABQtIbKjgl2tpBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECg3AUkNpT7GzI/AgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQwQISGyr45VoaAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAodwGJDeX+hsyPAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhUsIDEhgp+uZZGgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgTKXUBiQ7m/IfMjQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIVLFBTwWuztAkk0NnZGS5evBimTZsWZsyYEerr60s6+8uXL4crV66Empqa1PjV1XJ+SvoCDEaAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwKQVsHt70r768ln4vffeGxoaGsLixYvDwoULw/z588Pzzz9fsglWVVWFurq6MG/evDBr1qwwZcqUcObMmZKNbyACBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhMZgEnNkzmtz9Gaz958mQ4depUmD59eliwYEHqM9hQ3d3dOcWXLl3KiY1FoLe3N7HbD8ZMbJIAACAASURBVD/8cMhTI4a7zsSBBAkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDDJBSQ2jNEX4OrVq+FXv/pVQb3X1tamkgBuvPHGcMMNN4Trr78+xFMEJuI1d+7ckJ2o0NraGt54442yXE6xzhNtnWWJP4JJvfvuu2Hnzp3h4sWLqV5iAs13vvOdEP8tjeU1XuOO5Zr0TYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGC8BSQ2jNEbmDp16oh6XrZsWXj66adDS0vLiPopZePOzs6cpIY4fnt7e4gnI1RXV5dyOmM21mRZ55gBjqDjnp6esGLFirB///6cXmJCUFtbW058NALjNe5ozF0fBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBMpdoDJ2mpeZcldX14hnFDdu33PPPamTG+JG+ol+FXsywkRb92RZ53i8lz179oTrrrsuMakhzmfGjBljMq3xGndMFqNTAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAmUo4MSGMXgp58+fH9VeGxoawt69e8PKlStHtd/R7uyjjz7K22VfX18qSSNvhQlUMFnWWS6v5MKFC2HJkiWho6OjpFMar3FLukiDESBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECgDASc2jMFLmDZt2qj3umrVqlDuJzfcdNNNedddXV05X7XJss68L7OEBdu3bw+zZs0qeVLDeI1bQlpDESBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECgbgcrZbV42pPkncuDAgXDt2rVw5cqVAZ9Lly6FEydOhG3btuVvHEK4/fbbBy0f78La2toQ19jc3BzmzJmT+ixbtiycO3duvKc2quNPlnWOKtowO4tJPFVVVWHz5s3DbDmy6uM17shmrTUBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBiS0gsaGE76+hoSHEkwumT58+4BM3yjc1NYVNmzaFvr6+sG7dusRZdXd3h5MnTyaWlUuwpaUlHD58OHR1daU+77zzTpg7d265TG/U5jFZ1jlqYMPoKJ6WEP+t5Lti4sxYXOM17lisRZ8ECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEJpKAxIYyfFs7d+4M8aSDpOu1115LCosRqAiB3t7evKc0xFNATp8+nUqcGe3Fjte4o70O/REgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCYiAISG8r0rf30pz9NnNnzzz+fGBckUAkCVVVVicvYu3dv6gSQ+vr6EJMQRvsar3FHex36I0CAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDARBSQ2lOlbmzt3boi/UJ99zZ49OzvkmUDFCPT19Q1Yy7p168K1a9fCypUr++P5khD6KxRxM17jFjFVTQgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhUnEBNxa2owhd0/vz5IVd45syZ8LOf/SxcvHgxXH/99aGhoSHcf//9Q7bLrnDy5Mnwzjvv9Pdz6623hpaWluxqA557enrC66+/HuIc4tjz5s0Lra2tobq6NDk0V69eDT//+c/D97///XDw4MHQ3d3dP79ly5aFJ598Mtx3331hpJvji1nn5cuXw549e/o9P/OZz4QlS5b0zy/exA32v/jFL8L3vve9AfOPSS7R/vHHHx+V+cex4skHv/3tb8OPf/zj8NZbb4U///nPqbnE5Jn4ueuuu8Lq1asTE2zSk44OsV5Nzej8VxK/J/E9zZw5M/zoRz8K8YSGUlzjNW4p1mYMAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAuUuMDq7kct9lRN0fnFzeebG/EKXsWjRopx2R48eDTFe6BU32C9cuDCn+okTJ0JTU1NOPB1YvHhx6OjoSD+m/m7dujW0tbUNiI32Q5zvo48+Gnbt2pW36/3794fly5enyvfu3TvgFIC8jfIUFLPO2267LccmnkaQTvqISQ8PPfRQ4ojxe9De3p76xAojnf/27dvD5s2b844VC44cOTKoZ7pxPFVh586d6ccR/43JNONxjde447FWYxIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAoJwGJDeX0NjLmEjfqZycIxOLGxsaMWsm3t9xyS05iw7Rp05Irj3I0JmNkXzNmzMgOjepzPAmhrq5uWH2uWrUqdTJAPB2hmKuYdSa1iSdHxJMTPvnJTya+73xzi/PfuHFj2LFjR74qifFirBI7ygh2dnZmPLklQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDA8ASqh1dd7VIJ/OEPf0gc6oknnkiMT9bg1atXh53UkLaKJzhMnTo1/Tguf8+ePRumTJkyrKSG9ESfeeaZsHv37vTjkH9HYjVY5xcuXBisWBkBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQGFZDYMCjP+BUuW7YscfAHHnggMT5Zg/X19YMuPZ5wsWbNmtDc3DxovfEqnD9/ft6hW1tbh5z32rVrQ0xYKOT64he/mLfa1q1bw9GjR8O5c+fCkSNHQhy70OvJJ58stKp6BAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQyBGoyYkIjKtAX19fuOOOO0J3d3fOPOLm85oarywNs2/fvkSnWB435r/22muhtrY2XT309vaGeMrB5s2b+2PleBMTC5YsWdI/tfideOGFF8Jjjz3WH8u8eemll8IjjzySGcq5P3PmTGhvb8+Jx8SP48ePD/hezZ07N7zxxhuhs7MzNDQ05LSZM2dO6OrqyokLECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoBgBJzYUo1Zkm7Nnz4a4ST1usM/+xI3iu3fvDtXV1alfzM8eIm5Ab2tryw5P6udVq1Ylrn/dunWpjfmZSQ2xYrTdtGlTOH36dGK78Q7GZIz4/chMaohzqqqqChs2bAgvvvhi4hQff/zxxHhmcMuWLZmP/fcnTpwYkNTQXxBCWLBgQeoEh8xYvI9JNydPnswOeyZAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEBRAhIbimIrrtGdd96Z2lw/ZcqUkP2ZN29eWLt2bWLHa9assZE8SyaeJpB0xdMEdu7cmVTUH6uvrw8ff/xx/3M53GzcuDGVjDHYXOKpDDHBJfuKiQZXr17NDg943rVr14Dn+PDqq6+mkiZyCjIC8fSG+P3LvvIlWWTX80yAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGhBGqGqqB8/AWefvrp8Z9Emc3g2WefTZzRH//4x8R4drCmpiaV3DB16tTsopI/xxMmduzYUdC4P/jBD8Ly5ctz6r7//vuhqakpJx4D8XSQpOtLX/pSUjgn9q1vfSu88sorA+IxscEJIgNIPBAgQIAAAQIECBAgQIAAAQIECFS4wJkT71b4Citzef/17vlhLazc6g9r8ioTIECAAAECBAgQIECAAAECBAgQIECAAIEJLODEhgnw8hYuXBjiL+fnO6VgAixh1Kf4wx/+MKfPeFrDggULcuL5AjG54dy5c/mKSxJvbm4e8oSJzIl8/vOfz3ws6L6qqiqxXnV18f/8Z8+endinIAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBIYrUPzO5uGOpP6IBLq7u0NDQ0N4++23R9RPJTTu6+sL0SP7+sY3vpEdGvI5JkOM57V+/fphDZ8vSWFYnQyz8syZM4fZQnUCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgULlBTeFU1RyqwcePG8NWvfjX09PTkdHXq1Knwm9/8JvzkJz8JHR0dOeXpwPLly8PRo0fDokWL0qFJ9/fs2bOJa3744YcT4+UcvHTp0rCmV0xiQ0wESbo+/vjjMH369KSiAbH29vYBz/Hh/PnhHd+e04EAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE/k9AYkMJvwrf/OY3w4IFC/KOuHr16rBjx45U4sOWLVvCM888k1h38eLFId9m9cQGFRaMG/KTrrlz5yaFKy7W3Nwcjhw5UvC6qqurQ2NjY07CzHe/+93Q1tY2ZD+PPfZYTp0NGzbkxAQIECBAgAABAgQIECBAgAABAgQIVJLAb3/yzUpaziRai/c2iV62pRIgQIAAAQIECBAgQIAAAQIECBAgQIBABQlUV9Bayn4pH330UUFzjL+iHxMcDh06lLf+vn378pZN1oIbb7xxsi59yHWvWLEip85TTz0VOjs7c+KZgXyJD1/5ylcyq7knQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBA0QISG4qmG/uGS5cuDc8991ziQF//+tcT45M5OJlPsRjqvb/wwguJVRoaGsLu3btzynp6esLDDz8cYvJD9jVnzpzQ1NSUHfZMgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBogQkNhTFVrpGGzZsSBysu7s79Pb2JpYJEsgWqKmpCWvWrMkOp57Xrl0bqqqqwoMPPphKZohJC9ddd1145ZVXEuv/7ne/S4wLEiBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoBiBmmIaaVNagdbW1tDe3p4zaPxV/dra2px4UuDs2bMV/yv7MdGjulquTtL7jzb5EhXS9ZO+Y+my9N94gojTGtIa/hIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgMBoCdoGPhuIY93HvvfcmjnDx4sXEeFLwl7/8ZVK4omLvv/9+Ra1nNBfzta99bcTdHThwIOQ7QWTEneuAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFJKyCxYQK8+r/85S+Js/zwww8T45M1eOrUqcm69EHXHU/2yD6tobGxMezduzfMmTNn0LaxcNu2beHatWuhpaVlyLoqECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYLgCNcNtoH7pBT744IPEQT/xiU8kxpOCdXV1SeEJGbv55psT5717926b7xNkXn/99Zzom2++GRYtWhS6urrC5cuXw/Hjx8PJkyf76zU1NYVbb7011NbW9sfcECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYCwEJDaMheoo97lr167EHqurCz9wY8+ePWHDhg2J/SQFN23alBQui1hVVVXiPKLTzp07E8vyBR999NF8RRUTP3PmTM5aYtJC+orJC0uWLEl90jF/CRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgUCqBwnfGl2pGxhkgsH379gHP6YfGxsaQL7HhrrvuSlfr/7t///7Q09PT/zzYzfPPPx+eeeaZwaqMa1lMbNi4cWPiHN59993EeFIw2uZLGkmqP1FjBw8ezJn6t7/97ZyYAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBMZDQGLDeKgXOObbb78dNm/enFj7pZdeSozH4P33359YtmXLlsR4ZjBu9n/ssccyQ2V5v379+sR53XnnnaGvry+xLDMY15nPNrNeJdy3tLTkLOOpp54KTU1NISY9dHZ2hniqw4ULF8Lly5dTCTBXr14tyDGnYwECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgMU0BiwzDBRlJ92rRpBTXv6uoKDz74YFi+fHne+kmb1dOVV65cmb4d8DeewrBv374BsfRDTAaIY06Uzf6LFi1KTz3n78KFC/Nuyu/t7Z1Q68xZXBGBfN+jjo6OcM8994SGhoYwf/78MGvWrFBXVxeuu+66MHXq1NSJIPF0jPiJSRBPPPFEOHbsWBEzGN0mcT5JV5z7WF7jNe5YrknfBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBMpBoKYcJjFZ5nD33XeHFStWhIsXLyYu+dSpU2H//v2JZZnBWG+wq7a2NjQ2Noa4cT37WrVqVWhtbQ3PPvtsqs6lS5fC3r17w9q1a7Orlv3ziy++mDjvuO7q6urw6quvhpjkETfpx9MIXn755QlxGsVow8ckkHXr1oVdu3YV3XU0jYkx8ROvQ4cOhaVLlxbd32AN4wkSO3fuDDNmzMipFpMXTpw4kROPgfRJI/E7nX3Ffw+rV6/ODg94Hq9xB0zCAwECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFJKCCxoYQvPW4OH8nm8jjVAwcOhAULFgw56zfffDMsXrw4sV57e3uIn4l+PfLII2Hr1q2JCRxxbQ899NBEX+KozT8mCvz6178OR44cGZU+77zzzrBx48awY8eOUekvs5Pbb789dHd3Z4YKvk8nNyQ1+OxnP5s6eSKpLMbGa9x88xEnQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgMFkEqifLQithnfGkhpaWloKWEn+lP276L/aKv3ofTzwo9+v48eMjmuIHH3wwIdY5okWGkDqxYrSSGtJziac3vP322+nHUfnb29tbdFLDUBNIOgEi3Wa8xk2P7y8BAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBySwgsWEM3v7NN988qr3GBIO+vr6CTmrIHLitrS31q/qZsaHum5ubw7Vr10JtbW04c+bMUNVzys+fP58TGypQTJt0nzU1NeHKlSthzpw56VBBf+M6P/744zBz5sy8Jz4M1lExcy6mzWBzKLTs6tWrYdasWYnVz507l3rf0SI6xoSWGDt9+nTqc+jQobBmzZrEtjG4fPny1Hczb4VhFlRXj91/SV1dXXlnM17j5p2QAgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKTSGDsdhFPIsTspcZN0s8991x2uKDnxsbG1EbyF198MbWxPCY0rF69uqC2SZV27NgRjh49GmK/g12xPP6i/+HDh0N6k/ctt9yS02T27Nk5sczAl7/85czH1P2nPvWpnFhmoJg2me2nT58e4qb1vXv3DpngkLnOmBQRry984QuZ3aXuB/t1/1ihmDkX0yZnYiGE22+/PSc82Hzvu+++nPoxEBMZ5s6dm3rf0SI6xoSWGKuvr099li5dGl5++eVBk0c6OjoS+y82OJKTRgYb85Of/ORgxSM64WSwjocad7C2yggQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhMBoGqvrhz3jUpBHp6esKxY8fCn/70p/71xk3XS5YsSW1q7w9m3MSvRzzBIV7pRICM4sTb3t7eED/xmjJlSqiqqkqslxkspk1m+8z7CxcupJI53nvvvf7wbbfdFhYtWlQx6yzUKyZ8zJs3r98hfROTXaLHcK7Lly+Hurq6nCbF9JXTiUDBAv+8aX+q7n9uX1ZwGxUJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIlLPA336yvpxnaG6jJhB/kT8mMcRPoVdMSig0oSHdZzzxIX3qQzo21N9i2uTrc+bMmSGeNBA/hV4TbZ2FesXTFrKv5ubmYSc1xD7iaQ5J11tvvVVUf0l9iREgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgMPkEqiffkq2YwOQWWL9+/agCtLa2jmp/OiNAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYHIJSGyYXO/bagmEgwcPFqXw+9//PrHdjBkzEuOCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKERAYkMhSuoQmKACly5dypn5K6+8Ejo7O3PigwUuX74cmpubE6vceOONiXFBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIFCIgsaEQJXUITFCBu+++O3HmDQ0NYffu3aGnpyexPB3s7e1N1aurq0uHBvx99dVXQ1VV1YCYBwIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECAxHoKqvr69vOA3UJUBg4gjExIQpU6YMOuHGxsawYsWK8OlPfzrU19eHM2fOhMOHD4c333wzdHR05G0b2508eTJvuYKxEfjnTftTHf/n9mVjM4BeCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECJRYoKbE4xmOAIESClRXV4dTp06FeEJDvismL+zatStfcWJ8zpw54b333kssEyRAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMBwBKqHU1ldAgQmnsCCBQtSyQ2jNfOtW7eGrq6uEJMmXAQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEBipgJ3JIxXUnsAEEIjJDX19feHQoUOhubl52DOOJzRs27YtXLlyJbS1tQ27vQYECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBDIJ1CTr0CcAIHKE1i6dGk4fPhw6O3tDX/961/DsWPHwvHjx8Pp06fDhx9+GC5evJha9E033RQaGxvDHXfckfo7ffr0ysOwIgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEykJAYkNZvAaTIFBagerq6lBfX5/6tLS0lHZwoxEgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCBDoDrj3i0BAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoKQCEhtKym0wAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIFNAYkOmhnsCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgpAISG0rKbTACBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEAgU0BiQ6aGewIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKCkAhIbSsptMAIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCBTQGJDpoZ7AgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoKQCEhtKym0wAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIFNAYkOmhnsCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgpAISG0rKbTACBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEAgU0BiQ6aGewIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKCkAhIbSsptMAIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCBTQGJDpoZ7AgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoKQCEhtKym0wAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAN0XBtAAAIABJREFUIFNAYkOmhnsCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgpAISG0rKbTACBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEAgU0BiQ6aGewIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKCkAhIbSsptMAIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCBTQGJDpoZ7AgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoKQCEhtKym0wAgQIECBAgAABAgQIECDw/9i7+xApr3tx4GfXVaNGozabeN2S1RC0QdyEok3JBgONem/ZxJbSag2lkXsx4VahoUahhFxNW1LwJfRyY6Da0ni5MdUEbuNLy432thH9o1VaNC1Fkagl7iVqXY0v60bd/XGmv9nMzjyzO7M7O+7ufA4M8zzf8/Kc85nZ/et85xAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBDIFJDYkKnhmgABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECirgMSGsnJ7GAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIJApILEhU8M1AQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgUFYBiQ1l5fYwAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIFNAYkOmhmsCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgrAISG8rK7WEECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBApoDEhkwN1wQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEBZBSQ2lJXbwwgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFMAYkNmRquCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgbIKSGwoK7eHESBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABApkCEhsyNVwTIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECZRWoKevTPIwAAQIECAwBgc9+9eVBtYq1n//3QTVfkyVAgECpBeY+d6rUQxqPAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIESCjixoYSYhiJAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgSKE5DYUJyX1gQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAJBSQ2lBDTUAQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEBxAjXFNdeaAAECBAgQyBaonTorOzSg778w644BPT+TG1oC/3voYpcF+f514XDTTwLZ37t+eoxhCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAokYATG0oEaRgCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgeAGJDcWb6UGAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiUSEBiQ4kgDUOAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgULyCxoXgzPQgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIESCUhsKBGkYQgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIHiBSQ2FG+mBwECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFAigZoSjWMYAn0SaG5uDpcvXw4jRowIY8aMCbW1tX0ar9jOra2t4dq1a6Gmpib1/OpqOT/FGmpPgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACB3gjYvd0bNX1KKvDoo4+Gurq6MH369DB16tRw1113hY0bN5b0Gd0NVlVVFUaPHh0mTpwYxo0bF4YNGxbOnj3bXRd1BAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFAiASc2lAjSMJ8InDx5Mpw+fTqMHDkyTJ48OfX6pDb36sKFCznBq1ev5sT6I9De3p447JUrV3o8NaLYdSY+SJAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIVLiCxoZ++ADdu3Ai//e1vCxp91KhRqSSAO++8M3zqU58Kt99+e4inCAzGMmHChJCdqNDU1BR27do1IJfTW+fBts4Bid+HSR06dChs2rQpXL58OTVKTKD5/ve/H+LfUqlKTFx58803w3/913+FI0eO5Aw7Z86c8M///M/hK1/5Shg7dmxOvQABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAoUJSGwozKnoVsOHDy+6T2aHuGn6pZdeCo2NjZnhAX3d3Nyck9QQJ7x79+4QT0aorq4e0PMvdHKVss5CPcrZrq2tLcyfPz/s27cv57ExIWjNmjU58WICcfwf/vCH4cUXX+yxW5xDfC1ZsiQ0NDSkEpliwotCgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEBxAkNjp3lxa+731i0tLX1+Rtww/cgjj6RObogb6Qd76e3JCINt3ZWyzlvxuWzfvj3cdtttiUkNcT5jxozp07TWrVuXGr+QpIbsB8UTHSZOnBh27tyZXeWeAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIEeBCQ29ADUm+qLFy/2plvePnV1dYNiw/THH3+cdw0dHR156wZbRaWsc6B8LpcuXQpTpkwJixYt6rcpPfroo2HVqlV9Hn/BggUhJmAoBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgULiCxoXCrgluOGDGi4LaFNowbpgf6yQ1333133uVUVw+dr1qlrDPvh1nGiniKwrhx48KpU6f67akx6SaekFKqEhMwWltbSzWccQgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgMeYGhs9t8EHxU+/fvDzdv3gzXrl3r8rp69Wo4ceJEWLt2bbermDFjRrf1t7py1KhRIa6xoaEhjB8/PvWaM2dOOH/+/K2eWkmfXynrLClakYPFJJ6qqqqSnKLQ06P/7//+L7FJfX192LNnT4h/nzH5Ib7a29vD6dOnQ1NTU2KfdPBf/uVf0pfeCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBDoQUBiQw9Apayuq6sL8eSCkSNHdnnFjfJTpkwJK1euTG2eXrp0aeJjL1y4EE6ePJlYN1CCjY2N4fDhw6GlpSX1evfdd8OECRMGyvRKNo9KWWfJwIoYKJ7SEP9W8pWYOFPKMmnSpC7DxYSGmLwQ/9bmzp0b4t9nusRki8mTJ4ddu3aFbdu2pcM572+88YZTG3JUBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgkC0hsSHa5pdFNmzaFeNJBUnnzzTeTwmIEhoRAPBFh1apViWuJp4CcOXMmlTiT2KCXwZhslC7xhIaY0BCTF3oqCxcuDKtXr87b7MMPP8xbp4IAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgU8EPtnR+0nM1QAQ+MUvfpE4i40bNybGBQkMBYF4IkJS2bFjR+oEkNra2hCTH0pd4pjxFU9oKKb827/9W97mv//97/PWqSBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBA4BMBiQ2fWAyoqwkTJoT4C/XZ5Y477sgOuScwZAQ6Ojq6rGXp0qXh5s2b4YknnuiM50t+6GzQi4s4Zm/Gjac95Dtd5dSpU72YiS4ECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEKk+gpvKWPLhXfPHixR4XcPbs2fDLX/4yXL58Odx+++2hrq6u6F+ijw85efJkePfddzvHue+++0JjY2O3z29rawtvv/12iHOIz544cWJoamoKcQN4OcqNGzfCr371q/DjH/84HDhwIFy4cKHzsXED+gsvvBAee+yxXm1i7xwohNCbdba2tobt27d3en72s58NM2fOzBw2xI39v/71r8OPfvSjLvOPSS7R/tlnny3J/OND4wkFf/jDH8LPf/7zsGfPnvDXv/41NZeYPBNfDz30UFi4cGFigk160tEhtqupKc2/knSiwNixY8PPfvazEE9oGOglGu3bt2+gT9P8CBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECAxYgdLsRh6wyxvcE4ubyzM35he6mmnTpuX0O3r0aIjxQkvcYD916tSc5idOnAhTpkzJiacD06dPD9m/VL969eqwZs2adJN+eY/zfeaZZ8LmzZvzjh83n8+bNy9Vv2PHji6nAOTtlKeiN+u8//77c2ziaQTppI+Y9LBo0aLEJ8bvwe7du1Ov2KCv81+3bl1YtWpV3mfFiiNHjnTrme4cT1XYtGlT+rbP7zGZRiFAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoHIEJDYM0M86btTPThCIU62vr+9xxvfcc09OYsOIESN67FeKBjEZI7uMGTMmO1TS+3gSwujRo4sac8GCBSGe4BBPR+hN6c06k/pUVVWlTk649957Ez/vfHOL81+xYkVYv359viaJ8d5YJQ6UEWxubs64q7zLmOyTVIr9TiaNIUaAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgEgSqK2GRg3GNf/rTnxKn/dxzzyXGKzV448aNopMa0lbxBIfhw4enb2/J+7lz58KwYcOKSmpIT3TDhg1hy5Yt6dse3/ti1d3gly5d6q56yNe99dZbiWtsampKjAsSIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQINBVQGJDV48BcxdPE0gqX/ziF5PCFRurra3tdu3xhIvFixeHhoaGbtvdqsq77ror76Pjxvie5r1kyZIQExYKKV/+8pfzNlu9enU4evRoOH/+fDhy5EgoZlP+Cy+8kHfcoV4R7ZNOVonr/od/+IehvnzrI0CAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFASgZqSjGKQkgl0dHSEBx98MFy4cCFnzLj5vKbGR5aG2blzZ6JTrI8b8998880watSodPPQ3t4e4ikHq1at6owNxIuYWDBz5szOqcXvxKuvvhqWL1/eGcu8eP3118NTTz2VGcq5Pnv2bNi9e3dOPCZ+HD9+vMv3asKECWHXrl2hubk51NXV5fQZP358aGlpyYlXYuC3v/1t4rKj0ciRIxPrBAkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQ6CrgxIauHv16d+7cuRA3qccN9tmvuFF8y5Ytobq6OvWL+dkTiRvQ16xZkx2u6PsFCxYkrn/p0qWpjfmZSQ2xYbRduXJlOHPmTGK/Wx2MyRjx+5GZ1BDnVFVVFZYtWxZee+21xCk+++yzifHM4PPPP59523l94sSJLkkNnRUhhMmTJ6dOcMiMxeuYdHPy5MnscEXef+1rX0tc9w9+8IPEuCABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABArkCEhtyTfotMnv27NTm+mHDhoXs18SJE8OSJUsSn7148WIbybNk4mkCSSX+Uv6mTZuSqjpjtbW14fr16533A+FixYoVqWSM7uYST2WICS7ZJSYa3LhxIzvc5X7z5s1d7uPNtm3bUkkTORUZgXh6Q/z+ZZd8SRbZ7Yby/YEDB/KeGPLMM88M5aVbGwECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGSCkhsKCln/wz20ksv9c/Ag3jUl19+OXH2f/7znxPj2cGampoBk9wQT5hYv3599hQT73/yk58kxj/44IPEeAzG00GSyle+8pWkcE7su9/9bk6s0hMb4skajzzySI5LDKxduzbvKRiJHQQJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIVLiAxIZB8AWYOnVqiL+cn++UgkGwhJJP8ac//WnOmPG0hsmTJ+fE8wVicsP58+fzVZcl3tDQ0OMJE5kT+cIXvpB5W9B1VVVVYrvq6t7/+d9xxx2JY1ZKcOXKlXmX2l1d3k4qCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECFSwQO93Nlcw2q1Y+oULF0JdXV3Yu3fvrXj8gHpm/LX86JFdvv3tb2eHeryPyRC3sjz99NNFPT5fkkJRgxTZeOzYsUX2GNrN33vvvbBhw4bERR45ciQxLkiAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQH6BmvxVakotsGLFivD1r389tLW15Qx9+vTp8Pvf/z689dZb4dSpUzn16cC8efPC0aNHw7Rp09Khins/d+5c4pqffPLJxPhADl69erWo6fUmsSEmgiSV69evh5EjRyZVdYnt3r27y328uXjxYk6sEgLxbzeespFUFi9eHGbOnJlUJUaAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQDcCEhu6wSl11Xe+850wefLkvMMuXLgwrF+/PpX48Pzzz+f9Vfjp06eHfJvV8w4+hCrihvykMmHChKTwkIvFjfXFnAxQXV0d6uvrcxJmfvjDH4Y1a9b06LN8+fKcNsuWLcuJVUJg0qRJeZe5devWvHUqCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBDIL1Cdv0pNqQU+/vjjgoaMv6IfExwOHjyYt/3OnTvz1lVqxZ133lmpS+9x3fPnz89p8+KLL4bm5uaceGYgX+LD1772tcxmFXH9+OOPhwsXLiSutdiTNxIHESRAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQoQISGwbwBz9r1qzwyiuvJM7wm9/8ZmK8koOVfIpFT5/7q6++mtikrq4ubNmyJaeura0tPPnkkyEmP2SX8ePHhylTpmSHh/T9c889F3bv3p24xhMnToRRo0Yl1gkSIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQINCzgMSGno1uaYtly5YlPj/+cnx7e3tinSCBbIGampqwePHi7HDqfsmSJaGqqirEEwliMkNMWrjtttvCG2+8kdj+j3/8Y2J8qAbjqRUbNmxIXN6ePXsqLskjEUKQAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQB8EavrQV9cyCTQ1NSX+Wnz8Vf1Cfyn+3LlzQ34Ddkz0qK6Wq5P0tYw2+RIV0u3znUiQro/v8QSRSjqtYePGjYmnVqQt5s6dm8njmgABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBXgjYBd4LtHJ3efTRRxMfefny5cR4UvA3v/lNUnhIxT744IMhtZ5SLuYb3/hGn4fbv39/yHeCSJ8HH4ADbN++PSxfvjxxZqtXr64oi0QEQQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIlEpDYUCLI/hzmww8/TBz+ypUrifFKDZ4+fbpSl97tuuPJHtmnNdTX14cdO3aE8ePHd9s3Vq5duzbcvHkzNDY29th2qDTYu3dvWLRoUeJyYlLDmjVrEusECRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAoXqCm+C56lFvgo48+Snzkpz/96cR4UnD06NFJ4UEZmzRpUuK8t2zZUlGb7xMREoJvv/12TvSdd94J06ZNCy0tLaG1tTUcP348nDx5srPdlClTwn333RdGjRrVGauUi0OHDoV58+YlLnfp0qWSGhJlBAkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAj0XkBiQ+/tytZz8+bNic+qri78wI3t27eHZcuWJY6TFFy5cmVSeEDEqqqqEucRnTZt2pRYly/4zDPP5KsaMvGzZ8/mrCUmLaRLTF6YOXNm6pWOVer7sWPHwuzZsxOXv3jx4qK/X4kDCRIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAg0EWg8J3xXbq5KZfAunXrEh9VX18f8iU2PPTQQzl99u3bF9ra2nLiSYGNGzeGDRs2JFUNiFhMbFixYkXiXOKv7Rdaom2+pJFCxxgM7Q4cOJAzze9973s5sUoPNDc3h+nTpycyNDU1ha1btybWCRIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAg0DcBJzb0za9fe+/duzesWrUq8Rmvv/56YjwG586dm7hh//nnnw/r16/P2y9WxM3++Z7ZbccyVz799NOJyRfx1/bb29tDvlMd0tMcLOtMz7cv742NjeGNN97oMsSLL74YXnvttRC/R1OnTg3Dhw8Pt912W6ipqUklzAwbNizEV0+OXQYdxDfxVIu6urrEFcyZMyfs2rUrsU6QQFrg7InCk6rSfcr6fnfXp/3voYtdA+4IlFHA96+M2B5FgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBQSLgxIYyflAjRowo6GktLS3h8ccfD/PmzcvbPm5Wz1eeeOKJxKp4CsPOnTsT6zo6OlLPHAxJDXEB06ZNS1xHDMaN+nE9SSUmPUTbwbLOpDUUG8v3PTp16lR45JFHUhv677rrrjBu3LgwevToVIJDTHSIJ4LExIb4mjJlSnjuuefCsWPHin18ydvnS7aIc+9NuXHjRojrTyoxqeHdd99NqhIjQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKBEAk5sKBFkIcM8/PDDYf78+eHy5cuJzU+fPh327duXWJcZjO26K6NGjQr19fUhblzPLgsWLAhNTU3h5ZdfTrW5evVq2LFjR1iyZEl20wF/H08cSJp3XHfclL9t27YQkzziJv1Lly6FrVu3huXLlw/4dZV6gjEJZOnSpYmneBT6rGgaE2PiK5aDBw+GWbNmFdq9qHbNzc1h06ZNYcyYMTn9YvLCiRMncuIxkP5s43c6u8S/h4ULF2aHU/ff+ta3EuMxGP8eH3jggbz1PVXMmDEj9b3rqZ16AgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABApUsILGhjJ9+3By+efPmPj1x//79YfLkyT2O8c4774Tp06cnttu9e3eIr8FennrqqbB69erEBI64tkWLFg32JZZs/jFR4He/+104cuRIScacPXt2WLFiRVi/fn1JxsscJCYDXLhwITNU8HU6uSGpw+c+97nUyRPZddGlu9IXs9g3GhXyN9vdHNQRIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQGMoCEhsG0acbT2oodIN0/JX+uOn/xRdf7NUK46/e79y5c8AnBxw/fjx1IkOvFhlC+OjJHbd5AAAgAElEQVSjj8KvfvWrAb/O3q4v3S+eWNGXDfrpcTLf4+kN//RP/xTmzp2bGe7TdXt7e6+TGnp6cNIJED31KUV9PEFFGXoCf3jrO4NsUYNtvoOM13QJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBPglU96m3zokCkyZNSoz3Nrht27bQ0dFRcFJD+jlr1qxJ/ap++r6Q94aGhnDz5s0QN2OfPXu2kC5d2ly8eLHLfSE3vemTHrempiZcu3YtjB8/Ph0q6D2u8/r162Hs2LF5T3zobqDezLk3fbqbQ6F1N27cCOPGjUtsfv78+dTnHS2iY0xoibEzZ86kXgcPHgyLFy9O7BuD8+bNS3038zYosqK6uv/+JbW0tCTOpr8/l/4eP3FRggQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQGkUD/7SIeRAilnmrcnP3KK6/0atj6+vrURvLXXnsttbE8JjQsXLiwV2PFTuvXrw9Hjx4NcdzuSqyPv+h/+PDhkN5cfs899+R0ueOOO3JimYGvfvWrmbep68985jM5scxAb/pk9h85cmSIm9Z37NjRY4JD5jpjUkQsX/rSlzKHS1339Ov+vZlzb/rkTCyEMGPGjJxwd/N97LHHctrHQExkmDBhQurzjhbRMSa0xFhtbW3qNWvWrLB169Zuk0dOnTqVOH5vg/Gkkf4o9957b+KwP/nJTxLjpQjGhJspU6aUYihjECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEBiyAlUdcee8UhECbW1t4dixY+Evf/lL53rjZu+ZM2emNrV3BjMu4tcjnuAQSzoRIKM68bK9vT3EVyzDhg0LVVVVie0yg73pk9k/8/rSpUupZI7333+/M3z//feHadOmDZl1FuoVEz4mTpzY6ZC+iMku0aOY0traGkaPHp3TpTdj5QwiULDAP67cl2r7P+vmFNxHQwIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIDWeDvP1k/kGdobiUTiL/IH5MY4qvQEpMSCk1oSI8ZT3xIn/qQjvX03ps++cYcO3ZsiCcNxFehZbCts1CveNpCdmloaCg6qSGOEU9zSCp79uzp1XhJY4kRIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFB5AtWVt2QrJlDZAk8//XRJAZqamko6nsEIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEKgsAYkNlfV5Wy2BcODAgV4pvPfee4n9xowZkxgXJECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQCECEhsKUdKGwCAVuHr1as7M33jjjdDc3JwT7y7Q2toaGhoaEpvceeediXFBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIFCIgsaEQJW0IDFKBhx9+OHHmdXV1YcuWLaGtrS2xPh1sb29PtRs9enQ61OV927ZtoaqqqkvMDQECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBIoRqOro6OgopoO2BAgMHoGYmDBs2LBuJ1xfXx/mz58fHnjggVBbWxvOnj0bDh8+HN55551w6tSpvH1jv5MnT+atV9E/Av+4cl9q4P9ZN6d/HmBUAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAmUWqCnz8zyOAIEyClRXV4fTp0+HeEJDvhKTFzZv3pyvOjE+fvz48P777yfWCRIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKAYgepiGmtLgMDgE5g8eXIquaFUM1+9enVoaWkJMWlCIUCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQF8F7Ezuq6D+BAaBQExu6OjoCAcPHgwNDQ1Fzzie0LB27dpw7dq1sGbNmqL760CAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIF8AjX5KsQJEBh6ArNmzQqHDx8O7e3t4W9/+1s4duxYOH78eDhz5ky4cuVKuHz5cmrRd999d6ivrw8PPvhg6n3kyJFDD8OKCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAYEAISGwbEx2ASBMorUF1dHWpra1OvxsbG8j7c0wgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIJAhUJ1x7ZIAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgUFYBiQ1l5fYwAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIFNAYkOmhmsCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgrAISG8rK7WEECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBApoDEhkwN1wQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEBZBSQ2lJXbwwgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFMAYkNmRquCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgbIKSGwoK7eHESBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABApkCEhsyNVwTIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECZRWQ2FBWbg8jQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEMgUkNmRquCZAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgTKKiCxoazcHkaAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhkCkhsyNRwTYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECJRVoKasT/MwAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBRIHPfvXlxLggAQKDV2Dt5/998E4+Y+ZznzuVceeSAAECBAgQIECAAAECBAgQIECAQOkFnNhQelMjEiBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgUKSGwoEEozAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoPQCEhtKb2pEAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoECBmgLbaUaAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFBGgdqps8r4NI8iQKCUAmdPHEoc7guz7kiMp4P/e+hi+jL1fqvaZ8+jy6TcECBAgAABAgQIECBAgAABAgQIEOgHASc29AOqIQkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIHCBCQ2FOakFQECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQINAPAhIb+gHVkAQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEBhAhIbCnPSigABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEOgHAYkN/YBqSAIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKAwAYkNhTlpRYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECPSDgMSGfkA1JAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFCYgMSGwpy0IkCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBPpBQGJDP6AakgABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEChMQGJDYU5aESBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAv0gILGhH1ANSYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBQmILGhMCetCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgX4QkNjQD6iGJECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAoTkNhQmJNWBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQD8ISGzoB1RDEiBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAoUJSGwozEkrAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoB8EJDb0A6ohCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgcIEJDYU5qQVAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAg0A8CEhv6AdWQBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQGECEhsKc9KKAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQ6AcBiQ39gGpIAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoDABiQ2FOWlFgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQI9IOAxIZ+QDUkAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgUJhATWHNtCLQvwLNzc3h8uXLYcSIEWHMmDGhtra2fx+YNXpra2u4du1aqKmpST2/ulrOTxaRWwIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECPSLgN3b/cJq0GIEHn300VBXVxemT58epk6dGu66666wcePGYoboU9uqqqowevToMHHixDBu3LgwbNiwcPbs2T6NqTMBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIFCbgxIbCnLQqQuDkyZPh9OnTYeTIkWHy5MmpV3fdL1y4kFN99erVnFh/BNrb2xOHvXLlSo+nRhS7zsQHCRIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKDCBSQ29NMX4MaNG+G3v/1tQaOPGjUqlQRw5513hk996lPh9ttvD/EUgcFYJkyYELITFZqamsKuXbsG5HJ66zzY1jkg8fswqUOHDoVNmzaFy5cvp0aJCTTf//73Q/xbKkWJCS9//vOfw5YtW8KePXvCkSNHcoadM2dOWLhwYepVW1ubUy9AgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEBhAhIbCnMqutXw4cOL7pPZIW6afumll0JjY2NmeEBfNzc35yQ1xAnv3r07xI3i1dXVA3r+hU6uUtZZqEc527W1tYX58+eHffv25Tw2JgStWbMmJ15M4NKlS2HFihVh8+bNPXaLc4iv5cuXh/Hjx6cSIWKChUKAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQHECQ2OneXFr7vfWLS0tfX5G3DD9yCOPpE5uiBvpB3vp7ckIg23dlbLOW/G5bN++Pdx2222JSQ1xPmPGjOnTtJ577rkwbty4gpIash8UTympq6sLGzduzK5yT4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBADwISG3oA6k31xYsXe9Mtb5+4YXrnzp156wdKxccff5x3Kh0dHXnrBltFpaxzoHwu8RSFKVOmhEWLFvXblB599NGwYcOGPo8fT2+ICRgKAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKFC0hsKNyq4JYjRowouG2hDRcsWBAG+skNd999d97lVFcPna9apawz74dZxop169alTlE4depUvz21vb097ykQ8aHjx48PixcvDitWrAhNTU09ziMmYNy4caPHdhoQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIPB3gaGz23wQfKL79+8PN2/eDNeuXevyunr1ajhx4kRYu3Ztt6uYMWNGt/W3unLUqFEhrrGhoSG1GTxuCJ8zZ044f/78rZ5aSZ9fKessKVqRg8UknqqqqrBq1aoiexbfPD4nqcS/x/i32dLSErZu3RrWr18fdu3aFeLpI0eOHEnq0hn71re+1XntggABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACB7gUkNnTvU9Laurq6EE8uGDlyZJdX3Cg/ZcqUsHLlytSm6aVLlyY+98KFC+HkyZOJdQMl2NjYGA4fPpzaDB43hL/77rthwoQJA2V6JZtHpayzZGBFDBRPaYh/K/lKTJwpZYmJCpnllVdeCfEUh/j3GP82k8rMmTPD9evXk6pSsc2bN+etU0GAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQFcBiQ1dPQbE3aZNm1InHSRN5s0330wKixEYEgIxoSDfKQ3xBJAzZ86kEmdKudiYbFRfX5/6m4snNCxbtix1WkRPz6ipqQlHjx7N2yyuRSFAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoGcBiQ09G92SFr/4xS8Sn7tx48bEuCCBoSBQVVWVuIwdO3akTgGpra1NnaaQ2KgPwXgSSjxdJN8JDfmGnjZtWiopIqn+ypUrSWExAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgSyBCQ2ZIEMlNsJEyaE+Av12eWOO+7IDrknMGQEOjo6uqxl6dKl4ebNm+GJJ57ojOdLfuhsUOaLhx9+OPGJf/vb3xLjggQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIdBWo6XrrbqALXLx4sccpnj17Nvzyl78Mly9fDrfffnuoq6sLc+fO7bFfdoP0r9inx7nvvvtCY2NjdrMu921tbeHtt98OcQ7x2RMnTgxNTU2huro8OTQ3btwIv/rVr8KPf/zjcODAgXDhwoXO+c2ZMye88MIL4bHHHgt93Rzfm3W2traG7du3d34un/3sZ8PMmTM75xcv4sb+X//61+FHP/pRl/nHJJdo/+yzz5Zk/vFZ7e3t4Q9/+EP4+c9/Hvbs2RP++te/puYSk2fi66GHHgoLFy5MTLBJTzo6xHY1NaX5VxK/J/FzGjt2bPjZz34W4gkNA73EUxuSyogRI5LCYgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIZAmUZjdy1qBuSyMQN5dnbswvdNS40Tq739GjR0O+DdhJ48YN9lOnTs2pOnHiRJgyZUpOPB2YPn16OHXqVPo29b569eqwZs2aLrFS38T5PvPMM2Hz5s15h963b1+YN29eqn7Hjh1dTgHI2ylPRW/Wef/99+fYxNMI0kkfMelh0aJFiU+Mn+fu3btTr9igr/Nft25dWLVqVd5nxYojR45065nuHE9V2LRpU/q2z+/vvvtun8co5wD//d//nfi4SZMmJcYFCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBDoKiCxoavHgLmLG/WzEwTi5Orr63uc4z333JOT2FCuX4+PyRjZZcyYMdmhkt7HkxBGjx5d1JgLFixInQwQT0foTenNOpP6xJMj4skJ9957b+LnnW9ucf4rVqwI69evz9ckMd4bq8SBMoLNzc0Zd5V3GRNAFAIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEei9Q3fuuevanwJ/+9KfE4Z977rnEeKUGb9y4UXRSQ9oqnuAwfPjw9O0teT937lwYNmxYUUkN6Ylu2LAhbNmyJX3b43tfrLob/NKlS91VD+m6jRs3Jq5v8eLFnSdxJDYQJECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgU0BiQyfFwLqYM2dO4oS++MUvJsYrNVhbW9vt0uMJF3GTeUNDQ7ftblXlXXfdlffRTU1NPc57yZIlISYsFFK+/OUv5222evXqcPTo0XD+/PkQTyCIzy60vPDCC4U2HVLtzp49G5YvX564pn//939PjAsSIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIJArUJMbErmVAh0dHeHBBx8MFy5cyJlG3HxeU+MjS8Ps3Lkz0SnWx435b775Zhg1alS6eWhvbw/xlINVq1Z1xgbiRUwsmDlzZufU4nfi1VdfzbuJ/vXXXw9PPfVUZ/uki7gJf/fu3TlVMfHj+PHjXb5XEyZMCLt27QrNzc2hrq4up8/48eNDS0tLTrySAgcOHAiPPPJI4pJjIk1PCTeJHQUJECBAgAABAgQIECBAgAABAgQIECCQJXD2xKGsiFsCBAa7wP8euljUEgZa+6ImrzEBAgQIECBAgAABAgQIECBAgACBIgSc2FAEVl+bnjt3LsRN6nGDffYrbhTfsmVLqK6uTv1ifvaz4gb0NWvWZIcr+n7BggWJ61+6dGlqY35mUkNsGG1XrlwZzpw5k9jvVgdjMkb8fmQmNcQ5VVVVhWXLloXXXnstcYrPPvtsYjwz+Pzzz2fedl6fOHGiS1JDZ0UIYfLkyakTHDJj8Tom3Zw8eTI7PKTv4+fS2toa9u7dGx544IG8SQ3x73Tr1q1D2sLiCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECJRaQGJDqUW7GW/27NmpzfXDhg0L2a+JEyeGJUuWJPaOvwBfaRvJEyEygvE0gaQSTxPYtGlTUlVnLP6a/vXr1zvvB8LFihUrUskY3c0lnsoQN85nl5hocOPGjexwl/vNmzd3uY8327ZtSyVN5FRkBOLpDfH7l13yJVlktxts9zHhKK45JpNkvmJSzOjRo8O8efO6JB7F71u6+DtNS3gnQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgUJyAxIbivG5J65deeumWPHcgP/Tll19OnN6f//znxHh2sKamZsAkN8QTJtavX589xcT7n/zkJ4nxDz74IDEeg3GzflL5yle+khTOiX33u9/NiQ3VxIa//vWvqRMpchacJxCTSmKJp4A4qSEPkjABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBHgRqeqhXPQAEpk6dGuIvw8dN+5MnTx4AM7r1U/jpT3+aM4loVIxPTG44f/58iKdl3KrS0NDQ4wkTmXP7whe+kHlb0HU8eSCpxFMIelvuuOOO3nYd0P1GjBjRq/lNmzYt/OAHPwj/+q//mjqVpVeD6ESAAAECBAgQIECAAAECBAgQIECAQMUL/OGt71S8AQACQ0/A3/XQ+0ytiAABAgQIECBAgAABAgQIECBAoD8EetvYRsoAACAASURBVL+zuT9mY8y8AvGX4evq6sLevXvztqmUio6OjsRf1f/2t79dNEFMhriV5emnny7q8fmSFIoapMjGY8eOLbLH4G0+fPjwXk0+/n0uX748DBs2LBw6dKhXY+hEgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoFIFnNhQxk9+xYoV4etf/3poa2vLeerp06fD73//+/DWW2+FU6dO5dSnA/PmzQtHjx4N8RfiK7WcO3cucelPPvlkYnwgB69evVrU9HqT2BATQZLK9evXw8iRI5OqusR2797d5T7eXLx4MSc2FAK1tbVh//794fjx42HUqFGdS2ptbQ3vvfde2LNnTzhy5EhnPOli9uzZ4bXXXgtPPfVUUrUYAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJZAhIbskD68/Y73/lOmDx5ct5HLFy4MKxfvz6V+PD888+HDRs2JLadPn16yLdZPbHDEAvGDflJZcKECUnhIRdraGjocXN95qKrq6tDfX19TsLMD3/4w7BmzZrMponX8SSC7LJs2bLs0JC5b2xsDPGVr8S/vT/96U9hzpw5iSeHxH5LliwJM2bMCLNmzco3jDgBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAv9foJpE+QQ+/vjjgh4Wf0U/JjgcPHgwb/udO3fmravUijvvvLNSl97juufPn5/T5sUXXwzNzc058cxAvsSHr33ta5nNKuo6npoxc+bM0NLSkjqZId/i48kNlZyAlM9FnAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEC2gMSGbJEBdB9/7f2VV15JnNE3v/nNxHglB20iz//pv/rqq4mVdXV1YcuWLTl1bW1t4cknnwwx+SG7jB8/PkyZMiU7XJH3Tz31VLfJDf/5n/9ZkS4WTYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKAYAYkNxWjdgrbLli1LfOqFCxdCe3t7Yp0ggWyBmpqasHjx4uxw6n7JkiUhnkLw+OOPp5IZYtLCbbfdFt54443E9n/84x8T45UajMkNDQ0Nict/+eWXE+OCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAh8IiCx4ROLAXvV1NSUOLf4q/qFlnPnzhXadNC2k+iR/6OLNvkSFdK9du/enWpz6tSpdCjnPZ4g4rSGHJbw5ptv5gZDCBcvXkyMCxIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAg8ImAxIZPLAbs1aOPPpo4t8uXLyfGk4K/+c1vksJDKvbBBx8MqfWUcjHf+MY3+jzc/v37Q74TRPo8+CAfoLa2NnEFMUmko6MjsU6QAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIG/C0hsGATfhA8//DBxlleuXEmMV2rw9OnTlbr0btcdT/bIPq2hvr4+7NixI4wfP77bvrFy7dq14ebNm6GxsbHHtpXaoDtHiQ2V+q2wbgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgUIFagptqN2tE/joo48SH/7pT386MZ4UHD16dFJ4UMYmTZqUOO8tW7bYfJ8g8/bbb+dE33nnnTBt2rTQ0tISWltbw/Hjx8PJkyc7202ZMiXcd999YdSoUZ0xF/kFzp07l7eyulr+WF4cFQQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgRCCBIbBsHXYPPmzYmzLGbD9Pbt28OyZcsSx0kKrly5Mik8IGJVVVWJ84hOmzZtSqzLF3zmmWfyVQ2Z+NmzZ3PWEpMW0iUmL8ycOTP1Sse8Fydw7NixxA4NDQ2JcUECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBD4R8FPin1gMyKt169Ylzqu+vj7kS2x46KGHcvrs27cvtLW15cSTAhs3bgwbNmxIqhoQsZjYsGLFisS5HDp0KDGeFIy2+ZJGktoP1tiBAwdypv69730vJ1apgfb29j4v/ZFHHkkc4xvf+EZiXJAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgU8EJDZ8YjHgrvbu3RtWrVqVOK/XX389MR6Dc+fOTax7/vnnE+OZwbjZf/ny5ZmhAXn99NNPJ85r9uzZoaOjI7EuMxjXmc82s91QuG5sbMxZxosvvhimTJkSYtJDc3NziKc6XLp0KbS2tqYSYG7cuFGQY87AgywQvyvDhg0LMVkmKQGkkOU899xzeZstWbIkb50KAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgT+LiCxoYzfhBEjRhT0tJaWlvD444+HefPm5W2ftFk93fiJJ55IX3Z5j6cw7Ny5s0ssfRM3eMdnDpbN/tOmTUtPPed96tSpeTflx1/nH0zrzFlcLwL5vkenTp0K8aSBurq6cNddd4Vx48aF0aNHh9tuuy0MHz48dSJI3PAfXzEJIm7gP3bsWC9mUNoucT5JJc692HLu3LnOLtEijh3/Rgo5xSH9Xcp3uklDQ0Oora3tHN8FAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQLJAjXJYdH+EHj44YfD/Pnzw+XLlxOHP336dNi3b19iXWYwtuuujBo1KtTX14e4cT27LFiwIDQ1NYWXX3451ebq1athx44dYTD+svxrr72WOO+47urq6rBt27YQkzziJv14GsHWrVsHxWkU2Z9ZX+9jEsjSpUvD5s2bez1UNI0b+NOb+A8ePBhmzZrV6/G66xhPkNi0aVMYM2ZMTrOYvHDixImceAykTxqJ3+nsEv8eFi5cmB0OV65cyYnFv5FY5syZk0rm+PznP59K+oixjz/+OJw8eTL8x3/8R4+e+/fvzxlbgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBXAGJDbkm/RaJm8P7srk8Tixulp48eXKPc3znnXfC9OnTE9vt3r07xNdgL0899VRYvXp1YgJHXNuiRYsG+xJLNv+YKPC73/0uHDlypCRjzp49O6xYsSKsX7++JONlDjJjxoxw4cKFzFDB1+nkhqQOn/vc51InT2TW3XPPPZm3Xa5jklEhiUZdOv3/m5gsNHbs2KQqMQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEsgSqs+7dDmCBeFJDY2NjQTOMv9IfN/33tsRfvY8nHgz0cvz48T5N8aOPPhoU6+zTIkNInVhRqqSG9Fzi6Q179+5N35bkvb29vddJDT1NIOkEiHiyR0NDQ09di6rfs2dP6qSQojppTIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKCCBSQ29MOHP2nSpJKOGhMMOjo6CjqpIfPBa9asSf2qfmasp+u4yfvmzZth1KhR4ezZsz01z6m/ePFiTqynQG/6pMesqakJ165dC+PHj0+HCnqP67x+/XrqV/XjSRrFlt7MuTd9ip1XUvsbN26EcePGJVWF8+fPpz7vaBEdY0JLjJ05cyb1OnjwYFi8eHFi3xicN29e6ruZt0GRFTHRoL9KS0tL4tCHDx8Oa9euTawrJhi/UzFRZu7cucV005YAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAxQv03y7iCqaNm7NfeeWVXgnU19enNpK/9tprqY3lMaFh4cKFvRordlq/fn04evRoiON2V2J9/EX/uMk7vbn8nnvuyelyxx135MQyA1/96lczb1PXn/nMZ3JimYHe9MnsP3LkyBA3re/YsaPHBIfMdcakiFi+9KUvZQ6Xuk76df/MRr2Zc2/6ZD4zfT1jxoz0Zed7d/N97LHHOttlXsREhgkTJqQ+72gRHWNCS4zV1tamXrNmzQpbt27tNnmkN4khmfPIvu7LSSPZY2Xe33vvvZm3Xa5XrlwZ4mkRMZGjqampS11PN0uXLg3xNJX4tzN27NiemqsnQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCBLoKoj7pxXKkKgra0tHDt2LPzlL3/pXG/c7D1z5szUpvbOYMZF/HrEExxiSScCZFQnXsYN4vEVy7Bhw0JVVVViu8xgb/pk9s+8vnTpUiqZ4/333+8M33///WHatGlDZp2FesWEj4kTJ3Y6pC9iskv0KKa0traG0aNH53TpzVg5gwzAQFzvhx9+GI4fP546xSI9xeh53333hbvvvjuVCJKOl+v9H1fuSz3qf9bNKdcjPYcAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAvwr8/Sfr+/URBh8oAvEX+WMSQ3wVWmJSQqEJDekx44kP6VMf0rGe3nvTJ9+Y8Vfz40kD8VVoGWzrLNQrnraQXRoaGopOaohjxNMcksqePXt6NV7SWAMpFtc7ZcqU1GsgzctcCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECAw1geqhtiDrIUCge4Gnn366+wZF1jY1NRXZQ3MCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAh8IiCx4RMLVwQqQuDAgQO9Wud7772X2G/MmDGJcUECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgUIiCxoRAlbQgMUoGrV6/mzPyNN94Izc3NOfHuAq2traGhoSGxyZ133pkYFyRAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEAhAhIbClHShsAgFXj44YcTZ15XVxe2bNkS2traEuvTwfb29lS70aNHp0Nd3rdt2xaqqqq6xNwQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgGIGqjo6OjmI6aEuAwOARiIkJw4YN63bC9fX1Yf78+eGBBx4ItbW14ezZs+Hw4cPhnXfeCadOncrbN/Y7efJk3noV/SPwjyv3pQb+n3Vz+ucBRiVAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBQZoGaMj/P4wgQKKNAdXV1OH36dIgnNOQrMXlh8+bN+aoT4+PHjw/vv/9+Yp0gAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEihGoLqaxtgQIDD6ByZMnp5IbSjXz1atXh5aWlhCTJhQCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAj0VcDO5L4K6k9gEAjE5IaOjo5w8ODB0NDQUPSM4wkNa9euDdeuXQtr1qwpur8OBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQyCdQk69CnACBoScwa9ascPjw4dDe3h7+9re/hWPHjoXjx4+HM2fOhCtXroTLly+nFn333XeH+vr68OCDD6beR44cOfQwrIgAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgQEhILFhQHwMJkGgvALV1dWhtrY29WpsbCzvwz2NAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECGQLVGdcuCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJlFZDYUFZuDyNAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQyBSQ2ZGq4JkCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBMoqILGhrNweRoAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECGQKSGzI1HBNgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIlFVAYkNZuT2MAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQyBSQ2JCp4ZoAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAoq4DEhrJyexgBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECCQKSCxIVPDNQECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFBWAYkNZeX2MAIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCBTQGJDpoZrAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoKwCEhvKyu1hBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQKaAxIZMDdcECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAWQUkNpSV28MIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBTAGJDZkargkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGyCkhsKCu3hxEgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKZAhIbMjVcEyBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAmUVkNhQVm4PI0CAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBDIFJDZkargmQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEyiogsaGs3B5GgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIZApIbMjUcE2AAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiUVUBiQ1m5PYwAAQIECBAgQIAAAQIECBAgQIAAAQIECBD4f+zdfYwd1X0w/rOLjbHBYFMM+dkVNigyTQlLUkGjYuRULaZNDaRqC8RRCygSTiWoGhVsqYoi7FRNFQNRpBqkBzcK/BEoJKkawI2emDYJD0RJIU0xrVoQiu00uCqm2GBjY7B3fzrzPnPn7pt313t3PyOtd+bMefl+P2fuXe/unB0CBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGqgIUNVQ37BAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwJQKWNgwpdwGI0CAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBKoCFjZUNewTIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECUypgYcOUchuMAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQqApY2FDVsE+AAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhMqYCFDVPKbTACBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgKmBhQ1XDPgECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDClAhY2TCm3wQgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGqgIUNVQ37BAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwJQKWNgwpdwGI0CAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBKoCc6oH9gkQIECAAAECBAgQIECAAAECBAgQmHkCT92zfOYlJaOeE7jqzj09F7OACRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEpkbAExumxtkoBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQIuAhQ0tKIoIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBqRGwsGFqnI1CgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQItAjMaSlTRIAAAQIECBAgQIAAAQIECBAgQIDADBb4jcvO6uns/un5N2vx93o+eTIzLa9mPnmePhMgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBBoCnhiQ1PEMQECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDBlAhY2TBm1gQgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGmgIUNTRHHBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwJQJWNgwZdQGIkCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBJoCc5oFjgmcDIG9e/eGQ4cOhVNPPTWcfvrpYcmSJVMaxpEjR8I777wT5syZk4zf32/Nz5ROgMEIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEJi1Au7enrVTP30S/+hHPxqWLVsWLrroonDBBReEc889N9x3331TFmBfX19YsGBBOPvss8OZZ54ZTjnllLBv374pG99ABAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQmM0Cntgwm2d/knLfvXt3ePXVV8O8efPC0qVLk4/hhjpw4EDH6cOHD3eUTUbB4OBga7dvv/32iE+NGGuerQMpJECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwCwXsLBhki6AY8eOhe9973uj6n3+/PnJIoBzzjkn/MIv/EI444wzQnyKQC9uixcvDs2FCmvXrg1PPvnktExnvM69lue0xD+BoJ5//vnwwAMPhEOHDiW9xAU0f/EXfxHia2kqtpdffjns2LGj9mSPJUuWhI985CPhsssum4oQjEGAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEBgxghY2DBJUzl37twT6nn16tXhC1/4Qli1atUJ9TOVjffu3duxqCGOv3379hCfjNDf3z+V4UzaWLMlz0kDPIGOjx49Gq6++urw9NNPd/QSFwRt2rSpo3yiC+6+++6wcePGrt1u2bIlbNiwoet5JwgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQqAvMjDvN6zmd9KP9+/efcAzxxu0rr7wyeXJDvJG+17fxPhmh1/KeLXmejHl57LHHwmmnnda6qCHGc/rpp096WAcPHhx2UcOkB2AAAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAjNQwMKGSZjUN998c0J7XbZsWXjiiScmtM/J6Ozdd9/t2u3Q0FDXc712YrbkOV3mJS4mWLFiRbjxxhtPekjXXHPNSY9BAAQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgRmmoCFDZMwo6eeeuqE93rdddeF6f7khvPOO69r3v39M+dSmy15dp3MKTxx9913hzPPPDPs2bNnCkdt9YL/6wAAIABJREFUH+rFF1/s+rSI9hZKCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAYjcDMudt8NNme5DrPPPNMOH78eHjnnXdqH4cPHw67du0KW7ZsGTbCiy++eNjzJ/vk/PnzQ8xxYGAgLFq0KPlYvXp1eOONN052aBM6/mzJc0LRxthZXMTT19cXNm7cOMaWk1c9XtdtW7zWbQQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIjF/Awobx24255bJly0J8csG8efNqH/FG+RUrVoQNGzaEoaGhcOutt7b2feDAgbB79+7Wc9OlcNWqVeGFF14I+/fvTz6+//3vh8WLF0+X8CYsjtmS54SBjaGj+JSG+FrptnVbYNCt/kSU33fffR3dLF++PMSP+Lq0ESBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAwfgELG8ZvN2ktH3jggRCfdNC2ff3rX28rVkZgRggMDg52fUpDfDLCa6+9liycmcpkjx49Gm6//faOIX/wgx8kCxs6TiggQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGBMAhY2jIlr6ir//d//fetgbX85vrWiQgI9KNDX19ca9eOPP548AWTJkiUhLn6Yyu33f//3O4Zbu3ZtWLp0qac1dMgoIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDB2AQsbxm42JS0WL14c4l+ob25nnXVWs8gxgRkjMDQ0VMvl1ltvDcePHw/XXnttUd5t8UNRYQJ3Xn755bB9+/aOHr/5zW92lCkgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGB8AnPG10yrkyXw5ptvjjj0vn37wj/8wz+EQ4cOhTPOOCMsW7YsXHXVVSO2a1bYvXt3+P73v1/08/73vz+sWrWqWa12fPTo0fCtb30rxBji2GeffXaIf92+v39q1tAcO3YsfPvb3w7/5//8n/Dss8/W/qL+6tWrw+c+97nwm7/5m+FEb44fT55HjhwJjz32WOH5K7/yK+GSSy6p+cUb+//xH/8xfPnLX67FHxe5RPvPfOYzExJ/HDQ++eBf/uVfwt/+7d+GHTt2hJ/97GdJLHHxTPz4yEc+Em644YbWBTZ50NEh1pszZ2LeSuJ1Eudp4cKF4atf/WqIT2g4mdtFF13UMfyDDz4Y5s2b11GugAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACB8QlMzN3I4xtbqxEE4s3lBw4cGKFW5+mVK1d2tHvppZdCLB/tFm+wv+CCCzqq79q1K6xYsaKjPC+IN4Lv2bMnP0w+33XXXWHTpk21sok+iPF++tOfDtu2beva9dNPPx3WrFmTnH/88cdrTwHo2qjLifHk+YEPfKDDJj6NIF/0ERc93Hjjja0jxusgPjkgf3rAicZ/9913h40bN3YdK57YuXPnsJ554/hUhQceeCA/POHPcTHNdNgeeuih1jBuvvnm1nKFBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiMT8DChvG5TXqreKN+c4FAHHT58uUjjn3++ed3LGw49dRTR2w3ERXiYozmdvrppzeLJvQ4PglhwYIFY+rzuuuuS54MEJ+OMJ5tPHm2tYlPjohPTrjwwgtb57tbbDH+O+64I9xzzz3dqrSWj8eqtaNK4d69eytHM2M3Pvnjlltu6UgmLhCyESBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAwsQL9E9ud3iZK4N/+7d9au7rzzjtby2drYbwBfayLGnKr+ASHuXPn5ocn5fPrr78eTjnllDEtasgDvffee0O3pwrkdaqfT8Sq2k9z/+DBg82inj++6aabOnJYu3btmJ560tGBAgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEWgUsbGhlOfmFq1evbg3iYx/7WGv5bC1csmTJsKnHJ1ysW7cuDAwMDFvvZJ0899xzuw4db6QfKe74VIG4YGE02+/+7u92rXbXXXeF+DSCN954I+zcuTPEsUe7fe5znxtt1Z6oF59A8cgjj3TE+s1vfrOjTAEBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAicuMOfEu9DDRAoMDQ2FD33oQ+HAgQMd3cabz+fMMWU5zBNPPNHqFM/HG/O//vWvh/nz5+fVw+DgYIhPOdi4cWNRNh134sKCSy65pAgtXhP3339/uP3224uy6s7Xvva1cPPNN1eLOvb37dsXtm/f3lEeF3688sortetq8eLF4cknnwzxBv9ly5Z1tFm0aFHYv39/R/lMKbj44os7Utm6dWuYN29eR7kCAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgROXMATG07ccNQ9vP766yHepB5vsG9+xBvFH3roodDf35/8xfxmp/EG9E2bNjWLZ/Xxdddd15r/rbfemtyYX13UECtG2w0bNoTXXnuttd3JLoyLMeL1UV3UEGPq6+sLt912W3jwwQdbQ/zMZz7TWl4t/OxnP1s9LPZ37dpVW9RQnAghLF26NHmCQ7Us7sdFN7t3724Wz4jjbotlor+NAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIHJEbCwYXJcW3u9/PLLk5vrTznllND8OPvss8Mtt9zS2m7dunUz9kby1oRHURifJtC2xacJPPDAA22nirIlS5aE9957rzieDjt33HFHshhjuFjiUxniApfmFhcaHDt2rFlcO962bVvtOB48+uijyaKJjhOVgvj0hnj9Nbduiyya9XrpOC42alssE5+gYSNAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYPIELGyYPNsJ6/kLX/jChPU1Uzr60pe+1JrKv//7v7eWNwvnzJkzbRY3xCdM3HPPPc0QW4//5m/+prX85z//eWt5LIw37Ldtv/d7v9dW3FH253/+5x1lM3Fhwx//8R935Ll69eqOJ2h0VFJAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMAJCVjYcEJ8U9P4ggsuCPEv53d7SsHURDG9RvnKV77SEVB8WsPSpUs7yrsVxMUNb7zxRrfTU1I+MDAw4hMmqoH8xm/8RvVwVPt9fX2t9fr7x//yP+uss1r77NXCffv2hbanWjz55JO9mpK4CRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECPSMwPjvbO6ZFGdGoAcOHAjLli0LTz311MxI6ASyGBoaCtGjuf3pn/5ps2jE47gY4mRu69evH9Pw3RYpjKmTMVZeuHDhGFv0XvXLL7+8I+i77rorzIbcOxJXQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGCKBeZM8Xizerg77rgjfOITnwhHjx7tcHj11VfDP//zP4dvfOMbYc+ePR3n84I1a9aEl156KaxcuTIvmnWfX3/99dacP/nJT7aWT+fCw4cPjym88SxsiAtB2rb33nsvzJs3r+1UrWz79u2143jw5ptvdpT1akFcLNT2mosLG2wECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECEy+gIUNk29cjPBnf/ZnYenSpcVxc+eGG24I99xzT7Lw4bOf/Wy49957m1WS44suuih0u1m9tcEMK4w35LdtixcvbiuecWUDAwNh586do86rv78/LF++vOPm/b/6q78KmzZtGrGf22+/vaPObbfd1lHWiwXxdRQXCzW3Z555JoxnEUmzH8cECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECIws0D9yFTUmSuDdd98dVVfxr+jHBQ7PPfdc1/pPPPFE13Oz9cQ555wzW1MfMe+rr766o87mzZvD3r17O8qrBd0WPlx//fXVaj27v2HDho7Y48KRVatWdZQrIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEBgcgQsbJgc1wnp9bLLLgtbt25t7eumm25qLZ/NhbP5KRYjzfv999/fWmXZsmXhoYce6jh39OjR8MlPfjLExQ/NbdGiRWHFihXN4p47PnjwYOtTUX74wx+eUC4LFiw4ofYaEyBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEJhtAnNmW8K9lu9tt90Wbr/99o6wDxw4EAYHB0N/v7UpHTgKOgTmzJkT1q1bFx555JGOc7fcckuIH2vXrg1nnnlm+MEPfhD27NnTUS8v+MlPfpLv9vTntkUbMaH/+q//Cm+99daIucUnq+zcubOj3gMPPBBWr14d4uKQuMXPcZFSrG8jQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKBTwMKGTpNpVxJvON++fXtHXPGG6fnz53eUtxW8/vrrM+Kv7LfllpdZ6JFLdH6ONm2LGqo1266x6vm4H58gMhOe1hBz+cY3vtFMLzm+6KKLWstHWxgXOwwMDNSqL1++POzevbtW5oAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgVTAn/vvgSvhox/9aGuUhw4dai1vK/zud7/bVjyjyn7+85/PqHwmMpk//MM/POHunnnmmRCfIDJTtrPOOmvKUpnKsaYsKQMRIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQmCABCxsmCHIyu/mf//mf1u7ffvvt1vLZWvjqq6/O1tSHzTs+2aP5tIb4BIHHH388LFq0aNi28eSWLVvC8ePHw6pVq0asqwIBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgTGKjBnrA3Un3qBt956q3XQX/zFX2wtbytcsGBBW3FPlr3vfe9rjfuhhx5y832LzLe+9a2O0u985zth5cqVYf/+/eHIkSPhlVdeCbt37y7qrVixIrz//e8P8+fPL8pm2s5HPvKRsHPnzpmWlnwIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQI9JyAhQ09MGXbtm1rjbK/f/QP3HjsscfCbbfd1tpPW+GGDRvaiqdFWV9fX2sc0emBBx5oPdet8NOf/nS3UzOmfN++fR25xEUL+RYXL1xyySXJR142Gz7Ha+WLX/ziuFOdM2dOOP/888OBAwdqfaxbty585StfCe+8805SfuzYsXDOOefU6jggQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKAUGP2d8WUbe1MocPfdd7eOtnz58tBtYUP8S/TN7emnnw5Hjx5tFrce33fffeHee+9tPTcdCuPChjvuuKM1lOeff761vK0w2nZbNNJWv1fLnn322Y7QP//5z3eUzcaCxYsXh/F+LFy4MFnY0HRbtWpV8qSLvN8lS5aEbotxmm0dEyBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEJiNAhY2TONZf+qpp8LGjRtbI/za177WWh4Lr7rqqtZzn/3sZ1vLq4XxZv/bb7+9WjQt99evX98a1+WXXx6GhoZaz1ULY57dbKv1ZsJ+vNG+uW3evDmsWLEixEUPe/fuDfGpDgcPHgxHjhxJFsDEpwyMxrHZr+MQDh8+jIEAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgTEIWNgwBqwTrXrqqaeOqov9+/eHa665JqxZs6Zr/bab1fPK1157bb5b+xyfwvDEE0/UyvKDeBN7HLNXbvZfuXJlHnrH5wsuuKDrTfmDg4M9lWdHcuMo6HYd7dmzJ1x55ZVh2bJl4dxzzw1nnnlmWLBgQTjttNPC3LlzkyeCxCcNxI+4COLOO+8ML7/88jgimNgm3Z5+EGO3ESBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECDQewJzei/k3o34iiuuCFdffXU4dOhQaxKvvvpqePrpp1vPVQtjveG2+fPnh+XLl4d443pzu+6668LatWvDl770paRO/Ovyjz/+eLjllluaVaf98YMPPtgad8y7v78/PProoyEu8og36cenETz88MM98TSKiYaPi0BuvfXWsG3btnF3HU3jwpj4EbfnnnsuXHbZZePub7iG8QkSDzzwQDj99NM7qsXFC7t27eoojwX5k0banpgQXw833HBDazuFBAgQIECAAAECBAgQIEBgNgr80/Nvzqi0Z1o++eTM1Lzy/HwmQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgkAtY2JBLTMHneHP4idxcHkN85plnwtKlS0eM9jvf+U646KKLWutt3749xI9e326++eZw1113tS7giLndeOONvZ7ihMUfFwr86Ec/Cjt37pyQPi+//PJwxx13hHvuuWdC+qt2cvHFF4cDBw5Ui0a9ny9uaGvwq7/6q8mTJ9rOKSNAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBA4OQJ9J+8oY08VoH4pIZVq1aNqln8K/3xpv/xbvGv3scnHkz37ZVXXjmhEN96662eyPOEkgwheWLFRC1qyGOJT2946qmn8sMJ+Tw4ODjuRQ0jBdD2BIiR2jhPgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMDkC1jYMAnG73vf+ya017jAYGhoaFRPaqgOvGnTpuSv6lfLRtofGBgIx48fD/Pnzw/79u0bqXrH+TfffLOjbKSC8bTJ+5wzZ0545513wqJFi/KiUX2Oeb733nth4cKFXZ/4MFxH44l5PG2Gi2G0544dOxbOPPPM1upvvPFGMt/RIjrGBS2x7LXXXks+nnvuubBu3brWtrFwzZo1ybXZtcIYT/T3T95b0v79+8cYjeoECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECEyFwJypGGS2jRFvzt66dWu4/fbbx5z68uXLwxVXXBF+67d+K/zO7/xOWLJkyZj7qDa45557wvr168PVV1897A38cdwnnngiXHLJJUXz888/v9jPd84666x8t/XzH/zBH4T4l/yr2y/90i9VDzv2x9Om2sm8efNCvGk9xn/TTTcN+xf/2/L8+Mc/HjZu3FjtMoz01/3HE/N42tSCyg4uvvji0Hz6wnDx/uZv/mZbN8lChmgXt3jNxkUicYuLWvItXn8PP/xw+OpXvxrigp0DBw7kp4rPe/bsCStWrCiOT3QnPmlk8+bNJ9pNR/sLL7ywo+xEC9rm4sMf/vCJdqs9AQIECBAgQIAAAQIECBCYcIGr7twz4X3qkAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAhMl0DcUHwVgmxUCR48eDS+//HL4j//4jyLfeLN3XMyQ3+BenMh24uURn+AQt/zG92ad5vHg4GCIH3E75ZRTQl9fX7NKx/F42nR0khUcPHgwvPTSS+GnP/1pUeUDH/hAWLly5YzJc7ReccHH2WefXTjkO9EneoxlO3LkSFiwYEFHk/H01dFJDxeMdi4mKsXf2vB00tX/vXv1RHWpHwIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQInVcATG04q/9QOHhcvxEUM1acyjBRBXJQw2gUNeV/xr//Hj7Fs42nTrf+FCxeGyy67LPnoVqdZ3mt5jtYrPm2huQ0MDIx5UUPso/okh2qfO3bsGFd/1T56eX+0c9HLOYqdAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwGQKjO3u88mMRN8ECEyJwPr16yd0nLVr105ofzojQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGB2CVjYMLvmW7YEwrPPPjsuhRdffLG13emnn95arpAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKjEbCwYTRK6hDoUYHDhw93RP7II4+EvXv3dpQPV3DkyJEwMDDQWuWcc85pLVdIgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACB0QhY2DAaJXUI9KjAFVdc0Rr5smXLwkMPPRSOHj3aej4vHBwcTOotWLAgL6p9fvTRR0NfX1+tzAEBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgTGItA3NDQ0NJYG6hIg0DsCcWHCKaecMmzAy5cvD1dffXW49NJLw5IlS8K+ffvCCy+8EL7zne+EPXv2dG0b2+3evbvreScmR+C3NjyddPx/7149OQPolQABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMAUC8yZ4vEMR4DAFAr09/eHV199NcQnNHTb4uKFbdu2dTvdWr5o0aLw05/+tPWcQgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECIxFoH8sldUlQKD3BJYuXZosbpioyO+6666wf//+EBdN2AgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIHCiAu5MPlFB7Qn0gEBc3DA0NBSee+65MDAwMOaI4xMatmzZEt55552wadOmMbfXgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAt0E5nQ7oZwAgZkncNlll4UXXnghDA4Ohv/93/8NL7/8cnjllVfCa6+9Ft5+++1w6NChJOnzzjsvLF++PHzoQx9KPs+bN2/mYciIAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFpIWBhw7SYBkEQmFqB/v7+sGTJkuRj1apVUzu40QgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFAR6K/s2yVAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQITKmAhQ1Tym0wAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoCpgYUNVwz4BAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAwpQIWNkwpt8EIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBqoCFDVUN+wQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMCUCljYMKXcBiNAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgSqAhY2VDXsEyBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAlMqYGHDlHIbjAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEKgKWNhQ1bBPgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQITKmAhQ1Tym0wAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoCpgYUNVwz4BAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAwpQIWNkwpt8EIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBqoCFDVUN+wQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMCUCvQNDQ0NTemIBiNAgACBcQt88eH/DP/0k9dCX18IYSiEvr6++Ck5iPv5Vu6ldZLKycn8TNqqbDMU+kJ+LrZJe4q1kjrZl4pa/UqluJt/MUnrDBXx5T2VbfMo089F/WKsWD6UjpumWR5ng+RDx5pJ+6Q8ASk6L+pkTnkMwcDZAAAgAElEQVSEeRxDcYyWnMs+08Fq9SuJFv3nMUSBEqGIPG8fhsqc0jHSUGOTNI76eIlBI76y+wjeUj8PKuk0TmJLnUqfyRhZm9hd3rwwyNsXbdIcyjiKIbL5aozX6LTofxxzksSUkqX/Jp1Vxkt2W4xrwcamlTpdco5NymujUj+Z63rO8TqKW3Wea8f5eNnlURgUbdpfK0XYSe/pP+kYlfGS3bHOSZJcpdfKvLfMSzraMK+V5NrIoi2Sy8yaxZWc00sjf89pGFeiiznnxpG6wyCpW4+vuFzz8YZ5rZRxpMFW57HYT/rJX035tdGoX5nnGFLy/lJ4ZMaFR/21mYbXMChpOnJOu6nnXBkqrZ/lXL6ou89JjDe2L5vU48uIy67yBvm1X4A3ckgapm4d85Yk0aif5dyck3S4LKbiGoillRdwZbdWP+aWxTemOUm6b4+vvA4bMQzXpogjvZrLa6v7vMQ6+bdpHfVbhk4nKLsuu81JyRh7qM1pt69D6cWRVK/XTy66+vtXHL12LSZxZDEVJ8prt6N+5UKs5lwEm3Q10rw0jLt87U3yD+X7S3W8ZD8Nu5ZPelDPOV6HRdtGfGl+JXpRr9omuTbS10k6J1n9xDL/z1VljDTwokHaZxps0X8l5zSGRDD5pzrPzfHiqyXd6uPlpR31k/mKpY36eYPi9dqYkyznbLD6e1wyJ519JmMU8ZXXWWGcvYEVBtWYsveHVCm2zYyL+DrHy2okIRb1R5qTtJusTfKpbF+JL42jYlbEkZ6p5lDOSZlz7DSpU+kzlhXvcVmixUuuDMUeAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCY9gIWNkz7KRIgAQIESoF4k+Nvb/x/ZYE9AgQIECBAgAABAgQItAgUCzOyBRT5wopYtVhEUVkMk5ZXOyqXeRT184UjjUUU8bBt0UVt8Uu3hSaxbcvilRhJ0m8lpCKnWpt0sUgWUrEOKc2nJYcs51r9bIzqAqBqzqNZaJKPly7nyT1iaWUxS+KUDZaiZVkONydpDqlF3I9bS59ZQrlR2n1WvzHPRfusTYV/xAVAaRxZGPm85wseG4ueiu7LaSj7L9rGdLKLI+u2tjinfqq4dpMFPZXAq22a85jGkZllQdXqJwfNlcgN4zLlIofUopyTWKV63VSv60qoaZ3GAqViTjo5ivGaCyzzsco40uTy8qLPSs7ZbpJNnnYZd6V9wtEwqKSaX2d527RluYAxLU+GSf5J6mc5lysHu89J0b6YlvIiKvJrXNcxnzy/0r6RQxlSnKz66y9p3Kif5Zxeoo36SV+dix6L/Fqv3cy4uCDqlSohlfNeua7iz4SK/JPyLKGkm3p8bXNSuGbN8tdKrFv2231eYp2xLL5N6ufvD5Wcy7Fq09A4yL82ZGYJTgw8ja/jcipyGGZOYp0s99QiPyqv3dSirJTE2uX1mkSW/dORUxpqbR7La6PLPCbxpfOYxlGJr3KBFxRZzsnXneIaSAcu4qlfYslsFO2LNkkSlWsgdUpL82ujUifZ7cyhnJM0h5px49qtTkR+HdbqV66bdOTGeLFytqW5ZtEWTo36JWUxJ7FF4RSvq0pQhVFep9t7YjZsDKXaJjnoct0kYVfmpYwj7ayMo5FD8Y6Vx53V75JzkU4WYzW+wqy4BuIrqzJeJb40t8qcFouR6zknfbbkXMB067MRQzle+gWxnKP6eNWrtKyT5dDIOR52i69oW4mvqF+5DpN5qxrlE1lAN+alKC9d037LiUzHToMt40jrp6X1nLu/VvILvFE/uTbynsr40jjyL5plfGmO/iVAgAABAgQIECBAgAABAgQIECBw8gUsbDj5cyACAgQIjEkg/0Vh/P1I8kvt7Bcl+S+X4y+Miv3kd0DJryuyMfJfZjTrxN/wpFXStpVfo8UBs99+lf1m7Ys2RfNs7L6koKN+S6b5ePFUsp/0WcYXD5s556MV/ee/natULM9V2udjJOmWf6k5HbsMLo0jTS7up3udOect0rHKnGv1s0q5fNkm3UvyS3+1nBQUcVf+knQ8kUxD1rgZX95T0TbtNKuduebXSfZLuWiY1x8uhmTsRps0v8w1O0j7Sg/yfqu/yE36yRGya7c5j/Gqy28Eq9XP561yHaYjlTmk6VWO8+smnZbyusz7igN0vFZiYRpVGUd7n7FezDN/pSQ5J0G11C86rb4WK/NSeKQV037jfnljTrKfXN+ZcWVOyhfICcxJMlYZXz6HSX61+LIx0vCy+UpjKuPIDJrFhX1fdmmUF0Q+XpzH4mXcNK7kXNRP4iivmzhks/1w71+t9WMQtZzTfLJ0iijKOYl79ZyrlZJY8/eoikHePj3V/bpJc21iljmn/cR/0y29dlvqV95EOozildzIOfZWODdeK0V+RZt0vKJ+bJvFE89Uc0j2k+qdOWfFnfVjX40YKulk85UN2BwviyR5f6kknuymYXeMN+FzkgVbe79Iwh1mHis3/pSuFbPGayW98NOEur5/jXFOCtjCqcW4uAZi7e7x1a6B5KahtK/KlKTzkL1WmjmX10Z7DLE0HyPWLdq3XDd5D9GpdU6y+Ur7zGsnnXb//1CsVpmTMoYUrzonab/5KyR9raS18rg72xT5JI2zL1RFnln9HLOSczyTF6dNO9/nY+Cx/4y+fD+LDWL77HOyn3SWqiUxJUNX5r06XnFtVOonfQ1z3bfOSZZDmmYxz7GrNL9h/p+aVapMadm+iC+tVDNO4kz/ScvTwbvlXCAVfVbqJ92Xx+lexaxy3cSq1fGq+rV5TBIq+0yGyF9/aXFt3tNM/EuAAAECBAgQIECAAIHuAsX3hNlik/z72Oaii7yHon5SEL8RSb97LOrH79nK4vZFRZWffaT9Zgst8m9Es+9v4rliIUgWX61+elD7t6ift036LBdyxMO2+Mqx0m9wYz9FOJV4YmHVIB8v6Tf5bjX2VI6X9Jt+F5vEWfZbz7mtz3SsPI5mn0l3RZ/5PKTfMcfiNPo0vvQ4/1lIPIrjlfmV36DW6udBpcklY6VtswnuMieN6uUctsxJHkMeUx5U7lqMl1Ss4+fh5U55RnkO1Z//FP3HnSKOdPRYP90b3ZzEuh3xxU4b13XNuHENpFGUP5/KY6q9/rKc83zSOmnLJOAEoMyhrc9oUuRX56vnULl2qxd4ZYh6/Qw//iyjW3xtRsPNSZJfll7yKRsjz6G8NspKyRhDqVoZRyWmlpwL40rOZdv6+0P1zSIdK47dYh5jLRZmN+LLTpRjVOYkXktl9bpxcaaeRBpHlxjSyzCJsRyv8p6VdJW9fuO4uXG3eUziS+vHEcs+M+M0jKKbtMusfjFWLK3MSSPnJP0coWjTkl/mkcaRtEqbZvYdY+Tvcd36bORccFdyjgNUc06OizgaOdVYy4PYPv3ZXkv92GEjvhKz+f6QpJv8k8TU7brP5iSJNXfND7IfMlZzKvaTOMoxatd+gdPIIauezkk95/Rl0qjfZU7S8LL2hUekqbRvxJfGnV0n8WejSSyV+sncpb5l/3EvrZPU79ZnJYZsgpLe0yFaxsjOxq+xxftL/trKc0gDLKc3tkmu3SyHZv14vhJfrNXMOR22M57qz5KLbmP7ZB6b4yUnkrHSkBrzmMRRjpHGkY6c1G/tM71205HSNPMWSQ4t12GRX9KoHC8ZI7+Os3npMG68lps5d9QfaU7ioN36zJJKpi5LqpiXxnWTlueZl5+L+vmcNnJOLZrXbjpw0WclvqJ+Hk9lTmJRdbzyK07DuAyvqJ/2m79o6/NYqW6XAAECBAhMmoCFDZNGq2MCBAgQIECAAAECBAgQIECAwMkRKBZKxN8/xF92JGFUFlaUvx8pAsx/8ZX+Civ59UVyLu0r7pa/oItHtfrxIPvNUa1+pVJSJRutiC+JI/3lTNJ/Xj+rl3+q1k/Gzn5lmbcpfsdVhl1bLFLElPzmKR+vzCECVcco6jd+GVQNL6nTyDn5JWZeKQmqYV6JLwVMIy/GqyxQSvLMQh12TiqwsZ/8ZqU0vthLSwxpcXZt5HoVg8Kj3j6NI5alWxp3lsNEz0lxbWT9Z65Jfl3ii1GVs5vmk7bODNKD4tpN6if9Fiuis8wqZslYWXFy3aeTGLvKfznaapyNlbSsBJXOS3oy9Ys1yviSfpv143XYknM+RKV653WcVEr7L+on10x6VI0hRpLGF4erGCTlmUERR9k+3Wt/f0j6TGYlGz2bx2rO6bhZ/3kMMYJirHiuHk88WcYe406Ikn/S8jK+tOd6fNULJc+5OUYeahlHo89uMRTXRpZzJack12zwVuOCKb3OkvpZcq31U5qOeU+7qeec51P2mdeqvPaL2GOt1DXdS+vkv0Qv7Svz0Hit1N7jCvBK/WSsvPd8sDSmbnOSz1H21tv1tVyNr1qp62tl1HMS401zSCJt5JyOm+ZQvmaTd63yem25bnKF9D2lUT+/9rNum/OY1O72WmnE121O4vhVsxhHNlyVL63T+LqXxF5erh3XYnK+kXNxOSTXQNm4FkNx3devwyTWpNP0n5p51iafo7xaYVY4tRhXgirqZ/GltRtGxVj1+GI86bWRCnbkFIOqzEusVeRQxJdWKtumX9vKOWmYpQNW5jAJPE2/6LMRT2VO0jOV12YlvthJEV/h0RJfGVKtfnIBZYHXXJOD+te26NzMOU2iHkNaVg5Ytml/z4vDJ3U6rt3KeFnOWai1HLp+rU+nMgmnZlRcG2lveXxFfoVHSw7ZvJRxZALd5jG52mI/6dZh3Mi5iCFWb8xz3ofPBAgQIECAAAECBAgQ6CZQLJQoFprEmiMvlEj7K77TSQ7znzEl7dPvpLPytHbyHVP8nib7RqdWP/teJ34rn1RJmxQLM9LycryybVaxWT9+i1R0VOaTfreVHWffeuVDxy6qbfLfjaTl2QCZU/pdfVa/+N46jy/NIWuR9ZkOlsed/JymiK+lfkw4iy+No94+GuZ9VeOLtdKfeTTqJz8XqsdXdj/ynLTG0Oizet0k30aXw2WxZjEV10aaQxlHApmwpbk1cmh0WszbOOYkMcsnqACsjJfsthjXgo0NK3WyazeWnn3mqeHOGy+qjmCfAIEQwhwKBAgQIECAAAECBAgQIECAAAECM0ug/oPq8qfC1fLhMy7bJHc+FZWr5UWhHQIECBAgQIAAAQIEelQguVco+29+XIyR3tySLypJ7tipLzzJb9BI8o0HaeN8IUc8TvaLPlOYeJiWN+sX9yslXbXGEMcoFnnE/srFKUm/Ffs0jmyM8g6fIoc0jiLsrLwRU7eFJtmNSEkweT7J2M0oyvji6SpZR37J0I36+aQUwdZzTi3KpKs5l6M1+yxzTmKKN9NkXSTts7t90r4q4xWVWsYbz5wkNxmV/Rfdl5dSbU5izTS+GG9LTmlXtTZ5Dkn9in7CmqWRLyjM+0/jyPrPgqrVH2lOkjg640u6KpzSjvP4kuu4El9tN3FqqZ8HFU/lMeVGSW7DLPRKBkj7zPPOr4LqQq78BsK0TnndpHHXY4o/Yyjz6XwtF/3ni//iHFYSzdMp4qlch+lIlfGS3ZbxinXq+SutUqe89y7RibEW73FFHJX6ddZO424xRKY01CpfeV0W10AMIx0vq15EURhkr8zSqZ5EZdrL/ivXQOeclC+uWp/pgIlLDL51HmO/2XUT4y3rZPW75JwYt+ScDFZPJ+lzpDmpvlbSONKw0xTKOwOb8XWfk3TCyvpJokWnec5F/8mZMufhYijbpDhxjDSOLsaFUxNzmNfKBM1JGWv6Os9fj2l+2XVTxBdrN3JIXNJXeWpZ5pxexo36+dedos9K/aT7ev3ai6PluklHTq/RtKd6+26vleRFmjRoqZ+mWbvWqy/q/F0mVqvmnBxXbtotr63u85jG0TCoGldyjrWq41Vfy+VY6f8A0h4b9SNGlnMZeyzKDLJG+TVQ1qn//yuNI57Nr5nK+0vROM25jCOrn+dQeZ+vdNSxm7dqzmPxfpGPN8z7V1WkdOqe8/jmJEZad4rH5Xh5JunnkeaxMC7mpMV4HP9PjddMPifN+Nqu6zSO8rrJ88k/x2y67TcyrhxWR0p6GOZc5ZRdAjNc4P/7hdNmeIbSIzA+AQsbxuemFQECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBHpaIL/xMyZRXQhd3S/u2O3ItLxFKrmpqzhfLS8K7RAgQIAAAQIECBAg0KMC+XqSuEoiLmwYeaFJuTAjXWgSE68v/GguXonn8+8kksUTLYth0vIUMbav1Y9HxQKqzvGq9OnijLR12WcZXzzTzDkfLW2bfANVBpLsle3TOMoR8zbJoqLK6q1ijHzBSCXnNLqszyzRjvqVnGv1s6E7lpRkBUl+2WK5WDWPL+ZYLqBKDbKh0zqV+NIh6jlXUsv6TFuXfZb1h4shianoLG1TxpGuKSrjzsbIcWKM+f4o5nHccxIDSIYuc0pjSsuT/JI4OuPLvefN7Y9NbAQINAT6hvJXSeOEQwIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDAZAtY8jPZwvonQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEugpY2NCVxgkCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEBgsgUsbJhsYf0TIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECXQUsbOhK4wQBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAw2QIWNky2sP4JECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBrgIWNnSlcYIAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCYbAELGyZbWP8ECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAVwELG7rSOEGAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAhMtoCFDZMtrH8CBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgq4CFDV1pnCBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQmW8DChskW1j8BAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECDQVcDChq40ThAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKTLWBhw2QL658AAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBDoKmBhQ1caJwgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIHJFrCwYbKF9U+AAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAh0FbCwoSuNEwQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMBkC1jYMNnC+idAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgS6CljY0JXGCQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGCyBSxsmGxh/RMgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJdBSxs6ErjBAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDDZAhY2TLaw/gkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGuAnO6nnGCAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECs0Bg7969Ye7cuUmmS5YsmQUZS5HA9BKwsGF6zYdoCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCYQoG4qGHZsmXFiK+++mpYunRpcWyHAIHJF+if/CGMQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgd4QePfdd3sjUFESmEECFjbMoMmUCgECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQ6DUBCxt6bcbES4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEZpCAhQ0zaDKlQoAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEek1gTq8FLF4CBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBGaHwN69eyc10blz54Yf//jHkzqGzgkQGFnAwoaRjdQgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGCKBZ566qmwZs2aKR7VcAQInAyB/pMxqDEJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAwnMBLL7003GnnCBCYQQIWNsygyZQKAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgZkicPjw4ZmSijwIEBhBwMKGEYCcJkCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEBg6gWuv/76qR/UiAQInBQBCxtOCrtBCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAYTmDFihVh7dq1tSrxeGhoKBw/fjwMDg6e8Efsa+fOnbUxHBAgMPUCfUPx1WgjQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDANBM4duxYmDt3bi2qN954IyxevLhWdiIHe/fuDcuWLSu62LVrV4iLKmwECEydgCc2TJ21kQgQIEBgHALxP4z79u1LPsbRXBMCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQ6GGBOXPmhB07dtQy+PVf//XasQMCBHpfwMKG3p9DGRAgQGDGCuSrYM8999wQP+KxjQABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgRml8BVV10VBgYGiqR37twZnn322eLYDgECvS9gYUPvz6EMCBAgMGsE3n333VmTq0QJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoBT44Q9/WB6EEK688sowNDRUK3NAgEDvCljY0LtzJ3ICBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECs0Jg/vz54cEHH6zlev/999eOx3vQ/KO7zePx9qsdAQKjF7CwYfRWahIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgcJIEbr755jAwMDDho5933nlh0aJFSb/x84UXXjjhY+iQAIHhBeYMf9pZAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQITA+BF154IQwNDSXB9PX1TUhQ8WkQ+/fvn5C+dEKAwPgELGwYn5tWBAgQmPUCe/funVSDuXPnhh//+MeTOobOCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKD3BCZqQUPvZS5iAjNXwMKGmTu3MiNAgMCkCTz11FNhzZo1k9a/jgkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBGaPQP/sSVWmBAgQIDBRAi+99NJEdaUfAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBWS5gYcMsvwCkT4AAgfEIHD58eDzNtCFAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECDQIWBhQweJAgIECBAYSeD6668fqYrzBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEBg2gkMDQ2F+GEjQGB6CVjYML3mQzQECBDoCYEVK1aEtWvX1mKNx/E/e8ePHw+Dg4Mn/BH72rlzZ20MBwQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYKwCzz//fLj00ktDX19f6O/vTz7i/kc/+tEQz9kIEDj5An1Dlhyd/FkQAQECBHpQ4NixY2Hu3Lm1yN94442wePHiWtmJHOzduzcsW7as6GLXrl0hLoHtZQ0AACAASURBVKqwESBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMDsEzh48GD4u7/7u/Dss8+GeH/ZmWeeGT784Q+Hj3/842HlypWtIHHxwtNPP916rlr41ltvhYULF1aL7BMgMIUCFjZMIbahCBAgMNMEnnrqqbBmzZoirYGBgfDCCy8Uxye6Y2HDiQpqT4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgd4XiH/H/dprrw3bt28fNpmdO3eGSy65pKgTn9IQy0a7TfQf9x3tuOoRIBBCPwQCBAgQIDBegauuuirExQz5Fv8DGFfC2ggQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwEQJnH322SMuaohjxfvZ8nvYnnjiiTEtaojt4zg2AgROjoCFDSfH3agECBCYMQI//OEPa7lceeWVIa6OtREgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgRMV2LRpUzhw4MCou4n3sO3fvz9cd911rW3i4ofVq1e3nouFDz30UNdzThAgMHkCFjZMnq2eCRAgMCsE5s+fHx588MFarvfff3/teLwH7777bq1p87h20gEBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIzCiBwcHBsHnz5jHn1PbkhS1btoTY3wsvvBC+//3vJ3/Ad8eOHR1933LLLR1lCggQmHwBCxsm39gIBAgQmPECN998c/IIr4lO9LzzzguLFi1Kuo2fL7zwwokeQn8ECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgME0Ftm/f3hFZvJfstddeSxYmDA0Nhffeey9s3bq1qJffc1YUhJD88d4NGzaEvr6+anG46qqrwq5du2pl8WD37t0dZQoIEJhcgb6h+Iq2ESBAgACBCRDIv6Q0//M3AV3rggABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgRmmcB9990Xbr/99iLruGhh//79xXF1Jy5GuOCCC6pFyf7y5ctHXKiwfv36sG3btqLt448/Hq699tri2A4BApMv4IkNk29sBAIECMwagbigwaKGWTPdEiVAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMCkChw+fLjW/09+8pPacfVgxYoVtSc35Oe+9rWv5btdP//lX/5l7dx//ud/1o4dECAw+QKe2DD5xkYgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGCMAnGxwp49e4pWg4ODw/7x3Xj+lFNOKerHnePHj4f+/uH/FvzQ0FCtzpYtW8KGDRtq/TggQGByBYZ/lU7u2HonQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAq8AHP/jBWvk777xTO24exAUMAwMDzWLHBAj0gICFDT0wSUIkQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgMNsEPvaxj9VSPu2002rHbQeLFi0qipcvX157EkNxwg4BAtNOwMKGaTclAiJAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYMmSJTWE//7v/64dtx3ccMMNRfFZZ51V7A+3c+jQoeFOO0eAwBQIWNgwBciGIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEBgbAJr1qypNVi/fn3teKIOvv3tb9e6uuKKK2rHDggQmHwBCxsm39gIBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiMUWDx4sW1Ftu3bw8HDx6slTUPDh8+XBT97Gc/K/aH29m4cWPt9MDAQO3YAQECky9gYcPkGxuBAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFxCDz66KO1Vtdcc03tuHlwyy23hHXr1iUfO3bsaJ7uON63b1/Ys2dPrXzhwoW1YwcECEy+QN/Q0NDQ5A9jBAIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECIxdoK+vr9Zo165dYcWKFbWy8R5ceumlYefOnUXzLVu2hA0bNhTHdggQmBoBCxumxtkoBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiMQ+DIkSPht3/7t5MnK7z55pvhpz/9aVi8ePE4eqo32bt3b1i2bFmt8L333gtz5syplTkgQGDyBSxsmHxjIxAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgMM0EBgcHw+c///lw6NChcMYZZ4TbbrstLFmyZJpFKRwCs0PAwobZMc+yJECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAEC01Kgf1pGJSgCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEBgVghY2DArplmSBAgQmFqBvXv3hrvvvjvs3r17agc2GgECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQM8JWNjQc1MmYAIECEx/gTvvvDNs3LgxXHDBBaGvry9s2rQp7N+/f/oHLkICBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIEpF+gbGhoamvJRDUiAAAECM1pgxYoVYc+ePR05Llq0KHz5y18On/jEJ8K8efM6zisgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCYfQKe2DD75lzGBAgQmHSBD37wg61jHDhwINxyyy3htNNOC5deeml49tlnw+DgYGtdhQQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABArNDwBMbZsc8y5IAAQJTKvDyyy+Hiy66aNRjrl27NnzpS18KK1euHHUbFQkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBGaGgCc2zIx5lAUBAgSmlUBcoDA0NBTeeOONsGXLlhFj2759e7IQoq+vL9x5551h3759I7ZRgQABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYGYIeGLDzJhHWRAgQGDaC8TFCvfdd1/YvHnzqGPdunVr+NSnPhXmz58/6jYqEiBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQI9JaAhQ29NV+iJUCAwIwQiIscvvjFL4Z77713VPksX748/PVf/3X42Mc+FubMmTOqNioRIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAj0hoCFDb0xT6IkQIDAjBXYu3dv2LRpU9i2bduocly9enWIT3K45JJLRlVfJQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgektYGHD9J4f0REgQGBWCezevTs8+OCDYfPmzaPK+9Zbb00WRSxdunRU9VUiQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCYfgL90y8kEREgQIDAbBVYvnx5uOaaa0adfnzKw7Jly0JfX1+47777Rt1ORQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBDofYEXX3wxrFixIqxfvz5ceuml4fnnn+/9pGRAYJYKeGLDLJ14aRMgQGC6CAwNDYUf//jH4Y477ghPP/30CYW1a9eu5D+pJ9SJxgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECDQEwJxMcPOnTuLWLdu3Rpuu+224tgOAQK9I+CJDb0zVyIlQIDAjBLYvXt3skq2v78/XH755SMuahgYGAiPPvpoWLRo0YxykAwBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIjF0g/lHd6qKG2MNNN9009o60IEBgWghY2DAtpkEQBAgQmB0C+/fvD5s2bQp9fX3hggsuCNu2bRsx8S1btoS33norvPDCC+GGG24IsY/XXnst3HrrrSO2VYEAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEZqZAXNjQ3M4444xmkWMCBHpEwMKGHpkoYRIgQKBXBY4cORLuu+++sHjx4nD22WeHzZs3j5jKunXrwq5du0L8j+eGDRvCwoULa22WLFkSHnjggXD8+PGwY8eOsHz58uT8qaeeWqvngAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgRmpkB/f39YtGhRLblDhw7Vjh0QINA7An1DbcuVeid+kRIgQIDANBSIX1qefPLJ8Cd/8idhz549o4pwYGAg3H///eHXfu3XQvwP51i3wcHBcbUb6zjqEyBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMD0EFi/fn3Ytm1bEUz8I7m7d+8uju0QINA7AhY29M5ciZQAAQI9I7Bp06ZRPZkhJrR169bwqU99KsyfP79n8hMoAQIECBAgQIAAAQIECLQLXHrppeFnP/tZ+8kQwoEDB0JcmN7X19e1jhMECBCYrgIHDx4MZ555ZsdfgKvGe/311ydPGq2W2SdAgAABAgQIECBAgAABAgQIECBAYPIEjh07FubOnVsbIP6R3X/913/1+4iaigMC01/AwobpP0ciJECAQM8JxBtZdu7c2TXudevWhXvuuScsXbq0ax0nCBAgQIAAAQIECBAgQKC3BBYvXpwsXBgu6pdeeimsXLlyuCrOESBAYFoLPPbYY+HGG28cNsb4s6+HH3542DpOEiBAgAABAgQIECBAgAABAgQIECAwcQL5HyVp9vjqq6+6R62J4pjANBaYM41jExoBAgQIzCCBuAr2/vvvD1dccYWVsDNoXqVCgAABAgQIECBAgACBKDCaRQ27du0KK1asAEaAAIGeFrjhhhuSJ49ed911XfN45JFHknMWN3QlcoIAAQIECBAgQIAAAQIECBAgQIDAhAnEJzbEhQ07duwIa9asqfW7bNmysHbt2jEvbjh06FD46le/GubNm1frzwEBApMr4IkNk+urdwIECMxKgbvvvjts3LgxyX3r1q3hU5/6VPIL31mJIWkCBAgQIECAAAECBAjMcAGLGmb4BEuPAIFWgSeeeCIMt7ghNvLkhlY6hQQIECBAgAABAgQIECBAgAABAgQmVODOO+8M995774T2GTvzFOoJJ9UhgREFLGwYkUgFAgQIEBiPQFwJO2eOBwONx04bAgQIECBAgAABAgQI9IqARQ29MlPiJEBgMgQsbpgMVX0SIECAAAECBAgQIECAAAECBAgQGJtAfFr0nj17xtZoFLU9iXoUSKoQmGABd5xOMKjuCBAgQCCEF198MVx77bXh6quvDj/60Y/CV77ylXDZZZehIUCAAAECBAgQIECAAIEZJGBRw/SfzPhHB773ve9NWaCXXnppWLJkSW28559/Pnz3u98Nb7/9dlJ+5ZVXhquuuqpWp9vB0NBQ+MEPfhCOHDlSq3L++eeH5cuXT9kjwHfv3h1eeeWVWgzz589PftYx2seQT/Rc/PIv//KYH51eS8DBhAjEn389/vjjwz654ZFHHknGevjhhydkTJ0QIECAAAECBAgQIECAAAECBAgQIFAXuOKKKyZlYcO7775bH8gRAQKTLuCJDZNObAACBAjMPoF4I8POnTuLxLdu3Rpuu+224tgOAQIECBAgQIAAAQIECPS2gEUNvTF/69evD9u2bZvSYONihHzbt29fOPfcc/PD4vNoH9890nU2FT9vGOkvfR0+fDjERQ4jbX19fSNVGfP5wcHBMBn9jjkQDYInN7gICBAgQIAAAQIECBAgQIAAAQIECJw8gf379yd/gGQ0P6sdbZTxD+780R/9Uejv7x9tE/UIEJgAAQsbJgBRFwQIECBQCsQbGJr/oXvrrbfCwoULy0r2CBAgQIAAAQIECBAgQKBnBUa62Twm5vHM02N6m394YCqiqt5sv3fv3rBs2bKOYUdzfcRfGi1YsKCjbbNgNH0124z2eNOmTWHz5s3DVh/N4or4S7Wzzz572H7Gc/L48eMdP4P5/9u7/9ioz/tw4I+NY9ckDjYdSWsm7FTUTMsw2cqUiUSsrEDXkbBVKkkhaomawaqBJm0QuqqTcCZl0mg8VftCtga2kGwlIo3EBEFIJVUCSqZkpVLj7AfxpNn+AzcNWWwgCpg4vq8+nnz44zvbZ9/nzj7f6yNZ93mez/O8n+d5nU0ud/f+PNOJo08yApIbknEUhQABAgQIECBAgAABAgQIECBAgAABAgTKV0AqUfk+91ZOgACBggiMvjPjyAC33HLLyKlHAgQIECBAgAABAgQIEChhAUkNpfXkXbp0qbQmPGq2v/jFL0aVxj/dunXr+BfzuBIlaEyW1BCFj3ZsmOwo5edhsrW5fkPg/vvvH74r3I2azLPnnnsubNmyJfOCGgIECBAgQIAAAQIECBAgQIAAAQIECBAgQCBIbPBLQIAAAQKJCkS7NdTX18difvDBB7GyAgECBAgQIECAAAECBAiUnoCkhtJ7zr7yla8UfdIVFRWJjFldXZ1TnLNnz4aBgYGc2k6l0cmTJ6fSfMK2ua5lwiBZLo7dMTNLE1VFFpDcUGRwwxEgQIAAAQIECBAgQIAAAQIECBAgQIDAnBKomlOrsRgCBAgQmBUCmzZtCgcPHkzPZfny5aG7uztddkKAAAECBAgQIECAAAECpSUgqaG0nq+R2X73u98NO3fuDLl8sf5///d/Q2tr60jX9OPhw4fD7/3e74WPPvooXZft5Pr16+HTn/50tksFrzt06FDYsWNHouN8/etfzxovuplDf39/1mtTrTx+/HhYu3ZtuHbt2lS7hrq6uin30aE4AiPJDRs3bhx3wGjnhug4cuTIuG1cIECAAAECBAgQIECAAAECBAgQIECAAAEC5SZQkUqlUuW2aOslQIAAgcIKDA4Ohptuuik2SPTliJ/97GchqTs3xoIrECBAgAABAgQIECBAgEDBBCQ1FIx21gXO9v/sFy5cCI2NjdOaa29vb1i8eHFG366urtDc3JxRP7pivL6j24w+T/Jt7ujmDHfcccfo8OOe79u3Lzz66KPjXo8ujLeWfGwnHNDFWSFw4sSJMFFyQzTJzZs3S26YFc+WSRAgQIAAAQIECBAgQIAAAQIECMxVgaGhoeFdf6Pvs0VHbW1tqKpyT/i5+nxbV+kLVJb+EqyAAAECBGabQPTi7/Lly7FpdXR0hMrKyuEP82MXFAgQIECAAAECBAgQIEBg1gpIapi1T03iExsvMSDaiWE2HdEuB9mOzs7ObNXTqot2uRh7RAkMGzZsGFudV3m22ea1GJ0zBEZ2bsi4MKoi2rlhy5Yto2qcEiBAgAABAgQIECBAgAABAgQIECCQr0BfX1/YvXt3iD7jmDdvXpg/f3649dZbh3+im/UODAxkHSJ6n/mtt94KFy9ezHpdJQEChReQdlR4YyMQIECg7ASiDNcrV66E06dPh3Xr1sXWH92pMfoiwFTv9vjBBx+Ep59+OtTU1MTiKRAgQIAAAQIECBAgQIBAYQQkNRTGVdT8BNavX581wLZt28KZM2eyXptKZfSB1smTJzO6RMkOL774Yka9CgITCYwkN0y0c0OU3BAdR44cmSiUawQIECBAgAABAgQIECBAgAABAgQI5CCwffv2cPDgwQlb9vT0hJaWllibaCffZcuWpety2Xk43dgJAQKJCUhsSIxSIAIECBAYEfjzP//z0N7ePlLMeMz2BYGMRlkq2traMl5UZmmmigABAgQIECBAgAABAgTyFJDUkCeg7gUTiG54EO2esGfPntgYZ8+eHb7LVr43RPjbv/3bWNyo0NraOrw9eX9/f8Y1FQQmE5DcMJmQ6wQIECBAgAABAgQIECBAgAABAgSSEcjls41opOrq6owBb7/99lidm93EOBQIFE2gsmgjGYgAAQIEykbghRdeKMhas72oLMhAghIgQIAAAQIECBAgQKCMBXJ549+disr4F2SGl55KpcI3v/nNrLM4dOhQ1vqpVI5NmIj6Pvnkk1MJoS2BDIGR5IaMC6Mqop0btmzZMqrGKQECBAgQIECAAAECBAgQIECAAAECuQrs3r075HNzmtra2rBhw4b0cNGNe6P3ox0ECBRXQGJDcb2NRoAAgbIQWLVqVUHWef369YLEFZQAAQIECBAgQIAAAQIE/k9AUoPfhNkuEH2QVFdXN7yLwti5RnfQyuc4d+5c1u733HNP1nqVBKYiILlhKlraEiBAgAABAgQIECBAgAABAgQIEMhd4MqVK6G9vT2jw9GjR8O1a9eGExSinXknO9ra2mJN3nvvvVhZgQCBwgtUFX4IIxAgQIBAuQkcOHAgfPGLXwxRJmtSx9WrV8PSpUuTCicOAQIECBAgQIAAAQIECIwRkNQwBkRxVgtEuyjce++9GXPs7OwMLS0tGfW5VHzlK1/JaLZv376MOhUEpiswktywcePGcUNEOzdEx5EjR8Zt4wIBAgQIECBAgAABAgQIECBAgAABAjcExiY1rF69Opw5c+ZGgxzP7rrrrljL119/PUTv6TkIECiegMSG4lkbiQABAmUjEH0ZZuvWrWWzXgslQIAAAQIECBAgQIBAqQvkktRw+vTp0NTUFAYHB2fFcisrK0P04yhPgfF2i9y2bdu0PrDq6+sLPT09GZj57gKREVDFjAjMln+3osXfd999Ye/eveGxxx4b10Jyw7g0LhAgQIAAAQIECBAgQIAAAQIECBDIEDh27Fis7pVXXomVcy1UVVWF+vr60N/fP9zl/PnzEhtyxdOOQEICEhsSghSGAAECBAgQIECAAAECBAgQIECAQCkK5JLUEK1r3bp1s255H3/8seSGWfesFGdCFRUVIUpiOHjwYGzAs2fPhoGBgVBTUxOrn6zwrW99K6NJdFevJHejzBhARVEEhoaGwk033VSUsZIcRHJDkppiESBAgAABAgQIECBAgAABAgQIzFWBVCoVOjo60suLduGN3j+e7rFkyZJ0YsN0Y+hHgMD0BdzSbPp2ehIgQIAAAQIECBAgQIAAAQIECBAoaYFckxpKepEmP2cFHn/88axrO3ToUNb68SqjL76PTZCI2u7fv3+8LonUV1dXJxJHkIkF8vkQc+LIhb8aJTds2bKl8AMZgQABAgQIECBAgAABAgQIECBAgMAcEVizZs0cWYllEChPATs2lOfzbtUECBAgQIAAAQIECBAgQIAAAQJlLiCpocx/AebA8hctWhTbFnxkSTt37gw7duwYKU76+MILL2Rts3z58qz1SVX+4Ac/CJs2bQrXr1/PKWS0E8XSpUvtIpGT1txpFCU3XL58Obz44otzZ1FWQoAAAQIECBAgQIAAAQIECBAgQCAhgWjHhqSOsbs/JBVXHAIEcheQ2JC7lZYECBAgQIAAAQIECBAgQIAAAQIECBAgMIsEnn322bBx48aMGXV2doaWlpaM+mwVDz74YEZ1oXdriAbcs2fP8E/G4JNUJPlB3SRDuTxLBK5cuTJLZmIaBAgQIECAAAECBAgQIECAAAECBGaXQGVlZWxCL7/8cli5cmWsLteC915zldKOQOEE4n/RhRtHZAIECBAoc4Hohd/Vq1dD9EFs9DjVHx/glvkvkOUTIECAAAECBAgQIJC4wPvvvz98t/vEAwtIoIgCX/rSl7KOtm3btqz1Yyu7u7vHVg2X//AP/zBr/WyoHBoamg3TMIciCaxevTqcOXOmSKMZhgABAgQIECBAgAABAgQIECBAgEDpCUTvoY0c0Q1lpvseatR39LFq1arRRecECBRBQGJDEZANQYAAgXIWeP7550Nzc3OIsmPnz58fbr311uHH6HwqP1G/3t7ecqa0dgIECBAgQIAAAQIECCQqUFFRESQ3JEoq2AwIVFVVhc2bN2eMfPbs2TAwMJBRP7Zi69atY6vChg0bQk1NTUa9itIUKOW7rElqKM3fObMmQIAAAQIECBAgQIAAAQIECBAorsA3vvGN2IBr1qyJlXMpRLsAt7e3x5q2trbGygoECBReoKrwQxiBAAECBMpRYHBwMCxatCj09/cntvzr168nFksgAgQIECBAgAABAgQIEAhhJLlh4cKFk/7/2+nTp8Pv/M7vDH9ZfOzWzsW2jO62FM1hpudR7HUbL7vAX/3VX4Xnnnsu4+KhQ4fCjh07MupHKqLdJKMEiLHH/v37x1bNmnJ9fb3f+yk+G9G/E9euXRu+S9tM/5sR/dsVJc385V/+ZXjssccmXImkhgl5XCRAgAABAgQIECBAgAABAgQIECCQFnjooYfCww8/nC5H7/s2NDSEKFkh+v5adETvrY4c1dXVI6fD7xv+3d/9Xdi5c2e6LjppamoKdXV1sToFAgQKLyCxofDGRiBAgEBZCixdunTSL8VMFUZiw1TFtCdAgAABAgQIECBAgMDkArkmWCiCqgAAIABJREFUN6xbty68++676Q8BJo+sBYHiCEQ7RWY7og+iJkpsGC+BYbx42cbIp+748eNh/fr1OW+LHt1E4pZbbslnyLLtO5t24HjttdckNZTtb6KFEyBAgAABAgQIECBAgAABAgQIFEIg2tk3er93dHJCdDPe2267bTih4ZFHHond5KatrS00NjaGY8eOhY6OjqxT+tGPfpS1XiUBAoUVqCxseNEJECBAoBwFuru7Q09PT2JLj7b1iu4M+tnPfjaxmAIRIECAAAECBAgQIECAwA2BkeSG0XcsunH1xln0IUBvb++NCmcEZonA4cOHs84kuiPXeMeePXsyLo0XJ6NhAhWf+9znhu/eX1tbG3L5ie4OFv2tOkpXIEpquPfeeydcgJ0aJuRxkQABAgQIECBAgAABAgQIECBAgEBWgegmN9F3zMYeUYJDe3t7rPrgwYPDNx8ZL6lh8+bNoaWlJdZHgQCB4ghIbCiOs1EIECBQVgJbt27NWO/Ro0fDtWvXQiqVGv4ZfVfEvXv3puuj6++//36sf/Qicu3atT68j6koECBAgAABAgQIECBAIFmBXJMbFi9eLLkhWXrREhD46le/mjXKtm3bstZHXzDPdkRblhfrsDNlsaRnxziSGmbH82AWBAgQIECAAAECBAgQIECAAAECc1fgzTffDOO9J5zrqnft2hWOHDmSa3PtCBBIWEBiQ8KgwhEgQIBACFGm6+ijq6srPPDAA8N3IRxdP3J+8803j5wOPzY0NIQLFy7E6rZv3x4rKxAgQIAAAQIECBAgQIBA8gKSG5I3FbE4AjU1NSG60/3Y4+zZs2FgYGBsdciWwBDdhSvastxBIGkBSQ1Ji4pHgAABAgQIECBAgAABAgQIECBAILvAU089Fd5+++3Q1NSUvcE4tdGO1lG/J554YpwWqgkQKIaAxIZiKBuDAAECZSYwepuu6EsBzc3NUxZobGwM0S4PI0e0Bdjg4OBI0SMBAgQIECBAgAABAgQIFEhAckOBYIUtuMDo3SFHD3bo0KHRxXDx4sXQ09MTq4sKPrDKIFGRgICkhgQQhSBAgAABAgQIECBAgAABAgQIECAwBYGWlpbQ3d0dLl++HI4fPz68i0Nra+twskOU8BD9ROVod4foetSur68vRP0cBAjMrIDbT82sv9EJECAw5wSGhoZia7rnnnti5akUol0eHnzwwXSXU6dOhfvvvz9ddkKAAAECBAgQIECAAAEChREYSW5YuHBhxq58o0dcvHjx8I57UXK6g8BMCyxfvjzrFHbu3Bl27NiRvvad73wnfT5yEt2Ny+/xiIbHpAQkNSQlKQ4BAgQIECBAgAABAgQIECBAgACBqQvU1dUNf9fM982mbqcHgZkSsGPDTMkblwABAmUi8OGHH0660vnz54/bJsqOHTnOnz8/cuqRAAECBAgQIECAAAECBAosMJLcEH3he6IjSm7o7e2dqIlrBIomsG/fvqxjdXZ2DtdHN2SIdoUcezz77LNjq5QJ5CUgqSEvPp0JECBAgAABAgQIECBAgAABAgQIECBAoAwFJDaU4ZNuyQQIECikQPTFl9HHeEkLoxMenn/++dFdnBMgQIAAAQIECBAgQIDALBGQ3DBLngjTyFngm9/8Zta20Zbi0fHCCy9kvb5hw4as9SoJTEdAUsN01PQhQIAAAQIECBAgQIAAAQIECBAgQIAAgXIXkNhQ7r8B1k+AAIGEBaIvvYzeZeHUqVNZR1i1alW6/uzZs2FgYCBdHn3S0dExuuicAAECBAgQIECAAAECBIosILmhyOCGy0sg2lp89PsSI8Gi9x6uXr0a/uiP/mikKv0YJT1UVnqrPA3iJC8BSQ158elMgAABAgQIECBAgAABAgQIECBAgAABAmUsUFXGa7d0AgQIECiQwJe//OUwkpBw8uTJMDg4GKqq4v/JWblyZWz09evXhzNnzsTq2traYmUFAgQIECBAgAABAgQIEJgZgZHkhoULF4b+/v5xJ7F48eJw4cKF0NjYOG4bFwgUWuDJJ58M9957b8Yw4+0q+fjjj2e0VUFgOgKSGqajpg8BAgQIECBAgAABAgQIECBAgACBwggMDQ2Fd955J/znf/7n8GcX0Si1tbXh4sWLYcmSJWH58uXh05/+dKipqSnMBEQlQGDKAvFvmU65uw4ECBAgQCBTYMuWLeGxxx5LX/j+978fduzYkS5HJ9ELwqamptDT0zNcH905saGhITz77LPDLxgfeeSRdHLESMc1a9aMnHokQIAAAQIECBAgQIAAgSILSG4oMrjhpi0wepfIyYJE700sWrRosmauE5hUQFLDpEQaECBAgAABAgQIECBAgAABAgQIECiKQPRe3R//8R9nfPdsvMHr6+vD9773vfD1r389RJ+FOAgQmDkB+2vPnL2RCRAgMGcFWlpaYmvbuXNniDJgxx6HDh2KVUV3/dy4cWP4zd/8zawvLMfu8hDrrECAAAECBAgQIECAAAECBRcYSW6I3uSf6Ih2bujt7Z2oiWsECiYQ/Z7u2rUrp/hj35vIqZNGBMYISGoYA6JIgAABAgQIECBAgAABAgQIECBAYAYE+vr6hm+sG+3o29HRkfMMou+sPfzww6GysjJE7/U5CBCYOQGJDTNnb2QCBAjMaYGjR4/G1tfe3h4rR4W1a9eG1tbWjPpsFadPn85WrY4AAQIECBAgQIAAAQIEiiwguaHI4IablsC3vvWtnPp94QtfyKldIRpVV1cXIqyYRRaQ1FBkcMMRIECAAAECBAgQIECAAAECBAgQyCIQJTUsXLgwREkK+RxRUsR3v/vdfELoS4BAHgJVefTVlQABAgQIjCvwwAMPhH/5l38Jp06dGn7BuGbNmqxtf/azn4U77rgj9PT0ZL0eVR4+fHg4CWLcBi4QIECAAAECBAgQIECAQFEFRpIbJvuQINq54cKFC6GxsbGo8zMYgUWLFoWmpqYJ32+IdnWIfpdn6li1alX4tV/7tWkNH/1NPfXUU9Pqq1NyApIakrMUiQABAgQIECBAgAABAgQIECBAgEA+AtHnFZMdI+8ZjzyO137Pnj3hd3/3d8Py5cvHa6KeAIECCUhsKBCssAQIECAQwpEjRyZliL5A0N3dHc6dOxfa2trS23ktWLBgeIuv6EsGdXV1k8bRgAABAgQIECBAgAABAgSKKyC5objeRpu6wP/7f/8vbNy4cdyO3/nOd8a9VowL0U0eJrrRw2Rz2L17d2hpaZmsmesFEpDUUCBYYQkQIECAAAECBAgQIECAAAECBAhMUeDEiRNZe2zYsCH8zd/8TfjMZz4Tqqoyvy595cqV8Oyzz4adO3dm9G9tbQ2pVCqjXgUBAoUVyPxLLex4ohMgQIAAgawCK1euDC+++GLWayoJECBAgAABAgQIECBAYHYKSG6Ync+LWf2fQPSh1XhH9KFUQ0PDeJdLor7U518SyONMUlLDODCqCRAgQIAAAQIECBAgQIAAAQIECMyAwF/8xV9kjNrV1RWam5sz6kdXRDfb3bFjx/DPli1bwnPPPTf68vDNeieLEeugQIBA3gKVeUcQgAABAgQIECBAgAABAgQIECBAgACBshUYSW6or6+f0GDx4sWht7d3wjYuzpxAIe48df369WkvKJ++I4NWVlaGzZs3jxRjj08++WSsXMjCpz71qYKE7+vrK0hcQScWkNQwsY+rBAgQIECAAAECBAgQIECAAAECBIopEL233dHRERsyKk81IeHIkSNh7M1yfvjDH8biKhAgUHgBiQ2FNzYCAQIECBAgQIAAAQIECBAgQIAAgTktMJLc0NTUNOE6o+SGQnyBfsJBXcxJIEoCyJaccvPNN+fUP1ujX/7lX85WHRYsWJC1fnTleH2j37WpHAcOHMhoHv2e3nPPPRn1k1XceeedGU3WrFmTUTe2IrLdv3//2Oq8y0uXLs07hgBTE4i2pr/33nsn7BR9+HnmzJkJ27hIgAABAgQIECBAgAABAgQIECBAgEAyAmM/c4je516+fPm0gv/TP/1TrN/8+fNjZQUCBAovUJEa+1dd+DGNQIAAAQIECBAgQIAAAQIECBAgQIAAAQKzUGBoaChEP9FRVVWVyAzziTk4OJieQz7zGYkTJRlEP9M98lnLdMfUjwABAgQIECBAgAABAgQIECBAgAABAgSyC0RfgR79nu/q1aunfeORsbFOnz4d1q5dm31gtQQIFEQgmU+mCjI1QQkQIECgVAWiD/nfeeedxKff2NiYeEwBCRAgQIAAAQIECBAgQIAAgRsC+X7x/0akG2f5xMwnmeHGDJJL0shnLaPn45wAAQIECBAgQIAAAQIECBAgQIAAAQIE8heIdvmNdunt6ekZDjbyOJ3IY+8T/+qrr0psmA6kPgTyEJDYkAeergQIECCQXaC9vT3s2bMn+8U8aru6ukJzc3MeEXQlQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgbkisH79+nDw4MHh5USJDVevXg21tbVTXt7JkydjfT73uc/FygoECBReoCI1NsWo8GMagQABAgTmuMCKFStCR0dH4quU2JA4qYAECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAoWYG+vr6wcOHC9PxXr14dzpw5ky7ncjI4OBhuuummWNNr166FmpqaWJ0CAQKFFagsbHjRCRAgQIBAcgLXr19PLphIBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFDSAg0NDWHbtm3pNZw9eza0tbWly7mcLFq0KNZs3759khpiIgoEiiNgx4biOBuFAAECZSVw4sSJsHHjximvub6+PvT392f0O3r0aIi2CfvTP/3TUFVVlXFdBQECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiUr8CKFStCR0dHGmDXrl3hiSeeSJfHO2lubh7+btrI9aamptDd3T1S9EiAQBEFJDYUEdtQBAgQIDC5QG9vb1i8eHGs4U9+8pOwcuXKWJ0CAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECMxNgatXr4ZNmzaFxsbGnBb4wx/+MOOmuq2treHuu+8et3+2Pl1dXeGTn/xkqKurG7efCwQIFEZAYkNhXEUlQIAAgTwE+vr6wsKFC2MRLl++7MViTESBAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECc1PgwIEDYefOnTO2uCjBIdrNwUGAQPEEKos3lJEIECBAgEBuAg0NDSF6YTj6uPfee0cXnRMgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECMwRAYkNc+SJtAwCBAjMNYEo23Xv3r3pZXV0dISLFy+my04IECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYG4K3HLLLTO6sOvXr8/o+AYnUI4CFalUKlWOC7dmAgQIEJj9AgMDA+ETn/hEeqL79+8PO3bsSJedECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMDcExgcHAw/+MEPQm1tbdEXd/Xq1fC1r30tVFa6f3zR8Q1Y1gJVZb16iydAgACBWS1QXV0dm9+HH34YKysQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwNwTqKqqClu3bp17C7MiAgTGFZBKNC6NCwQIECAw0wLXrl2b6SkYnwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoMACEhsKDCw8AQIECExfYNOmTdPvrCcBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEBJCEhsKImnySQJECBQXgIDAwPhvvvuCydPnowt/Fd+5VdiZQUCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIHSF6hIpVKp0l+GFRAgQIDAbBLo7e0NTz31VLj55punNK3//u//Dj/60Y9CT09P1n7Xrl0LNTU1Wa+pJECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKE2BqtKctlkTIECAwGwWaGtrCwcPHkx0inv37pXUkKioYAQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEJg7AtG93n/84x+Hf/zHfwz/+q//Ou4NdnNZ8fvvvx8aGhpyaaoNAQIJCdixISFIYQgQIEDghkBzc3NeLwpvRPq/s9bW1vDmm2+OrVYmQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQLhxIkTYePGjYlJdHV1heh7cA4CBIonUFm8oYxEgAABAuUisH79+sSWevz4cUkNiWkKRIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgbkl8MwzzySa1DC3dKyGQOkI2LGhdJ4rMyVAgEDJCHR3d4f9+/eHW265ZcpzXrRoUVi2bFlYsWJFiM4dBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEAgm0BfX19YuHBhtkt51dmxIS8+nQlMS0Biw7TYdCJAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYCYFtm/fHg4ePJgxhV27doWvfvWrobGxMdx0000Z1yeqqKqqCg0NDRM1cY0AgQIISGwoAKqQBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgUVqCioiI2QFNTU/if//mfUFlZGatXIEBg9gtIbJj9z5EZEiBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAwSmBoaCjMmzdvVE0IH3/8saSGmIgCgdIRkI5UOs+VmRIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgkEUg2q3BTg1ZYFQRKBEBiQ0l8kSZJgECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAEC/ycgicFvAoG5JSCxYW49n1ZDgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoCwEtm3bll5nT09PGBgYSJedECBQWgIVqVQqVVpTNlsCBAgQKEWBoaGhcOnSpXDx4sVpv3hcvnx5KS7dnAkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgAALR99Fuu+22dOTW1tbw5ptvpstOCBAoHQGJDaXzXJkpAQIESlLgtddeCw899FCIsmHzPbq6ukJzc3O+YfQnQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgTkisHv37tDe3p5ezebNm8ORI0fSZScECJSGgMSG0niezJIAAQIlKbBixYrQ0dGR2NwlNiRGKRABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgTmjEB0w9zRN9/dsGFDePHFF+fM+iyEQDkISGwoh2fZGgkQIDADAr/9278dzp49m+jIEhsS5RSMAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECc0agoaEh9Pf3x9bT2toaK+dSuHTpUviv//qvUFtbm0tzbQgQSEhAYkNCkMIQIECAwA2Bt956K0z0grCpqSksWLDgRocczrxYzAFJEwIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECJShQHd3d7jjjjsSW7mb8CZGKRCBnAWqcm6pIQECBAgQyFHg29/+dkbL1atXhxdeeCEsWrQo45oKAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAwHYGXXnoprFu3bjpd9SFAYBYJ2LFhFj0ZpkKAAIG5IlBRURFbyr59+8Kjjz4aq1MgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQL5CFy9ejXMnz8/nxBZ+9qxISuLSgIFFbBjQ0F5BSdAgED5CQwNDcUWXV9fL6khJqJAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAkkI/PVf/3XWMK2treHP/uzPwp133hlqamqytpmosrm5eaLLrhEgUAABiQ0FQBWSAAECBG4ILFiw4EbBGQECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQSEjg8OHDGZHef//90NDQkFGvggCB2S0gsWF2Pz9mR4AAgZITqKysLLk5mzABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIlJbA0NBQ6OnpiU36ww8/DLW1tbE6BQIESkPAt09L43kySwIECJSUwLZt29LzjV44DgwMpMtOCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBA0gKtra2SGpJGFY9AEQUkNhQR21AECBAoF4G2trbYUtevXx8rKxAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgXwEKivjX4O+dOlSPuH0JUBghgXif9EzPBnDEyBAgMDcEGhsbAybN29OL+bs2bNhbLJD+qITAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAwDYENGzake/X09IShoaF02QkBAqUlUJFKpVKlNWWzJUCAAIFSEWhoaAj9/f3p6e7du1eCQ1rDCQECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAjkI9DZ2RmWLVuWDhHdkPfIkSPpshMCBEpHQGJD6TxXZkqAAIGSERgcHAzvvvtu+OlPfxo2btwYm3dra2u4++67Y3W5FD744IPw9NNPh5qamlyaa0OAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECZSBw3333hZMnT6ZXum/fvvDoo4+my04IECgNAYkNpfE8mSUBAgRKSmD37t2hvb098Tm//fbboaWlJfG4AhIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBA6Qo0NDSE/v7+9AIkN6QpnBAoGQGJDSXzVJkoAQIESkegubk59PT0JD7hrq6uEMV2ECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBwcHB8O6774ZXX301PPjggzGQ1tbWcPfdd8fqcil88MEH4emnnw41NTW5NNeGAIGEBCQ2JAQpDAECBAjcENiyZUt47rnnblQkdGbHhoQghSFAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMAcENi9e3dob29PfCW+q5Y4qYAEJhWomrSFBgQIECBAYIoCBw4cCF/84hdDbW3tFHuO3/zq1ath6dKl4zdwhQABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgTKSuCFF14oyHqrq6sLEldQAgTGF5DYML6NKwQIECAwTYGGhoawdevWafbWjQABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQITC6watWq0NPTM3nDKba4fv36FHtoToBAvgIVqVQqlW8Q/QkQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFBMgb6+vnD8+PFQW1ub2LBXr14NX/va10JlZWViMQUiQGByAYkNkxtpQYAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBRIQCpRgWCFJUCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBCYXkNgwuZEWBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQIEEqgoUV1gCBAgQIBATSKVS4dq1a2FwcDBUVU39Pz9Rv7q6ulhMBQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgdIXmPo3S0t/zVZAgAABAkUUeP7558OePXtCT09P3qNeuHAhNDY25h1HAAIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCY2wJDQ0NhYGBg+Ga80Upra2undVPeua1kdQRmj4DEhtnzXJgJAQIE5pRAtMPCokWLQn9/f2Lrun79emKxBCJAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBuSXQ19cXHn/88fAP//APWb+7du3atVBTU5Ox6M7OzuEkiE996lPD33vLaKCCAIGCC0hsKDixAQgQIFCeAkuXLs36wjAfDYkN+ejpS4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgbkrsH379nDw4MEJF9jT0xNaWlpibbq7u8OyZcvSdV1dXaG5uTlddkKAQHEEKoszjFEIECBAoJwEohd60QsVY/CmAAAgAElEQVTApI7W1tZw+vTp8NnPfjapkOIQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwBwRaGhomDSpIVpqdXV1xopvv/32WN3OnTtjZQUCBIojILGhOM5GIUCAQFkJbN26NWO9R48eDdE2XqlUavhn//796TZ79+5N10fX33///fS16KSjoyOsXbs2VFRUxOoVCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKC8BXbv3h36+/unjVBbWxs2bNiQ7n/y5Mnh77OlK5wQIFAUAYkNRWE2CAECBMpLYOyLxGhrrgceeCDU1NRkhbj55ptj9VH27IULF2J10TZhDgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgMCJw5cqV0N7ePlJMP46+EW9ra2u6fryTtra22KX33nsvVlYgQKDwAhIbCm9sBAIECJSdQLTDwsixefPm0NzcPFLM+bGxsTFELy5HjoMHD4bBwcGRokcCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKHOBsUkNq1evHt5tYaIb8WYju+uuu2LVr7/+eqysQIBA4QUkNhTe2AgECBAoK4GhoaHYeu+5555YeSqF6MXl6OPUqVOji84JECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAoIwFjh07Flv9K6+8EivnWqiqqgr19fXp5ufPn0+fOyFAoDgCEhuK42wUAgQIlK3Ahx9+OOna58+fP26b0duAebE4LpMLBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKCuBVCoVOjo60mvet29fqKioSJenerJkyZKpdtGeAIEEBSQ2JIgpFAECBAiEjBeG4yUtjE54eP7559ERIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFpC6xZs2bafXUkQGDmBSQ2zPxzYAYECBCYUwJRxuvoXRZOnTqVdX2rVq1K1589ezYMDAyky6NPRmfUjq53ToAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQLlKxDt2JDUMXb3h6TiikOAQO4CEhtyt9KSAAECBHIU+PKXv5xuefLkyTA4OJguj5ysXLly5HT4cf369bFyVGhra8uoU0GAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBCor41+Dfvnll6eNkmSSxLQnoSOBMheI/0WXOYblEyBAgEAyAlu2bIkF+v73vx8rR4WamprQ1NSUro92bWhoaAgnTpwI586dCytWrAiPPfZY+np0YquwGIcCAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEylpg9erV6fXv2bMnDA0NpctTOYn6jj5WrVo1uuicAIEiCFSkpBgVgdkQBAgQKD+BioqK2KI//vjjMDZD9qWXXgrr1q2LtZuo4D9ZE+m4RoAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgfISeOaZZ8LDDz+cXnSU6HDmzJl0OTqJbrLb0dExXNfV1RWam5tj1zs7O8OyZctidZcvXw51dXWxOgUCBAorYMeGwvqKToAAgbIVOHr0aGzt7e3tsXJUWLt2bWhtbc2oz1Zx+vTpbNXqCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQKBMBR566KHYys+ePRsaGhrCxYsX0/X19fXp8+rq6vR5tLvDgQMHMpIampqaJDWklZwQKJ6AHRuKZ20kAgQIlJ3Ali1bwqlTp0J/f3/4yU9+ElauXJlhEO3CcMcdd4Senp6MayMVhw8fDlu3bh0peiRAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAsMCUXLCzp07MzSihIZHHnkkjL4p77Zt20JjY2M4duxYeheHsR3ffvvt0NLSMrZamQCBAgtIbCgwsPAECBAgkJvAuXPnQltbW3jttdeGOyxYsGB4i7Bdu3bJfs2NUCsCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiUpcCKFSvGTVSYCsjmzZvDkSNHptJFWwIEEhKQ2JAQpDAECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECMyMwPbt28PBgwenPXh0E94nnnhi2v11JEAgPwGJDfn56U2AAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwCwQ6OzsDOvXrw89PT05z6a+vj688cYboaWlJec+GhIgkLyAxIbkTUUkQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGCGBK5cuRJeeeWVcOLEieGkhUuXLqVnsmDBgnD33XeH+++/P3z+858PdXV16WtOCBCYOQGJDTNnb2QCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFD2AlVlLwCAAAECBKYlcO7cuWn1y6XTL/3SL4VPfvKTMmFzwdKGAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFDiAnZsKPEn0PQJECAwEwLd3d3hjjvuKMrQu3btCvv27QuVlZVFGc8gBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFBaAlevXg3/8R//EQYGBsKv/uqvhoaGhpwWEPV76aWXQm1tbYjO77vvvlBRUZFTX40IEEhWQGJDsp6iESBAoCwEent7w+LFi4u61suXL9vBoajiBiNAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgMDsF8j2fbahoaGcEhTa2trCY489ll5kU1NTiG786yBAoPgCbn9dfHMjEiBAgMA0BJYsWTKNXroQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwFwWuPPOO2PL27ZtW05JDVGnb3/727G+PT09wzs4xCoVCBAoioAdG4rCbBACBAjMLYG+vr6wcOHCoi+qq6srNDc3F31cAxIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIDA7BPo7OwMy5Yti00slUrFypMV3nrrrdDa2hprNtUYsc4KBAhMS8CODdNi04kAAQLlLdDQ0BCiF26F+vnoo4/C0aNHM5BPnjyZUaeCAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBMpT4Iknnogt/O23346VcyksX748rF69OtY0uvmvgwCB4gpIbCiut9EIECBAIAeBqqqq8MADD4Tjx4/HWn/44YexsgIBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIlK/AG2+8kV58fX19aGlpSZencvLMM8/Emo/97lrsogIBAgURkNhQEFZBCRAgQCAJgd/6rd9KIowYBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDAHBTo6OtKr+tKXvpQ+n+pJU1NTrMu7774bKysQIFB4AYkNhTc2AgECBAhMU6Cnp2eaPXUjQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgbksMDQ0FFver//6r8fKCgQIlJaAxIbSer7MlgABAmUl8Mgjj8TWu2bNmlhZgQABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgTKU6CysjKM3mnhwIED04b44IMPpt1XRwIEkhGQ2JCMoygECBAgkLBAb29vGL1NWBT+N37jNxIeRTgCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKFWBBQsWpKfe09MTrly5ki5P5eTv//7vp9JcWwIECiAgsaEAqEISIECAQP4CDQ0NobW1Nf3z6quvhijD1kGAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBCKBdevWxSCWLFkSUqlUrG6yQmdnZ9izZ0+s2Zo1a2JlBQIECi9QkZrqX2/h52QEAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQITChw8eLFcNttt2W0OX36dPjCF74QKioqMq6NVAwNDYX29vaMpIbo+kcffRSqqqpGmnokQKAIAv7iioBsCAIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEkhVYtGhR2Lx5c3juuedigUd2coiu/cEf/EH4zGc+M3z95z//eTh//nz453/+59DR0RHrM1LYu3evpIYRDI8Eiihgx4YiYhuKAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIHkBKKdF+bNm5dYwFQqlVgsgQgQyF2gMvemWhIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGD2CFRWVoaPPvooNDU15TWp+vr6cO3atbxi6EyAwPQFJDZM305PAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgRmWKCqqip0d3eHo0ePTmsmhw8fDn19faGmpmZa/XUiQCB/gYqU/VLyVxSBAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIFZIdDb2xuOHTsWTp06Ff793/89XLp0KfT39w/PLdqZobW1Ndx3331h06ZNobm5eVbM2SQIlLuAxIZy/w2wfgIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgMIMClTM4tqEJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBMheQ2FDmvwCWT4AAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEZlKgaiYHNzYBAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgSSFhgaGgoDAwNhcHBwOHRtbW2oqvLV6aSdxSOQlIAdG5KSFIcAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgRkT6OvrC7t37w4NDQ1h3rx5Yf78+eHWW28d/rnpppuGEx2yTa6zszO89dZb4eLFi9kuqyNAoAgC0o6KgGwIAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQKJ7B9+/Zw8ODBCQfo6ekJLS0tsTbd3d1h2bJl6bqurq7Q3NycLjshQKA4AhIbiuNsFAIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECiAQ7dDQ398/aeTq6uqMNrfffnusbufOneHFF1+M1SkQIFB4gcrCD2EEAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIJC+we/funJIaxhu5trY2bNiwIX355MmTIZVKpctOCBAojoDEhuI4G4UAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgQQFrly5Etrb2zMiHj16NFy7dm04QaG1tTXj+tiKtra2WNV7770XKysQIFB4AYkNhTc2AgECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECCQuMTWpYvXr1cDLDAw88EGpqanIe7a677oq1ff3112NlBQIECi8gsaHwxkYgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQCBhgWPHjsUivvLKK7FyroWqqqpQX1+fbn7+/Pn0uRMCBIojILGhOM5GIUCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEAgIYFUKhU6OjrS0fbt2xcqKirS5ameLFmyZKpdtCdAIEEBiQ0JYgpFgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEDxBdasWVP8QY1IgEBiAhIbEqMUiAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBYghEOzYkdYzd/SGpuOIQIJC7gMSG3K20JECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEBgFghUVsa/Bv3yyy9Pe1ZJJklMexI6EihzgfhfdJljWD4BAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAqUhsHr16vRE9+zZE4aGhtLlqZxEfUcfq1atGl10ToBAEQQkNhQB2RAECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECCQr8I1vfCMWcM2aNbFyLoXOzs7Q3t4ea9ra2horKxAgUHgBiQ2FNzYCAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIJCzz00EOxiGfPng0NDQ3h4sWL6fr6+vr0eXV1dfo82t3hwIEDYdmyZem66KSpqSnU1dXF6hQIECi8QEUqlUoVfhgjECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAIFmBKDlh586dGUGjhIZHHnkkthvDtm3bQmNjYzh27Fjo6OjI6BNVvP3226GlpSXrNZUECBROQGJD4WxFJkCAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECgwAIrVqwYN1FhKkNv3rw5HDlyZCpdtCVAICGByoTiCEOAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIGiC7z55psh2o0hn2PXrl2SGvIB1JdAngJ2bMgTUHcCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBGZeoLOzM6xfvz709PTkPJn6+vrwxhtvhJaWlpz7aEiAQPICEhuSNxWRAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAIEZErhy5Up45ZVXwokTJ4aTFi5dupSeyYIFC8Ldd98d7r///vD5z38+1NXVpa85IUBg5gQkNsycvZEJECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEDZC1SWvQAAAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAYMYEJDbMGL2BCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgSoEBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKEWBVCoVfv7zn4dXX301/Nu//Vs4f/58uPXWW8Mtt9wSent7Q2NjY1ixYkVYvXp1WLp0aaitrS3FZZozgTkvILFhzj/FFkiAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIEBgbglESQvbt28PJ0+enPLC9u3bF/7kT/4k1NTUTLmvDgQIFEagIhWlKTkIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECAwywWGhobCxo0bp5XQMHZpUYLDo48+OrZamQCBGRCQ2DAD6IYkQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQGBqAn19fWHhwoVT6zRJ6/r6+nDx4sVQVVU1SUuXCRAopIDEhkLqik2AAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQN4CuSY1RIkKS5YsGR7v0qVLoaenJ6exP/roI8kNOUlpRKAwApWFCSsqAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEkhGYaKeGffv2hXfffTd8/PHHIUqAePPNN4d/uru7QyqVGq6/cOFCiNqNdyxdunS8S+oJECiCgMSGIiAbggABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACB6Qk888wzWTvu379/OHHh0UcfDYsWLQqVldm/Gh3VNzY2hqhdlOhw+PDhjHjRzg7nzp3LqFdBgEBxBCpS0V+ngwABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABArNMIPqqc7aEha6urtDc3Dzt2V68eDHcdtttsf719fXDOz7EKhUIECiKQPa0pKIMbRACBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAiML/DjH/8442JHR0deSQ1RwGiHhwsXLsRi9/f3h+7u7lidAgECxRGQ2FAcZ6MQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDBFge9973uxHhs2bAjLly+P1U230NjYGDZv3hzrfvjw4VhZgQCB4ghUpKL9WRwECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBCYZQIVFRWxGV2+fDnU1dXF6vIpXLlyJdx6663pEE1NTXZtSGs4IVA8AYkNxbM2EgECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECOQoMDQ2FefPmpVsXKumgoaEh9Pf3p8f5+OOPQ2VlZbrshACBwgv4iyu8sREIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIEJiiwDvvvBPr8fDDD8fKSRU2bdqUVChxCBCYpoDEhmnC6UaAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAQPEEbr755oIMtmLFiljcgYGBWFmBAIHCC0hsKLyxEQgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQyFPg93//9/OMkFv3X/ziF7k11IoAgcQEJDYkRikQAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQKFEqiuri5UaHEJEJhhAYkNM/wEGJ4AAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECJSzgMSGcn72rZ0AAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAiQjYsaFEnijTJDANgapp9NGFAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECRRX46U9/Gmpra8Pg4GBi437iE58IXV1dicUTiACB6QlIbJiem14ECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBRRYOPGjUUczVAECBRToLKYgxmLAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIDBaQGLDaA3nBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAjMCoHr16/PinmYBAEChReoSKVSqcIPYwQCBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAjkLjA0NBTmzZuXe4eEWkbjVlRUJBRNGAIEchGQ2JCLkjYECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECMyIQJRoUIwjGqeqqqoYQxmDAIExAhIbxoAoEiBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAsUTqCzeUEYiQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECMQFJDbEPZQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBIgpIbCgitqEIECBAgAABAgQIECBAgAABAgQIEB4RH2QAAAI9SURBVCBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgACBuIDEhriHEgECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIFBEAYkNRcQ2FAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIBAXkNgQ91AiQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEiiggsaGI2IYiQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIE4gISG+IeSgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEARBSQ2FBHbUAQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgEBcQGJD3EOJAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQKKKAxIYiYhuKAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQiAtIbIh7KBEgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQJFFPj/SCMom4cQBJEAAAAASUVORK5CYII="
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visual Representasion of the Data\n",
    "\n",
    "![image.png](attachment:image.png)\n",
    "\n",
    "## here we try to predict the energy consumption of the building and the time it is colored in the picture above. for more detail, you can visit in this link :\n",
    "\n",
    "https://www.drivendata.org/competitions/55/schneider-cold-start/page/111/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 509376 entries, 0 to 509375\n",
      "Data columns (total 4 columns):\n",
      "series_id      509376 non-null int64\n",
      "timestamp      509376 non-null object\n",
      "consumption    509376 non-null float64\n",
      "temperature    280687 non-null float64\n",
      "dtypes: float64(2), int64(1), object(1)\n",
      "memory usage: 15.5+ MB\n"
     ]
    }
   ],
   "source": [
    "train_data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 111984 entries, 0 to 111983\n",
      "Data columns (total 4 columns):\n",
      "series_id      111984 non-null int64\n",
      "timestamp      111984 non-null object\n",
      "consumption    111984 non-null float64\n",
      "temperature    67068 non-null float64\n",
      "dtypes: float64(2), int64(1), object(1)\n",
      "memory usage: 3.4+ MB\n"
     ]
    }
   ],
   "source": [
    "test_data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Drop Irrelevant Columns\n",
    "\n",
    "train_data.drop('Unnamed: 0', axis=1, inplace=True)\n",
    "test_data.drop('Unnamed: 0', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"\"\"Change the types of timestamp columns and set the index\"\"\"\n",
    "\n",
    "train_data.timestamp = pd.to_datetime(train_data.timestamp)\n",
    "test_data.timestamp = pd.to_datetime(test_data.timestamp)\n",
    "\n",
    "train_data.index = train_data.timestamp\n",
    "test_data.index = test_data.timestamp"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Check for similarity of training data and test data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>consumption</th>\n",
       "      <th>temperature</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>5.093760e+05</td>\n",
       "      <td>280687.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.076238e+05</td>\n",
       "      <td>15.188679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.626611e+05</td>\n",
       "      <td>8.987142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>-13.466667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.542092e+04</td>\n",
       "      <td>8.451190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>4.986205e+04</td>\n",
       "      <td>15.163333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.351661e+05</td>\n",
       "      <td>21.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2.085109e+06</td>\n",
       "      <td>44.350000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        consumption    temperature\n",
       "count  5.093760e+05  280687.000000\n",
       "mean   1.076238e+05      15.188679\n",
       "std    1.626611e+05       8.987142\n",
       "min    0.000000e+00     -13.466667\n",
       "25%    1.542092e+04       8.451190\n",
       "50%    4.986205e+04      15.163333\n",
       "75%    1.351661e+05      21.800000\n",
       "max    2.085109e+06      44.350000"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data[['consumption', 'temperature']].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>consumption</th>\n",
       "      <th>temperature</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1.119840e+05</td>\n",
       "      <td>67068.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.585893e+05</td>\n",
       "      <td>15.981019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>5.282630e+05</td>\n",
       "      <td>7.796996</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>-12.212500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.417107e+04</td>\n",
       "      <td>10.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.869147e+04</td>\n",
       "      <td>16.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.067592e+05</td>\n",
       "      <td>21.600000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>5.366167e+06</td>\n",
       "      <td>42.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        consumption   temperature\n",
       "count  1.119840e+05  67068.000000\n",
       "mean   1.585893e+05     15.981019\n",
       "std    5.282630e+05      7.796996\n",
       "min    0.000000e+00    -12.212500\n",
       "25%    1.417107e+04     10.750000\n",
       "50%    3.869147e+04     16.000000\n",
       "75%    1.067592e+05     21.600000\n",
       "max    5.366167e+06     42.000000"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_data[['consumption', 'temperature']].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Data Look Very similar, let's visualize it just to having fun"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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CDx48UFIo8tKfgwcP5saNG0pQPHToUIPjdOjQgYsXL1K1alW97QkJCbi7uzNr1iz27NmTY3slfSIHSUlJwIu8mbzYunUrjx8/ZtiwYXoBMbwIAGvVqsX+/fu5ceOGwWtHjBihFzTAi2UsgNOnTyvbdANcZnk6FSpUyHSW9lV07txZb2BUqVRK4FajRg2DwHfw4MEAWS5ZDB48WC8gBvjss88wNTVl69at+Q7mdUuM8+bN07s4wczMjFmzZgEvZi0zExgYqATE8GI2sHfv3ty9e1dZOi0o7du3zzQghsxzp8uWLcvIkSMBMk3dyUq1atWYNWuW3gdkq1ateOutt4iPj1dSNnLjs88+05sZK1++PO+//z6gf67u3LmThw8f8v777xuc29OnT8fU1DTXx8wL3SzJy+lKxuxPgLp16xoEHPDib7l8+fJ5rk/kX2xsLCdPnsTb21svIIYXfwP+/v48e/aMkJAQg9c6ODjoBcTwYrYKXpwnL18/ktOY17NnT4O85wkTJmBubs6ePXtITU0FXqRl7Nixgw4dOhh8iTIxMeHzzz8HYMuWLQbHMDU15Ysvvsj0PCxO56efn59BQAyg0WgAWLJkiUEu7rBhw2jQoAE7d+7k0aNHBda2MmXKKOmSL7O2tjYI4ADef/99atasSWRkZJ6ONWvWLCUghhe/X915pEvXyo1+/foZzLjrzt2M6WjJyckcOnSI2rVrG3xmd+rUCXd39zy1P7esrKxQqVRotVq9FBhj92eNGjUMAmJ48bfs6urKiRMnePDgQY71yExxDnT5hXm9ev3f//43AF26dDHYV6FCBdq3b8+OHTuIj483CLgzLg3ovPnmmwDK4Ang4eHBV199xeTJkzl48CBubm60a9eOpk2bZjoAvqoWLVoYbLOysgKgadOmBn2j25dZwA8v/gBfVq1aNRwcHIiLiyMxMTHXs54vu3fvHpcvX8bCwsLgywigzK7ofj8ZmZmZYWtra7A9s74vCNkt7SQnJ7N48WIOHTrEtWvXDP64b968mevjNG7cWC/w16lduzZnzpxR8mhzI7NzVXc+Z+yv+Ph44EXg/zK1Wk2jRo2Mlk+cmZfPUWP2J7xYmVmzZg0//fQTFy5c4N69e3q5yXmtT+SfLsf377//JiAgwGC/7neS2ZfdzFLlLC0tAbC3tze4E4BuX17GvIoVK9K6dWv27dvH2bNncXZ2Ji4uDq1Wy7NnzzJts+48zazNDRs2zPLvtjidn1mNczExMZiYmLB58+ZM92u1WtLT07l27Rp2dnYF0rZatWplOQH27Nkz1q9fT0hICOfPn+fu3bs8f/5c2Z/ZmJqd3I6dr1KPhYUFZcuW1avnt99+Q6vV0rp160yD/vbt2xMeHp7r476KjOOwsfsTXqy2rlmzhl9//ZXbt28bTLAlJydn+hmfkQTFObCysuLixYuZXuSWHd3FC1ndhkQ3iGZ2EU5m33bKlCkDvDiRdKytrYmIiCAwMJADBw4oSwMWFhb4+fkxceJE5XX5kdkVtLp6s9uX1YxvVn2iyxXLz4VJOfV7pUqVqFq1aq77HTLv+4KgOyde9tdff9G1a1du3LiBo6MjQ4YMwczMjDJlypCSksLatWt5/Phxro+T1fvUfWvPy/vMrC5dPRkHuHv37gFZ/14K6nY9ug/7mjVrKtuM3Z9arZb33nuPiIgIGjRoQL9+/bCwsFA+eJYsWZKn+oRx/P3338CLZfkDBw5kWS6zi0KzO6+z25fVKktO571uPNK1OTY2ltjY2CzbfP/+fYNtWY0fxe38zKydjx49Ut5TYGBgtq/P7L0bS1Z9CC9muLdt24aNjQ0eHh5YWVkpX45Wr16d5z7M7jzK7xisUqkoU6aMXj05jcEFlat969YttFotKpVKL/XM2P25bt06Jk6cSNWqVXFxccHGxgYTExNUKhX79u3jzJkzuapTguIcdOjQgSNHjvDLL7/w0Ucf5fp1uhM14x0VMtKlZWQVoOSWnZ0da9as4dmzZ5w7d44jR46wZs0a5s6dy/Pnz5VlPt3McVZ/bHfu3MHMzCxfbcmtrPpEt8Sdnz7Jqd8fPHjA3bt39ZatiousViPWrFnDjRs3+OqrrwxuPxYZGcnatWsLo3n5ovvylNXvJavt+RUVFQVA27ZtlW3G7s/o6GgiIiLo2bMnmzZt0lulefToUaYXRYmCpxsLFi1ahI+PT5G2JafzXtdW3X8nTZqkpHrlVlbjR0Gcn7o6MvsScOfOnTy3s0KFClSsWBG1Ws1//vOfPLfHWLLqw4SEBLZt20aHDh3YuXOnwUqBRqPJNBWgOMlpDM7sjljGoBuDmzZtqlyoaez+1Gq1zJs3jxo1avDLL79Qp04dvf3x8fG5TkmRnOIcDBkyhHLlyrFr1y4SEhKyLZsx10mXM6s7IV4up1vaezm39lWVKVOGFi1aMHbsWEJDQwHYvXu3sl+3rJbZU77++9//Fupto44ePWqwLTU1lYSEBCpVqqS3NJbXWdoqVapQv359kpOTMx1cjxw5AmS+5FRc/f777wD07dvXYF9mfVkc6VJwMnvCUWpqqnJbHWM6c+YM4eHhlC1bVrk4FV6tP7M7D3X19enTxyBt6fjx43oz5qLwtGvXDoBjx44VcUsyP6/S09M5ffo0b7zxhpKuofvyprvA2xhe5fzMadzVfZ5ktoKa8VqCvGjbti23bt0qlg/A0rXJw8PDIICLj48vEbddbNasGSqVitOnT2e6imvMp8/ppKenK3fy0eVLw6v1Z3bn5J07d0hJSaFNmzYGAfHDhw/zlJonQXEObGxsmDFjBk+ePOGdd94hLi4u03InTpzQu6XJO++8Q/ny5Vm7dq3BB35QUBA3btygR48e+XrAwqlTp5QZ54x02zLm5LRu3Zo33niDrVu36i0X3r9/3+B+kgVty5YtBjm98+bN4/79+3h7e+vlO+mWW7K6n2dmdE/XmTlzpt4f/927d5kzZw5Anmb9i5ruFnQvf8GKjY1l+fLlRdGkPPP09KRSpUps2rTJ4MvK/Pnzjb4kun//fgYPHszz588ZN26c3t0FXqU/dedhZl8qs6rv5s2beld+i8LVqVMnWrVqxbZt2zK9MA3gP//5T6Hk04aHhxucH4sWLeKvv/6iV69eSpBZt25d+vXrx/Hjx1m8eHGmAcDVq1fzFDi+yvmZ3fkO/wveX74H73//+1+CgoJy3baMxo4dq/w3s8+1hw8fZnov6MKg68Po6Gi97X///XemT8krjiwsLHBzc+PGjRvKRY06R48eZd++fUY93pUrV3jnnXdISEigadOmDB8+XNn3Kv2pW93N7JxUq9WYmZkRHx+vt1Lx9OlTZsyYwa1bt3Ld7uI9319MTJgwgadPn/L111/TvXt32rZtS+vWralSpQq3b98mNjaWhIQEvXwZGxsbAgMDmTRpEi4uLvTv3x9LS0tiYmI4evQob775Jt99912+2hUSEsKaNWvo0KEDDRo0oHr16ly/fp29e/fyxhtv6N1yxdLSkiFDhrBhwwacnZ3p0aMH6enpHDp0CBsbG6M8/Sy3unfvTs+ePfHy8sLS0pJjx44RExODra2twZKhi4sLp06d4sMPP6RHjx5UrFgRa2tr3n333SzrHzNmjHLbt44dO+Lu7s6TJ08ICwvjxo0bvPvuuwa3YyvOPvjgA1auXMnEiRM5ePAgtra2JCYmsm/fPjw9Pdm+fXtRNzFHNWvWJCAggPHjx+Pm5oaXl5dyn+JLly7h6OhIbGxsni9ojYiIUL7kpaenc+vWLWJjY/n9998pV64cU6ZMMbhN0qv0p4uLC/v372fkyJH07t2bSpUqYW5ujo+PD506daJFixZs2bKF69ev065dO27evMn+/ftp1apVngZkYTwqlYp169bRv39/RowYwbJly2jTpg1mZmbcvHmT3377jYSEBH766acCH/88PDwYMGAA/fv3x9ramlOnTvHLL79gaWlpcEHdkiVLuHbtGl988QUbNmygffv2mJubc/PmTRITEzl9+jSLFy/O9b29X+X87Nq1KyqViqCgIP78808lJ3/s2LGYmJjg5eXFt99+y48//sjvv/9O69at+fPPP5X76+seeJEXPXv2ZNq0acyfP5/WrVvTrVs36taty/3797l+/TrHjh2jWbNmBX4xWGaaN29Oly5d2L9/P66urnTq1ImUlBQOHTqEtbU1NjY2pKenF3q78iowMJDu3bsza9YsfvnlF9566y3++OMPfvrpJzw8PJTYIS9u3LihnMPPnj1THvMcFxfH8+fPcXV1RaPR6N3j+lX609nZmbJly7J27Vru37+v5H8PGzaM6tWrM2rUKObPn0+nTp3o1asXWq2WqKgokpKS6Nq1q/Igm5xIUJxL/v7+9O/fnzVr1nDkyBE2b97MgwcPUKvVODg4EBgYqNyKSsfX15f69euzdOlS9uzZw/3796lVqxZ+fn74+/vn++KiQYMG8eTJE2JiYti5cycPHjzA0tISd3d3xowZY3CVb1BQEBYWFmzZsoXg4GAsLS3x9vZmypQpODo65qsteTFq1Cj69OnDihUruHTpEpUrV+aDDz5g1qxZBveA/fTTT7l79y579+5l8eLFPH36lE6dOmUbFJcvX57t27ej0WjYunUra9as4Y033qBJkyZMmzZNmUkuKWxtbdmzZw9z5swhKiqKgwcPYm9vz/Lly2nRokWJCIrhxW0Fq1evzsKFCwkNDaVixYp06dIFjUaj3Gc7r3ntkZGRREZGolKpMDU1Ra1W07hxYz744APeeeedTB9e8yr9+fHHH5OcnMz27dtZtmwZT548oUmTJvj4+FCuXDm2bdvGV199RUREBKdOnaJOnTqMGDGCSZMmZXoXFFE4bG1tOXLkCCtXrmT37t2EhITw7NkzLCwsaNSoEUOHDqV169YF3o7Bgwfz7rvvsnDhQnbv3k3FihUZNGgQs2bNMjhH1Wo1+/btY926dWzfvp1du3aRnp6OhYUFtra2zJkzx+ApcNl5lfOzRYsWrFixghUrVvDDDz8oT1kbOnQoJiYmmJqaEhYWxqxZs4iMjOTUqVM0atSIRYsW0bx581cKigGmTZuGs7Mzq1atIiYmhr1791KlShVq1arF+++/z6BBg16p3vxSqVT88MMPBAQE8PPPP7Nq1SqsrKx49913mTJlCi4uLiUiKG7QoAEHDx5k9uzZHD58mGPHjuHg4EBwcDA3btxg7969eb6m58aNG8rFkRUqVKBq1arY2toybNgwBgwYoPfkT51X6c+6deuybt06Fi5cyKZNm5Q7sXh6elK9enUmT56MWq3m//2//8cPP/xAlSpVePvtt9m8eTOLFy/OdVCsSk1NLbjn1wqRwahRo/jXv/5FWFiYwT07Ren1+PFjHBwclBmh4n7BihC5NXPmTJYtW6b38CMhiqOxY8fy448/GjzoprSRnGIhRKFITU01+Pb//Plz5s6dS0pKCr1795aAWAghClBmOfTHjh1j8+bNmJmZGTwpsbSRTyAhRKGIjo5mzJgxuLq6Ym1tzb1794iJiSEhIQFLS0u++OKLom6iEEK81lq2bEn79u1p1KgR5cuX58KFCxw6dAiVSsWCBQsK7OmiJYUExUKIQtGkSRPc3d2JjY1l//79PHnyhNq1azN8+HAmTZqU50epCyGEyBs/Pz9++eUXQkNDuXfvHmZmZvTo0YNPPvmEzp07F3XzipzkFAshhBBCiFJPcoqFEEIIIUSpJ0GxEEIIIYQo9SQoFkIIIYQQpZ4ExYUgMTGxqJvw2pC+NB7pS+ORvhTFgZyHxiN9aVwlpT8lKBZCCCGEEKWeBMVCCCGEEKLUk6BYCCGEEEKUehIUCyGEEEKIUk+CYiGEEEIIUepJUCyEEEIIIUo9CYqFEEIIIUSpV7aoGyCEeP2p1/2Z7f5U3zcLqSVCiNeVjDMiv2SmWAghhBBClHoSFAshhBBCiFJP0ieEELLsKIQQotSToFgIIYQQxV5OX96FyC9JnxBCCCGEEKWezBQLIYQQosjJTLAoajJTLIQQQgghSj2ZKRZCCCHEa08uKBY5KdKZ4lu3bjFy5EgaNGiApaUlTk5OREdHK/u1Wi0BAQE0btwYKysrevfuzfnz5/XqSE1Nxc8+ULTWAAAgAElEQVTPDxsbG2xsbPDz8yM1NVWvzLlz5+jVqxdWVlY0adKEwMBAtFqtXpmdO3fi5OSEhYUFTk5OhIWFFdwbF0IIIYQQxUqRzRSnpqbi7u5O+/bt2bp1KzVq1ODq1auYm5srZRYvXszy5ctZvnw5dnZ2LFiwAC8vL+Li4qhSpQoAw4cP548//iAkJASVSsW4ceMYMWIEW7ZsAeDu3bt4eXnRsWNHIiIiSExMZMyYMVSqVIlPPvkEgNjYWIYOHcr06dPp27cvYWFh+Pj4sG/fPtq2bVv4nSNEMSMzLEIIIV53RRYUL1myBCsrK1auXKlss7W1Vf5fq9Wi0WiYMGECnp6eAGg0Guzs7AgNDcXX15cLFy5w8OBBwsPDcXJyAmDhwoV4eHiQmJiInZ0dISEhPHz4EI1Gg4mJCQ4ODly8eJEVK1YwduxYVCoVGo0GZ2dn/P39AbC3tycqKgqNRsPatWsLr1OEEEIIIUSRKLL0iT179tCmTRt8fX1p2LAhnTt3ZtWqVUpaw9WrV0lKSsLV1VV5jYmJCR07diQmJgZ4McNbuXJlJSAGaN++PaampnplOnTogImJiVLGzc2NmzdvcvXqVQDi4uL0jqMro6tDCCGEEEK83oosKL5y5Qpr167F1taWbdu2MXLkSGbPns3q1asBSEpKAtBLp9D9nJycDEBycjI1atRApVIp+1UqFTVr1tQrk1kdun26Y2V3HCGEEEII8XorsvSJ58+f06pVK7744gsA3nrrLS5fvsyaNWvw8/NTymUMeOFFWsXLQfDLciqjm43OqUxmdWeUmJiY7f5XLSuyJ31pPP/ry0pGqicr2df/OvxOM74HOzu7ImxJ3gQFBREWFsalS5coX748bdu25YsvvsDBwUEpo9VqmT9/PuvXryc1NZU2bdrw7bff0qRJE6VMamoqU6ZMITw8HICePXuyYMEC1Gq1UubcuXNMnjyZ06dPU61aNXx8fJgyZYreWLtz506+/vprfv/9d+rVq8fMmTPp27dvIfSEEKK0K7Kg2NLSEnt7e71tjRo14o8//lD2w4vZ3Dp16ihlUlJSlFldCwsLUlJS9AJYrVbL7du39cq8POObkpIC/G/G2NLSMtMyL88evyy3H3y6/GaRf9KXxqPXl9H5u2l+jr+THOov6b/TknxeRkdHM2zYMFq3bo1Wq+Xrr7+mf//+xMTEUK1aNUAuehZClA5FFhS3b9+eS5cu6W27dOkS1tbWANStWxdLS0siIyNp3bo1AOnp6Rw/fpw5c+YA4OjoSFpaGrGxsUpecWxsLPfv31d+dnR05MsvvyQ9PZ2KFSsCEBkZSa1atahbty4A7dq1IzIyknHjxiltiYyM1MtVFkJkTZ5EVXJt375d7+eVK1diY2PDiRMn8PDwkIuehRClRpHlFI8ePZq4uDi+/fZbLl++zE8//cSqVasYPnw48CKdYdSoUSxatIhdu3aRkJDA6NGjMTU1ZdCgQcCLAbNbt25MnDiRuLg4YmNjmThxIu7u7sqszaBBgzAxMWH06NEkJCSwa9cuFi1axOjRo5XZ5ZEjR3LkyBGCgoK4ePEiQUFBREVFMWrUqKLpHCGEKCJpaWk8f/5cSXuQi56FEKVFkc0Ut27dmo0bNzJnzhy++eYb6tSpw2effaYExQDjx4/n4cOHTJ48Wclj2759u7JcB7B69WqmTp3KgAEDAPDw8GDBggXKfjMzM3bs2IG/vz8uLi6o1WrGjBnD2LFjlTJOTk4EBwczd+5cAgICqFevHsHBwbJcJ4QodaZNm0bz5s1xdHQEsr/o+ebNm0DuL3quXbu2QR26fba2tq900fPrkI9uTCW7P/J3bUN+vdx3Jbsvi5/C7s9XSWkr0sc8u7u74+7unuV+lUrF9OnTmT59epZlqlWrxqpVq7I9TtOmTfn555+zLePp6aksDQohRGn02WefceLECcLDwylTpozevuJ60XNJzeUuCCU5tx3I97UN+ZWx70p8XxYzJaU/izQoFkIIUTxMnz6d7du3ExYWpvcgpZJw0bMQxqB/bUQlgyBdntz5+iuynGIhhBDFw9SpUwkNDWXXrl00atRIb1/Gi551dBc9Z7ygWXfRs05mFz0fP36c9PR0pUxWFz1nJBc9CyEKiwTFQghRivn7+7Np0ybWrFmDWq0mKSmJpKQk0tLSALnoWQhRekj6hBBClGJr1qwBMLimYurUqcr1HHLRszAGuXWjKO5Uqamp2qJuxOuupCSYlwTSl8aTsS+L+sOqpOfqyXkpioPifh4W9TiTXyV9nCpKxf3c1JH0CSGEEEIIUepJUCyEEEIIIUo9CYqFEEIIIUSpJ0GxEEIIIYQo9SQoFkIIIYQQpZ4ExUIIIYQQotSToFgIIYQQQpR6EhQLIYQQQohST4JiIYQQQghR6klQLIQQQgghSj0JioUQQgghRKknQbEQQgghhCj1JCgWQgghhBClXtmiboAQQgghSj71uj+LuglC5IsExUIIIYQQOcgp6E/1fbOQWiIKSpGmTwQEBKBWq/X+NWrUSNmv1WoJCAigcePGWFlZ0bt3b86fP69XR2pqKn5+ftjY2GBjY4Ofnx+pqal6Zc6dO0evXr2wsrKiSZMmBAYGotVq9crs3LkTJycnLCwscHJyIiwsrODeuBBCCCGEKFaKPKfYzs6OCxcuKP+OHTum7Fu8eDHLly8nMDCQiIgIzM3N8fLy4t69e0qZ4cOHEx8fT0hICKGhocTHxzNixAhl/927d/Hy8sLCwoKIiAjmz5/P0qVLWbZsmVImNjaWoUOH4u3tTVRUFN7e3vj4+HDy5MnC6QQhhBBCCFGkijx9omzZslhaWhps12q1aDQaJkyYgKenJwAajQY7OztCQ0Px9fXlwoULHDx4kPDwcJycnABYuHAhHh4eJCYmYmdnR0hICA8fPkSj0WBiYoKDgwMXL15kxYoVjB07FpVKhUajwdnZGX9/fwDs7e2JiopCo9Gwdu3awusMIYQQopiSnGHxuivymeIrV67QpEkTWrRowdChQ7ly5QoAV69eJSkpCVdXV6WsiYkJHTt2JCYmBngxw1u5cmUlIAZo3749pqamemU6dOiAiYmJUsbNzY2bN29y9epVAOLi4vSOoyujq0MIIYQQQrzeinSmuG3btqxYsQI7OztSUlL45ptv6NGjBydOnCApKQkAc3NzvdeYm5tz8+ZNAJKTk6lRowYqlUrZr1KpqFmzJsnJyUqZ2rVrG9Sh22dra0tSUlKmx9HVkZXExMRcv9e8lBXZk740nv/1ZaVi0o6SK+N7sLOzK8KWCCGEeBVFGhR3795d7+e2bdvSsmVLNm3aRLt27QD0Al54kVbxchD8spzK6C6yy6lMZnVnlNsPPl0qh8g/6Uvj0evL6KJdFi3pv1M5L4UQouQr8vSJjCpXrkzjxo25fPmykmf88mxtSkqKMqtrYWFBSkqK3p0ktFott2/f1iuTWR3wvxljS0vLbI8jhBBCCCFeb8UqKE5PTycxMRFLS0vq1q2LpaUlkZGRevuPHz+u5BA7OjqSlpZGbGysUiY2Npb79+/rlTl+/Djp6elKmcjISGrVqkXdunUBaNeund5xdGUy5ioLIYQQQojXV5EGxTNnziQ6OporV65w8uRJ/u///o8HDx7w3nvvoVKpGDVqFIsWLWLXrl0kJCQwevRoTE1NGTRoEPDiLhHdunVj4sSJxMXFERsby8SJE3F3d1eWMgcNGoSJiQmjR48mISGBXbt2sWjRIkaPHq2kR4wcOZIjR44QFBTExYsXCQoKIioqilGjRhVZ3wghhBBCiMJTpDnFN27cYPjw4dy+fZuaNWvStm1bDhw4gI2NDQDjx4/n4cOHTJ48mdTUVNq0acP27dupUqWKUsfq1auZOnUqAwYMAMDDw4MFCxYo+83MzNixYwf+/v64uLigVqsZM2YMY8eOVco4OTkRHBzM3LlzCQgIoF69egQHB9O2bdtC6gkhhBBCCFGUVKmpqdqci4n8kItwjEf60ngy9mVR33+0pD8eVc5LURwU9HlY1ONEcVfSx7GCVFLGyGKVUyyEEEIIIURRKPIn2gkhhBBClHQ5zaTLTHLxJzPFQgghhBCi1JOZYiFEkZMZFiGEEEVNZoqFEEIIIUSpJ0GxEEIIIYQo9SQoFkIIIYQQpZ4ExUIIUYodPXqUd999lyZNmqBWq9m4caPe/lGjRqFWq/X+devWTa/Mo0ePmDx5MvXr16d27dq8++67/Pmnfp749evXGTx4MLVr16Z+/fpMmTKFx48f65WJjo7m7bffxtLSkrfeeovg4OCCedNCCJEJCYqFEKIUu3//Pg4ODsyfPx8TE5NMy3Tt2pULFy4o/0JCQvT2T58+nbCwMNauXcvevXu5d+8egwcP5tmzZwA8e/aMwYMHk5aWxt69e1m7di27du1ixowZSh1XrlzhnXfewdHRkSNHjjBp0iSmTJnCzp07C+7NCyFEBnL3CSGEKMV69OhBjx49ABg9enSmZSpUqIClpWWm++7cucOGDRtYvnw5Li4uAKxcuZLmzZtz+PBh3NzciIiI4Pz585w9e5Y6deoAMHv2bMaNG8fnn39O1apVWbduHVZWVnzzzTcA2Nvbc/LkSZYtW4anp6ex37YQQhiQmWIhhBDZOn78OA0bNqRNmzaMGzeOv/76S9l35swZnjx5gqurq7KtTp062NvbExMTA0BsbCz29vZKQAzg5ubGo0ePOHPmjFImYx26Mr/++itPnjwpyLcnhBCAzBQLIYTIRrdu3ejbty9169bl2rVrzJ07l379+nH48GEqVKhAcnIyZcqUoUaNGnqvMzc3Jzk5GYDk5GTMzc319teoUYMyZcrolenatatBHU+fPuX27dtYWVll2r7ExEQjvdPXQ8H2R6UCrPv1V9rP1cJ+/3Z2dnl+jQTFQgghsjRw4EDl/5s2bUrLli1p3rw5+/bto1+/flm+TqvVolKplJ8z/n9G2ZXRarXZvhZe7YPvdZWYmFiw/RGd/UN2RPZK87la4OemkUj6hBBCiFyrVasWtWvX5vLlywBYWFjw7Nkzbt++rVcuJSVFmR22sLBQZoR1bt++zbNnz7Itk5KSQtmyZalevXpBvR0hhFBIUCyEECLXbt++zc2bN5UL71q2bEm5cuWIjIxUyvz5559cuHABJycnABwdHblw4YLebdoiIyOpUKECLVu2VMocPnxY71iRkZG0atWKcuXKFfC7EkIISZ8QQohSLS0tTZn1ff78OX/88Qfx8fFUq1aNatWqMX/+fPr164elpSXXrl1jzpw5mJub06dPHwDMzMz48MMPmTVrFubm5lSrVo0ZM2bQtGlTJUfY1dWVJk2aMHLkSObOncs///zDrFmz+Oijj6hatSoAvr6+rF69mmnTpuHr60tMTAybNm1izZo1RdIvpZF6naRHiNJNgmIhhCjFfv31V/r27av8HBAQQEBAAO+99x5BQUEkJCSwefNm7ty5g6WlJc7Ozqxbt44qVaoor/n6668pU6YMvr6+pKen06VLF77//nvKlCkDQJkyZdiyZQv+/v707NmTihUrMmjQIObOnavUYWtry9atW/nss88IDg7GysqKwMBAuR2bEKLQSFAshBClmLOzM6mpqVnu3759e451VKxYkW+++Ua5x3BmrK2t2bJlS7b1dO7cmSNHjuR4PCGEKAiSUyyEEEIIIUq9PAXFgYGBJCQkZLn//PnzBAYGvlJDvvvuO9RqNZMnT1a2abVaAgICaNy4MVZWVvTu3Zvz58/rvS41NRU/Pz9sbGywsbHBz8/PYNbj3Llz9OrVCysrK5o0aUJgYKByqx+dnTt34uTkhIWFBU5OToSFhb3S+xBCiIJWkGOxEEKUVnkKiufPn8+5c+ey3P+qA3FcXBzr16+nadOmetsXL17M8uXLCQwMJCIiAnNzc7y8vLh3755SZvjw4cTHxxMSEkJoaCjx8fGMGDFC2X/37l28vLywsLAgIiKC+fPns3TpUpYtW6aUiY2NZejQoXh7exMVFYW3tzc+Pj6cPHkyz+9FiOJIve5Pg3/toisp/y9KloIai4UQojQzavpEWlpanm+dc+fOHT7++GOWLl2KWq1Wtmu1WjQaDRMmTMDT0xMHBwc0Gg1paWmEhoYCcOHCBQ4ePMiiRYtwcnLC0dGRhQsXsm/fPuXJKSEhITx8+BCNRoODgwOenp6MHz+eFStWKLPFGo0GZ2dn/P39sbe3x9/fn86dO6PRaIzUM0IIUXheZSwWQojSLscL7X777TfOnj2r/Hz8+HGePn1qUC41NZXg4GAaNmyYpwbogt63336bBQsWKNuvXr1KUlISrq6uyjYTExM6duxITEwMvr6+xMbGUrlyZeVemADt27fH1NSUmJgY7OzsiI2NpUOHDpiYmChl3NzcmDdvHlevXsXW1pa4uDj8/Pz02uXm5saqVavy9F6EEKKgFPRYLIQQpV2OQfHu3buVZTiVSsW6detYt25dpmWrVKnC6tWrc33w9evXc/nyZVauXGmwLykpCUB52pGOubk5N2/eBCA5OZkaNWoYPCa0Zs2aypORkpOTqV27tkEdun22trYkJSVlepyXn670srw8x7u0P/PcmKQvX0Wlom5AvpSE33nGNhbE40wLciwWQgiRi6D4o48+olu3bmi1Wnr06MG0adNwc3PTK6NSqahUqRINGjSgfPnyuTpwYmIic+bM4eeff872NS8/816r1RoEwS/LqYwubSKnMpnVnVFuP/hKyjO/SwLpy1cUXbLzhov777wwzsuCGouFEEK8kGNQXLt2bWWmNSwsDHt7e4NZ1VcRGxvL7du36dChg7Lt2bNnHDt2jODgYE6cOAG8mM2tU6eOUiYlJUU5voWFBSkpKXoBrFar5fbt23plXp7xTUlJAf43Y2xpaZlpGWO8TyGEMIaCGouFEEK8kKcL7Tp37my0Qbh3794cO3aMqKgo5V+rVq0YOHAgUVFRNGzYEEtLSyIjI5XXpKenc/z4cSWH2NHRkbS0NGJjY5UysbGx3L9/X6/M8ePHSU9PV8pERkZSq1Yt6tatC0C7du30jqMrkzFXWQghigtjjsVCCCFeyPMT7Q4fPsz69eu5cuUK//zzj8H9flUqFWfOnMmxHrVarXe3CYBKlSpRrVo1HBwcABg1ahTfffcddnZ2NGzYkG+//RZTU1MGDRoEgL29Pd26dWPixIksXrwYrVbLxIkTcXd3V5YyBw0aRGBgIKNHj8bf359Lly6xaNEipkyZoswujxw5kl69ehEUFESfPn3YvXs3UVFRhIeH57V7hBCiUBhrLBZCFI6cbn+Z6vtmIbVEZCVPQbFGo2HGjBnUrFmTtm3b0qRJk4JqFwDjx4/n4cOHTJ48mdTUVNq0acP27dupUqWKUmb16tVMnTqVAQMGAODh4aF3FwszMzN27NiBv78/Li4uqNVqxowZw9ixY5UyTk5OBAcHM3fuXAICAqhXrx7BwcG0bdu2QN+fEEK8isIei4UQojRQpaamanMu9kKzZs2oV68e27Ztk4s48kAuDjMe6ctXU9If0FHcZ1AK+7yUsVhkJr/nYUkfJ0q64j7O5UdJ+ezOU07x7du3GTBggAzCQghRhGQsFkII48tTUNyyZUuuXbtWUG0RQgiRCzIWCyGE8eUpKJ43bx6bNm3iyJEjBdUeIYQQOZCxWAghjC9PF9oFBARQtWpV+vfvT4MGDbC2tqZMmTJ6ZVQqFVu3bjVqI4UQQvyPjMVCCGF8eQqK//Of/6BSqahTpw6PHj3i0qVLBmVyegqcEEKI/JGxWAghjC9PQfHZs2cLqh1CCCFyScZiIYQwvjzlFAshhBBCCPE6ytNM8fXr13NVztra+pUaI4QQImcyFgshhPHlKShu0aJFrvLU/v7771dukBBCiOzJWCyEEMaXp6B42bJlBgPxs2fPuHr1Kps3b8bCwoLhw4cbtYFCCCH0yVgshBDGl6egeMiQIVnumzBhAq6urqSlpeW7UUIIIbImY7EQQhif0S60q1y5MkOGDGHFihXGqlIIIUQeyVgshBCvxqh3nyhXrhw3b940ZpVCCCHySMZiIYTIO6MFxWfPnuX777/H3t7eWFUKIYTIIxmLhRDi1Rjl7hN37tzh7t27VK5cmeXLlxutcUIIIQzJWCyEEMaXp6C4U6dOBgOxSqVCrVZTv359Bg4ciFqtNmoDhRBC6JOxWLwK9bo/i7oJQhRreQqKNRpNQbVDCCFELslYLIQQxpevnOJ79+5x7949Y7VFCCHEK5CxWAgh8i/PQfG1a9cYMWIE9evXp27dutStW5f69eszcuRIrl27VhBtFEII8RIZi4UQwrjyFBQnJibStWtXQkNDadWqFSNHjmTEiBG0bt2akJAQXFxcuHTpUq7qWr16NR07dsTa2hpra2u6d+/Ovn37lP1arZaAgAAaN26MlZUVvXv35vz583p1pKam4ufnh42NDTY2Nvj5+ZGamqpX5ty5c/Tq1QsrKyuaNGlCYGAgWq1Wr8zOnTtxcnLCwsICJycnwsLC8tItQghRqIw5FgshhHghTznFs2fPRqvVEhkZSYsWLfT2nT17Fk9PT2bPns2GDRtyrKt27drMnj2bBg0a8Pz5c/71r38xZMgQDh8+TLNmzVi8eDHLly9n+fLl2NnZsWDBAry8vIiLi6NKlSoADB8+nD/++IOQkBBUKhXjxo1jxIgRbNmyBYC7d+/i5eVFx44diYiIIDExkTFjxlCpUiU++eQTAGJjYxk6dCjTp0+nb9++hIWF4ePjw759+2jbtm1eukcIIQqFMcdiIYQQL+Rppjg6OpoRI0YYDMIAzZs35+OPPyYqKipXdfXu3Zvu3btTv359GjZsyOeff07lypWJi4tDq9Wi0WiYMGECnp6eODg4oNFoSEtLIzQ0FIALFy5w8OBBFi1ahJOTE46OjixcuJB9+/aRmJgIQEhICA8fPkSj0eDg4ICnpyfjx49nxYoVymyxRqPB2dkZf39/7O3t8ff3p3PnznIhixCi2DLmWHz06FHeffddmjRpglqtZuPGjXr7ZdVOCFFa5Ckofvz4MVWrVs1yv5mZGY8fP85zI549e8a2bdu4f/8+jo6OXL16laSkJFxdXZUyJiYmdOzYkZiYGODFDG/lypVxcnJSyrRv3x5TU1O9Mh06dMDExEQp4+bmxs2bN7l69SoAcXFxesfRldHVIURhUK/7M9t/QmRkzLH4/v37ODg4MH/+fL2xUke3ahcYGEhERATm5uZ4eXnpXdg3fPhw4uPjCQkJITQ0lPj4eEaMGKHs163aWVhYEBERwfz581m6dCnLli1TyuhW7by9vYmKisLb2xsfHx9OnjyZq/chhBD5laf0CQcHB7Zs2YKvr6/B4Pno0SO2bNmCg4NDrus7d+4cPXr0ID09HVNTU3788UeaNm2qBKTm5uZ65c3NzZVHlyYnJ1OjRg29e3WqVCpq1qxJcnKyUqZ27doGdej22drakpSUlOlxdHVkRzcjnRt5KSuy93r2ZaVs9+b/PWdff3FXEn7nGdtoZ2dXoMcy5ljco0cPevToAcDo0aP19r28agcvVtfs7OwIDQ3F19dXWbULDw9XJikWLlyIh4cHiYmJ2NnZ6a3amZiY4ODgwMWLF1mxYgVjx45FpVLprdoB2NvbExUVhUajYe3atfnqLyGEyI08BcWTJk3igw8+wMXFhWHDhikD/8WLFwkODiYxMZEff/wx1/XZ2dkRFRXFnTt32LVrF6NGjWL37t3K/pdvTq/Vag2C4JflVEa3XJdTmczqzqz9uaH7YBD599r2ZXT2s8H5fs851F/cFfffeWGfl8Yei7OS06qdr69vjqt2dnZ2Wa7azZs3j6tXr2Jra0tcXBx+fn56x3dzc2PVqlX5fh9CCJEbeQqKe/XqxapVq5g5cyZTpkxRAketVoulpSWrVq3Cw8Mj1/WVL1+e+vXrA9CqVStOnz7NihUrlJmC5ORk6tSpo5RPSUlRZnUtLCxISUnRC2C1Wi23b9/WK/PyjG9KSgrwvxljS0vLTMu8PHsshBDFhbHH4qwkJSUBxX/VTgghjCFPQTHAoEGD6N+/P2fOnFHuhWljY0PLli0pWzbP1el5/vw5jx8/pm7dulhaWhIZGUnr1q0BSE9P5/jx48yZMwcAR0dH0tLSiI2NVWYoYmNjuX//vvKzo6MjX375Jenp6VSsWBGAyMhIatWqRd26dQFo164dkZGRjBs3TmlHZGSk3qyHEMWd5B2XPgU5Fr+sOK/alYTUmsKUfX+U7DSq193rfi4X9vt7ldW7Vxo5y5YtS9u2bfN1y7Ivv/ySHj168Oabbyp3lYiOjmbr1q2oVCpGjRrFd999h52dHQ0bNuTbb7/F1NSUQYMGAS/yzbp168bEiRNZvHgxWq2WiRMn4u7urnTEoEGDCAwMZPTo0fj7+3Pp0iUWLVqkN7MycuRIevXqRVBQEH369GH37t1ERUURHh7+yu9NCCEKgzHG4uxYWloCxXvVrrin1hSmHNN4Snga1evudT6XS0rqY453n0hKSqJdu3Z89dVX2Zb76quvcHR0VAa63NTr5+dHu3bt8PT05PTp04SGhtK9e3cAxo8fz+jRo5k8eTIuLi7cunWL7du3K/cohhcPAGnWrBkDBgxg4MCBNGvWjJUrVyr7zczM2LFjBzdv3sTFxYXJkyczZswYxo4dq5RxcnIiODiYf/3rX3Tq1InNmzcTHBws9ygWQhQrBTUWZyfjqp2ObtUu44qcbtVOJ7NVu+PHj5Oenq6UyWrVLiNZtRNCFCZVamqqNrsCs2fP5ocffuDMmTN6AenL7t69S6tWrRg6dCgzZswwekNLspLyDakkeF37Mqf0h1TfN/P1+pIup/df1ArjvCyosTgtLY3Lly8D4O7uzoQJE/Dw8KBatWpYW1uzaNEivvvuO5YvX66s2h07dkzvQUqDBtNLoMIAACAASURBVA3ixo0byqrdhAkTsLa2Vh6kdOfOHdq1a0fnzp2VVbsxY8YwZcoU5UFKMTEx9OrVixkzZiirdl9//TXh4eEySZFLOZ2Hr/s4UdIV93EuP0rKZ3eOM8X79+9nwIAB2Q7CAFWrVmXgwIH8/PPPRmucEEKIFwpqLP7111/p0qULXbp04eHDhwQEBNClSxe+/vprQFbthBClR445xb///rvBbXKy0rRpU6PcBkgIIYS+ghqLnZ2dDZ4+l5FKpWL69OlMnz49yzLVqlXL8dZpTZs2zTFQ9/T0VO6HLIQQhS3HmWKVSsXz589zVdnz589zdX9fIYQQeSNjsRBCFKwcg2IbGxtOnTqVq8pOnz6NjY1NvhslhBBCn4zFQghRsHIMit3d3dm2bRsXL17MttzFixcJDQ2lZ8+eRmucEEKIF2QsFkKIgpVjUDx27FhMTU3p27cvoaGhPH36VG//06dPCQ0NpV+/flSpUkXvwgkhhBDGIWOxEEIUrBwvtKtZsyYhISEMGTIEPz8/xo0bR8OGDalcuTJpaWlcunSJ9PR0atWqxebNm6lRo0ZhtFsIIUoVGYuFeL3l99acIv9y9US7Vq1acfz4cdatW0d4eDgXLlzg3r17VKlShRYtWuDh4YGPjw9mZmYF3V4hhCi1ZCwWQoiCk+vHPJuZmTFhwgQmTJhQkO0RQgiRDRmLhRCiYOSYUyyEEEIIIcTrToJiIYQQQghR6klQLIQQQgghSr1c5xQLIURRkauyhRBCFDSZKRZCCCGEEKWezBQLIYQQr4F20ZUgOvtVFSFE1mSmWAghhBBClHoSFAshhBBCiFJPgmIhhBBCCFHqSU6xEEIIIUQxJ3fhKXhFNlMcFBSEi4sL1tbWNGjQgMGDB5OQkKBXRqvVEhAQQOPGjbGysqJ3796cP39er0xqaip+fn7Y2NhgY2ODn58fqampemXOnTtHr169sLKyokmTJgQGBqLVavXK7Ny5EycnJywsLHByciIsLKxg3rgQQgghhCh2iiwojo6OZtiwYezbt49du3ZRtmxZ+vfvzz///KOUWbx4McuXLycwMJCIiAjMzc3x8vLi3r17Spnhw4cTHx9PSEgIoaGhxMfHM2LECGX/3bt38fLywsLCgoiICObPn8/SpUtZtmyZUiY2NpahQ4fi7e1NVFQU3t7e+Pj4cPLkycLpDCGEEEIIUaSKLH1i+/btej+vXLkSGxsbTpw4gYeHB1qtFo1Gw4QJE/D09ARAo9FgZ2dHaGgovr6+XLhwgYMHDxIeHo6TkxMACxcuxMPDg8TEROzs7AgJCeHhw4doNBpMTExwcHDg4sWLrFixgrFjx6JSqdBoNDg7O+Pv7w+Avb09UVFRaDQa1q5dW7gdI4QQQgghCl2xudAuLS2N58+fo1arAbh69SpJSUm4uroqZUxMTOjYsSMxMTHAixneypX/P3v3Hpfj/T9w/JWccsht6aSjJeQ0ROV8yCk5k4aNnDJpM5vWGDMzKuZscshpaObQHCeykFkJY4xNDnM+pAiRUP3+8Luvr7v7jqJUej8fjx4PrutzXdfnvu7r/lzv63O9r89VTgmIAVxcXChbtqxGmcaNG2NgYKCUcXV15fr161y8eBGAQ4cOaWxHXUa9DiHym2r51Rf+CSGEEOL1FJig+Msvv6ROnTo4OTkBcPPmTQCMjY01yhkbGxMfHw9AfHw8RkZG6OnpKfP19PSoVKmSRhld61DPU2/rRdsRQgghhBBvtwIx+sS4ceOIiYkhPDwcfX19jXnPB7zw7OG7zEFwZi8ro37I7mVldK37eWfOnHnh/FctK17s7dyXZfK7AoVaQTgmnq+Dvb19PtZECCHEq8j3oHjs2LGEhYWxdetWbG1tlemmpqbAs95cS0tLZXpCQoLSq2tiYkJCQoJGAJuRkUFiYqJGmcw9vgkJCcD/eoxNTU11lsnce5xZdk986vxm8fre2n0pr2Z9Lfl9TLy1x6UQQhQh+Zo+4e/vz4YNG9iyZQvVqlXTmGdjY4OpqSl79uxRpj169Ijo6Gglh9jJyYnk5GRiY2OVMrGxsTx48ECjTHR0NI8ePVLK7NmzB3Nzc2xsbABo1KiRxnbUZZ7PVRbidUhOsBBCCFGw5VtQPGbMGEJDQwkJCUGlUnHz5k1u3rxJcnIy8CydYcSIEcyePZstW7Zw6tQpfHx8KFu2LL179waejRLRtm1bRo8ezaFDh4iNjWX06NF06NBB6bXp3bs3BgYG+Pj4cOrUKbZs2cLs2bPx8fFRepc/+ugjoqKimDlzJnFxccycOZP9+/czYsSI/Nk5QgghhBDijcq39ImQkBAAZbg1NX9/f8aOHQvAqFGjSElJwc/Pj6SkJBwdHQkLC6N8+fJK+SVLluDv70/Pnj0BcHNzY9q0acr8ChUq8MsvvzBmzBhat26NSqVi5MiR+Pr6KmWcnZ1ZtmwZ3333HQEBAVSpUoVly5bRsGHDPPv8QgghhBCi4NBLSkrKeHkx8Tok3zD3FNZ9KSkSeSu/X29aWI9L8XaRdqZoy+928EUKSxtZYIZkE0IIIYQQIr9IUCyEEEIIIYo8CYqFEEIIIUSRJ0GxEEIIIYQo8iQoFkIIIYQQRZ4ExUIIIV4oICAAlUql8ff8C5cyMjIICAigRo0amJmZ4e7uzj///KOxjqSkJLy9vbG2tsba2hpvb2+SkpI0ypw8eZJOnTphZmaGg4MDQUFBZGTIAElq8hIgIfKWBMVCCCFeyt7entOnTyt/f/zxhzJvzpw5/PDDDwQFBREZGYmxsTE9evTg/v37SpmhQ4dy/Phx1q9fz4YNGzh+/DjDhw9X5t+7d48ePXpgYmJCZGQkgYGBzJs3j/nz57/RzymEKLry7eUdQgghCo/ixYtjamqqNT0jI4Pg4GA+/fRT5WVMwcHB2Nvbs2HDBgYNGsTp06fZvXs34eHhODs7AzBr1izc3NyU8UvXr19PSkoKwcHBGBgYULNmTeLi4liwYAG+vr7KG0iFECKvSE+xEEKIl7pw4QIODg7UrVuXwYMHc+HCBQAuXrzIzZs3adOmjVLWwMCAJk2acPDgQQBiY2MpV66cEhADuLi4ULZsWY0yjRs3xsDAQCnj6urK9evXuXjx4hv4hEKIok56ioUQQrxQw4YNWbBgAfb29iQkJDB9+nTat29PTEwMN2/eBMDY2FhjGWNjY65fvw5AfHw8RkZGGr29enp6VKpUifj4eKVM5cqVtdahnmdra5tXH0+It0J28soL8lvvCgIJioUQQrxQu3btNP7fsGFD6tWrR2hoKI0aNQLQSm/IyMjQCoIze1kZ9UN2L0qdOHPmTDY/xdugTH5XQBRy+fl7edPbfpXXSktQLIQQIkfKlStHjRo1OH/+PJ07dwae9eZaWloqZRISEpSeXhMTExISEjSC4IyMDBITEzXKqHuNn18HaPdCP+9VTnyF1u8ywoR4Pfn1e1E/O1DQSU6xEEKIHHn06BFnzpzB1NQUGxsbTE1N2bNnj8b86OhoJYfYycmJ5ORkYmNjlTKxsbE8ePBAo0x0dDSPHj1SyuzZswdzc3NsbGze0CcTQhRlEhQLIYR4ofHjx/P7779z4cIFDh8+zMCBA3n48CF9+/ZFT0+PESNGMHv2bLZs2cKpU6fw8fGhbNmy9O7dG4Dq1avTtm1bRo8ezaFDh4iNjWX06NF06NBB6T3q3bs3BgYG+Pj4cOrUKbZs2cLs2bPx8fGRkSeEEG+EpE8IIYR4oWvXrjF06FASExOpVKkSDRs2JCIiAmtrawBGjRpFSkoKfn5+JCUl4ejoSFhYGOXLl1fWsWTJEvz9/enZsycAbm5uTJs2TZlfoUIFfvnlF8aMGUPr1q1RqVSMHDkSX1/fN/thhRBFll5SUpK8LiiPFZZcmsKgsO5LedtU3srvJ6oL63EpChdpR8Tryq+2srC0kZI+IYQQQgghijwJioUQQgghRJEnQbEQQgghhCjy8jUoPnDgAO+//z4ODg6oVCrWrFmjMT8jI4OAgABq1KiBmZkZ7u7u/PPPPxplkpKS8Pb2xtraGmtra7y9vUlKStIoc/LkSTp16oSZmRkODg4EBQUpg8Krbd68GWdnZ0xMTHB2dmbr1q1586GFEEIIIUSBk69B8YMHD6hZsyaBgYEa77tXmzNnDj/88ANBQUFERkZibGxMjx49uH//vlJm6NChHD9+nPXr17NhwwaOHz/O8OHDlfn37t2jR48emJiYEBkZSWBgIPPmzWP+/PlKmdjYWAYPHoyHhwf79+/Hw8MDLy8vDh8+nLc7QAghhBBCFAj5OiRb+/btad++PQA+Pj4a8zIyMggODubTTz+lW7duAAQHB2Nvb8+GDRsYNGgQp0+fZvfu3YSHhysDwM+aNQs3NzflScf169eTkpJCcHAwBgYG1KxZk7i4OBYsWICvry96enoEBwfTvHlzxowZAzwbU3P//v0EBwezdOnSN7hHhBBCCCFEfiiwOcUXL17k5s2btGnTRplmYGBAkyZNOHjwIPCsh7dcuXJKQAzg4uJC2bJlNco0btxYoyfa1dWV69evc/HiRQAOHTqksR11GfU6hBAFm2r51Rf+CSGEEC9TYIPimzdvAtrvvDc2NiY+Ph6A+Ph4jIyMNN52pKenR6VKlTTK6FqHep56Wy/ajhBCCCGEeLsV+DfaZX69Z0ZGhlYQnNnLyqgfsntZmZe9WvTMmTMvqf2rlRUvVjj3ZZn8rkCR9iaOmee3URgGqRdCFD0vu3OW3y9Cym8FNig2NTUFnvXmWlpaKtMTEhKUXl0TExMSEhI0AtiMjAwSExM1ymTu8U1ISAD+12Nsamqqs0zm3uPMsnviKyxvcikMCu2+/F1u4eenvD5mCu1xKYQQQlFg0ydsbGwwNTVlz549yrRHjx4RHR2t5BA7OTmRnJxMbGysUiY2NpYHDx5olImOjubRo0dKmT179mBubo6NjQ0AjRo10tiOuszzucpCvIjktAohhBCFW772FCcnJ3P+/HkA0tPTuXLlCsePH6dixYpYWVkxYsQIZsyYgb29PVWrVuX777+nbNmy9O7dG3g2SkTbtm0ZPXo0c+bMISMjg9GjR9OhQwel16Z3794EBQXh4+PDmDFjOHv2LLNnz+aLL75Qepc/+ugjOnXqxMyZM+ncuTPbtm1j//79hIeH58+OEUIIUeTIBbQQ+Stfe4qPHj1KixYtaNGiBSkpKQQEBNCiRQumTp0KwKhRo/Dx8cHPz4/WrVtz48YNwsLCKF++vLKOJUuWULt2bXr27EmvXr2oXbs2ixYtUuZXqFCBX375hevXr9O6dWv8/PwYOXIkvr6+ShlnZ2eWLVvGTz/9RNOmTVm7di3Lli2jYcOGb25nCCGEEEKIfKOXlJSU8fJi4nVIvmHuKaj7Unp4Cra8fnikoB6XonCRdkTkt7xqKwtLG1lgc4qFEEIIIYR4UyQoFkIIIYQQRV6BHZJNiIJEbmsKIYQQbzfpKRZCCCGEEEWeBMVCCCGEEKLIk/QJUSTIqy2FEEII8SISFAsh3npyUSSEEOJlJH1CCCGEEEIUedJTLIQQQgghivxdNQmKhRBCiDwmwzoKUfBJ+oQQQgghhCjypKdYCKQXRwghhCjqpKdYCCGEEEIUeRIUCyGEEEKIIk+CYiGEEEIIUeRJUCyEEEIIIYo8edBO5LmiPu6hEOLtJw/rClH4SVAshBBCCCFe6m3v5JL0CSGEEEIIUeRJT7F4K8itSyGEEEK8Dukpfk5ISAh169bF1NSUli1b8scff+R3lYQQosiRtlgIkR+kp/j/hYWF8eWXXzJjxgxcXFwICQnBw8ODmJgYrKys8rt6Qog8lJ07DYU9V66wKKhtsdyNEuLtp5eUlJSR35UoCFxdXalVqxZz585VpjVo0IBu3boxceLE11r3mTNnsLe3f90qFlpyMhFvgxcFxUX9N56b8rItfhFpp4TIewW9c0F6ioHHjx9z7NgxPv74Y43pbdq04eDBg6+9/qJ+sizoPwIhXldR/43nlrxui19E2ikhhOQUA4mJiaSlpWFsbKwx3djYmPj4+HyqlRBCFC3SFgsh8pMExc/R09PT+H9GRobWNCGEEHlL2mIhRH6QoBgwMjJCX19fqyciISFBq8dCCCFE3pC2WAiRnyQoBkqWLEm9evXYs2ePxvQ9e/bg7OycT7USQoiiRdpiIUR+kgft/t/IkSMZPnw4jo6OODs7s2zZMm7cuMGgQYPyu2pCCFFkSFsshMgv0lP8/3r27ElAQADTp0+nefPmxMTEsG7dOqytrV95nTIAfe4ICAhApVJp/FWrVi2/q1UoHDhwgPfffx8HBwdUKhVr1qzRmJ+RkUFAQAA1atTAzMwMd3d3/vnnn3yqbcH2sn05YsQIreO0bdu2+VTbwisv2uK3nZxrcm7mzJm0bt0aKysr7Ozs8PT05NSpUxplpH18dTNmzEClUuHn56dMKwz7U4Li5wwdOpQTJ04QHx/Pvn37aNq06SuvSz0A/eeff05UVBROTk54eHhw+fLlXKxx0WFvb8/p06eVP2n0s+fBgwfUrFmTwMBADAwMtObPmTOHH374gaCgICIjIzE2NqZHjx7cv38/H2pbsL1sXwK0atVK4zhdv379G67l2yE32+K3nZxrXs3vv//OkCFD2LlzJ1u2bKF48eJ0796dO3fuKGWkfXw1hw4dYuXKldSqVUtjemHYn/LyjjySXwPQv40CAgLYsmUL0dHR+V2VQs3CwoJp06bRv39/4NlVe40aNRg2bBhjxowBICUlBXt7eyZPniy3q18g876EZz3Ft2/f5ueff87HmomiRs41uSM5ORlra2vWrFmDm5ubtI+v6O7du7Rs2ZI5c+Ywbdo0atasyfTp0wvN/pSe4jygHoC+TZs2GtPfxAD0b6sLFy7g4OBA3bp1GTx4MBcuXMjvKhV6Fy9e5ObNmxrHqYGBAU2aNJHj9BVFR0dTtWpVHB0d+eSTT7h161Z+V0m8xeRck3uSk5NJT09HpVIB0j6+qk8//ZRu3brRsmVLjemFZX/Kg3Z5QAagz10NGzZkwYIF2Nvbk5CQwPTp02nfvj0xMTG88847+V29QuvmzZsAOo/T69ev50eVCrW2bdvSpUsXbGxsuHTpEt999x1du3Zl7969lCpVKr+rJ95Ccq7JPV9++SV16tTByckJkPbxVaxcuZLz58+zaNEirXmFZX9KUJyHZAD63NGuXTuN/zds2JB69eoRGhqKr69vPtXq7SHHae7o1auX8u9atWpRr1496tSpw86dO+natWs+1ky87eQ3/HrGjRtHTEwM4eHh6Ovra8yTfZs9Z86c4dtvv2XHjh2ULFkyy3IFfX9K+kQekAHo81a5cuWoUaMG58+fz++qFGqmpqYAcpzmEXNzcypXrizHqcgzcq55fWPHjmXjxo1s2bIFW1tbZbq0jzkTGxtLYmIijRs3xsjICCMjIw4cOEBISAhGRkbKXd2Cvj8lKM4DMgB93nr06BFnzpxRGi3xamxsbDA1NdU4Th89ekR0dLQcp7kgMTGR69evy3Eq8oyca16Pv78/GzZsYMuWLVrDfEr7mDPu7u788ccf7N+/X/mrX78+vXr1Yv/+/VStWrVQ7E9Jn8gjMgB97hk/fjwdO3bE0tJSySl++PAhffv2ze+qFXjJyclKT2V6ejpXrlzh+PHjVKxYESsrK0aMGMGMGTOwt7enatWqfP/995QtW5bevXvnc80Lnhfty4oVKxIYGEjXrl0xNTXl0qVLfPvttxgbG9O5c+d8rrl4m8m55tWMGTOGn3/+mdWrV6NSqZSc17Jly1KuXDn09PSkfcwB9djszytTpgwVK1akZs2aAIVif0pQnEd69uzJ7du3mT59Ojdv3sTBwUEGoH9F165dY+jQoSQmJlKpUiUaNmxIRESE7MtsOHr0KF26dFH+HxAQQEBAAH379iU4OJhRo0aRkpKCn58fSUlJODo6EhYWRvny5fOx1gXTi/blzJkzOXXqFGvXruXu3buYmprSvHlzli9fLvtS5Ck517yakJAQALp166Yx3d/fn7FjxwJI+5jLCsP+lHGKhRBCCCFEkSc5xUIIIYQQosiToFgIIYQQQhR5EhQLIYQQQogiT4JiIYQQQghR5ElQLIQQQgghijwJioUQQgghRJEnQfFrWLNmDSqViosXL76R7fXr149hw4a9kW0VZQEBAVqDkOe2x48f4+DgwNKlS3O0XEpKCg4ODqxcuTKPaiZy4tGjR1SvXl2+DyGKgOTkZKpWrcratWvzfFu7d+9GpVJx6NChHC23bNkyjZeR5LbNmzdjbW1NUlJSnqw/v0lQXEgcOXKE8PBwRo8erTUvNTWVRYsW0b59e6ytrTE2NqZu3bqMHDmSY8eO5UNtC76rV68SEBDA8ePH82X7JUuWxMfHh++//56UlJRsL7d48WL09PSUt/lt2bIFlUrFhg0btMp26dLlhfNsbGzIyMjZMOW//vorQUFBOucFBQXx66+/Zntd58+fR6VSMW/ePJ3zf/75Z1QqFdHR0Tmq45tUunRpPvroI6ZNm0Zqamp+V0cUEOq3e73sb82aNfld1QIhKSmJgICAAv1bB/jhhx+yfAPbzZs3GT9+PE5OTpibm2Nubk6zZs2YPHky8fHx+VDbvNGlSxdMTEyYO3duflclT0hQXEjMnTsXFxcX5XWJaomJibi5ueHv74+hoSH+/v7MmDEDDw8PYmJiaN26NVevXs2nWhdc165dIygoiBMnTmjN8/Pz48aNG3lehw8//JCEhATWr1+frfJPnz5lwYIFfPDBB5QsWRKAxo0bA2idTJ4+fcqRI0coXrx4lvNcXFzQ09PLUZ137NjBtGnTdM6bNm0aO3bsyNH63gYDBgzg5s2bbNy4Mb+rIgqIRYsWafw1btyYEiVKaE1v2rRpfle1QLh79y5BQUHExMTkd1Wy9PjxYxYtWsTAgQMpXlzzZcCxsbG4uLgQEhKCs7MzU6ZMYerUqTRq1IiQkBC6d+/+xuo5cOBAbty4gampaZ6sv1ixYgwcOJCQkBAePnyYJ9vIT/Ka50Lg9u3b7Nixg4CAAK15I0aM4OjRoyxbtoyePXtqzBs3bhzz589/U9V8axQvXlyr0csLKpWK1q1bExoayoABA15aPiIigps3b9KrVy9lmrGxMXZ2dlqB719//cXDhw/p06dPlvNcXFxy54O8hR4+fEiZMmWyVdbIyIgWLVqwZs0a+vXrl8c1E4WBp6enxv/37t3Ln3/+qTX9bZWT309eS0lJwcDA4LXX8+uvv3L79m2t82xiYiIffPABpUqVYteuXdjb22vM//rrr9/oeVhfXx99ff083Ub37t35+uuv2bp161t3TEtPcR749ddfcXV1xdzcHBsbG/r3709cXJxWuejoaFxdXTE1NaV27drMmTOH1atXa+Up79y5k8ePH9OqVSuN5Q8fPsyuXbv44IMPtH6o8OzHMWrUKCwsLJRpp06d4v3338fa2hpzc3PatWtHRESExnL79+9XbrvPnz+fOnXqYGpqSrt27fjrr780ysbHx/Pxxx9Tq1YtTExMqFGjBp6enpw8eVIpo1KpdAb07u7uuLu769zujBkzqFWrFhYWFvTr14/bt2/z9OlTJk2aRPXq1alcuTKDBw8mOTlZY5116tShV69e7Nu3j5YtW2JqakqDBg1YvXq1xnbatWsHwMiRI5Vbmeo6ZpVT/OOPP9KkSRNMTU2pWrUqw4cP5/r16xplRowYgampKfHx8QwaNAgrKytsbGwYNWoUjx490lpny5YtiYmJ4datW1rzMtu2bRvm5uZUr15dY3rjxo35999/NXK8YmJiMDc3x9PTU+c89XLPr7tPnz44ODhgbGxMnTp1mDRpEo8fP1bKeHt7s2rVKtLS0jRuAV+9ehWVSkVaWhqrVq1Spnfr1u2ln+lVHDhwAHd3dypXroylpSU9evTgzz//1Cjz3XffYWRkpLXs3r17tVIyOnbsSOPGjTl+/DidO3emcuXK+Pv7A3Du3DkGDBhA9erVld+pl5eX1p2EVq1a8ccff3Dnzp08+MTibZeens6CBQto3LgxpqamvPvuuwwfPlzrOGvbti3NmjXj77//plOnTpibm1OvXj02bdoEwMGDB2nfvj1mZmY0aNCAXbt2aSyvzjeNiYnh008/pUqVKlhaWjJ48GCdbdChQ4fo3bs31tbWmJmZ0a5dO3777bcs1+nn54e9vT3vvvsuAAkJCYwbN47GjRtjYWGBpaUl3bp14/Dhw8rycXFxvPfeewBMmjRJaT/UqYKDBw+mUaNGWnXTlTtbrVo1+vXrR2RkJK1bt8bU1JSFCxcq8yMiInBzc8PCwgILCwu6devGkSNHXv4F8ayNtLW1xdbWVmP6kiVLiI+PJygoSCsgBqhYsSITJkzQmJad/ZqV06dP4+XlhZ2dHWZmZjRs2JCvv/5amZ/VftGVeqlr365bt46WLVtiaWmJtbU1TZo0YebMmRplrKyssLOzY9u2bdmqc2EiPcW5bMOGDQwbNozatWvz1Vdfce/ePRYvXkz79u3Zu3ev8oM6ceIEPXv25J133sHPz4+SJUuycuVKnVfXMTExGBoaKg2NmvpW9fvvv5+tup09e5aOHTsq+axly5YlNDQUT09PVq5cSZcuXTTKz58/nydPnuDt7c3Tp0+ZO3cu/fv35+jRo5QoUQJ4dqvm5MmTeHt7Y21tTWJiIn/88Qdnz56lVq1aOd19AMyZM4eSJUvy8ccfc/nyZYKDg/Hx8aFy5cqcPXuWMWPGcPLkSVasWIGJiQmBgYEay1+4cIEBAwYwcOBA3n//fdavX4+vry+lSpXCw8OD6tWr8+WXXxIYGIiXl5cSHL6ovrNmzWLSpEk0adKEb7/9litXrrBkyRKio6OJiorSCKLT09Pp0aMHtWrVYtKkSRw+fJiVK1diZGSk0XgBnVGVrQAAIABJREFUNGjQAHj2HWfe/5nFxMRQr149rekuLi6sXr2a2NhY2rdvr5R1dnZWGrzM80qXLk39+vWVdaxatYqSJUvi7e1NhQoVOHjwIHPmzOHatWssWrQIgCFDhnDt2jX++OMPgoODlWVVKhWLFi1ixIgRNGnShA8//BAAMzOzF34etYcPH5KYmKg1/cGDB1rToqKi6NWrF5aWlnzxxRc8ffqU5cuX4+7uzq+//qrxmXLizp079OrVi+7du9O7d28qVqxIamoqPXr04OnTpwwbNgwTExNu3LjBb7/9xo0bNzQ+X/369cnIyCAmJgY3N7dXqoMounx9fVm3bh19+/bF29uba9eusXjxYg4dOsS+ffsoX768UvbOnTt4enoqx+uyZcsYMmQI6enpjB07loEDB9KzZ09++OEHvLy8+Pvvv3nnnXc0tvfZZ59RoUIFvvzyS/777z+WLFnCuXPn+O2335S7ZHv27MHT05P33nsPPz8/SpQowYYNG/Dw8OCnn36iQ4cOGuscPXq0cj67f/8+AGfOnGH79u1069aNKlWqcPv2bVasWEGXLl2IiorC3t4eMzMzpk6dyrhx4+jZs6ey3qpVq77Svjx9+jSDBw9m0KBBDBw4UDnnrl69mo8//pg2bdowYcIEnjx5wqpVq3B3d2fnzp1KYJ6VmJgYncH5jh07KF++vEYHz4vkdL8+76+//qJz584UL14cLy8vbGxsuHDhAtu3b+fbb7/N1vZfZOfOnXh7e+Pq6qrcvYyLi9OZ692gQQP27t372tssaCQozkVPnjzhq6++omrVqoSHh1O2bFngWY9o69atmTp1KosXLwZg6tSppKens2PHDqytrQHo378/jo6OWuuNi4vD2tpaK//z9OnTwIuDued9++23PHz4kN27d1OtWjXgWVDbpEkTxo4di7u7O8WK/e/mwb179/jjjz8oXbo0APb29nzwwQdERkbSoUMH7t69S3R0NJMnT+bjjz9WltN1RZoTqamp/Pbbb0rebFJSEmvWrKFp06Zs3bpVqePVq1dZs2YNAQEBGvvm3LlzhISEKA9DeHl50aJFC7755ht69eqFiYkJrq6uBAYG0qhRo5fe/klMTCQwMJBmzZqxadMm5aTh4uJC//79mT9/PuPHj1fKP3nyBDc3N2Xa4MGDSUpKYuXKlVpBsbrB1nUn4XlPnz7l/PnzSg/389RBfUxMjBL4Hjx4kNGjR2NoaEiNGjW05tWvX59SpUop61i+fLnGBdngwYOxtbVl+vTpTJo0CTMzM5ydnalSpQrR0dFa+8zT0xMfHx+qVKmS49tpAQEBOu8k6DJu3DgMDQ3ZvXu30hPs6emJs7Mz48ePZ/v27TnattqNGzf4/vvvGTp0qDLt2LFjXLp0idWrV9O5c2dl+hdffKG1/PPfowTFIif27dtHaGgoS5cu1UiN6tSpE66urixfvpxPPvlEmX716lVWrFih5Km2bt2aRo0aMXToUH799VclLapOnTq4u7uzceNGrVGLSpYsyZYtW5TOjapVqzJmzBjWr19P3759SUtLY9SoUbRo0YL169cr7evQoUNp06YNEydO1AreVCoVW7Zs0bh1X79+fY4ePapxXhkwYACNGjVi8eLFTJ8+HUNDQ9zd3Rk3bhx16tR57dvx586dIywsjDZt2ijT7t69y9ixY/Hy8mLWrFnKdC8vLyUHeN26dVmu8+HDh1y5ckXnA3ZxcXHUqlUrWyl3r7Jfn/f5558Dz+542djYKNMnTpz40m1nx86dO6lUqRLr16/X+M50sbGxIT4+njt37lCxYsVc2X5BIOkTuejYsWPcvHmTIUOGKAExwHvvvUerVq3YtWsXGRkZpKWlsXfvXtzc3JSAGJ7lJnp4eGit9/bt2zpv56uvxp/vRchKWloav/32Gx07dlQCYgBDQ0MGDx7MlStXNFIe4FmQrg6IAZo1awY864mFZ0/elyhRgt9//z1Xbxu///77SkAM0LBhQ+DZkHTP/1AdHR25f/8+CQkJGssbGxtrpJMYGBgwYMAArl69yt9//53j+uzdu5fU1FR8fHw0Gj53d3fs7e3ZuXOn1jJDhgzR+H/Tpk1JTExUvjM1dWOiq6f0eXfu3CEjI0PncWBnZ4epqalyNX/u3Dni4+OVk6OLi4vWvCZNmmisQx0Qp6enc/fuXRITE2nSpAnp6el5PkKHl5cXmzZt0vrLfHGl/v769++vkRphZWVFz549iY6O5t69e69Uh5IlS2rldat/V7/99ttLHyjJ7vcoRGabNm1CpVLRsmVLEhMTlT9ra2usrKyIiorSKF+hQgWN1CR7e3sqVKiAnZ2dxnMC6nbzv//+09rm4MGDlYAYnj30W7ZsWSWV7s8//+TSpUv06dOH27dvK3W6e/cu7dq1499//9UaUcHLy0srl7V06dJKm/3o0SNu375NsWLFqFevnlYqXm6pUqWKRkAMz4Y3u3//Ph4eHhr7+PHjxzRr1oz9+/e/cCQe9e86c/ublpZGSkoK5cqVy1bdXmW/ql29epXDhw/z4YcfagTEQI4fmM5K+fLluXfvntYxp8vb2uZJT3EuunTpEoBG0KlWvXp1IiMjuXfvHikpKaSkpGBnZ6dVTtc0QOcPVn3Svn///kvH1U1ISODBgwdZ1k1d/zp16ijTraysNMqpt6EOgEuVKsXEiROZOHEi9vb2NGzYkHbt2tGnTx+tZXPC0tJS4/+GhoYvnJ6UlISxsbEyvUqVKlpXuer9evnyZerWrZuj+rzoe61WrRq///67xrQSJUpgbm6uMe35fff8RYz6e81uo5ZVw+3s7MyuXbt4/PgxMTExlClTRvkunZ2dCQ0NVeYBWg/ZnTx5kokTJ3LgwAGtIeLu3r2brbplJfN4mRUqVNC42LKzs9PKl9e1nPp70JW3V716ddLT07l69apyXORE5cqVNS7E1PUaNmwYS5YsYe3atTg7O9OhQwc8PT21bkfn9HsUQu3s2bMkJSVlmS6QuW23sLDQOs4MDQ01nh2BZ+1zqVKldI4nm/k8U6pUKSwtLbl8+bJSJ3j2HEFWbt26hYmJifL/KlWqaJVJS0tjxowZrF69Wvn9qmV+NiK36KqH+vN06tQpy+WSk5Nf2sGUuf3V19fHwMBA69mWrLzKflVTX9xkHoEqN3l7e7N161a6d++OhYUFLVu2pGvXrnTs2FGr7Nva5klQ/IZkdzxYXeXeeecdnQ1b9erV2bZtG6dOndLq+cuNumX1BOvz5X19fencuTO//vore/fuZfr06cycOZPQ0FBatmz5wu2mp6frvEWT1Xazup2Tuf66fqQ5HY83u3St90W3nTKXV3+vuh4Ke94777yDnp5elgOmu7i4sGXLFo4ePUpMTAyOjo5Kr7azszOPHj1S5hUrVgwnJyeNOnTp0oXy5cvz9ddfY2tri4GBAZcvX+bjjz8mPT39hXV7kadPn2qd/BYtWpRvTyynpaXpnJ7V0+nTp09n0KBB7Nixg8jISMaPH8+MGTPYvn27xufK7vcoRGbp6emYmZlpPBD2vMy9kFm1L9lpr9Ve1kaqf/NTpkzJMj0vc2/l8xe6akFBQUybNo0PP/yQVq1aUbFiRYoVK0ZQUJDWHb6sZBV0ZfVb1lUP9ecJCQmhUqVKOpd70QgV6t+1rva3WrVqxMXFkZaW9tJRH15lv6q9ThCa3X1oYWFBdHQ0kZGR/Pbbb+zevZvQ0FDc3d21xtR+W9s8CYpzkToVIi4uTuv2zZkzZ1CpVBgaGlKuXDkMDAw4d+6c1jrOnz+vNa169eqEhYWRkZGhcXC7ubkxY8YM1q5d+9KguFKlSpQtW1Zn7uqZM2c06p9Ttra2+Pj44OPjw5UrV2jRogWzZs1SgmKVSqWzt/HSpUtaT/LmhvPnz2sF3Or9qu7BzknD8vz3mrk358yZM6+83+B/V/+6eqGfp6+vj52dXZZvT1R//zExMcTExGiMi2lra4uZmZkyr1atWlSoUEGZv2/fPm7fvk1oaKhGD3LmUUngxftN1zx9fX3lyXg1BweHLNfxIur9rD5enxcXF0exYsWU3jL1aBjJyckaQUXm3qrsqFmzJjVr1uTzzz/n+PHjtG7dmkWLFmk8kZ3d71GIzKpUqaKMc6sroMsLZ8+e1ThnpKamcvXqVWrXrq3UCZ71QOu6i5Ndv/zyC23bttV6QU/mHNgXtSsvOn9kl/rzGBsbv7SzRpcyZcpgaWmps/11c3MjMDCQbdu2vXTEndfZr+oH7U+dOpWj5SBn+7BUqVK4ubnh5uZGRkYG48aNIzg4mGPHjmk86H3hwgVMTEzy/O2vb5rkFOeievXqYWpqyrJlyzRuQZ84cYI9e/bQvn179PT00NfXp1WrVuzYsUPjoExMTNT5IgdnZ2fu3bunFUQ3bNiQ9u3bs3r1ajZv3qy1XFpaGnPnzuXq1avo6+vj6urKzp07lVs48Cz1Yvny5VhaWuZ4tIiHDx9q3Wq3tLTE2NhY44r63Xff1Uox2L59e569VOTWrVuEhYUp/09JSeHHH3+kcuXKymdU59Bm51WVrVq1olSpUixcuFDjynrHjh2cOXPmhQ9GvIx6KDFnZ+eXlnV2ds7yDYV16tShXLlybN++nTNnzmilRzg7O2c5T33xkLmnaMGCBVrbKVOmDGlpaVq50ep5mfennp4erVq10vh71UHlLSwsqF27NqGhoRo57FevXiUsLIzGjRsrqRPqE8j+/fuVck+ePGH58uXZ3t7du3d5+vSpxrQaNWpQunRprc959OhR9PT0NHrghciOXr168eTJE50vxUlPT+f27du5vs3ly5fz5MkT5f+rVq3iwYMHtG3bFgAnJyesrKyYM2eOztSA7Pby6uvra/VUR0VFaeUTq5/B0dUeV6lShfj4eP79919l2t27d1/4YFxmHTt2pFy5ckybNk3jc6tl5/O4uLhw9OhRrenDhg3D2NiYsWPH6uzoSkpK4rvvvgNeb79aWFjQsGFDfvzxRyXNRe1ld0KrVKlCTEyMxmc/dOiQ1vkk87Gmp6enpOFl/m7+/PPPt7K9k57iXFSiRAmmTJnCsGHDlNxD9ZBshoaGjBs3Tik7duxYIiMjcXNzUx56WLlypfJO8eevnNu3b0+JEiXYs2ePVk9lcHAwvXv3ZuDAgbRv355WrVpRvnx5Ll68yObNmzl37pzyxOyECROUB/yGDh2qDMl25coVVqxY8dKnTTM7e/YsXbt2pXv37tSoUUMZvPz06dNMnjxZKefl5cUnn3xCv379aNeuHXFxcWzYsEFn7ldusLOzU3r1KleuzLp16zhz5gwLFy5Ubm/Z2dlhaGjIsmXLKFeuHOXKlcPBwUFnvpaRkRFffvklkyZNolu3bnTp0oWrV6+yePFirK2t8fX1feW67t27FycnJ42c6Kx06tSJNWvW8M8//2j1turr69OwYUP27t1LsWLFlIds1JydnZXjL/NdhcaNG6NSqfD29sbb25vixYuzefNmnUOiqYc8GzNmDG3atKF48eJ06tQJAwMD6tevz549e5g3bx6VK1fGxMSE5s2b52h/vMzUqVPp2bMnbdu2ZcCAAaSlpbFs2TLS0tI0jrl27dphaWmJr68vvr6+lCxZMltPVD9v7969jB07lq5du1K1alUyMjLYuHEjDx480BoXfM+ePbi4uGjlGgvxMq1bt8bLy4uZM2fy119/0bp1a0qXLs2FCxfYunUrw4cPx8fHJ1e3mZqaSteuXenRowfnz58nJCSE2rVrKw96Fy9enPnz5+Pp6YmLiwv9+vXD0tKS69evc/DgQRISErL1MJabmxuzZs1i5MiRODk5ERcXx6pVq5RnANSMjIywtrZm3bp1WFlZUbFiRd59913q16+Pp6cnU6dOpW/fvgwbNozHjx+zcuVKzM3NtZ47yIpKpWLGjBmMGDGC5s2bK6MQXblyhaioKCpVqvTSV2536tSJDRs28N9//2mcu4yMjFizZg2enp40a9aMPn36UK9ePfT09Pj777/ZsGEDFhYWjB8//rX36/fff4+7uzstW7ZUhmS7dOkS27Zt4+DBg1kuN2jQII1h/C5fvsyPP/5IjRo1NC78vb29SUlJoXnz5lSuXJmrV6+yZMkSLC0tNQLgS5cuce7cOcaMGZOd3V+oSFCcy3r37o2BgQEzZsxg8uTJlCxZkmbNmvHNN99opArUrVuXsLAwJkyYQFBQECYmJgwbNozSpUtz/PhxjdtoRkZGuLm5ERYWpjW0jpGREeHh4SxfvpyNGzcSGBhISkoK5ubmtGzZkmXLllG5cmXg2QNK4eHhTJo0iR9++IHHjx9Tp04d1q5dqwzXlROWlpZ4eHgQFRXFhg0b0NPTw87Ojnnz5ilj1QJ88MEHXLp0iR9//JHIyEjq16/P+vXr+eqrr3K8zeywtbVl5syZfP311/z7779UrlyZuXPnaoznXKpUKRYtWsTkyZMZM2YMT548wd/fP8uHGEaPHo2RkRELFy5kwoQJlCtXjm7dujFx4sRXvn10584d9u3bx/fff5+t8h06dMDExISNGzdqDAGn1rhxY/bu3YuDg4NGegRoPliXuae4UqVKrFu3jvHjxxMQEKB8tgEDBmgFtb169eLw4cNs2rSJdevWkZGRwcmTJ7GwsGDatGl89tlnBAQE8PDhQ1q2bJnrQXGLFi3YtGkTAQEBBAUFoaenR6NGjVi5cqUy5jM8u0BdvXo1/v7+BAQEYGRkxIcffoizs7PGsFcvUrduXdq0acPOnTtZuXIlpUqVwsHBgZ9++klj2LXExER+//13Zs+enaufVRQds2fPpkGDBqxYsYIpU6agr6+PhYUFHTt21PmQ0+uaOXMma9euZerUqTx58oTOnTszbdo0jREpWrZsSUREBNOnT2fp0qXcv38fExMT6tatq3NYQl38/f15/PgxYWFhhIWFUbNmTVatWsXKlSs5ceKERtng4GC++uorvvrqK1JTUxk0aBD169fH2NiYVatWMWHCBCZOnIiFhQW+vr4UK1Ysyztnunh6emJpacmsWbOYP38+qampmJqa0qhRIwYOHPjS5d3d3alYsSIbN27UCgadnJyIjo5m3rx57Nq1S2kb1Q/rDh8+XCn7Ovu1Xr167Nq1i6lTp7J06VJSU1OxsrJ66RjJHTp0YPLkySxcuJCxY8dSs2ZNVqxYwfLlyzW+h759+7JmzRqWLl3K3bt3MTExoVOnTvj7+2sM2bl582bKly+fZy9oyk96SUlJefMEkngl/v7+rFy5Ukl5UDt8+DDt2rXj999/f+WXYhQFderUoVq1amzcuDG/q/JS8+bN44cffuDo0aPZfg3p7NmzWbRoEceOHdMYZ1jkn1mzZhESEsKRI0feWE6oEK9i2bJlfPbZZ0RFReV4FB4BgYGBhIaG8ueff2ZrXOK3UXp6Ok5OTnTu3Jlvvvkmv6uT6ySnOB9lzsdNSEjg559/pkmTJlpPsTZs2FC5FSUKv8ePH7NgwQLGjBmT7YAYUHocfvrpp7yqmsiB1NRUFi5ciJ+fnwTEQrzlRo4cycOHD3U++1NUbN26lfj4eEaNGpXfVckTRfNSp4CoW7cuffr0wd7enuvXrysPO2R1CyU0NPQN11DklZIlS/LPP//keDkDA4NXWk7kjVKlSilvlhRCvN3Kly+v8aB6UdStW7e3Mm1CTYLifNS+fXvlqqt48eLUq1ePxYsXa+V8CiGEEEKIvCU5xUIIIYQQosiTnGIhhBBCCFHkSVAshBBCCCGKPAmKhRBCCCFEkSdBsRBCCCGEKPIkKBZCCCGEEEWeBMVCCCGEEKLIk6BYCCGEEEIUeRIUCyGEEEKIIk+CYiGEEEIIUeRJUCyEEEIIIYo8CYqFEEIIIUSRJ0GxEEIIIYQo8iQoFkIIIYQQRZ4ExUIIIYQQosiToFgUOe7u7qhUqvyuhhBCCCEKEAmKC6CzZ8/y5Zdf0rRpU6ytrTE2Nsbe3p4ePXqwePFi7t27l99VLNDUQe/FixfzuyovFRAQgEqlyvZfnTp18rxOixcvRqVSMW/evBwv++6772rUt1KlSlSpUoUmTZrg7e1NWFgYqampuVLPU6dOoVKp8PT0zJX1iaIjJ785lUrFmjVr8rvKhdr48eNRqVRs3rw5v6uSI+Hh4Tk+VhITE/O0TocOHUKlUjF48OAcL9urVy+Nur7zzjtYW1vToEEDPvjgA0JCQkhKSsq1upqamlKtWrVcW9+bUDy/KyA0zZgxgylTppCeno6joyOenp4YGhqSkJBAdHQ0X3zxBYGBgZw/fz6/q1poLVy4kJSUlPyuBgDNmjXTmnbp0iV++uknrKys6Nevn8a8ChUqvKmqvZZPPvkEAwMD0tPTuX//PufOnWPHjh2sW7cOGxsbgoODadKkSX5XUxRR/v7+WtNCQ0O5fPkyffv2xdraWmPem7gYFQVP1apVtY6VJ0+eMHPmTEqUKMFnn32mtYyBgcGbqt4r69OnD1WqVAEgOTmZK1euEBMTw7Zt2/j2228JDAzUOvcUFRIUFyCzZ89m8uTJWFhYsGzZMpydnbXKHDhwgC+++CIfavf2sLKyyu8qKJo3b07z5s01pu3fv5+ffvoJa2trxo4dm081ez2jRo3CyMhIY1pycjIzZsxg1qxZeHh4sH37durVq5dPNRRFma7f1e+//87ly5fp16+f1m9SFE1Vq1bVOlaSk5OZOXMmJUuWLLTtc58+fWjbtq3GtKdPn7JmzRq+/PJLfHx80NfXL5J34SR9ooC4dOkSU6ZMoUSJEqxdu1ZnQAzQtGlTIiMjtaZHRUXh4eFBlSpVMDEx4b333sPf359bt25plR0xYgQqlYr9+/ezefNm2rRpg7m5Oba2tgwaNIirV69qLXP+/Hk++eQT6tevj5mZGTY2Njg5OTFy5EguX76slNu/fz8qlYoRI0bw33//MWDAAKpUqYKlpSU9evTg1KlTANy6dQtfX1+qV6+OqakprVq1IioqSmu76vSCNWvWEB4eTrt27ahcuTK2trZ4eXnx33//aZRXqVQcOHAAgPfee09n2kFWOcUZGRmsWLECV1dXLC0tMTc3p1mzZsybN4/Hjx9rla9Tpw4qlYqnT58yY8YMGjRogImJCbVq1WLChAm5libwIrt378bDw4N3330XY2Nj6tati7+/v85beHFxcfj4+PDee+9hamqKra0tLi4ufPLJJ9y4cQOAAQMGKBddEyZM0LjVdvTo0deqa7ly5Zg4cSIfffQRDx48YNy4cRrzb9++zcyZM+nUqRM1atRQ0ob69++vte3FixcrPc07d+7UqKc67UP9ffbt25e6detiamqKtbU1bm5uhIWFvdZnEUXXnTt3mDRpEk5OTpiZmWFlZYW7uzu//vqrVln17Xc/Pz9Onz5N3759sbW1xcrKCg8PD86cOQPAtWvXGD58OPb29piamtK2bVsOHjyotb7n0xCeb7vfffddhg0bptEWP+/hw4fMnDmT5s2bY2FhQeXKlXF1dWX16tVaZZ9PS7p48SJDhgzB3t6eihUrsnfvXuDZLfwxY8bQuHFjrK2tMTU1pWHDhnz99dda6X2tWrVi/vz5AAwcOFBnqsGAAQOyTD1Q18fPz09junqZo0ePsnz5cpo1a4aZmRkdO3bUKJeTNjK3/f333wwbNgwHBweMjY2pVq0aQ4cOVb735926dYuJEyfi5OSEhYUFVlZW1K9fn8GDB3Ps2DEAZs2aRbt27QAICwvT2JfLli17rboWL16cgQMHMnv2bAC++uorHjx4oMx/+vQpISEh9OnTh9q1ayvtaefOndm2bZvGutQpHqmpqcTHx2vU8/m0j/DwcIYPH46jo6NyXKrPuU+fPn2tz/OqpKe4gFizZg1PnjyhR48eL71VV6pUKY3/L1++nM8++wwDAwO6deuGmZkZBw8eZNGiRWzfvp0dO3bo7B1dunQpO3bsoFOnTjRt2pTDhw/zyy+/cOLECQ4cOKBs5/r167Rp04bk5GRcXV3p0qULjx8/5sqVK2zduhUPDw+t9V+6dAlXV1dq1apF//79OX36NBEREXTu3JmdO3fSq1cvKlWqRK9evbh+/TqbNm3Cw8ODw4cP66zr1q1b2b17N126dKF58+YcP36cTZs2sX//fnbt2oWdnR3w7Lao+jboRx99pKQbZCftwNvbm/Xr11O5cmX69etHiRIlCA8PZ8KECezevZuNGzdSvLj2T2bo0KFER0fTtm1bypcvT0REBPPmzePWrVssXLjwpdt9VVOmTGH69OkYGxvToUMHKlWqxPHjx1m0aBHh4eHs3r0bY2NjAC5cuECbNm1ITU2lffv2dO/enUePHnH58mXCwsL48MMPMTMzo0ePHqSkpBAREUHr1q1xcnJStmdmZpYr9fbz82PJkiX88ccfXLlyBUtLSwCOHz9OYGAgzZo1o1OnThgaGnLhwgV27NjBrl27CAsLU3rwHB0dGTJkCEuXLsXOzo7evXsr61fXOS0tjU8//RRHR0eaN2+OiYkJt27dYufOnQwePJj//vuPzz//PFc+kygaLly4QJcuXbh8+TLNmzenbdu23L9/n/DwcPr168e3337LJ598orXcmTNnaNeuHY6OjnzwwQf8/fffREREcOLECbZu3UrXrl2xtramT58+XLx4kW3bttGzZ0+OHj2KiYmJ1vrWrl3L7t276d69O61ateLIkSOsX7+e/fv3ExERodGG3rlzhy5duvD333/j6OhI//79SUtLIyIiAl9fX/766y+mT5+utY0bN27Qrl07zMzM6NmzJ48ePaJ8+fIALFmyhKioKJo0aYKrqytPnjzhyJEjzJ07l8jISCIiIpQ0Ai8vL0JDQ4mNjaV79+5Ur15d2UZupBoEBATw+++/4+bmhqurq8a8nLSRuW3Tpk14e3tTrFgx3NzcsLKy4uLFi2zatImdO3eyefNmGjRoAEBqaipubm6cPXuWZs3DdpQ4AAAgAElEQVSa0a5dO4oVK8a1a9fYv38/Li4u1KtXDxcXFz788ENWrVqFg4MDXbt2VbZXv379XKl3nz59CAoK4vz580RGRtKlSxfgWQ+5n58fjRo1olWrVhgbG3Pz5k3Cw8P54IMPCAwM5KOPPgKgcuXK+Pv78/3331O6dGl8fX2V9desWVP593fffUdqaiqOjo6Ym5tz//599u/fz4QJEzh48KDOi7a8JkFxAREdHQ1A69atc7TcpUuX8Pf3p0yZMuzevRsHBwdl3nfffcf333/P559/zrp167SWjYyMZN++fdSoUUOZNnToUDZs2MD27dvp2bMnAJs3byYpKYkpU6YwcuRIjXWkpqby5MkTrXUfOHCAyZMn8/HHHyvTPv30U6Untn///kydOhU9PT0AateuzeTJk1mwYAEBAQFa6wsPD+fnn3+mQ4cOyrR58+YxYcIE/Pz8lJ6/sWPHKrdBR4wYgY2NTbb244YNG1i/fj21atVix44dGBoaAjBx4kR69+7Nvn37WLBggc4T3sWLFzl48KDS+zxhwgSaNWvGunXr+Oabb3ItmHxeREQE06dPp3nz5oSGhionK3h2sfP5558zfvx4Fi1aBMDGjRtJTk5mzpw5DBw4UGNdKSkppKenA9CjRw9u3bpFREQEbdq00fj+couRkRE1a9bkxIkTHDlyRAmK33vvPeLi4rR68c+dO0fbtm2ZMGGC0lPl6OiIgYEBS5cu1XmLE0BfX59jx45ha2urMf3hw4d07dqVadOm4eXlpZXmIURWhg4dytWrVwkNDaVTp07K9Dt37tCxY0cmTZqEu7u7cpGutnfvXmbNmsWgQYOUacOGDWP9+vW4urri7e3N+PHjlXnffvstM2fOZPHixRrT1cLDw9myZYtGmkdgYCCBgYGMGzeOVatWKdM///xz/v77b6ZNm4a3t7cyPSUlBQ8PD5YsWULnzp1p2bKlxjb++usvBg0axIwZMyhWTPOm8ldffcXChQu1pqvb5FWrVinb8vLy4uzZs8TGxtKjRw+6deuW9Q5+BTExMezZs0cj2Iact5G5SX3+MTEx0eqUio2NpVOnTvj4+BAdHY2enh4HDhzg7NmzeHl5KT21amlpady/fx+Axo0bU7x4cSUozov0DT09PZo1a8b58+c5cuSIEhSXK1eO48ePa3Va3bt3Dzc3N6ZMmUL//v0pX748FhYWjB07ltmzZ1O2bNks67lq1Solt1ktPT2dUaNGsWrVKvbv3//GU5kkfaKAuHnzJvDsCisn1q1bx+PHjxkyZIhGQAzPeuTMzc3ZtWsX165d01p2+PDhGgExoARMf/75pzJN3fCVKVNGax2lSpWiXLlyWtNtbW21Aug+ffoAzw76CRMmKAExoOQunThxQufnbNGihUZADM/SQCwtLYmMjNT5+XJCfUU6ceJEJSAGKFmyJFOnTgVg5cqVOpf95ptvNAK5smXL0qdPH9LT05XbXrktODgYgLlz52o09gBDhgzBzs6OzZs3Kykc6u9QV8+MgYEBZcuWzZN6ZsXc3BxAI72nYsWKOtNa7OzscHNz49ixY9y+fTvb29DT09MKiOHZcTx48GBSU1OVVBshXiY2NpbDhw/j4eGhERDDs2N3zJgxpKWlsX79eq1la9asqREQw//aw+LFi2s9J/Ky9rBjx45awcKnn36KsbEx27dvV0YQuHbtGr/88guNGzfWCIjh2e9+woQJAPz8889a2yhbtiwTJ07UCnwBbGxsdE4fPnw4JUuW1Jnil1e8vb21AmLIeRuZm1asWEFKSgqTJ0/WCiKdnJzo3r07//77L3/99Rfw4vZZX1//jQ8hqu7Ieb59Ll68uM67uIaGhnh5eXH//n0OHTqUo+1kDojh2b7w8fEBYM+ePTlaX26QnuICIiMjA0AjUMwO9Y+qRYsWWvNKlSqFi4sLv/zyC8ePH9cKuHU95GRhYQGgMSyLm5sbkydPxs/Pj927d+Pq6kqjRo2oVauWzoYRnvX8Zp6n/qG9++67WgG2el5WwW3Tpk21phUvXhxnZ2euXLmi8/PlhHo/6roqrV27NsbGxpw7d47k5GSti4Ds7sfcdPDgQQwMDFi7dq3O+RkZGTx69IhLly5hb2+v9IyOHDmS7du3K6kRDg4OOT7mclPmbUdFRbF48WKOHDlCQkKC1l2I69ev884772R7/f/99x9z5swhKiqKa9eu8ejRI631CZEd6hzf27dv67ybpT6WdOWL6kqJMzU1BaB69eqULFlS57yctIelS5emQYMG7Ny5kxMnTtC8eXMOHTpERkYGaWlpOuv88OHDLOtctWrVLIOx1NRUQkJC2LRpE6dPn+b+/fvKOQze7O/K0dFR5/SctpG5KSYmRqnDv//+qzVf/b3GxcVRr149nJycsLW1JTg4mJMnT9K+fXucnZ2pV68eJUqUyNW65UTm9jkuLo45c+Zw4MABbty4odWe5rRzKikpiXnz5hEeHs6FCxc0cphfZX25QYLiAsLMzIy4uDidD7m9iPqhBl15Z/C/xlXX2MbP94iq6evrA89u2ahZWVkRGRlJUFAQERERbN++Xdmmt7c3o0ePVpZTy3xl/vy6dc1T5+rqSsVQb0sXdT7Y647dfO/ePQwNDbPMcTM1NeXWrVvcu3dPKyjWla+saz/mltTUVKXxCAoKemFZdTk7Ozt+++03pk2bRmRkpDJeqLm5OT4+Pvj6+r7R4Fh90qxUqZIy7eeff+ajjz6iXLlytGrVChsbG8qUKYOenh579uwhNjZW5wOPWfn3339p3749Dx48UPL0ypcvj76+PufOnWPDhg05Wp8o2tR3KSIiIoiIiMiyXHJystY0XW2tus170bysHjbKqj1UT1e3h+o6x8bGEhsbm2WdMwcj8L9zR2YZGRn07duXyMhI7Ozs6Nq1KyYmJkrwNnfu3Df6u9JVz1dpI3PTnTt3AF76TIl622XKlGHXrl0EBQWxfft25aFzQ0ND+vbty4QJE3Tekc0r6gevn2+fjx07hru7O6mpqbRo0YKOHTtSvnx5ihUrxj///MOWLVty9L3fv3+ftm3bcvbsWerVq4enpyfvvPMO+vr6PHjwgPnz5+dL+yxBcQHRuHFjoqKi2LdvHwMGDMj2cuoGNT4+Xud8dVqGroY3J+zt7QkJCSEtLY2TJ08SFRVFSEgI3333Henp6Xk+TFxWn099e+d1P5+hoSF37twhJSVFZ2CcW/sxN5QqVYrSpUujUql09kJkpWbNmqxYsYKnT5/+H3v3Hh/Tve9//DWNWyQqGhGySRwMkmC7RGharaBI1T3dOE7PrtYOInXpiaJVLdtpxF3bSF3KUdVdEnSHuuz2kdAiRC8axY742VI0TZq0QZCWmN8fTtYxErmQy8S8n49HHsz6fmfNZ82sfOeT7/p+v4vvv/+effv2sXr1al5//XUeeuihQsNdKkp2draxCsntvTzz5s2jXr167Nu3r9BltTNnzhT7pV6U5cuXc+nSJdavX19oHOP69euJjY29xyMQe1Twu79s2TKef/75Ko3lbu1hwfaCWAv+ffnll5k9e3aZXuNufyTv37+f+Ph4+vfvz0cffWR1RfC3334rctJeSQr2UdQfARcvXixznPfaRpaXgvf95MmTxlCxkjRq1IjFixezePFiUlNTOXDgAOvWrWPlypX88ssvrF69uiJDNlgsFvbv3w+An5+fsX3JkiVcuXKF2NjYQsu5RUVFERcXV6bX+dvf/sbp06eZMmUKb775plXZd999Z6xYUtk0pthGjB49mpo1axIXF2ckDHdz+xioP/7xj8CtpdCKqldwya+g3v1ycHCgQ4cOhIWFGUnFncuxVISixn7euHHDOL4OHTpYxQgYk8dKo+D9KWgMbnfixAl+/vlnWrVqVal/rRfHz8+Pn3766Z5u4lKjRg06duzI5MmTjbHUt3+GFdnLDbBw4ULy8/N57LHHjEl2N27c4Ny5c7Rr165QQnz9+vUiE+KS4vzXv/7FQw89xIABAwqVaSyxlFXXrl0BOHjwYBVHUvT5m5eXxzfffMNDDz1kDNcoSGoKJnKXh4JlMJ955plCQ+QSExOLbHdL+l0tGKZR1JXS2+e3lMX9tJH3q+Bcudf33Ww28/zzz7Nr1y6cnZ359NNPjeEpFd0+b968mTNnzuDm5mY18f/MmTPUrVu3UEIMd29PHRwc7hpnwedy+woaJe2vMigpthGenp689tprXL9+nT/96U93HbB+6NAhq5PyT3/6E7Vq1eL999/n1KlTVnWXLFnCjz/+SN++fUv912pRvv76a6On9HYF2+rUqXPP+y6tL774gj179lhti46O5vz58wQGBlqNJy5YTeBua3YW5bnnngNuzfq+/fLn9evXee211wDK1INf0QqWuAkLCyvys7l27ZrVOqdJSUlkZWUVqlfQs3T7Z1jw/p0/f75cY87NzWXOnDm899571K1b15jACLcSdQ8PD/75z39axXnz5k3mzJlT5C27S4rT09OTmzdvFmpgd+zYUeRkKJHiPPbYY3Tq1IktW7YUOTENbg3ZqYzxtLt37y7UEbJs2TJ+/vlnnn76aSPJ9PLyYtCgQSQmJrJ8+fIiE5S0tLQyJY4Fd/u78/XT09OZMWNGkc8p6Xe1IHm/c63d//f//h9LliwpdWy3K2sbWZ5efPFF6tSpw+zZs4vs5MrPz7dal/+f//xnkZ9BTk4Ov/32G7Vq1TJ6xAvmVJR3+3zjxg0++OADpk6dCtxazu72Cdienp5cvXqVr7/+2up5mzdvLnKN7oJYc3JyjNUzbne38+j48eP3dLWhvGj4hA2ZMmUKN27c4K233uKpp57Cz8+Pzp07U69ePbKzs0lKSuLEiRNWS0h5enoSGRnJyy+/TGBgIEOGDMHd3Z3Dhw9z4MAB/vCHP7B48eL7iismJoY1a9bw6KOP0rJlSx555BHOnTvHzp07eeihh4pcpqy8BQUFMXr0aAYNGkTz5s1JTk7m888/55FHHmHRokVWdQMDA9m2bRuTJ09m8ODBODk5Ub9+/UKzr283fPhwdu/eTUxMDN27d2fAgAHGOsWnT5/mySefZMKECRV9mKXWv39/ZsyYwfz58+ncuTN9+vTBy8uLK1eucO7cOQ4ePEi7du3YvXs3cGvpm48//pjHHnuMFi1a4OLiYqwBXKNGDaul1wICAqhduzYbN24kPz+fJk2aYDKZjLWMS2P58uU4OjpisVi4fPkyZ86c4eDBg1y+fBlPT0+io6MLXb2YMGGCsZzdwIEDjaWKzp07x1NPPVVoHGfDhg1p3749x44d47nnnsPHx4caNWrQs2dPunbtSkhICFu3bmXkyJEMHjwYNzc3vv/+e/bu3cuQIUPYtm3bfX4KYk9MJhPr1q1jyJAhjBs3jnfffZcuXbpQv3590tPT+f777zlx4gSffPLJfXVClEZQUBDDhg1jyJAhNGvWjK+//pp9+/bh7u5eaELd22+/zQ8//MAbb7zBhg0b6N69O25ubqSnp5Oamso333zD8uXLadGiRale+7HHHqNDhw5s2rSJc+fO0bVrV9LT0/nHP/5Bp06djPGot+vZsycmk4klS5Zw4cIFY6xqWFgYjo6ODB06lEWLFvHhhx/yr3/9i86dO3PhwgVjHf0tW7aU+T0qaxtZnpo3b86qVasICQnh8ccfp3fv3rRq1QqLxcKFCxdISkoiJyfHSNYPHjzIyy+/jJ+fn3FDq59//pmdO3dy/fp1q9tJe3l50bJlS77++mteeOEFWrdujYODA0899VSp7xC6efNmo+Pt6tWrnDt3jsTERDIyMnj44YeJiooyVkcpMH78eHbt2sWgQYMYMmQIDRo04LvvvmP//v0MGTKETz75pNDr9OrViw8++IDg4GB69OhB7dq1adu2LQMHDuTZZ59l6dKlzJkzh0OHDtG6dWvOnj3L7t27GTBgQJXdYElJsY0JDw9nyJAhrFmzhi+++IKPP/6Yq1ev4uLigo+PD5GRkYXuST5mzBhatGjBO++8w6effsqVK1do0qQJISEhhIeH33VSRmkFBwdz/fp1Dh8+zN///neuXr2Ku7s7/fr1Y+LEiXed/VuennnmGZ5//nkWLVrE7t27qVmzJoMHD+aNN94o1Jj/x3/8BxcuXGDz5s1ERUVx/fp1mjVrVmxSDLBy5UoCAgLYsGEDGzZs4ObNm7Rs2ZK5c+cyfvz4Kp0FXJQZM2bQo0cPVq1axeHDh9m5cyf16tWjSZMm/Pu//7vVDS3+/d//HQcHB5KSkjh69Ch5eXk0btyYgQMHEhYWZjX8pFGjRmzYsIGFCxeyefNmYzJInz59Sp0Uv/3228CtHmBnZ2eaNGlC//796d+/PwMGDCjy6kJYWBjOzs6sXr2aDz/8kLp16/L444/zP//zP6xfv77IyU3r1q3jtddeY//+/ezYsQOLxUKdOnXo2rUrfn5+bNu2jbfeeoudO3disVho3749mzdvJj8/X0mxlFnz5s354osvWLlypXHFIT8/n0aNGtG6dWteeOEF44YMFWnEiBGMHDmSpUuXsmPHDurUqUNwcDCzZ88utGyWi4sLe/bsYd26dWzdupW4uDjy8vJo1KgRzZs3Z+7cuYXuAlecmjVrsmXLFv76178SHx9vrDU+btw4Xn755UJLg8Kt4W0rVqxgxYoVfPDBB1y7dg2AF154wVgScvv27cyePZuEhAS+/vprWrduzbJly2jfvv09JcVQtjayvA0aNAhvb2/effdd9u3bxxdffEHt2rWNO7gWrP8L8OSTTxIWFsbBgwf5xz/+wcWLF3Fzc6NLly785S9/Me5iB7f+ONuwYQOzZ88mPj6ebdu2YbFYcHV1LVNSDLfGcjs7O+Pq6oqfnx89e/YkODiYBg0aFHrOE088QWxsLJGRkcTFxWEymejYsSOffPIJWVlZRSbFc+fO5ebNm3z++ed89dVX5OfnM2zYMAYOHIibmxs7d+7kzTffJCkpib1799KyZUveeuutKk2KTTk5OZaSq4lUjYiICCIjI4mKimL06NFVHY6ISJWZNWsW7777bpGTR0Xk/mlMsYiIiIjYPSXFIiIiImL3lBSLiIiIiN3TmGIRERERsXvqKRYRERERu6ekWERERETsnpLiSpCamlrVIVRLet/ujd63e6P3TaB6ngfVLebqFi9Uv5irW7xgGzErKRYRERERu6ekWERERETsnpJiEREREbF7SopFRERExO4pKRYRERERu6ekWERERETsnpJiEREREbF7Nao6ABGpeC7LXIotz5mSU0mRiIgUTe2UVDX1FIuIiIiI3VNSLCIiJfrpp58YP348LVu2xN3dnW7durF//36j3GKxEBERQdu2bWncuDEDBgzg5MmTVvvIyckhJCQET09PPD09CQkJISfHuvfv+PHjPP300zRu3Bhvb28iIyOxWCyVcowiYt+UFIuISLFycnLo168fFouFzZs3c/jwYRYsWICbm5tRZ/ny5URFRREZGUl8fDxubm4MHTqUy5cvG3XGjh1LcnIyMTExxMbGkpyczLhx44zyS5cuMXToUBo1akR8fDzz58/nnXfe4d13363U4xUR+6QxxSIiUqy3336bxo0bs3LlSmNb8+bNjf9bLBaio6OZMmUKgwcPBiA6Ohqz2UxsbCxjxowhJSWFzz//nN27d9OtWzcAli5dSlBQEKmpqZjNZmJiYrh27RrR0dE4Ojri4+PDqVOnWLFiBWFhYZhMpko9bhGxL+opFhGRYn366ad06dKFMWPG0KpVKx5//HFWrVplDGtIS0sjIyODXr16Gc9xdHQkICCAw4cPA5CUlISzs7OREAN0794dJycnqzqPPvoojo6ORp3evXuTnp5OWlpaZRyqiNgx9RSLiEixzp49y/vvv09oaChTpkzh2LFjTJ8+HYCQkBAyMjIArIZTFDxOT08HIDMzE1dXV6veXpPJRMOGDcnMzDTqeHh4FNpHQdntvdMFUlNTy+cgK3ifFa26xXwv8Zb0nK6fdi22/MiAI2V+zbK8vq2pbvFC+cZsNpvL/BwlxSIiUqybN2/SqVMn3njjDQD++Mc/cubMGdasWUNISIhR787hDRaLpVASfKeS6hT0Rt9t6MS9fPEVp2AoR3VS3WK+13jv9xjv5/n28h5XJVuIWcMnRESkWO7u7rRp08ZqW+vWrTl//rxRDhg9vgWysrKMnt5GjRqRlZVltZKExWIhOzvbqk5R+4DCvdAiIuVNPcUiD4CSFr0XuR/du3fn9OnTVttOnz5Ns2bNAPDy8sLd3Z2EhAQ6d+4MQF5eHomJicydOxcAf39/cnNzSUpKMsYVJyUlceXKFeOxv78/b775Jnl5edSpUweAhIQEmjRpgpeXV6Ucq4jYL/UUi4hIsUJDQzly5AiLFi3izJkzfPLJJ6xatYqxY8cCt4Y2TJgwgWXLlhEXF8eJEycIDQ3FycmJ4OBgANq0aUOfPn2YOnUqR44cISkpialTp9KvXz/jkmlwcDCOjo6EhoZy4sQJ4uLiWLZsGaGhoVp5QkQqnHqKRUSkWJ07d2bjxo3MnTuXhQsX0rRpU1599VUjKQaYPHky165dY9q0aeTk5NClSxe2bt1KvXr1jDqrV69m+vTpDBs2DICgoCAWLFhglNevX59t27YRHh5OYGAgLi4uTJw4kbCwsMo7WBGxW1XaU3zgwAFGjhyJt7c3Li4ubNy40ap8woQJuLi4WP306dPHqs5vv/3GtGnTaNGiBR4eHowcOZILFy5Y1Tl37hwjRozAw8ODFi1a8Morr/D7779b1dm/fz9PPvkk7u7u/PGPf2Tt2rUVc9AiItVQv379OHDgABkZGXz99deMHz++0AS5mTNnkpKSQkZGBjt37sTHx8dqHw0aNGDVqlWcO3eOc+fOsWrVKlxcrIf++Pr6smvXLjIyMkhJSWHGjBnqJRaRSlGlSfGVK1fw8fFh/vz5VutS3q5nz56kpKQYPzExMVblM2fOZPv27bz//vvs3LmTy5cvM2LECPLz8wHIz89nxIgR5ObmsnPnTt5//33i4uJ47bXXjH2cPXuWP/3pT/j7+/PFF1/w8ssv88orr/D3v/+94g5eRERERGxGlQ6f6Nu3L3379gVujVkrSu3atY2ZzXe6ePEiGzZsICoqisDAQABWrlxJ+/bt2bt3L7179yY+Pp6TJ09y7NgxmjZtCsCcOXOYNGkSr7/+Og8//DDr1q2jcePGLFy4ELg19u2rr77i3XffNe7OJCIiIiIPLpufaJeYmEirVq3o0qULkyZN4ueffzbKjh49yvXr163uotS0aVPatGljdYekNm3aGAkx3LpD0m+//cbRo0eNOrfvo6DOt99+y/Xr1yvy8ERERETEBtj0RLs+ffowcOBAvLy8+OGHH5g3bx6DBg1i79691K5dm8zMTBwcHHB1dbV6npubm9Udku5c39LV1RUHBwerOj179iy0jxs3bpCdnU3jxo0r7iBFbEBJS7rlTMmppEhERCqG2jkpiU0nxcOHDzf+7+vrS8eOHWnfvj179uxh0KBBd31eae6idOf2st5FCcp2O8LqeLtFW6D3zTbYy+dQXsdZ1XdlEhGRsrPppPhOTZo0wcPDgzNnzgC37n6Un59PdnY2DRs2NOplZWUREBBg1CkYSlEgOzub/Pz8Eu+iVKNGDR555JG7xlPaLz5buHVhdaT3zXbYw+eg801ExL7Z/Jji22VnZ5Oenm5MvOvYsSM1a9YkISHBqHPhwgVSUlKs7pCUkpJitUxbQkICtWvXpmPHjkadvXv3Wr1WQkICnTp1ombNmhV8VCIiIiJS1ao0Kc7NzSU5OZnk5GRu3rzJ+fPnSU5O5ty5c+Tm5jJr1iySkpJIS0vjyy+/ZOTIkbi5ufHMM88AtxZ6f+6555g9ezZ79+7lu+++Y9y4cfj6+hpjhHv16oW3tzfjx4/nu+++Y+/evcyePZv//M//5OGHHwZgzJgx/Pjjj8yYMYOUlBQ++OADPvroIy0YLyIiImInqnT4xLfffsvAgQONxxEREURERDBq1CiWLFnCiRMn+Pjjj7l48SLu7u706NGDdevWWd0h6a233sLBwYExY8aQl5fHE088wXvvvYeDgwMADg4ObNq0ifDwcPr370+dOnUIDg5m3rx5xj6aN2/O5s2befXVV1m7di2NGzcmMjJSy7GJiIjYCU3EkypNinv06EFOzt1Psq1bt5a4jzp16rBw4UJjjeGiNGvWjE2bNhW7n8cff5wvvviixNcTERERkQdPtRpTLCIiIiJSEZQUi4iIiIjdU1IsIiIiInZPSbGIiIiI2D0lxSIiIiJi95QUi4iIiIjdU1IsIiIiInZPSbGIiIiI2D0lxSIiIiJi95QUi4iIiIjdU1IsIiLFioiIwMXFxeqndevWRrnFYiEiIoK2bdvSuHFjBgwYwMmTJ632kZOTQ0hICJ6ennh6ehISEkJOTo5VnePHj/P000/TuHFjvL29iYyMxGKxVMoxiojUqOoARETE9pnNZnbs2GE8dnBwMP6/fPlyoqKiiIqKwmw2s2DBAoYOHcqRI0eoV68eAGPHjuX8+fPExMRgMpmYNGkS48aNY9OmTQBcunSJoUOHEhAQQHx8PKmpqUycOJG6devy0ksvVe7BihTBZZlLseU5U3KKLRfbp6RYRERKVKNGDdzd3Qttt1gsREdHM2XKFAYPHgxAdHQ0ZrOZ2NhYxowZQ0pKCp9//jm7d++mW7duACxdupSgoCBSU1Mxm83ExMRw7do1oqOjcXR0xMfHh1OnTrFixQrCwsIwmUyVerwiYn80fEJEREp09uxZvL296dChAy+88AJnz54FIC0tjYyMDHr16mXUdXR0JCAggMOHDwOQlJSEs7OzkRADdO/eHScnJ6s6jz76KI6Ojkad3r17k56eTlpaWiUcoYjYO/UUi4hIsfz8/FixYgVms5msrCwWLlxI3759OTkDaPIAACAASURBVHToEBkZGQC4ublZPcfNzY309HQAMjMzcXV1tertNZlMNGzYkMzMTKOOh4dHoX0UlDVv3ryiDk8qSUnDD0SqmpJiEREp1lNPPWX12M/Pj44dO/LRRx/RtWtXgELDGywWS6Ek+E4l1SmYZFfc0InU1NRSHkXpVcQ+K1p1jLmsbP0YbS0+W4unNMozZrPZXObnKCkWEZEycXZ2pm3btpw5c4ZnnnkGuNWb27RpU6NOVlaW0dPbqFEjsrKyrJJgi8VCdna2VZ2CXuPb9wGFe6Fvdy9ffMUpGONcnVTHmO+FrR+jLcVXHc8JW4hZY4pFRKRM8vLySE1Nxd3dHS8vL9zd3UlISLAqT0xMNMYQ+/v7k5ubS1JSklEnKSmJK1euWNVJTEwkLy/PqJOQkECTJk3w8vKqpCMTEXumpFhERIo1a9Ys9u/fz9mzZ/nqq6/485//zNWrVxk1ahQmk4kJEyawbNky4uLiOHHiBKGhoTg5OREcHAxAmzZt6NOnD1OnTuXIkSMkJSUxdepU+vXrZ/QMBQcH4+joSGhoKCdOnCAuLo5ly5YRGhqqlSdEpFJUaVJ84MABRo4cibe3Ny4uLmzcuNEou379Om+88QYBAQF4eHjQpk0bxo4dy7lz56z2MWDAgEKLyr/wwgtWdbRovIjIvfvxxx8ZO3YsXbt25bnnnqNWrVp89tlneHp6AjB58mRCQ0OZNm0agYGB/PTTT2zdutVYoxhg9erVtGvXjmHDhjF8+HDatWvHypUrjfL69euzbds20tPTCQwMZNq0aUycOJGwsLBKP14RsU9VOqb4ypUr+Pj4MGrUKMaPH29VdvXqVb777jvCw8Np3749ly5dYtasWQQHB3PgwAFq1Pi/0EePHs3s2bONx3Xq1LHalxaNFxG5d2vXri223GQyMXPmTGbOnHnXOg0aNGDVqlXF7sfX15ddu3bdU4wiIverSpPivn370rdvXwBCQ0OtyurXr88nn3xitW3p0qV0796dlJQUfH19je1169YtclF5QIvGi4iIPAC0pJtUtGo1pvjy5csAuLhY/2Js2bKFFi1a0L17d2bNmmXUAy0aLyIiIiIlqzZLsv3+++/MmjWL/v3784c//MHY/uyzz9KsWTMaN27MP//5T+bMmcP3339v9DJX5KLxZVlPrzquF2gL9L7ZBnv5HMrrOKt6WSERESm7apEU37hxg5CQEC5evMjf/vY3q7Lnn3/e+L+vry/Nmzend+/eHD16lI4dOwIVt2h8ab/4bGHtvepI75vtsIfPQeebiIh9s/nhEzdu3ODFF1/k+PHj/P3vf+eRRx4ptn6nTp1wcHDgzJkzgPWi8QXKa9F4EREREXkw2HRSfP36dcaMGcPx48fZvn37XSfT3e748ePk5+cbdbVovIiIiIiUpEqT4tzcXJKTk0lOTubmzZucP3+e5ORkzp07x40bN/jzn//MV199xZo1azCZTGRkZJCRkcG1a9cA+Ne//kVkZCTffvstaWlp/OMf/+DFF1+kQ4cOdO/eHdCi8SIiIiJSsiodU/ztt98ycOBA43FERAQRERGMGjWKGTNmsHPnTgB69uxp9byoqChGjx5NzZo12bdvH++99x5XrlzhD3/4A3379mXGjBk4ODgY9VevXs306dMZNmwYAEFBQSxYsMAoL1g0Pjw8nMDAQFxcXLRovIiIiIgdqdKkuEePHoXuLHe74soAmjZtaiTOxdGi8SIiIiJSHJseUywiIiIiUhmUFIuIiIiI3VNSLCIiIiJ2T0mxiIiIiNg9JcUiIiIiYveUFIuIiIiI3VNSLCIiIiJ2T0mxiIiIiNg9JcUiIiIiYveUFIuIiIiI3VNSLCIiIiJ2r0ZVByAiIiLVn8syl6oOQeS+qKdYRERKbfHixbi4uDBt2jRjm8ViISIigrZt29K4cWMGDBjAyZMnrZ6Xk5NDSEgInp6eeHp6EhISQk5OjlWd48eP8/TTT9O4cWO8vb2JjIzEYrFUynGJiCgpFhGRUjly5Ajr16/H19fXavvy5cuJiooiMjKS+Ph43NzcGDp0KJcvXzbqjB07luTkZGJiYoiNjSU5OZlx48YZ5ZcuXWLo0KE0atSI+Ph45s+fzzvvvMO7775baccnIvZNSbGIiJTo4sWL/OUvf+Gdd97BxeX/LpNbLBaio6OZMmUKgwcPxsfHh+joaHJzc4mNjQUgJSWFzz//nGXLltGtWzf8/f1ZunQpe/bsITU1FYCYmBiuXbtGdHQ0Pj4+DB48mMmTJ7NixQr1FotIpVBSLCIiJSpIep988kmr7WlpaWRkZNCrVy9jm6OjIwEBARw+fBiApKQknJ2d6datm1Gne/fuODk5WdV59NFHcXR0NOr07t2b9PR00tLSKvLQREQATbQTEZESrF+/njNnzrBy5cpCZRkZGQC4ublZbXdzcyM9PR2AzMxMXF1dMZlMRrnJZKJhw4ZkZmYadTw8PArto6CsefPmRcZW0NNcnipinxWtOsb8oLG1z8DW4imN8ozZbDaX+TllSoojIyMZOHAgPj4+RZafPHmSuLg4pk+fXuZARESk/JRXe52amsrcuXPZtWsXtWrVumu92xNeuDWs4s4k+E4l1SkYNlHUcwvcyxdfcVJTU8t9nxWtOsb8IOr6addiy3Om5BRbXp6q4zlhCzGXafjE/PnzOX78+F3LT548SWRk5H0HJSIi96e82uukpCSys7N59NFHcXV1xdXVlQMHDrBmzRpcXV155JFHAIwe3wJZWVlGT2+jRo3IysqyGhtssVjIzs62qlPUPqBwL7SISEUo1zHFubm51KxZs9T1Dxw4wMiRI/H29sbFxYWNGzdalVfmMj9///vf6datG40aNaJbt25s3769jEcvIlJ9lLa9HjBgAAcPHuTLL780fjp16sTw4cP58ssvadWqFe7u7iQkJBjPycvLIzEx0RhD7O/vT25uLklJSUadpKQkrly5YlUnMTGRvLw8o05CQgJNmjTBy8urvA5bROSuShw+8f3333Ps2DHjcWJiIjdu3ChULycnh7Vr19KqVatSv/iVK1fw8fFh1KhRjB8/vlB5wTI/UVFRmM1mFixYwNChQzly5Aj16tUDbi3zc/78eWJiYjCZTEyaNIlx48axadMm4P+W+QkICCA+Pp7U1FQmTpxI3bp1eemll4BbjfMLL7zAzJkzGThwINu3b+f5559nz549+Pn5lfp4RESqUkW01y4uLlarTQDUrVuXBg0aGEMzJkyYwOLFizGbzbRq1YpFixbh5OREcHAwAG3atKFPnz5MnTqV5cuXY7FYmDp1Kv369TMulwYHBxMZGUloaCjh4eGcPn2aZcuW8corrxQ7fEJEpLyUmBTv2LHDuMRmMplYt24d69atK7JuvXr1WL16dalfvG/fvvTt2xeA0NBQq7I7l/kBiI6Oxmw2Exsby5gxY4xlfnbv3m30NixdupSgoCBjbMrty/w4Ojri4+PDqVOnWLFiBWFhYZhMJqKjo+nRowfh4eHArQb8yy+/JDo6mvfff7/UxyMiUpUqsr0uzuTJk7l27RrTpk0jJyeHLl26sHXrVqPzAmD16tVMnz6dYcOGARAUFMSCBQuM8vr167Nt2zbCw8MJDAzExcWFiRMnEhYWVi4xioiUpMSk+D//8z/p06cPFouFvn37MmPGDHr37m1Vx2QyUbduXVq2bFnsRIyyKGmZnzFjxpS4zI/ZbL7rMj///d//TVpaGs2bN+fIkSOEhIRYvX7v3r1ZtWpVuRyLSHVX0u1bK3MCidxdZbXXn376aaF9zpw5k5kzZ971OQ0aNCixTfX19WXXrl33FJOIyP0qMSn28PAwlsnZvn07bdq0qZRJD5W5zE9GRkaRr3PnpI87lWXpkOq4NIot0PtWPTwon1N5HUdVzaCuqvZaRORBUKYl2R5//PGKiuOuKmuZn5Jepyil/eKzhWVGqiO9b9XHg/A5PWjnW1W01yJyd7riZvvKfPOOvXv3sn79es6ePcuvv/5aaBUHk8nE0aNH7zswd3d34FZvbtOmTY3td1vmpyCBvZdlftzd3YtdTkhEpDqqrPZaRORBUKakODo6mtdee42GDRvi5+eHt7d3RcWFl5eXscxP586dgf9b5mfu3LmA9TI/BeOKi1rm58033yQvL486deoAhZf56dq1KwkJCUyaNMl4/YSEBKuxyiIi1UllttciIg+CMiXFUVFRPPbYY2zZsqVcJtTl5uZy5swZAG7evMn58+dJTk6mQYMGNGvWrNKW+Rk/fjxPP/00S5Ys4ZlnnmHHjh18+eWX7N69+76PUUSkKpR3ey0i8qArU1KcnZ3Nf/3Xf5VbA/vtt98ycOBA43FERAQRERGMGjWK6OjoSlvmp1u3bqxdu5Z58+YRERHBv/3bv7F27VqtUSxSShorZ3vKu70WEXnQlSkp7tixIz/88EO5vXiPHj0K3X3udpW5zM/gwYON9ZBFRKq78m6vRUQedGW6zfN///d/89FHH/HFF19UVDwiIlIO1F6LiJRNmXqKIyIiePjhhxkyZAgtW7akWbNmODg4WNUxmUxs3ry5XIMUEZGyUXstIlI2ZUqK//nPf2IymWjatCm//fYbp0+fLlRH96gXEal6aq9FRMqmTEnxsWPHKioOEREpR2qvRUTKpkxjikVEREREHkRl6ik+d+5cqeo1a9bsnoIREZHyofZaRKRsypQUd+jQoVRj0H755Zd7DkhERO6f2msRkbIpU1L87rvvFmpk8/PzSUtL4+OPP6ZRo0aMHTu2XAMUkZJvjiFyJ7XXIiJlU6akePTo0XctmzJlCr169SI3N/e+gxIRkfuj9lpEpGzKbaKds7Mzo0ePZsWKFeW1SxERqQBqr0VECivX1Sdq1qxJenp6ee5SREQqgNprERFr5ZYUHzt2jPfee482bdqU1y5FRKQCqL0WESmsXFafuHjxIpcuXcLZ2ZmoqKhyC05ERO6N2msRkbIpU1L82GOPFWpkTSYTLi4utGjRguHDh+PiolnyIiJVrTzb69WrV7Nu3Tpj7eO2bdsSHh5Ov379ALBYLMyfP5/169eTk5NDly5dWLRoEd7e3sY+cnJyeOWVV9i9ezcA/fv3Z8GCBVYxHD9+nGnTpvHNN9/QoEEDnn/+eV555RXdjlpEKkWZkuLo6OiKikNERMpRebbXHh4ezJkzh5YtW3Lz5k3+9re/MXr0aPbu3Uu7du1Yvnw5UVFRREVFYTabWbBgAUOHDuXIkSPUq1cPgLFjx3L+/HliYmIwmUxMmjSJcePGsWnTJgAuXbrE0KFDCQgIID4+ntTUVCZOnEjdunV56aWXyu1YRETupkxJ8Z0uX74MYDR6IiJim+6nvR4wYIDV49dff53333+fI0eO4OvrS3R0NFOmTGHw4MHArYTcbDYTGxvLmDFjSElJ4fPPP2f37t1069YNgKVLlxIUFERqaipms5mYmBiuXbtGdHQ0jo6O+Pj4cOrUKVasWEFYWJh6i0WkwpV5ot0PP/zAuHHjaNGiBV5eXnh5edGiRQvGjx/PDz/8UBExiojIPaiI9jo/P58tW7Zw5coV/P39SUtLIyMjg169ehl1HB0dCQgI4PDhwwAkJSXh7OxsJMQA3bt3x8nJyarOo48+iqOjo1Gnd+/epKenk5aWdk+xSvlyWeZS7I9IdVemnuLU1FT69evHxYsX6dmzJ23atMFisZCamkpMTAyfffYZe/bsoVWrVhUVr4iIlEJ5t9fHjx+nb9++5OXl4eTkxIcffoivr6+R1Lq5uVnVd3NzM5Z8y8zMxNXV1aq312Qy0bBhQzIzM406Hh4ehfZRUNa8efN7eh9EREqrTEnxnDlzsFgsJCQk0KFDB6uyY8eOMXjwYObMmcOGDRvKNUgRESmb8m6vzWYzX375JRcvXiQuLo4JEyawY8cOo/zO4Q0Wi6VQEnynkupYLJa7PrdAampqqeIvi4rYZ0WrjjGLtfL+DKvjOVGeMZvN5jI/p0xJ8f79+xk/fnyhBhagffv2/OUvf2HlypVlDuJu2rdvb8x2vl3fvn3ZvHkzERERREZGWpU1atSIU6dOGY/La1a0iEh1Ut7tda1atWjRogUAnTp14ptvvmHFihWEh4cDt3pzmzZtatTPysoyenobNWpEVlaWVRJssVjIzs62qlPQa3z7PqBwL/Tt7uWLrzgFY5yrk+oYsxRWnp9hdTwnbCHmMo0p/v3333n44YfvWl6/fn1+//33+w6qQEJCAikpKcbPvn37MJlMDBkyxKhjNput6hw8eNBqHwWzoiMjI4mPj8fNzY2hQ4cak07g1qzo5ORkYmJiiI2NJTk5mXHjxpXbcYiIVLaKbq9v3rzJ77//jpeXF+7u7iQkJBhleXl5JCYmGmOI/f39yc3NJSkpyaiTlJTElStXrOokJiaSl5dn1ElISKBJkyZ4eXndc5wiIqVVpqTYx8eHTZs2ce3atUJlv/32G5s2bcLHx6fcgmvYsCHu7u7Gz2effUa9evWskuIaNWpY1WnYsKFRZrFYrGZF+/j4EB0dTW5uLrGxsQDGrOhly5bRrVs3/P39Wbp0KXv27KmWlx5ERKB82+s333yTgwcPkpaWxvHjx5kzZw779+/n2WefxWQyMWHCBJYtW0ZcXBwnTpwgNDQUJycngoODAWjTpg19+vRh6tSpHDlyhKSkJKZOnUq/fv2MnqHg4GAcHR0JDQ3lxIkTxMXFsWzZMkJDQ7XyhIhUijINn3j55Zf5j//4DwIDA3nxxReNxuzUqVOsXbuW1NRUPvzwwwoJ1GKxsGHDBkaMGEHdunWN7WfPnsXb25uaNWvi5+fH7NmzjQkZJc2KHjNmTImzoqu6K19E5F6UZ3udkZFBSEgImZmZPPzww/j6+hIbG0vv3r0BmDx5MteuXWPatGnGMLWtW7daLf+2evVqpk+fzrBhwwAICgpiwYIFRnn9+vXZtm0b4eHhBAYG4uLiwsSJEwkLCyuvt0REpFhlSoqffvppVq1axaxZs6zuMmSxWHB3d2fVqlUEBQVVSKAJCQmkpaXx3HPPGdv8/PxYsWIFZrOZrKwsFi5cSN++fTl06BCPPPIIGRkZwP3Pir6bsvQkq9f53uh9ezBUl8+xvOK0hT+my7O9LulGICaTiZkzZzJz5sy71mnQoAGrVq0qdj++vr7s2rWrVDGJiJS3Mt+8Izg4mCFDhnD06FFjnUtPT086duxIjRr3dS+QYq1fv57OnTtbTRp56qmnrOr4+fnRsWNHPvroI6vehfKYFV2U0n7x2cLg8epI79uDozp8jg/i+VZV7bWISHV0T61ijRo18PPzw8/Pr7zjKdLPP//Mzp07WbRoUbH1nJ2dadu2LWfOnAHA3d0duP9Z0SIi1VVlt9ciItVViRPtMjIy6Nq1K3/961+LrffXv/4Vf39/Ywmd8rRx40Zq165tjEW7m7y8PFJTU41kuLxmRYuIVAe20F6LyL3RHQOrXolJ8Xvvvccvv/zClClTiq03efJksrOzy3WdYrjVa/vBBx8wbNgwq0kbALNmzWL//v2cPXuWr776ij//+c9cvXqVUaNGAZTbrGgRkeqgqttrEZHqrMSk+B//+EeRCemdHn74YYYPH17ukyS+/PJLzpw5w5///OdCZT/++CNjx46la9euPPfcc9SqVYvPPvsMT09Po87kyZMJDQ1l2rRpBAYG8tNPPxU5K7pdu3YMGzaM4cOH065dO31ZiEi1U9XttYhIdVbimOJ//etfhISElGpnvr6+5b4k2xNPPEFOTk6RZWvXri3x+eU1K1pExNZVdXstIlKdldhTbDKZuHnzZql2dvPmTS2yLiJSRdRei4jcuxKTYk9PT77++utS7eybb76xGrogIiKVR+21iMi9KzEp7tevH1u2bOHUqVPF1jt16hSxsbH079+/3IITEZHSU3stInLvSkyKw8LCcHJyYuDAgcTGxnLjxg2r8hs3bhAbG8ugQYOoV6+ebskpIlJF1F6LiNy7EifaNWzYkJiYGEaPHk1ISAiTJk2iVatWODs7k5uby+nTp8nLy6NJkyZ8/PHHuLq6VkbcIiJyB7XXIiL3rlR3tOvUqROJiYmsW7eO3bt3k5KSwuXLl6lXrx4dOnQgKCiI559/nvr161d0vCIiUgy11yIi96bUt3muX78+U6ZMKXFReBERqVpqr0VEyq7EMcUiIiIiIg86JcUiIiIiYvdKPXxCRCqOyzKXqg5BRETErqmnWERERETsnpJiEREREbF7SopFRERExO4pKRYRERERu6ekWERERETsnpJiEREp1pIlSwgMDKRZs2a0bNmSESNGcOLECas6FouFiIgI2rZtS+PGjRkwYAAnT560qpOTk0NISAienp54enoSEhJCTk6OVZ3jx4/z9NNP07hxY7y9vYmMjMRisVT4MYqIKCkWEZFi7d+/nxdffJE9e/YQFxdHjRo1GDJkCL/++qtRZ/ny5URFRREZGUl8fDxubm4MHTqUy5cvG3XGjh1LcnIyMTExxMbGkpyczLhx44zyS5cuMXToUBo1akR8fDzz58/nnXfe4d13363U4xUR+6R1ikVEpFhbt261erxy5Uo8PT05dOgQQUFBWCwWoqOjmTJlCoMHDwYgOjoas9lMbGwsY8aMISUlhc8//5zdu3fTrVs3AJYuXUpQUBCpqamYzWZiYmK4du0a0dHRODo64uPjw6lTp1ixYgVhYWGYTKZKP3Z7ovXSxd7ZdE9xREQELi4uVj+tW7c2ynW5TkSk8uXm5nLz5k1cXG4lUWlpaWRkZNCrVy+jjqOjIwEBARw+fBiApKQknJ2djYQYoHv37jg5OVnVefTRR3F0dDTq9O7dm/T0dNLS0irj0ETEjtl8T7HZbGbHjh3GYwcHB+P/BZfroqKiMJvNLFiwgKFDh3LkyBHq1asH3Lpcd/78eWJiYjCZTEyaNIlx48axadMm4P8u1wUEBBAfH09qaioTJ06kbt26vPTSS5V7sCIi1cCMGTNo3749/v7+AGRkZADg5uZmVc/NzY309HQAMjMzcXV1tertNZlMNGzYkMzMTKOOh4dHoX0UlDVv3rxQLKmpqeVzUBW8z4pWHWOWsinrZ1wdz4nyjNlsNpf5OTafFNeoUQN3d/dC23W5TkSk8r366qscOnSI3bt3W3VSAIXaS4vFUigJvlNJdQqu2t2tLb6XL77iFHw3VCfVMWYpu7J8xtXxnLCFmG16+ATA2bNn8fb2pkOHDrzwwgucPXsW0OU6EZHKNnPmTLZs2UJcXJxVr21Bx0VBj2+BrKwso6e3UaNGZGVlWQ1Ns1gsZGdnW9Upah9QuBdaRKS82XRS7Ofnx4oVK4iJieHtt98mIyODvn378ssvvxR7ue72S3GluVxX1D4KykREBKZPn05sbCxxcXFWczsAvLy8cHd3JyEhwdiWl5dHYmKi0Snh7+9Pbm4uSUlJRp2kpCSuXLliVScxMZG8vDyjTkJCAk2aNMHLy6siD09ExLaHTzz11FNWj/38/OjYsSMfffQRXbt2Barmcl2Bsox9qY5je2yB3rcHQ0mz2o8MOFJJkRSvvM63qr4EWN7Cw8PZtGkTH374IS4uLkanhJOTE87OzphMJiZMmMDixYsxm820atWKRYsW4eTkRHBwMABt2rShT58+TJ06leXLl2OxWJg6dSr9+vUz3q/g4GAiIyMJDQ0lPDyc06dPs2zZMl555RUNZRORCmfTSfGdnJ2dadu2LWfOnOGZZ54BbvXmNm3a1Khzt8t1BQ1qeV6uK+0Xny2Mk6mO9L7ZD1v4nHW+3d2aNWsAjPkbBaZPn87MmTMBmDx5MteuXWPatGnk5OTQpUsXtm7dakx6Bli9ejXTp09n2LBhAAQFBbFgwQKjvH79+mzbto3w8HACAwNxcXFh4sSJhIWFVfQhiohUr6Q4Ly+P1NRUevToYXW5rnPnzkZ5YmIic+fOBawv1xVcnivqct2bb75JXl4ederUAXS5TkTkdncuY1kUk8nEzJkzjSS5KA0aNGDVqlXF7sfX15ddu3aVOUYRkftl00nxrFmz6N+/P02bNiUrK4uFCxdy9epVRo0apct1IiIiYjdKGoaWM6XkP16leDadFP/444+MHTuW7OxsGjZsiJ+fH5999hmenp6ALteJiIiISPmw6aR47dq1xZbrcp2IiEjp6DbOIsWz6SXZREREREQqg5JiEREREbF7SopFRERExO4pKRYRERERu2fTE+1ExD5oqSEREalqSopFKoFmfYuIiNg2DZ8QEREREbunpFhERERE7J6GT4iUAw2PEBERqd6UFIuUgpJeERGRB5uGT4iIiIiI3VNSLCIiIiJ2T0mxiIiIiNg9JcUiIiIiYveUFIuIiIiI3VNSLCIiIiJ2T0mxiIiIiNg9JcUiIlKsAwcOMHLkSLy9vXFxcWHjxo1W5RaLhYiICNq2bUvjxo0ZMGAAJ0+etKqTk5NDSEgInp6eeHp6EhISQk5OjlWd48eP8/TTT9O4cWO8vb2JjIzEYrFU+PGJiIBu3iEiIiW4cuUKPj4+jBo1ivHjxxcqX758OVFRUURFRWE2m1mwYAFDhw7lyJEj1KtXD4CxY8dy/vx5YmJiMJlMTJo0iXHjxrFp0yYALl26xNChQwkICCA+Pp7U1FQmTpxI3bp1eemllyr1eEWqo9LcZCpnSk6JdeyZTfcUL1myhMDAQJo1a0bLli0ZMWIEJ06csKozYcIEXFxcrH769OljVee3335j2rRptGjRAg8PD0aOHMmFCxes6pw7d44RI0bg4eFBixYteOWVV/j9998r/BhFRGxd3759mT17NoMHD+ahh6y/NiwWC9HR0UyZMoXBgwfj4+NDdHQ0ubm5xMbGApCSksLnn3/OsmXL6NatG/7+/ixdupQ9e/aQmpoKQExMDNeuXSM6OhofHx8GDx7M5MmTWbFihXqLS8llmUuxPyJSPJtOM7CjWgAAIABJREFUivfv38+LL77Inj17iIuLo0aNGgwZMoRff/3Vql7Pnj1JSUkxfmJiYqzKZ86cyfbt23n//ffZuXMnly9fZsSIEeTn5wOQn5/PiBEjyM3NZefOnbz//vvExcXx2muvVdqxiohUR2lpaWRkZNCrVy9jm6OjIwEBARw+fBiApKQknJ2d6datm1Gne/fuODk5WdV59NFHcXR0NOr07t2b9PR00tLSKuloRMSe2fTwia1bt1o9XrlyJZ6enhw6dIigoCBje+3atXF3dy9yHxcvXmTDhg1ERUURGBho7Kd9+/bs3buX3r17Ex8fz8mTJzl27BhNmzYFYM6cOUyaNInXX3+dhx9+uIKOUESkesvIyADAzc3Narubmxvp6ekAZGZm4urqislkMspNJhMNGzYkMzPTqOPh4VFoHwVlzZs3r6hDEBEBbDwpvlNubi43b97ExcX6MlBiYiKtWrWifv36PPbYY7z++utGY3r06FGuX79u1YvRtGlT2rRpw+HDh+nduzdJSUm0adPGSIjhVg/Fb7/9xtGjR3niiScq5wBFRKqp2xNeuDWs4s4k+E4l1SkYNlHUcwsUDL8oTxWxz4pWHWOWymfr50l5xmc2m8v8nGqVFM+YMYP27dvj7+9vbOvTpw8DBw7Ey8uLH374gXnz5jFo0CD27t1L7dq1yczMxMHBAVdXV6t9ubm5WfVQ3NnL4erqioODg1FHREQKK7hKl5mZadWxkJWVZbSrjRo1IisryyoJtlgsZGdnW9W5s73NysoCCvdC3+5evviKk5qaWu77rGjVMWapGrZ8ntjCeVxtkuJXX32VQ4cOsXv3bhwcHIztw4cPN/7v6+tLx44dad++PXv27GHQoEF33V9pejGK2w5l+4vG1v86s1V63wQq7zwor9ep6oa9Mnl5eeHu7k5CQgKdO3cGIC8vj8TERObOnQuAv78/ubm5JCUlGeOKk5KSuHLlivHY39+fN998k7y8POrUqQNAQkICTZo0wcvLqwqOzPZospxIxaoWSfHMmTPZunUr27dvL3FcWZMmTfDw8ODMmTPArd6H/Px8srOzadiwoVEvKyuLgIAAo07BZI8C2dnZ5Ofnl0sPhS389VMd6X2TApVxHuh8u7vc3FyjTb158ybnz58nOTmZBg0a0KxZMyZMmMDixYsxm820atWKRYsW4eTkRHBwMABt2rShT58+TJ06leXLl2OxWJg6dSr9+vUz3vPg4GAiIyMJDQ0lPDyc06dPs2zZMl555ZViOydERMqLTa8+ATB9+nRiY2OJi4ujdevWJdbPzs4mPT3duKTXsWNHatasSUJCglHnwoULpKSkWPVQpKSkWC3TlpCQQO3atenYsWM5H5GISPXy7bff8sQTT/DEE09w7do1IiIieOKJJ3jrrbcAmDx5MqGhoUybNo3AwEB++ukntm7daqxRDLB69WratWvHsGHDGD58OO3atWPlypVGef369dm2bRvp6ekEBgYybdo0Jk6cSFhYWKUfr4jYJ1NOTo7NLgAZHh7Opk2b+PDDD2nbtq2x3cnJCWdnZ3Jzc5k/fz6DBg3C3d2dH374gblz53LhwgUOHz5sNMgvv/wyu3btIjo6mgYNGvDaa6+Rk5PDvn37cHBwID8/nx49euDq6sq8efP49ddfmTBhAs888wwLFy687+NQD9S9saX3TZctq1ZlLDhvS+ebVB1bPg/UDsn9suWbd9jC755ND59Ys2YNAIMHD7baPn36dGbOnImDgwMnTpzg448/5uLFi7i7u9OjRw/WrVtn1UPx1ltv4eDgwJgxY8jLy+OJJ57gvffeM8YmOzg4sGnTJsLDw+nfvz916tQhODiYefPmVd7BioiIiEiVsemkOCen+L9oHB0dC61lXJQ6deqwcOHCYnt9mzVrZtxuVERERETsi82PKRYRERERqWg23VMsIiIiIuWjpHHptjzmuDKop1hERERE7J56ikXQrG4RERF7p55iEREREbF7SopFRERExO4pKRYRERERu6ekWERERETsnibaiYjdK81ES3tfqkgqnib8SlWz9yXblBRLlauMX0J92YiIiEhxlBSLSLVn770bIiJy/5QUywNBPcEiIiJyPzTRTkRERETsnnqKRcTm6UqAiIhUNPUUi4iIiIjdU0+x2Dz1EoqIiFS9B31Ss3qKRURERMTuKSkWEREREbun4RMiIiIVTMPARGyfeopvs2bNGjp06IC7uztPPvkkBw8erOqQRETsjtpiEakK6in+X1u3bmXGjBksXryY7t27s2bNGp599lkOHTpEs2bNqjo8EbkP6qWrPtQWi1Rf1X0iniknJ8dS1UHYgt69e+Pr68vbb79tbOvcuTODBw/mjTfeuK99p6amYjab7zfEB5YSFqkObL0xf1BUZFtcGvfaXqsdE7l/Vd3OqqcY+P333zl69CgvvfSS1fZevXpx+PDh+96/EuLiVfUvgYjYhopui0vjXttrtWMi1Z/GFAPZ2dnk5+fj5uZmtd3NzY3MzMwqikpExL6oLRaRqqSk+DYmk8nqscViKbRNREQqltpiEakKSooBV1dXHBwcCvVEZGVlFeqxEBGRiqG2WESqkpJioFatWnTs2JGEhASr7QkJCXTr1q2KohIRsS9qi0WkKmmi3f+aOHEi48aNo0uXLnTr1o21a9fy008/MWbMmKoOTUTEbqgtFpGqop7i/zVs2DAiIiJYuHAhPXr04NChQ2zevBlPT8973qcWoC+biIgIXFxcrH5at25d1WHZpAMHDjBy5Ei8vb1xcXFh48aNVuUWi4WIiAjatm1L48aNGTBgACdPnqyiaG1DSe/ZhAkTCp1/ffr0qaJo7VdFtMWl8T//8z8888wzeHp64uLiQlpaWqE6OTk5hISE4OnpiaenJyEhIeTkVN2qE7b8HVPd2qglS5YQGBhIs2bNaNmyJSNGjODEiRNWdWwt5tWrVxMQEECzZs1o1qwZTz31FHv27LHZeO+0ePFiXFxcmDZtmrGtqmNWUnybsWPHcuzYMTIzM9m3bx+PPfbYPe+rYAH6//qv/+KLL77A39+fZ599lnPnzpVjxA8es9lMSkqK8WNLjbwtuXLlCj4+PsyfPx9HR8dC5cuXLycqKorIyEji4+Nxc3Nj6NChXL58uQqitQ0lvWcAPXv2tDr/YmJiKjlKgfJti0vr6tWr9OrVixkzZhQbV3JyMjExMcTGxpKcnMy4ceMqPLai2Pp3THVro/bv38+LL77Inj17iIuLo0aNGgwZMoRff/3VZmP28PBgzpw57Nu3j4SEBJ544glGjx7N999/b5Px3u7IkSOsX78eX19fq+1VHbNu3lFBqnoB+uooIiKCuLg4EhMTqzqUauUPf/gDCxYsYPTo0cCtv7Tbtm3LX/7yF8LDwwG4du0aZrOZv/71r7oMTeH3DG71FP/yyy9s2rSpCiOTqvbtt98SGBjId999h5eXl7E9JSWFbt26sXv3brp37w5AYmIiQUFBHDlypNLXo69O3zHVsY3Kzc3F09OTjRs3EhQUVC1iBmjevDlvvPEGzz//vM3Ge/HiRZ588kmWL1/OggUL8PHxYeHChTbxHqunuAIULEDfq1cvq+2VuQB9dXX27Fm8vb3p0KEDL7zwAmfPnq3qkKqdtLQ0MjIyrM4/R0dHAgICdP6VIDExkVatWtGlSxcmTZrEzz//XNUhiY1ISkrC2dnZasJf9+7dcXJyqvTfq+r+HVMd2qjc3Fxu3ryJi8utOxXaesz5+fls2bKFK1eu4O/vb9PxTpkyhcGDB/Pkk09abbeFmDXRrgJoAfp74+fnx4oVKzCbzWRlZbFw4UL69u3LoUOHeOSRR6o6vGojIyMDoMjzLz09vSpCqhb69OnDwIED8fLy4ocffmDevHkMGjSIvXv3Urt27aoOT6pYZmYmrq6uVuslm0wmGjZsWOntenX/jqkObdSMGTNo3749/v7+gO3GfPz4cfr27UteXh5OTk58+OGH+Pr6GkmkrcW7fv16zpw5w8qVKwuV2cJ7rKS4AmkB+rJ56qmnrB77+fnRsWNHPvroI8LCwqooqupL51/ZDB8+3Pi/r68vHTt2pH379uzZs4dBgwZVYWRyr+bNm8eiRYuKrbN9+3Z69OhRqv0V9ftTlb9X1f133Fbjf/XVVzl06BC7d+/GwcHBqszWYjabzXz55ZdcvHiRuLg4JkyYwI4dO4xyW4o3NTWVuXPnsmvXLmrVqnXXelUZs5LiCqAF6MuHs7Mzbdu25cyZM1UdSrXi7u4O3OrZatq0qbFd51/ZNGnSBA8PD51/1diECRP405/+VGyd239HitOoUSOysrKsvqAtFgvZ2dmV/ntV3b9jbLmNmjlzJlu3bmX79u00b97c2G6rMdeqVYsWLVoA0KlTJ7755pv/3955h1VxdA38hyBYEURAqiIiNozYAKOCBRSxN+wiKr62+JpoiF00UqyxiwVFkRhFXnsvWCLYe6JYYlQsRBAsIP37w+fu53IvAgZEZX7Pc/+4U3bOzu7Onp055wzLly+XbHI/J3nPnj1LXFwcDg4OUlpGRganT58mKCiIqKgooGhlFjbFhYAIQF8wvH37ltu3b0uDkSBvVKlSBUNDQ9n99/btWyIjI8X9lw/i4uJ48uSJuP++YPT09KhRo8YHf2XKlMnTsZo0acLr1685e/aslHb27FnevHnzyZ+rL/0d87mOUd7e3oSFhbFz506lcKCfq8zZyczMJDU19bOU183NjdOnT3Py5EnpZ2trS/fu3Tl58iTVq1cvcpnFTHEhIQLQ558pU6bQrl07TE1NJZvipKQk+vTpU9SifXa8fv1amsHMzMzk0aNHXL16FV1dXczMzBgxYgTz58/HysqK6tWrM2/ePMqWLUuPHj2KWPKi40N9pquri7+/P506dcLQ0JAHDx4wc+ZM9PX16dChQxFLLvgUPHv2jGfPnnHnzh3gXbSJxMREzMzM0NXVxdramjZt2jBu3DgWLVpEVlYW48aNo23btp888gR8/u+YL22MGj9+PL/99hshISHo6OhI9q1ly5alXLlyqKmpfXYyz5gxAxcXF0xMTHj9+jVhYWGcOnWKLVu2fJbyKuK/v0+ZMmXQ1dWldu3aAEUuswjJVoisWbOGRYsW8ezZM2rVqoWvr+8nibf5peLp6cnp06eJi4ujUqVKNGrUiMmTJ1OzZs2iFu2z4+TJk3Ts2FEpvU+fPqxYsYKsrCz8/f1Zv349CQkJNGzYkHnz5kkDT3HkQ322YMEC+vXrx9WrV0lMTMTQ0JDmzZszefLkPC+vC75s/Pz8CAgIUEpftmyZFErsxYsXeHt7s2/fPgBcXV2ZM2eO0ov+U/E5v2O+tDEqp2vo7e3NxIkTAT47mUeMGMHJkyeJjY1FW1ubOnXq8N1339G6devPUl5VuLm5SSHZoOhlFkqxQCAQCAQCgaDYI2yKBQKBQCAQCATFHqEUCwQCgUAgEAiKPUIpFggEAoFAIBAUe4RSLBAIBAKBQCAo9gilWCAQCAQCgUBQ7BFKsUAgEAgEAoGg2COU4n/Bpk2b0NHR4e+///4k7fXt25dhw4Z9kraKM35+foUedzQ1NZVatWqxdu3afNVLTk6mVq1aBAcHF5Jkgvzw9u1brK2txfUQCIoBr1+/pnr16mzevLnQ2zp8+DA6OjqcO3cuX/WCgoJkm48UNDt27MDc3JyEhIRCOX5RI5TiL4QLFy6wf/9+xo0bp5SXkpJCYGAgLi4umJubo6+vT7169Rg1ahSXL18uAmk/f2JiYvDz8+Pq1atF0r6mpiYjR45k3rx5JCcn57neqlWrUFNTk3b527lzJzo6OoSFhSmV7dix4wfzqlSpQlZW/sKU7927V+UGBwABAQHs3bs3z8e6d+8eOjo6LFmyRGX+b7/9ho6ODpGRkfmS8VNSqlQp/vOf/zBnzhxSUlKKWhzBZ4Ji567cfps2bSpqUT8LEhIS8PPz+6yfdXi3kUtOu6s9e/aMKVOm0KRJE4yMjDAyMqJZs2bMmjWL2NjYIpC2cOjYsSMGBgYsXry4qEUpFIRS/IWwePFi7O3tlXZ1iYuLw9XVFW9vb7S1tfH29mb+/Pn07NmTqKgoWrZsSUxMTBFJ/fny+PFjAgICuHbtmlLehAkTePr0aaHLMGDAAJ4/f87WrVvzVD49PZ3ly5fTv39/NDU1AXBwcABQepmkp6dz4cIFNDQ0csyzt7dHTU0tXzLv27ePOXPmqMybM2eOtNNXcWLgwIE8e/aMbdu2FbUogs+EwMBA2c/BwYGSJUsqpX8uu88VNYmJiQQEBBAVFVXUouRIamoqgYGBDBo0CA0NDVne2bNnsbe3Z82aNdjZ2TF79mx8fX1p3Lgxa9asoUuXLp9MzkGDBvH06VMMDQ0L5fglSpRg0KBBrFmzhqSkpEJpoyjRyL2IoKiJj49n3759+Pn5KeWNGDGCS5cuERQURLdu3WR5kyZNYunSpZ9KzK8GDQ0NpUGvMNDR0aFly5aEhoYycODAXMsfOnSIZ8+e0b17dylNX18fS0tLJcX3ypUrJCUl0atXrxzz7O3tC+ZEvkKSkpIoU6ZMnsrq6enRokULNm3aRN++fQtZMsGXgLu7u+x/REQEFy9eVEr/WsnP81PYJCcnU7p06X99nL179xIfH6/0no2Li6N///5oaWlx8OBBrKysZPnTpk37pO9hdXV11NXVC7WNLl26MG3aNHbt2vXV3dNiprgQ2Lt3L61bt8bIyIgqVarQr18/oqOjlcpFRkbSunVrDA0NqVu3LosWLSIkJETJTvnAgQOkpqbi5OQkq3/+/HkOHjxI//79lR5UePdwjB07FhMTEyntjz/+oHfv3pibm2NkZISzszOHDh2S1Tt58qS07L506VJsbGwwNDTE2dmZK1euyMrGxsYyZswY6tSpg4GBATVr1sTd3Z0bN25IZXR0dFQq9G5ubri5ualsd/78+dSpUwcTExP69u1LfHw86enp+Pj4YG1tjbGxMZ6enrx+/Vp2TBsbG7p3787x48dxdHTE0NCQBg0aEBISImvH2dkZgFGjRklLmQoZc7Ip3rBhA02bNsXQ0JDq1aszfPhwnjx5IiszYsQIDA0NiY2NZfDgwZiZmVGlShXGjh3L27dvlY7p6OhIVFQU//zzj1Jednbv3o2RkRHW1taydAcHB27evCmz8YqKisLIyAh3d3eVeYp67x+7V69e1KpVC319fWxsbPDx8SE1NVUq4+XlxcaNG8nIyJAtAcfExKCjo0NGRgYbN26U0jt37pzrOX0Mv//+O25ubhgbG2NqakrXrl25ePGirMzPP/+Mnp6eUt2IiAglk4x27drh4ODA1atX6dChA8bGxnh7ewNw9+5dBg4ciLW1tfScenh4KK0kODk5cfr0aV68eFEIZyz42snMzGT58uU4ODhgaGhItWrVGD58uNJ91qZNG5o1a8b169dp3749RkZG1K9fn+3btwNw5swZXFxcqFy5Mg0aNODgwYOy+gp706ioKP773/9iYWGBqakpnp6eKsegc+fO0aNHD8zNzalcuTLOzs4cOXIkx2NOmDABKysrqlWrBsDz58+ZNGkSDg4OmJiYYGpqSufOnTl//rxUPzo6mm+++QYAHx8fafxQmAp6enrSuHFjJdlU2c7WqFGDvn37cvToUVq2bImhoSErV66U8g8dOoSrqysmJiaYmJjQuXNnLly4kPsF4t0YWbVqVapWrSpLX716NbGxsQQEBCgpxAC6urpMnTpVlpaXfs2JW7du4eHhgaWlJZUrV6ZRo0ZMmzZNys+pX1SZXqrq2y1btuDo6IipqSnm5uY0bdqUBQsWyMqYmZlhaWnJ7t278yTzl4SYKS5gwsLCGDZsGHXr1mXy5Mm8fPmSVatW4eLiQkREhPRAXbt2jW7dulGxYkUmTJiApqYmwcHBKr+uo6Ki0NbWlgYaBYql6t69e+dJtjt37tCuXTvJnrVs2bKEhobi7u5OcHAwHTt2lJVfunQpaWlpeHl5kZ6ezuLFi+nXrx+XLl2iZMmSwLulmhs3buDl5YW5uTlxcXGcPn2aO3fuUKdOnfx2HwCLFi1CU1OTMWPG8PDhQ1asWMHIkSMxNjbmzp07jB8/nhs3brB+/XoMDAzw9/eX1b9//z4DBw5k0KBB9O7dm61btzJ69Gi0tLTo2bMn1tbW/PTTT/j7++Ph4SEphx+Sd+HChfj4+NC0aVNmzpzJo0ePWL16NZGRkZw4cUKmRGdmZtK1a1fq1KmDj48P58+fJzg4GD09PdngBdCgQQPg3TXO3v/ZiYqKon79+krp9vb2hISEcPbsWVxcXKSydnZ20oCXPa9UqVLY2tpKx9i4cSOampp4eXlRoUIFzpw5w6JFi3j8+DGBgYEADBkyhMePH3P69GlWrFgh1dXR0SEwMJARI0bQtGlTBgwYAEDlypU/eD4KkpKSiIuLU0p/8+aNUtqJEyfo3r07pqam/Pjjj6Snp7Nu3Trc3NzYu3ev7Jzyw4sXL+jevTtdunShR48e6OrqkpKSQteuXUlPT2fYsGEYGBjw9OlTjhw5wtOnT2XnZ2trS1ZWFlFRUbi6un6UDILiy+jRo9myZQt9+vTBy8uLx48fs2rVKs6dO8fx48cpX768VPbFixe4u7tL92tQUBBDhgwhMzOTiRMnMmjQILp168ayZcvw8PDg+vXrVKxYUdbe999/T4UKFfjpp5/466+/WL16NXfv3uXIkSPSKtmxY8dwd3fnm2++YcKECZQsWZKwsDB69uzJr7/+Stu2bWXHHDdunPQ+e/XqFQC3b99mz549dO7cGQsLC+Lj41m/fj0dO3bkxIkTWFlZUblyZXx9fZk0aRLdunWTjlu9evWP6stbt27h6enJ4MGDGTRokPTODQkJYcyYMbRq1YqpU6eSlpbGxo0bcXNz48CBA5JinhNRUVEqlfN9+/ZRvnx52QTPh8hvv77PlStX6NChAxoaGnh4eFClShXu37/Pnj17mDlzZp7a/xAHDhzAy8uL1q1bS6uX0dHRKm29GzRoQERExL9u83NDKMUFSFpaGpMnT6Z69ers37+fsmXLAu9mRFu2bImvry+rVq0CwNfXl8zMTPbt24e5uTkA/fr1o2HDhkrHjY6OxtzcXMn+89atW8CHlbn3mTlzJklJSRw+fJgaNWoA75Tapk2bMnHiRNzc3ChR4v8XD16+fMnp06cpVaoUAFZWVvTv35+jR4/Stm1bEhMTiYyMZNasWYwZM0aqp+qLND+kpKRw5MgRyW42ISGBTZs28e2337Jr1y5JxpiYGDZt2oSfn5+sb+7evcuaNWskZwgPDw9atGjBjBkz6N69OwYGBrRu3Rp/f38aN26c6/JPXFwc/v7+NGvWjO3bt0svDXt7e/r168fSpUuZMmWKVD4tLQ1XV1cpzdPTk4SEBIKDg5WUYsWArWol4X3S09O5d++eNMP9PgqlPioqSlJ8z5w5w7hx49DW1qZmzZpKeba2tmhpaUnHWLduneyDzNPTk6pVqzJ37lx8fHyoXLkydnZ2WFhYEBkZqdRn7u7ujBw5EgsLi3wvp/n5+alcSVDFpEmT0NbW5vDhw9JMsLu7O3Z2dkyZMoU9e/bkq20FT58+Zd68eQwdOlRKu3z5Mg8ePCAkJIQOHTpI6T/++KNS/fevo1CKBfnh+PHjhIaGsnbtWplpVPv27WndujXr1q3ju+++k9JjYmJYv369ZKfasmVLGjduzNChQ9m7d69kFmVjY4Obmxvbtm1TilqkqanJzp07pcmN6tWrM378eLZu3UqfPn3IyMhg7NixtGjRgq1bt0rj69ChQ2nVqhXTp09XUt50dHTYuXOnbOne1taWS5cuyd4rAwcOpHHjxqxatYq5c+eira2Nm5sbkyZNwsbG5l8vx9+9e5fw8HBatWolpSUmJjJx4kQ8PDxYuHChlO7h4SHZAG/ZsiXHYyYlJfHo0SOVDnbR0dHUqVMnTyZ3H9Ov7/PDDz8A71a8qlSpIqVPnz4917bzwoEDB6hUqRJbt26VXTNVVKlShdjYWF68eIGurm6BtP85IMwnCpDLly/z7NkzhgwZIinEAN988w1OTk4cPHiQrKwsMjIyiIiIwNXVVVKI4Z1tYs+ePZWOGx8fr3I5X/E1/v4sQk5kZGRw5MgR2rVrJynEANra2nh6evLo0SOZyQO8U9IVCjFAs2bNgHczsfDO875kyZKcOnWqQJeNe/fuLSnEAI0aNQLehaR7/0Ft2LAhr1694vnz57L6+vr6MnOS0qVLM3DgQGJiYrh+/Xq+5YmIiCAlJYWRI0fKBj43NzesrKw4cOCAUp0hQ4bI/n/77bfExcVJ10yBYjBRNVP6Pi9evCArK0vlfWBpaYmhoaH0NX/37l1iY2Oll6O9vb1SXtOmTWXHUCjEmZmZJCYmEhcXR9OmTcnMzCz0CB0eHh5s375d6Zf940px/fr16yczjTAzM6Nbt25ERkby8uXLj5JBU1NTya5b8VwdOXIkV4eSvF5HgSA727dvR0dHB0dHR+Li4qSfubk5ZmZmnDhxQla+QoUKMtMkKysrKlSogKWlpcxPQDFu/vXXX0ptenp6SgoxvHP6LVu2rGRKd/HiRR48eECvXr2Ij4+XZEpMTMTZ2ZmbN28qRVTw8PBQsmUtVaqUNGa/ffuW+Ph4SpQoQf369ZVM8QoKCwsLmUIM78KbvXr1ip49e8r6ODU1lWbNmnHy5MkPRuJRPNfZx9+MjAySk5MpV65cnmT7mH5VEBMTw/nz5xkwYIBMIQby7TCdE+XLl+fly5dK95wqvtYxT8wUFyAPHjwAkCmdCqytrTl69CgvX74kOTmZ5ORkLC0tlcqpSgNUPrCKl/arV69yjav7/Plz3rx5k6NsCvltbGykdDMzM1k5RRsKBVhLS4vp06czffp0rKysaNSoEc7OzvTq1Uupbn4wNTWV/dfW1v4N2fQYAAAOv0lEQVRgekJCAvr6+lK6hYWF0leuol8fPnxIvXr18iXPh65rjRo1OHXqlCytZMmSGBkZydLe77v3P2IU1zWvg1pOA7ednR0HDx4kNTWVqKgoypQpI11LOzs7QkNDpTxAycnuxo0bTJ8+nd9//10pRFxiYmKeZMuJ7PEyK1SoIPvYsrS0VLKXV1VPcR1U2e1ZW1uTmZlJTEyMdF/kB2NjY9mHmEKuYcOGsXr1ajZv3oydnR1t27bF3d1daTk6v9dRIFBw584dEhIScjQXyD62m5iYKN1n2traMt8ReDc+a2lpqYwnm/09o6WlhampKQ8fPpRkgnd+BDnxzz//YGBgIP23sLBQKpORkcH8+fMJCQmRnl8F2X0jCgpVcijOp3379jnWe/36da4TTNnHX3V1dUqXLq3k25ITH9OvChQfN9kjUBUkXl5e7Nq1iy5dumBiYoKjoyOdOnWiXbt2SmW/1jFPKMWfiLzGg1VVrmLFiioHNmtra3bv3s0ff/yhNPNXELLl5MH6fvnRo0fToUMH9u7dS0REBHPnzmXBggWEhobi6Oj4wXYzMzNVLtHk1G5OyznZ5Vf1kOY3Hm9eUXXcDy07ZS+vuK6qnMLep2LFiqipqeUYMN3e3p6dO3dy6dIloqKiaNiwoTSrbWdnx9u3b6W8EiVK0KRJE5kMHTt2pHz58kybNo2qVatSunRpHj58yJgxY8jMzPygbB8iPT1d6eUXGBhYZB7LGRkZKtNz8k6fO3cugwcPZt++fRw9epQpU6Ywf/589uzZIzuvvF5HgSA7mZmZVK5cWeYQ9j7ZZyFzGl/yMl4ryG2MVDzzs2fPztE8L/ts5fsfugoCAgKYM2cOAwYMwMnJCV1dXUqUKEFAQIDSCl9O5KR05fQsq5JDcT5r1qyhUqVKKut9KEKF4rlWNf7WqFGD6OhoMjIyco368DH9quDfKKF57UMTExMiIyM5evQoR44c4fDhw4SGhuLm5qYUU/trHfOEUlyAKEwhoqOjlZZvbt++jY6ODtra2pQrV47SpUtz9+5dpWPcu3dPKc3a2prw8HCysrJkN7erqyvz589n8+bNuSrFlSpVomzZsiptV2/fvi2TP79UrVqVkSNHMnLkSB49ekSLFi1YuHChpBTr6OionG188OCBkidvQXDv3j0lhVvRr4oZ7PwMLO9f1+yzObdv3/7ofoP///pXNQv9Purq6lhaWua4e6Li+kdFRREVFSWLi1m1alUqV64s5dWpU4cKFSpI+cePHyc+Pp7Q0FDZDHL2qCTw4X5Tlaeuri55xiuoVatWjsf4EIp+Vtyv7xMdHU2JEiWk2TJFNIzXr1/LlIrss1V5oXbt2tSuXZsffviBq1ev0rJlSwIDA2Ue2Xm9jgJBdiwsLKQ4t6oUusLgzp07sndGSkoKMTEx1K1bV5IJ3s1Aq1rFySv/+9//aNOmjdIGPdltYD80rnzo/ZFXFOejr6+f62SNKsqUKYOpqanK8dfV1RV/f392796da8Sdf9OvCkf7P/74I1/1IH99qKWlhaurK66urmRlZTFp0iRWrFjB5cuXZY7e9+/fx8DAoNB3f/3UCJviAqR+/foYGhoSFBQkW4K+du0ax44dw8XFBTU1NdTV1XFycmLfvn2ymzIuLk7lRg52dna8fPlSSYlu1KgRLi4uhISEsGPHDqV6GRkZLF68mJiYGNTV1WndujUHDhyQlnDgnenFunXrMDU1zXe0iKSkJKWldlNTU/T19WVf1NWqVVMyMdizZ0+hbSryzz//EB4eLv1PTk5mw4YNGBsbS+eosKHNy1aVTk5OaGlpsXLlStmX9b59+7h9+/YHHSNyQxFKzM7OLteydnZ2Oe5QaGNjQ7ly5dizZw+3b99WMo+ws7PLMU/x8ZB9pmj58uVK7ZQpU4aMjAwl22hFXvb+VFNTw8nJSfb72KDyJiYm1K1bl9DQUJkNe0xMDOHh4Tg4OEimE4oXyMmTJ6VyaWlprFu3Ls/tJSYmkp6eLkurWbMmpUqVUjrPS5cuoaamJpuBFwjyQvfu3UlLS1O5KU5mZibx8fEF3ua6detIS0uT/m/cuJE3b97Qpk0bAJo0aYKZmRmLFi1SaRqQ11ledXV1pZnqEydOKNkTK3xwVI3HFhYWxMbGcvPmTSktMTHxg45x2WnXrh3lypVjzpw5svNWkJfzsbe359KlS0rpw4YNQ19fn4kTJ6qc6EpISODnn38G/l2/mpiY0KhRIzZs2CCZuSjIbSXUwsKCqKgo2bmfO3dO6X2S/V5TU1OTzPCyX5uLFy9+leOdmCkuQEqWLMns2bMZNmyYZHuoCMmmra3NpEmTpLITJ07k6NGjuLq6Sk4PwcHB0p7i7385u7i4ULJkSY4dO6Y0U7lixQp69OjBoEGDcHFxwcnJifLly/P333+zY8cO7t69K3nMTp06VXLwGzp0qBSS7dGjR6xfvz5Xb9Ps3Llzh06dOtGlSxdq1qwpBS+/desWs2bNksp5eHjw3Xff0bdvX5ydnYmOjiYsLEyl7VdBYGlpKc3qGRsbs2XLFm7fvs3KlSul5S1LS0u0tbUJCgqiXLlylCtXjlq1aqm019LT0+Onn37Cx8eHzp0707FjR2JiYli1ahXm5uaMHj36o2WNiIigSZMmMpvonGjfvj2bNm3izz//VJptVVdXp1GjRkRERFCiRAnJyUaBnZ2ddP9lX1VwcHBAR0cHLy8vvLy80NDQYMeOHSpDoilCno0fP55WrVqhoaFB+/btKV26NLa2thw7dowlS5ZgbGyMgYEBzZs3z1d/5Iavry/dunWjTZs2DBw4kIyMDIKCgsjIyJDdc87OzpiamjJ69GhGjx6NpqZmnjyq3yciIoKJEyfSqVMnqlevTlZWFtu2bePNmzdKccGPHTuGvb29kq2xQJAbLVu2xMPDgwULFnDlyhVatmxJqVKluH//Prt27WL48OGMHDmyQNtMSUmhU6dOdO3alXv37rFmzRrq1q0rOXpraGiwdOlS3N3dsbe3p2/fvpiamvLkyRPOnDnD8+fP8+SM5erqysKFCxk1ahRNmjQhOjqajRs3Sj4ACvT09DA3N2fLli2YmZmhq6tLtWrVsLW1xd3dHV9fX/r06cOwYcNITU0lODgYIyMjJb+DnNDR0WH+/PmMGDGC5s2bS1GIHj16xIkTJ6hUqVKuW263b9+esLAw/vrrL9m7S09Pj02bNuHu7k6zZs3o1asX9evXR01NjevXrxMWFoaJiQlTpkz51/06b9483NzccHR0lEKyPXjwgN27d3PmzJkc6w0ePFgWxu/hw4ds2LCBmjVryj78vby8SE5Opnnz5hgbGxMTE8Pq1asxNTWVKcAPHjzg7t27jB8/Pi/d/0UhlOICpkePHpQuXZr58+cza9YsNDU1adasGTNmzJCZCtSrV4/w8HCmTp1KQEAABgYGDBs2jFKlSnH16lXZMpqenh6urq6Eh4crhdbR09Nj//79rFu3jm3btuHv709ycjJGRkY4OjoSFBSEsbEx8M5Baf/+/fj4+LBs2TJSU1OxsbFh8+bNUriu/GBqakrPnj05ceIEYWFhqKmpYWlpyZIlS6RYtQD9+/fnwYMHbNiwgaNHj2Jra8vWrVuZPHlyvtvMC1WrVmXBggVMmzaNmzdvYmxszOLFi2XxnLW0tAgMDGTWrFmMHz+etLQ0vL29c3RiGDduHHp6eqxcuZKpU6dSrlw5OnfuzPTp0z96+ejFixccP36cefPm5al827ZtMTAwYNu2bbIQcAocHByIiIigVq1aMvMIkDvWZZ8prlSpElu2bGHKlCn4+flJ5zZw4EAlpbZ79+6cP3+e7du3s2XLFrKysrhx4wYmJibMmTOH77//Hj8/P5KSknB0dCxwpbhFixZs374dPz8/AgICUFNTo3HjxgQHB0sxn+HdB2pISAje3t74+fmhp6fHgAEDsLOzk4W9+hD16tWjVatWHDhwgODgYLS0tKhVqxa//vqrLOxaXFwcp06d4pdffinQcxUUH3755RcaNGjA+vXrmT17Nurq6piYmNCuXTuVTk7/lgULFrB582Z8fX1JS0ujQ4cOzJkzRxaRwtHRkUOHDjF37lzWrl3Lq1evMDAwoF69eirDEqrC29ub1NRUwsPDCQ8Pp3bt2mzcuJHg4GCuXbsmK7tixQomT57M5MmTSUlJYfDgwdja2qKvr8/GjRuZOnUq06dPx8TEhNGjR1OiRIkcV85U4e7ujqmpKQsXLmTp0qWkpKRgaGhI48aNGTRoUK713dzc0NXVZdu2bUrKYJMmTYiMjGTJkiUcPHhQGhsVzrrDhw+Xyv6bfq1fvz4HDx7E19eXtWvXkpKSgpmZWa4xktu2bcusWbNYuXIlEydOpHbt2qxfv55169bJrkOfPn3YtGkTa9euJTExEQMDA9q3b4+3t7csZOeOHTsoX758oW3QVJSoJSQkFI4HkuCj8Pb2Jjg4WDJ5UHD+/HmcnZ05derUR2+KURywsbGhRo0abNu2rahFyZUlS5awbNkyLl26lOdtSH/55RcCAwO5fPmyLM6woOhYuHAha9as4cKFC5/MJlQg+BiCgoL4/vvvOXHiRL6j8AjA39+f0NBQLl68mKe4xF8jmZmZNGnShA4dOjBjxoyiFqfAETbFRUh2e9znz5/z22+/0bRpUyUv1kaNGklLUYIvn9TUVJYvX8748ePzrBAD0ozDr7/+WliiCfJBSkoKK1euZMKECUIhFgi+ckaNGkVSUpJK35/iwq5du4iNjWXs2LFFLUqhUDw/dT4T6tWrR69evbCysuLJkyeSs0NOSyihoaGfWEJBYaGpqcmff/6Z73qlS5f+qHqCwkFLS0vaWVIgEHzdlC9fXuaoXhzp3LnzV2k2oUAoxUWIi4uL9NWloaFB/fr1WbVqlZLNp0AgEAgEAoGgcBE2xQKBQCAQCASCYo+wKRYIBAKBQCAQFHuEUiwQCAQCgUAgKPYIpVggEAgEAoFAUOwRSrFAIBAIBAKBoNgjlGKBQCAQCAQCQbFHKMUCgUAgEAgEgmLP/wFFqqoDVdmW1gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x230cf83e048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "'Here I manipulate consumption data to be add by 1 and then log it, that is for make us can see data better, you should try the resul if didnt do that'"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plt.style.use('fivethirtyeight')\n",
    "\n",
    "plt.figure(figsize=(10, 8))\n",
    "\n",
    "plt.subplot(2, 2, 1)\n",
    "plt.hist(np.log(train_data['consumption']+1), bins=30)\n",
    "plt.title('Consumption Training Data')\n",
    "plt.xlabel('log(Consumption) (Watt-Hours)')\n",
    "plt.ylabel('Count')\n",
    "\n",
    "plt.subplot(2, 2, 2)\n",
    "plt.hist(train_data['temperature'].dropna(), bins=30)\n",
    "plt.title('Temperature Training Data')\n",
    "plt.xlabel('Temperature (Celcius)')\n",
    "plt.ylabel('Count')\n",
    "\n",
    "plt.subplot(2, 2, 3)\n",
    "plt.hist(np.log(test_data['consumption']+1).dropna(), color='g', bins=30)\n",
    "plt.title('Consmption Test Data')\n",
    "plt.xlabel('log(Consumption) (Watt-Hours)')\n",
    "plt.ylabel('Count')\n",
    "\n",
    "plt.subplot(2, 2, 4)\n",
    "plt.hist(test_data['temperature'].dropna(), color='g', bins=30)\n",
    "plt.title('Temperature Test Data')\n",
    "plt.xlabel('Temperature (Celcius)')\n",
    "plt.ylabel('Count')\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "\"\"\"Here I manipulate consumption data to be add by 1 and then log it, that is for make us can see data better, you should try the resul if didnt do that\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "series_id           0\n",
       "timestamp           0\n",
       "consumption         0\n",
       "temperature    228689\n",
       "dtype: int64"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.isnull().sum() #Find Missing Value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "series_id         758\n",
       "timestamp       40392\n",
       "consumption    276923\n",
       "temperature     16526\n",
       "dtype: int64"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.nunique() #Count Unique Value on column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "series_id          0\n",
       "timestamp          0\n",
       "consumption        0\n",
       "temperature    44916\n",
       "dtype: int64"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_data.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "series_id        625\n",
       "timestamp      36648\n",
       "consumption    81827\n",
       "temperature     6692\n",
       "dtype: int64"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_data.nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "series_id               1383\n",
       "surface                    7\n",
       "base_temperature           2\n",
       "monday_is_day_off          2\n",
       "tuesday_is_day_off         2\n",
       "wednesday_is_day_off       2\n",
       "thursday_is_day_off        2\n",
       "friday_is_day_off          2\n",
       "saturday_is_day_off        2\n",
       "sunday_is_day_off          2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "meta_data.nunique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### What we got :\n",
    "\n",
    "- Here we have 1383 building, 758 in training data and the rest in test data.\n",
    "- We have 276923 training data, and 81827 test data\n",
    "- We have many missing value in temperature\n",
    "- etc\n",
    "\n",
    "each series_id has a different sample of data, some have samples for 1 day, 2 days, 1 week, etc. but each sample is always in multiples of days, not days 1.5 and so on. so let's look at the sample distribution in each series_id."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 509376 entries, 2014-12-24 00:00:00 to 2017-12-18 23:00:00\n",
      "Data columns (total 4 columns):\n",
      "series_id      509376 non-null int64\n",
      "timestamp      509376 non-null datetime64[ns]\n",
      "consumption    509376 non-null float64\n",
      "temperature    280687 non-null float64\n",
      "dtypes: datetime64[ns](1), float64(2), int64(1)\n",
      "memory usage: 19.4 MB\n"
     ]
    }
   ],
   "source": [
    "train_data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training Data\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Count (hours)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>series_id</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>100003</th>\n",
       "      <td>672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100006</th>\n",
       "      <td>672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100008</th>\n",
       "      <td>672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100017</th>\n",
       "      <td>672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100021</th>\n",
       "      <td>672</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Count (hours)\n",
       "series_id               \n",
       "100003               672\n",
       "100006               672\n",
       "100008               672\n",
       "100017               672\n",
       "100021               672"
      ]
     },
     "execution_count": 117,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print('Training Data')\n",
    "count_train = train_data.groupby('series_id')[['timestamp']].count().rename(columns={'timestamp':'Count (hours)'})\n",
    "count_train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "28.0"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "672/24"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test Data\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Count (hours)</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>series_id</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>100004</th>\n",
       "      <td>96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100010</th>\n",
       "      <td>288</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100012</th>\n",
       "      <td>240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100020</th>\n",
       "      <td>312</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100028</th>\n",
       "      <td>312</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Count (hours)\n",
       "series_id               \n",
       "100004                96\n",
       "100010               288\n",
       "100012               240\n",
       "100020               312\n",
       "100028               312"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print('Test Data')\n",
    "count_test = test_data.groupby('series_id')[['timestamp']].count().rename(columns={'timestamp':'Count (hours)'})\n",
    "count_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Count    14\n",
      "dtype: int64\n",
      "Count    1\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "print(count_test.nunique()) # N unique value in id_series test\n",
    "\n",
    "print(count_train.nunique()) # N unique value in id_series train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "144    60\n",
       "288    51\n",
       "192    50\n",
       "24     50\n",
       "336    49\n",
       "312    48\n",
       "96     47\n",
       "120    43\n",
       "48     42\n",
       "216    40\n",
       "72     40\n",
       "168    39\n",
       "264    34\n",
       "240    32\n",
       "Name: Count, dtype: int64"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"The Distribution of Data who\"\"\"\n",
    "\n",
    "count_test.Count.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Days</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>series_id</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>100003</th>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100006</th>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100008</th>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100017</th>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100021</th>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Days\n",
       "series_id      \n",
       "100003       28\n",
       "100006       28\n",
       "100008       28\n",
       "100017       28\n",
       "100021       28"
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(count_train/24).rename(columns={'Count (hours)':'Days'}).head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Days</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>series_id</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>100004</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100010</th>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100012</th>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100020</th>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100028</th>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Days\n",
       "series_id      \n",
       "100004        4\n",
       "100010       12\n",
       "100012       10\n",
       "100020       13\n",
       "100028       13"
      ]
     },
     "execution_count": 122,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(count_test/24).rename(columns={'Count (hours)':'Days'}).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### In the data test each building is provided with the same number of sample trainings, namely samples in units of hours in 28 days. while in the data test, the number of data samples for each building varies, there are 4 days, 12 days, etc.\n",
    "\n",
    "#### Remember, Our task is to predict the building's energy consumption in hours, days and weeks in each buildings. here is the sample of submission"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>pred_id</th>\n",
       "      <th>series_id</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>temperature</th>\n",
       "      <th>consumption</th>\n",
       "      <th>prediction_window</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>102781</td>\n",
       "      <td>2013-03-03 00:00:00</td>\n",
       "      <td>19.931250</td>\n",
       "      <td>0.0</td>\n",
       "      <td>daily</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>102781</td>\n",
       "      <td>2013-03-04 00:00:00</td>\n",
       "      <td>20.034375</td>\n",
       "      <td>0.0</td>\n",
       "      <td>daily</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>102781</td>\n",
       "      <td>2013-03-05 00:00:00</td>\n",
       "      <td>19.189583</td>\n",
       "      <td>0.0</td>\n",
       "      <td>daily</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>102781</td>\n",
       "      <td>2013-03-06 00:00:00</td>\n",
       "      <td>18.397917</td>\n",
       "      <td>0.0</td>\n",
       "      <td>daily</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>102781</td>\n",
       "      <td>2013-03-07 00:00:00</td>\n",
       "      <td>20.762500</td>\n",
       "      <td>0.0</td>\n",
       "      <td>daily</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>5</td>\n",
       "      <td>102781</td>\n",
       "      <td>2013-03-08 00:00:00</td>\n",
       "      <td>19.800000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>daily</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>6</td>\n",
       "      <td>102781</td>\n",
       "      <td>2013-03-09 00:00:00</td>\n",
       "      <td>20.466667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>daily</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   pred_id  series_id            timestamp  temperature  consumption  \\\n",
       "0        0     102781  2013-03-03 00:00:00    19.931250          0.0   \n",
       "1        1     102781  2013-03-04 00:00:00    20.034375          0.0   \n",
       "2        2     102781  2013-03-05 00:00:00    19.189583          0.0   \n",
       "3        3     102781  2013-03-06 00:00:00    18.397917          0.0   \n",
       "4        4     102781  2013-03-07 00:00:00    20.762500          0.0   \n",
       "5        5     102781  2013-03-08 00:00:00    19.800000          0.0   \n",
       "6        6     102781  2013-03-09 00:00:00    20.466667          0.0   \n",
       "\n",
       "  prediction_window  \n",
       "0             daily  \n",
       "1             daily  \n",
       "2             daily  \n",
       "3             daily  \n",
       "4             daily  \n",
       "5             daily  \n",
       "6             daily  "
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "submission.head(7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(7529, 6)"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "submission.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### STATE THE PROBLEM AND THINK ABOUT THE NEXT STEP\n",
    "\n",
    "We have explored the data in understanding the problems we are facing. the problems we face are:\n",
    "\n",
    "\"\"We have electricity consumption data for each building every hour, there are 1383 buildings where 758 buildings as our training sample are used as input models. The remaining 625 are buildings that we will predict their electricity consumption in the hour, daily and weekly periods\"\"\n",
    "\n",
    "\"\"Training data provides 28 days of electricity consumption in a matter of hours. while the data test provided a sample of electricity consumption in each building in varying amounts is 4 days, 12 days, etc.\"\"\n",
    "\n",
    "What do you think is the next step, how will we manipulate the data to be input as our modeling later?\n",
    "in my mind:\n",
    "\n",
    "first, we can create 3 models in which each data predicts data in hours, days and weeks. the drawback in my opinion this method will make us lose a lot of information because our data will be a little because it is divided into 3 parts.\n",
    "\n",
    "second we make 1 model to predict the amount of electricity consumption in any period. in my opinion this method is better than the previous metedo.\n",
    "\n",
    "but why don't we try to try these two methods, just to experiment and have fun. but I will first try the second method because my hypothesis is that the method is better relative to the first.\n",
    "\n",
    "I am open to those of you who want to share their ideas and join in to participate in this competition. because I will need hours and even days to complete this project.\n",
    "\n",
    "See you next day Guys ...\n",
    "\n",
    "==============================================================================================================================\n",
    "\n",
    "kita telah melakukkan explorasi data dalam memahami masalah yang sedang kita hadapi. masalah yang kita hadapi adalah :\n",
    "\n",
    "\"Kita memiliki data konsumsi listrik setiap gedung setiap jam, terdapat 1383 gedung dimana 758 gedung sebagai sampel training kita untuk dijadikan input model. dan sisanya sebanyak 625 adalah gedung yang akan kita prediksi konsumsi listriknya dalam periode jam, harian, dan mingguan\n",
    "\n",
    "Data training memberikan sampel konsumsi listrik selama 28 hari dalam hitungan unit jam. sedangkan pada test data di sediakan sampel konsumsi listrik pada setiap gedung dalam jumlah yang bervariasi adalah 4 hari, 12 hari, dsb.\"\n",
    "\n",
    "Apa menurut kalian langkah selanjutnya, bagaimana kita akan memanipulasi data untuk dijadikan input sebagai pemodelan kita nantinya?\n",
    "in my mind :\n",
    "\n",
    "pertama, kita bisa membuat 3 model yang dimana setiap data memprediksi data dalam periode jam, hari, dan minggu. kekurangannya menurut saya metode ini akan membuat kita kehilangan banyak informasi karena data kita akan menjadi sedikit karena di bagi menjadi 3 bagian.\n",
    "\n",
    "kedua kita kita membuat 1 model untuk memprediksi jumlah konsumsi listrik dalam periode apapun. menurut saya metode ini lebih baik dari metedo yang sebelumnya.\n",
    "\n",
    "tapi mengapa kita tidak mencoba untuk mencoba ke dua metode tersebut, hanya untuk bereksperimen dan bersenang-senang. tapi saya akan terlebih dahulu mencoba metode ke 2 karena hipotesis saya metode tersebut lebih baik relatif yang pertama.\n",
    "\n",
    "See you next day Guys..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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