{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Using SD models to understand the differences between population measures at varying levels of geographic disagregation \n",
    "In this recipe, we will use data at a national level to infer parameters for a population aging model. We'll then try two different ways of using this trained model to understand variation between the behavior of each of the states. \n",
    "\n",
    "\n",
    "## About this technique\n",
    "Firstly, we'll use the parameters fit at the national level to predict census data at the disaggregated level, and compare these predicted state-level outputs with the measured values. This gives us a sense for how different the populations of the states are from what we should expect given our understanding of the national picture.\n",
    "\n",
    "Secondly, we'll fit parameters to a model at each of the state levels actual measured census data, and then compare the differences in fit parameters to each other and to the national expectation. This is a helpful analysis if the parameter itself (and its inter-state variance) is what we find interesting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "%pylab inline\n",
    "import pandas as pd\n",
    "import pysd\n",
    "import scipy.optimize\n",
    "import geopandas as gpd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##Ingredients\n",
    "\n",
    "### Population data by age cohort\n",
    "We start with data from the decennial census years 2000 and 2010, for the male population by state and county. We have aggregated the data into ten-year age cohorts (with the last cohort representing everyone over 80 years old). The data collection task is described [here](data/Census/US Census Data Collection.ipynb). In this analysis we will only use data at the state and national levels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th colspan=\"9\" halign=\"left\">2000</th>\n",
       "      <th colspan=\"9\" halign=\"left\">2010</th>\n",
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       "    <tr>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>dec_1</th>\n",
       "      <th>dec_2</th>\n",
       "      <th>dec_3</th>\n",
       "      <th>dec_4</th>\n",
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       "      <th>dec_8</th>\n",
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       "    <tr>\n",
       "      <th>state</th>\n",
       "      <th>county</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th rowspan=\"5\" valign=\"top\">1.0</th>\n",
       "      <th>1.0</th>\n",
       "      <td>3375.0</td>\n",
       "      <td>3630.0</td>\n",
       "      <td>2461.0</td>\n",
       "      <td>3407.0</td>\n",
       "      <td>3283.0</td>\n",
       "      <td>2319.0</td>\n",
       "      <td>1637.0</td>\n",
       "      <td>825.0</td>\n",
       "      <td>284.0</td>\n",
       "      <td>3867.0</td>\n",
       "      <td>4384.0</td>\n",
       "      <td>3082.0</td>\n",
       "      <td>3598.0</td>\n",
       "      <td>4148.0</td>\n",
       "      <td>3390.0</td>\n",
       "      <td>2293.0</td>\n",
       "      <td>1353.0</td>\n",
       "      <td>454.0</td>\n",
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       "    <tr>\n",
       "      <th>3.0</th>\n",
       "      <td>9323.0</td>\n",
       "      <td>10094.0</td>\n",
       "      <td>7600.0</td>\n",
       "      <td>9725.0</td>\n",
       "      <td>10379.0</td>\n",
       "      <td>8519.0</td>\n",
       "      <td>6675.0</td>\n",
       "      <td>4711.0</td>\n",
       "      <td>1822.0</td>\n",
       "      <td>11446.0</td>\n",
       "      <td>12006.0</td>\n",
       "      <td>9976.0</td>\n",
       "      <td>11042.0</td>\n",
       "      <td>12517.0</td>\n",
       "      <td>12368.0</td>\n",
       "      <td>10623.0</td>\n",
       "      <td>6307.0</td>\n",
       "      <td>2911.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5.0</th>\n",
       "      <td>2002.0</td>\n",
       "      <td>2198.0</td>\n",
       "      <td>2412.0</td>\n",
       "      <td>2465.0</td>\n",
       "      <td>2178.0</td>\n",
       "      <td>1699.0</td>\n",
       "      <td>1026.0</td>\n",
       "      <td>689.0</td>\n",
       "      <td>301.0</td>\n",
       "      <td>1673.0</td>\n",
       "      <td>1739.0</td>\n",
       "      <td>2260.0</td>\n",
       "      <td>2208.0</td>\n",
       "      <td>2233.0</td>\n",
       "      <td>1910.0</td>\n",
       "      <td>1490.0</td>\n",
       "      <td>739.0</td>\n",
       "      <td>324.0</td>\n",
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       "    <tr>\n",
       "      <th>7.0</th>\n",
       "      <td>1546.0</td>\n",
       "      <td>1460.0</td>\n",
       "      <td>1680.0</td>\n",
       "      <td>1762.0</td>\n",
       "      <td>1624.0</td>\n",
       "      <td>1237.0</td>\n",
       "      <td>774.0</td>\n",
       "      <td>475.0</td>\n",
       "      <td>187.0</td>\n",
       "      <td>1471.0</td>\n",
       "      <td>1577.0</td>\n",
       "      <td>1798.0</td>\n",
       "      <td>2016.0</td>\n",
       "      <td>1928.0</td>\n",
       "      <td>1581.0</td>\n",
       "      <td>1140.0</td>\n",
       "      <td>579.0</td>\n",
       "      <td>211.0</td>\n",
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       "    <tr>\n",
       "      <th>9.0</th>\n",
       "      <td>3741.0</td>\n",
       "      <td>3615.0</td>\n",
       "      <td>3393.0</td>\n",
       "      <td>3901.0</td>\n",
       "      <td>3773.0</td>\n",
       "      <td>3007.0</td>\n",
       "      <td>2227.0</td>\n",
       "      <td>1269.0</td>\n",
       "      <td>550.0</td>\n",
       "      <td>3741.0</td>\n",
       "      <td>4252.0</td>\n",
       "      <td>3312.0</td>\n",
       "      <td>3719.0</td>\n",
       "      <td>4129.0</td>\n",
       "      <td>3782.0</td>\n",
       "      <td>3052.0</td>\n",
       "      <td>1723.0</td>\n",
       "      <td>652.0</td>\n",
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      ],
      "text/plain": [
       "                2000                                                    \\\n",
       "               dec_1    dec_2   dec_3   dec_4    dec_5   dec_6   dec_7   \n",
       "state county                                                             \n",
       "1.0   1.0     3375.0   3630.0  2461.0  3407.0   3283.0  2319.0  1637.0   \n",
       "      3.0     9323.0  10094.0  7600.0  9725.0  10379.0  8519.0  6675.0   \n",
       "      5.0     2002.0   2198.0  2412.0  2465.0   2178.0  1699.0  1026.0   \n",
       "      7.0     1546.0   1460.0  1680.0  1762.0   1624.0  1237.0   774.0   \n",
       "      9.0     3741.0   3615.0  3393.0  3901.0   3773.0  3007.0  2227.0   \n",
       "\n",
       "                                 2010                                     \\\n",
       "               dec_8   dec_9    dec_1    dec_2   dec_3    dec_4    dec_5   \n",
       "state county                                                               \n",
       "1.0   1.0      825.0   284.0   3867.0   4384.0  3082.0   3598.0   4148.0   \n",
       "      3.0     4711.0  1822.0  11446.0  12006.0  9976.0  11042.0  12517.0   \n",
       "      5.0      689.0   301.0   1673.0   1739.0  2260.0   2208.0   2233.0   \n",
       "      7.0      475.0   187.0   1471.0   1577.0  1798.0   2016.0   1928.0   \n",
       "      9.0     1269.0   550.0   3741.0   4252.0  3312.0   3719.0   4129.0   \n",
       "\n",
       "                                                \n",
       "                dec_6    dec_7   dec_8   dec_9  \n",
       "state county                                    \n",
       "1.0   1.0      3390.0   2293.0  1353.0   454.0  \n",
       "      3.0     12368.0  10623.0  6307.0  2911.0  \n",
       "      5.0      1910.0   1490.0   739.0   324.0  \n",
       "      7.0      1581.0   1140.0   579.0   211.0  \n",
       "      9.0      3782.0   3052.0  1723.0   652.0  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv('../../data/Census/Males by decade and county.csv', header=[0,1], index_col=[0,1])\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###A model of an aging population\n",
    "\n",
    "The model we'll use to represent the population is a simple aging chain, with individuals aggregated into stocks by decade, to match the agregation we used for the above data. Each cohort is promoted with a timescale of 10 years, and there is some net inmigration, outmigration, and death subsumed into the `loss` flow associated with each cohort. This loss is controled by some yearly fraction that it will be our task to understand. \n",
    "\n",
    "<img src=\"../../models/Aging_Chain/Aging_Chain.png\" alt=\"Still Image of Vensim Aging Chain Model\" style=\"width: 600px;\"/>"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    ".. image:: ../../../source/models/Aging_Chain/Aging_Chain.png\n",
    "   :width: 600 px"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = pysd.read_vensim('../../models/Aging_Chain/Aging_Chain.mdl')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our model is initialy parameterized with 10 individuals in each stock, no births, and a uniform loss rate of 5%. We'll use data to set the initial conditions, and infer the loss rates. Estimating births is difficult, and so for this analysis, we'll pay attention only to individuals who have been born before the year 2000."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model.run().plot();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Geography Information\n",
    "\n",
    "This information comes to us as a shape file `.shp` with its associated `.dbf` and `.shx` conspirator files. Lets check the plotting functionality:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "        vertical-align: top;\n",
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>OBJECTID</th>\n",
       "      <th>FIPS</th>\n",
       "      <th>FIPSNum</th>\n",
       "      <th>StateFIPS</th>\n",
       "      <th>StateName</th>\n",
       "      <th>CensusReg</th>\n",
       "      <th>CensusDiv</th>\n",
       "      <th>XCentroid</th>\n",
       "      <th>YCentroid</th>\n",
       "      <th>Notes</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>StateFIPSN</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>02000</td>\n",
       "      <td>2000</td>\n",
       "      <td>02</td>\n",
       "      <td>Alaska</td>\n",
       "      <td>West</td>\n",
       "      <td>Pacific</td>\n",
       "      <td>-1.882092e+06</td>\n",
       "      <td>2.310348e+06</td>\n",
       "      <td>None</td>\n",
       "      <td>MULTIPOLYGON (((-2247528.774 2237995.012, -224...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>9</td>\n",
       "      <td>53000</td>\n",
       "      <td>53000</td>\n",
       "      <td>53</td>\n",
       "      <td>Washington</td>\n",
       "      <td>West</td>\n",
       "      <td>Pacific</td>\n",
       "      <td>-1.837353e+06</td>\n",
       "      <td>1.340481e+06</td>\n",
       "      <td>None</td>\n",
       "      <td>MULTIPOLYGON (((-2124362.243 1480441.851, -212...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            OBJECTID   FIPS  FIPSNum StateFIPS   StateName CensusReg  \\\n",
       "StateFIPSN                                                             \n",
       "2                  1  02000     2000        02      Alaska      West   \n",
       "53                 9  53000    53000        53  Washington      West   \n",
       "\n",
       "           CensusDiv     XCentroid     YCentroid Notes  \\\n",
       "StateFIPSN                                               \n",
       "2            Pacific -1.882092e+06  2.310348e+06  None   \n",
       "53           Pacific -1.837353e+06  1.340481e+06  None   \n",
       "\n",
       "                                                     geometry  \n",
       "StateFIPSN                                                     \n",
       "2           MULTIPOLYGON (((-2247528.774 2237995.012, -224...  \n",
       "53          MULTIPOLYGON (((-2124362.243 1480441.851, -212...  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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r9WZkXErZcLhvwqA5r9CK319ej4ocE37/7mE8tqER3zx9Nr68qiKDo0zItxrw4/MXAgC+/387EY6NnlkeHjricudLe/HR4X48+KU6SiYihExLGSuAIAgCbrnlFqxZswaLFo19tOHuu++G3W4f/lNWVpap4WVcS38Qd/1r35jvy7fqcdfnFuGlm05BkcOAdw/24n83NqPCZYbbL20VomR9/+x5WFV1rCNMjlmHqlwzurxh2I2J+7DX9nbj7lf2KzVEQgiRVcaWaq+//nr8+9//xgcffIDS0rGPSIw14ywrK5tWS7XBaBzffWYn/r2rE8fXfS+yG3D9uhpcurwMDAP8/eMWPPRWA4w6Dn+4oh7tAyGcubBQmYGPIAginvioCX/f1IIzFxRgaZkD7x3sg07LossTxht7uxEXRPzt2lVYdVzbNUIIUaNklmozEjhvvPFGvPDCC3jvvfdQVTX1/a/ptMcZjvHY0TqI7S2DuOc/J87GvnvWXFy7tgp6DYdoXMC5v3n/hAo/Xz+1GrefM2/U0RQlNfT4ceav34UgAsVDQf9/XtiDC5cW4/kdHZhTYMGLN54y6ggLIYSokWr2OEVRxE033YTnnnsO77zzTlJBc7rY0NCHxz9swvuHekftC9oMGiwqsaO2zIFPzcsfbkMGAFFewOHe0UGTYxnkW/WqCZpA4phMvtWALm8YHZ4w2gdDcJq0eO9QH245fTYeePMQfv7KPvzkAqo6RAiZPmQNnDfccAP+/ve/44UXXoDVakVXVxcAwG63w2g0ynlpRTT3B/DR4X7k2/RYNycfj37QiLteGb2PubomB7d+eg7qK5zjBkGLXoPllS5sakyU5lta5sAd5y1AncoKDJQ6Tbjrc4vw1b9swcnVLjT0+LGqKgf/2dOFpeUOAMATHzWjvsKJC5aWKDtYQgiRiKyB83e/+x0AYN26daPe/thjj+Gqq66S89IZ5QnFcOdLe4bL3wFAicOIDs+JtWBFEVheOXZW8Ug3rJ+FqpxOfGlVOWrLHFIOV1Knzy/AT85fiF++egAGLYdPL8hHRY4JtWUOGLUcQjEe//3sLqyscqHIPv1ulgghM4/sS7XTiSCI2Nzkxpahg/81eWb4wnH8+vWD6PCEsaDIBk8ohvbBEHp8YVy2shyra3Kwv9OH1bNy0OePYkGRdUrXOm1OHk6bkyfnpyMZo47D3EILtjYPwmrQ4g9X1OOef+/HBUuL4Q5E8drebjzy3hHccd5CpYdKCCFpo1q1Y4jGBeg0o0/qeEIxfPbB99E2EMLI+4G6cgfqKpyYF+Xxm8vqMBhMFEtnWQafX1aKw71+nL2wEBpu+rY+PWtRItN3a/MgDBoWP315LxYU2fDH9xtRnWfGbWfPw/2vH8TyChfOWlgwrb8WhJDpb8YHzkicxyPvHsHp8wuwoNiGN/d146t/2YIz5ufjj19ZPrwPadFr8F/rZuGUWbmw6DX4oCFRvOCG9bPAscf2Ki16DUqcQRzpDeDt/T1YPy9/vEsPi/MCHv+wCdeurZbt85STzaDF+UuL8ZePmrC9dRBGLYc39/fAbtSCYxjk2/SwGTW44e/bUGDT47wlxThjQQFWVblUlexECCFTMWMDpz8Sx09e2oOPjvTj5OocbGjow4FuL373zmGwDBCM8ojywnD1G45lcNnK8uGPP6+2eNznXl2TC6OWQ6cnPKWxsAyDJaWOtD4fpek1HH7zxTrc9uwurJmVi0hcwKX1ZYgJArY1D6BvqHBDtzeCP33QiD990IiTql3427UnjbrxIIQQtZux/TgbevxgGaAyxwyWZdDjDWMwFEOcF1Fg0yPHopf0ejPFgS4fwjEeO9s9eHt/D9492Isb19fgrxtb4A5EwTCAy6QbbqH27nfXoSLHrPCoCSEznWrOcarZrHzLqH/n2wzItxkUGs30Mbcwkfy0qMSOQ90+8IKI375zGI9csRx3vLgHFr0GHZ4QXGYd3IEojvQFKHASQrIKZWkQWXAsg6+cXIElJXbEeBHf/7+d+MrJ5Tjc68dgMIYie+Impc0dVHikhBCSHAqcRDZv7OtBdV5iNtnji6ChJ4Cnv3EyrlpdicFgDABQQLN8QkiWocBJZPON02qwelYuvn/2PFgNGrx3sBdLSh348fkLMSvfgnyrHqfMzlV6mIQQkhQKnERWn6srweFeP24+fTb6/FGEYzwA4I7zFuAPV9TDpJux2+yEkCw1Y7NqSeb0+SPwheNwmXSwm7RKD4cQQk5AWbVEVXIteuTS8R5CyDRBS7WEEEJIEihwEkIIIUmgwEkIIYQkgQInIYQQkgQKnIQQQkgSKHASQgghSaDASQghhCSBAichhBCSBAqchBBCSBIocBJCCCFJoMBJCCGEJIECJyGEEJIECpyEEEJIEihwEkIIIUmgwEkIIYQkgQKnysV5AZ5QTOlhEEIIGUKNrFVOw7Gw6hn8+YNGdHnDWDcnD8srXdBp6J6HEEKUQIEzC7AsA4YBHnnvCB557wjMOg5rZuXi9Pn5WD8vH/lWg9JDJISQGYMCp0KuePRjXLu2GqfNyRv3MYe6fegPRLG73YPLVpbh0Q8a0TYQQiDK47W93XhtbzcAYG6BFWtm5WLNrBysqs6BRU/fVkIIkQu9wipgMBjFhoY+bGsewGNXr8TKKteYj3tmaxvsRg0EETBqNbhgaTEefvvwCY870O3DgW4f/ryhERqWwbJyJ1bPysGaWblYWuaAlqNlXUIIkQoFTgU09PghiEAgyuMrf/4Yf7hi+Zgzz5vPmI13D/QiHOfBsgzCMWHS544LIjY1ubGpyY0H3jgEk47DqioX1szKxeqaXMwrtIJlGTk+LUIImREYURRFpQcxHq/XC7vdDo/HA5vNpvRwJPPqni5c99etw/9mGOCsBYX46toqLK9wgmFGB7YPDvWBY4Er/7wZUX7y4DkRp0mLVVU5OKnahVXVOZhbQIGUEEKSiTc041TAgiIbTDoOwSgPABBF4D97uvCfPV1YXGLH2YsKcdqcPCwqsSMc4/HCjnZ8cUUZ8qx6tA+G0rr2QDA2fC0AcJi0WFHpwspKF1ZWubCw2AYNLe0SQsi4KHAqoMxlwpkLCvD8jo4T3rer3YNd7R786tUDWF7hhNOkRVWeBbVljrSD5lgGgzG8vrcbrw8lGpl0HOrKHVhe4cKKShfqyh0wU7IRIYQMo1dEhUwlGG1pHoDDpMW8Ihte2tmBXIsOff6orOMKRnlsaOjHhoZ+AADHMphfZMUZ8wpQmWtGXbkD5S7TCcvJhBAyU1DgVEj/FAPg2QsLMa/IinZ3GBU5ZtkD5/F4QcTudi8MGg4PvHkIAOAy67C0zIGlZQ4sK3dgcYkDdpM2o+MihBClUOBUyP4u76SPMWo5bGsZwPwiG/65tRUNPf4MjGxs3d7w8N/dgSje2t+DDxv6EOUFCCJQnWvG0jIHasscWFxqx4IiGwxaTrHxEkKIXChwKiQSnzw7NhTjcbDbD1EUFQ2adqMGrQMn7q9W5pqxv8sHADjSF8CRvgCe3d4OILHEOzvfgkUldiwusWNRSSKYGnUUTAkh2Y0Cp0Iqckzo9IQnfVyJw4jwFIKsnCpyzNjZ5jnh7Xbj+MuzvCBif5cP+7t8eGZrGwCAZYBZ+RYsKrZjfpFt6I8VORa9bGMnhKhLnBfQ1B9EVa4Z3NBRuA0Nffjxi3tQW+bAVasrsajErvAoJ0aBUyGVOWZsPOKe9HFfXFGGrikEWDkZx1lyjcT5pJ5HEIGD3X4c7PYDQzNTAMiz6jGv0Ip5hVbMLbRhXqEVs/IttNRLyDT0xr4efON/t+LNb5+GmjwLnt/eju88/QnigohDPX48s7UNX1hehp9ftHg4sKoNBU6F3HzGbHzQ0Ie2MZZARzrc60djXyBDoxrbQHDshKT2QWkCeq8vgl5fBO8f6ht+G8skbi5mF1gwpyARSGflW1Cda6HlXkKy2Es7E8fwfvziHiwuseO375xYRvQfW1px6YpS1FeMXY5UaRQ4FRCO8fj5K/unVIx9rLOemaTlmDEDd45Zh15fRLbrCuKxfdNX93QPv51hEsvX1XkWVOeaUZVrRmWuGdW5ZhQ7jKq9QyWEAIFIHG/uS/w+v3+ob9TN8vFe29NNgZMcMxiM4bU9XVNKEFJada4FB7p9J7y91GlEfyCzR2OARJWltoEQ2gZCeO9g76j36TgWFTkmVOaaUTn8fzPKXSYU2Q1UEYkQhb2xr3tKNbeBRGnS286Zp8oz4xQ4FVBoN+APV9Tjqsc2Kz2USY13PlON+49RXsChHj8OjZGBrGEZFDuMKHMZUeowodRpRKnLiJKhvxfYDDRbJURmLyaxgtbUH0RDjx+zC6wyjig1FDgVEIryo5Yf1Wy8BCDVdgYYR1wQ0eIOosUdBNB/wvs1LIMCmwFFdgOKHEYU2xN/L7QbUWg3oMCmR65FP6NatL34SQd0HIuzFhao8q6fZBdPMIb3DvVO/sARXt3TRYGTAIIg4vT73kGHwpmyU9XqHjt5aV+HZ1Sh+mwXF0S0D4YS9YCbB8Z8DMMk9nbzrccCaa5VjxyzDnnWoX9bdHCadXCZdFm/NPzijna8sa8Hf792FVbPylV6OCTLvbqnCzE+uVvu1/Z248ZPzZZpRKmjwKmAmnwLev2RpH+IMq3QpkeXd+wEIF+Ex6oqFz5unPxIzXQhikCfP4o+fxR7O8d+zNwCCw50J5aKbQYNcix6uMw6OE06OExaOIxa2I1aOExa2IxDfwxa2AwaWAwamPUamHUaVSwbH51l7mr3UOAkafugYfxEoPHsbPOg0xNCkd0ow4hSR4Ezw1iWwb2X1KJ9IIRntrXh7f3d6PTIl52ajmKHcdzACSRmaWQ0XyQ+/HdvOA5vOJ7ScSKjloNZr4FFn/i/Wa+BUcvBpONg1HIw6DjoNSwM2sT/tRw7/H8tx0KnYaHlGGhYFhzLQMMy0GkSM2COZcAwAMcwYJjE348niomlNSBxJIqQdLnMupQ+7o293bji5EppB5MmCpwZFonzOOWet4Znm6uqXLAbdTjY7YPa4tBks55Ymk21pyNvKD75g6YgFOMRivHokzBmraxyYVMKKwQHuk7MqiYkWSWO1GaNr6kwcGb3JkwWemVX56gl2o8b3djf5UN9hVPBUY3NPclxE72GfnxG0rCAPyJN4JTDQIrHh/Z1+WQ9s0umv2hcwD+3tKb0sRuP9MMXjkk8ovTQjDPD/vJh85hv39w0AJdZN2mwyhS9hkFTf3DCx+xsG8T8Iiv2ddKMBADsRp0iZ1un6lCPHxYdB3+SCV3RuIAz7n8X5S4TFhbbsH5ePuxGLVZWusCyDJr7A9jWMgCzToNV1TkT1jAmM1Nzf2DMY2JTEeNFdHsjsBrU83NFgTODYrwwYZcTp0mrmsBZnWvBvkmW6CJxEfs6fVhe4cSWcTJRZxKrQaPqwFlkN0ypscBYPKEYdrV7sKvdg6c2J2YO/++LSxGJC/jZy3vhDSdm2g6TFt/81GxcflLF8J4qIenuQn3xkY/gNCUy1p/62klgFU6eo8CZQR809E24lNejouUwaxKzhi5vdhytkZtZr76iECMNhqRd7rr5qR0nXiMYw09e3ou/fNSE286eh8pcc+IIj80g6bXjvJD1x31mkupcM+xGLTwp/gwezWYHgO2tg4pvbdFPXgZNVDWj0GaAL6ye/bFwbOrLeW0DISwusck4muyg16g7cPIZzD5r7g/i+r9twzn/733c+OR29PhOvLna2jyAf+0c51zPOAYCUXz9iS3Y0zF5I3iiHhqOxffOnivJc3V6Jm6MkQk048yQRLWgrnHf3+UNY2WlC7vaBxEaUcuRYwAljns2T7K/eTwGyp87VJpGBWcvJ1Jg049b0EJOmxrdWPXzN3H9aTW49dNzwLEM/ndjM+58aS/yrHq4AxE09QcxEIjCF4njG6dVo77ChRgvIM6LMOo4iKKIF3Z04P7XD+LOCxaitsyR8c+DpOcFiRpWPPLeEXQMhrCnw4tfXrxEkRtWRhRFlR2COMbr9cJut8Pj8cBmy+4ZzQs72sdc2jpenlWPqlwzRFGEJxRD20AIZS4THEYt2gaCkrXymkiJw5iooJMEi46DSa9R1XJzpqm9IIRJxyES4xW5ETvKoE0sck1U6Nuq16A8x4SVVS58+8y50HIMvv7EVrS4g3j4S8uwoDi7Xwtmok2Nblz6h48kf95Ll5fins8vkaQkZDLxhmacGSAIIn43Rs+5sRztTTnS0XN0DAMsLXMgFOWh1TAwaLjhpBwNm8jqjAyd/3OYdPCFY4jyImxGTVLnC3PMuqQDpz/Kw2nRId+qn7HBU1DvPSgAIBjlMa/Qiv0KnsucrDMGwwCrql347lnzMLcwUaOUF0R89ZQqrK7JoX3NLBTjBXz3mU9kee5/bmnDuUuKcdqcPFmefzwUODPgzf09krxYiSKwo3Vw1Nuqck0wajU42O0bldF59O9FdgO6vWFY9BpU5Zph0nEYDMZwuNeH8bqa9fpTC3yt7hAqXKYZm2UbzYI2cTaDOn/lC2x6XL6qApcsL0OhfXQiEccyODXDL4xEOoe6/Ulv/UwVxzKozjXL8twTUedv0TTzxEdNsj13Y9/EP5BHjx/4I3HsavcMv12nYTEvP5Hp5o/EcLgngPDQC7+WS33Zo9kdRJ5Vn/LHZ7NQEglVStnX6YNRy47aR1fa1Wsq8b2z5sGoS36vKhoXsK/Ti3CMR32Fk2akKiRn8YIrTqpAmcsk2/OPhwKnzFr6gxN2OVdKNC6MmgVzLIOaPDNyLHqYtCxa0kgiSXXGmu3UXDXoKF8kjiUlduwccROlFJYBfnHREly6oiylj39qUwt+/so+OM06fK6uBPOKbLAbKXCqyQs72mVpSecy6/DQZXU4uSZH8ueeCgqcMnt6a2plpjKNF0Qc7g3gcG8ALnPqFToWFluxp2NmVhI6WhRd7Y4m6CjtgS/W4fza4pQ+9rntbbjt2V3Qa1j88SvLMUeFPRtnsme3teHFTzoQivKSJ8yZdBweu2qFopnV6vgNmqZ4QcTzO9qVHkbS3IEYVla6UjpgouXUfZZRLlqWQSBLepOqoSn1dadWpxQ0RVHE/a8fxLf+kUg2efTKFRQ0Vej9Q31450AvBiW6mXSatKgrd8Bp0uKRK5YrfhyJZpwyemVXpyLn5qSwqcmNFZVObG6aepKPy6QbtY86kzjNuqzJJlY693fNrBx856zUDsM//HYDfvPmIQDA+rl5OGU29QlVm2hcwGAokZx4oNuHHHNqNZx1GhbRuIDqPDOuWl2JfKsedqNOseXZkWjGKaM/b2hUeghpYZOcmcwusGS0Oo2aWFWarToWJY9un1dbjN9fXg9tkkk8oijima1tePjtY8e6rl83C49+0IgH3zyE57a3oT/FvfW9HV58/YktuPfVAyl9/EwnCCL2dXrx2IZGXPuXzaj7yWtoGZFFW5OXfNbrklI7/ufc+QCAWz89By/s6ECORa+KoAnQjFM2B7t92N4yqPQwUjav0IqtzcntTbQlefZzOkklI1QpSsXNzy4pwgNfWDrc51UURfz2ncNYWeXCikrXmB8jiiIOdPvwk5f24sPD/aPe9/GRftz3+sHhf5t1HP545XKsrhl/FuoJxfDani58dKQf4RiPXl8EW5sHIIg4oatLtzeMF3a047NLilGcYi/J6YgfCpSbGt34uLEfHze6T1iSHXn/7E2hlGhjXwAX1pVgdoEVvb4w/v61VdCpKGOaAqdM/rE5O5KCxuIya9HjDY97znMsFh2H9oFjgVPDMojPoNmnXkW/1JNRYkn5u2fNxX+tqwHDMBBFER83uvHH947gzf09eOhLdSc8vtUdxNee2ILm/uC4x3xGBk0ACER5/M/zu/HCjafAoj/xpW1/lxfX/mUL2gbGvsHb2ebBs9vaIIiJHpAvfdKBSFxAfYVzRgdOURTR0OPH5iY33tjXg81N7knraudadGjsCwBITCLsRg08SRRhWVHpQqs7hB5fGCdV56iuDrSsgfO9997Dr371K2zduhWdnZ147rnncOGFF8p5SVXwhWN4Zmub0sNIWXWuJekCBoIoor7cia0tA1hW7kBTXxBaDYNub3bs+6WLY7MncMaFzJ7hPGN+Aa5eXYlefwT/3NyKF3Z0DPdmrMkz49zFRcOPFQQRGxv78YPndg+/8CbjcG8At/5jB7539lxsaRpAvk2PVVU5ePtAD27/v13wTXBk6EC3D7f+c6wKN8onU2Vavz+CDxr68O6BXnx4uD9RS7vKhU1TzJDd3jIILccgxosQRGB2vjWp15TGvgCMWhaBCI98q7SddaQga+AMBAKora3FNddcg4suukjOS6nKXz5sSrl9jtIWFNlSqvoTjAnY1+lBTZ4Z24aWqJdXOGdM4FRBouqUGTJ4976gyIoNh/uw7Gevj1luz2nS4fO/+xBGHYfT5xXgH5tbcaA7veNMr+3txmt7uwEkzoqyTHqrH839AdRXONExGEKPL4LaUrsqMpOlIooi3jnQi51tHuzv8mJPhxct7hMLqwSSOKdc4jSOqhYU5ad+s8YwwCXLS1GVZ0FVnmXKH5dJsgbOc845B+ecc46cl1CdHm8Yf3jviNLDSNlAMPVAF4wJONx7bJYQS+KXJdtl07J0ry8CLcsgloExm/UahCY4pjPyJm1DQz9q8szDMxUpCGL6NYRve3YXglEeLpMO//X3bfjphYtwxUkVkoxPaaIo4n9e2I3/3dgy6WOn2gS92GFA+Ljv+f4uH/QaBpH4xN8LlgH2/fRs1S3NHk9Ve5yRSASRyLEXbq83u3ruiaKIHz6/W1V9NaeKYRIzxGSOn0xGq8me5ct0ZUOd2qN8kTiWlTuGVwbklGzMOtwbwOISOzQcgy5PeMov1qmy6jV4+vqTYTdqsavNgw0NfdjROogCmwHnLy1Gc38Qi0rsABKz50euqMf8ounTneW37xyeUtAEAHcgOukRtVn5FrQPBE8o6RiNC1hSasfOtvGPqzlNWnxhRbnqgyagssB59913484771R6GCn7167O4SWibKLlGFTkmCQNmgDAz6AZZzbUqR0pU8Ua+BRmeyPPAtsMGpS7TImZa4zHvk5v2rPRNbNy4DDqUJ1nRn2FE/MKE4GwyG7EmQsLJ/zYyd6fTV7Y0Y5fJXkEZ+SK0ljivDBuHWTdODfSPzx3Pvr8UVx3ajWcZl1S41GKqgLn7bffjltvvXX4316vF2VlqdWxzDR3IIo7Xtij9DBSUlfmxKYm6ftINvQGwDDKHX/IJEEQwUD54gJTdaTXn5HrpHuu1xuOY3fHsZUnlzkR8EJRHlFeQCASR7cnPKUeoxzL4KyFBfjtl+snfFxjXwDPb2/HFSdXINcyPRsWtA+G8N/P7kr649yB6IRLrq3jZCwDY//MFdoM+OopVVm3Z6yqwKnX66HXZ+cP6p0v7UmpOobSzDpOlqAJAL5wHHMKLDjYnZkXaSV1esMQkZgh2YxamHUaGLQstBwLlmXAILHXFucFRHkBwaiAUDSOQCQOf4TPeMCN8SJcJi3cMtbX5RjAIPFyvTsQhfu43zObQYM4LyA4xkzn/Npi9AciuHp1FeKCAJNu4pe8N/Z247r/3QpeEPGH9w4j16JHmdOEP125HOYxjrhkI1EU8T/P705p1SHXokOff/zXOZOWGzdz2R2IndAPNhznsy5oAioLnNnqqU0teGFHh9LDSEm+TT9pa7J0xHlR0mQPNdJyzHACjDccT+nAt1HHwazjYNRy0Gs56DgWWo6BhmXBsADHMEPBVQREBrwoQhBF8ELiT5wXERcE8LyImCAgxifexovH3sYL4lCyTOKaEx3NSFdlTqLV0yaJl//HEorxqC11ICYI+KT12DJvicOI+y+tTarV2J8+ODI8Sw7HBLQNhNA2EMLqX7yFz9WV4KJlJVhckt1ZtTtaB/HW/p6UPna85dajjLrxAyeAE24+Pr+sNKVxKE3WwOn3+9HQ0DD878bGRuzYsQMulwvl5eVyXjqjnsriYgeNfUHMyreMeScvhSN9AVS4TOj0hpNOoMm36rOi/qvTlH6d2lCUnzD7VA6iTFm1Ji2LgWAsY0eyYrw4nJ3rNGkxMDSLvuLkiqT7c373rHn4xb/3nbDf7wnF8PiHTXj8wybkmHX47JIi3HnBImk+gQxyB6L46ct7U/74jsEwSh3GcauE2YzaCX8Xjj+bu7A4OxOtZE173LJlC+rq6lBXl6gMcuutt6Kurg4/+tGP5LxsxkWyKKNyLEd6/bK2mmp2BzE7P7nzWIU2A3p8EVgNGiwqsWFlpRMrK12oK3egJs8Mk4pK3I1VpUbtVla6MMnJgJQtKrUrdo55ZOnDkYUVpuKJj5pw09+3TZok1x+I4omNzXjnQGqzNqUMBqO47JGNaWdTFznGL0jgMk3cknAgGB31mKUKdzlJlay/8evWrVO0oHSmhKLZd/xkpNn51rQPnU+GncLKFssAcwoSeyAFNj26vGH4wnHsbh/7WJLDpEWeRQ+rQQMNxyIS5+ENxdHtDSOYwdmbmoL4VCRTASYVSiZT51n06BgM4+TqHJS5TBAEEbwoTlhU3huOgedF/CiJ5D6nSTdhIowa3fTkdkl+zzsmOCI02SRCFBNnnhcW29A2EEJVbvIF4NUg+26VVWYwGEV7lhc312nk368x6jRYWGyDScchzosIRONwGHWICcLweb1lFU5saRrA3EIrDNrJg9FgMDZuvz+7UYM8qwFWgwZajoUoigjHBHhCMfT6IpIeH5ls30dtPMEYNCySqkWcjK3NA1hZ6czI/ubxjv7c3HT6LADAD57fhfNrSybsqvGtp3bgt5cvQ4nDOOXf5VCUx7o5eekPOIPCEv3Mi6KIIrthzDO2U/ld8IbjiMYFnL2wIGv3iilwpmlL00BWJ76UOIzYNc6MTkrbmwdgM2rHzTw2allsGXqhNem4tKsOeUJxeELjZ/M6TFoUWA0w67nEPthQYPVF4vCEovCF41P+via7j6a0A90+1Jba0eoOypZVq1QhpQ5PCHVldqyuycXudg+e296OH567YNzHv72/Z6iqDZfUykEoxuPc37yPjf99+qSZumrx5NdOwn/2dOHGv29P63k6BhMBsybPfMK5zql+3w/1+HH1mqq0xqGk7PiOq1ggy5dpS5xTv8tOR0wQJzyuM/LQ9PaWQcxKck80WRPNVo+y6Dm4zHpYDRwMGg04LnF3HOcFhGM8/JE4BgKxtEu6KeGTNg+WlTvglql60KBCe5xtAyH87MLFiMR5/OiF3fjC8rJxj5E8/HYDfvXqAZw2Jw+dnhBaB5LLLveG49jZ5sFJ1eroETkZDcdKWjvaZdadEDinem53QZEVZc7s7ThDgTNNOebsPHd6lFTLN1Lr8ii//O2P8PBHJn8xVevXcDJy1tftVSgb+hcXLcaps3Nxyz92YFvLIO67dOm4j31yU6LU3JE+P857cMOYRegnk2yzd6UtkLBc4Fg/Pg09k5/ZPrrH/uInHVibZcvdR2XXGpMKnVTtwknVrqzMrAQwZhcEpbnMOvgj2ROMMn2MRCpyTpT1Cuz7FtoMuLi+DI9/2IQXdnRg3dy8cZNP7n31ALqG9uha3SH0+VML9NlUoxgA6sodkj3XWF+zyfY4a/LM2DxUcOWFHR2yHIHLhOx8tVcRTyiGjUfc4BhgUbENZr0GXd7wqJY6alXsMAzvV6hJoU2fVb9QfhkLCchJzrlSwdBxokw6a2EBGACPDHUnunJ15biPbXEHJZlxOyY5fqEm/9zcikc/aJTs+VrdQRg0LMIjbh7yrcd+dzUsUJljhsuiQywuom0wNGpp99wlRXBlSW3a41HgTFOXNxF4eBGjamrmWnSoyDEhzos42ONX5aykyG5UZeDMttJm2dp7Vc7I6Q5m/sZnfpENVz2+GZ2eMEqdxgmzXq2G9H/GHvpS3XDnFLV7e38Pvv/sTklXGQQRmFVgGT4uVuwwwKTjcHJNDvp8ETT1B9DQGwDGKQx/VhYXzM+uVygV4sY5oNjnjw7XdNSwwPwiK2wGLfr8kUk7DGTKVM5WKiGbUtT1GialvbHpzqrXwKLXZHQ2/t/P7Rred5tfZJvw5yiVsojHG3l4v6HHh32dPpy1sFB1x5O2Ng/gu898IsvSvMOoxeISO1rcQXQMhpO6Ed/T4YFJx6G+wpl1N8vZNVoVmspMMi4A+zqPHTzOGerwEI0LONDtU+yFV6kEjskEs2jp02HUoVulX8fJyHl7sr/Lh5o8MxaYbWjo9Wdk6X3kyutEXU1CUR7vpFir9ai6csfwNR566xD+35uHEONFfGZxIR7+0rKM3PyJoogubxgHunw40huACGB1TQ4qc8z468YmvHuwF93eyJQSdlIV48VRbeCS8eBbiXKsyyuc+N9rV8Gg5dA+GEKrO4hciw6z8q1SDlVSFDjTtD2FdP7+QHT4aIaWY7CoxAajlkPHYDhjxRRMOg5NKt2H7U0xUUMJVqMmawOnrJETid6Nh3sDqMkzo8huwJ6OzDWm39Mx/ov5a3u70ipwf+8ltbi4PlGc/P1Dvbj3tYPD73tlVxc+OtKP1TW5KT//ZBp6fPjdO0fw2p6xPw+rQQOfBDPqTNnSPIA7X9qDuy9aghKHESUOI57c1IKqXMu4K3pKo8CZBkEQ8deNzWk9R4wXR5WUK7LrUeo0IRoXcKQ3IFsHi6pcc0ZfyKbKoJX2rJncjFOocKRWjNyRc8jh3gA4BphbaMWBLnlLOx714/MXjvu+pjS7AZW7TMN/f3xD0wnvf+dAryyBkxdEfPeZT/Dc9vYJl13VHDR1HAOjjoMnNHqMT25qxXlLirF6Vi584Rg+ONSHUqcRa2er87gKBc40vHeo94Rq/+nq9ETQ6UkEDgbArHxL4nhGOI4jfX7JlnXVenym2G7EEYm/pnLSa7I3cGYSLwK93jCqcs2S/84cr8RhxLJy57jvz7eld/b6zx80YmmZAy9+0oG3xij0vrVZnlKDHMvg/UN9WdUYPteiQ6nTBB3HQsMy2NY6gHBMQI5Zd0JBlO88/QkWFNvRH4jgM4uKYDeqN2NZna+eWeKfW+RtJybi2IHiRIaugHmFFtiNOnjDMTT0+FMu96fWikfZlN4PAKxKl5KmItMjdwdj8IZjWFnlwrbmAdkKMEwWGGvy0qtK9Z89XVj9i7fgDkTGDGLbWwYwEIjCKcNRi8tWluM3bx6S/HlTdfznX+Y0otBugCAA7YMhdHnDw0mSq6pcwzf+C4pM8EdiiAy16Ln103Nw/+sH8bllJfjWGcugGaovrVYUOFPU6g7izX2ZaytUYDWguT+I/V3HNvq1HIP5hVZYjVp4QzE09gWm3OKsSaWzuom6WKhR9oZNQInk5bgAbGp0w2HSwqLXoE2GDiN72r3gBXHc/bHntrenfY2JCiYIIvDuwV5cWFeS9nWOd/Pps8ExDH79xsHJH5wBOo7BqioXglEeLe4gWgdC43aNGbmEnGfVYz7s2NE6iG+ePhvXrq2CRc/hqtVVwzejoRiv2jrA2fUqpRKeUAzX/XVrRvtwhuMnZu/GeBH7unzY1OjG/i4f4ryAWfkWrKx0YWmZfdzDxeUuk2or80TH+DzVLJ7FBf6VNBiMwW6U50XRMskZzULb+P0kpfLqni5ZnpdjGXxhRZksz52KvkAEHze6savdM+l55oPd3uGKUlW5ZnjDMVy9uhJfWlmOnW0evLqnG5///YcAEsldt/3frpQrOslNneFcxQKROL7y503Y25m5xBqWAY5MIaWcF0+sFVlk16PYbgTHMuj1R9DUH0S+Va/KUnuAMgfn0xHhsyvQq4kcs00AOG1O3oTZmFefUonfvdsg6zGwN/f1oNMTQpFd2kLmnmAMl/1xo6TPmY4299S/h3EBKLDp0T4YQq8vgge+sBSLS+xgGAYFNj2+e9bc4b3pBUU2PPCFpardCqEZZ5J++PxufNI6mNFrVudZ4E+x8lCnJ4KtLYPY1DSAxr4gjBoW4RiPVVUuLCiywaiiJswsA7RnWXPgTDbMnm48oTgK7dLP/uorxk8MAgCbQYsvriiX/LojRXkBT37cIvnzPr21VdbkKptRA0sSrwn+KJ/UDN6k47CyyoWr11RhSalj+LwrwzBYXukaDpQMw6g2aAI040xKry8iyf5IsqSs5xiMCaNKAzIAKnNMw4e5+wMRNPcHFemnWOwwyjYLkYtfxan/UuKYxDLh0T8ajgXLMNCyDDQcA83Q2zQsC47F0P8ZsGyigwgDBgyTSHgTRRGCCPCCAIZhhoutS2Xt7MmPgtxyxmy8sKMdAzL1IwUg+Sbyg28ewn2vS7e3yTFAZa4ZLrMOggh0eRLnyMtdJhRpWByaYuGEfJt+uPToeHLMOnxpVTlOn5eP2jJHVlUHGwsFziQMKLSMKGclHRFAU39wVDEEvYZBVa4ZdqMOUV5Ax2AoI2crcyz6rAucSvWdTNe8Qit2tXmg07CjEpxG9hblBXH4BooXAZ4XE39JvEWScSwrd4BlpG18PRiMoWKSFpkOkw5fXFmO371zWLoLH0cr4Yzp1T1daQVNlknkNuRa9GAYYCAYQ3N/YLhIxUgt7iC0HIMCq35KxT0M45xltuo1WFJmx0V1pTh3SdG4j8tGFDiTMDvfgsUl9pRLTKVCwzI41JOZQ+NHReLiqOxdADDrOJS5TLAbtQjFeHR6wpKX7DOorMbnZIxadlQD7mwS5QXEBFHaiJWCbS2DWFhsxZ4O6X7GNzW6UTuijux4Vla5ZAmcVr0GZy8qlOw4yj+3tOK/n9015cczAMpcRuRZ9OBYBoOhGJqHbo6nWi0sxosocRqnFDjj/Ojfgc8vK8V5tUVYMysXWo6FPxKHLsuy5SdDgTMJDMPgu2fNxVf+vClj16zJt2Ss2spEAlEe+48bR65Zh2KnEUYth3BcQJ8vgg5PKOUD2jE+u4KQzahFdZ4OOg0HLcuCGZo5xXkBkTiPYJRHIMrDF46prhB8pyeM2jI7PmnN3E3gWEocRkmDJgBsa5laAYL6Cmdi+Vjie4dT5+ThiyvLMb8ovVqr4RiPHz6/G7vaBsc986rXMCh3mWEfOv88GIyh1R1EizuEliQSd8ayrWUQq6pc6PCE0DrBc43MLL+4vhT3fH7JcHJWpyeECx/eAAD43eX1ExamyCYUOJO0dnYuVlQ6sblJnuogx3OouHqG1ajBzrbRL7xajkGp0wSnSQsNl0hE6vVF0DmFfaxsa89lNWin/KKvZRlYjVqY9RxMWg0MWhYajkns/w3t94zc+4sLIqJxATFeQDQuIhLnEY4JCMd4SQoHhKI8NKzyswA5apFOtX60zaBFnkUved/Qk2tyJk1QmkyPN4yv/XUrPmkdxIrKxHMV2vTItxlg1HKI8gL6/VG0DgSnvBeZio8b3TBoWZxcnYNwnMfuds8JRVcMOg4mHYf7L63F2YuKACSC/jNb2/C7dw6jxxfBDz4zH3VTWAXIFhQ4k8QwDL60qjxjgVPNdSddZj0aj6v7GeNFNPYFcHy7XKOWRbnLDNvQ2b1AJI4ubxjuwLFgmW0ZtaYk9mxiggh3IAq3BAmRDBI1fXUaFlou8ceg5cAySKplnRoqs7QNBOEyaeGWMEkn8XMVnVJSXVTiVY6zFxbinEXp9ZnceKQftzy1YzjhpqHHD5OOQ5c3gi4F6jjPK7ThoyP9ABJZsYtLrBABHOzyIRDlYdJyePq6k2HUJbqbPLetDY9/2IQ+fxS5Fh0ev3olTpugN2o2osCZAjk7H4yk5Rg0ZHh/MxnJzBZCsUQLteNZ9RyKHEbkWvT48HC/lMOTnVJ9F0Ukvp7H768atSxWVbmwrWUATpMO5S4TGCaR1RrlhVEzMS3H4OAY349MSzRDtmJTo1vS523sC0wpcEYkXkL/+UWLU86Cb3UH8cj7h/HXj0YfY5E183cKtNyx3/NglMe2oZ8jDcugwmXCpxcW4J2DvfjVqwdGfdypc/Jw3yW1yLOmVxtYjShwqlhNnuWEfUU18UiQZeyL8PB1+7MyeUBt58xCMQEfN7pR5jLCE4phy3HFxucVWmE1aLCv04cSh3HMGxklbGp0Y0GRDVaDBpsa3UhmHswAcJq0sBo0MOu10GsTxcT7p1BxxhOKIRST9hyuQZv8z/FAIIrfvHUI/7uxGXFehJZjUq5BLbVCuwHbx9kzjgsiQjEeGxr68MquY5WS9BoW3zlzLr56SpXqfkekQoEzBUeSWA5Lh03F+5tA4g5ZKiYVFWKYKrW+JIyXyHH0Jsxl0qHFHUSpw4i2DPV/nczRSlynzs5FMMqDZTB8DlIQRMQFEXFeQJQXEIkn9noDER7+SBzuYGxoqffY53Ll6slnkh9JvMKxdnZu0rVV/7O7Ez98fvdwIXQgkTClll65Vr0GveMUSdNyDHp8keGgWWgz4LNLinDl6kqUjWi9Nh1R4EySKIr4+Sv7MnItKWZ0cilxGCVtuq2O++vkxAV1ZcpOlTsYxfIKJywGjWoC51H7u3zIs+rT7hU7WYa2KIr40/tH0rrGSGYdh/surU3qY57c1ILbxzhm4jTrVBM4+/wRaDgGfPzE39DLVpbjQJcPVblmXLSsFMsrnNN2hnk8CpxJauoPZuQcp1HLnVB3Vk3yh2pOSkXNSVDjUdsRk2QcXcZV07IgAMkyXH/zZgPOXFAI8zh9Z3e0Dp6wlJ2OC+pKkG+deum5XW0e3PnSnjHfp6ZtizkFVnw8xv6z06RFVa4Z3/703OGjMDOJer5DWaJ7ktJSUpmVb4GKXs9OIHX7r8lKdqlRaBrUqS2WoVZsunp8ESwpsY9KSklWY19gwr6Vr+/tnvJzHV8ByGXSYX6RFSsqnVhR6cS8Qive3t+D2/5vJz441Ad3IIrwGHun/kgcHx/px3Pb2/CVP3887o1XJrsuTabTE0ZNnvmEtweiPF7e2YlzH3wfgsJFNJRAM84kSX3mazxGlZenkrIMoN2oxaDCmYOpyMZZ8vEcZh2a0zwoL4ed7R6srHRiUxrHvl78pAO3nTPvhLqoh7p9eOKjZgCAScvCZdHDZtDAoOWGGyhH4gJ84Tj6/RGE4wKWlzvgDcXQ6QnDHYyO2cXnqc2teGrzseb2Fy4txs8vWoxQlMfv3z2Mpza1wjeF3xt3QD1bNC3uIIw6Dk6TdlR2bzQuYOvQjH0gGEWOZfplzk6EAmeSpC4zN55MzWxT1TIg3R5Mod2QdcUPAOVqF0tKxZOFQJoz+k5PGG/t78Hp8wuG3/b2/h7c//pBOExaCKKIYJRHcArnh9sHQlMq4jHS8zs68P6hPohILhi2DwShYRlJCl1IIRTlYdRy45ZGVNNSf6ZQ4ExSiUP+pS2XWYdmlfbLBBI99aQs+m4dZx9KzSx6TrXNwJPxSZsHNXnmpAonZIoUqy4Pv92Af+3qxIpKF17e2YENDall0jpNuqQDJwD0pzB75EWg3GlUVc9cdyCKgWAUi0ts2NU+OnEr20plSiH7XrEU9ukFhZhfZMM+GRtZV+aYVLVcc7xCu1HSwLm7w4NZeWbYTTpoWAbhGI+BYBSdnrBq72btRu20CJxA4kZNbYGzzGmUJHnHG47h2W3teHZbeu0AM9231mXWqSpwAsCKSteYhSoGgzGUuRQYkIIocCaJYxncfs48WQu9q71XndRdTMIxAQ29AQCjX7wZBsi36pFr0cOk58AxDKJxAZ5QDJ2DQYTGSJHPFIteC0Ddy+lTpcabk2KHEa0SlGD0hqTZh5ajpu5E9CrrFLSw2DZudae2gSAWl9ozPCJlUeBMwdrZuTip2oWNR6QtE3aUlIUF5BCMZiYpRhQTyVhjJWTNzreg1x9BnkUPq0EDLccmKplEeQyGoujxhiFncmIqFWLUam+nF4U2vSJ1UEdymbRwmnVwmnXY1CTN79agRPvQmc4cVdOts1WvgT88fg6CVO3TsgkFzhQcbS/2+d99JPlzFzsM6BhU90xGDcXY+/wRDAZjE2bj5ph1cJl1sBg00A1lS4bjAryhGPr8kbSWWpWqUyuHaFxAqdOkaOCsK3Nge+tgogKQhMvGUV6EUcelfXQomMGjRxYdh94plAyUW22ZHTa9Fge6feNmXpt0HOrKHZkdmApQ4ExRfYULi0ps2N0u7V5nnkWv6sCZY9allPAgJaOWnVLh6/5AdMKxWvQa5Fp0sBoSNU45hoEgJtp5+SNxeEIxuAPRMXs9sypfTk9Wh8IVhOSsyew0adMOnFLNXKfCH+VRqUt0u1Eisdai4zCvyIbtrYM4ZVbuhEfwrjipAnqNuo/OyYECZxrWz82XPHC2D4bAQL2nBIodRsUDZ6HdiMa+9Gcl/kgc/imcq7MbtbAbNTDrNdBrOOg4BjoNixWVTsR5EeE4j+BQ3VRvKIaYSo4RJGMqXwc5zS+yDnfdkJpVgv3oTM8AtRyLYrv8tYQ1LFCRY4bLrIMgAj2+MFrdIQwEo+BYBpW5Jrx7cOyPzTHrcOOnZsk6PrWiwJkGm0H6UlN9/ihWVbnGLHOlBmooxu7IcIkvTyiW1DlTo5Yb6tahgXGob6aGZdHnj6imBunxvOE4lpTaT2hMninbWgZRaDegK4UjH5Mx6tJfVo/xYkZXWyIxHjkWnaSBk2WAcpcJORY9WCbRrqy5P4DDvYFRWdUcy+BIXwAWvQZlThNWVDrH7D/8rU/PgVWG18BsQIEzDXIdSdnWMoAypzRZhVIbq5RYpkld7k9qoRifaFd13BLXomKbQiOaGiW/rjlmHfwyVWKS6vNyZjBw+iM8Cu2pByWjlkWZywS7UQtRTCw1twyE0NQfnPDmjWMZXLysFP/Y0oqaPAt+9eoB/PSCRZiVb8VLn3QMr0wU2gy4bGV5yuPLdhQ403Dx8lK8tLMDMV7E365dhVd2deJvH7dM/oGTiPEi9FpOlUu2cswIkpWttTHDceVvOibCKbhvW+YyYUfroCzPLdV+tCWDhTr8kRji/NSyVfOtehTaDDDqOETiAnp9EZh1HAaDMdiM2imfh63ONeOcxYX4342J1zANyyASF3D7c7uw8fbT8ZMLFsIbiuGhtxsQiMQzfkRHTdR9665yq2ty8cuLl8Ck46DlWGyXcI+mocePlVXqOlVsM2jQnaGSgxNRej8uVZnMzEyJQq+DHJPYW5OLIEpzo5WpriUWPQd34MSMcZOWxewCC1ZUOnHKrJxEY3K9Bj2+CHa2e9DUF8Du9kFohpZae3wRbGkaQHWuGZYpbLGcu6QIeRb98LZEU39i+ZYXRPzlwyZoORY5Fj3cgSjOWVwk/SeeRWjGmabP1ZWiYzAMu1E73IxXKttaBlDmMo7bmDjTSp0myT/HVPSpIFU/FQGVB3wpu71wDGDSa2DRczDpNNBrWOg0HLQcAwZAIBrHng4f6sodONIbkDWTXKoCDxmbkA8Nt30whJWVLgSj8eHzzIe6E60GbQYNvCOWtnMtOoTjAuIC0OwOYkmpHYFIHId7AzjSF8DKShd6fOFxl2l1Ghb1FU4IoohSpxFtAyH0+aOoyDGiuT+EP29oxFVrKpFr0eN7Z89TZVedTKLAKYHtLYNYNzdP8iAX40XoNepZsrUalP9x0XEM+vzqLUc4EbV3U9nb4cFps3PhCcfBMIkJKAMGIsThalaiKEIUE7O4uCAixguI8SKivIBYXEAkLiAYjSPGi/CF40Of84k3OgwDVLiMYBnIXuA/ItG+fKZqss4tsmFr8wAicWHcQhDecHy4Y8nyCicO9fhHfR0NWhY72wKoL3eg2R2EIIpo6g+Om+gTjQv4+Sv78Nq3TsM7B3qHu8cU2hKBMxjl8cVHNuK2s+fh9Pn5qq9uJjflXwmznCCI2Nk2iMocM06ZlYcnN6W/xzlSQ49fNVm2aijmXOQwoLlfHTPwZEhxCF9uvAgEY7xse40jiWKi+0l+Bl6AAxJVusrEUnu+VT/lBvYFNgNmF1jHKYWX+LpubRmEXsMMF6jv90exssoFdyCKQCQGbyg+3IVmYbEdgiCOmqGPvNlr6PHj2ie24NVbTsXcQmuKn+H0QHucaWofDKHHF8HXntgi21Lc0SxbpfUoXJINAOzG7CzvlS0dYPZ3elFoy8wynCCKY85+pCZVtq53grJzUtByDPKs+inPwPUaFpvHmJFqOQb9I7YzInER7UPHWo70BbCp0Y2GHj8KbQYsKD5WY3ZVlQt7O73YeORYB5lDPb4TalP/e3dnUp/XdESBM01H78g+PNyPFz/pkOUaI7NslWLUcbIfxp4KQ5ZWKVHD+dep8EV4FNkz05Q4U8Xlp1Jlairk2iJwmbRYVu5AVa4ZezqmnkPwSZsHY+U9zSmwTqnbzfZWD5r7js1ud7V7UJlrxq8uXgLz0M9rjBcxpyAxu7QaNFhUYlO8ypQaZMdtsIplquC50ku25S4TDshYFm2qRFXs9ibPoOVQ6jTCoOVg0LDQciw4lgHLMGCYxB62IIjgRRHxoX3DGC8gGhcQ5QWEYzwiMQFhOSvXD9ne6kF9hRNbJWjrNRFfOD6ciCInEYmiGRPVNZ6KaFyQ5HlGYgDk2wySVU2aX2SdcmBbWGwbFahf39uNn16wCP/Y3DqqiXivP4JCmwFd3jB2t3sl6ZOa7Shwpml+kQ35Vv2E9RylomRhBJsKEoMAaTM/M0nHsZIFCC3HJEr/aVhoWAZajoWGY8CxDDiGGQ7ILJs4w8hg6CzjiISfo38fD8Mkmra3y1w3udguf+AEAIdRmoDnNOkkDZxzC62S1enVconv+1Rm2CyTKGIwMnD2+CL47+d24ZTZuXh6a9vw249v4F3mNEky3mymjlfDLGbWa/DlVRX49RvjFHSUkJKFEdRSc0DpOrmp0nLSLbQnZqPxsZJVJWU3arGqKnEcYpfENZmP6vRm5ibQLNEes9SZ5VKNq8RpRLcnNOWlXg3Host74k3RU5tbcdWaStz0qVmIxHlU5Jjxw+d3j1oSLs+hwEl7nBL4+qnVuGxlORZmoKRaQ48fKxQojNCvgrOTHAN0j/HLng3YLKyy4gnF8HGjGwYZl+Za3aGMFPqQ6sZFqgbTcwusmJVvkez3qsRuSKr/bDQuoNxlwufqSvCVkytw5ckVWFbugEHLon0ghG+fORflLjMuXFqCc4eKHThNWqyodOLU2XmSjDmbUeCUgFHH4e6LFuPO8xdm5HrbhwojZIqWY1TRXLvQblTNzDdZ2XrubW6hFVtkznzd1OiWvaejVGdFNSyLfKse8wqtsOhTv6Gwm7Ro6PGnVYlrZZULFUOzv1T2vv+9uwvPbW/Hyzs74Q3HYdZr8NMLFmH93HwAwJdXlWNzkxs3fWo2Ll1eCk8oBpNOMyP7bx6PlmollKlZRaYLI5S5TDgiYXPhVOVYdMNp9dkmO8MmYDdoM/Iztr1lUNaEpOP36VIV44XhKj46DYuqXHNaLe7S2bP3hmLwheKoLbXjkzS62rgDUTy3vR1A4nTA1uYBrJ+Xj7MWFqImz4Iylwnzi2wwaDn89svLsvYmUEo045SIOxDFr1+Xf5/zqEwu2bpM6jg7KeeSodx4ieqlZtqmJjdqS+2TP1ACW5sHUFtmh07C/eCjpOqQMnKrIBoXhlvIjacmz4zlFU5Jrj1Soc2Awz1+uIPRtILmSFqOAS+IeGpzK2742zYAiZvmSJzHw283YEmpXbI92WxHgVMi1zy+Ge8f6svoNbe3DKA8A0u2arnBlKpYtxL4bF1jBtA6EEprWTIZn7R6sLRc+kAzp8CS9nPkWnSwH9cLdm+nF4FIHFqOwaJiG6pyzVhUYsPKSheWVzjROhDCluYBLBlx85Fr0Y1ZuCAZBTa95A3TOZbBl1eVw2rQwG489nluaOhDnz+KEgclBR1Ftw8S6VEgaSXGi9ByrOxLtlIdIE9XUOVF0icSz9Bhfzm4A1HMzrfAYtBI2gFoPHL0fO1Oo+pVXbkDOo7F3g4vdo+RXSyIgMCL2D1BRuvONg/mFVohiiJsRm3axRTkuIkMxwQ8s7UN151ajb2dPniCseG9WACjgulMRzNOiegkyrZL1uHegKxZiRzLoLlf+f1NAPCovEj6RCIq78U5mUM9fsQyUHwBADoGQ1hV5cKycgdWVDqh16S/5NE2EILDlNoLf483go8b3fCleeO2v8sHTyiWdpnBYodBtuNBkbiA37zVgDf2deNPHxwBkGiqDSRyDEgCBU6JPPzlZYoFz20yLtmWOo0ZK402mYEsPcMJJO7ms12mfgr6/FF83OjGtpZBbG4awJJSR9rPOSvPDG8KmbXlLqOkR6CkSCAscci/PVNbah8+u8kLiZ/dJRna684GFDglsrDYjkvqSxW5dowXodPIU8s215KZuqWTMWpZ9TeCnkCmSjPKSaktZimaJ7Ask/RRpnyrHuGYgLiEe4npVt3Js+qxvUX+wvi+cBxfWFEGADh9fgGK7QYsk2HvOVtR4JTQNadUKXZtubJsOZVkBhVkqGOHXPxZvD97TOYjJ8cy6ErzKEmR3YCD3VNr1XWUy6QDyzCSl9L8uNGN2rLUZ27VueakCh2k4tQ5eTjSF8BnfvM++vwRLCt34oPvf4oyakegwCmhIrsBnIIVYra3DKBC4iVbuVspTdXx2YzZRMPSUm2qFhbZ4E4jOY1Bakkt1XnmMUvSSaFjMIy8FFdyMpFktrvdgy+uKIPDpMWhbj86BkPoCyhfOUxNKHBKyKTT4PPLShS7fowXoeFYSBm72waUrxgEZG87MQCwGrI36I+kxFJtunuCyyudUyqizjFA/YjzlnLWRO71RZBn1Sf1e8owgMushT8i/42sOxDFa3u7cUFtCX7w/C6s/sVb+N4zO2W/bjahwCmxOoX3AQ73BrC8Upol2wKbHjqJDo6nK5vPcGZLL87JZOO3gJlk59+oTfx8Ly61Y2vzAKrzzFhUbEOLzCUm93Z6UZVrxuwCC1wTrKbYjVrMyrdgQZEN/nAcB5Jcck6VOxDFQ283DFcMe+dALz4e0eB6plPHq+I0ckl9KRaXKJt9JtWSbaHNAHcwBpdZh0XFtuEjAmVOY8ZLyAUi2ZsYZJwmgVOJm5cWdwBVueaUP37kmAtt+uHn0rIMlpU7YDfqUOEy4tBQQDrSG8DuDm9GClYc7g1Az7GoyR9dnGHkTHRuoQUNPX7s6fAiqnB2+2MbGhW9vprQbq/ENByLn164CBc+vEGxMYxcsk3n9/9oiTt3IAr3cUtXeg2LMpcJDpMWDBKZj12eCNxBeZa4+lTQnSVV+ixeZh5JiZdtdyCGUFTAomLbhAUGxqPlGCwstsETig31/YxgXqEVVoMm7fOU6Sp1GtHUFwDLMZhbYMWBbh+0HIN5hVYYtBx84Tg2NSozRqdJizKXCUYtB38kjk5PGCurcnCo24fZBVZFxqQmFDhlsLTMgXMXF+FfuzoVG8Ph3gBWVbnwcWPqpb0mKkAdiQvDFUVGshk0KHYYh/b1RPjCcXR5w2k1/9Vy0mc3ZpJUdVKVptRyeSjGY3+XDyurXGjpD6AriSpA7kAMB7pH73FK1Tg6HVW5JkTjAvxDv2PekA+z8swIxwXZihuMx6RlUZ5jhs2gRVwQ0OUNo2MwjIHg6Bq4T21uwTIZ6u5mo4wEzocffhi/+tWv0NXVhdraWjz44INYuXJlJi6tmJtOn6Vo4AQShREqXEY0u1PrKJJKVqE3HId3jBcmu1GLQpsBVqMGLAOEowL6AxG0D05+jSK7UfY9JzlpsrAX51iU3OOMCyI2Dd0ETvWGcHmFE1tk6raSjvHG1ZCBDkRWPYcylxkWA4cYL6LXF0HbQGhKNxMHu/14alMLnCYtKnJSXz6fDmQPnP/4xz9w66234ve//z1WrVqFBx54AGeddRYOHDiA/Px8uS+vmHmFNiwqsY1Z2zJT0lmyteg4SWd5nlBszJ6IRi2HYocBdqMWWo5FjBfgDcfR7Q3DN1Riz2nSoiW9mtiKYlVyFjZdokqyg3a2eZBv1U/689ncH4TLrDthm0FJ8wqtGSlgACQKOBTaDDDqOETiPDo9YXR7I9jbmfxr0rxCK+6/dCn6AxHsavcgx6KHZQaf62REmX8bVq1ahRUrVuChhx4CAAiCgLKyMtx000247bbbJvxYr9cLu90Oj8cDm80m5zBl8frebnztiS1KDyOlJdt5hVbFl7RsBg0KbAZUuEzwReKICyICkTj6/VH0ZtGeZ7pL5mpRkWNCc786Zv4rq1zDM9DjWfUcZhdYEY7xiRq7KikZqeUYmPWatLYtxmLWcSh2GmE3aMEwiao/7QOhtGvrAomCCzesn4XPLC5ClzeMcIyHCBHbmgfx5VXl06o3ZzLxRtZbhmg0iq1bt+L2228ffhvLsjjjjDPw0UcfnfD4SCSCSOTYC6LXq9xsTQqZurOcTGLJ1oTmcZY75xZYYNZroOVYHO71o88fhU0FnRC84Ti8YT8cJu0JiRxajkG+1QCHSQujlgPHMojxAvyROAYCMVUF1mw+SjOSoKLWaJsa3XCZdGMmoy0otqvyRqW21JHy0rFew6DYYYLNoBlKNhMRiPLo8UXQ64sMZwVL6aunVOG82mL8e1cn7n3tADo9YbjMOrAM8M1PzUbbQBBlrpm5ZCtr4Ozr6wPP8ygoKBj19oKCAuzfv/+Ex999992488475RxSRr2xr1vpIQBILNlyHDPukq3dqMOmof6Ay8odMGo57GqXpjmuFMZKUorxItoHQ2gfHHv/lmMZFFj1yLXqYdCwAMOA50WE43F4Q3G4A1EEMlT7dtoEThV9GrPyLaOS0wptiaVbQVRfXWCjlsPiEvvw79hYShwGFDuM0GvY4WMn0bgAXzgGdyCKgWAMjX2Z7VL0z82tePSD0UdQji5767UsOJYdbj0206hqkfr222/HrbfeOvxvr9eLsrIyBUeUulCUHzPrVClHJsiyHXlmbVsG+i0mK5UqLrwgosMTRscEdU6NWg4usw42owZGLQcNm8h+jQkCQlEegUgc3nAMnlB6L8TRuIoiThp4Fd0ANPT4UZ1rxpG+ABYUWXGkLwCXWYeaPAt6fBFoWEbS4uypYBlgWbkTR/oC2NTkRq5Fh9yhvUGWZRCN8xgIxtDtDaN9MPFn1QRL0Jk20VIvLwDFDiNa3UEKnFLLzc0Fx3Ho7h498+ru7kZhYeEJj9fr9dDr1dGNI10Hun2qukMHgK3NA6jMMaHpuH2qKK/e4gIcy0ja1mmkUIwfmrVO/DiWSWQFWw1amHQcDFoWGpYdKgcngheAOC8gFOMRiPDwhmKjXnSiGepjKTe1JAcdZdByKHcl2t6FYwLCsSj6/MoFncT2gR5Okw4mnQYMkyjub9Ry0HIM+vzRCRtYG3VcVqxOPP2Nk7FiqDpZFgxXFrIGTp1Oh/r6erz55pu48MILASSSg958803ceOONcl5acVaDBjoNq6oXzbgggmUYcAwwMl9CTWM8XoFNj44pHFmRkyACA8EYBiZI6lhR6cQnbceWtzkmsQRuMWggQsSiYhu0GhYcw4BlE4XgRCSWcQVBBC+K4AURMV5EnBcQiQsIx3hEYgKCMT4jlWwmo4YxjHQ0O3SVnI3cGcBl1sNu0sBm0A6fyRWGvl+RuAB/OI7BoazxozPHVMzKMytelGEyuRbdcNAEAFGRshjKk32p9tZbb8WVV16J5cuXY+XKlXjggQcQCARw9dVXy31pRdXkWfDQZXV4ZVcn9nZ6k25rJJcjfScu2SpdymsiLpNO8cA5FccfOeFFwB2MSlZJScsy0GtZ6DQcdBwDnSaREKXlGHAsAw3LgGEYsAwDhknU0mSG/g5gOFAzYABGHK7hOtZ3/uhjj75ThAgGAMcxis7oxjPZkqyGxahWXE6TFg6TDhY9B4OWA8swEJFYNegPRBGNJ25cQlEeoRiPXn9E1mQzLcegOs+S8cIHU3XqnDywDOAy63DxsmM9h7s8x46MzTSyB84vfOEL6O3txY9+9CN0dXVh6dKl+M9//nNCwtB0dObCQpy5MLEkvbvdg5uf2o7DGTjkPJmtzQOoyjUPJxsYteotCZctBdLlXmKLCSJiER5QsGavzaiqlAgAiRuKiWbCDpMWg8EYih0GCEKidONkqweZtLLKhe3NA2hXSReisRzs8uH1W08d7vIjCCJ2tXtQk29BoT27++SmKiO/CTfeeOO0X5qdzKISO17/1mlocQex4XAf7nxxL6K8MkukiTt0cXjJVqdR81ksNY/tGLUtY8pBUNHKRKFND45lEIoJ2NE6CCBxntFq0MCk08CoS8zONSyD7S2Dqlq1sBo0qMwxwajTDCcCxVTcxCAuiKOKHfT5I1hUYle097DS1HcLOY2xLIPKXDMqc80w6Th86x+fKDaWxr7g8CFyNWd9hmPqfUEZqbEvgDyrHmYdB6OOg15zLIGIQWJGGudFxAUB0biISIxHMMYjFI0jEOVVl0g2lkxkqVr0mqEErEQSll7DQcMxEARx1B4yADhNOrChGERRC2848XVMHDFSzxne4xm1HGwGrWqXZcdycX0pQjEeeg0HdyCKfNvMnGWOJHvloHRke+UgQRDx+r5u1JU70DkYxtyhrgdHfe2JLXh9r3JnPTUsg7oyO7a1elQ7YypzGdGaYq3dTDHruLTPhOo0bCJgaDjoNCzsRq2qztICgIYB5hbZEnuoTOKGYHhPlWGAxH+JvdWhjxGRyMYVxcRxFp4XERdERHkB0Xgi+Sk2lJEcik28AjOymtXRJdhss7jEllVBE8Dw0Z7r19XgrIWFWFrmUHpIslBN5aCZjmUZ7Gn3oNUdRJ5Vj5/9ay/OWliIr55SBYZh8MNz5+P9Q70IT/KCIZe4ICYKA6g0aAKJBAS1sxq1aQfOaFwYym5OBINCFd7Vx0WgbSA0Zs1huWm50T+nVTlmbA8OZnwcqbIaNJidb1HlOenJHF1paO4PTNugmSwKnDK79cy5w3+/YGnJqPdV5Jjx/A1rcOeLe7GxsV+RM1GMivcQ86x69GZBOzGzDAlMWpXuOxfY9IoEzkUldmwfEXTignqPUB3PotegwmXKyqBp0WuwuMQOdyCK7589T+nhqAYFToXNK7Thya+fhDgvYF+nD5f9cSP8EhRnnqrm/gAMWlaxWe9Ecsy6rAicBhmyknUq7eF5NLMyk+YVWrGv04t8qx5mPQeLXoM9KTS1zrQFRTZoOAYdg6GUmnArKc+qx3fPmovza4tl+fnOdhQ4VULDsVhcasdJ1TkZrXHb7YtgQZEVezuVb+57PIshO3489Rrpg5xGpYFTiUzKo/ua4VgE8AGlTiP0Gg4hFSeOrah0plTMwKjjkGvWwWbUwqDhwHEMICZm2AwYbM1A44jqPDOeuGYlSp0m2a+VrbLjlWkGGZTowHwylJhFTEW29LGUI5hoVZrqr4YqU06TFm0D6k0YYxhgV9vUErtm5Vtg1LKJQu6BKIJRHq3REDDO5zdRO7U8qx5OkzatYiu1pXY8dvVKuMy6lJ9jJqDAqTLf+vQcvL2/BxsO92NfCg1nU9HUF4DTpFXNofCjYip4kZ4KOXoSajh1Bk53QPmlczWujhy1oMgGo5bF1kn2MxMF6ZMvsbe33YM5BRZYDdpEK72hQvFdnjB6h1qMzS+yDr8tGSUOI564ZtWMLNqeLAqcKhGNC9BpWKyZlYs1s3LR6QnhvAc3oC8DfSW7fRHUldkxEFTX8QclklBSIceJLo5R51Jt52AYDKNcce98a6J9mFpFeX64hu7xCmx6FNgMEEURu9q9wy26kuGP8pPOKPd1+mDSslhW7phyQhLDAL+5rI6C5hSp87dzBvrTB0fw7sHe4X8X2Y34/eXLoJF5yY4BsKTEnnbrLDn0yNQVRWpxGSrqsCr9zYwJomJHZWpL7arOptWwDGwGLeYXWVFf4cSqKhfqyh2oyjXDoGHR74+AATJyjjMYE7CtZRD15U4Yp5D1vXZ2HuornLKPa7qgGadKXFxfil+/fginzckbftvyShfuOG8B/ueFPbJc06BhkW8zYKfKDtoDgMOoxWCWzDjlKJ2o5mNCuRY9OhU4XxsXRLgDyv1MGLUsXBY9HMZEezmGYRDnBQQicbgDMfT6IxPO8Cban5TL1pYBFDsMKHEYJ+wPfOrs3AyOKvtR4FSJfKsBd1+0+IS3X35SBV7b2433D/VJfs3aMseYja3VIM+qz5rAGUqz+MFY1JwXpdcqMx2WoxiGQcvCZtDCrOdg0mlg0Cbq24qiiCgvIhTl4Q3HMBCIYnGJA5ua3GhPMTFJqW9px2AYHJNov7apyT3mMntNviXzA8tiFDhV4Oj+5lgYhsEd5y3AGfe/J/l11byHaM2SoygAZDl3q95aTlBscLkWHfon2RdkGcBm1MI2oum4UcuBF4CYICT6m0bjCER4DIaiQw2wE8dcJhOJp3eD9HGjGwuLrRgYmp3GMlg0nxcT159XaEX/UAbv2YsKsao6Bw6jFqfOzpv8Sciw7Hl1msae3daGzy0rgV4z9l7ErHxryufCxsMyQItbva2MtCo9xzgWrxw3IOotIa2IU2blIhIXsLLKNVw0nxdEROMCwnEBoWgc3nAcvnAcg8HYqDq25S4jWiSod3ywx39CE/hk7elIRGiWAeYWWnGgK7MZwvu7fDhrYSFu/fQczC20ZvTa0wkFThVYXGrHa3u6cV5t8biPWV7pkjRw1pU5M3KYOlVyJNzIQadhEZbh2IyKywcrMuGM8gI2N6W2reAPS7OUHorymF9kxT4JjsMIIuAJRsFN0k9UalevqcSPPrtAliNUM0n23NZPYwuL7RMGTUDaeqgrK13Y3aG+hKCRfBH1LiOPZJNpSZlX84wzw0NbWZleUo2UdX+lLBbS5Y1kNJN1cYkdP/jMfAqaEqDAmSX8Eja63d3hQUTlxQX6VHxWbyS5qi7xKp5xixmMnAU2PT5pS29lRMrKTp0eaSsWbW50Y2FxZlom3n7OPNWWcsw29FXMEr6wNDOwPIseQRmyQKVk1HFwq6yK0XiMMhXAVvOMM5Mjc5l1iKTZaF3KwNnqDqHAqpfs+UQALf0BrKh0wiRDl52jlpTasXoWHTmRCgXOLFHmkqbgMi+IKLarr9fjSGrsRTkeOQq8A4AvHMfsAjoiIMXKiEbiahJS/S4e5Yvw2Nw0AIOGQ5nTKOlzH7Wk1C7L885UlByUJS6uL0WR3YC2gRA6PSG0D4TQMRhG+2AoqeMQ7qEi8tV5ZhzpDcg13LTYjdlT9kuumrIt7iDsRi1qS+0waDnwogh/OD7cKURJmZoMr6py4UB3+p+v1N8iuaoXuYNRmA1GFNsN6JD4zGoszVk7GY0CZ5bItehPaIR9lCcUQ/tQQO0YDKFtMDT07zDaB0Lo9oVHvdjlq7xBtFyzODnI2cHFE4rhkxFdNjK1FzY5+V+Ey1xGbGp0S3IlTuIZZ0NPACwjT+ZzqzsEBqm3JRuLhmVwQd3EyYckORQ4pwG7UQu7UYsF47ywxngBXZ4wtrYM4C8bmnCg26fqfU5Bxft7x8vkWI/0BVBf4YSGZbCnw4M4LyLKCxDFzO47ZuJTLrQZ0CrB2UtA+rZv/kgccwusksyGxyIC2Nw0gFyLDn3+9NoMmnQcvryqHKtraH9TShQ4ZwAtx6LMZcKVj21S7fLsSHJU4pFLPINn8EJRHlubE7MQhknMdmvLHBgMRhHnRbAMg2YVF7WYqkK7QdJzvHIUzHdkoItIsd2IQIRPuWG3XsPib9euQl05FW+XWvasiZG0/de6WcjJgga1/WneZWdSJKbMsR5RTCR6bW8ZRGNfEK0DIQiiiPqhF8lSx4lJJsnOuzhm7PPDcs84nSYttrcOSvZ8ciynT1b6Two72z0wajmsrHKl1CXpR+ctoKApEwqcM8jF9aV469vrcOXJFZC5W1nKtByj6n6Lx/OrqFBD60AI4TiPVVUutA2GMDvfAu2Ib/TySidm51tQaNNDNyJjxmXSYm6BFZU5JqyqcmFBkQ31FU7UV7pg0HKoyTOPuo6ccZNjGRzpnbjfZCrPKbXDvX7YjfIv2LmDUWxqdGNZkoUS/mtdDb68qkKmURFaqp1h7CYt7rxgES5ZXoYfvbB7yo1uM6XQZkBrit0nlKC2Qvl7Oo71ejzU40eeVY/qXDMCkTi2NA8MzxZr8sxwmnQYDMXAC8Lwfl1T/4lLvb5IHCsqndjRMoiYIMpaACHPokePT9qMUjnuEUURqM61SDoznsiedg+cJi0GpnC++dLlpfjuWXMzMKqZiwLnDLWoxI5nvrEaz2xrwz3/3p+RpaepcJh0WRM4OZZRZQPwkXp9kTEzqA/3BgBMbb87GhewuWkAFr0Gi/Itw5HIpGURlHip2qBlYdBI+7xyJT6zGVy2CUR5LCqxT9gGkGWAn124GJetLKOyejKjpdoZjGUZXLq8DG99ex2+opLlW7kq8cjBZVL/frGU/JE4trcOYn+XD9W5ZgRjAlZUSruH1tQfRIFd2iIAcjUFb+zLbKJdx2AI5eMUX6grd+Dpb6zGl1aVU9DMAAqcBHaTFj+5YBFevPEU1JU7FB5N9hxFsWZgj0uNQlEeR4aChhwv0lKf45UrjrgD0RP2f+XUOhBC20AQtWNUAer3RzNaMH6mo8BJhi0qseP/vrEav/z8ErgUyr4Npph6rwSzbmYGTrlJHjglfbbRnBn+PRHEREbvyJsBi16DBy+ry+g4ZjoKnGQUlmVw6YoyvP2ddfja2ipoZSopN54Bley1ToUuiyocyUWOnw7pO3jI9zO8q82TkTOdI7UNhFCVk5jpmnUc/nzVCtSWOTI6hpmObpnJmOxGLX5w7gJ8aVUF7vrXXryxr0f2a7IM0CVxjU45pXK2brphGaAixwiWYaFhGXBsImmKZYb+sIkdRpZhwDCJEDZyeVcUE9WXBFEEL4jgRREdg9Imh8m55ReJC5hbaMVgMLP9bS16DeorHLh+3SysrHJl9NqEAieZRFWuGX+6cgXeO9iLn768F4d6pD1jN1KBzYDOLAqc2bMbKx9eENHcL22gs8rUHFwuO9s8cJm0GW2Ft7M9Eai11F9TEfRVJ1Ny6pw8vHLzWtxx3gLYZHphy4aqRiOJWVRTVy5yfAUqc6Rt25WJ79KsAmsGrjLauYuLcNqcvIxfl1DgJEnQciyuXlOFd767HlecJP3xFTkb+cqBWjXJU37PIPGRpEwsqAsZrFkMAPMKrbjjvAUZvSY5hgInSZrLrMNPL1yEV25ei9U1OdI9cZadPwvHsycDWC5yhIsGibcDMhHS2iXel52MNxRDfhY1fJ9uKHCSlM0rtOFv167CH66oR4UEy2vhcY6iJBtPl5U7sLzCiYXFNpS7TLDq5VlaDqm4NVumyLFcPRCMYZWUCS8yR06OZdDtzeze/JkLCzN6PTJadu3CE9VhGAZnLSzEurl5eHxDE57e2oYjvf6UmvwOBsc+inLPRUtwxoICtA0E0TZ0CLxtINGsu20ghA5PCL7wsdJ3jX2BE2p66jgGORY97EYNjDoNtBwLBolepaEYD384jsFQbNTzTCab2p/JRa59Xin7xcpZWxcASp1GNI9R41dOxQ6abSqJAieRhF7D4brTanDdaTUIx3g09wdxuNePwz1+NPYH0NQXGDOgjTReRm2ZywSXWQeXWYclpY4xH+MLx9DpCaNjMIQebxiPvN84askvyovo9ITROcmpAQ0LOE162IwamHQcdBpuuLuGICQaR4djPAJRHj1ZlAEsFwnbZo4iRw9NuYy3UiKnQonLEpLkUOAkkjNoOcwttGJu4YmZhoPBKBqHgmhTXwBH+gJo6g/AH46P2ZkDAMpck79IWA1aWA1azBnKbjx1Tj5OueetpBtNxwWg1x9Brz97WpspSY5+pAwDhKPSPa/cyc/d3ggWl9iwq907+YMloNewWDeXsmmVRIGTZJTDpENdue6EBruiKKI/EEVzfxBtA0G09AfROrQkW5hCEkSh3YCzFxXi5Z2dUg2djKFPhhuMlZWuCbuAJEuOfpzH02ewOcEZCwpgM2S2WhEZjQInUQWGYZBr0SPXopesWPV1p9Zg45F+9Pmzp4xftukPRLGyyoVNEgW6mjwztjZLFzSBRGUiuWUyH/xouT2inCzaSSAkOYtL7Xj/e5/CZxZTBqKcNjW6JTmDyzKJpd+4xKu/UiYajSeTrbwO9fgydi0yNgqcZFoz6jj88uLajLZ/molKHOknq9SVO9Emw3nIwQyUwvOGYrI1RKjKNWN5pRPLyh2YnW9BROo7C5I0Cpxk2rPoNfj95fVZ1SQ729gk6E0q17nYHpnPWGrYRFa3XL1s8616bGkawLaWQRzq8eP9Q32IUPENRdEeJ5kRZhdY8YvPL8bNT+1QeijT0tbmwbT3Ot0BeTKZY4KIXIsupb1uDQu4zHrYjFqYdRz0Gg4MA0R5Af5wHAPBKPr8UbQPhiGKicenOyE0allYDVqYdBy8oTiahpqGH8ULIt472IdPLyhI70IkZRQ4yYxxwdIS7Ov04ffvHlZ6KNNSQ3fqe28alkGPT74jQC7z2IGzKteMHLMOHMtAEEXEeRGhGI9AJA5vOA5PKIYeX2RKY+vwhLGy0olNTQPgGAwFWw2Meg5GDQctxyYyfBkAYiIAxngBkfhQEY5IHL5wDKGYgFAscb2VVS7s7Tjx8PFz29socCqIAieZUb531lxYDRo88t4ReEKZawM1E7iDMcwpsOBgd/K1ZkudxnHP8Y5HwybODPsjky9bWsYpu2jRa7CleSCp605ke+sgjDoOoSiPgWBswoIfU9HYF8DcAhu2towe44eH+xGJ89BraPtBCRQ4yYzCsgxuWD8LX1hRhsse2Shrf9GZyGlKrTUcxzKoK3eAG2qAjaGJ2dEG1zF+RNWmSBy+cDzRRHqMoDKW8fpWCqIALccgJlEJpBgvIsZLt//Y64ugd4zZ7mAwhjf29uDcJUWSXYtMHQVOMiPlWvR45CvLcdkjG9GV4QLd5ESHewOTP2gMMX5qG4ojz3LW5JnRPhhCOCZgT4cPuZZEsM+2877/2NJKgVMhlFVLZqyqXDNuPmO20sOYVjLdobTHN7WbnpFnOR/60jJ864w5w//u80dh1mXfHOL9Q71o7k/thoOkJ/t+WgiR0AVLi/Hzf+2DjzqdpE3HMTjSm9ml74ocM7q8kyfuHN3PzrXoUZNnQbnLhN+/e3h4D/Job1WGAerLnVg7Ow/lOUY4TDrYjVp0DIawq82DHa2D2No8kFQNZJ2GxdJSB3IsOrx/qE+yrjqiCDz+YRPuOG+hJM9Hpo4CJ5nRTDoNPl9fisc/bFJ6KFlvablTstJ7U/VxoxuLim3Y3TG6wHp1rhkLim14Y183wrHE3ugd5y1AdZ4FOg0LnYbFRctK8egHjZidb8a6uflYWubEqmoXci36E66zrNyJzy4pBpCY5f727cP468Zm8FMIoI9fvQKra3IBAJ5gDC980o4/f9CYdDLUWP72cQuuXl2Fcgn64ZKpo8BJZrzT5+dT4JSAXL05J3N09nfWwgJ8rq4Ui0psKHUmAkk0LiAU5aHhGJhHZNY29QVQmWPCf25Zi7kF1qRK5uVbDfjx+Qvx5VXl+N7/7cT2lsExH2c3anFxfemowg52kxZfObkSF9aV4JwH3kd7mpWSonEBP/3XXvzxK8vTeh6SHAqcZMZLpnk1Gd9UZl9yaHEHUVfmwC8uWgKneXRW79HZ5fEqc82ozE2vDOPsAiue+cZqbDzSj+v+unXUEuz8IhseuaIeZa6xZ4I2gxZ/uKIe9/xnP94/1JfWOF7f2423D/Rg/dz8tJ6HTB0lB5EZL0D7m5LIRPuusXx2SRGeuu4kRa7NsQzWzMrFxfWlsBo0WFHpxK2fnoNnr189btA8alGJHd8/e54k4/jRC7sRjNLPcaZQ4CQz3trZeVDoNX9aYTPYIeSoG9fPwi8vrsUzW9twx4t7Mn79o245Yza2/PAMPP2N1fjm6bNhnGK3mEUldjz5tZOwojK9Vnqt7hB++Z8DaT0HmToKnGTGK7Qb8Kl56ZUvc5l1WF2TI9GIslN0imcqpfS3j5vxmzcP4Z+bW/HiJx3YeKQ/42MAEg3aU63ic3JNDu67ZCnmF9nSGsPjHzbh2W1taT0HmRpGVGpHfwq8Xi/sdjs8Hg9stvR+qAiZyL5OLy7748akW1Cdu7gIn11ShHVz82HUcdh4pB8NPX54wzHsavOg0xNGnz+CtgHp22WpyfwiK/Z1Ktcn8pL6Upj1Gtxx3oKM9saUWrc3jH/v6sSPX9qb0sfrNCye+vpJWFYuTTP4mSSZeEOBk5AhB7p8uPzRj8cscTaWuQVWvPzNU8Yt53aUKIr42b/24dEPGqUYpmJMOm7cptDLyh3Y1jKIXIsOpU4Tcsw68KKI7S2D49YErq9w4jtnzsXfPm5GZY4Zb+3vwd5O75iPnYhRy+GhL9VhdU3ulJdI1e7qxzbh7QO9KX1srkWHf153MqrzLBKPanqjwElIipr6Arj80Y+nNEP861dXYu3svCk9ryCI+NoTW/Dm/p50h6iIZeUOPPKV5bjm8c3Y2XasW4fTpMXqWblYUGjFRfWlKLKPbmgd4wW8c6AXf3r/CD4+7oznxfWlOHthIbp9YZxXW4xWdxDn/uaDpMeWOFZyKgzTqN+qNxzDl/64Ebvbk7+RAIBiuwHP3bAGBTaDxCObvihwEpKGgUAUD73dgFd2daLTM3ZJt3mFVvz75rVJLQt6wzFc+PAGHEmxLqtS9BoW731vPfKtevzg+d1490AvNByDr62txsX1pVMOWO2DIexp96B16Kbk4vpSHOjy4aG3G3Du4kJcurwM/9zSih2tg/jXzk54Jzkm9NklRbh0eRm+8udNKLIbcPlJFci36rF2dh4K7dkfMH784p60zhdftboSPz6fqgpNFQVOQiQQiMTxxUc2Ylf76H6ILAM8c/3qlPaR2gaC+MqfN2Vd8PzRZxfg6jWV+NeuTjhNOpxUnSPb8RNRFPHjF/fgLx81T/i4v1yzEqtrcvDXj5rx7sFevH+oF4KY6O35x68sxymzcyddRlezB944iAfeOJTyx//+8mU4exEVgZ+qZOJN9v5UESIzs16D/7t+NW799BxouWNB4uun1qScfFHqNOH/vrEaC4uz60bwJy/vxY9f3INT5+RhzaxcWc9sNvcH8UHDiUUB5hVacd1p1bjjvAUAAIdRCw3L4JpTqvCXa1bizW+vQ55Vj7gg4pq/bJa1MXYmpNtrs32Quv7IhSoHETIBnYbFN0+fjXMWFeKR946g2xfBLWl2VHGadfj1F5biM//v/aSKhStpVr4Flywvg82glf1alblmvP6t0/D6vm789p3D+KQ1kXT0/A1rYNByaBsIoshuQG2ZY9THVeWa8ez1q3GkL4BwjEeJwzj2BbLEVFumjefFHe24Zk1lVmcZqxUt1RKikMse2YiPFDp3mIzLVpbjjvMWKJJ8I4oimvuDKHEas3rZNRVf/tNGbGhI7+fjoS/VDRenJxOjpVpCssCZC9MrupAJ151WjbsuXKRYxirDMKjMNc+4oBnnBWxtHkj7eX74/G50U6N2ycn203jXXXdh9erVMJlMcDgccl2GkKx16fIy2Azq3C2x6DX46YWLcPs588FSPcKM03AsqnPTP4c5GIzhF//eL8GIyEiyBc5oNIpLLrkE119/vVyXICSrmfWJXqBqwjLAV06uwIbbPoUrTqpQejgzmsOkxS8vXoJ7Pr84rf3a57a3Y3tL+rNXcoxsgfPOO+/Et771LSxevFiuSxCS9S5WIHBeurwUcwuscJl1uP/S2uG3r5ubh1duXoufXLAIdqP8SUBkYqfMzsVPXtqL82tLsLjEntZz3fnSXghZkoiWDVS1ThSJRBCJHEsh93pTq5pBSLZYWGzHvEIr9ndlrs7rS5904srVlbjljNno9oZx4dJi/Nf6WZhTYM3YGMjkLq4vRcdgCJ+0DeI/e7rSeq4drYN44ZN2fK5OXSsc2UpVO+5333037Hb78J+ysjKlh0SI7M5fmrmsR4teg1CMx6t7utDUH4DDqMMDX6yjoKlC+VYDfvTZhfjlf6TZo/zFv/dT71mJJBU4b7vtNjAMM+Gf/ftT/ybffvvt8Hg8w39aW1tTfi5CssUXlpehKteckWvdcsZs/P7yZfjWGbMxK88Cu4mWZNXsX7s6sK1lUJLn6vZG8Pt3D0vyXDNdUku13/72t3HVVVdN+Jjq6uqUB6PX66HX61P+eEKyUY5Fj//cshY3P7kj7SW5iRTbDdByLHgBOK+2mA7GZ4Hza0uwoaEfz2yVps/mI+8dwRdWlKHUaZLk+WaqpAJnXl4e8vKm1g2CEDJ1eg2H75w1F6/u7YIcJUlqS+34zWV1iMQFWpbNIhzL4O6LFuNIr1+SmWckLuBP7zdS8fc0ybbH2dLSgh07dqClpQU8z2PHjh3YsWMH/H6/XJckJKvNyrfgPBmqvBi0LH558RLoNCwFzSyk5Vjce0kt9BppXq5flXFVY6aQLXD+6Ec/Ql1dHe644w74/X7U1dWhrq4OW7ZskeuShGS975w5F3lWabYrci16PPX1k7Dlh5+GSac5oVcmyR7VeRZ896y5AICvn1qd1s9IpyeM0DgNycnUyBY4H3/8cYiieMKfdevWyXVJQrJeeY4Jz3zjZJxcnZP2c4WiccR5Eb2+CPJtlDuQ7b56ShXOry3GktLEEaZ0DASjEo1qZlLVcRRCCFCRY8aTXz8JV56cXuWeQJTHpqZ+CKKYdosqojyGYXDXhYtwzqIihGPpzRiDNONMCwVOQlRqgQQ9O5eWOVCTl37NU6IOFoMG7QMhfOO0mrSeJ93AO9NR4CREpT5udKf18XVlduRaaIl2OmEYBgYdCw3H4tEr61NuEkCFENJDgZMQlbrjs6kdGbDoNTi/thiXrihDNc02p518qwGnzcnD6fMLcftn5qf0HIEoBc50UOAkRKW84VhKH+ePxPHiJx2I8yIselWVoyYS+8ziInAptH3r8UYmfxAZFwVOQlTKYdKi2G5I6WM5lsGaWbkSj4iojd2oxfq5+Ul/XNtASIbRzBwUOAlRKatBi+duWJPSPlap0wjqIjUz/PDc+Vha5sDX1lbhpGrXpI9fUenElasr5R/YNEbrOISoWIHNgM8sLsJTm5NreBDnRXhDMYRjPAxaOooynVXmmvHP606Gbqiy0A1/34Z/7ewc9/GfmlcgWZGNmYpmnISo3Mk1yRdDaB8MQa9hcSCDfT6JcnQjyvH9/HOLUWgbf4m/zGXE7nZPJoY1bVHgJETlTpuTB4M2+V/VA90+CHJUjCeqZjdqcfdFi8d9/7amAWg5eulPx4z/6gWjcfgjcYj0AkNUymHS4bdfXoZFJckVRHj7QC8cJp1MoyJqtn5ePlZWnbjfWeIw4rzaYswpoGNK6Zixe5yiKOLnr+zD4x82IcaLuGZNFX503gKlh0XImD41rwDr5+Zj4xE3Hv3gCLa3DKI/MHG90Zc+6cCPz18AXzgGq4EaVs80nmDiOFOuRY+5hRacXJ2Dy0+qwMFuP/ViTdOMC5yDwSgcJh22NA/gj+83Dr89haNQhGQUwzA4uSYHJ9fkgBdEPLmpBXe8uAf8BOmzfb7ohPtdZPr6+UWLsafDg/Nri4dXHhr7Aqgrdyg7sGlgRgXOu/+9D1U5ZnxxZTnqy5245/OL8egHjQhEeFy6okzp4REyZRzL4PKTKrCk1I5nt7WjyxOGw6RFizuInW0e+IdKqr2xrxtfXlWu8GiJEuornKivcA7/eyAQgc2gof1NCcyYwBnnBdgMWnxhKECyLIMvrCjHF1aUQxRFWrogWWlJqQNLSh2j3ra73YMv/XEjvOE4tjS5ccP6WcoMjqhGQ48fLrMOORba85YCI6o4K8br9cJut8Pj8cBmS79ThBS2Ng+gqS+Az9eXKj0UQsbVMRjCng4vTp+XD5b2IWaslv4gRIioyDErPRTVSybezJgZZ7rivIBr/rIF7x3shYZlUFfuoALaRLWKHUYUO4xKD4NkWI8vjDtf3Is8qx4/Pn8hHGYtbJQYJjla7J4iDceiaCjJIi6I+PUbh+gICyFENXa3e/DUplacubAA3z97HgBQ0JQJzTiT8P1z5uGjI/2wG7X4965O/Nymxw/OpSMshBBliaKIfKse3zx9ttJDmREocCbBZdbhve+tBwB0ekKIxIRR7//P7k7k2www6zSYU2CBICKllj+EEJIMhmGQT8eOMoYCZ4qK7KP3j/r8ETz6QSM6BsPo8oZh1nG463OLcV5tsUIjJIQQIgcKnBLJtejx9DdWAwB4QUSMFxCO8bj6sU344spyfHp+AWU3EkLINECBU2K9vggufHgDvra2CqfPL8CHh/vx9oFe5Fp0qMgx49ufnoPV1GCYEEKyFmXVSizPqseFdcXwR+Ioc5nw6y8sBQD0+aPY2jyAL/3pY/z+3cPKDpIQQkjKaMYpg++eNW/4759ZXITbzpmHX/x7P/Ktepw6J4/2PQkhJItR4MyAb5xWg8tWlsNm0FBpP0IIyXIUODPEbqSDyIQQMh3QHqdCDnb7EBjqYEEIISR7UOBUyM/+tQ9rf/k2HtvQiHCMV3o4hBBCpogCp0K+tLIM7kAUd760F8t++jp++PwudHvDSg+LEELIJChwKuRwb2D478Eoj//d2ILT73sXr+3pUnBUhBBCJkOBUwEPvHEQv3r1wAlv90fi+OZT2xGM0t4nIYSoFQXODBNFEX/7uGXc94djAh59vzGDIyKEEJIMCpwZxjAMfv65xRM+5jdvHcI/N7cizgsTPo4QQkjmUeBUwGlz8iY81xnjRdz72gG4A9EMjooQQshUUOBUgE7D4lPz8sd9/xnzC/DSTadQfz1CCFEhqhykkOPPbtaW2vHN02cj16JHbZlDmUERQgiZFAVOhXR6jp3ZvO60anz3zLnQcLQAQAghakev1Ar53tlzUeo0wmnS4ob1syhoEkJIlqAZp0JW1+Ti9W+dhj5/BDYDFYAnhJBsQdMcBRl1HMpcJqWHQQghJAkUOAkhhJAkUOAkhBBCkkCBkxBCCEkCBU5CCCEkCRQ4CSGEkCRQ4CSEEEKSQIGTEEIISQIFTkIIISQJFDgJIYSQJFDgJIQQQpJAgZMQQghJAgVOQgghJAkUOAkhhJAkUOAkhBBCkqDqfpyiKAIAvF6vwiMhhBAynR2NM0fjzkRUHTh9Ph8AoKysTOGREEIImQl8Ph/sdvuEj2HEqYRXhQiCgI6ODlitVjAMo/RwMsrr9aKsrAytra2w2WxKDydr0NctefQ1Sw193VKj1q+bKIrw+XwoLi4Gy068i6nqGSfLsigtLVV6GIqy2Wyq+uHKFvR1Sx59zVJDX7fUqPHrNtlM8yhKDiKEEEKSQIGTEEIISQIFTpXS6/W44447oNfrlR5KVqGvW/Loa5Ya+rqlZjp83VSdHEQIIYSoDc04CSGEkCRQ4CSEEEKSQIGTEEIISQIFTkIIISQJFDizQFNTE7761a+iqqoKRqMRNTU1uOOOOxCNRpUemqrdddddWL16NUwmExwOh9LDUa2HH34YlZWVMBgMWLVqFTZt2qT0kFTtvffew3nnnYfi4mIwDIPnn39e6SGp3t13340VK1bAarUiPz8fF154IQ4cOKD0sFJGgTML7N+/H4Ig4A9/+AP27NmDX//61/j973+P//7v/1Z6aKoWjUZxySWX4Prrr1d6KKr1j3/8A7feeivuuOMObNu2DbW1tTjrrLPQ09Oj9NBUKxAIoLa2Fg8//LDSQ8ka7777Lm644QZs3LgRr7/+OmKxGM4880wEAgGlh5YSOo6SpX71q1/hd7/7HY4cOaL0UFTv8ccfxy233ILBwUGlh6I6q1atwooVK/DQQw8BSNSHLisrw0033YTbbrtN4dGpH8MweO6553DhhRcqPZSs0tvbi/z8fLz77rs49dRTlR5O0mjGmaU8Hg9cLpfSwyBZLBqNYuvWrTjjjDOG38ayLM444wx89NFHCo6MTHcejwcAsvY1jAJnFmpoaMCDDz6I6667TumhkCzW19cHnudRUFAw6u0FBQXo6upSaFRkuhMEAbfccgvWrFmDRYsWKT2clFDgVNBtt90GhmEm/LN///5RH9Pe3o6zzz4bl1xyCb72ta8pNHLlpPI1I4Soxw033IDdu3fjqaeeUnooKVN1W7Hp7tvf/jauuuqqCR9TXV09/PeOjg6sX78eq1evxiOPPCLz6NQp2a8ZGV9ubi44jkN3d/eot3d3d6OwsFChUZHp7MYbb8TLL7+M9957L6tbRlLgVFBeXh7y8vKm9Nj29nasX78e9fX1eOyxxyZttDpdJfM1IxPT6XSor6/Hm2++OZzcIggC3nzzTdx4443KDo5MK6Io4qabbsJzzz2Hd955B1VVVUoPKS0UOLNAe3s71q1bh4qKCtx7773o7e0dfh/NDMbX0tICt9uNlpYW8DyPHTt2AABmzZoFi8Wi7OBU4tZbb8WVV16J5cuXY+XKlXjggQcQCARw9dVXKz001fL7/WhoaBj+d2NjI3bs2AGXy4Xy8nIFR6ZeN9xwA/7+97/jhRdegNVqHd5Dt9vtMBqNCo8uBSJRvccee0wEMOYfMr4rr7xyzK/Z22+/rfTQVOXBBx8Uy8vLRZ1OJ65cuVLcuHGj0kNStbfffnvMn6srr7xS6aGp1nivX4899pjSQ0sJneMkhBBCkjAzN8oIIYSQFFHgJIQQQpJAgZMQQghJAgVOQgghJAkUOAkhhJAkUOAkhBBCkkCBkxBCCEkCBU5CCCEkCRQ4CSGEqN57772H8847D8XFxWAYBs8//3zSzyGKIu69917MmTMHer0eJSUluOuuu5J+HqpVSwghRPUCgQBqa2txzTXX4KKLLkrpOW6++Wa89tpruPfee7F48WK43W643e6kn4dK7hFCCMkqDMPgueeeG+7qAwCRSAQ/+MEP8OSTT2JwcBCLFi3CPffcg3Xr1gEA9u3bhyVLlmD37t2YO3duWtenpVpCCCFZ78Ybb8RHH32Ep556Cjt37sQll1yCs88+G4cOHQIAvPTSS6iursbLL7+MqqoqVFZW4tprr01pxkmBkxBCSFZraWnBY489hqeffhpr165FTU0NvvOd7+CUU07BY489BgA4cuQImpub8fTTT+OJJ57A448/jq1bt+Liiy9O+nq0x0kIISSr7dq1CzzPY86cOaPeHolEkJOTAyDRpD0SieCJJ54Yftyjjz6K+vp6HDhwIKnlWwqchBBCsprf7wfHcdi6dSs4jhv1vqNN64uKiqDRaEYF1/nz5wNIzFgpcBJCCJkx6urqwPM8enp6sHbt2jEfs2bNGsTjcRw+fBg1NTUAgIMHDwIAKioqkroeZdUSQghRPb/fj4aGBgCJQHn//fdj/fr1cLlcKC8vx+WXX44NGzbgvvvuQ11dHXp7e/Hmm29iyZIlOPfccyEIAlasWAGLxYIHHngAgiDghhtugM1mw2uvvZbUWChwEkIIUb133nkH69evP+HtV155JR5//HHEYjH87Gc/wxNPPIH29nbk5ubipJNOwp133onFixcDADo6OnDTTTfhtddeg9lsxjnnnIP77rsPLpcrqbFQ4CSEEEKSQMdRCCGEkCRQ4CSEEEKSQIGTEEIISQIFTkIIISQJFDgJIYSQJFDgJIQQQpJAgZMQQghJAgVOQgghJAkUOAkhhJAkUOAkhBBCkkCBkxBCCEnC/we+jwEfKF/L8QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "state_geo = gpd.read_file('../../data/Census/US_State.shp')\n",
    "state_geo.set_index('StateFIPSN', inplace=True)\n",
    "state_geo.plot();\n",
    "state_geo.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Recipe Part A: Predict state-level values from national model fit\n",
    "\n",
    "### Step 1: Initialize the model using census data\n",
    "\n",
    "We can aggregate the county level data to the national scale by summing across all geographies. This is relatively straightforward."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2000  dec_1    20332536.0\n",
       "      dec_2    20909490.0\n",
       "      dec_3    19485544.0\n",
       "      dec_4    21638975.0\n",
       "      dec_5    21016627.0\n",
       "      dec_6    15115009.0\n",
       "      dec_7     9536197.0\n",
       "      dec_8     6946906.0\n",
       "      dec_9     3060483.0\n",
       "2010  dec_1    20703935.0\n",
       "      dec_2    21878666.0\n",
       "      dec_3    21645336.0\n",
       "      dec_4    20033352.0\n",
       "      dec_5    21597437.0\n",
       "      dec_6    20451686.0\n",
       "      dec_7    13926846.0\n",
       "      dec_8     7424945.0\n",
       "      dec_9     4083435.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "country = data.sum()\n",
    "country"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If we run the model using national data from the year 2000 as starting conditions, we can see how the cohorts develop, given our arbitrary loss rate values:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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OZcaMGQwbNqzGLIqImEMPsIoIAN988w233nora9eu5fDhw+Tn5/P666+TlJTEnXfeyZtvvklxcTFjx47l+uuvt1vuvvtuVq1aZTvW4MGDcXZ2ZuLEifTp04egoKAa41VWVnLy5Em75euvv65TzYZh1DjGyZMnqa6uvmCfwYMH4+joyPPPP1+nsUSk/mhmRESAH79N06VLF5YtW8axY8eoqKggKCiI8ePHM3fuXO655x569+5Nw4YNa/S9++67SUpK4vDhw0RFReHu7s6QIUP461//ypgxY8473pEjRwgICLDb5urqWqcfJPvhhx9qHAOgsLDwgl/5dXJyYsqUKSQlJXHffffh4eFR6/FEpH5YjLp8909EftXZs2fJz88nNDTU7tdARS4Ffb7kWqTbNCIiImIqhRERERExlcKIiIiImEphREREREylMCIiIiKmUhgRERERUymMiIiIiKkURkRERMRUCiMiIiJiKoURERERMZXCiIhgsVguuixYsIDjx49jsVjIzs4GsK07Ojry1Vdf2R2vsLAQJycnLBYLx48ft2t/vuW99967YG27d+/m1ltvpVGjRri7u9O6dWtGjRpFeXk5CQkJF607JCQEgJiYmPPu/+ktw7+8Bg0bNqRHjx7s2rXrkl5nETk/hRERobCw0LYsX76cBg0a2G2bNWvWBfs2bdqUV155xW5bWloaTZs2PW/7HTt22B27sLCQTp06nbdtbm4ucXFx3HjjjfzrX/8iJyeH5ORkXFxcqKqqYsWKFXbHAUhNTbWtv//++7ZjjR8/vsa4SUlJduP91Hffvn00btyYfv368fnnn9fqGorIb6e39oqI3RtuGzZsiMViqfHW2//+97/n7Ttq1ChSU1OZM2eObVtqaiqjRo3iiSeeqNHe19f3gm/U/aVt27bh7+9vFxpatmxJXFwcAFartcZbhL29vc97fHd3918d96e+/v7+vPDCCzRt2pTt27czceLEWtUrIr+NZkZE6plhGFSfOWPKcjleyn3HHXdQXFzM3r17Adi7dy/FxcX079//dx/b39+fwsJC/vWvf/3uY9WV1WoFoLy8/LKPLfJHo5kRkXpmlJWRd8P5b0PUt/BDWVjc3et1DGdnZ0aMGMHq1av505/+xOrVqxkxYgTOzs7nbd+9e3ccHOz/HVRSUnLetoMHD+af//wn0dHR+Pv707VrV3r16kV8fDwNGjSoU50pKSm89NJLdtv+8pe/MHz48Bptz5w5w8MPP4yjoyPR0dF1GkdE6k5hRER+tzFjxtC9e3cWLlzI66+/zoEDB6isrDxv2w0bNtCmTZtaHdfR0ZHU1FSefPJJdu3aRWZmJgsXLmTx4sUcPHiQgICAWtc4fPhw5s2bZ7etSZMmdutDhw7F0dGRsrIyrrvuOlatWkVUVFStxxCR30ZhRKSeWaxWwg9lmTb25RAZGUlERARDhw6lTZs2XH/99bZv3fxSUFAQrVq1qtPxmzZtysiRIxk5ciRPPPEEYWFhvPjiizz22GO1PkbDhg1/ddxly5bRu3dvGjZsyHXXXVenGkXkt1MYEalnFoul3m+VXAnGjBnD5MmTeeGFF+p1HB8fHwICAigtLb3kx/b3969zUBKR309hREQuifHjxzN48GC8vb0v2u6bb77h5MmTdtu8vb1xc3Or0fYvf/kL2dnZDBgwgJYtW3L27FleeeUVjhw5QnJycp3qO3PmTI1xXV1d8fHxqdNxROTS07dpROSScHJyonHjxjg5XfzfOL179yYgIMBu2bJly3nbdu7cmZKSEiZNmkS7du2Ijo7mvffeY8uWLXV+sPRvf/tbjXGHDh1ap2OISP2wGJfju38ifyBnz54lPz+f0NDQ8/5rX+T30OdLrkWaGRERERFTKYyIiIiIqRRGRERExFQKIyIiImIqhRERERExlcKIiIiImEphREREREylMCIiIiKmUhgRERERUymMiAgAMTExTJ8+vU59QkJCWL58eb3UIyJ/HAojInJFeeqpp+jevTvu7u4XfOleQUEBffv2xd3dHT8/PxITE6msrLy8hYrIJaO39orIFaW8vJzBgwfTrVs3Vq1aVWN/VVUVffv2xd/fn/3791NYWEh8fDzOzs4sXLjQhIpF5PfSzIiI2FRWVjJlyhQaNmxI48aNeeSRR/jpXZpFRUX0798fq9VKaGgo69atq9F/6dKlREZG4uHhQVBQEJMnT6akpASA0tJSGjRowMaNG+36bNmyBQ8PD06fPg3AY489xgMPPEBkZOR5a9y2bRu5ubmsXbuWDh068Oc//5knnniC559/nvLy8kt5OUTkMlEYEalnhmFQca7KlKWuL+VOS0vDycmJgwcPsmLFCpYuXcpLL70EQEJCAl9++SXp6els3LiRlJQUioqK7Po7ODiwcuVKjhw5QlpaGrt27WL27NkAeHh4MGTIEFJTU+36pKamMmjQILy8vGpV44EDB4iMjKRJkya2bbGxsfzwww8cOXKkTucrIlcG3aYRqWeV5dX8ddpuU8aesCIaZ1fHWrcPCgpi2bJlWCwWwsPDycnJYdmyZURHR/POO+9w8OBBbrrpJgBWrVpFmzZt7Pr//AHYkJAQnnzySSZNmkRKSgoA48aNo3v37hQWFhIQEEBRURFvv/02O3bsqHWNJ0+etAsigG395MmTtT6OiFw5NDMiIjZdu3bFYrHY1rt168ann37K0aNHcXJyolOnTrZ9ERERNR4w3bFjB7169aJp06Z4eXkxcuRIvvnmG86cOQNA586dadeuHWlpaQCsXbuW4OBgevbsWf8nJyJXLM2MiNQzJxcHJqyINm3sy+X48eP069eP++67j6eeeopGjRqxd+9exo4dS3l5Oe7u7sCPsyPPP/88Dz30EKmpqYwePdouAP0af39/Dh48aLft66+/tu0TkauPZkZE6pnFYsHZ1dGUpS5/yQNkZmbarb/33nu0bt2aiIgIKisrycrKsu3Ly8vju+++s61nZWVRXV3NkiVL6Nq1K2FhYZw4caLGGCNGjOCLL75g5cqV5ObmMmrUqDrV2K1bN3JycuyeV9m+fTsNGjSgbdu2dTqWiFwZFEZExKagoIAZM2aQl5fHq6++SnJyMtOmTSM8PJy4uDgmTpxIZmYmWVlZjBs3DqvVauvbqlUrKioqSE5O5vPPP2fNmjW8+OKLNcbw8fFh4MCBJCYm0qdPH5o1a1ajhuzsbAoKCqiqqiI7O5vs7Gzbt3L69OlD27ZtGTlyJB999BH//Oc/efjhh7n//vtxdXWt3wskIvXDEJFLqqyszMjNzTXKysrMLqVOoqOjjcmTJxuTJk0yGjRoYPj4+Bhz5841qqurDcMwjMLCQqNv376Gq6ur0bx5c+OVV14xgoODjWXLltmOsXTpUiMgIMCwWq1GbGys8corrxiAUVxcbDfWzp07DcB47bXXatQxatQoA6ixpKen29ocP37c+POf/2xYrVajcePGxsyZM42Kior6uCxXnKv18yVyMRbDqON3/0Tkos6ePUt+fj6hoaG4ubmZXc4Vac2aNTzwwAOcOHECFxcXs8u5qujzJdciPcAqIpfNmTNnKCwsZNGiRUycOFFBREQAPTMiIpdRUlISERER+Pv7M2fOHLPLEZErhG7TiFximkaX+qTPl1yLNDMiIiIiplIYEREREVMpjIiIiIipFEZERETEVAojIiIiYiqFERERETGVwoiIABATE8P06dPr1CckJITly5fXSz0i8sehMCIiV4zjx48zduxYQkNDsVqttGzZkkcffZTy8nK7docPH+bmm2/Gzc2NoKAgkpKSTKpYRC4F/Ry8iFwxPv74Y6qrq/nLX/5Cq1at+Pe//8348eMpLS3l2WefBeCHH36gT58+9O7dmxdffJGcnBzGjBmDt7c3EyZMMPkMROS30MyIiNhUVlYyZcoUGjZsSOPGjXnkkUf46Ueai4qK6N+/P1arldDQUNatW1ej/9KlS4mMjMTDw4OgoCAmT55MSUkJAKWlpTRo0ICNGzfa9dmyZQseHh6cPn2auLg4UlNT6dOnDy1atOCOO+5g1qxZbNq0ydZ+3bp1lJeXs3r1atq1a8eQIUOYOnUqS5curccrIyL1SWFEpJ4ZhkHF2bOmLHV920NaWhpOTk4cPHiQFStWsHTpUl566SUAEhIS+PLLL0lPT2fjxo2kpKRQVFRk19/BwYGVK1dy5MgR0tLS2LVrF7NnzwbAw8ODIUOGkJqaatcnNTWVQYMG4eXldd6avv/+exo1amRbP3DgAD179rR7yV5sbCx5eXkUFxfX6XxF5Mqg2zQi9azy3DlWjhpkythT0zbiXIf3lwQFBbFs2TIsFgvh4eHk5OSwbNkyoqOjeeeddzh48CA33XQTAKtWraJNmzZ2/X/+AGxISAhPPvkkkyZNIiUlBYBx48bRvXt3CgsLCQgIoKioiLfffpsdO3act57PPvuM5ORk2y0agJMnTxIaGmrXrkmTJrZ9Pj4+tT5fEbkyaGZERGy6du2KxWKxrXfr1o1PP/2Uo0eP4uTkRKdOnWz7IiIi8Pb2tuu/Y8cOevXqRdOmTfHy8mLkyJF88803nDlzBoDOnTvTrl070tLSAFi7di3BwcH07NmzRi1fffUVcXFxDB48mPHjx9fD2YrIlUIzIyL1zMnVlalpG3+9YT2NfbkcP36cfv36cd999/HUU0/RqFEj9u7dy9ixYykvL8fd3R34cXbk+eef56GHHiI1NZXRo0fbBSCAEydOcMstt9C9e3f++te/2u3z9/fn66+/ttv207q/v389nqGI1BeFEZF6ZrFY6nSrxEyZmZl26++99x6tW7cmIiKCyspKsrKybLdp8vLy+O6772xts7KyqK6uZsmSJTg4/Djp+tprr9UYY8SIEcyePZuVK1eSm5vLqFGj7PZ/9dVX3HLLLXTq1InU1FTbsX7SrVs35s2bR0VFBc7OzgBs376d8PBw3aIRuUrpNo2I2BQUFDBjxgzy8vJ49dVXSU5OZtq0aYSHhxMXF8fEiRPJzMwkKyuLcePGYbVabX1btWpFRUUFycnJfP7556xZs4YXX3yxxhg+Pj4MHDiQxMRE+vTpQ7NmzWz7vvrqK2JiYmjevDnPPvssp06d4uTJk5w8edLWZtiwYbi4uDB27FiOHDnChg0bWLFiBTNmzKjfiyMi9UZhRERs4uPjKSsro3Pnztx///1MmzbN9tsdqampBAYGEh0dzcCBA5kwYQJ+fn62vu3bt2fp0qUsXryY66+/nnXr1vH000+fd5yfbt2MGTPGbvv27dv57LPP2LlzJ82aNSMgIMC2/KRhw4Zs27aN/Px8OnXqxMyZM5k/f75+Y0TkKmYx6vrdPxG5qLNnz5Kfn09oaChuV8ntmcttzZo1PPDAA5w4ccLuK7ry6/T5kmuRnhkRkcvmzJkzFBYWsmjRIiZOnKggIiKAbtOIyGWUlJREREQE/v7+zJkzx+xyROQKods0IpeYptGlPunzJdcizYyIiIiIqRRGRERExFQKIyIiImIqhRERERExlcKIiIiImEphREREREylMCIiAMTExDB9+vQ69QkJCWH58uX1Uo+I/HEojIjIFeWOO+6gefPmuLm5ERAQwMiRIzlx4oRdm8OHD3PzzTfj5uZGUFAQSUlJJlUrIpeCwoiIXFFuueUWXnvtNfLy8njjjTc4duwYgwYNsu3/4Ycf6NOnD8HBwWRlZfHMM8+wYMEC/vrXv5pYtYj8HgojImJTWVnJlClTaNiwIY0bN+aRRx7hpx9pLioqon///litVkJDQ1m3bl2N/kuXLiUyMhIPDw+CgoKYPHkyJSUlAJSWltKgQQM2btxo12fLli14eHhw+vRpAB544AG6du1KcHAw3bt356GHHuK9996joqICgHXr1lFeXs7q1atp164dQ4YMYerUqSxdurQ+L42I1COFEZF6ZhgG1eVVpix1fdtDWloaTk5OHDx4kBUrVrB06VJeeuklABISEvjyyy9JT09n48aNpKSkUFRUZNffwcGBlStXcuTIEdLS0ti1axezZ88GwMPDgyFDhpCammrXJzU1lUGDBuHl5VWjnm+//ZZ169bRvXt3nJ2dAThw4AA9e/a0e8lebGwseXl5FBcX1+l8ReTKoLf2itQzo6KaE/P3mzJ24OPdsbg41rp9UFAQy5Ytw2KxEB4eTk5ODsuWLSM6Opp33nmHgwcPctNNNwGwatUq2rRpY9f/5w/AhoSE8OSTTzJp0iRSUlIAGDduHN27d6ewsJCAgACKiop4++232bFjh91xHnzwQZ577jnOnDlD165defPNN237Tp48SWhoqF37Jk2a2Pb5+PjU+nxF5MqgmRERsenatSsWi8W23q1bNz799FOOHj2Kk5MTnTp1su2LiIjA29vbrv+OHTvo1asXTZs2xcvLi5EjR/LNN99w5swZADp37ky7du1IS0sDYO3atQQHB9OzZ0+74yQmJvLhhx+ybds2HB0diY+Pr/Msj4hcPTQzIlLPLM4OBD7e3bSxL5fjx4/Tr18/7rvvPp566ikaNWrE3r17GTt2LOXl5bi7uwM/zo48//zzPPTQQ6SmpjJ69Gi7AATQuHFjGjduTFhYGG3atCEoKIj33nuPbt264e/vz9dff23X/qd1f3//y3OyInJJaWZEpJ5ZLBYcXBxNWX75l/yvyczMtFt/7733aN26NREREVRWVpKVlWXbl5eXx3fffWdbz8rKorq6miVLltC1a1fCwsJqfCUXYMSIEXzxxResXLmS3NxcRo0addGaqqurATh37hzw42zNv/71L9sDrQDbt28nPDxct2hErlIKIyJiU1BQwIwZM8jLy+PVV18lOTmZadOmER4eTlxcHBMnTiQzM5OsrCzGjRuH1Wq19W3VqhUVFRUkJyfz+eefs2bNGl588cUaY/j4+DBw4EASExPp06cPzZo1s+3LzMzkueeeIzs7my+++IJdu3YxdOhQWrZsSbdu3QAYNmwYLi4ujB07liNHjrBhwwZWrFjBjBkz6v8CiUi9UBgREZv4+HjKysro3Lkz999/P9OmTWPChAnAj996CQwMJDo6moEDBzJhwgT8/Pxsfdu3b8/SpUtZvHgx119/PevWrePpp58+7zg/3boZM2aM3XZ3d3c2bdpEr169CA8PZ+zYsURFRbF7925cXV0BaNiwIdu2bSM/P59OnToxc+ZM5s+fb6tTRK4+FkNPhYlcUmfPniU/P5/Q0FDc3NzMLueKtGbNGh544AFOnDhh9xVd+XX6fMm1SA+wishlc+bMGQoLC1m0aBETJ05UEBERQLdpROQySkpKIiIiAn9/f+bMmWN2OSJyhdBtGpFLTNPoUp/0+ZJrkWZGRERExFQKIyIiImIqhRERERExlcKIiIiImEphREREREylMCIiIiKmUhgREQBiYmKYPn16nfqEhISwfPnyeqlHRP44FEZE5Ip07tw5OnTogMViITs7227f4cOHufnmm3FzcyMoKIikpCRzihSRS0JhRESuSLNnzyYwMLDG9h9++IE+ffoQHBxMVlYWzzzzDAsWLOCvf/2rCVWKyKWgMCIiNpWVlUyZMoWGDRvSuHFjHnnkEX76keaioiL69++P1WolNDSUdevW1ei/dOlSIiMj8fDwICgoiMmTJ1NSUgJAaWkpDRo0YOPGjXZ9tmzZgoeHB6dPn7Zte+edd9i2bRvPPvtsjTHWrVtHeXk5q1evpl27dgwZMoSpU6eydOnSS3kpROQyUhgRqWeGYVBeXm7KUte3PaSlpeHk5MTBgwdZsWIFS5cu5aWXXgIgISGBL7/8kvT0dDZu3EhKSgpFRUV2/R0cHFi5ciVHjhwhLS2NXbt2MXv2bAA8PDwYMmQIqampdn1SU1MZNGgQXl5eAHz99deMHz+eNWvW4O7uXqPGAwcO0LNnT7uX7MXGxpKXl0dxcXGdzldErgx6a69IPauoqGDhwoWmjD137tw6vRk3KCiIZcuWYbFYCA8PJycnh2XLlhEdHc0777zDwYMHuemmmwBYtWoVbdq0sev/8wdgQ0JCePLJJ5k0aRIpKSkAjBs3ju7du1NYWEhAQABFRUW8/fbb7NixA/gxuCUkJDBp0iRuvPFGjh8/XqPGkydPEhoaaretSZMmtn0+Pj61Pl8RuTJoZkREbLp27YrFYrGtd+vWjU8//ZSjR4/i5OREp06dbPsiIiLw9va2679jxw569epF06ZN8fLyYuTIkXzzzTecOXMGgM6dO9OuXTvS0tIAWLt2LcHBwfTs2ROA5ORkTp8+rTf6ivzBaGZEpJ45Ozszd+5c08a+XI4fP06/fv247777eOqpp2jUqBF79+5l7NixlJeX2265jBs3jueff56HHnqI1NRURo8ebQtAu3bt4sCBA7i6utod+8Ybb2T48OGkpaXh7+/P119/bbf/p3V/f//LcKYicqkpjIjUM4vFUqdbJWbKzMy0W3/vvfdo3bo1ERERVFZWkpWVZbtNk5eXx3fffWdrm5WVRXV1NUuWLMHB4cdJ19dee63GGCNGjGD27NmsXLmS3NxcRo0aZdu3cuVKnnzySdv6iRMniI2NZcOGDXTp0gX4cbZm3rx5VFRU2MLW9u3bCQ8P1y0akauUbtOIiE1BQQEzZswgLy+PV199leTkZKZNm0Z4eDhxcXFMnDiRzMxMsrKyGDduHFar1da3VatWVFRUkJyczOeff86aNWt48cUXa4zh4+PDwIEDSUxMpE+fPjRr1sy2r3nz5lx//fW2JSwsDICWLVva2g0bNgwXFxfGjh3LkSNH2LBhAytWrGDGjBn1fHVEpL4ojIiITXx8PGVlZXTu3Jn777+fadOmMWHCBODHb70EBgYSHR3NwIEDmTBhAn5+fra+7du3Z+nSpSxevJjrr7+edevW8fTTT593nJ9u3YwZM6bONTZs2JBt27aRn59Pp06dmDlzJvPnz7fVKSJXH4tR1+/+ichFnT17lvz8fEJDQ3FzczO7nCvSmjVreOCBBzhx4sRVcwvrSqHPl1yL9MyIiFw2Z86cobCwkEWLFjFx4kQFEREBdJtGRC6jpKQkIiIi8Pf319d3RcRGt2lELjFNo0t90udLrkWaGRERERFTKYyIiIiIqRRGRERExFQKIyIiImIqhRERERExlcKIiIiImEphREQAiImJYfr06XXqExISwvLly+ulHhH541AYEZErSkhICBaLxW5ZtGiRXZvDhw9z88034+bmRlBQEElJSSZVKyKXgn4OXkSuOI8//jjjx4+3rXt5edn+9w8//ECfPn3o3bs3L774Ijk5OYwZMwZvb2+9LE/kKqWZERGxqaysZMqUKTRs2JDGjRvzyCOP8NOPNBcVFdG/f3+sViuhoaGsW7euRv+lS5cSGRmJh4cHQUFBTJ48mZKSEgBKS0tp0KABGzdutOuzZcsWPDw8OH36tG2bl5cX/v7+tsXDw8O2b926dZSXl7N69WratWvHkCFDmDp1KkuXLq2PSyIil4HCiEg9MwyDqqozpix1fdtDWloaTk5OHDx4kBUrVrB06VJeeuklABISEvjyyy9JT09n48aNpKSkUFRUZNffwcGBlStXcuTIEdLS0ti1axezZ88GwMPDgyFDhpCammrXJzU1lUGDBtnNfixatAhfX186duzIM888Q2VlpW3fgQMH6Nmzp91L9mJjY8nLy6O4uLhO5ysiVwbdphGpZ9XVZWTsjjRl7JjoHBwd3WvdPigoiGXLlmGxWAgPDycnJ4dly5YRHR3NO++8w8GDB7npppsAWLVqFW3atLHr//MHYENCQnjyySeZNGkSKSkpAIwbN47u3btTWFhIQEAARUVFvP322+zYscPWb+rUqdxwww00atSI/fv3M2fOHAoLC20zHydPniQ0NNRu3CZNmtj2+fj41P4CicgVQTMjImLTtWtXLBaLbb1bt258+umnHD16FCcnJzp16mTbFxERgbe3t13/HTt20KtXL5o2bYqXlxcjR47km2++4cyZMwB07tyZdu3akZaWBsDatWsJDg6mZ8+etmPMmDGDmJgYoqKimDRpEkuWLCE5OZlz587V45mLiJk0MyJSzxwcrMRE55g29uVy/Phx+vXrx3333cdTTz1Fo0aN2Lt3L2PHjqW8vBx39x9naMaNG8fzzz/PQw89RGpqKqNHj7YLQL/UpUsXKisrOX78OOHh4fj7+/P111/btflp3d/fv/5OUETqjWZGROqZxWLB0dHdlOVif8mfT2Zmpt36e++9R+vWrYmIiKCyspKsrCzbvry8PL777jvbelZWFtXV1SxZsoSuXbsSFhbGiRMnaowxYsQIvvjiC1auXElubi6jRo26aE3Z2dk4ODjg5+cH/Dhb869//YuKigpbm+3btxMeHq5bNCJXKYUREbEpKChgxowZ5OXl8eqrr5KcnMy0adMIDw8nLi6OiRMnkpmZSVZWFuPGjcNq/d/MS6tWraioqCA5OZnPP/+cNWvW8OKLL9YYw8fHh4EDB5KYmEifPn1o1qyZbd+BAwdYvnw5H330EZ9//jnr1q3jgQceYMSIEbagMWzYMFxcXBg7dixHjhxhw4YNrFixghkzZtT/BRKR+mGIyCVVVlZm5ObmGmVlZWaXUifR0dHG5MmTjUmTJhkNGjQwfHx8jLlz5xrV1dWGYRhGYWGh0bdvX8PV1dVo3ry58corrxjBwcHGsmXLbMdYunSpERAQYFitViM2NtZ45ZVXDMAoLi62G2vnzp0GYLz22mt227OysowuXboYDRs2NNzc3Iw2bdoYCxcuNM6ePWvX7qOPPjL+9Kc/Ga6urkbTpk2NRYsW1cs1uRJdrZ8vkYuxGEYdv/snIhd19uxZ8vPzCQ0Nxc3Nzexyrkhr1qzhgQce4MSJE3Zf0ZVfp8+XXIv0AKuIXDZnzpyhsLCQRYsWMXHiRAUREQH0zIiIXEZJSUlERETg7+/PnDlzzC5HRK4Quk0jcolpGl3qkz5fci3SzIiIiIiYSmFERERETKUwIiIiIqZSGBERERFTKYyIiIiIqRRGRERExFQKIyICQExMDNOnT69Tn5CQEJYvX14v9YjIH4fCiIhccd566y26dOmC1WrFx8eHu+66y25/QUEBffv2xd3dHT8/PxITE6msrDSnWBH53fRz8CJyRXnjjTcYP348Cxcu5NZbb6WyspJ///vftv1VVVX07dsXf39/9u/fT2FhIfHx8Tg7O7Nw4UITKxeR30ozIyJiU1lZyZQpU2jYsCGNGzfmkUce4acfaS4qKqJ///5YrVZCQ0NZt25djf5Lly4lMjISDw8PgoKCmDx5MiUlJQCUlpbSoEEDNm7caNdny5YteHh4cPr0aSorK5k2bRrPPPMMkyZNIiwsjLZt23LPPffY2m/bto3c3FzWrl1Lhw4d+POf/8wTTzzB888/T3l5eT1eHRGpLwojIvXMMAxKq6pMWer6toe0tDScnJw4ePAgK1asYOnSpbz00ksAJCQk8OWXX5Kens7GjRtJSUmhqKjIrr+DgwMrV67kyJEjpKWlsWvXLmbPng2Ah4cHQ4YMITU11a5PamoqgwYNwsvLi0OHDvHVV1/h4OBAx44dCQgI4M9//rPdzMiBAweIjIykSZMmtm2xsbH88MMPHDlypE7nKyJXBt2mEalnZ6qrafmvHFPGPtYzEg9Hx1q3DwoKYtmyZVgsFsLDw8nJyWHZsmVER0fzzjvvcPDgQW666SYAVq1aRZs2bez6//wB2JCQEJ588kkmTZpESkoKAOPGjaN79+4UFhYSEBBAUVERb7/9Njt27ADg888/B2DBggUsXbqUkJAQlixZQkxMDJ988gmNGjXi5MmTdkEEsK2fPHmybhdIRK4ImhkREZuuXbtisVhs6926dePTTz/l6NGjODk50alTJ9u+iIgIvL297frv2LGDXr160bRpU7y8vBg5ciTffPMNZ86cAaBz5860a9eOtLQ0ANauXUtwcDA9e/YEoLq6GoB58+Zx991306lTJ1JTU7FYLLz++uv1eeoiYiLNjIjUM3cHB471jDRt7Mvl+PHj9OvXj/vuu4+nnnqKRo0asXfvXsaOHUt5eTnu7u7Aj7Mjzz//PA899BCpqamMHj3aFoACAgIAaNu2re24rq6utGjRgoKCAgD8/f05ePCg3dhff/21bZ+IXH00MyJSzywWCx6OjqYsP5/lqI3MzEy79ffee4/WrVsTERFBZWUlWVlZtn15eXl89913tvWsrCyqq6tZsmQJXbt2JSwsjBMnTtQYY8SIEXzxxResXLmS3NxcRo0aZdvXqVMnXF1dycvLs22rqKjg+PHjBAcHAz/O1uTk5Ng9r7J9+3YaNGhgF2JE5OqhMCIiNgUFBcyYMYO8vDxeffVVkpOTmTZtGuHh4cTFxTFx4kQyMzPJyspi3LhxWK1WW99WrVpRUVFBcnIyn3/+OWvWrOHFF1+sMYaPjw8DBw4kMTGRPn360KxZM9u+Bg0aMGnSJB599FG2bdtGXl4e9913HwCDBw8GoE+fPrRt25aRI0fy0Ucf8c9//pOHH36Y+++/H1dX13q+QiJSHxRGRMQmPj6esrIyOnfuzP3338+0adOYMGEC8OO3XgIDA4mOjmbgwIFMmDABPz8/W9/27duzdOlSFi9ezPXXX8+6det4+umnzzvOT7duxowZU2PfM888w5AhQxg5ciQ33XQTX3zxBbt27cLHxwcAR0dH3nzzTRwdHenWrRsjRowgPj6exx9/vB6uiIhcDhajrt/9E5GLOnv2LPn5+YSGhuLm5mZ2OVekNWvW8MADD3DixAlcXFzMLueqos+XXIv0AKuIXDZnzpyhsLCQRYsWMXHiRAUREQF0m0ZELqOkpCQiIiLw9/dnzpw5ZpcjIlcI3aYRucQ0jS71SZ8vuRZpZkRERERMpTAiIiIiplIYEREREVMpjIiIiIipFEZERETEVAojIiIiYiqFEREBICYmhunTp9epT0hICMuXL6+XekTkj0NhRESuGBkZGVgslvMu77//vq3d4cOHufnmm3FzcyMoKIikpCQTqxaR30s/By8iV4zu3btTWFhot+2RRx5h586d3HjjjQD88MMP9OnTh969e/Piiy+Sk5PDmDFj8Pb2tr3UT0SuLpoZERGbyspKpkyZQsOGDWncuDGPPPIIP/1Ic1FREf3798dqtRIaGsq6detq9F+6dCmRkZF4eHgQFBTE5MmTKSkpAaC0tJQGDRqwceNGuz5btmzBw8OD06dP4+Ligr+/v23x9fVl69atjB49GovFAsC6desoLy9n9erVtGvXjiFDhjB16lSWLl1az1dHROqLwohIPTMMgzPllaYsdX3bQ1paGk5OThw8eJAVK1awdOlSXnrpJQASEhL48ssvSU9PZ+PGjaSkpFBUVGTX38HBgZUrV3LkyBHS0tLYtWsXs2fPBsDDw4MhQ4aQmppq1yc1NZVBgwbh5eVVo55//OMffPPNN4wePdq27cCBA/Ts2dPuJXuxsbHk5eVRXFxcp/MVkSuDbtOI1LOyiirazv+nKWPnPh6Lu0vt/zMPCgpi2bJlWCwWwsPDycnJYdmyZURHR/POO+9w8OBBbrrpJgBWrVpFmzZt7Pr//AHYkJAQnnzySSZNmkRKSgoA48aNs92KCQgIoKioiLfffpsdO3act55Vq1YRGxtLs2bNbNtOnjxJaGioXbsmTZrY9vn4+NT6fEXkyqCZERGx6dq1q+12CEC3bt349NNPOXr0KE5OTnTq1Mm2LyIiAm9vb7v+O3bsoFevXjRt2hQvLy9GjhzJN998w5kzZwDo3Lkz7dq1Iy0tDYC1a9cSHBxMz549a9Tyn//8h3/+85+MHTu2Hs5URK4kmhkRqWdWZ0dyH481bezL5fjx4/Tr14/77ruPp556ikaNGrF3717Gjh1LeXk57u7uwI+zI88//zwPPfQQqampds+D/Fxqaiq+vr7ccccddtv9/f35+uuv7bb9tO7v719PZyci9UlhRKSeWSyWOt0qMVNmZqbd+nvvvUfr1q2JiIigsrKSrKws222avLw8vvvuO1vbrKwsqqurWbJkCQ4OP066vvbaazXGGDFiBLNnz2blypXk5uYyatSoGm0MwyA1NZX4+HicnZ3t9nXr1o158+ZRUVFh27d9+3bCw8N1i0bkKqXbNCJiU1BQwIwZM8jLy+PVV18lOTmZadOmER4eTlxcHBMnTiQzM5OsrCzGjRuH1Wq19W3VqhUVFRUkJyfz+eefs2bNGl588cUaY/j4+DBw4EASExPp06eP3fMgP9m1axf5+fmMGzeuxr5hw4bh4uLC2LFjOXLkCBs2bGDFihXMmDHj0l4MEblsFEZExCY+Pp6ysjI6d+7M/fffz7Rp02y/3ZGamkpgYCDR0dEMHDiQCRMm4OfnZ+vbvn17li5dyuLFi7n++utZt24dTz/99HnH+enWzZgxY867f9WqVXTv3p2IiIga+xo2bMi2bdvIz8+nU6dOzJw5k/nz5+s3RkSuYhajrt/9E5GLOnv2LPn5+YSGhuLm5mZ2OVekNWvW8MADD3DixAm7r+jKr9PnS65FV8eNbBG5Jpw5c4bCwkIWLVrExIkTFUREBNBtGhG5jJKSkoiIiMDf3585c+aYXY6IXCF0m0bkEtM0utQnfb7kWqSZERERETGVwoiIiIiYSmFERERETKUwIiIiIqZSGBERERFTKYyIiIiIqRRGRASAmJgYpk+fXqc+ISEhLF++vF7qEZE/DoUREbmifPLJJ9x55500btyYBg0a8Kc//Yn09HS7NgUFBfTt2xd3d3f8/PxITEyksrLSpIpF5PdSGBGRK0q/fv2orKxk165dZGVl0b59e/r168fJkycBqKqqom/fvpSXl7N//37S0tJ4+eWXmT9/vsmVi8hvpTAiUt8MA8pLzVnq+APLlZWVTJkyhYYNG9K4cWMeeeQRfvqR5qKiIvr374/VaiU0NJR169bV6L906VIiIyPx8PAgKCiIyZMnU1JSAkBpaSkNGjRg48aNdn22bNmCh4cHp0+f5r///S+ffvopDz30EFFRUbRu3ZpFixZx5swZ/v3vfwOwbds2cnNzWbt2LR06dODPf/4zTzzxBM8//zzl5eW/5f8hETGZXpQnUt8qzsDCQHPGnnsCXDxq3TwtLY2xY8dy8OBBPvjgAyZMmEDz5s0ZP348CQkJnDhxgvT0dJydnZk6dSpFRUV2/R0cHFi5ciWhoaF8/vnnTJ48mdmzZ5OSkoKHhwdDhgwhNTWVQYMG2fr8tO7l5YWnpyfh4eG88sor3HDDDbi6uvKXv/wFPz8/OnXqBMCBAweIjIykSZMmtmPExsZy3333ceTIETp27Pg7L5qIXG4KIyJiExQUxLJly7BYLISHh5OTk8OyZcuIjo7mnXfe4eDBg9x0000ArFq1ijZt2tj1//kDsCEhITz55JNMmjSJlJQUAMaNG0f37t0pLCwkICCAoqIi3n77bXbs2AGAxWJhx44d3HXXXXh5eeHg4ICfnx/vvvsuPj4+AJw8edIuiAC29Z9u5YjI1UVhRKS+Obv/OENh1th10LVrVywWi229W7duLFmyhKNHj+Lk5GSbnQCIiIjA29vbrv+OHTt4+umn+fjjj/nhhx+orKzk7NmznDlzBnd3dzp37ky7du1IS0vjoYceYu3atQQHB9OzZ08ADMPg/vvvx8/Pjz179mC1WnnppZfo378/77//PgEBAb/9WojIFUvPjIjUN4vlx1slZiw/Cxb17fjx4/Tr14+oqCjeeOMNsrKyeP755wHsnuUYN24cL7/8MvDjLZrRo0fbAtCuXbt48803Wb9+PT169OCGG24gJSUFq9VKWloaAP7+/nz99dd2Y/+07u/vX9+nKSL1QGFERGwyMzPt1t977z1at25NREQElZWVZGVl2fbl5eXx3Xff2dazsrKorq5myZIldO3albCwME6cqDkjNGLECL744gtWrlxJbm4uo0aNsu07c+YM8OOzJz/n4OBAdXU18ONsTU5Ojt3zKtu3b6dBgwa0bdv2t5+8iJhGYUREbAoKCpgxYwZ5eXm8+uqrJCcnM23aNMLDw4mLi2PixIlkZmaSlZXFuHHjsFqttr6tWrWioqKC5ORkPv/8c9asWcOLL75YYwwfHx8GDhxIYmIiffr0oVmzZrZ93bp1w8fHh1GjRvHRRx/xySefkJiYSH5+Pn379gWgT58+tG3blpEjR/LRRx/xz3/+k4cffpj7778fV1fX+r9IInLJKYyIiE18fDxlZWV07tyZ+++/n2nTpjFhwgTgx1sqgYGBREdHM3DgQCZMmICfn5+tb/v27Vm6dCmLFy/m+uuvZ926dTz99NPnHWfs2LGUl5czZswYu+2NGzfm3XffpaSkhFtvvZUbb7yRvXv3snXrVtq3bw+Ao6Mjb775Jo6OjnTr1o0RI0YQHx/P448/Xk9XRUTqm8Uw6vhDBCJyUWfPniU/P5/Q0FDc3NzMLueKtGbNGh544AFOnDiBi4uL2eVcVfT5kmuRvk0jIpfNmTNnKCwsZNGiRUycOFFBREQA3aYRkcsoKSmJiIgI/P39mTNnjtnliMgVQrdpRC4xTaNLfdLnS65FmhkRERERUymMiIiIiKkURkRERMRUCiMiIiJiKoURERERMZXCiIiIiJhKYUREAIiJiWH69OkX3B8SEsLy5cvr5dgi8semX2AVkVp5//338fDwuGibjIwMbrnlFoqLi/H29r48hYnIVU9hRERq5brrrrvo/oqKistUiYhca3SbRqSeGYbBmYozpix1/YHlyspKpkyZQsOGDWncuDGPPPKI7Ri/vE1jsVh44YUXuOOOO/Dw8GD8+PHccsstAPj4+GCxWEhISLC1r66uZvbs2TRq1Ah/f38WLFhgd40WLFhA8+bNcXV1JTAwkKlTp/7may4iVxfNjIjUs7LKMrr8vYspY2cOy8Td2b3W7dPS0hg7diwHDx7kgw8+YMKECTRv3pzx48eft/2CBQtYtGgRy5cvx9HRkTvuuIO7776bvLw8GjRogNVqtTv2jBkzyMzM5MCBAyQkJNCjRw9uu+023njjDZYtW8b69etp164dJ0+e5KOPPvrd5y8iVweFERGxCQoKYtmyZVgsFsLDw8nJyWHZsmUXDCPDhg1j9OjRtvX8/HwA/Pz8ajwzEhUVxaOPPgpA69atee6559i5cye33XYbBQUF+Pv707t3b5ydnWnevDmdO3eun5MUkSuOwohIPbM6Wckclmna2HXRtWtXLBaLbb1bt24sWbKEqqqq87a/8cYba33sqKgou/WAgACKiooAGDx4MMuXL6dFixbExcVx++23079/f5yc9EeUyB+B/ksXqWcWi6VOt0quJr/27Zqfc3Z2tlu3WCxUV1cDP87I5OXlsWPHDrZv387kyZN55pln2L17d41+InLt0QOsImKTmWk/g/Pee+/RunVrHB0da9XfxcUF4IIzKRdjtVrp378/K1euJCMjgwMHDpCTk1Pn44jI1UczIyJiU1BQwIwZM5g4cSKHDh0iOTmZJUuW1Lp/cHAwFouFN998k9tvvx2r1Yqnp+ev9nv55ZepqqqiS5cuuLu7s3btWqxWK8HBwb/ndETkKqGZERGxiY+Pp6ysjM6dO3P//fczbdo0JkyYUOv+TZs25bHHHuOhhx6iSZMmTJkypVb9vL29+dvf/kaPHj2Iiopix44d/L//9//w9fX9raciIlcRi1HXHyIQkYs6e/Ys+fn5hIaG4ubmZnY5co3R50uuRZoZEREREVMpjIiIiIipFEZERETEVAojIiIiYiqFERERETGVwoiIiIiYSmFERERETKUwIiIiIqZSGBERERFTKYyIyAXFxMQwffp0s8sQkWucwoiImObs2bMkJCQQGRmJk5MTd911l9kliYgJFEZExDRVVVVYrVamTp1K7969zS5HREyiMCJSzwzDoPrMGVOWurwHs7S0lPj4eDw9PQkICGDJkiU12pw7d45Zs2bRtGlTPDw86NKlCxkZGXZt9u3bR0xMDO7u7vj4+BAbG0txcfF5x/Tw8OCFF15g/Pjx+Pv71+m6isi1w8nsAkSudUZZGXk3dDJl7PBDWVjc3WvVNjExkd27d7N161b8/PyYO3cuhw4dokOHDrY2U6ZMITc3l/Xr1xMYGMjmzZuJi4sjJyeH1q1bk52dTa9evRgzZgwrVqzAycmJ9PR0qqqq6ukMReRaoDAiIpSUlLBq1SrWrl1Lr169AEhLS6NZs2a2NgUFBaSmplJQUEBgYCAAs2bN4t133yU1NZWFCxeSlJTEjTfeSEpKiq1fu3btLu/JiMhVR2FEpJ5ZrFbCD2WZNnZtHDt2jPLycrp06WLb1qhRI8LDw23rOTk5VFVVERYWZtf33Llz+Pr6ApCdnc3gwYMvQeUi8keiMCJSzywWS61vlVzJSkpKcHR0JCsrC0dHR7t9np6eAFhrGX5ERH5OD7CKCC1btsTZ2ZnMzEzbtuLiYj755BPbeseOHamqqqKoqIhWrVrZLT89fBoVFcXOnTsve/0icnXTzIiI4OnpydixY0lMTMTX1xc/Pz/mzZuHg8P//r0SFhbG8OHDiY+PZ8mSJXTs2JFTp06xc+dOoqKi6Nu3L3PmzCEyMpLJkyczadIkXFxcSE9PZ/DgwTRu3Pi8Y+fm5lJeXs63337L6dOnyc7OBrB7cFZErm0KIyICwDPPPENJSQn9+/fHy8uLmTNn8v3339u1SU1N5cknn2TmzJl89dVXNG7cmK5du9KvXz/gx8Cybds25s6dS+fOnbFarXTp0oWhQ4decNzbb7+dL774wrbesWNHgDp9LVlErm4WQ//Fi1xSZ8+eJT8/n9DQUNzc3MwuR64x+nzJtUjPjIiIiIipFEZERETEVAojIiIiYiqFERERETGVwoiIiIiYSmFERERETKUwIiIiIqZSGBERERFTKYyIiIiIqRRGROSCYmJimD59utll2Dl+/DgWi8X2DhsRufopjIiIac6ePUtCQgKRkZE4OTlx1113mV2SiJhAYURETFNVVYXVamXq1Kn07t3b7HJExCQKIyL1zDAMKs5VmbLU5T2YpaWlxMfH4+npSUBAAEuWLKnR5ty5c8yaNYumTZvi4eFBly5dyMjIsGuzb98+YmJicHd3x8fHh9jYWIqLi887poeHBy+88ALjx4/H39+/Ttf153bv3k3nzp1xdXUlICCAhx56iMrKStv+jRs3EhkZidVqxdfXl969e1NaWgpARkYGnTt3xsPDA29vb3r06GH3FmERqX9OZhcgcq2rLK/mr9N2mzL2hBXROLs61qptYmIiu3fvZuvWrfj5+TF37lwOHTpEhw4dbG2mTJlCbm4u69evJzAwkM2bNxMXF0dOTg6tW7cmOzubXr16MWbMGFasWIGTkxPp6elUVVXV0xnCV199xe23305CQgKvvPIKH3/8MePHj8fNzY0FCxZQWFjI0KFDSUpKYsCAAZw+fZo9e/ZgGAaVlZXcddddjB8/nldffZXy8nIOHjyIxWKpt3pFpCaFERGhpKSEVatWsXbtWnr16gVAWloazZo1s7UpKCggNTWVgoICAgMDAZg1axbvvvsuqampLFy4kKSkJG688UZSUlJs/dq1a1evtaekpBAUFMRzzz2HxWIhIiKCEydO8OCDDzJ//nwKCwuprKxk4MCBBAcHAxAZGQnAt99+y/fff0+/fv1o2bIlAG3atKnXekWkJoURkXrm5OLAhBXRpo1dG8eOHaO8vJwuXbrYtjVq1Ijw8HDbek5ODlVVVYSFhdn1PXfuHL6+vgBkZ2czePDgS1B57R09epRu3brZzWb06NGDkpIS/vOf/9C+fXt69epFZGQksbGx9OnTh0GDBuHj40OjRo1ISEggNjaW2267jd69e3PPPfcQEBBwWc9B5I9OYUSknlksllrfKrmSlZSU4OjoSFZWFo6O9ufj6ekJgNVqNaO0i3J0dGT79u3s37+fbdu2kZyczLx588jMzCQ0NJTU1FSmTp3Ku+++y4YNG3j44YfZvn07Xbt2Nbt0kT8MPcAqIrRs2RJnZ2cyMzNt24qLi/nkk09s6x07dqSqqoqioiJatWplt/z08GlUVBQ7d+68rLW3adOGAwcO2D2su2/fPry8vGy3mSwWCz169OCxxx7jww8/xMXFhc2bN9ud25w5c9i/fz/XX389f//73y/rOYj80SmMiAienp6MHTuWxMREdu3axb///W8SEhJwcPjfHxFhYWEMHz6c+Ph4Nm3aRH5+PgcPHuTpp5/mrbfeAmDOnDm8//77TJ48mcOHD/Pxxx/zwgsv8N///veCY+fm5pKdnW17fiM7O7tOP2g2efJkvvzyS/7v//6Pjz/+mK1bt/Loo48yY8YMHBwcyMzMZOHChXzwwQcUFBSwadMmTp06RZs2bcjPz2fOnDkcOHCAL774gm3btvHpp5/quRGRy80QkUuqrKzMyM3NNcrKyswupU5Onz5tjBgxwnB3dzeaNGliJCUlGdHR0ca0adNsbcrLy4358+cbISEhhrOzsxEQEGAMGDDAOHz4sK1NRkaG0b17d8PV1dXw9vY2YmNjjeLi4guOGxwcbAA1lgvJz883AOPDDz+0G/Omm24yXFxcDH9/f+PBBx80KioqDMMwjNzcXCM2Nta47rrrDFdXVyMsLMxITk42DMMwTp48adx1111GQECA4eLiYgQHBxvz5883qqqqfttFvAyu1s+XyMVYDKMOP0QgIr/q7Nmz5OfnExoaipubm9nlyDVGny+5Fuk2jYiIiJhKYURERERMpTAiIiIiplIYEREREVMpjIiIiIipFEZERETEVAojIiIiYiqFERERETGVwoiIiIiYSmFERC4oJiaG6dOnm12GnePHj2OxWOr0/hoRubIpjIiIac6ePUtCQgKRkZE4OTlx1113mV1SvbkSg53IlUJhRERMU1VVhdVqZerUqfTu3dvscn6TiooKs0sQueopjIjUM8MwqDh71pSlLu/BLC0tJT4+Hk9PTwICAliyZEmNNufOnWPWrFk0bdoUDw8PunTpQkZGhl2bffv2ERMTg7u7Oz4+PsTGxlJcXHzeMT08PHjhhRcYP348/v7+dbquP7d79246d+6Mq6srAQEBPPTQQ1RWVtr2b9y4kcjISKxWK76+vvTu3ZvS0lIAMjIy6Ny5Mx4eHnh7e9OjRw+++OKL847z0y2iDRs2EB0djZubG+vWreObb75h6NChNG3aFHd3dyIjI3n11Vdt/RISEti9ezcrVqzAYrFgsVg4fvw4AP/+97/585//jKenJ02aNGHkyJH897///c3XQuRq5GR2ASLXuspz51g5apApY09N24hzLd/smpiYyO7du9m6dSt+fn7MnTuXQ4cO0aFDB1ubKVOmkJuby/r16wkMDGTz5s3ExcWRk5ND69atyc7OplevXowZM4YVK1bg5OREeno6VVVV9XSG8NVXX3H77beTkJDAK6+8wscff8z48eNxc3NjwYIFFBYWMnToUJKSkhgwYACnT59mz549GIZBZWUld911F+PHj+fVV1+lvLycgwcPYrFYLjrmQw89xJIlS+jYsSNubm6cPXuWTp068eCDD9KgQQPeeustRo4cScuWLencuTMrVqzgk08+4frrr+fxxx8H4LrrruO7777j1ltvZdy4cSxbtoyysjIefPBB7rnnHnbt2lVv10zkSqMwIiKUlJSwatUq1q5dS69evQBIS0ujWbNmtjYFBQWkpqZSUFBAYGAgALNmzeLdd98lNTWVhQsXkpSUxI033khKSoqtX7t27eq19pSUFIKCgnjuueewWCxERERw4sQJHnzwQebPn09hYSGVlZUMHDiQ4OBgACIjIwH49ttv+f777+nXrx8tW7YEoE2bNr865vTp0xk4cKDdtlmzZtn+9//93//xz3/+k9dee43OnTvTsGFDXFxccHd3t5sBeu655+jYsSMLFy60bVu9ejVBQUF88sknhIWF/fYLI3IVURgRqWdOrq5MTdto2ti1cezYMcrLy+nSpYttW6NGjQgPD7et5+TkUFVVVeMvyHPnzuHr6wtAdnY2gwcPvgSV197Ro0fp1q2b3WxGjx49KCkp4T//+Q/t27enV69eREZGEhsbS58+fRg0aBA+Pj40atSIhIQEYmNjue222+jduzf33HMPAQEBFx3zxhtvtFuvqqpi4cKFvPbaa3z11VeUl5dz7tw53N3dL3qcjz76iPT0dDw9PWvsO3bsmMKI/GEojIjUM4vFUutbJVeykpISHB0dycrKwtHR0W7fT3+ZWq1WM0q7KEdHR7Zv387+/fvZtm0bycnJzJs3j8zMTEJDQ0lNTWXq1Km8++67bNiwgYcffpjt27fTtWvXCx7Tw8PDbv2ZZ55hxYoVLF++nMjISDw8PJg+fTrl5eUXra2kpIT+/fuzePHiGvt+LRCJXEv0AKuI0LJlS5ydncnMzLRtKy4u5pNPPrGtd+zYkaqqKoqKimjVqpXd8tOth6ioKHbu3HlZa2/Tpg0HDhywe1h33759eHl52W4zWSwWevTowWOPPcaHH36Ii4sLmzdvtju3OXPmsH//fq6//nr+/ve/16mGffv2ceeddzJixAjat29PixYt7K4dgIuLS41nZ2644QaOHDlCSEhIjWv6y8Ajci1TGBERPD09GTt2LImJiezatYt///vfJCQk4ODwvz8iwsLCGD58OPHx8WzatIn8/HwOHjzI008/zVtvvQXAnDlzeP/995k8eTKHDx/m448/5oUXXrjot0Nyc3PJzs62Pb+RnZ1dpx80mzx5Ml9++SX/93//x8cff8zWrVt59NFHmTFjBg4ODmRmZrJw4UI++OADCgoK2LRpE6dOnaJNmzbk5+czZ84cDhw4wBdffMG2bdv49NNPa/XcyM+1bt3aNvty9OhRJk6cyNdff23XJiQkhMzMTI4fP85///tfqquruf/++/n2228ZOnQo77//PseOHeOf//wno0ePrteHfkWuOIaIXFJlZWVGbm6uUVZWZnYpdXL69GljxIgRhru7u9GkSRMjKSnJiI6ONqZNm2ZrU15ebsyfP98ICQkxnJ2djYCAAGPAgAHG4cOHbW0yMjKM7t27G66uroa3t7cRGxtrFBcXX3Dc4OBgA6ixXEh+fr4BGB9++KHdmDfddJPh4uJi+Pv7Gw8++KBRUVFhGIZh5ObmGrGxscZ1111nuLq6GmFhYUZycrJhGIZx8uRJ46677jICAgIMFxcXIzg42Jg/f75RVVVV67ENwzC++eYb48477zQ8PT0NPz8/4+GHHzbi4+ONO++809YmLy/P6Nq1q2G1Wg3AyM/PNwzDMD755BNjwIABhre3t2G1Wo2IiAhj+vTpRnV19XlruFo/XyIXYzGMOvwQgYj8qrNnz5Kfn09oaChu18CzInJl0edLrkW6TSMiIiKmUhgRERERUymMiIiIiKkURkRERMRUCiMiIiJiKoURERERMZXCiIiIiJhKYURERERMpTAiIiIiplIYEZELiomJYfr06WaXISLXOIURETFNRkYGd955JwEBAXh4eNChQwfWrVtndlkicpkpjIiIafbv309UVBRvvPEGhw8fZvTo0cTHx/Pmm2+aXZqIXEYKIyL1zDAMqsurTFnq8h7M0tJS4uPj8fT0JCAggCVLltRoc+7cOWbNmkXTpk3x8PCgS5cuZGRk2LXZt28fMTExuLu74+PjQ2xsLMXFxecdc+7cuTzxxBN0796dli1bMm3aNOLi4ti0aVOdrrGIXN2czC5A5FpnVFRzYv5+U8YOfLw7FhfHWrVNTExk9+7dbN26FT8/P+bOncuhQ4fo0KGDrc2UKVPIzc1l/fr1BAYGsnnzZuLi4sjJyaF169ZkZ2fTq1cvxowZw4oVK3ByciI9PZ2qqqpa1/z999/Tpk2bup6qiFzFFEZEhJKSElatWsXatWvp1asXAGlpaTRr1szWpqCggNTUVAoKCggMDARg1qxZvPvuu6SmprJw4UKSkpK48cYbSUlJsfVr165dret47bXXeP/99/nLX/5yic5MRK4GCiMi9czi7EDg491NG7s2jh07Rnl5OV26dLFta9SoEeHh4bb1nJwcqqqqCAsLs+t77tw5fH19AcjOzmbw4MG/qdb09HRGjx7N3/72tzoFGBG5+imMiNQzi8VS61slV7KSkhIcHR3JysrC0dH+fDw9PQGwWq2/6di7d++mf//+LFu2jPj4+N9dq4hcXfQAq4jQsmVLnJ2dyczMtG0rLi7mk08+sa137NiRqqoqioqKaNWqld3i7+8PQFRUFDt37qzT2BkZGfTt25fFixczYcKES3NCInJVURgRETw9PRk7diyJiYns2rWLf//73yQkJODg8L8/IsLCwhg+fDjx8fFs2rSJ/Px8Dh48yNNPP81bb70FwJw5c3j//feZPHkyhw8f5uOPP+aFF17gv//973nHTU9Pp2/fvkydOpW7776bkydPcvLkSb799tvLct4icmVQGBERAJ555hluvvlm+vfvT+/evfnTn/5Ep06d7NqkpqYSHx/PzJkzCQ8P56677uL999+nefPmwI+BZdu2bXz00Ud07tyZbt26sXXrVpyczn9HOC0tjTNnzvD0008TEBBgWwYOHFjv5ysiVw6LUZcfIhCRX3X27Fny8/MJDQ3Fzc3N7HLkGqPPl1yLNDMiIiIiplIYEREREVMpjIiIiIipFEZERETEVAojIiIiYiqFERERETGVwoiIiIiYSmFERERETKUwIiIiIqZSGBGRC4qJiWH69Olml2EnIyMDi8XCd999Z3YpInKJKIyIiGkyMjK48847CQgIwMPDgw4dOrBu3TqzyxKRy0xhRERMs3//fqKionjjjTc4fPgwo0ePJj4+njfffNPs0kTkMlIYEalnhmFQXl5uylKX92CWlpYSHx+Pp6cnAQEBLFmypEabc+fOMWvWLJo2bYqHhwddunQhIyPDrs2+ffuIiYnB3d0dHx8fYmNjKS4uPu+Yc+fO5YknnqB79+60bNmSadOmERcXx6ZNm+p0jd944w3atWuHq6srISEhNWpPSUmhdevWuLm50aRJEwYNGmTbt3HjRiIjI7Farfj6+tK7d29KS0vrNL6I/D7nf6+3iFwyFRUVLFy40JSx586di4uLS63aJiYmsnv3brZu3Yqfnx9z587l0KFDdOjQwdZmypQp5Obmsn79egIDA9m8eTNxcXHk5OTQunVrsrOz6dWrF2PGjGHFihU4OTmRnp5OVVVVrWv+/vvvadOmTa3bZ2Vlcc8997BgwQLuvfde9u/fz+TJk/H19SUhIYEPPviAqVOnsmbNGrp37863337Lnj17ACgsLGTo0KEkJSUxYMAATp8+zZ49e+oU4kTk91MYERFKSkpYtWoVa9eupVevXgCkpaXRrFkzW5uCggJSU1MpKCggMDAQgFmzZvHuu++SmprKwoULSUpK4sYbbyQlJcXWr127drWu47XXXuP999/nL3/5S637LF26lF69evHII48AEBYWRm5uLs888wwJCQkUFBTg4eFBv3798PLyIjg4mI4dOwI/hpHKykoGDhxIcHAwAJGRkbUeW0QuDYURkXrm7OzM3LlzTRu7No4dO0Z5eTldunSxbWvUqBHh4eG29ZycHKqqqggLC7Pre+7cOXx9fQHIzs5m8ODBv6nW9PR0Ro8ezd/+9rc6BZijR49y55132m3r0aMHy5cvp6qqittuu43g4GBatGhBXFwccXFxDBgwAHd3d9q3b0+vXr2IjIwkNjaWPn36MGjQIHx8fH7TOYjIb6MwIlLPLBZLrW+VXMlKSkpwdHQkKysLR0dHu32enp4AWK3W33Ts3bt3079/f5YtW0Z8fPzvrvXnvLy8OHToEBkZGWzbto358+ezYMEC3n//fby9vdm+fTv79+9n27ZtJCcnM2/ePDIzMwkNDb2kdYjIhekBVhGhZcuWODs7k5mZadtWXFzMJ598Ylvv2LEjVVVVFBUV0apVK7vF398fgKioKHbu3FmnsTMyMujbty+LFy9mwoQJda69TZs27Nu3z27bvn37CAsLs4UmJycnevfuTVJSEocPH+b48ePs2rUL+DEs9ujRg8cee4wPP/wQFxcXNm/eXOc6ROS308yIiODp6cnYsWNJTEzE19cXPz8/5s2bh4PD//69EhYWxvDhw4mPj2fJkiV07NiRU6dOsXPnTqKioujbty9z5swhMjKSyZMnM2nSJFxcXEhPT2fw4ME0bty4xrjp6en069ePadOmcffdd3Py5EkAXFxcaNSoUa1qnzlzJjfddBNPPPEE9957LwcOHOC5556zPbfy5ptv8vnnn9OzZ098fHx4++23qa6uJjw8nMzMTHbu3EmfPn3w8/MjMzOTU6dO1ekBWhG5BAwRuaTKysqM3Nxco6yszOxS6uT06dPGiBEjDHd3d6NJkyZGUlKSER0dbUybNs3Wpry83Jg/f74REhJiODs7GwEBAcaAAQOMw4cP29pkZGQY3bt3N1xdXQ1vb28jNjbWKC4uPu+Yo0aNMoAaS3R09AXrTE9PNwC7Y27cuNFo27at4ezsbDRv3tx45plnbPv27NljREdHGz4+PobVajWioqKMDRs2GIZhGLm5uUZsbKxx3XXXGa6urkZYWJiRnJz8m67f5XK1fr5ELsZiGPoOm8ildPbsWfLz8wkNDcXNzc3scuQao8+XXIv0zIiIiIiYSmFERERETKUwIiIiIqZSGBERERFTKYyIiIiIqRRGRERExFQKIyIiImIqhRERERExlcKIiIiImEphREQuKCYmhunTp5tdhp2MjAwsFgvfffed2aWIyCWiMCIipsnIyODOO+8kICAADw8POnTowLp168wuq16EhISwfPlys8sQuSIpjIiIafbv309UVBRvvPEGhw8fZvTo0cTHx/Pmm2+aXVqtGIZBZWWl2WWIXPUURkTqmWEYVFWdMWWpy3swS0tLiY+Px9PTk4CAAJYsWVKjzblz55g1axZNmzbFw8ODLl26kJGRYddm3759xMTE4O7ujo+PD7GxsRQXF593zLlz5/LEE0/QvXt3WrZsybRp04iLi2PTpk11usZvvPEG7dq1w9XVlZCQkBq1p6Sk0Lp1a9zc3GjSpAmDBg2y7du4cSORkZFYrVZ8fX3p3bs3paWl5x3np1tE77zzDp06dcLV1ZW9e/dy7Ngx7rzzTpo0aYKnpyc33XQTO3bssPWLiYnhiy++4IEHHsBisWCxWGz79u7dy80334zVaiUoKIipU6decHyRa5WT2QWIXOuqq8vI2B1pytgx0Tk4OrrXqm1iYiK7d+9m69at+Pn5MXfuXA4dOkSHDh1sbaZMmUJubi7r168nMDCQzZs3ExcXR05ODq1btyY7O5tevXoxZswYVqxYgZOTE+np6VRVVdW65u+//542bdrUun1WVhb33HMPCxYs4N5772X//v1MnjwZX19fEhIS+OCDD5g6dSpr1qyhe/fufPvtt+zZsweAwsJChg4dSlJSEgMGDOD06dPs2bPnV0PcQw89xLPPPkuLFi3w8fHhyy+/5Pbbb+epp57C1dWVV155hf79+5OXl0fz5s3ZtGkT7du3Z8KECYwfP952nGPHjhEXF8eTTz7J6tWrOXXqFFOmTGHKlCmkpqbW+hqIXO0sRl3+6SQiv+qXr3ivqjpzxYeRkpISfH19Wbt2LYMHDwbg22+/pVmzZkyYMIHly5dTUFBAixYtKCgoIDAw0Na3d+/edO7cmYULFzJs2DAKCgrYu3fvb6r3tddeY+TIkRw6dIh27dqdt01GRga33HILxcXFeHt7M3z4cE6dOsW2bdtsbWbPns1bb73FkSNH2LRpE6NHj+Y///kPXl5edsc6dOgQnTp14vjx4wQHB/9qfT+NvWXLFu68886Ltr3++uuZNGkSU6ZMAX58ZmT69Ol2DwSPGzcOR0dH/vKXv9i27d27l+joaEpLS3Fzc6tx3F9+vkSuBZoZEalnDg5WYqJzTBu7No4dO0Z5eTldunSxbWvUqBHh4eG29ZycHKqqqggLC7Pre+7cOXx9fQHIzs62hZm6Sk9PZ/To0fztb3+7YBA5n6NHj9YIBj169GD58uVUVVVx2223ERwcTIsWLYiLiyMuLo4BAwbg7u5O+/bt6dWrF5GRkcTGxtKnTx8GDRqEj4/PRce88cYb7dZLSkpYsGABb731FoWFhVRWVlJWVkZBQcFFj/PRRx9x+PBhu4d2DcOgurqa/Pz8Os0QiVzNFEZE6pnFYqn1rZIrWUlJCY6OjmRlZeHo6Gi3z9PTEwCrtXbh55d2795N//79WbZsGfHx8b+71p/z8vLi0KFDZGRksG3bNubPn8+CBQt4//338fb2Zvv27ezfv59t27aRnJzMvHnzyMzMJDQ09ILH9PDwsFufNWsW27dv59lnn6VVq1ZYrVYGDRpEeXn5RWsrKSlh4sSJTJ06tca+5s2b/7YTFrkK6QFWEaFly5Y4OzuTmZlp21ZcXMwnn3xiW+/YsSNVVVUUFRXRqlUru8Xf3x+AqKgodu7cWaexMzIy6Nu3L4sXL2bChAl1rr1Nmzbs27fPbtu+ffsICwuzhSYnJyd69+5NUlIShw8f5vjx4+zatQv4MSz26NGDxx57jA8//BAXFxc2b95cpxr27dtHQkICAwYMIDIyEn9/f44fP27XxsXFpcazMzfccAO5ubk1rmerVq1wcXGp45UQuXppZkRE8PT0ZOzYsSQmJuLr64ufnx/z5s3DweF//14JCwtj+PDhxMfHs2TJEjp27MipU6fYuXMnUVFR9O3blzlz5hAZGcnkyZOZNGkSLi4upKenM3jwYBo3blxj3PT0dPr168e0adO4++67OXnyJPDjX9yNGjWqVe0zZ87kpptu4oknnuDee+/lwIEDPPfcc6SkpADw5ptv8vnnn9OzZ098fHx4++23qa6uJjw8nMzMTHbu3EmfPn3w8/MjMzOTU6dO1fn2SOvWrdm0aRP9+/fHYrHwyCOPUF1dbdcmJCSEf/3rXwwZMgRXV1caN27Mgw8+SNeuXZkyZQrjxo3Dw8OD3Nxctm/fznPPPVenGkSuaoaIXFJlZWVGbm6uUVZWZnYpdXL69GljxIgRhru7u9GkSRMjKSnJiI6ONqZNm2ZrU15ebsyfP98ICQkxnJ2djYCAAGPAgAHG4cOHbW0yMjKM7t27G66uroa3t7cRGxtrFBcXn3fMUaNGGUCNJTo6+oJ1pqenG4DdMTdu3Gi0bdvWcHZ2Npo3b24888wztn179uwxoqOjDR8fH8NqtRpRUVHGhg0bDMMwjNzcXCM2Nta47rrrDFdXVyMsLMxITk6u09iGYRj5+fnGLbfcYlitViMoKMh47rnnaly7AwcOGFFRUYarq6vx8z96Dx48aNx2222Gp6en4eHhYURFRRlPPfXUBWu4Wj9fIhejb9OIXGL6toPUJ32+5FqkZ0ZERETEVAojIiIiYiqFERERETGVwoiIiIiYSmFERERETKUwIiIiIqZSGBERERFTKYyIiIiIqRRGRERExFQKIyJyQTExMUyfPt3sMkTkGqcwIiKmycvL45ZbbqFJkya4ubnRokULHn74YSoqKswuTUQuI721V0RM4+zsTHx8PDfccAPe3t589NFHjB8/nurqahYuXGh2eSJymWhmRKSeGYZBaVWVKUtd3oNZWlpKfHw8np6eBAQEsGTJkhptzp07x6xZs2jatCkeHh506dKFjIwMuzb79u0jJiYGd3d3fHx8iI2Npbi4+LxjtmjRgtGjR9O+fXuCg4O54447GD58OHv27KnTNRaRq5tmRkTq2Znqalr+K8eUsY/1jMTD0bFWbRMTE9m9ezdbt27Fz8+PuXPncujQITp06GBrM2XKFHJzc1m/fj2BgYFs3ryZuLg4cnJyaN26NdnZ2fTq1YsxY8awYsUKnJycSE9Pp6qqqlY1fPbZZ7z77rsMHDjwt5yuiFylLEZd/ukkIr/ql694L62quuLDSElJCb6+vqxdu5bBgwcD8O2339KsWTMmTJjA8uXLKSgooEWLFhQUFBAYGGjr27t3bzp37szChQsZNmwYBQUF7N27t051du/enUOHDnHu3DkmTJjACy+8gIODJm7P55efL5FrgWZGROqZu4MDx3pGmjZ2bRw7dozy8nK6dOli29aoUSPCw8Nt6zk5OVRVVREWFmbX99y5c/j6+gKQnZ1tCzN1sWHDBk6fPs1HH31EYmIizz77LLNnz67zcUTk6qQwIlLPLBZLrW+VXMlKSkpwdHQkKysLx1+cj6enJwBWq/U3HTsoKAiAtm3bUlVVxYQJE5g5c2aNcUTk2qR5UBGhZcuWODs7k5mZadtWXFzMJ598Ylvv2LEjVVVVFBUV0apVK7vF398fgKioKHbu3Pm7aqmurqaiooLq6urfdRwRuXpoZkRE8PT0ZOzYsSQmJuLr64ufnx/z5s2ze24jLCyM4cOHEx8fz5IlS+jYsSOnTp1i586dREVF0bdvX+bMmUNkZCSTJ09m0qRJuLi4kJ6ezuDBg2ncuHGNcdetW4ezszORkZG4urrywQcfMGfOHO69916cnZ0v5yUQERMpjIgIAM888wwlJSX0798fLy8vZs6cyffff2/XJjU1lSeffJKZM2fy1Vdf0bhxY7p27Uq/fv2AHwPLtm3bmDt3Lp07d8ZqtdKlSxeGDh163jGdnJxYvHgxn3zyCYZhEBwczJQpU3jggQfq/XxF5Mqhb9OIXGL6toPUJ32+5FqkZ0ZERETEVAojIiIiYiqFERERETGVwoiIiIiYSmFERERETKUwIiIiIqZSGBERERFTKYyIiIiIqRRGROSCYmJimD59utll2MnIyMBisfDdd9+ZXYqIXCIKIyJimry8PG655RaaNGmCm5sbLVq04OGHH6aiosLs0kTkMtK7aUTENM7OzsTHx3PDDTfg7e3NRx99xPjx46murmbhwoVmlycil4lmRkQEgNLSUuLj4/H09CQgIIAlS5bUaHPu3DlmzZpF06ZN8fDwoEuXLmRkZNi12bdvHzExMbi7u+Pj40NsbCzFxcXnHbNFixaMHj2a9u3bExwczB133MHw4cPZs2dPnWp/4403aNeuHa6uroSEhNSoPSUlhdatW+Pm5kaTJk0YNGiQbd/GjRuJjIzEarXi6+tL7969KS0trdP4IvL7aGZEpJ4ZhkFZRZUpY1udHbFYLLVqm5iYyO7du9m6dSt+fn7MnTuXQ4cO0aFDB1ubKVOmkJuby/r16wkMDGTz5s3ExcWRk5ND69atyc7OplevXowZM4YVK1bg5OREeno6VVW1O//PPvuMd999l4EDB9b6HLOysrjnnntYsGAB9957L/v372fy5Mn4+vqSkJDABx98wNSpU1mzZg3du3fn22+/tYWdwsJChg4dSlJSEgMGDOD06dPs2bMHvT9U5PLSW3tFLrFfvlX1THklbef/05Rach+Pxd3l1//NUVJSgq+vL2vXrmXw4MEAfPvttzRr1owJEyawfPlyCgoKaNGiBQUFBQQGBtr69u7dm86dO7Nw4UKGDRtGQUEBe/furVOd3bt359ChQ5w7d44JEybwwgsv4OBw/onbjIwMbrnlFoqLi/H29mb48OGcOnWKbdu22drMnj2bt956iyNHjrBp0yZGjx7Nf/7zH7y8vOyOdejQITp16sTx48cJDg6uU81m0Vt75Vqk2zQiwrFjxygvL6dLly62bY0aNSI8PNy2npOTQ1VVFWFhYXh6etqW3bt3c+zYMQDbzEhdbdiwgUOHDvH3v/+dt956i2effbbWfY8ePUqPHj3stvXo0YNPP/2UqqoqbrvtNoKDg2nRogUjR45k3bp1nDlzBoD27dvTq1cvIiMjGTx4MH/7298ueEtJROqPbtOI1DOrsyO5j8eaNvalUlJSgqOjI1lZWTg62h/X09Pzx/Gs1t907KCgIADatm1LVVUVEyZMYObMmTXG+S28vLw4dOgQGRkZbNu2jfnz57NgwQLef/99vL292b59O/v372fbtm0kJyczb948MjMzCQ0N/d1ji0jtaGZEpJ5ZLBbcXZxMWWr7vEjLli1xdnYmMzPTtq24uJhPPvnEtt6xY0eqqqooKiqiVatWdou/vz8AUVFR7Ny583ddr+rqaioqKqiurq5V+zZt2rBv3z67bfv27SMsLMwWZpycnOjduzdJSUkcPnyY48ePs2vXLuDH/3969OjBY489xocffoiLiwubN2/+XecgInWjmRERwdPTk7Fjx5KYmIivry9+fn7MmzfP7rmNsLAwhg8fTnx8PEuWLKFjx46cOnWKnTt3EhUVRd++fZkzZw6RkZFMnjyZSZMm4eLiQnp6OoMHD6Zx48Y1xl23bh3Ozs5ERkbi6urKBx98wJw5c7j33ntxdnauVe0zZ87kpptu4oknnuDee+/lwIEDPPfcc6SkpADw5ptv8vnnn9OzZ098fHx4++23qa6uJjw8nMzMTHbu3EmfPn3w8/MjMzOTU6dO0aZNm0tzYUWkdgwRuaTKysqM3Nxco6yszOxS6uT06dPGiBEjDHd3d6NJkyZGUlKSER0dbUybNs3Wpry83Jg/f74REhJiODs7GwEBAcaAAQOMw4cP29pkZGQY3bt3N1xdXQ1vb28jNjbWKC4uPu+Y69evN2644QbD09PT8PDwMNq2bWssXLjwotcuPT3dAOyOuXHjRqNt27aGs7Oz0bx5c+OZZ56x7duzZ48RHR1t+Pj4GFar1YiKijI2bNhgGIZh5ObmGrGxscZ1111nuLq6GmFhYUZycvJvu4CXydX6+RK5GH2bRuQS07cdpD7p8yXXIj0zIiIiIqZSGBERERFTKYyIiIiIqRRGRERExFQKIyIiImIqhRERERExlcKIiIiImEphREREREylMCIiIiKmUhgRkQuKiYlh+vTpZpdhJyMjA4vFwnfffWd2KSJyiSiMiIhp8vLyuOWWW2jSpAlubm60aNGChx9+mIqKCrNLu+RCQkJYvny52WWIXJH01l4RMY2zszPx8fHccMMNeHt789FHHzF+/Hiqq6tZuHCh2eX9KsMwqKqqwslJf5SK/B6aGRERAEpLS4mPj8fT05OAgACWLFlSo825c+eYNWsWTZs2xcPDgy5dupCRkWHXZt++fcTExODu7o6Pjw+xsbEUFxefd8wWLVowevRo2rdvT3BwMHfccQfDhw9nz549dar9jTfeoF27dri6uhISElKj9pSUFFq3bo2bmxtNmjRh0KBBtn0bN24kMjISq9WKr68vvXv3prS09Lzj/HSL6J133qFTp064urqyd+9ejh07xp133kmTJk3w9PTkpptuYseOHbZ+MTExfPHFFzzwwANYLBYsFott3969e7n55puxWq0EBQUxderUC44vcq1SGBGpb4YB5aXmLHV4KXdiYiK7d+9m69atbNu2jYyMDA4dOmTXZsqUKRw4cID169dz+PBhBg8eTFxcHJ9++ikA2dnZ9OrVi7Zt23LgwAH27t1L//79qaqqqlUNn332Ge+++y7R0dG1rjsrK4t77rmHIUOGkJOTw4IFC3jkkUd4+eWXAfjggw+YOnUqjz/+OHl5ebz77rv07NkTgMLCQoYOHcqYMWM4evQoGRkZDBw4kF97mflDDz3EokWLOHr0KFFRUZSUlHD77bezc+dOPvzwQ+Li4ujfvz8FBQUAbNq0iWbNmvH4449TWFhIYWEhAMeOHSMuLo67776bw4cPs2HDBvbu3cuUKVNqff4i1wKL8Wv/1YlIndR4xXt5KSwMNKeYuSfAxeNXm5WUlODr68vatWsZPHgwAN9++y3NmjVjwoQJLF++nIKCAlq0aEFBQQGBgf87n969e9O5c2cWLlzIsGHDKCgoYO/evXUqs3v37hw6dIhz584xYcIEXnjhBRwczv9vpYyMDG655RaKi4vx9vZm+PDhnDp1im3bttnazJ49m7feeosjR46wadMmRo8ezX/+8x+8vLzsjnXo0CE6derE8ePHCQ4O/tU6fxp7y5Yt3HnnnRdte/311zNp0iRbsAgJCWH69Ol2DwSPGzcOR0dH/vKXv9i27d27l+joaEpLS3/8/PxCjc+XyDVAMyMiwrFjxygvL6dLly62bY0aNSI8PNy2npOTQ1VVFWFhYXh6etqW3bt3c+zYMeB/MyN1tWHDBg4dOsTf//533nrrLZ599tla9z169Cg9evSw29ajRw8+/fRTqqqquO222wgODqZFixaMHDmSdevWcebMGQDat29Pr169iIyMZPDgwfztb3+74C2ln7vxxhvt1ktKSpg1axZt2rTB29sbT09Pjh49apsZuZCPPvqIl19+2e56xsbGUl1dTX5+fq2vgcjVTk9didQ3Z/cfZyjMGvsSKSkpwdHRkaysLBwdHe32eXp6AmC1Wn/TsYOCggBo27YtVVVVTJgwgZkzZ9YY57fw8vLi0KFDZGRksG3bNubPn8+CBQt4//338fb2Zvv27ezfv59t27aRnJzMvHnzyMzMJDQ09ILH9PCwn22aNWsW27dv59lnn6VVq1ZYrVYGDRpEeXn5RWsrKSlh4sSJTJ06tca+5s2b/7YTFrkKKYyI1DeLpVa3SszUsmVLnJ2dyczMtP0lWFxczCeffGJ7fqNjx45UVVVRVFTEzTfffN7jREVFsXPnTh577LHfXEt1dTUVFRVUV1fXKoy0adOGffv22W3bt28fYWFhtv5OTk707t2b3r178+ijj+Lt7c2uXbsYOHAgFouFHj160KNHD+bPn09wcDCbN29mxowZta553759JCQkMGDAAODHkHH8+HG7Ni4uLjWenbnhhhvIzc2lVatWtR5L5FqkMCIieHp6MnbsWBITE/H19cXPz4958+bZPbcRFhbG8OHDiY+PZ8mSJXTs2JFTp06xc+dOoqKi6Nu3L3PmzCEyMpLJkyczadIkXFxcSE9PZ/DgwTRu3LjGuOvWrcPZ2ZnIyEhcXV354IMPmDNnDvfeey/Ozs61qn3mzJncdNNNPPHEE9x7770cOHCA5557jpSUFADefPNNPv/8c3r27ImPjw9vv/021dXVhIeHk5mZyc6dO+nTpw9+fn5kZmZy6tQp2rRpU6fr17p1azZt2kT//v2xWCw88sgjVFdX27UJCQnhX//6F0OGDMHV1ZXGjRvz4IMP0rVrV6ZMmcK4cePw8PAgNzeX7du389xzz9WpBpGrmiEil1RZWZmRm5trlJWVmV1KnZw+fdoYMWKE4e7ubjRp0sRISkoyoqOjjWnTptnalJeXG/PnzzdCQkIMZ2dnIyAgwBgwYIBx+PBhW5uMjAyje/fuhqurq+Ht7W3ExsYaxcXF5x1z/fr1xg033GB4enoaHh4eRtu2bY2FCxde9Nqlp6cbgN0xN27caLRt29ZwdnY2mjdvbjzzzDO2fXv27DGio6MNHx8fw2q1GlFRUcaGDRsMwzCM3NxcIzY21rjuuusMV1dXIywszEhOTq7T2IZhGPn5+cYtt9xiWK1WIygoyHjuuedqXLsDBw4YUVFRhqurq/HzP3oPHjxo3HbbbbZrEBUVZTz11FMXrOFq/XyJXIy+TSNyienbDlKf9PmSa5G+TSMiIiKmUhgRERERUymMiIiIiKkURkRERMRUCiMiIiJiKoURERERMZXCiIiIiJhKYURERERMdVWFkX/961/079+fwMBALBYLW7ZsqVP/BQsWYLFYaiy/fOmViIiIXD5XVRgpLS2lffv2PP/887+p/6xZsygsLLRb2rZty+DBgy9xpSLXhpiYGKZPn252GSJyjbuqwsif//xnnnzySdubMX/p3LlzzJo1i6ZNm+Lh4UGXLl3IyMiw7ff09MTf39+2fP311+Tm5jJ27NjLdAYiciGfffYZXl5eeHt7m12KiFxmV1UY+TVTpkzhwIEDrF+/nsOHDzN48GDi4uL49NNPz9v+pZdeIiws7IKvQxeRy6OiooKhQ4fqv0WRP6hrJowUFBSQmprK66+/zs0330zLli2ZNWsWf/rTn0hNTa3R/uzZs6xbt06zIiL/v9LSUuLj4/H09CQgIIAlS5bUaPNrs48A+/btIyYmBnd3d3x8fIiNjaW4uPiiYz/88MNERERwzz33XMpTEpGrhJPZBVwqOTk5VFVVERYWZrf93Llz+Pr61mi/efNmTp8+zahRoy5XifIHZRgGZZVlpoxtdbJisVhq1TYxMZHdu3ezdetW/Pz8mDt3LocOHaJDhw62NlOmTCE3N5f169cTGBjI5s2biYuLIycnh9atW5OdnU2vXr0YM2YMK1aswMnJifT0dKqqqi447q5du3j99dfJzs5m06ZNv/eUReQqdM2EkZKSEhwdHcnKysLR0dFun6enZ432L730Ev369aNJkyaXq0T5gyqrLKPL37uYMnbmsEzcnd1/tV1JSQmrVq1i7dq19OrVC4C0tDSaNWtma/PT7GNBQQGBgYHAjw+Fv/vuu6SmprJw4UKSkpK48cYbSUlJsfVr167dBcf95ptvSEhIYO3atTRo0OC3nqaIXOWumTDSsWNHqqqqKCoq+tX7zvn5+aSnp/OPf/zjMlUncmU7duwY5eXldOnyv9DUqFEjwsPDbeu1mX3Mzs6u07fTxo8fz7Bhw+jZs+fvPAMRuZpdVWGkpKSEzz77zLaen59PdnY2jRo1IiwsjOHDhxMfH8+SJUvo2LEjp06dYufOnURFRdG3b19bv9WrVxMQEMCf//xnM05D/mCsTlYyh2WaNvalUpvZR6u1buPt2rWLf/zjHzz77LPAj7e0qqurcXJy4q9//Stjxoy5NMWLyBXtqgojH3zwAbfccottfcaMGQCMGjWKl19+mdTUVJ588klmzpzJV199RePGjenatSv9+vWz9amurubll18mISGhxh+oIvXBYrHU6laJmVq2bImzszOZmZk0b94cgOLiYj755BOio6OB2s0+RkVFsXPnTh577LFajXvgwAG750m2bt3K4sWL2b9/P02bNv2dZyUiV4urKozExMRgGMYF9zs7O/PYY49d9A9CBwcHvvzyy/ooT+Sq5enpydixY0lMTMTX1xc/Pz/mzZuHg8P/vnBXm9nHOXPmEBkZyeTJk5k0aRIuLi6kp6czePBgGjduXGPcNm3a2K1/8MEHODg4cP3119f7OYvIleOa+WqviPw+zzzzDDfffDP9+/end+/e/OlPf6JTp052bVJTU4mPj2fmzJmEh4dz11138f7779tmU8LCwti2bRsfffQRnTt3plu3bmzduhUnp6vq3z0icplZjItNNYhInZ09e5b8/HxCQ0Nxc3Mzuxy5xujzJdeiq+KfK9XV1Zw4cQIvL69a/2aCiFnKy8uprq6mqqrqor+vIfJbVFVVUV1dTUlJCeXl5WaXI3JRhmFw+vRpAgMD7W77/tJVEUZOnDhBUFCQ2WWI1EpwcDAvvvgiZWXm/NCZXPv++9//0rdvX7744guzSxGplS+//NLud4t+6aoII15eXsCPJ6MfRpIrXXl5OV9//TUhISGaRpdL7uzZsxw/fpwPPvgAFxcXs8sRuagffviBoKAg29/jF3JVhJGfbs00aNBAYUSueGfPnuXUqVM4Ojrq6+NyyTk6OuLg4ICnp6fCrlw1fu0RC32bRkREREylMCIiIiKmUhgRERERUymMiIiIiKkURkRERMRUCiMickExMTFMnz7d7DLsZGRkYLFY+O6778wuRUQuEYUREbkifPbZZ3h5eeHt7W12KSJymSmMiIjpKioqGDp0KDfffLPZpYiICRRGRASA0tJS4uPj8fT0JCAggCVLltRoc+7cOWbNmkXTpk3x8PCgS5cuZGRk2LXZt28fMTExuLu74+PjQ2xsLMXFxRcd++GHHyYiIoJ77rnnN9X+xhtv0K5dO1xdXQkJCalRe0pKCq1bt8bNzY0mTZowaNAg276NGzcSGRmJ1WrF19eX3r17U1pa+pvqEJHf5qr4BVaRq5lhGBgmvafGYrXW+uWSiYmJ7N69m61bt+Ln58fcuXM5dOgQHTp0sLWZMmUKubm5rF+/nsDAQDZv3kxcXBw5OTm0bt2a7OxsevXqxZgxY1ixYgVOTk6kp6df9IWBu3bt4vXXXyc7O5tNmzbV+RyzsrK45557WLBgAffeey/79+9n8uTJ+Pr6kpCQwAcffMDUqVNZs2YN3bt359tvv2XPnj0AFBYWMnToUJKSkhgwYACnT59mz5496GXmIpeXwohIPTPKysi7oZMpY4cfysLi7v6r7UpKSli1ahVr166lV69eAKSlpdm92KqgoIDU1FQKCgoIDAyE/4+98w6Pqsr//+ve6S29dwIkQEgA6SBNqgUr2BcR1EWsaxcUwbYryi5+9efuuq5t1dUVsDeQXkOTmkAgEEJCQkL69HZ/f0wyZKhBEpLAfT3PPGHuvXPOuZeTOe982gGeeOIJfv75Zz744ANeffVV5s6dS58+fXjnnXf8n8vIyDhtvxUVFUyePJlPPvnkd2/18Ne//pWRI0fy/PPPA5CWlkZOTg6vv/46kydPprCwEIPBwDXXXIPJZCI5OZlevXoBPjHidru58cYbSU5OBiAzM/N3jUNGRub3I7tpZGRkyM/Px+l00r9/f/+xsLAw0tPT/e937tyJx+MhLS0No9Hof61cuZL8/HwAv2Wkqdx7773cfvvtDB069HePPTc3l8GDBwccGzx4MPv27cPj8TB69GiSk5NJTU3lD3/4A59++ilWqxWAHj16MHLkSDIzM5k4cSL/+te/zupSkpGRaX4uacvI//b+j4M1B7m9y+0kBiW29nBkLlIEnY70rVtare/mwmw2o1Ao2LJly0kbABqNRgB059jfsmXL+Pbbb3njjTcAn0vL6/WiVCp59913mTJlynmP22QysXXrVlasWMHixYuZNWsWs2fPZtOmTYSEhLBkyRLWrVvH4sWLeeutt5g5cybZ2dl06NDhvPuWkZFpGpesGPF4Pby/632KzcV8mvspwxKGcXvX2xkQO6DJPnYZmaYgCEKTXCWtSceOHVGpVGRnZ5OUlARAVVUVeXl5DBs2DIBevXrh8XgoKys7bdZLVlYWS5cuZc6cOU3qd/369QHxJN988w2vvfYa69atIz4+vkltdO3albVr1wYcW7t2LWlpaX7RpFQqGTVqFKNGjeKFF14gJCSEZcuWceONNyIIAoMHD2bw4MHMmjWL5ORkvvrqKx577LEm9S8jI3P+XLJiRBAEnhvwHJ/mfsqa4jWsKFrBiqIVdAzuyO1db+ea1GvQq9r2AiIj01wYjUamTp3Kk08+SXh4OFFRUcycORNRPO7JTUtL44477mDSpEnMmzePXr16UV5eztKlS8nKyuLqq6/m2WefJTMzk+nTpzNt2jTUajXLly9n4sSJREREnNRv165dA95v3rwZURTp3r17k8f++OOP07dvX1566SVuueUW1q9fz9tvv+2PW/n+++85cOAAQ4cOJTQ0lB9//BGv10t6ejrZ2dksXbqUMWPGEBUVRXZ2NuXl5SeNS0ZGpoWR2gE1NTUSINXU1LRI+weqD0ivbHhF6vdJP6n7h92l7h92lwZ+NlB6Y9MbUlFdUYv0KXPxYrPZpJycHMlms7X2UM6Juro66c4775T0er0UHR0tzZ07Vxo2bJj0yCOP+K9xOp3SrFmzpJSUFEmlUkmxsbHSDTfcIO3YscN/zYoVK6RBgwZJGo1GCgkJkcaOHStVVVU1aQwffPCBFBwcfMZrli9fLgEBbS5YsEDq1q2bpFKppKSkJOn111/3n1u9erU0bNgwKTQ0VNLpdFJWVpb0xRdfSJIkSTk5OdLYsWOlyMhISaPRSGlpadJbb73VpLG2Fu11fslcmjR1/RYkqe3nsNXW1hIcHExNTc3vjrhvCnXOOr7Z/w2f7fmMw3WHARAFkeEJw7mj6x30jekru3BkzordbufgwYN06NABrVbb2sORuciQ55dMe6Kp67ecTdMIk9rEnd3u5PsbvuftK95mYOxAvJKXZYeXMXXxVG767iYW5i3E5m6dmhEyMjIyMjIXI7IYOQWiIDIscRjvjnmXr6/7mlvSb0Gn1LGvah+z189m9ILR/G3L3ygxl7T2UGVkZGRkZNo9spumidQ4avh6/9f8d89/KTYXA6AQFFyRdAV3dL2Dy6Iuk104MoBsRpdpWeT5JdOekN00zUywJpi7Mu7ihxt+4M0Rb9I/pj8eycOSQ0uY/PNkbv7+Zr7a9xUOj6O1hyojIyMjI9OuuKTFiNNmPec9KBSizxry3tj3WHTtIm7qfBNahZY9lXuYtW4Wo78czf9t/T9KLaUtNGoZGRkZGZmLi0vaTfPz3+dTuGs7aQMup8vAIUR37Py7XC3V9moW7V/E53s+p8TiiyNRCApGJ4/mjq530COyh+zCuYSQzegyLYk8v2TaE01dvy9ZMSJ5vbx7/92Yqyv8x4Iio0kfeDnpA4cQ1aHjOQsIt9fNisMr+DT3UzYf3ew/3i28G3d0vYNxKeNQK9TNMn6Ztou8WMi0JPL8kmlPyGKkCZT8cyuHdm2lyLOf4po83G6n/1xITCzpA4eQNuByIpM7nLMw2VO5h89yP+OHAz/g9PraDdOGcXP6zdycdjOR+shmuw+ZtoW8WMi0JPL8kmlPyGLkLEheiapF+7BtL0dyeXF7XZQ4DnBEcYCisj24XceFSWhcgs9iMuByIpJSzqmfKnsVC/ct5L97/kuZtQwApaBkTMoY7uh6B1mRWc1yPzJtB3mxkGlJ5Pkl056QxUgT8drcWLeVYckuxVVqAcDldXJUdZhi734OF+7G43b5rw9PSCJtgM+VE57Q9J1+XV4XSwuX8lnuZ/xW9pv/eFZEFrd3vZ0xyWNQKVTNd2MyrcbFtFgMHz6cnj17Mn/+/NYeip8VK1YwYsQIqqqqCAkJae3hXHAupvklc/HT1PX7kt0orwFRp8Q4MA7DgFich+uwbCzFtr2cBFdHEujIZUkjOBZ2lMOWPRTu20FFUSHrF3zG+gWfEZGUQvqAy0kbOISwuDPvMKoSVYxLGce4lHHsrtjNZ7mf8dPBn9hxbAc7Vu/gjc1vcHP6zUxMm0iE7uQNxWRkLnb2799Pr169UCgUVFdXt/Zwmp2UlBQeffRRHn300dYeioxMm+OSFyMNCIKAJikITVIQ3mtS/dYSSiC2IpFYEumTNYbysFIOle3k0O7tHCss4FhhAWv/9wmRKamk11tMQmJiz9hXRngGr1z+Co/1fowv877kf3v/R7mtnHe2vcO/dvyLKztcye1dbycjPOMC3b2MTOvicrm47bbbGDJkCOvWrWvt4TQZSZLweDwolfJXqYzM+XBJ1xk5HaJWiXFAHFEP9yLqgZ4Y+sYgqEXEKono/Gj6WUdzy7hZXHHTvaT0uAxRoaC84ABrPv+Yfz9yL588+ygbv1lATdmZa42E68KZ1mMav9z0C68NeY2syCxcXhff5n/Lrd/fyh9+/AM/H/wZl9d1xnZkZJoDi8XCpEmTMBqNxMbGMm/evJOucTgcPPHEE8THx2MwGOjfvz8rVqwIuGbt2rUMHz4cvV5PaGgoY8eOpaqq6ox9P/fcc3Tp0oWbb775d4194cKFZGRkoNFoSElJOWns77zzDp07d0ar1RIdHc2ECRP85xYsWEBmZiY6nY7w8HBGjRqFxWI5ZT8rVqxAEAR++uknevfujUajYc2aNeTn53PdddcRHR2N0Wikb9++/Prrr/7PDR8+nEOHDvGnP/0JQRACAuLXrFnDkCFD0Ol0JCYm8vDDD5+2fxmZixVZzp8BQRBQJ5pQJ5oIvroD1u3lWDaW4io2482xEEkYsRHXMnTy7RzxHGDf1vUU7trO0QP7OXpgP6s/+5CYTmn1rpzLCYqIOmU/KoWKq1Kv4qrUq9hZvpPP9nzGzwU/s618G9vKtxGlj+LW9Fu5Ke0mwrRhF/gpyJwvkiThdnpbpW+lWmxyJtiTTz7JypUr+eabb4iKimLGjBls3bqVnj17+q958MEHycnJ4fPPPycuLo6vvvqKcePGsXPnTjp37sy2bdsYOXIkU6ZM4c0330SpVLJ8+XI8Hs9p+122bBlffvkl27ZtY9GiRed8j1u2bOHmm29m9uzZ3HLLLaxbt47p06cTHh7O5MmT2bx5Mw8//DD/+c9/GDRoEJWVlaxevRqAkpISbrvtNubOncsNN9xAXV0dq1evPmsxxGeeeYY33niD1NRUQkNDOXz4MFdddRWvvPIKGo2Gjz/+mPHjx7N3716SkpJYtGgRPXr04L777uPee+/1t5Ofn8+4ceN4+eWXef/99ykvL+fBBx/kwQcf5IMPPjjnZyEj01655ANYfw/OIl9siXVbOZKz/ktWIaDrHoHYTU9h2S7yNqzh8O5dSNLxRSg2rQvpA4aQNnAwprAzx4WUW8v5Mu9Lvtj7BZX2SgDUopqrUq/ijq530CWsS4vdn8z5cWKAocvh4d1HVrbKWO57cxgqjeKs15nNZsLDw/nkk0+YOHEiAJWVlSQkJHDfffcxf/58CgsLSU1NpbCwkLi4OP9nR40aRb9+/Xj11Ve5/fbbKSwsZM2aNU0aX0VFBb169eKTTz5h6NChfPjhhzz66KNnjBk5MYD1jjvuoLy8nMWLF/uveeqpp/jhhx/YvXs3ixYt4u6776aoqAiTyRTQ1tatW+nduzcFBQUkJyefdbwNfX/99ddcd911Z7y2e/fuTJs2jQcffBA4dczIPffcg0Kh4J///Kf/2Jo1axg2bBgWi+WUAapyAKtMe0IOYG0CrqNlmJcvI/TWW8/pc+oEE+qEE6wlRWZs28thO0RHRJE6dDrSFBUHdm1m74bVFOXupiRvDyV5e1jx8b+I79KNtAFDSBswGGPoydaOSH0k03tO557Me/il4Bc+yf2EnIocvt7/NV/v/5qsiCxuSruJcSnj0Kv0zfVIZC5R8vPzcTqd9O/f338sLCyM9PR0//udO3fi8XhIS0sL+KzD4SA8PByAbdu2+cVMU7j33nu5/fbbGTp06O8ee25u7knCYPDgwcyfPx+Px8Po0aNJTk4mNTWVcePGMW7cOG644Qb0ej09evRg5MiRZGZmMnbsWMaMGcOECRMIDQ09Y599+vQJeG82m5k9ezY//PADJSUluN1ubDYbhYWFZ2xn+/bt7Nixg08//dR/TJIkvF4vBw8epGvXruf4NGRk2ieXrBjxWiwU3nUXzoIC3JWVRE6ffs5tiBolxn6xGPvF4iw2Y9lYgnVbOe5jNmp+OggKgcSMVLrcMQhXiId9m9aTt2E1xXty/K/lH71LQtcM0gcMoXP/QRhCAr8E1Qo14zuO55rUa9hevp1Pcz/l10O/+rJwju1g7qa5XNXhKiakTaBbeLfmejwyzYhSLXLfm8Nare/mwmw2o1Ao2LJlCwpFoLXFaDQCoNPpzqnNZcuW8e233/LGG28AxxdipVLJu+++y5QpU8573CaTia1bt7JixQoWL17MrFmzmD17Nps2bSIkJIQlS5awbt06Fi9ezFtvvcXMmTPJzs6mQ4cOp23TYDAEvH/iiSdYsmQJb7zxBp06dUKn0zFhwgScTudpWvBhNpv54x//yMMPP3zSuaSkpN93wzIy7ZBLVoyIBgPB119P+fz5HPu/t8DtIeKhB3/3HjLqeCPqGzoTfFUqth3lmDeW4jpch23HMWw7jqEI19Kpb096PDEWq7OWvA1r2bthNSV5eyjK2UVRzi6WffBPEjO6k1YvTPRBwf72BUGgZ1RPekb15JjtGN/mf8vCvIUU1hXyZd6XfJn3Jd3Cu3FT55u4qsNVGNXG5npUMueJIAhNcpW0Jh07dkSlUpGdne1fBKuqqsjLy2PYMJ+Q6tWrFx6Ph7KyMoYMGXLKdrKysli6dClz5sxpUr/r168PiCf55ptveO2111i3bh3x8WdOl2+ga9eurF27NuDY2rVrSUtL84smpVLJqFGjGDVqFC+88AIhISEsW7aMG2+8EUEQGDx4MIMHD2bWrFkkJyfz1Vdf8dhjjzWp/4b+Jk+ezA033AD4REZBQUHANWq1+qTYmcsuu4ycnBw6derU5L5kZC5GzkmM/PnPf2bRokXs2bMHnU7HoEGDeO211wJMuafiyy+/5Pnnn6egoIDOnTvz2muvcdVVV53XwJuDiGl/RFAqKHtjHsfeeQfJ6yHykUfOa1M7UaPA0DcGQ98YnEfMvtiS38rwVNip/bmA2sWH0GWEk9FvKJddeS11FeXkbVjD3g1rKN2fR+GuHRTu2sHS9/9OUvcepA8cQqe+A9CZjvvaInQRTOk+hckZk9lcupkFeQv4tfBXcipyyKnI4Y3Nb3BlhyuZ0HkC3SO6y5v0yZwVo9HI1KlTefLJJwkPDycqKoqZM2ciisctK2lpadxxxx1MmjSJefPm0atXL8rLy1m6dClZWVlcffXVPPvss2RmZjJ9+nSmTZuGWq1m+fLlTJw4kYiIk+OkTnRDbN68GVEU6d69e5PH/vjjj9O3b19eeuklbrnlFtavX8/bb7/NO++8A8D333/PgQMHGDp0KKGhofz44494vV7S09PJzs5m6dKljBkzhqioKLKzsykvLz9n90jnzp1ZtGgR48ePRxAEnn/+ebzewKDllJQUVq1axa233opGoyEiIoKnn36aAQMG8OCDD3LPPfdgMBjIyclhyZIlvP322+c0BhmZdo10DowdO1b64IMPpF27dknbtm2TrrrqKikpKUkym82n/czatWslhUIhzZ07V8rJyZGee+45SaVSSTt37mxyvzU1NRIg1dTUnMtwm8yx9z+QctK7SDnpXaSjb7wheb3eZm3f43BL5k0l0tH/95t0+OlV/teR1zZKNcsKJXetQ5IkSao+WiJlf/2l9J9nHpHeuPlq/+uvt10rLXh1lrRz+RLJVld3yj4qbZXSh7s+lK5ZdI3U/cPu/teN39wofZb7mVTjaJlnJ3MyNptNysnJkWw2W2sP5Zyoq6uT7rzzTkmv10vR0dHS3LlzpWHDhkmPPPKI/xqn0ynNmjVLSklJkVQqlRQbGyvdcMMN0o4dO/zXrFixQho0aJCk0WikkJAQaezYsVJVVVWTxvDBBx9IwcHBZ7xm+fLlEhDQ5oIFC6Ru3bpJKpVKSkpKkl5//XX/udWrV0vDhg2TQkNDJZ1OJ2VlZUlffPGFJEmSlJOTI40dO1aKjIyUNBqNlJaWJr311lvn1LckSdLBgwelESNGSDqdTkpMTJTefvvtk57d+vXrpaysLEmj0UiNv3o3btwojR49WjIajZLBYJCysrKkV1555bRjaK/zS+bSpKnr93ll05SXlxMVFcXKlStPG4B2yy23YLFY+P777/3HBgwYQM+ePfnHP/7RpH4uRDZN5cf/4eirrwIQNnkyUU8/1SIWBWeJxRdb8lsZkr3eZCsK6LqGYegfi6ZTCIIoUFV6hLz1PotJecEB/+dFhZKUHr1IG3A5HXv3R2sMdMdIksTWsq0syFvA4oLF/k36tAotY1LGMCFtAj0je8rWkhZEznaQaUnk+SXTnrgge9Ps37+fzp07s3PnztOaVZOSknjssccC0tleeOEFvv76a7Zv337KzzgcDhwOh/99bW0tiYmJLZ7aW/nppxx96WUAQv/wB6JnPNtii7bX6cG28xiWjaU4D9X6jytCNT43T59oFEEa37iOFPmFybHCAv+1okJBUmZP0gYMplOfQFcOQI2jhu8PfM+CvAXsr97vP94xuCMT0iYwvuN4gjXByDQv8mIh05LI80umPdHiYsTr9XLttddSXV19xpoCarWajz76iNtuu81/7J133mHOnDkcPXr0lJ+ZPXv2KQPgLkSdkaov/kfpCy8AEHr7bUQ/9xyC2LKFal2lFiwbS7FsLUOyu30HRdB2CcfQPwZt51AE0SeKKooK2bt+Dfuy13Ls8CF/G4IoktS9B2n9B9Op7wD0wSH+c5Iksb18Owv3LeTngz9j99gBX92S0SmjuanzTfSJ7iNbS5oJebGQaUnk+SXTnmhxMXL//ffz008/sWbNGhISEk573e8RI61lGWmgeuFCSp57HiSJkFtuIeaFWS0uSAAklwdrg7WkoJG1JKSRtSRY4z9eUXyYfdnryMteG+DKEQSRhG7dSRtwOZ37DQxIF65z1vHDgR9YkLeAvVV7/cdTglK4qfNNXNvpWrnK63kiLxYyLYk8v2TaEy0qRh588EG++eYbVq1adcZcfPh9bpoTaY0KrNVffU3JjBkgSQRPuInYF1+8IIKkAdfRRtYSW721RABtF19siTbtuLUEoKr0iE+YbFjL0QP7jjckCCR0yaBz/8F07j/QX/lVkiR2V+xmQd4Cfjz4Iza3DQClqGRk0kgmpE2gX0w/REHevuhckRcLmZZEnl8y7YkWESOSJPHQQw/x1VdfsWLFCjp37nzWz9xyyy1YrVa+++47/7FBgwaRlZXVpgJYT0XNt99y5Jlnwesl+PrriX3lZQTFha0XIbm82HYdw7yxBOfBRtaSMC3GgXEY+kQj6gIztGvKSsnLXse+DWsp2b834FxcejfS+g+mc/9BBEVEAmBxWfjp4E8syFvA7ord/msTTYnc2PlGru90PRG6M5evlzmOvFjItCTy/JJpT7SIGJk+fTqfffYZ33zzTUBtkeDgYH/lxUmTJhEfH8+f//xnANatW8ewYcP4y1/+wtVXX83nn3/Oq6++ytatW5tcS6A196ap+eEHjjz1NHg8BI0fT9yfX0Vope3CXWVWn7Vky1G/tURQi+gvi8Y4KA5V1Mll4WuPlbEvez152Ws5sjcn4Fxsp3Q6DxhMWv9BBEfFAJBbkcvCfQv5/sD3WFy+nUOVgpLhicOZkDaBgXEDZWvJWZAXC5mWRJ5fMu2JFhEjpwtw/OCDD5g8eTLg2yo7JSWFDz/80H/+yy+/5LnnnvMXPZs7d+45FT1r7Y3yan/+heInngC3m6CrriJu7mutJkjAl4lj3VaGee0R3Eet/uOaziEYB8ah7RIW4MJpoK7yGPuy17Mvey1Fe3ZDo//66NTOpA3wWUxCY+Kwuqz8UvALC/YtYEf5Dv91cYY4v7Uk2hDdsjfaTpEXC5mWRJ5fMu2JC5Lae6FoKTGSZ7FjUorEatRnH8OSJRT/6TFwuzGNG0f863MRVKpmG8vvQZIkHAdqMK87gj2nAur/J8/kwmnAUl3Fvo3ryduwhqKcwN2FI1NSSes/mLQBlxMWF09eVR4L8xby3YHvqHPWASAKIkMThjKh8wQuj78chdi2y51fSOTFQqYlkeeXTHtCFiNN4A87DrCkopauBi1XhAdxRZiJfsFGVKewKgDULVtG0SOPgsuFafQo4ufNQ1CfXchcCNyVdswbSrBsKm2yC6cBa001+zdtIC97LYW7tiM1KmMdkZRSL0wGY4iJYsmhJSzIW8DWsq3+a6L10dzY+UZu6HQDscbYlrvJdoK8WMi0JPL8kmlPyGLkLEiSxM3b81lTZabxAzAqRIaGmvziJE4bKDbqVqyg+KGHkVwujCNGEP/mfMQ2Ikjg97twGrDV1bJ/8wbyNqylcOc2vI029gqLTyRtgM9iUmvysHD/Qr7L/45qRzUAAgKXx1/OTWk3MTRhKCqxdS1HrcXFtFgMHz6cnj17Mn/+/NYeikw9F9P8krn4kcVIE6lwullZVceyilqWV9ZR4XIHnO9i0HJFWBBXhJvoF2xALYqYV6+m6IEHkZxODMOGkvB//4eo0Zymh9bhfFw4DdjNZvK3ZJO3YQ2HdvyGx3382YTGxpM2YDApffuynQMs2r+IjaUb/ecjdZFc3+l6bux8Iwmm09ehuRi5mBaLlhYjBQUFpywPsH79egYMGNAifbZ3Lqb5JXPxI4uR34FXktheZ6sXJrVsrbXSeN9Ng0JkSKiRK8KCGFiwD8/0+5EcDgxDhpDw1v8httEvhvNx4TTgsFo4sGUjezespWD7Fjwul/9ccHQMaf0HY8rsyDLnJr7N/5ZKe6X//MDYgUxIm8DwxOGoFW3HitRSXEyLxYUSI7/++isZGRn+4+Hh4ahaOSarrXIxzS+Zix9ZjDQDlS43qyrrWFpZy/KKOo6dYDXpLHjptWwx/bZvZkBkKKlv/R9ifYpzW+SMLpxBcWjTz+zCacBps3Jg6ybystdy8LctuJ3Hq+UGRUbRsd9AapLV/GRfw/rSDf5zwZpgxqWM49qO15IZkXnRlp9vr4uFxWLh/vvvZ9GiRZhMJp544gm+++67ADHicDiYOXMm//3vf6murqZ79+689tprDB8+3N/O2rVrmTlzJhs3bkSj0dCvXz8+//xzQkNDT+qzQYz89ttv9OzZ88LcaDunvc4vmUsTWYw0M15JYqfZZzVZVlHHllpLgNVEa7fTt6yYq4cOZGRsBInatmsB8Ltw1h7Bnvv7XDgNuOx2Dm7bTN6GtRzYugmXw+4/ZwyPILZXJgeizXxnW0WZvcx/LiUohfEdx3NN6jXEGeOa9f5amxMXC0mScDfa3uBCotRomiz6pk+fzg8//MD7779PVFQUM2bMYOXKlUyZMsUvRu69915ycnL4y1/+QlxcHF999RXPPfccO3fupHPnzmzbto0BAwYwZcoU/vjHP6JUKlm+fDm33norEREnF85rECOJiYnY7XbS0tJ46qmnuPbaa5vzMVxUyGJEpj0hi5EWpsrlZmVlHcsqa1l2tJJjUuAXfme9pj7WJIgBIQY0F7CU/Lngd+FsLPVv0neuLpwGXA47Bdu31guTjThtNv85Q0goxowO7I2o5Bd3NjbpuGjpG9OX8anjGZ08GqPa2Hw310qcuFi47Hb+764JrTKWhz9agKoJC5bZbCY8PJxPPvmEiRMnAlBZWUlCQgL33Xcf8+fPp7CwkNTUVAoLC4mLOy4gR40aRb9+/Xj11Ve5/fbbKSwsPOPmmY05duwYH3/8MYMHD0YURRYuXMjcuXP5+uuvZUFyGmQxItOeaOr63XqVu9o5oSol10eHcn10KN4uSWzZvI1vvvya7M5dyUlNY5/VwT5rOf8sKkcnilweavRn6CTr2k6wqzJMS8hVHQgalYT1tzLM63wuHMuGEiwbSs7JhaPSaOncbxCd+w3C7XRyaOdv5K1fQ/6WjViqq7CsrSIEmGRIRZ0Wx+6wMlYqd7KpdBObSjfxavarXJF0Bdd2vJYBsQPk2iUXkPz8fJxOJ/379/cfCwsLC6i0vHPnTjweD2lpaQGfdTgchIeHA7Bt2za/mGkKERERPPbYY/73ffv25ciRI7z++uuyGJGRuYSQxUgzIAoCffv2ortGQeHUe6jxeNk57hp23PoHVtTZOOp0s6SiliUVvr1lOvmtJiYGBBvRKlrfaiKqFRj7x2LoFxPgwnHsq8axrxpFuBbjgKa7cJRqNR1796dj7/64XS4Kd21j/8b17N+cja22Bsdv+0gCJqs7IaSGsyOkhN9Mhfx48Ed+PPgjkbpIrk69mms7Xkvn0LPvgdSWUWo0PPzRglbru7kwm80oFAq2bNmC4oQ9moxGn0VL1wwxU/3792fJkiXn3Y6MjEz7QXbTNDO2XbspnDoVb00N2qwsEv/1LntEFcsqfenDm2oteBo9cZ0oMjjUyBVhvtomKW3IatKcLpwGvF4PR/bksm/TevZtXEfdsXL/OUGhwJ1oYkfIEfaGV2DX+KJyuoZ1ZXzH8VzZ4cp2sWFfezSjm81mwsLC+PTTT/2WjaqqKhISErj33nuZP38+eXl5pKens2rVKoYMGXLKdu6++2727dvXZDfNqbj33nvZsmULW7duPfvFlyDtcX7JXLrIMSOtiD0nh8K7p+CpqUGbkUHSv99DERICQK3bw6qGWJOKOkqdroDPpuo0XBFu8qUPhxjRtQGridfpCXDhNHCuWTgnIkkSZQfz2bfRJ0wqiw8fPymAI1rLzrBSCqLMmPUeFIKCwfGDGd9xPCMSR6BRtB3h1pj2uljcf//9/PTTT/4A1pkzZ7Js2TKmTp3qD2C98847Wbt2LfPmzaNXr16Ul5ezdOlSsrKyuPrqq8nLyyMzM5OpU6cybdo01Go1y5cvZ+LEiacMYP3oo49Qq9X06tULgEWLFvH888/z3nvvcffdd1/I2283tNf5JXNpIouRVsa+Z49PkFRVoenalaT3/43yhNRGSZLItdhZWlHLsspaNtVYcAdYTQQGhvhiTUaGBdFB37qL72mzcM7RhXM6KooP+1w5m9ZTmr8v4Jw1TGRPRCWF0VaqjS5MahNjUsZwbcdr6RXVq02lCbfXxcJsNgek9j7++OP88MMPAam9LpeLl19+mY8//pji4mIiIiIYMGAAc+bMITMzE4CVK1cyY8YMtmzZgk6no3///nz++eeE1Avyxnz00Ue89tprHDp0CKVSSZcuXXjyySeZMKF1An7bA+11fslcmshipA1gz8vzCZKKCjTp6SR98D7KsLDTXl/r9rC6vhrssso6ShyBVpMOOrU/Q2dgiBF9K1pNfC6cI1g2Hm02F05jao+Vs3/TBvZvXEdR7u6AjfwsRi8Houo4FGPlWLCTBFMC4zuOZ3zqeBKDEs+r3+ZAXixkWhJ5fsm0J2Qx0kZw5OdzaPJkPOXH0HTuRNIHH6A8hbn6RCRJYk+91WR5ZR3ZNeYAq4m2wWoSFsSIcBMddU2vJ9GctJQLpzHW2hryt2Szf+P6k8rSW7UeDkVbOBRt42iYnZ4xvRjfcTxjU8YSpG6duSIvFjItiTy/ZNoTshhpQzgOHKTwrrtwl5ej7tiRpA/eRxUVdU5tmBusJvWBsMUnWE2StGpGhJkYGR7E4BAjBuWFTYuVJAlHfv1eOC3gwmnAYbVycNtm9m9cz4HfNuOyH69lYld5OBxl81lMojwM6zCCaztey8C4gRd00z55sZBpSeT5JdOekMVIG8NZUMChuybjPnoUdUoKSR99iCo6+ne1JUkSeVZHvTunluxqC85G/41qQaB/iMFvNUnXay+o1eS0Lpze0ZgGx6OMaJ6S+W6nk8Jd29m3cR35m7Ox1dX6z7kUXooibRTGWLEkahmTdhXXdryWLmFdWvxZyIuFTEsizy+Z9oQsRtogzsJCDk2ejPtICarkJJI/+ghVTMx5t2txe1hbbfZbTQrtzoDz8RoVI+rrmgwJNWG6QFaTU7pwBNB2Dcd0eRzqDsHNJgy8Hg/Fe3b7Uoaz12OuPOY/5xEljoTbKIyxoewczZUZ13F16tVE6c/NOtVU5MVCpiWR55dMe0IWI20UZ1ExhXfdhau4GFViIskffYgqrvn2ZpEkiXybg+UVvvThddVmHN7j/8VKAfoGG/yBsN0MLW81kSQJx/5qzGuKse+t8h9XxRkwDklAnxmBoGy+YFxJkjiav89fy6TqSLH/nBeJsjAHhTE2IrK6cGWPG7gi8Qr0qvMLuG2MvFjItCTy/JJpT8hipA3jKi7m0OS7cR0+jCo+nqSPPkKdEN8ifVk9XtZXm1lWHwh7wBa4YVuMWsWIcBMjwoIYFmokWNWyRXldZVbMa4uxbi1DcvkyZESTGuOgWAz9YlEYmj+2o6LoMPs2rmNv9hqOFRwMOHcsyEFJnJvkPn24pu/N9I7ujSicnzCSFwuZlkSeXzLtCVmMtHFcJSUcmjwZ16FClHGxJH/4IeqkpBbvt8Dm8KcOr62qw9bIaqIQoHeQwV8NtrtRh9hCVhOPxYVlYwnmdSV463xuJUElor8sCuPl8agim89S0Zja8jL2b1rPzvXLOZa3P+BctcFFZaJI536DuHbwHaSGpP6uPuTFQqYlkeeXTHtCFiPtANfRoxTeNRlnQQHKmBiSP/wAdUrKBevf7vGSXWPxB8LuswZaTSLVSoaH+arBDgszEdYCVhPJ7cW6oxzzmmJcRyz+49r0UIyXx6PpFNJibiRrTTX7N29gy5pfqNizH6GRMDNr3VhT9KT3G8zVQ24nOii2ye3Ki4VMSyLPL5n2hCxG2gmusjIK756CMz8fZVQUSR9+iCa1Q6uMpdDmYEV9qfrVVWYsnuOFxgSgV5Dev8FfD5MeRTOKBEmScB6soW51MfY9lf7UYFWMHuPl8eh7RCGoWq7Im8NqYe/m9WSv+p7q3HzERkVdHEovtmQ9HXv348or7iQ69MwxPvJiIdOSyPNLpj0hi5F2hPvYMQrvvhvHvv0oIiNI/vBDNB07tuqYnF4vG2ssLKuoY3llLbkWe8D5MJWC4WFBjAgzMTzMRKS6+WI9XMdsvriSLUeRnPVxJUYVxgGxGAbEojCqm62vU/bvdLBr8yrWrfyWutwCVI7jvyIeQcIepyX5st6MHnUbcTEnC8eLabEYPnx4QDn4tsCKFSsYMWIEVVVVpywxf7FzMc0vmYsfWYy0M9yVlRROvhtHXh6K8HCSP/wATefOrT0sP0fsTpbXW01WVdZR18hqAtDDpPNn6PQy6VGeZ9VVAK/VhWVTKeZ1R/DU1KcrKwX0PaMwXR6PKsZw3n2cdQxeDzu2r2HNyq+p3rUfXV3gr4sjQk18zx6MGDGRxI5dEQTholosWlqMFBQU0KHDyYJu/fr1DBgw4JSfkcXIxTO/ZC5+ZDHSDnFXVVE4ZSqO3FwUoaEkffgB2vT01h7WSbi8EltqLf4MnZ1mW8D5EKWCoWEmrgjzZelEa87PaiJ5vNh2HaNudTGuIrP/uKZzCKbL49GkhV6wom4792azfPmXHNu5h6BjEgLH+3UblURnZTBg6HV4NUZSU1Pb/WJxocTIr7/+SkZGhv94eHg4KtWp540sRmQxItN+aOr63fr708v4UYaGkvzB+2i7dcNTVUXhpLuw5+S09rBOQiUKDAgxMqNjHEv6prN9UAbzuyRyXVQIIUoF1W4P35ZV8+iew/RYt5tRm/bySv4R1lebcXnPXfsKChF9jyiiHuhJ5LQsdN3DQQDHvmqOfbCbo3/bgjm7BMnlaYG7DSQzvT8PT3uDOW9/x9i5L6K4MoPyeAm36EVpdlOxbjvL332H2opyqspKsNXV4vW0/LiaA4vFwqRJkzAajcTGxjJv3ryTrnE4HDzxxBPEx8djMBjo378/K1asCLhm7dq1DB8+HL1eT2hoKGPHjqWqquqkthoTHh5OTEyM/3U6IXI6Fi5cSEZGBhqNhpSUlJPG/s4779C5c2e0Wi3R0dEBuwIvWLCAzMxMdDod4eHhjBo1CovFcmIXMjIyLUjLFpWQOWcUISEkffA+hffci33nTg7dPYWkf/8bXfeMs3+4lYjWqLg1NpxbY8NxeyW21Vn9G/xtr7Oyy2xjl9nGW4VlmBQiQ8NMjKwvVR+raXr8hyAIaFKC0aQE+0rOry3Gsvko7jIb1V/tp3ZxAYb+sRgHxqEwtWxciSAIZCb3JnNybyRJYmfpNpas/B+Ht20j2epBkMBtd1BTdhQJCYVCjd4QhEavR3GOC+15jVMlNtlq9OSTT7Jy5Uq++eYboqKimDFjBlu3bqVnz57+ax588EFycnL4/PPPiYuL46uvvmLcuHHs3LmTzp07s23bNkaOHMmUKVN48803USqVLF++HM9ZBNm1116L3W4nLS2Np556imuvvbbJ97hlyxZuvvlmZs+ezS233MK6deuYPn064eHhTJ48mc2bN/Pwww/zn//8h0GDBlFZWcnq1asBKCkp4bbbbmPu3LnccMMN1NXVsXr1atqBwVhG5qJCdtO0UTx1dRy+515s27cjmkwk/fs9dFlZrT2sc6bc6WJlpW+DvxWVtVSeYL3oatByRXgQV4SZ6BdsRHWOsSZeuxvLpqOY1xbjqa5PTVYI6HtEYrw8HnWcsblupWnjkbz8VvQbrjIHkRGhaCUFol3C82HZBR1HA3EvDkJUn738v9lsJjw8nE8++YSJEycCUFlZSUJCAvfddx/z58+nsLCQ1NRUCgsLiWtUNXjUqFH069ePV199ldtvv53CwkLWrFnTpPEdO3aMjz/+mMGDByOKIgsXLmTu3Ll8/fXXpxUkJ7pp7rjjDsrLy1m8eLH/mqeeeooffviB3bt3s2jRIu6++26KioowmUwBbW3dupXevXtTUFBAcnJyk8bc2shuGpn2RFPXb9ky0kZRmEwk/vs9Dt/3R2xbt1I4ZSqJ/3oXfa9erT20cyJSrWJCTBgTYsLwSBLb66wsqy9V/1utlVyLnVyLnf9XWIZRITI01MSIcF9tk3jt2a0bolaJaUg8xkFx2HKOYV5zBOehWqxby7BuLUOTGozx8ni0XcIQmiGo9qzjEUQyIjM4aD5IXFQKHoWHmprKFu/3fMnPz8fpdNK/f3//sbCwMNIbxSzt3LkTj8dDWlpawGcdDgfh4eEAbNu2zS9mmkJERASPPfaY/33fvn05cuQIr7/+epOtI7m5uVx33XUBxwYPHsz8+fPxeDyMHj2a5ORkUlNTGTduHOPGjeOGG25Ar9fTo0cPRo4cSWZmJmPHjmXMmDFMmDCB0NDQJt+DjIzM+SOLkTaMwmgk6V/vcviP07Bu3szhqff4BEnv3q09tN+FQhC4LMjAZUEGnugQQ4XTzcqqOn8gbIXLzY/HavjxWA0A6QYtV4SZGBkeRL9gA2rx9CFOgkJAnxmJPjMSR2Et5jXF2HYdw3GgBseBGpQROoyD49D3jm6SpaA5EAQBo9qIIcKAZ04sVpeFWnstDqsVlQuUbgGhkV1SEAU0egManQG1Xo+oOP9xNmdtFrPZjEKhYMuWLShOGJvR6LNA6XTnvyNz//79WbJkyXm304DJZGLr1q2sWLGCxYsXM2vWLGbPns2mTZsICQlhyZIlrFu3jsWLF/PWW28xc+ZMsrOzT5nlIyMj0zLIAaxtHNFgIPHdf6Lv3x+v1Urhvfdh3bSptYfVLISrldwYHcrb3ZLZOTiDn3un8VSHGPoE6RGBvRY7fz9czoRt+XRds4vJOw/wUfExDp+wK/GJaJKCCL+9KzFP9cU4NAFBq8B9zEb1N/mU/HkjNT8dxF3jOGMbzYkgCCg1KoKMISREJNEhMY2QhDg8sXosIRIOg4SkEUAh4HBYqa0u51jJIaqPlWCz1eEVvIhqxe96NTVepGPHjqhUKrKzs/3HqqqqyMvL87/v1asXHo+HsrIyOnXqFPCKqd99Oisri6VLl57X89q2bRuxsU2veNu1a1fWrl0bcGzt2rWkpaX5RZNSqWTUqFHMnTuXHTt2UFBQwLJlywDf/8/gwYOZM2cOv/32G2q1mq+++uq87kFGRubckC0j7QBRryfxH3+n6IEHsKxbT+F9fyRh/t8wDhvW2kNrNkRBoGeQnp5Beh5LiaHK5WZlZR1LK2tZXlHHMZebn4/V8vOxWgA66zVcER7EyLAg+ocY0JzCaqIM0RJyVQeCRiZh3VxK3bojeCrs1K0som51MbqsCEyXx6NOMJ302Za9V5EgTRBBmiA8Rg9ml5kaRw12mwWVS0DtFlF4BJw2G06bjTrKUao1aA0GNHoDSo2m2VOZjUYjU6dO5cknnyQ8PJyoqChmzpyJ2Oi5pqWlcccddzBp0iTmzZtHr169KC8vZ+nSpWRlZXH11Vfz7LPPkpmZyfTp05k2bRpqtZrly5czceJEIiIiTur3o48+Qq1W06ve/bho0SLef/993nvvvSaP/fHHH6dv37689NJL3HLLLaxfv563336bd955B4Dvv/+eAwcOMHToUEJDQ/nxxx/xer2kp6eTnZ3N0qVLGTNmDFFRUWRnZ1NeXk7Xrl3P84nKyMicC7IYaSeIOh0J77xD0UMPY1m9msP3Tyf6mWcI/cOdF6zGxoUkVKXk+uhQro8OxStJ7DLb/Bv8ba6xsM/qYJ+1nH8eLkevELk8xMiI+kDYZJ0moC1Ro8A4OB7DwDjsuZXUrSnCebAW27ZybNvKUacEYbo8Hm238AsSV9IYhaggWBNMsCYYj9FDnbOOGmcNdXYLKreA2iWicou4nQ7MTgfmqkoUSqXPnWMwoNbqEM7gvjoXXn/9dcxmM+PHj8dkMvH4449TU1MTcM0HH3zAyy+/zOOPP05xcTEREREMGDCAa665BvAJlsWLFzNjxgz69euHTqejf//+3Hbbbaft96WXXuLQoUMolUq6dOnCF198EZB6ezYuu+wy/ve//zFr1ixeeuklYmNjefHFF5k8eTIAISEhLFq0iNmzZ2O32+ncuTP//e9/ycjIIDc3l1WrVjF//nxqa2tJTk5m3rx5XHnllef+AGVkZH43cjZNO0NyOimZM4eahYsACL39NqJnzEBQXjq6strVEGviK1Vf5nQHnO+k1/j30BkQbESrOHmxdhabMa8pxrq9HOprnyjCtBgHxWHoG42o+f3PszmyHdxeN7XOWmodtdic1gBhEhhnIqLR6dHUW02aI85Epm0jZ9PItCfkCqwXMZIkUfn++5S9MQ8kCcPgwcT/7a8oLsFnI0kSu802llX6AmE31VrwNJrROlFgUIiJK8J9gbApJ1hNPDUOzOtLsGwswWv1iRpBo8DQLwbjoDiUoef+Zd/ci4XL66LWUUutsxar67gwUbtFRG8jS44Aaq3OZzXRG1CoVBel1exSRxYjMu0JWYxcAtT9+ivFTz6FZLOh7tiRxH/8HXViYmsPq1WpcblZVWVmWX2sSanTFXA+VafhivrU4YEhRnT1VhOv04N1axnmNcW4j9WXtxdB1z0C4+XxaJKaPu9acrFweVzUOGt8MSZuO0qPL8ZE7fLFmTRGoVL5hYlap0UQ5Hj1iwFZjMi0J2Qxcolg272bovun4y4rQxEaSsL/exv9ZZe19rDaBJIkkWuxs7SilmWVtWyqseBuNNu1osDAECMjw4O4IiyIVL0GySthz6vCvKYYx/5q/7XqJBPGIfHoukUgKM5sbbhQi4XD46DWUUuNswaH24HoFVA3uHM8IpzCnaPW631Wk0vIrXexIYsRmfaELEYuIVxHj1J0/3TsOTkIKhWxr7xM8DmU075UqHN7WFVVx/L6omtHHIFWkxSd2r/z8KAQI8oymy+uZFsZDb4fRYjGFwzbNxpRe+oFvTUWC7vbTq2zlhpHDU6PE0ECldvnylG7RYTATZZRabRo9L5YE6W6+bNzZFoOWYzItCdkMXKJ4bVaOfL009Qt+RWA8PunEfnQQ82WaXGxIUkSeyx2f6zJxhoLrka/ChpRYGCwz2oyTKsl6rdjWDeUBsaV9K2PKwkLXBBac7GQJAmHx0Gds45aZy12tx0ApUdA5RbRupWI7sBfeVGpQKOrz87R6RBFOQi2LSOLEZn2hCxGLkEkr5fyv/2Nin/5ajSYrhxH3J//jCh/YZ0Vs9vD6qo6llfWsbSiluITrCbJWjVXhBoZXOklY8MxVGX1cSVCo7iSZN/cbEuLhdPj9GXlOGuxuXxjFiVQuUS0HiVKlwCNvgIEQUClawiC1aNUteyGgzLnTluaXzIyZ0MWI5cw1QsXUvLCbHC70WZlkfj/3kYZGdnaw2o3SJJEntVRX9eklg3VJ1hNBIH+ag0Dix30z60jyeo7p04yYbw8HqGjkYLCgja3WLg8Lr/FxOKy+I+r3AI6jwqVWwR3oD9HqVb7hYlKq5PdOW0AWYzItCdkMXKJY8neSPHDD+OpqUEZG0viP/6OttGmZzJNx+z2sKY+Q+dUVpNEj8DAIw4GlbnpU+lBHaOhboiO1PRO6PTnv1dLS+D2uqlz1lHnrMPsMtPwNaDwCmg9SrRuJbg8AUGwoij6A2DVej0KhRwE2xrIYkSmPSGLERmcBQUcnnY/zoICRL2euL/OwzR8eGsPq10jSRJ7rXbfzsMVtWSfGGvikRhT5+GeeCWdYhIJDjKgMKoRlG03dsfj9ZWkr3XWYnaa8Uo+64gggcajRO9VIzq9SJ5Aq4lKq/WnDivVatlqcoGQxYhMe0IWIzIAeKqrKXrkUazZ2SCKRD/zNKF/+IO8cDQTDbEmDYGwxQ4XCaLEq0EiUYlJqJVqjG4wiSImgwrleVR2vRB4JS9mp9lvNfnDtX+gS/cuPPPKM6i9CgxeDUoXeE+oettQol6tbwiCbTnxtWLFCkaMGEFVVRUhISEt1k9bRRYjMu2Jpq7fbffPNZlmQRESQtK/3iV4wk3g9XL01T9TOmcOkst19g/LnBWjUsGVkSG8np7I5oHdWNEvnfsTo9CKAgLgEgWq1AKFSokch5P8aitlZgeOE6wMbYWGTfziTfGkhaWhVWrRKDUoRSVO0UOV0kq5zkp1kBuPSYVC50sL9rjdWGtrqC49QnnBAapKjmCtqcZzlnlWUFCAIAgnvTZs2HCB7vjCkZKSwvz581t7GDIybZK2/WeaTLMgqNXEvvQSmtSOlL3+OtWff4Gr8DDx8/92SZaQbykEQaCLQUdKXDgHD9aSZNDiVqqodXmodXtwA2YRzF4PJRYPaiBIpcSkUmBUiIhtzFolCiIKQYFRZSQtNA2r2+oLgHXU4vK6qBYsoAZBLWBC54szcbjxuN04rBYcVgtQ3igI1oBKqz2lVe7XX38lIyPD/z48PPwC3unvR5IkPB4PSrmInIzMeSFbRi4RBEEgfMrdJLz9FoJOh2XdOgpuvQ1nYWFrD+2iRSEIBKuUJOo1dDPpSNNpiEZEX19AzQkcc7k5aHWwy2zjgNVBudOFw9s6VhOLxcKkSZMwGo3ExsYyb948/zlBEDCoDIQqQ/nnK/9kdI/R9E3uy+1jbyd7bTa1WClT1lJmsLI2bxs3TZpEavcsulzWhwm330nxoQIqjxRRfuggNUdLsZnr8Ho8/vbDw8OJiYnxv1Qq1TmNfeHChWRkZKDRaEhJSQkYO8A777xD586d0Wq1REdHB+wKvGDBAjIzM9HpdISHhzNq1CgsFsuJXQA+F5EgCPz000/07t0bjUbDmjVryM/P57rrriM6Ohqj0Ujfvn359ddf/Z8bPnw4hw4d4k9/+pPf+tPAmjVrGDJkCDqdjsTERB5++OHT9i8jc7Eii5FLDNPIkaR8+gnK6GicBw5QcPMtWLdsae1hXdRIkoTL5UIheQjTiiTplHRye4k2OzBYHOB04HI6qbLZKKyzsKuqll2VNRTUmqmw2rA7HDidzt/1OpeQsCeffJKVK1fyzTffsHjxYlasWMHWrVsDrnnwwQfZsGEDX3z+BTt37OQPt/2B+2+5H/MRM1qllj0793D7DXeSmJ7Mf376hC9++oKx14xDodEiKkS8Hg82cx01R0spO3SA6tISAK4dP56oqCguv/xyvv3223N6vlu2bOHmm2/m1ltvZefOncyePZvnn3+eDz/8EIDNmzfz8MMP8+KLL7J3715+/vlnhg4dCkBJSQm33XYbU6ZMITc3lxUrVnDjjTee9bk988wz/OUvfyE3N5esrCzMZjNXXXUVS5cu5bfffmPcuHGMHz+ewnqxv2jRIhISEnjxxRcpKSmhpMR33/n5+YwbN46bbrqJHTt28MUXX7BmzRoefPDBc3oGMjLtHTmA9RLFdbSMounTse/ejaBSEfPSi4Rcf31rD+ui4MQAQ6fTyauvvtoqY5kxYwZq9dkLl5nNZsLDw/nkk0+YOHEiAJWVlSQkJHDfffcxf/58CgsLSU1NpbCwkLi4OP9nR40aRb9+/Xj11Ve59bZbOXjoIJ//9DlWlzWgD41CQ5BgQO0WcNscuJ1OKior+fKrr+nXuzdKlZKffl3Km2//PxYtWsT1p5mPJwaw3nHHHZSXl7N48WL/NU899RQ//PADu3fvZtGiRdx9990UFRVhMpkC2tq6dSu9e/emoKCA5OTksz6nhr6//vprrrvuujNe2717d6ZNm+YXFikpKTz66KM8+uij/mvuueceFAoF//znP/3H1qxZw7Bhw7BYLKcMUJUDWGXaE01dv2VH5yWKKjqK5E/+w5GnnqZuyRJKnnkWZ0EBkQ8/LJeQvwTJz8/H6XTSv39//7GwsDDSG9Wm2blzJx6Ph7S0tIDPOhwOf4zHju07mDhxIh2CO5xUZM3hcVCOAwC1UY1JYSQhLIRHHnoQp82GJElkZWRQdPgwf37lZYb27VNf10R/xv1zcnNzTxIGgwcPZv78+Xg8HkaPHk1ycjKpqamMGzeOcePGccMNN6DX6+nRowcjR44kMzOTsWPHMmbMGCZMmEBoaOgZn1efPn0C3pvNZmbPns0PP/xASUkJbrcbm83mt4ycju3bt7Njxw4+/fRT/zFJkvB6vRw8eJCuXbue8fMyMhcLshi5hBF1OuLfnE/53+ZT8a9/UfGPf+IsOETcn19F1LXNYl3tEZVKxYwZM5p0reTx4rW68JhdUB864lSARa/AohCwSN7A3XgFMIgKgpQiRqUCzQlC8lxjL86E2WxGoVCwZcsWFIrA/WuMRiMAukbzRqVQEaYLI0wXdlKRNafHSYWn0nedRoXJaEQvaRCcXvr07s2qtetw2m047TbMlRWICoW/2FrjWJOmYDKZ2Lp1KytWrGDx4sXMmjWL2bNns2nTJkJCQliyZAnr1q1j8eLFvPXWW8ycOZPs7Gw6dOhw2jYNBkPA+yeeeIIlS5bwxhtv0KlTJ3Q6HRMmTMDpdJ71mf7xj3/k4YcfPulcUlLSOd2njEx7RhYjlziCKBL1+GOoO3Sg5IUXqPv5Zw4VF5Pw/95GFRXV2sO7KBAEoUmuEj86LVKohNfmxmt2onZ5Mfr2u0PSabDqFZiRqPV4cXsl7IDdC2VOLxpRwqRUEKRUYFCITa4n07FjR1QqFdnZ2f5FsKqqiry8PIYNGwZAr1698Hg8lJWVMWTIkFO2k5WVxdKlS5kzZ07AcaWoJFQbSqg29KQiay6vi0pHFZX4Mni27c8hJi4GY0QELpsNp83mizWpq8VWV+uPMzFXVaLXaunatStr164N6G/t2rWkpaX5RZNSqWTUqFGMGjWKF154gZCQEJYtW8aNN96IIAgMHjyYwYMHM2vWLJKTk/nqq6947LHHmvTsGvqbPHkyN9xwg29sZjMFBQUB16jVajwnCKnLLruMnJwcOnXq1OS+ZGQuRmQxIgNAyI03oE5MoOjBh7Dv3EnBLbeS+Pd30Hbp0tpDuyQRRAGFQYWoVyI5PHjMLiS7G8HmxmBzY1QriDOqcGpFaj1e6tweLF4vDq+Ew+nmmNONKIBRocCkFAlSKlCfwf1mNBqZOnUqTz75JOHh4URFRTFz5syA4mVpaWnccccdTJo0iXnz5tGrVy/Ky8tZunQpWVlZXH311Tz77LNkZmYyffp0pk2bhlqtZvny5UycOJGIiAgAFKKCYE0wwZpgPvjwAySFRKdunbC4LPz83c/87z//Y87f5nDIdQS9To8pKBidV4XX4cJhPR6HYqmuotLr4e7bbmHsdTcw67nnuO3229m4aRNvv/0277zzDgDff/89Bw4cYOjQoYSGhvLjjz/i9XpJT08nOzubpUuXMmbMGKKiosjOzqa8vPyc3SOdO3dm0aJFjB8/HkEQeP755/GekBWVkpLCqlWruPXWW9FoNERERPD0008zYMAAHnzwQe655x4MBgM5OTksWbKEt99++5zGICPTrpHaATU1NRIg1dTUtPZQLnocBQXS/nFXSjnpXaTcXpdJtUuXtfaQ2h02m03KycmRbDZbs7brcbolV6VNchTVSo7D9a8jdZK71iF5PV7J7fVKVU6XVGi1S7vqrNK2GkvAK9dslYptDqnW5ZY8Xu9J7dfV1Ul33nmnpNfrpejoaGnu3LnSsGHDpEceecR/jdPplGbNmiWlpKRIKpVKio2NlW644QZpx44d/mtWrFghDRo0SNJoNFJISIg0duxYqaqq6pT39OGHH0pdu3aV9Hq9FBQUJPXp20f61yf/kvZV7ZN2le8KeOVV5kkl5hLpx5+/lwCpYE+uVHpgv1SyP0/619tvSWmdOkkqlUpKiI+XXp4zW3JYrZLX65VWr14tDRs2TAoNDZV0Op2UlZUlffHFF5IkSVJOTo40duxYKTIyUtJoNFJaWpr01ltvnfb/YPny5RJw0v0cPHhQGjFihKTT6aTExETp7bffPunZrV+/XsrKypI0Go3U+Kt348aN0ujRoyWj0SgZDAYpKytLeuWVV047hpaaXzIyLUFT1285m0bmJDw1Nb4S8hs2gCAQ9fRThN11l1xCvom0dLaD5PHitTTEldT/+goCokHp3wdHkiTsXi+17nqryQkVX0UBTAoFJqXPcnImq0lr4fQ4/TEmFpclIN1WIfqKsZlUJjReJS67DafVisvhCGhDVIiodXrUOt8Gf4qLoDiZnE0j056Q96aROS8kl4vSF1+i+ssvAQi5+WZinn8OoRkDIi9WLtRiIXmPx5VIruNiQ9AqUZhUCGqFX0C6vRJmj68SbF19rEljtAoBk8IXa6Jvg9VgG+JMGsSJx3s89kIQBPRKPSa1CYNCj1TvznHarCcFuyrVGjT1GTq+arBtT4SdDVmMyLQn5NRemfNCUKmIeXEO6tRUyubOpfp//8N5uJCE+fNRBAe39vBkOH1ciWR347a7EVQiolGNqFOiFAVCRCUhKiWSJGFrZDWxerzYPRJ2j5vy+lgTk1JRL05EVG3AatI4zkSSJH9p+jpnHU6PE4vLgsXlq1qqUWowmUyYwmJQegScVisOmxWX3Y7b6cDtdGCprkIQRTQ6HWq9AY1Oj0IW2jIyrYYsRmROiyAIhN89GXVyEsVPPIl1/QYKbrudxH/8HbWcdthmEAQBQatE1Crxujx4zS68VjeSy4unyo6nRkA0qlAYVAj1GTZ6hQK9QkGMRoXbK1Hn8VDn9llOPBLUuDzUuHxWBa1CJEgpYlKcW4ZOS96vQWXAoDIQY4jB4XZQ5/IJE6vLisPtwOF2cIxjKEUlJrUJkzGEYFGLy27HabXgsPqsJnaLBXt96XWlWo1Gp/ftPKzVyvV2ZGQuILKbRqZJ2HNzOXz/dNylpShCQkh46//Q9+3b2sNqk7QFM7qvXokbj9kJnoa4EhB1KkSjClGtOPXnJAmr11svTLzYTog1UQi+nYqD6rN02oLVpDFurxuz00ydqw6z04xXauS+EgRfnInahFFlBLcHh9WKw2rFZbcFtCOIAmqtz52j1utRqs4hNbuFaQvzS0amqcgxIzLNjqusjKLpD2DftQtUKmJffJGQG65v7WG1OdrSYiFJDXElLiRnozgLtcIXV6JVntHS4WpkNamrt5o0RqcQfanDCl+sSWtbTRrjlbxYXcfdOS6vK+C8TqnzWU3UJtSCCqfN6o818bjdAdcqVKr6WBMDKq0uIOX5QtOW5peMzNmQxYhMi+C12TjyzLPU/fILAOH33Ufko4/IJu1GtNXFwuv04DU78VobLbQKEYVRhWhQIYhnFhKSJGH1eKn1eKg7jdXEl53jizdRnaW9C4kkSTg8Dr8wsbkDLSEqUeUXJnqVHo/ThdNmqbea2AMyeQRBQKXT+Vw6Oj1KtfqCirC2Or9kZE6FLEZkWgzJ66X8zf+jon5zL9OYMcS99he5hHw9bX2xkNxePBYXXsvJqcGiQY2oapqwdHm91Ll94sR8GqtJkFLEpFSgF9uW1cTlcfldOWaXOUBsiIKIUe1LGzaqjYgIOG2+1GGH1XKS1URUKvzCRK3Tt3j6cFufXzIyjZGzaWRaDEEUifrTo6g7pFDy/CzqFi/m0JEjJLzz/+QS8u0AQSmiDNYgmdQBqcFeswuv2eVLDTaqEDSKMwoIlSgSphYJw5ehY/F4qfP4Yk3sHp/lxObxctThRiFAUCOribKVrSYqhYowRRhh2jC8kheLy+K3mri9bmodtdQ6agHQq3xpw6bQYEwRkXhcLhxWC06b1Veq3u3BVleHra4OqE8f1ulQ6/Wt7tKRkWkvyGJE5ncTcv31qBPqS8jv2kXBzbf4SsjLO422C5qWGqxC1J3dhSMIAkalAqNSQazGZzWpdXv98SYeCapcHqrqM3T0CrF+Dx0RXStbTURB9LtoJEnC5rb5hImrDofbgdVlxeqycpSjqBVq37UGEyHBISBJOB12nPWxJi6H43j6cE21z6Wj1foCYXVn3n1YRuZSRnbTyJw3zsJCDk+7H+eBAwh6PfFvvI7piitae1itRns2o3tdXrwWJ16LGySJ0ROvIisji7/N+6svNVh57n/lextiTdwe6jwe7Cf4c5SCgKnendMWrCaNaagCW+esw+q2BlaBFRQY1UaMKiNGtRGlqMTjcftdOqcKhBUVinp3ju531zZpz/NL5tKjqeu3bD+UOW/USUmk/Pcz9AMHIFmtFD3wIBXvf0A70LkyJyCqRJQhWlSxBhTBGhAAJLx1TlylFtwVNrxOz9maCWyz3moSp1WTbtDR1aglQasmSKlAFHxWlPnz5tGza1f0Oi3RcXE8O+dFrB5Pq88htUJNuC6clOAU0kPTSTAlEKwJRiEq8Egeahw1FJuL2Vu5l/zqfCoclUgaBUGRUUQkpRCRmExQRCQagwFBFH21Tcx11JaXUV5YwLHDh6g9Vo7dYsHrPbfnKiNzMSG7aWSaBUVwMEnvvkvpy69Q/cUXlM2di/PgQWJmPS+XkG+HCKKAwqRGUCsQtUoEjQLJ4fHFmNjcvuNGFaLuzKnBp0ItioSrRcLVSrySxPSHHubXJYt5+pVXSemaQU1VFTVVleyzOFCKAiaF6I83UbSii+PEKrAN7hyzy4zdbfe/yin3751jVBsxmozog0OQJMlXdM3WuCKsE7fTibXBpaPRoq536ag0sktH5tLhnC0jq1atYvz48cTFxSEIAl9//fUZr1+xYoWvQuQJr9LS0t875majpmYrlVXrqavLwW4/gtttbvW/xNozgkpFzOwXiH72GRAEqr/8ksJ778NTU9PaQ5NpAhaLhUmTJmE0GomNjWXevHmAL+BVFalHGaXHpfDy9MszScnqRFBECP1792Ppj0uQGqX5rl27luHDh6PX6wkNDWXs2LFUVVWdss+9e/bw73/+gx++/Zbpt0xkVPcujB7Yj7FjxiAIvj11qlweDtmc7DLb2G+xc9ThwubxturvqiAI6FV6og3RdAzpSFpYGnHGOII0QYiCiMdbbzWp81lNDlQfoNxWjkcJhtAwwuMTiUpJJSQ6Fn1QMAqVCkmScNptmCsrqCw+TPmhA1SXlmCtrcHtcp19UDIy7ZhztoxYLBZ69OjBlClTuPHGG5v8ub179wb4i6LaQNbFvv2vUVOzOeCYIChRKoNQqYJRKoOP/1QGo1Q1/AxCpQypfx+EShWCUhmMQiH7bwVBIOyuu1AlJVH8+BNYN2yg4JZbSfznP1AnJ7f28FoFSZLwem1nv7AFEEVdk/+6fvLJJ1m5ciXffPMNUVFRzJgxg61bt9KzZ09fW2oFj856gpzdOXz64X+IDorkmx+/4+obx7NlyQbSu3dhx/7djBw5kilTpvDmm2+iVCpZvnw5Hs+pXRDfffcdqampfP/994wbNw5Jkhg1ahRz584lOTQUS0OsiduDw+vL2LF4vJQ6XKgaWU2MrWw1UYkqQrWhhGpD/XvnNKQN2912bG4bNrctwGpiUpsw6A1ojUYA3C6XL0PHasVpt+L1eLFbzNgtZqC+8JpOj6RQIHm9ZxqOjEy747wCWAVB4KuvvuL6668/7TUrVqxgxIgRVFVVERIS8rv6aakA1t27H6e2bhdudw0uVw2S5Dyv9kRRjVIZUi9gGkRKUL2ACUGlDPILmhPFjihefK4M+549vhLyJSUogoOJe+MNjEMub+1htTgnBhh6PFZWrMxslbEMH7YThUJ/1uvMZjPh4eF88sknTJw4EYDKykoSEhK47777mD9/PoWFhaSmplJYWEhcXJxPZFndjLlyDH2yevPSMy8w6cEpHC4pZvXKVWdNDQaYNm0aH374IT179uT111/H4/Hwpz/9idDQUJYtWxZwraNRmXqzx0PAN5cABoVYX6ZegVYU2oyLw+VxYXaZ/eKkcYl6AJ1K569polVoEQTB59JxOHDaLDitNlyO44XXXB4PR0qPcnjdCmJTO5Gc1ZPYTuktXt9ERub30ObqjPTs2ROHw0H37t2ZPXs2gwcPPu21DocDh8Phf19bW9siY8rImOf/t++vVzsuVzVudy0uVw1udzUuV229WKnG5T7+7+PX+IQMePF6nTidZTidZec8FoXCcGqLTIM15oRjanUEanU4oqhpxifSvGi7dCHli88peuBB7Dt3cvjeewmbMoWoRx9BULedvT5kID8/H6fTSf/+/f3HwsLCSE9P97/fuXMnHo+HtLS0gM86HA7CoyMRdEq25+zkpquvx33MhqCsTw3Wnz412Ov14nA4+Pjjj/3t/vvf/6Z3797s3bs3oH+NKKJRi0SofRk6Zo/Xv7mf0ythcXuxuL2U1FtNgpQKTAqx9a0mChWhCp/VxCt5A2JNHG4HNpcNm8tGmbUMpag8HmuiNmLUhkMoeL0eX5aOzYalzvd9WH7oIId+28SGhf9FrdORmJFFcmZPkrMuIzQ2rs2IMRmZptDiYiQ2NpZ//OMf9OnTB4fDwXvvvcfw4cPJzs7msssuO+Vn/vznPzNnzpyWHloAgiCgUOhQKHRA7Dl9VpIkPB5zgDhxuWtwn+K9y338mNtdg9vtK5Tk8VjweCw4HCXn1LdSafIJE1VEvUDxiZTAn75XU/5Cbm5UUVEk/+djyubOpeqz/1L5/vtYN24kft4bl4zbRhR1DB+2s9X6bi7MZjMKhYItW7agUARutGc0GlGF69AbDQhqBQiCr9JrtQNPrRPRoDplanBsbCxKpTJA4HStr1NTWFgYIEYC7kvwiY0gpYJ4wOEvU+/B7PHi8kpUON1UAEK91cSk8F2vaUWriSiI/h2HwZc63GA1sbgsuL1uqh3VVDuqAV/BtQaXjkZvQGswojaaqLTYGHzrnRT+toVDu7Zjr6slf3M2+ZuzATBFRJKc2YuUHr1I6t4DnUkuiSDTtmlxN82pGDZsGElJSfznP/855flTWUYSExMvyjojkuRpZGWprbfA1OB21eJyV9cLmFrcjS0zziqcrkok6dyC2hQKfb1oCRQpqkbvNX7hYmz2L+y6X3/lyMzn8NbUIOr1xMx+geBrr23WPtoC7bEOhNlsJiwsjE8//dTvpqmqqiIhIYF7772X+fPnk5eXR3p6OqtWrWLIkCGnbOfuu+9m3759rF61Gq/VV9FVch93S4g6JaJRhaD2uXAWL17M2LFj2b9/Px07dgRg+/bt9OzZk717955khWkKnvpqsA2xJk5v4FdcW7KaNKZhY78GceLwOALOK0UlRrURjVfD0aKjdEztiFarRfJ6KSs4QMGO3yjc+RvFe3IC65sIAtEdOpKc1YvkzJ7EpXVFKVsmZS4QF2Rvmt8rRp588knWrFnD+vXrm3S9XPTsZCRJwu2uwek81uhVcfzfroqAc16v4+yNNkIU1SdYWxpES6CQ0agjUCqDEYQm7mdSUsKRJ5/CutkXOBx83bVEPz8LhdFwzs+grdIexQjA/fffz08//cT7779PVFQUM2fOZNmyZUydOpX58+cDcOedd7J27VrmzZtHr169KC8vZ+nSpWRlZXH11VeTl5dHZmYmU6dOZdq0aahUKpYtXsqNY68l3Bjq76shNRiNSL9+/TAajcyfPx+v18sDDzxAUFAQixcvPu97kiQJR/3Ow7VuDxaPNyDWpMFqElRfcK01rSYn4vQ4/XEmFpfFH2vidXkpLyrnu+rvyIzNZEj8EDqFdPKP2+WwU5S7m0M7fuPQzm0cKywIaFehUhGf3pXEjB4kde9BTMfOiCdYumRkmos2LUZGjx6NyWRi0aJFTbpeFiPnR4Mb6bhgaSxajp0kaDweyzm1LwhK1KrwesESFiBWjouWSDSaKJTKEPB6OfbPf3Ls7f8HXi+qpCTi581Dl9m9ZR7ABaa9ihGz2cz999/PokWLMJlMPP744/zwww/07NnTL0ZcLhcvv/wyH3/8McXFxURERDBgwADmzJlDZqYvSHflypXMmDGDLVu2oNPp6N+/P59//jlBBpNv/xurCxq+dRQCR2vLefTZx1m8ZAkGg4Err7ySefPmERYW1uz36JEkzG4PdfWWE9cJVhO1KNSXqVdgVIiIbUSYNFhN6lx11JhrKC4s5rX9r1Hi9Ll1o/XRDEkYwuXxlzMgdoDfDQRgrqqkcOc2Cnb8xuFd2zFXVQa0rdbpSOjanaTuPUjMyCIyKUXehVum2WgxMWI2m9m/fz8AvXr14q9//SsjRowgLCyMpKQknn32WYqLi/n4448BmD9/Ph06dCAjIwO73c57773HW2+9xeLFixk5cmSz3oxM8+Dx2E62tPiFS+Axt/vcgotFUYNGE41GE4vSosKxcgdCkQVFnYKIK28n8sYpaLTRiGL7zQxor2LkQiF5vHgtLjwWF/6tfgUQdSpfwKv6wvyV3mA1aShTfyqridG/h44CTRtZoO12O/vy97GXvSwtWcqm0k0BLh2lqKR3VG+/OEkNTvVbTSRJoqqkmMKd2yncvZ3Du3diN9cFtK8zBZGYkUVS9ywSM3rIwbAy50WLiZGGVN0Tueuuu/jwww+ZPHkyBQUFrFixAoC5c+fy7rvvUlxcjF6vJysri1mzZp2yjfO9GZkLjy+DqOJkV9FJFpdjuFynLnx1MqLPkqKNqRcuMfWvaLSa48d8wcZtD1mMNA1Jkup3DXYhNSoxL6gViIb66q4XcJ+as1lNNI2sJoZWtJqcOL/sbjubSjexpngNq4pWUWQuCrg+zhDH5fGXMyRhCP1i+qFXHQ9kl7xeyg4d5PCu7RTu2k5R7m5cDnvA543hESRlZJHU3efWMYVHXJD7lLk4uCBumguFLEYuDjweB07nUeyOozjsJTicR3HYS7E7SrEe2Y3dXIQnSIIm/mGsVAYHiJMGweITMTFoNTH18SwXdtGQxci543V6fC4cWyMXjiicNgunpZEkCbtX8qUO11tNOMlq4tt12HSBrSZnml+SJHGo9hBritewung1m0s34/Qer5+kFJVcFnUZA+MGMihuEF3CuiA2ivfyuN2U5u+jcNc2Du/awZG83JM2+wuNjau3nPQkMSMTfVBwy96wTLtGFiMy7Q7H/v0UPf4YtpI8PCES+puuQDu2Hw7PMRyOUhz2UhzOo9jtpU2uaOpzCx0XJz7h4nMTNQgXtSqiWd1Cshj5/fhcOO56F84JWTgGVZMKqbUEDVaT2nrLSWtaTc5lflldVjaVbmJ18WrWFK+h2FwccD5UE8qAuAEMihvEwNiBRBuiA867nA6O7Mn1uXR27aA0fx/SCUXbIpNSSMrsQWJGDxK6dkejv/AlBGTaLrIYkWmXeO12yua+TtVnnwGgzcjw1SRJSfFf48skqvMJFEcpDsdR7P5/+947HEdxuSpP08uJiGg0UY0sLNHHxYs2Dp02Ho0mGkFomslGFiPnjyRJSHY3HrMLydHIhdOEQmoXYmz2E2JNLqTV5PfOL0mSKKwrZN2Rdaw7so6NJRuxuq0B13QK6eS3mvSO7o1OGegKdVgtFOXuonDXDgp3bT8pU0cQRWJSO9eLkyzi0ruiUrfdwowyLY8sRmTaNXVLl1IyYyaemhoEvZ6YWc8Tco5ZW363kL30FMLlKA5HKU5nGZJ09q3bBUGBRhOLVhuPVhuHVhuPThvf6H2cvxquLEaaF6+r3oVjdeOPMBUERIPPWiKqWjct1SP53Dk+l44XdwtbTZprfrm8LnaU72DdkXWsP7KeXcd2ITVSVSpRxWXRlzEobhCD4gaRFpoW4NIBsNZUczhnpz8gtro0sGijQqUiLq0rSRlZJNanEctl6y8tZDEi0+5xlZb6apJs2gRA0PjxxLwwC0X9xmLNgSR5cDor/GKlsVCx20uw24/gcJQgSe6ztqVWR6HVxqNRdwGuISUlGZ3OgCiqEUVVky0rMqdG8kqnLKQmaBQojGoEbeu4cBpzIawmLSV2q+3VbCjdwPoj61l3ZB2llsCd1cO14X6rycC4gUToTg5krT1WRuGuHf6A2BPTiFVaHQldM3wBsZk95TTiSwBZjMhcFEgeDxXvvkv52/8PPB5UiYnEz3sDXVbWhRuD5MHhKMNuL8ZuP1L/0/ey1f/0eo9nIIhiHCHBL5CYGIVafXxxFARFvShRB/wURTWC4BMrrb2YtgckSUJyeHwuHHsjkagQURhViHolgqJtLHAtYTW5EJY3SZI4WHvQL0w2lW7C5g6M00oLTfMLk8uiLkOrPDmYtqqk+Lg4ydmJvS6wFIDWaCIxI5Ok7j1J6p5FaGy8/DtwkSGLEZmLCuvWrRQ/8QTuIyWgVBL16COETZnSJv6qkiQJl6vSL1bM5mOYzR1JTIxCpfYieV1NdAWJCEK9OBFViMJxoeL7qZS/qE9AcnvxWFx4LS7wNnLh1Jedv1A1S5pCc1lNWsMN6PQ42V6+3R9vkluRG+DS0Sg09I7u7RcnnUM6nzRXJa+X8sICChunEdsDBY4xLNzv0knqnkVQRNQFuT+ZlkMWIzIXHZ7aWkpmvUDdzz8DYBg0iLjX/oIyMrKVRxbIqRYLSfLg9brwep1Iku+nV3IheZ14va4muYFA8FlURBWi37qiqncDNYiV1hdnrYHkbahZ4kRyNXLh1JedF3VtT8j9XqtJW4hJqrRXkl2S7RcnZdbAncojdZEMjBvIwLiBDIgdcEqXjsft5uiBffXxJvVpxK7A/bZCYmJJzMgisVsmCd26YwqTa5y0N2QxInNRIkkS1QsWcPSVV5HsdhRhYcT95c8Yhw5t7aH5+T2LhSR560WJT5x4JSdSgHhp2qaIx4VKgwtIc16WleHDhweUg28LFBQU0KFDB3777Td69uwZcE6SJCSnF6/ZidfWSOCJAqKxvmZJG3HhNOZcrCZqt4viQ4faTIC0JEkcqDngFyabSzdj9wQWTusS1sUfb9IrqhcaxckZNi6ngyN7czm825epU5q/D8kbmEYcEhNLQtdMEjMySejanaCItvWHiMzJyGJE5qLGkZ9P8WOP49i7F4Cwu+4i8vHHENvAbqQt8ZerJEl+UdLYutLYysLZfpUF0e/6OW5NafzvkxfpCyFGJEli3rx5vPvuuxw6dIiIiAimT5/OzJkzT3n9mcRIQLunKjvPyTsHt0XOZDWRnA6qig6zSRtMv6hQBgQb0bYhgeXwONhWts2fpZNbmRtwXqvQ0jumN4NiBzE4fnBAufqAdurTiA/n7KIoZydlBw+cVOMkOCqahG6ZJNa/giJlt05bQxYjMhc9XoeDstffoOqTTwDQdutG3Lw30HTo0Krjag0zuk+suBtZV46/GqwtZ0MQlCcJldGjr6Vnz17Mn/9miy3cDz/8MIsXL2bu3LlkZmZSWVlJZWUlo0ePPuX1TRUjDZy27LyqvmaJrvVqljSFE60mZpuNssJCZtR6KfIK6ESRwaFGrggzMTI8iGRd26rrUWGrYEPJBr84KbeVB5yP0kf504cHxA4gVBt6ynYcVgvFe3I4nLOTopydHD2Yf5LlJCgyyufS6dqdxIxMgiKj26zgvFSQxYjMJUPdsuWUzJiBp7raV5Pk+ecJvv66VvsSOlGMSJKE9YQvzQuFXhQRBOEEN9CJQsWJJHmxWKw89tjLfPfdUoxGAw89dBc//7ySzMx0/vLaM4iCGpdLYs6cv/Hll99QXV1LRkY3XnvtL4wYcXzTy7Vr1zJz5kw2btyIRqOhX79+fP7554SGnrzI5ObmkpWVxa5du0hPT2/SPZ1KjKxcuZInn3yS7du3ExYWxl133cXLL7+Msr6mxYIFC5gzZw779+9Hr9PTIyOLhf/+Lwa9gZUb1jDjz7PI2ZODSqUiIyODzz77jOTk5PP/D2gBLDYbe/MP8K2o4+sqG6XOQKHZUafhinATV4QFMTCkbVlNJElif/V+vzDZfHRzwCZ/AgJdw7v6xUnPyJ6oFKpTtuW0WSnem+sXJ6dy65jCI0ns1t1vPQmOjpHFyQWmqeu3XH1Gpt1jumIE2m++9tUk2biRkmefxbJ2LTGzX2jWmiS/F6vXS8dVO1ul7/yhmRgUCgRBRKHQACf/1eyzqnh4+unprFu3jS+//JiIiGBeeOEvbN+eS2ZmOkgSXsnBo4/OZu/eA/z7338mJiaK779fypVXXsX69V+TlpbGzp37GDnyeu6663bmzfsLarWWFStW4/GcOpvou+++IzU1le+//55x48YhSRKjRo1i7ty5hIWFNekei4uLueqqq5g8eTIff/wxe/bs4d5770Wr1TJ79mxKSkq47bbbmDt3LjfccAN1dXWsWrkK0aTG7fEyceptTLntLj5+8z1copctOb+dzyNvcRSCgE4h8kyHOF7QaMi12FlaUcuyylo21VjItznIL3Lwr6Jj6ESBwaGmNmM1EQSBzqGd6Rzambsy7sLhcbDl6BZ/CnFeVR45FTnkVOTw3s730Cl19InuQ//Y/gyIHUDn0M7+wmtqnZ4OPXvToWdvAJx2my/mJGcnRTm7KM3Po66inJzVy8lZvRzwZes0WE0SumbKOxK3IWTLiMxFg+TxUPGvf1H+1tu+miQJCb6aJD16XNBxnGgZsXg8rS5GzobZbCY8PJxPPvmEiRMnAlBZWUlCQgL33nsvf/vbXAoKDpCWlkle3mZiYsPqM4GcjB8/hd69u/PCC48wderTFBWV8ssvHzVqXTheT0VUNwqwVTN9+qN89NFH9OzZk9dffx2Px8Of/vQnQkNDWbZs2SnHeqJlZObMmSxcuJDc3Fz/wvLOO+/w9NNPU1NTw7Zt2+jduzcFBQUnWTsqKiqIiIjg169/YUjvgcdHrBR91V0Nbc+FcyY3YK3bw6rKOpZV1rKsou6UVpMRjawmujZkNQEot5b7XTrrjqyj0h5YNC1UE0q/2H4+cRIzgARTwmnFhMtu50jeHp84yd1Jyb48vJ7ArDVDaJhPnNRn64TFnb49md+HbBmRueQQFAoipk1D378/Rx5/AldREQV33EnkIw8TPnVqq9Uk0Ysi+UMzW63vppCfn4/T6aR///7+Y2FhYaSnpyMIAqKoITf3AB6Ph6ysywM+63A4iIpKQKdLYteufG648SqUSmO9K8gFSH630Ik4HBU4HA7+8Y+XSE9PQRTV/POf8+nffzi5ubvp0qXbWReH3NxcBg4cGHDd4MGDMZvNFBUV0aNHD0aOHElmZiZjx45lzJgxTJgwgdDQUMLDw5k8eTJX33Ito0aO4oohI7hp7HXERkbjqXHgqXUi6utrlrRy2fmmEKRUcE1UCNdEhSBJ0mmtJu8VHUMrCgwMMTIizMQV4UF01GlafSGO1EcyvuN4xnccj1fysq9qHxtKNrChZANbjm6hylHFLwW/8EvBLwDEGmLpH9vf94rpT6T+eHaNSqslOasnyVk9AXA57JTs2+sPiC3ZtwdLVSV7161i77pVAOiDQxoFxHYnLD6x1Z/JpYIsRmQuOvS9etHh668oeeEF6n76mfJ5f8W6fj2xf/kLqqgLH20vCEKTrBNtHbPZjEKhYMuWLShOuB+j0YhKFYxeb0SlDEKv9wURH88COjlOxet1EhMTgVKpJDU1BperGoDkZN+ur3v3riUhQTgeUCtqEAU17vrN3Zpq1FUoFCxZsoR169axePFi3nrrLWbOnEl2djYdOnTggw8+4OGHH+bnn39mwbcLeeGV2fz8zY/0y7gMyeXLyPFaXAgahc9a0gZrlpwKQRDoZtTRzajjoeRoat0e1lTVsbyyjmUVtRQ7XCyv9L2ftf8IiVo1I+rdOYNDjBiVrTtnRUEkPSyd9LB07sq4C5fHxc5jO8kuySa7NJvt5dspsZTw9f6v+Xr/1wB0DO7oFyd9YvoQpD7+l7hKoyWpew+SuvsspS6ng9JG4uTIvj1Ya6rJW7+avPWrAdAFBZPYtTsJ3XzWk/CEpDZRaPFiRHbTyFy0SJJEzcKFlL7yKpLNhiI01FeTZNiwFu23LRSlOlfMZjNhYWF8+umnfjdNVVWV300zf/588vLySE9PZ9WqVQwZMuSU7dx9993s27ePNWvWNKnfX375iXHjriI39zc6dIjH63Wwfft2Bg68hi1bvqVTp5STPnPoUDFZWVeyZs0CevbMYs6cN/nmm5/ZsSMbhUKLKKr5+9/f5dlnn6W6uhrxhMXD4/GQnJzMY489xmOPPXZS+wMHDqRv3768+eabSM76Tfoa1yxRCCgaXDit4OZojvklSRJ5VgfL660mG6otOBstBSpBoF+wgSvCg7gizEQXg7bNCTCry8pvZb+RXZLNhpIN7KncE1AVVhREMsIz/OKkZ2TPk0rWN8btdFK6P4/Dub6A2CN5e3E7HQHXaE1BAeIkIjFZFidnQc6mkZGpx3HggK8myZ49AITdNYnIxx9vsZok7VGMANx///389NNPvP/++0RFRTFz5kyWLVvG1KlT/XVG7rzzTtauXcu8efPo1asX5eXlLF26lKysLK6++mry8vLIzMxk6tSpTJs2DbVazfLly5k4cSIRESdXz/R6vfTt2xej0cj8+fPxer088MADBAUF8csvP9dbUBzHLSuSg4KDB+nefRSrV/+PrKwuHDlylN69x3PHHddz3323sW9fAQ89NJv77ruD5557gs2bd7Ny5TpGjx5DTEwcGzdu5Q9/+ANff/01Xbp04d133+Xaa68lLi6OvXv3cvvtt/PSSy9x//33+8d5yrLz1NcsMagQNBeuZklLzC+Lx8O6KjPL6q0mh+yBLrUYtcofazI01Eiwqu0Z1avt1Ww6uslnOSnJpqC2IOC8WlTTM6qnX5xkhGegFE9/H26Xi9L8PIpydlGUu4vivTm4HSeIE6OJhK4Z/kJs8sZ/JyOLERmZRngdDsrmzaPq4/8AoOnalfh589CkNn9NkvYqRsxmM/fffz+LFi3CZDLx+OOP88MPPwQUPXO5XLz88st8/PHHFBcXExERwYABA5gzZw6Zmb64mJUrVzJjxgy2bNmCTqejf//+fP7554SEhJyy3yNHjvDQQw+xePFiDAYDV155JfPmzTttNk1DAOvmzRvIyuqK1+tk5aoVzHj2JXbuzCU0NJjbbruW559/EKVSyd69B3j22bls355LXZ2FxMQ4pk37A/ffP5Xy8hoefvhZNm3aSkVFJbGxsdx111288MILJ1lU4Aw1SxoCXi/AJn0XYn4dtDr8QbDrquuwNRJgCgF6Bxn8sSaZRl2TNvi70JRaSv3CJLskmzJbYMl6o8roz9TpH9ufTiGdzigoPW4XRw/s5/DunT5xsicHlyOw0qzGYCC+SwaJXbsT3zWDqJSOKJRtT7hdSGQxIiNzCuqWL6fk2fqaJDodMc89R/CNNzTrX7XtVYxcLDTUVPF6HY3iUxynDaINRGhU+E1zUhG4xvPE6/T44kms7uPVbwUQtS1b4fVCzy+7x0t2jaVenNSyzxpoHQhXKRkRZmJEmIlhYUFEqNve4itJEgW1BX5hsrF0I7XOwB2Ew7Xh9Ivtx4DYAfSP7U+8Mf6MbXrcbsoO5vvrnBTvzcFpC9z4T6nRENc5nfguGcR3ySCucxdUl9h3gixGZGROg+toGUeeegprdjYAQVddRcyc2ShMpmZpXxYjbZeTi785AoJrAzaEOQnBv99PY8EioAa7gNfqviDWktaeX4ftTlZU1rK8oo5VVXWYPY02JgR6mPT+QNheQXoUbdBq4vF62FO1xy9Oth7detJ+OgnGBL/VpF9MP8J14Wds0+vxHBcne3ZzZE8Odos54BpBFInu0NEnTrpmEJ/eDX1QcLPfX1tCFiMyMmdA8nioeO/flP/f//lqksTH+2qSNKG8+Nlo7cVC5vcRmPnTWKQ48ErOs+z9U29REdTgViI4FAgeJYJXhYACUadCNCibxVrSluaX0+tlc42V5ZW+QNjd5sAFPUSpYGi91eSKsCCiNaeuptraOD1Otpdv91tNdpbvxH3CTtqdQzvTP8ZXfK1PTB8MKsMZ25S8XiqKD1O8ZzdFubsp3pNDXUX5SdeFxSX4hUlC14yLroS9LEZkZJqAbds2ih9/AldxMSgURD78MOH33nNeQWhtabGQaR7OKFTOZlGRBASvCtGrQkCNQq1FodUhKjSIZwigPB1teX6VOlw+q0llHSsr66h2B1bezTBqGREWxIgwE32DDajbaLCnxWVhy9EtfsvJ3qq9AecVgoLuEd39lWF7RPZArTh7QHztsTKKc3dTtMcnTiqKCk+6xhgWTnx6N+K7ZpDQJaPdZ+zIYkRGpol46uoofeEFan/8CQD9wAHE/eU1VNG/ryZJW14sZJqf40LF0UioNC1GRRAU9W4fzQlxKppT7qIM7Wd+ub0S2+qsLKt36WyrswZINqNCZEioz2oyIjyIRG3r77h9OirtlWws3egXJ4frDgec1yq09Irq5RcnXcK6oBDPXqfFVldL8d5civfspnjPbo4e2I/3hK0TNHoDceld6+NOuhHTMQ2lqm1amE6FLEZkZM4BSZKoWfQVpS+/7K9JEvvqK5hGjDjnttrLYiHT8vhiVOqtKB4HHpcNr8eBJLiQhFPv19OAUF9CXxQ1iMJxkeJ0eigoONTu5tcxp5tVVb7U4eWVdVS4TnCD6DVcERbEFeFB9A82tKkN/k7kiPmIv77JxtKNHLMdCzhvUpvoHd2bvtF96RvTl7TQtCaJE5fDTun+PL/l5EjeHlz2wKBYhUpFTMc04rt0I6FLBnHpXdHoz+wyak1kMSIj8ztwHDhI8eOP48jNBSBk4gSiHn8cxWnSUk+FLEZkzoQkSUhOLx6LA4/DhiS66l9uJKXb92/p9ELF6ZQoKqpE4jsMhlD0ug7o9Sno9R3QaGJOa1FpS3gliZ1mG8vrhcnmWgueRiuRThQYFGLy1zbpoFO32TgKSZI4UHOADSUbyC7JZnPpZupcdQHX/F5x4vV4KD900BdzstcnUKw11YEXCQKRSSnEd8kgoasva8cY2rRNJi8EshiRkfmdeJ1OyufNo/KjjwFQhIcT/cwzBF1zdZO+EGUxItNUJI8Xr9WN1+JCch/PSkEN6CVQu+uLvR13/TgdHg4fLqO6Zg5e75GA9kRRg16Xgk5fL1AaCRWVKqzNLug1Ljerqswsr483KXEEbvCXpFUzvD4Q9vJQE6ZWLlV/JtxeN3sr97KpdBObjm5iy9EtWFyWgGuC1EE+cRJzXJyITRCRkiRRVXLEJ0xycyjes5vqoyUnXRccHVNvNfEFxYbGxrfa/70sRmRkzhPr5s2UvDAbZ34+AIZBA4l54QXUJ+z8eiKyGJE5V3zWkvq6JTb38XhYQfBt1GdQIaoVSJKEzWbm4MF8DMb9uJx5WG0FWK0HsdkOI0mu0/ahVJrqxUkqen0H9IZUv1hRKHQX5kabgCRJ7LHY/dVgN9ZYcDVappQC9AkyMDzMxPCwILJMbbPoWgMtKU4AzFWVFO/xCZOiPbspP3TwpMwvXVCwP1snvksGUSmpiBdovyxZjMjINAOS00nF++9z7J2/IzmdCGo1EdPvJ3zKFITTlJOXxYjM+XA6a4mg9m3U5xTcFBwqOGl+eb1u7PZirLaDPnFiPYTVehCr7SB2+xHOlPGj1cT5RIqhQyPBkopWG9vqbh+L28PaajMrKutYUVnHAVtg0bUwlYJhoT5hMjzM1GbThxtwe93sqdzjEyelm9hatvWM4qRfTD86h3ZusjhxWC0cydtTHxSbQ8n+vXhcgSJVpdESm9aFhPqg2NjO6ag0LfNdJYsRGZlmxHnoEKVzXsSybh0A6k4diZ0zB33v3iddezGJkeHDhweUg28LNJSD/+233+jZDHVh2iqSJCE56q0l9uPWErvXyeHyYpKiEzAlNC02wONxYLMVYLUWYLUeqH8dxGI9iNtdfdrPiaK2kbunXqTUW1RUqtb5Lj5kc/iFyeoTiq4BdDNoGV6fPtwvxICmjafFNlWc9Inu47ecnIs4cbtcHM3fR/Fen/WkeG8ODktg+6JCQXSHTgybdA/x6V2b7d5AFiMyMs2OJEnUfv8DR//8ZzyVlcCpA1xlMXJuSJLEvHnzePfddzl06BARERFMnz6dmTNnnvL69ipGzudZNlhLPBYXdrudQ0cKMS23oA8zYegfgz4zAkH1+8zuTmelX5z4XgewWA9isx06o9tHpQrHcJLLJxWdLhFRvDDWCZdXYkuthRWVdSyvrGVHnS3A/qMTRQaFGBkR7os3SdVp2mzcTANur5vcilw2Ha0XJ0e3YnVbA645H3Eieb0cKypsVO9kN+bKCgAmzX2LyOTm3a+rqet329tEQEamjSIIAsHjr8E45HLK5v2V6i+/pPrLBdQtXUb0s88QdM01bf6Lri3yyCOPsHjxYt544w0yMzOprKyksl7stQdcLheqFq77IChEFCY1olGFu1ZCKFeACM5DtTgP1VL93QEMvaMx9ItBFaU/p7bV6jDU6jBCQvoEHPe5fYpOECk+0eJ0luFyVVBdU0F1zabAsQpKdLpEnxVFl+J3+egNqahV4c36O6ISBQaEGBkQYuSZ1FiOOd2srvIJkxWVdZQ53SytrGVppW8fmkStmhFhJobXB8IGtcFAWKWoJDMyk8zITKZ0n3JKcVLrrGXZ4WUsO7wMgGBNsF+c9Inuc0ZxIogikUkpRCal0HPs1b4/ssrLKN6bQ0TimePhWhLZMiIj8zuxbtlCyQsv4NwfGODqjY4OsIxIkoTNdeaaEi2FTtX08uMWiyVg194nnniC7777LuCveYfDwcyZM/nvf/9LdXU13bt357XXXmP48OH+dtauXcvMmTPZuHEjGo2Gfv368fnnnxMaGnpSn7m5uWRlZbFr1y7S09ObNM5TWUZWrlzJk08+yfbt2wkLC+Ouu+7i5ZdfRlm/Y+qCBQuYM2cO+/fvR6/X06tXL7755hsMBgMrVqzgqaeeYvfu3ahUKjIyMvjss89IPkWgckPfn3/+Oe+88w7Z2dn84x//YPz48Tz44IOsWrWKqqoqOnbsyIwZM7jtttsAmDx5Mh999FFAWwcPHiQlJYVdu3bx5JNPsnr1agwGA2PGjOFvf/sbERERp7z/BstbUmQ8nu3VWDaV4qk+Hkeh7hCMsX8Muu4RCMqWcVG43eaTRIrNWoDVdhCPx3raz13IIFpJksi12FleWceKylqyqy04pcDdh08MhG2L++icSIM42Vi6kU1HN/Hb0d9OspycizhpaWQ3jYzMBcAX4PoBx/7+dySHA0GtJvixP1Hdrx8dUlPRarVYnW66zfqlVcaX8+JY9E3cRXX69On88MMPvP/++0RFRTFjxgxWrlzJlClT/GLk3nvvJScnh7/85S/ExcXx1Vdf8dxzz7Fz5046d+7Mtm3bGDBgAFOmTOGPf/wjSqWS5cuXc+utt55ycZ07dy7//ve/ue+++3j77beRJIlRo0Yxd+5cwsJOHQ9xohgpLi4mLS2NyZMn89BDD7Fnzx7uvfdeHnjgAWbPnk1JSQlJSUnMnTuXG264gbq6OlavXs2kSZPQarVERERw7733Mm3aNJxOJxs3bmTEiBEkJSWdtu+UlBTmzZtHr1690Gq1eL1e/vvf/zJq1CiCgoL44Ycf+NOf/sS6devo168fNTU1XHnllXTv3p0XX3wRgMjISOrq6khLS+Oee+5h0qRJ2Gw2nn76adxuN8uWLTvl/Z/oBpS8Eva8KizZJdj3VPpjS0SDEn3vGIz9YlBGXJhsGUmScDhK690+x+NTLNaD2O1FNCmIVt8oPqUZg2gtHg/rqy3+Tf7yTxEIOzTU5BcnMW08ELYBl9fls5zUZ+tsPboVmzuwUFpjcdI3pi+dQjpdMHEiixEZmQtI4wBXb2wsntkv0DEzE0NYWLsQI2azmfDwcD755BMmTpwIQGVlJQkJCdx3333Mnz+fwsJCUlNTKSwsJC4uzv/ZUaNG0a9fP1599VVuv/12CgsLWbNmTZPGN23aND788EN69uzJ66+/jsfj4U9/+hOhoaGnXYxPFCMzZ85k4cKF5Obm+q1A77zzDk8//TQ1NTVs27aN3r17U1BQcJK1o7KykvDwcFasWMGwYcPOOt6GvufPn88jjzxyxmuvueYaunTpwhtvvAGcOmbk5ZdfZvXq1fzyy/H5UVRURGJiInv37iUtLe2kds8Uk+SudmDZVIp1Uyme2uOl6DWdQjD0i0HXLbzFrCVnwxdEe8hvTWkQKVbrAdzumtN+zh9EWy9ODPqOfrGiVP7+yqOFJwTC1p0QCNvVoK2vbRJEvzZeEbYxDeJkY+lGNpduZmvZyeIkRBNCn+g+9Inp0+LiRI4ZkZG5gKiTk0n893vUfv8DR95/H4/bjauoCKfNhjYqipwXx7bKuHRNDGrMz8/H6XTSv39//7GwsLAA18nOnTvxeDwnLZAOh4PwcN/26tu2bfOLmabg9XpxOBx8/PHH/nb//e9/07t3b/bu3dsk101ubi4DBw4McEcNHjwYs9lMUVERPXr0YOTIkWRmZjJ27FjGjBnDhAkTCA0NJSwsjMmTJzN27FhGjx7NqFGjuPnmm4mNjT1jn336BMZXeDweXn31Vf73v/9RXFyM0+nE4XCg1585fmP79u0sX74co9F40rn8/PxTipEzoQzREDw6maArkrDvrfRZS/KqcOyvxrG/GtGoQt8zCkOfaFQxF7aEuEKhwWhMw2g8+Z4Cg2iPZ/rYbIfweu2YzXswm/ec9DmNJqZemHTEUP+zqdaUJJ2GSfEaJsVH4PJKbPUHwtaxvc5KrsVOrsXO3w+XoxMFBoYYGVGfPtxJ33YDYVWiiqzILLIis7gn8x5cXhc5FTlsKt3kFyfVjmp+LfyVXwt/BY6Lk3uz7qVbeLdWGbcsRmRkmomGAFdl/34crC+U5qmqwltbhzo2BkVwcJv9AmsKZrMZhULBli1bUJxQMKlhMdXpzs0dEBsbi1KpDFh0u3b1pRYWFhY2OY7kTCgUCpYsWcK6detYvHgxb731FjNnziQ7O5sOHTrwwQcf8PDDD/Pzzz/zxRdf8Nxzz7FkyRIGDBhw2jYNhsCF/PXXX+fNN99k/vz5ZGZmYjAYePTRR3E6z7xRntlsZvz48bz22msnnTubIDoTgkJA1y0cXbdw3FV2LJtKsWw6irfOiXlNMeY1xagSjBj6xKDvEYmoa92loClBtBZrvk+oWHwxKi5XBQ5HKQ5HKVVV6wM+57Om+Nw9hnqB0hCfciprikoU6B9ipH+IkadTY6nwB8L64k2OOt2+ImyVvjLv8RqVX5gMCTUSrGq7S6lKVNEjsgc9InucVZzck3lPq42z7T5BGZl2iiIoCEVICKroaISKCiSHA1dREZ6qKlRxcYgaTWsP8SQ6duyISqUiOzvbHytRVVVFXl6e333Rq1cvPB4PZWVlDBky5JTtZGVlsXTpUubMmdOkfgcPHozb7SY/P5+OHTsCkJeXB3DKANJT0bVrVxYuXIgkSX6xt3btWkwmEwkJCYBPKA4ePJjBgwcza9YskpOT+eqrr3jsscf899arVy+effZZBg4cyGeffXZGMXIia9eu5brrruPOO+8EfBafvLw8unU7/lemWq3Gc8KOrJdddhkLFy4kJSXFH2zb3ChDtQSPSSFoZDL2vEosm49iz63EVWSmumg/1d8fQNc9HEOfaDSpIQhi2xHMoqisd9GkEEHgppUuV00jd0/9T8uBRtaUXMzm3JPa9FlTAt09BkPHgH19wtVKro8O5froUH9FWH8gbI2FYoeLT0oq+KSkAoUAl5kM/nL1PYL0bToQ9lTiZPex3Ww5uoX0sPMX/78XWYzIyLQQCr0eTUgI7ooK3GVleC0WHPv3o4yMRBkRgdCGijEZjUamTp3Kk08+SXh4OFFRUcycOROx0RjT0tK44447mDRpkj94s7y8nKVLl5KVlcXVV1/Ns88+S2ZmJtOnT2fatGmo1WqWL1/OxIkTTxnAOmrUKC677DJ/kKzX6+WBBx5g9OjRTXZRTJ8+nfnz5/PQQw/x4IMPsnfvXl544QUee+wxRFEkOzubpUuXMmbMGKKiosjOzqa8vJyuXbty8OBB3n33Xa699lri4uLYu3cv+/btY9KkSef0/Dp37syCBQtYt24doaGh/PWvf+Xo0aMBYiQlJYXs7GwKCgowGo2EhYXxwAMP8K9//YvbbruNp556irCwMPbv38/nn3/Oe++9d5IF6nwQFAK6ruHouobjMTux/laOZXMp7qNWbNvKsW0rRxGiQd87GkPvaJRhbbtGjkoVTHBwL4KDewUc91lTDtdbUw5gteT7LSsuV2Uja8q6gM/5rCmp9daU1ABrSlejga5GHdOTorB6vKyvNrOiPn14n9XBploLm2otvF5QSqhSwZAwE8NCTQwNM5GoPXWl5raCSlTRM6onPaN6tuo4ZDEiI9OCCKKIKjISRVAQrpISvGYz7rIyPDU1qOLiUBjaztbfr7/+ut9tYDKZePzxx6mpCQws/OCDD3j55Zd5/PHHKS4uJiIiggEDBnDNNdcAPsGyePFiZsyYQb9+/dDpdPTv39+f4noioijy3Xff8dBDDzF06FAMBgNXXnkl8+bNa/K44+Pj+fHHH3nyySfp0aMHYWFhTJ06leeeew6AoKAgVq1axfz586mtrSU5OZl58+Zx5ZVXcvToUfbs2cNHH31ERUUFsbGxPPDAA/zxj388p2f33HPPceDAAcaOHYter+e+++7j+uuvD3h+TzzxBHfddRfdunXDZrP5U3vXrl3L008/zZgxY3A4HCQnJzNu3LgAIdjcKIxqTEPiMV4eh6vYjGXzUazbyvBUO6hbWkjd0kI0HYMx9IlBmxGOqG579ThOh8+a4nPRRHBFwDmXqzqgXorVkn9CbEoOZnPOSW1qNDHH3T36DvQ0dGRwYiovJF8LMQAAkUFJREFUdkqn2OH2F11bXVVHldvDt2XVfFtWDUBHnYah9bVNBoUY2/Qmf62JnE0jI9PMnC7bQZIkPDU1uEtLkdxuABShoT53TguZ6GUuPlqqwq/k8mDbXYFl81Ec+dX+LFxBo0DfMxJDnxhUCcZ2Hfd0OhqsKQ3unoa4FKv1AC7X6QvwiaIuwJKi1XWgkDjWWsNYUe1ha50FT6MVViFA7yADw0JNDAsz0dOkR9mG3GItgZzaKyPTSpxtsZDcblxHj+KpqgJAUChRXgQBrjIXhgux3YC7yo51y1EsW47iqTpej0MZpcfQJxp9rygUprbtfmgu/NYUS0N8Sn79LsmHkCT3aT+n0cSi0aVSpUggzxPLelsEWx1RVBEG9b/nQUqRy0NMfstJiq7txZOdL7IYkZFpJZq6WHgsFtxHjuB1+L7sRYOhzQa4yrQdLuTeR5JXwnGwBuvmo9h2HUNy1dfiEAW0XcIw9IlGmx6K0E5qcDQnXq8Lu73opLgUq/XgGa0pXlFPlZhAvieWQ1IcR4ijhHhKiSVWZ2RYfbzJ5aFGQtpwlk5TkcWIjEwrcS6LheT1+gNckSQQhDYZ4CrTdmitjRi9djfW7eVYNx/FebjOf1w0qtBfFoWhdzSq6LYTA9WauFxV9SLluCXFas3HZitEkk69NYQXgXKiKCGOI8RTSjx6fSrp4V0ZFJFEn2AD6nb4nSCLERmZVuL3LBZeh8Mf4AogaDRtLsBVpm3QFnaFdh21YNlyFOvWMrz/n70zj6+iOv//e2bunhtCdsK+I8oqEECqoCC41qUuX6oialFrqVoFFbCIS/ErlhbqUn/WSt2XWq391hURUAGDgijKJmtkC4GEJDfJ3WbO74+ZuyaBBBIC5LxfjnPmzNlmuLnzuc95zjO+2Jt9HR1S8QzONWOXuE78X/WNjWEEqa4ujJv22WJFod1MOFxRZ71KUthLOwxnJzJTe9Aj/RS6p/fC4+l0zN6QfKRIMSKRNBNH+rCQDq6S+nA8iJEIQjfwbyw1Y5dsKAHDfJwodhV3nyw8g3Jxdk07rmKXHI8IIQiGDljTPabzbEnFj5RXbkEN7UGp450+BirC0Z50b3fSvd2jy5FTPN2w21sf24uoAxkOXiI5wVAUBVvr1mheb9TB1YzgWo4tL086uEqOOxRNjUZ61SuCVH2zj8qviwjvq6Lqm31UfbMPLd1JyqBcPINysaUf37FLmgtFUXA6snA6skhPH5pwTtf9VFZtZ1PJen4s3UiZbwv24A7asAsXfggWUl5SSHlJ4ruc7PYMK7hbVzwp3WIrflztUdXj79EvLSMSSSPTWL9cpYOrpDaOJ8tIbQghCO30Ufn1XqrWFCMClo+EAs5urUkZnIv7tEyUer43SVKTat3gy4MVfFm8jc2lGwhWbyOP3bRlF3nsIov9ddZVFAceT6eYUPF0s6wpXbHZUht9rHKaRiJpJhrzYSEdXCXJHO9iJB4jqOP/4QCVX+8lsCUWAE5xaeYL+wblnrSxS44lxcEQn5VUsLS0gqUlFRwM+GhjiZO27KKzuoeu6h7S9J0oIlBnO/37/52szFGNOjY5TSORnAREI7impRHavfu4juAqkSSjOjQ8A3PwDMwhXOI3nV5XFaEfDFD55R4qv9yDLTcudom3ZcQuaWyyHXZ+0SaDX7TJQAjBxio/n5V0ZUlJBe8frKTaMEAHRRhksp98VzFDXcV01/bQKvwT/uptBIP78Ljr9z6opkBaRiSSRqbJImQ2g4PrqFGjGDBgAPPmzWuS9iUN50SyjNSGMASBrQep+rqIqu8PQDgudknvDFIG5eLqlYGiSWtJYxAwDL4uq2SpZTn5rqI6wR3WoSgMSUvh7DSFn+e1o6O7cT9T0jIikZxkJDq47kMvLYk5uLZpg9a69Qln7p41a1atb/j1eDxUVlY2w4gkTY2iKri6p+Pqnk7rajN2SeWqIkI/VeD/4QD+Hw6gptrxDMwlZXAu9hxPcw/5hMapqoxIT2VEeirTgZJQmM9LK/ispIIlJRXsCoRYdtDHsoPQv3Wo0cVIfZFiRCI5wVBsNhzt2qK3bk149y4zRsmuXegHD55wDq5Tpkzh1ltvTcgbPXo0Q4YMaaYRSY4lqtuGd1ge3mF5ZuySr63YJRUhfJ/txPfZTjN2ycAc3P2y5DROI5Bht3FJTjqX5KQjhGBrdYClJRUsO+hjSFrzTftKDziJpKkRAoKVjb5pdoGjQxtsGamgBzDK9hPYsJbQT9sQ1eVmuQbMwlZWVjJhwgS8Xi95eXm1vjk3EAgwZcoU2rVrR0pKCkOHDmXJkiUJZZYtW8aoUaPweDykp6czbtw4Sq338CTj9Xpp06ZNdCsqKmLdunXcdNNNDbrFkhMfe24KrS/sSt70fDKv642rdwaoEPypgoP/2cKe2QXsX/A9VWv2YQRrj2IqaRiKotDN4+LG9tn8vU8XXM0Y1l9aRiSSpiZUBbPbNknTCmC3ttoQ9+1EcdVvud7UqVNZunQp7777Ljk5OUyfPp3Vq1czYMCAaJnJkyezbt06Xn/9ddq2bcs777zDeeedx9q1a+nRowdr1qxh9OjR3HjjjcyfPx+bzcbixYvR9fo9PJ577jl69uzJmWeeWa/ykpMPRVNxn5aF+7QsM3bJt8VUrdlHaKcP/8ZS/BtLURxmGc/AHJzdWkv/kpMA6cAqkTQyNRwMg5VNJkYOO5Yrl2Jr2+mw/iQ+n4/MzExefvllrrzySgBKSkpo3749N998M/PmzaOwsJCuXbtSWFhI27ax6xkzZgz5+fnMnj2bX/7ylxQWFvLFF180fKx+P23btuW+++7jnnvuafjFthBOdAfWIyVUbAVSW1OMXuKP5qteO57+2XgG5mBvJ5cJH29IB1aJ5HjB7oHpu49Zd9FVN8XFCEMz/Un278eWm4uamlrrl/WWLVsIBoMMHRqL/piRkUGvXr2ix2vXrkXXdXr27JlQNxAIkJmZCcCaNWuiYqahvPPOO1RUVHD99dcfUX3JyY0920Pa2M60OrcTwcIKqtbso/rbYgxfCN+y3fiW7caW5TaXEg/Ixpbpbu4hSxqAFCMSSVOjKOA4do5hCmDL8aJl5aEfKCG8vxgjECBYWIjq8WDLzT2i+CQ+nw9N01i1ahWalhg90+v1AuB2H/kD4LnnnuOiiy4iNzf3iNuQnPwoioKzUyucnVrR+qKu+DeVUrWmGP+6A4T3V1O+cAflC3fg6Gg5vvaVjq8nAlKMSCQnKYqqYsvOQktvTXj/fsIHDmBUVRHctg0tNdW0lFhm/m7dumG32ykoKKBjx44AlJaWsmnTJkaOHAnAwIED0XWdffv21enT0a9fPxYtWlTrct1DsW3bNhYvXsx//vOfo7hiSUtD0VTcvTNx987ECISp/v4AVWv2Edh8kGBhBcHCCg7+31ZcPdPxDMzG1TsT1SHD0B+PSDEikZzkKDYb9jZt0DIzzeitpaXoFRXoFRVordOx5WTj9Xq56aabmDp1KpmZmeTk5DBjxgzUuJDzPXv25JprrmHChAnMnTuXgQMHUlxczKJFi+jXrx8XXngh06ZNo2/fvtx2223ceuutOBwOFi9ezJVXXklWVladY3z++efJy8vj/PPPPxa3RHISojptpAzKJWVQLnp5nOPrLh/+DSX4N5SgODTcfTJjjq/ybcLHDVKMSCQtBNVux9GuHUZWFuGiIvTycvSDpehlB7FlZjLn0Ufx+XxcfPHFpKamcvfdd1NWVpbQxoIFC3jkkUe4++672bVrF1lZWQwbNoyLLroIMAXLxx9/zPTp08nPz8ftdjN06FDGjx9f57gMw+Af//gHEydOrDH9I5EcCVorB6lntiP1zHaE9lVRtcZ8g7BeGqBq9T6qVu8zA6v1N/1LpONr8yNX00gkjcyJstrBqKoitLcIo8qMdKqoGlp2FrbMTPkSvuOYE+XzdbwhhDAdX7/ZR/V3xRhV4eg5W7YbzwDzHTq2DHlPGxO5mkYikRwS1ePB0aWz+fK9oiIMv9+0mBw4gC0nBy09Xf5alJw01O74uo/qdSWEi+McXzu1wjMwG3ffbLSUuiL4SBobKUYkkhaMoihoqamoXq+5HLioCBEKEdq9m/D+A9hzc1BbtZKiRHJSodhU3Kdm4j41E8Mf5/i65SDBHeUEd5Rz8D9bcfVKxzMgB/epGSh2OYXYlEgxIpFIYi/ha9UKvaTEjFESDBD86SdUtxtbbhs0b/O9t0IiaSpUl42UweZL+fTygOn4+s0+Qrsr8a8vwb++BMWp4e6ThWdAtnR8bSKkGJFIJFEUVcWWlYWWnh5bDlxdTXD7NlSvF3tuLupRxBKRSI5ntFZOUs9sT+qZ7QkVVVK1xlyRo5cGqFpVRNWqItRURyzia9sUaTVsJKQYkUgkNVA0DXtuLraMDMLFxYRLSzF8PgI+H1rr1thyclAdMpCU5OTFnptC2rgUWo3tRHBHuen4unY/RkUQ3xe78H2xC1uOFfG1v3R8PVoa7DL/2WefcfHFF9O2bVsUReHf//73YessWbKE008/HafTSffu3fnHP/5xBEOVSCTHGsVux962Lc7u3dHS0gDQDx4k8OOPhPbsQYTDh2lBIjmxURQFZ+c00i/rQd70oWROOBV33yywqYT3VVP+0Q72zvmKfc98i+/LPeiVoeYe8glJgy0jlZWV9O/fnxtvvJHLL7/8sOW3bdvGhRdeyK233sorr7zCokWL+NWvfkVeXh7jxo07okFLJJJji+p04ujQASMri1BRkbkC58AB9NJStCxrObCMESI5yanp+LqfqjXFpuPr9nKC28s5+H9bcPVMx90vG3fvDFSXnICoDw2+S+eff36DoiQ+88wzdOnShblz5wLQu3dvvvjiC/785z9LMSKRnGCobjfOzp3RfT7Ce4sw/NVmVNeSEmzZ2eZyYBmjRNICMB1f25AyuA16WZzj656Y42uppkhhUk+a/M6sWLGCMWPGJOSNGzeOO++8s846gUCAQCAQPS4vL2+q4UkkkiNA83pRu6VglJcTKipCBIOE9uwhHIlRkpYmHfskLQYtzUnqWe1JPctyfP1uP9XfFRMurq4pTPpm4T41UwqTJJr8J8zevXtrvIUzNzeX8vJyqqura63z6KOPkpaWFt06dOjQ1MOUSCS1MGrUqDp/OCiKgpaWhrN7d+x5eSg2mylKdu4kuGULus/XJGNasmQJiqJw8ODBJmlfIjka7LkppJ3bidy7BpF75+mkju6ILccNujBFyZub2P3wl+x/4QcqVxdh+KXfFRwDMXIkTJs2jbKysuj2008/NfeQJBJJHSiqii0zE2ePHthyclBUFcPvJ7h9O4Ft2zCqav/RATBr1iwURamxpaTImCaSExtFUbC3MYVJm7sGk/u7QwiTf0hh0uR2ojZt2lBUVJSQV1RURKtWrXDXEa/A6XTidDqbemgSiaQRUTQNe05ObDlwSQlGZSWBrVvQ0tLM5cBJf9dTpkzh1ltvTcgbPXo0Q4YMOZZDl0iaHNNiYoqT6FTO2mLC+6qjbxUu1RRcPeKmctwtZyqnyS0jw4cPZ9GiRQl5CxcuZPjw4U3dtURyXCCEoCpU1SxbQ96DWVlZyYQJE/B6veTl5UWdzuMJBAJMmTKFdu3akZKSwtChQ1myZElCmeUFBZw7fjyZQ4bQ9mc/4+e33ML+wkICmzcT3L0bEYotffR6vbRp0ya6FRUVsW7dOm666aYG3eN//etfnHbaaTidTjp37lxj7E8//TQ9evTA5XKRm5vLFVdcET331ltv0bdvX9xuN5mZmYwZM4bKysoG9S+RNITIVE6ixcRjWkw2lFD6z03sfsSymKwqwqg++S0mDZZdPp+PzZs3R4+3bdvGmjVryMjIoGPHjkybNo1du3bx4osvAnDrrbfy5JNPcs8993DjjTfy6aef8uabb/Lee+813lVIGg8hQBhg6CB0MMJW2sozwlZ+JF1bvh5LR9swIh3E+mnM4wbVqWd5AEW1NsXaa7E8VYs7F5dv2CDshmAVqDrV4WqG/vPs2u52k1PwywI8dk+9yk6dOpWlS5fy7rvvkpOTw/Tp01m9ejUDBgyIlpk8eTLr1q3j9ddfp23btrzzzjucd955rF27lh49erBmzRpGjx7NjTfeyPz587HZbHz68ccIjweEQC8pQT94EFtmJrasrBrLgZ977jl69uzJmWeeWe9rXLVqFVdddRWzZs3i6quvZvny5dx2221kZmYyceJEvv76a26//XZeeuklzjjjDEpKSvj8888B2LNnD+PHj2fOnDlcdtllVFRU8PnnnzdIxEkkR0PtFpP9hPdVtSiLiSIa+Fe3ZMkSzj675hfr9ddfzz/+8Q8mTpzI9u3bE34tLVmyhN/97nesW7eO9u3b8/vf/56JEyfWu8/6voL4mCOE+aDVg9YWakC6IWVrSUdFQrIAOJR40JOEhG6KhIR6enPf1RMev7cD20bMpUu7bFw2hSo9wNBPJzXLWApGL8BjdwOKKZrq2Pt8VWT2HMzLz/yJKy+9CBQoKS2j/WlDufn6a5j32IMU/rSbrv2HU7jua9q2zYvWHXPRFeQPPp3ZD/6eX95wM4U/7eSLTz+q0Yfh9xM+UILh94Mwp3W0jExrObCGPxCgbbv23Hfffdxzzz11XlPkO6i0tJTWrVtzzTXXUFxczMcffxwtc8899/Dee+/xww8/8Pbbb3PDDTewc+dOUlNTE9pavXo1gwYNYvv27XTq1Knx/wGaAL/fz7Zt2+jSpQsul4z6ebISKqqkeu1+qr4zhUmUE0yY1Pf53eCrGDVq1CF/NdQWXXXUqFF88803De2q6Vnyv3Bg89GJh5aGopkWAdVmpdW4tBZ3PpK2JVoQzEasXSMfH7LM4c7XdixilqLkLSL4hCXm4i1KrmxQ7eamqbhVOwWjF1jt1malqcUi00i4FbVen9MtmzYRDAYZ2qcLVJcAkOGEXl07QagKfPtYu2oFuq7Tc+AZCXUDwRCZqU44uIM136zmyovGQMnWGn2ogMMJRN1GwhDaDft2A/DOvz+koqKC68cNgj3fxaxRKLHPj6JA2S6zeukOEAdZ//23XHLBWDPfqjPi9NOYN28eenkR5444nU4d29O1axfOO3cM540dw2WXXoLHk0L/U3sy+pyz6du3L+PGjmXsuedyxZVXkp6RcWQ3XCJpJOy5KdhzU2g1plNMmKzdT7goyWLSvbUZx+QEECaH4sQdeWOweRHsXNm4bWpO0Byg2a19fLq2vCMpa08UAAkioA6RoNriphaSREI0nZyvJQkNtebDXVITvx+2bYOsLuByoQD1myhJIn7aSFj7hOPa8kRiWhhxbYm696llZjlvG2jVNpav2sDhgZRsfLqGpmmsWvJfNFWzyhggwJviAYcXt9sDqgPsnkP2KaJCT0Q/Us+9+g4XjTmT3OwMS+DVcV9C1q9EfxlUWwIwVAWV+2JlqkvMvsp+IlXTWP3eP1iyfBUff7aCmbMeZNaDD/HV+y/TOi2VhS/+keVff8vHS1fwxPw/MmPGNAr++yJdOnUgUQhFhFEkL36KLj7vUFtd5eTflaRuDilMNpbi31gaEyZ9s3GfmoHqsTf3sBtEyxYjQ2+B0y5roEg4RFrV5JeKpPGIt9I08ceqW5/B2O12Cr7fQsfepwNQWlrKpi3bGHnOGEhrz8AR56LrOvv89jp9OvqdPoRFX67hwexeh+wvcjnCMAiXlLD52zUsXv41bz3xF/zlDrS0NLTWaaiaGrM6RcSV11rq36ottEqld+/eLFu9HlJyomWWfbORnt26onkyAAObQzBm9DmMOWcUD0y9ndY9h/Hp8tVcfsE5KIpgxJABjBgygJm/u5lO+RfyzgeLueuWa61BHoupy0OIlOS8kGEKsVUvgE0Bu9vaPHXsrbTNKb+fTgIShMm+Kqq/Kz4phEnLFiN9rzh8GYmkBeD1ernpppuYOnUqmZmZ5OTkMGPGDNS40O49e/bkmmuuYcKECcydO5eBAwdSXFzMokWL6NevHxdeeCHTpk2jb9++3Hbbbdx66604HA4WL17MlVdeSVZWVo1+FVXFlpXFy4uXkNemDeeNHoMIhwkfOEi4pMxcEpyVhRrvG+Gy5p1TssDbmrvvu58hQ4bw8F+e5+qrr2bFihU8+dyLPP3005DZlf/+979s3bqVs846i/T0dN7/cDGGYdBr2LkUFPpYtGgRY8eOJSc7m4Ivv6S45CC9h4yEnFNrCqEax8lbZLqutnNJ5TDi7oSwrEH1ED5hYYqRFU+AryExmBRwpMRtXmuLP7bSzrrOJe3tHtMKK2kW7Dke7GM6nRTCpGWLEYlEEuXxxx/H5/Nx8cUXk5qayt13301ZWVlCmQULFvDII49w9913s2vXLrKyshg2bBgXXXQRYAqWjz/+mOnTp5Ofn4/b7Wbo0KGMHz++zn4Nw+CFF15g4g034O7Vy3wJX3ExRlUV+sGD6AcPoqWmomVloXpqTnidfvrpvPnmm8ycOZOHH36YvLw8HnrooaiTfOvWrXn77beZNWsWfr+fHj168Nprr3Haaaexfv16PvvsM+bNm0d5eTmdOnVi7ty5nH/RzxvvxtaFSBI49doEBILgrIZeF0H1HghVm9NUoera00ZkKbWAoM/cGhN7vIBJqUXE1CF4HN7a69hTpMA5AhomTCzn1+NImDR4NU1zcNyuppFIakGudmgcjKoqwvv3o8e9m0p1e7BlZ6GmprbYd980+POlh+JEShUEfBCstLbktK+W/EoIVCQeB300hcN1FLsnJlCcXnC2Amdq0tbqEPmppgXN5mrxU1OhfVXWqpxiwkVxq3JUBVePphcmTbaaRiKRSI4FqseDo2NHjEDAFCUHD2JUVxEsLERxOLFlZaK1bi3fEnw4Ik7vrkb8ISeEKXASBEySiAnUda4OwRP0xRyuI8LpaGPPqbaaIqXGcR2CxhWXb/ecsKLGnuPBProjrUZ3jAqT6rXFhPbGWUzUzTi7tybt3E44OqQevtEmQIoRiURyXKM6nTjatUPk5BA+UIJeUoIIBgjt3k143z60zExsGRk1AqhJmhBFMVdZOTxATuO0GRU4yYLFB/5y0zqTsJUn7ZM2rDhQ1aXmdjQoai3CpS5xY1llXGmxzZlm5mnNOy1yKGES2FQKY5sv1o4UIxKJ5IRAsduxt8nFlp2FXlpK+MABRChEuKgIvbgYLSMDLTMT1X78zINLGkCCwMk+urYMA0LW9JL/UKKlvG4xE8mP+Ov4y8ztaLCnJIqUZNGSIGBagat1Yp7NcXT9xw8lXpgUV+HfUIq9nbfR2m8oUoxIJJITCkXTsGVloWVkoJeVoe/fH53KCR84UPsKHEnLQlVjVopWbY+8HSFiPjM1LDKHsM74y0wRFBEwIWu+KVRpbhW7j2w8Nnc9BEzkuHVN0VOHD40924M9+4iiITUaUoxIJJITEkVVsaWno7VufdgVOC3V2VVylCiK5UDrBfKOvB09ZImUgzGBEt3Ka8mztkB5bA8QrgZfNfiKjmwcmuPQAmbwjZDR5civ8yiQYkQikZzQKIpiCo/U1IQVOHpFBXpFhVyBI2l+NDt4MsztSDD0mDA5nIiJljuYWBZhvhqistjcaqP3z6UYkUgkkqNFrsCRnJSoGrjTze1IMAzLEfgwFpi09o077gYgxYhEIjnpkCtwJJI4VNXyG2kFdGju0dSKFCMSieSkRa7AkUhODKStUiKR1MmoUaO48847m3sYCSxZsgRFUTh48GC960RW4Dh79MDerh2q02m+pG//fgKbNhHcuRPD72+6QUskkkMixYhEImk2Zs2ahaIoNbaUlJQm6S+yAsfRvTuOTp1QPSkgBPrBgwQ2bya4Ywd6ZSVN8ZaMzp07M2/evEZvVyI5GZDTNBKJpNmYMmUKt956a0Le6NGjGTJkSJP221grcIQQ6LqOzSa/SiWSo0FaRiSSJkYIgVFV1SxbQ37hV1ZWMmHCBLxeL3l5ecydO7dGmUAgwJQpU2jXrh0pKSkMHTqUJUuWJJRZtmwZo0aNwuPxkJ6ezrhx4ygtrT0ct9frpU2bNtGtqKiIdevWcdNNNzXoHv/rX//itNNOw+l00rlz5xpjf/rpp+nRowcul4vc3FyuuOKK6Lm333+fQRdeSMaQIbQ/80wunDSJigP7CRYWEvhxM+GSEoRhvjMlMkX0wQcfMGjQIJxOJ1988QVbtmzhkksuITc3F6/Xy5AhQ/jkk0+ifYwaNYodO3bwu9/9Lmr9ifDFF19w5pln4na76dChA7fffjuVlUf7UhaJ5MRCynmJpIkR1dVsPH1Qs/Tda/UqFE/9IitOnTqVpUuX8u6775KTk8P06dNZvXo1AwYMiJaZPHky69at4/XXX6dt27a88847nHfeeaxdu5YePXqwZs0aRo8ezY033sj8+fOx2WwsXrwYXdfrNYbnnnuOnj17cuaZZ9b7GletWsVVV13FrFmzuPrqq1m+fDm33XYbmZmZTJw4ka+//prbb7+dl156iTPOOIOSkhI+//xzAPbs2cP48eOZM2cOl112GRUVFXy2ZAlaVhZKIFBjBY6wruO+++7jj3/8I127diU9PZ2ffvqJCy64gD/84Q84nU5efPFFLr74YjZu3EjHjh15++236d+/PzfffDOTJk2Kjn3Lli2cd955PPLIIzz//PMUFxczefJkJk+ezIIFC+p9DySSEx1FNMXkaCNT31cQSyTHA8mveDeqqppVjKj1ECM+n4/MzExefvllrrzySgBKSkpo3749N998M/PmzaOwsJCuXbtSWFhI27axENtjxowhPz+f2bNn88tf/pLCwkK++OKLBo/V7/fTtm1b7rvvPu655546yy1ZsoSzzz6b0tJSWrduzTXXXENxcTEff/xxtMw999zDe++9xw8//MDbb7/NDTfcwM6dO0lNTXwj6erVqxk0aBDbt2+nU6fEl4QJXU9YgQPw+ddfM+6GG3j7rbe47Be/OOT19OnTh1tvvZXJkycDps/InXfemeAQ/Ktf/QpN0/h//+//RfO++OILRo4cSWVlJa5aQtonf74kkuOZ+j6/pWVEImliFLebXqtXNVvf9WHLli0Eg0GGDh0azcvIyKBXr17R47Vr16LrOj179kyoGwgEyMzMBGDNmjVRMdNQ3nnnHSoqKrj++usbVG/9+vVccsklCXkjRoxg3rx56LrOueeeS6dOnejatSvnnXce5513Hpdddhkej4f+/fszevRo+vbty7hx4xg7dixXXHEF6enptb4DJ/LbrW96OsGfdqJlpKN6PFRWVjJr1izee+899uzZQzgcprq6msLCwkOO/dtvv+W7777jlVdeieYJITAMg23bttG7d+8G3QuJ5ERFihGJpIlRFKXeUyXHMz6fD03TWLVqFVpSsDCv13zbp7ue4qc2nnvuOS666CJyc3OPapzJpKamsnr1apYsWcLHH3/MzJkzmTVrFl999RWtW7dm4cKFLF++nI8//pgnnniCGTNmUFBQQJcuZljs+Hfg2H78EYAUlwu97CB62UEUh5O7Zv+BRZ9/zh//+Ee6d++O2+3miiuuIBgMHnJsPp+PW265hdtvv73GuY4dOzbqfZBIjmekA6tEIqFbt27Y7XYKCgqieaWlpWzatCl6PHDgQHRdZ9++fXTv3j1ha9OmDQD9+vVj0aJFDe5/27ZtLF68uMGOqwC9e/dm2bJlCXnLli2jZ8+eUdFks9kYM2YMc+bM4bvvvmP79u18+umngCkWR4wYwYMPPsg333yDw+HgnXfeqdGPoiholqh0du6Clp4OqooIBli+bBnXXHABFw4ezKldupCbm8v27dsT6jscjhq+M6effjrr1q2rcT+7d++Ow9F4r4uXSI53pGVEIpHg9Xq56aabmDp1KpmZmeTk5DBjxgzUuHe49OzZk2uuuYYJEyYwd+5cBg4cSHFxMYsWLaJfv35ceOGFTJs2jb59+3Lbbbdx66234nA4WLx4MVdeeSVZWVl19v/888+Tl5fH+eef3+Cx33333QwZMoSHH36Yq6++mhUrVvDkk0/y9NNPA/Df//6XrVu3ctZZZ5Gens7777+PYRj06tWLgoICFi1axNixY8nJyaGgoIDi4uLDTo+oHjeO1q0Rbdqgl5XRvWtX3v3kEy4YORJFUXj4qacwdD26CgdMn5HPPvuM//mf/8HpdJKVlcW9997LsGHDmDx5Mr/61a9ISUlh3bp1LFy4kCeffLLB90IiOWERJwBlZWUCEGVlZc09FInksFRXV4t169aJ6urq5h5Kg6ioqBDXXnut8Hg8Ijc3V8yZM0eMHDlS3HHHHdEywWBQzJw5U3Tu3FnY7XaRl5cnLrvsMvHdd99FyyxZskScccYZwul0itatW4tx48aJ0tLSOvvVdV20b99eTJ8+vV7jXLx4sQAS2nzrrbfEqaeeKux2u+jYsaN4/PHHo+c+//xzMXLkSJGeni7cbrfo16+feOONN4QQQqxbt06MGzdOZGdnC6fTKXr27CmeeOKJBvUthBDbtm0TZ48cKdwul2jfpo340/Tp4szBg8Vvrr1WBHbsEOHycrF8+XLRr18/4XQ6RfxX78qVK8W5554rvF6vSElJEf369RN/+MMf6hzDifr5krRM6vv8lqtpJJJGRq52aNkIXTcDqJWUYFRXR/MVux0tPR0tPf2o3oUjP1+SEwm5mkYikUiaAUXTsKWnY0tPx/D70UtK0csOmi/o27eP8L5itFQvWkYGqtd7yAivEklLQYoRiUQiaSJUlwu1bR62Nrkxa0lVVTTsvGK3o7VOR0tvjSodViUtGClGJBKJpIlRVBVb69bYWrc2rSWlpegHLWtJ8T7CxftQU1Oxpacf9n04EsnJiBQjEolEcgxRXS7UvDxsuZa1pLQUo7ISo6KCYEUFis0W8y2R1hJJC0GKEYlEImkGEqwlgUDMWhIOEy4uJlxcjOr1xqwlqgwLJTl5kWJEIpFImhnV6URt0wZbTg5GRQXh0lIMnw/D5yPo85nWktatzUBrEslJiBQjEolEcpygqCpaWhpaWhpGMGhaS0pLTWvJ/v2E9+8n5HJhVFdjBIMgl/ZKThKk3U8ikUiOQ1SHA3tuLs5evXB07IhqvXHYqKpCLy1lx3UTKPrfxwhs3drMI5VIjh4pRiQSieQ4RlEUtFatcHbqhLNnT7SMTFA1jPJySv7xD7ZecCHbr72Wsv/8B8Pvb+7hSiRHhBQjEomkTkaNGsWdd97Z3MOQWKgOB/asTOy5ObR5cBbec84BTaP661XsvudefjxrJHv/MBt/3AsOJZITASlGJBJJs/LRRx8xbNgwUlNTyc7O5he/+EWNN95KklAUUvLz6fD0U3T/dBHZd9yOvW1bjPJySl96iW0/v4Tt/zOeg/96G6OqqrlHK5EcFilGJBJJs7Ft2zYuueQSzjnnHNasWcNHH33E/v37ufzyy5t7aCcM9txcsn79a7p9spAOf/sbqWPHgs1G9Zo17Jkxgx/PGsmeBx/Ev359cw9V0owIIQiFSvH5NnLgwGfs3v0W27Y/xYaND/Dtd7fw1VeXUV39U7ONT66mkUiaGCEE4aBx+IJNgM2h1juaZ2VlJb/+9a95++23SU1NZcqUKTXKBAIBZsyYwWuvvcbBgwfp06cPjz32GKNGjYqWWbZsGTNmzGDlypU4nU7y8/N5/fXXSa9lWeqqVavQdZ1HHnkE1YqjMWXKFC655BJCoRD2o3ihXEtDUVW8Z/4M75k/I1xczMF//5uD/3yLUGEhB197nYOvvY6zd29aXXA+rc4/H0f79s09ZEkjEQ77CAT2EQgWEQzsIxDYax3vIxAoIhDYRzBYhGEED9mO378Ht7vDMRp1Ii1ajPz4VRFVFUE0m2pudiWWjt9qyVdtCppdRVUVGbpZckjCQYNn71jaLH3fPH8kdqdWr7JTp05l6dKlvPvuu+Tk5DB9+nRWr17NgAEDomUmT57MunXreP3112nbti3vvPMO5513HmvXrqVHjx6sWbOG0aNHc+ONNzJ//nxsNhuLFy9G1/Va+xw0aBCqqrJgwQImTpyIz+fjpZdeYsyYMVKIHAW27GyyJk0i86abqFq5koNvvkn5wk8IrF9P8fr1FM/9E65+/Uxhct552Nu0ae4hS2pB1wMEo4KiKCouTMFRRCBoCg1dr6x3m3Z7Ok5HDg5nDk5nG5zOHJyOXJzOHFJSujfh1RwaRQghmq33elLfVxA3lH/N+Zq9W8uPrhGFOJESJ1rsNfPUJHFjs6modvUw9WvPVzUFVVPi0mrs2KZIkdSMJL/iPRTQj3sx4vP5yMzM5OWXX+bKK68EoKSkhPbt23PzzTczb948CgsL6dq1K4WFhbRt2zZad8yYMeTn5zN79mx++ctfUlhYyBdffFHvMS5dupSrrrqKAwcOoOs6w4cP5/3336d169YNvt6WQPLnq76ES0upWLiQ8vc/oGrlSjBi1jr3oEG0Ov98Wo0biy07uymGLYnDMEIEg/sJBPcRtCwXtVkzwuGD9W5T07ymsHDmRsWFI3Js5Tkc2Wias+kurBbq+/xu0ZaR9r0z8Ga40EMGelighw2MsIEe3YR1LjFPGHH6TWCWCTWPGf5Q1CZYNFuScLHKxJ/TNAXVOqdFhI5NQbPqxc5F8mvmRdtJPqcpKKqVr8bGEt2sc8pJJKZsDpWb549str7rw5YtWwgGgwwdOjSal5GRQa9evaLHa9euRdd1evbsmVA3EAiQmZkJwJo1a6Jipj7s3buXSZMmcf311zN+/HgqKiqYOXMmV1xxBQsXLjxpPgPHA7b0dNKvuor0q64iXFxM+ccfU/7+B1SvWhXdimbPxpOfT6vzzyd17LnYZMTXBmH6ZZTELBnJ1oygmRcMHgDqZwdQVQdORxtLWETERpxVw2mKDJvN27QX18S0aDEy9OKuR1TPMEzhEhUqoTjxEi9cQgZGcl7YQA/VkhcWcXVqyU/qx9ANDF2g6wIjbKZrjFMXGHrz+SscLRFhomoKSkQUqcnCpXYxo2oqimoKJSVOcKlqzXLRPqw8zaob32a8gEo+Z9aNtR02ghi6QTikE9YMFMUUhpj/gfWAjTxnT5QHrs/nQ9M0Vq1ahaYlWlu8XvOL0O12N6jNp556irS0NObMmRPNe/nll+nQoQMFBQUMGzbs6AcuqYEtO5uMa64h45prCO3dS/mHH1L+wQf4v/2Oqi+/pOrLL9n70EOknHGGKUzGjEZrRKv0iYgQhmnNCOzFH9hDwL/XSpv7gN9MC3Fov4wIiqLhcGTXEBeOuGkTpzMXmy3thPmOOBpatBg5UlRVQXVo2B31m4s/FgghMAwRFT+mELEES/Q4ltZ1UygZuiVuDCOpblJZS/To1jmjtnYifUbaMURMOEX2hoi2H0knWJriMAyzDKFjfDOPEleaSt+L0yhzV1Nlq91XojaiXzhR0WL+L/o9pIASPUlcvhJXPpKvJJU5dN02We2x2+18tvgLLr/sCgAOHixl06ZNjDjjZ/h9QU7t1Qdd1/mpcDdnjvhZjb6D/jB9TuvDJws/4f4ZMxPHVEfflZWVqKqKECJ6/RGhYxgnpog+0bC3aUPmxIlkTpxIcOdOyj/4gPIPPiCwbj2Vn39O5eefs/cBOylnnkmr88/He/bZaN6U5h52o2IYYYLB4iRxsSeWDuwlEChCiHC92rPbM3E546wZceLC6czF4czFYU9HUY6fZ0hzI8XISYKimFYATaPeDovHC1EhpQtEglCJCSMzz6ghZOLLiPi8eNFziPrCKq8btfctDJHQVsKxEddnpL4hsKeAohKdahLmRdbrPpiJeAPusXHpUrDzy6uuY/qMabgdqWRlZvPo4w+jKCrBap3yA35y0zvwi0uv4sYbJ/Lg/X+gz2n9OHDgAJ8vW8Kpvftw7jnjuPWGOxh13nBuvukWJlxzIw67g2UrPuPiCy8jMyOzRr8jhpzNvHnzuO/u+7ns51fgq6xg9uMP0aF9R9pnd6f4p4qYuEoQaU0nzGLtx04m1q0tv45+k8dcQ3AeX1YyR/v2ZE2aRNakSQS2baP8gw+o+OADAj9uxvfpp/g+/RTF6cQ7ciStLrgA78izUBtoDTvWGEaQQKCYQGBPTGzUEBr7gPqIX9USFW1wOtvgcrbB6Yqk86LWDVV1NPVlnXS0aAdWiaQpqMvBsIbYsI6jf4ECRJwSif1liqQytdUVVn58XZEobOpq38r3Vfi46547+L/33sWb4mXyr2/no08+ou9pfXn04ccBCAaD/HHeY7zxz9fYs3c3GRmZDD59CPfePYNTTzkNASxb/gV/mDOL79auweV0c/rAQTz7xAJapaXVqq3e+c9bPPX/5rNl2xbcbjeDB+bz+/sepEf3njULtxAOZSULhgPs2v0TO1YE0f1KbDoyfioxMoWoxk1TRo/VmtOadU55mlOWxv4i/N+uwb96Fca+vSjCQBE6qsNOysABeM8YRsqggWhOR93TqPHTro3kE6brgThBEbFq7IlOmQQCewkG91MfUa8ommnBSBYXLkt0ONvgcGSjqnKVV0Oo7/NbihGJpJE50tUOLYU6RVn0f7WVOXTdhGStwiwuP1q/bmFWZ91o9/UoYx3UJSSPlFA4yK49P7H2/8rwl524U1k1hFKyX5cthN1TguYuxeYqQXOWoDpLUB0lqI4DKLYSFFtZ/ToTdlSy0JRsNCUHm5qDTcvBpuXisOVit+dit2Wg2Wx1OPjHOf4nibaTydm+KZCraSQSyXFJjV/9tLwv8qOxklX7VdyVDs657hQUYUuYOqyRTpp6rJmXOOUpLKd4YdScskxuyzAEeqWfsK8SvcqPIUAoKkLREKqG0OxmulbtJVDs5dg9B7B7SrCllGD3mJstkueqqNe9NMIOwtWtCVWlE65OJ1SdTjiStvZ6wEvdAcd1YLe1HRmRVYNanHCpbeVibSsbNVt83biVi3ErGBPqJ61s1JL2CSsdk/qNX9F4vCHFiEQikRxjjkaQ6cKGza6S16X1cWN5E4ZB9erVlL//AeUffUSofD9GOoQzBKJDCtrpnaFra0IpAXMaJbinXqtOFMWFTc1FU3KsLRuVbBQjG0Vkg56JULwIp8CwCYwUkeh0ryeLqchqxJr5CQ73tdSNtFnbjI9ZRqd+7q3Nj6oqCWIlIorGTepDTqfmmX2QYkQikUgk9SayxNXv340/sNvc+3cTcOzGf/5u/Gf7CYXil8CVAd+aBoiEGJMKTmeu6Zvhaosrsjlj6eNxWWtt1qLkFYzxKw0TViPGr2BMWu2YvI+uXkze64doJ1yzXz1s1BBQhiEwgjXDPohmnPWTYkQikUgkUXS9Cr9/D37/rpqCw78Hf2APQhx+vb2mpeBytsVW7UYp9GF8vwe1KIhWoqCVKLhS2pE27nxSzz8f16mnHneioy5MR2ANTiA/VjPsg5EQl6o2EZSe52m2MUoxIpFIJC0E06pRHBUXNYXGbkKh0nq0pJpWjVqsGU7r2GZLTRAYRjBI5RdfUP7e+1QsXky4ZDcHnvs7B577O/ZOHWl1wQW0Ov98XD1b7iqqpiISG+t4fuAfz2OTSCQSSQMQQicQKKK6eid+/06q/bvw+3firzbTgcDeelk1bLZUXM62semTOLHhcrXF4chBVRv2+FAdDlLPOYfUc87BqK7Gt/Qzyj/4AN+SJYR2FHLgr89w4K/P4OjezXxPzvkX4Oza5UhvheQEQy7tlUgaGbm0V9JUCCGorq5g27atpKYWEtZ3JImNPYeNEqoomhVHI86S4WqLy5kX56uReoyuCHRfJb7Fiyn/4AMqP/8cEedv4uzdm1bjxuIdORLnKaecMFM5khgyzohE0kxIMSI5UoQQCBHCMEIYRhAhgnHpkPW2V4OfftrHwbIHMYyay1EVxY7L1Ra3qz0uVztc7vaxtKstTmfucRuGXC8vp+KTRaYwWbECwjFhZcvNxTtyJN5RI0kZNgzV03z+DZL6I8WIRNJMSDEiqYv6iI3DRQsNBgU7d5ZgGO/gdnsSxYa7PU5H9nErNhpCuLSUioUL8X26mMovv0T4/dFzisOBJz8/Kk4cHTo040glh0KKEYmkmTiZxMioUaMYMGAA8+bNa+6hRNm+fTtdunThm2++YcCAAc09nAQaQ2yAgqraUVUHimLu49OBQDh6D070z1d9Mfx+qlauxLdkKb6lSwnt2pVw3tG1qylMRo7EM+h0FPsJtNTlJEdGYJVIJCcEH330EQ888AA//PADLpeLs846i7lz59K5c+fmHloNTLERxjCCRy02FNWOqlhCI5q2oyj2Q/pGKEr93wR9sqC6XHjPOgvvWWchxP0Et2zBt3QpviVLqVq9muDWrZRs3UrJggWoXi8pI0aY4uSsM7FlZTX38CX1QIoRiUTSbGzbto1LLrmEu+66i1deeYWysjJ+97vfcfnll7N69epmGZMQelRgxASHtYlgPd4tc3RiQ3JoFEXB2b07zu7dybzpJvTyciqXLTOtJp9/jl5SQsVHH1Hx0UcAuPr0iU7nuE47DUWtKyy8pDmR/yoSSRMjhCDk9zfL1pBZ2MrKSiZMmIDX6yUvL4+5c+fWKBMIBJgyZQrt2rUjJSWFoUOHsmTJkoQyy5YtY9SoUXg8HtLT0xk3bhylpbXHrli1ahW6rvPII4/QrVs3Tj/9dKZMmcKaNWuSongemqVLl5Kfn4/T6SQvL4/77ruPcJzz41tvvUXfvn1xu91kZmYyZsw5lJUVEQyW8PHHbzN48ABSUjy0bt2K4cMHs379UqqrdxAI7CEYPEA4XIFhBKJCRFUdaLYU7PZ0M96Guz0eT1e83l6kpp6G19uLFE9X3O72OJ05OOzp2Gwp1nSLFCKNidaqFa3OP5+2j/0vPb74nM5vvE7Wbb/GdeqpAPi//579Tz3F9iuv4sezRrJ7+gzKP/oY3edr5pFL4pGWEYmkiQkHAvzl+iuape/bX3gLez39CqZOncrSpUt59913ycnJYfr06axevTrBL2Py5MmsW7eO119/nbZt2/LOO+9w3nnnsXbtWnr06MGaNWsYPXo0N954I/Pnz8dms7F48WJ0vfaphUGDBqGqKgsWLGDixIn4fD5eeuklxowZg72e8/67du3iggsuYOLEibz44ots2LCBSZMm4XBo/P7397Br10+MHz+eRx65j4suOpvy8oMsX76Kysrt6LqDq66ayIQJl/Pcc7MJhUKsWrUWVdXQNDeK6ohaN+J9N6SgOD5RVBV3//64+/cn+/bbCe3bR+Vnn+FbupTKZcvR9++n7O23KXv7bbDb8QwaFPU1cXTpLP9dmxHpwCqRNDLJDqwhv/+4FyM+n4/MzExefvllrrzySgBKSkpo3749N998M/PmzaOwsJCuXbtSWFhI27Zto3XHjBlDfn4+s2fP5pe//CWFhYV88cUX9R7j0qVLueqqqzhw4AC6rjN8+HDef/99WrduXWv5iPPmqlUr6devN/ffP5N33vkP33yzyPLbCPLss68wa9Y8fvppOd99t4GRI/+HtWs/pGPHyLjNqZSDB6vo0OF0Pv7434waNcoSGw4z3PdxysnkIH0sMYJBqr/+OuprEtyxI+G8vWPHmBNs/hBUh6OZRnpyIR1YJZLjBJvTye0vvNVsfdeHLVu2EAwGGTp0aDQvIyODXr16RY/Xrl2Lruv0TArXHQgEyMzMBGDNmjVRMVMf9u7dy6RJk7j++usZP348FRUVzJw5kyuuuIKPP/4wKi4i/hrCCFJZuRWAqqrtVFW5+OGH7xgypA/hcOwtbMOGDcTnq2Lv3jIGnp7P2WefyRlnXMHYsWM499yxXHnl1WRkZOD1wsSJE7n44qs599xzGTNmDFdddRV5eXn1vgbJiYHqcJByxhmknHEGudOmEdy+3RQmS5dS+dXXhAoLKX3pJUpfegnF4yFl+HC8I8/CO3Ik9tzc5h7+SY8UIxJJE6MoSr2nSo5nfD4fmqaxatUqNC3RcuD1egFwu931bk8IwZNP/oVWrVJ55JH7LGfRTJ599mF69TqLxYtfZ8iQ/jXqmStWwLRumFYMRXXidLaJTqWkpJhlPJ7OpHo7smjRUpYvX87HH3/MU0/9ld///gEKCgro0qULCxYs4Pbbb+fDDz/kjTfe4P7772fhwoUMGzbsyG6U5ITA0bkzGZ07k3H99ei+SipXLDeFydLPCBcX41u0CN+iRYAZCTYiTNz9+qFox6/l7ERFOrBKJBK6deuG3W6noKAgmldaWsqmTZuixwMHDkTXdfbt20f37t0TtjZt2gDQr18/Fllf4GAKDsMIEg77CAYP4PfvoapqBz7fJip8P1BWtgsI4vfvIhgsJhQqA0whYRgCRTF9N+z2NByObFyudrjdZoCrlJRueL296NNnMF+t/BaHIwu7PQ1Nc7N8+ZekpqbSvn17wBSEI0aM4MEHH+Sbb77B4XDwzjvvJFzbtGnTWL58OX369OHVV19tqlstOQ7RvCm0Ovdc2j7yCN0/W0rnf71F1u2/xdW/HygKgfXrOfDM/2PH+F/y48/OZNc991D23nvoZWXNPfSTBmkZkUgkeL1ebrrpJqZOnUpmZiY5OTnMmDEDNW4ZZM+ePbnmmmuYMGECc+fOZeDAgRQXF/PJJ5/Qt++pnH/+aO6++1YGDTqLm2++jhtvvBKbDT77bCWXXTaWzMz0Gv2OHXsWTz31Eo8//jxXXX05lb4gDzzwKJ06dWTEiMvweLw16ths5nRMxNnwtttuY968efz2t79l8uTJbNy4kQceeIC77roLVVUpKChg0aJFjB07lpycHAoKCiguLqZ3795s27aNZ599lp///Oe0bduWjRs38uOPPzJhwoQmutOS4x1FUXCfdhru004j+7bbCJeU4Is4wX6xDL20lPL//B/l//k/0DTcAwdEfU2cPXpIJ9gjRZwAlJWVCUCUlZU191AkksNSXV0t1q1bJ6qrq5t7KA2ioqJCXHvttcLj8Yjc3FwxZ84cMXLkSHHHHXcIw9BFOOwXlVUHxIwZU0SnTh2E3W4Xbdpki4suGi2WL39LlJV9J8rKvhPvvfe8GDp0gHA6HSItLVWMHj1C/PTTV6Kycpuort4lAoH9IhQqF7ruF4ZhiNdee00MHDhQpKSkiOzsbPHzn/9crF+/vs5xbtu2TQDim2++ieYtWbJEDBkyRDgcDtGmTRtx7733ilAoJIQQYt26dWLcuHEiOztbOJ1O0bNnT/HEE08IIYTYu3evuPTSS0VeXp5wOByiU6dOYubMmULX9Sa910fDifr5OhkwgkHhKygQe+fMEZsvvFCs63VKwrbp7LPF7lmzRPmiT0W4vLy5h3tcUN/n9xGtpnnqqad4/PHH2bt3L/379+eJJ54gPz+/1rL/+Mc/uOGGGxLynE4n/rj3DBwOuZpGciJxoq52EMKwgn0Fos6ihhGIOpAeEkWxlsA645bBOuVS2CbgRP18nYwEd+7Ct3QJvqVLqSpYiQgEYidVFVfv3niGDsWTPwTP4MFo3pqWvpOdJltN88Ybb3DXXXfxzDPPMHToUObNm8e4cePYuHEjOTk5tdZp1aoVGzdujB7LLyaJpHkwBUckomiy6DhMkDFFQVVqig0pOCQtFUf7dmRccw0Z11yDUV1N5ZdfmsJkxZcEd+zA/8MP+H/4gZLnnzfFyWmnkTI0H09+Pu7TB6F5U5r7Eo4bGixG/vSnPzFp0qSoteOZZ57hvffe4/nnn+e+++6rtY6iKFEHN4lE0rTEBEcgblmsmRaHERyKolqBvmqzcNik4JBI6kB1u0k9+2xSzz4bgNDevVR99RWVBQVUrfyKUGEh/rVr8a9dy4Hn/g6ahqvPaaTkD8WTn4/n9IGoKS1XnDRIjASDQVatWsW0adOieaqqMmbMGFasWFFnPZ/PR6dOnTAMg9NPP53Zs2dz2mmn1Vk+EAgQiDN3lZeX11lWImmJCGuVSkxwBOIsHYcXHOb7Upxx0UWl4JBIGhN7mzakXXwxaRdfDEBozx6qVq6kcuVKqgpWEtq5E/+33+H/9jsO/O1vYLPh7tPHFCZD8/EMHIjq8TTzVRw7GiRG9u/fj67r5CYFgMnNzWXDhg211unVqxfPP/88/fr1o6ysjD/+8Y+cccYZ/PDDD9Fld8k8+uijPPjggw0ZmkRy0iES3hAbSBIeQQ71dlhF0WJTKEmiQ1E0KTgkkmOMPS+PtEsuIe2SSwAI7dpF5cqvqFq5kqqCAkK7d1O9Zg3Va9Zw4NlnwW7H3bcvnvwhpAwdinvAANQGxPE50WiQA+vu3btp164dy5cvZ/jw4dH8e+65h6VLlybEKKiLUChE7969GT9+PA8//HCtZWqzjHTo0EE6sEpOCBrqYGi+JbY2wRFACKPuiopiWjSiUyrOOD8OuWr/ZEU6sJ6cBHfuoqqgIGo9Ce/Zk3Besdtx9e9HSn4+nvyhuAf0Rz0B/v2bxIE1KysLTdMoKipKyC8qKqq3T4jdbmfgwIFs3ry5zjJOpxNnPcNYSyQnAtFpFREvOurnx6Gq9jih4YyzcEinUYnkZMHRvh2O9pfT+heXm2/63rnTFCYFBVQVrCRcVET116uo/noVPP1XFIcDd//+0Wkdd//+qCfwc7NBYsThcDBo0CAWLVrEpZdeCoBhGCxatIjJkyfXqw1d11m7di0XXHBBgwcrkRzPCCEIhUooL9+GrkMgsA/DEA2YVkkUGzE/DhkoWSJpSSiKgqNDBxwdOtD6F78wv1sKC6P+JlUFBYSLi6n66iuqvvoKnnrKFCcDB0andVz9+p1QL/trsC33rrvu4vrrr2fw4MHk5+czb948Kisro6trJkyYQLt27Xj00UcBeOihhxg2bBjdu3fn4MGDPP744+zYsYNf/epXjXslEskxQterzZe0VW+jqnKrua8yt3C4HFVtS+u0BwiFHImWi4RYHMnCQ06rSCSS2lEUBUenTjg6dSL9yisRQhDcvp2qlV9RVVBA5Vcr0Yv3m9M8BQXsf+JJFKcT98CBsaXEffuiHMfipMHfgFdffTXFxcXMnDmTvXv3MmDAAD788MOoU2thYWFCCOnS0lImTZrE3r17SU9PZ9CgQSxfvpxTTz218a5CImlkhDDw+3dRVbWVqqptVFZto7pqG5VVWwkE9hyipoLTmYuqOrHbW+NyeaLCQ06rSCSSxkBRFJxduuDs0oX0q68yxcm27VSttHxOClaiHzhA1ZdfUvXll2YdlwvP6QPxWEuJ3X37oNjtzXwlMY4oAuuxRkZglTQVhhGgqmo7lZWbqazaSlXlZiqrtlBVtRXDCNRZz2ZLw+PpSoqnCx5PFzyerng8XXC7OxEKcdI4GI4aNYoBAwYwb9685h5KlO3bt9OlSxe++eYbBgwY0NzDOeZIB1bJ4RBCENy6NRrjpGrlSvSSkoQyiseDZ+BAPEOHkpI/BNdppzWJOGmyCKwSyYlIOFxBZeUWKqs2U1W5hcqqLVRWbqa6+ieg9hUriuLA4+kUFRoedxc8Kebe4cios69QqP6vOpDARx99xAMPPMAPP/yAy+XirLPOYu7cuXTu3Lm5h9aoHI/CTnJyoigKzm7dcHbrRsYvf2mKk82bqSxYaS4lXrkS/eBBKpcto3LZMooB1eOh3fx5eM88s1nGLMWI5KRBCEEwWGxZObZYomMzlZVbCAb31VnPZkvF4+lOiqcrKSnd8KR0J8XTDbe7A4qiHcMraHls27aNSy65hLvuuotXXnmFsrIyfve733H55ZezevXq5h5evQiFQtiPI3O3RJKMoig4e/TA2aMHGddegzAMAj9utoSJaT3Ry8pwNOMPAOmmLznhEEKnqmo7xfsXsWPH/2Pdunv46utf8NnnA/li2XC+WXMdmzbNYueulygtXREVIg5HDunpw2nf7jp69pzFwAEv8bMRKzjrzG8YMvgtTj11Dp063UJ21mg8ns6NJkSEEBhBvVm2hszCVlZWMmHCBLxeL3l5ecydO7dGmUAgwJQpU2jXrh0pKSkMHTqUJUuWJJRZtmwZo0aNwuPxkJ6ezrhx4ygtLa21z1WrVqHrOo888gjdunXj9NNPZ8qUKaxZs4ZQ6DDvyolj6dKl5Ofn43Q6ycvL47777iMcDkfPv/XWW/Tt2xe3201mZiZjxoyhsrISgCVLlpCfn09KSgqtW7dmxIgR7Nixo9Z+tm/fjqIovPHGG4wcORKXy8Urr7zCgQMHGD9+PO3atcPj8dC3b19ee+21aL2JEyeydOlS5s+fj6IoKIrC9u3bAfj+++85//zz8Xq95Obmct1117F///56X7tE0lAUVcXVqycZ111L+yeeoMeK5XR5913sdQQiPRZIy4jkuEXX/ZbzaGxqpapyC1XV2w7xFlkVt7sDKZZ1w5PSjRRPd1JSumGzpR7T8UcQIYPdM5c3S99tHzoDxVE/UTV16lSWLl3Ku+++S05ODtOnT2f16tUJfhmTJ09m3bp1vP7667Rt25Z33nmH8847j7Vr19KjRw/WrFnD6NGjufHGG5k/fz42m43Fixej63qtfQ4aNAhVVVmwYAETJ07E5/Px0ksvMWbMmHpbG3bt2sUFF1zAxIkTefHFF9mwYQOTJk3C5XIxa9Ys9uzZw/jx45kzZw6XXXYZFRUVfP755wghCIfDXHrppUyaNInXXnuNYDDIypUrD+tofN999zF37lwGDhyIy+XC7/czaNAg7r33Xlq1asV7773HddddR7du3cjPz2f+/Pls2rSJPn368NBDDwGQnZ3NwYMHOeecc/jVr37Fn//8Z6qrq7n33nu56qqr+PTTT+t1/RLJ0RIRJ82JFCOSZicUKosJjqgj6Raq/T9RV2wOVXVaDqSRaZWupKR0x+3ujKaduIF/mgufz8ff//53Xn75ZUaPHg3ACy+8kPDKhsLCQhYsWEBhYSFt27YFYMqUKXz44YcsWLCA2bNnM2fOHAYPHszTTz8drXeo91B16dKFjz/+mKuuuopbbrkFXdcZPnw477//fr3H/vTTT9OhQweefPJJFEXhlFNOYffu3dx7773MnDmTPXv2EA6Hufzyy+nUqRMAffv2BaCkpISysjIuuugiunXrBkDv3r0P2+edd97J5ZdfnpA3ZcqUaPq3v/0tH330EW+++Sb5+fmkpaXhcDjweDwJASKffPJJBg4cyOzZs6N5zz//PB06dGDTpk307Nm8DwiJ5FghxYjkmCCEIBDYa1k3TMFRWbmZqqotBIN1m6RttjTTj8PTjZQ4K4fL1e6E8edQ7CptHzqj2fquD1u2bCEYDDJ06NBoXkZGBr169Yoer127Fl3XazwgA4EAmZmZAKxZs4Yrr7yy3uPbu3cvkyZN4vrrr2f8+PFUVFQwc+ZMrrjiChYuXFivpdDr169n+PDhCWVHjBiBz+dj586d9O/fn9GjR9O3b1/GjRvH2LFjueKKK0hPTycjI4OJEycybtw4zj33XMaMGcNVV11FXl7eIfscPHhwwrGu68yePZs333yTXbt2EQwGCQQCeA7zorNvv/2WxYsX4/V6a5zbsmWLFCOSFoMUI5JGxXQi3Yev8kcqfZuorPwRX+UmKis3o+u+Ous5nW1qTKt4UrrjsGee8LE5FEWp91TJ8YzP50PTNFatWoWmJV5P5GHqbuCLvJ566inS0tKYM2dONO/ll1+mQ4cOFBQUMGzYsKMet6ZpLFy4kOXLl/Pxxx/zxBNPMGPGDAoKCujSpQsLFizg9ttv58MPP+SNN97g/vvvZ+HChYfsOyXpVe+PP/448+fPZ968efTt25eUlBTuvPNOgsG6phNNfD4fF198MY899liNc4cTRBLJyYQUI5IjJhg8ECc2fsRniY9wuKzW8oqi4XZ3tKwcpk9HSkp3PJ4uzebPITHp1q0bdrudgoICOnbsCJgBCzdt2sTIkSMBGDhwILqus2/fPs6sY/lfv379WLRoUb3ful1VVZUQJBGICh3DOMRLAuPo3bs3//rXvxBCRIXrsmXLSE1NjU4zKYrCiBEjGDFiBDNnzqRTp06888473HXXXdFrGzhwINOmTWP48OG8+uqrDRJCy5Yt45JLLuHaa6+Njn3Tpk0JwR0dDkcN35nTTz+df/3rX3Tu3BmbTX4dS1ou8tMvOSyhUDmVlXFWDt8mfJU/EgodqKOGisfTiZSUnqSk9MBr7T2ezqjq8RuOuCXj9Xq56aabmDp1KpmZmeTk5DBjxowEodCzZ0+uueYaJkyYEHXeLC4uZtGiRfTr148LL7yQadOm0bdvX2677TZuvfVWHA4Hixcv5sorryQrK6tGvxdeeCF//vOfeeihh6LTNNOnT6dTp04MHDiwXmO/7bbbmDdvHr/97W+ZPHkyGzdu5IEHHuCuu+5CVVUKCgpYtGgRY8eOJScnh4KCAoqLi+nduzfbtm3j2Wef5ec//zlt27Zl48aN/Pjjj0yYMKFB969Hjx689dZbLF++nPT0dP70pz9RVFSUIEY6d+5MQUEB27dvx+v1kpGRwW9+8xv+9re/MX78eO655x4yMjLYvHkzr7/+Os8991wNC5REcrIixYgkSjhcacbl8P1IZeWmqMUjENhbZx2XqwNeb7Lo6CadSE9AHn/88ei0QWpqKnfffTdlZYlWrgULFvDII49w9913s2vXLrKyshg2bBgXXXQRYAqWjz/+mOnTp5Ofn4/b7Wbo0KGMHz++1j7POeccXn31VebMmcOcOXPweDwMHz6cDz/8sN5TPu3ateP9999n6tSp9O/fn4yMDG666Sbuv/9+AFq1asVnn33GvHnzKC8vp1OnTsydO5fzzz+foqIiNmzYwAsvvMCBAwfIy8vjN7/5DbfcckuD7t3999/P1q1bGTduHB6Ph5tvvplLL7004f5NmTKF66+/nlNPPZXq6mq2bdtG586dWbZsGffeey9jx44lEAjQqVMnzjvvvBoWI4nkZEaGg2+BmEtmt9Tw6/D7d9ZZx+lsExUbKd6eeFN64vF0w2ZLqbNOS0WG65Y0JfLzJTmRkOHgJRhG0IzTkeTXUV1dSF0h0B2OrMTpFW8PUjw9sNulCJRIJBJJ0yDFyEmAEDrV1YWWA2lseqWqahtChGutY7O1rjG9kpLS45DvXJFIJBKJpCmQYuQEQgiB378bX+WGOL+OH6mq2lxnRFJN8+K1hEZkeiUlpScOR9YJv2RWIpFIJCcHUowcp+h6FT7fJny+9fh8G6nwrcfn21BnrA5VdVlWDlN0RCweTmeeFB0SiUQiOa6RYqSZMa0dO/H5NlDh24DP2qqrd1BbKHRFsZuRSFN6RqdXvN6euFztURTpfS+RSCSSEw8pRo4h4XAllZUbE0SHz7exTmuHw5GN13tKdEv19sbj6SJjdUgkEonkpEKKkSZACAO/f6c1tbLRmmrZYK1iqYmiOEhJ6Y7X24tUb29LfPTC4agZJEoikUgkkpMNKUaOknC4Al/lJnwVG/BVbsBXsR5f5SZ0vbLW8k5HLl5vL0tw9Mbr7YXH0xVVrd/r0iUSiUQiOdmQYqSeCGFYy2djlo4K3wb8/p9qLa+qDsuJ9JS4qZZeOByZx3jkEolEIpEc30gxUgvhcIUlOjZEp1oqKzei61W1lnc621jWjt54U3rhTe2Nx90FVZW3V3JiM2rUKAYMGMC8efOaeyhRtm/fTpcuXfjmm28YMGBAcw9HIpE0Ai36aRkJFmY6lK6PCpC6wqKb1o6eSU6lp2C3px/jkUskJw9vvvkms2fPZtOmTWRnZzN58mSmTp3a3MNqdI5HYSeRHC+0aDHyZcEFVFVtrvWcae3oHRUcXu8puN2dpbVDImlEPvjgA6655hqeeOIJxo4dy/r165k0aRJut5vJkyc39/DqRSgUwm6XPl8SydHQogNTeDydUFUnqal9aZt3FT17/J7TB77KWWeu4mcjljGg/3N07zaF3NyLSEnpLoWI5IgQQhAMBptla8h7MCsrK5kwYQJer5e8vDzmzp1bo0wgEGDKlCm0a9eOlJQUhg4dypIlSxLKLFu2jFGjRuHxeEhPT2fcuHGUlpbW2udLL73EpZdeyq233krXrl258MILmTZtGo899liDxr506VLy8/NxOp3k5eVx3333EQ7HXoXw1ltv0bdvX9xuN5mZmYwZM4bKStPJfMmSJeTn55OSkkLr1q0ZMWIEO3bsqLWf7du3oygKb7zxBiNHjsTlcvHKK69w4MABxo8fT7t27fB4PPTt25fXXnstWm/ixIksXbqU+fPnoygKiqKwfft2AL7//nvOP/98vF4vubm5XHfddezfv7/e1y6RnAy06Kfrqb3nYLOloihacw9FchITCoWYPXt2s/Q9ffp0HI76xaWZOnUqS5cu5d133yUnJ4fp06ezevXqBL+MyZMns27dOl5//XXatm3LO++8w3nnncfatWvp0aMHa9asYfTo0dx4443Mnz8fm83G4sWL0XW91j4DgQAejychz+12s3PnTnbs2EHnzp0PO+5du3ZxwQUXMHHiRF588UU2bNjApEmTcLlczJo1iz179jB+/HjmzJnDZZddRkVFBZ9//jlCCMLhMJdeeimTJk3itddeIxgMsnLlysNGLb7vvvuYO3cuAwcOxOVy4ff7GTRoEPfeey+tWrXivffe47rrrqNbt27k5+czf/58Nm3aRJ8+fXjooYcAyM7O5uDBg5xzzjn86le/4s9//jPV1dXce++9XHXVVXz66aeHvXaJ5GShRYsRu711cw9BIjku8Pl8/P3vf+fll19m9OjRALzwwgu0b98+WqawsJAFCxZQWFhI27ZtAZgyZQoffvghCxYsYPbs2cyZM4fBgwfz9NNPR+uddtppdfY7btw4fve73zFx4kTOPvtsNm/eHLXI7Nmzp15i5Omnn6ZDhw48+eSTKIrCKaecwu7du7n33nuZOXMme/bsIRwOc/nll9OpUycA+vbtC0BJSQllZWVcdNFFdOvWDYDevXsfts8777yTyy+/PCFvypQp0fRvf/tbPvroI958803y8/NJS0vD4XDg8Xho06ZNtNyTTz7JwIEDE8Tq888/T4cOHdi0aRM9e/Y87FgkkpOBFi1GJJJjgd1uZ/r06c3Wd33YsmULwWCQoUOHRvMyMjLo1atX9Hjt2rXoul7jARkIBMjMNJesr1mzhiuvvLLe45s0aRJbtmzhoosuIhQK0apVK+644w5mzZqFqtZvFnn9+vUMHz48wZoxYsQIfD4fO3fupH///owePZq+ffsybtw4xo4dyxVXXEF6ejoZGRlMnDiRcePGce655zJmzBiuuuoq8vLyDtnn4MGDE451XWf27Nm8+eab7Nq1i2AwWKvVJ5lvv/2WxYsX4/V6a5zbsmWLFCOSFoMUIxJJE6MoSr2nSo5nfD4fmqaxatUqNC1xajPyMHW73Q1qU1EUHnvsMWbPns3evXvJzs5m0aJFAHTt2rVRxq1pGgsXLmT58uV8/PHHPPHEE8yYMYOCggK6dOnCggULuP322/nwww954403uP/++1m4cCHDhg2rs82UlJSE48cff5z58+czb948+vbtS0pKCnfeeSfBYO1v047g8/m4+OKLeeyxx2qcO5wgkkhOJlq0A6tEIjHp1q0bdrudgoKCaF5paSmbNm2KHg8cOBBd19m3bx/du3dP2CJTD/369YuKiYagaRrt2rXD4XDw2muvMXz4cLKzs+tVt3fv3qxYsSLB4XXZsmWkpqZGp5kURWHEiBE8+OCDfPPNNzgcDt55552Ea5s2bRrLly+nT58+vPrqqw0a/7Jly7jkkku49tpr6d+/P127dk24dwAOh6OG78zpp5/ODz/8QOfOnWvc02TBI5GczEgxIpFI8Hq93HTTTUydOpVPP/2U77//nokTJyZMlfTs2ZNrrrmGCRMm8Pbbb7Nt2zZWrlzJo48+ynvvvQfAtGnT+Oqrr7jtttv47rvv2LBhA3/961/rXB2yf/9+nnnmGTZs2MCaNWu44447+Oc//9mgWBy33XYbP/30E7/97W/ZsGED7777Lg888AB33XUXqqpSUFDA7Nmz+frrryksLOTtt9+muLiY3r17s23bNqZNm8aKFSvYsWMHH3/8MT/++GO9/Ebi6dGjR9T6sn79em655RaKiooSynTu3JmCggK2b9/O/v37MQyD3/zmN5SUlDB+/Hi++uortmzZwkcffcQNN9xQp9OvRHJSIk4AysrKBCDKysqaeygSyWGprq4W69atE9XV1c09lAZRUVEhrr32WuHxeERubq6YM2eOGDlypLjjjjuiZYLBoJg5c6bo3LmzsNvtIi8vT1x22WXiu+++i5ZZsmSJOOOMM4TT6RStW7cW48aNE6WlpbX2WVxcLIYNGyZSUlKEx+MRo0ePFl9++eUhx7lt2zYBiG+++SahzyFDhgiHwyHatGkj7r33XhEKhYQQQqxbt06MGzdOZGdnC6fTKXr27CmeeOIJIYQQe/fuFZdeeqnIy8sTDodDdOrUScycOVPoul7vvoUQ4sCBA+KSSy4RXq9X5OTkiPvvv19MmDBBXHLJJdEyGzduFMOGDRNut1sAYtu2bUIIITZt2iQuu+wy0bp1a+F2u8Upp5wi7rzzTmEYRq1jOFE/X5KWSX2f34oQDVjM30yUl5eTlpZGWVkZrVq1au7hSCSHxO/3s23bNrp06YLL5Wru4UhOMuTnS3IiUd/nt5ymkUgkEolE0qxIMSKRSCQSiaRZkWJEIpFIJBJJs9Ki44wcOHAAwzBwOBzY7XYcDgeaph02FLREIpFIJJLGo0WLkff++zeK9u3GMLToJoQNm82NzebE4XBGRUpj7O12uxQ6EolEIpEk0aLFSFqrd2jXofb4B0IoGIaKYdhiYkU396GQhj9gq3k+ftNrz1dVJ6rqQtMimxu73YPN5sJuT8FudzZI3MRv0qojkUgkkhORFi1GRDkEbTZUzUDVBKo9tspZUQSapqNpxzbwkGEoGIaNUFgjEKxF5BxC6BjChqo4UBQHiupEVRyW8HGiai5slvgxLT9ubHYPdpsbh8OLw+GqVeAkbzabTQoeiUQikTQqLVqMdNn6J2zfhzCEQBcGujAw1AC6EkBX/RhqwDxW/QglgK75QQuCPQi2IGgBhBZEaEFQAxhKEKEGEUoQoYQQShDUMGg6is1A0QxrL1Aje0sIRVBVgaqGgNAxuQehsLn5KhV0XUMYGobQomndiOxNS5AQNhB2UOwoOEBxmAJIdaKqlvhRnWiaG01zYbO50Wwu7DY3NpsHuz2yubHbU3A4PNjtjgSxI0WPRCKRtCxatBhpk5NC6KeKpNy4IEIC0K2tERFgrmPSQKgCoRjoWgBDC6KrESHkN0WR4rc2M21gHRNAJ4BBAEMNIWxhhBZCaDpopgBC01E0HTQDRdNRNANV01FUwxJBRnRMiiKw2cJAuHEvFtB1cyNQ+3lzuqumpUcImyl+sEc3RbGblh8cqKopgjTVhao6olNfqubCZnNhs3mwaa44AWSKIIcjxbIGeXA43Nhstnq/IbalMWrUKAYMGNCg8OwSiUTSUFq0GEm/pBtGdRgRMhC6AWGBCBvWJhC6gQgZoBsYIQM9oBOuDptbQEcP6BhBHSMUK4cuUARoiqk31Og+9itfATDMTUEBNDQ8wKFfN97YCAyEGkZXq9G1ILrqJ6z4MZSAmRcRQ6p5ztwH0bUAuhbC0IIIzRJBatgSQWFQTUGkaDqKqltCSEdVDRRVNwVRnNFDVQ1U1aAxrEG69c8QqmdTpm9QvPjREMKeIIIUxY6CJYIUB4rqsHx/zL1mTYXF/IDS0LTe+P1lQABFUVEUBUXRrLQazQOlxVuA3nzzTWbPns2mTZvIzs5m8uTJTJ06tbmHJZFIjiEtWow42qc2SbuhgE5lWYCqsmB0X1Xmp6o0SHVZAH9FkEB5kHB1OCpUVGoKGPNYQVXMtNNlw+lUcTg0HHYVm6Zi0xRsmoKmWOWwxI4eE1WEDUtYmQIL3ZwWUlBRDAeq4cDe+AaROhEIUHSEGjKtOmoIoZnpkFpNSKkiqPoJqwHCajVhNYih+glrQQw1iKGGMDSrnhqyBFAYoYVRItNiapwQigggVUdVdUv4mJi+QWE0LUydpptDYBjmFoq7f6raltZpDxAOFxEM1kdoKKa1TJjipNZNUSzhqgARIZO4VxQVU9wkCh4zX7WsP/EiSI2231yC6IMPPuCaa67hiSeeYOzYsaxfv55JkybhdruZPHlys4xJIpEce1q0GGkq7E6N1jkeWucc2tKhhwwqyxNFS/y+sixIVVmAal/InNvxB+s9BqfHhjvVgTvVjjvDZe4jx147brcNl8eGy2XH4VJRDEzREm8ZChsxIRNnNUqwINWwKFkCyLIqCT2+XqLFSeh21FDiq5GOxZs2YhahIGHNFD0hNYCuBQirAcv6EyRsCSLTbyhk+RCFMNQgwhI/RMWQZQ1SdWyODFqlqtb0k4qiCKzJOStdc0QKQK3n6rgGkbg/ehQqK6v43V2P8N//+wSvN4XJv72RsF5FMFhKefmPgEIgEOThh//MW2/9H2Vl5Zx6ai8eemg6Z501IiqMvvzyK2bNepSvv/4Gp9PB4MGDeOWVBWRkZEbLRATQiy++yKWXXsItt9wMKHTt2pVp06bx2GOP8Zvf/KbFW40kkpaCFCPNiGZXaZXpplWm+5DldN2gujxEVXmAyoMBqsqDVFeEqK4ImpvPTFdVhPD7QghDEKgKE6gKc7DokE2bKOBKscSK19x7Uu24rL071YG7lcMSMw6cbhuK2jgPCSEE6PHiRkCoNgGUKJKEbljlEqfWIuLJCIbRA2GMUBgjqCNCOkZIt9pSEboNVbfhMNw4wwoYoIrG8RsJpypUZKXgqsrDFXQghMAQfvN6sSxDCIQiTGFk7VGEZTVKOrbKknAu0hrR/OixlVYUTL+aiHHlMILo97+fy/JlX/Pqq/PJzs7goYf+wnffrqNf356AOf4pU2axceNWnn/+f2nTJof//ncRl112LStW/Itu3Trx3XcbuOCCa7n22kt59NHfYbNpfP75V1RWbsflKqvRa2VlMR6Pm4qKH6wcBShh586dfP/9J3Tq1J5kK1HEslOblSdmKappNYq3HMWXrbtNKYQkkmNFixYjft001ytx0yEqHHdfQpqm4k134k13QqdDl40IkaqKIH5fkKryUIJgMbdQdO+vMq0ufp8pZErrMR5FVaKiJWpxST6OSztcdcc/URQFbAqKrfkdSKPCSE+yDMWLoJBOuDpI2B8gVB1A9wfRA0F0fwg9GMIIhgmpBsImMDQD3aaj69UUbPxZs1zTGd1XoKqm2BWWGBHEix5T6FRUlvPSS//m2SeeZNSQixGK4K9/OoVTTx+MCLswqlvz066dvPLKu3z3zTLy2uQgFMFtt/Zi4cIvefHF//L7++9m3rwXGTCgD3PmPGj5BQl69uqFAhiGiOaBKYpGjx7B9OlzWLLk55x1Vj5btxby5JMvAFBUVESnTm1qXFO8Najp3zlen2mzOGGjKCjRffLUmQKKak6PKvF11Rpt1pxCkwJJcnLTosXIFWs283V5Va3nFEzfDeu3kpVWLOES8euwvjqU+DIxHxDi0pH68WUiv8ui5ZPbiUsnCqZYfsRXJPmcap1TPKB6FNQ2ppOsqnii/WuK+SPaCJkOukbQQA/q6EEDI6gTDphOu0ZAJ2xtRtBAEaaTrkIINRxCKalCOWCNM3IubtPUiL+LZm02nC4Nl8uG02nD5TbTLrfNnD5y23G5Neyaal6DAhqmX4wWd92xY3OvKYrpM2Pla1Z+fb/AE4SR80g+USaRV7y7slNxuVzougM2Hnl7R4Nfr0QTBhFX6fgHWuTBpwI7tv5EMBhkeL9hOMIuQCEvNYWe3XpgMxx4Qq3ZsvZLdF0nf9johD4CwQA5rdrgrW7DD9/9yC8uvBRvVbvo+Zg1KCKEiObcePkdbN9YytVX3U4oHCI1NZVbb/oV/zv3jxBIx6jKJMEylJAm9iEjYjkiLh2zHEWtQYo1JWaVPbS1KK6tWrLjc5teFEVQCAYFfn8xK76cihAllnO1HUV1oCh207FasZtO1prlZK1Zm+pEs5lpm+ZCs0UcsR1WXCJrlVqkHdWBotqtc2abSrT9SFntWF285CSmRYuRQ31/CKJ+nsS+eY7ZN07zomA+jKMPZNXa7I3UgbWUKLJ6JhJWJXmVdSOSLE40EoVcRMzUOE46p6Fgs8SOGid61IgYUiBTGFwmwjj8QexCQQiV7vlfgyVmwXpmEvutjQLxEiGhTJyWikmKWJ2a5WNtaKrbEh8CDGE+NYWBEMK0BAmBEAa613ygBFMgkKIjDLOcoQhCShCfWs6BqmI0TeOT//6f6QwrsJ7CCt4UDxWhUpxOO0HDT2W4LGG0yQIoPv/h+2by4NQZFBUXk52RxeLlnwHQs10vXKGU6DXF35uGEC9+Iqn4vAR7kZIoeOItSCSdI/5cvPipZcrMvIZafIfqEEex/NquRmD+/ZQhRFHsq8motUKTI4SCotgx3ecjq89sKGpkBZod1RJLatxmiiMHqhYnjjRzib6qxpW3hE9MFEXEkj0p7YwTUZEwADJe0YlCixYjbw3oji4EBqaJ3sD8vjasL4RIWgjr8SliX16Rc4aIHIvEvVVG1FI/vl2zrLDyzHGIuLpGLeV1q0xs7OZ5XZh9RPoy4vqN3+sicdx6cpkG1hNx5xLbEOiGIBQ2CIUFumEQ1s28sG4QNgS6ENaKaGEFn7OuVQFDURCK1Z9CYp5i5dXTd0UXoB8jUdleFYxrpVIRNlfwmByFqeWoOJzTswJoqF16YLPb+WD1t4zt1A2A8tJSfty6lb5nnsVP3nSyh45A13U2BMMMOmNEtDaYd3Qv0KX/AD5ZuZIbMjOIPnjj77mwHriRvKgnrg1ataMIwQvv/YuBg4dQ3TaNwsj4RezhHH2OR9q38uKFWnzZRPkTv8UEkhLdqzGLZ8QCKZSowUVBiWszkhe7k4eidgEUv08SSkosJ14U6eEgRqCKsrWXEAgcRChhDDUEamwvLIdqoVjO1WoIFB1U08laUczl9KpixR1qQF78ajSICKvI56w6+j3V2PGZjgwF8zGnWYIpIlAiAskUTKaYscct2bdHLUmq5ohalhKFUS0iqUa+Pc6SZI8Kp1if0rIUoUWLEbfW/H4KkpoYhiBQFSJQGcZfGYptvhCBqrDp31JlHvsrg/grw1RVhQgG9TihosQEC3UImbg8RVOweWzY3BoOjw2b24bmtmFzamhODc2lojk0FKeG5lBRHBqqXUV1qGBToqJRR2ALhUgvP0COw4bNaVqTYg+buEdQ7PmcuBeiZp71v5oPstrOxT3URHLfsT7i81JSvVw24Xr+PHMGrTMyyMjO5smHH0wIBtepew8uuOpqZtw8ibv/8Cin9OtPyYH9rFyymB59+nLWuPO44a4pXDE8nwd+dydX3ngTdoeDrz77jHMvu4z0zKwaT+7SA/v55N//ZvCZZxLw+3n3lZf48D//4bn3P8LvSqnnJ+Z4QsRmiuLSscuuxfJFbeIpUjomtiJl9WCAapuLr3NH4vODZghrM20TmsBMG6AJYR4nbAKEgSqENa1qoFjHCGsaFsNKGyB0EEnHhBFqCIUgKCFQAiiEUdQgKEEUJWwtvQ9jWGJIaKYYQo0TSUoYlMiyewNVsWIRRfaqYQmimDBKPo4IpVh+4r9HxPQqIk7k1r08LrQSEBFMCnZQbFGxFLHsqJbYUdSY1ceceotYmBymhakuAaTGhFeyaEoQT4odj6cTmnZs411FaNFiRHJ8oqoKbq8Dt9fRoHp62IgKl2QhE6gM4bfyAnHixl8ZRg9bv/RKagZbqU8AXkUBh8eG023D6bHjydDQTtdwVOo4wzqqqqCoCqoKiqqgqKqZp5n5SgP8WpqS5+f9mV//+tfc+T9Xkpqayu/uuguj0kem3cZpXjcCwZsvvsCjf/gDf/n9dHbv2kVmVhb5Q4dy3WWX0iPFSff+ffjPBx8w6/77ue6ckbjdbgbl53PLhGtJc5v/nvGiyON08NEbrzLv99MRQjBo6DD+vfATTh+SX1PA1RBc1j5JvCWLs5itIVEAJrYpks6ZhWv2d7h/J8teoySnGw9hKFRpCh/m2thpNP/npjYUIVAF2JJEkCbAZsTy1ASxZNYx93GbAaouUOMEVOSckpBniiUFA0XoqIQB3RQrhFEw8xR0FCWEqljHio6qhFAJoxJCUcLRtKaEsaGbeyWEpujYCKOqYWyE0dRIfhi7EkJTQthUM61aoqqmsEqeTzMFkyCUYCxsDnr0eI6OHc5ulr4VIZrz0utHeXk5aWlplJWV0apVq+YejuQkIxTUawiUiIgJVocJVIcJVpn7QFXYzKsyrTSGXvPPx5Wm0vfiNNrldcBuq5+gMsWKJU4iwkVREvJjYiax7PEiZloKNcRPVMTUzBfCMKcyDXMaUlg+OrF0bDPziOURORcTSwJBOBhiz66dvLz6W/ZVVWEoKoaiIlQVQ41LK/HHCrqqIRTFytOsMuaxiCtrRNupo4yqJRxL6kYzYsKphsgSAhUjbm+gYlmpMFDRUaL5OqrQrfxw9LwmTLGloZvH8ZuioxFO2pvCSiOMTdHRlBAaOjYljKaEOb/zRAb1alwxUt/nd4u2jPiWLkU/eBDFbgebDcVuR7HZzb09cmyLO++oka/YbOY5+TA4YbE7NOwODW96w0KuCSHQQ0aSSAlTVV1F0HYQdysHDpsDwxCWlVtYaRFNR9syTF+aIyVBoChxx4qCEhExcWlViYiZmOiRoqZ+xDsImxk1EnE0/sPa7/cTrijnLzdMwOGwEw4GCQcChAIBQgG/mQ7GpePPBQOEA9WEg0FC/kD0fDgYMPOsdCwvQMgfQIjavWPNKVAlKmJEbYImIoDUmqLJULWoWEoQT5oGdgeKw2l979rBbgfr+xmbuQnNZu5tNjOtaQjNhtA0DE1DqFpsTIr5CDdQEYpiPepBR0EXEBamD1s4Ka0Ttyd+b27hQ/zJ6KrZz4nCsOrWzdZ3ixYje1/dhMOZDcIPho6IzI0aOggdYRjWXKlu5RlmGUOP5otIOs7JLDJJLBTThC9UAdYXfmSdr6IpoKrmXlNRbSrYNFRNRbFpKDYN1WEz93Ybik1FsdvAplmCyIZi11DtGkSPbSgOG2pUJMUJK5stJpwiYio+Tz6EGoyiKNgcGjaHRkpazEHV709h2zYfnlQHLlfdAkdYnn5RgSIEhiVa4oVLnWIm6il49GIm/priRYqaLFji8w8hdJDC5pigqhoOlxuH69CBE48GIQSGHrYESjAqdsIR4RKsh6iJqxMKxrfjt9ox6xj6MXwvRRyKomJzOKzNGUs7ndgjefak805n9Fh1OFAcDhS709zbzGNTQEX2lnBSNYSime/QCltO/bpupsOCsGGYDv7hmKN/WDfzzUUAWGlhnhPmXo+kI8cRMSUEYczFAeE4YWV6/sSlFYU2HZvmFSn1oUWLEb8zA5cns7mHkYgBBEEEQa89BMphCCNEME4wJYkmoYMREVUx5zRhbWAt+zTX6WDECS0BGFb0TwOsyKE1nUENRTHTqoKhKtb5SNraq2p0LxQFXVOi5l9DU9CtX0+6qmFoKroWv9fQrS1sUzE0DUOzWZv5a4gmNB/XeMQmZXg0g6FZOvsq/NgDdQuEej2qVcXc6qxh+TpEzfuYvg4RkWIJlmg+sbKR/MSZWhH3Escjx3SZiLO2WMJcsfIOe87cxZWr0XrN/pIODu/dUWPAdZ+vpXJt52u0cJix1NJt7aOI6y8Q0gnpBjsOVGJzhK17FbtnkXhIEHdfk85F+lWj56y4R/H/Hla+GdNIRXG4sTncOFKVhPNKXD9Hix4Om0IlapXxW8dmXigUjAqZiPCJlTfToWDd55LPR/5QhDAIBfyEAv6jvob6omq2OAHkQIuIHbvdEj92PA4nWuTYEcu3JeQn1rE5nGhRARUra3c40Rx2VLXm6h1hCHPJodZ8PyBatBiZ7nETwIcNK+4E0UVgcelIfqyMXQhsQuAQAntkw9zbiByDLXKMgiYEtrg24/uJ7FVFsdKKFQjN2ivWgkNFQY28AA2l1g8VmCqfpJVCx+Vv1Ei4ETiKF/YKTH0ftgRXTGRFBVac2BLRGBsGhiW8DGFYy6utDRE7tvamSVZEl1DrivmLQ7eEmS5Mc60OqK1daJf2xlZehaaFoqOMbkrMGVLUOBefp0TLG/FllcR6xO0bTPxSjkYn2SNU0hiIcJB95QFmvfsVuyqOnzUhEBMxakREWioqMS8mPJPTkTJYoikh2KQldlQVIoHe1CQxFC2vguJWUNyR8kqCMFOj6YgiNyLKPJY2zB9ilrkyzlJupSObZUUXRmxvntNjebpuWd8jq5Vif/2KAEUXKLoAv5UvIud10+GWahQR+9aILmsXceno6i0RTcf6iJVRFRXNpqJpNjRNQ7Np2DQNzWbjV9ddQq/ePZv+g1ILLVqM5PbOYUdJJSEgGP0laf5SVIT1C1EAhkCJBdgwf1FGjqO/MkXssxzniEZ8M1HrQmzJaeR5bD5wRKysEilvxfpQav/S0ZK2eNEUETq2pDJ2IXAYBg5hWGLKsISVtY8IqwSxFRNX5qZYx5awEmaeplie8Uqi2IqIK1N0qdZslRXTISq8Et80q0RDZ1ub6cFpiq1aUFTrCi2N1lwCLJyqUKHa8WpOXPV0YG08YlaRRAUQJwziHC3jz9WmF+LPCCU5Pz6t1DgvktLJq1VEfN2kcollYqIs9tVbez+17Q9L3LgjD8Lk/Ni5Q2UkUnv/Sfde1JpMzEs6Yajm35nXaaNVSImWMe+diLuHsdhEJB3Hl2tMIu0bosH/CicACrFv0cYretxgwNjSano1U/ctWoz86pJTKAubD/kEk6N1PsG0GXdM/Pk4s2dC3bi2FEy/AD1oEAqG0YNGdAsHdcIhHT1goId0QgGdsBWWPRywzgd19KBOwK8TCppbOGiYX87RLxfry4a4L2gBQjEDkIEVzE3Exd6IfHFY5f2KoBqrTuS8AqqmoGhmPA1VVa0/MgVVs9KqgtCsh5EChhprw7CmcsIiJqziA5zpwsAQENbNOdBoEDTLJ0I3dHShm3UMKwCcNThVWL+mBDgj4sowcArDElZGVExF0xg4jHgLVkR0JYotuwAbIibyRLzgixdalkVLRCK2ghp24TZOIawHCREXrCvJJq/E/Z/Ir8ikvFhunN39kChxRWope5hpgyalvp02+uDqEGjx6ii6q+U8tT9SE86KWsopyTc7ZiWIMwtYRWPHsekpxXrdjTlvEvHN8YdA8Th486LTcLncph+ZGvFJMzdFAbRIG1Ze7OVbsbJK7FIjIiU+WGPkXDTgY2Rv1BQ3kXqR2xFdHRSpF/mxFlcvUoZa8iL9xsZn9SEi32lWQElRc9zJ5eP7TW7DOER5w0gafy3lESJpDLHyCcEwRXx+0j0VsWCRsWuI9RVdfRXXliFq74eEtoiu5tJ1Hd0wMHTT98QwDAxdN59NhoGuG7Rrl1fLJ/3Y0KLFyEM/rGdVsLFCnDcCduqIuH4cS2whEgIyYQmE2vNENC8+cna8aIt8P8e9JizufT6m5UeJ+x5VI6ZZ60s1rCjoSrwZNmYGjrheKAqJTw3rCyX+SxHrj5/4L6cEC1hi2nRANevlaILb3XbsXgeqw2kJw8THWW2/SOtaZR+frcStaoiZZGPHCfedeJNvJE/UKBc178b9e8TOWXVEcl7NNLXWjU8rtdeLk2HxR8nB32Mm/9pKJ153InUINCW51DFGcAjDQc2TkRwjHMKoDFH63y3YKupsoP7DiExLRH+WJG8QH74+cW/9PSnCElgiJqisP1JFtaZYIsIqQRwliShVSXDsV1Rrr6mxfNVy8o+U0bRoGTPfXAwQv1dsmmlZjSwgSBgHRL4gIuOOF2uxdC2CTtJotGgx0mv/agxSicywCeuXKJCQF01HzsXlkVQmWjepXsSEHZvJO3zbwvryFYcYk6EodbYZOWfmN5FDpxJ/bYct3AQDSOo1apduROI9/upBUBWEVYVQ5EtU0kwkfzbMXW3/ikqSEEwQONFTMTFdW1tKXLH4ySSl1vN19JW8FzXPhVUot8EbHQwqAsIU7CiWgFfijpXEc8K0IkbSConWxcg+WjZaR9TMS6pj5sWErpqQn5SnC9RwXH91jsGwjvWa5xPqiDrGnZRH4xNdgUkkam2yqKslT7HKxh1H0krEc9zKi77PSBFxos+arFQxy0RuRqSMaonHiFA0Z7fN85G0GjtHZEWcBu4xY7F17NIEd+rwtGgx8if7FijeYB2JxJ+gIu6XyeHS8fOj9UpT/7br6qfWMvHniB3HnRNE3F7i5uGjxwIjKmxErAxJDpRYAkkIc5VM9FzMtUoIgWEJoKQ/NbOOoRDCQVjYCeMgJKy0cBDCjo7dzMNulYnbY+brhp2wYubrRM7Z0K1yOpF8GwI15jhq7YUSLwDj84nmY5UTdZSLHcfeo5PuUXAPcJPiN1D1+PgM1hcESf9WcU+cQ51LzE/4R67RRy25MSLXnXBeSSqrRK+T2s7Vlk4Q3HW1HZdOEP/RwSVd1dE8Qmo3fdR61xphJcixQig6lXaVDzulHrcRWI9XVMuSq0bE06HES22iK26vJIm0WkVVnFiqW+xFzh1C9CXk1S4iawjBSLnDXIcqLHEYhvOXf0M/KUaagQvmHPMuk03x8e5s8edquhjGC6Va2q3DHFBnfq1TAqLWEE0NCdLbsP6akLgJbzN+h0E4ZKAHdMLhiK+O5bsTMtPhoG6u7Q/q6CHD9OUJC/SwgR4yovtwWMSOwwZ6iFgZXWB3KzjCTtwBA7ten9UOdf1ObnziVypYeiNhCW2kTCR90eUX0LdPPx77w2OWcUiJGoniy9VckkuCQanOfuP2NRGJvw+s/fbtO+jW61S+XrmcAf37J+ru+L8nataNppM1e420qFE+KhMjc/1x+fG+ErH8uIiscf3Fl43mJY2nRp9xo9LDQSr0MMNKd7M/GLZeWBl7OWfCPiEd96MhKsQjIesjv9UVKy9iWSV6HNvH/fBQqP1cQvux/OQ+Yz8KYj5nCRbnuA9HNB0pE/8hqieG9aGMeQpK4um8P4V+zdR3ixYjN3x4A98Vfwckf/kkPTgTvhBrL3cokSE5SVAxX757mBfw5jnyuNdxL6UeO6r9xJ6mCeDHRzk/scPMSDLcNAYf/vtD/jbvb+zYuoP0zHTG3zSeGyffWGf5Xb7dAGz37cZdntbwDpVkb5R6VImv0YDKDe2pzvJx2bqiYyg+ytQ3KbcdSKgXifURmZqJVo84yqIghDm1Y9o+6zAX1XYsiNaF2HdepM1IXvxx/OclIsKixyLp+zM+T9TMi/pyRdtNFKuxm2SOUCTlmZlK3L1UiL+xUaudYpkElZrnI23GhJUabavW81FhlXQcN66IYIvmR8SWiLkOJLaT2E8sLzLeuDYS2gai1urYL4n4euWdz6e5aNFiJGSECBqHe8W6RCJpKj7/5HPu+/V9THt0GmeMOoOtm7Yy665ZuFwufvmrX9ZR6xA/HOqDOMqfCs38O8MwDMJGmKLKIvYE9zTvYBqTxGe/5AioIcCIrQVV4sRVROxEy1oiJS085FgON4EWLUbOX5nH4C2xMKe1RRBMyKvDJFhXGSWx0CH6URIKJ56Pr1d7e2apun+51dpfXedrXOIhyiadrvGrLnmMhzGp1mw7+RprVKitkQbVOfy9qdlFrd+YcVmO1Fa06uQiK5CCQ7clPLvq/1176D6agsqqKqZOm857H3xIijeF39xyCw7DRoruoE3AfMFVIBDgD3Me5+1/v0t5eTmn9OrFzOnT+NkZw6PtFHz1FX947HG+WbMGh9PB6QMG8LennqR169Y1+lz4+oecP24st4+fBMDgNqdR9pv9PPmXZ7jzmltQFKWG1dHvTwEgPeAhpyoVASz/8ksenD2bdevX0zotjauuuIJpd0/BZtMQwP+9/z5z589n+/btuN1u+px2Gv949m+keDws+3IFDz/6v2z8cRN2m41ePXvy1Lz5tG/Xjrr+HRK/9GOIhGwlMb+WczV0TVyTyb43kcNwWMcV8jFo61gO+irjpjySpkciaTVuuiXufGSaBEVFqLE2ok7p1pRGtGz0WI1rI7ZHUWPTLsn1EvLVhKkWoajmlFZ0uiZuDBHLQdSAkzyG+Lw460TSNFT8VFDydFF8ncg0W7wFIt6qUeM4znKRHAcnOh2VYBkxjw0l7jMQX66W/ogbZ/Q+1ugnZuk4GiqdvqNu40hp0WJECRvoQWkZaSnEfzEkbIfIo55liUt7VRcdhcBvvTtCCIFfxM1zJxDnsKnUkhfNVxJ8CMz8ZGfPuPpWWy4lIrjivgzreFjO+sPv+eLLAp564QUys7L40+zZfPv993Tv25cDdvMdO/ffO53Nmzbyx2f/Rk6bNix8/32uum4C/1m6lM5du7Fu7ff8z//8ksvH/5Kps/8XzW5j5RdfsM/mIuhMqXFNFbqOy+Nln8sbHU8otTW79+zhmwMHadexI8k3bX/KQQBKPKkUpbamaPdufnnDDfx8/C958Nm/s+3HTTx4x28Jt0rjtvumU7x3L7++/XbufPBhzrnoYqp8PlavWM6+tHQcLjfX33orl0+YyMMvvEQoFOT7Vas4kJ6FIzOn1rvb3IhggEq3h4U/Gy0dWCWNSl5qerP13aLFyM/vnoEeisQhj5uXBKKv9cZ0ADNDgZv5uogFBQtbc6GRMiJSPlpXJDmTxfJ16+ESCztuOlYJzPDi0f4x24vkR94WYwbOievXGlOkLSMhj2hY88gYjfjxRvKJC6ADCQ5xZp6o4SAXbZ+4QDuRc5FrqaXt+D6S60Ty9KRjI6muELXk1VY/+i/c9LRXBcM8KmWtMlAcTvy6wSVrNh+j3hN5d0B3XPVYXlzl8/HP117jD8/+nQFjLwBg1rPPM+7UnoRtdqpdKez56Sfefv01PvhhIzl5ZnCka045jc+WLOHNN9/i9gce5Nm/Ps2pA0/nvvlPRtvu2G8gALXJ/qFjxvHH6fdy0bLlDDlrJD9t3cI//vo0AHv3HyC3a/cadXTVbu01dM3GawueJ7dde+6bOw9FUeh0Sm+K9hYxf9bvufm+Gezbt49wOMw5P7+Uth07AtC9T18AykpK8JWVcdZ559OhazcAuvbqXZ9bWy8SpULt9pTDHSfnGZiB+fJEGJuIzW5EvQNEfJyemEdAJCZNZFmvImJ5xOVF4wFFz5l/TGpcPiJujyAabyhuf/g86480kmdYv/8tAV+jXCQCGFgRsc1z8WUxrHTkug0rHR1n3D4+Ro+wXHKj15R8H2L5sfsYdz8i97NGvcTz8bGWEu59dCwi4b7H4v6IxH7i6whQMGLXnXCtgLVEOjauxHsRX6/b7dfW8uk7NhyRGHnqqad4/PHH2bt3L/379+eJJ54gPz+/zvL//Oc/+f3vf8/27dvp0aMHjz32GBdccMERD7qxuHFHCavLq+JERuKDXCLRFMsZUInEOlIicZOi+Ur8eRRyVAObIrApCpqqoIvaHi/HhtZ2DbemWl9oSg1LbuRw3c5CQsEgo4YPI9thQwFy8nLo1rMnHk0l12ln7Y8b0HWdSwf1T2gjGAjQJjuLti47W79fy8W/+AXtXPa49pXE/uIMRL/79S2U/7SDO66+glAoRGqrVtw6+bf878MP0c7toIvHmVgX0NxmiP0OLgfdPE72bfmRnw0fTo8UV7Ttn599Fo9O8ZFSup+LhuVz9jmjufqMfMaMHcuYc8/l8l9cQXpGOnjbMuH66/nN5ZcweswYRo8ZwxVXXkleXp55v+LvVR33LrFM0/9b+/0amsvJP3ufcsi3QrdUIkEIDUNg6FZAQoPosWEYsbdg68lvx47VMSJ5SWUM3fqhGm1bxLUdn0fNN23Hv4HbGqfQI2lqeWN33PVY/dbVthBg6Na1idrf+h3tV092/jVJbUZrYIPFyBtvvMFdd93FM888w9ChQ5k3bx7jxo1j48aN5OTUvJDly5czfvx4Hn30US666CJeffVVLr30UlavXk2fPn0a5SKOBF95OftK9uNTjv6PObo+HGsNeFza3CenY79Y4o9rTycdi7r7aPhxfDtxQYuSxyESx1HbNdV1PQq13ZfE8kpdfYvE+vHl6zv2+tZPHk9sYuMIUG04nG1oK4I4rbDZawd0PNLWjgq37kephyk/NVQd3acFY35UmmHg0MOkBirRSw+gaRpfLF2MlvSSRq83BY+/Eo/TiT0cwu2vrPcYZ8+cwcMz7qOoqIisrCyWLF0KQLe8XLSqihrl1WqzbcVfhVJVAeEw6CGwygoAq4xRVYHir+Q/b/+TLwsKWPTpYp5+4i88cP/9LFn0CZ07d+Lpv8zjlptuZOEnn/Dma6/ywO9/z3/+/Tb5Q5rPme9QBIJBAtVVfLdsERjh5h6OJB6FhIDZCsdt7GxE5H8CK26bwNO6+cbTYDHypz/9iUmTJnHDDTcA8Mwzz/Dee+/x/PPPc99999UoP3/+fM477zymTp0KwMMPP8zChQt58skneeaZZ2rtIxAIEAgEosfl5eUNHeZhWVewmEFfb2CgokbNcxFTVrzJLtksl3xOztgmEv8i3paK1+tlxIgMfFV+/MHmfVjU92XImTltsNvtLP1iORdffDEABw8e5MfNmxmSn0+Zr4qu3Xug6zrbC3cydOjQGm2U+aro2asXiz5dzG9vv6PBY01p1ZrqYJhXXnuDQYMG4XB5KPNV1ShXUVUd3Zf5qujcpQvvv/8+Bysqo5aJT5d+jtfrxZuWHm3j1D79OLVPP277zWTy8/N5819vc8sttwDQuVt3JnXrzqRbbuXiiy/m5Vdfp1fv0xp8DceCcDhMdSDIsm/W4/M1n8Oh5ORDtSvkn3tJ8/TdkMLBYJBVq1YxZsyYWAOqypgxY1ixYkWtdVasWJFQHmDcuHF1lgd49NFHSUtLi24dOnRoyDDrTWqgmjR/Ja38VaQGqvEGqkkJ+vGEArhDQVzhEM5wCKcexqGHsRs6NmGgxVlCJJKTgZSUFP7nf/6HRx55hC+++IINGzbwu9/9znwxokW3bt24/PLLueOOO3j//fcpLCzkm2++4YknnuCTTz4BYPLkyXz77bdMmzaNdevWsXnzZl544QVKSkpq7bekpIQXX3yRzZs38/333zNz5kzee+89HnzwwXqP/frrr2f37t3cf//9bN68mY8++oi5c+dy8803o6oqq1ev5i9/+Qvffvstu3bt4v3336ekpIQePXpQWFjIo48+ytdff83OnTtZunQp27Zto3v3mr4qEomk6WiQZWT//v3ouk5ubm5Cfm5uLhs2bKi1zt69e2stv3fv3jr7mTZtGnfddVf0uLy8vNEFyalDz27U9iSSKKoNh9OB1+PC6XA092jqzeP/O5s777qbG264Aa/Xy+2Tf0NVVSVOh500rweAvz/7DI89/kceefhhdu/ZQ2ZmJkMGD+bSn19EmtfD6f378u47b/PgQw9x0UUX4Xa5GDx4MBOu+WW0jXhCgWreefttHnnkEYQQ5A8Zwgfv/R9DBg+uc5wHPW4AUj1u0rwe0np04+23/sn9v5/JueeeS3p6OhMnXMfMGdOw2Wzk5Waz6uuv+fvf/05FRQUdO3Rg9h8e5rKfX0TRvn1s376NW265hZKSEtq0yeWWmycx+de3JAix44lAMIjb6eCsgb3lNI2kUWnO56IiGhCne/fu3bRr147ly5czfHgsrsA999zD0qVLKSgoqFHH4XDwwgsvMH78+Gje008/zYMPPkhRUVG9+i0vLyctLY2ysjJatWpV3+FKJM2C3+9n27ZtdOnSRToYShod+fmSnEjU9/ndIOmflZWFpmk1RERRURFt2rSptU6bNm0aVF4ikUgkEknLokFixOFwMGjQIBYtWhTNMwyDRYsWJVhK4hk+fHhCeYCFCxfWWV4ikUgkEknLosGrae666y6uv/56Bg8eTH5+PvPmzaOysjK6umbChAm0a9eORx99FIA77riDkSNHMnfuXC688EJef/11vv76a5599tnGvRKJRCKRSCQnJA0WI1dffTXFxcXMnDmTvXv3MmDAAD788MOok2phYWGC49cZZ5zBq6++yv3338/06dPp0aMH//73v5s1xohEIpFIJJLjhwY5sDYX0oFVciIhHQwlTYn8fElOJJrEgVUikdSfE0DnS05ADKOlhxWUnIy06BflSSRNgd1uR1EUiouLyc7OPibvK5Gc/AghCAaDFBcXo6oqjhMoho1EcjikGJFIGhlN02jfvj07d+5k+/btzT0cyUmGx+OhY8eOx21QNonkSJBiRCJpArxeLz169CAUqu/bYSSSw6NpGjabTVrbJCcdUoxIJE2Epmlo2vH6zk6JRCI5fpB2PolEIpFIJM2KFCMSiUQikUiaFSlGJBKJRCKRNCsnhM9IJF5DeXl5M49EIpFIJBJJfYk8tw8Xd+mEECMVFRUAdOjQoZlHIpFIJBKJpKFUVFSQlpZW5/kTIhy8YRjs3r2b1NTURl3SVl5eTocOHfjpp59kmPkmRN7nY4e818cGeZ+PDfI+Hxua8j4LIaioqKBt27aHjI1zQlhGVFWlffv2TdZ+q1at5Af9GCDv87FD3utjg7zPxwZ5n48NTXWfD2URiSAdWCUSiUQikTQrUoxIJBKJRCJpVlq0GHE6nTzwwAM4nc7mHspJjbzPxw55r48N8j4fG+R9PjYcD/f5hHBglUgkEolEcvLSoi0jEolEIpFImh8pRiQSiUQikTQrUoxIJBKJRCJpVqQYkUgkEolE0qxIMSKRSCQSiaRZOeHFyKOPPsqQIUNITU0lJyeHSy+9lI0bNyaU8fv9/OY3vyEzMxOv18svfvELioqKEsoUFhZy4YUX4vF4yMnJYerUqYTD4YQyS5Ys4fTTT8fpdNK9e3f+8Y9/NPXlHTccq/v89ttvc+6555KdnU2rVq0YPnw4H3300TG5xuOBY/l5jrBs2TJsNhsDBgxoqss67jiW9zkQCDBjxgw6deqE0+mkc+fOPP/8801+jccDx/I+v/LKK/Tv3x+Px0NeXh433ngjBw4caPJrPF5orHt9++23M2jQIJxOZ53fCd999x1nnnkmLpeLDh06MGfOnKO/AHGCM27cOLFgwQLx/fffizVr1ogLLrhAdOzYUfh8vmiZW2+9VXTo0EEsWrRIfP3112LYsGHijDPOiJ4Ph8OiT58+YsyYMeKbb74R77//vsjKyhLTpk2Lltm6davweDzirrvuEuvWrRNPPPGE0DRNfPjhh8f0epuLY3Wf77jjDvHYY4+JlStXik2bNolp06YJu90uVq9efUyvt7k4Vvc5QmlpqejatasYO3as6N+//7G4xOOCY3mff/7zn4uhQ4eKhQsXim3btonly5eLL7744phda3NyrO7zF198IVRVFfPnzxdbt24Vn3/+uTjttNPEZZdddkyvtzlpjHsthBC//e1vxZNPPimuu+66Wr8TysrKRG5urrjmmmvE999/L1577TXhdrvF//t//++oxn/Ci5Fk9u3bJwCxdOlSIYQQBw8eFHa7Xfzzn/+Mllm/fr0AxIoVK4QQQrz//vtCVVWxd+/eaJm//vWvolWrViIQCAghhLjnnnvEaaedltDX1VdfLcaNG9fUl3Rc0lT3uTZOPfVU8eCDDzbRlRzfNPV9vvrqq8X9998vHnjggRYlRpJpqvv8wQcfiLS0NHHgwIFjeDXHL011nx9//HHRtWvXhL7+8pe/iHbt2jX1JR23HMm9jqeu74Snn35apKenJ3yX3HvvvaJXr15HNd4TfpommbKyMgAyMjIAWLVqFaFQiDFjxkTLnHLKKXTs2JEVK1YAsGLFCvr27Utubm60zLhx4ygvL+eHH36IlolvI1Im0kZLo6nuczKGYVBRURHtp6XRlPd5wYIFbN26lQceeOBYXMpxTVPd5//85z8MHjyYOXPm0K5dO3r27MmUKVOorq4+Vpd2XNFU93n48OH89NNPvP/++wghKCoq4q233uKCCy44Vpd23HEk97o+rFixgrPOOguHwxHNGzduHBs3bqS0tPT/t3d/oez9YRzAHzqN4wIrzFiKMpHkQkpTbkQuXJAIyY0yf4poxY3ihgu5UFvtgl1tLSlTLlwNWa7UyJ+J/LmgbUUtE2vY8734/XYy/H5f/84f2/Oqc2Hn0znneXccz+zzaV++3l/xrb0fFQqFYHBwEDQaDRQXFwMAgMfjAZlMBqmpqRFjFQoFeDwebszLGz28P7zv/8bc3t7Cw8MDsCzLR0mSxGfOr01PT8Pd3R00Nzf/cBXSx2fOJycnMDIyApubm8AwUfUY+DQ+cz47OwOHwwGJiYmwtLQE19fX0NvbCzc3N2AymXiuTFr4zFmj0YDZbIaWlhYIBALw9PQE9fX1oNfrea5Kmr6a9Ud4PB7Izc19c4zwPrlc/qVrjqqnUF9fH+zv74PD4RD7UqKaUDlbLBYYHx+H5eVlyMjI4PVcUsRXzs/Pz9DW1gbj4+OgVqt/9Ni/EZ/3cygUgri4ODCbzdzXqM/MzEBTUxMYDIaYehPDZ86Hh4cwMDAAY2NjUFtbC263G3Q6HWi1Wpibm/vx80ndb/xbGDUf0/T398PKygqsra2BSqXiXs/MzIRgMAg+ny9ivNfrhczMTG7M6xnF4Z//NiY5OTmmHih85xxmtVqhq6sLFhYW3nw8Fgv4zNnv98P29jb09/cDwzDAMAxMTEzA7u4uMAwDdrud3+IkhO/7WalUQnZ2NteIAAAUFhYCIsLl5SUfJUkS3zlPTk6CRqMBnU4HJSUlUFtbCwaDAebn58HtdvNYmfR8J+uP+Mxz/FO+NeNEAkKhEPb19WFWVhYeHx+/2R+etLO4uMi9dnR09O4EKa/Xy40xGo2YnJyMgUAAEf+ZwFpcXBxx7NbW1piZwCpUzoiIFosFExMT0Waz8ViRNAmR8/PzM+7t7UVsPT09WFBQgHt7exGz76OVUPez0WhElmXR7/dzY2w2G8bHx+P9/T1f5UmGUDk3NjZic3NzxLG3trYQAPDq6oqP0iTnJ7J+6W8TWIPBIPfa6Ojotyew/vpmpKenB1NSUnB9fR3dbje3vfxF12q1mJOTg3a7Hbe3t7GiogIrKiq4/eGlYzU1Nbizs4Orq6uYnp7+7tJenU6HLpcL9Xp9TC3tFSpns9mMDMOgXq+POI/P5xO0XrEIlfNrsbaaRqic/X4/qlQqbGpqwoODA9zY2MD8/Hzs6uoStF6xCJWzyWRChmHQYDDg6ekpOhwOLCsrw/LyckHrFdNPZI2IeHJygk6nE7u7u1GtVqPT6USn08mtnvH5fKhQKLCjowP39/fRarViUlISLe0FgHc3k8nEjXl4eMDe3l6Uy+WYlJSEDQ0N6Ha7I45zcXGBdXV1yLIspqWl4fDwMD4+PkaMWVtbw9LSUpTJZJiXlxdxjmgnVM5VVVXvnqezs1OgSsUl5P38Uqw1I0Lm7HK5sLq6GlmWRZVKhUNDQzHxXxFEYXOenZ3FoqIiZFkWlUoltre34+XlpRBlSsJPZf1fz+Dz83NuzO7uLlZWVmJCQgJmZ2fj1NTUt68/7t8iCCGEEEJEETUTWAkhhBDyO1EzQgghhBBRUTNCCCGEEFFRM0IIIYQQUVEzQgghhBBRUTNCCCGEEFFRM0IIIYQQUVEzQgghhBBRUTNCCCGEEFFRM0IIIYQQUVEzQgghhBBR/QFxxb4DYLlPagAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model.run(return_timestamps=range(2000,2011), \n",
    "          initial_condition=(2000, country['2000'])).plot();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 2: Fit the national level model to the remaining data\n",
    "We've used half of our data (from the year 2000 census) to initialize our model. Now we'll use an optimization routine to choose the loss rate parameters that best predict the census 2010 data. We'll use the same basic operations described in the previous recipe: [Fitting with Optimization](2_1_Fitting_with_Optimization.ipynb).\n",
    "\n",
    "To make this simple, we'll write a function that takes a list of potential model parameters, and returns the model's prediction in the year 2010\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def exec_model(paramlist):\n",
    "    params = dict(zip(['dec_%i_loss_rate'%i for i in range(1,10)], paramlist)) \n",
    "    output = model.run(initial_condition=(2000,country['2000']),\n",
    "                       params=params, return_timestamps=2010)\n",
    "    return output"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we'll define an error function that calls this executor and calculates a sum of squared errors value. Remember that because we don't have birth information, we'll only calculate error based upon age cohorts 2 through 9."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def error(paramlist):\n",
    "    output = exec_model(paramlist)\n",
    "    errors = output - country['2010']\n",
    "    #don't tally errors in the first cohort, as we don't have info about births\n",
    "    return sum(errors.values[0,1:]**2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can use the minimize function from scipy to find a vector of parameters which brings the 2010 predictions into alignment with the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'dec_1_loss_rate': 0.05,\n",
       " 'dec_2_loss_rate': 0.05,\n",
       " 'dec_3_loss_rate': 0.05,\n",
       " 'dec_4_loss_rate': 0.05,\n",
       " 'dec_5_loss_rate': 0.05,\n",
       " 'dec_6_loss_rate': 0.05,\n",
       " 'dec_7_loss_rate': 0.05,\n",
       " 'dec_8_loss_rate': 0.05,\n",
       " 'dec_9_loss_rate': 0.05}"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res = scipy.optimize.minimize(error, x0=[.05]*9,\n",
    "                              method='L-BFGS-B')\n",
    "country_level_fit_params = dict(zip(['dec_%i_loss_rate'%i for i in range(1,10)], res['x']))\n",
    "country_level_fit_params"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If we run the national model forwards with these parameters, we see generally good behavior, except for the 0-9yr demographic bracket, from whom we expect less self-control. (And because we don't have births data.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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OZcaMGQwbNqzGLIqImEMPsIoIAN988w233nora9eu5fDhw+Tn5/P666+TlJTEnXfeyZtvvklxcTFjx47l+uuvt1vuvvtuVq1aZTvW4MGDcXZ2ZuLEifTp04egoKAa41VWVnLy5Em75euvv65TzYZh1DjGyZMnqa6uvmCfwYMH4+joyPPPP1+nsUSk/mhmRESAH79N06VLF5YtW8axY8eoqKggKCiI8ePHM3fuXO655x569+5Nw4YNa/S9++67SUpK4vDhw0RFReHu7s6QIUP461//ypgxY8473pEjRwgICLDb5urqWqcfJPvhhx9qHAOgsLDwgl/5dXJyYsqUKSQlJXHffffh4eFR6/FEpH5YjLp8909EftXZs2fJz88nNDTU7tdARS4Ffb7kWqTbNCIiImIqhRERERExlcKIiIiImEphREREREylMCIiIiKmUhgRERERUymMiIiIiKkURkRERMRUCiMiIiJiKoURERERMZXCiIhgsVguuixYsIDjx49jsVjIzs4GsK07Ojry1Vdf2R2vsLAQJycnLBYLx48ft2t/vuW99967YG27d+/m1ltvpVGjRri7u9O6dWtGjRpFeXk5CQkJF607JCQEgJiYmPPu/+ktw7+8Bg0bNqRHjx7s2rXrkl5nETk/hRERobCw0LYsX76cBg0a2G2bNWvWBfs2bdqUV155xW5bWloaTZs2PW/7HTt22B27sLCQTp06nbdtbm4ucXFx3HjjjfzrX/8iJyeH5ORkXFxcqKqqYsWKFXbHAUhNTbWtv//++7ZjjR8/vsa4SUlJduP91Hffvn00btyYfv368fnnn9fqGorIb6e39oqI3RtuGzZsiMViqfHW2//+97/n7Ttq1ChSU1OZM2eObVtqaiqjRo3iiSeeqNHe19f3gm/U/aVt27bh7+9vFxpatmxJXFwcAFartcZbhL29vc97fHd3918d96e+/v7+vPDCCzRt2pTt27czceLEWtUrIr+NZkZE6plhGFSfOWPKcjleyn3HHXdQXFzM3r17Adi7dy/FxcX079//dx/b39+fwsJC/vWvf/3uY9WV1WoFoLy8/LKPLfJHo5kRkXpmlJWRd8P5b0PUt/BDWVjc3et1DGdnZ0aMGMHq1av505/+xOrVqxkxYgTOzs7nbd+9e3ccHOz/HVRSUnLetoMHD+af//wn0dHR+Pv707VrV3r16kV8fDwNGjSoU50pKSm89NJLdtv+8pe/MHz48Bptz5w5w8MPP4yjoyPR0dF1GkdE6k5hRER+tzFjxtC9e3cWLlzI66+/zoEDB6isrDxv2w0bNtCmTZtaHdfR0ZHU1FSefPJJdu3aRWZmJgsXLmTx4sUcPHiQgICAWtc4fPhw5s2bZ7etSZMmdutDhw7F0dGRsrIyrrvuOlatWkVUVFStxxCR30ZhRKSeWaxWwg9lmTb25RAZGUlERARDhw6lTZs2XH/99bZv3fxSUFAQrVq1qtPxmzZtysiRIxk5ciRPPPEEYWFhvPjiizz22GO1PkbDhg1/ddxly5bRu3dvGjZsyHXXXVenGkXkt1MYEalnFoul3m+VXAnGjBnD5MmTeeGFF+p1HB8fHwICAigtLb3kx/b3969zUBKR309hREQuifHjxzN48GC8vb0v2u6bb77h5MmTdtu8vb1xc3Or0fYvf/kL2dnZDBgwgJYtW3L27FleeeUVjhw5QnJycp3qO3PmTI1xXV1d8fHxqdNxROTS07dpROSScHJyonHjxjg5XfzfOL179yYgIMBu2bJly3nbdu7cmZKSEiZNmkS7du2Ijo7mvffeY8uWLXV+sPRvf/tbjXGHDh1ap2OISP2wGJfju38ifyBnz54lPz+f0NDQ8/5rX+T30OdLrkWaGRERERFTKYyIiIiIqRRGRERExFQKIyIiImIqhRERERExlcKIiIiImEphREREREylMCIiIiKmUhgRERERUymMiAgAMTExTJ8+vU59QkJCWL58eb3UIyJ/HAojInJFeeqpp+jevTvu7u4XfOleQUEBffv2xd3dHT8/PxITE6msrLy8hYrIJaO39orIFaW8vJzBgwfTrVs3Vq1aVWN/VVUVffv2xd/fn/3791NYWEh8fDzOzs4sXLjQhIpF5PfSzIiI2FRWVjJlyhQaNmxI48aNeeSRR/jpXZpFRUX0798fq9VKaGgo69atq9F/6dKlREZG4uHhQVBQEJMnT6akpASA0tJSGjRowMaNG+36bNmyBQ8PD06fPg3AY489xgMPPEBkZOR5a9y2bRu5ubmsXbuWDh068Oc//5knnniC559/nvLy8kt5OUTkMlEYEalnhmFQca7KlKWuL+VOS0vDycmJgwcPsmLFCpYuXcpLL70EQEJCAl9++SXp6els3LiRlJQUioqK7Po7ODiwcuVKjhw5QlpaGrt27WL27NkAeHh4MGTIEFJTU+36pKamMmjQILy8vGpV44EDB4iMjKRJkya2bbGxsfzwww8cOXKkTucrIlcG3aYRqWeV5dX8ddpuU8aesCIaZ1fHWrcPCgpi2bJlWCwWwsPDycnJYdmyZURHR/POO+9w8OBBbrrpJgBWrVpFmzZt7Pr//AHYkJAQnnzySSZNmkRKSgoA48aNo3v37hQWFhIQEEBRURFvv/02O3bsqHWNJ0+etAsigG395MmTtT6OiFw5NDMiIjZdu3bFYrHY1rt168ann37K0aNHcXJyolOnTrZ9ERERNR4w3bFjB7169aJp06Z4eXkxcuRIvvnmG86cOQNA586dadeuHWlpaQCsXbuW4OBgevbsWf8nJyJXLM2MiNQzJxcHJqyINm3sy+X48eP069eP++67j6eeeopGjRqxd+9exo4dS3l5Oe7u7sCPsyPPP/88Dz30EKmpqYwePdouAP0af39/Dh48aLft66+/tu0TkauPZkZE6pnFYsHZ1dGUpS5/yQNkZmbarb/33nu0bt2aiIgIKisrycrKsu3Ly8vju+++s61nZWVRXV3NkiVL6Nq1K2FhYZw4caLGGCNGjOCLL75g5cqV5ObmMmrUqDrV2K1bN3JycuyeV9m+fTsNGjSgbdu2dTqWiFwZFEZExKagoIAZM2aQl5fHq6++SnJyMtOmTSM8PJy4uDgmTpxIZmYmWVlZjBs3DqvVauvbqlUrKioqSE5O5vPPP2fNmjW8+OKLNcbw8fFh4MCBJCYm0qdPH5o1a1ajhuzsbAoKCqiqqiI7O5vs7Gzbt3L69OlD27ZtGTlyJB999BH//Oc/efjhh7n//vtxdXWt3wskIvXDEJFLqqyszMjNzTXKysrMLqVOoqOjjcmTJxuTJk0yGjRoYPj4+Bhz5841qqurDcMwjMLCQqNv376Gq6ur0bx5c+OVV14xgoODjWXLltmOsXTpUiMgIMCwWq1GbGys8corrxiAUVxcbDfWzp07DcB47bXXatQxatQoA6ixpKen29ocP37c+POf/2xYrVajcePGxsyZM42Kior6uCxXnKv18yVyMRbDqON3/0Tkos6ePUt+fj6hoaG4ubmZXc4Vac2aNTzwwAOcOHECFxcXs8u5qujzJdciPcAqIpfNmTNnKCwsZNGiRUycOFFBREQAPTMiIpdRUlISERER+Pv7M2fOHLPLEZErhG7TiFximkaX+qTPl1yLNDMiIiIiplIYEREREVMpjIiIiIipFEZERETEVAojIiIiYiqFERERETGVwoiIABATE8P06dPr1CckJITly5fXSz0i8sehMCIiV4zjx48zduxYQkNDsVqttGzZkkcffZTy8nK7docPH+bmm2/Gzc2NoKAgkpKSTKpYRC4F/Ry8iFwxPv74Y6qrq/nLX/5Cq1at+Pe//8348eMpLS3l2WefBeCHH36gT58+9O7dmxdffJGcnBzGjBmDt7c3EyZMMPkMROS30MyIiNhUVlYyZcoUGjZsSOPGjXnkkUf46Ueai4qK6N+/P1arldDQUNatW1ej/9KlS4mMjMTDw4OgoCAmT55MSUkJAKWlpTRo0ICNGzfa9dmyZQseHh6cPn2auLg4UlNT6dOnDy1atOCOO+5g1qxZbNq0ydZ+3bp1lJeXs3r1atq1a8eQIUOYOnUqS5curccrIyL1SWFEpJ4ZhkHF2bOmLHV920NaWhpOTk4cPHiQFStWsHTpUl566SUAEhIS+PLLL0lPT2fjxo2kpKRQVFRk19/BwYGVK1dy5MgR0tLS2LVrF7NnzwbAw8ODIUOGkJqaatcnNTWVQYMG4eXldd6avv/+exo1amRbP3DgAD179rR7yV5sbCx5eXkUFxfX6XxF5Mqg2zQi9azy3DlWjhpkythT0zbiXIf3lwQFBbFs2TIsFgvh4eHk5OSwbNkyoqOjeeeddzh48CA33XQTAKtWraJNmzZ2/X/+AGxISAhPPvkkkyZNIiUlBYBx48bRvXt3CgsLCQgIoKioiLfffpsdO3act57PPvuM5ORk2y0agJMnTxIaGmrXrkmTJrZ9Pj4+tT5fEbkyaGZERGy6du2KxWKxrXfr1o1PP/2Uo0eP4uTkRKdOnWz7IiIi8Pb2tuu/Y8cOevXqRdOmTfHy8mLkyJF88803nDlzBoDOnTvTrl070tLSAFi7di3BwcH07NmzRi1fffUVcXFxDB48mPHjx9fD2YrIlUIzIyL1zMnVlalpG3+9YT2NfbkcP36cfv36cd999/HUU0/RqFEj9u7dy9ixYykvL8fd3R34cXbk+eef56GHHiI1NZXRo0fbBSCAEydOcMstt9C9e3f++te/2u3z9/fn66+/ttv207q/v389nqGI1BeFEZF6ZrFY6nSrxEyZmZl26++99x6tW7cmIiKCyspKsrKybLdp8vLy+O6772xts7KyqK6uZsmSJTg4/Djp+tprr9UYY8SIEcyePZuVK1eSm5vLqFGj7PZ/9dVX3HLLLXTq1InU1FTbsX7SrVs35s2bR0VFBc7OzgBs376d8PBw3aIRuUrpNo2I2BQUFDBjxgzy8vJ49dVXSU5OZtq0aYSHhxMXF8fEiRPJzMwkKyuLcePGYbVabX1btWpFRUUFycnJfP7556xZs4YXX3yxxhg+Pj4MHDiQxMRE+vTpQ7NmzWz7vvrqK2JiYmjevDnPPvssp06d4uTJk5w8edLWZtiwYbi4uDB27FiOHDnChg0bWLFiBTNmzKjfiyMi9UZhRERs4uPjKSsro3Pnztx///1MmzbN9tsdqampBAYGEh0dzcCBA5kwYQJ+fn62vu3bt2fp0qUsXryY66+/nnXr1vH000+fd5yfbt2MGTPGbvv27dv57LPP2LlzJ82aNSMgIMC2/KRhw4Zs27aN/Px8OnXqxMyZM5k/f75+Y0TkKmYx6vrdPxG5qLNnz5Kfn09oaChuV8ntmcttzZo1PPDAA5w4ccLuK7ry6/T5kmuRnhkRkcvmzJkzFBYWsmjRIiZOnKggIiKAbtOIyGWUlJREREQE/v7+zJkzx+xyROQKods0IpeYptGlPunzJdcizYyIiIiIqRRGRERExFQKIyIiImIqhRERERExlcKIiIiImEphREREREylMCIiAMTExDB9+vQ69QkJCWH58uX1Uo+I/HEojIjIFeWOO+6gefPmuLm5ERAQwMiRIzlx4oRdm8OHD3PzzTfj5uZGUFAQSUlJJlUrIpeCwoiIXFFuueUWXnvtNfLy8njjjTc4duwYgwYNsu3/4Ycf6NOnD8HBwWRlZfHMM8+wYMEC/vrXv5pYtYj8HgojImJTWVnJlClTaNiwIY0bN+aRRx7hpx9pLioqon///litVkJDQ1m3bl2N/kuXLiUyMhIPDw+CgoKYPHkyJSUlAJSWltKgQQM2btxo12fLli14eHhw+vRpAB544AG6du1KcHAw3bt356GHHuK9996joqICgHXr1lFeXs7q1atp164dQ4YMYerUqSxdurQ+L42I1COFEZF6ZhgG1eVVpix1fdtDWloaTk5OHDx4kBUrVrB06VJeeuklABISEvjyyy9JT09n48aNpKSkUFRUZNffwcGBlStXcuTIEdLS0ti1axezZ88GwMPDgyFDhpCammrXJzU1lUGDBuHl5VWjnm+//ZZ169bRvXt3nJ2dAThw4AA9e/a0e8lebGwseXl5FBcX1+l8ReTKoLf2itQzo6KaE/P3mzJ24OPdsbg41rp9UFAQy5Ytw2KxEB4eTk5ODsuWLSM6Opp33nmHgwcPctNNNwGwatUq2rRpY9f/5w/AhoSE8OSTTzJp0iRSUlIAGDduHN27d6ewsJCAgACKiop4++232bFjh91xHnzwQZ577jnOnDlD165defPNN237Tp48SWhoqF37Jk2a2Pb5+PjU+nxF5MqgmRERsenatSsWi8W23q1bNz799FOOHj2Kk5MTnTp1su2LiIjA29vbrv+OHTvo1asXTZs2xcvLi5EjR/LNN99w5swZADp37ky7du1IS0sDYO3atQQHB9OzZ0+74yQmJvLhhx+ybds2HB0diY+Pr/Msj4hcPTQzIlLPLM4OBD7e3bSxL5fjx4/Tr18/7rvvPp566ikaNWrE3r17GTt2LOXl5bi7uwM/zo48//zzPPTQQ6SmpjJ69Gi7AATQuHFjGjduTFhYGG3atCEoKIj33nuPbt264e/vz9dff23X/qd1f3//y3OyInJJaWZEpJ5ZLBYcXBxNWX75l/yvyczMtFt/7733aN26NREREVRWVpKVlWXbl5eXx3fffWdbz8rKorq6miVLltC1a1fCwsJqfCUXYMSIEXzxxResXLmS3NxcRo0addGaqqurATh37hzw42zNv/71L9sDrQDbt28nPDxct2hErlIKIyJiU1BQwIwZM8jLy+PVV18lOTmZadOmER4eTlxcHBMnTiQzM5OsrCzGjRuH1Wq19W3VqhUVFRUkJyfz+eefs2bNGl588cUaY/j4+DBw4EASExPp06cPzZo1s+3LzMzkueeeIzs7my+++IJdu3YxdOhQWrZsSbdu3QAYNmwYLi4ujB07liNHjrBhwwZWrFjBjBkz6v8CiUi9UBgREZv4+HjKysro3Lkz999/P9OmTWPChAnAj996CQwMJDo6moEDBzJhwgT8/Pxsfdu3b8/SpUtZvHgx119/PevWrePpp58+7zg/3boZM2aM3XZ3d3c2bdpEr169CA8PZ+zYsURFRbF7925cXV0BaNiwIdu2bSM/P59OnToxc+ZM5s+fb6tTRK4+FkNPhYlcUmfPniU/P5/Q0FDc3NzMLueKtGbNGh544AFOnDhh9xVd+XX6fMm1SA+wishlc+bMGQoLC1m0aBETJ05UEBERQLdpROQySkpKIiIiAn9/f+bMmWN2OSJyhdBtGpFLTNPoUp/0+ZJrkWZGRERExFQKIyIiImIqhRERERExlcKIiIiImEphREREREylMCIiIiKmUhgREQBiYmKYPn16nfqEhISwfPnyeqlHRP44FEZE5Ip07tw5OnTogMViITs7227f4cOHufnmm3FzcyMoKIikpCRzihSRS0JhRESuSLNnzyYwMLDG9h9++IE+ffoQHBxMVlYWzzzzDAsWLOCvf/2rCVWKyKWgMCIiNpWVlUyZMoWGDRvSuHFjHnnkEX76keaioiL69++P1WolNDSUdevW1ei/dOlSIiMj8fDwICgoiMmTJ1NSUgJAaWkpDRo0YOPGjXZ9tmzZgoeHB6dPn7Zte+edd9i2bRvPPvtsjTHWrVtHeXk5q1evpl27dgwZMoSpU6eydOnSS3kpROQyUhgRqWeGYVBeXm7KUte3PaSlpeHk5MTBgwdZsWIFS5cu5aWXXgIgISGBL7/8kvT0dDZu3EhKSgpFRUV2/R0cHFi5ciVHjhwhLS2NXbt2MXv2bAA8PDwYMmQIqampdn1SU1MZNGgQXl5eAHz99deMHz+eNWvW4O7uXqPGAwcO0LNnT7uX7MXGxpKXl0dxcXGdzldErgx6a69IPauoqGDhwoWmjD137tw6vRk3KCiIZcuWYbFYCA8PJycnh2XLlhEdHc0777zDwYMHuemmmwBYtWoVbdq0sev/8wdgQ0JCePLJJ5k0aRIpKSkAjBs3ju7du1NYWEhAQABFRUW8/fbb7NixA/gxuCUkJDBp0iRuvPFGjh8/XqPGkydPEhoaaretSZMmtn0+Pj61Pl8RuTJoZkREbLp27YrFYrGtd+vWjU8//ZSjR4/i5OREp06dbPsiIiLw9va2679jxw569epF06ZN8fLyYuTIkXzzzTecOXMGgM6dO9OuXTvS0tIAWLt2LcHBwfTs2ROA5ORkTp8+rTf6ivzBaGZEpJ45Ozszd+5c08a+XI4fP06/fv247777eOqpp2jUqBF79+5l7NixlJeX2265jBs3jueff56HHnqI1NRURo8ebQtAu3bt4sCBA7i6utod+8Ybb2T48OGkpaXh7+/P119/bbf/p3V/f//LcKYicqkpjIjUM4vFUqdbJWbKzMy0W3/vvfdo3bo1ERERVFZWkpWVZbtNk5eXx3fffWdrm5WVRXV1NUuWLMHB4cdJ19dee63GGCNGjGD27NmsXLmS3NxcRo0aZdu3cuVKnnzySdv6iRMniI2NZcOGDXTp0gX4cbZm3rx5VFRU2MLW9u3bCQ8P1y0akauUbtOIiE1BQQEzZswgLy+PV199leTkZKZNm0Z4eDhxcXFMnDiRzMxMsrKyGDduHFar1da3VatWVFRUkJyczOeff86aNWt48cUXa4zh4+PDwIEDSUxMpE+fPjRr1sy2r3nz5lx//fW2JSwsDICWLVva2g0bNgwXFxfGjh3LkSNH2LBhAytWrGDGjBn1fHVEpL4ojIiITXx8PGVlZXTu3Jn777+fadOmMWHCBODHb70EBgYSHR3NwIEDmTBhAn5+fra+7du3Z+nSpSxevJjrr7+edevW8fTTT593nJ9u3YwZM6bONTZs2JBt27aRn59Pp06dmDlzJvPnz7fVKSJXH4tR1+/+ichFnT17lvz8fEJDQ3FzczO7nCvSmjVreOCBBzhx4sRVcwvrSqHPl1yL9MyIiFw2Z86cobCwkEWLFjFx4kQFEREBdJtGRC6jpKQkIiIi8Pf319d3RcRGt2lELjFNo0t90udLrkWaGRERERFTKYyIiIiIqRRGRERExFQKIyIiImIqhRERERExlcKIiIiImEphREQAiImJYfr06XXqExISwvLly+ulHhH541AYEZErSkhICBaLxW5ZtGiRXZvDhw9z88034+bmRlBQEElJSSZVKyKXgn4OXkSuOI8//jjjx4+3rXt5edn+9w8//ECfPn3o3bs3L774Ijk5OYwZMwZvb2+9LE/kKqWZERGxqaysZMqUKTRs2JDGjRvzyCOP8NOPNBcVFdG/f3+sViuhoaGsW7euRv+lS5cSGRmJh4cHQUFBTJ48mZKSEgBKS0tp0KABGzdutOuzZcsWPDw8OH36tG2bl5cX/v7+tsXDw8O2b926dZSXl7N69WratWvHkCFDmDp1KkuXLq2PSyIil4HCiEg9MwyDqqozpix1fdtDWloaTk5OHDx4kBUrVrB06VJeeuklABISEvjyyy9JT09n48aNpKSkUFRUZNffwcGBlStXcuTIEdLS0ti1axezZ88GwMPDgyFDhpCammrXJzU1lUGDBtnNfixatAhfX186duzIM888Q2VlpW3fgQMH6Nmzp91L9mJjY8nLy6O4uLhO5ysiVwbdphGpZ9XVZWTsjjRl7JjoHBwd3WvdPigoiGXLlmGxWAgPDycnJ4dly5YRHR3NO++8w8GDB7npppsAWLVqFW3atLHr//MHYENCQnjyySeZNGkSKSkpAIwbN47u3btTWFhIQEAARUVFvP322+zYscPWb+rUqdxwww00atSI/fv3M2fOHAoLC20zHydPniQ0NNRu3CZNmtj2+fj41P4CicgVQTMjImLTtWtXLBaLbb1bt258+umnHD16FCcnJzp16mTbFxERgbe3t13/HTt20KtXL5o2bYqXlxcjR47km2++4cyZMwB07tyZdu3akZaWBsDatWsJDg6mZ8+etmPMmDGDmJgYoqKimDRpEkuWLCE5OZlz587V45mLiJk0MyJSzxwcrMRE55g29uVy/Phx+vXrx3333cdTTz1Fo0aN2Lt3L2PHjqW8vBx39x9naMaNG8fzzz/PQw89RGpqKqNHj7YLQL/UpUsXKisrOX78OOHh4fj7+/P111/btflp3d/fv/5OUETqjWZGROqZxWLB0dHdlOVif8mfT2Zmpt36e++9R+vWrYmIiKCyspKsrCzbvry8PL777jvbelZWFtXV1SxZsoSuXbsSFhbGiRMnaowxYsQIvvjiC1auXElubi6jRo26aE3Z2dk4ODjg5+cH/Dhb869//YuKigpbm+3btxMeHq5bNCJXKYUREbEpKChgxowZ5OXl8eqrr5KcnMy0adMIDw8nLi6OiRMnkpmZSVZWFuPGjcNq/d/MS6tWraioqCA5OZnPP/+cNWvW8OKLL9YYw8fHh4EDB5KYmEifPn1o1qyZbd+BAwdYvnw5H330EZ9//jnr1q3jgQceYMSIEbagMWzYMFxcXBg7dixHjhxhw4YNrFixghkzZtT/BRKR+mGIyCVVVlZm5ObmGmVlZWaXUifR0dHG5MmTjUmTJhkNGjQwfHx8jLlz5xrV1dWGYRhGYWGh0bdvX8PV1dVo3ry58corrxjBwcHGsmXLbMdYunSpERAQYFitViM2NtZ45ZVXDMAoLi62G2vnzp0GYLz22mt227OysowuXboYDRs2NNzc3Iw2bdoYCxcuNM6ePWvX7qOPPjL+9Kc/Ga6urkbTpk2NRYsW1cs1uRJdrZ8vkYuxGEYdv/snIhd19uxZ8vPzCQ0Nxc3Nzexyrkhr1qzhgQce4MSJE3Zf0ZVfp8+XXIv0AKuIXDZnzpyhsLCQRYsWMXHiRAUREQH0zIiIXEZJSUlERETg7+/PnDlzzC5HRK4Quk0jcolpGl3qkz5fci3SzIiIiIiYSmFERERETKUwIiIiIqZSGBERERFTKYyIiIiIqRRGRERExFQKIyICQExMDNOnT69Tn5CQEJYvX14v9YjIH4fCiIhccd566y26dOmC1WrFx8eHu+66y25/QUEBffv2xd3dHT8/PxITE6msrDSnWBH53fRz8CJyRXnjjTcYP348Cxcu5NZbb6WyspJ///vftv1VVVX07dsXf39/9u/fT2FhIfHx8Tg7O7Nw4UITKxeR30ozIyJiU1lZyZQpU2jYsCGNGzfmkUce4acfaS4qKqJ///5YrVZCQ0NZt25djf5Lly4lMjISDw8PgoKCmDx5MiUlJQCUlpbSoEEDNm7caNdny5YteHh4cPr0aSorK5k2bRrPPPMMkyZNIiwsjLZt23LPPffY2m/bto3c3FzWrl1Lhw4d+POf/8wTTzzB888/T3l5eT1eHRGpLwojIvXMMAxKq6pMWer6toe0tDScnJw4ePAgK1asYOnSpbz00ksAJCQk8OWXX5Kens7GjRtJSUmhqKjIrr+DgwMrV67kyJEjpKWlsWvXLmbPng2Ah4cHQ4YMITU11a5PamoqgwYNwsvLi0OHDvHVV1/h4OBAx44dCQgI4M9//rPdzMiBAweIjIykSZMmtm2xsbH88MMPHDlypE7nKyJXBt2mEalnZ6qrafmvHFPGPtYzEg9Hx1q3DwoKYtmyZVgsFsLDw8nJyWHZsmVER0fzzjvvcPDgQW666SYAVq1aRZs2bez6//wB2JCQEJ588kkmTZpESkoKAOPGjaN79+4UFhYSEBBAUVERb7/9Njt27ADg888/B2DBggUsXbqUkJAQlixZQkxMDJ988gmNGjXi5MmTdkEEsK2fPHmybhdIRK4ImhkREZuuXbtisVhs6926dePTTz/l6NGjODk50alTJ9u+iIgIvL297frv2LGDXr160bRpU7y8vBg5ciTffPMNZ86cAaBz5860a9eOtLQ0ANauXUtwcDA9e/YEoLq6GoB58+Zx991306lTJ1JTU7FYLLz++uv1eeoiYiLNjIjUM3cHB471jDRt7Mvl+PHj9OvXj/vuu4+nnnqKRo0asXfvXsaOHUt5eTnu7u7Aj7Mjzz//PA899BCpqamMHj3aFoACAgIAaNu2re24rq6utGjRgoKCAgD8/f05ePCg3dhff/21bZ+IXH00MyJSzywWCx6OjqYsP5/lqI3MzEy79ffee4/WrVsTERFBZWUlWVlZtn15eXl89913tvWsrCyqq6tZsmQJXbt2JSwsjBMnTtQYY8SIEXzxxResXLmS3NxcRo0aZdvXqVMnXF1dycvLs22rqKjg+PHjBAcHAz/O1uTk5Ng9r7J9+3YaNGhgF2JE5OqhMCIiNgUFBcyYMYO8vDxeffVVkpOTmTZtGuHh4cTFxTFx4kQyMzPJyspi3LhxWK1WW99WrVpRUVFBcnIyn3/+OWvWrOHFF1+sMYaPjw8DBw4kMTGRPn360KxZM9u+Bg0aMGnSJB599FG2bdtGXl4e9913HwCDBw8GoE+fPrRt25aRI0fy0Ucf8c9//pOHH36Y+++/H1dX13q+QiJSHxRGRMQmPj6esrIyOnfuzP3338+0adOYMGEC8OO3XgIDA4mOjmbgwIFMmDABPz8/W9/27duzdOlSFi9ezPXXX8+6det4+umnzzvOT7duxowZU2PfM888w5AhQxg5ciQ33XQTX3zxBbt27cLHxwcAR0dH3nzzTRwdHenWrRsjRowgPj6exx9/vB6uiIhcDhajrt/9E5GLOnv2LPn5+YSGhuLm5mZ2OVekNWvW8MADD3DixAlcXFzMLueqos+XXIv0AKuIXDZnzpyhsLCQRYsWMXHiRAUREQF0m0ZELqOkpCQiIiLw9/dnzpw5ZpcjIlcI3aYRucQ0jS71SZ8vuRZpZkRERERMpTAiIiIiplIYEREREVMpjIiIiIipFEZERETEVAojIiIiYiqFEREBICYmhunTp9epT0hICMuXL6+XekTkj0NhRESuGBkZGVgslvMu77//vq3d4cOHufnmm3FzcyMoKIikpCQTqxaR30s/By8iV4zu3btTWFhot+2RRx5h586d3HjjjQD88MMP9OnTh969e/Piiy+Sk5PDmDFj8Pb2tr3UT0SuLpoZERGbyspKpkyZQsOGDWncuDGPPPIIP/1Ic1FREf3798dqtRIaGsq6detq9F+6dCmRkZF4eHgQFBTE5MmTKSkpAaC0tJQGDRqwceNGuz5btmzBw8OD06dP4+Ligr+/v23x9fVl69atjB49GovFAsC6desoLy9n9erVtGvXjiFDhjB16lSWLl1az1dHROqLwohIPTMMgzPllaYsdX3bQ1paGk5OThw8eJAVK1awdOlSXnrpJQASEhL48ssvSU9PZ+PGjaSkpFBUVGTX38HBgZUrV3LkyBHS0tLYtWsXs2fPBsDDw4MhQ4aQmppq1yc1NZVBgwbh5eVVo55//OMffPPNN4wePdq27cCBA/Ts2dPuJXuxsbHk5eVRXFxcp/MVkSuDbtOI1LOyiirazv+nKWPnPh6Lu0vt/zMPCgpi2bJlWCwWwsPDycnJYdmyZURHR/POO+9w8OBBbrrpJgBWrVpFmzZt7Pr//AHYkJAQnnzySSZNmkRKSgoA48aNs92KCQgIoKioiLfffpsdO3act55Vq1YRGxtLs2bNbNtOnjxJaGioXbsmTZrY9vn4+NT6fEXkyqCZERGx6dq1q+12CEC3bt349NNPOXr0KE5OTnTq1Mm2LyIiAm9vb7v+O3bsoFevXjRt2hQvLy9GjhzJN998w5kzZwDo3Lkz7dq1Iy0tDYC1a9cSHBxMz549a9Tyn//8h3/+85+MHTu2Hs5URK4kmhkRqWdWZ0dyH481bezL5fjx4/Tr14/77ruPp556ikaNGrF3717Gjh1LeXk57u7uwI+zI88//zwPPfQQqampds+D/Fxqaiq+vr7ccccddtv9/f35+uuv7bb9tO7v719PZyci9UlhRKSeWSyWOt0qMVNmZqbd+nvvvUfr1q2JiIigsrKSrKws222avLw8vvvuO1vbrKwsqqurWbJkCQ4OP066vvbaazXGGDFiBLNnz2blypXk5uYyatSoGm0MwyA1NZX4+HicnZ3t9nXr1o158+ZRUVFh27d9+3bCw8N1i0bkKqXbNCJiU1BQwIwZM8jLy+PVV18lOTmZadOmER4eTlxcHBMnTiQzM5OsrCzGjRuH1Wq19W3VqhUVFRUkJyfz+eefs2bNGl588cUaY/j4+DBw4EASExPp06eP3fMgP9m1axf5+fmMGzeuxr5hw4bh4uLC2LFjOXLkCBs2bGDFihXMmDHj0l4MEblsFEZExCY+Pp6ysjI6d+7M/fffz7Rp02y/3ZGamkpgYCDR0dEMHDiQCRMm4OfnZ+vbvn17li5dyuLFi7n++utZt24dTz/99HnH+enWzZgxY867f9WqVXTv3p2IiIga+xo2bMi2bdvIz8+nU6dOzJw5k/nz5+s3RkSuYhajrt/9E5GLOnv2LPn5+YSGhuLm5mZ2OVekNWvW8MADD3DixAm7r+jKr9PnS65FV8eNbBG5Jpw5c4bCwkIWLVrExIkTFUREBNBtGhG5jJKSkoiIiMDf3585c+aYXY6IXCF0m0bkEtM0utQnfb7kWqSZERERETGVwoiIiIiYSmFERERETKUwIiIiIqZSGBERERFTKYyIiIiIqRRGRASAmJgYpk+fXqc+ISEhLF++vF7qEZE/DoUREbmifPLJJ9x55500btyYBg0a8Kc//Yn09HS7NgUFBfTt2xd3d3f8/PxITEyksrLSpIpF5PdSGBGRK0q/fv2orKxk165dZGVl0b59e/r168fJkycBqKqqom/fvpSXl7N//37S0tJ4+eWXmT9/vsmVi8hvpTAiUt8MA8pLzVnq+APLlZWVTJkyhYYNG9K4cWMeeeQRfvqR5qKiIvr374/VaiU0NJR169bV6L906VIiIyPx8PAgKCiIyZMnU1JSAkBpaSkNGjRg48aNdn22bNmCh4cHp0+f5r///S+ffvopDz30EFFRUbRu3ZpFixZx5swZ/v3vfwOwbds2cnNzWbt2LR06dODPf/4zTzzxBM8//zzl5eW/5f8hETGZXpQnUt8qzsDCQHPGnnsCXDxq3TwtLY2xY8dy8OBBPvjgAyZMmEDz5s0ZP348CQkJnDhxgvT0dJydnZk6dSpFRUV2/R0cHFi5ciWhoaF8/vnnTJ48mdmzZ5OSkoKHhwdDhgwhNTWVQYMG2fr8tO7l5YWnpyfh4eG88sor3HDDDbi6uvKXv/wFPz8/OnXqBMCBAweIjIykSZMmtmPExsZy3333ceTIETp27Pg7L5qIXG4KIyJiExQUxLJly7BYLISHh5OTk8OyZcuIjo7mnXfe4eDBg9x0000ArFq1ijZt2tj1//kDsCEhITz55JNMmjSJlJQUAMaNG0f37t0pLCwkICCAoqIi3n77bXbs2AGAxWJhx44d3HXXXXh5eeHg4ICfnx/vvvsuPj4+AJw8edIuiAC29Z9u5YjI1UVhRKS+Obv/OENh1th10LVrVywWi229W7duLFmyhKNHj+Lk5GSbnQCIiIjA29vbrv+OHTt4+umn+fjjj/nhhx+orKzk7NmznDlzBnd3dzp37ky7du1IS0vjoYceYu3atQQHB9OzZ08ADMPg/vvvx8/Pjz179mC1WnnppZfo378/77//PgEBAb/9WojIFUvPjIjUN4vlx1slZiw/Cxb17fjx4/Tr14+oqCjeeOMNsrKyeP755wHsnuUYN24cL7/8MvDjLZrRo0fbAtCuXbt48803Wb9+PT169OCGG24gJSUFq9VKWloaAP7+/nz99dd2Y/+07u/vX9+nKSL1QGFERGwyMzPt1t977z1at25NREQElZWVZGVl2fbl5eXx3Xff2dazsrKorq5myZIldO3albCwME6cqDkjNGLECL744gtWrlxJbm4uo0aNsu07c+YM8OOzJz/n4OBAdXU18ONsTU5Ojt3zKtu3b6dBgwa0bdv2t5+8iJhGYUREbAoKCpgxYwZ5eXm8+uqrJCcnM23aNMLDw4mLi2PixIlkZmaSlZXFuHHjsFqttr6tWrWioqKC5ORkPv/8c9asWcOLL75YYwwfHx8GDhxIYmIiffr0oVmzZrZ93bp1w8fHh1GjRvHRRx/xySefkJiYSH5+Pn379gWgT58+tG3blpEjR/LRRx/xz3/+k4cffpj7778fV1fX+r9IInLJKYyIiE18fDxlZWV07tyZ+++/n2nTpjFhwgTgx1sqgYGBREdHM3DgQCZMmICfn5+tb/v27Vm6dCmLFy/m+uuvZ926dTz99NPnHWfs2LGUl5czZswYu+2NGzfm3XffpaSkhFtvvZUbb7yRvXv3snXrVtq3bw+Ao6Mjb775Jo6OjnTr1o0RI0YQHx/P448/Xk9XRUTqm8Uw6vhDBCJyUWfPniU/P5/Q0FDc3NzMLueKtGbNGh544AFOnDiBi4uL2eVcVfT5kmuRvk0jIpfNmTNnKCwsZNGiRUycOFFBREQA3aYRkcsoKSmJiIgI/P39mTNnjtnliMgVQrdpRC4xTaNLfdLnS65FmhkRERERUymMiIiIiKkURkRERMRUCiMiIiJiKoURERERMZXCiIiIiJhKYUREAIiJiWH69OkX3B8SEsLy5cvr5dgi8semX2AVkVp5//338fDwuGibjIwMbrnlFoqLi/H29r48hYnIVU9hRERq5brrrrvo/oqKistUiYhca3SbRqSeGYbBmYozpix1/YHlyspKpkyZQsOGDWncuDGPPPKI7Ri/vE1jsVh44YUXuOOOO/Dw8GD8+PHccsstAPj4+GCxWEhISLC1r66uZvbs2TRq1Ah/f38WLFhgd40WLFhA8+bNcXV1JTAwkKlTp/7may4iVxfNjIjUs7LKMrr8vYspY2cOy8Td2b3W7dPS0hg7diwHDx7kgw8+YMKECTRv3pzx48eft/2CBQtYtGgRy5cvx9HRkTvuuIO7776bvLw8GjRogNVqtTv2jBkzyMzM5MCBAyQkJNCjRw9uu+023njjDZYtW8b69etp164dJ0+e5KOPPvrd5y8iVweFERGxCQoKYtmyZVgsFsLDw8nJyWHZsmUXDCPDhg1j9OjRtvX8/HwA/Pz8ajwzEhUVxaOPPgpA69atee6559i5cye33XYbBQUF+Pv707t3b5ydnWnevDmdO3eun5MUkSuOwohIPbM6Wckclmna2HXRtWtXLBaLbb1bt24sWbKEqqqq87a/8cYba33sqKgou/WAgACKiooAGDx4MMuXL6dFixbExcVx++23079/f5yc9EeUyB+B/ksXqWcWi6VOt0quJr/27Zqfc3Z2tlu3WCxUV1cDP87I5OXlsWPHDrZv387kyZN55pln2L17d41+InLt0QOsImKTmWk/g/Pee+/RunVrHB0da9XfxcUF4IIzKRdjtVrp378/K1euJCMjgwMHDpCTk1Pn44jI1UczIyJiU1BQwIwZM5g4cSKHDh0iOTmZJUuW1Lp/cHAwFouFN998k9tvvx2r1Yqnp+ev9nv55ZepqqqiS5cuuLu7s3btWqxWK8HBwb/ndETkKqGZERGxiY+Pp6ysjM6dO3P//fczbdo0JkyYUOv+TZs25bHHHuOhhx6iSZMmTJkypVb9vL29+dvf/kaPHj2Iiopix44d/L//9//w9fX9raciIlcRi1HXHyIQkYs6e/Ys+fn5hIaG4ubmZnY5co3R50uuRZoZEREREVMpjIiIiIipFEZERETEVAojIiIiYiqFERERETGVwoiIiIiYSmFERERETKUwIiIiIqZSGBERERFTKYyIyAXFxMQwffp0s8sQkWucwoiImObs2bMkJCQQGRmJk5MTd911l9kliYgJFEZExDRVVVVYrVamTp1K7969zS5HREyiMCJSzwzDoPrMGVOWurwHs7S0lPj4eDw9PQkICGDJkiU12pw7d45Zs2bRtGlTPDw86NKlCxkZGXZt9u3bR0xMDO7u7vj4+BAbG0txcfF5x/Tw8OCFF15g/Pjx+Pv71+m6isi1w8nsAkSudUZZGXk3dDJl7PBDWVjc3WvVNjExkd27d7N161b8/PyYO3cuhw4dokOHDrY2U6ZMITc3l/Xr1xMYGMjmzZuJi4sjJyeH1q1bk52dTa9evRgzZgwrVqzAycmJ9PR0qqqq6ukMReRaoDAiIpSUlLBq1SrWrl1Lr169AEhLS6NZs2a2NgUFBaSmplJQUEBgYCAAs2bN4t133yU1NZWFCxeSlJTEjTfeSEpKiq1fu3btLu/JiMhVR2FEpJ5ZrFbCD2WZNnZtHDt2jPLycrp06WLb1qhRI8LDw23rOTk5VFVVERYWZtf33Llz+Pr6ApCdnc3gwYMvQeUi8keiMCJSzywWS61vlVzJSkpKcHR0JCsrC0dHR7t9np6eAFhrGX5ERH5OD7CKCC1btsTZ2ZnMzEzbtuLiYj755BPbeseOHamqqqKoqIhWrVrZLT89fBoVFcXOnTsve/0icnXTzIiI4OnpydixY0lMTMTX1xc/Pz/mzZuHg8P//r0SFhbG8OHDiY+PZ8mSJXTs2JFTp06xc+dOoqKi6Nu3L3PmzCEyMpLJkyczadIkXFxcSE9PZ/DgwTRu3Pi8Y+fm5lJeXs63337L6dOnyc7OBrB7cFZErm0KIyICwDPPPENJSQn9+/fHy8uLmTNn8v3339u1SU1N5cknn2TmzJl89dVXNG7cmK5du9KvXz/gx8Cybds25s6dS+fOnbFarXTp0oWhQ4decNzbb7+dL774wrbesWNHgDp9LVlErm4WQ//Fi1xSZ8+eJT8/n9DQUNzc3MwuR64x+nzJtUjPjIiIiIipFEZERETEVAojIiIiYiqFERERETGVwoiIiIiYSmFERERETKUwIiIiIqZSGBERERFTKYyIiIiIqRRGROSCYmJimD59utll2Dl+/DgWi8X2DhsRufopjIiIac6ePUtCQgKRkZE4OTlx1113mV2SiJhAYURETFNVVYXVamXq1Kn07t3b7HJExCQKIyL1zDAMKs5VmbLU5T2YpaWlxMfH4+npSUBAAEuWLKnR5ty5c8yaNYumTZvi4eFBly5dyMjIsGuzb98+YmJicHd3x8fHh9jYWIqLi887poeHBy+88ALjx4/H39+/Ttf153bv3k3nzp1xdXUlICCAhx56iMrKStv+jRs3EhkZidVqxdfXl969e1NaWgpARkYGnTt3xsPDA29vb3r06GH3FmERqX9OZhcgcq2rLK/mr9N2mzL2hBXROLs61qptYmIiu3fvZuvWrfj5+TF37lwOHTpEhw4dbG2mTJlCbm4u69evJzAwkM2bNxMXF0dOTg6tW7cmOzubXr16MWbMGFasWIGTkxPp6elUVVXV0xnCV199xe23305CQgKvvPIKH3/8MePHj8fNzY0FCxZQWFjI0KFDSUpKYsCAAZw+fZo9e/ZgGAaVlZXcddddjB8/nldffZXy8nIOHjyIxWKpt3pFpCaFERGhpKSEVatWsXbtWnr16gVAWloazZo1s7UpKCggNTWVgoICAgMDAZg1axbvvvsuqampLFy4kKSkJG688UZSUlJs/dq1a1evtaekpBAUFMRzzz2HxWIhIiKCEydO8OCDDzJ//nwKCwuprKxk4MCBBAcHAxAZGQnAt99+y/fff0+/fv1o2bIlAG3atKnXekWkJoURkXrm5OLAhBXRpo1dG8eOHaO8vJwuXbrYtjVq1Ijw8HDbek5ODlVVVYSFhdn1PXfuHL6+vgBkZ2czePDgS1B57R09epRu3brZzWb06NGDkpIS/vOf/9C+fXt69epFZGQksbGx9OnTh0GDBuHj40OjRo1ISEggNjaW2267jd69e3PPPfcQEBBwWc9B5I9OYUSknlksllrfKrmSlZSU4OjoSFZWFo6O9ufj6ekJgNVqNaO0i3J0dGT79u3s37+fbdu2kZyczLx588jMzCQ0NJTU1FSmTp3Ku+++y4YNG3j44YfZvn07Xbt2Nbt0kT8MPcAqIrRs2RJnZ2cyMzNt24qLi/nkk09s6x07dqSqqoqioiJatWplt/z08GlUVBQ7d+68rLW3adOGAwcO2D2su2/fPry8vGy3mSwWCz169OCxxx7jww8/xMXFhc2bN9ud25w5c9i/fz/XX389f//73y/rOYj80SmMiAienp6MHTuWxMREdu3axb///W8SEhJwcPjfHxFhYWEMHz6c+Ph4Nm3aRH5+PgcPHuTpp5/mrbfeAmDOnDm8//77TJ48mcOHD/Pxxx/zwgsv8N///veCY+fm5pKdnW17fiM7O7tOP2g2efJkvvzyS/7v//6Pjz/+mK1bt/Loo48yY8YMHBwcyMzMZOHChXzwwQcUFBSwadMmTp06RZs2bcjPz2fOnDkcOHCAL774gm3btvHpp5/quRGRy80QkUuqrKzMyM3NNcrKyswupU5Onz5tjBgxwnB3dzeaNGliJCUlGdHR0ca0adNsbcrLy4358+cbISEhhrOzsxEQEGAMGDDAOHz4sK1NRkaG0b17d8PV1dXw9vY2YmNjjeLi4guOGxwcbAA1lgvJz883AOPDDz+0G/Omm24yXFxcDH9/f+PBBx80KioqDMMwjNzcXCM2Nta47rrrDFdXVyMsLMxITk42DMMwTp48adx1111GQECA4eLiYgQHBxvz5883qqqqfttFvAyu1s+XyMVYDKMOP0QgIr/q7Nmz5OfnExoaipubm9nlyDVGny+5Fuk2jYiIiJhKYURERERMpTAiIiIiplIYEREREVMpjIiIiIipFEZERETEVAojIiIiYiqFERERETGVwoiIiIiYSmFERC4oJiaG6dOnm12GnePHj2OxWOr0/hoRubIpjIiIac6ePUtCQgKRkZE4OTlx1113mV1SvbkSg53IlUJhRERMU1VVhdVqZerUqfTu3dvscn6TiooKs0sQueopjIjUM8MwqDh71pSlLu/BLC0tJT4+Hk9PTwICAliyZEmNNufOnWPWrFk0bdoUDw8PunTpQkZGhl2bffv2ERMTg7u7Oz4+PsTGxlJcXHzeMT08PHjhhRcYP348/v7+dbquP7d79246d+6Mq6srAQEBPPTQQ1RWVtr2b9y4kcjISKxWK76+vvTu3ZvS0lIAMjIy6Ny5Mx4eHnh7e9OjRw+++OKL847z0y2iDRs2EB0djZubG+vWreObb75h6NChNG3aFHd3dyIjI3n11Vdt/RISEti9ezcrVqzAYrFgsVg4fvw4AP/+97/585//jKenJ02aNGHkyJH897///c3XQuRq5GR2ASLXuspz51g5apApY09N24hzLd/smpiYyO7du9m6dSt+fn7MnTuXQ4cO0aFDB1ubKVOmkJuby/r16wkMDGTz5s3ExcWRk5ND69atyc7OplevXowZM4YVK1bg5OREeno6VVVV9XSG8NVXX3H77beTkJDAK6+8wscff8z48eNxc3NjwYIFFBYWMnToUJKSkhgwYACnT59mz549GIZBZWUld911F+PHj+fVV1+lvLycgwcPYrFYLjrmQw89xJIlS+jYsSNubm6cPXuWTp068eCDD9KgQQPeeustRo4cScuWLencuTMrVqzgk08+4frrr+fxxx8H4LrrruO7777j1ltvZdy4cSxbtoyysjIefPBB7rnnHnbt2lVv10zkSqMwIiKUlJSwatUq1q5dS69evQBIS0ujWbNmtjYFBQWkpqZSUFBAYGAgALNmzeLdd98lNTWVhQsXkpSUxI033khKSoqtX7t27eq19pSUFIKCgnjuueewWCxERERw4sQJHnzwQebPn09hYSGVlZUMHDiQ4OBgACIjIwH49ttv+f777+nXrx8tW7YEoE2bNr865vTp0xk4cKDdtlmzZtn+9//93//xz3/+k9dee43OnTvTsGFDXFxccHd3t5sBeu655+jYsSMLFy60bVu9ejVBQUF88sknhIWF/fYLI3IVURgRqWdOrq5MTdto2ti1cezYMcrLy+nSpYttW6NGjQgPD7et5+TkUFVVVeMvyHPnzuHr6wtAdnY2gwcPvgSV197Ro0fp1q2b3WxGjx49KCkp4T//+Q/t27enV69eREZGEhsbS58+fRg0aBA+Pj40atSIhIQEYmNjue222+jduzf33HMPAQEBFx3zxhtvtFuvqqpi4cKFvPbaa3z11VeUl5dz7tw53N3dL3qcjz76iPT0dDw9PWvsO3bsmMKI/GEojIjUM4vFUutbJVeykpISHB0dycrKwtHR0W7fT3+ZWq1WM0q7KEdHR7Zv387+/fvZtm0bycnJzJs3j8zMTEJDQ0lNTWXq1Km8++67bNiwgYcffpjt27fTtWvXCx7Tw8PDbv2ZZ55hxYoVLF++nMjISDw8PJg+fTrl5eUXra2kpIT+/fuzePHiGvt+LRCJXEv0AKuI0LJlS5ydncnMzLRtKy4u5pNPPrGtd+zYkaqqKoqKimjVqpXd8tOth6ioKHbu3HlZa2/Tpg0HDhywe1h33759eHl52W4zWSwWevTowWOPPcaHH36Ii4sLmzdvtju3OXPmsH//fq6//nr+/ve/16mGffv2ceeddzJixAjat29PixYt7K4dgIuLS41nZ2644QaOHDlCSEhIjWv6y8Ajci1TGBERPD09GTt2LImJiezatYt///vfJCQk4ODwvz8iwsLCGD58OPHx8WzatIn8/HwOHjzI008/zVtvvQXAnDlzeP/995k8eTKHDx/m448/5oUXXrjot0Nyc3PJzs62Pb+RnZ1dpx80mzx5Ml9++SX/93//x8cff8zWrVt59NFHmTFjBg4ODmRmZrJw4UI++OADCgoK2LRpE6dOnaJNmzbk5+czZ84cDhw4wBdffMG2bdv49NNPa/XcyM+1bt3aNvty9OhRJk6cyNdff23XJiQkhMzMTI4fP85///tfqquruf/++/n2228ZOnQo77//PseOHeOf//wno0ePrteHfkWuOIaIXFJlZWVGbm6uUVZWZnYpdXL69GljxIgRhru7u9GkSRMjKSnJiI6ONqZNm2ZrU15ebsyfP98ICQkxnJ2djYCAAGPAgAHG4cOHbW0yMjKM7t27G66uroa3t7cRGxtrFBcXX3Dc4OBgA6ixXEh+fr4BGB9++KHdmDfddJPh4uJi+Pv7Gw8++KBRUVFhGIZh5ObmGrGxscZ1111nuLq6GmFhYUZycrJhGIZx8uRJ46677jICAgIMFxcXIzg42Jg/f75RVVVV67ENwzC++eYb48477zQ8PT0NPz8/4+GHHzbi4+ONO++809YmLy/P6Nq1q2G1Wg3AyM/PNwzDMD755BNjwIABhre3t2G1Wo2IiAhj+vTpRnV19XlruFo/XyIXYzGMOvwQgYj8qrNnz5Kfn09oaChu18CzInJl0edLrkW6TSMiIiKmUhgRERERUymMiIiIiKkURkRERMRUCiMiIiJiKoURERERMZXCiIiIiJhKYURERERMpTAiIiIiplIYEZELiomJYfr06WaXISLXOIURETFNRkYGd955JwEBAXh4eNChQwfWrVtndlkicpkpjIiIafbv309UVBRvvPEGhw8fZvTo0cTHx/Pmm2+aXZqIXEYKIyL1zDAMqsurTFnq8h7M0tJS4uPj8fT0JCAggCVLltRoc+7cOWbNmkXTpk3x8PCgS5cuZGRk2LXZt28fMTExuLu74+PjQ2xsLMXFxecdc+7cuTzxxBN0796dli1bMm3aNOLi4ti0aVOdrrGIXN2czC5A5FpnVFRzYv5+U8YOfLw7FhfHWrVNTExk9+7dbN26FT8/P+bOncuhQ4fo0KGDrc2UKVPIzc1l/fr1BAYGsnnzZuLi4sjJyaF169ZkZ2fTq1cvxowZw4oVK3ByciI9PZ2qqqpa1/z999/Tpk2bup6qiFzFFEZEhJKSElatWsXatWvp1asXAGlpaTRr1szWpqCggNTUVAoKCggMDARg1qxZvPvuu6SmprJw4UKSkpK48cYbSUlJsfVr165dret47bXXeP/99/nLX/5yic5MRK4GCiMi9czi7EDg491NG7s2jh07Rnl5OV26dLFta9SoEeHh4bb1nJwcqqqqCAsLs+t77tw5fH19AcjOzmbw4MG/qdb09HRGjx7N3/72tzoFGBG5+imMiNQzi8VS61slV7KSkhIcHR3JysrC0dH+fDw9PQGwWq2/6di7d++mf//+LFu2jPj4+N9dq4hcXfQAq4jQsmVLnJ2dyczMtG0rLi7mk08+sa137NiRqqoqioqKaNWqld3i7+8PQFRUFDt37qzT2BkZGfTt25fFixczYcKES3NCInJVURgRETw9PRk7diyJiYns2rWLf//73yQkJODg8L8/IsLCwhg+fDjx8fFs2rSJ/Px8Dh48yNNPP81bb70FwJw5c3j//feZPHkyhw8f5uOPP+aFF17gv//973nHTU9Pp2/fvkydOpW7776bkydPcvLkSb799tvLct4icmVQGBERAJ555hluvvlm+vfvT+/evfnTn/5Ep06d7NqkpqYSHx/PzJkzCQ8P56677uL999+nefPmwI+BZdu2bXz00Ud07tyZbt26sXXrVpyczn9HOC0tjTNnzvD0008TEBBgWwYOHFjv5ysiVw6LUZcfIhCRX3X27Fny8/MJDQ3Fzc3N7HLkGqPPl1yLNDMiIiIiplIYEREREVMpjIiIiIipFEZERETEVAojIiIiYiqFERERETGVwoiIiIiYSmFERERETKUwIiIiIqZSGBGRC4qJiWH69Olml2EnIyMDi8XCd999Z3YpInKJKIyIiGkyMjK48847CQgIwMPDgw4dOrBu3TqzyxKRy0xhRERMs3//fqKionjjjTc4fPgwo0ePJj4+njfffNPs0kTkMlIYEalnhmFQXl5uylKX92CWlpYSHx+Pp6cnAQEBLFmypEabc+fOMWvWLJo2bYqHhwddunQhIyPDrs2+ffuIiYnB3d0dHx8fYmNjKS4uPu+Yc+fO5YknnqB79+60bNmSadOmERcXx6ZNm+p0jd944w3atWuHq6srISEhNWpPSUmhdevWuLm50aRJEwYNGmTbt3HjRiIjI7Farfj6+tK7d29KS0vrNL6I/D7nf6+3iFwyFRUVLFy40JSx586di4uLS63aJiYmsnv3brZu3Yqfnx9z587l0KFDdOjQwdZmypQp5Obmsn79egIDA9m8eTNxcXHk5OTQunVrsrOz6dWrF2PGjGHFihU4OTmRnp5OVVVVrWv+/vvvadOmTa3bZ2Vlcc8997BgwQLuvfde9u/fz+TJk/H19SUhIYEPPviAqVOnsmbNGrp37863337Lnj17ACgsLGTo0KEkJSUxYMAATp8+zZ49e+oU4kTk91MYERFKSkpYtWoVa9eupVevXgCkpaXRrFkzW5uCggJSU1MpKCggMDAQgFmzZvHuu++SmprKwoULSUpK4sYbbyQlJcXWr127drWu47XXXuP999/nL3/5S637LF26lF69evHII48AEBYWRm5uLs888wwJCQkUFBTg4eFBv3798PLyIjg4mI4dOwI/hpHKykoGDhxIcHAwAJGRkbUeW0QuDYURkXrm7OzM3LlzTRu7No4dO0Z5eTldunSxbWvUqBHh4eG29ZycHKqqqggLC7Pre+7cOXx9fQHIzs5m8ODBv6nW9PR0Ro8ezd/+9rc6BZijR49y55132m3r0aMHy5cvp6qqittuu43g4GBatGhBXFwccXFxDBgwAHd3d9q3b0+vXr2IjIwkNjaWPn36MGjQIHx8fH7TOYjIb6MwIlLPLBZLrW+VXMlKSkpwdHQkKysLR0dHu32enp4AWK3W33Ts3bt3079/f5YtW0Z8fPzvrvXnvLy8OHToEBkZGWzbto358+ezYMEC3n//fby9vdm+fTv79+9n27ZtJCcnM2/ePDIzMwkNDb2kdYjIhekBVhGhZcuWODs7k5mZadtWXFzMJ598Ylvv2LEjVVVVFBUV0apVK7vF398fgKioKHbu3FmnsTMyMujbty+LFy9mwoQJda69TZs27Nu3z27bvn37CAsLs4UmJycnevfuTVJSEocPH+b48ePs2rUL+DEs9ujRg8cee4wPP/wQFxcXNm/eXOc6ROS308yIiODp6cnYsWNJTEzE19cXPz8/5s2bh4PD//69EhYWxvDhw4mPj2fJkiV07NiRU6dOsXPnTqKioujbty9z5swhMjKSyZMnM2nSJFxcXEhPT2fw4ME0bty4xrjp6en069ePadOmcffdd3Py5EkAXFxcaNSoUa1qnzlzJjfddBNPPPEE9957LwcOHOC5556zPbfy5ptv8vnnn9OzZ098fHx4++23qa6uJjw8nMzMTHbu3EmfPn3w8/MjMzOTU6dO1ekBWhG5BAwRuaTKysqM3Nxco6yszOxS6uT06dPGiBEjDHd3d6NJkyZGUlKSER0dbUybNs3Wpry83Jg/f74REhJiODs7GwEBAcaAAQOMw4cP29pkZGQY3bt3N1xdXQ1vb28jNjbWKC4uPu+Yo0aNMoAaS3R09AXrTE9PNwC7Y27cuNFo27at4ezsbDRv3tx45plnbPv27NljREdHGz4+PobVajWioqKMDRs2GIZhGLm5uUZsbKxx3XXXGa6urkZYWJiRnJz8m67f5XK1fr5ELsZiGPoOm8ildPbsWfLz8wkNDcXNzc3scuQao8+XXIv0zIiIiIiYSmFERERETKUwIiIiIqZSGBERERFTKYyIiIiIqRRGRERExFQKIyIiImIqhRERERExlcKIiIiImEphREQuKCYmhunTp5tdhp2MjAwsFgvfffed2aWIyCWiMCIipsnIyODOO+8kICAADw8POnTowLp168wuq16EhISwfPlys8sQuSIpjIiIafbv309UVBRvvPEGhw8fZvTo0cTHx/Pmm2+aXVqtGIZBZWWl2WWIXPUURkTqmWEYVFWdMWWpy3swS0tLiY+Px9PTk4CAAJYsWVKjzblz55g1axZNmzbFw8ODLl26kJGRYddm3759xMTE4O7ujo+PD7GxsRQXF593zLlz5/LEE0/QvXt3WrZsybRp04iLi2PTpk11usZvvPEG7dq1w9XVlZCQkBq1p6Sk0Lp1a9zc3GjSpAmDBg2y7du4cSORkZFYrVZ8fX3p3bs3paWl5x3np1tE77zzDp06dcLV1ZW9e/dy7Ngx7rzzTpo0aYKnpyc33XQTO3bssPWLiYnhiy++4IEHHsBisWCxWGz79u7dy80334zVaiUoKIipU6decHyRa5WT2QWIXOuqq8vI2B1pytgx0Tk4OrrXqm1iYiK7d+9m69at+Pn5MXfuXA4dOkSHDh1sbaZMmUJubi7r168nMDCQzZs3ExcXR05ODq1btyY7O5tevXoxZswYVqxYgZOTE+np6VRVVdW65u+//542bdrUun1WVhb33HMPCxYs4N5772X//v1MnjwZX19fEhIS+OCDD5g6dSpr1qyhe/fufPvtt+zZsweAwsJChg4dSlJSEgMGDOD06dPs2bPnV0PcQw89xLPPPkuLFi3w8fHhyy+/5Pbbb+epp57C1dWVV155hf79+5OXl0fz5s3ZtGkT7du3Z8KECYwfP952nGPHjhEXF8eTTz7J6tWrOXXqFFOmTGHKlCmkpqbW+hqIXO0sRl3+6SQiv+qXr3ivqjpzxYeRkpISfH19Wbt2LYMHDwbg22+/pVmzZkyYMIHly5dTUFBAixYtKCgoIDAw0Na3d+/edO7cmYULFzJs2DAKCgrYu3fvb6r3tddeY+TIkRw6dIh27dqdt01GRga33HILxcXFeHt7M3z4cE6dOsW2bdtsbWbPns1bb73FkSNH2LRpE6NHj+Y///kPXl5edsc6dOgQnTp14vjx4wQHB/9qfT+NvWXLFu68886Ltr3++uuZNGkSU6ZMAX58ZmT69Ol2DwSPGzcOR0dH/vKXv9i27d27l+joaEpLS3Fzc6tx3F9+vkSuBZoZEalnDg5WYqJzTBu7No4dO0Z5eTldunSxbWvUqBHh4eG29ZycHKqqqggLC7Pre+7cOXx9fQHIzs62hZm6Sk9PZ/To0fztb3+7YBA5n6NHj9YIBj169GD58uVUVVVx2223ERwcTIsWLYiLiyMuLo4BAwbg7u5O+/bt6dWrF5GRkcTGxtKnTx8GDRqEj4/PRce88cYb7dZLSkpYsGABb731FoWFhVRWVlJWVkZBQcFFj/PRRx9x+PBhu4d2DcOgurqa/Pz8Os0QiVzNFEZE6pnFYqn1rZIrWUlJCY6OjmRlZeHo6Gi3z9PTEwCrtXbh55d2795N//79WbZsGfHx8b+71p/z8vLi0KFDZGRksG3bNubPn8+CBQt4//338fb2Zvv27ezfv59t27aRnJzMvHnzyMzMJDQ09ILH9PDwsFufNWsW27dv59lnn6VVq1ZYrVYGDRpEeXn5RWsrKSlh4sSJTJ06tca+5s2b/7YTFrkK6QFWEaFly5Y4OzuTmZlp21ZcXMwnn3xiW+/YsSNVVVUUFRXRqlUru8Xf3x+AqKgodu7cWaexMzIy6Nu3L4sXL2bChAl1rr1Nmzbs27fPbtu+ffsICwuzhSYnJyd69+5NUlIShw8f5vjx4+zatQv4MSz26NGDxx57jA8//BAXFxc2b95cpxr27dtHQkICAwYMIDIyEn9/f44fP27XxsXFpcazMzfccAO5ubk1rmerVq1wcXGp45UQuXppZkRE8PT0ZOzYsSQmJuLr64ufnx/z5s3DweF//14JCwtj+PDhxMfHs2TJEjp27MipU6fYuXMnUVFR9O3blzlz5hAZGcnkyZOZNGkSLi4upKenM3jwYBo3blxj3PT0dPr168e0adO4++67OXnyJPDjX9yNGjWqVe0zZ87kpptu4oknnuDee+/lwIEDPPfcc6SkpADw5ptv8vnnn9OzZ098fHx4++23qa6uJjw8nMzMTHbu3EmfPn3w8/MjMzOTU6dO1fn2SOvWrdm0aRP9+/fHYrHwyCOPUF1dbdcmJCSEf/3rXwwZMgRXV1caN27Mgw8+SNeuXZkyZQrjxo3Dw8OD3Nxctm/fznPPPVenGkSuaoaIXFJlZWVGbm6uUVZWZnYpdXL69GljxIgRhru7u9GkSRMjKSnJiI6ONqZNm2ZrU15ebsyfP98ICQkxnJ2djYCAAGPAgAHG4cOHbW0yMjKM7t27G66uroa3t7cRGxtrFBcXn3fMUaNGGUCNJTo6+oJ1pqenG4DdMTdu3Gi0bdvWcHZ2Npo3b24888wztn179uwxoqOjDR8fH8NqtRpRUVHGhg0bDMMwjNzcXCM2Nta47rrrDFdXVyMsLMxITk6u09iGYRj5+fnGLbfcYlitViMoKMh47rnnaly7AwcOGFFRUYarq6vx8z96Dx48aNx2222Gp6en4eHhYURFRRlPPfXUBWu4Wj9fIhejb9OIXGL6toPUJ32+5FqkZ0ZERETEVAojIiIiYiqFERERETGVwoiIiIiYSmFERERETKUwIiIiIqZSGBERERFTKYyIiIiIqRRGRERExFQKIyJyQTExMUyfPt3sMkTkGqcwIiKmycvL45ZbbqFJkya4ubnRokULHn74YSoqKswuTUQuI721V0RM4+zsTHx8PDfccAPe3t589NFHjB8/nurqahYuXGh2eSJymWhmRKSeGYZBaVWVKUtd3oNZWlpKfHw8np6eBAQEsGTJkhptzp07x6xZs2jatCkeHh506dKFjIwMuzb79u0jJiYGd3d3fHx8iI2Npbi4+LxjtmjRgtGjR9O+fXuCg4O54447GD58OHv27KnTNRaRq5tmRkTq2Znqalr+K8eUsY/1jMTD0bFWbRMTE9m9ezdbt27Fz8+PuXPncujQITp06GBrM2XKFHJzc1m/fj2BgYFs3ryZuLg4cnJyaN26NdnZ2fTq1YsxY8awYsUKnJycSE9Pp6qqqlY1fPbZZ7z77rsMHDjwt5yuiFylLEZd/ukkIr/ql694L62quuLDSElJCb6+vqxdu5bBgwcD8O2339KsWTMmTJjA8uXLKSgooEWLFhQUFBAYGGjr27t3bzp37szChQsZNmwYBQUF7N27t051du/enUOHDnHu3DkmTJjACy+8gIODJm7P55efL5FrgWZGROqZu4MDx3pGmjZ2bRw7dozy8nK6dOli29aoUSPCw8Nt6zk5OVRVVREWFmbX99y5c/j6+gKQnZ1tCzN1sWHDBk6fPs1HH31EYmIizz77LLNnz67zcUTk6qQwIlLPLBZLrW+VXMlKSkpwdHQkKysLx1+cj6enJwBWq/U3HTsoKAiAtm3bUlVVxYQJE5g5c2aNcUTk2qR5UBGhZcuWODs7k5mZadtWXFzMJ598Ylvv2LEjVVVVFBUV0apVK7vF398fgKioKHbu3Pm7aqmurqaiooLq6urfdRwRuXpoZkRE8PT0ZOzYsSQmJuLr64ufnx/z5s2ze24jLCyM4cOHEx8fz5IlS+jYsSOnTp1i586dREVF0bdvX+bMmUNkZCSTJ09m0qRJuLi4kJ6ezuDBg2ncuHGNcdetW4ezszORkZG4urrywQcfMGfOHO69916cnZ0v5yUQERMpjIgIAM888wwlJSX0798fLy8vZs6cyffff2/XJjU1lSeffJKZM2fy1Vdf0bhxY7p27Uq/fv2AHwPLtm3bmDt3Lp07d8ZqtdKlSxeGDh163jGdnJxYvHgxn3zyCYZhEBwczJQpU3jggQfq/XxF5Mqhb9OIXGL6toPUJ32+5FqkZ0ZERETEVAojIiIiYiqFERERETGVwoiIiIiYSmFERERETKUwIiIiIqZSGBERERFTKYyIiIiIqRRGROSCYmJimD59utll2MnIyMBisfDdd9+ZXYqIXCIKIyJimry8PG655RaaNGmCm5sbLVq04OGHH6aiosLs0kTkMtK7aUTENM7OzsTHx3PDDTfg7e3NRx99xPjx46murmbhwoVmlycil4lmRkQEgNLSUuLj4/H09CQgIIAlS5bUaHPu3DlmzZpF06ZN8fDwoEuXLmRkZNi12bdvHzExMbi7u+Pj40NsbCzFxcXnHbNFixaMHj2a9u3bExwczB133MHw4cPZs2dPnWp/4403aNeuHa6uroSEhNSoPSUlhdatW+Pm5kaTJk0YNGiQbd/GjRuJjIzEarXi6+tL7969KS0trdP4IvL7aGZEpJ4ZhkFZRZUpY1udHbFYLLVqm5iYyO7du9m6dSt+fn7MnTuXQ4cO0aFDB1ubKVOmkJuby/r16wkMDGTz5s3ExcWRk5ND69atyc7OplevXowZM4YVK1bg5OREeno6VVW1O//PPvuMd999l4EDB9b6HLOysrjnnntYsGAB9957L/v372fy5Mn4+vqSkJDABx98wNSpU1mzZg3du3fn22+/tYWdwsJChg4dSlJSEgMGDOD06dPs2bMHvT9U5PLSW3tFLrFfvlX1THklbef/05Rach+Pxd3l1//NUVJSgq+vL2vXrmXw4MEAfPvttzRr1owJEyawfPlyCgoKaNGiBQUFBQQGBtr69u7dm86dO7Nw4UKGDRtGQUEBe/furVOd3bt359ChQ5w7d44JEybwwgsv4OBw/onbjIwMbrnlFoqLi/H29mb48OGcOnWKbdu22drMnj2bt956iyNHjrBp0yZGjx7Nf/7zH7y8vOyOdejQITp16sTx48cJDg6uU81m0Vt75Vqk2zQiwrFjxygvL6dLly62bY0aNSI8PNy2npOTQ1VVFWFhYXh6etqW3bt3c+zYMQDbzEhdbdiwgUOHDvH3v/+dt956i2effbbWfY8ePUqPHj3stvXo0YNPP/2UqqoqbrvtNoKDg2nRogUjR45k3bp1nDlzBoD27dvTq1cvIiMjGTx4MH/7298ueEtJROqPbtOI1DOrsyO5j8eaNvalUlJSgqOjI1lZWTg62h/X09Pzx/Gs1t907KCgIADatm1LVVUVEyZMYObMmTXG+S28vLw4dOgQGRkZbNu2jfnz57NgwQLef/99vL292b59O/v372fbtm0kJyczb948MjMzCQ0N/d1ji0jtaGZEpJ5ZLBbcXZxMWWr7vEjLli1xdnYmMzPTtq24uJhPPvnEtt6xY0eqqqooKiqiVatWdou/vz8AUVFR7Ny583ddr+rqaioqKqiurq5V+zZt2rBv3z67bfv27SMsLMwWZpycnOjduzdJSUkcPnyY48ePs2vXLuDH/3969OjBY489xocffoiLiwubN2/+XecgInWjmRERwdPTk7Fjx5KYmIivry9+fn7MmzfP7rmNsLAwhg8fTnx8PEuWLKFjx46cOnWKnTt3EhUVRd++fZkzZw6RkZFMnjyZSZMm4eLiQnp6OoMHD6Zx48Y1xl23bh3Ozs5ERkbi6urKBx98wJw5c7j33ntxdnauVe0zZ87kpptu4oknnuDee+/lwIEDPPfcc6SkpADw5ptv8vnnn9OzZ098fHx4++23qa6uJjw8nMzMTHbu3EmfPn3w8/MjMzOTU6dO0aZNm0tzYUWkdgwRuaTKysqM3Nxco6yszOxS6uT06dPGiBEjDHd3d6NJkyZGUlKSER0dbUybNs3Wpry83Jg/f74REhJiODs7GwEBAcaAAQOMw4cP29pkZGQY3bt3N1xdXQ1vb28jNjbWKC4uPu+Y69evN2644QbD09PT8PDwMNq2bWssXLjwotcuPT3dAOyOuXHjRqNt27aGs7Oz0bx5c+OZZ56x7duzZ48RHR1t+Pj4GFar1YiKijI2bNhgGIZh5ObmGrGxscZ1111nuLq6GmFhYUZycvJvu4CXydX6+RK5GH2bRuQS07cdpD7p8yXXIj0zIiIiIqZSGBERERFTKYyIiIiIqRRGRERExFQKIyIiImIqhRERERExlcKIiIiImEphREREREylMCIiIiKmUhgRkQuKiYlh+vTpZpdhJyMjA4vFwnfffWd2KSJyiSiMiIhp8vLyuOWWW2jSpAlubm60aNGChx9+mIqKCrNLu+RCQkJYvny52WWIXJH01l4RMY2zszPx8fHccMMNeHt789FHHzF+/Hiqq6tZuHCh2eX9KsMwqKqqwslJf5SK/B6aGRERAEpLS4mPj8fT05OAgACWLFlSo825c+eYNWsWTZs2xcPDgy5dupCRkWHXZt++fcTExODu7o6Pjw+xsbEUFxefd8wWLVowevRo2rdvT3BwMHfccQfDhw9nz549dar9jTfeoF27dri6uhISElKj9pSUFFq3bo2bmxtNmjRh0KBBtn0bN24kMjISq9WKr68vvXv3prS09Lzj/HSL6J133qFTp064urqyd+9ejh07xp133kmTJk3w9PTkpptuYseOHbZ+MTExfPHFFzzwwANYLBYsFott3969e7n55puxWq0EBQUxderUC44vcq1SGBGpb4YB5aXmLHV4KXdiYiK7d+9m69atbNu2jYyMDA4dOmTXZsqUKRw4cID169dz+PBhBg8eTFxcHJ9++ikA2dnZ9OrVi7Zt23LgwAH27t1L//79qaqqqlUNn332Ge+++y7R0dG1rjsrK4t77rmHIUOGkJOTw4IFC3jkkUd4+eWXAfjggw+YOnUqjz/+OHl5ebz77rv07NkTgMLCQoYOHcqYMWM4evQoGRkZDBw4kF97mflDDz3EokWLOHr0KFFRUZSUlHD77bezc+dOPvzwQ+Li4ujfvz8FBQUAbNq0iWbNmvH4449TWFhIYWEhAMeOHSMuLo67776bw4cPs2HDBvbu3cuUKVNqff4i1wKL8Wv/1YlIndR4xXt5KSwMNKeYuSfAxeNXm5WUlODr68vatWsZPHgwAN9++y3NmjVjwoQJLF++nIKCAlq0aEFBQQGBgf87n969e9O5c2cWLlzIsGHDKCgoYO/evXUqs3v37hw6dIhz584xYcIEXnjhBRwczv9vpYyMDG655RaKi4vx9vZm+PDhnDp1im3bttnazJ49m7feeosjR46wadMmRo8ezX/+8x+8vLzsjnXo0CE6derE8ePHCQ4O/tU6fxp7y5Yt3HnnnRdte/311zNp0iRbsAgJCWH69Ol2DwSPGzcOR0dH/vKXv9i27d27l+joaEpLS3/8/PxCjc+XyDVAMyMiwrFjxygvL6dLly62bY0aNSI8PNy2npOTQ1VVFWFhYXh6etqW3bt3c+zYMeB/MyN1tWHDBg4dOsTf//533nrrLZ599tla9z169Cg9evSw29ajRw8+/fRTqqqquO222wgODqZFixaMHDmSdevWcebMGQDat29Pr169iIyMZPDgwfztb3+74C2ln7vxxhvt1ktKSpg1axZt2rTB29sbT09Pjh49apsZuZCPPvqIl19+2e56xsbGUl1dTX5+fq2vgcjVTk9didQ3Z/cfZyjMGvsSKSkpwdHRkaysLBwdHe32eXp6AmC1Wn/TsYOCggBo27YtVVVVTJgwgZkzZ9YY57fw8vLi0KFDZGRksG3bNubPn8+CBQt4//338fb2Zvv27ezfv59t27aRnJzMvHnzyMzMJDQ09ILH9PCwn22aNWsW27dv59lnn6VVq1ZYrVYGDRpEeXn5RWsrKSlh4sSJTJ06tca+5s2b/7YTFrkKKYyI1DeLpVa3SszUsmVLnJ2dyczMtP0lWFxczCeffGJ7fqNjx45UVVVRVFTEzTfffN7jREVFsXPnTh577LHfXEt1dTUVFRVUV1fXKoy0adOGffv22W3bt28fYWFhtv5OTk707t2b3r178+ijj+Lt7c2uXbsYOHAgFouFHj160KNHD+bPn09wcDCbN29mxowZta553759JCQkMGDAAODHkHH8+HG7Ni4uLjWenbnhhhvIzc2lVatWtR5L5FqkMCIieHp6MnbsWBITE/H19cXPz4958+bZPbcRFhbG8OHDiY+PZ8mSJXTs2JFTp06xc+dOoqKi6Nu3L3PmzCEyMpLJkyczadIkXFxcSE9PZ/DgwTRu3LjGuOvWrcPZ2ZnIyEhcXV354IMPmDNnDvfeey/Ozs61qn3mzJncdNNNPPHEE9x7770cOHCA5557jpSUFADefPNNPv/8c3r27ImPjw9vv/021dXVhIeHk5mZyc6dO+nTpw9+fn5kZmZy6tQp2rRpU6fr17p1azZt2kT//v2xWCw88sgjVFdX27UJCQnhX//6F0OGDMHV1ZXGjRvz4IMP0rVrV6ZMmcK4cePw8PAgNzeX7du389xzz9WpBpGrmiEil1RZWZmRm5trlJWVmV1KnZw+fdoYMWKE4e7ubjRp0sRISkoyoqOjjWnTptnalJeXG/PnzzdCQkIMZ2dnIyAgwBgwYIBx+PBhW5uMjAyje/fuhqurq+Ht7W3ExsYaxcXF5x1z/fr1xg033GB4enoaHh4eRtu2bY2FCxde9Nqlp6cbgN0xN27caLRt29ZwdnY2mjdvbjzzzDO2fXv27DGio6MNHx8fw2q1GlFRUcaGDRsMwzCM3NxcIzY21rjuuusMV1dXIywszEhOTq7T2IZhGPn5+cYtt9xiWK1WIygoyHjuuedqXLsDBw4YUVFRhqurq/HzP3oPHjxo3HbbbbZrEBUVZTz11FMXrOFq/XyJXIy+TSNyienbDlKf9PmSa5G+TSMiIiKmUhgRERERUymMiIiIiKkURkRERMRUCiMiIiJiKoURERERMZXCiIiIiJhKYURERERMdVWFkX/961/079+fwMBALBYLW7ZsqVP/BQsWYLFYaiy/fOmViIiIXD5XVRgpLS2lffv2PP/887+p/6xZsygsLLRb2rZty+DBgy9xpSLXhpiYGKZPn252GSJyjbuqwsif//xnnnzySdubMX/p3LlzzJo1i6ZNm+Lh4UGXLl3IyMiw7ff09MTf39+2fP311+Tm5jJ27NjLdAYiciGfffYZXl5eeHt7m12KiFxmV1UY+TVTpkzhwIEDrF+/nsOHDzN48GDi4uL49NNPz9v+pZdeIiws7IKvQxeRy6OiooKhQ4fqv0WRP6hrJowUFBSQmprK66+/zs0330zLli2ZNWsWf/rTn0hNTa3R/uzZs6xbt06zIiL/v9LSUuLj4/H09CQgIIAlS5bUaPNrs48A+/btIyYmBnd3d3x8fIiNjaW4uPiiYz/88MNERERwzz33XMpTEpGrhJPZBVwqOTk5VFVVERYWZrf93Llz+Pr61mi/efNmTp8+zahRoy5XifIHZRgGZZVlpoxtdbJisVhq1TYxMZHdu3ezdetW/Pz8mDt3LocOHaJDhw62NlOmTCE3N5f169cTGBjI5s2biYuLIycnh9atW5OdnU2vXr0YM2YMK1aswMnJifT0dKqqqi447q5du3j99dfJzs5m06ZNv/eUReQqdM2EkZKSEhwdHcnKysLR0dFun6enZ432L730Ev369aNJkyaXq0T5gyqrLKPL37uYMnbmsEzcnd1/tV1JSQmrVq1i7dq19OrVC4C0tDSaNWtma/PT7GNBQQGBgYHAjw+Fv/vuu6SmprJw4UKSkpK48cYbSUlJsfVr167dBcf95ptvSEhIYO3atTRo0OC3nqaIXOWumTDSsWNHqqqqKCoq+tX7zvn5+aSnp/OPf/zjMlUncmU7duwY5eXldOnyv9DUqFEjwsPDbeu1mX3Mzs6u07fTxo8fz7Bhw+jZs+fvPAMRuZpdVWGkpKSEzz77zLaen59PdnY2jRo1IiwsjOHDhxMfH8+SJUvo2LEjp06dYufOnURFRdG3b19bv9WrVxMQEMCf//xnM05D/mCsTlYyh2WaNvalUpvZR6u1buPt2rWLf/zjHzz77LPAj7e0qqurcXJy4q9//Stjxoy5NMWLyBXtqgojH3zwAbfccottfcaMGQCMGjWKl19+mdTUVJ588klmzpzJV199RePGjenatSv9+vWz9amurubll18mISGhxh+oIvXBYrHU6laJmVq2bImzszOZmZk0b94cgOLiYj755BOio6OB2s0+RkVFsXPnTh577LFajXvgwAG750m2bt3K4sWL2b9/P02bNv2dZyUiV4urKozExMRgGMYF9zs7O/PYY49d9A9CBwcHvvzyy/ooT+Sq5enpydixY0lMTMTX1xc/Pz/mzZuHg8P/vnBXm9nHOXPmEBkZyeTJk5k0aRIuLi6kp6czePBgGjduXGPcNm3a2K1/8MEHODg4cP3119f7OYvIleOa+WqviPw+zzzzDDfffDP9+/end+/e/OlPf6JTp052bVJTU4mPj2fmzJmEh4dz11138f7779tmU8LCwti2bRsfffQRnTt3plu3bmzduhUnp6vq3z0icplZjItNNYhInZ09e5b8/HxCQ0Nxc3Mzuxy5xujzJdeiq+KfK9XV1Zw4cQIvL69a/2aCiFnKy8uprq6mqqrqor+vIfJbVFVVUV1dTUlJCeXl5WaXI3JRhmFw+vRpAgMD7W77/tJVEUZOnDhBUFCQ2WWI1EpwcDAvvvgiZWXm/NCZXPv++9//0rdvX7744guzSxGplS+//NLud4t+6aoII15eXsCPJ6MfRpIrXXl5OV9//TUhISGaRpdL7uzZsxw/fpwPPvgAFxcXs8sRuagffviBoKAg29/jF3JVhJGfbs00aNBAYUSueGfPnuXUqVM4Ojrq6+NyyTk6OuLg4ICnp6fCrlw1fu0RC32bRkREREylMCIiIiKmUhgRERERUymMiIiIiKkURkRERMRUCiMickExMTFMnz7d7DLsZGRkYLFY+O6778wuRUQuEYUREbkifPbZZ3h5eeHt7W12KSJymSmMiIjpKioqGDp0KDfffLPZpYiICRRGRASA0tJS4uPj8fT0JCAggCVLltRoc+7cOWbNmkXTpk3x8PCgS5cuZGRk2LXZt28fMTExuLu74+PjQ2xsLMXFxRcd++GHHyYiIoJ77rnnN9X+xhtv0K5dO1xdXQkJCalRe0pKCq1bt8bNzY0mTZowaNAg276NGzcSGRmJ1WrF19eX3r17U1pa+pvqEJHf5qr4BVaRq5lhGBgmvafGYrXW+uWSiYmJ7N69m61bt+Ln58fcuXM5dOgQHTp0sLWZMmUKubm5rF+/nsDAQDZv3kxcXBw5OTm0bt2a7OxsevXqxZgxY1ixYgVOTk6kp6df9IWBu3bt4vXXXyc7O5tNmzbV+RyzsrK45557WLBgAffeey/79+9n8uTJ+Pr6kpCQwAcffMDUqVNZs2YN3bt359tvv2XPnj0AFBYWMnToUJKSkhgwYACnT59mz5496GXmIpeXwohIPTPKysi7oZMpY4cfysLi7v6r7UpKSli1ahVr166lV69eAKSlpdm92KqgoIDU1FQKCgoIDAyE/4+98w6Pqsr//+ve6S29dwIkQEgA6SBNqgUr2BcR1EWsaxcUwbYryi5+9efuuq5t1dUVsDeQXkOTmkAgEEJCQkL69HZ/f0wyZKhBEpLAfT3PPGHuvXPOuZeTOe982gGeeOIJfv75Zz744ANeffVV5s6dS58+fXjnnXf8n8vIyDhtvxUVFUyePJlPPvnkd2/18Ne//pWRI0fy/PPPA5CWlkZOTg6vv/46kydPprCwEIPBwDXXXIPJZCI5OZlevXoBPjHidru58cYbSU5OBiAzM/N3jUNGRub3I7tpZGRkyM/Px+l00r9/f/+xsLAw0tPT/e937tyJx+MhLS0No9Hof61cuZL8/HwAv2Wkqdx7773cfvvtDB069HePPTc3l8GDBwccGzx4MPv27cPj8TB69GiSk5NJTU3lD3/4A59++ilWqxWAHj16MHLkSDIzM5k4cSL/+te/zupSkpGRaX4uacvI//b+j4M1B7m9y+0kBiW29nBkLlIEnY70rVtare/mwmw2o1Ao2LJly0kbABqNRgB059jfsmXL+Pbbb3njjTcAn0vL6/WiVCp59913mTJlynmP22QysXXrVlasWMHixYuZNWsWs2fPZtOmTYSEhLBkyRLWrVvH4sWLeeutt5g5cybZ2dl06NDhvPuWkZFpGpesGPF4Pby/632KzcV8mvspwxKGcXvX2xkQO6DJPnYZmaYgCEKTXCWtSceOHVGpVGRnZ5OUlARAVVUVeXl5DBs2DIBevXrh8XgoKys7bdZLVlYWS5cuZc6cOU3qd/369QHxJN988w2vvfYa69atIz4+vkltdO3albVr1wYcW7t2LWlpaX7RpFQqGTVqFKNGjeKFF14gJCSEZcuWceONNyIIAoMHD2bw4MHMmjWL5ORkvvrqKx577LEm9S8jI3P+XLJiRBAEnhvwHJ/mfsqa4jWsKFrBiqIVdAzuyO1db+ea1GvQq9r2AiIj01wYjUamTp3Kk08+SXh4OFFRUcycORNRPO7JTUtL44477mDSpEnMmzePXr16UV5eztKlS8nKyuLqq6/m2WefJTMzk+nTpzNt2jTUajXLly9n4sSJREREnNRv165dA95v3rwZURTp3r17k8f++OOP07dvX1566SVuueUW1q9fz9tvv+2PW/n+++85cOAAQ4cOJTQ0lB9//BGv10t6ejrZ2dksXbqUMWPGEBUVRXZ2NuXl5SeNS0ZGpoWR2gE1NTUSINXU1LRI+weqD0ivbHhF6vdJP6n7h92l7h92lwZ+NlB6Y9MbUlFdUYv0KXPxYrPZpJycHMlms7X2UM6Juro66c4775T0er0UHR0tzZ07Vxo2bJj0yCOP+K9xOp3SrFmzpJSUFEmlUkmxsbHSDTfcIO3YscN/zYoVK6RBgwZJGo1GCgkJkcaOHStVVVU1aQwffPCBFBwcfMZrli9fLgEBbS5YsEDq1q2bpFKppKSkJOn111/3n1u9erU0bNgwKTQ0VNLpdFJWVpb0xRdfSJIkSTk5OdLYsWOlyMhISaPRSGlpadJbb73VpLG2Fu11fslcmjR1/RYkqe3nsNXW1hIcHExNTc3vjrhvCnXOOr7Z/w2f7fmMw3WHARAFkeEJw7mj6x30jekru3BkzordbufgwYN06NABrVbb2sORuciQ55dMe6Kp67ecTdMIk9rEnd3u5PsbvuftK95mYOxAvJKXZYeXMXXxVG767iYW5i3E5m6dmhEyMjIyMjIXI7IYOQWiIDIscRjvjnmXr6/7mlvSb0Gn1LGvah+z189m9ILR/G3L3ygxl7T2UGVkZGRkZNo9spumidQ4avh6/9f8d89/KTYXA6AQFFyRdAV3dL2Dy6Iuk104MoBsRpdpWeT5JdOekN00zUywJpi7Mu7ihxt+4M0Rb9I/pj8eycOSQ0uY/PNkbv7+Zr7a9xUOj6O1hyojIyMjI9OuuKTFiNNmPec9KBSizxry3tj3WHTtIm7qfBNahZY9lXuYtW4Wo78czf9t/T9KLaUtNGoZGRkZGZmLi0vaTfPz3+dTuGs7aQMup8vAIUR37Py7XC3V9moW7V/E53s+p8TiiyNRCApGJ4/mjq530COyh+zCuYSQzegyLYk8v2TaE01dvy9ZMSJ5vbx7/92Yqyv8x4Iio0kfeDnpA4cQ1aHjOQsIt9fNisMr+DT3UzYf3ew/3i28G3d0vYNxKeNQK9TNMn6Ztou8WMi0JPL8kmlPyGKkCZT8cyuHdm2lyLOf4po83G6n/1xITCzpA4eQNuByIpM7nLMw2VO5h89yP+OHAz/g9PraDdOGcXP6zdycdjOR+shmuw+ZtoW8WMi0JPL8kmlPyGLkLEheiapF+7BtL0dyeXF7XZQ4DnBEcYCisj24XceFSWhcgs9iMuByIpJSzqmfKnsVC/ct5L97/kuZtQwApaBkTMoY7uh6B1mRWc1yPzJtB3mxkGlJ5Pkl056QxUgT8drcWLeVYckuxVVqAcDldXJUdZhi734OF+7G43b5rw9PSCJtgM+VE57Q9J1+XV4XSwuX8lnuZ/xW9pv/eFZEFrd3vZ0xyWNQKVTNd2MyrcbFtFgMHz6cnj17Mn/+/NYeip8VK1YwYsQIqqqqCAkJae3hXHAupvklc/HT1PX7kt0orwFRp8Q4MA7DgFich+uwbCzFtr2cBFdHEujIZUkjOBZ2lMOWPRTu20FFUSHrF3zG+gWfEZGUQvqAy0kbOISwuDPvMKoSVYxLGce4lHHsrtjNZ7mf8dPBn9hxbAc7Vu/gjc1vcHP6zUxMm0iE7uQNxWRkLnb2799Pr169UCgUVFdXt/Zwmp2UlBQeffRRHn300dYeioxMm+OSFyMNCIKAJikITVIQ3mtS/dYSSiC2IpFYEumTNYbysFIOle3k0O7tHCss4FhhAWv/9wmRKamk11tMQmJiz9hXRngGr1z+Co/1fowv877kf3v/R7mtnHe2vcO/dvyLKztcye1dbycjPOMC3b2MTOvicrm47bbbGDJkCOvWrWvt4TQZSZLweDwolfJXqYzM+XBJ1xk5HaJWiXFAHFEP9yLqgZ4Y+sYgqEXEKono/Gj6WUdzy7hZXHHTvaT0uAxRoaC84ABrPv+Yfz9yL588+ygbv1lATdmZa42E68KZ1mMav9z0C68NeY2syCxcXhff5n/Lrd/fyh9+/AM/H/wZl9d1xnZkZJoDi8XCpEmTMBqNxMbGMm/evJOucTgcPPHEE8THx2MwGOjfvz8rVqwIuGbt2rUMHz4cvV5PaGgoY8eOpaqq6ox9P/fcc3Tp0oWbb775d4194cKFZGRkoNFoSElJOWns77zzDp07d0ar1RIdHc2ECRP85xYsWEBmZiY6nY7w8HBGjRqFxWI5ZT8rVqxAEAR++uknevfujUajYc2aNeTn53PdddcRHR2N0Wikb9++/Prrr/7PDR8+nEOHDvGnP/0JQRACAuLXrFnDkCFD0Ol0JCYm8vDDD5+2fxmZixVZzp8BQRBQJ5pQJ5oIvroD1u3lWDaW4io2482xEEkYsRHXMnTy7RzxHGDf1vUU7trO0QP7OXpgP6s/+5CYTmn1rpzLCYqIOmU/KoWKq1Kv4qrUq9hZvpPP9nzGzwU/s618G9vKtxGlj+LW9Fu5Ke0mwrRhF/gpyJwvkiThdnpbpW+lWmxyJtiTTz7JypUr+eabb4iKimLGjBls3bqVnj17+q958MEHycnJ4fPPPycuLo6vvvqKcePGsXPnTjp37sy2bdsYOXIkU6ZM4c0330SpVLJ8+XI8Hs9p+122bBlffvkl27ZtY9GiRed8j1u2bOHmm29m9uzZ3HLLLaxbt47p06cTHh7O5MmT2bx5Mw8//DD/+c9/GDRoEJWVlaxevRqAkpISbrvtNubOncsNN9xAXV0dq1evPmsxxGeeeYY33niD1NRUQkNDOXz4MFdddRWvvPIKGo2Gjz/+mPHjx7N3716SkpJYtGgRPXr04L777uPee+/1t5Ofn8+4ceN4+eWXef/99ykvL+fBBx/kwQcf5IMPPjjnZyEj01655ANYfw/OIl9siXVbOZKz/ktWIaDrHoHYTU9h2S7yNqzh8O5dSNLxRSg2rQvpA4aQNnAwprAzx4WUW8v5Mu9Lvtj7BZX2SgDUopqrUq/ijq530CWsS4vdn8z5cWKAocvh4d1HVrbKWO57cxgqjeKs15nNZsLDw/nkk0+YOHEiAJWVlSQkJHDfffcxf/58CgsLSU1NpbCwkLi4OP9nR40aRb9+/Xj11Ve5/fbbKSwsZM2aNU0aX0VFBb169eKTTz5h6NChfPjhhzz66KNnjBk5MYD1jjvuoLy8nMWLF/uveeqpp/jhhx/YvXs3ixYt4u6776aoqAiTyRTQ1tatW+nduzcFBQUkJyefdbwNfX/99ddcd911Z7y2e/fuTJs2jQcffBA4dczIPffcg0Kh4J///Kf/2Jo1axg2bBgWi+WUAapyAKtMe0IOYG0CrqNlmJcvI/TWW8/pc+oEE+qEE6wlRWZs28thO0RHRJE6dDrSFBUHdm1m74bVFOXupiRvDyV5e1jx8b+I79KNtAFDSBswGGPoydaOSH0k03tO557Me/il4Bc+yf2EnIocvt7/NV/v/5qsiCxuSruJcSnj0Kv0zfVIZC5R8vPzcTqd9O/f338sLCyM9PR0//udO3fi8XhIS0sL+KzD4SA8PByAbdu2+cVMU7j33nu5/fbbGTp06O8ee25u7knCYPDgwcyfPx+Px8Po0aNJTk4mNTWVcePGMW7cOG644Qb0ej09evRg5MiRZGZmMnbsWMaMGcOECRMIDQ09Y599+vQJeG82m5k9ezY//PADJSUluN1ubDYbhYWFZ2xn+/bt7Nixg08//dR/TJIkvF4vBw8epGvXruf4NGRk2ieXrBjxWiwU3nUXzoIC3JWVRE6ffs5tiBolxn6xGPvF4iw2Y9lYgnVbOe5jNmp+OggKgcSMVLrcMQhXiId9m9aTt2E1xXty/K/lH71LQtcM0gcMoXP/QRhCAr8E1Qo14zuO55rUa9hevp1Pcz/l10O/+rJwju1g7qa5XNXhKiakTaBbeLfmejwyzYhSLXLfm8Nare/mwmw2o1Ao2LJlCwpFoLXFaDQCoNPpzqnNZcuW8e233/LGG28AxxdipVLJu+++y5QpU8573CaTia1bt7JixQoWL17MrFmzmD17Nps2bSIkJIQlS5awbt06Fi9ezFtvvcXMmTPJzs6mQ4cOp23TYDAEvH/iiSdYsmQJb7zxBp06dUKn0zFhwgScTudpWvBhNpv54x//yMMPP3zSuaSkpN93wzIy7ZBLVoyIBgPB119P+fz5HPu/t8DtIeKhB3/3HjLqeCPqGzoTfFUqth3lmDeW4jpch23HMWw7jqEI19Kpb096PDEWq7OWvA1r2bthNSV5eyjK2UVRzi6WffBPEjO6k1YvTPRBwf72BUGgZ1RPekb15JjtGN/mf8vCvIUU1hXyZd6XfJn3Jd3Cu3FT55u4qsNVGNXG5npUMueJIAhNcpW0Jh07dkSlUpGdne1fBKuqqsjLy2PYMJ+Q6tWrFx6Ph7KyMoYMGXLKdrKysli6dClz5sxpUr/r168PiCf55ptveO2111i3bh3x8WdOl2+ga9eurF27NuDY2rVrSUtL84smpVLJqFGjGDVqFC+88AIhISEsW7aMG2+8EUEQGDx4MIMHD2bWrFkkJyfz1Vdf8dhjjzWp/4b+Jk+ezA033AD4REZBQUHANWq1+qTYmcsuu4ycnBw6derU5L5kZC5GzkmM/PnPf2bRokXs2bMHnU7HoEGDeO211wJMuafiyy+/5Pnnn6egoIDOnTvz2muvcdVVV53XwJuDiGl/RFAqKHtjHsfeeQfJ6yHykUfOa1M7UaPA0DcGQ98YnEfMvtiS38rwVNip/bmA2sWH0GWEk9FvKJddeS11FeXkbVjD3g1rKN2fR+GuHRTu2sHS9/9OUvcepA8cQqe+A9CZjvvaInQRTOk+hckZk9lcupkFeQv4tfBXcipyyKnI4Y3Nb3BlhyuZ0HkC3SO6y5v0yZwVo9HI1KlTefLJJwkPDycqKoqZM2ciisctK2lpadxxxx1MmjSJefPm0atXL8rLy1m6dClZWVlcffXVPPvss2RmZjJ9+nSmTZuGWq1m+fLlTJw4kYiIk+OkTnRDbN68GVEU6d69e5PH/vjjj9O3b19eeuklbrnlFtavX8/bb7/NO++8A8D333/PgQMHGDp0KKGhofz44494vV7S09PJzs5m6dKljBkzhqioKLKzsykvLz9n90jnzp1ZtGgR48ePRxAEnn/+ebzewKDllJQUVq1axa233opGoyEiIoKnn36aAQMG8OCDD3LPPfdgMBjIyclhyZIlvP322+c0BhmZdo10DowdO1b64IMPpF27dknbtm2TrrrqKikpKUkym82n/czatWslhUIhzZ07V8rJyZGee+45SaVSSTt37mxyvzU1NRIg1dTUnMtwm8yx9z+QctK7SDnpXaSjb7wheb3eZm3f43BL5k0l0tH/95t0+OlV/teR1zZKNcsKJXetQ5IkSao+WiJlf/2l9J9nHpHeuPlq/+uvt10rLXh1lrRz+RLJVld3yj4qbZXSh7s+lK5ZdI3U/cPu/teN39wofZb7mVTjaJlnJ3MyNptNysnJkWw2W2sP5Zyoq6uT7rzzTkmv10vR0dHS3LlzpWHDhkmPPPKI/xqn0ynNmjVLSklJkVQqlRQbGyvdcMMN0o4dO/zXrFixQho0aJCk0WikkJAQaezYsVJVVVWTxvDBBx9IwcHBZ7xm+fLlEhDQ5oIFC6Ru3bpJKpVKSkpKkl5//XX/udWrV0vDhg2TQkNDJZ1OJ2VlZUlffPGFJEmSlJOTI40dO1aKjIyUNBqNlJaWJr311lvn1LckSdLBgwelESNGSDqdTkpMTJTefvvtk57d+vXrpaysLEmj0UiNv3o3btwojR49WjIajZLBYJCysrKkV1555bRjaK/zS+bSpKnr93ll05SXlxMVFcXKlStPG4B2yy23YLFY+P777/3HBgwYQM+ePfnHP/7RpH4uRDZN5cf/4eirrwIQNnkyUU8/1SIWBWeJxRdb8lsZkr3eZCsK6LqGYegfi6ZTCIIoUFV6hLz1PotJecEB/+dFhZKUHr1IG3A5HXv3R2sMdMdIksTWsq0syFvA4oLF/k36tAotY1LGMCFtAj0je8rWkhZEznaQaUnk+SXTnrgge9Ps37+fzp07s3PnztOaVZOSknjssccC0tleeOEFvv76a7Zv337KzzgcDhwOh/99bW0tiYmJLZ7aW/nppxx96WUAQv/wB6JnPNtii7bX6cG28xiWjaU4D9X6jytCNT43T59oFEEa37iOFPmFybHCAv+1okJBUmZP0gYMplOfQFcOQI2jhu8PfM+CvAXsr97vP94xuCMT0iYwvuN4gjXByDQv8mIh05LI80umPdHiYsTr9XLttddSXV19xpoCarWajz76iNtuu81/7J133mHOnDkcPXr0lJ+ZPXv2KQPgLkSdkaov/kfpCy8AEHr7bUQ/9xyC2LKFal2lFiwbS7FsLUOyu30HRdB2CcfQPwZt51AE0SeKKooK2bt+Dfuy13Ls8CF/G4IoktS9B2n9B9Op7wD0wSH+c5Iksb18Owv3LeTngz9j99gBX92S0SmjuanzTfSJ7iNbS5oJebGQaUnk+SXTnmhxMXL//ffz008/sWbNGhISEk573e8RI61lGWmgeuFCSp57HiSJkFtuIeaFWS0uSAAklwdrg7WkoJG1JKSRtSRY4z9eUXyYfdnryMteG+DKEQSRhG7dSRtwOZ37DQxIF65z1vHDgR9YkLeAvVV7/cdTglK4qfNNXNvpWrnK63kiLxYyLYk8v2TaEy0qRh588EG++eYbVq1adcZcfPh9bpoTaY0KrNVffU3JjBkgSQRPuInYF1+8IIKkAdfRRtYSW721RABtF19siTbtuLUEoKr0iE+YbFjL0QP7jjckCCR0yaBz/8F07j/QX/lVkiR2V+xmQd4Cfjz4Iza3DQClqGRk0kgmpE2gX0w/REHevuhckRcLmZZEnl8y7YkWESOSJPHQQw/x1VdfsWLFCjp37nzWz9xyyy1YrVa+++47/7FBgwaRlZXVpgJYT0XNt99y5Jlnwesl+PrriX3lZQTFha0XIbm82HYdw7yxBOfBRtaSMC3GgXEY+kQj6gIztGvKSsnLXse+DWsp2b834FxcejfS+g+mc/9BBEVEAmBxWfjp4E8syFvA7ord/msTTYnc2PlGru90PRG6M5evlzmOvFjItCTy/JJpT7SIGJk+fTqfffYZ33zzTUBtkeDgYH/lxUmTJhEfH8+f//xnANatW8ewYcP4y1/+wtVXX83nn3/Oq6++ytatW5tcS6A196ap+eEHjjz1NHg8BI0fT9yfX0Vope3CXWVWn7Vky1G/tURQi+gvi8Y4KA5V1Mll4WuPlbEvez152Ws5sjcn4Fxsp3Q6DxhMWv9BBEfFAJBbkcvCfQv5/sD3WFy+nUOVgpLhicOZkDaBgXEDZWvJWZAXC5mWRJ5fMu2JFhEjpwtw/OCDD5g8eTLg2yo7JSWFDz/80H/+yy+/5LnnnvMXPZs7d+45FT1r7Y3yan/+heInngC3m6CrriJu7mutJkjAl4lj3VaGee0R3Eet/uOaziEYB8ah7RIW4MJpoK7yGPuy17Mvey1Fe3ZDo//66NTOpA3wWUxCY+Kwuqz8UvALC/YtYEf5Dv91cYY4v7Uk2hDdsjfaTpEXC5mWRJ5fMu2JC5Lae6FoKTGSZ7FjUorEatRnH8OSJRT/6TFwuzGNG0f863MRVKpmG8vvQZIkHAdqMK87gj2nAur/J8/kwmnAUl3Fvo3ryduwhqKcwN2FI1NSSes/mLQBlxMWF09eVR4L8xby3YHvqHPWASAKIkMThjKh8wQuj78chdi2y51fSOTFQqYlkeeXTHtCFiNN4A87DrCkopauBi1XhAdxRZiJfsFGVKewKgDULVtG0SOPgsuFafQo4ufNQ1CfXchcCNyVdswbSrBsKm2yC6cBa001+zdtIC97LYW7tiM1KmMdkZRSL0wGY4iJYsmhJSzIW8DWsq3+a6L10dzY+UZu6HQDscbYlrvJdoK8WMi0JPL8kmlPyGLkLEiSxM3b81lTZabxAzAqRIaGmvziJE4bKDbqVqyg+KGHkVwujCNGEP/mfMQ2Ikjg97twGrDV1bJ/8wbyNqylcOc2vI029gqLTyRtgM9iUmvysHD/Qr7L/45qRzUAAgKXx1/OTWk3MTRhKCqxdS1HrcXFtFgMHz6cnj17Mn/+/NYeikw9F9P8krn4kcVIE6lwullZVceyilqWV9ZR4XIHnO9i0HJFWBBXhJvoF2xALYqYV6+m6IEHkZxODMOGkvB//4eo0Zymh9bhfFw4DdjNZvK3ZJO3YQ2HdvyGx3382YTGxpM2YDApffuynQMs2r+IjaUb/ecjdZFc3+l6bux8Iwmm09ehuRi5mBaLlhYjBQUFpywPsH79egYMGNAifbZ3Lqb5JXPxI4uR34FXktheZ6sXJrVsrbXSeN9Ng0JkSKiRK8KCGFiwD8/0+5EcDgxDhpDw1v8httEvhvNx4TTgsFo4sGUjezespWD7Fjwul/9ccHQMaf0HY8rsyDLnJr7N/5ZKe6X//MDYgUxIm8DwxOGoFW3HitRSXEyLxYUSI7/++isZGRn+4+Hh4ahaOSarrXIxzS+Zix9ZjDQDlS43qyrrWFpZy/KKOo6dYDXpLHjptWwx/bZvZkBkKKlv/R9ifYpzW+SMLpxBcWjTz+zCacBps3Jg6ybystdy8LctuJ3Hq+UGRUbRsd9AapLV/GRfw/rSDf5zwZpgxqWM49qO15IZkXnRlp9vr4uFxWLh/vvvZ9GiRZhMJp544gm+++67ADHicDiYOXMm//3vf6murqZ79+689tprDB8+3N/O2rVrmTlzJhs3bkSj0dCvXz8+//xzQkNDT+qzQYz89ttv9OzZ88LcaDunvc4vmUsTWYw0M15JYqfZZzVZVlHHllpLgNVEa7fTt6yYq4cOZGRsBInatmsB8Ltw1h7Bnvv7XDgNuOx2Dm7bTN6GtRzYugmXw+4/ZwyPILZXJgeizXxnW0WZvcx/LiUohfEdx3NN6jXEGeOa9f5amxMXC0mScDfa3uBCotRomiz6pk+fzg8//MD7779PVFQUM2bMYOXKlUyZMsUvRu69915ycnL4y1/+QlxcHF999RXPPfccO3fupHPnzmzbto0BAwYwZcoU/vjHP6JUKlm+fDm33norEREnF85rECOJiYnY7XbS0tJ46qmnuPbaa5vzMVxUyGJEpj0hi5EWpsrlZmVlHcsqa1l2tJJjUuAXfme9pj7WJIgBIQY0F7CU/Lngd+FsLPVv0neuLpwGXA47Bdu31guTjThtNv85Q0goxowO7I2o5Bd3NjbpuGjpG9OX8anjGZ08GqPa2Hw310qcuFi47Hb+764JrTKWhz9agKoJC5bZbCY8PJxPPvmEiRMnAlBZWUlCQgL33Xcf8+fPp7CwkNTUVAoLC4mLOy4gR40aRb9+/Xj11Ve5/fbbKSwsPOPmmY05duwYH3/8MYMHD0YURRYuXMjcuXP5+uuvZUFyGmQxItOeaOr63XqVu9o5oSol10eHcn10KN4uSWzZvI1vvvya7M5dyUlNY5/VwT5rOf8sKkcnilweavRn6CTr2k6wqzJMS8hVHQgalYT1tzLM63wuHMuGEiwbSs7JhaPSaOncbxCd+w3C7XRyaOdv5K1fQ/6WjViqq7CsrSIEmGRIRZ0Wx+6wMlYqd7KpdBObSjfxavarXJF0Bdd2vJYBsQPk2iUXkPz8fJxOJ/379/cfCwsLC6i0vHPnTjweD2lpaQGfdTgchIeHA7Bt2za/mGkKERERPPbYY/73ffv25ciRI7z++uuyGJGRuYSQxUgzIAoCffv2ortGQeHUe6jxeNk57hp23PoHVtTZOOp0s6SiliUVvr1lOvmtJiYGBBvRKlrfaiKqFRj7x2LoFxPgwnHsq8axrxpFuBbjgKa7cJRqNR1796dj7/64XS4Kd21j/8b17N+cja22Bsdv+0gCJqs7IaSGsyOkhN9Mhfx48Ed+PPgjkbpIrk69mms7Xkvn0LPvgdSWUWo0PPzRglbru7kwm80oFAq2bNmC4oQ9moxGn0VL1wwxU/3792fJkiXn3Y6MjEz7QXbTNDO2XbspnDoVb00N2qwsEv/1LntEFcsqfenDm2oteBo9cZ0oMjjUyBVhvtomKW3IatKcLpwGvF4PR/bksm/TevZtXEfdsXL/OUGhwJ1oYkfIEfaGV2DX+KJyuoZ1ZXzH8VzZ4cp2sWFfezSjm81mwsLC+PTTT/2WjaqqKhISErj33nuZP38+eXl5pKens2rVKoYMGXLKdu6++2727dvXZDfNqbj33nvZsmULW7duPfvFlyDtcX7JXLrIMSOtiD0nh8K7p+CpqUGbkUHSv99DERICQK3bw6qGWJOKOkqdroDPpuo0XBFu8qUPhxjRtQGridfpCXDhNHCuWTgnIkkSZQfz2bfRJ0wqiw8fPymAI1rLzrBSCqLMmPUeFIKCwfGDGd9xPCMSR6BRtB3h1pj2uljcf//9/PTTT/4A1pkzZ7Js2TKmTp3qD2C98847Wbt2LfPmzaNXr16Ul5ezdOlSsrKyuPrqq8nLyyMzM5OpU6cybdo01Go1y5cvZ+LEiacMYP3oo49Qq9X06tULgEWLFvH888/z3nvvcffdd1/I2283tNf5JXNpIouRVsa+Z49PkFRVoenalaT3/43yhNRGSZLItdhZWlHLsspaNtVYcAdYTQQGhvhiTUaGBdFB37qL72mzcM7RhXM6KooP+1w5m9ZTmr8v4Jw1TGRPRCWF0VaqjS5MahNjUsZwbcdr6RXVq02lCbfXxcJsNgek9j7++OP88MMPAam9LpeLl19+mY8//pji4mIiIiIYMGAAc+bMITMzE4CVK1cyY8YMtmzZgk6no3///nz++eeE1Avyxnz00Ue89tprHDp0CKVSSZcuXXjyySeZMKF1An7bA+11fslcmshipA1gz8vzCZKKCjTp6SR98D7KsLDTXl/r9rC6vhrssso6ShyBVpMOOrU/Q2dgiBF9K1pNfC6cI1g2Hm02F05jao+Vs3/TBvZvXEdR7u6AjfwsRi8Houo4FGPlWLCTBFMC4zuOZ3zqeBKDEs+r3+ZAXixkWhJ5fsm0J2Qx0kZw5OdzaPJkPOXH0HTuRNIHH6A8hbn6RCRJYk+91WR5ZR3ZNeYAq4m2wWoSFsSIcBMddU2vJ9GctJQLpzHW2hryt2Szf+P6k8rSW7UeDkVbOBRt42iYnZ4xvRjfcTxjU8YSpG6duSIvFjItiTy/ZNoTshhpQzgOHKTwrrtwl5ej7tiRpA/eRxUVdU5tmBusJvWBsMUnWE2StGpGhJkYGR7E4BAjBuWFTYuVJAlHfv1eOC3gwmnAYbVycNtm9m9cz4HfNuOyH69lYld5OBxl81lMojwM6zCCaztey8C4gRd00z55sZBpSeT5JdOekMVIG8NZUMChuybjPnoUdUoKSR99iCo6+ne1JUkSeVZHvTunluxqC85G/41qQaB/iMFvNUnXay+o1eS0Lpze0ZgGx6OMaJ6S+W6nk8Jd29m3cR35m7Ox1dX6z7kUXooibRTGWLEkahmTdhXXdryWLmFdWvxZyIuFTEsizy+Z9oQsRtogzsJCDk2ejPtICarkJJI/+ghVTMx5t2txe1hbbfZbTQrtzoDz8RoVI+rrmgwJNWG6QFaTU7pwBNB2Dcd0eRzqDsHNJgy8Hg/Fe3b7Uoaz12OuPOY/5xEljoTbKIyxoewczZUZ13F16tVE6c/NOtVU5MVCpiWR55dMe0IWI20UZ1ExhXfdhau4GFViIskffYgqrvn2ZpEkiXybg+UVvvThddVmHN7j/8VKAfoGG/yBsN0MLW81kSQJx/5qzGuKse+t8h9XxRkwDklAnxmBoGy+YFxJkjiav89fy6TqSLH/nBeJsjAHhTE2IrK6cGWPG7gi8Qr0qvMLuG2MvFjItCTy/JJpT8hipA3jKi7m0OS7cR0+jCo+nqSPPkKdEN8ifVk9XtZXm1lWHwh7wBa4YVuMWsWIcBMjwoIYFmokWNWyRXldZVbMa4uxbi1DcvkyZESTGuOgWAz9YlEYmj+2o6LoMPs2rmNv9hqOFRwMOHcsyEFJnJvkPn24pu/N9I7ujSicnzCSFwuZlkSeXzLtCVmMtHFcJSUcmjwZ16FClHGxJH/4IeqkpBbvt8Dm8KcOr62qw9bIaqIQoHeQwV8NtrtRh9hCVhOPxYVlYwnmdSV463xuJUElor8sCuPl8agim89S0Zja8jL2b1rPzvXLOZa3P+BctcFFZaJI536DuHbwHaSGpP6uPuTFQqYlkeeXTHtCFiPtANfRoxTeNRlnQQHKmBiSP/wAdUrKBevf7vGSXWPxB8LuswZaTSLVSoaH+arBDgszEdYCVhPJ7cW6oxzzmmJcRyz+49r0UIyXx6PpFNJibiRrTTX7N29gy5pfqNizH6GRMDNr3VhT9KT3G8zVQ24nOii2ye3Ki4VMSyLPL5n2hCxG2gmusjIK756CMz8fZVQUSR9+iCa1Q6uMpdDmYEV9qfrVVWYsnuOFxgSgV5Dev8FfD5MeRTOKBEmScB6soW51MfY9lf7UYFWMHuPl8eh7RCGoWq7Im8NqYe/m9WSv+p7q3HzERkVdHEovtmQ9HXv348or7iQ69MwxPvJiIdOSyPNLpj0hi5F2hPvYMQrvvhvHvv0oIiNI/vBDNB07tuqYnF4vG2ssLKuoY3llLbkWe8D5MJWC4WFBjAgzMTzMRKS6+WI9XMdsvriSLUeRnPVxJUYVxgGxGAbEojCqm62vU/bvdLBr8yrWrfyWutwCVI7jvyIeQcIepyX5st6MHnUbcTEnC8eLabEYPnx4QDn4tsCKFSsYMWIEVVVVpywxf7FzMc0vmYsfWYy0M9yVlRROvhtHXh6K8HCSP/wATefOrT0sP0fsTpbXW01WVdZR18hqAtDDpPNn6PQy6VGeZ9VVAK/VhWVTKeZ1R/DU1KcrKwX0PaMwXR6PKsZw3n2cdQxeDzu2r2HNyq+p3rUfXV3gr4sjQk18zx6MGDGRxI5dEQTholosWlqMFBQU0KHDyYJu/fr1DBgw4JSfkcXIxTO/ZC5+ZDHSDnFXVVE4ZSqO3FwUoaEkffgB2vT01h7WSbi8EltqLf4MnZ1mW8D5EKWCoWEmrgjzZelEa87PaiJ5vNh2HaNudTGuIrP/uKZzCKbL49GkhV6wom4792azfPmXHNu5h6BjEgLH+3UblURnZTBg6HV4NUZSU1Pb/WJxocTIr7/+SkZGhv94eHg4KtWp540sRmQxItN+aOr63fr708v4UYaGkvzB+2i7dcNTVUXhpLuw5+S09rBOQiUKDAgxMqNjHEv6prN9UAbzuyRyXVQIIUoF1W4P35ZV8+iew/RYt5tRm/bySv4R1lebcXnPXfsKChF9jyiiHuhJ5LQsdN3DQQDHvmqOfbCbo3/bgjm7BMnlaYG7DSQzvT8PT3uDOW9/x9i5L6K4MoPyeAm36EVpdlOxbjvL332H2opyqspKsNXV4vW0/LiaA4vFwqRJkzAajcTGxjJv3ryTrnE4HDzxxBPEx8djMBjo378/K1asCLhm7dq1DB8+HL1eT2hoKGPHjqWqquqkthoTHh5OTEyM/3U6IXI6Fi5cSEZGBhqNhpSUlJPG/s4779C5c2e0Wi3R0dEBuwIvWLCAzMxMdDod4eHhjBo1CovFcmIXMjIyLUjLFpWQOWcUISEkffA+hffci33nTg7dPYWkf/8bXfeMs3+4lYjWqLg1NpxbY8NxeyW21Vn9G/xtr7Oyy2xjl9nGW4VlmBQiQ8NMjKwvVR+raXr8hyAIaFKC0aQE+0rOry3Gsvko7jIb1V/tp3ZxAYb+sRgHxqEwtWxciSAIZCb3JnNybyRJYmfpNpas/B+Ht20j2epBkMBtd1BTdhQJCYVCjd4QhEavR3GOC+15jVMlNtlq9OSTT7Jy5Uq++eYboqKimDFjBlu3bqVnz57+ax588EFycnL4/PPPiYuL46uvvmLcuHHs3LmTzp07s23bNkaOHMmUKVN48803USqVLF++HM9ZBNm1116L3W4nLS2Np556imuvvbbJ97hlyxZuvvlmZs+ezS233MK6deuYPn064eHhTJ48mc2bN/Pwww/zn//8h0GDBlFZWcnq1asBKCkp4bbbbmPu3LnccMMN1NXVsXr1atqBwVhG5qJCdtO0UTx1dRy+515s27cjmkwk/fs9dFlZrT2sc6bc6WJlpW+DvxWVtVSeYL3oatByRXgQV4SZ6BdsRHWOsSZeuxvLpqOY1xbjqa5PTVYI6HtEYrw8HnWcsblupWnjkbz8VvQbrjIHkRGhaCUFol3C82HZBR1HA3EvDkJUn738v9lsJjw8nE8++YSJEycCUFlZSUJCAvfddx/z58+nsLCQ1NRUCgsLiWtUNXjUqFH069ePV199ldtvv53CwkLWrFnTpPEdO3aMjz/+mMGDByOKIgsXLmTu3Ll8/fXXpxUkJ7pp7rjjDsrLy1m8eLH/mqeeeooffviB3bt3s2jRIu6++26KioowmUwBbW3dupXevXtTUFBAcnJyk8bc2shuGpn2RFPXb9ky0kZRmEwk/vs9Dt/3R2xbt1I4ZSqJ/3oXfa9erT20cyJSrWJCTBgTYsLwSBLb66wsqy9V/1utlVyLnVyLnf9XWIZRITI01MSIcF9tk3jt2a0bolaJaUg8xkFx2HKOYV5zBOehWqxby7BuLUOTGozx8ni0XcIQmiGo9qzjEUQyIjM4aD5IXFQKHoWHmprKFu/3fMnPz8fpdNK/f3//sbCwMNIbxSzt3LkTj8dDWlpawGcdDgfh4eEAbNu2zS9mmkJERASPPfaY/33fvn05cuQIr7/+epOtI7m5uVx33XUBxwYPHsz8+fPxeDyMHj2a5ORkUlNTGTduHOPGjeOGG25Ar9fTo0cPRo4cSWZmJmPHjmXMmDFMmDCB0NDQJt+DjIzM+SOLkTaMwmgk6V/vcviP07Bu3szhqff4BEnv3q09tN+FQhC4LMjAZUEGnugQQ4XTzcqqOn8gbIXLzY/HavjxWA0A6QYtV4SZGBkeRL9gA2rx9CFOgkJAnxmJPjMSR2Et5jXF2HYdw3GgBseBGpQROoyD49D3jm6SpaA5EAQBo9qIIcKAZ04sVpeFWnstDqsVlQuUbgGhkV1SEAU0egManQG1Xo+oOP9xNmdtFrPZjEKhYMuWLShOGJvR6LNA6XTnvyNz//79WbJkyXm304DJZGLr1q2sWLGCxYsXM2vWLGbPns2mTZsICQlhyZIlrFu3jsWLF/PWW28xc+ZMsrOzT5nlIyMj0zLIAaxtHNFgIPHdf6Lv3x+v1Urhvfdh3bSptYfVLISrldwYHcrb3ZLZOTiDn3un8VSHGPoE6RGBvRY7fz9czoRt+XRds4vJOw/wUfExDp+wK/GJaJKCCL+9KzFP9cU4NAFBq8B9zEb1N/mU/HkjNT8dxF3jOGMbzYkgCCg1KoKMISREJNEhMY2QhDg8sXosIRIOg4SkEUAh4HBYqa0u51jJIaqPlWCz1eEVvIhqxe96NTVepGPHjqhUKrKzs/3HqqqqyMvL87/v1asXHo+HsrIyOnXqFPCKqd99Oisri6VLl57X89q2bRuxsU2veNu1a1fWrl0bcGzt2rWkpaX5RZNSqWTUqFHMnTuXHTt2UFBQwLJlywDf/8/gwYOZM2cOv/32G2q1mq+++uq87kFGRubckC0j7QBRryfxH3+n6IEHsKxbT+F9fyRh/t8wDhvW2kNrNkRBoGeQnp5Beh5LiaHK5WZlZR1LK2tZXlHHMZebn4/V8vOxWgA66zVcER7EyLAg+ocY0JzCaqIM0RJyVQeCRiZh3VxK3bojeCrs1K0som51MbqsCEyXx6NOMJ302Za9V5EgTRBBmiA8Rg9ml5kaRw12mwWVS0DtFlF4BJw2G06bjTrKUao1aA0GNHoDSo2m2VOZjUYjU6dO5cknnyQ8PJyoqChmzpyJ2Oi5pqWlcccddzBp0iTmzZtHr169KC8vZ+nSpWRlZXH11Vfz7LPPkpmZyfTp05k2bRpqtZrly5czceJEIiIiTur3o48+Qq1W06ve/bho0SLef/993nvvvSaP/fHHH6dv37689NJL3HLLLaxfv563336bd955B4Dvv/+eAwcOMHToUEJDQ/nxxx/xer2kp6eTnZ3N0qVLGTNmDFFRUWRnZ1NeXk7Xrl3P84nKyMicC7IYaSeIOh0J77xD0UMPY1m9msP3Tyf6mWcI/cOdF6zGxoUkVKXk+uhQro8OxStJ7DLb/Bv8ba6xsM/qYJ+1nH8eLkevELk8xMiI+kDYZJ0moC1Ro8A4OB7DwDjsuZXUrSnCebAW27ZybNvKUacEYbo8Hm238AsSV9IYhaggWBNMsCYYj9FDnbOOGmcNdXYLKreA2iWicou4nQ7MTgfmqkoUSqXPnWMwoNbqEM7gvjoXXn/9dcxmM+PHj8dkMvH4449TU1MTcM0HH3zAyy+/zOOPP05xcTEREREMGDCAa665BvAJlsWLFzNjxgz69euHTqejf//+3Hbbbaft96WXXuLQoUMolUq6dOnCF198EZB6ezYuu+wy/ve//zFr1ixeeuklYmNjefHFF5k8eTIAISEhLFq0iNmzZ2O32+ncuTP//e9/ycjIIDc3l1WrVjF//nxqa2tJTk5m3rx5XHnllef+AGVkZH43cjZNO0NyOimZM4eahYsACL39NqJnzEBQXjq6strVEGviK1Vf5nQHnO+k1/j30BkQbESrOHmxdhabMa8pxrq9HOprnyjCtBgHxWHoG42o+f3PszmyHdxeN7XOWmodtdic1gBhEhhnIqLR6dHUW02aI85Epm0jZ9PItCfkCqwXMZIkUfn++5S9MQ8kCcPgwcT/7a8oLsFnI0kSu802llX6AmE31VrwNJrROlFgUIiJK8J9gbApJ1hNPDUOzOtLsGwswWv1iRpBo8DQLwbjoDiUoef+Zd/ci4XL66LWUUutsxar67gwUbtFRG8jS44Aaq3OZzXRG1CoVBel1exSRxYjMu0JWYxcAtT9+ivFTz6FZLOh7tiRxH/8HXViYmsPq1WpcblZVWVmWX2sSanTFXA+VafhivrU4YEhRnT1VhOv04N1axnmNcW4j9WXtxdB1z0C4+XxaJKaPu9acrFweVzUOGt8MSZuO0qPL8ZE7fLFmTRGoVL5hYlap0UQ5Hj1iwFZjMi0J2Qxcolg272bovun4y4rQxEaSsL/exv9ZZe19rDaBJIkkWuxs7SilmWVtWyqseBuNNu1osDAECMjw4O4IiyIVL0GySthz6vCvKYYx/5q/7XqJBPGIfHoukUgKM5sbbhQi4XD46DWUUuNswaH24HoFVA3uHM8IpzCnaPW631Wk0vIrXexIYsRmfaELEYuIVxHj1J0/3TsOTkIKhWxr7xM8DmU075UqHN7WFVVx/L6omtHHIFWkxSd2r/z8KAQI8oymy+uZFsZDb4fRYjGFwzbNxpRe+oFvTUWC7vbTq2zlhpHDU6PE0ECldvnylG7RYTATZZRabRo9L5YE6W6+bNzZFoOWYzItCdkMXKJ4bVaOfL009Qt+RWA8PunEfnQQ82WaXGxIUkSeyx2f6zJxhoLrka/ChpRYGCwz2oyTKsl6rdjWDeUBsaV9K2PKwkLXBBac7GQJAmHx0Gds45aZy12tx0ApUdA5RbRupWI7sBfeVGpQKOrz87R6RBFOQi2LSOLEZn2hCxGLkEkr5fyv/2Nin/5ajSYrhxH3J//jCh/YZ0Vs9vD6qo6llfWsbSiluITrCbJWjVXhBoZXOklY8MxVGX1cSVCo7iSZN/cbEuLhdPj9GXlOGuxuXxjFiVQuUS0HiVKlwCNvgIEQUClawiC1aNUteyGgzLnTluaXzIyZ0MWI5cw1QsXUvLCbHC70WZlkfj/3kYZGdnaw2o3SJJEntVRX9eklg3VJ1hNBIH+ag0Dix30z60jyeo7p04yYbw8HqGjkYLCgja3WLg8Lr/FxOKy+I+r3AI6jwqVWwR3oD9HqVb7hYlKq5PdOW0AWYzItCdkMXKJY8neSPHDD+OpqUEZG0viP/6OttGmZzJNx+z2sKY+Q+dUVpNEj8DAIw4GlbnpU+lBHaOhboiO1PRO6PTnv1dLS+D2uqlz1lHnrMPsMtPwNaDwCmg9SrRuJbg8AUGwoij6A2DVej0KhRwE2xrIYkSmPSGLERmcBQUcnnY/zoICRL2euL/OwzR8eGsPq10jSRJ7rXbfzsMVtWSfGGvikRhT5+GeeCWdYhIJDjKgMKoRlG03dsfj9ZWkr3XWYnaa8Uo+64gggcajRO9VIzq9SJ5Aq4lKq/WnDivVatlqcoGQxYhMe0IWIzIAeKqrKXrkUazZ2SCKRD/zNKF/+IO8cDQTDbEmDYGwxQ4XCaLEq0EiUYlJqJVqjG4wiSImgwrleVR2vRB4JS9mp9lvNfnDtX+gS/cuPPPKM6i9CgxeDUoXeE+oettQol6tbwiCbTnxtWLFCkaMGEFVVRUhISEt1k9bRRYjMu2Jpq7fbffPNZlmQRESQtK/3iV4wk3g9XL01T9TOmcOkst19g/LnBWjUsGVkSG8np7I5oHdWNEvnfsTo9CKAgLgEgWq1AKFSokch5P8aitlZgeOE6wMbYWGTfziTfGkhaWhVWrRKDUoRSVO0UOV0kq5zkp1kBuPSYVC50sL9rjdWGtrqC49QnnBAapKjmCtqcZzlnlWUFCAIAgnvTZs2HCB7vjCkZKSwvz581t7GDIybZK2/WeaTLMgqNXEvvQSmtSOlL3+OtWff4Gr8DDx8/92SZaQbykEQaCLQUdKXDgHD9aSZNDiVqqodXmodXtwA2YRzF4PJRYPaiBIpcSkUmBUiIhtzFolCiIKQYFRZSQtNA2r2+oLgHXU4vK6qBYsoAZBLWBC54szcbjxuN04rBYcVgtQ3igI1oBKqz2lVe7XX38lIyPD/z48PPwC3unvR5IkPB4PSrmInIzMeSFbRi4RBEEgfMrdJLz9FoJOh2XdOgpuvQ1nYWFrD+2iRSEIBKuUJOo1dDPpSNNpiEZEX19AzQkcc7k5aHWwy2zjgNVBudOFw9s6VhOLxcKkSZMwGo3ExsYyb948/zlBEDCoDIQqQ/nnK/9kdI/R9E3uy+1jbyd7bTa1WClT1lJmsLI2bxs3TZpEavcsulzWhwm330nxoQIqjxRRfuggNUdLsZnr8Ho8/vbDw8OJiYnxv1Qq1TmNfeHChWRkZKDRaEhJSQkYO8A777xD586d0Wq1REdHB+wKvGDBAjIzM9HpdISHhzNq1CgsFsuJXQA+F5EgCPz000/07t0bjUbDmjVryM/P57rrriM6Ohqj0Ujfvn359ddf/Z8bPnw4hw4d4k9/+pPf+tPAmjVrGDJkCDqdjsTERB5++OHT9i8jc7Eii5FLDNPIkaR8+gnK6GicBw5QcPMtWLdsae1hXdRIkoTL5UIheQjTiiTplHRye4k2OzBYHOB04HI6qbLZKKyzsKuqll2VNRTUmqmw2rA7HDidzt/1OpeQsCeffJKVK1fyzTffsHjxYlasWMHWrVsDrnnwwQfZsGEDX3z+BTt37OQPt/2B+2+5H/MRM1qllj0793D7DXeSmJ7Mf376hC9++oKx14xDodEiKkS8Hg82cx01R0spO3SA6tISAK4dP56oqCguv/xyvv3223N6vlu2bOHmm2/m1ltvZefOncyePZvnn3+eDz/8EIDNmzfz8MMP8+KLL7J3715+/vlnhg4dCkBJSQm33XYbU6ZMITc3lxUrVnDjjTee9bk988wz/OUvfyE3N5esrCzMZjNXXXUVS5cu5bfffmPcuHGMHz+ewnqxv2jRIhISEnjxxRcpKSmhpMR33/n5+YwbN46bbrqJHTt28MUXX7BmzRoefPDBc3oGMjLtHTmA9RLFdbSMounTse/ejaBSEfPSi4Rcf31rD+ui4MQAQ6fTyauvvtoqY5kxYwZq9dkLl5nNZsLDw/nkk0+YOHEiAJWVlSQkJHDfffcxf/58CgsLSU1NpbCwkLi4OP9nR40aRb9+/Xj11Ve59bZbOXjoIJ//9DlWlzWgD41CQ5BgQO0WcNscuJ1OKior+fKrr+nXuzdKlZKffl3Km2//PxYtWsT1p5mPJwaw3nHHHZSXl7N48WL/NU899RQ//PADu3fvZtGiRdx9990UFRVhMpkC2tq6dSu9e/emoKCA5OTksz6nhr6//vprrrvuujNe2717d6ZNm+YXFikpKTz66KM8+uij/mvuueceFAoF//znP/3H1qxZw7Bhw7BYLKcMUJUDWGXaE01dv2VH5yWKKjqK5E/+w5GnnqZuyRJKnnkWZ0EBkQ8/LJeQvwTJz8/H6XTSv39//7GwsDDSG9Wm2blzJx6Ph7S0tIDPOhwOf4zHju07mDhxIh2CO5xUZM3hcVCOAwC1UY1JYSQhLIRHHnoQp82GJElkZWRQdPgwf37lZYb27VNf10R/xv1zcnNzTxIGgwcPZv78+Xg8HkaPHk1ycjKpqamMGzeOcePGccMNN6DX6+nRowcjR44kMzOTsWPHMmbMGCZMmEBoaOgZn1efPn0C3pvNZmbPns0PP/xASUkJbrcbm83mt4ycju3bt7Njxw4+/fRT/zFJkvB6vRw8eJCuXbue8fMyMhcLshi5hBF1OuLfnE/53+ZT8a9/UfGPf+IsOETcn19F1LXNYl3tEZVKxYwZM5p0reTx4rW68JhdUB864lSARa/AohCwSN7A3XgFMIgKgpQiRqUCzQlC8lxjL86E2WxGoVCwZcsWFIrA/WuMRiMAukbzRqVQEaYLI0wXdlKRNafHSYWn0nedRoXJaEQvaRCcXvr07s2qtetw2m047TbMlRWICoW/2FrjWJOmYDKZ2Lp1KytWrGDx4sXMmjWL2bNns2nTJkJCQliyZAnr1q1j8eLFvPXWW8ycOZPs7Gw6dOhw2jYNBkPA+yeeeIIlS5bwxhtv0KlTJ3Q6HRMmTMDpdJ71mf7xj3/k4YcfPulcUlLSOd2njEx7RhYjlziCKBL1+GOoO3Sg5IUXqPv5Zw4VF5Pw/95GFRXV2sO7KBAEoUmuEj86LVKohNfmxmt2onZ5Mfr2u0PSabDqFZiRqPV4cXsl7IDdC2VOLxpRwqRUEKRUYFCITa4n07FjR1QqFdnZ2f5FsKqqiry8PIYNGwZAr1698Hg8lJWVMWTIkFO2k5WVxdKlS5kzZ07AcaWoJFQbSqg29KQiay6vi0pHFZX4Mni27c8hJi4GY0QELpsNp83mizWpq8VWV+uPMzFXVaLXaunatStr164N6G/t2rWkpaX5RZNSqWTUqFGMGjWKF154gZCQEJYtW8aNN96IIAgMHjyYwYMHM2vWLJKTk/nqq6947LHHmvTsGvqbPHkyN9xwg29sZjMFBQUB16jVajwnCKnLLruMnJwcOnXq1OS+ZGQuRmQxIgNAyI03oE5MoOjBh7Dv3EnBLbeS+Pd30Hbp0tpDuyQRRAGFQYWoVyI5PHjMLiS7G8HmxmBzY1QriDOqcGpFaj1e6tweLF4vDq+Ew+nmmNONKIBRocCkFAlSKlCfwf1mNBqZOnUqTz75JOHh4URFRTFz5syA4mVpaWnccccdTJo0iXnz5tGrVy/Ky8tZunQpWVlZXH311Tz77LNkZmYyffp0pk2bhlqtZvny5UycOJGIiAgAFKKCYE0wwZpgPvjwAySFRKdunbC4LPz83c/87z//Y87f5nDIdQS9To8pKBidV4XX4cJhPR6HYqmuotLr4e7bbmHsdTcw67nnuO3229m4aRNvv/0277zzDgDff/89Bw4cYOjQoYSGhvLjjz/i9XpJT08nOzubpUuXMmbMGKKiosjOzqa8vPyc3SOdO3dm0aJFjB8/HkEQeP755/GekBWVkpLCqlWruPXWW9FoNERERPD0008zYMAAHnzwQe655x4MBgM5OTksWbKEt99++5zGICPTrpHaATU1NRIg1dTUtPZQLnocBQXS/nFXSjnpXaTcXpdJtUuXtfaQ2h02m03KycmRbDZbs7brcbolV6VNchTVSo7D9a8jdZK71iF5PV7J7fVKVU6XVGi1S7vqrNK2GkvAK9dslYptDqnW5ZY8Xu9J7dfV1Ul33nmnpNfrpejoaGnu3LnSsGHDpEceecR/jdPplGbNmiWlpKRIKpVKio2NlW644QZpx44d/mtWrFghDRo0SNJoNFJISIg0duxYqaqq6pT39OGHH0pdu3aV9Hq9FBQUJPXp20f61yf/kvZV7ZN2le8KeOVV5kkl5hLpx5+/lwCpYE+uVHpgv1SyP0/619tvSWmdOkkqlUpKiI+XXp4zW3JYrZLX65VWr14tDRs2TAoNDZV0Op2UlZUlffHFF5IkSVJOTo40duxYKTIyUtJoNFJaWpr01ltvnfb/YPny5RJw0v0cPHhQGjFihKTT6aTExETp7bffPunZrV+/XsrKypI0Go3U+Kt348aN0ujRoyWj0SgZDAYpKytLeuWVV047hpaaXzIyLUFT1285m0bmJDw1Nb4S8hs2gCAQ9fRThN11l1xCvom0dLaD5PHitTTEldT/+goCokHp3wdHkiTsXi+17nqryQkVX0UBTAoFJqXPcnImq0lr4fQ4/TEmFpclIN1WIfqKsZlUJjReJS67DafVisvhCGhDVIiodXrUOt8Gf4qLoDiZnE0j056Q96aROS8kl4vSF1+i+ssvAQi5+WZinn8OoRkDIi9WLtRiIXmPx5VIruNiQ9AqUZhUCGqFX0C6vRJmj68SbF19rEljtAoBk8IXa6Jvg9VgG+JMGsSJx3s89kIQBPRKPSa1CYNCj1TvznHarCcFuyrVGjT1GTq+arBtT4SdDVmMyLQn5NRemfNCUKmIeXEO6tRUyubOpfp//8N5uJCE+fNRBAe39vBkOH1ciWR347a7EVQiolGNqFOiFAVCRCUhKiWSJGFrZDWxerzYPRJ2j5vy+lgTk1JRL05EVG3AatI4zkSSJH9p+jpnHU6PE4vLgsXlq1qqUWowmUyYwmJQegScVisOmxWX3Y7b6cDtdGCprkIQRTQ6HWq9AY1Oj0IW2jIyrYYsRmROiyAIhN89GXVyEsVPPIl1/QYKbrudxH/8HbWcdthmEAQBQatE1Crxujx4zS68VjeSy4unyo6nRkA0qlAYVAj1GTZ6hQK9QkGMRoXbK1Hn8VDn9llOPBLUuDzUuHxWBa1CJEgpYlKcW4ZOS96vQWXAoDIQY4jB4XZQ5/IJE6vLisPtwOF2cIxjKEUlJrUJkzGEYFGLy27HabXgsPqsJnaLBXt96XWlWo1Gp/ftPKzVyvV2ZGQuILKbRqZJ2HNzOXz/dNylpShCQkh46//Q9+3b2sNqk7QFM7qvXokbj9kJnoa4EhB1KkSjClGtOPXnJAmr11svTLzYTog1UQi+nYqD6rN02oLVpDFurxuz00ydqw6z04xXauS+EgRfnInahFFlBLcHh9WKw2rFZbcFtCOIAmqtz52j1utRqs4hNbuFaQvzS0amqcgxIzLNjqusjKLpD2DftQtUKmJffJGQG65v7WG1OdrSYiFJDXElLiRnozgLtcIXV6JVntHS4WpkNamrt5o0RqcQfanDCl+sSWtbTRrjlbxYXcfdOS6vK+C8TqnzWU3UJtSCCqfN6o818bjdAdcqVKr6WBMDKq0uIOX5QtOW5peMzNmQxYhMi+C12TjyzLPU/fILAOH33Ufko4/IJu1GtNXFwuv04DU78VobLbQKEYVRhWhQIYhnFhKSJGH1eKn1eKg7jdXEl53jizdRnaW9C4kkSTg8Dr8wsbkDLSEqUeUXJnqVHo/ThdNmqbea2AMyeQRBQKXT+Vw6Oj1KtfqCirC2Or9kZE6FLEZkWgzJ66X8zf+jon5zL9OYMcS99he5hHw9bX2xkNxePBYXXsvJqcGiQY2oapqwdHm91Ll94sR8GqtJkFLEpFSgF9uW1cTlcfldOWaXOUBsiIKIUe1LGzaqjYgIOG2+1GGH1XKS1URUKvzCRK3Tt3j6cFufXzIyjZGzaWRaDEEUifrTo6g7pFDy/CzqFi/m0JEjJLzz/+QS8u0AQSmiDNYgmdQBqcFeswuv2eVLDTaqEDSKMwoIlSgSphYJw5ehY/F4qfP4Yk3sHp/lxObxctThRiFAUCOribKVrSYqhYowRRhh2jC8kheLy+K3mri9bmodtdQ6agHQq3xpw6bQYEwRkXhcLhxWC06b1Veq3u3BVleHra4OqE8f1ulQ6/Wt7tKRkWkvyGJE5ncTcv31qBPqS8jv2kXBzbf4SsjLO422C5qWGqxC1J3dhSMIAkalAqNSQazGZzWpdXv98SYeCapcHqrqM3T0CrF+Dx0RXStbTURB9LtoJEnC5rb5hImrDofbgdVlxeqycpSjqBVq37UGEyHBISBJOB12nPWxJi6H43j6cE21z6Wj1foCYXVn3n1YRuZSRnbTyJw3zsJCDk+7H+eBAwh6PfFvvI7piitae1itRns2o3tdXrwWJ16LGySJ0ROvIisji7/N+6svNVh57n/lextiTdwe6jwe7Cf4c5SCgKnendMWrCaNaagCW+esw+q2BlaBFRQY1UaMKiNGtRGlqMTjcftdOqcKhBUVinp3ju531zZpz/NL5tKjqeu3bD+UOW/USUmk/Pcz9AMHIFmtFD3wIBXvf0A70LkyJyCqRJQhWlSxBhTBGhAAJLx1TlylFtwVNrxOz9maCWyz3moSp1WTbtDR1aglQasmSKlAFHxWlPnz5tGza1f0Oi3RcXE8O+dFrB5Pq88htUJNuC6clOAU0kPTSTAlEKwJRiEq8Egeahw1FJuL2Vu5l/zqfCoclUgaBUGRUUQkpRCRmExQRCQagwFBFH21Tcx11JaXUV5YwLHDh6g9Vo7dYsHrPbfnKiNzMSG7aWSaBUVwMEnvvkvpy69Q/cUXlM2di/PgQWJmPS+XkG+HCKKAwqRGUCsQtUoEjQLJ4fHFmNjcvuNGFaLuzKnBp0ItioSrRcLVSrySxPSHHubXJYt5+pVXSemaQU1VFTVVleyzOFCKAiaF6I83UbSii+PEKrAN7hyzy4zdbfe/yin3751jVBsxmozog0OQJMlXdM3WuCKsE7fTibXBpaPRoq536ag0sktH5tLhnC0jq1atYvz48cTFxSEIAl9//fUZr1+xYoWvQuQJr9LS0t875majpmYrlVXrqavLwW4/gtttbvW/xNozgkpFzOwXiH72GRAEqr/8ksJ778NTU9PaQ5NpAhaLhUmTJmE0GomNjWXevHmAL+BVFalHGaXHpfDy9MszScnqRFBECP1792Ppj0uQGqX5rl27luHDh6PX6wkNDWXs2LFUVVWdss+9e/bw73/+gx++/Zbpt0xkVPcujB7Yj7FjxiAIvj11qlweDtmc7DLb2G+xc9ThwubxturvqiAI6FV6og3RdAzpSFpYGnHGOII0QYiCiMdbbzWp81lNDlQfoNxWjkcJhtAwwuMTiUpJJSQ6Fn1QMAqVCkmScNptmCsrqCw+TPmhA1SXlmCtrcHtcp19UDIy7ZhztoxYLBZ69OjBlClTuPHGG5v8ub179wb4i6LaQNbFvv2vUVOzOeCYIChRKoNQqYJRKoOP/1QGo1Q1/AxCpQypfx+EShWCUhmMQiH7bwVBIOyuu1AlJVH8+BNYN2yg4JZbSfznP1AnJ7f28FoFSZLwem1nv7AFEEVdk/+6fvLJJ1m5ciXffPMNUVFRzJgxg61bt9KzZ09fW2oFj856gpzdOXz64X+IDorkmx+/4+obx7NlyQbSu3dhx/7djBw5kilTpvDmm2+iVCpZvnw5Hs+pXRDfffcdqampfP/994wbNw5Jkhg1ahRz584lOTQUS0OsiduDw+vL2LF4vJQ6XKgaWU2MrWw1UYkqQrWhhGpD/XvnNKQN2912bG4bNrctwGpiUpsw6A1ojUYA3C6XL0PHasVpt+L1eLFbzNgtZqC+8JpOj6RQIHm9ZxqOjEy747wCWAVB4KuvvuL6668/7TUrVqxgxIgRVFVVERIS8rv6aakA1t27H6e2bhdudw0uVw2S5Dyv9kRRjVIZUi9gGkRKUL2ACUGlDPILmhPFjihefK4M+549vhLyJSUogoOJe+MNjEMub+1htTgnBhh6PFZWrMxslbEMH7YThUJ/1uvMZjPh4eF88sknTJw4EYDKykoSEhK47777mD9/PoWFhaSmplJYWEhcXJxPZFndjLlyDH2yevPSMy8w6cEpHC4pZvXKVWdNDQaYNm0aH374IT179uT111/H4/Hwpz/9idDQUJYtWxZwraNRmXqzx0PAN5cABoVYX6ZegVYU2oyLw+VxYXaZ/eKkcYl6AJ1K569polVoEQTB59JxOHDaLDitNlyO44XXXB4PR0qPcnjdCmJTO5Gc1ZPYTuktXt9ERub30ObqjPTs2ROHw0H37t2ZPXs2gwcPPu21DocDh8Phf19bW9siY8rImOf/t++vVzsuVzVudy0uVw1udzUuV229WKnG5T7+7+PX+IQMePF6nTidZTidZec8FoXCcGqLTIM15oRjanUEanU4oqhpxifSvGi7dCHli88peuBB7Dt3cvjeewmbMoWoRx9BULedvT5kID8/H6fTSf/+/f3HwsLCSE9P97/fuXMnHo+HtLS0gM86HA7CoyMRdEq25+zkpquvx33MhqCsTw3Wnz412Ov14nA4+Pjjj/3t/vvf/6Z3797s3bs3oH+NKKJRi0SofRk6Zo/Xv7mf0ythcXuxuL2U1FtNgpQKTAqx9a0mChWhCp/VxCt5A2JNHG4HNpcNm8tGmbUMpag8HmuiNmLUhkMoeL0eX5aOzYalzvd9WH7oIId+28SGhf9FrdORmJFFcmZPkrMuIzQ2rs2IMRmZptDiYiQ2NpZ//OMf9OnTB4fDwXvvvcfw4cPJzs7msssuO+Vn/vznPzNnzpyWHloAgiCgUOhQKHRA7Dl9VpIkPB5zgDhxuWtwn+K9y338mNtdg9vtK5Tk8VjweCw4HCXn1LdSafIJE1VEvUDxiZTAn75XU/5Cbm5UUVEk/+djyubOpeqz/1L5/vtYN24kft4bl4zbRhR1DB+2s9X6bi7MZjMKhYItW7agUARutGc0GlGF69AbDQhqBQiCr9JrtQNPrRPRoDplanBsbCxKpTJA4HStr1NTWFgYIEYC7kvwiY0gpYJ4wOEvU+/B7PHi8kpUON1UAEK91cSk8F2vaUWriSiI/h2HwZc63GA1sbgsuL1uqh3VVDuqAV/BtQaXjkZvQGswojaaqLTYGHzrnRT+toVDu7Zjr6slf3M2+ZuzATBFRJKc2YuUHr1I6t4DnUkuiSDTtmlxN82pGDZsGElJSfznP/855flTWUYSExMvyjojkuRpZGWprbfA1OB21eJyV9cLmFrcjS0zziqcrkok6dyC2hQKfb1oCRQpqkbvNX7hYmz2L+y6X3/lyMzn8NbUIOr1xMx+geBrr23WPtoC7bEOhNlsJiwsjE8//dTvpqmqqiIhIYF7772X+fPnk5eXR3p6OqtWrWLIkCGnbOfuu+9m3759rF61Gq/VV9FVch93S4g6JaJRhaD2uXAWL17M2LFj2b9/Px07dgRg+/bt9OzZk717955khWkKnvpqsA2xJk5v4FdcW7KaNKZhY78GceLwOALOK0UlRrURjVfD0aKjdEztiFarRfJ6KSs4QMGO3yjc+RvFe3IC65sIAtEdOpKc1YvkzJ7EpXVFKVsmZS4QF2Rvmt8rRp588knWrFnD+vXrm3S9XPTsZCRJwu2uwek81uhVcfzfroqAc16v4+yNNkIU1SdYWxpES6CQ0agjUCqDEYQm7mdSUsKRJ5/CutkXOBx83bVEPz8LhdFwzs+grdIexQjA/fffz08//cT7779PVFQUM2fOZNmyZUydOpX58+cDcOedd7J27VrmzZtHr169KC8vZ+nSpWRlZXH11VeTl5dHZmYmU6dOZdq0aahUKpYtXsqNY68l3Bjq76shNRiNSL9+/TAajcyfPx+v18sDDzxAUFAQixcvPu97kiQJR/3Ow7VuDxaPNyDWpMFqElRfcK01rSYn4vQ4/XEmFpfFH2vidXkpLyrnu+rvyIzNZEj8EDqFdPKP2+WwU5S7m0M7fuPQzm0cKywIaFehUhGf3pXEjB4kde9BTMfOiCdYumRkmos2LUZGjx6NyWRi0aJFTbpeFiPnR4Mb6bhgaSxajp0kaDweyzm1LwhK1KrwesESFiBWjouWSDSaKJTKEPB6OfbPf3Ls7f8HXi+qpCTi581Dl9m9ZR7ABaa9ihGz2cz999/PokWLMJlMPP744/zwww/07NnTL0ZcLhcvv/wyH3/8McXFxURERDBgwADmzJlDZqYvSHflypXMmDGDLVu2oNPp6N+/P59//jlBBpNv/xurCxq+dRQCR2vLefTZx1m8ZAkGg4Err7ySefPmERYW1uz36JEkzG4PdfWWE9cJVhO1KNSXqVdgVIiIbUSYNFhN6lx11JhrKC4s5rX9r1Hi9Ll1o/XRDEkYwuXxlzMgdoDfDQRgrqqkcOc2Cnb8xuFd2zFXVQa0rdbpSOjanaTuPUjMyCIyKUXehVum2WgxMWI2m9m/fz8AvXr14q9//SsjRowgLCyMpKQknn32WYqLi/n4448BmD9/Ph06dCAjIwO73c57773HW2+9xeLFixk5cmSz3oxM8+Dx2E62tPiFS+Axt/vcgotFUYNGE41GE4vSosKxcgdCkQVFnYKIK28n8sYpaLTRiGL7zQxor2LkQiF5vHgtLjwWF/6tfgUQdSpfwKv6wvyV3mA1aShTfyqridG/h44CTRtZoO12O/vy97GXvSwtWcqm0k0BLh2lqKR3VG+/OEkNTvVbTSRJoqqkmMKd2yncvZ3Du3diN9cFtK8zBZGYkUVS9ywSM3rIwbAy50WLiZGGVN0Tueuuu/jwww+ZPHkyBQUFrFixAoC5c+fy7rvvUlxcjF6vJysri1mzZp2yjfO9GZkLjy+DqOJkV9FJFpdjuFynLnx1MqLPkqKNqRcuMfWvaLSa48d8wcZtD1mMNA1Jkup3DXYhNSoxL6gViIb66q4XcJ+as1lNNI2sJoZWtJqcOL/sbjubSjexpngNq4pWUWQuCrg+zhDH5fGXMyRhCP1i+qFXHQ9kl7xeyg4d5PCu7RTu2k5R7m5cDnvA543hESRlZJHU3efWMYVHXJD7lLk4uCBumguFLEYuDjweB07nUeyOozjsJTicR3HYS7E7SrEe2Y3dXIQnSIIm/mGsVAYHiJMGweITMTFoNTH18SwXdtGQxci543V6fC4cWyMXjiicNgunpZEkCbtX8qUO11tNOMlq4tt12HSBrSZnml+SJHGo9hBritewung1m0s34/Qer5+kFJVcFnUZA+MGMihuEF3CuiA2ivfyuN2U5u+jcNc2Du/awZG83JM2+wuNjau3nPQkMSMTfVBwy96wTLtGFiMy7Q7H/v0UPf4YtpI8PCES+puuQDu2Hw7PMRyOUhz2UhzOo9jtpU2uaOpzCx0XJz7h4nMTNQgXtSqiWd1Cshj5/fhcOO56F84JWTgGVZMKqbUEDVaT2nrLSWtaTc5lflldVjaVbmJ18WrWFK+h2FwccD5UE8qAuAEMihvEwNiBRBuiA867nA6O7Mn1uXR27aA0fx/SCUXbIpNSSMrsQWJGDxK6dkejv/AlBGTaLrIYkWmXeO12yua+TtVnnwGgzcjw1SRJSfFf48skqvMJFEcpDsdR7P5/+947HEdxuSpP08uJiGg0UY0sLNHHxYs2Dp02Ho0mGkFomslGFiPnjyRJSHY3HrMLydHIhdOEQmoXYmz2E2JNLqTV5PfOL0mSKKwrZN2Rdaw7so6NJRuxuq0B13QK6eS3mvSO7o1OGegKdVgtFOXuonDXDgp3bT8pU0cQRWJSO9eLkyzi0ruiUrfdwowyLY8sRmTaNXVLl1IyYyaemhoEvZ6YWc8Tco5ZW363kL30FMLlKA5HKU5nGZJ09q3bBUGBRhOLVhuPVhuHVhuPThvf6H2cvxquLEaaF6+r3oVjdeOPMBUERIPPWiKqWjct1SP53Dk+l44XdwtbTZprfrm8LnaU72DdkXWsP7KeXcd2ITVSVSpRxWXRlzEobhCD4gaRFpoW4NIBsNZUczhnpz8gtro0sGijQqUiLq0rSRlZJNanEctl6y8tZDEi0+5xlZb6apJs2gRA0PjxxLwwC0X9xmLNgSR5cDor/GKlsVCx20uw24/gcJQgSe6ztqVWR6HVxqNRdwGuISUlGZ3OgCiqEUVVky0rMqdG8kqnLKQmaBQojGoEbeu4cBpzIawmLSV2q+3VbCjdwPoj61l3ZB2llsCd1cO14X6rycC4gUToTg5krT1WRuGuHf6A2BPTiFVaHQldM3wBsZk95TTiSwBZjMhcFEgeDxXvvkv52/8PPB5UiYnEz3sDXVbWhRuD5MHhKMNuL8ZuP1L/0/ey1f/0eo9nIIhiHCHBL5CYGIVafXxxFARFvShRB/wURTWC4BMrrb2YtgckSUJyeHwuHHsjkagQURhViHolgqJtLHAtYTW5EJY3SZI4WHvQL0w2lW7C5g6M00oLTfMLk8uiLkOrPDmYtqqk+Lg4ydmJvS6wFIDWaCIxI5Ok7j1J6p5FaGy8/DtwkSGLEZmLCuvWrRQ/8QTuIyWgVBL16COETZnSJv6qkiQJl6vSL1bM5mOYzR1JTIxCpfYieV1NdAWJCEK9OBFViMJxoeL7qZS/qE9AcnvxWFx4LS7wNnLh1Jedv1A1S5pCc1lNWsMN6PQ42V6+3R9vkluRG+DS0Sg09I7u7RcnnUM6nzRXJa+X8sICChunEdsDBY4xLNzv0knqnkVQRNQFuT+ZlkMWIzIXHZ7aWkpmvUDdzz8DYBg0iLjX/oIyMrKVRxbIqRYLSfLg9brwep1Iku+nV3IheZ14va4muYFA8FlURBWi37qiqncDNYiV1hdnrYHkbahZ4kRyNXLh1JedF3VtT8j9XqtJW4hJqrRXkl2S7RcnZdbAncojdZEMjBvIwLiBDIgdcEqXjsft5uiBffXxJvVpxK7A/bZCYmJJzMgisVsmCd26YwqTa5y0N2QxInNRIkkS1QsWcPSVV5HsdhRhYcT95c8Yhw5t7aH5+T2LhSR560WJT5x4JSdSgHhp2qaIx4VKgwtIc16WleHDhweUg28LFBQU0KFDB3777Td69uwZcE6SJCSnF6/ZidfWSOCJAqKxvmZJG3HhNOZcrCZqt4viQ4faTIC0JEkcqDngFyabSzdj9wQWTusS1sUfb9IrqhcaxckZNi6ngyN7czm825epU5q/D8kbmEYcEhNLQtdMEjMySejanaCItvWHiMzJyGJE5qLGkZ9P8WOP49i7F4Cwu+4i8vHHENvAbqQt8ZerJEl+UdLYutLYysLZfpUF0e/6OW5NafzvkxfpCyFGJEli3rx5vPvuuxw6dIiIiAimT5/OzJkzT3n9mcRIQLunKjvPyTsHt0XOZDWRnA6qig6zSRtMv6hQBgQb0bYhgeXwONhWts2fpZNbmRtwXqvQ0jumN4NiBzE4fnBAufqAdurTiA/n7KIoZydlBw+cVOMkOCqahG6ZJNa/giJlt05bQxYjMhc9XoeDstffoOqTTwDQdutG3Lw30HTo0Krjag0zuk+suBtZV46/GqwtZ0MQlCcJldGjr6Vnz17Mn/9miy3cDz/8MIsXL2bu3LlkZmZSWVlJZWUlo0ePPuX1TRUjDZy27LyqvmaJrvVqljSFE60mZpuNssJCZtR6KfIK6ESRwaFGrggzMTI8iGRd26rrUWGrYEPJBr84KbeVB5yP0kf504cHxA4gVBt6ynYcVgvFe3I4nLOTopydHD2Yf5LlJCgyyufS6dqdxIxMgiKj26zgvFSQxYjMJUPdsuWUzJiBp7raV5Pk+ecJvv66VvsSOlGMSJKE9YQvzQuFXhQRBOEEN9CJQsWJJHmxWKw89tjLfPfdUoxGAw89dBc//7ySzMx0/vLaM4iCGpdLYs6cv/Hll99QXV1LRkY3XnvtL4wYcXzTy7Vr1zJz5kw2btyIRqOhX79+fP7554SGnrzI5ObmkpWVxa5du0hPT2/SPZ1KjKxcuZInn3yS7du3ExYWxl133cXLL7+Msr6mxYIFC5gzZw779+9Hr9PTIyOLhf/+Lwa9gZUb1jDjz7PI2ZODSqUiIyODzz77jOTk5PP/D2gBLDYbe/MP8K2o4+sqG6XOQKHZUafhinATV4QFMTCkbVlNJElif/V+vzDZfHRzwCZ/AgJdw7v6xUnPyJ6oFKpTtuW0WSnem+sXJ6dy65jCI0ns1t1vPQmOjpHFyQWmqeu3XH1Gpt1jumIE2m++9tUk2biRkmefxbJ2LTGzX2jWmiS/F6vXS8dVO1ul7/yhmRgUCgRBRKHQACf/1eyzqnh4+unprFu3jS+//JiIiGBeeOEvbN+eS2ZmOkgSXsnBo4/OZu/eA/z7338mJiaK779fypVXXsX69V+TlpbGzp37GDnyeu6663bmzfsLarWWFStW4/GcOpvou+++IzU1le+//55x48YhSRKjRo1i7ty5hIWFNekei4uLueqqq5g8eTIff/wxe/bs4d5770Wr1TJ79mxKSkq47bbbmDt3LjfccAN1dXWsWrkK0aTG7fEyceptTLntLj5+8z1copctOb+dzyNvcRSCgE4h8kyHOF7QaMi12FlaUcuyylo21VjItznIL3Lwr6Jj6ESBwaGmNmM1EQSBzqGd6Rzambsy7sLhcbDl6BZ/CnFeVR45FTnkVOTw3s730Cl19InuQ//Y/gyIHUDn0M7+wmtqnZ4OPXvToWdvAJx2my/mJGcnRTm7KM3Po66inJzVy8lZvRzwZes0WE0SumbKOxK3IWTLiMxFg+TxUPGvf1H+1tu+miQJCb6aJD16XNBxnGgZsXg8rS5GzobZbCY8PJxPPvmEiRMnAlBZWUlCQgL33nsvf/vbXAoKDpCWlkle3mZiYsPqM4GcjB8/hd69u/PCC48wderTFBWV8ssvHzVqXTheT0VUNwqwVTN9+qN89NFH9OzZk9dffx2Px8Of/vQnQkNDWbZs2SnHeqJlZObMmSxcuJDc3Fz/wvLOO+/w9NNPU1NTw7Zt2+jduzcFBQUnWTsqKiqIiIjg169/YUjvgcdHrBR91V0Nbc+FcyY3YK3bw6rKOpZV1rKsou6UVpMRjawmujZkNQEot5b7XTrrjqyj0h5YNC1UE0q/2H4+cRIzgARTwmnFhMtu50jeHp84yd1Jyb48vJ7ArDVDaJhPnNRn64TFnb49md+HbBmRueQQFAoipk1D378/Rx5/AldREQV33EnkIw8TPnVqq9Uk0Ysi+UMzW63vppCfn4/T6aR///7+Y2FhYaSnpyMIAqKoITf3AB6Ph6ysywM+63A4iIpKQKdLYteufG648SqUSmO9K8gFSH630Ik4HBU4HA7+8Y+XSE9PQRTV/POf8+nffzi5ubvp0qXbWReH3NxcBg4cGHDd4MGDMZvNFBUV0aNHD0aOHElmZiZjx45lzJgxTJgwgdDQUMLDw5k8eTJX33Ito0aO4oohI7hp7HXERkbjqXHgqXUi6utrlrRy2fmmEKRUcE1UCNdEhSBJ0mmtJu8VHUMrCgwMMTIizMQV4UF01GlafSGO1EcyvuN4xnccj1fysq9qHxtKNrChZANbjm6hylHFLwW/8EvBLwDEGmLpH9vf94rpT6T+eHaNSqslOasnyVk9AXA57JTs2+sPiC3ZtwdLVSV7161i77pVAOiDQxoFxHYnLD6x1Z/JpYIsRmQuOvS9etHh668oeeEF6n76mfJ5f8W6fj2xf/kLqqgLH20vCEKTrBNtHbPZjEKhYMuWLShOuB+j0YhKFYxeb0SlDEKv9wURH88COjlOxet1EhMTgVKpJDU1BperGoDkZN+ur3v3riUhQTgeUCtqEAU17vrN3Zpq1FUoFCxZsoR169axePFi3nrrLWbOnEl2djYdOnTggw8+4OGHH+bnn39mwbcLeeGV2fz8zY/0y7gMyeXLyPFaXAgahc9a0gZrlpwKQRDoZtTRzajjoeRoat0e1lTVsbyyjmUVtRQ7XCyv9L2ftf8IiVo1I+rdOYNDjBiVrTtnRUEkPSyd9LB07sq4C5fHxc5jO8kuySa7NJvt5dspsZTw9f6v+Xr/1wB0DO7oFyd9YvoQpD7+l7hKoyWpew+SuvsspS6ng9JG4uTIvj1Ya6rJW7+avPWrAdAFBZPYtTsJ3XzWk/CEpDZRaPFiRHbTyFy0SJJEzcKFlL7yKpLNhiI01FeTZNiwFu23LRSlOlfMZjNhYWF8+umnfjdNVVWV300zf/588vLySE9PZ9WqVQwZMuSU7dx9993s27ePNWvWNKnfX375iXHjriI39zc6dIjH63Wwfft2Bg68hi1bvqVTp5STPnPoUDFZWVeyZs0CevbMYs6cN/nmm5/ZsSMbhUKLKKr5+9/f5dlnn6W6uhrxhMXD4/GQnJzMY489xmOPPXZS+wMHDqRv3768+eabSM76Tfoa1yxRCCgaXDit4OZojvklSRJ5VgfL660mG6otOBstBSpBoF+wgSvCg7gizEQXg7bNCTCry8pvZb+RXZLNhpIN7KncE1AVVhREMsIz/OKkZ2TPk0rWN8btdFK6P4/Dub6A2CN5e3E7HQHXaE1BAeIkIjFZFidnQc6mkZGpx3HggK8myZ49AITdNYnIxx9vsZok7VGMANx///389NNPvP/++0RFRTFz5kyWLVvG1KlT/XVG7rzzTtauXcu8efPo1asX5eXlLF26lKysLK6++mry8vLIzMxk6tSpTJs2DbVazfLly5k4cSIRESdXz/R6vfTt2xej0cj8+fPxer088MADBAUF8csvP9dbUBzHLSuSg4KDB+nefRSrV/+PrKwuHDlylN69x3PHHddz3323sW9fAQ89NJv77ruD5557gs2bd7Ny5TpGjx5DTEwcGzdu5Q9/+ANff/01Xbp04d133+Xaa68lLi6OvXv3cvvtt/PSSy9x//33+8d5yrLz1NcsMagQNBeuZklLzC+Lx8O6KjPL6q0mh+yBLrUYtcofazI01Eiwqu0Z1avt1Ww6uslnOSnJpqC2IOC8WlTTM6qnX5xkhGegFE9/H26Xi9L8PIpydlGUu4vivTm4HSeIE6OJhK4Z/kJs8sZ/JyOLERmZRngdDsrmzaPq4/8AoOnalfh589CkNn9NkvYqRsxmM/fffz+LFi3CZDLx+OOP88MPPwQUPXO5XLz88st8/PHHFBcXExERwYABA5gzZw6Zmb64mJUrVzJjxgy2bNmCTqejf//+fP7554SEhJyy3yNHjvDQQw+xePFiDAYDV155JfPmzTttNk1DAOvmzRvIyuqK1+tk5aoVzHj2JXbuzCU0NJjbbruW559/EKVSyd69B3j22bls355LXZ2FxMQ4pk37A/ffP5Xy8hoefvhZNm3aSkVFJbGxsdx111288MILJ1lU4Aw1SxoCXi/AJn0XYn4dtDr8QbDrquuwNRJgCgF6Bxn8sSaZRl2TNvi70JRaSv3CJLskmzJbYMl6o8roz9TpH9ufTiGdzigoPW4XRw/s5/DunT5xsicHlyOw0qzGYCC+SwaJXbsT3zWDqJSOKJRtT7hdSGQxIiNzCuqWL6fk2fqaJDodMc89R/CNNzTrX7XtVYxcLDTUVPF6HY3iUxynDaINRGhU+E1zUhG4xvPE6/T44kms7uPVbwUQtS1b4fVCzy+7x0t2jaVenNSyzxpoHQhXKRkRZmJEmIlhYUFEqNve4itJEgW1BX5hsrF0I7XOwB2Ew7Xh9Ivtx4DYAfSP7U+8Mf6MbXrcbsoO5vvrnBTvzcFpC9z4T6nRENc5nfguGcR3ySCucxdUl9h3gixGZGROg+toGUeeegprdjYAQVddRcyc2ShMpmZpXxYjbZeTi785AoJrAzaEOQnBv99PY8EioAa7gNfqviDWktaeX4ftTlZU1rK8oo5VVXWYPY02JgR6mPT+QNheQXoUbdBq4vF62FO1xy9Oth7detJ+OgnGBL/VpF9MP8J14Wds0+vxHBcne3ZzZE8Odos54BpBFInu0NEnTrpmEJ/eDX1QcLPfX1tCFiMyMmdA8nioeO/flP/f//lqksTH+2qSNKG8+Nlo7cVC5vcRmPnTWKQ48ErOs+z9U29REdTgViI4FAgeJYJXhYACUadCNCibxVrSluaX0+tlc42V5ZW+QNjd5sAFPUSpYGi91eSKsCCiNaeuptraOD1Otpdv91tNdpbvxH3CTtqdQzvTP8ZXfK1PTB8MKsMZ25S8XiqKD1O8ZzdFubsp3pNDXUX5SdeFxSX4hUlC14yLroS9LEZkZJqAbds2ih9/AldxMSgURD78MOH33nNeQWhtabGQaR7OKFTOZlGRBASvCtGrQkCNQq1FodUhKjSIZwigPB1teX6VOlw+q0llHSsr66h2B1bezTBqGREWxIgwE32DDajbaLCnxWVhy9EtfsvJ3qq9AecVgoLuEd39lWF7RPZArTh7QHztsTKKc3dTtMcnTiqKCk+6xhgWTnx6N+K7ZpDQJaPdZ+zIYkRGpol46uoofeEFan/8CQD9wAHE/eU1VNG/ryZJW14sZJqf40LF0UioNC1GRRAU9W4fzQlxKppT7qIM7Wd+ub0S2+qsLKt36WyrswZINqNCZEioz2oyIjyIRG3r77h9OirtlWws3egXJ4frDgec1yq09Irq5RcnXcK6oBDPXqfFVldL8d5civfspnjPbo4e2I/3hK0TNHoDceld6+NOuhHTMQ2lqm1amE6FLEZkZM4BSZKoWfQVpS+/7K9JEvvqK5hGjDjnttrLYiHT8vhiVOqtKB4HHpcNr8eBJLiQhFPv19OAUF9CXxQ1iMJxkeJ0eigoONTu5tcxp5tVVb7U4eWVdVS4TnCD6DVcERbEFeFB9A82tKkN/k7kiPmIv77JxtKNHLMdCzhvUpvoHd2bvtF96RvTl7TQtCaJE5fDTun+PL/l5EjeHlz2wKBYhUpFTMc04rt0I6FLBnHpXdHoz+wyak1kMSIj8ztwHDhI8eOP48jNBSBk4gSiHn8cxWnSUk+FLEZkzoQkSUhOLx6LA4/DhiS66l9uJKXb92/p9ELF6ZQoKqpE4jsMhlD0ug7o9Sno9R3QaGJOa1FpS3gliZ1mG8vrhcnmWgueRiuRThQYFGLy1zbpoFO32TgKSZI4UHOADSUbyC7JZnPpZupcdQHX/F5x4vV4KD900BdzstcnUKw11YEXCQKRSSnEd8kgoasva8cY2rRNJi8EshiRkfmdeJ1OyufNo/KjjwFQhIcT/cwzBF1zdZO+EGUxItNUJI8Xr9WN1+JCch/PSkEN6CVQu+uLvR13/TgdHg4fLqO6Zg5e75GA9kRRg16Xgk5fL1AaCRWVKqzNLug1Ljerqswsr483KXEEbvCXpFUzvD4Q9vJQE6ZWLlV/JtxeN3sr97KpdBObjm5iy9EtWFyWgGuC1EE+cRJzXJyITRCRkiRRVXLEJ0xycyjes5vqoyUnXRccHVNvNfEFxYbGxrfa/70sRmRkzhPr5s2UvDAbZ34+AIZBA4l54QXUJ+z8eiKyGJE5V3zWkvq6JTb38XhYQfBt1GdQIaoVSJKEzWbm4MF8DMb9uJx5WG0FWK0HsdkOI0mu0/ahVJrqxUkqen0H9IZUv1hRKHQX5kabgCRJ7LHY/dVgN9ZYcDVappQC9AkyMDzMxPCwILJMbbPoWgMtKU4AzFWVFO/xCZOiPbspP3TwpMwvXVCwP1snvksGUSmpiBdovyxZjMjINAOS00nF++9z7J2/IzmdCGo1EdPvJ3zKFITTlJOXxYjM+XA6a4mg9m3U5xTcFBwqOGl+eb1u7PZirLaDPnFiPYTVehCr7SB2+xHOlPGj1cT5RIqhQyPBkopWG9vqbh+L28PaajMrKutYUVnHAVtg0bUwlYJhoT5hMjzM1GbThxtwe93sqdzjEyelm9hatvWM4qRfTD86h3ZusjhxWC0cydtTHxSbQ8n+vXhcgSJVpdESm9aFhPqg2NjO6ag0LfNdJYsRGZlmxHnoEKVzXsSybh0A6k4diZ0zB33v3iddezGJkeHDhweUg28LNJSD/+233+jZDHVh2iqSJCE56q0l9uPWErvXyeHyYpKiEzAlNC02wONxYLMVYLUWYLUeqH8dxGI9iNtdfdrPiaK2kbunXqTUW1RUqtb5Lj5kc/iFyeoTiq4BdDNoGV6fPtwvxICmjafFNlWc9Inu47ecnIs4cbtcHM3fR/Fen/WkeG8ODktg+6JCQXSHTgybdA/x6V2b7d5AFiMyMs2OJEnUfv8DR//8ZzyVlcCpA1xlMXJuSJLEvHnzePfddzl06BARERFMnz6dmTNnnvL69ipGzudZNlhLPBYXdrudQ0cKMS23oA8zYegfgz4zAkH1+8zuTmelX5z4XgewWA9isx06o9tHpQrHcJLLJxWdLhFRvDDWCZdXYkuthRWVdSyvrGVHnS3A/qMTRQaFGBkR7os3SdVp2mzcTANur5vcilw2Ha0XJ0e3YnVbA645H3Eieb0cKypsVO9kN+bKCgAmzX2LyOTm3a+rqet329tEQEamjSIIAsHjr8E45HLK5v2V6i+/pPrLBdQtXUb0s88QdM01bf6Lri3yyCOPsHjxYt544w0yMzOprKyksl7stQdcLheqFq77IChEFCY1olGFu1ZCKFeACM5DtTgP1VL93QEMvaMx9ItBFaU/p7bV6jDU6jBCQvoEHPe5fYpOECk+0eJ0luFyVVBdU0F1zabAsQpKdLpEnxVFl+J3+egNqahV4c36O6ISBQaEGBkQYuSZ1FiOOd2srvIJkxWVdZQ53SytrGVppW8fmkStmhFhJobXB8IGtcFAWKWoJDMyk8zITKZ0n3JKcVLrrGXZ4WUsO7wMgGBNsF+c9Inuc0ZxIogikUkpRCal0HPs1b4/ssrLKN6bQ0TimePhWhLZMiIj8zuxbtlCyQsv4NwfGODqjY4OsIxIkoTNdeaaEi2FTtX08uMWiyVg194nnniC7777LuCveYfDwcyZM/nvf/9LdXU13bt357XXXmP48OH+dtauXcvMmTPZuHEjGo2Gfv368fnnnxMaGnpSn7m5uWRlZbFr1y7S09ObNM5TWUZWrlzJk08+yfbt2wkLC+Ouu+7i5ZdfRlm/Y+qCBQuYM2cO+/fvR6/X06tXL7755hsMBgMrVqzgqaeeYvfu3ahUKjIyMvjss89IPkWgckPfn3/+Oe+88w7Z2dn84x//YPz48Tz44IOsWrWKqqoqOnbsyIwZM7jtttsAmDx5Mh999FFAWwcPHiQlJYVdu3bx5JNPsnr1agwGA2PGjOFvf/sbERERp7z/BstbUmQ8nu3VWDaV4qk+Hkeh7hCMsX8Muu4RCMqWcVG43eaTRIrNWoDVdhCPx3raz13IIFpJksi12FleWceKylqyqy04pcDdh08MhG2L++icSIM42Vi6kU1HN/Hb0d9OspycizhpaWQ3jYzMBcAX4PoBx/7+dySHA0GtJvixP1Hdrx8dUlPRarVYnW66zfqlVcaX8+JY9E3cRXX69On88MMPvP/++0RFRTFjxgxWrlzJlClT/GLk3nvvJScnh7/85S/ExcXx1Vdf8dxzz7Fz5046d+7Mtm3bGDBgAFOmTOGPf/wjSqWS5cuXc+utt55ycZ07dy7//ve/ue+++3j77beRJIlRo0Yxd+5cwsJOHQ9xohgpLi4mLS2NyZMn89BDD7Fnzx7uvfdeHnjgAWbPnk1JSQlJSUnMnTuXG264gbq6OlavXs2kSZPQarVERERw7733Mm3aNJxOJxs3bmTEiBEkJSWdtu+UlBTmzZtHr1690Gq1eL1e/vvf/zJq1CiCgoL44Ycf+NOf/sS6devo168fNTU1XHnllXTv3p0XX3wRgMjISOrq6khLS+Oee+5h0qRJ2Gw2nn76adxuN8uWLTvl/Z/oBpS8Eva8KizZJdj3VPpjS0SDEn3vGIz9YlBGXJhsGUmScDhK690+x+NTLNaD2O1FNCmIVt8oPqUZg2gtHg/rqy3+Tf7yTxEIOzTU5BcnMW08ELYBl9fls5zUZ+tsPboVmzuwUFpjcdI3pi+dQjpdMHEiixEZmQtI4wBXb2wsntkv0DEzE0NYWLsQI2azmfDwcD755BMmTpwIQGVlJQkJCdx3333Mnz+fwsJCUlNTKSwsJC4uzv/ZUaNG0a9fP1599VVuv/12CgsLWbNmTZPGN23aND788EN69uzJ66+/jsfj4U9/+hOhoaGnXYxPFCMzZ85k4cKF5Obm+q1A77zzDk8//TQ1NTVs27aN3r17U1BQcJK1o7KykvDwcFasWMGwYcPOOt6GvufPn88jjzxyxmuvueYaunTpwhtvvAGcOmbk5ZdfZvXq1fzyy/H5UVRURGJiInv37iUtLe2kds8Uk+SudmDZVIp1Uyme2uOl6DWdQjD0i0HXLbzFrCVnwxdEe8hvTWkQKVbrAdzumtN+zh9EWy9ODPqOfrGiVP7+yqOFJwTC1p0QCNvVoK2vbRJEvzZeEbYxDeJkY+lGNpduZmvZyeIkRBNCn+g+9Inp0+LiRI4ZkZG5gKiTk0n893vUfv8DR95/H4/bjauoCKfNhjYqipwXx7bKuHRNDGrMz8/H6XTSv39//7GwsLAA18nOnTvxeDwnLZAOh4PwcN/26tu2bfOLmabg9XpxOBx8/PHH/nb//e9/07t3b/bu3dsk101ubi4DBw4McEcNHjwYs9lMUVERPXr0YOTIkWRmZjJ27FjGjBnDhAkTCA0NJSwsjMmTJzN27FhGjx7NqFGjuPnmm4mNjT1jn336BMZXeDweXn31Vf73v/9RXFyM0+nE4XCg1585fmP79u0sX74co9F40rn8/PxTipEzoQzREDw6maArkrDvrfRZS/KqcOyvxrG/GtGoQt8zCkOfaFQxF7aEuEKhwWhMw2g8+Z4Cg2iPZ/rYbIfweu2YzXswm/ec9DmNJqZemHTEUP+zqdaUJJ2GSfEaJsVH4PJKbPUHwtaxvc5KrsVOrsXO3w+XoxMFBoYYGVGfPtxJ33YDYVWiiqzILLIis7gn8x5cXhc5FTlsKt3kFyfVjmp+LfyVXwt/BY6Lk3uz7qVbeLdWGbcsRmRkmomGAFdl/34crC+U5qmqwltbhzo2BkVwcJv9AmsKZrMZhULBli1bUJxQMKlhMdXpzs0dEBsbi1KpDFh0u3b1pRYWFhY2OY7kTCgUCpYsWcK6detYvHgxb731FjNnziQ7O5sOHTrwwQcf8PDDD/Pzzz/zxRdf8Nxzz7FkyRIGDBhw2jYNhsCF/PXXX+fNN99k/vz5ZGZmYjAYePTRR3E6z7xRntlsZvz48bz22msnnTubIDoTgkJA1y0cXbdw3FV2LJtKsWw6irfOiXlNMeY1xagSjBj6xKDvEYmoa92loClBtBZrvk+oWHwxKi5XBQ5HKQ5HKVVV6wM+57Om+Nw9hnqB0hCfciprikoU6B9ipH+IkadTY6nwB8L64k2OOt2+ImyVvjLv8RqVX5gMCTUSrGq7S6lKVNEjsgc9InucVZzck3lPq42z7T5BGZl2iiIoCEVICKroaISKCiSHA1dREZ6qKlRxcYgaTWsP8SQ6duyISqUiOzvbHytRVVVFXl6e333Rq1cvPB4PZWVlDBky5JTtZGVlsXTpUubMmdOkfgcPHozb7SY/P5+OHTsCkJeXB3DKANJT0bVrVxYuXIgkSX6xt3btWkwmEwkJCYBPKA4ePJjBgwcza9YskpOT+eqrr3jsscf899arVy+effZZBg4cyGeffXZGMXIia9eu5brrruPOO+8EfBafvLw8unU7/lemWq3Gc8KOrJdddhkLFy4kJSXFH2zb3ChDtQSPSSFoZDL2vEosm49iz63EVWSmumg/1d8fQNc9HEOfaDSpIQhi2xHMoqisd9GkEEHgppUuV00jd0/9T8uBRtaUXMzm3JPa9FlTAt09BkPHgH19wtVKro8O5froUH9FWH8gbI2FYoeLT0oq+KSkAoUAl5kM/nL1PYL0bToQ9lTiZPex3Ww5uoX0sPMX/78XWYzIyLQQCr0eTUgI7ooK3GVleC0WHPv3o4yMRBkRgdCGijEZjUamTp3Kk08+SXh4OFFRUcycOROx0RjT0tK44447mDRpkj94s7y8nKVLl5KVlcXVV1/Ns88+S2ZmJtOnT2fatGmo1WqWL1/OxIkTTxnAOmrUKC677DJ/kKzX6+WBBx5g9OjRTXZRTJ8+nfnz5/PQQw/x4IMPsnfvXl544QUee+wxRFEkOzubpUuXMmbMGKKiosjOzqa8vJyuXbty8OBB3n33Xa699lri4uLYu3cv+/btY9KkSef0/Dp37syCBQtYt24doaGh/PWvf+Xo0aMBYiQlJYXs7GwKCgowGo2EhYXxwAMP8K9//YvbbruNp556irCwMPbv38/nn3/Oe++9d5IF6nwQFAK6ruHouobjMTux/laOZXMp7qNWbNvKsW0rRxGiQd87GkPvaJRhbbtGjkoVTHBwL4KDewUc91lTDtdbUw5gteT7LSsuV2Uja8q6gM/5rCmp9daU1ABrSlejga5GHdOTorB6vKyvNrOiPn14n9XBploLm2otvF5QSqhSwZAwE8NCTQwNM5GoPXWl5raCSlTRM6onPaN6tuo4ZDEiI9OCCKKIKjISRVAQrpISvGYz7rIyPDU1qOLiUBjaztbfr7/+ut9tYDKZePzxx6mpCQws/OCDD3j55Zd5/PHHKS4uJiIiggEDBnDNNdcAPsGyePFiZsyYQb9+/dDpdPTv39+f4noioijy3Xff8dBDDzF06FAMBgNXXnkl8+bNa/K44+Pj+fHHH3nyySfp0aMHYWFhTJ06leeeew6AoKAgVq1axfz586mtrSU5OZl58+Zx5ZVXcvToUfbs2cNHH31ERUUFsbGxPPDAA/zxj388p2f33HPPceDAAcaOHYter+e+++7j+uuvD3h+TzzxBHfddRfdunXDZrP5U3vXrl3L008/zZgxY3A4HCQnJzNu3LgAIdjcKIxqTEPiMV4eh6vYjGXzUazbyvBUO6hbWkjd0kI0HYMx9IlBmxGOqG579ThOh8+a4nPRRHBFwDmXqzqgXorVkn9CbEoOZnPOSW1qNDHH3T36DvQ0dGRwYiovJF8LMQAAkUFJREFUdkqn2OH2F11bXVVHldvDt2XVfFtWDUBHnYah9bVNBoUY2/Qmf62JnE0jI9PMnC7bQZIkPDU1uEtLkdxuABShoT53TguZ6GUuPlqqwq/k8mDbXYFl81Ec+dX+LFxBo0DfMxJDnxhUCcZ2Hfd0OhqsKQ3unoa4FKv1AC7X6QvwiaIuwJKi1XWgkDjWWsNYUe1ha50FT6MVViFA7yADw0JNDAsz0dOkR9mG3GItgZzaKyPTSpxtsZDcblxHj+KpqgJAUChRXgQBrjIXhgux3YC7yo51y1EsW47iqTpej0MZpcfQJxp9rygUprbtfmgu/NYUS0N8Sn79LsmHkCT3aT+n0cSi0aVSpUggzxPLelsEWx1RVBEG9b/nQUqRy0NMfstJiq7txZOdL7IYkZFpJZq6WHgsFtxHjuB1+L7sRYOhzQa4yrQdLuTeR5JXwnGwBuvmo9h2HUNy1dfiEAW0XcIw9IlGmx6K0E5qcDQnXq8Lu73opLgUq/XgGa0pXlFPlZhAvieWQ1IcR4ijhHhKiSVWZ2RYfbzJ5aFGQtpwlk5TkcWIjEwrcS6LheT1+gNckSQQhDYZ4CrTdmitjRi9djfW7eVYNx/FebjOf1w0qtBfFoWhdzSq6LYTA9WauFxV9SLluCXFas3HZitEkk69NYQXgXKiKCGOI8RTSjx6fSrp4V0ZFJFEn2AD6nb4nSCLERmZVuL3LBZeh8Mf4AogaDRtLsBVpm3QFnaFdh21YNlyFOvWMrz/n70zj6+iOv//e2bunhtCdsK+I8oqEECqoCC41qUuX6oialFrqVoFFbCIS/ErlhbqUn/WSt2XWq391hURUAGDgijKJmtkC4GEJDfJ3WbO74+ZuyaBBBIC5LxfjnPmzNlmuLnzuc95zjO+2Jt9HR1S8QzONWOXuE78X/WNjWEEqa4ujJv22WJFod1MOFxRZ71KUthLOwxnJzJTe9Aj/RS6p/fC4+l0zN6QfKRIMSKRNBNH+rCQDq6S+nA8iJEIQjfwbyw1Y5dsKAHDfJwodhV3nyw8g3Jxdk07rmKXHI8IIQiGDljTPabzbEnFj5RXbkEN7UGp450+BirC0Z50b3fSvd2jy5FTPN2w21sf24uoAxkOXiI5wVAUBVvr1mheb9TB1YzgWo4tL086uEqOOxRNjUZ61SuCVH2zj8qviwjvq6Lqm31UfbMPLd1JyqBcPINysaUf37FLmgtFUXA6snA6skhPH5pwTtf9VFZtZ1PJen4s3UiZbwv24A7asAsXfggWUl5SSHlJ4ruc7PYMK7hbVzwp3WIrflztUdXj79EvLSMSSSPTWL9cpYOrpDaOJ8tIbQghCO30Ufn1XqrWFCMClo+EAs5urUkZnIv7tEyUer43SVKTat3gy4MVfFm8jc2lGwhWbyOP3bRlF3nsIov9ddZVFAceT6eYUPF0s6wpXbHZUht9rHKaRiJpJhrzYSEdXCXJHO9iJB4jqOP/4QCVX+8lsCUWAE5xaeYL+wblnrSxS44lxcEQn5VUsLS0gqUlFRwM+GhjiZO27KKzuoeu6h7S9J0oIlBnO/37/52szFGNOjY5TSORnAREI7impRHavfu4juAqkSSjOjQ8A3PwDMwhXOI3nV5XFaEfDFD55R4qv9yDLTcudom3ZcQuaWyyHXZ+0SaDX7TJQAjBxio/n5V0ZUlJBe8frKTaMEAHRRhksp98VzFDXcV01/bQKvwT/uptBIP78Ljr9z6opkBaRiSSRqbJImQ2g4PrqFGjGDBgAPPmzWuS9iUN50SyjNSGMASBrQep+rqIqu8PQDgudknvDFIG5eLqlYGiSWtJYxAwDL4uq2SpZTn5rqI6wR3WoSgMSUvh7DSFn+e1o6O7cT9T0jIikZxkJDq47kMvLYk5uLZpg9a69Qln7p41a1atb/j1eDxUVlY2w4gkTY2iKri6p+Pqnk7rajN2SeWqIkI/VeD/4QD+Hw6gptrxDMwlZXAu9hxPcw/5hMapqoxIT2VEeirTgZJQmM9LK/ispIIlJRXsCoRYdtDHsoPQv3Wo0cVIfZFiRCI5wVBsNhzt2qK3bk149y4zRsmuXegHD55wDq5Tpkzh1ltvTcgbPXo0Q4YMaaYRSY4lqtuGd1ge3mF5ZuySr63YJRUhfJ/txPfZTjN2ycAc3P2y5DROI5Bht3FJTjqX5KQjhGBrdYClJRUsO+hjSFrzTftKDziJpKkRAoKVjb5pdoGjQxtsGamgBzDK9hPYsJbQT9sQ1eVmuQbMwlZWVjJhwgS8Xi95eXm1vjk3EAgwZcoU2rVrR0pKCkOHDmXJkiUJZZYtW8aoUaPweDykp6czbtw4Sq338CTj9Xpp06ZNdCsqKmLdunXcdNNNDbrFkhMfe24KrS/sSt70fDKv642rdwaoEPypgoP/2cKe2QXsX/A9VWv2YQRrj2IqaRiKotDN4+LG9tn8vU8XXM0Y1l9aRiSSpiZUBbPbNknTCmC3ttoQ9+1EcdVvud7UqVNZunQp7777Ljk5OUyfPp3Vq1czYMCAaJnJkyezbt06Xn/9ddq2bcs777zDeeedx9q1a+nRowdr1qxh9OjR3HjjjcyfPx+bzcbixYvR9fo9PJ577jl69uzJmWeeWa/ykpMPRVNxn5aF+7QsM3bJt8VUrdlHaKcP/8ZS/BtLURxmGc/AHJzdWkv/kpMA6cAqkTQyNRwMg5VNJkYOO5Yrl2Jr2+mw/iQ+n4/MzExefvllrrzySgBKSkpo3749N998M/PmzaOwsJCuXbtSWFhI27ax6xkzZgz5+fnMnj2bX/7ylxQWFvLFF180fKx+P23btuW+++7jnnvuafjFthBOdAfWIyVUbAVSW1OMXuKP5qteO57+2XgG5mBvJ5cJH29IB1aJ5HjB7oHpu49Zd9FVN8XFCEMz/Un278eWm4uamlrrl/WWLVsIBoMMHRqL/piRkUGvXr2ix2vXrkXXdXr27JlQNxAIkJmZCcCaNWuiYqahvPPOO1RUVHD99dcfUX3JyY0920Pa2M60OrcTwcIKqtbso/rbYgxfCN+y3fiW7caW5TaXEg/Ixpbpbu4hSxqAFCMSSVOjKOA4do5hCmDL8aJl5aEfKCG8vxgjECBYWIjq8WDLzT2i+CQ+nw9N01i1ahWalhg90+v1AuB2H/kD4LnnnuOiiy4iNzf3iNuQnPwoioKzUyucnVrR+qKu+DeVUrWmGP+6A4T3V1O+cAflC3fg6Gg5vvaVjq8nAlKMSCQnKYqqYsvOQktvTXj/fsIHDmBUVRHctg0tNdW0lFhm/m7dumG32ykoKKBjx44AlJaWsmnTJkaOHAnAwIED0XWdffv21enT0a9fPxYtWlTrct1DsW3bNhYvXsx//vOfo7hiSUtD0VTcvTNx987ECISp/v4AVWv2Edh8kGBhBcHCCg7+31ZcPdPxDMzG1TsT1SHD0B+PSDEikZzkKDYb9jZt0DIzzeitpaXoFRXoFRVordOx5WTj9Xq56aabmDp1KpmZmeTk5DBjxgzUuJDzPXv25JprrmHChAnMnTuXgQMHUlxczKJFi+jXrx8XXngh06ZNo2/fvtx2223ceuutOBwOFi9ezJVXXklWVladY3z++efJy8vj/PPPPxa3RHISojptpAzKJWVQLnp5nOPrLh/+DSX4N5SgODTcfTJjjq/ybcLHDVKMSCQtBNVux9GuHUZWFuGiIvTycvSDpehlB7FlZjLn0Ufx+XxcfPHFpKamcvfdd1NWVpbQxoIFC3jkkUe4++672bVrF1lZWQwbNoyLLroIMAXLxx9/zPTp08nPz8ftdjN06FDGjx9f57gMw+Af//gHEydOrDH9I5EcCVorB6lntiP1zHaE9lVRtcZ8g7BeGqBq9T6qVu8zA6v1N/1LpONr8yNX00gkjcyJstrBqKoitLcIo8qMdKqoGlp2FrbMTPkSvuOYE+XzdbwhhDAdX7/ZR/V3xRhV4eg5W7YbzwDzHTq2DHlPGxO5mkYikRwS1ePB0aWz+fK9oiIMv9+0mBw4gC0nBy09Xf5alJw01O74uo/qdSWEi+McXzu1wjMwG3ffbLSUuiL4SBobKUYkkhaMoihoqamoXq+5HLioCBEKEdq9m/D+A9hzc1BbtZKiRHJSodhU3Kdm4j41E8Mf5/i65SDBHeUEd5Rz8D9bcfVKxzMgB/epGSh2OYXYlEgxIpFIYi/ha9UKvaTEjFESDBD86SdUtxtbbhs0b/O9t0IiaSpUl42UweZL+fTygOn4+s0+Qrsr8a8vwb++BMWp4e6ThWdAtnR8bSKkGJFIJFEUVcWWlYWWnh5bDlxdTXD7NlSvF3tuLupRxBKRSI5ntFZOUs9sT+qZ7QkVVVK1xlyRo5cGqFpVRNWqItRURyzia9sUaTVsJKQYkUgkNVA0DXtuLraMDMLFxYRLSzF8PgI+H1rr1thyclAdMpCU5OTFnptC2rgUWo3tRHBHuen4unY/RkUQ3xe78H2xC1uOFfG1v3R8PVoa7DL/2WefcfHFF9O2bVsUReHf//73YessWbKE008/HafTSffu3fnHP/5xBEOVSCTHGsVux962Lc7u3dHS0gDQDx4k8OOPhPbsQYTDh2lBIjmxURQFZ+c00i/rQd70oWROOBV33yywqYT3VVP+0Q72zvmKfc98i+/LPeiVoeYe8glJgy0jlZWV9O/fnxtvvJHLL7/8sOW3bdvGhRdeyK233sorr7zCokWL+NWvfkVeXh7jxo07okFLJJJji+p04ujQASMri1BRkbkC58AB9NJStCxrObCMESI5yanp+LqfqjXFpuPr9nKC28s5+H9bcPVMx90vG3fvDFSXnICoDw2+S+eff36DoiQ+88wzdOnShblz5wLQu3dvvvjiC/785z9LMSKRnGCobjfOzp3RfT7Ce4sw/NVmVNeSEmzZ2eZyYBmjRNICMB1f25AyuA16WZzj656Y42uppkhhUk+a/M6sWLGCMWPGJOSNGzeOO++8s846gUCAQCAQPS4vL2+q4UkkkiNA83pRu6VglJcTKipCBIOE9uwhHIlRkpYmHfskLQYtzUnqWe1JPctyfP1uP9XfFRMurq4pTPpm4T41UwqTJJr8J8zevXtrvIUzNzeX8vJyqqura63z6KOPkpaWFt06dOjQ1MOUSCS1MGrUqDp/OCiKgpaWhrN7d+x5eSg2mylKdu4kuGULus/XJGNasmQJiqJw8ODBJmlfIjka7LkppJ3bidy7BpF75+mkju6ILccNujBFyZub2P3wl+x/4QcqVxdh+KXfFRwDMXIkTJs2jbKysuj2008/NfeQJBJJHSiqii0zE2ePHthyclBUFcPvJ7h9O4Ft2zCqav/RATBr1iwURamxpaTImCaSExtFUbC3MYVJm7sGk/u7QwiTf0hh0uR2ojZt2lBUVJSQV1RURKtWrXDXEa/A6XTidDqbemgSiaQRUTQNe05ObDlwSQlGZSWBrVvQ0tLM5cBJf9dTpkzh1ltvTcgbPXo0Q4YMOZZDl0iaHNNiYoqT6FTO2mLC+6qjbxUu1RRcPeKmctwtZyqnyS0jw4cPZ9GiRQl5CxcuZPjw4U3dtURyXCCEoCpU1SxbQ96DWVlZyYQJE/B6veTl5UWdzuMJBAJMmTKFdu3akZKSwtChQ1myZElCmeUFBZw7fjyZQ4bQ9mc/4+e33ML+wkICmzcT3L0bEYotffR6vbRp0ya6FRUVsW7dOm666aYG3eN//etfnHbaaTidTjp37lxj7E8//TQ9evTA5XKRm5vLFVdcET331ltv0bdvX9xuN5mZmYwZM4bKysoG9S+RNITIVE6ixcRjWkw2lFD6z03sfsSymKwqwqg++S0mDZZdPp+PzZs3R4+3bdvGmjVryMjIoGPHjkybNo1du3bx4osvAnDrrbfy5JNPcs8993DjjTfy6aef8uabb/Lee+813lVIGg8hQBhg6CB0MMJW2sozwlZ+JF1bvh5LR9swIh3E+mnM4wbVqWd5AEW1NsXaa7E8VYs7F5dv2CDshmAVqDrV4WqG/vPs2u52k1PwywI8dk+9yk6dOpWlS5fy7rvvkpOTw/Tp01m9ejUDBgyIlpk8eTLr1q3j9ddfp23btrzzzjucd955rF27lh49erBmzRpGjx7NjTfeyPz587HZbHz68ccIjweEQC8pQT94EFtmJrasrBrLgZ977jl69uzJmWeeWe9rXLVqFVdddRWzZs3i6quvZvny5dx2221kZmYyceJEvv76a26//XZeeuklzjjjDEpKSvj8888B2LNnD+PHj2fOnDlcdtllVFRU8PnnnzdIxEkkR0PtFpP9hPdVtSiLiSIa+Fe3ZMkSzj675hfr9ddfzz/+8Q8mTpzI9u3bE34tLVmyhN/97nesW7eO9u3b8/vf/56JEyfWu8/6voL4mCOE+aDVg9YWakC6IWVrSUdFQrIAOJR40JOEhG6KhIR6enPf1RMev7cD20bMpUu7bFw2hSo9wNBPJzXLWApGL8BjdwOKKZrq2Pt8VWT2HMzLz/yJKy+9CBQoKS2j/WlDufn6a5j32IMU/rSbrv2HU7jua9q2zYvWHXPRFeQPPp3ZD/6eX95wM4U/7eSLTz+q0Yfh9xM+UILh94Mwp3W0jExrObCGPxCgbbv23Hfffdxzzz11XlPkO6i0tJTWrVtzzTXXUFxczMcffxwtc8899/Dee+/xww8/8Pbbb3PDDTewc+dOUlNTE9pavXo1gwYNYvv27XTq1Knx/wGaAL/fz7Zt2+jSpQsul4z6ebISKqqkeu1+qr4zhUmUE0yY1Pf53eCrGDVq1CF/NdQWXXXUqFF88803De2q6Vnyv3Bg89GJh5aGopkWAdVmpdW4tBZ3PpK2JVoQzEasXSMfH7LM4c7XdixilqLkLSL4hCXm4i1KrmxQ7eamqbhVOwWjF1jt1malqcUi00i4FbVen9MtmzYRDAYZ2qcLVJcAkOGEXl07QagKfPtYu2oFuq7Tc+AZCXUDwRCZqU44uIM136zmyovGQMnWGn2ogMMJRN1GwhDaDft2A/DOvz+koqKC68cNgj3fxaxRKLHPj6JA2S6zeukOEAdZ//23XHLBWDPfqjPi9NOYN28eenkR5444nU4d29O1axfOO3cM540dw2WXXoLHk0L/U3sy+pyz6du3L+PGjmXsuedyxZVXkp6RcWQ3XCJpJOy5KdhzU2g1plNMmKzdT7goyWLSvbUZx+QEECaH4sQdeWOweRHsXNm4bWpO0Byg2a19fLq2vCMpa08UAAkioA6RoNriphaSREI0nZyvJQkNtebDXVITvx+2bYOsLuByoQD1myhJIn7aSFj7hOPa8kRiWhhxbYm696llZjlvG2jVNpav2sDhgZRsfLqGpmmsWvJfNFWzyhggwJviAYcXt9sDqgPsnkP2KaJCT0Q/Us+9+g4XjTmT3OwMS+DVcV9C1q9EfxlUWwIwVAWV+2JlqkvMvsp+IlXTWP3eP1iyfBUff7aCmbMeZNaDD/HV+y/TOi2VhS/+keVff8vHS1fwxPw/MmPGNAr++yJdOnUgUQhFhFEkL36KLj7vUFtd5eTflaRuDilMNpbi31gaEyZ9s3GfmoHqsTf3sBtEyxYjQ2+B0y5roEg4RFrV5JeKpPGIt9I08ceqW5/B2O12Cr7fQsfepwNQWlrKpi3bGHnOGEhrz8AR56LrOvv89jp9OvqdPoRFX67hwexeh+wvcjnCMAiXlLD52zUsXv41bz3xF/zlDrS0NLTWaaiaGrM6RcSV11rq36ottEqld+/eLFu9HlJyomWWfbORnt26onkyAAObQzBm9DmMOWcUD0y9ndY9h/Hp8tVcfsE5KIpgxJABjBgygJm/u5lO+RfyzgeLueuWa61BHoupy0OIlOS8kGEKsVUvgE0Bu9vaPHXsrbTNKb+fTgIShMm+Kqq/Kz4phEnLFiN9rzh8GYmkBeD1ernpppuYOnUqmZmZ5OTkMGPGDNS40O49e/bkmmuuYcKECcydO5eBAwdSXFzMokWL6NevHxdeeCHTpk2jb9++3Hbbbdx66604HA4WL17MlVdeSVZWVo1+FVXFlpXFy4uXkNemDeeNHoMIhwkfOEi4pMxcEpyVhRrvG+Gy5p1TssDbmrvvu58hQ4bw8F+e5+qrr2bFihU8+dyLPP3005DZlf/+979s3bqVs846i/T0dN7/cDGGYdBr2LkUFPpYtGgRY8eOJSc7m4Ivv6S45CC9h4yEnFNrCqEax8lbZLqutnNJ5TDi7oSwrEH1ED5hYYqRFU+AryExmBRwpMRtXmuLP7bSzrrOJe3tHtMKK2kW7Dke7GM6nRTCpGWLEYlEEuXxxx/H5/Nx8cUXk5qayt13301ZWVlCmQULFvDII49w9913s2vXLrKyshg2bBgXXXQRYAqWjz/+mOnTp5Ofn4/b7Wbo0KGMHz++zn4Nw+CFF15g4g034O7Vy3wJX3ExRlUV+sGD6AcPoqWmomVloXpqTnidfvrpvPnmm8ycOZOHH36YvLw8HnrooaiTfOvWrXn77beZNWsWfr+fHj168Nprr3Haaaexfv16PvvsM+bNm0d5eTmdOnVi7ty5nH/RzxvvxtaFSBI49doEBILgrIZeF0H1HghVm9NUoera00ZkKbWAoM/cGhN7vIBJqUXE1CF4HN7a69hTpMA5AhomTCzn1+NImDR4NU1zcNyuppFIakGudmgcjKoqwvv3o8e9m0p1e7BlZ6GmprbYd980+POlh+JEShUEfBCstLbktK+W/EoIVCQeB300hcN1FLsnJlCcXnC2Amdq0tbqEPmppgXN5mrxU1OhfVXWqpxiwkVxq3JUBVePphcmTbaaRiKRSI4FqseDo2NHjEDAFCUHD2JUVxEsLERxOLFlZaK1bi3fEnw4Ik7vrkb8ISeEKXASBEySiAnUda4OwRP0xRyuI8LpaGPPqbaaIqXGcR2CxhWXb/ecsKLGnuPBProjrUZ3jAqT6rXFhPbGWUzUzTi7tybt3E44OqQevtEmQIoRiURyXKM6nTjatUPk5BA+UIJeUoIIBgjt3k143z60zExsGRk1AqhJmhBFMVdZOTxATuO0GRU4yYLFB/5y0zqTsJUn7ZM2rDhQ1aXmdjQoai3CpS5xY1llXGmxzZlm5mnNOy1yKGES2FQKY5sv1o4UIxKJ5IRAsduxt8nFlp2FXlpK+MABRChEuKgIvbgYLSMDLTMT1X78zINLGkCCwMk+urYMA0LW9JL/UKKlvG4xE8mP+Ov4y8ztaLCnJIqUZNGSIGBagat1Yp7NcXT9xw8lXpgUV+HfUIq9nbfR2m8oUoxIJJITCkXTsGVloWVkoJeVoe/fH53KCR84UPsKHEnLQlVjVopWbY+8HSFiPjM1LDKHsM74y0wRFBEwIWu+KVRpbhW7j2w8Nnc9BEzkuHVN0VOHD40924M9+4iiITUaUoxIJJITEkVVsaWno7VufdgVOC3V2VVylCiK5UDrBfKOvB09ZImUgzGBEt3Ka8mztkB5bA8QrgZfNfiKjmwcmuPQAmbwjZDR5civ8yiQYkQikZzQKIpiCo/U1IQVOHpFBXpFhVyBI2l+NDt4MsztSDD0mDA5nIiJljuYWBZhvhqistjcaqP3z6UYkUgkkqNFrsCRnJSoGrjTze1IMAzLEfgwFpi09o077gYgxYhEIjnpkCtwJJI4VNXyG2kFdGju0dSKFCMSieSkRa7AkUhODKStUiKR1MmoUaO48847m3sYCSxZsgRFUTh48GC960RW4Dh79MDerh2q02m+pG//fgKbNhHcuRPD72+6QUskkkMixYhEImk2Zs2ahaIoNbaUlJQm6S+yAsfRvTuOTp1QPSkgBPrBgwQ2bya4Ywd6ZSVN8ZaMzp07M2/evEZvVyI5GZDTNBKJpNmYMmUKt956a0Le6NGjGTJkSJP221grcIQQ6LqOzSa/SiWSo0FaRiSSJkYIgVFV1SxbQ37hV1ZWMmHCBLxeL3l5ecydO7dGmUAgwJQpU2jXrh0pKSkMHTqUJUuWJJRZtmwZo0aNwuPxkJ6ezrhx4ygtrT0ct9frpU2bNtGtqKiIdevWcdNNNzXoHv/rX//itNNOw+l00rlz5xpjf/rpp+nRowcul4vc3FyuuOKK6Lm333+fQRdeSMaQIbQ/80wunDSJigP7CRYWEvhxM+GSEoRhvjMlMkX0wQcfMGjQIJxOJ1988QVbtmzhkksuITc3F6/Xy5AhQ/jkk0+ifYwaNYodO3bwu9/9Lmr9ifDFF19w5pln4na76dChA7fffjuVlUf7UhaJ5MRCynmJpIkR1dVsPH1Qs/Tda/UqFE/9IitOnTqVpUuX8u6775KTk8P06dNZvXo1AwYMiJaZPHky69at4/XXX6dt27a88847nHfeeaxdu5YePXqwZs0aRo8ezY033sj8+fOx2WwsXrwYXdfrNYbnnnuOnj17cuaZZ9b7GletWsVVV13FrFmzuPrqq1m+fDm33XYbmZmZTJw4ka+//prbb7+dl156iTPOOIOSkhI+//xzAPbs2cP48eOZM2cOl112GRUVFXy2ZAlaVhZKIFBjBY6wruO+++7jj3/8I127diU9PZ2ffvqJCy64gD/84Q84nU5efPFFLr74YjZu3EjHjh15++236d+/PzfffDOTJk2Kjn3Lli2cd955PPLIIzz//PMUFxczefJkJk+ezIIFC+p9DySSEx1FNMXkaCNT31cQSyTHA8mveDeqqppVjKj1ECM+n4/MzExefvllrrzySgBKSkpo3749N998M/PmzaOwsJCuXbtSWFhI27axENtjxowhPz+f2bNn88tf/pLCwkK++OKLBo/V7/fTtm1b7rvvPu655546yy1ZsoSzzz6b0tJSWrduzTXXXENxcTEff/xxtMw999zDe++9xw8//MDbb7/NDTfcwM6dO0lNTXwj6erVqxk0aBDbt2+nU6fEl4QJXU9YgQPw+ddfM+6GG3j7rbe47Be/OOT19OnTh1tvvZXJkycDps/InXfemeAQ/Ktf/QpN0/h//+//RfO++OILRo4cSWVlJa5aQtonf74kkuOZ+j6/pWVEImliFLebXqtXNVvf9WHLli0Eg0GGDh0azcvIyKBXr17R47Vr16LrOj179kyoGwgEyMzMBGDNmjVRMdNQ3nnnHSoqKrj++usbVG/9+vVccsklCXkjRoxg3rx56LrOueeeS6dOnejatSvnnXce5513Hpdddhkej4f+/fszevRo+vbty7hx4xg7dixXXHEF6enptb4DJ/LbrW96OsGfdqJlpKN6PFRWVjJr1izee+899uzZQzgcprq6msLCwkOO/dtvv+W7777jlVdeieYJITAMg23bttG7d+8G3QuJ5ERFihGJpIlRFKXeUyXHMz6fD03TWLVqFVpSsDCv13zbp7ue4qc2nnvuOS666CJyc3OPapzJpKamsnr1apYsWcLHH3/MzJkzmTVrFl999RWtW7dm4cKFLF++nI8//pgnnniCGTNmUFBQQJcuZljs+Hfg2H78EYAUlwu97CB62UEUh5O7Zv+BRZ9/zh//+Ee6d++O2+3miiuuIBgMHnJsPp+PW265hdtvv73GuY4dOzbqfZBIjmekA6tEIqFbt27Y7XYKCgqieaWlpWzatCl6PHDgQHRdZ9++fXTv3j1ha9OmDQD9+vVj0aJFDe5/27ZtLF68uMGOqwC9e/dm2bJlCXnLli2jZ8+eUdFks9kYM2YMc+bM4bvvvmP79u18+umngCkWR4wYwYMPPsg333yDw+HgnXfeqdGPoiholqh0du6Clp4OqooIBli+bBnXXHABFw4ezKldupCbm8v27dsT6jscjhq+M6effjrr1q2rcT+7d++Ow9F4r4uXSI53pGVEIpHg9Xq56aabmDp1KpmZmeTk5DBjxgzUuHe49OzZk2uuuYYJEyYwd+5cBg4cSHFxMYsWLaJfv35ceOGFTJs2jb59+3Lbbbdx66234nA4WLx4MVdeeSVZWVl19v/888+Tl5fH+eef3+Cx33333QwZMoSHH36Yq6++mhUrVvDkk0/y9NNPA/Df//6XrVu3ctZZZ5Gens7777+PYRj06tWLgoICFi1axNixY8nJyaGgoIDi4uLDTo+oHjeO1q0Rbdqgl5XRvWtX3v3kEy4YORJFUXj4qacwdD26CgdMn5HPPvuM//mf/8HpdJKVlcW9997LsGHDmDx5Mr/61a9ISUlh3bp1LFy4kCeffLLB90IiOWERJwBlZWUCEGVlZc09FInksFRXV4t169aJ6urq5h5Kg6ioqBDXXnut8Hg8Ijc3V8yZM0eMHDlS3HHHHdEywWBQzJw5U3Tu3FnY7XaRl5cnLrvsMvHdd99FyyxZskScccYZwul0itatW4tx48aJ0tLSOvvVdV20b99eTJ8+vV7jXLx4sQAS2nzrrbfEqaeeKux2u+jYsaN4/PHHo+c+//xzMXLkSJGeni7cbrfo16+feOONN4QQQqxbt06MGzdOZGdnC6fTKXr27CmeeOKJBvUthBDbtm0TZ48cKdwul2jfpo340/Tp4szBg8Vvrr1WBHbsEOHycrF8+XLRr18/4XQ6RfxX78qVK8W5554rvF6vSElJEf369RN/+MMf6hzDifr5krRM6vv8lqtpJJJGRq52aNkIXTcDqJWUYFRXR/MVux0tPR0tPf2o3oUjP1+SEwm5mkYikUiaAUXTsKWnY0tPx/D70UtK0csOmi/o27eP8L5itFQvWkYGqtd7yAivEklLQYoRiUQiaSJUlwu1bR62Nrkxa0lVVTTsvGK3o7VOR0tvjSodViUtGClGJBKJpIlRVBVb69bYWrc2rSWlpegHLWtJ8T7CxftQU1Oxpacf9n04EsnJiBQjEolEcgxRXS7UvDxsuZa1pLQUo7ISo6KCYEUFis0W8y2R1hJJC0GKEYlEImkGEqwlgUDMWhIOEy4uJlxcjOr1xqwlqgwLJTl5kWJEIpFImhnV6URt0wZbTg5GRQXh0lIMnw/D5yPo85nWktatzUBrEslJiBQjEolEcpygqCpaWhpaWhpGMGhaS0pLTWvJ/v2E9+8n5HJhVFdjBIMgl/ZKThKk3U8ikUiOQ1SHA3tuLs5evXB07IhqvXHYqKpCLy1lx3UTKPrfxwhs3drMI5VIjh4pRiQSieQ4RlEUtFatcHbqhLNnT7SMTFA1jPJySv7xD7ZecCHbr72Wsv/8B8Pvb+7hSiRHhBQjEomkTkaNGsWdd97Z3MOQWKgOB/asTOy5ObR5cBbec84BTaP661XsvudefjxrJHv/MBt/3AsOJZITASlGJBJJs/LRRx8xbNgwUlNTyc7O5he/+EWNN95KklAUUvLz6fD0U3T/dBHZd9yOvW1bjPJySl96iW0/v4Tt/zOeg/96G6OqqrlHK5EcFilGJBJJs7Ft2zYuueQSzjnnHNasWcNHH33E/v37ufzyy5t7aCcM9txcsn79a7p9spAOf/sbqWPHgs1G9Zo17Jkxgx/PGsmeBx/Ev359cw9V0owIIQiFSvH5NnLgwGfs3v0W27Y/xYaND/Dtd7fw1VeXUV39U7ONT66mkUiaGCEE4aBx+IJNgM2h1juaZ2VlJb/+9a95++23SU1NZcqUKTXKBAIBZsyYwWuvvcbBgwfp06cPjz32GKNGjYqWWbZsGTNmzGDlypU4nU7y8/N5/fXXSa9lWeqqVavQdZ1HHnkE1YqjMWXKFC655BJCoRD2o3ihXEtDUVW8Z/4M75k/I1xczMF//5uD/3yLUGEhB197nYOvvY6zd29aXXA+rc4/H0f79s09ZEkjEQ77CAT2EQgWEQzsIxDYax3vIxAoIhDYRzBYhGEED9mO378Ht7vDMRp1Ii1ajPz4VRFVFUE0m2pudiWWjt9qyVdtCppdRVUVGbpZckjCQYNn71jaLH3fPH8kdqdWr7JTp05l6dKlvPvuu+Tk5DB9+nRWr17NgAEDomUmT57MunXreP3112nbti3vvPMO5513HmvXrqVHjx6sWbOG0aNHc+ONNzJ//nxsNhuLFy9G1/Va+xw0aBCqqrJgwQImTpyIz+fjpZdeYsyYMVKIHAW27GyyJk0i86abqFq5koNvvkn5wk8IrF9P8fr1FM/9E65+/Uxhct552Nu0ae4hS2pB1wMEo4KiKCouTMFRRCBoCg1dr6x3m3Z7Ok5HDg5nDk5nG5zOHJyOXJzOHFJSujfh1RwaRQghmq33elLfVxA3lH/N+Zq9W8uPrhGFOJESJ1rsNfPUJHFjs6modvUw9WvPVzUFVVPi0mrs2KZIkdSMJL/iPRTQj3sx4vP5yMzM5OWXX+bKK68EoKSkhPbt23PzzTczb948CgsL6dq1K4WFhbRt2zZad8yYMeTn5zN79mx++ctfUlhYyBdffFHvMS5dupSrrrqKAwcOoOs6w4cP5/3336d169YNvt6WQPLnq76ES0upWLiQ8vc/oGrlSjBi1jr3oEG0Ov98Wo0biy07uymGLYnDMEIEg/sJBPcRtCwXtVkzwuGD9W5T07ymsHDmRsWFI3Js5Tkc2Wias+kurBbq+/xu0ZaR9r0z8Ga40EMGelighw2MsIEe3YR1LjFPGHH6TWCWCTWPGf5Q1CZYNFuScLHKxJ/TNAXVOqdFhI5NQbPqxc5F8mvmRdtJPqcpKKqVr8bGEt2sc8pJJKZsDpWb549str7rw5YtWwgGgwwdOjSal5GRQa9evaLHa9euRdd1evbsmVA3EAiQmZkJwJo1a6Jipj7s3buXSZMmcf311zN+/HgqKiqYOXMmV1xxBQsXLjxpPgPHA7b0dNKvuor0q64iXFxM+ccfU/7+B1SvWhXdimbPxpOfT6vzzyd17LnYZMTXBmH6ZZTELBnJ1oygmRcMHgDqZwdQVQdORxtLWETERpxVw2mKDJvN27QX18S0aDEy9OKuR1TPMEzhEhUqoTjxEi9cQgZGcl7YQA/VkhcWcXVqyU/qx9ANDF2g6wIjbKZrjFMXGHrz+SscLRFhomoKSkQUqcnCpXYxo2oqimoKJSVOcKlqzXLRPqw8zaob32a8gEo+Z9aNtR02ghi6QTikE9YMFMUUhpj/gfWAjTxnT5QHrs/nQ9M0Vq1ahaYlWlu8XvOL0O12N6jNp556irS0NObMmRPNe/nll+nQoQMFBQUMGzbs6AcuqYEtO5uMa64h45prCO3dS/mHH1L+wQf4v/2Oqi+/pOrLL9n70EOknHGGKUzGjEZrRKv0iYgQhmnNCOzFH9hDwL/XSpv7gN9MC3Fov4wIiqLhcGTXEBeOuGkTpzMXmy3thPmOOBpatBg5UlRVQXVo2B31m4s/FgghMAwRFT+mELEES/Q4ltZ1UygZuiVuDCOpblJZS/To1jmjtnYifUbaMURMOEX2hoi2H0knWJriMAyzDKFjfDOPEleaSt+L0yhzV1Nlq91XojaiXzhR0WL+L/o9pIASPUlcvhJXPpKvJJU5dN02We2x2+18tvgLLr/sCgAOHixl06ZNjDjjZ/h9QU7t1Qdd1/mpcDdnjvhZjb6D/jB9TuvDJws/4f4ZMxPHVEfflZWVqKqKECJ6/RGhYxgnpog+0bC3aUPmxIlkTpxIcOdOyj/4gPIPPiCwbj2Vn39O5eefs/cBOylnnkmr88/He/bZaN6U5h52o2IYYYLB4iRxsSeWDuwlEChCiHC92rPbM3E546wZceLC6czF4czFYU9HUY6fZ0hzI8XISYKimFYATaPeDovHC1EhpQtEglCJCSMzz6ghZOLLiPi8eNFziPrCKq8btfctDJHQVsKxEddnpL4hsKeAohKdahLmRdbrPpiJeAPusXHpUrDzy6uuY/qMabgdqWRlZvPo4w+jKCrBap3yA35y0zvwi0uv4sYbJ/Lg/X+gz2n9OHDgAJ8vW8Kpvftw7jnjuPWGOxh13nBuvukWJlxzIw67g2UrPuPiCy8jMyOzRr8jhpzNvHnzuO/u+7ns51fgq6xg9uMP0aF9R9pnd6f4p4qYuEoQaU0nzGLtx04m1q0tv45+k8dcQ3AeX1YyR/v2ZE2aRNakSQS2baP8gw+o+OADAj9uxvfpp/g+/RTF6cQ7ciStLrgA78izUBtoDTvWGEaQQKCYQGBPTGzUEBr7gPqIX9USFW1wOtvgcrbB6Yqk86LWDVV1NPVlnXS0aAdWiaQpqMvBsIbYsI6jf4ECRJwSif1liqQytdUVVn58XZEobOpq38r3Vfi46547+L/33sWb4mXyr2/no08+ou9pfXn04ccBCAaD/HHeY7zxz9fYs3c3GRmZDD59CPfePYNTTzkNASxb/gV/mDOL79auweV0c/rAQTz7xAJapaXVqq3e+c9bPPX/5rNl2xbcbjeDB+bz+/sepEf3njULtxAOZSULhgPs2v0TO1YE0f1KbDoyfioxMoWoxk1TRo/VmtOadU55mlOWxv4i/N+uwb96Fca+vSjCQBE6qsNOysABeM8YRsqggWhOR93TqPHTro3kE6brgThBEbFq7IlOmQQCewkG91MfUa8ommnBSBYXLkt0ONvgcGSjqnKVV0Oo7/NbihGJpJE50tUOLYU6RVn0f7WVOXTdhGStwiwuP1q/bmFWZ91o9/UoYx3UJSSPlFA4yK49P7H2/8rwl524U1k1hFKyX5cthN1TguYuxeYqQXOWoDpLUB0lqI4DKLYSFFtZ/ToTdlSy0JRsNCUHm5qDTcvBpuXisOVit+dit2Wg2Wx1OPjHOf4nibaTydm+KZCraSQSyXFJjV/9tLwv8qOxklX7VdyVDs657hQUYUuYOqyRTpp6rJmXOOUpLKd4YdScskxuyzAEeqWfsK8SvcqPIUAoKkLREKqG0OxmulbtJVDs5dg9B7B7SrCllGD3mJstkueqqNe9NMIOwtWtCVWlE65OJ1SdTjiStvZ6wEvdAcd1YLe1HRmRVYNanHCpbeVibSsbNVt83biVi3ErGBPqJ61s1JL2CSsdk/qNX9F4vCHFiEQikRxjjkaQ6cKGza6S16X1cWN5E4ZB9erVlL//AeUffUSofD9GOoQzBKJDCtrpnaFra0IpAXMaJbinXqtOFMWFTc1FU3KsLRuVbBQjG0Vkg56JULwIp8CwCYwUkeh0ryeLqchqxJr5CQ73tdSNtFnbjI9ZRqd+7q3Nj6oqCWIlIorGTepDTqfmmX2QYkQikUgk9SayxNXv340/sNvc+3cTcOzGf/5u/Gf7CYXil8CVAd+aBoiEGJMKTmeu6Zvhaosrsjlj6eNxWWtt1qLkFYzxKw0TViPGr2BMWu2YvI+uXkze64doJ1yzXz1s1BBQhiEwgjXDPohmnPWTYkQikUgkUXS9Cr9/D37/rpqCw78Hf2APQhx+vb2mpeBytsVW7UYp9GF8vwe1KIhWoqCVKLhS2pE27nxSzz8f16mnHneioy5MR2ANTiA/VjPsg5EQl6o2EZSe52m2MUoxIpFIJC0E06pRHBUXNYXGbkKh0nq0pJpWjVqsGU7r2GZLTRAYRjBI5RdfUP7e+1QsXky4ZDcHnvs7B577O/ZOHWl1wQW0Ov98XD1b7iqqpiISG+t4fuAfz2OTSCQSSQMQQicQKKK6eid+/06q/bvw+3firzbTgcDeelk1bLZUXM62semTOLHhcrXF4chBVRv2+FAdDlLPOYfUc87BqK7Gt/Qzyj/4AN+SJYR2FHLgr89w4K/P4OjezXxPzvkX4Oza5UhvheQEQy7tlUgaGbm0V9JUCCGorq5g27atpKYWEtZ3JImNPYeNEqoomhVHI86S4WqLy5kX56uReoyuCHRfJb7Fiyn/4AMqP/8cEedv4uzdm1bjxuIdORLnKaecMFM5khgyzohE0kxIMSI5UoQQCBHCMEIYRhAhgnHpkPW2V4OfftrHwbIHMYyay1EVxY7L1Ra3qz0uVztc7vaxtKstTmfucRuGXC8vp+KTRaYwWbECwjFhZcvNxTtyJN5RI0kZNgzV03z+DZL6I8WIRNJMSDEiqYv6iI3DRQsNBgU7d5ZgGO/gdnsSxYa7PU5H9nErNhpCuLSUioUL8X26mMovv0T4/dFzisOBJz8/Kk4cHTo040glh0KKEYmkmTiZxMioUaMYMGAA8+bNa+6hRNm+fTtdunThm2++YcCAAc09nAQaQ2yAgqraUVUHimLu49OBQDh6D070z1d9Mfx+qlauxLdkKb6lSwnt2pVw3tG1qylMRo7EM+h0FPsJtNTlJEdGYJVIJCcEH330EQ888AA//PADLpeLs846i7lz59K5c+fmHloNTLERxjCCRy02FNWOqlhCI5q2oyj2Q/pGKEr93wR9sqC6XHjPOgvvWWchxP0Et2zBt3QpviVLqVq9muDWrZRs3UrJggWoXi8pI0aY4uSsM7FlZTX38CX1QIoRiUTSbGzbto1LLrmEu+66i1deeYWysjJ+97vfcfnll7N69epmGZMQelRgxASHtYlgPd4tc3RiQ3JoFEXB2b07zu7dybzpJvTyciqXLTOtJp9/jl5SQsVHH1Hx0UcAuPr0iU7nuE47DUWtKyy8pDmR/yoSSRMjhCDk9zfL1pBZ2MrKSiZMmIDX6yUvL4+5c+fWKBMIBJgyZQrt2rUjJSWFoUOHsmTJkoQyy5YtY9SoUXg8HtLT0xk3bhylpbXHrli1ahW6rvPII4/QrVs3Tj/9dKZMmcKaNWuSongemqVLl5Kfn4/T6SQvL4/77ruPcJzz41tvvUXfvn1xu91kZmYyZsw5lJUVEQyW8PHHbzN48ABSUjy0bt2K4cMHs379UqqrdxAI7CEYPEA4XIFhBKJCRFUdaLYU7PZ0M96Guz0eT1e83l6kpp6G19uLFE9X3O72OJ05OOzp2Gwp1nSLFCKNidaqFa3OP5+2j/0vPb74nM5vvE7Wbb/GdeqpAPi//579Tz3F9iuv4sezRrJ7+gzKP/oY3edr5pFL4pGWEYmkiQkHAvzl+iuape/bX3gLez39CqZOncrSpUt59913ycnJYfr06axevTrBL2Py5MmsW7eO119/nbZt2/LOO+9w3nnnsXbtWnr06MGaNWsYPXo0N954I/Pnz8dms7F48WJ0vfaphUGDBqGqKgsWLGDixIn4fD5eeuklxowZg72e8/67du3iggsuYOLEibz44ots2LCBSZMm4XBo/P7397Br10+MHz+eRx65j4suOpvy8oMsX76Kysrt6LqDq66ayIQJl/Pcc7MJhUKsWrUWVdXQNDeK6ohaN+J9N6SgOD5RVBV3//64+/cn+/bbCe3bR+Vnn+FbupTKZcvR9++n7O23KXv7bbDb8QwaFPU1cXTpLP9dmxHpwCqRNDLJDqwhv/+4FyM+n4/MzExefvllrrzySgBKSkpo3749N998M/PmzaOwsJCuXbtSWFhI27Zto3XHjBlDfn4+s2fP5pe//CWFhYV88cUX9R7j0qVLueqqqzhw4AC6rjN8+HDef/99WrduXWv5iPPmqlUr6devN/ffP5N33vkP33yzyPLbCPLss68wa9Y8fvppOd99t4GRI/+HtWs/pGPHyLjNqZSDB6vo0OF0Pv7434waNcoSGw4z3PdxysnkIH0sMYJBqr/+OuprEtyxI+G8vWPHmBNs/hBUh6OZRnpyIR1YJZLjBJvTye0vvNVsfdeHLVu2EAwGGTp0aDQvIyODXr16RY/Xrl2Lruv0TArXHQgEyMzMBGDNmjVRMVMf9u7dy6RJk7j++usZP348FRUVzJw5kyuuuIKPP/4wKi4i/hrCCFJZuRWAqqrtVFW5+OGH7xgypA/hcOwtbMOGDcTnq2Lv3jIGnp7P2WefyRlnXMHYsWM499yxXHnl1WRkZOD1wsSJE7n44qs599xzGTNmDFdddRV5eXn1vgbJiYHqcJByxhmknHEGudOmEdy+3RQmS5dS+dXXhAoLKX3pJUpfegnF4yFl+HC8I8/CO3Ik9tzc5h7+SY8UIxJJE6MoSr2nSo5nfD4fmqaxatUqNC3RcuD1egFwu931bk8IwZNP/oVWrVJ55JH7LGfRTJ599mF69TqLxYtfZ8iQ/jXqmStWwLRumFYMRXXidLaJTqWkpJhlPJ7OpHo7smjRUpYvX87HH3/MU0/9ld///gEKCgro0qULCxYs4Pbbb+fDDz/kjTfe4P7772fhwoUMGzbsyG6U5ITA0bkzGZ07k3H99ei+SipXLDeFydLPCBcX41u0CN+iRYAZCTYiTNz9+qFox6/l7ERFOrBKJBK6deuG3W6noKAgmldaWsqmTZuixwMHDkTXdfbt20f37t0TtjZt2gDQr18/Fllf4GAKDsMIEg77CAYP4PfvoapqBz7fJip8P1BWtgsI4vfvIhgsJhQqA0whYRgCRTF9N+z2NByObFyudrjdZoCrlJRueL296NNnMF+t/BaHIwu7PQ1Nc7N8+ZekpqbSvn17wBSEI0aM4MEHH+Sbb77B4XDwzjvvJFzbtGnTWL58OX369OHVV19tqlstOQ7RvCm0Ovdc2j7yCN0/W0rnf71F1u2/xdW/HygKgfXrOfDM/2PH+F/y48/OZNc991D23nvoZWXNPfSTBmkZkUgkeL1ebrrpJqZOnUpmZiY5OTnMmDEDNW4ZZM+ePbnmmmuYMGECc+fOZeDAgRQXF/PJJ5/Qt++pnH/+aO6++1YGDTqLm2++jhtvvBKbDT77bCWXXTaWzMz0Gv2OHXsWTz31Eo8//jxXXX05lb4gDzzwKJ06dWTEiMvweLw16ths5nRMxNnwtttuY968efz2t79l8uTJbNy4kQceeIC77roLVVUpKChg0aJFjB07lpycHAoKCiguLqZ3795s27aNZ599lp///Oe0bduWjRs38uOPPzJhwoQmutOS4x1FUXCfdhru004j+7bbCJeU4Is4wX6xDL20lPL//B/l//k/0DTcAwdEfU2cPXpIJ9gjRZwAlJWVCUCUlZU191AkksNSXV0t1q1bJ6qrq5t7KA2ioqJCXHvttcLj8Yjc3FwxZ84cMXLkSHHHHXcIw9BFOOwXlVUHxIwZU0SnTh2E3W4Xbdpki4suGi2WL39LlJV9J8rKvhPvvfe8GDp0gHA6HSItLVWMHj1C/PTTV6Kycpuort4lAoH9IhQqF7ruF4ZhiNdee00MHDhQpKSkiOzsbPHzn/9crF+/vs5xbtu2TQDim2++ieYtWbJEDBkyRDgcDtGmTRtx7733ilAoJIQQYt26dWLcuHEiOztbOJ1O0bNnT/HEE08IIYTYu3evuPTSS0VeXp5wOByiU6dOYubMmULX9Sa910fDifr5OhkwgkHhKygQe+fMEZsvvFCs63VKwrbp7LPF7lmzRPmiT0W4vLy5h3tcUN/n9xGtpnnqqad4/PHH2bt3L/379+eJJ54gPz+/1rL/+Mc/uOGGGxLynE4n/rj3DBwOuZpGciJxoq52EMKwgn0Fos6ihhGIOpAeEkWxlsA645bBOuVS2CbgRP18nYwEd+7Ct3QJvqVLqSpYiQgEYidVFVfv3niGDsWTPwTP4MFo3pqWvpOdJltN88Ybb3DXXXfxzDPPMHToUObNm8e4cePYuHEjOTk5tdZp1aoVGzdujB7LLyaJpHkwBUckomiy6DhMkDFFQVVqig0pOCQtFUf7dmRccw0Z11yDUV1N5ZdfmsJkxZcEd+zA/8MP+H/4gZLnnzfFyWmnkTI0H09+Pu7TB6F5U5r7Eo4bGixG/vSnPzFp0qSoteOZZ57hvffe4/nnn+e+++6rtY6iKFEHN4lE0rTEBEcgblmsmRaHERyKolqBvmqzcNik4JBI6kB1u0k9+2xSzz4bgNDevVR99RWVBQVUrfyKUGEh/rVr8a9dy4Hn/g6ahqvPaaTkD8WTn4/n9IGoKS1XnDRIjASDQVatWsW0adOieaqqMmbMGFasWFFnPZ/PR6dOnTAMg9NPP53Zs2dz2mmn1Vk+EAgQiDN3lZeX11lWImmJCGuVSkxwBOIsHYcXHOb7Upxx0UWl4JBIGhN7mzakXXwxaRdfDEBozx6qVq6kcuVKqgpWEtq5E/+33+H/9jsO/O1vYLPh7tPHFCZD8/EMHIjq8TTzVRw7GiRG9u/fj67r5CYFgMnNzWXDhg211unVqxfPP/88/fr1o6ysjD/+8Y+cccYZ/PDDD9Fld8k8+uijPPjggw0ZmkRy0iES3hAbSBIeQQ71dlhF0WJTKEmiQ1E0KTgkkmOMPS+PtEsuIe2SSwAI7dpF5cqvqFq5kqqCAkK7d1O9Zg3Va9Zw4NlnwW7H3bcvnvwhpAwdinvAANQGxPE50WiQA+vu3btp164dy5cvZ/jw4dH8e+65h6VLlybEKKiLUChE7969GT9+PA8//HCtZWqzjHTo0EE6sEpOCBrqYGi+JbY2wRFACKPuiopiWjSiUyrOOD8OuWr/ZEU6sJ6cBHfuoqqgIGo9Ce/Zk3Besdtx9e9HSn4+nvyhuAf0Rz0B/v2bxIE1KysLTdMoKipKyC8qKqq3T4jdbmfgwIFs3ry5zjJOpxNnPcNYSyQnAtFpFREvOurnx6Gq9jih4YyzcEinUYnkZMHRvh2O9pfT+heXm2/63rnTFCYFBVQVrCRcVET116uo/noVPP1XFIcDd//+0Wkdd//+qCfwc7NBYsThcDBo0CAWLVrEpZdeCoBhGCxatIjJkyfXqw1d11m7di0XXHBBgwcrkRzPCCEIhUooL9+GrkMgsA/DEA2YVkkUGzE/DhkoWSJpSSiKgqNDBxwdOtD6F78wv1sKC6P+JlUFBYSLi6n66iuqvvoKnnrKFCcDB0andVz9+p1QL/trsC33rrvu4vrrr2fw4MHk5+czb948Kisro6trJkyYQLt27Xj00UcBeOihhxg2bBjdu3fn4MGDPP744+zYsYNf/epXjXslEskxQterzZe0VW+jqnKrua8yt3C4HFVtS+u0BwiFHImWi4RYHMnCQ06rSCSS2lEUBUenTjg6dSL9yisRQhDcvp2qlV9RVVBA5Vcr0Yv3m9M8BQXsf+JJFKcT98CBsaXEffuiHMfipMHfgFdffTXFxcXMnDmTvXv3MmDAAD788MOoU2thYWFCCOnS0lImTZrE3r17SU9PZ9CgQSxfvpxTTz218a5CImlkhDDw+3dRVbWVqqptVFZto7pqG5VVWwkE9hyipoLTmYuqOrHbW+NyeaLCQ06rSCSSxkBRFJxduuDs0oX0q68yxcm27VSttHxOClaiHzhA1ZdfUvXll2YdlwvP6QPxWEuJ3X37oNjtzXwlMY4oAuuxRkZglTQVhhGgqmo7lZWbqazaSlXlZiqrtlBVtRXDCNRZz2ZLw+PpSoqnCx5PFzyerng8XXC7OxEKcdI4GI4aNYoBAwYwb9685h5KlO3bt9OlSxe++eYbBgwY0NzDOeZIB1bJ4RBCENy6NRrjpGrlSvSSkoQyiseDZ+BAPEOHkpI/BNdppzWJOGmyCKwSyYlIOFxBZeUWKqs2U1W5hcqqLVRWbqa6+ieg9hUriuLA4+kUFRoedxc8Kebe4cios69QqP6vOpDARx99xAMPPMAPP/yAy+XirLPOYu7cuXTu3Lm5h9aoHI/CTnJyoigKzm7dcHbrRsYvf2mKk82bqSxYaS4lXrkS/eBBKpcto3LZMooB1eOh3fx5eM88s1nGLMWI5KRBCEEwWGxZObZYomMzlZVbCAb31VnPZkvF4+lOiqcrKSnd8KR0J8XTDbe7A4qiHcMraHls27aNSy65hLvuuotXXnmFsrIyfve733H55ZezevXq5h5evQiFQtiPI3O3RJKMoig4e/TA2aMHGddegzAMAj9utoSJaT3Ry8pwNOMPAOmmLznhEEKnqmo7xfsXsWPH/2Pdunv46utf8NnnA/li2XC+WXMdmzbNYueulygtXREVIg5HDunpw2nf7jp69pzFwAEv8bMRKzjrzG8YMvgtTj11Dp063UJ21mg8ns6NJkSEEBhBvVm2hszCVlZWMmHCBLxeL3l5ecydO7dGmUAgwJQpU2jXrh0pKSkMHTqUJUuWJJRZtmwZo0aNwuPxkJ6ezrhx4ygtLa21z1WrVqHrOo888gjdunXj9NNPZ8qUKaxZs4ZQ6DDvyolj6dKl5Ofn43Q6ycvL47777iMcDkfPv/XWW/Tt2xe3201mZiZjxoyhsrISgCVLlpCfn09KSgqtW7dmxIgR7Nixo9Z+tm/fjqIovPHGG4wcORKXy8Urr7zCgQMHGD9+PO3atcPj8dC3b19ee+21aL2JEyeydOlS5s+fj6IoKIrC9u3bAfj+++85//zz8Xq95Obmct1117F///56X7tE0lAUVcXVqycZ111L+yeeoMeK5XR5913sdQQiPRZIy4jkuEXX/ZbzaGxqpapyC1XV2w7xFlkVt7sDKZZ1w5PSjRRPd1JSumGzpR7T8UcQIYPdM5c3S99tHzoDxVE/UTV16lSWLl3Ku+++S05ODtOnT2f16tUJfhmTJ09m3bp1vP7667Rt25Z33nmH8847j7Vr19KjRw/WrFnD6NGjufHGG5k/fz42m43Fixej63qtfQ4aNAhVVVmwYAETJ07E5/Px0ksvMWbMmHpbG3bt2sUFF1zAxIkTefHFF9mwYQOTJk3C5XIxa9Ys9uzZw/jx45kzZw6XXXYZFRUVfP755wghCIfDXHrppUyaNInXXnuNYDDIypUrD+tofN999zF37lwGDhyIy+XC7/czaNAg7r33Xlq1asV7773HddddR7du3cjPz2f+/Pls2rSJPn368NBDDwGQnZ3NwYMHOeecc/jVr37Fn//8Z6qrq7n33nu56qqr+PTTT+t1/RLJ0RIRJ82JFCOSZicUKosJjqgj6Raq/T9RV2wOVXVaDqSRaZWupKR0x+3ujKaduIF/mgufz8ff//53Xn75ZUaPHg3ACy+8kPDKhsLCQhYsWEBhYSFt27YFYMqUKXz44YcsWLCA2bNnM2fOHAYPHszTTz8drXeo91B16dKFjz/+mKuuuopbbrkFXdcZPnw477//fr3H/vTTT9OhQweefPJJFEXhlFNOYffu3dx7773MnDmTPXv2EA6Hufzyy+nUqRMAffv2BaCkpISysjIuuugiunXrBkDv3r0P2+edd97J5ZdfnpA3ZcqUaPq3v/0tH330EW+++Sb5+fmkpaXhcDjweDwJASKffPJJBg4cyOzZs6N5zz//PB06dGDTpk307Nm8DwiJ5FghxYjkmCCEIBDYa1k3TMFRWbmZqqotBIN1m6RttjTTj8PTjZQ4K4fL1e6E8edQ7CptHzqj2fquD1u2bCEYDDJ06NBoXkZGBr169Yoer127Fl3XazwgA4EAmZmZAKxZs4Yrr7yy3uPbu3cvkyZN4vrrr2f8+PFUVFQwc+ZMrrjiChYuXFivpdDr169n+PDhCWVHjBiBz+dj586d9O/fn9GjR9O3b1/GjRvH2LFjueKKK0hPTycjI4OJEycybtw4zj33XMaMGcNVV11FXl7eIfscPHhwwrGu68yePZs333yTXbt2EQwGCQQCeA7zorNvv/2WxYsX4/V6a5zbsmWLFCOSFoMUI5JGxXQi3Yev8kcqfZuorPwRX+UmKis3o+u+Ous5nW1qTKt4UrrjsGee8LE5FEWp91TJ8YzP50PTNFatWoWmJV5P5GHqbuCLvJ566inS0tKYM2dONO/ll1+mQ4cOFBQUMGzYsKMet6ZpLFy4kOXLl/Pxxx/zxBNPMGPGDAoKCujSpQsLFizg9ttv58MPP+SNN97g/vvvZ+HChYfsOyXpVe+PP/448+fPZ968efTt25eUlBTuvPNOgsG6phNNfD4fF198MY899liNc4cTRBLJyYQUI5IjJhg8ECc2fsRniY9wuKzW8oqi4XZ3tKwcpk9HSkp3PJ4uzebPITHp1q0bdrudgoICOnbsCJgBCzdt2sTIkSMBGDhwILqus2/fPs6sY/lfv379WLRoUb3ful1VVZUQJBGICh3DOMRLAuPo3bs3//rXvxBCRIXrsmXLSE1NjU4zKYrCiBEjGDFiBDNnzqRTp06888473HXXXdFrGzhwINOmTWP48OG8+uqrDRJCy5Yt45JLLuHaa6+Njn3Tpk0JwR0dDkcN35nTTz+df/3rX3Tu3BmbTX4dS1ou8tMvOSyhUDmVlXFWDt8mfJU/EgodqKOGisfTiZSUnqSk9MBr7T2ezqjq8RuOuCXj9Xq56aabmDp1KpmZmeTk5DBjxowEodCzZ0+uueYaJkyYEHXeLC4uZtGiRfTr148LL7yQadOm0bdvX2677TZuvfVWHA4Hixcv5sorryQrK6tGvxdeeCF//vOfeeihh6LTNNOnT6dTp04MHDiwXmO/7bbbmDdvHr/97W+ZPHkyGzdu5IEHHuCuu+5CVVUKCgpYtGgRY8eOJScnh4KCAoqLi+nduzfbtm3j2Wef5ec//zlt27Zl48aN/Pjjj0yYMKFB969Hjx689dZbLF++nPT0dP70pz9RVFSUIEY6d+5MQUEB27dvx+v1kpGRwW9+8xv+9re/MX78eO655x4yMjLYvHkzr7/+Os8991wNC5REcrIixYgkSjhcacbl8P1IZeWmqMUjENhbZx2XqwNeb7Lo6CadSE9AHn/88ei0QWpqKnfffTdlZYlWrgULFvDII49w9913s2vXLrKyshg2bBgXXXQRYAqWjz/+mOnTp5Ofn4/b7Wbo0KGMHz++1j7POeccXn31VebMmcOcOXPweDwMHz6cDz/8sN5TPu3ateP9999n6tSp9O/fn4yMDG666Sbuv/9+AFq1asVnn33GvHnzKC8vp1OnTsydO5fzzz+foqIiNmzYwAsvvMCBAwfIy8vjN7/5DbfcckuD7t3999/P1q1bGTduHB6Ph5tvvplLL7004f5NmTKF66+/nlNPPZXq6mq2bdtG586dWbZsGffeey9jx44lEAjQqVMnzjvvvBoWI4nkZEaGg2+BmEtmt9Tw6/D7d9ZZx+lsExUbKd6eeFN64vF0w2ZLqbNOS0WG65Y0JfLzJTmRkOHgJRhG0IzTkeTXUV1dSF0h0B2OrMTpFW8PUjw9sNulCJRIJBJJ0yDFyEmAEDrV1YWWA2lseqWqahtChGutY7O1rjG9kpLS45DvXJFIJBKJpCmQYuQEQgiB378bX+WGOL+OH6mq2lxnRFJN8+K1hEZkeiUlpScOR9YJv2RWIpFIJCcHUowcp+h6FT7fJny+9fh8G6nwrcfn21BnrA5VdVlWDlN0RCweTmeeFB0SiUQiOa6RYqSZMa0dO/H5NlDh24DP2qqrd1BbKHRFsZuRSFN6RqdXvN6euFztURTpfS+RSCSSEw8pRo4h4XAllZUbE0SHz7exTmuHw5GN13tKdEv19sbj6SJjdUgkEonkpEKKkSZACAO/f6c1tbLRmmrZYK1iqYmiOEhJ6Y7X24tUb29LfPTC4agZJEoikUgkkpMNKUaOknC4Al/lJnwVG/BVbsBXsR5f5SZ0vbLW8k5HLl5vL0tw9Mbr7YXH0xVVrd/r0iUSiUQiOdmQYqSeCGFYy2djlo4K3wb8/p9qLa+qDsuJ9JS4qZZeOByZx3jkEolEIpEc30gxUgvhcIUlOjZEp1oqKzei61W1lnc621jWjt54U3rhTe2Nx90FVZW3V3JiM2rUKAYMGMC8efOaeyhRtm/fTpcuXfjmm28YMGBAcw9HIpE0Ai36aRkJFmY6lK6PCpC6wqKb1o6eSU6lp2C3px/jkUskJw9vvvkms2fPZtOmTWRnZzN58mSmTp3a3MNqdI5HYSeRHC+0aDHyZcEFVFVtrvWcae3oHRUcXu8puN2dpbVDImlEPvjgA6655hqeeOIJxo4dy/r165k0aRJut5vJkyc39/DqRSgUwm6XPl8SydHQogNTeDydUFUnqal9aZt3FT17/J7TB77KWWeu4mcjljGg/3N07zaF3NyLSEnpLoWI5IgQQhAMBptla8h7MCsrK5kwYQJer5e8vDzmzp1bo0wgEGDKlCm0a9eOlJQUhg4dypIlSxLKLFu2jFGjRuHxeEhPT2fcuHGUlpbW2udLL73EpZdeyq233krXrl258MILmTZtGo899liDxr506VLy8/NxOp3k5eVx3333EQ7HXoXw1ltv0bdvX9xuN5mZmYwZM4bKStPJfMmSJeTn55OSkkLr1q0ZMWIEO3bsqLWf7du3oygKb7zxBiNHjsTlcvHKK69w4MABxo8fT7t27fB4PPTt25fXXnstWm/ixIksXbqU+fPnoygKiqKwfft2AL7//nvOP/98vF4vubm5XHfddezfv7/e1y6RnAy06Kfrqb3nYLOloihacw9FchITCoWYPXt2s/Q9ffp0HI76xaWZOnUqS5cu5d133yUnJ4fp06ezevXqBL+MyZMns27dOl5//XXatm3LO++8w3nnncfatWvp0aMHa9asYfTo0dx4443Mnz8fm83G4sWL0XW91j4DgQAejychz+12s3PnTnbs2EHnzp0PO+5du3ZxwQUXMHHiRF588UU2bNjApEmTcLlczJo1iz179jB+/HjmzJnDZZddRkVFBZ9//jlCCMLhMJdeeimTJk3itddeIxgMsnLlysNGLb7vvvuYO3cuAwcOxOVy4ff7GTRoEPfeey+tWrXivffe47rrrqNbt27k5+czf/58Nm3aRJ8+fXjooYcAyM7O5uDBg5xzzjn86le/4s9//jPV1dXce++9XHXVVXz66aeHvXaJ5GShRYsRu711cw9BIjku8Pl8/P3vf+fll19m9OjRALzwwgu0b98+WqawsJAFCxZQWFhI27ZtAZgyZQoffvghCxYsYPbs2cyZM4fBgwfz9NNPR+uddtppdfY7btw4fve73zFx4kTOPvtsNm/eHLXI7Nmzp15i5Omnn6ZDhw48+eSTKIrCKaecwu7du7n33nuZOXMme/bsIRwOc/nll9OpUycA+vbtC0BJSQllZWVcdNFFdOvWDYDevXsfts8777yTyy+/PCFvypQp0fRvf/tbPvroI958803y8/NJS0vD4XDg8Xho06ZNtNyTTz7JwIEDE8Tq888/T4cOHdi0aRM9e/Y87FgkkpOBFi1GJJJjgd1uZ/r06c3Wd33YsmULwWCQoUOHRvMyMjLo1atX9Hjt2rXoul7jARkIBMjMNJesr1mzhiuvvLLe45s0aRJbtmzhoosuIhQK0apVK+644w5mzZqFqtZvFnn9+vUMHz48wZoxYsQIfD4fO3fupH///owePZq+ffsybtw4xo4dyxVXXEF6ejoZGRlMnDiRcePGce655zJmzBiuuuoq8vLyDtnn4MGDE451XWf27Nm8+eab7Nq1i2AwWKvVJ5lvv/2WxYsX4/V6a5zbsmWLFCOSFoMUIxJJE6MoSr2nSo5nfD4fmqaxatUqNC1xajPyMHW73Q1qU1EUHnvsMWbPns3evXvJzs5m0aJFAHTt2rVRxq1pGgsXLmT58uV8/PHHPPHEE8yYMYOCggK6dOnCggULuP322/nwww954403uP/++1m4cCHDhg2rs82UlJSE48cff5z58+czb948+vbtS0pKCnfeeSfBYO1v047g8/m4+OKLeeyxx2qcO5wgkkhOJlq0A6tEIjHp1q0bdrudgoKCaF5paSmbNm2KHg8cOBBd19m3bx/du3dP2CJTD/369YuKiYagaRrt2rXD4XDw2muvMXz4cLKzs+tVt3fv3qxYsSLB4XXZsmWkpqZGp5kURWHEiBE8+OCDfPPNNzgcDt55552Ea5s2bRrLly+nT58+vPrqqw0a/7Jly7jkkku49tpr6d+/P127dk24dwAOh6OG78zpp5/ODz/8QOfOnWvc02TBI5GczEgxIpFI8Hq93HTTTUydOpVPP/2U77//nokTJyZMlfTs2ZNrrrmGCRMm8Pbbb7Nt2zZWrlzJo48+ynvvvQfAtGnT+Oqrr7jtttv47rvv2LBhA3/961/rXB2yf/9+nnnmGTZs2MCaNWu44447+Oc//9mgWBy33XYbP/30E7/97W/ZsGED7777Lg888AB33XUXqqpSUFDA7Nmz+frrryksLOTtt9+muLiY3r17s23bNqZNm8aKFSvYsWMHH3/8MT/++GO9/Ebi6dGjR9T6sn79em655RaKiooSynTu3JmCggK2b9/O/v37MQyD3/zmN5SUlDB+/Hi++uortmzZwkcffcQNN9xQp9OvRHJSIk4AysrKBCDKysqaeygSyWGprq4W69atE9XV1c09lAZRUVEhrr32WuHxeERubq6YM2eOGDlypLjjjjuiZYLBoJg5c6bo3LmzsNvtIi8vT1x22WXiu+++i5ZZsmSJOOOMM4TT6RStW7cW48aNE6WlpbX2WVxcLIYNGyZSUlKEx+MRo0ePFl9++eUhx7lt2zYBiG+++SahzyFDhgiHwyHatGkj7r33XhEKhYQQQqxbt06MGzdOZGdnC6fTKXr27CmeeOIJIYQQe/fuFZdeeqnIy8sTDodDdOrUScycOVPoul7vvoUQ4sCBA+KSSy4RXq9X5OTkiPvvv19MmDBBXHLJJdEyGzduFMOGDRNut1sAYtu2bUIIITZt2iQuu+wy0bp1a+F2u8Upp5wi7rzzTmEYRq1jOFE/X5KWSX2f34oQDVjM30yUl5eTlpZGWVkZrVq1au7hSCSHxO/3s23bNrp06YLL5Wru4UhOMuTnS3IiUd/nt5ymkUgkEolE0qxIMSKRSCQSiaRZkWJEIpFIJBJJs9Ki44wcOHAAwzBwOBzY7XYcDgeaph02FLREIpFIJJLGo0WLkff++zeK9u3GMLToJoQNm82NzebE4XBGRUpj7O12uxQ6EolEIpEk0aLFSFqrd2jXofb4B0IoGIaKYdhiYkU396GQhj9gq3k+ftNrz1dVJ6rqQtMimxu73YPN5sJuT8FudzZI3MRv0qojkUgkkhORFi1GRDkEbTZUzUDVBKo9tspZUQSapqNpxzbwkGEoGIaNUFgjEKxF5BxC6BjChqo4UBQHiupEVRyW8HGiai5slvgxLT9ubHYPdpsbh8OLw+GqVeAkbzabTQoeiUQikTQqLVqMdNn6J2zfhzCEQBcGujAw1AC6EkBX/RhqwDxW/QglgK75QQuCPQi2IGgBhBZEaEFQAxhKEKEGEUoQoYQQShDUMGg6is1A0QxrL1Aje0sIRVBVgaqGgNAxuQehsLn5KhV0XUMYGobQomndiOxNS5AQNhB2UOwoOEBxmAJIdaKqlvhRnWiaG01zYbO50Wwu7DY3NpsHuz2yubHbU3A4PNjtjgSxI0WPRCKRtCxatBhpk5NC6KeKpNy4IEIC0K2tERFgrmPSQKgCoRjoWgBDC6KrESHkN0WR4rc2M21gHRNAJ4BBAEMNIWxhhBZCaDpopgBC01E0HTQDRdNRNANV01FUwxJBRnRMiiKw2cJAuHEvFtB1cyNQ+3lzuqumpUcImyl+sEc3RbGblh8cqKopgjTVhao6olNfqubCZnNhs3mwaa44AWSKIIcjxbIGeXA43Nhstnq/IbalMWrUKAYMGNCg8OwSiUTSUFq0GEm/pBtGdRgRMhC6AWGBCBvWJhC6gQgZoBsYIQM9oBOuDptbQEcP6BhBHSMUK4cuUARoiqk31Og+9itfATDMTUEBNDQ8wKFfN97YCAyEGkZXq9G1ILrqJ6z4MZSAmRcRQ6p5ztwH0bUAuhbC0IIIzRJBatgSQWFQTUGkaDqKqltCSEdVDRRVNwVRnNFDVQ1U1aAxrEG69c8QqmdTpm9QvPjREMKeIIIUxY6CJYIUB4rqsHx/zL1mTYXF/IDS0LTe+P1lQABFUVEUBUXRrLQazQOlxVuA3nzzTWbPns2mTZvIzs5m8uTJTJ06tbmHJZFIjiEtWow42qc2SbuhgE5lWYCqsmB0X1Xmp6o0SHVZAH9FkEB5kHB1OCpUVGoKGPNYQVXMtNNlw+lUcTg0HHYVm6Zi0xRsmoKmWOWwxI4eE1WEDUtYmQIL3ZwWUlBRDAeq4cDe+AaROhEIUHSEGjKtOmoIoZnpkFpNSKkiqPoJqwHCajVhNYih+glrQQw1iKGGMDSrnhqyBFAYoYVRItNiapwQigggVUdVdUv4mJi+QWE0LUydpptDYBjmFoq7f6raltZpDxAOFxEM1kdoKKa1TJjipNZNUSzhqgARIZO4VxQVU9wkCh4zX7WsP/EiSI2231yC6IMPPuCaa67hiSeeYOzYsaxfv55JkybhdruZPHlys4xJIpEce1q0GGkq7E6N1jkeWucc2tKhhwwqyxNFS/y+sixIVVmAal/InNvxB+s9BqfHhjvVgTvVjjvDZe4jx147brcNl8eGy2XH4VJRDEzREm8ZChsxIRNnNUqwINWwKFkCyLIqCT2+XqLFSeh21FDiq5GOxZs2YhahIGHNFD0hNYCuBQirAcv6EyRsCSLTbyhk+RCFMNQgwhI/RMWQZQ1SdWyODFqlqtb0k4qiCKzJOStdc0QKQK3n6rgGkbg/ehQqK6v43V2P8N//+wSvN4XJv72RsF5FMFhKefmPgEIgEOThh//MW2/9H2Vl5Zx6ai8eemg6Z501IiqMvvzyK2bNepSvv/4Gp9PB4MGDeOWVBWRkZEbLRATQiy++yKWXXsItt9wMKHTt2pVp06bx2GOP8Zvf/KbFW40kkpaCFCPNiGZXaZXpplWm+5DldN2gujxEVXmAyoMBqsqDVFeEqK4ImpvPTFdVhPD7QghDEKgKE6gKc7DokE2bKOBKscSK19x7Uu24rL071YG7lcMSMw6cbhuK2jgPCSEE6PHiRkCoNgGUKJKEbljlEqfWIuLJCIbRA2GMUBgjqCNCOkZIt9pSEboNVbfhMNw4wwoYoIrG8RsJpypUZKXgqsrDFXQghMAQfvN6sSxDCIQiTGFk7VGEZTVKOrbKknAu0hrR/OixlVYUTL+aiHHlMILo97+fy/JlX/Pqq/PJzs7goYf+wnffrqNf356AOf4pU2axceNWnn/+f2nTJof//ncRl112LStW/Itu3Trx3XcbuOCCa7n22kt59NHfYbNpfP75V1RWbsflKqvRa2VlMR6Pm4qKH6wcBShh586dfP/9J3Tq1J5kK1HEslOblSdmKappNYq3HMWXrbtNKYQkkmNFixYjft001ytx0yEqHHdfQpqm4k134k13QqdDl40IkaqKIH5fkKryUIJgMbdQdO+vMq0ufp8pZErrMR5FVaKiJWpxST6OSztcdcc/URQFbAqKrfkdSKPCSE+yDMWLoJBOuDpI2B8gVB1A9wfRA0F0fwg9GMIIhgmpBsImMDQD3aaj69UUbPxZs1zTGd1XoKqm2BWWGBHEix5T6FRUlvPSS//m2SeeZNSQixGK4K9/OoVTTx+MCLswqlvz066dvPLKu3z3zTLy2uQgFMFtt/Zi4cIvefHF//L7++9m3rwXGTCgD3PmPGj5BQl69uqFAhiGiOaBKYpGjx7B9OlzWLLk55x1Vj5btxby5JMvAFBUVESnTm1qXFO8Najp3zlen2mzOGGjKCjRffLUmQKKak6PKvF11Rpt1pxCkwJJcnLTosXIFWs283V5Va3nFEzfDeu3kpVWLOES8euwvjqU+DIxHxDi0pH68WUiv8ui5ZPbiUsnCqZYfsRXJPmcap1TPKB6FNQ2ppOsqnii/WuK+SPaCJkOukbQQA/q6EEDI6gTDphOu0ZAJ2xtRtBAEaaTrkIINRxCKalCOWCNM3IubtPUiL+LZm02nC4Nl8uG02nD5TbTLrfNnD5y23G5Neyaal6DAhqmX4wWd92xY3OvKYrpM2Pla1Z+fb/AE4SR80g+USaRV7y7slNxuVzougM2Hnl7R4Nfr0QTBhFX6fgHWuTBpwI7tv5EMBhkeL9hOMIuQCEvNYWe3XpgMxx4Qq3ZsvZLdF0nf9johD4CwQA5rdrgrW7DD9/9yC8uvBRvVbvo+Zg1KCKEiObcePkdbN9YytVX3U4oHCI1NZVbb/oV/zv3jxBIx6jKJMEylJAm9iEjYjkiLh2zHEWtQYo1JWaVPbS1KK6tWrLjc5teFEVQCAYFfn8xK76cihAllnO1HUV1oCh207FasZtO1prlZK1Zm+pEs5lpm+ZCs0UcsR1WXCJrlVqkHdWBotqtc2abSrT9SFntWF285CSmRYuRQ31/CKJ+nsS+eY7ZN07zomA+jKMPZNXa7I3UgbWUKLJ6JhJWJXmVdSOSLE40EoVcRMzUOE46p6Fgs8SOGid61IgYUiBTGFwmwjj8QexCQQiV7vlfgyVmwXpmEvutjQLxEiGhTJyWikmKWJ2a5WNtaKrbEh8CDGE+NYWBEMK0BAmBEAa613ygBFMgkKIjDLOcoQhCShCfWs6BqmI0TeOT//6f6QwrsJ7CCt4UDxWhUpxOO0HDT2W4LGG0yQIoPv/h+2by4NQZFBUXk52RxeLlnwHQs10vXKGU6DXF35uGEC9+Iqn4vAR7kZIoeOItSCSdI/5cvPipZcrMvIZafIfqEEex/NquRmD+/ZQhRFHsq8motUKTI4SCotgx3ecjq89sKGpkBZod1RJLatxmiiMHqhYnjjRzib6qxpW3hE9MFEXEkj0p7YwTUZEwADJe0YlCixYjbw3oji4EBqaJ3sD8vjasL4RIWgjr8SliX16Rc4aIHIvEvVVG1FI/vl2zrLDyzHGIuLpGLeV1q0xs7OZ5XZh9RPoy4vqN3+sicdx6cpkG1hNx5xLbEOiGIBQ2CIUFumEQ1s28sG4QNgS6ENaKaGEFn7OuVQFDURCK1Z9CYp5i5dXTd0UXoB8jUdleFYxrpVIRNlfwmByFqeWoOJzTswJoqF16YLPb+WD1t4zt1A2A8tJSfty6lb5nnsVP3nSyh45A13U2BMMMOmNEtDaYd3Qv0KX/AD5ZuZIbMjOIPnjj77mwHriRvKgnrg1ataMIwQvv/YuBg4dQ3TaNwsj4RezhHH2OR9q38uKFWnzZRPkTv8UEkhLdqzGLZ8QCKZSowUVBiWszkhe7k4eidgEUv08SSkosJ14U6eEgRqCKsrWXEAgcRChhDDUEamwvLIdqoVjO1WoIFB1U08laUczl9KpixR1qQF78ajSICKvI56w6+j3V2PGZjgwF8zGnWYIpIlAiAskUTKaYscct2bdHLUmq5ohalhKFUS0iqUa+Pc6SZI8Kp1if0rIUoUWLEbfW/H4KkpoYhiBQFSJQGcZfGYptvhCBqrDp31JlHvsrg/grw1RVhQgG9TihosQEC3UImbg8RVOweWzY3BoOjw2b24bmtmFzamhODc2lojk0FKeG5lBRHBqqXUV1qGBToqJRR2ALhUgvP0COw4bNaVqTYg+buEdQ7PmcuBeiZp71v5oPstrOxT3URHLfsT7i81JSvVw24Xr+PHMGrTMyyMjO5smHH0wIBtepew8uuOpqZtw8ibv/8Cin9OtPyYH9rFyymB59+nLWuPO44a4pXDE8nwd+dydX3ngTdoeDrz77jHMvu4z0zKwaT+7SA/v55N//ZvCZZxLw+3n3lZf48D//4bn3P8LvSqnnJ+Z4QsRmiuLSscuuxfJFbeIpUjomtiJl9WCAapuLr3NH4vODZghrM20TmsBMG6AJYR4nbAKEgSqENa1qoFjHCGsaFsNKGyB0EEnHhBFqCIUgKCFQAiiEUdQgKEEUJWwtvQ9jWGJIaKYYQo0TSUoYlMiyewNVsWIRRfaqYQmimDBKPo4IpVh+4r9HxPQqIk7k1r08LrQSEBFMCnZQbFGxFLHsqJbYUdSY1ceceotYmBymhakuAaTGhFeyaEoQT4odj6cTmnZs411FaNFiRHJ8oqoKbq8Dt9fRoHp62IgKl2QhE6gM4bfyAnHixl8ZRg9bv/RKagZbqU8AXkUBh8eG023D6bHjydDQTtdwVOo4wzqqqqCoCqoKiqqgqKqZp5n5SgP8WpqS5+f9mV//+tfc+T9Xkpqayu/uuguj0kem3cZpXjcCwZsvvsCjf/gDf/n9dHbv2kVmVhb5Q4dy3WWX0iPFSff+ffjPBx8w6/77ue6ckbjdbgbl53PLhGtJc5v/nvGiyON08NEbrzLv99MRQjBo6DD+vfATTh+SX1PA1RBc1j5JvCWLs5itIVEAJrYpks6ZhWv2d7h/J8teoySnGw9hKFRpCh/m2thpNP/npjYUIVAF2JJEkCbAZsTy1ASxZNYx93GbAaouUOMEVOSckpBniiUFA0XoqIQB3RQrhFEw8xR0FCWEqljHio6qhFAJoxJCUcLRtKaEsaGbeyWEpujYCKOqYWyE0dRIfhi7EkJTQthUM61aoqqmsEqeTzMFkyCUYCxsDnr0eI6OHc5ulr4VIZrz0utHeXk5aWlplJWV0apVq+YejuQkIxTUawiUiIgJVocJVIcJVpn7QFXYzKsyrTSGXvPPx5Wm0vfiNNrldcBuq5+gMsWKJU4iwkVREvJjYiax7PEiZloKNcRPVMTUzBfCMKcyDXMaUlg+OrF0bDPziOURORcTSwJBOBhiz66dvLz6W/ZVVWEoKoaiIlQVQ41LK/HHCrqqIRTFytOsMuaxiCtrRNupo4yqJRxL6kYzYsKphsgSAhUjbm+gYlmpMFDRUaL5OqrQrfxw9LwmTLGloZvH8ZuioxFO2pvCSiOMTdHRlBAaOjYljKaEOb/zRAb1alwxUt/nd4u2jPiWLkU/eBDFbgebDcVuR7HZzb09cmyLO++oka/YbOY5+TA4YbE7NOwODW96w0KuCSHQQ0aSSAlTVV1F0HYQdysHDpsDwxCWlVtYaRFNR9syTF+aIyVBoChxx4qCEhExcWlViYiZmOiRoqZ+xDsImxk1EnE0/sPa7/cTrijnLzdMwOGwEw4GCQcChAIBQgG/mQ7GpePPBQOEA9WEg0FC/kD0fDgYMPOsdCwvQMgfQIjavWPNKVAlKmJEbYImIoDUmqLJULWoWEoQT5oGdgeKw2l979rBbgfr+xmbuQnNZu5tNjOtaQjNhtA0DE1DqFpsTIr5CDdQEYpiPepBR0EXEBamD1s4Ka0Ttyd+b27hQ/zJ6KrZz4nCsOrWzdZ3ixYje1/dhMOZDcIPho6IzI0aOggdYRjWXKlu5RlmGUOP5otIOs7JLDJJLBTThC9UAdYXfmSdr6IpoKrmXlNRbSrYNFRNRbFpKDYN1WEz93Ybik1FsdvAplmCyIZi11DtGkSPbSgOG2pUJMUJK5stJpwiYio+Tz6EGoyiKNgcGjaHRkpazEHV709h2zYfnlQHLlfdAkdYnn5RgSIEhiVa4oVLnWIm6il49GIm/priRYqaLFji8w8hdJDC5pigqhoOlxuH69CBE48GIQSGHrYESjAqdsIR4RKsh6iJqxMKxrfjt9ox6xj6MXwvRRyKomJzOKzNGUs7ndgjefak805n9Fh1OFAcDhS709zbzGNTQEX2lnBSNYSime/QCltO/bpupsOCsGGYDv7hmKN/WDfzzUUAWGlhnhPmXo+kI8cRMSUEYczFAeE4YWV6/sSlFYU2HZvmFSn1oUWLEb8zA5cns7mHkYgBBEEEQa89BMphCCNEME4wJYkmoYMREVUx5zRhbWAt+zTX6WDECS0BGFb0TwOsyKE1nUENRTHTqoKhKtb5SNraq2p0LxQFXVOi5l9DU9CtX0+6qmFoKroWv9fQrS1sUzE0DUOzWZv5a4gmNB/XeMQmZXg0g6FZOvsq/NgDdQuEej2qVcXc6qxh+TpEzfuYvg4RkWIJlmg+sbKR/MSZWhH3Escjx3SZiLO2WMJcsfIOe87cxZWr0XrN/pIODu/dUWPAdZ+vpXJt52u0cJix1NJt7aOI6y8Q0gnpBjsOVGJzhK17FbtnkXhIEHdfk85F+lWj56y4R/H/Hla+GdNIRXG4sTncOFKVhPNKXD9Hix4Om0IlapXxW8dmXigUjAqZiPCJlTfToWDd55LPR/5QhDAIBfyEAv6jvob6omq2OAHkQIuIHbvdEj92PA4nWuTYEcu3JeQn1rE5nGhRARUra3c40Rx2VLXm6h1hCHPJodZ8PyBatBiZ7nETwIcNK+4E0UVgcelIfqyMXQhsQuAQAntkw9zbiByDLXKMgiYEtrg24/uJ7FVFsdKKFQjN2ivWgkNFQY28AA2l1g8VmCqfpJVCx+Vv1Ei4ETiKF/YKTH0ftgRXTGRFBVac2BLRGBsGhiW8DGFYy6utDRE7tvamSVZEl1DrivmLQ7eEmS5Mc60OqK1daJf2xlZehaaFoqOMbkrMGVLUOBefp0TLG/FllcR6xO0bTPxSjkYn2SNU0hiIcJB95QFmvfsVuyqOnzUhEBMxakREWioqMS8mPJPTkTJYoikh2KQldlQVIoHe1CQxFC2vguJWUNyR8kqCMFOj6YgiNyLKPJY2zB9ilrkyzlJupSObZUUXRmxvntNjebpuWd8jq5Vif/2KAEUXKLoAv5UvIud10+GWahQR+9aILmsXceno6i0RTcf6iJVRFRXNpqJpNjRNQ7Np2DQNzWbjV9ddQq/ePZv+g1ILLVqM5PbOYUdJJSEgGP0laf5SVIT1C1EAhkCJBdgwf1FGjqO/MkXssxzniEZ8M1HrQmzJaeR5bD5wRKysEilvxfpQav/S0ZK2eNEUETq2pDJ2IXAYBg5hWGLKsISVtY8IqwSxFRNX5qZYx5awEmaeplie8Uqi2IqIK1N0qdZslRXTISq8Et80q0RDZ1ub6cFpiq1aUFTrCi2N1lwCLJyqUKHa8WpOXPV0YG08YlaRRAUQJwziHC3jz9WmF+LPCCU5Pz6t1DgvktLJq1VEfN2kcollYqIs9tVbez+17Q9L3LgjD8Lk/Ni5Q2UkUnv/Sfde1JpMzEs6Yajm35nXaaNVSImWMe+diLuHsdhEJB3Hl2tMIu0bosH/CicACrFv0cYretxgwNjSano1U/ctWoz86pJTKAubD/kEk6N1PsG0GXdM/Pk4s2dC3bi2FEy/AD1oEAqG0YNGdAsHdcIhHT1goId0QgGdsBWWPRywzgd19KBOwK8TCppbOGiYX87RLxfry4a4L2gBQjEDkIEVzE3Exd6IfHFY5f2KoBqrTuS8AqqmoGhmPA1VVa0/MgVVs9KqgtCsh5EChhprw7CmcsIiJqziA5zpwsAQENbNOdBoEDTLJ0I3dHShm3UMKwCcNThVWL+mBDgj4sowcArDElZGVExF0xg4jHgLVkR0JYotuwAbIibyRLzgixdalkVLRCK2ghp24TZOIawHCREXrCvJJq/E/Z/Ir8ikvFhunN39kChxRWope5hpgyalvp02+uDqEGjx6ii6q+U8tT9SE86KWsopyTc7ZiWIMwtYRWPHsekpxXrdjTlvEvHN8YdA8Th486LTcLncph+ZGvFJMzdFAbRIG1Ze7OVbsbJK7FIjIiU+WGPkXDTgY2Rv1BQ3kXqR2xFdHRSpF/mxFlcvUoZa8iL9xsZn9SEi32lWQElRc9zJ5eP7TW7DOER5w0gafy3lESJpDLHyCcEwRXx+0j0VsWCRsWuI9RVdfRXXliFq74eEtoiu5tJ1Hd0wMHTT98QwDAxdN59NhoGuG7Rrl1fLJ/3Y0KLFyEM/rGdVsLFCnDcCduqIuH4cS2whEgIyYQmE2vNENC8+cna8aIt8P8e9JizufT6m5UeJ+x5VI6ZZ60s1rCjoSrwZNmYGjrheKAqJTw3rCyX+SxHrj5/4L6cEC1hi2nRANevlaILb3XbsXgeqw2kJw8THWW2/SOtaZR+frcStaoiZZGPHCfedeJNvJE/UKBc178b9e8TOWXVEcl7NNLXWjU8rtdeLk2HxR8nB32Mm/9pKJ153InUINCW51DFGcAjDQc2TkRwjHMKoDFH63y3YKupsoP7DiExLRH+WJG8QH74+cW/9PSnCElgiJqisP1JFtaZYIsIqQRwliShVSXDsV1Rrr6mxfNVy8o+U0bRoGTPfXAwQv1dsmmlZjSwgSBgHRL4gIuOOF2uxdC2CTtJotGgx0mv/agxSicywCeuXKJCQF01HzsXlkVQmWjepXsSEHZvJO3zbwvryFYcYk6EodbYZOWfmN5FDpxJ/bYct3AQDSOo1apduROI9/upBUBWEVYVQ5EtU0kwkfzbMXW3/ikqSEEwQONFTMTFdW1tKXLH4ySSl1vN19JW8FzXPhVUot8EbHQwqAsIU7CiWgFfijpXEc8K0IkbSConWxcg+WjZaR9TMS6pj5sWErpqQn5SnC9RwXH91jsGwjvWa5xPqiDrGnZRH4xNdgUkkam2yqKslT7HKxh1H0krEc9zKi77PSBFxos+arFQxy0RuRqSMaonHiFA0Z7fN85G0GjtHZEWcBu4xY7F17NIEd+rwtGgx8if7FijeYB2JxJ+gIu6XyeHS8fOj9UpT/7br6qfWMvHniB3HnRNE3F7i5uGjxwIjKmxErAxJDpRYAkkIc5VM9FzMtUoIgWEJoKQ/NbOOoRDCQVjYCeMgJKy0cBDCjo7dzMNulYnbY+brhp2wYubrRM7Z0K1yOpF8GwI15jhq7YUSLwDj84nmY5UTdZSLHcfeo5PuUXAPcJPiN1D1+PgM1hcESf9WcU+cQ51LzE/4R67RRy25MSLXnXBeSSqrRK+T2s7Vlk4Q3HW1HZdOEP/RwSVd1dE8Qmo3fdR61xphJcixQig6lXaVDzulHrcRWI9XVMuSq0bE06HES22iK26vJIm0WkVVnFiqW+xFzh1C9CXk1S4iawjBSLnDXIcqLHEYhvOXf0M/KUaagQvmHPMuk03x8e5s8edquhjGC6Va2q3DHFBnfq1TAqLWEE0NCdLbsP6akLgJbzN+h0E4ZKAHdMLhiK+O5bsTMtPhoG6u7Q/q6CHD9OUJC/SwgR4yovtwWMSOwwZ6iFgZXWB3KzjCTtwBA7ten9UOdf1ObnziVypYeiNhCW2kTCR90eUX0LdPPx77w2OWcUiJGoniy9VckkuCQanOfuP2NRGJvw+s/fbtO+jW61S+XrmcAf37J+ru+L8nataNppM1e420qFE+KhMjc/1x+fG+ErH8uIiscf3Fl43mJY2nRp9xo9LDQSr0MMNKd7M/GLZeWBl7OWfCPiEd96MhKsQjIesjv9UVKy9iWSV6HNvH/fBQqP1cQvux/OQ+Yz8KYj5nCRbnuA9HNB0pE/8hqieG9aGMeQpK4um8P4V+zdR3ixYjN3x4A98Vfwckf/kkPTgTvhBrL3cokSE5SVAxX757mBfw5jnyuNdxL6UeO6r9xJ6mCeDHRzk/scPMSDLcNAYf/vtD/jbvb+zYuoP0zHTG3zSeGyffWGf5Xb7dAGz37cZdntbwDpVkb5R6VImv0YDKDe2pzvJx2bqiYyg+ytQ3KbcdSKgXifURmZqJVo84yqIghDm1Y9o+6zAX1XYsiNaF2HdepM1IXvxx/OclIsKixyLp+zM+T9TMi/pyRdtNFKuxm2SOUCTlmZlK3L1UiL+xUaudYpkElZrnI23GhJUabavW81FhlXQcN66IYIvmR8SWiLkOJLaT2E8sLzLeuDYS2gai1urYL4n4euWdz6e5aNFiJGSECBqHe8W6RCJpKj7/5HPu+/V9THt0GmeMOoOtm7Yy665ZuFwufvmrX9ZR6xA/HOqDOMqfCs38O8MwDMJGmKLKIvYE9zTvYBqTxGe/5AioIcCIrQVV4sRVROxEy1oiJS085FgON4EWLUbOX5nH4C2xMKe1RRBMyKvDJFhXGSWx0CH6URIKJ56Pr1d7e2apun+51dpfXedrXOIhyiadrvGrLnmMhzGp1mw7+RprVKitkQbVOfy9qdlFrd+YcVmO1Fa06uQiK5CCQ7clPLvq/1176D6agsqqKqZOm857H3xIijeF39xyCw7DRoruoE3AfMFVIBDgD3Me5+1/v0t5eTmn9OrFzOnT+NkZw6PtFHz1FX947HG+WbMGh9PB6QMG8LennqR169Y1+lz4+oecP24st4+fBMDgNqdR9pv9PPmXZ7jzmltQFKWG1dHvTwEgPeAhpyoVASz/8ksenD2bdevX0zotjauuuIJpd0/BZtMQwP+9/z5z589n+/btuN1u+px2Gv949m+keDws+3IFDz/6v2z8cRN2m41ePXvy1Lz5tG/Xjrr+HRK/9GOIhGwlMb+WczV0TVyTyb43kcNwWMcV8jFo61gO+irjpjySpkciaTVuuiXufGSaBEVFqLE2ok7p1pRGtGz0WI1rI7ZHUWPTLsn1EvLVhKkWoajmlFZ0uiZuDBHLQdSAkzyG+Lw460TSNFT8VFDydFF8ncg0W7wFIt6qUeM4znKRHAcnOh2VYBkxjw0l7jMQX66W/ogbZ/Q+1ugnZuk4GiqdvqNu40hp0WJECRvoQWkZaSnEfzEkbIfIo55liUt7VRcdhcBvvTtCCIFfxM1zJxDnsKnUkhfNVxJ8CMz8ZGfPuPpWWy4lIrjivgzreFjO+sPv+eLLAp564QUys7L40+zZfPv993Tv25cDdvMdO/ffO53Nmzbyx2f/Rk6bNix8/32uum4C/1m6lM5du7Fu7ff8z//8ksvH/5Kps/8XzW5j5RdfsM/mIuhMqXFNFbqOy+Nln8sbHU8otTW79+zhmwMHadexI8k3bX/KQQBKPKkUpbamaPdufnnDDfx8/C958Nm/s+3HTTx4x28Jt0rjtvumU7x3L7++/XbufPBhzrnoYqp8PlavWM6+tHQcLjfX33orl0+YyMMvvEQoFOT7Vas4kJ6FIzOn1rvb3IhggEq3h4U/Gy0dWCWNSl5qerP13aLFyM/vnoEeisQhj5uXBKKv9cZ0ADNDgZv5uogFBQtbc6GRMiJSPlpXJDmTxfJ16+ESCztuOlYJzPDi0f4x24vkR94WYwbOievXGlOkLSMhj2hY88gYjfjxRvKJC6ADCQ5xZp6o4SAXbZ+4QDuRc5FrqaXt+D6S60Ty9KRjI6muELXk1VY/+i/c9LRXBcM8KmWtMlAcTvy6wSVrNh+j3hN5d0B3XPVYXlzl8/HP117jD8/+nQFjLwBg1rPPM+7UnoRtdqpdKez56Sfefv01PvhhIzl5ZnCka045jc+WLOHNN9/i9gce5Nm/Ps2pA0/nvvlPRtvu2G8gALXJ/qFjxvHH6fdy0bLlDDlrJD9t3cI//vo0AHv3HyC3a/cadXTVbu01dM3GawueJ7dde+6bOw9FUeh0Sm+K9hYxf9bvufm+Gezbt49wOMw5P7+Uth07AtC9T18AykpK8JWVcdZ559OhazcAuvbqXZ9bWy8SpULt9pTDHSfnGZiB+fJEGJuIzW5EvQNEfJyemEdAJCZNZFmvImJ5xOVF4wFFz5l/TGpcPiJujyAabyhuf/g86480kmdYv/8tAV+jXCQCGFgRsc1z8WUxrHTkug0rHR1n3D4+Ro+wXHKj15R8H2L5sfsYdz8i97NGvcTz8bGWEu59dCwi4b7H4v6IxH7i6whQMGLXnXCtgLVEOjauxHsRX6/b7dfW8uk7NhyRGHnqqad4/PHH2bt3L/379+eJJ54gPz+/zvL//Oc/+f3vf8/27dvp0aMHjz32GBdccMERD7qxuHFHCavLq+JERuKDXCLRFMsZUInEOlIicZOi+Ur8eRRyVAObIrApCpqqoIvaHi/HhtZ2DbemWl9oSg1LbuRw3c5CQsEgo4YPI9thQwFy8nLo1rMnHk0l12ln7Y8b0HWdSwf1T2gjGAjQJjuLti47W79fy8W/+AXtXPa49pXE/uIMRL/79S2U/7SDO66+glAoRGqrVtw6+bf878MP0c7toIvHmVgX0NxmiP0OLgfdPE72bfmRnw0fTo8UV7Ttn599Fo9O8ZFSup+LhuVz9jmjufqMfMaMHcuYc8/l8l9cQXpGOnjbMuH66/nN5ZcweswYRo8ZwxVXXkleXp55v+LvVR33LrFM0/9b+/0amsvJP3ufcsi3QrdUIkEIDUNg6FZAQoPosWEYsbdg68lvx47VMSJ5SWUM3fqhGm1bxLUdn0fNN23Hv4HbGqfQI2lqeWN33PVY/dbVthBg6Na1idrf+h3tV092/jVJbUZrYIPFyBtvvMFdd93FM888w9ChQ5k3bx7jxo1j48aN5OTUvJDly5czfvx4Hn30US666CJeffVVLr30UlavXk2fPn0a5SKOBF95OftK9uNTjv6PObo+HGsNeFza3CenY79Y4o9rTycdi7r7aPhxfDtxQYuSxyESx1HbNdV1PQq13ZfE8kpdfYvE+vHl6zv2+tZPHk9sYuMIUG04nG1oK4I4rbDZawd0PNLWjgq37kephyk/NVQd3acFY35UmmHg0MOkBirRSw+gaRpfLF2MlvSSRq83BY+/Eo/TiT0cwu2vrPcYZ8+cwcMz7qOoqIisrCyWLF0KQLe8XLSqihrl1WqzbcVfhVJVAeEw6CGwygoAq4xRVYHir+Q/b/+TLwsKWPTpYp5+4i88cP/9LFn0CZ07d+Lpv8zjlptuZOEnn/Dma6/ywO9/z3/+/Tb5Q5rPme9QBIJBAtVVfLdsERjh5h6OJB6FhIDZCsdt7GxE5H8CK26bwNO6+cbTYDHypz/9iUmTJnHDDTcA8Mwzz/Dee+/x/PPPc99999UoP3/+fM477zymTp0KwMMPP8zChQt58skneeaZZ2rtIxAIEAgEosfl5eUNHeZhWVewmEFfb2CgokbNcxFTVrzJLtksl3xOztgmEv8i3paK1+tlxIgMfFV+/MHmfVjU92XImTltsNvtLP1iORdffDEABw8e5MfNmxmSn0+Zr4qu3Xug6zrbC3cydOjQGm2U+aro2asXiz5dzG9vv6PBY01p1ZrqYJhXXnuDQYMG4XB5KPNV1ShXUVUd3Zf5qujcpQvvv/8+Bysqo5aJT5d+jtfrxZuWHm3j1D79OLVPP277zWTy8/N5819vc8sttwDQuVt3JnXrzqRbbuXiiy/m5Vdfp1fv0xp8DceCcDhMdSDIsm/W4/M1n8Oh5ORDtSvkn3tJ8/TdkMLBYJBVq1YxZsyYWAOqypgxY1ixYkWtdVasWJFQHmDcuHF1lgd49NFHSUtLi24dOnRoyDDrTWqgmjR/Ja38VaQGqvEGqkkJ+vGEArhDQVzhEM5wCKcexqGHsRs6NmGgxVlCJJKTgZSUFP7nf/6HRx55hC+++IINGzbwu9/9znwxokW3bt24/PLLueOOO3j//fcpLCzkm2++4YknnuCTTz4BYPLkyXz77bdMmzaNdevWsXnzZl544QVKSkpq7bekpIQXX3yRzZs38/333zNz5kzee+89HnzwwXqP/frrr2f37t3cf//9bN68mY8++oi5c+dy8803o6oqq1ev5i9/+Qvffvstu3bt4v3336ekpIQePXpQWFjIo48+ytdff83OnTtZunQp27Zto3v3mr4qEomk6WiQZWT//v3ouk5ubm5Cfm5uLhs2bKi1zt69e2stv3fv3jr7mTZtGnfddVf0uLy8vNEFyalDz27U9iSSKKoNh9OB1+PC6XA092jqzeP/O5s777qbG264Aa/Xy+2Tf0NVVSVOh500rweAvz/7DI89/kceefhhdu/ZQ2ZmJkMGD+bSn19EmtfD6f378u47b/PgQw9x0UUX4Xa5GDx4MBOu+WW0jXhCgWreefttHnnkEYQQ5A8Zwgfv/R9DBg+uc5wHPW4AUj1u0rwe0np04+23/sn9v5/JueeeS3p6OhMnXMfMGdOw2Wzk5Waz6uuv+fvf/05FRQUdO3Rg9h8e5rKfX0TRvn1s376NW265hZKSEtq0yeWWmycx+de3JAix44lAMIjb6eCsgb3lNI2kUWnO56IiGhCne/fu3bRr147ly5czfHgsrsA999zD0qVLKSgoqFHH4XDwwgsvMH78+Gje008/zYMPPkhRUVG9+i0vLyctLY2ysjJatWpV3+FKJM2C3+9n27ZtdOnSRToYShod+fmSnEjU9/ndIOmflZWFpmk1RERRURFt2rSptU6bNm0aVF4ikUgkEknLokFixOFwMGjQIBYtWhTNMwyDRYsWJVhK4hk+fHhCeYCFCxfWWV4ikUgkEknLosGrae666y6uv/56Bg8eTH5+PvPmzaOysjK6umbChAm0a9eORx99FIA77riDkSNHMnfuXC688EJef/11vv76a5599tnGvRKJRCKRSCQnJA0WI1dffTXFxcXMnDmTvXv3MmDAAD788MOok2phYWGC49cZZ5zBq6++yv3338/06dPp0aMH//73v5s1xohEIpFIJJLjhwY5sDYX0oFVciIhHQwlTYn8fElOJJrEgVUikdSfE0DnS05ADKOlhxWUnIy06BflSSRNgd1uR1EUiouLyc7OPibvK5Gc/AghCAaDFBcXo6oqjhMoho1EcjikGJFIGhlN02jfvj07d+5k+/btzT0cyUmGx+OhY8eOx21QNonkSJBiRCJpArxeLz169CAUqu/bYSSSw6NpGjabTVrbJCcdUoxIJE2Epmlo2vH6zk6JRCI5fpB2PolEIpFIJM2KFCMSiUQikUiaFSlGJBKJRCKRNCsnhM9IJF5DeXl5M49EIpFIJBJJfYk8tw8Xd+mEECMVFRUAdOjQoZlHIpFIJBKJpKFUVFSQlpZW5/kTIhy8YRjs3r2b1NTURl3SVl5eTocOHfjpp59kmPkmRN7nY4e818cGeZ+PDfI+Hxua8j4LIaioqKBt27aHjI1zQlhGVFWlffv2TdZ+q1at5Af9GCDv87FD3utjg7zPxwZ5n48NTXWfD2URiSAdWCUSiUQikTQrUoxIJBKJRCJpVlq0GHE6nTzwwAM4nc7mHspJjbzPxw55r48N8j4fG+R9PjYcD/f5hHBglUgkEolEcvLSoi0jEolEIpFImh8pRiQSiUQikTQrUoxIJBKJRCJpVqQYkUgkEolE0qxIMSKRSCQSiaRZOeHFyKOPPsqQIUNITU0lJyeHSy+9lI0bNyaU8fv9/OY3vyEzMxOv18svfvELioqKEsoUFhZy4YUX4vF4yMnJYerUqYTD4YQyS5Ys4fTTT8fpdNK9e3f+8Y9/NPXlHTccq/v89ttvc+6555KdnU2rVq0YPnw4H3300TG5xuOBY/l5jrBs2TJsNhsDBgxoqss67jiW9zkQCDBjxgw6deqE0+mkc+fOPP/8801+jccDx/I+v/LKK/Tv3x+Px0NeXh433ngjBw4caPJrPF5orHt9++23M2jQIJxOZ53fCd999x1nnnkmLpeLDh06MGfOnKO/AHGCM27cOLFgwQLx/fffizVr1ogLLrhAdOzYUfh8vmiZW2+9VXTo0EEsWrRIfP3112LYsGHijDPOiJ4Ph8OiT58+YsyYMeKbb74R77//vsjKyhLTpk2Lltm6davweDzirrvuEuvWrRNPPPGE0DRNfPjhh8f0epuLY3Wf77jjDvHYY4+JlStXik2bNolp06YJu90uVq9efUyvt7k4Vvc5QmlpqejatasYO3as6N+//7G4xOOCY3mff/7zn4uhQ4eKhQsXim3btonly5eLL7744phda3NyrO7zF198IVRVFfPnzxdbt24Vn3/+uTjttNPEZZdddkyvtzlpjHsthBC//e1vxZNPPimuu+66Wr8TysrKRG5urrjmmmvE999/L1577TXhdrvF//t//++oxn/Ci5Fk9u3bJwCxdOlSIYQQBw8eFHa7Xfzzn/+Mllm/fr0AxIoVK4QQQrz//vtCVVWxd+/eaJm//vWvolWrViIQCAghhLjnnnvEaaedltDX1VdfLcaNG9fUl3Rc0lT3uTZOPfVU8eCDDzbRlRzfNPV9vvrqq8X9998vHnjggRYlRpJpqvv8wQcfiLS0NHHgwIFjeDXHL011nx9//HHRtWvXhL7+8pe/iHbt2jX1JR23HMm9jqeu74Snn35apKenJ3yX3HvvvaJXr15HNd4TfpommbKyMgAyMjIAWLVqFaFQiDFjxkTLnHLKKXTs2JEVK1YAsGLFCvr27Utubm60zLhx4ygvL+eHH36IlolvI1Im0kZLo6nuczKGYVBRURHtp6XRlPd5wYIFbN26lQceeOBYXMpxTVPd5//85z8MHjyYOXPm0K5dO3r27MmUKVOorq4+Vpd2XNFU93n48OH89NNPvP/++wghKCoq4q233uKCCy44Vpd23HEk97o+rFixgrPOOguHwxHNGzduHBs3bqS0tPT/t3d/oez9YRzAHzqN4wIrzFiKMpHkQkpTbkQuXJAIyY0yf4poxY3ihgu5UFvtgl1tLSlTLlwNWa7UyJ+J/LmgbUUtE2vY8734/XYy/H5f/84f2/Oqc2Hn0znneXccz+zzaV++3l/xrb0fFQqFYHBwEDQaDRQXFwMAgMfjAZlMBqmpqRFjFQoFeDwebszLGz28P7zv/8bc3t7Cw8MDsCzLR0mSxGfOr01PT8Pd3R00Nzf/cBXSx2fOJycnMDIyApubm8AwUfUY+DQ+cz47OwOHwwGJiYmwtLQE19fX0NvbCzc3N2AymXiuTFr4zFmj0YDZbIaWlhYIBALw9PQE9fX1oNfrea5Kmr6a9Ud4PB7Izc19c4zwPrlc/qVrjqqnUF9fH+zv74PD4RD7UqKaUDlbLBYYHx+H5eVlyMjI4PVcUsRXzs/Pz9DW1gbj4+OgVqt/9Ni/EZ/3cygUgri4ODCbzdzXqM/MzEBTUxMYDIaYehPDZ86Hh4cwMDAAY2NjUFtbC263G3Q6HWi1Wpibm/vx80ndb/xbGDUf0/T398PKygqsra2BSqXiXs/MzIRgMAg+ny9ivNfrhczMTG7M6xnF4Z//NiY5OTmmHih85xxmtVqhq6sLFhYW3nw8Fgv4zNnv98P29jb09/cDwzDAMAxMTEzA7u4uMAwDdrud3+IkhO/7WalUQnZ2NteIAAAUFhYCIsLl5SUfJUkS3zlPTk6CRqMBnU4HJSUlUFtbCwaDAebn58HtdvNYmfR8J+uP+Mxz/FO+NeNEAkKhEPb19WFWVhYeHx+/2R+etLO4uMi9dnR09O4EKa/Xy40xGo2YnJyMgUAAEf+ZwFpcXBxx7NbW1piZwCpUzoiIFosFExMT0Waz8ViRNAmR8/PzM+7t7UVsPT09WFBQgHt7exGz76OVUPez0WhElmXR7/dzY2w2G8bHx+P9/T1f5UmGUDk3NjZic3NzxLG3trYQAPDq6oqP0iTnJ7J+6W8TWIPBIPfa6Ojotyew/vpmpKenB1NSUnB9fR3dbje3vfxF12q1mJOTg3a7Hbe3t7GiogIrKiq4/eGlYzU1Nbizs4Orq6uYnp7+7tJenU6HLpcL9Xp9TC3tFSpns9mMDMOgXq+POI/P5xO0XrEIlfNrsbaaRqic/X4/qlQqbGpqwoODA9zY2MD8/Hzs6uoStF6xCJWzyWRChmHQYDDg6ekpOhwOLCsrw/LyckHrFdNPZI2IeHJygk6nE7u7u1GtVqPT6USn08mtnvH5fKhQKLCjowP39/fRarViUlISLe0FgHc3k8nEjXl4eMDe3l6Uy+WYlJSEDQ0N6Ha7I45zcXGBdXV1yLIspqWl4fDwMD4+PkaMWVtbw9LSUpTJZJiXlxdxjmgnVM5VVVXvnqezs1OgSsUl5P38Uqw1I0Lm7HK5sLq6GlmWRZVKhUNDQzHxXxFEYXOenZ3FoqIiZFkWlUoltre34+XlpRBlSsJPZf1fz+Dz83NuzO7uLlZWVmJCQgJmZ2fj1NTUt68/7t8iCCGEEEJEETUTWAkhhBDyO1EzQgghhBBRUTNCCCGEEFFRM0IIIYQQUVEzQgghhBBRUTNCCCGEEFFRM0IIIYQQUVEzQgghhBBRUTNCCCGEEFFRM0IIIYQQUVEzQgghhBBR/QFxxb4DYLlPagAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "model.run(params=country_level_fit_params,\n",
    "          return_timestamps=range(2000,2011), \n",
    "          initial_condition=(2000, country['2000'])).plot();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###Step 3: Make state-level predictions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If we want to look at the variances between the states and the national level, we can try making state-level predictions using state-specific initial conditions, but parameters fit at the national level."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe thead tr:last-of-type th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th colspan=\"9\" halign=\"left\">2000</th>\n",
       "      <th colspan=\"9\" halign=\"left\">2010</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>dec_1</th>\n",
       "      <th>dec_2</th>\n",
       "      <th>dec_3</th>\n",
       "      <th>dec_4</th>\n",
       "      <th>dec_5</th>\n",
       "      <th>dec_6</th>\n",
       "      <th>dec_7</th>\n",
       "      <th>dec_8</th>\n",
       "      <th>dec_9</th>\n",
       "      <th>dec_1</th>\n",
       "      <th>dec_2</th>\n",
       "      <th>dec_3</th>\n",
       "      <th>dec_4</th>\n",
       "      <th>dec_5</th>\n",
       "      <th>dec_6</th>\n",
       "      <th>dec_7</th>\n",
       "      <th>dec_8</th>\n",
       "      <th>dec_9</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>state</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>312841.0</td>\n",
       "      <td>329043.0</td>\n",
       "      <td>301076.0</td>\n",
       "      <td>315262.0</td>\n",
       "      <td>321447.0</td>\n",
       "      <td>246427.0</td>\n",
       "      <td>165327.0</td>\n",
       "      <td>109918.0</td>\n",
       "      <td>45131.0</td>\n",
       "      <td>312605.0</td>\n",
       "      <td>338568.0</td>\n",
       "      <td>321236.0</td>\n",
       "      <td>297502.0</td>\n",
       "      <td>321810.0</td>\n",
       "      <td>318358.0</td>\n",
       "      <td>229496.0</td>\n",
       "      <td>124070.0</td>\n",
       "      <td>56543.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.0</th>\n",
       "      <td>50687.0</td>\n",
       "      <td>53992.0</td>\n",
       "      <td>42537.0</td>\n",
       "      <td>51442.0</td>\n",
       "      <td>56047.0</td>\n",
       "      <td>35804.0</td>\n",
       "      <td>14974.0</td>\n",
       "      <td>7628.0</td>\n",
       "      <td>2325.0</td>\n",
       "      <td>53034.0</td>\n",
       "      <td>52278.0</td>\n",
       "      <td>58166.0</td>\n",
       "      <td>47753.0</td>\n",
       "      <td>51856.0</td>\n",
       "      <td>54170.0</td>\n",
       "      <td>29869.0</td>\n",
       "      <td>10392.0</td>\n",
       "      <td>4151.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.0</th>\n",
       "      <td>395110.0</td>\n",
       "      <td>384672.0</td>\n",
       "      <td>386486.0</td>\n",
       "      <td>391330.0</td>\n",
       "      <td>352471.0</td>\n",
       "      <td>257798.0</td>\n",
       "      <td>187193.0</td>\n",
       "      <td>144837.0</td>\n",
       "      <td>61148.0</td>\n",
       "      <td>463808.0</td>\n",
       "      <td>466275.0</td>\n",
       "      <td>455170.0</td>\n",
       "      <td>422447.0</td>\n",
       "      <td>418398.0</td>\n",
       "      <td>381076.0</td>\n",
       "      <td>300553.0</td>\n",
       "      <td>178849.0</td>\n",
       "      <td>89247.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5.0</th>\n",
       "      <td>188589.0</td>\n",
       "      <td>201405.0</td>\n",
       "      <td>180801.0</td>\n",
       "      <td>187516.0</td>\n",
       "      <td>186931.0</td>\n",
       "      <td>149142.0</td>\n",
       "      <td>104621.0</td>\n",
       "      <td>72629.0</td>\n",
       "      <td>33050.0</td>\n",
       "      <td>201821.0</td>\n",
       "      <td>205074.0</td>\n",
       "      <td>196956.0</td>\n",
       "      <td>183761.0</td>\n",
       "      <td>192596.0</td>\n",
       "      <td>188081.0</td>\n",
       "      <td>143285.0</td>\n",
       "      <td>81138.0</td>\n",
       "      <td>38925.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6.0</th>\n",
       "      <td>2669364.0</td>\n",
       "      <td>2588761.0</td>\n",
       "      <td>2556975.0</td>\n",
       "      <td>2812648.0</td>\n",
       "      <td>2495158.0</td>\n",
       "      <td>1692007.0</td>\n",
       "      <td>1002881.0</td>\n",
       "      <td>725610.0</td>\n",
       "      <td>331342.0</td>\n",
       "      <td>2573619.0</td>\n",
       "      <td>2780997.0</td>\n",
       "      <td>2849483.0</td>\n",
       "      <td>2595717.0</td>\n",
       "      <td>2655307.0</td>\n",
       "      <td>2336519.0</td>\n",
       "      <td>1489395.0</td>\n",
       "      <td>780576.0</td>\n",
       "      <td>456217.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            2000                                                         \\\n",
       "           dec_1      dec_2      dec_3      dec_4      dec_5      dec_6   \n",
       "state                                                                     \n",
       "1.0     312841.0   329043.0   301076.0   315262.0   321447.0   246427.0   \n",
       "2.0      50687.0    53992.0    42537.0    51442.0    56047.0    35804.0   \n",
       "4.0     395110.0   384672.0   386486.0   391330.0   352471.0   257798.0   \n",
       "5.0     188589.0   201405.0   180801.0   187516.0   186931.0   149142.0   \n",
       "6.0    2669364.0  2588761.0  2556975.0  2812648.0  2495158.0  1692007.0   \n",
       "\n",
       "                                           2010                        \\\n",
       "           dec_7     dec_8     dec_9      dec_1      dec_2      dec_3   \n",
       "state                                                                   \n",
       "1.0     165327.0  109918.0   45131.0   312605.0   338568.0   321236.0   \n",
       "2.0      14974.0    7628.0    2325.0    53034.0    52278.0    58166.0   \n",
       "4.0     187193.0  144837.0   61148.0   463808.0   466275.0   455170.0   \n",
       "5.0     104621.0   72629.0   33050.0   201821.0   205074.0   196956.0   \n",
       "6.0    1002881.0  725610.0  331342.0  2573619.0  2780997.0  2849483.0   \n",
       "\n",
       "                                                                       \n",
       "           dec_4      dec_5      dec_6      dec_7     dec_8     dec_9  \n",
       "state                                                                  \n",
       "1.0     297502.0   321810.0   318358.0   229496.0  124070.0   56543.0  \n",
       "2.0      47753.0    51856.0    54170.0    29869.0   10392.0    4151.0  \n",
       "4.0     422447.0   418398.0   381076.0   300553.0  178849.0   89247.0  \n",
       "5.0     183761.0   192596.0   188081.0   143285.0   81138.0   38925.0  \n",
       "6.0    2595717.0  2655307.0  2336519.0  1489395.0  780576.0  456217.0  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "states = data.groupby(level=0).sum()\n",
    "states.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can now generate a prediction by setting the model's intitial conditions with state level data, and parameters fit in the national case. I've created a `model_runner` helper function to make the code easier to read, but this could be conducted in a single line if we so chose."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>dec_1</th>\n",
       "      <th>dec_2</th>\n",
       "      <th>dec_3</th>\n",
       "      <th>dec_4</th>\n",
       "      <th>dec_5</th>\n",
       "      <th>dec_6</th>\n",
       "      <th>dec_7</th>\n",
       "      <th>dec_8</th>\n",
       "      <th>dec_9</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>state</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "      <th></th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <td>68817.239206</td>\n",
       "      <td>1.425135e+05</td>\n",
       "      <td>1.752830e+05</td>\n",
       "      <td>1.856499e+05</td>\n",
       "      <td>1.905074e+05</td>\n",
       "      <td>1.766502e+05</td>\n",
       "      <td>1.430809e+05</td>\n",
       "      <td>104576.864395</td>\n",
       "      <td>112780.892489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2.0</th>\n",
       "      <td>11149.879343</td>\n",
       "      <td>2.323983e+04</td>\n",
       "      <td>2.717858e+04</td>\n",
       "      <td>2.883606e+04</td>\n",
       "      <td>3.114106e+04</td>\n",
       "      <td>2.841718e+04</td>\n",
       "      <td>2.006445e+04</td>\n",
       "      <td>11731.576605</td>\n",
       "      <td>9263.036022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4.0</th>\n",
       "      <td>86914.373061</td>\n",
       "      <td>1.731934e+05</td>\n",
       "      <td>2.158222e+05</td>\n",
       "      <td>2.308789e+05</td>\n",
       "      <td>2.268514e+05</td>\n",
       "      <td>1.985338e+05</td>\n",
       "      <td>1.576861e+05</td>\n",
       "      <td>120469.144700</td>\n",
       "      <td>140567.692416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5.0</th>\n",
       "      <td>41484.889527</td>\n",
       "      <td>8.658169e+04</td>\n",
       "      <td>1.061958e+05</td>\n",
       "      <td>1.115457e+05</td>\n",
       "      <td>1.128048e+05</td>\n",
       "      <td>1.048007e+05</td>\n",
       "      <td>8.660780e+04</td>\n",
       "      <td>65340.896065</td>\n",
       "      <td>74727.981971</td>\n",
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       "    <tr>\n",
       "      <th>6.0</th>\n",
       "      <td>587193.689179</td>\n",
       "      <td>1.167877e+06</td>\n",
       "      <td>1.443928e+06</td>\n",
       "      <td>1.583683e+06</td>\n",
       "      <td>1.589019e+06</td>\n",
       "      <td>1.372822e+06</td>\n",
       "      <td>1.015240e+06</td>\n",
       "      <td>699665.480214</td>\n",
       "      <td>759574.642778</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               dec_1         dec_2         dec_3         dec_4         dec_5  \\\n",
       "state                                                                          \n",
       "1.0     68817.239206  1.425135e+05  1.752830e+05  1.856499e+05  1.905074e+05   \n",
       "2.0     11149.879343  2.323983e+04  2.717858e+04  2.883606e+04  3.114106e+04   \n",
       "4.0     86914.373061  1.731934e+05  2.158222e+05  2.308789e+05  2.268514e+05   \n",
       "5.0     41484.889527  8.658169e+04  1.061958e+05  1.115457e+05  1.128048e+05   \n",
       "6.0    587193.689179  1.167877e+06  1.443928e+06  1.583683e+06  1.589019e+06   \n",
       "\n",
       "              dec_6         dec_7          dec_8          dec_9  \n",
       "state                                                            \n",
       "1.0    1.766502e+05  1.430809e+05  104576.864395  112780.892489  \n",
       "2.0    2.841718e+04  2.006445e+04   11731.576605    9263.036022  \n",
       "4.0    1.985338e+05  1.576861e+05  120469.144700  140567.692416  \n",
       "5.0    1.048007e+05  8.660780e+04   65340.896065   74727.981971  \n",
       "6.0    1.372822e+06  1.015240e+06  699665.480214  759574.642778  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def model_runner(row):\n",
    "    result = model.run(params=country_level_fit_params, \n",
    "                       initial_condition=(2000, row['2000']), \n",
    "                       return_timestamps=2010,\n",
    "                       return_columns=[\n",
    "                           \"dec_1\", \"dec_2\", \"dec_3\", \n",
    "                           \"dec_4\", \"dec_5\", \"dec_6\",\n",
    "                           \"dec_7\", \"dec_8\", \"dec_9\"\n",
    "                       ])\n",
    "    return result.loc[2010]\n",
    "    \n",
    "state_predictions = states.apply(model_runner, axis=1)\n",
    "state_predictions.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 4: Compare model predictions with measured data\n",
    "Comparing the state level predictions with the actual data, we can see where our model most under or overpredicts population for each region/cohort combination."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>1.0</th>\n",
       "      <td>-2.437878e+05</td>\n",
       "      <td>-1.960545e+05</td>\n",
       "      <td>-1.459530e+05</td>\n",
       "      <td>-1.118521e+05</td>\n",
       "      <td>-1.313026e+05</td>\n",
       "      <td>-141707.812835</td>\n",
       "      <td>-86415.080653</td>\n",
       "      <td>-19493.135605</td>\n",
       "      <td>56237.892489</td>\n",
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       "      <th>2.0</th>\n",
       "      <td>-4.188412e+04</td>\n",
       "      <td>-2.903817e+04</td>\n",
       "      <td>-3.098742e+04</td>\n",
       "      <td>-1.891694e+04</td>\n",
       "      <td>-2.071494e+04</td>\n",
       "      <td>-25752.819389</td>\n",
       "      <td>-9804.550877</td>\n",
       "      <td>1339.576605</td>\n",
       "      <td>5112.036022</td>\n",
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       "    <tr>\n",
       "      <th>4.0</th>\n",
       "      <td>-3.768936e+05</td>\n",
       "      <td>-2.930816e+05</td>\n",
       "      <td>-2.393478e+05</td>\n",
       "      <td>-1.915681e+05</td>\n",
       "      <td>-1.915466e+05</td>\n",
       "      <td>-182542.183715</td>\n",
       "      <td>-142866.899500</td>\n",
       "      <td>-58379.855300</td>\n",
       "      <td>51320.692416</td>\n",
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       "      <th>5.0</th>\n",
       "      <td>-1.603361e+05</td>\n",
       "      <td>-1.184923e+05</td>\n",
       "      <td>-9.076017e+04</td>\n",
       "      <td>-7.221535e+04</td>\n",
       "      <td>-7.979121e+04</td>\n",
       "      <td>-83280.336688</td>\n",
       "      <td>-56677.198680</td>\n",
       "      <td>-15797.103935</td>\n",
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       "      <td>-1.986425e+06</td>\n",
       "      <td>-1.613120e+06</td>\n",
       "      <td>-1.405555e+06</td>\n",
       "      <td>-1.012034e+06</td>\n",
       "      <td>-1.066288e+06</td>\n",
       "      <td>-963697.077944</td>\n",
       "      <td>-474154.512342</td>\n",
       "      <td>-80910.519786</td>\n",
       "      <td>303357.642778</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              dec_1         dec_2         dec_3         dec_4         dec_5  \\\n",
       "state                                                                         \n",
       "1.0   -2.437878e+05 -1.960545e+05 -1.459530e+05 -1.118521e+05 -1.313026e+05   \n",
       "2.0   -4.188412e+04 -2.903817e+04 -3.098742e+04 -1.891694e+04 -2.071494e+04   \n",
       "4.0   -3.768936e+05 -2.930816e+05 -2.393478e+05 -1.915681e+05 -1.915466e+05   \n",
       "5.0   -1.603361e+05 -1.184923e+05 -9.076017e+04 -7.221535e+04 -7.979121e+04   \n",
       "6.0   -1.986425e+06 -1.613120e+06 -1.405555e+06 -1.012034e+06 -1.066288e+06   \n",
       "\n",
       "               dec_6          dec_7         dec_8          dec_9  \n",
       "state                                                             \n",
       "1.0   -141707.812835  -86415.080653 -19493.135605   56237.892489  \n",
       "2.0    -25752.819389   -9804.550877   1339.576605    5112.036022  \n",
       "4.0   -182542.183715 -142866.899500 -58379.855300   51320.692416  \n",
       "5.0    -83280.336688  -56677.198680 -15797.103935   35802.981971  \n",
       "6.0   -963697.077944 -474154.512342 -80910.519786  303357.642778  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "diff = state_predictions-states['2010']\n",
    "diff.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is a little easier to understand if we weight it by the actual measured population:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
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       "      <td>-0.579070</td>\n",
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       "      <td>-0.408013</td>\n",
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       "      <td>-0.399470</td>\n",
       "      <td>-0.475407</td>\n",
       "      <td>-0.328252</td>\n",
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       "      <td>-0.812607</td>\n",
       "      <td>-0.628559</td>\n",
       "      <td>-0.525843</td>\n",
       "      <td>-0.453473</td>\n",
       "      <td>-0.457810</td>\n",
       "      <td>-0.479018</td>\n",
       "      <td>-0.475347</td>\n",
       "      <td>-0.326420</td>\n",
       "      <td>0.575041</td>\n",
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       "      <th>5.0</th>\n",
       "      <td>-0.794447</td>\n",
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       "      <td>-0.460814</td>\n",
       "      <td>-0.392985</td>\n",
       "      <td>-0.414293</td>\n",
       "      <td>-0.442790</td>\n",
       "      <td>-0.395556</td>\n",
       "      <td>-0.194694</td>\n",
       "      <td>0.919794</td>\n",
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       "      <td>-0.493267</td>\n",
       "      <td>-0.389886</td>\n",
       "      <td>-0.401568</td>\n",
       "      <td>-0.412450</td>\n",
       "      <td>-0.318354</td>\n",
       "      <td>-0.103655</td>\n",
       "      <td>0.664942</td>\n",
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       "          dec_1     dec_2     dec_3     dec_4     dec_5     dec_6     dec_7  \\\n",
       "state                                                                         \n",
       "1.0   -0.779859 -0.579070 -0.454348 -0.375971 -0.408013 -0.445121 -0.376543   \n",
       "2.0   -0.789760 -0.555457 -0.532741 -0.396141 -0.399470 -0.475407 -0.328252   \n",
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       "6.0   -0.771841 -0.580051 -0.493267 -0.389886 -0.401568 -0.412450 -0.318354   \n",
       "\n",
       "          dec_8     dec_9  \n",
       "state                      \n",
       "1.0   -0.157114  0.994604  \n",
       "2.0    0.128905  1.231519  \n",
       "4.0   -0.326420  0.575041  \n",
       "5.0   -0.194694  0.919794  \n",
       "6.0   -0.103655  0.664942  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "diff_percent = (state_predictions-states['2010'])/states['2010']\n",
    "diff_percent.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###Step 5: Merge with geo data to plot\n",
    "\n",
    "I'm using geopandas to manage the shapefiles, and it has its own plotting functionality. Unfortunately, it is not a particularly well defined functionality."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>OBJECTID</th>\n",
       "      <th>FIPS</th>\n",
       "      <th>FIPSNum</th>\n",
       "      <th>StateFIPS</th>\n",
       "      <th>StateName</th>\n",
       "      <th>CensusReg</th>\n",
       "      <th>CensusDiv</th>\n",
       "      <th>XCentroid</th>\n",
       "      <th>YCentroid</th>\n",
       "      <th>Notes</th>\n",
       "      <th>geometry</th>\n",
       "      <th>dec_1</th>\n",
       "      <th>dec_2</th>\n",
       "      <th>dec_3</th>\n",
       "      <th>dec_4</th>\n",
       "      <th>dec_5</th>\n",
       "      <th>dec_6</th>\n",
       "      <th>dec_7</th>\n",
       "      <th>dec_8</th>\n",
       "      <th>dec_9</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>StateFIPSN</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>02000</td>\n",
       "      <td>2000</td>\n",
       "      <td>02</td>\n",
       "      <td>Alaska</td>\n",
       "      <td>West</td>\n",
       "      <td>Pacific</td>\n",
       "      <td>-1.882092e+06</td>\n",
       "      <td>2.310348e+06</td>\n",
       "      <td>None</td>\n",
       "      <td>MULTIPOLYGON (((-2247528.774 2237995.012, -224...</td>\n",
       "      <td>-0.789760</td>\n",
       "      <td>-0.555457</td>\n",
       "      <td>-0.532741</td>\n",
       "      <td>-0.396141</td>\n",
       "      <td>-0.399470</td>\n",
       "      <td>-0.475407</td>\n",
       "      <td>-0.328252</td>\n",
       "      <td>0.128905</td>\n",
       "      <td>1.231519</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>9</td>\n",
       "      <td>53000</td>\n",
       "      <td>53000</td>\n",
       "      <td>53</td>\n",
       "      <td>Washington</td>\n",
       "      <td>West</td>\n",
       "      <td>Pacific</td>\n",
       "      <td>-1.837353e+06</td>\n",
       "      <td>1.340481e+06</td>\n",
       "      <td>None</td>\n",
       "      <td>MULTIPOLYGON (((-2124362.243 1480441.851, -212...</td>\n",
       "      <td>-0.792005</td>\n",
       "      <td>-0.585096</td>\n",
       "      <td>-0.510514</td>\n",
       "      <td>-0.430876</td>\n",
       "      <td>-0.426070</td>\n",
       "      <td>-0.459076</td>\n",
       "      <td>-0.393843</td>\n",
       "      <td>-0.135940</td>\n",
       "      <td>0.674966</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>10</td>\n",
       "      <td>23000</td>\n",
       "      <td>23000</td>\n",
       "      <td>23</td>\n",
       "      <td>Maine</td>\n",
       "      <td>Northeast</td>\n",
       "      <td>New England</td>\n",
       "      <td>2.068850e+06</td>\n",
       "      <td>1.172787e+06</td>\n",
       "      <td>None</td>\n",
       "      <td>MULTIPOLYGON (((1951177.135 1127914.539, 19511...</td>\n",
       "      <td>-0.765509</td>\n",
       "      <td>-0.556475</td>\n",
       "      <td>-0.409031</td>\n",
       "      <td>-0.338041</td>\n",
       "      <td>-0.430710</td>\n",
       "      <td>-0.473652</td>\n",
       "      <td>-0.409398</td>\n",
       "      <td>-0.164981</td>\n",
       "      <td>0.726818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>11</td>\n",
       "      <td>27000</td>\n",
       "      <td>27000</td>\n",
       "      <td>27</td>\n",
       "      <td>Minnesota</td>\n",
       "      <td>Midwest</td>\n",
       "      <td>West North Central</td>\n",
       "      <td>1.310476e+05</td>\n",
       "      <td>9.821300e+05</td>\n",
       "      <td>None</td>\n",
       "      <td>POLYGON ((-91052.168 1282100.079, -30035.391 1...</td>\n",
       "      <td>-0.786822</td>\n",
       "      <td>-0.557537</td>\n",
       "      <td>-0.463915</td>\n",
       "      <td>-0.369641</td>\n",
       "      <td>-0.403840</td>\n",
       "      <td>-0.452106</td>\n",
       "      <td>-0.335580</td>\n",
       "      <td>-0.123440</td>\n",
       "      <td>0.645598</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>18</td>\n",
       "      <td>26000</td>\n",
       "      <td>26000</td>\n",
       "      <td>26</td>\n",
       "      <td>Michigan</td>\n",
       "      <td>Midwest</td>\n",
       "      <td>East North Central</td>\n",
       "      <td>8.425679e+05</td>\n",
       "      <td>8.094373e+05</td>\n",
       "      <td>None</td>\n",
       "      <td>MULTIPOLYGON (((764918.731 786184.882, 772386....</td>\n",
       "      <td>-0.746814</td>\n",
       "      <td>-0.547370</td>\n",
       "      <td>-0.378482</td>\n",
       "      <td>-0.282202</td>\n",
       "      <td>-0.364176</td>\n",
       "      <td>-0.423316</td>\n",
       "      <td>-0.329958</td>\n",
       "      <td>-0.074694</td>\n",
       "      <td>0.747247</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            OBJECTID   FIPS  FIPSNum StateFIPS   StateName  CensusReg  \\\n",
       "StateFIPSN                                                              \n",
       "2                  1  02000     2000        02      Alaska       West   \n",
       "53                 9  53000    53000        53  Washington       West   \n",
       "23                10  23000    23000        23       Maine  Northeast   \n",
       "27                11  27000    27000        27   Minnesota    Midwest   \n",
       "26                18  26000    26000        26    Michigan    Midwest   \n",
       "\n",
       "                     CensusDiv     XCentroid     YCentroid Notes  \\\n",
       "StateFIPSN                                                         \n",
       "2                      Pacific -1.882092e+06  2.310348e+06  None   \n",
       "53                     Pacific -1.837353e+06  1.340481e+06  None   \n",
       "23                 New England  2.068850e+06  1.172787e+06  None   \n",
       "27          West North Central  1.310476e+05  9.821300e+05  None   \n",
       "26          East North Central  8.425679e+05  8.094373e+05  None   \n",
       "\n",
       "                                                     geometry     dec_1  \\\n",
       "StateFIPSN                                                                \n",
       "2           MULTIPOLYGON (((-2247528.774 2237995.012, -224... -0.789760   \n",
       "53          MULTIPOLYGON (((-2124362.243 1480441.851, -212... -0.792005   \n",
       "23          MULTIPOLYGON (((1951177.135 1127914.539, 19511... -0.765509   \n",
       "27          POLYGON ((-91052.168 1282100.079, -30035.391 1... -0.786822   \n",
       "26          MULTIPOLYGON (((764918.731 786184.882, 772386.... -0.746814   \n",
       "\n",
       "               dec_2     dec_3     dec_4     dec_5     dec_6     dec_7  \\\n",
       "StateFIPSN                                                               \n",
       "2          -0.555457 -0.532741 -0.396141 -0.399470 -0.475407 -0.328252   \n",
       "53         -0.585096 -0.510514 -0.430876 -0.426070 -0.459076 -0.393843   \n",
       "23         -0.556475 -0.409031 -0.338041 -0.430710 -0.473652 -0.409398   \n",
       "27         -0.557537 -0.463915 -0.369641 -0.403840 -0.452106 -0.335580   \n",
       "26         -0.547370 -0.378482 -0.282202 -0.364176 -0.423316 -0.329958   \n",
       "\n",
       "               dec_8     dec_9  \n",
       "StateFIPSN                      \n",
       "2           0.128905  1.231519  \n",
       "53         -0.135940  0.674966  \n",
       "23         -0.164981  0.726818  \n",
       "27         -0.123440  0.645598  \n",
       "26         -0.074694  0.747247  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "geo_diff = state_geo.join(diff_percent)\n",
    "geo_diff.plot(column='dec_4')\n",
    "geo_diff.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Recipe Part B: fit state-by-state models\n",
    "\n",
    "Now lets try optimizing the model's parameters specifically to each state, and comparing with the national picture. \n",
    "\n",
    "### Step 1: Write the optimization functions to account for the state\n",
    "We'll start as before with functions that run the model and compute the error (this time with a parameter for the information about the state in question) and add a function to optimize and return the best fit parameters for each state."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "def exec_model(paramlist, state):\n",
    "    params = dict(zip(['dec_%i_loss_rate'%i for i in range(1,10)], paramlist)) \n",
    "    output = model.run(initial_condition=(2000,state['2000']),\n",
    "                       params=params, return_timestamps=2010).loc[2010]\n",
    "    return output\n",
    "\n",
    "def error(paramlist, state):\n",
    "    output = exec_model(paramlist, state)\n",
    "    errors = output - state['2010']\n",
    "    #don't tally errors in the first cohort, as we don't have info about births\n",
    "    sse = sum(errors.values[1:]**2)\n",
    "    return sse"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###Step 2: Apply optimization to each state\n",
    "We can wrap the optimizer in a function that takes census information about each state and returns an optimized set of parameters for that state. If we apply it to the states dataframe, we can get out a similar dataframe that includes optimized parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%capture \n",
    "def optimize_params(row):\n",
    "    res = scipy.optimize.minimize(lambda x: error(x, row),\n",
    "                                  x0=[.05]*9,\n",
    "                                  method='L-BFGS-B');\n",
    "    return pd.Series(index=['dec_%i_loss_rate'%i for i in range(1,10)], data=res['x'])\n",
    "    \n",
    "state_fit_params = states.apply(optimize_params, axis=1)\n",
    "state_fit_params.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Step 3: Merge with geographic data\n",
    "As we're looking at model parameters which themselves are multiplied by populations to generate actual flows of people, we can look at the difference between parameters directly without needing to normalize."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "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>OBJECTID</th>\n",
       "      <th>FIPS</th>\n",
       "      <th>FIPSNum</th>\n",
       "      <th>StateFIPS</th>\n",
       "      <th>StateName</th>\n",
       "      <th>CensusReg</th>\n",
       "      <th>CensusDiv</th>\n",
       "      <th>XCentroid</th>\n",
       "      <th>YCentroid</th>\n",
       "      <th>Notes</th>\n",
       "      <th>geometry</th>\n",
       "      <th>dec_1_loss_rate</th>\n",
       "      <th>dec_2_loss_rate</th>\n",
       "      <th>dec_3_loss_rate</th>\n",
       "      <th>dec_4_loss_rate</th>\n",
       "      <th>dec_5_loss_rate</th>\n",
       "      <th>dec_6_loss_rate</th>\n",
       "      <th>dec_7_loss_rate</th>\n",
       "      <th>dec_8_loss_rate</th>\n",
       "      <th>dec_9_loss_rate</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>StateFIPSN</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>02000</td>\n",
       "      <td>2000</td>\n",
       "      <td>02</td>\n",
       "      <td>Alaska</td>\n",
       "      <td>West</td>\n",
       "      <td>Pacific</td>\n",
       "      <td>-1.882092e+06</td>\n",
       "      <td>2.310348e+06</td>\n",
       "      <td>None</td>\n",
       "      <td>MULTIPOLYGON (((-2247528.774 2237995.012, -224...</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>9</td>\n",
       "      <td>53000</td>\n",
       "      <td>53000</td>\n",
       "      <td>53</td>\n",
       "      <td>Washington</td>\n",
       "      <td>West</td>\n",
       "      <td>Pacific</td>\n",
       "      <td>-1.837353e+06</td>\n",
       "      <td>1.340481e+06</td>\n",
       "      <td>None</td>\n",
       "      <td>MULTIPOLYGON (((-2124362.243 1480441.851, -212...</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>10</td>\n",
       "      <td>23000</td>\n",
       "      <td>23000</td>\n",
       "      <td>23</td>\n",
       "      <td>Maine</td>\n",
       "      <td>Northeast</td>\n",
       "      <td>New England</td>\n",
       "      <td>2.068850e+06</td>\n",
       "      <td>1.172787e+06</td>\n",
       "      <td>None</td>\n",
       "      <td>MULTIPOLYGON (((1951177.135 1127914.539, 19511...</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            OBJECTID   FIPS  FIPSNum StateFIPS   StateName  CensusReg  \\\n",
       "StateFIPSN                                                              \n",
       "2                  1  02000     2000        02      Alaska       West   \n",
       "53                 9  53000    53000        53  Washington       West   \n",
       "23                10  23000    23000        23       Maine  Northeast   \n",
       "\n",
       "              CensusDiv     XCentroid     YCentroid Notes  \\\n",
       "StateFIPSN                                                  \n",
       "2               Pacific -1.882092e+06  2.310348e+06  None   \n",
       "53              Pacific -1.837353e+06  1.340481e+06  None   \n",
       "23          New England  2.068850e+06  1.172787e+06  None   \n",
       "\n",
       "                                                     geometry  \\\n",
       "StateFIPSN                                                      \n",
       "2           MULTIPOLYGON (((-2247528.774 2237995.012, -224...   \n",
       "53          MULTIPOLYGON (((-2124362.243 1480441.851, -212...   \n",
       "23          MULTIPOLYGON (((1951177.135 1127914.539, 19511...   \n",
       "\n",
       "            dec_1_loss_rate  dec_2_loss_rate  dec_3_loss_rate  \\\n",
       "StateFIPSN                                                      \n",
       "2                      0.05             0.05             0.05   \n",
       "53                     0.05             0.05             0.05   \n",
       "23                     0.05             0.05             0.05   \n",
       "\n",
       "            dec_4_loss_rate  dec_5_loss_rate  dec_6_loss_rate  \\\n",
       "StateFIPSN                                                      \n",
       "2                      0.05             0.05             0.05   \n",
       "53                     0.05             0.05             0.05   \n",
       "23                     0.05             0.05             0.05   \n",
       "\n",
       "            dec_7_loss_rate  dec_8_loss_rate  dec_9_loss_rate  \n",
       "StateFIPSN                                                     \n",
       "2                      0.05             0.05             0.05  \n",
       "53                     0.05             0.05             0.05  \n",
       "23                     0.05             0.05             0.05  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "geo_diff = state_geo.join(state_fit_params)\n",
    "geo_diff.plot(column='dec_4_loss_rate')\n",
    "geo_diff.head(3)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}