3. Polynomial Model Predictions.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Import"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from scipy.integrate import odeint\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Get Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Use the World Bank API"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# need to install \"pip install wbdata\"\n",
    "import wbdata as wb\n",
    "import datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'SH.DYN.MORT': 'CM',\n",
       " 'SH.IMM.MEAS': 'M',\n",
       " 'NY.GDP.PCAP.CD': 'G',\n",
       " 'SP.DYN.TFRT.IN': 'Fr',\n",
       " 'SP.POP.TOTL': 'Population',\n",
       " 'PA.NUS.FCRF': 'Local2USD'}"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#from world bank API:\n",
    "wb_indicators = ['SH.DYN.MORT','SH.IMM.MEAS',\n",
    "                 'NY.GDP.PCAP.CD','SP.DYN.TFRT.IN',\n",
    "                 'SP.POP.TOTL','PA.NUS.FCRF']\n",
    "wb_indicator_names = ['CM','M',\n",
    "                       'G','Fr',\n",
    "                      'Population','Local2USD']\n",
    "wb_dict = {indicator:name for indicator,name in zip(wb_indicators,wb_indicator_names)}\n",
    "wb_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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></th>\n",
       "      <th>CM</th>\n",
       "      <th>M</th>\n",
       "      <th>G</th>\n",
       "      <th>Fr</th>\n",
       "      <th>Population</th>\n",
       "      <th>Local2USD</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <th>date</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 rowspan=\"5\" valign=\"top\">Bangladesh</th>\n",
       "      <th>2019</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>30.2</td>\n",
       "      <td>97.0</td>\n",
       "      <td>1698.262802</td>\n",
       "      <td>NaN</td>\n",
       "      <td>161356039.0</td>\n",
       "      <td>83.466202</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>31.9</td>\n",
       "      <td>97.0</td>\n",
       "      <td>1563.994082</td>\n",
       "      <td>2.062</td>\n",
       "      <td>159670593.0</td>\n",
       "      <td>80.437542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>33.9</td>\n",
       "      <td>97.0</td>\n",
       "      <td>1401.620628</td>\n",
       "      <td>2.090</td>\n",
       "      <td>157970840.0</td>\n",
       "      <td>78.468092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>36.1</td>\n",
       "      <td>97.0</td>\n",
       "      <td>1248.453398</td>\n",
       "      <td>2.120</td>\n",
       "      <td>156256276.0</td>\n",
       "      <td>77.946908</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   CM     M            G     Fr   Population  Local2USD\n",
       "country    date                                                        \n",
       "Bangladesh 2019   NaN   NaN          NaN    NaN          NaN        NaN\n",
       "           2018  30.2  97.0  1698.262802    NaN  161356039.0  83.466202\n",
       "           2017  31.9  97.0  1563.994082  2.062  159670593.0  80.437542\n",
       "           2016  33.9  97.0  1401.620628  2.090  157970840.0  78.468092\n",
       "           2015  36.1  97.0  1248.453398  2.120  156256276.0  77.946908"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# fetch the data for 1980 - 2020\n",
    "data_date = (datetime.datetime(1980, 1, 1), datetime.datetime(2020, 1, 1))\n",
    "\n",
    "wb_data = wb.get_dataframe(wb_dict,country=['ETH','BGD','LAO','TZA'],data_date=data_date).reset_index()\n",
    "wb_data['date'] = wb_data['date'].astype(int)\n",
    "wb_data = wb_data.set_index(['country','date'])\n",
    "\n",
    "wb_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### [Heritage Foundation Data](https://www.heritage.org/index/explore) for the *Trade Freedom* variable"
   ]
  },
  {
   "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",
       "    .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>name</th>\n",
       "      <th>index year</th>\n",
       "      <th>overall score</th>\n",
       "      <th>property rights</th>\n",
       "      <th>government integrity</th>\n",
       "      <th>judicial effectiveness</th>\n",
       "      <th>tax burden</th>\n",
       "      <th>government spending</th>\n",
       "      <th>fiscal health</th>\n",
       "      <th>business freedom</th>\n",
       "      <th>labor freedom</th>\n",
       "      <th>monetary freedom</th>\n",
       "      <th>trade freedom</th>\n",
       "      <th>investment freedom</th>\n",
       "      <th>financial freedom</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2019</td>\n",
       "      <td>51.5</td>\n",
       "      <td>19.6</td>\n",
       "      <td>25.2</td>\n",
       "      <td>29.6</td>\n",
       "      <td>91.7</td>\n",
       "      <td>80.3</td>\n",
       "      <td>99.3</td>\n",
       "      <td>49.2</td>\n",
       "      <td>60.4</td>\n",
       "      <td>76.7</td>\n",
       "      <td>66.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Albania</td>\n",
       "      <td>2019</td>\n",
       "      <td>66.5</td>\n",
       "      <td>54.8</td>\n",
       "      <td>40.4</td>\n",
       "      <td>30.6</td>\n",
       "      <td>86.3</td>\n",
       "      <td>73.9</td>\n",
       "      <td>80.6</td>\n",
       "      <td>69.3</td>\n",
       "      <td>52.7</td>\n",
       "      <td>81.5</td>\n",
       "      <td>87.8</td>\n",
       "      <td>70.0</td>\n",
       "      <td>70.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Algeria</td>\n",
       "      <td>2019</td>\n",
       "      <td>46.2</td>\n",
       "      <td>31.6</td>\n",
       "      <td>28.9</td>\n",
       "      <td>36.2</td>\n",
       "      <td>76.4</td>\n",
       "      <td>48.7</td>\n",
       "      <td>18.7</td>\n",
       "      <td>61.6</td>\n",
       "      <td>49.9</td>\n",
       "      <td>74.9</td>\n",
       "      <td>67.4</td>\n",
       "      <td>30.0</td>\n",
       "      <td>30.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Angola</td>\n",
       "      <td>2019</td>\n",
       "      <td>50.6</td>\n",
       "      <td>35.9</td>\n",
       "      <td>20.5</td>\n",
       "      <td>26.6</td>\n",
       "      <td>83.9</td>\n",
       "      <td>80.7</td>\n",
       "      <td>58.2</td>\n",
       "      <td>55.7</td>\n",
       "      <td>58.8</td>\n",
       "      <td>55.4</td>\n",
       "      <td>61.2</td>\n",
       "      <td>30.0</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Argentina</td>\n",
       "      <td>2019</td>\n",
       "      <td>52.2</td>\n",
       "      <td>47.8</td>\n",
       "      <td>33.5</td>\n",
       "      <td>44.5</td>\n",
       "      <td>69.3</td>\n",
       "      <td>49.5</td>\n",
       "      <td>33.0</td>\n",
       "      <td>56.4</td>\n",
       "      <td>46.9</td>\n",
       "      <td>60.2</td>\n",
       "      <td>70.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>60.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          name  index year  overall score  property rights  \\\n",
       "0  Afghanistan        2019           51.5             19.6   \n",
       "1      Albania        2019           66.5             54.8   \n",
       "2      Algeria        2019           46.2             31.6   \n",
       "3       Angola        2019           50.6             35.9   \n",
       "4    Argentina        2019           52.2             47.8   \n",
       "\n",
       "   government integrity  judicial effectiveness  tax burden  \\\n",
       "0                  25.2                    29.6        91.7   \n",
       "1                  40.4                    30.6        86.3   \n",
       "2                  28.9                    36.2        76.4   \n",
       "3                  20.5                    26.6        83.9   \n",
       "4                  33.5                    44.5        69.3   \n",
       "\n",
       "   government spending  fiscal health  business freedom  labor freedom  \\\n",
       "0                 80.3           99.3              49.2           60.4   \n",
       "1                 73.9           80.6              69.3           52.7   \n",
       "2                 48.7           18.7              61.6           49.9   \n",
       "3                 80.7           58.2              55.7           58.8   \n",
       "4                 49.5           33.0              56.4           46.9   \n",
       "\n",
       "   monetary freedom  trade freedom  investment freedom  financial freedom  \n",
       "0              76.7           66.0                10.0               10.0  \n",
       "1              81.5           87.8                70.0               70.0  \n",
       "2              74.9           67.4                30.0               30.0  \n",
       "3              55.4           61.2                30.0               40.0  \n",
       "4              60.2           70.0                55.0               60.0  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "heritage_data = pd.read_csv('data/new/heritage_data_2019.csv')\n",
    "heritage_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "name        index year\n",
       "Bangladesh  2019          63.6\n",
       "Ethiopia    2019          60.8\n",
       "Lao PDR     2019          81.8\n",
       "Tanzania    2019          67.8\n",
       "Bangladesh  2018          61.2\n",
       "Name: trade freedom, dtype: float64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Tf_series = heritage_data[heritage_data['name'].isin(['Ethiopia','Bangladesh','Laos','Tanzania'])\n",
    "                         ][['name','index year','trade freedom']]\n",
    "\n",
    "Tf_series['name'] = Tf_series['name'].replace('Laos','Lao PDR')\n",
    "Tf_series = Tf_series.set_index(['name','index year'])['trade freedom']\n",
    "\n",
    "Tf_series.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Assemble"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = wb_data.copy()\n",
    "df.insert(loc=4,column='Tf',value=Tf_series)\n",
    "\n",
    "df = df.sort_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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></th>\n",
       "      <th>CM</th>\n",
       "      <th>M</th>\n",
       "      <th>G</th>\n",
       "      <th>Fr</th>\n",
       "      <th>Tf</th>\n",
       "      <th>Population</th>\n",
       "      <th>Local2USD</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <th>date</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 rowspan=\"5\" valign=\"top\">Bangladesh</th>\n",
       "      <th>1980</th>\n",
       "      <td>198.7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>227.751947</td>\n",
       "      <td>6.359</td>\n",
       "      <td>NaN</td>\n",
       "      <td>79639491.0</td>\n",
       "      <td>15.454058</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1981</th>\n",
       "      <td>194.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>247.649620</td>\n",
       "      <td>6.217</td>\n",
       "      <td>NaN</td>\n",
       "      <td>81767515.0</td>\n",
       "      <td>17.986692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1982</th>\n",
       "      <td>189.3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>220.718810</td>\n",
       "      <td>6.058</td>\n",
       "      <td>NaN</td>\n",
       "      <td>83932127.0</td>\n",
       "      <td>22.117883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1983</th>\n",
       "      <td>184.2</td>\n",
       "      <td>1.0</td>\n",
       "      <td>204.417678</td>\n",
       "      <td>5.884</td>\n",
       "      <td>NaN</td>\n",
       "      <td>86142495.0</td>\n",
       "      <td>24.615425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1984</th>\n",
       "      <td>178.9</td>\n",
       "      <td>1.0</td>\n",
       "      <td>213.996658</td>\n",
       "      <td>5.698</td>\n",
       "      <td>NaN</td>\n",
       "      <td>88416521.0</td>\n",
       "      <td>25.353933</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    CM    M           G     Fr  Tf  Population  Local2USD\n",
       "country    date                                                          \n",
       "Bangladesh 1980  198.7  NaN  227.751947  6.359 NaN  79639491.0  15.454058\n",
       "           1981  194.1  NaN  247.649620  6.217 NaN  81767515.0  17.986692\n",
       "           1982  189.3  1.0  220.718810  6.058 NaN  83932127.0  22.117883\n",
       "           1983  184.2  1.0  204.417678  5.884 NaN  86142495.0  24.615425\n",
       "           1984  178.9  1.0  213.996658  5.698 NaN  88416521.0  25.353933"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.loc['Ethiopia']['CM'].plot()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Check that transformations match the old transformed dataset (SelectVar)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "SelecVar = pd.read_csv('data\\oxymoron\\SelectVar.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_oxy_wb = SelecVar[\n",
    "    ['country','year','trade_freedom',]+wb_indicators[:-1]][SelecVar['country'].isin(['Ethiopia','Bangladesh','Lao PDR','Tanzania'])]\n",
    "df_oxy_wb.columns = ['country','date','Tf'] + wb_indicator_names[:-1]\n",
    "df_oxy_wb = df_oxy_wb.set_index(['country','date'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Tf</th>\n",
       "      <th>CM</th>\n",
       "      <th>M</th>\n",
       "      <th>G</th>\n",
       "      <th>Fr</th>\n",
       "      <th>Population</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <th>date</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 rowspan=\"5\" valign=\"top\">Bangladesh</th>\n",
       "      <th>1995</th>\n",
       "      <td>0.00</td>\n",
       "      <td>11.42</td>\n",
       "      <td>0.79</td>\n",
       "      <td>5.757350</td>\n",
       "      <td>3.732</td>\n",
       "      <td>18.601915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996</th>\n",
       "      <td>0.38</td>\n",
       "      <td>10.86</td>\n",
       "      <td>0.69</td>\n",
       "      <td>5.805846</td>\n",
       "      <td>3.596</td>\n",
       "      <td>18.622812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997</th>\n",
       "      <td>0.38</td>\n",
       "      <td>10.32</td>\n",
       "      <td>0.72</td>\n",
       "      <td>5.825111</td>\n",
       "      <td>3.468</td>\n",
       "      <td>18.643387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>0.38</td>\n",
       "      <td>9.79</td>\n",
       "      <td>0.71</td>\n",
       "      <td>5.846080</td>\n",
       "      <td>3.346</td>\n",
       "      <td>18.663458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>0.34</td>\n",
       "      <td>9.29</td>\n",
       "      <td>0.71</td>\n",
       "      <td>5.862445</td>\n",
       "      <td>3.231</td>\n",
       "      <td>18.682790</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Tf     CM     M         G     Fr  Population\n",
       "country    date                                                \n",
       "Bangladesh 1995  0.00  11.42  0.79  5.757350  3.732   18.601915\n",
       "           1996  0.38  10.86  0.69  5.805846  3.596   18.622812\n",
       "           1997  0.38  10.32  0.72  5.825111  3.468   18.643387\n",
       "           1998  0.38   9.79  0.71  5.846080  3.346   18.663458\n",
       "           1999  0.34   9.29  0.71  5.862445  3.231   18.682790"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_oxy_wb[15:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "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></th>\n",
       "      <th>Tf</th>\n",
       "      <th>CM</th>\n",
       "      <th>M</th>\n",
       "      <th>G</th>\n",
       "      <th>Fr</th>\n",
       "      <th>Population</th>\n",
       "      <th>Local2USD</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country</th>\n",
       "      <th>date</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 rowspan=\"5\" valign=\"top\">Bangladesh</th>\n",
       "      <th>1995</th>\n",
       "      <td>0.0</td>\n",
       "      <td>113.9</td>\n",
       "      <td>79.0</td>\n",
       "      <td>329.424085</td>\n",
       "      <td>3.713</td>\n",
       "      <td>115169930.0</td>\n",
       "      <td>40.278318</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996</th>\n",
       "      <td>38.0</td>\n",
       "      <td>108.2</td>\n",
       "      <td>69.0</td>\n",
       "      <td>394.717475</td>\n",
       "      <td>3.591</td>\n",
       "      <td>117649932.0</td>\n",
       "      <td>41.794168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997</th>\n",
       "      <td>38.0</td>\n",
       "      <td>102.6</td>\n",
       "      <td>72.0</td>\n",
       "      <td>401.498691</td>\n",
       "      <td>3.478</td>\n",
       "      <td>120160564.0</td>\n",
       "      <td>43.892116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998</th>\n",
       "      <td>38.0</td>\n",
       "      <td>97.3</td>\n",
       "      <td>71.0</td>\n",
       "      <td>407.429186</td>\n",
       "      <td>3.371</td>\n",
       "      <td>122682815.0</td>\n",
       "      <td>46.905652</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999</th>\n",
       "      <td>34.0</td>\n",
       "      <td>92.2</td>\n",
       "      <td>71.0</td>\n",
       "      <td>409.543197</td>\n",
       "      <td>3.269</td>\n",
       "      <td>125189651.0</td>\n",
       "      <td>49.085400</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Tf     CM     M           G     Fr   Population  Local2USD\n",
       "country    date                                                              \n",
       "Bangladesh 1995   0.0  113.9  79.0  329.424085  3.713  115169930.0  40.278318\n",
       "           1996  38.0  108.2  69.0  394.717475  3.591  117649932.0  41.794168\n",
       "           1997  38.0  102.6  72.0  401.498691  3.478  120160564.0  43.892116\n",
       "           1998  38.0   97.3  71.0  407.429186  3.371  122682815.0  46.905652\n",
       "           1999  34.0   92.2  71.0  409.543197  3.269  125189651.0  49.085400"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['Tf']+wb_indicator_names][15:20]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# perform transformations were needed\n",
    "df_trans = df.copy()\n",
    "\n",
    "df_trans['CM'] = df['CM']/10\n",
    "df_trans['M'] = df['M']/100\n",
    "df_trans['Tf'] = df['Tf']/100\n",
    "df_trans['G'] = np.log(df['G'])\n",
    "df_trans['Population'] = np.log(df['Population'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot new transformed data divided by the equivalent old data. Everything should be 1 if equal.\n",
    "\n",
    "country = 'Lao PDR'\n",
    "for label in list(df_trans.columns[:-2]):\n",
    "    \n",
    "    # get ratio - should be 1 if correct\n",
    "    (df_trans[label]/df_oxy_wb[label]).loc[country].plot()\n",
    "\n",
    "    plt.title(label+' - '+ country)\n",
    "    plt.ylim(0,1.2)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The Model from the paper"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-5.571000000000001"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def CM_change(p_array):\n",
    "    M,Tf,G,Fr = p_array\n",
    "    return -0.03*Tf*G + 0.86*M - 6.4*M/G - 0.001*Fr**3\n",
    "\n",
    "# test\n",
    "CM_change([1,1,1,1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_se(preds):\n",
    "    \"\"\"Given a two column dataframe of true and predicted values,\n",
    "    return root mean square errors\"\"\"\n",
    "    \n",
    "    preds = preds.dropna()\n",
    "    y = preds.iloc[:,0]\n",
    "    y_pred = preds.iloc[:,1]\n",
    "    rmse = np.sqrt(sum((y - y_pred)**2)/len(y))\n",
    "    \n",
    "    return rmse"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAY0AAAEnCAYAAABVIB9ZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvIxREBQAAIABJREFUeJzs3Xd4VNXWwOHfyhACIaFjAOlIBw1NBel4Fb2ooCKiAlGvitfutaBXELvIh3ptKCqCqJSggNgRTEIJCGiAWOggoIReQ0nI+v44ExxCyqTNTDLrfZ7zZGbO3uesSWDWnLLXFlXFGGOM8UaIvwMwxhhTcljSMMYY4zVLGsYYY7xmScMYY4zXLGkYY4zxmiUNY4wxXrOkYQpFREaJyEe5rP9FRHp42XaziFxcDGEWKc84ReRxEXnP3zEVNxFpICIqImUK2F9F5JxCxlAi/n2UdpY0TJ5E5AYRWS4ih0XkLxH5WkS6eNNXVVupalwRxDDR/cFzZZbXX3W/HlPA7Rbqw1BVn1fVfxXFtvLisf3D7iVFRN4SkdDi2J8x2bGkYXIlIg8CrwLPA1FAPeAt4Co/hLMWGOoRWxlgALChIBsrrg93H6isqhFAG6ATcJef4zFBxJKGyZGIVAKeBu5S1c9U9YiqpqnqHFV92KNpWRH5UEQOuU9HdfDYRo6nFERksIhsEZE9IvJfL0KaA1wkIlXcz/sAq4AdHtsMEZEn3Nvd6Y6rkntd5jf1W0XkD2A+kODuut/97b2TiDQWkfnuuHaLyMciUjmH9+B5yi3rtrqLyF4RaePR/iwROSoiNbx4v7lS1Z3AXKClx/aHi8gG99/iVxHp77EuRkQWisj/icg+EdkkIpd5rG8oIgnuvt+LyJs5nU4UkZtF5Dd3240ickeW9Q+7j0r/FJFbsqwLc8fwh/to6W0RKe9eV11EvhCR/e7f3QIR8fycihaRVSJyQESmiUi5Qv0STb5Z0jC56QSUA2bm0e5KYCpQGfgceCOvDYtIS2AcMBioDVQD6uTR7Zh7+9e7nw8BPszSJsa99AQaARHZxNMdaAFcCnRzv1ZZVSNUNREQ4AV3XC2AusCovN5TNtuKx/m93OTRZhDwvaru8mJ7uRKR2u73sMTj5Q1AV6AS8BTwkYjU8lh/AbAGqA68BLwvIuJe9wnwI87fYhTO3yYnO4G+QEXgZuAVEWnnjqsP8BDwD6AJkPVLw2igKRANnAOcDYx0r/sPsA2ogXNk+zjgWevoOpwvCw2Bc3H+1saHLGmY3FQDdqtqeh7tFqrqV6p6EpgMnOfFtq8FvlDVBFU9DowAMrzo9yEwxH300B2YlWX9jcDLqrpRVQ8DjwHXZzkVNcp91HQ0ux2o6npVnauqx90f7i+791UQk4AbPL4tD8b5HRXGbhHZD2wHjgAzMleoaqyq/qmqGao6DVgHnO/Rd4uqvuv+W00CagFRIlIP6AiMVNUTqroQJ0FnS1W/VNUN6ogHvsNJVuB8sH+gqsmqegSPhOtOULcBD6jqXlU9hHPqM/OLQJo7pvruo9oFenqBvNfc728vzpFndH5+cabwLGmY3OwBqntx7n+Hx+NUoJwXfWoDWzOfuD9c9uQVkPvDrAbwBE7SyfrBXxvY4vF8C1AG51trpq3kwn0KaaqIbBeRg8BHON/M801Vl+J8sHcXkeY436yz/TB2n9rLvMjdNbs2btVVtTIQDiwCvvHYxhARSXKf3tkPtM4S+6m/laqmuh9G4Pze9nq8Brn8nkTkMhFZ4j6FtB+43GM/tbP09fx71HDHvcIjxm/crwOMAdYD37lPew3Psuus/9YicorRFA9LGiY3iTinhPoVw7b/wjntA4CIhOMc2XjjI5zTGFlPTQH8CdT3eF4PSAdSPF7THB5nesH9+rmqWhHn9JJk0y6rnEpGT3JvYzAwQ1WPZdvZudMswr0syHNnTsKcCHRyXwuoD7wL3A1UcyeWZC9j/wuo6v47ZKqbXUMRCQM+Bf4PiHLv5yuP/fyVpW89j8e7gaNAK1Wt7F4quS/so6qHVPU/qtoIuAJ4UER6exG/8RFLGiZHqnoA51zzmyLST0TCRSTU/S3zpUJufgbQV0S6iEhZnAvu3v57fA3nfHlCNuumAA+4L+pG4Jz6mJbLKbZdOKfFGnm8FgkcxrmgfTbwcHYdvdwWOKej+uMkjuwSXYG4P7wH43z73gNUwElcu9zrb8Y50siTqm4BlgOjRKSsiHTC+dDOTlkgzL2fdPfF9Es81k8HYkSkpTsJPemxnwycxPaKiJzljvNsEbnU/biviJzjPo11EDjpXkyAsKRhcqWqLwMP4pwO2oVz2uFuzryWkN/t/oJzq+gnON9M9+FcAPWm715VnZflXHemCTgf0gnAJpwjpXty2VYq8BywyH265EKcC8jtgAPAl8BnXsaV3bZQ1W3ATzgf6HkeQXhhv4gcxjl66gRc6b628CswFucIMQXnltxF+djuje7t7QGeBaYBx7M2cl+HuBcnOewDbsDjlJuqfo1zm/Z8nFNN87Ns4lH360vcp/++B5q51zVxPz/sfh9vFcU4H1N0xCZhMqb4icgE4E9VfcLfsXhLRKYBv6vqk3k2NkHDkoYxxUxEGgBJQFtV3eTfaHImIh2BvThHaJfgHE12UtWf/RqYCSh2esqYYiQiz+BcjB4TyAnDrSYQh3Nq6DXgTksYJis70jDGGOM1O9IwxhjjNUsaxhhjvFZSq3zmqHr16tqgQQN/h2GM8YE9e5wiAtWqeTsu1ORkxYoVu1U1z0KapS5pNGjQgOXLl/s7DGOMD0ycOBGAmJgYv8ZRGojIlrxblcKkYYwJHt26dcu7kSlSljSMMSVWo0ZZK7aY4mYXwo0xJdaOHTvYsWNH3g1NkbGkYYwpsb755hu++eabvBuaImNJwxhjjNcsaRhjjPGaJQ1jjDFes6SRRUpKCt26daNixYp069aNlJSUvDsZY0yQsFtus7j66qvZungxjYHExEQGDBhAQkJ2E8QZY/ytd2+bCdbX7Egji6SkJO4Dfgbi0tNpsmwZnDjh77CMMdmoW7cudetmO5W5KSaWNLJo3749z4vwAHAW8P6xY1C3Ljz3nL9DM8ZksXXrVrZu3ervMIKKJY0sYmNjadWlC++UL08LEW6uVYuj550HGzf+3WjpUrB5SIzxu3nz5jFv3jx/hxFULGlkERUVRUJCAqmpqcQlJDDj0CHabNzIHyNGOA1++gkuvBBatoQ33oCDB/0bsDHG+JAljVx06dKFuXPnsmvXLrr37MnmzZudZDFpEkRGwj33wNlnQ9myIPL3UrGiv0M3xphiYUkjDxdeeCHz5s1j//79dOvWjQ3bt8OQIfDjj85yzTWQlnZ6p0OH/BOsMcYUM0saXujQoQPz588nNTWVbt26sXbtWmdFx47grudvjDHBwJKGl9q2bcsPP/xAWloa3bt357fffvN3SMYEvT59+tCnTx9/hxFULGnkQ5s2bYiLi0NV6d69O6tXr3ZWREae3jDrc2NMsahZsyY1a9b0dxhBxZJGPrVs2ZL4+HhCQ0Pp2bMnSUlJzh1Uqn8vdkeVMT6xceNGNnreDm+KnSWNAmjWrBnx8fGEh4fTq1cvm5PcGD9JSEiwMj8+ZkmjgM455xzi4+OpVKkSvXr1Ijo62oocGmNKPUsahdCwYUPi4+NJS0vj2MqVDD10iFWLFzNgwAB/h2aMMcXCkkYh1atXD5fLRX/gdWDTyZP0X7oUtm3zd2jGGFPkLGkUgXbt2jHG5aITMBe498QJaNgQbr/d36EZY0yRsqRRBGJjY+ncuTPJERHcGhFB8zJlWNenD1Sp4jRQhfnzISPDv4EaU8r07duXvn37+juMoGJJowhkFjk8dOgQW7dupUbHjjT/6is+atPGaZCYCL17Q/Pm8NZbcOSIfwM2ppSoXr061atX93cYQcWSRhGrXLky3333Hd27d2fIkCG8++67cP75MG2ac+Rx113O/BxhYVbk0JhCWrNmDWvWrPF3GEHFkkYxiIiI4Msvv+TSSy/l9ttv57W33oLrroMlS2DRIujZ88zZAK3IoTH5lpiYSGJior/DCCqWNIpJ+fLlmTVrFv379+e+++7jxRdfdI4oOneGTz/1d3jGGFMgljSKUVhYGNOmTWPQoEE89thjjBw5ErUZ/4wxJVgZfwdQ2oWGhjJ58mTKly/PM888Q2pqKmPGjEEiI08/JWVFDo0xJYAlDR9wuVy8++67hIeHM3bsWI4ePcrr+/cTEmIHesaYksWSho+EhITw2muvUb58ecaMGUNqairvvfceLpfL36EZU2L179/f3yEEHfuq60MiwujRoxk1ahQTJ06kVlQUVSIirMihMQVUqVIlKlWq5O8wgoolDR8TEZ588kkaNGhAhz17WHXkCJ0WLuRm+8ZkTL4lJyeTnJzs7zCCiiUNP9mzZw/7gLXAaFWmJybCffeBTShjjNeWL19u89n4mCUNP4mOjmZ5mTJcDEQDs10udNw4p9yI1agyxgSogEkaIjJBRHaKSLLHa1VFZK6IrHP/rOLPGItSbGwsnTp1IjIykow2bbgzPJzza9Rg89NPQ0iIM2L8yith+nRIT/d3uMYYAwRQ0gAmAn2yvDYcmKeqTYB57uelQmaRw4MHD7Jq1SoSEhLYevIk7e+/nyVLlsDmzfD77zBwIDRuDC+/7IzlsHpVxhg/CpikoaoJwN4sL18FTHI/ngT082lQPhQdHc2iRYuoUqUKvXv35usNG5ykMXu2MzfHf/4Dhw+f3snqVRljfEwCqayFiDQAvlDV1u7n+1W1ssf6fap6xikqEbkduB2gXr167bds2eKbgItBSkoKl112GatXr2bChAkMHjzYWbFiBXTocGaHAPr7GeNrqampAISHh/s5kpJPRFaoajYfMqcLmCONwlDV8araQVU71KhRw9/hFEpUVBRxcXF069aNIUOGMHbsWGdF+/b+DcyYABQeHm4Jw8cCPWmkiEgtAPfPnX6OxycqVqzIV199xbXXXstDDz3EI4884hQ6zFqfyupVmSCXlJREUlKSv8MIKoFeRuRzYCjwovvnbP+G4zthYWFMnTqVe+65hzFjxrBz507e3bOH0NBQf4dmTMDITBjR0dF+jiR4BEzSEJEpQA+guohsA57ESRbTReRW4A9ggP8i9D2Xy8Wbb75JVFQUo0aNYvv27aSmprJ69Wqio6OJjY0lKirK32EaY4JIwCQNVR2Uw6rePg0kwGSWHYmKiuLOO+9EgOo4M5YNGDCAhIQEf4dojAkigX5Nw7gNGzaMcuXKcQmwFXgvPd25o8oYY3zIkkYJ0rFjRzaEhPAucA2QkJoKXbpAbCycPOnv8IwxQSCgxmkUhQ4dOmhpLWCWkpLCgAEDWLFiBRHp6cRkZDCyWjUqlCkDmzZBaKhTcqRMwJx1NKZYpaWlAdgNIkUgqMZpBIvM0iNHjhxh5ZYtzDvvPCrv3MnHt93mJIy0NGjRAm6/HaxctAkCoaGhljB8zJJGCVWzZk3i4+Pp889/ctOoUTz66KNkHDgAPXrA5MnQpg1cfDGEh1u9KlNqLVu2jGXLlvk7jKBiSaMEq1ChAjNnzuTOO+/kpZde4oa77+bY66/D1q3w/PNO7aqjR0/vZPWqTCnyyy+/8Msvv/g7jKBiSaOEK1OmDG+++SajR49m2rRpXHLJJewNCYHHHnOucxhjTBHyOmmISEMRuVpEmhdnQCb/RIRHHnmEqVOnsnTpUjp37symzAvjxhhThHJMGiIyy+PxVcB84ApgtojEFH9oJr8GDhzI999/z86dO7nwwgudaTCtXpUxpgjldqRR3+Pxo0AvVb0ZuAh4oFijMgXWtWtXFi9eTHh4ON27d2fOxx875dMzl4MH/R2iMaYEyy1peA7gKKOqmwBUdTdgk1gHsObNm7NkyRJatmxJv379OOecc6hYsSLdunUjJSXF3+EZU2RiYmKIiYnxdxhBJbekcZ6IHBSRQ0C0iNQEEJGygMsn0ZkCy5yXo3LlyuzdsIF3Dh2i7KJFDLj2Wn+HZowpwXJMGqrqUtWKqhqpqmVVdYd7VThwR24bFZEqItJKRBqJiN2h5ScVKlTgxIkTtAEuAb7PyGD8okXw+utw4IC/wzOm0BYvXszixYv9HUZQydcHuoj0VdX9qpqYzbpKIvK4iKwGlgDvANOBLSISKyI9iyZkkx9t27ZlcZky1MGZkOSQCNx7L5x9Nuze7e/wjCmUtWvXsnbtWn+HEVTyexTwdC7rZuAUYO2qqs1UtYt7Cta6OPNiXOWeF8P4UGxsLJ06dSI0MpKfWremd4UKXFq1Kn/cfDNUr+40evJJ+OgjOHbMv8EaYwJefpOG5LRCVf+hqpNVdX8261ao6v2q+n6+IzSFklmv6uDBg6xevZolS5awvnJlmr77LlOnToUTJ2DGDBg8GOrWheHDISLCSo8YY7KVa9IQkRAR6ezxUq7XMtx9LhKRCu7HN4nIyyJSP69+xjdatmzJ0qVLOf/88xk0aBBPPvccumoVzJ0LXbvCmDFw5Mjpnaz0iDHGLdekoaoZwFiP5z96sc1xQKqInAc8AmwBPixMkKZoVa9enblz5xITE8PTTz/NoBtv5OhFF8Fnn8Hmzf4OzxivWZVb3/Nm4oXvROQa4DP1bvKNdFVV9yjy/6nq+yIytHBhmqIWFhbGhAkTaNGiBcOHD2fTpk3MmjWLWnXr+js0Y7x24403+juEoOPNNY0HgVjgROa4DRHJbVjxIRF5DLgJ+FJEXIB9FQhAmTWrPvvsM5KTkzn//PNJSkqy0iPGmBzlmTTc4zRCVDXUY9xGbldGBwLHgVvdYzvOBsYUUbymGPTr14+FCxcC0KVLFz7/6CMrPWJKhPj4eOLj4/0dRlDJM2mI4yYRGeF+XldEzs+pvaruUNWXVXWB+/kfqmrXNAJc27Zt+fHHH0+VHmnYsCGRkZFWesQEtE2bNjkVnY3PeHN66i2gE3CD+/lh4M2cGrvLp68TkQNens4yAaJWrVrExcVRrVo1dm7ezMTDh6m6aBHXW+kRY4ybN0njAlW9CzgGoKr7gLK5tH8JuFJVK3l5OssEkPDwcI4dO0ZT4EJgVkYGkxctgmeegT//9Hd4xhg/8yZppLkvZiuAiNQg9yq3Kar6W1EEZ/yjbdu2JJcpQ32gP/ArwMiRUK8ebNzo3+CMMX7lzS23rwEzgbNE5DngWuCJrI1E5Gr3w+UiMg2YhXNBHABV/azw4RpfiI2NZcCAASQlJfFHkyYM27ePsK1bmdC/P50aNXIajRrl3FUVEwPVqvkzXBPEwsPD/R1C0BFvhl64p3jtjVNGZF52RxIi8kEum1BVvaXAUeZDhw4ddPny5b7YVdDYt28fgwYN4ttvv2XYsGH879VXKXvFFc4o8rAwuO46+PRTSE39u1NkpN11ZUwJIiIrVLVDXu1yPNIQkaoeT3cCUzzXqepez/buWf0QkYtUdVGWbV3kbeAm8FSpUoUvv/yS//73v4wePZrk5GRmzJhBVEoKvP02TJ58esIAKz1iTCmV2zWNFcBy989dwFpgnfvxilz6ve7la6YEcblcvPjii0yZMoUVK1bQvn17lh0/Dm+9ZRfIjd98//33fP/99/4OI6jkeKShqg0BRORt4HNV/cr9/DLg4qztRaQT0BmoISIPeqyqiM30V2pcf/31NG/enH79+tG1a1fGjx/PkCFD/B2WCVLbtm3zdwhBx5u7pzpmJgwAVf0a6J5Nu7JABE4iivRYDuJcPDelRHR0NMuXL6dz584MHTqUBx54gPSIiNMbWekRY0olb+6e2i0iTwAf4dx2exOwJ2sjVY0XkYVAG1V9qmjDNIGmevXqfPvttzz88MO8+uqrLO/ShfT0dH755Reio6OJjY0lyt9BGmOKnDdHGoOAGji33c4CznK/dgZVPQlUzW6dKX1CQ0N59dVX+eCDD1i0aBFLliyhyqFDJCYmMmDAAH+HZ4wpBnkeabjvkrovH9v8WUQ+x6mMe2o2HxunUXrFxMRw1113USM1lfXA/PR0/rdsmVPsUHKc7NGYQqtos0r6XJ5JQ0SaAg8BDTzbq2qvHLpUxTl95bleAUsapVj79u1ZvWgRj2dk8ADw5bFjnOzQAdfjj0O/fuCyeyFM0bv66qvzbmSKVJ6D+0RkJfA2zm22JzNfV9Xcbrv1Gxvc5x8pKSkMGDCAn3/+mVpVqtBz61YeDw2lriohmzZBnTr+DtEYk4tCD+7zkK6q47zY4SOq+pKIvI67TpUnVb3Xi33ltO0HgH+5t7sauFlVjxV0e6boRUVFkZCQcOr5/Pnz6TRoEOccOMCt8+YxdOhQGDwYzj0X7rgD7LSCKQLffPMNAH369PFzJMHDmwvhc0Tk3yJSS0SqZi7ZtMssLZI5IDDrUiAicjZwL9BBVVvjjPm4vqDbM77Rq1cvflq5ElenTsTExDBsyBBObtsGjzziFD78738hIsK55pG5WCIx+bRjxw527Njh7zCCijdHGpnzez/s8ZoCjTwbqeoc989JACJS0XmqRVFPogxQXkTSgHDAhiCXADVr1uT777/nqaee4tlnn2VRq1bMmT6dBtOmwQsvOBfKPVnpEWMCnjfTvTbMZmmUU3sR6SAiq4FVQLKIrBSR9gUNUFW3A/8H/AH8BRxQ1e+y7PN2EVkuIst37dpV0F2ZYuByuXj66af55ptv2LFjB61vvpmP+/eH33/3d2jGmALwZrrXIdktuXSZAPxbVRuoan3gLiC3Crh57b8KcBXQEKgNVBCRmzzbqOp4Ve2gqh1q1KhR0F2ZYnTJJZeQlJREu3btuOmmm7hj7FiO+jsoY0y+eVVGxGPpCowCrsyl/aHM+cEBVHUhUJjzDhcDm1R1l6qm4dy627kQ2zN+cvbZZzN//nyGDx/O+PHj6RQSwjqP9RlZS5EYk4dq1apRzeZz8SlvBvfd4/lcRCoBk7O2E5F27oc/isg7OKXUFRgIxBUixj+AC0UkHDiKM6+H3VNbQpUpU4YXXniBrl27ctVVV9E0I4MuwHKXi45t25KQ5xaM+dsVV1zh7xCCjjcXwrNKBZpk8/rYLM+f9Hic90xPOVDVpSIyA/gJSAd+BsYXdHsmMFx++eWEhYVRKz2dH4A/T57kzaVL4fBh564qY0xA8mZE+Bz+/tAPAVoC07O2U9WeRRvaadt+ktOTkCkF2rVrx+JFi7gyI4NHgdEnTpB+9tmUufdeeOABqGplzEzu5syZA9gRhy95c6Txfx6P04EtqmpF7E2hZc5FvjApiW0NGlD/r7+4Zc8ernjxRUJuu42QqlUhPR3KFOSA2ASDPXvOKLhtipk3t9zGeyyLLGGYopI5ivzgwYOsWrWKSWvW8FH//tRKT+fSW2/lr7/+gssvhwEDwErDGBMQvLl7yhifqFq1KjNmzOD58eNZtGgR0W3asL5SJZg7Fzp2hF69IDzcRpEb40dFnjREJFxERojIu+7nTUSkb1Hvx5ROIsJtt93GTz/9RO26dWkyYwYPDxxI2vPPw5o1cDTL6A4bRW6MTxXHkcYHwHGgk/v5NuDZYtiPKcWaN2/OkiVLeOCBB/i/8eNp98kn/Prll/4OywSYmjVrUrNmTX+HEVTynTREZJKIjBOR1jk0aayqLwFpAKp6FLCZeEy+hYWF8fLLL/P111+zc+dO2nfqxDgKcf+2KXX69OljFW59rCBHGm8A3wODc1h/QkTK4/6/LSKNcY48jCmQPn36sGrVKnr06MG/gX7Abvc6G0VujG95nTREpAKAqi5T1U9V9dEcmo4CvgHqisjHwDzgkcIGaoJbVFQUX375JY0aNWIOsBl4C7ilaVP/Bmb86rPPPuOzz2xSUF/ypmBhZxH5Ffd8GSJynoi8lVN7dwXaq4EYnFIiHVQ1rkiiNUEtJCSEXbt2EQH8CtwCTPzpJ05eeCFMnnzmRXJT6h08eJCDBw/6O4yg4s2RxivApTjzfqOqK4FuOTUWkc+BS4A4Vf1CVXfn1NaY/IqOjuZomTIMBeoADwJ/rFgBQ4bA1187jfKYwtgYU3BenZ5S1a1ZXjqZbUPHWJxquL+KSKyIXCsi5QoaoDGeYmNj6dSpE5GRkbTs2pUes2dzcd269AIeXbiQY8eOwTPPwMUXw4wZkJbm75CNKVW8SRpbRaQzoCJSVkQe4u+pXc/gHjn+b5yZ/cYD1wE7iyRaE/Q8R5EnJCRw5ZVXsnLVKprecQcvvfIKHTp04I/jx2H9emckeb16EBZmAwKNKSLeJI1hOBMpnY0z5iIa+HduHdx3T13j7tsRmFS4MI3JWUREBG+//TZfffUVe/fupfFLL/HcLbdw8vPPnZHkJ06c3sEGBJYaderUoU6dOv4OI6iI5nH+V0QuUtVFeb3msW4acAHOHVTTca5tZBRRvHnq0KGDLrc6RUFr79693H333UyZMoULLriASZMm0ax58zMb2nUPY04jIitUtUNe7bw50njdy9cyfYAzwG+Yqs73ZcIwpmrVqnzyySdMnTqVdevW0bZtW14H7B+hMUUjx5rTItIJZ1rVGiLyoMeqioArm/a9VHU+EA5cJXL6IHBVtZupjc8MHDiQrl278q9//Yt7v/6aWTjfZurhDAi0Sp2lw/TpztQ+1113nZ8jCR65TVRQFohwt4n0eP0gcG027bsD84HsZkNRnLm9jfGZ2rVr8+WXX9K0aVPmr1/Pn8BCYFHDhryp6lwUNyVaamqqv0MIOjkmDVWNB+JFZKKqbslrQ+7Z9VDVm4swPmMKRURISUmhLLAUGArcsHo1ac2aEXr33TB4MFSp4ucojSk5vJkSLVVExgCtgFPjLVS1l2ejLKewzqCqLxcoQmMKKTo6msTERO5PT+e/IgwE7ty4kQ733YdGRiI33+zMEOhy2dGHMXnw5tTux8DvQEPgKZyyP8uyaReZx2KMX3gOCGzXpQu3JybyYOfOtAWumTaN7du3w2uvQbt28PbbdkuuMbnw5pbbFaraXkRWqeq57tfiVbW7TyLMJ7vl1ngjIyODN954g+HDhxMWFsbMG2+k+8KFyMqVEBEBx4+fPpo8MhKsxlHAiY+PB6B794D8OCpRivKW28z/OX+JyD9FpC1O2R9jSqyQkBDuvfdeVq4RlAdFAAAgAElEQVRcSevWren55ptcWacOu+bMgWuvPbP8iB19BKTu3btbwvAxb5LGsyJSCfgP8BDwHvBAsUZljI80adKEuLg4XnnlFebNn0/TwYOZ3KuXTfRkTA5yTRoi4gKaqOoBVU1W1Z6q2l5VP/dRfMYUO5fLxf3338/KlStp1aoVQ4YMoR/wl78DM3n6+OOP+fjjj/0dRlDJNWmo6kngSm83JiKXuqeC/VxEZrsf21yMpkRo0qQJ8fHxjB07lu9wbhf8HGeQ0RHXGeNZTQBIS0sjzSoZ+5Q3p6cWi8gbItJVRNplLlkbicirwH1APPASMMb9+F4R+V+RRm1MMXG5XDz44IO4KlRgH9AU2AWMDwmBdev8HJ0x/ufNOI3O7p9Pe7ymQK8s7S5X1TPm3nQXMFyLk1CMKRHatWvH4kWLuC8jg9uBe9LSoGlTMnr0IGTkSOjZ098hGuMXeSYNVfX2f8cxETlfVX/M8npH4Fi+IzPGj2JjYxkwYACJSUnsb9GC2HLlaJSQwF2LF3Pixx9p2LMn7N4Ne/ZAs2b+DtcYn/HmSMNbMcA4EYnEmXcDoC5OraqYItyPMcUuc7KnTKrKjBkz6HD33ex5/HHu272b58qXp+wzz0D37nDHHdC/P5SzSSp9qWnTM05umGKW5+C+fG9QpCbOhE0CbFPVHUW6gzzY4D5TnPbt28ejjz7Ku+++S8e6dfnoH/+gaVwcbNzolCDx/P9kAwJNCVKUg/vys9NKONVuu+PME95dRCoX5T6M8acqVaowfvx44uPjORgeTrMJExjSqRP7Y2PPnNjJBgSaUijPpCEiy0XkLhHJtRSoiAwBfgJ64MypUQHoCaxwrzOm1OjWrRtJSUmMHDmSqdOnc86wYXwINijQxyZOnMjEiRP9HUZQ8eZI43qgNrBMRKa6x2JkVwr0v0B7Vb1TVZ91L8OADsATRRizMQGhXLlyPPXUUyQlJdGsWTOGAv8ANvg7MGOKUZ5JQ1XXq+p/cW5Z/wSYAPwhIk+JSFWPpkL2X7Qy3OuMKZVatmzJggULeEWEZTjzdiQDB7Ne4zCmFPDqmoaInAuMxRmw9ynOzH0HcWbqy/Qc8JN7FPjj7uVtnFNWzxVt2MYElpCQEEZGRHAQ2IpT0bOiKoeaNYMJE+DoUT9HaEzR8OaaxgrgFZw5NM5V1XtVdamqjgU2ZrZT1Uk4p6LigePACSAO6KCqE4s+dGMCS3R0NGXKlGE4UFeEu8qUYfO6dXDrrRwZMcLf4RlTJLw50higqr1V9RNVPQ4gIg0BVPVqz4aquk9Vp6rqWFX9P/fjfYUNUkQqi8gMEfldRH4TkU6F3aYxRc1zsqe2Xbrw0Nq1TH3sMXq7XHR87z3ee+89Mr74Aq68Er77DjIy/B1yideqVStatWrl7zCCijeTMP2kqu2yvLZCVdt7vROR1arapoAxIiKTgAWq+p6IlAXCVXV/dm1tnIYJNL/++it33nknCQkJjGrShMf37CF0715o2hS2bHEmfMpkYzuMn3g7TiPHEeEi0hyn0GclEfE8oqiIx1zhHu2vzvpa5iqgZl6B5BJHRaAb7lHlqnoC59SXMSVCy5YtiYuL48MPP+Shhx5i9P79vP/Pf3Ldrl241q49vbGN7ciXzAq3oaGhfo4keORWRqQZ0BeoDFzh8foh4LZs2k/DmU88u0OXwtRWaIRTaPQDETkPWAHcp6pHMhuIyO3A7QD16tUrxK6MKR4iwtChQ+nbty/Dhw/nhvfeY3i9enyIMxLWFEzmXBoxMTH+DSSIeHN6qpOqJua5IeeC+VBVTc5m3VZVrVugAEU6AEuAi1R1qbvM+kFVzfbKop2eMiXBokWLGDZsGMnJyVwFvAac+rpjt+l6LXNgnyWNwit0GRERecT98AYReS3rkk2X+3Fuw81O/7xDztE2nBpWS93PZwBnzOdhTEly0UUX8dNPP/GsCHOBr4A/gFSABQvghJ2BNYEpt9NTv7l/evW1XVUX5LKuwF/9VXWHiGwVkWaqugboDfxa0O0ZEyhCQ0MZHRFB6qFDrAXa44zvoFs3NDwcGTjQGeMBztFHtoUYjPGtHJOGqs5x/5zku3BydA/wsfvOqY3AzX6Ox5giER0dTWJiIq+kp/O/kBBqhoXR8ehRhlarRpfy5akBTsJo1cqZt6NXLxg+HFJT/96I3XFlfCi3u6fmkEv9NVX1eu7wwlLVJJyBg8aUKpmTPSUlJREdHc2UKVP47LPPuGXkSA698w53h4Yy6qGHqNy5M8ybB7NmnbmRIL7jKjo62t8hBJ0cL4SLSK43dahqfDZ9QoBrVXV60YSXf3Yh3JQGu3fvZsSIEbzzzjtUq1aN5557jltvvRXXH39Ao0ZndrCL56aQCn0hXFXjc1ty6JMB3F2IuI0xQPXq1Rk3bhw//fQTLVq04I477qBjx44s3L7d36EFlNTUVFI9T9WZYudN7akm7hIev4rIxswlly5zReQhEakrIlUzlyKM2ZigER0dTXx8PFOnTmXXrl107dqVQWXKnJpPGSAjIsJv8fnb9OnTmT7dbyc2gpI3tac+AMYB6TiTKn0ITM6l/S3AXUACzkC8FXh5B5Yx5kwiwsCBA/n9998ZMWIE006epC7QEmgbEkIvO69vfMibpFFeVefhXP/YoqqjgF45NVbVhtks2ZyENcbkR4UKFXj66acJDw8H4FHg54wMZi1ciPbpA889B/HZnjk2psh4kzSOuS9wrxORu0WkP3BWTo1FJFxEnhCR8e7nTUSkbxHFa0zQa9euHWXKlGEkMBiYCmyIi4MnnoBhw/5u+N57MHMm7NwJFSs64zwyl4oV/RO8KfG8SRr348z5fS/O+KObgNzm/P4Ap6BgZ/fzbcCzhYjRGOMhswT7vshINnfpgrz9NpfUrk1V4PbKlUlKSnLupnrySbj6aoiKOvO23CC+TdcUTm4jwjM1UNVlwGHcg+pEZADOrJbZaayqA0VkEICqHs1hTnFjTAFERUWRkJBw2msxMTGMGzeOZ555hvfatWPw4ME8ExdHvd27YeFCeOSRHLZWsnXoYMO3fM2bI43HvHwt0wkRKY97YKCINMaZyc8YU0zCwsK4//772bBhAw8//DDTpk2jaZs2DJ89mwO33+7v8IpN69atad26tb/DCCq5De67DLgcuA6n7HmmikBLVT0/h37/AJ7AubnjO+AiIEZV44ou7JzZ4D5jYMuWLYwYMYKPPvqIqlWrMuLwYe48fpyymQ1KSemRAwcOAFCpUiU/R1LyFXpwH/Anzq2yx/j71tkVwOfApTl1UtW5wNU4kyZNwZkjPM7bwI0xhVe/fn0+/PBDVqxYQdu2bbn/+HEqlStHjbAwenTuTMq6df4OsUjMnDmTmTNn+juMoJJbwcKVIpIMXFKAooXdgS44p6hCAfurGuMHbdu25bvvvuPcc88lOTmZJ4DbFy9mXsuWXD9zJnTpAiHenKU2xpHrvxZVPQlUc1eX9YqIvAUMA1YDycAdIvJmoaI0xhSYiLBlyxYA5gPfA1fs3Qvdu3OiVi3nVl1jvOTN3VNbgEUi8jlwaopVVX05h/bdgdbqvlgiIpNwEogxxk8yS7DPT08n3uWied26dNqzh3/u3EmVyZOJuukmmjdvDq+9Bj17QuvWNn+HyZY3x6V/Al+420Z6LDlZg8fMlUBdYFVBAzTGFF7m2I7IyEg6d+7MvCVLeHn7dlaOGkXfPXto1aoVDw0ahD74IJx7rpM0nnkGIiJsUKA5TZ5zhJ9qKBIJqKoezqNdPNAR+NH9UkcgEfdMlsU9D4fdPWVM/uzatYvnn3+et956i7OA/3XrxhWHDxO6ZEn2HQKoDPuaNWsAaNasmZ8jKfm8vXsqz6QhIq1xChRmVqrdDQxR1V9yaJ/veTiKkiUNYwpm8+bNjBo1ig8//JDIyEieueMO7hgzhrCsDQMoaZiiU5RJYzHwX1X9wf28B/C8qnbO0k40j41506awLGkYUzjJyck88cQTzJ49myjgaWAo/J08Aihp7N69G3DmHzGFUxTjNDJVyEwYAO4xFxWyafeDiNwjIp7XMxCRsiLSy31BfKgX+zPG+FHr1q2ZNWsWixYtojGwGUgDfgP2A2Rk+DG6033xxRd88cUX/g4jqHiTNDaKyAgRaeBengA2ZdOuD3ASmCIif2ZO2gSsAwYBr6jqxCKL3BhTrDp37kxIly7ME2EaUAeoDBw46yzSR40KqCMO4zveJI1bgBrAZziD9GrgLlzoSVWPqepbqnoRUB/oDbRT1fqqepuqJhVh3MYYH5gxYwZhXbpwf0QEvVu25MlGjVi2Zw/zR4/mjTff5NixY/DVV1Y1N4jkOU5DVffhlEX3mqqmAX8VNChjTGDIWlFXVZk/fz7PP/kk8ffcw6Rnn+XHnTuhfHnk6qshJgb69YPDHjdZlpI6V8aRY9JwD+bLUXHfOmuMCTwiQu/evenVqxc//PADT40aRaeUFP4NDPz0U8I++ujMTnYUUqrkdqTRCdiKU3RwKWDDQ40xgJM8evXqRa9evYiLi2PUqFHcHh/PkEqVGH7gALWA8j6Io1u3bj7Yi/GU2zWNmsDjQGvgf8A/gN2qGl/cYy2MMSVHjx49iIuL49u4ONa3a0djoD+wBI+6Q8WkUaNGNGrUqJj3YjzlmDRU9aSqfqOqQ4ELgfVAnIjc47PojDElRvfu3Zk/fz5fA32BDjj35m8HUp97DnbsKPJ97tixgx3FsF2Ts1wH94lIGPBPnFtmG+DMpTFBVbf7JLoCyG5wX1paGtu2bXPu9DAlTrly5ahTpw6hoaH+DsV4oVu3biQmJlI1PZ1BwI04tYQOh4dzZN06omrXdsZ6FEFJ9okTJwLOdLemcLwd3JfbhfBJOKemvgaeUtXkIozPp7Zt20ZkZCQNGjTApisvWVSVPXv2sG3bNho2bOjvcIwXYmNjGTBgAElJSfwUHc1VTz3Fg2PGsPHrr/m2cWNu+9e/+L/58ynbti0MHgy9e0MZbwpum0CQ219qMM4pyabAvR4ftoJTuLDElLs8duyYJYwSSkSoVq0au3bt8ncoxktZb9MF6NmzJ2vXrqXqiy8yadw42qhyw/r1VPj4Y4iKgr17IS3t7w52m27Ayu2aRoiqRrqXih5LZElKGJksYZRc9rcrHZo2bcqECRNYtWEDK++8k1rAtSL8GBpKhmfCALtNN4DZPI/GGJ+qX78+b7zxBmu3bKHRQw/Re/9+quGUnvjV38GZPFnS8KEdO3Zw/fXX07hxY1q2bMnll1/O2rVrERFGjBhxqt3u3bsJDQ3l7rvv9mO0xhSvmjVr8tJLL7Flyxbux5l7oSVwEKe43ckvvoATJ3LdRu/evendu3fxB2tOsaThI6pK//796dGjBxs2bODXX3/l+eefJyUlhUaNGp1WqTM2NpZWrVr5MVpjfKdq1ao85HIxCmeK0O9xEojriis4WrUqB7dty7Fv3bp1qVu3rm8CNYB3c4SXKvfffz9JSUVbOzE6OppXX3011zY//PADoaGhDBs27LR+mzdvpnz58rRo0YLly5fToUMHpk2bxnXXXceff/5ZpHEaE6gOb99+6o6r8847jyNDh5L8yiuE/forr7ZsyW233cZTmzYRUbkyDBjg3HFVtixbt24FyF/i6NHD+RkXV+TvIxgEXdLwl+TkZNq3b5/j+uuvv56pU6dSs2ZNXC4XtWvXtqRhgkZ2d1zxr3+xbNky1r/yCv979VVaqHJDmTKEf/ABVK4Mhw8z76abAIiZONHuuPKRoEsaeR0R+EufPn0YMWIEUVFRDBw40N/hGBMQOnbsyCeffMLo0aN5/fXXafDOO5yflsbdoaH0Tk8/vbHdceUTJeaahoi4RORnESmR03S1atWKFStW5Li+bNmytG/fnrFjx3LNNdf4MDJjAl/dunV56aWX2LBtG/949VXurFCBCCAJ58L5AT/HF0xKTNIA7sOZcbJE6tWrF8ePH+fdd9899dqyZcvYsmXLqef/+c9/GD16NNWqVfNHiMYEvMjISO677z7Wr1/PJ0AloKL7Zwrw1+DBkJgYUFPSljYlImmISB2cGljv+TuWghIRZs6cydy5c2ncuDGtWrVi1KhR1K5d+1SbVq1aMXSoTaNuTF5cLhd9XC4a4pSt+BhYBVT76CPo3JmpL79MamqqUyQxj9t2vdKjx98X0INcrgULA4WIzABeACKBh1S1b5b1twO3A9SrV6+957d3gN9++40WLVr4KFpTHOxvaLJKSUnh5ptvZs2aNZx99tlMmDCBuFmz+On11xn3xx9UrlyZBVWq0GL3blxXXQX9+8PQoQWbVTAI7rjytmBhwCcNEekLXK6q/xaRHmSTNDxlV+XWPnBKPvsbGm+pKgsXLuStt97icGwsV588yTVlylAxPR0lm9nkvPkMtKRxSkk4PXURcKWIbAamAr1EJJs5JY0xwWbjxo1s3LjxtNdEhK5duzJlyhTe276dHc8/T3StWvQEJgBfAn/5I9hSIuCThqo+pqp1VLUBcD0wX1Vv8nNYxpgAkJCQcOb4Dg9RUVE89thjrNu0if/MmcOnwDNALZxSJb8D6cuWeXe0YYASkDSMMaawXC4Xffv2JdblYhrO0cYOoAlQ5vzz2Ve5Mlu/+65od1pKL56XqKShqnG5Xc8wxpjcHN6+nb2VKlHR5eKRLl2Y8frrvHreecw7eJAml17KxRdfTNJNN3Fy8GCYPRtSU/0dcsAJuhHhxpjgFRUVRVR0NAALMi9q330327Zt4/EJE3j//ff5fN48GohQ+aOPyChXjpD0dMgcfS4S9OVKStSRRkmWU1n0zZs356s0+sSJExER5s2bd+q1mTNnIiLMmDHD63ji4uLo2zf3gzZv2hhTGtSpU4eRI0eyceNGzv/6a26/6iouCQnhzWPHSElPZwtw6pgjyMuVWNLwgdzKogP5Lo3epk0bpkyZcur51KlTOe+884rvDRgToPr27VukX2xcLhd9+vRh+syZTP7zT1JffJEuQB+cW3VXAxsB3by5yPZZ0ljSyE7Fis5haOZSsXCz2+ZUFr1r164Ap5VGB06VRs9J165d+fHHH0lLS+Pw4cOsX7+eaPchN8C8efNo27Ytbdq04ZZbbuH48eMAfPPNNzRv3pwuXbrw2WefnWp/5MgRbrnlFjp27Ejbtm2ZPXt2od6vMb5SvXp1qlevXizbjoqK4tFHH2UN8D4QD5QHGgHSsCE7a9Zk11dfFe1OS8DFc0sa2cl6+FnIw9G8yqLD36XRt23bdqo0ek5EhIsvvphvv/2W2bNnc+WVV55ad+zYMWJiYpg2bRqrV68mPT2dcePGcezYMW677TbmzJnDggUL2LFjx6k+zz33HL169WLZsmX88MMPPPzwwxw5cqRQ79kYX1izZg1r1qwp1n0cdbnojHO0cRZOyZI3GjZkdUoKbfv25fLLL2fJPfdw8vrrYcoU2LvX+aIZH+8sRfDFM5BY0ggQffr0Ye7cuUyZMsWr0uiZSWbq1KkMGjTo1Otr1qyhYcOGNG3aFIChQ4eSkJDA77//TsOGDWnSpAkiwk03/T3U5bvvvuPFF18kOjqaHj16cOzYMf7444+if5PGFLHExEQSExPz1ykuLl8juw9v387PlSqxwOWib9euXLxjB3dv3Ei9tWuJefxxVq9ezZQ33mDv9Olwww3oWWehRfzFM5DY3VM+0KpVqzwvUnuWRv/ll1+YM2dOru3PP/98kpOTKV++/KkEAc71k5yInFFA4VSfTz/9lGbNmp32euY1F2OCmecdVwkeyaZJkyY8++yzPPXUU8ybN4/7J0xg28yZXHziBNcCVXCug0T5I+hiZEca2YmMzP15PuVUFj0+Pv60dvktjf7CCy/w/PPPn/Za8+bN2bx5M+vXrwdg8uTJdO/enebNm7Np0yY2bNgAcNqF9EsvvZTXX3/9VML5+eef8/8mjQlSLpeLSy65hI+nTmV2Sgpnvf02NwPtgWrAOuBn4MA338DJk0UfgI+vg1jSyM7Bg05ZgcylkPdke1MWHfJfGv2yyy6jZ8+ep71Wrlw5PvjgAwYMGECbNm0ICQlh2LBhlCtXjvHjx/PPf/6TLl26UL9+/VN9RowYQVpaGueeey6tW7c+7fZfY4z3KleuzB133MFcYD7wA7AfaANUuuwyDpQvz7yHH+ZgCR7nEfBVbvPLqtyWTvY3NNmZOHEiADExMcW7o3xWue3WrRvPLFiAAhe7XFzUsiV3NGhA2Lx5PJqayrawMJ5v04bBhw5RadAgyvbrB126+LVsu7dVbu2ahjGmxOrfv79vdpTPD+TY2Fj+bNaMw4cP07lzZ6bHxhIVFYWqUnvJEqZNm8Zvkybxx/79tB81CkaN4ihQFnBlbiRAL55b0jDGlFiVKlXydwjZyuniuYjQqVMnOnXqxMmxY1mwYAGPvP8+x2bOpNuRI9QH9gCVgebun4HGrmkYY0qs5ORkkpOT/R1GgbhcLnr06MFLkyczdt8+IoBJQDvgQpyEsaFCBZZ268baTz/N9c5IX7IjDWNMiZV5/bJ169Z+jqRwQkND6epy0efkSU4CK4HtQLWQEM5bsICbFyxgUd26DLnoIm4IC6PhHXdQ/oILIMT33/staeQkCKZ3NMYEjsPbt7PWfR3kv507E+u+DvLXhg1cOncux7/7jt0zZ9Ly+HGYNIl9ZcuSkp5OlYwMZyyICBkREYQU87UQSxrGGFMc8vmFM6frILUaNyamcWNihg3j+PHjLJg1i60TJhCRmMgFJ05QDbgE+A4I8bz7qpjYNQ0fKU2l0ePi4qhUqRLR0dGnlu+//97rfRtjCiYsLIyuAwdyw7ffcuXBgxwCPgF6+zAGSxo+UBpLo3ft2pWkpKRTy8UXX3zaelUlIyPjtNdOejka1tt2xgS7c4AhwKM+3KclDR8IltLomzdvpkWLFvz73/+mXbt2bN26lYiICEaOHMkFF1xAYmJijrE1aNCAp59+mi5duhAbG1ug/Zvgc9111+X6f6W0y4iIyPV5cbCk4QOlsTT6ggULTjs9lVnTas2aNQwZMoSff/6Z+vXrc+TIEVq3bs3SpUvp0KFDtrFlKleuHAsXLuT666/Pdd/GZAoPDyc8PNzfYfhNyKFD0L27s6gW+0VwsKQRMEpaafSsp6caN24MQP369bnwwgtPtXO5XFxzzTW5xpbJm/dtjKfMf3+lRj7LtvuD3T3lA8FUGr1ChQqnPS9XrhwulyvP2LLra0xeMhOG5+lZU7zsSMMHrDR67rEZY0oOSxo+UBpLo2e9puHN7b45xWaMKTmsNLopEexvaLLjs9LoQcDb0uh2pGGMMcZrdiHcGFNi3Xjjjf4OIegETdJQ1RzvHjKBrbSdQjVFJzQ01N8hBJ2gOD1Vrlw59uzZYx8+JZCqsmfPHsqVK+fvUEwAWrZsGcuWLfN3GEElKI406tSpw7Zt29i1a5e/QzEFUK5cOerUqePvMEwA+uWXXwDo2LGjnyMJHkGRNEJDQ2nYsKG/wzDGmBIvKE5PGWOMKRqWNIwxxnjNkoYxxhivlboR4SKyC9hSBJuqDuy2PtbH+vh0X9bHf33qq2qNPHupqi3ZLMBy62N9rE/gx2d9fPtvwU5PGWOM8ZolDWOMMV6zpJGz8dbH+lgfn+/L+gR2n9J3IdwYY0zxsSMNY4wxXrOkYYwxxmuWNLwgIuVEJF/Fq0pTHylgTfmC9LM+1qc09vHlvoq7jyUNDyJSPodVTYCZIhJe2vu4+2X9B9RIRO4SkbI5bK/A/ayP9SmNfQI9voK+J8AG92UZ7DIPqOZ+XBaoCXQCrgNOAO1Lcx/gTuAaj+eZN0pUBJZmt4+C9rM+1qc09gn0+Ar6njyXoCiNng8hwDsish9ojvOLPAFsBcYAf5byPkOAuiJyETBOVdcBqOpBEVkBXAisyGY/BelnfaxPaewT6PEV9D2dYknjdCuBK4GHgAlAsqoeDKI+s3CORlYC74rIt8DbQC2chJNT34L0sz7WpzT2CfT4CvqeTrGkcbrFwH5V/SzzBRGpBJwPhKnqF6W8zzagpapOEpF1wCAgEfjZve6rbPZR0H7Wx/qUxj6BHl9B39Pf8jp/FUwLUAm4Agh3P28DrAZ+Az4FninNfYBzgPezvHYWMBg4L5ffW777WR/rUxr7BHp8BX1Pp7X3plGwLIAAbwCV3c8/Aa7yWP8LEFXK+9QBLgVmA9uBvThHLB8ATwAVcvjd5buf9bE+pbFPoMdX0Pd0qn9BPlxL8wKsA+q6HycAbT3WzQcuKs19gLY45zjvBBp6vH42sAj4Rw6/t3z3sz7WpzT2CfT4CvqeMhcbp3GmucDDInIW8BJwo4jcIiL/Ab4Ffi3lfe4DtqvqOFXdlPmiqm7H+VbSNJt9FLSf9bE+pbFPoMdX0PcE2IXw7IwB+gOjccY01AQ2A58Db6vqvlLeZx3QQkQqq+p+ABFpDfTD+QeV3QX3gvazPiWvTyt3n23Al9Yn2z6BHl9B3xNgVW5zJCLN3A/Xqqq6v6mrqu4qzX1EpAkwFGfUeBucW/FScI5Yxqvq6hy2n+9+1qfE9Gns7lMbOIBzWvN/qrrK+pzZJ9DjK+h7OtXfkkbuRKQMzsWhujiD5Zaq6tulvY+InAvsw/nmIUAV4JCqnshj+/nuZ30Cvk9H4Cjwu6qme7weoaqHrU/2fQI9vgK/J0saZxKR+4BpqrpDRJ4AWuBcOCoPjAJuUtWNpbxPJeBmoJu73S4gHed+7omqeiiH312++1mfwO6THRGpDgwHXnGfC7c+Xgrk+Lzqo7lcJQ/WBWe0ZFf34zlAZ491M4DrSnMfnMPWCTjXQf4BtAJaAv8EvgH65fB7y3c/6xPwfW4G6ng8rwDUAy4CdgM3Wp8z+wR6fAV9T6pWeyoni4AewALga6CP+7ROM5xh9kmloE9oLn0GAsdxjkJO6t+nLn4Vke5AZ5xyBFkVpJ/1Cew+/X67YvEAAA8aSURBVIBLRGQaToKJBMKBIzi3cGd3GsP6BH58BX1PljRy8B4wSETm4Zzzq4Yz3D4OmIZz90F++kxR1bVe9hmIc0Hqkzz2Mx9IBaoD1+P8oaflcz/zgKnZ9EkDKun/t3f+wVZV1x3/LODxQ55I0KABBFHLTCoKaVSEhuqoBTRG44/Q2NqmiVbUYmNiapK2JlEnpIaYmCrxR6uRQM0YXlI0mcS0NohC2hiqEo3RqEHApiq+hyEQkV+rf3zX4V3O2+fe8xCM7ezvzJt5997zPfvH2Xuttddaex/3V2GnS+NwZJ2ORKm7KZR5Q2rwmnFG7QZnJMoYa8XZD1neu1u3upyi705+g/pgWnCurcn5nRac7wEfR6vVvuiwy5dREH0+sKYmZ93r4HwNWP0GlLMnOXurrLV7uZyXqO5vICuNJNz9YTN7DjgKdWgb8JQ35DRXcFYBR8dXBjzjpVhBgvMLtNmmDzq+fE3wXmtRtwlRRj9gjbs/2aKc1dGePtGeZ4AXPB3w6gBGmdkPo07rkIXaBXS4+8qKogre8uB1AduBTmARkMrK6ABGV3AWuntq5dSBTupMce5qwinaNCDaBBKAd1W0KVUOKJC8CB3J0qoPOpGwfgX4ZpNyUv3WhZR6s/b8B3qencAOJCjupLqvy+VsQacdL6zgPAG0u/vftwqQVnAGu/umGpyfAUN2g7NvLzlPAO1IQQ6u2Z7dKWdnWbtTv93g7Evv2rQ75QA5EF4bZjYa+D0k4IcDH/bmGSejUIbSeOBFd7+n4ro+7r6j4rd/Bi4oLMPE74ejCb8ZmIWCmze7+9Ia7Tke+S+PAr7i7g+Ufh+C2rsOKaYdwFqPvO4m9x0a99yAhGWXu/9PC07/qMt6JMS63P2F+G24u7+U4AxACnpTcNYX5ZhZm7tvTXDao00vIsXxnLc4Kdj0Iqt3ouX6FqSgm05KM9sXOAYppB3Aq+7+bAtOUbcN9OyDQ4FVXpqs8YzeHhxDRkAXTRArnwnBeQ31Xx80RnuMM9OLuv7C3b8cnw35v7c3GZf7ALPc/UsN3xmSN1VjfR/gQ+5+Y4lDlLfN3TfX4PRBqeRJwRacC9z9H4oy3N2jrD7uvr0Vpy7KfVfUr+iDouxWZRX9EPUcUh6zwbnQ3a/vZd12eUbx/duAzqayLSuNNMxsNvB9d3/azAajzXCbgSXARcD73P2RBO9y4KN058E/hAT7euCGVgI07tHH3XeEVTzb3R8u/X4Icjm1oQn/XaQwHkLn4f+1l3Ktzex04DF3X2Vm7wJuQDn664ATgY+XOcGbggT6vlHeWLQRbFHVaqiiTaOAS4Db3f2Z0m+j3b3HEtrMDgauBua6+xOl34YBm939NwnezcA8r95TcmW05W5gtbu/3KTeu1jXZjYOndszGSmts5uUMwKYilyI7cBb0TsMmiqQBn5fd99uZvOBL6ZWKWZ2EDqUciXwc+B8NBZ+BNzi7p0tyjgXnXo8Aq2cbqrixLg7lu5jtA8BvgH8W5UySNxjJHoJ2DdTz7yCczBypdzg7k8lft8P2JAQwF9Ch/M9XnHfi9CcXoE8CVtTgrzh+gHFmA9FfjxS9EcAF6fq1sA11HejUV/3Q3MhtSG3hzHZIBNuQUZeaiy0o7n6FDJYzgVOQ66ohTWMnRlovB4GLAUWpDj5GJFqnIEGA7F0Ww3c7e5fQLGACWWCmZ2JBMPxKLh0B/Axd78YPYhTE5wLzOyzZjbRzNpDCBSvYX0gVQ7amPMoElhTo66L3P3TwC/Q4CzjvIZ7XQB8zt2vcPe5aIf45FK9hprZbcCn6XabPYZiNGeimEgPmNl7zex34/8+ZtYWq4JtSDlNS9A+YmZLrHsDYrFaWIss6CkJziwU3C+uP7IoFxiILP1y3dri3yOBA4E/By4zs4uj31O42MxObvh8K/BJNAa6SPS1mfUzszko/vUF9OKb0chF9cmYnC3RYPVup9vt2VjOeGAeeq6zo27HAgvQivg9Cc55RXvM7AzgQyjd9ma0Kj4twRlgZtchBTEDKcHXgGeBC1FMrcw5ybSJrHHFgCuN8wTSc2GOmS00bTwtvusb42AoEmhlzl8BxxWC3sxGmNnY+Hl/YFKCU7zS9F1Igc0GPmFmf4rGeg+Y2SXsOg7nAlcgN88gJKyTMLOP0D13rkFKfTgwx8z+IMUpK+GGz8UKu1zGIcBt6Dypm5Cr6lRk5J4EnJXgnGlmU+P/yWhcb0LG1AlonvdAjmlU41HkXirQiaxFUIB6ElIKjZiMLJ5nAMzsVbQquRxZfsehB9uIDUhJfA4Js5XAk8GdgQRgGfsjy6iwkJcD081sRdRxeILzElKCi9FAPyKs/wPRBq9fla4/FY2PPy5bnuECOAEFzMr4Q+BEM7saCbO3AWPQMe0DkKuhjK1I2V5lZj8HrnP3oj7/BUxMcN4a3xfn/89EwdwPor4+BqWX7kSDy+pptMr+GzM7K9o608zud/erSuWMQILkvvi8GOjv7reZ2TbSSv0U1KfnuPuLsWp1d59nZlfQneK6E2ZWCK/lyDJcDwx09x/Htcclypke113m7tvM7Fr0et8Ok+tqMj3H6JTg3IfciEvd/WtRh7Hx+/wSZwYaUzPd/blSvS9CQf47E3V7BZgDHBZC7Qg0pyahOEEZg5DBdaOZ3Y92qhebzh5AbsJ/KnEOQQrl+/H5IpRwcD6wLDjlOVeMg7XI7XelmZ2HVg2nm9mDCVfUOKQsl8TnB4GfuvtNZrYVKdweMLOTkMH4HuR5uBC5Ar9uZp8Czom2NXLOQobh4ihnO9A35Mo9JJQnekabkWvr17HKWu/u15vZr9D4Kc/XqUhJPIgMuiXuPifq0B8p1QXlgrLSqMYPgI9G5znyHS+M3+ajgVrGCuCDIYzbkXVZDOYH0Bk/u8Ddv2Fmi+N+G6OcacFfjjKkylgCXBoCtj8Slk+jN/T9N3BLgrMQWfR3BP9UJFAeQXs3FpWub0eZNp0AZvYWdG7VFOBs4MuksQxZrQcgF0YXmpw/Bb4FpFwFP4z2X4YspG+b2YIo70SkUMtYgYRzgY3A2BCc40kotBCko9HzfLcpoeAg5D4cg4RWGT9GQr5AW7QLtKrrYTEjpT7Y3V+Mz+ujrvOQUXBGgvMkesdJG9qxfxjwsJm9HOWnXuf7MhImhWBdC0wxs8uQ5ZsKbC8D3hf/LwVmmdl09LxOA/4xwTkQBU2fC4NhIFKKE5Ew/JcE51HgdjObhvrjFWAVsrj/DCn2MpagcfC3wHXAKTEOhiBLeWGCs4JdV6+dwMlmdikSessTnP5m1hd4AfgjM/vPKHcLMtxSca6HkCIssA25bEErrj9JcEBGx1s8kmjM7HnkNvo6kgmfTXDWIGPpKOTqbgOWmdlmpFRTLq1XUZyp2Jz5OHC+mZ2NFMbmBOcRulcTPwI+YGbvRM92Ot2yaxfkmEYFQllMQROpP8qwSQ3ARs5QtFQ/B020Re5+dfw2AD3UbU1uUb7fQKBf2a9oCrSejoTJEGC+uy8ys4nIukimy4UlOQlNpkFI0awEflCOT5h8z59HFtZSNKEGomyy5cC3Um0xsyPj9xEo5tCyveFmWeDu7zDtOXkHWir/Egm5ReUAZdRvbpSzCq085qKXyTwI3OmlYLh1n/Q7AAmaL6IV1proi7WJvh6JFNnBcd3bgbPcfU0InqGJldhhyLC4BwmmmShB4Ttmtj9waKwgUn3RvwhCRl8eRfS7u99aunYssqKfjb6ait6fMg0ptHleyoqJ8i9B42clMg4moBXbUuC75WdmZmOAr6Cg/r3IZXgAMAwZA3ckxs949Ea4Q9HbI3skJiTaPh74qrsfE2N/BvCXSKE+geITW0qcMUgZd0abj0bW8buBh1FcpxxAHx7tGYIEagdSwE8jQfpsOdYQ5dyIxssqtLqa5e4/iTE7zNMJG+OiPtei+OEs4F53Xxgu0aM9/dbNwsjZiOTPySg9ui/KMvtU6drDo5y70Zg7Bz2rCVHudYlxeiCKFR2LVrfj4vp/j77rSMUts9JoAVNw6TcRhKoMkpU4Y4Bf1pkoFfzKTI7SdcNRpsN2a5KFleDVujYG9Ti0khmEJtbPPL0XpLHu17j73zV8Lnzanuq/uObShEugVf1GIovagMWpAZ7gTELC/3J3/1jNckYgV08/4F+rgpclzmS0ujgAKeWO+L5ZtlxlZk349lOZPUciV+FgJPB/Et/vVD4JTj8UczsYrQKeRwkBlQH6UIQT0XgYjFwtK72UdddwvSFFOavhcxFD9VQfxDWfAT5Tavswb5IVZt3JCfsgY2FtKyPNFFd6CsX2esRkKjjFPph24HtekQCR4J2CNtONAu6POGLxHLZXzYkqWWNmA8uKML7/fTTm9kdj4dvhIWhLKbTgFEbDBDRWV6OU/0oDOSuNJqirJPYWf28iJiigGbyH790ObOrNfctCsTdKsIFTu7+tOxtlZzpjb8qqWcY+wJberC4T92hZv1jxeG8Mm9dRn94YJwcB61oZPyXOft4dz6r9TMNtRm/7wLoz1Jqm6jbWB6pTh5vwhgEbqxR5zXu0bFfjmOtlP9S/9k0q0zIyMjL+X+DNbDzuDrLSyMjIyMiojbxPIyMjIyOjNrLSyMjIyMiojaw0MjJeJ0xYFlkyxXczzezeZryMjP+LyDGNjIw9gNhjsAjtMemLNrfNaJbGWuOe/V5P5lVGxt5AVhoZGXsIZvZ5dCzDYPTe7WvM7ANog1p/tPN9dqSF3oqOrRiENo4Wm0CfRzv6ZwDXu3t5p35Gxm8V+RiRjIw9h6vQTtotwNGx+jgTvV53WyiK96Nzmj7h7l2xwWuJmXV490m+m9y98gC8jIzfJrLSyMjYQ3D3TabXZ25099dMp8keA6yIPXqD6H7z2rlmdj6agyPQDu1Cadz1xtY8I6M+stLIyNiz2BF/oONNbnf3KxsvMB0Z/mHgWHd/xcwWsutpxrXfopaR8UYjZ09lZOw93IeOXD8AdFig6Q2QQ4BfAxtMb0qb3uQeGRlvKuSVRkbGXoK7P2ZmVwH3xdlGW9H7HlYgV9Tj6GTWpqcnZ2S8mZCzpzIyMjIyaiO7pzIyMjIyaiMrjYyMjIyM2shKIyMjIyOjNrLSyMjIyMiojaw0MjIyMjJqIyuNjIyMjIzayEojIyMjI6M2stLIyMjIyKiN/wWwvcAitLr1kAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAY4AAAEnCAYAAAC+F6RaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvIxREBQAAIABJREFUeJzs3Xd4FHUawPHvmxAMISEicEGKNAGRlkBAKQGlCHiIIgqoCCiKYkPOruCBitgrlkNPyqGIwYKgYEEhlChdKVKkI4KAIr0kee+P2UAIKZtkk9nNvp/n2YfszLwz727CvjszvyKqijHGGOOtELcTMMYYE1iscBhjjMkTKxzGGGPyxAqHMcaYPLHCYYwxJk+scBhjjMkTKxymSIjIcBGZmMP6VSJyiZfbbhaRDoWQpk9lzFNEHhWRd93OyRhfsMJhfEZErheRxSJyUER+F5EZItLam1hVra+qs32QwzgRURHplmn5K57l/fO53+qe+BL5iVfVp1X1Fl/sKzeFvf8Mx9ksIkc8v+9dIjJWRCI962aLyFEROSAi+0VkiYg8LCJnZYgfLiInPPH7RGSBiLQozJyNb1jhMD4hIv8CXgGeBmKA84A3gStdSGcd0C9DbiWAa4EN+dlZYX8AB7grVDUSaAI0A4ZmWHeXqkYB5wL3Ab2BL0VEMmwz2RNfHvgeSCyatE1BWOEwBSYi0cATwJ2q+omqHlLVE6o6TVUfyLBpSRGZ4PkWukpE4jPsI9vLTyJyo4hsEZG9IvKYFylNA1qJSFnP887Az8DODPsMEZGhnv3+4ckr2rMu/Rv7ABHZCnwHJHlC93m+IbcQkVoi8p0nrz0i8r6InJ3Na8h4+S3zvtqKyJ8i0jDD9v/wfJuv4MXr9ZqINBeRZM83/N9FZLSIlMywvqWILBKRvz3/tvRmv6r6GzADaJDFukOes8luQAvgn1lskwK8D1T29Ws2vmeFw/hCCyAc+DSX7boBHwJnA58Do3PbsYhcCLwF3AhUAsoBVXIJO+rZf2/P877AhEzb9Pc8LgVqApFZ5NMWqAd0Atp4lp2tqpGqmgwIMMqTVz2gKjA8t9eUxb7m4LwvfTJscx3wraru9mJ/eZEKDMH5ht8CaA/cASAi5wBfAK/hvM8vAV+ISLncdioiVYHLgWXZbaOqW4HFQEIW8SVxfk97gb/y9IpMkbPCYXyhHLDH860xJ/NU9UtVTQX+BzT2Yt/XANNVNUlVjwHDgDQv4iYAfT1nEW2BzzKtvwF4SVU3qupB4BGgd6bLUsM935aPZHUAVf1VVb9R1WOeD/iXPMfKj/HA9SKS/n/yRpz3yKdUdYmq/qCqKaq6GfgPp3L+J7BeVf/nWT8JWANckcMuPxORfcA8YA7Opcqc7ADOyfC8pyf+CHArcI0Xf0fGZVY4jC/sBcp7cS9gZ4afDwPhXsRUAralP1HVQ57j5UhV5wEVcK65T8/iw78SsCXD8y1ACZz7M+m2kQPP5aQPReQ3EdkPTMT5Jp9nqvojcAhoKyIXAOfjnDVlddxVnktcB0XkjG/vueRcR0Smi8hOT85PZ8g583uC53nlHHZ5laqerarVVPWO7IpsBpWBPzM8/0hVz8Z531cCTb1+McY1VjiMLyTjXB66qhD2/TvOJSAARCQC5wzHGxNxbspmvkwFzjffahmenwekALsyLNNsfk43yrO8kaqWwbnUJFlsl1l2Q1KP9+zjRmCKqh7NMthpgRbpecz14ngZvYVzFlHbk/OjGXLO/J6A8778lsdjZMlzOaspcEbOqroHuA0YLiLn+uJ4pvBY4TAFpqp/A48Db4jIVSISISJhItJFRJ4r4O6nAF1FpLXnOvgTeP93+xrQkVM3ozOaBAwRkRqeJqRP47Twye4yyW6cS2Q1MyyLAg7i3OSuDDyQVaCX+wLn0lR3nOKRVbHLq7NEJDzDI8ST837goOfMZlCG7b8E6ojTrLqEiPQCLgSmFyQJz99DW2AqsNBznDOo6hrgK+DBghzPFD4rHMYnVPUl4F84l4Z241zmuYsz7y3kdb+rgDuBD3DOPv4CtnsZ+6eqztKsJ515D+eDOgnYhHPGdHcO+zoMjATme1okXQyMwGmG+jfOTeVPvMwrq32hqtuBpThnJHk9k8jKQZx7B+mPdsD9wPXAAeAdYHKGvPYCXXHO0vbifIB39ZwN5MdoETmAcxb3CvAx0FlVc7pH9TwwUET+kc9jmiIgNpGTMf5DRN4Ddqjq0Fw3NsYl1rHJGD8hItWBq4E4dzMxJmd2qcoYPyAiT+K0KnpeVTe5nY8xObFLVcYYY/LEzjiMMcbkiRUOY4wxeVIsb46XL19eq1ev7nYaxphCtnevM4hAuXLe9gk12VmyZMkeVfVqgMliWTiqV6/O4sWL3U7DGFPIxo0bB0D//v1dzaM4EJHMw81kq1gWDmNMcGjTpk3uGxmfs8JhjAlYNWtmHrXFFAW7OW6MCVg7d+5k586duW9ofMoKhzEmYM2cOZOZM2e6nUbQscJhjDEmT6xwGGOMyRMrHMYYY/LECkcmu3btok2bNpQpU4Y2bdqwa9eu3IOMMSaIWHPcTK655hrmz5+PqpKcnMy1115LUlJWE8gZY9zWvn17t1MISlY4Mlm2bBnpIwanpKSwfPlylzMyxmSnatWquW9kfM4uVWXSpEkTQkNDTz4/99xzXczGGJOTbdu2sW3bNrfTCDpWODJJTEykZcuWREZGcvbZZ7Nu3ToeeOABUlNT3U7NGJPJrFmzmDVrlttpBB0rHJnExMSQlJTEgQMH+OOPP7jzzjt54YUX6NatG/v373c7PWOMcZ0VjhyEhYUxevRo3nzzTb766itatGjBxo0b3U7LGGNcZYXDC4MGDeLrr7/m999/p3nz5syePdvtlIwxxjVWOLzUrl07Fi5cSIUKFejYsSPvvPOO2ykZY4wrrDluHpx//vn88MMP9O7dm4EDB7Jy5UpefPFFSpSwt9EYN3Tu3NntFIKSnXHkUXR0NNOnT2fIkCG89tprXH755fz1119up2VMUKpYsSIVK1Z0O42gY4UjH0JDQ3nppZd49913mT17Ns2aNSM+Pt6GKTGmiG3cuNEarLjACkcBDBgwgFmzZrFlyxZ+WrKE+gcOnBymxBhT+JKSkmxIIBdY4SighIQEzjrrLB4A5gFDUlJYtnSp22kZY0yhscLhA02aNOGNkBCmAM8BE0+c4MDvv7udljHGFAorHD6QmJhI41atuKV0aUaVLUvX48fZWaMGm775xu3UjDHG56xw+MDJYUoOHuSRP//k52efJfzECa7v3p3p06e7nZ4xxviUFY5CEPfgg6StWcPxunW54ooreP/660lLSXE7LWOKna5du9K1a1e30wg6VjgKSbXatZk3bx7PXHYZN0yaxI9VqrBv61a30zKmWClfvjzly5d3O42g4zeFQ0TeE5E/RGRlhmXPi8gaEflZRD4VkbPdzDGvSpUqxYMzZjC3Rw+a7drF3vPPZ/20aW6nZUyxsXbtWtauXet2GkHHbwoHMA7IPH7AN0ADVW0ErAMeKeqkCkpCQkiYMoXVr75KdEoKMd26Mf+hh9xOy5hiITk5meTkZLfTCDp+UzhUNQn4M9Oyr1U1/ebAD0CVIk/MRxrdcw8pP/7I9tKlefG553ioZElSRcDzSIuKcjtFY4zxit8UDi/cDMzIbqWIDBSRxSKyePfu3UWYlvcqNmtGrT/+4B+33cZzJ07wOKcqZcjBg26mZowxXguIwiEijwEpwPvZbaOqY1Q1XlXjK1SoUHTJ5dFZERG8/fbbTASuBo4CdoXWGBNI/L5wiEg/oCtwg6qq2/n4yg3AWcBhoC7wE6BHj7qakzHGeMOvJ5IQkc7AQ0BbVT3sdj6+lBYZSYODB9kDfA50A7ZWqkSFr7+mVHy8y9kZExi6d+/udgpByW/OOERkEpAM1BWR7SIyABgNRAHfiMhyEXnb1SR9KOTAAVClvCr/TEnh/d69Cf/rL/7TrRsbNmxwOz1jAkJ0dDTR0dFupxF0pBhd/TkpPj5eFy9e7HYaefbtpEn0vuMOUlSZ9sgjJPTvDzExbqdljN9audLp9tWgQQOXMwl8IrJEVb263OE3ZxwGOlx3HYuXLeOCmjWp9vDDHKxZk1TrMGhMthYvXkwgfkkMdFY4/Ez16tWZvWAB/+3Rgw2HDxParRuHBwyAI0fcTs0YYwArHH4pPDycEVOmsPw//+HV0FAi3nuPwxdeCH/+mXuwMcYUMiscfqzfwIG0WbSIvhUrMnbrVkafey6aobc5Zcq4naIxJghZ4fBzcXFxvLp6NTMvv5y7jx9nEHAofeWBAy5mZowJVn7dj8M4ypYty9SpU3kmNJRJwGqgDE7HQWOCWc+ePd1OIShZ4QgQISEhPApcBtQASuIMHdxBFRFxNTdj3BIREeF2CkHJLlUFkEOhocQDacA2oCPwZd26/L1nj7uJGeOS5cuXs3z5crfTCDpWOALIwd9+o01CArWiorizZUsWNGvGP9ev5706dVi0aJHb6RlT5KxwuMMKRwCJiYkhKSmJ/fv38/38+bRcuJBfnnmGMaVL06pVK159/nmK40gAxhj/YoUjwNV76CHm//QTV3fqxCUPPsjEevXY66fzkRhjigcrHMXAOeecw6RJkwhv2pQb165lWdWqJH/xhdtpGWOKKSscxYRERlJ30SK2PvQQbY4do2LXrrw7aBCpqalup2aMKWZsdNxi6NB333HkiitYd/gwD7VqxYmUFFavXk1sbCyJiYnE2Ii7ppg4ceIEAGFhYS5nEvjyMjqu9eMohkq3a0fE5s1sHz+eJQ88wLk4k7W3mjuXQ5UrQ0qK2yka4xNWMNxhl6qKKalQgZ73389i4F3gImA+EG6XrkwxsmjRImuK7gIrHMXchThFIwloBWwAds+b52pOxvjKqlWrWLVqldtpBB0rHEEgAmgHzALKAaXbtOGXhx92NyljTMDyunCISA0RuVpELijMhIyPRUWd/LE98Ed4OD+VKsW7zz3H008/TVpamnu5GWMCUraFQ0Q+y/DzlcB3wBXAVBHpX/ipGZ/Yvx9UTz7qHTlCgx072NmrF4899hjDmzdn3/TpbmdpjAkgOZ1xVMvw80NAO1W9CedS+ZBCzcoUqqjoaCZ+8AFvv/UWXZcuJeqKK9g2YIC1tjLGeCXbfhwislRVm3h+XqiqzTOsW6aqcUWUY54Fez+OvFg+dy4bL7+cqw8e5Lfq1an0/fdI9epup2WMKWJ56ceR0xlHYxHZLyIHgFgRqejZeUkg1Ad5Gj8Qm5BA++3beblZMyI3b+Zw7drsW7HC7bSMMX4s28KhqqGqWkZVo1S1pKru9KyKAG7LaaciUlZE6otITRGxllt+Ljo6mnt//JFPhg1jVFoaTRo3ZnGGuc3TMtxgN8afLFiwgAULFridRtDJ04e6iHRV1X2qmpzFumgReVREVgA/AP8BPgK2iEiiiFzqm5RNYRARbnriCbrOn0+qKjcA3wIKhBw86HJ2xmRt3bp1rFu3zu00gk5ezwaeyGHdFJyJ6RJUta6qtlbVeFWtCjwDXCkiA/KbqCkaF198McuATkAHYDdwCMB6nBtjPPI6VlW2k1urascc1i0BluTxWMYl5wCv4HwTqAk0AQ7VrUvp116DLl2cS1jGmKCV4xmHiISISMsMi3K8t+GJaSUipT0/9xGRl0SkWm5xxn+kRUYSAlwDpAB3A79v2MDxq64izSaJMibo5Vg4VDUNeDHD84Ve7PMt4LCINAYeBLYAEwqSpClaIQcOnOww2FyVp/btY1iPHrQ+cYLL+/blj127YOhQWLPG7VRNkAsLC7MRcl2Q63wcIjIC+Bn4RL2YvCO9/4eIPA78pqr/zdgnpChYPw7fU1XGjBnD4MGDiYuKYu6hQ5Q4fhxuvhmGD4dKldxO0RhTAL7qx5HuX0AicDy9X4eI7M9h+wMi8gjQB/hCREIB+0oQ4ESE2267jYULF7KvfHkqHzlCctOm6LhxcP75cNZZJ5vvIgJlyridsjGmkORaODz9OEJUNSxDv46cPhV6AceAAZ6+H5WB532Ur3FZo0aNWLRoEV369aPlwoX0jo3lUOfOcPz46RseOOBOgiaozJkzhzlz5ridRtDJtXCIo4+IDPM8ryoizbPbXlV3qupLqjrX83yrqto9jmIkMjKScePGMWHCBL5YvZpqSUnMdDspE5Q2bdrEpk2b3E4j6HhzqepNoAVwvef5QeCN7Db2DL2+XkT+9vLSlglQN954I0uWLKFKlSp0Ae4DjucWZIwJeN4UjotU9U7gKICq/gWUzGH754Buqhrt5aUtE8Dq1q3LDz/8wK0ivAR8AfwOHAqxkWaMKa68+d99wnODWwFEpAKQ0+w/u1T1F18kZwJDeHg4H0ZGEgM0BM4FflYFu/ZsTLHkTeF4DfgU+IeIjATmAU9n3shziepqYLGITBaR69KXeZabYiw2Npa9JUpQD6eX6HmqcMklpHboANu3u52eKaYiIiKIiIhwO42gk2s/DgDPdLHtcYYcmZXVGYWIjM1hF6qqN+c7yzyyfhxFb9euXVx77bUsX76cRo0a0axBA0L+8x9uDQ+HBQu4IC4ODh8G+09ujF/KSz+OnCZyOienQFX9M5u4Vqo6P7dlWcS9B3QF/lDVBhlymAxUBzYDPT33WHJkhcM/zJgxg7433sjhI0d469VXufHZZ5EWLZwOgzVrup2eMSYDX3UAXAIs9vy7G1gHrPf8nNOAha97uSyzcUDnTMsexjnDqQ3M8jw3AaJLly789PPPNG/enEG33soXJUuiiYlQty7ccQfs2OF2iibAffvtt3z77bdupxF0sh0dV1VrAIjI28Dnqvql53kXnBG3TyMiLYCWQAUR+VeGVWXwYsZAVU0SkeqZFl8JXOL5eTwwG2f+cxMgKlWqxLfffsvIkSO5csQIWlavzifx8VR45x14663TN46Kgv3Wctt4b7vdP3OFNzfHm6UXDQBVnQG0zWK7kkAkTjGKyvDYjzPQan7EqOrvnuP+Dvwjuw1FZKCILBaRxbttBFe/EhoayuOPP853333HxqNHqTp1Kv8bOpQzLpJab3NjAoI383HsEZGhwEScJrl9gL2ZN1LVOSIyD2ioqiN8m2buVHUMMAacexxFfXyTu7Zt27J8+XL69+9P3+HD+RT4L1DW7cSMMXnizRnHdUAFnCa5n+F8678uqw1VNRVnHiBf2SUi5wJ4/v3Dh/s2LqhQoQLTpk3jhRdeYBoQB3gzVr8xxn94M8jhn6o6WFXjPI/B2bWo8lgmIp+LyI0+6MfxOdDP83M/YGo+92P8SEhICPfddx9f4VzfLAusAexClcmrMmXKUMZGYi5yuV6qEpE6wP04TWJPbq+q7bIJOQfnUlbG9Qp8kstxJuHcCC8vItuBf+PMVf6RZ67yrcC1ueVrAsfwhAR2zJ/PpLQ0/gWcBRzu35+IUaPg3HPdTs8EgKuvtr7FbvBmIqefgLdxmuCmpi/3zCPul6wfR2BI7zS4bNky6pcvT7+tW7klLY2Q8HBCf/wRGjVyO0VjgkZe+nF4c3M8RVXfym0jEXlQVZ8TkdfhzAYzqnqPNwmZ4BETE0NSUtLJ5z/99BOXd+9O+02bODplCkMvvJASS5c6BSQ83MVMjb+aOdMZ0L9z58xdwExh8qZwTBORO3Bujh9LX5jFfY70YUjsq77Jl8aNG/Ppzz9z1113Mf7JJ/lh1iy+XLmSkOhoGDEC+vaF0Fy7BJkgsnPnTrdTCEreFI70m9MPZFimwGljRqjqNM+/4wFEpIzzVO2ep/Fa+iRR7du3Z9CgQfQIDWVseDhn33wzvPACbNwIR4+eCrBOg8YUOW9aVdXI4pHtQEMiEi8iK4CfgZUi8pOINPVl0qb4S58kamP16pRdv57xV1yBnjhxetEA6zRojAu8aVXVN6vlOUwH+x5wR/rUsSLSGhgL2J1Okyd169blxx9/5L777qP/m2/ydnw8n+DM92GMcY9XQ45keCQAw4FuOWx/IL1oAKjqPKyJvsmn8PBw3njjDaZMmcIv69dzAZDodlLGb5QrV45y5cq5nUbQ8Wo+jtMCRKKB/6lqt0zLm3h+vBGIACbh3AvpBfylqo8VPF3vWHPc4mnTpk30qlmTRTjDLQ8A0kJDKZ2S4nJmxgQ+XzfHzewwUDuL5S9mev7vDD/b2FGmwGrUqMEvkZGEHjxID5xe558BPX78ES66yOXsjAke3tzjmMapD/4Q4ELgo8zbqeqlvk3NmDPFxcWRnJxMs5QU7gZuS02Fiy9GW7VCXngBLr7Y7RRNEZo2bRoAV1xxhcuZBBdvzjheyPBzCrBFVW0QfOOKxMTEk1PUfnrhhcwvVYoas2fz6NKllPzzT2ek3T17nClqbZraYm/v3jMG6jZFINfCoapziiIRY7yRube5qjJ69Ghq3H8/0QMGMGHCBDpOmQIff+zMMnjnnRAT42LGxhQ/3rSqMsZviQh33303PyxaRNmyZbnssst448AB0lq2hKeegmrVoGRJEDn1sNFUjSkQnxcOEYkQkWEi8o7neW0R6err4xiTUaNGjVi8eDG33XYbd02aRPMdO9g0YwbcdBOcOHH6xtZp0JgCKYwzjrE4Y1q18DzfDjxVCMcx5jQRERG8/fbbfPzxx2zcuJGGPXowtnlza9JXjFWsWJGKFSu6nUbQyU8/jvE4TXLfUNWVWaxfrKrxIrJMVeM8y35S1cY+ydgL1o/DbN++nT59+jBnzhx64cwLcHbGDfL4d29McZeXfhz5OeMYDXyL09EvK8dFpBSeJrwiUosMo+oaUxSqVKnCrFmzGDlyJFOAWGCBZ11aZKSLmRkT+LwuHCJSGkBVF6nqx6r6UDabDgdmAlVF5H1gFvBgQRM1Jq9CQ0N59NFHadC4MVuAfcBc4MlKleCYfZcpDj755BM++STHyUVNIci1cIhISxFZjWe+DRFpLCJvZre9qn4NXA30xxl2JF5VZ/skW2PyYePGjYBzmnwu8O9160itVAkefNAZpt0ErP3797PfhtUvct6ccbwMdMKZRxxV/Qlok93GIvI5cBkwW1Wnq+oeXyRqTH7FxsZSokQJXgYuEKFzSAhfHDhA2osvwuTJzkYpKc7DGJMrry5Vqeq2TItSs9zQ8SLOKLqrRSRRRK4REZv307gmMTGRFi1aEBUVRcvWrRmxYAEj4+KokpbGPatXc+jQIUhMhOrVnZkGf/vN7ZSN8WveFI5tItISUBEpKSL3c2qa2DOo6hxVvQNnhsAxQE/gD59ka0w+pPc2379/P0lJSVx00UXMmzePfg8/zOj336dp06asO3IEGjZ0Cke1ahAWZp0GjcmGN4XjduBOoDJOn4xY4I6cAjytqnp4YpsB4wuWpjG+FRYWxqhRo/j22285cOAADQcN4uXLLiNt3Tq4//4zL1tZp0G/VKVKFapUqeJ2GkEn134cItJKVefntizDusnARTgtqz7CudeR5qN8vWL9OExe7NmzhwEDBvD555/TuXNnxo0bR0xWncqs74cpxnzdj+N1L5elGwvUUtXbVfW7oi4axuRV+fLl+eyzz3jzzTeZPXs2jRo1YqbbSRnjx7IdHVdEWgAtgQoi8q8Mq8oAoVls305Vv8OZ/e9KETltvapaY2vjt0SEQYMGkZCQwHXXXUeXP/7gXuAZ4CycToM2Iqj/+egjZ2qgnj17upxJcMlpWPWSQKRnm6gMy/cD12SxfVvgOyCrGVUUsMJh/F6DBg1YuHAhtWrV4pXff2cnUEKEHY0bM8vt5MwZDh8+7HYKQSnbwuGZh2OOiIxT1S257UhV/+359yYf5mdMkStVqhQHDx4EnF6snVT5Y/589NFHkUGDoGpVV/Mzxm3ezAB4WESeB+oDJ/tjqGq7jBtlupx1BlV9KV8ZGuOC2NhYkpOT6ZKSQgecZoVdR40i5NlnkSefhEcfdTtFY1zjzWXb94E1QA1gBLAZWJTFdlG5PIwJGOmdBiOjojjSujW/jBrFhWedxaslSzLv+HFno23bYPRosCEvTJDxpjnuElVtKiI/q2ojz7I5qtq2SDLMB2uOawrDmjVruOGGG1i6dCkDBgzgjXr1OOv++yEyEm68EcaPh4zX3KOirKgUsjlznJmt27b124+jgJGX5rjeXKpKnz7tdxH5J7ADsB43JuhccMEFJCcnM2LECEaNGsXsmjX59L//pWFSErz33pkj7lqnwUJnBcMd3lyqekpEooH7gPuBd4EhhZqVMX6qZMmSjBw5kjlz5pCSkkLcwIEMr16dlM2b3U7NmCKTY+EQkVCgtqr+raorVfVSVW2qqp8XUX7G+KWEhAR++uknbrjhBkaMGEHrq67iV7eTCkLvv/8+77//vttpBJ0cC4eqpgLdvN2ZiHQSkbdE5HMRmer5uXOBszTGD0VHRzN+/HgmT57MunXriMU5HU+/a2gzDRa+EydOcOLEidw3ND7lzT2OBSIyGpgMHEpfqKpLM24kIq8AdYAJOIMhgnMv5B4R6aKqg32TsjH+pWfPnrRs2ZKGDRty6759jAFCQ0IIi40lye3kjCkE3hSOlp5/n8iwTIF2mba7XFXrZA72DHq4DrDCYYqtKlWqkOIZUfffwD/T0lg+fz68/TbccIPTwsqYYiLXm+Oe+xqZH5mLBsBREWmexfJmwNECZ2qMn4uLi6NEiRJcBwwCZzTdQYPQc8+Fp55yOTtjfMeX47b1B14XkdUi8rXn8QvOSLr9fXgcY/xSeqdBoqJY0aoVE+69l5YhIXwErPnDM5fZ4cPw3/+CZ0gTUzB16tShTp0zLnSYQpZrB8A871CkIs6kTwJsV9WdPtjnEOAWnEtkK4CbVDXbsxjrAGj8xcKFC+nbty9r167lrrvu4oWLL+asPn2cS1d9+linQeM3fD0fR14OHI0zSm5bnHnH24rI2QXcZ2XgHiBeVRvgDOneu6C5GlMUmjdvzrJlyxg8eDCjR4+m0YgRrBozBrp3h7FjTy8aYJ0GTUDItXCIyGIRuVNEyuayXV9gKXAJzpwcpYFLgSWedQVRAiglIiU8+95RwP0ZU2RKlSrFK6+8wqxZszh67BiNbr+doVWrcnzTJrdTC3jjxo1j3LhxbqcRdLxpVdWMW8wvAAAgAElEQVQbuAlYJCKLcWb4+1rPvMb1GNBUVfdlXOgpOD/iNNPNM1X9TUReALYCRzzH/jrzdiIyEBgIcN555+XnUMYUqnbt2vHzzz8zZMgQRo4cyRdffMEEoKHbiRmTR960qvpVVR/D6aPxAfAesFVERojIORk2FU71fcoozbMuXzyF50qc0XkrAaVFpE8WeY5R1XhVja9QoUJ+D2dMoYqOjua9995j6tSp7Nixg3jgWSDVs946DZpA4M0ZByLSCOes43LgY5yh1lvjzPgX69lsJLBURL4GtnmWnQd0BJ4sQI4dgE2qutuTyyc4fUsmFmCfxriqW7dutGjRgnr16vHw3r18DFQOCWFf48Z873ZyxuTCm3scS4CXcebgaKSq96jqj6r6IrAxfTtVHQ/EA3OAY8BxYDbOTe1xBchxK3CxiESIM5F5e+CXAuzPGL9QoUIFjnlG1L0D+DQtjY/mz0fvuQeWLnX6gRjjh7yZj6Omqm7MtKyGqhbZnT0RGQH0AlKAZcAtqnosu+2tOa4JFG3atCE5ORlSUugM9AWuFKGkKnTtCtOmuZ2iX1u0yJlTrlmzZi5nEvh83Rx3ipfLckpoRV62z0xV/62qF6hqA1W9MaeiYUwgSe80WCoqin2tW/P7q69SJzKSe8LC+CYqirS0NDh+HHr3hsmT4agNwpBRs2bNrGi4INt7HCJyAc4849EicnWGVWXIMPd4hu2vzrwsfRVQsSBJGlNcxcTEkJR0+lCIPXr04LbbbuOySZNovW0bE4cOpdr8+U7hiI6GXr1g4kTrOAgnR8YNCwtzOZPgktPN8bpAV+Bs4IoMyw8At2ax/WScm+ZZXfs6o9AYY7JWuXJlpk2bxoQJExg8eDD1unfnmZEjuat+fUImTjyzaEDQdhxMn4ujf//+7iYSZLItHKo6FZgqIi1UNdmLff0MvKCqKzOvEJEOBcjRmKAjIvTr148OHTowcOBABv/rXyS2bs3YsWM5/403oEwZt1M0QSzbexwi8qDnx+tF5LXMjyxC7gWyO1fuXtBEjQlGlStXZvr06YwdO5YVK1bQqFEjXn3vPdLcTswEtZxujqc3eV0MLMnicRpVnauqW7PakapaEydj8klE6N+/P6tWreLSSy/l3nvv5ZKQkNOmqrWOg6Yo5XSpaprn3/FFl44xJjvpZx/jx4/nlltu4UGcIRUmh4RwJDbWOg6aIpNtPw4RmUbWN7oBUFWv5yIvataPwxR3kZGR9D90iKdwWq/8Afzj7rvh+uvhootA8j3KT0BZvnw5ALGxsblsaXKTl34cORWOtjkFquqcLGJCgGtU9SNvDl5YrHCY4q5NmzYsWLCAEqmpdAGuB64MDSW0dm1CV692CsfOnVDRWsIb7/ikA6CqzsnpkU1MGnBXPvM2xngpMTGRli1bUjIqil0tWvBFv36UT02l819/Mf2LL+DIEahTB2Jj4bnnYNs2pyWWyKlHMWiZdfjwYQ5nbppsCp03Q47UBkYBF5KhP4aq1sxm+2E4w59PBg5l2P5PH+TrFTvjMMFowYIFDBw4kFWrVtGne3dGN2lC9BdfwA8/ZB8U4ONhpc/FYf04Cs7XQ46MBd7CGSfqUpx5Nf6Xw/Y3A3cCSZxqgWWf4sYUspYtW7J06VKeeuopEr/8kmovvMDb/fqRtm4dPFmQAaqNOZ03haOUqs7COTvZoqrDgXbZbayqNbJ4ZHl2YozxrZIlS/LYY4+xYsUKmjRpwqBBg0jo359V3a0rlfEdbwrHUc9N7/UicpeIdAf+kd3GnuHPh4rIGM/z2iLS1Uf5GmO8ULt2bWbNmsXYsWNZs2YNcXFxDA0LI+MQidb3w+SXN4XjXpx5vu8BmgJ9cEZ/zs5YnLk4WnqebweeKkCOxph8SO84uGbNGnr37s3IEyeIBQYAZUNDuSQuzu0UTYDypnBUV9WDqrpdVW9S1R44M/tlp5aqPgecAFDVIxRg6lhjTMFUqFCBCRMmUKpUKXoC/wW2paYyIDkZ5s8P6Bvk8fHxxMd7dT/X+JA3heMRL5elOy4ipfB0HhSRWjgzAhpjXBQfH8/TISG0xGny2CMlBVq3Rps3D9ji0aBBAxo0aOB2GkEnp/k4uuDMMV4506CGZXBaWGXn38BMoKqIvA+0AvoXPFVjTEEkJiZy7bXXsnz5ct6qU4fE8HAqzZ9P7O+/03LJEuKbNoUhQ6B9e+jSBUrkNOuCf/j7778BiI6OdjmT4JJTz/HGQCzwBPB4hlUHgO9V9a9sdypSDrgY5xLVD6q6x2cZe8H6cRiTO1Vl8uTJDBkyhF27dvFwv3489cUXhOze7fQ479cPRo+GQ4dOBfnZhFHWj8N38tKPI6dBDn8SkZXAZfkY6LAt0BrnclUY8Gke440xhUxE6N27N126dGHYsGE8+8YbTChfng+GDCHh11+RF16A1NTTg4J0wihzuhzvcahqKlBOREp6u0MReRO4HVgBrARuE5E3CpSlMabQREdH89prr7Fw4UIqVatG25dfpuPhw/z63Xdup2b8lDcXMbcA80Xkc04fQuSlbLZvCzRQzzUwERmPU0SMMX6sadOmJCcnM2bMGB555BHqd+zIg8CjQCm3kzN+xZtWVTuA6Z5tozI8srOW05vrVsWZVtYY4+dCQ0MZNGgQa9eupWfPnjwFdOTUN79DoaEuZmf8Ra6DHJ7cUCQKUFU9mMt2c4BmwELPomZAMnAYimYeD7s5boxvREREcPORI4wGjgJfhIbSY9o06NjRL1pdrV27FoC6deu6nEng88nN8Qw7a4AzqOE5nud7gL6quiqbkMezWW6MCTDx8fG8PX8+C9LS6A9cn5oKl19OWtWqhKxfD2ed5Wp+VjDc4c1XhjHAv1T1ewARuQR4h1NDiuBZLurIcq6O9G0KkKsxpohl7Pvxfr16zK9UieOffUaLAweo/eWXXHXVVchdd0G9enDddVCuXJHmt2eP09K/fPnyRXrcYOfNfBw/qWpjL5bNBj4Gpqrq1gzLS+I0ze2H0/9jnG9Sz55dqjKm8CQlJXHXXXexYsUKurZvT+LvvxO+ejWEhcEVV8CMGc5EUukKse+H9ePwHV/Px7FRRIaJSHXPYyiwKYvtOgOpwCQR2SEiq0VkI7AeuA54uSiKhjGmcLVp04alS5fy2muvMXfxYsqsX8+rN93E8YEDYd6804sGWN+PYsibwnEzUAH4BKcjXwXgpswbqepRVX1TVVsB1YD2QBNVraaqt6rqch/mbYxxUYkSJbj77rtZu3Ytffr04d6xY6n52WdMfvFFAnPUK5MXuRYOVf1LVe9R1SaqGqeqg3MabsQTc0JVf1fVfb5L1Rjjb2JiYnjvvfdITk4mJiaG3jfeSDucnr+m+MppkMPPcwosima1xpjAcPHFF7Nw4ULeffddHr39dq4BPgBqAmEhIZR2OT/jWzkNcrgb2AZMAn4k05waObWecpvdHDfGPVFRUbQ+eJBxQAzwNxDRpw9h/frBpZeCDzsRbty4EYCaNW126oLy1c3xijijDTQAXsXpQLpHVef4c9EwxrgrLi6Ob0uUoDLQCefm6NH33ye1c2dO7N3rbLRnj0/mAKlZs6YVDRdkWzhUNVVVZ6pqP5wh0n8FZovI3UWWnTEm4CQmJtKiRQsioqI4kpBAxS+/pEerVrRJTeXCVq346KOP0CuvhPPPh6FDYfVqKFMGRE49ypTx6lg7d+5k586dhfyKTGY59uMQkbOAf+I0p60OfA68p6q/FUl2+ZTVpaoTJ06wfft2jh496lJWJr/Cw8OpUqUKYWFhbqdi8klVmTFjBg899BArV65keI0a3F2uHOcsXQppadkF5bpf68fhOz4ZcsQzqm0DYAYwQlUDuqHE9u3biYqKonr16lgH9sChquzdu5ft27dTo0YNt9Mx+SQiXH755XTq1ImJEycybNgwhi9ezHXt2vF8s2ZUfvZZt1M0eZDTPY4bgTrAYGCBiOz3PA6IiP9MAealo0ePUq5cOSsaAUZEKFeunJ0pFhOhoaH069ePdevW8fzzzzNz2TKqPvccfXHmbzCBIad7HCGqGuV5lMnwiFJV7y5A+hkrGoHJfm/FT3h4OPfffz8bNmzggQce4COgFbAU2A8cCvGmb7Jxi/12jDGuKVu2LM8++ywlSpemGlAZKAOEp6WRctFFMHIk7NrlcpYms4AoHCJytohMEZE1IvKLiLRwO6f82LlzJ71796ZWrVpceOGFXH755axbtw4RYdiwYSe327NnD2FhYdx1110uZmtM0WnSpAkLS5TgXKA58CTw85IlMHQoR/7yDFQxfz5MnQoHT00J1L59e9q3b+9GykEtIAoHTj+Smap6AdAY+MXlfPJMVenevTuXXHIJGzZsYPXq1Tz99NPs2rWLmjVrMn369JPbJiYmUr9+fRezNaZopTfhjYyKIjwhgdbffMOwTp2oANS89FLefPNNUkePhquucoZu79QJwsOpet55VD3vvDw14TUF5/4UXrkQkTJAG6A/gKoeB44XZJ/33nsvy5f7dszF2NhYXnnllWzXf//994SFhXH77befFrN582ZKlSpFvXr1WLx4MfHx8UyePJmePXuyY8cOn+ZojL+KiYkhKSnptGUdOnRg3rx5PProo9x55528Uq0arz/4IB2PHydkxgw4doxtVasCUHXbNhuFtwgFwhlHTWA3MFZElonIuyJyxtA3IjJQRBaLyOLdu3cXfZa5WLlyJU2bNs12fe/evfnwww/Zvn07oaGhVKpUqQizM8Y/tW7dmjlz5jBz5kzKlC9P5+eeo8FXX/HxyJEoMKt9e2bZpaoi5/dnHDg5NgHuVtUfReRV4GFgWMaNVHUMzmyFxMfH59hzKKczA7d07tyZYcOGERMTQ69evdxOxxi/ISJ06tSJyy67jE8//ZShQ4dyzTXX0BS4Hs+c1nlxySXOv7Nn+zLNoBIIZxzbge2q+qPn+RScQhJQ6tevz5IlS7JdX7JkSZo2bcqLL75Ijx49ijAzYwKDiHD11VezYsUKxo8fzx6cm51HcT4kjoaEFNpMg+Z0fl84VHUnsE1E0melbw+sdjGlfGnXrh3Hjh3jnXfeObls0aJFbNlyqtvTfffdx7PPPku5Ip632ZhAEhoaSt++fdkbGUkYcBgoi9OEV8uWhdatwUbHLlSBcKkK4G7gfc/85RvJYgZCfycifPrpp9x7770888wzhIeHU7169dMum9WvX99aUxnjpbi4OI6KsEKV8iIkhIZySUoKV//8MwfWraNZfDx89BFMngwdO8Jll0Fs7Kmb6CKFOh96cZbjIIeBKqtBDn/55Rfq1avnUkamoOz3ZzLbtWsXN910E2vXrqVy5cpMmDCBqVOn8swzz7Bz5046dOjAW/HxnP/BB7B1a/Y7Koafgfnhq/k4jDHGb8XExPDll1+yYcMGkpKSqF69OoMHD2bDhg289NJL/Pzzz9R+5hk61a3L8smTYfRot1MuNqxwGGMC1saNG0/OApguIiKCIUOGsHHjRp5//nmWLV9OXK9edJk+nYX5PdAll5xqjWWscBhjAldSUtIZHQfTlS5dmvvvv5+NGzfyzDPPsGjRIi4CunJq6IlDPpzGNphY4TDGFGuRkZE89NBDbNq0iZIlS7IBqAecAH5OS0MfewxmzYIjR1zONHBY4TDGBIWoqCguuugiXgFGAy8Aokrq009Dhw4cmzjR2XDnTkhKgmPHXMzWvwVKc1xjjCmwxMREdtStS8TBgzzaogXlbryRR/7zH0otXcqGhx6i17Zt3B8RQZlHHoFSpaBlS5g7F457hsezJryAnXEUqeyGVd+8eXOehlYfN24cIsKsWbNOLvv0008REaZMmeJ1PrNnz6Zr164F3saYQBETE0Pcvn0kpKQwd+5cBg4cyHeLF/NIUhL12rThqaeeova//83ojh3585prYPfuU0UjnQ2maIWjqOQ0rDqQ56HVGzZsyKRJk04+//DDD2ncuHHhvQBj/FDXrl0L/MVGREhISOCzzz5jzZo1XH3zzTwwdy7l/vc/ulatyjwgXz09inFLLCsc2SlTxjktTX8UcKz/7IZVT0hIADhtaHXg5NDq2UlISGDhwoWcOHGCgwcP8uuvvxIbG3ty/axZs4iLi6Nhw4bcfPPNHPNcr505cyYXXHABrVu35pNPPjm5/aFDh7j55ptp1qwZcXFxTJ06tUCv15iiUL58ecqXL++z/dWpU4e33nqLrVu3MmLECBYuXEgCEA/MBeyuh8MKR3Yyn44W8PQ0t2HVIW9Dq4sIHTp04KuvvmLq1Kl069bt5LqjR4/Sv39/Jk+ezIoVK0hJSeGtt97i6NGj3HrrrUybNo25c+eyc+fOkzEjR46kXbt2LFq0iO+//54HHniAQ4cOFeg1G1PY1q5dy9q1a32+3woVKvD444+zZcsWXgNKAgnAWcAB4FCXLvDaa5CpD0mwsMLhRzp37sw333zDpEmTvBpaPb3QfPjhh1x33XUnl69du5YaNWpQp04dAPr160dSUhJr1qyhRo0a1K5dGxGhT58+J2O+/vprnnnmGWJjY7nkkks4evQoW3MapsEYP5CcnExycnKh7b9UqVIkJiTwNPBfYADwCbB75kwYPJiVL79MWloa/PYbvPiiM7hiSopzhWLOHOdRDGcntMJRRHIbVh3yPrR68+bNWblyJXv27DlZJMC5n5IdEclyuary8ccfs3z5cpYvX87WrVttbChjcO43nh0dTZ3QUNYnJNBwyRLeGzaM+PLlSRg9mtq1azP14Yfh/vuhWTM45xyfX7HwN1Y4shMVlfPzPMpuWPU5c+actl1eh1YfNWoUTz/99GnLLrjgAjZv3syvv/4KwP/+9z/atm3LBRdcwKZNm9iwYQPAaTfXO3XqxOuvv36y6CxbtizvL9KYYihjS6ykpCSaNGnCE088wYLffuPtDz+kSpUqXDVxIjVKluStNm3Yddll+buZDgFzQ90KR3b273dGzUx/FLDddvqw6t988w21atWifv36DB8+/Iz7GPXr16dfv35e77dLly5ceumlpy0LDw9n7NixXHvttTRs2JCQkBBuv/12wsPDGTNmDP/85z9p3bo11apVOxkzbNgwTpw4QaNGjWjQoMFpTYONMWcqWbIkvXr1Ys6cOaxYsYLLb7mFB5cupeLHH9MMmIgzV0hxZMOqm4Bgvz+TlXHjxgHQv39/V/NId+DAASZOnMjrd9zBL8Am4DjON/SaM2YQ0qpVzlcvXJzW1oZVN8YEhe7du9O9e3e30zgpKiqKQYMGsS0ykteBRcCfQHUgpEsXUqOj+X3IEGfj1FT46y/Xci0IG3LEGBOwoqOj3U4hS3FxcTScOxcFWoeG0rhWLS4vW5bwhQv55pVX2Pf999zXti19Xn8dadgQ2rSBd9+Fo0edHfj50CZ2xmGMCVgrV65k5cqVbqdxhsTERMpERxMaGkrLli35MimJJ3/4gYG7dnHt6NGEh4fz2Guv8bgqS7Zv58Q775wqGun8uCWWFQ5jTMBavHgxme9n+oPMLbFiYmIAp2PhnXfeyQ8//MCsdesI/fe/6VW2LBHHjtEGeB+YhzPku9dcaIllhSMnAdI0zhgTeGrXrs3w4cNZv349SQsW0BAYDJwPpAArgc2PPopu3+5qnlmxwmGMMS4SEVq0aMFzoaHswGmJNRuIBKqPGoVUrcr3HTuyadOmU90DXGaFowgVp2HVZ8+eTXR0NLGxsScf3377rdfHNsac7uBvv7EqOpqU0FBGJSRwfM0aPh4xgjE1avDot99Ss2ZNbo2N5VDZshzt1w+mTXNuoLswtIkVjiJSHIdVT0hIODlEyfLly+nQocNp61XVGccng9TUVK/27e12xhQXMTExxMXGktC6NUlJSdSpW5cejz/OwI0bmbxlC6NGjeLPAweY8fffnJgwAbp1I/XgQU77n1JEN9StcBSRYBlWffPmzdSrV4877riDJk2asG3bNiIjI3n88ce56KKLSE5Ozja36tWr88QTT9C6dWsSExPzdXwTXHr27Jnj/5Pi4rzzzuPhhx9myoYNnL9sGU/ecw+9ypblDWAdcAdF20vdCkcRKY7Dqs+dO/e0S1XpY2CtXbuWvn37smzZMqpVq8ahQ4do0KABP/74I/Hx8Vnmli48PJx58+bRu3fvHI9tDEBERAQRERFup+E7s2fn2GtcRIiNjeW5V1/lg927qQeMAhYCpYomQ8AKh18JtGHVM1+qqlWrFgDVqlXj4osvPrldaGjoydF+s8stnTev25h06X97wSg0NJSWoaFMwOmhLsCh0NAiObYVjiISTMOqly5d+rTn4eHhhHr+oHMbGy1zrDE5CebCAc4N9WXR0cwLDaVNQgIHf/utSI5rhaOI2LDqOedmjMm7zDfU0zsaFjYrHEWkOA6rnvkehzdNgbPLzRgTOGxYdRMQ7PdnsuJvw6oHMhtW3RhjTKGxYdWNMQHrhhtucDuFoBRUhUNVs21VZPxXcbycanwjLCzM7RSCUtBcqgoPD2fv3r32IRRgVJW9e/cSHh7udirGDy1atIhFixa5nUbQCZozjipVqrB9+3Z2797tdiomj8LDw6lSpYrbaRg/tGrVKgCaNWvmcibBJWgKR1hYGDVq1HA7DWOMCXhBc6nKGGOMb1jhMMYYkydWOIwxxuRJsew5LiK7gS0F3E15YI/FWIwfxxTlsSym+MdUU9UKXkWqqj2yeACLLcZi/DnG3/OzmOIXk/6wS1XGGGPyxAqHMcaYPLHCkb0xFmMxfh5TlMeyGIs5qVjeHDfGGFN47IzDGGNMnljhMMYYkydWOLwgIuEikqeBrophTJ7Ho7cYi/H3mKI8VnGKscKRgYiUymZVbeBTEYko7jEZYjP/IdUUkTtFpKTFWEygxvh7fv4cc5r8dgApjg9gFlDO83NJoCLQAugJHAeaBkHMIKBHhufpDSjKAD9ajMUEYoy/5+fPMVk9gmZYdS+FAP8RkX3ABThv5nFgG/A8sCMIYvoCVUWkFfCWqq4HUNX9IrIEuBhYYjEWE2Ax/p6fP8ecwQrH6X4CugH3A+8BK1V1f5DFfIZzZvIT8I6IfAW8DZyLU3iyircYi/H3GH/Pz59jzmCF43QLgH2q+kn6AhGJBpoDZ6nq9CCI2Q5cqKrjRWQ9cB2QDCzzrPvSYiwmAGP8PT9/jjmTN9ezguUBRANXABGe5w2BFcAvwMfAk0EQcz7w30zL/gHcCDTO5n2zGIvx6xh/z8+fY7Lcj7cbBsMDEGA0cLbn+QfAlRnWrwJiinOMZ3kVoBMwFfgN+BPn7GUsMBQobTEWE2gx/p6fP8ecsY+8frgW9wewHqjq+TkJiMuw7jugVRDExOFc9xwE1MiwvDIwH+hoMRYTaDH+np8/x2R+WD+OM30DPCAi/wCeA24QkZtF5D7gK2B1EMQMBn5T1bdUdVP6QlX9DecbSh2LsZgAjPH3/Pw55jR2c/xMzwPdgWdx+jxUBDYDnwNvq+pfQRCzHqgnImer6j4AEWkAXIXzh5XVTXWLCY6Y+p6Y7cAXARbj7/n5c8xpbHTcbIhIXc+P61RVPd/YVVV3F/cYEakN9MPpYd4Qp6neLpyzlzGqusJigiqmliemEvA3ziXOV1X150CK8ff8/DnmjH1Y4ciZiJTAuWFUFadD3Y+q+nYwxIhII+AvnG8hApQFDqjq8Rz2bzHFL6YZcARYo6opGZZHqurBQIvx9/z8OebkNlY4ziQig4HJqrpTRIYC9XBuJpUChgN9VHVjcY7xxEUDNwFtPNvuBlJw2nyPU9UDFlP8Y7IiIuWBh4GXPdfGAzrG3/PzuxjN5e55MD5welUmeH6eBrTMsG4K0DMIYmrh9DZ/FugI1AcuBP4JzASuspigiLkJqJLheWngPKAVsAe4IZBi/D0/f47J+LCb41mbD1wCzAVmAJ09l3jq4nTJX14MYsJyiekFHMM5I0nVU5cyVotIW6AlzvAFFlO8Y64CLhORyThFJgqIAA7hNO/O6pKGP8f4e37+HHOSFY6svQtcJyKzcK4BlsPpmj8bmIzTKiEvMZNUdZ2XMb1wblJ9kMtxvgMOA+WB3ji/7Ml5PM4s4MNsYk4A0ap6BE5e4jgf55tqZZymvbnFlClgTJV8Hud5L19PrSJ4PenvW4cieg8u88Q862VM7VxiZgAP4Zy1huIMkLkH58b6eGCrlzG7CxAzAdjio+MURn5FGbOtkI/zB9m/3ydZ4ciCqi4Vkc1AI5w3NQxYqxnaPGcTswmI9ywS4FfN4t5BppiNOB1yQnCGPt/qiTuWS26NPccoAWxV1TW5HGeL5/WEeF7Pr8BOzf4m2BSgiogs8OS1G+fb6p/AFFX9KYeY+Z6YP4FUYC+QCGTVWmMKcF42MRNVNauzoSk4I3xmFTM5h5j013OW5/WA8yE4OYfXk/k44NxcTsQZviW392Avzgf2PuDjPL5vf+IU9pxeTzLO73MvkIbzYfEB2b/XmY9zHGeU5InZxKwGIlX1GW9ummYRU1pVD3kR8wtQJh8xUXmMOZkfTqEs7eVrys+x8vM+5Dcmiry9nvwc5yS7Oe4lETkPaILzIf8PYLDm3BKlCk7LpQbALlX9PJvtQlQ1LZt17wO3pH9DzGL9+Tj/6Y8Ct+Hc8HxbVed48Xra4lzPbAS8qapJWWxTBuc178YpUGnANvW0/c5mv2d79rkf5wPzT1X9PZdcSnpy+Qvng+xPVd3pWfcPVf0ji5izcIr0IU/MX+nHEZEwVT2RRUyk5/XswikemzWX0YLFmQyrKc6p+3GcIp1zixORKKAZTlFKA46o6oZcYtJz28+Z70FNYJNm+s/q+f3U88QIzheBP8mB5wyosSfmGM77F4LzN3rG35k4k33dqqqvep4LzvXw1Bz+LiOA21T15QzLBOfzJru/9QjgZlUdnSkGz/FSVPWoFzEhOM3Ms/1g88TdoqqvpR9HVdVzvBBVTc0txmpa9JIAAAxLSURBVBuZ37v0/NLfg/Tj5nac9PfBk2OZzH+znpiBqvpKHnM77XfkWX4usDenzzawwpEtEbkL+EpV14tIaZwOc0eB74HbgWtVdVkWcfcB/+JUO/mFOB/ufwGv5/Yh6tlHiKqmeb4d36WqSzOtr45z+SkM5z/9lzhFYyHOePoPaKa22PL/9s492OqqiuOfFW8hRECxq4BI40wpgpPyStJRA8RXIFGWZYYjYlqYjmnlAx1xEjEbxVdpEoxOXjLUpqxIRKAybyq+8hkq5mSCT1Dk0eqP7/5xDr+7z733KBg16ztzZ+4557d+e//2b+313nubHQ086u4rzOxA4CpUw/8qcAjwnTJNFe1IJNg/mtocgBaMNdbyjDL32B04FbjJ3Z8t/dbP3Zu502bWF7gImOnuT5R+6wmsc/d3MnTXAbM9szYh/X5eeo47gBfcfVUL/d7CyjazvdA+PyOQ4jq2hXYagFEonNgN2BmdgdCiEqmib+fum8xsDnBFzlsxs13RRpbLgaeByYgX7geud/fVrbRxHNotuQF5UNfWokl8N5TKFtx7ALcBv6+lEDL32A0dJPaL3DuvQdMXhVWucvenMr/vCLyVEcI/RBv6PdbCvU9B87oJRRU25AR61fWdCp5PCv0gpPD3Bqbm+peuNTR2/dBYt0dzIbcAt5lBWSUTrkeGXo4XuqF5+hQyWo4DjkRhqXltMHjGIn4dCCwG5taiiS1HauMYxAwkN+4F4A53vxzlBgaXCcxsPBIOB6GE083AWe4+Fb2McRmak8zsEjMbYmbdkiAojnS9L9cOWrzzMBJao1JfG939AuDviEHLOL7qXicBl7r72e4+E60kH5HpWw8zuxG4gEoY7VGUtxmP8iRlms+Z2SfT/x8xsw7JO9iIFNToTN/OMLNFVlmkWHgNK5ElPTJDMwUl/IvrBxXtAp2RxV/uW4f07yCgD/A1YJqZTU3jnsNUMzus6vMNwLmIB14jM9Zm1t7MZqB82OXo8Jx+KFx1bpqgraLK8t1EJQRa3c4+wGz0Xk9LfRsKzEWe8VEZmuOL5zGzY4Cvo1Lc65B3fGSGppOZzUJKYixShO8BzwEnoxxbmeZQ00Kzas8BV4nnweTnwgwzm2danFp81y7xQQ8k1Mo03wSGF4LezBrMbED6uRcwrEyTriuOSD0QKbLTgHPM7CuI13M0p7IlL84EzkZhny5IaOfozqAyby5Gin0XYIaZfSZHU1bEVZ8LT7vcxh7AjWj/qWtR2GocMnQPBSZkaMab2aj0/wjE12uRQXUwmuNZRI6jNh5GoaYCq5HVCEpaD0OKoRojkOXzLICZvYu8kzORBTgcvdxqvIUUxaVIoC0Hnky0Y5EQLKMXso4KS3kZMMbMmlIfd8nQ/AspwgWI0fdOXkAftAjszQzNOMQjXypboSkkcDBKpFXjs8AhZnYREmgfA/qjLd47obBDGRuQwp1uZk8Ds9y96M9fgSEZmp3T98X5AZNQgvdENNYHoNLTzagKXz2DvO3vmtmE9JyTzOxed59eaqcBCZKF6fMCoKO732hmG8kr9sPRmE5091eS9+ruPtvMzqZS/roZZlYIr2XIQnwd6OzuD6Rrh2faGZOum+buG83sB+io4PmmMNYImvPoyESzEIUUF7v7z1IfBqTf55RoxiKemuTuz5f6fQpK/N+S6dsbwAxgYBJse6M5NQzlDMrogoyuq83sXrSivViYdh8KGf6kRLMHUiq/TZ9PQUUIk4GliaY850A8B0oKr3D388zseOQ9HG1mSzJhqb2Q0lyUPi8BHnf3a81sA1K8W8DMDkVG41EoAnEyCgveambnAxPTs1XTTEDG4YLUxiagXZIrd5JRoOgdrUNhrreTt/W6u19pZm8i/inP1VFIUSxBRt0id5+R+tARKdW5mbZCcbSAe4BvpwF0FEuel36bg5i1jCbgxCSQuyErs2Do+9CeQFvA3W8zswXpfmtSO6MT/TJUOVXGIuD0JGQ7IoH5DDrp7x/A9RmaeciyvznRj0NC5SG0tqMxQ9MNVeGsBjCzndBeVyOBY4EfZWiWIuu1NwpnvIYm5+PA7UAubPDH9PzTkKV0l5nNTW0dgpRqGU1IQBdYAwxIwnMfmk+SIifQD73PI0xFBruiUGJ/JLjKeAAJ+gId0nOBvLtmljNS7F3d/ZX0+fXU19nIMDgmQ/MkOiOlA1rZPxB40MxWpfZzx/yuQgKlEK4rgZFmNg1Zv7nQ41Lg8+n/xcAUMxuD3teRwI8zNH1QIvX5ZDB0RopxCBKIv8zQPAzcZGaj0Xi8AaxAlvdXkXIvYxHig+8Bs4DDEx90RxbzvAxNE1t6sauBw8zsdCT4lmVoADqaWTvgn8AXzOzPqe31yIDL5b7+ghRigY0ofAvyvr6coWkAdvJUWGNmL6EQ0q1IJlySoXkRGUz7orB3B2Cpma1DijUX3noX5Z2KBZyPAZPN7FikNNZlaB6i4lXcD5xgZp9C73YMFdnVDJHjqIGkMEaiydQRVd7UYsKCpgdy2yeiydbo7hel3zqhF7uxhVuU79cZaF+OM5qSr0cjgdIdmOPujWY2BFkZ2VK6ZFEOQxOqC1I2y4F7crkKUzz6MmRpLUaTqjOqNFsG3F5+HjMblH5rQDmIVp83hVzmuvt+pjUp+yG3+WUk6BrLCcvUt5mpnRXIA5mJDqRZAtzipQS5VXYI7oSEzRXI03oxjcXKzFjvhpRZ33TdJ4AJ7v5iEjw9Mt7YQGRc3IkE0yRUtPArM+sF7Jk8idxYdCwSk2ks9yWNubvfULp2ALKmn0tjNQqdvzIaKbXZXqqWSe2fivhnOTIOBiPPbTHw68w77Q9cgxL9d6PwYW+gJzIIbi7zT3qnfwL2RKdQNitWyDz7PsBP3f2AxPtjgW8gpfoEylesL9H0Rwp5dXrm/ZGVfATwIMrzNBOaiReuQfNnOKo4W4X44CHguXL+IbV1NeKZFcjTmuLujyS+7emlQg5TTmwu4qFXUYj1bnefl8Kj+3v+JM7C0FmD5M9hqHS6Hao+O7907cdTO3cgnpuI3tXg1O6sDJ/2QbmjocjL3Std/4c0dvNr5TBDcbQCU8LpnZSYqpk0K9H0B15uy2SpQV+zuqN03S6oAmKTtVCdlaGr59pdEUPtjpTNKuBvnl/7UfT9Ynf/ftXnIsbtufFL15yeCQ201rfdkGVtwIJaTF6iGYYUwJnuflYb22lAYZ/2wO9qJTRLNCOQl9EbKeb56fuWquhqVtykWH+u2mcQChl2RUL/kfT9ZgWUoWmPcnB9kTfwEioSqJm0T8pwCOKFrijsstwz1XhF/5GynFL1ucipem4M0jUXAheWnr2nt1AtZpWChR2QwbCyLYaaKdf0FMr3NcvT1KAp1sp0A37jNQojSjSHowV3uwP3prxi8R421ZoTtWSNmXWuoQw/jXiuF+KFu1KUoENZoVXRFIbDYMSrL6DlAC0byaE4aqOtimJb0W9LpEkKaBZv5Xt3A9bWc9+yYKxHuVXRtHm8rVKlsrnUsZ622tjGDsD6erzMzD1a7V/yfLwe4+YD9Kdeo+PV1gygEs2OXslvtfmdphAa72cMrFK91mopb9EnqF1aXIOmJ7CmljJv4z1afa5qnqtzPtQ3ZtupXAsEAoH/C2zPBuT7RSiOQCAQCNSFWMcRCAQCgboQiiMQCAQCdSEURyDwAWHC0lQ9U3w3yczubokuEPhfReQ4AoGtgLQGoRGtQWmHFsCNbanEtQ33bP9BKrICgW2FUByBwFaCmV2GtnDois7xvtjMTkCL2DqiFfKnpZLRG9D2Fl3Q4tJioehLaOX/WOBKd8+t6A8E/quILUcCga2H6WjF7Xpg/+SFjEdH9W5MyuKLaF+nc9z9tbQIbJGZzffKDsBr3T27YV4gsD0gFEcgsJXg7mtNR3Gucff3TLvQHgA0pXV8Xaic4HacmU1Gc7ABreQuFMfPP9yeBwL1IRRHILB18e/0B9oK5SZ3P6/6AtN2498Chrr7G2Y2jy13Qa7rNLZA4MNGVFUFAtsOC9F27b1BGwyaTpLsDrwNvGU6cW1MC/cIBLY7hMcRCGwjuPujZjYdWJj2QdqAzotoQmGpx9COri1uKBcIbG+IqqpAIBAI1IUIVQUCgUCgLoTiCAQCgUBdCMURCAQCgboQiiMQCAQCdSEURyAQCATqQiiOQCAQCNSFUByBQCAQqAuhOAKBQCBQF/4DigH3GF8xX1YAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for country in ['Bangladesh','Ethiopia','Tanzania','Lao PDR']:\n",
    "    \n",
    "    # create copy of true values as dataframe\n",
    "    preds = df_trans.loc[country].loc[1995:][['CM']].copy()\n",
    "    \n",
    "    # do the predictions and store in the second column of preds\n",
    "    for year in range(1995,2019):\n",
    "        p_array = df_trans.loc[country,year][['M','Tf','G','Fr']].values\n",
    "        CM_next_year = CM_change(p_array) + df_trans.loc[country,year]['CM']\n",
    "        preds.loc[year+1,'CM Model'] = CM_next_year\n",
    "    \n",
    "    # get errors for 2013 onwards based on pre-2013 fit\n",
    "    se = get_se(preds.loc[:2014])\n",
    "    \n",
    "    ## PLOT 1\n",
    "    \n",
    "    # a. points\n",
    "    preds['CM'].plot(color=['k'])\n",
    "    plt.scatter(preds.index,preds['CM'],c='k',s=15,label='_nolegend_')\n",
    "    plt.scatter(preds.index,preds['CM Model'],c='r',marker='s',s=15,label='CM Model')\n",
    "    \n",
    "    # b. dashed pairwise lines\n",
    "    for year in list(preds.index)[:-1]:\n",
    "        plt.plot([year,year+1],[preds['CM'][year],preds['CM Model'][year+1]],'r--')\n",
    "    \n",
    "    # c. errorbars\n",
    "    plt.errorbar(preds.loc[2014:].index,preds.loc[2014:]['CM Model'],yerr=2*se,fmt='none',c='r',label='CM Model Error')\n",
    "    \n",
    "    # d. draw vertical line to separate taining and prediction data at 2013\n",
    "    plt.axvline(x=2013,linestyle='--',color='grey')\n",
    "    \n",
    "    # formatting\n",
    "    plt.legend()\n",
    "    plt.xticks(range(1995,2020),rotation=280)\n",
    "    plt.title('Child Mortality - '+country)\n",
    "    plt.ylabel('Mortality rate, under-5 \\n(per 100 live births)')\n",
    "    plt.xlabel('Year')\n",
    "    \n",
    "    # output to file\n",
    "    plt.savefig('outputs/figs_modelling/model_CM_'+country+'.png',dpi=200)\n",
    "    plt.show()\n",
    "    \n",
    "    \n",
    "    \n",
    "    ## PLOT 2 - Zoomed in\n",
    "    zoom_pred = preds.loc[2013:]\n",
    "    \n",
    "    # a. points\n",
    "    zoom_pred['CM'].plot(color=['k'])\n",
    "    plt.scatter(zoom_pred.index,zoom_pred['CM'],c='k',s=15,label='_nolegend_')\n",
    "    plt.scatter(zoom_pred.loc[2014:].index,zoom_pred.loc[2014:]['CM Model'],c='r',marker='s',s=15,label='CM Model')\n",
    "    \n",
    "    # b. dashed pairwise lines\n",
    "    for year in list(zoom_pred.index)[:-1]:\n",
    "        plt.plot([year,year+1],[zoom_pred['CM'][year],zoom_pred['CM Model'][year+1]],'r--')\n",
    "    \n",
    "    # c. errorbars\n",
    "    plt.errorbar(zoom_pred.loc[2014:].index,zoom_pred.loc[2014:]['CM Model'],yerr=2*se,fmt='none',c='r',label='CM Model Error')\n",
    "    \n",
    "    # formatting\n",
    "    plt.title(country+' [zoom]')\n",
    "    plt.xticks(range(2013,2019))\n",
    "    plt.ylabel('')\n",
    "    plt.xlabel('')\n",
    "    \n",
    "    # output to file\n",
    "    plt.savefig('outputs/figs_modelling/model_CM_'+country+'_zoom.png',dpi=200)\n",
    "    plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}