Ideal_Team_Lineup_World_Cup_2018.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![world-cup-18](images/fifa-world-cup-2018.jpg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Import libraries\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "from plotly.offline import iplot, init_notebook_mode\n",
    "from geopy.geocoders import Nominatim\n",
    "import plotly.plotly as py"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1 - Data Preparation\n",
    "### 1.1 Load Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Unnamed: 0', 'Name', 'Age', 'Photo', 'Nationality', 'Flag', 'Overall',\n",
       "       'Potential', 'Club', 'Club Logo', 'Value', 'Wage', 'Special',\n",
       "       'Acceleration', 'Aggression', 'Agility', 'Balance', 'Ball control',\n",
       "       'Composure', 'Crossing', 'Curve', 'Dribbling', 'Finishing',\n",
       "       'Free kick accuracy', 'GK diving', 'GK handling', 'GK kicking',\n",
       "       'GK positioning', 'GK reflexes', 'Heading accuracy', 'Interceptions',\n",
       "       'Jumping', 'Long passing', 'Long shots', 'Marking', 'Penalties',\n",
       "       'Positioning', 'Reactions', 'Short passing', 'Shot power',\n",
       "       'Sliding tackle', 'Sprint speed', 'Stamina', 'Standing tackle',\n",
       "       'Strength', 'Vision', 'Volleys', 'CAM', 'CB', 'CDM', 'CF', 'CM', 'ID',\n",
       "       'LAM', 'LB', 'LCB', 'LCM', 'LDM', 'LF', 'LM', 'LS', 'LW', 'LWB',\n",
       "       'Preferred Positions', 'RAM', 'RB', 'RCB', 'RCM', 'RDM', 'RF', 'RM',\n",
       "       'RS', 'RW', 'RWB', 'ST'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "FIFA18 = pd.read_csv('CompleteDataset.csv', low_memory=False)\n",
    "FIFA18.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's select the most interesting columns from loaded dataset:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "interesting_columns = [\n",
    "    'Name', \n",
    "    'Age',  \n",
    "    'Nationality', \n",
    "    'Overall', \n",
    "    'Potential', \n",
    "    'Club', \n",
    "    'Value', \n",
    "    'Wage', \n",
    "    'Preferred Positions'\n",
    "]\n",
    "FIFA18 = pd.DataFrame(FIFA18, columns=interesting_columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.2 Summarize Data"
   ]
  },
  {
   "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>Name</th>\n",
       "      <th>Age</th>\n",
       "      <th>Nationality</th>\n",
       "      <th>Overall</th>\n",
       "      <th>Potential</th>\n",
       "      <th>Club</th>\n",
       "      <th>Value</th>\n",
       "      <th>Wage</th>\n",
       "      <th>Preferred Positions</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Cristiano Ronaldo</td>\n",
       "      <td>32</td>\n",
       "      <td>Portugal</td>\n",
       "      <td>94</td>\n",
       "      <td>94</td>\n",
       "      <td>Real Madrid CF</td>\n",
       "      <td>€95.5M</td>\n",
       "      <td>€565K</td>\n",
       "      <td>ST LW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>L. Messi</td>\n",
       "      <td>30</td>\n",
       "      <td>Argentina</td>\n",
       "      <td>93</td>\n",
       "      <td>93</td>\n",
       "      <td>FC Barcelona</td>\n",
       "      <td>€105M</td>\n",
       "      <td>€565K</td>\n",
       "      <td>RW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Neymar</td>\n",
       "      <td>25</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>92</td>\n",
       "      <td>94</td>\n",
       "      <td>Paris Saint-Germain</td>\n",
       "      <td>€123M</td>\n",
       "      <td>€280K</td>\n",
       "      <td>LW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>L. Suárez</td>\n",
       "      <td>30</td>\n",
       "      <td>Uruguay</td>\n",
       "      <td>92</td>\n",
       "      <td>92</td>\n",
       "      <td>FC Barcelona</td>\n",
       "      <td>€97M</td>\n",
       "      <td>€510K</td>\n",
       "      <td>ST</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>M. Neuer</td>\n",
       "      <td>31</td>\n",
       "      <td>Germany</td>\n",
       "      <td>92</td>\n",
       "      <td>92</td>\n",
       "      <td>FC Bayern Munich</td>\n",
       "      <td>€61M</td>\n",
       "      <td>€230K</td>\n",
       "      <td>GK</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Name  Age Nationality  Overall  Potential  \\\n",
       "0  Cristiano Ronaldo   32    Portugal       94         94   \n",
       "1           L. Messi   30   Argentina       93         93   \n",
       "2             Neymar   25      Brazil       92         94   \n",
       "3          L. Suárez   30     Uruguay       92         92   \n",
       "4           M. Neuer   31     Germany       92         92   \n",
       "\n",
       "                  Club   Value   Wage Preferred Positions  \n",
       "0       Real Madrid CF  €95.5M  €565K              ST LW   \n",
       "1         FC Barcelona   €105M  €565K                 RW   \n",
       "2  Paris Saint-Germain   €123M  €280K                 LW   \n",
       "3         FC Barcelona    €97M  €510K                 ST   \n",
       "4     FC Bayern Munich    €61M  €230K                 GK   "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "FIFA18.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 17981 entries, 0 to 17980\n",
      "Data columns (total 9 columns):\n",
      "Name                   17981 non-null object\n",
      "Age                    17981 non-null int64\n",
      "Nationality            17981 non-null object\n",
      "Overall                17981 non-null int64\n",
      "Potential              17981 non-null int64\n",
      "Club                   17733 non-null object\n",
      "Value                  17981 non-null object\n",
      "Wage                   17981 non-null object\n",
      "Preferred Positions    17981 non-null object\n",
      "dtypes: int64(3), object(6)\n",
      "memory usage: 1.2+ MB\n"
     ]
    }
   ],
   "source": [
    "FIFA18.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.3 Preprocess Data\n",
    "Right away I can see that values in columns: 'Value' and 'Wage' aren't numeric but objects. Thus I'll preprocess the data to make it usable. I will use short supporting function to convert values in those two columns into numbers. I will end up with two new columns 'ValueNum' and 'WageNum' that will contain numeric values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Supporting function for converting string values into numbers\n",
    "def str2number(amount):\n",
    "    if amount[-1] == 'M':\n",
    "        return float(amount[1:-1])*1000000\n",
    "    elif amount[-1] == 'K':\n",
    "        return float(amount[1:-1])*1000\n",
    "    else:\n",
    "        return float(amount[1:])\n",
    "    \n",
    "FIFA18['ValueNum'] = FIFA18['Value'].apply(lambda x: str2number(x))\n",
    "FIFA18['WageNum'] = FIFA18['Wage'].apply(lambda x: str2number(x))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To make things simpler, I select the first position from list as preferred and save it in 'Position' column."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "FIFA18['Position'] = FIFA18['Preferred Positions'].str.split().str[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2 - Data Visualization\n",
    "### 2.1 Age"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10ae17588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16,8))\n",
    "sns.set_style(\"whitegrid\")\n",
    "plt.title('Grouping players by Age', fontsize=30, fontweight='bold', y=1.05,)\n",
    "plt.xlabel('Number of players', fontsize=25)\n",
    "plt.ylabel('Players Age', fontsize=25)\n",
    "sns.countplot(x=\"Age\", data=FIFA18, palette=\"hls\");\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.2 Overall"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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rCL7SzRHCXr16Gdoyj3Z66l//+pdhUa+MEdzMHKdF//rrr4btxo0bOx1TvHhxjRo1Ktf1OQoMDNTw4cOdrqtBgwapTJkyhjZ3plwHBQVpwoQJWrFihX7//XfNmTPHaaSsdOnShm3HZ1bXr19f1apVs2+npKQYpj5fu3bNsO3r66vHH3/cvr13715DGL3nnnucRi0LFSpkD4MZMkJOVurXr28PNRky3j/H62zMmDGKjY1VSkqKva1v377atGmT5s6dqw8++MCwQJunwsPDnaYTBwYGOi0AdfjwYfvIqWQMgtLNe1Uzj1yvXbvW8Dvm0UcfdSusOy46JilH0+Azy7xYluPxdevWNTx/+9KlS/rxxx+z3Pbz8zN8QZIf10i9evU0efJkxcfHKyEhQe+8847T8Y6zeRw/GwCQE4z8ArjjBQcHG7YvX74sq9Xq8o9Mb3jggQey7Hvbtm2G7QcffFBly5Z1uW/r1q3l5+dn/0P6+vXr2rFjx215ju6jjz6aZfvUqVPt2wcOHJDNZnO5YE5O+Pr6qm7duk7tme+PluR0j6fj808dp51mqF27tkJCQgzhJbdCQ0NdTt/09fVVkyZNtHjx4izrzKkiRYqoSJEiOnz4sLZu3aodO3Zo8+bN+uOPPwz7ZQ5dGcLDww2rPK9YscK+4NC6desMoSAsLMwQGnbu3Gno68KFC4Yp+1md1/E4R46hJrPu3bvr+++/twe2jAWnMlZZb9CggRo1aqSHH34421kb7srqmnn44Yfl4+NjuJf30KFD9muyXr16ql69uvbv3y/p5qjqL7/8Yv/MrFy50tCfOwtdSVKJEiWc2i5fvuxWH477O/4O7Nq1q95991379pIlS+xf2K1cudLweWvRokW+XyOZlShRQunp6dq+fbt27Nihbdu2adOmTYYvFV2dHwBygvAL4I7nuNBMWlqaDh06ZBghyzB48GCnPxzHjh1rmDZ4K47BLbOTJ08atrNbwbVIkSIKCQkxjLI4TvXNCVcL8mSncOHCTn8sZ3Acpbtx44YuX77s9rTMDCVKlHD5+JasHu+U4a+//sq2rszKli3r1fCb3X/fe+65x7DtWGdO7NmzR7Nnz9aaNWt0/vx5t49/4oknFBUVZf/v/uOPP+ratWsqWrRotlOeJTmd7/r16zlauOv06dPZfqHkOCKeWf369fXhhx9q1KhRun79ur09I+Bs375dM2fOVOHChdWmTRv169dP99133y1rupWs7vsvXLiwSpYsqbNnz9rbHGcehIeH66OPPrJvr1ixQo8++qiSk5MN98IGBQXd8lFdjhxH9yXZg3ZO/Pnnn05fFjm+/506ddJHH31kn0kSHx+vS5cuKSgoKNspz1L+XCMZ4uPjNXfuXP3yyy+Gad0A4C1MewZwx3O1+mlW01HbtGmj8PBwwz+ZV0fNiez2d/XYmew4TnfMbrQ6q5CbOVDkRHp6epbTLF2152YEPav341Z9Ok7rzI6no9JZyW7avOP7c6vnsjqKiYnRU089pfnz59tDRvHixdWoUSO98MIL+vLLL2/ZR5kyZdSsWTP79pUrVxQfH6/U1FTDdNbAwECn6cPuflGSwWazZbk6uJT9ffbSzfvJ16xZo4EDB2Z5j3RqaqqWLVumLl26eGX18+xGBh2vmczP+5VufmmQuS02NlZpaWmKi4szBM/27du7/ZkPDAx0+mLOcZp/dhwfsSTJ6bFbQUFBhlszUlNTtWrVKiUlJWnz5s329pCQEKdZIPl1jbz99tvq27ev1q5daw++pUqVUosWLTRo0CC9+eabHtUFAJkx8gvgjlexYkXVqlXLvvqoJM2bN089evRwO5zkRObFhRw5jlA6TtXL7Nq1a04jvZlHHR3/QM/qfmB3Rx+tVquOHTvmclTacQTVz88vV1NRPQ3OjiPTSUlJWe7ruKBSbmX338zx/XE1hTW7fkeNGmUP1/7+/vrwww/VqlUr+7N8c3q/enh4uCHorlixQn5+fob7aNu1a+d0rTrW+8ADDygmJibHP0NWchIAQ0JC9Morr+iVV17R2bNnlZCQoN9++02//fab/vjjD/sXC2lpaRoxYoQee+wx+/viiawWREpLS3Oa6eF4vZUuXVqPPvqo/T2+ePGifv7551uOrOdU06ZNDYu8bd68WXv27FGNGjWyPc5msxkWs5JuBkRXx3Xr1s0wyrtmzRpduXLF8AVOeHi40+/I/LhG/vvf/xoeL1atWjWNHTvWcMtE5hF3APAUI78ATMFxoaa9e/fmaBTt1KlT2Y5WuJJdoHMc1dqyZYvTVOgMq1evNoSd4sWLq06dOvZtx+CS+dEkmWUO/TmV1eI0jiNQ999/v9t9e4PjtNes/vDdtm2bR1PFs7NlyxbDlNgMVqvV6dmiOV3pWZKWLl1q+O/dpUsX+6OUMmQX8jNr0aKFSpYsad+Oj4/Xf//7X8M+roKZY0g6ePCgITBn2LFjh2JiYrRt27YcLSyU3WfiypUr2rlzp5YuXaro6GhZrVaVLl1aHTp00Ntvv62FCxdq+fLlhuv9woULuX6EVeYvBzLbtGmT4b9DoUKFXE6zdpwOvHDhQsPzkytWrOhy1klO9OzZ0+k9Gz58+C1nccyePdtpXYFevXq5fP9DQ0NVpUoV+/bPP/+spUuX2rctFovTzyjlzzXiOBV74MCBTmsF5PSzAQDZIfwCMIXw8HCnoDZx4kSNHz/e6f446WaQiYmJ0ZNPPun2yGl202wffvhhw+htxjN8Hf84PHLkiOGxHZLzFMrM4Ua6+XxQx8f6rF+//parrLry+eefO4WLAwcOaPbs2Ya2sLAwt/v2BsepmAkJCVq2bJmh7dKlS3my2nNaWpqGDx/uNAo7ZcoUpy8ymjZtmuN+HY/ds2ePYRTuxo0bmjBhgtNxrqai+/n52Z+RKt0MmJlHJcuXL+9y4bS6desa7oW9cuWKxowZY5hmnpaWpvfff1/Dhg1T165d1aBBA6dnLjvK6jORlJSkBg0aKDw8XIMHD9b48eOdnoEt3Ry9dOzD3RWQHcXGxhoWJ5NuPmYo87280s17kl3NbnjssccMn8GVK1ca7kP1dNRXurlOQeZVuCVp+/btevHFF12GPKvVqunTp+vDDz80tN9111169tlnszxP5mclX79+3f7cbUlq2LChy+eK3+5rRHJ+9vHu3bsN2xcuXDAsxCfl/voA8PfEtGcApuDj46MJEyaoa9euhlGK6Ohoff/99/rHP/6hypUry2az6fDhw1qzZk2WIwm5uYe0UKFCeumll/TBBx/Y2xISEvT4448rPDxcZcqU0f79+/Xdd98ZAnFAQID69+9v6KtmzZoqVKiQ4Y/Ol19+WT169FCZMmW0bds2LV261K37YzNcunRJ3bp1U0REhKpXr64jR45o3rx5hlFwPz8/Pf3002737Q0tWrRQ+fLlDVOa33jjDcXHx6tBgwY6e/asFixYkGejQXFxcerSpYs6d+6sgIAA/fTTT1q7dq1hn7CwMKfF1rLjuODPpk2b9Pzzz6tVq1b666+/tHTpUh08eNDpuGvXrrlcffqpp57SN9984/JcnTt3dnkd+/n5qVevXvrss8/sbfPnz9fu3bvVunVrFS1a1P4opgw2m80QtN1xzz33KCwszDBi+s4772jDhg1q0KCBihYtquPHj2vx4sWGaf0lSpTI9aJXNptNQ4YMUWxsrBo3bqzLly/ru+++09GjRw379e7d2+Xxfn5+6ty5s2bOnOny9dyEX0kaNWqUtm/fblhMKiEhQe3atVOrVq1Ut25d+/uzatUqHT582HC8j4+PoqKisp1636VLF40fP97ldHpXo77S7b9GpJtT4jP/fJMnT9apU6f0wAMP6M8//9TChQudpqrfrsfCATAXwi8A06hWrZpmzJihl19+2bBi6alTpzRr1qwc9dG6dWv17NkzV3X07t1bv/32m1asWGFvO378uCZOnOhyfz8/P0VFRalcuXKG9pIlSyosLMzw3NaLFy86Tedu1qyZYZ+cCAwM1OXLl7MMT9LNZwE71nS7FC5cWKNGjVJkZKQ93FutVi1atMgwRTIwMFC+vr5ZTgn3RMZ7s2/fPn3yyScu9wkICNC///1vt/pt3769vvzyS8OCQj///PMtn6V89uxZl/dn16xZU7Vr13Z6PJKUfTB76aWX9OOPP2r79u32tm3btjlNp83w9NNPq2HDhtnWmJ0RI0YoIiLCvqKy1WrVqlWrtGrVqiyPGThwoNsLSWVWuHBhVaxYUQcOHNDKlSudHk+UoUWLFurQoUOW/YSHh7sMv//zP//jctTUHQEBAZo6daoiIyMNj8y6evWqli5dapii7KhYsWIaM2aMHn744WzPUapUKbVs2dLpXuXAwECXjy/KcLuvkY4dOxpuKbhx44ZiYmKyvdf43LlzHp8PwN8X054BmEq9evW0dOlSde7cOceLXfn4+Oixxx7TrFmz9Pnnn6tUqVK5ruOTTz7RoEGDbrlgz913361p06apefPmLl//97//rfLly2d5fPv27fXee++5Xd+0adOcplVnsFgsevXVV/X888+73a83NW/eXO+8806W72FQUJAmTZrk9OiY3C5y1rp1a7366qtZvn7XXXdp+vTp2T7GypXq1atryJAh2c4sKF++vFOgcZzqnll4eLhTW/369Q33ejoqXLiwpk6dqiZNmtyy5m7dumnEiBG33C87lSpV0jfffJOjsOjn56fBgwc73cPvLl9fX3399dfZ3rPerFkzjR8/Ptt+atasabgPP0NuR30zlC9fXnPnzlXv3r2zXUgvs0aNGmnu3LnZhtfMMk99ztCxY8dsHzd2u6+Rrl276h//+Ee2+zRp0sTwu/DEiRM6depUrs4L4O+HkV8ApnPXXXdp3LhxGjhwoFasWKGEhATt379f58+f140bN1SyZEmVLl1aNWvWVJMmTdS0aVOXz97MDR8fH/Xr109PPvmklixZorVr1+rYsWO6ePGiSpQooRo1aqhVq1aKiIjI9o/e8uXLa+HChZo+fbpWrVqlEydOyN/fX3Xq1FH37t3VunVrj54Vm/ElwRdffKG4uDidPn1awcHBCg0NVZ8+ffTggw/m5sf3mm7duqlevXqaPn26fv31V507d05lypTRo48+qpdfflnly5d3uvcvpyEiO6+99poaNmyoqVOnatu2bbp27ZoqVKig1q1b6/nnn8/yOcm30qdPH9WoUUMzZ87U1q1bdenSJRUrVkxVqlRRq1at1LNnTyUkJBgWHlu0aFGWU0rbtm2r999/39CWk2BWokQJzZgxQ7GxsVq+fLm2bNmi8+fPKy0tTSEhIWrQoIG6d++eq9G8zGrVqqVly5ZpyZIlWrNmjXbv3q1z587pxo0bCggIUKVKldSwYUN17dpVlStX9so5y5Urp5iYGM2ZM0eLFy/WoUOH5Ovrq1q1aikiIkKdOnXK0S0Obdu21c6dO+3bfn5+at++vVdqlG6u+j18+HC9+OKLWrFihX799Vft27dPFy5cUGpqqoKDg3XPPfeoUaNGatmypct7ubPzyCOPON1CkNWU58xu5zXi4+OjTz/9VDExMVq4cKH27Nmj69ev239XPvHEE+rUqZPGjh1rGIlftGiR+vbtm+vzA/j7sNhYMQAATO3YsWNOz3vds2dPPlWTMykpKUpPT8/Ro4SaN29uuPd37dq12Y6WO5o4caImTZpk3+7SpYvGjBnjXsH5ZOXKlRo4cKB929fXVz/99JNXZi/gppdffllxcXH27ZYtW+ZoJXkAQMHDyC8AoMDZsGGDBgwYoKJFiyokJEQhISHq3bu32rZta9hvx44dhuBbvHhxlS1b9naXmy9SUlKcpu02bdqU4OtFP/30kyH4SsrVwk4AgPxF+AUAFDjVqlWTdHNF16NHj+ro0aPavXu3tmzZosqVK+v69evav3+/0+OPWrRoke3zRO90U6dOVbFixXThwgUtXrzYaQXg3N4r+3d3+PBh/fDDDwoMDNT+/fudHssUEhKiNm3a5FN1AIDcIvwCAAqcatWqKSwsTOvXr7e3JScna9q0aVke4+fnZ/r7/5YsWaJdu3a5fK1+/fpZLpyGnLl27ZqioqKyfL1fv363XMQOAFBwmffrcQDAHW3cuHHRKRhsAAAgAElEQVSqX79+jvYtXry4Pv74Y9WsWTOPq8pf99xzj8v2kJAQffzxx7l6RjVurr6elY4dO6pHjx63sRoAgLcx8gsAKJBKlSqluXPnatWqVVq9erX27NmjpKQkXb16VT4+PgoKClLVqlXVpEkTRUREqEyZMvldcp578MEH7atE+/n5qWLFimrRooX69OnDvb5eULJkSdWpU0eHDh3S9evXFRgYqNq1a+vJJ59U586d+XIBAO5wrPYMAAAAADA9pj0DAAAAAEyP8AsAAAAAMD3CLwAAAADA9Ai/AAAAAADTI/wCAAAAAEyP8AsAAAAAMD3CLwAAAADA9Ai/AAAAAADTI/wCAAAAAEyP8AsAAAAAMD3CLwAAAADA9Ai/AAAAAADTI/wCAAAAAEyP8AsAAAAAMD3CLwAAAADA9Ai/AAAAAADTI/wCAAAAAEyP8AsAAAAAMD3CLwAAAADA9Ai/AAAAAADT883vAm63zZs353cJAAAAAIA89NBDDzm1/e3Cr+T6jQAAAAAA3PmyGvBk2jMAAAAAwPQIvwAAAAAA0yP8AgAAAABMj/ALAAAAADA9wi8AAAAAwPQIvwAAAAAA0yP8AgAAAABMj/ALAAAAADA9wi8AAAAAwPQIvwAAAAAA0yP8AgAAAABMj/ALAAAAADA9wi8AAAAAwPQIvwAAAAAA0yP8AgAAAABMj/ALAAAAADA9wi8AAAAAwPQIvwAAAAAA0yP8AgAAAABMzze/CwAAIDuRiV95fGx06EterAQAANzJGPkFAAAAAJge4RcAAAAAYHqEXwAAAACA6RF+AQAAAACmR/gFAAAAAJge4RcAAAAAYHqEXwAAAACA6RF+AQAAAACmR/gFAAAAAJge4RcAAAAAYHqEXwAAAACA6fnmdwEAANwOkYnfenxsdGgPL1YCAADyAyO/AAAAAADTI/wCAAAAAEyP8AsAAAAAMD3CLwAAAADA9Ai/AAAAAADTY7VnAIBBZOJ7Hh0XHTrCy5UAAAB4DyO/AAAAAADTI/wCAAAAAEyP8AsAAAAAMD3CLwAAAADA9Ai/AAAAAADTI/wCAAAAAEyP8AsAAAAAMD3CLwAAAADA9HzzuwAAAO4kkYlLPD42OrSTFysBAADuYOQXAAAAAGB6hF8AAAAAgOkRfgEAAAAApkf4BQAAAACYHuEXAAAAAGB6hF8AAAAAgOnxqCMAQJ6ITBzv0XHRoa97uRIAAABGfgEAAAAAfwOEXwAAAACA6RW48Lt161Y9++yzkqQjR46oR48e6tmzp0aNGiWr1SpJmjRpkiIiIvT0009r27Zt2e4LAAAAAECBCr9fffWV3n77bV2/fl2SNHr0aA0aNEhz5syRzWZTbGysdu7cqYSEBC1YsEBRUVF65513stwXAAAAAACpgC14de+992rixIkaMmSIJGnnzp1q1KiRJKlZs2basGGDqlSporCwMFksFpUrV043btzQ+fPnXe7bpk0bl+fZtWvX7fmBAOBvxFu/W735O7qg1cT/fwAAyD8FKvy2bdtWx44ds2/bbDZZLBZJkr+/vy5fvqzk5GQFBwfb98lod7VvVmrVqpVHPwEAmECiZ4c5/W5NXOmlftZ7VpBjX4lbvNTPfu/0AwAA8sTmzZtdtheoac+OChX6v/JSUlIUFBSkgIAApaSkGNoDAwNd7gsAAAAAgFTAw2/t2rW1ceNGSdK6desUGhqqBg0aaP369bJarTpx4oSsVqtKlSrlcl8AAAAAAKQCNu3Z0ZtvvqkRI0YoKipKVatWVdu2beXj46PQ0FB1795dVqtVI0eOzHJfAAAAAACkAhh+K1SooPnz50uSqlSpotmzZzvtM2DAAA0YMMDQltW+AAAAAAAU6GnPAAAAAAB4A+EXAAAAAGB6hF8AAAAAgOkRfgEAAAAApkf4BQAAAACYHuEXAAAAAGB6hF8AAAAAgOkRfgEAAAAApkf4BQAAAACYHuEXAAAAAGB6hF8AAAAAgOkRfgEAAAAApkf4BQAAAACYHuEXAAAAAGB6hF8AAAAAgOkRfgEAAAAApkf4BQAAAACYHuEXAAAAAGB6hF8AAAAAgOkRfgEAAAAApkf4BQAAAACYHuEXAAAAAGB6hF8AAAAAgOkRfgEAAAAApkf4BQAAAACYHuEXAAAAAGB6vvldAAAg9yITh3h8bHToR16sBAAAoGBi5BcAAAAAYHqEXwAAAACA6THtGQCAfBKZ+KNHx0WHtvByJQAAmB/hFwCAO1xkYqLHx0aHhnqxEgAACi6mPQMAAAAATI/wCwAAAAAwPcIvAAAAAMD0CL8AAAAAANMj/AIAAAAATI/wCwAAAAAwPcIvAAAAAMD0CL8AAAAAANMj/AIAAAAATI/wCwAAAAAwPcIvAAAAAMD0CL8AAAAAANMj/AIAAAAATI/wCwAAAAAwPcIvAAAAAMD0CL8AAAAAANMj/AIAAAAATI/wCwAAAAAwPcIvAAAAAMD0CL8AAAAAANMj/AIAAAAATI/wCwAAAAAwPcIvAAAAAMD0fPO7AAAAUDBExiV6fGz0Y6FerAQAAO9j5BcAAAAAYHqEXwAAAACA6RF+AQAAAACmR/gFAAAAAJge4RcAAAAAYHqEXwAAAACA6RF+AQAAAACmR/gFAAAAAJge4RcAAAAAYHq++V0AAPydRSa+4vGx0aFfeLESAAAAc2PkFwAAAABgegV+5DctLU1Dhw7V8ePHVahQIb333nvy9fXV0KFDZbFYdN9992nUqFEqVKiQJk2apLi4OPn6+mrYsGGqV69efpcPAAAAACgACnz4jY+PV3p6uubOnasNGzZowoQJSktL06BBg9S4cWONHDlSsbGxKleunBISErRgwQKdPHlSAwYMUExMTH6XDwAAAAAoAAr8tOcqVaroxo0bslqtSk5Olq+vr3bu3KlGjRpJkpo1a6aff/5ZmzdvVlhYmCwWi8qVK6cbN27o/Pnz+Vw9AAAAAKAgKPAjv8WLF9fx48fVvn17XbhwQdHR0dq0aZMsFoskyd/fX5cvX1ZycrKCg4Ptx2W0lypVyqnPXbt23bb6ASCveOt3mVn78WZfZu3Hm33x/1YAQEFX4MPvjBkzFBYWpsGDB+vkyZP65z//qbS0NPvrKSkpCgoKUkBAgFJSUgztgYGBLvusVatWntcNADmS6Pmhht9l3uonF30597PSS/2s96wgx74St3ipn/3e6UeSEpO81I/nF4Chr1Ne6gcAgHy0efNml+0FftpzUFCQPcSWKFFC6enpql27tjZu3ChJWrdunUJDQ9WgQQOtX79eVqtVJ06ckNVqdTnqCwAAAAD4+ynwI799+vTRsGHD1LNnT6Wlpen111/XAw88oBEjRigqKkpVq1ZV27Zt5ePjo9DQUHXv3l1Wq1UjR47M79IBAAAAAAVEgQ+//v7++vTTT53aZ8+e7dQ2YMAADRgw4HaUBQAAAAC4gxT4ac8AAAAAAOQW4RcAAAAAYHqEXwAAAACA6RF+AQAAAACmR/gFAAAAAJge4RcAAAAAYHqEXwAAAACA6RF+AQAAAACmR/gFAAAAAJge4RcAAAAAYHqEXwAAAACA6RF+AQAAAACmR/gFAAAAAJge4RcAAAAAYHqEXwAAAACA6RF+AQAAAACmR/gFAAAAAJge4RcAAAAAYHqEXwAAAACA6RF+AQAAAACmR/gFAAAAAJge4RcAAAAAYHqEXwAAAACA6RF+AQAAAACmR/gFAAAAAJge4RcAAAAAYHqEXwAAAACA6fnmdwEAAMBcIpckenxsdKdQL1YCAMD/YeQXAAAAAGB6hF8AAAAAgOkRfgEAAAAApkf4BQAAAACYHuEXAAAAAGB6hF8AAAAAgOkRfgEAAAAApkf4BQAAAACYHuEXAAAAAGB6vvldAADcTqMSIz067p3QaC9XAgAAgNuJkV8AAAAAgOkRfgEAAAAApse0ZwDwwGAPp09L0idMoQYAALjtGPkFAAAAAJgeI78AAKDAivw20aPjonuEerkSAMCdjpFfAAAAAIDpEX4BAAAAAKZH+AUAAAAAmB7hFwAAAABgeoRfAAAAAIDpEX4BAAAAAKZH+AUAAAAAmJ7b4fett97SlClTcrTvu+++q2effdbtogAAAAAA8Ca3w+/333+v+Pj4HO2bmJiobdu2uV0UAAAAAADe5Jvdi4cPH9aiRYuc2k+ePKlPP/00y+NsNptOnDihvXv3qmTJkrmvEgAAAACAXMg2/FasWFErV67U4cOH7W0Wi0UnT55UdHR0th3bbDZJUps2bXJfJQAAAAAAuZBt+PXx8dHw4cM1efJke9umTZsUGBiomjVrZnlcoUKFVLx4cdWuXVsvvfSS96oFAAAAAMAD2YZfSQoLC1NYWJh9u2bNmrr//vs1a9asPC0MAAAAAABvuWX4dTR69GjdddddeVELAAAAAAB5wu3w26VLl7yoAwAAAACAPON2+M1w4cIFbdu2TZcvX1Z6enq2+z755JOengYAAAAAgFzzKPxGRUVp2rRpunHjxi33tVgshF8AAAAAQL5yO/wuXLhQU6ZMkXQz2JYqVUpFihTxemEAAAAAAHiL2+F3/vz5slgs6ty5s9566y0FBwfnRV0AAAAAAHiN2+F37969CgoK0nvvvafChQvnRU0AAAAAAHhVIU8OqlChAsEXAAAAAHDHcDv8VqtWTceOHZPNZsuLegAAAAAA8Dq3w2+3bt30119/ac6cOXlRDwAAAAAAXuf2Pb9du3ZVYmKiRo8erSNHjqhFixYKCQnJdhp0xYoVc1UkAAAAAAC54Xb4DQsLkySlp6dr1qxZmjVrVrb7WywW/fHHH55V9/9NnjxZa9euVVpamnr06KFGjRpp6NChslgsuu+++zRq1CgVKlRIkyZNUlxcnHx9fTVs2DDVq1cvV+cFAAAAAJiD29Oez549q7Nnz0qSbDbbLf+xWq25KnDjxo36/fff9e2332rWrFlKSkrS6NGjNWjQIM2ZM0c2m02xsbHauXOnEhIStGDBAkVFRemdd97J1XkBAAAAAObh9shvbGxsXtSRpfXr1+v+++/Xq6++quTkZA0ZMkTz589Xo0aNJEnNmjXThg0bVKVKFYWFhclisahcuXK6ceOGzp8/r1KlSt3WegEAAAAABY/b4bd8+fJ5UUeWLly4oBMnTig6OlrHjh1Tv379ZLPZZLFYJEn+/v66fPmykpOTFRwcbD8uo91V+N21a9dtqx+AOXjz94a3+qKf29eXWfvxZl9m7QcAYB5uh9/bLTg4WFWrVlXhwoVVtWpVFSlSRElJSfbXU1JSFBQUpICAAKWkpBjaAwMDXfZZq1atPK8bQAGV6NlhTr83POzHqa+C1k8u+nLuZ6WX+lnvWUGOfSVu8VI/+73TjyQlJrne0e1+PL8ADH2d8lI/+73UjyRt8awv/l8PAH9fmzdvdtnudvidNGmS2yfv37+/28dkeOihh/TNN9/oueee0+nTp3X16lU1adJEGzduVOPGjbVu3To9/PDDuvfeezVu3Di98MILSkpKktVqZcozAAAAAECSh+E3Y8rxrWRMT85N+G3RooU2bdqkiIgI2Ww2jRw5UhUqVNCIESMUFRWlqlWrqm3btvLx8VFoaKi6d+8uq9WqkSNHenxOAAAAAIC5uB1+GzZsmOVrV69e1enTp3X69GlZLBZFRESodOnSuSpQkoYMGeLUNnv2bKe2AQMGaMCAAbk+HwAAAADAXNwOv7d6rq8kbdu2TYMHD1ZCQoIWLlzoUWEAAAAAAHiL28/5zYl69eopKipKR48e1ZdffpkXpwAAAAAAIMfyJPxKUt26dVWpUiWtXr06r04BAAAAAECO5OmjjooWLapDhw7l5SkAAABuKfIrzx6ZFP1SqJcrAQDklzwb+T148KD279+vEiVK5NUpAAAAAADIEbdHfn/55ZdsX09NTdXBgwc1ffp0Wa1WNWnSxOPiAAAAAADwBrfD73PPPZej5/zabDb5+/urX79+HhUGAAAAAIC3eHTPr81my/I1Hx8flSxZUg0aNNArr7yiKlWqeFwcAAAAAADe4Hb43b17d17UAQAAAABAnsmzBa8AAAAAACgocvWoo6tXryohIUGHDh1ScnKyAgICVKlSJTVs2FABAQHeqhEAAAAAgFzxOPzOnDlTn3/+uS5fvuz0WtGiRfXqq6/qxRdfzFVxAAAAAAB4g0fhd+zYsZoxY4ZsNpv8/PxUpUoVBQQE6NKlSzp8+LCuXr2qTz75RKdOndLw4cO9XTMAAAAAAG5xO/z++uuvmj59unx9ffXaa6/p2WefVbFixeyvJycna/bs2Zo0aZJmz56tf/zjH2rYsKFXiwYAAAAAwB1uL3g1Z84cWSwWDRs2TH379jUEX0kKCAhQZGSkhg0bJpvNpnnz5nmtWAAAAAAAPOF2+P3tt99UsmRJ9ejRI9v9evTooZIlS+q3337zuDgAAAAAALzB7fB78eJFVahQQRaLJdv9LBaLKlasqLNnz3pcHAAAAAAA3uB2+A0MDFRSUlKO9k1KSpK/v7/bRQEAAAAA4E1uh986derozJkzWr16dbb7/fDDDzp9+rTq1KnjcXEAAAAAAHiD2+G3a9eustlsGjp0qJYvX+5yn+XLl+utt96SxWJRRERErosEAAAAACA33H7UUdu2bdW6dWutWbNGgwcP1ujRo1W7dm0FBAQoOTlZf/zxh86ePSubzabWrVurXbt2eVE3AAAAAAA55nb4laQJEyZo9OjRmjdvns6cOaP4+Hhjp76+6tatm4YOHeqVIgEAAAAAyA2Pwq+vr69GjBihvn37at26dTp48KCSk5Pl7++vqlWrqlmzZrrnnnu8XSsAAAAAAB7xKPxmuPvuu9W1a1dD27FjxxQcHJyrogAAAAAA8Ca3F7ySpPT0dI0fP14tWrTQ9evXDa999NFHatq0qT755BOlpqZ6pUgAAAAAAHLD7fCbmpqqF154QVOmTFFSUpIOHTpkeP3MmTO6cuWKvv76a/Xv399rhQIAAAAA4Cm3w++sWbO0ceNGlSxZUuPGjVP16tWdXv/8889VunRp/fTTT1qwYIHXigUAAAAAwBNuh99ly5apUKFC+uqrr/T444/L19d427Cvr69atWqlzz//XJIUExPjnUoBAAAAAPCQ2+H30KFDqly5surUqZPtfvXq1VOFChW0d+9ej4sDAAAAAMAb3A6/FotFhQsXztG+gYGBslqtbhcFAAAAAIA3uR1+K1SooP379+v8+fPZ7vfXX39p//79Klu2rMfFAQAAAADgDW6H31atWik9PV3Dhg3L8lFG6enpGjFihNLS0tS8efNcFwkAAAAAQG743noXo169emn+/PmKj49Xhw4d9MQTT6hmzZoqXry4UlJStHfvXi1ZskRHjx5VUFCQnn/++byoGwAAAACAHHM7/JYuXVqfffaZBg4cqGPHjumLL75w2sdmsyk4OFiTJk1SSEiIVwoF8Pc2LjHSo+P+FRrt5UoAAABwJ3I7/ErSQw89pOXLl2vu3LmKi4vT0aNHdfHiRRUrVkyVK1dW8+bN1bNnT5UqVcrb9QIAAAAA4DaPwq8kBQUFqW/fvurbt6836wEAAAAAwOvcXvAKAAAAAIA7DeEXAAAAAGB6hF8AAAAAgOkRfgEAAAAApkf4BQAAAACYHuEXAAAAAGB6hF8AAAAAgOkRfgEAAAAApkf4BQAAAACYHuEXAAAAAGB6hF8AAAAAgOkRfgEAAAAApkf4BQAAAACYnm9+FwDAvL5MjPT42H6h0V6sBAAAAH93hF8AAIAcihyf6PGx0a+HerESAIC7mPYMAAAAADA9wi8AAAAAwPQIvwAAAAAA0yP8AgAAAABMj/ALAAAAADA9wi8AAAAAwPQIvwAAAAAA0yP8AgAAAABMj/ALAAAAADA9wi8AAAAAwPQIvwAAAAAA0yP8AgAAAABMj/ALAAAAADA9wi8AAAAAwPQIvwAAAAAA0yP8AgAAAABM744Jv+fOnVPz5s114MABHTlyRD169FDPnj01atQoWa1WSdKkSZMUERGhp59+Wtu2bcvnigEAAAAABcUdEX7T0tI0cuRIFS1aVJI0evRoDRo0SHPmzJHNZlNsbKx27typhIQELViwQFFRUXrnnXfyuWoAAAAAQEFxR4TfsWPH6umnn1ZISIgkaefOnWrUqJEkqVmzZvr555+1efNmhYWFyWKxqFy5crpx44bOnz+fn2UDAAAAAAoI3/wu4FYWLlyoUqVK6dFHH9WUKVMkSTabTRaLRZLk7++vy5cvKzk5WcHBwfbjMtpLlSrl1OeuXbtuT/EAPOatz2lB68ebfdHP7evLrP14sy/6ub19AQDcV+DDb0xMjCwWi3755Rft2rVLb775pmFENyUlRUFBQQoICFBKSoqhPTAw0GWftWrVyvO6AUhxiZ4f6/g5XephX06f93zux6mvgtZPLvpy7mell/pZ71lBjn0lbvFSP/u9048kJSZ5qR/PLwBDX6e81M9+L/UjSVs868upn/Ve6melF382AECe2Lx5s8v2Aj/t+T//+Y9mz56tWbNmqVatWho7dqyaNWumjRs3SpLWrVun0NBQNWjQQOvXr5fVatWJEydktVpdjvoCAAAAAP5+CvzIrytvvvmmRowYoaioKFWtWlVt27aVj4+PQkND1b17d1mtVo0cOTK/ywQAAAAAFBB3VPidNWuW/d9nz57t9PqAAQM0YMCA21kSAAAAAOAOUOCnPQMAAAAAkFuEXwAAAACA6RF+AQAAAACmR/gFAAAAAJjeHbXgFYDbY1ZipMfHPhsa7cVKAAAAAO9g5BcAAAAAYHqEXwAAAACA6THtGQAA4DaLfC/R42OjR4R6sRIA+Ptg5BcAAAAAYHqEXwAAAACA6RF+AQAAAACmR/gFAAAAAJge4RcAAAAAYHqEXwAAAACA6RF+AQAAAACmR/gFAAAAAJge4RcAAAAAYHqEXwAAAACA6RF+AQAAAACmR/gFAAAAAJge4RcAAAAAYHqEXwAAAACA6RF+AQAAAACmR/gFAAAAAJge4RcAAAAAYHqEXwAAAACA6RF+AQAAAACmR/gFAAAAAJieb34XAMB7vk+M9Oi4LqHRXq4EAAAAKFgY+QUAAAAAmB7hFwAAAABgeoRfAAAAAIDpEX4BAAAAAKZH+AUAAAAAmB7hFwAAAABgejzqCAAA4A4V+Waix8dGjw31YiUAUPAx8gsAAAAAMD1GfoECYE1ipEfHtQ6N9nIlAAAAgDkx8gsAAAAAMD3CLwAAAADA9Ai/AAAAAADTI/wCAAAAAEyP8AsAAAAAMD3CLwAAAADA9Ai/AAAAAADTI/wCAAAAAEyP8AsAAAAAMD3CLwAAAADA9Ai/AAAAAADTI/wCAAAAAEzPN78LAO5UvyZGenzsw6HRXqwEAAAAwK0w8gsAAAAAMD3CLwAAAADA9Ai/AAAAAADTI/wCAAAAAEyP8AsAAAAAMD3CLwAAAADA9Ai/AAAAAADTI/wCAAAAAEzPN78LAAAAQP6LfCXRo+Oivwj1ciUAkDcIv/jbSfwp0uNjQx+N9mIlAAAAAG4Xpj0DAAAAAEyP8AsAAAAAMD3CLwAAAADA9Ai/AAAAAADTI/wCAAAAAEyP8AsAAAAAML0C/6ijtLQ0DRs2TMePH1dqaqr69eun6tWra+jQobJYLLrvvvs0atQoFSpUSJMmTVJcXJx8fX01bNgw1atXL7/LBwAAAAAUAAU+/C5evFjBwcEaN26cLl68qCeffFI1a9bUoEGD1LhxY40cOVKxsbEqV66cEhIStGDBAp08eVIDBgxQTExMfpcPAAAAACgACnz4bdeundq2bStJstls8vHx0c6dO9WoUSNJUrNmzbRhwwZVqVJFYWFhslgsKleunG7cuKHz58+rVKlS+Vk+AAAAAKAAKPDh19/fX5KUnJys1157TYMGDdLYsWNl+X/t3Xl8jXf+/vHrBEFEqrYpkiD2ZWqLYmhtLaWE1K6o6lQzVB8UFbGWRBvVjLZTTbUMRVtm2tp/qBaZ1NIk5TGkgiiiBl87iSWR3L8/PHKGuE+d+3Za5ng9/9KTc18+d3L3ct6573Mfh8P59UuXLikzM1OlSpW6ZbtLly6ZDr979+79fRYPr+OpY8dbczyZ5a05nswi5/fL8tYcT2aR8/tleWsOAPzW7vvhV5KOHz+u4cOHq3///uratavefvtt59eysrIUEBAgf39/ZWVl3fJ4yZIlTfPq1Knzm68Z96/kf9nf9uZjZ3uyZ3Ik6ZjNrII5aR7KSfbQvm324PdotYf2Tfc457as+y3nLrJuz1nnoZxEewsqmJW8y0M56Z7JkaTkEx7KsX8A3JJ10kM56R7KkaRd9rJuy0n0UM46T+3b/ZZjP4vXVQDuNykpKaaP3/d3ez59+rSGDBmisWPHqmfPnpKkunXraseOHZKkhIQEhYaGqnHjxkpMTFReXp7+85//KC8vj0ueAQAAAACS/gfO/MbHx+vixYuaM2eO5syZI0maMGGCoqOjFRcXp5CQEHXs2FGFChVSaGio+vTpo7y8PE2ePPkerxwAAAAAcL+474ffiRMnauLEibc9vnjx4tseGzFihEaMGPF7LAsAAAAA8D/kvr/sGQAAAACAu8XwCwAAAADwegy/AAAAAACvx/ALAAAAAPB6DL8AAAAAAK9339/tGciX/P8ibG8b2inegysBAACuvBaRbGu7uPhQD68EAG7FmV8AAAAAgNdj+AUAAAAAeD2GXwAAAACA12P4BQAAAAB4PYZfAAAAAIDXY/gFAAAAAHg9hl8AAAAAgNdj+AUAAAAAeD2GXwAAAACA12P4BQAAAAB4PYZfAAAAAIDXY/gFAAAAAHg9hl8AAAAAgNdj+AUAAAAAeD2GXwAAAACA1yt8rxcA75f8jwhb24X2ivfwSgAAAAA8qDjzCwAAAADwepz5BQAAwH1nckSy7W2nxYd6cCUAvOGeFUYAAB3gSURBVAVnfgEAAAAAXo/hFwAAAADg9Rh+AQAAAABej/f8wqXkv9u8S/ML3KUZAAAAwP2FM78AAAAAAK/H8AsAAAAA8HoMvwAAAAAAr8fwCwAAAADwetzwCgAAAHDDhxHJtrb7S3yoh1cCwA7O/AIAAAAAvB7DLwAAAADA63HZMwAAALzW2zYvVZaksVyuDHgVzvwCAAAAALwewy8AAAAAwOsx/AIAAAAAvB7DLwAAAADA6zH8AgAAAAC8HsMvAAAAAMDrMfwCAAAAALwewy8AAAAAwOsVvtcLAAAAAB4kiyKSbW03MD7UwysBHiyc+QUAAAAAeD2GXwAAAACA12P4BQAAAAB4PYZfAAAAAIDXY/gFAAAAAHg9hl8AAAAAgNdj+AUAAAAAeD0+59fLJL8fYXvb0BHxHlwJAAAAANw/OPMLAAAAAPB6DL8AAAAAAK/H8AsAAAAA8HoMvwAAAAAAr8cNrwAAAID/QV9HJNveNjw+1IMrAf43cOYXAAAAAOD1GH4BAAAAAF6P4RcAAAAA4PUYfgEAAAAAXo8bXt0nkt+MsL1t6Ph4D64EAAAAD5Jv7uLGWU/ddOOs7XeR05wbcOF3wJlfAAAAAIDX48zvXUqOsnfGNnQGZ2sBAAAA4PfC8AsAAADgvpIckWhru9D4VgVy1tnMedrWdri/cdkzAAAAAMDredWZ37y8PE2dOlX79u2Tr6+voqOjVblyZdPnJr9q83Ll97hcGQAAAHiQJEf8w/a2ofG9PLgS3A2vGn43btyo7OxsLV26VLt27dJbb72lDz/88F4vCwAAAACUHPF329uGxr/gwZU8mLxq+E1JSdHjjz8uSWrYsKH27Nlzj1cEAAAAAPev5Ig3bW0XGj/ewyv57TkMwzDu9SI8ZcKECerQoYNat24tSWrTpo02btyowoX/O+OnpKTcq+UBAAAAAH4HTZo0ue0xrzrz6+/vr6ysLOd/5+Xl3TL4SubfBAAAAACAd/Oquz03btxYCQkJkqRdu3apZs2a93hFAAAAAID7gVdd9px/t+f9+/fLMAzNmDFD1apVu9fLAgAAAADcY141/Np15swZPfvss5o/f75KlSqliRMn6uLFi8rNzdXMmTMVHBxsK+tvf/ubTp8+LUk6duyYGjRooL/+9a+Wc7KzszVlyhQVKlRIVapUUUxMjHx83Dtpf3PO1atXNWXKFPn6+qpOnTqaMGGC2znh4eHy9/eXJAUGBqpPnz6KiYlRoUKF1KpVK73yyiu2ct58803l5uZq1KhR6tmzp5544glbOWFhYZo9e7YKFy6sMmXKKDY2VsWLF7ec06NHD8XGxsrhcKhp06YaO3asW+txtW+SFB8fr3379rn9sy+Y065dO8XGxqpChQqSpBEjRuixxx6znBMREaEpU6YoJydHvr6+iouL08MPP2w555dffnF+7eeff1Z4eLjGjBljOadr166aNWuWChcurBYtWmjUqFF3zHCV9cwzz2jWrFkqXry4Hn/8cQ0bNsytnI8++kjfffedcnJy1K9fPz322GOKjIyUw+FQjRo1NGXKFLf+HymY06vXjY80mDFjhqpWrap+/frZWk/9+vU1ffp0FSpUSL6+voqNjVXZsmUt5zRq1EiTJk2SYRiqUqWKoqOjb3tLiNV9W7VqlRYvXqylS5fayqlXr55efvllValSRZLUr18/de7c2XJOu3btbHV2wZytW7fa7muzn5udzi6YU7duXcud/dVXX+nrr7+WJF27dk179+7VokWLLPe1Wc7333+vEiVKWO5rs6xZs2Zp/vz5ljrbLOfvf/+75c52tW8BAQGW+tosJy4uznJfm+V89tlneueddyz3tVlWSEiIAgICJLnf2WY5b7/9tubOnWups81yYmNjNXfuXEt9nZOTo8jISB07dkw+Pj6aPn26ChcubLmvzXLyT5JY7WuzrOzsbMudbZZjGIblzv61fbPS12Y5165ds9XXZll2Xmeb5dh5je3qZ2a1r81y7L7Gzs7O1vjx43X06FH5+/tr8uTJOn/+vOXONsupUqWK5dfYZjnHjx+3/BrbLOf06dOW+9rVfknWX187GQ+47OxsY9iwYUaHDh2M9PR0Y9y4ccaaNWsMwzCMbdu2GZs2bbKdle/8+fNGWFiYcfLkSVs5w4YNMzZv3mwYhmG89tprxrfffmsrJzw83EhJSTEMwzDi4uKM5cuXu5Vz9epVo1u3brc8FhYWZhw5csTIy8sz/vznPxupqam2co4cOWL06dPHaNOmjbFlyxbb6+nQoYNx6tQpwzAMY9asWcbChQtt5YSHhxsZGRmGYRjGgAED3NovV1mGYRibN282+vTpY4wcOdJ2TlxcnLFu3Tq3tv+1nIEDBxo7d+40DMMw1q1bZ/z444+2cvJlZGQY4eHhRmZmpq2cbt26GQcOHDDy8vKMvn37GmlpaXfMMcvKzc01Wrdu7fy5jR492khKSrpjzvbt242XX37ZyM3NNTIzM4333nvPePnll43t27cbhmEYkyZNMjZs2GAr58yZM8aLL75otG/f3vjss8/c2i+znOeee8746aefDMMwjM8//9yYMWOGrZy//OUvxg8//GAYhmGMGzfOrf1ylWUYhpGammoMGjTI6NWrl+2cZcuWGfPmzXNr+1/LsdPZrvbLMKz3tVmWnc42y7Hb2fmmTp1qfPHFF7b62izHTl+7yrLT2WY5dju7YI5hWO9rsxw7fW2WY6evXWXls9LZZjl2O7tgjp2+/uabb4xXX33VMAzDSExMNF555RVbfW2WY6evXWXZ6WyzHDudbZZjGNb72izHTl+7yrLT2a72zTCsdbZZjp2+Nsux29eLFi0yJk6caBiGYRw8eNAYMmSIrc42y7HT2WY5dvraLMdOX5vlGMbd9bVXvefXjtjYWPXt21fly5eXJP344486efKkBg8erFWrVrl1hs1VVr73339fAwYMuO1xd3Pq1Kmj8+fPyzAMZWVluX3GpmDOyZMn1bhxY0k33h/t7p2v09LSdOXKFQ0ZMkSDBg1SUlKSsrOzFRwcLIfDoVatWmnr1q2Wc3bt2qXLly8rJiZGzZo1c2strnIWLVrk/O3q9evXVbRoUVs5y5YtU1BQkLKyspSZmSk/Pz/bazpy5IiWLl2qV1999a72LTU1VV9++aX69++vt956S9evX7ecs3PnTp09e1abNm3SwIEDtWvXLj366KO21pMvJiZGY8eOVYkSJWzl5B/XOTk5unbtmgoVKnTHHLOslJQUBQQEKCgoSNKNY/vHH3+8Y05iYqJq1qyp4cOHKyIiQm3atFFqaqrz//knnnjCrePaLCcrK0sjRoxQt27d3NonVzlxcXGqU6eOJCk3N9et49os5/3331fTpk2VnZ2tU6dOOc+a28k6d+6c4uLiFBUVdVf7tmfPHm3evFnPPfecoqKilJmZaSvHTmeb5eSz2tdmWXY62yzHbmdL0u7du5Wenq5nnnnGVl8XzOnTp4+tvnaVZaezzXLsdnbBHDt9bZZjp68L5nTr1s1WX7taUz4rnW2WY7ezb8558sknbfV11apVlZubq7y8PGVmZqpw4cK2+tosx05fu8qy09lmOXY62yzHTl+b5djpa1dZdjrbLCeflc42y7HT12Y5dvs6PT3deUY2JCREu3fvttXZBXMOHjxoq7PNcuz0tVmOnb42y7mbvpa87IZXVn311VcqXbq087OBpRuXTgQEBGjBggWqUKGCPv74Y9tZ0o3Ljrdt26Znn33Wdk7+ZRidOnXSmTNn3DqIzXKCgoL0ww8/SJI2bdqkK1euuLWmYsWK6cUXX9S8efP0xhtvaPz48bdc7lCiRAldunTJcs6YMWNUvXp1y+/LNsspXbq0JGnDhg3asWOHunfvbitHunGztK5du6ps2bJ65JFHbK9p8uTJmjZtmqUXCGY5zZo106RJk7RkyRJdvnxZX3zxheWc0aNH68CBA2rRooU+/fRTXbhwwXkpmtX1XL9+XWlpacrKylKLFi1s71e1atUUERGhzp07q0KFCgoJCbGVNX78eGVmZurgwYPKzc1VQkKCLl++fMecc+fOac+ePXr33XedazIMQw6HQ5L7x7VZTmBgoBo0aODW/vxaTrly5STd+KXc4sWLNXjwYFs5Pj4+OnbsmLp06aJz586pdu3attY0evRoRUVFafz48ZZeQJut6dFHH9Xrr7+uJUuWKCgoSB988IGtHDud7epnb7WvXWXZ6WxXx5GdzpZuXEI9fPhwZWZm3vLC2d3jumCOJNWuXfuu7qNxc1b+C1UrnW2WU7hwYVudfXNOVlaWpk2bZrmvzdbTsmVLy31dMOfChQu2+trVmiRZ7myznFq1atnq7JtzSpcuratXr1ruaz8/Px07dkydOnXSpEmTNHDgQFt9bZYTFBRkua9dZd18IsXdzjbLKVSokOXOLpgzYMAATZgwwXJfm63HTl+7yrLT2WY5kvXX2GY5dvra1XFkp6/r1KmjTZs2yTAM7dq1S5cuXbplKHT32C6Yc/LkSdWoUcNyZ5vllClTRpK1vjbLcTgclvvaLGfq1Km2+1p6wIffL7/8Ulu3btXAgQO1d+9ejRs3Tj4+PmrXrp0kqV27dtqzZ4/trFOnTmndunXq0qWL2z8gs5zIyEgtWbJE69atU/fu3fXWW2/Zynnttdf00Ucf6fnnn1eZMmXcev+QdOM3XGFhYXI4HKpatapKliyp8+fPO7+elZXlfD+RlZxSpUrp1KlTbq3BnZwFCxZo/vz5+uSTT9z+batZTsOGDfXdd9+pbt26mjt3rq015f/DNWrUKM2YMUPbt293K8tsTV26dFFQUJAcDofat2+vn376yXJO/s+6efPmcjgcatu2rVvHtqvv0cqVK53v/XSH2ffn7bff1po1a7Rx40ZVrlxZ8+fPt5VVqlQpzZw5U1OnTtXQoUNv2d9fU6pUKbVq1Uq+vr4KCQlR0aJFb/kHxt3j2izn7Nmzbu2LOzlr167VlClTNHfuXOcveezkVKpUSRs2bFC/fv3c6hCzrBMnTujw4cOaOnWqXnvtNaWnpysmJsbWmtq0aaP69etLkp566im3jmuznNzcXMud7ep7ZLWvXWWNGTPGcmeb5URFRdnq7IsXL+rQoUNq3rz5bR8B6O5xXTDnbpllWe1sVzl2OvvmnO+//16nTp2y3Ndm6+nRo4flvi6Y89BDD6lEiRKW+9rVmiRZ7uyCORcvXtRHH31kq7NvznE4HLb6esGCBWrVqpXWr1+vFStWKDIyUjk5Oc6vu3tcm+Vcu3bNrf1wN8tqZ7vKsdrZBXP69++v/fv3W+5rs/U88cQTlvvaVVapUqUsd7ar75HVzjbLiYmJsdzXZjlTp0611dc9evSQv7+/+vfvr2+++Ua1a9e+ZXB299gumFOvXj1bw6GrHKt97SrHal8XzAkODtaZM2ds9XW+B3r4XbJkiRYvXqxFixapTp06io2NVdu2bbVlyxZJUlJSkqpXr247q1y5ctq2bZvbNwVxlRMYGOj8zX358uV18eJFWzmpqamaNWuWFi5cqPPnz6tly5Zuremf//ynswxOnjypK1euyM/PTxkZGTIMQ4mJiQoNDbWck5mZ6TyzZYVZzpdffqnk5GQtWLDArX9szHIuXbqkkSNH6sKFC5Ju/LbN3RuCFcxyOBxat26dFi1apKioKDVv3lxDhw61taZevXrpxIkTkqRt27apXr16lnOysrJUr149JScnS7pxbNeoUcNyTv7PbPv27bdd5WAlJycnR4GBgc7fbrp7XLta0/bt2zVv3jx98sknysjI0J/+9Kc75jRp0kT/+te/ZBiG87hu0aKFduzYIUlKSEhw67g2yylVqpRb+3KnnISEBOf/x/mXCdrJmTBhgg4fPizJ2nFdMOsPf/iDVq9erUWLFikuLk7Vq1fXhAkTbK1p6NCh+ve//y3J/ePaLKd9+/aWO9vVz8xqX7vKCg4OttzZZjkpKSm2OjspKcl5hs/f319FihSx3NcFc+5WwawPP/zQcmcXzDEMQ/3797fV2TfndOjQQStXrrTc12brCQsLs9zXBXOKFSumKlWqWO5rs6x8VjvbbE1+fn62OrvgehITEy33dUBAgEqWLClJeuihh3T9+nXVrVvXcl+b5eTm5rq1H+5krV271nJnm+VERERY7uyCOZUqVXIe11b62tV6rPa1q6yGDRta7mxXPzernW2WU7JkSct9bZazadMmW329e/dutWjRQp9//rmefvppValSxVZnF8xx9/hzJ8dOXxfMCQwMtNXXBXPq1q1ru6/zuffm0QfIuHHjNHHiRH3xxRfy9/fXO++8c1d5hw4dsn0A5ouOjtaoUaNUuHBhFSlSRNOnT7eVU7lyZQ0ePFjFixdXs2bN1Lp1a7e269mzp8aPH69+/frJ4XBoxowZ8vHx0ZgxY5Sbm6tWrVq5dcmQWY6771/+tZxp06ZpyJAhqlu3rl566SVJUqdOndS/f39LOW+++abOnj2rl156Sb6+vipXrpyio6NtrclT+/bmm2/q8uXLeuWVV1SsWDFVq1ZNvXv3trUePz8/vfHGG8rNzVVgYKBbd2h2tV+nTp1y+7eaZjmzZs3SmTNnNGTIEBUtWlQlS5Z0+2yk2ZrS09PVq1cvFStWTF27dnXrhWLbtm2VlJSknj17yjAMTZ48WYGBgZo0aZLi4uIUEhKijh072sqx89tWs5zRo0erQoUKGjFihCSpadOmd3yPi1lOiRIlFBkZqSJFiqh48eJuH9e/5b6VLl1a06dPV5EiRVS2bFm3es0sJyQkxHJnu9ovO31tllW8eHHLnW2Wk5OTY6uzDx06pMDAQOd/519GbaWvzXLuxs1Zp0+f1gcffGC5swvmOBwODRkyxFZne2rfCq4nOjracl+brWfGjBmW+9pVliTLnV0wx9fXV5GRkbY6u+B6ypcvb7mvBw8erKioKPXv3185OTkaNWqU6tevb7mvzXKsvE/817JGjhyp6Ohoy51ttqZKlSpZ7mxP7ZtZTkhIiOW+dpXVuHFjy53tat+sdrZZToUKFSz3tVlOiRIlbPV15cqV9e677yo+Pl4lS5ZUTEyMjh8/brmzzXLsKJjzxhtvqGPHjpb72mw9u3fvttzXntqvm/FRRwAAAAAAr/dAX/YMAAAAAHgwMPwCAAAAALwewy8AAAAAwOsx/AIAAAAAvB7DLwAAAADA6/FRRwAA/Aays7O1fPlyfffdd0pLS9PZs2fl4+OjihUrqkmTJgoPD1fjxo3v9TJ/Ezt27NCgQYMkSampqc6PfouMjNTXX3+trl27atasWfdyiQCABxDDLwAAHpaYmKiJEyfq+PHjkqSHH35Y1atXV2ZmpjIyMnTw4EEtW7ZMHTt21IwZM+Tv73+PVwwAgPdj+AUAwIOWL1+uqKgo5ebmKjQ0VKNGjVKTJk3kcDgkSZmZmfrHP/6hDz74QOvXr1d6eroWLlyocuXK3eOVAwDg3XjPLwAAHpKamqpJkyYpNzdXffv21aJFixQaGuocfCXJ399fL7zwgj7//HOVL19eBw8eVFRU1D1cNQAADwaGXwAAPGTmzJnKzs7WH//4R02ePFk+Pq7/ma1Ro4amTZsmSUpISNDy5ct/r2UCAPBAYvgFAMADDhw4oO3bt0uSXnzxRRUqVOiO27Rt21aNGjWSJC1evFiXL19Wo0aNVKtWLX3zzTcut3vhhRdUq1YtzZ49+5bHT58+rZkzZ6pz585q0KCBGjVqpB49emj+/Pm6du3abTnvv/++atWqpVmzZmnjxo3q2LGj6tevr3bt2mnNmjXO5x05ckQxMTEKCwtTaGio6tWrp2bNmmnQoEFatmyZcnNz3foeAQBwLzH8AgDgAVu3bpUk+fj46PHHH3d7u6eeekqStGfPHl25ckVPP/20JGnlypWmzz958qRzyH722Wedj6ekpOiZZ57RvHnzlJGRoaCgIFWsWFGpqamKjY1V7969derUKdPMpKQkvfrqq7p48aKqVaum//u//1OdOnUkSRs3blSXLl306aef6ujRo6pYsaJCQkKUnZ2tHTt2aNKkSXr99dfd3l8AAO4Vhl8AADwgLS1NklSpUiVLd2+uW7euJMkwDO3fv189evSQJG3evFmXLl267fmrVq1SXl6eQkNDFRwcLOnGQDxs2DCdP39evXv31tatW7V69WqtWbNGGzZsUIMGDZSWlqaRI0earmHXrl1q166dtmzZohUrVighIUEhISG6cOGCoqKilJ2drX79+mnr1q1auXKlVq1ape+//14DBw6UJK1evVoHDhxw/5sFAMA9wPALAIAHnDt3TpJUqlQpS9uVKVPG+eezZ88qNDRUlStXVnZ2ttatW3fb81esWCHp1rO+8+bN0/nz59WuXTtNnz5dAQEBzq8FBwdrzpw58vf3V3JysrZs2WK6jnHjxsnX11eSVLp0aUlScnKycnJyVK5cOU2cOFHFixd3Pt/Pz0+RkZEqUqSIJGn//v2W9hsAgN8bwy8AAB6Q/57a/GHQXTe/N9gwDElSeHi4pNsvfd67d6/2798vPz8/5+XR0o1LkyUpLCzM9O8oW7asWrZsKUnatGnTbV8vV66cgoKCbnu8ffv22rlzpzZu3KjChW//dMRr1645h/0rV6643kkAAO4DfM4vAAAekD8EXrhwwdJ2+WeMpf+ecQ0PD9d7772npKQknThxQo888oik/5717dixo0qUKCFJysrK0rFjxyRJc+bM0aeffmr69+Q/5+eff77ta+XLl//VNRYrVkxpaWlKS0vT0aNHlZGRofT0dB04cEA5OTmS/ju4AwBwv2L4BQDAA2rXrq21a9cqIyNDV65cueUS4V+zd+9e559r1qwpSXrkkUf0pz/9SYmJiVq1apVeeukl5ebmavXq1ZJuveQ5MzPT+Wd3Lj02ex9x0aJFXT5/y5YtiomJ0ZEjR255vHz58nr66aeVkJBgeeAHAOBeYPgFAMAD2rRpo7i4OOXk5Gjz5s3q1KmTW9vlX7Jcr149lS1b1vl4jx49bhl+t27dqlOnTikoKEhNmzZ1Pu/mIXvVqlXOAdoTtm/froiICOXl5alhw4bq2rWratasqWrVqjnfq2zlztYAANxLvOcXAAAPqFWrlpo1ayZJio+PV3Z29h23SUpKcn5s0YABA2752pNPPqmHHnpI+/bt0+HDh7Vq1SpJUvfu3eVwOJzPCwgIcA7N6enpLv+uffv2ae/evZbO0n788cfKy8tT8+bN9dlnn2nAgAF67LHHnINvdnb2LZdtAwBwP2P4BQDAQ6ZPny4/Pz+lpaVpypQpys3NdfncjIwMjR07VpLUsmVL502u8vn6+qpLly6SpLVr1+rbb7+Vw+G47XnSjbPOkrR48WLl5eXd9vVLly5p0KBB6t69uxYuXOj2/vzyyy+SblzSffONufItX77c+Z7f69evu50LAMC9wPALAICHVK5cWTExMfL19dVXX32l559/Xjt37rzlOZcvX9bSpUvVu3dvHT9+XMHBwYqNjb3lbG6+/Pf2fvLJJ8rMzFSzZs1UqVKl2543dOhQ+fn5KSUlRWPHjtXZs2edXzt27JiGDh2q8+fPq2TJknruuefc3p+QkBBJ0po1a3Tw4EHn49euXdPixYsVHR3tfOzq1atu5wIAcC/wnl8AADyoc+fOqlSpkkaOHKmkpCT17dtXZcqUUYUKFXTt2jUdOXLEeUl0p06dFB0dLX9/f9Os+vXrq2bNms4bWd18o6ubVa5cWbNnz9aoUaO0evVqrV+/XtWrV1dOTo4OHz6s69evy8/PT3Pnzr3lc4XvZPjw4c73Gnft2lVVqlSRr6+vjhw5osuXL6t06dKqWrWq0tLSdOLECYvfKQAAfl+c+QUAwMMaNGig9evXKzo6Wq1bt5aPj4/27duno0ePKjg4WH379tXSpUs1e/Zsl4Nvvh49ekiS/P391aFDB5fPa926tdasWaPBgwcrODhYhw4d0pEjR1SpUiX1799fK1euVOPGjS3tR/369bVixQqFhYWpYsWKysjIUEZGhoKDgxUREaHVq1dr0KBBkqTNmzfzcUcAgPuaw+BfKgAAAACAl+PMLwAAAADA6zH8AgAAAAC8HsMvAAAAAMDrMfwCAAAAALwewy8AAAAAwOsx/AIAAAAAvB7DLwAAAADA6zH8AgAAAAC8HsMvAAAAAMDrMfwCAAAAALwewy8AAAAAwOv9f/xgPlcMU6oOAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10ac09e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16,8))\n",
    "sns.set_style(\"whitegrid\")\n",
    "plt.title('Grouping players by Overall', fontsize=30, fontweight='bold', y=1.05,)\n",
    "plt.xlabel('Number of players', fontsize=25)\n",
    "plt.ylabel('Players Age', fontsize=25)\n",
    "sns.countplot(x=\"Overall\", data=FIFA18, palette=\"hls\");\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.3 Preferred Position"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10b5785f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16,8))\n",
    "sns.set_style(\"whitegrid\")\n",
    "plt.title('Grouping players by Preferred Position', fontsize=30, fontweight='bold', y=1.05,)\n",
    "plt.xlabel('Number of players', fontsize=25)\n",
    "plt.ylabel('Players Age', fontsize=25)\n",
    "sns.countplot(x=\"Position\", data=FIFA18, palette=\"hls\");\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.4 Nationality"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "IOPub data rate exceeded.\n",
      "The notebook server will temporarily stop sending output\n",
      "to the client in order to avoid crashing it.\n",
      "To change this limit, set the config variable\n",
      "`--NotebookApp.iopub_data_rate_limit`.\n"
     ]
    },
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "data": [
        {
         "autocolorscale": true,
         "colorbar": {
          "title": "Amount of Players"
         },
         "locationmode": "country names",
         "locations": [
          "Afghanistan",
          "Albania",
          "Algeria",
          "Angola",
          "Antigua & Barbuda",
          "Argentina",
          "Armenia",
          "Australia",
          "Austria",
          "Azerbaijan",
          "Barbados",
          "Belarus",
          "Belgium",
          "Belize",
          "Benin",
          "Bermuda",
          "Bolivia",
          "Bosnia Herzegovina",
          "Brazil",
          "Brunei Darussalam",
          "Bulgaria",
          "Burkina Faso",
          "Burundi",
          "Cameroon",
          "Canada",
          "Cape Verde",
          "Central African Rep.",
          "Chad",
          "Chile",
          "China PR",
          "Colombia",
          "Comoros",
          "Congo",
          "Costa Rica",
          "Croatia",
          "Cuba",
          "Curacao",
          "Cyprus",
          "Czech Republic",
          "DR Congo",
          "Denmark",
          "Dominican Republic",
          "Ecuador",
          "Egypt",
          "El Salvador",
          "England",
          "Equatorial Guinea",
          "Eritrea",
          "Estonia",
          "Ethiopia",
          "FYR Macedonia",
          "Faroe Islands",
          "Fiji",
          "Finland",
          "France",
          "Gabon",
          "Gambia",
          "Georgia",
          "Germany",
          "Ghana",
          "Gibraltar",
          "Greece",
          "Grenada",
          "Guam",
          "Guatemala",
          "Guinea",
          "Guinea Bissau",
          "Guyana",
          "Haiti",
          "Honduras",
          "Hong Kong",
          "Hungary",
          "Iceland",
          "India",
          "Iran",
          "Iraq",
          "Israel",
          "Italy",
          "Ivory Coast",
          "Jamaica",
          "Japan",
          "Kazakhstan",
          "Kenya",
          "Korea DPR",
          "Korea Republic",
          "Kosovo",
          "Kuwait",
          "Kyrgyzstan",
          "Latvia",
          "Lebanon",
          "Liberia",
          "Libya",
          "Liechtenstein",
          "Lithuania",
          "Luxembourg",
          "Madagascar",
          "Mali",
          "Malta",
          "Mauritania",
          "Mauritius",
          "Mexico",
          "Moldova",
          "Montenegro",
          "Montserrat",
          "Morocco",
          "Mozambique",
          "Namibia",
          "Netherlands",
          "New Caledonia",
          "New Zealand",
          "Niger",
          "Nigeria",
          "Northern Ireland",
          "Norway",
          "Oman",
          "Palestine",
          "Panama",
          "Paraguay",
          "Peru",
          "Philippines",
          "Poland",
          "Portugal",
          "Puerto Rico",
          "Qatar",
          "Republic of Ireland",
          "Romania",
          "Russia",
          "San Marino",
          "Saudi Arabia",
          "Scotland",
          "Senegal",
          "Serbia",
          "Sierra Leone",
          "Slovakia",
          "Slovenia",
          "Somalia",
          "South Africa",
          "Spain",
          "Sri Lanka",
          "St Kitts Nevis",
          "St Lucia",
          "Sudan",
          "Suriname",
          "Swaziland",
          "Sweden",
          "Switzerland",
          "Syria",
          "São Tomé & Príncipe",
          "Tanzania",
          "Thailand",
          "Togo",
          "Trinidad & Tobago",
          "Tunisia",
          "Turkey",
          "Turkmenistan",
          "Uganda",
          "Ukraine",
          "United States",
          "Uruguay",
          "Uzbekistan",
          "Venezuela",
          "Vietnam",
          "Wales",
          "Zambia",
          "Zimbabwe"
         ],
         "marker": {
          "line": {
           "color": "rgb(180,180,180)",
           "width": 0.5
          }
         },
         "reversescale": false,
         "text": [
          "Afghanistan",
          "Albania",
          "Algeria",
          "Angola",
          "Antigua & Barbuda",
          "Argentina",
          "Armenia",
          "Australia",
          "Austria",
          "Azerbaijan",
          "Barbados",
          "Belarus",
          "Belgium",
          "Belize",
          "Benin",
          "Bermuda",
          "Bolivia",
          "Bosnia Herzegovina",
          "Brazil",
          "Brunei Darussalam",
          "Bulgaria",
          "Burkina Faso",
          "Burundi",
          "Cameroon",
          "Canada",
          "Cape Verde",
          "Central African Rep.",
          "Chad",
          "Chile",
          "China PR",
          "Colombia",
          "Comoros",
          "Congo",
          "Costa Rica",
          "Croatia",
          "Cuba",
          "Curacao",
          "Cyprus",
          "Czech Republic",
          "DR Congo",
          "Denmark",
          "Dominican Republic",
          "Ecuador",
          "Egypt",
          "El Salvador",
          "England",
          "Equatorial Guinea",
          "Eritrea",
          "Estonia",
          "Ethiopia",
          "FYR Macedonia",
          "Faroe Islands",
          "Fiji",
          "Finland",
          "France",
          "Gabon",
          "Gambia",
          "Georgia",
          "Germany",
          "Ghana",
          "Gibraltar",
          "Greece",
          "Grenada",
          "Guam",
          "Guatemala",
          "Guinea",
          "Guinea Bissau",
          "Guyana",
          "Haiti",
          "Honduras",
          "Hong Kong",
          "Hungary",
          "Iceland",
          "India",
          "Iran",
          "Iraq",
          "Israel",
          "Italy",
          "Ivory Coast",
          "Jamaica",
          "Japan",
          "Kazakhstan",
          "Kenya",
          "Korea DPR",
          "Korea Republic",
          "Kosovo",
          "Kuwait",
          "Kyrgyzstan",
          "Latvia",
          "Lebanon",
          "Liberia",
          "Libya",
          "Liechtenstein",
          "Lithuania",
          "Luxembourg",
          "Madagascar",
          "Mali",
          "Malta",
          "Mauritania",
          "Mauritius",
          "Mexico",
          "Moldova",
          "Montenegro",
          "Montserrat",
          "Morocco",
          "Mozambique",
          "Namibia",
          "Netherlands",
          "New Caledonia",
          "New Zealand",
          "Niger",
          "Nigeria",
          "Northern Ireland",
          "Norway",
          "Oman",
          "Palestine",
          "Panama",
          "Paraguay",
          "Peru",
          "Philippines",
          "Poland",
          "Portugal",
          "Puerto Rico",
          "Qatar",
          "Republic of Ireland",
          "Romania",
          "Russia",
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      ]
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     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Grouping the data by countries\n",
    "valcon = FIFA18.groupby(\"Nationality\").size().reset_index(name=\"Count\")\n",
    "\n",
    "# Plotting the choropleth map\n",
    "init_notebook_mode()\n",
    "plotmap = [ dict(\n",
    "        type = 'choropleth',\n",
    "        locations = valcon[\"Nationality\"],\n",
    "        locationmode = 'country names',\n",
    "        z = valcon[\"Count\"],\n",
    "        text = valcon[\"Nationality\"],\n",
    "        autocolorscale = True,\n",
    "        reversescale = False,\n",
    "        marker = dict(\n",
    "            line = dict (\n",
    "                color = 'rgb(180,180,180)',\n",
    "                width = 0.5\n",
    "            ) ),\n",
    "        colorbar = dict(\n",
    "            title = \"Amount of Players\"),\n",
    "      ) ]\n",
    "\n",
    "layout = dict(\n",
    "    title = \"Nationalities of FIFA 18 Players\",\n",
    "    geo = dict(\n",
    "        showframe = False,\n",
    "        showcoastlines = False,\n",
    "        projection = dict(\n",
    "            type = 'Mercator'\n",
    "        )\n",
    "    )\n",
    ")\n",
    "\n",
    "fig = dict( data=plotmap, layout=layout )\n",
    "iplot(fig)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In case the plot.ly image doesn't show:\n",
    "\n",
    "![nationalities](images/Nationalities.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "England                1630\n",
       "Germany                1140\n",
       "Spain                  1019\n",
       "France                  978\n",
       "Argentina               965\n",
       "Brazil                  812\n",
       "Italy                   799\n",
       "Colombia                592\n",
       "Japan                   469\n",
       "Netherlands             429\n",
       "Republic of Ireland     417\n",
       "United States           381\n",
       "Chile                   375\n",
       "Sweden                  368\n",
       "Portugal                367\n",
       "Mexico                  360\n",
       "Denmark                 346\n",
       "Poland                  337\n",
       "Norway                  333\n",
       "Korea Republic          330\n",
       "Saudi Arabia            329\n",
       "Russia                  306\n",
       "Scotland                300\n",
       "Turkey                  291\n",
       "Belgium                 272\n",
       "Name: Nationality, dtype: int64"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "FIFA18[\"Nationality\"].value_counts().head(25)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I can see that the players are very centralized in Europe. To be precise, England, Germany, Spain, and France.\n",
    "\n",
    "### 2.5 Value\n",
    "Let's see the 20 players with highest value:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sorted_players = FIFA18.sort_values([\"ValueNum\"], ascending=False).head(20)\n",
    "players = sorted_players[[\"Name\" ,\"Age\" ,\"Nationality\" ,\"Club\" ,\"Position\" ,\"Value\"]].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table><tr><th>Name</th><th>Age</th><th>Nationality</th><th>Club</th><th>Position</th><th>Value</th></tr><tr><td>Neymar</td><td>25</td><td>Brazil</td><td>Paris Saint-Germain</td><td>LW</td><td>€123M</td></tr><tr><td>L. Messi</td><td>30</td><td>Argentina</td><td>FC Barcelona</td><td>RW</td><td>€105M</td></tr><tr><td>L. Suárez</td><td>30</td><td>Uruguay</td><td>FC Barcelona</td><td>ST</td><td>€97M</td></tr><tr><td>Cristiano Ronaldo</td><td>32</td><td>Portugal</td><td>Real Madrid CF</td><td>ST</td><td>€95.5M</td></tr><tr><td>R. Lewandowski</td><td>28</td><td>Poland</td><td>FC Bayern Munich</td><td>ST</td><td>€92M</td></tr><tr><td>E. Hazard</td><td>26</td><td>Belgium</td><td>Chelsea</td><td>LW</td><td>€90.5M</td></tr><tr><td>K. De Bruyne</td><td>26</td><td>Belgium</td><td>Manchester City</td><td>RM</td><td>€83M</td></tr><tr><td>T. Kroos</td><td>27</td><td>Germany</td><td>Real Madrid CF</td><td>CDM</td><td>€79M</td></tr><tr><td>P. Dybala</td><td>23</td><td>Argentina</td><td>Juventus</td><td>ST</td><td>€79M</td></tr><tr><td>G. Higuaín</td><td>29</td><td>Argentina</td><td>Juventus</td><td>ST</td><td>€77M</td></tr><tr><td>A. Griezmann</td><td>26</td><td>France</td><td>Atlético Madrid</td><td>LW</td><td>€75M</td></tr><tr><td>Thiago</td><td>26</td><td>Spain</td><td>FC Bayern Munich</td><td>CDM</td><td>€70.5M</td></tr><tr><td>G. Bale</td><td>27</td><td>Wales</td><td>Real Madrid CF</td><td>RW</td><td>€69.5M</td></tr><tr><td>A. Sánchez</td><td>28</td><td>Chile</td><td>Arsenal</td><td>RM</td><td>€67.5M</td></tr><tr><td>S. Agüero</td><td>29</td><td>Argentina</td><td>Manchester City</td><td>ST</td><td>€66.5M</td></tr><tr><td>P. Pogba</td><td>24</td><td>France</td><td>Manchester United</td><td>CDM</td><td>€66.5M</td></tr><tr><td>C. Eriksen</td><td>25</td><td>Denmark</td><td>Tottenham Hotspur</td><td>LM</td><td>€65M</td></tr><tr><td>De Gea</td><td>26</td><td>Spain</td><td>Manchester United</td><td>GK</td><td>€64.5M</td></tr><tr><td>M. Verratti</td><td>24</td><td>Italy</td><td>Paris Saint-Germain</td><td>CDM</td><td>€64.5M</td></tr><tr><td>M. Neuer</td><td>31</td><td>Germany</td><td>FC Bayern Munich</td><td>GK</td><td>€61M</td></tr></table>"
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       "<IPython.core.display.HTML object>"
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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.display import HTML, display\n",
    "\n",
    "table_content = ''\n",
    "for row in players:\n",
    "    HTML_row = '<tr>'\n",
    "    HTML_row += '<td>' + str(row[0]) + '</td>'\n",
    "    HTML_row += '<td>' + str(row[1]) + '</td>'\n",
    "    HTML_row += '<td>' + str(row[2]) + '</td>'\n",
    "    HTML_row += '<td>' + str(row[3]) + '</td>'\n",
    "    HTML_row += '<td>' + str(row[4]) + '</td>'\n",
    "    HTML_row += '<td>' + str(row[5]) + '</td>'\n",
    "    \n",
    "    table_content += HTML_row + '</tr>'\n",
    "\n",
    "display(HTML(\n",
    "    '<table><tr><th>Name</th><th>Age</th><th>Nationality</th><th>Club</th><th>Position</th><th>Value</th></tr>{}</table>'.format(table_content))\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's make a scatter chart of the players' Value with respect to their Age and Overall:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1040d6be0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16,8))\n",
    "sns.set_style(\"whitegrid\")\n",
    "plt.title('Players Value according to their Age and Overall', fontsize=30, fontweight='bold', y=1.05,)\n",
    "plt.xlabel('Age', fontsize=25)\n",
    "plt.ylabel('Overall', fontsize=25)\n",
    "\n",
    "age = FIFA18[\"Age\"].values\n",
    "overall = FIFA18[\"Overall\"].values\n",
    "value = FIFA18[\"ValueNum\"].values\n",
    "\n",
    "plt.scatter(age, overall, s = value/100000, edgecolors='black')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.6 Wage\n",
    "Let's see the 20 players with highest wage:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sorted_players = FIFA18.sort_values([\"WageNum\"], ascending=False).head(20)\n",
    "players = sorted_players[[\"Name\" ,\"Age\" ,\"Nationality\" ,\"Club\" ,\"Position\" ,\"Wage\"]].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table><tr><th>Name</th><th>Age</th><th>Nationality</th><th>Club</th><th>Position</th><th>Wage</th></tr><tr><td>Cristiano Ronaldo</td><td>32</td><td>Portugal</td><td>Real Madrid CF</td><td>ST</td><td>€565K</td></tr><tr><td>L. Messi</td><td>30</td><td>Argentina</td><td>FC Barcelona</td><td>RW</td><td>€565K</td></tr><tr><td>L. Suárez</td><td>30</td><td>Uruguay</td><td>FC Barcelona</td><td>ST</td><td>€510K</td></tr><tr><td>G. Bale</td><td>27</td><td>Wales</td><td>Real Madrid CF</td><td>RW</td><td>€370K</td></tr><tr><td>R. Lewandowski</td><td>28</td><td>Poland</td><td>FC Bayern Munich</td><td>ST</td><td>€355K</td></tr><tr><td>L. Modrić</td><td>31</td><td>Croatia</td><td>Real Madrid CF</td><td>CDM</td><td>€340K</td></tr><tr><td>T. Kroos</td><td>27</td><td>Germany</td><td>Real Madrid CF</td><td>CDM</td><td>€340K</td></tr><tr><td>S. Agüero</td><td>29</td><td>Argentina</td><td>Manchester City</td><td>ST</td><td>€325K</td></tr><tr><td>Sergio Ramos</td><td>31</td><td>Spain</td><td>Real Madrid CF</td><td>CB</td><td>€310K</td></tr><tr><td>E. Hazard</td><td>26</td><td>Belgium</td><td>Chelsea</td><td>LW</td><td>€295K</td></tr><tr><td>K. Benzema</td><td>29</td><td>France</td><td>Real Madrid CF</td><td>ST</td><td>€295K</td></tr><tr><td>K. De Bruyne</td><td>26</td><td>Belgium</td><td>Manchester City</td><td>RM</td><td>€285K</td></tr><tr><td>Neymar</td><td>25</td><td>Brazil</td><td>Paris Saint-Germain</td><td>LW</td><td>€280K</td></tr><tr><td>I. Rakitić</td><td>29</td><td>Croatia</td><td>FC Barcelona</td><td>CM</td><td>€275K</td></tr><tr><td>G. Higuaín</td><td>29</td><td>Argentina</td><td>Juventus</td><td>ST</td><td>€275K</td></tr><tr><td>A. Sánchez</td><td>28</td><td>Chile</td><td>Arsenal</td><td>RM</td><td>€265K</td></tr><tr><td>M. Özil</td><td>28</td><td>Germany</td><td>Arsenal</td><td>RW</td><td>€265K</td></tr><tr><td>Iniesta</td><td>33</td><td>Spain</td><td>FC Barcelona</td><td>LM</td><td>€260K</td></tr><tr><td>Marcelo</td><td>29</td><td>Brazil</td><td>Real Madrid CF</td><td>LB</td><td>€250K</td></tr><tr><td>J. Rodríguez</td><td>25</td><td>Colombia</td><td>FC Bayern Munich</td><td>RM</td><td>€250K</td></tr></table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from IPython.display import HTML, display\n",
    "\n",
    "table_content = ''\n",
    "for row in players:\n",
    "    HTML_row = '<tr>'\n",
    "    HTML_row += '<td>' + str(row[0]) + '</td>'\n",
    "    HTML_row += '<td>' + str(row[1]) + '</td>'\n",
    "    HTML_row += '<td>' + str(row[2]) + '</td>'\n",
    "    HTML_row += '<td>' + str(row[3]) + '</td>'\n",
    "    HTML_row += '<td>' + str(row[4]) + '</td>'\n",
    "    HTML_row += '<td>' + str(row[5]) + '</td>'\n",
    "    \n",
    "    table_content += HTML_row + '</tr>'\n",
    "\n",
    "display(HTML(\n",
    "    '<table><tr><th>Name</th><th>Age</th><th>Nationality</th><th>Club</th><th>Position</th><th>Wage</th></tr>{}</table>'.format(table_content))\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's make a scatter chart of the players' Wage with respect to their Age and Overall:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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5T686mjhemUwGLy+vIssJFLRuzZ07V7CNqKgoTJo0SRDM8slkMqxbt07peL6goCCMHTtWZeIaxW3s3LkT8+fPF5SD786dO5xgttCwYcPY///www+CYFZRWloavLy81O6nNA4ePIitW7cKplEpJJPJsGzZMsH9DSi4tvnBrKLk5GTMnDmzVNdsaZ06dQozZswocp+5ublYs2YN1q9fX0ElK3Ds2DHs2rVL5TmTlpaGhQsXCtZXxHXMt3fvXsFc7CYmJqXKDfHy5UuEhYVx1g0dOhQikQhDhw7lrD9//jzEYrHKbUkkEnz55Zdqs+BGRETgm2++KbJcS5YsEQSzfLm5uVi2bJna8b+qyGQyfPXVV0qDWb6MjAx88803nFZsZfbt24ft27erPIekUimWLl2qNC/E0qVLBcGsopSUlDLfZ/7991/Bc0xJhuTwf0+lUin7m8uvVHjw4IHS+31CQgLu37/PLuvq6nKedbKzszF+/Pgih4YlJCRg0qRJeP78udrXZWZmYtOmTYL1ivf4BQsWFCtLe15eHr7//ntOJQ/5b6AWWlKpsrKyOJNdF+ratWuJtrNlyxbIZDJ22cbGBq6urqhVqxZSUlLYblWF+A82o0aNwoYNG9jlgIAATJo0ifOaiIgIzk2yVq1anC5ZN27cEIxh6tGjB7p37w6GYRAYGMipef3111/h5OSEOnXqqDwuqVQKIyMjjBs3DrVr18bNmzfZLMNnzpzh/Oiam5vD2dmZbb2NjIyEv78/++OYlJSEAwcO4Ntvv1W5P2Xs7e05P+KKASl//Gzh99a1a1fOj11wcDCbFZT/I8j/Af7rr7848+hVq1YNo0ePhq2tLcRiMW7fvs154IyNjcWLFy9gZ2fHrtuyZYvgYbJly5YYPnw49PX1cevWLQQGBuLZs2dqj93Hx4fTpVokEmHQoEGwt7eHWCzGhQsX2PHA+fn5WLJkCa5evQp9fX2129X08e7btw8hISGc7Xbu3Bn9+vWDSCTCzZs3cffuXfZv9+/fx7lz59habLlcDm9vb+Tm5rKv0dfXh6urK5o3b47ExEQcO3aM8/Czdu1aDBgwgFODvmDBAs7DmK6uLkaMGIHWrVsjPT1dcB1euHABrVu3VtnaC4DdXufOnTFw4EB8+PABQUFB6NChA4CC7o78h2VjY2O4u7ujUaNGePPmDY4dO4a0tDSV+yitwuu5S5cu6Nu3L2QyGY4ePYq4uDj2NRkZGex8q4WioqJw6NAhzrYKv/cGDRrg1atX8PPzK/XQCwCws7PDL7/8guDgYM7nY2dnx37eihV5L1++xI8//sh50Dc2NsaoUaNgZ2eHhIQEnD59mnNd7dmzB23atBFkPlelU6dO+OWXX3D58mVOJUWnTp3YpIHqsge/f/8eIpEIAwcORKdOnZCVlYWjR49y7svR0dGIioribKcirmM+qVQKkUiEkSNHonXr1njy5Al0dHRKtU3++W1ra8tWGg4fPpzTpTY7OxsXLlwQtKgVOnTokKDbuq2tLVxdXVGtWjUEBwcjICCgyHvjxYsXOV2wAaB3795wdHSETCbD9evXOb13Vq9ejV69eqFWrVpFH/D/nDt3jlMOPT09jBkzBk2aNIFEIkFwcDCn11RaWhpCQkI4v8t8hdeso6MjnJycIJVKcfToUU7QnJaWhlu3bmHIkCHsun/++Qf+/v6cbZmYmLD36ri4OBw7dqxYFczq8H+3AJSoC62y1xb+vtja2qJz587sZyCXy3Hu3DnB/dff359TSefk5MTpyr9hwwa8evWKXS68z7do0QIpKSk4deoUexxisRiLFy9WO767sDeXjY0NPDw8IJVKcebMGbayJjg4mPMbKBKJ4OrqijZt2kAulyMyMhKnTp1iyyyRSHD79m2MGTOm6A+MfDYooCUV4unTp+yPslwuR3Z2Nt6+fYvLly8jPj6e89oWLVqUqGusXC5HrVq10KxZM7x8+RKGhobw9fXl3IDd3NzQs2dP9saZnp6OzMxMttuxi4sLNm3axP790aNHiI+P5wSb/FbboUOHcsbiKj5UAAUZnBWTNEybNg2rV69mH2QLxwXNmzdP7fH9/PPPbPbViRMnsg+c/FawlStXCro2duvWDcuXL0ejRo1gZ2dXqrEl/IDzxYsXyMrKgomJCacWF+AGtDt37mTXBwcHY9KkSUhJSeGUW0tLS9ACrKWlhfbt2+PZs2cQi8X4448/OBUcEydOhLOzMycwevv2LRvg5ebmCh4A+/Xrh61bt7Lf17hx47Br1y5OJQZffn4+9u/fz1m3fv16TmDi5eWFWbNmsVOQfPz4EQEBARgxYoTK7fKV9XhlMhkOHDjA2eaECRM44/kmTZqERYsWcaZvOXLkCHssN27cwIsXL9i/6erqwsfHB+3bt2fXeXh4wMXFhQ2y0tLSEBAQwNb6+/j4IDExkX29kZERfHx80KZNG3bdtGnTMH/+fM61tH37dri7u6sdG9yqVSvs37+fnf5JMejijzczNTWFr68vGjVqxK4bO3YsRo8ezSmfpkyfPh3e3t7ssqurKwYOHIiMjAx2Hb+F4vDhw5xjMDU1hZ+fH+f6dHd3h4eHB2c7JVG7dm24uroiPz+fcz1YWFgozTi/fft2TuuWpaUl/v77b860H9OmTcP06dM5lScbNmzAF198wbkXqmJrawtbW1u8fv2aE9A2aNBAaZmUWb16NSdYGzlyJAYNGsRplYyOjmYD2oq6jpUZP3485zosqjeCMvn5+YLun4qtss2aNUPTpk05gd/x48dVBrR///03Z7lDhw7Yv38/26V17Nix6NOnDxYsWKC2XPzfO29vb0yfPp1dnj59OpYvX872QsjOzsbx48cxc+ZMtdtVJJVK0alTJ8TExCAjIwOrVq3ifCcTJkzAlClTcO/ePXZdUb1DAGDmzJmcil1XV1cMGDCAU0GseD8EIOhRZWZmBj8/PzRo0IBd5+npidGjR5epIkpZy3BReRMUKcuVoViZ5+bmxqlYP3v2rNKAVpHiuZSamsoJTnV0dHDw4EHOc8L06dMxZswYtmfW48ePERoaqnY2A2NjY/z111/sUK8ZM2awQ9HS09Ph6OiIZ8+eITk5GXPnzsVXX33Feb+Wlhant0BxzgPyeaEux6RCXLt2DUuWLMGSJUuwdOlS/Pzzz/Dx8REEs/r6+li9enWJtq2lpYVffvkF/v7+CAsLw7lz5wSJQXR0dARjBhUfgCwtLdG9e3d2WVm3Y353Y8Uf1oyMDE6XMB0dHc6PeyF+kpaiusBZWFgIgtTCmzx/jO+2bdtw/vx5zo/XsGHDEBoaihMnTmDt2rUYOXKk2v0p07x5cxgZGbHLcrmcnarn8ePHnLIWJsCxt7fnjIsNDg4GwzCC1tlmzZoJEmp5eXnh6NGjCA0NxY0bNwSt9TKZTHDsit8lfxohLS0tLF++XPDAPX36dDRt2lTlcUdHR3POz/r16wvG5WhpaWHy5MmcdcXp9qtIE8er+AClp6entLugl5cX3NzcsGzZMhw6dIgzPvPmzZuc1w4cOJATzAIF3++cOXMwbdo0rFu3Dv7+/uw1wDAMJ5kZAMyZM4cTzAIF18WaNWs4D2iZmZm4fv268INR4OnpyZnLWHHMPT+L9vTp0znBLADUq1evRA/SxWVmZoavv/6as87c3JwzXykAQZdjfiK1qVOnCiqbGjduXKwx3pqgLIPu999/L5jD0tjYGOvWreNcS3FxcYLusOWlSZMmgkDN0tJSkFRO8R5YUdexMhMmTOAsl2b6lNu3b3N6cAAQdDPmH09YWJjSbp5v3rwRtAB+//33gvGZzs7Oals5k5OTOV2W9fX1lSYgK+nvHZ+7uzv++usvBAcHIzAwUDDEpzDRliJ13a2BguuTHwwVJnFTxK9I4t9nZs6cyQlmAcDKyqrMXY6V5RQoSUUIfxYC/vsHDRrEeRZ6+vQp51x5+vQpp3Kkdu3a6NmzJ7scFBQkGGbEr/Q2MDDgJM8Eiv7uBwwYwPkuFa+V/v3748CBA7h37x7u3LmDL7/8UnB8FhYWnHVFnQfk80MttOSTUatWLWzYsEFpxtvi0tXVhaWlJd6/f4/w8HA8efIEoaGhiIiI4HRJBiBYdnV1xa1bt9jlgIAA9iEnMjKS0yWpSZMmnC5tUVFRnC46DMMIfnyVefHiBXJzc2FgYKD0761bt1aZNMfFxQV79uxhb9wxMTH47rvvoKWlhSZNmqBDhw7o3LkzunXrVqYMvNra2mjfvj2nFjwiIgK5ubmcz7BLly7s/w0MDNC+fXu2JjgtLQ3//vuvIKBVNzZIJBKhXr16bMKWyMhIPHr0CMHBwYIfK8Vy8LvKNWrUCHXr1lW6/V69eqnsWscfr5OcnKy0ayV/vFNxxvkoU9rjffr0KedvhVnD+Ro3bqwyg7PiGGcAbHdevrFjxypd//HjR0HllKo5XU1MTNCrVy/OmNfQ0FC1rWH8wLhQVlaWYAyY4sOXouIkiympli1bKk1gx88BoDgOPjc3VzAmkB8AF+rTp0+FjFONiYnhdDfX09NTmRjJysoKbdu25QSxISEhFTL1Fr+SpRD//qb4eVf0dVzI1NRUEPCUBr+3SYsWLQRZeIcOHYqNGzdyApdjx45hyZIlnNcp9vIAClrzVPWGcnJyUjmWmD/+Vi6Xc8Y7FuIHYjExMZDJZJzKqeKqW7cuW4n6+PFjhIeHIzg4WNDFl/+7zteqVasSX7Pp6emc7MAAVAb8qq7l4lKWrE/ZGHxVlPXoUMzwrq+vj+HDh+Ovv/5i1/n7++O7774DIEwG5erqyqnA4l8Xjx8/Vno98ccyF3U9qbrH81lYWCAvLw8PHz7EkydPEBERgQcPHgh63xR1HpDPDwW0pFLo6OjAwMAANWrUQIMGDdCzZ0+MGjWqVFPLFHr79i0OHTqES5cu4cOHD0W+nv9j269fP5iZmbG1++Hh4Xj//j3q1asnyG7MD1ZTUlI4y/n5+ZwxJqrIZDIkJiYKWkIKqUuOZWVlhS1btmD+/PmcH3W5XI6YmBjExMTA19cXOjo66N69O2bOnKm2y486Dg4OnIA2PDxccMz8lkVHR0dO16bg4GBBQihV5cnOzsbff//NjqEqqoZa8e/8Bxx1U0YoC3QL8Y8vNze3WN8pP7ArjrIcL39sqLm5eYn3X9Zt8BNw6OjoqJyaCig4dxUV1RVY1XWg7EFP1Ri9sk4dooyqz4lfQaXu/ARUl03d+HpN4t8v69SpozbTvJWVFSegLY+u3Mqo+rwVM14D4FQuVuR1rIjfYlQaqampgt4LlpaWShMsFSYKLHTmzBnMnz+f8z3yzz11vy/q7o38pGFSqbRYn2leXh5SUlJKlPRRIpHAz88PZ86cUToPekmpmtaJP7ZZ8ZpVFiSW131G2Xnz/PlzpZntlXn58mWR2yxs+S507tw5fPvtt+yYWkX8oQD86ykzM7NYAXdRz2RFnROFUwSdPHkSoaGhRSYALU33flK1UUBLKsScOXMwd+7cctv+rVu3MG/ePE5Llp6eHlq2bIk2bdrAwcEBa9asUfvgpaenh2HDhrE3+sJux1OnTuUEtFpaWnB2dua8tyw/ssrGzBQqak67nj174urVqzh58iQCAgIQEREhyLgqk8lw8+ZN3Lp1C0uXLhV0gysOZZmO+WNU+AFt165dsXnzZnb5/v37nC7KgPIW2rdv32LixImcrnEikQh2dnZo06YN7O3tcfHiRZWtByX5LtR1ASxtDW9+fj6ys7OLPR9hWY9X2f7LqqTHXpppthQVNXWPshZnVe9TdfzFGeNZUqqOW93xaOr81KSSfn/8h8Wivj9NUdWT5VO4jvlUnbMloZjUr1BgYCA71led1NRUXL16lZPYSBP3BqBsrV+ZmZnFDmjT0tIwceJENmFXIVtbW7Rp0wYdOnRAWFiYIDmVOqrOdXX3h4q8zzRv3hwGBgacHhP//POP0hZwZfh5LXR0dASt8M2bN0ebNm3Y3+N3794hLCwMeXl5nGekzp07C3oZlPYcUvecA6i/XiQSCby8vARJKOvVq4e2bduiffv2iI+PF+SSIP8tFNCSKi8rKwvz589ng1kdHR0sX74cI0aM4DwAKU7Vo4qrqyun5jIgIADdu3fnTP/cIKUdAAAgAElEQVTStWtXQS0sv5tQjRo1BOPkSqM4GTGrV6+OyZMnY/LkyUhPT0dwcDBCQ0MRGhqKx48fsw8fDMNg7dq1GDx4cIkyTQJAu3btoK2tzf6YJSYmcn746tevL2hlbtu2LYyMjNjv5caNG5xuXNbW1kofbBYvXswJ7iZMmIDZs2dzWmcUM/by8bsfqmtpUZZRspBiNy2goLvj0aNHVb6+tDR9vOqm3Xn37h3q1q0reECrUaMGXr9+XeQ2srKyIJVKBfvkXw8ymYzt3aAMv8ttUQ+4qh5ClXXPi4+PV9pKUtYWN2VKE8gpK7Oqea8rauoJ/r7j4+MhkUhUfu78yqySTrNWkSrqOuYrayUPIOxuXFLHjx/nBLT8zyIhIQEMwyitEFB37vG3U6dOHcE4fE1YtWoVJ5gdOnQoFi5cyOm5UJwpfRSVppJI1X1G2e9oWe8zenp6cHBw4Nzzz58/D29vb8HnzpebmyvoMty2bVullTKjR4/mVDBfuXJF0E1Y2Ry1/M/C2dlZI8Mi1F0v27Zt4wSzXbt2xcqVK9GwYUN2HT9rPPnvoaRQpMq7fv06p0tQz5494eHhwQlmJRJJseZzbNWqFZo1a8YuR0RECDJkKhsbq/geoKB2XFmWvdevX7MJgIrTTUfdA3NeXh5iYmJw8eJF/Pnnn8jKyoKpqSn69++PhQsXwtfXF4GBgZzuRlKptFQJXIyNjdV2eVI2PlFHRwedOnVil/nz6SprnX337h0n+YapqSmWLl0q6Gqo7qGhMDFVoVevXint7iSXy9UmI+J/p8+fP1eaaCIiIgInT57E48ePS5yIQhPHy/9eXr16JUgiAxQ8oPbt2xft27eHi4sL5s+fzz7A8I9Vsau4ooMHD6Jr165wdHTEhAkT4OPjA6CgGx+/W5uq+RqzsrI4Y9UB9WOp1V0DBgYGgmRKil3jFfH3WVmMjY1Rv359zjpVFRZXr17V+P6VdcVr1KgR54FSIpGovDbevHlTrJ4W6vCDivLsHlgR17EyZW21joqKEoxtL6mgoCBOZRk/CV5WVpZgGEghdece/zONj49Xes958eIF/Pz8EBYWVmQLHV9eXh4nMaNIJMKqVasE3fDLo6KKz8TERFBhW573mfHjx3OWxWIxfvjhhyKvk7Vr1wrG+qrqkTVkyBBOsserV69yMo9Xq1ZN6dhY/nf/5MkTpeW6e/cuzp49i+joaMFvvzLqrhfF7PwAsGzZMk4wC1TMeUA+bRTQkiqPH6y8evVKcAPdvHmzoOuWqh8H/pgRxeytRkZGGDBggOA9lpaWgvkTf/rpJ0E5NmzYgBUrVsDT0xMdO3ZUmglZkara5Ly8PDg6OsLZ2Rnz5s3D5s2bOdPkFDI1NRXUfJb24VHd+FtV8warm0+YnxkREH6XWVlZgoqBq1evCoJyxWNq3749J4uuXC7HqlWrBF2ltmzZonbcV7t27Tg14llZWVi3bh1nXxKJBKtWrcKSJUvg5uYGe3t7/PTTTyq3yaeJ423dujWnpUAulwvKCQC7du0CUHDuREdHIyYmhs1u6uTkxHnt7du3BQ9maWlpbMtWSkoKHjx4wF5TIpFIkGl127ZtgsBHJpNh6dKlnMocMzMz9O7dG6oU1aLCTwK1b98+wZQbr1+/xp9//ql2OxWJX+b9+/dzeoEABcm+Cr+zsuCPL1XsylioWrVq6NOnD2fdzz//LGj9ys7OxqJFizjXUqNGjUo0zRoAQVIgZWXSlIq4jpUpa3dxfuushYUFoqKi2PwIyv7xM1XL5XLOFCs2NjaCCqBffvlF8Pn7+voKuq4qsra2FiSm+umnnzi/sQzDYP369Vi+fDk8PDzg4OAgyC6szsePHzldmxmGEXQ9DgsLEwTe5VU5wk8CtXfvXsHvx6tXr5T+DpdUnz59BNfUxYsX4e3trbQiPDc3F6tXr8bhw4c565s3b65yjmgTExNO631cXBwnKBwyZIjSLv49e/bkdKt++fIl9u3bx3lNeno6li5dCm9vb7i4uLBTQ6mj6nqRy+WCHkP8ip7Y2Fi189yS/wbqckyqPH7LUGxsLDw9PeHs7Iy8vDxcvnxZ8GANgJN6XpGzszN+++03pUkH+vfvz6nVVFQ412ehmzdvYsSIERgyZAjMzMwQGBiI27dvc97Dn36huAozFSrOjbdr1y48efIE3bt3h4mJCT5+/Ijz589zaugLMxaXhoODg8puPZoKaPnfZX5+PsaNGwdPT08YGRnh/v37SluOFL9LPT09uLu7Y+/evey6a9euwd3dHc7OztDW1sbVq1eL7BKup6eHcePGYdu2bey6I0eO4OnTp+jbty/09fVx4cIFTgsHwzDFHuukqePV0dHBpEmTOHPqnj17FnFxcRg8eDC0tbVx9+5dwbg7xZp7Jycn2NnZsdM3MAyD2bNnw9nZGW3btkVycjJOnDjBebAwMjLiVP6MHTsWfn5+bEtMdnY2PD09MWLECLRu3Rrp6ek4e/asINPq3LlzyzTecOzYsTh8+DAbZGVkZMDd3R3u7u5o1KgR4uLicPTo0RJlCi1vhZ9V4Xj39PR0uLm5wcPDA9bW1nj27BmOHz+ukUCP/9lGRERg8+bNMDQ0hL6+PiZNmgSgYI7Z69evs/e9hIQEuLi4YNSoUbCzs8PHjx9x6tQpQTf9hQsXlrg1kl+m69evY9euXZBIJLCxsRHkKCiLiriONU0ikQjGhfLnPVemQYMGsLe3R2hoKLvu5MmTmDt3LvsdjRs3jpPtPCwsDCNGjICrqytMTExw9+7dYvUMmDx5MpYvX84uX7lyhZ2D2czMDNeuXRO0YpbkMzU3N4eOjg4nqJ01axY8PT1Rq1YthIWF4eLFi4LxvOVVOTJ+/Hj4+fmx95m0tDS4ubnB3d0dDRs2RGxsLOf+VxYikQi///47Ro0axUnYd+7cOdy5cwcDBgxA06ZNoaWlhVevXuHSpUuCFvJq1aphy5Ytaq9Nd3d3lYGgqnmMLS0tMXjwYE7yqHXr1iEoKAjdunVDfn4+Tpw4wams1dbWFkw/WFxaWlqoWbMmp+V52bJliIyMhLW1NWJiYuDv7y/oLl2elWTk00QBLanynJycYGxsjOzsbHbdkydPBFML8CUlJcHOzk6w3tzcHE5OTrhy5Yrgb+qmFnFxccGlS5c4AciLFy+wdetWpa/v1atXsab2UeWbb77B7du3OQ+Y9+7dU9kVCih4CCnteDdlASgA2NnZqczo2aJFC07m6ELm5uaCuUKBggey1q1bc767hIQEbNq0SW3Z+N2sZs2ahatXr3LGhUZGRgqmDrCxsUFcXJzK7Xp5eSEwMJDzvkePHuHRo0dKXz9+/PgSZZLW1PFOnToVgYGBCAkJYdeFh4cLpkkq5ODgwHlg0dLSwvr16+Hh4cEGy1KpFCdOnMCJEyeUbmPx4sWcsbTW1tZYu3Yt5s6dywZqUqkUx44d40x4r2jEiBGC7nUl1ahRI8yZM4eTgCw7O1uQIMTY2Bg1a9ZU+31XlGbNmmHKlCmcSpfMzEzs3r2b87qizs/i4HczlcvlbGu1o6MjG9C2a9cOCxcu5AQ72dnZbLdyZb766itBy25x8Lst5uTksBUybm5uGg1ogfK/jjXt2rVrgnsmvweEKq6urpyANj4+Hrdv32Z7QXh6euLs2bOcAP7Vq1ecCjGg6HPPzc0Nly5d4iSre/bsmcpp0Pr3769yKi9ljI2N4eTkxAmu09LSsH37drXvU5yTW5Ps7Owwa9Ys/PHHH+y6rKwsQcujiYkJatSoUeKxvXxWVlbYs2cPZs+ezQlW09LS4Ofnp/a9tWrVwh9//FHktFHt27dH06ZNBd9Z06ZN1fa6WLx4MUJDQznjrG/fvi2osC80f/58tVnvizJ06FAcPHiQXc7NzS2yxbe8zgPy6aIux6TKMzc3x5o1awRd6xSZmZmhX79+nHWqHmYAYbdjoCDxibq5LEUiETZv3lysVtc+ffpg06ZNZeqWVqNGDRw6dAitWrUq8rUikQgTJ06Et7d3qfdXu3ZtwXQrgPpWWJFIxJmftpCq4BgoGAekbtoYHR0dQcUC/7usVq0adu7cqXI6JACYMmUK3N3dOev4LSAGBgbYu3cvOnfurHI7hTw8PATzPhaHJo5XR0cHu3btUjl3qKKuXbtix44dgmNt2bIlDh48WGSFh66uLhYtWoQxY8YI/ta/f3/4+PgoPU/425g9ezZ+/fXXIstbHLNnz1bbfd/MzAzbtm2DjY2NRvanCd7e3moryJo0aYItW7Zw1pVmXKaNjY3KOTP5Xd4nTpyIrVu3Fjltk6GhIVasWIGvv/66xOUBgE6dOgnGuhcqj7FwFXEdaxK/u3HDhg2LPT/74MGD2aEEhRQrlHR1dbF9+3a0aNFC5TaGDRuG2bNnc9bx7xdaWlrYtm2b0iE4fAMHDsRvv/1WnOJzrFixQu29RCQSCRIXlSZHRHHNmTMHU6dOVfl3c3NzbN++vcj7X3G1adMGJ06cwLBhw4p17YtEIgwcOBDHjx9XOZc4n7KWWFWts4UsLCxw4MABQWUZn7a2Nr799lu20qy0vv766yLPf2dnZ84z4OPHjzWW1ZtUDdRCSz4LgwcPho2NDfbu3YsHDx4gNTUV+vr6sLGxQc+ePTFhwgSkpKTg2rVr7Hv8/f0xc+ZMpdvr1asXDA0NOd1YivOjoqenh40bN8LDwwP+/v4IDg5GYmIiJBIJatSogXbt2sHV1bVYgUdx1K9fH8ePH8elS5dw6dIlREZGsvszNjaGlZUV7O3t4erqWqzAtygODg5FTtfD17VrV8E8vuoCWjs7O5w+fRq7d+/GrVu38P79e2hpaaFu3bpwcHDAxIkTYWdnhxs3brDzKgYFBSExMZHTUtywYUOcPn0aBw8exMWLF/H27Vvo6emhVatWmDRpEnr37i0Y76Qsq3RhxcHVq1cREBCAR48eITk5GTKZDLVr14aDgwPGjBlT4sQ4mj5eExMTbN++HXfv3sWpU6cQGhqK5ORkyOVy1KpVC23atMHw4cPRv39/lRUpHTp0wOXLl+Hn54dr167h+fPnSE9Ph76+PqytrdG1a1eMGTNGaet6oU6dOuHChQu4du0azp07h+fPnyM+Ph56enqoX78+unXrBk9PT40Hl97e3nBycoKPjw9CQkKQkZGBevXqoV+/fpg6dSpq1aqFPXv2aHSfZaGlpYW1a9eif//+8PX1RWRkJHJycmBtbY2hQ4diypQpgvkvVU1bU5QtW7Zgx44duHjxIj58+AAjIyNYWVkpvQ8NGDAA3bp1Q0BAAC5evIhXr14hMTERRkZGsLa2Rq9eveDp6VmmeVZ1dHRw8OBBbN26FYGBgUhKSoKJiQlsbW01dm/kK+/rWFMSEhIEScKK2zoLFNwH+vfvz+myXPgZF461r1WrFvz8/PD333/j7NmziI2NhUgkQvPmzeHp6Ylhw4YJEvEoO/cMDAywdetWBAUFwd/fHyEhIUhKSoJEIkHNmjXRrl07jBo1Su0YeXUsLS1x6tQp7NmzB9euXcObN2/AMAwsLCzQvn17jBs3Dg4ODggLC2PnX3327Bmio6OLPW9rSYhEIixatAh9+/Zl7zOZmZmoV68evvjiC0yZMgU1a9bU6Hj92rVrY8OGDfjqq69w+fJlBAUFIS4uDqmpqZDL5ahRowasrKzg6OjIdkUuCRcXF/z2229svg9dXd1i9ZBo0KABTp8+DX9/f1y+fBlPnz5l56itW7cuunbtinHjxpW4PMqYmJjg8OHDOHjwIAICAvDq1SvIZDKYm5ujdevWGD16NJycnJCamsq2Eqenp+PGjRvo379/mfdPqgYRQ7MPEyLw+PFjQS3lqVOnBImfyKcpISEBtWrVKnLM2YYNGziJd7755hvMmjWrvItH/uNSU1NhYGAgaEnje/nyJaebZoMGDQSJfwgpicTERJiZmant0QQAf//9NycxloeHB3788cfyLh4hhJQKtdASwiOVSrF27VrOusaNG1MwW4UMGDAAUqkU5ubmsLS0RJs2bbBy5UrOayQSiWDuRH7mTkLKw+bNm3HkyBFUq1YNlpaWqF27NlauXCkY88ZPzqOuZZyQ4hg/fjxev37N3hsbNGiAjRs3cnofMQwjSEZH90ZCyKeMAlpCAPj5+UEikUAsFuPixYuC5EHjxo2rpJKR0mjcuDHb/ToxMRFPnjxBUlISunTpAl1dXSQkJODy5ctsVl+gIGuvujHShGhKYXCQmZmJzMxMPH/+HF5eXhg5ciTMzc2RmZmpdEoSfh4AQkqqUaNGiI2NRXJyMpKTkxEVFYXU1FT06dMHhoaGSEpKwo0bNzgzA2hpaZUq+RchhFQU6nJMCAqydaqaqqB+/foICAhQOr6SfJpOnz7NmUKpOGbOnIlvv/22nEpEyP9LS0vDoEGDkJqaWuz3NGjQAGfPnqX7ECmToKAgTJ48uUTvGTlypMYSuBFCSHmgLMeEAKhTp47S9SYmJvj999/pIbKKGTFiBGbPnl3srLCurq6YO3duOZeKkAJmZmbYsWMHm6SnKLa2tti+fTvdh0iZOTo6YsWKFUWOoS3k5OSEFStWlHOpCCGkbKiFlhAUTJOwceNGpKWlQSQSoX79+ujevTumTJmisRT8pOJFR0fjzJkzCAsLQ1xcHDIzM5Gfnw8TExPUqVMH7du3x8iRI4s9xQEhmpSVlYVTp07hzp07eP78OVJSUpCXlwd9fX3UqFEDzZs3R9++fTF8+HAKZolGxcXF4eTJk3j48CFiY2ORmZkJqVQKY2NjWFhYoG3bthg2bJjKKZ8IIeRTQgEtIYQQQgghhJAqibocE0IIIYQQQgipkiigJYQQQgghhBBSJVFASwghhBBCCCGkSqKAlhBCCCGEEEJIlUQBLSGEEEIIIYSQKokCWkIIIYQQQgghVRIFtIQQQgghhBBCqiQKaAkhhBBCCCGEVEkU0BJCCCGEEEIIqZIooCWEEEIIIYQQUiVRQEsIIYQQQgghpEqigJYQQgghhBBCSJVEAS0hhBBCCCGEkCqJAlpCCCGEEEIIIVUSBbSEEEIIIYQQQqokCmgJIYQQQgghhFRJFNASQgghhBBCCKmSKKAlhBBCCCGEEFIlUUBLCCGEEEIIIaRKooCWEEIIIYQQQkiVpFPZBdCEkJCQyi4CIYQQQgghhJBy5ODgIFj3WQS0gPKDK8rTp0/RokWLcigNqWroXCCF6FwghehcIIXoXCCF6FwghehcqHiqGjGpyzEhhBBCCCGEkCrps2mhJYQQQkiBuLg4BAcH4+E//+DR3btIS0uDVCqFgb4+6tvYwKF3b3Ts1AkdO3ZE9erVK7u4hBBCSKlRQEsIIYR8BiQSCU6ePIk/165FdHQ0uurpwSErC7Pkclig4Ac/F8DryEg8vHYNPxga4kleHkaOGIHZ8+ejY8eOlXwEhBBCSMlRQEsIIYRUYQzD4KivL76bPRvN8/PxdWYmXADo5uYqfX1PAOMlEkAiQSKAfX5+cPP3h02zZth1+DCaN29ekcUnhBBCyoTG0BJCCCFVVEJCAtyGDMGq6dNxKi0N1zMz4QZAt5jvtwCwSC7HC7EYY8LD0cPeHut/+QX5+fnlWGpCCCFEcyigJYQQQqqg8PBw2LdogabXriEkOxtdyrAtbQBfyeV4kJODC6tXY1ifPsjOztZUUQkhhJByQwEtIYQQUsWEhYVhQM+e+D01Fb9IpTDQ0HYbAbgiFsMyOBhDeveGWCzW0JYJIYSQ8kEBLSGEEFKFvH79GkP79sWfmZkYXQ7b1wGwLzcXNpGR8Bg+HAzDlMNeCCGEEM2ggJYQQgipIhiGwTQPD8zNzMSoctyPFgqC2vj797Frx45y3BMhhBBSNpTlmBBCyH9efn4+oqOjERISgpioKGSnpyMtLQ1WtrZo3qoVHBwc0LRpU2hra1dqOXft2IGMx4+xoAKSNukC2J+djd7e3hg0ZAgaNGhQ7vskhBBCSooCWkIIIf9JDMPgxo0b+HPdOly8cQN19fTQEUDLrCzUAtAAQCYAfxMT/ADgo1SKYQMGYPaCBejRowdEIlGFljc1NRVLFyzAzezsCvvxbgXgu7w8fDt9Ok5evlxBeyWEEEKKjwJaQggh/ykMw8D3yBH8uHAhdNPTMTsrC7sB1JBIlL8hKwsAkATg8LlzmH79OnQtLPDTxo0YOXJkhZX7wL59GMQwaFVheywwLz8fNrdv4/Xr19RKSwgh5JNDY2gJIYT8Z8THx8N10CCs8fLCjnfvEJGVhVkAahTjvbUAfM0weJqdjQ2xsVg8fjw8XVyQlJRUzqUG5HI5tm/YgNmVkHXYGMAEuRy7tm2r8H0TQgghRaGAlhBCyH9CYGAg2jVtipY3biAkOxtOAErTaVgEYACAMLEY9S5eRNsmTRAUFKTRsvLdvXsX+pmZcCzXvag2UyLB3p07KeMxIYSQTw4FtIQQQj57AQEBGD10KHwzM7FGKoW+BrZpBGCDRII9aWlw7t8fgYGBGtiqckH37qGfRFKqAFwTmgPQlskQGxtbSSUghBBClKOAlhBCyGft7t27mOTmBn+xGH3KYftDAPiJxRg9bBgePnxYDnsAHgYGwkHVGN8K0lFHp9yOjxBCCCktCmgJIYR8ttLT0zF2xAgcEIvRtRz30wfAtuxseLq4QFwO41xDw8LgoPGtloxDVhZCHzyo5FIQQgghXBTQEkII+Wx5z5mDQVlZGFIB+3IH0Dk1FUu9vTW+7cT0dNTT+FZLpq5cjsS3byu5FIQQQggXTdtDCCHksxQYGIjLJ0/icW5usV7/EUAIgCgA2ShI/mSMgrlYHVCQ5bgoW3Jy0ObAAXhOnozOnTuXruBKSGQyjYz7LQt9AHnF/CwJIYSQikIttIQQQj5Lv61ciR/EYlRX85oXABYAsAHQDMBvAN4AkAKQAHgN4FcAjQE0BLD0f+tUqQlgSW4ufl+9uuwHoEBPRwd5Gt1iyeUB0DcwqORSEEIIIVzUQksIIeSz8+rVK/xz/z78VPw9GsB8AA8ATAZwCQWZfFVlEZajoOV2DwB7AL0AbADQSMlrJzIMVly+jPj4eNSpU6f0B6HAwtQUH3JzYaaRrZXOBy0tWFhZVWIJCCGEECFqoSWEEPLZ2f3nn5gol8OItz4fBa2wPVAwl2wcgPUAWkD9nLRaAFoD2PS/9zgC6AJgGwqCXUWmANxFIuzbvbush8Gy79ABIRrbWumEmJjAXoPdqAkhhBBNoICWEPKfl5qaiuvXr+Pw4cM4e/YsAgICEB8fX9nFImVw4/x5uPCmuclEQRB7DgUts/MAGJZi28YAFgK4A+BvAM4A+HmNnXNzEXjuXCm2rpxD794I0dXV2PZKI0Qmg4NDZedaJoQQQrioyzEh5D8pOTkZB/btw94tW/AmIQHtjYxgLZcjPz8fl3V1EZqbi2omJpgwbRq8vvoKNjY2lV1kUkwymQwRz5+jg8K6TABfAOgA4A8A2hrYTzMANwFMRcFctAH4/wDZAUBIZCQYhoFIJGz7ZRgGb968QWxsLORyOWrVqoXmzZtDR0f5z7Jjt26YY2AARipV25JcXmIAyHR00LBhw0rYOyGEEKIatdASQv5T5HI5tvz+O5pYW+PRDz9gz9u3SJNKcTs9HYczM3FULMbV9HQk5+XhfHIyMjdvRodmzbDo22+RSxleq4SnT5/CysCATQaVD2AkgPYA/oRmgtlCugAOArAG4AGA+d/6ugD05XK8fv3/KaQYhkFQUBAmurmhdvXq6NK8Ob53dsYPI0bArVs3mBoZoY+DAw4fPoy8PG4KqB49eiDHxAT/aLDsJbFDTw9Tpk9XGpwTQgghlYkCWkLIf0ZKSgr6de2Ko8uX45+cHBzKyUE3KA9wRCgYM7k5Lw9Pc3PxYtcu2DdrhufPn1dsoUmJxcXFobHW//+8bQIgQ8F41/IIx7QA7APwHoDiqNnGenpsQPv27VsM6d0b47/4Au1OnkRYVhbe5+TgTno6bqanIzozE/FSKeaEhmLvjBlobmODa9eu/f8+tLQw67vv8KcRf1Rw+csG4KOlhRlz5lT4vgkhhJCiUEBLCPlPSE1NRZ8uXWAfHo5b2dloWoL31gZwXCzG12/fwqlLFwpqP3G5ubkwYAraSmMA/IKCgFOTLbN8ugAOgDutj+H/ynLlyhXYt2iBbkFBiM7OxnyGgRWEwXU1AKMAXMvKwp8fP2KyszOWLlgA5n/HMnnqVFxAQbblirRVWxs9u3eHra1tBe+ZEEIIKRoFtISQzx7DMPB0dkafuDj8JpGUOrCZKZdjeVoahvXpg5ycHI2WkWiOjo4OZP/7vzeAZVA+vY6mtUJBoqnF/1uWAnjy5AnGjRiBE1lZWC6TobhpnQYDCBOLcWn7diz+7jsAgLm5OVavW4cpxsbs8ZW3KAAb9PWxac+eCtojIYQQUjIU0BJCPnt7d+9GYlgY1kskZe5yOkMuR/vkZCxfuFAjZSOaZ2pqihSRCK8ABAGYUYH7ngvgIoB4AIn5+Vi7ciV8xWL0LMW2agG4lJ2N47t24dz/MibPmDULJq1bY4N2ebY3F5ABmGJsjFXr11PrLCGEkE8WZTkmhHzWxGIxlsyfj2vZ2cVuHSvKHzk5aLF3L2Z98w0aN26soa1WLdnZ2QgNDUVISAhiHj1CrlgMXT092DRtCodOndCxY0dYWFhUStnatGmDiJwcbAcwCaWbmqe0TAGMBrADQFx2Nr7U1UXfMmyvJoC9YjHGT5yIqNhYVK9eHXt9feHYvj2apqdjpEZKLSQHMM3AABadO2PGrFnltBdCCCGk7CigJYR81o4ePYouANpqcJu1AEySybBz61as27RJg1v+9D169AjbfvsNx06cQDM9PTjk5aFVXh6MUNDF9qWODjYYGyMkNxc9HB0xe+FCDBw4EFpaFdchqGbNmqhpaoojiYkIqLC9/r+pADxR0NX9J95cuKXhBMBRIrdTqAoAACAASURBVMEhHx98NWcObG1tcf76dQx2ckJ+ZibcyrwHLhmA6QYGeNWyJS6eO0eZjQkhhHzSqMsxIeSzdnDrVnhlZWl8uzOkUhzcv59N2PO5S01NxaTRozGse3c09PVFTG4u7mdk4M+8PMxBQRA3A8BamQxX09PxLi8ProGBWDp6NHp06ICYmJgKLW/btm2RBqBlhe61QAcUZDyeqKUFEw1t86vsbOz47Td22d7eHpdu3cLXZmZYqquLPDXvLYlYAAONjPC+Y0cE3LoFo0rIqkwIIYSUBAW0hJDPVn5+PkKiotC7HLbdBIC2VMqZZ/RzdefOHbSxs0N1f39Ei8X4Pj8flkW8xwjAFAAPs7Iw9skTdO/QATv//LMCSlugfffuaI7K+ZHTA1AdwCi5XGPb7AUg7sMHJCcns+vat2+P0KdPEenkhI7GxnhYhu3LAewQidDJ0BADvv8e52/cgLGxcVmLTQghhJQ7CmgJIZ+tZ8+ewVJXF6bltH0HXV2EhoaW09Y/DdeuXcPIgQOxJyUFW/PyStziqAVgjlyOf3JysH7BAqxbs6Y8iilQvXp1dKiQPQnJAWQCsNfgNrUAdDAwQEhICGd9nTp1cOrSJSzZuRPDTE3R38QEJ4FiZ0FOArBeSwt2xsY41KYNbj58iEVLl0JHh0YkEUIIqRoooCWEfLaSkpJQpxyzwdaRyZCUlFRu269sjx8/hoeLC06IxRhUxm3ZAbglFmPnzz/D58ABDZROvdzcXJiX+16Uy0LBHLNmGt6utVyOhIQEwXqRSISx48bhdUICpu3ahd/btYOVoSFGVK+OVSIRzgH4B0AIgLsA/gbwna4uepuaoomBASJHjYLv9eu48+gRWrasjE7ahBBCSOlRFSwh5LNV3slsmArYR2WRSqWY7O6OX8Ri9NLQNusBOC0Wo++cOejTrx+sra01tGUhkUgEkZYWoMFuv8XeNwrODU0r6nzT19eHp6cnPD09ERsbi+DgYITcv48/7t5FamoqpFIpDPT1YdWgARx698byjh3RqVMnmJqWVx8GQgghpPxRQEsI+WzVrl0b72TF7XxZcu90dFC7du1y235l2vDrr7B48wbTNJz0qg2AeXl5mDlhAs4HBmp024pMTEzwTlcXyNNUuqTiM0ZBUJuMgml3NOW1tjbq1q1brNfa2trC1tYW7u7uGiwBIYQQ8umhLseEkM+WnZ0dkmUyJBf90hJjAIRIJHBwcCiHrZedXC7Hx48f8fbtWyQlJZUoG3NeXh5+X78em8VilEf78yKZDOHBwXj8+HE5bL1Aq1atEGFgUG7bV0cLQHUtLYQU+criywfwSCyGvb0mR+YSQgghVR+10BJCPltaWlro0q4dbjx4oPG5OqMA6Bkaon79+iV6X2JiIuLi4iCTyVCtWjU0adIEurq6GinTs2fPsG/nTty7ehWPYmKgJxJBX0sLOfn5gLY27Fu2RK/BgzHVywtWVlYqt3P8+HG0Yxg000iphHQBeOXl4c+NG7F9//5y2Ye9vT0eicXIB1B+o6iVywWQxjA4aWCAAbm5gr/nAIhAwZjWeBQkkaoOoB0ABxTMc8x3BUCzhg1Ro0aN8io2IYQQUiVRCy0h5LM29ZtvsMNEU7OB/r8d+vqYOmNGkWNoGYbBjRs3MNbFBdY1a6KptTWm9+2LuQMHYkSXLjAzNkbn5s2x9uefkZiYWKqyhIaGYoCjI3q2bw9m61asiIhAbF4eknJz8U4sRkpeHqLEYnz78CE+rluHtnZ2GDVoEJ4/f650e767dmFKOczdq2hqfj6O+vkV2XKcmZkJX19fzJ87F/07dULHJk3QpXlzuA8ahF9/+QX37t1Tuo0aNWqgTs2aCC+vA1AjGICdtTWOMgzSFNY/ADAZgCWAmQBCUVCrrI+CwPZXAI0B9AZwFIBE4b1/GBtj1sKF5V94QgghpKphPgMPHz4s1fuioqI0XBJSVdG58PnKzc1l6piaMv8ADKOhf28BxtzAgImLi1O779u3bzOtbW2ZliYmzFaRiPkXYOS8bWUCzA2AmWJoyJjq6zPzZsxgsrKyinVseXl5zLKFCxkLQ0NmN8DkFrP8GQCzVkuLqWlkxGzeuJHJz8/nbLeOqSnzSoOfl6p/9Y2MmBcvXig9tnfv3jFfTZvG1DA0ZIZWq8b8LBIxAQBzH2DuAcxfAPOtri7T1NiYaW1ry+zZvVtwHCu+/56Zra9f7sfB/zfR0JBZv3YtM2PiRMbLwID5CDBjAKYBwKwDmEQ175UAjB/A9AKYFv873nMA09DSksnOzi7WeUE0j34jSCE6F0ghOhcqnqqYjwJaQhg6Fz53vr6+TAtjYyZHA8GKHGCGGhkxP3z/vcr9SaVSZv6cOUxdQ0PmuJIgVtW/RIAZb2jINK5bl7l//77aY8rOzmYG9ujBDDIyYt6V8liiAaaTkREzecwYRiqVMgzDMO/fv2fM9fWLXeay/HOuVo3x8/PjHJdcLmd8Dh5kLExMmAW6usybYnwfVwHG0diY6eXgwDx//pzd1ps3b5gaBgZMRgUGs4kAY2ZgwCQlJTHp6elMbVNTphbAeAOMuITnmS/A1AYYcx0d5tq1a2W4AkhZ0W8EKUTnAilE50LFUxXzUZdjQshnb/To0WjVuzdmGhigrJO4rNPRwXsrK3z/ww9K/y6TyeDh7IyIffvwOCcHo4BiJ1aqBeBQTg7WffiAoX36IFBFFmCJRIKRAwfC4uFDnBWLUa80BwKgGYAbYjHenD0LrwkTwDAMPn78iPr6+uWSDIqvvlSKjx8/sssMw2DB11/jl1mzcDErC+ukUqge6VtABKAfgNvZ2XAJC0O3Dh1w//59AICVlRX69emDLeU4FzHfBl1djHB2Rs2aNf+PvTMPb6ra+vCbpGmTtIVS5qmFMiPILIii4FVARLwgoigoioggIojiPCGooF5AFFABceCKIDggODGLIkOZoczzUIECnZKmTbK/P1ZaOiRt2gbk8+73efJAz9lnT2enPb+z1l6L+Ph43E4nXwJvA9Zi1GMA7ga2AlUMBn5dvPhSdFej0Wg0mv/3aEGr0Wj+8RgMBmbPm8f+hg0ZGBZGSRK5eIBxISF8VKECi5YvJzQ01Ge5xwcNIn3VKhbZ7SVO2dILmGe306d7dxISEgqcf+O11zBs2sQnGRmljuwXDnxnt7Np0SI+/eQT3G73ZQuiZFIKt9ud8/PLzz7Lylmz+N1up7ixfE3Akx4Ps1JT6XHzzezYsQOAd6ZNY5LFws7gddsvG4FZFgtvTp7MoUOHuLtHD77OyODmUtRZBVidlcV306cz8+OPg9RTjUaj0Wj+OWhBq9Fo/icIDw/n5zVrSO7Ykdbh4WwsxrWHgJvDw1nUsCG/xcf7jWz8008/8eO8eXxltxNWyv52Al6z2xlw1124cuXS3bJlC1MnTmSm3R60MPXhwKfp6Yx+4gnS0tJI9pTWjh0YKSEhRHgDdq1atYpZU6bwo91OaeL43ga8mZ5Ov549ycrKIjY2lrFvv82D4eF5giwFGwcwIDycidOmUalSJR66+26edjjoGIS6ywNf2e08O3IkR48eDUKNGo1Go9H8c9CCVqPR/M8QHh7Ogh9/5Nnp07mtTBm6RUTwPeArnq8TWAXcZ7PR0mKh6/PP8/uWLVSr5tvB1+l0Mrh/f2bY7ZQJUn8HK0X4oUNMe//9nGPPDhvG6w4HhSULOgksAt4H/gNMBX6BQvPxNgMGZmTw+ccf85fTSUrpu18kW00mmjRpgtPp5KF77mG6w0HFINT7oFLUOHmSCePGAfDIo49S/brruN9qxV3EtSUhC7jbZqNFly70vfdevvzyS+y7dvGkO3itNQWecDp5asiQoNWp0Wg0Gs0/AS1oNRrN/xQGg4H7+vXjcGIifaZM4e2rr6ay2UyjyEg6ly3LLRERtChThnIhIYyIi6P1mDEcPHmS0c8/j6mQvZgLFy6kXindS/NjBN6w25k8fjwej4f9+/ezKT6eB3yUPQK8ANQErkbE7C7gGJLz9E0gDqiPpIc57aOO4S4XX3/9NY1r12ZzEMfhiwxgr93O1Vdfzfz586mTlsbtPsp5gATgC+AZYCjwOPAG8BNw1sc1BmCS3c7kd98lIyMDg8HAl999R1Lz5txntQbVUusA7rTZ4NprmTV3LgaDgffffJMX09N9um6fAz4BHgOuRe5JLUSw3oe8gCjoZC484XKxdPlyTpw4EcQRaDQajUbz/5tgeaxpNBrN/yusVisDBgxgwIABZGVlsWvXLhITEzl8+DAtWrSgadOmWK2Bh/GZPmECT/jJ3aqQnKOrvP8eAVxAJCI+WwNdgSgf17YFyqSns3TpUlYtXcoDbjeWXOcvAKOAb4H+wM9AI3wHovIA8cB0JCDUIGAM5NRXFbjZZMJeuzYLjxzhRmfhu40VcADYCaQDoUBd4CrAXOiVYkFu26wZFouFqePHMzrf3GULv2mAG2iDWJFjvOM4AowHNgM3IEK3Mxff0tYFWgLz58+nf//+WCwWFi1fzn09e9L2t9+YnZ5OsyL6WBQbEDfjll26MGvuXMxmM9u2bePkoUN0y1d2NzABWAjcArRHgj5V9/b5ArAF2Yd7E9AQGAnczsV7GQncqxQzP/yQl8eMKWXvNRqNRqP5Z3BFCdrMzEyee+45jh07RkREBC+//DIXLlxg3LhxmEwmrr/+eoYNG/Z3d1Oj0fzDMJvNNGvWjGbNmpGQkECjRo2Kdb3D4WDDjh0FRIwHmANMAs4DtyJipQ4i+LJFzH+BIUAfxAoZl6sOA/Dv9HSW//IL65Yv59msrJxzvwIPIaLnMCJ4CsOICMM2iIVzGNACsX628pa5OT2d5SEhfGEw8AayvzY/mxE35gVABGJdLIO4aScAR5E9wEMRoe7LFWhqZCRDRo8mOTmZbXv2cJv3uELm7Emgi7dvbfEfKTodmIvM23hgJhfnr09aGj8vWED//v0BsFgsfL1kCbNnzeLmJ55gqNPJEy4X0f6nzCdnkGjGn1gsTJo+nXv69sVgkB6uXLmSWz2eHOusC3gHeBcRqPvAr1t1C+BBYCLwDfAs8Cky15W9ZW5zOnlnyRIIUNAmJSURHx/Pnj17yMzMpGzZsjRr1oymTZtisViKrkCj0Wg0miucK0rQzps3D5vNxrx58zh48CCvv/46Z8+eZcqUKdSsWZNHHnmEXbt20bhx47+7qxqN5h+CUoo1a9awYsUKziUmknT2LHENG9K6TRu6detWqJtxNtu2baOBzYYl5eLO00PAQERwjUXEmS9hly2CExHL6TXAK4hLanb5Vh4PE1etYlNCQo7w/C8i+uYgaWuKS2VgPiIGb/X+exMibD/YsYMbb7iBKcuW8WyufaBnEBH8ByLAt4PPvbypwNfAS97PJ4glOps1wD6zmZ49e/L7779ztdWKOSsLB3A/Ys38kYsiuzDCkXkegLw4uAZxt74HsXxP2LAhT3mDwcCDAwdyS5cuPD9iBHUWL6anwcBDDgetAX8Szw6sB2babPzg8dCrZ0+2/uc/VKlSJU+5+NWruT4jA4AU4A4kAvNGIDaA8YBYuu/2XvsaInR/QCzOrYBNu3ahlMoR0fnxeDwsWLCAqePHs2n7dlparTR2Oglzu9lhNvN+SAiHnE7uuvNOHh89mmbNSmur1mg0Go3m7+OKErT79+/nhhtuACAuLo7t27dTvnx5YmJiALj++uv5448/tKDVaDSlJjU1lS8+/5ypb79N1pkz9HQ4iPF4qI24u46LjGRYWBiDhw9n4COPULlyZb917d+/n4ZK5fz8JyJGRnk/gaTBqQK8CvQFHgB+Bz5HLLmNgD0HDmBUigrA9956lyHuvaXhHsTVuDewGHFFPpyYyPcrV9KmSRPuSE+nESJC7wL6AbMpPKdqJGJpHADMQgT3GEQE24EHbTY+mDULs9nM3r17aeRykQF0987DRih2lGgTMiedEYHuBO4F9p065VP81ahRg8++/pozZ84w6+OPeXzmTPYcPUp9m42mbjeRbjcepUgzm9lmNLLf4aBRbCz3DR7M5IceIjrat133wO7dOS8yuiJu0h9QsoAVFmTvc1vvmH4GmgN4PJw7d47y5Qsmhtq/fz8P9ulD5r59jEpL499AaGauXcNeC/9fwKyvvqLrt99y30MP8fqECcVysddoNBqN5krhihK0jRo1YsWKFdx8881s3bqV1NRUatasmXM+PDycY8eO+bzWV67GosjIyCjRdZp/Hnot/G+xdetWnnjkEdq7XExyOLiJgi6tr6WmEp+aygfjxtFw3DheefNNunTt6rO+w4cPY/am1tkM9EBcRW8tQd8aACuBOxFB+AUi7jIyMzEDp4CHkT2opRWz2dwIfIgIwD+BTJcLh8PB0JEj6fvuu4x3OOiHWIM7F6NeA2I97eS9zglsCQ2lUfv21K9fn4SEBI4cOUKoy8UjiCvuZwT2AsAfTYGlQEegtvfYjh07CAnx/+euR8+e9OjZE6fTyZ49ezhw4AAOhwOXy0VsmTLcUbcu9evXz8k9/Ndff/HXX3/5rCstLY0wRLzXQ9yF/blLB8q/EdflHohVPNRgYOfOnVSsmNd5ef369YwaOpQXMjJ4wuMpVERXBp5zuxlkt/PojBm0XbKED7/4gqgoXzu5NfpvxJWJ0+nkwIEDpKWlYbVaqVWrFpGRRW2+KB16LWiy0WvhyuGKErR33nknBw4c4N5776Vly5Y0bNgQh8ORcz49PZ0yZXwnxCjunjegRHvlNP9M9Fr43+HXX3/l8YEDmW235+zb9EcrYJbTyePA7S+8gM1i4REfaVPq1KnDlpAQHIiFdTIlE7PZWBCX3Q7IntAbgHCrlaTkZB4FHkGsdsGkF7Jv8wXAYjbTqFEjXh0zhoN79tB7/nwWUDwxm5s4xJrcGqhQrRrrFy7MeeiMi4vjD4OB48BWSidms2kIfIRYiY0GA02aNPHrnpuf5s2b5/y/JL8XypYty6+IhX0bpRez2fRGhPqTgMPjoWnTppQrdzFj78aNG3lq6FDm2+10Kka9FYD5GRmMPnaM4QMHsjo+XltqfaD/RlxZHDx4kOnvvccnM2dSxWiknMFAOnDQ6eTOXr0YOmoULVu2vCRt67WgyUavhctPfHy8z+NXVNqe7du3c+211/Lll1/StWtXatWqhdls5ujRozn73Fq3bv13d1Oj0fw/Zdu2bdzXsycLAxCzuWkBrHI4eGXUKBYtWlTgfKNGjdiBuAw3Q0RtabEirr3PIRbbqxo2JCQkhB3IvtRLwWRgHhBbtSog+03TU1IYbDSWWMxmE4vspc1IT88jLuvWrctGp5NZgK2UbeSmByL6K0dEBCxmg0H9pk15D3kR4SugVmmYgOQTNpvNeSypDoeDfj178n4xxWw2BmBCVha1Dh/mlWefDVJvNZpLw8fTp3NNkyZ4pk5lbVoa21NSWJ2cTHxyMrszMqjz1Vfc0aEDox5/HI/H83d3V6PRXAauKEEbGxvLp59+yt13383kyZN59tlnee2113jqqafo3bs3jRs31sErNBpNiRkxcCDj0tPpUIJr6wDzHQ6GDBiAy+tenE3jxo054nDwESIKg0UTZD/tbKBNx45EWa0Mo/j7SwMlGsmFGhouUmz9+vVsXrOGsUF6KOwOtElP56Pp03OO7du3j6uhRPekKF4HUuz2PJ4+lxpTRASxiMtzsCkDDAeiLJY8In3CuHE0TUri7lLUbQCmOhx8PmMG27dvL2VPNZpLw4dTp/LWqFGsdTh4JyuLuvnOZ7vSb7XbWT9rFsMHD0blim+g0Wj+mVxRgjY6OprZs2fz1VdfMWPGDCpXrkzz5s2ZN28eCxYsYOTIkX93FzUazf9TEhISSNi5kwdKUcf1QK2srAJWWrPZTFxsLF2QoEbBZAjiitu6bVvOpqQwIMj15+dx4MCBA3g8Hqa++y5DHA6/kX9B0uycRfLCnkJSFRXGCLudaf/5T47lZOakSTwTjI77oA7QNiSEefPmXaIWCrJr3TqevIT1PwScSU7m3LlzgKS7mzZlCmODINorAsOcTt5/++1S16XRBJuEhAReeuopfrHbqVdE2WjgB7udFV9+ycKFCy9H9zQazd/IFSVoNRqN5lIxdeJEHs7KIrSU9QxNTWXq+PEFjps9Hh4M4PrzQDwSfGkP4C68OHWA+gYD27Zto4XVSrkiypeWBkCkwcDevXtZ8N13DPBhnXUgVuPbEAFfD7GwNgeikD2/bwKnfdR/LWBKTWXz5s2kpqaybe/eUu03Loq7MzJY+t13l7CFi7hcLuJ37qT7JWyjPHCN1cqff/4JwI8//kgjpWgQpPofdruZO38+mbkjIwdIRkYG27Zt488//2Tr1q2X1TIebM6ePcvixYsZ+/rrjBgyhPFjxzJx4kRWr16N3W7/u7v3P8nUiRMZnJVFnQDLlwVeSU9nyhtvXMpuaTSaK4ArKiiURqO5sjl27BiffPwxa37+mS27dnHebsdsMlG/Rg1atW1L7/vvp0uXLhiNV9a7sqysLL744gu25XMVLgl3AiO2buXw4cPUqlULkLyfB06epI2fa/YjOWa/RdKl1EXS8SQhou8aJHJxL3y7E3cyGlm1YgWtvflNLzWtTCYWLVpEZbOZSk5nznEPkuP1dSQn6sPIuGpwMfjROUSwz0HE8X2IuM2OO2oA2nk8xMfHk56eztU2G+bk5Es2ltbAf/LlovWFx+Nh6dKl/LxoEfFr1nAyMRGXy0WtmBhadejArT160KlTp0L34+7atYuaFguR3tQ4l4pWDgfxGzbQrVs31v72G53S04NWd2UgJjSUHTt2BBRU5/z588yeNYsvpk8n4fBhalutRBiNpCvFQbudBjEx3Dd4MA8OHOgzzdCVxu+//87EsWNZumIFbcLCaGW3E+tyUQPYv2ABc8PC2O9y0f/++3li9Ghq165dZJ2a0pOWlsacL75gazF/h/8beCIhgZ07d3LVVcGKC6/RaK40rqynTo1Gc0Vy5swZ+vXqRbN69TgzYQLD169nS1oaaR4Pf2Vl8fGhQzSfO5cX+/ShfvXqLF68+O/uch6SkpIwK0XNoosWSRjQKCyMQ4cO5Rw7cuQIZU0m8mcmTUVchq9Fovd+C1xAUvusBw4Ax7xlZiIC8BcfbTZ3uzm6cyeNL7FQyuaq1FTWrVtHs1zi7SSyL3Qu8BuSE/UuoCZ5I/lGA7cgFtwDyBxcDazNVaa53c72jRvZtWsXTUpgCSwOVwF7T57E7fZtC1dKMffLL2lQowZP9+rFifffJ2LLFuokJtLg7FlsmzZxfPJkhvfoQeOYGL799lu/bSUkJNDkEo0jN01cLhI2bgRg29q1NPezxzkRGIvsxa6ABN2qhqRR+hLwN/Mt3G62bt1aaB88Hg/vT55M3Ro1iH/5Zd7dv59zLhc7U1NZl5zMjpQUzrlcvHfwINtffZV6NWsy6d13r9ggPSkpKQx+4AH6du7MTT/9xFGnk19TUnjL5WIk8BTwgdPJupQUNtntWGfMoE2TJkyZNOmKHdM/iY0bN9LIbC727/BQ4A6lWLZs2aXolkajuULQglaj0RTKsmXLuLpePaouXsxRp5MpTifdkQfjMMTy1gbZe7kxLY3piYk83qcPg/r1I+syCbCiSE5OpmwheUiLS5RSJOeyKqanp1MmX/17kIjHmcA+YDwiLPKnpYniYkqWj4BBwGhkb2o2ZQCX0xn0qLn+sAH21FTKeh/UjyMuxZ0QMdswwHqikXy8k5Gowyu9x8sAaRcuYLfbifAjNIOFGTAbjThzWZqzSU1NpXe3brw8cCDtT53ir/R0TiMplx5C0v50QcZ/Pj2da44fZ+S999KvVy+fbqd2u53wAMVNMiL6xwKvAO8h6yQQIgB7WhoAKcnJBdzQ9wL3AI2Ao8jLkgTEG2AD8BgwA4hBImbnt/tHuVykpKT4bT8tLY1uN97If194gT/sdr6w2+kIBfZaW5B186nDwXqHg4WvvMIt7dsXWvffwalTp2jfrBmuefPYbrczFFmj/ogF3nS5+MNu578vvsi9PXteMb/r/qlcuHCBktr3KzideX5fazSafx5a0Go0Gr/88ssv9O3Rgy+Tk3k7M5OIIsobgJuBbXY7pxYu5O7bby8QEbgkeDyeUkWqtNlsOIJoRbEbDNhsF5PMmM1mMnPVfxD4FyIWZiKiNRA6I9bbVcCoXMedgNFk4nI9MmcB5rAwnAYDTmSv7MPAa5QsT2wPJB1QH8RqmwmEhoXJvF1i93QFZLrdmM3mPMdTU1PpfN11uJYtI83hIAJYASxHBN9d3v4+joj4HxFrj8vh4PzixdzWsWOBPaJms5msIlIE7QIGA7WARch+ZICdwHWIgF5E3hca+ckEzKGyGzw0LCyPIP0NEZEtgEPIS5K2SMCnCKA68gJlmXe8OxGL+rlcdTiNRkJDfe82z8jIoHunTlTfuJHf0tMD3rtbF1iRnk79LVu49YYbrph9qCkpKdzSvj33HD/OzIwMyhbj2vrImFKWLmVQv346mu4lxGaz4Shh+i17SEie39cajeafhxa0Go3GJ8ePH+e+Xr1Y6LW+FIcIYIHDwYXffuPNMWNK3P7Lzz1HTIUKmENCMIeE0CQ2linvvVfst+3ly5fnXGYmwdhpqICjbjcVK1bMORYTE8OJjAycgAvJQ/sUBBQkKj/RwE+IqMl2bt1rMFA+JobDl2lv8mGrlfoNGrDHaGQMYskrbXbSTsicDAQSzGbqNGlCbGwsB/wIp2BxGKhStmwBQTu4f38q7t7N2qwspgEfIBZNf1wNfAy8DWzMzCR061ZGDB6cp0xMTAwHC7lHCxC37eqIsF0AjENeFHyIWFP7A88AQ5G15IuDBgMx9esD0ODqq9nlPR6P7MP+3FtHUS9SGgFfA62AbkC2xNwZGkqDBr6l6kujR1Nu504+zsgo9ssNE+K2W2PPHp67QrIWPDVsGG0TE3mxYuorXwAAIABJREFUhC/eLMDXdjsbFi/mq6++Cm7nNDk0atSITU4nJXkN8pvFovfPajT/dNQ/gI0bN5boul27dgW5J5r/r+i1UJBuN96oXgsJUQpK/DkGqoLVqrZt21astqdMmqTKWSxqWFiY2gYqC5QT1EpQd9tsqkJEhPr555+LVWf3jh3VjFKMJfvzO6h6Vasqt9udp/6ra9VSG0C9C+omUO5StvMbqKqgLoC6IzJSjRgxQt0eGVnq/gfyaRoZqVavXq3CTCZVHtSpINXrAtUaVH2rVS1dulSdOHFCVbBYlOcSjmU+qNtvvDHPvfr2229VnNWqqoFaUII6PwMVA6qG1ap+/fXXnHpTUlKUzWxWWT6uWQSqCqhNAdSfDKoTqEfB59zcGRmp5syZo5RSasaMGeqe8HCVBqo6qIUlGI8HVD9QA0FlgIowm9X58+cLfIc2bNigqlit6nQp70kSqGpWq/r999+L9R0ONqtXr1Y1bTaVHIR1tg5UpchIlZyc/LeO6Z9M944d1cxi3pf1oGpXqqRcLlfQ+qGfFzTZ6LVw+fGn+bSFVqPRFGDTpk1s37CB50rpLlwDGO10MuHVVwO+5oP33uO9558nPiODKU4nTZFw7KHAjcBcu52FaWn069mTlStXBlzv0NGjmRoRUagrZyBMtdkYMmpUgUjON916KwtNJt4BJlF695frkfQ3HwKrs7Lo27cv61wuv1a7YHEeOJCRQZs2bagWHU1fgpdb1wQ8B5zOyKBt27ZUq1YNW0QE2wK8PhU4gQQ7CnQeloaFce0tt+T8rJTi1VGj6OhwcDNi0Swu/RGrZheHg9dHj845HhkZSVy1aqzLV/4C8ABicW8RQP1lvGV/A77Jdy4L+N3lom3btgDcfvvt/OR2MwOJPN2z+MPBgOzh/RpxkW/fujVRUQXtu2+/+irPZWRQscCZ4hENvOxw8PYrr5SyptIxaexYnrPbC90vGyjXADd4PHz+2WdBqE3ji6GjRzMxPLzAnm9/KGC8xcLgESMwmUqyWUKj0fy/4fLq6kuDttBqSoteC3l5pH9/Nc5kCoqFLAlUlMWizp49W2S7J06cUOUsFnUwgHp/BhVbsWLAb97dbreqXamS+qMUY0kEVdZiUUlJSQXq37Vrl4oKDVXXB2HOsj+rEUvgnV27KqWUat+0qfomiPX7+kw0GFTfHj2Ux+NR5W02lRDk+rNARZtMat++fUoppV576SX1qMXis6wL1Peg7kCsjxZQ5UGV8/7/alBPgtrrp61kUOUsFnX8+PGc+/Tnn3+qOjabqo1Y1fJfk+Kd93mIdXcNqDQf5ZaCugpUVYtF7dixI6f+dyZMUP2t1jxlJ4HqW4K5motYanMf+xpUh+bN86y9vnfcoWJB/VjKe/MgqBpms/rmm28KrO/Tp0+rKItFXfBx3SlQMxCL8o2grgF1A6jBoD4CdcLHNamgoi0WdeLEiYC+v8Hm9OnTKiosTKUEcW0vB9W8Tp2/ZTz/C7jdbtWne3fV22JRziLuhQfUiyEhqmWDBio1NTWo/dDPC5ps9Fq4/GgLrUajCZjlv/5KjyBFn40G2oSGsnbt2iLLfjxtGvcoRXZmRw+wG4mOuwrZY6i85zoDlTMy+PHHHwPqh9Fo5LUJE+hvs3GmeEMAJDBTH5uNoUOHEh2dP0GP7PGqUL48txVRTxYSbfYokAKFWoyvA84AAx57DIChzzzDBxFFheYqOR5gms3GY6NHc/ToUUI8noCD/gRKCHBdSAjr1okdc9CQIXwFnMpVRiHpgWoALwLdgV+BNOAsEsDoNDAFcCPWsc7AkXxtfWg08q9OnahevXrOsWVLl9IsI0PWpfdYGhI8qTVijX4a+Mrbh5FAJaAd8AkXgzjdhFiJW3s8LF++PKf+BwcOZJFSnMg1lqnIntjsn9cge5JvAeoBdZDATY8C/+Vi1OGeSHTihFzXToqIYEguqzBA7/vvx+mdg9LwGJCmFLfdVnAVr127lrahoXmCJu0E7kb24i5Dol+/hES1fgVojHxvr0KCbOW2xEcA14eG8scff5Sy1yVj3bp1XBMWlpMfORh0APYePUpqamoQa9VkYzQa+XT+fLI6dOAWm41V+P79uR24NyyMxXFxLF65kohL+DtTo9FcGWhBq9Fo8pCSksKppKRCA+QUl1bp6Wzy5s0sjE8/+ohBTifLgDuRoDbdkIfjF5GH/srIg/824JHUVGa//37A/ej/wAPc89hjdLbZ8gioRCSQziTgP8AsYH+u8+nAnVYrFTt2ZOzbb/utv0JUFK19HHcDSxBhFoE84F+HBAeq7h3fcR/XGYGmZnNOxNnevXtzuEwZvgtksCVgitFI5QYNaN++PZs3b+Zqo5GSxRUtnHZOJ5vXrwegatWqPDZ8OI/abCgknU0P4AXEBXYrEmG5EXkjLEciLtmTEDHcAUmTNNN7fj8wPiyMNyZPztP2ptWr8Xg83I642i5ChNgS4A3EPfhPb9tfI/mCLyBC7Wtv2V+913YHQjIziV+9Oqf+6Ohoho8cyWDvePYiAvU6JFJyMyQwlgUYASxGcg//BxGAs5EgXG942+gDfO+te6bBgKNGDe666648Yzp+/Dh3hISU+g96K8BsMnH27NkC5zZt3EirdAmr5vb2ryPynTyMCPEnkOje7RDBPxz4AnnR0AGJgD4GcqJ1t0xLI35dfgfty8OmjRtpmR6MMHEXCQGa2mxs2bIlqPVqLmKxWFjw44/0GT+eITVr0iQighcMBt5BgqvdEBlJ16goGj79NKs2bqRKlWBtmNBoNFcywUvMqNFo/hGcPXuWimFhmIKYV7Ga282e474kW16OnjnDM4i4G45Elc1vCz0KfAZ0Ba4Fjh48WKy+vD5+PBarlXZvv819Dgf7kBywtyDWOROSOudZoDlixVtis9G8Rw8++uyzAntnc5OckkLVfMdmIA//0YgFbB6S5zWbncA0JIpuJ2AiImiyiQsL48wZsSmHhYUxa+5c7u7ShesdjhLnZfTFfuD1sDDWzp2LwWDg3LlzVAxCyiVfVAb2Jybm/PzimDG0nj+fiYcOMRMRSTspmNfUHxZEcN6JrIvjwE82Gy+OGUO9evXylD196hTlgXKIoFwEzEH2Z/vDjKQuug0Rnw8D/ZB7egQ4ffJknvIvvPoqbebNY9bBgzRUiirea5YD7yMvafK/KKiDiN7hiAgeAcxHBGISku7oOYuFFfPnE5Iv5/G5pCQqBelelQ8N5fz581Stmnclnzl+nEZuN1lIFO8zSFTlGB915KcMMq5ewADvdfOAah4P6wL4vXApOHvqFHUuQQ7kKkqRlJQU9Ho1FzGZTDw2bBhDH3uMlStXsnrVKk4lJRFetixPtGhBjx49CkQ112g0/2y0oNVoNHkwGo14VGGOsMXHAxiKSDmzfv16QpWiAyIm/T2OxCDW2mGIRejA4cOcOHEij1tpYRgMBkY8/TQ/ff89c7Zt40mPhxlQIP9kBmKRe9toJL1MGca+806RD0kGg4HsbLQe4EnEmjcXcYv1xVWIyHkTCczTHhFZ2cGDPAZDHhHdoUMH+g0aRK8ZM/jJbsca0KgL5yzQw2ZjzFtv5QhAo9FY6gBa/vBAniAtYWFhzFu8mGubNOE+j4f3KSj4AqExYl1tA8Q2bMhwH6lhjEYjRmAh4jK8iYL3vjA6e6/pgljbKyH3PTehoaF8+f333HTttQxPSeEwEIt4FQTi4lofsdxOQ9Z6V6CzzcbYt9+mSZMmBcqHmM3YjUbwk2vZg4hiOyLkCwuC5FKqgGAG+f66EWHuRIR9WABjyU0NxBJ+DxIk60Ykv/LfQe7vajBxQ6EvvTTBw2Aw0KlTJzp16vR3d0Wj0fzN6N+6Go0mD1WrVuVMZmbOXsFgsD80lFp+8loC7Nmzh9tvvpl5iKUtkHfrUcCnwJMuF7e0bx/wvrW0tDT+1a4dDXbvZr/HwxP4FjQWxAq3xePhobNnua5FC44dO1Zo3bExMRzw/v8ZYAPwO/7FbG4iETfbiYgFb5/3+AGDgZiYvHawtyZOJLZbN2612bgQQN2FcRzoaLPRc+hQhj7+eM7x6tWrc+wSWTkOGgxUrV07z7HF339PA6WYQsnEbDbVEDGYsHMnp06dKnA+tm5djiDjXkLxxGw25YGfEav2EaB2w4YFyjRu3Jgfli1jQkgIbYAvCUzMZmNA9t2+i7gcD3ruOQYPHeqzbPny5UkMKygvzwDjEetvQyRydlXEHXg+F11/s3EDZzIzfe4Rj61fn59MJjYg1tXiitlsQpG5SAAW5cqne7mpWacOhy5BDuRDSlGjRo2g16vRaDQa/2hBq9Fo8hAWFkbDmBg2B7HOjRYLrVq18nnO7XbzQO/evJSWRvcS1P2iUrQ7fZrRw4cXWVYpxT09etDkwAFmZGQEJJwNwPMuF8POneO2jh1JS0vzW7bVjTey0WhkHmJlXYQI7+JwF7LP8HZk7+4uu53mzZvnKWM0Gvlk7lxa3H8/Ta1WAguLlReF7BtuabXywAsvMHbChDznW7ZsydasrEtixdpgtdLam3YGIDExkddfeon/KhWUP0rNgUedToY99FCBcw1atmQfsuezNOlayiP7Q/cAjVu29Fnm3LlzlAkJ4b/k3f9bHB4E/m02c+zQIb9lunTpwvdKYc917Edk3/EeRIAmAceQtEyDEW+AtsDJfNc0qFOHChUqFGijQcOGrHG7+QRK7RUQhuwV/k0pGjQK5m79wGndpg0bLYE6tQdGOnAoI8OnFV2j0Wg0lw4taDUaTQG633UXX/qw+JSE/cB+j4d27dr5PP/ZZ58ReugQQ0vh5jwxI4Pv580rMhjLihUrOLRhA9MzMoptBRzldhOXmMins2f7LdP1ttuYZ7XyDmJZK2jnCoxBiGvoq0DbZs0IDw8vUMZkMjFx2jRmL1rE0EqV+LfNxjIKj5oM4mb7LXBTeDhvx8Xx05o1PP388wXcZsuXL0/NKlVYU8Ix+CMFiHe786yHDz/4gJ5ZWdQp5LoLwGrgB0R4bafwXLTPAcuWLeNkvv2t586coRuBWc2LoiNi9TznZ8/kC8OH815GRqnznE7JymLuf//L0aNHfZ6Pi4uj7TXX8JX356WIS+/3SICzNrnKhiKRiVcjUZT/hUSNBpgaEcHQZ57x2cb+ffu4ARHBwaAF4r69f8+eINVYPNq0acPurCyfwdhKyvdA+5Ytc4K4aTQajeYycVmTB10idB5aTWnRayEvx44dU+UsFnU2CLkZh4WGqqeGD/fZjsfjUS3q1lVLgtDO6yaTGtS/f6HjurNLFzXVx7VnQH0M6ikkr+kkUEd8lFsBqnFMjPJ4PH7HU7daNVUTyaFamvF8Bqqq0ajmzZtX5P1KS0tT06ZOVU1q1VJ1wsPVAJtNTUHyki4DtRjUu6DujYhQ1W021b5pU/XFF18op9NZaL2TJk5UvUNDC831eNRb/zxQ34LaVcTY3wN1V7dueeasSmSk2uyj7CFQz4KqCyoCVDtQ3UB1AdUAlA3Je/o5KIeP6weAGjdmTE5bbrdbxVSooOKDsN6yPytBNapZs8DcrV+/XtUODy/1Osj+DA8NVS+MHu33Xv3www+qVUSEygBVFcmJGki9Q0ENAbUPVIWICGW3233W3yQ2NuA6A/38Aap+tWpFLe9LxmMDB6oXQ0KCMhYPqPaRkWrBggV/23g0lwf9vKDJRq+Fy48/zcdl7sclQQtaTWnRa6EgI4YMUX2t1lI95K0FVblMGfXXX3/5bOPQoUOqstWq3H4eEI+B+g7UR4jg/AVUkp+2joKKDg/3KzaPHz+uylksKsVb/jyoQaAqgwoBVQtUK1CtQdUDZQYVDerfoA7m6lOjiAi1cuVKv/PWuUMHNS4ID8gOUGUMhmKtTY/HozZv3qw+/PBDNahfP3XLNdeojs2bqy7t2qlhDz+sPvnkE5WQkBBwfefPn1cVIyIKCMA9oO4FVRZUeVAWUIZccxYJqgMiqjy5rrsAqobVqtasWZPTxtGjR1U5k6lAuYHeukaA2oJvkZwMaiGoW7z38ct87S0EdVOrVjlt7d69W8WGhxc676dA/ZBrzS0B9Vch5T2gylss6sSJE3nm7tWXX1bPmExBFX8t6tTxe69cLpdq17Sp6mUyqY7FqPcEqHKgmtlsasK4cT7rTkpKUpGhoT6/p6UVgdFhYSoxMTHgNRlM9u/fr8pbrWpfEMYyB9RVtWqprKysv2UsmsuHfl7QZKPXwuXHn+bTLscajcYn4955h00VKjDVR8ROO7AL+AOJ+HrCx/UngXttNt6fOZNKlSr5bGPjxo1cky9/ZiowGdn/1xKJ9LrO29ZYoBaS3mQOeV1OawIWpTh8+LDPtn788Ue6mUxEIhGFayA5RhsjaXQUEiCoLLIXw+ztw1/eMg95y9yXns73Cxb4bANg965d9PFz7jTiAvoWkjNxErAMfO5TtQA9w8JYnSvHaVEYDAbq1q2L8njYu2MHR44dY+/hwxw5epS9O3YQFhZG7XzBmAojKiqKdz/4gPutVpxAGuKu2hZJQTMC2Qu5FFgJrELuS3Y+138jeVePeOt7IiSEbnfdxXXXXZfTRnx8PE2VynEBXwM0Reb/EBIkqxm+96CWQdxmf0HcPccge5Czdzm3Arbs2pWnrVY+1rMDmI7c7/rA68AK5N68CsR5+zQTifCbGwPQKjSU+Pj4PMfjV62iTRDTwjQHdh89SkZGhs/zJpOJ75ctY7XRyJBi1FsNiawd2bQpTz33nM8ymzZtornFEvQ9SgagpcVSYO4Kw+128/PPPzNp0iRee+01xo8fz+zZszl37lzRF+ejTp06vDBmDANstgL3tTgcBkZarcz2kVJJo9FoNJce/ZtXo9H4xGazsWTlSjq1bcuF8+d5xu1mDyIw5yC5RKOQ9DbHENE3FMk1uQfoabPx6PPP07t3b79tHD58mHqOi/GUf0H2j7ZF8rdeR8GIty4k2NJ/EEE4G0l9A1DPbObw4cM+RVtSUhJVHA6uRSIIt0Zy2t6PRF2tnK98CpLa5T3v2FYCdYFRSrEv377M3JxLSyO3fFfAWmAqEn23K17xDRz09t8ODEFydJbLdW3lrCzOnz/vt63cHDlyhHfGjWPOF1/Q0Wjk6fR06gDhQOqFC+w6eZLpO3YwYvBgBg4ezJPPPOMz+E9++vXvzw/z53Pbjz+y3e3Gicz9VcCHyD2ojohLOzKn7YBxSFqbhxFB2h3YUKUKG6ZMyVP/yZMnqe1NN/MrcB8SvfrWgEZ9kWuQlyuPIXszf0bm+bzDgcfjwWg0cvz4cWo78sbvXoPkVa0PTEEiAOcXbh5vfW96xzUPWT/ZxGVlcTxfPtUjR44Uuie4uFiBiqGhJCYmUqtWLZ9lKlasiDUigjYBrplsOgBn27UrsI86mxMnTlDrEuRsBYj1MXe+OHv2LLM+/pjpkyZR3uGgvdNJ2cxMkkJCiLdYGDlkCP/u0YOhTz1FmzZtiqwvm+EjR/LHihX0XrGC+Q5HwLmPszkM3Gyz8dIbb9C6deuiims0Go3mEqAttBqNxi9xcXGs2bSJH5o0oabRSCdExG5F0m6sBTYDp5CcsB8hwvC60FBeev99Rr/wQqH1ezyenF9CE4GBiJCdhwTb8fV4HYJY5VYj4rcj8JP3nMlbpy+ysrL4yuPhHBIY5xrEyvwkBcUsiEAbAGxEAuykesuNAex+rGQAbo8nx5poB3p7r2+FCNgvgQneet5D5m82EA/UgzwRi01K4XIVFvpIWLduHe2aNSP8k0/Y6nCwMD2d25BULTURQd4bWJqWxqrUVJLee492V1/N3r17i6zbYDDw8ltvsc7joSry0mEmkku0AfJyYCeyFrYilvm+iPB7EHkB0h2xoI584QXKlMkbIkkpiWycANwLLKD4YjYbC7J+mnj7p3K1kbutbGYCdyAeAcuAm/H9R9Ho7dMqxHp7C3IfszEoVWDdqVxW52BhNBj8ru+cdslrzd6P5HW+A+n3Xcg9yZ3kKgRwF7LOLsVYsjH6mLv8LFy4kAaxsSS8/jpfnT7NhtRUJmdm8howweViXloa+zIyaPT11/Tp1In+vXvjdAZmczWZTMz55hvK3norbcLDCdRWrJBI2W2tVka88QbDnngiwCs1Go1GE2y0oNVoNIViMBhIOnuWew0GjiEP9DXzlTEDdyJuqD8DEUYj9kLS22RTpUoVjlsszALeR9yKbwm0X8AjwHeIlfVP4JjbTeXKvuQp/PLzzyjE8vouIioDscYYgeGIIDuAuGiuW7/eb/kom43ziJjtjFjWdgAjyWt9zT2O9kgKmO8REZgdrfZ8WBjlyvm66iIbNmyg+003MSM5mbdcrgL3Jj8NgQ8zM3k2MZGObdty8ODBQstnZWXRrVMnairFdMQC3wsRSs8AFfOVt3LxfnwE9EfE1O3As8OGFcjlGx0dzUnvuMcg1sLSYAA+ABIRi6vNbMZkEomXO1/rQiQS8h/e8QRa932IsB2GrHWARLO5gLW7YoUKFMyCW3JcwBmns0irerXKldmHvCjpClyL5Jd9EHgKeRm0FIgFHke+D/tCQ6kaG+u3zujoaE6bSpp4qHD+CgkpdEyfzJzJ4/368avdzide6/qDSARxE7LerkVyCg/3eNiVnk76kiV079QpYFEbGhrK519/zbPTp9MtMpK+NhvfI67zTYEKQBXgBuQlyGdAh4gI3qhVi8WrV2sxq9FoNH83l28b76VDB4XSlBa9Fnxz4cIF1TQuTr1ZzOA2h0BVt1rV/CIi9G7fvl3F2myqPBIdt6QBWb5GIuHazGafQVm2bt2qrEjAp/GlaGcRqFgk4u7nn3/uc0y33XCDmgnqDlD3kzdIUSCfbaAqItFz64WHqz/++MPv/J08eVJVjYpS35VwPO8bjap+jRoqPT3dbxtPDh+uIrz9iQX1aTHb2Owdz0/e65s3apQncFdCQoIqazCoThDUoEPbQEWRN5BSfHy8uioyUiV6z/1ZivqXg6oA6hyomPBwtXfv3jzz9vSIEWqswRC08WwHVb9qVb/3KZv3Jk9WN4aFqQqgpuM7+rNCAq49CKopqLKhoerYsWN+6zx69KiqZLUWey0H8qlhs6n9+/f7bPfnn39Wla1WtQcJANYNCd72FqjjSKCwNCRwXBdQVUCt9h6/02pV9/Xq5TdInD/OnTununfpoqyg+iLBuP5Cgmd9C6o9qAijUT3//PMqMzOzWHVr/hno5wVNNnotXH50lGMf6IWoyUavBd8899RT6v6wsBI9yMaDKh8eXqhYcrlcqrzZrN4MwoNxT1CNY2N9tnN9mzaqE5L2pbRpVO73PjzXjo722dYPP/yg6lutqgkoZwnbmA+qMahmcXGFPpC/+Mwz6rFC0uoE8ukeHq5mzJjhs/7U1FRV1mRSL4N6AEmhU5I2FiMvHH4BVdZgyCPSXS6XivQKkWCLpTtBdbz++py2nE6nKmezqd6gnghC/Q+C6odE8na73XnmbvHixeqayMigjeUNk0kN6tfP71rIZtWqVSoc1G8B1OkB9TSoquHhyuFw+K3T4/GoauXKqR1Bvj/7QFWMjPS5xj0ej2pYo4b6CRGt14B6FFRWIfX9grw8WQXKDqpOES+EfDFq2DDVKjxcnSyknd9BVbZa1XfffVesujX/DPTzgiYbvRYuPzrKsUajKRZOp5OZH37I805nifbPtQTaGgx89dVXfsscP36cLKV4vMS9vMirwNmkJLKysvIcT0tLY9OGDZwFXsJ3tNzi8BKy3zXx3DnWrVtX4HzXrl0553LxOLJXtyT0BM4D3fr08RuoJzMzkxnTp/NYZmYJWxGGpafzwVtvoZQqcO7jjz4iy+3mXsS1e1QJ27gVCRDlAaooxcujR+ecW7NmDZVCQri+hHUXxkjg2L59OT+HhoZy1113sQQofHd3YLwKfAP0f/BBjPmiJ3fp0oXEsDA2BqEdFzA9LIxHR44ssuwbzz3HRAhoPg3AeKCxx8OcOXP8lzMYeHDQID70umsHiw/NZgY89JDPNb5y5UpMFy7QGXENr48EVisskuUtyL7WuwAFDLXbmfrOOwH357vvvmPRrFn8mp5O1ULKtQcWORw81LcviYmJAdev0Wg0mkuDFrQajcYnCxYsoKlSNChFHUPT0pg6frzf8/PnzaOv0Uh4KdrI5mog1mjkt99+y3N8zpw5VALOAV2C0E5dZF9dC2DatGkFzp84cYIspbivFG2YkD2axwoJ2rRw4UIaud00KkU7ICIg5dQpn+J8zowZdESiSvdA9hLm5wLwG7KHcRmSwim/NDYgEbCnIYG/1v/5Z46AXrl8OXeqSxN0qD2QdOECp0+fzjkWW78+HSm497ckxCDpdOIaFPyWmEwmnn3lFYaHh1Pa+MATQkJo1LIlLVu2LLTc/v372bRpE/2LUbcBeMrh8PtSI5tHHnuMOUYjRccjDoxTwOyQEB4dPtzn+Q8mTGBoWhqpyP7y8fgOEpefm5GAb3OBAUrxw5Ilee5/YUweO5bX7Hafe93z0wbo5fEwY/r0gOrWaDQazaVDC1qNRuOTOdOm8XAAgZ0Koytw6tgx9uzZ4/P8hhUruK4QC6MdScWyHAnEsx0KFQftMzLYuGFDnmO//vorMUjgGF/W2T3Iw3If5EG4DSLeXkPy1Pp6xL8OsThu+f33Aufmz59PH5OpgEhXSBChXkhk5muR+XkaOOujjUHAgkWL/EaA/fqTTxhQyvsD8kfgAbud+T4sdAcOHswJWPVwruNJSC7d2kBVJFXOG0g03asQ4fsYEgE5m3uR+9gYMLvdHDki2WnjV62i9SVKCWMAWuXLc5qweXNAgccUvu99fm4Bdm7Z4vPc4KFDCWvcmHF+cpPageNIvt3zftrbAEwMC+OjQiyo2Xz8wQcMcLuLnXqmM5B86lSh+WBjYmJ4YtQoBtlsAc1LYSjgUZuNwcOGERcXV+C8w+FgydKl9ENShP3pwT2lAAAgAElEQVQLCcYWKEMRa2400M1o5Jtvvinymt27d5Owc2fAAcIAhmZk8OGUKbgv0frVaDQaTWBoQavRaHxy8sQJ6peyDhNQx2zm1Cnf8V53JyTk5JDNzR5gBBJN+UEksvJLSOqZOEQ8/eXjuqsyM9m9aVOeY4d27sSCCKnc7EAe5DsgKYDOIhFTrUAasA4RuW2AFfmubQo4gXM+8tEmHjtG3VzRVVOAV5BcrY8grtgDkDRH/0bytsYgInd1rnoqAiEGA6mpuROsXORMYiIxPo5nINGHa3vriAIqISmBJiBuv/mpqRRn843F4XCA00ljJBVPfUSIzEKs1PGI2EgDtiH5XDcgwmwtEIa8IBjp7VO4tx8VAIdS7PO6Ah86dCigdXYI+ByJXPwhEhHaf/Kki9TLzOTQoUM5P+/bvt3nmlPI/PdEUjaFeD9lgbuRqM2+hFxTKLDmsjEajXzxzTfMLl+ed0wmFOI+PAfxKIjy/nsNsj6qAs8jcwiyBm+3Wpn15ZfExPi623lJ2LSJ6/K53AeCEbjWYCAhIaHQcs+9/DJJtWrxstlc7DZy80ZICEerV+el11/3eT4pKYlyoaGUQdZZoJHPs7kF2IKs9TiHg78CcAveuHEjnUymYm0TaA5kORwBW4A1Go1Gc2kobDuKRqP5H8aekYE1CPXYALvd7vNcZmZmHmvSeSRn6zrENXUTkl4kN5sQ19WGSHqYd7n4i8wCZObLEev2WoBt3p8VMAkYi+wzDEPcZvshosIInEHyoaYhD633IuI2uy0LYil2+7Ce2lNTc+ZtC2JdaouImI4UdJt8FLF4zkRSH92E7AM0ATaTCbvdTtmyZQu243DkuT9piOD/HRGcryFiKxzJObrO2/83EdfrL3LNmw0KpFnKysrCaDAQphR2b9m7ECv5Cu+8+MKAiN//IBbbAYh79ipvOy5k7jK99yXL5fIrItxIjuGp3v7fgljdspC0QQORFx6PIi86fGH2ePLsq3Y6nQUsmAsQS3kqYjW9FqiBrJVjwA+IO3V577huy3WtxVunP6pXr86qDRvo3qkTnx45wnFvaqVnkPuVvStVISmE3vG2XQc4abMx+6uv6N69u9/6c2O320v8nbW53X6/p9mYzWZ+WLGCTm3bkn7iBG9lZRVLAGYBL5nNfFO5MitXrSLMz55cu92O1bsn2c7F726ghCDfn0zAphTJAXgy2O12bEXkw/VF9ne0tKSmppKYmIjH46Fy5cpERUWVuk6NRqP5X0FbaDUajU+iIiNJLuR8GmJdPI1vq182F8Dvw1nZMmU45/3/ScSVt4633jcoKGZBLJwfIzlh9yLuwdkS9hxQNl9OS0uZMiguuvW+hgjiiojb8CJEBA7x1tUdEUk/IC7HcYhIW4+IXre3nVAkyFB+oipVIhmxUt6AiOclQCf87wEsD4z2jucQsg/QA1zIzPQpZkHmLvv+HEVEZBayn3UzIvZbeI+3Qtww93vHuxuxWKd4r08GykZH56nfarXiUooLiJXyAUTob8G/mM1PJWAxkoP2ei5aHkOByMhIAMKt1px+5CYZccl+CRHSx4AvkRyzHyHuy2uRebrGe8wXqSYT4eEXHcDLRkXlrDmQdTYIEU5PIXO5FJgNfOpt5xDiMXAOWQOTc11/DojKN3f5qVmzJtd16sRZl4tfEIv2fVwUsyBr4zokyNQh5OVKhehobrzxxkLrzk3ZqCiSAi6dl6SQEL9rLTeVKlVi9caN7Lv+elqHh/NHgPWvB9qGh7O1XTt+i4+nalX/YZeioqJIdrkAyd3syxujMC4gDzdhwAWTiajy5Yu8Jjo6msRi5tp1AUmZmSUWn0opVq1axd3du1O9QgVubdmS7q1bE1O5Mt07dmTJkiV+txxoNBqN5iJa0Go0Gp80bt6cNfkityrgV8QtszLyAN4IcWd9Gwo8TCcDuzMyqFu3rs82ml9zDZsRy9htQF9gInkf9P0RjbidhiMC1ANsttlo3q5d3jbatiUFEWLfA58gD6IPI1bKwsRZHGKR+wAR0PsQC1o8YgGq7iMYUINGjVhutXIrYnUtToCecojbazJwB1CxbFmsVt82tzqNG7PZaCQFEXRdgV+KGI8BEZZrEZfkVshcbA4LI65xXqdss9mMtUwZNiFzvRv4EYptAcyOpNsSEdCJiAWtadOmADRp3pxt+a5JQyzb9RE35gF+2q2L3I+1yPqb5KPMtpAQrrrqopNxiw4dciIPv4fc36uQlwnPIC8X8lMJeBFxhc+2fn/iPbcOaN2xo4+rLvLyCy+weMYMNiMu7EVRCXmh0vr4cW5o1apA5G5/3HTHHSy0FdeeKfdleWYmHTp0CKh8+fLl+X7ZMp6eOpX7KlakTWQkU5C5sCO/J+zIvZsKtIuM5K4KFXh88mSWrFpFpUqVCq0/OjoaQkLYj7xgmkNg+5mzmeO9zgCss9moX79op/Z//etf/J6VRXGchxcBTRs2pHwAgjk/aWlp3P6vf/Fo9+50WLKEY5mZ7E9LY19aGomZmfRatYqX7r6b61u04MyZM8WuX6PRaP6nuIypgy4ZOg+tprTotVCQtWvXqjrh4crtzb2YieQibQjqQ1CpuXJZ/gmqP6hqoDblytc4xWBQfW67zW8bn332meoeEaFGe/N5liTfrQNUS1D/BVXDZlM7duzI08bixYtVNKiyoKqCagPqhRK08wWomqDKg6oF6mpQo0ePLjCm9PR0FWE0qqdLkZ/zLKgIUCOGDfM7d+vWrVO1w8PVtaC6Qc59CvRjB9UMydVazmJRx48fL9BG5xtvVE1BRYLaWIrxKFAXkByhfUBVCA/PaWPy5MlqkMWSp2wvUAOLuR6OgKoO6qd8a8MaEpInF/LixYtVc5NJbfeuiZbectlr+TdQfUHVA1UfyTv8Z64605AcwZFIHtV6ISFq1apVfu/Tnj17VKTBoA6WYM6yQLUH9cxTT/mtPzfJyckqympVJ3LV4QQ11zvvt4Ia4uNefgDqzq5dA2ojPy6XS/3www9qYN++qnlcnAo1mRSgQk0m1ax2bfXQPfeo7777TrlcrmLV+/QTT6hRZrNyg6oNam2Ac+b23p/loHaAqlK2rHI6nQG1OfDee9VYozGgdjygboqIUHPmzCn2nDkcDtWhZUv1kMWiMosYy7Nms7qqdm11/vz5YrejuTTo5wVNNnotXH78aT4taDUapdeCLzwej2pRt26OQBgEqrP3gd7fA9g8UFVAHfA+8DWKiFArV67020Z6eroqZ7WqCl5xUFKxNA8RZ9c2aVKgDbfbrSqYzaoeqE6ganiFQkna6YQIwEqgLKCSkpIKtHfhwgVlBXWqFONRoB4D1bN790LvT9O4OGUBdbiEbawBVQZUz86dfbbx008/qTBQ3Us5luzPJG97jw8ZktPGgQMHVAWLRdm9ZXZ615CzhOvgxlw/fwaqc/v2ecaUlZWlKkdGql6gbLnmzoWI6DrefiaA2gXqHVCxoB7nosDehbxwuAdU7YoVlcfj8XufevfooZ78P/bOO0yqImvjv+6e1GkyOecoiKIoAkbEhAkMn4oiKqJiwCzqrii6KooBzIs54eourIoYFjOYSIqBjJLT5DzTfb4/TjXT03S4PSBuuO/z3Ifp7rp1blWde6m3Tt3z7kGfzQdp4nZLIBCIaSMcl48ZIxelp0vQXGdHkCNAngV5G+Ru054zUCK/A6SDxyPz5s2zVL8VWL3WeAj3ixnoQtqOBH0VBLkZ5DDz9xXp6XL7zTdbtvnTTz9JvscjX1gYlwdcLunVvr1UVVUl3babJkyQEW63pUWoIMgVaWkyasSIpO3Y+H1gzxdshGD7wr6HTWijwHZEGyHYvhAdL7zwgvT1emU+Gv0qtTABuwNkNMg0p1P279Il7mRfROTkE06QIXsw4Rc0epwD8vDDD0e1MXr0aMkFOQXkrj2w8zeQQ0DcIAdFIc8iIrdOnCjD97A9ArICxO9ySWVlZcy+GzhwoAzdAxtBlMBdfPHFUesPBAKS7XDIvL3QHkGjtOmw2/12/KBB8pwpMx7ktj3wgxYgP5i2DfD7Zfbs2bu16+4775RUkGPCzr0VJX7RFmyKQAaA/CXsuwEgqSDTH3005viUl5eLz+WStXs4Rl1AZs2aFdNOOIqLi6VPp04yweWS1rCrX8OPKjQKfibIIR6P3HDVVZbq3tc46YgjZFJKigjILSA9QL6N0U87QC4H6QWyDSXzuW63rF+/Pimbc+fOlXyPR2aYfoq0sx3k+tRU6di8ufz6669Jt6miokLyfb6kIvaFINkZGbJly5ak7dnY+7DnCzZCsH1h3yMW57PfobVhYx8hEAhQXl6OiPzRl2IZo0aNYsCIEZzjcjEWTaKUCFegWWMn+3y8NXcuDkesVEiKwo0bmbCH15mKZrpdt2JF1N/vvfdeStFMuxdH/FaLSs48AlwFjEff+fwIKI8oewqaNCgPuOmOO6Laeunxx/e4PaDvJfcIBJg5c2bMMqu++45ro3xfjSZjmoG26zm0PZFqmQ40EdIns2ZFrb+qqooKYGCU3wR9d/UB9D3hk9FM0H82tqOpC2eh78VuiZBRufnuu7nd42ET+v7j2IjzvkKTWh0IdEMzXA9FEzoVhZVLRRM8PYW+H13RpAknnHDCbteR26QJWWhmY9B3SB8350TqB4eu+2X0fdtQArIbUNmdeAmhnn/+eQ4IBGgfs0RiOIDrgHtvu81S+czMTD6cP583c3MZgr5/HIl0tD1zgV4jRnDvQw/twRX+fnjqlVeYkZ3NCw4H96D9MBI4BJgOvIlKOY1G322uQO/lKuBEj4epjz1G69atk7I5bNgw5nzyCa8efDBtMzK4PiWFJ1G5qPPdbrpkZLD9tNNYsHSpJSmlSMycOZMB6DvsVpGNtvuvTz2VtD0bNmzY+F+ATWht2PgdsWLFCq4dP57mWVmkp6aSn51NWkoKPdu25aEHH6SwsDBxJRaxePFixl98MccdeiiH9e7NsEMO4ZLzzmP+/PmNJtEOh4PHZsyg0OlskNxoC5og6HVgFpr8JWQhH5WpmTBxIh07xhJTqce69evpF+X7JSix6YVmfG2LJjy6FSWVkegPrIuho7lixQq6ZmTQFGhuvisD7jB1X4JKpqSik/0f0azDrYArTXsxv/cHOjqd7NwZPZ9sQWlpVJ3TxqAf8OOPP8b8vbimhgFhn9cBt6B9dT+avXkVSuQnEl3DdwBQVBROC+vx888/09bpbJCkS1AytB+ajOs3VGpoDJosrBa4F81QfRe7a8UeBHz/fcM0UEOGDOHks8/msrQ0clH9YYyddqb+79FM0Zehcj0t0GzXbdFs0qExGoJmeb7O7eb5v/2NlJTd1elWL19OEapBDDDbnNcCeB/1u1NQneBxaKbjTqhm7HthdiqANWvWRO07gMWLFhErzdLXaCbq49AEWCPQzMrR0j/1BzavXx/TTiSaNm1KRkoKV8cp4wYucblo3rIlTue/51SgZcuWvPfpp9yem8vklBTOQ5Oz3YY+H15FSXlvNGHbc8DPwEC3myvvuIMLLrywUXYPOuggPvr6az5dvBjvTTex+Lzz+Or00zng7rtZtWEDz8+cmTCxVSx88u67nGpBRigSp1VV8em77zbKpg0bNmz8t8PWobVh43fA0qVLuWHcOJYuXcqYujpm19ZSDVTX1eEBqtev59k//Yk7b7uNEaefzpTp08nJyUnajojw2muvMe2ee9i4di1jq6s5MRDAh0YXl33zDRfMmoW3WTOuuOkmxlx0Ea4kpSlSUlKoEqEpSoweQyf9bVCCF0TlWNxodPZ8oGNGBpmZmZbqL6mowB/2+Z8oIdoAXGrqzEOji1tQ6ZZ+aLbe29HJPkAmUFIcXWiotLQUv8u1iyx8DpyFId7G5kdASzR78VY0KjIB2Ihmcn4czcKcCVQ5HJSWlka1VRUINGjPniAP2FpQEPW3YDBINeBHMxVPQPvmfLR90fK6hmv4Xo+S3EygJhAZu1WUlZXhD1sM2YFGwzagkd+j2F2K6P/Mvz+hxONAlHj0Nd/nm3ojcd8jj9Dv/fdJ37iRKuBYNJv0jWh0tkmU6xOUGN5q2nQPSphXOBzccNttHHDAAVHbVbR9O0HqMyevQTN0N0f9WdBMw4L6/Juor7dHFw3A+AFQEmNhA6Box44G41ADPIn2XRm6CDAI/Y+4AI0CTkAj3ZOoX3zJBCrjaN1Gw+aCAnbPwd0Q3QMBFqxbl1S9+xo9e/ZkwdKlXHTWWUxbtIgxdXWMrq3lUjQbeAa68DQHeNzvZ3N6Og8/8QQjRo7cY9vdu3dn0uTJgC7u9OjRY4/rLCkspDEiPzlASUk0gSsbNmzYsGETWhs29jLef/99Ro0YwV3l5dwA/BWNwvRAJ9CFqKbmBRUVzAVeevNNDvviC9777DPatWtn2U5tbS1jzz+fxW+/zaTyck5k9xv6OBGuLS/nozVruHPCBN59801enTULT5LSHp60NI6tq2MDSkhS0AhdPjqpX4iSnefRLae9gUE+KxuUwZuRQUVVFTnAZOBZVLrnpCjtaYeS0LvR6N0JKEEbgRJ4bwybbrebGoeDCjQadyG6vfgJNMp2MzToP0FJ4eMoeR+HEsANKBEJulwx5XTSnE7Kg8GoMjMb0K2qv6Ak1IdGG8cQfbtMEcRcGHA6naSh/jQGjeytMXX+y7TpW3O9WWhE8XJUr/VOtH/Xm7alxojQud1uKs2W8e3AEcDxwN9RLdl46IluPX8F3R78DiovVAw0zcjYrbzP5+PZ117jrCFD2A8diyXo1utYcKDbTz9C/eYqdKEit0kTbpg4MeZ5mbm5ONCt2etRglmDRkqvRIl6qEeCqA9MQyWVVqP+5kWj+b44GqS+7GxC1L0QJa9eY+94dPEkHNcDy1D/74bKwgxBxzA9iuZxPOT6fGyoriaesuxGp5OcRkYa9yVatWrF3C++4OOPP2bitdfy6JIlNEcXfCpRv8/PyuKia6/llltuITU19Y+94Djw+v0kH59VaTOfN9qGeBs2bNiw8e+5z8iGjf9QzJ8/n1Gnn87r5eV8jE6OBwO/olta/4VGyb5GJ7MnAd1qarhowwaOHTQo5jbWSASDQS4480y2zZ7Nl+XlnELs1SknGu2aV1GB7/PPOW3YMMu6lgA7d+7EZaKBaSgB+g2NBk5Dt30uRKNYPVFCtbSqiqIYkcVItGrWjOXAX0wdC9CtnvFW27xo9PZ99J3Xd9GoXKsO0d9M69WrF6uqq3UhAY2CPQX8w9QR2X8OlEi8DnyHErizUKKxANiSmkrv3r2j2spyu4nchPorul26Mzr5boJGg31odLEZulU4Er8AnTp1itEL4HU6OR/1pbfRbZc9UGI0DH2fcBXqd32Ac9EFgUo08rgEJbe+GAsB3bp1Y50INSiJOxV9Z9YqtXIA56Fk8xRgG7DI6WygCxuOvn37UoSOxQJ2J7PF6JbS1TR8H9iBLgy8AcwE2nbvHve62nbqRBZKsgeg/vQ1uthxDEp0V5ijBiWfc9BFDhcadf4A8DkctInzHmX3Hj1YhJKRfuiCwFfofR9rn0Rv9N3nV9BFls9RP8hrEi1GHRtnjxrFjDgkOAA8l5HB2eefn1S9iVBSUsJvv/1GcYzdEo3FczNmcMaJJ3LITz+xCPWBb4Af0B0VtxUX8+aUKZx+3HGUl0e+/f7vg4OOOIIPGqEV/EFqKgda1Am2YcOGjf857MvMVL8X7CzHNvYUe8MXysrKpHlWlryD6oKOpF7fMtaxFqQbyIMmc+apQ4dasnXf5Mky0OvdJXVi9agFOdHjkeuuuMKSnbq6OhnUr58c6HDIYJNtM5GNZ1HZlbz0dPn8888T2pj26KMyJD1d2kID/czQEUAlcLYTXZd0AUg+SDu3W+bPnx/TTocmTSQP5DpUdufHJPptG0hnkJtAvCC+1FQpKSmJamfcxRfL+WHn/gCSjcrJtAXpj2ZafhDkUjQ78xBU3/bUsPM2gngcDikuLo7Zpv4HHCBdQcpRCZ58kJkx+inUl4+imYCXm3blgYwaNSqmjXa5uXIdKoVSF1FfMSpr0wGV42mOZin+NYrtG9DMul6nU7Zt2xbV1ksvvSQedpdw+g7kHGOjq+nHtqgETVFE2VtA8tPS4mqPbt26VTKcTvGbvlhvzl2DyvPkmvHuZPrnWpDfTJnVqJ5uJki60ylFRUUx7RQUFIjH4ZD+qJ5tsjrLs1Gt3D4gM2bMiGknGtatWydNfD75V5R6gyAT0tLk6EMOSarOeHj33XfluMMOE29qqrT2esWbmipDDzlEZs+enTDTeSI889RT0t7jkV8S9FcNyOiMDDm8f/9GyenEw96aLxQWFmrG4ijXX0X0/zMqQPIzMmT16tV75Rps7BnsuaONEGxf2PewZXuiwHZEGyHsDV94+qmn5BSvVyaDDDWTKyuT1l9BWoJ8YnHSUl1dLc2zsuSnJCfHoWMTKgERbyIewjvvvCMdMzKkexTiEO94AKQ3yNEHH5zQRlFRkWQ7HPJ8lMnpfahmZr4hEAeAvByFGFwB0io7O+7E+cwRI6QvKrfyRiP67QeUCJ8N0qdLl5h2Nm/eLB6HQ4rM5DQPZBhIe1RTNLLeEpQodzRlrzff3wZy/JFHxu27gfvtJ6+BbAVpBvKexbb8FSVrVSCTQS4488yYNm69+WbJBFkWUcdClIx7QU5E9T8vQPVZs4yN8PKV5hr7de0a01bb7GyZFHHeq6bfp4IURNj/P1SmJVzztxolqXfeeWfcvjuob1/JBPnSnLfA2LmFevIaIrnXmToXm+/eRxcpjh48OK4NEZFD+/WTHBqnqyumjRkOh9TU1CS0FYmPP/5Ymvh8clFGhnyGauvOBBns88nBvXrJjh07kq4zEsFgUK4bP166eL3yPOxaZKsEeQmku9crV15ySaNJ7bJly6SJ2y3LLfZXHchpbvdelyLam/OFS847T8anpe265r+DDEZloNLQ59zz1D/n7nG55IQhQ/aafRt7BnvuaCME2xf2PWxCGwW2I9oIYU99IRgMyv6dOsm71OtgJjNpnQpyLsh1aWly4zXXxLX1+uuvy5F+f6Mmx6HjTI9HpsXRzwzhhMGDpS9KIpOpvwYl6bnp6fLzzz/HtbFq1SrJcrkaRJtrUJI0jHrdyQDIHENgbomwF9KcjBeVO7hHD/kLGtmLjDRaPY4BuQckz+ORurq6mLYG9u0rU9CoZFeUyK1NUPetIINQkliGRgkXLlwY08ZPP/0kzdxuqUZJ6cVJtmWoGdet6AJHQUFBVDtPPvmkHBxx7gaU0PUBWRfxW4nx5Sx2J9i3ggw/9tiodubPny9uNGocKv8dSjIjyXToCILcDnIoDRc57gNpm50ds+9ERDq2aCEHmPLbzRi9E6e/ZqJazMXGVmfiL2yEcPghh8jERvqboMQ90+mM62/xsHXrVrn7zjvlwC5dpGuLFjJ0wACZOXNm3HslGTw+bZr09XobLDaEH0UgB3o88vADDzSq/ssuvFDuMFq0Vo+1ILkej5SXl++VNors3fnCzp07pVubNjI5JUXuMM+IN9HnXsDcNweCjAN5GqR1bq789ttve82+jT2DPXe0EYLtC/seNqGNAtsRbYSwp76wYMEC6eT1yuvo9tFkJ60FhiAsAMn3+eJulxvSr5/8bQ8myIJGg3u0aRM3arJmzRrJTkuTpmgkL1kbd4Ac7HDIVZdeGrfvbrzmGrkuNbXBuU+AHIFukY6sdwdIG5BvIr4/0ueT119/PaqNyspKSXc65QJ0m2pj++3vIANBWrtcsmzZsphtWrhwoficTmmOkmArNivQSHQrkB4gRySIbk+4/HKZmJIitaY/FifZln+YtgjIuR6PPDx1alQ7Y0eNkmkR514O4qch+Qw/6tCt1d0jvl8M0rN166h2xo0bJ4dFlD8HXeyJ144gum3/s7DvVqGR48rKyqi2fvjhB8kN2xVwL8hoC302EmS6+ftRkGynM+6OitLSUvE6nbu2NDf26AUyc+bMuP7wR6Curk7a5efvWnSKdSwFaZWTI7W1tUnVX1xcLDlud9RXERIdJ3m9SW/Tjoe9PV/YuHGjdGndWvLQRaXI6y9Fd200y86W5cuX71XbNvYM9tzRRgi2L+x7xOJ8dlIoG//TqKmpYevWrWzZsiWqlIhVLFmyhKOCQeagiXeSRQ6aYXU1miho48aNMct+t2wZwxp1lfUYAqzdvJmKioqYZRYsWEB7VFs0PWap2Pg/YIMIX3z0UdxyCz//nGMjklQ9gUq+REsMlYcmgnoi4vtjy8pY9M03UW0sW7aMNg4H89HERo3FcDR5UJ9AgIULF8Ysd8ABBzB56lQKTPmLLNTtBkahurubXS7mfvZZ3PI/fvcdg+vqWIRmMd7fWhN24SQ0wdJWYHBFBT/GaM+ir77iwLDPQeAlVB4oVpoiF5qYahua0CiEXsDaLVui+t03n3/OwLDPxWjSptEJ2uFAtWlnhH3XERDgsxh9+M0331AusssXZpg6EuHyMDuno8nZvvvuu5jlf/nlF1oEg7S2UHc8nAHMeeedPaxl72PevHnkV1fvks7ahiZq+pf5N6R33AdoX1fH3Llzk6r/008/5cDUVFo24trOLS/n7VdeacSZ+wYtW7bksMMOY4LDQbQ80z7gT0Dfnj3p2jWaCJcNGzZs2AjBlu2x8T8HEeHzzz/n8SlTmD13Lr6UFFKBoro6urVrx+U33sg5556LNwmJhKKiInJqaviJeu3IZNEM1aLMdjopLCyMWqampoYaozO7J3AA2ampFBUVxWxnYWEhKYHAbu2pRLPJfk69DmRbNHtw+LSrWej3GHqtIRQVFxOuwCuodMnhcc450lxDOLKBNVu3RikN27dvp5kIK1BCHI4gmqn5GTQbLSi5PA3NPByeJzYF1X1tDuzYsSPOFaqGZUjQpVnckvXogWZtzcvKIj09/jJCUVER2ahcUlt+LFkAACAASURBVKuI32rRzM/foySjJarPejT1qe1TUK3VnSghLorRnu0FBQ18oBQlrIcBP6K6qouAEsADdAIuBg5FpYlWoxqxoFqu2WlpFBYW7iYdVbpzZwPisglogS72rEXljr41bXOiE/5LUKmePmgm6hAc6DivXbs2apt27txJLarviqnfyoJAH1MWIBeVfIp1r2J+i6XG/Amqm7sF7acsdBHocnb/jzkHWLhli4Ur3B1VVVXMmjWL1atXU1FWRlZODocddhgDBw7E4YhUEU4Oa9eupW9dHfNQiat/oZm8/aifrEIzO18O9KmpiTkesVBQUEDzMI3kAJqV/HHUF0LPnzbowseF6LiAeZ4muEf/aPy4eDGXisT8/Ujg1p9/3ncXZMOGDRv/obAJrY3/KSxatIgLRo6kbvt2Li8v5ykRsurqACU2H61ezePXXcfNEyYw8fbbufammyxN+tLS0qhxuUgLBKhp5LXVouSpBmKSmZSUFMRcayzZD8v2REiLI+uRlpaGOJ3UmAnlNmAKqjV7MHAyOtGuQonNYHTCH5KMqTHtSUugCZmamrpbn6WjBCk3Snmon8iGowZIi6JvCtpvdQ7Hrv4F7cOLgH+av5ujBCVofn8SeNC06xXYRU5r0Ym1yxV/BLxeL3WmrKAkax2qS7wM7bd8NGJ8Ckr2qk25FAs6mmlpabv6ONSmbahG7zMouSxEH/IBc/216PhcjZK50Pm1QFosn3O5CI+fp5nrvAclwyehUjN1qE+moCSzytiNbEldMBi175wuF3URdorQqO5qtK+2wy7/zwYmodrFfdn9P7MAxNQjDfl9wJyXhi7UhO4GMZ8d0EBPuCqsTI05N97CQ1paWoO+E+B+YLppSwdTXwqqo3wrcAeq2/sM9YQ7nm/Hwm+//cb0qVN5bsYMDnQ4OKC8HHcwyJaUFMakp5PRtCmX33gjF4weTUaSdYdQVFTEu1VVfIOS1udQMhtCGfAq6nNba2q4PA75j4a0tDRqjUbyK8Dt6ELF5Wj/ZKPj9BOqr9wJjWZPxfh0ktq9+xput5t44kbFgDvBwpYNGzZs2LB1aG38D2HevHkMGzyYiWvX8lNZGVeKkBX2e0ivdVZZGd9WVPDiXXdx5SWXIHFW0EPIz89nY1oaHYClEb+VoBGFs9DJ/wWoZmggotxSNNK5pbqavLzIOKK5RqeTXK+X9TGuow7V75yDapBWxyhXCpTV1ZGdnR2jBDRv3pwKl4vvgeXAISjh+xqN/l0KnIluPb0P1aYdDYxFNWV/QLekNm8abUNdPZo0bcqGsM8OlCy/jBKAL9Etrq+ixBnz2ykR9WxwuchvGX1zYufOnVmNRvxWoxPtbsCHxsYh5po/QvVZH0OjIw5Ui7SrOS8U//0Z6NIlUiW1Ifr06UM5OgF/HTgOjQIWAuegk/IhKMFpbf59FyUvrbt1i1s3QG5+PlvQiNgyNGLVEdV8HYrqBFeboxyd8B+ALkp0RPV1C02fbAFym0ffW9C5Y0eWh31+AyVhR6P++jYaCf4FHZ+P0P49Fo2SvUn9IsFOoEqEplF8ok3XrvwQ9vk71E8LUOI3Ee3/GnPMQ7f3hyL6y6iPsFeihPHQQw+N2qbmzZvjoz7aOgTVoF0DXIcSST8aBc4Gbkb9e5YpC+oPHocjaltCaNq0KVvMNQZQjdu7wuodgZK0O9H7pitKoL9A/XNdmK1YGsvR8Omnn3JQ797I44/zVVkZc0tLuScY5HZgal0dP5eX8+Datfz9uus4asCAhLsNomHZsmVMnTyZW0X4Ht2yvQmNpI9G+/E3064lwCQRpt9/P4sXL7Zso0OHDiwVYRK6/fZV1M8vRP3WjS56DQJeRO/VOnR3x3yHgw4J9Ij/aJxy3nm8FEeT9uXUVE4544x9eEU2bNiw8R+Kffom7+8EOymUjURYunSpNPF65eMkkooUo9k5J912W8L6t27dKtkZGfIlmuU4lK3yz2iyp5FoRtnZaMKjAWi23dnG1kLz+R8gA3r2jGtr3OjRu2X9LEO1TZuhWqCd0ORCuSATYbcMpI+DjBg2LK6diooKyfN6JQvNWPyMxX7bCNITpB9In9RUeerJJ+Paee655+QEn69BHV+hMj2dTF3nonI5rdDMujloZtpQ+RqQVh6PLF26NKqNYDAoWenpchsqg9LF1N0H4sqBbAE5zpTPN305BsTvcsmWLVviO4WIHNC9uxyEJlB6ANWLjWbnB1SqIwskA+Tbb79NWPeTTzwhp3q9ImhyJzeaHCpWRuDQ8RkqD+Qx/RoE2d/nk7lz50a1c+tNN8ktLpeI8c8WIGONrd5mTG5EkyRNBtnf+HIfkKOMr99obL8LMqRv36h27r77bmlvrudjc3055n6Jp99aYOw0Q5ND1Zo2ZjscMZOeFRUVic/lkhtMHbNBWmM0hk1f5pnDbcbPa2yEniHjQPypqVJRURFzjILBoLTKzJSP0KzS2abO54gu4xM0vt8LzXzbBJXZynQ4LCcGmj9/vuR7PFH1ZyOPAMgNqanSr2vXmLrK0bBp0yZpm5+/K/v5V6bv/cYv+qNyWz40G/QXptzfQFrl5sr69est2QkGg9IyO1u6ED1xUrQjiEpf5Tgc8vHHH1tuUyL8HvOFnTt3SovsbHktSjs+Amni9cqaNWv2ul0bewZ77mgjBNsX9j3sLMdRYDti8vjhhx/kr3/9q7zyyisxZT7+HXH0wQfLUxYnROHHZpDcjAz59ddfE9o497TTZKrDIYeDvILKqAyEmBlOP0PJwatohtV7QI7z+eSFF16Ia+f777+Xlm73Lp3bQpREtEPJ7C0gT6Jkuq2ZYHYyE+PQhK+Xzyf/+te/Erbp+quukuawmzZoouNXM7n1p6dLaWlpXBsVFRWS7/PJ6rDru8i06TM0w/JikB8NCXgTJdjhmXffAhkUgyiFcOkFF8gEVOexJch+pu8StSUkIdTFtOlekMMS2AphxowZ4gGZZcFOBUr+mqSnW6q7tLRUctxu+RUlSs1Mv1sZn0Uoee6MZtbu3Ly5BAKBqHaWLFkirdxuKUAXSK42/pSPas2+gMoNtTJ9ej8qr9QO5CCQE4wPzgcZ6fXK9GnTotopLCwUv7me5qb+5yy2pwrV8cxGNWPPATmkX7+4/Xf2aadJDqqXOsmMrQcl4tmoZNSxpp/6mN/8IA+ji11+kHFjxiQcp7smTZLe6EJFHvW6t/GOQmOzPZopuk/79okdQjSbd4ucnLjyQ9EI4Jj0dLnkvPMs2RARuXrcOLnGLKq9jy4+HWfGLnzx4RuQk8zvb5vvbnK55LILL7RkZ9OmTZKZkpJQ8ipam4Y5HHLfX/5iuU2J8HvNF5YuXSpt8vNlqM8nT4HMADnV65Umfr988sknv4tNG3sGe+5oIwTbF/Y9bEIbBbYjWse2bdtk6KGHSku3Wy7weuVUn0+yMzLkjokT40q//Dvg559/lmZud6OkZwTkqrQ0mXjDDQntfPnll9LZ65V/mcluX1R6IV7dP5jJcyvqJXtiSY2EY/D++8uLpo6hKEG7DnaR3NBRhxKwpuZ6AiBzQbq1amVp3D788EPxm0l/sv02EaRft26Wxui68ePlaiPdMwXkENN3D6BEraeZ3HdFpXPWoRG1D02bhvh88uqrr8a1sWzZMslNSZFslCwlimSGH0VmnDJAOjkc8tZbb1lq15Vjx8qEJOwUoNHfjRs3Wq7/PKdT8kFeT3J8/mL89JT0dHlwypS4dgb36yejUGKfhUYOZ4EcjuplvgWyGuRTkNONP39q/LItyGUgJ6PaoMXFxTHtDDr4YOkDkmpsJdOeX1Hi1MSMUyIysHTpUslxOuVK6iOwzdGdDsVh9Rai+rktUVLrRaOz2U6nrFq1KuEYFRcXixeNuj6cRHtWG5/zgjz11FMJ7YiIvPTSS3JsxG4HK0ciLeJwlJWVSa7HI+uolxsbY+7DWOTyclNuG7qDI8ftjusHIdz5pz/J2IyMRj23vwbp0LRpzIUaKwgGg/Lpp5/KLTfeKFeNHy8rV65sdF3xUFVVJS+//LKMPuMMGXXaafLUk08mXAi08cfBnjvaCMH2hX0Pm9BGge2I1lBXVyf9e/SQG1NTGxCmjSAHeDwy5Z57/uhLjIurLr1UJkZs0U3m+BmkWWZmXG1YEZ38DD/6aLkwPV06gbxnsf4rQM4H6eXxyKMxtEAj8fXXX0u+xyMvm4niCOJvyxyHRoOfBWnmdsfcXhqJCVdcIdc7nY3qt/VmkmxlK+OmTZukdW6uvGyu8weUWPQD+SlsYjwPJRZvo5HBYSA3p6XJwL59pbq6OqGdowYPFj/IkY1oz+Vo1LFFfr6lxYCysjLJSk+XdUnaGQNyh4Vt7iIiK1asEC9K4qJtYY13bEe3hPpcLtm5c2dcO4sWLZIsh0MuQwnsSNMfp6GLJpF1P4xuR34IjTqfgpLBB+6/P66djRs3SoYZY6v3T/hxMkqGe3btaqn/Lh41Srwood0PXfyJVfetaNTUZ9oyYfx4SzZ+/PFHyUDv0+JGtKcJyOXjxlmydWjv3rteY0j2ONfjkakPPJDQxjPPPCMnG9J8Ixp1TuR7tehiwVXm80ivVx6bPj2undraWmmVkyNLGtmeIMiBfr/MmTPHUt9FIhAIyPlnnCFdvF75M8hVKSmSl5EhzyR4haKx+PLLL+W8U0+Vs088sdHXbGPfwJ472gjB9oV9D5vQRoHtiNbwzjvvyIE+X1TCtBykqd+fkOz9kejQpIn82MhJUejon5kpn332WUJbpaWl0rNDB2lN7IhF5LECjcJcOXZsUtHu2bNnS5bTKc3Qd9ji2ViJRtZyHA55bsYMyzba5uXtIpThx1aQT9Ao3VyQJUQn1Mf5/ZajmUuXLpXMjAw5hPqIaLTt2nPQ7cgVpkynli1l+/btlmwc2r+/9EK3hCfrA4tRotU+K8uSrVdffVUOD1sMKEK3SR+NRsu7oWRvNLodNxhmp01OjiUb1dXVkkr9O6rJHmeAuF2uhHZWrVolTVNTZX906/U/URK4KUa9QTSi/o4ZIx/IMKdTnn322bh2gsGg+Ew/W71/wo+30YjwEYMGWeq/qqoqSaV+O3A5Gv1/ASXlD4O8aPyw0NxDbpAMh8Ny5O/iiy+WNugrCMm25x3jJ+2ysxPaWb9+veRnZERdYLByfARySI8eCe2cetRRu975bAZym8X6J6PkXNBdFscPHBjXztdffy37+f179Nx+GGTsqFGWxikSf/vb36Sf1ysVYfWtRBfpNm/e3Kg6Y2HBggWS7/HIdHTLcQu3W2bPnr1XbdjYe7DnjjZCsH1h3yMW57OzHNtIiLmzZ3N2WRnRxGu6Am0cDhYuXLivL8sydpSUED33rXW0QLUrE8Hn83HtrbfSz+VqkEK8Ds0kuwbN9Cphv3VBJWBunzw5KV3Ik08+mbZt2lCJyuhUAC+gWUbHoVIZT6NZljujsifuzExGjxlj2cb2khLamr8F+AzVH+2ASrNMRbOPHofK3twDDWQo2tTVsW3bNku2+vTpw+ixYxli7ByEZv+NxDBgA5r9tqfTyT0PPUR+fr4lG+U7dlBNQ71cq+iCjl11VZWl8hs2bKBPMMhKdDzao+060hxD0Wys7YBRwIGopE9nYEtxMSISrdoGKCgowGPOCUcxKgFzNKoHOxTNblwZUa4zUB2IzLe9O7Zv3047j4ffgF9ReZ6u6H0hqBbuGuo1VR2opuo3qJRKDtDM6Ux4D1VWVlJnzon8z2k5mhH4UtT3HkdldMLRCc2AXFRQkLBNoLIzKU4nOahW7lloJuhZaNbmn4G3gP1QiafOaGbdGhGqLPrBpo0b8aMaw8miO3r/VldUJCy7detWWqelRZXz+hXVvZ2DZg0viVKmLbDNwjNu5/bttEAzV1ejOrNWcDj1Gaqbk/h5umPHDlo592yK0hLYsXlzo87923PPcWV5eQPZps7AcKeTWbNm7dF1ReLphx/m9ooKrgDGAI9WVvLYPffsVRs2bNiw8d8MW4fWRkIEA4G4mqdOIBgMxinxx8M6TYx9vhWCAaot6PV4oLSUVaiu5DvozRaqIQWVbbkale9ISWncrej1eBCUvL6AksAjUMJZDrwH3AScjRKNWLqcsSAiOID1qFxJAJXjmAMNJI8E+BwlTZPNcS3J9RtAkyZNqHA4CBq7DwPTqJcfykIlgpzohNrv8+Hz+ZJqj9A4f3DQcCHCCtajCwAXA6ehEjfvoRPtVFTeZgtKDk9HNX7/SXL3k4P69vyAkudFwFHoQoMXlbP5J+qLQ4AnUIKdTD+E2h86AsBDpq7t6NhUouNyIeySLHKEn2/RF0LnBNE+eQCVgBmKkqFSVPP0RtPOKajMTei8ZHxORChHSfmFwExUwzccpah01IOwSyvXqg0xY9lYn2ts+Tp0zCeh8kSdUDJeiPblicBtqHZ06FwrbQo9E4AG99IKVLv5W7S//OgizTiUmO+yYdFWuJ1wBNDnz/uoTnEGulhwAbpoF45knz/hCAYCUSdIKSJ7/f+7QF1dA73mVP79/0+1YcOGjX8n2ITWRkIcc9JJTHnjDSaUle3221pgTSDAAQccsO8vzCJy/X62Vlc3IGDJYiuQm5trqWzHjh1ZFAxyEqon6UFJ5WDzdwEa9XkAJQSXA6SkkJOTk/R15bZsSeDnnwGdSEZTqtyITjS3Az2bNUuq/vzMTL4oKOBM04ab0YnyLOBvKAnIQCeul6CEbQUagVwLbExJ4RiL0VOArl278rTXy+qyMr5CtXkvRXVTA6ie5TkooX0ZWFJbm1APNhz+Jk0I/Pora8w1h7AYuBdYiZKoVihxD2nRgkYgc4EMd3jMJjZ27NjBPJRE3g60QSfeP6BELwPty2bm831AL5SA+pxOamtrSUtLi2sjJyeHcrSvn0QXNq5FtV9bRJS9CdUzfRjobcqsBdIsRMHy8vLYXFtLa+oXSn5Bfe55NAoc6qfVaPT0RdTnV5l2lqWlxdRXDsHtdpOC6q9WmPMLUeJ1NrsTzZXogseB6CJKd1QjN9eiz1VUVOAU4SpUCzYWgfSj9+k41C+eAUpLS/F6vQltNG/Zkh/NtYbjF+AR1MdrUZ8bh+r3hkZklbFdZcHn8vPz2VRbSxDYjGqz+tFxHwmkh5XdhI7REcDx6FhtAPItPINy8/PZaq4xDdXvvRe9Ny9ExyETjQJ/YGz0Avqhkf10YBuJn6d5eXlsDiOjoQWUaahvn4nqXFcC89EdFMPRcWxvztkC5CX5zAvh1FGjmP7FF5xVXk7oLtwAzBZh0vDhjaozFi4cP56z5szBX1mJG7jW4+H+a6/dqzZs2LBh478av/tm530A+x3a3xe1tbXSq0MHmexyNXivrQBkkMcjk2699Y++xLgYN3q0TNqDpFCr0OzD8fQmw1FdXS3+lBTJBHmD6ElzBKQEzQTsAznIogxMOBYsWCC5GRnyocV2fA2Sn5Ym7733nmUbF55zjmSiWqCCvnvaAmQImmDqI/S9xStRzdCz0MQ3W9H3IN0ulxQWFlq2V1VVJR5jYw7R36OsROVcfCBNLb5rGsIzzzwjWWgyqdDY9kLfn7wdTUT0AchUNAFUa1Q6SECuAekIcqEFyZEVK1ZIE69XHkTfuTzanDsNfZc2vD3fgFxg2tzZXM9xTqdcfM45ltrUq2NHyUTf7/zOoi+8hyY2Sgc5/aSTEtoIBoPSrVUrGWf6pZ3pux1oVuoD0MzG3UCuRd8LL0Flb5qhki7Z6emyadMmS+1pBtIBlXyJzLAd0ngO/24h+q5uH1SWaebMmQntlJSUSO+OHeVui30WftwE0r9nT0vPhEWLFkm6uT/K0GR6h5nP1xs//wDVhu5q+vF9Y2ckmkxpjAWfCwaDckCXLvIymsX7LuInihPji4ea8RmdkSF/mTw5oZ3Hpk+XkUb/+CzjRw9HGafQUQXyGJon4BTz3Tkejzz04INx7VRXV0vzrCz5ydRxCsgRZqwFfd95LZo5WYwv3mHuo8Xmu0P9fpk1a1bCNkVDbW2tnDZsmOzv88lUkNudTmnh8cjUBInNGosPPvhAhh9+uBw/cKDMfP3138WGjb0De+5oIwTbF/Y97KRQUWA7onWsX79eDu7VS9pkZMiRLpcclpoqWenpcs24cXski7AvsHTp0ga6rckeN6SmyvVXXWXZ3sjhwyUT6+TiUTTBzssvv2zZRnl5ubTIzk5Kb1JQDcx8r1e2bdtmyc4Jxxwjl5hzH0OJTKx2laLZlPuhpPYXNNmOFXmOEA4/9FBpHzZJjXcsNf12++23W64/EAhIXkqK5BrSkA3yIJqFNbL+ICpH40eTIOWgBNBKAqpxo0fLzQ6H+ECOQjVSE2ne/h2VV2qDJmvKzciQdevWJbT1yiuviJvEicEij1ko2V68eLGlvnvk4YfloNRUaYbqM/+Deo3WPBCXGe/9Tb/ehpLPw1HCe+aJJ1qy88Ybb0i66bPQPVuC6tt2MnZSUH3b98PaswglV9kpKZaSqz1w//1yssuVkPRFO4IgR6emylMWM952bNpUeqJSSS1M30STEQuG+eXTqAyRF2Tr1q2W7Dz99NOSixK7aPfnRnaX9qpAk5R5nU5LdoqLiyXH7ZZvULJtRWNZQN41/v011iWCbrvpJhmflibnoYS2Gk1EOMb0TVvjg4eii4dB829LNKFWm7w8qa2ttdR30RAIBOTtt9+Wy8eMkTHnnSeLFi1qdF02/ntgzx1thGD7wr6HTWijwHZE61i9erUM6NVL2mZkyAWpqXJaerpkpaXJ+Isukpqamj/68hJiUN++u3Rbkzl2guRnZFjSmxQR2bx5s2Q7HPJsknbOMJMvq1mOZ8yYIce73Y0i6Bekpcm9d9+d0EZZWZl4nE5ZayahLUDWWJjojwM5x3weBnK/xYjGunXrJB3V30yGlGVCUosqF5x/vrQx5z1hwca/UKLUGeTg/fZLWH9xcbFku90yBqQHGpmNjMrGOp5EFwT8IFempMgt11+f0N65Z58t5zfCDwRkYBLjU1BQIFkOh7yPRhRzUYJyNUoygqgU0BQ0m217kDvRyJkbLEfKSktLxY1G3wRd3NgP5EyUtAfR6Nyzpm//HNae60Hat2iR0EYgEJCOzZrJ/Eb2m5g+6NOhg6V7dtq0aeI2Pnenhbq/RYlsW5D+FnwuhLfffls60DAyu9L0nQ+Nljdld0L9C4jX4bCcrf6yCy+UAWikOpk+ux3kYJCLLO4++O233yQzLU3amzFfYHzrLnQXiKCLUf9AtapvMN9NBOnudMpdd9xhue8SwZ4v2AjB9gUbIdi+sO9hE9oosB3RGgoKCqRdkybykNPZYPvsTpBj3e5GyyLsS4R0W79OYvJVgW6pvv7KKy3buXr8eMkhevQl3vGVmewuWLAgoY3Q1sI5jZyIfwfSLj9f6urq4tqZNm2aHGHOOQfVFLVSfwkazdyAksHmXq+lSf/hgwfLiUm2JYAS7SlTplgeo+rqasn3+aRbEnZOA3E7HLJx48aE9U+fNk3O8HqlCRplnJaEnVp0y2lbkAkklsSqra0Vv9PZaK3O2SAtvF5L/fbFF19Ih/R0qTPkoSWx5Y++R6O2fpR4nONyyV8sLKKIiEycOLGBTvCJKHGKFkndhi40/NN8XgficTiktLQ0ro25c+dK74yMRkVnw32vQ3q6fPnllwnbFAwGpXe3btIM63JE41CSmYxEzGF9+8rjYXWsMffHvdRr4C5H9W1PjLiWAVjfJfLTTz+Jm+iyWvGOzWgU3+quABGRg3r2lPvQZ2pIgzpa3QUg3VFyuxm9X3/77TfLdmLhlZdekv876SQZecIJ8s033+xxfTb+82HPHW2EYPvCvodNaKPAdkRruP/ee+W8GNHAEnRr5Nq1a//oy0yIf/7zn5Lvdsu7Fideh3g8MmrkyKSif/lut1zfiMlxEH138qShQxPaWLZsmbT1eBql0xk6+vl8Mm/evLh2erZqJX83pCHbTBit1n85GjkLohGhZcuWJWxXJsjHjWjL/SAt/H7LYyQi0r97d5mRhI0vQZp6PJaI+dH9+8tklMxlYz06GzomgRyJktoBmZny8ccfx7T17rvvSo898IM6dPFh+fLlCds15uyzZYrDIZ+ixGJQWD3Vxk/KqSeeN6NbWe9GF2y6tmxpaWza5+TsIi3Ljf/EWyB6FX1HOfT5cJC7E5Dni845Rx7eg34LHXeBXH3ZZZbaNeL44+UvSdT9C0h2WppUV1dbqn/Hjh3idjikNKyO0TSMYIeOGjM24Ytib4D0ad/ekq0ZM2bI8EbuEBmZkSGPP/64JTtFRUWSlZ4uO0BeBhmaoO7X0C3+AnKm2y2PPfaYJTuxcN/kydLd45Hn0ffq8z0e+fzzz/eoThv/+bDnjjZCsH1h38PWobXRaLzx7LNcVBmpYKnwAyNF+Mc//rFvL6oRGD58OP/44AOuaNqUAX4/L9BQl1OAr4Dz3W56ZGQw9MoreX7mTJwWtRCDwSA1lZUc3Ihrc6BasmtWrUpYdsOGDXRyOnfT6UwGXQIBNmzYELdMUVER7YFlqA5nMjmYh6LSMQ5UosaKFm057NZ3JWhG3VeA14GP0Yyw4TgEqI6SgTseVq9dyzFhn2uAecbGK8BcVHokhEOB4spKyizY2bFzJ9vRTKzdIens2oOM7Uo08+2OHTtill2yZAk9o3xfjWYxvhfNsHw/KnUSqTjrQvVHE/kCwNrly9lfhE9R6ZzhwF/QzNpeVDYnD80EfRXaZztR/dO+wLqtWxGRhHaKS0t3tekdYAQNM/RGYgSqrVpuPvcDfvnll7g2tq5fvysT7p6gPbBt/XpLZRd/+y3Dkqi7G5AeCLBx40ZL5Tds2EBTEUIiVgK8AVwRpWwqmj381bDvegNbLWpGr1q+nAEx/k9IhIOrqlidYHxC+PXXX2mdnk4e6gvnJCh/OprxuBwYUFnJimXLGnWNAIFAgDsmTeKDigouACYAtflZxQAAIABJREFUUysqmHzjjY2u04YNGzZs/D6wZXtsJERZWRlN4vzepLra0kT/3wGDBg1i1aZNvPfeezw0eTJjv/2WTEMOy0XIyc7mmptu4qExYxJKjESirq4OByrH0hhkANXV1QnLVVdXN9rGLlvBIFVVVXHL1AUCek2ofmUIy4DHUB3IYpRsdEYlR0LkI3Qe5u9EtoLBIAHqicsPqL7p68D+KIEKoHIu61GJoEuA1qZ+K0Qpsm1uU9fTwFOmjV6UhFeiZGwUcBkqO5KG9r3f749bd3V1NQGUNESOU5Fp0yqgCl0kOA4YSL1kTEjOJ0DicSopKSFcOOY3VL7nadOegKkr9KB3ofIzF8Oue9rK+ITalYGO+RbgLuAUdKK/GV188KIyRBuBi4ztQrTv6oJBgsEgLlc8VWstF+q3SlSneaVp19yw+toCo1E5H7cp60WlfdZXVMRvS1XVHt9DYPzcQt8B1NbW7rqPBCXhL6A+WIsuBgwHzqDeb0I+ZwXV1dUNiH8deg/mofJKP6JSSNnA4dTr+Ya3pbauDiuorqjAmojZ7sgAqsrLE5YD43MOvTMqSbw4lBaq3/xbncAP4qGqqgoRoXXYd52AwoKCRtdpw4YNGzZ+H9gRWhsJsd/++/NZnN8/9fvp1avXPruePcXy5ct54/nnWbhkCWempXFTXR231tUxXgRXZSVvPPccH3zwQdIkKS0tDXE4iIxxBNDo2G2oRuhdwPdRzt8KZGUljudlZ2dT6NhdMbME1bY9CNU7PRDVQN0ZpY7ClBSys7Pj2nFnZFAINAV+BX5Co26DUR1dBxqBbIFqUE5EJ8lTTfkQYSo21xwPTqeTdJQoXQ8MQ7Usr0S1Hz9Ao7M1wDWojmVfVAN1K+CyGEUPIcvj4RE0KvUWSiiOQ4neWOA0lCR9aNp7LVApYml8sjIz8QBlqN6noBq2Y9Fo5jyUdDVBCceFKGmfYcpuMrZTgSKXK27ftW/ffpe/zQH6AM+ZekPELxsltKWoL0xHCfq35rxCEo8PQHZODivRyO+RwI3AAmPPjfpCHtpnLwLnov22Al388KWnJySzAO7U1F0+m2nqOox67eFvUV+4ER27Nqh2cGhktqGarHHbkptLUYzfQmPewxxHQMznXxGQbXHhKzc3l19R/ea+KOHvBlyN6jsPB15Cifqt6P1cIJKwLSFkZ2dTHPY5iC4u9EQ1W98HvgNeQ/3+VhruutgJeDKs0fzspk3ZluQ9F8JWh4Mci9qwubm5bK2tRVAyudB8X4UubryM+sBv5vvVqK9nJ2knGrxeLz06duRR86ytAR7KyGDQ0Uc3uk4bNmzYsPE7YR9ue/7dYL9D+/ti3rx50tHrlZ1R3lmaA9IqN/c/ItOxiGr9NfF65V6nU3bEeKfwbZBeHo9ccdFFSUsS7d+jhxxu6gqCTEdlWHqbd9mmoHqmTdEkLPNM2WI0q+mdkyYltFFUVCTZGRmy2ZxbC3IRmon3BPMu3EeoDMxINMPsCOp1IkvR954TJUw56Zhj5M9o4pjWaNKqHPNe3jcR/VaAJo1qjyahaYUmHNqOJmfZuXNnwnY183jkUPTdzFtMe04C+RDNeLvKtO0gVKpjGqpV2hdk4CGHWB4jEZHDBw6UPFSv8zH0XfBIX6gGeR2VKmoL0t5iFurRZ54pf0aT37QF+SuaXfZ6kD+hmXnzTJ96QU5H3wM+CORc0+aBqFZpM7dbVqxYEdPW2rVrxYvKC2WZPssCOdDYb2X6qAWa5ba/+ddtyr1j/k6URElE5J7Jk6W5wyHXou+sDqU+63Bk361B36PuAPIU+i7x0QMHWhqbwf37yx0gy9B3de8mtsZpyNZBIGej79rmgXzyySdxbdz15z/LRU7n7s8yMyaXgTxjjktMv7YB+STC9hkpKfLw1KmW2vXQ1KnS0/TJB8RODrUCZDia2bl/9+6W6hbRBGE56emyyNyPQ4wPzY1iqxh9NrVC39kOGv8cdeaZlmx9++230t7jaZAkcAfIdSBdzLh1QjNgbw8rEwDp4vXKF198YclOSP/4c5Cf0OfmBDTT8SA0Wd0paMbt4Wi2+BsaYScWVq5cKd1at5bOPp80TU+X4UcfbVmP3MZ/L+y5o40QbF/Y97CTQkWB7YjWcfOECdLV65UX0aylK0FuT0mRJnth0rCvEMp0/JmZXK02k5++aHbM08Imf0UgAz0euSEJ/VkRkdmzZ4sX5GeQi1EiG0n+QklZZprJ96soOctyOqWoqMiSnbGjRskkh0Pq0Ey6A1GNyWgT5O0o0e1tiMETIKdZSD61ePFiyUMT8/hRMvtRHGIhKDEcaiaet6O6m0dZJJunnHii9AAZi2auXRfHznxzPVNRsvTiiy9asiEi8v7770uu0VP9IUF7BE0Q1hOklcsljzz4YML6FyxYIJ28XumDEshMM76tQUahEkghElgC8rhp7yWozFEmqnd7D8hRBx2U0F67/HzxU0+6QvIszcznPJSU56AEJgcl8h5ja+CBB1rqt3EXXigjQY5FFzXCyUys40lj+z6QHm3aWFoQ+OyzzyQbXQx4wYINMX59FEpq2mZlJbSxadMmyU5L25Ww6xXTH/ehia0i6y9FiZ8XXagR9DmYlZ5uSU9VROSB++6T1safErWnDiVr/Xv2TEpH9ZYbb5Sz0efBpSTOqBzy7bvQBY5ffvnFsq2DunffpYM92fTfSHQB6ns0w/lZ5vvbTblkpI5CePihh+Rsj0dWG18eg5L+8HaUobq9WeiiYWPsxEJFRYXMmzdP3njjjb1Sn43/fNhzRxsh2L6w72ET2iiwHTE5vPPOOzJs4EDJ83qlVU6OjL/kElm5cuUffVmWEAwGZf/OneV1MwF63kyOrkMJxo9mQrQfKmlRiUYcWrjdsnTpUst2AoGA5Hs80gslyqXEn1D+gEYXckGGH3usZTuLFy+W1m63jAU5FI0mxrMTQCN/p4D08nrlww8/tGSnQ36+HG2u750ENsInl33NRLYJyFdffZXQTnV1tTTLzJSHUOIXLXoeeXyPEu0pIMcMGGC57wb36yf5IJ9bbI+g5DoLpFlmZsLdCMFgUPp17iyTUcI4CY2Qvhan/mJ0YeJKlIQ2ARnk98tbb72VsD3Dhw2TJihR9ZkjByXIX6HSKh+jEcwmph25Znxagtx8000JbZSVlUmO2y1T0Khfbdi1B8099Awa5Qz/TdDI3xiQdunp8vXXX1sao9y0NBmXxPgIugiVCXL11VdbsnHmiSfKI2j034tm0bVC0H0omZ2MdT3V0K6KVUm0pwakv9dryQdC2LJli6SDHI91eaAN6KJQF4tZqEN46aWXZH+vV/4E0pzdSWboWIMupNwMcpDHI888/XRSdgoLCyXf55N2II8kaMtK49Md0tPl2RkzkrITibq6Orn/nnukTV6etPB4JCs1VQ7u0UNmz569R/XGQkVFhbz33nvy9ttvS0lJye9iw8begT13tBGC7Qv7HjahjQLbEf93MH/+fOns9UrATO5boLIYkROianR77kXm8ySXS8aNHp2Urblz54objWxamVBOB8l2OmX79u1J2TlvxAhxmwm5FTs70e2lQwcNsryV+plnnpE0Gkq0WDn+jiFmfr+lqMZrr70mR/l80t2ca9XOjWjUs2lGhqXo0rJlyyQnLU2GJNkeQSPHHdLS5M0330xo569//avs73ZLNkosb7E4Prkgd4AcgG7lTxSdKy8vl2y3WzLNOSFi+0EMG8+bMm3RbcnpKJFJNEbPPP20HJeaKv1puLCxA5XJ6QhyIcgh6LbzRWFltqKE6c8gF5xxRsK+q6iokJwkyV/ouAbkmssvT2hDRHV1m6enyzB0B4NVG4NATgVpkpFhWU/10UcekbMaIXPzKsjRBx9syYaIbjvOd7tlcZJ2ktluHEIwGJRzR4yQDBI/69agz57TTzihUVHOCddcI8MstuVtkFZ+f9Kvi0S2bdTIkXKExyMLTb11qN5xW49H/pokKU+E1197TfJ9PhmSmSnHZGZKjtst0x95ZK/asLH3YM8dbYRg+8K+h01oo8B2xP8djBoxQh50OERAjjMT+1gTomJDCjaaI9vtTmrF/MUXX5RBEe/nxTtKQPwpKbJ+/fqk2vToo4/KkUlOXP8P5LprrrFs46EHH5S2xI8uRjtq0UWDppmZliaWRx54oExBt8JGRvjiHb+i0bVrXS65bvz4hHauGjtWusGuSH0yx2KUDFqJBtfV1UnX1q3lapTMxdoOHnlcje4acIP8/e9/T2jnxRdflNZOp3ipf2d2fAIbJ6OR7Sw0otkkJUU+++yzuHYO7dVLHkG3D4dvNT4JfacxPBr4Bholqwj77iw0oulPS0v4vu6LL74owzyepMdH0NcI8rxeqaysTNh3IiL3Tp4sfurfZbdy/NP03RPTp1uyISLSo02bXa86JHNUoe9RW90KPGvWLOmfnp60nXUgOW63lJWVWW6TiMgN118vJ1u0cSbIlVdckVT9Ikoue7drZ3mMAiAdPB7LuwGiYd68edLN623gw6HjF9NXeyuKunDhQmnm8TRYhFht2jBnzpy9YsPG3oU9d7QRgu0L+x62Dq2N/2l899VXHCvCDjQz61lxymaieoZvoBqqHVJTWb58uWVbH82axQXBoOXyfuDwYJBPPvnE8jkA/3jpJUYldYZmnn3/rbcsl1/61VdsBU6M+F7QrKhr0Ky8kcIiKeackvJySkpKEtr5eeVKKsw5yWiJtTVH00CAX5YsSWxnyRI2AscmYSOE/dHMzj9Z8AWXy0V+VhbNgP6oH1nB/wEfAQM8HjweT8LyK375hepgkJZoRts6VM4oHi42ZV1oX6cHAqxYsSLuOWvXr6cSOMqcB7AW+Bq4h4bp8s9As/iGe9nxwC9AjsvF1q1b49pa+t13HNVIuZWOQKbDYVm79YhjjiGIZjK2ihNQndNhJ5xgqXxVVRWrNm5kUBI2QkgHBrlcLLHg2wDffPUVwy3K/ISjHeoTK1euTOq8t195hUstlh0LvDdzZpJXBps2bWLr1q2Wx8gJnFFVxdz33kvaVgjPTZ/OFRUVDeTKQugGHOFy8VYSz9F4eGzKFK6tqmL/sO86AndWVPDo3XfvFRs2bNiw8d8OW4fWxv8Eyior8QMFqFxKInGKdsB287ff4aC0tDRe8QYoKihoIIdhBbkiSdkAKC0qIrHYSkNkAxUWNSBDNmoAn/lchMqoTEXlctKp10w9E7gKlQsCXRhIczopKSlJKAtTWlVFNcTVO46FTJRoWiHOZWVlVKCLCI2BH9hWWWmpbEVFBUEgJLoSAN4DnkEXAmrQ8RgKXIrKz+SjMkedUlIstae0oIAAKs8jwA7UdytRWZhvqdcRPhZ4GF0AqEHHzgGISEJbpZWV1NFQB3QtOrl/EfjKXLfXfNcVlVAJwY/KBnkgoZ+XFRbSKX6z48JvfM4Ktm3bhp96DWBQTd1/wC45pOboAldT89mFtmPLli106NAhoY2ysjL8qak4ohDN31AJryqUxBwQ5XxfIGD52VBWUNCoewj0Hk/2GVRRUYFVYZymQIXFeyccpaWl5KSm4gjT+xW074rQZ3kbdExCyA0G2VFYmLStEDauW8f5IjF/715RwYYNGxpdfzhW//wz50VZAD0ImLRq1V6xYcOGDRv/7bAJrY3/CfjcbkrQSNk2dMIfbfU9hHWopidAqQh+v3UKlJOXR0GS17fD4SAzMzOpczJzcoicsm1BNTpL0AnqYJTAhFAIeLxeyzb82dmkoWTkceBOU28AJQGlaEQkB41ovw10QQlBMVATDFpqlz8jg4yaGiLjajtR3dNNKJHoTL1GbAgh7U1Ldvx+PGj/5IZ9/xPwLErSAqifnIfq7oaTnRIg00LkFMDn8+FE/e1xNJKZj+qO9kYn4juB14H90LG6ACWNJRb9wZ+bSwpKWmtRkro/uhjTBvXhFJTAzkbJZ4hgV5m2eSzY8rvdpNTW7urrbagG6EKUrJ6GWSxBNVtfN9dxKhqtLTXlyi3cS76cHJKjVQ1RatHnAJo1a0YpSpAWAA+h+qZtI8rdgOrEXou2qwJo0aKFJRt+v59So6XqQPVhH0cXhTah4+FCfSEDJc/3w67FqjKXy3J7/Hl5WKPyu6MUa/dQOLxeL1uKixMXRBfAvBbvnXBkZmZSUFtLEL3/XgQeQ33ciy6olaO7Ty5H76WdTieZubkxakyMNp068ePixRwtwjfARvQ+6o4u1vzo8XB6mzaNrj8cXXr35usffuDICFL7NdC1a9e9YsOGDRs2/tthbzm28W+FQCDAnDlzOG3oUHq2bk3P1q059ZhjePfddwkEAo2u9+CBA3nf6SQPJQ6vxylbjBKys9CJzLraWrp3727Z1rGnn84LLlfiggYlwOdOJ0ceeaTlcwDOHDOGF8zfi9Dtqj1QAvgd8E+gH3AK8IUp9yJwynnnWbbR77DDaOZwcCbwIBoF8QO3oaS/DigDZqJbMWuAH9FI02wgNzOTrKysKDU3RM+uXXGjhLgWJZajgdbATegE9lHgMnRr5A1ov62D/2fvvMOjqrb3/5mS6cmkQhIIoYMCIqAUC0VF7L2B12vvDez6VeyKXuzlqliu6FWwV/RivyoiXFAERRApUgOBEEidJLN+f6w9JIRJcs4QuXp/8z7PeZKZObPX2Xuvc2avvfZ+X1YCa9xudh8wYIdyd7DTvz/tgH+Z1z8AI4AD0WBiNPBXNMt5Otp+0825c9GApJdFXxg4bBhFLhezgUfR9vgeOBPNvvRBl7o+AawC9kWzqn2A/1RV0bdv3xZt9Nx9dzxOJ2uoX/rdFc36rkN9uQYNlsqBUWgWvMS8XwdUuVz06NGjWTudO3TAD3yCLh0ejLbXz8A0dJnziWibPYNmOU9A2/V9c+wOlIqQm5vbrK1+AwfyUaNJFwE+B45AfWsQGlyubfTdJWhg1r59+2ZtxDBgwAA8TieXoQHrt9Rnk9eZowydxJmBZrnHAhkpKRQWFlqy4fV66V5QwBfoREAHYAIauI4B2gFZaFudh94/7VF/qQa+rKujX79+lmwNGjKEt307rj+pQZ8JXwDxFhUvBzY4HHTr1s2SnRiOPf10nmjwWtB7dw6aoW+Y43wCOPLUU22VDzpxkJ+Xx0Q0i/0kGszuAQxFfdGDTqQMBy4Bpnq9HGpxSXg8nHruudzpdtMDvV8nA08Bw9BJrk8iEY477riEy2+Ii6+6igd8PmY3eG8RcFMgwOU33tgqNpJIIokk/uexa7fy/j5IkkL9b+Dnn3+Wnh06yIBQSJ4BWWCOZ0H2Sk2VHgUFsnDhwoTK/vbbb6WzYTn+NyozsaAJEpajUA1HAbnZ5ZKLzjrLlq2qqirJCgRkoSmjGiVVOhHVGT0b5CvqtUgfAjlu1CjbdaqoqJCQyyWPoWRF94OUmDJjxD1lqNRILsgDIH6HwxabcklJifgcDslEyY3upHk5kJ9QBt0QStZ0y003WbIzdepUGZ6aKr1QGZ4MlLAoG5W9eR8l47nYlBsG2Q3kQlQTNcfnk8WLF7do56effpJ0j0f2Q2V7clC5mXiyR3UoY2pbVNLlHJCOHo8lsiYRkcWLF0vY5ZJ+KPGXFUKbN0zdDh8xwpKNiooKyQgExG/a5TRTp7tB1jcqewUqndIG1VxOBXGD9GjfvkXm2WeeeUZGpqRIP5Ts63GL9ZmJymOFUC3SM085pcU6VVZWSk4otE0G5keUjKoAZCIqDfSmqWsQJTqLmHOvcLvlaouyPTEM6NtXMo3PZaHMzwWNDp9p13TTP8OGDrVl49FHHpGjfD7JMW1/KErgdRuqqTwbJaobYup6C0oMdgXISIs6ziJKRlaQlSX/Me2xBeR0c/1Z5n4Kx+nDqxwOGZcAYVNJSYn4HQ75EeQ5VNM2C6SH+dvT3F+LQAIOhxQXF9u2ISIy9vLLJWh8dxzKmtzQzypM+xWCdEFZjhPVjC0uLpZBvXvLwS7Xds/p2LN8KkgPr1cuOOOMnWJSbojXX3tN2qalyaC0NNk/LU2ygkF58vHHW6XsJFofybFjEjEkfWHXI8lyHAdJR/zjYOnSpZKXni6TDBNxvOMZh0Py0tNlyZIltsuPRqMyoEePbVqT/zQDuz1RqZSQGYzlgxxnBi7rQXL9fpk/f75texMnTJDdzYCoA8gIM+B7Hw3YuoEchAbXmR6PzJ4927YNEZHjjz5a0lAG3k0gN5rBqsMMXq8EWYvqM2aDDBkwwFb5JSUl4jGD0ztbCF5ixzIz8MwEGX/jjZbsVFdXS144LLebgCJgBvu1ccovBzkBDcgCaPB28JAhlus0bMAAyTJ1+peF+vyIBjNBkLz09BaldGJYuHChhB0OS5q6DY87QIba6KerLrtM0ozftmF7yZx4x79MfYajQdOjjzzSoo3y8nLJDARkMBpk2anPO8b32tvw82vHjZPz3W5ZiE5sPMX2gUXs2ITKBh2ISghl+3zy66+/Wm673377TUIpKdsC1fbG3pUo8/EnKGt0CA1Aw+ZI9Xhk/fr1lu2UlpZKEGQkyN7oxExTbN5vmP4Zb3xu6tSplu2IiNx9xx1ysNstxcYfAuhE2pvo8+Yx9PkTRpmHV4Bkeb2yaNEiW3ZiuOfuuyWMPj+nUT/hVQfyIcge6ETArePHJ1T+pk2bJMPvlza0zE6+BqQ7SKHLZVvvVkSfQ/vuuaeMS0mJ62+xoxRkv0BArrXBGN8SNm/eLPfcc4/ccccdsnbt2lYrN4nWR3LsmEQMSV/Y9UgGtHGQdMQ/Dg4fNkzusSB1M9HplEP22y8hG//5z38kOxCQT83ALssMGpejmc1X0IzC5agm6MBAQG646qqEbEWjUfnrySdLkHrJm5VoJqYEDdTONYPnqVOmJGRDRGTonnvKS2jw3dMM7AeYAWRfM5DtYOr4MUiPdu1sZS4eevBByUF1RpvLzDY+HjPtm5+RYTmL8dB990k7t1vSQa5tofw6U9cASLrHI59//rnlOn388ceS6nTKRTbq8wRIpsMhj9nQhrz0vPPkGhs2Gg6W09xuWb16tSU7r776qvhA9jI+bMXG31Dt1QDIsmXLLNm56OyzJQCywWZ9osY3e3ToYLntioqKpGObNtIe1WlurvxKkN4gXVNSZJxFDdoYbrz2WtnN4ZB2aMC6O8SdgFhr7oFccz/t5nTKPXfdZas+PpDL0CCyuWBJ0Am3Pmimc7zNQLCqqkqG7bWXtEED8Y9NmXPRYHmtuX8uQYPaHKdT7rvnHls2GuLOW2+V/uhEU1P9Mwjk5uuvT6j8+ydOlF4ul1xl0d9+RCfTdu/QwXaW9qWXXpL9QyFLz7pikAyfT1atWpVQvRriqb//XbKCQdk/LU0OSEuTdL9f7rr11oSzzEn8vkiOHZOIIekLux5/ioA2EonIFVdcISeffLKMHj1alixZIsuXL5dTTjlFRo8eLePHj487OE4GtH9uLF26VLJ8viYHRI0HR9k+X0JZWhGRzz77TLKDQclEsweNy99sBq7tvV4Zd9FFOzWguOKSS2SsyyVRkOvNIGtPNNB7xwwqe/v98q9//Suh8n/44QfJ9/slAnIWuoyxA5qJKTb164lqhR5hBtG9QiH59NNPLZUfjUalY5s2koEuZ7YTxGxBg/U2TqdlLcWqqioJOJ3ix9oS3TloQNaroMBWu1VWVkq617ttSauVowwkzeWyHPyVlZVJ2OuVFTbbLXacBTL+hhss2erZpYscbPo+XkY73lGCTnrsCTLK4nL3O2+/XU5MsD5PgBxkY+msiMhrr70m2Rbr9C5IjtcrtbW1lsuvrq6WnNRUCRlfDUCz/bUQDRDD6OqAgqwsy/ZOHTNGDkAD4p8s1CeKBrPXgbQLhWy1m4jI7NmzJRXkLnQbxdHoctzDTb//3djYHSSckpLw0tlIJCLZgYDMb6E+i9Dgr6qqylb5dXV10qVtW0lHJ+Ws+tvBILkeT4v6yo2x/557yms27Fzk9crN//d/tmw0xjvvvCOFgcB2fvEbSJ9AQJ547LGdKjseFi9eLCcccogM79dPHn3ooWTQnACSY8ckYkj6wq7Hn0KH9osvvqC2tpYpU6Zw8cUX8+CDD3L33XczduxYXnrpJUSETz755L99mUm0MqZOmcLoujqs8F/6gDF1dbz80ksJ2Ro+fDi33HMPXdxuRsX5PIySEHXo0YP7H3sMh8MR56yWUVdXx/PPPcdldXW8gRK8LAa+QwlyzkJZPy+trGTSAw8kZOON115jdCRCBUoE9RNKznQMSjIzCiWGmokS2qwETi8v57UXX7RU/ubNm1m7cSNVKHlNQ9SgpC9zjd3GrM6pGL3OaJQZX32FFcyYMQNQMiErnNL9UUKdRatWUWqRaTVmZzevFzv0N0HgeI+H9957z9L58+bNo300ugNbrlWcDHz67ruWzi1etox04DTqNWJbQjqq+dsTmGexf7764IMd/MAqTgC+/e47W99565VXuABrdToUqItEWLp0qeXyf/rpJ9yRCHkoO+I+7Mhu3BA9gV4okVYuUFFWZtnel++9x94oqdFuFs53oARhG4G1ZWXU1tZashPDgxMnUoOSTD2Fsrr/AryH3rM3oERk1wDOmhrmz59vq/wYPvroIwqqqujdwnndge6RCNOmTbNV/tKlSyktKWEvlKjNKs4AciIRplm8hwCKiopYsHAhR9mxU13NK88/3/KJzeDem27i/oqK7fyiAHiqooJ7b7uNqA1N85awZcsWDtxnH/aePp3rvvuOv19/PZOeeKLlLyaRRBJJ/MHxhwpoO3XqRF1dHdFolLKyMtxuNz/++CMDBw4EYOjQodsGvUn876Bo5Uo61dRYPr9zTQ1FK1cmbG/z5s0c1MwgYSiwYf36Jj+3gi1btlBbU0Mn4GuU/TXLfDYIlTL5AZUAWZag1mDxmjV0qKtjOZCHDloHNzqnGzr47oIyZ7YXoXhtY27Y+CgtLcWLyrvEtC1/QxmO26FbD6lYAAAgAElEQVSMn39B2WELUQbaD1BZEozdamDzhg1YwcaNG3FGo/SydLaiC5DidLJpk3WhpI0bN5If5/1qlCl4FSrL0hj5VVWW7ZSWlpIpEvezWnQy4zdoUmIlE/VTK4hGo9Sgg+AYBPW7p1B5mKdRhuWGKDDnSRx91Hgo3bx5m+SPXWQA5ZGILabytcuXE+Neno9KsuyO+nohyjb7GNqGLiBfhHXr1lkuv6SkBB/aBgGUZbolDKRek9nvcFjuo5qqKgQNaK2iE6or7AZb9QL49aefyESfOR+hLNQpDcodibJG90WD5xUrVtgqP4ZVq1axu8WAq3c0ykqbz+2SkhKCLtd2vm0FBeikW0lRkeXvFBcXk+vxbGsnq3aKLfpAU5j9448cEuf9QcDGkhLLPmYF8+bNIz8S4ZpolFHAbRUVvDelOc7/JJJIIok/B/5QOrSBQIDVq1dz6KGHUlJSwhNPPMHs2bO3ZcmCwWCTwu8LFy60ba+qqiqh7yXRuiirro4bQDSFCqCiujrhvisvL2dtSgo0MZBfD/i83p3yjaqqKqrq6qhGB5XzUVmJcjTbt8y8XwK4nM6EbFVUV1MJpJlyytGMTMxOAA1wV6FSN2nm/5raWkv2NmzYQK0ILlS65CrgVeAUVP6jYUahApVCugaVzXgVDYTdWO+rDRs2UAe2NEjLgToRVq5cSVVVlaXvbNiwgTIzCBdUludGdILBjw7wy9Fg+To08+kEKl0uqrZssVSXoqIiKhu9Nw/N/n+JBmApaLvmof12BboCAbTtrPqF05RXaa77OVTHtAoN0qtNuW6gjanTKdTr0Dps+F/jFi5Gg8o30H7zoT53HZqVi6EacDscLFq0yPKqhzpgATrB9CtwDupjWag81C+oFMyN6MRKORr4Wa1LUVERtWi7RE1dWsJGc10AtdEoa9eutWTP4XTiIP5ESVOoQP2x1lxrU799ceFyUYbWKxfViJ6F+kg6mqU9D9iM+kBxcXFCz6CSkhJKHQ4QIYreS19QL3W0P7pSxIVOPGzevNmWnTVr1lATje5wL7WESrRfqyIRy/ZWrVpFuU1puCrA43bv1G9Fut/Pyq1baSyctQmoMc+2IhuBeXMoKytjaXU169DfhK/dbgLp6clxkE0kx45JxJD0hT8Qdu3K5+Zx1113ycSJE0VEZM2aNTJy5EgZOHDgts8/+ugjufXWW3f4XnIP7Z8b7777rgxMTbW8b2lIaqq8+eabCdtbuXKlZPh82yRuGh9/8fvl3gkTdrpeBw0aJLeD7IPKZvRGyVG6oOylZ4Oc6PMlbOvll1+WA0MhJScx+wDTQU4FGQvyV5QtNc3YWwEyOhCQB++/31L51dXV4nO7JQclHDqElve2RlEm0kyQjii77cMPP2zJ3ooVK8TrdEpnU85WdO9lf1NOW5ADQF5HGWI3oyy9WcGgrb2TS5culWyfT1aZvmiLMiVPRyVGngB5D2XW7WZs/wQyIDVVPvjgA8s2slJSpBqVlDmAevbcZQ3aqwbkLVSuJRXdCyooEdJJhx9uyVZbv19ORlmLOxof2AtkMsr6ugUlJHsUZYDNNJ93RyWquljcg3z2mDEywVzfVnRfZgAlOXoJJT+bgrIgh1FSsiXm/BkgPfLzLdmJ4cILL5RUU48tIFdTT8yUb+owDWQ1yMno/taVK1daLn/t2rUSSkmR9iizdiZKbPSyKT/FHB1QMqUtxobP+EwwJUVKSkos2erXo4dcaGyUmTZZgu71bEO9xM2H1BNGnQByDUjI4bDVbiIizz33nKSDjDFlDzY+/iC6LzcPpB/I/qbuW7ZssW1DRJ+lIadT/mb6piv6vNvXHN2NT94DkuZ0ytKlS22VX1paKiGPR3KJL63V1HE1yO5ut/z973+3bKu6ulrapKbKIht2ngA5duRIu822Ha4dN05O83p3IAq71u2W044/fqfKjoe7b71VMrxe6REKye6FhUlG5QSQHDsmEUPSF3Y9/hSkUI8++qg8+eSTIqIyESNGjJAzzjhDZs6cKSIiN910k7z//vs7fC8Z0P65UVtbK4XZ2TLLwgBiDkrGYlU6pSlceu65MjwQkKIGZdegLMqd2raVjRs37nS9/jJmjKShcjeNNUEXgJxpAgKrQVJjVFVVSXYoJDlmgP1ynEFfLGDqiAa9IRuDcBGRv550kgRRMhmrhEOCyp0EQDxOpy15k8OHDZMQyO0meMgx5WSbgbnf/J9HfeB0i0VpoIY4cOBAyQQ5Dw3CuphyU83R1gQa94Pch04I5Gdm2iLP2a9vX3nZBA7DaXkyYJqx8ypI95QU+fjjjy3ZufLKK6UtGmhloIF5cxMOL6DBdar5jlVd3RkzZkhHn082gnRCg6WXUSbtNDSYyUYD2UdBJpj354GMdrttTdx89dVXku33y7cg95p26YdqjX4N8hnKhB02vr0c5CKHQ/br108qKyst2zlyxAjJRycBskCcxu/SUBKlwgZt5UKD6Uzz/phjjrFs5+2335YwSs72gPG3WLkHoYRuBeY6giBvm748AWSkRU3ihli/fr2E0AmLeAFaHcgHKLNzd5ukag1RU1MjhZmZ0t34RG80cH7G9H8f01Y9QNqHwxKJRGzbOOOkk6Qnqv9q5dlTYfoy1eOR0tJSW7auu/JKGevxiKBs448af/aZvhqJku7Vmntpj1BIpk+fbrtODVFaWir9uneXnm637I9OMvRxu6VTbq6sWbNmp8puCitXrpR58+bZJulKQpEcOyYRQ9IXdj3+FAFtWVmZXHbZZTJ69Gg54YQT5J133pGlS5fKqaeeKieddJJcd911cTMxyYD2z49nnnpKugcCsq6Zgcp6kJ6BgEx64omdtldbWytXXXKJBD0e6Z6SIru7XJKRkiJD+vSxzGTbHB595BFpQ32GqqnjLZCgwyE//vijbRs1NTWSHQhIB1SKozk7JSC9UDmYsrIyyzaefvppyTODRKvBbOyYCNIlJ8dWnaZPny4eM4AMmeDhWjP4fgedBAhigmUQr8tlWd6mITq3aSNnoVq3mWgWri+IGw1qeppBeAbIKWhQm+5228oEv/LKK9IWzcpbzS59ZOrXITvbMvtobW2tBNHgzsqkkJi2jAVUVhGNRqVv587SHZWcugLNwE1G2cdjgdJ0VFJpBBrYpIOkeTyyYcMGy3Z6tG8vb6KavA2lZxofVSDnmz5cDXKIzycP3Hef5Tp9+OGH0s7jkXw0U5lh7O2HZjWHoBnHGLuxBw0C23g88vXXX1u2IyLSxuuVa4ydMBosbW1QlzpUI3h34wOnmPvA7u9UbW2tjBg4UM6jPtsbBfkPmgFuyOS8AaSbxyOPPPCALRsxXHLOOdLb7Za25to3gDyCZkgfQp/Zn6ATAX3dbjn3L3+xbWPWrFmS4/FIN3aUVIonr3OVacMLzjjDtq3ly5dLViAgr6ITJcegesRlqObxi6gs2kiQ+xwO6d2pU8IM0TE8OHGipPt8corLJY8avzjL4ZAMr1duuOqqnS4/idZHcuyYRAxJX9j1+FMEtIkiGdD+b+C2G2+UToHAdgNkMf+/ANI5EEhYy7Axtm7dKiP32Ue6B4NyB6qbeoTfL23DYdsD1caoqKiQoNMp8ywGF/eC7NG5s207L7/8sviJn4GJd6xFM5x/u/deyzZGH3WUTLRYfuNjCxpA21kGWlJSIj6HQ0Jo5qosTrkr0WxgAKQwK8u27MQPP/wgqWhQl4kuae6MBmYVaFb7XXRJ6wA0yPkbyG4gkyZNsmyntLRU/LQ8qdH4OBVk30GDLNtZsmSJpILc2qic1Wim+ww0IN/Y6PMzQPwOh60s1p133CHt0aWre5pBvoAUocFSzBdr0SXvJ6GB2ZABAyzb+Pjjj6VXMCir0IDuyxbaK2rarD/IVyDd8/MtBwF1dXWyf//+4jD93APNMv8VzcS9DjIazdjHsqpOkEOHDrXtdy+88IJ40UmEb821L0VXcFwH8rmpSyma2fSCjBw61JYNEZWB6ePxbFtR8RUa4HVDA7FMkOMa+MMikKxAQMrLy23Z+fXXXyXd65UskO9AnqV+y8ME04bp6LLcBaZdM71e+fnnn23X6cxTTpEebrfsAfIrqrfcH8SBZmOvRIPpq9HJqbz0dFvPnYaYPHmyBNEtB/H8rQZdnZDhdicsHxfDow89JN38fpls7qc26HL37uj2hwF+v/zf1VfvlI0kWh/JsWMSMSR9YdcjGdDGQdIR/3j44IMP5OB99pEcv18OCIflwHBYcnw+GTl4cNzl5oli9FFHyRle7w7LaKeBtElNlaKiooTLfvjhh2V/i8GLoFmaAMiKFSts2dmtUyc50IYdMQOxvHDY0mB83bp1kpqSsi1oSeQ41+GwrKcqIvLQgw9KjhnYNadL/Atsy0p+9dVXttpt1IgRMg5kILqkuT3xM9wV5pweZtD8DEi3tm0t27nlllts+UHsmAMStpENvvSCCyTYqA7fmrpdCPK0CTLas31wPQcNOB6xuMdZROSAQYNkIpqljE3Y3GnKORAN/E5EM6eVph/fQAMZq/U5btQoeQwNJA+12Gax4HcVSJ9gUD766CPLdZo8ebKkUr/EPZ4+9ZtoljGABqTvvPOO5fJjiE1wXGPKnGr86hKQW9Ag5gw06zjT+PbkyZNt2zlk333lH8bGT2gg+Sb12dpykEvR7HMsw3lgSoo8++yztuxcM3asDHE65WJ0CXg7dpxcW4IGmB+CjAMZ4nDI2AsvtF2nSCQiJxx+uHRNSZGg8eUP0ImTJcZX0tBJp7z0dPnhhx9s24jhnrvuktEpKc36WwSkg88ns2bNSthOWVmZZAYC8qK5T2La5FF0cqMADWozfL6EVqH8t/Hiiy9Kjtcr6ehy89jWsf8FJMeOScSQ9IVdj2RAGwdJR/zjYtmyZTJ9+nSZPn26bSKRlrBixQrJ8Hq3W+7X8DjT75e777gj4fK75OTImxYH4rHjbJDLL73Uso2ioiJJp55EyOrxrRn4LViwoEUbU6ZMkUNaGNi1dPwbZO/u3S3Xa/eCAgmC3Gyh7EPRIOSsU06xXL6ISKrTKR9TT550fzM2pplAow26PNwDsnnzZkt2dsvLk1cSbLfOINOmTbNkp01amhzR4LtRNHv1UqMy70Yzcw3f6w3S32L/VFVVicfhkH+iS3LFDLw7ouRTggayh6OZYUEzj1eiGfUvvviiRRvRaFS8brdsRoPLf9los8NATjf1vOyCCyzVSUSksF07SUOXFo9ppvwj0QkOP8gePXtaLj+GO++8U4IoKdgWNFPacBVHOcgeaGATRbO0eenptmysX79e0lJStm0ROLtBXzQ8omhGMNa+b4GMsJFFFxHJC4clB2Sh6fNnm2i3f6KrLZaYOmcGArbsxFBXVycT77lHAmigHq8+B+y3n/z2228JlR9D57Ztt2XQmzvucjjk7DFjErbz9NNPy+F+vww3bdS4/M/QybRz3G65bfz4narTrsaMGTMk5HDIdaYeJ4Kku1yWtx380ZEcOyYRQ9IXdj2aivn+UDq0SSQRQ8eOHRk5ciQjR46kU6dOrVr2119/zYEezzY9ycY4rrKSz997L+HyN5eWbidpYwV9gYXz5lk+v6ioiCjbS6NYQXdUQsWKruWmTZvItSlj0RhtUC1Fq1i+di0B4EAL545CtSZ//flnW9dUEY1ShUqiFAGHt2BjKSpJ8xsqfVRcbEXgBbZu2UKhrSurRwdg6dKlls4traigS4PXa9BrPbnReRcD71KvEwzQESi22D8bN27EL8JvqAYsqDzThaj0EIAX+D/zPua8n1H9VSs+V1FRgQMIo9Ive1q6MsUgYIm5lk02dFvXFRWRgcofHd3MecegPpMNLEtAt/XLL77Ah7b5p8AAYA/0fiwzZZ8PvIlK6QwCSrc0pVQcH+vWraOty4XfvP6IHf0AU/6JqMwOqF71Gov61KDax0VbtrAV6Al8BhzbxLnHopq3nVHJo9LKSiKRiGVbMTidTgYOGUKvtLQdnq8O4AKgIDeXggK7qrX1qKqqYlVxMXtbOHeoCD9+913CtubNmsXwykq+Bk6I8/kw9LnTt7aWed98k7Cd/waefOIJeohwNzAc+CdQW1fHtGnT/rsXlkQSSfzP4g+lQ5tEErsCTqeTGnSw8Ao6CK5BB6rHmv9dLlfC5TsAsfkdsWnTaXQt49kpRoOaNqgGZWM7DvP9luBwOGzXozEEcFrUHcWcK9RrfQJ8DyxEdVsHALHpjdg5Lgt1aQhHoyNWzq/AHPO6Fxps1DX4TsyKlbaDnWs/O/7Q2A/c6HXXUX/NoNqtbnN+Q1jtH6fTqf1JfVDsBhYDtwKlqPZxCvU/LA3Pt9JuTqcTEYlbr5YQNbbEoq0YYnYcqOZrU4h9JmBZS7ch3O76n9sNqI5uDtpusT7rjd6zgtbHrpVYH8XgQp9n8VBjPgf792ms/jFbTppuu1rq/VAAEUmo/UDviRqJ7xURwJ2SklC5MTgcjm3+1xKi2H/2NESsr2J+52n0uaB9ZPV5/UeCOyWFKurvqxrUvxveA0kkkUQSrYk/11MyiSRaAT179uTT8nIKgWlAKioyvw6dFR/rdNKpb9+Ey8/OzqbhvL0AM4C7gRuBB4Dljb7zNbDnoEGWbeTlaU7sB/N6C5pxyUAzVPuhWb504DA0yI2d7wXat29vqR4rdyKwBw2ss7OyLJ/frbCQCuBtNOOSg9bleuAKYHcgH7gXzWR5gZ42+yrkcuFBJzRygCuBrmgwcS1wE5pZbI+2aTcgiAbSW4CcnBxLdsKZmfzS6L2YL9wJ3AA8BTTOjwo6ydKjRw9LdjJTU/mpweu2pj5HoJn/zuhEwLFoNjoWSgiwCGjbpo01O5mZRBwOOgIfA8+iGd8PgQq0X1KAd9Cs9njz2R5o0GvF5/x+P26Xiw1oNtxOXupztA9/czjIzs+3/L1OhYUUowHRK2h2+3bgTOAs9L5dA0xFfWY90Gs3u2sw4OBDDqEaOAr150OBy4BTgeOAsWiGeCnQB82eZmdn27KRn59PUTRKLK97JPB8nPNqgJfMtQAsAAoLra8ncDgcdMjOJhudBDoMeBmoQvvhbTRrW2neP9TY8ANtw2FSEgw89957bza43Xwbpz7PhkIce+qpCZUbg9frpXtBAV9YOPdfTif99tknYVuDhg5lWiDASGBynM/fQ59BX6WkMOhAK2tW/ji44oorWOlwcDrwIuofQZ+PI4888r98ZUkkkcT/LHbluuffC8k9tElYxYIFC6QgK0vGORyyKs6+pSqzn6md3y8PTpyYkI3JkydLvwZ70/ZE9xBehTLRnoeSwRxh9oJtMvvy7BJRDejVSwahmpVBVB7mTZSFU1CCkQ9BDkDJbJ5EdSk75uZaKr+kpETSPJ64hEkLUObUTJQI6MYm9pmNdjpt6Y8+/fTTko7uje2Bkr10RZllXeje0FOMzYBpt++++85Wux1/9NFyLshQYycf3Xu5r3kdQCV8zkRJZtKMvYdA+nTsaNnOgw8+KP0btMVklKAnzRwB034pIAfDNsmqf4PkeL2WWXRvuPZaCaF7M8tBTkYJktrANlZdD6rd6wMZi5LpfAmS5XDIc889Z7lORx98sNxs/Hc3lNjoSpSkJxXd93oSSgR1hHnvWZDcUMhyfU47/ni5x+GQ82EHUq0fUS3a11E24Nj7S4wvbATpEgjIjBkzLNfpo48+klTz/UxzL7Uz7dcGJeeJaSH7TZ0SIbgpLi6WELqP+XxjJ3bE+ijN1PluY/NhG4RdMZxw6KHyqGmX5SiZ1SMgP4PMNm14IrrvNUYUNcTjkVdeecWWndvGj5dBLpecjspNpaH70jsZ3+hsXodB3kOfe0OcTrnx2mtt16khXpk6VXL9fpkE8hvIFyAjAwE54oADbMlqNYVHH3lEjvT5tpM82sr2zPvlIHl+f0JyazFUVVVJm7Q0edH41uOm3GrYRhQ1GSTd55Pi4uKdrteuxmeffSadcnKkTUqK9O7cudW5MP6bSI4dk4gh6Qu7HklSqDhIOqJ9LF26VB555BF5/vnnpbq6+r99ObawevVqKcjKkslmUDIHZRXNMYOxfcwAogbVauwYCMjkf/zDtp1IJCKpLpeMNYPhD9DgshKVUqkzA5cHzaDlryBD+va1bef999+XFDPwfYL4AWXseNUMxl0gTz75pGUbZ5966nZyMJVmgOxDWW3PN9efaQau9zU4txh7+qMiIitXrpQQyNFoEHkmGqQ/j0o3vYySQfVECZ3SXC7bOo1Lly4VH0ghyvS6Bxooj0QZWduDDEOJj9qbACTT/P/qq69athOJRCTN5ZIfUDmRNNN296JyLUUoqdIx1Ac1v6HkQxdfdJFlO6tXr5ZUp1PGmvq0QQOyVHPtl1JPoJVrjpNAjgcJeTxSUVFh2dacOXMkjJIjTTJlnoaSjRWhQdONpr3OA7nYXM9dd95p2cbMmTOlUyAgG027vGX6Pc34WKr560MDp43ohMD+6AROv65dbUnq1NXVic/jEb+5X30ghxhfvs/4uc/4RhAkLRi0LdkjIjL66KPlOIdD9jH3bFtTpwxzxILpWGB4H0j7zEzZuHGjLTuffPKJdPV6twVgl1Cvr5uHTnLko4RngurT5oXDEolEbNlZs2aNpHk8kmH8rY+59hPRSY6Tzes+xl46SLrXu9OkTSIi//73v+XIESMkPz1d+nbqJA/cd1+r/R5t3bpVenXsKDc4HHKzuV88qEZ1L5TtfJTXK2faJKOLh6lTpkg7v19eRCeAPOgE1wjzvOvq98tD99/fCrWqR11dncyZM0e++OKLP2Wg/EdAcuyYRAxJX9j1SAa0cZB0ROvYuHGj9O/WTXxmgFIIkupwyEU22ET/27j47LPlKrdbxAxKYsHFb2iW9G00S3cImqmdB5KTmiqVlZW2bd12222SgWbNfjLt5TFH0NipNoP1ACTki3V1dZIKchf1QeQHaCCWD7I3GsjGMg3PmEGtnQBm7ty5kuvxSAkaiGeggWR3U1a6OUJoltOPZoME5AaQvxx3nK067d2vn+yHTjJMRYO7IJql7WLa6jI0g9XdDKSvTSDj075tW+lofPlwE0zsa9qtDTq5kY8y5+ah2dyAy2U7kLn0wgslDw3CRtC0FNHHpp4ZIKkul2zatMmWnWMOOUSCaJCUh07UlDSysdb4dj71Ge6rLr/clp2ff/5Z0tAAMx3k+ybqU4xm8MeCDAZ5/PHHLduIRqMyoEcPmYRmY13Gv7qjmasVIPPRoCmEBpu5aGA7xO+XSU89ZatOMXvtjI+9YPrba44D0VUb7c0xzCYbsIjIokWLpI3fL+eado9lZv3oRMqxsb437Zph+mmMzycTbehGx+pzwmGHydEulxyOPnvehW0SZSWornIQ5AGQfI9HXn7pJdt1EhEZf/31koZOMJ0Msj6OH5xm+i4V5Npx4xKy0xizZs2SMUcfLT3y82XfPn3kqSeflJqamlYpW0T9PN3tllGohFK5OV5HM8/d27WTqqqqVrE1dcoUyQwEJMvh2LZ6I9PhkFSPRx5/5JFWsRHDG6+/Lt3y8qR7KCT7hsMS9nrlrFNOka1bt7aqnV2NpUuXyltvvSXz5s3bJfaSY8ckYkj6wq5HMqCNg6QjWkNdXZ0UZGTI0WgWJjZY+cYM/i8877xWt7l48WK5Zfx4ufmmm2TRokU7Xd6WLVskw++XlSBzzYB+cZyBeA2a1brCvD44FJIXXnjBtr0jhg+XZ9FMXAjVA/3UDCz/ZQb5+cbGiX6/PPzQQ7ZtTJs2TVLR4FtQeY5cEwT8hAaEndAsWWwJci7Igw8+aMvOpeedJ/u63XI0GkDGsrET0eWLH1K/fPc0MyB/CSQ/Pd1WNqayslJC6LLo29GAPBcNwqaiS1f3NEHFhWiGcQxIG5/PbtNJ+1BIzkQzmjmmL65EM4zL0YmOHDN4PdjYSXU4bGeBotGopLlckgFSFsffGh6PmEDmXpsBjIjKOHnM94+hfhKj8REBGYAGamG323ZW7pLzzpMrUKme91qoz1o0aHoJpE9hoS07CxYskDahkLyBBqz7Gz//Ep0omYAGsP8xfrcbyEkejxxz8MG2l53OnDlTcj0eCYA8Z3xuqmmrKjTAjS3/9IFkezyWZK8aYtxFF8kVbrcETFlB0w9noYGeF53wOMfUx2/68h6QLrm5tlchVFRUSJ+ePSUXDSrj9c90Y+fB++6zVXZDTJ06VTo6nTISdtD0jh116MRQZ4cjoWdpY7z+2mvSxu+Xk8yz4niQQX6/HDtqVKssORYROXbUKDkNXcp+sOmfILoiZR1IN5BnnnmmVWx9++23EnY6ZW90JcrL6DaRNIdD3nrrrVaxISLy9ltvSZ7fL583eD4Ug5zh9cqwvfay7WN/BNTU1Mg5Y8ZIls8nR6SlSUEgIAcNGSIlJSW/q93k2DGJGJK+sOuRDGjjIOmI1vD4449LvhngNR6sfJPgQL85zJ8/X3JCIbnS6ZSrnE7JCYXk+++/36kyn3nmGTk2GBRBl7FOaGYg/hsatG1Fl7sO69fPlq3ly5dLls8n5WhQdhKqdZoLMgrdL/WZGdg+i+4B262gwHadOublyThzzavNgKvxvuBNZmA837y+F6RtMGjLTm1trZx63HESRve0Bk1g0XgiYC9jKwiS6vXa7rMrr7xSeqIB8cto8Hwu2wdnEXS5awDkNTQzFACZNWuWZTtffvmlhNClxiPQzOxNcfzgJTSD28PUqyfIHTb1iefPny8hmt5j3PAoM23Xp0sXWzZERJ5//nnJN377Qwt23kUnBbKwpg0bQ01NjYS9XnnV9E2dhTqdBHI9SL7bbdsfZsyYIT6XSwIgv6BBZh7ILehqgG7Gvy9HA7NDhg6V8vJyu00np594orRFJ0k6m/uxcT3eM75wqrmPLznnHMvlR6NRyQgE5Dbjq7H902eimdl1aOD8ADpRMBidMMpG98X3TU211U8xdHMe3joAACAASURBVM/NlUkt9M++INdff73tsmMYPmCAFKJL55uzM8P43JDevRO2JaL7TtumpcnJpp2eAxmHZqH7BALy+uuv71T5IiIbNmyQoNO5LXC91/TPeuPPZ5l7qHte3k7bEhHpWVgoI9h+QiCKTqLlpqUltLy9MaLRqPTu2DGurnMtSL9QSD744INWqE09SktL5bhRo6QwK0suPffcVptsaIi/TZggIwKBbZOFtSDnezzy1xNOaHVbDZEcOyYRQ9IXdj2SOrRJJIznHn+cC1AG08YYDGSK8PLLL7eavXvGj+e68nImRqP8LRrl/8rKmHDjjTtV5q+//EL/8nJAmY1HN3NuAcoyOgPoD/y6fLktWz/88AODvF4CKLvruShz7myU9fVh8/p8YAKwP7Bk9Wqqq6tt2SnbsIFh5v/XUEbTdo3OyUCZWmNMp/sCkYoKW3ZcLheTX32VauArlDV3v0bnuIFxqDTDAUBeYSF9bbIPz5w5kx4oK+4nKKPsDWwvXZICXIMyORcBq1D24c8//9yyna+++ordUH3UmcB3wKVxzjvJ2FiPSqnsDsydO9dOlZg7dy5emtc3jSGIao/a9TeABd9/TyXK2N2nhXMPRWVj/MCCBQss29i0aROOujoWoOy4Vn48TgK+AHpFo/z666+WbQEMGTKENL+fDihr800oC/HNwD+Agebv6YAPGHvDDQQCAVs2AH6YM4dalBHai96PjXEYKq+zP+rj875tzLPbNMrKyojU1LAIlclxAkPRe/YplJXai7IcF6I+EDXvLQR6ifDbb7/ZqpOIsHTdurgatA1xJvDhq6+2cFbTmD1/PlvR+jSHwWi7zVm4MGFboPd5oQjvo8/SM4D7Ua3T3SoqmPr00ztVfszGgGiU74Es4Gq0L3KAJ1CN5f2BlevWUWJDYzseSkpKWLdiBddRL6EE+sy7HqjYsoWFO9lmAL/88gul69czMs5nLuCMsjJemxyPazlx3H7jjQQ++4yPNm5k9ksvteoYIYZ/PP44d1VUEDSvXcDdkQivv/MOlZWVrW4viSSS+OMiKQqWRIuIVFaS0cznYWDLli3NnGEPWzdvpkBk2+sOwMelpTtVZk11NWnm/2rY9gPYFELmvBQgUtucOmUcWzU1pJjrjw1MvWgQBjo4L0V1b6vRwUuK00kkEsHr9Vq2IyLbJhm2oEHXJuA/5nUI6IcOmGPyMR7zPbtwOp3UoXqJTYnwZKGDdes12B6RSASX+X4lKgESz1Y2IOZzD/oQKzeTFVZQXV2N23y30pSVHuc8l3l/q7HhAipsTjpEIhEE623iA+qi0RbPa4ya6mqi5vugdfoMDdbLUAmc/YC90Xq4zTmRSMS6jZoa3KjP+i1+x4tKqqTYtBWDiBBAJx42oNJDm9G+C6OTDfug91lVVZXt8gEiNTWqj4pOAMUmUKrM/17zN93YEfMdq6ipqSHF6aQKbXtB+yPKjn7X1nwe00euBVJEEmq7OlrupyBQm0DZMdTW1RGmZb1cB+qbNXV1iCSuQ1teXk5aNEoItj3PQSfyltI6v0ORSIQQ6mdtG32WhvZhNeqDdichG6OyshIcDrLiPJOz0P6382xrzk7Y7W6ynzKAiq1bd9pOQ6xfu5a9IhG6AbvX1LB+/fpWLR+gdOtWGouopQEOEaqqqvD7rT6pkkgiiT87khnaJFrEXsOH80YTn61Hs5BHHHFEq9k7+tRTuTkQYC46IL8pEODondQXzM7NZZXRPuyDZo3molnSoWgG4WhUM3EL8C3QC1gNZKfHC3eaRrt27VgcjSJoxuwTdOCYC3QEDkSD2n+imYWVQEpKCqFQyJYdl9e7Tc82D9Uy7Ihmem4HrgK6oxmMDua85WjGNREEgB7ALFSr8w3gSTT7uxB4HdXynAPstddetstv3749m4AfUd3UfLQ/ngIuR/Vi30D1M8vQbFYU1Q/u2bOnZTudOnViFRqo7Ib2841oXxSiGfq90TYsQYPeVaiWb74NfVOAgoICAOaZ13PRDHZnY2c3VK81ggYy84H0YEvTLTsit6CAIOqvE4CewNloFvAjNLN5lKnXBOpnMmN6xlaQkZHB1miUrrCDDqgA5Wh/NMQcNIO+xuGwrakK0LZDB34BxqAawS+h+sOvAM8AbYCRxq4dH2iI/Px8XKhPzUf1j7PRgXFMo/oC1Oc3oMFZvulXKwiHw5TX1tIB1et1oZMNPVCt4FHACOB4dPXIBuonwrKAdS4XmZmZturkcDjI9niYYV6vQu/PF4APUJ/GXEfnPi3l9JtG+5wcytG2aQ5r0cm2dpmZCQezAIMHD2Z2TQ05wF1oYDkH1UTe4vUy9LDDEi47hl69ejHb4WAY+juxqMFnL6DP7k2AIyUlIZ9uiNzcXNw+H6/E+exVwON00qtXr52yAdCtWzfW1tXtoH8ew7RAgMEHHbTTdhrikmuu4c5QiL3T0vg0I4MxY8a0avmg2s7PNfo9ex3YvWtXMjKam4ZPIokk/uewyxY9/45I7qH9fbFx40YJOhwypdHemwhKQLNn166tai8ajcoDf/ubdMvLk265uTJxwoSd3ke0ePFiaeP3SxUqhxHTl7zD7P+agTKZHoDul+xj6niJ1yvjbe4xi0aj0qNdO/kMlYMJoqQ1Z6N7QhvK3PwfyI1ut1xy7rm263TFFVds2+OVg+5hDZs+ORfkBFOXAejew2tR9t6jjz7ati0RkS6dO8v+Zv+fz+zvOxWV2InJqexh/iayp3rhwoXio14Sxm+O2F7X4WaPYcjU9wZTxzSwRWhSU1MjaU6njGnQP12NjV4oO+9QY9dn3htp/rerpRiJRMTvdEpPlEHXba7dY+rhNa/9pi7p2JO4iWH58uXiNd/vZfw7ZOrmpZ4NuBDdJxoG8bvdttlNDxo0SJ40ffwryGPGl93GToqxdT5Ihanb6yCZfr9tVtiZM2dKlt8vT6Aanb3QfZj7onvT01Bm3Y9RJuKD99svIebZyZMnS0e3W7LM/XIVSuYWNcdiVPoobI5Cj0fefPNNWzYOHzZM7jL94zPXnopK6rxq2ug+49+p1DMgX4/qkG7evNl2vc4+6yzZG92nm46SGx1n7q9slCzODztFunfnbbfJHi6XXGfa6iNjb7h5Lnxg3r8ZpK/TKeNvuCFhWzGcNXq0FLhcEqZe57YAJCctzZZEWHPo2a6d/BMl2EtHuQMOQZ+j34P8BeTi889vFVt33n67BFGd65gO7fOx++iss1rFhojIdePGyWF+/3Z6urH94W3S0n4XIqWioiL56quvZMuWLa1etojIihUrpCA7W87w+eRlkKtTUiQ7GJSvv/76d7EXQ3LsmEQMSV/Y9UiSQsVB0hGtY+rUqRJ0OGQ4yKMoC207kIL0dNs6if8tHDxkiNyDYfoFeQcN9lLRIK0ADZJmmYHl3SCZPp+sXLnStq3777tPMlFSkeNM+VlmIBnTIz0nZtvplB9//NG2jZqaGvGbQX42Kt+zsdFgZQvIw+bzrmYAm2h/ffLJJxJA9UWXowRUH6MapJUgU0wdC3eCLKV9eroca9olpqnqQ4mZupr/26EETako++0Bw4fbtnPEoYdKPzNoHGL6+x6Q2SgL9pMgfdHgtg0aQPW2ydQbwxl/+cs21tqRps1iRFfrQe40/ZOKBoaJBC/V1dWSFwrJ3tQHQ3moduoglNW7AA2kveiETa+OHW1PFL3//vvSy+XaFgzFgq9zUdbra017pZnPe6FkS9fYlGtZtmyZ5KalyWumzQajwdJ/UCKgKWjQOdH43D9Ajk5JkdOOP96WHRFlBE5zuWQwyGaaJjYqRlm2M71e2+zQ77//vuyVmip7mGfBDSghXC8QJypN1Ma032vUMx9f53TKeaedZrtOIiLPPP20pKKTDlsa1eUXdIItw+OxPUnTEOvWrZM0r1fSzfUXmvvoRVQaqDM6qREGCXu9CT1LG+Kf//ynhJ1OyUYnA18w9Ytp+x48fHiryPd88803kupyyVTznPs7OuG5AdWUbpeR0Wq/e9FoVMZdeqmEnU5JQSeF0h0OOfXEE1uVSCkSicgxo0ZJZkqK9EB/m7o6nZIZDMo333zTanZ2NTZs2CB333GHnHTIIXLtuHE75c9WkRw7JhFD0hd2PZIBbRwkHdEeNm7cKGeffbb07dxZ9urdWx5//PHfhep/7ty5cspRR0m63y/pfr+cdPjhCfdxQ0yfPl1CqB7rGZhsmBkYr0cZjfdCA8QfzEDskBEjErJ18PDh0h0NxFKpz8h2NQOvmH7ryWhQNWnSJNs2fv31Vwk5nZIDcdkrGx4zzcA/3eGwxQgcQ0VFheSlpclEM8A7xtRpBBr0dTaD2JVmYDt1yhTbNkREXn/9dQlhdF/RSYViNEv2GxpIn2+CqFhwkMgg+ZtvvhEfOqFxLsrS3LjNomZQXmj67r4E5U1yQyHJQFlsm+qfdcY3giCPJKA9+fhjj0kvl0uC6GTJ3rCdPEctysza1fSbF6SDxyPvv/++LTu1tbWye2GhZBu/vZQdtXXr0KAzYI6wx2NLvklENaOvdjjkRONr801/Z6ESS+3QgPmyBvfqeyB5Pp/Mnz/flq3nnntO+nq92+qx0tyXmeY4zfSPoAFvT59PXn31VVs2amtrpWt+vrQzz5wj0Yz9yyiDbtTco0eZun2ETgpkJcAWLqJM3tler8w3Zb+NTqwNRTOzP5r63AfSo317KSsrs20jhnvvuUcCaHD5E8o6fDTKPj0fzUAHQG69+eaEbYiIvPHGGxJCs73x7tdvjX+M2HffVmEG/vrrryXs90uY+kmHNJCeHTvKunXrdrr8hpg7d67079VLwg6HhEF6dOwon332Wava+PLLLyUjEJBODof4zDOtDUim2y1nnHzy78JC/L+K5NgxiRiSvrDrkQxo4yDpiPaxceNGmTZtmvz73//+XX4Ap0+fLjmBgDzgcMhaM5B8yOGQnEBAPvzww50q+/XXX5eBXq88hGasVsYZFNWhS4L7oFm6IxMIaEtKSiRoBuKp5pjSYBC2GeQ6834amqntnJ1t2841Y8fKQIdDrm4UGF2LZrUuRwPA2Gd/M4HOGSedZNvWM888I/uhwWUXM6iMSSVE0SXbHdHJgukg7cPhhAaV77//vuSbAfA7aDazO2ZJIbrcdBEqs5NlgppElhlee+WVsi/IQdTLz0xDNS2PQDN+sfcvRpeiHzZ0qG07b7zxhgRATonja42P5abehenptmxEo1HpXVgoeWigOoCmNW+L0AA9Bc1AH5FAdvvdd98VPzopFCv3G3RZ8NsN2u0fxr8PPfRQW+Vv3bpVMvx+mW4G3EvQwDIDleyZY3zscOMTp4G8gmZxb3Q45CIbyzSj0ajs2aWLfGiuea655gLjY/+HZrrDIAvNOa+CDLUp5SUi8sQTT0gXU2bfZvroejRzez3IfgMG2LYjoqtRYj58Ovo8uxhkLDqBk4NmggXkILc7oQm1GLrn5ckk0985IBeYa7/I9N9TqIZvx+zshAPNaDQqbQMBubRBO61CJ2lmUT9xM9c8E1ojGDz0gAOkHchb6LO7FF0WHAR5+OGHd7r8GD788ENJRVdSPIdODB6EThg9/fTTrWJj+fLlku73SwaabY753mx0eXiB0ynXX3FFq9j6/wHJsWMSMSR9YdcjGdDGQdIR7WH+/PmSn5EhB4XD0isUkkOHDrW99K451NbWSmFOjnwSZ5D3GUhBVtZOLSc7cOBAeckM6F9pJrAoN4OWmeiS4xUrVtiyc+GFF8qe6PLYzAYDx8bHGWbwFTt39uzZlm1UVVVJdjAomSDLTHmb0EzpRWhwdq0ZjMcC941oVjjN67W9XK5zdra8hwayZzdRn/lmAFuBZpm+/PJLWzZERPbebTfpjy4D/gVdihvbh1cD8ojpv1I08NgP5AKb+48jkYhk+HzSEw2MxAy6O6EB+VQ0Ux/T+F2GBs9Bh0PWrFljy1bfrl0lDDKvGX9reByOBpszZsywbOPLL7+UAq9XAtRn95qzMcm0oRsk3eOR5cuX26pTz27dxNfAr+5DVzWcC9IPnRSoM0ceSMDhsFX+pEmT5AivV85H9XsvNX39TaN6RNHJpzSQBegk1XSQDL/fsh7tzJkzpUswuC0Iz0UnL6oa2KlAg+VC8zoCku/3284EH7LffvKY8aU5zfRPLfUZ59SUFNv7D3/55RfJ8nikEs0A90f3f+6NTp7loUF1Bjq59gFIv65dEwo258yZIzkOhyynfsIhB+RQ8ywYb+q7xLStHb9uiPfee0/8IGtNG31sng2HoBNp51Mf1B4KMrh//4TsxDB79mzxo/rejfvnLZCw09kqq5Oi0ahk+3wymh11na80dhLZF94YV19+uRSYZ1vj+lSgK4lCHs/vttf1fw3JsWMSMSR9YdcjqUObxE7j4r/+lVs2b+aj0lK+Lyuj9j//4elW0P2L4fPPPye7qooD4nw2HMiLRPj0008TLv+ruXPZG2VmPqaZ8wKoTu3DwPCUFGbOnGnLzpcffsjeqGyOsxlbV6Nssz+g8jpTpkyxbOO3337DE43SCWU2BtXkHAw8hmqNTgBONq8BMlGJk1yn05a2YXl5OSuLizkEZfm8pInzeptjOspK+8knn1i2EcPPixaxCrgQZVA+BzgEZZZ1G9vdUTbYv6Lsql9+8IEtG8uXLyelupoNKON0FLgFZc89C9VOnY6253q0fXsCnUSYPXu2PVtLlxJGtXWt4ExU7/KVV+LxnsbH999/T35NDS7qdYCbw2iUGTodZb+eP3++ZVsAK3/5hd5Ae1PO7cA3KBv1TGAF8Dbq++cANWJPdmbhvHkMq67mI9R/n0f1oAc3Os+BatJGgSkoi/MCVM5n9erVlmx9++23jKqtxYmy2ZYDf2N7mSU/ei+VYBjJgYOcTmbNmmW5TgAzZ8+mEGVP7t/MeS6UofoVoDAa5YcffrBl5/PPP+egujp8KPvvEJRd+RtgEqol/QgwzNg4GFi0fHlCkjf/eO45ThPhJZQl/kHUB6ahutuPos+/yahvPztpkm0bAM889RSDUKZ4UO3hKShj8wLgS/SexdhZ/P33CdmJYfxNN3ESyrTeGEcBoWiUF198cadsgGpvl1VVcRc7Sk7cBESiUV7dCZ3gGF74xz8Q4IQ4n/mBi4A20SjTpk3baVtJJJFEEv8NJAPaJCxj2YoVHCgCaHAxrKKC5b/+2mrlr1u3jm7NfN5NhKKiooTKrqurI1JbyxZ0wJvSwvkdUGmG1GjUtg5gpKJi2/956AA1HjqjA00HGvzaGVCWl5fjdTgIN3hvMTp4bYjB1GvQgg6mU7CnbVhWVoYPrcd6VIalKXREZUcygI0J6A5GjNxRW1RiqG+cc/Y0n7VDNU6rKyvjnNU0ysvL8ZhrdKJBTAnbB50ZaD2Xm9eZaJBj1xdqo9Ht9DJbQjrqD6U2dJfLy8txilCLytg4Ub96HrgClaa6CpXwqUElpHxoIOgWsV2nKGzTflyNSh21N689wCDqZVxy0GeFLd/esoUg2i9pqIxWU4I8nVAJmg2oxE05EHQ4LNepvLyckNGUXYu2225xzuuFtl3s6ROqrbXdbhU1NdSgkkAtoQD1yRD2fa6srIx0o2W8FvWnIdQ/hzqba8gznzuBkMuVkN5pSXExbVA/yEGfm53NZ7H/s4ydNsDm4mLbNgC2lJRsa7caU94I8zqIPueWm9dZQDQBLeeGKF69mt5NfOZAn3NLly7dKRsAK1eupI76ScmGCKPPodawU1pRQWeaHvB1Bdx1dZSUlOy0rSSSSCKJ/waSAW0SlrHXgAH83e1GgI3A1GCQvQYNarXyu3fvzuxodActS9BB9GxUTy8RuFwugl4vacBmICYhX4UGgj+iOqMxzEMHZBtcLsLhMHbgC4eJotmy5cZGPMxFdS4d6IA8J6exRHzTSEtLo7yujnUN3hsM/B3Nzu6L6lv+DWioCFtkrictzXqYFQ6HqUQDh86oNnAN8DkaJL2H6lyK+ayTeZ3Xvn284pqF3+3GiQbh/VAtxsuBw9AM0Hg0K7Mn8BM6mA3aqAtAeno6ZWhwXo0GDR2BDxucswRYRn1wsxINduz6gsflYj3aNlawBhMw2vCFcDhMrcOBB82OjkUDon+iGaY90WDjfjT4vBrVvXUA1Q6HLV8A/dFYZv7vgvZ1bA3DejQ7F5uIWILeB3Y0IdOysihFg/t1aFbumybOnYsO/LugQXQGUCpiuU7hcJiNXs3HdkX96UtU4/Ycc0wG/o1OBHU039uYkmLbF1K93m191FK4tQB9/mx0OEi3qYOdkZHBGqPN2cPYehudoAO9b7ei2tE90OfBltpa2/UBaN+xI7+g98kS1H8fAt5Hs7PL0GdgT/N5fmGhbRsAbdu12+ZzKaiW+JPm9XL03o1lvVcAbrebnUHX3r35vInPatDfi0Gt8NvXq1cvvOhzszFWoZMa/fs3l8+3hvysLBbQ9G/RbKDa7aZ9As/sJJJIIok/BHbx0uffBck9tLsG69atk0G9e0u2zyfBlBS5duzYVmGTjCEajUr/7t3lKYdjh30+zzgc0jfBfV4xnHzEEfKwwyG7m71d48z+ri6oTmwY5DBUnsGHsqem+3yyadMmW3Zuv/12KUD3q2agZEyxvXFbzV6vOpQh2IOScvjB1l7duro66ZiTI/lmP95NZs9attlzeDvIFSgjbCaqd7nc/J8VDEpFRYWtOu3Vo4f8A2Ud7mzKKUClH7qgZEb9zD65StOWCxcutGVDROTgYcNkX3RPZiFKchQEcaBMo2no3s+Bpo/6g9xxxx22bESjUemQmSkDQV4yfTORelbe2HGu6ac55nqCLpeUlpbasjVsyBDJhu32hZeixCx3g3zRyM8HmfrZkZ748ccfJcvj2aYBexH1+6obHwuo1+51oQzExcXFtuq0//77S9DcH1F036TflBlEGXwr0X2oaahcix289tprMsTnkxtNH9xh7tNJINeY++UwkDdAhpm+WmJsfQSSFw5b3tu/aNGibfrUleb6U42v+Yz/uUy7htH9s1tAMhKQ8zrthBPkFuPXH6KkRoPQPafZqMTSv9A9/Kno3tbsQMA2T0FRUZGEPR7ZBPKpuU+PNPXwGP8ah+63rkLZiUcOHmzLRgzLli2TVIdDZpn2D6GSWvuYvyFTl5kgaQ6HLF68OCE7c+bMkQD1xFw/o8+eXGPjsQY+vhfIkTaJyBpjxYoVymsQ5x6aCNLG59up8huiQ3a2DGZ7krCI6bMsr7dV9ureO2GCdHQ4ZEKc+qxFfztyUlNblRPjfxnJsWMSMSR9YdcjSQoVB0lHtI9oNCpr1qyxPbC3igULFkg4EJBsNBjMMIO9NL9f5s2bt1Nlf/HFF9IzGJTrzCD4ajPw34yyv25FWSY7o0QjtzsccvaYMbbtRCIRSXc65XQzCPaZwWpsQOlHA82Q+f9UkD5duti2c++ECdLf5ZJOpo3eZEc5izozSC4wdRrocMhVl11m29a7774rncx170a9bmonNNjzmQFmGOQkkD4dO9q2IaLyFT6UGMmPElDNM/WoMQP0w81nbvPXbnAuojrBA8ygO8/UxYcG5TEt17D5OxSdfDjjlFNs25k1a5a4UXbmJcYPUsy1p6CBUwjVav3GXMfuCejdDurdW0KotmlLxFNRdEInA2T0McfYtrVy5UrxojI6ftNOHnPt/4+98w6Tqsja+K9znhzIOWdQUAmCsgoiKJhQMScU066un64Rc1pzTruKCVxWFBUzLmYUBAURQQwEEYGZASYwoft8f5y6MwPODPS9A6xuv89znwndXe+tcKvPqapzXh+6kONGkyvFSH7BoaKiQpplZMhbqJP0reEJm/LTzO9Bw3s4yJ1oduqJHo9cffnlSfEdtO++8pBpj5Dp8y5oVuBz0AUb61nNQeWXjjj44KQ4RNQpy/d45BFTVhBNYHQqmtzqeNOWMTNeTgW58rLLkuYRETl+7Fi5AXVWg6bNAqb8ADUO+q8gvfx+mTFjhi0eEZGeHTpIDF00+267sfY9mlk5BtK5VSvbHCIi7fLzZRS6MChmPliOztsW3wwzNhrju/2yyy6TCKoZPB9dfDrOjI93333XcfkWli1bJhler2SaNrwIddTTXK5G04ctKCiQVrm5kosuEs1DFzitBHF5Xq88/sgjjcL1R0ZBQYF89tlnMnPmzEZdzE/h94uUH7H7kXJo60BqIP53oaSkRDq1aCEZxoj4yFxXGCO5Y7NmjvQSE4mE9OrUSTJReYe3jKMSNsZsC1QjshCVTUj3eOTrr7+2xXXepEmSgTqR+SAPU7MCvwqqneqDzM933nknaY7169dLwOORXFSjtSEnZoO5l5DLJd99913SXBs3bpSY2y3djVFvGd6WYxZDHVpLc/eqK69MmkNEd8y8pj8WU+OUL2XbXcdXTbsF3W5bY6KoqEiyQiEJmHJuQrNE1878+Q9qdusiLpcsXbrUVp16tW8vGcaxsByjvdEMrdnU7Dr7UActWW1YEZFBffvKVTsYA9s7tceDnDh+vK067b///uI17XMruuP4OJoBdooxkqMgYa/XluE3+cor5ViPRy6nZqfUkgqagkoE9WFbx/Y/IJmBgKxevToprjfeeENCpi6tUT3T7dvqQ3ThI2r4Pvzww6TrJCIyYvBgSUdPFgw09cpHF4oi5ueJ5veMQEDWrl1ri2fZsmUS8vkkii5AvYDu+gm6eHcjNYs4+++9t+3s8cuXL5fMYFBmmrK/RbPzHo7uAi8x/38dzaht59SGhcWLF0uGxyOj0fmzDTULhBPQDOwRkAvPO882x/a49957pUkkIunod1D7li1tZW/fEQoLC+Wiv/xFWuTkSNOsLDnj1FMbXev2xx9/lJ7t20uezyfN0ZMB7dxuifh8cu9ddzUq1x8Nv/zyi5x89NGSHghIv/R0aR0KSefmzeWpf/5zT99aCnsYKT9i9yPl0NaB1ED878I+0oofKgAAIABJREFUPXtKV5D1dRjgG1Btxr27d7ddfiKRkO6tWslMYxQ3QWUtyg3HAtTBHGWcm6Z+v3zxxRe2+Xp06SJtzb3X5VR8agzyq6++2lb58XhcMtxueWcnnZgvDd/OSprUxk033CCdUWc1hjr8c0AWgnwNcpsx9i0HPicctqVTfMShh0oI1ZYUkH9Ts2OejzqC88xrD6LO4IMPPpg0j4jIAYMGSQjVTq2vzRaYNmuWpDZsbZSUlEjItE9/tt3FqkB3ScKoU3vggQcmXf6aNWskw++XTTs5DqzrO5DscDjpHe54PC5Bj0fSUCdyX5AOqLO5H7ow9BZIN9RJT/Zoroga+N1at5bOqNPXEdVY3r4OL5i2C4F09fnkehvP0sMPPywe9NjlugbaazW60OIBefHFF5PmERGZNGmStEFPNmSjGsv3mfloNOqQhdBTDjmhkC0OEd3ljqBHmuvTu/3CPMvZaWm2eU486ii52pR3jynvL+i8+lfzfN5mXr8JZPyYMba5RFROJ8PjkQFmnOWYdhxuxsFpJ5/sqPzaeP7ZZyUvFJLD0NMI/UFGezzSNCPD9kJnfYjH4/LEE0/I/n36yH7dusndd90l5eXljcohot+B7777rowdM0YOGDxYrp08WQoLCxudR0Sl5Z577jmZPHmyzJo1q1GOTu8JrF+/Xjo2by5/9fmqbZMEyPsgncNhueX66/f0LaawB5HyI3Y/Ug5tHfijDMREIiH33XWXjBo0SM4/80wpKira07eUNJYtWyZhdCeuPoNyuTH27O6UffDBB9IxEpECdLX96zo4Ko2B/k+Qa91uOfPEE21xJRIJyY9E5P0dOBWXghxx6KG2OO69915pTY3+4s5ce4FcdNFFSfHE43FpGotVx+MOQZ3x5ujuT6YxXmcYAzaGHnF+6aWXkuLZtGlTdXysoNrDTY3hkECPGj5tHI9VaPxfDCQ7Fkt6F7CsrEzcaDzmjtrsAnQnK5m41tqYOnWqeEzb1ed03m3aLt3jSbr8yVdeKae73Uk5s9Z1oM8n/0xyl2HWrFmSjsYS7oPujNXW0HwV3f15E3XQTrBxVFtE4zODpu1/aKAOl5j3tGrWzNZucJOMDMlAF0h21F63mLmjdbNmtuqUaUIRckHGUXN81rqeMWN6L1OnZHebLZx88sl69HYH9bkWXWix851RUFAgUa9X1qELUJnoMdba5a9Cnc4P0UXCqMcjv/76q606iYjcdccdMtDrlSi68DiVmp3Z/UB6tm3bKEdB161bJxnBoPS3+ht1nNNBjgbZq3PnRj1yevqECdLL7ZZ/m+dnkMslI/ffv9GPta5bt066t20rg2MxOSEclqxgcJccNS4sLJQ+HTvKgdGoXAHSKxqVcSNG2Frk3NO46Lzz5Byfr95Frgwbp0JS+OPgj+JH/J6QcmjrwB9lIN5/993SKxyWGSAn+/1yyJAhe/qWksbxxx0nA3fCoBwCMv7oo21x/OXcc+V6l0seRo/E1cfxijGOVqIJlOzgk08+kZbs2NlcBRJyu20ZLgN695brd6LNal+PgHRN0hj/6quvJBddTMgwjkordHdMjKHa0xiXndHdp44g40aMSIpn5syZko7uVgkaX/hkHXW4AD2GLmgCJK8Nw3/atGmSiR6R3VGbWTGc559/flIcFlo1by4xqN7JqusqNkY5ID///HNS5Q/fe295PclxYF0Pg5yepMPZv2dP8aPHSDuxrTNrXaeiR5E7ggTc7qTKtzBr1izxo7G4O3qGAqgDmCwSiYRE0aOrW3bAI+hpCyuON1msWbNGQmhMboj6wwS6mfoMBzn88MOT5hERCZldzB3V52fDdcwxxyTN8fzzz1f3zfFokrO6OO4COdL8PgrkySeftFUnEZGuLVtKa9M2tefWf6POZodwuFHiTm+9+WYZ7fdLJppgL4EuoI1Ed4LbhsPy2WefOeYRMTG0Hs82468CpJXHI++//36jcFi4YOJEObeWc7YMJN1G4sMd4dqrrpIJgUB1H5WD9ItGk17k3NOorKyU7EhEvm/gGTo7EJAbr7tuT99qCnsIfxQ/4veE+ny+lGzPHwBvvvgiV5eWMhZ4pKKCtz/6CBHZ07eVFFb+8AM9d+J9Pc177aDgl19oJsJ3/FavtTb2BlagkicFpaW22nLlypW0R6VRGkILIJ5IUFpLu3ZnUVpQQH6Sn8kHyoqLk/pMQUEBYVQepQyVLikBjjavZwLHohIq+5rXEkBBkprBhYWFuFF9WVApiz/V8b7hwELze1tUxqOoqCgprh9//JEEKveyI7RH671m5codvbVObCkowEuNrEhdiKDt6gK+++67pMrftGkTOy+Ksy0ygU0FBTt8X22sXb2aMCqPsj91a78NAxahsjAVNjVBFy1aRBXbyk7VhRao1q0dlJeXE0elm6I78f5sdLzZqdFPP/1EJqqhGkOllerCcFTPNxf7GqSueLxe7d7aaIr237Jly5LmKCgoqNYfXoSOhbowBJUhAqPvneR4q43vfv6ZEnS+qT23Ho7RK66qSvr5qQvfLlyIr6KCrcAkwxVAZZyiQGcRW21WFz7//HMGiWwz/nzA6HicuXPnNgqHhQ/efpsTje4yQEegt9/P/PnzG5Xn47ff5rjy8uo+8gNHFhfz0Zw5jcqzq1FUVESiqqpB7fV+5eV8v2TJbrunFFJIoW6kHNo/ADr27MmLgQAlwFSgfbNmuFw7cqX+u5CWkbGNpmp9WGfeawfhtDSKgSxUu7A+rEIN/S1A2Oez1ZYZGRlsNL8ngLeBm4ErgTtQDVWAYlSnMxgMJs3hD4cpSfIzJYDP70/qM5FIhCrUqfObMspR/V7QbcXP0QWAn1BjzAWEozvjItQgHA4j1GgENweW1vG+pYYLVFM4bj6bDDIzM3GjOo87QiFap7QktFRrwxsIkEA1OutDAh3bAuTnJ7dMEQ6HqWs5pAzVb30FmIvqZ26PEpLvp2g0ShmQg+oF14VlqH7sesCTVOk1aNKkCW5Uj7MhWOPRzhKe3+/Hg2oMx3fi/RWGy84XZ3Z2NiWoM7sZffYTqKb3L6Zs0PFdiT3dYwvicm2jq10fSg1XVlZW0hyRSIRN5vd8oD7X+3sgz/xeRPLPam1kRSJ4gO3dr0VACNUHtlOX7ZHTrBlul4sg8Fmt/89F22yjx0N2drZjHoDWrVuzxOX6zfj9wu2mtU3d3vrQvlMn5tX6uxT4pqKCdu3aNSpP2y5d+MKz7ZP/RThMO5s68nsK0WiU8kSiepzXhTVuN5l5eQ28I4UUUtgt2K37xLsI/+tHjjdv3iyHDR8uPo9HurZqJQsXLtzTt5Q0Zs2aJSGQjQ0c7Sk0R/VeffVVWxzPPfecDDPHh6x4xgI0VvMt9GipoFlGr0OPu44cPNgWV2lpqYTdbrnaHLvsjWpoXovKgTRBMyyfDzLAZqKrc845RwZt10ZVaDzbGyAfU5PZ1LqOBDl89OikeEpKSiTidks6Gm83EeRRc8RvLzQhUG80gZKVqbUTyF133pkUzw8//CA+NEbNOh69D6r7GTfH/r435X9m/m4N4ne7k9ZP/OWXX8SHHo2t3T6WRvD2RyZj2JfquPjii8WPJjVLoEdbp6Nx2pbO5euGIwxJHz+feNJJcl2t+/2GmgRD7UzftEKPyR6Pxn1Z7z3F7Zabkkxqcuedd0oGquHbpNaz84EZA9+jcc7voMeA+/fokVT5FkpKSiRi2uQnkDvQzMa5aPz2YWacP2jarm3LlrZ4MkyCq1drtctWU48fqEkaJ+ix+gyQrCS1dUX0eHPMjO8cNLFaUzT2NNf01+Ho8ecWpr/ee+89W3Xq07u3hKk7wV7t6x+GZ/78+UlzWEdlt4L8C5U6Kt+u/Ao0odKz5vdsj0cWL15sq04iGs84woyrS9CEandQK3FcWpps3brVdvkWvvrqK2kaDFZndD8bnTvTURmvZhkZjabZmkgkpG+nTnIu+h1XjGo7t8rJaZS61Mb8+fMlJxKRaz0eeQpkv0hETrMZ494Qli5dKrnRqNzidssckAt8PmnXpMkuk/vblTjm0EPlbperzuenHKRVOGzr+Unhj4E/ih/xe0IqhrYO/NEG4u9ZFy2RSEiLtDQ5wRiv16B6o4eisYc/gZwM0txGAiALW7dulfy0NFmCyjxY+qm5xgCPovGfuag+496RiMycOdMWV0VFhXRo2lT6ow7z0yBHgRwMcpox9p9DHeuJZ5xhi2PTpk0SNs5EuTGC8qhxKFuY8v+KOlHrsJ/c6PQTTpDO1OjpphujfB/UUbMkaawr5HLZMl56deokQXOvBSCDjaHvMlcamk233LRrDOQvNmNbe7RvL0FUHuhEamKEM0wdhqAOTT5IzO+3Pe4qKysliDpmTdCYXz8au2jpt1q6pCOSjDsWUSO1eSAgVaiTHEEXTc5Fk3a1BemBLqicaPjeRvWX0/3+pKVhSkpKxIXGgp5l6pFh+saSJ9oPddyi4CjWsF3r1tWyPbnmZ7hWe2UbjgDYjp2cOHGieNHFmW9RB8yS8rK0aQegWaG7mvF/1VVX2eLaf/Bg6UqNxvKjaPbcHmh24JvNM9wTJN3lssUhIrJ27VqJojHmj6JJ2izt5pjhfB8j5WUzxllEZGi/fvI0upB2CLrA1A1d5LLG3nA02d6/QPZzkKVeRGT16tUSDQYlwzw7lq5uGiqtddvNNzsqvzbOPf102SsUkr6GK4JmwW8aCsm0qVMbjUdE5Ndff5UjRo6UgMcjfrdbDtpvP/nxxx8blcPCkiVL5LwzzpBjDjlE/vnPf+6yRE1ff/21nDp+vAzq3l0uOu882xJUexoLFy6UnHBY3mRbZ7YEZHwwKONsaFKn8MfBH82P+D0g5dDWgdRA/O/Cl19+KVGXSyLoivjL5jrHGBNRcLz7fOdtt0nnQEDSjNGajjpp3WpxZKK7p/06d7b9ZX/68cfLqFBI5lCj25phjMlMw7MfyHx0hXfa88/b4jlw4EDZD5Wz6Yo6sZaT5Ed3gHqhDu4okL4dO9riWb58ebX0TCd0V+QEVE9zKMgNpp8sp+2c006zxfPWW29J2Bj4TdGduIhxXLKME9McpK9p1wD2ZGFERBYsWCAuU2Yaqm35KSoLdLvhjxgn4Nlnn7XFYeHcc8+tdiYy0OzKQ41jETJXAGzv+gzo2lUuNf3zd8PTD+QJkFmoNExH02Z3mPddCDI+yd16C9ddc40ETfscjO4wLwf5BHXUwqY+fbt1s1W+hb/ffnu19muaeY6GmP4PGZ6IcWaSTaZlYevWrRKjxlmOoI7gS2jm7jPZ1omOgW3d1qlTp0o6umNp1csa29acdAa6UHTgoEGOFimHGFmqdNRBtuqWju7aB9EEV6+//rptjnfeeUdyPR55zdShDTqXNjM/25n57hWQPI9HZs2aZZsrHo/LkP79JR1NOGbtPleZ8vuDZHm9jSapE4/H5eorrpCsUEhyXC7JdLmkTZMmMn369EYpf3ssWLBAJk2aJGeeeaZ88MEHv+sF6j8a/vOf/0jLnBzZLxaTS91uOcPvl+xgUE444oikZc9S+GMh5UfsfqQc2jqQGojJo7S0VGbPni0LFixo9C/cW2+4QXqEQrKW3x7tWQfSKxiUm6691hFHYWGhRDweiaK7Lp/V4vgV3cVKM9dDDz1ki2PJkiWSHwrJPGM8RkDGgMxGs0o+jx7PyzCG5WyQtnl5tpznsrIyyfL5pLcxWK+gRkuzwBh+YXT3Kd3lcqQ52LtbN+lu2qgVyJ3okdlXQcaiju7Npr5Ojpadd/bZ1c6z5UBYO5xh83eO4XnhhRds8yQSCQkaY38dmvF3KCrbdJMxmA8z97FlyxbbPNYObQQ9Zuozv1v1aY7uoAVBzp00yRbH7NmzJQ2VlYmg8i/bP0MJ0z/pZpykgW3j//STTpIIuuv2KrqgEjIOzd0gXxlHpmVOjq3yRfRYeMznq+77h9n2SOtKdFcwaup09KhRtrmmTp0qEXQh5T+m372mr45ENZc7mDq++eabtjgqKiqkaUaGPGvKiYIMRB2/tuhR1hxT19NA2kYi8uGHH9qu05+GDpXmhidmxnlnw+dHnc4QyctrbY9rr7lGdYDRRboXQF5Dj9UPMZwhkCsuvdQRz1mnny5Z6C76NPTkhHUy4ASQUtNX+TY1sLfHyy+9JFnBoJzjcsmbIC+CHOr1SuvcXFm+fLnj8i2UlpbKvj17ShZ6quIidFGwS4sWjZ59OAX7qKyslJdfflluvPFG+dvf/iY//PDDnr6lFP4LkPIjdj9SDm0dSA3E5PDmm29Kbiwm+6WlSbtIRAb27i3r169vlLKLiookIxSSn+owxK1rFUhGMOjIKbv3nnskCz0uWZ9Mx+XGAOzVrp0tjgsmTpTLvV45zhhcV9bBsdUYf+noMdG9YzF57bXXkuZau3Zt9S7MY/XU51Xj5KSBfPPNN7bqVF5eLhE0nrQj6vxvz3M9KrGyF8ipp55qi0dE5P777pPmqIMXQnd+TzFG/jHU7Nhmu92OJDqeeOIJCYKsMQ5Mi1pOTHPj3Gw0TsahNrWCRUSuu+46CaHOsrXTZx05zjD1yTP1DZJ8DK2IyLvvviv56CLNXxt4hgTVPx1r7sXOscatW7eqjBEqsWTtMI5Hnb5801czzLj88ssvk+YQEbnh2mslxzyLT9ZTl0p0JzoIEvF6be/SHjJihIRQxzUX5F40lnETuuOdb14LgpxsU5v6hRdekKGxmGSbPh+AOuTvo8feL0dPBVhO7R0gE8aNs8W1adMmCZlnvq25/gHykeHJMeOwN0ib3FxbHBaOO+II6YceMX/IjIUu6ILGvWh4Rz+QcQ4WHCoqKiTL45EpaMx01Mwz46iR0umEzulRkMcff9xRnVauXClZweA2C57WdQ9Ij0bSuxUROXjIEBmDagb/GXVqv0BPBtj9DmoIFRUV8sQTT8jNN9+8y22gwsJCWbBgwS7dxVy2bJkM6t1bIn6/dGvVSubMmbPLuCykbMcULKTGwu5HyqGtA6mBuPMoLi6W7EhE3jdf6nE00cPJNjVht8eDDzwgR4bDDRriAnJMKCT33XuvbZ4uLVtKOhpXVh9HgTE40z0eW0ec82IxmWcMxjTUea2LZ64xvgYYQ3DC2LFJc103ebL0Rlf069IDta7uxnidaNPRvPTSS6Urerz06Xo4KtBdn9tA8nw+Wzwi2kfWTuxZxvi+Dd0ZboEe13WbtjvpqKNs8wR9PjkC1dVtgu6QbUadpNMM191oIq8w9qfK7GBQQtTsiHVEF2cSxji2nNrBqMP0vI3j5wcPHSqXm8/Xp29qXR8bZ+NEkLPPPjtprilTpkgI3SnLRnfgimrNC+PNuP8GddSH29TFbp+fL0HT/1UN1OcVamK6/3777ba4Aua+T0Z35+ta5DoPPbbvtzkWxgwbJk+ZMdANTXBVuR3PFWYcpqOOTdTvt+UMnHXWWdU7yukgP27Hcy+6YBNBF1bWrVtnq07l5eUScbslrdZzZCXX+w5dGJplnuWwy2XbsXn00UclDd2FTUMXh3JALkaPZ48xdZlt2q1rq1a2eCxcddllMtHtrnO8JUA6BQIye/ZsRxwiegohBPK1absrzPjLQROsZWB/QaguJBIJOWLkSBkWDsuFXq/kRCK7LInkwoULJS8tTbrFYtKpRQv59ddfG52jpKRE2jVpIve4XFIEMhMkJxKxlSciGaRsxxQspMbC7kdKhzYFR3j//ffp6fEwxPztBv5WWcmMV15plPK/+fJLBu+EFuvgsjK+WbDANs+Pa9fiQrUe60Mm0APwJxJJ60DG43E2FBdTgUq9DEX1C+vCAECAr4F2wLrVOxIo+S0WzZ9PJXAQDUuJHI7KhHy7cGED76ofn3/+OfugshWj6nmPz9xHBbC1si6RmJ3D9z//TACVNIkDFwKXALcC/YFegCXctOSrr2zzuCorGQ68Yf6+G5VU8QL3o1Iqr6M6mvX14c6gdOtWgqj+aAi4AtVOdQEXoHURtN38wLx58+opqX6sX72aEJBG/fqmFvYFNgHdgJUrViTNNXfuXALo/XqAiahGMegYvBjV1X0P6AssXby4rmJ2iFUbNuAGBtOw9M+BqHTPVmC1DY3qiooKAqh27juoxun2OBaV3joAHed2sHrlSoLomM4zZW6vn3siYNXgHSDd62XDhp0R4NkW8+bNqx7L+wCtt3v9ZFRyyY/qqi6wOaeuW7cOTyJBM+BjU24n81p74HTgfXR+C4iwZs0aWzxffPEFXVHZHw8QBq4F/o6205umHveh47vo119t8Vj45N13GVuPfrILGFNezqeffuqIA+Cjjz6iD/ABOnfeAPwNbbcZwEjglUb6jgXtr/fee483S0u5u6qK80tKeOqxxxqt/Nq4+6ab+L/Nm/l6yxb2Wb+eZ555ptE5Fi9eTFppKReIkA6MAQ4RYfbs2Y3OlUIKKfx3I+XQprBTiMVibBTZRiuvAEhzoClYG16fj/KdeF854E1SR7U2PG43LlSjsyGUooaL17u9ydkw3G43Lper2gAvbuC9VagGpNf66UveVPb5/bhhh3q0xejDbocDVK/TcrgaqlMxanA6UUH2GE1Gt7ksEziOOoXxWpcvyf6pDcuJDBuejbVeK6DGcK747UeTggvtX4/5WZunghrdXY+5J5+NPvJ4vdXl7wjWe6oAXyB5Vz0YDFIFBNHnceN2rxeg7Wm1ncfTkDtaP7zmczta5iqj5ovMztzg8XgQtC5h1GnaHpvMa+XoQosdeL1evGgfJ+rhKUIXPdyo41wpkvQcBDqGXGgf18djKV/HgYCNcQBapyp0MSHGb8fCBvN/S+fXztjGfK6Smnt2o5rXoPODz3BkomPO7XZm2gSCwQbnuc1uN34H30MWwuEwxegC0M9Q/f26xvxvE6r321gIhUJUilRrXv/k8xGzqeu+I2Tm5PCNz8ca4AePh0ybOt4NIRQKURSPbzPvbXC7CYVCjc6VQgop/Hcj5dCmsFMYOHAgiexsTne7eRLdwTolGOTs889vlPKHHnQQL0ejO3zfS9EoQw8+2DZP/169qACmmb+XAE8DTwBvoQbgcnSXZLPLRd++fZMq3+Vy0aFp02qH+BNgvXmtCnVeLIN4JmokHwjM83jo0L170vUZPmoUVegORTHwOXAScChwPLpLVgU8hxrKQ0fVt7/aMMaPH8+bptxn63lPIfAualjG0tPredeOsW/fvmxFDdM16A7qAHTXPIDumm5BdyOHHnKIbZ6MvDyeQdtpC3AC8AowG90ZyQImoGNlRwsGDSG/SRNcQAe0768DngI+BI5DDf0E2m5bgbFjxybN0al3b7435Xy+g/e+DDRF67nXgAFJc40ePRoXsA7daX4ImIMayN+ju+kF6I7nXGDE4YcnzQHQo0MH4uju1eYG3jcVHRcRoGeSzyuoQ1vucjENGA/cBdss3In533jDJTYXUbr36cP3Lhd+4DvgSfQUgIUEegohDx0HZwJ4veTm5ibNNX78eFahjt5P1JxCAK3P9UAzdOxVAPvuu2/SHABNmjQhFg6zFX0+XwYeBlYBjwMvoKcqitDFkxYtWtjiGTNmDN+gizEBYBkwHegNDAQOQefbq4GXgDY25tLaOGzCBJ6op5+3AjO8XsaMGeOIA2DYsGH84HbTG10s2Q89BbAAOAL4DzBhwgTHPBbS09O54cYb6RsM0iMW4/NWrbjwoosarfzauPL661mzzz70iUbpPHYsJ5xwQqNzdO/enW57780xoRD/Ai7w+/khK6tR+iaFFFL4nWE3H33eJUjF0O5aVFVVyb133y3t8/OlnccjI9HkPxlerxwyZIh88MEHjjkqKyulZXa2vNNArNx7IM2zsmxLZoiIzJgxQ3LcbgmjsavpaDKRLmjm3qbm9yDImAMPtMVx+623yomhkPwfGqvYw7SXx8SrhdDkRpaMzxsgzcNhW7FSZWVlEvN6JQNNZpMGMhHkOhPzl23+HzExbBs2bLBVJxGRLLdb7jLxXf9B435PRhOZLDXxhWebWLB77rnHNs/LL78szTweiZn6hFD5jzam/aKm7SJeryOtxgULFkgIjSm9y/R5uukTqx1XGv4bb7zRNs9LL70kfjMOfGj8rxUj7DV1smRosvx+WxwrVqyQCJrcaoS570NN+S7z8zSQn9H4zbPNeCguLk6aK5FISNTjkT9RkygpVKsuVkKjG0wdf/nlF1t1evLJJ6v1oSeiuo+XovGTI9HYzLVmfIfQhHF2YzSvuuoqCaNSPa3QJFBWvfLRZFcvmOfovvvus8Xx8ccfS/tIRHqZcbafGWetzNXEzD1Rw/MXv18uvegiW1zxeFzSXS5pZfogC00Edj6aTKm96adeIHv37m2Lw8KVl18unc29v01NsrsBaFxtDzPmLv7zn21zJBIJaRaNylUgi0ydfOh8nW76aSLICvO7k+zQIiJbtmyRNnl5cicaM2t9B5WBjPN4bMtd1YUrL7tMWpo59Q40U/n7pt1OOOaYRuOpjR9//FHmzZsnW7du3SXl706UlZXJ5CuukHHDh8uFZ5/daIkqG0LKdkzBQmos7H6kkkLVgdRA3DEqKyvlqFGjZEg4LB9u9+VeimbOzA+F5JkpUxxzvfPOO5IbDssUVIvRys55OipDkhsKyVtvveW4Pm2bNpUI6mw2M8ZkS8NlSY9EwXYG3Q0bNkhGMCgfo85fnvnZE3VsWxiOsDH+HgUZ1KuX7TqNP+YYCaOJXo42xmsIdfpGgTxiDMAhAwfa5hARufzyyyUNleJIM+Xvh8p1WDIko0DyQiGJx+O2eaqqqqRrmzaSgcqaBExfpZl6DDNtN/7IIx3VR0SkRfPm1RqwlrxJOjUZh7NBQh6Po/qIiDTLzBSPcVTag9wIcj8qNxKiRu926tSptjn6dOggF1Cjzxoy9fGYOlmLKbmovMmhf/qTba6nn366WsfUV4vH0moNmGucA8O/rKxMmmQxfNNlAAAgAElEQVRkSICarNBZZtxlmjpGDX8+yOV//asjLr/RwN7XzD+HocmGzkSdwChI0Ou1vaCWSCRk765d5e5a48tjxlgONdJUITSTb3Yo5Ci5zQ033CARajSp02qNcT81zrNT+ZGysjLp0qKF5Ji+sOoQMn/ngLTLy5OSkhJHPP/4xz8khCamsyS98qjRE2+PzuX9HGofW1ixYoX07tBBWvp8chDIUJdLMn0+OXbMGMd1qY3CwkIZ1K+fBKmRVQqC9O7QQVavXt1oPBbi8bjMnTtX3nnnnV2SqOl/ASnbMQULqbGw+5FyaOtAaiDuGP93wQUyIhyuN1OvoBka80IhmTt3rmO+yZMnS8Q4SbegOqrdjMF/1VVXOS7//fffl0yfr1r6xcpEHDLGcgB1btu5XHKWTXkOEZEnHntMsl0uaYc6fRcYR8IyJK+kRqIjze+XRYsW2eJZvXq1hF0uedoYqp1MffzG6OtiDL6nTRsuWLDAdp1ERFo0bSoxVM/0WDRj7z4g14AMNxxOn6sZM2ZIvscj2bWMVctATjf16wKS4ffbliGysGrVKomZMdbdjImm6ILDANOGL7/8siMOEZFrjFbni2gm4E9AXkbljwrRhY6YgyywVl38tRy9A42Rn2sM5WFmjIRM223evNk21/z58yVg+vsIVM+5DN0hu6SWU3O/g4zkFk/Q5apezIiiO9CW7m2aeWYH9OolFRUVtnmKioqkRWamTESdZUu/NYouemWjO9zt8vMdOTPfffedZAQC1YsYg1FJon+b8i1JpyjIk//4h20eCwP22kuCaEbldtRoX7cyffTUU0855hAROXTECAma++6NntzoR43jOXz//R1zJBIJ6dmpk0RAJqFSXr3NePg/02dhkBUrVjRCjXRhctT++0uO3y9HezxyiMcjaX6/XHzeeY2icysiUlBQID3btZOz/H5ZiephrzE/LzWat6tWrWoULhGRGS++KO3y86VbLCbD0tMlIxiUU8ePd6Sz/b+EsrIy+fTTT+WNN97Y07eSwn8JUn7E7kfKoa0DqYHYMIqKiiQjGJSfaVgGREDuc7kcH8NatWqVREDuBJmHyi9MAvkclU+JgPz000+OOEYPGyZ51BzPPRHVgFwL8gA1R9kyUMkMu8clv/nmG4l6PNID3fGJGQfjYtTpzAC5yNxD0/R02wbS8ePHy/HoDlVXw9MU5DjjlMXQnWeLb/jgwbZ4RESWLl0qQVRqJgdkNCoxchDq/B2GOrfdunSxzZFIJKR3u3bSk5pd3xYgk2u1l6WpOwzkTAeLDiIiIa9Xupn2ewmVh0mgep0dQQaZNnSCeDwuaaje8Cr0eHF7c//pqCRRmemnM844wzZPVVWVuM397m/Km47KqPzTjPnhZiz4PR5Hddq3d2+JUbfGsoC8Zfov6HY7Ota4YMGCagfvXPRUiMWxxIyNdJDcYNBRfe64/XY5yHruzXhbiOqBXmb+l4WeGHjs0Udt8xQWFqpmLrpDv327fUWNkz5t2jRHdfr0008lhDqzh4J8CrIeZJqZG3qCpHu9jk8ffPDBBxI29/3WdvV5j5oFQ6enaz766COJodI21gkRa1EyD10QyAE5eOhQRzwi+szu06OHTHK55ALzLHVFvyMGBQJy6YUXOuYQEZl40klyjt8vv5h5wTpu3h6VPbre45ExBxzQKFyzZs2SpqGQzKHmpFUByEmBgAzfd99G09X9o+KFadMkLxaTPmlpkhcIyIjBg2Xjxo17+rZS2MNI+RG7H7Yc2ksuucTx9X//93+7pEK1kXJodw0euP9+OWYntGEF1aHMDAZtO4AiIkcdcYQMQHevcqjZoc0xDsa+IOMOP9x2+StXrpSYz1e9U3pkHfV4wxjIrUA6uVxy0/XX2+L68znnSAc05i8D5PFaHHGQo4whdixIS79fXnvttaQ5EomEZHi98pgx8MJonJyl2ZlA48piaHze39G4SbsOxl59+lTv+o1CHfRXMLqz6C7njYbP7k7jZ599Jk293mpntgfq7Fltt8bU1Yp1jfl8smnTJltcRUVF1acBXq5jLFg6qwGQF1980RaHiMg999wjWajm6HDUCbQMytXoiYD3QB4z9bKLadOmSQjdGUsD2bhdfb43Y665MZq/+uorWzw//PBDdbxxeQNzwnDznD3zzDO267R3r16Sie6eJ+rg+IwaLdX58+fb4kgkEtIiM1NOQ3dj70Sd2Ji5bkC1iJujR5E7N2tmuz6333abeNEjzPW1221mzujRrp1tHhGRQf37Sxt0kWl7vdvlhiMAMn36dEc83Tp1kqiZX+pc7DTt2MGhNuyQAQOqHcuoeWYEddIHmvpcaLgKCgoccb3++uvSOxSSE9ATNp+h3w35aO6AjGDQMYe1YLwWXVyIoTv2I0z98kG2gGQFg46PhYuI7N25c53zXBVI12hU3nvvPcccf1QsX75cckIhmW/arALkXJ+vUWOpU/h9IuVH7H7U5/M1mK5x5syZuFwuRKSht9UJ63Mul4tbb7016c+nsOfx1dy5DNsJbVhQHcoegQBLly4lPz/fFt9Hb7zBdcA9aCbYc8z/M9Aso2cBV7z1lq2yAZYsWUKe200CEFTfdHscjGbRLAJCIiz+7DNbXPM//JAf0CzKfuDUWq+50fq9hWqGRioqWLBgAaOSzEBcWlpKSVVVdTk/ArdQo9npAm5EMzi3AF40dVq1ahUdOnRIuk7fffUVF6FZod8DfkW1H0ej2Yi/B5aimVM//fRTDjjggKQ5vvzySzpUVfEtmn31SmqkOkAzs56GZlL1AbnAihUrks5GDfDwww/jRaVFRtfxeidUq/VX4Morr2TcuHFJcwBMnTqVgwzPPGAWNbJGzYG/AM+gGpTnA1VVVbakWp6eMgUX2l4T0CzNtdEWzQibQDMsz5kzh549eybN88UXX5AAxqJjuz6cAnwGfDh7tu1MrT8uWUIczfhblxRUfyAHzYL87LPP0q9fv6Q5tmzZwoaiIr5C+3oIqtv8E5pVtxuqQXsDsAJY/vPPxONxW3JEb8+cSYxt54PtcRxwDbA0SQ3s7fHV/Pl0B87gt3q3HVB92qXAtOee48gjj7TN8/3y5YBq6NaFE9ExvnLlStscAAsXLOBEdP45Ds2iDdr/D6Da4pXo+F64cKGt+cfCK//6FxPKyrgcfW6tnO2PoZmU93G5ePfddznqqKNsc8yfP5+egQAVW7fyPaqf+zY6zk9BM0QvBg7yevnwww9p06aNba61a9fy/Y8/cmgdr3mACSUlzJw+nWHDhtnm+CPjuWee4cTKSqzZxQfcVFlJszffpLi4mOhOKDSkkEIKuxYNWk1jx47F5XKiKJnC7xnxeJxkTDYPaozbhSQS1dqWtZXxMlDnJmjeYxfxeLz69wQqmbM9LIegDHV6qyp3Rtmzbi5L29LSlayNKNvqWdrhicfjuKnRFY2j0iW1ETY8gsr3eIBKm3XC6BAH0S/02kp/aWjblRuOigp76q1WnTDl1aXAmG5e8+JszJWUlOBB61OfflkIh22G3l8AbRsfv510Y6gUiA/tp3g8bsuh3VpWhgvt7/rMqwjq/AmwdevWpDmgZmzvSLk0gLar3bEA6KIo2y5qbI8gKrtUXr4zSta/RTwex+NyUWUWbqvQdoqhbWmN87h5zQUkEglbDm28qgo3DbddEPtat9vAPK/1KYVH0LFY5aB/LJ449feRVR+nGoEiolra1DiYFqJo38SpeYacoLK8HB+/nYPSMN9FiYSjOQH0Hn3od40LdcwtayvH/CxDF42cfK+Czl8Bj6fePoiIsNbmfPC/gLKSEqLbjakQRmPc4ThIIYUUGgcNWk233HLL7rqPFP4L0a5rVxYEArAThmIFsKSignbt2tnm69i3L9M++YRTgIuBTNQIugy4GdVSbderl+3y27ZtS4EIYdSBeAbYa7v3LAI2ok50CGjbrZstrk49erBqyRJ6A5+i+qZeVM80B3jNvG8TUOX10rFTp6Q5otEobpeLoSJ8YsqfhO7MbUIN8grU2KtA9W7vBlq2bGmrThnNm/PN6tWsQ3etjgUOQ/VIH0J3fUYBrwL9+/e3xdG+fXt+9nopraoiDlwF/APdAfYA7VDNXR+q2/qLCK1bt7bFdfLJJ3P79dcTQXcS+6E7dAl053eL+X8FcMUpp9jiABg6dCj/+vxzWgJN0J2XY81rW1FN58tRvdUAEAjsyFWsG6NGj+aD2bPxomP7RlOHLdQsEL0LtDI8dvuoc+fOeNExLNS9cwqqB1oK9N57b1s8AJn5+az/+WdeACbW8foPwEpzD4fY1CROT0/H5/PRrbycX9Cd2c7A3qiTNBDVBW2Cjr/v0tLw+Xy2uPYeNIj/fPop/0Z3TuvCq6gTGsnOtsVhoUmrVmz+6SemojuatVGI6hBvBf48YoQjnuycHIo3bOBl6t6lfRmdi4IOtKkBWrVqxSfff48fPXXyZ/SEQwK4Fh3TMXRu6Nq1qyOu/UeO5J///jf9t27lbHQHuAi4ABiHznf3DhrkiKN79+4sKC+nKTpHv4buZEfQEyheVH/75ESCi/r0ccTVokULQrEYn5WWsk8dr78YjXK+w3HwR8bYo47i6Acf5PzSUixV6IddLvbq1YvMzMw9em8ppJCCwe479bzrkIqh3TVYvXq1ZAaDsrmBeC/reh5k+IABjvjmz58vIVS78M9o3GcTExf1jon/++yzzxxx7NO9e3Wm3DCqPzrXXK+bOLmAiV9K9/nk22+/tcXz0UcfSa7PJ/ugWVODaAzwwWisaRiNC8wCyQyHpayszBbPQfvvLxeaOMIImv31ETQZ0BOoxI6VIfh6kL06d7bFIyIye/ZsCaAJZiwt2Oamj/ymzQ4CaZqdbZujqqpKWmVnS56pT080odEnIB+C3I7GOcbQZDdjHUjPiIiE0GQs+aafLFmTCJo4p78ZK05QVlYmUVSj83PT5x2oyap8PBrj2B/koOHDbfOUlpaKz4y15qZsSxvWg8aidzL1c4OjJDBtTbbrJ0GmoNlmm5p6XWeeJ0vWp7Cw0DbPK6+8ImHzvNyJ6jd3MXx3orGTMZAMt9s2h4jIpRdfLEdTI21zOJoUrBOaxdnSDR4DtuPqRTSOP2za5l1qYt2tuPf1pu+8IPc60HIWEXnxxRclgCY0ugzNpi0g36CxmlYWb7tzj4XnnntOQqb/fzBjudD8XIkm7gqBPPHEE454pk+fLmGQq82zasWL56Ix/Pub8dfbwRxnoaysTFrn5sq9plyvmePOBTnJ7ZZjx4xxzCEicsSIEXKr2y0L0Jh0a6xH0e+8p0H27d69UbgefuAB6RUOy1pqvrcTIH93u6Vzy5aOsoT/L+Dqyy6TnGBQTgmHZVgkIq3z8mTp0qV7+rZS2MNI+RG7H7aSQsXj8Ua5djVSDu2uw3GHHSaTAoE6E7JY1waQjpGIzJw50zHfISNHVkuL7GUuS0/zIIfOi4jI1KlTpbnPJ1nGQLF0GqPU6I82N87MIUOG2OZJJBLSvX17iaCZjU9HHbEMYyRfagzlGMhfHWTM/OKLLyRijPzF9fTPCtTRTQNHfbRlyxZJ93rV2UezDj+FZmu1dDr9IPfdd59tDhGRk088UTKMwX+maTMf6phZycL+YQy/xx9/3BHXzTffLAHT51losq7jjBGea8bDiIMOcsQhIjL2sMMknRoJovaos26Nuw7m97Vr1zriGT1yZHVCLas/XNRo3UZNu02++mpHPDNnzhS/KT9o+n8CuqARNHxukAvPPtsRj4hI27w88VOz0NDa9Jf1PzfIAw884Ihj1apVkhEISKdaTkVTdLHG+rsbqg3rVLtzwpFHitc4SVnm/l1mHFiySzmxmGMplUQiIYP795eAaacMwxc1dQuA/KMRpIESiYR0aNmyejGl9pwaNHVqlZ/v2BaoqqqSLm3bShhdrImYdvOatmtiOJ1Kk1n4+uuvpU1engwJBuV2VJqsYygkf9pvP0eSV7WxfPlyaZKeLg+4XFKCZol+DaQYXSTOiUQcL+JaSCQScu0VV0hGMCjHhUJygc8nXaNR6dOxY6MknfpfwPLly+Xhhx+We+65x1H29hT+OEj5EbsfthzaLl26OL66du26SypUGymHdtehqKhI+nTsKGcFArIc5A5UnuU4NDPsPJDu4bD87eKLHXPdcccd1SvwG9jWYZ5sDL3bb7vNEUcikZCzTzlFIsYIugZkKZpt9nl01y8G0jQrS9atW2eb59tvv5XMQED+jjqSZ6ESIGvQHegDjWH+Z5Ce7drZXh1//vnnpa3Xu017rQX5D7o7Yv2vGKS3xyP33nWX7TodesABkoNKKdWV3fZj06Yxv992Bt1ly5ZJTjgsnxrjuyeq0VmEarY+aAzX7iAvgLTMybG9w7Ro0SJJ8/tV8xPNXFl75+J1cw/pHo+88sortjgsrF69WmIgQ9GsqVaW4GzUiY6BdOrY0RFHVVWV9OvatXqHZyKayXs/dBf4VGp2f44aNcoR17x58ySM7vIt47cLXGcYrnscjDcRXVRtkpkpEXQxYzC6A3yhGQcdDc/f//53RzwiInv17i0RVN90ea36LEGzkUdBDmgEPdXy8nLJDoWkuRnP16KLXk+B/MnwfPLJJ455RDTzddQ8L9eipzQuNGMvw+ttNP3RKVOmVPeRB12Ask4FREAef+yxRuG5//77JYzq3C5AM8ZvRE/aZIK0b968UeVnPvnkExnUt6+keTyS6fPJcUceKatXr2608kVU4q13x44SRhcdLOmo9k2bNoq2+/b44Ycf5KyzzpKjjz5annrqqZRcjw2kbMcULKTGwu6HLYe2c+fOjq8uDjQpdxYph3bXoqioSI4aPVrCxkB+AJVo6AyS5fPJg/fd5/hLsaCgQGIgD9fhKFnXY+aLfsOGDY64jhw9WrKM0foyuqu0F+pIF4GMM8aek6N4Z554olyIOrOzzf0vRVfgfzEO0+XG0Ozn8ci///3vpDkSiYT069hRXqNGSuAs4xz1M4bReJAS8/rnIG1yc21p3s6bN08yPR4ZR93yKdY11xiwx9mUV/rzOefI37xe6QAy0tTpTfSo30WoTudG9BjliSAHR6Py9NNP2+I66pBDJAPkVWrkKz5GFwMsvdPFxmHq1qqVozGe4ffLAcaRuL9Wn3xlnLRhqJPrRKtz5syZ1TqWF5r+t2R6LAf6MlMfP8iXX35pm6tN06bSlW0llWpfCdQxDIMjp+nyyy+XALqw8O52HBWok97ePGfl5eW2eWprnNZXnwvM/LN48WLbPCIiJ510knRAJa58pkxLe3YQyNkgzWMxRxwiOqdGzXNzELoAMNCMg0vQY9vNMzIc86xatar6REAUPd0ywfSLNR6jIN9//70jng0bNmyj37sEPanxGurYfm/GyYUXXOC4TiIir776qqR5vdLePD9BVDKoSVpao+5ovv766xJzuWQ0uqgxBV2AioA86kDzuC688847kubzyUDz3ZDpcsm4ESOksrKyUXlERObOnSv9e/WSJhkZcvCwYY415Pc0Nm3aJH/761+lX/v2sn/fvvL666/v6VtK4b8AKT9i98OWQzt37txGuXY1Ug7trsfwffaRG10uGWgMZGt3c3A4LI81wur7eZMmSUtjmNTnLCXQXc2zJ060zbN582ZJd7nkfpBnjfH1AsgHqLM+At0JDGH/GGNRUZGk+f1yDrqTIOgx2XzjuOSiTlMcPfo3GWRov35J88ydO1faRiLV8XdXmvKLzN8lqHN+Zq027B+Lyauvvpo016nHHisx6j/WXPsaCBLyepM+mllSUiJZ4bB8bozHtWgccAs0XnIyuuPzCerkpoHMANmvR4+k6/Pzzz9L2OuVnuaey9H45q7o8ezuZhwIehoh2+2WDz74IGkeETX4g+giw+N1tNdWVPf4EJDMaNQWh4jI/v36ScSMuXSQdqizfDm6090WXewYYdr39AkTbPEsWrRI0kBe2sE4+Nnw3HnHHbbrlO71Smc0droujip0lzYAcumll9rm6dyunWTSsK5uMeqY7bP33rZ5EomEZLrd8pS55zSQe0CmoprLUXQxIgry6aef2uYRERk5cqR0Nf19MTUnENaiceM3mv5xGgd4+imnSJqpy6XULHglzDObhi6uHH/MMY54TpgwQbqYcl9E59ET0VM1R6Lz6b0gWR6P4wXWiooKyY1GJRPdNfeZZ2eYGW9HHXKIo/ItJBIJaRaLydnoYqS1uHE4uqOe5fU2WmxrYWGhRL3eav1eQRfuBoJcP3lyo3BY+PLLLyXd7ZaBIH9DQypygkFH8fR7EolEQgb16SMTAgH5COQ5kObhsLz00kt7+tZS2MNI+RG7H7Yc2t8LUg7trsVPP/0kOcGgXAJykjEc1qGO7b0gg3r2dMzRPD1drtmBgSzmS75pWpptnhdffFG8IJtQp+U/2xnH7UDmo8lf9raZjOO9996Tfn6/tEF3/L5HHTErGcerxigSkKtQB8TndidthN13331yTiBQbTxau86122u9MZK2mL+vAbny8suTrlPL7GxpvRP9I6gT2srjSdpxXrhwoXRPS5Pz0WRWCfQYYW0n+imQ4WYMZqCJonw2DNjp06dLa5D7TLkPow5tleE9D92REzQ5SwuQ6667LikOC0ceeaT0NAbx1nra7A50RzoD+1Oyx3CcijpLvdHEPAKyGV08CYOcb3ia2XyObrjhBgnUKruha1+QfjbDTkpLSyXd1KWwAY6b0bj0PAfJyEIg5+xEfY5Fd87s4uuvv5Z01AFLQ5O3WWUXogtpaeju9nAHCcJERLLcbpmMLqRt76i/gy6w7AUyevRoRzyZwWB10qzteSrNWPODpPv9jnjygkG5wzyfuSCfUbNT3w9kJrqY5wFZsWKFI6433nhDmrtc0t+0URHI1+gcmwMS9HikuLjYEYeIOn5+NPFdCzOO+6IO4N3meZ0+fbpjHhGRhx9+WA6tY0zPA8mPRBqFw8JBQ4dKH2qSnRWacXD1VVc1Ks/uwpw5c6R7NLrN6aRXQfbt1m1P31oKexgpP2L3oz6fz6k0XAr/A9i4cSPN/H5+Bg5ApXTygB6otMD6DRscc1RVVJC1E+/LBuIOdBMLCwtxo3qCK4GetV7zAF1R2Y5coLi42BZHWVkZERHKTDlrUbmPJub1QcDP5vd8oBiIJxJJayeWlZURNp+pRPVFtxdNykF1IIvM32GgzEa9tpaXE9vJ96YDLhHKysqS4igrKyPscrEebTerTl1qvacHKq1j9eEmVBM0WZ3G0tJS3NTI2awB9kXHgAvtozXmtQxUvsVOuwGsXbuWCNou9QnytEYlbuzqjyYSCeLm85sNT09qdNliQHvDYakmltl8jjZv3kyIHWi+GWQCJaWltnhKS0tJoP2R0cD7mqFSLRUOdDQFfRZ3hDycacT++uuvpKFjKwHUFiHLQMd9qbmXzZs3O2ACtwgeoA2qZVobndE5KB+d350gXllJGTq/bc/jBVqg0lcJh3qdUlVFDvosFqAyW6B93xudZ9PQviwqKqqzjJ3Fhg0biIiQAQxFn91uqORVE8PptH8A1q1bh6DfAenAOcDf0Hb71fxv1apVjnkAfvnll23Gm4WOQFGSc/WOsGblSvpAtY59BtAS+G7Zskbl2V1YuXIlPdhWoqwH8NOaNfV8IoUUUtjd2BmbpE6sWLGCb7/9lq1bt5JIbPsVH4/HKSsrY926dcyZM4dZs2Y5vtEU9hw6dOjAyspKTgduQw2k71Ftxv2Bvnttr+aaPNJzc/lq5codvu8rIOZAn7Fjx454gW9RQ2UKqmcIsAr4CHgcuA5oY1NTNzc3lzUuF82AhcBBqPP8DDAcuAFdGADVqG0OxIJBvN7kHsesrCy+CASgqgo/anC9DoxEDaSI4Q8ATc1nfvZ6yW/SpM7yGqxTVharioupYseTxjdApdtNTk5OUhzZ2dmsrazkeOA+1GjsifbHRNQBeBTojzptv6LGZdjvT1oXNC8vj3KXi0UiAAwDTgHGoEbk34FTzXuXom2Y17Tpb8rZGQwZMoQpH3/MFtSJaFbHe95GF2vsrjC63W7CHg/eeJwmaFu9gd57F+BD4GtUo9hjXm+atTNLSL9F27ZtKUX1mht6EgUdCx1s6h6np6fjRjU6F6MGZF34GB0POXl5tngAPC4Xn5mx0BC+ALwezw7fVx+6d+/OemACqnn9CDrWAD4B1qMO4FzzXidwhUKsKy3lW9SBbl7rtZnAPqjO8pEO5+/0zEy8Gzawqg6edcB36MJGIC3NEU8wLY0FBQWchOqz3ghciY6N19B5fCm6gGdXm9pCr169+NXtpiqRYCG6ALASdaQLUK3o3NzcBsvYWZ4g6vCtBq5BHfYgOp8XofNHY6B///5chLZbbcdsFtC1TZtG4bBwwMiRPP/QQ3yH6pPPRm2GK8aNa1Se3YXBgwfz56oqfqFmYXqK283QoUP35G2lkEIKtZHsVm88Hpe//vWvO5XhOJUU6o+DiyZNkpGhkNwOsg+aZOQZkCbhsONYLxGRp556SsLoUeD6jvttNsf9nEhNxONxyQmHZSKaZCYDjctthx5vnYTGaEbBdsxkPB6XNjk5cpU5PpZAjzHvbY7KjUMzwa439fkzyMSTT06aZ+3atZIeCEghegT3OlMHr7l/SxbkQnP0aytIfihkK2bulhtvlCZozGpDRzLj5ohjbiyWdKKRRCIh3Vu3lrfN/b+Pama2RmNA26EZewvRmNo8kNvdbjnpqKOSrk95eblkRyLbxE0+gcaZNkOPglvx3H1Bwl6v7eym8XhcYqh+73A07q+9OWLYH03UFEVjAfv06WOLQ0Rk0umnSwjNpJyFZlCOovG5VubUduaKgNxx++22eAoKCiSMHvVtaCx8bHjefvtt23Vq2bSptET1Z+tKRrYKqo8lO0nSMuG44ySEZiGvrz7L0SPB559/vm0eEZEWaWlyKzVSSt1BDkDjWcNkyzMAACAASURBVANmHAZBNm3a5IjnlltukTQ0hroXyBsgP6JJlXKgOgO70xjNhx56SHymrB4gX5r2WmSenRh65PgOB7HUIiKPPPKIxNDwiZXo95DPjO3nDedEkJYOjp7XxqDevaWjabthaGb6Fub5ubYRj84O6N1buoP8C9W83Q/Nur4/SPsmTRqNp6qqSrq2aiWnoIkJ4yCvoImhnDyjdWHz5s3SvlkzCVIT6nDg4MG7RcZxV+GmyZOlSSgk5/r9Mioclla5uY4TnaXw+0fKj9j9aLQY2hdeeKE6g3GPHj1k0KBB0rlzZxkwYIAMGTJEevToUe3Ijh071lb21mSRcmh3PSoqKuSsE0+UzEBAjojFZGhamuTGYjJt6tRGKb+qqkpygkE5hLrjDMtBRoPkBAK2svTWxj133SUR8yXbyRiPXmOs5BnDv0OLFo4Si9x+661ykMsl3dC44yvNF3sGmh36QWPIngaS6/PZzjh77GGHyQ1oEpEeaEzz4yC3gjyCxob2NwbZAyDDBwywxbN+/XoJ+3zSEk2W9DIaZ9zNlH8dmgToetOGk6+80hbPA/ffL2PDYTnbtNXJ5mcu6qQ1R2NEQ8aIbReJ2F5QufLSS6W56YM4mjX1AjSWco4Zd3eijuG4gw+2xWGhZ/fukmHGwM3oosknqDTQGOPYBEAKCgpscyxZsqQ6a+5E1DEPoDqnAdNXR1GjT7tx40bbXGMPOUQ1P9Hs3b1MO7U2Y2Mj6rTnxmKOnqP33ntPwqbcU0A+RbPAzjBt186MiUyfzzaHiMjGjRsljDpghWZsjUO1ol9CF6C6mjnDaezk9OnTJYwuCHYxc4+lpfqgabeDDzjAEYeFnGBQuqNJ6QaYthqHJtmKgBx77LGOOcrKyiQvGpUM0z4hUx/LYc9C9XtLSkoc8VRVVUluMCgHoAm6BP2usBY6Hjf8r732muM6iWjiuG5t2khTl0t6oItqGW63HDd2bKNmBS4sLJQ2OTnVKgLHo4sATSKRRs8MXFBQIMcefrgE3W7xgbTPy7OVJHBnUFlZKc8//7xceuml8tZbb/0h5IEWLVokd9xxh9xyyy2NEkOdwu8fKT9i96PRHNqTTjpJunTpIjfeeKNUVVVJcXGxdO/eXS655BIR0Z2PadOmSa9evWTgwIGOjKadRcqh3X1YtWqVTJ06VV599VVHsjZ1YdmyZZLp8UgrNClQM3PtbwzaDI/HcUbOeDwuRx96qLRBd64eBikwhtEcNNNsU5CcaNTR6mtJSYns1aWLjDCGnQ91mJujO5gh41j0cLnkovPOs82zePFiSfd45EiQ24wh1AHd7etsDMor0AyaaS6XvP/++7a5Hrr/fslyuSRGzS4wtYxXvzEou7dta1uqZcuWLdKlVSu5xOWSNNR5nYQmZtkPlRsZAdISZHwgIIcfdJBtQ6m4uFj6du4suaYublMfq05WopumGRmOtCfLy8vlwH32kWNBHkUddMuBTUMT2swByfX7HRuXN117rURAXNRIwWSZn1Hz/yDIszaljiwUFxdLi9xc8VPjIGebsmO1HBunz6uIyIUXXCBBU6bbPEvuWs9VFGTlypWOef71r39JwNQlfTtH02/a8M0333TMIyJy1113Vd972PSV39Rpv/79G834Ly0tlWYZGeI3/RKkJklTYzizFtauXSu5sZhETNlppm8iIFnhsKxatapReNasWSM5gYCkodnbz0IXoXoYrnvuuadReCxUVVXJzJkzZdJZZ8lpJ58sX3zxRaOWX5tnypQpMnTgQBk8YIDcf//9jZbduC5UVlamHDIHSNmOKVhIjYXdj0ZLCvXtt98SCoW46KKL8Hg8RCIROnXqxNy5cwHw+/0cc8wxXHLJJWzcuJGnn366kQ5Hp7CnUVVVxezZs5kxZQozp01j8eLFjVp+x44deWrGDDa6XOwHvGmugcAGl4t/Tp9O586dHXHMmDGDj15/nSgawzYRE9+FxgPPQhNzBIuLueC002zzhMNhHnvuOd5HE/L0Ay4GLjflZ5r3rQwEuOXOO23zrF69mmZ+PwOAO9AYzFw0tjEXjXedgiZL6RkI8OOPP9rmOvvcc2nSsiUJc/+VaDKjTGriaiuAex57jGg0aosjGo3y8ttv8xBwEfASsByNowwD76Pxz8OBD30+np0xA5fLVW95DSESifD6nDlsRmOOo+g4CJmrHNgKTH35ZZo3b15/QTvA008/TWLRInqicX7HoLGLq9H44I3A4cBzFRVMPOmkpBNc1cbfrr6aSE4OQXSsfQJMQ+NMJ5p6/T971x0eZZW93+l90hPS6CRD76h0EBRQBKkWUBQrWLCL6wqKfVdXxLXhKva6iGJBxVUQBGEBBRGkd5ASCAkJySTz/v4495sMbHQl3w26/uZ9nnkm+QLfO/fe8925595zztuyQwdcMGpUjTkA6Tun0wkbJCe3LSQPuTskP5cArBYL8vLyTPEAwK233QZA8v7cELv2QWzOCiC/ZUvk1jBPNxahkJQfS4fkux8FUArgBYiNE1JPQAeOFhXBY7EgAskxNAro2AFEjh5F2GQBJQN79uxByZEj6ATpMy+kUFwOgG1r14K/Im/412Dfvn0oKS5GCDImbkh7QgCOlpRg3759WniysrKwo7AQqVlZeAHAOwCmA9gM4O2PPsJ1112nhcfAggULMOnGG/HKCy/gjVdfxaSbbtJWpCkWVqsVFosFzspK2MNhWC2WGs9rvwSSePnll9GzXTt0yM/H+LFjsWvXrv/+H+OII444fu84Uc+4efPmHDhw4DHXbrnlFoZCoWNOY8vKyti2bVsOHjz4RClOGPET2pOD8845h+3tdr4ICZtMc7k4U2NIeTgcZkYgwI/wnyHHnwBM8/lMh3r1aN+eyQC/rYbDeEUgsjo+m41btmypMdf5Q4fSBdExnKBOLbLVSck/1EmtDzB1KndO796cpk56EiBSLX0hkg/nQk5rk9Qp0AyAp9ZQiogklyxZQoc68cuEyNy8CtGaTEbVqfP555xTYw6SfP3113mKxcJsSAieB3LabOR+DlJtTLbbTZ8AXnXVVYTqn4chuowVkJBTr/gwbFsDnVsDkUiEbRs35mw1/vcrG1sOkWwpgkQIpAEcDrBLIMCZM2fWmG/37t0MQvIk71OncU2UbbwA8EY1RmZPf3bs2EGvuu9wNUaZ6hSzk7ruBzhZg77lKR060KuelxWoSkF4CFWntqtXrzbNk9+wIX2Q0PkfIKHolwHcAMk99QA8pX170zy7d++m22qlXz2T/SDRB49DwloTYK5OQCw6hELsrsYlRT0/KcoWcwA+8cQTWnhaN2rEDpCw9hSAXdR7c0gEQrPcXC08JNmne3cGIXnHr0F0To2IgKNHj2rjWbVqFZNdLg5W905Utt4kO1srD0neOH480yARFBZl6yOOW2fpwP2TJ7O5x8MPILnOEywWNsjIMJXq8HP4/vvvWS89nQlWK9uGQty/f792jt8K8bVjHAbitnDyoS3kuEOHDhw0aNAx16ZNm8ZQKMSlS5cec33w4MFsr2EB8N8Qd2hrH0uXLmW203lMfuuXABukpWkLj/vwww/ZwmL5WUeztcXC999/v8b3LygooNtqZbOfuX/sa5pyoh577LEa8zmtVqYCnKoWKHmQAkDJakE5Uf18Wtu2Nbp/eXk5HTYbp0Mc186QcNzY4jmjIEWCWiiHLcnl4p49e2rEd+0VV0QLvHRAVdEkQhzbXEhIo8NiMZUv169zZ94BySX0QULDL1UL/1bqd59yNibVMFfXQILNRidQrT7j7UA0vLqm2Lp1a1Q/0wdxmN8FWAdSIKotREfzYeXIPAPwQhObgD179owW1EpTTsVAxZcAKU7mAjhp0qQac5Bkjx496ISEtnsgebNG4aQAJHQ/DWCiydxWktGQ3OoKknVVzkyP7t1NcUQiEToh+sMHIc75/ZDNmlxIzubFkDBas3j4wQeZANnkygT4FMBPlV0/AdkIaNWokWmeQ4cORUOM/ZANjV2QvOAk9SyFsrJM8xQUFNClnv1UgJtRVbArXdmHG+Du3btNcx09epQO9dzEzj/Pqzb9WWOxpssuvJCDVf+1gszhXoBtbTa++uqr2niMDY6g6iePelaDFgtXrlypjae4uJhJHg+3HvcMjXA4+NeHH9bGQ8rzlOb1MlHZRDLAjhr06n9rfPzxx8xKSmL3du20p1zF8b+JuB9x8qEt5DgrKwvbt29HWVlZ9FpOTg5I4scffzzm35aXl6PchGZoHL8fLF++HL0qK4/R0ewOYE9BQY31Wo/H5s2b0f4XQuA6kNi8eXON73/w4EF4rFbU/xX/tlHM/6kJwuEwbJEIDkBCF5MhcgkPABgK0WvMhoQB7qyhll1xcTE8Nhv2QcKa3QDOxrGSDAMhIaA2iGRMqtNZY43GPdu2IaI+e38cKzFzFoD9UBq0qHm/AcCe3btRCSAPoslpA/APAK9DJEAKITJEyQD2mdQBLFM2fXo1f+sJCQE1E/h38OBBpDudWArRYfRAwqgnQ6R6DkDCJdtB+jMTwEET4Znr1q1DfUg/ZQEYCZFoaQ8JNT2kPsPixYtrzAEAmzZtgh2ie2wDcI663hgiqVIOCW+tNKs9SqJM3a9rNX/vB4AANh733XOiKC0thQPSTz9AxmoiREYlAGAjgA4Qe6DJMN2tGzaAkDkmBcBVEGmv0RDZnqMAduzebYoDEO3MBMjz74HIUmWiSud0F4CDJjVoAWDr1q3wQZ7HNkB0fs2B9FkqJOVh/fr1prm2qTloGI6dfwZA+m3p0qWmOQx8v3w5wpD5ZimAlyE23biyEqtXrdLH8/33SFSawX8D8AaU9jKJFStWaOPZvHkz6tjtqHvc9f7hMFaanA+OR2FhIUpKShACsAeSnrJh7VqtHL8Fnrj/ftx+8CB2/fCDVluLI444zOOEHdpOnTqhpKQEDz/8cFR/1sg9+uCDD6Jf9hs3bsSWLVtQpwaal3H8/hAKhbDYZkNlzLVvAST6/fD5fFo4srKy8MMv5A2ttliQlVWdiuevQzAYxNFIBHt+xb/dBVlUBAKBGnHZ7XZUQPQFnRCdzEcAPAHgPUhunuHsptZQV9fn86GkogKJ6n5hSI5pLOZDLcIhC8uD4XCN25Scng4bJLd0gbqngQWQBW0xgAiJhISEGnEAQHJKCuwQ3Uc3pG2TANwAoAFkE+AnxZVoUgvSYbWiHKL7eTyWAqjEse08UQQCARRUVKApxKbCEEf5LxAHww6gLkQ/MwLRuAwmJtaYLycnBzsguc17AbwNydleDLG3JEh/mtU4rVOnDsKoatMidX0vRJ/aCbETywlqKx8Pi8UCp7rf8mr+vkC9Z5nMofV4PKiA5Gc3hmhmvgTJcd4P6c81EHswm9tYR33WPer1PsSJfhfyDDkhus9mkZWVhULIl/wRAHMhn/95iK2lAgiY1IYFxOaOADgI0YQ1XOSDAL5Tvx8GUF+D1ml2djYsAD497voCyFzRtGlT0xwGGublwQlxxgcDuB5i0zusVjTUlEsNSO2IQpVPfRuASyHfPUUWi+maEbHIycnBrnAYx2+XLbTZ0KRlS208gHzXOhwOrIHk1zsAZObkaOX4LXDBFVfgZpsN9vR0tGnT5rf+OHHEEUcsTvSod+vWrWzZsiVDoRC7devGsrIykmTfvn0ZCoV4ySWX8MEHH2TXrl0ZCoV466231vxc+VciHnJc+4hEIux1yikcYLXyMxViWtfp5PSnn9bGcfToUSa63VxcTWjhUoCJLpfpMJ/2eXlMUKGRvxRy3BpgwG7nmjVrasw14PTT6YXkXY1AVdhxEBKGXFeFl73++us15ujdsSOfhYSzJkDCdMdA8jOvheTspqq/vwKwRf36NQ4R/+KLL+hQoaQZiucLgNPV7y7FM9Ck5Mhzzz3HXhYLUyFSTYacSkvVX0Mh4dUZdjtXrFhhimvEiBGEuu+rMWGM8yChswCYV79+je8fiUSYn53Nz9S4P6vu/xEkz3k3JAy5LiQv+Ey/ny+bqEC8fv16BtVYj4OEtLZUNvAQwHvV5ygpKakxB0muXr2aPhXK2l+NUTt17zwVYugDOG7cOFM8JNksL48eZds7UJXn/roaNyugRQu7bkYGEwEeArgAEr7fX809hmZ0s8aNTfNs3ryZHouFiRAJopZq/O+GVHQPAnxcU7Xe5nXrsiuqKg5bY+aDPIBTpkzRwhPKymIb9ZzmqDmvrvq9FcBGaWlaeEiyXYsWDEBCwL+EhGwbVZUPHz6sjWfRokVMczrZG5LXagN4PqTqeU2ruP8cRg8bxjqQ9AYnJEWgZ6dO2qVubhw3jt1cLq6ASGs9ArBOQoKWcPDjMW/ePCa7XPQBzElJMVWP4veEsrIyLTn7cfwxEPcjTj605dCS5GeffcaOHTuyXbt20WtffvklmzZtylAoxFAoxPz8fLZp00a7jlp1iDu0JwdHjhzh/VOm8LRmzdi/a1fOnj1bO8fMmTOZaLPx7+oLtwCizZhks/Htt982ff8ZM2awrsXCbpBcr9PVAi8VYH1Inp5RsKmHyfzvlStX0q8W943UosvIM8tQvyd6PKYK9Lzzzjs81e/nrRBpI796z1XtCULyay8GONDr5VNPPlljrkgkwrZ5efSpNiSoRauRO+sE6LJY+OWXX9aYgxQ7S/X5eL/6/P0hep0tIYWo0iDFjU4xUeDKwMGDB+lUC30fJA8vXTloTvWq6fxiYOpjj3GQx8MrlAN2v7LtiHKc2kOc568guq1mN20yUlLoAXgepChPjnIshqlx6qiprkFGMEi3srle6tUXknMYVG3Vode5du1aOlElddRa2ZxPcTTSkAdKkvPnz6dH2dkyVDnOi1GlV61LtuW6q66K9tEAiFZ1krKDJjk52hym5cuX02+1spt6XoNq7mkLMJSTo01P9YsvvqBHOa8eyEaaB5K774E+uSNSckHrp6dHC10lqrGZNWuWNg4Db735JrMSE9nQ6WSa3c52eXlctWqVdp7y8nI+eN99bJKZyfppabzjlltqRVanoqKCD957L+unpdHvcnFwnz61ug6KRCLaC2j9HhBfO8ZhIG4LJx9aHVqSLCws5Oeff37MtUWLFnHs2LE888wzefXVV/P777+v6e1PCHGHtvZRWVnJ56ZPZ7smTWi1WOi22zl8wAB+88032rkWLVrEXp060Wax0G6xsEeHDvz666+13Lu8vJw9O3ViQC2ImwG8AeBNkKrAht6l3+Hgd999Z5rvkosvpg9yemA4galqYe7UsAgLh8Ps2rYtL7HbmQs5kctSPBnK4UwHeI3VylaNGpleJO3cuZONMjNpQ5WuqaGn6bRYtJ3YL1iwgIlOJ5uqMclSjqxfLZqzk5K0aI+S5LfffksHqjRU/co2bADfeOMN0/cvLi5m27w83m638yZUnZYlQk5kUgEuBNjA6+WLL7xgmu+jjz6iRzn/5wE8B+AFEG1nv9Vq2kE3cPToUSa4XHTFtMmhnh87oHX+/+qrr+hQ97XFvOpmZbGiokIbz8svvxw9sQ+olwtyUv/uu+9q44lEIrxlwgRald0ZOsintGqlvRrs5ZdfHo2eMDR2HVar9rn7qaeeYordTo/acPACTLHZ+Le//U0rD0n+9NNPvPrKK9m2SRP27tKFX331lfbTTAO7d+/m1KlTee+99/5hCgEVFRVxz549rKys/K0/yv8k4mvHOAzEbeHkQ5tD++GHH3Lz5s1mP49WxB3a2kVlZSUvOPdcnur18hOAYUgl0GkWC9M9Hr6j4eQ0FleMHUsfRKalkVoYjR0zRtv9J06cSA/Ae9TJSy6q5DJuUJyZiYmmed577z0G1H1zUBWOGYw5WQg4HNy5c6cpnu3btzPZ4WCe6qsOkGqtXdXCvD7AgNWq5WTh6NGjbB8KMV85mAHIyVITxf3FF1+Y5iDllLZOIMAhENkUIxR8CaSybtcOHbQsYMPhMNMSEugB2FGNSxKqwmddFgsPHTpkmuenn35im/x8BiCnV1MA/h0SmulWjuBTGiRUVqxYwVSPhxerjYzbAL4IcLxq1xUA6wSD3L59u2mu9evXR52XICRcNkc56G6A06dPN81BVjnOxmZDV2UDbuXU3nzTTVp4SDIjOZl2ZdeeGMfWrpxnXZg9ezYDkNDSPwN8FOAp6hnq36+fNp4Rw4fTCwk/nwkJeX8LIq0UgPnoAwPz589nstvNWyAn6CmQ09lbAKa43Zw7d64WHpJ8//33meTx8FSLhY0hp825bjdHDR2qdXOjoqKC48eOpddmY5bFwkyLhQG3W8umU3VYuHAhx40dy8tHjeKcOXNqxUHfsWMHh/XvT7/TyWSXi40zM/nyiy9q5yHJXbt2ccrkyRwzfDinPf641nDw3xrxtWMcBuK2cPKhzaHt1asXW7RoUSu6ZTVF3KGtXbz00kvs6POxFP+Za7oCYJLHw4MHD2rhmjhxItMgoZgvQOQYvlaLcx352JFIhMlWK29QC/wXIGGSnSB5rW0hp7VugHPmzDHF1TAzk0mQk9KJEOkPQ86ir7ruAHjj9deb4nnm6afZVC2G/wY5pTVOhP+mrjcFeO/dd5viIcm77rwzemo6BHIKeA5E4igHIgtkVuOUJK+/5hr2x7ESRMarGHLy/OGHH5rmeeCBB+gC2EC1KU3ZmqHX6QPYs2tX0zwkmZuczN6o2mgwXtPU+/z5801zjDjrLI5W47EZEq6dB/BCgOuUbQyzWHjrhAmmudK9XmZCcrUNOa8IwJeV4+kGojUWzGD40KEMAOytntnmaoxOgYTz2wDu3bvXNM8999xDu3pebgO4DaI/ez2qTp9nzJhhmicSidAPkaEqU/a8V/XfU4rLbNg+KZsohiZxB+XAtlDj8ieInJfHbjfNU1lZyUZ16vB2yCmzH3Kq7VdjczvA3JQULc7mli1bmOx2Mw2yyeBAVWpAG5uN999zj2kOAzddey2T1DMDSDRKFsAkq1VrCDVJ3jd5MhMgm13Zyq7HXXqpVo6ioiI2zsrin6xWLgH4GcDPATbwePiSBruOxcqVK5keCLCbzcYzAJ7qdDI/N5f79u3TymMgHA5z2bJlpuTiTgTxtePvE3v37uUFgwaxdYMGHD106EnRPo7bwsmHNoe2RYsWHGxCJ7E2EHdoaxentWjB96txLIzX+V4vp5rQa41FmsPBmQBPU4vxAWrhOgtgqobF18yZM+mG5Kz9STkwQyGntV6Aj0NOTs8G2NhEMaDvvvtOQvsA9qymzw5BTrWSAfqdTlO78R3y85kECSs1TkyvQFWhpnFQ+a4pKTXmIGUhnurxMA2SjxkC+CZET9NwqBsBfOutt0zzBKzWaB5jda+nATarW9cUD0m6bDa2VP1khJt7IQ6mC7LR4Yb5XNDdu3fTDdHT9aq+u0gt+j2QYjNNTLZn//79THC52BGiC9sUEp79F8gpai/IBsfZAFP9flMOxpYtW+iGbCxUt+lwoVr8P2xS3zISiURD2pMBzlX3D0NSBAao52joueea4iFJj81GHyTf/Pj2nKvGyet0muZ57LHH6IZsbH2untcgwDsUVwuA6amppnl6dO/ODDUXtAd4RN3/e2XTb6p+3bhxoymeTz/9lE0dDgaVbTeAbAbVV33mB9jKbtdSc2HizTfzFIgz61F2losqBzorMVFLXnBRURG9djuz1JzaBLJBGFRzaScN+fsGdu3aRTdkI+NqyKm2V7VHR9qLgaeefJIDPR7OUN8NHSEbHf8C2KhOHa3hx2d26cI+kO/xvyib6Gm1atlIOx6FhYVMdjiiqSJLly7VznE84mvH3x8ikQg7NW/OG+x2LgU43uFg9/btay0VwUDcFk4+tOrQ7t27F2GT+oJx/O/gux9/RM9f+HuvkhItOnbl5eXYHw6jLkTq4UMAH0B0ALMAFFRUmNa8nTt3LrIA/BuiA0sAbwH4M4AJ6ucMAE0AFP70U415Nm3ahEqIzuTgav6eANHVPASA5eUoLS2tMdf6rVthAdAKIvnxMIBnADwLkWlJg0h37Dp40JQu9OHDh1FcWooiiNzIowBGqHdCNCcdAJYsWVJjDgAoKipCWSSCdr/wb3oC2GVSgxYALJWVcEKkgAIA/gmRZ4lAJJf2QTQ8D5jU6/zkk0+QBJEbIURC5UUAoxRXZwCHtm83xbFt2zbk2O1YAaAHgK0AZgK4GcALAFZC9IPXAgiXl+Pw4cM15lq+fDlSAJyL6nV6hwNwAfjg/fdrzAEAJSUliABoCSAdVXrBdoie6o8QGaLFX31ligcA7EqT+IJq/jYKYgfQoKv+8ssvIwui0/oXANMgWsSPQNoyBMDB/ftN83y7YgV6QaS7boVoqAJAc8jz8x1EcunLL780xfP999+jeziMw5DnKAR5btpA5rliAL0qKrB69WpTPADw7/nzsQ3yDF0N4BWInrMDIqkTKSvDnj2/Rpjtl/HDDz8gicReSL+tgUhfhSFz6oo1a0xzGJg3bx5SIePyJGT+7g+RcJo7d642ngVz5mBoaSkeg3zPfQN5jsoBFBUWauk3ACCJuYsWYbniuRkiV1cSieCz2bO1cMTi/vvvR1Y4jEKIPvG4ceO0c8Tx+8fu3buxaeNGPFJRgQ4AHg+HsWLVKhw6dOi3/mhxnCScsEN7yy234NChQ7jpppuwY8eO2vhMcfzO4HW5cPAX/l5gscCrQc/QbrfDDlkg7wewDsAGyOLIpl5ut9sUR0JCAkogzosTstjaCqAC4uSmQrRAKwHQZqsxj8vlgg2iM/tzy4Q9kAVFBQCn01lzLocDhDhGpQC+hizuFip+4yEnCbsJXVCXy4UKyOLRA9GcBGR89kE2IWwQDUIzcLlcqIS05edwCIDdxPgYqASi4xSGOLQvQNpXAdG2jMC83aWnp6MYVXa3AKLNuQwyPhUwZ29Qn7GEhF/d244q7dbl6vf9kAV6WWUlXC5XjbkSEhIQBvBzWwp7Ic9x47JmgwAAIABJREFUQlJSjTkAeS4skOd0H2SMDGyFOEx2AG6PxxQPIOMcAbC7mr/tgthKxDQLkJKSgkPqXnUhm3YzIA6MC6KxbLGe8Ffzf8DpcuEAAD9EV9cAAWyBzHWVENs0A4/Hg4MWCywQvdsfALwG2UAxth8Pqn9nFv5gEF6IbS1WfPMhz5ANQHFFBbxe7y/c4dchEAigDDIehwF8CRknO2TcPCbm6+ORnJyMMsiYFAAogfRhhfqbLiSkpmKXxYIsyMbaYsgzlASgtLJSm568xWJBss+HZBw7/7ghtq8bbdq0wTYAr0K+83RqEcfxv4NgMIjSSAS71O/bAFSS2uw6jv8BnOhR7yOPPMKRI0dG5Xm6devGIUOG8IILLqj2deGFF5o8XP7viIcc1y4uHz2a99hs1YZ+RgA29/v5r3/9SwtX83r1OAGibRpU4V7PQPJam+bmmr7/zp076Qd4MyQU+HwVrhZUIZLPQgoC1QM4bNiwGvMcPHiQXouFPki+30/H9dtcVBWGatGokak2jR46lDmQXMneKjTTqt5bAzxVhcv169LFFA9JntqiBetBQnFzoPRgIeGzRnjh2rVrTfM0qVOHM6qxN+N1GcBLRo82zRNq1Cha3CpDhawZYdtG7rGOPMNIJMIEFX5nFBoyKkU3heS8XnzxxaY4wuEwc1NSOBQSvjpFcRm6oy8re78QYOeWLU1xlZWV0a3uv+24sTkKkYryAaZ1gkky0eulG2AXgGdBcurfVM9VP/X86shtzc7OjuZTH4ppz35U5aWHQiHTPIZW8GyAhyEh+xcA/E7x+gCeddZZpnmmTp1KN8DX1D2fhWjqjlVzj6HfarZy77Zt25jocLC9sucsqErkqKpKnuRwmA5tJsnXXnuNLR0O2lFVGdoPyaFtCrDPKaeY5iDleW2UlRWVBAqql1PNC+Muu0wLDynPbVZiInPV8+RTc1HQ6dRaSOnrr79mPa+XK9Vz00LZxN1WKwf37auNhyTvvPVWdnQ6maq+JxoAbOh2m05H+TmMufhiZnu97HHqqSelcnN87fj7xF8feIC5Xi9H+XzM9nr5hKZUuF9C3BZOPrTl0Obn50d1Zn/NS8cC4L8h7tDWLn744Qemer38ApKHtQbgRoAVAG9yONilTRtteQorVqxgwGrlSEhuz7/UItxvsXDZsmVaOOpmZLAzRMakFcDBaqF8BsQJvFMtksxWtx1xzjl0Q5zWupD83I8A3qocJkOu48033zTFs3jxYqZYrQxCnPQJAAdBKtsOUs5TjsWiJYdt3rx5DKAqn6yNcl7ckGI9fTt3Ns1BSl5eEsD1ALcCnAHwFYCFkGImXkBLpd5Vq1bRD8klC6KqyEwQkrvtA/jss89qaBF5zTXX0A+paNtQ9eFgSHGtIKBFd/K+e+5hL7udGcreVimHZg3EyW0AsJXLxVdffdU016ABA5gJcSwfBfiOWiC3Ufae7vOZ5iDJd999lzZI7uIZaoEcghRW8yrb07GI3bx58zEbGhMg1cKNjTUfoK34XVZ6OgMA/6nmUUIc2jZqTtBhC5WVlfQrO34JkgeaDslr/FC1qV3bthpaQ44eMoSDIRuBLlTloOdAKnkPHzBAC09ZWRlPbdmSp6j7G7JhTSDVlBctWqSFhxTpsKDDQRckHzhH2UBuWpqWImSxWLt2LUM5OfQrO89NSuKSJUu0cpDk7TfcwPpeLx+yWPgywHPdbjbIyODWrVu18pSXl/Oqiy9mgsvFPL+fiW43H7r3Xq0cvyXia8ffLxYvXswXXnjhpORSk3Fb+C2gzaF9/PHHOW3atBN61TbiDm3t4+2332aCw0GvWrSkA0ywWNgkN5c//fSTVq5PP/2UWcnJ0eqVmcnJ/Pjjj7Xdf8eOHfSrRWs2pIrp7RDZEZ9aKE2cONE0z969e5keDNKJKokRqJ+diqdfz55aFuNT7rqLWag6rTAqgPrUYuyayy7Ttulw04030q8W+g3VQs8FMCcpiQcOHNDCQUqlY6/qN7fisKl3nZqgf/vb36K6wIbWqTFG548YoY2HJEeMGBEdl6Ba+LutVq5fv17L/UtLS9m1bVsOsNl4mmqPR733BdjF6eTws8/WYnOVlZXMq1+fAVQVBEtRjpLXYtHm/JHk1VdfTaeybyg7MOR0tmzZoo3nqaeeivZXonrZVPtef/11bTzhcJi5mZn0KafMpjjdgNbvpfXr19OvPv8YgJPVPOcGmJmRoe00q7i4mH27dGGew8HrAY5UGwIhh4M9O3bUetJYWFjIi0eMoMduZ4bdTr/NxtaNG/Orr77SxmHghx9+4Pnnnsv0YJCZiYm849Zba61yaiQS4fr167lmzZpaLWQzb948Du7fn907duR9997LwsLCWuGJRCL84osv+Pe//11rcavfA+JrxzgMxG3h5EObQ/t7RNyhrV3s2LGDDTIyeL3dzu2oCjX+CuCpXi/HjByp7Qv4uWefjVb/vUq9ktXi/+knn9TCsXr1aia5XHwAcjJrOJyNoSoyWiy8T4PEDSkbQA61+M6HhHqlqYW/B+CGDRu08FRWVrJpo0bRtnhRVbk3KzWVR48e1cLz6quv0q8+vxEynaq48gC2C4W0yPYsW7aMLuX4JUJOf5uqPvMCTHY6tTlMY8aMiTqxiapdTsXVvkULLRwkOWPGjGg4oQ8SLpmjuBLdbtOhnwaKi4vZqF49uS/kxCdBjVHnU07RUgWWJD/66CMGLBamq3vHVorOBDjx5pu18CxfvpwJViuzVF8ZDrRxatqxVStt+qPvzZrFZLebV0AiAT4BeAnAFI+Hn376qRYOUnSW66en0xfzrCYCdFssXLBggTYeUnR8e/XqRUeM4/z4449r5SAlzSLF749KH9kBJno82qVa5s6dyxSfj3l2O1tCaYg7nbz28strLdx0586dWk9/q8OKFSt4+aWXcszo0fzqq69qxal9d+ZM1ktLY6tAgH0SEpjocvHi4cNZVFSklWfp0qVs07gxG/p8PCMhgekeD8/o3FlLVE112LZtG9977z2uXr26Vu5/POJrxzgMxG3h5ON/wqH95z//yVGjRnHUqFEcPnw4W7RowRUrVnDYsGEcOXLkz572xh3a2sXgvn05yW6vNpfxCMA2Ph/feOMN0zxr1qxhECKbUQ7wR4Br1c+XKqdWxxdW744deVeMU9YbksOWqJyN+wAG7Hbu3LnTFM/hw4ejC/D5MX1WAfCv6noDDfIcJHnd+PH0QrQlu0NCS0+FyJr4AA7q3980R0lJCX02GwOQk7JJkLDWqZCQ3WTIafDDDz1kmis7ISF66tcM4OkA+yhHqZHi79url2meefPm0a5sKwVVchmpqMqjnTRpkmmegwcP0q/s6zI1NiH1c33FeWqHDqZ5SHLSpElRB9MIYTQiD5zQc7pdWlrKQIxURiOAN0LyXL2oOuFcvny5aa56KSnMVTynQvLr70ZV2L4H5uWBSHLTpk1Mcbs5F7I5Y4FsOrQCOAdgitfLXbt2meYhyab16tEPyWddC3APRI/Yp8ZIp4NxWocO0dPsFFSF1c+aNUsbRyQSiY5FY0jodBP1uxN6QsJJOXFOcruZDnA0RC94AkS6p5HDwSl33aWFx8DatWsZqlePVkhkwNB+/bQ7fyR503XXRedVY8Nm+KBBWp3azz77jHU8Hn4A2aTpB/BFgBe53ezfvbs2rg0bNjDN7+drACtRlVc/xWZjk+xsLeH0BiKRCG8cN47Jbjf7B4PM8ng4qE8flpSUaOOoDvG14+8Xa9eu5VtvvcV169adFL64LZx81IpDO3/+fN599928+OKLOWTIEJISDjRt2jTToYeTJ0/mG2+8wXPOOYdbt25lJBLhZZddVq1DE3doaw/btm1jstvNYvx8gZ63AHbXkIs17JxzmAJxYMcr5yUTckobVk7GuSZzsTZu3MhEm42Xq3u/FtOO3ZAQ5AS1WJr0pz+Z4powYQLTIMVXquu3fmpxuXLlSlM84XCYNoB1ILmL1wNcAtHWTYWcDNsB02F/06ZNY33lSDyt+u9s5ZD9SXEHAeYmJJjiWbZsGe2QsPa2aoHXXjlNqWpRbjhnZWVlprgaZGXJiS9kI+WIsrX7FY8NYNBmM8VBkpdcfDHdkJzmZIgG5Di1cB2FKqdTx0IswWqNOhcdlU13UPf3A8wIBk1zzJgxgy0gDuXZMQtXQjZr/Gq8zhs0yBTPokWLouHm5+JYzdttqv/SITmHZnHrhAm8BuKQGSkJCern1gAvslh4jwaHad26dXRC9K+PnxNeh2wEjB8/3jQPSf744490o8pJMkK13WpO0IXbbruNfjXXnAfZ6LoQsjHg19ie6668ks0hRQIzAJ6j5p3b1FileL3aIh0qKyuZlZLCACSqxqeeqTHnnafl/gZWr17NgJoXEpU9JygunVEB3dq04Yuq3zIhG59eiDZ1Q5+Pixcv1sIzfuxY/sluZymk/kU9gBPVszvQ5+OzzzyjhYckX3/9dbbx+XhQPT/lAM91ubRFh/wc4mvH3yfenTmTaV4vzw0Gmerx8IMPPqh1zrgtnHxodWj379/PUaNGRSsdxxZ/WrNmDfPz89mpUyd+++23NfqwK1eu5KhRo1hUVMR+/fpFr8+YMYPTp0//j38fd2hrD2+99RbPDQZ/1pklwFKAdqvV9A5vks/HcZATi0yARQCL1YL8e4DXAUzwek1xvPnmmzzDYmEGJP8zclxb7oHs9k8BeLrJE7NWDRrQBqlkWl2/vaMWF3fccYcpnu+//55OSKXhvOPa1AVyuu0FTFeiHtinD/PUYmsc5ISWAPeqBfI9akFmB3jkyJEa80ycODG6OG4D8MyYxUomJEy8MWQzwOwizAhhduLYyrYRyAZBGuSUziySPB42gJzIpqm2EFLsKg2IFrmp6VxmoLS0lBZ1r3yAvdTz1Ey1x8jfNYsLhwxhHYhztOQ4uy5T9uAAmGPSeb7tttuYrngWVfMMjUBVES+zodQdmjThvyAns2mQzY1CdW8rwI8B9tSwcTdx4kQmQSqdH9+eMMSRyUlONs1DSji9EZ79oBqb1mpsXNBTWI0kUxMSaIM4L7eoZ+p6yCmtHWCiyXnbQCg7m07I5tMDqNqIdEMc6boaC0MtWrSIdvUchQHuUv1mA7SenN4wYUK08vlByPdprppLB2sqplVcXEy33c5nVV8ZDuD1kLSHiRYL7/rzn7VwNUxP52qAT6i5e42yg/mQDZvBvXtr4SHJQb1785XjnqGVABukp2vjqA7xtePvE63q14/Oqx8A7JifX+uccVs4+fi5ddIJi1KWl5dj7NixWLt2Lfx+Pzp37ozvvvsOe/fuBQBYrVYkJCSgsLAQl1xyCWbPno3s7OwT4njmmWcwfvx4FBcXw+/3R6/7fD5s37692v+zpgZC50ePHq3R//v/hO3btyNSWfmL/8ai3tesWQOLxfKL//aXEIlEYAFAiK6gocRoVdcs6t+YGbMdO3bAQgKo+tyxsMS8l5aWmuIqKyv7WZ7Y6/v27TPFs3HjxujP1uP4YtUst2zZYoqnuLg4Og6E6D7GcsTyrl27tsa6k/v27Tvmd4PHEsNtcG3cuNG07q2B45U/DT6gZvNLLGKfodgxiu07C4BNmzaZ0tE0bM64pw2ie2tw6mrP4cJCUP38S4qplZWVprj2798f/bk6nthra9asMaWzXF5efszzb8xBsdd0fGcY9v1z848FQEVFhZbvpoKCguh9DY3v2Odp3bp1KCoqMs1ToezbAtFptUI0bo02RkzaQZQnLErExncEcOz3A0ls3rwZCQkJprk2b94cvX9svxHmv+ticeDAgei4xz6nFgCHDx/W0m9HjhyRZb6C0Xd2IPoc79u7V88YVVRExyR2/jHGqLi4WNu660hx8X/MC1aIndTm2i6+dvx9ory8PPqc2iDfh7U9TnFb+B3hRD3j559/nvn5+Rw5cmQ0rPj8888/Rp6nqKiI5513HkOhEKdMmXJC9y8sLOQAtStZVFTE/jG5fzNmzOBzzz33H/8nfkJbe9iyZQtT3G4eqeY0wXj9E2DX1q1Nc507YABT1W745WqXui7khDGsTk3OOfNMUxzr169nos3GsZDT0bdi2rFXcSaoE4A7b7/dFNc111zDNIDP/Uy/na12/GsayWCgvLycNsjpZQ5EFuhbdSKTAsnVtAOmq1lOnTqVDdXJwTOq/4ZATktvhYQeBwBmBYOmTjCWLFlCu7p/B0jI4mmqHSnKDlyq78yGHNfPzKQHEu53mTodMXKck9VpTNBqNcVBkheefz49kDDTJIh+7w2Q09KR0BxybLEcE3Kcrt6NkOP0QMA0x/PPP8+WiuNcHBtyPFXxNAQ4zKSe6oIFC+iGnCqNwLHRBztRFXKcbTLMnSRvuvZaToDkn/tRVbzNDznhvhTm0xBIyfFyqnE/fk54W9nClVdeaZqHlO+42JBjo1K0R80Juk4ab7jhBvohESKjICHHl6AqfFtXe8ZfdhmbQ3TE0wAOU+N1k+q3JI9HW/5kRUUFMxITGVBzq9GHo4YO1XJ/AytXroxKRaVCdHyNkGOd1f27tGrFl9TzUhdSk8ALKYTY2Ofj119/rYXn6ksu4V02G0vUfJepxicCcLDPx6efekoLD0m+8sorbOf1shBVEQ7DnU7eOmGCNo7qEF87/j7x1ptvMsPr5chAgGkej9Y6AT+HuC2cfGgLOR46dCibNm3Kbdu2Ra8d79CSUhm3efPmPOOMM07o/nPnzj3GCT4+h7a6xX/coa1dDOzVi1Nstp8NN27v8/G1114zzbN69WoGIc5sGKKhuVI5GFdDQv9WrVplmqdHu3acrByWJEhY1Bj1ex1I6GzAZjMdjldYWBgNh1wEKfyyDhLuNU0t9OomJppuD0mOu/JKeiEFrk6DOOYdIDlmPoD9+/QxzXHkyBF6rdZo8ZJ7lfPyOMRBS1aLy/vvu880V1YwGC0K1QKS79Ub4rA3UYvL03v0MM3z+eefR4tCpaKqqnKKao8P5kPCSfLAgQPiTAK8AlJoqC4kV7uRak8HDZtCJHnHHXdEi0IFUJUHauQd6yjgduTIEQbsdnpVH4UgOre9UVUIKBnmQ6hJMjc5OaoB2h1SyMbYrDGqKt9///2meTZs2MAUt5v/gjjjFvUKQSoeJ3s83LFjh2kekmySnU0fJHR/k5oTpqtxcsD85lMsOrRqxYAa/1TIJo0uOzBQWVkZ1Z/Ng4Q1h1AVeq6j8jkpmwGJbjfTIA7zbZCNofoAm9jtnKRBbi0Wq1evZoPMTFogRaHO6tWrVmRurr3yymhBKMOZHdS/v9bQ5jlz5jDL6+VHkNzW0yG60Ze6XOxz2mnauNatW8c0v5/voGoDqhzgwzYbG9apo7WoVmVlJa8ZO5apbjcHBQKs6/Wyf/fuWgtPVYf42vH3i1WrVvGVV16JV7z+A0ObQ9u2bVueffbZx1yrzqElybPOOostW7Y8oftPnz6dL7zwQvT3FStWcPjw4RwyZAgfffTRav9P3KGtXWzbto1109J4q93OPajKMfwGYDevlxcOGaKtiuXfp02LOhej1StNORxTH3tMC8fKlSuZ5HJxMqq0LA2d2NEA86xWTtLgxJDks88+SyuqNEfTUCU94ga06Y9WVFSwU5s2tKtFsXEaZwdYPydHm2zPjBdeiGrQGu9BxZMHsFXjxqZPTUk5pXUqZyVJOX2N1O8+gIkOhzbN25FKG9alnLBUtQj3AmyZl6eFgxSNU0NKxzgBNBwyv8OhtTLnoIEDo/q9sbq6N2sslvL+++9Hn1VDM9qQ7skGeOM112jhWbp0KQMWCzMhuaxGxWajinO7pk21yfa88/bbTHa7eS0kx/UzgFcCTHa7+eGHH2rhICX6KCc5mf4Ypy9Rtenzzz/XxkNKJdiHH36YbrudVoiu95IlS7RykLJpkxoIHCPbk+zzadcpnzNnDhM9HobsdjYH2NJiYaLDwSsvvlibHcQiEolw8+bNtaJzG4slS5bwogsu4HlDh3Lu3Lm1Itvz5htvMDspiR2CQQ4IBpnkcvH8c87R7qQvWrSIzerVY77fz7ODQWZ5vezZoYNWzehYbNy4ke+88w5XrFhRK/c/HvG1YxwG4rZw8qHNoW3duvWvdmgHDx7MNm3anCjFCSPu0NY+du7cyUvOO48eu52ZdjtT7XZmJiby0b/8Rav2XyQS4V1/+hOTHA5mQMJOEx0O/un227V+wV9//fXR6pW3QQqMdFaLy6RgUFubxl9+OTMB9oxxXhIhp8JegB999JEWnn379rF5gwbR3X1jwZ8IsG56+jERFWYQiUR4zplnRk9p85UTmA4w4HBwzZo1WnhI8ptvvmHQ4ZCiMuplAZiTnq5d27Jfv370KOfcaFvDhg213T8SifDy0aPZyulkd8gpjBdykj4MEga8bNkybXw3TJhAP+REu1vMppBu/dFPP/2UTouFXsgJlnEKfKemDSEDDz34ID3KmW2s2pMEvaemBtasWcOm+fnRjaE2LVty48aNWjlIWYT37dqVTouFNoCNMzJqpSrn3Llz2apBA+a63ezo8TDR5eLQfv24Z88erTzbt29nXm4u3WpOcAFsnJXFzZs3a+UhJQJsxPDhzM/O5qlt2/K9997TznE8/ijrhbVr1/KSiy7ioP79+eyzz2rTpT4ekUiE33zzDd97770/TN8Z+KO1J46aI24LJx/aHNoBAwawRYsWx4SNVOfQFhQUsHnz5jzLZA7Vr0Hcoa197N27l6HcXGapxX4ywGSrlddfeaVWR/OBe+5hU7ebf4ZoqvYAeCfA5m4379WgB0qSW7duZQAS2rwfYH+A7QDOUqcyXoB9Tj/dNM+cOXOYppw9j3LO/UC0OuxpAL0Wi5bd8R5Ka/J0ICqtkwNwoOIM1aunZZyemDqVKZCQtachOpp3QELXEgFmp6ZqCy/seuqp9Crn/21IqGlL1Z7JmmyBJC+88EL6IKfz90E0Tm9QdpDXuLEWjhdffJGtPR4mK4fPoRxAv+IZBrB+erqWxeXkyZPpA/guJJS+vWrPc8oO33rrLQ0tknC/BJuNacrmxkKqNRt6vrpCvhYuXMggRFP5fHX/upCw42SA9evU0bYBVVBQwIDFwqYAH1IcjSF51GYqdx+PH3/8kUlqntsNsARSATbVYuE/qqnkX1PMmzePqW43Z0Iqaj8E8BNIDmooN1fbyVxBQQETrFZ2Ups1FvXeCWDAauXevXu18JDSdwkeTzQ826E2ax7RoH99PCKRCB979FG2aNKErfLzOX/+fO0cJxNPPfEEU9xuTnA4+DDAzn4/OzRtyoKCgt/6o/1PIb52jMNA3BZOPrQ5tA899BDz8/N5V4weX3UO7Y033shQKMQHH3zwRClOGHGHtvYxZuRIpqsTi1aQ/KggwFSrVZtWXkFBARPdbt4OycGaDSm93hZyiprodmsJM81r3JjZAPcpxzILEi7rVs6ZEYps1gFsl5fHvqg6MQ0op8+jXsnKAXjY5ELsu+++o8diYRtUhTWnqvu7IXmHfovFdChjRUUFU3w+toXoCqZCCn40UE76k8p5/+c//2mKh5R8xgBEVuJ4WZMukHBGHaHNkUiEAYgklOGIuZWj+Vdl42ZtLhKJsF2TJuyJKtkPIxzcrxb/XoCn+HycOXOm6TYlWa2crsaioRqfXGXjdwCso6EoFEmOGzeOCRC5lLvVMzsG4CPKBrMzMrTwnNKqFeujSkt3HKSgjR9S0CYJ+orn5DVsyN6QDQajGNVFAE8F2F6DZI+BQX36RGVnYl+rIZEOupznrq1b8zWAXdXzaoTVPwHwbLtdWxrHgP792VbZcV1Ubaj5IRsqp/fsqYWHJFs2bhzN101Q82qKso1169Zp4yGlNoEHVYW0vAA/+eQTrRwG7pg4MfrdMOqCC7Tff926dUz1ePguZJPGp+a9KxwOXjVmjHY+UupILFy4UMtc/UvYsGED//KXv/Cbb76pVR4Dtb12PHr0KJ9++mm++OKLtRJGH4c+xP2Ikw9tDu3+/fvZqVMnhkIhjh8/nnPmzOHZZ5/NUCjEDRs28KOPPuKFF17IUCjE9u3baw9rqg5xh7Z2UV5eTrfNFq3C+BDAwQCbq8XE6CFDtPC89NJLHOh2MwXg+phF3ka1CBvsdh+TX11T+CA6s6eoxVcjgIPUgjwB4Ha18DNTgCoSidCmFlo5apEyDOBi5VwYC6QeAFvVq2eqPVOmTGEy5CQzF+DDqNI4zYackiQCvPaKK0zxLF++nKmQglYOVJ2UJSjH6R7lAA6N0Y6uKa666io6IJsOxy/6P1M8OjZSZs2aRSfkdNENKd61UbWttbLvfibb89NPPzHJ5WIiqvKne0NO7BtBTmodkGrBY00uZL/77ju6IKexhmbvEkiVYz/AT5Vt6zhFT3C56IUUM2qubHsEwBsheqR+mNe7LS8vpxvgn1W/fRZjBwMgGynZ0KfXGQT4qLLrQoAHIBsDj6lnSAdKSkrosliilVmPf50K8J133jHNs2vXLiY5nZyl2vAopPhUH2WHHwPs3KKFhhaRqXY7s5Wj1AHgUkgESiNlh8kaKoWTEl3jU89/BsCFkE0Uv2rTnzWGuldUVETTNvqgqnhbXU0bNbHYv38/A6otNyke3fmgk+68kzc6HGwISYGpA9mYng4w4HJpd5wqKioYqluXjb1eDotRq9CNkpISZiYl8TKHgyler/ZNjepQ22vH8Zdeyh4eD9t7vbz/7rtrlSsOc4j7EScfP+fz/ZKEYLVISUnBk08+iWAwiLlz52LChAnYsGEDAODss8/GjTfeiH//+9/weDx49NFHkZGRYUJUKI7fA8rKylBJggCOALgKwBCI3lsZgIPH6YbWFEVFRUitrMRhAHVjrucAKAaQUlGB4uJi0zx2ACkA9gBIANATwHUADkDalAygAkBhYWGNOSorK0EApRBdRgeAgQBOAdARQBiAC9J/ZUeP1pgHAEpjBKNoAAAgAElEQVRUnxRCPv+p6vppAMoBFKnPUGqy70pKSuAA4IdovHkAXATADemvAkh/Hj50yBQPAOzatQuEjNPxyIJ4gYcPHzbNs2nTJoQB7Ia0oyOAhgAaQewhCcDOnTtNcZSWlsJvt6MCMu5lAH5Uf8tU7xWQsTpqcoz2798PN4CfION0OqRNnQF4FX8YotdnGuEwyiBzQkeIbZ8BYDvkmeUv/Ndfi/Ly8qjNVQLIj/lbKwAlAFIBHFZ6q2ZRCeAogKYAgpC5oBHk+YloYRB7sAII/Mzfs6DHtouKipBgs+Ew5LP3AZAImRcIeVZ1zKeAzHcVkPHoA6ADgH7q9woAFdRhDcChQ4fgslgQAdAcYteDIfNROfR9FwGiL+mA9N14yPxtB1Coqc9isX//flgBXALgasgzumnTJq0cB/ftQ3Y4jF0AvlfX0iHP79FwGGGl8asLJSUl2LJrF64pKcGKFSu03jsWhYWFOHLkCO4Mh5FrtWLLli21xnWysHbVKlxUWorBJSVYu2rVb/1x4ojjfwIn7NACQPv27fH+++/joosuQmZmJignvSCJlJQUDBs2DLNmzUL37t11f944fgP4fD40zs5GBEA9AA0AXAtZuKYC6HzGGVp42rVrh/kOB7oBeCLm+lOQRdh8pxNt27Y1zVNut+NTSBvWA/gKwAjIosgBYB5kAd2sWbMac9jtdiQ4nWgMccYrAYwD0AnAHIjAfDlkUdmkRYsa8wBA0+bNEYE4RwcAXAngcQCjIYuxxpC2hdq0McXTpEkTFFosWKK4ygDMUO+FEAejEED7Ll1M8QDAkCFD4AHweTV/m6XeddjCyJEjEQDQHbLw7gOxhdUAhgPYB+Caa64xxZGRkYHiSARpAHwQG7MDaALg3+pnLwCP3Y7GLVua4urQoQPCAFpAns97AZwJ4FUAhyG2GADg9XpN8QBAWr16SIN89rkA+gKYCNns+haAzWIxzeH1emFxubAU0k/XAdgPYAmApyEOzQYAXXr3Ns0FAHarFREAiwDcDuAmAGsVp83h0MKRlJSElIQEfFPN38IAvgDQsWNH0zx169ZFsdWKXHXfYZA5aCrEPr4C0KZDB9M8AJCQkoJkyHw2FTIuD0I2BJIAJCQkaOHJy8tDic0GO4BvIBspF0HalwSg6+mna+EB5HvP6fcjDOACAM9Bnp8zNHIYaNy4MSxuN84E0BJih2eeeaZWji69e2OW349LAKQByIPYdgBAq8aN4Xa7tfIFAgE88fe/45MuXfD0yy9rvXcs6tSpg/Hjx6O1x4PG3bqhZ8+etcZ1sjDpkUcwOSUFL2Vl4ZZJk37rjxNHHP8b0HH8e+TIEe7Zs4eHDx/WcbsTRjzkuPbxzttvM8lqZVCFZhp6eenBoLaKs5FIhB2bNeOtEK3R1gDbqDC22wG2D4W0FDaaMmUK3QC/hQi/GxV0U1WIa1uAPrfbNM/NN9zAbpB8MqMwlJE7mab6LxUwLaFx5MgR+pxO+iAhzA4VhumCFLsKAnTZbFrGaUDPngwC0Twsu+J7WIW3+i0WLdIM5eXldKh+W4YqqahZkDy2jORk0xwG/A4HsyG6uomqv66AhGr7NIWZjrv0Ug5Tn90mB2SE6j8fJCw92e3m1q1bTXPl16/P3hCNYJfi8EIKa4UAntm3r4YWifyVExKe/TeAz0NCnZuqNl199dVaeO6cOJF+1Z6gapNR7fg89UzpkoZ57LHH6IOE1Q9X939c9d9LL72khYMkn3j8cYYgRemMUONKgNcA7NG+vTae2264gWfb7fwkZk7oCglDz3C7tcn3vPbaawxAUkNy1NxdT819iQCfe+45LTwkee+kSQyiKn/WkDvKTU/Xnqu5YcMGBlwuJijba5mfz9LSUq0cBo4cOcJrr72Wl112Gffv36/9/mVlZWybl8dxdjufgYSgPw8wy+vl7NmztfP9kRFfO8ZhIG4LJx/acminTp2qTQJEF+IO7cnB66++ynppaQzYbPTYbDzjtNO056ts3ryZTbKz2c3t5jDlcHZ3udgoM5ObNm3SwhGJRJjo8zEA8AKALSAFc85UDrSu/KUDBw4wxe3mKWoxZENVhVs/pGJv944dNbSIfPXll+m3WukG2Fe16yxUFTh67K9/1cKzZcsWJnq9DAC8DOA/IIV58tTi9d7Jk7XwkOSyZcuiUkdZynHyA/Q4HFqrph4+fDhajKUzJF/O2HzQJaWzZcsW1klI4AjVHheqNFVzAZ7qdvOGceO0cB04cIBJdjtDAF+C5J3+XTkamcGgtirUJHnTTTfRBcnHS4bkSzogUje6UFpaymYNGtCvHMy/QHLgW6jnappmKaKbb76ZQTU2RuGhKVOmaOWIRCK8+dpr6bNYeD7A8arvOjVrplWSqrS0lP179GALl4vPApwD2RxMdbn4hKaCUAYuGjWKbkgObVP17gY4ctgwrTyRSIR/ffDB6CaeHWD/Hj20690aCIfDXLduHf/1r3/VijbsycT+/fs59oIL6HM66bLZ2K5Jk7gzWwPE145xGIjbwsmHNoc2Pz+foVCIo0aN4rvvvsuSkhLTH84s4g6tIBwO1/oXbmVlJbdv366l2nB1KC4u5kXDh9Nns7GzcjB8NhtHDR16jFSUWXzzzTf0qQVXV+XMJilndsTQodp4brruOiZDKs26ISeObrXg81ks2nRoSXLWu++yXnp6VIPWBTAjGOSLGgppxWLr1q0c2KcPLcopA8CMhAS+8vLLWnlIkYtKSkqKnmi2adOmVipm7tu3j53atYs6tvUyM7lhwwatHKtWrWLjrCzWUxrLSZBiWkGnkzeOH6+1KEtxcTE7d+4cdcj8AAcPHlwrmpM7duxgTk4OrVYr/X6/torDsSgpKeHoCy+kQ20IeAEGvV7OmjVLO1c4HOZ9993HjKQkpiUk8NFHH621SqNbt27ltddey4suuohz586tlfm7oqKCs2fPZt+uXdmyYUOOHT1am6TS8fjhhx/YoF49+lwu1svNNVVY778hHA5z69at2qSH/hv+SOuFcDisVYbq/xv+SLYQhznEbeHkQ5tDO2bMGDZt2jTq2LZt25YTJ07k0qVLTX/ImuL/u0P7j3/8g1l+v4R82Wy8ZPRobbqMx+Orr77ieeedx+uvv167UxsOh9m9fXsOg4QDPwjwfoDLAY4E2LlNGy0L8j179jBgsbAzwHxUyXMkQbRIPQDvvece0zzvvvsus9Qpwn2qDW0hUjSXQMKNU3w+7t692zQXSW7cuJFJDgfd6nTJD9BvtWqvlvnjjz8S6nTMovrOC3DQwIFaeRYvXky/astQtengVieAR48e1cazYcMG2tVJT+zLCnDu3LnaeI4ePcr2LVvSCzmpN9rmAvj+++9r4yHJM3v2pFX1l129A+BVl1+ulWfevHm0qfE3HGcbcIysmw488sgjtCmbM0K1DQ3fQ4cOaeMpKCigR0U6ZEMiA3wA/Q4Hi4uLtfGQ5Mcff0yPxSKa3mqMrhg7VisHKXItyU5nVKLMAbBTq1banfQvv/ySHmXbdmXXboBz5szRykPKOF179dVsnJHB0zt3rlW5lkgkwm3btnHhwoW1xkGS8+fP56XnncfRQ4bwww8/rFWuOMzhj7J2jMM84rZw8qHNoSXFIZg+fToHDhzI/Pz8qHPbt29fPvnkk9y1a5epD3ui+P/s0M6cOZNeiHbq9wBfh4RmDh80SDvXnXfeST9E4qQfJF9SZ/j5zJkz2dJq5UK1ODacskSACwC2tlr59ttvm+YZMWwYUyGyD36AV0FCGHPUAnk4QL/NZnpToGvr1syChEgaTqYFcgqcqZy01lYrp2gI041EIkx1u2lTDnmS4rQqp1bnyZzhwPRUbcmFyMIEoEdKx4AdkovXVvWdMTbJAF0ulzaeemlpdKr7twXYTfWhU710bQ5NvusueiG6wEYeaI5y0tyANodpxowZUTvwQUJzjTBnwHzOtoHKysqoLVwG8HOAD6jfHQDXrl2rhae0tDS6yeCKcWSNHMrmTZpo4SHJenXq0KM+v7HR5VB92Uwjz759++hRYzMZ4J0AL1S28JjGUODKykoGbDYmQOSUXoakJKQDPOuMM7TyGGH6QTW/GRscHkDr/FNSUsK0YJABNZ961DxnVme7OhQUFDDR5YpG73Ro2bJWTtFfeO45JttsUZ3qNJuN906apJ2HlKiA/Hr1mOn388933lkrHAYKCgq4cOHCWss7/q3wR1g7xqEHcVs4+dDq0MZizZo1fOCBB9ilS5eoY9u0aVOOGTOGs2fP1nqS8nP4/+zQNq1Xj1fhWB3DjwEmWCxaQ4rKy8vpgpycGjw3A8zLzdXGcVb37nwRUkykO8ASgKXKccoF+ArAMzt3Ns0TsNl4nrF4jGnPLuUAtFaOzIIFC2rMsXPnTiY4HExUbfFAChqVQ8TsA5AT6ASAzevWNd2mhQsXRk9KZ6n2zEdVDu1rr71mmoOUvNYgZEMjE1KYxyiY4gaYnJCghefHH39kAKLd6wN4KxAdsysUpw5s375dnH6AF0H0RxMVn7Fg1hUWnuTzMVFxnaacPw/AZura888/r4WnWW5u1PHbrGzh38oZ9ADs27OnFp4ZM2bQDdGkjp1/nlB916N7dy08t99+e9SJ9QG8G3Jab2iP2gAtTsaRI0foVX0UhKQidFJtCSj71uWYXTZ2LL0AJ0I0fAdC9Gc7AEzzerVwkORbb73FVEiESGzxqTaq73Sd0k6bNo1O1W+Gbm+WepacAB944AEtPCT54osvMgBwFMAySI64B2BuSoo2DgOtQiEGIRvF9yo7eOSRR7RyhMNhpvj9TIVsDPaC5KR7HQ6t0QcG6ni97A3ZxPUCWjaJq8PevXuZm5rK5n4/T2nRotbC9klyxYoVPLtHD77/3nu1xhGLP8LaMQ49iNvCyYc2HdrjEQqFcPvtt2P+/PmYPn06Bg4cCK/Xi8WLF+OWW25Bt27dzFLE8Qs4uHs3eh53rRuAIyR2796tjefAgQNwAGgdc+1MAId++kkbx67t29EEIv0yDKJz6obIpxyGyM/s3rHDNI+1shKlECmbWMGhTIjm5E8QmZ1du3bVmKOgoAAJdjtyAayBaM4Ogki2XAaR7dkKkYE4oEG3deXKlXBC5CsGqWvdIDIxBPDvf//bNAcAfP/997ABOAiRtFkM4ByI3mQOgEMmtHtj8eWXX+IIRJIlEcBDEJmWUohuohUANWhb7ty5E4RIwiRBtC0vgWjqVkL6bu3ataZ5AKDoyBGEFNcjEFmY9gB2QNqzfv16LTwF+/ahAkAIQH11rT2kHwlgjyadxu+++w5OiN5oLHqp941r1mjhWbFiBVwQ224G4C4Aj0KeXx9knHTo6u7fvx8uiA4tAbwGkaVyQGzODT36sACwavlypANYCrHtdwEsB9AFQGFJiRYOQJ57F0SP2IAVQG9IvxUVFWnhWb58OQjpo+vV60bIHE4Ay5Yt08IDAN8uWwYbRJ7MCZHaSgL+j73zDq+qyv73e3vLTS8EQkcSQKog0tEBbKAwIigqFlTUr4qKojB2wXEcxYpiG8UGiopdURGV3hGDNAHpvQbS712/P/a+Nxl+lpHsExXP53nyJERz33vOWWffvfZZe33YumePMUZMm9etoytwHjAKZYM2bdpPmYkdvfbt20eh9rx9BpiE8g4PgSWeqoWFhfwbuB1oDUyZMsU4A1Ts1Sku5ttDh1i5ejXbt2+3hAPw3JNPsuDrr3nwjjssY9iyZeuPrSontPEXcjrp0qUL1157LUOGDCEYDCIixj4wbf200mvX5tMjfvc5kOBwUKtWLXOc9HTKUQlMTFOAjJwcY4w6DRqwAkgDXkUlsQXAKyg/w5VA7Xr1qsyJut34Ub6j71X6/QZUApWNmsTWqVPnqBnp6ensj0TYiFoEKAUmoHxiH0VN8uoCiUBmaupRc2Jq27YtxagJ3qv6d5+gEk2Ajh07VpkByvs15vmYhvKz/AB1HJuAdAPHAtCjRw/lBQzsB64GLkBNmGNJjMOAz2mdOnVwoJKlrajk8i2UN6MLtfBwfBV9gmNKTkxkuWZdBdwKLEL5OkeBJk2aGOGkZ2fjQS2kxFLKGaiFIgeQc9xxRjjt27enhApf4Jg+0d+PN+ATDNChQ4d4bC8HbkYlMxHUgpAb8Hq9VeZkZmZSjPLVBeiDWkwrRcVDEeb8VNt26MBOVAJ7PSop6wx8CaSGw0YYAJ06daIY+KjS78pRXthuIDEx0QgnNr4UAg8B9wL/RF0fp34fptTupJMo15zdwNuoBbY6WVnGGDE1bNKEr1GJ5gjUmNC7d2+jjNTUVBJDIUqAC4EzUWNcocNBw4YNjbIAwomJXIU6nsXAoEGDjDMATjrpJHYkJlIvEOCE1q3Jzs62hANw3c0306NfP+555BHLGLZs2fqDy8Tj3+3bt8vzzz8vZ599tuTl5UleXp7k5uZKnz595EXDHVZ/Sn/lkuOpU6dKCOQG1D7Tp3U55iUXXmicNXbsWAnpEsOTQBJdLqP2KR9++KHkuVyyELUH1KPL1VJAFoA0dbnkPQMlRZdcdJEko/YvJqCaNd2MatIUAOkHkujxVLmM8W8nnii1dblfzLvXp783BDkdpIXLJQ8+8ECVj0lEJDscjnuOxspL3SCJbrfRJmEeh0MCIL1Qfrq5KAuiBJBvvvnGGMeFsgPqpo/FD3KZju9QKGSM0zgnRzxUeJu20OfQq5mm9sz965//lBCqc3dsb2YjzQ253cY6xk+aNCneEMqPKqMOULGH9ttvvzXCEZG4j25/kLdRpdpBHXcm/IhFKjyJY527Y7GQqu+lNi1aGOGIiDSuWze+hzbWTTm2n9YkZ9++fRLU1/8ukDtAztIluyY9W6PRqCR7PJKC2uc8To/dGSADDXZzj0QiKo71NcnQ32Ol4ibHn5KSEqmdmSlhKpqrOcGSpk0FBQWSpffrBkH+1q2bcYaIyBsTJ0qiyxXfc5zqchmzWjtSO3fulBNatpQ6GRlG92v/lA4fPiz5+fmWdFf/PXUszB1tmZEdC9Uv43toCwoKZPLkyTJ48GBp0qRJPIk98cQT5d5775X8/PyjfrO/VX/lhFZENVOqn5EhKSCZPp8Mv+EGy+x7li9fLiNGjJCHH37YeNfPSCQip3frJqeCfAhyhZ6EfQByBkivzp2N7MPZvXu3hJ1OaYXaS+bTk9ZMVGOWIGYas3zyySdSw++XEMgokKtRHqe3g/wdtQc1Ixw25ju5detWyQqFxElFp9EUj0dWrVpl5PVj2rhxozj15DuWQHtArjTcQXf16tVxa6VTQNpT0bXX5ARp8+bN4kftl/Xor1gTorlz5xrjlJWVyd86dYonyy49GfdjvqHNeX//u1ApkY11Ob5txAijnEWLFomLigWbkD6uxx57zCjnpZdeUosz+roEdNyFXS6j1nGHDh2SsM8nCTopi3kfp4ZCxhvbzJo1SxK9XknRHJ8F10dExXd2OCx+1KKdB6RX9+7GPyMWLlwoYYcj3kwttkg0Z84coxwRdZ3uu+cead+0qZzXt6/l842CggJZunSppYwlS5bITddeK9decUWV+jfYsl7HytzRVtVlx0L1y1hC+/nnn8t1110nLVq0iCexTZo0kSFDhshHH31kiUfkr+mvntAeS1q/fr0cl50tftQT1Bw9eW2YlSXr1q0zxlmxYoX4HA5x60Qm9uUBGXnrrcY4jz38sGT6/dJQv75TT8iPB0lPSJDZs2cbY91z112S4HBILqppzvEgQYdD/m/oUKOT1927d8u5Z58tCain50kgDWrWNPL0/EiVl5dL06ZN4z60gwYNMs4QUcfUp3dvCTmdEgRp26aNrF271jinvLxcrrnmGgm6XBIAycnONpo0V9Znn30mHU84QXJr1JC/de1qibXahg0b5OIBA8TvcEiSTmx7tG9vNK5jmjp1quSkpUkKSKrDIaedeqrs27fPOCcajcrYsWMlOytLMtPTZfz48Zb6e69YsULmzp0rpaWlljFE1LX66quv5ODBg5YxIpGIvPTSSzJ06FB5/vnnLbOPq26VlpZa6qlr688le+5oKyY7FqpfxhLaWCfj3Nxc6dWrlzz99NOyffv2Kr/BqshOaNWEfPbs2UaTviO1d+9euesf/5AOTZvKqR06yMSJE40nSrUzMiQR1fkzDVVW2Ew/mamVlmasxLl/377xJ1fnglyD6soZBgk6nUafPvc/5xxx6uQvTEXnz1dffdUYY8TNN0sGyPn6mGLH9neQeiAXDBhghLN7926pmZwcL/v06CQ9Vv751LhxRjgxVkYwKFQ6Ji9Ii7w8o09od+/eLenhcLxkMlkvogScTmPWMyLKhzY9FJIwFd6wsae1Dz74oDGOiEqcR958s4RdLgEk1euVRx9+2Oj9un79eqmRlCQ19HmLWVMlgSR5PPLJJ58YY7368suS4vFIP1RX6BNR3cMb16plzMdZRCVkl194YfxJsxtlTzbs6quNJ7WlpaVy1dChkh0MSqbHI906dLBkEaWoqEg6tWsXt/FKcblk1KhRxjkiIi+++KLkpKVJ2OGQWikp8sz48ZZwiouL5YknnpBTOnWSK4cMMVbefqTefPNNqZucHF+IbNmwoaxZs8YSVklJiXz00Ufy7rvvGnUosGVex9Lc0VbVZMdC9ctYQtuqVSsZOXKkJav9R6u/ekL73rvvSlowKG2TkiTd75ebrrnG+OTr4MGDcnz9+jLY55PpIG+CtAiFZORNNxlj3DZ8+H/tbb1If4X175JBbh42rMqctWvXigO1t3CkTioCqJLWK3Ty3Pv00w0ckSoHjz1tHgvyMMp2JJbImKhoKCgoED/K1za2bzZWNhukYg+qiYn/+f37xxOxWFLr1tcrDBJ2OIxZTdTOyFCJpeZ4Kx1fvz59jDBERFrk5opfJzCxUkmHPqYkv9/YvXRCq1YSQllQJVLhFZysmZs3bzbCERE5v18/SdTHkEKFp/M9d9xhjHHOaadJho6F2J7W2IJAEKRmcrKRhYcff/xRkjweaaLPW6yk3ova797n5JMNHI3SXaNGxeMMHQexvcgPG150aNusmXgqxYIPJMnlMu7jXj8jQzrpuEsBOQG1WHir4fLmfz/wgASoWLRL1OdxtAGf7coqLi6WOjVqiE8fR2yMMF0VMHXq1LjHewdUz4D/Q23jKCgoMMpatWqVpAeD0lxfn0SPx5Iqh5huvPFG6dWrl9H99EcqGo3KLbfcIm3btpWnn37aMo6IiolFixbJgQMHLOXEdKzMHW1VXXYsVL+MJbSFhYWyZ88emTNnjnz00Ufy0UcfyezZs2XPnj1VfpNHq79yQrt161ZJD4VkPspjcB9Iy1DImO9oTI8/9pj0Cwb/y29yF0iyz2dkAhaJRCQpEJAGevI4ArXfK0P/7Ec1Ukr0+6u8j7Z7586SBHKnngiFUftZE1F7XJN0cmNCNVNTxY9q1lWDir2zD+hJ3/XXX19lxp133ildqNg3GwA5s1LS7EU18rrw/POrxCkqKpKw0xmfQKbo85RExVNNL8i/DUz8V65cKb5KiVgbkPpU7DkNYmYxYNOmTZJAhadp7AljqNKxffbZZ1XmlJaWihtVBZAIkoUqC6/8ZLNXz55V5oioJn1uHdeXgXyN8g2OnTsT3uDbt2+XBJcrvrARRi0ONdD3rEcf47vvvltl1j9GjJC++rxdAlIMsoqKJm7Jbrds2LChypyysjJJ9PnEe0RSFtbHk5aQYKyEdubMmeLS7/8pkE/1uOADOe/cc40wRERmzJgR9z5O0vdQBkhrkCSn09hiTVlZmSS6XBJGLTJ8DTJAn7uw02nUj/6xxx4Tn74+tfRYkAmSGg4bY4iItGjQQG7V566+jucsVGXAMAMLq5XVskEDebDSZ+tEkJykJEtK3fPq15dMkC563DHdYyGmM049VcIoj+UAZr2IK6ugoEBqJiaqCiu3W1asWGEJp7Ksnjtu3bpVenfvLgPOPLPaknRbR6djIY/4s8mID+3777/PxRdfTOfOnbn00ksZPnw4w4cP57LLLqNTp07079+fd9890sTBlpXKz8+nudtNO/3vZOCiw4eZN2OGUc6sqVM55wh/xHSgk8/HvHnzqvz6BQUFFJWW4gNqA2+iLCy+QvlB1kVZ6ZSWlbG/ir6tP3z/PYeALSh7hKeBtSg7lXko+4woUFJSUiUOwP69e8kGpqK8R9+mwvu2CJhuwNNw7uzZNELZY0SBa4EPgftQVidO1LVavnhxlTg7duzAE41SCgjKUmkdynfUozkJwMI5c6rEAZg5cyalQAnKqmcByjKqVLMiKA/Zqur777/HhfIZDaHO2yrNBWU7Mnv27CpzNm/ejBvly+lEeU1+CrTVvysBli5YUGUOKE/QEMpC5Vmgq/4eRZ3LtWvXVpmxdu1aEkQoQVna3A3cD0xEXZtk/f+tWrWqyqzlCxawE3V/jkZ5OjcGrkTFQ140yvfff19lzrZt23CXlOBDxfd81PjjRJ23skOHOGDIZ/ntt9/GA7RDWVKdCtyDiu3533xjhAHw8ssv017/fD1qnEtF3bdF0agxX92NGzfiikQoBv6DirmXUPeVIxpl3bp1RjgAUyZOJAE11mwE/oG6RkUFBUSjUWOczRs2sBM1hh5CWa7tB3oDs7/4whgHIH/dOq6p9O+BwL6DB9m9e7dRDsC29et5D/gG5e1+//33G2cAzP/iCx4C3gcuBsY//rglnClTppB58CCbgfPLy3nwwQct4VSnnnriCRJnzGDftGm8/vrrv/fbsWXrT6H/KaHds2cPQ4cO5dZbb2XZsmVEo1FEPd39r6/8/HxGjhzJ5Zdfzh4LTM5t/f9KT09nfXk5xZV+t9LjId2w51uNOnVY7XL91+8E+CEaNeIv5/f7iUajOIFtQB4qAXwIaILyCHUB5SIEg8Gff6H/QYFQCB+QhEoq/wOMQU0mk4Af9f/n8XiqxAHwOJ3sAgR5btgAACAASURBVBoAk1GJ7UzUBNkHpGdmVpmRkpZGIep6uFATiC9QiwJl+v+JAAnJyT/9Av+jEhISiOify1EJ4FWoSX8sCSgG0gwcU05ODg6UV+Zh1KLG05U4Lsx4giYnJ+PQrxdBeQTfi0oyI6jrVKNGjSpz0tLSKEMNuBHgZZR/7zJUUgYQruL1iSkzM5MyVDzHfKNnUHEu09PTq8xITEykxOHAg4qxd1E+xG9V4rgw43OalJ5OKup4lujfxRJOB7DT6STZwLlLSkqiBJX4O4EHUGMQqHgvcziqPPbE1LBhQ8pRPsF7NfNLzUnJyDDCAMjLy2Mr6r6cAvwb2I6KbwcYO57U1FQiqOQvlo5/g7p/HJiJuZgaNG5MESrBfBA1NsQWuZzO37RG/4sK+v3UQC0MJaI8sT0ov/I0w5+vKYEAyyv9exOAw2HMJ7iynE4nL6A82NcBXbp0Mc4A8IfDvAF8jvrcq2uBpy4ob/QfgEdQC5IdOnSwhFOd6tC5M594PCx0OGjbtu3v/XZs2fpz6Nce7R46dEjOOOOMeCOogQMHygsvvCCzZ8+W1atXy9q1a2XhwoXyyiuvyMUXXxxvGtWrVy/jti4/p79yyXE0GpXzzz5bugWD8izINR6P1M/KMmYFE1N+fr5kBIMyU5dElYLc43LJCXl5xsqiTu3cWUJUlP5eob966d+FQHp06FBlzssvvyw+kEGoMmavLvVLAHlEl7DVzsgwcEQil156qSSBXIlqPNUN5EGQlqjyYBN2E9999118n3GsHDe2n9GnSw1rgXz66adVZjVr0CBuZRLWJXg5VHiPJmHG57SsrEyCEPdTje0HjXnD5qSnV5khokrdg263pOmy0pjPqQ9VIh4AY3uCk/1+8elzFdbnKgnVtCsB5O233zbCiUajUjMpKb4XNFaW6QNp17SpMUZerVrx0vMsHW/pVPi3JrjdRvZtf/rpp9LQ4YjH9vkg7fQ5PBGkXkaGsVLgUzp0EDcV/qYJVDQ+63vaaUYYImrPX7LLJSF9TBma5QZ5//33jXFKSkokqMs+Y57eAZC/gbRs3NgYR0Sk+0kn/VfMxfa9d2zTxihn/fr1EtAxV0OPPz6Q4Qa2b1TWDTfcIE1AeuvzloLyCw6BzJs3zyhr7L//LTVAJoBM0p9Lw665xigjpjlz5kiq2y0pIL169LCEIaJs17ICAUkBaZCVZWmjqzfeeENO6dhR/nn//ZYxKqs65o4bNmww2vDOljU6FvKIP5uOeg/t9ddfL7m5udKlSxeZPn36r4Lmz58v3bp1k7y8PLnJYMOgX9JfOaEVUR1Nn3jsMbl0wAAZefPNxjoBH6kpU6ZITmqqNE5IkAy/X05u1042bdpk7PVnzJghyW631Ebtj6rcdbYOSIrbLV9//XWVOZFIRELaxP5sPUn5B8jNmucE+eqrrwwckdo7mezzSZKeELXRE70EkB7duxthiIg0rllT+lGxlzWRir2ZF4LUSEgwsvDw2WefSfiI1w9RsXe3c9u2Bo5G6fnnnxefnqw6UE16YgmnSU/Id955J56gJ+uvFH2N7rr9dmOczz77TDx6kn8cSGOdACaA1MnMNMYRUZPJFK83vq85AFInLU127NhhjDHp9dclxeGIL5zE9qEHUXuFrx0yxAgn5k/dTZ+v2AJUZ5AMj0feMbQQIKIaUKXqztou/QVIVlKS8WZNM2fOlHSvV5yaE8SsZVhMU6ZMkSBq3+xZOgnMTkgwbt+zb98+Ob5hQwnpcxYCya1bV3bv3m2UI6I+K1ISEuLxfdP11xu3CIpGo9K1bVsJ6zH0DD3mWXGNREQmTpwo7Zs2lROOO07GjRtnqVWUrarpWJk72qq67Fiofh1VQrt48WLJzc2Vdu3ayQ8//PA/wzZs2CAnnXSS5OXlWdpFL6a/ekJbnSorK5Nly5ZZZpMw4cUXJaxXj2voSXIKqtnDf55/3hhn586dkuz1ilsnMGGdWDhBnjfIEVFPSc7t319CsackHo/861//MsrYv3+/1EpKkuNAhqAaslyG9rv1+41Oxl+eMEESnU7xUPHkLxGka7t2xqsypk+fLo1q144nnCe1aWOJbcbnn38udWvUUE8WQZKDQXnxxReNc6ZNmyZpwWA8ifGCnNqrV5Ubnf2UysrK5IMPPpBHHnlEpk2bZskEedzjj0uCxyM1UVUBNUDCLpdcedFFRn1Vi4qK5ObrrpNkv18aeDyS6fFI83r15MMPPzTGiGnXrl3yj9tuk8Y5OdIwO1vuuesu2bt3r3GOiEqavvzyS5k8ebLxzrmVVVxcLHfffbcMHDhQpkyZYmmytGjRInn55ZdlwYIFlidlZWVlljPmzp0rl112mVx00UXGFzVs/Tllzx1txWTHQvXrqBLaO+64Q/Ly8o5qYjdp0iTJzc2Ve+655zf/7W+VndCqrqMffvihkRLWX1MkErF0ErFx40YZefPN0qx+fWlWv77cNny4kS6mR6qoqEjOHzhQUlwuSXQ4JLdOHUsWYKLRqLz00kvS8fjjpV56uvTt0UNmzZplnFNeXi7PPfecpIfDqhQ0GJR///vfRhMLEXXerrzoIgm73dLc7ZYst1uOr1tX5s6da5QT08qVK+XBBx+UJ554wnLP6xkzZsj48eONP+2prLKyMhk7dqxccsklsnz5css40WhUJkyYIJdeeql88MEHlnH27t0r48aNk+HXXy/3jxljiZdqTNu2bZNx48bJW2+9Zek1iqk6PiOi0aj9NO5PoGNpvmCrarJjwVZMdixUv44qoT3jjDPk+OOPP6q9D4WFhdK8eXPp3bv3b/7b36q/ekL7wH33SaLHI129Xqnh8cgZ3bpZsl9l27ZtkpOUJA79ZOnsM8+0ZCL2ww8/SHYoJB7U/rUawaCsXr3aKKO8vFxaHnecnIyyT2kFMhQkwek0Ws4qInLDVVdJE5dLmqDsJdqDpPt88t577xnlbN26VUJOp/h1yWfM9sa0LcN5Z50lfTyeuJ2JC22zFArJypUrjbJG3XKLJOhyv1N0yd+UKVOMMkRE1qxZI1Bhc+TA3J7WysrPz1dWMzoWvCDtW7c2ztm7d6+k+3wSqFSmWzctzfjihkhFyXaSfrp95ZVXGmeIiLwyYYK4dQwEQOpkZFiyxywSiUiN9PR4LNTJybFknItGo3JGr14Ve7YTEox6EVdWQUGB9OnTR5o1biyjR4+2hCGiFrsa1a8vPqdT6tepI4WFhZZwotGoPPXkk/K3k06SKy6+2LJtNiIiy5Ytk5EjRsj1111nSfl0TIsXL5ZLBgyQC/v2Nbbl5fdWUVGRrF+/3pIKlN9Tx8rc0VbVZcdC9euoEtpWrVpJr169jhrau3dvadWq1VH//f+qv3JCO3v2bKnp9cpWVLOmMpCznE4ZdcstRjnRaFSygkHJ0JOvWAOgKy+/3ChHRKR2crI0BqmLapjTGKRWYqJRxqRJkyRXJ2SxPa0JINeBtD/+eGOcNWvWSIrHE5+Ex/ZmNgNpVKOG0adMLRo3lhR9ffz6exZIjaQkY4zvv/9esvz++L7MgSjv0QDIDSBXXnSRMVZ+fr6E9d6/LJ2Y9QMJOBzGF2xcOon16phw6C/TTwGT3W4JUOF369Y/T5482SindfPm4kbtZYx9D4GcX0Uv4iO1c+dO8ety8Ng+UB/Is88+a5SzZcuW+L2aqc+dD6SDBZ8vtXTpeawRUBDkuEaNjHMuGTw47kUb24ee5vMZ50QiEUn1eqW+HkvDIBddcIFxjoiIX/tUJ+nz5nU4LFkM+Mett0qYigZuGeGwJYu4S5YsEY8+njBIejhsfO+xiBrrgi5XxX5qh8NIv4ifUlFRkVx4zjnSunFjSxPnlStXSlIwKAGQBjVrGmuu91N64bnnJC87W24ZNqxaqh2OhbmjLTOyY6H6dVQ+tNFolHA4fNQdlH0+H+Xl5Uf997Z+XW+9/jpDS0uJmQi4gbujUd58+WWjnH379rGnsJBy4DSgBsqu4+NJk4xyCgsL2bJ/PweA1ShP0AJg+8GDxjwTAV597jn6o2wlPgJ2ofw0XwcW5ecb40ydOpXWZWX4UNZAe4AOwEqgaP9+fvjhB2OsNatXUwMVA1egshgPcOjAAcrKyn7xb/9XTZs2jd7RKG7gTpSf6hKU3cjXwOeffmqEA8pfsDvKsula4HSUBURDEb4x6NVZVFSEoGKhPtAJdd68wJdffmmMU1hYyMHycspQVlTjUNfKBdxx663GOABrv/uOctQxDEV5dh4Gpr39tlHO+PHjKUPZzoRQx+IE/jlmjFHOBx98QBQIovyVO6DGnzlLlxr/jNm5fTtu1DVqoH+3weB9GtP7r7+OoM6XG3Wt9paUGB3nABYtWkRhaSnJwL9Q9+oHr71mlAFw8OBBInpsmIiy2IqKsGvXLuOsx8aOJQgM0JzSggLmGPC/PlLPPfEEQeB2lH94QUEBXxj2oAWY+OqrFEYiNEJ5ExeJ8OKTTxrnALzwwgt8+PbbrF+9mv59+ljCALhv1CiKCgu5BNizdSsTJkywhLNnzx7+78oreWjbNl577DFmzpxpCceWLVt/bLl/6T+mpqaydevWo37xbdu2kZKSctR/b+vX5fX7OXzE74oAn9drlON2q1ApR/nEFqImYiZ9/9Cv50R5cx5CeRiW6O+x92BCbo+H2DR4O7Af5dUYAFwOhzmO2005asK/A5VU7NP/rUzEiNdtTII6T07UQoATlZhFAYehY3K73ZQ4HAgqOQe14CCoZOOQwWvk8/ko06+9GXX+Iqh48BqMb5fLheif96OSMjQ3FAoZ4zidThz6dfcDa6lIAL1+vzEOVBiMO1Fep7Gr7zjCS7qqSkhIUI9/UbEd1D97DI8/Pp8PUMexHhV78WMyeL/GFEH5w8Z8aa2Qw+lEUB/CJVTEgslxDiAQCBAFDqJizkPFuTMpt9uNoM7dWojfuybHuDhLn7uNVIx7JseEmLx+P4KKue2aZQXH4/XiRH02xM6b6TEhpoSEBFwOBwUiZBvyIf4pBUMhnMAa1PUJBAKWcDweDw6Hg7UiFDkcRsdsW7Zs/Yn0S491r7rqKsnLy5NFixb95kfCS5YskdzcXBk6dOhv/tvfqr9yyXF+fr6k+XyyUJcc7wY5ye2Whwx30RURyc3JkSwqvEGDIP/85z+Nc5rWrSuNKpUBNwJpUru2UcZnn30mtfRexpiHagC1j7Zn587GOFu3bpVEj0cy9bG4dOlaF5A2xx1ntDyqR9eukhAr9dNfSSB59esbY2zcuFFSfD5J1eerRaXyz8tBbhk2zBhrw4YNEgA5XTNCIBeDJHk8UlZWZowjIuJ3u+MxEKDCJsh0+VpWQkLc8ihBM/wgM2fONMrp1aNH3D4l9uUDufnmm41yDh06FPeOjvkFB0CmTp1qlLN37954V+2wPhYXSL8zzjDKERFpf+KJcTuYWGl9r549jXPuu+8+ceoS9xivQXa2cY6ISIOsLEkHydXnzqp9tBnJyfHO8R6QlFDIEs5zzz4rCfo+TQBpWr++8TFBRHveut0S0teoecOGUlJSYpyzadMmyUhMFKf+fA253ZY1eIxEIjL6rrtk0N//bukcaNu2bZJXt644QHp06iTFxcWWsb788ks5u0cPeek//7GMUVnHwtzRlhnZsVD9Oqo9tG+88Ybk5ubKhRde+JtgkUhELrzwQsnLy5O33nrrN/3t0eivnNCKKD/IzIQEqePzSaLXK8OGDrWkCUNRUZGc1LKlJKP8H2//xz+MM0REDhw4IC0bNxafnuS1bNRI9u3bZ5QRjUald48e0ghkGMrqpi9Imt8vGzduNMp69KGHpIbHIx1BmoN0BckIhYx3BS4oKJDMxMS4PVAQJMnrNd4w5ab/+z85MRCQtpUSshEgOWlpsmXLFqOsCS+9JH6Uf28TkES3W+bPn2+UIaI8NH1udzz5c4ElE8rdu3dLit5Hm6In/ZdecolxTmlpqTTOyYkngR6QDm3aWLK/bMWKFZLo8UiiXnR44YUXjDNERL755htJ0OfOC/K3Dh0ss7rp3q1bfD/1mWeeaQlDRGTkbbdJksMhYZATmjWToqIiSziRSETuu+8+GTRokKUdr6PRqJx//vmSmZEh/fv3t3Q/47Rp0+S2ESPkySeftOy8iSgHgRdeeEEefvhhS5OyzZs3y+j77pO777zTeBPE31PHYgfvY2XuaKvqsmOh+vVzOZ9DROTnnt6WlpbSq1cvduzYwfnnn88dd9zxq+Vd5eXl3HnnnbzzzjvUrFmTqVOnWlJyVFmLFi3ihBNO+M1/t2LFCpo0aWLBO6p+lZaWsn79erKyskhOTv69386fQiLCG2+8weNjxrBvzx7OHDiQkbffTlpamnHWrFmzePbRR9n644+06tiR/7vxRurVq2ecI3p/6fz582nRogU9e/Y0XhYejUZ5fOxYxj7wAIWHD1MciXBGz57868knqV+/vlEWqL15X375JYFAgJNPPtmSkr+YiouLWb58+VGNJ79Fy5cvZ9OmTXTp0sXSErmVK1eyYMECunfvTu3atS3jVJei0Shr164lKSmJzMxMy3nH0meErarJjgVbMdmxYCsmOxaqXz+X8/3iZh2v18vo0aMZOnQoEydOZPny5QwZMoROnTr9f5OwkpISvvrqK8aPH8/KlSvx+Xw8+uijlieztpTcbjd+vx+/Rftufg8VFhYiIpZN+B0OB4FAgKLyckojEaL631aoY8eO7Nq1i2XLlnH22WdbksyCOqZu3brRrVs3S14f1F7Qa66/nqxatfhq6lSycnIYcsUV1K1b1xJeYmIiffv2teS1j5Tf7ydo4b6ymJo1a0azZs0s5+Tl5ZGXl2c5p7rkdDrJysqK76m1ZcuWLVu2bNn61Uc3nTt3ZsyYMXg8Hr799luGDRvGiSeeSK9evRgwYAAXXHABvXv3pm3bttxwww2sWLECv9/PAw88QIsWLarjGP7yeuCBB0jzesmtV4/UQIDTTz6ZaNSaViYjRoygQXY2TRs1MtpptrLWrFlDis9HjVCI7IQEkr1eVq9ebZzTo3NnBvfty66VKyncuZPJjzxCdjjMjh07jHLWr19PisfDVf368eFdd9GxVStya9cmEokY5QDcdNNNJDgcpDgchB0OzjvvPOOMvXv3ckJeHtcNGsRrEyYwbswYmjVqxKTXX7eG1bQpXoeDoMPBwH79jHVsPlJPP/00YY+Hts2acdVVV1nCAFi6dCnZmZkkBgL0P+ccfqFIpkoqKCigZs2a+DwecnNzLRsTysrKGHLxxWSkptK1Y0d2795tCWfx4sXUTk2lTlISmX4//c48k9LSUktYy5Yt48zTTuOaq65i5cqVljBAdUFv37w5xzdowD23327JmADwxRdf0L5JE2omJjKwTx+2bNliCQfg+++/Z/To0Xz33XeWMUAtoi9btoydO3dayrFly5YtW38C/a81y/n5+TJ48GDJzc39xa/BgwfLhg0bDFRJ/+/6o++hLS0ttey1p02bJkGQx0H+DnK/bvxxgWG/SRGRc84+W0JUeMMGQL755hvjnCSHQ04AmQsyD6QdSKLDYZTx0UcfSVjvL2wG0hDkOJT3bau8PKOszEBAeuvGRjkgtfV+0HP79zfKefPNNyUB5QtbUx9TEOTee+81yrnyooskUTdkSdH7JgEJejyye/duo6zaKSlSUzcbih1b39NOM8oQEXn44YfjDWbC+nhOt4CzYsUK8YGkguTp/ceNGzQwzikrKxOoaHIV2w9qWtFoVDJSUsSvXz8WCwcOHDDKKSgokESXK75PN6R55/bta5QjIjJr1iwJ6DiIeZ0uXbrUOOfTTz+VoB4P2ul79ZJBg4xz5s2bJwlUeG4HQepmZFjyuXTdddf9VyOySy+91DhDRDXb87lcEtLH9Nwzz1jCERGZPHmyuEDcTqelXqolJSVybv/+clqvXpZ43VbWxx9/LKNGjbKkwdXvJSvnWUfK3jdpKyY7FqpfR9UU6qe0Zs0amTBhgtx2220ydOhQufTSS+XGG2+UZ555RlatWlXlN3o0+iMntGPuvFMAefLRRy15/W4dO8q1euJ1s04wHtJNm0wrUb++V0/880CaNW5slDFz5kzxgmxEdW0WkM2aOX36dGOcts2bS45u0jQQ5KVKzXO8Bif+O3bsEB9IFkgGSFuQliCngiQbTtLTUlIkXXPe18lfLZAEg7EQjUYloJsn+UHeAOmpz1kmyHPPPWeMtWLFCknS1+VxkGt0nHvBeNMzv37t60DG6oTJYUEC2LJlS0kASUN1iO6uWaab2gwfPlwclZLzgP5+NB3rf0lr1qwRt16sceiFBx/I448/bpQzfvx4cenjaExFB/REkEgkYpSVnZIiYb3okK6P7bg6dYwyRETaNWsmdUBK9Dg3TMe26Vg4/+yzxaOPZ7i+b9NAPvzwQ6McEYl3726u49pvwT0kInJO794SomJh1WVBHMQU6xofBvEaHrMrq0vHjhLU56xuTo5lnNmzZ0sApD5IYws51amXX3pJHA6H3Hr99dXCs5MYWzHZsVD9+rmc7zcb3jVq1IhGjRqZeTz8F1D+0qVkud0sX7rUktc/dOAAmSgP1XOAj1EesaXl5b/4d79VIkIU5TEYRnmPlgDOQ4eMcrZt20Y5kF7pd2mau3nzZmOcokOHENR56wacgfLY9aLOnykdPHgQL3AAtWG9J/A2ymswarjUtKS4mGTUuTsdeApYCUQNxoKIUKxfz4c6b98Bs1AZ0yGD8XDgwAFCwE6gN1ATeA0VC+Xl5bgMeqpGUfsvegBNgNuMvfJ/K3ZMDqALsAjlP1pcXGx0//umTZuUTzTq/imu9Ps2bdoY4xw+fDjurZtOhZ/qrl27jDEAdu/ejUu/difgcyr8nKPRqNHGZ8WFhZSjrlFUfz904ICx14/p8OHDZKPGHIDjUGOE6VjYt2sXUSAH9RnxqP79/v37jTEqqww4D7gb6zx8t23fjhs1zj2PiouysjJL9lZHUWNdMeCwaHsAwI8//kgEFQN79+z5tf/9qLVmzRqCwCnABxZtD6hufb9sGZkuF99ZNM+yZcvWH19m25/a+v/01IQJPPH66zz4xBOWvP6AwYN5FrgBOAvIBFYBxzVtapTjcDjIyMggC/XBngDsAAYNGWKUc/bZZ5NAxWQoCtwHhIABAwYY45xz0UVEUZOvW4BaQHPUxCXLYBOqhg0bIsBpQAYwFdgDeIBsw42hzhkwgD2o6xIAFgLbgVYdOhhjOJ1OuuruchEgBXgYtQhQ6HTyt7/9zRirTZs27ENdk1zgAtTEtVZqqvGJa4vWrTkAnAs0RcVdogUN1m655RYKgPqohYDVwGEw3pl8zJgxRIAi1GJKbGfm6aefbpSTm5tLGSqRLdG8EjC+d/u8884jtnwxCYhNw7Nr18bt/s3rsr+oK6+/nijquhSjjueGkSONMgD6n38+3wE3AeOAUUDNnBzjsTDg8stJBtYBvVBjz2Hg1FNPNcoBSExNpQx4EH0PhcPGGQD3PvAAZcBzqDH8pPbtLWsUdlzz5pSiEs2HHn/cEgbAh598gtfjAaeTt9591zLOhRdeyPEdO/JJUhKTp061jFOdunP0aJ6cOJGX3nrr934rtmzZ+r1Urc+JLdIfueTYakUiETmxWTNJBDkHtW8y3eeTH3/80Thr165d0iAzU8K6DG+QBft0RURuv/12SdDlzam6hG3kyJFGGSUlJZLi8Ug9Xa7m02V4PpApU6YYZY0fP178usy4L0hHXUa7du1ao5xIJCI1UlIkBOLUJX8pPp+UlZUZ5cydO1fCXq+4qNgrlw5y8YABRjkiIp9//rn4Ufu2s0GSPR5Zv369cU40GpV6tWrFjyfB45HDhw8b54iIXHLxxXF/WD/IunXrLOE8/PDDgi4FBuTjjz+2hLNq1SpxVoqFSZMmWcK56/bbJajvV4eO7R9++ME4JxqNymUXXyxeXWp607BhxhkiIuXl5TL4vPPintENa9WSTZs2GedEIhG5+pJLxKe3IyT7fMbHuMo65ZRTJBgISJcuXSxjiIjMnz9fbh4+XJ599llLfNeP1LEwX7BlRnYs2IrJjoXq11H50P5ZZPvQwscff8zkyZM5/vjjGTZsmPGnFtWt3bt3c9111wHw2GOPWeI5uW/fPnr36sWShQspAzLDYca/9hp9+vQxzlq0aBFXXXYZO378kbannMIzzz5LRkaGcQ7A9OnTmTRpEn369KF3796WMJYuXcqYUaOYMWsWmampDB0+nKuuvtpoGXBMxcXFzJgxg2AwSIcOHYz76h6pY2lcONa0efNm3n33XbKzsznrrLMst4WrjlgoKiqiuLiYlJQUSzk7d+5ky5YtNG3a1LY9OgrZ44KtmOxYsBWTHQvVr5/L+eyE1g7Ev7wOHjzIkiVL6Nq1Kw6HwzLOqlWr2Lx5M82bN7ckQQf4+uuvueXaa9m4YQNZ2dmMfughSxL0Y1n2uGArJjsWbMVkx4KtmOxYsBWTHQvVr5/L+ew9tBZr165dLFy4kL1791rKWb9+Pe+88w7z58+3lLNgwQIuuOAChg8fTkFBgSWM8vJyTj/1VILae/TUnj0pN9zkClQDqoaZmWQkJXFG9+6kut08++yzxjk7d+6keaNGnJCXx1k9elAnK4tLBw0y7jl5w7XX0qd7d/Lz8ykoKGDN6tUMOussBvbrZ5QT05gxY8jMzOSkk07i4MGDljAikQgDBw4k3eslKxjk3nvvtYQDcPfdd5Po89GueXNL/HtjKi4u5oUXXuDOO+9k8eLFlnGqU9988w33338/kydPtsxLVUR44YUX6NauHeeefbal/rDVJREhPz+fb775hpKSEks577//Pg899BDLly+3jAPKh/add94hPz/fMoaIcP3119M0N5cuXbqwbds2y1jHokpKStizZ49lHti2bNmyVe2qnopna/VH3UP71ptvSkogIK0SEyUtFJJPP/3UGs5bYfewqQAAIABJREFUb0lA78MKgQz6+98lGo0a5zz44IMSBDkFZT+TALJr1y7jnHrZ2XGP2JDm1MnKMs7JCgRkCMh+kAjIu5o5Z84co5ym9esrn1Z9LD69x/Uft95qjLFy5UoJ6z2ZDv3dibIhSgD56quvjLFERLKysuK2HB69d3Lfvn1GGSIiebVrS1gzYvYwF1qwd/vcc8+VAMjZ+isB5Lj69Y1zDh8+LD4dC2G9H/Thhx4yzhERmThxYvzcJYJ8++23lnCGXHKJeCvtoa2Xk2PJnsZz+/QRlx4TvNquZd68ecY5IiKJfn/8eLIzMixhRKNRqZ2VFR8XrNpPHY1GpWPr1hLQe9EDmLdVimnMPfdIQI89AZA7Dfc+iKlV48ZSF+RelP96AsjGjRstYX3xxRdSMzNTGtWrJ9u2bbOEISKyadMm6dSmjZzQpIksX77cMs6Lzz8vQY9HAm63dD3hBEu9dTdt2iTvvvuuJZ8Nv6fsfZO2YrJjofplzIf2j6g/YkJ7+PBhSQ4EZDHKY3AGSFpCgnGvvEgkIl6nU4IgN6L8ToMgM2bMMMoREQmB9AZphfIc7Yl5H9rNmzeLF6QGSA+QXvqYfGC00dXnn38uaSDlVPjdCsrLt22LFsY4+fn5kqCvSW09aa2lE5mA02mMc26/fuLWE3C/PmeVk9tOJ5xgjFVQUCBBkDY6saihGSkpKcYYIiKrV6+OJ83hSpN+LxhfsEnSsebXsdZWT8j37NljlDN8+HAJ6sQ8iQqfWCsSwESQ0XrB5krNMq2tW7eKT1+b1lT43ZpuDLV582bx6+vTDOXhGwRpUq+eUY6IyNVXXy1+HdcZekHg3nvvNc4ZPXq0JIAMBnlCn7ssw/eQiMirr76qEj49xr2kr5fpe2j79u0S0IsnI3R8ByxINBcsWCAJILsrjdsXg7Ro1swoR0Rk3759EkJ5tiaBJPp8xhkxpfr98c+KgMMhJSUlxhk//vijJHq9kqbHuMYOhwwbOtQ4R0Tds6mBgLRzOKRhjRpSWlpqCef3kJ3E2IrJjoXq18/lfHbJsUXauXMnCQ4HrfW/OwPFJSXGy3QLCgqQaJTawFjgKv37jRs3GuWICEXAcuA/wMUoO5WdmzYZ5axYsQInyv7jCZSdRSHKrsVkCduSJUvI1a9bWW2BXQbP3caNG+OelntQnolOlAWERKPGyjM3rF1LQP/sR2UViSiLDi+wfcsWIxyAdevW4QX2o2KuHGXfs2/fvl/8u9+qJUuWkKB/dqHiQFA2HabLM6PAGqAjcBnK4qQYVT5pUvmLF1MKlKKuTcyn0wpP0HJgMJAEXISKOdPaunUrgjqeOSjLI1Belya1bt06QHnq7kFZkzk137S++OILfMAjwP1AEJhqgb3J7NmziQL3ANcCNYADFsTBsmXLaADU1v8+HXUPFRUVGeVs2bIFAboC/0JZBEX1701qwYIF5KBiIaYOwIEdO4xyQMWdG5iAslcqs6gsPBqNsre4mO4oD9+oiHEvZ4ANGzaQ7HRyDvAGsEOEtYbHuJiWLVtGTkkJM0XYsXMnO3futIRjy5YtW2DvobVMtWrVwhkK8RJqYvy4w0Gd7GwSExONchITEwmHQmwBWgD/Rk36W7VqZZTjcDhIcDg4AeiC+oDfDLTp1Mkop3379ghqst8dtRDgR/lodu7c2RjnjDPOYClw5M7Pd4Bm7dsb4zRv3hwHKrlIA0YA+/S/g6GQsa7A7bt0oVD/XIY6rkOoRKMQOL5NGyMcgLy8PA6jEqR7UR6++4Cmhr2Pe/TowQHUYkApagHFgUow/IY9Yp2oZGwh8CrQHuV9fOKJJxrlnHbWWbhRiwzFqGsFkJqaapQDahHgOuBTlNdyqXECNGrUKH6/JqESTS9m71WAFi1aALAXSAdSUcfTum1boxyAG2+8kQLUot21QAFwww03GOcMHjwYgN7A31H+0bl5ecY5p59+OmuAz1Axdx+Q4PEQDAaNcho1aoQD+Bo4EfgEdV81btzYKOe0005jA7BM/7sUeAVopGPEpJo1a0aZw0EP4J9Anfr1jTNA+Xs3rVePBcBHQEo4THZ2tnFOs2bNOOxy8Q7Kdz3N7abraacZ5wB06dKFspwckp1OunXrRs2aNS3h2LJlyxZgQQ3a76A/YsmxiMiyZcukef364nY6pW1enqxevdoSTn5+viT7/RLQ5XHPP/usJZx58+ZJCCRHl19lhcPGPU5FRP5+1lnio2LfpB/krDPPNM5p2aiRtAb5CuR7kOGo/XmmvSDPOfNMcejjie0v84O8+sorxhg7d+6UgH7/VPry6d+Zjr3LL79cfLqMNVY2a7qcXkRkYP/+cV9djz6e8ePHG+c8/fTTEgJpoktngyAXXHCBcU40GpUOrVuLUx8LIDNnzjTOERHZsmWLhFBeziGnU4qKiizhTJo0STy6FNwHcokF501E5NGxY+MlzYCEXC7ZvHmzJay+ffuKU8fdkCFDLGGIiAw67zzx6fGgRkqKZdfoFl3q7gRJcbks2ZIiIvLZZ59JMFY2C/LRRx9ZwrnskkskCNIFtYUjOyHBkhJdETW2Dh06VK699lpL/W5LSkrkkUcekfvvv18KCgos48yfP19OatZMGmZlycibbrL0mMrLy2Xnzp2W9PT4PWWXmdqKyY6F6pe9h/YnVF2BWB2DeSQSkW3btklxcbGlnMLCQlm4cKGsXr3a0uN68803pWHdutKgbl2ZOHGiJYyysjIZeO65kup0SiJIk7p1JT8/3zintLRUhul9eUGQ5EBAJrz4onHO22+/HV/U8OrvQZCnn37aOEtEZNu2bfLiiy9aNjmO6dNPP5UO7dtLz549Lb1nV69eLV27dpXjjz9evvzyS8s4IiLr1q2ThQsXWjpxrU7t27dPFixYYFmCGdO6devkySeflDfffNOy5K+yjqXPiOLiYtm6daslC0+VVVZWJlu3brVksbOy5s2bJ8OGDZNnnnmmWs6fPXG1FZMdC7ZismOh+vVzOZ/tQ2v7R9miemIhGo1SUlKC3++3zO/2wIEDPPLIIyyYPZvjW7XilhEjSE9Pt4R1rMoeF2zFZMeCrZjsWLAVkx0LtmKyY6H69XM5nxV9QmwdwyoqKmLevHmkp6fTrFkzyxKzQ4cOMWfOHESEDh06EA6HLeHs2rWLiRMnsmrlSi659FLatWtnCefw4cM89dRTLF2yhL79+nHOOefgdJrfwp6UlMTdd99t/HVt2bJly5YtW7Zs2fojym4KdYxo3LhxNG7QgAsGDaK8vNwSxty5c0kJBul58sm0bN6cvDp1KCsr+/U//I1at24dyeEwZ/XqRd9TTyUlMZG1a9ca53z77bfUzMxk5LBhTHj6abqdeCI3DxtmnLNz505yUlJ4eMQI3ps4kasHDKBds2ZEo9Ff/+PfqOnTp+NxOPA4HHgdDl555RXjDFAdjf0OB36Hg6DDwRVXXGEJJ8bq0aMHgwcPtiy2QcW3w+GgadOmPPXUU5Zx9u/fT+2aNfG6XNx7772WcaLRKG3btCHgdNL7zDMt4wCMGDECn89H165dLWMUFhbSs0sXXDq2J7z0kmWs/fv3k5WVRffu3Y131D5Sb731Fg888AClpVa07arQ6tWrmTBhAocPH7aUs2rVKm666Sa+++47SzlFRUVMmDCBlStXWsqpThUWFhp3QrBly5atv4Sqs+7ZKv3R99BarWeeeUZ8KO/RBJBWTZtawkl0OsWnG7/EGvRcfNFFxjkhr1f82vuvnm6YEvB4jHNqp6dLgubU1sfjtaApVI+uXeMeqkF97tJBpkyZYpQjIvEmWgm6KYsbLGmW4tfNplqCZGumFU3PSktLxa2vixvlq2uFCgoKBH3OgppjVbMmYp6WKD/iZy1q4lYjLU0C+hoFQbp362YJ55ZbbhEXFV7B6amplnAu0A3CGlZqRPbtt98a50Sj0XgsxJpQWaXWLVuq8U3Ht1V67bXXJFwp5goLCy3hzJkzJ+7l7AeZNm2aJZySkhJx6DhItLBPgIjyWk70eqVGRoZlDBGR6dOni8/hEB/I66+9ZimruvSP4cPluOxseemFF37vt2JEBQUFMuqWW+SpceN+77di6w+iYyWP+DPJ9qE9hjXu8cdJgrh9xgYLfOVEhIPRKGVAGGU74wQWfv21cVZxaSl+oB3KXzAAlFrwJHjz7t0cRvm1DgHqoCxHFixYYJSzfOFCDunXTkDV+RcD77//vlFOQUEBMVfbVzWjHPXExLScKF/L7ai4SwDGjx9vnLN27VrcKOumKMqyxwpNnToVNxX+sB6sOR5Qdjo+lOVREjB69GhLOLv27OF8YCnQBphtwb0K8NhjjxEEngFKgP1791rC+XLaNARYCYxHjUNz5841ztmzZw9ulEVUFBULxcXFxjkAy779lhIqxgWrvDqH33QTUeBR1HmbMWOGJZzbb78dH5CMGrdHjhxpCWfJkiUko2zqHMCtI0ZYwgHo2bMnztJSduzaZUm8xXT/HXcQEcEN3H3bbZZxqksHDhzgwUce4f5t27jr1lt/77djRK+//jovjB3LbcOH/95vxZYtW0fITmiPAXXp3p0ClFerD/Aa9roF5UPrQQVMGWoCBlDTIl++IpSP4YcQ91c1rbDXSwDYAjyI8oGMAg0bNjTKSc/OxoW6PsWaEYKjamT2S0pISMCFSpjORSV/LqC+BddIUOctFchEXa8zLShrzcnJwYmKuzDq/Fmhk046iQhqEh5FHV/Pnj0tYUWAwyhv2EKgV69elnDcwNvAbcBiINWi5mAx7+iLqVh4sEKN9H15NTAGFXOm71WAlJQUHKh7x4s6Hp/PZ5wDEAoECFExLljVwO2c/v1xAENR47dpn/KYBgwYwGHUwkYBMHDgQEs4ubm5lKB8lsuB3r17W8IBuOeeexDU4pPpMbuy+g0cSBi1gHJWv36WcapL4XCYzm3bMtjt5uxj4HhAjdWNW7Tgwgsu+L3fii1bto5U9T4otkZ/9ZLjSCQiXTt0kGSQmsnJlllnPP744+LU5Z9eXVK2bds245yPPvpIXLp8MUGX4r3//vvGOZMnT5aAZoR12d8JzZoZ5yxevFgCutQP7Qua6vNZYjty4403/pcPbf/+/Y0zRJTfpE+XzvotLDMVEXnvvffix7Nx40bLOOedd16cU6tWLcs4X331VZxTs0YNyzibNm0Sj/YeDTqdcvjwYctY6amp4tYsq6yINmzYICG3O37uLjz3XMvsWp577rk457333rOEIaJKZ9u0aSPp6emydOlSyzgiIrfddpvk5eXJ119/bSln1KhRkpKSIjfffLOlnDlz5kjjxo3luuuuO2Zse2bNmiVffPHFMePbWl5eLjt27DhmjiemY2XuaKvqsmOh+mXb9vyE7Hbbv10zZszglVdeITk5mZEjR5KSkmIJ59tvv+X+0aOJRqOMuv12WrdubQln+vTpDL/6anbu2MGQa6/lH3fcgdfrNc759ttvufS889i1ZQutO3XipddeIzU11TgHYNu2bUyfPp3OnTtTp04dSxgAkUiEuXPn0rhxYzIyMizjVLfsceGPq6KiIr7//nuSkpJo1KiR5Tw7FmzFZMeCrZjsWLAVkx0L1S/btseWEXXp0oUuXbpYzmnZsiVvTJ5sOefkk09m8cqVlg9KLVu2ZPGKFZa9fmVlZ2czaNAgyzkul4tOnTpZzrFlK6ZAIGBp2actW7Zs2bJl688new+trb+0SktLefHFF3n22WfZvHnz7/12bNmyZcuWLVu2bNmy9RtkJ7THgKLRKBcMGkS91FTatmhhWadMUF0skz0e0i3yho3p3Xffxel04nA4eOeddyxh5Ofnk+Tzce1ll/H8o49St3ZtbrOoW+YNN9yAW/vDuh0O5syZYwlnzZo1JHk8eBwOQg4H8+fPt4QDytfy1FNP5YEHHrCMAfD6a6/RsWlTTjnxRGbNmmUZZ+PGjbRr147evXszb948yzgAP/74I5988oklPs6VtX37dp566ikOHTpkKQeUh6bVO1gikQifffaZpWMPQElJCa+99lq1XKPS0lL2799vKQNUp/qioiLLOZFIhI0bNxKJRH79f66iioqKLI85W7Zs2bL1J1D1beO1Tn/1plA9unWTuiDPgZwFkub1SiQSMc4ZNWqU+EFSQNJ0M6D9+/cb58yePVuCIOeDDNIemjNmzDDOyUxMFCr5tjp0U5v169cb5XzyySfi0cfh1CynBf6wZWVl8YZdibrJlRPkwIEDRjki6ho5K3l1JobDxhkiIm9MmiRQ4REMyHfffWecs2/fPnFU8s90gSxatMg4R0Skb9++EgZJ1iwrmoOJiNx9993i0dfHCzJ9+nRLOOXl5eLUx+IH+eGHHyzhlJWViVvfPyGQLp07W8YJeb3x2E5OSLBkPBUReeqpp8Srx4amjRpZwhAR+eGHH+JjUGZysmXHs2HDBnHoOABkzZo1lnCi0aikhEKSqOPhaOcA/4tWr14tqaGQ1KlRQ8rKyizjFBQUSL1atSQrLU22bNliGUdEed7efffdlsVBTO9OmSKXDBgg8+fPt5RT3TpW5o62qi47FqpfPzfe2wntMaAUh0NmgQhIuf6AX7BggXFOotMpKTrRrKW79Y4dO9Y4JysrSzro4xGQziBpaWlGGUVFReLUk65skAt0p+MEkFGjRhlltWrVSnwg9UAy9Xlzg8ydO9coZ+nSpeLTk9Z7QDw6SZ80aZJRjohIZmamuPTxpOjjsUKndugQT9C9+njGjBljnPPoo49KAKQVSB997nr27GmcIyLiB+kJMlVP/G+77TZLOE59HHfpBNDtdlvCGTdunHhBMvRCV0pKiiWc559/XsIgl+h71qqYmzdvngDSFaStjrnly5dbwvKA1AYZqK/Rvn37LOGc0Lq1BECG63Fuzpw5lnA6deokIR0LIZBmFnSNFxFZsGCBuEG+0dcozaKYExFJD4clSY8/V199tWWc008/Xbx6EeW4hg0t44iIBB0OSQG57rrrLGMcOnRIQl6v3AGSl5NjGef30LEyd7RVddmxUP36uZzPLjk+BuRyOtmof94FlIIlXWddPh9OYDawF+X/l5OTY5yTlZXFVpQ3YzHK7zQzM9Mow+1249A/7wdmofxBBfPnLisri6h+/d0o71EHkJycbJSTnJwc92x9D+K+wVbEQmZmJm5UHIA6b1YoOT2dKMrX0qM5oVDIOCczMxMBNgBLUdcnKyvLOCem1cAHqGOyqltvVL/+O2gf33DYEk5ubi4C7EGNCbVr17aEU7duXQSYCRywhKCUnJyMA1gO/ICKhUQLvL0B/F4ve4A5qHE7GAxawqnfoAECfIwah6zqSl63bl1AfQ6BdbGdmZmJF5gC/Ii192pWzZoUo+4lq7rtA7Ro0QI36r5t1LixZRyA1HCYg5pplbxeL6mJiXwWDFrabd+WLVu2AIuWuKtZf/UntI888ogEQE7WT/86tWljCWfZsmXi009hkkCS3W5L/OVKSkokQT/5S9FPTU2X54qIdNFP/9BPYdBPtEz7de7YsUNc+olFsi5r9Tgclpy77JQUQT+9AiTRwmsU4zhAbrjhBuMMEXWPQoWvbkZCgiVl7pFIRNKCwf8qObbKt/XLL7+Ml+emWlSqLSKyc+fOOMfz/9i77/CoyvTh498zkzKZSSOhBAhBUJReREAQBAvYFUXFiigWVHSFVUQRyyI2FhuuYsGGYkMEFNBFWEAQFVkQkd4CAUILCell5n7/mBnW366+u2LuSfH+XJfX6q7s98zMk0meOSfnBikrK1NrdWzfPngJelycVFRUqHWaNW0qMaF198knn6h1BvTvf2TNXX/ttWqdjRs3SkJMjESDPPvss2qd0tJSOf644yQKZHQlX4Hy7xokJ4sDUjc+XnUtXD94sMSEzs6WlJSodfx+v4wePVoee+wxtUbYpEmT5PHHH1fv+P1+tXnRP7d7926ZPn16RFqRVFt+djS/n62FyLM5tL+gNs2PWr58OVOnTqVz585cc801ap39+/fz4osvcswxxzBo0CAcx/nvf+go+P1+nnzySfx+P/fffz9ut7vSGyUlJZx56ql8s3w5ASApNpY5//gH3bt3r/TWtm3b6NC+PYWFhRx//PGs/vFHoqOjK70TCAQYNGgQi+bPp+NJJzF9+nSVTlhBQQFerxeXS+9ij507dzJr1iw8Hg+XXXaZ2tkygAULFrB27VqGDh1KVJRNNfsjKykpYcOGDXTo0KGqD8VUA7Xp5wXz+9haMGG2FiLv1/Z8tqG1hfiHV1JSwg8//EC3bt2q+lBMNWDvCybM1oIJs7VgwmwtmDBbC5H3a3s++x1a84cXCATUR3MYY4wxxhhjKp9taGuJPXv28Oyzz6rOHQXIz89n1KhRvPHGG6qdVatW0bx5c5o3a8bKlStVGoWFhTRKTKSOz8dpvXqR5DhMmTJFpfXTTz9R1+fD6zi0bN5cbR5kIBDgnHPOoW5KCj179qSiokKlAzB16lROP/10hgwZQlFRkVrHHJ1AIMDbb7/NA/ffz4wZM2xeZzUkIqxcuZKFCxeqz4gtLCwkMzMzIvNhjTHGmIiK2G/xKqrON4UKBAKye/dulRvzhH322WfiC92cxwvS94wzVDpbt26VuNANc+JAYl0ulc4333wjntCNX6JCN7VZunRppXea1Ksnp4DsBikFmRB6/oqKiiq1s2vXriM3nooJPX9epZtC1U9IkMahkSPHgiQpjWp5YPToI2NhAPE4jsqNu0RETuzY8cgNesaMGaPSEBE544wzJCE0IigxMVGts27dOokO3SQsSbFzxUUXSWuQQSBNQe6/5x61VozLdWS00p49e9Q6XTp2PHKjK625uiIi2dnZ4o2LE6/XKwcOHFDr3HTNNZIC0gykWYMGKjc8EwneiMwbeo2OTUtTGw8UCASkYWqqxILUT0pSnXO6a9cuGThwoMpYsn+3cuVK1fUmEpxDe8ctt8gNV10l+/fvV2298sorcs0116itg9qquLhY3nzzzYisOVMz2E2hIs/m0P6CSCzEkXfeKVEulzz28MNqjcSYGGkAcmZoxqAPVDZLPp/vyB1TwwPtNeYzpiQnS2xo1mTj0F2BkxTuBusFWce/5t0KyAkgw4YNq9TO5ZdfLtGhH8JPC71GgGzevLlSO/n5+eIOzYA8LfT6eEBWrlxZqR0REY/jiCu0OU8MPZ433nij0jvhDwPC8xk1P4NLAHkY5J3QBxtaP1Q6oQ8bHgx9ra5Zs6bSG1lZWRJPcMapC6RN6M7aGnedvfnmmyU29IFQPZDY2NhKb4gENxXe0PtBCkic46h0RETcbrc0AUkD8Sg9ni1btkh86P0gGqQzyFNPPaXSyqhTR3qFOt1AHlH6fjR8+HCJD70vxINcf/31Kh0RkYZJSeIOPX8aX0Nhzz//vESH3hO0PnAQEbn5uuskIdTp17OnWufLL788suaOa9xYrVMb3Xb99XJKXJzUiY2VTZs2VfXhmGrANrSRZ3Noq8j+vXtJdLvZv3evWiPg9+MAzUBtHihARUUFbiCG4MxEAQ4fPlzpnbKyMhygbugvF1Ch8DuuAeDfJ5r6gLy8yp1yWVhYeOR1aRH6TzfBx1mZKioqcAi+Nu2BciCK4GXilS0gggBx/GvNFRYWVnqntLQUh+DzpX2hpAM0B04ItSr79fm5VKBlqFNQUFDp//9lZWVEEZzf6wMKCF7eGggEKr2VnZ2NEHw88aD2++jFxcVH1lwFwTWoxe/3U5/g66T1eEpKSogh+HUaQ3DOaUlJiUqrrKyMIiABiAWKFNYcBO+CD8F18PN/1lBSUnLk/Vvjayhs9+7dRBNcc5qXheceOoSf4PtQXm6uWudQqBMH9qsiv1HeoUM0KSsjxnHsuTOmuonsvlpHdT5DW1RUJP/4xz/ULscUERk3bpx4Q2d7YkCOzchQ6cyZM0fiQ2dIokMtjTPBb775pnhDn/CHP7F+5ZVXKr2TEhsrV4QuNxaQuaEzmtnZ2ZXa+eGHH46cZfTyr5m35eXlldoREUl0uaQDSFuQrqHnUOOyv8suvfTIYwpfRq11+VpCXNyRS47POP10lYaISHJS0pEzgJpvjS+++GLwcuPQWtDg9/ula5s20g+kL0gXkIEXXqjSKi8vl+jQ4/GBLFq0SKXj9/ulXkKCxIe+jiZMmKDSERFZvHixRIXWtcYVDiLBx9OnSxdpAXISSHJsrOzcuVOl9dYbb0g8yPEgSTExkpmZqdIpLS0VX+jqDS+ozoddtmyZtD7+eBk+fLhaI+yJJ56Q5557TrWxe/du6XniiXLiCSfIhg0bVFs3DB4s7Vq2tLNLv9HevXtl1N13y3ilKylMzWNfQ5Fnlxz/gtq0EGfNmiXdu3eX+++/X/X3dRctWiQNGzaUk046SWVDFjZx4kSJcbslxu1W+0Fi69atkuQ4khi6NDMO1H44mjJlikSHNjA+x1H7wTUvL0/S69WTZJB6SUlqv88YCATkjttvlyb160vHtm1l69atKp2wXbt2ycGDB1UbIiIHDhxQ25BFWkFBgYwcPlzO69VLHn34YSkrK6vqQ/rdAoGAZGZmql76+XPa3yPKysrkvffek5deekl2796t2tqwYYN8/vnnkpOTo9qprWrTzwvm97G1YMJsLUTer+35bA6tzY/6w5szZw5ff/01o0ePJi4urqoPx1Qxe18wYbYWTJitBRNma8GE2VqIvF/b80VVwbEYU62ce+65NGvWzDazxhhjjDHG1DDVbkP78ssvs2DBAsrLy7nyyivp2rUro0aNwnEcWrRowUMPPYTLZfeyqkqlpaVER0ervw7hmy54vV7VTlZWFj/99BPHH388brdbtWWMMcYYY4ypPNVqZ/jtt9+ycuVK3nvvPaZMmUJ2djaPP/44d911F1OnTkVEmD9/flUfZrVTUVFBl/btiXMc6icksHHjRtWOx+PB7XYz+dVXVToAbsch1eejrs+H23GCJtpCAAAgAElEQVTUOp6YGFo0acKgyy7DExXFnj17VDqPPvoo8Y5DsuMQ5TiVfiflsMLCQpJjYvA5DokuFzk5OSodEeHUbt2Cj8ntZu3atSodgHnz5uF2HGJjY9m9e7da5/Dhw9RNTeXETp3Ytm2bWgfg/PPPJyEhgQ0bNqh2ht91F3USEnjppZdUO7NnzyY1NZURI0aodgC2bNlCruJdYMO+//571q9fr9ooLS3liXHjGDFsmPqai5S///3vdOvWjVmzZql2tmzZQt++fXn++edVO8YYY2qACP4e73/117/+VSZMmCBDhw6Va665RlavXi09e/Y8cpOjefPmycO/MD/vj35TqNtvv13iQne09YE0TEpS6bzwwgsSG2rEheZbHjhwoNI7d911l8SDXAFyVehOxzfffHOld2bNmiVxIBkE5916QByl2ZZxoccRH3retO5u27J5czkfJBNkMEhqXJxKZ+LEiXICyCaQv4IkKs4EjQrdMdWjfPdhQJIJztWNUex07979yHqIU+y8/vrr4gmtuSiQ5cuXq3Ty8/Ml5mfvP+PHj1fpiIh0OfHEI3c/37Vrl1pn1KhREhdac5qP566hQ+UYl0vSQTLq11e5I3lYo9Adoq+++mq1xvbt2498L/KCrF+/Xq2VEPpa9YLqHYg/+ugjSQBJdhzVGyHm5+dLk8REqe/xqN2FOmzYDTdI66ZNVV8fEZHLL7pIEl0uefTRR1U7kVZbfnY0v5+thcj7tT1ftbrk+NChQ+zevZtJkyaRlZXFrbfeiojghM7Q+Xy+X52puW7dut/cKykpOao/V918s3QpAF6gmOAcVY3HtXjxYqKBm4GZwBbg66+/5rjjjqvUzueff44AownOH50BfPnll5X+mGbMmIEb2ENo3iTBM48az10swbm3HoKzQcs5ujX732RnZjIKyAAuBz4pLlbpzJs3j7OA44ArgAeUnrdAIIAr1PgBWIXO8wbBWaD5BL+OHMXOd999RwpwJ/C0YmfKlCl4CM43Bfj000/x+f598vLv99NPP+EiONeyDJg8eTLnnXdepXcA1qxaRQJwCPjiiy84+eSTVTpT332Xcwiuh7feekvt8Xz31VdkBQKkAgf372fVqlVqv8tfkJ9PHPDZzJlqa+7vf/87LoJfQ4XAtGnTuOSSSyq9U1ZWhpvg94ixwHvvvUffvn0rvQMwYcIE3MBhEebMmUOLFi3+6585GmvWrGHP4cPEAO+88w4XX3yxSgfgnffeI7asjI8++ogBAwaodRZ/8QWeQID3X39dZR1Uldrys6P5/WwtVCMR3Vb/F+PHj5fJkycf+ecLLrhA2rdvf+Sf582bJ4888sh//Lk/+hna6dOnS0xofmYcyLn9+ql0li1bJk7o7IgPJNblUpmvO3/+fPGEOomhx/T5559XeiczM1NiQ2fjfKFP+lu3alXpHZHg2T9X6AwjIMcff7xK5+GHHpI6IGNAGoJc0r+/SmfFihUSBzISpCNIB6XHIxJ87sJnfDLS09U6Xbt2FffP5gRr+fLLL4NnfBTP1IuIbN68+cjVAIDqqBtCZ4GjQPXs0vTp0yUWJMXnUz1btmrVKqnjdksdt1s2b96s1vlk+nSJj4mR5OhoGXLVVWodEZFhw4ZJ3bp15euvv1ZrlJeXi8/lCl7J4ziq89ePa9pUkkPfJzRfo+LiYmnSpIl06dJFrRE2YsQIGTx4sOqZepHg+L0JEyaozgkWEZk9e7b07du31vysFVbbHo85erYWIq9GzKFdsGCBDB48WAKBgGRnZ8uZZ54pt9xyi3zzzTciIjJmzBiZPXv2f/y5P/qGViR4+eyFF1wgY8eOVZ1D+8UXX0jn1q3lgn791GacioiMHTv2yOZvzJgxap1nn332SKdBgwZqz11FRYX4fD4B/s+HNBrefPNN6dC+vTz99NOqneXLl8tFF14oY8eOlYqKCrWO3++XadOmyeLFi9UaYVu3bpUZM2aod0RE9Yf9sMOHD8vy5culqKhIvRWJRqRF4ntEVlaWrFmzRvV9O9IisbYj2RGpXT8vmN/H1oIJs7UQeTVmDu1TTz3Ft99+i4gwfPhw0tPTGTNmDOXl5TRv3pxHH330P+5Ea3Noze9la8GE2VowYbYWTJitBRNma8GE2VqIvBozh3bkyJH/8d+98847VXAkxhhjjDHGGGOqs2o1tscYY4wxxhhjjPlf2YZW2ZYtW5g6dSo7d+5Ua1RUVHDFgAEkxsbS+rjj1GZ1+v1+6iclEes4xDoOo0ePVukAbNiwgZiYGGJiYlRndT7xxBO4HYe2rVtTNyVFrfPGG28QHZpBG+M4ZGdnq3REhCsGDiTe46HfmWfi9/tVOgBvv/026XXr0ve003717uOVJTMzk3379qk2Iun777/n/fff5/Dhw6qdFStWcPfdd7NlyxbVjqn+CgoKWL9+PYFAoKoPxRhjjKlcEfw9XjXV9aZQ69atkySPR45zuyXF51O7++fQG28UL8j9IMeANFCaQ9uze3fx/uzOw7EgP/30U6V3/H6/xITuXpkQuguxxl0fi4qKjsw49YXuQty9e/dK75SVlYkr9HzFg0SH/tJwxeWXSxxI39Br1K1zZ5XOvHnzJD50p14PSIOUFJWOiEhsbKz4Qq/RRRddpNYZO3aseEOvkeYdTV9//XVJAjkFJDk6Wu3GNl9++aW4Ql9DbpDt27erdEREmjZqFJzf63Kp3qH18ccflziQNK9X9u7dq9b58MMPxRdaCwsWLFDr5ObmynENG0qdmBj54osv1DqZmZkSA5IEUj8+Xq0jIjLg/PPFA3Kh0t32wwYPGiTxICkej+odr7OysiQ9KUlaN2+u1hAJ3uAqweWSBFC94aKIyGk9e0pDn++of3aqbtavXy/XDhig+rX6c3YjIBNmayHyasRdjo9Wdd3QvvDCC9LCcaQByHFut7zzzjsqnWPS0uRKEAGZHvqhReOOmXGOI4DUDd0VOAlU7qS7Z88eiQK5HOQqxVEgS5YsOTKmpX5oY+Y4TqV3srKyxB36IKB+aKPpVtrQ+jweOSO0FgYpjoW58847xQWyH+Qy5TE30T8bcaPZcbvdRzaALsVO55Yt5WWQAEgqyIYNG1Q6p59+uiSH1lw8yEMPPaTSERGJDXWSQX788Ue1zrEpKTIB5FiQxx9/XK1Tt25duR7kYpBmzZqpdT744AMBpB5I727d1DqjRo2SuiANQl9HxcXFaq1okC9DHc07N3sc58ja1vhgNezyyy+XOqHHozke6M9//rNEhT6469q1q1pHRCQm9H08EqOIIuG2IUOkAUhP5QkCYbaJMWG2FiLv1/Z8dsmxop49e7I3JoZEx2F/dDTdunXT6fTpw6fAM8CDQJTXi+M4ld5p2a4dcUAFkAiUAn369Kn0Tv369XEBnwLTCV4Xn56eXumdDh064AK8QBHBx9O6detK79SrV48AUB7qVACV/+oE9Tr1VL4GrgGmAa1POEGlc8YZZ+ADOgGfAUler0oHgs9XOcHXqWPHjmqdW2+9FS/B16bZsceqda656SbGAAOAUpeLjIwMlc7QoUPJA8oIrruBAweqdADik5IoAwqBli1bqnUGDBnCSOBgVBRXXXWVWufRRx9lKjAXePLJJ9U6p59+Og0TEihxHO645x61zuDBg8kn+LWUFB2Nx+NRa/Xq3p0zgVNOPFHl+1DYaf36UQS43G6OO+44tc7YsWOJjo3lmHr1OFbxfeHhhx/GS/BOnW+88YZaB6Bdq1Y40dE88cQTqp1IufH22+ncqxf3/OUvVX0oxpiqEuGNtYrqeoZWRGTlypUyceJE1VZJSYn07t5d4h1HGqWmqn2KXFJSIj63W6JCZ02vGDhQpSMSHPxO6IzcwoUL1To33njjkU5UVJTaGYWxY8dKVOhT/miQ9evXq3QqKiqkR7du4oC0adlSSkpKVDoiIg8/+KB4o6OlZbNmsn//frVOIBCQzz77TFavXq3WCCstLZUlS5aod+bOnSvPPPOM6mWzIiKffvqp9O/fX5YtW6baEYns7FHNy5rDysvLI7LmAoGA6hznsL1798rChQsj8jpF4vFEsiNiZ2LMv9haMGG2FiKvxsyhPRo2hzay/H4/LpdL9dP3SIvUWvD7/f8xR9lUL/a+YMJsLZgwWwsmzNaCCbO1EHk1Zg6tqf5sQ3b07LkzxhhjjDGm8tjv0BpjjDHGGGOMqZFsQ1tL5OTk8NZbb7F27VrVzojhw4l1u0ny+Vi+fLlaZ9euXTRp0oTGjRuza9cutc6UKVPwuVx0bd2arl27qnXKy8vpc+qppCUnc/fdd6t1APbu3cucOXNUZx9D8PLpWbNmsWPHDtVOSUkJ48ePV79RSiQVFhayc+dOasFvfAAQCATIzMyktLS0qg/FGGOMMX8wtqFVtmDBArp06cJ3332n1ti1axcNU1MZMngwHdq0YeLEiSqdB0aPZtKzz1IRCFBYVMQpXbuyb9++Su8UFRVxbHo6+7OyOLh7N8emp1NQUFDpnU2bNjF00CCiRSgHVi1fTq+ePSu9A9AoOZmsr74iNi+P1ydMYNA116h01q1bR1paGgPOO4+MjAwWL16s0vH7/SRERXH1RRdxQtOmapv0iooKGsXHc//Ikdx8ww306NRJpQPwl7/8Bbfj0LZ1a0455RS1zvTp02kYH8/xGRmkeDxqm1q/309CXBwuxyEjPV2tU1ZWRkb9+rQ45hgSPR4yMzNVOgBPP/008Y5DfFQUZWVlap1t27aRHB1N9/btyc7OVusAnHPOOTRp0oSioiLVzlUDB1InMZFPP/1UtbNhwwauuuoq1qxZo9rJzc3luuuuY86cOaqd2kZEGHrDDXRu00b9NTLGmIiJ2G2pFFXnuxzXjY6WeiBpPp9a44477jgyVy4RpKFSKz4uThyQlNAc1QSQ559/vtI7EydOFG9oXqs3NJfviSeeqPTO1VdfLXEgMaH5jN7QXxrcoRmddUHSQJIV5t2KiPQ980zx/Wz2aPNGjVQ6r7zyitQBKQV5LPRaafjyyy+PrDW38hxaV+ju3fHKc2gTYmPlApAVobWndVfy2bNnS1JozcWDbN++XaWzYMECiQt1kkDuvPNOlY6IiA9kGEgjkGHDhql1GjdqJGeD9AJp3bq1WiczM1PcIHVA2rRpo9bZsWOHJIZeo7ioKLWOiEir9HSpB9KiQQPVzoUXXih1QZLdbtVOWG25m+myZcskLjT7uLPimqvNastaML+frYXIszm0VeSY448nD2ipOD+zffv2CJBPcIZm3UaNVDqpdeviBoqBBMAPKvP/OnTogB/wALGhztHcxfq/adeuHRVAPMHHFAcQHV3pHYAYgs9ZPpAERMXFqXRO6tKFAJBHcPfXpkMHlc6JJ55IMTAZmAVExcaqdJo3bw4E14CP4JrQ4omKIg4IoHvpSpNjjmEZ8CTB9Z2amqrSOf7446kADgMlip309HT8oU4AaNu2rUoHguvsfeAQwRmuWk7t3ZslwD+Bvn37qnUaNmyIj+Dr079/f7VOSkoKDsH3n4xjjlHrAJzcpw95QJdevVQ7ffv2pQA4TnE2bG2UkZGBx+2mAOjSrVtVH44xxlSOCG+sVVTnM7SREAgE5LyzzpI6Lpc0q1dPcnJyVDo7duwQV+gsTDxIWv36anNb0xo0EA+IB6R+vXoqDRGRhKgoiQqdKfOB2gzSRx99VDyhM+hekHXr1ql0KioqpF2LFhIN0rRePdU5tAMHDpR4kIToaMnNzVXrPPLII5Lickm96GiZMWOGWqe0tFSaNGkiiYmJkpWVpdpp0ayZeKOi5I033lDriATP0l500UVH/R75v/roo4+kS9u2Mua++9TeE0SC6/vBBx+U2bNnqzXCZs6cKS+//LJ6J1IOHDggS5cujejs1tqktvy8ICKye/du+eabb1S/Vmuz2rQWzO9jayHybA7tL7D5Ub9dUVERCxYsoH79+qo3UYqkN998k2XLljFu3Djq1q2r1ikpKeHgwYOkpaXZ+J5qzN4XTJitBRNma8GE2VowYbYWIs/m0JpK4fV6Of/886v6MCrV4MGD6datm+pmFsDj8dC4cWPVhjHGGGOMMX8k9ju0xhhjjDHGGGNqJNvQ1hIiQl5eHn6/v6oPpVLs27eP8ePH89RTT7F37161TnFxMYMHD+bqq6/m+++/V+tAcFZnXl6e+uzR8FqoBb9NYIwxxhhjzP+XbWiVVVRUsHr1agKBgFqjtLSURklJJCcn442KUt2YJScmkuw4xDsODz30kEpj//79NE9LY/rIkUy/916ObdhQZVNbXl5OHZ+PKW+9xcqVK+nTpQtz586t9A7Ac889h8ftJjU5GbfLRUlJiUonNzeXJLeb+snJJLhc7NmzR6UDwbtR+xyHaMchLy9PrZOTk4Pb7SY+Pl71A5ucnBwaJiXRo0MH1q1bp9YBeOWVVzjrrLM4dOiQamfUqFF4vV4mT56s1hAROrRqheM4JHs85Ofnq7UiadeuXezfv1+9s2XLFhYuXKje2bx5M6NHj6aiokK1U1ZWxrRp09Te42qzvXv3kpWVVdWHYaqBrKws1Q/zjal1InVXKk3V+S7Ht11/vfiiouT+P/9ZrfHII4+IN3RH4ASQ5krz//bs2SOJII+C9FGc1TlhwgTpBhIb+qub0hzaOXPmiCc0QzX8n/Feb6V3REQIPZZLQnc6bty4sUrnxiFD5GKQAMitID1OOkmlIyISHXrOUkESEhLUOlGh18cD0rJlS7VOi4wMuRhkBEiiy6XW2bx5s3hBzgJJr1NHrZOfny+JoXWnNV9ZRGTu3LmSAHJpqNWvXz+1VqTs2LFDkuPiJDkuTvbt26fWKS0tFa/jSCzIq6++qtYREUkOvT7HNmum2unevr3Egpyk+LVaFbR/XsjJyZHU+HhJiotTm01tKof2Wti8ebMkxcVJany8HDp0SLVlfh+7y3Hk2RzaKuI4DiKC4zhqDZfr315GxRYEZ03qnW8O+veLZTWfP+fnvQg8d8IvvGaVSEJ/BZQ7P29pvj4R4zgECM68jYRI/nJAJC4+Dz8e7TUXCY7jqL8XHGn9vKksEl+r4de/VrwnRJDjOEeeM3vu/thsHRhzFCK7r9ZRnc/QlpeXy5o1a8Tv96s1SktLpWFiohCap7pixQq1VlJS0pFZquPGjVNp7N+/X+JdLukGcjKIz3Fk7969ld4pKysTj+OIK7Qviwf54osvKr0jIvK3v/1NokDcoTPbWvNhc3NzJdHlkqjQXN09e/aodEREOnbsKF6QKFCdQ3vw4EFxu92SkJCgOkMzJydHGiYnS3J0tNqc4LDJkyfLueeeq/7p+5gxY8Tn88k777yj1ggEAtKxdWtxQJI9HsnPz1drRdLu3btl8eLF6p3t27fLV199pd7Ztm2bPPzww+qd8vJymTFjhpSWlqq3IikSPy/s27dPdQa2qRyRWAtZWVmqV4eYymFnaCPP5tD+gto2P6qwsBCv11srPtXbv38/U6ZMQUS49tprqV+/vkqnpKSEO++8k1WrVjFp0iROPPFElQ4Ef9ewqKgIn8+n1gh3CgsL8fl8tWItRFpte18wR8/WggmztWDCbC2YMFsLkWdzaP8AtDdKkVSvXj1GjBih3vF4PLzyyisReVNyHCcir5HjOMTHx6t3jDHGGGOMqWo1/5edjDHGGGOMMcb8IdmG1lRbgUBAddxRpG3bto2FCxeSk5NT1YdSKQKBADt37qSgoKCqD8UYY4wxxvxB2Ya2lnjmmWdo4PXS7/TTVTeBy5cvp15KCp07dVLdyFxx6aV43G5i3W4u7d9frTNt2jSiHYd2rVvTpnVrtc5999xDu+bNGXbaaaSnprJ06VK1Vod27UhwHJqmp6s1cnNz6dyqFScccwz169Th448+UmsBrFy5ks2bN6s2AObNm8ecOXPUO1OmTOH2229XnRMMwd/vueOOO8jOzlbtRMrbb75Jh2bNOLtnTzIzM9U6ZWVlvPTSS3z00Ufqc1trm6KiIhYtWmQfdBljjImcyN2XSk91vstxJGzevFliQ3e1bQxy0003qXTKy8vFFZoHmgjSsH59lc53330n7tBdh+NDd9H9+uuvVVpRocfiAYkGmTNnTqU38vPzJQZkC4iATAZJ8/kqvSMi8thjj0lc6LEkgfTv31+lc9/dd0tdkCtA6oLERUVJWVmZSqt1q1biDc1Ynjp1qkpDRGTEiBGSELqDd5P0dLXO+++/f2QmaGJ0tFqntLRUfCAZoTWuadbMmZLg8ciYe+5Ra2zYsEGSoqIkFaQdyJnduqm17ho6VHrHxUk3j0ceUHxMgUBA+p1yijRKSVGfPTr8llskKS5O5s2bp9pp1aSJNAE5Li1NtbNo0SJJ9nrl9uuvV+1s375dmtSrJye3a6c6rcBUfytXrpS6CQlyXp8+VX0oppqoLfuImsTm0NZimZmZeIF4wA0s//ZblU5xcTEAXqAI2LNvn0pn69atuIGTgG4EH9OmTZtUWhUEH4uX4NzWVatWVXojPz+faOCY0D93BEpCz2VlW7BgAXFAEhANfP/99yqdfbt2cRgYCXQAyv3+I+ujsm3euBE3UAxMnTpVpQHw6aefUkzwspVdWVlqnVWrVlFG8Ou1oLxcrZOXl0cJMJzgOtf07dKleMvLWfTll2qN7Oxs4kWIAbYDWYqv0aa1axlQXMxFJSVsWrtWrVNeXs5X332Hv7CQ9evXq3UAFv3jH3jKytS+P4Rl7t7NSGDH3r2I4hCFFStWEFtWxsIFC9QaAJs3b6bk8GFWrVtHSUmJastUb6tXr8ZdUsJ3K1ZU9aEYY/5dZPfVOv7oZ2jLy8slKSpKYkNnfTQfV7OmTcUJzVL9+OOPVRqFhYWSEDrDmBQ6S1tYWKjSatSggUSH5sMCKjM0A4GANPD55BqQj0HagFw5YECld0SCs1TjQme1PSDbtm1T6Xz55ZeS4DiSAJIG0q9XL5WOSPAKhCiQWLdbdbZlXl7ekZnEml9DOTk5UtfnEzfIvYpn/0REWrVoIXVA+vXrp9opKCiQV199VbZv367WKCkpka5t2ki62y3JUVEy6W9/U2t9++23cmxamhzboIGsWrVKrRNuvf/++xIIBFQ7mzZtksmTJ0tRUZFq55133pHOLVrI65Mnq3ZKSkrk9ddfl/Xr16t2AoGAfPjhh6pXh5iaoby8XN5++2355JNPqvpQTDVRW/YRNYnNof0FtWl+lIiwe/du6tatS2xsrGpr7969+Hw+1dEw+/bt495770VEeOqpp9Tm0AK89tprLFmyhOeff57ExESVRm5uLpddcAFb1q7lwiuv5Onnn8fl0rlAwu/3s2fPHtLS0oiK0pvMtWjRImZ8+CGNjzmGYXfcgcfjUWtFUm16X6htSkpKWLJkCWlpabRt21a9Z2vBhNlaMGG2FkyYrYXIszm0tZzjODRu3DgirQYNGqg36tevzxtvvKHeAbjxxhs55ZRT1DazAMnJycz76iu1//+fc7vdpCveECqsd+/e9O7dW71jTJjH4+HMM8+s6sMwxhhjTDViv0NrjDHGGGOMMaZGsg2t+c3Ky8tVb/ZhjDHGGGOMMf8L29DWEtu3b+fJJ5/kH//4h1qjrKyMPiefTEJMDLEuFy+/9JJa69tvvyXJ6yXR62XJkiVqnddee40Yx6FT69Y0zchQ6wA899xznHPOOSxevFi1886UKfTr3ZsXX3hB9YOHAwcO0LNnTyZMmKDWCMvNzY3IHUZffvllXnzxRfXO9u3bmT17Nn6/X71Vrngn5bDc3FwmTpzIunXr1Fv2gZoxxhhj/o9I3ZVK0x/9LscHDhyQWJDmoTsCa92B7/6RI8X1szsPx4Ns2LCh0jt+v1+8ICeBdA3NBdWa/xcTmt/rBnEUZ/g+/PDD4gu9RrGgdmfOmTNnShRIcugx/e2FF1Q6IiKJIE1B4kAuvvhitU67du2OrLfnn39erXNa796SEHruGqemqnVmzpwpcSCpIMkxMWqdQCAgp3btKvEg1w4cqNYpLy8Xn9styaG7a69YsUKt9fG0aeKJipI2zZrJoUOH1Dr5+fnSrmlTaZORoXpnbRGRR+6/Xy4791zJyclR7UTKnXfeKakul9xyyy1VfSiVSvvnBb/fL3fedJMMvvxyKS4uVm1Fyicffyxnn3KK6nuCiMiKFSvk7FNOkU+UJi/8u9rys2MkXX/11ZKRlCTz58+v6kOpVLYWIs/m0NZia9euJQEoBOoAbyvdTGnJggUECM43LQBKgA0bNlR6Z9++fbiAd4H3AAedmZM5OTmUAenAOIKzWz/55JNK7wBMfvVVUgk+b4nA3LlzVTqff/45cUBMqDPjww9VOhB8LN8DFwKzZs1S66z78UeiCK7v0aNHq3VWfPUVRQTXW+7Bg2qdcePGEUXwjnyHy8rUOqWlpaz87ju8wKcff6zW2bJlC+V+PzEEZ+t+8MEHaq13X36ZRysqcPbuZfny5WqdmTNnsjkzk007dqhf9fLQY4+x+O9/Z/78+WqdSHpv0iSiAgE+njy5qg+lRtm5cyeTJk/mk+nTWblyZVUfTqWY8MgjrFy6lMmKV3MBTH7xRVYuXcqERx5R7Zij9/HUqZTk5fHEE09U9aGYWso2tLVAhw4dKABigX3AncOHq3TOvugi3EAp4An12rVrV+md+vXrUw6cDfQF/KBy196UlBRigD3AI0AuMHTo0ErvAIwcNYq9BJ+3w8All1yi0rn00kspBYqBfGDwzTerdAB8wLHALPSeN4C+55xDORAHTJ06Va1z3sCBRBNc302aN1frPPvss5QBRUC9hAS1jsfj4ewLL6TU7ebG229X67Ro0YKEuLgja+7GG29Ua906ciQTkpOp37YtPXr0UOtcdtlldOnShc6dOtG3b1+1TkxMDC9NnMjl11/POeeco9aJpD//5S9IXBzDHnigqg+lRsnIyODhBx9k6LBhdOnSpaoPp1KMfQIrBwQAACAASURBVO45zr78cv50zz2qnT+NHMnZl1/O2OeeU+2Yo3fbPfdQv2lTnnrqqao+FFNL2RzaWjI/6uDBg8yfP5+2bdvSunVrlYbf7+eGa67hvfffJyY6mnc/+oiLLrpIpbV9+3Z69+6NiLBo0SKaNWum0vnqq68489RTcQNde/dm4cKFKh2Azz77jPnz5zN06FBOOOEEtc6CBQuYNm0aZ599NhdeeKFap7y8nAceeIDzzz+fXr16qXUiaenSpaxevZpbb71VtXP48GH2799P8+bNcRxHtRUJFRUVzJ8/ny5dupCSklLVh1NpatP3CPP72FowYbYWTJithcj7tT2fbWhtIRpsLZh/sbVgwmwtmDBbCybM1oIJs7UQeb+257NLjo0xxhhjjDHG1Ei2oTXGGGOMMcYYUyPZhtb8JoFAgPnz57Nt2zb11vr161m/fr1qIxAIcO+993LbbbexY8cO1VYkVVRURKxTC35rwVSCSK05Y4wxxpifsw2tsnfeeYfmzZvz2WefqXbOP/98HMchJiZGteN2uznzzDNp3rw5559/vlrn3LPPpnWrVrRu1Yp+p5+u1mnSoAETnnqKhQsX0rRpUw4cOKDWchznyF9aAoEAbschOjoat+NQXl6u1krwekmNjibe5VL9MKCgoACfz0fDhg3VGgD5+fl4oqNp27o1GzduVG2NGDGCli1bqn+IsnHjRsaOHcuePXtUOzcPGkRMdDQntWpFYWGhWqegoICLLrqI8ePHqzUguDk//vjjVW+qVlvt2LGDsWPHqn/oOWfOHDIaNGDQFVeofqjm9/t5YeJE1fFNxhhjfqdIDcLV9GtDdv+bSAxErhsVJfVBGsTFqXaiQOqDJCq+pHl5eQJIKogLRHP5OCAxILEgjmKH0GOpG/rP8ePHq3TGjx8vSaHXKFrx8WzYsEESQp1kkE8//VStlQjyJEgKSHp6ulqnTZs2khh6fd5//321zqWXXipukASQOklJah0RkbjQmuvUqZNq56wePaSB48gtgwapNQ4ePCgel0vyQE50uWTGjBlqraFDh0pdkCjlb10jRowQT+hr9ZlnnlFt1TZXXXSRNHAcGXDWWaqdpmlpUj/09bp+/Xq1zpw5c6RedLREuVxSUFCg1jE1RyR+djQ1g62FyPu1PZ+doVXW7uSTKQa69+un2vE7DkVAQLHh8/kAKAMSAa/Xq9YS/jXrVvOC1iiCj6UUiAa6d++u0unfvz9+gvNh9c6ZQqNGjSgIdYqAjh07qrXKgLFACXD11Verdf70pz8BkACcd955ap3bb7+deMABBl55pVoHIC0lhTLg+uuvV+1ceu21JDRowAWXXabWSExMpH5KCpcDW9xu2rRpo9YaOHAggago2irOCQa47rrriAW8BGc7m/9d/yuvJKFBAy655hrVzhlnnkkJwe9LGnPKwzp16sQxxx3HWaeeqvo9zxhjzNGzsT12u+3fZN68eVxwwQWkpqSwbft2tUucDx06xLnnnov4/cyeO5fU1FSVzg8//MDJnTpRLsJ1N9zA5MmTVToAq1ev5umnn+aVV15RvTR8/fr13Hfffdx333107dpVrbNv3z769evHFVdcwahRo9Q6kXTgwAHWrFlDnz59qvpQapR9+/Yxe/ZsunbtqrqhjTT7HlF9iQhbtmyhYcOGRz5s1WRrwYTZWjBhthYiz+bQ/gJbiCbM1oIJs7VgwmwtmDBbCybM1oIJs7UQeTaH1hhjjDHGGGNMrWIbWmOMMcYYY4wxNZJtaM1vUlRUxFtvvcX8+fOr+lCMMcYYY4wxf3C2oa0lRo4cSZTjqN08CYJzOuv7fAwZPJh+Z55JT8UbDs2dO/fIzNZPP/1UrTNr1iwcx6F169Z07dRJrQPQrFkzHMfh6aefVu00b9oUj+OQmpxMIKB33+tZs2YRHxtL1y5d1BoAP/74I41TUmjdvDn79+9X65SVldG4QQO6de6sPh923759LF26VHV+JkBhYSELFixQnUcMwdeoT8+evPvuu6qdSCktLeWxsWOZ/MorVFRUqLZ27NjB999/r9qIpNLSUubPn09xcXFVH4oxxpg/iogNDlJUnefQRkocSFJoJt/cuXNVGg899JBEg8SH5sMCUlpaqtLiZ3NoNZdpdKgRH5pzumfPHpXO5s2bJTH0+mjO0Pzmm2/EBzI89Py9+uqrai1PaO5xAshbb72l1klLTpa40OO54uKL1To9evSQGBAPSHJ8vFpHRKR106aSEhMj7777rmrnigsukJToaLn3rrtUO3W93iPvP7m5uaqtSHj22Welp8cjnWNj5bXXXlPrlJeXS92EBEmJjZWFCxeqdSLp9htukJToaLnxqquq+lAqVW36ecH8PrYWTJithcizObS1nAAFob/XOkubnJwMBGe2RoX+O7fbrdKC4DxQbW6Cj6Uk9M8ej0el4/P5cIBCwK9SCEpMTMQBvif42Bo0aKDWclwuikJ/r9lJTEzET/B1qtewoVqncePGuAnOcvbFx6t1ANLS0ijw+6lXr55up1Ej8ioqSGvcWLXj9fnIBxzHITo6WrUVCXXq1GGvy8V+x6FOnTpqHZfLRb3QTOLw+2tNl9a4cXDNNWpU1YdijDHmjyLCG2sVdoZW5Ouvv5bY2Fi57bbb1BoVFRXSOClJCJ01vevOO9Va27dvP9LZunWrWmfNmjXiDnWGDx+u1hERmThxovh8Ptm+fbtq56abbpIox5Gzzz5btZOZmSnt2rWThx56SLWTnZ0tF593ntx2001SXFys2rr88sulc+fOalcehJWXl8vBgwdVGyIigUBA9u7dq97JycmRcePGyU8//aTeioRAICAzZ86USZMmSSAQUG2VlJTIoUOHVBuRFF5z2s9bpNWmnxfM72NrwYTZWoi8X9vz2Rxamx/1m4gIe/bsIT4+nsTExKo+nEpja8GE2VowYbYWTJitBRNma8GE2VqIvF/b80X9wr9rzK9yHIdGdimZMcYYY4wxphqw36E1xhhjjDHGGFMj2YbWGGOMMcYYY0yNZBvaWmL58uW0PP54nnrySdXOvX/+85H5sP/85z/VOj/++CNxjoPHcfjhhx/UOgDDhg2jX79+qnMT9+3bR5dWrUiIiuKma69VnQ+7bds2+vfvz5o1a9QaEJzb+vrrr7N+/XrVDkBBQQFlZWXqncmTJzNp0iTV1wfA7/eTnZ2t2gjLycmJSKe4uFh9ri4E55xqvz4A5eXl6jNoAQKBAKWlpeodU/2VlJRQVFT03//F3ykQCFBSUvLf/8VKEKl5xDb32Jg/NtvQ1gIVFRV07dqVjZs2MW7UKObPn6/S2bRpE08//TRRQDwc1Y24/lft27fHITi6p2PHjmqdRx55hLf+9jeys7Lwer1qnbtvv53y9esp8vuZ/c47TJ8+Xa3VunlzZs6cSfd27VR/8O/Uti03DRnCya1asXfvXrXOkiVLqJuQQD2vl4KCgv/+B47S008/zZ033sgrzz/PgIsvVusANIiNJb1hQ+644w7VTu/OnUlNTeWayy9X7bz37rv4fD7uvPFG1c6KFSuok5DAaV27qnb2799P0wYNOKdPHw4fPqzWCQQCdG3blnrJyaxdu1atY6q/ffv2Uc/nI9XnY9WqVaqts3v1ok5iIsuWLVPt3H377fh8Pt6cPFm18+bkyfh8Pu6+/XbVjjGm+rINbS1QXl6OGwhPMdy5c6dKJzc3NzijE9A/VxacB6p9vmf16tWUEXxMmg5kZ1MB1AUS0T1rFgWkEJxDq3lWc092NokE5+rm5uaqdTZt2hScFez3q3bWr19PBcHnL3PbNrUOBB9LAsH1pykrM5MUYNO6daqdTRs2UC8qivXKm7KdO3eS6HazbtMm1U5ubi5FRUXkFRSQn5+v1vH7/WzOzCQO2L17t1rHVH/79++nLBDAATIzM1Vb6zduJMnlYseOHbqdn36iXlQUm5Sv4tm4bh31oqLYYB8KGfPHFcHRQWpsDq3IVVdeKYDEx8VJeXm5SqOiokJSk5LEDRIN8uTjj6t0RETGPfrokTm0DyvOOa2oqDjSefvtt9U6y5YtkzjHkbog6XXqqM6dvOWWW8QNct5556k1RETWrVsnxx1zjNyhOPs4bOLEiTJ9+nTVRnFxsZx84olybHq67Ny5U7U1ffp0ueqqq9Tn3W7fvl1GjRqlPvO2tLRUZsyYIfv27VPtBAIB+eKLL2Tz5s2qHRGRb775Rj766CP1zvr162X+/PnqHfP7ROLnhffff19efvll9c7WrVtl7ty56rOCDxw4IJ988omUlJSodkpKSuSTTz6RAwcOqHbCatPPjub3sbUQeTaH9hfY/KjfLhAIsGbNGlJSUkhPT1dthX9/LSpKf7pUJNbCwYMH2bFjB61atcLj8ai2zNGz9wUTZmvBhNlaMGG2FkyYrYXIszm0plK4XC7at28fkVYkNrKRlJqaSmpqalUfhjHGGGOMMbWG/Q6tMcYYY4wxxpgayTa0xhhjjDHGGGNqJNvQmt/s4MGDEZn5dvjwYdWRGWHZ2dnqYxIgOGNQ+662kVRUVMQnn3yiPm4kEAjw+uuvM3v2bNVObRQIBNizZ09E5sMaY4wxxlQF29Aqm/bhh3Ru0YLPP/9ctZOcnEyy4+B1HNVOlMtFo7p1SfV62bNnj1qnT58+ZCQlkZGURFfFmZMLFy7k+IYNufWqq4hTvFFTSUkJqXFxnNqhAynx8WodgMaNG5PsONRR7vTq3JlbLrmE7m3bsmLFCrVO9y5duG3IEC49/3xG3XuvWqeiooLW6emc2aULWVlZah2AsaNH06NdOzYpjp8REc7u1YvjMjK4+Zpr1DrG/Nzszz6jc4sWzFCctW2MMcb8nG1olb09aRK7Nm9m6muvqXYK8/KIBaJVKxArwkigCfDkk0+qdRYtWkQxUAIsX75crfPss89SSPB5KyktVeusXbuWaCAGKCosVOsA5O/eTSyAcmfVhg24AEeEb7/9Vq2zbvVqbgQ6ANOnTVPrbNiwgQ27dpFfWMjHH3+s1gH429/+xta1a1U/6CotLWX+smW8XVHBp599ptYx5ufeeeUVdm3ezNuTJlX1oRhjjPmDsA2tsideeIFr77qLhxQ3fwAXDRhALlDh9ap2evbrx3NAFvD444+rdRYvXkwA8BM8i6pl0qRJBIDDQL9+/dQ6HTt2xImLIx84uVcvtQ7AJdddRx5w4umnq3ZuveEGDgFR8fH0799frXPTsGFMAdYBf33mGbVOmzZtuH7wYE7s0YNbb71VrQPw9ocfcuM993DdddepNTweD4888ACjGzVi3Pjxah1jfu4vEyZw7V138djzz1f1oRhjjPmDsDm0Nj/KYGvhaOXm5hIfH68+YqmgoIDo6GhiY2NVO2BrwfyLrQUTZmvBhNlaMGG2FiLP5tAaYypdcnJyRDrxyr8PbIwxxhhjaia75NgYY4wxxhhjTI1kG1pjjDHGGGOMMTVStbvk+OKLLz5yeWF6ejoDBw5k3LhxuN1uevbsybBhw6r4CE1t8/7777N48WL++te/4lW+qZYxxhhjjDGm8lSrM7SlpaWICFOmTGHKlCk8/vjjPPTQQ0yYMIH33nuPH374gbVr11b1YVZLSQkJeB0Ht+MQCATUOp07dybOcXA5DgcOHFDrbN26lVjHweM4bN26Va1z6SWXcMuVV/LlSy/RKDFR9blr0qQJXsfhtttuU2sAzJs3jxNbt+aDDz5Q7bzwwgskuFy0yMjA7/erdT7++GOS3W7qxcaybds2tU4kPThmDCd37EhmZmZVH4oxxhhjTI1WrTa069evp7i4mBtuuIFBgwaxfPlyysrKyMjIwHEcevbsyddff13Vh1ktFRUUkADEg+pM0H/+85+Eb89zyy23qHWOPfbYX/z7yvaPmTN5DVgLlPj9qhuM/KwsEoDXXnpJrQHwpxtuYPe6dYy8+WbVzph77sErwp6dO1m9erVa5/4RI7guEKBFWRkPPvigWieS/vroo2z94QdGjBhR1YdijDHGGFOjVatLjj0eD0OGDOGyyy5j+/bt3HTTTSQmJh75330+Hzt37vzFP7tu3brf3CspKTmqP1cdCVAa+svj8ag9LrfLRXkgQDwwaNAgtc6AAQP48uOPAehz1llqnXoZGTy4fTufEfxiOHz4sFqrwnFwRGh63HGq6+78K6/kreeeo+8ll6h2evbpw6LPPyfK7SYQCKi1zjjvPCa99BJu4OYzzlD/mo3E+0K3rl1Zv3o1F154Ya15D6qNatP3CPP72FowYbYWTJitheqjWs2hLSsrIxAI4PF4gODv0+bl5bFgwQIA3nrrLSoqKhgyZMj/+XM2hzZo27ZtNGnSRH0maFZWFsnJybVilEpFRQWXXnop69at4/3336dTp05VfUg1SqTm0GZnZ+P1ev/PB1xaatv7gjl6thZMmK0FE2ZrwYTZWoi8X9vzVatLjqdNm8YTTzwBwN69eykuLsbr9bJjxw5EhCVLlnDSSSdV8VFWX82aNVPfWEDwZl21YTMLEBUVxYwZM5gxY4ZtZo9CcnJyRNZcWlpaRDazxhhjjDGmZqlWlxxfeuml3HfffVx55ZU4jsNjjz2Gy+Xi7rvvxu/307NnTzp06FDVh2mMMcYYY4wxphqoVhvamJgYJkyY8B///YcfflgFR2OMMcYYY4wxpjqrVpccG2OMMcYYY4wx/yvb0NYSa9euJSkpSX0MSF5eHo7jkJycrNqB4N2aY2Nj1TtXXHEFp59+OmVlZaqd++69l2PT0o7c5EzL4sWLuaZ/f2bPnq3aqY1WrFjBN998U9WHYaqBr776ih9++KGqD8P8ioqKCj7++GN27NhR1YdijDGmitmGtpbo1LYt0YcPM/mZZ1Q7ycnJ1AGK8vL48ccf1TqtW7eG0lKcsjLVObQFBQVM/+ADSrOzad68uVrnwIEDPPPUU1yxdy+XnXWWWgfgqosvpvXMmVx28cVUVFSotmqTQ4cO0btHD/48dCjff/99VR+OqUIbN27kgr59uWnQILKysqr6cMwveOmll7j9yiu58PTTq/pQjDHGVDHb0NYSvuRkcgBHuZOYmEgB4AEyMjLUOn369MFFcIGeccYZap2YmBg8QD4c1ein/5XX68UNTAOSUlLUOgDNmzblE5+PJmlpuN1u1VZt4vV6OaZxY9yxsaSlpVX14ZgqlJqaSkJCAinJySQlJVX14Zhf0LJlS3ICATp07FjVh2KMMaaKVaubQpmjl5OTQ1ZWFunp6aqdvLw8lixZQrt27VR/0HvxxRd54IEHAGjUqJFaJyYmhgOlpSxdupTTTjtNreP1etm0axdLly7lggsuUOsAfLZwIYsWLaJHjx44jvZHHLVHbGwsP27Zwk8//aT+dWSqt9TUVDL37mXdunUkJCRU9eGYX9C3b1+KSkoiMjbMGGNM9WbfCWqRSP0Q3rNnz4h0NDeyPxcTExORM3KNGjXisssuU+8kJiaqb5prK8dx7Ky2AcDlcuFy2UVM1ZltZo0xxoBdcmyMMcYYY4wxpoayDa0xxhhjjDHGmBrJNrTGGGOMMcYYY2ok29DWIuPGjSM7O1u1UVBQQI8ePRg+fLhqB2DZsmUsW7ZMvZOTk8PmzZvVO36/n127dql3du/ezUsvvcTWrVvVW8aYmqGiooLdu3dX9WEYY4wxlc42tLVESmIiDz3wAC0bNlTtpKel8f2yZbz67LO8/fbbap3PPvuM03r04LQePZg+fbpaJxAI0LxBAwZceCGvvfaaWgfg2ksuoVlGBm9MnqzaObd3bz4fMYJeXboQCARUW8aYmuHyc8+lWUYGU6dOrepDMcYYYyqVbWhridLSUjwR6JSXlRENVAD79+9X6+Tk5CChvz906JBaB6DM7yc61NR0KCcHn9vNIeVOQWEhTUpKKCopQUT++x8wxtR6ubm5eF0ucpXfT40xxphIs3ve1xKH8vPp1asXY8aMUe2s27yZTh070qJFC/785z+rdQYNGsT+/fsJBAIMGTJEreNyufhm1SrmzZun+ngAPpwzhx9//JGTTz5ZtTPj73/nnbfe4vNLL7URNMYYAD6ZN49169bRrVu3qj4UY4wxplLZhraWiImJ4dtvv1XvZGRkcFD5DGOY9gYzrH379kRHR6t3EhIS6NGjh3qnbdu2PDF+vHrHGFNzJCUlqX+YZowxxlQFu+TYGGOMMcYYY0yNZBtaY4wxxhhjjDE1km1ojTHGGGOMMcbUSLahrSVenDiRXu3bc+vgwRQWFqq2Nm7cyIEDB1QbxhhjjDHGGPPf2Ia2Fpg/fz4PjxjBlh9/ZMlbbzHmnnvUWj27d+ekE04go149MjMz1TobNmwgyXFIchx++ukntY4xxhhjjDGm5rINbS2wZcsW6lVUEABKgc1r16q11nz/PTcADYFly5apdaZNm0YJwcfzwQcfqHWMMcYYY4wxNZdtaGuB8847jwOJiSQ6Dvujorj+T39Sa8388kvecBzyfT4GDBig1hk9ejRtOnXihPbt+ctf/qLWMcYYY4wxxtRcNoe2FmjcuDGrN25k4cKFtGzZkg4dOqi1evfuTV4goPb//3P//Oc/I9IxxhhjjDHG1Ey2oa0lGjRowMCBA6v6MIwxxhhjjDEmYuySY2OMMcYYY4wxNZJtaI0xxhhjjDHG1Ei2oTXGGGOMMcYYUyPZhraWWLhwISc0bMjo++9X7SxfvpyUqCiap6WpdowxNcemTZu4un9/5s6dW9WHYowxxpjfIBAI8MA99zDyzjvx+/1VfThHxTa0tcToe+8lLzubSU89pdoZMmQIbr+fbXv3UlBQoNoyxtQMLz3/PPNnzuSh4cOr+lCMMcaY/9fO3cdUWf9/HH8dbiYIoZLpcMnMvClCZouwG8ObIrVhONeaWPgziBRzRawSTcnErTHp6x8m/lqLboiFouAwZ+nMpAbSsgUDoVjSCmUZinE3Dpzj+f7RON+EU9+v377nXFxez8df8Lnu3tf22Xu8uD7XhWvQ3Nysf+zcqf/fs0e1tbVGl/Nf4SvH14mcbduUkZysZSkpXr3Om2++qWULFmjymDEKDQ316rUAmMPTGRlqaWrS/61bZ3QpAADgGkybNk1r09PV39+vWbNmGV3Of4VAe51YtGiRzl665PXrxMfH65JJlyMA8I6oqCiVHztmdBkAAOAa+fv76x979hhdxt/CkmMAAAAAgCkRaAEAAAAApkSgBQAAAACYEoEWAAAAAGBKBFoAAAAAgCkRaAEAAAAApkSgBQAAAACYEoEWAAAAAGBKBFoAAAAAgCkRaAEAAAAApkSgBQAAAACYEoEWAAAAAGBKBFoAAAAAgCkRaAEAAAAApkSgBQAAAACYEoEWAAAAAGBKBFoAAAAAgCnZXC6Xy+gi/q7Tp08bXQIAAAAAwIvuuuuuYWPXRaAFAAAAAFgPS44BAAAAAKZEoAUAAAAAmFKA0QX4Wm1trfLz81VUVKQzZ85ozZo1mjJliiQpOTlZjzzyiLEFwusGBga0adMmnTt3Tv39/crIyNC0adOUnZ0tm82m6dOn69VXX5WfH//vud55mgsRERH0BQtyOp3avHmzWlpaZLPZ9Nprr2nUqFH0BQvyNBccDgd9waIuXryo5cuXq7CwUAEBAfQEC/vjXLDb7fSEEcRSgfbtt99WRUWFgoODJUkNDQ166qmnlJqaanBl8KWKigqNHTtWO3bs0OXLl7Vs2TLddtttyszM1Jw5c5STk6Pjx48rISHB6FLhZZ7mwrPPPktfsKATJ05IkkpKSlRTU6OdO3fK5XLRFyzI01xYuHAhfcGCBgYGlJOTo6CgIEnS66+/Tk+wqKFzgQwxsljq30qRkZHatWuX+/f6+np9/vnneuKJJ7Rp0yZ1d3cbWB18ZfHixXr++eclSS6XS/7+/mpoaFBcXJwkKT4+XlVVVUaWCB/xNBfoC9b00EMPKTc3V5J0/vx5hYWF0RcsytNcoC9YU15enlasWKEJEyZIEj3BwobOBXrCyGKpQLto0SIFBPzroXRMTIxefvllFRcXa/Lkydq9e7eB1cFXQkJCFBoaqu7ubj333HPKzMyUy+WSzWZzb+/q6jK4SviCp7lAX7CugIAAbdiwQbm5uVq6dCl9wcKGzgX6gvWUlZUpPDxcDzzwgHuMnmBNnuYCPWFksVSgHSohIUHR0dHun8+cOWNwRfCVtrY2rVq1SklJSVq6dOlV78D09PQoLCzMwOrgS0PnAn3B2vLy8vTpp59qy5Ytstvt7nH6gvX8cS7MnTuXvmAxBw4cUFVVlVJSUtTY2KgNGzbo0qVL7u30BOvwNBfi4+PpCSOIpQNtWlqa6urqJEnV1dW64447DK4IvtDe3q7U1FS99NJLeuyxxyRJUVFRqqmpkSRVVlYqNjbWyBLhI57mAn3Bmg4ePKi33npLkhQcHCybzabo6Gj6ggV5mgvr16+nL1hMcXGxPvzwQxUVFen2229XXl6e4uPj6QkW5GkurFu3jp4wgthcLpfL6CJ8qbW1VVlZWdq3b58aGhqUm5urwMBAjR8/Xrm5uQoNDTW6RHjZ9u3bdeTIEU2dOtU99sorr2j79u0aGBjQ1KlTtX37dvn7+xtYJXzB01zIzMzUjh076AsW09vbq40bN6q9vV0Oh0Pp6em69dZbtWXLFvqCxXiaCxEREfy9YGEpKSnaunWr/Pz86AkWNzgX+vr66AkjiOUCLQAAAADg+mDpJccAAAAAAPMi0AIAAAAATIlACwAAAAAwJQItAAAAAMCUCLQAAAAAAFMi0AIAYICPP/5YM2fO1MyZM5WTk2N0OQAAmBKBFgAAAxw4cMD986FDh9Td3W1gNQAAmBOBFgAAHzt//rxOnTqlsWPHavbs2ert7dWhQ4eMLgsAANMh0AIA4GNlZWW6cuWK7rzzTi1cuFCStHfvXoOrAgDAfAi0AAD4kMvlUnl5uSQpPj5eS5YskSQ1Njbq22+/AvBF8AAABgJJREFUNbI0AABMJ8DoAgAAsJJTp06ptbVVfn5+evDBBzVx4kTFxMSorq5OH330kWbPnu3xOIfDofLycpWWlqqlpUVXrlxRdHS00tPTFRgYqFWrVikuLk5FRUVXHed0OlVRUaHy8nI1NTWpt7dXEyZM0P3336+0tDRNmTLFB3cNAIB38IQWAAAfGvwYVFxcnCZOnChJSkxMlCQdOXJEv/3227Bj7Ha71q9fr82bN6u2tlbjxo1TZGSkvv76a6WlpQ0LsYN6enr09NNPKzs7WzU1NQoKCtKMGTN0+fJl7du3T0lJSTp69KiX7hQAAO8j0AIA4CNdXV06duyYJOnRRx91jycmJsrf3192u929HPmPdu/erRMnTmjs2LH64IMPdPToUZWXl+uzzz7T3Xff7T7nUFu2bFFVVZWmT5+u0tJSVVZWqqysTNXV1Vq7dq36+vr04osv6vvvv/fODQMA4GUEWgAAfOTw4cPq6+tTUFCQFi1a5B6/8cYbdd9990mSSkpKrjqms7NT7777riQpLy9Pc+bMcW+bOHGi9uzZo5tuumnYtZqamnT48GEFBwfrnXfeUUxMjHvbqFGj9MILL2jJkiWy2+0qKCj4n94nAAC+QqAFAMBHBpcbL1iwQKGhoVdtG3xi29LSourqavf4yZMn1d/fr0mTJmn+/PnDznnDDTdo+fLlw8YHn9r+cWnzUElJSZKkyspKOZ3Oa78hAAAMxkehAADwgebmZtXV1Um6ernxoISEBI0ePVq9vb0qKSnRvffe6z5OkmbOnPmn546OjvZ4PUmqr69XcnKyx+Psdruk39+1/eWXXzRp0qRruCMAAIxHoAUAwAcGn85KUkZGxl/ue/z4cbW3t2v8+PHq6OiQJI0ePfpP9x/6tFf6/X1dSbp48aIuXrz4b+vr7Owk0AIATIdACwCAlw0MDKiiokKSFBYWpuDgYI/7uVwuXbhwQQMDA9q/f7/Wrl3r3re7u/tPz9/T0zNsbPC41NRUbdiw4e/eAgAAIxKBFgAALzt58qT7KWlhYaFmzZr1p/smJiaqublZ+/bt0zPPPKMZM2ZI0l9+ibipqWnY2C233CLpX0uPPeno6NDZs2cVERGhiIgI2Wy2/+h+AAAYKfgoFAAAXrZ//35Jv78H+1dhVpL7fddz586psrJS8+fPV2BgoNra2vTll18O299ut+vgwYPDxhcsWCBJqq6u1g8//ODxWm+88YZWrlyplJQUuVyua7onAABGAgItAABe9Ouvv+qLL76QJI9fIx4qKSnJ/b5sSUmJxo8fr5UrV0qSsrOz9c0337j37ejoUGZmplpbW4edJzY2VnPnzpXD4VB6evpVx/X396ugoEClpaWSpPT0dPn58ScBAMB8WHIMAIAXHTx4UA6HQ4GBgR6/bjxUaGioli5dqr1796qyslJtbW3KyspSY2OjvvrqKyUnJ2vKlCkKCQlRc3OzHA6HoqOjVV9fL39//6vOlZ+frzVr1qi2tlbJycm6+eabNWbMGP3888/q7OyUJK1evVorVqzwyr0DAOBt/DsWAAAvKisrkyQtXLhQ4eHh/9Exg8uOnU6n9u7dq6CgIBUWFio7O1tRUVG6cOGCfvzxR8XGxur999/Xww8/LEkKCgq66jzjxo1TcXGxtm3bpri4OHV1dem7775TQECA5s2bp4KCAm3cuPF/eLcAAPiWzcVLMwAAmFpeXp4KCwv1+OOPKzc31+hyAADwGZ7QAgAwgrW0tGj+/PlavXq1+vv7h213uVzud3SjoqJ8XR4AAIYi0AIAMIJNnjxZdrtd1dXVys/PV19fn3tbV1eXtm7dqubmZoWHh2vx4sUGVgoAgO+x5BgAgBHuk08+UVZWlpxOp0JCQhQZGSmn06mffvpJfX19CgsL065du3TPPfcYXSoAAD5FoAUAwATOnj2r9957T6dPn1ZbW5skKSIiQvPmzdOTTz6pSZMmGVwhAAC+R6AFAAAAAJgS79ACAAAAAEyJQAsAAAAAMCUCLQAAAADAlAi0AAAAAABTItACAAAAAEyJQAsAAAAAMKV/AoZiAFS2q/2rAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x104097518>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16,8))\n",
    "sns.set_style(\"whitegrid\")\n",
    "plt.title('Players Wage according to their Age and Overall', fontsize=30, fontweight='bold', y=1.05,)\n",
    "plt.xlabel('Age', fontsize=25)\n",
    "plt.ylabel('Overall', fontsize=25)\n",
    "\n",
    "age = FIFA18[\"Age\"].values\n",
    "overall = FIFA18[\"Overall\"].values\n",
    "value = FIFA18[\"WageNum\"].values\n",
    "\n",
    "plt.scatter(age, overall, s = value/500, edgecolors='black', color=\"red\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3 - Best Squad Analysis\n",
    "For simplicity of this analysis, I only pull in data I am interested in:"
   ]
  },
  {
   "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>Name</th>\n",
       "      <th>Age</th>\n",
       "      <th>Nationality</th>\n",
       "      <th>Overall</th>\n",
       "      <th>Potential</th>\n",
       "      <th>Club</th>\n",
       "      <th>Position</th>\n",
       "      <th>Value</th>\n",
       "      <th>Wage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Cristiano Ronaldo</td>\n",
       "      <td>32</td>\n",
       "      <td>Portugal</td>\n",
       "      <td>94</td>\n",
       "      <td>94</td>\n",
       "      <td>Real Madrid CF</td>\n",
       "      <td>ST</td>\n",
       "      <td>€95.5M</td>\n",
       "      <td>€565K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>L. Messi</td>\n",
       "      <td>30</td>\n",
       "      <td>Argentina</td>\n",
       "      <td>93</td>\n",
       "      <td>93</td>\n",
       "      <td>FC Barcelona</td>\n",
       "      <td>RW</td>\n",
       "      <td>€105M</td>\n",
       "      <td>€565K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Neymar</td>\n",
       "      <td>25</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>92</td>\n",
       "      <td>94</td>\n",
       "      <td>Paris Saint-Germain</td>\n",
       "      <td>LW</td>\n",
       "      <td>€123M</td>\n",
       "      <td>€280K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>L. Suárez</td>\n",
       "      <td>30</td>\n",
       "      <td>Uruguay</td>\n",
       "      <td>92</td>\n",
       "      <td>92</td>\n",
       "      <td>FC Barcelona</td>\n",
       "      <td>ST</td>\n",
       "      <td>€97M</td>\n",
       "      <td>€510K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>M. Neuer</td>\n",
       "      <td>31</td>\n",
       "      <td>Germany</td>\n",
       "      <td>92</td>\n",
       "      <td>92</td>\n",
       "      <td>FC Bayern Munich</td>\n",
       "      <td>GK</td>\n",
       "      <td>€61M</td>\n",
       "      <td>€230K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>R. Lewandowski</td>\n",
       "      <td>28</td>\n",
       "      <td>Poland</td>\n",
       "      <td>91</td>\n",
       "      <td>91</td>\n",
       "      <td>FC Bayern Munich</td>\n",
       "      <td>ST</td>\n",
       "      <td>€92M</td>\n",
       "      <td>€355K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>De Gea</td>\n",
       "      <td>26</td>\n",
       "      <td>Spain</td>\n",
       "      <td>90</td>\n",
       "      <td>92</td>\n",
       "      <td>Manchester United</td>\n",
       "      <td>GK</td>\n",
       "      <td>€64.5M</td>\n",
       "      <td>€215K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>E. Hazard</td>\n",
       "      <td>26</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>90</td>\n",
       "      <td>91</td>\n",
       "      <td>Chelsea</td>\n",
       "      <td>LW</td>\n",
       "      <td>€90.5M</td>\n",
       "      <td>€295K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>T. Kroos</td>\n",
       "      <td>27</td>\n",
       "      <td>Germany</td>\n",
       "      <td>90</td>\n",
       "      <td>90</td>\n",
       "      <td>Real Madrid CF</td>\n",
       "      <td>CDM</td>\n",
       "      <td>€79M</td>\n",
       "      <td>€340K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>G. Higuaín</td>\n",
       "      <td>29</td>\n",
       "      <td>Argentina</td>\n",
       "      <td>90</td>\n",
       "      <td>90</td>\n",
       "      <td>Juventus</td>\n",
       "      <td>ST</td>\n",
       "      <td>€77M</td>\n",
       "      <td>€275K</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Name  Age Nationality  Overall  Potential  \\\n",
       "0  Cristiano Ronaldo   32    Portugal       94         94   \n",
       "1           L. Messi   30   Argentina       93         93   \n",
       "2             Neymar   25      Brazil       92         94   \n",
       "3          L. Suárez   30     Uruguay       92         92   \n",
       "4           M. Neuer   31     Germany       92         92   \n",
       "5     R. Lewandowski   28      Poland       91         91   \n",
       "6             De Gea   26       Spain       90         92   \n",
       "7          E. Hazard   26     Belgium       90         91   \n",
       "8           T. Kroos   27     Germany       90         90   \n",
       "9         G. Higuaín   29   Argentina       90         90   \n",
       "\n",
       "                  Club Position   Value   Wage  \n",
       "0       Real Madrid CF       ST  €95.5M  €565K  \n",
       "1         FC Barcelona       RW   €105M  €565K  \n",
       "2  Paris Saint-Germain       LW   €123M  €280K  \n",
       "3         FC Barcelona       ST    €97M  €510K  \n",
       "4     FC Bayern Munich       GK    €61M  €230K  \n",
       "5     FC Bayern Munich       ST    €92M  €355K  \n",
       "6    Manchester United       GK  €64.5M  €215K  \n",
       "7              Chelsea       LW  €90.5M  €295K  \n",
       "8       Real Madrid CF      CDM    €79M  €340K  \n",
       "9             Juventus       ST    €77M  €275K  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "FIFA18 = FIFA18[['Name', 'Age', 'Nationality', 'Overall', 'Potential', 'Club', 'Position', 'Value', 'Wage']]\n",
    "FIFA18.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.1 Squad of Highest Overall Players\n",
    "What's the best squad according to FIFA 18 purely based on overall rating?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def get_best_squad(formation):\n",
    "    FIFA18_copy = FIFA18.copy()\n",
    "    store = []\n",
    "    \n",
    "    # iterate through all positions in the input formation and get players with highest overall respective to the position\n",
    "    for i in formation:\n",
    "        store.append([\n",
    "            i,\n",
    "            FIFA18_copy.loc[[FIFA18_copy[FIFA18_copy['Position'] == i]['Overall'].idxmax()]]['Name'].to_string(index = False),\n",
    "            FIFA18_copy[FIFA18_copy['Position'] == i]['Overall'].max(),\n",
    "            FIFA18_copy.loc[[FIFA18_copy[FIFA18_copy['Position'] == i]['Overall'].idxmax()]]['Age'].to_string(index = False),\n",
    "            FIFA18_copy.loc[[FIFA18_copy[FIFA18_copy['Position'] == i]['Overall'].idxmax()]]['Club'].to_string(index = False),\n",
    "            FIFA18_copy.loc[[FIFA18_copy[FIFA18_copy['Position'] == i]['Overall'].idxmax()]]['Value'].to_string(index = False),\n",
    "            FIFA18_copy.loc[[FIFA18_copy[FIFA18_copy['Position'] == i]['Overall'].idxmax()]]['Wage'].to_string(index = False)\n",
    "        ])\n",
    "                      \n",
    "        FIFA18_copy.drop(FIFA18_copy[FIFA18_copy['Position'] == i]['Overall'].idxmax(), \n",
    "                         inplace = True)\n",
    "    \n",
    "    # return store with only necessary columns\n",
    "    return pd.DataFrame(np.array(store).reshape(11,7), \n",
    "                        columns = ['Position', 'Player', 'Overall', 'Age', 'Club', 'Value', 'Wage']).to_string(index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4-3-3\n",
      "Position             Player Overall Age                 Club   Value   Wage\n",
      "     GK           M. Neuer      92  31     FC Bayern Munich    €61M  €230K\n",
      "     RB           Carvajal      84  25       Real Madrid CF    €32M  €195K\n",
      "     CB       Sergio Ramos      90  31       Real Madrid CF    €52M  €310K\n",
      "     CB       G. Chiellini      89  32             Juventus    €38M  €225K\n",
      "     LB            Marcelo      87  29       Real Madrid CF    €38M  €250K\n",
      "    CDM           T. Kroos      90  27       Real Madrid CF    €79M  €340K\n",
      "     CM           N. Kanté      87  26              Chelsea  €52.5M  €190K\n",
      "    CAM           Coutinho      86  25            Liverpool    €56M  €205K\n",
      "     RW           L. Messi      93  30         FC Barcelona   €105M  €565K\n",
      "     ST  Cristiano Ronaldo      94  32       Real Madrid CF  €95.5M  €565K\n",
      "     LW             Neymar      92  25  Paris Saint-Germain   €123M  €280K\n"
     ]
    }
   ],
   "source": [
    "# 4-3-3\n",
    "squad_433 = ['GK', 'RB', 'CB', 'CB', 'LB', 'CDM', 'CM', 'CAM', 'RW', 'ST', 'LW']\n",
    "print ('4-3-3')\n",
    "print (get_best_squad(squad_433))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4-4-2\n",
      "Position             Player Overall Age               Club   Value   Wage\n",
      "     GK           M. Neuer      92  31   FC Bayern Munich    €61M  €230K\n",
      "     RB           Carvajal      84  25     Real Madrid CF    €32M  €195K\n",
      "     CB       Sergio Ramos      90  31     Real Madrid CF    €52M  €310K\n",
      "     CB       G. Chiellini      89  32           Juventus    €38M  €225K\n",
      "     LB            Marcelo      87  29     Real Madrid CF    €38M  €250K\n",
      "     RM       K. De Bruyne      89  26    Manchester City    €83M  €285K\n",
      "     CM           N. Kanté      87  26            Chelsea  €52.5M  €190K\n",
      "     CM           A. Vidal      87  30   FC Bayern Munich  €37.5M  €160K\n",
      "     LM         C. Eriksen      87  25  Tottenham Hotspur    €65M  €165K\n",
      "     ST  Cristiano Ronaldo      94  32     Real Madrid CF  €95.5M  €565K\n",
      "     ST          L. Suárez      92  30       FC Barcelona    €97M  €510K\n"
     ]
    }
   ],
   "source": [
    "# 4-4-2\n",
    "squad_442 = ['GK', 'RB', 'CB', 'CB', 'LB', 'RM', 'CM', 'CM', 'LM', 'ST', 'ST']\n",
    "print ('4-4-2')\n",
    "print (get_best_squad(squad_442))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4-2-3-1\n",
      "Position             Player Overall Age              Club   Value   Wage\n",
      "     GK           M. Neuer      92  31  FC Bayern Munich    €61M  €230K\n",
      "     RB           Carvajal      84  25    Real Madrid CF    €32M  €195K\n",
      "     CB       Sergio Ramos      90  31    Real Madrid CF    €52M  €310K\n",
      "     CB       G. Chiellini      89  32          Juventus    €38M  €225K\n",
      "     LB            Marcelo      87  29    Real Madrid CF    €38M  €250K\n",
      "    CDM           T. Kroos      90  27    Real Madrid CF    €79M  €340K\n",
      "    CDM          L. Modrić      89  31    Real Madrid CF    €57M  €340K\n",
      "    CAM           Coutinho      86  25         Liverpool    €56M  €205K\n",
      "    CAM      R. Nainggolan      86  29              Roma  €42.5M  €130K\n",
      "    CAM      Cesc Fàbregas      86  30           Chelsea    €41M  €210K\n",
      "     ST  Cristiano Ronaldo      94  32    Real Madrid CF  €95.5M  €565K\n"
     ]
    }
   ],
   "source": [
    "# 4-2-3-1\n",
    "squad_4231 = ['GK', 'RB', 'CB', 'CB', 'LB', 'CDM', 'CDM', 'CAM', 'CAM', 'CAM', 'ST']\n",
    "print ('4-2-3-1')\n",
    "print (get_best_squad(squad_4231))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Alright, now let's move onto studying different squad's impact on Nationality teams. First let's modifiy above get_summary and get_best_squad functions for Nationality:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def get_best_squad_n(formation, nationality, measurement = 'Overall'):\n",
    "    FIFA18_copy = FIFA18.copy()\n",
    "    FIFA18_copy = FIFA18_copy[FIFA18_copy['Nationality'] == nationality]\n",
    "    store = []\n",
    "    \n",
    "    for i in formation:\n",
    "        store.append([\n",
    "            FIFA18_copy.loc[[FIFA18_copy[FIFA18_copy['Position'].str.contains(i)][measurement].idxmax()]]['Position'].to_string(index = False),\n",
    "            FIFA18_copy.loc[[FIFA18_copy[FIFA18_copy['Position'].str.contains(i)][measurement].idxmax()]]['Name'].to_string(index = False), \n",
    "            FIFA18_copy[FIFA18_copy['Position'].str.contains(i)][measurement].max(),\n",
    "            FIFA18_copy.loc[[FIFA18_copy[FIFA18_copy['Position'].str.contains(i)][measurement].idxmax()]]['Age'].to_string(index = False),\n",
    "            FIFA18_copy.loc[[FIFA18_copy[FIFA18_copy['Position'].str.contains(i)][measurement].idxmax()]]['Club'].to_string(index = False),\n",
    "            FIFA18_copy.loc[[FIFA18_copy[FIFA18_copy['Position'].str.contains(i)][measurement].idxmax()]]['Value'].to_string(index = False),\n",
    "            FIFA18_copy.loc[[FIFA18_copy[FIFA18_copy['Position'].str.contains(i)][measurement].idxmax()]]['Wage'].to_string(index = False)\n",
    "        ])\n",
    "        \n",
    "        FIFA18_copy.drop(FIFA18_copy[FIFA18_copy['Position'].str.contains(i)][measurement].idxmax(), \n",
    "                         inplace = True)\n",
    "    \n",
    "    return np.mean([x[2] for x in store]).round(2), pd.DataFrame(np.array(store).reshape(11,7), \n",
    "                                                                 columns = ['Position', 'Player', measurement, 'Age', 'Club', 'Value', 'Wage']).to_string(index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def get_summary_n(squad_list, squad_name, nationality_list):\n",
    "    summary = []\n",
    "\n",
    "    for i in nationality_list:\n",
    "        count = 0\n",
    "        for j in squad_list:\n",
    "            \n",
    "            # for overall rating\n",
    "            O_temp_rating, _  = get_best_squad_n(formation = j, nationality = i, measurement = 'Overall')\n",
    "            \n",
    "            # for potential rating & corresponding value\n",
    "            P_temp_rating, _ = get_best_squad_n(formation = j, nationality = i, measurement = 'Potential')\n",
    "            \n",
    "            summary.append([i, squad_name[count], O_temp_rating.round(2), P_temp_rating.round(2)])    \n",
    "            count += 1\n",
    "    \n",
    "    return summary"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Also let's make our squad choices more strict:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "squad_343_strict = ['GK', 'CB', 'CB', 'CB', 'RB|RWB', 'CM|CDM', 'CM|CDM', 'LB|LWB', 'RM|RW', 'ST|CF', 'LM|LW']\n",
    "squad_442_strict = ['GK', 'RB|RWB', 'CB', 'CB', 'LB|LWB', 'RM', 'CM|CDM', 'CM|CAM', 'LM', 'ST|CF', 'ST|CF']\n",
    "squad_4312_strict = ['GK', 'RB|RWB', 'CB', 'CB', 'LB|LWB', 'CM|CDM', 'CM|CAM|CDM', 'CM|CAM|CDM', 'CAM|CF', 'ST|CF', 'ST|CF']\n",
    "squad_433_strict = ['GK', 'RB|RWB', 'CB', 'CB', 'LB|LWB', 'CM|CDM', 'CM|CAM|CDM', 'CM|CAM|CDM', 'RM|RW', 'ST|CF', 'LM|LW']\n",
    "squad_4231_strict = ['GK', 'RB|RWB', 'CB', 'CB', 'LB|LWB', 'CM|CDM', 'CM|CDM', 'RM|RW', 'CAM', 'LM|LW', 'ST|CF']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "squad_list = [squad_343_strict, squad_442_strict, squad_4312_strict, squad_433_strict, squad_4231_strict]\n",
    "squad_name = ['3-4-3', '4-4-2', '4-3-1-2', '4-3-3', '4-2-3-1']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3.2 France\n",
    "Let's explore different squad possibility of France and how it affects the ratings:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "               Squad  Overall  Potential\n",
      "Nationality                             \n",
      "France         3-4-3    84.55      89.55\n",
      "France         4-4-2    84.00      89.91\n",
      "France       4-3-1-2    84.55      89.64\n",
      "France         4-3-3    84.64      89.91\n",
      "France       4-2-3-1    84.55      89.91\n"
     ]
    }
   ],
   "source": [
    "France = pd.DataFrame(np.array(get_summary_n(squad_list, squad_name, ['France'])).reshape(-1,4), columns = ['Nationality', 'Squad', 'Overall', 'Potential'])\n",
    "France.set_index('Nationality', inplace = True)\n",
    "France[['Overall', 'Potential']] = France[['Overall', 'Potential']].astype(float)\n",
    "\n",
    "print (France)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So we can say that France has the best squard as 4-3-3 for the current squad; and 4-4-2, 4-3-3, and 4-2-3-1 for the future squad based on team ratings. Let's check out the best 11 squad line-up of France in 4-3-3 for current rating as well as 4-4-2 for potential rating:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-Overall-\n",
      "Average rating: 84.6\n",
      "Position        Player Overall Age                     Club   Value   Wage\n",
      "     GK     H. Lloris      88  30        Tottenham Hotspur    €38M  €165K\n",
      "     RB      K. Zouma      79  22               Stoke City    €15M   €96K\n",
      "     CB     R. Varane      85  24           Real Madrid CF  €46.5M  €175K\n",
      "     CB    A. Laporte      84  23  Athletic Club de Bilbao  €35.5M   €36K\n",
      "     LB    L. Kurzawa      80  24      Paris Saint-Germain  €16.5M   €69K\n",
      "     CM      N. Kanté      87  26                  Chelsea  €52.5M  €190K\n",
      "    CDM      P. Pogba      87  24        Manchester United  €66.5M  €195K\n",
      "     CM    B. Matuidi      85  30                 Juventus  €28.5M  €145K\n",
      "     RM    F. Thauvin      82  24   Olympique de Marseille    €28M   €40K\n",
      "     ST    K. Benzema      86  29           Real Madrid CF  €44.5M  €295K\n",
      "     LW  A. Griezmann      88  26          Atlético Madrid    €75M  €150K\n"
     ]
    }
   ],
   "source": [
    "rating_433_FR_Overall, best_list_433_FR_Overall = get_best_squad_n(squad_433_strict, 'France', 'Overall')\n",
    "print('-Overall-')\n",
    "print('Average rating: {:.1f}'.format(rating_433_FR_Overall))\n",
    "print(best_list_433_FR_Overall)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-Potential-\n",
      "Average rating: 89.9\n",
      "Position        Player Potential Age                     Club   Value   Wage\n",
      "     GK     A. Lafont        89  18              Toulouse FC  €11.5M   €10K\n",
      "     RB      K. Zouma        86  22               Stoke City    €15M   €96K\n",
      "     CB     R. Varane        92  24           Real Madrid CF  €46.5M  €175K\n",
      "     CB    A. Laporte        89  23  Athletic Club de Bilbao  €35.5M   €36K\n",
      "     LB  L. Hernández        88  21          Atlético Madrid  €13.5M   €36K\n",
      "     RM       A. Pléa        86  24                 OGC Nice  €20.5M   €41K\n",
      "    CDM      P. Pogba        92  24        Manchester United  €66.5M  €195K\n",
      "    CAM    O. Dembélé        92  20             FC Barcelona    €40M  €150K\n",
      "     LM      T. Lemar        91  21                AS Monaco  €38.5M   €37K\n",
      "     ST     K. Mbappé        94  18      Paris Saint-Germain  €41.5M   €31K\n",
      "     ST    A. Martial        90  21        Manchester United    €33M  €115K\n"
     ]
    }
   ],
   "source": [
    "rating_442_FR_Potential, best_list_442_FR_Potential = get_best_squad_n(squad_442_strict, 'France', 'Potential')\n",
    "print('-Potential-')\n",
    "print('Average rating: {:.1f}'.format(rating_442_FR_Potential))\n",
    "print(best_list_442_FR_Potential)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "![griezmann](images/griezmann.jpeg)\n",
    "\n",
    "### 3.3 Germany\n",
    "The holding champion is certainly a heavy candidate for this year's 1st place:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "               Squad  Overall  Potential\n",
      "Nationality                             \n",
      "Germany        3-4-3    86.27      88.55\n",
      "Germany        4-4-2    85.09      88.36\n",
      "Germany      4-3-1-2    85.36      88.00\n",
      "Germany        4-3-3    86.27      88.55\n",
      "Germany      4-2-3-1    86.09      88.55\n"
     ]
    }
   ],
   "source": [
    "Germany = pd.DataFrame(np.array(get_summary_n(squad_list, squad_name, ['Germany'])).reshape(-1,4), columns = ['Nationality', 'Squad', 'Overall', 'Potential'])\n",
    "Germany.set_index('Nationality', inplace = True)\n",
    "Germany[['Overall', 'Potential']] = Germany[['Overall', 'Potential']].astype(float)\n",
    "\n",
    "print (Germany)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see, Germany's current ratings peak with either 3-4-3 or 4-3-3 formation; while those 2 plus 4-2-3-1 are their best options for the future. With that, I'll show Germany's best 11 squad with 4-3-3 for current ratings and 4-2-3-1 for potential ratings."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-Overall-\n",
      "Average rating: 86.3\n",
      "Position       Player Overall Age               Club   Value   Wage\n",
      "     GK     M. Neuer      92  31   FC Bayern Munich    €61M  €230K\n",
      "     RB   A. Rüdiger      82  24            Chelsea  €24.5M  €105K\n",
      "     CB   J. Boateng      88  28   FC Bayern Munich    €48M  €215K\n",
      "     CB   M. Hummels      88  28   FC Bayern Munich    €48M  €215K\n",
      "     LB    J. Hector      80  27         1. FC Köln    €14M   €42K\n",
      "    CDM     T. Kroos      90  27     Real Madrid CF    €79M  €340K\n",
      "    CDM  I. Gündoğan      85  26    Manchester City    €46M  €190K\n",
      "    CDM   S. Khedira      84  30           Juventus    €29M  €160K\n",
      "     RW      M. Özil      88  28            Arsenal    €60M  €265K\n",
      "     ST    T. Müller      86  27   FC Bayern Munich  €47.5M  €190K\n",
      "     LW      M. Reus      86  28  Borussia Dortmund    €45M  €120K\n"
     ]
    }
   ],
   "source": [
    "rating_433_GER_Overall, best_list_433_GER_Overall = get_best_squad_n(squad_433_strict, 'Germany', 'Overall')\n",
    "print('-Overall-')\n",
    "print('Average rating: {:.1f}'.format(rating_433_GER_Overall))\n",
    "print(best_list_433_GER_Overall)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-Potential-\n",
      "Average rating: 88.5\n",
      "Position       Player Potential Age                 Club   Value   Wage\n",
      "     GK     M. Neuer        92  31     FC Bayern Munich    €61M  €230K\n",
      "     RB   A. Rüdiger        86  24              Chelsea  €24.5M  €105K\n",
      "     CB      N. Süle        89  21     FC Bayern Munich  €30.5M   €78K\n",
      "     CB   J. Boateng        88  28     FC Bayern Munich    €48M  €215K\n",
      "     LB  B. Henrichs        86  20  Bayer 04 Leverkusen    €11M   €36K\n",
      "    CDM     T. Kroos        90  27       Real Madrid CF    €79M  €340K\n",
      "    CDM  L. Goretzka        88  22        FC Schalke 04    €30M   €46K\n",
      "     RW      M. Özil        88  28              Arsenal    €60M  €265K\n",
      "    CAM    J. Brandt        88  21  Bayer 04 Leverkusen    €22M   €49K\n",
      "     LM      L. Sané        91  21      Manchester City  €34.5M  €125K\n",
      "     CF   K. Havertz        88  18  Bayer 04 Leverkusen     €8M   €25K\n"
     ]
    }
   ],
   "source": [
    "rating_4231_GER_Potential, best_list_4231_GER_Potential = get_best_squad_n(squad_4231_strict, 'Germany', 'Potential')\n",
    "print('-Potential-')\n",
    "print('Average rating: {:.1f}'.format(rating_4231_GER_Potential))\n",
    "print(best_list_4231_GER_Potential)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![kroos](images/kroos.jpeg)\n",
    "\n",
    "### 3.4 Spain\n",
    "How about our 2010's winner?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "               Squad  Overall  Potential\n",
      "Nationality                             \n",
      "Spain          3-4-3    86.27      88.82\n",
      "Spain          4-4-2    86.45      88.73\n",
      "Spain        4-3-1-2    86.55      88.09\n",
      "Spain          4-3-3    86.64      89.00\n",
      "Spain        4-2-3-1    86.64      89.00\n"
     ]
    }
   ],
   "source": [
    "Spain = pd.DataFrame(np.array(get_summary_n(squad_list, squad_name, ['Spain'])).reshape(-1,4), columns = ['Nationality', 'Squad', 'Overall', 'Potential'])\n",
    "Spain.set_index('Nationality', inplace = True)\n",
    "Spain[['Overall', 'Potential']] = Spain[['Overall', 'Potential']].astype(float)\n",
    "\n",
    "print (Spain)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Well, Spain does best with either 4-3-3 or 4-2-3-1 for both current and potential rating. I'll choose 4-2-3-1 for the current squad and 4-3-3 for the potential squad."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-Overall-\n",
      "Average rating: 86.6\n",
      "Position           Player Overall Age               Club   Value   Wage\n",
      "     GK           De Gea      90  26  Manchester United  €64.5M  €215K\n",
      "     RB         Carvajal      84  25     Real Madrid CF    €32M  €195K\n",
      "     CB     Sergio Ramos      90  31     Real Madrid CF    €52M  €310K\n",
      "     CB            Piqué      87  30       FC Barcelona  €37.5M  €240K\n",
      "     LB       Jordi Alba      85  28       FC Barcelona  €30.5M  €215K\n",
      "    CDM           Thiago      88  26   FC Bayern Munich  €70.5M  €225K\n",
      "     CM  Sergio Busquets      86  28       FC Barcelona    €36M  €250K\n",
      "     RM        Juan Mata      84  29  Manchester United  €30.5M  €195K\n",
      "    CAM    Cesc Fàbregas      86  30            Chelsea    €41M  €210K\n",
      "     LM      David Silva      87  31    Manchester City    €44M  €220K\n",
      "     ST      Diego Costa      86  28            Chelsea    €46M  €235K\n"
     ]
    }
   ],
   "source": [
    "rating_4231_ESP_Overall, best_list_4231_ESP_Overall = get_best_squad_n(squad_4231_strict, 'Spain', 'Overall')\n",
    "print('-Overall-')\n",
    "print('Average rating: {:.1f}'.format(rating_4231_ESP_Overall))\n",
    "print(best_list_4231_ESP_Overall)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-Potential-\n",
      "Average rating: 89.0\n",
      "Position           Player Potential Age               Club   Value   Wage\n",
      "     GK           De Gea        92  26  Manchester United  €64.5M  €215K\n",
      "     RB  Héctor Bellerín        88  22            Arsenal    €21M   €91K\n",
      "     CB     Sergio Ramos        90  31     Real Madrid CF    €52M  €310K\n",
      "     CB            Piqué        87  30       FC Barcelona  €37.5M  €240K\n",
      "     LB      Azpilicueta        87  27            Chelsea  €37.5M  €160K\n",
      "    CDM           Thiago        90  26   FC Bayern Munich  €70.5M  €225K\n",
      "    CAM    Dani Ceballos        88  20     Real Madrid CF  €16.5M  €105K\n",
      "    CDM   Diego Llorente        87  23      Real Sociedad    €16M   €29K\n",
      "     RM             Saúl        90  22    Atlético Madrid    €32M   €59K\n",
      "     ST           Morata        88  24            Chelsea    €41M  €170K\n",
      "     LW    Marco Asensio        92  21     Real Madrid CF    €46M  €175K\n"
     ]
    }
   ],
   "source": [
    "rating_433_ESP_Potential, best_list_433_ESP_Potential = get_best_squad_n(squad_433_strict, 'Spain', 'Potential')\n",
    "print('-Potential-')\n",
    "print('Average rating: {:.1f}'.format(rating_433_ESP_Potential))\n",
    "print(best_list_433_ESP_Potential)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![ramos](images/ramos.jpg)\n",
    "\n",
    "### 3.5 England\n",
    "Although having the best soccer league in Europe, England did not seem to do that well at the national level. Let's figure out their options for the upcoming World Cup:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "               Squad  Overall  Potential\n",
      "Nationality                             \n",
      "England        3-4-3    82.64      87.18\n",
      "England        4-4-2    82.64      87.27\n",
      "England      4-3-1-2    82.27      86.73\n",
      "England        4-3-3    82.73      87.36\n",
      "England      4-2-3-1    82.36      87.36\n"
     ]
    }
   ],
   "source": [
    "England = pd.DataFrame(np.array(get_summary_n(squad_list, squad_name, ['England'])).reshape(-1,4), columns = ['Nationality', 'Squad', 'Overall', 'Potential'])\n",
    "England.set_index('Nationality', inplace = True)\n",
    "England[['Overall', 'Potential']] = England[['Overall', 'Potential']].astype(float)\n",
    "\n",
    "print (England)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "England should stick to 4-3-3 with their current squad and either 4-3-3 or 4-2-3-1 with their potential squad. Thus, I'll choose 4-3-3 and 4-2-3-1 respectively."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-Overall-\n",
      "Average rating: 82.7\n",
      "Position        Player Overall Age               Club   Value   Wage\n",
      "     GK       J. Hart      82  30    West Ham United    €14M  €110K\n",
      "    RWB     K. Walker      83  27    Manchester City    €24M  €130K\n",
      "     CB     G. Cahill      84  31            Chelsea    €21M  €160K\n",
      "     CB      M. Keane      81  24            Everton    €21M   €91K\n",
      "    LWB       D. Rose      82  26  Tottenham Hotspur    €21M   €99K\n",
      "     CM    A. Lallana      83  29          Liverpool    €25M  €135K\n",
      "     CM       E. Dier      82  23  Tottenham Hotspur    €25M   €85K\n",
      "     CM  J. Henderson      82  27          Liverpool  €21.5M  €115K\n",
      "     RW    R. Barkley      81  23            Everton    €24M  €105K\n",
      "     ST       H. Kane      86  23  Tottenham Hotspur    €59M  €165K\n",
      "     LM       D. Alli      84  21  Tottenham Hotspur    €43M  €115K\n"
     ]
    }
   ],
   "source": [
    "rating_433_ENG_Overall, best_list_433_ENG_Overall = get_best_squad_n(squad_433_strict, 'England', 'Overall')\n",
    "print('-Overall-')\n",
    "print('Average rating: {:.1f}'.format(rating_433_ENG_Overall))\n",
    "print(best_list_433_ENG_Overall)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-Potential-\n",
      "Average rating: 87.4\n",
      "Position                 Player Potential Age               Club   Value   Wage\n",
      "     GK             J. Butland        87  24         Stoke City    €18M   €50K\n",
      "    RWB  A. Oxlade-Chamberlain        85  23          Liverpool    €20M  €105K\n",
      "     CB               M. Keane        87  24            Everton    €21M   €91K\n",
      "     CB              J. Stones        85  23    Manchester City  €14.5M  €105K\n",
      "     LB                L. Shaw        84  21  Manchester United    €14M   €91K\n",
      "     CM               A. Gomes        90  16  Manchester United   €975K    €9K\n",
      "     CM                E. Dier        87  23  Tottenham Hotspur    €25M   €85K\n",
      "     RM            M. Rashford        89  19  Manchester United    €22M   €74K\n",
      "    CAM             M. Edwards        87  18  Tottenham Hotspur   €1.2M   €11K\n",
      "     LM                D. Alli        90  21  Tottenham Hotspur    €43M  €115K\n",
      "     ST                H. Kane        90  23  Tottenham Hotspur    €59M  €165K\n"
     ]
    }
   ],
   "source": [
    "rating_4231_ENG_Potential, best_list_4231_ENG_Potential = get_best_squad_n(squad_4231_strict, 'England', 'Potential')\n",
    "print('-Potential-')\n",
    "print('Average rating: {:.1f}'.format(rating_4231_ENG_Potential))\n",
    "print(best_list_4231_ENG_Potential)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![kane](images/kane.jpg)\n",
    "\n",
    "### 3.6 Brazil\n",
    "Having won the World Cup the most times in history, the Samba team will no doubt be one of the top candidates for this summer in Russia."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "               Squad  Overall  Potential\n",
      "Nationality                             \n",
      "Brazil         3-4-3    85.36      88.45\n",
      "Brazil         4-4-2    84.73      88.00\n",
      "Brazil       4-3-1-2    84.64      88.00\n",
      "Brazil         4-3-3    85.45      88.73\n",
      "Brazil       4-2-3-1    85.36      88.73\n"
     ]
    }
   ],
   "source": [
    "Brazil = pd.DataFrame(np.array(get_summary_n(squad_list, squad_name, ['Brazil'])).reshape(-1,4), columns = ['Nationality', 'Squad', 'Overall', 'Potential'])\n",
    "Brazil.set_index('Nationality', inplace = True)\n",
    "Brazil[['Overall', 'Potential']] = Brazil[['Overall', 'Potential']].astype(float)\n",
    "\n",
    "print (Brazil)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you can see, Brazil has similar options like England. I'll go with 4-3-3 for the current rating and 4-2-3-1 for the potential rating."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-Overall-\n",
      "Average rating: 85.5\n",
      "Position         Player Overall Age                 Club   Value   Wage\n",
      "     GK        Ederson      83  23      Manchester City    €26M   €87K\n",
      "     RB     Dani Alves      84  34  Paris Saint-Germain     €9M  €115K\n",
      "     CB   Thiago Silva      88  32  Paris Saint-Germain    €34M  €175K\n",
      "     CB     David Luiz      86  30              Chelsea    €33M  €190K\n",
      "     LB        Marcelo      87  29       Real Madrid CF    €38M  €250K\n",
      "    CDM       Casemiro      85  25       Real Madrid CF    €42M  €195K\n",
      "    CAM       Coutinho      86  25            Liverpool    €56M  €205K\n",
      "    CAM        Willian      84  28              Chelsea  €31.5M  €200K\n",
      "     RM  Douglas Costa      82  26             Juventus    €24M  €115K\n",
      "     CF          Jonas      83  33           SL Benfica  €16.5M   €21K\n",
      "     LW         Neymar      92  25  Paris Saint-Germain   €123M  €280K\n"
     ]
    }
   ],
   "source": [
    "rating_433_BRA_Overall, best_list_433_BRA_Overall = get_best_squad_n(squad_433_strict, 'Brazil', 'Overall')\n",
    "print('-Overall-')\n",
    "print('Average rating: {:.1f}'.format(rating_433_BRA_Overall))\n",
    "print(best_list_433_BRA_Overall)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-Potential-\n",
      "Average rating: 88.7\n",
      "Position         Player Potential Age                   Club   Value   Wage\n",
      "     GK        Ederson        89  23        Manchester City    €26M   €87K\n",
      "     RB     Dani Alves        84  34    Paris Saint-Germain     €9M  €115K\n",
      "     CB     Marquinhos        89  23    Paris Saint-Germain  €30.5M   €75K\n",
      "     CB   Thiago Silva        88  32    Paris Saint-Germain    €34M  €175K\n",
      "     LB        Marcelo        87  29         Real Madrid CF    €38M  €250K\n",
      "    CDM       Casemiro        89  25         Real Madrid CF    €42M  €195K\n",
      "    CDM        Fabinho        88  23              AS Monaco  €29.5M   €37K\n",
      "     RM         Malcom        87  20  Girondins de Bordeaux  €24.5M   €47K\n",
      "    CAM       Coutinho        89  25              Liverpool    €56M  €205K\n",
      "     LW         Neymar        94  25    Paris Saint-Germain   €123M  €280K\n",
      "     ST  Gabriel Jesus        92  20        Manchester City    €31M  €115K\n"
     ]
    }
   ],
   "source": [
    "rating_4231_BRA_Potential, best_list_4231_BRA_Potential = get_best_squad_n(squad_4231_strict, 'Brazil', 'Potential')\n",
    "print('-Potential-')\n",
    "print('Average rating: {:.1f}'.format(rating_4231_BRA_Potential))\n",
    "print(best_list_4231_BRA_Potential)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![neymar](images/neymar.jpg)\n",
    "\n",
    "### 3.7 Argentina\n",
    "Lionel Messi is still waiting for the only trophy he hasn't gotten yet in his career. Can he carry Argentina to the top after going short in the final 4 years ago?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "               Squad  Overall  Potential\n",
      "Nationality                             \n",
      "Argentina      3-4-3    84.27      87.36\n",
      "Argentina      4-4-2    83.45      87.27\n",
      "Argentina    4-3-1-2    83.55      86.73\n",
      "Argentina      4-3-3    84.27      87.36\n",
      "Argentina    4-2-3-1    84.00      87.09\n"
     ]
    }
   ],
   "source": [
    "Argentina = pd.DataFrame(np.array(get_summary_n(squad_list, squad_name, ['Argentina'])).reshape(-1,4), columns = ['Nationality', 'Squad', 'Overall', 'Potential'])\n",
    "Argentina.set_index('Nationality', inplace = True)\n",
    "Argentina[['Overall', 'Potential']] = Argentina[['Overall', 'Potential']].astype(float)\n",
    "\n",
    "print (Argentina)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Both 3-4-3 and 4-3-3 fare very well for the current and potential ratings of Argentine players. For the sake of diversity, I'll choose 3-4-3 for their current squad and 4-3-3 for their future squad."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-Overall-\n",
      "Average rating: 84.3\n",
      "Position        Player Overall Age                 Club   Value   Wage\n",
      "     GK      G. Rulli      83  25        Real Sociedad  €25.5M   €28K\n",
      "     CB   N. Otamendi      83  29      Manchester City    €20M  €140K\n",
      "     CB  M. Musacchio      83  26                Milan    €27M  €105K\n",
      "     CB      E. Garay      83  30          Valencia CF    €19M   €40K\n",
      "     RB   P. Zabaleta      79  32      West Ham United     €7M   €99K\n",
      "     CM     E. Banega      83  29           Sevilla FC  €25.5M   €27K\n",
      "     CM     L. Biglia      83  31                Milan  €17.5M  €105K\n",
      "     LB       M. Rojo      82  27    Manchester United    €21M  €130K\n",
      "     RW      L. Messi      93  30         FC Barcelona   €105M  €565K\n",
      "     ST    G. Higuaín      90  29             Juventus    €77M  €275K\n",
      "     LW   A. Di María      85  29  Paris Saint-Germain  €37.5M  €145K\n"
     ]
    }
   ],
   "source": [
    "rating_343_ARG_Overall, best_list_343_ARG_Overall = get_best_squad_n(squad_343_strict, 'Argentina', 'Overall')\n",
    "print('-Overall-')\n",
    "print('Average rating: {:.1f}'.format(rating_343_ARG_Overall))\n",
    "print(best_list_343_ARG_Overall)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-Potential-\n",
      "Average rating: 87.4\n",
      "Position        Player Potential Age                  Club   Value   Wage\n",
      "     GK      G. Rulli        89  25         Real Sociedad  €25.5M   €28K\n",
      "     RB      J. Figal        82  23         Independiente     €8M   €16K\n",
      "     CB  M. Musacchio        86  26                 Milan    €27M  €105K\n",
      "     CB    E. Mammana        86  21  Zenit St. Petersburg    €10M   €36K\n",
      "     LB       M. Rojo        83  27     Manchester United    €21M  €130K\n",
      "     CM      E. Barco        90  18         Independiente   €6.5M    €8K\n",
      "     CM   G. Lo Celso        86  21   Paris Saint-Germain    €10M   €48K\n",
      "    CDM  S. Ascacibar        86  20         VfB Stuttgart     €7M   €17K\n",
      "     RW      L. Messi        93  30          FC Barcelona   €105M  €565K\n",
      "     ST     P. Dybala        93  23              Juventus    €79M  €215K\n",
      "     LM    M. Lanzini        87  24       West Ham United  €24.5M   €95K\n"
     ]
    }
   ],
   "source": [
    "rating_433_ARG_Potential, best_list_433_ARG_Potential = get_best_squad_n(squad_433_strict, 'Argentina', 'Potential')\n",
    "print('-Potential-')\n",
    "print('Average rating: {:.1f}'.format(rating_433_ARG_Potential))\n",
    "print(best_list_433_ARG_Potential)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![messi](images/messi.jpg)\n",
    "\n",
    "### 3.8 Belgium\n",
    "The Red Devils has some of the best players in English Premier League, but can't never seem to make it far in the national level. Can Hazard and De Bruyne drive them far this time?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "               Squad  Overall  Potential\n",
      "Nationality                             \n",
      "Belgium        3-4-3    83.91      86.55\n",
      "Belgium        4-4-2    83.36      86.73\n",
      "Belgium      4-3-1-2    83.09      86.09\n",
      "Belgium        4-3-3    84.27      87.27\n",
      "Belgium      4-2-3-1    84.00      87.00\n"
     ]
    }
   ],
   "source": [
    "Belgium = pd.DataFrame(np.array(get_summary_n(squad_list, squad_name, ['Belgium'])).reshape(-1,4), columns = ['Nationality', 'Squad', 'Overall', 'Potential'])\n",
    "Belgium.set_index('Nationality', inplace = True)\n",
    "Belgium[['Overall', 'Potential']] = Belgium[['Overall', 'Potential']].astype(float)\n",
    "\n",
    "print (Belgium)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Again, 4-3-3 is the best formation for Belgium's both current and future squad."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-Overall-\n",
      "Average rating: 84.3\n",
      "Position           Player Overall Age               Club   Value   Wage\n",
      "     GK      T. Courtois      89  25            Chelsea    €59M  €190K\n",
      "     RB         T. Foket      73  22           KAA Gent   €5.5M   €19K\n",
      "     CB  T. Alderweireld      86  28  Tottenham Hotspur  €40.5M  €165K\n",
      "     CB    J. Vertonghen      85  30  Tottenham Hotspur  €28.5M  €130K\n",
      "     LB     T. Vermaelen      78  31       FC Barcelona     €7M  €120K\n",
      "    CDM       M. Dembélé      83  29  Tottenham Hotspur    €25M  €115K\n",
      "    CAM    R. Nainggolan      86  29               Roma  €42.5M  €130K\n",
      "    CAM        A. Witsel      82  28                NaN      €0     €0\n",
      "     RM     K. De Bruyne      89  26    Manchester City    €83M  €285K\n",
      "     ST        R. Lukaku      86  24  Manchester United    €59M  €210K\n",
      "     LW        E. Hazard      90  26            Chelsea  €90.5M  €295K\n"
     ]
    }
   ],
   "source": [
    "rating_433_BEL_Overall, best_list_433_BEL_Overall = get_best_squad_n(squad_433_strict, 'Belgium', 'Overall')\n",
    "print('-Overall-')\n",
    "print('Average rating: {:.1f}'.format(rating_433_BEL_Overall))\n",
    "print(best_list_433_BEL_Overall)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-Potential-\n",
      "Average rating: 87.3\n",
      "Position           Player Potential Age               Club   Value   Wage\n",
      "     GK      T. Courtois        92  25            Chelsea    €59M  €190K\n",
      "     RB         T. Foket        79  22           KAA Gent   €5.5M   €19K\n",
      "     CB  T. Alderweireld        87  28  Tottenham Hotspur  €40.5M  €165K\n",
      "     CB    L. Dendoncker        86  22     RSC Anderlecht    €15M   €25K\n",
      "     LB        J. Lukaku        83  22              Lazio    €10M   €39K\n",
      "     CM          D. Rigo        84  18                PSV   €1.3M    €3K\n",
      "    CAM     Y. Tielemans        90  20          AS Monaco  €23.5M   €35K\n",
      "    CAM    R. Nainggolan        86  29               Roma  €42.5M  €130K\n",
      "     RM     K. De Bruyne        92  26    Manchester City    €83M  €285K\n",
      "     ST        R. Lukaku        90  24  Manchester United    €59M  €210K\n",
      "     LW        E. Hazard        91  26            Chelsea  €90.5M  €295K\n"
     ]
    }
   ],
   "source": [
    "rating_433_BEL_Potential, best_list_433_BEL_Potential = get_best_squad_n(squad_433_strict, 'Belgium', 'Potential')\n",
    "print('-Potential-')\n",
    "print('Average rating: {:.1f}'.format(rating_433_BEL_Potential))\n",
    "print(best_list_433_BEL_Potential)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![de-bruyne](images/de-bruyne.jpg)\n",
    "\n",
    "### 3.9 - Portugal\n",
    "The winner of Euro 2016 and the best player in the world 3 times in a row, Cristiano Ronaldo, has a real chance in this tournament as well."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "               Squad  Overall  Potential\n",
      "Nationality                             \n",
      "Portugal       3-4-3    83.00      87.00\n",
      "Portugal       4-4-2    83.00      87.27\n",
      "Portugal     4-3-1-2    82.82      86.55\n",
      "Portugal       4-3-3    83.45      87.45\n",
      "Portugal     4-2-3-1    83.45      87.27\n"
     ]
    }
   ],
   "source": [
    "Portugal = pd.DataFrame(np.array(get_summary_n(squad_list, squad_name, ['Portugal'])).reshape(-1,4), columns = ['Nationality', 'Squad', 'Overall', 'Potential'])\n",
    "Portugal.set_index('Nationality', inplace = True)\n",
    "Portugal[['Overall', 'Potential']] = Portugal[['Overall', 'Potential']].astype(float)\n",
    "\n",
    "print (Portugal)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "OK, I'll go with 4-2-3-1 for current rating and 4-3-3 for potential rating of Portugal."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-Overall-\n",
      "Average rating: 83.5\n",
      "Position             Player Overall Age                Club   Value   Wage\n",
      "     GK           A. Lopes      83  26  Olympique Lyonnais  €22.5M   €60K\n",
      "     RB      Nélson Semedo      81  23        FC Barcelona  €20.5M  €125K\n",
      "     CB               Pepe      86  34         Beşiktaş JK  €13.5M   €94K\n",
      "     CB         José Fonte      79  33     West Ham United     €5M   €99K\n",
      "     LB            Antunes      79  30           Getafe CF     €9M   €29K\n",
      "     CM   William Carvalho      83  25         Sporting CP  €27.5M   €21K\n",
      "     CM     Danilo Pereira      83  25            FC Porto  €27.5M   €18K\n",
      "     RM     Bernardo Silva      84  22     Manchester City  €43.5M  €165K\n",
      "    CAM         João Mário      83  24               Inter    €34M   €70K\n",
      "     LM               Nani      83  30               Lazio  €24.5M   €47K\n",
      "     ST  Cristiano Ronaldo      94  32      Real Madrid CF  €95.5M  €565K\n"
     ]
    }
   ],
   "source": [
    "rating_4231_POR_Overall, best_list_4231_POR_Overall = get_best_squad_n(squad_4231_strict, 'Portugal', 'Overall')\n",
    "print('-Overall-')\n",
    "print('Average rating: {:.1f}'.format(rating_4231_POR_Overall))\n",
    "print(best_list_4231_POR_Overall)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-Potential-\n",
      "Average rating: 87.5\n",
      "Position             Player Potential Age                Club   Value   Wage\n",
      "     GK           A. Lopes        86  26  Olympique Lyonnais  €22.5M   €60K\n",
      "     RB      Nélson Semedo        87  23        FC Barcelona  €20.5M  €125K\n",
      "     CB               Pepe        86  34         Beşiktaş JK  €13.5M   €94K\n",
      "     CB       Rúben Semedo        85  23       Villarreal CF  €12.5M   €27K\n",
      "     LB        Rafa Soares        83  22              Fulham   €8.5M   €11K\n",
      "     CM   William Carvalho        86  25         Sporting CP  €27.5M   €21K\n",
      "    CAM         João Mário        88  24               Inter    €34M   €70K\n",
      "    CAM        André Gomes        88  23        FC Barcelona    €30M  €150K\n",
      "     RM     Bernardo Silva        91  22     Manchester City  €43.5M  €165K\n",
      "     ST  Cristiano Ronaldo        94  32      Real Madrid CF  €95.5M  €565K\n",
      "     LM     Gelson Martins        88  22         Sporting CP    €25M   €20K\n"
     ]
    }
   ],
   "source": [
    "rating_433_POR_Potential, best_list_433_POR_Potential = get_best_squad_n(squad_433_strict, 'Portugal', 'Potential')\n",
    "print('-Potential-')\n",
    "print('Average rating: {:.1f}'.format(rating_433_POR_Potential))\n",
    "print(best_list_433_POR_Potential)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![ronaldo](images/ronaldo.jpg)\n",
    "\n",
    "### 3.10 - Uruguay\n",
    "Uruguay has the 2 best strikers in Europe: Suarez & Cavani. Can they perform this time?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "               Squad  Overall  Potential\n",
      "Nationality                             \n",
      "Uruguay        3-4-3    80.64      84.91\n",
      "Uruguay        4-4-2    81.09      85.27\n",
      "Uruguay      4-3-1-2    81.09      84.73\n",
      "Uruguay        4-3-3    80.18      84.91\n",
      "Uruguay      4-2-3-1    79.82      84.27\n"
     ]
    }
   ],
   "source": [
    "Uruguay = pd.DataFrame(np.array(get_summary_n(squad_list, squad_name, ['Uruguay'])).reshape(-1,4), columns = ['Nationality', 'Squad', 'Overall', 'Potential'])\n",
    "Uruguay.set_index('Nationality', inplace = True)\n",
    "Uruguay[['Overall', 'Potential']] = Uruguay[['Overall', 'Potential']].astype(float)\n",
    "\n",
    "print (Uruguay)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Fantastic, Uruguay does best with a 4-3-1-2 for current rating and 4-4-2 for future rating."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-Overall-\n",
      "Average rating: 81.1\n",
      "Position         Player Overall Age                 Club   Value   Wage\n",
      "     GK     F. Muslera      82  31       Galatasaray SK  €13.5M   €57K\n",
      "     RB     M. Cáceres      77  30        Hellas Verona   €6.5M   €28K\n",
      "     CB       D. Godín      88  31      Atlético Madrid    €40M  €125K\n",
      "     CB     J. Giménez      83  22      Atlético Madrid  €28.5M   €53K\n",
      "     LB       F. Ricca      74  22            Málaga CF     €7M   €18K\n",
      "    CDM      M. Vecino      78  25                Inter    €13M   €59K\n",
      "    CDM       M. Lemos      77  21        UD Las Palmas  €10.5M   €17K\n",
      "     CM  S. Cristóforo      76  23           Fiorentina   €8.5M   €48K\n",
      "     CF     N. Lodeiro      78  28  Seattle Sounders FC  €10.5M   €11K\n",
      "     ST      L. Suárez      92  30         FC Barcelona    €97M  €510K\n",
      "     ST      E. Cavani      87  30  Paris Saint-Germain  €48.5M  €160K\n"
     ]
    }
   ],
   "source": [
    "rating_4312_URG_Overall, best_list_4312_URG_Overall = get_best_squad_n(squad_4312_strict, 'Uruguay', 'Overall')\n",
    "print('-Overall-')\n",
    "print('Average rating: {:.1f}'.format(rating_4312_URG_Overall))\n",
    "print(best_list_4312_URG_Overall)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-Potential-\n",
      "Average rating: 85.3\n",
      "Position       Player Potential Age                       Club   Value   Wage\n",
      "     GK   F. Muslera        82  31             Galatasaray SK  €13.5M   €57K\n",
      "     RB  C. González        82  20           Sevilla Atlético   €1.8M    €3K\n",
      "     CB     D. Godín        88  31            Atlético Madrid    €40M  €125K\n",
      "     CB   J. Giménez        87  22            Atlético Madrid  €28.5M   €53K\n",
      "    LWB  M. Saracchi        85  19                River Plate   €3.4M    €7K\n",
      "     RM  F. Valverde        85  18  RC Deportivo de La Coruña   €3.6M   €44K\n",
      "     CM    N. Nández        85  21               Boca Juniors   €3.5M   €11K\n",
      "     CM  L. Torreira        83  21                  Sampdoria    €10M   €26K\n",
      "     LM    D. Laxalt        82  24                      Genoa  €13.5M   €30K\n",
      "     ST    L. Suárez        92  30               FC Barcelona    €97M  €510K\n",
      "     ST    E. Cavani        87  30        Paris Saint-Germain  €48.5M  €160K\n"
     ]
    }
   ],
   "source": [
    "rating_442_URG_Potential, best_list_442_URG_Potential = get_best_squad_n(squad_442_strict, 'Uruguay', 'Potential')\n",
    "print('-Potential-')\n",
    "print('Average rating: {:.1f}'.format(rating_442_URG_Potential))\n",
    "print(best_list_442_URG_Potential)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](images/cavani.jpg)\n",
    "\n",
    "### 3.11 - Croatia\n",
    "Well, I'm a big fan of Modric and Rakitic. Needless to say about their winning habits?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "               Squad  Overall  Potential\n",
      "Nationality                             \n",
      "Croatia        3-4-3    80.55      83.00\n",
      "Croatia        4-4-2    80.82      83.00\n",
      "Croatia      4-3-1-2    81.27      83.64\n",
      "Croatia        4-3-3    81.64      83.91\n",
      "Croatia      4-2-3-1    81.64      83.64\n"
     ]
    }
   ],
   "source": [
    "Croatia = pd.DataFrame(np.array(get_summary_n(squad_list, squad_name, ['Croatia'])).reshape(-1,4), columns = ['Nationality', 'Squad', 'Overall', 'Potential'])\n",
    "Croatia.set_index('Nationality', inplace = True)\n",
    "Croatia[['Overall', 'Potential']] = Croatia[['Overall', 'Potential']].astype(float)\n",
    "\n",
    "print (Croatia)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Dope, Croatia is superior with a 4-2-3-1 using current form and 4-3-3 using potential form."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-Overall-\n",
      "Average rating: 81.6\n",
      "Position        Player Overall Age              Club   Value   Wage\n",
      "     GK    D. Subašić      85  32         AS Monaco    €22M   €46K\n",
      "     RB       D. Srna      81  35  Shakhtar Donetsk   €3.8M    €1K\n",
      "     CB    V. Ćorluka      82  31  Lokomotiv Moscow    €15M   €54K\n",
      "     CB     D. Lovren      81  27         Liverpool  €17.5M  €110K\n",
      "     LB    I. Strinić      75  29         Sampdoria     €5M   €31K\n",
      "    CDM     L. Modrić      89  31    Real Madrid CF    €57M  €340K\n",
      "     CM    I. Rakitić      87  29      FC Barcelona  €48.5M  €275K\n",
      "     RM    J. Brekalo      70  19     VfB Stuttgart   €3.1M   €21K\n",
      "    CAM    I. Perišić      84  28             Inter  €31.5M  €110K\n",
      "     LM  M. Mandžukić      83  31          Juventus  €23.5M  €135K\n",
      "     ST    N. Kalinić      81  29             Milan    €18M   €84K\n"
     ]
    }
   ],
   "source": [
    "rating_4231_CRO_Overall, best_list_4231_CRO_Overall = get_best_squad_n(squad_4231_strict, 'Croatia', 'Overall')\n",
    "print('-Overall-')\n",
    "print('Average rating: {:.1f}'.format(rating_4231_CRO_Overall))\n",
    "print(best_list_4231_CRO_Overall)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-Potential-\n",
      "Average rating: 83.9\n",
      "Position      Player Potential Age                 Club   Value   Wage\n",
      "     GK  D. Subašić        85  32            AS Monaco    €22M   €46K\n",
      "     RB   T. Jedvaj        84  21  Bayer 04 Leverkusen    €10M   €36K\n",
      "     CB   D. Lovren        83  27            Liverpool  €17.5M  €110K\n",
      "     CB  V. Ćorluka        82  31     Lokomotiv Moscow    €15M   €54K\n",
      "     LB    A. Milić        76  23          KV Oostende   €2.7M    €9K\n",
      "    CDM   L. Modrić        89  31       Real Madrid CF    €57M  €340K\n",
      "    CDM  M. Kovačić        88  23       Real Madrid CF    €30M  €150K\n",
      "     CM  I. Rakitić        87  29         FC Barcelona  €48.5M  €275K\n",
      "     RM  J. Brekalo        82  19        VfB Stuttgart   €3.1M   €21K\n",
      "     ST  N. Kalinić        81  29                Milan    €18M   €84K\n",
      "     LW    M. Pjaca        86  22             Juventus  €12.5M   €89K\n"
     ]
    }
   ],
   "source": [
    "rating_433_CRO_Potential, best_list_433_CRO_Potential = get_best_squad_n(squad_433_strict, 'Croatia', 'Potential')\n",
    "print('-Potential-')\n",
    "print('Average rating: {:.1f}'.format(rating_433_CRO_Potential))\n",
    "print(best_list_433_CRO_Potential)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](images/modric.jpg)\n",
    "\n",
    "## 4 - Final Comparison\n",
    "Ok, let's make some comparison between these 10 line-ups with the current rating of players for these strongest contenders for World Cup 2018."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10b54ed30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "teams = ('France', 'Germany', 'Spain', 'England', 'Brazil', 'Argentina', 'Belgium', 'Portugal', 'Uruguay', 'Croatia')\n",
    "index = np.arange(len(teams))\n",
    "average_overall = [84.6, 86.3, 86.6, 82.7, 85.5, 84.3, 84.3, 83.5, 81.1, 81.6]\n",
    "\n",
    "plt.figure(figsize=(16,8))\n",
    "plt.barh(index, average_overall, align='center', alpha=0.5)\n",
    "plt.yticks(index, teams, fontsize=20)\n",
    "plt.ylabel('National Teams', fontsize=25)\n",
    "plt.xlabel('Average Overall', fontsize=25)\n",
    "plt.title('Average Overall Rating of Players', fontsize=30, fontweight='bold', y=1.05,)\n",
    " \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1040be400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "total_value = [446.5, 502, 484.5, 298.5, 433, 382, 440.5, 323, 283.5, 244.9]\n",
    "\n",
    "plt.figure(figsize=(16,8))\n",
    "plt.barh(index, total_value, align='center', alpha=0.5, color='red')\n",
    "plt.yticks(index, teams, fontsize=20)\n",
    "plt.ylabel('National Teams', fontsize=25)\n",
    "plt.xlabel('Total Value in Million Euros', fontsize=25)\n",
    "plt.title('Total Value of Players', fontsize=30, fontweight='bold', y=1.05,)\n",
    " \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1062afb38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "average_wage = [141, 188, 228, 119, 167, 151, 166, 118, 99, 110]\n",
    "\n",
    "plt.figure(figsize=(16,8))\n",
    "plt.barh(index, average_wage, align='center', alpha=0.5, color='green')\n",
    "plt.yticks(index, teams, fontsize=20)\n",
    "plt.ylabel('National Teams', fontsize=25)\n",
    "plt.xlabel('Average Wages in Thousand Euros', fontsize=25)\n",
    "plt.title('Average Wages of Players', fontsize=30, fontweight='bold', y=1.05,)\n",
    " \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusion\n",
    "So based purely on the FIFA 18 Data:\n",
    "* Spain has the highest average overall rating, followed by Germany and Brazil. \n",
    "* Germany has the highest total value, followed by Spain and France. \n",
    "* Spain has the highest average wage, followed by Germany and Brazil.\n",
    "\n",
    "My bet is for a **Spain vs Germany** in the final, and **Brazil vs France** for the 3rd place. Your turn?"
   ]
  }
 ],
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