co2 emmision plot

co2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv('co2.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df.columns = ['year', 'co2', 'avg_tmp']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>co2</th>\n",
       "      <th>avg_tmp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1960</td>\n",
       "      <td>120581.961</td>\n",
       "      <td>24.287167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1961</td>\n",
       "      <td>130402.187</td>\n",
       "      <td>23.815250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1962</td>\n",
       "      <td>143467.708</td>\n",
       "      <td>23.884750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1963</td>\n",
       "      <td>154083.673</td>\n",
       "      <td>24.095750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1964</td>\n",
       "      <td>150647.694</td>\n",
       "      <td>24.070500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   year         co2    avg_tmp\n",
       "0  1960  120581.961  24.287167\n",
       "1  1961  130402.187  23.815250\n",
       "2  1962  143467.708  23.884750\n",
       "3  1963  154083.673  24.095750\n",
       "4  1964  150647.694  24.070500"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "year         int64\n",
       "co2        float64\n",
       "avg_tmp    float64\n",
       "dtype: object"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Set some parameters to get good visuals - style to ggplot and size to 15,10\n",
    "plt.style.use('classic')\n",
    "plt.rcParams['figure.figsize'] = (10, 8)\n",
    "#pd.options.display.mpl_style = 'default'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fd32f3140d0>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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vXq0+ffpYHC8sLFR5ebni4uIs4gaDQZs3b9Zbb72llJQU+fv733Sc7OxsvfzyyxozZowW\nL17c/BemH55VJzW+WUp7o5gDAAAAHJitboBSX1+vlStX6uTJk1q1apWCgoKscqZMmaJRo0ZZxK5c\nuaLVq1crKipKo0aNUs+ePc3H8vPz5e7ubu6mSdIXX3yhVatWaciQIUpISLjhfEpLS60KtsLCQu3a\ntUv+/v4WHUNbQTEHAAAAoM0lJSXp8OHDCg0NVWlpqfbs2WNxPDIyUgEBAQoICLCINyy39PPzU2ho\nqMWxuLg4DRkyRGvWrJEkfffdd0pISJDBYNDo0aO1b98+i3x/f3/1799fkrRhwwZdvHhRQ4cONe9m\n+f7776uqqkpPPvnkbX3ttwvFHAAAAIA2d+bMGRkMBh0+fFiHDx+2Oh4ZGXnDc2/U9bs+/u2336qy\nslLSD483uN6vfvUrczE3YsQIZWZmaseOHSovL1enTp00ZMgQPfbYY1YFpa2gmAMAAAAcmMFgsNiC\nvy3HvZm1a9f+pOv26NFDe/fubfTY9fEhQ4bcMPd6ERERioiI+Elzai88mgAAAAAA7BCdOQAAAMCB\n2eoGKLh1dOYAAAAAwA5RzAEAAACAHWKZJQAAAODAWGbpuOjMAQAAAIAdojMHAAAAODA6c47LJou5\nyspKpaen69SpUzp16pTKysq0bNkyTZw40SLvxRdfVFZWltX5ffr00RtvvGERu9EzIx5//HFNnz7d\nIlZeXq4NGzbo4MGDqqqqUlBQkBYsWKABAwZYnZ+Tk6Pk5GTl5eWpQ4cOCgsL05w5c+Th4WGRZzKZ\nlJ6erszMTBUXF8vX11czZ860u2dZAAAAALANNlnMlZaWatOmTerevbv8/f31xRdf3DDX1dVVv/3t\nb2Uymcyxjh07Npo7fPhwTZgwwSJ2fYFmMpn09NNP6+uvv9a0adPUuXNn7dixQ0uWLFFycrJ69+5t\nzs3Ly9PSpUvVt29fPfHEEyosLNQ777yjCxcu6IUXXrC4bmpqqtLS0vTwww8rMDBQhw4d0qpVq2Qw\nGBQeHt7s9wYAAAAAJBst5nx8fLR161Z16dJFubm5WrBgwQ1znZ2dNW7cuGZd19fXV+PHj79pzv79\n+3XixAmtXLlSo0ePliSFhYVp1qxZeuONN5SQkGDOTU1Nlaenp9atW2fuxHXv3l1r1qzR0aNHNWzY\nMElSUVGRMjIyNGnSJC1atEiSFB0drcWLFys5OVlhYWG0oQEAANAqWGbpuGxyAxQXFxd16dKl2fn1\n9fW6evVqs3JrampUU1Nzw+MHDhyQl5eXuZCTJKPRqLCwMB08eFC1tbWSpKtXr+ro0aOaMGGCxZLK\niRMnyt3dXfv27TPHsrOzVVdXp9jYWIuxYmNjVVhYqOPHjzdr7gAAAADQwCaLuZaoqqpSdHS0YmJi\nFBsbq1deeUWVlZWN5mZlZennP/+5oqKiFBcXp71791rl5OXlNXpv3KBBg1RdXa3z589Lks6ePau6\nujoFBgZa5Lm4uCggIEB5eXkW13R3d1efPn2srmkymXT69OkWv24AAACguRq6c235g9Znk8ssm8vb\n21vTpk1TYGCg6uvrdeTIEe3YsUNnz57V2rVr5eT0f7VqcHCwwsPD1aNHDxUVFWn79u16/vnnVVFR\noV/84hfmvOLiYt1///2NjtVwvF+/fiouLpbBYJCXl5dVrpeXl3Jycsy/l5SUNNpp/PE1AQAAAKAl\n7LqYmzNnjsXv4eHh8vX11caNG/XJJ59YbCySmJhokfvQQw9p7ty5+vOf/6yoqCi5urpKkqqrq3XX\nXXdZjeXq6iqTyaTq6mpJMi/VbDjv+tyGvKau2XAcAAAAAFrC7pdZXu/RRx+VJB09evSmec7Oznrk\nkUdUXl6ur776yhx3c3PTtWvXrPJrampkMBjk5uYm6f8Kscbuv6upqTHnNXXNhuMAAABAa3Bycmq3\nH7Quu+7MNcbV1VVGo1FlZWVN5nbr1k2SLHK9vb0bXfbYEGtYGunt7S2TyaSSkhKr3JKSEnOe9MOy\ny2PHjjV5zRtZsmSJjEajRWz69OlWz8cDAABA60lLS1NaWppFrLS0tJ1mAzhgMVdZWanS0lLdfffd\nTeZevHhRkiwKJX9/f4v73RqcOHFCbm5uuueeeyRJ/fr1k7Ozs3JzczV27FhzXm1trfLy8iyWeAYE\nBGjnzp3Kz8+32ATlxIkTMhgMCggIuOk8165dq6FDhzb5egAAANB6Gvsy/fPPPzc/jspW8WgCx2W3\nvc+amppGd638y1/+Ikl64IEHzLHGvjG5evWq3n33XRmNRg0cONAcHzt2rC5fvqwDBw5YnH/gwAGF\nhobKxeWH+rdjx44aNmyY9uzZYzGPrKwsVVVVKSwszBwbOXKknJ2dtX37dos5ZGZmysfHR8HBwS18\n9QAAAADudDbbmdu2bZsqKipUWFgoSTp06JD5z5MnT9b333+vuXPnKiIiwtztOnLkiI4cOaIHH3xQ\nI0eONF9r+/btys7OVkhIiLp3766ioiLt2rVLly5dUkJCgpydnc25Y8eO1datW/XSSy/p3LlzMhqN\n2rFjh+rr6xUXF2cxx/j4eC1atEiLFy9WTEyMCgsLlZGRoREjRmj48OHmvK5du2rKlCnasmWLamtr\nNXDgQGVnZysnJ0cJCQl8awEAAACgxWy2mNuyZYsuXbok6YcWbXZ2trKzsyVJkZGR6tSpk0JCQvT5\n559r9+7dqq+vV+/evfX4449r6tSpFtcKDg7W8ePHtXPnTpWWlsrDw0NBQUFatmyZhgwZYpHr5OSk\nF154QRs2bNC2bdtUXV2tQYMGafny5fL19bXIHTBggF5++WWlpKRo/fr18vDwUHR0tNUum5I0b948\nde7cWZmZmcrKypKvr68SEhIUERFxO982AAAAwALLLB2XzRZz199c2pjly5c361rDhg1r0VrmTp06\naenSpVq6dGmTucHBwVaPPbgRNi0BANgSk8mk/fv369VXX9XevXtVXl4uDw8PDR8+XAsXLtQvfvGL\nRh+tAwCwDTZbzAEAgNZz9uxZTZo0SV9++aW6deum//iP/5CHh4dqamp05swZ/fKXv1Tv3r2VkZGh\nkJCQ9p4ugFtEl8wxUcwBAHCHOXPmjEJCQlRfX6+ZM2eqb9++Fv/QCw0N1Xfffafdu3crPDxcu3fv\n1pgxY9pxxgCAxtjtbpYAAKDl6urqFBMTI5PJpFmzZsnPz6/Rb+y7d++u6dOnq1evXoqNjW30GawA\ngPZFMQcAwB0kKytLp06dUnR0tDp27HjTXBcXF8XGxqq8vFyvv/56G80QwO3WsAFKe/ygdVHMAQBw\nB3n11VfVq1cv9e7du1n5HTt21KBBg/Tqq6+qvr6+lWcHAGgJijkAAO4QJpNJe/bs0eDBg1v0jXlw\ncLDOnTunM2fOtOLsALQWJyendvtB6+IdBgDgDnH16lVdu3atyeWV12vILy0tbY1pAQB+Ioo5AADu\nEO7u7pKka9eutei8hvwOHTrc9jkBAH46ijkAAO4Qzs7Ouu+++3T27NkWnZeXlydPT0/5+fm1zsQA\ntCo2QHFcFHMAANxBFixYoNzcXH3//ffNyq+trdW//vUvxcXF0ZkDABtDMQcAwB3kscceU6dOnbRn\nzx6ZTKYm87Ozs1VWVqYFCxa0wewAtBa6co6JYg4AgDuIp6enNm3apNzcXL333ns3vH+uvr5en3zy\niQ4ePKgXX3xRQUFBbTxTAEBTXNp7AgAAoG3FxsYqPT1ds2bN0tmzZ3Xfffdp8ODB6tChg6qrq3X6\n9Gl98cUXunLlin7/+9/rt7/9bXtPGQDQCIo5AADuQFOnTtXw4cO1YcMGvfbaa/r73/9uPubu7q6Z\nM2dq4cKF+tnPftaOswRwO7TXM994zlzro5gDAOAO1b9/f7300kv6f//v/+nLL79UaWmpOnXqpMGD\nB8toNLb39AAATaCYAwDgDufu7q4HHnigvacBoJW014YkbILS+uh9AgAAAIAdopgDAAAAADvEMksA\nAADAgRkMhnbZjIRllq2PzhwAAAAA2CE6cwAAAIADYwMUx0VnDgAAAADsEMUcAAAAANghllkCAAAA\nDoxllo6LzhwAAAAA2CE6cwAAAIADc3JyapdHE7THmHca3mEAAAAAsEMUcwAAAABgh1hmCQAAADgw\nNkBxXHTmAAAAAMAO0ZkDAAAAHJjBYGiXzUjozLU+OnMAAAAAYIco5gAAAADADrHMEgAAAHBgtroB\nSm5urnbt2qVjx46poKBARqNRQUFBio+Pl6+vb6Pn1NXVKT4+Xvn5+Zo/f76mTp160zGqq6v14Ycf\n6tChQ/r6669VWVmp3r17KyYmRjExMVbLT00mk9LT05WZmani4mL5+vpq5syZioiIaNmLbyN05gAA\nAAC0ubS0NGVnZ2vYsGFatGiRYmJi9OWXX2ru3Lk6d+5co+ds3bpVly5danZxevHiRf3pT3+SJE2d\nOlULFixQz549tW7dOv3v//6vVX5qaqpee+01jRgxQk899ZR69OihVatWad++fT/5dbYmOnMAAACA\nA3NycmqXDVCaGnPq1KkaOHCgnJ2dzbHw8HDNnj1bb7/9tlasWGGRf/nyZW3atEkzZszQxo0bmzUH\nLy8vbdy4UX379jXHYmJi9NJLLykrK0uzZs1Sr169JElFRUXKyMjQpEmTtGjRIklSdHS0Fi9erOTk\nZIWFhdncpi505gAAAAC0ucGDB1sUcpLUu3dv+fn5KT8/3yo/JSVFffv21fjx45s9htFotCjkGowe\nPVqS9M0335hj2dnZqqurU2xsrEVubGysCgsLdfz48WaP21Yo5gAAAADYjMuXL8toNFrETp48qd27\nd2vhwoW3ZYzi4mJJshgnLy9P7u7u6tOnj0XuoEGDZDKZdPr06dsy9u1EMQcAAAA4uIZNUNry56fY\ns2ePioqKFB4ebhFPTEzUuHHjFBQUdMvvRW1trd5991317NlTgwYNMsdLSkrUpUsXq3xvb29J/1cA\n2hKKOQAAAADtLj8/X6+88oqCg4M1ceJEc3znzp06d+6c5s6de1vGWbdunc6fP6+nnnrK4r6+6upq\n3XXXXVb5rq6u5uO2hg1QAAAAAAdmq48m+LGSkhItX75cnp6eevbZZ83nXr16VampqZo2bZp8fHxu\neU7p6en68MMPFR8frwceeMDimJubm65du2Z1Tk1Njfm4raGYAwAAAHBLCgsLVVRUZBGrra1t1rkV\nFRVatmyZKioqlJiYKC8vL/Ox9PR01dbWKjw8XAUFBeaxJKm8vFwFBQXy8fGRi0vTZc2uXbv02muv\nKTY2VjNnzrQ67uXlpWPHjlnFG5ZXNiy3tCUUcwAAAABuSdeuXdW1a1eLWHl5ub788subnldTU6MV\nK1bowoULWr16tdXmI4WFhSovL1dcXJxF3GAwaPPmzXrrrbeUkpIif3//m46TnZ2tl19+WWPGjNHi\nxYsbzQkICNDOnTuVn59vMY8TJ07IYDAoICDgpmO0B4o5AAAAwIHZ6nPm6uvrtXLlSp08eVKrVq1q\ndHOTKVOmaNSoURaxK1euaPXq1YqKitKoUaPUs2dP87H8/Hy5u7urW7du5tgXX3yhVatWaciQIUpI\nSLjhfEaOHKmkpCRt375dTz31lDmemZkpHx8fBQcHN/ma2xrFHAAAAIA2l5SUpMOHDys0NFSlpaXa\ns2ePxfHIyEgFBARYdcQallv6+fkpNDTU4lhcXJyGDBmiNWvWSJK+++47JSQkyGAwaPTo0dq3b59F\nvr+/v/r37y/ph+7ilClTtGXLFtXW1mrgwIHKzs5WTk6O+Rq2hmIOAAAAcGC2ugHKmTNnZDAYdPjw\nYR0+fNjqeGRkZIuvfX3822+/VWVlpaQfHm9wvV/96lfmYk6S5s2bp86dOyszM1NZWVny9fVVQkKC\nIiIibvpa2gvFHAAAAIA2t3bt2p90Xo8ePbR3795Gj10fHzJkyA1zb2T69OmaPn36T5pbW6OYAwAA\nsGFVVVUqKSmRk5OTvL29G30OFoA7Ew8NBwAAsDEmk0n79+/Xo48+Kk9PT/Xu3Vs9e/bU3Xffrfnz\n5ze5QyDwYwaDwbwJSlv+2OI9Zo6GzhwAAIANKS0t1ZQpU7R37151795dUVFR6tq1q0wmk/7973/r\nnXfeUXLaFfqHAAAgAElEQVRysubMmaOkpCQ6dcAdjGIOAADARlRUVGjcuHE6efKk4uLiFBQUZNHd\nGDx4sMaNG6cjR47o9ddf1/fff6+0tLR22XYe9sNWN0DBraOYAwAAsBHLli1TTk6O5s2bJ19f30Zz\nnJ2dFRISok6dOmnz5s0KCwvTggUL2nimAGwBX+MAAADYgNLSUm3cuFFjxoy5YSH3Y/fdd5/uu+8+\nrVu3TiaTqQ1mCMDWUMwBAADYgDfffFM1NTV64IEHmn1OSEiIvvrqK+3fv7/1Jga717DMsj1+0Loo\n5gAAAGxAdna2/Pz8ZDQam31O//795enpqezs7FacGQBbxT1zAAAANqCsrEzu7u4tOsdgMMjDw0Pf\nf/99K80KjqDh0QTtMS5aF505AAAAG+Dp6amqqqoWnWMymVRZWSlPT89WmhUAW2aTnbnKykqlp6fr\n1KlTOnXqlMrKyrRs2TJNnDjRIu/FF19UVlaW1fl9+vTRG2+8YRX/4IMPlJGRoW+//VbdunXT5MmT\nNWnSJKu88vJybdiwQQcPHlRVVZWCgoK0YMECDRgwwCo3JydHycnJysvLU4cOHRQWFqY5c+bIw8PD\nIs9kMik9PV2ZmZkqLi6Wr6+vZs6cqYiIiBa+OwAAwBGFhoZq69atKisra3Zxdu7cOZWVlWnkyJGt\nPDsAtsgmi7nS0lJt2rRJ3bt3l7+/v7744osb5rq6uuq3v/2txS5OHTt2tMp77733tG7dOo0dO1aP\nPvqo/vWvf+mPf/yjqqurNW3aNHOeyWTS008/ra+//lrTpk1T586dtWPHDi1ZskTJycnq3bu3OTcv\nL09Lly5V37599cQTT6iwsFDvvPOOLly4oBdeeMFi/NTUVKWlpenhhx9WYGCgDh06pFWrVslgMCg8\nPPxW3i4AAOAAfv3rX+vpp5/WkSNHNG7cuGadc+jQIQUEBPDlMG6K58w5Lpss5nx8fLR161Z16dJF\nubm5N312irOzc5N/4dXU1Gjjxo0KCQnRM888I0mKjo5WfX29Nm3apJiYGHXq1EmStH//fp04cUIr\nV67U6NGjJUlhYWGaNWuW3njjDSUkJJivm5qaKk9PT61bt87cievevbvWrFmjo0ePatiwYZKkoqIi\nZWRkaNKkSVq0aJF5/MWLFys5OVlhYWH8xw4AwB3u7rvv1q9//Wu9+eabCgoKUq9evW6af/z4cf3r\nX//SK6+8wr8jgDuUTd4z5+Lioi5dujQ7v76+XlevXr3h8X/+858qKytTbGysRfyRRx5RZWWl/va3\nv5ljBw4ckJeXl7mQkySj0aiwsDAdPHhQtbW1kqSrV6/q6NGjmjBhgsWSyokTJ8rd3V379u0zx7Kz\ns1VXV2c1fmxsrAoLC3X8+PFmv1YAAOC4Xn75ZQ0cOFCvvfaacnNzG31+XH19vf7xj3/orbfeUmxs\nrJ544ol2mCnsiZOTU7v9oHXZZGeuJaqqqhQdHa3q6mp5enoqIiJCc+fOtSiwTp8+LUkaOHCgxbmB\ngYEyGAzKy8vT+PHjJf2wdLKxe+MGDRqkDz74QOfPn1e/fv109uxZ1dXVKTAw0CLPxcVFAQEBysvL\nM8fy8vLk7u6uPn36WF3TZDLp9OnTCg4OvrU3AgAA2L1OnTrp448/1qRJk/TnP/9ZvXr10ogRI9S1\na1eZTCb9+9//1j/+8Q+VlJTo17/+tVJSUvgHM3AHs+tiztvbW9OmTVNgYKDq6+t15MgR7dixQ2fP\nntXatWvNf7mVlJTIycnJ6rktLi4uMhqNKioqMseKi4t1//33NzpWw/F+/fqpuLhYBoNBXl5eVrle\nXl7Kyckx/15SUtJop/HH1wQAAJCkLl266OOPP9bevXv16quvKjMzU/X19ZIkd3d3zZgxQ0888YT5\ndg4Ady67LubmzJlj8Xt4eLh8fX21ceNGffLJJ+aNRaqrq+Xi0vhLdXV1VU1Njfn36upq3XXXXY3m\nmUwmVVdXS5L5HFdX10ZzG/KaumbDcQAAgAZOTk6KjIxUZGSkKioqVFhYKBcXF/n4+LT4WXQAG6A4\nLofryz/66KOSpKNHj5pjbm5u5nvdrldTU2NRkLm5uenatWuN5hkMBrm5uUn6v0Lsx4Xgj3Mb8pq6\nZsNxAACAxnTs2FF+fn7y9fWlkANgwa47c41xdXWV0WhUWVmZOebl5aX6+nqVlpZaLLWsra1VaWmp\nfHx8zDFvb+9Glz02xBqWRnp7e8tkMqmkpMQqt6SkxJzXMP6xY8eavOaNLFmyxGqJ6PTp0zV9+vSb\nngcAAIDbJy0tTWlpaRax0tLSdppNy9Alc0wOV8xVVlaqtLRUd999tzkWEBAgk8mk3NxcPfDAA+b4\nqVOnZDKZ5O/vb475+/tb3O/W4MSJE3Jzc9M999wjSerXr5+cnZ2Vm5ursWPHmvNqa2uVl5dn8ey4\ngIAA7dy5U/n5+RaboJw4cUIGg0EBAQE3fU1r167V0KFDW/AuAAAA4HZr7Mv0zz//nPsX0W7sdpll\nTU2NKisrreJ/+ctfJMmiaBs6dKg8PT21Y8cOi9z33ntP7u7uCgkJMcfGjh2ry5cv68CBA+ZYaWmp\nDhw4oNDQUPO9dx07dtSwYcO0Z88ei3lkZWWpqqpKYWFh5tjIkSPl7Oys7du3W4yfmZkpHx8fdrIE\nAAAA0GI225nbtm2b+YZfSTp06JD5z5MnT9b333+vuXPnKiIiwtztOnLkiI4cOaIHH3xQI0eONF/L\n1dVVs2fPVmJiop599lmNGDFCX375pfbu3as5c+aYHxgu/VDMbd26VS+99JLOnTsno9GoHTt2qL6+\nXnFxcRZzjI+P16JFi7R48WLFxMSosLBQGRkZGjFihIYPH27O69q1q6ZMmaItW7aotrZWAwcOVHZ2\ntnJycpSQkEDbGwAAAK2mvZ75xmMzWp/NFnNbtmzRpUuXJP2wxjc7O1vZ2dmSpMjISHXq1EkhISH6\n/PPPtXv3btXX16t37956/PHHNXXqVKvrxcbGysXFRRkZGTp8+LC6deumhQsXavLkyRZ5Tk5OeuGF\nF7RhwwZt27ZN1dXVGjRokJYvXy5fX1+L3AEDBujll19WSkqK1q9fLw8PD0VHR1vtsilJ8+bNU+fO\nnZWZmamsrCz5+voqISFBERERt+stAwAAAHAHsdli7vqbSxuzfPnyFl0zOjpa0dHRTeZ16tRJS5cu\n1dKlS5vMDQ4OVmJiYrPGZ9MSAAAAtDUeTeC46H0CAAAAgB2imAMAAAAAO2SzyywBAAAA3DqDwdAu\nm5GwzLL10ZkDAAAAADtEZw4AAABwYGyA4rjozAEAAACAHaKYAwAAAAA7xDJLAAAAwIE5OTm1ywYo\n7THmnYZ3GAAAAADsEJ05AAAAwIGxAYrjojMHAAAAAHaIYg4AAAAA7BDLLAEAAAAHx5JHx0RnDgAA\nAADsEJ05AAAAwIGxAYrjojMHAAAAAHaIYg4AAAAA7BDLLAEAAAAHxjJLx0VnDgAAAADsEJ05AAAA\nwIHRmXNcdOYAAAAAwA5RzAEAAACAHWKZJQAAAODAWGbpuOjMAQAAAIAdojMHAAAAODi6ZI6JzhwA\nAAAA2CGKOQAAAACwQyyzBAAAABwYG6A4LjpzAAAAAGCH6MwBAAAADszJyUlOTm3fw2mPMe80FHMA\nAAAA2lxubq527dqlY8eOqaCgQEajUUFBQYqPj5evr2+j59TV1Sk+Pl75+fmaP3++pk6d2uQ4n332\nmT7++GOdOnVK33zzjbp37663337bKq+goEAzZsywihsMBv3ud79TeHh4y19kK6OYAwAAANDm0tLS\ndPz4cY0dO1b9+/dXSUmJtm3bprlz5yopKUl+fn5W52zdulWXLl1q0f14e/fu1f79+zVgwAB17dq1\nyfxx48bpwQcftIjde++9zR6vLVHMAQAAAA7MVjdAmTp1qgYOHChnZ2dzLDw8XLNnz9bbb7+tFStW\nWORfvnxZmzZt0owZM7Rx48Zmz+Pxxx/X0qVL5ezsrBUrVujcuXM3zR8wYIDGjx/f7Ou3JxayAgAA\nAGhzgwcPtijkJKl3797y8/NTfn6+VX5KSor69u3b4kLLy8vLapymVFVVqba2tkXntAc6cwAAAICD\ns6fHBFy+fFn9+vWziJ08eVK7d+/Wn/70p1Yf/80339SGDRtkMBgUGBio+Ph4DR8+vNXH/SnozAEA\nAACwCXv27FFRUZHVZiOJiYkaN26cgoKCWm1sJycnjRgxQvPmzdPzzz+vhQsX6sqVK1q2bJn+/ve/\nt9q4t4LOHAAAAIB2l5+fr1deeUXBwcGaOHGiOb5z506dO3dOzz33XKuO361bN7344osWscjISMXF\nxWn9+vVWm6LYAjpzAAAAgANr2AClPX6aq6SkRMuXL5enp6eeffZZ87lXr15Vamqqpk2bJh8fn9Z6\ni27I09NTUVFROn/+vIqKitp8/KbQmQMAAABwS77++murXSJramqadW5FRYWWLVumiooKJSYmysvL\ny3wsPT1dtbW1Cg8PV0FBgSSpsLBQklReXq6CggL5+PjIxaX1yppu3bpJksrKytqloLwZijkAAADA\ngbXFown69++v/v37W8SKi4v1wQcf3PS8mpoarVixQhcuXNDq1avVp08fi+OFhYUqLy9XXFycRdxg\nMGjz5s166623lJKSIn9//9vyOhpz8eJFSZLRaGy1MX4qijkAAAAAba6+vl4rV67UyZMntWrVqkY3\nN5kyZYpGjRplEbty5YpWr16tqKgojRo1Sj179jQfy8/Pl7u7u7mb1hKlpaVWBVthYaF27dolf39/\ni46hraCYAwAAANDmkpKSdPjwYYWGhqq0tFR79uyxOB4ZGamAgAAFBARYxBuWW/r5+Sk0NNTiWFxc\nnIYMGaI1a9aYY2fPntWhQ4ckSRcuXFBFRYU2b94sSfL391dISIgkacOGDbp48aKGDh0qHx8fffvt\nt3r//fdVVVWlJ5988va++NuEYg4AAABwYG2xzPJG497MmTNnZDAYdPjwYR0+fNjqeGRkZIuv3Vj8\nq6++0uuvv24Ra/h9woQJ5mJuxIgRyszM1I4dO1ReXq5OnTppyJAheuyxx6wKSltBMQcAAACgza1d\nu/YnndejRw/t3bu30WONxaOiohQVFdXkdSMiIhQREfGT5tReKOYAAAAAB2arnTncOp4zBwAAAAB2\niGIOAAAAAOwQyywBAAAAB8eSR8dEZw4AAAAA7BCdOQAAAMCBsQGK46IzBwAAAAB2iGIOAAAAAOwQ\nyywBAAAAB8YyS8dFZw4AAAAA7BCdOQAAAMCB0ZlzXHTmAAAAAMAOUcwBAAAAgB2yyWWWlZWVSk9P\n16lTp3Tq1CmVlZVp2bJlmjhx4g3PqaurU3x8vPLz8zV//nxNnTrV4nhERESj5z3++OOaPn26Ray8\nvFwbNmzQwYMHVVVVpaCgIC1YsEADBgywOj8nJ0fJycnKy8tThw4dFBYWpjlz5sjDw8Miz2QyKT09\nXZmZmSouLpavr69mzpx5w3kBAAAAtwPLLB2XTRZzpaWl2rRpk7p37y5/f3998cUXTZ6zdetWXbp0\n6ab/0QwfPlwTJkywiF1foJlMJj399NP6+uuvNW3aNHXu3Fk7duzQkiVLlJycrN69e5tz8/LytHTp\nUvXt21dPPPGECgsL9c477+jChQt64YUXLK6bmpqqtLQ0PfzwwwoMDNShQ4e0atUqGQwGhYeHN+dt\nAQAAAAAzmyzmfHx8tHXrVnXp0kW5ublasGDBTfMvX76sTZs2acaMGdq4ceMN83x9fTV+/PibXmv/\n/v06ceKEVq5cqdGjR0uSwsLCNGvWLL3xxhtKSEgw56ampsrT01Pr1q0zd+K6d++uNWvW6OjRoxo2\nbJgkqaioSBkZGZo0aZIWLVokSYqOjtbixYuVnJyssLAwvrkAAABAq6Az57hs8p45FxcXdenSpdn5\nKSkp6tu3b5OFmiTV1NSopqbmhscPHDggLy8vcyEnSUajUWFhYTp48KBqa2slSVevXtXRo0c1YcIE\niyWVEydOlLu7u/bt22eOZWdnq66uTrGxsRZjxcbGqrCwUMePH2/2awUAAAAAyUaLuZY4efKkdu/e\nrYULFzaZm5WVpZ///OeKiopSXFyc9u7da5WTl5fX6L1xgwYNUnV1tc6fPy9JOnv2rOrq6hQYGGiR\n5+LiooCAAOXl5Vlc093dXX369LG6pslk0unTp5v1WgEAAACggU0us2yJxMREjRs3TkFBQSooKLhh\nXnBwsMLDw9WjRw8VFRVp+/btev7551VRUaFf/OIX5rzi4mLdf//9Vud7e3ubj/fr10/FxcUyGAzy\n8vKyyvXy8lJOTo7595KSkkY7jT++JgAAANBaWPLomOy6mNu5c6fOnTun5557rsncxMREi98feugh\nzZ07V3/+858VFRUlV1dXSVJ1dbXuuusuq/NdXV1lMplUXV0tSealmg3nXZ/bkNfUNRuOAwAAAEBL\n2O0yy6tXryo1NVXTpk2Tj49Pi893dnbWI488ovLycn311VfmuJubm65du2aVX1NTI4PBIDc3N0n/\nV4g1dv9dTU2NOa+pazYcBwAAAFpDwwYo7fGD1mW3nbn09HTV1tYqPDzcvLyysLBQ0g/PiSsoKJCP\nj49cXG78Ert16yZJKisrM8e8vb0bXfbYEGtYGunt7S2TyaSSkhKr3JKSEnOe9MOyy2PHjjV5zRtZ\nsmSJjEajRWz69OlWz8cDAABA60lLS1NaWppFrLS0tJ1mA9hxMVdYWKjy8nLFxcVZxA0GgzZv3qy3\n3npLKSkp8vf3v+E1Ll68KEkWhZK/v7/F/W4NTpw4ITc3N91zzz2SpH79+snZ2Vm5ubkaO3asOa+2\ntlZ5eXkWz44LCAjQzp07lZ+fb7EJyokTJ2QwGBQQEHDT17p27VoNHTr0pjkAAABoXY19mf7555+b\nH0cFtDW7LeamTJmiUaNGWcSuXLmi1atXKyoqSqNGjVLPnj0l/fCNyfWdratXr+rdd9+V0WjUwIED\nzfGxY8fq008/1YEDBzRmzBjz+QcOHFBoaKi509exY0cNGzZMe/bs0axZs8yPJ8jKylJVVZXCwsLM\n1xw5cqSSkpK0fft2PfXUU+Z4ZmamfHx8FBwcfPveGAAAAOBHeM6c47LZYm7btm2qqKgwL508dOiQ\n+c+TJ09WQECAVUerYbmln5+fQkNDzfHt27crOztbISEh6t69u4qKirRr1y5dunRJCQkJcnZ2NueO\nHTtWW7du1UsvvaRz587JaDRqx44dqq+vt+oCxsfHa9GiRVq8eLFiYmJUWFiojIwMjRgxQsOHDzfn\nde3aVVOmTNGWLVtUW1urgQMHKjs7Wzk5OUpISOA/dAAAAAAtZrPF3JYtW3Tp0iVJP1T12dnZys7O\nliRFRkaqQ4cOjZ7XWGEUHBys48ePa+fOnSotLZWHh4eCgoK0bNkyDRkyxCLXyclJL7zwgjZs2KBt\n27apurpagwYN0vLly+Xr62uRO2DAAL388stKSUnR+vXr5eHhoejoaM2ZM8dqDvPmzVPnzp2VmZmp\nrKws+fr6KiEhQRERET/p/QEAAACag86c47LZYu76m0ubo0ePHo0+CHzYsGEtWsvcqVMnLV26VEuX\nLm0yNzg42OqxBzfCpiUAAAAAbhe7fTQBAAAAANzJbLYzBwAAAODWsczScdGZAwAAAAA7RGcOAAAA\ncHB0yRwTnTkAAAAAsEMUcwAAAABgh1hmCQAAADgwNkBxXHTmAABtymQytfcUAABwCBRzAIBWVVZW\npvXr1+tnP/uZ3N3d5ezsLG9vb82ePVtHjx5t7+kBgMNr6My1xw9aF8ssAQCt5u2339b8+fNVUVGh\nn//855o6darc3Nx08eJFvfPOO3r99dcVGRmp9PR0eXl5tfd0AQCwKxRzAIBW8dprr2nu3Ll69NFH\n9T//8z/q1auXxfH//u//1q5du7RkyRKNGTNGn376qbp06dJOswUAwP6wzBIAcNt9/vnnmj9/vmbP\nnq2kpCSrQk6SnJ2dFR0drffff18XL15UfHx8O8wUABwfyywdF8UcAOC2W7dune655x794Q9/aPJ/\n5oGBgVq5cqW2b9+uM2fOtNEMAQCwfxRzAIDbqqioSO+8847i4uLk7OzcrHMmTZoko9Go9evXt/Ls\nAODOQ2fOcVHMAQBuq08//VQ1NTX65S9/2exzPDw8FB0drY8++qgVZwYAgGOhmAMA3FalpaWSJB8f\nnxad161bN125cqU1pgQAgENiN0sAwG3VoUMHSVJFRYXuvvvuZp9XUVGhjh07tta0AOCOxpJHx0Rn\nDgBwWw0ZMkSStGfPnmafU19fr48++kg/+9nPWmtaAAA4HIo5AMBtFRgYqHHjxun1119v9jmffPKJ\nzp49qwULFrTizADgzsQGKI6LYg4AcNstXLhQR44c0ZYtW5rMLSsr08qVK3X//fcrNDS0DWYHAIBj\n4J45AMBt98gjj+g3v/mNnnrqKVVXV+uxxx5r9BvagoICxcXFKT8/X9nZ2XyLCwBAC1DMAQBuO4PB\noJSUFLm4uGjJkiVKSkpSXFycRo0aJTc3N124cEFpaWl67733dPfdd+ujjz7Sfffd197TBgCH1F5L\nHvmCrvVRzAEAWoWLi4uSk5P12GOPKSkpSc8884xqa2vNx/39/fX73/9ev/nNb+Tl5dWOMwUAwD5R\nzAEAWo3BYNCYMWM0ZswYFRYW6uzZs6qqqpKXl5fuvfdeOTlx6zYAtDYnJ6d2+fuWv+NbH8UcAKBN\ndO3aVV27dm3vaQAA4DAolwEAAADADtGZAwAAABwcm5E4Joo5AAAAAG0uNzdXu3bt0rFjx1RQUCCj\n0aigoCDFx8fL19e30XPq6uoUHx+v/Px8zZ8/X1OnTm1ynM8++0wff/yxTp06pW+++Ubdu3fX22+/\n3WiuyWRSenq6MjMzVVxcLF9fX82cOVMRERG39FpbC8UcAAAA4MBs9dEEaWlpOn78uMaOHav+/fur\npKRE27Zt09y5c5WUlCQ/Pz+rc7Zu3apLly616PXs3btX+/fv14ABA5q8dzs1NVVpaWl6+OGHFRgY\nqEOHDmnVqlUyGAwKDw9v9phthXvmAAAAALS5qVOnKj09XU8++aQeeughPfbYY0pMTFRdXV2jnbPL\nly9r06ZNmjFjhkwmU7PHefzxx/X+++8rMTFR/fv3v2FeUVGRMjIyNGnSJC1ZskTR0dF6/vnndd99\n9yk5OblFY7YVijkAAAAAbW7w4MFydna2iPXu3Vt+fn7Kz8+3yk9JSVHfvn01fvz4Fo3j5eVlNU5j\nsrOzVVdXp9jYWIt4bGysCgsLdfz48RaN2xYo5gAAAAAH1rDMsj1+forLly/LaDRaxE6ePKndu3dr\n4cKFt+MtaVReXp7c3d3Vp08fi/igQYNkMpl0+vTpVhv7p6KYAwAAAGAT9uzZo6KiIqv70xITEzVu\n3DgFBQW12tglJSXq0qWLVdzb21uSVFxc3Gpj/1RsgAIAAAA4MFvdAOV6+fn5euWVVxQcHKyJEyea\n4zt37tS5c+f03HPP3e4pWqiurtZdd91lFXd1dTUftzUUcwAAAABuyfHjx3XixAmLWEuKn5KSEi1f\nvlyenp569tlnzYXg1atXlZqaqmnTpsnHx+e2zvl6bm5uunbtmlW8pqbGfNzWUMwBAAAAuCX33nuv\n7r33XotYQUGBXn/99SbPraio0LJly1RRUaHExER5eXmZj6Wnp6u2tlbh4eEqKCiQJBUWFkqSysvL\nVVBQIB8fH7m43HpZ4+XlpWPHjlnFG5ZXNiy3tCUUcwAAAIADs+VlljU1NVqxYoUuXLig1atXW20+\nUlhYqPLycsXFxVlde/PmzXrrrbeUkpIif3//W55vQECAdu7cqfz8fIt5nDhxQgaDQQEBAbc8xu1G\nMQcAAACgzdXX12vlypU6efKkVq1a1ejmJlOmTNGoUaMsYleuXNHq1asVFRWlUaNGqWfPnuZj+fn5\ncnd3V7du3Vo8n5EjRyopKUnbt2/XU089ZY5nZmbKx8dHwcHBLb5ma6OYAwAAABxce3TmmpKUlKTD\nhw8rNDRUpaWl2rNnj8XxyMhIBQQEWHXEGpZb+vn5KTQ01OJYXFychgwZojVr1phjZ8+e1aFDhyRJ\nFy5cUEVFhTZv3ixJ8vf3V0hIiCSpa9eumjJlirZs2aLa2loNHDhQ2dnZysnJUUJCgk2+hxRzAAAA\nANrcmTNnZDAYdPjwYR0+fNjqeGRk5A3PvVFh1Vj8q6++srp3r+H3CRMmmIs5SZo3b546d+6szMxM\nZWVlydfXVwkJCYqIiGjWa2prFHMAAAAA2tzatWt/0nk9evTQ3r17Gz3WWDwqKkpRUVHNvv706dM1\nffr0nzS3tkYxBwAAADgwW94ABbfGqb0nAAAAAABoOTpzAAAAgAOjM+e46MwBAAAAgB2imAMAAAAA\nO8QySwAAAMCBsczScdGZAwAAAAA7RGcOAAAAcGB05hzX/2fv3qOqrvL/j78OEBcVSUDRJMVAlGJ9\nNVEbb3HxmmjeRvPWaMJ4Tc35OZH6XaXfrCG/asY0ikZOpRMk46hhKZFRiFpjlvVFlDyZ0ZiOB1AC\nFBA4vz9cnOl0UAFF4fR8rMUK9n7v/fl8Tjbjm/f+7E1lDgAAAACaIJI5AAAAAGiCWGYJAAAA2DGD\nwSAHh9tfw2GZZcOjMgcAAAAATRCVOQAAAMCOsQGK/aIyBwAAAABNEMkcAAAAADRBLLMEAAAA7BjL\nLO1Xo0zmLl++rKSkJJ04cUInTpxQUVGRYmJiNHTo0GuOqaysVFRUlHJzczV79mxNmDDBJua9995T\ncnKyzp49qzZt2mjs2LEaM2aMTVxxcbHi4+N14MABlZaWKigoSHPmzFHnzp1tYrOysrRx40YZjUY1\na9ZMYWFhio6Olpubm1Wc2WxWUlKSUlJSlJ+fL19fX02ZMkURERH1+IQAAAAA/No1ymWWhYWF2rJl\ni+zMnQsAACAASURBVHJzc+Xv71+rrH779u06f/78NWPfffddrVmzRp06ddKCBQv0wAMP6M9//rOS\nkpKs4sxms5555hmlp6dr7Nixmj17ti5evKhFixbpzJkzVrFGo1GLFy9WeXm55s6dq8jISO3evVsr\nVqywuX5CQoJee+019erVSwsWLFDbtm21cuVKpaen1+GTAQAAAOqmujJ3J77QsBplZc7b21vbt29X\nq1atlJOTozlz5lw3/sKFC9qyZYsmT56szZs32/SXl5dr8+bN6tOnj5577jlJUmRkpKqqqrRlyxaN\nGDFCLVq0kCR9/PHHys7O1ooVKzRgwABJUlhYmB5//HG98cYbWrZsmWXehIQEubu7a926dZZKnI+P\nj9auXasjR44oJCREkpSXl6fk5GSNGTNG8+fPt1x/4cKF2rhxo8LCwvjDDgAAAKBOGmVlzsnJSa1a\ntap1/KZNm9SxY0cNGjSoxv4vv/xSRUVFGjVqlFX76NGjdfnyZX366aeWtoyMDHl6eloSOUny8PBQ\nWFiYDhw4oIqKCknSpUuXdOTIEQ0ZMsRqSeXQoUPl6upqVXHLzMxUZWWlzfVHjRolk8mkY8eO1fpZ\nAQAAAEBqpMlcXRw/flwffPCB5s2bd82YkydPSpK6dOli1R4YGCiDwSCj0WhpMxqNNb4b17VrV5WV\nlemHH36QJJ06dUqVlZUKDAy0inNyclJAQIDNnK6ururQoYPNnGaz2XJ/AAAAQENgiaV9avLJXFxc\nnAYOHKigoKBrxhQUFMjBwUEeHh5W7U5OTvLw8FBeXp6lLT8/X15eXjZzVLfl5+db/mkwGOTp6WkT\n6+npaYmrvn5NlcZfzgkAAAAAtdUo35mrrT179uj06dN6/vnnrxtXVlYmJ6eaH9XZ2Vnl5eVWsXfd\ndVeNcWazWWVlZZJkGePs7FxjbHXcjeas7gcAAAAaAkcT2K8mW5m7dOmSEhISNHHiRHl7e1831sXF\nxfKu2y+Vl5dbJWQuLi66cuVKjXEGg0EuLi6S/pOI/TwR/HlsddyN5qzuBwAAAIC6aLKVuaSkJFVU\nVCg8PFznzp2TJJlMJklXz4k7d+6cvL295eTkJE9PT1VVVamwsNBqqWVFRYUKCwutkkEvL68alz1W\nt1UvjfTy8pLZbFZBQYFNbEFBgdVSTU9PTx09evSGc17LokWLbJaITpo0SZMmTbruOAAAANw6iYmJ\nSkxMtGorLCy8Q3cDNOFkzmQyqbi4WNOnT7dqNxgM2rp1q/72t79p06ZN8vf3V0BAgMxms3JyctS7\nd29L7IkTJ2Q2m+Xv729p8/f3V1ZWls31srOz5eLionvvvVeS1KlTJzk6OionJ0ehoaGWuIqKChmN\nRoWHh1vaAgICtGfPHuXm5lptgpKdnS2DwaCAgIDrPuvLL7+sHj161O6DAQAAQIOo6ZfpX3zxheU4\nqsaKZZb2q8kmc+PGjVP//v2t2i5evKg1a9Zo2LBh6t+/v9q1aydJ6tGjh9zd3bVr1y6rZO7dd9+V\nq6ur+vTpY2kLDQ3V/v37lZGRoYcffljS1d+4ZGRkqG/fvpZ375o3b66QkBClpaXp8ccftxxPkJqa\nqtLSUoWFhVnm7Nevn9avX6+dO3dqwYIFlvaUlBR5e3srODj41n44AAAAABqVCxcuWFYUtm3btk5H\nsV1Lo03mduzYoZKSEsvSyYMHD1q+Hzt2rAICAmwqWtUfjp+fn/r27Wtpd3Z21owZMxQXF6fly5er\nV69e+vrrr7Vv3z5FR0dbDgyXriZz27dv16pVq3T69Gl5eHho165dqqqqsqkCRkVFaf78+Vq4cKFG\njBghk8mk5ORk9erVSz179rTEtW7dWuPGjdO2bdtUUVGhLl26KDMzU1lZWVq2bBm/tQAAAECDoTJ3\nZx05ckSbNm2yOrpMurp6b+bMmTdV2W20ydy2bdt0/vx5SVf/IGRmZiozM1OSNHjwYDVr1qzGcdf6\nQzNq1Cg5OTkpOTlZhw4dUps2bTRv3jyNHTvWKs7BwUGxsbGKj4/Xjh07VFZWpq5du2rJkiXy9fW1\niu3cubNWr16tTZs2acOGDXJzc1NkZKSio6Ntrj9r1iy1bNlSKSkpSk1Nla+vr5YtW6aIiIg6fzYA\nAAAAGr/9+/dr+fLl8vT01MSJEy35xA8//KC0tDTFxMToueee04ABA+o1f6NN5n75cmlttG3bVvv2\n7btmf2RkpCIjI284T4sWLbR48WItXrz4hrHBwcGKi4ur1f2xaQkAAADw6/H666+rU6dOiouLsylG\nTZkyRQsWLNDrr79e72SuyR5NAAAAAODGqpdZ3omvX7uzZ89q2LBhNa4qbN68uR555BHLq2L1QTIH\nAAAAAA2gQ4cOunjx4jX7L1y4YPMqV12QzAEAAAB2jqrcnTFr1iylpKRY9v74uf3792v37t2aM2dO\nvedvtO/MAQAAAEBTtmPHDnl4eOi5556Tl5eX2rdvL0k6c+aM8vPz5evrq3/84x/6xz/+YTXuhRde\nqNX8JHMAAAAA0AC+/fZbGQwGtWnTRtJ/jlJzdHRUmzZtVF5erlOnTlmNqUtVk2QOAAAAsGMODg5y\ncLj9b1fdiWs2NklJSQ06P58wAAAAADRBVOYAAAAAO3anNiRhE5T/qKioUF5enoqKimQ2m236AwMD\n6zUvyRwAAAAANIDi4mJt2LBBH374oSoqKmz6zWazDAaD9u3bV6/5SeYAAAAAoAHExsbq0KFDCg8P\nV1BQkJo3b35L5yeZAwAAAOwYyyzvnM8//1xjx47VvHnzGmR+NkABAAAAgAbQsmVL3XPPPQ02P8kc\nAAAAYOeqq3O38wvSiBEjlJ6erqqqqgaZn2WWAAAAANAAfve73+nKlSuaPXu2Bg8erNatW9d4/t7D\nDz9cr/lJ5gAAAACgAZhMJn355ZcyGo0yGo01xrCbJQAAAIAasQHKnbNq1Sp98803mjx5MrtZAgAA\nAEBTkZWVpUmTJumJJ55okPlJ5gAAAAA7RmXuzvH09JS7u3uDzV/v3SwvX74ss9l8zf6LFy/qq6++\nqu/0AAAAANCkjR8/Xu+//74uX77cIPPXuTK3d+9evfHGGzKZTHJxcVFoaKh+//vfy9PT0yru8OHD\nio2NrffLfAAAAADQlJWXl8vJyUlTpkxRWFiY2rRpY7ObpcFg0Pjx4+s1f52SuSNHjmjVqlXq0KGD\nfvvb3yo/P1/p6ek6ePCgVqxYoe7du9frJgAAAAA0DJZZ3jnx8fGW73fu3FljzG1L5rZu3arAwED9\n+c9/1l133SVJOnPmjJYvX66YmBg988wzCg8Pr9eNAAAAAIA9efvttxt0/jolc999951+97vfWRI5\nSWrfvr1effVV/c///I9WrlypixcvasyYMbf8RgEAAADUHZW5O6dt27YNOn+dNkCpqqqSo6OjTbuL\ni4uef/55DRkyRK+++qo2b958y24QAAAAAJqigQMH6sMPP7xm/0cffaSBAwfWe/46Vebat2+vrKws\njRo1yqbPwcFBMTEx8vDw0NatW+Xr61vvmwIAAABg33JycrR3714dPXpU586dk4eHh4KCghQVFXXN\nXKKyslJRUVHKzc3V7NmzNWHChFpdKysrSxs3bpTRaFSzZs0UFham6Ohoubm5WWLOnTunyZMn24w1\nGAz67//+73q9Tna93f+lq8Wym1GnZO43v/mNkpKS9NNPP6lly5Y1xsyePVt33323Nm3aRGkVAAAA\nuMMa6zLLxMREHTt2TKGhobrvvvtUUFCgHTt2aObMmVq/fr38/Pxsxmzfvl3nz5+v0/MYjUYtXrxY\nHTt21Ny5c2UymfTOO+/ozJkzio2NtYkfOHCgHnroIau2Bx54oNbX+6Vr3WtJSYkOHz4sDw+Pes9d\np2Ru+PDhatmypS5cuHDNZE6SJk6cqPbt2+vUqVP1vjEAAAAA9mvChAnq0qWL1Wtc4eHhmjFjht5+\n+20tXbrUKv7ChQvasmWLJk+eXKfXuhISEuTu7q5169ZZKnE+Pj5au3atjhw5opCQEKv4zp07a9Cg\nQfV+rjfffFNvvfWWpKuJ3IsvvqgXX3yxxliz2ayxY8fW+1p1SuZat25d681NBgwYoAEDBtTrpgAA\nAADcOo1xxdz9999v09a+fXv5+fkpNzfXpm/Tpk3q2LGjBg0aVOtk7tKlSzpy5IgmTJhgtaRy6NCh\nWr9+vdLT022SOUkqLS2Vk5OTnJzqfCy3unbtqlGjRslsNmvXrl0KCQnRvffeaxPn5uamwMDAm8qZ\n6n53NTh9+rT+/e9/S7qa5dZUEgUAAACAG7lw4YI6depk1Xb8+HF98MEHevXVV+s016lTp1RZWanA\nwECrdicnJwUEBMhoNNqMeeuttxQfHy+DwaDAwEBFRUWpZ8+etb7mQw89ZFmmWVpaqpEjR9aYuN4K\nN5XMZWZmasOGDTp37pxVe9u2bTV37lz169fvpm4OAAAAwK9HWlqa8vLyNGPGDKv2uLg4DRw4UEFB\nQTa5x/Xk5+fLYDDI09PTps/T01NZWVmWnx0cHNSrVy/1799f3t7eOnv2rJKTkxUTE6MXX3zR5j26\n2oiJialTfEFBgcaPH6///d//VY8ePW4YX+9k7tNPP9Vzzz2ntm3bKjo6Wh06dJAk5ebmavfu3Xr2\n2Wf1pz/9Sb17967vJQAAAADcJAcHBzk41OlEslt23brIzc3VK6+8ouDgYA0dOtTSvmfPHp0+fVrP\nP/98ne+hvLxckuTs7GzT5+zsrLKyMsvPbdq00UsvvWQVM3jwYE2fPl0bNmyoVzJXHzfaAfPn6p3M\nbdmyRf7+/nrllVes1p/269dPo0eP1oIFC/Tmm2+SzAEAAAB27vDhwzp8+LBV2+XLl2s9vqCgQEuW\nLJG7u7uWL19uecfv0qVLSkhI0MSJE+Xt7V3n+6pO4qqTup8rLy+Xi4vLdce7u7tr2LBhSkpKUl5e\nXr3uoSHVO5k7deqUoqKirBK5am5ubho6dKhef/31m7o5AAAAADfndhxN0Lt3b5siTm5u7jV3cfy5\nkpISxcTEqKSkRHFxcVZLIpOSklRRUaHw8HDL8kqTySRJKi4u1rlz5+Tt7X3NjUq8vLxkNptVUFBg\n01dQUCAvL68b3l+bNm0kSUVFRfaTzDk7O6uoqOia/UVFRTWWMwEAAABAulodW7p0qc6cOaM1a9ZY\nXt2qZjKZVFxcrOnTp1u1GwwGbd26VX/729+0adMm+fv71zh/p06d5OjoqJycHIWGhlraKyoqZDQa\na3UQ+I8//ihJN3UeXEOpdzL34IMPavv27erdu7fNIXrZ2dn6xz/+UaddXwAAAAD8elRVVWnFihU6\nfvy4Vq5cqaCgIJuYcePGqX///lZtFy9e1Jo1azRs2DD1799f7dq1s/Tl5ubK1dXVUk1r3ry5QkJC\nlJaWpscff9yyqjA1NVWlpaUKCwuzjC0sLLRJ2Ewmk/bu3St/f/8aN1G50+qdzM2aNUtff/21FixY\noK5du1rOTvjhhx904sQJ3X333Zo1a9Ytu1EAAAAAdXc7llle67rXs379eh06dEh9+/ZVYWGh0tLS\nrPoHDx6sgIAABQQEWLVXL7f08/NT3759rfqmT5+u7t27a+3atZa2qKgozZ8/XwsXLtSIESNkMpmU\nnJysXr16WRWf4uPj9eOPP6pHjx6W3Sx3796t0tJSPfnkk/X6DBpavZO5du3a6fXXX9fbb7+tzz77\nTOnp6ZKunjM3duxYTZ48Wa1atbplNwoAAADAfnz77bcyGAw6dOiQDh06ZNM/ePDga469VqJYU3vn\nzp21evVqbdq0SRs2bJCbm5siIyMVHR1tFderVy+lpKRo165dKi4uVosWLdS9e3dNnTrVJqFsLOqd\nzFVWVsrZ2Vnz5s3TvHnzbPpLSkpUWVkpR0fHm7pBAAAAADfnTlTmbuTll1+u17i2bdtq3759NfZd\nqz04OFhxcXHXnTciIkIRERH1uqdbxcXFRUOHDq31Riv1PnAiLi7uuuXG+fPna/369fWdHgAAAAB+\nVZo3b66YmBibjWCupd6VucOHD2vIkCHX7A8NDVVaWprmz59f30sAAAAAQJMVERFxw6qos7OzWrdu\nre7du+uxxx5T+/btaz1/vZO5Gx2a5+Xlpby8vPpODwAAAOAWcHBwkINDvRfk3dR1f+1+97vf6cCB\nAzp9+rR69+5tSdTOnDmjf/7zn+rUqZN69OihM2fOaO/evfroo4+0bt26Wr+jV+9kzsPDQz/88MM1\n+7///ns1a9asvtMDAAAAQJPm5eWlwsJCvfnmm7rnnnus+s6cOaOnnnpK9957r2bPnq1//etfmjdv\nnhISEhQbG1ur+eudLlfv9nLy5Embvm+++Ua7d+/WQw89VN/pAQAAANwC1UcT3ImvX7t33nlHo0eP\ntknkJKl9+/YaPXq0EhMTJUm+vr569NFHdezYsVrPX+/K3IwZM3T48GHNmTNHffv2lZ+fnyTp9OnT\nOnjwoFq1aqUZM2bUd3oAAAAAaNJMJtN1d/d3dHSUyWSy/Ny2bVtduXKl1vPXO5nz9vZWfHy8Nm3a\npAMHDigzM1OS1KxZMw0aNEjR0dG13lITAAAAAOyNn5+f3n33XQ0ePFienp5WfQUFBXr33XctRTFJ\n+vHHH23irqfeyZx0dQ3okiVLZDabdfHiRUnS3XffTUkVAAAAaCTu1JJHcgJpzpw5iomJ0dSpU9W/\nf3+rDVAyMzNVUVGhp59+WpJUXl6u1NRU9e7du9bz31QyV81gMKhVq1a3YioAAAAAsAvdu3fXq6++\nqjfeeEP79+9XWVmZpKvHEYSEhGjatGkKDAy0tP3973+v0/y3JJkDAAAA0HhRJbtzOnfurBdeeEFV\nVVVWqxlvxdENHP4AAAAAAA3g008/VWVlpaSr5+55enrK09Pzlp3BR2UOAAAAABrA0qVL5e7urgED\nBig8PFwPPvjgLT1MnWQOAAAAsGNsgHLnxMbGKj09XRkZGdqzZ488PDz08MMPKyIiQv/1X/910/OT\nzAEAAABAA+jdu7d69+6tiooKHT58WOnp6frwww+VkpIiT09PhYaGKjw8XA888EC95ieZAwAAAOyY\ng4PDLV3aV5fr4ionJyf16dNHffr00ZUrV/TZZ58pPT1d7733nnbs2KF9+/bVa14+YQAAAAC4TS5f\nvqyLFy/qwoULKi8vv6m5qMwBAAAAQAMqLi7W/v37lZ6erqNHj6qiokKdOnXSE088ofDw8HrPSzIH\nAAAA2DE2QLlzPvjgA3388cf6/PPPVVFRoQ4dOmjKlCkKDw9Xhw4dbnp+kjkAAAAAaACxsbFq166d\nJkyYoPDwcPn7+9/S+UnmAAAAADtHlezO2LBhg7p06dJg8zfKZO7y5ctKSkrSiRMndOLECRUVFSkm\nJkZDhw61invvvfeUlpam3NxcFRcXy9vbW926ddO0adPUtm1bq9iIiIgar/X73/9ekyZNsmorLi5W\nfHy8Dhw4oNLSUgUFBWnOnDnq3LmzzfisrCxt3LhRRqNRzZo1U1hYmKKjo+Xm5mYVZzablZSUpJSU\nFOXn58vX11dTpky55n0BAAAAaNoaMpGTGmkyV1hYqC1btsjHx0f+/v766quvaow7efKk2rVrp379\n+snd3V1nz57V7t279dlnnykhIUGenp5W8T179tSQIUOs2n6ZoJnNZj3zzDP67rvvNHHiRLVs2VK7\ndu3SokWLtHHjRrVv394SazQatXjxYnXs2FFz586VyWTSO++8ozNnzig2NtZq3oSEBCUmJmrkyJEK\nDAzUwYMHtXLlShkMhpt66REAAABA41VeXq5PPvlEJ0+eVElJiaqqqqz6DQaDnn766XrN3SiTOW9v\nb23fvl2tWrVSTk6O5syZU2PcU089ZdPWr18/zZ49W6mpqTYVN19fXw0aNOi61/7444+VnZ2tFStW\naMCAAZKksLAwPf7443rjjTe0bNkyS2xCQoLc3d21bt06SyXOx8dHa9eu1ZEjRxQSEiJJysvLU3Jy\nssaMGaP58+dLkiIjI7Vw4UJt3LhRYWFhlL4BAADQINgA5c45d+6c/vCHP+jcuXNq0aKFSkpK5O7u\nruLiYlVVVcnDw8NmRV9dNMpz5pycnNSqVat6jfXx8ZF0dalkTcrLy697nkNGRoY8PT0tiZwkeXh4\nKCwsTAcOHFBFRYUk6dKlSzpy5IiGDBli9S9g6NChcnV1VXp6uqUtMzNTlZWVGjVqlNW1Ro0aJZPJ\npGPHjtX9QQEAAAA0avHx8SopKdFf/vIXbdmyRWazWc8++6zef/99zZw5Uy4uLlq1alW952+UyVxd\n/fTTT7p48aJycnK0atUqGQwG9ejRwyYuNTVVjzzyiIYNG6bp06fXeNK60Wis8d24rl27qqysTD/8\n8IMk6dSpU6qsrFRgYKBVnJOTkwICAmQ0Gq3mdHV1tdl+tGvXrjKbzTp58mS9nhsAAAC4EQcHhzv2\n9Wv35ZdfatSoUQoKCrJUKs1ms5ydnTVx4kQ9+OCDevXVV+s9f6NcZllX48eP15UrVyRdraI9+eST\nliWO1YKDgxUeHq62bdsqLy9PO3fu1AsvvKCSkhI9+uijlrj8/Hx169bN5hpeXl6W/k6dOik/P18G\ng8HmvTxJ8vT0VFZWluXngoKCGiuNP58TAAAAgH0pKyuzrBxs3ry5DAaDSkpKLP0PPPCA4uPj6z2/\nXSRzL730ksrLy5Wbm6u0tDSVlpbaxMTFxVn9PHz4cM2cOVOvv/66hg0bJmdnZ0lXP/C77rrLZryz\ns7PMZrPKysokybJUs3rcL2Or4240Z3U/AAAAAPvSpk0b5eXlSZIcHR3l7e2t7OxsPfzww5Kk77//\nvsZ8orbsIpnr3r27JKl3797q27evZsyYITc3N40ePfqaYxwdHTV69GitW7dO33zzjYKDgyVJLi4u\nlirfz5WXl8tgMMjFxUXSfxKxmt6/Ky8vt8TdaM7q/utZtGiRPDw8rNomTZpks8ELAAAAGk5iYqIS\nExOt2goLC+/Q3dQeG6DcOQ8++KAOHDigadOmSbq6v8bbb79t2QAlLS3NZrf9urCLZO7n7rnnHgUE\nBOjDDz+8bjInXc2UJamoqMjS5uXlVeOyx+q26qWRXl5eMpvNKigosIktKCiwxElXl10ePXr0hnNe\ny8svv1zjO4AAAAC4fWr6ZfoXX3xh83oPUG3y5Mk6ceKEysvL5ezsrKlTpyo/P1+ffPKJHBwcNHDg\nQM2dO7fe89tdMiddrXjVVAn7pR9//FGSrKpe/v7+Vu+7VcvOzpaLi4vuvfdeSVKnTp3k6OionJwc\nhYaGWuIqKipkNBqtzo4LCAjQnj17lJuba7UJSnZ2tgwGgwICAur+kAAAAEAtUSW7M3x8fCzvzElX\nV/f98Y9/1B//+MdbMn+T3WKmsrKyxuMHjh8/rlOnTqlr166WtprK35cuXdLf//53eXh4WJ3MHhoa\nqgsXLigjI8NqfEZGhvr27Ssnp6v5b/PmzRUSEqK0tDRdvnzZEpuamqrS0lKFhYVZ2vr16ydHR0ft\n3LnT6h5SUlLk7e1tWeIJAAAAALXVaCtzO3bsUElJiUwmkyTp4MGDlu/Hjh2rqqoqTZgwQeHh4fLz\n85Orq6tOnTqlvXv3yt3dXVOnTrXMtXPnTmVmZqpPnz7y8fFRXl6e9u7dq/Pnz2vZsmVydHS0xIaG\nhmr79u1atWqVTp8+LQ8PD+3atUtVVVWaPn261T1GRUVp/vz5WrhwoUaMGCGTyaTk5GT16tVLPXv2\ntMS1bt1a48aN07Zt21RRUaEuXbooMzNTWVlZWrZsGb8pAQAAAFBnjTaZ27Ztm86fPy/palk4MzNT\nmZmZkqTBgwfLy8tLkZGROnr0qDIyMlRWViZvb28NGjRIU6dOtSpnBgcH69ixY9qzZ48KCwvl5uam\noKAgxcTEWDZPqebg4KDY2FjFx8drx44dKisrU9euXbVkyRL5+vpaxXbu3FmrV6/Wpk2btGHDBrm5\nuSkyMlLR0dE2zzNr1iy1bNlSKSkpSk1Nla+vr5YtW6aIiIhb/dEBAAAAFmyAYr8abTL3y52CajJv\n3rxazRUSElKnF1NbtGihxYsXa/HixTeMDQ4Otjn24FrYgRIAAADArdJokzkAAAAAN4/KnP1qshug\nAAAAAMCvGckcAAAAADRBLLMEAAAA7JiDg4McHG5/DedOXPPXhk8YAAAAAJogKnMAAACAnWMzEvtE\nZQ4AAAAAmiCSOQAAAABoglhmCQAAANgxzpmzX1TmAAAAAKAJojIHAAAA2DEqc/aLyhwAAAAANEEk\ncwAAAADQBLHMEgAAALBjDg4OcnC4/TWcO3HNXxs+YQAAAABogqjMAQAAAHaOzUjsE5U5AAAAAGiC\nSOYAAAAAoAlimSUAAABgxzhnzn6RzAEAAAC47XJycrR3714dPXpU586dk4eHh4KCghQVFSVfX98a\nx1RWVioqKkq5ubmaPXu2JkyYUKtrZWVlaePGjTIajWrWrJnCwsIUHR0tNzc3qziz2aykpCSlpKQo\nPz9fvr6+mjJliiIiIm76eRsCyRwAAABgxxprZS4xMVHHjh1TaGio7rvvPhUUFGjHjh2aOXOm1q9f\nLz8/P5sx27dv1/nz5+v0PEajUYsXL1bHjh01d+5cmUwmvfPOOzpz5oxiY2OtYhMSEpSYmKiRI0cq\nMDBQBw8e1MqVK2UwGBQeHl7ra94uJHMAAAAAbrsJEyaoS5cucnR0tLSFh4drxowZevvtt7V06VKr\n+AsXLmjLli2aPHmyNm/eXOvrJCQkyN3dXevWrbNU4nx8fLR27VodOXJEISEhkqS8vDwlJydrzJgx\nmj9/viQpMjJSCxcu1MaNGxUWFtbolo6yAQoAAACA2+7++++3SuQkqX379vLz81Nubq5N/KZNm9Sx\nY0cNGjSo1te4dOmSjhw5oiFDhlgtqRw6dKhcXV2Vnp5uacvMzFRlZaVGjRplNceoUaNkMpl0HtCg\n8wAAIABJREFU7NixWl/3diGZAwAAAOxY9TLLO/FVHxcuXJCHh4dV2/Hjx/XBBx9o3rx5dZrr1KlT\nqqysVGBgoFW7k5OTAgICZDQaLW1Go1Gurq7q0KGDVWzXrl1lNpt18uTJOj5JwyOZAwAAANAopKWl\nKS8vz+b9tLi4OA0cOFBBQUF1mi8/P18Gg0Genp42fZ6ensrPz7f8XFBQoFatWtnEeXl5WeZqbHhn\nDgAAALBjBoNBDg63v4ZT18pcbm6uXnnlFQUHB2vo0KGW9j179uj06dN6/vnn63wP5eXlkiRnZ2eb\nPmdnZ5WVlVl+Lisr01133VVjXHV/Y0NlDgAAAMAdVVBQoCVLlsjd3V3Lly+3JIKXLl1SQkKCJk6c\nKG9v7zrPW52IVSd1P1deXi4XFxfLzy4uLrpy5UqNcdX9jQ2VOQAAAAA3JT09XR9//LFVW0lJSa3G\nlpSUKCYmRiUlJYqLi7NaEpmUlKSKigqFh4fr3LlzkiSTySRJKi4u1rlz5+Tt7S0np5rTGi8vL5nN\nZhUUFNj0FRQUWJZQSleXXR49etQmrnp55c9jGwuSOQAAAMCO3Y5z5iIiImwO1j558qSefPLJ644r\nLy/X0qVLdebMGa1Zs8Zm8xGTyaTi4mJNnz7dqt1gMGjr1q3629/+pk2bNsnf37/G+Tt16iRHR0fl\n5OQoNDTU0l5RUSGj0Wj1bl5AQID27Nmj3Nxcq/vIzs6WwWBQQEDAdZ/lTiCZAwAAAHDbVVVVacWK\nFTp+/LhWrlxZ4+Ym48aNU//+/a3aLl68qDVr1mjYsGHq37+/2rVrZ+nLzc2Vq6ur2rRpI0lq3ry5\nQkJClJaWpscff9xyPEFqaqpKS0sVFhZmGduvXz+tX79eO3fu1IIFCyztKSkp8vb2VnBw8K18/FuC\nZA4AAACwY7ejMnet617P+vXrdejQIfXt21eFhYVKS0uz6h88eLACAgJsKmLVyy39/PzUt29fq77p\n06ere/fuWrt2raUtKipK8+fP18KFCzVixAiZTCYlJyerV69e6tmzpyWudevWGjdunLZt26aKigp1\n6dJFmZmZysrK0rJlyxrdgeESyRwAAACAO+Dbb7+VwWDQoUOHdOjQIZv+wYMHX3PstRKrmto7d+6s\n1atXa9OmTdqwYYPc3NwUGRmp6Ohom9hZs2apZcuWSklJUWpqqnx9fbVs2TKbJaSNBckcAAAAgNvu\n5Zdfrte4tm3bat++fTX2Xas9ODhYcXFxtZp/0qRJmjRpUr3u7XYjmQMAAADsWGNdZombxzlzAAAA\nANAEUZkDAAAA7JjBYJCDw+2v4VCZa3hU5gAAAACgCSKZAwAAAIAmiGWWAAAAgB1jAxT7RWUOAAAA\nAJogkjkAAAAAaIJI5gAAAACgCSKZAwAAAIAmiA1QAAAAADvGBij2i8ocAAAAADRBVOYAAAAAO0Zl\nzn5RmQMAAACAJohkDgAAAACaIJZZAgAAAHaMZZb2i8ocAAAAADRBVOYA2JW8vDz9+9//lqOjo9q1\naycPD487fUsAANxxVMnsE5U5AE1eRUWFduzYocGDB6t169YKDg5WUFCQvL299dhjj+mTTz6R2Wy+\n07cJAABwS5HMAWjSzp8/r/79+2vs2LEqLi7W5s2bdeDAAe3fv1+rV6/WV199pbCwMD322GO6fPny\nnb5dAACAW4ZllgCarIsXLyoiIkJ5eXnav3+/+vfvb9Xfv39/LViwQNu2bdMTTzyh3/72t9q1a5ec\nnPifPgDArwcboNgvKnMAmqz/9//+n86cOaP09HSbRK6awWDQY489pp07dyo1NVVxcXG3+S4BAAAa\nBskcgCYpPz9fb7/9tp555hkFBQXdMH7IkCGaNGmS/vKXv6iqquo23CEAAI1DdWXuTnyhYZHMAWiS\n3njjDVVVVWnGjBm1HjN37lydOnVKH3zwQQPeGQAAwO3RKF8cuXz5spKSknTixAmdOHFCRUVFiomJ\n0dChQ63i3nvvPaWlpSk3N1fFxcXy9vZWt27dNG3aNLVt29Zm3vfee0/Jyck6e/as2rRpo7Fjx2rM\nmDE2ccXFxYqPj9eBAwdUWlqqoKAgzZkzR507d7aJzcrK0saNG2U0GtWsWTOFhYUpOjpabm5uVnFm\ns1lJSUlKSUlRfn6+fH19NWXKFEVERNzkpwX8On322Wfq16+fWrduXesxv/nNb9SmTRv985//1LBh\nwxrw7gAAABpeo0zmCgsLtWXLFvn4+Mjf319fffVVjXEnT55Uu3bt1K9fP7m7u+vs2bPavXu3Pvvs\nMyUkJMjT09MS++6772rdunUKDQ3V+PHj9X//93/685//rLKyMk2cONESZzab9cwzz+i7777TxIkT\n1bJlS+3atUuLFi3Sxo0b1b59e0us0WjU4sWL1bFjR82dO1cmk0nvvPOOzpw5o9jYWKt7TUhIUGJi\nokaOHKnAwEAdPHhQK1eulMFgUHh4+C3+BAH7V1JSopYtW9ZpjMFgUMuWLVVUVNRAdwUAQOPDBij2\nq1Emc97e3tq+fbtatWqlnJwczZkzp8a4p556yqatX79+mj17tlJTUzVp0iRJUnl5uTZv3qw+ffro\nueeekyRFRkaqqqpKW7Zs0YgRI9SiRQtJ0scff6zs7GytWLFCAwYMkCSFhYXp8ccf1xtvvKFly5ZZ\nrpWQkCB3d3etW7fOUonz8fHR2rVrdeTIEYWEhEi6eohxcnKyxowZo/nz51uuv3DhQm3cuFFhYWH8\nYQfqqGXLlvrXv/5VpzFVVVW6cOECB4kDAAC70CjfmXNyclKrVq3qNdbHx0fS1aWS1b788ksVFRVp\n1KhRVrGjR4/W5cuX9emnn1raMjIy5OnpaUnkJMnDw0NhYWE6cOCAKioqJEmXLl3SkSNHNGTIEKsl\nlUOHDpWrq6vS09MtbZmZmaqsrLS5/qhRo2QymXTs2LF6PSvwaxYaGqqDBw/qhx9+qPWYjz76SPn5\n+QoNDW3AOwMAALg9GmUyV1c//fSTLl68qJycHK1atUoGg0E9evSw9J88eVKS1KVLF6txgYGBMhgM\nMhqNljaj0Vjju3Fdu3ZVWVmZ5S+Op06dUmVlpQIDA63inJycFBAQYDOnq6urOnToYDOn2Wy23B+A\n2psyZYqaN2+ujRs31nrMX/7yFwUHB1/zGAMAAICmpFEus6yr8ePH68qVK5KuVtGefPJJyxJHSSoo\nKJCDg4PN0ionJyd5eHgoLy/P0pafn69u3brZXMPLy8vS36lTJ+Xn58tgMFi9l1fN09NTWVlZVtev\nqdL48zkB1I27u7uio6O1Zs0aRUZGqk+fPteN37p1q3bu3KnXXnuNZc0AAMAu2EUy99JLL6m8vFy5\nublKS0tTaWmpVX9ZWZmcnGp+VGdnZ5WXl1vF3nXXXTXGmc1mlZWVSZJljLOzc42x1XE3mrO6H0Dd\nvfjii/r88881ZMgQvfbaaxo/frwcHR2tYi5fvqz169fr6aef1vTp0xUVFXWH7hYAgDuDDVDsl10k\nc927d5ck9e7dW3379tWMGTPk5uam0aNHS5JcXFws77r9Unl5uVVC5uLiYqny/TLOYDDIxcVF0n8S\nsZ8ngj+PrY670ZzV/dezaNEim6ripEmTLBu8AL9Wrq6u2rNnj6ZMmaJJkyYpJiZG0dHR6tKliyor\nK3XkyBH99a9/VUFBgZ566imtXr2a/2MBANRbYmKiEhMTrdoKCwvv0N0AdpLM/dw999yjgIAAffjh\nh5ZkztPTU1VVVSosLLRKiioqKlRYWChvb29Lm5eXV43LHqvbqpdGenl5yWw2q6CgwCa2oKDAEld9\n/aNHj95wzmt5+eWXrd4BBPAfzZs3186dO3X48GFt2LBBf/rTn3T58mVJV//be+KJJzR79mwFBATc\n4TsFADR1Nf0y/YsvvrB6vacxojJnv+xiA5RfKi8vV0lJieXngIAAmc1m5eTkWMWdOHFCZrNZ/v7+\nljZ/f/8aNyTJzs6Wi4uL7r33XklSp06d5OjoaDNnRUWFjEaj1V8cAwICVFZWptzcXJs5DQYDf8kE\nboFevXpp8+bNKi4u1oULF1RUVKS8vDytXr2a/8YAAIBdarLJXGVlpdXxA9WOHz+uU6dOqWvXrpa2\nHj16yN3dXbt27bKKfffdd+Xq6mq1cUJoaKguXLigjIwMS1thYaEyMjLUt29fy7t3zZs3V0hIiNLS\n0ixVAElKTU1VaWmpwsLCLG39+vWTo6Ojdu7caXX9lJQUeXt7Kzg4uH4fAgAbDg4Ouvvuu9WiRQt+\nIwgAAOxao11muWPHDpWUlMhkMkmSDh48aPl+7Nixqqqq0oQJExQeHi4/Pz+5urrq1KlT2rt3r9zd\n3TV16lTLXM7OzpoxY4bi4uK0fPly9erVS19//bX27dun6Ohoy4Hh0tVkbvv27Vq1apVOnz4tDw8P\n7dq1S1VVVZo+fbrVPUZFRWn+/PlauHChRowYIZPJpOTkZPXq1Us9e/a0xLVu3Vrjxo3Ttm3bVFFR\noS5duigzM1NZWVlatmwZf+EEAABAg+Lvm/ap0SZz27Zt0/nz5yVd/cOXmZmpzMxMSdLgwYPl5eWl\nyMhIHT16VBkZGSorK5O3t7cGDRqkqVOnWg4PrzZq1Cg5OTkpOTlZhw4dUps2bTRv3jyNHTvWKs7B\nwUGxsbGKj4/Xjh07VFZWpq5du2rJkiXy9fW1iu3cubNWr16tTZs2acOGDXJzc1NkZKSio6NtnmfW\nrFlq2bKlUlJSlJqaKl9fXy1btkwRERG38mMDAAAA8CvRaJO5X+4UVJN58+bVac7IyEhFRkbeMK5F\nixZavHixFi9efMPY4OBgxcXF1er67EAJAACA240NUOxXk31nDgAAAAB+zUjmAAAAAKAJarTLLAEA\nAADcPJZZ2i8qcwAAAADQBFGZAwAAAOwYlTn7RWUOAAAAAJogkjkAAAAAaIJYZgkAAADYMZZZ2i8q\ncwAAAADQBJHMAQAAAEATRDIHAAAAAE0QyRwAAAAANEFsgAIAAADYOTYjsU9U5gAAAACgCaIyBwAA\nANgxjiawX1TmAAAAAKAJojIHAAAA4LbLycnR3r17dfToUZ07d04eHh4KCgpSVFSUfH19LXHvvfee\n0tLSlJubq+LiYnl7e6tbt26aNm2a2rZte8PrVFZWauvWrfrggw9kMpnUunVrPfLII5o0aZIcHR0t\ncefOndPkyZNtxhsMBv33f/+3wsPDb82D30IkcwAAAIAda6zLLBMTE3Xs2DGFhobqvvvuU0FBgXbs\n2KGZM2dq/fr18vPzkySdPHlS7dq1U79+/eTu7q6zZ89q9+7d+uyzz5SQkCBPT8/rXmflypXKyMjQ\n8OHDFRgYqOzsbG3evFnnz5/XH/7wB5v4gQMH6qGHHrJqe+CBB+r28LcJyRwAAACA227ChAnq0qWL\nVXUsPDxcM2bM0Ntvv62lS5dKkp566imbsf369dPs2bOVmpqqSZMmXfMaOTk5+uSTTzRt2jRNmzZN\nkjRy5Eh5eHgoOTlZY8aMUadOnazGdO7cWYMGDboVj9jgeGcOAAAAsGPVlbk78XU9999/v1UiJ0nt\n27eXn5+fcnNzrzvWx8dHklRcXHzduK+//loGg8FmiWR4eLjMZrPS09NrHFdaWqqKiorrzt0YUJkD\nAAAA0GhcuHDBplomST/99JOqqqr073//W2+99ZYMBoN69Ohx3bmuXLkiSXJ2drZqd3V1lSR98803\nNmPeeustxcfHy2AwKDAwUFFRUerZs2d9H6dBkcwBAAAAaBTS0tKUl5enGTNm2PSNHz/ekpx5eHjo\nySefVEhIyHXnu/fee2U2m5WVlWW1WcpXX30lSTKZTJY2BwcH9erVS/3795e3t7fOnj2r5ORkxcTE\n6MUXX7R5j64xIJkDAAAA7Fhj3QDll3Jzc/XKK68oODhYQ4cOtel/6aWXVF5ertzcXKWlpam0tPSG\ncz700EPy8fFRfHy8XFxcrDZAcXJyUnl5uSW2TZs2eumll6zGDx48WNOnT9eGDRtI5gAAAADglwoK\nCrRkyRK5u7tr+fLlNSaC3bt3lyT17t1bffv21YwZM+Tm5qbRo0dfc15nZ2fFxsZqxYoVWr58ucxm\ns5ydnTVr1ixt2bJFbm5u170vd3d3DRs2TElJScrLy5O3t/fNPegtRjIHAAAA2LmGrsy9//772rNn\nj1XbjTYnqVZSUqKYmBiVlJQoLi7uhkcNSNI999yjgIAAffjhh9dN5iSpY8eO2rx5s77//nsVFRXJ\nz89Pzs7OevXVVy0J4vW0adNGklRUVEQyBwAAAMC+DB8+XMOHD7dqy87O1sSJE687rry8XEuXLtWZ\nM2e0Zs0adejQodbXLC8vt7xDVxsdO3a0fP/pp5/KbDbf8J07Sfrxxx8lXX1Pr7HhaAIAAAAAt11V\nVZVWrFih48ePa/ny5QoKCrKJqaysrLHCd/z4cZ06dUpdu3a1as/NzdX58+eve92ysjJt3rxZXl5e\nioiIsLQXFhbaxJpMJu3du1f+/v61qhjeblTmAAAAADvWWDdAWb9+vQ4dOqS+ffuqsLBQaWlpVv2D\nBw/W5cuXNWHCBIWHh8vPz0+urq46deqU9u7dK3d3d02dOtVqzPTp09W9e3etXbvW0rZixQp5e3ur\nY8eOunTpkt5//32dO3dOsbGxVu/MxcfH68cff1SPHj0su1nu3r1bpaWlevLJJ2/BJ3LrkcwBAAAA\nuO2+/fZbGQwGHTp0SIcOHbLpHzx4sFxdXRUZGamjR48qIyNDZWVl8vb21qBBgzR16lTL4eHVakog\nu3btqj179mj37t1ydnZWt27d9Oyzz+q+++6ziuvVq5dSUlK0a9cuFRcXq0WLFurevbumTp2qgICA\nW/vwtwjJHAAAAGDHGmtl7uWXX77hHE5OTpo3b16tr7lv3z6btscee0yPPfbYDcdGRERYLbtsCnhn\nDgAAAACaIJI5AAAAAGiCSOYAAAAAoAkimQMAAACAJogNUAAAAAA71lg3QMHNozIHAAAAAE0QyRwA\nAAAANEEsswQAAADsGMss7ReVOQAAAABogqjMAQAAAHaOKpl9ojIHAAAAAE0QyRwAAAAANEEsswQA\nAADsGBug2C8qcwAAAADQBFGZAwAAAOwYlTn7RWUOAAAAAJogkjkAAAAAaIJYZgkAAADYMZZZ2i8q\ncwAAAADQBJHMAQAAAEATRDIHAAAAAE0QyRwAAAAANEFsgAIAAADYMTZAsV9U5gAAAACgCaIyBwAA\nANg5qmT2icocAAAAADRBJHMAAAAA0AQ1ymWWly9fVlJSkk6cOKETJ06oqKhIMTExGjp0qCXGbDYr\nNTVV+/fvl9Fo1E8//aR27dopIiJCEyZMkLOzs9WcERERNV7r97//vSZNmmTVVlxcrPj4eB04cECl\npaUKCgrSnDlz1LlzZ5vxWVlZ2rhxo4xGo5o1a6awsDBFR0fLzc3NKs5sNispKUkpKSnKz8+Xr6+v\npkyZcs37AgAAAIDraZTJXGFhobZs2SIfHx/5+/vrq6++sokpLS3VqlWrdP/99+vRRx/V3Xffrezs\nbP31r3/VF198obVr19qM6dmzp4YMGWLV9ssEzWw265lnntF3332niRMnqmXLltq1a5cWLVqkjRs3\nqn379pZYo9GoxYsXq2PHjpo7d65MJpPeeecdnTlzRrGxsVbzJiQkKDExUSNHjlRgYKAOHjyolStX\nymAwKDw8/GY+LgAAAAC/Qo0ymfP29tb27dvVqlUr5eTkaM6cOTYxd911l1599VXdf//9lrbIyEj5\n+PjozTff1BdffKEePXpYjfH19dWgQYOue+2PP/5Y2dnZWrFihQYMGCBJCgsL0+OPP6433nhDy5Yt\ns8QmJCTI3d1d69ats1TifHx8tHbtWh05ckQhISGSpLy8PCUnJ2vMmDGaP3++5V4XLlyojRs3Kiws\njJdSAQAA0CA4msB+Ncp35pycnNSqVasbxvw8kas2YMAAmc1mff/99zWOKy8vV3l5+TXnzcjIkKen\npyWRkyQPDw+FhYXpwIEDqqiokCRdunRJR44c0ZAhQ6yWVA4dOlSurq5KT0+3tGVmZqqyslKjRo2y\nutaoUaNkMpl07Nix6z4rAAAAAPxSo0zmbkZ+fr6kqwnYL6WmpuqRRx7RsGHDNH36dO3bt88mxmg0\n1vhuXNeuXVVWVqYffvhBknTq1ClVVlYqMDDQKs7JyUkBAQEyGo1Wc7q6uqpDhw42c5rNZp08ebLu\nDwoAAADgV61RLrO8GUlJSWrevLkeeughq/bg4GCFh4erbdu2ysvL086dO/XCCy+opKREjz76qCUu\nPz9f3bp1s5nXy8vL0t+pUyfl5+fLYDDI09PTJtbT01NZWVmWnwsKCmqsNP58TgAAAKAhsMzSftlV\nMrd161Z9+eWXeuqpp9S8eXOrvri4OKufhw8frpkzZ+r111/XsGHDLLtflpWV6a677rKZ29nZWWaz\nWWVlZZJkWar5y10zq9uq4240Z3U/AAAAANSF3SRzH330kf76179q+PDhGjly5A3jHR0dNXr0aK1b\nt07ffPONgoODJUkuLi66cuWKTXx5ebkMBoNcXFwk/ScRq+n9u/Lyckvcjeas7r+eRYsW2SwbnTRp\nks2RCgAAAGg4iYmJSkxMtGorLCy8Q3dTe1Tm7JddJHOff/65YmNj1adPHy1atKjW49q0aSNJKioq\nsrR5eXnVuOyxuq16aaSXl5fMZrMKCgpsYgsKCixx0tVll0ePHr3hnNfy8ssv2+zMCQAAgNurpl+m\nf/HFF5YdzIHbrclvgJKdna1nn31WQUFBevbZZ+XgUPtH+vHHHyVZb5bi7+9f44Yk2dnZcnFx0b33\n3itJ6tSpkxwdHZWTk2MVV1FRIaPRqICAAEtbQECAysrKlJubazOnwWCwigUAAACA2mjSydz333+v\npUuXql27dnrhhRdqfH9Nqrn8fenSJf3973+Xh4eHunTpYmkPDQ3VhQsXlJGRYTU+IyNDffv2lZPT\n1WJm8+bNFRISorS0NF2+fNkSm5qaqtLSUoWFhVna+vXrJ0dHR+3cudPqHlJSUuTt7W1Z4gkAAAAA\ntdVol1nu2LFDJSUlMplMkqSDBw9avh87dqwMBoOefvppFRcXa+LEiTp06JDV+Pbt21vOodu5c6cy\nMzPVp08f+fj4KC8vT3v37tX58+e1bNkyOTo6WsaFhoZq+/btWrVqlU6fPi0PDw/t2rVLVVVVmj59\nutU1oqKiNH/+fC1cuFAjRoyQyWRScnKyevXqpZ49e1riWrdurXHjxmnbtm2qqKhQly5dlJmZqays\nLC1btoz1xAAAAADqrNEmc9u2bdP58+clXX15MjMzU5mZmZKkwYMHy2w2Ky8vT5L02muv2YwfMmSI\nJZkLDg7WsWPHtGfPHhUWFsrNzU1BQUGKiYlR9+7drcY5ODgoNjZW8fHx2rFjh8rKytS1a1ctWbJE\nvr6+VrGdO3fW6tWrtWnTJm3YsEFubm6KjIxUdHS0zf3MmjVLLVu2VEpKilJTU+Xr66tly5YpIiLi\n5j8sAAAA4BrYAMV+Ndpk7pc7BdWkpkO/axISElKnF1NbtGihxYsXa/HixTeMDQ4Otjn24FrYgRIA\nAADArdKk35kDAAAAgF+rRluZAwAAAHBrsOTRPlGZAwAAAIAmiGQOAAAAAJogkjkAAAAAaIJI5gAA\nAACgCWIDFAAAAMCOcc6c/aIyBwAAAABNEJU5AAAAwI5RmbNfVOYAAAAAoAkimQMAAACAJohllgAA\nAIAdY5ml/aIyBwAAAABNEJU5AAAAALddTk6O9u7dq6NHj+rcuXPy8PBQUFCQoqKi5Ovra4l77733\nlJaWptzcXBUXF8vb21vdunXTtGnT1LZt2xtep7KyUlu3btUHH3wgk8mk1q1b65FHHtGkSZPk6Oho\nFWs2m5WUlKSUlBTl5+fL19dXU6ZMUURExC1//luBZA4AAADAbZeYmKhjx44pNDRU9913nwoKCrRj\nxw7NnDlT69evl5+fnyTp5MmTateunfr16yd3d3edPXtWu3fv1meffaaEhAR5enpe9zorV65URkaG\nhg8frsDAQGVnZ2vz5s06f/68/vCHP1jFJiQkKDExUSNHjlRgYKAOHjyolStXymAwKDw8/P+3d+9h\nUVf7HsffA8hFxVFAUMELQihqyfZSiRVqoiYWqeUltQxNM2/R6dmWdEo71dH2LsvcXvLSRROvxwx3\nQaKWadZTGrkVRUmN0lQuioDcmfOHm9lOg4qlzAx8Xs/j88j6rbV+39+Ml/nOWr/v72a9FH+YkjkR\nEREREalxw4YNo127dharY7179yYmJobVq1czc+ZMAJ5++mmrsT179uTJJ58kKSmJkSNHXvEcaWlp\nfPnllzz22GM89thjANx///0YjUbWr1/P4MGDCQwMBCArK8vcNnXqVACioqKYPn06S5YsoVevXnZ3\nH6DumRMRERERqcUqC6DY4tfVdOjQwWqbo7+/P23atCEjI+OqY/38/ADIz8+/ar/9+/dXuarWu3dv\nTCYTO3bsMLft2rWL8vJyoqOjLfpGR0eTmZnJwYMHr3ouW1AyJyIiIiIiduPcuXMYjUar9gsXLnD+\n/HnS0tJ4/fXXMRgMdOnS5apzlZaWAuDq6mrR7u7uDsCRI0fMbenp6bi7u9OqVSuLvu3bt8dkMnH0\n6NE/dD03k7ZZioiIiIjUcva2PfBKtm7dSlZWFjExMVbHHn74YXNyZjQamTJlCl27dr3qfC1btsRk\nMnHgwAGLYik//vgjAJmZmea2nJwcmjRpYjWHt7c3ANnZ2dd/QTeZkjkREREREbG5jIwM3n77bTp1\n6kT//v2tjs+dO5eSkhIyMjLYunUrRUVF15zzjjvuwM/Pj8WLF+Pm5mZRAMXFxYWSkhJz3+LiYurV\nq2c1R+WqXnFx8Z+4uptDyZyIiIiIiNhUTk4Ozz//PJ6ensyaNavKlcSwsDAAbr/9dsJFkLxWAAAg\nAElEQVTDw4mJicHDw4MHH3zwivO6uroyZ84cZs+ezaxZszCZTLi6ujJx4kRWrlyJh4eHua+bm5t5\n5e9ylQmfm5vbn73MG07JnIiIiIhILVadYiR/1qZNm/j4448t2i5cuFCtsQUFBcyYMYOCggLmz59/\nzUcNALRo0YLg4GCSk5OvmswBtG7dmhUrVvDzzz+Tl5dHmzZtcHV1ZcGCBeYEEcDLy4uUlBSr8ZXb\nKyu3W9oTJXMiIiIiIvKnDB48mMGDB1u07d+/v8rtkpcrKSlh5syZnDx5kjfeeMOq+Mi1xla1knYl\nrVu3Nv/+m2++wWQyWdxzFxwczGeffUZGRoZFHKmpqRgMBoKDg6t9rpqiapYiIiIiIlLjKioqmD17\nNocOHWLWrFmEhoZa9SkvL6/y8QOHDh3i2LFjtG/f3qI9IyODs2fPXvW8xcXFrFixAm9vb/r06WNu\n79mzJ87OzlYrjAkJCfj4+NCpU6frubwaoZU5ERERERGpcQsXLmTPnj2Eh4eTm5vL1q1bLY5HRkZS\nWFjIsGHD6N27N23atMHd3Z1jx46RmJiIp6cno0ePthgzduxYwsLCePPNN81ts2fPxsfHh9atW3Px\n4kU+/fRTTp8+zZw5cyzumWvatClDhw5l3bp1lJWV0a5dO3bt2sWBAweIi4uzy4qgSuZERERERKTG\n/fTTTxgMBvbs2cOePXusjkdGRuLu7k5UVBQpKSns3LmT4uJifHx86Nu3L6NHjzY/PLxSVQlX+/bt\n+eyzz9iyZQuurq507tyZF198kbZt21r1nThxIo0aNSIhIYGkpCQCAgKIi4uzWMGzJ0rmRERERERq\nsZoogHKl817NvHnzrjmHi4sLkydPrvY5t23bZtU2fPhwhg8fXu05Ro4cyciRI6vd35Z0z5yIiIiI\niIgD0sqciIiIiEgtZq8rc/LnaWVORERERETEASmZExERERERcUBK5kRERERERByQkjkREREREREH\npAIoIiIiIiK1mAqg1F5amRMREREREXFASuZEREREREQckLZZioiIiIjUctryWDtpZU5ERERERMQB\naWVORERERKQWUwGU2ksrcyIiIiIiIg5IyZyIiIiIiIgDUjInIiIiIiLigJTMiYiIiIiIOCAVQBER\nERERqcVUAKX20sqciIiIiIiIA1IyJyIiIiIi4oC0zVJEREREpBbTNsvaSytzIiIiIiIiDkgrcyLX\nae/evWzfvp0LFy7QoEEDunXrRp8+fXBy0ncjIiIiIlJzlMyJVIPJZGLt2rX87W9/Y9++fTg7O+Pk\n5ERFRQXl5eUEBgYyffp0Jk+ejIuL/lqJiIiIyM2npQSRazCZTEybNo2RI0eSkpICQHl5OaWlpZSX\nlwNw4sQJYmNjeeCBBygsLLRluCIiIiJSRyiZE7mGl156iQULFgBQUVFRZR+TyYTJZCIpKYlRo0Zh\nMplqMkQRERGRK6osgGKLX3JzKZkTuYpffvmFV155pdr9Kyoq2LRpEzt27LiJUYmIiIiIKJkTuap3\n3333ugubuLi4mFfyREREROyBVuVqJyVzIlexdOlS831x1VVWVsbmzZvJzs6+SVGJiIiIiCiZE7mi\n0tJSzpw584fGVlRUcPLkyRsckYiIiIjIfyiZE7mCsrIym44XEREREbkau3wgVmFhIWvWrOHw4cMc\nPnyYvLw8ZsyYQf/+/c19KisHfvXVV6Snp3PhwgWaN29Onz59GDZsGK6urlbz/vOf/2T9+vX89ttv\n+Pr6MmTIEAYPHmzVLz8/n8WLF7N7926KiooIDQ1l0qRJ3HLLLVZ9Dxw4wJIlS0hPT6d+/fr06tWL\n8ePH4+HhYdHPZDKxZs0aEhISyM7OJiAggFGjRtGnT58b8IrJzeDh4UGDBg0oKCj4Q+N9fX1vcEQi\nIiIiIv9hlytzubm5rFy5koyMDIKCgqq8gbKoqIjXX3+d3NxcHnjgAaZMmUJoaCjvvfcezz33nFX/\nTz75hDfeeIPAwECmTZtGx44deeedd1izZo1FP5PJxHPPPceOHTsYMmQITz75JOfPnyc2NtZq21x6\nejrPPvssJSUlPPXUU0RFRbFlyxZmz55tdf5ly5axdOlSunfvzrRp02jWrBmvvPKKqh7auZEjR173\nQ8CdnJy48847CQgIuElRiYiIiFSfHk1Qe9nlypyPjw8bN26kSZMmpKWlMWnSJKs+9erVY8GCBXTo\n0MHcFhUVhZ+fHx988AH79u2jS5cuAJSUlLBixQp69OjBSy+9ZO5bUVHBypUrGTRoEA0bNgTgiy++\nIDU1ldmzZ3P33XcD0KtXL8aMGcP7779PXFyc+XzLli3D09OTt956y7wS5+fnx5tvvsnevXvp2rUr\nAFlZWaxfv57BgwczdepU8/mnT5/OkiVL6NWrl/6w26nJkyezbNmy6xpTUVFhfp9FRERERG4Wu1yZ\nc3FxoUmTJtfsc3kiV+nuu+/GZDLx888/m9t++OEH8vLyiI6Otuj74IMPUlhYyDfffGNu27lzJ15e\nXuZEDsBoNNKrVy92795tvg/q4sWL7N27l379+llsqezfvz/u7u4WK267du2ivLzc6vzR0dFkZmZy\n8ODBq16r2E5YWBjR0dE4OztXq3/ln8uhQ4fe5MhEREREpK6zy2Tuz6gsB280Gs1tR48eBaBdu3YW\nfUNCQjAYDKSnp5vb0tPTq7w3rn379hQXF/PLL78AcOzYMcrLywkJCbHo5+LiQnBwsNWc7u7utGrV\nympOk8lkjk/s00cffcTtt99+zefNOTs74+/vT1JSEm5ubjUUnYiIiIjUVbUumVuzZg0NGjTgjjvu\nMLfl5OTg5ORkkeDBpcTLaDSSlZVlbsvOzsbb29tq3sq2ymQxOzsbg8GAl5eXVV8vLy+LZ4zl5ORU\nudL4+znFPjVo0IDt27czZcoU3N3drfaAOzk54ezszNChQ/nuu+90r5yIiIiI1Ai7vGfuj1q1ahU/\n/PADTz/9NA0aNDC3FxcXX7GIhaurKyUlJRZ969WrV2U/k8lEcXExgHlMVVUzXV1dzf2uNWflcbFv\n7u7uvP3227z88susXLmS7du3c+7cORo1akS3bt0YP348zZs3t3WYIiIiIlZsVYxENSFuvlqTzG3f\nvp333nuPgQMHcv/991scc3Nzu+Izv0pKSiwSMjc3N0pLS6vsZzAYzNvnKsdcnghe3vfybXZXm7Py\n+NXExsZarSqOHDmSkSNHXnWc3HhGo5EpU6YwZcoUW4ciIiIiNSw+Pp74+HiLttzcXBtFI1JLkrnv\nv/+eOXPm0KNHD2JjY62Oe3l5UVFRQW5urkVSVFZWRm5uLj4+PuY2b2/vKrc9VrZVbo309vbGZDKR\nk5Nj1TcnJ8diq6aXlxcpKSnXnPNK5s2bZ67MKSIiIiK2UdWX6fv27TNXMBepaQ5/z1xqaiovvvgi\noaGhvPjii1UWqQgODsZkMpGWlmbRfvjwYUwmE0FBQea2oKCgKguSpKam4ubmRsuWLQEIDAzE2dnZ\nas6ysjLS09MJDg62OH9xcTEZGRlWcxoMBou+IiIiIiIi1eHQydzPP//MzJkzad68Oa+++mqV968B\ndOnSBU9PTzZv3mzR/sknn+Du7k6PHj3MbREREZw7d46dO3ea23Jzc9m5cyfh4eHme+8aNGhA165d\n2bp1K4WFhea+SUlJFBUV0atXL3Nbz549cXZ25uOPP7Y4f0JCAj4+PnTq1OkPvwYiIiIiIlI32e02\ny02bNlFQUEBmZiYAX3/9tfn3Q4YMwWAw8Ne//pX8/HxGjBjBnj17LMb7+/ubn0Pn6upKTEwM8+fP\nZ9asWXTv3p39+/ezbds2xo8fb35gOFxK5jZu3Mjrr7/OiRMnMBqNbN68mYqKCsaOHWtxjnHjxjF1\n6lSmT5/OoEGDyMzMZP369XTv3p1u3bqZ+zVt2pShQ4eybt06ysrKaNeuHbt27eLAgQPExcXp5lAR\nERERuWlUAKX2sttkbt26dZw9exa49Adh165d7Nq1C4DIyEhMJpP5kQJLly61Gt+vXz+Lh4pHR0fj\n4uLC+vXr2bNnD76+vkyePJkhQ4ZYjHNycmLOnDksXryYTZs2UVxcTPv27Xn++eetSs7fcsst/P3v\nf+fdd99l0aJFeHh4EBUVxfjx463imThxIo0aNSIhIYGkpCQCAgKIi4ujT58+f+6FEhERERGROslu\nk7nfVwqqyrZt265rzqioKKKioq7Zr2HDhjz77LM8++yz1+zbqVMn5s+fX63zqwKliIiIiIjcKA59\nz5yIiIiIiEhdpWRORERERETEAdntNksREREREfnzVACl9tLKnIiIiIiIiANSMiciIiIiIuKAlMyJ\niIiIiIg4ICVzIiIiIiIiDkgFUEREREREajkVI6mdtDInIiIiIiLigJTMiYiIiIiIOCBtsxQRERER\nkRqXlpZGYmIiKSkpnD59GqPRSGhoKOPGjSMgIMDc75///Cdbt24lIyOD/Px8fHx86Ny5M4899hjN\nmjW75nlMJhMJCQkkJCRw8uRJ3N3dCQkJYcyYMXTs2NHc7/Tp0zzyyCNW4w0GAy+88AK9e/e+MRd+\nAymZExERERGRGhcfH8/BgweJiIigbdu25OTksGnTJiZMmMDChQtp06YNAEePHqV58+b07NkTT09P\nfvvtN7Zs2cK3337LsmXL8PLyuup5Fi1axIYNG+jXrx8PPvgg+fn5fPLJJzz99NMsWLCAdu3aWfS/\n9957ueOOOyzaLk/67ImSORERERGRWsxgMNikAMq1zjls2DDatWuHs7Ozua13797ExMSwevVqZs6c\nCcDTTz9tNbZnz548+eSTJCUlMXLkyCueo7y8nISEBHr16sVzzz1nbo+IiOCRRx4hOTnZKpm75ZZb\n6Nu3b7Wu0dZ0z5yIiIiIiNS4Dh06WCRyAP7+/rRp04aMjIyrjvXz8wMgPz//qv3Ky8spLi6mcePG\nFu1GoxGDwYCbm1uV44qKiigrK7vWJdicVuZERERERMRunDt3jsDAQKv2CxcuUFFRwZkzZ/jwww8x\nGAx06dLlqnO5uroSGhpKUlISHTp04LbbbiMvL4+VK1diNBoZNGiQ1ZgPP/yQxYsXYzAYCAkJYdy4\ncXTr1u2GXd+NpGRORERERETswtatW8nKyiImJsbq2MMPP0xpaSlwaWVtypQpdO3a9ZpzxsXFMXv2\nbF577TVzW4sWLZg/f75FARUnJye6d+/OXXfdhY+PD7/99hvr169nxowZvPbaa1b30dkDJXMiIiIi\nImJzGRkZvP3223Tq1In+/ftbHZ87dy4lJSVkZGSwdetWioqKqjWvh4cHbdq0oWPHjnTp0oWcnBzi\n4+N54YUXmD9/Po0aNQLA19eXuXPnWoyNjIxk7NixLFq0SMmciIiIiIjUrJoogLJ27VrWr19v0Zab\nm1vt8Tk5OTz//PN4enoya9asKuMNCwsD4Pbbbyc8PJyYmBg8PDx48MEHrzhveXk5zz77LGFhYUyd\nOtXc3rVrVx5//HHWrl3LE088ccXxnp6eDBgwgDVr1pCVlYWPj0+1r6kmKJkTEREREZE/Zfjw4Qwf\nPtyi7YcffiA8PPyaYwsKCpgxYwYFBQXMnz//mo8agEvbJIODg0lOTr5qMrd//36OHz/OU089ZdHu\n7+9Pq1atOHDgwDXP5evrC0BeXp6SOREREREREYCSkhJmzpzJyZMneeONN2jVqtV1ja28h+5Kzp07\nh8FgoKKiwupYWVkZ5eXl1zzPqVOngEv36dkbPZpARERERERqXEVFBbNnz+bQoUPMmjWL0NBQqz7l\n5eVVPn7g0KFDHDt2jPbt21u0Z2RkcPbsWfPPAQEBmEwmtm/fbtHvyJEj/PLLL9xyyy3mtqq2hWZm\nZpKYmEhQUFC1VgxrmlbmRERERESkxi1cuJA9e/YQHh5Obm4uW7dutTgeGRlJYWEhw4YNo3fv3rRp\n0wZ3d3eOHTtGYmIinp6ejB492mLM2LFjCQsL48033wQgJCSErl278vnnn1NQUEC3bt3Izs7m448/\nxsPDg6FDh5rHLl68mFOnTtGlSxdzNcstW7ZQVFTElClTbv4L8gcomRMRERERkRr3008/YTAY2LNn\nD3v27LE6HhkZibu7O1FRUaSkpLBz506Ki4vx8fGhb9++jB492vzw8EpVFU559dVXWbduHdu3b+e7\n776jXr163HbbbTz++OMEBASY+3Xv3p2EhAQ2b95Mfn4+DRs2JCwsjNGjRxMcHHzjX4AbQMmciIiI\niIjUuHnz5l2zj4uLC5MnT672nNu2bbNqc3V1ZfTo0VareL/Xp08f+vTpU+1z2QPdMyciIiIiIuKA\ntDInIiIiIlKL1cRz5q50Xrm5tDInIiIiIiLigJTMiYiIiIiIOCAlcyIiIiIiIg5IyZyIiIiIiIgD\nUgEUEREREZFaTAVQai+tzImIiIiIiDggJXMiIiIiIiIOSMmciIiIiIiIA1IyJyIiIiIi4oBUAEVE\nREREpBZTAZTaSytzIiIiIiIiDkjJnIiIiIiIiANSMiciIiIiIuKAlMyJiIiIiIg4IBVAERERERGp\n5VSMpHbSypyIiIiIiIgDUjInIiIiIiLigJTMiYiIiIiIOCAlcyIiIiIiIg5IBVBERERERGoxg8Fg\nkwIoKrpy82llTkRERERExAEpmRMREREREXFASuZEREREREQckJI5ERERERERB6QCKCIiIiIitZgK\noNReWpkTERERERFxQErmREREREREHJCSOREREREREQekZE5ERERERMQBqQCKiIiIiEgtpgIotZdW\n5kRERERERByQXa7MFRYWsmbNGg4fPszhw4fJy8tjxowZ9O/f36Lf4cOH+eyzzzh8+DDHjh2joqKC\nbdu2VTlnnz59qmx/4oknGDlypEVbfn4+ixcvZvfu3RQVFREaGsqkSZO45ZZbrMYfOHCAJUuWkJ6e\nTv369enVqxfjx4/Hw8PDop/JZGLNmjUkJCSQnZ1NQEAAo0aNumJcIiIiIiIiV2OXyVxubi4rV67E\nz8+PoKAgfvzxxyr7ffvtt3z22WcEBQXRokULfv3116vO261bN/r162fR9vsEzWQy8dxzz3H8+HFG\njBhBo0aN2Lx5M7GxsSxZsgR/f39z3/T0dJ599llat27NU089RWZmJmvXruXkyZPMmTPHYt5ly5YR\nHx/P/fffT0hICF9//TWvvPIKBoOB3r17X8/LIyIiIiIiYp/bLH18fNi4cSPx8fFMnDgRk8lUZb/o\n6Gi2bNnCokWL6Nq16zXnDQgIoG/fvha/WrdubdHniy++IDU1leeee44xY8YQHR3NvHnzcHJy4v33\n37fou2zZMjw9PXnrrbe4//77iYmJYdq0aXz33Xfs3bvX3C8rK4v169czePBgYmNjiYqK4tVXX+XW\nW29lyZIlV7w+sX/x8fG2DkGuQO+N/dJ7Y9/0/tgvvTci8nt2mcy5uLjQpEmTa/Zr3Lgxrq6u1zV3\nSUkJJSUlVzy+c+dOvLy8uPvuu81tRqORXr16sXv3bsrKygC4ePEie/fupV+/fhZbKvv374+7uzs7\nduwwt+3atYvy8nKio6MtzhUdHU1mZiYHDx68rmsQ+6H/WO2X3hv7pffGvun9sV96b+SPqiyAYotf\ncnPZZTJ3syQlJXHfffcxYMAAxo4dW+X9denp6VXeG9e+fXuKi4v55ZdfADh27Bjl5eWEhIRY9HNx\ncSE4OJj09HSLOd3d3WnVqpXVnCaTiaNHj96IyxMRERERkTrELu+Zuxk6depE7969adasGVlZWXz8\n8ce8+uqrFBQU8MADD5j7ZWdn07lzZ6vx3t7e5uOBgYFkZ2djMBjw8vKy6uvl5cWBAwfMP+fk5FS5\n0nj5nCIiIiIiItejziRz8+fPt/h54MCBTJgwgeXLlzNgwADzds3i4mLq1atnNd7V1RWTyURxcTGA\neatmVds8XV1dzf2uNWflcRERERERketRZ5K533N2dubBBx/krbfe4siRI3Tq1AkANzc3SktLrfqX\nlJRgMBhwc3MD/pOIVXX/XUlJibnfteasPF6VyuOHDh26nkuTGpSbm8u+fftsHYZUQe+N/dJ7Y9/0\n/tgvvTf2qfJz2tVqMtiarT5L6jPszVdnkzkAX19fAPLy8sxt3t7eVW57rGyr3Brp7e2NyWQiJyfH\nqm9OTo65H1zadpmSknLNOX/v9OnTAIwePbpa1yO2UZ1KqmIbem/sl94b+6b3x37pvbFfp0+fNi8O\n2Auj0Yi7u7tNP0u6u7tjNBptdv7ark4nc6dOnQKw+AMWFBRkcb9bpdTUVNzc3GjZsiUAgYGBODs7\nk5aWRkREhLlfWVkZ6enpFs+OCw4O5rPPPiMjI8OiCEpqaioGg4Hg4OAq4+vWrRtxcXE0a9bsuqt2\nioiIiMjNV1JSwunTp+nWrZutQ7Hi5+fH+++/T25urs1iMBqN+Pn52ez8tV2dSOZyc3OtvhG4ePEi\nGzZswGg00q5dO3N7REQEX331FTt37uSee+4xj9+5cyfh4eG4uFx6yRo0aEDXrl3ZunUrY8aMMT+e\nICkpiaKiInr16mWes2fPnixcuJCPP/6YadOmmdsTEhLw8fG54rc4jRs3pm/fvjfkNRARERGRm8Pe\nVuQu5+fnp2SqFrPbZG7Tpk0UFBSQmZkJwNdff23+/ZAhQ6hfvz5nzpxh69atAKSlpQGwatUq4NIf\n3MjISAA+/vhjdu3aRY8ePfDz8yMrK4vExETOnj1LXFwczs7O5vNGRESwceNGXn/9dU6cOIHRaGTz\n5s1UVFQwduxYixjHjRvH1KlTmT59OoMGDSIzM5P169fTvXt3i29nmjZtytChQ1m3bh1lZWW0a9eO\nXbt2ceDAAeLi4vQMDhERERERuW6GHTt2mGwdRFVGjhzJ2bNnqzy2evVq/Pz8SElJ4ZlnnqkyGerc\nuTNvvvkmAHv37mXt2rUcP36c3NxcPDw8CA0NZcSIEYSFhVmNzc/PZ/HixezevZvi4mLat2/PpEmT\nqnz+3IEDB3j33Xc5evQoHh4e9O7dm/Hjx1s8SLxSfHw8CQkJZGdnExAQwKhRo+jTp8/1vjQiIiIi\nIiL2m8yJiIiIiIjIlTnZOgARERERERG5fnZ7z1xdVlpayooVK0hOTiYvL4+2bdsybtw4lSO2A4WF\nhaxZs4bDhw9z+PBh8vLymDFjBv3797d1aHVeWloaiYmJpKSkcPr0aYxGI6GhoYwbN46AgABbh1en\nnThxgvfff5+jR4+Sk5ODm5sbrVu3ZsSIEfTo0cPW4cnvrFq1ihUrVhAYGMjy5cttHU6dVnk7ye8Z\nDAYWLFhAaGioDaKSyx05coQPPviAAwcOUFJSQvPmzbn//vsZPHiwrUOTOkLJnB2aM2cOX331FQ89\n9BD+/v4kJiby3HPPMW/ePLuullQX5ObmsnLlSvz8/AgKCuLHH3+0dUjyb/Hx8Rw8eJCIiAjatm1L\nTk4OmzZtYsKECSxcuJA2bdrYOsQ668yZMxQVFdG/f3+8vb0pLi5m586dxMXF8V//9V9ERUXZOkT5\nt8zMTD766KMq7/sW2xk6dKhF5W0Af39/G0Ujlb777jvi4uIICQkxVzY/deqUuWCfSE1QMmdnDh06\nxI4dO5g0aRIPP/wwAJGRkcTExLBkyRLeeecdG0dYt/n4+LBx40aaNGlCWloakyZNsnVI8m/Dhg2j\nXbt2FtVpe/fuTUxMDKtXr2bmzJk2jK5uu+OOO7jjjjss2gYPHsyECRNYv369kjk7smjRIjp27Eh5\neTkXLlywdTjyb7feeqv5cUliHy5evMicOXMIDw9n1qxZtg5H6jDdM2dnvvzyS5ydnRk0aJC5zdXV\nlYEDB5Kamqpve2zMxcWFJk2a2DoMqUKHDh0sEjm49M11mzZtyMjIsFFUciUGgwFfX1/y8/NtHYr8\n248//shXX33F5MmTbR2KVKGwsJDy8nJbhyH/lpyczPnz5xk3bhwARUVFmEyqKSg1Tytzduann34i\nICDAaotL+/btAUhPT6dp06a2CE3EIZ07d47AwEBbhyFc+rBTXFxMQUEBu3fv5ttvv9XjWexERUUF\n77zzDlFRUfr7Yodef/11Ll68iJOTE7fddhsTJ0602nYpNWvfvn3Ur1/f/MziX3/9FXd3dyIjI5k8\neTKurq62DlHqCCVzdiY7Oxtvb2+rdm9vb0wmE9nZ2TaISsQxbd26laysLGJiYmwdinBpC19CQgJw\naWXunnvuYdq0aTaOSgA2b97M2bNn9XfFztSrV4977rmHO++8E6PRyIkTJ1i3bh1PP/0077zzDsHB\nwbYOsc769ddfKSsr44UXXmDQoEFMmDCBlJQU/u///o+CggJeeOEFW4codYSSOTtTXFxMvXr1rNor\nv+EpLi6u6ZBEHFJGRgZvv/02nTp1UrVRO/HQQw8RERFBdnY2X3zxBRUVFZSWlto6rDrvwoULvP/+\n+zz66KM0atTI1uHIZTp27EjHjh3NP/fo0YN77rmH8ePHs2zZMubMmWPD6Oq2wsJCSkpKeOCBB8xb\nk++66y5KS0vZsmULjz/+uIrUSI3QPXN2xs3NrcoPNyUlJebjInJ1OTk5PP/883h6ejJr1iwMBoOt\nQxKgZcuWdOnShcjISF599VUuXrxIXFycrcOq85YvX47RaFQpdQfh7+9PeHg4P/zwg+7RsqHKz2O/\n3yp+7733YjKZSE1NtUVYUgcpmbMz3t7eVW6lrGyragumiPxHQUEBM2bMoKCggLlz5+Ll5WXrkOQK\nIiIiSEtL49dff7V1KHXWyZMn2bJlC4MHDyYzM5PTp09z+vRpSkpKKCsr4/Tp0+Tl5dk6TPkdX19f\nysrKKCoqsnUodVbl57HfF0Vr3LgxgP7eSI3RNks7ExQUREpKCoWFhRZFUFJTUzEYDNofL3IVJSUl\nzJw5k5MnT/LGG2/QqlUrW4ckV1G5bbygoMDGkdRdlRWSFyxYUOWjb0aNGsWQIb2dZ/cAAA5NSURB\nVENU4dLOnDp1CldXVz0P0IZCQkLYt28fWVlZBAQEmNsrv3yvTOpEbjYlc3YmIiKCdevWkZCQwLBh\nwwAoLS0lKSmJ0NBQVbIUuYKKigpmz57NoUOHeOWVVwgNDbV1SPJv58+ft/pgU15eTlJSEq6urrRu\n3dpGkUlgYCAvv/yyVfvy5cspLCxk6tSpNG/e3AaRCUBubi5Go9GiLT09nT179nDnnXfaKCqBS88x\njY+P59NPPyUsLMzcvmXLFlxcXCzaRG4mJXN2JjQ0lIiICJYtW8a5c+fw9/cnMTGRM2fO8Ne//tXW\n4QmwadMmCgoKzN9of/311+bfDxkyhPr169syvDpr4cKF7Nmzh/DwcHJzc9m6davF8cjISBtFJm++\n+SYFBQXcdttt+Pj4cO7cOZKTk/nll1+YNGkS7u7utg6xzjIajfTs2dOqfcOGDRgMBsLDw20QlVSa\nPXs2bm5udOzYkSZNmnDixAm2bNmCh4cH48ePt3V4dVpwcDD33XcfiYmJlJWV0blzZ3744Qe++uor\nRo0apS3+UmMMO3bs0N2zdqa0tJQVK1aQnJxMXl4ebdu2Zdy4cXTt2tXWoQkwcuRIzp49W+Wx1atX\n4+fnV8MRCUBsbCz79++/4vFt27bVYDRyuR07dvDpp59y/PhxLly4gIeHByEhIQwZMoQePXrYOjyp\nQmxsLBcuXGD58uW2DqVO27RpE8nJyZw8eZKLFy9iNBrp2rUrjz76KC1atLB1eHVeeXk5H330EYmJ\niWRlZdGsWTMefPBBhgwZYuvQpA5RMiciIiIiIuKAVM1SRERERETEASmZExERERERcUBK5kRERERE\nRByQkjkREREREREHpGRORERERETEASmZExERERERcUBK5kRERERERByQkjkREREREREH5GLrAERE\nRETE8eTk5LBhwwYOHz5MWloahYWFzJs3j86dO1d7ju3bt7NmzRp+/vln6tevT3h4OBMmTMBoNFr0\nGzFiBGfPnrUaf//99xMbG2vRlpaWxvLly0lNTcVkMtGhQwcmTpxIcHDwH7rO/fv3s3btWtLT0zl/\n/jwNGzYkODiYMWPG0KlTpz80p8iNomRORERERK5bRkYGa9euxd/fn7Zt25Kamnpd4zdv3szbb79N\n165dmTx5MpmZmWzYsIEjR46wcOFC6tWrZ+5rMBgIDg5m2LBhFnO0bNnS4ucjR44wffp0fH19GTt2\nLBUVFWzevJnY2FgWLVpEQEDAdV/nL7/8grOzMw888ABeXl7k5eWRnJzM9OnTmTNnDt27d7/uOUVu\nFCVzIiIiImIlNjaWZs2aMWPGjCqPt2vXjs2bN9OwYUO+/PJLXn755WrPXVZWxvLlywkLC+Nvf/ub\nub1Dhw7ExcWxZcsWBg8ebDGmadOm9O3b96rzrlixAjc3NxYuXEjDhg0B6Nu3L2PGjGHZsmXMmjWr\n2jFWioqKIioqyqItOjqaRx55hI0bNyqZE5tSMiciIiIi183Dw+MPjz1+/Dj5+fn06tXLor1Hjx54\neHiwY8cOq2QOLiWBZWVluLu7VznvgQMHuP32282JHICXlxedO3dmz549FBUVWYz99ttvWb16NUeO\nHMHJyYnbbruNiRMn0qZNm6vG7+bmRuPGjcnPz6/+RYvcBCqAIiIiIiI1qrS0FABXV1erY25ubhw9\netSqfd++fQwYMICBAwcycuRINm7caNWnpKQENze3KucsKyvj+PHj5rbPP/+cmTNn4uHhwcSJE3n0\n0UfJyMhg+vTpnDlzxmqOixcvkpubS0ZGBkuXLuXEiRN06dLluq5b5EbTypyIiDickpIS6tWrh8Fg\nsHUoIvIH+Pv7YzAYOHDgAAMGDDC3Z2RkcP78eQwGA3l5eXh6egIQFBTErbfeSsuWLblw4QKJiYn8\n4x//ICcnhyeeeMI8vmXLlubCJ5X/PpSVlXHo0CEAsrKyACgsLGTBggUMGjTIooBK//79GTNmDB99\n9BHPPPOMRcyzZ8/mu+++A8DFxYVBgwYxZsyYm/DqiFSfkjkREamWlJQUnnnmGV5++WXuuusui2PJ\nycm89tprLFiwgA4dOpCRkcHy5ctJSUmhqKiIwMBAHn30UcLDw81j8vLyWLVqFd9//z2//fYbTk5O\ndOrUiSeeeIKgoCCr877wwgscP36cxMREcnJy+OSTT2jQoEGNXb9IbVZeXm61ZbCsrIzS0lJyc3Mt\n2hs1avSnv0gxGo306tWLzz//nFatWnH33XeTmZnJO++8g4uLC+Xl5RQXF5uTuVdeecVi/IABA5gx\nYwbr169n8ODB+Pj4AJfuZXv77bd5/fXXGTFiBBUVFaxcuZKcnBwAiouLAfj+++8pKCigd+/eFtdn\nMBgIDQ0lJSXFKuYJEyYwbNgwMjMzSUpKMm/5vLxQi0hNUzInIiLVEhYWhq+vL8nJyVUmc/7+/nTo\n0IHjx48zbdo0mjZtyiOPPIK7uztffPEF//3f/83s2bPNY0+dOsXXX39NREQEzZs359y5cyQkJBAb\nG8v777+Pl5eXxTlWrlxJvXr1GD58OKWlpfoAJXID/etf/7JaiQI4ePAg27dvN/9sMBhYvXo1fn5+\nf/qczzzzDCUlJSxZsoTFixdjMBjo27cvLVq0YNeuXde8J++hhx7iu+++IyUlxVwY5YEHHiArK4s1\na9aQlJSEwWAgJCSEESNG8NFHH5nnPHnyJCaTqcprNhgMVX5RdPmXTH379mXChAnMnTv3DxVVEblR\nlMyJiEi19e3blw0bNnDx4kXq168PQG5uLnv37jVvN1qwYAHNmjVj8eLFODs7A5e+LZ86dSrvvvuu\nOZkLCgpi5cqVFvNHRkby6KOP8umnnzJ69GiLY6Wlpbz77rtK4kRuguDgYP7+979btC1cuBBvb2+G\nDx9u0f77L1r+qAYNGvA///M/ZGZmcvr0afz8/PD19WXKlCkYjcZrrrz7+voCl1b5LxcTE8OwYcM4\nceIEDRo0IDAwkGXLlgH/eZRB5TbMmTNn0qRJE6u5K//tuhIXFxfCw8OJj4+npKSkynv/RGqCkjkR\nEam2fv36sXr1ar788kvuu+8+4NJDfysqKoiMjCQvL4+UlBQef/xxqy1b3bp148MPPyQ7Oxtvb29c\nXP7zX1BFRQX5+fm4u7vTsmVLjhw5YnXuAQMGKJETuUkaNmxoVczD09MTLy+vm17ko2nTpjRt2hSA\n/Px8jhw5YlXlsiqnTp0CsHrAOFy6nssf6L13716aNm1Kq1atAGjRogUmk4nGjRv/4eur3LJZWFio\nZE5sRsmciIhUW6tWrWjXrh3JycnmZG7btm2EhobSvHlzDh8+jMlk4r333mPFihVW4w0GA+fOncPb\n2xuTycSGDRv45JNP+O2336ioqDD3qerD2Y3Y1iUitnH27FmKiorMydSVLF26lIqKCh566CFzW15e\nHg0aNMDJ6T9F2MvLy1m9ejX16tXjL3/5y1Xn3L59O2lpaTz11FPmtu7du1O/fn0++ugjwsLCrFbi\ncnNzzf8OnT9/nsaNG1scz8/PZ+fOnfj6+lb575VITVEyJyIi16Vfv3784x//ICsri+LiYlJTU3n6\n6acBzAnZsGHDrvggXX9/fwBWrVrFe++9x8CBA4mJiTEXVViwYAEmk8lqXFXlxkXEtlauXInBYOD4\n8eOYTCY+//xz/vWvfwFYbJV+7bXX2L9/v8X9d/Hx8Rw/fpzQ0FCcnZ356quv2LdvH+PGjSMkJMTc\nb/fu3axatYqIiAiaNWtGXl4e27Zt48SJE4wfP95im+T+/fv58MMP6datG40aNSI1NZXExETuuOMO\nhgwZYu5Xv359YmNj+d///V8mTJhA7969ady4MWfPnuWbb76hU6dOTJs2DYAZM2bQtGlTQkNDady4\nMWfOnCEpKYns7Gxeeumlm/bailSHkjkREbkuffr0YdGiRWzfvp2ioiJcXFzMW6JatGgBXLqf5Fpb\nl3bu3Mlf/vIXnn32WYv2/Px8q2/BRcQ+vffee+bKlgaDgcTERPOxy5M5g8FgVQEzMDCQXbt28fXX\nX1NRUUHbtm156aWXuOeeeyz6tW3bljZt2pCcnMz58+epV68eQUFBVfb18fHB2dmZdevWcfHiRZo1\na8b48eN5+OGHLVb2AO699158fHyIj49n3bp1lJaW4uPjw6233mreeQAwcOBAtm/fzsaNG8nPz6dh\nw4Z07NiR4cOHW2zlFLEFJXMiInJdjEYjt99+O59//jklJSXcfvvtNGrUCIDGjRsTFhZGQkICgwcP\ntiqUcPnWJScnJ6sVuC+++IKsrCwCAgJq5mJE5IrmzZt3zT6Xr7Rd71x33nknd9555zXHhoSEWD2a\n4EpatGjB3Llzq9UXoHPnznTu3PmqfaKjo4mOjq72nCI1ScmciIhct379+jFr1iwMBgPjxo2zODZ9\n+nSmTZtGTEwMUVFRtGjRgnPnznHw4EGysrJYunQpAD169GDlypXMnTuXTp06cezYMZKTk82reyIi\nInJ1SuZEROS6hYeH4+npiclksngQOEDr1q1ZsmQJH3zwAZ9//jm5ubk0adKE4OBgHnvsMXO/UaNG\nUVRUxLZt2/jiiy8ICQlhzpw55mTvcn/2AcUiIiK1kWHHjh3Wd5mLiIhcRXl5OQ8//DDh4eFW97yJ\niIhIzXC6dhcRERFLu3btIjc3l/79+9s6FBERkTpL2yxFRKTaDh06xE8//cSqVau45ZZbuPXWW20d\nkoiISJ2lZE5ERKrtk08+ITk5meDgYGbMmGHrcEREROo03TMnIiIiIiLigHTPnIiIiIiIiANSMici\nIiIiIuKAlMyJiIiIiIg4ICVzIiIiIiIiDkjJnIiIiIiIiANSMiciIiIiIuKAlMyJiIiIiIg4ICVz\nIiIiIiIiDuj/ATuxaD35gjoLAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fd32f3147d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df.plot.scatter(x='year', y='co2', c='avg_tmp', s=100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import scipy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from scipy.stats import pearsonr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-0.19777222094051761, 0.74983990808071277)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pearsonr(df.co2, df.avg_tmp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}