concrete_strength_predict.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Predict the concrete strength "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A simple neural network and Linear regression based concrete strength prediction. Let import some library first"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn import linear_model\n",
    "from sklearn.neural_network import MLPRegressor\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import mean_squared_error"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, it's time to import the dataset. Note- Data is already available in data folder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pandas.read_excel(\"data/Concrete_Data.xls\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lets see the summary of our dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1030 entries, 0 to 1029\n",
      "Data columns (total 9 columns):\n",
      "Cement (component 1)(kg in a m^3 mixture)                1030 non-null float64\n",
      "Blast Furnace Slag (component 2)(kg in a m^3 mixture)    1030 non-null float64\n",
      "Fly Ash (component 3)(kg in a m^3 mixture)               1030 non-null float64\n",
      "Water  (component 4)(kg in a m^3 mixture)                1030 non-null float64\n",
      "Superplasticizer (component 5)(kg in a m^3 mixture)      1030 non-null float64\n",
      "Coarse Aggregate  (component 6)(kg in a m^3 mixture)     1030 non-null float64\n",
      "Fine Aggregate (component 7)(kg in a m^3 mixture)        1030 non-null float64\n",
      "Age (day)                                                1030 non-null int64\n",
      "Concrete compressive strength(MPa, megapascals)          1030 non-null float64\n",
      "dtypes: float64(8), int64(1)\n",
      "memory usage: 72.5 KB\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "    }\n",
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       "        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>Cement (component 1)(kg in a m^3 mixture)</th>\n",
       "      <th>Blast Furnace Slag (component 2)(kg in a m^3 mixture)</th>\n",
       "      <th>Fly Ash (component 3)(kg in a m^3 mixture)</th>\n",
       "      <th>Water  (component 4)(kg in a m^3 mixture)</th>\n",
       "      <th>Superplasticizer (component 5)(kg in a m^3 mixture)</th>\n",
       "      <th>Coarse Aggregate  (component 6)(kg in a m^3 mixture)</th>\n",
       "      <th>Fine Aggregate (component 7)(kg in a m^3 mixture)</th>\n",
       "      <th>Age (day)</th>\n",
       "      <th>Concrete compressive strength(MPa, megapascals)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1030.000000</td>\n",
       "      <td>1030.000000</td>\n",
       "      <td>1030.000000</td>\n",
       "      <td>1030.000000</td>\n",
       "      <td>1030.000000</td>\n",
       "      <td>1030.000000</td>\n",
       "      <td>1030.000000</td>\n",
       "      <td>1030.000000</td>\n",
       "      <td>1030.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>281.165631</td>\n",
       "      <td>73.895485</td>\n",
       "      <td>54.187136</td>\n",
       "      <td>181.566359</td>\n",
       "      <td>6.203112</td>\n",
       "      <td>972.918592</td>\n",
       "      <td>773.578883</td>\n",
       "      <td>45.662136</td>\n",
       "      <td>35.817836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>104.507142</td>\n",
       "      <td>86.279104</td>\n",
       "      <td>63.996469</td>\n",
       "      <td>21.355567</td>\n",
       "      <td>5.973492</td>\n",
       "      <td>77.753818</td>\n",
       "      <td>80.175427</td>\n",
       "      <td>63.169912</td>\n",
       "      <td>16.705679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>102.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>121.750000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>801.000000</td>\n",
       "      <td>594.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.331808</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>192.375000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>164.900000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>932.000000</td>\n",
       "      <td>730.950000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>23.707115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>272.900000</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>185.000000</td>\n",
       "      <td>6.350000</td>\n",
       "      <td>968.000000</td>\n",
       "      <td>779.510000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>34.442774</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>350.000000</td>\n",
       "      <td>142.950000</td>\n",
       "      <td>118.270000</td>\n",
       "      <td>192.000000</td>\n",
       "      <td>10.160000</td>\n",
       "      <td>1029.400000</td>\n",
       "      <td>824.000000</td>\n",
       "      <td>56.000000</td>\n",
       "      <td>46.136287</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>540.000000</td>\n",
       "      <td>359.400000</td>\n",
       "      <td>200.100000</td>\n",
       "      <td>247.000000</td>\n",
       "      <td>32.200000</td>\n",
       "      <td>1145.000000</td>\n",
       "      <td>992.600000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>82.599225</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Cement (component 1)(kg in a m^3 mixture)  \\\n",
       "count                                1030.000000   \n",
       "mean                                  281.165631   \n",
       "std                                   104.507142   \n",
       "min                                   102.000000   \n",
       "25%                                   192.375000   \n",
       "50%                                   272.900000   \n",
       "75%                                   350.000000   \n",
       "max                                   540.000000   \n",
       "\n",
       "       Blast Furnace Slag (component 2)(kg in a m^3 mixture)  \\\n",
       "count                                        1030.000000       \n",
       "mean                                           73.895485       \n",
       "std                                            86.279104       \n",
       "min                                             0.000000       \n",
       "25%                                             0.000000       \n",
       "50%                                            22.000000       \n",
       "75%                                           142.950000       \n",
       "max                                           359.400000       \n",
       "\n",
       "       Fly Ash (component 3)(kg in a m^3 mixture)  \\\n",
       "count                                 1030.000000   \n",
       "mean                                    54.187136   \n",
       "std                                     63.996469   \n",
       "min                                      0.000000   \n",
       "25%                                      0.000000   \n",
       "50%                                      0.000000   \n",
       "75%                                    118.270000   \n",
       "max                                    200.100000   \n",
       "\n",
       "       Water  (component 4)(kg in a m^3 mixture)  \\\n",
       "count                                1030.000000   \n",
       "mean                                  181.566359   \n",
       "std                                    21.355567   \n",
       "min                                   121.750000   \n",
       "25%                                   164.900000   \n",
       "50%                                   185.000000   \n",
       "75%                                   192.000000   \n",
       "max                                   247.000000   \n",
       "\n",
       "       Superplasticizer (component 5)(kg in a m^3 mixture)  \\\n",
       "count                                        1030.000000     \n",
       "mean                                            6.203112     \n",
       "std                                             5.973492     \n",
       "min                                             0.000000     \n",
       "25%                                             0.000000     \n",
       "50%                                             6.350000     \n",
       "75%                                            10.160000     \n",
       "max                                            32.200000     \n",
       "\n",
       "       Coarse Aggregate  (component 6)(kg in a m^3 mixture)  \\\n",
       "count                                        1030.000000      \n",
       "mean                                          972.918592      \n",
       "std                                            77.753818      \n",
       "min                                           801.000000      \n",
       "25%                                           932.000000      \n",
       "50%                                           968.000000      \n",
       "75%                                          1029.400000      \n",
       "max                                          1145.000000      \n",
       "\n",
       "       Fine Aggregate (component 7)(kg in a m^3 mixture)    Age (day)  \\\n",
       "count                                        1030.000000  1030.000000   \n",
       "mean                                          773.578883    45.662136   \n",
       "std                                            80.175427    63.169912   \n",
       "min                                           594.000000     1.000000   \n",
       "25%                                           730.950000     7.000000   \n",
       "50%                                           779.510000    28.000000   \n",
       "75%                                           824.000000    56.000000   \n",
       "max                                           992.600000   365.000000   \n",
       "\n",
       "       Concrete compressive strength(MPa, megapascals)   \n",
       "count                                       1030.000000  \n",
       "mean                                          35.817836  \n",
       "std                                           16.705679  \n",
       "min                                            2.331808  \n",
       "25%                                           23.707115  \n",
       "50%                                           34.442774  \n",
       "75%                                           46.136287  \n",
       "max                                           82.599225  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.info()\n",
    "data.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "if want to get the indepth detail go to this url : https://archive.ics.uci.edu/ml/datasets/Concrete+Compressive+Strength"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, let's seprate the input and output variable"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###### Input Variable\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "inpt_colmn = ['Cement (component 1)(kg in a m^3 mixture)',\n",
    "         'Blast Furnace Slag (component 2)(kg in a m^3 mixture)',\n",
    "         'Fly Ash (component 3)(kg in a m^3 mixture)',\n",
    "         'Water  (component 4)(kg in a m^3 mixture)',\n",
    "         'Superplasticizer (component 5)(kg in a m^3 mixture)',\n",
    "         'Coarse Aggregate  (component 6)(kg in a m^3 mixture)'\n",
    "         ]\n",
    "input_var = data[inpt_colmn]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###### Output Variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "outpt_colm = ['Fine Aggregate (component 7)(kg in a m^3 mixture)',\n",
    "              'Age (day)',\n",
    "              'Concrete compressive strength(MPa, megapascals) ']\n",
    "output_var = data[outpt_colm]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's visualize the distribution of the input variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xe1bb4a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xf327e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "input_var.plot(kind='hist',subplots=True, layout=(4,3), figsize=(15,15),sharex=False,alpha=.5,grid = True,\n",
    "                 title=\"Histogram Plot for Concrete features\")\n",
    "plt.show()\n",
    "\n",
    "output_var.plot(kind='hist',subplots=True, layout=(4,3), figsize=(15,15),sharex=False,alpha=.5,grid = True,\n",
    "                 title=\"Histogram Plot for Concrete features\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###### Let's find out the correlation between input variables "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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rp9XS8Wf0U59z/lBezf9NWDjrG/044nldcPNg9b93tDb+ukzfffp4ieUbtTxMp13+oKrXPKDYusljXtWKhVN1+R2f6Np/fqPklBoa/d69e7P5cW/Z3HGaNvZF9fnjy7rg1pHasmGpJo+K/TcoK2Oz2h5+gS4YMFIX3DpKVatV1zcf3lmw/pQrntdlAycVPOo16axmh5xSXl2JO1kr1mjeP5/WssEflFqu7kk91fLW/hp/yhUa3ep4pTZvpNYDby5Y3+WNR7Rp6iyNqH+EZt/1qLq++7iq1d1vbzc/rnmeV8pHZbXD/3TMrIGZvWNm881slpn9z8zalEfjdsTMPjazShteM7PaZnb9HqhniJm12BNtqmzM7AozO6iU9TeZ2Wwzm2lmD4bLOprZ4CLlzjazu8Lng83s/F1sTzczK/k/oXJgZlXM7FMzW2dmhxRZd6+ZTTOzqWY2orR9txPbGWRmJ+6gzB27Wn8J9Z1hZvfsyTor0pRvh6prr/NUv2FrpVSvpeP6Xqcp44bGLFulSjUddcrlatqmqxISEoutb9Sikzof3Vd1Dmi0t5v9m9GxuemnBa51m6XMbGnczDx1ah47WDB/pfTLUml7jpSTK02c62oUEdOpXV1asMq1NUvKzZNmLXYdUKucOhKnfhjziY4+/mwd1LiVqqfV1Onn99f3Y2JfxZwyfpQOatRCXY86WVWrJemMC67TssVztGr5QklS+05HqttRp6jWfsVPUrHrZo4fqo49zlfdg1orObWWevS5XjN++Chm2cQq1dT1+CvUqFU3WULxfy83rVumZu17qnrNuqpSNUltu52udSvn7u0uxLV5k4eqTbfztF/91kpKqaXOva/TvMmx/wY1bttLzTv2UbXkNFWplqL2R16i1Ysnxyy7ZcNyrV40Sa06992bzY9rq4Z+qdWfjNL2XzeWWq7R78/W0leGKH3WPOVs3Ky59z+tRpedI0mq3rqZanbpoDn3PKG8zCyt+miEtsyYowbnEsRB+Sk1WGBmJukjSWPcvaW7HyzpDkm7lTNmgd26JGNmtSUdJqm2mTXfnbqK1Fv8v/hdV1vSbgULzKyDpER3X7BnmlTpXCEp5gmvmfWW1FdSJ3fvIOlhSXL36ZIamVmTiOJ/k/T07jbG3Se6+807LrlXPSNptoK+v2tmkWePD7l7J3fvLGm4pLt2dSPufpe7j9xBsTIHC8ystOFNn0o6y8xSy1pvZbRm+Tw1aNy24HWDxu2UvnmdtqVvqMBWId8BNU2rIw7F6g1SWoopJXaWe5TGB5jWbSp8/dMCV6O6prRkqUqi1KGZaf7KynslYF+wYukCNWpW+P1p1KyNNm/8Velbiv9zvWLp/KiySckpOqB+I61YOr9c2vpb9evKuTqgUbuC1wc0aqttW9YpYxd+x3U86nwtXzBZ6RtXK3t7hn6eMEzNO/Tak839zdmwZp7qNCj8XtRp0E4Z6euUuW3Hx2f1oonar36rmOvmTRmq+s26qkYdgtd7W40OrbV52i8FrzdPm63kBgeoap3aSju4lTIWLFVu+taI9b+oxsGxjxuwN+zohL23pGx3fzZ/gbtPdfdvwhP+h8xshplNN7MLJcnM0sxslJlNDpf3DZc3M7OfzexpSZMlNQ6vAOe//y9huZZm9rmZTTKzb8ysXYx2SdJ5koZJekfSRfkLw/f/YGYTwiun6eHyBDN7OrxCPTzMkDg/XLfIzO4ys3GSfldSG0qpO2afJf1LUsvwKvBDYdlbw/dP28krrP0kfRzRvz7hdn4ys1HhsjpmNjSs8wcz6xQuv9vMXg2vQC8ys3PN7MGwjZ+bWdWI/v/bzH4MH63C5U3Dfk0LfzYJlw82s8fN7DszWxB5FT9W/yKO/Qvh/h9hZinh+7pJejPcRylF+n6dpH+5e5YkufuaiHXD8o+7BZkuWe6+rujOs+BK/ODw+J9mZr+Y2biw/cNjlD8uf3m4/142szFhP2MGEczsGTObGPYt5jEN63jUzL4O98XhZvahmc01s/siyg2UtMnd/+ru30q6StLbZlYr3AebI6qtLqnY2YoF2RpDzWyYmS00sxvN7K9mNiX8fNQJyw02s/PNrJYF2Rttw+Vvm9nVZvYvSSnhsXkzPI4zIrYzwMzujujfP81srKQ/mdkBZvZB+FmYYGZHh+13SWMknRFrP+1rtmduU3JKjYLXySlpkqSsjG0V1SREqFZVysou/IpkZRcuL029WtIxHUyjfiqc3ODXLdLmba4/nZ2oW89LUN2apm9mEizYHVmZ25SSmlbwOv95ZsbWGGUzospKUnJqWsyy2HO2Z21TUnLhfk8Kf99tzyr7ft+vXnPV3O8gPXtnLz1+S1etXzVfPU69YY+19bcoZ/s2VUsu/BtULTxW2Vml/w1av2q2pnz1jA7vE3vY27wpn6j1YefsuYaiRInVU5WzKb3gdc6mLZKkKjWqq0padWVv3hJVPmfTFiXWqF6ubYw3ee6V8lFZ7WiCw0MkTSph3bmSOks6VFJdSRPM7GtJayWd4+6bzayupB/MLD+vsK2kP7j79WbWVVJDdz9EKsgUkKTnJV3r7nPN7AgFV4uPj7H9iyXdI2m1pCGSHgiXPybpMXd/28yuLdLeZpI6Sqon6WdJL0esz3T3nmFbRpXQhpLqziyhz7dJOiS8CiwzO1lSa0ndJZmkT8ysl7t/XcI+lqSjJb0dvv8ASS9I6uXuC/NP+sL9MMXdzzaz4yW9puDYSFJLBUGfgyV9L+k8d/+bmX0k6XRJ+flqm929u5ldJum/Ck7mnpT0mru/amZ/lPS4pLPD8gdK6impnaRPJA0pqX+SloTLL3b3q83svbAdb5jZjZIGuPvEGH1vI+kYM7s/3McD3H1CuG5iuH8fDPdRsVw6C4Yt1JL0B0lJkp6L2Hdvl7LPI7UL918NSbPN7Bl3zy5S5k53X29BVsooM+vk7tNi1LXd3XuZ2Z8UBIC6Slovab6ZPeruv7p7VLDB3b+XdEyRft0v6TJJm8K2xXKIpC6SkiXNk/R3d+9iZo+G7/1vxDY2hcdhsJk9Jmk/d38h3NaNEZ/fZqXsJ0mq7e7HhmXfkvSou48Lg0xfSGoflpsY9um9ohWYWX9J/SXp6r89oxPP7r+DTZavn74bpk9evVuS1LRNV1VLTlVmZuEf+azweVJKXCRO7HM6NDWd1i0YZrB0rbQ9W0qqasqPqSWFQYLtRb/BEfZLky46NkEjpriWri1cfmo3U5VE0yMf5io7R+rR3nTRsQka/GWM2RIR0/ivP9Vbzwex0VbtDlNScqoyMgq/PxnhiX9ySvF/hJOSU6LKSkFQIVZZ7LpZP36iL98eKElq2KqrqiWlFvxek6Tt4TGollT2/T7ynYHKycnSDQ+OV9VqqZow8gV98NTVuvRv7++Zxv8GzJ86TN9+fLckqX7TrqpSLVXbsyKOT/i8alLJf4M2/7pYIwb315Gn364GzboVW79q0SRlpK9Tsw4n79nGI6bcrdtUpWZhQC7/ec6WrcpJ36oqNaKDpFVqpil3C0FSlJ/duRtCT0lvu3uupNXhFcXDJX0m6Z/hSWKepIYqHLaw2N1/CJ8vkNTCzJ5QkJo8wszSJB0l6X2zgnGlSUU3bGb1JbWSNM7d3cxyzOwQd58hqYcKT2jfUpi6Hrb3fXfPk7TKzL4qUu27Yd2ltaGkuq2UPkc6OXxMCV+nKTiJLi1YcKCCAIwkHSnpa3dfKEnuvj6ib+eFy0ab2f75V6Ilfebu2WY2XVKipM/D5dMVBE/yvR3x89GI/p4bPn9dwYl5vqHhvpwVHo/S+rdE0kJ3nxoun1Rk2yWpImm/sN+HS3rPzFqEV6fXqHD4QuQ+yvcPSePdvb8kWZAdsiB/34X93Jkz0U/DzIYsM1uj4LguK1LmgvAkt0rYloMlxQoW5AfNpkua6e4rw7YtkNRY0q870R65+52S7jSz2yXdKGlgjGJfufsWSVvMbJOCTIz8bXeKUeeXZvY7SU8pCADuincjnp8o6eCI71BNM6sRtiny2BVtx/MKAoZ67/vKN9vLoUedqUOPOrPg9XvPDtCqJbPVsfupkqRVS2YrrWZdpaYx+VBFmLnYNXNx4cembw9T/drSz0uD1/VqS+kZroztsd9fM1W6pHeCxs10zVgU/fGrV9s0dnqeMsP3TpjjOrZjglKqqcT6EO2IXqfriF6nF7x+6b+3admiOep2VDD+dtmiOapZe3+l1ahd7L0HNW6p78cMK3idlZmhtauW6aDGLfd+w39DDu5+lg7uflbB6+Gv3KK1y2erXdfTJElrl/+i1Bp1lbILv+PWLJ+tY878s1KqB8e3y7G/17fDH9e29PVKTauzg3dDklp2PlMtOxf+DRrz7gCtXzlbLToGf4PWr5ytlLS6Sk6NfXzSNyzX5y//UZ17X6dWXWLPRzBvylA1PfhEVd2FgBDKbsvMuarZqa1WDvlMklSzUztlrlqr7PUblT5rnlJbNFZiWvWCoQg1OrXTineKJcYCe82OhiHMVHD1M5bYs0QFafMHSOoaXpFcreDqpiQVhMLcfYOCk5Ixkm6Q9GLYno3u3jni0V7FXajgJHKhmS1ScOJ5UYxyO9PefPlt29k2RCqtz0Xb8EBEva3cfUf3d8qIqKvwElnxeovKL5efwp+nYEhJ/vI8RQeLvITnseosqLfI9kvrX2T5XO1coGqZpA898GPY5vwpx5IV7Bspeh/lmyCpa0T2xY6Of0lKbbcF82UMkHSCu3dSEPiKdewj68orUm/RY7Gz3lIYJCplW0W3F3NbFswh0l7Bvizpv7YcRf/OKNrPyFB3gqQeEZ+FhmGgIP99cXHDuS5H9dXkrz/QmuXzlLF1k8YMe1Zdep5dYvmc7O3K3h4citzcbGVvz1L+VzIvL0/Z27OUm5sjlyt7e5ZycjgL3R3TF7oObWGqW1NKrir17JCgaQtj/3qrkSJdenyCJs11TZ5fvMzK9a6OzRKUVFVKMKlra9OWbSUHHrBjRx57pr4bPVQrls7X1vTN+uyDF9TjuLNilu3c/XitWDpfk38YqeztWfr0/efUqGlrNWgYTFmUl5ur7O1ZysvNlXvw/cnNKSWFBDulQ/e+mv7dEK1bOU+Z2zbp+8+f0SFHlpyenpO9XTnZwe+4vNxs5WQX/o5r0LSjZv74sbIytig3N1tTv35LabXqESjYDa269NXcSR9ow5p5ysrYpJ/GPKtWh8X+G7R102p99vIf1P7IS9TuiNj/MudkZ2rRjC8YgrAHWGKiEpKqyRITIp4XnxZt+Rsfq9Efzlda+5aqUrumWt1xnZa9FkwiunXuIm3+6We1+ccNSkiqpvp9T1TNjm216sMvyrs7caWi73oQb3dDGC0pycyuzl8QjrU+VsHV8AvNLDFMj+8l6UcFad9rwqvZvSU1jVVxmK6f4O4fKLgKfFg4HntheIUzfyLEWFc5L5bUx92buXszBQGN/N98P6jwBCryt+E4SedZMHa9vqTjYrVrB20oqe6S+rxFQfp6vi8k/THMXpCZNTSzerHaEeFnBVkUUjCM4NjwBFURJ8JfKwhYyMyOk7SuyNj2nXFhxM/8O0x8p8J+9lOwD0uzK/0ruo8iDVU4BMWCeQmqScqfl6CNpPzx85H7KN/nCuaM+NTMakj6RUEmS7Nw/YXaM2oqOEneFH6uTt1D9cZkZq0jXp6loF97wl8U7MeLJb1s4XwWkrIjnq+WVC/MXElS6fMOjFCQ9ZDf7s4R6yKP3T6tdadj1PO0K/Xyv6/QI7ecoNr7H6Tjz7mpYP3jd5yhn74rvBr62G2nalD/ztq8YbVeffgqDerfWRvXrZAkLZ49UYP6d9br/7lGm35dqUH9O+vVh64q9z7FkwWrpO9/cfU7PkE3npWgTVtdX88o/IPc/9QEdWgaxBE7tzDtl2Y6poPp1vMSCh75Rk115eS6rjs9QX85J0GtDjQNGccQhN3RocvROrnvFXr07qt153Wnqs4BB+qMC68rWH/Pn8/V+K8/lSTVqFVH1wx4WB+/9aT+ekUvLZw7XVf+5V8FZX/4erhuuuQIvfXC/Zr382TddMkRev3ZQeXep3jTvEMvdT/pKr332GV6/h+9VbNOQx11euH0Pa/ce7pm/Vh4B4uXB/XRf//cSekbV2vIk1fqv3/upM3rl0uSjjvnb6pSpZpevPtkPf33Hlo4c6z69n+q3PsUTxq1OUYdj7lSn714hd576ASl1T5Ih51Q+Dfow8fO0Pypwd+gOROHaMv6pZoy+mm9dk/XgkekxbNGqWpymg5scUS59iMetbrjOp2aPl2t/n6NGvXrGzy/4zolNz5Qp2yYrOTGB0qS1o74RgseeVFHfvmajp//lTKWLNfcewpvyjWl319Vq+shOnntBLW7f4AmXXiztq9jEmWUH/MdTKhgwa3Z/qvghDxT0iJJf1YwDvpBBSdHLuk+d383DAIMk1RV0lQF48nzT6CGR8xRcKikV1QYsLjd3T8LT4SfUZDOXVXSO+5e8Bc/PNn7VlKjiKvkMrPJCibEWy/pDQVXkj+V1N/dG4ZXTp9WENSYo2BowX/C9OtFkrrlT5BXUhvCE7VYdcfss7svCsdud1IwHODWcLx6/hlAuqRL3b3E6ZzN7PeS2rr7/4WvT5X0z3C/rXH3k8KgwSuSmkvaFrZrmgWTz6W7+8Phe9PdPf9EvmBd2P9XJJ0W1nuxu88L9/XLCq7mr1Uw38QSC25bONzdh8Sot1j/FFyRjzz2AySlufvdZnZe2J8MBVeiC644m1m1cPudJW1XMGfB6HDdk5K+cPdhFsysP0HB/BAe2b5wroXfh307UdJDCgIOP0qq7+79iuzv48LtnBFj/82QdIa7LyrynsGSjlAwtCZL0ifuPrhImTFhvRMjt1F0nXbAzD5QMPdHnqTFCubWWF6kzBUKPs83hq8Xha/XRa7L308Khkx8LKm7u28xs/9I2uLuA83s3wqCEpPdvZ8FkzzeLGmhpOWSFoXHMaoP4XfiKQXZClUUDJ+5Nlw3XMH3fXppfa2MwxAQmLuYQ1PZHdWBlIfKbN7qovP5ojJZv5FAYGV2yMU7SvhFRTs9e/auZvTudTf+Z1Ol/Cfmyb/WqpT7bIfBgn1NeOKYEZ40XqTgxDf/jgxp7p5uZvsrOFk82t1X7Ym69xYL7hDwlYK25u6lbSxSRLCksguvao+V1NPdc8Jlj0ka5qXcCjDi+JuCE9m57v5oSeWx54XZF2+5+wk7KkuwoPIiWFD5ESyo3AgWVG4ECyo3ggWVX2UOFtzw8MZK+U/MUwNqV8p9tjsTHFZWXSU9GZ4QbpT0x4h1wy2460I1SfeWJVCwE3XvFe6eYcHt9BoqmCgQUhNJt+UHCkL/VHB1vzRXm9nlCo7/FAV3R0D5aiLplopuBAAAAIDSxV2wwN2/UQmzubv7cXur7r3J3ffqTCbhvA/7DHefK2lukWWrVXi3gZLe96gK7/SACuCFt74EAAAAUInFXbAAAAAAAICiGORaNju6GwIAAAAAAPiNIVgAAAAAAACiMAwBAAAAABD3nHEIZUJmAQAAAAAAiEKwAAAAAAAARGEYAgAAAAAg7rkzDKEsyCwAAAAAAABRCBYAAAAAAIAoDEMAAAAAAMS9PO6GUCZkFgAAAAAAgCgECwAAAAAAQBSGIQAAAAAA4h53QygbMgsAAAAAAEAUggUAAAAAACAKwxAAAAAAAHHPuRtCmZBZAAD/z959R8talucf/14cRBCkKSpKEwUNKAHBKOpPBaNpdonGWJJYkxhLNMUSRY2JNaTYIqiIGBuKFGtAUURFBQTBQlAQ7AUVUBSEc//+eGefM7PLQZI9+3nm7O9nrVln3nfOwWut23vvmWeeIkmSJGmCgwWSJEmSJGmCyxAkSZIkSRs9lyFcP84skCRJkiRJExwskCRJkiRJE1yGIEmSJEna6K0tlyFcH84skCRJkiRJExwskCRJkiRJE1yGIEmSJEna6HkawvXjzAJJkiRJkjTBwQJJkiRJkjTBZQiSJEmSpI1eeRrC9eLMAkmSJEmSNMGZBZIkSZKkjd5aNzi8XpxZIEmSJEmSJjhYIEmSJEmSJrgMQZIkSZK00SuXIVwvziyQJEmSJEkTHCyQJEmSJEkTXIYgSZIkSdroVbkM4fpwZoEkSZIkSZrgYIEkSZIkSZrgMgRJkiRJ0kav1q5tHWGmOLNAkiRJkiRNcLBAkiRJkiRNcBmCJEmSJGmjt3atpyFcH84skCRJkiRJExwskCRJkiRJE1yGIKlLDz9wk7TOsJySPKmqDm+dY1kc2DrA8tuo6gPAFq0DLKuNrT4H3bF1guW1sdVnY/wubaOq0SHnt06w7Daq+nSuymUI18fG99NQkvr0pNYBtEHWp2/Wp2/Wp3/WqG/WR11ysECSJEmSJE1wGYIkSZIkaaNXnoZwvTizQJJWhmsR+2Z9+mZ9+mZ9+meN+mZ91KW4yYMkSZIkaWP3h399UZcffo/511t3ubG3yxAkSZIkSRs9lyFcPy5DkCRJkiRJExwskCRJkiRJE1yGIElTkOQA4P8BtwR+AZwHnFxVP24aTCTZCfgjFtbnA8CHqmptw3jC/ulZks2B+7NI/1TVl1pm08Aa9c36tLXWX/HXizMLJGkZJfnTJGcBzwG2AM4HfgDcAzgpyVFJdmmZcTVLciTwZuBq4OXAI4G/BE4Gfhc4Lck92yVc3eyfviV5IfAp4EDgs8AbgHcD1wAvS3JSkn3aJZQ16pv10axxZoEkLa8tgbtX1S8WezHJvsAewCUrmkpz/qWqzlvk/nnAsUk2A/ww2o7907fPV9ULl3jtsCQ3w/5pzRr1zfpopnh0oiRpVUqyBbBLVZ3fOos0i5JsWVU/b51DS7NGfbM+K+8hf3VBlx9+3/eaPbo8OtFlCJI0BUn2TPLRJOeNrvdJ8g+tc2mQ5IHA2cCHR9f7JjmhbSrNsX/6luRuSb4MfGV0/ZtJXtc4lsZYo75ZH80KBwskaTqOYFh3/SuAqvoiw6Z66sOhwG8BPwWoqrOB3VoG0gT7p2//CvwOcClAVZ0DuNdHX6xR36yPZoJ7FkjSdNyoqj6XTMwqu6ZVGC1wTVVdNq8+6of907mq+ua8+lzbKosWZ436Zn3aqLVdrkLoloMFkjQdP0pyG6AAkhwCfLdtJI05L8kfA2uS7AE8Dfh040xaz/7p2zeT3A2o0aagT2M0nVrdsEZ9sz6aCS5DkKTpeArDkUi3T/Jt4BnAn7eNpDFPBfYGrgLeDlzGUCP1wf7p258z1OhWwLeAfUfX6oc16pv10UxwZoEkLbMkmwAHVNVvJ9kS2KSqrmidS4Mka4AXVdXfAs9rnUeT7J++jfrnMVX1qNZZtDhr1Dfr05YnAV4/ziyQpGVWVWuBvxo9/7kfdPpSVdcC+7fOocXZP30b9c+DWufQ0qxR36yPZokzCyRpOk5K8jfAu4B1ZyhX1Y/bRdKYL4yOSjyGyfoc2y6Sxtg/fftUktewsD5ntYukeaxR36yPZkKciiFJyy/JRYvcrqrafcXDaIEkRy5yu6rqcSseRgvYP31Lcsoit6uqDl7xMFqUNeqb9WnnAU/+Spcffk98w290eTyTMwskaQqq6tatM2hpVfVnrTNoafZP36rqoNYZtGHWqG/WR7PCwQJJmoIkj13sflW9daWzaKHRzIIF3y44s6AP9k/fkrxgsftV9eKVzqLFWaO+WR/NCgcLJGk67jz2fHPgPsBZgB92+vD+seebAw8BvtMoixayf/r287HnmwP3xzPie2ON+mZ9Gqm1Xa5C6JZ7FkjSCkiyDXB0VT2wdRYtNDqu72TXi/bJ/ulbkhsCJ1TV77TOosVZo75Zn5Vz/yd+ucsPv+8/Yq8u9yzw6ERJWhlXAnu0DqEl7QHs0jqElmT/9O1GgJtP9s0a9c36qEsuQ5CkKUhyIuvXxG8C7MVwTJ86kOQKJvcs+B7w943iaB77p29JzmV9fdYAOwD/2C6R5rNGfbM+7VStbR1hpjhYIEnT8aqx59cAF1fVt1qF0aSqunHrDNog+6dv9x97fg3w/aq6plUYLcoa9c36aCa4DEGSpuP3q+oTo8enqupbSV7eOpQGST7669xTM/ZP315SVRePHt+uqmuSHN06lCZYo75ZH80EBwskaTruu8i931vxFJqQZPMk2wM3TbJdku1Hj92AW7ZNpzH2T9/2Hr9Isimwf6MsWpw16pv1aaTWVpePXrkMQZKWUZK/AP4SuE2SL469dGPg021SacyTgWcwDAycCcztPnw58NpWoTSwf/qW5DnAc4Etklw+dxu4GjiiWTCtY436Zn00azw6UZKW0eiIt+2AlwLPHnvpiqr6cZtUmi/JU6vq1a1zaJL9MxuSvLSqntM6h5Zmjfpmfdr5/ced2+WH3w+++Y4enShJG7uquqyqvgG8aWw94sVV9eMkf9I6n9a5WZI1cxdJtk5yZMtAsn9myNfGL5KsSXJoqzBalDXqm/VppPVyg1lbhuBggSRNxwuSvD7JlkluPjoK7gGtQ2mdNcDnkuyT5H7A5xmWJagP9k/f7pPkg0l2THJH4HSGpSLqhzXqm/XRTHDPAkmajnsBzwLOHl2/oKre0TCPxlTVc5N8DPgs8BPgnlX1tev4Z1o59k/HquqPkzwCOBe4EnhkVX2qcSyNsUZ9sz6aFc4skKTp2A64C/B14Cpg1yRdrkdbjZLcE/h34MXAx4HXJPE0hH7YPx1LsgfwdOC9wDeAxyS5UdNQmmCN+mZ92llba7t89MrBAkmajtOBD1XV7wJ3Zth9328N+vEq4A+r6qVV9cfA4cDHGmfSevZP304Enl9VT2aYBXIBw1IeJbYhCAAAIABJREFU9cMa9c36aCZ4GoIkTUGSXarqknn37llVp7bKpPWSrKmqa+fdu0lVXdoqk9azf/qWZOuqunzevT2q6oJWmTTJGvXN+rTzO39ydpcffj9y1L7/69lzSbYH3gXsxjBT5eFV9ZNF/t4uwBuBnYECfn+0qfCS3LNAkpZRkttX1VeBmya56byXf9Yik9ZL8uiqehvw9CVmtR+2wpE0xv7pW5KDq+pjwG8v0T9+0GnMGvXN+rTX88kD/wfPBj5aVS9L8uzR9d8v8vfeCvxTVZ2UZCvgOtc/OFggScvrmcCTgH9Z5LUCDl7ZOJpny9Gf7jrdJ/unb/diWK6z2MkUBRy7snG0CGvUN+ujaXgQcO/R86MY9mKaGCxIshewaVWdBFBVv9YAvMsQJEmSJEkbvfs95gtdfvj976P3+78sQ/hpVW07dv2Tqtpu3t95MPAE4Grg1sDJwLPnL8mcz5kFkjQFSdYAf8Cwfmzdz9qqcpp7B5LcGngqC+vzwFaZtJ7907ck2wKPZWF9ntYqkyZZo75Zn3ZqbZ8nDyR5EsPMujmHV9XhY6+fDNxikX/6vF/zf2JT4P8B+wGXMOxx8KfAm67rH0mSlt+JwC8ZzlDu8zfT6nYcwy/IE7E+PbJ/+vZBhhMrrE+/rFHfrI8mjAYGDt/A67+91GtJvp9kx6r6bpIdgR8s8te+BXyhqi4c/ZvjgLviYIEkNbFTVe3TOoSW9Muq+o/WIbQk+6dvm1fVM1uH0AZZo75ZHy2nE4A/AV42+vP4Rf7O54HtkuxQVT9k2APojOv6D2+ynCklSet8KMn9WofQkv49yaFJDkxyp7lH61Bax/7p29FJnphkxyTbzz1ah9IEa9Q369NIra0uH/9HLwPum+QC4L6ja5IckOSNAKO9Cf4G+GiSc4EAR1zXf9iZBZI0HacD70uyCfArhh/KVVVbt42lkTsCj2EYWZ+bAupu+/2wf/p2NfBKhrWyc+9yC9i9WSLNZ436Zn20bKrqUuA+i9w/g2FTw7nrk4DrNWvPwQJJmo5/AQ4Ezi2PnenRQ4Ddq+rq1kG0KPunb88EbltVP2odREuyRn2zPpoJDhZI0nRcAJznB51unQNsy+KbAKk9+6dvXwKubB1CG2SN+mZ9GqlyP8nrw8ECSZqO7wIfT/Ih4Kq5mx791o2bA19N8nkm6+PRiX2wf/p2LXB2klOYrI/HvvXDGvXN+mgmOFggSdNx0eix2eihvhzaOoA2yP7p23Gjh/pljfpmfTQT4gw/SZIkSdLG7qCHf7bLD7+nvPsuaZ1hMR6dKEmSJEmSJjhYIEmSJEmSJrhngSRJkiRpo1drPQ3h+nBmgSQtoyQ3SvJ3Sf42yeZJ/jTJCUlekWSr1vlWuyS3T/KhJB9Icpskb0ny0ySfS/IbrfOtdvZP35LcIsnrk7w2yU2SvDDJuUnenWTH1vlkjXpnfTRrHCyQpOX1FoZj+W4NfAA4AHgVEOD17WJp5HDgdcDbgI8BHwa2A/4ReE3DXBq8BfunZ28Bvgx8EzgF+AXwB8Angf9sF0tj3oI16tlbsD6aIZ6GIEnLKMnZVbVvkjCcFb9jVdXo+pyq2qdxxFUtyReqar/R869V1W3HXjurqu7ULp3sn77N659LqmqXsdfOrqp926UTWKPeWZ/27vXQT3f54fcTx97N0xAkabWoYST2g6M/5667/AW1yqwZe37YvNc2W8kgWpr9063x941v3cBrasca9c36aKb4f0pJWl5nzK2trqrHzd1MchvgimapNOe1Y/V53dzNJLcFTm6WSnPsn74dP1aff5i7Oeqf/2mWSuOsUd+sj2aKyxAkaYUkSflDV/pfsX8kSf9X93zIaV3+Hjn1ffdwGYIkrRZJ1sy/5wedfiS5VesMWpr907ckN26dQRtmjfpmfTQrHCyQpGU2ehNwfOscWlySOwLvaZ1Di7N/+jYaaHt/6xxamjXqm/XRLNm0dQBJ2piMzkk+Dvin1lm0UJKDGI5IfFDrLFrI/ulbkr2BdwJPbJ1Fi7NGfbM+7dVaJ6ldHw4WSNLy+iTwt1V1QusgWtQJwF2q6mutg2hR9k/fTgEeVFWntw6iJVmjvlkfzRSXIUjS8voJ4Hr4fr0deEESf//1yf7p2+eBh7UOoQ2yRn2zPpopvlmSpOV1b+D3kjyldRAtVFVPBs4D3tY6ixZ1b+yfnj0Q2DrJK1oH0ZKsUd+sT2O1dm2Xj145WCBJy6iqfs7wZmC/1lm0uKp6CfDh1jm0kP3Tt6q6tqqeBPysdRYtzhr1zfpo1sSTiCRJkiRJ0jg3OJSkKUqyNWM/a6vqxw3jaEySfYDdmKzPsc0CaQH7p19JtgN2ZrI+Z7VLpPmsUd+sj2aBgwWSNAVJngy8GPgFMDeFq4Ddm4XSOkneDOwDfAmYWyxYgIMFHbB/+pbkH4E/Bb7OZH0ObpVJk6xR36yPZoXLECRpCpJcABxYVT9qnUULJflyVe3VOocWZ//0Lcn5wB2r6urWWbQ4a9Q366NZ4QaHkjQdXweubB1CS/pMEgcL+mX/9O08YNvWIbRB1qhv1kczwZkFkjQFSfYDjgQ+C1w1d7+qntYslNZJck/gROB7DPUJUFW1T9NgAuyf3iU5ADie4QPPeH0e2CyUJlijvlkfzQr3LJCk6XgD8DHgXNaviVc/3gw8BuvTK/unb0cBL8f69Mwa9c36aCY4WCBJ03FNVT2zdQgt6ZKqOqF1CC3J/unbj6rqP1qH0AZZo75ZH80ElyFI0hQk+SfgYoap7uNTDD36rQNJXsewXnR+fTwNoQP2T9+SHMZQlxOYrI/HvnXCGvXN+mhWOFggSVOQ5KJFbldVefRbB5IcucjtqqrHrXgYLWD/9C3JKYvcrqry2LdOWKO+WR/NCgcLJEmSJEnSBI9OlCRJkiRJExwskCRJkiRJExwskCRJkiRJEzw6UZKmJMl2wB7A5nP3qurUdok0LskfAHszWZ8Xt0ukcfZP35LcAdiLyfq8tV0izWeN+mZ9NAscLJCkKUjyBODpwE7A2cBdgc8A7nTcgST/CdwIOAh4I3AI8LmmobSO/dO3JIcC92b4oPNB4PeA0wA/6HTCGvXN+mhWuAxBkqbj6cCdgYur6iBgP+CHbSNpzN2q6rHAT6rqRcCBwM6NM2k9+6dvhwD3Ab5XVX8G/CZww7aRNI816pv10UxwsECSpuOXVfVLgCQ3rKqvArdrnEnr/WL055VJbgn8Crh1wzyaZP/07RdVtRa4JsnWwA+A3Rtn0iRr1Dfro5ngMgRJmo5vJdkWOA44KclPgO80zqT13j+qzyuBs4ACjmgbSWPsn76dMarPEcCZwM9wGU9vrFHfrI9mQqqqdQZJ2qgluRewDfDhqrq6dR5NSnJDYPOquqx1Fi1k//QtyW7A1lX1xcZRtARr1Dfro545WCBJkiRJkia4Z4EkSZIkSZrgYIEkSZIkSZrgBoeSpFUpya2AXRn7XVhVp7ZLJM2OJGuAmzPZP5e0S6T5rFHfrI9mgYMFkjQFSR4KvBy4GZDRo6pq66bBBECSlwOPAL4MXDu6XYCDBR2wf/qW5KnAocD3gbWj2wXs0yyUJlijvlkfzQo3OJSkKUjyNeABVfWV1lm0UJLzgX2q6qrWWbSQ/dO3UX3uUlWXts6ixVmjvlkfzQr3LJCk6fi+H3S6diFwg9YhtCT7p2/fBDxqtG/WqG/WRzPBZQiSNB1nJHkXcByw7tvrqjq2XSSNuRI4O8lHmazP09pF0hj7p28XAh9P8gEm63NYu0iaxxr1zfpoJjhYIEnTsTXDB9L7jd0rwA87fThh9FCf7J++XTJ6bDZ6qD/WqG/WRzPBPQskSZIkSdIEZxZI0jJK8ndV9Yokr2b4JnSC09zbSvLuqnp4knNZvD7uRN2Q/dO3JP9WVc9IciKL1+eBDWJpjDXqm/XRrHGwQJKW19ymbGc0TaGlPH305/2bptBS7J++HT3681VNU2hDrFHfrI9missQJEmSJEnSBI9OlCRJkiRJExwskCRJkiRJExwskCRJkiRJE9zgUJKmIMl/LHL7MuCMqjp+pfNo0hKnIVzGsLHeS6rq0pVPpTn2T9+W2Ml9rn/eUFW/XPlUGmeN+mZ9NCucWSBJ07E5sC9wweixD7A98Pgk/9YymAD4EPAB4FGjx4nAqcD3gLe0i6UR+6dvFwI/A44YPS4Hvg/sObpWe9aob9ZHM8HTECRpCpJ8DLhfVV0zut4U+G/gvsC5VbVXy3yrXZJPVdXdF7uX5NyqumOrbLJ/epfk1Kq652L3knypqvZulU0Da9Q366NZ4cwCSZqOWwFbjl1vCdyyqq4FrmoTSWO2SnKXuYskvwVsNbq8pk0kjbF/+rZDkl3mLkbPdxhdXt0mkuaxRn2zPpoJ7lkgSdPxCuDsJB8HAtwT+OckWwIntwwmAJ4AvDnJ3ADBFcATRvV5abtYGrF/+vYs4LQkX2eoz62BvxzV56imyTTHGvXN+mgmuAxBkqYkyY7AbzG8EfhcVX2ncSSNJLlhVV2VZBuG34U/TbJ9Vf24dTYN7J++JbkhcHuG+nwVqKpy1kdHrFHfrI9mgcsQJGkKkry4qr5bVcdX1XHA95L8V+tcWufYJJtW1WWjgYJbACe1DqWB/dO3JG+uqquq6pyqOhtYA3ywdS6tZ436Zn00KxwskKTp2CXJc2DdtwfHMezqrj4cB7wnyZokuzFsnvecpok0zv7p27eTvB4gyXYMA21vaxtJ81ijvlkfzQSXIUjSFCQJ8F/AucBBwIeq6l/bptK4JE8BfhfYDXhyVX26bSLNsX/6l+TlwDbA/sDLquq9jSNpHmvUN+ujWeBggSQtoyR3Gru8AfAG4FPAmwCq6qwWuTRI8szxS+AxDB9IvwBQVYe1yKWB/dO3JA8dvwSeD3wO+DBAVR3bIpfWs0Z9sz6aNQ4WSNIySnLKBl6uqjp4xcJogSSHbuj1qnrRSmXRQvZP35IcuYGXq6oet2JhtChr1Dfro1njYIEkSZIkSZrgBoeStIySPHq03nqp12+T5B4rmUnrJTk8yR2WeG3LJI9L8qiVzqWB/dO3JP8w2oxtqdcPTnL/lcykSdaob9ZHs2bT1gEkaSNzE+DsJGcCZwI/BDYHbgvcC/gR8Ox28Va91wEvSHJH4DzW12cPYGvgzQwb66kN+6dv5wLvT/JL4Cwm+2df4GTgn9vFE9aod9ZHM8VlCJK0zJKsAQ4G7g7sCPwC+ArDju6XtMymQZKtgAMYq09Vnd82lcD+mQVJ9mBhfU6tql80DaZ1rFHfrI9mhYMFkiRJkiRpgssQJGmZJdkcuD/w/4BbMnxrcB7wgar6UstsgiQHAo9mqM/ctzrnAR8A3lZVlzWMt+rZP31LshPwRyxSH4bZH2sbxhPWqHfWR7PEmQWStIySvBB4APBxhjXXP2BYj7gncNDo+bOq6ouNIq5qST4EfAc4HjiDhfV5AHBYVZ3QLOQqZv/0bXTs262A97N4/+wPPLuqTm0WcpWzRn2zPpo1DhZI0jJK8gdV9YENvH4zYJeqOmMFY2kkyU2r6kf/17+j6bB/+pbkDlV13gZe34yhPl9bwVgaY436Zn00axwskCRJ0v9KkjtV1Vmtc0izKslNqurS1jmkxWzSOoAkrRZJDm+dYbVLsnOSdyb5ZJLnJrnB2GvHtcwmSHKLJK9P8tokN0nywiTnJnl3kh1b51vtktxp3mN/4IQk+yW5U+t8giS/O/Z82yRvSvLFJG9PcvOW2QRJXpbkpqPnByS5EPhskouT3KtxPGkBZxZI0jJKsv1SLwHnVNVOK5lHk5KcBLwXOB14PMP60AdU1aVJvlBV+zUNuMol+TDDJl9bAn8M/BfwDuBBwG9X1YMaxlv1kqxl6J2rxm7fdXSvqurgJsG0TpKzqupOo+dvBL4HHAE8FLhXVT24Zb7VLsm5VXXH0fNTgL+rqs8n2RN4e1Ud0DahNMnBAklaRkmuBS5mGByYU6PrW1XVZk2CCYAkZ1fVvmPXjwaeAzwQOGbuTbbaGB+wSXJJVe0y9tpE7bTykhwCPBV4eVV9cHTvoqq6ddtkmjNvsGD+zzt7qLEkXwXuUFXXJDm9qu469tq6gQSpFx6dKEnL60LgPlV1yfwXknyzQR5NukGSzavqlwBV9bYk3wM+wvBtttoaXx751g28pgaq6j2j2R//mOTPgGcxDIaqHzdL8kyGAeqtk6TWfzNoD7X3WuCDSV4GfDjJvwHHAvcBzm6aTFqEgwWStLz+DdgOWDBYALxihbNooTcCdwE+MXejqk5O8odYnx4cn2SrqvpZVf3D3M0ktwX+p2EujVTVz4C/TrIvcBSwVeNImnQEcOPR86OAmwI/THIL/DDaXFW9Osm5wF8wHJe46ejP44CXtMwmLcZlCJIkSbrekgS4cVVd3jqLJGn5OVggSZIkSZImuHZJkiRJkiRNcLBAkrTqJFmwe/ti99RGkhv+OvfUhv3TP3uob9ZHs8LBAkmagiQf/XXuqZn3LnLvPSueQkv5zK95T23YP/2zh/pmfTQTPA1BkpZRks2BGwE3TbIdw/FVAFsDt2wWTAAkuT2wN7BNkoeOvbQ1sHmbVJoz2rH9VsAWSfZjsn9u1CyYAPtnFthDfbM+mjUOFkjS8noy8AyGgYEzWf9G4HKG85XV1u2A+wPbAg8Yu38F8MQmiTTud4A/BXYCDhu7fwXw3BaBNMH+6Z891Dfro5niaQiSNAVJnlpVr26dQ4tLcmBVOeWzU0keVlWLTXVXB+yf/tlDfbM+mhUOFkjSlCS5G7AbY7O4quqtzQJpnSQ7MHwTuhuT9Xlcq0xab7TR18NYWJ8Xt8qk9eyf/tlDfbM+mhUuQ5CkKUhyNHAb4Gzg2tHtAhws6MPxwCeBk1lfH/XjeOAyhqU8VzXOooXsn/7ZQ32zPpoJziyQpClI8hVgr/KHbJeSnF1V+7bOocUlOa+q7tA6hxZn//TPHuqb9dGs8OhESZqO84BbtA6hJb0/ye+3DqElfTrJHVuH0JLsn/7ZQ32zPpoJziyQpClIcgqwL/A5xqYYVtUDm4XSOkmuALYErh49AlRVbd00mABI8mXgtsBFDP0zV599mgYTYP/MAnuob9ZHs8LBAkmagiT3Wux+VX1ipbNIsybJrovdr6qLVzqLNIvsob5ZH80KlyFI0hSMBgW+Adxg9PzzwFlNQ2mdDB6d5Pmj652T/FbrXBqM3jDvDBw8en4lvmfphv3TP3uob9ZHs8KZBZI0BUmeCDwJ2L6qbpNkD+A/q+o+jaMJSPJ6YC3DG7XfSLId8N9VdefG0QQkORQ4ALhdVe2Z5JbAMVV198bRhP0zC+yhvlkfzQpHsCRpOp4C3B24HKCqLgBu1jSRxt2lqp4C/BKgqn4CbNY2ksY8BHgg8HOAqvoOcOOmiTTO/umfPdQ366OZ4GCBJE3HVVV19dxFkk0Bp3L141dJ1jCqSZIdGL4pVR+uHh07OlefLRvn0ST7p3/2UN+sj2aCgwWSNB2fSPJcYIsk9wWOAU5snEnr/QfwPuBmSf4JOA3457aRNObdSd4AbDta0nMycETjTFrP/umfPdQ366OZ4J4FkjQFSTYBHg/cj+FIpI8Abyx/6HYjye2B+zDU56NV9ZXGkTRmNMi2rn+q6qTGkTTG/umfPdQ366NZ4GCBJGlVGk2jvjmw6dy9qrqkXSJpdtg/krTx2/S6/4ok6fpKcnfghcCuDD9rA1RV7d4ylwZJngocCnwfuJZRfYB9WubSIMlDgZczbAoa1vfP1k2DCbB/ZoE91Dfro1nhzAJJmoIkXwX+GjiT4c00AFV1abNQWifJ1xh2dLceHRrV5wFObe+T/dM/e6hv1kezwpkFkjQdl1XVh1qH0JK+CVzWOoSW9H3fRHfN/umfPdQ366OZ4GCBJE3HKUleCRwLXDV3s6rOahdJYy4EPp7kA0zW57B2kTTmjCTvAo5jsj7HtoukMfZP/+yhvlkfzQQHCyRpOu4y+vOAsXsFHNwgixa6ZPTYbPRQX7YGrmTYKXxOMQy+qT37p3/2UN+sj2aCexZIklatJDdm2FTqZ62zSLPG/pGkjdsmrQNI0sYoyTZJDktyxujxL0m2aZ1LgyR3SPIF4DzgS0nOTLJ361waJNkpyfuS/CDJ95O8N8lOrXNpYP/0zx7qm/XRrHCwQJKm483AFcDDR4/LgSObJtK4w4FnVtWuVbUr8CzgiMaZtN6RwAnALYFbASdi//TE/umfPdQ366OZ4DIESZqCJGdX1b7XdU9tJDmnqn7zuu6pDfunb/ZP/+yhvlkfzQpnFkjSdPwiyT3mLpLcHfhFwzyadGGS5yfZbfT4B+Ci1qG0zo+SPDrJmtHj0cClrUNpHfunf/ZQ36yPZoIzCyRpCpLsCxwFbAME+DHwJ1X1xabBBECS7YAXAfdgqM+pwAur6idNgwmAJLsArwEOHN36FPD0qrq4XSrNsX/6Zw/1zfpoVjhYIElTlGRrgKq6vHUWLTTadHJtVV3ROos0a+wfSdq4uQxBkqYgyU2S/AfwceCUJP+e5CaNY2kkyZ2TnAucA5yb5Jwk+7fOpUGS3ZOcmOSHo93Cj0+ye+tcGtg//bOH+mZ9NCscLJCk6Xgn8EPgYcAho+fvappI494E/GVV7VZVuwFPwZ2oe/J24N3Ajgy7hR8DvKNpIo2zf/pnD/XN+mgmOFggSdOxfVX9Y1VdNHq8BNi2dSitc0VVfXLuoqpOYzjqUn1IVR1dVdeMHm8DXDfZD/unf/ZQ36yPZoJ7FkjSFCR5FXAGwzcHMMwu2LuqDm2XSnOS/CtwI4Zvcgp4BPAT4L0AVXVWu3RK8jLgpwwzdObqc0PgtQBV9eN26WT/9M8e6pv10axwsECSpiDJFcCWwNrRrU2An4+eV1Vt3SSYAEhyygZerqo6eMXCaIEkGzqGr6rKtb0N2T/9s4f6Zn00KxwskCRJkiRJEzZtHUCSNlZJ9gF2Y+xnbVUd2yyQ1kmyLfBYFtbnaa0yab0ka4A/YGF9DmuVSevZP/2zh/pmfTQrHCyQpClI8mZgH+BLrF+KUICDBX34IHA6cC7r66N+nAj8EuvTK/unf/ZQ36yPZoKDBZI0HXetqr1ah9CSNq+qZ7YOoSXtVFX7tA6hJdk//bOH+mZ9NBM8OlGSpuMzSRws6NfRSZ6YZMck2889WofSOh9Kcr/WIbQk+6d/9lDfrI9mgjMLJGk6jmIYMPgecBUQhh2O/SahD1cDrwSex/qzrQtwB+o+nA68L8kmwK9Y3z+eItIH+6d/9lDfrI9mgqchSNIUJPka8EzmrUesqoubhdI6Sb4O3KWqftQ6ixZKciHwYODc8o1Kd+yf/tlDfbM+mhXOLJCk6bikqk5oHUJL+hJwZesQWtIFwHm+ie6W/dM/e6hv1kczwcECSZqOryZ5O8OOx1fN3fToxG5cC5yd5BQm6+PRb334LvDxJB9isj4eK9YH+6d/9lDfrI9mgoMFkjQdWzC8ARjfwMijE/tx3OihPl00emw2eqgv9k//7KG+WR/NBPcskCStSkk2A/YcXZ5fVb9qmUcLJbkxw6ZfP2udRZPsn9lgD/XN+qh3Hp0oSVOQZKck70vygyTfT/LeJDu1zqVBknszrBl9LfA64H+S3LNpKK2T5A5JvgCcB3wpyZlJ9m6dSwP7p3/2UN+sj2aFMwskaQqSnAS8HTh6dOvRwKOq6r7tUmlOkjOBP66q80fXewLvqKr92yYTQJJPA8+rqlNG1/cG/rmq7tY0mAD7ZxbYQ32zPpoVziyQpOnYoaqOrKprRo+3ADu0DqV1bjD3QQegqv4HuEHDPJq05dybaICq+jiwZbs4msf+6Z891Dfro5ngBoeSNB0/SvJo4B2j60cClzbMo0lnJHkT62d+PAo4s2EeTbowyfOZnJlzUcM8mmT/9M8e6pv10UxwGYIkTUGSXYDXAAcynILwaeDpVXVx02ACIMkNgacA9wACnAq8rqqu2uA/1IpIsh3wIob6wFCfF1XVT9ql0hz7p3/2UN+sj2aFgwWSpFUnyZbAL6vq2tH1GuCGVXVl22RS/+wfSVod3LNAkqYgyVFJth273i7Jm1tm0oSPAluMXW8BnNwoi+ZJctIi/fORlpk0wf7pnD3UN+ujWeFggSRNxz5V9dO5i9HUwv0a5tGkzcfPtR49v1HDPJp000X652YN82iS/dM/e6hv1kczwcECSZqOTUZrEgFIsj1uKtuTnye509xFkv2BXzTMo0lrR/t+AJBkV4a9P9QH+6d/9lDfrI9mgm9cJWk6/gX4dJL3MLwBeDjwT20jacwzgGOSfGd0vSPwiIZ5NOl5wGlJPjG6vifwpIZ5NMn+6Z891Dfro5ngBoeSNCVJ9gIOZtgt/KNV9eXGkTQmyQ2A2zHU56tV9avGkTQmyU2BuzLU5zNV9aPGkTTG/umfPdQ366NZ4GCBJC2jJFuNr+X93/4dTUeSe1TVaRt4fWtgl6o6bwVjaSTJblX1jQ28HuBWVfWtlUulOfZP/+yhvlkfzRqXIUjS8jo+ydnA8cCZVfVzgCS7AwcxLEc4AnhPu4ir2sOSvAL4MHAm8ENgc+C2DPXZFXhWu3ir3iuTbMKof1hYn/sAhwK+kW7D/umfPdQ366OZ4swCSVpmSX4feBRwd2B74FfA+cAHgDdV1fcaxlv1RhtPHsJQnx0ZNmb7CvCBDX1rqpUxWr4z1z87Alcy1OeDwHuq6pcN46169k//7KG+WR/NEgcLJEmSJEnSBI9OlCRJkiRJExwskCRJkiRJExwskCRJkjYSGezcOoek2eeeBZI0BUmOrqrHXNc9tZHkoYvcvgw4t6p+sNJ5tFCSWzHsrr/u5KaqOrVdIml2JDmzqvZvnUPSbPPoREmajr3HL5KsAXzj1o/HAwcCp4yu7w2cDuyZ5MVVdXSrYIIkLwceAXwZuHZ0uwAHC6Rfz+lJ7lzEpkfGAAAWnElEQVRVn28dRNLscrBAkpZRkucAzwW2SHL53G3gauDwZsE031rgN6rq+wBJbg68HrgLwwdSBwvaejBwu6q6qnUQTUoSYKeq+mbrLNqgg4A/T/IN4OcMv4eqqvZpmkrSTHGwQJKWUVW9FHhpkpdW1XNa59GSdpsbKBj5AbBnVf04ya9ahdI6FwI3ABws6ExVVZLjcKZU736vdQBtWJJ7AHtU1ZFJdgC2qqqLWueSxjlYIElTUFXPcc111z6Z5P3AMaPrhwGnJtkS+Gm7WKtbklczLDe4Ejg7yUcZGzCoqqe1yqYJTnHvXFVdvNiH0da5NEhyKHAAcDvgSIbB0bcBd2+ZS5rPDQ4laQqSvAz4I+atua6qB7ZLpTmjqdQPY3hjFuA04L3lL8WmkvzJhl6vqqNWKouWluTLDB9yvoFT3Ls0/mG0qvZMckvgmKryw2gHkpwN7AecVVX7je590R5Sb5xZIEnT8RBcc92t0aDAe0YPdWKxwYAk2wE7V9UXG0TS4pzi3r+HMPowClBV30ly47aRNObq0ZKeAhjNapO6s0nrAJK0kZpbc60OJblrks8n+VmSq5NcO7YhpRpL8vEkWyfZHjgHODLJYa1zaVBVFwM7AwePnl+J7yl7c/VoUNQPo316d5I3ANsmeSJwMvDGxpmkBZxZIEnT4Zrrvr2GYZnIMQxTdR8L3LZpIo3bpqouT/IE4MiqOjSJMws64XrrmTD/w+jj8MNoN6rqVUnuC1zO0EcvqKqTGseSFnCwQJKm44TRQ52qqq8lWVNV1zJ8c/3p1pm0zqZJdgQeDjyvdRgt4BT3zvlhtG9JXl5Vfw+ctMg9qRsOFkjSFFTVUUm2AHapqvNb59ECVybZjGH2xyuA7wJO0+3Hi4GPAKdV1eeT7A5c0DiT1nO9deeSPB94y/gAQZInVdXhDWNpvfsC8wcGfm+Re1JTri+TpClI8gDgbODDo+t9kzjToB+PAdYAf8Wwm/vODKcjqANVdUxV7VNVfzm6vhB4WeNYWs/11v17KvCRJAeN3fvzVmE0SPIXSc4Fbpfki2OPiwCXWqk7Hp0oSVOQ5EzgYODjY8cinVtVd2ybTJodSfZi2FvikcBlVXVA40gaGU1xvx/DsYkfcYp7X5J8AXgQw74s76mqVyb5wtzvI7WRZBtgO+ClwLPHXrqiqn7cJpW0NJchSNJ0XFNVlyUZv+fobGOjb3SWrINnXLeXZFeGwYFHAtcAuwIHVNU3WubSeq63ng1VdUmSewGvT3IMsEXrTKtdVV0GXMbw840kNwM2B7ZKslVVXdIynzSfgwWSNB3nJfljYE2SPYCnAW6g1979WwfQ0kabTG4DvBM4pKouSHKRAwXdcb11/84AqKpfAn+W5CnA/m0jac5oqeJhwC2BHzAMin4F2LtlLmk+9yyQpOl4KsMv/auAdzDsSP2MpolEVV08/gB+BtwJuOnoWm39ELgxcHNgh9E9Z+R0wvXWs6Oqnjjv+rVVtXurPFrgJcBdgf+pqlsD9wE+1TaStJB7FkiSVo0k7weeXVXnjY7mO4vhG7jbAIdX1b81Dai5Nb0PY5ime1tgW+B3qupzTYPJ9dYzIMm7q+rhSy25cqlVH5KcUVUHJDkH2K+q1ib5XFX9Vuts0jgHCyRpCpIcADwX2I2xJV++UWsryZeqau/R8+cCt6+qx47OiP+U9enLaD3vIxgGDnauqp0bR9KYsfXWwLBGvmEcAUl2rKrvjvb+WMAZVH1IcjLwYIaBt5syLEW4c1XdrWkwaR4HCyRpCpKcD/wtcC6wdu6+b9TaSnJ2Ve07ev5R4Iiqeuf819SfJLvaP31Yar313ECc2ktya+C7oz0LSLIFcHP3/+hDki2BXzKcJvIohr1a/quqLm0aTJrHDQ4laTp+WFUntA6hBb6Z5KnAtxj2KvgwrHsjfYOWwbRhDhR0ZW699clVtV+Sgxjt7q5uHAOMf0t97ejendvE0biq+vnY5VHNgkjXwcECSZqOQ5O8EfgowyaHAFTVse0iCXg88GLgt4FHVNVPR/fvChzZLJU0W35VVZcm2STJJlV1SpKXtw6lCZtW1dVzF1V1dZLNWgbSekmuYOGeEpcx7KHzrKq6cOVTSQs5WCBJ0/FnwO0Zvq2eW4ZQgIMFDVXVD4A/X+T+KcApK59Ii0myvRvmde2nSbYCTgX+K8kPgGsaZ9KkHyZ54NwMtyQPAn7UOJPWOwz4DvB2hqUIfwTcAjgfeDNw72bJpDHuWSBJU5Dk3Kq6Y+sc0ixKcgFwNsNsjw+Vb1a64nrr/iW5DfBfDPtKBPgm8Niq+lrTYAIgyWer6i7z7p1eVXdNck5V/WarbNI4ZxZI0nScnmSvqvpy6yDSDNqTYanI44BXJ3kX8Jaq+p+2sVa3JM9gOAv+C1V17ei26607VFVfB+46mgGSqrqidSZNWJvk4cB7RteHjL3m4Ki64cwCSZqCJF8BbgNcxLBnQYDyaD7p+hltnvc2YEvgHODZVfWZtqlWpySvYtg07/bAF4FPMwwefMZlI31I8uiqeluSZy72elUdttKZtFCS3YF/Bw5kGBw4Hfhr4NvA/lV1WsN40jrOLJCk6fjd1gG0tCR7Aq9nOErsDkn2AR5YVS9pHE1AkpsAjwYeA3wfeCpwArAvw47ut26XbvWqqr8BGG2UdwDDwMHjgCOS/LSq9mqZT8AwqAZw40Ve8xvCTow2MHzAEi87UKBuOFggSVNQVRcnuQewR1UdmWQHYKvWubTOEcDfAm8AqKovJnk7w5Fwau8zwNHAg6vqW2P3z0jyn40yab0tgK0Z9irYhmGjtnObJhIAVfWG0dOTq+pT468luXuDSFqEA9aaFS5DkKQpSHIowzdvt6uqPZPcEjimqnyz1oEkn6+qOyf5QlXtN7p3dlXt2zqbIEnc1LA/SQ4H9gauAD7LMHX69Kr6SdNgWiDJWVV1p+u6pzaSfILRgPXY76DzquoObZNJk5xZIEnT8RBgP+AsgKr6TpLFpoWqjR+NdgsvgCSHAN9tG0lJTmR9TRa8XlUPXOlMmrALcEPgAoa11d8Cfto0kSYkOZBhecgO8/Yt2BpY0yaVFnGjqvrcvJ9zHj+q7jhYIEnTcXVVVZK5Dz5bXtc/0Ip6CnA4cPsk32bYiPLRbSMJeFXrAFpaVf1uhk83ezN8IH0WcIckP2bY5PDQpgEFsBnDkrdNmdy34HImd9xXWw5Yaya4DEGSpiDJ3wB7APcFXsqwCdjbq+rVTYNpwmgQZxOPFetDkl2q6pLWOXTdkuwE3J1h0OD+wE2qatu2qTQnya5VdfHo+SbAVlV1eeNYGhmdhnA4Q//8hGHA+lFzNZN6sUnrAJK0MaqqVzGcn/xe4HbACxwo6EeSf06ybVX9vKquSLJdEjeWau+4uSdJ3tsyiBZK8rQk70zyTeBUhkGC84GHAts3Daf5Xppk69GA6JeB85P8betQWjd4c0BV/TawA3D7qrqHAwXqkTMLJGkZJbktw+7G83ehvifw7ar6eptkGje+seHYPTf/amzehpMLaqS2khwGfBr4VFU5Zbpjcxu2JnkUsD/w98CZVbVP42gCkpxaVfdsnUO6Ls4skKTl9W8MO4XPd+XoNfVhTZIbzl0k2YJh4za1VUs8Vweq6plV9R4HCmbCDZLcAHgwcHxV/Qp7qicnJfmbJDsn2X7u0TqUNJ8bHErS8tqtqr44/2ZVnZFkt5WPoyW8DfhokiMZ3kA/DjiqbSQBv5nkciDAFqPnjK6rqrZuF02aKW8AvgGcA5yaZFeGTQ7Vh8eN/nzK2L0Cdm+QRVqSyxAkaRkl+VpV3fb6vqaVl+T3gPswfBD976r6SONIkjQ1STatKo/nk/Rrc7BAkpZRkncAH6uqI+bdfzxwv6p6RJtkkqTVJMkfMBxzufncvap6cbtEmpPkoYvcvgw4t6p+sNJ5pKU4WCBJyyjJzYH3AVcDZ45uH8Bw9vVDqup7rbJpvSR3BV4N/AZDbdYAP3eau6SNQZL/BG4EHAS8ETgE+FxVPb5pMAGQ5APAgcApo1v3Bk4H9gReXFVHN4omTXCwQJKmIMlBwB1Gl1+qqo+1zKNJSc4A/gg4hmEw57HAbavqeU2DSdIySPLFqtpn7M+tgGOr6n6tswmSnAg8oaq+P7q+OfB64AnAqVV1hw39e2mluMGhJE1BVZ3C+m8M1KGq+lqSNVV1LXBkkk+3ziRJy+QXoz+vTHJL4FLg1g3zaNJucwMFIz8A9qyqHyf5VatQ0nwOFkiSVqMrk2wGnJ3kFcB3gS0bZ5Kk5fL+JNsCrwTOYthp/41tI2nMJ5O8n2F2G8DDGE6t2BL4abtY0iSXIUiSVp3RMWLfZ9iv4K+BbYDXVdXXmgaTpGWW5IbA5lV1WessGiQJwwDB3RlO5DkNeG/5wUydcbBAkiRJ2ggsscv+OlV17EplkTT7XIYgSVp1ktwdeCGwK2O/C6tq91aZJGkZPGADrxXgYEEHklzBUI9xlwFnAM+qqgtXPpW0kDMLJEmrTpKvMiw/OBO4du5+VV3aLJQkaVVI8iLgO8DbGZYh/BFwC+B84C+q6t7t0knrOVggSVp1kny2qu7SOockTUOSmwCHAvdg+Ab7NODFDoj2YbHfQUlOr6q7Jjmnqn6zVTZp3CatA0iS1MApSV6Z5MAkd5p7tA4lScvkncAPGTbRO2T0/F1NE2nc2iQPT7LJ6PHwsdf8JlfdcGaBJGnVSXLKIrerqg5e8TCStMySnFlV+8+7d0ZVHdAqk9ZLsjvw78CBDIMDpzMsjfs2sH9VndYwnrSOgwWSpFUlySbAIVX17tZZJGkakryKYbO8uZ9zhwB7V9Wh7VJpQ5Lcuao+3zqHNM7BAknSqpPk1Kq6Z+sckjQNo932t2T9Bq5rgJ+PnldVbd0kmCYk2Ythc8NHApc580O9cbBAkrTqJHk+8AuGNbxzb6Cpqh83CyVJyyBJgJ2r6pLWWbRQkl0ZBgceCVzDcITvAVX1jZa5pMU4WCBJWnWSXLTI7aqq3Vc8jCQts8X2LFB7ST4NbMOwAeU7q+qCJBdV1a0bR5MWtWnrAJIkrTTfmEnayJ3uGvgu/RDYCbg5sANwAZ5+oI45s0CStOokeexi96vqrSudRZKWW5IvA7cDvsGw1CoMs6f2aZlLkGQbhiMtHwncFtgW+J2q+lzTYNIiHCyQJK06Sf5/e/cbqnddxnH8/TlL2ZpmaWp/ENN0Zpk2m7BMDDOlemBoywWZoCY9DKUeKJVFD5KKSqXARRiKCEqZVFjLtCWzOd1It6A//ltpLdH+rc2y5dWD333aff5sBjvnfO+d3/sFN/y+v5sDHziwA9e+13VdN3RcCJwJbKyqFY0iSdKMGfTFT1FVW+Y6i3YvyWHASrrCwRFVdUTjSNIEFgskSb03+J+em6rqnNZZJGkmJDkNOLaqbkhyKHBAVU03r0UjIMmRFnM0aiwWSJJ6L8l+wMNVdXzrLJK0t5JcBSwDjquqJUleA9xWVW9vHE3SPsQBh5Kk3knyPXYNlRoD3gjc2i6RJM2oc4GlwEaAqvpDkgPbRpK0r7FYIEnqoy8NPe8EtlTVk63CSNIMe76qKkkBJFncOpCkfc9Y6wCSJM2VJMsBqmrN0GethQJJ88ytSa4HXp7kUuAu4BuNM2kgyZIkP0myeXA+McknW+eSJnNmgSSpN5JsrKqTB88/r6q3tc4kSbMhyVnA2YPj6qr6ccs82iXJGuATwPVVtXTwbnNVndA2mTSRbQiSpD7J0PPCZikkafZtAhbRzWfZ1DiLJnppVa1Phv8ksbNVGGl3bEOQJPXJWJJXJDlk6Png8U/rcJI0E5J8BFgPnAesANYlubhtKg15JsnrGQzaTbIC+GPbSNJUtiFIknojyRPAC0y8YTCuqurouU0kSTMvya+BU6vq2cH5EOC+qjqubTIBJDkaWAWcCvwFeBy4oKqeaJlLmsw2BElSb1TV61pnkKQ58CSwbei8Dfh9oyyapKoeA9412FIxVlXbXuxnpBZsQ5AkSZLml6eA+5N8JslVwDrgkSSXJ7m8cbbeS/KxJC8DdgBfSbIxydkv9nPSXLNYIEmSJM0vjwLfZdATD9xB1xN/4OCjti6uqr/Tbas4DLgIuLptJGkq2xAkSZKkeaSqPts6g/ZofG7Oe4EbquqhTFqNII0CiwWSpN5JclNVffjF3knSvijJPey6VfA/VfXOBnE01YYkq4GjgCuSHEg3fFcaKRYLJEl99KbhQ5IFwFsbZZGkmfbxoeeFwPuBnY2yaMjgBsGngUOBx6pqx2BbxUVtk0lTuTpRktQbSa4ArgQW0Q2Wgu466PPAqqq6olU2SZpNSdZU1Tta5xAk2VBVFqg18iwWSJJ6J8nnLQxImq+SHDx0HKO7OXVtVR3XKJKGJPka8K2qeqB1FmlPbEOQJPXR95MsrqrtSS4ATgauqaotrYNJ0gzYQDezIHTtB48DlzRNpGFnAB9NsgXYTvd7qqo6sW0saSJvFkiSeifJw8BJwInATcA3gfO8oitJmm1JjpzuvQVrjZqx1gEkSWpgZ3XV8vfR3Si4BnePS9rHJTklyauGzhcmuSPJtZNaE9RQVW0ZFAaeo7sBMv6RRorFAklSH20bDDu8APjBYBvCfo0zSdLeup5uYCtJTgeuBm4E/gasaphLQ5Kck+S3dO0ha4AngDubhpKmYbFAktRHK4F/AZdU1VbgtcAX20aSpL22oKr+PHheSbfl5dtV9SngmIa5NNHngOXAb6rqKOBMYG3bSNJUFgskSb1TVVur6stVde/g/LuqurF1LknaSwuSjA8wPxO4e+g7B5uPjn9X1bPAWJKxqroHeEvrUNJk/qMhSeqdJMuB64Djgf2BBcA/quqgpsEkae/cAqxJ8gxdP/y9AEmOoWtF0Gj4a5ID6H4/Nyd5mm5rhTRS3IYgSeqdJA8CHwRuA5YBFwLHVtWVTYNJ0l4aFENfDayuqu2Dd0uAA6pqY9NwAiDJYuCfdCsTPwQcBNw8uG0gjQyLBZKk3knyYFUtS/Lw+F7rJPdV1amts0mS5r8khwOnDI7rq+rplnmk6TizQJLURzuS7A/8IskXklwGLG4dSpI0/yU5H1gPfAA4H7g/yYq2qaSpvFkgSeqdJEcCT9OtS7yM7gro16vqkabBJEnzXpKHgLPGbxMkORS4q6pOaptMmshigSRJkiTNkSSbqurNQ+cx4KHhd9IocBuCJKk3kmwCdlslH59fIEnSLPphkh/Rba8AWAnc2TCPNC1vFkiSemPQfrBbVbVlrrJIkvoryXnAaXQbEX5WVbc3jiRNYbFAktRrSV4JPFv+QZQkzaIkxwCHV9XaSe9PB56qqkfbJJOm5zYESVJvJFme5KdJvpNkaZLNwGbgT0ne3TqfJGle+yqwbZr3OwbfSSPFmwWSpN5I8iBwJd32g1XAe6pqXZI3ALdU1dKmASVJ81aSzVV1wm6+2+SAQ40abxZIkvrkJVW1uqpuA7ZW1TqAqvpV41ySpPlv4R6+WzRnKaT/k8UCSVKfvDD0/Nyk77xqJ0maTQ8kuXTyyySXABsa5JH2yDYESVJvJPkPsJ1u+vQiuj5RBueFVbVfq2ySpPktyeHA7cDz7CoOLAP2B86tqq2tsknTsVggSZIkSXMkyRnA+OyCX1bV3S3zSLtjsUCSJEmSJE3gzAJJkiRJkjSBxQJJkiRJkjSBxQJJkiRJkjSBxQJJkiRJkjSBxQJJkiRJkjTBfwFnI/YSTIt2ZQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xe4a94e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "correlations = input_var.corr()\n",
    "\n",
    "plt.figure(figsize=(14,14))\n",
    "plt.title(\"Correlation heatmap for Patient features\")\n",
    "temp = sns.heatmap(correlations, cbar = True,  square = True, annot=True, \n",
    "            fmt= '.2f',annot_kws={'size': 12}, cmap= 'coolwarm') \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So, input variables are uncorrelated."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Lets findout the strength of the concrete using linear regression and Neural Network"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Divide the data in to train and test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(input_var.get_values(), output_var['Concrete compressive strength(MPa, megapascals) '].get_values(), test_size=0.40, random_state=42)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Linear Regression Prediction "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "167.118999119\n"
     ]
    }
   ],
   "source": [
    "lr = linear_model.LinearRegression()\n",
    "lr.fit(X_train,y_train)\n",
    "y_pred = lr.predict(X_test)\n",
    "error = mean_squared_error(y_test,y_pred)\n",
    "print(error)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "NN Prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "167.062293337\n"
     ]
    }
   ],
   "source": [
    "ml_regr = MLPRegressor()\n",
    "ml_regr.fit(X_train,y_train)\n",
    "y_pred = ml_regr.predict(X_test)\n",
    "error = mean_squared_error(y_test,y_pred)\n",
    "print(error)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As you see above the error is bit high, the best way is to make your network deeper and try with the different activation function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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