Bank_Data.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np \n",
    "import os\n",
    "import matplotlib.pyplot as plt \n",
    "import seaborn as sns \n",
    "import plotly.graph_objs as go\n",
    "from plotly.offline import iplot\n",
    "import plotly.express as px\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Age</th>\n",
       "      <th>Experience</th>\n",
       "      <th>Income</th>\n",
       "      <th>ZIP Code</th>\n",
       "      <th>Family</th>\n",
       "      <th>CCAvg</th>\n",
       "      <th>Education</th>\n",
       "      <th>Mortgage</th>\n",
       "      <th>Personal Loan</th>\n",
       "      <th>Securities Account</th>\n",
       "      <th>CD Account</th>\n",
       "      <th>Online</th>\n",
       "      <th>CreditCard</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>25</td>\n",
       "      <td>1</td>\n",
       "      <td>49</td>\n",
       "      <td>91107</td>\n",
       "      <td>4</td>\n",
       "      <td>1.6</td>\n",
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       "      <td>34</td>\n",
       "      <td>90089</td>\n",
       "      <td>3</td>\n",
       "      <td>1.5</td>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>39</td>\n",
       "      <td>15</td>\n",
       "      <td>11</td>\n",
       "      <td>94720</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>35</td>\n",
       "      <td>9</td>\n",
       "      <td>100</td>\n",
       "      <td>94112</td>\n",
       "      <td>1</td>\n",
       "      <td>2.7</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>35</td>\n",
       "      <td>8</td>\n",
       "      <td>45</td>\n",
       "      <td>91330</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID  Age  Experience  Income  ZIP Code  Family  CCAvg  Education  Mortgage  \\\n",
       "0   1   25           1      49     91107       4    1.6          1         0   \n",
       "1   2   45          19      34     90089       3    1.5          1         0   \n",
       "2   3   39          15      11     94720       1    1.0          1         0   \n",
       "3   4   35           9     100     94112       1    2.7          2         0   \n",
       "4   5   35           8      45     91330       4    1.0          2         0   \n",
       "\n",
       "   Personal Loan  Securities Account  CD Account  Online  CreditCard  \n",
       "0              0                   1           0       0           0  \n",
       "1              0                   1           0       0           0  \n",
       "2              0                   0           0       0           0  \n",
       "3              0                   0           0       0           0  \n",
       "4              0                   0           0       0           1  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "file_data = r\"D:\\5.DataAnalysis\\2\\Project 4--_ Finance Data Analysis-20230402T013311Z-001\\Project 4--_ Finance Data Analysis\\Bank_Personal_Loan_Modelling.xlsx\"\n",
    "Bank_data=pd.read_excel(file_data,1)\n",
    "Bank_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "ID                    0\n",
       "Age                   0\n",
       "Experience            0\n",
       "Income                0\n",
       "ZIP Code              0\n",
       "Family                0\n",
       "CCAvg                 0\n",
       "Education             0\n",
       "Mortgage              0\n",
       "Personal Loan         0\n",
       "Securities Account    0\n",
       "CD Account            0\n",
       "Online                0\n",
       "CreditCard            0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Bank_data.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5000, 14)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Bank_data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Drop unnecessary columns\n",
    "Bank_data.drop(['ID' , 'ZIP Code'] , axis = 1 , inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
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       "      <th>Income</th>\n",
       "      <th>Family</th>\n",
       "      <th>CCAvg</th>\n",
       "      <th>Education</th>\n",
       "      <th>Mortgage</th>\n",
       "      <th>Personal Loan</th>\n",
       "      <th>Securities Account</th>\n",
       "      <th>CD Account</th>\n",
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       "      <th>CreditCard</th>\n",
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       "      <td>1</td>\n",
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <th>4</th>\n",
       "      <td>35</td>\n",
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       "      <td>45</td>\n",
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      ],
      "text/plain": [
       "   Age  Experience  Income  Family  CCAvg  Education  Mortgage  Personal Loan  \\\n",
       "0   25           1      49       4    1.6          1         0              0   \n",
       "1   45          19      34       3    1.5          1         0              0   \n",
       "2   39          15      11       1    1.0          1         0              0   \n",
       "3   35           9     100       1    2.7          2         0              0   \n",
       "4   35           8      45       4    1.0          2         0              0   \n",
       "\n",
       "   Securities Account  CD Account  Online  CreditCard  \n",
       "0                   1           0       0           0  \n",
       "1                   1           0       0           0  \n",
       "2                   0           0       0           0  \n",
       "3                   0           0       0           0  \n",
       "4                   0           0       0           1  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Bank_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1-Provide a summary of the dataset using the five-number summary with visual distributions (such as box plots, histograms, or kernel density plots) of the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>Experience</th>\n",
       "      <th>Income</th>\n",
       "      <th>Family</th>\n",
       "      <th>Education</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>5000.000000</td>\n",
       "      <td>5000.000000</td>\n",
       "      <td>5000.000000</td>\n",
       "      <td>5000.000000</td>\n",
       "      <td>5000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>45.338400</td>\n",
       "      <td>20.104600</td>\n",
       "      <td>73.774200</td>\n",
       "      <td>2.396400</td>\n",
       "      <td>1.881000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>11.463166</td>\n",
       "      <td>11.467954</td>\n",
       "      <td>46.033729</td>\n",
       "      <td>1.147663</td>\n",
       "      <td>0.839869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>23.000000</td>\n",
       "      <td>-3.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>35.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>39.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>45.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>64.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>2.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>55.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>98.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>67.000000</td>\n",
       "      <td>43.000000</td>\n",
       "      <td>224.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>3.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Age   Experience       Income       Family    Education\n",
       "count  5000.000000  5000.000000  5000.000000  5000.000000  5000.000000\n",
       "mean     45.338400    20.104600    73.774200     2.396400     1.881000\n",
       "std      11.463166    11.467954    46.033729     1.147663     0.839869\n",
       "min      23.000000    -3.000000     8.000000     1.000000     1.000000\n",
       "25%      35.000000    10.000000    39.000000     1.000000     1.000000\n",
       "50%      45.000000    20.000000    64.000000     2.000000     2.000000\n",
       "75%      55.000000    30.000000    98.000000     3.000000     3.000000\n",
       "max      67.000000    43.000000   224.000000     4.000000     3.000000"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stats_df = Bank_data[['Age', 'Experience', 'Income', 'Family', 'Education']]\n",
    "stats_df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "#plotting using px \n",
    "fig = px.box(data_frame=Bank_data , y=['Age', 'Experience', 'Income', 'Family', 'Education'])\n",
    "fig"
   ]
  },
  {
   "attachments": {
    "newplot%20%2827%29.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![newplot%20%2827%29.png](attachment:newplot%20%2827%29.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x000002BF50AD0DF0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002BF509F1310>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x000002BF509F4760>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002BF50AC4BE0>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x000002BF50A2C0D0>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x000002BF50905520>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "stats_df.hist(figsize=(20 , 20) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#From the analysis and the graphs, it is obvious that there are some negative values in the experience column\n",
    "#This needs to be fixed by attaching the mean value of the experience instead of the negative ones\n",
    "plt.figure(figsize=(14,8))\n",
    "sns.distplot(Bank_data['Experience'])"
   ]
  },
  {
   "attachments": {
    "newplot%20%2827_1%29.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![newplot%20%2827_1%29.png](attachment:newplot%20%2827_1%29.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "In this data we have 624 negative experinces which will corrspond to 12.5% of the data\n"
     ]
    }
   ],
   "source": [
    "neg_exp=Bank_data[Bank_data['Experience']<0]\n",
    "print('In this data we have {} negative experinces which will corrspond to {:.1f}% of the data'.format(neg_exp.size,neg_exp.size/Bank_data['Experience'].size * 100))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "#We can use np.where to replace the negative values with the mean of the data\n",
    "np.where(Bank_data['Experience']<0,Bank_data['Experience'].mean(),Bank_data['Experience'])\n",
    "Bank_data['Experience']= np.where(Bank_data['Experience']<0,Bank_data['Experience'].mean(),Bank_data['Experience'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.figure(figsize=(14,8))\n",
    "sns.distplot(Bank_data['Experience'])"
   ]
  },
  {
   "attachments": {
    "newplot%20%2827_2%29.png": {
     "image/png": 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NjPbnyq3zJ0hMeIj9KO+XEhMmK3JT5O9XTDG//x+umiaXzUiRjp5++fOeKln7ntYHKJJfby2R9wvrpLypyxQVBAAAzkb4BwD4vbr2HvnNtlJ5YlOxaAweHu3XtfW+uo1eoPX7zk6KkmvnpFt/nmmmI+C+5Tly8cR4s3PAG3ur5an3hwoFPrO5WN7aVy37j7VKa3ef/R0AAICTsNWfj2DbDgCjzV+3+jtgBd4/FFSY6fE6Yv6NRRNNQD6f0O8L28Z1ufqlpKFTjtRZR32HHLWOyuZuc19SdKhMTIyUSdahtxMTImVCQoRZVuBUbPUHwEnIDPCE8O8jeCEDGG3+Fv61Cv77h+rkj7sqpaiuXW5bMEHuWjhRMuMj7EecO18Lkn3W30F5Y5fpBCht7JSKpm7r6JLWnj7R8gapMeEm/GfE6REumdaRYf39JEeHmS0InYDwD8BJyAzwhPDvI3ghAxht/hT+df37hk8r5Q+7KiQqNFjuys+SG+ZlSKR1fiF8OUjqx4GmTpcJ/+XN3VLe2GlmBFS19kin9felHxZiw4Ot8B8u6bHWERcuadatdhCkxYZJQlSoWWrgawj/AJyEzABPCP8+ghcygNHmL+G/tq3H/Flf3V0p87MT5FuLJsqSqUkjElydFCTd7kGpa++1wn+3VLf0SLXetg7d1rX1msfoX1lCZOhQJ0BsmOkUSLUO7QxIiwmX+MgQr6+ZQPgH4CRkBnhC+PcRvJABjDZ/CP+Ha9vlt9tL5W+f18nX5qabrfGmpkTb9144pwfJ9p6+oQ6Alh5TJLGmzbpt6zUdKs1dLtFPFJr1k6I1/IeZjoChDgHr2nQKhJvZA97UIUD4B+AkZAZ4Qvj3EbyQAYw2J4d//VG3o6TJBP99la3y9UUT5VuXTDJr10eSvwVJt/X32tzpssJ/r+kM0E6AmlbtGLCurbbmbpf1ly8SGBhg/q51RkBqzFBHgC4byNRaAvHhEhYcZH/HsUf4B+AkZAZ4Qvj3EbyQAYw2p4Z/Lez31wM18tLHZWYbu+8syTZ791/o+v7TIUgOLRdo7HRZ4b9Hak2HQK/Utur50AyBNus50A8eIUEBZlaAFhCcYB1aaDEzPtzsMBA1hrsL8JwBcBIyAzwh/PsIXsgARpsTw39Hb7+89kmlCf5amO6eJZPkqllpEhwYaD9iZBEkT2/APSgNHUPhX2cE6HIBnSGg9QSqWrqlb2BQdCFAckyYFf4jvthuMCFSshIjRnVmAM8ZACchM8ATwr+P4IUMYLQ5LfzryPMrO8tlvRb2mxQv3106WRZmJ4zqenOC5Nlz9btNJ4CGfz2O2TsL6G4Dna5+CbKeJ91e0HQEJEVKTlKU5CRHSUpM2Ig+hzxnAJyEzABPCP8+ghcygNHmpPBfVNtuRvvf/bxWrp2dbqb6T00ducJ+Z0KQPH+6XKC+o9eE/wp7q0G9rbSue/rdEhEaZDoAJidHSk5ytOkIyE6KlJCgC5vFwXMGwEnIDPCE8O8jeCEDGG1OCP/6I22nKexXJp9VtsjX8yfKNy+ZZEaLxwJBcuT0u91maYB2BpQ2dklJQ6eUWocWE9S4n5kQIVNToiQ3NUampQ11BpzP8gCeMwBOQmaAJ6Oz6BEAgDGmhf027q+RX/6tSI7Ud8iDl02Vv1ueM2bBHyNL6zJkJUTK0qnJZmeGR6/KtY7pcv+KKXJFXqoV9APlo+JGef7Do+Y5f3JTsbyxp0oOVrdJT9+A/V0AAMAwwj8AwOd19vbL73dVyForBOpycA2K31g0cUyrxmN06e4MszJj5YZ5GbJ61TTTEfDQFdPMdWx4sHx8pFHWbdWOgMPy5KYi+fOnx+RAVSsdAQAA2Aj/AACfpoX9NPQ9+8ERyU2LNqFQ1/kHX+BacHivoMAAUwhw1YxUMxNAn/OHr8iVm+ZlSnxkqFn68euPSsyMgCfeK5INn1TK/mOt0u2iIwAA4L/4ZAQA8FnFdR3y1PvF8vudFXLFzFQTAi/JSRzViv7wLvpcZ8ZHyGUzUuTvV+SYWR+PXJkrt1ycKcnRYVJQ1iy/2VZqZgTQEQAA8GeEfwCAzxku7KeBblNhnXzzkony0OXTZNoYVPSH99KOgIy4CFmRmyJ/d+kXHQG3zZ8gqTHhsrv85I6A1z49ZrYZ7Btw298BAADnIvwDAHyKBrWhwn6Hpah2qLDf3y+fIqmx4fYjgKGOgDTr38TyacnyvWWTTUfAmhM7Asqa5cWPSuS9wlrTgbSnopmOAACAoxH+AQA+o6XLJS9tL5O17xWZ6zVWoPsmhf3wFbQjQDuHLj2hI0BnBNx6caZEW/92yho75aPiBnmvsE7etzsCKpu7KBYIAHAUwj8AwCccre+QpzcfkRe2lsjszFizvv9rcyjsh3Mz3BGwPDdZvn9pjlw5M83Ui7h4YrxEhwVJaUOnbDvSaDoC9NhZ0mi2jmzr7jPLTQAA8FV8YgIAeDUNXNutMKaV29/aVy03X5xppm9T2A8XSv/9xEaEyLTUGFk2Ndl0BFw+M1UuyoqXBKu9trXHFAzcdFA7AmplS1G9fFbZIhXNXWZ7SToDAAC+hPAPAPBaWpFd92vX9f1a2f+BlVPMGv/spCj7EcDIGO4IyE3TjoAkuTIvzTpSTSfTxMQIK+wPyMHqtqHlAdoZcLBWthY1yL5jrWbZQFOnS/qpFwAA8GKEfwCAV9I11+s+PGq28osMCzbr++++ZJLEWQENGE3aEaB1JLSTKT87Ua6YOdQRsDI3ReZOiJPk6FBp6e6TA1Wtx2sF6MwAvd12ZKhDoKShQ2pau6W1yyW9/QPMEgAAjLsA64cRP418QH5+vhQUFNhXADDyXtlRbp+NvrsXT7LPvsxt/VjacbTJ7Me+/WijXD4jVe7Mz5J5Vujy9mn+Y/l3qDz9PY60fZWt9tnom5sVZ5+NvnN9zvRjU0+fW5qsUN/c6TKdAO09evSb276BQdF/pUGBARIRGiQRIUESbh0RIYHWdbCsnJ4s4cFDbWFWm96GBgVKoPV463/WobdD5/oBTV8P+kntdLfuL7Wf3KZHSHCA+f5h1q8ZGhxojkjr95UQGWrOATgLmQGeEP6/QnFxsbz99tvidrtlwYIFsnz5cvueL2zcuFGKiookJCREbr31VsnIyJC2tjZ57bXXpKOjw3xYXbhwoSxevNg8fvPmzfLJJ59IZGSkub7yyislNzfXnJ8JL2QAo80bwr+Gp7f21Zjgr+e3zs8yFdkvZBu/sQytOuI7lsYy/HtL59BIG4k/l6vffbwDoM2+7XT1S49rQLr7hg59jH7gSosNs1K5leztfqwQK5iHBllh34T/kzsA9PEnhvpTb4c7AE5sPx39NcLs4D8U/oOt8B9iOgASouxb68iMj7Bea2Hm1wbgm8gM8ITw74H+1axZs0ZSUlIkOjpadu/eLf/1X/9lrodp6P/pT38ql1xyidTW1kp4eLj827/9mxw7dkxeeukliYmJEZfLddLX/uQnP5H9+/fLVVddZb4H4R+ANxjvcHekrkM2fFopf/msWqanxcgdC7PMqP+Fjk6O5Z9rrBH+L9xo/bkGrDSuWwWa8O8aMOdd1rEwO8Gc6+wBve3td4vLLAuwvsb6P70dCvU6g8D6z+4MGL7VzgEdVDj5/OTHHL+1fh+uAf3+Q4f+Wnp0ufpNjYK+E2oU6AwFDf/ZSZEyOTlKJidFyaTESLbRBHwMmQGeEP49KC8vlzvuuEPeeecdiY2NlXvvvVfuvPNOue222+xHiAn0Gvofe+wxqayslBtuuEE++ugjc197e7uZBaDh//LLL5fHH3/cjP5r+NfOhH/8x380jzsbvJABjLbxCncagD44VC9vflYleypb5NpZ6XL7giyZlRlrP+LCEP5HBuF/ZJz4Z9OPYP3uwaFZAcfD/xej+hreh8P96UL+yedDjzmVfj9dijAU/oc6G4bCf5+06NIFc/RJY4fL7GKgOxzoL5waE2aF/yiZkhJldj+YkR5jljIA8G5kBnjCYi8PCgsLJScnRxISEiQoKEiWLVsmu3btsu8dotcrV64051lZWRIaGipVVVUm3GvwV11dXdLf3286EIbt3LlTnnnmGXn99delp8f6QQtgROkH3abOXlOFW4ty7bVC5d6KFtlT3iyfWscnZdZh3Wr1bt3Xu7atx0zXpVr32NKiaFrU74n3iqSuvVfuXzFFfnT5tBEL/oA307CuU/J1dD06PNgUs4yPDJXEqFBJjg6TJOvQc23T+2LCQ8xjddq+qRUQHGi+XkP56YK/0nZ9nH5//X46uq9bG+ouBtfMTpdvLJpkdtB49Kpcc+j5dVZ7UlSYee98aXuZ2W3jeet1uqu0yXTWAQB8EyP/Hqxfv96s91+3bp251mn8GtqffPJJc61uvPFG+Zd/+ZfjtQB0Cv/Pf/5zs8Zf6aj/L3/5S1M7QL8uLCxM/vKXv8jhw4fN+aFDh0ynwje+8Q3z+BPpUgE9lM4wOHjwoDkH8AW3e1DqO3qluqVbqlp7pME67+jpl47eoUPX3uqtjq7p0Jq+4+mbnnnrsz4UmyJcWozL+jCtxbkirfMY8yE51Hz4PfFWP2w72ViOgN6xcIIZ7f/LvmrZU9EiK6Ylyw3zMk0gGenRRUb+RwYj/yNjLP9s50vfH+vbe6W0sUsKq9tMR+nh2nZJiAqVBZMSzNKFBdYRG87OG4C3YeQfnhD+PfjrX/8qL7zwgvzxj38017/61a/MWv6f/exn5lp961vfku985zty/fXXm+tFixbJyy+/LNOnTzdFAn/zm9/Ihx9+KP/8z/8seXl55jGdnZ3Hi/1pUcD//u//Nr/WqQj/wOnpWtVDNe1yTAO/dVRboV/Dv47cmxEw67/hka4YHVGzjhDrWiPl0ODY0FRZffvr7nNLt6vfrMnVtbld1m2fTsG17teH6khbkvWBd2jELFyyEiKsI1ImxEc4bi3sWIQg/TvXDprgoEDZaAV/HcG8fl66XD8n44KK+nni5PCv286NlbEsZkj49x76mi1r7DIdALvLms2/g2DrfXZRTqKZIXDRxHiz7ACAdyD8wxPCvwfDa/7fffddU7hP1/zr9e23324/Qsw6/rq6ui+t+ddp/6+++qoJ9z/60Y9k6dKl9leI2QFA71c6s0BnCmzatMlcnwkvZPg7Xat6uKZDPq9ulQNVbWYUqq9/0IT4lJihqawZceEmQMZaoV8D/1D4D7HD/1CnwPBn1KHwL8eLcZ0Y/lu7+6Sxs9esgW3stA4rrOoomE531a9Ls36NCfGRpiNAC2JNTY02nQG+vh52tEOQ/h0fqmmTwpp201GzbGqy3DgvQy6ZkmiFidFbhebk8O9UhH/vpO+D2gmg0/915o6+7147O9060kwHKYDxR2aAJ4R/D3Tk/pFHHpG0tDQT1nV9/9q1a6WsrMzcry8unb6vBfy0kJ92Auia/3//9383HQc333yzZGdny9e+9jXz+OGq/r/97W/N6L/SugLz58+X733ve+b6THghw1/pyL6u19fAf9A6atp6zBrYvPQYmZwcbUbjM+IizK2O0o8kfXts7+03nQD6oVd/LxVNXWbGQWVzt9nKS/N+dlKUTE2JlmmpQ0d2YqQZ2fY1oxWCtOq51l7Q0K+dNrp2+Z4l2SY0pMeNzmj/iQj/vofw793auvtkU2GtvH2g1szCWjk9Wa6bnSGLchJGtSMPwFcjM8ATwv9X0K38dHRe/5o0pK9YseL4C0pfXOqtt94ya/p1n/9bbrlFMjMzTfh/8cUXJTU1VYaL8AyHf50NUFNTY9ri4+PlpptuOj4T4Ex4IcOXjMS+6joKX1zXYdaDa9EpXcev+0/r9lOzM2NlZnrs8Wn3c7PGbuqzFg3UwnSVzV2mA0BDbV1brxnJ1s4H3SJrinXoLATtlNA9tHXGwfkYyz+XGukQpO+bOnNCiypq8NeR/+npMTIrI1b+6doZYzZTgvDvewj/3k9f34dq22Xjvhp59/Ma8/533Zx0ueXiTEmMYhYAMF7IDPCE8O8jeCHDl1zIh2mttl9qBepDtR1ypL7DFOObmhJlppdmWmFai/GdWtV6PIOCjmrrrgLaIaCHzhDQmQKD1n8p0WGSER9uft/aEaAFBc/FWIeEkQxBunSiuK7ddOBoJ4kuj5hphf7c1GhTONHJ4Q4XjvDvO3TbwC2H62Xj/hqzi4p2ANy7dLJMtF7zAMYemQGeMDcLgFfQfkgdTd9SVC/vHawzW8BNt4LilTNT5bLpqWakPzYi5EvBf7zp6HVKTLjMzoyzfp8pcmVeqqyakWL9fmPENeA2MxfeK6yzjlpTLKu6tdt0GDhVZ2+/fFZp/ZkP1sqHRQ1mBseSKUnW30uaKU7n9B0TAH+jRTuvm5Mhj141XW6+eIK8+Vm1PLmpyMz4AQB4F8I/gHHXd0JI1mn1WrTvihkaolNlSkq0zxTS04rXui1gXkas6bC4cmaaXDo1WTLjwqWmtUe2HWkwHRubD9WZD8YtXS7T6eEEOqX/c+vPpKF/86F6syODVgHXv4OlU5NMnQYAzpWTHCUPrJwi3780Rz4+2ii//Nthc8sEUwDwHoR/AONK1/JvO9Io71uBWDfgX5GbYkb7Z2X69iixdlhoMbv5kxLMqLceuj+2/pl0nax2AGhnx3brz17a0Gl2EvBFOr1ft/7SmQ3vW38eLYqYlxFjZkCsyE02U3/ZBgzwD1rM896l2fKjy6dJeWOX/PJvRfLO57WOnu0EAL6E8A9g3NS29ZjQr6NDOUlRJjAuzE4w0/udRAO/jootm6rT31Nl1fRUyU2LMdsK7i5vNsFZR8w/tc5rfGBZgI7kaW2D3WVN5vf9weE6OdbcLVNS9DlMM7MecpKjqfoN+CF9v7tz4URZc1Wuea9Y+7ci2fBJpfS73fYjAADjhYJ/PoLiHfAlX1VAy2297Wgxv10lTWbbPB0dX2SF/rjI85sa7ovFwfSDsO4SUN3aY0bLdQvD3v4BSbD+DtJjw02Bw79fkSNZCZFeUxVfp/br79NsedjcZf3+e0yFby3mp9sdZiVEnPVsDQr+wROtDzFWdObKWHJawb8z0Y+XHx9tkhe2HpXDtR3yj9dOl5vmZXpd3RbAacgM8ITw7yN4IcOXeApbOqqt+/bvtIK/ni+anGDWhocFn/8Uf18PklotW2sCVLV2m1vdNUA/HudPTjQ7HegsgWkp0VbAjpTgoNEbTT/dn83V77Z+Pz3m96XBX2+1iF9SVKiZ0q+hX2sanOvvi/APfzWWHRtjvV3o6ew/1iqPbSw07yP/+rU8UxCVDgBg9JAZ4Anh30fwQoYvOVPY0hF/Lei3qbBOUmLC5JKcRJluBdsLXRPulCCpb8ctXX1mNoDuChAZFiwVTV3mvokJETItNdoUQJyg2x5ah/4djuSsAP2zud2D0tbTJ83W76O5y2VG92vbeqXdaosIDZb02DBJj4swo/z665/vc0f4B0bfWL7O9lWeeQbFrtImefGjEkmKDpP7lufI5KQo+57z4w2dGoC3IjPAE8K/j+CFDF9yurClbzUHqtpM8Set/H51XppMsALkSHBikNRZEcumJZl98oePssZOc190WLAJ/3oMdQSEW3+nYRIbESyx4SESGRr0lSNr+nzoCL4W7Gvr7jdBf/3uSmnudJkOCL3uc7tNuE+LDZc0K+hnWL+WLkkYiUKMhH9g9HnL60zfbw7XtsvbB2qs968QuX5Ounk/OV9j+ecCfA2ZAZ4Q/n0EL2T4klM/BOrbjFa4f+dArUSGBcm1s9NlYkKkfe+Fc2qQHP5zaUdAZXOX6QAob+oydRKqWnrMqPyg9V9IYKAkRIWaQomx4UMdAHoeZf1dB5gFBNZzYP5fWaHfZYf+nn47/PeZwH+spct0GsRZXx8fGWK+p3bUaODXDoeRnKpL+AdGnze9zvTngNZX0J8DGXHhcu2cdEmODrPvPTeEf+DMyAzwhPDvI3ghw5ec+iHwSF27/PXzWjOKfO3sNFMJfiQ5PfyfqqO33xTdO/Fo6e43IV6n53da4X447g+H/xPp8gsVGRpsOgl0e664iGCpbO42BQcTrOAfb92GjGJ9AcI/MPq87XWm7z27S5vlvUO1po7JNbPSz2t3F8I/cGZkBnhC+PcRvJDhS078EKhT1f96oMYUjtMRf123PtLFnvwt/J+qb8B9fAS/vaffrNnX86FOgC8M/61rcUVdIqChfzj862wBnfY/Vgj/wOjzxtdZv/V+9XFJk2w+VGe2dr0qL+2cOxoJ/8CZkRngCZswAxg1Whn+vcI6s5/9FTNTRyX4Q8wHZ50+q8UAdeeEFbkpcsO8TPl6/sSTjrvs4+aLM2XVjFSzxeJU62v0a0OD+XEAYPTpziCXTE6UBdb7T0Fpk1kKwDgUAIwNRv59BL148CU6AtTV2y9v7K0ya9R1bee8CXGjFvz9feR/pIzln83J+7gD3sKb3xt1ttKrn1SaWUp3LsySrHOoA8PIP3BmZAZ4Qvj3EbyQ4Ut+93GZbDlcLx9Yh07pXDo16YK38/OE8D8yxvLPBmD0eft7Y0lDp+kA0KKit86fYAqLng3CP3BmZAZ4wjxPACOuqLZdth9tlNmZsWZN52gGfwCAb5qcFCkrpiXL0foO+dj6maE7mwAARg/hH8CIKm3olPcP1ZsCcpdNTxmRPeEBAM6jS8EunhRvapXssML/weo2+x4AwGgg/AMYMZ29/fLcliPS2NErl89IkZSYcPseAAC+THcf0SKlKTFhZgeAmrYe+x4AwEgj/AMYEVo+5LVPj8n/flYti6ckyYz0WPseAADOLDEqVC6fkWq2J/3gUJ309J28TSkAYGQQ/gGMiN1lzfL8h0dliRX89QgKZJ0/AODsTE2NlmVTk+Tz6jZ26ACAUUL4B3DBmjpd8tSmYgm2Av9Dl08764rNAAAoLQybn50ok5Oi5KPiBmno6LXvAQCMFMI/gAui0/03fFIpO0oa5YGVU2Re1tjt3w4AcI6I0CBTKLajt1+2FTdQ/R8ARhjhH8AFOVrfKb/dXibLc1PkposyTfVmAADOx+TkKLNF7J7KFimu67BbAQAjIWBQh+3g9fLz86WgoMC+As7dvsqRX0M5YL19vLKjXN78rEr++dqZ5gObGuv1mncvnmSfjT79846VsfxzqbH8swEYfXMnjN1MrJF832/ucsnvPi6TsOBA630w+0tLycb6vRHwJWQGeEL49xG8kHGhRiPYHanvMN93QXa8fG1OhlmzOR4I/yOD8A/AW+ytaJHXPq2UVTNSzVKAE2eVEf6BMyMzwBOm/QM4L7oV04eH682IjFb3H6/gDwBwnryMWJlpHTtKmqSqpdtuBQBcCEb+fQS9eLhQIz2qq1v7vbHnmFw/N8Ps6z+efHVq61dh5B+AP6tq6ZLffVwuExMj5Y4FWRIaPDRmxcg/cGZkBnhC+PcRvJBxoUYy2LV0uUyRv8jQIPn24mxToRkjj/APwJ/pR9QtRQ3yfmGd3Dp/glw8Md60E/6BMyMzwBOm/QM4J/phbGdpkynItHJ6CsEfADAqdJ2/FpLNiAuXrUX1ZgtAAMD5I/wDOCfHWrrNlP/ZmbEyNSXabgUAYORpXZnl05Klrr1XPqtssVsBAOeD8A/grLndg/JRcYMp7qcfxoICKfIHABhduWkxMiUlSj4+2mSWnQEAzg/hH8BZq2zpksKadrPuMi023G4FAGD0aKG/5dNSpK27z8w8o1wVAJwfwj+As+K2Pmx9fLRRwkICJT874aQ9lwEAGE05yVEyMz1GCqzwX9LQabcCAM4F4R/AWalu6TGj/hdNiJfEqFC7FQCA0afLzC6dliyufre89HGZ6ZAGAJwbwj+Ar6RTLHXUPyQwUPInM+oPABh7ExIiZO6EOHljT5V8XtVmtwIAzhbhH8BXqmnrkc+r28yHruToMLsVAICxo8Vml05NkuCgAHnxoxLpH3Db9wAAzgbhH4BHOuq/42iT9aFLZFFOIqP+AIBxkxoTJncsyJJ3DtTKJ+XNdisA4GwQ/gF4pHsrH6hqldmZceZDFwAA40U7oL91ySRJiAqVdR+WSG//gH0PAOCrEP4BnJGO+u8saRL3oMjiKYz6AwDG38TESLl78STZUlRvfkYBAM4O4R/AGTV09Mq+Y60yKyNW0tnXHwDgJW6fP8H8XPrNtlLpY+0/AJwVwj+A09JR/4LSZul3u2XJlCRG/QEAXiPVCv535U+UbcWNsqe8xW4FAHhC+AdwWs1dLtl7rEVmpsdIRjyj/gAA73Lr/AmSGBUqv91eKgO6Pg0A4FHAoA7vwevl5+dLQUGBfQWn2FfZap+NPp2+fy42H6qT963jvuU5Mikxym7FWNI1rWPplR3l9hkAeK8T3xt//nahvLS9TF6+f7HMy4q3WwH/RWaAJ4R/H8EL2Zm8NWz19A3IM5uPSFxEiHx32WQJ0n3+MOYI/wDwZSe+N5Y0dMjXn/1YLp+ZIo/dMU8CWaIGP0dmgCdM+wfwJUfqOkyxv0WTEwn+AACvNTkpSq6fmyHvfl4rRbUddisA4HQI/wBO4nYPys7SJkmODpVpqdF2KwAA3keL0Q7PBPj9znJTrBYAcHqEfwAnqWnrltLGTrl4YrxEhAbZrQAAeKfctGi5Oi9N3txXbX5+AQBOj/AP4CSflLdIcGCgzKVwEgDAB+g6/3uWZEu3a0DWF1TarQCAUxH+ARzX1tMnB6raZHpatCRFhdqtAAB4t9kT4mTVjBT5854qOdbSbbcCAE5Etf+vUFxcLG+//ba43W5ZsGCBLF++3L7nCxs3bpSioiIJCQmRW2+9VTIyMqStrU1ee+016ejoMOvRFi5cKIsXLzaP7+7ulvXr10tLS4vEx8fLXXfdJeHhnvdRp3KnM3lbdfUdJY3yv3ur5O8uzZEpKaz3H29zrQ+zY+lct4MEgPFwpp1QdpU0yb2/3ikPXzFNfnj5NLsV8C9kBnjCyL8H2i/yxBNPSHNzswwMDMizzz4r9fX19r1DNPS//PLL5ryyslLWrVtnztvb26W6utqc9/b2ypNPPnn8a999913ZunWrOddbvQbGW9+AWwpKm2VCfIRMTIy0WzGeNIyP5QEAvuziSfGyZEqS/LGgQpo7XXYrAGAY4d+DiooK2b59uzz00EPyyCOPmM6A4dA+7M0335SsrCxz/+rVq82Ivo72x8XFyXe/+1350Y9+ZI6SkhI5evSo+ZoXXnhBbrvtNnn44YfN7XCHATCeyho7pbq1W/InJ0hIEG8NAADfoj+7vrMkW8qbumTzoTq7FQAwjE/4HhQWFkpOTo4kJCRIUFCQLFu2THbt2mXfO0SvV65cac61EyA0NFSqqqokOjraTP9XXV1d0t/fL7GxseZ69+7dx5cP6K1en462P/fcc+bo7KR6LUaPdmztKm2WmPAQmZk+9O8UAABfs3hKouRlxMorO8ult3/AbgUAKMK/B7pufziwKz3X6fwn+qrHuFwuE94vuugimTJlimnTmQHaOaD0lmCP8dbQ4ZLiug6ZMyHWdAAAAOCLosKC5Rv5E2VPRYt8Wt5itwIAFOHfg5iYGBPuh+m5tp3I02O0SODvfvc7OXjwoPzDP/yDhIWFmXYN/NoBoPQ2KirKnJ9KiwQ+8MAD5jjTY4CR8Flliwy4B2X+pAS7BQAA33TtnHRJjg4zRXWpaw0AXyD8e5CXl2fW6mtVfi34t23bNlNB80SLFi2SLVu2mHMt+Kcj/ZmZmeZaq/1v2rTJhHf9XsN014ATC/5pyAfGS2/fgOytaJHJSZGSHut51wkAALxdmvWz7Pq5GfLB4XopaWB2JQAMI/x7oGv4dXs+rdSvVf+193jFihVm+4zhLTRuvPFGKS8vl7Vr18ozzzwjt99+uxnZ17b/+I//MEsA9u7da3YK0J0B1H333ScbNmww31dv9RoYL2WNXdLQ6ZIF2QkSGBBgtwIA4LvuXJgl/W63vPbpMbsFAED49yAwMFDWrFlj9uLXgn9azT8lJcW+d8j06dPlnnvuMXv5a2fB/fffb98jppL/ddddZ1994Zprrjmp4N/VV19tzoGxph1an1Y0S2xEsExlX38AgENMT4uRZVOT5PU9VdLU2Wu3AoB/C7A+/LMYygfocoPh2QZwDl2POJ7auvvkyU1FMjszVm6dn2W3AgDgve5ePMk+80y3+7vvfwrkP++YK3cunGi3As5GZoAnjPwDfuxwXbt09Q3IRRPj7RYAAJzhkpxEmZURK/9vZ4X0WD/rAMDfEf4BP+XWKf/lLZIaEyZZCZF2KwAAzhAZGizfWDTR7GjzSXmz3QoA/ovwD/ip+vZeqWzuknkT4iQkiLcCAIDzXDMrTVJjws0yO+30BgB/xid+wE8dqGo1t7Mz48wtAABOkxobLjfMzZAtRfVytJ5t/wD4N8I/4If6+t2yr7JVJiVESnJMmN0KAIDz3LFwggy4B+WNvVV2CwD4J6r9+wgqdzrTeFX7L6nvkHVbS+T2BRNkYXai3QoAgPebO+HcZqzpdP8fv7ZPulwD8vM75kl4SJB9z9mZm8UMOfgOMgM8Ifz7CF7IzjRe4f+1TyvlYHW7PHT5NImNCLFbAQBwpv3HWuX/7SyXby+eJLPOcbnb2W4tCHgDMgM8Ydo/4Gc6e/vlUG27TEuNlpjwYLsVAADnmpoSLYlRobK7rFkY9wLgrwj/gJ8pru+Qtu5+mT8xXgICAuxWAACcKyI0SOZMiJOjDZ3S0NFrtwKAfyH8A35ERzv2lLdIUlSoTEpib38AgP+4KCtO3IMi+44N7XYDAP6G8A/4kaZOl5Q2dsqcCbESFnxuBY8AAPBluu1fdlKkfFbZKr39A3YrAPgPwj/gRw7WtEu/e1DmToi3WwAA8A+BAQGSn50g9e29UtrAnv8A/A/hH/ATutWRVjtOjw2XNOsAAMDfaLHb+MgQKaDwHwA/RPgH/IQWOKpq6ZbZmbESFEihPwCA/4kMDbZ+DsbJkfoOaex02a0A4B8I/4CfOFTdLjrGkZcRO9QAAIAfunhivAy4B2V/FYX/APgXwj/gB8yUf+tDTkZsuKREh9mtAAD4H136NjEhUvZWtIqr3223AoDzEf4BP6BT/qtbe8yU/0Cm/AMA/JgufVuYnSB1bT1S1kjhPwD+g/AP+IHC6jZzy5R/AABEpqfFSGwEhf8A+BfCP+BwbvegHKhqk4y4cElmyj8AABIVFiyzMmKluK5DWrv77FYAcDbCP+BwTPkHAODLtPBfb/+AFNYMzY4DAKcj/AMOd9Ce8j+TKf8AAByXER9uZsXtqWgx1f8BwOkI/4CDMeUfAIDTCw4MlHlZ8VLV0iO1bT12KwA4F+EfcLB6nfJvfaCZkxkngQFM+QcA4ES67l+r/+871mK3AIBzEf4BB9Mp/xr5Z2TEDDUAAIDjEqNCZXJSlOw/1mbW/wOAkxH+AYfS9Ys65T8zPoIp/wAAnEZAQIDMnxQvjZ0uKW/sslsBwJkI/4BD1bf3Sk2bXeWfKf8AAJzW1JRoiY0Ilk8r2PMfgLMR/gGHGp7yPzOdKv8AAJyJ7vk/Iy1Giuo6pL2n324FAOch/AMOZKb8V7eaKf9J0aF2KwAAOB3d87/LNSBFde12CwA4D+EfcKCGjl6pbetlyj8AAGchKyFSUmPC5NPyFnEz9R+AQxH+AQc6XDs0cqHTGAEAgGchQYEyb0KcVDR3SUN7r90KAM5C+AccRosVfV7dJmkxYVT5BwDgLM3OjDO3+6tazS0AOA3hH3CYlu4+qWrpMYX+AgOZ8g8AwNlIjgmTSQmRsq+yVfoG3HYrADgH4R9wmCN1HdJvfWiZmcGUfwAAzpbWyLl4UrzUtfdKZTN7/gNwHsI/4CDDU/6TokIlPTbcbgUAAGdjelqM2fpvbwVT/wE4D+EfcJDO3n4pa+ySXOvDS3AQL28AAM5FTHiITE2JkkO17dLtGrBbAcAZSAeAg5Rawb+7b0DyMmLtFgAAcC4uyoqX1u4+62dqp90CAM5A+Acc5GB1m8RGBEtWQoTdAgAAzkV2UpTERYTI3ooWs5wOAJyC8A84RE/fgBxp6JCpydESHhJktwIAgHMRERokM9Ji5Eh9h3T09tutAOD7CP+AQ1Q2d0tbdz9T/gEAuEDzsuKkyzUgxXUddgsA+D7CP+AQOuU/IiRIJidF2i0AAOB8ZCVESlJ0qHxW2crUfwCOQfgHHED39S+qbZdsK/jrFkUAAOD8hQYHmpl0ZY2dcqyl224FAN9G+AccoKatRxo7XTLL+qASEBBgtwIAgPM1NzNOXANuef9Qnd0CAL6N8A84QGFNu4QEBcrU1Gi7BQAAXIj0uHBJiw2X/91bJQNupv4D8H2Ef8DHua0PJIXVbZIZHy7xESF2KwAAuBDBQYEyJzPOrPsvbWDPfwC+j/AP+LjGzl6pbe81axOZ8g8AwMiZlRkrWu/vnc9r7BYA8F2Ef8DHHa7tELE+mExPi7FbAADASEiJCZO5E+LkrX3V0jfgtlsBwDcR/gEfptsPHaxpMx9OkqPD7FYAADASAgMC5MZ5Gaa2ziHrAABfRvj/CsXFxfLUU0/JE088IVu3brVbT7Zx40Zz/zPPPCPV1dV2q8jrr78uv/jFL+Tpp5+2W4Zs3rxZHn/8cXn22WfNUVRUZN8DnJuO3n451twtM9KjJSiQKf8AAIy0K2amSVhwkGzc/8VnPADwRYR/D3RUVUN9c3OzDAwMmKBeX19v3ztEg/vLL79szisrK2XdunXmXJWVlZnOgNOF/23bttlXwPkrbeyU3n63zGDKPwAAoyIrMUIWTIqXv+6vkW7XgN0KAL6H8O9BRUWFbN++XR566CF55JFHTGfAqaP/b775pmRlZZn7V69eLevXr5eOjg5z3y233CL333+/OT/VkiVL5MEHHzRHbm6u3Qqcm8LqdomNCJaM+Ai7BQAAjCSd+n/zRZlytKFTDlS12q0A4HsI/x4UFhZKTk6OJCQkSFBQkCxbtkx27dpl3ztEr1euXGnOtRMgNDRUqqqqzHV2drZERJw+lO3cudMsE9ClAT09PXYrcPZc/W7rg0iHTEmOMtMRAQDA6FiRmyIx4SFM/Qfg0wj/HrS1tUlsbKx9Jea8vf3kYi9n85hTLVq0SJYuXWpmEmzatMl0AJzO7t275bnnnjNHZyf7y+Jk1a3d0trdLzPTv/j3BwAARl5qbJjkT06Q9w7WMfUfgM8i/HsQExNjwv0wPde2E53NY061atUqefTRR80ygcsuu0x+/etf2/cAZ0+rDocFB8rkpCi7BQAAjIaAgAC5YW6GlDV1yb5jTP0H4JsI/x7k5eVJSUmJtLS0mIJ/WqQvPz/fvneIjuJv2bLFnGvBP5fLJZmZmeb6THTEX3+I6BEZGSl9fX32PSdbuHChPPDAA+aIiiLg4Qtu69/Qodp2yYyPkJjwYLsVAACMlkunJUtceIi8zdR/AD6K8O+BruFfvHixPPnkk6bqv4b2FStWSEFBgTnUjTfeKOXl5bJ27Vqzhv/222+X6Ohoc9+rr74qL7zwgjQ2Npqt/T799FPTvmHDBvNYPXSbwHvvvde0A2erqdMlde29MjM9xnQiAQCA0ZUaEyaLchJkU2GddLn67VYA8B2Efw8CAwNlzZo1Eh8fbwr+6TT9lJQU+94h06dPl3vuuccEMO0sOLW6v37tD3/4Q/tqyInLArTq/5133mlfAWenuK7DdEblprLFHwAAY2Fo6n/m0NT/Sqb+A/A9AVaAGLTP4cV0ucHwbAM4xys7yu2zs6cv2f/ZXirNnX3yyJW5EhTIyD8AAKPl7sWT7DORurYeufaXW+TWiyfIv988224FvAeZAZ4w8g/4mC7XgFQ0dUtuWjTBHwCAMZQSEyaXTE6U9wprmfoPwOcQ/gEfU97UJd19A2a9PwAAGDs69f/6eRmmE/4zpv4D8DGEf8DHFNa0SXRYsGQlRNotAABgrCybmiTxkSHy1j6q/gPwLYR/wIf0DbhNsb/JSZESHhJktwIAgLGSHB0mi3MS5f3COunsZeo/AN9B+Ad8SG1bj7R09THlHwCAcWKq/s/LlMrmbtlb2WK3AoD3I/wDPuRwbbsEBwXIlJRouwUAAIy1pVOSJCEqVDYy9R+ADyH8Az5Ct/grrGmX9NhwiYsIsVsBAMBYS4oOHZr6f6ieqf8AfAbhH/ARLd19UtPaIzPSY8yUQwAAMD6Gpv5nMPUfgE8h/AM+4mh9hwy4B2VGGuv9AQAYbzr1PykqlKr/AHwG4R/wEYdq2s3WQmmx4XYLAAAYL0nRYbJkSpKZ+t/B1H8APoDwD/iAnr4BKW3skqkp0RIcxMsWAABvoFP/jzV3y57yZrsFALwXKQLwAVUt3WZUQdf7AwAA77BkSiJT/wH4DMI/4AMO1bZLeHCgZCdG2i0AAGC8JUaFydKpSbL5cL109DD1H4B3I/wDXs7tHpSi2g6ZkBAhUWHBdisAAPAGN8zNkKqWHvmUqf8AvFzAoG4eDq+Xn58vBQUF9hWc4pUd5fbZmTW098raTUVyzaw0WZGbYrcCAICxMHdCnH12ek2dLvnRK5/IFTNT5f4VU+zW8zM3y/OvBXwVMgM8Ifz7CF7IznQ24X/H0Ub538+q5KHLcyU9jkr/AAB4m9/vKpeyxi5Zc2WuhIcE2a3n7u7Fk+wz4PyQGeAJ0/4BL6fr/ROjQiUlJsxuAQAA3kRnB7R290lFU5fdAgDeh/APeLFu14CUWx8kpqVGS1BggN0KAAC8SU5SlESHBcu+Y612CwB4H8I/4MUqm7ukyzUgM9LY4g8AAG8VaQX/qSlRUlTXIT19A3YrAHgXwj/gxQpr2iQiJEgmssUfAABebXjqf3ljp90CAN6F8A94qQH3oBTXdcikxAiJDGWLPwAAvNnk5CiJCWfqPwDvRfgHvFRDR680drpkRjpT/gEA8HbaUW+m/td3SDdT/wF4IcI/4KWK69rN7dSUaHMLAAC829zMOGnr7mfqPwCvRPgHvNDg4KAcqmmXlOgwSYpiiz8AAHxBNlP/AXgxwj/ghTp7+6WypVty06IlkC3+AADwCTr1f1pKtBTr1H8XU/8BeBfCP+CFdG//nj63TGeLPwAAfIpW/dep/2VM/QfgZQj/gBc6VNsu0WHBkpXAFn8AAPiS7CSm/gPwToR/wMv0D7jlSH2HZCdGSnhIkN0KAAB8QURoEFP/AXglwj/gZerae6W5s0+ms8UfAAA+Saf+t/cw9R+AdyH8A16mqLZdggID2OIPAAAfpVP/YyOY+g/AuxD+AS9itvizwn9qbJjER4bYrQAAwJcw9R+ANyL8A15EpwhWtfbI9NQYCQxgiz8AAHzVnEym/gPwLoR/wIuUWh8QXP1s8QcAgK9j6j8Ab0P4B7yITvnX7YEy4sPtFgAA4IuY+g/A2xD+AS/R1++Wo/WdkpMcJWHBbPEHAICvY+o/AG9C+Ae8RE1bj7R298kMpvwDAOAITP0H4E0I/4CXOFzbLiFBAWbkHwAA+D6m/gPwJoR/wAvoFn8a/jNiwyUugi3+AABwirkThqb+a1FfABhPhH/AC+h0f532Pz09RgLY4g8AAMeYlDg09X8/U/8BjDPCP+AFjjZ0St/AIFv8AQDgMEz9B+AtCP+AFzhU0y7xESGSFssWfwAAOA1T/wF4A8I/MM56+wfMh4EpKVESEsRLEgAAp5lE1X8AXoCkAYyzqpZuMxowI50p/wAAOFFEyNDU/yP1HdLl6rdbAWBsEf6BcaZV/sOCA2VyElv8AQDgVMNT/8samPoPYHwQ/oFx5DZb/HVIZny4RIcF260AAMBpjk/9r2LqP4DxQfgHxlFzp0vq2ntlRhpb/AEA4GRfTP3vZOo/gHFB+AfGka7909H/3FTW+wMA4HRM/Qcwngj/X6G4uFieeuopeeKJJ2Tr1q1268k2btxo7n/mmWekurrabhV5/fXX5Re/+IU8/fTTdsuQ7u5ueemll+TJJ580tz09PfY98De6xV9SVKikxITZLQAAwKmo+g9gPBH+PRgcHDShvrm5WQYGBuTZZ5+V+vp6+94hRUVF8vLLL5vzyspKWbdunTlXZWVlpjPg1PD/7rvvHu9I0Fu9hv9p6XJJWVOXTEuNlmC2+AMAwPF06n8uU/8BjBMShwcVFRWyfft2eeihh+SRRx4xnQGnjv6/+eabkpWVZe5fvXq1rF+/Xjo6Osx9t9xyi9x///3m/EQvvPCC3HbbbfLwww+b2xM7DOA/PilvsX7wD8jM9Fi7BQAAON0cnfrfy9R/AGOP8O9BYWGh5OTkSEJCggQFBcmyZctk165d9r1D9HrlypXmXDsBQkNDpaqqylxnZ2dLRESEOT/R7t27Zfny5eZcb/Ua/mdTYa1EhQbJxIRIuwUAADgdU/8BjBfCvwdtbW0SG/vFqKyet7e321dDzuYxp9KZAdHR0eZcbzs7T9/zq50Czz33nDnO9Bj4pt7+AfmwqEGyrQ8AEaFBdisAAHA6pv4DGC+Efw9iYmJMuB+m59p2orN5zKk08A8vDdDbqKgocw7/oXv7VzR1ycx0qvwDAOBvhqf+lzL1H8AYIvx7kJeXJyUlJdLS0mIK/m3btk3y8/Pte4csWrRItmzZYs614J/L5ZLMzExzfSYLFiw4qeDfwoULzfmptP2BBx4wBx0EzrL5UJ2EBgfKlJShGSAAAMB/DE/938/UfwBjiPDvga7hX7x4sdmST6v+a8G/FStWSEFBgTnUjTfeKOXl5bJ27Vqz1d/tt99+fEr/q6++aor7NTY2yuOPPy6ffvqpab/vvvtkw4YN5vvqrV7Df+i+/u8X1plCf/GRIXYrAADwF0z9BzAeCP8eBAYGypo1ayQ+Pt4U/NNq/ikpKfa9Q6ZPny733HOPBAQEmM6CU6v769f+8Ic/tK+GXHPNNScV/Lv66qvNOfxDdUu3HKxulytmpkqg9e8GAAD4n7lM/QcwxgIGdTgbXk+XGwzPNoBv+1NBhfx/r34mf/7RpbL/2Bf1IgAAgP/o6RuQX753WHKSouQbiyaZtrsXD90C54vMAE8Y+QfG2KbCOslKiJTpaRT7AwDAX4Uz9R/AGCP8A2OorbtPdpU2yfJpyeaHPgAA8F869b+jt19KmPoPYAwQ/oExtLeyRRo6XHJlXqrdAgAA/JVW/Y+LCJF9VP0HMAYI/8AY2nSwThIiQ2TBpAS7BQAA+CudBTg9Taf+d5gZAAAwmgj/wBhx9bvlg8P1JvgnRIXarQAAwJ/NmxAnnb0DcqSuw24BgNFB+AfGiPbqlzV2mS3+AAAAVFZipCRFhZqlgWzCBWA0Ef6BMfLBoXoJCgqQS3OT7RYAAODvwoKDJC8jVkobO6W6tcduBYCRR/gHxoD25OsWf7qub2JCpN0KAAAgMmdC3PHlgQAwWgj/wBioaumR/VWtcsWMVAkKDLBbAQAARDLjwiUlJkz+d2+VuN1M/QcwOgj/wBj46EiD9PQNyBV5aXYLAADAkOCgQJmdGSd7KlqkvKnLbgWAkUX4B0aZTvl/50CNTEqMlJnpMXYrAADAF2Znxkr/wKD87WCt3QIAI4vwD4yyxk6XFJQ1y+UzUs1+vgAAAKdKjQmXvIwY+ctn1dLvdtutADByCP/AKNtV0iQtXX1y9Wym/AMAgNPTmkDXz8uQA9Vt7PkPYFQQ/oFR9tcDNZIeFy7zsuLtFgAAgC+7Oi9NggICrM8OTP0HMPII/8Aoauvpk21HGmX5tGSJDgu2WwEAAL5sclKUXDQxTjbuqzZb/wHASCL8A6NoT3mL1LX3yrVM+QcAAF8hMDBAbpqXKYfrOuRgTZvdCgAjg/APjCKt8p8YFSr52Yl2CwAAwJmtmpEikaFB8ta+arsFAEYG4R8YJd2uAdlS1CCXTE6UhKhQuxUAAODMMuMjzKDBOwdqpcvVb7cCwIUj/AOj5POqVqlo7mLKPwAAOGsBAQFyy8WZUtrYaZYPAsBIIfwDo+Tdg7USHRosS6cm2S0AAABfbXlusiRHh8mf9xyzWwDgwhH+gVHQN+CWTYV1cvHEeEmLDbdbAQAAvpoG/8ump8jmQ/XS2NFrtwLAhSH8A6OguK5djtR3yjWz08z0PQAAgHNx2/wJ0mAF/w+LGuwWALgwhH9gFGw6WCchQQGyMjfFbgEAADh78yfFy5TkaNnwSaW43YN2KwCcP8I/MMIGrB/Q735eK3kZsTIxMdJuBQAAOHuRocFy/dx02V3WbIr/AcCFIvwDI6y8qUsO1rTL1XlpEhjIlH8AAHB+rp+XIQODg/L2gRq7BQDOH+EfGGEfHKozo/9XzEy1WwAAAM7dtNRouSgrXt7cWy29/QN2KwCcH8I/MIJ0Td7G/TWSmxYtU60f2AAAAOcrODBQbp0/QQ7Vtsu+Y612KwCcH8I/MIJ0yv9nla1y3ex0CQni5QUAAC7M5TNSJDY8WF7/tMpuAYDzQzoBRtB7B4em/F9rhX8AAIALlRYbLpdOS7Y+Y9RKS5fLbgWAc0f4B0aIhv6/7KuSvIwYs0YPAADgQgUEBMjtCyZIVWuPbD/SaLcCwLkj/AMj5Gh9hxyoapOvzcmQYKb8AwCAEbJocqJkJ0WaPf8HB9nzH8D5IaEAI0T39ldXzUoztwAAACMhJjzELCncUdoklc3ddisAnBvCPzAC+gfcsnF/tcyZECc5yVF2KwAAwMi4aV6m9LjcxwcbAOBcEf6BEVBU1yGFNe1yw9wMCQoMsFsBAABGxsyMGJkzIVb+vOcYe/4DOC+Ef2AE/PVAjdna78q8VLsFAABg5OjnjDsWZMnnVW2yt6LFbgWAs0f4By6Qq98tb++vkYuy4mViYqTdCgAAMLK0rlBiVKj8qYDCfwDOHeEfuECFNW1m2v+N8zIkMIAp/wAAYHTonv9X5aXJ+4fqpLqVwn8Azg3hH7hAG/fVSGRIkKyakWK3AAAAjI47F2ZJW3e//PUAhf8AnBvCP3ABevoG5N3Pa2RBdrxkxkfYrQAAAKNDdxaamxUnr35SaT6HAMDZIvwDF+DAsTY52tApN87LlACm/AMAgFEWGhwody3MkoPV7fJpOYX/AJw9wj9wAd7aXy0x4SGyIjfZbgEAABhdV+SlSkp0mPyxoILCfwDOGuEfOE+dvf3yt4O1cklOoinAAwAAMBZSY8Ll6llp8sHhejnWTOE/AGeH8A+cp0/KmqW8sUtuvogp/wAAYGzdsTBLOnr75e0DNXYLAHhG+AfOg06xW/9JpaTFhcuyqUl2KwAAwNiYnRkrF2fFyYZPjkm3i8J/AL4a4R84D9WtPfJhUYNclZcqSdFhdisAAMDYCAkKlK/nT5RDNe2yu6zZbgWAMyP8A+fhvYO10t7TJ7fPz7JbAAAAxtaqmamSFkvhPwBnh/APnCNXv9tMsZuVEWv22gUAABgPydFhcu3sdPmwqF4qmrrsVgA4PcI/cI4OVLXKfuu4bf4Es9cuAADAeLl9wQTp7XfL63ur7BYAOD2Sy1coLi6Wp556Sp544gnZunWr3XqyjRs3mvufeeYZqa6utlvP/LWbN2+Wxx9/XJ599llzFBUV2ffAF/z502MSHRZsttgBAAAYT3kZsbJkSpKZldjU2Wu3AsCXEf490LVTGtybm5tlYGDABPX6+nr73iEa3F9++WVzXllZKevWrTPnnr5Ww/+2bdvMOXxLU6dL3v28VpbnJktmfITdCgAAMD6CgwLlO0uypbypS/5mfUYBgDMh/HtQUVEh27dvl4ceekgeeeQRE+hPHf1/8803JSsry9y/evVqWb9+vXR0dHzl1y5ZskQefPBBc+Tm5tqt8HZbi+uluq1H7lyYxd7+AADAKyyekihzJ8TJyzvKpbO3324FgJMR/j0oLCyUnJwcSUhIkKCgIFm2bJns2rXLvneIXq9cudKcaydAaGioVFVVfeXX7ty50ywTeP3116Wnp8duPdnu3bvlueeeM0dnZ6fdivEy4B6UPxVUypTkaMnPTrRbAQAARsa+ytbzOo7UdcqiyYmyv6pNXt9TddrHnHoA8D+Efw/a2tokNjbWvhJz3t7ebl8NOdNjPH3tokWLZOnSpWY2wKZNm0wHALzfkfoOs4/ujfMyJCos2G4FAAAYGfuOWcH8PI/UmDBJiAyR32wrkT0VLad9zIkHAP9D+PcgJibGhPhheq5tJzrTYzx97apVq+TRRx81ywQuu+wy+fWvf23aT7Vw4UJ54IEHzBEVFWW3Yrz85bOhKroa/gEAALyJDkwsmJQgJQ2dcqyFbf8AfBnh34O8vDwpKSmRlpYWU7RPi/Tl5+fb9w7RUfwtW7aYcy3453K5JDMz0+PX6oi/rhfXIzIyUvr6+kw7vJeun3vzs2rJn5woU1Oi7VYAAADvMS8rTsJDgmRHSZP5vAkAJyL8e6Br+BcvXixPPvmkqdyvb6IrVqyQgoICc6gbb7xRysvLZe3atWYN/+233y7R0dFn/Fq1YcMG81g9dJvAe++917TDe+0qbZKjDZ2m0F9gIIX+AACA90mIDJU5mXFyqKZd6jvY9g/AyQj/HgQGBsqaNWskPj7eFO3TafopKSn2vUOmT58u99xzjxnF18B///33m3ZPX3vi0gGt+n/nnXfaV/BG7sFB+WNBpWTEhcvyacl2KwAAgHfRz6P5kxPE7R6UT8pa7FYAGBIwyJwgn6BLBoZnG2BsHa5tl7ue3S5fz8+S/98Ns+zWkfHKjnL7DAAA4MLpoMUfdpZLRXO3PHjZVImNCLHvOdndiyfZZ3ASMgM8YeQf+ArrCypk0PpPp/wDAAB4s8CAAFk8JUnae/tlfxVV/QF8gfAPeFDd2m0K/V2WmyK5qSfv9AAAAOCNJiVGSrZ1aM0iLVoMAIrwD3jwlhX8Gzpdcs+SbAr9AQAAnxAcFChLpyZJQ7uL0X8AxxH+gTNo7e6TPxRUSH52gsyflGC3AgAAeD+dsTg5KVI+Ptoo7T1sKw2A8A+c0QeH6uVIXYd8Z2m2hAbzUgEAAL5DP7tcOi1ZGjtc8lklo/8ACP/AafX0DcjvPi6TGekxbO8HAAB80tTUaJmSEiU7S5qkrZvRf8DfEf6B09hd1iyfVjTLNxdNkpjw02+RAwAA4M1CggLl0qnJ0tLtkj3W5xoA/o3wD5xiwD1oRv3TYsPlujnpdisAAIDvyUmOkmkp0bKrtFlaulx2KwB/RPgHTnGopk0+LGqQWy7KlNTYcLsVAADA92jlf137397Tb2Y2Dg4O2vcA8DeEf+AE+gPx97sqJCQoQG5fkGW3AgAA+K7spCiZkRYtu8ubpamT0X/AXxH+gRNUNnfL2/tr5Mq8NFMgBwAAwNcFBQbIsmnJ0u0akAJG/wG/RfgHbPqD8A+7KqTT1S/fXjxJAgIC7HsAAAB828SESMnLiDUFjRs6eu1WAP6E8A/YjtR3yKufVMpVeWkyd0Kc3QoAAOD7AnX0f2qS9A8MyvYjjdat274HgL8g/AMWt3tQfru9zOzvf9+lOaY4DgAAgJNkxkfIxRPjZW9lq3x8tMluBeAvSDiAZX9Vq/zv3iq56aJMmcOoPwAAcKDAgABZOjVJYsKD5ZkPjrD1H+BnCP/we30Dbvn11hIJDwmSe5dmm2lxAAAATpQUFSbLpyXLJ2XN8vqeYxT/A/wI4R9+r6C0Wf52sE7uWpglU1Oi7VYAAABn0tpGuvf/ix+VSnFdh90KwOkI//Brusb/+Q+PSmpMmHxjERX+AQCA84WFBMmDl02Rjt5+M/vR1U/xP8AfEP7h1z4sqpePihvkniXZMiEhwm4FAABwtgWTEuTr+RPlzc+qZWtxvd0KwMkI//BbbT198vyHJTI1NVpuvjjTbgUAAHA+rXGkgx+TkiLlmc1HpJG9/wHHI/zDb71zoFb2VLTI312aI8nRYXYrAACAf9Ct/36wcoocqGqTP+2upPgf4HCEf/ilyuYus8ZN97q9Znaa3QoAAOBfrp6VLlfMTJWXtpfJJ+XNdisAJyL8w+/o1n5a3fZYS7cpdhMbHmLfAwAA4F8iQoPM6H94SKA8ualYalp77HsAOA3hH37n/cI6Wb+70mzttyI3xW4FAADwT3MmxMnqy6bKnvIWefGjEuntH7DvAeAkhH/4lYqmLvnV+8UyJSVKvn9pjoQE8RIAAAD+Tbc6vvGiTLlzYZb8oaBC/rKvmvX/gAORfOA3dA/bX39UImWNXfKjVdPY2g8AAMAWHhIkf7c8R+ZOiDPV//cda7XvAeAUhH/4jfcKa+XVTyrl6/lZctkMpvsDAACcSKv/P3xFrhkweWpTsTSw/R/gKIR/+IXyxi55+v0jkpsaLd9juj8AAMBpLZqcIA+snCIflzTKb7eXmkLJAJyBBATH06I1L2wtMdv7/ejyaaZXGwAAAF+m6/9vmz9Bbrlogvzu43LZyPp/wDEI/3A0/WH1lvVD67U9lfKNRRNlJdX9AQAAPIoMDZb7V06RvIwY+dX7R2TzoXo6AAAHIPzD0T4qbpCnNx+Ri7Li5bvLJksw0/0BAAC+0qTESFlzZa5EhgbJ2veKZEdJk30PAF9FEoJjaZVa/WEVHhwkj1g/vDLimO4PAABwthZNTjQdAL39bln7tyLZW9Fi3wPAFxH+4UiljZ3yhBX869p7reA/TfKzE+x7AAAAcDZ0/b/ukPTIFdOktq1H1r53WApr2ux7Afgawj8cp94K/FrZX3unf7hqmlw5M8388AIAAMC50c9Q185Ol4eumCaHazvM4EpJQ6d9LwBfQviHo3T09Mu6D4/K3z6vlb9bnmOq1QYGEvwBAADOl36WuvmiTFl92VT5pKxZnnqfDgDAFxH+4RjdrgH53Y4y+WNBhdyVnyXfXjxJQoP5Jw4AAHChtGjyndbnq79fMUW2FTeaJQCfljezCwDgQ0hGcITmLpf8ZluJvPhRqVw9K838YIoJD7HvBQAAwIUKCw6SuxdPkh9cNkX2H2uVX/6tSN47WCcDbjoAAF9A+IfPO9bSLc9+cET+Z1upXDEzRX54+TRJiQmz7wUAAMBIiQwNlm8vzpZHrsiVLle//PK9Inl1d6X09A3YjwDgrQj/8GlacfZJ64fOG3uq5Nb5E+Rh6wfR5KQo+14AAACMtJCgQLnpokx59KrpMiE+XH71frH85qMSaep02Y8A4I0I//BJur5sx9FGM91s25FG+d6yyfLgZVMlM569/AEAAEab7gJw6bRk0wGwbGqS/M/2MtMJoAUB3SwDALwS4R8+p7O3X97aV22Cf2lDp6xeNVW+a4X/+MhQ+xEAAAAYC3kZsfLwlblyx4Is+bCo3vp8dlhe2VkmdW099iMAeAvCP3yGjvZ/Vtkiz2w+Ik9uKhbduv/Rq3JNZf/wkCD7UQAAABhLOvNSiwD+cNU0iQ4PlnVbS2Tte0XyweF6cfW77UcBGG+Ef/iE+vZe+f2uCjPav3F/tSydkmSmmV07O12CA/lnDAAAMJ50l6VbLh6qA6CzAPaZ3QAOy6+3lsjnVW3sCAB4AVITvJru3b/lcL3pPX5+y1EJCQqQ1ZdNNdPLLslJNOvNAAAAMP70c9n0tBi5f8UUWWN9VstNjZY/FujgzWFZ9+FR2V3WLL397AoAjJeAQZ1LDa+Xn58vBQUF9pXz1bX3yN6KFtlT3iLbjzZKv3tQrpqZJlfPTpOZ6TGOCf2v7Ci3zwAAAMaO7tc/2qpaumVTYZ3sKm2SQzXtZivmhZMSZOHkBJlv3UaHBduPxEjxt8yAc0P49xH+8ELW6WBH6jtkj4Z+6zhwrNWE/LkT4mTVjBRTUdZpa/sJ/wAAYDyMRfhXGjVKG7vMqP/usibZV9kq4aFBMn9ivMxIj5VpqdEyLSXa1ArAhSP8wxPCv49w6gtZp/WXNXVKaUOXlDR0mPVhJQ2dkhIdJhdlxcvFk6zD+uGQZF07EeEfAACMh7EK/yeqbeuRAu0EKG2SA1Vt0t03IIlRoSb8T0uLNssEspOiTFsgSzvPC+EfnhD+v0JxcbG8/fbb4na7ZcGCBbJ8+XL7ni9s3LhRioqKJCQkRG699VbJyMgw7Wf62u7ublm/fr20tLRIfHy83HXXXRIeHm7uOxMnvJD1n1qXFfYbOnqlqqVHShut0G8dZY1d5oeBWP8SJyZGykVW2Nfe4FmZsY6v4k/4BwAA42E8wv+w1q4+K/y3SnF9hxTXDR0dvf0SFxFiwn96bLhkxodLely4ZFhHemyERISys9PZIPzDE8K/B/pXs2bNGklJSZHo6GjZvXu3/Nd//Ze5Hqah/6c//alccsklUltba0L8v/3bv3n82jfeeEP+8pe/yJw5c2T//v1y4403yk033WR/x9PzpRdy34Bb2nv6zZt4e3efNHa6pN4K/A3t1qG3HS6pbu2Wnj63RFjhPjsp0rzR5yRHmiIxk5Oj/Ka3l/APAADGw3iG/xM1dfaa8F9kdwIca+42nx11UCg4KMB0AGhngM4GiI/UI0QS7FvtLIgMDbKOYAkKZKaAIvzDE8K/B+Xl5XLHHXfIO++8I7GxsXLvvffKnXfeKbfddpv9CDGBXkP/Y489JpWVlXLDDTfIRx99JE1NTWf82ltuuUVWr14t1113nZkZ8Mwzz8jrr79uf8fT85YXcpsV5ksaO6XXCu5arXX4tqffbabwt/f0DYX+4+G/X1q6XTL8rywqLFiSo0MlNSZcsq2wP9kK/Xqkxob55fQuwj8AABgP3hL+T9Rqfc7U8K+DRDWtPVJl3da29ZoZor19A9ofYIQEBZqOgLiIYBP8tQNAP2MOdwSEBwdKqH2Emdsgs2OUdhCYw/rMGWjf6vXwue4ePXyf/mL66w1HpaFzvR2648TroU4I76hZQPiHJ4R/DzS4r1u3Tv74xz+a61/96ldy7Ngx+dnPfmau1d133y333HOPXH/99eZ60aJF8vLLL0tpaekZvzYrK0sKCwvNjICOjg6ZOXOm6TjwxFteyHsrW8xe+/oGrAX69B+PRvYT3wj1jVart0aHhUhMeLAkRIZIihX2U2JCreAfZg6t9ur0Kf1ng/APAADGgzeG/1O5+t1mBygN/81dfdLc6ZKW7j5p6bJureu2nn7pcllHr/W5dCiJG6eOJ+lnU+0w+HL4t8K+dftF+P/iVpO9frvhpKRXx38Jc/vF9R0LJsglOUl6z7gj/MMTwr8Hui5fR+Y1xKuXXnpJdu7cKU8++aS5Vjpl/1/+5V+Or+e/8sor5ec//7mUlJSc8Wt1nb+u9x+WkJAgzc3N9tUXdKmAHur//t//K//6r/9qzseTFuN7fc8xcx5svTGGWQE+LFiPQLMWK0ZDvxX4NfwPn8eGhwy9ieJLdhRVS2RkpH0Ff9LV1cVz76d47v0Tz7v/8tbnXndT8lW6xHQ4/Hdb4b+zVzsBBqTTOrqs895+t7gGBsTVZ9263ccD/Gi5Ki9N5pzm73M8nvtf/OIXZlkycDqEfw/++te/ygsvvOBx5P9b3/qWfOc73/nSyL+G/zN97dmO/J8Y/hsbGyUpyTt6FDFyfvnLX8qjjz5qX8Gf8Nz7L557/8Tz7r947v3XeDz3ra2t8k//9E/2FXAywr8Hw2v+3333XYmJiTHr9vX69ttvtx8h8vjjj0tdXd0Z1/yf7mtvvvlm+eEPf3hOa/7hTEzN8l889/6L594/8bz7L557/8VzD28TaN/iNHSEfvHixWaq/hNPPCHaT7JixQrzIh5+Ieu0f+0kWLt2rQnxGu51RP9MX6vuu+8+2bBhg7lPb/UaAAAAAIDRQvj3IDAw0GzXp2v0g4KCTIX+E7f5U9OnTzcF/wICAkzgv//++027p6+95pprjtcI0Nurr77anMP/LFy40D6Dv+G591889/6J591/8dz7L557eBum/QPjSGs68IPBP/Hc+y+ee//E8+6/eO79F889vA3hHwAAAAAAhyP8A+OguLjYFHt0u92yYMGC48tA4Exa0PPw4cMSFRVlin2q7u5us52obvupy4PuuusuCQ8PN/fBGdra2uS1114zu7ro0jAd/dFaMDz3ztff3y8vvviiDAwMmPf5WbNmyapVq3ju/YR+tH7uuedMwee7776b591PaGX/sLAw836vy38feOABnnt4Hdb8A2NMPxRoEcjm5mbzwfDZZ5+V+vp6+144UVlZmVRXV8vTTz9tt4jZCWTr1q3mXG/1Gs7S3t5unnfV29trirzqa53n3j+4XC5zq+/zzz//vNkRiOfeP2zfvl1effVVeeWVV8w1z7t/0PCv+/qfiOceXkdH/gGMHSsIDubn5w82NTUN9vf3D959992DGzZssO+FE5WWlg5+/vnng7Nnz7ZbBgdvvvnmwY0bN5pzvdVrOIsV/gerqqrMuRX+B5ctWzb48ccf89z7CX3OVU9Pj3nP57n3D62trYMPPvjg4C9+8YvBG264wbTxvPuH7Ozswfr6evtqCM89vA0j/8AYKywslJycHElISDA7QViBQHbt2mXfCyeyPhBIRESEfTVEiwCduOuHXsNZdNvXjIwMc66jQToVPDY2lufeT4SEhJiZXY899phMnjzZ7AjEc+98f/zjH817/olF3nje/YNO93/ppZfMko/h55jnHt6G8A+MMV0HrAFgmJ7r9GD4F10HruFQ6W1nZ6c5h/Po9G/9MHjRRRfJlClTeO79jE7713XA2hnAc+9sWtvlww8/lO9+97smCA7jefcP9913n0RGRprnVzv+dMkfzz28DeEfGGNaAEg7AIbpubbBv+iHAP1QoPRWiwHCebTY2+9+9zs5ePCg/MM//IMJgTz3/kHD34MPPig//vGPTfDftm0bz73Dvffee6a2wx/+8AdT5K2kpEQ2bNjA8+4n1qxZIz/4wQ9MoT8d1OE1D29E+AfGWF5envlAoJVfdURIfzjk5+fb98Jf6C4PJxYBYh9gZ9Jq/5s2bTIfBvW1r3junU+XefT09Jjz4OBg0wmk7/k89842ffp0ueGGG+yrL/C8O19fX5/p3FWhoaGmw0/beO7hbYJ+YrHPAYwBHeXft2+fHDhwQD799FM5duyY6SmmN9i5tOrzxo0b5aOPPjLb/+g2P1OnTpU33nhDSktL5YMPPpBvfvObMmPGDPsr4ATl5eWyevVqU+9BX/cFBQUSFxcnEydO5Ll3OB391Urv+h6/Y8cOqampMVu+8dw7my7rWbp0qSxZssRM/9YZP//xH/9hznnena2xsdFs77lnzx6z20NdXZ18+9vfNrU+eO7hTQj/wBjTqaC5ubnmw6Ge33TTTcdHBOFM+gFQRwEvvvhiMyKgBR91v3edAqhbwOlokf470JECOEdra6t53nWt//D6Xw0H8+fP57l3OK3zUFxcbLZ21Q6/a665xoz4aSE4nnv/ofu6z507l+fdD+hrXgs6K33NX3fddea9nuce3iZAS/7b5wAAAAAAwIFY8w8AAAAAgMMR/gEAAAAAcDjCPwAAAAAADkf4BwAAAADA4Sj4BwDACPo//+f/SGpqqn0lMmfOHFm+fLl9NfIOHTok9fX1o/prAAAA38fIPwAAI+hnP/uZfTb63G63fQYAAOAZI/8AAIyg6Ohos6/ziXSP5+eff16+9a1vSVJSkrz66quSk5MjCxYsMJ0F+fn5UlJSIhEREXLnnXdKZGSkNDc3y1/+8hfp6uoy+0Lr/tDJycny5z//2TyupqZG0tLSJD09XaqqquT66683j33zzTeltbXV/Lq61/TEiRNl8+bNpk2/p94uWbJEFi9ebB6zd+9e2bZtmwQEBJjvd9ttt53x+wAAAN/FyD8AACOov79fnn322ePHgQMHTPuRI0dk3bp1sn//fvnd735n2tRPf/pT+eyzz8z5Bx98IG+99ZY5/5//+R9pamoy55WVleZaafh/5ZVXzKh/YGCg7Nmz5/jXaKdCeXm5Odfg/tRTT5lzDf8vvPCCDAwMmGD/85//3Hy9LhfQx2ib6u7uNrdn+j4AAMB3Ef4BABhlYWFh8vDDD8v27dtN8L766qvNqL/q6+sz1z/4wQ/M6P5vf/tbcblc8vTTT5sZBBrS9foPf/iDebzS0f7vfe97cs0119gtQ371q1+ZDgMN+Xr86U9/Ml+rEhMTzdesWbNGdu3aJW1tbbJjxw5paGiQ1atXy4MPPmhG/ZWn7wMAAHwT4R8AgBEUHBxsgvTwMXv2bNOu0/x1pP6dd94xYX+YTrcffsy8efOkoqLCLBPQUXkN7GrChAny3e9+15yriy++2HzdqXR2QWZmpjmPi4uThx56yJyrvLw8CQoKMksKYmJiTPjXpQb6a2ub0uUEytP3AQAAvonwDwDAGNBRf/XNb35Tfv/73x8v1qeldz7//HNzvm/fPpk0aZKEhoZKRkaGrFy58ngngtYCGKY1AE5nypQpMnfu3ONfc/fdd5vvpTT4D9OOA/31tUNClyUMT/cfvvX0fQAAgG8K+onFPgcAABdIt/rTwnwFBQXmaGlpMaPn2v6Nb3zDhHhdv5+SkmJCthb8mzFjhim8t2nTJrnjjjvMDICenh4zLb+oqMjc6kwAHaXXNf/Tp0+XWbNmmV9P1/wPF/wLDw+X999/34zo79y5U44ePWqWF+iafw3vy5YtM1+jSwo00Gv412J/paWlpu6A3mroP9P3AQAAvovwDwDACNIR9aioKPtqaK29juJr4Tyt9q/X8fHxZvR+8uTJ8p//+Z/y6KOPmjX2U6dOlVtvvdXcp+Feq/PrWnudHaAdBfp4NXPmTNN5MExrAOTm5ppDlwxoAT/9mqysLNNRoPRrT6zYv2jRIrPzQHZ2tlRXV5vZAAkJCeZ7e/o+AADAN7HVHwAA4+h0WwMCAACMNNb8AwAwjn784x/bZwAAAKOHkX8AAAAAAByOkX8AAAAAAByO8A8AAAAAgMMR/gEAAAAAcDjCPwAAAAAAjiby/wfuYhZYsw0rTQAAAABJRU5ErkJggg=="
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![newplot%20%2827_2%29.png](attachment:newplot%20%2827_2%29.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2- How strongly are the variables in the dataset related to one another?\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>Experience</th>\n",
       "      <th>Income</th>\n",
       "      <th>Family</th>\n",
       "      <th>CCAvg</th>\n",
       "      <th>Education</th>\n",
       "      <th>Mortgage</th>\n",
       "      <th>Personal Loan</th>\n",
       "      <th>Securities Account</th>\n",
       "      <th>CD Account</th>\n",
       "      <th>Online</th>\n",
       "      <th>CreditCard</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Age</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.977008</td>\n",
       "      <td>-0.055269</td>\n",
       "      <td>-0.046418</td>\n",
       "      <td>-0.052030</td>\n",
       "      <td>0.041334</td>\n",
       "      <td>-0.012539</td>\n",
       "      <td>-0.007726</td>\n",
       "      <td>-0.000436</td>\n",
       "      <td>0.008043</td>\n",
       "      <td>0.013702</td>\n",
       "      <td>0.007681</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Experience</th>\n",
       "      <td>0.977008</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.049054</td>\n",
       "      <td>-0.045488</td>\n",
       "      <td>-0.048719</td>\n",
       "      <td>0.018097</td>\n",
       "      <td>-0.013378</td>\n",
       "      <td>-0.014045</td>\n",
       "      <td>-0.000462</td>\n",
       "      <td>0.005502</td>\n",
       "      <td>0.013455</td>\n",
       "      <td>0.008833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Income</th>\n",
       "      <td>-0.055269</td>\n",
       "      <td>-0.049054</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.157501</td>\n",
       "      <td>0.645993</td>\n",
       "      <td>-0.187524</td>\n",
       "      <td>0.206806</td>\n",
       "      <td>0.502462</td>\n",
       "      <td>-0.002616</td>\n",
       "      <td>0.169738</td>\n",
       "      <td>0.014206</td>\n",
       "      <td>-0.002385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Family</th>\n",
       "      <td>-0.046418</td>\n",
       "      <td>-0.045488</td>\n",
       "      <td>-0.157501</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.109285</td>\n",
       "      <td>0.064929</td>\n",
       "      <td>-0.020445</td>\n",
       "      <td>0.061367</td>\n",
       "      <td>0.019994</td>\n",
       "      <td>0.014110</td>\n",
       "      <td>0.010354</td>\n",
       "      <td>0.011588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CCAvg</th>\n",
       "      <td>-0.052030</td>\n",
       "      <td>-0.048719</td>\n",
       "      <td>0.645993</td>\n",
       "      <td>-0.109285</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.136138</td>\n",
       "      <td>0.109909</td>\n",
       "      <td>0.366891</td>\n",
       "      <td>0.015087</td>\n",
       "      <td>0.136537</td>\n",
       "      <td>-0.003620</td>\n",
       "      <td>-0.006686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Education</th>\n",
       "      <td>0.041334</td>\n",
       "      <td>0.018097</td>\n",
       "      <td>-0.187524</td>\n",
       "      <td>0.064929</td>\n",
       "      <td>-0.136138</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.033327</td>\n",
       "      <td>0.136722</td>\n",
       "      <td>-0.010812</td>\n",
       "      <td>0.013934</td>\n",
       "      <td>-0.015004</td>\n",
       "      <td>-0.011014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mortgage</th>\n",
       "      <td>-0.012539</td>\n",
       "      <td>-0.013378</td>\n",
       "      <td>0.206806</td>\n",
       "      <td>-0.020445</td>\n",
       "      <td>0.109909</td>\n",
       "      <td>-0.033327</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.142095</td>\n",
       "      <td>-0.005411</td>\n",
       "      <td>0.089311</td>\n",
       "      <td>-0.005995</td>\n",
       "      <td>-0.007231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Personal Loan</th>\n",
       "      <td>-0.007726</td>\n",
       "      <td>-0.014045</td>\n",
       "      <td>0.502462</td>\n",
       "      <td>0.061367</td>\n",
       "      <td>0.366891</td>\n",
       "      <td>0.136722</td>\n",
       "      <td>0.142095</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.021954</td>\n",
       "      <td>0.316355</td>\n",
       "      <td>0.006278</td>\n",
       "      <td>0.002802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Securities Account</th>\n",
       "      <td>-0.000436</td>\n",
       "      <td>-0.000462</td>\n",
       "      <td>-0.002616</td>\n",
       "      <td>0.019994</td>\n",
       "      <td>0.015087</td>\n",
       "      <td>-0.010812</td>\n",
       "      <td>-0.005411</td>\n",
       "      <td>0.021954</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.317034</td>\n",
       "      <td>0.012627</td>\n",
       "      <td>-0.015028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CD Account</th>\n",
       "      <td>0.008043</td>\n",
       "      <td>0.005502</td>\n",
       "      <td>0.169738</td>\n",
       "      <td>0.014110</td>\n",
       "      <td>0.136537</td>\n",
       "      <td>0.013934</td>\n",
       "      <td>0.089311</td>\n",
       "      <td>0.316355</td>\n",
       "      <td>0.317034</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.175880</td>\n",
       "      <td>0.278644</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Online</th>\n",
       "      <td>0.013702</td>\n",
       "      <td>0.013455</td>\n",
       "      <td>0.014206</td>\n",
       "      <td>0.010354</td>\n",
       "      <td>-0.003620</td>\n",
       "      <td>-0.015004</td>\n",
       "      <td>-0.005995</td>\n",
       "      <td>0.006278</td>\n",
       "      <td>0.012627</td>\n",
       "      <td>0.175880</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.004210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CreditCard</th>\n",
       "      <td>0.007681</td>\n",
       "      <td>0.008833</td>\n",
       "      <td>-0.002385</td>\n",
       "      <td>0.011588</td>\n",
       "      <td>-0.006686</td>\n",
       "      <td>-0.011014</td>\n",
       "      <td>-0.007231</td>\n",
       "      <td>0.002802</td>\n",
       "      <td>-0.015028</td>\n",
       "      <td>0.278644</td>\n",
       "      <td>0.004210</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         Age  Experience    Income    Family     CCAvg  \\\n",
       "Age                 1.000000    0.977008 -0.055269 -0.046418 -0.052030   \n",
       "Experience          0.977008    1.000000 -0.049054 -0.045488 -0.048719   \n",
       "Income             -0.055269   -0.049054  1.000000 -0.157501  0.645993   \n",
       "Family             -0.046418   -0.045488 -0.157501  1.000000 -0.109285   \n",
       "CCAvg              -0.052030   -0.048719  0.645993 -0.109285  1.000000   \n",
       "Education           0.041334    0.018097 -0.187524  0.064929 -0.136138   \n",
       "Mortgage           -0.012539   -0.013378  0.206806 -0.020445  0.109909   \n",
       "Personal Loan      -0.007726   -0.014045  0.502462  0.061367  0.366891   \n",
       "Securities Account -0.000436   -0.000462 -0.002616  0.019994  0.015087   \n",
       "CD Account          0.008043    0.005502  0.169738  0.014110  0.136537   \n",
       "Online              0.013702    0.013455  0.014206  0.010354 -0.003620   \n",
       "CreditCard          0.007681    0.008833 -0.002385  0.011588 -0.006686   \n",
       "\n",
       "                    Education  Mortgage  Personal Loan  Securities Account  \\\n",
       "Age                  0.041334 -0.012539      -0.007726           -0.000436   \n",
       "Experience           0.018097 -0.013378      -0.014045           -0.000462   \n",
       "Income              -0.187524  0.206806       0.502462           -0.002616   \n",
       "Family               0.064929 -0.020445       0.061367            0.019994   \n",
       "CCAvg               -0.136138  0.109909       0.366891            0.015087   \n",
       "Education            1.000000 -0.033327       0.136722           -0.010812   \n",
       "Mortgage            -0.033327  1.000000       0.142095           -0.005411   \n",
       "Personal Loan        0.136722  0.142095       1.000000            0.021954   \n",
       "Securities Account  -0.010812 -0.005411       0.021954            1.000000   \n",
       "CD Account           0.013934  0.089311       0.316355            0.317034   \n",
       "Online              -0.015004 -0.005995       0.006278            0.012627   \n",
       "CreditCard          -0.011014 -0.007231       0.002802           -0.015028   \n",
       "\n",
       "                    CD Account    Online  CreditCard  \n",
       "Age                   0.008043  0.013702    0.007681  \n",
       "Experience            0.005502  0.013455    0.008833  \n",
       "Income                0.169738  0.014206   -0.002385  \n",
       "Family                0.014110  0.010354    0.011588  \n",
       "CCAvg                 0.136537 -0.003620   -0.006686  \n",
       "Education             0.013934 -0.015004   -0.011014  \n",
       "Mortgage              0.089311 -0.005995   -0.007231  \n",
       "Personal Loan         0.316355  0.006278    0.002802  \n",
       "Securities Account    0.317034  0.012627   -0.015028  \n",
       "CD Account            1.000000  0.175880    0.278644  \n",
       "Online                0.175880  1.000000    0.004210  \n",
       "CreditCard            0.278644  0.004210    1.000000  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#To find the corelation between all the variables we can use the following method\n",
    "Bank_data.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "#for better representation we can use sns heatmaps\n",
    "plt.figure(figsize=(14,8))\n",
    "sns.heatmap(Bank_data.corr(), annot=True)"
   ]
  },
  {
   "attachments": {
    "newplot%20%2827_3%29.png": {
     "image/png": 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3O4oKi6U9NILX2tGbW0Has36bjGeLzji5JLdcPoo9VD6xfRV7CE350Oihpnyok56bkyfj9Ob6ctkV+VvpE+9gb5w/fR7FF4vlyPKBzQcQITpw2oQnhGPPhj0ynpeZJ0c6Hbsrbqth8WGw6GqBfZv3yc8aCs4VoPB8ofqpY4lKjMS29cpIOLlJGonrderesHzI9ZJGBA7vPiI/0/FRib1lnH733Kw8Kf4bU1lRiSghPPoK0VImyotGtvQB2bBdywb6zZu1wc8Dh/c0taE15ycOicfJw6koLmzYUbd1sEVw7yDs2LhLTWkfvcU17FivfEfuDWzw1LJhpzierp1o6XwarSXXV02d3bNpnzyWcHR2kB37n79YIp+3Gujc4ZOTpYsfuQfqCh9x/5zTupa94j6IFPVDG/q8c73ycljaIe5psuNG52aezEZgeCD69I9GoBAmR9VRa32jXFN9e9C8PRGynAhte4js1ByUX2k6JcRBlMuwKclYNG+J3sWBvspEg62DDYJ6B2LXRqVN1CZ5/CCsX7ZB/XSboxFyug6MwcPCUE9kZ2ejsLAQzzzzDHbs2CGF39mzZzFz5kz8/PPPWLZsGZ588kls27ZNihASkYsWLcKSJUvw+eefy3OYtlFSWgYH0eHWYC/iNIqoTWJMJPYJsUiCkVxOqaNXIsSGlZUlIkMDsWLdZqxYu0m+cdYIyI7GztGuQWftUnGJFEHa0ByUq+VXZd0hLhWVyPMIEk8Xzl7E8LFDMOHO0Rg6pv5t8/7dh5AwIBajJg7HnfdNgp3oBOobaU9RQ3vsmrXnWr09ZLNqT3RCFKxtrbFVFcsanHt0Q60RMGTkACSPGYS7HpgsxKGPmqs/6LqKC0vUT+0rn3xRPsPGDlbLZ5BM10AuwP2T+0pXq4xT+p1HbCM6OaVFpeonIU6LS+WIjDYkFEqEjRroGEojl7LkqclY9sUy8bw3nAc+1S0a9dNA8ZvVN7Kv8TEtMWjMAIy+Y4QcFaB5hvqA7kuqMxpKxG/e+F6lFwrXpA3Kb6/YoBxzs/ONjI0wZOxArGumExs/IAZZp7Ll3ORbgf5eg3IQ10f1RpvmbNAc09L5LaVT537YpGTp3ksjOtr4BvvCP9wfvy3S7ZwuO8eG9wbF7Rwb3j/NXS+l3ejcfVv2ITgqEEMnDkGIEOk0B64jsG1yTeJeF2na0G+tbY+mPWgJTbkc23u8SbnoA32ViYYYcX9ki/ujsNH9Qd4XoTGhdaL5tqexoNNVYAweFoZ6gkTeuHHj5PzCoKAgORK4cuVKOZL1wQcf4O9//zsKCpQFNEg0vvPOOxg0aBAmTpwILy8vfPbZZzKvMTk5OdiyZYsMp88oowuMgrmZuZwTpIHmDXZp5Lo0akg/eLj1wrrNO5F/sRA9nJ1gZdkFeecvIC0zB689+wRefeYJ2FpbY92W1s+/u1Vc3XvJESQKldcr5SIJGiwsLHDtWsORMHJro7pEI0sEHa+Zs0GjWM8+8TJee24mFv+wAo889ZAcwSJef+5dvPnCbMx57SMERwQhOq7h21Bd4SLs6ZPYW4ZKUQ4N7RHl1Gh+SRN7tGx+4LFpSDuRjrh+feTInL/o5NHbXZp7172HM35dvAZvCZvIjXTStHHyHF1D9mjKp6LZ8rmJPQ3KJ0eUz39kWSz5Ybmcr6gpHzqeFtghN9q5737Z5Ht1DdU18y71brDkGlrRqK7RKKy2qyzFyZY+A/vIeA+3HvAL85OdQ99QX/WojoXmYtFIHgWlvtVfL8Wb1rfKRvWt6THNQQJ41gvv46XHX5X2BjdyUbsVyAZyg6RA7u3adUz5zRu1AVWN6xiVnWJD4zra+Pxu4j4iN9i9qhupBvouGvVY98t6NaVt9JQ2RMjQuBw09UabxjZQXdQcQ/WuufObSye76YXG6DtH4OK5i+jTL1qmK+6LZpj8wHicyTyD8NgwuHj0gpu3q/y9b5WKa+L+Efe/hsa/M0Fl0fgek3bc4Nyx08fg6znf4c2/vYOvZ3+L+5+cIdP1TaW4JroXNGiuVZvGzyc6RlPvmsPG3hoj7hwmyyW6X5Q8PiI+XJaLPtBXmRBUTwePG4T1vyhzqbWh0XoabdTliPTvC4k4fQTG0GFhqAcqxANx8eLFsLW1xfr16+Hi4iLdSY8fP46kpCTZuDg4OCA8PFwen5eXh6KiIqxbt06el5+fDz8/P5nXmJMnT8pjKJxM7Zi3iLcL7q49cTb/ouxM00hAakYOfDwazgGiTsi0SaPxr8f/gGEDEuXoDInD7NyzMDM1Q9culjAVaZ5uPZF/QRHuHQGNdA0bM1iGjNRMBIUp8zrI5dDa1goXzyurpWogdzd6YPXo1V1+puMzTikLgtTUVNcJ5NzsM9JGegiamBjL84jyK+U4nZWLbqoLkK4ht86howfJQNfV0B5rOddJG2nP9et19gSG+SMzVbGHVuckETtq0nC4erggKi5CusFeEN+Rf+5C3QqlORm5cHJ2kHFdQwsB0cgeBZofGCSuj6gvn2bsaVA+/uJ3UBbMobqpcXk9nZ1XVz4ErWI6/Q9TsVQIxoN7Ffc6fXIu5xy6u3WXK0NSu0SupafTlRVsNdA8QY3go7fiNNqmWUyGVicdOGEgIpMi5UqkEX31v3pxc9BCKjSSRyFLXK9/qNJ+0pwhK1HfGo9+XRHXXSHqW/dezvKzvyif7DSlfFqCxDu1HwSJ58ILRfDQ4RxQb39hw+j+MmSlZsuVUQkb8ZtTHWvOhusVZEM3+ZlszkpT5nRmiTp6o/P7D0vCwV2HmyyQ4djNXq64u3tTQ9fg1uLt74kB4vopkFthfTmIeiPKobDRIkQaG5y1bMhJU+of/QbNnU+rxNLLCFlnjY3gG+Ijyi4Hll27yMV3+tHiJxMHyxVxB47qJ1devVRUiu4uzjLdO8hbfi8tnnKr5OXk1V+LuH/IzZXs1obs8GtQFho7Wj43LCZUujgS5Arcrad+2unGNL0mb3H/N2wPFHu02gNRtxqXqza02FnGsUwkDe8r50pSuVD9oL+hD/RVJgQtWkOrxTZ2nScGSzfSjeqn2x+ag6mPwBg+vCqpHjhx4gS++uorWFlZyTmFNF+Q5hQGBwfLN6T9+vWT4vHTTz9FfHw8PD098euvv2LevHmYNGkSRo4cidjYWDkS0RgSjJRPwbtHy+4buuD4qXQZtu3aJ+cbUqfIhrYF0Be3uCqpnWjcaQEZWmqd5g1u2bUf904Zg7LL5TLQtV8oLMKRE2k4J0TfZmFXgLArNipMnF2L9Vt2wcnRXgjCQmzdcxBJcVHw9mj/PMO2rEpK2xVs3bBDhitCtI2eOAzFRSVy7hxd2+plyht8mpNGLmI0/4FWx6QVLGmeDgmwtSs3yu+hFS29/TyleOodGw4b0ZH/5adVQsRYI1p8Xw/RGaYVSWkEbtWStbjYSne4tqzad1pcx7aNO2UgETpK2nMJ0fGR8p3hb+qIRHh0SL09Tg5SUGrsWbcyRdqTsmYrUn7bIkOIEIg0Qrhj024prsh+WpCCXDn7DorDsYMncPzwKfndN6Mt7y6V8tkpg6Z86Lr7qPNPWi4fbykokrXKx7+F8rGzt8VL7z4jV5Y9uOewHKWklxzk8tga2rMqKc2Rix8ej+pKcb1C2MUOjsUvX/1S1+GjbSauXbmGgeMHSpex0NhQed6WFVuQdSILO9fsxK61u0SnqhAuXi745MVPZD7NKaLV/hKGJ8j5OuRO1tY5h21ZlTQ36wx2btwtA9W3YROGgNzgIuOFUK0V9/ZypcMWGhUs06l8aIVOb6pvol0bNKo/Nq7cjNzMM3IkI6ZvFKJFoG1QKkU9O3/2gly8hDrs5MLs4eOGPklRWL8iBQWNXgq0BHU0b0RDG64KGwbLuhQZR2KbbFBXfG1sQ4Byz5ANKb9ukTbc6Hwqi0ee+SN++W4lzmQ39DpJHj9YLhCyenHDBauao7lVSc9k5cm5VxSoHEgIkKtyeJzyEnSDeg20eiPVJ7LBXtz3JOzJBlrdkWyg0b2rwobmzi+7VIp+QmTQAmFOPZzkYigL5y2RIzWbV23FtjU7ZBh/7xg8/8eX5ErA+7bsr0t36u4ot75Y/fMa+Z0a2rMqKd0/JHjktYjvpUVNFn+5VN4/JDbo/iE7hkwYJO2IEHZQu7NR2tH8ubTNAa20StsekECJ6tsb165eF9fe0JX+ZrRnVVL6rZKGJ9ZdU3xyXLP2DBblQq6Yij21SFmuLFREL1hoW4e4QbFSUNGWDrTlxZbV27B97Q4Zxk4fjRf/9LLe5ufqq0wIGi00szDF2sUNR9RpmsD9f7kXn705T7pGtxaDXpW0sPVb8bQFUyf9LqjG3DosDPUAuYpGRERg1qxZmDBhgnQP3bp1K5ydnXH06FH5P81B/P777zF69GjExMRg06ZN0jWutLQUGRkZcn6ih4eH+o3No+/tKlas2YBDx07ILRtyzuTB2ckR7o32BdQptygM6cHu6dZLCryMnFw5Itg7LEjYcArFJaXShfRCYTGWrNqATJFPQvGeSaPldgP2drZyRG3H3kNyuwofTzeMHTpAdqLaS3u3q6DRJzt7OyQOjJPz2b76+HshFpR5YFOnTcCJI6ek20tmWhYSBsbKUabTokP2y8JVoD2vQiODMGTkQLmYC33Plx9+K0Um7QM4Zdp4uYWFj58XNq3dip1bmk6gb4n2dJwIssdWiB7FHnvMF/aUqvbQ9hS0X6FiT7awJw4h4UFypHO5ao825HKbnZEjO+pERmq2EF0D5VYVxQXFWPTtL9KNszW0RRhqo5SPLfqq9miXD/2+GnuyhD1kM412UqdfY0+ILJ8BavnY4qsPv5PlQ6OhsX2jUSiEOo280FYDZ3PP1Y2I3oz2CEP6Ec5mnUXSqCS5v9i2VdtwYt8JKeqos0N7GtLoILnpRfePlu6Tiz9d3KRTR/t7UUf26K6j8rNXkBeG3TEMFVcr5FxEmqd0ZEfbRkDbu10FjYzRdcb17wN78f/3n/xUt+0JbdWQejRNjubSKFPcgD4ICg+QAmnVojWyfEgMTn/0bumuaC5EIi1pT2LNyqarXDGT7h8PPw+ZtmtT6++fmwlDbaQNom7EDYiRLz2+n6tlwz2jG9og7Gxsw43OJwFG5ywUHV56UakNueLSKqWNBWNz3Gy7Cs01xIjfmOZvLZj7c129oe0pyAYaeSUbYsT1BApBQXvG/bZobQMbGp9P05RIgA4cPUDuN7dJCEmav9YYGtnZsWG3nEeuDbnRXiq8JFdA1aY97ZvmWmgEjOrJ5l+34ti+43IrE2q7yR56aUKeBbQlDNXLn+YubGBH43MJWiWXfhMvYR+N0C/8dJFc7KgttGsfQ3lNZ8U19ZNifYt6TaHN2KMpF409BM0lDO0TLEei3XxcUSTasrM5ygJ7GqhcdjVTLrpCX2VCkGvygW0H6/Y21ODq6SLdTres3qqmtA6DFoZFDUeKdYWp0437tczvD29wrweeffZZTJ06FdHR9atELl++HLm5ufJBTO6gJA5pj8O3335bjhpmZmbKEcTy8nL5FnX8+PEYMWKEenbz6HuD+45GFxvcGxK3ssG9IXIrG9wbIreywb0h0t4N7g2VW9ng3hBpizC8HWjNBve3E+3d4N5Qae8G94ZKWza4v10w5A3ur6e2TeS2FouAfmqMMVRYGHYwGzZskHOKaMGZjz/+WI4a0nzD9sDC0LBhYWjYsDA0bFgYGjYsDA0bFoaGj0ELw1Nb1JhusQjsr8YYQ6Vztey3AZoFZlavXi1XJm2vKGQYhmEYhmEYnVNbrZ/AGDw8YngbwyOGhg2PGBo2PGJo2PCIoWHDI4aGDY8YGj4GPWJ4Qj8rrFoE1++rzBgmPGLIMAzDMAzDMIwCvTjVR2AMHhaGDMMwDMMwDMMoNCfqdBEYg4eFIcMwDMMwDMMwKiTi9BEYQ4eFIcMwDMMwDMMwCjU1+gmMwcPCkGEYhmEYhmEYhebcQHURGIOHhSHDMAzDMAzDMCok4vQRGEOHhSHDMAzDMAzDMJLa2hq9BMbwYWHIMAzDMAzDMIxKc6N9ugiMocPCkGEYhmEYhmEYhebmB+oiMAYPC0OGYRiGYRiGYRSaE3W6CIzBY1QrUOPMbUblhTQ11jmoralWY52DqMj71VjnwMSoc71HqulkTZ+buYMa6xxcqr6qxjoHRkZGaqxzYNrJ3isbd7LyMUbnsqe2E7ohppxZp8YMj2v7l6kx3dIleoIaYwwVFoa3MRVnj6mxzoGRuaUa6xxEhU5TY52DztZx6mzCsIeZrRrrHFypqVBjjCFiZmSixjoHnat163wv8lgYdizX9i1VY7qlS5+JaowxVNiVlGEYhmEYhmEYBXpxqo/AGDwsDBmGYRiGYRiGUaCtJfQRGIOHhSHDMAzDMAzDMCo0uqePwBg6LAwZhmEYhmEYhlGoqdFPYAweFoYMwzAMwzAMwyg0Nz9QF4ExeFgYMgzDMAzDMAyjQiJOH4ExdFgYMgzDMAzDMAyj0Nxony4CY/CwMGQYhmEYhmEYRqE5UaeLwBg8LAwZhmEYhmEYhlFobuEYXQTG4GFhyDAMwzAMwzCMQnOjfboIjMHDwpBhGIZhGIZhGBUScfoIjKHDwpBhGIZhGIZhGEltbY1eAmP4GNUK1Dhzm1Fx9pgaaz9Fl0qQnnVa3LBArx7d4OHaS81RqKyqwqmMbFy7dh3GxkYI9PWGVVdLmXfmbD7OXbgo41ZduyLIz0sc0/53DUbmyvfqi5NpmSgqLoaZmRlioyLUVP0RFTpNjbUdvyAfOHVzQHV1DU4eS8Pl0stqTj1dLLsgJCIQpmamIv8KThw9hdqa+tvZxtYa0fGROH74FC7mF8g0Nw8X9HLrKePn8s7jTM5ZGW8NxkZGaqztkD2Owp4aaU+qvN7GaNtTJuw9eSRV1MuG9kQJe05o2RPfPwbVVdWopX/i2P07D8n01lBzC02fIZZPDzNbNdY27J3s4RXoCSNRvvl5F3A2u+nf9Ar0gkM3e1l+6ccycKVMKT/fEB84ODug8nolDu08LNMIK5uu8Ba/kbGJkbQ562R2s7/RjbhSU6HG2o5PoLe4Xqpv1Ug7nt5CfbNAYHiALB+y59SRNFmHLK0sERDqJ2ywQk76aeSpZUBtW3hMqPyffquCC4U4nZEr8/SNPuzRQLZExkeg4loFjh88oabeHDMjEzXWMt6y3ij3fdqx9Lp6o41F3XWbSLvoOM190tL5VGd9RJ64eFFn85HXqM66eLrAO8ATu1L2oKqySqZ1te4q66upiYl83h3efRg1WvdjW1o3+vt0bco90/TvEze69ubOdfdxQw/XHqisrJSfT4uyKi64BIsuFojq2xtXy6/K9Msll5FxIlPGb4SJUfuexdrtwQXRHrRkm32z7YGvaA/sUSXag4Na7YG7rzscRTtBVFRUIkOcU3G9bfc3tfGtpf43hmzTWi4fe9mGa9vQ0rl0//gEeYs2zVjWz8yTWbJNo9+J6pW1jbWsRBfPFYhz8uQ5NyPlzDo1Znhc3fSlGtMtlgMfVGOMoWLykkCN37asWLEC586dQ05OjgxVQsw4OjqqubonPz8f58+f1+vfaA3VZYooay/Uafjxl9XYvucgMnPO4HhqJqLDg2EuhJOG46kZWLB0FXKFCDwhhFVVdRX8vT1xvaICc7/+GalCNGadzsOOfYcQEuALO2oc24mRSf3f1QcLlqzAxi07sXLNRtw9eayaqj/mfrRIjbUNElAPP/UQfEVnMKJPmCgPU5wS4qMxiQNjMWX6eHh4eyAmsbc8pvRSmcyjh9WICcl45tW/Iu1kBjJTs2ElOkYP/fleBIX7wzfAB76i435437G6jtPNoO9sD2TPn558UP7N8OhQIczJnnQ1tx6yZ/I0sscdfRJ6I/V4Q3uGj0/Gv159CuknM6U9xOeLPoClEGCe4hxvP09sT9kl01tD67sZDTHU8rE2sVBjrYeuY/x9YxEzMAYe/h4IiPDHkd1HG/xN6gBO/8s0eAZ4IDg6CKbmZsg4rnRMx88Yi74j+iJ50hD88vVymUb0H5WEQeMHopd7L4THh0mxojmntVTWVquxtkGd8YeevFcIAy+ERQXL600THb/GxA6IwfhpY0T5uKF3QoQQXBkoE+XTw6U7pj4wSeSNxnXReT2yV3kBZ2Jqgrv+NBU+4nt9g30QFh0i89rawW0r+rJHg5uXK5565XFpz5ql69XUm3Mz4UGd7vv+Ml0KtJDoYJiZmyJdXFNjYgf0wdh7RsNNXHdkfLisJ3TdLZ1PdXbifeMRNygGXn4eCIwIEHX2iBBUSp216GKOux+eiv/34iNY8tUyXL92XZ6TPGEw+g5NgKc4x08ImN1CNNZoLYbR2tZN++/Td9HfPyz+vvY9Q9c+Q1y71w2uvfG5Ux6ciFF3jYSNnTW8/D1xPjcfhfmFcO7ZDW9/+7oQMNUyvUvXLjh56JT6l1qmPS/ylPZgHGJFe+B1g/ZghmgPyLYg0R6QbZp7e8KMcUgS7cFQ0R4s02oPEofGI7p/NDyEzZGibl4qLEH+mXw1V7eQDRPEb6zY4CltONzIBiqfe2X5eIk2TSkfsuFG5w4Y1Q+Dxw8WbVpPWU9NZJuWge6u3THjieno5dlL1quQPqE4sO2AfGF5Mx74631qzPCoyj6gxnSLmVeUGmMMlU7hSjp58mQsXry4Lhw8eFDN0T0kprKzs/X6NzqKS6VlWL4mBX99+D688NT/ITfvHI6ebNhhX/LreoQF+ePZJ/6Ih++7A98tWinf+F0qKUPK9j3426P34xmRVyUawaMnm3aODYmRQwbgiYcfUD8ZLgOHJcm3mC///Q3MnTUP0/90F8wtzNXceu5/dDp+mr8Y//nHG8hMy8b4O0arOaKz5+mKvoPipbDQ4BsoOrNRIXjz+dl47dmZcPNwRXB4oJqrPwYMTUKt6IDRdX4660tM/2Pz9tz36DRpzyv/fFPYk4Nxd4xSc+rtOaJlj4b3Xv8Eb74wG2//+z01Rb90pvKxsbPBsMlD8emrn2POM+/LkZbAyAA1VyEhOU6W36yn5+DbOd9j8kMTYWahvMRJWbEZ896YJ+PajLhzBDav3IIP//2ROGYTBk8YpObon6TkBDkS9MY/Z2LenG9w10NTRPk0fek0/ZG7sPjrX/DG0zORnXYao6cOl+klRSX49uMfkPLrZvlZA3UOP3r1U7z7wvuY9eIHCI4IhIevu5qrP/RlD0H1lsTk4T1H1BTdkahe99tPz8L8Od/ijocmN3vddz9ypxQR74jjctJzMWLKMJne0vk29jYYKY756L+fYuYzc4SwdUFQZP190jshUnT0zeRomwYarRon7Pz2gx8w67n3xLlz5TOrPdDfp2v8WPz9d8Xfd2309wm6dhpVIpvo2qdqXfuNzt322za89+KHMpw6nKqmAoUXiurSl87/RU3VPdQeDBftwdxXP8OsZ96Dq2inghq1B4nJ8bJcZj49W20PJmm1B5vweTPtQcryzXj/hQ/xgWgP0o6mYch4/bUHGhs+oXtV/MYu0oaG5ZMgbKA2baYon2/mfIcponzIhhudO1K0aSkrN+F9YcMGYSe9aCDCY8PkffS+KJuP/jNXvuiwFeV8+0OvTvURGEOnUwhDc3NzzJkzpy5MnTpVumNs3LgRly8r7kv79+/H6dOnZXzVqlU4fvw4Nm/ejB07dgiho7zxvXLlCnbt2iXTt23bVncuicBjx47JY48ePQoXF9F5ClQaCzp379692LJliwxFRUUyPTU1VZ63fft2rF+/HllZWTKdOHPmDDZt2iTDgQPKW5mWvkefpGbmwK1XT3RzdICpqSn6xvTG3kMNO96XL5fD0d5OxrtaWiIv/yIuFhXDQvzmLj27Y8vO/di6+4B4UNTAy91VHmeo+Pl41rnBGjIxiVHYsn6bjGenn5YuvM49nORnDTTq5hvghf27FHedzeu2Ibav8ibOQjykptw7Hr8uXitdMjWQ62Jx4SX5coNejxcVFCGuXx81V39Ie9Ztl/HsDLLHuFl7fPy9cGC3Ys8WYQ+dR0h7pgt7ljS0RwON2tEIo8YFU990pvLxCfbGudPnUXyxWI5I7Nu8H5GiY60Nfd61freM52ackeXn1F2xNyc1B+VXFBc3bbJOZiEg3F+OEgSKjtWxRqNU+iQqMRLb1u+UcXL1NDKpv14NNIJJIwI0WkPQ8VGJvWX8ctkV5GblSfHfmMqKSkSJ36Ov6PiXlZTJkS19o0976LtpBGp3yl41RXf0Ft+9Y70ygp8rrptc8Jq7bho50wjTneJ4uiaipfNptPbs6XN1dXbPpn3yWIIEIHXsf/5iiXIfqUTEheF87nmZT26zNGKknd8WbvT3NbTn2ome7j2lsKWRJ/ptNJC7LY20hcWECtHRPpfx1tC4Pdi7eV8z7UGELCdC2qbVHmS30B7QqC29ROkj2gMXDxfpJqsvFBvqf+PmbYgUNmjatHobbnRu5slsBIYHShuoTTuqtmkF5wukNwGNApPgzM3MlffcbQ+NpusjMAZPpxCGdANrhBaFs2fPSmH44YcfYuXKlfLza6+9hhMnlPkTNMK4cOFCObo4a9Ys7NmzR6avWbMGP//8M5YsWYKvv/5aCkhi9uzZeO+997B8+XLs3r1bCr25c+fKPBKQP/74ozzn+++/x4IFC2Q6xelv/vLLL/K7Zs6cKe6JGpSVlclzKX/RokXybxItfU9jyFVWIx5Pn2nqN98WSkrL4GBX/2bLXsRpFFGbxJhI7BNikQQjuZxSx6hEdGatrCwRGRqIFes2Y8XaTfINrUZAMreGvaOdEAgl6ifgUnEJ7B0a/rY034HmnGhcoS4VlcBOnEf0SYiSImPLekWMacg4lSnfbCYOjEOMEFKevh7yb+kbuq7iovq392SPXbP2XKu3h2xWry1a2GMt7NnayB7iwK5DSOgfi5EThmLqjInie/XXadLQmcrH1tEWJeL6NVDc1rHh225bBxs56qShpLhUpt2IfVv2IzAqCMkTByO4dxAyjrXNjfRWoLrV4Hrpt79JfSO7Gx/TEoPGDMDoO0bgnBAaNM9Q3+jLHnKJHj11BH78bFG7RdKNoHuxYb0RdavR/Unu09fkdSt/X/uYls5vKZ0698MmJUtXWRKB2jj3coa1vTX6D++LwWMHYNL9E+rux7ZCf6vx32/c7jR3DKXd6NzzZ/LlfMKBon6Nu3csgnqrL5+vV8r5bOTKOGxyMoZPGSqFiD5o2h6Ie12kadPYhlLZHjQ8pjlITFF74OrtIkTVcTVV99g106bZNWrTmqtDlHajc/dt2YfgqEAMnTgEIaJNo3mJBIlhmp9LnhfkQkvzPzX34W0NtQn6CIzB02mEobYraUZGBrp27Yrnn38e8+bNkwLR19cXI0aMkMdfv34d/fv3l4Jv5MiRMp/mJb7yyiuIiYnBxIkT5f+Ur4EenP/973/xhz/8QU1ReP311+V3T5gwAUOHDpVCk76LIHFK3/n+++/L6yovL5cjlyTq3n77bSk2H3vsMXnsjb5Hm5MnT9bZeTK9fhSyPZibmcs5Jxpo3mCXRq4+o4b0g4dbL6zbvBP5FwvRw9kJVpZdkHf+AtIyc/Das0/g1WeegK21NdZtUd5qM23Hxb2XHImiQB0B6iBosLCwkIv/aENubTTKS3MiCDqe3soSDzw2DWknMhDfL0aOZPkH+6JbdyecP3sB38xdIIUHuTHmZJxudjEIXUD29EnsLUOlqFcN7RH17mb2SJuVuqnYky5HzzT2aN5Qv/n8LLz14mzpTkoLvUTFNXwzrCs6W/looA6Nthssxa+rv7sGste8y42PacyY6WPw3Zzv8PbfZuKb2d9ixpP3qjn6geb90EgeBaW+1V8vxZvWt8pG9a3pMc1Bz4FZL7yPlx5/VXaGgxu5qOmKjrAnflCsLEsX9x5y8Rd6CREQ5q/mtg9lxCtChsbXrdSbRtctnnHa1031THMMzd1s7vzm0itEOrlpjr5zBC6eu4g+/aJlOo1u0UvLqooqKYS/+eAHfPjKXLh49pLzxNpDZQvXpU1Lx9zo3C2rt+Gtf8zEey9+gPTj6bjr/+6Q6SROXn3iDenC+NPchZh43zi9vTCqvCbaNnFNGpq3rWH7R8fQ738z1i5eh7dEe7B+yQaMnVY/TUDXVAgbzEWbrEGxoTVtmqhbNzh3rGjTvhZt2pt/ewdfizbt/idnyHRaGKiooBivPfkmXvvLm3JEuiNczPUPiTh9BMbQ6ZSupCT6iMjISDg5OeGzzz7DI488ItMIeghpjhk0aJB0K7169SrS09OluyiJLnIZpfM1DBgwQL6RbAy5gtKxdA65oCYlJdWtKhYXFydXwLS1tYW9vT2Ki4tx+PBheQylETY2ytuoG32PNiRuSTRSGD4oSU1tH+6uPXE2/6Ls1NIbrtSMHPh4NGzQ6KE9bdJo/OvxP2DYgESYmJhIcZidexZmpmbo2sVSrvLm6dYT+ReUlRWZtuMX6I2hYwbJkJGahSC1g2ZrZwNrWytcPN/wtyVXFXpg9ejVXX6m4zNOKQuynMvLl3PTRk0aBjdPF7nypYvosBF7dxyQ8/E+njkPXa0scbQNqxC2BVqYZehoYY8IGafIHmWeimKPdfP2XL9eZ0+gsCdT/A7EuTPnERwRJOwZDlcPFyH+IuAi6puJiXGdy075lXLkZp+RAksfdLby0XA25yx6uPWQrmrULvoE+yAntaGbF70R9wv1k3FrO2tpb1H+jV3dQ2NCQG6nBLlqdeupn3LRQAuz0EgehSxxvf7q9dKcIStR3wryG47sXSkrF53D6+jey1l+9hflk52mlE9LkHswtYcECWqa9+Xho58OYEfYIwocVy6XY9jEZMT0j5Zl1Cfp1haG8Pb3xIDR/WWgelN/3dbyugsb1Ru67usV1+Hcq5v8TMfnpCn1Lys1u9nzaVXVujprrKwImZ2WA8uuXeSCO/1o8ZOJg8VnSwwc1U+u1kou37TCJI1O0ksbGu2lRX3aQ0t/Xxu6ds09Q9dObd6Nrp2g8qMXDxRoIRSn7sridnRfXlXdM2mEmsqM7kN9kJeT16A98A32btIeKLb5yjhdh5VoDxqXa2PIXVkDuUPT6p76oqkN4jcWdVGblsun5XPJjZfaMoJs0LRpNLJLC+nQCq3kJVIk2gVH5993YUKdQKN7+giMwdMpViUll81nn31W/VQPjRyS0PL09IS1tTXCw8Plzf7yyy/jj3/8I+zs7KQYI/fQ6dOnY/78+fjiiy9w5513YtSoUVI80mjA0qVLERISIgNBcwfJPXX06NH48ssvpZvojBkz5DlDhgyRfyslJQWWlpbo27evPOfjjz/GPffcg8LCQikO6VgSWST+6P+WvudG3OqqpHaiMaQFZExNTeS8wS279uPeKWNQJh48FGysrXChsAhHTqThnBB9m3ftQ4CPJ2KjwsTZtVi/ZRecHO2FICzE1j0HkRQXBW+P9s8z1PeqpMdPpcuwTdhB8w2pk0c26ou2rEqak5mLrRt2ynBFiJzRE4dJ98M+6vyG1cuU1QJpVU9Kp1FyegNOgoU6rMlCgK1duVF+T8pvW+pCiBBUKxf/hh2blPkUSYMShFhxRmCovxQnNEKlWc3vZtC901pOi+vYtnGnDCTaRgl7yJ2URBA9Gn77RWNPSL09Tg5SUNLcGhKU61amKPas2drAnl8Xr5H20AM9OqG37Ax7+XogLqkPVi1Z22r3vrY8om6H8mnPqqS0Smrf4YlyBT0ahY1PjsWSL5epAtAaV0qvyE4pLR5TWlSK8Djl3k9Zvkme7x/mB/9wfzm/hjpQ9D00ykmrLVpaW8oOFr1Rv371Orav2SHPaS1tWZU0N+sMdm7cLQPVt2EThoDc4OjtPXVG1i/fKI8LjQqW6VQ+DnJZelHfRDswaFR/bFy5GbmZZ+QIU0zfKESLYCXaBxrlodFc6uxR59CZtvXxcZMiav2KFDnHSNd0hD2pR9Ow+bet2LJmu7SBFhp59/nWL+DU3KqkZ7LysGvjHhnoummBDqXeKKNzG5anyP+Do4KkCyJdt72470kI031P7pIpv27BGXHdVO+aO7/sUin6De8rF49x6uEkF0NZOG+JFH6bV23FNlHPKIy/dwye/+NLso7T3N3+I5Lk9gI9XbvLEcWNVHZaAru1rRv9/STx9+U9I/4+zStbJP6+9j1D8+zo2kvEtUc0uvbmzqV7huay0XYVPd16In5wLE6n5+LQrsNw9XaVAqWHuG4S/DQatfKHVVLg3oj2rEpKv1WSaA/kbyuEaXxyHBZ/ubSZ9oBsK5G20TYS9e2Bv5xbHDcotkF7QJ/p+0h0UVtxJvssDu2o385Cl9C8X/qNNTbQb9ycDUPUNk2xAdgoy6f5czVtGm15omnTrok2bZu4d+g5RPNCy0ouw93bHRHiHl398+pmt5RpjEGvSpqhTLHSNWa+sWqMMVQ6hTAkd00ScZrtKmj0j1xJyT2TXEL/7//+D++8846MOzs7y+ODgoLkYjMkHEm89evXD2lpaXJhGBJrtFgMfZefn58UhgEBAc0Kw9LSUuzbt08+jGm1UnL1pO8mYUgjmRph+NFHH2HatGlSpNJcQgcHB7nlRV5enkxr6XtuxK0KQ3pweLr1kgIvIydXjgj2DgvCoWOnUFxSKl1ILxQWY8mqDcgU+SSi7pk0Wi7Pb29nK0dsduw9JLer8PF0w9ihzY+qthZ9C8MVazYI207ILTVyzuTB2ckR7o32bdQl7d2ugkaf7Oxt0XdgHOyF8P7q4+9RIjoUxJRp4+X+fuT2kpWWLd0OaTSNOpLLF66SK+FpQy6Q2Rk5siNITJk+TgqOXqID8s1nP9alt4a2CENtyB5aMIGuleyZL+wpVe2h7Sk09tDKnQnimJBwYU928/a4atlD+0ZNumes3D6ARio2r92GnVtav4hGW4ShNoZaPu0RhvQj5InO/IDR/eTS7Vt+3Yrj+47LJfZpDhbtaUhL5tPIaB9abc/BFj/PXSg7UMTQSckI7RMiF9Fx83GVb8vP5ZxDTloOYvr3kfsfdrWxwsJPF8vFWtpCe7eroM4+XWec+Pv24v/vP/mpbpsQWoGTBBGN5tJITZywKSg8QHRU87Bq0RpZPiSepj96t3T5Mxeiin4XEmi0NyOtKOkb4C2X3ae0XZv003nSRl/2UKddA3V4ab7fgTbsA3qz7SrkdYv7JEZcE83fWjD357p6Q9tT0HXTyCtdN9WVQCEoaM+43xatldfd0vk06EACdODoAXK/uU1CSB5rZs4ajUrt2LBbzosnEXVJiMMBQjB7irI7sOMQdoo8bVrbumn+/gD1729W/z7dB/ZOdtIGec+Ia6cVKpu79sbnEv2FKKZ9Mj0DPOVIKm21QW6zJARpFU/aTqa7izMWz1sqRzxvRrv2nZXXd1a2ByTWqT04JtqD0Ghhm2gP6mwT7YGmXMi9VVOuNMcztE+wFOBKe1CIs6I96C++LzgqWG55U375KpbOp21EbuyO3l7qf+P+sq5vVm2g7Vga26Bp0zQ2tHQuQSv9ato0mtO78NNFsk0j+2irCip/Dz93uXLp8X2t8/QwbGFI94f4QXQczHzjxP+MIdMpNrineXleXl7qJyA6OlrO03v11VflKByN3NFIIP1P4oxG4j755BMpxEhA/vOf/5Sjh7Q/IQk4cvmkuQ/kPnr33XfLuYaxsbHSvZOgxWfI7fThhx+Wgo6+Kzc3V779DAsLk/MGf/jhB3Tp0gWTJk2S5/z5z3/Giy++iO7du2PDhg1SkJKI8vHxwZNPPtni99wIXWxwb0joe4P7juZWNrg3RNrV0TBgbmWDe0OkvRvcGyq3ssE9o39as8H97UTnat1uLtxvN9qywf3tgkFvcP/bB2pMt1iO+LMaYwyVTiEM2woJQ81WFLczLAwNGxaGhg0LQ8OGhaFhw8LQsGFhaPgYtDBc/b4a0y2WIx9XY4yh0rlajlZCc/gYhmEYhmEYhmkEvTjVR2AMnv9JYUh7FTIMwzAMwzAM04jmRJ0uAmPw/E8KQ4ZhGIZhGIZhmqG2Rj+BMXhYGDIMwzAMwzAMo9DcaJ8uAmPwsDBkGIZhGIZhGEahOVGni8AYPCwMGYZhGIZhGIZRaE7U6SIwBg8LQ4ZhGIZhGIZhVEjE6SMwhg4LQ4ZhGIZhGIZhFGpq9BMYg4eFIcMwDMMwDMMwCs25geoi3IQLFy5g48aN2LBhA9LT09XUeiorK7F7925s2rQJKSkpyM3NVXMYXcHCkGEYhmEYhmEYFRJx+ggtUyuE4/z58/Hll1/i+++/x5w5c1BWVqbmKhw/fhyzZ8/GokWL8N133+G9995DDY9E6hQWhgzDMAzDMAzDKDQe6dNVuAFFRUX45ptv8NZbb+GTTz5BRkYG9uzZo+YqrFy5Er169ZKC8D//+Y88vrq6Ws1ldIGRUOg3LinGYFm34Ds11jkwMrVQY52DRT9vUGOdg9/W71BjnYNhHrZqrHOwM7dCjXUOPM3t1FjnwL3LdTXWOTh4rXO9V3Yy7lzPn9LaSjXWOahG5xsV2nxmvRozPK4uelWN6RbLKc+psaaQCymNEi5dulR+njVrFi5duoSXX35ZfiYWLFiAX3/9Fffeey/Onj0rj12yZAmMjIzUI5hbhYXhbUxoj3g11jkwEv86EweOfa/GOgf2HkPUWOcg/5EINdY5sP9gnxrrHLzca5Aa6xzc3/OcGusc3HVGjXQS+pn1UGOdg91VBWqsc1BR2/lGhbblGe7L46sL/6vGdMuF2Bk4ffq0+gnw8PCAp6enjC9cuBCrV6/G559/Lj/TaOCuXbvwwQcfyM9EZmYmnnrqKdjZ2aGwsBADBgzA3/72N5iamqpHMLcKu5IyDMMwDMMwDKOg7f6pw3Dy5EksXry4LtBnDRYWFrh69ar6Cbh27RosLS3VTwrLli1DUlKSnItIAvLrr7+WC9YwuoOFIcMwDMMwDMMwCs2IOl2EESNGSBdRTaDPGvz8/JCTk4Py8nK5oMzhw4cREhKi5ips27YN/v7+0nXU0dERVlZWcm4ioztYGDIMwzAMwzAMo9CMqNNJuAEBAQFwcnKSo4Jr166V21UkJydLsUiBoNFC2qaCtqtYtWoVbG1tpTsqoztYGDIMwzAMwzAMo9CcqNNFuAEmJiZ44YUXpOij+YYPPvigFH20RQUF4v7775fzCyl/3bp1eP7556U4ZHQHLz5zG8OLzxg2vPiMYcOLzxg2vPiMYcOLzxg2vPiM4WPQi8/88G81plss76lfYZQxTHjEkGEYhmEYhmEYhcYjfboKjMHDwpBhGIZhGIZhGIXaGv0ExuBhYcgwDMMwDMMwjEJzo326CIzBw8KQYRiGYRiGYRiF5kSdLgJj8LAwZBiGYRiGYRhGoTlRp4vAGDwsDBmGYRiGYRiGYf7HYWHIMAzDMAzDMIxCTY1+AmPw8D6GtzHt3cfQL8gHTt0cUV1djZPH0nC59LKaU08Xyy4IiQiEmZkZykT+iaOnUFtTC3sHO4RFheDa1WvyuIL8QmRnnpbxhP6x8jupSlHYt/OgTG8t7d3HULHHQfztmpvaY2pmKvKv1NmjwcbWGtHxkTh++BQu5iv7P7l5uKCXW08ZP5d3Hmdyzsp4a9H3PoYn0zJRVFwsyyg2Sv978ulqH8OQkAA4O3eTdeXw4eMoLS1Tc+rx9HSDl5cHrKwssW7dZlRUVKo5gKOjg/wOIyMjVFRWYtfO9u3fp4t9DI2s7WDc00NEjFBTfBG1BU33qjOyslGOofpdXYXq7JMy3cQ/UjwoaW8uxcWmOlPZwLe96Gofw9DQQHSn8hHXdujgMZQ0Uz5eXu7wluXTFWvWptSVD9XFyIgQdBXlViPux0OifMvKmt6PrUEX+xh2dbKFc4Cb/OlLzxaiODtfzVGw6ekAB09l/zq63osnc3H98lX5uUeIsK+bHaoqqnB65wmZdivoeh9DYwd7mPl4ybpXff4Cqs7kqTkKxna2MA8JQu01pa2uLixC1WndbT7Y1n0MfQK94KC202nH0nGl7IqaU4+FpQUCwwNEPVLa6VTRnmva6ebOt+hiDv9QP5hbmMtnTn7eBZw9Xf8793LvKQPlFRdcQnZajprTFF3sY2gl6ltPWd+McOlsAQob1Tdzqy5wCfZEF5uuuJhxFoWnlXzzrl3gGi7KUsW8iwUuZp5DUe4FNaXttHcfQ3sne3gFesr29YL4PfOymz73vEVZ2Hezl/dM+rGMurL0DfGFg7M9qq5X4uDOwzJNGxfPXvAM8MSelL2oqqxSU1tHW/cx/D3qG+Hq6QIvYePulD2ovImNBr2P4Zf/VGO6xfLBt9QYY6iYvCRQ44zKqlWr4O/vr34yXD5653M11nocRUP38FMPwS/QG+F9wmAuGsRTojFsTOLAWEydPgEe3u6ISewtG8ySS2UIjw7Fy+88AxMTE/gGeMvOffrJTHnOvEUfoot4wHn5eMDL1xPbUnbK9NbSHmGoscdX2BNxE3umTB8v7PGQ9tAxpcIegh6AIyYk45lX/4q0kxnITM2GlXVXPPTnexEU7i/s9IGvEJ+H9x1r08Pskf83RY3phwVLVmDjlp1YuWYj7p48Vk3VH2/Mmq/G2o+zsxOe/tfjCA72R2xMlHjAmuHI4aad7hEjB2PypDF45tm/4NNPv8FV9UUEPcBnzLgDQ4b0Q0Cgr7hPfbBeCMf28I+YW+0IGsEsaRRMAqNg3MMdxm5+qM4S4k6IvzqMTWAWlwyTgN4w6u4GE2dXVJ86ILMsH/uv6AFawLibK4xFnia9vbyx+9aFR/fu3fDsM3+RwjsuNhoW5uZS3DVm1MghmDJlLJ5/7il8/Mn8uvKJjo7AY489AB8hWKJ6h8HU1BTHjp+SeW1lsE19R7ldiOakz71D4TMgHN38XdErzBu5e06hWuse9koKQ8DwPnDydYFbH38Ym5viwgnlRRedGzA8GqETk7D/m3Uy7Vbobd0+gdwsos2ymjweXRJiYeblCfPgAFw/dATQss08NAgOz/xVPOVNYOrtKeplNaoys9XcW2dhqRppBQ5CRNz/l3vhHeCFkOhgmJmbIf14hppbT9yAGIy7ZzTcvF3ROz5CHlMm2umWznd0dsDk+ydIoeIX7IMA0V4f2XNUdsjtHGxlXkhUMLz8PGRn/tThVPUvNcXDxFqNtRNR3xLvHYaAARHoIeqbq6hv2Y3qm10vRyTeNxyxdw0W4qkCOfuVZ5WVkw3i7x6CHn6u4lw3DPvrVJw7noP81PYL+byacjXWeuhZOP6+cYgdGAMvfw8ERIjfc/fRBs89EoQz/jJNip+g6CBRFqbIOK70ASbMGIekEX0xdNIQLPt6uUzTQL//nf83FY++8DCWzv8F169dV3NaRzW9QGslv0d9I0g43v3wHfjzi49g8VfLbmrjH/52vxozPKoOrFFjusUsargaYwwVdiVthjvuuEONdT4GDusn3/K99Pc3MHfWl7j3T3fJBrsxDzx6L36cvxgv/+MNZKZlY9wdo9UcID01C68//64Mq5auVVMV5rz2sUx/69+z1RT9MnBYknyj97K0Zx6mt2DP/Y9Ox0/Cnv+o9ozXssfN0xV9B8VL4afBN9BHjoy++fxsvPbsTLh5uCI4PFDNNQxGDhmAJx5+QP10ezBq1BDU1NTg8T8/izfffB+PPvogLJoprz27D+CZZ17FhQsN33r7+Xlj3PjheOmlt/HXp17EG6/PUXM6HqOu1jDtMwgVK77C9YUfC4HXC8buDV8oGQkhaBqWgIpfv0HF4rmoWLNAzVGQ6Us/Q8WyL9SU35fRo5Jl+Tz62NN4Tfy2f378IVE+FmpuPbt278c/n36lSfk8eP9d2LPnIJ586gX897XZopz/0Gz5dgSWdlYIm9wPG15fgFXPfQkHrx7oFemj5ioUZpzFhle/x5p/f439365Hwp/q24XjK3dh41s/qZ8MC2NbG1iNHo6S9+ei+K3ZMHFzgXlI0/apMisHJe9+IMPVtRvV1I6nb3KCrFdvPf0u5s/5Fnc8NFm002Zqbj13P3Inln79C95+ehZy0k9j5BSlE9nS+dfKr+PHTxdi5rNzMOelD9E7IUJ08t3kOUnDEmHraIuZz80R4T2sW6Zf+7vaWSN6cn/8+vr3WPLcF3Dy6gm3CF81V6G8+DI2zV2Bo6t3qykKpeeL8cvLX8uw4YMluFpyBenb659HHYWNnQ2GTx6Kua9+hlnPvAdX8WwMigxQcxUSk+NFWdRi5tOz8e2c7zH5oUkwU8syZcUmfP7GPBlvTKQoGzNzczlyq29+j/pG9E6IlCKyI2zUO7WKJ4vOA2PwsDC8AYWFhdi+fTv27t2LjRs3Yv/+/WoOcOnSJWzduhWbNm3Cli1bUFVVJRuSgwcPyrTNmzejoEDpNOXm5orO0h7s3r0b69evR3Z2NjIzM+Ux9B2VlYob1pUrV7Br1y6Zvm3bNly+rMM3zCqxiVHYsn67jGen58DY2BjOPZzkZw00KuMb4IX9uw7Jz5vXbUNc32gZJ2zFwyNGfE9EdKgcWdMmsk8Y+iT0hovqgqlv6Dq2rN8m49miYTc2NrqBPYprC9kT2zdKxqnTOuXe8fh18VrpMquBXEuLCy+Jdkw0ZEZAUUER4vr1UXMNAz8fT1h1tVQ/3R7065+A31YrHbS0tEyYmBijZ6/u8rM2WVmncfFiU1coGkncv/8wfH29kJQUB2vrW3zLfwsY9fJCbWE+astEJ6CmWo74mfiGqbkKpiF9UH0mHcbOLjDxCSWfZjVHwcQzUKYbOTirKb8vAwYkYtWq9TKempohPQN6NVM+mZmnm4hCws7Oti79ypVy6RLco0fT8zuC7sEeuHT6Aq4UlKC2ugZZm4/AMz5YzVUoTD+LCtHZIyqvXlfud5WC1DOouKKMhBoaZn4+qMo7i5qiYjkSeH3XXlhERaq59Rjb2Mh089BgGHVt2FZ3JL0TI7Fj/S4ZP52RC2Nx3zt1b9pO08je4T1H5Oft4vgocR7R0vllJWXIq3PxN8KVsnL5TCMGjx2I/dsOIDQ6BGEx4h4zartHSlvoKepb0el8XBb1jV6+pm4+DO+EhvXtmri+wuzzMr8lAgf1Rt7hTFwpbMOQrI7wCfbGudPnUXyxWHoD7d28Twi6hvWKBN5OtSxyqSzE760py+zUHJRfUVyxtXFwdsCwKclYNG9Jh4iD36O+0WjiCCGqf/5icYN25PaFbNBHYAwdFoY34MiRI/h//+//Yfny5fjxxx/xyiuvSLFIAnDBggX4+uuvsWjRIixcuBAVFRWiI5WKOXPmyM/z58/HN998I48lMfivf/0LK1eulOnvvPOO/E4699VXX8WJE4or3Zo1a/Dzzz9jyZIl8rvJpVXX2DnaScGj4VJxiZw3qI2VjRWull+V105cKiqR5xEkni6cvYjhY4dgwp2jMXTMYJlO7N99CAkDYjFq4nDced8k6cqjb+ylPSXqp7bb0ychSopAjVjWkHEqU448Jg6MQ4wQup6+HvJvMbeGo6M9CoTI1lBUWCznDLYWV5decHHpibHjhmPq1LH4wx+myXluvwc0d7D2Sn3njeKUpo2RXTcRnGASFg+T3v1gljiSJhDJvOrME9LF1DSqP0xFulHXhuf+HjiJstAun8KCYpnWWtat34wB/RPRv38Chg0dKEcbnUSZ/x5YOtjganH9/EgarbF0aP5FAh0befcgHF28VU0xbGj+YM2l+navpqRUpDVsn2ouX0H1xYvoMqQ/uo4eDsvB/dWcjoeeBSWi3dVQItrpxs+HrtZdca38mminlc6j9jE3O59eMNFIFrnuZaUq7rLdeznDP8QPA0YkYeSUYUieUP+s0gdW9ta4UqRd38pkWlsg8RoxOgEHV+xQUzoWGmGl31ZDSXGpTNPGtlFZlNIxjcpSGxJOwyYl49je4zife15N1S8dXd/IxuGThuLI3mM410E26h0St/oIjMHDwvAmFBUV4fHHH8fHH3+M8vJy7Nu3T44Wvvfee/jHP/4h/3/99ddlB4iEoJubG95//328/PLL+OSTT1BcXCy/h0YDSRxSHolKDw8PKSLj4uKwYsUKOeJIwjMmJgYTJ06U/8+e3dQdMycnR45QUqisbp2Pvqt7LzmyRqHyeiUsutS7htF1X7tWoX5SoPkENDdI84aVjtf4ytOo3LNPvIzXnpuJxT+swCNPPSTfvBGvP/cu3nxhNua89hGCI4IQHdf0DbYucNGyp6JZexr+Ljey54HHpiHtRAbi+8XIkUb/YF906+6E82cv4Ju5C6QwJDfTnIzTzU5eZ24OjRr16xcvw/XrFejSRRFGRBdRFpqFjFoDLTZjY2OD/77yLl588S0MHtIPgYEN3bU6jKpKwEzLTZLilQ3vJZpvaNSlKypWf4+KX7+WQtC4h+J6JF1Il36OipUi3c0Xxt4NRxc6Ci9PdynkKMjysWxYPpr5g63hx5+WIT0jC5MnjYaray+cyTuHMiFQfg9oAQxTLTdWUwszVDZq6wgLa0uET0pCF1srHPjh93O3bAu1wjYjLRdfI2Fn7fVG7d7pXBS//CZKZn6A8hWrYPPQveJHUNrqjoAWfSFXOwqVFY3bafMm86/oGajdTpt3qT+maTtfnyfFVFw4Rk4dhq9mf1uXXllRJUevPnjlE/z42ULc++jddc8qfUB/z0xcswaqe5XX6hfNag22Pezh7OuCjN/BjZSg69V2/aaXo43LqXEfgo6paHSMNjZCHI+4cxgunruI6H40r9wcEfHh0uVSl/ye9c3G3gaj7xyBC+cKENMvWtqouM7q1sYOhTScPgJj8LAwvAlBQUHo1q2bbAx8fX2Rn5+PvLw8ODg41C1Q07VrV+lydfz4cQwerLyVJIHYvXt3eSwRGRkJS0tL2NnZwcrKCgkJCTLdy8tLfufVq1eRnp6OHTt2YPHixTh69Kg8pzEnT56U+RSuV7euw0bz5YaNGSxDRmomgsKUOQPkEmotOkMXz1+UnzVcFgLouuhA9VBdyOj4jFNZMl5TUy07j0Ru9hlpNzWo9AaNziPKr5TjdFauFFj6gBbOGTpmkAwZqVni+pRyqLenoYtbU3v8hT3KW+Vzefly7uCoScPg5ukiVyZ1EQ8YYu+OA1Lofjxznlxl8ejBW1+Z8H+RoGB/TJg4UoaTJ9NEvQ6V6fb2drLMzp9v/cp7J46n4nTOGbkKJr2oOXfuPJycHNXcjqWm4ByMHUSdMhMdCNE+GLt4oSZfWbhEQ835HNQWCftoQRrRca8tKYSRlS29RkftNWVxiNqKa3I1UyPb1o/M6ZLgEH8p5CgcP5GK3mr5OIjyIdfQc+cbrqx4I6iz9eFHX+Kpv74o2qiVwuwq0QbqdjXO1lKckw9bt24wtRQdXWMj9Aj2QGFawxUWTUXbFTQ6Dm6xAUh580eDdR1tTJV4rpj06gEj6ryKukeupTSfUBtyn62tUNrqyjNnYSTaaiPz+k6/vvHy98Sg0QNkyErNkas5EjZ21rCytUZBfv3INEFuedcrrsO5Vzf5mY7XrCKaJdr5ls6nBUCmPjgJKxesxlGteeJ0Tm6WsnhLAT0TRP+fnlX6oijnPBxEfSNxSP2FXqK+XUhvuFLszQge2gdZu0/gWmnbF47RBXk5eejh1kOu1in7PMHeyElt2KbRCJlfqPIyzlqWhRUKG5WlNrQgXcaxTCQN7ytHbS27WmLA6P7yb+iS37O+WQobaXGa/rTwzsQh0saBo/qji45t7Ehqa0T7oYfAGD68KmkzvPbaa3j22WflXECa8zdt2jSZTq6dvXr1koKQRv3uvPNOOfpBnSFqRNeuXSs6qU5S0NEI4WeffYbp06fLUT4Sf6NHKwsb0Ejho48+KgXloUOHpHgcMWKEdDP94osv5PeOGjUK/fuLxlPrrTDh5+eHkSNHyvD5rG/U1BuTk5mLrRt2yEDzfkZPHIbiohI5F5Be4axepswpohVHyc2S5hbQap9+QlDS9g5DRw/C2pUb5fcEBPvB289TziHsHRsOGxsr/PLTKtHBt0a0+L4evZzliqQ0H2/VkrW4eKFQfndraO2qpIo9O2XQ2EPX3UedC9GyPd7yjXGylj0pv22pCyERQVi5+Dfs2KQsDJA0KEHaExjqL8UjjSDebPlpbfS9KunxU+kybNu1T843pLefNtZWaq7uae+qpBnp2Vi7ZpMMl8suY+od41BYWIykvnEyf9HCFfL/mNjeKCwqFmKiWm6HQCtcTp4yBieEWDE3M5Nz1woLizBu3HAUXyqBj7C5b2Isvv12YbNbXtyMW16VtLwMpmHxQv2J+9/WEaYhMajcvBxGltYiiHK4dgW1V8qkGymuXoZxt54w8Q5B1R5RP0V7QXMLje2cYNzdBSZ+4ag6sAW1pYqHQXto76qk6elZ+O23jTJcvnwFd905AQXid+7XL06+4P35Z2V1wbjYKFk+VWr59OkTiTumjhNi8hTMheDIz78o2sceiIuLgoe7q2jvknHkyEls3tw+t7hbXZX02qXLCBjWRxRPNay728NvcCT2fPWbHBnsYtsV10XH0CM+CMNevBeHF4rfvrYWtq5OKM1T2qyeYV7oFe4F34ERKEjNk99zvazp/KnWostVSWtKS2HZvy9qxbPHpJsTuvRNwJWfFsPYxhrG1taoFeVIYtHM0x2mPXvCPFzUNSsrlK/S3UqDN1uV9ExWHnZu3C0DvSwkUVBSVIrIuAhRr2qxYXmKPI5WDSWXRWqnaasE7wClnR44qh9Sft2C3MwzuHrlarPn29rb4F9v/12uJHlk71H0FKKGRnDIRZCey73jwmWbHRgRIOeA/frTb/JvNsetrkpaLuobCTuqJzTyFzg4CttlfesqA80vNDU3hW9iCHwSQtDFxlKOal86Wyg6zLUwMjbGqH/ehd0/bERhTutfxrREe1YlpZW6k4Ynynvcqbsj4pPjsPjLpVIAWgtxdKX0iiyLwbIsSuTIGZVFyvJN8nz/MH8pnOIGxcr5htSW05YXW1Zvw/a1O2QYO300XvzTy7LM2sLNViX9PetbwflCbFq1FVvXbJdhwr1j8dwf/1238nlLGPKqpJV7dT+ViTCLGaXGGEOFRwzbAbmBent7y7mAtNAMLUxDC8iMGTNGxintl19+gaurK9zd3dWzbgyJRBKDP/zwQ9130uihrjl28IQQPnswSogpcpv8/L2v1Ryg/+BEWKpuZAu+Wgg7R1tx3FBkZwghtlHZeoLmbYwYlyznGNI2DrNf/Uimk8vEwKFJMn3w8P74dfEaHD/SvmXq24Jiz255nf5CtGrb029wQp09P361SM4RHCnszhH2bFPt0ebk0dS6PQwJ2tZixPhk6bI6d/aXKC9vf6dQH+zadxA79uxHsL8PVq7ZgKycXDXHcNm//wg2bNgqBQXtl/fOO0r9IYYPG4iuankFBwfgzrsmYPfuAxgzeiiShEgh8vLOy5GoiRNGifttKL744jvk5rbtrbzOEEKiYu2PMPENh2lEX1TuWofaSwXSVVTjLlpbUoCqQ9tgGp4Ik9B4VO5YjdriizAyMYVJcB+YRIj0kDhU7t+MmjNNl1PvaPbuO4R167fgrjsmICwsCG+99YGaA4wYMUh6PRBhoUGYdvdkuTrpuLHD0b+fsqeqtRAftM0IiX8SWh9/8pVM/z2gzvaWOUvkgjPBo+Nw6OfNci9D2rqCAkH/n9mXBmd/NwSNjEPgiFiZTnj1DYVP/3DkH8+RW1Y4+fZScwwAYVvZvG9gEd0bXYcMRPmK1ajOvwAzb08ZCBPnbrBMHijnGJr5eKLko7Zvb6QrTh5Kxd4t+zF0whD4BHnj2w9+UHOABCEiNCMrS+Yvk3O5kscPFh30POxK2SPTWzrf0dlRisDSkrK60aIeLopnyO6UvXKUZ/CYgQiJDsGnbza/WqauoPq2/r0lUvSFjUrA3p83yb0Mu4s6RoGg0eveE5JgamYGC5uuMm5iaiLzjE2NUVZQKkcMfy/Ihq9nf4feiREYOGYAVv+4Rgo7Tz8PGQja8mP/5v0YIsqIyuKHD36U6UR0Um/EDIiWo2e0ZYWHX/2KnRr2bz3Qpm2f2sPvUd+02bt1f5teIhsm2v6fugyMocMb3DcDbVdBi8DQ4jMk/l588UWZPnfuXDlil5ycjLS0NPmZFp2ht+X//e9/5QTkjz76CBkZGTL+xz/+EeHh4XLxGXITffjhh+X3/OEPf8CsWbNga2vbII9GFel8mpdIbzsHDBiAu+++W57THO3d4N5Qae8G94aKvje472h0tcG9oaCLDe4NCV1tcG8o6GKDe0NC1xvc/960dYN7Q0cXG9wbEu3d4N5QaesG97cDhrzBffnHj6sx3dL10ffVGGOosDC8jWFhaNiwMDRsWBgaNiwMDRsWhoYNC0PDx6CF4Ud6EoaPsTA0dNiVlGEYhmEYhmEYBVooRh+BMXhYGDIMwzAMwzAMo0DOhPoIjMHDwpBhGIZhGIZhGIXmRJ0uAmPwsDBkGIZhGIZhGEahOVGni8AYPCwMGYZhGIZhGIZh/sdhYcgwDMMwDMMwjEJzC8foIjAGDwtDhmEYhmEYhmEUmnMD1UVgDB4WhgzDMAzDMAzDKJCG00dgDB4WhgzDMAzDMAzDKDQ32qeLwBg8LAwZhmEYhmEYhlEhEaePwBg6LAwZhmEYhmEYhlFobrRPF4ExeIxqBWqcuc0I65GgxjoHRur/nYXX5jyuxjoHX32/Qo11Du43v6DGOgePrjmnxjoHk+2C1VjnYIxjqRrrHLxa0LlWGAwxtVdjnYPU6s5V3yprO9+Kllvz1qsxw6P8rYfUmG7p+s95aowxVFgY3sZE9ExUY4whklHauTrql05vUGOdAw+/sWqsc5Bo56fGOgdnKkvUWOfA1dRWjXUOSmuuq7HOQU0nc3OrZbc9gyflzDo1ZniUv/GAGtMtXf/1lRpjDBV2JWUYhmEYhmEYRkJjRvoIjOHDwpBhGIZhGIZhGAXScPoIjMHDwpBhGIZhGIZhGAUa3dNHYAweFoYMwzAMwzAMw6iQiNNHYAwdFoYMwzAMwzAMwyjUCBGnj8AYPCwMGYZhGIZhGIZRaM4NVBeBMXhYGDIMwzAMwzAMo9CcqNNFYAweFoYMwzAMwzAMwyg0J+p0ERiDh4UhwzAMwzAMwzAKpOH0ERiDh4UhwzAMwzAMwzAKtTX6CYzBw8KQYRiGYRiGYRiF5txAdREYg4eFIcMwDMMwDMMwCqTh9BEYg8eoVqDGmduMiJ6Jaqxt+AX5wLGbA2qqa3DyWCoul15Rc+rpYtkFIRGBMDUzRVnpZZw8kgrtqmJja42o+EicOHwKF/MLZJqpqSkCQv1gZW0lGoBanDqWhtKSMpmnT/RlT3z/GFRXVYu2TPwTx+7feUimt5aM0nNq7NYICQmAs3M3VFdX4/Dh4ygtbfqbenq6wcvLA1ZWlli3bjMqKirVHMDR0UF+h5GRESoqK7Fr5z41p21cOr1BjemHk2mZKCouhpmZGWKjItRU/eHhN1aN3RqBwf6ifBxF+dTg2JETonwuqzn1uHu4wtPLDZZdLZGyfhsqRTkQVlZdERoeJOqfDdJTM5GTnSvT20OinZ8aaxt2TnZwD/CQ9ePi2Ys4n9203nqIfLtu9vIeyzqeifKycpluYmoCr2BvWFpbys9Zx7NwpeQyXHxc4eziXGdnXsYZlBSUyHhrOVPZtuNbwjfQGw5q+5B6PK2F9sECgeEBsu5dLruMU0fS5D3v3LMb3EW5EdU11Ug/kYErqu1txdXUVo21DSof+v1FAaFAlM+55son0FMeV1MjyudYo/IJEeUj2gUiW5TPZVE+Dj0c4SrKqEvXLjix5ziuNPOb3IzSmutqrP3YO9nDS1w71b38vAs4m31WzanHK9BLlJ9S99KP0e9/BeYW5vAL84OZuZk4ohYXxLnnTp9XTmgnNe3stWrbQNeR14wN3sIG+0Y2EL4hvnBwtkfV9Uoc3HlYpmnj4tkLngGe2JOyF1WVVWpq66Dn1q1CttG1C9Nk+bRkG5UPtX+NbXMUtlVerxK2te3ZqUv0YYOnv6dMr6mpxbWr15AhzqkSfYW2knJmnRozPK48d4ca0y1Wr/6sxhhDxeQlgRpnWmDFihU4d+4ccnJyZOjevbvsQLSX/Px8nD9/XnTYHZGamopLly7JeFv5+J0v1FjrIQH1pycfhG+AD8KjQ4UdpkLApau59SQOjMXkaePh4e2OPgm9ZYeq9JIiSOgBOHx8Mv716lNIP5mJzNRsmR4ZE4bxd46CX6CPEGu+yErPQVFBsczTF/q05/NFH8BSCEpPcY63nye2p+yS6a2l+HpTgdBWnJ2d8PS/HkewEB+xMVGiQ2SGI4dPqLn1jBg5GJMnjcEzz/4Fn376Da6KhxVBv8eMGXdgyJB+CAj0hb+/D9YL4dge/vXU/WpMPyxYsgIbt+zEyjUbcfdk3Yi2GzHrve/VWPvpJsrnyb8/jIAgP0THhMNcdFSPHT2l5taTPGwAxk0cgb8+/Rjmf/5DXfm4uPbAg3+ahmkzpuDatevYu/ugTG8P7l3a3oZQ3R9x7yhEDYiCm787fEVnm4SCdifUrpsd7nj8LpHvgYDegaIzbioFBhEYHYTBU4cIYekJjyAPIQDzUFJYgtH3j8XgO5JhbWsNdz93XDhzAcUXiuQ5rUUXwoME4UNPzoC3uL6wqBB57WmiE9eYuAExmDBtDNy93RCVEIm04xmyfYjtF42BI/vB09cd4aJ9o3afxGF7sDW2UGOth8pn5IxR6C3Kx53KJ9wfx5srnyfuEmXgDn9ZPmaNyidZCEtPeArxcoYEuiif4JhgDJw8GBMfnoz9KftQnN+2siGu17a9I6wN2Tb+vrGIGRgDD6pbEf44svtoA9tITE3/yzQhjjwQLGwxFbZlHM8UYsoBE0QdI9HoE+QtzvXD0Ua/S1tpj4xSbBiHWGGD1w1smCFs8BJlECRsoDpINhATZoxD0oi+GDppCJZ9vVymaSDxe+f/TcWjLzyMpfN/wXXRPnQkZNuE+8artnlK2w43so3E1L1/mS5s8xLlE9zItvHCtkQMm5TcxLaOQl82jLprJCLiwuDh54HeiZE4n5uPwvxCNbf1PPDX+9SY4VG5/ic1plvMk+9UY4yhwq6krWDy5MlYvHhxXbh8+dY6/NnZ2Th4UOkAfv/991iyZImMdwQDhiahtqYG//nHG/h01peY/se75AOoMfc9Og0/zV+MV/75JjLTcjDujlFqDuDm6Yq+g+JxZN8xNUV5M/3Q4zOwYdVm/Pdfb+P1Z2ci73TTN3O6Rl/2aHjv9U/w5guz8fa/31NTOpZRo4bIUYDH//ws3nzzfTz66IOwaMa+PbsP4JlnXsWFC8popwY/P2+MGz8cL730Nv761It44/U5ao7hMXLIADzx8APqp9uDocMHylGAfz75b8x++xP84eEZzZbP/r2H8fLzb6HgYsPOQ1FRCT6aMw8rl69VUzoWaztrIRAG4evXv8Knz32MXl694Bfpr+Yq9BkSI+vgJ898iIXv/4jRD4yFmYWZvOcnPzYVu9bsxKfPf4zPX/gU+aKDpGHP2l344uXPZMg40vRlTUfQLzlBvtV//Z8zMW/O17jroany5Upj7n3kbiz++he88fRMZKedxuipw2V6dvppvPefjzDzhfdE/jJx3F0yvaNQymewLJ+5z36Mnl49mymfWFkHP/6XKJ/3fsSYB+vLZ4oon92/7cTc5z7CZy/MrSuf3NTT+O6tb+T/vxc2djYYNnkoPn31c8x55n24eLogMDJAzVVISI6T7fusp+fg2znfY/JDE6Vt169ex8LPFuO9597HRy9/goj4CLh5u6pndRxkw3Bhw9xXP8OsZ96Dq3iWBDWyITE5XtbBmU/PVm2YJG0gUlZswudvzJPxxkQmRAiRYo7igktqSseise2TVz/Fu8/MEeVDtgWquQoJwjYqn5lPz8I3c77DlIcma9mW0qJtHYW+bNi7eR9mP/ce3nvhA2SdysawqUPVnM4DeUzoIzCGDwvDVmAuGuc5c+bUBRrd27FjBzZv3oxNmzbJ0T+ivLwcGzduxKFDh5CSkoL9+/ejoKAA27Ztw4YNG+TIIOHiIh6AgQ0bpytXrsjv09D4s66ISYzClnXbZTw74zSMjY3h3MNJftZAo0w+/l44sFtxbdmybps8j6BO75Tp4/HrkrXSJVODvYOdHFkrKiyWI3LkvlVxvULN1R/6skdDRJ8waU8vt55qSsfSr38Cflu9UcbT0jJhYmKMnr26y8/aZGWdxsWLDUUhQSOJ+/cfhq+vF5KS4mBtba3mGB5+Pp6w6qq4vN0uJCbFYv1a5T7NSM+GsSifHj2d5WdtyEW04GLTUZmy0jJkZeZIN+HfA89gL+Sfzscl0fmkazi4+QBC48PUXIXQ+HDs26C4H+dl5kkbHbo7wsbBRgpJchENiQ+VI1aVWvd8d7ce8rvIlZFEyu9BdGJvbFu/Q8ZzMnLltXfr3rB9IPdyGu05tPuI/EzH03lEjhCGV8uV0d1r165JgdyR1JXPxfryCUtoWD5hCVQ+e2W8Sfl4u2iVj0dd+RScK0DR+baPcOgSn2Bv6f5ZfLFY2rZv834hhiLVXAX6vGv9bhnPzTgj23cnUX5lJWU4m6O41BqJf+TeS3kdTWMbSDA0tSECO9cr3ia5VAdVG4js1ByUX7kq49rQiOiwKclYNG+JnJbxe6DYdu4mtkUK2zTl09S2q83Y1pHoy4b0Y+lS7BP0kqK2uhMKHjJJH4ExeFgYtgJqUEgAUtizZw8qKiqwbNkyOXr43Xff4csvv5THXbhwAffdd590Pf3555/x8ssvY+XKlfJYEpQUJ9avX4+5c+fKuIaysjL84x//QGlpqfy8a9cuvPvuuzKuS+wc7VBcVP8G8lJxCeyEqNPGysZKdoY0nSA6xl6cR0QnREn3sK3rFTGmwblHN9QaAUNGDkDymEG464HJQhz6qLn6Q1/2EAd2HUJC/1iMnDAUU2dMFN/bvjlCt4Kjoz0KCuoFBQlvmjPYWlxdesHFpSfGjhuOqVPH4g9/mCbntTG6wUHUIyoTDVQXHRzs1U+GD4mHsmKlzSEoTmna0OfSovr5fmXFZbCxt5Hig4gfnoCEkX0xcsZoZS6cgFxHzbuYI3F0XwyfNhL+vRuOonQUdM9e0rr2EhFvTfvQ+F6nc8bfMwarFnfsyK7y22uXj/Lba9O0DMUxIk1TPnEjEpDYqHwMAVtHW5SI31oDxW0dG9pmK+ygMtNQIuykNA0kguOHxEk3S+rEdzRNbRDXJ9K0sRV1SduGUmlDy88SEibkunhs73Gcz721eZO3gl0z5WPXqHzoPmlYPk3vnd8TfdtAo9R9+kVh25qm/YfbHhK++giMwcPCsBWQMNS4ka5du1aOIJJ76aRJkzBu3Dh8+OGH8m0yUVJSgnvvvRcffPCBjB87dgxvvvkmnnzyScyfP18e0xw9e/ZEUFCQFJ803P71119LkdkYmuO4ZcsWGSqrWzfnwMW9F/ok9pahUohaiy71c11oxKzx3AXyv6eFZMg/n7CwsBD2KW+aH3hsGtJOpCOuXx85Mucf7CvfrtEiE917OOPXxWvw1guzpRvppGnj5Dm6piPsId58fhbeenG2dCelhWui4hq+adQXtJBMv37xMly/XoEuXbqoORBxce3q/LTWQIvN2NjY4L+vvIsXX3wLg4f0Q2Cgr5rLtAdaSCYhKUYGeklEZaKB6qKmLbgdqLhe2cD1muKV6r2hgUaZSORpoGMqxDF0XzmKe2bLL5sx7+XPkC86scl3DZPHkHvpR09/gC9e+kwuVjP+TxNlekfQy72nnCdIgRZhatA+CDuatg+VTdqH61q/gZV1V4yaMkwuELT0uxVqasdQSeXTzG+vDXlmNC7DBuWzbJN0580/U18+hgBdY+Pr1v7dCVk/G9mvOYbKKyw2TLrxfTvnuybl2hFUXhP1q4kNDa+DylC7Dirl0/K12thbY8Sdw3Dx3EVEC9FBx0fEh8u5ox1JhbDNXNwLGlpfPh1fDi2hTxucezlj0gMTcepQKg7u+P0W19EbNFKtj8AYPCwMW4G2K+mzzz6LM2fO4PPPP5ejguvWrZNzDouKlFGdXr16iY69skIZ/R8VFSXjXl5ectGZG3H//ffLOYe00M3hw4cxbFjTh/jJkyfrROq1qta5aZBb59DRg2TIOJWFoDDl7b2tnY0cLbt4vqEL4uWyK0KQXEcP1WUxMMwfmanKYgbnROciOCIIoyYNh6uHixBLEXBx64kL4jvyz12oW9GT3LacnFs/stUWOsIectmk84jyK+XIzT7TxAVNXwQF+2PCxJEynDyZhsjIUJlub28nbTx//oL83BpOHE/F6ZwzsoNMrs7nzp2Hk1PbFylh6gkI8sWYccNlSD2ZgdDwYJluZ28LW1H/zp+/KD/fDpzPOYdubt1hYWkBI2PRZgV7ITet4byz3NRceIcqLxOs7KzR1aarXEimKL8QhVouiWczz8qFUAgSk5o5JTknsqVrXEfhE+CFIWMGyJCVmiNXSiZovpEVtQ+NFokgN8QK0T50Fx09IjDMD1lpygJU1KEfMnYgIuPC8dHrn6L8cvtWJG0vVD7OmvKhZwqVT3rDlWtpnqBXqOKdUVc++c2VT55cWdZQOJtzFj3cetTZ5hPsg5xGcx5pFNBPLT+ab2ltayXsUp61/uF+mPTgBKz+8Tcc39d0Qa6OIC8nr4ENvsHeTWzISs0WNij3D9lgJWwovMFiP7RSbMaxTCQN74vkCYPlSsYDRveXf6MjaWqbT5NRWcU2zf1F5WN9Q9s6Gn3ZQCudjps+WsZ/+PhH+X/ng0ScPgJj6PCqpK3gtddek4JQw8KFC5GRkYFPPvkEcXFx0i30oYceknk//vgjHnvsMRknF9Lg4GCEhITI0UNyO6U8Wnjm7NmzGD16tJyLSMKzb9++cHV1xXvvvSeFJo0g0mhkY/z8/DBy5EgZ5s3+Tk29Maczc7Ft404ZSOSMmjhMurxFx0fK2/S3X9bL48KjQ6TbFY2QOjo5SAFG829IgK1bmYIc8T0pa7Yi5bctMoQIQUUjhDs27ZZvrWk1UlrYgeYb9h0Uh2MHT+D44aYrNN4qHWEPPSCiE3rLzqKXrwfikvpg1ZK1KLjQ+nk57V2VlOaqrV2zSQZaOn/qHeNQWFiMpL5xMn/RQmXUIia2NwqLiuWWGl5e7oiOjsDkKWNw4kQqzM3M5EI0hYVFoh4NR/GlEvj4eKJvYiy+/XZhs1te3Ax9r0p6/FS6DNt27ZPzDWkUx4a2PtET7V2VNCsjBxvXbZHh8uUrmDh5NIpEOcQn9hHPvVr8smS1PC6qT4Sol8rcFg9PN0RGhWLcpJFIPZEu3/5fFHWJ3k4n9Y9D335xsLGxli8w8s6cq5u/0hbasyrp5UtliBsWL+pQFRy7OyJ6cAxWfrVcCijqwJaXXcG18qvoN74/yopKERIXIl/6bluxVY6E0Lw1WqjBRohiWjkz/VAaMo8KsRwfBmdXZ3R37Y6oQdHISz+D47ubLu50I9q7Kmlu1hns2LhbBmofhk9Ilu6hUfER8trXLVfm7IZGBYNc/6h8HET74BPoJevcoFH9sWHlZuRmnpFzDZ986f9h5c+rZZn0dO2B83k3fsHXEu1ZlbSMymd4PKoqRRvWQ6t8VIFRXirK58pV9B8/QLoohsSGyPM05eMRSOVjLl1LqXwyRPlkHMmAvRDqtGIpfTfNvyL3xcI2zjm81VVJadXXvsMTZftFXhrxybFY8uUyVQBayy00aH7X4AmDpDtteBzNraxFyvJN0p32b289hcslZTi695js/NNI0DV1Pmh7aPsdp9iQJGygrQqcxP0TnxyHxV8ubcaGwdJdMSIuXPwdxQbCP8wfAeH+iBsUKwUL/Ra05cWW1duwfe0OGcYKAfLin16WdaEjob9H4lRjGy3S0pxtQ9TyUWwDNi5PkecHaNlG4ots02wD0VHoy4YJ94/DiKnDseyb5VIkWtHLmHYsEmTIq5JWrPlBjekW8+H3qDHGUOERw3Zgb28v34Rv374dq1evliMxuoAEIonBjz76CPfco5+b59jBk0L47MFIIab8Q/zwxftfqzlA0uBEuT0D8eNXi+T8vZEThkkBRSKsMaeOptWNEBJffvQdaEn4oWMHS0G2ctEaNUd/6MseWpa+f3Iiho4ZhIHD+wlRuAYnjuhe5N6M/fuPYMOGrbhj6jiEhgbinXc+UnOA4cMGoqtqX3BwAO68awJ27z6AMaOHIkkIDSIv7zwWL16JiRNGYcyYofjii++Qm5sn8wyNXfsOYsee/Qj298HKNRuQldP+Pf06ikMHjmFzyg5MmDIawSEB+GD252oOMGRoP/m2nwgM9sOkO8Zi/55DGD5qMBL6xsh0yy5dZDptc0F7aVLc9Ba2wmkrtULs/DznR7nADM0H3PDzOhScLYCbv5sMRPrhdBzeelCKQ9ovb/FHC2U6sXTuEvhFBiBBnEvCZMsyZSEeWnAmcVRfmU57tK36+leZ3tGcOHQKu7fsxfDxQ+Ab5IOvP6h/mZY4OF7uX0gsnL9EzisaJjrwp4Ug3JmiLEbh7e+Jw0J4aEYhSTR2JFQ+P81eIBec6Ts6CRt/EuWTdxHufm4yEFQ+h0T59B83AJ5BXlikVT5LPlkM/97+sizKisqweakiSLq7d0f/iQNxPuc8AqMCheDsI9M7ErLt29nfoXdiBAaM6Y/VP66RosjDz10GIvVwKvZv3o/B4wfBO8gbP3ygjM44CmFLIrCs5DL6izKh0N2l6aJP+oZs+Fq1YaCoHxobPP08ZCBOqTYMGT9Ybq2hsYGITuqNmAHRSD+eIbes8FDLVJv9Ww9It+COhl6EzJ/9rdyOgWxb9eNv0jYvYRcFgmyjRYM05fP9BwtkOhElbesjt36hOZPN2aZv9GWDm7cbju45ipj+0Rgwqh8iYsNleqeCFLI+AmPw8Ab3reCOO+6QbqMaaIGYV155BVVVVfDx8cGJEyegGXj9z3/+I+cXErNnz0ZsbCySkpLkwjSaPFp8Jj09HQ8//DB++OEHOYeM5isSv/76q/xuWsmU3uLeiPZucM90DLra4N5Q0PcG9x2Nrja4NxTau8G9oaKrDe4NhfZucG+o6GKfSUOivRvcGyo0MskYNoa8wf3lp8arMd1iPesXNcYYKiwMDQha8ZTcTSMiIupcU28EC0PDhoWhYcPC0LBhYWjYsDA0bFgYGj6GLAzLntTP4oE2s5erMcZQYVdSA4JWPKX5LlOnTlVTGIZhGIZhGKYDofcK+giMwcPC0ICgBW7ef/992Np2rjfLDMMwDMMwzG0CORPqIzAGDwtDhmEYhmEYhmEUmhN1ugiMwcPCkGEYhmEYhmEYhRoh4vQRGIOHhSHDMAzDMAzDMArNjfbpIjAGDwtDhmEYhmEYhmEUSMPpIzAGDwtDhmEYhmEYhmEUmhvt00VgDB4WhgzDMAzDMAzDMP/jsDBkGIZhGIZhGEZSW1url8AYPiwMGYZhGIZhGIZRIA2nj8AYPCwMGYZhGIZhGIZRaG6rCV2Em3DhwgVs3LgRGzZsQHp6uprakMLCQmzatAkpKSnYvn27msroChaGDMMwDMMwDMMokNunPsINIFfT+fPn48svv8T333+POXPmoKysTM1VqKyslHnfffcdfv75ZyxatEjNYXSFkSiIG5cUY7CE90xUY4wh4udwRY11Dv7v5WfVWOfg+wWr1Vjn4PTO02qsc2BqbKLGOgeRsFJjnYODKFdjnQMrI1M11jkoqb2uxhhDZfOZ9WrM8Ch9aJga0y2289aqsabQSODgwYOxZs0adOvWDePHj8ff//53DBkyRD0COHbsGJ544gksWLAAzs7OKCkpgZ2dnZrL6AIWhrcxYT0S1BhjiOyc3l2NdQ785zXv1nG7cjp9hRrrHPTwHqHGOgcTnSLVWOfg3qudy0HnFbNiNdY5CDZ1UGOdg0OVBWqsc1DTCSeo7cjbqMYMj5IHh6ox3WL35To11hRyIaVRwqVLl8rPs2bNwqVLl/Dyyy/Lz8Tbb7+NgoICTJgwAVVVVfDx8YGbm5uay+gCdiVlGIZhGIZhGEaBdLgeQk5ODrZs2VIX6LMGGjGkkUINFKc0bc6cOYO8vDwsW7YMP/74I+bOnYsrVzqXd9bvDQtDhmEYhmEYhmEUmls4Rgfh5MmTWLx4cV2gzxosLCxw9epV9RNw7do1WFpaqp8UzMzMUFpaKkcRX3/9daxduxYnTpxQcxldwMKQYRiGYRiGYRgFoeP0EUaMGCFdRDWBPmvw8/OTI4jl5eWoqanB4cOHERISouYqhIWFwcvLS4pIKysruLq64uLFi2ouowtYGDIMwzAMwzAMo9CMqNNJuAEBAQFwcnKSbqI0EkjbVSQnJ0uxqHE5pc8kBGk7i3Xr1skRxsbikbk1WBgyDMMwDMMwDCOhdSn1EW6EiYkJXnjhBblH4cKFC/Hggw/Cw8MDx48fl4Fwd3fHHXfcIbepWL58OR555BF4enrKPEY38KqktzG8Kqlhw6uSGja8Kqlhw6uSGja8Kqlhw6uSGj6GvCrppWn1W0ToEvvvN6gxxlDhEUOGYRiGYRiGYRSaWThGJ4ExeFgYMgzDMAzDMAyjQBpOH4ExeFgYMgzDMAzDMAyj0Jyo00VgDB4WhgzDMAzDMAzDSLQXjNFlYAwfFoYMwzAMwzAMwyg0HunTVWAMHl6V9DamvauS+gX5wKmbA6qra3DyWBoul15Wc+rpYtkFIRGBMDUzFflXcOLoKdTW1MLewQ5hUSG4dvWaPO5ifgFyMnNh0cUCwWEBMLMwFzd/Lc6dOY8zp8/KY/TNrdijwcbWGtHxkTh++JS0iXDzcEEvt54yfi5P2JPTNnt0sSqpkbUdjHt6iIgRaoovorbgnJpTj5GVjXIMjIDqKlRnn5TpJv6RQE21iAk7RZlUZyrLPbcXXa1KGhjsD2dnR1lex46cQGkz5eXu4QpPLzdYdrVEyvptqKyslOlWVl0RGh4kyssG6amZyMnOlentQd+rkp5My0RRcTHMzMwQGxWhpuoPXa1KGhwcgG7dnUTVqcaRw1Q+ZWpOPR6ebqJ83GElymf9+i2orFDKR4OdnS0SEvvg4MFjyD9/QU1tG7pYldTGyRauAR50+6DwbAEuZJ9XcxQsrLrAI9gLljZdcS4jDxdP56s5og6KdNtudqiqrMKpncfU1Paji1VJzbrZwirQXdhjhGt5Bbia1dAe8+726OrronwQ9/zlk7mounQZJl27wCbSR0kXmFia40rGWVzLaV/ZEO1dldTeyR5egZ7Shgt5F5CX3bRd9Q70gn03e1EHa5B+LANXyq7IdN8QXzg426PqeiUO7jws0wh3Hzd0d+0uy4rIST+NSwWXZLy16GJVUqpvvQLcZXtdLOrbxWbqm5ta386L+lagVd8kop76xQajUtiXc+jW2tu2rkrqI35zB/U5mnYsve4318bC0gKB4eI5rz5HU8XzVvMcbe58Y2MjhMeEwcjYWLkHLxThdEZ9m93LvacM1A0tFuWVnabsVdccbV2V1CfQW1yPUodSW7Cni2qPpl/Q0J7mzzc1NYGfqIdW1l3lFaWJ+llWUia/x9LKsu6YqqpqUUcPyc8tYcirkhZPGaTGdIvDohQ1xhgqJi8J1DjTAtevX8ehQ4dw8uRJuclmfn4+HBwcZGf1wIEDSE1NRXZ2NoqKiuTmnKampvK8o0ePyvN8fHzkQ1DXfPTO52qs9TiKhvvhpx6Cr2j0IvqEwVw0iKdEY9iYxIGxmDJ9PDy8PRCT2FseU3qpDOHRoXjpnX/B2MQYPgFeyoP7ZCa6iY7+3Q9OgV+gDwKC/RAsRNiB3UfqOvT64lbtIahsRkxIxjOv/hVpJzOQmZotG/2H/nwvgsL94RvgA18hPg/vO1bX8WgNf4ywUmPtxQhmSaNgEhgF4x7uMHbzQ3WWEHdC/NVhbAKzuGSYBPSGUXc3mDi7ovrUAZll+dh/RU/RAsbdXGEs8jTp7eX9A0VqrP10c3bCk39/GAFBfoiOCYe5uRmOCZHemORhAzBu4gj89enHMP/zH3BVfRHh4toDD/5pGqbNmIJr165j7+6DMr09PPXENDWmHxYsWYGNW3Zi5ZqNuHvyWDVVf7wz51s11n6ofP72j8cQJMqnT2xvmInyOXpEedGgzdDhAzFh4ij885k/44vPvqsrH4LupwmTRuGNt1/EieOpOHWqfR3coK7KS5l2I65jyL0jEDYgEr383eAd5oO0PSca3MOOvRwx5L5RGHDXENkZz9hfXxcHzxiOqGFxSJjQHxu//U1NbT8RVbf4DBCnuz0wHI6DI9E1wA22ET64tOskarXssQ7xQI8Jiejq7wrb3r4wc7RB2cEMmDvZwOXeZFgFuAphKX6Lf96Jy0ezcUUIx/ay2aS+zFsL1Y3x941D7MAYePl7ICDCH0d2H21QJiQIZ/xlGrwCPBEUHSTqoCkyjmfKvAkzxiFpRF8MnTQEy75eLtOISQ9OwMi7RsDa1hqe4nvPn8lHYX6hmts6nI2VTn27EeUz4N7hCBb1raeob56ivqXvOYlqLdscRH0beN9I9BX1jcRt5v5UNUfB2bMH7nzpQXhH+WPvL9vU1PaRX1Ouxm4OCaD7/3IvvMUzPSQ6WN736ccz1Nx64gbEYNw9o+Hm7Yre8RHymDLxHG3pfBMhkO784xQh9D3lC1zKO7r3GCquV8DOwRaT75+AkKhgePl5iEeVOU4dbvh7aNMWWUjX8+BfZsg+SqioQ6Yt2BMr7Bkv7HH3dpP2pGnZ09L5YX1CMeqOEVI4+gZ5IyfjtBS1o6YMk/Z5+XtipIgHRwbht8Xr5Dkt8ce/PaDGDI9rP36lxnSL5V2GazOjwK6krWDNmjWYN28efvjhB/z000/48ccfkZmZiSVLlmD+/PlYsGABfv75Z5l+4YLyBpbegL3yyit49NFHUVBgOPsJDRyWJN/ovfz3NzB31jxM/9NdskFuzP2PTsdP8xfjP/94A5lp2Rh/x2g1B8hIzcIbz8+SYdXStTLtavk1fP3JD/jvv97Gmy/OFuIrCp4+7jJPn+jCHjdPV/QdFC+FnwZfIXBpZPTN52fjtWdnws3DFcHhgWpux2DU1RqmfQahYsVXuL7wYyHwesHY3V/NVTASQtA0LAEVv36DisVzUbFmgZqjINOXfoaKZV+oKb8vJCjoZcI/n/w3Zr/9Cf7w8AxYNFNe+/cexsvPv4WCiw07d0VFJfhozjysXK7UO0Nm5JABeOLh2+shOHzkINTU1OCpv7yAd976CA8/en+z5bN3z0G88NzruHihadvm5eWOIcn95TG/J1Z21kicPBA/v/4NvnnuMzh79YRXhJ+aq3C5+DJWzV2Kfat3qSn17F25A4ve+k799Ptjam+NnncMQPor3yL1n5+hi3cP2ET5qrkKZYezkPrsl0h7/iuc+fI3uP1hlEy/fr5YplHInrUIlZeuoHjrUZnXkdjY2WD45KGY++pnmPXMe3AVbW9QZICaq5CYHC/qYC1mPj0b3875HpMfmgQzCzOZl7JiEz5/Y56MN2bbb9vxwb8/kiH1BgJDX1B9i588AEte/xYLZH3rAc+IhuVD9W3d3GU42Ex9Ixv73p2MjL1NX5Tpm77JCfK+f+vpdzF/zre446HJ4jmq/Oba3P3InVj69S94++lZclR25JThMr2l86sqq/Hxa59h9gsfYPa/P0RQRCA8fJV+QdKwRNg62mLmc3NEeA/rlulu9CwpOVFezxtPz8SX4nruasGeaY/chcXCnjfFdZM9o1R7WjqfhO6MP0/D5tVb8fYzs+R1nz2tePF8+/ECzH5R2CnCudzz2Cjq6u0MjZzqIzCGDwvDm3Dx4kW88cYbGDt2LD777DN89NFH+POf/4y8vDy89957eOCBB/Dpp5/K9BkzZsjGRHMejRjGxMRIYUmcOHFCjixqoJHGjIwMKSKPHDmClJQU7N69G7t27cK5c01dBnUBCbYt65U3kdmiISRXD+ceTvKzBnIT8Q3wwv5diqvO5nXbENs3SsYJW/Fwp++h0UMaWSNKS8qQm5Mn4/RW+LJ0I9F/9bpVe6jTO+Xe8fh18VqUabk0kmtpceElWTb0JriooAhx/fqouR2DUS8v1Bbmo7bsknQJpRE/E98wNVfBNKQPqs+kw9jZBSY+oeQbo+YomHgGynQjB2c15fclMSkW69dulvGM9Gw58tyjZ9NrIxfRgotNRyjLSsuQlZmD6mpykTVs/Hw8pavl7URSv3isXaO4+qSnZcry6dmzqUu0Uj5NR2S6dLHAjAfuwqKfl6OkGRfUjsQ92EO66pUUlIjbpxrHNh9CYEKImqtwtaxcupfSy4rG5KXm4lp520fF9AWNBl7NyUflhRLUiustTjkMh8SG9tRcr5TupPZJobBPCMblo1lqTj3dkqOFgMxAZUGpmtJx+AR749zp8yi+WCzv4b2b9yEyoaHLcGRCBHauV4RTbkaufI44dVfa9OzUHJRfuSrjjenp3lOeS+6m5BrY0biq9a1M1rcanNh8GP6N6tu1G9Q3v/gQ6ap5YsuN3Q/1Qe/ESOxQf3Ny9aT7XvOba6DnKI3sHd5zRH7eLo6PEucRNzqf3Mx7i3JJHBIvXS41njqDxw7E/m0HEBodgrAY8YwS/QZdQde1ff1OGW/JHqoj2vZsE8dHJfaW8ZbOp1FOdy9X2Tcgm8jlmUY/tbEVxwT3DsKOjU3F/20FaTh9BMbgYWF4E7Zv3w5HR0eMGqW8eSXINfTUqVOIj49HXFycmgqEh4fD09NTxlevXo2+ffviwQcflKOJJBhJIH7+eb375zvvvCOF4NmzZzFz5kx53LJly/Dkk09i27ZbcyNpCXtHO9GolaifgEvFJXLeoDZWNla4Wn61TuReKiqBnTiPIPGUf/Yiho0djAl3jsbQMQ390E1MTNA/uS+uX7uOjFOK+48+uVV7+iRESRG4Zf12+VkDXTuNPCYOjENMQm94+nrIv9WR0NzB2iv1nTeKU5o2RnbdRHCCSVg8THr3g1niSMC8i8yrzjwhXUxNo/rDVKQbdW147u+Bg/gNiwrr5yYVF12Cg4O9+on5vXF0tEehVvlQWTmItNaS2DcWdnY2Qlz+/m/LrextUFZUf/9cLi6DtUi7XTFzsEFlUb3YpjilNaaLuzO6j0+EkxCAhSmNRAa9OBufgPylDdu7joJGiEpEG62hpLhUpmlDHesS0UZrKKVjRNqNINdRmuc+YEx/jJs+BkG9O9a7g6D6dlmrfKi+UVprsOlmJ0cbN3z5q/IysoMhwaP9m1MZUZo2Xa27yhclNJpLaB9zs/MHjR6AUXeOEOV0Xs4zJLr3coZ/iB8GjEiSrpfJEwbLdF1Af5ue8xqonjW2h15q38ie5s7vRi+dyWV4ZBIGjRqAyfdNgE+At3qUQvyAGGSdykZBG12ZDQ6NkNN1YAweFoY3geYU+vk1dD8iWkonSIAsXLgQd955J/r374/09HScP38e48aNw7p163Dt2jWUlpbKkcGhQ4di5cqVcl7iBx98gL///e83dD2lv7tlyxYZKquvq6k3xsW9lxxZo1BxvVI+QDVYWFjIuVra0HwPuh7NGzw6noQekZ2eg2ef+A9ef+5dLPlhuZzfR28SCTo+Kj4S4+4Yhbnvftnke3WFLu154LFpSDuRgfh+MXKk0T/YVy68cf7sBXwzd4EUhuRmSvMImpu8rleqKkVvUMuNj+KVDd9O0nxDoy5dUbH6e1T8+rUUgsY93GSWdCFd+jkqVop0N18YewfL9I6GFpJJSIqRoaKiQo4qaaCyoPuB+f3wEOXTN0nUcxHo7XeXLsqLBYLKSrPQVGv481/+gOPHTmHAwAQ5EhwSGoDuPbqpuR1LVUUlzLrU3z+0MFbFtUb3z20EjQYaa9lD8epGoxVE6b40pD79OdL//TVcZwyFsdbomUUPB7k4ze/hRkpUXhPttZZrMr1807TFGmiup3abTsdU3ORZsm31Nrzzj3fxwYsfyblgd/5pqprTcdDIWOP6VtnK+kbzEul4JzdnuIf5wFoIfvfQhoJD19CiLzTqRYGuveFztGm5VFU1fI6aC1s1xzR9DtfnkdAl98r/PP6aFPhBEYrrcGVFlRz9/eCVT/DjZwtx76N31/Ul2oNiT6QMFY3sUepZw7JobI+FsEdTzxrbozmfrtm5hzPWLNmA2f/+QLqRjptWP2hA35U8fhDW/bJeTbl9ofcT+giM4cPC8CbY2NigpKT+zZGGltIJGgHcuXOnXLRmx44d6NatG1asWCFHGrt27Ypjx47JEcHAwEA4Ozvj+PHjSEpKko0KLWpDI48tQQvgLF68WIZr1a3rsPkFesuRPQo0PzAoTJmnRi6h1rZWuHi+oRAlN1BqBHv0UlzI6PiMU4oLLIlejevE6ew8OUJIDwiCVv2c/oepWCoE48G9inuGPtClPefy8uXcwVGThsHN00WuTOoiHjDE3h0H8OYLs/HxzHnoamWJowdPyPSOoqbgHIwdxDWbiQeUqBvGLl6oyT+t5irUnM9BbdEFZUEaUd9qSwphZGUr7mxj1F5TFh+orbgmVzM1sr31VffaQ0CQL8aMGy5D6skMhIYrAtXO3ha2ttY4f/6i/Mz8PtAqseMmDJfh5Ml0hEco5WMvy8emTeVDKxFHRIZg8tSx8PJ0R3xiHyk8fw8u5JxHN9HRNhcdPGpb3YM9cS79jJp7+3E1+zy6uHWDsaVob42NpGtpeWpDe0y61ndmr50rFELQEUZd6udWdRsRg5JdJ1Bd0vqFSXRJXk4eerj1kC6TVCa+wd7ISW3YpmWlZsMvVJmbZ21nDSvRphfm33jhq+vimUQChELGiUw4du/4tq5A1DcnUT70PCTbyLX0fCvrG0mTa5evImZ8EgKTwmAnyi0gMVTJ1BO0SAqN5FHISs2Bf6jyottG/ubWKGj0m18pK8f1iutw7qW86KHjNauIZonncHPnk9CjFToJeilD5eihrj1A5+RmKb9PAT2zxY+g6Uu0B29/L2FLfxmoDgVoXQ/1CxqP4Gns6a5lT5aWPc2dX5BfgAvnLsj/idzMXNBKrBocu9nLRXZ2b9qnptzGkIjTR2AMHl6V9CbQ/IZvvvlGjuzZ2SmuhJcuXZKikNxFk5OTYW1tLdNp4RmaN0GjhWfOnJEjfzR3kN7A79+/H9OmTZOjI+SeSi6kkyZNQkhIiBw5LC8vR79+/eSICs1ZJDdVymsMjVKOHDlShi9mtW4VQtpOYuuGnTJcuVKO0ROHSTeJPurcjtXLlLdbNGeQ0skGWu2TBBg17MmjB2Htyo3ye/yD/eDt5wkXt57oHRsuBLIVfvlplezkv/TuMyi5VIaDew7LUT0auaNFaXSNLu1J+W1LXQiJCMLKxb9hx6bd8vykQQlCTDojMNRfikcaQazUWmHuZtzyqqTlZTANixfqr0qIOkeYhsSgcvNyGFlaiyC++9oV1F4pk26kuHoZxt16wsQ7BFV7hP2iY0JzC43tnGDc3QUmfuGoOrAFtaXtW2KeaO+qpFkZOdi4bosMly9fwcTJo1FUVCxFA71C/GXJanlcVJ8IFIt0Ki/aDiEyKhTjJo1E6ol0ucrdxQuF8s1tUv849O0XJ+qetXz5knfmXJ07UFvQ96qkx0+ly7Bt1z4535DeTttY3+pKtS3T3lVJMzOy5bxPClQ+k6eMEeVzCQl9Y2VHe+niX+VxfWIiUVR4SZaPpyifqOhwUZajpJg0NzMT7V8BVq/agNW/KiEyKgyLflqOjRva5xZ/q6uSXrl0Gb2HxqK6qgr2PRwQMTgK675aha6ik0eB5hfSaoNBiWEISgiVWwjQaBVta0GLJNCqkhTCBkbhbFqu+J5qeU57udVVSWnbCRJ2tZXVcuTPcWg08j5bDVM7K5gKe6pKy2Eb7Q9Lz+5CQDrDro8/zByscf5Hxa3XyMQYPs/dg7PfrBMis9E2Ce2gPauS0vyypOGJcil/p+6OiE+Ow+Ivl0oBSCuKXim9gqtXrmLwhMHSNTEiLlz0JWuRslyxwT/MHwHh/ogbFCvnG1KZkCcHzS3s4dodPYXopDyaF3Z4V9teTt7qqqRU3yKGxkjb7ET5hA2OxsavVsu6ZllX30yl4AtICFHrWwWKzhbizLFsHF67B0fW7UOJEE+0OulPL32pfnP7uNmqpGey8rBz424ZysVzlFw5S4pKERkXIX/zDcuVuca0aii5UtJ9T1uNeAcoz9GBo/oh5dctQhydkWXW3PnkehnaJwTdenaTK5n2SYrChpUpQggWyhG73qJ86ZkaGBEAR2cH/PpTy6v/3qyFJ5FZb89VDBPXQ89/uh46e30z9jio9tB8w0Gj+tfZ09L59FKcViql0V1yLY0bGIsTB0/h1BFlsaPk8YPFs8ocqxe3bnE0Q16V9Oq3Xyk/uo5D1+kPighjyLAwvAk9evSQW1JkZWXJrRfIlXPfvn3w9fWV6WVlZaIzdVmmk+CjET+aL/jvf/9bzhWcMGGCXLjmzTfflK6kNEpI8dzcXPznP/+BpaWl7DDSCqc0ekiL03z//fcYPXo0goKC1KtonvZsV0GjaSTi+g6Mg72jPb76+Hsh5pR5OFOmjcdJ0cCRC0hWWrZ0owwWYoka3OULV8nOUkhkEIaMHAAffy/5PV99+J3ozJfA1cMFsX2jUSg6797+nrLxPJt7rm5PQH1xq/ZoQ2I2W4gYciMlpkwfJwVhL9ce+OazH+vSW8utb1ehjBqahveV+xRWHd6OmpxTMPEKhJG1rbKn4XXx8Bedd9PgGLldRdXBrag5nSbdS03jhyrbXFD68T2oSbu1RQ10sV1F/vmLcg7ogCF95Xy2Tz74Ss4LJabfN0Xum0cvFOISozF+0ig5B9HN3UV0RMxwYN8RWAth9egTD0kXRxKJ/oG+2Lh+q+xktBV9C8MVazbg0LETsBMCNudMHpydHOHu2kvN1T262K7i/LkL8j4aNDgJjqLT9OF781Csls+M++4Q5XNclk9C3xhMUgW+u7urLJ/9++r3lSPcPdyQkZaJvLz2LaR1y9tViNs7P/scYkYmwDXAXa48mrE/FX59AuV+c7QISBdrS4z8vwmio2cGUwtTuPi54eimA1JwJE7sD9/oQJSXXEYPbxeUXChusM9hW7nl7SqEPbRvYfcx8bAOdMfFlbtRsjcVtjEBMBP2UB5tUdFtWB909XOBuaMNcj76BZWF6rY8ZiZw6h+BM/NWo1bYd6u0RxiSDWeyzmLA6H5ya4Mtv27FsX3H5QIkNIeb9jSkbSbkAmcD+sjO909zF8otBIhhk5KF0AiWe9W6+biiSDxvzuacQ/+RSQiLDYNngIcQl+VYNv+XOs+W1nLL21UI26hORY2Ml3sZHly9G1mivvn0CZD1jfY07GLdBUNlfTOX9a2nqG8nNh2U9U1DF6susl6m77o1D5W2bFdBo2G24jlK21GQu+eCuT/XLRJD21OkHk2TXjc5aTmI7d8HgUKcU1mtXrRWPkdbOt9GxEdMHiq3q/Dy85SibfemvfJ7aREiqgMRotychHCkc4oLWn5x2fBpfWO0r4eeN9/P/anOHtqeQmMPjXjGCXuCwgNwJjsPqxataWJP4/OzRV9ioBCRtFUFrW/wy/cr6rZbiUqIxL5tB+R3tQZDFoblJAz1QNd7WRgaOrzBfSug/QlpRVKaK2hubo7u3bvjT3/6k3SrpHSaP0guld7e3rj//vulIKRFZshtVMNrr70m5xtSePzxx2Fra4tXX31V5lERvP/++9JNlMThxo0b8fbbb8tRwxvR3g3umY5BFxvcGxK62uDeUND3Bvcdja42uDcUdLHBvSGhiw3uDYn2bnBvqOhig3tDoq0b3Bs6bd3g/nbAkDe4Lxg5UI3plm6rb+9tPP4XYGFoIGzYsEGKS3JR/fjjj+WoIY0+3ggWhoYNC0PDhoWhYcPC0LBhYWjYsDA0fAxaGI7QkzD8jYWhocOLzxgItFopLShD8xZpZdKbiUKGYRiGYRiG0Tmkw/URGIOHhaGBQK6mc+bMkRvl04I2DMMwDMMwDNPR1NboJzCGDwtDhmEYhmEYhmEkNMlMH4ExfFgYMgzDMAzDMAyjQCJOH4ExeFgYMgzDMAzDMAwjaW60TxeBMXxYGDIMwzAMwzAMw/yPw8KQYRiGYRiGYRiFWiP9BMbgYWHIMAzDMAzDMIwCuX3qIzAGDwtDhmEYhmEYhmEkzW01oYvAGD4sDBmGYRiGYRiGkdTWGuklMIYPC0OGYRiGYRiGYRSacwPVRWAMHhaGDMMwDMMwDMNImttqQheBMXyMagVqnLnNiO3VX411Dmo62eukZxJM1Fjn4MWt5Wqsc/D2B0+psc7BNz+sUmOdg6r9l9RY52BSlaUa6xx8alykxjoHniY2aqxzkF7Vue6fzthR3ZG3UY0ZHmf7DlZjusVlu+HazCiwMLyNGe0xWo11Dq7XVKmxzsGmC8fUWOdgfK8+aqxzkFJ0Qo11DvKzflNjnYP48PvUWOcgwcJFjXUODlReVGOdgy5Gpmqsc3C1plKNdQ6MjDrf/DRDFoZ5CUPUmG5x3blBjTGGCruSMgzDMAzDMAwj0Xb/1GVgDB8WhgzDMAzDMAzDKJCI00dgDB4WhgzDMAzDMAzDSJrbakIXgTF8WBgyDMMwDMMwDMP8j8PCkGEYhmEYhmEYSW2NfgJj+LAwZBiGYRiGYRhG0pwbqC4CY/iwMGQYhmEYhmEYRqG5hWN0ERiDh4UhwzAMwzAMwzCS5kb7dBEYw4eFIcMwDMMwDMMwzP84LAwZhmEYhmEYhpE0tzm9LgJj+LAwZBiGYRiGYRhGgUScPgJj8LAwZBiGYRiGYRhG0tz8QF0ExvAxqhWoceY2Y7THaDXWeuyc7OAZ4AkjIyNcPHsRZ7PPqjn1eAZ6wt7JHjU1Ncg4loHysnI1R1QYcV5oXCgqrlcg9WCqTHPs4QhXH1dYdrXEsT3HcKX0ikxvK9drqtRY66Hr9BLXS9eVn3ehWXu8Ar3g0E3YU12DdGHPlTLl+nxDfODg7IDK65U4tPOwTCOsbLrCO8gHxiaiIaupRdbJbFwuvazmtp5NF46psVsjNDQQ3Z27obqmGocOHkNJaZmaU4+Xlzu8vTxgZdUVa9amoKKiUqabmZkhMiIEXa0spf2HDh9HWVnbbSHG9+qjxtoG1Tn3AI+6Onc++5yaU4+HyLdTyyjreGZdnTMxNYFXsDcsrS3l56zjWbhSchkuor45uzijslKxMy/jDEoKSmS8taQUnVBjt0ZwcAC6dXcS116NI4dPoLSZ8vHwdIOnKCMrcY+sX78FlWr5aLCzs0VCYh8cFOWbf/6Cmto28rN+U2P64WRaJoqKi2Wdio2KUFP1R3z4fWqs7fgGesPR2VGWyaljaeL+bdomdbG0QFB4oLDHFJdFm3DySKrouNTCSZzn5ech4tQ5qkXGqSyUXiqFsbExImPDRD02hpGxEQryC5CTkat+281JsHBRY+3HxskWvQLcqSFG8dkCXMw+r+YoWFh1gVuwFyxFG3Y+Iw8Fp/PVHBXRL/OLDZZtXs6hdDWxfRyovKjG2o6PKB9Nm5x6LL2uTdaGyicwPACmVD6i/FJFOVJ7bCnaMv9QP1jbWCEn/TTycurbfP8QX6VNr6jCgR0H1dTW0cXIVI21De1n0AXxDMpr5hnkLZ5B9s0+g+h67VElyuOg1jNIg4tnL/m83pOyF1WVbXs+Xq1p2Ma0BaV8HOT9k3Y8vcX7R1M+ZM+pI6J8xP1C5RMgyseqmfKJ7ReNKvEb0M1Fxx7c1dTmlqDft70YYn0jduRtVGOGR0bYCDWmW3yP6vc5xdw6Ji8J1HinY8WKFTh37hxycnJkqKqqgqOjo5qrUFhYiKNHj8LV1VVNuXXoO69fvw5LS6UzS3/78uXLsLW1lZ91xXezvlNjrYMa1jEzxqDPgD5w93eHX7ifFHLaDxx6eN39xN2yox7YOxCm5qayM67BxdMFD7/0MIKig5CyLEWmhcSEYMjkIZjy8BTsFQ+wovwimd5Wqtu4+ynZM/6+sYgZGAMPfw8ERPjjyO6jTeyZ/pdp4uHqgWBxzabmZsgQwoMYP2Ms+o7oi+RJQ/DL18tlGtF/VBIGjR+IXu69EB4fJh8UmnPaQs6V9necNHTv3g3PPvMXhIQEIC42Ghbm5lLcNWbUSPH7TxmL5597Ch9/Mh9Xr16T6dHREXjssQfg4+OFqN7CFlNTHDt+Sua1lUCbtndsqYxG3DsKUQOi4CbqnG+YH07sOd6gjOy62eGOx+8S+aIMRZ0zE3UuW61zgaLMBk8dIoSlJzyCPIQAzENJYQlG3z8Wg+9IhrWtNdz93HHhzAUUX2hbvcu+WqDG2k83Zyf87R+PISjID31ie4trN8PRIyfV3HqGDh+ICRNH4Z/P/BlffPZdXfkQ9BtNmDQKb7z9Ik4cT8WpU+3rsP/jyRlqTD8sWLICG7fsxMo1G3H35LFqqv74/OMlaqxtOIoO7R+fvB++AV4Ijw6V9zx1BhsTPyAOk6aNg4ePG6LjI5EqOsCll8pkp3bYuCHw9vdEaO9g2Dva4djBE/IlxbQ/3gGfAG/4B/vK7z6896ho6yvUb7wxbqY2aqydiH7xgHuHI3hAJHr6u8EzzAfpe06iWutecujliIH3jUTfu4ZIsZG5X3l5p8HZswfufOlBeEf5Y+8v29TU9nG+pv6FYVugDvqDf5khfkcvhKptcvrxDDW3ntgBMRh/z2i4e7uhd3yEECgZKBPl06OXM6Y+MBHjRF7FtQoc2Vf/Am7yfRPQf3gSRkwaisVfL1NTW4epEPxtRXkGjUOseAZ53eAZNEM8g7xEG0bPTWrfNM+TCTPGIUk8g4aKZ9AyrWcQYW5hjjv/byoefeFhLJ3/C65fu67mtI6qdu4mToLwoSfvhbcon7CoYFk+aULMNkaWz7Qx8KDySdAqH5fuonwmibzR8t44sre+fD78eRYsuljA3VfUX18P7ErZo+bcHPqt24Oh1jfij397QI0ZHsUffqvGdIvj/9Pvc4q5dTq1K+nkyZOxePHiunDwYNM3OkeOHMF//vMf9ZNuSElJwfbt29VPwPHjx5Ga2vAB/XtgbWctBdy81+fhw2c/RC+vXvCP9FdzFWKHxKK2uhbv/+t9/PDeD5jw4ASYWZjJPHpQjbhnBE7sbTjSkpOag/lvzZf/dyQ2djYYNnkoPn31c8x55n0pWgMjA9RchYTkONTW1GDW03Pw7ZzvMfmhiXX2pKzYjHlvzJNxbUbcOQKbV27Bh//+SByzCYMnDFJzOp7Ro5LlyO2jjz2N116fgz8//hAsLCzU3Hp27d6Pfz79Ci5caCh2Hrz/LuzZcxBPPvUC/vvabDz+5z+I883VXP1DdW7g5EH4+vWv8OlzH8s659eozvUZEiNt/OSZD7Hw/R8x+oGxsoyoIz75sanYtWYnPn3+Y3z+wqfIz60fAdmzdhe+ePkzGTKO3NroR3sZPnKQvPan/vIC3nnrIzz86P3N/r57RRm88NzruNiofAga7R2S3F8eY8iMHDIATzxsuB0ZDf2GJsoy+e8/38Zns+fjnj/cIduuxsx49G4s/HopXhXHZaXnYOxU5Q35icOn8Nbzs/H2C3Pw05eLcNcfpsh06uy/9+onIn023nlxDoIjg2TntqOwEvdS/OQBWPL6t1jw3Gdw9uoBzwhfNVfhcvFlrJu7DAdX71JT6qF7qu/dycjY274XQ7oiKVkpnzeenokv53yLux6aLMpHaZO1mfbIXaKz/QvefPpdOVIzaspwmV5SXIrvPl6AlF+3yM/abFiegk/e+Fz9pH/oGTRcPIPmvvoZZj3zHlw9XRHU6BmUmBwv7K3FzKdnq8+gSVrPoE34vJlnEBEpxJaZuTmKCy6pKR1DUnKCvN43/jkT8+Z8I8pnSrPlM10tHyrH7LTTGD1VLZ+iEnz78Q+ifDbLz4355M3PMeuF9zHnpQ/VFP3SmepbR6J4TOg+MIZPpxaG5qJRnTNnTl2YOnWqTL9w4QI2btyIbdu2yRFFDSTeMjLq3ySRwCsvV96KnjlzBps2bZLhwIEDMi0/Px9bt27F5s2bsWPHDjlKSMfTSOXKlSvlsUVFRfD19YWnp6c8p7S0VJ5DeXv27KlzhSMheeLECWzZsgUbNmyQ5+ka72BvnD99HsUXi1FdXY0Dmw8gQjx8tAlPCMeeDcpbvLzMPBibGMOxuzLKGhYfBouuFti3eZ/8rKHgXAEKzxeqnzoOH2HPOS179m3eLx6mkWquAn3etX63jOdmnJHuYE7dneRnErLlV67KuDZZJ7MQEO6P6P7RQmgG4pjWG8+OZsCARKxatV7GU1MzYGJigl69usvP2mRmnm4iCglyUdSkX7lSLuqhG3r0aHq+vvAM9kL+6XxcEp0bKqODos6FinqkTWh8OPZtUOqUps45iDpn42AjhSS5iIbEh8I9wB2VWqMz3d16yO/yCvGWIvL3IKlfPNauUUbO09My5bX37Nn0983JzkXBxab3SJcuFpjxwF1Y9PPyZl2EDQk/H0/pCmvoxCRGYev6HTKek3Fa3PNG6NZDuec1kDssjQge3K24sm1dtwN9+kbJOLnJk2twTFI0ohN6I/VomkwnyAWY0qizWVpSKl1MOwrXYA/pGlom7gdyiTux+TD8E0LUXIVrZeW4kH1e5jfGLz4EFpYWOLHlkJry+xCVGInt63fK+OmMXHnPaNpkDeSlQe68h/cckZ+3ieOjEnvLOLn95mblyfakMZmp2aJNb99IZnto/AzaK56NTZ9BEdi5XhHquWSv1jMou4VnELknDpuSjEXzlnR4b5rKh35vgsrHqKXyEffP4d03Kp/mRyzDokPkiFxP1x5qin7pTPWtI6Fap4/AGD6dWhjSjawRcxTOnj0r3xx9+eWXMvzyyy9S/Gn4/vvvsWRJvfvSn//8Zykiy8rKMHfuXJm/aNEirFmzRuanp6fL4yntk08+wb59+6TLKI0Q0kgkjVKS8NT+Xjr2iy++wMKFC/HBBx9g//79Mv3ZZ5+V17R06VK8//77Da5DG3JLJfFI4WpV0wfKjaCOdmlRfUemtLgUNvYN3ZtsHWxRUlw/V4uOoTRyh0memoxlXywTzynDuL1tHRteK8VtHRvbYyPfYGqgt3+UdiP2bdmPwKggJE8cjODeQcg41nY3Ul3h5OiAgoL6lwSFBcUyrbWsW78ZA/onon//BAwbOlCONjo52qu5+ofqXJn4zTVQnNK0UeplfRmVFZfJeknikIgfnoCEkX0xcsZo6eJMkOuoeRdzJI7ui+HTRsK/d8O39B2Fo/gtCwuL1U9AkYg7tOH3TewbK8S7jRCXm9QU5laxE+3VpQb3fIlM04bmEV8rvyafB8QleYydjBO93Hti2LjB6DskATs2Nhx9Sx4zEOPuHIVzuedRcKHjXohZiXviclH9y4PL4j6htNZg081OjjZu+PLX3739blo+pU3Lx1pTPsq1NleGhkDTZ5B4vog0beQzVctezTO1JUg4DpuUjGN7j+O8qGMdDd0HDZ6ZIq59bxA0f/Cq1v2jlE/DY5rj0O7DiO3fB8MmDMHEGeNu+Dvois5U3zqS5haO0UVgDJ9OLwy1XUlpNJBG4ubNm4c33nhDBisrK/XoliHxRkLs7bffxnvvvYfHHntMpvv4+MhRSHJZdXFxwVdffYXu3btj1KhRmDBhghylDA0NlccSNDr41ltv4W9/+5sUf/369ZPiUAOdO3PmTPz973+X4rE5Tp48WWfP5aq2LSJCCw5QZ1oDuVeRz7w29LZc2+2K4jS3oc/APjLew60H/P4/e+cBEPWR/fGvSpOOFEE60gUBxa7Yey/pPXeXcr3879Iu5e7Sm5qYRKPpptlNTDOx9947IqioKEWkV//z3v4WFlyQsosreR8ycX7z+83uvJ36fvNmJiaUG/TOXWqaMbU0lPZr01pbnmtlrv1MbcbeNRafz/wcr/3jDXw2Yz7u+evd2p2WISjQnxU5crRGw669nXZHN8NkuD7teny9YDmST57ClMlj4Ovrg7Pp55GXf+3Ce3PBv3+tPCqr9fvTLKCxckmmex06umPDN+vx4X/mIkMNkobeNpyfIfPSdx+bhQ+em8ub1Uz43SQObwkCAnzRt19PdlRf7Oxq5k9xI/Lnj3/5DQ4fOoakgb3R0dsT0V3C4dXRQ7srNJRO/j48k0eONl6idUx66GVI7XauTJUtWm+rX7dE5r+Ga7hoHdFLj7+B6f+Zhcn3TOQZRoKUKjIxfeqP/+WBY1TXSA5vCWi20tqgnlgbqUt1QesS6Xl3P0/4x4TA0c0J/l2CtbvmhxTt+N5x7Grnj7E2uby8Vv4ouUsbucauJSgrVrKo9OvRyVIzndTv1pa3PlmcXB0x8tbhuHT+Err1T+Dnu/aK5fXL5oLyJ0HlDbmy0lL+vfWQv7ZM5WosU1/9qYs3n34bM56dhfdemovI2HDezMkctNby1pIYU+pM4QTL51dlSjpgwAA2Ce3YsSMrctQIDBpUvX6Mrg3fpurfhu3fvx/9+vWr2jzGyUn3lpZmG0kZpNk/mj1MTU3l8LogM9OCggLExOgawyFDhuDQoWozRfoOIiwsjM1UjTFy5EhMnz6dnaedpxbaMM6nnYeXnxebE5GsZFp6Ovm0dlcHmVfqFT5aH0ZvBvWbydBOkQMnDkRcvzjeibRrX/PvTFgf59LOsaKqlyckKkSlv6Y8ZKoT2iWU/SSPo3O1PHXRJTGazU4JMv3x8K5pdmJuoqLDWJEjd/jIccTH6V4uuLm6sGno+QvGy4YxylWH9867H+Fvf38GS5Z8hwp1na6Uw5bigipzHvoy17YNm5aeOVEzj84cP4NgrczROip7J3veSCY7IwtZ5zORrZkpn0s5xxvVEKRMUl0ll3YklU2vWoqIqDCMnziC3dGjyYjtGsXhrq7Oqo1wwoULDd906Ozpc+gaF40p08bxC4Fefbqz4ik0DtpYgmbyyJF5V0QX3TpWZxcnOKg6f+lCTTNr2pWwuKQEXj66NjQiJgynVDyivX21op9x/iI8O7rDxs6aB+Y0eCRI0cxUZbQl1xhmpl1Qip0Hv0Sh9o5MSy8k69qp60HDseL8IiRO6IeIfjFwUe13eJ/ql5bmJjgsCIPGDGBHvzNt8EM4aW1ypqrrhhSovqaklPJH95KEdoU8daJl17A3hPS09Bp9UGfVp9bug0jeUMM+VcmbVU8fZKfKH1mp9BvRF0MnDubdvpPU70bfYS5oo5lBY5PYnVJ9Jv3eBK2hdHB2NJo/pQb1J0zVn9QT9Y9/yIST4hGFhUU4q/rv2iadpqK1lrcWhYbC5nCCxdOqFUNjODo6oqioiBU0Ij09nf8lSOG7fFm30Ds3N7fK7+7uziahpaW6t0z6dYHvvPMOpk6dyrN/EyZMqLpPgwcakNeG3jqT068fJCWVPluP/q00mZIYs2dvLmdTzvKamN7DeyNhQAJ8An2wd9NeVhbJEdt/2Y7IhEhW/vqP7Y+je44iPzcfqxavwvT/m46Z/5qJxXMWI/VoKpbO1Zm70qA8oX8Cd3rh8eGISIjgcHNzRpOn74g+6D6gG3yDfLBn0x7uqMkRW37eyruRJvSLx8BxSTiy5wjycnXmWGExoYjp0YUHgrSe0KuT7jfYt3kf70ratXcsBo0fyFuFtyQ//LCaFTlyK1asRK+e3TB4cD9MU8oDbTKTo5ku9eyRwDNUBG1gMnToAL5OSuqNrl11a4+8vDwxZEh/DBrYF3fdNQULFn7bqBnH5nIuJR35l/PQY3hPxPWPh7cqc/s37YOnrxc7Yueq7QhPCEds367oN7Yfju85zmWuILcAB7ceQOKwHryWMLpnFxzYpFsTFtk9Cl16x3B496GJ2L2m5fLo55/W4ol/Pc/uh+9XITExDkkD+2CiUuRpA5nLl3X5012F6zcKorWdg1QeUv70698TMTG6maa//Okp/OWPOrdt2258NO9L9Rk3dg1YXRw+lozd+w+hUJWfLTv24HxG83fdNRW0ppBm8sit+2kjYrtHo0f/7hg2fjAO7j6EK1qdj0mI5hkD4udvVmPstJH8XJ/BvfDzt7qt42kmg9Yb0uzjoJEDeHdCGjjSbo09kxLRvU88eg7oDi9vDxw90HIbuWSknEdBTj5ihycickAsPAO9cXTTQXTw9WRH0C7Skf1j4RGg2vRgH/a3tWqHbUvW47N/vovPH5uDX+Z8g/SjaVg1bwXHaQk2r96KGc/MYrdh5WZ06RaF7v0SMGTcIBzafbiqTY5OiKrKn1XfrMGoqSP4ud6DemL1Cp25NSnoZI7oG9iJd5Akv36NcURsGOJ6xrIyReG0Q6Y5qe6D+nIf1CmoE3Yb7YOiuA8aNG4gDtfog8IQ2yOG00vxqQ/KOHsRL/7lFbz2zzfZkVnjrGff5TbRXNAaPNoQhtyGlZt4HWBi/24YMl7lz67q/OlikD+/UP5Mo/zpxvmz6tvq/KH6oc8f8lP+ODg6qDzpxrOSFEYvXI/sM0/9aa3lrSUxNttnCidYPr+qNYa0uUtAQADPGNL6Qtp8hjaA0RMXF8emmvTsqlWreL0gQSafNIP3008/8b2tW3ULmf38/HiWkD6HNpTRExQUhFOnTvGzhpvI2Nvb86zlwoUL+d7y5cvZDLWloDN5vpzxJW8w039Mf/y84GdcSr+EgNAAdsSJ/SewZ+MeDFQKUXBkMBa+u5DDDaE1Esf2VjfoHf07YtCkQbiQdoGVysTBidod80LyzJ/xOeL7dEXS2AH48euVfI5UQKg/O+L4/uPYvX43Bk8YxPJ8OetrDicSVAeQmNSdt64eOnkw/EP9OJzMR/2CfPktrXeADz5/60sOvxHs3LUPv6zagNtumcjKxKuvVpsejxw5qOpIlJgukbjz9imsOI4fNwID+vficEcHB0yZPBbTbhmvGuWreG/2xxzeUlAeLZz5NW8wQ+sBVy/8BZnnMuEX5seOSN6fjP0b96L/hAEIiAjEkncXcTixbM5ShMaFo7eKS+Vuw3LdTne04Uyf0X05nLbl/+HT7zm8pdm7+wDWrt2MyVPHshnozDff1+4AQ4cNUHVeN/sUGR2OabeOZ8Vx1Ogh6NOvB4cbQmcgNvUMw5Zg2669SiHcjaiwEHy3cjVOpTX8DL+W5PC+o9i2fidGThyK0KgQfDSretv1vkN68XllxMKPl/K6qJEThuC0GuBvXqtbS+jm0QHDxg3m2cfQyBC8/eJsDrdq1xZ91YBx6NhBGDhStZ9KsaRjLFoKqkvfv7UY4b27IGF0b2xZuJbPMvQJ82VH2LS3QY+JA2BlbQ07JzVYJX+tjZkKcvKQ2swzDJvDUaUM7Niwm9eZ0e/76azq9rXPoB5V+bP4k+Vsrjtc5Q8pYFvX6jYRo/sjpwzjATvNvpFfP5NLSgop73T2HoWbe0aX8uRTrQ8aODapqg8KVP0pOeKY1gcNmTAYIbX6oG5KWUxM6sZ9EB1ZEaD1QYbsVv2x4fEX5oaUte0bdmGYSm+oSu+ns77Q7gC9B/c0yJ9lKn+cVD4OVvlzxiB/7DBiynDOHzr7j/yUP3RMR9+hvTFY/U79lSL989JVOHbA/Lu1t6byJggtQas+4J7W+ZGSpqdbt2647777eM3g3Llz2TQ0OjqaN3R55plneMbv+eef59lCMuekTWTomEda+0c7hdK6PprNo7WFf/3rX7Ft2zbMmzePZ/0iIiJw4sQJvPjiizwLSesX6dmHHnqITVFpHdLkyZORkpKCd999l3cw9fb2xl/+8heexaTNZx588EGEhobyzqV/+9vf6lxnqKcpB9xbMk054N6SMdUB95ZCUw+4t1RMdcC9pWDuA+5bmuYccG+JmOKAe0uiOQfcWyJNPeDeUmnOAfeWCJnqtjYs+YD7I6HmGV9GJd+Yl7hCw2nVimFrRxRDy0YUQ8tGFEPLRhRDy0YUQ8tGFEPLx5IVw8Odx2o+0xJ98jvNJ1gqv7o1hoIgCIIgCIIgGMdwvxhTOsHyEcVQEARBEARBEATG2MYxpnCC5SOKoSAIgiAIgiAIwq8cUQwFQRAEQRAEQWCMzfaZwgmWjyiGgiAIgiAIgiAwtC2lOZxg+YhiKAiCIAiCIAgCQzqcOZxg+YhiKAiCIAiCIAgCY8wM1BROsHxEMRQEQRAEQRAEQfiVI4qhIAiCIAiCIAiMsdk+UzjB8hHFUBAEQRAEQRAE4VeOKIaCIAiCIAiCIDCVV83jrsfFixexZs0arF69GsnJyVrotVy+fBkrVqzA+fPntRDBVLS5qtD8wk3GcP+Rmq91UFZZoflaB5fyLmq+1kGgi6/max2kFrau/HlnzpOar3WwdNFazdc6qNiaoflaB3vKLmm+1oFzWzvN1zrIrSjWfK2EVmiFuCV9jeazPHb6TdJ8piXx7DLNdy2kjrz++us4cOAAbGxs0L59e7z44otwcnLSntBBz3322Wf417/+hVmzZmHatGnaHcEUiGJ4E9O70yDNJ1gi461blyK1vOys5msdxNh4ar7Wwd6SC5qvdbDtwKear3Xwj8QnNF/rYFcrUwwDrVw0X+sgrTxX87UOKlvhYQeiGNYkKysLgwcPxsqVK+Hh4YEJEybg//7v/zBkyBDtCR00k/jss8+isLAQd911lyiGJkZMSQVBEARBEARBYIxtHGMKVx/79+9HSEgIvL29YWVlheHDh2PdunXaXR3FxcWYN28e7rjjDri4tK6XOZaCKIaCIAiCIAiCIDA0P2sOl5aWhg0bNlQ5utZDM4Y0U6iH/BRmyPr163l94ZgxY7QQwdSIYigIgiAIgiAIAmNsts8U7ujRo1iyZEmVo2s9tra2KCoq0q50s4O0ztCQ1157DbGxsbxBDW08Q+sRL1xoXcsobjSiGAqCIAiCIAiCwBib7TOFGzlyJKZPn17l6FpPaGgozyDS2sHKyko2LY2Ojtbu6ggMDMTu3bvxxRdfICUlBRs3bkRqaqp2VzAFohgKgiAIgiAIgsAYU+pM4eojPDwc7u7uWL58OX7++WfeZGbo0KGsLOpNTml94QcffMCuX79+ePTRR9G7d2++J5gGUQwFQRAEQRAEQWCMmYGawtVHu3bt8PTTT/OGM4sWLcIDDzyAgIAAHD58mF1t4uPj4ePjo10JpkKOq7iJkeMqLBs5rsKykeMqLBs5rsKykeMqLBs5rsLyseTjKjb7TNV8pqXv+cWaT7BUZMZQEARBEARBEASm8mobszjB8hHFUBAEQRAEQRAExnBdoCmdYPmIYigIgiAIgiAIgvArRxRDQRAEQRAEQRCYq2hjFidYPqIYCoIgCIIgCILAGDMDNYUTLB/ZlfQmpqm7koZEBMPNww2VFRU4cTgZ+VcKtDvV2LW3RURsOKysrVCQV4BjB06Aikp7h/YI7xIKBycHpCWfRnraOX6+bdu2iE3swv+2adMGmRezcPrkGb5nbixVHlPsSmrv7gzPcD9VU4Er57KQk5qh3dHh5O0Gt8CO7K+sqMSlo2dQkl/E1x2jA+Dg4YLy0nKc3nqEw5qDqXYl7VyVX5U4fvhEvfllbW2N/Lz8qvzy9PaAf5D6PRQVlRVIPnJS5WchXzcWU+xK6qTyxzc8QJURIOtcJi6m1twZ1NbBDgFRQWjvZI/zJ9Nx6XR1/vmrcGfKn7JyHNt6SAttOs3ZlZTypINnB65Dxw7VnSeRsREqT6xUnhTg6IHjnCfuKl5QaIDyq45f/e/ksVO4cvkK1524HjHqt1F1qK2qQxmZSGtEHWqJXUmPnkhBdk4Ol7MeCV21UPNgil1JHVV58wn35/KWrdqDTCPlzTcqkMtbxslzyDQob4yK17lHFMpLSpG276QW2DQauytpSEQQ1/sKVe9PHErmdrg2tlX1XpUxVQaPq7J4tVI3RKkrfmL/bqgor1CDTvWnyt++bQc4XI9vYCcEhQdi+9odKFN1rS6auiups7sL/LQ2IFO1ARmp57U71dB9F1XXqc1LO3wKhVqb5RXQEe6ddO1QUX4h3yN52zvaq3YjEG3btUVpUSlSD6WwjI2hObuSmiuvrKzaITS6M+yVfMSJQyeRl5vH/uvR2F1JdeMCV10/U4cMhuOCa2W4Nj6NF+h5PRSfxgXnTp9HUFigagtVv6biFxcVs9zl18kzS96VdG3HWzSfaRmUsVDzCZZKu+cUmr/V8u2336KwsLDqvBPqPFauXIns7Gz4+jZ88H7lyhXk5ubCwcFBC7mxzHvjY83XcKixfvCvdyM4PAgxCVGwsrHmxrk2PZISMeHOsQgI9kN8765K4VIN+OU8dOzkhWn3T1b3xqBEDS4O7NQNaNupBv+2301DiPrczlEhiOkWzfdK1TPmxJLliWjnrPmaiBpodL97GEKSYuER5gufmGCc2XEMFQaDm6B+MQgf0R3unTvBr3sY2tpY4eKR03yP4oaP6IYuk/ph92e/cFhzOFZ5RfM1HV1+3aPyK1DlVzSsVXqN5VdPlV8TVX75q/xK6B3H+XVF5VcPNQgcOKo/Ajv7K8U9hgf0pBw2Ba92zazHaiQ45O6RiEmKg0+YH4JjQnBixxFW9PR08OmAIfeORtJtQ1BWUoaTu49pd4DB94xAwvCe6D1xANbM/0kLbToXKvI1X+PooPLkt3+9D51VWY/t1oXrEA2EatMrqScm3zkeASF+6NYrTin1yZwn9GJl+PghCFYDoy7xUXDt4IJDe49wHbrzt7eoOhSMsKjO/Nn7dx7ketYQfvf7yZrPfHy1dAXWbNiK71auwe1Txmmh5mHl+6s0XxNR7cGAu4cjUpW3jqq8+avylrLjaI32wFWVt6R7R6EPl7dSnNp9XLujwyOwI6Y9dz8CE8Kw65tNWmjTOF/Z8BcyNMC+7y+6djq6W5Sq96reqjpdG6r34+8YA79gX8T36srPUDtdX/y3FrwBOztb+If4q3YhANvW7eBwwtbOBrc/fAv++MwjWPLxcpQUl2h3rsW1rZ3mawSqDRh29yh0TYqHb5i/agM649iOwzXaAHr5M+lPt/D90PgwtFNpP304Fda21pj851sRqBRA31A/xPaPw6mDKSjILUDvcf3QY1RveAd1Quf4UGSlX8LlS5e1T2wYuZV1y1of5syrmO7RGHXLSFa6QiKD+EVRTmbD5GqMWkhpeOAv93D/3aVbJLdpxmTgcYGSgfoZkkE/Lqgrvpu7K48jSAkk+R76xwPcVqYcS8W420Yjrlcs903d+sTj/JkLyMzI0r7JOL/9x/2az/I49bp5FLjgf96q+QRL5VdhSjp58mT85z//QUWF7u3NhQsX8Nvf/hb//e9/+bohkDK5d+9efP/991rIzUm/ob35jdbL/3oDH878DLc9OBU2qoOqzV2P3IYln36Dlx97A6knTmPMtBEcnpudi/nvfYm136/naz3UEb77wvt48+m3Mf2ZWYjqGoEA1UCam9YmjyHtXRwQM6U/Vr/0FX546iO4BXWET1yIdldH1slzWP3CF1j57KfYPX8Vev9ujHYHOPzdNqx5dYF2ZRn01/LrJc6vT1V+TTOaX3c/crvR/EpNPo23/vsu3nj6LXV/uXruNg6/ETi4OKLPlIFY+NJn+OypufAM8kZQ11Dtro78nHz8MGcZdv24TQupZud3W7D41c+1qxtH/2F9VJ5U4vl/vYa5Mz7BHb+5ReWJjXa3mnsevR2LPl2GF9Rzp5LTMG7aSA4/sv8YXv33DLz29Ews+GgxbvuN7vwrqkNvvTBbhc/A68/MRFRcJA/cLYlRQ5Lw54ctd3BmiL0qbz2mJGH5S59jwVPzVHnriICunbW7OgpUeVs15xvsNVLeSBHpe/tQpOysfjnRUvTlel+JVx97E5/MnI9bHpxitN7f/sitWKbq/WuPTWcLjlFTdfX+evHnvPIBZqh2+q3/vKuF6IjvHceKSUOVj8biqPJkgGoDvnzpU3z41BylyHkjJK5mG5AwpDuuqrR/8MR7WPr2Ioy6fyznhaOrE7oP74HPn/8Enzw7D+2srdA5LozjTPj9FHw/9xsVPhe7ftmB4feO5vCWwFx5RS+K7v7jndjw4ya8/sQMvPnU2zzTZg76DdW1adR/fKTScFsdMtypjQteUWklGUZrMtQV/9KFTC5n5Ei2K7l52LVpD8fZvn4nXn9SyaXGDCnHTmG01mfdrBhbH2gKJ1g+vwrF0M7ODkVFRThzRmfG9N1336Fr12qzobKyMuzYsQPr1q3Dxo0beWaQOH78OPbv34+tW7di586d+OGHH/DNN9/wc+fOnUNpaSnfW79+PT/3yy+/cBhBn0fha9euRVpaGocRp0+fxurVq7F582bs27cPBw7ozF4oHn3Hhg0b2NFspjlI6BOHTau2sp9MINq0awt3L3e+1kNmFfRGbP92Xdro+YQ+8ewnE7Izp9LZRKQ2ZaVlPLtDHQOZh9CbN3PT2uQxxCsqAJdPX0RBZi6uqvSdWn8Agb2itLs6spJVOSzUvRkuKyrhFxh6Mo+fRWlBsXZlGdCb1E2rtrCf3haTqZSH0fwKwL6q/NrC8QjqvIsKdTIVFxdz532j8Ff5Q6Z6uSp/yATz0Pp9iOgdrd3VUZRXyOalZI5Um/TjZ1CsyXIjSeyTgI1VeXIabdu2gUfHmnlCM7M0I7h3+36+3vjLFnTvm8B+mkWnPEzs1w3desfj+METHE5QHaIwGmhdyb3CJqaWRGhIIBzs22tXlo0vl7eLyOPyVomj6/cjtFZ5K1bl7ZIqb9Re1CZUtR3W7W1xdIMuD1uSeNVOb1mlU1apnaZ6X7udJpNEMknev0NX7zer56l9J64Xv0u3aMT16oqOvjqzeqKDpxtGThmGhR8sqdEumhIy97zIbcBlbgP2r9+LqF4x2l0ddL139S72n09J5z7K1cuNLQgunbmI+CHd0HVgPNq0bYtz6j5BppZ5Obq6ckXld5e+5jVzNsRceeXi5gy/IF/kZOWw1U5wRJDZLIooLZsNxgXGZOB+xkAGw3FBQ+L3GdILR/cfV/LoXjrQzCG99CRKVF9srM2/mTCm1JnCCZbPr2bzmfHjx7NSRwPJFStWYOLEidodsEI2a9YsLFq0CPPmzcPSpUs5/IsvvsALL7zApqikDNJzJ0+exJIlS/hfUv5mzpzJ14sXL8add95ZpVSS8kmf89VXX2H27Nms+NFA9p133sH8+fM5LS+//DLmzJnDz2/atAlff/01x6HvpXjmwMXNhWfJ9JCfwgyh9XY0+NYPunNzrn2mLgaNTcKYW0bqzCgu1m9GYQpamzyGtHdzQlFOtTJamJOvwhy1q5rQs3G3D8LBJRu1EMuEBgeXG5lflzm/aprlUpwJd4zFD0t+1kJaHgdXJ+RlVys6+SqvaBbgZuOaPDHyezs42bMSWzNPqvPNx98bw8cPRt8hvbFlTc3ZqqFjB2L8raNvSB1qTVB5K8iubg8KVHlzcDXeHtTGycMFPaYMxLqPvjebklQfVJ5qtNNGyhgpQ7oypkuf4TP1xacXfolJ3TFs4mBMumccnFU4rW8dMXkYm/9TuTMXjqrd1StwBLUBTirMEH7GIN/07QStKTyx+xj6TUpC/8mDUK7GCHlZus/a9ct29BnXH5E9o5Vi2aVF2xVz5RW/bGrTBkmj+mHg6AGYfO8ENjM3B/R9Ndu0K9fI4HAdGeqLT2umh4wbiF+Wr9ZCqvEP9kXigG7YsHKzFnJzQr+KOZxg+fxqFMNx48bhxx9/xKlTp3i9YXh49QJiUgqTkpLw9ttv4+9//zteeeUVnkUk8vLy8Oyzz+L//u//cNddd2HAgAGsDNK/pOSNGjUKM2bMYEXz8uVqcxVSRCdNmoSpU6diwYIFbL6akpLCs4oUnxRO/SCLeOmll9C5c2f+nGHDhmH69OkoL792oTzNPupnFUsqGjbbQIM2mvkiV6Y6H1p3oYf8tdddlCvZraysVBuue7tja3vtM8agAcf0p9/Gc396gTvnqLgI7Y5paW3y1EV5iUq3gUmfla01yoqvfcNq69gesZP7wc7ZAXu+tLzF7Ib5VVpapvLIVrvT0PyyVc9Uy00d+uipw+Hk7IRln6/QQlueciWLtUHZs1Z5VWokfyyRTv4+PJNH7po8Ub93bTlo04766tCBXYfw0uNvYPp/ZmHyPRN5hpGgOkQmpk/98b88sIrqGsnhQuOh2dfa5a2sWNdPXQ9al0jtRwc/T/jHBMNBKSt+XYK0u+aB6j3NDJGjtNcsY0bqvervDMuYjUHbUKrawrriswnps+9g9kvzEB4bjq6JMXBSitSYW0fi4vlM3pyGTKPjVDrIrNSUUBttaHZtrA2gtZ7X5lspPP284B8ZiPf+/pZyM1FwuQCJo3rzM8tnLWaFktYZFuTmo1ApkeakJfKqrLQcnh09sHLpasxU+XX+9HmMu9N0JrI6GeLY1W7TKI8M+xCitgzUF5XWIUPt+KTk0tKSnZoZqR6vTp6Y9sBkHNl7DLu37NVCb05qK3SmcoLl86tRDIOCgvgtIs3eGc4WEocPH8bgwYPZTyampAyS8kj07dsXNjbVjbohFI8USqJbt25wdNS9vc3KysJHH33ECiHNNpKSefbsWTZNjYlRnZaTE9q1a4d+/frx88SePXtw8OBBnn0kE1S6p1dODTl69Cg/Q664vGGdBS2SppkvcqeOpyGsi24NhJOLExycHa9ZIE27PJaWlMDLR7dbWlhMGFJPpLK/Lsi0hBpZgjrGrIvZCAgxz5q81iZPXeSkZcDZzwNW7VX5a9sGHaMCkHVCt2uqHivVmUWO6Qm/HuFY+8rXFmc6StAC/iEqr8hRftFmJYQ+vy5dJ78iYkJxSssv6qzpTW1cz1i8+9L7Zh8w1cfFtAvwUANtG5UmGlz4RwXifLJpdm41N5QnNJNHLuV4KiK66NY2OXOeOPBaGkNoR77iGnkSpvJSlyft7as37cg4f1EN/tzVb2LNg3DDOpSp6pClrTG8mchU5c1NtQekZFB566TagwsNLG809KXdirtP6IfwfrFw7dgBYX266G6aCTLfHzRGtdPK1WynHbV2uuZyCar3JaUl8PTx4Gt6PvWEbhnGqeOnjMYnEz+KRxQVFiE99RzcvTpwmaTNQgaM7Ithk4ao6/Y8S0W7SJqSC/o2QH0uzSKRaWn6iZo775LJeKCmhDu4OMDeyR45F3PgE+LLL8FKVJtNZocXUs/D3UdnrnglOxeL3vwSn/33Q342eU/NTYRMTUvkFe1KfFG1D/r++XTKWdBmZKYiOEyNC8YMYEdtU3U/4whH1aYZGxeQDF4GMpwykKG++AOG98PebfuRf6V6wy/amGbSXeNY+Zn/nnksvgShJfhV7Er64osv4sknn2RzTjLVJD/N7tE6PzL/XLhwIbp3747AwEBW6j788EP88Y9/ZPNOe3t7Vg4JUtxSU1N59pEg088ePXogICAAly5d4lm+v/71r7xJDZmWfvbZZ6xwkmnoiBEjQG/iV61ahVtuuYWV1OXLl3OaxowZw4rkG2+8gXvuuQejR4/GkCFDqhRNQ0JDQ3mWktz8mV9rofVz5tRZbF2znV1hQSGGTxzCphG0JgNXr2LVt7pZpi4JURxOm/RQIxccEcwDu0GqQ13z3XqcUQ05DfYS+yagm3IOjg78NvTCuYu81X1MYhd+I0i7Fnbvl4BVK9Yis9YA0xTcLPI0d1fS4sv5CB/eHZXlFXD0ckXo4Djs+Pgnnhm0c7ZHierYAnpFYvgzd2P/og08O+Ps644r6boOzDsmCD6xQeg8sCsyj6fz55Tk6Y6yaApN3ZWU8muLyitylF8jJg5lU8QElV8qyfjFaH658Zbn+vxareUXrTX863N/wHcLf2QTIG/fjriQXmtL/gbS3F1JC1T+xA/rgYrycjXQdkPXwQn45eMfYK/yhxytL6Td7CL7xCCydxc+QoDWFdGxFrQlemBMCLuYgQk4pwaTtB09xWkqjdmV9LTKk81rtrEj5XrkJJUnajBKeULvdVd+ozORop1jKa8oT2j3UjrWwsraGoPVAHLVd+vU4O4MYrtF85EAPr7evPMomZh+u+AHeKi6E9u9C7y8dXWoR79unNe1lc66aIldSQ8fS2a3adsuXm9I5c1JtQPmoLm7khaq8hY7rDuXExdV3qIHd8P6j39UZc0e7ZXTlTcrVvho7aGdKm80o5VzLgtnD6XiwM87cfCXXchVg3TanXTxc43f1dqQ6+1KevZUeo12eujEwcjNVu10T1Xv1d/qb9fyc9EG9d6V2unwYH4xN3B0f6z9fgPX+6KCIqPxHZXSQTtBenp78ou7bv3i2byP1iKv+2EjNq7czG7i3ePw1G+f5V1066Ipu5Lmq8/rPrynrg1QCmm8ypOfPv6OX65QG0DHUpC5Yp8JA5Cv0h7RMxptVJu3dcUm1tZpRjD3Ug46KOUkblAC9q/fg/Mp5+AfQTuV+sMrwBu9RvfBhiVreS1jY2jMrqQtkVe0npBeSNHsG1ng9ByYiKN7j+HYgYYpvdebbao5LihS44LB3KZRGij2KiMy8LhAyUDrDamf0ctQX3wauz3yxG/xzeff4Wyqbk0oMfW+CRh9y0gs++wb/m1oSUROZo521ziWvCtp8uuLldTG1wk2x4X+c5r2DYKl8qtSDP38/HjmsFevXqzg6RXD/Px8bNmyhTepoc1iaHBAyhv5abZQrxjm5OTwxjHe3t4cTqag27Zt43i7d+9mRe9f//oXH2lBm9KQonnkyBFWIKdNm8azkeR3d3fHxYsXedbP09OTlTxam7hr1y7+bkobzQxGRtZvdtWU4yrorRc3ygO6w1X9+8XsBVWdJW3DTBtHkMkEvf3rmdQdkbHh3Pj9sHglD2ZJebrr0dvZ7MJGDXqDVENPDTGtQRo5dTg6q0Y2IDSAwwy3DTcXlixPs4+rUD1h9qkLiBzVA54Rfjj6ww6k7z7Bx1LQ+YZ0pmHoUNoApA2/sfYI9eVjK1LW6zaXiJnUj58tzi1Ah2Af5F/M4c1smoopjqvQ5ZcTeg1IZAXii9lfV+XXxDvH4djB45xfNENI26FHxoap/DpXlV+0gybJSzMCdOQFzUBtXdu0ctbs4ypU/tCZZWT+5RvuzzuPntx9HKHdI/h8Q9p0xs6xPUY9NJF3IbSytUKnUD8cXLeHB/d9Jg1A524RKMzNR8fgTshV+WN4zmFjaepxFZcyMuHi6ozeST3g0sEZn83+qipP6A04nVeoy5M09FLPRKk6dEblyXeLfuQ8iY6PwoBhfRGs6omrytPPZn/JGzK4kDnf1BGsTNKMxObVW7Fl3Xb+3IbQEorhipWrse/QEbg4OSLtbDo83TvA31d3rJGpafZxFaq80cYy8aN6wifcD/t+3M7HUQSpOk7nG2aq9sDW0Q5DH5rA5opU3rxVeTu6bi+XNz101iGVy5Pbmne2aWOOq+B6r8oY1Wlqr7+as7CqjNGRB/p2Ok2VsR6qLY9Q9Z5m/35c/DOXsbri00zOuDtG8zmFtJHI5l+2YueG3fy5hoREBmPL6m1sJlkXTTqugtqAU+fRc1Qf+EUEYPsPW3ndYFj3SD7fkNqHHKWIO7o6InZAPK8V/O79ZWweSmsNacOarkkJfFxFenI6Ni9bz/LS7qQ9RvaCn2pXju86hp0/6TZCaQxNPa7CXHlFUD9MM7fBkUG4nJWLb7/4jncvbgjXUwwNMUwDtUlfzDEYFxjIwOMCJUPtcUF98UmJpDiLPlpWY7nP2FtG8UsvTx9Pbu+ojzqyr/4dgC1bMVyk+UyLKIaWz6/igHtS8mhW0BDaDZRmD5955hk2HaV1fxkZqmO1teXZQlIgv/zyS1b66LgLQr/ekN40kaJHZqGvv/46CgoK+DzEd999l81FCVpDSLOPFE5K3x133IHY2FjelIbMS93c3HjdYXR0NP75z3/yM2TmSjun0ufTZ//+97/nz6qLph5wL7QMpjjg3pIw1QH3loIpDri3JJpzwL0l0hIH3Lckpjjg3pJo7AH3lk5TD7i3VJpzwL0l0tgD7m8GLPmA+x863q75TMvoDDGztXR+FYqhuSBzVFobSKYFpBDSUReffPKJdtc4NLNICiatH5w7dy6bnvbpQ7MgjUcUQ8tGFEPLRhRDy0YUQ8tGFEPLRhRDy8eSFcPvzaQYjhHF0OL51Ww+Yw5og5ply5bxekIyGf33v/+t3akbWn+oP95i6NCh6N1btwuZIAiCIAiCIAjCjUJmDG9iZMbQspEZQ8tGZgwtG5kxtGxkxtCykRlDy8eSZwxXdLxD85mWcRlfaj7BUpEZQ0EQBEEQBEEQmKttzOMEy0cUQ0EQBEEQBEEQGJqfNYcTLB9RDAVBEARBEARBYIydQWgKJ1g+ohgKgiAIgiAIgiD8yhHFUBAEQRAEQRAExpgZqCmcYPmIYigIgiAIgiAIAmNMqTOFEywfUQwFQRAEQRAEQWAqzeQEy0cUQ0EQBEEQBEEQmKtt2pjFCZaPKIaCIAiCIAiCIAi/ctpcVWh+4Sajd6dBmk+wRB51dNd8rYMPCi5rvtbBoLYdNF/rYFNljuZrHbw562+ar3WwZckOzdc6+GLNBs3XOujRxk3ztQ62VWZrvtZBazRD3Jy+WvNZHgt97tJ8puWW859rPsFSEcXwJqaP72DN1zpobUVxkX/rmpD/03kHzdc6+FNJe83XOljUusSBVSs78+qNnS9pvtbB6IRHNV/r4JFyD83XOnir7QXNJ1gq69NXaT7LY4GZFMNbRTG0eMSUVBAEQRAEQRAEpvamMaZyguUjiqEgCIIgCIIgCMzVNuZxguUjiqEgCIIgCIIgCIz+3EFTO8HyEcVQEARBEARBEATmKtqYxQmWjyiGgiAIgiAIgiAIv3JEMRQEQRAEQRAEgTG2cYwpnGD5iGIoCIIgCIIgCAJjbOMYUzjB8hHFUBAEQRAEQRAExtjGMaZwguUjiqEgCIIgCIIgCIwxpc4UTrB8RDEUBEEQBEEQBEH4lSOKoSAIgiAIgiAIjLHZPlM4wfIRxVAQBEEQBEEQBMaYUmcKJ1g+ba4qNL9wk9HHd7Dmuz4hEcFw83BFZUUljh9KRkFegXanGrv2toiIDYeVtRXyrxSo507gaqWueBiL396hPT+vh+KfPnkG506f53C6T1hZtUN5eQX2bt3H13XR1KKoS5ubSlsFThxO5rTXxlA2SvuxA0o29X2UxvAuoXBwckBa8mmkp53TYuho06YN4np1RWlxKQ7vPaKFNoxF/qZ979LWzRXWIUGUKFRcuIjys+naHR1tXZxhEx2Jq8XFfF2RlY3y02fZbwr+dN5B8zUOF3cXBIQHcLozz13C+dTz2p1qAiIC+bnKykqcOpSCwrxCDm+nyk5QdHBVWUo9fAr5uflw69gBviG+sLO3w5Edh1FgJM+vx59KdJ/ZHKw9nOEQ4c/lpDg9E0WnLmh3dNh4ucK+cyfdhSpv+UfPoPxyPtqpdDvFhejCFe3a26Dg5DkUp13UQhrPouaLAyd3Z/iE+3Ne5ZzLxKXUmvLYOtjBLyoI7Z3sceFkOjJPZ2h3NNoAoT2iUFZShrR9yVpg07AywWHIjpo8Shxkn8tCphF5fKMCWZ4M9fsbk6ezkqe8pFTJc1ILbBpv7HxJ85mPoydSkJ2TA2tra/RI6KqFmofRCY9qvsbh6u6KIFXfKVMupl/EudSabS4RFBEEV+5vKnBStQfUZtvY2SBUtdXWNtbqiavIOHsRF87o8jMwLEA976aqWCWKi0pUnJOoUH1OY3ik3EPzNR1b1R44R/hxeSs8m4X81JrlydbTBU6hPtoo+SquHDuL0ssFaGdnDdeYILS1seLnCs9mouD0JfY3lbfa1izr9UF5Eqx+c2rHMtIzkG4kT+i+rp+txAmDMUR9cX38veGtHPW1OZmXkXYiDY7OjugcrWv7qIafTjmL7IvZfG0qzCFPUFgg3DxVGVNjouKiYiSrODSuoedCozvzGKKN6vIvqnYzPbVm31wX69NXaT7LY57f3ZrPtPz27HzNJ1gq7Z5TaH6LYMWKFTh//jxSU1ORlZWFjh07om1by5jYPHPmDE6fPs1pMqSucHPzwZufaL76IYXugb/cg5DwIHTpFgkr1bEmH752kNMjKRET7hgD/2A/xCtl6IR6Ju9yXp3x3VQDOuHOsdxgBqt7D/3jAVYaU46lYvTU4YjuFsX3Ril/VFwkflryi/ZNpoMa9gf/ejd/f0xCFKfthBoU1IZlU2kNINl6V8vWsZMXpt0/Wd0bgxI1+Duw85AWQ4dfkC/+9r8/IaZbNFYua1wjfqtL8we2VajOx2HKBNj17gHroEDYRIWjZN8BoKxce0ApIV0i4fbE31WtbgerYDXwUoOq8pRU7W7z+SHfRvM1HOo0R90zGvFJCfAP80fn2DAcVopcuUG6XTxccMufb4O/GsCHxUfwwI8UQCJClbfB04YqxTIQgWowefbkWeRm5SIqMQoDpwzGpIenYPfaXcjJaPzAolcFDTCbgcpev/tHoMPgONiH+8G5awgubzuKqwayOUYHoOPEPrAP84VzfGdYd3BC3t6TsHF3Qqe7h8Ih3Fcpln4I/tetyD+YigKlODaVw80Uh+RJunsEopLi4B3mh8CYECTvOIoKA3ncfDpg4L2j0Pe2IUpZKkPK7uPaHR2egR1x63MPIDghDDu/2aSFNo22zVUMVfQBdw9HpJKno5LHX8mTUkseVyVPkpKnj5KnTNX/U7Xk8VDyTHvufgQqeXY1U56RDw3TfObjq6UrsGbDVny3cg1unzJOCzUPn8/5TvM1HGoPJtw7DolJ3VmZC4sNxcHth2q0B6QQ3vXnO7jviEpQ/Y1SclMOp3BbT3FJqQyJDOa4h3bq2pJRt41ATI8YBHT2R1yfrkppzEBWI9uExEp7zddEVHnrfN8weA+MhbOq125dg5G57RgqDWRz6RII//G94KzaA7f4ENio9iBnbwrslMIYcv9wuESqdiQygONm7TheI25j2dYmX/PVD+XJpHsnoOegRASGBiCiazj2bz9QI09oDHDPX+5CkGqHqV+3VgosjQHqi+vi5oxJ901AtOqX6Z61rQ2O7z+ulMWOGHXLSF3+x4TBP8QP+7apvsxEmEue0beNQtdesVzGEvrE80uJzAw1RvX14s/yDfDhFxddEqOxe+OeBr2YeOAf92k+y2PXm0s0n2np/vcpmk+wVCzOlHTKlClYsmQJFi1ahFdffRXHj9fsqOuiJSY+V61ahTlz5mhX1dQVbin0G9qHZ2JefuwNfDRzPm57cApsbK8dRd75yG1Y8uk3eOWxN3n2bPTUERxeV/xLFzIx45lZ7D5R4Vdy87Br0x6OM/+9r6runVcN6JoV6zjc1PQb2lul7Spe/tcb+HDmZyptU43KdpcmG8mQeuI0xkzTyZabnavS+iXWfr+erw2xUR0ZKZP7d5iu02oqbZ2d4DBmBHLfnoOcV2egnV8n2ERHaHerKTuVhtw3Z7Er+nmNFnrjcHRxZAXu05c+xpwn34N3kDdC48K0uzq6D+nBb23fe/wdLHrra4x9YJwaRFjzbOHU30/D9p+2Ys5T72Lu03OQcUb3Bv7M8dP4/NXP+N8bhZWrI7xvSULy/+bj+L/mwi64I5wSOmt3deTtP4XjT36EE//+GGc/+gl+vxnN4SUXcjiMXOr0xSi7XICcjQf53o3CQeVVrylJWPrSfHz11Fx4BnVEYNea8uTn5OOXOcux98dtWkg1lGd9bx+KkzuPaSE3FnslTw8lz/KXPseCp+axPAG15ClQ8qya80298qRYiDwNYdSQJPz54fu1K8vDycUJw6YMxfsvfoCZT7wN3yBfRMRVW50QvYb05DZ9+uMz8fnMLzDlwYmcFyVFJVg0bwneemoW3v3PbB6k+wb7cpxd63fjrX+/jVnPvIvUY2kYNtX8SnhtrF0dEDCtPw48/xV2P/YRHFR5I+XPkMuqPdj770+x9+lPcfKjnxH6m5EcXlFYihNzvseexz/G/mfnw6N3JBxDvPmeuXFydcLIqcPx3vPv480nZqo86YTIuJp9Sx/Vz9JM2euPTee+fpo2Bqgvbt/hfeDSwRnTn3qL3erluv7o3OkLePvZd/DWM+/gk+mfYfL9E9G2bTNfAhlgLnl2rt+F6U/OxMynZ+HUsVMYMW04h8f2iOGxwkwlzzv/nY2eSYlwVp9zs8OT2mZwguVjcYqhjY2qYDNnYtasWfDy8mIFsaKiAnv37sWGDRuwfv16XLigM5Ggmbpdu3Zh+/bt2LRpE4qLi7F582asW7cOa9euRXa27o1henp6VdiRI9XmgD/88AOOHj3K9zZu3IiSkhIOz8jI4Gv6ri1btlSFN5aUlBT+TnLk17Njxw7+bApPS0vTQutOT3NJ6BOHzau2sp9MPdu2awt3L3e+1kMmlkGhAVVK0Cb1PL0VIxoSv8+QXji6/zhysi5rITqc3ZwRFR+JLWuuHXiZAkobpZWgtLWpS7awQH7zRxjKlp9XgDOn0lUZq+RrQ+izyVRx+9qdWsiNwzo0BOXp51CZncMzgSXbdsI2IU67W01bJycOt+kShTb2zXwDbgICo4KQcToDly9d1tXj9XsQ0ztGu6sjpncsdq3W/cbpKelcvty8OsDJzQk+wZ2Qm5mL6F5d4B8ewLM6ROb5TGRfyGL/jYJmA4vSMlB2MRdXVfnJWbsfbn2itbs6KkvK2JzUtV8XuPaOQv5B3UyoIR5DuykF8iTKMq9oITcG36gANqXMU783KepH1u9HWO+a8hTnFeJi6gW+X5vQXtGwbW+LIxvqNxlvKXTyXKyS56iSJ9SIPGQuS/lXm9BeUbBW8hzdsF8LsXxCQwLhYG8Cm2IzERwVjPNKMci5lMPtwa51uxDXu6bJK11vX72d/WdSzrLFELXpebl5OJ+mM0Nvo/4K8wurrImSD52sWvZQosYBxvLT3Liq8lagylvxJV17kLHuADz7RGl3dVB7YKfaA89+0az8XT6os+gozS1AgYEZeXleEdqYUFmqj85RIbz8Q58nO1SexKu+zxC63rJK14efMRgD1Bd30Lgk7N60F126RSMmsQvPxhFlpWWwd3Lg52jmOPlwiklf7JtLHjI3pRcWBJkr69vAzAuZ/BKz16BE9B7aC6dTzvC44mZHr8iZ2gmWj8UphnqoofD09ERBQQEOHDiAL774AkuXLsVXX32Fjz76iCstzdQ99thjbH5KStXBgwfxxhtv8IzjwoULWXEkZZFm8z7//HMOmzFjRpViSbOTFHfx4sV46aWXsH+/bgCQnJzM30Xhs2fPZuWzseTm5uLtt9/m9JIjRZfCiO+++65KFvr80lLdYLeu9DQXMum4nK37biI35wqHGeLgaI/iwuKqhi83J7fqmevFpw5syLiB+GX5ai2kml5JiTh1LJVNLsyBi5sLz/rpIT+FGUK2/0Usm64h18lW85nadPBww5hpI/H13MUtMht9PWj9YOXlajkrc6+osJoyVOYXoOLSJdgNGQD7MSPQfvAA7c6Ng5S7K9nVCk9eTh6/lTWEnslTZUoPP6PCSDkkeo7sjT6j+mLUPWN0axUtBGuVxrLsPO1KDXiUn8JqY+fvCa8JfeCuFMCstbWUJlV3PCf0RsayzVrAjcNB5Uu+gTz5Kh8orCE4ebjwbOPqj763iPpCUNoLDOQpYHkctav6IXl6TBmIdRYkT2vAWdWPGu21qvdOtfoieplY+xmKp4cG8T2H9EBJUSnSjle/WCVoBjGhXwI2/7xFC2k5bFQaS7Oqy1tpTr4Ku7a82ft7wG98L3gPiUfGmprWKPRi03toPK9pvXKsYevUmsu1v3d136/H2DMUVl9cTx9PhEaHov/IvhgxdRiGTqzeE4GWoQxWY4bB4wdh5zrTvng1lzx6/FQZ6z6gGzau1LXZp1QZpD0Ihk8djuGTh+Lk4ZNVYw1BuBmxOMWQFD797N7hw4cxYMAAvPPOO7C3t8fEiRMxbtw4fPDBB8jJyeHnaR3iP//5T7zwwgvYt28fK5N/+MMf8PzzzyM8PJxn6r799lu89tpreOutt1BYWMiKGUEKWVJSEof37duXlTUiJCQE06ZNY0WtU6dO+Pjjjzm8MdAsJimqpIiSIyVv505dAzh+/HhMmjQJU6dOxYIFC6oU1brSYwjNMNLMKbmSCt0mI8agRd/xvePYlZaWwdbOVrujM5EsUQ2ZIeXl5bCysqp6q2drZ6MaO92MZWlJ/fE9Orqz3f1OzYxUD33W0AmD8Ms3pl1gTbIlKLnIlanfjNKqh/wlWrr1lJeV1ZSN01//bGyvQT1Yzk7+HXnTGtcOLgiPqWkC2ZJcVXnQxrY6D9qotF2tNaNcfvoMcv7zCnLfmIXCFT/A6cG7aecf7e6NgTYhoU0j9NBvSp2oIaVqEEThevTP0LqODqpsbVi+Dh/8Zy4yzl7A0Nt05juWAL39b2sgG/krtBlNQ67sOoHjj81D8rOfwveeYWhrXZ0nth3deHOaG21GStCbfGsDeWhNUFmtvKoLWpdIz7v7efJaPkc1SPbvEqzdvTEYl6dMu6ofWpdoZWuNDixPMByUPH5dgrS7QlOh9sCwvdbV9ZrtGFkF1G4z9P0NteG0lnC4UjTmz/y8Rjvu6eOBSfdP4HVs+7a0/CxvhZKtnUG626nyU2Gk/mTvSsaexz/C/v98jpB7hlS3B0o2954RCLylP45MX2o0rjmg37t2ntTuH+t6pr645aXlKCwoxLv/m4OFcxfhjkdvY+sdgmaCybz09X+9iQGjB7BCZirMJQ/h1ckTUx6YhKN7j2HvFt1Lvm5945F9KRsv/OVlvPDnlxGnxiU0HrrZqVTDJXM4wfKxSMWQZvyWLVuGwYMHY+TIkdizZw9vRkPhP/30EytPRUVF/Hz37t3h5KR7m9i7d29W/PTxSWk8ceIEYmNj4eLignbt2mHQoEE4dEi3wQiZrfbo0YP9YWFhbEJKkFJKyiCZsdLsIX13YyGltk+fPrCzs2NHfvpeShPNeJJCSAprmVJazp7V7RxZV3oMIVNTko9cUZlu50ZjBIcFYdCYAexOHU/lnTcJJxdHODo7XDODV5BXiJLSEnipzpUIU8+fOqF7G3vq+Kl64w8Y3g97t+1H/pWai907eLgiNDIE29c1fsa1PmijmUFjk9jR2zpKK0HrVxycHY3KVqqUKC8fT76mBe+pJ66Tp6qTLsgvxPBJQ5E4oBs8vN3RvV+CdrPlKU9PRzufjmhDCrpKG5mW0npCQ8h86ao2+1x29hzaqPLeRpWpG8mFtPPw9PNiE0Ma1JFp6Znkmhus0DrBoC66tTi0zs3eyZ43k8lW+ZhlYDJ6LiUdLqpMWQpFqRdg5+eBtu3Vb9y2DZuWFh6vuQtsO/tqZb74fJZSBDuoPKxeA+sxMhG5246gIrfuutxSZKZdUIqdBw/KKa/IFPNCcsN2taX+vji/CIkT+iGiXwxclJzhfbrobt4gSB43JQ8phyRPp0bKU6Lk6a7kCe8XC1clT9gNlqc1QLs+d/TrWNUehEQFI+1EzXXCqapND+2iWwtKa5Spv8nWNpKhDWcmPzABPy74CYd3Vy8LoZ0kx9w1hkyN8PV7C7XQlqUgLYNnA2mHYWqjXVR7cOVEzd0wDduDovPZaN/RFW3tdMqSW9cghP5mBFK/Wofsnc3b0bcx1MgT1Y7RjqGpWt+vh8YQtLEKoRsDOPLmPvXFpXHD2VO6Wc9L1IarSkVtiz7vCZoNbmfVFq4dTNeum0seKmPj7xrL5pBfvvc1hxG0QVJG+kWQaWlRYRHvsOquWbvczJCc5nCC5WOxawzJPfzwwzzT4+Hhgdtvv70qfPr06fD3172RIaVLD8300b2EhARW6mjGzdXVlZUxmo0jkyBab+jurluDRoqivoGitQqklBI0Q0mzeWQKOmHChCpTz8bQoUMHngmkzyRHfgojJZcUxDfffBMvvvgi3Nzcqj6/rvQYQooyyUjO1a7uxmfz6q1Vm79sWLkZXbpFsWIzZJxSjHcf5vUaBO0YRm/FiFXfrMGoqSP4ud6DemK1tmHMhp+31Bmf0jlo7AAVdy1fG0ILvA/tOcqNvymh9Y7Tn36b3YaVm3jH0MT+3TBkvErbruq0dTGQ7ReSbRrJ1o1lW/WtTjbaAbPngO7wDezEu7GSn9YL/LDwJzz/t5fx4v+9hs/f/YrXQXw5ZwHHuRHQbCCZj9oN6AvbniqNvr4o2bEb7bw7siOsgwNh2y2O1xi2H9gfZceScbXwxioctGYw/3IeegzvhbgB8fAO9MH+TftYWSRH7PxlOyISIhDbryv6je2H43uO8ZEUBbkFOLj1ABKH9USX3jGI7tkFBzfrZgJcPd0Q1z+eB45h8eEIV/FbmqKT51GWk8/KXYekWNgFeyNn/UGlLHqyIxxjg+HaNxqufaLhOaoH8g+noSJP91KLzMY8x/WyCDNSIiPlPG/GEjs8EZEDYuEZ6I2jmw6ig68nO8LKxgqR/WPhEeAFr2Af9rdV9WXbkvX47J/v4vPH5uCXOd8g/WgaVs1bwXFuFBeVPIU5eSxPhJLHQ8lznOXxYEeQPBFKBnclj6eSh/wkz3Ylz+f/fA9fKnlocxqSZ828xu/C2dIcVnV+9/5DKCwqxpYde3A+o3lHHpiasylncUXlSd/hvdFtQDd0CuqEPZv28mCcHLHll22IVIPthH7xGDg2CUdUH0JtOpmgP/Tkb0Gzh/mX83nzGdrBlBg+bRgGjx+IXRv38kA9OLLlZ6vzVXtQouqPz4ju8EqKgUOQFy5tOAh7Pw92hGtsEDz7RvH6wk4ju+Py4dMozyuGjasDYv99B88S0vEVdJ+OvmgJaI3dFdVH9x/RF4nUFwb5qt9xT4082aTGALR7Zzc1Bhg0biAr5ZQndcUlaMM5GjfQGr1+w/vwhi10DBHt9kmzbLSWtPeQnrw7+MXzpiun5pJn1C0jMGTCYOzasIvj0npEgmYPyZqI10yqOHQ0Fm1wd7NjTKkzhRMsH4tdY2gIKYU0u6bfyIXWExqDNpahTWrat2+PmJgYtvPu2rUrK1g007hmzRo2Nx02rP4dy/z8/HiWkDa0oU1gGgKtZ/z555+rXLdu3VgJ/eWXX9iRn8xDHRwc2G3dupXXSF682PRzyxrK0X3HsGPDbgyfOIRn8D6d9aV2Rylvg3pwQ0Ys/mQ529MPnzCETT22rtVtAFBffFKiaKE2zRjWhtYt/rh4pXZlHo6otG1XDfUw1WCHqsHAp7O+0O4AvQf3NJBtmZLNSckwWMl2pko2u/Z2GDFlOCuIjk4O7KeXEYaQYnt4T+POMDQ5lVeR9+FnSvGLh/2QgShc8SMqMi6yMkiOaOfpgfZDB/IaQ+uQQOS+O4/DbyS0IcSCGV/xhjN9x/TDmgW/IDP9EvxD/dgRyfuTsU8N6AaMT0JgZBAWv7uIw4mls5coxS8MfUb3RV52HtYv0yn0Xv5eGDBpIC6kXWClstvg7hzekpBsqW8uhlvfLvAa1xsXvlzLZxnah/uyI2w8XOA1vg88x/aEY5Q/kp//nMMZpRjSxjWXt97gsqVB8nz/1mKE9+6ChNG9sWXhWj7L0CfMlx1h094GPSYO4CME7Jza6/yqDTCE1vKlNvMMQ1NA8vz4lio/vaMRP7oXtmnydFSykCOslTyJE/tXycN+I/I090zGlmLbrr1KIdyNqLAQfLdyNU6lNf34E3NAeTJ/xueIU4PopLH98dOClXyWYUCoPzuCTEF3b9iDQRMGIjgqCF+9o5ud6eDphiKl8NJLo/5j+rPTW4HQuq+DOw4rZTOBw2N71tzgqiUg2Y6+uRReSvHzG9cTaV+vR2F6Fh9dQY6wU8qe77he8FPtgXOkHw68qJPN1ssVFYUlvDsx3SNn36nmJmrmgvYV+GTGfKXYxLMVzg9f/8h5QsdJkCOO7TuuFKLdvE6ws+pn52tjgLriEjvW7uJZOAonRWreKx9xuIOTPZLGDMBA5Ui5//CNT3gjIVNhLnmojB3YcZCVP0q7vozRWkOagaQ1k6QAfzN/RdX5mjczxpQ6UzjB8rG4A+5vueUW3iTGEJpRmzt3LptRUnJpt9JnnnmGFSsy9aSZRWL16tVsYkkzb6Qc/u1vf+OzBWnNIs0gUtzExETcf79uO2/D7yIlkHYL/etf/4pt27Zh3rx5PLMYERHB5qg0u1f7+/RQOG0i4+hYvdCc1jSSUklKITFixAiefSTTUVoPSbOYvr6+uHLlCu644w42d60rPXXRmAPubwYsrCg2G1MfcH+jaeoB95aKKQ64tyRMccC9JWGKA+4tiZY44L4laeoB95aKKQ64tyQac8C9cGOw5APuZ/mb54D7P56RA+4tHYtTDIWGI4qhZSOKoWUjiqFlI4qhZSOKoWUjiqHlY8mK4VtmUgz/LIqhxdO6Rq6CIAiCIAiCIDSZq23M4wTLRxRDQRAEQRAEQRAYst8yhxMsH1EMBUEQBEEQBEFgjCl1pnCC5SOKoSAIgiAIgiAIjDGlzhROsHxEMRQEQRAEQRAEgTGm1JnCCZaPKIaCIAiCIAiCIAi/ckQxFARBEARBEASBqTSTEywfUQwFQRAEQRAEQWCMHTVhCidYPqIYCoIgCIIgCILAGFsfaAonWD6iGAqCIAiCIAiCwBhT6kzhBMtHFENBEARBEARBEIRfOW2uKjS/cJPR13eI5msdtLai+Lhn6zKon5fdXvO1DsaW22i+1sEG69ZVf6zQuurP72bcr/laBz8s3qD5WgcJq89rvtbB220zNF/roaKVbV+yMX215rM8Xgy8W/OZlifT5ms+41y8eBGHDh3i8WBAQABCQ0O1OzrS09ORnJzM/nbt2qFr165wdnbma8E0iGJ4EzPAd6jmEyyRylZmOGHXxkrztQ5aW/4UXy3XfK2Dtq1MMWzf1lrztQ5+2POe5msdLI99WvO1Dt5pd1HztQ4qrlai9GqFdtU62HpureazPF4IvEvzmZan0j7XfNdC6sjrr7+OAwcOwMbGBu3bt8eLL74IJycn7Qlg6dKl+Omnn2BtbY28vDwMHToU99xzj3ZXMAViSioIgiAIgiBYLK1NKbR06LWpOVx9ZGdn47PPPsOrr76K2bNn4+TJk9ixY4d2V0dkZCQrj2+//TYeeeQR9gumRRRDQRAEQRAEQRAYY0qdKVx97N+/HyEhIfD29oaVlRWGDx+OdevWaXd1REVFwdHRkf00o9i2ragxpkZ+UUEQBEEQBEEQzEpaWho2bNhQ5ehaT1ZWFjw8PLQrsJ/CjJGZmYkPPvgAd99tnrWQv2ZEMRQEQRAEQRAEgaFtfszhjh49iiVLllQ5utZja2uLoqIi7QooLi7mWcHaXLlyBfPnz8fly5fx0EMPaaGCqRDFUBAEQRAEQRAExpgZqCncyJEjMX369CpH13poB1KaQSwsLERlZSWblkZHR2t3dZDiuGjRImzcuBEvvfRSjY1pBNMgiqEgCIIgCIIgCIwxpc4Urj7Cw8Ph7u6O5cuX4+eff+ZjKWjXUVIW9SanmzZtwnPPPcfrD+k+maMKpkUUQ0EQBEEQBEEQmKttzOPqg84lfPrpp3nDGZoVfOCBB/gsw8OHD7Mjjhw5gn79+vG13hxVMC1yjuFNjJxjaNnIOYaWjZxjaNnIOYaWjZxjaNm0tnMMiyrLNF/rwZLPMXw6yDznGP4vte5zDAXLQGYMBUEQBEEQBEFgrprpT7B8RDEUBEEQBEEQBEH4lSOKoSAIgiAIgiAIjLGjJkzhBMtHFENBEARBEARBEBgy+jSHEywf2XzmJuZ6m88ERwTBzcMNlRWVOHEoGQV5Bdqdamzb2yIiNhxW1u2Qf6WAn7taqSsSdcV3dXdFiLqHNm2QkZ6B9NRzHK6nU2AnBIcHYtvaHSgvq94Qw9bOFgl943D65FmcS6sZpyFYkjz2jvboHB0Cq3btQDVo//b9qNS+R09jNjeh76e0VTRANmtrK5bt+KETVbIZi29rZ4OwLqGwsbVRabyqZLuIc6fP8/OEj783O7qXk3kZqSd020HXhSk2n6HfOigiUP3U9Fur9NT6rYkglsWV8yn50EmWhWQIjQmFtQ1t4HEVF1Xc86cv6CI0kaZuPmMoA6WjdnkhqKy51pKB6BzdGW6erigvKcPerfs5jPAP8YOXr1dV+UpLPo3LKk8aQ3M2nwmJCK76zY/XUf7squpWzfLX3qE9lzNHJwdOd7pB3Q5jed1QVlqOPVv2aqENo7Gbz5ijDhGJ/buhorxClRb1p+rKvm0HOFyPr2ofglT7sF21D2UG7V1tmrr5jL68UftE5a2uOqMrbxU4eShFV2dU/Q9V+aKvMxlnL+LCGV2dCQwLUM+7KXkqUVxUouKcZBkbQ0tsPnP0RAqyc3JUflmjR0JXLdQ8mGLzGVsPZzhH+FFWofBsFvJTM7Q7Omw9XeAU6qONkq/iyrGzKL1cgHZ21nCNCUJbG10bW3g2EwWnL7G/qTR18xmztG+d/dFBtQNEaWkZl7fSklK+bijN2XxG175R31+BE4eTue7XxrB9I3mOHVBtg8ojat/CVT1yMNK+9VBtQ7n6DSgv6dm926plbgiWvPnM40F3aj7T8nLqF5pPsFTaPUcHgjSCEydO4MCBA1Xniri4uKB9+/baXdNz7Ngx/tfe3h4pKSlwdnZG27a6ic5t27ahY8eOvMVtc6HtcbOzs+HjoxrtG0hZWRnOnDkDV1dXLaRuPnrzU813LTTIu/cvd7FCE90tSg0OrJB8+KR2t5oeSd0x7o4x8Av2Q1yvWJw8nIK8y3l1xqfOYtK9E9BzUCKCQgMQ0TUcB7YfqBoQkTJy+8PT8IdnHsHSj5ejpLiEw4nE/t3xtxf+jKKCQhzcpdt6uKFYkjwUZ+jEweg7rDcCVZxQ1RnSoJAOZDWkoWoHpe2+v9yt0hakpc3aqGw9kxIxnmXzRXyvrvyMXjZj8akjnnLfRO7EQ6NCEB4bhgM7DrJsLm7OfC86IYrlJsXr2P7j2jcZx6pN8wwM6HebcO84JA5MRIAamIZ3VenZfrDGywMabNz1lzsRGB6AqG6RsFKyUB6ScjHxvnE8AA6JDFZxQ3Fwx+EacRtLU9RCnQzj0UPJEFSPDPcoGUhZiFQyUFkjGYiJ94xHv5F9MWzyECz/9FsOIyY/MBGjbhsJR2dHHrRfOJuBrIws7W7DKG+ioQ6Vnwf+cg9CVPnpov3mxutWIiao8uev6haVvxNa+evo44lp90/isllaXIoDuw5pMYAp907EgBH9MHLyMCz5dLkW2jDaNEIxNFcdIt5a8Abs7GyV8u6PwM4B2LZuB4cTuvbhFvxRtQ9LarV3tbFu0/h+qqrOqHaNykVYrCr32w9dW2f+fIcqj4GISlD5p5SoFKozaiBMcWmQT3WG4h7aqaszo24bgZgeMQhQA/a4Pl2V0kjlLVv7xIZx9yPjNJ/5+GrpCqzZsBXfrVyD26eY9/uOvbdG8zURVVw73zcM3gNj4RzuC7euwcjcdgyVBnnl0iUQ/uN7wTlM3Y8PgU0HJ+TsTYGdUhhD7h8Ol0g/OEcGcNysHcdrxG0sO9peq/xcD3O1b32G9UK3Ad0QoPqauN5dcTkrl8tcYyi/2tT2zQ0P/lVXt2NUf0ft2wmlmNaG27c7xyKA2jeVxqr2rZOXat8mq3tjUKKU2QM7q9u3dxZO5xfe/p39dG2DGgc0ht/+437NZ3n8PGOR5jMtw/86TfMJlkqjRno5OTl4++238fXXX/MZI1999RUrMeaC3sDs3LkTZ8+e5esZM2agsLCQ/cSPP/6I0tLGvXUyRn5+Pv70pz/h8ccfR0VF496amprLly/j3Xff1a6aTp+hvXkG67XHpuOTmfNxy4NT1OD/2jfWtz9yKzfgr6vn0pLPYOTU4RxeV3wnVyeMUs+8+/z7eOOJmfAL6oTIuAiOQ8T3juNBFc1AGdLBs4PqLAZjbyNnDfRYkjykcI1XHcj8WV9i+lNvqbhzUN7It+2G9OW0VeLVx968rmzLPv2GZaA3l6OmjuDwuuIXF5bg6/cX4Y0nZ2Lmc+9wZ0cKM9FveB84d3DGG0/NVO4t/LK8mYOiBuDk4oThU4bh/RfmYeYTb/NMbERcuHZXR++hPXFVyTL9sZmYP/MLTHlwEqyVLCVFJVg0dwneeuptvPuf2eiqBvU0uG9pSIYRSoY5L8zF9Cfegm+gryovNWXoM7QXl7U3HpuhyTCZZSDWrliHeS9/yP7abPppM2Y9+y6749dR0k1Jv6F9uPy8/Ngb+EiVn9vqKH93PnKbUu6+wSuqnFH5G62Vv9ycK/j8va+w9vtrDxpe/e1azH55nnZlPsxVh/TMeeUDzHhmFt76T822ua72zlRQeRs2ZSjef/EDrjO+Qb7X1JleQ3pyeZv++Ex8zuVtYnWdmUd1ZpZWZ2Lhq9WZXet3461/v41Zz7yL1GNpGDZ1GIdbGqOGJOHPD1vu4NkQa1cHBEzrjwPPf4Xdj30Eh6COrPwZcnn/Kez996fY+/SnOPnRzwj9zUgOrygsxYk532PP4x9j/7Pz4dE7Eo4h3nyvJTFX+7b22/V4++l3uG07cfAEhkwYpN0xP/20vv/lf72BD2d+ptq3qUbbhru09o3awdQTpzFmmta+Zedi/ntfqvZtPV/XZvYr8zD96be5jxWE1kCjFMN9+/axe+utt1hBfOWVV+Dnpxto5ubmYvPmzVi/fj22bt2K4uJiDi8oKMCWLVt4Ro7u0XVWVha2b9/O9wmagdQrmKtWrcLx48exadMmVgi7dOnCs4KnTp3CggULsHbtWv48on///mxiQtCzGzZs4O/Zv38/K5U8tb93L8ehcJpxNAal19fXFxcvXuRZUD2kpG3cuJHj0meXl5fzZ9LBmhRGjtJFZGZmsnwURt9JgwyC5NErr/R59BsRJCM9R9f0jP5zSBFeuHAhf47+QM+mEN8nDltWbWP/mZNn0LZdW7h7ufO1HjKZoBmv/Tt0plFb1fMJKh5RV/zOUSFsjphzKYeV6B3rdvGzBClM1Kks/GAp/056KO4INbjZv+0Amw82BUuSp2vPGDbJovtxSkGh2QbD+43FMG2n65CNTN9oZk8v2+Y6ZDOMn5ebZ2D20gYFeYVVs+2Dxw3E7k170KVbNGISu/CbYnMTEhXM5p/635oGp3FqYG0IXW9bpWsbzpw8y+nVy3IuTWcGSzNJhrK0JLVl2Ll+lxEZunLZI7isaTIQqcfTUFhQxP7aePt7c1wyx6Ky3FJQOdq8aiv76yp/lB7D8rdJPZ/QJ579+XkFOHMq3ehLtZTjqUre6pd55sJcdUgP1ROq6x19O2ohuvZhJLcPS5pV/+sjuHadUe0TlRFD6Hr7aq3OpNSsM+cN6kxhfnWdIfM/vQltieqrr5I5nAUSGhIIB3vzWSSZEteoABScvojiS7n8e2asOwDPPlHaXR2VJWWw83KFZ79oVv4uH0zl8NLcAhSkVfeN5XlFaNPW/G1ybczVvtFMOs1Odx/QDZ0COuF08mntjvmhOk7tFUF1u01d7VtYIPZvr699M15HYlTbQNYH3gZtQ2uApDWHEyyfRo2syGSTFDFSkkiZI7PHDh06sBK0bNkyLF68GEuXLsW8efOqlLfvvvsOH3zwAd+jWUZSjijuf//7X75PzJkzh5Uj4je/+Q0rgN988w0rSzRLSEriwYMHebbw22+/xYoVK6qevXLlCs/4ffHFF1iyZAk7mnEjRZO+6+WXX+bvJbd7926OV5svv/wSd911F8aNG8fxCZKJZkQ//fTTqrSTgkdpmjVrFqeRwvbs2cPPfvLJJ/wshc2cOZNNbgl9Gonk5GQ8+eST7Kf0vvjiiywnxXvjjTf4c0hhzsvL43SQqWxTIVNBetOlJzcnF84qzBAHR3sUFxar79UNEAyfqSt+XeHUOQyfPJTNLPTrWPR0juqMsNgw/LT4Fy2k8ViSPJ4+nnB0dcSAEX2VgpWEyfdNhEsHF+1u4zGWBgozhNY01pZN/8z14rdTHSG95aXO+ZQaqBNeSoaw6FAkjezHM6ZkGmtuaIaS0qaHf+sOTtqVDmc3p1qyXOEwPTRgpxkSkoUGIS3NtTKo9KkwQ6j8GMpwhWWo+UxtyHSUTJKSxg7A+LvGIjK+etba3FBZuVzrN69d/ozVrdrP3EiuVweIptYhGiySKecwVUcm3TOuqn0YMXkYtw/na7UPpsRYfXCqJVft8maszvQc0gMlRaVIq1VnaAYxoV8CNv+s66+FpmOjfvPSrDztSil7OfkqzFG7qsbe3wN+43vBe0g8MtboFBE9pLR4D41HeUkprhxL10JbDnO1b0REXASGThqsylwnHNzZ9JfejcXFzaVm/VB+CjOE1g8WcdugU1109f/6ffq+7fvRY0B3DJ84RLUN4xv0O9wsUCtpDidYPo1SDHv06IHo6GhWvEjZI2WIFDCaLXz99dcxaNAgTJo0CUFBQZg7dy7PsL3wwgusHNEsIz3j4eGhfVrdUHyajUxKStJCgPHjx7MSSsoUfaYhpJyRskjPTJkyhdcKfv/997hw4QKn75FHHsHTTz+NUaNGaTGqIeWRFLARI0ZwXFI8SeGlcErzP//5T/73pZdegq2tLT7//HPY2dlVzTHPlxwAAIa6SURBVJoOHz6cv+/999/Hf/7zHw7r1KkT5s+fr31D3dD3/O9//+M4pAiS4nvffffB29ublcsHHnhAe7IamtEkxZxcSYVuVlYPzTiQuSC5MqXE0voXPbSGrPb6F8ofKyurqtki2qxA/wwtDDcW31h4qQonk8wxt47EpfOX0L1/Nw6nN4tkZjXl/gk4m3IWsT1i0CnAh00AadOT62Gp8pSXlqODhxs+m/Ul3vnfHHQK9OH1jI2B5K+WrUylwVa7A1XOGitb3fHp+a49YzFq2nB8PGN+VThtBkJvdmf9bza+nrsIdz96O8+omBNaf0a/ox5dHtQ0BSdZSDY9hs+QLLQuavi0YZg/8/MqWVqSsmL1W18jQ810lNXKD3qGylR9bPpxE17/55ts2kdr2279nXnXYejKXxw72gyidnpr50vt8kd15noymZuWqkNsQvrsO5j90jyEx4aja2JMVftw8Xwmb05Dv5m+fTAlurJ0bftkSJlqw65bZ6ZeW2c8fTwwSbXNZLa8b0vjNs0QrqVC5VU7g3xoZ2uNilr1iMjelYw9j3+E/f/5HCH3DEFbfbur8sq9ZwQCb+mPI9OXGo1rbszVvhE/L/kFr/7jDaxauhrj7hythZoHahsSVNtGrvbYgfzXtA1qLFajfTMitzHefPptzHh2Ft57aS4iVdsQp+paa8GYUmcKJ1g+jVIMSSGiGbxnn30WPXv2xA8//MAKUHp6OitHv/zyCys4GRkZCA0NRVFREZuN9unTh+Pb2NioCmfLlc/Q9Eb/lkYPKZiNgcxbS0pKsHz5cv5+UiBpUxx/f39ERETwLB6F62fxDCEzU5oJpVlMSittdkPPkUxubm4ICwvj52jzG3qOzD9Hjx5dteGNk5MTP0vmrr6+uvUbQ4YMwaFDugXKhrLWlpN+Q5qBpQ11aLMZWsN5PY4ePcqysCJZVnNxeXBYIJLGDGBHsym0UyDh5OIIB2fHazYXIHO8ktISHiAQ9HzaCZ2JB80sGYtPpokd/Try7n5k6kI7c9Julu3t7Xixdn9aeD5psLpuj4Gj+/NOX5ezr8CrkyeHB9MmCOpzaeH69bBUeVKTT7NJLM0+0KJ8mjGgBe6NgcxWBo1JYnfKiGyZDZBNv4voqeOn6oxPG85Me2AyvvvqRxw02BSE4pw5pVu7m3khUxVUVT8NOk9zQDvRVv3Wql6ERIUg7XhNkyLKZ9pJkXBUsjg6OyBbk4U2z6BNWn78+icc3nWEw1qa9DRV1w1k6BwVfI0MVNZCu3RmP8ngoGS43sYetKkBtRPkTh5JQQevxpWnxhIcFqTK3gB2lF7adY+g8kO/eWatjW/05c/LoPydus4utuamJeoQzbZRPKKosIh3aHT36sDtAynwA7h9GKK1DwO4fTAlNdonrjOqvGltmh5dnakub9fWmQn4cYGqM7ur6wztPDnmrjFqpHYVX7+3UAsVmkNBWgbPBrZrr9pRlVcu0QG4cqLmjp7t7KvLR9H5bLTv6Iq2djrF0K1rEEJ/MwKpX61D9s5kDmtpzNW+2an6oofMOWkzJHNCG80MGqvaBuVqtg1OWt2+tn0rVWNIsqQhwmLCVNugs66pC8O2oVC1DWdVXa1tonozw7swm+FPsHwatSspmWzSW1daVxgbG8t+WoM3ZswYnqH78MMPMXnyZJ6Zo9lFUp5o5vDWW2+Fo6MjK0bkSIkkJe7+++/nz6B4kZGRiI+PZ8Xz97//PStiBJmohoeH80wlmXBSHPosgp596KGHcP78eZ61pFk8MgcdOXIkxyGli2b0SHkjc1Qy27zttts4LkGDMDJpJcWMzDzJXJWUV1oHmZiYyKaklHZSiCmd1FCuXr2avz8hIYGvadaPZvr05qgUn2bzaM3hhAkTWLaJEyfC3d2d1xPu2LGDZSCFlHZz7du3L6flvffewx133MFvrT7++GP88Y9/5PDakMJNvy+5L9+q2aGfPZWObWt2sKN1PWQeeEUpZbE9dbNZtBEEQTvXkfkHrSFwdXfjRpRs7JOU4kMbSNDsXlFBkdH4eZevoP+Ivur3qIB7R3c2UVz04VJWlNb/sBGbVm5hN+Husfj3b5/Dlct52LVhd1U4DapoK/gfF67kz6wPS5UnJ+uyGhD2Q/6VfHj7evGM4poVa6/pbOprAkm2rWu2s9PLlqvSFtezKzeeetlo11Ay59HJ5qpkC+aZPVJSSTZaU6SXrXZ8Z1cnPP7a//HOagd2HoS36vDpLSgrtKo8x6vfgXYopZ1Yab3U92rwWB/N3ZWUfru+I/rwtvjUgfYa2gNLP1quDWYdUXClgGUZPHGQlk/09vUq1n67jmdo/vHq35Cfm4eDOw/x4IVmRUiWptKULopk6Kdk4PKiynKvoT2x5KNlRmSg/Mjl2VrKD5KBoAEHKes9B/XgAT39FrQ1Os02dVRlifKI7tHgidbkNobG7EpKLwWqy18Rhqv0kjkplR/6ZVYZKX9uWvmjujVIKUH68kezZN37JqBb33g4ODrwLHzGuYu8hi1CyRqpylfvQT15QKmXtyFcb1fSlqhDlKdkDeDp7YmAEH906xePX5av5o1r1qn2YePKzewm3j0OT/32WS4fddGUXUmp7vYdruqMqqcdVPtEZtTLrqkzxRg0YSC3gWSVQVTVmVf+irzcfBzacVhXZ1TeUJ0Zf+84jJg2DN/O/x6uHVxg7+TQ6ONRWmJX0sPHktlt2raL1xtS/+ikypg5aO6upGWX8+EzsjsqyypgpxQ+76FxOPnBT7B2cYC1sz3KrhSiQ7dQOAZ6wd7XA+7KT6amaQs2wMbVAd1f/y2vNczafhz2fh48Y1hReP1Zq7poyq6k5mrf6Jo+j8og7QB+NvVco2epG7Mrac32rZBNPakNoHXC9DJk1be6vO5Su32LUO2bKmPUvq35bn1V+5bI7VsCt280Q39BtW/kj9fahsDO1DYk4Odlq5F1seG7SVvyrqQ/mWlX0pGyK6nF0yjFkGbSSLm5dOkSmzSSckMK0tChQ3mzFFKSaD3dyZMnefatc+fOOHLkCCtutD6PNn+h2TxSxGiNXUBAAM+20S6nvXv3rlIMSdkzphiuXLmS49IaPJoN1D9Lpps0K0izhGQ+SrNqpJRSenbt2sXrQUhhS01NxbRp1YWSlDcy5SSF8fbbb2cFjuSh9X6knJJM1GDoZaLvpM8hs1X6LjJTJSWS5KTZU1IgSW5KM5m1krJLM5E0g0pQ+um30CuG9Fl6xZDMc++8806epaRZWIpLCqenp+4NljHqO66ClBRnV2deG0NrZb6as5AHGQQd53D84Ak27aM35okDuvMAjt6G/7T4Zx7Q1RVftak8IBs4JomPQVinBla0BXpt6I3gltXb2cTLEA81uLmsFCvaMbQxWJI8NEtIMiSpzoM2u9mzZR+2aps/GNJQxUOfNtpKn9YoUNr0A0zaWp9kIyUoTclG6xn0sv1YS7ba8X38fXjhfabqqGh2hRytl6TnaYMBUqC7qoGku7cHx8nJrH/GurmKIf0g6eq3ThrTH0Hquzd8vxGHdx3m4wFojSadz0ZHNDi7OKG7yieSZeGcRZxPZBpEylP2pWwEhAYiUMmScfbCdd9U10dTFEOKdPbUOZaBfj+S4ZCSgTYnoQE25YteBn1ZW6DJQNC61S7do/ilgl+IL7JV3tCmOgNG9WOTPzqmo0ANIJd/8g0rWI2hqcdVGJYfVzcXfDFnQVX5o+Mp9OWP6lZPVf7IZOpsajp+WLySyx+tP7zr0dvZpIx2J6QjYWhARoPCkVOGI7Z7F+QpeQNC/Di/0k9fey6aMRpzXIW56hDNvo27YzRbONDGNZt/2YqdG65dq65rH7Zd094Z0hTFUF9nBlCdiQjExh82Ga0zpAR2T+rG68EWzVlcVWe69umKnIs58A8L4CNiMs5kqIFrNkbeMhyZF7Lg4ePB4TQDemxf43bCbQnFcMXK1dh36AhcnJQCdTYdnu4d4O9rniOlmn1chcqrgpQL8Bvbg88yPPf9DmTtPAH3xDDYujsj/1QGOsSHwHtYApxDO7FSeHz297wu0T7AC159olB88TIfZUHHXRSeuYTijKbvdtsUxdBs7Zv6vCilhFH7VphfhGWf0NEujWzfmnhcBddtlU5qu1zVv1/MNmjf7hxbs31TMl3bvjlw+0YmqDZKSaS+i9o3O3tbbluovaOjZDb9vAU7Nuziz20olqwY/qAUQ+ojTe1GiWJo8TTqgHuaVaO1dDRzSIoXnflHM1ukrJHSR/dImSFlimbLaObu3LlzeOedd1i5ojcxjz32GK+ho1kx2g2UlDoK79WrFyuYtB5x+vTp/JkEKX80+9ivXz9WyGgzG1Iu9WsX9c/SLB0phzQjSZ9H6wpJ8aK1enoR7733XnTv3p39BClttE6S1j7qofi0to++lxRH2hiHlFr6rOeff55nISntpHDS95CMY8eOZXNWmh2k+GR++uijj/KzZFJKawjJVJQUXPoNaZ0kzTCSIkkzrAT9js888wy8vLw4PaTEUlqNrTPUc70D7oUbS1MPULdUTHHAvSXR2vKnOQfcWyKNPeDe0mnqAfeWSksccN+SmOKAe0uiqQfcWyrNOeDeUrHkA+7/EnS75jMtM1O/0nyCpdIoxVCwLEQxtGxEMbRsRDG0bEQxtGxEMbRsRDG0fEQxFCyRZtqGCYIgCIIgCILQWqC1o+b4EywfUQwFQRAEQRAEQWBIhTOHEywfUQwFQRAEQRAEQWCMKXWmcILlI4qhIAiCIAiCIAiMMaXOFE6wfEQxFARBEARBEASBMVwXaMo/wfIRxVAQBEEQBEEQBKb2TJ+pnGD5iGIoCIIgCIIgCAJjTKkzhRMsH1EMBUEQBEEQBEFgDM0/TfknWD6iGAqCIAiCIAiCwNSe6TOVEywfUQwFQRAEQRAEQWCMKXWmcILlI4qhIAiCIAiCIAiMofmnKf8Ey0cUQ0EQBEEQBEEQmNozfaZyguXT5qpC8ws3GUm+QzVf66C1FUTXtjaar3VQcLVC87UOHNpYab7WQXZlseZrHbRvZfkTCFvN1zp4bsbvNV/rIG3RDs3XOnhz0zbN1zqwrmhd/Q/x9bkfNZ/l8WDQNM1nWj5MXaT5BEtFFMObmEF+wzRf66CylRXFPtZemq91sL08U/O1DqKs3DRf6+BIeY7max34tHPUfK2DKaX2mk+wRCYe+J/max08k/hvzdc6CC9rfQZuD6TP13yWhyiGv17ElFQQBEEQBEEQBKYSV83iBMtHFENBEARBEARBEBhS4czhBMtHFENBEARBEARBEBhjSp0pnGD5iGIoCIIgCIIgCAJD24+YwwmWjyiGgiAIgiAIgiAIv3JEMRQEQRAEQRAEgak0kxMsH1EMBUEQBEEQBEFgrprpT7B8RDEUBEEQBEEQBEH4lSOKoSAIgiAIgiAIjOEsnyn/BMtHFENBEARBEARBEBj98RKmdoLlI4qhIAiCIAiCIAiMMaXOFE6wfNpclYNFbloG+Q3TfA3H1d0VwRFBaNMGyEi/iPTUc9qdaui+m4crKioqkXzoJAryCji8rrgOTg4IiQxG23ZtcbXyKlKOnkL+lXy+1xgqG1gUq9PRRqUjox4Z3FCpZDhxKNmIDDXj+of4oaNvR5SVlfH16eTTyMm8DFs7WyT0jUdRYRGH5+fm4+SRFPZfjz7WXpqv6Ti4O8M73E/V1Da4fC4TWakZ2h0dNg526BQVCDsne1w6eQ5Zp3X3bezt4BsbxH7CRslxKeU8ss9c1EIaz/byTM3XOOg3D4oI5N/8Yj1lzlWVOcovwzLXOboz3DxdUV5Shr1b93OYIZ0CfRAYHogda3eivKxcC20YUVZumq/pOKn88Qn35/zJUflzKfWCdkeHrcofv6ggtFf5c+FkOjK1/KlC1aXQHlEoU/Kl7UvWApvGkfIczdc4LDV/fNo5ar7G4ezuAr/wAMoSZKo8yUg9r92phu67eLiwPGmHT6Ewr5DDvQI6wr2TJ/uL8gv5HrVp7R3tEaDqGbVxpUWlSD2UgoryCn6uoUwptdd8TcfWwxnOEX4sW+HZLOTXag9sPV3gFOqjjcKu4sqxsyi9XIB2dtZwjQlCWxsrfq7wbCYKTl9i/43EkuSZeOB/ms98HD2RguycHFhbW6NHQlct1Dw8k/hvzdd0qP/pqPofahvq639sndqr/kf1LwbtW4cAL7h2cuesK8kvwvnDaVyXmkp4WfPnMeyUPG6qvFG7m5+ehbxa8th7u8E5qCP7r6q2IfvoGZTl6fp+JyWPg6873UFZfjGyDzVPHuKB9Pmaz/K4NXCS5jMtC9KWaT7BUmn3nELz33SUlJRg3759OHr0KNLS0pCRkQE3NzeUl5fj559/xvnz55GSkoKzZ8+ibdu2cHFx0WJey8GDB/mzQkJCuBG8kVCanZ2dOc318fGbn2q+hkFyTbx3AnoMTERQWCDCu4Zh//aDNQZspBDe/Ze7EBQehKhuUbBWHe/Jwyn1xk0a3R+DJwyGj7834nrFop01xTmpfWLDaUgTS+mYpNLRc1AiAkMDENE1XKXjwDUy3MMyBCJakyFZpae+uFMfmITRt42Ck4sjy3fhTAayMrLg6e2B1+a/pJTkCg63UwrX0X3HtG+qH/92Dpqviahi2Ofu4QhP6oqOYb7wjQlG6o5jqDCQ1cWnA/rcOwI9bhusBuelSNt9gsMd3J3Q6/Yh6Bjqq+L6Yfjfp3HHnHH8LN9vCumVusFzY6DffMK947VyE8Dl5kCtMkcKxz1/uZPzK7JbZFWZIybeMx79RvbFsMlDsPzTbzlMj42tDW59aBoeffphLPvkG5QUl2h3GoZn2/aar4mo/Em6ewSikuLgrX7jwJgQJO84WiN/3FT+DLx3FPreNoSVp5Tdx7U7OjwDO+LW5x5AcEIYdn6zSQttGpmVxZqv4Vhy/ji1tdF8jUDJM+zuUeiaFA/fMH8Ex3TGsR2Ha8jjrBTCSX+6he+HxoehnY01Th9OhbWtNSb/+VYEqoGub6gfYvvH4dTBFBTkFqD3uH7oMao3vIM6oXN8KLLSL+HypcvaJzaMqAprzddEVHnrfN8weA+MhXO4L9y6BiNz2zFUGrYHXQLhP74XnFV74RYfApsOTsjZmwI7pWCF3D8cLpF+cI4M4LhZO47XiNviWJg8kb8fovnMx1dLV2DNhq34buUa3D5lnBZqHta8v1rzNRGVP73vHsb9j5fW/6TV2f8M4vbttNb/WKm6NPjPk+EdGQivzr4IHRCLcwdPoUjVpabiXqkS1BxU9Mh7h8J3UCxcVb/orspMxvaa5c2nfwwCRnaHS2gneHUPRVs1lsk5cgbtlDxxf52EDtEBKm4ndEqKRdaBVJQ2Qx4i4R9TNJ/lsWDGl5rPtNz6tzs0n2Cp3NSmpCtXrsSHH36IL7/8EgsWLMDXX3/NStXFixdx7733YvHixVi4cCG++OILzJs3D2fOnNFi1oQmTf/3v//h0UcfRWZm02ZFTMmMGTNQWNj4Qfj1cHJxwogpwzD7hffx5hMz0SnQF5FxEdpdHb2H9sLVykq88dh0fDbzc0x9cAoPmOqLO+rWkVj73Tq8/ey7WL1iHYZOHMzh5sDJ1Qkjpw7He8/r0uGrBmq1ZegztDe/yXtdyfDJzPmYpmSwIRmuE3fTT5vw1jPvsDu2v3oAn3UxuyqcBrgthb1SUrtNGYDvX/oCS5/6AO5B3vDr2lm7q6MwJx/r5qzAwR+3ayE6rlzIwTf/+ZTd6llLuUNO3nxIu9ty6MvNnBfmYvoTb8GXy024dldHH1XmKlV+vfHYDMyf+QWmPDiZyxyxVpWneS9/yP7axPXuqpQUG57ZvRE4qPzpNSUJS1+aj6+emgvPoI4IrJU/+Sp/fpmzHHt/3KaFVEMy9r19KE7ubNiLBnPQ2vLHUeXJgCkD8eVLn+LDp+YoRc4bIXGh2l0dCUO6cxv3wRPvYenbizDq/rEsj6NqH7oP74HPn/8Enzw7j19wdY4L4zgTfj8F38/9RoXPxa5fdmD4vaM5vCWxdnVAwLT+OPD8V9j92EdwUOWNlCVDLu8/hb3//hR7n/4UJz/6GaG/GcnhFYWlODHne+x5/GPsf3Y+PHpHwjHEm+/dKFqbPA1h1JAk/Pnh+7Ury4b6nwTV//zw0pdY9tSH3P/4dq2ZP9T/rOf+Z4cWosPe1RHRw7rj+xc+x7fPfYJ2Vu3gF1ezbWxpbFV56zy1P3ao8rb5iY/gHOQFj7hg7a6O3ORz2PG/L7BNlbejn61CzMNjONzWzREBI7rxva1Pf6YUxnbwqFVWWxuGG8aY8k+wfG5axfDSpUt4+eWXMW7cOMydOxfvvvsu/vjHP1bNsnl7e2PmzJkc/uyzzyI5OZmfMwZ9Fs0YJiYmsrKph2Ykd+zYgXXr1rHLydGZatEMpD5sz549HFZUVIQtW7ZwGP1L18TevXt55lLPDz/8wP9mZWVh8+bN2LlzJ9asWYPdu3dz+KlTp1jJXbt2LX+OKQmJCsb50+eRcymHZ8B2rt+lBm9x2l0ddL11lU7JOHPyDP+e7l7u9cZNOZqKiNgIdB/QDRFK0Tq403wKSOeoEJwzSMeOdbsQ36emDHS9ZZVuIM4ytNPJcL243v7eiFcyhUZ3hpUaFOqxbW/Lg9yYxC5wdnXWQs2Pd1QAm+bkZ+ayydvx9fsR3DtKu6ujOK8QWakX+H5dRAyKR/r+FBRkXdFCWg5dublwnTLXVZU5g/zSyhyRejwNhQW6umSIm6cbhk8disUfLqU3O1poy+Kr8odMQ/O0/Dmi8iesd7R2Vwflz8U68ie0VzSXrSMb9mkhLU9ryx8y97yo8iRXKaOVSp796/ciqleMdlcHXe9dvYv951PS0Ua1D65ebmzOe+nMRcQP6YauA+PRRsl5Tt0n7B3tkZejqz9XVH536WteM0BjuKryVnD6Ioov5bKZW8a6A/DsU7M9qFQy2Hm5wrNfNCtLlw+mcjjNbBSkVZuRl+cVKfmaOQPTTFqbPA0hNCQQDvbNtFRoIXT9z8Wq/udEHf1PppH2jWYPc85eQuSQeIQN7KrajDbITLnWRL0lcVPy5J++VFXe0lV5865V3kgxLC/UWTaUF5VWmYpWKHnyz2bCb2g8zzhSWctNvtZEvTVBkpvDCZbPTasYklLVoUMHjB5d/eaWzEC7dOmiXVVDSuLf//53nlk0xo8//oi+ffvigQce4BnGykpdI7dx40bMmTOHZx4XLVrECmFeXh6H0SwkhesVydWrV2P27Nn83HvvvcfKHkGzf5s2VZuI3XLLLfzvgQMH8Ic//AHffvstz3TSjCUpi6Sg0mwhha9YsYKfNRUuHZyRm5OrXalGUPldOjhpVzpc3NQz2bWeUWH1xd21YReiEiIwbNIQRMdH8hokc+FcR/oMMfYMhdUX98LZDF5POHBsEsbfPQ6R8bqZxFLVIdCaSTKXHT5lKEZMHcZvP1sCB1dHFGTnaVf0djaPwxoDmQp2HdMbe1eY9iVDQ3G+ptxc4TBDaufLFXpGyxdjkGIyfPJQHNp5GBfO1FzT15I4uDoh3yB/8jl/atanunDycOHZxtUffc8WCzeK1pY/jm5OVQocQXnipMIM4Wdq5RvNFtKawhO7j6HfpCT0nzwI5aWlyNNepuz6ZTv6jOuPyJ7RSrHsws+3NDYq3aVZ1ekuzclXYde2B/b+HvAb3wvealCeseaAFqqDlGBvNbgls/Mrx3RK742itcnT2qBZv8Ia/U9+g9u34vwiNiuNn9gPCZP6o6y0HPkGeX0joFm/YgN5SpQ8dkbKG0HPht8xCCeX6MZuZUqeiztPIGRyX4RO7c+KouFntUZqK3SmcoLlc9MqhrSmMDS0polQfXTu3JkVu9qQEkjK3K233ooBAwbwzOKFC7rBzIsvvsgzkm+99RbPPtJn0Mzehg0b8Nprr3H473//e372pZdewj333IO3334bd999N89mXo/s7Gz86U9/YkWSlMFdu3Zh/PjxrPDSd7/wwgvak9WQ3PT95IorGremqLS4DDa2ttqVbg1QSXGpdqWDFCEbu+q1PbpnSuqNO+6usfh05ud45R+v49MZ83HfX+/hcHNQpgYAtkbSZ0hdz9QXd8OPm/DqP9/AW8/MQvLhZNz2kE6Bp0HzC39+mc1kF8xZhEn3jodrh7rXqpoS6kytDdJrpdJbpvKhMTh3dIVn5044eQPMSAlKr61Ktx7j+aWeUUq5HnqmtNYzhjipAcvIW4fj0vlL6NY/gZ/v2isW1jbNXMPVSMpKy2rkjzXnT836VBe0LpGed/fzhH9MCCsr/l1qmjW1BK0tf2imgr5PD/3GpbXyhNoBY/nm6ecF/8hAvPf3t5SbiYLLBUgc1ZufWT5rMecRrTMsyM1HoVIiWxoajLYzSDete6owUt6ydyVjz+MfYf9/PkfIPUN4nRTTpg3ce0Yg8Jb+ODJ9qdG4LUlrk6e1Ua76H6sa/Y91g9s3N9WueUf4Y+E/3sMC5WgpQ5eRidrdG0NlSTlvWqSHylu5kf7U2rE9Ok/tBxtnexz/QveC39HPA25R/tjwl9lYrxzNWAeOvrHyCIK5uGkVQycnJ+TmVr/Fvh6XL1+Go+O1b4fOnTuHrVu3stkomW56eHhUzdTt37+/akaS3oLb29tzWL9+/XhzGILSQdAGOAMHDmT/4MGDcfjwYfbTjI3hjIB+NpKIjIzk76NnSOmkzXOuB33PkiVL2BWWNW7hc3paOjr6dWTzNf7OqBA2BTPk1PFUhHbRKdy0EYujsyOyMrLrjUsmlmRiRpxW/3p468zMzEF62rnqdLRV6YhW6TjRUBnqjluq8p/yiRxtrOHu1YHDSdYizVQu82IWCtSAkNYxtQTZaRdUB+vBg1hKh09UAC4mN+6teNSw7ji1/QiKr7T8QJa4ttwEI+34ae2uDl1+6daf0G/r4OzA+VUXtAHQyUMp6DeiL69nbW/fHkljBvB3tCSZKn/cVf7QixSSjUxLLyQ3bHMfMnqjt+qJE/ohol8MXDp2QHifa60dzE1ry58LKk881KDURqvjZFqafqLm2vL042cQ2EW3Y6+DiwPsneyRczEHPiG+KC8rQ0lBMcg07kLqebj76NqyK9m5WPTml/jsvx/ys8l7am4i1BIUpGXw7Fm79mqwrvLKJToAV07UNM9rZ1/9Gxedz0b7jq5oa6dTpNy6BiH0NyOQ+tU6ZO9s3g64pqC1ydPaqN3/kGlpQ/sfjxAf3vCppED1q6ou0XIHF60u3SiuqPJGCh6VN2ob3FR5u3yipjz0oiJoXE907BGBXS8v4N1HCefOPqhQinK5Js+VU6rs+ujGCK0V2iXeHE6wfG5axbBbt244fvw4Tp+uHsSQ8kfmmLWh2ThS9pKSkrSQashkk2Yely5dyuahPj4+bCJK621IaUtN1a1pIIWBdjt1d3fnNYOlpbo3Z/rjDWg3VFIyifT0dH6OIMWR0kVQPP3zBG1ZrYcUT/pOwsrKir/LGCNHjsT06dPZdbBrXEN7NuUs8i5f4QEbrQekzVd2b9rDA0NyxJaftyC6WyS69UvAoHEDcXjPEeTl5tUZl9i7eS+GTBjEa5EGjx+IbWtrLkQ3JaSAkilbf5WOxAHdVTp8sWtjTRk2sQxR1TLs1slQV1wiJjGG1xeS6zusN7at1q2z9Anw4eMq4pVstKlNbvYVXDzXMtu80/ESBTn5iB7eHWEDYuAe2BHJmw7C1deDHWFlY4Ww/jG8NbhHsDf722qmrrRGKnZ0T+xfsZWvbwRnVLm5ospNX63cdDJa5rbyDrgJ/eJrlDkiLCYMsT1iWLmg+F6dvJBx9iJe/MsreO2fb7KjWd1Zz77LR4m0JBla/sQOT0TkgFh4BnrjqMqfDr6e7AjKn8j+sfBQ+eMV7MN+yp9tS9bjs3++i88fm4Nf5nyD9KNpWDXPtKbjDaG15Q+tGcy/nM+byMT0j0NHlScHN+2Hh8oPcsTuVTsRmhCBLn1j0WtsP5xUSh7NAp5PPcfHUsT074qo3jEIiA7CsZ1HOI5vqD+i+8Ty2sLE4T2x+ovqtegtRf7J82z+5jOiO7ySYuAQ5IVLGw7CXg12yRGusUHw7BvF6/E6jeyOy4dPozyvGDauDoj99x08q0bHPdB9OiriRtLa5GkIh48lY/f+QygsKsaWHXtwPuPGHxlSF9T/FKn8iVL9T2id/Y81QrX+x131P+Sn9i0r9TzsHNvzNa1LpJeaaTdwky3iilbeaBMZnwFdePOZ8xsPsbJIjvBKDEP836bgnCqHTkGqDeylW1JyJeUCzyT6qHLq3ScSHbooJXnHjZXH3FRvF2PaP8HyuWmPq+jYsSNv/EKbtZCyRSaWZIpJ0MwgbTRDyiPtUkrr+UgBpF1HaR2iHlLEnnzySd6c5q9//SsmTpzIpqOvvPIKm3QS9B3t2rXj77Gzs4O/vz+vCSRFkExOSQkMDAxk/7Fjx3hGkJRQmg0cMmQIb2xD6yHpedrI5ptvvsEzzzzDCieF33nnnfw933//PTp16oT4+Hhet0gzkrSekb6vLhp7XAW9rDl7Kp3f3tNxFOu/34hDuw4jpls0m0fS+WV0RIOzixO6J3XndURkPpl3Oa/OuETqidOsaAVFBPGZhoveX1w1cGwMDWkyqtORxGerrf9+A69l6tJdyeBuIIOrM3ooGWgN4VdzFtaSoWZcYsDo/ohN7MJnrhXkFWLpx8tRWlKKgM7+rPQGhAWoQa8nlny4DOcbuG6q2cdVqPRmpmYgZlRPdAz3551HT+8+joDuYXy+FJ0pZeNoh4EPjWNzODKN8Qr1xfF1+1BZXoF21u1UxxyLLZ/81Ogz14zRlOMqSIazp86p37w/glW52aCVmy5Gylyill/6MkfQWrUu3aP4XEy/EF9kX8zCubSai/7pDE1S5Mm0szE0+7gKJRttLJMwqhefZbhX5c8plT8h3cP5fEM609BO5c+whyZy/ljZWsE71A9H1u2tkR92DnY8iEreplNCmkpTjquw5Pxp0nEVSp6MU+fRc1Qf+EUEYPsPW3ndYFj3SD7fkM40zMnIhqOrI2IHxPNawe/eX8aKIa01pA1ruiYl8HEV6cnp2LxsPW9AQbuT9hjZC34qn4/vOoadPzX+ZUuzj6tQshWoAarf2B589t+573cga+cJuKvBrK0qb/mnMtAhPgTewxLgHNqJ1+sdn/09r+OzpxcTfaJQfPEyH/1Ax0MUnrmE4owbs6MvY2HytMRxFStWrsa+Q0fg4uSItLPp8HTvAH9fH+2uaWn2cRUqf6r7Hz8c4v7nxDX9TxL3P9bcvun7n/xLug1rwuioi86+uKTq0t7lm6s2c2kKzT6uQn11nipTgWN6wC3CH2mqvF3amQzP7qGwc3fiMw39hybwozRT7arKlWtnH96khhRKahv8BtJRF51445mTSzbTtBo/31Qs+biKL6d/oflMyx1/0415Bcvlpj7gntbokQJI6wJtbGzg5eWF3/3udzzjRkqgn58fK43t27dnk9Bhw2oeCE/mo7ThDB1lQWaiemh9H603jI2NxaxZs9jEk2b06DNJ4aONZsiUk8JI0SSlko7IoHWIV65c4fMS//KXv8DT05NnC59//nmecYyLi2MFlTa4IWWVZilJSSRoQxuauRw6dCgrlt999x2vNTS2zlBPUw64t2Ram5mBKQ64tySaesC9pRJlggPuLYmmHnBvqTT1gHtLxRQH3AvmoyUOuG9JTHHAvSVhigPuLQ1LPuB+fIB5ztn89nTLW8YIjeOmVgx/7YhiaNmIYmjZiGJo2YhiKLQkohhaNqIYtiyiGP56aX01TRAEQRAEQRCEJlGJq2ZxguUjiqEgCIIgCIIgCIzhhjGm/BMsH1EMBUEQBEEQBEEQfuWIYigIgiAIgiAIAkPbj5jDCZaPKIaCIAiCIAiCIDCkwpnDCZaPKIaCIAiCIAiCIDDGlDpTOMHyEcVQEARBEARBEAThV44ohoIgCIIgCIIgMMaOmjCFEywfUQwFQRAEQRAEQWCumulPsHxEMRQEQRAEQRAEQfiVI4qhIAiCIAiCIAiMsaMmTOEEy0cUQ0EQBEEQBEEQGP0uoqZ2guXTRmnwklc3KYP8hmm+1kFrK4mRVi6ar3VwvOKK5msd+LZ10Hytg9MVeZqvdeDerr3max30LbfTfK2DNtq/rYVR7zyo+VoHO5fs1Hytg9Or92u+1sMz6Ys0n+Ux2G+45jMta87+rPmMc/HiRRw6dIhnFwMCAhAaGqrdqebgwYP8XLt27RAfHw8Xl9Y11rrRiGJ4E2OuiisIxrjayt73lV2t1Hytg4pWJk+7Nq3LoKVdK1OlWlv+9Lby1Hytg//ufF7ztQ6Gxv1O87Ue1qev0nyWh7kmHtae/UXzXQupI6+//joOHDgAGxsbtG/fHi+++CKcnJy0J4CMjAw8+eSTrBQWFhZi+PDhuO+++7S7gikQU1JBEARBEARBEBh6DWwOVx/Z2dn47LPP8Oqrr2L27Nk4efIkduzYod3V8d1336Ft27aYM2cOnn76acycORPFxcXaXcEUiGIoCIIgCIIgCAJDs3fmcPWxf/9+hISEwNvbG1ZWVjwbuG7dOu2uDroeO3Ys2rRpg4iICFRUVOD8+fPaXcEUiGIoCIIgCIIgCIJZSUtLw4YNG6ocXevJysqCh4eHdgX2U5ghDXlGaB6iGAqCIAiCIAiCwNCKdXO4o0ePYsmSJVWOrvXY2tqiqKhIuwKbiNI6Q0Ma8ozQPEQxFARBEARBEASBuWqmv5EjR2L69OlVjq710A6kNINIm8pUVlayaWl0dLR2V0dMTAz27t3L/pycHOTm5qJTp058LZgGUQwFQRAEQRAEQWBqbxpjKlcf4eHhcHd3x/Lly/Hzzz8jOTkZQ4cOZWVRb3I6btw4bN26FatWrcKCBQvQq1cvuLm58T3BNIhiKAiCIAiCIAgCYzjLZ8q/+qAjKGinUdpgZtGiRXjggQf4LMPDhw+zIxITE3lTmq+++orPM3ziiSc4XDAdco7hTYycYyi0JNdr1G825BxDy0bOMbRs5BxDy0bOMbR8LPkcwz6+gzWfadmSvkbzCZaKzBgKgiAIgiAIgsAYHjFhSidYPqIYCoIgCIIgCILAkApnDidYPqIYCoIgCIIgCILAXDXTn2D5iGIoCIIgCIIgCAJjqMyZ8k+wfGTzmZuYpmw+4+ruiqCIQLRp0wYX0y8iPfWcdqea4IgguHq4orKiEsmHTqIgr4DDO0d3hpunK8pLyrB3634OM6RToA8CwwOxY+1OlJeVa6HmxRzy+Hf2RwdP3fbHpaVlOKnilJaU8nVLYKl5ZIpGnWSjtCvRkFGPbG5KtgojsnVQspWVlCvZ9nFYc2js5jMhnC43TteJQ8lV6TLEtr0tImLDYW1thfwrBTh+6ASuVup+N2Px27Ztg9jEGLRp25Z/k6yL2Th98gw/T/j4e7OjZjon8zJST+i27DZGczafCYkI5rRVVlTgxOFkTntt7DTZrJRslPZjB5RsKl3tHdojvEsoHJwckJZ8Gulp1Xnao383lCt51YP87N5t15bJumjO5ibmyCvCyqodQlU5tHe05+sTqnzm5eax/3o0ZvOZ6nrSRtWTjHrqCeVZzTTWF5fKkrdBeUpT5cnR2VHVrRC+Tyk8nXIW2aocXo+m5o+lttmm2HzGwd0ZHcP9WLbL5zKRlZqh3dFh42CHTlGBsHVqj0snzyP7dPX9DgFecO3kzq1sSX4Rzh9OqyqPTaElNp85eiIF2Tk5qg5Zo0dCVy3UPDRm8xlz1R+iU2AnBKk+dPvaHdyHunZwQWBYgHq+rapXldxG52Zf0Z6uH0vefKZHpyTNZ1p2nFuv+QRLRRTDBlBcXIwDBw4gL083APDy8uJDN9uqwVxd0BkrAwYMgI2NDTZu3Ij+/ftrd0xHYxVDauhueXgaQiKDUa46z5KSEsx7+SMUFRRpT6hGUXXGv3v8QW4sbdTAafeG3fhp4c987/6/34uw2FAeXDw47CEO02Nja6Pu34Mpv5mMW3vciSs5DWsYm4O55Bl5y3CEdw3nTtnJ1Qnff/Uj9m1pviLSECw5j5qrGJJstz58Sw3Z5r78YQ3ZSCH87eO/Ydlo4L5rwy4D2e5TsnVGJ38fPDCs+TvUNUYxpHQ9/Phvq9K1U/3mPyz8SbtbTZ8hvTBy6nAU5BegfXs7fPDmJzywqCu+lXU7/OHfjyjFsA2s2rXjX/j9Vz5QykY+XNyccdvvpvFApaK8HMlHUrB8/grdFxmhqYohDY5+/8RvWQmys7PF9o278P0C47KNnjYChXmFsLO3xdw3PmbZfNVA6d4/3ImuPWPw7Vc/4IvZX2sxgKXbvsJWNYAqLS1l2Wc+94525/o0VfEwV14RXXt0wfDJw7gsq/+w+OPlSDl6iu9dj4YqhvTZt1E9iQpGmVKASMF5/+UPrqknv9PqiZ1K+05VT35cuLLeuFSebvndVK08VXB5+laVp8BQf0y6byIri9RGZF7IxCcz5vN1fTQlf8zVvpmizW62Yqiyd8DvxsI7wh8VSmEoKy7FytcWoKSgWHtAp/wNenQCAhPDsXPBOmyY+x2HW9laY9QTd6CdlRWuKrntOzipuF8rxfEi328KLaEYzpr3GY4eP4mz5y5g2fzZWqh5aKhiaK76Q9ja2eABVQan/mYKpiXejlzVh8b17oqhEwejUtUpKq9px9Pw9fuL+PnrYcmKYaLPAM1nWnae36D5BEul6a9kf0X8+OOPmDdvHr7++mt8+eWXeO+99/j8lPr4zW9+gytXdAPvb775hv+90Ti5OGHElGGY88JcTH/iLTWg80VkXLh2V0efob1QqTrXNx6bgfkzv8CUByfDWnVaxNoV61Qn/iH7a0ONo7VSguktdEthLnnWfrsebz/9DmY9+y5OHDyBIRMGaXfMT2vLI0P0ss1+4X28+cRMdGLZIrS7Onor2a5WVirZpuOzmZ9j6oNTDGRbW6ds5qbv0N7qN6/Eq4+9iU9mzsctKl02WroMuf2RW7Hs02/wmko/zZ6NmjqCw+uKX15WgfdenIsZT8/CjGffQWTXCAR09uc4/Yb3gXMHZ7zx1Ezl3sIvy82zzXc/TttVvPyvN/DhzM9w24NTjcp21yO3YYmS7eXH3kDqidMYo5REIjc7F/Pf+xJrvzf+Jnj2K/Mw/em3G6UUNgdz5VU7q3a4+493YsOPm/D6EzPw5lNv49zp8xzHlJBiQwrre8/r6olvUKdr6kkflUZSgl5Xaac0TtPSWF/cvqo8uajyNF2VJXKrtfJ07vQFvK3K3lvPvINPpn+GyfdP5Jlsc9Aa22w99i6OSJgyAD+89CWWPfUh3IO84dtVNxOrpzAnH+vnrMDBH3doITrsXR0RPaw7vn/hc3z73Cdc1vziOmt3LZdRQ5Lw54fv164sA3PVHyKudxysbKxr9KGXzl3C3Fc+5Dac6s/tqp2kF303O/RayBxOsHxEMbwOly5dwssvv4xbbrkFc+bMYde5c2e8+OKLSE1Nxc6dO7Ft2zasXr0aR44c0WLVZPBg3XkwWVlZ2Lx5M8dZs2YNdu/ezeFEbm4u31u/fj22bt3Ks5Smht6CnVeDgJxLOaioqMDO9bu4oTOElIetq7ax/8zJMzwr6u7lztepx9NQaPDWTY+bpxuGTx2KxR8uVTW/5aq+ueQpKS7hwXn3Ad3QKaATTqtBY0vR2vLIEJ1s568jW5ySbTv7jclm+Na3JYnvE4ct2m9Opp5t21WnSw+ZJAaFBmD/jgN8vVk9n6DiEfXFLystQ7zKU5rBIrPEK5d1lgmDxw3E7k170KVbNGISu/DbbHNAady0aiv7KW1tjMhG5qNBYYHYv10nGz2f0Cee/fl5BThzKp1nHI0Ro9If36srvH07aiHmxVx5RTNufkG+yMnK4fwic7PGmis2hM5RIaxw6uvJjnW7OE2GGKaR64mWxvriDhqXpMrT3mvKE5U/eycHfi4xqTuSD6dcd7awqbTGNluPd1QAz/DlZ+byTNSJ9fsR3DtKu6ujOK8QmakX+L4hZBqbc/YSIofEI2xgVyVzG2SmXGv+aGmEhgTCwb69dmUZmKv+kKkyvdRY9MHSGvWDns/T2uzy8gqeBacye7OjWxFo+j/B8hHF8Dps2rQJnp6eGDZsGF9ThX/kkUfYPPS7777D448/zjOCX3zxBV544QUUFV3baZFSSZA56h/+8Ad8++23PPv4v//9j5VFeju9bNkyLF68GEuXLuXZyS1btnAcU0KzD7k5udqVUkZzrnCYIc5q8EMzAHrI3JDC6oJ+j+GTh+LQzsO4cOaCFtoymEMePRFxERg6aTB8gzvhoJKtpWhteWQIzVbUlC1XhTlpVzpo8G0oGz/TgPwyNw1JF607Ky4s5tkOwvCZ68UfNCYJo28diQtnL/A6Q8LLxxNh0aFIGtkPo6YOZ3Mlc+Di5lIzbcpPYYbQ+sEilk03oNWlv+Yzxti3fT96DOiO4ROHYNI94xtU95qLufLKo6NSTpQylTSqHwaOHoDJ905ASHiw9pTpqF2/jaXf2DMUVl9cT1WeQlV56j+yL0ZMHVajPLm5u/KLiMHjB2Hnup1aqOlpjW22Hpr1K8yuXm9Ks4MOrjXbt7oozi/C6d0nED+xHxIm9VfKejnysxq2dlWoSX11QI+xZyisrrj6PvTgzkN19qH2Du0x9o7R2PDjRjbVvtkh5dccTrB8RDG8DqdPn0ZoaKh2pcPe3p6VRXqjROaiTz31FN59913s3bsXZ85UbxxhjOzsbPzpT39ic9TCwkLs2rWLZwtff/11DBo0CJMmTUJQUBDmzp2rxahJWloaNmzYwK64onGzimXFZbC1tdGudGvO6E2rIWRXb2tnq13pnimt9YwhTqozHHnrcFw6fwnd+ifw8117xcLa5lrTLVNjDnn0/LzkF7z6jzewaulqjLtztBZqflpbHhlSqmSzsa2Z7pLimjMupUo2G7v65W8paB0TzQyRo1kVw9+c8qh2usrLy2FlZVU1E0Ny6J8hueqKT53ljGdm4b9/epEHJpFddaZ1NDik2ZFZ/5uNr+cuwt2P3s4zXaaAZEvoHceurLRUpa36Nyf/NbKVldWQzZj8xnjz6bcx49lZeO+luYiMDUdcjxjtjmlpibyi/PDs6IGVqk2Y+ew7PPttjrahrKRmfhhvA4w/U1/cci5PhXj3f3OwUJWnOx69jWeCiTMpZ9m89PV/vYkBSumlcmgOWmObrYd+XyuD357WDdI6w4bg5ufJaxMX/uM9LFCuKLcAXUYmaneFxmCO+kMmpvTi7qLqQ7v378bhuqUZuj6UrpPGDEBoVGd8+V71GuubGVLhzOEEy0cUw+vg6OjIipshNKggpY7eIiUkJLCiSJvMBAQEICOj5i5ktYmMjISHhwcPSMgklZ5PT09nhfGXX37BkiVLOKy2Mqrn6NGj/Ay5wrJ8LbRhpKelo6NfR95Qgb8/Khhpx2ua3Jw6norQLrq1DY4ujnBwdkBWRt071NnZ2+HkoRT0G9GX30C3t2/PDSR9h7kxhzwEyaSHTMloo4SWorXlkSHXyhbCpmGG6GTTlX0nJRvtmHi9/DIXZDpJM3nkTql0hhmky0GlK7NWugryClFSWgJPHw++puf1u4ieOn7KaHxS9GinS6JUDSJJ1oAQ3RpDinPm1Fn204YgtLmFodLcHILDgzBorJJNuZqyOWlpy+JrPSRbaUkJz2ISYTFhSrZU9tcFmWdRPKKwsAhn085VmQSampbIq8yMTDUwvFj129DunbRxj6mhXV2r6klbVU+iVT2ptRttXfWkvrgk19lT6ey/dEHJoJUnfX0kaAavnVVbuHZw5WtT0xrbbD3ZaReUgucBa/WbkmxkWnoxWfd7Xw+PEB/e4bKkoIQ3n8lKvQAXH/PUldaOOepPe1W+kg+f5Nl2mpXmPnR0f96pmdrv3kN7cp/6wWsfIftiDn/uzc5VM/0Jlk+75xSaXzACNfCffvopRo4cCWdnZ367v2PHDvz000/o1asXMjMzMWbMGH6WNqbp06cPz/jNmDEDDz30ECuNtB7xySef5DWJtB7xzjvv5Od/+OEH+Pj4ICwsDN9//z0+/PBDTJ48GaNGjUKPHj1gazC7oocURrpPbsFbi7XQhkFrl/qN6MN28O5eHdBLNWZLPlrGnS81jAVXCngN12ClPJA5RdeesVyR1367juPTYDA8Ngw9B/XgAT2ZS9B247QZw+aft7Abd9cYPPO7/1TZ3JsTc8hDW1bTNX0edRA9ByXibOo57NvS8G32m0NryyND6PtIOdXLRhvNGJNtyMRBuJJ9RZMNWPPtWo4fbiAbdez6/GoqlfzpdUOD6K1rtrOjmRZSqmkb8rieXfk3X62lKzohigfUZEHAW52HB7PCN1ANHNZ+v4FnY0guY/HJPLFL92h4eHvAL9gX3fslYPV3a5UimMUvoOLVb1CmBowRXcN5jYux3UL10Gc2FFI4DWUjU0+SIa5XV/VBV7HqW93GJF0MZCNzw+CIYJ5pGzR6ANZ8t55lo7fmiX0T0E05B0cHfut+4dxF9sf3ioWntycCO/ujm5Lt52WrkXWxptJZF201ZaUhtERe0XrCEKVQ0+wAzaj1HJiIo3uP4diB4/zZ16NtA3clzbt8hesJlW93VT6ontDaYMN6QjPJ+jRSPSEojXXFpXpC5SmuVnn6ccFKfkFD6y29fL34KA7ain/Flz/wzGt9NCZ/9Fhym+3X1kHzNY3Cy/m8gQylybmjKyIGx2Pzxz+hvVJs7ZzteX0hbVwS0icaIb2j+cgKWlt4+ZyqD1crETOyB/Iu5SqFsAMiBsbxGsXMlKZvbjT4oSGaz3wcPpbMbtO2XbzekNoGJ1XvzcGns7/VfPVjjvpDRyut/2EjNq3cwm783WPx9G+f4/JM9eefr/2Dw+naW5VBOu6l9jpSYzzwj/s0n+Ux+/UPNJ9pefT/fqP5BEtFFMPr0LFjR94shkxKacv1kydP8npCMvmkWcJz585VKYYU3rdv33oVQ9pgRq8YkjLYqVMnPtZi3bp1qsMuY9NU+g5ae0gzkPXxyZufab4GosaNZ0+dQ9KY/jxjsOH7jTi06zBvRkBn8dBW7VkZWXB2ceJNCMi2fsGcRTygJ8jGvkv3KORfyYdfiK9q/LJwLq1mx0Vvaret3n7dQYVJMJM8A9TnRakBZGB4AArzi7Dsk+WobfJoNlpbHhlAywtoAE9vVoOUbOs12WhzktqydVey0eDbULZhLFs08pRs/iF+rGDUlq0xXE8xNIRmiZxdlTKQlMjp+mrOQh4EEOPvGIPjB09wGaFz4WhNXYQavJI8Py7+mXe/qyu+k/KPnDJMKVyBanAeyIrNdm2NF23SQWWga48YuCvFkeLkZNb9NroxiqEhnDaVjp4q3a7q3y9mL6iSbcKdY6tkozfnPVW+kEno2dR0/LB4JctGCuBdj97OJlg2auBLeUty0JEW9NsEK0WDzvna9PMW7Niwiz+3ITRF8SDMlVcE/Qa0vjA4MgiXs3Lx7RffNfg80IYqhtX1JIk3uFmvFFZaH0xl39XdoJ6oNPbQ2gBKI9WTuuIS+vIU26MLPLzd8bWqW1SeAkL9MXBsEv/bUSmHpKg1pF41KX84fZbZZjdXMSTZMlMzEDOqJ59leOjH7bxuMKB7GJ9vSGca2jjaIemhcbzLqpWtFbxCfXF83T7kK4WQFImwpK7w6uyLS8np2Lt8M5fHptISiuGKlaux79ARuDg5Iu1sOjzdO8Df10e7a1oaqhiaq/4YQn3oVq0Ppc1pyNSUIMsF3qRr24EG9a+WrBi++/o87lFM7X7/f79V/xcsGTnHsAHQrCCtCTx79ixvvpCYmIgHH3yQdxBNTk7Gww8/zM/997//5Rm/2NhYPq5i+vTpPMtIm88sXLiQN5+hzWWeeeYZfp52OKUZwKFDhyIlJQXvv/8+m6jS2+wJEybwLGV9NOWAe0FoKk1VPCyVxh5wb+k054B7S6Q5B9xbIo054P5moLXljykOuLckWuIcw5akMQfc3yxY8jmGMR17az7TcjBDtwO2YLmIYngTI4qh0JKIYmjZiGJo2YhiaNmIYmjZiGLYsohi+OtFNp8RBEEQBEEQBIGhF8Hm+BMsH1EMBUEQBEEQBEFgSIUzhxMsH1EMBUEQBEEQBEFgaJWZOZxg+YhiKAiCIAiCIAiC8CtHFENBEARBEARBEBg6zskcTrB8RDEUBEEQBEEQBIExZgZqCidYPqIYCoIgCIIgCIIg/MoRxVAQBEEQBEEQBOaqmf4Ey0cUQ0EQBEEQBEEQGFLhzOEEy0cUQ0EQBEEQBEEQGGPrA03hBMtHFENBEARBEARBEBilxpnlT7B82igNXnLqJmWw33DNJ1girW1r5jbav62F0quVmq91UNnK5GnbpnW9t7RqdTWodTGinbfmax0kTZ+m+VoH3y3eoPlaD6988abmszxCPOI1n2lJydyr+QRLRRTDm5hBfsM0n2CJlLWygbp1Kxuol1yt0HyCYH6sW5mBTmkrqz8Pt/HTfK2Dj3Be87UOVu2bq/laD9YeIZrP8gh2j9N8puVU1j7NJ1gqYkoqCIIgCIIgCAJDM0bmcILlI4qhIAiCIAiCIAiM4bpAU/4Jlo8ohoIgCIIgCIIgMLTKzBxOsHxEMRQEQRAEQRAEgTE0/zSlEywfUQwFQRAEQRAEQWCumulPsHxEMRQEQRAEQRAEQfiVI4qhIAiCIAiCIAiMsfWBpnCC5SOKoSAIgiAIgiAIjOG6QFM6wfIRxVAQBEEQBEEQBMbYbJ8pnGD5iGIoCIIgCIIgCAKj1Diz/AmWjyiGgiAIgiAIgiAIv3JEMRQEQRAEQRAEgTFmBmoKJ1g+bVRGSU7dpAzyG6b56sfV3RXBEUFo0wbISL+I9NRz2p1q6L6bhysqKiqRfOgkCvIKOLyuuOGxYWjv0J797azaoaK8Avu27oeHtwd8gzpxOGHvaI/92w5UfZ4pMIc8Dk4OCIkMRtt2bXG18ipSjp5C/pV89VwbdI4OgaOTo6otwKXzmSpOOse5HmVXKzXf9Qnh9Lpxek8cSjb6e9m2t0VEbDisra1U2gpw/NAJTithLL6tnQ3CuoTCxtaGG2SS99zp8/y8Ht/ATggKD8T2tTtQVlauhRrHuk3T3iM1J786R3dGB09XlJWUY+/WfRxGBIYFcnilkr+4qBgnVZxyVQYbQ8nVxj0fEhHMaaxUaTxeRx7ZaXlkZTSPjMe3UvUnVMnpoOoKPXlCyZKXm8efo69j9AzJZ/gbmJLmyEZppHLmqOpQWvJppKdV52+YksvN0w1lpeXYs2WvFmoezJE/JBs9r4finz55hutRkCqD7ko2fRmkeldfGbRuxHvY6jrTRtWZjHrqjPp+lV7DNqOuuJReyguSl9KbrKWXnuPyp/KPqvjFcw1r40obWX8M0f3WlPYKnDiczHlRG8O8ItmOHVB5pdoxypNwVd4ovbXLW4/+3VCufg/1ID+7d9t+7c71ebiNn+ZrOnbuznCLUJ+j2rr89CzkpWZod3TYe7vBOagj+6+qdGYfPYOyvCK+dgrwgoOvO91BWX4xsg+lVZXNpvARarb19WGO8qank0EfU676GNcOLqr9DlDPq75W9ZGpJ9KQm31Fe7puVu2bq/nMx9ETKcjOyVF9rDV6JHTVQs2HtUeI5rM8vFwiNZ9puZh7VPMJlkqrUwxLSkpw8OBB5Obmom3btmjfvj1iYmLg4OCgPdFw9u7di44dO8LHxwf79u1DSEgInJyccOLECYSFhWlPmfY7iePHj6Ndu3bo3LmzFmKchiiG1Fjf+vAtrPSUl5ZxWue+/CGKCnSdEUGDod8+/htu8En52LVhF35a+HO9cW9/9DZ4elMnBkTGR6qOPR+P3fMk4vt0xYBR/TmclMJB4wbiwWG/w/kzFzisuZhLnqETB6Pn4J7IVwNyFzdn7NiwW8VZCS9fL/z2Xw/wwIUUMuqn3/3PeygpLtG+rW4aqhhSeh9+/LdV6d2pvvuHhT9pd6vpM6QXRk4djoJ8NWBtb4cP3vyEO+G64nv6eOCeP97JcrdT5bJYpXneax+hUPutSHF88O/34ZbfTMHkxNuQm1N/59wUxbA5+UXcr9IXFtsZnfx98IAqR3qo/HUK8OaBraOLIxbPW4Jj+49rdxtGYxRDSuOjj/9OS6MNtteTR6M5jwrVwNYO8978uCqP6orftUcMRkwexr+V+g+LPl7GLybufvR2eKg8JKK5jhXg73c/xtempLmy+Qb4cDkjOVZ89QO+mLNAiwH89h/3IzwmTOWVD+4e+qAWanrMlT+e3h646/e3c1zKn9FThuPVJ6bjl2/WcP50CvThwa6TixO+nrcIR+spgw1VDOl7bqM6ExWMspIylJaU4v2XP7imzvxOqzMkx05VZ35U7VV9ce+gOmOQ3kXzFnN6O1Ib99iDKMjNh5WNtWrjruKd567fxjVVMSTl4vdP/JZfAtnZ2WL7xl34fkEdeTVtBArzVF7Z22LuG1p5U4rGvX9Q5a1nDL6l8jb7ay0GsHTbV9iqFJDS0lL+bWY+94525/o0WzFUdTfm4TFwi/JHZUk5ytXvv+vlBSgvKNYeAAJGJcJ3YCwqVbtl42iHcxsP4eTiTWhna43Ep25HW9XHXFXKsm0HZ+x+ZQHy0i5qMRtPQxVDc5U3gvqYB/5+L6aqPmZa4u3cx8T17sr9Lf8Gqr1PO56Gr99fxM/XR0sohrPmfYajx0/i7LkLWDZ/thZqPixZMfR0idB8puVS7jHNJ1gqTZsCsGBWrlyJDz/8EF9++SUWLFiAr7/+GikpKdpd3fR4Q5kxYwY2bdrE/vXr1+Py5cvsf/HFF/lfPdf7zutRO01ffPEFli5dql01DxoAjJgyDLNfeB9vPjFTDQx8ERlXs8L3HtoLVysr8cZj0/HZzM8x9cEpsFYdVX1xv3rva7z97LvsLiilb9136zl875b9VeGrv12HEweTTaYUEuaSZ9StI7H2u3W6dK9Yxx0XEasGuzTj9vYz7+Dd/85Bj6TucHZ14numou/Q3qhU6X31sTfxycz5uEWl10altza3P3Irln36DV5TctGb8lFTR3B4XfGLC0u4w33jyZk8QIpXHbJfcPXgJ753HKzVQDAnU1euzUFz8otYu2It5ilFsjY71+/CjKfewltPz8KpY6kYPq1hs+dNpd/QPvwbv/zYG/hI/ca31ZFHdz5yG5aoPHpF5QXl0Wgtj+qKT7PtpFSt/3EjXlMKxxtKJv2s7vz3vsKMZ2axozq0RpVLc9Bc2Wiw97lK69rvN/C1Iau/XYvZL8/TrsyHufLn0oXMqjygunUlNw+7Nu3hONvX78TrT87Am0+/jZRjp1iJMQVOqn2hF0DvPa+rM2SBUbvO9FF1nmaTXld1htI1TUtvfXGpzkyntoDrzCmMmDacw/Vt3EzVxr3z39nomZRo8jbOkH7cXl3Fy/96Ax/O/Ez91lON5tVdWl5RnqSeOI0x2u+bm52r6saXqrzp+pzazH5lHqarPGmMUmgKbF0d0Hlqf+x4/itsfuIjOAd5wSMuWLurIzf5HHb87wtse/pTHP1sFSuShK2bIwJGdON7W5/+TCmI7eAR3zJKg7nKGxGn+hh62WDYx1w6dwlzX/kQM1Q5/GT6Z6pfuw1t2iqt2gIYNSQJf374fu3q1w2NS83hBMunVSmGly5dwssvv4xx48Zh7ty5ePfdd/HHP/4ROTk52LJlC3bv3o01a9Zw4Tx8+DA2bNiAdevWIS0tTfsE4MCBA1i7di22b9/Osxt6unfvzrOFR44cwVdffcXx6PPq+k6aOSwvL+fvJaWSnr9wQacgFRYWcjrouyicrmkWksLo+fz8fH7OFNCbvPNqoJlzKQcVFRU8OKDG2hC63rpqO/vPnDzDaXf3cm9QXGc3J0TGR2Dbmh1aSDVDJwzCquWrtSvTYC55Uo6mIiI2At0HdEOE6tgO7jzE4ZlqYEiD956DElmBOZNyBvlGTNSaQ3yfOGxZtY39ZKZG5qyUXkNotjIoNAD7dxzg683q+QQVj6grPpkjVptZtUFBXiH/FkQHTzeMVArbwg+WmLWxbk5+EanH02q8udZDZnA0uCRKikpwtcK8HQ791ptXbWV/XXlEJm+GebRJPZ/QJ579dcWn2Wn/IF/kZF1mxZ1MsuituyHO6pmo+EhsWaPLY1PTXNmoPpw5lc75W5uU46koLCjUrsyHufLHEJrBohk2yiuCzE0NyyDNppiCzlEh/HJAX2d2rNvFddwQwzrPdUZLb31xyfxPn95ig/Tq27heWht32gxtnCH0W9NvT9Bv3aauvAoLxP7t9ZU34793TLdoxPfqCm9fnclmS+EWFYD805dQfCmXzUTT1x2Ad58o7a4OUgzLC3XjivKiUla2iIqSMuSfzYTf0Hj4DoplRSk3ueGmoM3BXOWN+hh6Kbjog6U1+hh6Pu9yHvvJ4oPGWfp+6UYTGhIIB3ud+f6vHcoxczjB8mlViuHmzZvRoUMHjB49WgtRA9OQEH4T/Pvf/x4rVqzAokWLkJqaivnz5/OsHM3wvf/++6ycnT9/Hm+88QbP+C1btoyf0/Pkk08iOTmZFUZqAJcsWcKKXF3f2aVLFzZnWb58OT/7+eef46OPPuL7Fy9exL333otvv/2W7507d45nJ2mmkJ4/dEinlJgClw7OyM3J1a7o7X6uCqv5NpgGp/QWVg8/o8IaEjcxKRGpx1KRlZGlhegg874uiV3UgN+0g1lzyUPmi1EJERg2aQib7dE6N4IUk9LiUgxXHdywyUNw8kgKlydTUld6DSGz3OLC4qqBneEz14vfTnXifdSAj0zDTqmBOnXCZLp4QCm/ppzNNUZz8qsh+AX7onv/BGxauVkLMQ+Unss10njlmjTSGsH68shYfI+OakDcBkga1Q+DRidhyr0TERJec5ahl6pjNCuaWauOmYrmymYJNFeG68WngfqQcQPxi5EXXf6qDCYO6IYNJiqD9CLgevXB2DMU1pC4XGdUejdq6T2lb+OmDsfwyUNx8vBJk7dxhri4udRMo/JTmCG0frCI80qXDp0cNZ8xxr7t+9FjQHcMnzgEk+4Zz79HS0GzfsXZOoWHKMnJh50KMwY9G37HIJxcorNIKssvwsWdJxAyuS9Cp/ZnRdHws8yJOcob9TFUlugFK1kUGcPeoT3G3jEaG37cyHsUCJaFfobP1E6wfFqVYkgzf6GhodpVTUgZe/jhh3lGjxSw7OxsTJw4EVOmTGEFjUw/SXEk3nnnHfzf//0fzwbW5r777oONjQ1mzpyJf/zjH/V+Jz1Hnz958mSMHz+eP7e4WLfegL5/6tSp/DmkgNK6wlmzZuGZZ55BXl7dHQJ9H810kiuuqF67UBelxWWwsbXVrlSabG2UglBzRqJUdUI2djbalf6ZkuvGpfUFg8cPwqpv1moh1dDbXZopos1GTIm55Bl311h8OvPz/2/vPuCkrK4+jl9F6U0RKbKAoiLSBUGlCKEKqIia2DF2Ew3Gkih5LUEjEX0tqK9gARELCiiChSjFWKKoqFgQjIgQMDRBaUoxvPM7+zzL7LILEnbYOTP/bz7z2WeGwezDzDxzz73nnhNuu+qO8Njdj4f+V5xtj7c8pkVYuWJVuPWK28KtA24Lzds2C3Ub5Nif7YpaOTVthYjbpo2bQpmyW3+vMtHvm4zV57322sv+zcH5xc/hfIv6+zy/WZumoecp3cKjifPicdJ/ev2yR1j27xWhdfsj7N+BfR+klRa3XXm9dqR6rerhpHP7hrmzvggfvV38RVlyX6PmdttY4DUq7DwKvkbsr9lYxGsU/32KslSvUT288ty0cPeN99ls+vFnbJ1k4r/FyvuUiVOjR4pHcZ5bSdkdr0+MAJ7P/ftRGmls/9rVwym/Pil8/tHc8EExFdfZtGGj/W6x3N8l/791Uc/Z0d/l9+33675hTuL3jT8zR3CNW74y/GXAX8NffvdXW8EvjmtcMl6rlon/LrdNG/P/jhwXPL/Nmzblf60K+TcoDGm9fI4eGPxQOKzpoaH5kU2iP0k99hWWKrv1Gsq+wc2J619Be1csFxqc3C6Urlw+fPHkdHusYp39bG/iGwOGhdcTt43frwv1jmttf5ZqqXi/8R1znH3HLA+tCvmO4X7HXh3CwY0ahKce2LpHVERKXkYFhqR6UgCmMI0aNbJCMvjwww8tUGS1buLEiaFNmzZhU+KLiJW6jh072mwXq4DNmu24KtX2/j8XLVoUHn744TB27NgwZcoUSxElIAQFbRo2zM3F5//36KOPTnz5lQnly5e336coc+bMsd+b2/pNO073WbxgcahRp0agqAdfsqR+sAqWjFWkgxvnBreVqlQMFStXDN8uXbnDv8uGdIqKzHx9ZvTIVp0tjTT3S684pep8mrRubCkyIL1pv7zCOg3D0kVLA2lXP6z/IaxctjLsW31f+7NdQZpUp14d7caMPVUdwe9bIfH7rkj8vslIA92wcYMVlAHPp5ob5n8xv8i/T/VYBq4vjpkcPp2ZuxJdrnzZ8OXseaFDj2NshbRc+XLh2OM6BKoAFrddeb22h0p4x5+Zuz8nVQOLAw+pn3h9OtiN35FKiMj9HStss4IXv0b7J71G85Neo8L+/oqlKxKDp2X2E6QqU5wjtm/iM3bwYQeFd/++7WdsVxTnuZWU3fH6xDp0a2cVLimyFdsn8R7se2YfS49iP2hxIf077zOzZ+Izc3jiM1Pg37roa1zRfzf3M9Pbft/kz0yjlofZBF7yNa7a/rt+jUt24KGJ16p34nqXuOW/3lWKrlfbvlYbN/BaVbf7hzQ5JHEeWzN4CkN6I38P6xPnsSjxb1EwRTWVVi9YagFeqXKl7d9+n8Prhu/+mb+6a6lEEFW/T5tQ48iGVpiG6qOo3KBW+Gnj5rB5HWnx/wmr5y8N5WsV72tQlFS83+LvmPaJ75gufTvbd0zH49rbdwwVlo/q0sYCw0duH5l4v62y/66kF4pQpeIm6a/UTQnRsXsEdKNHjw5du3YNVarkpp1QMIbAi6qhZ5xxhj02bdq00L59e0sP7dWrV+jSpUs44IADwsyZM8O6detChw4dAnnvpJi2bds2HH744eHRRx8N3bt3D7Vr17Y9hX/84x9toFvU/yf/nZdeeinMmzcvDBs2zIK94cOHh/POy63MRwor6a1gfyF7F/ldSJ0hzZXA8ZhjjrE/T8bqZM+ePe329NAdV/Iil79d92Msl58ve/aQPDtygqV6cnFft3qd7eH6xYmdwuqVq211iY/u9EmvFfl34zLVrBbuXWav8Oqz+VczquxbJfQfcJZtMCd1qzil6nwaNjvU0jX5gmOVkD04pCfyJciKxJrv14acA3NCs7bNwuSxkwstr17Qf7aTUb9o/uLwzvR37cYeLIrdULK7eZtmib+1xYp24PCWjQJpbaQvW1nwQw+0/YbHJr5kKfbxr68W2fkW9vcpIHHt7VfbeX/y/qehZuILnNncFUu+DX9/+U1LJeN24ll9wp8uuDGsTjxve0ol3u87a1deL1DRkuC2TacjbXBCyhGv14n9jw89Tukenh89yf5dKlQqv9NFdH6y/6ei/Wv+oqTX6IfQLfFvTLoh/8bslphayGtEsMBrxB6pTolgO36Nivr77Cc8KDFo3rtMaUvBanPskbb6NPeT3OqWXU7oHPYuXTpMfja3SmtxKc5zYxWg1TEtbeWpQsUKdk5Lv1lm+6caJl67wxKfraM6tcn3+hWH3fH6gGv8JdddECY+8WJYlNTG4eT+J4TjTu0RJoyeGL0HKyTeg0UPckuRM/wzrPlutX1m+LeqVqOafWbGj3gu32eG3zf+zPOZAZ/5ov4u/+Z9E79vz1P5zOT+vrQX4fclOMu9xq0JOQflhOZtm1qV0OQguDA7+vwky/9arU/8W//CXhMyMEJisDh1Uu4kYuOCr1XDxGu1V+5rNf3F1/Peb63t/dbS3m+sWi1JvN84bpH43avXrB7qNcgJR7RrGV6dMC18uyx/0FmU1nvsWtrpxu/WWgEZqm2Wq1E15HRpHj4f8UooU6WCrQ5uXL0+1DzqsNDmxrPCl2PfsM9HxQOqhXWLc3+/escdGX5Y8X2oUGufUOcXzcPi1z4Oq+f996n+H4WfV6sgFe83JhpeT3zHvPXK23Y7/qze4foLbrLvGCYHr7n9Knuc+3wvMRmxoz26/S89ITpKndlzv7TbWzNm2n5D3nuVEu+rVClVfuskYLoZfOs90VHxum7ggOhI0lVGBYasCLIaOH/+fFsBJO2SYI9UzYULF+YFhnzYX3zxxVC1alV7/OOPPw7169e39hLjx48P+++/v/03KDJDwFcwMGQPIu0qCABbtGhR6P8n2GPICh//PR5j32IcDJLOGh9XrFjR7vO8xYsXW9DIHsXCAsNkj975WHRUNCZoCEKYnaufGIC+/tKb4bOZs22DPv2EKP/N/sDKicFBKypuJganzwwfZwP6ov5ujNSQD9/6yP4bySgnTqoIeweKW6rOh6p3rTu0CvUbJt4HiQHTuAfH20DpmwX/DrXq1QqNWx0e6h6cY5VLZ8/83P7OjmwvMEzGbHnlqomggGqAid93zPCxeUHa8af3Cl98+s9EQLcxLPjnAts/w2Cb85w8/lUbXBT192vl1LJCDysSAyNWKLmx36Pg7Dyrvm9Pm2Eprdvz3wSGu/J6oetJXezffk1ikJpzUB0b5PGa9EwMyCmawQoqPbFoETNn1s6Vwd6ZgW3yv3HVfapYS4b4NToh6TVitrxN4jUijY0g4uXxr2zzGhX8+6yEsGLbIPE6rPr2+zDxyRespQBIvaMKZnJAUtx29dzYu3fmpafZZ55qsgceWs8CAAaLPfp1C01bNbbXry6vH6sMC7ftkbarUvn6EETyd8aNnBBIR431PrWnVS0lpZnPFqskn2/nPfhzA8Otn5mOVozo9UTw+tn7s+1zULVa0mcm8ftSJZkJBT7z+a9x+f8uCApzPzO5v2/ZxO/LZ4ZVH9pYNEm8TqSQvvbC3/Nd54uyM5+fZPZvnfid+Tetmvj55LCk1+qM3vlfq8T5bft+q2DvN1IYSyeCRK4rvN9oacH1kvcf14S3Xn07vPfGz19p39XAkH+ONfOXhnq9jgz7NMwJC156Lyx//8tQvdXBoWy1StbTMKdLS3tqqcTvWvWQA0LVBrWsSA37EenpWOfYpqHqwbWt8My8Z//Bso09/7/xcwPDVL3fkvEd8860d+07huI0pJoi/l6i1/GOvn92R2D4wivTwqzPPg9VKlUMCxYtDtWr7RtyDqgV/WnxS+fA8K+3Do2OipcCw/SXcX0MSdWkOiiFYtjjR7B11FFHhRkzZtj+PXDKrPK99957dsxK35/+9CcbXLJKSM9CVhDRqVOn0K5dO1tdZLWPFTuCRIrQ0GeQfYaF/X9eeOGFFvDdfPPNNpigIA2rgnEcPmjQINtTGCMYZCWTv7vffvuFnJwc25u4PT+3wb2UjJ1pcO/Bf9vgPl3tbIN7kV2xMw3uPdiVBvfpqDga3KeTnWlw78Hu6GO4u6VzH8PKFVLzu61e9/NbuUnJyLjAMJsoMExvCgzTmwJD2Z0UGKY3BYbpTYHh7lUpRYHhGgWGaS+zvqlEREREROS/xppRKm6S/hQYioiIiIiIZDkFhiIiIiIiYiiel4qbpD8FhiIiIiIiYgpLAy2Om6Q/BYYiIiIiIiJZToGhiIiIiIiYwlb7iuMm6U+BoYiIiIiISJZTYCgiIiIiImZLiv4n6U+BoYiIiIiImMLSQIvjJulPgaGIiIiIiEiWU2AoIiIiIiKmsNW+4rhJ+lNgKCIiIiIikuX2SETwCuGdGvjr66Oj1FqwYEGoV69edM+/3XU+m7f8JzpKrYULFoa69epG91Jnrz12zzzS7np9Nm35KTpKrQWJ16febnh9dqdMO6fdcT6lduM87MLEZ6huij9Du+v6hoULE+dTN7Xn03OPatFR6u2Oa/aUsCo6Sr3d8X67Zehl0VHq7bbv1Mo1o6P00/ekc6Oj4jXhuUejI0lbBIYi2zNw4MDoKDPofNKbzif96TVKbzqf9KbzSW+Zdj4iO0OppLJDf/vb36KjzKDzSW86n/Sn1yi96XzSm84nvWXa+YjsDAWGIiIiIiIiWU6BoexQJu0vhM4nvel80p9eo/Sm80lvOp/0lmnnI7IzSt2UEB2LFKpq1arh4IMPju75p/NJbzqf9KfXKL3pfNKbzie9Zdr5iOwMVSUVERERERHJckolFRERERERyXIKDEVERCRtfP7559HRVoU95sXbb78dHW1V2GMiIiVNqaSyjQ0bNoQ5c+aEH3/8MbRt2zasWbMmrFq1KtSt67+h9U8//RRKlSoV3ZN08cYbb4ScnJxwwAEHhL333jt61K9///vf0dFWnFelSpVCmTJlokckHWTCNWHjxo1hwYIF4Ycffgj/+c/WxvMtWrSIjnw577zzwogRI6J7uX7961+HkSNHRvd84LXg/fWLX/wiTJs2LXo0hE2bNoVu3bqFt956K3rEl0wZI3z11VfRUeEOOuig6EgkeygwlG3Qw2f69OlhxowZ9pMBx4MPPhj+8pe/RM/why+tWbNmhbVr14Y+ffqE1atX23k1bdo0eoYv69atCx9//LF9QXfq1MnOZ+nSpeGQQw6JnuHLxRdfHA499FD7/QkOGWBUr149+lN/7r77bnvP7bfffnZ/xYoVoU6dOnb/yCOPtGNvVq5cGb744ouwfv36kPy10aVLl+jIl0y6Jrz00kvhvffeswAxOTAcPHhwdOTD119/ba/BhRdeGB566KHo0RA2b94cbrzxxvDmm29Gj/gwd+5cW+m86qqrwp133pn3uSEwJPB9+eWX7b43mTJGGDJkiP3kGvDdd9+FmjVr2n2+S/fdd197z4lkGwWGsg0Gen/+85/DZZddFj766COb8WzZsqUFIl4xyCB15/XXXw9ffvllmD9/frj22mvD008/HT3Dl7Fjx4a///3vdj68Lgyo+JL7v//7v+gZvrDCNmXKFFs5ZFWtRo0a9p4jQGTW1tsqIoEGK4OtW7e2+++//74N2gkMOSc+X97w3iKQioMPvjr22GOPMGrUqOgZvmTSNYFVm0svvdQqKe6559YdIsccc0x05MPEiRPD888/b8EGq2wxAqlmzZpZgOUJ58Nt5syZdi2Ih1vly5cPPXr0CL1797b73mTKGOGpp56yn+PHjw9VqlTJ+7xwXWA19PHHH7f7IlmFwFAkWWKQsWXDhg1bWrRoYfdXrly5JfGlZsdetWnTZsvy5cvzzglNmjSJjvxp167dlrlz52bM+eD777/f8sknn2wZPHjwllatWm3p27fvlkGDBm154YUXomf4kRjUblm1alV0b4sdd+/efcvq1au3NG3aNHrUF95fiQB3y3fffWfnEd+8yqRrAu+tpUuXRvf8WrdunZ3HkCFDtixZsmTLwoULt3z99df22Pr166Nn+TNp0iT7Hl20aNGWf/3rX3k3rzJtjNC+ffsta9euje5tseMOHTpE90Syi4rPyDYSg/IwdepUSxljD8SYMWNCYhAV/alP5cqVy9tHxGrHvHnzQuXKle2+R4nPrqVcxlhxq1ChQnTPH1ZtXnzxRZu5Zd/HRRddFG677TZL6/OYwkzqG2mXicGf3ThmBpqVgrJly0bP8oWVTj5HfH6Sb15l0jWBlWhWdEkpJT0xvnnD52P//fcPp556avjggw8sPZZbfH3wims117bnnnsuPPvss3k3rzJtjEB2B6uEXKe5vfPOO9oLLllLDe5lG4cddpilKpIewt6Bb775xlKsaPrq1cKFC22PFClKBx54oA0yGjVqFDp27Bg9wxf2rpDSx0CQ14s9HwyoKGjgEcEfgwxSlC655BIbZFSrVs3Ojf0eHTp0iJ7pA0Egr8m3335re4xIk+XcSIdbtGiRy315DM4ZPLG/ldTLeBDFOXmUSdcE0l+ZgCDVl3S+Dz/80I4JsDwaNGiQpcovW7bMXie+h7j16tUreoYvTHSRds01jbT4vfbay34SYHmUaWMEJlpJYea7hus114TTTz89NG7cOHqGSPbQHkPZBqtPzKAzgAWznaxyeK6oSGEJ9hSxH4K3PPsh+LLmnDxasmRJuP/++8Onn35qK4W8Ruy/ITj0JK4Kx/nEG/+Tea0Kx+oTAybOj/fb4YcfbvtXGBx69ac//Sk6ys9rUapMuyawD4+gncF6jEDEIzIFWInynNWRjIkuJla8ZgsUhoJa//znP22swPcPwa7Holp89lnJbd68efjss8/ssSZNmqgiqWQtBYayjUysqMjgj9m/uIgJgyi+BFo4LefO70/gzuvEQJC0OPCF5klcFa4of/jDH6IjX26//XZbhapVq5YNmvjpPTWJ9xwrhKyygaCDKrLeCgPFmFQpiHOhCEVhkxTpjFW1Tz75xCYkuBZwXaCq4gUXXBA9wxeKsvzxj38MtWvXzldMx+tg/cQTTwynnXaaXROSz8dr+iUr0hTUITMiOZ38d7/7XXTkS9euXcO4ceNcZ0WJFBcFhrKNTKyoeNJJJ1mFsXgfHuWp+/fvb/s+PCJNkS9nvpiTVwhuvvnm6MiHuCpcUUjn8YjzorQ+l9cGDRrYgJZg4+ijj46e4Q+pfaRbfv/993afQRSpfccee6zd94aKilwHCNpBpgSvEYE8FTE9pZGxmkswOGHCBOv3xzWb1enJkydHz/CF12bx4sX2HZQ88eB1ooj0eLIHaMmTfD533XVXdOTL8ccfb+mkXNfiQJf3GyvuHhG0U9mXVcPknqZer20iu0KBoWyD/U8ETPHsGf19fvWrX9mMWrt27Vy2rWBlkCIGySuGrH6ykujRUUcdZb2+6tWrl28GOrnEuwescBA4FbZ6A28roAWxF5T9X3x2WImiHYdXxx13XDj77LPz3mPsw6FVhdfg48wzz7Tsh3j/KqmL7JWi5QPNu5944gl73AMGtFzfWIGiaAvnQW9QrwVbipow8jpRlGnXt0xLjWUyhYkItmJwTgyLCXQffvjh6Bki2UOBoWyDWTJS4ZJn0q+55powbdo0W/F499137XFP+vXrZxd/ZmzBgH3kyJG2t8CjE044Idx33332RZY8w+ktrY9Kir/5zW/C9ddfHz2Sn7cV0Bh9JRmcU8yAlQICYF6ne++9N3qGPxTKePXVVy1FEaSUUuyIlDKP2PNJcBun+G7YsCF07tzZVnopqFPUYD4dUTCHKpGs5Fx33XVW3fPyyy+36ooeUeSoMF5X3JMrxJJ6ybCL6wGTLR5lWmosRY5AZlRyBg4TryLZRoGhbOOBBx6wVUEKZoCZ6IoVK4Y777zTBuoei00Q1BIINmzY0O6zInD++efbQNCje+65x4IPBrdxMMgMJ1/YnjDJwGCC16cw3lZAY3xWCAbBKjuvU+nSpW3PlFekiVGghckVvjY4P1anhg8fHj3DF/axsapGejyo6jls2DBrSN6zZ08Lgr249dZbw4ABA+x357PEqgcBvMe0f/z2t7+16xkYqDM5SQDitcXDL3/5y7zzoZUN+8PZBkDlWI8yLTWWCTxqDvCT1+mHH36wMY/Xqr4iu0KBoWyDtwR72BgYsepRo0YNm1Wnr5xnVIlk7w0ztqRe5eTk5BVt8YYKpPPnzw/77LNP3oCDn1RZ9Ih0ZSrc8YWcfEnyuseDFEtSFBlckKLEjUCKwbtXDAQpTJW8x/CKK66wVQOPuL499thjlk7Ke47XiFRZVt9IZSTDwBOqrLKKSxEaAkMmvagU6RHtUGKk/f/jH/+w1U+v17eCOJcRI0aEBx98MHrEl0xLjSVDavbs2db+iVV3WlYwEeE59V/kv6XAUPJQ6jwexDKjyZczA1z24rDiwQy7VwRRrBISeCRXUTvllFOiI1/YM0kaHIFhJmCAxGCjYJU7j3s86F3IZ4gWHLzvKAjC60R6Ir2+vOFaQPBEYAj6TYJ0RXgu684KAfuMWcVh9YNVNo8tHnifvfbaa/kqxjKp4jVoJxiMMURhMoIBu9fUWFY8kzERxsSDt/NhHy4ZEMmpscm8psaSCcGeSSbzKOrGdxGZUTTuF8k2CgwlDylhpFPwJUx1Pi6SVIcjZdG7K6+80lLF2JOXvCfC654vUkZJ56GCYvL5eJ2xpW8ZQWD9+vXzVkDhrS8jq1AEUKxO834jHZu9oDzmtV0Fk0NU8C2qtYjXSpGZ1OKBDAIm9uJCOuyTZLWalRCPmEzhOhAPT8hcIfB95pln7L43bM9IxsQRK7xDhw6NHvGBFiJkDiWnxoLXifsU2vKIvausDnbv3t2uc6y4s9VkxowZ0TNEsocCQ8nDXi/Sw0inYnWDoIPH4pUCzzKtYfKll15qA1tep+R0Ma/FWvgSpgcWLVGSA924AJIXVLplTxRVfE8++WRbsaHKJSs6XlF1lD13999/f17hmRjBFMWDPMqkFg9cB1h9ildxWdWlcrHHCtIgOI8DQ4q0sJ2BYifxvndv2BMe43yY8OrRo4dVKvYkeSW3MN6Kn8Uo2HTDDTfYJBhppLS14jNE6rxItlFgKHmoBMesGWkUFMmgjcCNN95o+w1ZQaxevXr0TH8yrWEyBSZIuaQPG1gd4Ly8Fmt59NFHbX8HaUoUaYkRAHvCHig+R7weBIQEhpwDRXYYDHrd8wUyCijWkqywx7zIpBYP9JMkKyIupMOkEYVAvLar4NrGqjtp2Yh76CZfuz0hRZ7VaSYiwAQL2R3e2j0UXMlNxuPeip+xyk41YiZUyOjgfUe/Vj4/TIYx7hHJNgoMZRt8iTH7TM49pegbNWpkX8peVwaQaQ2TGTAxqE0eaHBuHvdHgfYbTEQkD/4YaLCK6A2XVAaBfH4ICBngsnpI6XNvAyfwHmPvGr87VS9j7MtjZZQ9OR5lUosHBuy03onb8VDIiWCRlD+PCNQJauNCR+zRZf/aEUccYfe9eeGFF+y2Zs0au66RucLr06dPn+gZPiSv5BbE496KAz3//PMW/NHcPhnZRXzH8r0kkm0UGMp28UXGRZKVRI9tKmJxw2TS/JL7/nltmEz/P2Y2WfHkI0zwwUDX2wpbjN+dgWClSpWiR3yiDxYz0PF58H5jcoVzI1j0WG6fzz971tiPmxyoc66kyD7yyCPRI75kWosH9kpSWZHrAatRpMZ6DQwpCkb2QJcuXew+hbb4Dho3bpzd94ZCQPRqjdsjsV9y0KBBdg33ignkgsXcvE1MkmFDdVj2tiej8B7ZA0wciWQbBYaSFVj1oGcUqZfM0rLxn2CKvYceMXM+adIk2wcKVkNZ+WCm3SNW1Lp27RoOO+ywfOli3tpVxJViqRqbjEE6M9DsK/KG1PI4qO3Xr1/0aLCCLaRheu3NmLxfinMkrYzzSU5l9ozVd1LiPOLzw4QEe73Afi8qY1NB1iPeV3x+kq/XfJbIKPCIfXhcEwoGht5avLBnlcmUwmzvz0Qymc+EfZGdNH78eOtZRt81MEi/5ZZb7Ngj9rCtWLHCzoMbx/EgyiNW2EjrYa/h6NGj7bXipzd33HFHofsICXa9VsBl9YmVdfassS+PVWpm2CkIwuSKV6zisgLF+47VNqrIsnJICnCcwuiZ5zlf3nOkxtK/kBvHXifxQEbEk08+aYWN2LNPBktcQdajv/71r9aygorltLPhRrDrDenjhU2e8JjXHsciu0orhpIV2EPAQLBbt255e6IYaDDr6RGDdAblDNTBedCw//e//73d92bZsmX2k/RE0i9j7MvzZHuzzI0bN7Z2MF4xoGX/HauirOwyGGR1zWN6LFjFIYinQBBfgwxy2TfJnmpS/s4999zomemLlc6icK0r2D/PC7I7uMYxAcZrw4ohxXW8BofLly+3Qk300gXvsQsvvNBdO54Yff8osuWteE5BTA7znUOhGSqygx6TXOu4NpD+K5JtFBhKVujUqZPNOrOngD1f7I0655xzLF3JI/Z3MGNLSg8ISPhy8/pFTaNxgiZ+UsSAFCUGhaeeemr0DB8YMDGoKDjgI/AljdRroRbwGaLFA6vu9CtjdY3A5MEHH4ye4QvtDyg+FRc04bWhPP3AgQPDWWedZcWd0t32Bq7sj2K1zSOCdD5DfG4YorA6zXHBvWBekALLxFBc+Iw0Zq53BVPOvWA7BvvZmYxMTv331keXIJC9xvzkPYYlS5ZYkMh1gG0BItlGgaFkBTb60z6AGUKaPtO4lvLUDHQ9mjJliqUnxfuhmPWkQIjXdhW8Jqy00bKCvZIEvAw4KDjhCYEGbV1YrYl7lJGWSON7BrZeG46DHo1xewf2tzIJQUNor02g2bNGynK874t2FQSEBFMEix6CeILz7fF6PaC1EH3l4vR49oZz7SaF0aOTTjopPP744/nOp3///rbFwSMKs9DfmMCW76A4OPTaR5frQNyjlb259AXl889En0i2UWAoWYFiM5TSZuaWtzwX/IsuushtFUwG5+yFilcIWUGkUIvXQTqvB+fDvhu+kFmJogrumDFjomf4QJsAJhuYSY9XDVkFZf8aM9OHHHKIPebR2WefbRX8CH5Jv6TkPmmkyS0sPLn22mttHxErOWAFh5RF3neshngrvZ9JSJEnnTTGNZsgJPkxT/jdmVRJXjFkosVbMR1eB9JhSYslICS7gyrMTLqSXk4BMY/69u1rLV9inGfB9jwi2ULFZySjUVQCbCYnlY+ZaAaEHHsunME+PL6QYxyzP8orAlwG6czakurLgIN0X29Y9WQvFD3XaMrNjX5lpF/Gab9e0aqCAS3nQrDLIN3rijvYQ0gPM1aluXEcV1Ukw0BKDp8bKvlSVIsbx/GKjkcUbKLwzNy5c+3GNgAmV7xhLzup4+xdJUuFCUmO+Z4lU8Ib2lLwWjARyc/kG6u6ItlIK4aS0ej3R2P+ovbieE19YbWTGWf2FoLVDgZP3vZ7sZeQgJAG46SOjRo1ygIoUq5YvWHPlyeZ3Bcr0/ZJDR482N53yQp7THY/PkOssLVu3domibi2tWrVKpx//vnRM3wh5XfkyJGhYcOGdp9VN84l7mvoxRlnnBGOPvpoa3QfV+3kOk0vU4rRUHnVk7Fjx9qNSS6uY/FwmMIz7NmnDoFItlFgKBmNPlEEUPfff39eEJXM6x4cUhZvu+22vD2GDNJZDSWlxxP22NDDkJlnZqPZ20XTZ3rKUezEW6rv9qqSbu/PPMiUfVLs9eRG8/dnnnkmejTYijuDdVasvdheVVJ4KwYS43rGvtyPP/44L42UNMV4UsIb+uhS4ITPP+fDBAsFTrwVNyEV/osvvrBgPRm9DAl6+V7yhGsYRc5oJVRYEBjvExfJJgoMJePxpXXJJZe4rZ5YFEqg80XM+dWpU8dmOfnpCYFg3JSf9EtSeDxjhYN9dxQwSEYqM4GVp6CjoEzZJ0W7DVZwWOVIXoHifFj9GDp0aPRI+ttROX2vGRGZVlyL/aoUNkpeZWN1jZU3T1i1pe9nwe8ZWteccMIJeddyL2hh1bt3b5vwKgyvmUi2UWAoWYFBOSlitWvXDqVKlYoeDaFWrVrRkS8UaCHIYKWNwDDGPjBPKDoTV39MPvYqk/ti9evXz/bgHXrooXafvVKkx9EGxhP2rlJR8eqrrw7/+7//Gz0abNBOnzxWELzI1KqkmVhci6ApXmlj2OWl8m0yrl9MDLF6m3x9I0Wefe5c/zy57777wmWXXVbkXmkKUYlkGwWGkhUImChH365du3y9/qg+6BEtHagCR1GDuFQ4gw72HnpC6itpPLj88svzjmOsInqSyX2xMmWfFJhM+dWvfmX9GJP7sHnFZAT7WNesWZNvooj9YB6xMsX7LbnlC0Gu1xV3WqM88cQToV69enafwmenn356eOedd+y+F99++63tw6XKd/L1jQrFXN+qVatmj3lB4Zzt8TpxLLIrFBhKVrjnnnuio60IpLytsMUKzqh7RUlwzoHLEINbekuC+7w+DNw9Yr9kXPU27ovlHYWCaLsR7/uipQBtOeL0OG/IIuDzTx9DVnNjTLZ4w4o0xT9ee+01mzAitY80TNKaPcqU4lqxm266ya5nnBNIySaA//Of/2z3veEaQHo81wGub1wLPHrggQfsJ6ud7AOlGi6ohEuQ63V8ILIrFBhKVqCYCV9mfAFQ1IQZT0rue+0rR0B12mmnWcnz5BUPAkaRVBg3blx0lNsuhX1SpF2eeuqp0aO+DBgwwMrs85lJnmChT6M3XNNIh6OVCJMprLZRmMZrIFVYcS3OLe456Q0rnrwWVL8kQKQoENdwgngpOfGE8SuvvGLvtfj7k8AdXidWRHaFAkPJCpSkptolq2wEiF9//XUYMmSItbPwiGI67JNiv1dypb677rorOhIpXqT6xljdpTohlTzpAejRU089ZT85Bwbr8d5jUvy8YSWKwSwD20mTJlmg2717d7d78sDkA9dptgDw+pD253USAgy1KBi2ePFiuzEpweSElDzSlKmuHKf6r1y50q4DrMSLZBsFhpIV2rdvb72x2FcUb/in0AQpfx4VVabea3l68YeBLfuKvKb7sh+PawGrOQQe7JOiSIi3Fik4++yz7frGaidZBJwLqx0TJ06MnuEHASHZHARPBIVM5rE6zY0+p96wL49zYS8ehY8mTJhgzfr5/rn22mujZ0lJorARK9SklYPXi9eG1GyRbKPAULICRWdIFyFAZDDI7DN7jLxt/t9ROwdvxVrED1aoY3xtEFD95je/cfcZitEu4KWXXsrb10q6ItVkaeLtDauFpFmyIkXKIkEUqeZt27aNnuEDlTu5NhNAUUyHIk60FCA1lkkvAnhP6MXI54b9xuzPZc8klTB5LH7fSckbPny4FTaK32PsaWWS6OKLL46eIZI9FBhKVmAmnQp9NIGn2T3BITO5zBJ6QlPuwgZHfIx53OvqjaQ/Uq+TMYCn2b23EvUxgqaHH37YVm5A9gB95TymX5LaS/BBgaDkqqT0nvSEXnhkQ1B1OQ5sGzRoYIGiR6T4sgJKpsrJJ59sq7lUYvZ6PpmMyYd3333XCtCw9/Ooo47KV5RKJFsoMJSsQBoPASGDDgazpIxcddVVYf/994+eISLbE+/JA/vx+OxQhj8uEOINE0WkJsbNukkfO+ecc6y6pzesfLJqSICYHBjSWsATqkCS4ktLFKrDcp1mrxfFaDyusNHYnvcTRZoICAkMaZFEAMLnR4FHeqDCKp8fJleuvPJK22P40Ucfue0DKrIrFBhKVoiLZbBnhbc8Aw4Kt3gd1IrsLgxit8drJVxaBVB4hlL7XBNYMaTCL60FvGFljYCD4CO5SjGBuze02qBQWFzUiBVc9rLSU46tAN7E7y32SvJZIvhg9ZCehlQmlZJHRV8ql7NVY+7cuTZOIDvnzTffjJ4hkj0UGEpWYK8HFcZoUxEXmujWrZtV7hORotEmgM8MqaO0e4kLNDB4oochjbs9Wrt2re0znD17tg3e2V/E6hSrO9706NEjjB49OuMyINhnSJD41ltv2XvwkUceif7EJ9JK2ctGkEhfxjFjxkR/IiXpiCOOsKCd1F+2mXA9oPes1+J0IrtCgaFkBfp8MaPOT1BtjFYVDDpEpGhxBdw77rjDimfEnyEGtwzchw0bZve9yMQV0DPPPNN6sjKwTV4xzJRiVAxTKAiSSVWXyWJRxkp66NWrl/U0ZCV36tSpVhzof/7nf2xCWSTbKDCUrMCM+siRIy0dCax+XHjhhVbxTkR2jGIMFGgoX7683afyJXtwvFUl7dChg6101q5dO69vWTKPvUBJe/vxxx+tp2ncj1HFqER+HsYGFKN75plnwkUXXWT7DUlbpg2MSLZRYChZgcbIbPxnUAhSkyg2EZemV5sHke075ZRTQt++fa0oCGg+Tq+8cePG2X0vWF3ja4/9eDVr1rT0S9Jj4/6FXlel6P3H4BbVqlULNWrUsGMRKRrXAjKHSJOPexzTqoJtJkyuiGQbBYaSFeIZ9Xg2nb0eZcuWtWPNrIvsGD3mhg4dmrcHj2INl19+ue3P8YSqnVQcZDBIyhgrh5So79q1q00eefT5559bn1b6/oEG6pxPo0aN7L43tHPIycmxqp2zZs2ynpmcS/Xq1aNn+EH/Qs6HPa1gAoL3WVwNV0oWQ2D6HJNCSiaBSLZTYChZgXLUdevWje7lfhlQAp3KpCJStHnz5lkvOfA5YlIFDGz5M3p+eUNwyAobFSInT55s7R7odcqqqEfnnXeepcl37tzZ7rOHmuJAI0aMsPveXH311WHQoEEWTNFWiBRZqscOGDAgeoYPVFilZQUTELThAIXP+Dydf/75Cg7TBJ97emiyTzeePIbXissiu0KBoWQFGtlTNIPBBZv+SRmZMmVKuPnmm6NniEhhqEp699132zF98a677jo7Bg3haRLvCauFpFwS5FI8h6bwtHtghY0UTI+ooMi+qLjXH9kRDGo//vhju+8N12lWCqm0yh5WAkUKg7Bq7QnBLcEhK+sEgwy3mEyhpy7pyzfccEP0TCkJZD2QQko7lHiimEwirg/8fPDBB6NnimQPBYaSFaioyIWfGXW+DOiR1bFjR5tpF5GikSoaD8iTj1HwvgddunSx/cWtWrWyPcf0k0vmcb9xv379rDl//fr17T77Pwmqxo8fb/e94XW5/fbbrVLkb3/7Wyt8RKDr7b3WunVrW40u2EZk2bJlVgmTlhVScp5//nnbZ1yhQoXokVz0LyQ4pL+hSLZRYChZgWDw3nvvtZ5rmzZtsubWpI8kp42IyLYoxJBclCE+RsH7HpAylry/OMZXodf9xrQOGT58uKXLcx4EvlRdZvLLI1ao2ZdH+uUDDzxgK6BXXnmluz6GTZs2LbIX3vb+THYPqiqTbh1PqMTIJLj44ott36FItlFgKFmBgJDUUWZwKQZAcEjVMdpYiEjRqN7JpApIiYuPwX0GUVKyVq5caXs/2ctG6iKrIKzmei2mwR5QsjrYj8fkAyts7Jls0aJF9AwfGjZsWGQ6Im0R5s6dG92TkkBf1tmzZ0f38tven4lkMgWGkhWYPb/sssts7wpveVJIJkyYEB599NHoGSJSmBNPPNFW2PjcsD833sfGfSZYnnvuObsvJWfYsGHh3HPPtdeHPoz8pNk97UU8Ym8kVWM//fRTWwklKHz55ZetYIsnvXv3zuudm4zPzpIlS9RHt4QxUUzLneTCdGD/8UknnRRmzpwZPSKSPRQYSkaLKyrSjJtS7pSmj9Gsm1QSERHPmPCiqA4tK0i9ZO80Bbfo1+rR6aefHo499lhbnf7ss8+sOin3vQ3U2etJcZN99tkneiQXK7xMthRMYZTd65ZbbrFJlJ49e4aqVavaY4wT/va3v1mrlOuvv94eE8kme0Y/RTJSnPZWvnz5MGrUKDuOPfnkk9GRiIhfrOIyCUaxGSrFHn/88TYZ5hWFwtjjVbp0abvPz7hNiidUViXQoPhM8o3A0GvF2ExCFhH7V8kceuqpp+w2cuRI++zwZyLZSIGhZDSKMsTGjh0bHeXyVuFORKQw7du3t6Bw1apV1qybgW3BaquesK91xowZtpozZ84cq+zpsecsVVVr1KgR3duK4JA/k5LFKuGQIUNsrzQta7hxTEXcgqu8ItlCqaSS0TKtoqKISDK+wmnST8oiDbobN24cli9fbhUvvabK06CfcyI45Bwo0nLppZda0OuJipuIiDcKDCWjqaKiiGQyKnjSe/GFF14Ie++9d/SoT5s3b7a9XRQ1oroqqZgMUdhDmZOT4+78VNxERLxRYCgZTRUVRSTTUX2UgjOkjyb3Zm3SpEl05AMrhZ06dbKK0YX1mOR67omKm4iINwoMRUREHCP7gb14pMfHk1+4+eaboyMfBg0aFG644QYroFNYYPjQQw9Fj/hAEHjrrbfaz3ivIW0qCBIHDhyofWwiknYUGIqIiDhG6x2qdv7www+hYsWK0aPB7R7Dt99+Oxx99NHRvVyFPeYF+z0XLFhgx6SVNmvWzI5FRNKNAkMRERHHli5daoW0li1bFs4555ywevVqW0Fs06ZN9Awf2C9JgEtAS7AbI+2/W7dubvsyioh4oXYVIiIijj3++ONh3LhxtqcNK1assFRFb+hf+OKLL4ZvvvnGWlRwHN8qV64cPUtERFJFK4YiIiKOUf2Snq20c4hb8DRt2tRSGD2ZOHGi3ajW2apVq+jREMqXLx969OgRevfuHT0iIiKpoMBQRETEsa5du4ZRo0ZZ4ES65fz588Nll11mVT49YaVzv/32syIzffr0iR7dqlatWtGRiIikglJJRUREHCMgpI8h+DlixIhw8skn231Ppk+fbj/pZ0jLioI3ERFJLQWGIiIiDlGs5auvvgodO3YMy5cvD507dw4zZswIRxxxRLj44oujZ/lBkRmSmL7++mvr/5d8489ERCS1lEoqIiLi0DvvvBMmT55sgVO5cuWsAbz3VggMSW6//fbwhz/8IXpERER2F60YioiIOERD+EqVKtmKIQ3gCai84zxY9Zw3b571ZWSlML6JiEhqacVQRETEoebNm4dZs2bZMf3/jjzyyPDBBx/Yfc8uuuiiULp06dChQ4dQpkwZe4yAkRVRERFJHQWGIiIiDh188MHh3nvvje6FcPnll+e7f9xxx0VHvlxwwQXR0VYEhlQrFRGR1FFgKCIi4hAraGXLlrVjvsrZa8gKG8cEUk8//bT9mTeLFi2KjvKrU6dOdCQiIqmgwFBERETSxtChQ6Oj3Mqr9DesUqVKuOaaa6JHRUQkFVR8RkRERNIGq57xba+99rIVxLfffjv6UxERSRWtGIqIiEjaWrt2raXNTp06NXpERERSQYGhiIiIpI133303Osr13XffhcGDB4fp06dHj4iISCooMBQREZG0ccUVV1jxHDBEYY9ht27dQv/+/e0xERFJDQWGIiIikjZYMaTa6p577hlKlSoVqlWrFipWrBjKly8fPUNERFJBxWdEREQkbSxcuDA0bNgwNGnSJDRq1ChUrlw5vPzyy9GfiohIqmjFUERERNJGq1atwowZM6wiKTZv3hzatm0bZs6cafdFRCQ1tGIoIiIiaYP00W+//Ta6F2yPIWmlIiKSWloxFBERkbRx1VVXhdq1a4fmzZvb/VmzZlkvw7vuusvui4hIaigwFBERkbSxZMmScMcdd4Rly5bZ/Zo1a4bf//73oVatWnZfRERSQ4GhiIiIpI0NGzaEOXPmWP/CNm3a2B7DVatWhbp160bPEBGRVFDSvoiIiKSN1157LTz11FPhpptuCuXKlQsrV64Mw4cPj/5URERSRYGhiIiIpI0hQ4aEPn362Coh6tSpEyZNmmTHIiKSOgoMRUREJG2sW7fOUkj32GMPu7969epQpkwZOxYRkdRRYCgiIiJpgz6GU6dODevXrw9vvfVWGDNmjAWKIiKSWio+IyIiImlj3rx5YdiwYWH27NlWcOann34KAwcODPXr14+eISIiqaDAUEREREocVUgpNkPaKMHgjBkzwjfffBMOOeSQcPjhh4e99947eqaIiKSCUklFRESkxI0fPz58//33dkyQSMGZ6dOnh8cee8xSSkVEJLUUGIqIiEiJu++++2zFEK+++qq1rTjzzDNDy5Ytw2233WaPi4hI6igwFBERkRJH+mjFihXt+LnnnrOg8JhjjglnnXWWpZSKiEhqKTAUERGRElerVq3wxhtvhPfeey98+umnoVOnTvY47Sv23FPDFRGRVNOVVkRERErc+eefH0aPHh1GjRoVOnfuHBo3bmyPs1qodhUiIqmnqqQiIiKSFubOnRtWrlxp+wrLli1rjy1evDj8+OOPoUGDBnZfRERSQ4GhiIiIiIhIllMqqYiIiIiISJZTYCgiIiIiIpLlFBiKiIiIiIhkOQWGIiIiIiIiWU6BoYiIiIiISJZTYCgiIiIiIpLlFBiKiIiIiIhkOQWGIiIiIiIiWU6BoYiIiIiISJZTYCgiIiIiIpLlFBiKiIiIiIhkOQWGIiIiIiIiWU6BoYiIiIiISJZTYCgiIiIiIpLlFBiKiIiIiIhkOQWGIiIiIiIiWU6BoYiIiIiISJZTYCgiIiIiIpLlFBiKiIiIiIhkOQWGIiIiIiIiWS2E/wdRaZ10EqGhwwAAAABJRU5ErkJggg=="
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![newplot%20%2827_3%29.png](attachment:newplot%20%2827_3%29.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3-What insights can we gain from analyzing the education status of customers in the Bank data set?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 2, 3], dtype=int64)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Bank_data['Education'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "#To create a new col with meaningful values on the Education level we can create the following funcion:\n",
    "def mark(x):\n",
    "    if x ==1:\n",
    "        return 'Undergraduate'\n",
    "    elif x ==2:\n",
    "        return 'Graduate'\n",
    "    else:\n",
    "        return 'Professional'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>Experience</th>\n",
       "      <th>Income</th>\n",
       "      <th>Family</th>\n",
       "      <th>CCAvg</th>\n",
       "      <th>Education</th>\n",
       "      <th>Mortgage</th>\n",
       "      <th>Personal Loan</th>\n",
       "      <th>Securities Account</th>\n",
       "      <th>CD Account</th>\n",
       "      <th>Online</th>\n",
       "      <th>CreditCard</th>\n",
       "      <th>Edu_mark</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>25</td>\n",
       "      <td>1.0</td>\n",
       "      <td>49</td>\n",
       "      <td>4</td>\n",
       "      <td>1.6</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Undergraduate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>45</td>\n",
       "      <td>19.0</td>\n",
       "      <td>34</td>\n",
       "      <td>3</td>\n",
       "      <td>1.5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Undergraduate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>39</td>\n",
       "      <td>15.0</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Undergraduate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>35</td>\n",
       "      <td>9.0</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "      <td>2.7</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Graduate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>35</td>\n",
       "      <td>8.0</td>\n",
       "      <td>45</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Graduate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4995</th>\n",
       "      <td>29</td>\n",
       "      <td>3.0</td>\n",
       "      <td>40</td>\n",
       "      <td>1</td>\n",
       "      <td>1.9</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Professional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4996</th>\n",
       "      <td>30</td>\n",
       "      <td>4.0</td>\n",
       "      <td>15</td>\n",
       "      <td>4</td>\n",
       "      <td>0.4</td>\n",
       "      <td>1</td>\n",
       "      <td>85</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Undergraduate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4997</th>\n",
       "      <td>63</td>\n",
       "      <td>39.0</td>\n",
       "      <td>24</td>\n",
       "      <td>2</td>\n",
       "      <td>0.3</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Professional</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4998</th>\n",
       "      <td>65</td>\n",
       "      <td>40.0</td>\n",
       "      <td>49</td>\n",
       "      <td>3</td>\n",
       "      <td>0.5</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>Graduate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4999</th>\n",
       "      <td>28</td>\n",
       "      <td>4.0</td>\n",
       "      <td>83</td>\n",
       "      <td>3</td>\n",
       "      <td>0.8</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Undergraduate</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5000 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Age  Experience  Income  Family  CCAvg  Education  Mortgage  \\\n",
       "0      25         1.0      49       4    1.6          1         0   \n",
       "1      45        19.0      34       3    1.5          1         0   \n",
       "2      39        15.0      11       1    1.0          1         0   \n",
       "3      35         9.0     100       1    2.7          2         0   \n",
       "4      35         8.0      45       4    1.0          2         0   \n",
       "...   ...         ...     ...     ...    ...        ...       ...   \n",
       "4995   29         3.0      40       1    1.9          3         0   \n",
       "4996   30         4.0      15       4    0.4          1        85   \n",
       "4997   63        39.0      24       2    0.3          3         0   \n",
       "4998   65        40.0      49       3    0.5          2         0   \n",
       "4999   28         4.0      83       3    0.8          1         0   \n",
       "\n",
       "      Personal Loan  Securities Account  CD Account  Online  CreditCard  \\\n",
       "0                 0                   1           0       0           0   \n",
       "1                 0                   1           0       0           0   \n",
       "2                 0                   0           0       0           0   \n",
       "3                 0                   0           0       0           0   \n",
       "4                 0                   0           0       0           1   \n",
       "...             ...                 ...         ...     ...         ...   \n",
       "4995              0                   0           0       1           0   \n",
       "4996              0                   0           0       1           0   \n",
       "4997              0                   0           0       0           0   \n",
       "4998              0                   0           0       1           0   \n",
       "4999              0                   0           0       1           1   \n",
       "\n",
       "           Edu_mark  \n",
       "0     Undergraduate  \n",
       "1     Undergraduate  \n",
       "2     Undergraduate  \n",
       "3          Graduate  \n",
       "4          Graduate  \n",
       "...             ...  \n",
       "4995   Professional  \n",
       "4996  Undergraduate  \n",
       "4997   Professional  \n",
       "4998       Graduate  \n",
       "4999  Undergraduate  \n",
       "\n",
       "[5000 rows x 13 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Bank_data['Edu_mark']=Bank_data['Education'].apply(mark)\n",
    "Bank_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Edu_mark</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Graduate</td>\n",
       "      <td>1403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Professional</td>\n",
       "      <td>1501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Undergraduate</td>\n",
       "      <td>2096</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Edu_mark  count\n",
       "0       Graduate   1403\n",
       "1   Professional   1501\n",
       "2  Undergraduate   2096"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "EDU_dis=Bank_data.groupby('Edu_mark')['Age'].size().reset_index(name='count')\n",
    "EDU_dis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "px.pie(data_frame=EDU_dis, names='Edu_mark' , values='count' , title='Education Level')"
   ]
  },
  {
   "attachments": {
    "newplot%20%2828%29.png": {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![newplot%20%2828%29.png](attachment:newplot%20%2828%29.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4-What are the different categories or types of account holders in the dataset, and what are their characteristics?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Age</th>\n",
       "      <th>Experience</th>\n",
       "      <th>Income</th>\n",
       "      <th>Family</th>\n",
       "      <th>CCAvg</th>\n",
       "      <th>Education</th>\n",
       "      <th>Mortgage</th>\n",
       "      <th>Personal Loan</th>\n",
       "      <th>Securities Account</th>\n",
       "      <th>CD Account</th>\n",
       "      <th>Online</th>\n",
       "      <th>CreditCard</th>\n",
       "      <th>Edu_mark</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>25</td>\n",
       "      <td>1.0</td>\n",
       "      <td>49</td>\n",
       "      <td>4</td>\n",
       "      <td>1.6</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Undergraduate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>45</td>\n",
       "      <td>19.0</td>\n",
       "      <td>34</td>\n",
       "      <td>3</td>\n",
       "      <td>1.5</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Undergraduate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>39</td>\n",
       "      <td>15.0</td>\n",
       "      <td>11</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Undergraduate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>35</td>\n",
       "      <td>9.0</td>\n",
       "      <td>100</td>\n",
       "      <td>1</td>\n",
       "      <td>2.7</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>Graduate</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>35</td>\n",
       "      <td>8.0</td>\n",
       "      <td>45</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>Graduate</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Age  Experience  Income  Family  CCAvg  Education  Mortgage  Personal Loan  \\\n",
       "0   25         1.0      49       4    1.6          1         0              0   \n",
       "1   45        19.0      34       3    1.5          1         0              0   \n",
       "2   39        15.0      11       1    1.0          1         0              0   \n",
       "3   35         9.0     100       1    2.7          2         0              0   \n",
       "4   35         8.0      45       4    1.0          2         0              0   \n",
       "\n",
       "   Securities Account  CD Account  Online  CreditCard       Edu_mark  \n",
       "0                   1           0       0           0  Undergraduate  \n",
       "1                   1           0       0           0  Undergraduate  \n",
       "2                   0           0       0           0  Undergraduate  \n",
       "3                   0           0       0           0       Graduate  \n",
       "4                   0           0       0           1       Graduate  "
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Bank_data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "#New col representing Account_holder_Category can be created based on the Securities Account and Personal Loan \n",
    "#This can be done using a np.where or a functon with if statment, a np.where will be used\n",
    "\n",
    "Bank_data['Account_holder_Category'] = np.where((Bank_data['Securities Account'] == 1) & (Bank_data['CD Account'] == 1),\n",
    "                                        'Hold Securities and Deposits',\n",
    "                        np.where((Bank_data['Securities Account'] == 0) & (Bank_data['CD Account'] == 0),\n",
    "                                                 'Does not Hold Securities and Deposits',\n",
    "                        np.where((Bank_data['Securities Account'] == 1) & (Bank_data['CD Account'] == 0),\n",
    "                                                          'Hold Securities and No Deposits',\n",
    "                                                          'Hold Deposits only')))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Hold Securities and No Deposits',\n",
       "       'Does not Hold Securities and Deposits', 'Hold Deposits only',\n",
       "       'Hold Securities and Deposits'], dtype=object)"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Bank_data['Account_holder_Category'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "px.pie(data_frame=Bank_data.groupby('Account_holder_Category').size().reset_index(name='count'),\n",
    "       names='Account_holder_Category', values='count')"
   ]
  },
  {
   "attachments": {
    "newplot%20%2829%29.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![newplot%20%2829%29.png](attachment:newplot%20%2829%29.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 5-Does age play a role in determining the availability of loans, and can we examine the relationship between age and loan availability in the context of other variables in the dataset, such as income, education level, or account type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Thsi could be approached using statistical analysis, such as a t-test or correlation analysis\n",
    "#t-test will be used to determine if there is a significant relationship between age and loan availability.\n",
    "#to use these statistical analysis we need to import scipy library as follows:\n",
    "import scipy.stats as stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "#first we can see how the scatter plot looks like\n",
    "px.scatter(Bank_data[['Age', 'Personal Loan']] , x='Age', y= 'Personal Loan')"
   ]
  },
  {
   "attachments": {
    "newplot%20%2830%29.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![newplot%20%2830%29.png](attachment:newplot%20%2830%29.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "#The hypothesis as follows:\n",
    "H0='Age has no impact on the personal loan'\n",
    "H1='Age has impact on the personal loan'\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Creat numpy array for each situation\n",
    "Age_PL0=np.array(Bank_data[Bank_data['Personal Loan']==0]['Age'])\n",
    "Age_PL1=np.array(Bank_data[Bank_data['Personal Loan']==1]['Age'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Age has no impact on the personal loan as the p value greater than 0.05 with value of 0.58\n"
     ]
    }
   ],
   "source": [
    "#Apply the ttest for the two arrays\n",
    "t,p_value = stats.ttest_ind(Age_PL0,Age_PL1, axis=0)\n",
    "if p_value<0.05:\n",
    "    print(H1 + ' as the p value less than 0.05 with value of {:.2f}'.format(p_value))\n",
    "else:\n",
    "    print(H0 + ' as the p value greater than 0.05 with value of {:.2f}'.format(p_value))\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "#To better use this test with other values than th age, a function must be created \n",
    "def Hypothesis (df,parameter):\n",
    "    arr1=np.array(df[df['Personal Loan']==0][parameter])\n",
    "    arr2=np.array(df[df['Personal Loan']==1][parameter])\n",
    "    t,p_value = stats.ttest_ind(arr1,arr2, axis=0)\n",
    "    if p_value<0.05:\n",
    "        print('The {} has impact on the personal loan as the p value less than 0.05 with value of {}'.format(parameter,p_value))\n",
    "    else:\n",
    "        print('The {} has no impact on the personal loan as the p value is greater than 0.05 with a value of {}'.format(parameter, p_value))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The Age has no impact on the personal loan as the p value is greater than 0.05 with a value of 0.584959263705325\n"
     ]
    }
   ],
   "source": [
    "Hypothesis (Bank_data,'Age')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The Family has impact on the personal loan as the p value less than 0.05 with value of 1.4099040685673807e-05\n"
     ]
    }
   ],
   "source": [
    "Hypothesis (Bank_data,'Family')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The Experience has no impact on the personal loan as the p value is greater than 0.05 with a value of 0.3207536024015185\n"
     ]
    }
   ],
   "source": [
    "Hypothesis (Bank_data,'Experience')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The Education has impact on the personal loan as the p value less than 0.05 with value of 2.70966319357669e-22\n"
     ]
    }
   ],
   "source": [
    "Hypothesis (Bank_data,'Education')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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