{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "b4fe0f1c",
   "metadata": {},
   "source": [
    "# Lab 10: Models of binary data and logistic regression"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7de8f9d1",
   "metadata": {},
   "source": [
    "## Learning goals\n",
    "\n",
    "- Understand the advantages and disadvantages of a linear probability model. \n",
    "- Understand the form of a logistic regression, and how it differs from a standard linear regression. \n",
    "- Be able to interpret the results of a logistic regression. \n",
    "- How to visualize the results of a logistic regression\n",
    "\n",
    "\n",
    "## Literature\n",
    "- ROS Ch. 13 (not 13.3, 13.5 and 13.6) and 14"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e580b02",
   "metadata": {},
   "source": [
    "Many events and decisions in life are binary: pass/fail, get the job or not, going bankrupt or not. In this lab, we will look in some detail at models to evaluate such data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "474d8313",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import scipy.stats as spt\n",
    "\n",
    "import statsmodels.api as sm\n",
    "import statsmodels.formula.api as smf\n",
    "import seaborn as sns\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f66d32b2",
   "metadata": {},
   "outputs": [],
   "source": [
    "from cycler import cycler\n",
    "\n",
    "plt.rcParams['xtick.labelsize'] = 12\n",
    "plt.rcParams['ytick.labelsize'] = 12\n",
    "plt.rcParams[\"axes.labelsize\"]= 12\n",
    "plt.rcParams[\"figure.facecolor\"] = \"#f2f2f2\"\n",
    "#plt.rcParams['figure.savefig.dpi'] = 100\n",
    "plt.rcParams['savefig.edgecolor'] = \"#f2f2f2\"\n",
    "plt.rcParams['savefig.facecolor'] =\"#f2f2f2\"\n",
    "plt.rcParams[\"figure.figsize\"] = [16,10]\n",
    "plt.rcParams['savefig.bbox'] = \"tight\"\n",
    "plt.rcParams['font.size'] = 14\n",
    "greens = ['#66c2a4','#41ae76','#238b45','#006d2c','#00441b']\n",
    "multi =['#66c2a4','#1f78b4','#a6cee3','#b2df8a','#33a02c','#fb9a99','#e31a1c','#fdbf6f']\n",
    "plt.rcParams[\"axes.prop_cycle\"] = cycler(color=multi)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c5b2b9d1",
   "metadata": {},
   "source": [
    "### Voting"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "898575bc",
   "metadata": {},
   "source": [
    "<iframe src=\"https://ntnu.cloud.panopto.eu/Panopto/Pages/Embed.aspx?id=0fc99329-2583-4093-8838-af0900c9ba86&autoplay=false&offerviewer=true&showtitle=true&showbrand=true&captions=false&interactivity=all\" height=\"405\" width=\"720\" style=\"border: 1px solid #464646;\" allowfullscreen allow=\"autoplay\"></iframe>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6bd2520b",
   "metadata": {},
   "source": [
    "We start by loading in data on a US election survey from 1992 and voter characteristics, that has been downloaded from the ROS website"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "15d868b4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>year</th>\n",
       "      <th>resid</th>\n",
       "      <th>weight1</th>\n",
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       "      <th>...</th>\n",
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       "      <th>year_new</th>\n",
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       "      <th>age_discrete</th>\n",
       "      <th>race_adj</th>\n",
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       "      <td>538</td>\n",
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       "      <td>1.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1.0000</td>\n",
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       "      <td>-2.0</td>\n",
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       "      <td>-1.952455</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>539</td>\n",
       "      <td>1952</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>63</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>540</td>\n",
       "      <td>1952</td>\n",
       "      <td>5</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>66</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
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       "      <td>2.047545</td>\n",
       "      <td>1.0</td>\n",
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       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <th>34903</th>\n",
       "      <td>39982</td>\n",
       "      <td>2000</td>\n",
       "      <td>1804</td>\n",
       "      <td>1.0454</td>\n",
       "      <td>1.0454</td>\n",
       "      <td>1.0454</td>\n",
       "      <td>51</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>34904</th>\n",
       "      <td>39983</td>\n",
       "      <td>2000</td>\n",
       "      <td>1805</td>\n",
       "      <td>1.0454</td>\n",
       "      <td>1.0454</td>\n",
       "      <td>1.0454</td>\n",
       "      <td>52</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>...</td>\n",
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       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>-1</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34905</th>\n",
       "      <td>39984</td>\n",
       "      <td>2000</td>\n",
       "      <td>1808</td>\n",
       "      <td>2.0407</td>\n",
       "      <td>2.0407</td>\n",
       "      <td>2.0407</td>\n",
       "      <td>23</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>34906</th>\n",
       "      <td>39985</td>\n",
       "      <td>2000</td>\n",
       "      <td>1809</td>\n",
       "      <td>0.3717</td>\n",
       "      <td>0.3717</td>\n",
       "      <td>0.3717</td>\n",
       "      <td>36</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
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       "      <td>-0.952455</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>34907</th>\n",
       "      <td>39986</td>\n",
       "      <td>2000</td>\n",
       "      <td>1810</td>\n",
       "      <td>1.5601</td>\n",
       "      <td>1.5601</td>\n",
       "      <td>1.5601</td>\n",
       "      <td>73</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>24</td>\n",
       "      <td>-2</td>\n",
       "      <td>2.747545</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
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       "</table>\n",
       "<p>34908 rows × 71 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Unnamed: 0  year  resid  weight1  weight2  weight3  age  gender  race  \\\n",
       "0             536  1952      1   1.0000   1.0000   1.0000   25       2     1   \n",
       "1             537  1952      2   1.0000   1.0000   1.0000   33       2     1   \n",
       "2             538  1952      3   1.0000   1.0000   1.0000   26       2     1   \n",
       "3             539  1952      4   1.0000   1.0000   1.0000   63       1     1   \n",
       "4             540  1952      5   1.0000   1.0000   1.0000   66       2     1   \n",
       "...           ...   ...    ...      ...      ...      ...  ...     ...   ...   \n",
       "34903       39982  2000   1804   1.0454   1.0454   1.0454   51       2     1   \n",
       "34904       39983  2000   1805   1.0454   1.0454   1.0454   52       2     1   \n",
       "34905       39984  2000   1808   2.0407   2.0407   2.0407   23       1     1   \n",
       "34906       39985  2000   1809   0.3717   0.3717   0.3717   36       2     1   \n",
       "34907       39986  2000   1810   1.5601   1.5601   1.5601   73       2     1   \n",
       "\n",
       "       educ1  ...  parent_party  white  year_new  income_new   age_new  \\\n",
       "0          2  ...           2.0      1         1           1 -2.052455   \n",
       "1          1  ...           0.0      1         1           1 -1.252455   \n",
       "2          2  ...          -2.0      1         1           0 -1.952455   \n",
       "3          2  ...           NaN      1         1           0  1.747545   \n",
       "4          2  ...          -2.0      1         1          -2  2.047545   \n",
       "...      ...  ...           ...    ...       ...         ...       ...   \n",
       "34903      2  ...           NaN      1        24           0  0.547545   \n",
       "34904      2  ...           NaN      1        24          -1  0.647545   \n",
       "34905      3  ...           NaN      1        24           1 -2.252455   \n",
       "34906      4  ...           NaN      1        24           0 -0.952455   \n",
       "34907      2  ...           NaN      1        24          -2  2.747545   \n",
       "\n",
       "       vote.1  age_discrete  race_adj  dvote  rvote  \n",
       "0         1.0             1       1.0    0.0    1.0  \n",
       "1         1.0             2       1.0    1.0    0.0  \n",
       "2         1.0             1       1.0    0.0    1.0  \n",
       "3         1.0             3       1.0    0.0    1.0  \n",
       "4         1.0             4       1.0    0.0    1.0  \n",
       "...       ...           ...       ...    ...    ...  \n",
       "34903     1.0             3       1.0    0.0    1.0  \n",
       "34904     NaN             3       1.0    NaN    NaN  \n",
       "34905     0.0             1       1.0    NaN    NaN  \n",
       "34906     0.0             2       1.0    1.0    0.0  \n",
       "34907     0.0             4       1.0    NaN    NaN  \n",
       "\n",
       "[34908 rows x 71 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "politics = pd.read_csv(\"https://jmaurit.github.io/anv_statistikk/data/nes.csv\")\n",
    "politics"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77ab87f3",
   "metadata": {},
   "source": [
    "There is one simple and under-appreciated model for binary data that ROS does not discuss. That is what is called a *Linear Probability Model*. Basically, you just run OLS with the normal 0/1 data on the left side. You can then interpret the coefficients as probabilities: \n",
    "\n",
    "Below the binary response variable, *rvote* indicates a 1 if a respondent who preferred George Bush in 1992 and 0 if they preferred Bill Clinton (A little history lesson for those of you who weren't born yet: this is referring to George HW Bush, father to George W. Bush who, confusingly, was also president. Bill Clinton won the 1992 election). \n",
    "\n",
    "*income* is an ordered categorical variable from 1 (poor) to 5 (rich)\n",
    "\n",
    "We can subtract our income variable by 1 so that the intercept term in our regression corresponds to the lowest category (1) of income. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "f6ecbd62",
   "metadata": {},
   "outputs": [],
   "source": [
    "politics92 = politics.loc[politics.year==1992].copy()\n",
    "politics92[\"income_m1\"] = politics92.income-1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "c0507950",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>OLS Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>          <td>rvote</td>      <th>  R-squared:         </th> <td>   0.018</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>                   <td>OLS</td>       <th>  Adj. R-squared:    </th> <td>   0.017</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>             <td>Least Squares</td>  <th>  F-statistic:       </th> <td>   24.23</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>             <td>Wed, 07 Sep 2022</td> <th>  Prob (F-statistic):</th> <td>9.60e-07</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                 <td>11:54:03</td>     <th>  Log-Likelihood:    </th> <td> -909.78</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>No. Observations:</th>      <td>  1356</td>      <th>  AIC:               </th> <td>   1824.</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Residuals:</th>          <td>  1354</td>      <th>  BIC:               </th> <td>   1834.</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Model:</th>              <td>     1</td>      <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>      <td>nonrobust</td>    <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "      <td></td>         <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intercept</th> <td>    0.2278</td> <td>    0.028</td> <td>    8.054</td> <td> 0.000</td> <td>    0.172</td> <td>    0.283</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>income_m1</th> <td>    0.0589</td> <td>    0.012</td> <td>    4.922</td> <td> 0.000</td> <td>    0.035</td> <td>    0.082</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Omnibus:</th>       <td>7972.680</td> <th>  Durbin-Watson:     </th> <td>   2.073</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Omnibus):</th>  <td> 0.000</td>  <th>  Jarque-Bera (JB):  </th> <td> 219.817</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Skew:</th>           <td> 0.602</td>  <th>  Prob(JB):          </th> <td>1.85e-48</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Kurtosis:</th>       <td> 1.438</td>  <th>  Cond. No.          </th> <td>    5.96</td>\n",
       "</tr>\n",
       "</table><br/><br/>Notes:<br/>[1] Standard Errors assume that the covariance matrix of the errors is correctly specified."
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                            OLS Regression Results                            \n",
       "==============================================================================\n",
       "Dep. Variable:                  rvote   R-squared:                       0.018\n",
       "Model:                            OLS   Adj. R-squared:                  0.017\n",
       "Method:                 Least Squares   F-statistic:                     24.23\n",
       "Date:                Wed, 07 Sep 2022   Prob (F-statistic):           9.60e-07\n",
       "Time:                        11:54:03   Log-Likelihood:                -909.78\n",
       "No. Observations:                1356   AIC:                             1824.\n",
       "Df Residuals:                    1354   BIC:                             1834.\n",
       "Df Model:                           1                                         \n",
       "Covariance Type:            nonrobust                                         \n",
       "==============================================================================\n",
       "                 coef    std err          t      P>|t|      [0.025      0.975]\n",
       "------------------------------------------------------------------------------\n",
       "Intercept      0.2278      0.028      8.054      0.000       0.172       0.283\n",
       "income_m1      0.0589      0.012      4.922      0.000       0.035       0.082\n",
       "==============================================================================\n",
       "Omnibus:                     7972.680   Durbin-Watson:                   2.073\n",
       "Prob(Omnibus):                  0.000   Jarque-Bera (JB):              219.817\n",
       "Skew:                           0.602   Prob(JB):                     1.85e-48\n",
       "Kurtosis:                       1.438   Cond. No.                         5.96\n",
       "==============================================================================\n",
       "\n",
       "Notes:\n",
       "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
       "\"\"\""
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mod1 = smf.ols(formula=\"rvote~income_m1\", data=politics92).fit()\n",
    "mod1.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b42971c1",
   "metadata": {},
   "source": [
    "The nice thing about the linear probability model is that it is simple to interpret, and we can easily use all of the inference tools for OLS that we have used up until now. \n",
    "\n",
    "The intercept, .23, can be interpreted as the probability of a voter in the lowest (1) category preferring the republican (George Bush).\n",
    "\n",
    "For every increase in income category, the probability of preferring the republican increases by, on average 5.9%. So someone in the largest income category would have a $.23 + 4*.059 \\approx .47$ probability of preferring the replublican. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ea2b663",
   "metadata": {},
   "source": [
    "So what is wrong with the above model. Actually, the linear probability model seems to work quite ok here. We might want to do our normal checks (see last lab) to see if this is a good fitting model, but at first glance it seems reasonable. \n",
    "\n",
    "But imagine if we had data with some variables with observations at the extremes. So, for example, perhaps we had a continuous income variable, and we had a few billionaires in the sample. Our model might then suggest that these people had a more than 100% probability of voting for a republican. This, clearly is problematic. \n",
    "\n",
    "We can generate some fake data to demonstrate."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "7a55f46c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "#Here we generate income data as coming from a normal distribution. \n",
    "#We assume a de-meaned data, so it is centered around 0\n",
    "income = pd.Series(spt.norm.rvs(0,100,size=10000)) # some de-meaned distribution of income\n",
    "income\n",
    "\n",
    "#create correlation between income and probabilities of voting\n",
    "xs = .5 + .01*income\n",
    "\n",
    "#inverse logit converts to 0-1 scale\n",
    "ps = pd.Series([np.exp(x)/(1+np.exp(x)) for x in xs])\n",
    "\n",
    "ps.hist(bins=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "932e00fc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 0, 1, ..., 1, 1, 1])"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#generate 0,1 data based on probabilities above using a bernoulli distribution\n",
    "\n",
    "vote = np.array([spt.bernoulli.rvs(p, size=1) for p in ps])\n",
    "\n",
    "vote = vote.flatten()\n",
    "\n",
    "vote"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "37c93ac8",
   "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>income</th>\n",
       "      <th>vote</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>29.591771</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>92.434680</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>23.906410</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-17.874557</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-113.337889</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9995</th>\n",
       "      <td>6.390314</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9996</th>\n",
       "      <td>-27.207364</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9997</th>\n",
       "      <td>-51.567032</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9998</th>\n",
       "      <td>95.526646</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9999</th>\n",
       "      <td>60.771587</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10000 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          income  vote\n",
       "0      29.591771     1\n",
       "1      92.434680     0\n",
       "2      23.906410     1\n",
       "3     -17.874557     1\n",
       "4    -113.337889     0\n",
       "...          ...   ...\n",
       "9995    6.390314     0\n",
       "9996  -27.207364     1\n",
       "9997  -51.567032     1\n",
       "9998   95.526646     1\n",
       "9999   60.771587     1\n",
       "\n",
       "[10000 rows x 2 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "f_df = pd.DataFrame({\"income\":income, \"vote\":vote})\n",
    "f_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "06cd2e0d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Now we run a linear probability regression of vote on income\n",
    "fmod1 = smf.ols(formula=\"vote~income\", data=f_df).fit()\n",
    "fmod1.summary()\n",
    "predictions = pd.Series(fmod1.predict())\n",
    "predictions.hist(bins=50)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9a5945ba",
   "metadata": {},
   "source": [
    "Here we see that the predictions from the linear probability model will indicate that some of predictions will go outside the 0-1 bounds, which is problematic when interpreting the predictions as probabilities. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5f47550b",
   "metadata": {},
   "source": [
    "(Some (See, for example, Angrist and Pischke, *Mostly Harmless Econometrics*), argue that the benefits outweigh the costs of linear probability models. In many cases, the problem with predicted probabilities not being between 0-1) is not that important if the primary purpose is inference, rather than prediction. It can often also be the case that range of predictions does not approach the bounds. \n",
    "\n",
    "For example, in the example above, it would be highly unlikely that any broad socio-economic group would, on average, have a predicted probability of voting for a certain party that was either close to 0 or close to 1. There were plenty of very rich people in 1992 that voted for Bill Clinton. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ff82f7dd",
   "metadata": {},
   "source": [
    "### Logistic regression"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "48c4176a",
   "metadata": {},
   "source": [
    "But if we are concerned about predictions close to the 0-1 boundaries, or if we otherwise think that the assumptions of the linear probability model (normality, linearity for example). The solution is to do **logistic regression**, which basically does a non-linear transformation of the data in order to constrain the fitted values to be between 0 and 1 - what we call the **inverse logit**: $(\\frac{e^x}{1-e^x})$. This is what we used above to convert our fake data to \"probabilities\" between 0 and 1\n",
    "\n",
    "Below we run a logistic regression using statsmodels:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 246,
   "id": "d11ca9b7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>Generalized Linear Model Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>         <td>vote</td>       <th>  No. Observations:  </th>  <td> 10000</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>                  <td>GLM</td>       <th>  Df Residuals:      </th>  <td>  9998</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model Family:</th>        <td>Binomial</td>     <th>  Df Model:          </th>  <td>     1</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Link Function:</th>         <td>logit</td>      <th>  Scale:             </th> <td>  1.0000</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>                <td>IRLS</td>       <th>  Log-Likelihood:    </th> <td> -5785.3</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>            <td>Mon, 21 Feb 2022</td> <th>  Deviance:          </th> <td>  11571.</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                <td>07:38:31</td>     <th>  Pearson chi2:      </th> <td>9.94e+03</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>No. Iterations:</th>          <td>4</td>        <th>  Pseudo R-squ. (CS):</th>  <td>0.1703</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>     <td>nonrobust</td>    <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "      <td></td>         <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intercept</th> <td>    0.4871</td> <td>    0.023</td> <td>   21.384</td> <td> 0.000</td> <td>    0.442</td> <td>    0.532</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>income</th>    <td>    0.0102</td> <td>    0.000</td> <td>   37.838</td> <td> 0.000</td> <td>    0.010</td> <td>    0.011</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                 Generalized Linear Model Regression Results                  \n",
       "==============================================================================\n",
       "Dep. Variable:                   vote   No. Observations:                10000\n",
       "Model:                            GLM   Df Residuals:                     9998\n",
       "Model Family:                Binomial   Df Model:                            1\n",
       "Link Function:                  logit   Scale:                          1.0000\n",
       "Method:                          IRLS   Log-Likelihood:                -5785.3\n",
       "Date:                Mon, 21 Feb 2022   Deviance:                       11571.\n",
       "Time:                        07:38:31   Pearson chi2:                 9.94e+03\n",
       "No. Iterations:                     4   Pseudo R-squ. (CS):             0.1703\n",
       "Covariance Type:            nonrobust                                         \n",
       "==============================================================================\n",
       "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
       "------------------------------------------------------------------------------\n",
       "Intercept      0.4871      0.023     21.384      0.000       0.442       0.532\n",
       "income         0.0102      0.000     37.838      0.000       0.010       0.011\n",
       "==============================================================================\n",
       "\"\"\""
      ]
     },
     "execution_count": 246,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "flog_mod0 = smf.glm(formula=\"vote~income\", data=f_df, family=sm.families.Binomial()).fit()\n",
    "flog_mod0.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1b28f434",
   "metadata": {},
   "source": [
    "A few things to parse in the above regression. \n",
    "\n",
    "- GLM: Notice we are not using OLS any more. Instead we are now in the realm of \"Generalized Linear Models\", estimated by maximum likelihood. The \"Generalized\" here means we are no longer constrained to the assumption of a normal distribition. In this case, we indicate that we have a binomial distribution (this is what the \"family\" parameter is for). \n",
    "\n",
    "- Link function: GLM models are also characterized by a \"link\" function. This really is nothing more than a transformation of the y-variable. Here the link function is the *logit* function, since we are estimating a model that looks like: \n",
    "\n",
    "$$logit(vote_i) = a + b*income_i$$\n",
    "\n",
    "Or equivalently\n",
    "\n",
    "$$vote_i = invlogit(a+b*income_i)$$\n",
    "\n",
    "- We are able to estimate the parameters we put into the model, but because of the non-linear logit/invlogit transformation, we can not interpret the coefficients as probabilities as in the linear probability model, or for that matter in any other straight-forward way (more on this below)\n",
    "\n",
    "- There is no $\\sigma$ term in the output: In the logistic regression there is no seperate error term. The model uncertainty comes from the mapping of the 0/1 data to probabilities (the binomial distribution)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c98bbdd",
   "metadata": {},
   "source": [
    "### Real data with logistic."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0d2e0a52",
   "metadata": {},
   "source": [
    "<iframe src=\"https://ntnu.cloud.panopto.eu/Panopto/Pages/Embed.aspx?id=32c6a3d9-4cec-4e3e-9daa-af0900c9ba89&autoplay=false&offerviewer=true&showtitle=true&showbrand=true&captions=false&interactivity=all\" height=\"405\" width=\"720\" style=\"border: 1px solid #464646;\" allowfullscreen allow=\"autoplay\"></iframe>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "898ff82e",
   "metadata": {},
   "source": [
    "Now let's use the logistic regression to fit our actual data, as in ROS (p.218-219): "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "a78974b3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>Generalized Linear Model Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>         <td>rvote</td>      <th>  No. Observations:  </th>  <td>  1356</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>                  <td>GLM</td>       <th>  Df Residuals:      </th>  <td>  1354</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model Family:</th>        <td>Binomial</td>     <th>  Df Model:          </th>  <td>     1</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Link Function:</th>         <td>logit</td>      <th>  Scale:             </th> <td>  1.0000</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>                <td>IRLS</td>       <th>  Log-Likelihood:    </th> <td> -867.26</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>            <td>Wed, 07 Sep 2022</td> <th>  Deviance:          </th> <td>  1734.5</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                <td>14:17:01</td>     <th>  Pearson chi2:      </th> <td>1.36e+03</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>No. Iterations:</th>          <td>4</td>        <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>     <td>nonrobust</td>    <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "      <td></td>         <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intercept</th> <td>   -1.4528</td> <td>    0.185</td> <td>   -7.832</td> <td> 0.000</td> <td>   -1.816</td> <td>   -1.089</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>income</th>    <td>    0.2668</td> <td>    0.055</td> <td>    4.844</td> <td> 0.000</td> <td>    0.159</td> <td>    0.375</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                 Generalized Linear Model Regression Results                  \n",
       "==============================================================================\n",
       "Dep. Variable:                  rvote   No. Observations:                 1356\n",
       "Model:                            GLM   Df Residuals:                     1354\n",
       "Model Family:                Binomial   Df Model:                            1\n",
       "Link Function:                  logit   Scale:                          1.0000\n",
       "Method:                          IRLS   Log-Likelihood:                -867.26\n",
       "Date:                Wed, 07 Sep 2022   Deviance:                       1734.5\n",
       "Time:                        14:17:01   Pearson chi2:                 1.36e+03\n",
       "No. Iterations:                     4                                         \n",
       "Covariance Type:            nonrobust                                         \n",
       "==============================================================================\n",
       "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
       "------------------------------------------------------------------------------\n",
       "Intercept     -1.4528      0.185     -7.832      0.000      -1.816      -1.089\n",
       "income         0.2668      0.055      4.844      0.000       0.159       0.375\n",
       "==============================================================================\n",
       "\"\"\""
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mod1 = smf.glm(formula=\"rvote~income\", data=politics.loc[politics.year==1992], family=sm.families.Binomial()).fit()\n",
    "mod1.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "c8e8f042",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Add some \"jitter\" to the data to make them easier to chart\n",
    "N = politics.shape[0]\n",
    "income_j = politics.income + spt.uniform(-.25,.5).rvs(size=N)\n",
    "rvote_j = politics.rvote + spt.uniform(-.05,.1).rvs(size=N)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "7d6422b4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Intercept   -1.452783\n",
       "income       0.266840\n",
       "dtype: float64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mod1.params"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "928d8af1",
   "metadata": {},
   "outputs": [],
   "source": [
    "def invLogit(x):\n",
    "    return(np.exp(x)/(1+np.exp(x)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "ae7f9bf9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Pr Republican Vote')"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "N = politics.shape[0]\n",
    "\n",
    "a = mod1.params[0]\n",
    "b = mod1.params[1]\n",
    "\n",
    "x_line = np.linspace(-2,8,N)\n",
    "y_line = invLogit(a+b*x_line)\n",
    "\n",
    "\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "ax.scatter(income_j, rvote_j, alpha=.02)\n",
    "ax.plot(x_line,y_line)\n",
    "ax.set_ylabel(\"Pr Republican Vote\")\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "56ea1486",
   "metadata": {},
   "source": [
    "So above we can see the estimated probability on the y-axis and the jittered data at the top and bottom. \n",
    "\n",
    "We extended the x-axis in the chart to show clearly that the regression line is non-linear. The equation for our regression line is: \n",
    "\n",
    "$$Pr(y_i = 1) = invlogit(-1.45 + .26x)$$\n",
    "\n",
    "Since the curve is non-linear, we can't give a simple slope estimate - the slope is changing along the entire curve!\n",
    "\n",
    "(I am unsure why the results are slightly different than those shown in the book for this regression. As far as I can see, they should be largely the same. Likely the data sets used are somewhat different). "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "abe191cb",
   "metadata": {},
   "source": [
    "If we want to interpret the regression results, we need to convert to the probability scale by using the inverse logit function. So, for example, if we want to see what the probability of someone in the the 3 income category for voting republican we would compute: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "a81d322f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.34247946844264443"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "invLogit(mod1.params[0] + mod1.params[1]*3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de5442f9",
   "metadata": {},
   "source": [
    "If we want to see the difference in probability of voting for the republican comparing, for example, groups 3 and 4 we could evaluation: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "27cd6af7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0623397542703194"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "invLogit(mod1.params[0] + mod1.params[1]*4)-invLogit(mod1.params[0] + mod1.params[1]*3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "177278eb",
   "metadata": {},
   "source": [
    "### Divide-by-four rule\n",
    "\n",
    "ROS (p.229) explains that diving the regression coefficient by 4 can be used as a quick approximation for an upper-bound on the probabilistic interpretation of the coefficient. \n",
    "\n",
    "So in the above regression we can take the estimated coefficient on the income variable:\n",
    "\n",
    ".23/4 = .058\n",
    "\n",
    "(Compare this to the estimated coefficient in the Linear Probability Model. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0229129d",
   "metadata": {},
   "source": [
    "### Prediction\n",
    "\n",
    "We can generate a prediction point estimate from our model with *predict*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "ae1f95e5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    0.404819\n",
       "dtype: float64"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Predict\n",
    "\n",
    "mod1.predict(exog=dict(income=4))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1201bd03",
   "metadata": {},
   "source": [
    "To get out more information, including standard error and confidence intervalls, we can use the *get_prediction* command:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "id": "84b469cd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.40481922]\n",
      "Standard Error,  [0.01741404]\n",
      "95% CI:  [[0.37119786 0.43935806]]\n"
     ]
    }
   ],
   "source": [
    "myPredictions = mod1.get_prediction(exog=dict(income=4))\n",
    "print(myPredictions.predicted_mean) #point estimate\n",
    "print(\"Standard Error, \", myPredictions.se_mean)\n",
    "print(\"95% CI: \", myPredictions.conf_int())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7d4d781b",
   "metadata": {},
   "source": [
    "### Displaying the result of multiple regression. \n",
    "\n",
    "We can also replicate the figure (ROS p.222)  showing the results for multiple regressions. We can run the regressions efficiently using *groupby*, and then iterating over the groups: \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "920ba65d",
   "metadata": {},
   "outputs": [],
   "source": [
    "presidential = np.arange(1952,2001, 4)\n",
    "\n",
    "\n",
    "politics_pres = politics.loc[politics.year.isin(presidential)].copy()\n",
    "\n",
    "election_groups = politics_pres.groupby(\"year\")\n",
    "\n",
    "labels = []\n",
    "income_b = []\n",
    "income_SE = []\n",
    "\n",
    "for year, election in election_groups: \n",
    "    #when we iterate through a grouped data frame,\n",
    "    #we get a tuple: basically a list with two items--a label (the grouped variable)--and the data frame\n",
    "    labels.append(year) \n",
    "    mod_m = smf.glm(formula=\"rvote~income\", data=election, family=sm.families.Binomial()).fit()\n",
    "    income_b.append(mod_m.params[1])\n",
    "    vcov = mod_m.cov_params()\n",
    "    income_SE.append(np.sqrt(vcov.iloc[1,1]))\n",
    "    \n",
    "\n",
    "labels = pd.Series(labels)\n",
    "income_b = pd.Series(income_b)\n",
    "income_SE = pd.Series(income_SE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "17005175",
   "metadata": {},
   "outputs": [],
   "source": [
    "ci_low = income_b - income_SE\n",
    "ci_high = income_b + income_SE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "4397cd46",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Coefficient of income')"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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n5I9//GNJswAAANC5dC/lpJ///OeZO3duevXq1Ra2RxxxRFasWFHSi/Tq1Str165tt7Z27dr07t17h993xBFH5PTTT88VV1yRX/3qV1sdnzBhQiZMmJAkOfXUU0uaBQAAgM6lpCu2VVVVaW5ubre2cuXKHHzwwSW9yJAhQ9Lc3JyGhoa2tfnz56eurm6n37tly5YsXbq0pNcBiumeeTNzz7yZHT0GAAAFVVLYjh8/PldddVWWLVuWJHnzzTfzxS9+Meecc05JL9KrV6+MGzcukydPTlNTU2bPnp0nn3wyF1xwwVbn/vjHP87y5cvT2tqa119/PbfddltOOeWU0n8jAAAA9iklhe0tt9ySgQMHZvTo0Xnrrbfy/ve/P4cffni+/OUvl/xCU6ZMyYYNG3L00UfniiuuyJQpU1JXV5fly5enX79+Wb58eZLkd7/7XcaMGZN+/frlr//6rzN06NB885vf3L3fDgAAgE6vpPfYVlVV5c4778ydd96ZlStXpk+fPm3vtS1VTU1Npk2bttX6kUce2e69ujfffHNuvvnmXfrZAAAA7LtKCtskWb9+fZYsWZKmpqa8+uqrbeujRo0qy2AAAABQipLC9qGHHsqXvvSl7LfffjnggAPa1rt06ZKXX365bMMBAADAzpQUtjfffHN++MMf5q/+6q/KPQ8AAADskpIf9/Pf/tt/K/csAAAAsMtKCtsbb7wxkyZNyqpVq8o9DwAAAOySksJ2yJAheeqpp3L00UfnoIMOykEHHZQDDzwwBx10UJnHAwAAgB0r6T22n/zkJ3PBBRfk7LPPzv7771/umQAAAKBkJYXtn/70p9x00027/OxaAAAAKLeSbkW++OKLM23atHLPAgAAwF6ivnFplqxZmUVvNWbSnEdT37i0o0farpKu2L700kv57ne/m7vvvjt9+/Ztd+zpp58uy2AAAAB0jPrGpZm6uD7NrS1JktUb12fq4vokyai+gztytG0qKWw/9rGP5WMf+1i5ZwEAAGAvMH3Z3Gxq2dJubVPLlkxfNre4YXvxxReXew4AAAD2Eqs3rt+l9Y5W0ntsk2Tq1Kk544wzctxxx+WMM87I1KlTyzkXAAAAHaSmR89dWu9oJV2x/drXvpZp06blc5/7XI488sgsX7483/jGN7JixYp86UtfKveMAAAAVND42pGZuri+3e3IVV27ZXztyI4bagdKCtsHH3wwTzzxRAYOHNi2dtppp2Xs2LHCFgAAoJN55320Dy6anebWltT06JnxtSP3yvfXJiWGbVNTUw455JB2azU1NXn77bfLMhQAAAAda1TfwXnuzYYkycQRYzp4mh0r6T22p59+eq688sosXrw4b7/9dhYtWpSrrroqp512WrnnAwAAgB0qKWzvvvvu9O7dOyeffHL69euXD3zgA+nZs2e+9rWvlXs+AAAA2KGSbkWurq7Od7/73fzjP/5jVq1alT59+qRr15I/UBkAAADKpqQ6feihh7JgwYJ07do1hx56aLp27Zr58+dn2rRp5Z4PAAAAdqiksJ08eXL69+/fbq1///75H//jf5RlKAAAAChVSWG7du3aVFdXt1s78MAD89Zbb5VlKAAAAChVSWH7vve9L4899li7tccffzzvfe97yzIUAABQPvWNS7Nkzcoseqsxk+Y8mvrGpR09ErwrJX141G233ZZzzjknP/vZzzJ48OAsWbIks2bNyk9/+tNyzwcAAOxB9Y1LM3VxfZpbW5Ikqzeuz9TF9Un+/NxSKKKSrtiOHj06s2fPznHHHZempqYcf/zxmT17dk466aRyzwcAAOxB05fNzaaWLe3WNrVsyfRlcztmINgDSrpimyRHHnlkrr322nLOAgAAlNnqjet3aR2KoKSwXb16db71rW9l3rx5aWpqanfs6aefLstgAADAnlfTo+c2I7amR88OmAb2jJLC9uMf/3g2bdqUM888MwcccEC5ZwIAAMpkfO3ITF1c3+525Kqu3TK+dmTHDQXvUklhO2fOnCxZsiQ9evQo9zwAAEAZvfMBUQ8ump3m1pbU9OiZ8bUjfXAUhVZS2A4bNixvvPFGjjrqqHLPAwAAlNmovoPz3JsNSZKJI8Z08DTw7pUUtn/5l3+Zs846K5dcckkOO+ywdscuvfTSsgwGAAAApSgpbF944YX0798/zz77bLv1Ll26CFsAAAA6VElh+8QTT5R7DgAAANgt2w3b1tbWdOnSJUnS0tKy3R/QtWvXPT8VAAAAlGi7YTtgwIC88cYbSZKDDz64LXLf8U74/vu//3tZBwQAAIAd2W7Y1tfXt309f/78igwDAAAAu2qHV2zfMXDgwIoMAwCwOzyuBGDf5g2yAAAAFJqwBQAAoNC2G7Z/+tOfKjkHAAAA7Jbthu2xxx7b9vVHPvKRigwDAADlMnHEGO/Hhk5qu2F7wAEH5OWXX86WLVvy0ksvpbW1NS0tLVv9AQAAgI603U9Fvv7663Pqqadm48aNSf78LNv/zHNsAQAA2BtsN2yvvPLKXH755fm///f/5oQTTkh9fX1bzAIAAMDeYrthmyTdu3dP//7986tf/cqzbAEAANgrlfS4n0GDBmXy5MkZPnx4Dj300IwYMSKTJ0/Opk2byj0fAAAA7NAOr9i+4ytf+UpeeumlfOMb38jAgQPz+uuv56677sratWtzxx13lHtGAAAA2K6Swnb69On59a9/nT59+iRJhg4dmpEjR+bkk08WtgAAAHSokm5Fbm1t3aV1gFLVNy7NkjUrs+itxkya82jqG5d29EgAABRMSWE7fvz4nH/++fnlL3+Z3/3ud5k5c2YuvPDCnHnmmeWeD+jE6huXZuri+jS3/vmZ2Ks3rs/UxfXilq3cM29m7pk3s6PHAAD2UiXdivzVr341d911VyZOnJg333wz/fr1y9lnn53rrruu3PMBndj0ZXOzqWVLu7VNLVsyfdncjOo7uIOmAgCgaEoK26qqqtx000256aabyj0PsA9ZvXH9Lq0DAMC2lHQrMkA51PTouUvrAACwLcIW6DDja0emqmu3dmtVXbtlfO3IjhkIAIBCKulWZIByeOd9tA8ump3m1pbU9OiZ8bUjvb8WAIBdUtIV29/85jfbXH/xxRf36DDAvmdU38E5qvqQvPfAvvn/TjxT1AIAsMtKftzPtpx11ll7chYAAADYZTu8FbmlpSWtra3t/rxjyZIl6d7dncwAAAB0rB2W6cEHH5wuXbq0ff2fde3aNV/84hfLNxkAAACUYIdhO3/+/LS2tuZDH/pQnnrqqbb1Ll265JBDDskBBxxQ9gEBAABgR3YYtgMHDkyS/Nu//VtFhgEAAIBdVdKbZFevXp1vfetbmTdvXpqamtode/rpp8syGAAAAJSipLD9+Mc/nk2bNuXMM890+zEAAAB7lZLCds6cOVmyZEl69OhR7nkAAABgl5T0HNthw4bljTfeKPcsAAAAsMtKumL7l3/5lznrrLNyySWX5LDDDmt37NJLLy3LYAAAAFCKksL2hRdeSP/+/fPss8+2W+/SpYuwBQAAoEOVFLZPPPFEuecAAACA3VLSe2yTZNWqVZk2bVr+/u//PkmyYsUK77sFAACgw5UUts8991yOP/74PPLII7nzzjuTJK+++mq+8IUvlHU4AAAA2JmSwvb666/PAw88kEcffTTdu//57uUTTjghL730UlmHAwAAgJ0pKWxff/31fPCDH2y3VlVVlebm5nLMBAAAACUr6cOj3ve+9+WXv/xlTj/99La1Z599NsOGDSvbYAAAAHSsiSPGdPQIJSkpbCdPnpzzzjsvf/M3f5MNGzbk85//fJ566qlMmzat3PMBAADADpUUtieeeGKef/75PPLII+nVq1cGDBiQZ599Nv379y/3fAAAALBDJYVtkhxxxBG55ppryjgKAAAA7Lrthu3f/d3f5Zvf/GaS5BOf+ES6dOmyzfO++93vlmcyAAAAKMF2w3bQoEFtXx911FEVGQYAAAB21XbDduLEiW1fT5o0qSLDAAAAwK4q6Tm2U6ZMyUsvvdRu7cUXX8w3vvGNcswEAACU2cQRYwrzKBfYmZLC9tvf/naOOeaYdmvHHHNM/uEf/qEsQwEAAECpSgrbTZs2Zb/99mu3VlVVlQ0bNpRlKAAAAChVSWE7cuTI/NM//VO7te9973sZOXJkOWYCAACAkpX0HNs77rgjH/3oR/PjH/84gwcPzpIlS9LY2JjHHnus3PMBAADADpUUtnV1dfnXf/3XPP3003njjTcybty4/O3f/m169+5d7vkAAABgh0oK2yTp3bt3zjnnnHLOAgAAALtsu2F75pln5tFHH02S/M3f/E26dOmyzfOefvrpkl5o9erVufrqq/PMM8+kT58+ueWWW3Leeedtdd6PfvSjfOc738mrr76a97znPTn33HNzyy23pHv3khscAACAfch2a/HCCy9s+/qyyy571y80ceLEVFVVpaGhIfPnz8+5556b4cOHp66urt15b7/9du64446ccMIJWblyZS644IJ885vfzLXXXvuuZwAAAKDz2W7YPvnkk21XVFtbW3PJJZfs9os0NTVlxowZmT17dnr37p3Ro0dn7Nixefjhh3Prrbe2O/fKK69s+/qII47Ieeedl3/5l3/Z7dcGAACgc9vu436eeeaZtLa2Jkm+/OUvv6sXaWhoSLdu3TJ06NC2teHDh2fhwoU7/d5f//rXW13VBQAAgHds94rtSSedlNNOOy1DhgzJhg0b8slPfnKb5333u9/d6Ys0NTWlurq63Vp1dXXWrVu3w++bOnVqfvvb3+bee+/d5vH7778/DzzwQJJk1apVO50DAACAzme7Yfvggw9m+vTpWb58ebp06ZLBgwfv9ov06tUra9eubbe2du3aHT4u6Oc//3luueWWzJgxI3369NnmORMmTMiECROSJKeeeupuzwfA3qu+cWmWrFmZ5taWTJrzaMbXjsyovrv/3yQAoPPZbtj+4Ac/yKc+9akkycKFCzNp0qTdfpEhQ4akubk5DQ0NGTJkSJJk/vz5273FeObMmfnc5z6Xn/zkJxk2bNhuvy4AxVbfuDRTF9enubUlSbJ64/pMXVyfJOIWAGiz3ffYfvWrX237+n/+z//5rl6kV69eGTduXCZPnpympqbMnj07Tz75ZC644IKtzp01a1auvPLKTJ06NSeccMK7el0Aim36srnZ1LKl3dqmli2ZvmxuxwwEAOyVtnvFdvDgwbnhhhtSV1eXzZs354c//OE2z7v00ktLeqEpU6bks5/9bI4++ujU1NRkypQpqaury/Lly3PiiSdmzpw5OfLII3PXXXdlzZo1Oeecc9q+d/To0fnZz362i78aAEW3euP6XVoHAPZN2w3b73//+/n7v//7/PSnP83mzZvz8MMPb3VOly5dSg7bmpqaTJs2bav1I488MitWrGj7+xNPPFHSzwOg86vp0XObEVvTo2cHTAMA7K22G7ZDhw5t+zTicePG5fHHH6/YUACQJONrR2bq4vp2tyNXde2W8bUjO24oAGCvs9332P5njz/+eDZv3pznn38+//zP/5zkz4/waWpqKutwAOzbRvUdnEuGjkr3Ln/+z1VNj565ZOgoHxwFALSz3Su2/9nLL7+c888/P1VVVfnDH/6Qs88+O88991ymTZvW9hxZACiHUX0H57k3G5IkE0eM6eBpAIC9UUlXbK+55prccMMNeemll7LffvslSf7iL/4iL7zwQlmHAwAAgJ0pKWxfeeWVrR7N06tXr7z99ttlGQoAAABKVVLYDhw4ML/97W/brb344os56qijyjIUAAAAlKqk99jeeOONOffcc3PFFVdk8+bNueeee/L9738/3/zmN8s9HwAAAOxQSVdsx44dm3/+53/OypUr84EPfCDLly/P1KlTc9ppp5V7PgAAANihkq7YJsnIkSMzcuTIMo4CAAAAu66kK7abN2/O5MmTM2LEiBx66KEZMWJEJk+enE2bNpV7PmAfMHHEGI9xAQBgt5V0xfYrX/lKXnrppXz961/PwIED8/rrr+euu+7K2rVrc8cdd5R7RgAAANiuksJ2+vTp+fWvf50+ffokSYYOHZqRI0fm5JNPFrYAAAB0qJJuRW5tbd2ldQAAAKiUksJ2/PjxOf/88/PLX/4yv/vd7zJz5sxceOGFOfPMM8s9HwAAAOxQSbcif/WrX81dd92ViRMn5s0330y/fv1y9tln57rrriv3fAAAALBDJYVtVVVVbrrpptx0003lngcAAAB2yQ5vRZ49e3ZuvvnmbR675ZZbMmfOnLIMBQAAAKXaYdjefffdOfnkk7d57AMf+EDuvvvusgwFAAAApdph2M6fPz9jxozZ5rG/+qu/yty5c8sxEwAAAJRsh2G7du3abNq0aZvHNm/enHXr1pVlKAAAACjVDsN26NCheeaZZ7Z57JlnnsnQoUPLMhQAAACUaodh+9nPfjaf//znM2PGjLS0tCRJWlpaMmPGjFxzzTW5+uqrKzIkAAAAbM8OH/dz3nnnpbGxMVdddVU2btyYPn36ZNWqVdl///0zadKknHvuuZWaEwAAALZpp8+xvfrqq3PZZZdlzpw5Wb16dWpqanLiiSemurq6EvMBAADADu00bJOkuro6p59+erlnAQAAgF22w/fYAgAAwN5O2AIAAFBowpayumfezNwzb2ZHjwEAAHRiwhYAAIBCE7YAAAAUmrAFAACg0IQtAAAAhSZsAQAAKDRhu4f5FGAAAIDKErYAAAAUmrAFAACg0IQtAAAAhSZsAQAAKDRhCwAAQKEJWwAAAApN2AIAAFBowhYAAIBCE7YAAAAUmrAFAACg0Lp39AAAsDMTR4zp6BEAgL2YK7YAe5l75s3MPfNmdvQYAACFIWwBAAAoNGELAABAoQlbAAAACk3YAgAAUGjCFgAAgEITtgAAABSasAUAAKDQhC0AAACFJmwBAAAoNGELAABAoQlbAAAACk3YAgAAUGjCFgAAgEITtgAAABSasAUAAKDQhC0AAACFJmwBAAAoNGELAABAoQlbAAAACk3YAgAAUGjCFgAAgEITtgAAABSasAUAAKDQhC0AAACFJmwBAAAoNGELAABAoQlbAAAACk3YAgAAUGjClrKpb1yaJWtWZtFbjZk059HUNy7t6JEAAIBOSNhSFvWNSzN1cX2aW1uSJKs3rs/UxfXiFgAA2OOELWUxfdncbGrZ0m5tU8uWTF82t2MGAgAAOi1hS1ms3rh+l9YBAAB2l7ClLGp69NyldQAAgN0lbCmL8bUjU9W1W7u1qq7dMr52ZMcMBAAAdFrCdg/yKcD/YVTfwblk6Kh07/LnLVbTo2cuGToqo/oO7uDJAACAzqZ7Rw/QWWzvU4CT7LMxN6rv4Dz3ZkOSZOKIMR08DQAA0Fm5YruH+BRgAACAjiFs9xCfAgwAANAxhO0e4lOAAQAAOoaw3UN8CjAAAEDHqFjYrl69OhdddFEOP/zwDBs2LI888sg2z3v55Zczfvz41NbWprq6ulLjvWs+BRgAAKBjVOxTkSdOnJiqqqo0NDRk/vz5OffcczN8+PDU1dW1O2+//fbLWWedlU984hO58MILKzXeHuFTgAEAACqvImHb1NSUGTNmZPbs2endu3dGjx6dsWPH5uGHH86tt97a7tyhQ4dm6NChefXVVysxGlTcPfNmJvH//AAAgD2lIrciNzQ0pFu3bhk6dGjb2vDhw7Nw4cJKvDwAAACdWMWu2P6/75etrq7OunXr3tXPvf/++/PAAw8kSVatWvWufhYAAADFVJErtr169cratWvbra1duza9e/d+Vz93woQJmTVrVmbNmpVDDz30Xf0sAAAAiqkiYTtkyJA0NzenoaGhbW3+/PlbfXAUAAAA7KqKXbEdN25cJk+enKampsyePTtPPvlkLrjggq3ObW1tzYYNG7J58+YkyYYNG7Jx48ZKjAkAAEABVew5tlOmTMmGDRty9NFH54orrsiUKVNSV1eX5cuXp1+/flm+fHmS5PXXX0/fvn1z4oknJkn69u2b448/vlJjAgAAUDAVe45tTU1Npk2bttX6kUcemRUrVrT9fdCgQVmzZk2lxgIAAKDgKnbFFgAAAMpB2AIAAFBowhYAAIBCE7YAAAAUmrAF2IvUNy7NkjUrs+itxkya82jqG5d29EgAAHs9YQuwl6hvXJqpi+vT3NqSJFm9cX2mLq4XtwAAOyFsAfYS05fNzaaWLe3WNrVsyfRlcztmIACAghC2AHuJ1RvX79I6AAB/JmwB9hI1PXru0joAAH8mbAH2EuNrR6aqa7d2a1Vdu2V87ciOGQgAoCC6d/QAAPzZqL6DkyQPLpqd5taW1PTomfG1I9vWAQDYNmELsBcZ1XdwnnuzIUkyccSYDp4GAKAY3IoMAABAoQlbAAAACk3YAgAAUGjCFgAAgEITtgAAABSasAUAAKDQhC0AAACFJmwBAAAoNGELAABAoQlbAAAACk3YAgAAUGjCFgAAgEITtgAAABSasAUAAKDQhC0AAACFJmwBAAAoNGELAABAoQlbAAAACk3YAgAAUGjdO3oAOreJI8Z09AgAAEAn54otAAAAhSZsAQAAKDRhCwAAQKEJWwAAAApN2AIAAFBowhYAAIBC87ifPczjbQAAACrLFVsAAAAKTdgCAABQaMIWAACAQhO2AAAAFJqwBQAAoNCELQAAAIUmbAEAACg0YQsAAEChCVsAAAAKTdhCBdU3Ls2SNSuz6K3GTJrzaOobl3b0SAAAUHjCFiqkvnFppi6uT3NrS5Jk9cb1mbq4XtwCAMC7JGyhQqYvm5tNLVvarW1q2ZLpy+Z2zEAAANBJCFuokNUb1+/SOgAAUBphCxVS06PnLq0DAAClEbZQIeNrR6aqa7d2a1Vdu2V87ciOGQgAADqJ7h09AOwrRvUdnCR5cNHsNLe2pKZHz4yvHdm2DgAA7B5hCxU0qu/gPPdmQ5Jk4ogxHTwNAAB0Dm5FBgAAoNCELQAAAIUmbAEAACg0YQsAAEChCVsAAAAKTdgCAABQaMIWAACAQhO2AAAAFJqwBQAAoNCELQAAAIXWvaMHAKC9iSPGdPQIAACF4ootAAAAhSZsAQAAKDRhCwAAQKEJWwAAAApN2AIAAFBowhYAAIBCE7YAAAAUmrAFAACg0IQtAAAAhSZsAQAAKDRhCwAAQKEJWwAAAApN2AIAAFBowhYAAIBCE7YAAAAUmrAFAACg0IQtAAAAhSZsAQAAKDRhCwAAQKFVLGxXr16diy66KIcffniGDRuWRx55ZLvn3nvvvRkyZEgGDBiQz3zmM9m4cWOlxgQAAKBgKha2EydOTFVVVRoaGnLffffl2muvzcKFC7c675e//GW+/vWv5/HHH8/8+fOzbNmy3H777ZUaEwAAgIKpSNg2NTVlxowZufHGG9O7d++MHj06Y8eOzcMPP7zVuQ899FAuu+yy1NXV5eCDD851112XH/3oR5UYEwAAgAKqSNg2NDSkW7duGTp0aNva8OHDt3nF9pVXXsmxxx7b7rzGxsasWrWqEqMCAABQMN0r8SJNTU2prq5ut1ZdXZ1169Ztde66devanfvO1+vWrUufPn3anXv//ffngQceSBLhCwAAsI+qyBXbXr16Ze3ate3W1q5dm969e291bu/evdudu2bNmrb1/9eECRMya9aszJo1K4ceeugenhoAAIAiqEjYDhkyJM3NzWloaGhbmz9/furq6rY695hjjsmCBQva/r5gwYL07dt3q6u1AAAAkFTwiu24ceMyefLkNDU1Zfbs2XnyySdzwQUXbHXuhRdemAcffDCvvPJK/vSnP+VrX/taLr744kqMCQAAQAFV7HE/U6ZMyYYNG3L00UfniiuuyJQpU1JXV5fly5enX79+Wb58eZJkzJgxueaaa/LhD384xx57bI488sjccMMNlRoTAACAgqnIh0clSU1NTaZNm7bV+pFHHpkVK1a0W7v66qtz9dVXV2o0AAAACqxiV2wBAACgHIQtAAAAhSZsAQAAKDRhCwAAQKEJWwAAAApN2AIAAFBowhYAAIBCE7YAAAAUmrAFAACg0IQtAAAAhSZsAQAAKDRhCwAAQKEJWwAAAApN2AIAAFBo3Tt6ANjXTBwxpqNHAACATsUVWwAAAApN2AIAAFBowhYAAIBCE7YAAAAUmrAFAACg0IQtAAAAhSZsAQAAKDRhCwAAQKEJWwAAAApN2AIAAFBowhYAAIBCE7YAAAAUmrAFAACg0IQtAAAAhSZsAQAAKDRhCwAAQKEJWwAAAApN2AIAAFBowhYAAIBCE7YAAAAUmrAFAACg0IQtAAAAhSZsAQAAKDRhCwAAQKF17+gB9pRXXnklxx13XEePASVZuXJlDjnkkI4eA0piv1IU9ipFYr9SJHvLfn3ttde2e6zThO173/vezJo1q6PHgJKccsop9iuFYb9SFPYqRWK/UiRF2K9uRQYAAKDQhC0AAACF1mnC9vLLL+/oEaBk9itFYr9SFPYqRWK/UiRF2K9d1qxZ09rRQwAAAMDu6jRXbAEAANg3CVsAAAAKba8L2+985zs55ZRTcsghh+Sqq65qd+wHP/hB/ut//a/p169fzjzzzKxYsaLt2O23356ampr069ev7c/SpUvbjr/22mv58Ic/nMMOOyzHH398nn322Yr9TnReu7tfk2Tu3Ln527/92/Tr1y9HH310/uEf/qHtmP1KOezufj3rrLPa/dvap0+fnHTSSW3H7Vf2tN3dqxs3bsw111yTo48+OgMHDsx5552XP/zhD23H7VXKYXf367//+7/nU5/6VI466qgcddRRuf3229t9r/3KnrZx48Z89rOfzbBhw3LEEUfkL/7iL/KLX/yi7fj//t//O8cff3wOO+ywfPjDH87rr7/edqy1tTU333xzBg0alEGDBuUrX/lKWlv/4x2te8N+3evCtl+/fvnSl76USy+9tN36c889l1tvvTUPP/xwXnvttdTW1uaKK65od85ZZ52VFStWtP0ZPHhw27ErrrgiI0aMyLJly3LzzTfnsssuy8qVKyvyO9F57e5+XbVqVc4666xMmDAhy5Yty9y5c3Paaae1HbdfKYfd3a8/+9nP2v3bOmrUqIwfP77tuP3Knra7e/Xb3/525syZkxdeeCGLFi3KgQcemC996Uttx+1VymF39+ukSZPy9ttvZ8GCBXn22Wfz8MMPZ+rUqW3H7Vf2tObm5vTv3z9PPvlkfv/73+fGG2/M5Zdfntdeey2rVq3KJZdckptuuimvvfZa3v/+97f7wKj7778/P//5z/P888/nhRdeyNNPP53vf//7bcf3hv2614XtRz7ykZxxxhk5+OCD260/9dRTGT9+fOrq6lJVVZXrrrsuv/71r7NkyZKd/szFixfn//yf/5MbbrghBxxwQD760Y/mv/yX/5LHHnusXL8G+4jd3a/33ntvTjvttJx//vnp0aNH3vOe9+R973tfEvuV8tkT/76+9tpref7553PBBRcksV8pj93dq6+99lpOO+209O3bN/vvv3/OPvvsLFy4MIm9Svns7n596qmn8vnPfz49e/bMoEGDctlll+WHP/xhEvuV8ujVq1duuOGGDBo0KF27ds3YsWMzaNCgzJ07NzNmzMgxxxyTM888M/vvv38mTZqUBQsWZNGiRUmShx56KJ/73OfSv3//HHHEEfnc5z6XH/3oR0n2nv2614Xt9rS2tra73P3O1+/8BytJnn766QwcODAnnnhi7rvvvrb1V155JbW1tXnPe97Ttnbssce2+17Yk3a2X3/zm9/k4IMPzumnn56jjjoq5513XpYvX57EfqXySvn39R3Tpk3LySefnNra2iT2K5W1s7166aWXZvbs2VmxYkXWr1+fRx55JGPGjElir1J5pfzb+v8ef+eY/UolNDY2pqGhIXV1dVm4cGGGDx/edqxXr14ZPHhwuz157LHHth0/9thj88orr7Qd2xv2a2HC9q//+q/z6KOPZsGCBXn77bdz5513pkuXLlm/fn2SP9+G/Jvf/CZLly7Nt771rdx55535yU9+kiRZt25dqqur2/28Aw88MOvWrav478G+YWf79Y033si0adNy55135uWXX86gQYPabk+yX6m0ne3X/2zatGm5+OKL2/5uv1JJO9urQ4YMyYABA/K+970v/fv3z6JFi/LlL385ib1K5e1sv55++un5+te/nrVr1+bVV1/ND3/4w7Zj9ivltnnz5lx55ZW56KKL8t73vjdNTU1b7bnq6uq2Pbdu3boceOCBWx1rbW3da/ZrYcL2gx/8YG644YZccsklGTZsWAYOHJj3vOc96d+/f5LkmGOOSb9+/dKtW7eMGjUqn/70p9suf/fu3Ttr165t9/PWrFmT3r17V/z3YN+ws/16wAEH5Iwzzsjxxx+f/fffP9dff33q6+vz1ltv2a9U3M726zteeOGFNDY25qMf/Wjbmv1KJe1sr37hC1/Ixo0bs2zZsrz55psZN25czj777CT2KpW3s/161113Zf/998/73//+XHjhhTnnnHNyxBFHJLFfKa+WlpZ84hOfyH777Ze77747yZ+v0K5Zs6bdeWvXrm3bc7179253/J1jXbp02Wv2a2HCNkk++clPZu7cuVmyZEk+8pGPpLm5OXV1dds8t0uXLm23dxxzzDFZtmxZu/+DL1iwYLvfC3vCjvbrsGHD0qVLl7Zz3/m6tbXVfqVDlPLv60MPPZRx48a1+w+V/Uql7WivLliwIBdffHFqamrSo0ePfOpTn8pLL72UVatW2at0iB3t15qamnzve99LQ0ND5syZk9bW1hx//PFJ/NtK+bS2tuazn/1s/vjHP2bq1KnZb7/9kiR1dXVZsGBB23lNTU1ZunRp25475phj2h1fsGBBjjnmmLZje8N+3evCtrm5ORs2bEhLS0u2bNmSDRs2tK29/PLLaW1tzfLly/P5z38+n/70p9veqP/EE0/kT3/6U1pbW/Piiy/mH//xH/OhD30oSTJ06NAMHz48d9xxRzZs2JDHH388//Zv/9buqgPsjt3dr5dcckl+/vOfZ968edm8eXPuuuuujB49OgcddJD9Stns7n5NkrfffjvTp09vdxty4t9XymN39+pxxx2XadOm5a233srmzZtz3333tT2iyl6lXHZ3vy5ZsiSrVq3Kli1b8otf/CL3339/rrvuuiT+baV8vvCFL+R3v/tdfvzjH+eAAw5oWx83blwWLlyYxx57LBs2bMidd96ZYcOG5b3vfW+S5MILL8y9996bP/zhD1mxYkW+9a1vtf1vgr1lv3ZZs2ZN685Pq5zbb789d9xxR7u166+/Pp/5zGcyduzYLF26NL17984ll1ySr3zlK+nWrVuSZMKECXnmmWeyadOmHHHEEbnyyivz6U9/uu1nvPbaa/n0pz+dF198MQMGDMg999yTU089taK/G53P7u7XJLnvvvvyta99LW+//XZOOumkTJkyJQMGDEhiv1Ie72a//uQnP8l//+//PQsWLGh3t0Fiv7Ln7e5eXbVqVa677ro8++yz2bx5c+rq6nL77bfnhBNOSGKvUh67u19/9rOf5frrr89bb72VIUOG5NZbb83pp5/e9jPsV/a0119/Pccee2x69OiR7t27t61/4xvfyPnnn59nn302X/ziF7N8+fKccMIJ+fa3v51BgwYl+Y/n2P7gBz9IknzsYx/Lbbfd1va/CfaG/brXhS0AAADsir3uVmQAAADYFcIWAACAQhO2AAAAFJqwBQAAoNCELQAAAIUmbAEAACg0YQsAAEChCVsAAAAKTdgCAABQaP8/ET2c60i9d0UAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.scatter(labels, income_b)\n",
    "ax.vlines(x=labels, ymin=ci_low, ymax=ci_high)\n",
    "ax.set_xlim(1950,2002)\n",
    "ax.set_ylabel(\"Coefficient of income\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ecce408c",
   "metadata": {},
   "source": [
    "The above shows the coefficient on income. The lines represent +/- 1 standard deviations, so you can think of them as 68% confidence intervalls"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "97b290e3",
   "metadata": {},
   "source": [
    "### Oil drilling"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ddd1658e",
   "metadata": {},
   "source": [
    "Let's move to a slightly more complicated modelling situation. We will load in data on historical well-drilling on the Norwegian Continental Shelf between 1966 and through 2019. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "af6c46c2",
   "metadata": {},
   "outputs": [],
   "source": [
    "drilling = pd.read_csv(\"https://jmaurit.github.io/anv_statistikk/data/drilling.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f1b418e",
   "metadata": {},
   "source": [
    "Data is incomplete for 2020, so we will delete the rows from that year: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "cba1712b",
   "metadata": {},
   "outputs": [],
   "source": [
    "drilling = drilling.loc[drilling.year!=2020].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "dfe060b4",
   "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>year</th>\n",
       "      <th>NpdidLicence</th>\n",
       "      <th>orgnr</th>\n",
       "      <th>nDrills</th>\n",
       "      <th>nDry</th>\n",
       "      <th>LongName</th>\n",
       "      <th>ValidFrom</th>\n",
       "      <th>ValidTo</th>\n",
       "      <th>revenues</th>\n",
       "      <th>oper_revenues</th>\n",
       "      <th>...</th>\n",
       "      <th>d_brent_neg</th>\n",
       "      <th>d_brent_pos_l1</th>\n",
       "      <th>d_brent_pos_l2</th>\n",
       "      <th>d_brent_neg_l1</th>\n",
       "      <th>d_brent_neg_l2</th>\n",
       "      <th>licenceStart</th>\n",
       "      <th>licenceYears</th>\n",
       "      <th>licenceOwnerYears</th>\n",
       "      <th>d2005</th>\n",
       "      <th>nComp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1966</td>\n",
       "      <td>20756</td>\n",
       "      <td>914048990</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Esso Exploration and Production Norway A/S</td>\n",
       "      <td>1965-09-01</td>\n",
       "      <td>2004-10-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1965-09-01</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1966</td>\n",
       "      <td>20780</td>\n",
       "      <td>914048990</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Esso Exploration and Production Norway A/S</td>\n",
       "      <td>1965-09-01</td>\n",
       "      <td>1977-09-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1965-09-01</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1967</td>\n",
       "      <td>20756</td>\n",
       "      <td>914048990</td>\n",
       "      <td>3</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Esso Exploration and Production Norway A/S</td>\n",
       "      <td>1965-09-01</td>\n",
       "      <td>2004-10-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1965-09-01</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1967</td>\n",
       "      <td>20804</td>\n",
       "      <td>927533081</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Amoco Norway Oil Company</td>\n",
       "      <td>1965-09-01</td>\n",
       "      <td>1989-04-14</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1965-09-01</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1967</td>\n",
       "      <td>20884</td>\n",
       "      <td>948138646</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>Phillips Petroleum Company Norway</td>\n",
       "      <td>1965-09-01</td>\n",
       "      <td>1968-01-01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1965-09-01</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>5</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",
       "      <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>12547</th>\n",
       "      <td>2015</td>\n",
       "      <td>917484</td>\n",
       "      <td>989795848</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Det norske oljeselskap ASA</td>\n",
       "      <td>2009-12-22</td>\n",
       "      <td>2016-09-30</td>\n",
       "      <td>1158683.0</td>\n",
       "      <td>1221802.0</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.637438</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.092486</td>\n",
       "      <td>-0.027887</td>\n",
       "      <td>1999-12-15</td>\n",
       "      <td>16</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12548</th>\n",
       "      <td>2016</td>\n",
       "      <td>917484</td>\n",
       "      <td>989795848</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Aker BP ASA</td>\n",
       "      <td>2009-12-22</td>\n",
       "      <td>2017-12-11</td>\n",
       "      <td>1129939.0</td>\n",
       "      <td>1117697.0</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.181405</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.637438</td>\n",
       "      <td>-0.092486</td>\n",
       "      <td>1999-12-15</td>\n",
       "      <td>17</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12549</th>\n",
       "      <td>2016</td>\n",
       "      <td>917484</td>\n",
       "      <td>989795848</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Det norske oljeselskap ASA</td>\n",
       "      <td>2009-12-22</td>\n",
       "      <td>2017-12-11</td>\n",
       "      <td>1129939.0</td>\n",
       "      <td>1117697.0</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.181405</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.637438</td>\n",
       "      <td>-0.092486</td>\n",
       "      <td>1999-12-15</td>\n",
       "      <td>17</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12550</th>\n",
       "      <td>2017</td>\n",
       "      <td>917484</td>\n",
       "      <td>989795848</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Aker BP ASA</td>\n",
       "      <td>2016-09-30</td>\n",
       "      <td>2018-05-16</td>\n",
       "      <td>2575654.0</td>\n",
       "      <td>2562933.0</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>-0.181405</td>\n",
       "      <td>-0.637438</td>\n",
       "      <td>1999-12-15</td>\n",
       "      <td>18</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12551</th>\n",
       "      <td>2019</td>\n",
       "      <td>917484</td>\n",
       "      <td>989795848</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Aker BP ASA</td>\n",
       "      <td>2018-12-04</td>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>3338667.0</td>\n",
       "      <td>3347088.0</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.103898</td>\n",
       "      <td>0.276069</td>\n",
       "      <td>0.215414</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1999-12-15</td>\n",
       "      <td>20</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>12528 rows × 55 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       year  NpdidLicence      orgnr  nDrills  nDry  \\\n",
       "0      1966         20756  914048990        1   0.0   \n",
       "1      1966         20780  914048990        1   1.0   \n",
       "2      1967         20756  914048990        3   3.0   \n",
       "3      1967         20804  927533081        1   1.0   \n",
       "4      1967         20884  948138646        1   1.0   \n",
       "...     ...           ...        ...      ...   ...   \n",
       "12547  2015        917484  989795848        0   0.0   \n",
       "12548  2016        917484  989795848        0   0.0   \n",
       "12549  2016        917484  989795848        0   0.0   \n",
       "12550  2017        917484  989795848        0   0.0   \n",
       "12551  2019        917484  989795848        0   0.0   \n",
       "\n",
       "                                         LongName   ValidFrom     ValidTo  \\\n",
       "0      Esso Exploration and Production Norway A/S  1965-09-01  2004-10-01   \n",
       "1      Esso Exploration and Production Norway A/S  1965-09-01  1977-09-01   \n",
       "2      Esso Exploration and Production Norway A/S  1965-09-01  2004-10-01   \n",
       "3                        Amoco Norway Oil Company  1965-09-01  1989-04-14   \n",
       "4               Phillips Petroleum Company Norway  1965-09-01  1968-01-01   \n",
       "...                                           ...         ...         ...   \n",
       "12547                  Det norske oljeselskap ASA  2009-12-22  2016-09-30   \n",
       "12548                                 Aker BP ASA  2009-12-22  2017-12-11   \n",
       "12549                  Det norske oljeselskap ASA  2009-12-22  2017-12-11   \n",
       "12550                                 Aker BP ASA  2016-09-30  2018-05-16   \n",
       "12551                                 Aker BP ASA  2018-12-04  2021-01-01   \n",
       "\n",
       "        revenues  oper_revenues  ...  d_brent_neg  d_brent_pos_l1  \\\n",
       "0            NaN            NaN  ...          NaN             NaN   \n",
       "1            NaN            NaN  ...          NaN             NaN   \n",
       "2            NaN            NaN  ...          NaN             NaN   \n",
       "3            NaN            NaN  ...          NaN             NaN   \n",
       "4            NaN            NaN  ...          NaN             NaN   \n",
       "...          ...            ...  ...          ...             ...   \n",
       "12547  1158683.0      1221802.0  ...    -0.637438        0.000000   \n",
       "12548  1129939.0      1117697.0  ...    -0.181405        0.000000   \n",
       "12549  1129939.0      1117697.0  ...    -0.181405        0.000000   \n",
       "12550  2575654.0      2562933.0  ...     0.000000        0.000000   \n",
       "12551  3338667.0      3347088.0  ...    -0.103898        0.276069   \n",
       "\n",
       "       d_brent_pos_l2  d_brent_neg_l1  d_brent_neg_l2  licenceStart  \\\n",
       "0                 NaN             NaN             NaN    1965-09-01   \n",
       "1                 NaN             NaN             NaN    1965-09-01   \n",
       "2                 NaN             NaN             NaN    1965-09-01   \n",
       "3                 NaN             NaN             NaN    1965-09-01   \n",
       "4                 NaN             NaN             NaN    1965-09-01   \n",
       "...               ...             ...             ...           ...   \n",
       "12547        0.000000       -0.092486       -0.027887    1999-12-15   \n",
       "12548        0.000000       -0.637438       -0.092486    1999-12-15   \n",
       "12549        0.000000       -0.637438       -0.092486    1999-12-15   \n",
       "12550        0.000000       -0.181405       -0.637438    1999-12-15   \n",
       "12551        0.215414        0.000000        0.000000    1999-12-15   \n",
       "\n",
       "       licenceYears  licenceOwnerYears  d2005  nComp  \n",
       "0                 1                  1      0      5  \n",
       "1                 1                  1      0      5  \n",
       "2                 2                  2      0      5  \n",
       "3                 2                  2      0      5  \n",
       "4                 2                  2      0      5  \n",
       "...             ...                ...    ...    ...  \n",
       "12547            16                  6      1     38  \n",
       "12548            17                  7      1     34  \n",
       "12549            17                  7      1     34  \n",
       "12550            18                  1      1     30  \n",
       "12551            20                  1      1     27  \n",
       "\n",
       "[12528 rows x 55 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "drilling"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "18df09c0",
   "metadata": {},
   "source": [
    "This is a rather complicated dataset because the underlying structure of the industry it comes from is quite complex. \n",
    "\n",
    "In order to do exploratory drilling in the Norwegian territorial waters (known as the Norwegian Continental Shelf), you first need to obtain a licence for a certain geographic block. \n",
    "\n",
    "The observations in this data set are company-licence-years: That is to say, every row represents one company on a given licence for a given year. \n",
    "\n",
    "The variable nDrills represents the number of exploratory wells a company has drilled in a year within a licence. Let us first simplify this to ask whether a company has drilled or not in a given year: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "12d10756",
   "metadata": {},
   "outputs": [],
   "source": [
    "drilling[\"drilled\"] = np.where(drilling.nDrills>0, 1, 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fc3ae6cd",
   "metadata": {},
   "source": [
    "### Descriptives"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3b5ad65a",
   "metadata": {},
   "source": [
    "We can start out with some quick descriptives. One question is how the probability of drilling has changed over time. So we can aggregate by year and get the mean probability of drilling: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "e87a050e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='year'>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "prByYear = drilling.groupby(\"year\")[\"drilled\"].aggregate(np.mean)\n",
    "prByYear.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b3c308bc",
   "metadata": {},
   "source": [
    "Here it looks like a lot of variation, but generally the probability of drilling seems to have declined markedly. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "4ffdb514",
   "metadata": {},
   "outputs": [],
   "source": [
    "drill_mod1 = smf.glm(formula=\"drilled~year\", data=drilling, family=sm.families.Binomial()).fit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "7cbcc4d2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>Generalized Linear Model Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>        <td>drilled</td>     <th>  No. Observations:  </th>  <td> 12528</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>                  <td>GLM</td>       <th>  Df Residuals:      </th>  <td> 12526</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model Family:</th>        <td>Binomial</td>     <th>  Df Model:          </th>  <td>     1</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Link Function:</th>         <td>logit</td>      <th>  Scale:             </th> <td>  1.0000</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>                <td>IRLS</td>       <th>  Log-Likelihood:    </th> <td> -3293.5</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>            <td>Wed, 07 Sep 2022</td> <th>  Deviance:          </th> <td>  6586.9</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                <td>13:50:49</td>     <th>  Pearson chi2:      </th> <td>1.26e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>No. Iterations:</th>          <td>6</td>        <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>     <td>nonrobust</td>    <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "      <td></td>         <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intercept</th> <td>  103.3713</td> <td>    4.978</td> <td>   20.764</td> <td> 0.000</td> <td>   93.614</td> <td>  113.129</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>year</th>      <td>   -0.0528</td> <td>    0.002</td> <td>  -21.220</td> <td> 0.000</td> <td>   -0.058</td> <td>   -0.048</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                 Generalized Linear Model Regression Results                  \n",
       "==============================================================================\n",
       "Dep. Variable:                drilled   No. Observations:                12528\n",
       "Model:                            GLM   Df Residuals:                    12526\n",
       "Model Family:                Binomial   Df Model:                            1\n",
       "Link Function:                  logit   Scale:                          1.0000\n",
       "Method:                          IRLS   Log-Likelihood:                -3293.5\n",
       "Date:                Wed, 07 Sep 2022   Deviance:                       6586.9\n",
       "Time:                        13:50:49   Pearson chi2:                 1.26e+04\n",
       "No. Iterations:                     6                                         \n",
       "Covariance Type:            nonrobust                                         \n",
       "==============================================================================\n",
       "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
       "------------------------------------------------------------------------------\n",
       "Intercept    103.3713      4.978     20.764      0.000      93.614     113.129\n",
       "year          -0.0528      0.002    -21.220      0.000      -0.058      -0.048\n",
       "==============================================================================\n",
       "\"\"\""
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "drill_mod1.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cddf8346",
   "metadata": {},
   "source": [
    "Using our quick divide-by-4 rule, we could quickly estimate that on average the probability of drilling has declined by $5.2/4 \\approx 1.3\\%$ per year "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "30f03392",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Pr Drilling')"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "N = drilling.shape[0]\n",
    "\n",
    "a = drill_mod1.params[0]\n",
    "b = drill_mod1.params[1]\n",
    "\n",
    "x_line = np.linspace(1965,2020,N)\n",
    "y_line = invLogit(a+b*x_line)\n",
    "\n",
    "\n",
    "\n",
    "year_j = drilling.year + spt.uniform(-.5,1).rvs(size=N)\n",
    "drilled_j = drilling.drilled + spt.uniform(-.05,.1).rvs(size=N)\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "ax.scatter(year_j, drilled_j, alpha=.1)\n",
    "ax.plot(x_line,y_line, color=\"black\")\n",
    "ax.set_ylabel(\"Pr Drilling\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "27af09b9",
   "metadata": {},
   "source": [
    "Now we have a declining time-trend in our model. We can notice that the probability of drilling towards the end of the period gets quite close to 0. This can be a good reason to prefer the logistic regression in this case, rather than a linear-probability model. \n",
    "\n",
    "Let us now ask whether the oil price effects the probability of drilling. We don't have information for the oil price for the entire history of our oil drilling (only starting in 1987), so let us limit the data set to where we have information on the oil price. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "9e167e48",
   "metadata": {},
   "outputs": [],
   "source": [
    "drillingOil = drilling.loc[drilling.brent_l1.notna()].copy()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cf55758e",
   "metadata": {},
   "source": [
    "In our model we will include both the current year's oil price and a one-year lag of oil the price. The indicator for the oil price is *brent*, referring to the *brent crude oil* indicator, which is a type of oil common in north sea. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "b962986a",
   "metadata": {},
   "outputs": [],
   "source": [
    "drill_mod2 = smf.glm(formula=\"drilled~year + brent + brent_l1\", data=drillingOil, family=sm.families.Binomial()).fit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "2338ef5f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>Generalized Linear Model Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>        <td>drilled</td>     <th>  No. Observations:  </th>  <td> 11476</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>                  <td>GLM</td>       <th>  Df Residuals:      </th>  <td> 11472</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model Family:</th>        <td>Binomial</td>     <th>  Df Model:          </th>  <td>     3</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Link Function:</th>         <td>logit</td>      <th>  Scale:             </th> <td>  1.0000</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>                <td>IRLS</td>       <th>  Log-Likelihood:    </th> <td> -2683.4</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>            <td>Wed, 07 Sep 2022</td> <th>  Deviance:          </th> <td>  5366.8</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                <td>13:51:00</td>     <th>  Pearson chi2:      </th> <td>1.16e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>No. Iterations:</th>          <td>6</td>        <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>     <td>nonrobust</td>    <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "      <td></td>         <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intercept</th> <td>  114.9980</td> <td>   13.450</td> <td>    8.550</td> <td> 0.000</td> <td>   88.637</td> <td>  141.359</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>year</th>      <td>   -0.0587</td> <td>    0.007</td> <td>   -8.705</td> <td> 0.000</td> <td>   -0.072</td> <td>   -0.045</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>brent</th>     <td>   -0.0038</td> <td>    0.002</td> <td>   -1.553</td> <td> 0.120</td> <td>   -0.009</td> <td>    0.001</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>brent_l1</th>  <td>    0.0069</td> <td>    0.002</td> <td>    2.815</td> <td> 0.005</td> <td>    0.002</td> <td>    0.012</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                 Generalized Linear Model Regression Results                  \n",
       "==============================================================================\n",
       "Dep. Variable:                drilled   No. Observations:                11476\n",
       "Model:                            GLM   Df Residuals:                    11472\n",
       "Model Family:                Binomial   Df Model:                            3\n",
       "Link Function:                  logit   Scale:                          1.0000\n",
       "Method:                          IRLS   Log-Likelihood:                -2683.4\n",
       "Date:                Wed, 07 Sep 2022   Deviance:                       5366.8\n",
       "Time:                        13:51:00   Pearson chi2:                 1.16e+04\n",
       "No. Iterations:                     6                                         \n",
       "Covariance Type:            nonrobust                                         \n",
       "==============================================================================\n",
       "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
       "------------------------------------------------------------------------------\n",
       "Intercept    114.9980     13.450      8.550      0.000      88.637     141.359\n",
       "year          -0.0587      0.007     -8.705      0.000      -0.072      -0.045\n",
       "brent         -0.0038      0.002     -1.553      0.120      -0.009       0.001\n",
       "brent_l1       0.0069      0.002      2.815      0.005       0.002       0.012\n",
       "==============================================================================\n",
       "\"\"\""
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "drill_mod2.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce88015f",
   "metadata": {},
   "source": [
    "The coefficients above are hard to interpret. For example, the intercept represents the value (on the linear scale) where year and oil price equal zero. Let's try centering our variables. The brent price we can also divide by the standard deviation, so that we can interpret the coefficient as standard deviations from the mean (ROS recommends dividing by 2 standard deviations, but that makes most sense when there indicator or categorical variables in the regression):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "5bdf6a0d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Brent, std 32.07939939017523\n"
     ]
    }
   ],
   "source": [
    "drillingOil[\"year_c\"] = drillingOil.year - drillingOil.year.unique().mean()\n",
    "drillingOil[\"brent_s\"] = (drillingOil.brent - drillingOil.brent.unique().mean())/drillingOil.brent.unique().std()\n",
    "drillingOil[\"brent_l1_s\"] = (drillingOil.brent_l1 - drillingOil.brent_l1.unique().mean())/drillingOil.brent_l1.unique().std()\n",
    "print(\"Brent, std\", drillingOil.brent_l1.unique().std())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef99b709",
   "metadata": {},
   "source": [
    "Notice above that we take the mean of the unique values of brent oil and year. This is because all observations in a given year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "8c42cf54",
   "metadata": {},
   "outputs": [],
   "source": [
    "drill_mod3 = smf.glm(formula=\"drilled~year_c + brent_s + brent_l1_s\", data=drillingOil, family=sm.families.Binomial()).fit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "3d16c382",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>Generalized Linear Model Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>        <td>drilled</td>     <th>  No. Observations:  </th>  <td> 11476</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>                  <td>GLM</td>       <th>  Df Residuals:      </th>  <td> 11472</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model Family:</th>        <td>Binomial</td>     <th>  Df Model:          </th>  <td>     3</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Link Function:</th>         <td>logit</td>      <th>  Scale:             </th> <td>  1.0000</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>                <td>IRLS</td>       <th>  Log-Likelihood:    </th> <td> -2683.4</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>            <td>Wed, 07 Sep 2022</td> <th>  Deviance:          </th> <td>  5366.8</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                <td>13:51:07</td>     <th>  Pearson chi2:      </th> <td>1.16e+04</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>No. Iterations:</th>          <td>6</td>        <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>     <td>nonrobust</td>    <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "       <td></td>         <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intercept</th>  <td>   -2.5137</td> <td>    0.039</td> <td>  -63.746</td> <td> 0.000</td> <td>   -2.591</td> <td>   -2.436</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>year_c</th>     <td>   -0.0587</td> <td>    0.007</td> <td>   -8.705</td> <td> 0.000</td> <td>   -0.072</td> <td>   -0.045</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>brent_s</th>    <td>   -0.1206</td> <td>    0.078</td> <td>   -1.553</td> <td> 0.120</td> <td>   -0.273</td> <td>    0.032</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>brent_l1_s</th> <td>    0.2204</td> <td>    0.078</td> <td>    2.815</td> <td> 0.005</td> <td>    0.067</td> <td>    0.374</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                 Generalized Linear Model Regression Results                  \n",
       "==============================================================================\n",
       "Dep. Variable:                drilled   No. Observations:                11476\n",
       "Model:                            GLM   Df Residuals:                    11472\n",
       "Model Family:                Binomial   Df Model:                            3\n",
       "Link Function:                  logit   Scale:                          1.0000\n",
       "Method:                          IRLS   Log-Likelihood:                -2683.4\n",
       "Date:                Wed, 07 Sep 2022   Deviance:                       5366.8\n",
       "Time:                        13:51:07   Pearson chi2:                 1.16e+04\n",
       "No. Iterations:                     6                                         \n",
       "Covariance Type:            nonrobust                                         \n",
       "==============================================================================\n",
       "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
       "------------------------------------------------------------------------------\n",
       "Intercept     -2.5137      0.039    -63.746      0.000      -2.591      -2.436\n",
       "year_c        -0.0587      0.007     -8.705      0.000      -0.072      -0.045\n",
       "brent_s       -0.1206      0.078     -1.553      0.120      -0.273       0.032\n",
       "brent_l1_s     0.2204      0.078      2.815      0.005       0.067       0.374\n",
       "==============================================================================\n",
       "\"\"\""
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "drill_mod3.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e9af880e",
   "metadata": {},
   "source": [
    "We see that the brent oil price is estimated to be negative, though with a relatively large standard error. Using the divide-by-4 rule, we could quickly say that an increase in the oil price by 1 standard deviation would lower the probability of drilling by $-.12/4 \\approx -.03$. \n",
    "\n",
    "But how robust is this? Looking at the standard error, we see that there is a good deal of uncertainty related to the estimate, and the 95% confidence interval (+/- 2*SE) covers a wide range, including zero. So perhaps we should discount this counter-intuitive result. \n",
    "\n",
    "On the other hand the 1-year lagged oil price is estimated to be positive, and almost double as large in magnitude, while the standard error is the same size. We can interpret the point estimate quickly as $.22/4 \\approx .055$, so a one standard deviation increase in the lagged oil price, increases the probability of drilling the following year by .055. \n",
    "\n",
    "At first, this might appear quite significant, but recall from above, that a one standard deviation in the oil price corresponds to a change of 32 dollars/barrell - a big swing!\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "195e35b7",
   "metadata": {},
   "source": [
    "### Plotting results and uncertainty. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "ece6aaea",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.3530843112619095e-16 1.3183898417423734e-16\n"
     ]
    }
   ],
   "source": [
    "mean_brent = drillingOil.brent_s.unique().mean()\n",
    "mean_brent_l1 = drillingOil.brent_l1_s.unique().mean()\n",
    "\n",
    "\n",
    "print(mean_brent, mean_brent_l1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "c0334527",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "265     -15.5\n",
       "266     -15.5\n",
       "267     -15.5\n",
       "268     -15.5\n",
       "269     -15.5\n",
       "         ... \n",
       "12547    11.5\n",
       "12548    12.5\n",
       "12549    12.5\n",
       "12550    13.5\n",
       "12551    15.5\n",
       "Name: year, Length: 11476, dtype: float64"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "drillingOil.year - drillingOil.year.unique().mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "3be11ba6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998,\n",
       "       1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009,\n",
       "       2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019])"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "year_labels = np.arange(1988,2020,1)\n",
    "year_labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "d78e6ada",
   "metadata": {},
   "outputs": [],
   "source": [
    "N = drillingOil.shape[0]\n",
    "\n",
    "a = drill_mod3.params[0]\n",
    "b_year = drill_mod3.params[1]\n",
    "b_brent = drill_mod3.params[2]\n",
    "b_brentl1 = drill_mod3.params[3]\n",
    "\n",
    "\n",
    "\n",
    "year_new = np.linspace(-15.5,15.5,N)\n",
    "y_line = invLogit(a+b_year*year_new) \n",
    "#Since we centered the oil price variables around the mean, excluding these variables (setting them==0) \n",
    "#is equivalent to holding the oil price variables at their mean variables\n",
    "\n",
    "\n",
    "year_j = drillingOil.year_c + spt.uniform(-.5,1).rvs(size=N)\n",
    "drilled_j = drillingOil.drilled + spt.uniform(-.05,.1).rvs(size=N)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "a0fe9a5f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.16748796, 0.16746584, 0.16744373, ..., 0.03156702, 0.03156217,\n",
       "       0.03155733])"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_line"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "347f4de0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Pr Drilling')"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.scatter(year_j, drilled_j, alpha=.1)\n",
    "ax.plot(year_new,y_line, color=\"black\")\n",
    "ax.set_ylabel(\"Pr Drilling\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "18ea3f27",
   "metadata": {},
   "source": [
    "Now let's show the effect of a high-price scenario, with oil prices a standard deviation higher (32 dollars)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "247350e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_line_high = invLogit(a+b_year*year_new + b_brent*1 +  b_brentl1*1)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "0a2a3fc2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Pr Drilling')"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.scatter(year_j, drilled_j, alpha=.1)\n",
    "ax.plot(year_new,y_line, color=\"black\")\n",
    "ax.plot(year_new,y_line_high, color=\"blue\")\n",
    "ax.set_ylabel(\"Pr Drilling\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "243624c3",
   "metadata": {},
   "source": [
    "Viewed in this way, the effect that the oil price has on the probability of drilling looks rather modest. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "221d9a8f",
   "metadata": {},
   "source": [
    "### Simulating and displaying uncertainty in a logistic regression\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "424d6b9b",
   "metadata": {},
   "source": [
    "We can also generate inferential and predictive uncertainty through simulation. \n",
    "\n",
    "Recall, from lab 9, our function for generating inferential uncertainty. We will adopt this for our logistic regression: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "16d43196",
   "metadata": {},
   "outputs": [],
   "source": [
    "def logSim(regMod): \n",
    "    #extract values from regression model\n",
    "    nmk = regMod.df_resid #n-k\n",
    "    bs_vcov = regMod.cov_params() #we extract the scaled vcov matrix\n",
    "    V_sim =np.array(bs_vcov)*np.sqrt((nmk/np.random.chisquare(nmk,1)))\n",
    "    bs = regMod.params\n",
    "    \n",
    "    #create simulated values\n",
    "    bs_sim = np.random.multivariate_normal(bs, V_sim, 1)\n",
    "    \n",
    "    return(bs_sim.flatten())\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "97006e35",
   "metadata": {},
   "outputs": [],
   "source": [
    "nsim = 50\n",
    "\n",
    "bs_sims = []\n",
    "\n",
    "for s in range(nsim):\n",
    "    param_sim = logSim(drill_mod3)\n",
    "    bs_sims.append(param_sim)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "6b3928ca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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u36nvWw1d3x9Vu951PLw0PoLQ5tqAFui5Hva87sLXr1R9ghxmIN98L2bmOpBO3c/bkzb2cPK6VbDU1PZ8m9VXbXs+xirDvXCIHa8LzzbX7jBNEEgbx0lUp2MrbWb+59WaWPV8z3qds9RaOVXnJRqi53gThczWUc3WK13gOI/Qd3wUusDLowGSIsOT29eRqMwE0gITafq7XhfHaYjjNMa+30FWFBhmMb7Avzb3/F1Ev+xBw8D2Cp1l7V7zb1OVQxUFXhodoeO66Ei3TNFJWzvfjpD1Q7P5etON1llugOaDsAqgb3S2AGDiZ9VrHcRjDLMYXduFhsAgjbHtBQikY0ZRpelUpYV56Nnl8fQc79T2KG3H60obvfJzBrYD37LrlI9d/3RBmgft5p9+eNiWRKoUXCnrVDZooFOerzvhAF3Xmwjq5zXqF1Fop+0amDWIsqyTgkoFXMsqj1MgLQdLljnenuPhdjhArEJorSHKbSs6jovb4eBUJ3n6WohVhuMkQtf1gBhLPdjOci7m/W21xrY6NqULRHmGtMiRqByeZV7/IAqRqhw3O9srVU08y/rtWQMChdYQMCPTgBlwcyyJKM/KvzPpWD3HR6Sy+ju9HvSRFvMrSa+jee1X65mra8o+hw7uebkXjwCYe3/HCyCAmYMx580pO3SjLEHfDZCoFGGWI1Qxntx+qC54dBHrtdqu/57jLDXAMesZC4ELG7icbkt7jocDNUaU59h29cSgFgC4nqyDMuB0u+tYEr7tYJgm5b8LM8CrsXC2vlmUaN/vYZjFOE7NM7Tv+nAsiUA6KGyNWKW4G48hoBHYZcbEgoH3Xa+D/3v4CopCw7YseOU6UV/auDU+wr7fPfX9TLcLWaFwLx7BtWx0bRdSiLp9veb3TlVFrtaOzloPPcrMVjZbjl8PJER5itvRsD6eWGV4/ug2fMfFluMjKXJ0pAOldT0AcdbnX/O4HEtix+vUA6jVsVeFDEdZYo5DZYjzHIfJCI/1dua21bP6BB3pout49ZrLk8yf9tdqex760qn7a8D8vmpbX+k4jRE47kmWQXl9F1qj63oTEysma2l+Jt+q57vtddbt41zUwGczVd0WFqQjcZCMMEgiOFLipr8F25IYlnUlBklcDwDkhYIvJbTr49XxMQZpBLt8Tk9/7mkX0S970Lx2PskGOssI0oujQ1Mx1LYxyhNkyjSYuVIoLLNGxrEsJGV6UZXCmxT5qWIE8xqts9wAs0a8p39WvTcAbLkBBlkMaGCcxejaHpTW9WL46kHbdjyLbtjqfHvSQaF1/Z7jLJkosrDMa1226YeHL22M0hh918MwNecLADzbqQts5UqhkJMVEZuqRv2k8zJZcOI8OnrLznosm7lwclzWRAEMe4njbWY4HJdp7rawkBcaQxUisB140j7VSa6uhYNkjFfDAQZpjF2vC8+y63Smtg512+dZt7M/62/brlNHmo6bX6YkAahTC5cJOJrtwa7Xwb14hLvhqE7fXnaAZ9bg0LYbIFNm1rlql3zpINNmSUHHdnEvGgNC43Wd7fo9d70ODpPw3Adgmh2iasCkuqbO4/XPKlU5EpUhUwU8KVEUpqJ23/EnOp8Xqed4uBMOYAkLvpRwLB++LNAt3Hp2qHLW87XMvVNdn4uenbOesUrr+rhXGbhcpp2a7mA7lsSW6yPMs1MDumYdonmOd2e0u1XKat/1EOcZwjyHEMCjS2z51SxK5FgWrskuOrZr0vqFWavtSRuHyRiOJdEtnxGJUhhlMRKVzd3FoOf6eF1351RRs2EaQ2u0fj/T7cJREgJaYNsLIISog+rmrPU806+XqAxCC3QbQb9Zt4qT4KScKddlReBxmsByzbWdltfFWZ9/ywyOO5bE/XgEW1iwpYXAdpA75pgW3UPz+gS2sNBzPPjSWSro0jCDjRoo/+9kvYnp+0hrlIMkpvhhz/FMX6I8ZlUoJHmGg6LAlhvAKQcLwzzHDa8z8b3Om5BYxaLzvWzm1fQ9Ps6Tuu90ngOfzVT1wziEY1nwLRtjaWHb6WDb65jnd4F60DdWGWKVm6UEGohVCt924AgbEAWSXOGV8RF2ve7cZ8NZ+iKb4LX7yTbAOiNIVSOQFXm9Dcb9cIyu46HjmI5ZlZ7p2x66totYZcgLMxLXd3zsepPpS3MDbL974TdA8zwMyzTFTOWAEOjY3sQ6k+qGrBqfqppe1cGoZrGqhmmUmcqxzRSonuOZGc7CpOpEeV4+AAKM0hi3o2EdGNwI+ks9XC/adADjSQePb+0jLRQOkhAd6aDn+nWBrQIaB0mIXGsIALlWZiuBqUZdQ+MgHqNjOxgkCplSOFBjbLk+BMSlzFCvkrlQPbw8aWOQxGaddUt62rz3SFUOt5zJrFLEZLlGKbDd2QNMGvCkjRtBH0IIHCWRme2fql542RW1px9St8MBtNaQVnMWyASHy6ybmm4Prgd9HCUhDpMQ14P+2WeaMxuJypCovE6pvRaY9YyWsKC0wl7QqTtapoMbzEx7O88OqC0ERlmKSKXo2B4EwnqW6KqMsgQd20VguxhnSRl8l2sLL6lz4kobXddDrlT9ne36HYzSGEkxud7sLN/HsvfOss/OWb+ntFp54HLZY2vrYAuIiUql1Wt1bAd5oTDOUtwNh/AdB46QeLS3W79e8z6yhIVtb/m063GeYMv1cZRE5fGYgou+tNFzvfpZsh/0keQ5CpiMietegKMkRKrUwl0MOrYLX9p1ewEAaWFms9q+n+l2odAa+0H31BrPZQdHTrczNjq2M/F6zeOpnpEdxynX9Vvl2tYIAiYIO6k9Mj/dfd5AxzKD4z3Hw8vjIwTSqZdc5UWBHS9Y2FbP6xOsMhhftS/V9wyYGcGq7zTKErwSHtd9DMCkt8uyfS50gVGW1/0k83x2IIXZM/cgHmPX65hMHXE6y+C8JhEWvU51X5rCWRlipcwAUXenfo22e3xc7tkc2O65Dny2paonSsGChZ7rwWlkpEUqQ8/xcS8awZMOthwfnxkeYJBGeF13G650MMpjBNIUCLvMZ8OD6PP3kz8A1umktc06+raNSMWwraAOajU0eo6Hh6p1JXNGmK96v8cqzS0tHyaeJSFhIdcFXClPrTOZ18EAZm9/0hwN3/U6dSGDqkFMVY4XBvdMcQXpIC0KvDC4h0d7u9DlebrKEvLzRtmKcrQ8LxQERLmfrzRrboqiHOlP0bHdidFMIQSkVRVakHX6Uphnc0vGn6dVMheaD6+OW8xMT5v3HkoXZfET3QgUJotltG3HUKfOlsVVADOCu+0Grb97VeX0nfJh2VyTZ4qwiKUCjun2wLEk9v0e0kKdGmlf1La0XbPVkoCqunN1Le56nYXX2zJpc6tqXlMawHESYtvroCNtpEphmMZ4fGt/5t+fdYuJRX/f7ABVqZV6iRmd89a1PRTldiEV33aQJHlr3YR1LHvvLPvsnPd7q2aT3I2GdVp+c+/06WNbpqPe/JwawEvjIxQwQc1+p4dRltQDtfVrLpFp8Wp4jFSZYNESApFKseX4EEKYwVwAge3imt+DKAsZASaQuR70J45R69N14tv6BW2BPLS5Npqa30/z81Q1D2b97qzPOn3PVG3Tbtk/aF6TzeOp9nH1pDPR50gtxzxHpQNLWAvT3ZcZ6Fj0vbnSxn7QwyhNJgaMmssMFgbPU4H2Ku3CyXZEAq48WecthYVxfrK/cSAdZEWBwziEEIBdHpvbuFerYkXNWcgt10eYJbgfj7DtBjOzDBZNWCxr3vl2pSk8WG2b5UmzbVbzXptOOx5lCXKt8OLoCI/1dmBXywAEsOuatriqaXEQjzHOk7pPsmj9bVuqelYobBUBBESd0VQtO7AtC/tBD4nKkRUFtlwfgHkO9Fwfj3q7sIWpHTOrEObnCwa2V2iddZxts44d24FKzVY6jjTV1UzpfWepB+J5zoKs08mr0twcIbHrBfXfb3snn6FpXucHwKmGKVEZxnlaFo/Iy7+x0He8sqiCeRC9ODqEJx34tnk/vwx2/uL4Lh7r7dRrF++EJg1s1ib0l72X2vR1dBCPAW32/qwq7XUdD175wG52tg7LNZQA6sZ129X1yPplWHVgpVkAo3mum7Pz896jqrZZbU7vWBZSpeDIyeIXYZ4B5Zrb4zSC1hqDMoV5yw1gl38/fa9c9UBRz/FwlIS4Ew1gwSrTwCR2/GCpCrrLtAfNTp2Aeai/PD7C9aC/MEBd1PFfdP8sSptbR7OdDGwHcVll3pES/XJmq81ZZ+eX+fsHpZDdrJnIR3u7K88SzbLsvbPss/OstRKmr3MB1HUZqgCg7dpY9Nxtfs5E5bjmdev2KLDdesZslYGwg2SMUZpCWgKxMhWTx6kJyB/t7uGa10FaFBjnMSxhsqOqNfhHWQSlj/Fwd6e+roQQpzrIbddd2/38aG/XBAVLDHis+h0tumeaS0ful6/bc31zP5fHkygzAPy67g4SlSNWGTqOOzGYuyjd/bwGMPe8LjJldnWodreoButWaV8W/e50u1oVz7KEgAVR1xzpOi6iPMNhMsau18W2F6Dv+nUdj+Mkwq7XgdK6LuLZvA+mZyEFBDrQeHxr/1wyIuZZ9OxIC4X9oDcxONe818Z5glwpRCpHmCfoOwF6tgetzbpvV5rlR9vlvup5YQqVaWgUukCYpmYXj8JkgaVq9l7TswqselKbyZ6pZQfjPC2D8bKeQVnNXGnUu4FUkxVnyZi5zL7rRdm8I34NWScFo+rkVA6TMeI8g2VZeKS3A78s977KnnvnVShp3Yapehgdp1GZUmPjsf4uOrbb2mlY1PlxrZOCSlrDrPXIzX5uN4I+NNB6vmOVoTuVcpgXOeI8w7BMXzLFrBRujY/whDzdUF92GioweR250kZaKPQdD+NyCxUI4OHONgCcSqtu6zRPB3UX3bit2nGvGt9xnmCcJtj2gvq6n3Wuq/fQ2jzI7schHCHQc3140sWwXJuktUasMrw6PoZvOzguzJ6Dd6MxrvldbLsB7kYjHMYRAinh2Q58aU/MGD4ogYiAhUEWAULgmteZqIo87wG2THtQdeo0gKMkqkf1B+UAwDL3/HTnL1U5DpJxmW5lY9sNTq1hnpc2dx6z4VWnsuo8APNnR8/auV3m79u+jzBP4UlnothZ9Xfn0SmZuc71gusOLHvvLHssZz3m5vfjSLM3qF1uP7fjdda+rx1LYpBGOCx3MOhIBztegJ5jBkvXGQg7TiJYAhjnKWRZwOm4CHGQxug6Y0ghsV0OeIdZip1qDR9MdeSjOMRREmLf79Wd7Fm7GExru5+r+3XReV/1O1r6ntPANb87UVTPZIGdFKH0pdnyrznAXVnUzzjPAcxZg3XLfNZqR4nPDe9Da2DH79TbwlW/WxUZbPZLbo0G2PYC7JS1C2wIFLrArdER+q6HruPVAzk917QvgzTEYRKh43i4HpxsEdS8DxYVzKpMtzFZcbbCgKM0xq3xEbQGfGkKrk0HlvO+s2pbLEtYyAtTJXucJYDjou+aIpyWMOfvdjTEQRLW10/HdjHKVtupoe26bxZYtYSFwDHXxbjc+aRjnzybzFr2CFm5HzEAJEWOvuOvtQXcVfRdL8pmHe1r0LLpUJUqFa8abd1xO0ikgmebUbK1izydQ4dl3U5etUdX1/awV6eImr25rHIGstnBWtT5UbowaYXapIoCZg/AURrjMBrh8Z3rrVuf+GX6sW+dVBqNcrMBvS2suhPgSYkwz1s/11WloTZnMTU0XhoeQVoWPGlSro6TGHvB6a0h2ir+3otGF7p9x6JjmNeBaja+eVkwbZglmLVtU/M9Xg2PMUpTeFJix/VxlIaIyvTsHb+DQRpjALPfpCzT/WWZwicEMEwj2L4poARRYJzl2Pa7p2YMr7qi9kEyRpznuB70cLPTh9IacZ5jlCfouf7SMx7z2oOqg3CcRuX1btUB4PSa42VUxzTKEgRlsZuj1MwMNF/vomfDVx2UOOvxLL3tTOP7SFWOQRpDiqzuwI2zBBp6bqGfZS26Pi6yHVvl3ln2WM5yzM3vp8qSkjAzq1Ge4rjcJx6xGVBt296mjQDwmeF9dKSHrmUjLgtC/n+7DwNYfyAszFPI8n7MCoVRnsCzLPjSQd/xkWuzzv4gMefYkRId2zNrbj2vLlo03ck+z+KRq/zuuls1tT2HA9uk997snGT6zPtci9qC8xrAnDdYt+izpirHrdFhub1jDE9K3I8KZEWOh4KtereH1n6JAOI8w67v1kuzhlkCVZiiSMM0QiJyOJbEy+MIe14Xu14XXcdHXiiEWYJC64m1qq60T+8g0LhHqnuirY15ZXyEwHZhlXvQ9hzv1G4VM89hGuP/HrwMDZNybgkgSwv03cnAct53NsrMIPmwXOvqS4koz/Hy+Bg3u1sotAYE0JEutl0fe8IMbL0aDuBJe62dGmZd93uNcyStctcG26n7Zr50IADsel3seua+B4Brfm8iY6rt/qmuuel26qqXUJ2nzTpagivLoiHKnij0UK3JWLfQ0Xl0WM5STr1qUKoU0RzA/dgUMZJCTHSwzPY1ef36052fg3hsitOUleRyrQAIeJYFDYlRmgAapzp9N4I+XhjcM+fDspAWBQpdlGsBT1KyTBVX2Vrc4arTUAHAtWxseWY0uqo6q3TWuu5iutMc5hn2g96Fbt+x6BjmdaCajW9e7m2stMYoS7A7Z4sGV5p1uInMUUDDsx28MXgIeaHKfeC66NkelC7w50e3sef16oEMDaBvu0i0SReTwsK+34MtJV7X2T41Y3gZM1vzHCcRvHLkGDAFkTwpcZxEuNnZXuoBtqg9qDoIzYd5VVBjneu9OQPsVGuYC/PzncYa5oueDV91UOKsx7PSDGXZ2fn08V24ll1f+8PU7C3qWPZEoZ+sUHhxdFgPBi47g3uVHZyrvnemTa+D2/U6pqiSznGcFHW2SKwyvDQ6rDudiwYWDpIQ+34fBQpAaORKI5AdHCQhuo63VoXmruPhfjxCV7jQWuM4ico9TF0cpxF6jg+tgTvhEI6QkMKknx4nEbqOC88ys5bTfYir6tQu2qpJa9TpzoDZUaGyMKtrif7Oom3eTCrv7H7IsuYd66L24bBccuJaNrqOC6ULxEUOO8sxtk92e2h7D7fc4xdAfW2PsxiAWaq17QY4TCIcRCE6jlO+t8Z+0EOUp3g1HJRL3k7Wqu417t/RnIyqg2Rc1zRwypTaRCnkRYzrQQ9KaxwmIfrlEqp5UpXj1vgIhQa6joMCJmuha7smm7GxJdq89v2wnIG1LYkwTzHOUsRFhsB2y20UzbZUu15Q1yTpOZ4pZJmaXUhW3alhnul2OLBd7Ac9hOVnqgafZrWNbffP7XBwagD01fAYnnRwLx4hkE69DVh1jq5yR4B1MbDdQNMbkgMn6XJXmSO/bievSv+zy1GzatYnK0zFxekOVlXEZlbnZ8/vYpynOMjNehGhZb1PmittaKB1Vqnn+nh8ax+3oyHGZVXkp/cexu1wgESpuiOZF2YksO1zPShpqPt+zxR/KEdf9/3eUisRTdqZGdWr1q1mKofGcvu1rmvZgZXmA7p6kFSjo8Dic73v9ybum7ZtKWwhEeZJ/TC3LQtpriCFSTlyXXMdVNdUW+N/HgNFF3Uvt3VyCq1xPx6eeq9Zx+BaErfGQ7PnnmWh4/gQZUGNZa73WVsqNDsH1ffarN4dlilZVRrhec+GrxpYnXV2ftVshRdHhzhMTBV8aZ20QYM4mpjxyQqFQRqj0Gaf1FVmcK96cO6iZ4VXMf39CAB9x8dWeX1W7UaicljCMmnFtgeUKbzHaYQdr1Onmlb3UKwydG0HlmUCiKxQGKVxvVXbOhWaC12gY5siP4kyS3F2nADSMtv6HMUhlFZwLRs7fmD2QS8zLY6SCA93t9ZKYbwoswZYlNaI8qzOWrNgCuwk5RpVV55P9fRmW1ClgjaDtFGWT2xzs+4gzLxjbavkq7Sqr5nPDe9DF4DrSEhLmEwOAOMsamz3Y+qWTL9HYFfFs05SzcMsRdfxy0FRC3t+B8dpiEhlsMp1s44lMSwK9J0ANxtLcOoB3monjRhmJ4bynFcDEffiEYZpjF2vg8A2ewe/Mj5Gx7YxzrKTyY3CDNI+sT25PWVT1SYeRGNoFEgLyxQJK0zWnioKbC+5nKL6HhxL4pHuDj47vI+ukPBs87zPCoVMmzW113y3Dr675fZZ15zu3J0aVn2et7XDflknZV6xxGaxO6ssOFgVu4tVaPZ4dhvfSZoikWYf56wocJiEdSr7VfRdz8OD8fSglcxqCIHZFYEvI7hdt2Jp8waqtiLKy5Qu2RhtA6a2DJjxmVxp47HeLrJCwYLAKItNWXoAXduFKabT3lHruf6polCOJXFrfIQwz+GXxWQERGsn4KrTUKvjLXQxsa1Ttc5l2nQHSQoL9+IRdsrUJFuYc6WBC72WVt3H1hZmhuIwDpED5boWtfLsWtu2FF3HwUvjYygNeNKqq4tW67WScpS7KpxxEY3/Wda77Hgd3I9HM/evnj4PWaFwLxrDkVZLZsTpqqDVz7ddHxaAu9EQiVJ4rL9rtpZacL3P21Kh+k4BM1gHmDQrAQGtNTJl1hO9ODrEvt/Djtc59xm9ZQKr5vVqZpB0OWt6MctAqnNm9jw1e8cep1FdxKQ50AKYDqSAQFAuUVll1vVBGZx7EMz6fppF9wAgVCmiLIUWQNfWOEwi6ELDcyTuxwWgBfaDbr1m3Dx/Tpa9OJZEYHvoucFSWVdtQV/HdiGCPsZZikESYdftILA9aKHrZ8IgS/D67i52/S4OkxCHyRhhlsKx5MyZsXUH2M46MDdvqybA7O15WPY1+p6PVEkcJGPc7Gyf23O4bgtilBVqc4yyFI5lwZP2qUrx65h3rK6crORrCYGsKDBME+wHtlluladwbRu+bWPL9TFI4rKPJOvnRbXGtvkeAgKPdncmAvP9oD+xx7iAwLYTwHOcuiI7MH87p0rz+8sKhcM4NNvq5eZ6G6YJHGnDsSxAmOfGtaALpQscJjG01nUhz6bmfvTV9dV1zIzqURphB4AFgXvxEDtut9xqaPFyislt38z3GxcZbGkmRgQ0oDUOkzFsKeFZNsI8xb1oAMeycT/WEMKChEDP8Sd2aljneb5OOzxZ7M4UBWsGqtOVzsdZYvZGh0bP9c2zV5sB/0VbKD7IGNhuoFkNIQRaRzjPmkK2ygNqnYqlzc9TaI3jNEJSlpmPVTZRyGXZDpYrbTza3cGt0SFyrWBDlsUQTIXgVTpqPdfHE3J/qXPwIKTSrfJQn+4gbXsB7oYjvDI+wk5dzl7XWxBcRDriOvvYAmVla9fDcRrDlfbCmY5ltqXICgVVmAEQKcxMTFFoXA/6dTn+qvBIVRXxIhr/s6SD7nodpGWlz7b9q6fPw3ESAUJPjOwCwO1oaD7n1DE0fx7YLnb9Lo6S0KyPtd2F13vbZ9v2gjolfMcLMEhjxCrD9aAPwGxnNUzN3225Hjxl11sGrXJvnccseNv1aq6B9QZ9lgmkq3MW2HZdIAjldlW+dNF1XLhS1rMvicogtGnrKsvOuj4Ig3MPUnXOtu9nutOZKlWu77MRqQyulFBCY5AmeKRrzluYp3Vw0LXdequdatlLojI83t1f6pjCcisWpYuJ9YiuZePG1hZeGNxD13ERqgzbTge+lMgLsz1alWq463UADey6XdiWBSnEqXZ32bZ5VsXds1QLH2VJOZBj19vQVNkbx2mEbtkvEBDI8wK5ULgXjer6GbOew+tcW+M8QZimcKQ0BZWSEHGeoe/5Z742Fx3rrfERjtO4nEXV6Dlmr90wT7Hrd5DkOY7TELbommw0YePhbqfcBSJB1tg6Z5nZ5ek9xm90txDmWev2SVmh6i3zBGD2Ri7P71E5+LPtBRhnJ9vlQVjYcX0cJhGGZR0FCwJhnuNG16uXFVVB2KwtllKVl7P1OQLbhtJA3/YR5xkilUFC4rH+5PZC856f099Dx/aw7/fK/WsVXh0P4FkOtAaiLMOdbAjfsjHMEry+34XWGlYZoNuWNXFdrPM8X6cdbr6PK6XZEhSiPqfTlc6zooAF1DVKqr3JQ5VhR5z/oPFl2bwjpqVHkYGzp5CtEnTMK4KwaC+3vXIE+W40hC8dPBT0oXQxsVi+urEXbZpe6bk+nti+Xr+uFBa2XH+pWaXWY1xlFuYKG4NVguvWPUuDLv7fcQilNdxyX71qtK9ZtGKZzsEyv7dKoz/92Tzp4Imt3lKNb9t5md6W4jiJYEsLj3euI1H5xPqtKvNgXuGRVTpN8373LOmgrjRVmme99vR5ULrAvt+bGOip1pTticmCY20/d6z2fW5nmZVipRwNq5yR2fO7dUbEC4N7GJYdu2oLK09KRKpYaaDlvKo+zrpezd7R9oUEY9U56zoeUqXQtV1EeYpxlsC1bLyhf60uAGKuSxsd25n4TlcZFLzKwblNqM453emUwkKoU2xZPsaZ2UJFw6RUVvUZ0qKof9+Vdr3s5TiLUWhd74ddpdPOUrUbFkS9PKa5HtGVNq4HfRS6gMZJ8ScAeH1/r9wj06Q+AwAE0G8MYDXvqWXa5rbvq6q4u87AXPV6HdtBXiikSiHJx9jyfAiI8v5vFruxEOc57sRDeJaDF0eH9bY9rZXX17i2UqUghBmwH2RxXfcjzfNzuTaba+hHmdnHVUMjzFIcxCN0pAMIgbvRGFlRlJWrzWBkqnIcJxHCPEOkUpPNZPdxmIQIbKf+nKOsfeuZiewTmLZmeo/xvW53Iih+tLeLg2SMw9jUc7BgKvKOMyBTCoHtYNfr4F48wt1whFznUEWBpFDlchNgtxzMTAvz+660Mc4SSJzsvT49oN68HpU2+9H34ZW7GviI8xR5UaBre3isZ3bWqKzaF+46bjl7be6VqgbEw/427scjWLAwzGNcD/rwbRsHcQhHW+g7/qk6Lus8z9dph5vvU2U/mbRu8zmmK52L8nu77pkBZMeS6Ls+tkXnzJkIV+nBeEp8Hlt3ZHqZUWTg7ClkqwQdZ+2MO5bEzc5W/V4ATi2WX2bT9OnzeaOzVVf9y8qU3GahqeYo8zhP65H0bS9orZ58Wc4aJC3TMLVdM5YQeKizNTFbB5xcS6uM4i/ze+vuY7uOtr9tBgRVkOdKu34oTm/3Muv9z3PPwbPey4vOUfPfqzTFJqWLejBp+hhm/fysBZM6tjtxzVbnyBKiTks+TiJsl8XyqiByWedVFGnWGuV70Qg3O1sXEoxNLNco94csNNB3g4m9N6vPsVueu2W2amlzlYNz51m86qJmfk/P7phKqaaQXQxdLlWxyzXjgKkJADTWT7o+XGnX7UD1PS26bqplAKZoWPt6xCrwti0LO24wkVVQvUaosoXFYtatQFxV3A3WCCyar1fV3UjKLege6+3iMAmx7Qa4H48RSBupUhhkETKl8XB/C1kxO9hc99rypI1xkZh9zMuf5VpBa4GjNMQ4Tyfuw3WM0rhOOXYtG4kyM7GOZUOUAXxgO0iVWV9cpZfu+V1Iy2RrXJd9bLk+7sVj3I1G6Ls+OraDbnktTn/OtueQgECuCyit5wZT4zytizGaIlAS9yNTxff15UDb9aCPu9EQr46H2PM62Pd7iFWGzw0PENgmzbrnnCzteml8BA3MHFBv24/elzaU68KTNgoN9NwAXceFPTXJs0oab3UuUuRQWiNUGfquqSruWBK+dNCRDm7HCjteB2GewrUsFChrcpSzttX5diyJuJwJz8qZcE/aCwtjVWnkVRs2yhK4Kp9Zff3Us1WYIqxCANte51Sl857rIVM2BEw/5yqycy7C6UV3F+Q//sf/iLe+9a3Y39/He97znrm/++M//uN48skn8eijj+I7v/M7kSTJJR3l5apupERlGGcJ7kQDfPr47slI6op6ZTXFvFDQWtdpkm1rQav3vh0OyrVbeetrzlrn2tahrG6qplU6vG3v5ZfrFG50trDnd+vCUrYl6xHUUZbghcE93A4HeDU8RqELuGVnfdZnqz5/9buJyvAXR7dxOzw2W/sICwdRiFfD45nn5iK1Hd+nB/dwa3R46jNN/+68zz1t1jVzI+jPvJaanQNRFlCpGvGmZX/vLNfNstfxvL8BzMjqjc4Wrgf9ibWKqxzLsp93md9d5V4+q1WvgXnXxlneb/rvq3O043UAy1RwLbTCy+X2FonKVvqcq7Rl87Rdr4M0hiftpb77dTTPmS1MmtuuF8zsTFeBl1UGE1XF/AdlxnOeWd9TmKcr3evrtIurtCfV+kcAiPIELw0PEecpbna24UkbqtB1Rz7Oc3Rs99S1vkqb0Tw/vnSw63dgCVGnjHbd01kZbd9/9W8Pd7ax1QhqgclaHbfDAUZZgnjqPptuD9u+r6ribrWf/N1oiHvxaOZnmv581etVKdM3gq2JDvxxGkFA4ziNcZSEsLSF60EH0jJrhZvnsPmd3o2GKMpCQNVxDdK43i5lFpOJ5qPQRdkOFVAa8KUN3zLBddX/WOVZVKlSji1h9gM3nzFGUeh6be9hHCJVOe5FJoW3up4EBHY8U8hpPzDFEQdpBFsI5EWOQmscxmH9uZvarj8zy2vXfa55bUZV5wA4yVwoCpNBUAVevnRws7uFrXKAJVEZurZrUoktq94OqOf6uB70sed3sNPYh7d5vTXb3p7jIdemUFpgORNt4p7XXfkZ1XYuOrYLx5J4uLONa34XDwV9CCFQAMi1xn55D5qCUagHsqo6LtX5di2Je9EIqVJwhECqTNr89KBR23VRtWECwO1wgE/e+xxuh0MI4FSbVj0nojzFQTQGtJmgebS3Ww8OV/f/jc4Wbna2caOztZHPiXkuLbB9+OGH8c/+2T/DN3/zN8/9vd/8zd/Ev/t3/w6/9mu/hueeew6f+cxn8KM/+qOXdJSXa5SZvQeHZQMclBXPbo2P1gqmlu3MrPrAvxePcDca1o3VrI7+WTvjywQ4zYdeVZBAwOwLOEgjjNLUrO9tdBIOkvGpz3trdAgNXTdisTIjc4XWcKSEIyV82zywzqtzuqyT6qdRXSRhmJrUs1Tlp76vdTpHleY1My73Zcy0STmqNiSfvpaWCRBSleNuNMRBHOKovG7afg9Y/7pZ5jqe7qiO0nju35zlGl4lcFr0u5cZmMx6r57rr3xtTGsLFKqA4DiN8dnRfbw4OkSksnJN3cl3V52jqkplWuQ4iENkWmHHDaC1qCuhLuOsA2+VtmskVhm23clR7nWC5llWuR6qc35YZp7sep2N66xMP3Pi8vpYJUhdtV1c9bmYqhy3wwFuh8fIyoJyL40GeGV8hC03wF7QgW1JXPN72As60MCp722dwZbm7L1Ze2ohViZlt3mszQ7srHoF09dxlGdIVFafg2rvzChPZ7aH0/dVVpgKxffiAf7f8R0keQYLApkqlrpf592nqcqRqAyZKrDtduBLB4nK4EmJjm1m1Ko02qxM625+p1JYeDU8xp1oCK01XMusPZ5ue6a5ltkurTquvCjgCIm+G5SzdALDLMYoTVYeXAbKvqAGPFldq1a5Lrr6Ts1gq2UJ9D2zU0RS5PX1JCDq68gUBLIhqwrz5Wyv2ZKmUTixfkaP6/sMWL7dqr6nUWYK/9mWBWkJ2FJCa+Cl8VE5oGHWou76HcQqg9ZAz3Vxs7eN1/f2sF9OWACTgdlhPMYr4wHuxeOJvaSbA3x9x0Ohi7LA0+nBm1Wen9N9y6MkxEFsBj9cy2wBdJxEyMqlIJYlcD3ol3U5CqS5qTieF8WpOi6jPIFtSQyzGPeTEEKYbMRltsKsUqCPksgMCkgXsUpxlEQTO3wAJ/d8mGemaFxZQCyw3Zlt36J2YhNd2if42q/9WgDAJz/5SURRNPP3PvKRj+Bd73oXnn76aQDA933f9+Ef/aN/hB/6oR+6lOO8LFWj0rZ2LMzztYv0TKeQVQ17Vqi6sFNzUf+8ipnNh4gnJYqiwN1oiL7jt1Y6PuvarGUWyzdTLZoFCRzLRl6YLXnGWTIxing/HuOa352bKmVGPk1KYUWW1XDvRqe3QbkoJ99XjkDaKMpS+H3Xhy/tevse4OT7Ouv2HFW6S6py+K5fn/tZa3IWpck2U0gtiHrEuFovMx1IrHvdLEorW3btV9t+n831RFX6e7MIR9uxrZI+vMzvXmY66Kz3WvXaaJqVbl3N+ndsB3m5dq1qa1J18rrNc9SxXVzze7CF6fj5ZXrdKgXNzrVS6tT1epaZ/pXed8n1iQ/y+tR5Zj1ziqLAtaC3UgrprHZxnKdAjFNt+qppqqMswTCLkShTgbbv+fBsVaYayoW7AQDrLR9qbgEzSGIIIWAJoGM7K33XbdexI2UZpMhyQCGHEMCr4QD7QQ9d2zvVNk8Xf7wXjwAtsOd1EecZjtIY1/wOrnd6rfdre+Gp9v1hqzoege2adHwAUZ6aehBS1m14Xr7W9He67QW4H40gLYWe7dZp4tuuP/N7ro5v2wtgletcx3mCR7vbdb0OIQDPslEAK1chB6pZeJNaa5ftSM/xcZxEGGYp9rzAPJdUgW7gYM/rwpNOnVrevI4ilaHQGgfJGJ5lo++YuiKxyuoBiaqdqNZZ6nKd9q7X/oxuU33vicrglwGdUxYpO0rGEBDo2x50gXrWf952eXW1Y5XiXjhE4Ljo2l69R24zYJ2osbHdXmNj1ednXZxMA4dxiKqgWgFTP6HaxgcwgwU7sgNXmqKVGiZro62Oi5llN3vEdvwuqi0jTVuUtLZFzetCAHglPEaqFCKVoG+bXTtsy8I4S+q1+c3P3XM8uFZnYmvDTd2Tdh0P3JPuT//0T/HVX/3V9X8/88wzuHPnDu7fv49r165d4ZGdn2bHvwqkmmvHfCnPZaR/svQ3cD8KAWHezxZWHWw45Ujm9EU//RDJigKuZcORcuaD88zrHxcEOM2HaKqU2c4EGruuWUNbFAWy4mS0txphnZUqVbEtCQ3UhT4AIFY5RkmCvaB7aZ3E6kHsScdUtCtL4Scqg2PJ+gHd/L7OY231MkFi1fnQ0GWBiPYAoZlCepiEsGEKqBwnUbn293Qgsc51syigb2ZE5OWAQKbVxIBG236fzaBt3YrNiwKnB6Hy7LLWXZc26++qqsqjLDEdactCXhSIVY5+GfTulQ/n6XPUd3zsBd362p5e/zxvTeV5FkWaN4AY5RnSIgc08Ghvd+XXblp1jeh5rk89z+Nc9nPMeubEOoU/tR5tUUetrV2sZn59aZ+6n1cdIMwKhTAzM3TVAKsrJVShcZSESwW267QD1XX84ugQWui6I1sFdG1t9qxzPn0d3w4H9YzdYRKatHfbQ6QUHDHnNcr76n48hGvZ2PYCHJXtvSq3/pteLwm0D8TM2x82S0K45Qz8jtfBjgfs+13ciYbolzO1zUr1h+XvVxxLoud5iLKsTuHe9Tuw53zPzXuqqgL/ueF9jLIUHcfDrt+p63JU66ir73PZQMKxJHzbwTBNyr81fcO9oAyElDLFovwAu97p420OdlSFi7YcH1IIvBoew7Es9FwzMFCt2bQtM7lxGIdm3/By0qPv+Es9h6rvfZyniMrq1Q8FWzhMQuRKAUJAWhYe7e/iOInrCZW27fKAk60qhQZ2vG5d1Gz6up7XVzjLmvrqHI6ypO4HKmjseh0cJxE0dF2lHzjZQvFmp3vqvZs7NBzEY3jSNhWJhagHLu7FY1gwmZrz+hb34hEyZQY+EmXhIA2x63Uhy2UIbX296bYvK1SdcVBNcFW/d5UV5y/KA/dpRqMRtrZOHgjV/x6NRqcC2w9/+MP4qZ/6KQDA/fv3L+0Yz6rZ8T9OIxTl6JVZN+Gh73rnMtLfbJCPkrDeE2yQxfClA1uIenaz7eaoHvTVQwQ43ZFcxiqNzbwOY7MoUhW0FEBdRKHneGXaiD2xEL76fNObk4e5mY2tflfrApaQdVrZURIhKPdvW2cUdh3VOe85nkklLMxYxJ1ohDDPcc3v1KN41fe1bOdo3Sq884oqtO3d2bxuqqJdeWG2wzjPQYFFAb1JHQqRlql2otxDDxDYxUkRlXn7fa4SKKwSOC37uw/CtifV99nc2sEWJuVsD7MLlM26pqqqyiZoscqfC6RlKljVvpw+R/Mr/S4zCHFRs+BVcHFrfARdrb2bmmlY1Tqzr2fN3ljHouNc5XPMeubciYq1ZzaBk3axGkCu7metgWEW4ziNyjV1ztLby5n2R090okzqp2j9/TbrDrYsmpVZd+a+Lb3UDNRkOEr1zCJJ1X3V/P6cMhW2urfN+Zk8n+Zz53g1CpHkGTzbwZ7XQVrYrcUPZxU7NBkT1qlz2Pb7nuXA9WxcD3r1z6oZ3jZtOwc81tvDnWhYpz0DQKIUrnsnz9xVBpfNbGyOvushzjOEuZkpf7y/j7RQJt22bIOrYlqOZWO3XNrRHOzwbRtJnmPH7UCWM8zQwHW/V6dIZ1qhZ3vmGV0Wo0vLGcllMnGaz6RqW6G6AFqh62UszbWxpkqz3bpdXrVVpQZwkJjlZdWM7q7XwTCNEZWzvvN2YFjUDs17llbn0KzfNlmAu67pW5oJqMmtK6fb1VnPlqxQ2HYDHKURUJhnndZm8OvxrWtz+xYaGtCiXrsb2A6GYYJjHSFXqkxZt08NojXbvjjP8NL4GHlRYNvzcSccwrYs7Deuh03J6FnWA/dJer0ehsNh/d+DwaD++bR3v/vdePe73w0AeNvb3nY5B3gOmo3/67o7eGl8BKUKs9+ke1Ih7rzex/zvk06ka0nkuoCEGfGZtRfnecwErl9eP5/Y/qcq3FD9bbUdyEE8rlNpBIC+48ORcuIBB5zenDzMU0Qqw+1oAF1o9F0fO14HXcfDuC7g4+J60J/4vBfdSayq58XKbDUzyCMMshDQZu83CwIvj48gRVlUJ8ZEsD+rc7RsFV6tcWpfurbgrmO79bqVts9QXTdV8Y9qdPM8G89FAf04SzBIY3Qct15vlBcawzSuq8Uu2u/zIis2L/rdByWttLomq31kBTRuh2YZxXEaYd/vtVYPn9V+VFWVq46vLUQZEMhT7UuVCj0q140dl4X1mtt/TWcKXPZsZSUtFPYbSx6A5bY7m2Wdz3MebfZ5H+eqn6MqMlTtzypgUkjzxnY5q8xsNtvFruvVM7/VrKQs912v1pNOby836z16joeu49azbACQqgKebfZlXta6gy0aGvfjcVmR1qpT89tScJe9F6bTS6M8w0EcYs/vwrMsRErNbYOm2/5XxsdQuoBXBuICYuJ8HqcRXhkfw5dm0CorCtwaHeHh7nbrs2V2m99+PG2/70pZb3m0zLW0TDC95QbmWYL1qstW1+pBMsZYpYiy1GQt5Cm6totRltfZRQICQotTqefVYMee10GuC4yzBPfjMXwp4TnOxPkZpymUnHzeW0LUlbpnWWaG3ZXy1ABkdb72/G4dYE5vVVlojaM0qmdLBYA74cAEokKiI525gdi8a74HLPUsdeXJVln21PFPhrXLt6smMC7qQf6q77Dl+guzUMyeuAKDLMcwTdBzHDP4UWRQukDP9sv06EnN6+nF4QEcaeNap1e//7bsYJyn9d72l/WMvCwP3Cf5oi/6IvzJn/wJ3vGOdwAA/uRP/gQPPfTQayYNGZhsKDu2izf0r+GovLG9sgrweXRcJx8yJ9sOBLaLnuPhqNwrrZk20XQe6ZKLGpvptTVpoRDmaVlMoUAgHQghcJREJmWoUUK9reNyo7PVeu6av6dRBjdK4ZpXpZEUpgCMF+ALd28CQF10ommpkvHJGMeJWUe+43Ww63WW/j5dS+Kzw3tQhQnUh2kCaVl4YmcfGiaVLsoybHk+urY70UDP295nUUen53h4NTzGKE0n9qXLlBmF79mTAy3zgrvLSrNdNNuRaQULp1PQPUc2RvfnzwJeRaBQuepArdJzPNyJhuV66QJ3oxGG5dqeLM9xEJlqnTc72zOXDTSvg2qE35M2Bklcr13acv1T10mzI9W13TqlPXeLU+v9rmK2smnV9180g7DO52k752GewpMOboeDpWf9V8kUWHScy36O5vpaS5jtT14eHWPb81v26V1+ZnPiXolR38/VrCRgthcJbPfU9nJtA4TN8/JIdxcv4QhhlpaBgYee42LPu9g9IFOVI1MKaZHDs2yoosDdcGSK8nS2T6XgAsvdC8300mG59Z3ZviQDYCOw7Yln8LTplNjAdhHmKaSQOE5jPNrdmTifR0kIR0h4ZTaZZ1l1Kve841s0iDt97TbTmm92tgFg6Wtp2WC6LWBbtR+XqhyWturr5348Qur46DkePjO8jyjP0HFcXPd7CMqqyM3vonpeOZbEjmeyuyyYlOCKFGarmTBPW5/3VYG/NrOeSc09zBdtNdY2kONYEvfjkSkI5QZ1/0kVBaIsheMG6M3Ya7kyr505SMZllt/JINCs6/g8BkPaXm96660tVyysVTLKTNHQhztb2PUUXh4fwbEk9v0+HunuwLEkjpMQ/+fgZbjShi8d3Aj69QCFa9nYDbp1P1qXSydilcISJjOl0Br348urI3MZLu3o8zxHnucoigJKKcRxDNu2YduTh/CN3/iN+I7v+A58/dd/PW7cuIEf+7Efwzd90zdd1mFeiukbp5ppbO4xt6hQzarv07Fd3IvGgDBbEDTfc25a8JJpUrM6QrMam1FuqhBWI2ixyvDS6NBUilM5LAgcJDH2g169bmXWQvl5BR/a9nU1I9I5AtuBI82xCSFQFCZVrXrwrRqgpSqvg0NLmFTY+/EIW46PN2zto+f6M7+ryihPYAkLwtIoNAChYQsT8D8U9HGUhHADiQJ6pfToRZ1LV5o91ap96WxL4rrXh4DZdkDJ5YO7s1431edZ1NAu6nw7wsycZNrsHVetKRICMx/Cscrq7QfSMC8LYYR11kBV2v8y1sJedaBWqWYCTBaF6bRe87vwpERWFBPVw5vX4LzroApSOm6BVKl6T7/p73C6IxWU2y+0ZQusOghx3mneq7z/MrPx6wyqTJ/zaj2VFGLpfVJXzRRYdJzzZhabqvW1Ulh4ZXwMCCCwbUgh6mtrmb2552m26ZnKy3Oi6/V+frkzQdv62LbzkhcF3tC/NnNfybbXOI9rbpQlCGynTnfPCwVHmtoMs1Jwlx2Qc6WNPa+D2+EAYZahZ9sIkWGkE7y+v7c4Y6Wx/rdju3io06/XSU7/XV4UGOUxxiqFZ1lwpWN2OWhkc897lk+bNaPYdu2usk5zmefZWZc5jLIEqVLwy8EDwPRLRlmMcZ4isB3sllWYx1kKV9oz19oCJ3VF2lKkO7Zrqle3PO/n9SWWeSZVz4vb0RCxyupga9513nM8vDw+QlBu1dR1XAyzk+KgVS2YtverzLrmAdTFm6oJnsM4xI4XIFLtxZumv+9VB0OaZj0HgdOZhNMZSM39qn0pEUgHUog6qB1nCV4amW2idt0AaVHghcE9PF72N833ZdeZUbZlIckzDNMUmWfOTZRlCJz563w3zaUd+b/5N/8GH/zgB+v//vmf/3l8//d/P775m78ZX/qlX4rf+73fw2OPPYa/9bf+Fr7ne74HX/3VX404jvG1X/u1+IEf+IHLOswL1WwwIXBqjSKwXLrEspo3lNIKe0EHoky7mjVL2/oaS4zuzzruWY1NqhQC16k7rLHKTWCl8jJ1yWy3M8pi7Mn5C+VXOZ4q2JaiWj5vmNefTOlYdf1T9WCSlsA4TyEtC56WuBuNMcwSPL69P5Gy2fYAPU4i9GyvDrgdaSHNcwzTGA8FfZMyBEykySwT7Czb0dn3exNrtrTW8KS9VBpgW3VLAPW6oF55Tpu/f7pq8SHGeQJb2PClKajRrJQ772+n75Udr4P78Qhd2zNFxrRGrDJc806WNTS/41GeYJya6pdSWPVA0G65AfudaIj9oHdpjf5VzhZP69gufGlD6QICAm5VwbOsHJkXRWvBu1ntR5ViDACuNbuTv0pwv8pA1DLXz6pByCrvv8xs/LzXW1gkq/zfB/G4rnI7633WObZlP/eimcWm5lruPb9r1tyVNR3mzRKuonm/V6vmmp3mqrjKdF2HaiBm0WzVPOe5tKC5nKlXLp9JldmiZNfrnClrptrGqGu7GKURXomHgNbYD3q4F4/wUNCHN5VC2bRo/W/zfbQu4FkOIDRSrZBmZiuvnhOcOmcC5np+eXyE60H/VCZUtU1eVuT1IFn1vS577cz7jlYdVJmVvVUdT9skQFHugXpyzgRGWYqe48O2LBylZosXAQAJsNfY77U6980+y7wU6cMkbH3er1qQbfqZVFeRdn3siU69Zrsa0GzjShv7QQ+j1Kz19crPcZSEEBAzM6qaZl3zEGgt3nQ/DiGgZxZvartezlQYdUbbOWsAwFTKdmD7sl4D7ds2LMuqg9rn7r+EcZ6i73jYKQJ0yvoAt6MhemXhrcB2zJaihWmzbkVHsKWFbcfHIIkQqQz7nd6l1ZG5DJd25D/wAz8wM0B95ZVXJv77ve99L9773vdexmFdmlmjvc2HWvXv55l6eNZRxGXMTTee0dh40p6oVJwXCq5llTNrptPcczzci0OTqliuoV3m4byoY2ZmfAQ+NzxCDjM77Fo2HMvBw73JztYq5y8rTAfuMB4j00VZXdKMiIYZ8LnBAY7cEI+WxTfaHqBZkcOWJ8VLOraLKMsAretzkBQ5dhxTcTiv12vMPyerbqVUqUZ3qy1all3D25yBr9arTXfipr8nrYE70QCOkNgKfCitMUwT9F3v1D2wTOd71+sgVTlilSEvzAx33/HrzkWl/o5jlCPGk8XW0kLhetC/kHXC8zxIlZObxyJgKpIDAj3PfE+WECsF3Mt28lcJ7lcZiFp0/awThKzy/svOfMwb6V+lGNO891nn2Jb93AfxeO7MYlP1XTfrQVRrr88zU6G636drNFRp2wICtjh9bsM8RVoOvFbrf+dV0522yrKcKtiZNYDRrIlwamuSRiDW/E6W3bZslCXItUKuFba9AEmRAwIYpzFsYcOCwONb+3M/6zL37ShLcLO7jZfGx2ZbGstDnCuM8wxv3H5o4pxV+3iaivw5PjO4j0MvxKPdHfRcv75fU6XqbfKq7WvsOVs8TVslZXWWqj7Iy+NDpLk5h1WqbbVFYcd2Z04CHCZJvT+pa9nQKMzAu1L1vVFojbvhEL60Tw0QTfdZZqVIrzNwuswzadZ1flhed7O+gz2vC2icFKEq6zFo6KVSgGe1Q4dJ2Fq86TAZLyzedJEWDQBMp5UDpu7LcRrjOAnx0ugI4yxFR0o4lo2XRkd4pLcD37IxbhTaSlUOv2yL70ZDaBToSA8HaYgoT7Hv95CovA6KXwvbAm1uSL5hlumIX1bq4Xmn4M2tmtrygK32o2s2qrYlkZb7AXarisAa2PPMmoRE5Wa2rKVIzazjaWruX3g3HpqCXSiQ5zkyFDhWMd64vY9CF3PXmMxj1u6az+mXI/zjPIEQFq55Zn2wJSzcGh+ZB27L9WBbNpIihxCinFUW8G2Tpmn2bbMxyiK8cHy33haj0Kj3AD1Lp3veQ2tRgD99fTdn4APbXep6N+tJrFMjq3G55q1p2cDgRmdr5rU+fR+EZaEO8/onnevqNS+7wV81Y+AyjkWUldRTZSo9QmvESqHnuisVvFt2VnDVWdjzWhe67vrmZQfClu1Utr3eKgOg63Re106BnhPAVxXSgdmzQs1A0+wNKpDrArtue9X+s2q7v7wy1W/63FYBjwWz17wqA6e+452avTzrspwq2KkGE9sGMOZtTVKnk/rd+jtZtTJ1XpjMjALaLOdQCsM0BWBmbhe1g8vct1mh0Hd8fEFf4k40RJhn8KSNfa9XL9upztlxaoLacbmW2bEsWBC4NTrEE9vX6/MU2PbJNnmFOQ/Vs7hti6fpwdlZKatKL7elWHWeh1kMaMCRNkKVYVua9Y+HyRjbbgdb7ul717UkIpUiyRR8WyLNcxyrCD3bRa6LcoDIrI1N87zuFyzKMJk3W7jOwKkQAvfLv9v2glPnse06L7TG3WiIm52t+RXrW2qmVOdnmWdg22d1rPWLN12kRc+Ytu9HQODR7g7+4vgOLGFhy/VgWxIdx0GqFO7HY1z3+/XnqrInbo0jeNJFz/GhtQYE4AgLodZ4dTzAja7JgMgKVdf72eT1tpt3xBtqmY74ZaQeXkSlVceSGGYx7oRDaACelJBCQqq8DrZOLdDH5PoCX9oYpTH6rhkF75dpuV3XQ9f2JtdeLhhxbjuPzf0LoyzFNa+P+8kI0pbo26aCo2876Nju2iN2ZtsYG+M8RlamZiZ5DseykWuNUW4KQVnCwlES4qHGnmjVeeg5HnSZMlvNMu563bqBP4jHcKULrc1sxihP8LruTrmp/dk63WcJpKav7+YMfPPzzbvezZYL1lT6mkCY59j2JgsqHCUhrHJLkGYa4TKBQfU60ylud6Ihdr1Ova67KrZmz3n987BsWulVqwYKdsv9iY+SELkusBd0lhpwalppEE+g7kjteJ3Wtuq814Ve9CDjWWbjLyo9+zyObdo6M+4QZk2cJ23suMHSmTrrmL6/qn1cm6SwcD8eT6x3M+n3Zv/5J7ZPljacx7Kc6f2eWzu+5YBxc2uSnm0C4Uzl0JjcFmWVgRrHkqaKvFJIlIJnSQhpYceX2Au68KVzaga0Kvy4yrrU6nxUBTSBk71Bp38nKwokKoO0qv03LXhSIlJF3Xa6VjkoHpvCUxbMcz/Js4ktnmbt0X43Gtbb6DiNgdVBGtdpyG3Pjc8O7yEo+yhm5ssEFWlRoNAKSaEQ5SluBFuI8wxah5MzwsKkGB8lIUZZDFUARa7g2y6u+f1yli6CLgP2rm0GU3bcoK6HO0pj3BodAsIUSAxmLOFpWvV53/zsDwV9xCrDURIhL06yumbNBB+nkUmrbUyARHl+avuo804BBmYXb+q7uPD+9jzLtOOzBhFcaWPXDbBTBHhpfIRU5ZAaGOYpthwfj3dPMiqa1frTwtwPoUqRFQq2sHCQDjHOE/QdH2GeAlpgP+hu9FZAm3W0G2yZB/xFpB5Od5rTIj9zuvP0awoAt0ZHcISEb5uCMuMiwyPd7Zmv22xUx3mKROXoOh7CPIPSpujEE9u9UyOhy3RcF+1fmKgcfddFBh+ukNjyAhRFgTDPztx5vdnZhi0svBwNoArAlhLVFmhbrg9VaKQ6g+W0V8Rrpv1OBzrV53csiW45e5YXZjY7KGd0z2rdQKp5fWeFwjhPEZdFCbIimEirqbQVupBCQkoLeWHSrxKlIMRJSk11Dna9Du5FJrVm3+/V37ErbRwmITxpTzxsp02nuNmWqUR5lI6hNbDlehhkSV1sbdaWWGf1oGzps4oqwG0rsDNtUSrlorVazY5UvWaqxXmuCwXOf5Bx3YI0bS4qPfssfzPLqs80t0yt3PO69flath7EeZhXgGZ6vZtjWbCnUqrPY1lO9e/Vfs/TP28W/Ku2JtEwqZ62MGmcGphoR1YdDHGEhCUtRHmKqMggYWHf76Ij3YlB4kXLTuatS13m2mjO4se5gictKGj0nABKa7iWXa/tr7aJyrXCMImQ5AqB42DbDWbOzE0GqgJd28NBMsYeuvClhNYawyxC3/VxOxxglCXo2M5kanReQBWxWaJR5MiVQoECYxWbis9l0H8nGpbnzYHbmBGWlsDtcAgLFnacALnWSAqFh7vb9XP9etDHQTzCUWpSTLdcH6YWiQlgb41NAaEqm2CYJeg7p5fwTFvled+8trNCYZiaDIZmqmszmwAwM7XHaYRXw2PcCLYQ5ikO4xBZkUMVBYZZAdea3M3iIvZubwsQgfnFmy7avHZ80bPPlw7SckDhke5OmSVgCso9PlWotHnvO5aNw9zshjLKTD2RXa+LrMjxF0d38GhvF/ud3qklAw/K4PqyNutoN9gyjfh5px62dZrvRaPWmcJlg6LW1yzXUVlCINcatpToOv7MgjLNz9srX9N3/Ynzsqg66ryOa9t5bO5f6JX75TlCIikbi6wo4NnOmTqvVcrL63q7uN7ZwlES4v/cfxnSFtjxAjMTWQbtVcEdYPm036qBau7/aYpeqUsdaWzT3OZhkJoHeqgT2ELiIB5jy/VP7WHYVujCK4OeKM/Mhuwap9YkV9fA9U4Px0mEO9EQtmWKJMS5SeM+zkMM0xgv66K10Egzxc28plmjpsXJmqx1iq01LfOAXmat53k/5C/LvKD9LGu12u7581wXCqxXEX1ReuIqBWnmvd46weKqHZPzyhRY95l2VZkKs87tjneSDl2td5ueXQTmX4ezzsX0shxgcr/ntiC7amsBswwlUTlkWQ6xqvLcrHC76mDIo71d3BofYdvtIFYZOrYLu9wmpjlIbN7fLDuJ5yw7abPMtdGcxb8bDZEVMM9SmDT1vuNBQ5dFyqptosz53PbMrg/HSYRYZQjsk9oV1WdvtjGulCi0hT2vg0ilUFpimEZIVY6BE5ntzYocg0RBWKbC7DhP4NqynIGViFQGYQmEWQrf8pAWGbQ2e8SOswS+5cJ33JNZfwCfPr6LnhMg1RlUlqPr+vAA3ImGeLSsfutaEneKAn3Hh2tZSAvTl3t8ax+HSYjjJIJjWUgKWX9XUcsSnrNoXtvVWuFqLbMq639khULX8ZBphaM4QpybwlcPBVsABD43vI9CA91yb3kLFoZZDDcxg6XnPdA7L0C8zKU+re25JfHC8BBRlsESAl3HR9dxcLOzvfDZdyPo44XBPQCAb9nY9/voO/6poBaY3l7UgSftOuNNQEBaAtJykChTVLXZJmzqetvN6CG9Bix7E636QJ/XAWq7OTxpY5CabXQqqwRFba9p9qyL4dsufNs+aVhVhh2rs/LrVT9vnoe1Oq7N89jYv/ChoI/PDg8ALaB1geM4xihPcN3v4V48xqPdnaXOxbRmp8gWZlbx0d4O0sI0ptX6YUCju8aMTdVANdOtdJkue1VFhSrV9f3i6LB+cO14AbJCIcpzhHk2kXI08XeNn9V7twkLO1Zn4npuruWuCtFU22Xt+10cJiEilSItCoySBFuei12vi0GZxtW2lcp0oRq/TPFKCzUxI1nfZ0tuw7XsA3redb2Js7lNc+/tGWvvgZNOe1Xhtam5Vr7Z5k133LNC4TiJ6rat7fua19au0ulZ9D2tOpu86PUepLXXy3iQ0ukXmXVuAeDF0QGOk6iuBbHtBbgRbE1UUNbQcwPIZZblVJ3var/n5s+jPIOGCYqqa0NAIClyuMKGa1l1lefmWuZVB0N6ro8n5D5GWYKwzKhypVmD3HWLiRnQqg1tDmLP2qe4ra+y6NqoZvF7todbo0PkuoBbLlcS5f+r6k28PD6CJQRc6cCRdh3MHqexSbGe+uzN/X6r56otLDh1QGjherAFWaYLV4HiMI2x73eRl7sUyHJg1C2vgSRXuB50cZRGOM5i9G0zC77lBbhefq/VdlxhnmHf7yEQNg7TCGkcYtvxEWVJfZyjLMF+0EOscnP+pETf9TDOU9yNhnDLJTzVDOmW4yPXxcL+1yoms7IKCJjCZY604FomkH55fIindm6gZ3uI8wyu5WC73GroMA4xTDP4UgBw6/trlCYYZ0m9BnbdjMK262vR611G29TWnr8aHiMrFHRhUtKzosBxOoYnTZ9jUX+355og9nY0xLisqPxosIu0UKf2K5/e9lNAwLIE+naAgySEgsa27UNC4G40wm65bAK4ul0YzmoznjavEed9Ey2zrc30zbHtBrgTDdfaaBo4fcNlhUKcZxBCwIJAphSOVAhfmlnJRQVllg1Yz5oa2Ly5A+ngke42Xh0fwxIOxlmKh4IuttwAQVm9s+pArqKtU/Rof69cM5sjLxRsS8KXJ0UfVrkemmtFOraD29EQYZ7ietB/IGbyqkbU9eTEOtmObapEHi4RFM47J06Z9jbMkrpqaaLMDLHZ2idEICXyIoctgUEW17MrVWXLqvpomKcYZQkKrWEBcwvVrBNgLvuAnnddn+Uh/yBYZu/k6UGN5nmWwsK9eITrQb/+PqbTICcL7eQATPpbc8/uddcKLXt/LvqeVh2UW+Z736RgcdO0ndtRGmOQRvV2LIXWOIhHEBDYcv36WsyUQoq8zjpJi7zOOpn7fjOCaZGnEymUjpSntm8KbLOOrrkeF2gJqNdJSZc29jCVVRBPrk10LAupUvUWddPvDZzPkoue69eFoprBy2ESmgFOYQJctyzMlBYnKeTK0bDKe6752Zvtr2NJ7PodHCcRwjzFrtfFlicQSMc8zwrzuQpoqHKwWpTvs+ea6vBBuS1amKfINXA96OMNZQXpzw0PMMpiBOUSGceSuBsN67WyrpQmuEtjHKQhrpWDf660kZV7qTdnnbXWuBMN4UsHjiUxzlJIAUgIHCUReo63sP+1ismBe2H+twD6rg8hBCKVoWN7dcHIXBdIVIrPDQ9wze+i67iwLdRbOgKiLgSWFeWuEFqhZ08e8zKzhrOur3Vf7zy1teepUhikEXbKIqKAmZxQ2qwZX2rpouvXs7OL7q/mtp+P9HeQHiu8Gg3gSxt9x0emC7PPdKLwueEBHuvtmgzMK54wWRefjBtsUQeo7eawhMD1oN/ayM/SHAmr1phUDew4S8pRIKDnekhUhjDLoXSC/2/34YUPrWUD1rOuP55+sPccH/+/69tlcFNMdAjy8nOu03Gc1VnvO96pVOu1Xtvv4iAZ4yiNsOX6dQNUBeNA+7YRl6UKPqtAHji/DcB7joc74QCWsCAtsy8tYFLTbocD+FIC5ai1LUyRLrOOpFPP9FXVR7tlOvj9eIRBlqHneOjaLu5FQxwl5txmhVp6FHl6tHicJ/AsG3ejIY7TGAIaPcc3M/WNjuK867o5m1C5qtSgdVKiVx2Mmj7P216Au+EIR+V+i9Nr5YHTe4mOsgT34yEcaU0UFqte/yKCwUWB66rn4bKq469qk9PiVzX9We9GQ3Rtv94CDADuhEMcJmGdTl4FmbHKcZzG0BrwpV1vdTRvsHTeIE8zhTLTCp49+RqyTBFeZq/x8zDdZnnSxrAs/Di9V2rlMAlNpWCYYny9NbbRAWZXva3ur2qrQPNza6LKa8d2Ty1Jmf4sovyZZ5tiXMdphFjlSAuzH7MGcL3MdouUqeJsCw1VaGgU9ZKbp7YfqtuzaqDNsSx4sJEphQNlluckKscXbF3DK+EAyM0xB9JBAY2nth86lWHUlpa+5fo4SiJ0HReJyhCrAkqregnPeWn2oWwpkRQ59rwubGHVtT6ueZ26cOY4TSCAeiZ5nKW45ndN6i0EvLIQWFZo7PgmwBunKZRcrq1s65dOPxdWeb2LMqtKdFqm/lbM8jRd9ztW6e+uPDOtgUglcC2zhFAowJESXdeB0mY9+H7Q25jssGmbd8QEwNzUd6MhBESd4lql2ixOP1r+Yp0eCerYDu5FI2y5Pgqt8UqZ9lA19paw0Hd82FKeyvVvs2zAeh7pd20PxeyCg4fzShtsNuLVA6I5eguYzkNVOXHZIHKdzurcKr6WxEujQzMjbZlqostsAL7McbjSRtf1kCtVF2/Z9TvQWuPPjl7Fdb+PcZai0AUyDfQdD7HK8YjjQWnz4PUbsxqB7eJmZ7vuCFX7Du6WAVG172CUp3AsCaeckZ6+z9pGS4/jEKlWUIWZ4REQOIhDZIXCQ41N2OddH+ddwGiRWd/BurMtqw5GTXcAHEtiPzAp5m1r5au/GaYxIpXh4c42eo43scVM5SIDw0Xf06rn4SK/93WD001Pi19F22e9Ew1wM5jcL7RaU9gkhYVxltRVSCt5oRbu49k0q6M6r6OuoWdWDz/P72+6zfKkKViTFqrcuqjals5kyABmfazZI7wsmpSEZYXas9+Tzfura7umiJQW2PZ83I2Gc6u8Llr37FgSr4yPIYWFJE+RaIUkz/D03sPolqmu48Zn9qRzMmidJ7gfjzFII3QdDw93dgCgrggc5hn2gx5sYeEL+nv1lke2ZeGJresT/adZbci2F8ASArt+B+NyCU/HNpMMy/S/Ksu2C81ZfNeyMUgjpGUm2p7fhdaAa5l7oO/6GKRxXQskh+kfXu/0cS8aQQoL0gK6roPdcvB52QGa6es5VarOiKvaycse8Jll1gSTWxb60trsnx3nOSwBbJeDL6v0G9dZqvd4/zrGeYJhFpslhI6LvDDbefUdD5awNrZt38yjfg1apcNR3dRWmf5blNX1qoIRZ0k/mjb9gA1sF9tegFfDAbZcHx3bgWPZSJWq1/a0FdWYZZVjvIj0u8sIHs563Ms24vfjIa41OlRnXcu3zLFM/40pAuXjMI1wmOZLbQC+ynF0bQ+FPD3D/lC5DipwHWihkeSmeuReua9jtca5qj6alR3NQRIiKwrs+h340sO2K09Sg7TGnWgAxzJ7EOqyQ9ZzPIzLNOaqozrdCZWWhYNwiD23W3fmTMVSMbMw1KLZhIt8KM/7DtZNiV51neooMx3EwLbrgboqw6QustRIg6y+Q2igI5264ypEe8XxixoQWPQ9rdoOX9T3fpbg5kFMi7+oGeS2z9otZ+8esk8KL1YFg5qqWbTpKsfL7OPZNKuj2tZRr9bddmx3ZvXwUZaYfdbL2gTVkpjzykwCTLr2nTQBhAn6pTAVcyFMOvDE/uSFqWLsSQeYWhO41rE0Ui2v+T1oaFMl37JNCveczI15656jPEPf8XAnHkJpjT3PbHf00vgI18sinF3bw42gvVjcQ0EfhQYsMfHy5eycgmfZuB0OAAFsOT6CoF8WWZxM/56Xrl6913ZjK5s9b3Y16un7ptoqcNV2Ydfr1APpVRXve9EIfdfDMDXLhTqOW28FZVsWOk4HDwV9pGUNBGgLXcu8h9KTu0LUfQSBU8uYTvdLTR90VK7VnfV6V1GPoK09r9boj9IEscoghUChC3jSzLrP2iZzlulMueaSt1m/33fNAExeaNjCrBtPVIEdL0Ch9bkMOl0VBrYPgFU7HNVNvVPuJ2nDjIgdl+sqTlWePcNN3HzAVikf96JRuSVKUAZUIRwhoKFxrSyosEon7CrXi11m8LCuZRtx4HSH6qxr+Vb9m3GeIM5zbDk+pCtwmIQYZ2b/3sp0kLHKccz6vh4K+rgdDSG0hWteF5YvEKkcnXLksTkKr7WpOBlmKSwI+NLG/WiMQis83D1ZCxerFBYsBI6Dqgp1URT43PAAW05QzwLcjYatlcZ9y4ZtCWRFAbucXS60SdOadc/3HO/UfpBpoS78oTzvOzhLauwy93Z1Ljq2Y9b5KIUkH2PLO11Ju/n9D9MY1UaOvcZMfK4L5IWuj/Oi7+llAtdV2riLKg51luB00TVw2WnKFzmD3PZZb3S28P8GdxHneV2VVgqBba9zql7FthecGlhp7uMJLF7O0FzyU/13tcfqThkYVNdG27rb6dcO8xTjcu2eW6brDtIYXUefXkO7guqYwzzFy+NjdG0XPdtU/a22nBkkMXa9Do6SCMBJwHsvHpl023P4/truLwGxduZGdQ+aVOTMrLd1g3o98e1wAE/a9RKJecXiquf1URJCa6CqwJ8UCrdGh3X2W6zMd/pod2elgf3ptqLnmNT3tkKHbffNrfGc/ZJXGLhsztwPEKMA8FCjPkJzwqNjOygKDa9cl303GqLv+PW2P9XAb3Ws1f1Vnefpe7TreEjyMRKVnUqHv8r+ZX1Pa4VxmtbbEN7smOyPTw/uIlYZIAT2vF5Z8bv93Le1sSh/9ygJ8er4GNteB13bMf3DNMbj5fruadX2iX3XDNjdiUemJkxvp65tcc3vtf7tJmBg+wBYtcPRTLWr1gDmhVn/cd6pYdWMptYn++QBGhYEPjs4wJ7fwb7fwTCNcScaTGwifREWdaDaRiOnA4VTHc41O5HLdObOo8PX1oiPswEOkzEyZba38aXT2qFqm6mqjumV8Bgd6aDn+hMzv/Me/Is7uMqMypeBbN8NEI2HCLNk5vqrcZ4gVwp5WZil2rS+7Tjavq+e4+AgGUNrjXGWYJhqBI6Dx/uTpe+rUfhhFiPNs3J9i8CWF0CICIepWQd2TZqOXqYUHMtCR7rlOU8wyszefdcbe7350sFxGtUj+FmhMMxiJEWOQuu6Q5QXBTTEzMJQWdnR2Q96dadjlOVL3U9nvc7mfa8XndXQPBd2eW4SlbVW0m5+/5HKTl2/hTYzNR3HnehILJopPmtAdt6dp7O83qzPdJYBirlFztIYt8ZH5ZpSCd82e2te5HOgec00A79xnrZWX19F22f1pG067UrVVUif2rlRBzJts2jAycBKovK52+zNWvKz7QWI8szU/tUCnXK9bvPc3g4HE5ko4zLzQUPX332i8nrrskEWIy8KFEVRb5Uz6x5IVY6DZGxm12BSnKvMkuYxpyqH1gXiPINvO3AsCyiAqMycaabLpoVJvdz3+/VymovIADhru+VKs0+whq4LSGVFgZfDQ+RK47gsWli9XnXss4KuoyTCtXImVsFk+9jCbBW0W/48LwcsVtFsKyb35QXuxyO8PD4y6yW99uwbrc331FzadNaBy+b+w9PPfTNoY6pYj7OkrKptw5Fy4r6d1y+e/m4dS2LL8xHm2aXOzC67zVvP9qDk6a0sd70ubgRbE4MvzWrmzfeZHpC4HQ7qTA0Bk8IcqbQsouag73pLbXcXOA62i06ZtWabpVnaTFRtKga2D4BVOxynKvmVo8ZnyYmfdYNWDdQwi1EUGscqwiCJIMqbNS1ybLsBtr0Oeq4P11q9mvCyFnWgpm/+WRvHt82KzdtIftb5WjRjcF6zCm0P6Lx+QIuyw6LRs03KDTB7pqp5TIE0+/lWaezV+8x78C/qLHjSxrgwa4hilSJTChB6IkhqPnBSlWOcJhObyx/GIfquNzONZvph+mp4jFGalltNmdnVOM8xypOJwLY5Cp8ohY7joOv4cCyrTlcKsxRbjl+fY9dy67TYHc/s6ehZ9sQ52nL9utJ4oTXuxSM4wsa+10WYZ0hyhW0vQAGzD2FVyXP6no/zDBBYeeT8PK6zed/rRWc1TG4gL+sUt2rvz2nN779Z+C0rlCnSIk93JICTbYSao92vhXWjzbYbMPuadmz31Gc6S0d/1jXQcxzcGh2a+9c29+8wTdB3vXNPU25+zmorqCod3S4zJCKlzvwdzvqsN4Kt1tdcZhZtP+jBEpP5qM1z37bkZz/o4dVwAF+6COxqqzjgKAnrgbTmVldamy1VqhnBAmicC4njPEGY5HClCXpyXWCYJng1PK47x81AqGd7OEjGGKVpPbN2Px4hVTludLYmjlnpAr7tQBUaYZ5g2w0gy0q5u57J4mqmyyYqw/7UM/e818GfR7tlChYCiVKwhMBBMkaSK+y6HdjCZCTtep2JgdhZQdcgq7Yfs7HrdnCUhOU5HyMra0Z0bPdMKaDVd6IBHKURbGGe86M0AbT5zrtTtTn8shBU01kHLqu+4+1oiFEWo9Aa224ANzNZXT3bgxCi3rWgLZib1y9uK64kIM48qLWKs2zzVu3OcFRW9G6my7ed+7aBvDtlCv9j/T3kWqPnuAhspz6vbee0qXqOZoXCQ34fYZ7WtUv2g+4Gh7UMbB8Iq3Y41m2w1y0Os+d3cT8ZY5BECGwHr+vt4NboqAyiNLq2Z/ZMc4NTxTTOS6ryugNlWQLHaYTb0RDbbgcQaN3Uum3j+KxQeGF4D4F0zVYvQmCUxbjZ2V5pVqxKFZsXhJx1XVozzWuUJdh2fTM7mERwLInXlZu3AycjvYtmn5vH1Hf9eo3iKI3Rd/2F19Gia69juyh0gTvREFoDnpQIbLMZ+/Qa0up4tr0AwyxBc9P64zTGE1vLpcIcJxE8ebI21hYCnpQ4TqI65adSjcJbQkAKq/4bS1i45vcghHn4A2aLjkIXE6PO0IBvTwbclhBlx9Wsc3YtG9cDcz6OkrAcGIrw+v61+hy03fNxWYCkaZnO3nmsf5z3vS5a33XW2c51A67mMRda49boEFGe4qHOVmPgBzhIxkCZAths38wgwmrn7UGrDDzddt+LR8hUgcB2TxVrO0tHf16RHQhzn9frJ2EGaZats7DO56zS5cysl7mP86JAYNtYp9ruMp91le95evCtOn6g/dy3deL9cku4m51+OVtognhZzrxWa8qrra5GWVJXWY0Ls+XQURpinKfoOR6ksOHIAhpm39Udu4tRFpXr2oG7ZdCaFwqfHRyYAEsDHceFZ9sm60RrvDw+xCvhwKxn9brYLes6+NLFqIgR5wpbjkaizN9Xy2VWCfTPw3l9j4/2dnFrfISjOIRTLgHTKLe5gamZ0C8HGID2tlRA4PX9a5BCTNSHuBePENim0KIqqyfvBfP3np2XklplYeW6qO8LE+CY2fm70RBD6U7UMfBtB6PYLDGr+kSulKeenauojrFaXiIgEGYpEpWZwmFeF9eD3txgbt5z4aKWa6xi0XN3VmBuCqyZ3Rl2vQ7uxSPcDUfYD7ozt9ipXqs5kGcLC6owdT8ETDX2RGV1lsS8NbZNGmYw0tQMMBlzAjjX9vuyMbB9AKza4Vjnpj5LcRhXmuI5ji/r7Q72gx4OkzHCcg/bXbdzYTdDqnK8ODrEnXgAXQBJodC1HXjSRZQnUJHCntc9dfO/ODyAFAJ+Y9+4QRpjkMTodj045cNklKY4kOO5DfmyBZyaQcj0+uS2FLF573c7HCAu14xoXeB+NMK2b/ZZ3fd7Ew+C6r0XpTC2zY4N0xihyhBo0xmet9/somuv2pJnywnqGdi8KGbO4GSFqteeVa9pWybz4KIeUlXxp2EWw9PmPRKl0HPdUwMcdVGj8rM+2tutU//bKo1PV+S9HvSx7/eQFgo3OlsTx3Cq8yOAYCpoXqazdx7bwyz6Xmd11Ned7Zw1y7hKwFUd82ES4m40LNdamyJizZmU+/G4taja/Xg8Nz207ZhX+cyXEQRPt92ACTLHWVLPhky0DWfoDLa1LaaqvF2vQTfvJxDmOba98wtSpj9ntRXUQTzGjaCPvNxXdNfvnMvM36qp4Iu+60XnflYnvso0skW5fKF8vrqNc1ENaB6nkdleBeZ7qLY8i5RCYmVIlMlGqYrZ5eXrF1rjKAkRZinccr3uvSSEKgo4lkDHcXFcbidjCu4l2PUDeJaN+/FJ8b2qLU+LHGGeQwhMbDmzSqC/7Hld5DyWCPRcH0/IfbwwuFdvX5MqE6xZMHtrB9LBnh/MXFPZlqKeFQpm79vG1n9C199fm7Y26NXwGAICge3UWVgH8Rj75U4VSmtoaAySGLZlwRKYqGOQFQpd2yvrdJgE1HnHsIzqfh2WacMaGlGawdEW9rwujsv6CM1gruc4EwOlpqhVXp+v1qJ8VziouO42b6lSCNyTSZHrQR9HSYjDJCwLJZ5uk6vXqtoA27JgWRYkzH2eqAxHSQy7LDCXLVhjW0mV2cYqLXJ4lg1VFLgbjuq+0KZiYPsAWKfDsepNfdbiMFWKaV4WzejYHqIsw5bnlWX7L6ZAS9WQj/MESmmMlVnjqLSNMDd7A/Zdv153EasMB8kY4zSDJ02QG2YZ7pQFfo6TqJxpXTy7N+/8zSrg1AxClksRa/8Oq33/fOnUe7bGyOBaNrqBh0JPVr1cdrS7NU3K9dHRLqABaYlThRpag9sZx+3K9i15Zq2ZbaY/V+dxlaragFn3dT8eQZTbCiitkRT5zOIHrrRNkYrExlESAgD2gg72vOU+a9u6ukUd1Onvpu2ef7S7MyNonn9Pndca2FXalLPMErd1zgQEcl1AlZWmlw24qtnvm2VqZKJyRHmCNM8R5ilulIFrW1E1ACudt1U+82VtjzPddtuWRFEUyBpVcZuf6bw7g44lEdgOhlkCFCaoTZSCEFhrr+5ZZm0FNc5jRGUl7WZV/vOc+Vtk2e963rmfnf7cr5eXZCov/01j1zdtZaE17sfDsjK7WZsbl7/XnMXu2C4iO0MBXW/PcpIOK3CURnAs8zdHaYyObZuAN42wLwSkMGnIeVFua2M76NpeWTk4RSd30Hc8HBcR9oMeurY3Nwid1+epgsNxnmCcmoye5lKiq1gqUGX6VEsfqoHqKM/rzwKcLG2Ytaay+ZmlsPD41rW6EJhtSez7vbkpoG1tUDVY3nf9OgvLtiwM06gsblaYgVYB9Gy/XnZT1THoOR469uRMcl5mpa3bVlT3a17+30GWwLUsFDCDtwXM7GAVzFUFr5r30CjLL6144joWPXdn3dOetCeeR075vVcDVG2q10pUBt+y69fR0NBaY5Sl2HJ9s7ey7cCVcu4a28ooSxDYTr3Xdl4oONIy2zU+IOd5HZt75K8xFz36dNbiMGY2RZSblSu4UuLR/g6yorjQRqdq7Aqt0XE8hCqBJQQSlcORFmKVYtvdrze1vhMNEWcZXGlBWh6SJETfcZDmGY6SELkusGUvv79bZZUqfJWqMWqmiClo7JZb0Mx7cBwlITzLngzAtQnEHt/aXzulcFZjK4SAtMRagcq0WVvytHU2z2Md1K7XQapyxCpDXmgIIdB3/DpQblMFt81Z1GWt00Ft+zyrBs2zXEVl77PMErd1zgIbZfXq1Su0VsfiWGbPyWoP5TDLcA8j7Prd1vZtp+z0Vce+6Lyt8pnPIz18GdNtd8/xcDcy6fCz2qXzVFfXdDxEeYZIZYCenKk7D23PKEuY9M7mliN5oS69qv15fNfzAr2qTdBAWWjIBPBZoXAvHpm6FtZJwSkIoG97p2axO44LR8iJKrO+dKChUWgFQCIvCiRKYc/vQBXKrLtTCrYQGGcptAa2PR9d22Q87ZY7M4Qqw7bXwRPbvTNlADQHCXJlBjiHWTKRGXXe99Cymu2sLUxdBl86daBdHfe866D5mR1LotBFvXYaWDyo29YGFbq6MiZrFNyJhui7AXa8APfjEFY52DRdxwBYbTeFZdT3q3WStSWAOlugYzvYdoM6mJt17uYFe1dt3W3eRlmy8kB09VrjPK0H8qpilcdJhFwrdGwHD3VOqlAvWmMLnC5Eu+zfPegY2H6eOGtxmGYHpvk7NzsXO3pa3XieNGkSXcdHnKWIigyO5WPPN6ksVeGsnuNhlJpiBa6UeKS3i1RlCLMMHa3x+v4eBmlUzzwvmt2rrFOFr1msyOwvbIpGOJY8U+NxlpTCWX97WBYxaFr34bZycHcO66CqYiZXvfbxItI9L/o913GWWeLzSJ1uO5as7ASlRY4kzxE4DvaDHkSZ6la9TzN9HMDS522Vz3zen3GW6XtNAOg7PhwpL+VaaF57lrCwY3Uu5N6b3aas9h1ehPP6rmfd+9XPpyvNHiUhoAW2vQBCiImCU22z2NUsavNcVQN7YZ7hfjRG13HqfSwLCDzW34NjSRzEY0hhoeu6ZSXgqjaBwI4X4JrfO5cApDlIkGtdL2epMqMu4h5a1qJ2dtXrYJ0ByVkDPHrqd6753bpic1ZORHRsZ6KtarZd55Hx0/bZfGljkMZQRYGi0Nj23Xqwpfkel9Venqdlnrtt93S1OwOw2kC0K2081ts9tQVSz/HQd/1T67eX+Q7PK9vrQcPA9vPEOsVhVlkjdFGqGy+QDiwIWGURjV3Lw/Wgbx6AU8WLdrwOrMaWM65lChhd83voOR601ivN7gGzC0IsqsI3ncJUWdR4bHsBDqJwMr1WqbqwxFlm+Nv+9jwbuFWvlfPIVrjq9TZNV3Esl/2eZ5klPu+HaXUsUZ4jkGZmx5PORLXSXb8z83o8jwJbF/0ZZ2m716q9IC/LZVx7i9qUq7z3r+q7LrTGftCdeB9fOua5WKYiT89iz/quntjaR9d2EasMWaEwSCN0pId93xR5qqq5V1WSM1WujS/y+t/Ow2QNCDO7J4WoA5yr7nTPu9ZXvQ7W6VO1tUGulGYpx4y6DwCwW86Ez1rmct4ZP83P1nXMut0oTyCFhS3XN1W5G++xqQHWZQ9Ez/pbYL3v8CqyvS6DGAwGm1zVufa2t70Nn/jEJ676MB5oD1pFz2VUqUlV8QNTHdLs3Woe7L2JtZGpyuvtX6otCqqHb9XhW/c8nOXvpkfZph88bX/zaniMVKlTlQov4jtb5xjp89tl3g/LvOaLo0NkhamEXqXcVal955XOtuxn5v30+eOqvuuDeHxqwLS63quZ2VXuzemCbhqmkFHz7+fta3venykrFA5jUwPBtkxA9CDfQ5d1Hcyrijzv+1605+pF9w2X3fOV7eV6Lrtfe9Xe/OY349lnn239Nwa29MBrFpNIyy1ROmWl45mdygt8+K5jncbjshucTW3gaPNcxLX2oHWOeD99/riK7/pBu97Pw/RnilWG4zQuCxzNfuY/KHjPr4/njlYxL7DlVUMPvCrdYw/Lzbq40sbNzvYDVa587ZSV11hKIRFwMdfaVS2XmHs8vJ8+L1zZ8oMH6Ho/D9OfyZMOnthaviDVVeM9vz6eOzovvIqIiOg1gZ0j+nzyWrzeX4ufiYguz/KbRRIRERERERE9gBjYEhERERER0UZjYEtEREREREQbjYEtERERERERbTQGtkRERERERLTRGNgSERERERHRRmNgS0RERERERBuNgS0RERERERFtNAa2REREREREtNEY2BIREREREdFGY2BLREREREREG42BLREREREREW00BrZERERERES00RjYEhERERER0UZjYEtEREREREQbjYEtERERERERbTQGtkRERERERLTRGNgSERERERHRRmNgS0RERERERBuNgS0RERERERFtNAa2REREREREtNEY2BIREREREdFGY2BLREREREREG42BLREREREREW00BrZERERERES00RjYEhERERER0UZjYEtEREREREQbjYEtERERERERbTQGtkRERERERLTRGNgSERERERHRRmNgS0RERERERBuNgS0RERERERFtNAa2REREREREtNEY2BIREREREdFGY2BLREREREREG42BLREREREREW00BrZERERERES00RjYEhERERER0UZjYEtEREREREQbjYEtERERERERbTQGtkRERERERLTRGNgSERERERHRRmNgS0RERERERBuNgS0RERERERFtNAa2REREREREtNEY2BIREREREdFGY2BLREREREREG42BLREREREREW00BrZERERERES00RjYEhERERER0UZjYEtEREREREQbjYEtERERERERbTQGtkRERERERLTRGNgSERERERHRRmNgS0RERERERBuNgS0RERERERFtNAa2REREREREtNEY2BIREREREdFGu7TA9uDgAO985ztx8+ZNvOlNb8Iv/MIvtP6e1ho//MM/jC/8wi/Eo48+iq/6qq/Cpz71qcs6TCIiIiIiItowlxbYvu9974Prunj++efxkz/5k/je7/3e1oD1v/7X/4qf+ZmfwW/8xm/gs5/9LL70S78U3/7t335Zh0lEREREREQb5lIC2/F4jF/91V/FBz7wAfR6PbzlLW/BV37lV+KjH/3oqd/97Gc/i7e85S14/PHHIaXE3//7fx9/+qd/ehmHSURERERERBvoUgLb559/HlJKPPXUU/XPnnnmmdYZ27/7d/8uPv3pT+Mv/uIvkGUZPvKRj+DLv/zLL+MwiYiIiIiIaAPZl/Em4/EYW1tbEz/b2trCaDQ69bs3b97EW97yFvy1v/bXIKXEo48+il/7tV9rfd0Pf/jD+Kmf+ikAwP3798/9uImIiIiIiOjBdykztt1uF8PhcOJnw+EQvV7v1O9+8IMfxCc/+Ul86lOfwt27d/H93//9ePvb344wDE/97rvf/W48++yzePbZZ3H9+vULO34iIiIiIiJ6cF1KYPvkk08iz3M8//zz9c+ee+45PP3006d+97nnnsM73vEOPPLII7BtG9/0Td+Eo6MjrrMlIiIiIiKiVpc2Y/v2t78dP/IjP4LxeIzf+Z3fwcc+9jF8wzd8w6nfffOb34xf/uVfxp07d1AUBX7u534OWZbhiSeeuIxDJSIiIiIiog1zKWtsAeBDH/oQvuu7vgtvfOMbsbe3hw996EN4+umn8eKLL+JLv/RL8Xu/93t47LHH8E//6T/F3bt38WVf9mUIwxBPPPEEfvqnfxo7OzuXdahERERERES0QcRgMNBXfRDn4W1vexs+8YlPXPVhEBERERER0QV485vfjGeffbb13y4lFZmIiIiIiIjoojCwJSIiIiIioo3GwJaIiIiIiIg2GgNbIiIiIiIi2mgMbImIiIiIiGijMbAlIiIiIiKijcbAloiIiIiIiDYaA1siIiIiIiLaaAxsiYiIiIiIaKMxsCUiIiIiIqKNxsCWiIiIiIiINhoDWyIiIiIiItpoDGyJiIiIiIhoozGwJSIiIiIioo3GwJaIiIiIiIg2GgNbIiIiIiIi2mgMbImIiIiIiGijMbAlIiIiIiKijcbAloiIiIiIiDYaA1siIiIiIiLaaAxsiYiIiIiIaKMxsCUiIiIiIqKNxsCWiIiIiIiINhoDWyIiIiIiItpoDGyJiIiIiIhoozGwJSIiIiIioo3GwJaIiIiIiIg2GgNbIiIiIiIi2mgMbImIiIiIiGijMbAlIiIiIiKijcbAloiIiIiIiDYaA1siIiIiIiLaaAxsiYiIiIiIaKMxsCUiIiIiIqKNxsCWiIiIiIiINhoDWyIiIiIiItpoDGyJiIiIiIhoozGwJSIiIiIioo3GwJaIiIiIiIg2GgNbIiIiIiIi2mgMbImIiIiIiGijMbAlIiIiIiKijcbAloiIiIiIiDYaA1siIiIiIiLaaAxsiYiIiIiIaKMxsCUiIiIiIqKNxsCWiIiIiIiINhoDWyIiIiIiItpoDGyJiIiIiIhoozGwJSIiIiIioo3GwJaIiIiIiIg2GgNbIiIiIiIi2mgMbImIiIiIiGijMbAlIiIiIiKijcbAloiIiIiIiDYaA1siIiIiIiLaaAxsiYiIiIiIaKMxsCUiIiIiIqKNxsCWiIiIiIiINhoDWyIiIiIiItpoDGyJiIiIiIhoozGwJSIiIiIioo3GwJaIiIiIiIg2GgNbIiIiIiIi2mgMbImIiIiIiGijMbAlIiIiIiKijcbAloiIiIiIiDYaA1siIiIiIiLaaAxsiYiIiIiIaKMxsCUiIiIiIqKNxsCWiIiIiIiINhoDWyIiIiIiItpoDGyJiIiIiIhoozGwJSIiIiIioo3GwJaIiIiIiIg2GgNbIiIiIiIi2mgMbImIiIiIiGijMbAlIiIiIiKijcbAloiIiIiIiDYaA1siIiIiIiLaaJcW2B4cHOCd73wnbt68iTe96U34hV/4hZm/+8ILL+Drvu7r8LrXvQ5veMMb8IM/+IOXdZhERERERES0YezLeqP3ve99cF0Xzz//PJ577jl83dd9HZ555hk8/fTTE7+Xpin+zt/5O/j2b/92/NRP/RSklHj++ecv6zCJiIiIiIhow1zKjO14PMav/uqv4gMf+AB6vR7e8pa34Cu/8ivx0Y9+9NTv/uzP/iwefvhhvPe970W324Xv+/jiL/7iyzhMIiIiIiIi2kCXEtg+//zzkFLiqaeeqn/2zDPP4FOf+tSp3/393/99vP71r8c73vEOvOENb8BXfdVX4f/8n/9zGYdJREREREREG+jSZmy3trYmfra1tYXRaHTqd1966SX80i/9Et7znvfgz//8z/G3//bfxjd+4zciTdNTv/vhD38Yb33rW/HWt74Vd+/evbDjJyIiIiIiogfXpQS23W4Xw+Fw4mfD4RC9Xu/U7wZBgLe85S34iq/4Criui+/+7u/GwcEB/uzP/uzU77773e/Gs88+i2effRbXr1+/sOMnIiIiIiKiB9elBLZPPvkk8jyfKAL13HPPnSocBQBvetObIIS4jMMiIiIiIiKi14BLm7F9+9vfjh/5kR/BeDzG7/zO7+BjH/sYvuEbvuHU737DN3wDfv/3fx+/9Vu/BaUU/v2///fY29vDF37hF17GoRIREREREdGGubR9bD/0oQ8hjmO88Y1vxLd8y7fgQx/6EJ5++mm8+OKLePjhh/Hiiy8CAJ566in85//8n/E93/M9eP3rX4+Pfexj+Pmf/3m4rntZh0pEREREREQbRAwGA33VB3Ee3va2t+ETn/jEVR8GERERERERXYA3v/nNePbZZ1v/7dJmbImIiIiIiIguAgNbIiIiIiIi2mgMbImIiIiIiGijMbAlIiIiIiKijcbAloiIiIiIiDYaA1siIiIiIiLaaAxsiYiIiIiIaKMxsCUiIiIiIqKNxsCWiIiIiIiINhoDWyIiIiIiItpoDGyJiIiIiIhoo9nL/NK3fdu3QQhx6uee5+F1r3sdvuZrvgbPPPPMuR8cERERERER0SJLzdhubW3hYx/7GLTWeOSRR6C1xq//+q9DSok/+7M/w5d/+ZfjIx/5yEUfKxEREREREdEpS83YPv/88/jFX/xF/PW//tfrn/3u7/4ufvRHfxS/8iu/go9//OP4/u//frzzne+8sAMlIiIiIiIiarPUjO0f/MEf4Eu+5EsmfvbmN78Zf/AHfwAA+PIv/3K8/PLL5390RERERERERAssFdg+88wz+OEf/mHEcQwAiOMY/+pf/St88Rd/MQDgM5/5DHZ3dy/uKImIiIiIiIhmWCoV+Sd+4ifwrd/6rXjkkUewu7uLw8ND/NW/+lfxkz/5kwCAw8ND/Nt/+28v9ECJiIiIiIiI2iwV2H7BF3wBfvM3fxO3bt3CK6+8gps3b+Kxxx6r//3Nb37zhR0gERERERER0Twr7WPreR729/eR5zleeOEFvPDCCxd1XERERERERERLWWrG9uMf/zje+9734tVXX534uRACR0dHF3FcREREREREREtZasb2fe97H77v+74Pr776Ko6Pj+v/z6CWiIiIiIiIrtpSM7ZHR0f4lm/5FgghLvp4iIiIiIiIiFay1Iztu971LvzMz/zMRR8LERERERER0cqWmrH9/d//ffzET/wEPvShD+HGjRsT//Ybv/EbF3JgRERERERERMtYKrB917vehXe9610XfSxEREREREREK1sqsP2mb/qmiz4OIiIiIiIiorXMDGx/7ud+Dt/4jd8IAPjpn/7pmS/wzd/8zed/VERERERERERLmhnY/uIv/mId2H70ox9t/R0hBANbIiIiIiIiulIzA9tf+qVfqv/3f/tv/+1SDoaIiIiIiIhoVTMD26IolnoBy1pqxyAiIiIiIiKiCzEzsN3d3YUQYuYfaq0hhMDR0dFFHBcRERERERHRUmYGts8999xlHgcRERERERHRWmYGtq9//esv8ziIiIiIiIiI1jIzsP22b/u2uanIlf/0n/7TuR4QERERERER0SpmBrZPPPHEZR4HERERERER0VpmBrb/4l/8i8s8DiIiIiIiIqK1zAxs/+f//J/4si/7MgDAs88+O/MF3vrWt57/UREREREREREtaWZg+73f+7343d/9XQDAe9/73tbfEULgj//4jy/myIiIiIiIiIiWMDOwrYJaAPijP/ojSCkv5YCIiIiIiIiIVmEt+gWlFB5++GEkSXIZx0NERERERES0koWBrZQSTz75JA4ODi7jeIiIiIiIiIhWMjMVuenrv/7r8fVf//V4z3veg0ceeWRif1sWjyIiIiIiIqKrtFRg+1/+y38BAHzwgx+c+DmLRxEREREREdFVWyqwfe655y76OIiIiIiIiIjWslRgCwB/8Rd/gYODA+zt7eGpp566yGMiIiIiIiIiWtrC4lEf+chH8OSTT+JLvuRL8BVf8RX4ki/5Ejz11FP42Z/92cs4PiIiIiIiIqK55ga2v/Vbv4X3v//9+Cf/5J/gf//v/407d+7gj/7oj/CP//E/xj//5/8c/+N//I/LOk4iIiIiIiKiVnNTkX/iJ34CP/iDP4jv+I7vqH/2+OOP47u/+7vheR7+w3/4D/ibf/NvXvhBEhEREREREc0yd8b2k5/8JP7e3/t7rf/2jne8A3/4h394IQdFREREREREtKy5gW0Yhrh+/Xrrv12/fh1hGF7IQREREREREREta2FVZK01tNatPxdCXMhBERERERERES1rbmA7Go2wu7vb+m8MbImIiIiIiOhBMDewfe655y7rOIiIiIiIiIjWMjewff3rX39Zx0FERERERES0lrnFo4iIiIiIiIgedAxsiYiIiIiIaKMxsCUiIiIiIqKNtjCwVUrhL//lv4wkSS7jeIiIiIiIiIhWsjCwlVJCSok4ji/jeIiIiIiIiIhWMrcqcuU7v/M78Q/+wT/A+9//frzuda+b2L/28ccfv7CDIyIiIiIiIlpkqcD2/e9/PwDgt37rtyZ+LoTA0dHRuR8UERERERER0bKWCmyPj48v+jiIiIiIiIiI1jI3sA3DED/2Yz+G//t//y/+yl/5K3jf+94Hz/Mu69iIiIiIiIiIFppbPOr9738/fv3Xfx1/6S/9JfzKr/wKPvCBD1zWcREREREREREtZW5g+/GPfxy//Mu/jH/5L/8lfumXfgn//b//98s6LiIiIiIiIqKlzA1swzDEzZs3AQCPPvoo19oSERERERHRA2fuGts8z/Hbv/3b0FoDAJRSE/8NAG9961sv9giJiIiIiIiI5pgb2F6/fh3f9V3fVf/33t7exH8LIfDHf/zHF3d0RERERERERAvMDWz/5E/+5LKOg4iIiIiIiGgtc9fYEhERERERET3oGNgSERERERHRRmNgS0RERERERBuNgS0RERERERFtNAa2REREREREtNEY2BIREREREdFGY2BLREREREREG42BLREREREREW00BrZERERERES00RjYEhERERER0UZjYEtEREREREQb7dIC24ODA7zzne/EzZs38aY3vQm/8Au/sPBvvuZrvgZbW1vI8/wSjpCIiIiIiIg2kX1Zb/S+970Pruvi+eefx3PPPYev+7qvwzPPPIOnn3669fd//ud/ngEtERERERERLXQpM7bj8Ri/+qu/ig984APo9Xp4y1vegq/8yq/ERz/60dbfPz4+xgc/+EH88A//8GUcHhEREREREW2wSwlsn3/+eUgp8dRTT9U/e+aZZ/CpT32q9fd/6Id+CN/6rd+KGzduXMbhERERERER0Qa7tBnbra2tiZ9tbW1hNBqd+t1PfvKT+N3f/V285z3vWfi6H/7wh/HWt74Vb33rW3H37t1zO14iIiIiIiLaHJcS2Ha7XQyHw4mfDYdD9Hq9iZ8VRYHv/d7vxb/+1/8atr14+e+73/1uPPvss3j22Wdx/fr1cz1mIiIiIiIi2gyXEtg++eSTyPMczz//fP2z55577lThqMFggD/8wz/EP/yH/xBPPvkk/sbf+BsAgC/6oi/C//pf/+syDpWIiIiIiIg2zKVURe52u3j729+OH/mRH8GP//iP47nnnsPHPvYxfPzjH5/4ve3tbfz5n/95/d+3bt3C2972Nvz2b/829vf3L+NQiYiIiIiIaMNc2j62H/rQhxDHMd74xjfiW77lW/ChD30ITz/9NF588UU8/PDDePHFFyGEwI0bN+r/XwWzDz30EFzXvaxDJSIiIiIiog1yafvY7u3t4ed+7udO/fyxxx7DK6+80vo3X/AFX4DBYHDRh0ZEREREREQb7NJmbImIiIiIiIguAgNbIiIiIiIi2mgMbImIiIiIiGijMbAlIiIiIiKijcbAloiIiIiIiDYaA1siIiIiIiLaaAxsiYiIiIiIaKMxsCUiIiIiIqKNxsCWiIiIiIiINhoDWyIiIiIiItpoDGyJiIiIiIhoozGwJSIiIiIioo3GwJaIiIiIiIg2GgNbIiIiIiIi2mgMbImIiIiIiGijMbAlIiIiIiKijcbAloiIiIiIiDYaA1siIiIiIiLaaAxsiYiIiIiIaKMxsCUiIiIiIqKNxsCWiIiIiIiINhoDWyIiIiIiItpoDGyJiIiIiIhoozGwJSIiIiIioo3GwJaIiIiIiIg2GgNbIiIiIiIi2mgMbImIiIiIiGijMbAlIiIiIiKijcbAloiIiIiIiDYaA1siIiIiIiLaaAxsiYiIiIiIaKMxsCUiIiIiIqKNxsCWiIiIiIiINhoDWyIiIiIiItpoDGyJiIiIiIhoozGwJSIiIiIioo3GwJaIiIiIiIg2GgNbIiIiIiIi2mgMbImIiIiIiGijMbAlIiIiIiKijcbAloiIiIiIiDYaA1siIiIiIiLaaAxsiYiIiIiIaKMxsCUiIiIiIqKNxsCWiIiIiIiINhoDWyIiIiIiItpoDGyJiIiIiIhoozGwJSIiIiIioo3GwJaIiIiIiIg2GgNbIiIiIiIi2mgMbImIiIiIiGijMbAlIiIiIiKijcbAloiIiIiIiDYaA1siIiIiIiLaaAxsiYiIiIiIaKMxsCUiIiIiIqKNxsCWiIiIiIiINhoDWyIiIiIiItpoDGyJiIiIiIhoozGwJSIiIiIioo3GwJaIiIiIiIg2GgNbIiIiIiIi2mgMbImIiIiIiGijMbAlIiIiIiKijcbAloiIiIiIiDYaA1siIiIiIiLaaAxsiYiIiIiIaKMxsCUi+v+z9yc/tiz7dR/+iYhsd1fNOeeec8/t3uMjqZ9oE5ZowYCA34RDDzyzBOM3E6CJIWli/wGEBwYMDzQQNNHIHtiGAQNuBMMTwTZoyYBlkCBggpZIPvI19/TV7Tb7iPgNIiNv7H3q3OZ19973YgGFqtq1KzMyMvfeuWKt7/pGRERERERERER8qxGJbURERERERERERERERMS3GpHYfkMxDAPW2q97GBEREREREREREREREd94JF/3ACLux/X1NcYY0jQlyzKyLCNNU5IknrKIiIiIiIiIiIiIiIgQkSV9Q3F+fk7XdfR9T1VVHA4HAKSUE8n136WMwntERERERERERERExK8uIrH9hqIoCoqimH7v+56+7+m6jq7raJpm+luSJEeqbpqmX8eQIyIiIiIiIiIiIiIivhZEYvstgSess9kMAGPMRHT7vqdpGqqqAkAIcaTqZlkWVd2IiIiIiIiIiIiIiF9aRGL7LYWUkjzPyfN8emwYhiNVd7/fT39TSk0kN8sykiRBCPF1DD0iIiIiIiIiIiIiIuJnikhsv6G4ublBSjkptV+mljZJEpIkoSxLAKy1R0S36zrqugacqhvW6WZZhlLq535cERERERERERERERERP2tEYvsNhZTyiIiCU11Dopum6eeSUW9JzrJsekxrfUR2D4fD1FbIE+mQ7EYLc0RERERERERERETENx2R2H5D0XUdUsq32vsMw3AUHBWqup6Qfh7ZVUqhlJqCqay1Rxbmvu/Z7XZHzz9NYY4W5oiIiIiIiIiIiIiIbxIisf2GYjabTUnIWuvpcaUUeZ5PKiu4IKmwnvbUwvx5/W+9JTkMpgotzP57qBz7FGZPdmO9bkRERERERERERETE14lIbL+hWC6X088+Adl/eYXVw5NTIcREeLXWdF03/R4S2JDs3kdI77MwG2MmontfCvOpavwuIh0REREREREREREREfGzxi+Mfdze3vL3//7f53/73/43Hjx4wO/93u/xt//2337ref/1f/1f80/+yT/hL/7iL1gul/ytv/W3+L3f+71fOaL0/PlzkiRhNpsxm83eSkAOLcQh4TXGTM9RSh0RV19fG5Jdr74mSTKR0/vIrpTyrd66njx7VbeqKg6Hw/T8r2KRjoiIiIiIiIiIiIiI+EnxC2OL//F//B+TZRnf//73+eM//mP+1t/6W/z2b/82f/Wv/tWj59V1zX/2n/1n/I2/8Te4vr7mP/gP/gP+0T/6R/xH/9F/9Isa6jcCf/zHf4yUkrIsJ4K7XC4py5KyLJnNZhNhDOHJa/gVWpmllEeBUMYY6ro+IsQhyf28RGal1DQej3C/97Uc+irhVxEREREREREREREREV8GvxBiezgc+Kf/9J/yf/1f/xeLxYK/+Tf/Jv/uv/vv8t/+t/8t/8l/8p8cPffv/t2/O/389OlT/vbf/tv8H//H//GLGOY3CnVd03Ud19fXKKWmIKkkSZjP52RZRp7nLJdLFovFkbJ7qqwaY+5Vd0PlNiSuWmu01kd1tV+2btf/zcPX64Y1u2H41SnZjUnMERERERERERERERFfFb8QYvv9738fpRS/8Ru/MT3227/92/yLf/EvvvB//8//8/98S9X9VcAnn3zCdrulaRratqXruun7brfDGIOUEqXU1LvWq7jz+fyI8JZl+VbNrLX2XnU3VG5DS7K1lrZtadv26O+e4IbkNPy/sF53Pp9P24pkNyIiIiIiIiIiIiLiZ4VfmGK7Wq2OHlutVkc21fvwX/1X/xV/9Ed/xD/+x//43r//F//Ff8F/+V/+lwDc3Nz8TMb6TcH3vve9qY7Wq7dVVbHf7yey6x8fhoHtdsv19TXgrMS+JnY2m00K7nK5ZLVaTYTXk9LQShwGVXmVN1R3wzRmYCK7IZn1RDckvKHl+PPI7mlAlUdIdr0FO5LdiIiIiIiIiIiIiAj4BRHb+Xx+1BsVYLfbsVgs3vk///P//D/ze7/3e/zTf/pPefDgwb3P+Tt/5+/wd/7O3wHgd3/3d392A/4GoKoqrLUIISjLkvl8zuXl5fRY3/cTsT0cDuz3++l3Tw6rqmK73U7qLkCWZcxmM+bz+UR2F4vF9L0oinuDqkJ11xNerfVEaK21E+n16rKUcvr7qZXZ26r93+9LYo5kNyIiIiIiIiIiIiLiy+AXQmx//dd/nWEY+P73v8+v//qvAy4c6V0W43/2z/4Z/+Af/AP+u//uv+Pf+Df+jV/EEL9xePDgwUQih2Gg67ojm7CUcrIcX15eTq1+PPlrmmYivF7d9eQwVHe9kurJrifRi8XiiPC+S90NVV2//VDd9cFVPkFZCDHt06cyh8pukiRHf/9pyG4MqIqIiIiIiIiIiIj41cAvTLH99/69f4//9D/9T/nH//gf88d//Mf8L//L/8I/+2f/7K3n/v7v/z5/9+/+Xf6b/+a/4W/8jb/xixjeNxL/+l//66Mk5NlshlIKY8ykng7DQNu2R/ZgpdRESB89ejT9zSu8viVPVVW0bUvTNJPCejgcGIYBYAqrKstysi6HZHe1Wk01vSHxBO5Vd/12/d/DcQFHhNeru6eEVwjxzh67p7XCIdn9ssFXERERERERERERERHfTvzC7u7/4T/8h/y9v/f3+N73vsfl5SX/8B/+Q/7qX/2rfPrpp/w7/86/w//9f//ffPTRR/zn//l/zna75d//9//96X//5t/8m/z3//1//4sa6jcCf/RHf0TTNBO58yrq2dkZFxcXnJ2dTeqqlHKqx71POQVHeFerFcvlclJ3gYncenXX1+/6oKqmadhut5PyqpSakpc90V2tVtP4VqsVZVmilDpKZg777oZj9Cq0V3/Dcfn9eXvxfequrye+zz59SnYPh8NREvR9ZPe+Hr4REREREREREREREd9siO12a7/4ad98/O7v/i5/8Ad/8HUP42eG//V//V85HA60bTuprZ5cWmsnRTUklBcXF5yfn7NYLMiybCKwIeENlVNgUi79c4UQGGPouo66rjkcDtM4PAn2pDe0RwshprpdP57lcslsNuPs7IzlcvmWsgufqa2npNcT0GEYjizYHj59+b5kZk92TxGS6/ArJLv39fCNZDciIiIiIiIiIiLi68fv/M7v8Pu///v3/i36Mb+h2Gw2CCGm9OI0TbHWTrWlnlju93vW6zXwWWJxkiQsFgvm8zmr1WpSeb2NOCS8IZkM4fvknp+fH207JLxVVU1E1/+82+24vr5Gaz21I/Ith1ar1UR4/djm8/lbais4u/Lp+Lyi69VYP6amabDWTq2PvK35vmTm0z67wFtkt2kaqqqa/n4f2Y0hVRERERERERERERHfHERi+w3Fdrud6me9ahgSs6IomM/nPHr0CCHEFDDliW9d12y3W549ewZ8VsPqk5CXy+WRwnt+fj4pk2Fo1anC6+tbV6vVUSLyMAxTOyJfv+vrdpum4fb2ltevX0+EN8uyqXbYk2+vPnul15PrEGF9cThOH1TVdd00Jq8+hwnMp62I/N9Og7FOe/x6Qu9xH3GOdbsRERERERERERERXw/infg3FOfn53Rdd6RQ+p62+/2eYRiObLdpmpLnOWmaMpvNpqRkbyvWWk9W4qurK16+fDmRvyRJyPN8Sln2hNcTTU/YQhXV26I9kiSZFFngyErsA6sOh8NEEH097/X1Na9evToivH4sZ2dnR4TX1+9mWXZUv+v3ExLdUOEdhmEKkwrri72K623dp6TX9//1+KKQqq9ii46IiIiIiIiIiIiI+NkhEttvKB49ejTZe/u+J03Tqd7U94/16cKeZJ0SXk9aPVlcLpdHymzTNBNZraqK29tbrq6upprWMCjKW4cfPHjAfD6f6mmVUtM2QvXUwxNeb4GGz9oA1XXNbrc76sdbVRV1XR8RXm8x9sfgFV5vaV4sFpRlOZHRUyX51NLs5y0kvKd1tuGCwSnpPQ2pCq3Mfpuhlfm0BZHfXkRERERERERERETEzwbx7vobCq018/mc9957jyzLJgJ52q5nGIbJNusJmye/1lqapjkKhgpVxCzLJoV3uVwCHFl6vcq73+/ZbDY8e/YMY8yRslqW5ZHKO5vNJuVYSvmWeurh2xItFovpMT92n9LsFV5/vIfDgZubG16/fk3XdSilpmNYLpecnZ29ZWvO83wio145DQnvqdLr05mbpsEYM82drxf2Ku996u5sNjs6f6cJ0Pepu6cKbwyqioiIiIiIiIiIiPjqiMT2G4r/6X/6n+j7flJLfV2st+f6dj9KqYl8eYtvVVUTqfI1t56wtW1LXddTojB81rPWE6s0Taca2Pl8Pm3fE2bf99aTtevra/78z/8c4Igsl2XJ5eUlq9XqSFVVSh2RyzBZWUrJbDZjNpvx6NGjaT6MMVNIlVd1Q0vz3d3dVMPrjyHP86lFkp87T6Y94fX9geEzUn9aYxwuHtR1PdnDw7m7z8rst39KqEMrc1VVbyncp2FVfnwREREREREREREREfcjEttvKP6tf+vf4u7ubiKqn376KV3XTXWzIXFbLpcTgTs7O+Py8nJSKD159YpnXdf0fX/Uq9ZaS1VVEyn0daen9aeecOV5PhFCT3b996Zp6LqO3W7Her2eVF5vaw5V3vPzc5bLJUVRTEQzTGwO63illJRlSVEUXF5eTo/7/YYq9n6/n+bt7u6Oq6srhmGYjinLsqmG19uk/RyGCq/vEQy8RXRPyW9d10dtiZRSR8ruaVBVURTTtk+DqkKLNMTa3YiIiIiIiIiIiIgvQiS231C0bcvjx4/5a3/tr3F5eTmpk3d3d2y3W3a7HbvdjsPhwN3d3URQgYn8eMLmQ53Oz8958ODBUT9Zr4T69GKv6HqS5ZVeX+vqvzy58kTRE+DVakWSJG8RXk/+PMF+/fr1RAQ9WQ5Tkn39bJ7nkxUbPlM9w5pYIcRE6v1zTm3NYYBV0zTTXPo2R74W2ZNuP28+tKooiomUhiT8tC1RSHzvax3kyfV9hDfLsmnBIKyd9tu7r3b3PpU42pkjIiIiIiIiIiJ+1SC226394qd98/G7v/u7/MEf/MHXPYyfCay1zOfzqb2MUoqPP/6Y73znO/zar/0a3/nOd/jOd77DBx98wMXFBW3bTkR3s9mw2Wwm1dKHT/ka21CxDEnvxcXFZBX2qrDvm3s4HKZEZW8DDoOsfA/ZsObVk9WQfPmfPWHTWk/WZt+L1rcu8m16PLH1hNOPuyiKaV9Syokkh7ZeP7bwcWPMRNZDon3apigkvF5tDufLE/D5fH5E8j1J9QnKp0pv13XTQkFI0P3CgF808McWqrxJknxuf1+PUztzDKuKiIiIiIiIiIj4ZcDv/M7v8Pu///v3/i3e7X5D8T/8D/8DL1684NmzZzx//pwf//jH/PjHP+Zf/st/+ZYC+OGHH/Kd73yH7373u3z3u9/lO9/5Dr/1W7/Fw4cP6fuezWbDdrudvvb7PdvtlvV6PZGiMEHZh0l5xdIrvWmaHrXx8ZbZuq6PLMC73W4ikKGNtiiKibSFlt/FYjGplL4m2Cuznljv93uur68nwumJX1EUlGU51c6WZTlZnj2ZC8kjOMKbpulUAxwqvKGCXVUV2+32KKn5+fPn07a8PdqT3LAH72q1Isuyo3Apbx++z9J8akMO645DwnuqHPu5u6+/76md+T51N9bvRkRERERERERE/DIgEttvIIQQ/NEf/RHWWoqi4Ld+67f4t//tf3sKVer7nru7O968ecOzZ8949uwZn376KX/4h3/I4XA42tYHH3wwEd5PPvmE73znO/yVv/JXePz48UR6/dfhcGC3200pyF5R9UqvD0MKa1K9xdmTttMWO97+W1UV+/1+Uiy9yusJqq+f9e2FpJTT9zRNp/ZAfkx939N1Hdvtls1mAzDV0Ybb9OMNCa+3ToeENwy0StN0Smv2gVJenfaW8P1+f3RcNzc3Exn16utisTjqwTufz6dz6ImlDwDzKu99Cq9PqK6qalo0CNsSKaUmBdsvIPjHQ+XY11afLozcR3hj/W5ERERERERERMS3CdGK/A3F//g//o+TldjXhXqy4+tKPSHyycl5nqO1Zr1ec3Nzw5s3b/j000/59NNP+fGPfzwRQI+nT59OtuZPPvmEjz/+mA8//JD33nsPY8yRtTmsUfWpy570CiHIsowsyzg7O2M2m00Kqq+59XZhY8ykytZ1fWQD7rpuIm1hSyH/NZvNJtXXK6be2uxbH3nC61VfYNpm2E/WE06/Ta+A5nk+WbHhM+IX2q7DY/GW7VPF2tcqeyIfnjN/LN5W7Qlw2CoptDb7/Z0qvf6a8EQ/tJu/S+U9XYAISW9oZ35XD99IeCMiIiIiIiIiIr4ufJ4VORLbbyjC0CVPKr2leLfbvdX2xpNNT7RCRc+rhMYY7u7uuLu74/r6mhcvXvDixQt+9KMfcXd3d7T/x48fT3W9H330ER999BEffPABT548oSiKSdVdr9cTOfU1uF5l9CTLK4pFURzVyc7n84l8+eM9DV0KSa8niF7N9XZjTwxDpdITX096/Xe/nXCePREMWxXN53PKsqQsyyNV1Kc2w2d25HDO4TOV1yu9/vxtt9tJMfVj8gTaz4NPYw5VXj93nvSGxNWT8JD0+mRqf/34dOlTlTe0bKdpOs2J/79IeCMiIiIiIiIiIr5JiMT2lxBhz9WwHtSrrCHxrapqSjz29aSeFHniC7Db7bi9veX29pY3b97w4sULnj9/ztXV1dG+Z7MZH3/8MZ988gmffPLJRHofP37MgwcPaNv2qK7Xk17/1bYtwESIPGHzZG65XE62Wp/gHPbh9aTXH18YkOXtvV7Jns1mk4ocpjoLIaaxeMLr1UsPT3r9WJIkmUinJ5shwQvtzd7aDByRvlD5Dfvy7na7aZHCK9cenoQWRTHVEXul1yvlYXp0qMqeWsND5T/sIXyq8pZlOR23J+whgf4iwhvOSURERERERERERMTPApHYfgtxOBym2k+vQH6VNi4+DMlbYsP2QKG12BMrTw69uhe2pVFKTYrjZrOZbM4+3Cokg+Dqej3x9Wrv+++/z4MHD0iShP1+z3q9ZrvdTvbmkFx6i3NIlkJ783w+P0r69UnKIcn3hNcTuZCketLma4Xn8/lE4oBJbfUk+j7Sq7U+skuHpDdUQv0c+nPnjytcYPABTn6cp6FZ+/1+Oo9h2Be4EC1Psv0ceYU+rLm9Lx05JL3+WEOV1xhzZPn22/LbCwmvH/d9hDdUdiPhjYiIiIiIiIiI+EkRie23EP/8n/9zrLVHbV88qfBBQV6hC8nvV4Enb97y64OjPAkObc6eVHly54m2lJKu66ak5bu7u4n4Pn/+/K263sViwXe/+10+/vjjqab3ww8/5NGjR1OLo81mM43B23a9xTYkqV7JVEpRluWRddfPx32Wbk94vWXa1816khj2APZEtSiKac78vPm582Q8VFk9Kffb82TTh1iFyqq3N4c/A9MxenXeq7w+tdl/+XZJfkHA798TbL/P+Xw+zY8n3p6YhwQbPlsY8dv2Fm5PekNSHiY/53l+pFz7sYfqsB/faSuj2JYoIiIiIiIiIiLi8xCJ7bcQP/zhD49qMX3NZEigwhY9PhTJE19PZnxNZmjB/bLQWk/tfLza65Vbr/R60usJV1jT6dvQeIu0J77X19dcXV3x4sWLI3UP4KOPPpqI74cffjhZnC8uLpBSTsR7s9lM4VNeTW3b9mjfvrWQtyd7xdeTxdCq6+3Nh8PhKITK1896q68nuWdnZ9P2PJkDJgLoFwV8knNI6oQQ0/a80upJr1+s8MQYmBTaUKn1iwoheffnyivwXrX2147/35CI+jRqH0Dmexl7ddtfQ6eLJqGi7effX59+/r1i7Y/zlLT6uT+dG3/uTgnvV7l2IyIiIiIiIiIifvkQie23HGGwkrfFdl032VNPbbxhHacntJ78htZVT2pC8vtVLM++lUyYmBy2DPLE99RqHNppvS3Z1+R6xff169dvtS7K8/wo0OqDDz7g/fff57333mO1WmGtZb1eU1XVRHxDRdWTL3+sfj78nPj6VSHERGrDY/Rk0Yc+eSLn58/P6Xw+5+zsjLOzsyPbrj/+sEbYjwuYaoTDhGZPOP22TxX6kBR6ou4XPMLH/LXiF0v88fjj9CQ5VJpDi7Pf/33hU6fXS6j0+rn3xxkGioWLMqfE1ZPeEP5/Yh1vRERERERERMSvJiKx/RVAGCblia8nF6Giekp+4TPbrCcYnlCF5De0PX9ZIuHrLsOEY094w/peHy7liV/bthOh9MnLXqVdr9dcX19zfX1N13VH+5vNZlOg1ccff8xHH33EkydPuLy8ZLFY0HXdtJ2wtjdsQ3TffPjj9wTPE0VP1sI0aG8JDgnnqWrsie9qtZpIsdZ6On4/L/58hfbkU9LrE5y9Ahy2+/Hk0P+vV3l96yHfBskTXX+dhFZtvzhySnrD6yIkvf65fjynNb3W2mlRJlR6Pen19uxw/kPSGyrtHtHWHBERERERERHxq4FIbCMmeALlA4o8kQnJr7euhn1aQ7JxqvyG7WhCRfGL4Ml113VHdueQ8NZ1PZHhkAwNw3DUAsn32/XtjN68eXNELgFWqxUfffTRRH691dnX0nqbtVec/Zz4sXri65VCPw++TY9XZ/1zQ0U9DGfycxpajn0NrE88Pj8/n0Ky/Hnzx3xferJXaj3p9eFYvmWRr6kNa6P9wkNYDxvam/3iQtiT1x9HqLqHKq4P5/JE11ubw4URT8691doTd29LDtsyebU3VHq9ShsS6XAOPEKSf/oVVd6IiIiIiIiIiG8fIrH9FuL6+hr4LJ3YEw7/80+SlPxl4YmZV359W5yQpIVK52nv3NCaG9aSnqq/XzT+MPjJB1Tt9/sjcufttZ6IhvW2d3d3k805/O5bGp3iwYMHfPDBB5Pi+/HHH08256IoJpJ9Snw9Mez7Hvisvjckvp68huqsJ/FeXQ9reoEju60nvrPZjNVqddTCKEw39uq3n4tQ3fQhW/68+O2F5yRMbb6vptuTUD/PocruFx7C/rxZlh0pqp5ke+J7Gl4VWpS96uyDrLzb4JT0+rk6fV144uvHHl5vITGOtbwREREREREREd8OfB6xjV69byiSJJlu3E/7mobwqtQXEeCvQoKllJMK+y54MuUJ2amFtWkaDocD6/X6iPz67XvC5onNqf3ZK4z+eWVZcnZ29tYY/BxprSfi6W3GXuVt23Z63JOvpmm4vr7m5ubmLQL8z//5P2e9Xr91zOfn5zx9+pQPPviADz/8cAq68iRTa31kc/bterzi6OdBCHFU1+uJnCepXrXc7XaTmn04HHjz5s20gOCJWqjQ+lY/i8WCp0+fTunQ3v7rLdN1XXN3d3e0MBGmQmdZNqnHp8Q3XMAwxpDn+UQu/fXlSedp7bc/D752NuybG4afhe2cTpO/fW1vGAIW1vCGyc1eVQ4dBP7aC23Pfix+/CHZPSW+ERERERERERER30xExfZbhNAeHNbJht/91334PNJ7+tjPCqH668nvaeiVr1f1gVceIenxicGh1dWTus8bc0h8fT1sGGzlk4M9efShSk3TcHV1NZFfT3o9Ab67u3trX2VZ8uTJk4n4fvjhhzx58oRHjx5N6qpXe09rfP1xe5IZBiv54/bEy8+lb8nk5zfsIesXPEKl3Nf4np2dTcRVSvlWL1uvIoe26dDm7ImlPw/ebuyJnyeUp7Xc3voMTAsMYT21/x62X/LKbWh/9yFaoep631e4OBSSXT8Ov8gQXjunQWqndeX32Zq/rPU+IiIiIiIiIiLip0NUbH9J8GVvoL3q93lE+NT2eor7yO59RPiLSHCo/i6Xy3c+L1R/PbEM1d/9fn+UqOwRtjzyX179DVVgT4qWyyWPHj06mqtT4uOVX092wxAu/3jTNNzc3ByR3/V6zXa75U//9E/5l//yX07W5HAu3nvvvUn1ffr0KY8fP+bx48cTUWyaZurf64l22AvYq7+eVF1cXBzZecP0bP//6/V6mt/QiiuEmFKc/XdvdX7w4MFEIP02/fnwSny4GBEGS81ms8luvFgsjuqv/TGEX55ohj+HtuaqqiYLtNZ6uv78+fZWbb//MEQrJKf+f0KyGiq8Xln230Pct71TEvwulTfW80ZERERERERE/PwRie0vIcKgnS/CqbJ2HxH26tZ9JDjspxqS3XcR4XfBk4DZbPbO53jSExJNb9X1yq8ncafjvY8Ah4TXE7H7LM+nRKzv+yOF17cU8mTc17ne3d3x6tWrKcXZ255fvnzJv/pX/4q6rt86xsvLSx49esTTp095+vQpT5484cGDB1Pf3CRJ3qrx9fXEIfy8P3jwgPfff/+oPZBXeH2tsh+TJ82h1dnbkufz+ZHV+fz8fCLUwNGCxG634/b2diKM9xFfr7z6/r1hUFbYIshff57k+vn3an9d15Oi7EmvH/dp2FnYlzesJw5DvMJwLX/uw3pePxa/eBTWL/trzKvbfj/vIrxR6Y2IiIiIiIiI+NkhEttfcYQ9T78I71J/w56u3lL6eUrw56m/nxeMFdpTF4vFvdv3hCO01obfQwIc9pA9HZ+33IYqYJgAPZ/Pef/994+UxPtsz54Ah+Pwdt/NZsOrV694/fo1r1+/5ubmZlJ+//AP/5D//X//3986vjRNefjwIe+9995kc378+DEXFxeTxdirzr7GeL/fH1mCgUm9nM/nk91XSjmN3bcA6vue/X7P3d3dUSiUn6s0TZnNZiyXy0nt9e2MwhZAYW2zJ76n9nNPPD3hzfN8IsFnZ2cT8QzVdV+D7rcf1vT6PsFhCvRp/1xfnxySX09I4XjhJsuy6bHwejtd9LDWUtf1UWJ1GG4VpkKHLY1OCXAkvRERERERERERXx6R2EZ8afgb/C9DhMN639P6X/+7JyDvIsGnitoXEWL/P2HI0Gq1unfbX5YAHw6HdxLg0A7ria+vBy6KYrL0ehXvPvLr643D2lY/jt1ux8uXL3n58uVEfK+vr1mv17x584Y//dM/pWmat46tKAoePnw4kd6HDx/y+PFjVqsVq9WKsizfah3kCZqfF0++ZrMZjx49muY6TEQObdqvX7+eSGV4Hnx9rFd9V6vV1MrIh1v5FkmenNZ1zXa7PbInh310Pen16q9X2fM8nxYaQrdBmNjsf/akPayz9Up12LopTG8OFeBT94E/Dn9tha+DsJWRJ+K73e4obTpUjU/VZU9+T9XfiIiIiIiIiIiIzxCJbcTPBV+m/tbDE5F32aFDQvCuYCzgS1mhw4TonyUB3mw23NzcvEXU/b7Dlj9eJfQE6sGDBxN58e1tQgIc9hoO2y951ff169cTAX7z5g23t7fc3Nzw6aef8id/8idT/90Qi8WChw8fTgT44uKCy8tLLi4uWC6XZFl2RF49CfTkFpjU7IuLi6OUYW8b9lZhv0Bwd3c3bStUQn0bIG9zPjs74/z8fLJe+6/wHPh2Rp44eruzJ+Snyu9isTjqnevPkx+jrx/259NbqT3xDZOU/XH7QLNQ9Q3reT3JttaSpumk9IZKrv/dX+s+VCwc431Kr792wv2G5De2LIqIiIiIiIj4VUMkthFfO0KS6YnH5+GLSPCXDcd619cpCQ6tyV9EgD2pC8mX/+6TjO/u7o76w943B6Fi5wnMo0ePJlXS7zMMv/IEze/Tk+Db21uePXvGixcveP36NW/evOH6+prb21v+8i//kj/8wz+8d57Oz8+5vLzk8vKS9957j7OzM5bL5VTvW5blRGC7rqOqqqOaUyklZ2dnE8HzSqcnlF5F9UnUu92O6+tr2rZ9qyVQmIjsa3x9myV/zoQQ03iqquLu7m46L16NDa3I3lbuye/5+fmRDfm0TVLYw9mr676+NwyQOq3b9ufxtHVReO7DuQn78/r5DEn46ePhdRNeO945EC3OEREREREREb8KiMQ24luHr2KJDsOx7iPAX1YNvs8WfR8R9mra5yVAh/WYnih5xTBUgauqOgrCuq8PsFecQxK8WCx4/PjxEUHzfXRDxdfXAbdty+vXr3n27BnPnz/n1atXXF1dTervn/3Zn72zldZqteLs7IyLiwvOz8958OABy+WSxWIx2Z5D4h2q80KIqS73dJ7DdOfQpr1er3n9+vVkUwaOSJsnqsvlcrI+LxaLSRH357vve9br9Vs14ackMVR+Ly8vJwLqVf9QUfftozyxDhdXwtTkUHENiXWe50fn1s+HP/dZlh0RX/+4H0dd1+x2u6Nr389naKP2+/ZhaafEN6q9EREREREREd9GRGIb8UuNrxKOBbxFet9VI/xFIVmfR4TDMKKiKO4NygKm2sywFZInvqF1dr/fs9lspvGFJPg0mffUBn1xcUGapvzmb/7mtE+/X0/Y/M8vX76clF8feuUDr168eMGf/MmfvNUmB1zNr1dYvc3YW429/Tg8Xk/aPKnzpNIHQPn59T1wwzZRXv199erVW314Q0WzLMuJgHuC52293k7tCerV1dVbwVvhfPpaXE/S/X78fsNaaj++/X7Pzc3NUajX6TbD5GhPgsNjCK+ZcDthkrmfL7+Icd8161Xm0Gbt66u94uyP+V3XakRERERERETE141IbCMiAnyV2mC4nwjflx79ZYnwu+zQXjk8DcsKx9F13b0kOAxP2m63E3E8Vf1OQ4rCtGAfIvXX//pfP+pH69vfeAJ+d3fHj370I168eDHV/fp+vzc3N/z4xz++t82RUorz83NWqxXL5ZLlcsnFxQWLxYLlcknXdVPdb0gyPfnN85z5fM6TJ08mxReYxhVapruu4/b2lqurq6O+yN4u7ZVfv02vqnpCnGXZNP9N03A4HN6qr/YqqSeL/n/n8/kUKKaUOrKTe5XeJ2dvNpuj4LLTwDJPOv12w5rboiiO5jcM1AoXasIUZ/+4n9NwTvI8n0j3fcQ3hlpFREREREREfN2IxDYi4qfAVyXCp9bodynDn9c7+HTf9ynBpyTYK21eFfW1wP4rJL++TjckwaEa7EnwaUqvUmrqwxs+HtYeG2NomoaXL1/y6aef8vz5c16+fMnV1RWvX7/m9vaWTz/99K2+vB6e9PrWRovFgvl8znK5nAior1UdhuEo7dgroH5cYYJyGJDlSbCv+Q0XAIAj9ddvM7QWz+fzabz+eKuqmhRa/+XHEdqEQ9tzGELlFw/8uWqahu12O1nK77NSewLqx+W3Haq+p9emMebIMu736VsnhSTb/49fBAmV5tDq7Gt9Y9/eiIiIiIiIiJ8nIrGNiPgF4qtao0OlLSSYp2T41Hr6rn2fkl2vxq1Wq3uJsFebPbEKVU+vCPd9z+FwmMYXqsHAUT2wP/7333+fjz766Egd9rZdvz9Pdr0FOrQ/397e8oMf/ODedkfAFHC1Wq0mu7O3PnuyBRyRdX/cvkbX17uGSqYn/Z4Mh0FSYdqx3563+IZKZ2grVkrRdR1FUUzJ0aeLCJ6o+nnyFvazs7Mje3BIfv252mw2XF9fT0FX/nyEZNR/ecvzbDabVGt/rYZp2N7W7NVwX6Pua8JD1drPw2lglye+IeH24VoRERERERERET8JIrGNiPgGI0xL/rL4PHt0+OUJ2lchw6EqekqCQ6vrqRockmFfG3vaO9erfz7AaDab8Wu/9mv8xm/8xkSOQhXTt8fxYVevX7/m9evX0+/e/vwXf/EX97Y8klJO6q8nv/P5/EhlnM1mAG8ptkqpqU7Xjyvsu+vJpf/5cDgc9eb12wnbJIVqZ6iq+lZB3vLrLczh4sFpDbGfx7Ozs6OkZ78I4omvD/XyP2utjxR5T0bDvsZ+fnxP4bB/r9+PV/49AfZJ3bvdjrZtj44/VP/9Nr21+lT9Pa0tjoiIiIiIiIjwiMQ2IuKXDF/VHg0/HzLslcbFYvEWEQ779IZk8JQIhxbmUMn0+5dSslqtOD8/56/8lb8y7T8kwEII6rrmzZs3U6ujV69e8ebNm8n+fH19zfe///3Jans6n77VkU9bDhVHr3yGNbPhXPhaXU9eQ3XdE27/2G63m2prwxAtT/b9cXmyGe7b1/7673meT2Pw+/PK72kttVeolVLTvj35rapqIsSheh2e47A/syeh/vf5fH6U8hxec2ErJa01TdNM9cp+P+9Kqj49D5H8RkRERERE/GojEtuIiIivnQwDb5EsT54+r2WTJ8K+LtaTL/94SIQ9Mf3N3/zNo+P15MlaS9M0XF1dcX19PX1/8+bNpAB7Yvyu2mffXujU9uwtxL4O1e/bk/xQEYfPamU9wTw95v1+f2RRD8+jPx5PiP0+vZobhpOF7X5OrwdPgv1Y/TGE6q+3IR8OB3a73TSWsI7Yj+e0t64PJfMqbahG+zGEfaGrqpqUXx/85euoQzXfq8x+/kMF2O8/VLEjIiIiIiIifjkQiW1ERMRPhJ8FGb6vbviUvN5HIsMaYa+GhgFZ9xHh0CYdWnHD/SRJwuPHj3nw4AG/+Zu/OT0GHBGh3W7H3d0dt7e3R19v3rzh5uaGu7s7nj9/zuFwuHcesiybEqBP60x9LW5Ye+wVSE/ewrAo3wbJWjulHPs58G2Q/KKCJ9Gh4hoGWXnyGpLF0NocqqFhkrbfnifTPpjKj20Yhon8wme140mSTHPs9+nnI0yTTpKE8/PzSZ32+w/PqW+B5ROlr6+vJ/ILx/2OfVBXaD2fzWZvWa39AkFERERERETENx+R2EZERPzC8JOQYU/UvqxCfBq+dF9YV0jETol0SIRDVTLssZumKefn53z88cdHtmFjzFESs2+B5Elw+PP19TV3d3dTO6R3qcBhCJYnXt4C7WtwvdXXz5ffvyfC4byHY/X1vp4YeuIJbhHC/78nwJ58CiEmAuwfC9Od8zw/Is/eShySaj9Wvy9gqkU+tXOHtddhiFbYf9irtKvVahpbeH69su+t7pvNhtvb24n8egLrSbZX2EPS61Ov5/P5pDaHKdsRERERERERXx8isY2IiPhGw5O0n4QQv4vwnj7mlUVfh/pF27yvZdNpuyZPhM/Ozvjkk0+Oald9enDYM7Zpmon83t7ecnNzw3q9nsjv3d0dP/zhD9lut/eOLUmSiQB74uXrXMMwKK+mhgpvaMcOxwSfBU6FrZGAyXp8qijDcSJySG5DlbcsyyPC6+uC/fbC89627ZF92+/PE2K/2HDagsqTU0+CfX3yYrGYnust32GvY7+Y0bbtWzXP4Rg8iffb94nangCH7aA8Yf6q13FERERERETEl0MkthEREb+U+EkSpYF3kt/Tx+77/RTeEuwtz54gnrZx8s95+vTpW6Q5DNjy/Xm92rherycC7L+8Kvzs2bN3WqHB1QN7AuzVSE/SQstukiTT+L3Ca4why7Ip4Om0tjYkvN4yHJ4X/z1csPDE1yvM/ufQmh3+3Y/RP7eqqqkmOwwq87/78+Hrff3/+ppb34rJq86r1Woix2ESdWjx9rb2w+HAer2e6snD4/PEPWz15Bcf/JcnxmHydSTAERERERERXw2R2EZEREQECInWV8F9lukvS5A9MQzrYz1puq+H8QcffDARTa8A+22FJLjv+yPCe3t7y2azYbvdTo+t12t+9KMfvVMJBqZ6VP/llUhPMH0drieZYeDVabiVP8bwCz6rmQ3V3/D/Ty3VYY9db4f2ddehPds/HtqqQ+XV1/qGirA/Dq92++PztbmehIbhW34RwJ8D3+rI1/76c+HPbbgA4Imv/x4GYJ0q8OFXOOcRERERERG/6ojENiIiIuJngJ/UMg1v26Z/EoIcktwwTfnp06dHzwv764aKsdaa3W53RIQ3m81Efj0ZfvXqFev1elImT5Gm6dQWyZM/H/rk1cuw7VDY9snXxIZj8vPZ9/00zyEZPj0Hp/2Gw3Pyrt65obofqqWeEIf7Csmkf37YesmTU09K8zxnsVhMzwkDyfz58nW//ntVVdPCRKjynxL3Uxu0/x5aoMNa7EiCIyIiIiJ+mRGJbURERMTXjJ/UNg18KTJ8+nNIfEMyHD4ehmeF6rF/7HA4TKQ3tEBvt9sjVfjFixdUVfXO8fva4LAfrSe+XnX1hM7XwwJvEeLQDu3Jmw+F8sQwbCEFn1mT7zsXIRn2RNJvIyTDfl+hKux/DuuMwzpnH3bla429RbksSy4uLqY6aL/dcFGiruuJBO92u7fOVVgzHaZZ+wTx096/pz2Z/bHGQKyIiIiIiG8bIrGNiIiI+Bbjpwkk8oT380jwqdo7DMMUtOQJ1Sk5Dv/ua1K32+2kAq/XazabzUSA/ddms+HVq1efWxucJMlbwUy+V68ncqdBTaH11xPAsDWUn8eQFHvS6//HP/+0btcnNXslNiS6oa09VHp94nTY5siT+LAfrz+u0H7srdCeBJ9akn3AV9gDuOs69vs9m83myLbux++PIex3HPYC9nXOfs7DNOrTfscRERERERFfFyKxjYiIiPgVhVf2flJ8GVLsCa8nWv7Lk+H7yPJpbbAnwSEp3u/3bLdbbm5ujtoU3XeMi8ViIsOekJ0SYF9TGxLeMCzLE8FhGI5UVCklXde9lSYdKsPhWIAjAhzW/IYKb9guyRPpsBVRqAKH9b+eEJ+qs75ONySh/jjbtp3aIQ3DwH6/Z71e03Xd0djCYC6/Tz+nnvyGNcghET5dePhprruIiIiIiIj7EIltRERERMRPhJ80aAuOw7bus0qH6u8wDJMK6R/z4UyeKG82m6ktkk+MDonwbrdjt9txdXXFZrN5Z42wPx6vWIaKcNgiKKzPBUf8fB0wcNTSyc+VP2ZPjj28IhyS4/B/vSLsCe+ptTpMoA5rgsMa4FAFPlWCZ7MZWZYxn88ncnx2dvaWIhsuQPhz0rYt+/1+ah0VKtzhteEXFPy+PRkOk6JDdThUj6MiHBERERHxZRCJbURERETELxw/TdiWx33E+LR+2BMx/90rk9vtluvr64kI+/pgb4n2gVn7/X5ShcO2RffBq6QhMQuJ4WlAVZhiHQZnAVM9sZRyslKfqsCe5J6S3VPbdFgre586DJ9Zp/34PAn1NbqhCuuVWk+Ey7JksVhMx+rJdFjP3fc9bdtS1zW73e6dyeBhuFdIbD0pD2uSwzZVPijrPit6RERERMSvBiKxjYiIiIj4VuKntVIDb6nEnhR7MuyJsFcmr66uuLq64ubmZiLE76oX/jJkOKwT9gTO24w90Tyt1/WqL3BEaMM2Rv6YPMH1db2eIIeK9WmvX//dt2AKCeJpr2FfnxumQ4ckNCSj/nevhIe1un4bYVK3t0gfDoe3bOFhu6TTWuWQEJ+S4fDnMFjr1JYeEREREfHtQyS2ERERERG/svhp7NQePpAprCdu25amadjtdrx+/Zqbmxtubm64vr6eSHFolfbq8NXVFV3XfeGYT0OzTmtuPeELLcE+NCsMz/JE1xPlEOHCgSfCod04JND39SgOxxuSYOBIWS2KYqod9mTXq8BhWJYnrF5NLsvyrXNgjKFtW6qqmuzgp+MP65c9IQ5JbmjR9iTYk3WvEGdZdrToEMlwRERExNePSGwjIiIiIiJ+CniyFrbp+bIIbdTesltVFVdXV7x+/Zrr6+uJDK/X66l+2Fuld7vdRIy/iBD7gCyvVnqVNGxfFBI1f1xhG6HQMuxVVE9uw3pjb0UOa269Ih7CbyNMiw7/57Rlkt92WHsb9usty5L5fM5yuZzU2dNk6dB+7ceotZ7IcGiRPp2/cJ5OFWpPfEOCHgZr+Xn3xxMJcURERMTPFpHYRkREREREfE0IQ558svFqteLJkyf89m//9hf+v68r9krl9fU1r1+/5s2bN5NCfHt7OwVreVK82+0motw0zRfux5O0MNnYk840TSdS6vvfnrZI8mMM635PLdC+VzB8Fpjlj9FaOxF3T3z9/PnHQsv0fcpsWPMcqrRelQ1ty6vV6sgu7RcBQkJqrZ3U4dOa4XBswBGZ9cpw+N3bpMPHQrJ8apeO9cMRERERbyMS24iIiIiIiG8pQpKT5zmr1Ypf+7Vf+9L/7/ve3t7e8ubNm0kh9iqxD9g6bbvkleJTVfM+eGJ4GqQVBlb5vsEhcbwv9Cqsq/V/P7VFn9YSh5bkUxX5PvLpnxeOzxPhPM+nhGn/e0hM/VdYz+uVZr+9YRhIkoT9fn90fKHqfZp67ccREt9TtThJkiPbtB9brCGOiIj4VUEkthEREREREb+i8DWuT58+5enTp1/5/w+Hw1Q/7GuHQ4XYq8T+uyfGNzc3n9tyycMTyrB+OFQtw4Rpr/KGRPddSdH+//wYQsXVP+4t2Kek2CMkocCkWId/C0lxeCynNuXw58Vi8VabKa84e3t4WPvsfz4d26mNO9x3aN8OU6f999NU7zDNOyIiIuKbikhsIyIiIiIiIn4izOdz5vM5H3/88Vf+X68U397eTpZp/7Ver6e6Yk+QfUumzWbzpezT8Fn/3FB59SQ4JKGhMupbDp2GYXnS6+HJct/3Uw1xqLqG9cPA0bY88fTKcRheFqZOh2Q+tIKHCm0YphUqtv7YT5Xy8Gc4VqpP5yN8fpg27ffpQ7RCohw+x6d8h+Q4IiIi4ueFSGwjIiIiIiIifuHIsownT57w5MmTr/y/xhg2m80RGQ4JcKgOh22Zdrsd2+2Wqqq+1H5CtdMTztPvoWIb2pt9mJhXgsPwrVMVOKwbDmt1Q4u1f77f/mmLpjRNp8dPQ8D8+MN6YU9KQ/U47MMcpkT7xYGQoPrHTvfn5yHs23waVhaS7lDBPrV6e8X6tAd0RERExH2IxDYiIiIiIiLiWwUpJRcXF1xcXPC9733vK/+/tZbD4XCkCG82m4kU+3ZMIWH27Zn2+z3r9foLexR7hKppWC/rCaCHJ4Ce4HoC55Xd01ZKp4qyryUOLclhP2JPrMP0ao+QLIdKrh9jSDDDXsv31f2GtcenoWOe2IbW7NO2S6fP82ne/jlhEJh/jlew/fdT6/epUn1fHXdERMS3H5HYRkRERERERPxKQQjBYrFgsVjw4Ycf/kTbGIaB7Xb7Vh1x+BXWG4fE+HA4cH19/ZX2FxK905Rm4Igoe9J2Sl5PleH7+vyG6dP++6niDEy1yOG+wnCq0N7tyaVXcrMsO1KTQxJ6SlZP1eVQRT4lr57AhqFZ/m9eDT5t13QaBhbuz//vaa2xP5aQIEeSHBHx9SMS228wOj2w71t6o0mlYpHmZOrnd8p+mv39osf6dew/3IfFInAfYl/H8f60+LrP15fFN3Wc39Rx/Tzw8zrWr7rdz3v+z2KMp6/v3miq3t3gn+czLvLZ0TZ/lvs8DC2d1uQqYZZkP/Uc++1WQ0erBzKlmCf5z/w67fTAbXtg09bAZ/ME3Pv46b79ONddxaat0daihOAsLznPZl96vO863kwq7tqKl9UWbTUX+ZwP5+cssuJncuz7oaUvEi4+eMJH3/nkC8fa6YG7tmLdOhv0WV6yECltVbPdbtlut5OF+vr2hqu7W27v7thtNtT7A+vbu+l5u92O3W7Hfr9nv99/qSAuj1Nr8FTjKwRCCmSqkEiMMAgrEAikkgj7mYocEmFPfMOewPBZjfFpT2BjDAYQQDImWANHpDhMpbZSIMbAL5UkCCFRSiClIkkUCEmapOQB0Q3t0tNxKoXBIFKFTBTzvGRVLpiVJUiBTRWDhSSRLIsZy9mcPHFKtEgUvbB0wo15Vc64KOYs5vMjhdkI2Jme6/ZAazWrcsbj+YrlbI5SCUWScTFfUKSOONe656o90JqBVCUs0tztc/z5Xa8Zf60LwML03vF51/wXvWeF70eHvmUwhlSqt16/P6v37n3X8Pyw5k29odPwsCh5Mj+/973ii7b9Vd5DT8eTScV+aNm09fRYKtXRvH7V96LPm5v79t8ZTW80nR44DB3aGgqV8rhcTu9Xp++3szQjk27bP81nsx/PpqtZtxVCwDItj/b9bYLYbrdfnNX/LcDv/u7v8gd/8Adf9zA+F1/lzaDTA7fNgURKlJA0umfTNSzS/Cvf+HyZG8LD0HLoWs7ykkKlaGsYjOGymH+pD+t3jTWR8nMJ4LtujL7Ki7PTA6+rLY3u3YeqNWhjyFTCYeiQQrBIi899kX7RjeBdc+DP16/R1r3RSyRFmvKwWCCFYDCGRZrTGf1T36R+2Q+fn3QB4rY9cF3vyVXCWVZO4/8y5/pngS87/tPr6qtck192v8BXnsv7xlUPPalSCMTRB9V9N9r+Gqn6jnro6I2mTDPO0pJMJfRG33vD8nnz9K4bHffhbKdx/TTXyizJqIeeRvc8KpefS1S+yrk11rLtmre2G26r0wPXzY5eG6QQzNOceZpxmc+5ayue7W5RSnKWzVhlBQLxpa6Tfdfwut6x7xtarXmQzxis4VW1oR56PpyfUyYZrRlYpgWPZ6tpbKfXwLZrqIaOXdeQSMmT+RmPy9U7j/91teXZ/m46P6usJJHyaPzAOwmbvxG67z39tjlgsdw2B5qhpzOa83zOPE15Mjv77BiC9975+H7dGz3d1ApAScU8zd4ixp0eeFVtWLc1g9FoY9BYLvIZqVTs+sa12jEWg+VhOeejxaU79mDOV2nObeOI3mFoKVTCfmiZqZxUST5ePuC9cnnvtXbXVlzXO7ZdQ6EUh6Fz89V3pNKRht5qZipDINDWssxyfv3sPWZpNn02ha8Rf5P76rDhpqlRAqQAbWEwmkWac5YVrLuGwRjATp/LHy4uWGTFdF01uqdQKZf5jNYMfLq7Zds1lCqjTBIMFikEmUxIxpvpami5a2r2feMIfj6j1T1vqgNZojjPSr6zfMBFMT8617um5sXNFT9685rddsOruytk0yOrjm5XcX13i6lbNuuNqzHe79lvdmx3Ww77PYfdnqquMV/SXu2RBHW2QgoSqd5SkkMlU2PBghCAGBOqASsEjATYGMOAAetJsIFxWBYL1s2btRZP563bEZlw+/QkubcGjEVKR86lSpBCkCiJlZIEiUrUuB2BSCRgEUKRZymzIkeplMEMIBVZ4o63Ez1GKhSKPM8o8ow8yzBSoaUlSROyspws2pflgkUxpxcGowTnszlJltGjWeZz8iJj03d0wnI5m6OSlLzIeH95wdPFOctyTms0V90eIwQNGoNlM7RkaYpFsCpmVLoFK1nkGWac6GVa8lsPn9Lonk5rzDh//r20N5p931IPLUoqbus9t02FxbJMSoo0YaYSEHDdVGz7hkxKeq1pjSYRksfl0h1jWnCZz+iMZt1W7Pqaq3rv5hQB1jJgmSc5g9GkSmE0aAzrviIVikRIzvKSi3zOo3KJAJ4f1hz6FikEsyQDAb3WCCBTKYe+QSBRUrj3aekWBjxhrXVPrwdAYK3hQblAIKiGljf1Dm00h65np1sKpTjPZrxXLumMGe+JNYMZuGsbtNXMk5wyTemMRliYJRlKKnozsExLCpVw21a8qraUScoyzUBIdl1NMww8nq1YpTk/2t3xZ5tX1LpDWkFjemZJxmW+IFcJEsGj2RJtDLftAQ08zGYkUnHTHMiU4mG5BCy9HjBYDv1Aqzvmac575ZJVXtIbzaatafVApwfKNGOZ5gghuKn3tLrjqjmghCRFcVnOmaUZv3n2+BtJbn/nd36H3//937/3b5HY/oIQfgDVQ89haKn7joez5b0r07fNAWMNiVT0RnM3fvD7G5+flHSG5MDvJ5GSXdfQGwOC6cZkMBop5PTcaXsnRNRiSYTEAuu25qbZkwpJkSQIFAjLWVZON2cPywWXudvmq2rDvuvIx5qe0xvIz9uvvwF+XW25afYUKsVYy11bcRgamn7gQbFACCiTDGMN3109PFr9Ckn9LHU37gL3gVkkCbu+pR06fri7ZZmVPCrm7PqGRmuezs+YpzkX+Yx66Nh0DWdZwU19oNE9vdGc56Uj1bP7b3C/yvnyK5zP9ncgIJMJZZK6VdWAVL2LsPnzve9bBO5mY7CGi3yGgLfO9ZfBT7JyG74OOjOAZbohDPHp/parakdvDEWScJ7P6PSAsZZH5fJLk1BPDPZ9y1lWUKiURvfcNIfxRrVglRVIId5JUMPj2/ft9NoE6I3mqt6RyYQHxZxtV/P8sKFUKfuh4TDeaJdJSp6kfLJ4QKN77toDVd9zlhUM1tCYnkRIJAohLLuuoUwzOm3IpbtRvMhLzvP5tDLvb8Bb3VMPHYM1tEPPg2JJmbjemYlIeFjO713A2HcNzw533DUViZS8Pz/nvXL51rUyWEeSLosZiZAYLMu0ONpWeO22I+mpho5H5ZIP58fn99n+juf7W26aA9uu5jyfc5nPWWY5F/mcRZpz2x7otKY1Pc/2d/SD4cl8Od7893TDgBEGbQTLNKNIEjpjmKUZl/mMXKVvXc9HZNkMXNc7Mply1+zZDe46eW+8kRqsQSD4cHExkiLDg2LBZTGf3p8t7nW27Wqe72+xRpDKlLt+RzMMfLy45K89+oiLk/fQV9WGl/sNiVRU2i2ELdOCs3yGNgO1HqiHjkylXOYlrR4mgrrICnoz8P7s7GgR0i+sXdU7pBCOoHYdWeJ6xFpAIZHSnc+Xhzsw8KBcMEty1l1FJhNa3XEYeiSQq4xMJSzTnAfl/GjB4FW14cfbW27aPQLhbsKEoB16FmlBIhOUFHS6p9ID1sDHy3NaPSCFHOe842W15lGxoEgyBm3Z9Q2d7ZnLlKfzc3prOM9LZklOZ9w81EPHYeio+o67bs+266bX2Hle0hlDZ3ravkfJhEfFHCS0ugcrOMtKvrd6jwflnE1XgxU8LOdoa3hZbWj6ntfVFotl09fctRWd1izSDCUE1TBwlhcUKiNXilykXJYzpFA8ma+4rvco9y5LPfTcdnsWac6u65inKZlyi6Ov6y3GwOPZgmVa8OPDLVYLEIb90GKsZa4ybrsKrCBPFEpK6r7nk+UD5mlGoVJq3bPr6unmf9/VzNKCMsl4WCyYJSkGSyoSZklKYzSD1qRKUqgMrKHHkMqEvu+5Xt/x/dfPuVnfIdse2fRQdahmYL/bsdtuuV2vOWy3tIeatq7Zb/dsDluqfUVbVbRNy9D3n/v+fC8EoBRKgFUKIRVSQCIEKIUUYlqQEFKNarB7rY68iZGbojEIx6MxZkyjRoA12Om7+x/3k1sWFEI49doahJBIBEY4oi2kuz+wwn1OqEQglEQI6Yi4cGQyVQopJPgkailIkwwh3DaMEFhhkDJByAQrBEkiEEJilSTLUhKVIKSiKDIu52fM8oyimNGJgYO0dNKS5SmJysjyDJEkkEjKLOf95SXzWYERlgFACd5bXnBWlOy1ZmtbjBB8fPaAh7MlN01NZXtqO9AJtzA/WEGSKFZ5QaM7rFA8LGbs+45X1ZZUJczTnHV7QArJR4tLzrM5B12zSApSkfLD/RXaGuZpymANvbac5QVV39PYHmFACekWea0ZF+8y916auM+abtA8XaxISXhZr6mHjotsRjHe12htQFhymdKYgdZ0zFRJM7QkSUIpEqqhRQmn2FvcItr7s3NSoXhTb91iWpLT6I67tgYsHy4ueH92hkDwolpz2+y5yGd0w8BedyRSUSYpbd8zWEOiJI+LFe/Pz3l52LAeX7ed7Tj0A7lUfDS/ZJal7IeWXVfz+rBj3dZYXGmDxiIVSCtJlV/wShDCopAss5xcJczTgkQKem3Z9TWFUryu9ygpsQZmSUoiBWWWcZbMKJIUheKq2TpVv6loTc9h6HlcLth0NbUeWOUFy7SgkCkXxYxH5ZL/z8X7X/11/HPG5xHbX07v3DcQ+751K+htRdV3bLsaIUAfoFQpnR6mG4ZOD1zVOwSCTCl6Y0aiI+iMnm6o933L5TtWsb3VqTcDUqjRWiHdKvbQs+lqEqnGi1/RGLeK02unMn0wPycRks7oo22fEtGbZk+nBx4WC6qRsBcqoR56/vzmDef5DCUkPzJ3PBpvru+aml471WrbNmRKkScJ6bjCuu8bur1bGffk4rY9sO86pIBdV/Oj7S2pkjwqF9y1NfMkI1cpu76h1T1X9Q5tBA9nS5qhoxo6MpnyR1c/RknJpqsR1vLB4oJcpUgheVPv3Epb4sb/strSG82bakOtB+jcyn2iFKVSbNqKfJz/euix1p2TWvdkSpFISaMHLA1Zm/B4tvpS10ki5bSgse9bWt1zGDou8xl/vrnCjqrxzrq/ATwoljyZLdHWTDdknvw0uudNvaMZOoy11LpjmRZOoRGSdVuRCEk1butLq5Ynyq+xZiQ/87cWJTyZ2Pct6TgviZCUKqXVmmeHNb+mHh4Rrh9sr5mrjExKbuo9f3b3mvdnS5RMMBbeiN1btsJwX4e+5dn+lkZrumHgPC/Z9zWDMWy6ht70XGYLVlnJuq1ZZDm7viHTCaus4FW15brZ8bBY8LBYsO8bvr95QzV0nGcl781WzJKMfd+SywSDI0NX9Z5UKG6bPTfNgf3QUiYZVdMhlWDd1izTAmMNWZK4Gw9jOHQ9SgrmKucwdO4DWhuEgBpLoRKafmAwGiUU182OzitlxtAZjRSCTduw6Z1q+H55wQeLczfm0SLq3zf2XcOfbV7T9ppESrZdw4+3f8lFMeeynJPJhKtmS9P37nxJicWtXt91FYukYN3VfDg/nwiVEpJUKV4cNuRSsUhyDl3LD/T1tKi07xr+bP2KTg9UfYeSktt2Tz005E0GK/e+IpAYNM/3az7d32GtZTc0zJOc1vQo3M3jLC1obU8hEqSA23pP1XessuJeJTORkkwqnu/vOPQdeeIUhERIcpnwvNrwuFhRqIR2VN1XacFgnD3Zva86pWDd1STCLQx22nDX1+RSUaoULTX/av2S19WGf/PhB3wwv8ACV/XOLY4IS54oai0oVOLU3r7ltt3zKF8yWE0uU76/ecN8VAQHo/nR7prEus+JVVbSGY21ht5YPlqcO9sogh9ub+j1QG9daNA8ycmU4rapSFB0dKQi5a6teVntyKRi062ZpymX+Zxt37AfGp5kKwbrXAS5Svh0f4cQ8P3NFevmgBAwTwta01OqlN24iPTx8gG3TUU1NDRDx11f84dXP2SR5kgJCQl5Ijl0Lf0wMM/c61MiuMzn9Bgq3VH1/ajCtu6mz7rPxeeHtXut64F56ubmqmlpdMeT2RnbTrPtapZ5yW5w76szlbLrava94nW94S82V+5zGIO9M/QGOt1T645H5YJOa14dtmzaikKlKCEw1rDrnKL90cJ9drxu9lgBT2fn/MX6msFq3iuXWGt4Va+ph57rakeZpvSmp5TuxrbWHY3WGAyvxBZlBZ3VrNvavZfplrprOctmZEnKm6amSFJ67dSjDxbnbizWqTXXzZ5Ba3ZDhzawHzo2bc08zVhlBeuuopAZT2ZnaAy3Xct5NqfRAw+LGbuu4tPDmr1uaVcZ89VjSpmQqoxlWfBevmDb18ySgqflilZrdkNDqpTbb9/S2452sMzGhT3ZGw67A6Zp2W43ZK1hqBqqzZY3a1d3rOtmUpM32w37/Z66qqgONV3T0NctdV3Bl3dbH0EkyrHbBKRMUEJgpcBaMaqagBUoaR1BFcKpyOPyBFKicO4zbSxWaLAarS16cAoyiEk1NlbTjK9EhNu1cLzb/TAqzQKDNQIhwQrnjhD43sMCIwVKusUMEFjhlGi3PZ8MbUFKksSRaAFIJcmyhEIV4/8IkAqpEnphSNKENFGQJFgF82JGmmUgBSaVIBPKsqDMM1SekyQSWeSkKkOkApWkkDoy30tBlkqSNOdmvuK8nGERLGclVkhqoRECXo5CyXlZUlcHGmMw1lDphkQmIBSD6RgMFFnmFgYQ7JqGIksYrGbXtXS6R0mFRTC3hptqj5GWlSqQEpSUdIPlzh7QRnKRz7jud3RolBDU/YDAUqYpt82ezmquK7c4d1XvyGVKpRu0sfzF+hpl4aqtSIXEWLhr63FhtUdbwyzNSaSi0wO2N6ybmr/cXqONRSkQ1t23CwS97vl/1s/4sLygGjqu2j1aa5SQ9GgOticB7CAQDCRKsm9aBgwX+QIrNHetJpEJ1+2OQubcNAcQhl7ryeK/ypwA05sBJRMSKXmQzyiShGYYqEanmLBO9f6zrsZYyypNaYaBQhqwPb02k6j2bUIktr8AeKJ61xyohgEloFSJW+0fGvZ9y0U+Y9+3LPhMrW2Gnk0HV/VmujnLVco8zR0ZPiGdd23Fp7sb1m3LfFyteVXtuCxmPJ6d0eqBl4cNF/lsXNEf2LbOlnLou/EGeWDdVTSDszFkMpmUqtv2wFW9x2IZSMiku7m6afes25r352eAu+l702yxAow1bPoDnTY8KkukSLhpdvSmoBkG1GhR2rQ1Z3mJtZZ1W3OeS7LckbLvb94waE2iEgYz0JmBVAm2rbOCDdaQCcV1s+em2ZMg2HUNUkie7e64KIrxDWnLj3d3vDdb0ZkebWCwsEgLPlycYS00uqNMEhrds+taEilojWaZ5AyjtU8pSSkSemt4NJLVzgyT9SST0pEAa+mNQSL58e4G4AstsL3RZCOpfVPv6PWANpZGH3h2uEVZZwvc9DXaGBrdMmhodM8qy5mnOY2uEAjKBK6aPbfNAaxl3dU8KhajnVRz3ewnO9CjckWp0neS09Pr2at5pXKq4LqruchnJFIeLbickgmnbN25Y84KHhYL1LjY8YPtNY/KJZlU/PnmjVNnjcViaU2PQfOv169Z5SVgyWTC94c3vD8/n8bW6n4iAP/q7iX10POwmNMKw8vDht4allnGRTbjTve8arZclgsyqbiqdyySPLix7MlFwk2956reUw8dq7QkQVD3PX9y85LH86W7sU5ylHQ325uuolQpL6stBkOeJCRC0GIZ2p47UzOUA0pIcp1CLmj6nkS6urLadAgJysBeNzwulmz7hsFaBtvxw12DRJIrxbqvWMiCw9CyHxp2XcsyK0m0wAjLj/c3PCwX02KYEpL90NJVA//vzUt2g1tZt4Nxlqs0Ydc13LR7ztKSq2bnbgZ0RyYVn+5veZAveVTMUcAPtle82N/x/vwMYy2Jkvzl+pp5mpOP/UJ7Y5BC8v/eveQsK3m+X7MdGlKcGpMJQT0MXPcHzjLLVb1j1zU8nZ9z21YMxrgFmP7AQTe8V5yNSl3FeV7w6+fOurvtGmdNtBawKCGPruVw0ci9T7mbgYNuERZ2Q8MyKRDa0umeRAoyqRiMQY9Jsun4v6lU7r1mcqq4xcRGd6S5W2jZ9R3aarfIt77ih9tbHs+W7LuOxrhFJomc3v9uu4pD17HKc9Z95RT9oeWuq1n0He/Nllgs+76hHwzPq1uezs/IkpR914wKkWCeZvTGcNXssNZwkc/pjVsgUBIylTHLUpoO3nRbZ00zmmw8liJJSYU7d1JAqwcKlXLbHLhp9ty2h2nsb+odiRJsu5ZcKlo9UA+awfYkUlKPC1i7vuOudouTGEOeply3B85mJQLLbujRwmIMDHbANhXLLGfdNtTD+HoQAkVCazveVFsaPYyqvWU/dFgsCks9DLw8rGmNpRo/19qhd2UjaUZnQJmBTV/zslojrKQaOrqhJ0sV3TDQWcN2dAfd1QcGXP/aTBvW/YFBD+79QSnOixkw8OxwRz46iC7yGS8Pm5G4OifGy+bAypbME8uBlk3XIi1Y4RZMtl2NtoZcJOzG9/fEwmEYGPSeNHW2V+gxxvD8sMFYy77vKNOEm+ZAP2g0BqMttehRBg7WsB8yrhu3cJsLyw8PNxhrWKqMSiWjyqnYdx031Z5ad3SDJk9SWiz90GIbS9X1zBLFMi15UW/IhKLSHduqIVcpsyTl0FoOfcPL/R2JSpHWsrpYYO2cx08eIiV8ML9g09cUMqEzmlQmVH2LsIJKt47ICcmL/Z2znyqBQpKLhKHrOGz3LLXg5u6Wvqrpq4Z2X7Hb7Rj2B9abHevNhqFp6auGrnLkuGlr+qbBNB1d32Oa7uiz7SvzZmd18r5qwOKkZoFVAuWkYIQEYWA0sGGtu56tlQgxqsgGjNbYaSSOKMvALo9w5NpYp1A6lVo4K72148YlQo7blWpUnHH/J8BKxhIxRiu4G58UCqkEVljH05EkSiESgbHO4ZX4+mofCqYkMhnLzRKJVIIyK0iTgiRTpEmKkS70zCQSlaSoPCHNMsp8hswTemGReUZZFM7irUAmkmW5IE0UvQCpFFmRIFVOkSlaa0HBLC+xCKRS3GYZA4ZlOqNInYVXSkEthBOSxqCzDk2pMoyFV9Wei6Kg6npa06GNprOW8VXEQhV8f3OFRVINDUoKrLHoseStMQOHoWWRllhr3L1K31ObnkwkZImiUDm16Wg7p4wYY9i3NYN2n4vGGookpdM9Gk0L5LiFlEEbDnRIBPXQkqYJSsOgW7Z9jWQ/3mMKWgYkgg5NVTeUqgALvXH9vpuuI0kUg+lRKLQ1VENHKhTaWqSFIXEim3MuLdgPNcss/6qviq8dkdj+nOFv7JWQ0wfXtms4z2eUaUYpE7Zdw8NiQWc0t+2Bu7Z2H1JmIB2DAADen52hEPzJ7QseFnNW2YwLPQDwutry4nDH8/2WPJFIDdK4N6nGDOz6ml3XsGkbbpo9T+ZnrLIScOSnUIrXbYUFumHgRVcjrOCvP/oIM9ac3TYHtLGkUnJbH8Yby5JSpqz7hk1bY7E829/SGz3VSimhmCUJd23Ne7OVq4M1BiWlsxUJgRJQDZ+FFZRJwjCujBtjqYaOoa9ZtzXzLKfTA9oYUiPJkoRD39NbZy0s0gStLSSWgYFt12Cs5brZ05iBwRpymYG01EOLwLJuU6q+40VVj3UImlp3nKuCeZKRKkk/9G51ekioRYeSirpvqdMcrLshpB1rfQA9hmVsugptjLOkDi3briGVCed5+ZbSmUr3hrNuK6rRRqgkdH3PXVOTKslhcKmY277m0HXMkpQVOS+rLY+KOc/2d2y7hkQK1FhfXA9u4UMKQTMMgOU8L7lpdqQypbeai2yGBXZ9w6ar32n39QTBwqSy94PhxWFNqTLsWHN2SiYOfTte1waFYNfVvKy2LJKUB7mzOba65/n+jrvOqcivqg0WizaWqm/Y655ZUvDj/R3nWcGub1FC8OHikutmP5L2gRf7NYeuZZ5laJw9dd3VWGtptfvATqSk7Xv+cnvFB/NzDn3LIslp9cAqLeisdnXbApqhYzCWVve0ZqAe67nbTUeRZryudjyeLTFWUKiUzjolo1QJuVBsh5Z66McVVUe6pJAcTEM6SCzupr6zmn5oKVVGM9q0vb3u0DdkKiEVCfuhQYncLfML2A3uRlSMdVOt1ZQiBemU1I+Xl4BbAFm3FQrFYF3d2rPmlkp3LNKShUqpdIcQgj/dvsJqQSIFje4RQJmk1Lqlp2TdN1gcwWm0e10lUjGgGUwPpGhr6Yzmpt5z21V8d3HJdbNj3VT0Vo/KtSOV2uqxnlDTW8Onh1uW6czVDOl2/PCVvKhuKZICsFRDz029n8ozlmk+6pUugGgwmk/3dyzSnHVbcZHPJufArmt4XW04ywrOizmbtubT5tbdJAyarJVkKkEJZ9dcZjmtcYuUszTjMF7b1/WBSnfUpmMwmru64sruaPRAIVNMYtxijpK8rNecpQWd1sySgmf7GxZJyaavqHXnSHZruW4O403JQN0NPBvWrLsD27Zj09eo0fqbSEmZZGzamotihskNN/WO26aiG5wFWApX1mAxbLuB81yw6+GqdQStGTpSpVj3LcukYNs1PK/WKCmYKWcfLGTGuqtQUpIIRW1aruo9m74il4pUddzVFSpRzFXGvqv5F/s7zvMFyzyn6lokkixRHExPRopUkrYfRut6S6s7+mEgT1JILGqAV/WWhLEfqr+2h55t59wqxljyJGWweqwdhMHU1CMB6K1mGNzj1h6munchc3b7xr0WhKsHRhtS497r2qGn1RrHNywCR/AHU9OagR6DtIYXO6fGCgtGQKV7Kt1hWk07uBrIdhjY9zVCKAar2XQ1jR4wRtMYy0Weu9fV0PN6fzOeK0GnB1IlSYDG9jTdQC4SGu0IkxXSLbj1HWkr2eoaV/ELCoHRjm9pY0D37Bloe80+bVAoOjOwoSKpdsyzjH3fcVVv2HYHBApjDZ3u6TszlhsphAKZpOzahjxNMEJSdx23zYFFVgLG3fDrns5qEquwQrDvGhrTI6x0n6VmYDDwoJxjsWSk3LUHdr0LLcqkIk0Sdm1DRUdiHKHKigVFWaDynEWWcf7xUzozUCYZAl8H3bPrO/ZdA9axysZ2pCgGjHNnAD2OPupBM9Q1w6GmOTT0VYWqemh72qqm3dc0+wND2zNUNe2+Yr/f01U1Q9ui6462axjaAdO1dH0Pnbsv+2rVyieQgJDuPkKAV2bBE2mw4/s/YnwnHkmu9WFcg3NhGSkQxtU3WwQaR5QtEjFarBESMYoR40anZ3nVWnq7txg/mKQgIVCQx3/zpFLJZByuxeBevwgx2rHVuGWDle6AXVCYU5gTmaCURCqJlsLdL45EWSiJUIokTUkSiZKKLC1I8oQkScnLHJW4vsxlntMllixNSdIMkUiSJCXNMqSSpGnORrSO+KaKNE9RKsEqSaUkBzUjTSQHBmcJls7OjLD0AvqhZWh7lxAuDB2GXkBjNUkPea9paNG4xWoJ6MEyoOkdP2fTd+TjEoYFOgwZTiQy41mozUBqnXLd9K7syOmzkoaefrxkDDjrue7QGCSuBGU7HFhSoq2lMS2JUmirx/cbi8ZwXVfMEknVt8xUSirVkXDwbUEktj9n+Bv7MknZDx2FUuRqXF2tdszTlLLPeFi49L3r2ll7F2mOtik/2F5TJAm9djVSAxqJ4K6ueTI747Y5OALYN2y7FsNAo92NpkBSCMmLw9olnSEolaIaBm6bik1XY4yh0QPnWUmqJOuuBgvzJEMIyXVbMc/cjZi2Bilg3dcMZmCmEtqhxyrLZT536uzo079MS4yEu2rLIs1ZJDn1qD4qIZx9OM1c7Yu1lCqhM5beDqzSknmac9dWVGM631WzY54WCCHYtBWDsSyz1NWhagMKrg5b2mHAAnnqrH1NP3BnKuZpyl1TM0sTV7uWlQgkUhgao3ldbxFWoixoq9n1FZ0ZmCUZj2dLrhtX7zcMGhLBRTrnUelqTfKu5sPFBfu+ZZak7NoWM96UVkPn7I4qc1btvuW22dMbR3o74yxrXulcpDm3zYG7piIdV0dboxmspUgUvbEchp5dVzFLs/EDDRgtxc/3twzGsu9rzvMZm6FHCsFVfWChnNXWWd8NxlqqYeCTxXJSou7aCjXeEN42B14c1m8FBXlV2eLqmXvrSHsuExZJjoGJqIcK9A+21xhr6c3AQbc8LpdgDJuuYpXNEAJ3w4flpt6RS7egsGtdWp8FlmmGxVAPGiWgUBmv6z1P5ucM1rDvajZdxbqtaU2P7ZzStkhzqrZFC7dK6ixNmkwktLrnrq64He04szRl3zdc13ustayyAm0MAsthaOmt5iwruan33JmW35gtWZuB29pdX7ftgXXXoMfXZWuMs+gKQWU0dlSY3I2js7Mtk4KDaVilc9LxZmbXueup1xpjDYO1YLS7ObNuTTmRktp0ZEJxMG4RadCaQmUMVlOIbLwuM+qh49P9mmEMjkiEpLLOOj8YQ903zqbZtWRK8uqwo5QJSBiwVH3PRV7yRDlHgxlfy3vTIHt4kC/Z9Q25UNR6YG7cDa6rMe4ppOLTw5qXh42XLNgO9aT8L9MciaTWHauk4M+2r7nInO1MG9DGsusqrLDkMuNBPkdjafSA6joSJakHzSoveH9+RjcucAxWI2ZnaGt4ddhixxorjabSPbaHRVYgBFR9zyrPkVium8otmszOGIzmVbUFBKlQrNsaY80YoqJ4VCyp+45nzRqEpekHUiFJM8V1U6EHTaIkvTaUywyARrdoC4nsXL354BYDt32DkhJhLXeNptEDu7Zi29XMVIoV1gUy2YEf7JxNVSERXc3ZuIjWmwGJHGuwBvK0cLZ1O5CJBb0xpAium4Nre6IUGKhMSyFSbpoty2TGxtbMVIZEMKB5XJ6hEsVdd3DziqTWPYfO2dYMlrXWlDJjsC03zY6DbhnG8WRC0VtNNbgFy9YYaizZWPuWJwnaugAhVwfac9e3FCqFMbdh0Ia672iNe2+TxtmaG+Pq9QzWXfsqYZkU9FZz0A1aa7R1pTxv9lv3mjIWhAsnkwDanSeNptd6XCKRaNx8D9bdZhogQ9DTc11vkVJRJIpn+xvaQfO6b1wtprbOomsaChKM0cixBj0bS4EyKblp9jS9C/bBGlIh6O1Ar91NfmMMCZBaidCCAcsic4srwlq2uqfD8QoN9Dh3h7CQoBDSjETa0LeaIlEchp5EKEzv3ocSkbBra3ptEWIAKyaLZcdoObaKTd9QpgnzLidXipfVlrrraYeeQ5ZhtRmtl1BrV6vdW2c7tSOZ1QYG416Pl3nJXxzecF3t0VbTM7DTkPWO4DuKONZFdg1n2YxUSPZdy0UxQxi38Ia1LlCnrchFQq5SDkMDdqCf7p0cNJ+psypRJMsFyXKBrwhWQIlyNZnWOo6pHLGzxqUzt4MjDgLJMI4yEynaaIwdaLuBZlST88pQVzvaqqGtapqq5nDYM1SNI8iHhrauGeqW/tDQtw193WH6jr4d0H3P0A/Yrvts5fwenCrO7yLW4ePu/gG/IuLkW/+YJ7eO8eIMteP/jAv3nRgLmsVn/+bcE27R247/YIXfnw8Pc7XSFjMSYrdf/zwhGR0K7hfh5OtRqR7Ts6UbmxBeJLFOecYp0Gb83bhQEZwj2+VYGOnKyhACoYSjiInASlcbLUZSrZRCpQkySRBJSp4mkApkliMSRZolqCQjTRQ2TZCJJElT0jRBZylZmoBKUFmCSBV5lpMogU5TVJKAFCghaUcCL0a3QqMEqRCOwCuJQVCJBqthS0c2KvGaAR2cQo8G408JKcZd8xZq3dBhSQaJwWBMRykzWmuRtqPXGUJo7toD31k+5HwUwL5NiMT254zwxv792Rl37d4FsXQVl3mJMYZMKn64u+Hj5QNyldAMrkYzFcrFvgvJrMxHa2zmbMxjINJgND9YX6GE5LrdorVlluautqdZc5GW7FpHDlOZYPOZq2dVikPfkIvUWcG6Fissj4sVvRnQ1tLqYSTEzmrb6YG7rmIYk+jKJKU3cDbW7xzGWqAiccRAIHhYLsAKWmsoZUKZJNzUB5CWB8UCPaqVu75hMJZybKDule5CuXqYQqVU46q+wNUbawNlmoKFZuhpBxeGsUwLUqkQSDZt7Qro85yHhWYwxhFFDIz1NUYPJElGO9qCO2O4LBbc1hXaaEo152EOb+odRZLyqFzxvbNHlEk61ku3HPKO3mq0tRxMi9HWKT+6RxuDVZofbK7IlMIK0HbgTbNl1qcInBrfGU2mEi6LOZ/ubxmMIVeuxrgc67u6rkEzUA09vdYsipyLfIG2mk93t+SJO5892rUPEII39YFMJSSJQmvnImi0Yde3nGfOyrPrnO0uES4VtRp6ijylVCk3zZ675sA8y5knzpbS6J7B6DE0q6YdNFIJZknKo9lqUn2Tsba7GQZa3VOqhBtr2LYNuUqwWFKZoO3A8/2aSrfs25ZMpa4Uybg5nKmM3dBgcPXMEsFtV/Nh6Yjbi4MLlKj0QCol8zSlsym7voXOrRRnY31JmWQ8P9y5wCgE+67DLXAbXh7ukCiezFbkMhlrtt1iST30zLMMadzNzjwrWCLGdFW4bfa8OBzIVcp7+YJ+6Pnx/oZZmvMgX1APA622XOYFSkhmScredk4RkoJH6TlnuQsAumkPnGcuDXXbtzRDS65SrNWkytWer8fa8lp3WGHHoCgQSA59y6Y3XGQGqSX/z+0zrHaKqoFJVem1s501w4BW0PYtlenY9JZMOltT3w8ooVikLnSr1j2bxi2s5CrDWkbVtidTCVmheH7YUPcDje64aQ6s25pUCDrtXmP7oUW3egw1cvtRRUKepFxkJVXXoYQEYafrTEmBkc5O7erRJMskp5AJd33Nb8wfcZ7POctLDn3Lj/a3SCM5L9w16+pbt+z6jrO8RBvN43LOtu94Xq0pZMonq0uu6wNWGM6zgmVWup6WSjG0lm1f8eH8gk5rrusDGsMqndOagSJJsdaRToGlGNOU923DIi04DJ17X263XGYFpXBr9L3WGGG5KEpylfL9zRWtdhax1uhxUSThYJwLA+usiH2nXa2YzHg6X3HQHW+aHWdJgcEyy3MeJcuxnsrd5EgkWhjWjXNvGOFasnRyAGmQNmWVF9x2bmHPCOtSU61mVzdcyx2ZSunGzwAF5EnORleAJVEJWMEgLJlIqG1HNwy0tkOh6IWmTDJ6bdDaOQzO8pJUKbQxVGbgvWKFtgONcYTEWsGgNQM9d/UeJQSJkM5Ch3sfg9otVOLCZjKRMEsLUukeW3cuHdpg6HrDZqhoMOQIctJJ6bDW0AwDzaiFKGAuFdIqaqsB7Qg6lpyUlp4DmtQYZAc3Zkc7BpNlJGhcum+CQAv3OZogmaXjghNuMacacxQWacG2ramMRbjGNCgrScfrt8eQCemIvnVlOLlI0LZHcUxYhvF7guVgegyWetSDtoM7NmkHSpnT2YHNuJDcYjDW3Rzq3tKPtK0fBsrElavs25bKtqhUYK1CSsGhd+E/1lhq3ZKO5TrZmLSthEIp104IAedZwXVb8fywodEdiRRobclQVGgOJzQtAeeKaNyCSpmkbNqaXCUYbRHCLcBZbWhFjxhV5sZ22HH+DJAycbAJ/u9H925opFDkQnEwA6k2pIliGJVNxu0YzFh/K0kRWJFgBCSF5KIoEZdO1ZxlOe2o6Pcj0fA34HLa1mc/C1z5igL6qaWSxRrN0HT0dU1/aBma1tUhH2p03dLXDUPdIKqOphpV6Lair1tM3dO0DUPbYbqOvhsYOvfz0Bns0IF+lyFbT3P1eZgca+96gnsj8jrwZ4zMi8Tj41YIpzcGj4lRkT7ek4WxNhlhEVY4e/W4PS922/H/hZDjlyfjjpg7FZpRURYjz3aqtN+VkJ/VTYuRKLvnyPFnBYlzTExF1covFEikHF0PI6GWytmzpZIupVu5VlUikQiVkCUSkSRIpUjzzJHt1AVKZWmOyBL6xJJkGSJJUZmExPWBlqkL78uylNnFGfmjS251Nb2qhikH3CJNP5qvBZiBXKSUaeoyMYb2G5mK/HmIxPbnDG8t7Y3hUblECkm1v+YymzFTqYvuLpdkMuG63vHJ8gHrrnZqklKkQnIYBh6WKwzwIJ/RaT2GCTi1c9M1FDLlPJ2xpRnTFDWDNlzrAzOVschyBmu4bfZ8d/WQQTubo0ok31285+LOrUYbzWAsm75ilc5Qwt2we6V1rnJq21LrgU3X8GS24tFsOaqkBmMMM+lqvJZpQSokb+o9Zap4UCzZdS2pkqRSctdW5EoxSzIOA/zG+QNH0Js9z/ZrjNFsdM+6r5mnOQzwutuRS8mDbElnBm7qilmSctMcuMhLUpU48mjh8WxJrTu+M7+kyFIOfcduqChFwqFrWaUFBkGaKIyFp/NzisTVG9RDz4OiZN3V/Gh3S6YSHmRzLooZHywuSaWkN85W7t+Td62Lov/Ns8djyFaLEglFKlmmOXddRTUSXnCWb2MM2/Ubp2qnn/WZm6U5u64mlwkH7RStXe/OszCSTHYgLOfJDGHhTbV1QT5pzizNyYbUWe7GMKHHswWvqjXGwiotuMxLdn3nxjXWDd80FU9nKxo9sMwKknGB4a6tyKWzFZ+P9dnV0DF2N6TTBilhJt3iC2wx1tIazVk24/nhjgf5gkRKrpodnRm4yApXD2YtSkqq3qURp0gaM1CZjveKJUIIGqMpEsa0U2fvSxJB1w80xvCgKOm0Zt00COFCls7zmVMYUBw6F2g2T3IWWU6RKNohYde2NLZnnrrHF0nKTV3RWc2nhzsK5dol3LY7jHGpuMng1LD1WF7wweJ8bMPiauYfFAtmacLzw5Y8cSE8vtVFIiWzVCCkJZWKx+UZl7lLzvYLWghJrgQflCuuZUWrk1HFdx/Wy2zmlF4z0BvjrhWVkaaJu0b868u4Fe1d3/DebMWmcQpjbzUPMhfituld6YCzK2oGO7h2ViQ0umGQkOJrUi3zJKMZNKVMxlpIF2KhjaFMMhgDbD6YX/BkdsYPt9fsuw5hLPPUvUabwdVcZjKhtc7iLaUgEQWlTJwKazSd1TwpV6y7msPQ8KB0NfkHIcicBsV1c+A8t+jEpSD/2tl7rNuKT3d3HIaGakw6H6ydrJTrvkHClPybyYT3yxWfHtZo09EOHZflgkEbtNXc1DsszsabS0XTag59Tz62ZcEqOn3nHAzG8mS24jC0tNq9/9amQ1pXElF1HWWWIYzhtql5Ms/4YL7i2f4Oow033Z5c5RjjQrWG0U6YjQEvdnALEKlw5QkSd3Ny0K5m3pMirS25UlR9w029J5fJGHLnAlMeZHNu6wPXzWFMxk0pZOZsaVKRqoSzvHTtLJKEh+WKm/rg6pG7ngO9q4O1gh5HvFvtgkiMcYt2wrrXi7ujdHeFLZrEamQPeZqBEOSZszo33YCSklxI6qFxN54GCpFQC0f6MqFo6V14lE2mdj0Jiso4q6nxqpywJFKwyguqYaCUKYM0JCh2tgluvi0V3UR09HiuM9yip0KRWsUsL2gb97yZzEhkQmc6FySEuzkcsDRao60nkS2lLNyc0KOsHImXplCCDBcQ1GpDNfRY45TgPHHvJV0/kAiXYF2Q4oLbcjrT0w+aPQMWQ2+9+d4ptadoRrXzFHr8wrRoo1zQEz40yf+9Z8CRwZaeQyeYZQXD0DNYTda7ZP5lXtAOA70ZaLXGNX5S5Ima5miwhrNsjjWWxnTc1gfqvptGl6UJ0rjPXx3QInedu+89jnDmGJTMUcJ9mqbKkWuFu36rvoFR1TslWAP3kzO/ECCAHIVGkymJEopcOwWy05rKdsxNPr6n5yAMhUids0VrpB64yObsuwYlnPupx5W1tLqjG+2hMxQ9mp7PuF3mRk1OihXu98b2I0kTLocBRZJlFKvFPUfh5ikFcnI6WnJca5zGdhQiJxOSjXEL2YyZBKlRNKajt5bEWPquc0S4aWirhq5qsXVLW9f0dU1TNbR1S7ev6NuGoe7om5ahbhi6jqHuMG2P7QaGoUf3A0PbofUAg2/d9C6KHD6u3/mX07N3D909xjiHx9/9jBHUSfuf/f+FBHi0eAuBsI68ftaf2ToSbDwBd5ZrK5hK7uxIhIUdibP/XTIRZrwyjVNyhSfrUnxGjj1pl26sQo7BZdKtGriaafe5oaTk0b/5G/x//8P/30Rq/ZGoaZYNLTBDUCQpEslNc+CDWc+mde7QbxMisf05w1tL/UtmnmY0xrBMs/HGd8aDYu4ITlcjheAin/Gvb1/RmtEeZV29zUJl1L2zQ30yBjVtu4aLvGTbuahyC4i+4flhRy4TlnnBRbag1R2JcITPkY6BTLrEuEWaoZlzfdiz6ztylVDKbKy3sOQqoR3f9sskJVcJq7F2bpGW001BJhPOCtdi4EE+56px6aSXZcnT+QWpVFyxY566G4NGd3Ras+tdu48ycRa9R+WSdVux6RtymbEYValEKD6cr5jJkptuTznOX6N7wPJeuaLHuMClUT2dJRlWuvCDDxZn5E3Cuq2p+45l6tr3ZCpFokiV+yActOZ1s8EMsMhySuX2n6mUfd/SDD1JmnHb7Nl0Dass59P97Rha4xLwysTZ97R19YGDNaRCuvj38fHZqE51duBf373ik9UD3tQ7zrKCR8UCbQx3bYW1jggt04JMpTS6m5Kba60pBK4n2VDSW0OtO4RwNsRK91wWJb12VTUzlWMFvKg2rv1E35IIyaN8wW174FW159FsTjHaju9GS28una3L1X65OlMfcCaBRVpynpdc1Xu6TnOezsZrRYF1tcyDsdy0FYlwtd9SMFm9XNqkYTtazxdjHeJ75YJBu0CzLEmRwrW86AfDRebaFJWqIFeKRAmM8X35DOfpHKstN23PLMn5jfMnNEPL84ML0UlVykJk3NYHftg3lCpHAI+KJduhBmFRVlIkxVi7p+nt4FaMhaUcFbpdX/MwX7iADSx3bU2ZJMyTFGEtN13t1GLTc5m73pOt7lh3FblM2XctW2pSmfLRYsmub/mLzRtylXCZz3hYLsfeyS4F2Fi4aXecpyWJUpxlBblKAVcfve1rusGpgO/lKwbtarbnaYYSkh8ebpipAmsNg3b15qUaUEpxMwaWlYmru1ZCMvS9qysS8P5shTGWW32g1AkX2Zyn85VbDNKaZZa7djjtgcsxKT1NXDuFTevCnTKp6Mb62lKlzLOcx+USIRhb1Yy9CItzyiTlRQXGanIF5/ncJYUPA2dZ4Wy/euCD2Tmt7nl9GIP2rAt+EoixPUs3hmK4632ebTpbfQABAABJREFU5TwqF9zUFd/fX7NQGakQ7IyrUW3NMAZ7QKYkm7YFLFq7NFSBwhhNmiacq0vSRPKi2tDqAWPhvXJFozvafcfBaBgkizzHWsu2a1EyQQI/3t2yG0Nz9NiqrOqH0ZUAuXDlHlMaM71b1LTuJklZ1zfxrtvT6oxMZi4dFWf1NMZwN1QY61rtPMiXLutmXBj1NjO3GGqYZ66n5SopsVhykdH7XrP1AaXAGkuK4KZ3KqmwkMuESjf0ZqwX12AQZKRTwnuKHW2xLp2/UAnWCmZ5SiZczfddU9EOA7NxIXCR5MxVAtbZi3MSUpVyns9cAFfvWnG5Mh1DnqT0gyt52fcuoCVLE7RwYXNmvEmUI4H1qpnGERuBoURSSBdEY42lswOyH8POcKm0+6GmRU83ij1OGTXW1XAOo13ZxdwZOiBBk9tktM/35GlKKlyXgqpzAS9SuVpCbZ3rRlin/szygmRUluq2AzSzkUxVup/qgO/DFylswzg2d089ymmYieAqoCCd2oW1ukViWY79Tw99Q27cwtxgNamQlKpEKKfAFkphlKvpHQaLkc7mbYUmSST10NOjobejjXo4Gp+f424cmQIS4RxIi6TgMNT0fcciK8hSl7S/6Q80DGT2beXwXfPhldyMFINbBNn3LSDJkKNybUaCbegYWJGSyZTa9CxFSYez3CslKbKctmtpR5putXVq+HRMetpv7+dZpKixj2uauB7fmVFoo1mbblxgeDc+U/bB0KKAmo7CZpTCLT62DJRkSOl6xW7b2i0uGPf5pYCszLFny2mBQ41zE1q1Pd6lzKYA1lJa5zzpzUBqlAtf1C1929I0LW3doJuWru3p64a+buj2DX1dobsOfehQ/eCe21S0VcvQ9Zi2o+9695y+Z+gG937QtdiudwT69MTb+2jvV4/a/tL/Mb4ojfQMwI6SfOC3Fl6fd4tTQn6mSUtc0jXWOassxiWzw0ioA1lahL+6IEG3D0NSHAdA+SpqhXv9t3gyKDgrZpPK/ePDNR8tL77CzHwzEIntzxneWoqAl4cN7TDwfrmcVnCwgn5s13FRzFxwx/6WMkmht3RWUyYpZepIX9s79enFfj3ZhT9eXmDYjDekY5893XGWzHkwm3GWlS6YoWvQY/3AIskoVEaZZNy1FdpaHs5cSxNwfSENgtv2wHnm+gKacXXPpTwmfDg/G1sW9DwsFywS1+Nz8Em/iWsnE9Zo3rUHDl2LlK7FyEXhegeGH8ouPCpDInk0W4wW1R4p4DybI6zivXLFg2LORT7jzdhD9Hm1JpOu5Uch3Yf+J4tLEpkwS52Fyq20uV5z789XLNOCTVdR6waLm+Nnh1vawcUs5EnCvt+xysem473mxWHDZVHy6f7OKajkvKn3JFKQi4RN5yxMCYJFlvOkPONlvcFYV8M3SzPOshwlJTdj25RcJbw5bF0PzPbAeT5zCqZRKCkoVEZmElZJzn7IeDlsSISkNR2HXlMPLcVYVzzoZOzB24G1rIqC3houywWFTMbaancu1Zh0eJaXrLKC19XGJU0b49KO+4qFKtj1DULAvq95tr9l3dcsZMbD2ZJiDG+5aQ/UQ8ecAjKXNu3foN/UO3pjeVKsWLcVr5odCYrvrR5y11XsESRjC6VeG551d2RKYuwjZ+czZlKqNq2rQXyaLpnnGUK6RM+zrKQeOteCp3Pq8iLN+WB5wUzlpFLysqvHxutn7IeGT/e34w27RKSuds3Vf6d8snzIw3LBvmtYdxXztEQIy2W+wFh3HWy7jqfzJYlUjtDVB27a/XjOUg66R2vjXnvaTFb+Ze5a+mg52lZV7pK4+4ZX1ZZqcAsoZeJCr3LlWhwdho5F4tT9i2wMXhkDOgbtahMvszlpqXhxWFO1LQftov1l715b+75ziYvGsB9TEa1wSe3zNKMRPeVolZRIVOoWfVbpjDRJEFgez1cskgIUbDqnCj+ercjH1mU/WF+RjDez+65h0Jo8Uey7hrbvKZIUbZxNcylyijSjG2+MsYbvLR6xyAq2fcPjckmne17Um6mhfD103I6tS85yyTIv+MvNNbftgQRXk6SkpNEd204wH9/nlBUUSYa1lkPn+gg2/cBMpTTGOIfE4EjGYWjJlaIZLNXQoo3hQT6j6gda40LLZsIlqe8GzaAHeqM5y1wrp0PXAZY8yVFSwLiAM1gXAnTT7CmSjMu85K5rxpAePfbptCiZMliLNnoKvtFYWu1ULoNLz0yQ9IOlxqmoujIUWUJvBuZpzrmcselqdm3LeTLjdbsnl4J5UjDYgSLJMH1Lr0GMCwJSCDadq/OXAuphYJamzHGLfNu+plApuXQhf/lYe1Z17fS+4tqRmKmWbq4yFplzJ7w3W9INrm7zPJvR9L1zVeSWqnW13hJBPS5aztKU/WDIrFMIU6XYdP0YZOYjaMAMjpAMaPpeoDLNShTsTEuZptzUe/c5ymfhPpLPVC4F5NJZyN17o1twGIBV7pwhre6pTm7nDVCNqpEavyxwMJ+poBJBj3GLZSplnjqy2BqX5K6kcL09TY/Rrobehb8IZN9xXsxoRqdMhyvHSIUkQ9DyE3fCwQLNOGaDC61JkLRjjZ4C1FjX2AuDJCFNnZsHa6hMS2vUZBHt7MDCFOQimRYPstFWX9MgtSBTKYgx+EdI9n2Nv6pDBTPENBZci0RpBIehpx1chsEsy7hrqsliafl8Esi4LXfek5HSu3RZt39Lj1NNnaVcj/8j3XWCW6TIVEKiFDPpKhkr0zEMrp69m6pvXSCQOdk3+AWVUZm2ls46tbm0Kda4RRKNnm7W75sbD0+QPQn1SvfAQGJd7abAlc8MGM7yEqx7rxuMZDFa+bvxWvbXc/g68dtPULRoinGe37ZyA8L1/9VSIEjHRRTFjJRuXpACK8YygJP/9+dbAmeqnBbV69GXMDCSu9GijRl7EmszKtHjdaANuu/pqxbTdZStoW87hkPN0PYc9ju2h4q2adBNg246usoR76HtME2PbjunRHcduhvouhajDWYw2KGF3tx/UiZrSGB2P1KrzdFTTzdx32v6y77OdUB091c3R9eNn9twe26Bz7BrKxKpKGTqgj6l4tuGSGx/QfBtc4wyXCQLbuoDZ1lGKiXrxtVAfnf1kB/urunHWo7LZE6uUqrB9ep7f37OtbWub6ZyfV8H46LMn87PeVPvEBZkVrJIy9G6mo8vfklvLEoKBjPweH6Otobraje2qknppeul6986XWuhbGp9YrDMk5QiSZglOUI4e/FHi4spWChTydTfVAl3k3TbVNy1FY/L5biqa1wbgr7h1WELWB6Wy6P5UmPfXoEL/pklqWsVoZxypoxrsbHKSmZpylW1HXv2uhv8ja55f3HuospHxfuudTWz2pippYvr75u6cBpreNPs2I3WVZ8mPU9ytNEc+o5HxZwX1ZYf7m7JleKymFENA5vu4GqEVcpFMcdi+OF+zdPynFVW8H55Rq8Nre7Z9w3GZmRCMU+EU5VxpGWWWG6amqtqz29evMd5VlLrng/n57yud+NCwsBlUfL9zZZeuxYralQ85knmEih1R60HnpQL5mnBg2LGtm9ZN04xvshnrLuDs4Uq17x8nuQ8Kpf0RlPr3rViMnDVbV1wEZZ1V9EPg2uRYQZnPc4spSqcLdkMnCvB2agEbbqaXGbcmWoMU+pIE8mH6QUCuO1c/WWSOwtZqzWtcYRca8sPd9cUKnWJ08Kp8I8Kp4Y1RjN0Ne+Vq2nx5HW15VXlFnmyJOU8KznLZ3y6u+UwdGzH0LReWM6S0rWMkgajoU/cgoTrkwe97tFGM0tdP2AlpLvhlQJhFR8uLuiN5jyfu+POCv7k9jmpUJQyZdu3XNc7HhVL9rp1C7PjNbJvO3IyRO6KgTozcF4U/HB7w213ILHOpplKRd13lEnKYAyzJOVhMedN467/B8Ucieun6vo1axDt2EZj4GW1JZWCMs2oTEfXG5cyTsfD2YJFVlD1ravDtJrLcsGhdwnOq6SgR2O1IVMpizSjGXqKUflFQimSSWnrtAtbe11tabRmNar1iZTkSUbSSRZpSaYUTd8554MSo51UopKMeeJqjJV0q9dnWcltveemceUZq8K9rw1jC5pCudusF/s1le4oZcptV6GMxBjLPCmo+h1bmaAFnOUlmUycjXtclHucL5hlTs3YUnPXa7SBNHGLgGYYyGVCbwe2Qw9WT+EniZJj4utALlMylbr3o/pAohyJNtYRcZckbslUxmXhFgmwri1TKhWXsxm3hx2ZUhTGBfO0ZiCxbsENbanp8ZEhOYoeA9qipWGwgiSRZEq5NjfWsh8aFmnuFqWGlhfNmnVTu16ywtW3D+P7v5Ku7rsZhlE7kKy7xtVKGmeHTITk/eycVCRsOJBJl/eQlYlzutjd2Equpx0GFxIknMvBAHXvWisdBneucunql7GMpQOCh+WM29rV5zd6oBla9xo1YIUlUYp+6F0bIAQSZxPVGGoMGYYzWWKVW0yQUnBRFGwa1wKut8ORJuhVKK+cLaVyrT+sC6FJhWKVF66+UQhQLjXZK2/+xtDfNCa4m+7PLL12JAISaR1ZLpMMYQXrrsIYTT72FBdSM/SaHT05+C6qNKZ39vTR3j1XJXni3Dsae+899VdBWIPq6lDFZFcUQGMtcyUR2tANHUI6h83gA4RwqnmKs4b31mAG5yJDutZJSrjwNOe+lGhjqE1LQjLOoZnORagmhVAINK5USGPIpQvX6wQ8294hhMTYAYmiRNNhJwuzJ0nu1eMrKyFTKcoKKtORkJHhsh/sOCMlCQ09Ckkm3fswEmYqmxxSpcqY5W7xuRs2LmUbiw7OjN/nZ7XQkgyF0+b9Y+7azHDlJolMSKxTkRs7OOv/PfMSwi/ygF+wcXZst6hvMEiaoSdNJa/rLXKqYXcLaynpJP4l43z7OUvGxwyMo/7sGgmvJcVnZDUci3dWKMRkCfeOiVN4PRJgrWtmOJcjg7PFD7j34FQIegnHOvI9eOC+udhQ975Tpjl1U7Mdj8aHi4Xk0b8veBItjUWN1742FmkdqbXGjCKVxfQ9NC1t09HWDUPdOlW66ejqir7q0K2rk9adS9NOe8FQt9RtTVPX6GHAdD39SKbNMGAHje4Ng+6g1y4N6l0ImbIRgQrsz8NnC0X+/CosvXHFNzWGJ2nGfBTVvk2IxPbnjOM+nq4OTmN5UMy5ayuavkNJyXdXD1lkBbuu5UExJ0t8Aq2hHwz1UPGgWDCMfVF9L8ZMJdw1tQupEpK7ztXNPSoXnOXl2F+xI08UT4oV8zxnkbp+p6+qLbUeWKYZZeoUXG2dnTAVrh1K1btEWiUUhZT01rUxOM/nXOTlW/1OM+X62z4o5mPYlURaw7qt+fH+lrM0p0gy7roKYaFIEgSSuu+oh45CpWhryGTC+bzEWPfxkkjFo7kL4EmE+1CVY6/YbdvQmoHzdE4iBXddjZCCUiYs0tIlcA4GIaRLre0qisQFe+y6jnJcOd93HQtVUMwTqq4f+2BWbERNmeScZa59SCETZOrI4W2759B3YASHrqEWHZ0ZeJgvWKUFO13z55srHhZzzrOSRAiuqx31GCLRDD2FdKnKnR74/7P357C2ZGl+H/pbU0x7ONMdMitr6JGPDaFlCpApQ4ZAkIYAESAIECBAhxANAgJk0CFoUI4AUgZ9yRJkE4QcCbJoEDIe8NQtgiKL3VVdWZl5pzPsIYY1PuNbcc7Jm5lVTUrdr/uhooxbee8++0TEjh2x/t9/iiWSc+Q+Lvx/Pnh+tLnmonpLf7C94g8e3jEYXTtXe2hELn4/S+p1SInWOELJ9Frxqr/gou2ZU+Km29Zz5Rn9xJvpyMMy8aLfodG0G8euylobbfj8dFdTL88cghcZppIu5UYpNk1LLpkpRIwK/Mb+JVYrLluRpwsAkQJ2pzU+SKfnoBtu2oFYE7m3TUsmczefperBNBgtMryEyOa3usUnhAnVhoLDaHjdXTDHwJfne3KVx4dU2LmO1jpMTfW8bAd+erjlPszSg6wMPz/fMQepDyoqU5QsRVptxcdZezlfD3sOfiZlAXirakFqc548XrnAjzZXPMSZu7BQcuamGxhzxCrDVTdAgdvlzGAt6FJDmWT4cvKeVOBVt2NOkTsvlV+qgFGW7++viCnybx7e8eDHWnsyU7L4K0FJsAiJk585hkXAXnEYHVlqIbui1GTdXP2/iu9vrllyoLOWrWk5eOGfftBumWN87NtOOUoaNzxW3TircdqSi3QFn8OC1oqfjw9YJCeg1bp6gQ2+RKzpUEWWzlZpzlHC7a7aARU9X51PJB6kXilFdk0rjG8F4RvXoRXSfUqSWhhtiDrhs3jJUs48LGcyhU+Gjt/eXfPz8730y2YBb621XPU9RYFTli/HE422TMmTcyEquO56jmEhFZHz+5If09d761hcZOMaNIVTCpSieNlv0EXx8/zApml5Px4IOWOt5XvDBT4leu3IwKGGgM3JM5ZEKcKsK23Y1H5PT8RZka4aRJpotRHPsrUoBb1uaLRm9FKNtLENY5a0YmENC8cwU0rmYZnYtV29ruV7aeqA5XV3wdA07ErHlOS4T9Gza1oarTmnmSl5tNb0rpF9VYqxeBqtK3C/4svzPWc/14R+GJN//F7J00uYuzFI0murLE2ruZ0mWtuwaSzOK7l/IMPOogx71zMGT6MacnmCDmsjaQGscyQyG9PiY+TlsJMKtKKYvoPzWEHVh3gWwENGFSvSeBTnODNFuV/pZ367j99NQoSEPdrqDp9jPWaFMSIjjyWxcS0+OrxR+BwwRgbdM6EusIW5L2gimUOY2BipL3NIurxP8RFg/PtuK9hTyOLWI0AVViZR0WBE7qwlyV8nQ2stXVEck1SXuLq3rZYAyCVK1y9Fhlets/iYCFkYtUOeK4BaIZWAjjUwSVjU+Pi52LqfHhgJAs5YKOha35PYmpZzivXd1ioa8UwnxKssTLgcX6caVIL0CLQ8W92LwgKpJcylcOE6zt7XbmdFp8UKlEqhYLluG6bgJXW6REDUKOu+r+fZfu1YpPaNIv+9SohBGNBIYpslnddowy5J/oTI3OMjoHzOqsLz0LCnz09Xy4AnslEdQ+tQRTPlwBwWNJYWV4ck4vsVXFQewR7Itd6phrn4Kr+HDsNS1STPwezHot91f8W7Xh49nl9vEn46Vxkef4eod4WgmAg4uQs+nrc/7iYgztBqS86ZcZ4xxuBS+MaA6vkxU38/SmE0bOjwJCYyUjwnaq/1u7SGgK3+8O/aFAKcL+xQu51n3oy3nEt+lB+Lf1Cuw11psEoxxomUS801EHl5Tpm8BMI8s5xH4jQTZk8YZ7afvvzG8cDTsMLU/XdYUkqMJbE1mlf9xWNg6J+n7VfA9k94e975OSYvbGxlI35td0PMSaTBNXXMal29mrJN0bNWD7ybjpXtE8nQZU1VPsaxLq4tO9fSWstNtyXUyP1GW0kQbTpZOAJaiRflN/Y3OGMIOUvoSZB6jt+5+hSfk3TstgPWWPEY5kTrxPf1Mahdt5CTsDGVoTgEATYqy6P67XTkwg04o3jwE7fLiZt2y+enOz7dXDLYhu9vLh/P3WAbvhof+PJ0YGMdGElVtcrw+emWnxxvubQ9203HGGVR3RXLm/nE680FFMXRe150A2OU/tmt7bBKM2fPlelZSmHKC/umo1EtU4zkpKSfc/VwpUjbWH64uaHXWqTCxpHCzEOYa+dpYZ4CRz/xotvzst/SacfDMgt7Yjo6J4uTkgoGxSnIv3VaEohLgU6Lh+8Pju/4Xrokl8JvX76mMVZ6XpcznXE4bWXxQMEqOJVEqwyNMhQ0t8uZl8OOkATspCzpl4nCJ/2OKSY+TGcUih/trx8Z8lNYKqCO6JPBKMhKMcZFpOJOEl0vWmGnWyteul+/eAFFUpNv5zMnL4ClM07OKSK7XyV9u0ZKxHvr+KPDbV1QZF51W+6WCVMkaGSwDaCYY+DNfOR7mwsuKlt/DAs2G2LtMzRGvmsX3UCjLe+mI3MKPASRVpYiTNBhGSkFhqbhqt2Riyy6rJKO39F7xhCwSupQChmD4eBH3k8jRsNgWm7nkd5ZCoqXw44+trwoiZ+f7snZMJeZ62YjXuJaPXTR9BgML7otrXX87Hgri4hasXGahU0PSWqNDnGmH8VfGEqsQS+a99MRZQqnuPDru5dYY2pFVsBoy8tauXSOwvRdNB1TjuKjtw4fI9aoR//vrml5Ox7pXMNVZbvfjEcu+15UGLqjNw1aKd5PZ7ZWArbmFLHacPQzMVdFRlw4LnMN0NL0ruXKbfDZk3WhUY7b+cycpc4oZM+bUaTL1mgJPCqFKczVlymBaJ2R8KhUCifv8UaTE3x/d8G9n5F5s7BkRRc+aS8wSqrMDn7mIYyUonjVbul7YV161XLyU2XrNZta8eSjqBLuljNLEJZg34h1wKfIQ5j5dHPBkiJTigzWVVbGcEjCllpleL255P18gKJ4O5656Tqumx1L9tz5M3fzmTEGYhIfojYSHtQZS9aZJsv9tzMOT8Ipue/uOvEpZxBvvV9l7VXYmTOzCpy9VJClkh67TZeS6rCyMMdAqy1XXUsuiZMPYu3KmY1z/IfX17ydjnw5HdjWTt93k/TCblzL2/FAoXDd7eidY4kRYyTbQFcAm1Kq/npYUuHKOeZSOEbPznaMaebNeWTnxPbx+XhPKJmdaRmTMMDbtq2gWoDS4jNWCUP4lLuiyCnRuYZWG6IqjyFrutOkpXCoSbnftuVnfxZAG1hyYYqRSOQcVoWfqmzTk79VwIuhtQ0pyfC1N534b1fg56Sm7hwD+66jFLGUhBxZcsQDLcLSyRWXq6w0Y1JEVcB1SvMjiJB6GsvxFyyjVwb5YzmsAFKpXXm+KG8QQD+RUAR63ROTonEKXaDVEnBkUsCSH+XxUw60RSStMUNjGjZtKxLqLJ7TtRdbFv4SqNjW781Qz9WaxryytxIcJZ/auhgXN6EE5eQi9V2BXH+uPPq6W205Z3FFGzSaJDLdEmrMlXyCATjmCZelfkpV2NwWSdcOJWKxnKKInBtlKSXx09MHOmUZGjnO6SPZ8Xo9rSBu/bwwsMkdpzx/6yd3IrBNjsa0eB0pubBvWqzXEhiUC1MdQzyNWp5+X1sDqgwSPNYXITYual+4X4Td9gRh25WtJGD+Gqv3fAtFyBVXvyGezFrco75lP9ZtJRBXdrDhaZjy8fac5W2xODRLCfV3redQAt7Ct/z8d20OsdxkFDlnitKP19bHUuDVc736jNctAkfCI9spMuynn3x+//hFsuGV/Ra6F+78WH2xpiY2q0fmWwTwoLF0tqHJLT7LgEaGD98MiPtFkvV131N9ZxmWUT3iii47dmaQasxfSZF/tX28reDyfpmErc0LKRfejyeRiKG47p56oj7dXPKTw/vqS4I34wOHZebT7QVOG+lmjZ4piUdzSVFkwVrxepA+1CkG3k5HWmM5x8Cv7W9QSnG3jPzR8ZZSCr1rkKRQSfd98BMhJe7mI+fqFVuT0Kw27Jvuses0pEQs+VtBLQjbMKfEYC2HsMhUEhicQ2vN1raMcWFaAg9+pFGWc5AFZ28bLptegiCMJPHOyQsQt5bGWNbS+/fxTKukTqYoeL+cpFRaGRKRUINcjJYJecwiDXrdbaVTd/VglELImdf9jqt2wxgDY5g5BumEXFKgsRLwVbL4zT7dXOCzPJxVVlKtY6SCQit48J7rLuFTodGFi1ZA2E8OHx791UaJvyiQ+PJ04PVmQyxSi6C1JubExsnAY06Rr8aHCiwdr/sdCakWAVlk3frpUVLYrRJBK52j26blFGRB2FnHvukF2OTEwzKCEnXAJ4MMK87TQXpa/cjGyiI/KOlgjSkzK0/Uho1t2DQd3xsu2Lq2StnhzXTgbjqz5MTGZk4x8eDHCno990FA5ZXpOaaZc5S6qb3tSEggis+x9nYKa1LITGnh4D033YYxRqx2tXqn4efnkY1ruWoGPsxnvjgd+GTY8bAIRyPT90TIMuzZNB1zCswx0m0clkYCuXLgRb8j1X7ez08PXHU926Yl5MjtMlHIbO3mMcSrZMW75UisXpqHMDKniNOKKzewazrmWKt7UoAi5/shnLlsNtzPI0lltq4lLImda8k1MKfRDqvE77J1miXKEDcU8Za9aDf4Enm7HPikvyDkwKebPa0Rn/U5zpz9RCoiu4s5sWs6phB4CAt719AqYQGN0rTWMtiGjWv5MJ2FvayPSJ8jWim8DxyWmbeI57jpxZs6Z6l1iiWjckErzZ0fed3v+Q+uP+V2OTMtsDMtjXXiY9W2LlGli9AZy10484m+xOhCyppTmLnuZJgUsww4QIZ5ZAGwY/JoLdJRhSTiWiWe4H97fMPopWRj61piztxqxaUa0GiW4vl8/MCu6bhut9yHieMyMarEGAIlC0uUAO0L1roadlf4o+Mtr4ZLrtseV1Uze9eJx74V9uewLCJvVhIOsuTEz+ZbrpoeXeB9mGmUDIAWpDMclWUQpxSNsTikvkFnRd80wlCnwsNyxhqLRkLZQgnsmoYpJ8bgHyWsN92W1jTczpKp0KKYkgxNr/ut9IwiQ5SdAu8jFM0hLLUaqOCU5RhnBtvW1PTA58cPYnUpCWcyxgjLOocguQNtx8Z2omgJooTpaoXF95prbv2ZJUrtTNNJzUTIGaOkkm7JEa0N+9awca1UkWkZbgSyPAOUFikgBYfGWFFCNFozaFn2fX97xYfq4R+CeCaXb1n6rexlixUlQoaHcCYScVipXalgc2WzVlapoLFKiw/TCjCcY+BQBAgZJCyvM6KM6E3DrT9zXGam6Akp4oBOt8KgJ1iXqAakGi2Lf3BdjEuSrn4WZfXNrQccDaGyo+v3WRQnilZrcra09d8K4lW22jJn8Tv7lB/D6mISL6krrp4D4UhlMZ8pJdPhRAqcI1PILHxTvt3V/RYgLYCjaxwhyPO5qXu61vSs/lsB5KZCq4wvklg9PjsHT/JKcNbyqR7IpXAOMzGndU8ffaiWp2HGmlYsDF/kIYzkClY9vg6vNKhc686K9CWHhVN+uqo+rmBaP82EpITvcI+D8+f//txPmymgan1YjNz6M6BossFoja6EQfzoWs6s3b2SJD8nqdw6LJKTnVUhllI7kwuegqm1XG1VCaznJj/bnxqFRa8tIRfW2KNCqOBWfev3CuRafQ6Yf5lfdGU9pSCpVIZz5fj/3UAtgMHhi4TqTURMgZT0t35GQD3S5z//9Q5kV4/l30czIeehsFctOsPRL6QUKsP+TWAs13PtAEfWSocog5n12l1l6Ot/x2c/uwLppb4ehG0H8dhPwBaFU1I5dBdOvIobfP6/pwj5/8X2K2D7J7w5bfhqPOCTzBq1khoEYxQPfuay7blbRglbci2v+h0+Rd5NB+6WiRAz192G61aqa6YYRAOfBLh9mM980knsu1GKkBOnMFMKXLiOhyJhNIXCEiW+PpXCsYKgU5U4jH7hZ6d7kkpcmI57P3H0wkacgyfOI1dtj64+w5vu26PmQZKg36ojS1005QKnNEMu3J1HGmOFiS7SweiMJMOppDj6mc9Pd/zGxUsaY9mChL4ow6YRdsJneehtbMNF06O05v10IGfFQ5WK5SIdur4m+l40nQRAFJkumip/tGjez2cG63g9XDDHWNNjLUfv2Tphj63RlbGSRWcu4tU9LjNvlgf2dUgRsnQzDrbhGBZ6uzDGietui1WSBrs1DQ9VAuhzpFMNU1748lxwWvO63z6CHKmLkpoOn4Tdl/RfS0xeouBBAk6KLPJiyRyj57PtJb22KBSv+h2fDJpUgRJKUlOdNgKGiiz4Ab4aH/jDh/fV/yWz/G3TMEapK1Ba1X5ai8+Jl7Zh23QoJWz8KSx8Nd6zFM+SE+9ORw7LjFY1YbQYLrvEtmn5ajpIEJLtyAl+frpj07S86jboUjjFwOt+RymF9/NIyImtcxz8gs8Jq8DnzL8avxSJkzJsnJMKqOXMv7w70WqD0YYpiuTRWYnL/6S/4CGMkIWNP+ZAzJkrJz2gucC26djZHsjcziOdsUxBOhcPYaQ1O0k4bTS9sdwtB5ZcuHQNL7tt9Rgb3o4nkespy4XpOacFY6TmaIoPWK34XneNNvBhOhGSDD+ayqwa24gcOM7cLiPnIAMyazRjFB7g6GdaZXk7y1Drqt0wpyqvbw1TjlKzU9n0Rhmumo6rbsMUPXd+5BikIqdQOCwTd16GO4dlxhnNkjIliUf9FBY64yglM4ZFeoYz3C8z26apAVqSRDsnz5fnA1AXK1rTKsOubQkh09mGwTa8n8+UkumNwxkFSrNrGvwcuJvGKjePEkCHQreKJSW2rkEVTQiBpDJD07JvOkJK/NuHdxz9glKinLmfJaX6uEhw0b5pGWzHl9M9L9oNSmt8DNyHGVOUAHStUelJMmhREqKnDRvjuGo7qN3ar7o9jbXsm54xBd5ND4wh8dmw54OfCDXkK8bIoiJGaXotEkmlFJ12+CjL6suhl6AvJA3Tx4zXEgY2p8ScvHznUyHXuqZPNxe0piUy02jLiUUSyq0lpCwpmzGTUqS1DZ1x9Nbiawq7LoWcCo21tLqAVrwdDyiEWTx68eNfNh1jCLzxR3rtMDWNmUwFf/L5NcpglQxIrU68rLYMEJa5FKm48VmgYiiZez+hlfQ7p1To6kDUVwl5VqV2mCvGOD8GEK4BKKrU4YdzXBjHKXhQcOF63lVHnfqOxfdTCm8k5lx9kFL9E5DfryvPoXhintbrIpXIkjOXtdP9GO5ICFBujainPoxnzs0iwAQJM2xNQ28dNhmmEKq8c+0fhqZK0AOFVhuGrGW4WYHo/AvWIcLCCivbYgkVpA3KUpD6PSxMPsh1UqX2IYdHT+e+3otQqh6rPM+UVqIoID6yew5pGAglMKanv39+fiXBV2TyqQJqrRR71zEpDxFyytXPK59VrN5jSU/ONVDt+cL9CThqYKMbBtsxWMtlv2X2HlTGeBko+yxMZW0MRrGmWj8Br1SvKfkdGumtlVeHnGmsY1ANS4rM67D72c8/B7fyOSocFk8UZZvSdMVw4us9seufCVhSJGZPYGX0lbBrWRMAVwcf67GvPxvqOyli5d+FpZyDVAFOaamMuYSDrey1qedgfR9X/25VKhg0Wmk2TgY1WoGORaqJUNj68x9v4h/+Onv9iza59iJzvV7kfHw3oP2u0LH1784EXIYByTWR8yWBaeHZ69bv3BrCtW7PId6qbBhwHP+dIXbtyFYtWimO2bPR4myXcMBvDkXknBXa+hkJkNXsTENjjKzXWMvpqHLtTBWiPzLqpqoVXL2TwTqWgoXC1kjSd0iRr8YD7+fTI2Hx52X7FbD9E94abXg/H9nUiy9Ug/mnm71IbStrl0rmdj5z3W34/vaKAuybDQ+tyIytVpSYq/xUHgAo2LuWKUeMMlINUydmjZVp5nUn7NWUvNSj1M6rK7upAK1w8hM/O91hDOxt/zgvKig+zCNawfv5xO185EVlNa/a4buP2Vi+v7nk89MdcwpMKdDVSPyrduAcvAQGac3WdlKRQabTDVNauFIDp7CwBW7n82Mi6TEs/HR+j9Oao18YbEMq0h3po0hND2GhKLhsBi6ajjkmlAVTU94kaEfCZ1oMF91Aayyvhz0KBVY8q40xXDdD7R4Vhuf1cEGoEqr7WRb6l13HB99yYTusFv/gyXtaRwX18hjvjOXDPNIoJ7UTRTxABUWjLUPTkKp3TympzyhFCXurFFMIjMUzuIbvbS754nSP05az97ydj3TGMuRa9F00SWU+LEdedXt0EsB23fVctRtO3tMZI2FmRSR2vWm4X0beTUfOYXkcXS850GkpltdoPtlc8uBFyvl62PHpcMlVO+CUkSTYsHA3n/npwx2HMIGCg59IOTMXScLuXANFcTudeTXsuOk2cry6sBRJv3a2YaMVzlnp9A0LWmVh/ZWic5ZGWUlndh1TDOxcy5QWSbwNswSO5YVLN+CLLOUe/Myl6oTh0PLw2HayAL2xW44VeEwh0BpLSJG34UFYg1L4MB05p4UBSef9N8e3fDZcELJcY1fthg/zmbfLmZt24LrdkMhcdRvmFHnwE04rSYcO0lNslWLbdqjq80wVoHfWPXX3FlEKlBpEFEuuIV/wYT7zot2iteIQFpySeoB7P2KUxufAnReGPBmRsk0p4LSjsQ0xZ1rVsChRYkw+oEzh56e1OqdO7rMmpMA5xMch05IiY4q0xjHFwNkHOmukkiAXLpqBgniFNs6xsSLdjjnRto7P3BU/z/fcL+JrDClyTp6YIn+4vGfXCEMXi1Qt3S+S6K011Z4hqc7X3YDTUrMRs7AUG9vx1h9YimhHW2cICUIuPCwTqpNzetlprNFcNANfTkc+HS5ojJWKKz8ypShBI0q+k0opSvXCaqVxSrOxwkA/zDMvug2h1qTl+YQqhiXN5EYCuNrekWImlsi26TglSfmWOjYBKVnJ3L43DtAMCjau5Rg9MTnGEDgsZ2HuNPSmxSpHVorb+UxsEoOVsBUXjaQ7J49PmU4bZp3RWtQlnREWNqdCTgmjrVSolBZv5Fp6lycum4acobeWn53u2LeSgeCKnPMOUxUNZ6lcy4nWiEQ/F0RF4jJLztwtZ6YUKAWR8eeC1ZZOW5ySAZwumjEt5FxolKiTPiwjgzbEotnZll0jtXTnMNPrBp8TqSRi9aYPjX2sWjtX9lop8V5GfjET4YGOTETTKFnqliIL7b3ppcKkJlzHIiyIsoqUoDUSDjVXtmPAobR+TDaPOULITDEQs9SjLSmQVGFnDKYY7uPp0WPYYrDKEEsUcFVgcB0+JijLLwS1T8cTJRhIQ6lAMZRCwtOqXkLCdCIneWaFCm1aJAfjHDznHOi1qc+ugg/yXOibFh01IccKOIuw6km8mM+B3bo9VcesbG/kxm4oRbynThsS0gFvjeXBn/EhPLK2K6MIT+zWE9tuGGzHruY9dNbiY6S1BoJm17Qoq/nqdM9SF/qm7uW6r2u1zgowRIuT2VQvaqhXkI2GM6lWmD55UnWFVN8EQ5pt2zN5ISAaY1FZ0eT0NbBXkAHBxrZiUSgJg6ZHZOBjDhQyHeuQWUp+PF9n6lYmz6GIypBKYilR7FDPXiOAXSrF0vp6RGS78OQf3SjLXBI5Jcbk5ftdgb/IdvMjMPtY+r4C2m9jsp9v65ACDJ70eE7Xz2RlSj9muleWft1Wye3z6yQgFUgiNRY588fM7CpLbnCkqjRwPLGgK1jOyBrf5fBLoa3jKW1czAlJuG4luSEpSfvD6tX9tvOzJpfDOtAupJKZU8HUsUsiYtC02nLMMh5bBz6rCmH1T3ti9aHLloAxRrSxXPcbAvDV+YG/cPn6lxzdn63tV8D2T3jzOfGi29ZgoIIzhsZYfnL4ILUkYWFTmTkQT+51txEZVWvkhpxEfnC3TCQKW9dy1Q5ctgNvxwP3fuKH2z1jDFLP43o2FYxddQM+iU8sF2EEt66XqpgUsdZwO5/xJbKjRaE5xgUfPT4mWue4bnsJasmZwXZYrb/7eFPkFBZJi+0GYsmURZFL4qrtQYlsd+MaUk68m4+86LciQS1FmJXNyjwvwjSniI/CRIeceTNKdc6cg3garWPfDlKbMHS8HraA5n4Zue62GGW5aqX78BwWdm3P2/GA04ZPN5ePzGjMiaZIevUpilcw1zRgp3UNtRJ/XWsNrXV8tnmFKoo/Ot8S4sLOdXxve8Hb8YSxFqMkNGyOUuVy1bS8X86UooXp05aiMzfdnlwyPgZSyVy5AVThbplpreUCYSYPfuJlv+NH+xveTUe+PB9QSvzTRlsOfsRow0Y7nJJrpzNOrqc6cDguI++XkZgjMUnYxb7pcVoz2JZ30+mxAzjmxFwWet3wbj4SU+a63fMbF9dsnTBiayXLMSyAVHQsScDzOXk5r8ZRitxcX3QbYo4sXgKM3k1Hdq7DKM0PN5dMKfPblxJ28GZ8YEmJ+/lMqxuUVmxtS6cbxrgw5oBTlo1tcMawdR0fFvEMj0lqZVpn6LF8OlxRyh1HL2Fqe+PYtBvmFNjYHZ9s9jTacYwjnVlrl3rQcDuPTNHTWse+DmPGnIkpMvvEzdDS2Y4xeLau48WwpTdy/j7MI5uupbVO5FMpcVOBbkgJXxKHZaZ37WPFzIXt2bU9G+u4X0be+zObpmEM0mH8ZjoQU6azlstmYIwLl21PZy0bK4Mhow3vpyMaeDXsSLnw1fwAQSSrL9qtLERy5GfTkUE7puRpbYP3kVIKo58lpA1ho8bgMUZTMihluGwl8ObtfOD1sKeUs0idXUtjDVNNFDZKhjTOWF70W45h5nY5cw6et+MDW9vzvaFh1oG7+Y4L1zHFmURi8lH8lClKzYeFOabq020YtGWsC+zWykK4NQ1b1/JgLRvTQZb72ZyCMC0xMS6B2Es9z/tpZA6Rc1h4Nx+YQyIXUUj0zsmSwcj302hTJdniPb/peooqTNFjdOHDcqJzDWHto9VSPyazIoUP0odpi2ZKXjqKq5In1YVNLgWrC2NMaB3Z2pYvxwc0hou2ZTAtcwnYVNi1Hfum4/10JqfAnBJLzuxdJGeRMO5cJwqgFDC25XrYotFcNgPv5wMlKRpjGFzD3XJijpGQC1vamuCbOC9eAqKUYdd2bG3L2/kosmGjMcqSSfgkoToXzYZYrTgxZxpt2JoOp1VlnD1zyhw9XHU9MQemGNi4lq3pePATjXIUW1hyZk4zGycd6xFp0GiswWbNoBpa3dDkhDNyrzbKMkXpHW6NIaTEgz/jlAQcNsVQagjO8+259FJAVCSWVZ6o0CiikmeCzjJ4SyWxbwYBESqjskIbzSl4nHZQxDYijGBCI9UrudpgQNLXzyFwjjPHKP7ZLbYOP4X1jkmTSGy0+HSdKpx/SXpOy7qwF2AkVTuKJXlmAg0SVAagVOGUfV38qrp4TzgldVM2wyn52oogPJ+yClXK1xJaDQYl6W6skGFNX/3Yy7gu4GWwlXgoIxorg7iUOLMQ/MhcGf1vk1yvPsgOjUG+l0YpzmlibwYum4HrbuB2mbCzCJaXes/IHwHalW39GFisQChWMe7KzCYKiYgq6lEKuu7VtycYZ2IOMrAuC00x5JxxGBLpEXis/ktVMkUpdFHMBBnK5MRGNXXAJ9aGtoLbth7TKqft1nNLEd+0caKge/x3zeqvBgHkkUKoAOv5/mvgWJbHAUI1cz3K8p+//mNw0fH1aqNvA6Lr1tRX2KqOsBhhVrXB5MBc4d36GcDX05nXUKb1vTvMY0XXuo+rv/v5sa2AfFUYKKWwRcD0c0a38AQQp+wff98vBbfK0lvDTrfEkigKYsnkkBiLjDXWc/RtmzCvT+d2IkNer0gJ4NPFshCrp1y25/u1fj5LPRL/7FpRAFrJ4LzAztlfaHH4s7r9Ctj+CW+hAtt7P2Hrg+y2BoV8tpFQoLt55KobsEo/6tlFgipy1LdRAMXetaAQmUBJfJhPAla2VyJJKsIQLkUm5Stgli7dgY1rWXJ8THhdkrCDpgbaLDHh88QhTJy9J5XMtZH6n8E15KQwWj0C8uuPPLbPE6AVcPAzd8uZm3bDISwikQ0LpujHKod1mo5SxJzoXVO9XoV305Gjnwk58XY+YJRCK9g0HTFKV+6XxwPHZuar6UgogV/fXtGv6ZJKpuHv5yOvap3QZTtwyWrFL4/Mc8iJo5+ZUuDT4YKbbkvOhZ8cP3C3nNnZTnyWrueyG8RfUkO+dk3Pld8w5/h43FpLuu3RLzwsIxftwEXtdb1oOi4axZfjA6kkOtVAyfSm4bPhkli7i//tw3t2TcfLTgDIkuT29AcP77hqB96NR1KduI1JJNdWOaYkwULbpuPT4UI6I+t1tW06fuvyNeHuS+79SMqSyLdzHUtKHPyBTKbRWvydxpBiZsoerRSf7S64ajfELJPcWDJfnO+YwsJ9mHFV9mKNI9U0YKuMTJOLyO3m5Hk7nrBaPHRGw0MQ5l0XTecESE3R4ypoUZVdEt/4zKFIN+pF24v/yFhChpAycxBm+9185oebK2IpNEqxb3rmGAj5wKfDJQY4pYAqiq1ruGoHxrBw7ws/Pr8h5cxYgcdUZae9sThj2TiR69tiCSSuuy1TDDzUQcRgG1IWD6xS8EfHO/ZNS05SVP++ymqXEiQgisQcZT6+dx0XXc++qeENxtFpy492N/xfd2+4C2cG2xJUJJRMyAFnDL1txSJQ5HMJKdZrRpMKkiasG47RY6wEt80lcD/Pcn3UIK+jn+TnMsw5cmU7tJY0V10tE51z4n8GVJWSttryg90VBz+LXLHAHGXxvG1aXlgRHx7jxBg9t/OZREEpzZQ9P354y2U78Bv7G76cHti6nkBg33Y8hAmnLEsJYnEospCjSFpuVplzlC7qrm2qZzxy1Q7cNT3nmrpu6j3Wl0wJC6cw8y8/fMnGiSXi02Ff70uBq6bnqC1zXCgFrBEpaQJ0Esbw1WbLKUZeY9k6w/208AfjO152G1EFUGSoSSREua59lqCpzli6YtnZnvecJdwpZ2IRcPiq3XPhJA36J4c7ckl8tr1Eofn8fCc+3KKqr1+LnN4v9K6lUZopBEn6LsLqr1E7Rz8RcuSzzZV4Z0uhswa0IhTobEtTWcglZ6jfEWM0XZbZv/jDUvVEG6wRvqu3DYOR/t3LpmeKEaXEa30MM3vX8oPdNV+cHjj4BasgZQkB62u38ahEzn1KC/u25WGZOfuZQmFnG845ctMO9MZxO8k11GCxRnEz7LEYvhjvWaLHKsOl67npNvzseEdMhaKkeimUhE1PjM26YDRo6Zt99mxb2SFFYcBWgGiJWoYfSmuyKqSYGeNCQaqgZu/xRfgwVQFErkzZ637Pvu05ekmq1srQ2kKhZY4BlVRlr8VCk3OpHllosig2cnmqF/qubT22VdIeYqr+VYsn0SvL5CcUmrmIkilXAJ+rVFiSfpXI9EukK5bWtrTFkqp6JLJm9cpvTUnO2iohFagisuPCE4Asz/YxUygJ2sbQKst9kYo3edSWr3k3V/C52gM6DK7Wj8VSGINnozte9lu0UhzCzGGZRYLrF2KR87kycauM97k3cd2e6m4KE6V6ReUTLSRa5aTGEAFLtgLgj32vACOFKUysJSpLingSnXKoYvD4KhWV8zSn1WG6Mo6ZQJZ0+SSZIxYFWaCgM1BSZuLJSym+6ogqlmP6ugh4qde6rWLllcFe92/1j8PXA6AcjvMzyPQ8ofg5oF8Bn2dloYVx1jk9StDXv5fvoHnsQ0dremVENZciD2GqEv0nIPr8DEcEQCueupnlOn6Cz7b+XfqWz4Znx9pUP72twuqPpdNNvU8sz9jqb3svW1nhjW7ZNR3388jJKhotSdVOaw5l/cy/CZCfbA6rrzzXz0expSVVWDuoFlebA56D8O86xudw9bkEm5yISaTnn25uuGy+W535Z3X7FbD9E95E7pm5aoVFuV8k+ey66x+T9WIW1mtjpW+wUCTJ1EsyrauLY1O7NHdNR0iRd/OJnW1xWrNrei6bnut2y9v5QGssVunHJM3sBCj2pqGUwrv5RCmFH+6uxJu5OE555t5PEgufAlkpkR+5hQx80u84+pmX3Vb2fRZAuPqDnydAr0B+a1sevIQD3fkzY/BiTteKuSZBfn6+46rdcNH0fG+4eGSy1kVXyolUIOfMGspujCHlwpvwwDE17F3Hi/4aXwFqUQWfAp1p+KTKjO+WUWSzWnyoc/So6QRITYxThsE4lhT48vzAGAKfDZfiq4yRVOB7WxlG+CSg7xwWOuu46nrezyNGKUn7NS0GzcbJn0uKfPAjg5HgplZXj02I3LQ9GTgnz0uz5YebG5w22CoVnlNiip45BRpjKMC76ci7+UijHEOjWHLinBfxDNVArRf9FpR4L2/LCIhs5nYZue42bFxLZxyHMDNHL4FjlWWOOXOMC42Wzrtd28uUHklxNiiWFAmV9VUoOmV4t0hSrtOKqbL3EoQDvWlorOXtdMYozd62nKP4xn9td8XZB5zRvGx2fDU+cL8sXLcdiuoxjhlV4OQXDsGjFHx/e0kBxhx52W+ZUgAtXYo71wizlg1oCRFrjeWTYSfHiXhYcym8n0Zu+h1TCuSSiTnhcybMZ667ngvXcggz5xD4jeFCvGBth4+yTLXKsHeGr7jnYfbsbMMpRt4tBw7zhNGW63bA64APGZ8mNk4SXpeUGYyu331EKogEu/1wd40C3s8DVhm62pN8oySxe4weXf3VIWb+8PgWhaI34rAJOaFL4cvzvYQ+pYjPgSa1eBW5m2emsNA7CSbxJdd+UJn+dtaRUXTKspTEi35LbyyttUxBrsclR6yy3C8TP9hdc9H0LDHyYTlL0btxdFo8TbHWl301HoVV0YZWi21iyoE4nfity5cyPLAtPz/fo0shlMISF3yMFK3QtSN7jiKp25qWUsR39G4+oxTMaaHTEs5zip6SM3OWYcDWWZxuOS+eJQbm1JKL5pNhx67VODNilea6t7w533MKMzEmjNFsdIvr5PoqCrZac+uP2GgYQ3gM/pKhiEicVdHS02pksXTZdDjtUFnzxXRPowxeB3amkxoX3WCw/HB/zZICN/1SmVCEHVKFkgqL8ozJEWcJigo5c20dS2VEUypYLYFcKSdykWt+3ww1IVw6YD0FUmbjGqI2PMSRlCOt0eQ6dGuN5hxlOa8KPCxjrT1Swjqvw9UkKbdX3ZYb4BQ9l83AOU41kE3YqsE6SrGMxTPnQFdD4hotQTetNigtKa1zCCilmOPCtunZOalzShQ2pqF1VjzHMXL0J/HXVksKFN6MRz4s0qV9igt711dAk5hJtJUdstX7KJnlmjPC8HfAXJd/TolcOpMYjASglQLHZcIp8YMabTjECQknKpXhSVX6KDLPMXpaI0qhlAutkQT0xmg+GS64DyMPswTVlfKUvLrBYmrYX6D8sbyKnUAeIpmpBlkpFB2O1jUi7cyJNsuz0ACNMfiUWSo8a5F9tUi9V68dES+hjEWeny2Oc1kepZ0Npg4FVF2Ol8cF9eq1XJk7DWij0EmGUsY4nHW87Lfcnk+SkbCuq+qfq+9Vo7FI/gRRYWvIpKJwjgs+ST2WrkMWqzUxhq8BNVuh8sf81PrvipXlkj93yLMylFQtBGCV4tPNFbfTqVYxPVXijM/eu9T3ePTKolnKk7i2Q9PiiCSstpATU4U7X2fhIg0OqzTaaAYlDFtMBVPHDM9DiPy3jEBkSCXS7qEygo4nZvM5ozpgiBUShvrnCoqe/57njPYK0vpnP7uGo6o6JBCgJtC4Nw1zCngiWzp2Xc/kPT56OR98PcDp4+1JNr4OpJ78x/KnwlTovQLjru7bU/iSoVWaucggqq2jioUnNrW1lq4Gh5Z6tRny4zWynpM1NT3khC9RAiJzIJaCyorgxUMsz1yHL+lxsLbuM/VYztXHHgFPrkMoGVrNJTIFT6nn9Pl+fNvWfvSa9dg9CRIUpWiN4dd2N7/knf7sbb8Ctn/C29a1jyzmZdNLYmjKJIyEAQHHZWEqCzs7kErkp8f3bGyDRnO7jDRGc91t2TUd57Dwbx7eMtY+x9KItOlROpUzFs3npzv2Tc9F2/N62HO3jOSSGWPgFBZe9MK6ZQq7piOVxDl6lhhByQR7bzqsrp6+XGSxrDUHPzHV0IOjn7lfJmIRT9f3Npeco5eKlNpz+MV4T87w5nyi1ZbbeKh9tYmdbcWfpA1j8nyYzwy2kfNlBx78hI+JrbW8n88sqSbyGQv1nO7ajm0jUmaNJhLpjOO62aC1ghqq5WodSW8dS5KpvUYY1jkm9l3LVbPnHBYMio1zdNah9J7TsjA4S8qZ3jpOfmbXiF/wHBaMtvzFq084hpmQpBYpk/ny9IAPsd7QOnrt2NiGz093XDdbDmXibhEJ4+v+QgJ92oG7ZRRWLmemNHIKM2NciEvhZV/obcOLdschzhhtGLRhnqVD96oduO42FOB2PtGbhtfDniUFfn66AxQ713C/TLybThI6ZKSncI6+LgQiU4g1+bqwaUTaHouj1zJN/TAduGk3vBxqQjMSEjT6BUqpSdaOXDIpJyg1IIQsjK4uXNiekAvvxhNXg+I3Ni/56vyAM4bOiL9oHcg4m3k/nzgET6MUWivezmcu2pbeSK2P04YrNxBy5qrZ4EvAx4BzLa+HvYSDFUdfg7KmGEAVxhB5Ox5IpTx6Kj/pLyiqcIwLVltu2g3v5zPv5zMbYzHKca51L8cgyoLGNFhleL+MnPxc+0EtFsUfne4YbMO+7ervpXY+SwduZwydbemNY44R0yneTydZACjF7TLSWsMhFKa0oIqiM2uycMNUJGn8RbsBpfij06103zWOOaXaSy2hbdYIwIglVWmtSHtDyhLAVDKLDrxq9oSUOGaRXq7fKacstrU8+JGhSl2VUjTKsm86PuQzr/qddGnPUw0Ue+DBT0DhYR7ZNC0lSUCP1ZIonlUmlMzGtly0PZnCm+kBq+EMNM5Kb19JnGql2MYJqF3iwqK1pOJqw8+PDxit+dFWBl4fzp6ixPvaa8dFN3C7jIRFlmiv+p18x3KuA6uWV02H3V5yDDNLiHw5yXt+Nlxz2bV8eT4QSyKFyA+3e7YmcreM3C4ju6ajM5Y5RfZth9bVT+8cvXE8hJlSCvf+RO96etuJ/zUp9o2jqf2V52WkqSFwafXZ2ZZSFsgt9/OZxjjp7sZwjBONEtZjyotIyqyj0T0hRwnqK4UxBgoLxhhU9JxjwBqpCrPaEIkobSiVGQ6lkIuSFNUU6WzLi7bhPsjzYe+kP7toURq96AaM0rxEyb0gGj7MI3fLyBi9PLXq6rdRmsNS/eFKWG5nBEA12bJvB4wBVRQ/2l0TSuRQvd1JZe6XM2cv32VhXAylJI6x1rAhks4lCcxcau6AQjGgkGZN8ZWG6mFbEPZyIT2yTS0wlYAtmlY7FJI0fr+cZFFYxJMaioT1JKr3uPoxDYVOOS5cR6MNX56POCsqrEyh0RI6djeP5ChcjK0szdoTGsmULHLRuQKFhm+G8ai6vxIRU8PJKgxpcDVpvnBOgY2VCjpRGQQZVhRhHz2rhLjgjGWgYQqBY/SkEhhUI20HTY9CcUHPfRwl1ExrrmzL3Xyq7bz5GUOqK2iQY8mI93cpBR0kLG1jpVZrqSFWG8TPuvps17Cwtg5FUJrGaV70O6YYuJ/P/OHy/nEg3BhHZy3GWkqO2GyYiaw9uOv7fszAPf/vlWX2RPa6g1TQxtAL+0AuhX3bE8bI2jI8fwtgXpOV5ypmXiuWQFg+T5CAruwxSs67L/Gxh3kNcsqV/1ZFWh966yQnAxlGCEP+1Km7Bm1920BkBfHhcV/yR7LsItcO8rvaZ8znxyzhc9DbIIPtkKu/NyXWlOkntl6uvJzmesVqUbeEhYcwIrnv3y3TXc/JCmjXLT3bf+nzFjn7yoAPiDXBZoW1DlttIU5bSgxMea2IUtUYgPS9xiLp7kqUELrIOnOpZ3plXtdkbvGz9mCknkqhmLJnxj+y46kUGRzVz2s93m/rKU6Igi3lzFieON7nCojnn8fHyo6Pge/T5yXfc+ozceN+1WP7q+2jTWTAG05BUlydtpQSGExHcYU340GS/UqRxFmlmaOwYDf9VkI2vMdvIkva8GE6yzS8Hdg3PW+me95MRy6agYu2Z4qei6Zj41puug0xP91OPxkuUErxbjrRaM2Dn1hSojFZ/KxFCauUJUzd1G/GOXouW8NxWdi2Df/y7ks+6S9YUsCnTGMMJis+zOfHuo7ByEx1ioHBdsxpEVaiyEM0lozRmlt/ZmNbQoo0xnE3nel3DQc/c91t+N7mUrp7c+HBjzUt1WJrl+3GCOu3dRK+I4BfwHtoEtfdBqsMqUQe/Mjb8UihsG96XvRbkQrmRGsNjXY4barnSWFqujEApXAOnmOYuWwHfn3/Ap/F+6yV4qrbSLJkEGn3MXsZYORELAmtJKxpzlGSiIcLYUJdR2ciTltJuqxeWKcNvXW8Od5K92ZNp5XuTglo+v7mGlKhtY6UE1ordq5j51qR5iaRj937kR/srjkGAazHsDClljF6zmEml8TtIqm2V076Vu9nSVw21iCVFZnGqJqEazl5zyksxJL4C5evOfr50b/4Zj7gjOFVuyMUkQvnXJA+4ZHBSvXRdbelNZaTF+Bz1fYMxjG4FqXh2kqllauvmbMwXaaGaXWN41W35Zw8h3Dmbhl50W950WzY1c7iJSRilhTjXApXbc9X4z1tEbm61Ybb+cSrfsuSxWO5sx2DbYRN9ZI0+8BIo43sc/0cpzjLsRU41+HA9zcXHJaFn50/cNlu6KyEcgl4U+xdy/d3V3xxumdwHSc1o7T0wMpQo6c3kqg9p8CDn/lsU9O6bcP9LLVh76YDMRU21mHQvFkONNaK70+JNF0BjZLrWeSRAoIlybfBl8RQGqzT3M1ntk3PQ57RxrDExM46Ju8BRSgLr4Yd9/7Mj/bXjCFiUbxst1y1GwqKq65/zApASViQUeKNOsaJwzzxECY666S2Bs0xjsQsC3ptEFlyDPSN4+wXjn7msCx0yvKQZ3rd8hCOTEHgx8tuw8Y2PCwzRlsZplnHEhOtdZK+rjK/vn2BQlXFiMIYw5IDvXE0StfvS8JoYcKNMWxsi9WWa9dy0+04homsalWKEtXGZdtJcJFt2TYt7+eA0xL6pBCJbVaZXTMIC1ESN3Yg5cLWdChVxEttpJcQpdi1HSklQsq8He+ZqqT8FIRJv+m2NMYwJ02HZuMcSwwUpXHWkZUoCIZGgJePkZIzY15o673l7BdCKVw0LYpcB5GKOXrGXNBGsdMdRonawSkNGvatMPWvhz1WWTrTkjkwOMO+2WCU4qLZ0BlJc19tGe0KzJFwk1Qyc5RFK0pXX1+icx25wGEZyVrCx4zSfLa95M34gFLwMI+MOeBTYtM0PMwTS0zoLECvVYZ915JBZOQ6M4fIRSfBhR3uEah5EnvVkpVi07YswVPizJpGLAzRmjNa63rIWCtshtGGFCJGWUyRUEdfxGIzqAaNreFAVCAtOQZow5gim6Zhbxu2Ve53025554/MtVKvU3VYwJPs0pO5cq3UUD1ba3wsYXSIHLNHVe1heVz0glhijnGhZEgpQ4JQJC26IBV6sEogFRkZaCQyngBFamR8iTTKoovCWYF9nzaXqCK9575kOtdiU5LnANJHmpHgo8TaOyvhcRaF1jIQ8lWRMWZfWe8noLUeywaLsxYfIkaDMZaHWQbBOWdmIj5VqWea6VOHVnKtK8ojA/h80d89c5GOlSvXCPMdKwOokRyHSMQlR1HSA3s/n2vzhcGk8I33XjcBO4k1PdnWz1YB5/r3AnOlP7fRjlZZbLWwxLoPjZJyF109+0qJgkKJ4RtTyqPSjcdr6Nu3VTo9YJnrf60/KQyiQVXgE5LHsyYlf7dfVgYQoh601tAkCRKlAmONYiI+SqcLcr/RiNfz5OfKh4oSK9Zz822/62NQu27rpynA3DwO4hsKjjW+TFNKwpiOK9syuJYpe96NJ6a4kOrnvqoM/BrSVN3Qc441cE2250y1rve+mMHoQskJaxxWK0jSyWswGK0YnwVRyXdPP9ZYfSwhvkvL4z6tcuXnqoDn28chXt+2rdfbvun5tf1LCZf9Ftvhn/XtT21vb29v+Tt/5+/wv/1v/xs3Nzf8/b//9/mrf/Wvfutr/8k/+Sf8d//df8c8z/yVv/JX+Mf/+B/Ttn/+pgbr1hj7eGFcpci/vn8j2n2tJZnUJK7bK74a73HaMFjHkhIf5qOEF2nNnBI/Pz/wUP24Sml2ruGr8UAs4j0IyAOmID6yAtwtZ/7odIeisHEtL/sdUHg7HXnwE+fg4Sy9eMaI3r9gWUrk4CXV1iqDVoZoMp/tLiQwyE8kVdjYhlOQCogpRUl4bHuabodSIlfduAalCi+GgWNYsMpwt5xlKqdlInsIEzfaUJTi7XgSwBMWrtqBv3D5Cf/nhy+57rcswdckacN1s+GwzOzq4mfbtLydTryZHmoqnMGnjiWda+9lIZNYUmIaZ45BanguG0mCPvgJQBjLnLBafIhGaRpj0KqlNY6mMlwhJwbXUmrVRKme25gLpcgC51W/5918plHSwVmypF9rxHP2etjzwm0EjITw5IV1LT5FSkmEJEy6MYbX3U5SQOeFD/5Ig+XN+YGiMiEhdRFKfHDnJH2P21o78+X5QYRGqnC/iNTwsMwV1Bv2tuPd/MBlO7BpHKrIA3JwDUvw5CwMhFOGWBJOKU5+5l/fvWFjO4ZG/NEvcsFHT6Kw73o+7S9pjSgUPj/dSzprHQqc/CzeyAK9bSubIz1tW9ty0fRcNwN/uJzRGnq7kTRSCoN1HMNCY+SxddNu2dkWay2xSN/qrumJtXLqi/OBxihiLtwuJ1rtGJzjZb+nMYbONiiluHA9x7gwnwNNfa8pepqmZ9+0klbuz4+BV7FErFacQyDkE422HMIs0nbXorXCJ1kwitRZFgNjXBic4xhmxuC5rWzSi97w2fYSgFf9Th70RjIPt02LNfD9csP7+fCoDOisq35FkZAPtmVnO5Yi/+60q2EpitZatq4RKXORRFnxV4oUa7COfSNBNkkXKNTvcpIKmxB52W+YszAK+7bjVb9/7LUOOfF+PHLvxa//5XggF9h3Axddz/tZ2K1bf8QoGZzEnPmQRn5z/4IL1wsLUCTt9/ubC95MRwbnuF1GCa3qnAysckJSpzveTSNWGZAZCrYeyxg8Q9dy026YoyzFfIzs2p6spdtwDX/yOdQu7Q3/4Yvv89PDB45hwhR55F80HW+nEz87feB1v2NrO+4WCbWbo7ChsWRaY2iNpXGGB79wiiKdH4wsD99OR66anqUEPhkuiTmzUaq+puFfn99w2Q4iJ09eBh0xULLUn1x3A4NrOcwjSwXil26o1W0S3kYokrjpHCEnUMLujDFgjAAznzNOKYpCWP8oA5WuOPb9wENYuLE9WcF1K+nlb8cH3o8jrbVcNvCj/ZWkGhvHvhGO8BhmvhzlXkIqKCf30q72sJ6Dp7MSqvSwCPjd2Y7OWgnuUuBTEnlsrXhTWnFeZs7BY5XI4Y9+obHSdlq0RRMYdIszspiMKdFqTTIyiBis+H998o/etKUEWt0waEcyiWuzFZ91zJxYsHUZ2KBxyuGLZw7S8TtHsbfsmo4pRakfC8LO+pLorAUlATiFhEWxbVrmGGm04roZGNqOl92Ow3Lmi/mBlKX/OhX5/HauI8TIIc+PAEJ9xCl+zJatwKulPLKZI7HKqg2NeQqDEs9mIutMTrHKUuU52aJroqqqYsxCIOCwNFqS26cYcVoSkWMQye/GSTL6TXfFrT8zes+kPA9+IVVwusoe12NqMHRGnrFouT8e04yuPLOAlqfU4Sc5qsJHz0wiRcOFcSxpYc5ePMX1fAhznkhZRKemqrsCX1/oC2DO7N3AHCKdiDPrOXCk+t+BjCWz9ouWoknBC0NeZf7umYT1420NXHpKAP46WFvDj5p6BtYgNqdslc0K3MtIknnIGafF0tLZRoCc0hzDSFsaVPFMfBPwrNsqGzas/bfQI9Lmp37gLJ5ypR/399vUAqvMfPWN6vq/FBIHJlEE0lB4SrZ+AsiqZq489S3L7yo1VTjxbaD2u7b1HMt3wtTRQa4SYcVCoCmO1hjJZkgR0/YoVUSeXgqF6mNG1WtKBjBL9KwWgVS58ZUZVcCuKiVA3ivlwJQyZJjiVBlkqROLRHL+egnZ6qlej6NBM38ES5+fi1/ktf9Fnlt4HsRVSGQe5pGp28qz48/Z9qcGbP+r/+q/omkafvzjH/N7v/d7/Bf/xX/B7/7u7/I7v/M7X3vd//q//q/843/8j/ln/+yf8cknn/DX//pf57/5b/4b/sE/+Ad/Wrv6J7o1xnLR9rwbJU3S5wgFpiTSYq1g4zrmJJU4TmuM1rys0mGfIz5FrvstU5TAjTEuNMagikgbfnb6wK/vb3g7HTl7cQXsGllQztGTCryZHkhJfId/cHhPoywv+x1JJU7pRIwRrTSdcbzot8xJmNfrbsM5LLydjlDg7fmIMcJubozF58i76cwYI/tG2MM5ymJ+Y3tSlim+qousTju5ERuHUoq+Pih/fP+WT4cLNrah0YYX/YbLtud+mSgl4ayj5CLJqmmi9xoK3M9n9m7gspGgpq/GA60xLClIL6lr8VkSAccYcMvMwzzhi+zv3nUo4P1ygExN/+zJiLyuN5bPT3e86LfEnPjq9CApqKbhph+4aiWoIhbLYRlZiOSc8LpAlM8/loxPAZ9jDceK7JsBo5RIdnli+v/o5Ii58KLbMqbArT+Tc6GUzId55HV7wWXTcb/MTGkkZcun/Y5d0/FhnjDasGs6fn68wxqJzFLKELOAy1jkJits5IasCoN2nHWoT/tCyYVQYg31gou2Y01DfJgn3s8nYo6k0pNV5qrtyK7lGGcaDO/mI1vb0hrxmX4+LsScIBfpAy5w6TpGLy62VCuSvhoPj36owXZctl2dfUqVzMFPmGLYt4PIYZtOWLnoUUVA3lQCg2qZc2CMgXOY+Gx7xSl4jNaUorhoGsYU2Lqen53ueD8emWNCG2qITsAph1EGpRSvh62oCIoIBA/LTKPFzzpnxfeGK64aqfm57nq+GqVm4n4amVPmECZ6J+dDa10lxsJonaNnlwJHP/N2OnDZbEgk+trFqZUE9JyMx2hLZxupIDGxevbl3Pgc8UUYkpfDlq7WOXV+QRmFz4neWsbgOfmFXdPJwEgrYqYuxIMEXKAxyjGnwOgjV41Mp3eu51W/I+Qs9WMIqP23D+/42XRHiNLTPMcg/dfR86Lf0WjHQ5wfHU5Lzly0PTdux8a2HMPMi37DD7bX3C0Tc/TchYm0SNCcMrLo37iGWCKtksTzu2XGp/DYjdpZw971NZSpLoiLIou2G1U7cXsjwG+9tjrdUIriHBf6mgx+ThLfUgCj5N7xZjpyZ0Z2rifkQKrKWm3Eh/7BZzaqEc+3FhmtrfLV3grTNafITTMwK+nUDLHQaEmU35qWU5yZ08JF09MYw+gjo1/YGEvIkobqjOGiGZhrxc6Cx1pJoL4yDW+mI1NYaGq2ABQG3eArV9ZbucfMydO7RkSzWnrPX7VbXvV7UklMOfB2PrJkSfW+anseguePjg/s24YLpXg/hUdVCEp8uCFnGr+gdcEHQ6sdl43kSOybjqwKk5dwNpGnRmH8TSNDyBhJWb5rPkWKUkSdOS8zqhRe9Hs60zArT5sbCRYrwnS2TvywG20Yo5fQwiDLcCsjDWEPU+TeS5/8YVnonSFqUHlNWBVPoC9y1pYkbE1MkSkEeueYqgd6rXyJJGIyhCKhZRb5vkqVjYCfc/KURWr2etMwRs8pFcYUGawjFPHaZ6Mxee1nFa/x8+X9x4tWkS+KeqIokYK7KqI12uBMg4+Szr2UjInCoPpH7kpu/+siuiFX1/HaIarobIPTFqz4DGOUgMEX/Y4X7Zbb5cT7ZcRoTWNbzkkStXMdoJXK9vU1JqmxYtPxKZFzxirxAGcKc12yryB4ZaYcYIwMDi0CpkcfmEt4lOw61qRfOWNziTTKSdNDKRWESc/ncw9lKlkYfdNxSsLuKpWJZQ0SW4GdpdESgLnaJHa1T94qjS4OT/hWYLGCvw22diQ/Je4K05uJeK5sL+njNW+lTY6peAHqJaGTqOxs0ZSkMErUL0tcpFoKVftu5fx9G9Auz/4UoAWWhNGObZZO5UZbyVQomVY72gzzN0YDX988wm52JT2+rwJGfP1WlUfGUaS7GWrSsIRaGRwOg6oBrP9unbFrxVCHYjDS0b6kp07dAswlEJLHIf/+/nxAa4vR6tG65isYfmKm5fpdKqw3GCyuahHS4zH12lHq/X/JSciK+u9rH7J/lB4/Bas9H+A8335ZVdJ3bc/fbx2aPE+S1vW9t6arCsmFKa5Rb3++tj8VYHs+n/mn//Sf8i/+xb9gu93yH//H/zH/2X/2n/E//U//0zcA6//4P/6P/I2/8TceAe9//V//1/ytv/W3/v8G2AoLV+hMw0UjD9v/8/bn4m3Shnt/5mGpMhqQIB5juVsmXvd7rtqBJUful5E5enz2Vd5cQxKyPAD+zf07Xg97jJaeXJcUVmt+droXUKHkC5coXLYboNA6y77ZMvvIO85cNAPf315itOF+OeOUqYEXDq0MY5yZkufC9lJVgfRDGq2gFI5hpGQB1VvXciwzezfwEGa2piMp8S6EHGmsFal2MgxOlhE+J95OUgf06eZCJqBGczdPpJQZ08zGOLS2nFPgy+nA0LRsbSfJtKbh3o+8n06Pqa3HIDZ9pWCJkS+DeOY2pqHVjjfTAaM1P9zc8G4+kjPc+zOfba/Yu46307GyPoWvzkdSkW5hrQoPfiLmzGAFpGsttSIX7SALZy1BLEZplM68ana14sijteZ1t0epJwdJYyw/3F3xfj6wRGHelhjEJ6YKg2kxBg5BOlqvmw3nEPjJ8Z7PdgWnjVTinKS/8ZXbc04Ll64VVs1L1dRgLWMM3M0jPga0VWyMgI9QCmMIj+Dlqm1RRXqVYylctAPv5iPn5AmlcFnZtnt/5sFLIJpVhlnLdXnRDhz9VAG2otWyAL2dzrxbTrzsdpQst/eHpcp/2w2/ffGCw7Lw3o8sObB1lrOX3ketYVd7Vbeu5c6Lv/XBz/TWkpWkTM8x4HPhFDyfDheEkjAo3i9nbrotD8vEi3bHm+meh3imeKk8aozjqmtw2nHwws6Vkrn3M6/6Ldfthq+mh+rLbOribsPb8VQ7g51I4BX8+u6KT4dLfnL4IInTOUklV45M+Co/HrlfRrau4+QXHqL8f40EvMxZenalRkoCilrbMJfA2UsH7CmK+sJpi8qaCU/KmRf9howMl8YoC4SrdsAay5QCvbWkBO/mE60xWC3+o6IyMSTu/ZkL33CKntF6fn68EzCiZGGTai/2xrUMpuPgH5hjpLeWY0pclUSrZQGq64LQ2MLgHINpiBR2xhGSKBuOYabRllftlp/cfyCWJEoPI6ndvW5Zqof1Zb/jdjqjyWgFS8yclOdHmyuW6Hnvz1z3AwbNQ5j4MI9cND0WTWMF2DdG1Bhv51tOceKi6fE50lnHHCJjDIQMThkOy0RbmZHLRtQoKRds1vS2oauhXrooARVaFpwpZ/au596PbHTHUqIE0sXEvh1QqnDTDGil+epwkH5jndm5np3LvJ/OfHE+sXENnZGF5hg9O9eCKlzpLRe2Z0yeOUtHeOscjZG+2IwMEjFgVe3UrgoiSuGm3bKkhNJyn7zz58cE8oum46EIu38fJmFbUXyYZIBx9jNjiMxp4bLbsmsaNraT1PklQPEMzRqSCIewSN2MM4SS+XC6w2jFzvVsnBMgEoLYKoyisRIsk7N0PrZac4oLrXbkXLBKEUIimERrG4yGmCM+RHIU1rrRiiUbcu3ybLBYNIcwViZUsQSY6uhFxPiy3BcGUxKRjVbYJJL2DsdgWsluqHLNRGIpskCnNI9hMO9HGQRapRmaHt1pfnp8JwFZWmqxQhYv/BgWvNLEGvLVUNCYGjDz3ZuAB2GOmyyWmIIkuDY5Y6JhLa2RoLvpUQraVe/rCn6EURQJ9spIaRTWyrqj5IyPcjxOG8aw8K/vv2BwkkLvtOHgJbhLa43LqwdZFvbOSbq5VRZVn5nnMBHqkrqtS/IV9K2L+qbuV6MazkhFEUWTWB6Dvtaf88+W5w0FSmGsYNPUd35eO7QANvra5bp6eWvH/bqWg0dwknJBK4hFRNJZQUmwPHq2v3vLSO9xTE9825r2vIKYOSV2rdTchZxIZcYkw5q7vMJmDZSSGSvQFTC2HhXVS/yLt4Z1KCKgRueC0gZbDKsk/5xm1oTrb2MJI9+Eugsi5ZU+V1O9xd+ETc9/TsBXoqVgjBMF478nzgrUaq2a/9EU2SdVj0qk4AsdhmOK9BR01vJ8dQ0hiKLPsPqaxav+VBimmOqnvR7DSMDnwCa3NM7R2objMpFI9RyVr12rz4cLq0+Wr/1d/trffdvW8E0FB8/ezyHDGFWZ+OeBXxZZNyjA58C+WUd6f762PxVg++Mf/xhjDL/927/9+He/+7u/yz//5//8G6/9V//qX/GX/tJf+trr3r59y4cPH7i5+fOXzvXxdgoLg23obcM5LJyTZ+Mk5VjXAvefn+5Q2nDVdKDAKJHVfjneM8aFel9miYFTkoVzU4OdiJIifIgzeSy87rdkY3nwExvjiDkxRs8Pttc0RiTBnw17vpyPhCRA01nNJjl+ff8CZ8WPpYFzWng/nXg17PnNixf8y9svWHISqSeFcxAJaUmFe0a+118iXl2R4V7oDXfzmdf9vk5rC+/mkc5aVAGlQGlFYxy5hjQZZTgHz+t+x+0iEt7BOt5OB3yKtKbluu/ZuZ4/PH6QEnZj6Y3M4q6bgVIyKSMVDynhlGZKucrYBNTu2q56VSXI5rLtiTXNGmTBfg6eJUpI1vv5xDFMItt1AqCXKL2Rnw4XtQIhkhvFnLx01KZAzIUfbgZKZX16bdhYhy+ZXOC664Gv9wGHlPjZ8Y5UIq2VGqc5Bu6Xid5YetsSdWKKAWc1pUjtTSwZZ8Rj2RjNu+nERduzJOnXPMWZvnRsGkfOSMhXgSsKuchD2mpLTJHBWjk/Bd5MJ3au4RAl/KY14k/2SRJneys+vgvX87BM7NueT5tLWmNFNusaXvQ7YkmMUSTvVivmkBjNwoP3td9TkmR//eIlW9dyju+grOy1p3dK+mur/FQSjuGm3bCzHanccdH0nKMnZFmIl5LEY25k/3wWmfEXp3tcDfbZtR1TCkxRyiV659jW1zqtxZeMSM976/ApcPAzJYFzGp9S7fFsuF0k1bSxhtfNBZdtW+u2Eu/nE1srITISJqV40W2ZYqzyZi19tTmTa6dyYx2qiABNU9BGrAJOi7QuRPnMB+PY2BZfIs5KZmjUiQ/LBEr6DDeu44vxgUaLv3JQjjl68cGpwk274bjKwl1LUplTDMwlknwRv78WRv+m2/EQR8jwUAds39tc8mrY8X46ElKkN4YpROYUUEhOQCzpsXs454kba3nRbyQ0LQbxeFZp2qZx3M8Ja/VjonfKmdZqzsHzo90Ng3XczTOnOLNvJS20rXLvje7YNS26CGuly8S+6UApWqvxsUgqPJpeW1LKTClwXCauug33y8wxLlI7sZxJCtpsWWLmQc01MRZa29R7jPgC0QVtda2+0iglUl2taxhUlmqrU5jIZD7p9nhVOISRUod/R++JZeam67lqBooaq5rFkqPca5ZkyFkqzHrjWBbP3jS05oIxherRF6XEfZj4QXfFb+5e8nt3X6C15oXrOAZRcoQUaGpXaSqZc/L4Re5v5IJz0hGrq3Rv3/WMIfB+ObMESTdfUqRPDScWXjQbYWmiBNylkkSNpNbOcg85s+TIgGPOUimza3pKLsw64IxDl8K2aRhjJPhJbB/BU3TGaiu9wUYk+6023M5jHc4tLElCwpw2dMYSo3yHQNgjj3g4E08S2XXR91RZktnqlot2IwNZNCFGYpIl+KAbmtYSSmLxAjdWf10goepxK2VZkqfJgV7veDcfeVgmtk2P1ZGS5fmgkeul0xqUpdOOc/TEDPkjD+TH2yorlSCiiEKxo8PjecgjCh6Dn0RoHDBID+xSF9CrBFiUVGvZEGQ8KXZQJfwJqd/auIbDLKD0HAMb20ldURJfqEPyMUoq9b0UOWY2Tc9cPGefOcbxa4zimhD7nKUyj59HYoknIjxCio+X4R/LZBeoYtJV6vkEAdbfI4J6TW8sPmcs0tG8ysBNHRsIqBQQqYrCommVFbVKzcP+47BrPnnWZtnVZyqMtMYhYX0+RGyzNgxD5knS/QSICmNehBigPAKZFdT8Iqkq9TWNauiMBBqGLNVqvTaUAkY7Wqd5v5woFRB+G+xZgaKt+7Hu4zoIWBnLP862JjYvaanBSr888ffbjgvgUAS4UtRjINx67tZz4xH2P6aIs04+f63RGDpE/eCLr1dbfgT4Sx0kWZ7Y/NULfmChDZGd6eic4Vix8C+7Nlbf7HMf+PPzvQaxPb8PeL79M1m/zwG5Zlu+ee8ogC+ZVOCH/YaN637JHv7Z3P7UGNv9fv+1v9vv95xOp2+89nQ6fe216/8/nU7fALb//X//3/M//A//AwAfPnz4f3iv/2S2UH0SY/SPi7cX7YZjrTc4J6neSDlJQEmWHrmHZWTMCzftjtZY5hjZtz0mKkIu6CJQcWNbci6oHCilkArsapDT7TIxVPC2ZJFPKaW49zMbIxIuULzqLrhwAzfdBqXE/7bkiK4BQKUUGm34wVaqPW6Xs6TGaUOPwRMZbCM3ZmU4xpHOGl70O35z/4Kfn+94WCYG2/CDzTV/ePyAVvLAaI0j5UKjbAWoEtRzqj24oTLS26bnpdlLWqgCrbXInIz4TPZNJyFIyxmfpK5CIfvuS2RJCWsUr7o9W9c9LrIOcWHvJGG5tw23y5mS4RRnXvV7rBEJ1u0yoVThbjmLvDgXrloJXlJKYZXhptvy1VkSoAfb0BnH+/HIrulxxsA8iiQ5ZbIqtNYQUuL3P/ycg5+5ajf0xjxKc3vrah+kp1Wave248xNKK441NMsmxYt2y/1y5rrbYLTmuht4Mx4Yk+ccZ3au4/10whqLMyLderccpaYlxUevtEaGJxvbSBCSsVgj/ZifT/dcWAnh2Lieox9RSNWRU4aCYt/2pCzy71ASOWas0XTW8RDGGnLkpbYlSw3NKRqcgmOK+FwI58xnw5GQUr0OA53tuHQ9uhV2oFDoKpA7+JEpiYzMVnCx1AofX3tiQ5r54lx4qw50zuKwjGmmN5YxWaYgSoRT9QG2WN7PR/Zu4EW34eQ9jdb8aHtVq7PObEyDMtKpeo6S7tq5nhe9YwxBAIVS5CI1GlvX8eX4QEiJu3AmpIzF8EGfRDJaazd0EQB9u5x50e3JOQswtXLrPs0eZ+CwzORS+GS3RyODpE47YqkyTlVEWhcDvbNECkrBxjl8TFhlmYvHaUfbSOBNoLCvdSmDaTnmBUXhdppojLAzx7CIxL9I2num8KLZ8OAn7ueJq25gcA23KbDRVhQJCj7dXmKVltAjqJ248r3/P2+/QiuZrl80Hd/fXnMOgat2y3kRmbEqBVVE9veD5pLOutoHLNL11/2e7232jw/zzjZsnOJUA9OkrktzCp4XwwBFo1RgSYHOOGIRdubGbvBJ6thuw0mCRlRBa0ujxK88poVt04JSXLU9WmvejAdyzuybTlKTswjUzjETSiJlYcovuo67ZUIpw4tuRyRx5yeKkoAWi9QpTSnRK805BAbb8NlwQamqEwrMOdDblo1t6YzUrw3W8fn5nod5xGhLrn2jptY4zFGkxZvaHX7wT0u9xjbEVBiVp7eyH4d5YokyXLswVhZBKbGkgPGaOUlSPkZ8ZQc/oYCtbbljxCjNZbOR+1BK5OTFYztPFAqtE2ljKJmmSnpFvifQYaMkzTSkJGF51R/aq1ZSvSlcdB03/RZTNB/mI+ewUJRmsI2EMOVMzJFcYPW9+boghSeJKXx90bkmm66JuCpnnDaUXBicDKBTRhL5dcNpFkYrk3HWcq4KrJICfbuBnNjbDapIzdsS42NKf2+lH/ocgvTGN47eNOIvLAlLpHiDqa6+ddH7MUPTwOOiu61eP2MVJpo6GJMh6BhC5W+e3mOVga7MzxLXbF2RZYNiSb6CU0ODhBieomeqAVQpKZTydLS0RuOjMFo6FQyWBoNRBmulo7ykVH/P1xNc47P9WuWS+hlr9jE4+GWE3sqoPV/8r2z6CsgG1eGcorcdLiXmZWIVZZrK368/kx73QzI8uqKx1pJiJH8j7uebmwHmWuOy1tGsIU4LmRbN4CTp+Oxn+Y4hKpCpDmLW+9za8+se9/UpOOmPA7AL4jlPUQYETomcfb1P22zriObrP/Ntm63X3vMzkJ/t4y/bFDJgWAG/hGX9csZyPRdf3xcZEqT6yc+PI5pvbjIIqVLhJHkiUyqPxzMX/wicYlV8KCJzPefPwecqmVf1HR/SjE75j3UG1uNwaDamwyfPWBO8NZqFNQ/76dpdt297/4//7uPhwFNvd+a39q/53vaKBz/xot/9Mfb2z9b2pwJsN5sNx+Pxa393PB7ZbrffeO12u/3aaw+Hw+Pff7z9zb/5N/mbf/NvAvCf/Cf/yf+Tu/z/+LYycO/mI6dl4aob6Gqk9tvKpDXG0puWwTbSbWllsfTVdM+26eh1y6fDJb1zkrCoRDj1/373MyiZ1oqcbymZa7PhEBamFNgXkY+eojCfBamB8SkyBs+UI6+aHRfOAYWbfoPVhpNfmNKCLZpP+wsG19S02MDPTrc0WgCdwfCy21KmA4c8YdAMpsHngK/fJquEyXozHbnptrweLrhfRm7nM61qmPLCrrHsXVtrCKCzjns/EUsRADGd+WxzgdWau2Xk3XySahMUl01P2V3xh4f3zDFyO41MacEoza/trmmN4/PTA71pOAUJ4ehMw3W7kQky8jtCjDwwMlW5sVGaKUQe4khnLJ9uLvFJHnHnEFCa2v2qOPqZTStCpTF6PswnkTXvbnBa14TqwoOfedlv2bmW91HApsHyBw8f5Hei2LqW++XE/zVKyNa+6TBGwpxSzvgklUbTEjjMM/fhTM5ahh4mMCZhuwabGP0MSnPd9hz8wk/mDxit2NiBF93ATw+3AGil+Gy45Jw9D/OZOUcabehdK14T53jZ7fjJ4b08+BrFzrb0TrqRQ0pcNL1M+I0jJPEQWqV4Pew5ealSuek23M4jWiVClFoPnxKNNmitmKNIjK1S5Jz56emWCzdx9DMXTcdlM6BqJP+uereuuoGYxSdntOGqGVCu8H/cfoGurzVValmK4uw9+7bl/Xni1WbDYKXz9s14h65dn1et4xxnTmmhMw0v+w0X7YDTlq1rySXzdjoy2JarZmDJUqkzRc8xZvF4tr2kwy6RbdPwahBP6rvpyGXbc/Azp8XTW8PGWn5+PgCFq74j19mvVMZIKJukp4sc3Rmpu+qM44FCiQIiBtMwVQlqrxve+xODabDaMNiGwTWc/Ewsmetm4Mv0IJ5BpTFWft/ONkxZEmZ9lvqjxmha02OMEj8hmVIUIUt43FArbLxKREQ1EieRsG+bVgKtXMcLPXDTSrjcm+nAnAIBz3GJj0Fam0a+R0tK/OHhPb2Rc6eV4sM0Ekn4kvjdy+9x2Q+8G4/MMTJnSfPOFO6XicE5LpsNSp+qt19z4TqOLIwxcdV2fDZc8eV0z7gEGmXpbcNhmSUcLSwsyXMIk/iogwz5eiML8jFICmlKkagEOLoaABWVXP8+Jy7bLacw4bNU1OwbR1Fyj7sgo4JI7HTRnKInpUhIufY9SvXYYCxLkd//WXPFMc5goNiWEEQR0mqR9D7EkcM0s2Txq+ZqFdk3A6iMT2JHuV9mIBFiYo6exhqOi/Quix+zx2eF0mIjOGsvw8KcBBynBCoTllI7WQtFCXAxSjHW2pG+abjuthIwtIgcMNWwPYywdo2yXPcbpuCFLYoJ1xletDtSltyHhUQqGVW03HdLZtv17JuOk59prNSRnaLnYZllOFzE/6yV2HHOOUJJ3+CM1LM/ny+OFdCgHoHdkj3v5kSvHc4alBYQnlKSSqQ8M1YJ8kZ3UJ5AYkTCi2KWIe11t6E1ktK6ROkzTRTOy0IogYKVDuQws7UNRhledjve5VMFTk9VRM+3BtjrllQkxMpqg87SY51XHTgSWBNKxlTB4fLIQD15PQEBpMjiWSPPBBmGZw7pTKMsSwwc08IK5wC6IgOgRRsaLL2R1PG1G7crhUE5fE6ooh5lj98FnAT8yRA7lfA4cPhFvabftq1+05VhW39Prucul8wSIcaJKS+PQHMVnXZoGaJhHv2z6zHPBNpIHR0otohX+dvY0g0ygByzZ6NE2i3Goqfk34tmkEFHnqVmBlG7CXP8VEX0vM4n8zSEWcHWH/f8KEpl+GVAnMmPA46ppG9ca1//2afPax0E/PsKWdf9fr49r+75rm3teV23Fuh0WwdS4rT+Zefi8edLoMMyV8FxixMGHcVIoEEzNA1H/83R0tq1bBAfuVWasSyc+Wa68bdtBbkWO+0kfT0VrnSLLxCK1F/9cTqs/zjbk89W4VPh9bCv2g3Nrzy237H91m/9FjFGfvzjH/Nbv/VbAPze7/3eN4KjAP7iX/yL/P7v/z7/+X/+nwPw+7//+7x69erPtQzZp/jYZSupxTMHP2Panq3teJ/PUKTy4+CFyYo5PDJzc8ikPGE7zdvpgPNWQgm05qbdcN0MhJJRSib3Ywhkm3jZbwhFum1Rhet2w2W7IRfwOYlXCSnEzrowNA2tNtL1VhNO788jrdJctH1NVIZlfCCkzE3b0RnHT8LCF9O9SCZLxhlLLMKwaaXZNR1aa3prmaLIYHdN7fFVmu9td0xJah5OcaHTjsu25+hlUXTVDhy8hMjEknFKApFulzN3fnyUb44x8IPNlQRwBJGffrK7lGAbpbjpB87R82LYcj9N0uubPRdmYOc6CXvKiUF1KApTjCiV2DYdu7ati5HMVTfwbjqwxEBSma1tZNKZE3vV4VMS1icVWqt4P0m69TktdMrhS6APMoF12rCxnfjk0szO9pziIo+2DHfLia1rKCoz+ULfO1orXucVbNzOJ9CKi7ZDK7gPwo5YDTln7sIi9RtZgrouml4kY9VnOdZOVKM0fdMwToHOSIfuVbth07SVmUlsXMu26bhutzgjAwijNa/6DW+mEygeJcfCrloao/nJ4QMX7cBgLF+cH7hpB97PJ+n31Ru+v73kYVmkM9VLpZAvidZoYkp8me4JMbFvO+79SMmwZAlr+f72klf9jh8/vOPCbYDMh+nEl9OBjW2qHzZI+q/S6AJoxWEphJI5BsOFG1hSIMREUaAVWGN50e3ZWMd1O3DRDlw20hEMyFDGWF508p3SaWGOqSbQFrSynL1n2zR8mM7cL2eu2oFjmEXypw2ome9vL/A5M8fARdvxYT5zP8+86IXpl1orkdNum44c4dWwkzlxI9+x720uuZ9HPJLU3aWEVeKx1sh9Yk4RZ61U0ZRCLgVrBeymIvJzqzRXzZYxz7x0A86oWlGgaI3ly9MDvXF0Work5zjT1OtAa4nCyEhNSc6ZU565abfi/06efdNDKUzJ15yBDhcM98tJamtSQKk1QKxwCJP0Ak8HlJKk4U+3Ozotg4iXmx0KRW/E//xuPrN3LU4ppjTjU+R7wyWddnxIpxruk/ExVbWBlfsUcp0uCDjtrSTxfnk+CLjMGrSiaQwui7JiCYHGWPZtS8lKeh81+Cr7DTmL507BTx8+sG87rrot+6bHKMWX4x1/cJBr/W6RUpHWWE7LTEGGVxddz8v+mnNY8CXy0vZYY5jyIpVNWnM7j1AUu6aVkDbr+MnDB/rG0Cs5pyELW/mQRlCKrXOoIiBNoTDasKnKCq3k+DpreTce2TUdYwpYbA2lyY+A2dVgt3fTCYoEQjXaYLUEcc1F8hMum56bfssfHT7ws/MtULjqNozBy7NGSY3bq2HPKSyMtcrtou3Zbi7YNi0/PdxhoqT8LiSsadgaS86ihLruthRVOPgFo2FOUnPUNnKtlFzQxuJywihJrRUQpioD+LSAf77otAjLVFgBjZKgn6zYmh6tlIQKzlPNy3WPC9dSMj5nGhxz7SUFLcnwRFrvBKAoGUqO0ZPi9MRGlsySJHwNDK0xUoWiFE6Z2nv51FEKq6cUphyx2qKR9URrHTE9HVmu4EgSfp8Wr3OFDhnoeArfSfW/nTZYFKcwUYpIMM8lotPT0n7t4FwVELum5eWw5cGPhCnTFFnDpJJ58DI0ssaIXYfvZgETsNONVFolXXlm9e+1+F7P2Qpi1mClgoBTlQstDb6yjh2SJC0BW6WqQ6QvegmezFOKbyTRYPAkwneAWgCnpapoWxS6KHzJ6CSjBcnBFwZ3SsujAkA9/v6n8CnLE1h6fu3+u4CfFZSurxdgnNmqjkOZH5nIX3SmnwP8zHdXAK2A/Jf5fT8+b4pv9rF+/O+r2mD9vR5Q2VeJt66DgW+ynM+3lbnPZLICW8R3aozCZen0luskMfkzDlU7g9PjeYqsQWcSFIdSrAHDfxxgKzaC6vlPEhR2m79eddTyTeb1l31G37Y9DUAKqXj+jw9f8Bv7a359/2v8ymP7Hdtms+Ev/+W/zD/8h/+Qf/JP/gm/93u/x//8P//P/C//y//yjdf+tb/21/jbf/tv81f/6l/l9evX/Lf/7X/LX//rf/1PYzf/xLZTWLC1M1Mpxct+xzHMPPiJy7bn9bDD54QPHl2k4Pu6H/ApcOdnUkpctnuMkvCn18MOpxWdbfn8dMdn20sKhT88fpBAjBJ5Ny0UpfiN3c1jsuxF0/OTw3t8Crzsttz5EbPWU1jDxjX0RkrA5+pV/QsXr7/WhXsOC0sUBmdMXmoqXMP9eaQxEtA0RmGn925gYxRzEDmoz1I3kIpDKyUeJSMz4Y3p2NqWJSXm5DnFBVfL6p3WZAo71/HF6UH8U8YI2zQ+oJRiqhJipw0vhh3/5v4tzohUddd0/Ox0x3XTs7MdVmt8OdC7lr1tKaXwdj4wh8Rn20u2ruWnx1usVlgt4LG3LV+c7vjD4zu+n694CBM3/U5YwmUmFQl8UVkYL6WULHhL4XYZiSnx6eZCbhEJTn6SupFSJJ03FMYwi/dJKd4vR5yyOCMpiDfdlrfzkZOXTlZh3jqUUpSMPOi1SFCNMsKmF4ltb61+TDTurJMe1hTpTUMqCVU0pUTG5Hk/nWQRnUSeOrimptpKt1zKha3r2FQwZLQkYt9GCVRKJRGiLAR8ylw07rHL1afAhWtZ62mctsKYa0uXEmcVKEWYlUY7WiPJ14kszK52vJtOXHbDYyWQ0YbXw16u6yyeNKu1ePWcZfQeZyy9s+goDGDnJIRiSRGlpPrltpxwRc7LGBdUv+E3h0u00tz5kU3byv5WUHuqaoi345E5B3wUH87GOVAtJy9J5as3cds0LDlKwFjJDK7h8/M9Z79w022Y48wYPRvbSvJv7fEbY2BjWz7pL/hqPqCLYmNtfXCKqmNJgU83l1x3G748H+iNJWt4v5zINdArVNZmq9raUy2JzxpDziJ/HEyLUoo5SV3Qi25T04Udd8vIwU9oI8mORiHvUwpTTCRmprCwbzt8yhSleD3sSGtqb9dzoza1hqygi6gSvhxnjFZs3cBGO3423rEkzxyd+PqSpzeWez9VG4bBKM19GOm15f104nvbS0kA7nrGKKFh92Xiqt3xsu9kiKg0O9dyDB6KwejMq26HRuwfe9dz6TrezEc+TCd8CsxJfM8X3UBrZQE7pwC6yvxqsm1jHNpo/oPrTzn6mZ8eP1B04brZEElMIXCXzqiqAAklYJTjptny+fjA0c+c4kSjZJjTWMv9PJFK4rAsXNiBxlg6ZdnYjo11HMJC0XDhNpy7wGAMTovcNOUioUmpcNP3ZBJfnO8JqdAaR2/kmmm1DDh3TUcH3M0CMLANHkmlnZMWP3EuGJOkv7LAYCwXrmdwAixb6wgV6EsKroEMrR143e6JJfPm/CDAWcsiPpUsipdiyUb8gSklUhLPbWcsnbZ8urni080lCvj8eE8i4rJYX65dx1QSc070VZWRSmZaPEbDMUdU0iypeuJikWRibTDZQBIp56lIH2TDNxeKq0RXFpSyXHdYNOIP3jSN5C9UeBjy6h5FOm0RRrStP78kiR1qMJzCLB3mxlLI2KJJWRhPqySrIEQJLzMGuQ9MD7TaEk1CxW+GSDXIonomYbIArEiCpEk1mfYpiOmJvXoOSNb/XhOSV6edRTrTP+TlUZb8sXR7fZ81fujoZ2zNNCAJINdG09aqv5gSYw6YnNB1375rK4g1QyuDrj7Z+H+TU1rB7Ap0NFRerjDhq/xZk9Gk6rMF6Y/Vek1PjhJCprRYpkioeo3o7/i9FhnOqgRb1zMFsbjkFKtkN+LQnMLEWiqsMVLJqBTkTKrKgI/BzHoO/zjnZT3+lZ0XYCjvmOsLXJK6qudy9e/a1mv/49eu0u2uMoHTL4W1Tz/3dE1JeNvpO6DtyvKWj/5OhhOyLtIZqAD0lx2Hw6CV3K8CCZPKo/9+wNZwMDlfjbIcSvoamBclQcHmiHscVeRHNvYXDR3Wmq3OWA5h+sbQrfDknf74eP99tnUo0mM4h5lj8LybTvzI/fmrWv1Tq/v5R//oH/Ff/pf/Jb/5m7/J9fU1/+gf/SN+53d+h5/97Gf8R//Rf8T//r//7/zgBz/gP/1P/1P+7t/9u/ylv/SXHnts/97f+3t/Wrv5J7KtU+yQE+e4SF9iCiLjgtopKdKuk/dsaEhZwn92rqXpxJfojGVX4N7Loi5WL2pjbO3s7FhCIGtN32l2Rh64+7Z7XJzeVW+rM5ZWu5quHMicOS0ehWZw4vdSuqk1GiMUOPmZU/S8m0/yhbOWlDNfjA8cw8wn/Z6rboMNy6OMRcKERKrptOIQFimWL4olRnwWKdTWtcSU8CmxbRoUlp3rsNXjG6v8t3fusRM1lcL/6+pTNq7lDx7eEXUG1/DhfKLR+lGCeu9HLlzPUrscD8vMTbtDa6kpOPoJowy9dVw1fb1xFLZuoLOGMQVK8DTaclxO/P77LzjlmZfNFmdqKFAzELJIKecUGFzLD3c3/PTwgZzlgbCkgDWWl/2eB39ma1tiKTXpWBbRmcJGO35+uue67dnZnjF7OqX4teGaQ/AsZeG6ESnz3XKW+H9ja4etkY41Y7huRR4bomYqns45WmU4hIUHP3HTbdnajp3r+Dzes1ctpzDjk6Qvv+p3KKWrzDYypoDW8FsXL3kzHrDaEHPkFCJLDvyHNz/kHBc+P9091gdtbctVN0g4WmXOO+OEichBqqxa8XG2UZaGL/VWpGkoGqsJRR6VTpuaPBp50YvXXDzHC7fLmdMy09mWxop0b2McpyLA46VtOIeJN8uJkgGtK18h0rjJe266DS+HgZwHtNbcxxmHDFUO80x7YR8tBYUijFrTcz4vXLQtt9Mo0/Qi4EKhaJTiFPxjKNmHfCIl+f+y8Ev85HgrXc/1XtE2DRvb8HLYQRHQ8KLfcd0PjCGAktc5beT8NTucNvJ5ofi3D+841OO/aHpCyhzixGXb4YB3k3SfWifhKD/YXJPITCmiFdIR3W7orHQ2pyLswBwCvZFqmJQTuR6H05rGOg5+oomO728uUVr6N1MuGKUwWgZZMRe2TmpcGiODq5CCACotAW9jUsQcyDUIKyOe9cbK9z6kzMa1NEoTc+Lzwx3WVFmt0lVtogh4ch54Px+5bDdVTuykw1V39Lpj30pAUmscJz/RGUdrLB+WI1MQub9PgUOYMErRWSevt4aQymPv+K/tXnDVbrhdRj4dLrBGLAMoCG1it/Tc9BsoijkvMuS0mptu4MN8ZkkOoxVLCCgDQ+NoVcchLnw1H/l02POq33EMi9SiGcu+69g3A6cwcwhnSJFWW1qjiCljjGJrG+4Wzf+Xvf9cki070zSxZ8mtXIQ4IgUSQHV1TQ+bnDEjjbyruq++E/7mmHHY05zuKqAAZJ48IoSLrZbij2+5n8hEooAWhWkYscxgiYyMcLF9+97r/V71pttzDgtTXFjijNWOKa7MKTHVmqhSoMRMUcJ2em3lmlwyW+srI6+IRV1r5zZektl3pmVWlcGylikuDK7jX+1eCVtRq5WOYaFRlqksHJaJJUVhqnKkc57/dHiPRoawX/Q3KBS/Oz/iqu98cJ6nJbJvejm+WqNyRqXE0zJx3w4c15VTnHBKNpJz+uyaCwR8qZmvRTEVyZUVxstUxildN+eXIB/5ewFyjXISIpdmHpdMLpHzGglXUCZbZgEnuQIlU9lR8QJb5dg1DTllOufYOs8xaB7SiEXuXZumI2Tx3rbW8XV/x//51VfYR8v/uvzmmnCt+KH8NL34mQAI2WzHWpMizLP6vQKaHkcgXIG9MLaGVEW1BkNAVF4XSHLpBvXVafpjWbTBsG86tNJ8WkYOUYLzDJpcLQOhHpVL4utP1Zy87CENJaFTYa4A4ac28v85lSgCYGQJ+6nQKlOUpsZb1HiocpVmrmRsiegkyptWNVx8lF47PI6c0xWIXIDmJYTs8roVSOp8Fe5a7dA643K+ni9riddjsBLIWdEoT665Kh7QlVV+mWR9OYY/dSxegtnLa7x0zl58w5fP+Jzk+tBgkRHmH4dOP/ZEX4S6EtYln/QFWL48Z38KnDdVBZSQz1z9iaLqi7f4wnwmRLXSugYVAlMdjPyhZetrLVmOb49UoS1kOmTfvSRJ945k5rL85DlXgIlUQ6k+v98/Bmoj0opijCGFz77cHx/9/5ZCYQPsXCNqsBz57fmRL4f9f8Nn+POsPxuwvbu749/9u3/3ez//5ptv+O67737ws7//+7/n7//+7/9cL+1ffEnc/cSH+cwcV95PR0IJ1ykcpfD15hYofJpGPi5HGutoiqfRiue40NWSemcMz8vMruskedZ3PK8TWmnetFuOZsGFGWonrDGaV7XKpDGWr4e9TLVKZo4rT+vIWOW/oRzx2hGzY+8GMguv2o3IJ9eZ5zBd++K0gXNcGeNCypnBOjJw32151W3JOTMnYdCcsWhVOIaFOQZ66zgF8Uy21rFzDae4sKaIVbb2wIpcTLryxGP6vCw0xtLbhlRmliDP77ThVbchVe/iu/FAayyhFHor3gZlwGvHXTuglwmrFI/rzH3bE3NhjBPv55lYJAFWI0zdvRokdEjDmAK9EfFHy4aHeeSu7xlrIE0qhcF7jmHhTS+hZ6lkUikyZa3ng1EKhWZOCaMVD/O5BsoUkS4WCaB/CjM37cDr5o6QMlOU/t9bu6GrgWCdabANOOWY8soxziITtwOt9dwax+M6MRSPQQDfu+nAq2aD11pkikT+dveKOaycUxD5dePpncUqCdx51Q2Ssps/A7E1RZSC1/2GN2xqyu1QJ+pSKv9hObPERGc9a5ZwkNtGmEWvrYjIiviIpHJnJOXCp+XEFIPIZ7XhTbvlnANFJUyxVYbtKEXCZBrteJcORFXYG+m7fVwntDLctz1LkkoUj3Sf2mLpjWWOiYVASplzEHnsxrdoCp/mEzFnXrUDTml+fXjgH0rmdbepgM6w6Mh9uyGWRF9D37yxpCzS3nOOhCL+2Od5Et9piozVp5lyZowrS47srKglDIp7LyzdaV1IIfNkpJIIFRmsvw7DjmFiSYlTWCQhWhve9lte5YGQC1OaySQG45nDwrmIB/L/+upnDK6VdOywEEviXm8oJXNKC2tJmCQVHjvfMceV1ouHP+fM4zoS1kRr5Tt132w4rBPHODPmwJ0d6IznYzhSCmSVmUNkyZGQW3ZeqmNCTqxa8xbFu+kgm7UoYVdzyjTG8LiMWC0dzxcv9hgLI/CVk57Z7w5HHsNEqw1aS6JlLgrVwWAajNKApjHSC77EyMiZXdPQWcs5zDyuE1vr+FiKgJfWUBKc1iCVJsCYZhrdsGs6dq7lrt3WAdPExrXcNT2fxpHDOnNcJ5y24ll2UnGji+bODaw587yONNrxqh1QKnNaJFDQ6symVh/tXctYP6NX7Za3nVSEveoGUi58HE/86vgRcrkmyp/WhZQiJSv+9+fvax6D3Ie0E5BxWEdMlmHe83ImFepxXbBWmCavDaMSdn3JmV672rcMU1gpDmJKPK8TISWyht56drXebWslhfrDOJJIHMLIcZ1k2JbkNWngmEdaXA2dg6Akb/Y/Pr1n3wiTPmW5Pi4lorTBKUPnHB/nM1vf4F2LrvacnfdMecIVx11rOa7TNbwrUWqYnFSV+SQ+6VwUSmtCLpjqbzRI96tBc2KpEkOFNZo5RpHtEUlrZOGH3ZAvK2Gk2kyYPPG6W7y1EhCGBKj5el+bbCSkROcabpuex3nknGZKhPfTM//Lp8zzfOa8Boyi5lykF55YASDhCsVy3dgLKAmVhbvIa1+uC7h5uS6u14VEh8jLa9Z3BaEC0V6Ckpcg8RJtNOdAjoWc5DNwRXGu/uuLBLxB09YQuwtAsPXnVltylgolVeGYx/xkuu5LOepFEvqH1iV4K9TPrEWxtS1OWaYc8BjOFZBcpMaKSxptQRWx+/SuqcdB1aF+4ZDX6+t56TX1fGYzE5k5RkISBcvPdnf80/ETuqLfKYv0OHDpXVVMFFJZxGuMKFiWqzLg8/t9ydr+FGi8dLgGPkvOf8qLO1OwlNqp+/vr5WNfOoYvoO3Cnl5+VqhVSi/CmzSf1QGXx7moDuR7WPuYkRTzPwZrO3Qdv3wekkgIl8IYg8lVYvxHHucS4qVIPwDebf1/Y0pXZvuPpTS/HB5YpLv2ksAOP/ysLsx5Bqa44NA/qHP6qdf9XyI//ql1Y1t6J0pDGW6K7e0vbf3ZgO3/Py+vDb8+fWKOkcMy8bhOwogNOzSwbwae5wnvJOH3dbtlToExS6z/1raAZjAN346P9LZhsJ7GWlCKkjPnLFHoD7NsAm+cxOyfVvHzXr45W99yCDPHZebTcsYbTcoOlCJlaJ0wVOc083V7yyksUvVRMmsSBnkMC+d1wRgj3uAYuPE9jTZMtU9xyTKn3DQNSwy8n84UCk5ZScUMKxbNmALHKsc6hcDGiSf3aRn57emRX+7u2fsNcwpsG5GQfZxPtMbyptvyuIxoNTO4hm/nZ6YUCCkxpRWNwmjNlAN9cXy5vwGgMYanZaSpYPMcZlIuOGU4rTNKFTrj+DCfGavXeEkrm1qz0yqHRnF2liVGHueJU5j5arMnJ8ev508iZy2aNUs34X23EVY6Z/FKOs+SVs7zyiHM5CJeyRgTyUgokhxBuQgqozkHSRje+warZcO/dS1Pa+LjekSjabXIo6zWHJcZ7RWttnL7LwKE/8f9W2JlHL21fNnfYpXmuxiYg/iYtZJ0UpXEs32yjlftliVGVIExLPxsc4tCcdcOPCxnPs1nCtBX/y5Fced7etcQl8ibdqAxlksYzgZHqX2/jXG0Wlj63nnejQf+/cO3xCJsRaR2+CLBMnNe6ayA9V3TYo10S7ZaUoiLyhzCwp3vq7pA/KrdxvPd+EzJGWss+85fw5gaI+Flcwqcwiy+vWbDzgmLP+WVkjLHdeIQZna+k3A226IK7HzHYZ0oWQYa76cjkch9s+FhOTPGyI3veQ5nNllxjoFTDOgiITsxR950W/ZNx5wifc41jCuz9z0UuGs63o9H1iwSvt41FApjXPh/fv+BlBLGGHauYYqB78ZnYsq87TbCLoeVX2zv2DU9//j8kUzGKpH1JwSo6LjSaCuMWox8mE48r2duvIDzUxRrgTeWTjvu24Hvz0eRCWNQRRjlfzh+YA6RjROJ7DnIAO1pHYHCr48PzCnwNJ153W952255Nz6hjbCHISeM0eyc5Lt6Y8kKUso8z5IG3ltHKYqPy6l6NVVVdnj2vpPNSc4oI+zo8zKTECZ4ayRlfE2Zu+pBfpgn5rJy07Z8mEdCjhgtadZih5DtfWc8sYgHGMST/WE8EUlklQkpMobAnEc0UuP0P26+4P145LvjCWs0z8vM4DwhR5QyOGuxMRBz4hgXQhQVj3ynFR/mIyF1aC2VW6/bDe+mZyiKNa045VnqkCSXTFdsvRZGNq5h4+VvlxApTUfO0lU4p4Q3pvqBhcsxiH2BImyHpNyX6/d7TiIAPawzz8uIUoaNdlIJohRb15NL5tM88tWw5bfnJ6aQWKNsdYsq5FRYcqTB03qPNtJproski2s078cT33Nk66SSLaaMUYU5L7TKc9PKd6+geNvtSCXRastSEnMIeC1b2+M6i3y5bvMTmecwYopCKS1VNLnU0puLJLWwUCt3uLCG+loDdtlILnyu5LiwXJeNsEdJInGJtMrjnWXrOhSF53VljJGCJFsbo5jiitWW3noephPnuLLkhTEtlJx5mkbmtDKVFVUkRKmpXs7r9lMBReHQ17znSLzWgMh7EeYx8nk7PP0ehyte0UvPZ6yAv+ElA6hrJ2m+ej1NhRO+3o/mtIqfVmWMUkwlMpaIR5jsC1PYK4tzjrRmNPlF4FJG5Uy8wpGIU3Kdcejac1uw6GvFTgRaLK21nOL8B4HHhSG+MGge8YkHCl4pEpqGyjBXSJGBXjWikKsd0mtaawd9DeYqmUZLA8VcmeiL9/nl8kh3ds6Fc5x5nmWwa41hXtdadaSuagBV/xkQUNwig7q+eI5Z8oMvNTvpnwGBL6WyLyuDXv6+43PC74+9u5dj9xJIay6M7w9hljyHwr5ggV8C5B8Lkq/J41ykxaEOFNRVvvuH3pe8ns/H7PI4rn7SIclRaZQlFWGAf2pdPq/L65MQJ805X2rBEhttCcUQSvyjwPJyjnkkdGzhcxK79MrKkOYyCLgw3StZVA71d//Q+/4vBbUvgbL0F4sVwiqNKkZ6g/8C11+B7Z9hneNKSBIGksgoVeidl5tsZSffzc/oRWSfY5xpjBS/xyR9rhrFOS6ElGm8rZO+xKqSJNDmyK9Pn4hFevZSvQzvvHSJvuo24scsBa8t354f+Tifaa3hTbsDpTiHmYdl5LbZoNGS4hZEOk1RbJz0JrbWMye5bCil2TUSWKKV4mkZmdJKTvDFsKXRjrHUoCNtCTnzMJ3keVxHUfBuPGGV5ZvNLRvXMKVVNqx0jDGQpiNOS33OkiJNZ7E1Zdho8eo8LiN3jfTkJpWhKG7bHqsMWQlY39TNvlGGMQZufMf78cA5iqf0q+EWo6UXdM6RL/otg2s4x8DzPLLpGpa00mrLYV2IOfFpOZOyBK0MVoKNNJrDMpGRocTGGp4XSYu2ShJl975jTkHCh7oNT8vMw3ICMq1q6FwDSoJofntcMFZz6zu89hQkrfX78YAzWpj/orntNtx6SQdWSFdmJvOL7X1lrFStjZFz4dN05hxnGqX5dnzmaZUezdY4spLzNmlPUYWYJMXTGqlFmqIkvhql+H99/I10GBdJ0+uMqx3Empump7een29ur15zUzfPY1wl+ZvPpeBTDOx8yy82d4QY+f88fscYVozSpAxzjDirCCkR0iSsc5bNzN9s73k/HWvv8YYv21s+rSce15FOS6JzYywpJ76bnkilSDhbKVhVbzglVVl5RhHY1yRib6Xb9FM4Q1B4JUEnth5T6cb0GK34dnxmCaKuiCUx6bXKyT3nKFL8i29Z0poVt25gW5ODL0z2XTNQFGxdV4PXAqe4sq3gtjOGU5CQIo3GFMVzmLDJXVkqrwxRRT4sZwYnXc0Py8g/HCSBuzMWjOIfDw/8m9svCCrS2T2tlcCrQ5hoTcPH8YwxI6VQPeWZnCPJSnJv5y1rFCnz8zqLQqFkHpcjHxcJLGu1JRvHGGqgVZtZQuD76ViPe4fDooxsjdYq6b7I0FstsuAP84TWik5L1+IxjFVqWbjznVS/lHz93871WK2oOU7ct4Pc0ItijuKpXlLDznUYJaDqOUxyzgFzDCwpsfc9jbKc4sIxTKhSiMkz2JatbTlFOS7vzs9cUpmXnGiU5m2/5XenR9ac2LUtz9PEnAPncUGr2tMYxX+6cS1TWFFaYYyjc07OyZT5tI7cNR29MTyuZx7mM85oEgZntCQK18TjvobJtcVLFVNJHKaFcwysWWq5QhawAYCWQZSoeQK6iPR3jIHGGELK9NaxxMzGS8L1kiP7duB5GVlTxpnEmiOEwqt2i7WGxjq8Mex8w5hm1nUWUGIkwXnve9YSBFgj8v01ZxpnyFmOy6nyhFYZkQQrGcaaIvaNL7sdd23P//78Aa3BK0Wo969zWJnzUqW0dbOfMzFfQID4W2dgUJ62OEbCVXKpyVgUTfVAl3pvHXAslRkFAdcXRilQ2Ubl8VoTs2LfdTyHhUbHajUKsunWnqAyCkPrxL271oFvKZ9B8pwi53TJzBW+zxZdt/wXeWnBaYsthiWv19dxARIvt6m9bRjjQgOc+exTvTCSGzwLmUikQ12rkRQyILjkRAc+pyDr+iydboTdV4ZxndC1/sYaQxsdicCKADALdKoRNjiKBL6UTCmhyl+Fqb2AlIB0ejf4q1PSG/H+5qLwWByF1lo603KI8x+UJr+UBF+A3ZolndpZR6aIwoLCGmrgFxZjDNZoirIyDE6FV/1AzLne+0XyusRAk+Uc/Slw7ar9SPZmiqdl4rTOBOK1Fufz+SVDlIvn9MJwem3ICswq4NtX6e5LEP1TTN8lEfpSg3MBci/Zw6b+7U+Byctxu0h+1fU1/T4YWn/iZz+1FBfpcbm+85WCr8/glWMtf5hBvFgHVsoV3MhAp2Cr4B081ih8/OFxelmbpeo7fFmZNVef7EVPkHKpgx8BhS8l5j9el59NdUTwUi0hIVPpBwMBg5RKXfqvLxL2/9arrZ/e5T1JR7ZkKRRVmOLA8FeP7V/XT62nZcQpjW86qeopcmI/h+Va43FeFnonYSlGW5xW3DUFrWDnBg5hROXI18MNaCSJL660psEqzcaJrG/A87SOHNaRu2Yj4G060juHr8mqn6YzDsurpmdMEmjTaCOVACjumy2ttSw5McaV22Zg33RX8HLbDEwxsPctuWQelpElB6YYcNrQaMtd211By8M80hrZRL07P1/9ascw8/VWukBPceXTMpIpNGYHWjE42ejfVnBRiiQVd8aI77ZITyQIg6iQMBSvLYMRED6liEUYoF8dPgHST3vXdLwbj5JQqwyNNhzXidZYGov00rYDHyZJBT1pwxJFDjeWKJJBpYgpUlShq8nGThvESiohGXNeIUn37VMY2dqOu3YjlStxoVQJ8hgXcpaE5cMyo5VIyFPJjDkwZLnEFrKwGPMBMrR4GmPZOs+Nazmvwjbtfcs+iVz9th14Nz5fr66nMLP1HXdtz3heOIWVx3UUuexSZMq8Rop1YOC+6bFG1eFBz5ILawr85vjAHANFFd60W0JOfHc+cN8NlJIxRpgerw1rLXo/ryuNsbTWcQpzHbRI3c/H6cjPtrdYLWIcZy33Xc+HcQQNO++xSnEIE7fNhikEphzZGvF6n+LKm37PbduzdR0AP9vdErLI7m21BNy2A++nA1oJG+6N5bzMLAWmHLjzA1pd5qbC/l02/6VIvdXgPM+rdAKfajjaGBemWNNXlWxaGuNRWupMiik1fG3l43rGY2Vwk4P4n63GV87jkvM5uOb63TnVUC+nNZ/mE/fdwFZL7VAk460mLyKzWmK4bpicNmg0D8uZVAqnMHPT9hg0a86seamDDrFAvGo3HMNEaw3LCuc4co4LJYK3ErBVSiLnjNaa//T0QdK5l4m9a+ltwzkunEKgFM3etxISp6lDMjiEiXfTkeMqjOeH8ch35ye5BgYZotz4DqXgEBcGJ4OzMUW0VjIIUeKPVkXVoKnEGBdufI/TmvfzmRun+ZjPTGnheR2xSpJn79oNcw582e4kWKjA4yI1X0YLYFriWr3MTlg7VTBWAriMksHjzlr2vqO3nk/LKAnlSN2X1SJvLRnezSdarelMw70dmLP00Z7LypIWWtOwKpG2ZQqxSLjbrW8xWsLrQjpzrNfOvesZw3LtRZ9i5HkdURgaZSi2MGjLXFM0pxw5LYVjnNFI0nhSUu1iqmrCa9lQynU7s3UDSxQf2hIjqWSOQWwx3/SvmHIkLBmrJc05l8KaCx+nE3fNRvpokfR3pRR71zLHi0LHgNI4I93Ha0woI57lOYtFI6XMYZ3ZeY/WmikFYcVyIeZMWRW3bYNCfOC/Pj0Qc2JaxYd+DFNtGEg14OWySf+hBLAQJdEajdO2tgV83shftptrSZUJknXZwAszKuznj+WVqiTGmpLfWU+qCc4xZWLMdN6x9R2JIj3sJclgYRUPvdYaQmYmEUho1NUvmKECks+g6QKFLjVRl432hVE2aFbkmA/Gs3WtBJbNM1KiddlYqwpY5d+FlZV6HU25Sq7h0pdLDd8ydegg/31eZ0JJtEUC5S6yRk1ldK3FFAdauEhTCl/0e45hZi9zfw7rxJSgQRFJuAo0UIVSNCuBmARwt9px4zuRUFQP8oBnJbLUY/ZjSe6Fsbywl6EOMk5xxmJYinx+2RiWFCUYKkZOmsquyqcdSExhYSkLpgqyvbWkNTH+hIhXAeeScDGgKTiseNdf+Jzhp3t6HRqPwig4hJmLz/PzXUvRvDgvLim/L1+F3AFUZcI/DzQu8u34o9//MUMLv98x/Ke5X//wKkjo2eVcDfW7apHgVWs0XRSp/Y+rf1o0GyvkRUG8r/OLx718by2yV7gcqwvIFFD9uUO4AB5LJNb3HBlweC5FTvK6jDK0RpQB4sH9/fVTbHeDuqatS/3UpScavBLeOpV8HU5dfNH/rThUi1gkeuNxKTAXsaWVXBPgnWctF977L2v9Fdj+mZbVkkzotTCXz8vEaZ3oqhy5aMWSEjdaqhZ637BEjbOWn21uSOykFzRGpixMUevlojvnxFfDHqMMH+cDr7sdU1w5x4X/+Pye1+2usnrwMJ3IqciEzxh2qiaulYhLjs6KF6cUYUd610hVTa2mOYcVqxR3bc8UAqkk3nZbvh8PrCQ62/DFsOd1t+XiNdk2jfRBhoWCYud6lhw4h4VUvVbik5R+xcM60btGGJzK8KWSuGsHznFlrl2Qt74H4LvzM+cg8kmnFaVYlAatNYPy4sszhi/7HWvOPK1nnteZKa6MQfpqQ81hf91teGMdG+f5T88fuPXipVO94rvzM14bTsvCpob9vB4gpUTjHEsM3LcDn5YTc5FgFYsma5HnWaX5ctjxRb/n++nAeZkZk2yHLuz4u+lAaxxfdDuWHHhcz9y4Hg0clpm1RJYUMGgG7zgE8Sx3VuqPnHFSCQOAujJIH6YjKSu8heMKUwjctj1vuz3/MXzPYDwly3RyioHGaFQpWG34tEzss0iXP0wnYkm0xjKGlY3tQAuQH3wDKJ6XiZ9vbq+dq787PfKq27CxDcnkawfzF/2eOUUBD8awa1oJhKlL2FWpe8pVCOlK5lZ3rJVFikV8fSllnuaJOS582d+SsoTgDE4Sio2qioeciCnxRXfDw3pi07ToIN6xUkTw9LyOvG53lCJJ06oIszrX7uAvh52w7day5EhrLd+eT7U2J4k3bpk4rAveGal+qpJ9CmijybnIsEpJ8vYcI8+LfMd+MdwBcNP0GC1e7I/zkXOQHuDWWva+waB5Nx/ptHiNzzEwx8gSJ4oCVVQFzAIKrVHkKIxEqwxohaoVXQZJO/6ylXqsx3ki5MhgG351+ii+1BR5ngNOK5Z6Dcml8LSItHjTtGQKxyhhbBcOJJVELiJZPK0LWkOjDR/GAw/rxJ3rWEvgGBYO64xWSJCRh1Y5tl5dE8AN0p38WI/dqfbLFuCrfkco5TpAWVNitVLn9f0oXZRWJRrT8Wk+8s32ltY5+iQeXJFMSuDQUoRxX3PiHGaxNRjxpt43A9ZYnNYMrsFqxbv5mZwTh7DQWkMpCq0N5yDf1SVIuNCRhWOYOa0Lb4ct923P06JwRoLJBi9Be+cwMaYIqyhRntaRwzLTaEle/bQcRQGUJRxPKliEAZ1L5pXdSip6KWilUEWjDeJ1T4nee1IqzKvM6gdjMcqgldguUsycWHjdddyVnm/nJ3yx3Da9pLnnQkoSbKRR9LZlSgu9daxRmEivNG+7HaiCMVoC8dqepyCqljUErG04hgWnxPdsrPgxb6x0dzbW4HTD03qms45SkvhVU2TneuaUed31/Pr0kUbX0LAS0EWjlSaXRO8cKQgjoq7CSlkyshBZrkFxSFK183IjKnLIgqNUaClb+EiuUtoLe/l5XTaha92A66x4WE6VwbVolel9Q2skNOywSDK20orzcoFgUFK5AhZVuVKl1fUtCHusroxkgJry3eOyxZeEx7G+CLTSQIOVAXsWQN12A2qZ62MWznkhVHDQqxantajOKrP38r0WRFVisq4ZDdK9GWtmRKFU1lSGiCHFyr8pWuMlHTrJYN/V2p+yFu7bgXMMaD2jk0IrXRn6dGUVB99gVyX1PMCrpmfjO9Z6DbDApmn4uMTqNf5hwFUBejwH1uqjvQC3VEFcIkXpGL6MMpZ6RuigCSUSiHRYUnSELC7JTJb9jvqcitzUz+dybn1OIRbmzylRKJg/AhEzMNbPwZXPUtnLme2QJoVYNJrPCd0XOf1laLMgoWKfAd9nOf1PPXvhs+/1pwYE/zWg9uU5dVE8vPwWJgq+KFE/8lnafbnLeLgy/aEmFb98X6JvoP48XkH8ZUAjOxdDozU5BxSKTrmaeP1y+FFEHYXCWMWd32KwPC6nWu30p7/ffGWEL6ytwtRzbC7rD/zOF2b88v39U4PR/rllAas+e8JXoEeCFBtrIRfmmHheRr7Z3P03eMY/3/orsP0zrH3T8TiPtDVA4hL41FqPV5bBtSypTq6rd+kYZsYUMEUCV1JNiU2lcN8MfJpPzCkQc5aQlul4ZVQ3rsFqzWGd6Yynd8IaKQVLksv23+5fcY4i0xrTTCmaXdtw22y4aTpUgcflzBf9HqNUBbcrg/NMMWCV5qYVL+A5LGxcy9/sXmOqRBi4AtK/3b3hV4dPuEbz/XSoaZyZ+26QG57SbBqp3okVRKc6Hd8Me1LJOG3wRuTKl05gU3vwlIIv+h3nGOhcQ6MT1oitPxep5dg3HccowOB5Wfg4HfHGs/eej4ukxBql0MoQS6Gpd053qe7xLU7bq7/qpumYfWSsfbmpJCYl6bdLjnhluW0GKPWYq0Iu4iX1xrKmJBt1rTjOkcf5zCkE2dxaz5gWpiXhjKYxBq1F8nrjO7LWYCxKC6trlGyMH8LIN+0ApXCOgVQyt77nt8cHsoa1BHwRf9dTkNqZX+7u2ZiGxa0UDUp1WKOYo0jnmywJpMdlxiTFx/HMbdejUZSsOKcZlTW/qeA1pCgVQkrVcKpYa1IinfWUIlU5343PbJzI1XrjGa6BBXLJDjmxpMiapFrGG4epE/IP88SUI6+7AauMdB8bx1Z7PiwnGnOmt56bZpCBSgq8Gw8ig9OWSYn02WtHSpl90wmo1/D1cMvTMspr0wJcJdBLWKm3vdRueWNozEBrHKUUzsvKFFce14lcThhj6KzI9nvbcFiXCiyFZWyMJdRU4Y3zNWRMvsulgNaqqgkUD/OJh3nksIgPPy2FX27uZXqbM0/xTKM9U1p52+35p/MDa1xETq2hNRarDGSNUZkb33OICyklQsm86Xcypy6S3P1xnflufCKXgrcWheZVK+BqiicabUmpkHMmaSo779BFepBzLpL8nhNLKdiS2NBUqbJCK2rwRqbVmscwEVO4MlGD60TFEWYe04mbZqjXjOplUgLQFCJNP+eV3vkKzApGW3IJdDqJzDNn7jrpKX5YJggjphjej0caI8nvuT5fRNJ529UxrQt73zKlyBwXTuuMU4YlZuY4kUshlkyrDc/rDBQomfMqicHL5Zqt6ia5ZKn7yZklr/z6OeCtY+M9c6g+xJxYc6jMQ5W5Gc2YVorK7Jue+27Lb49PKIVYCawhxcxU2VtrxT92jmvtTjcEa8glctd0fDceBfhpxVRTapQSr56ocAqfUsIqaHRDyJE37R4obH3LfTvwsJww2eAKPK4jCalji0kCxW6ano1vOYSJc1goWdLQ5xj5urvhn04PjCVCyvTGUYDOS/hZEx2uJiyrAo/rkVIKY0z0pmXOifu2AySM6HEamWLgXBa2TU8qksBtlSJi6Kz0Hx/XhSkvP/DwGWUknKXKoE1l3l6u/OKfey0yVFJmrhtgEfNpVlL1jVpJ0M/i7dRI7c9hKXQuwQKNk652+Q4XskosOWKS+H9jhdCFcvVKXhhblS9NufLfRHorjOqF/TmHid50mOS4dJ4GCq6CY600c02X31jPlAJNysxppeTCnes5BAG6rzcDT/NETuUaiiWAPl3ll7ootNEyIMly3U8kNtaTS+aYqis0SRSPRoK5Ysmg5Dqz963USWVhTD/MZ6yWvYczmlKQbvYkbHIsmb22bAcn/b8FjDZoLQFC0RkO80Qol5AfKGg8GfeiqmUlXCW5lwAmuIA48V1nIo3yODTnItnQtgRJza3HdowLS4n1WNcQyJKuUu3BtMScmMulpujzBlzXYZoqFWBRrlLkP7Qun7Wuf6+qauCE1OaZH/3uS7/sRTZs+JzUfGFiuxqY9Yee/SWovTC4/7Wc3o///sf/nikkxbW20KIYtCcXWErtEM6F5+sI54f1VRdA/1lmLOvyTZfvaWKtBEeL1Nwdqs3lEmJltCLnwkpko6UC8GmdWXP4fE3hnw8s48V/v/jVHeCUFUvGT/z+BTBfHv+/BNhePmuFSNYdogQb83h9/JVMU4p49I2pSrQ/9m7++1t/BbZ/hnXXDJz7hY/TGacsr1tJK85JQOjgG0lAXaaa8igy3mKlX7LRhpXCYZl5028l1VJp5gJfDzd8nM88riNP88TGNXw/H2iVsBD3bQ9K6jLOVQYUcqaxEqzQWZlKhZT4n1/9jM6KhObTfGanOow2pHpxF29lqJt6+dtj3ex9Px35OJ/YePEInmvolNNG+irNk8hOjQQuOa0ZtOOU1ipd3jBYxz8eHjitkdaampI701qJVv/20xNTXHHa0Flfpcqe22ZgsJ5YMh/GA785PTKtEkhVSmbr2uq3k3TiNa18mkd+sWtRtuMr6/k0jcxxZc2RoQZkNcbysJ6xxjBYkYQWHN/URNc1J359+MSyRgHzRXFKUhGzpsi78YlONzUhuVAofDc+cwoLT8uZQxCG43kdOcYZZaBTnilFTuuCUoYv+w1zTLTW0xlJ+Jxz4k27pa8y1TVn3na7Wvsj7GBjDBsngCCSuXM9Ec8ShR31GO7ansE1vB2kZ/Lb8xPHMF9lh0oJG7rkxG0rm/8HMzKGhcF50BmKIaTAP80jj8uZKQTe9tLT3NuG99MzOUtXb8iJmGVzNlcg82k8U1SpXb1DHR6sHBY5rzrrWEJkYmFZIrFkLiK7KazctgMpZ5w1mNoRfd9sKps3w1p4XCT5+05vMDXNONnCvRoY88LgNlAQJi3MbJ2vPcG+yqJFE+eUeRHxL3LhwzpxCgtjXMkqgxKAOofAUyp0ca29wkY8tH2DPimmIPPYi6/LGQcFclYc48K/vf2Cznp+dfjIh2nkOYxMKdApmVZ/mE98PdzglGHMK+dVNoHnOKG1MHWd9fSmkeTbdebGScfvnDJLymhVaI2oRxKJX25eIWFL4lFNuRAquDrFWZJ1jSakWnuhC7n24974noTIQJcc62BDAFYMiezlprzzIn3U1fBqlOFxOcngThViKdgYuGk6nuZJJtlK0xrHkhIxFaYig7QlybmUgI1tpHJs2NNay9MCD9NRUlOLVBeELP7PnWuEWcwS2tNZf01XjynTOgepcNNI0rp3ntsiveJrzhzjzNt+Q2c8c57594/v2bmWm7blrh94d3omljoYMo41BAkLKRmlFbdNL1LnFCs4qtJM46qnuFQ/dMFqRcyF87qSS+G78Sj+QqMxymOVQWeFsuKBLKkQU+FhOvHN7pac5XEDmZThYZ1xRktoUc5Ybdg6z1rtII2x3PiOqWl40+5QiBTcIKx4LpnOSJ0JFpqm5ZwWxhjrcNCw8y2ddhI2lAshRU5RqphO61xzGqzUAgXJn2is4Webe6zWnNaJ9/OJOUZyLmitiSERlTAZjZPhj3ROy4C40ZZzWJlWYd3XkmmNZ84ray40WpQTc15q2JJcR5wSRcaFM3IVoP4hxqq3LY01PMcRpx0lJ6wS0FWhdu0nXa8slAAI8cutMbGxrWQYhMB92/FuOZCzbKRTKfSlOlVLYS2JmJYrU2OV9HiGItvoRECkyOkawiSsY0HpjElytfS2oRRpKohk1rLQ5ZYxzMQYeZjPzC9cmSlcAJNhCRFvLCVIF2gm1SGUbK8lvTXgdBYve71ObG0nIX7LzFLlpYUggU/12nBeF1rruO06frl7hVIwhpVvS+I8HvGmlcC9dWQpmbZYrJOQMaOkRzhj0UWu/w/rJD5236KzdIumnDFKgnB8hSnOGnKUEKCLvHOpn/rL+hmFqoFi8vexgtSESGYvK5LI+TPQV/XIlMouGvTnerSir6yjqTsDiyESqwc8/8nA5XJ+LS9YzMu5e/HQ5he/e5GlvwRHF1Dj6s/nK1v9z6/LY/9Y4vwvsVw9/hpFi8EpLUnpVSYsSd8CLi/MZuYzo3uR817+mfg8WHj5uwE5hiOFEiakdElCrxplUGLQrzL7FVTtHS4irbfK0hhJEp6v35DP38sff64/sBCUz0qEn1oXFcilW/pPYcgvz3v53B1SZ3dMExO/3+UbgCVHdFKsRtPiGaz78cP+d7/+Cmz/DEuYxjs2TtJ+Q050SW78pyBT9UZbjkqxbVredlvGJL2jFKlo2fmOXQPHsLD3Hc5Y2lJ4nCdSltPTaYOtkiHl4Mt+TymSoncKM7kUdr7l03Tm0yQhJI323Dc98/UGLTHfn+YTW9dyWGe+GvYsKRJrL1tjWowS/8776cgpLJU9EDC4xMioNHMMVZ4Kr7otU1wpSnFaZ7Q2fDcdKGRMq9kCvzk+8Lrb4FCMaeX76cTbbsO6rGgtFQtGKZaYUCrQWcemGttTLZyz2vL15oZP85k1JaYkkrFtZQWOYeE5ziitmELAGPHXdtZWYLThdbvhV2Gm0b4WyGee0iiyMaV4W9OYj2HmtpF6m+/jEas1W9OSrGwgUhZZ5PM6iuRKSypfMplcoDOOx/UsjLVtBBxpriFjushGXympOzquEoPwRbsjq8IYFlKy2Arq/h9vfslSGf/fnp74NJ/4OJ0JWWSeg2vorOKm6RlDxNZu5d56lhTlOcIoXmFleDvsKCie55Fck5hfNwMoTWeECTuHhaWyOyCF88cw89vDA7tWlAqpMlVLirQ1FZlS+N30RMiRvW3pbMP76cQvt/cc1pmiCl4bvuy3fFpGHuczWinWFOmssKlzjMwp8LrZCANuHG/6Dfuml+qZdcEbOXZGafF3afGcnuPKYZl4Wk8c5oXBe+6aDVaLXG7XtOx9z8f5RCmFxjiM1tfP/98/fsdhnemteJwbazmGGW8dOhpiWdFK/N0xJbIq9NXT1honoEJJL6ipYsjbdgCd+dnmhn3TE3LisC7MccUoxc61EpqWEt9PB2FzcpbvpcokNE/rxHldiSkRUuS4LgzuC36xueUYJB39xvWc4sJzOGOUlLF31vFhPPGOI18NO365fcU/Hj/SWEObpQMbZIMx5pVYClvjKRV4KV2kzJ7Cxm94XicJYSmFouC4CKDqLdz7ARr47nxgTrIx10qGHXvfUxB58zHOvGq2eCsDhUZbPsYj3khFijGGXBRv+i0gn4tGc1oXliTfFbFkrOgKPigixf6y3/NxPnEME2sK7HzHUj2cS0w4K5/NpzAzaEdnxZIxpYUb5ySQqKpfnJHu1p3vWaYDvWlYiwS4LSmwlEiDY7ANqJpGri2WXIPCFG/6AV00z2FmScLM3viWRGFcA60NOKVJpTCmFYPFa8NN27EEsUIcwix+v5LJudCbBmPlb77qd/zm9MhxWUBlzusqPr3KkCmlaZTheV1E7eB6Ous4LBMay13TcgqRw7rwvMy86ns0hsMysTEtjU7kUlhy4nldSKVwmzu8k2umLuKRG8PKQzyLGslonHGEMhNK4TmMvOm3WGO5bwcO68yiIjEktBZnp7WaUqvjWmPxtVfZ1ulALGL3WZPkPdz4gdM6MSWROd+zYcqRkhKKjMoiydy7VoC7KoQ1XENkXi6FPIdVhvthh6HwbjzSWS+qrGXiuJ5ZkECli19RNv8ixafAXAKDalCq1Eo8xeBaokrEEPDO87SMpOr1FOmwZmua6zWoU6KASCmTX2yHXwbhxFhwWpFRhCw2CKcNW9uwpkzKItc9lpml+jovclVFwbuWNUgF1VqVNKWC/ovH0SBdtwFRle2UpLSvJO6sY0kZynSV4QpgzKgsLuEGz43vSEnuZ2tKHMJMiJm7dotSMCdxEptcsFbjqoJpCYFU4jUtfcmROSzkHGVfpTToIlaQnGq2bqZVMuC1KJx2nHOiIddamx8mF2+VZKJE0hXIvpTMvgR1P440UhUEZ+CN3+KMwKwP0wlHZlCeXdej0ISYeFifr8Dlj62fYu1+ChS9DCm6MHaX53jJGiokPPGzm/SHYUqXx79AHGEZDekFePvx8/7X+m0vrw3kvBU2tWCVkCylxCso5cXrfOlFffnaLgBe6rAylxC4z15b8SXr6u2ViiBNRvy7qmSO9bz3QFFaLHqo2ncvne6xyolfvv8/xGq/HH6JkuCi0vi8Lp/D5bP8U4cIFvluClOfJQCNwJp+6OF+2WUMyGAvFZpkuW8GXnXbP/EZ//tZfwW2f4a1psipdrZdQpiE1Yk0uvA4jywpcIwLf7O5rxUuE04pBmd5mEdygRvfURDpb2clJOH/+/Q9MRf2bcdgPc91M1/IOG357vwMSjadGy+yyP2+4znMPKwj9+2Gn2/vmZJMu8YUOIeVne/lhK9M3uAkpGrvJZRHvHUTS4pXH+w5rnVjKFLjfzvsaI0wwhfGdAwLX3Q3jHEmlkxKGV00H+cjqWS8Eg/Rl90NOReRQNWLjTOajW+xpk6za3/nxjU8zGdOYSGXzBQivW34epB6k//w9E7SNHOWoCdjSbZhzonBaOYcsMZI5YxxHNaJjW0pCl41W3JJjCGRysq/vf2CjW85xQWC4tN85NN0Zus9WmlSLuxdz57MmjNaKQ7rJFNz3bDzLa21FDpSTjhlaYxm8J6EAIDGOkwWj+uUAt84z2ERue2HMPHKGAZr+ThNfL8882/vv+K2lfQ6pw2/PT+x5sgcAxvXcFwzU4qsJXHjOtYkftV9I5/lrw+fqkRUbvRbLyEcU1hwxuKUYo6BW9+QrQDUwzozpYWUJRmzsz03Tc/rdstvpyeSkuCXULJIZNst47qyGvFQv+4HfDCsJfBuPvJVpxkqAE1FGOindeK23XDTbviV+sgpzJxjpHeOt/0dhzDXegzHUhb2TcPgxA9mtOZ1JymVl8/203JiCgtryjzHSSo0UBzjXKtNCrumxxvDsfqdn+aRzjk2rsUpU+ulBPze+J7OOT7Np8q2JD4tqwRcYIlKs+8GXjcbSd6Omd+ujzzME611rDkhmVSFxniR12vDEsV/fg4rp7AwxUWGCdbId0lBzNK767Ri56R26FIB9GkZsUpSzHMpfJif2PrX3PhBlCI5c0gzG9eRchEPYioseeXTPFHINNpIDQWIRFBLENp354MMRmJEa7mRByXfxW+GO76bDtw6z+tu4N104HE+0xnHzrfcNQNjEp/z23YnPvdZ/OqndcZby8Z7EoXjOkvwlipyHmLprcNpDVmBFq/t/WZDZx3fnQ802vDr8yOtqaMCXfh4HumNYymBWAHfnCPHsPA/3fxMQmJq6vZ9t+XWD5zjzKflwBoLg7MsMTHnkVaLx/N5GQkUXjcbvHUYI9Lxt/2ed+MzSokPs/NyXFWRjAVrpGfVKC3hYqajNxZvHXfNlg/Lid6J8kQVOKwLN02HN6LQWFLAVgXMUqXOS8w8LSODamgwpJKYU8Zrya2FwnM48bQqHqYzc1jQVuTJicySAqtK/M3mFacwUZCU1Tfdnvfzkd46SbqOwkV93e/EW54kPO8CQr8dn7FGmPXncObDNJNS4pXa8rROwugXATOnNNMqAaRjWphzRJN4VjJ0e14mdB2cSjiLpEUnLr2tWQY3GnKSwQk60yJy45ASvXG1kkmsBjdFMeZIUIlLAsGcA6dVaraU1tw3HWMKlAxTPP/efdwCn+YjxQ0SemQcd80gSokQUUWGVbnINZGqLGmxmCr1nlOUgJqU6JoBi6rWlMi2afgUVs7LSKFI1YZStMpx02x43Q68nw+ELOofbRQ+W45luW58LxviRnmSEqDW1bq+VBKmiNz/8vrW8rlK5eIhNcCJQB8KmcRxnWswlGOq8GClVHmm8FdOWWxRHNNKZzytsnwaj2JVABo8kc+9rpmEwcigAsky+PZ8IJOrN7owxhmjDVZZLJqoNKFkwpqktionWmuYw0yo+tqmBglOZUGRaa0nY+h8Sw6KlCO5Dvu10bSmo0FC51wutRdXaoY8olAI1ad6AUuXrlbxUMu6MH4vAcmFQW8wjGnhjZcqN28sYx3o3TcDGsW7+IxTDaUsfxK4vbCxF5DzU3U8cEkEfgnezDXJ97IuIu2lxib1WE4V4qoXf39hoi2WXmnmEq4e1cvvXOTPDqnbedlHfElXfrleemt/KvlX3qdiynOVW6t6Lpfr6/vx+kM/t1z8rJ/95p/7nz/35V685RbFYFtRsJE41+NzOSZTWRhUQ8iFwYtFrxK6V4n6Zf0Y1LYv3ptEXcH04uc/fj+Xf/7ncKcJmEjX92ZfWgf47Ne9DAJeStQd0NqWv7t5zW3T/2c8638f66/A9l94rUlkPgUJj/kwnTiEmS/6Ha/6jYCeqNjqjlfdBqctvxkfMUif6xSFmfRGvIRKKXrjGdNKrw2tbVjTypzEl/XV0KFK4fvpwCnMfDnspPeyJGIpfDnsWFJk41pSKdy1PTFndr7j++nIcZmxWtNZz8N8lgkxmm+XJ2KR6qG9a6XqRYtnGJAKIyttYV5bdo3DasPzOtXqFPg0n+iME/Y1G77o99gadPC0CtA4xoWvNzd1Qhf5MJ941Q0YJV+64zqzdY30ShYJffLGctcOPFdZqDNy7Jw2UhPUbPju/IzWmp1r+Jvtax7dxO/GRzQKikGVhDUSTvO8Tnw93LDxLeewcFgDVksXqjeW0zrzj88feZhPnNLKrevpjefDdCYSRWqoHR2S6LjmxKt2y65tpWsTaI1h3/ZA4fvpiedlpeQsvZYliVzcaO78wKd5ZMorW9vyut3ysJz4uMi26a7b1JoSxcN8BgWv2gGjpDpAK1UTg5eaKh3w2vK637KxDQ+LVLqoorBaapE6a8iVnTdKs+s2HNalSlonYs6kLMnQY1ir705kzXMI9MbilOFhFe+nRfF+PKCMZkDAd8oiHeqMDFtQkEviHIWxWnPi43yitw6vBdBZY/iq3wmgree7q9VBXw/7axjVZeNbSiGUTK+9yL3XhTWJQiJl8Xm97vc4rXhaJ9YKKKY18C4daJRn6xpSgX94/kSjRX48RtlYOaX4crjFoJmzyGOlhiuijGbrDF6ZmlK+8LPBY9E01hCLyKwvwPbjeGJNkdum4zfHR+YYuWk7UCJ/a7XFavG8rClCybTG8tWwF//RdOa35ydJB8+JoOBplZCvUjLfjUf+b69+xpQi301HlhiqR7+gVMEb6Yjeek/KmYe00GuPNwIkGpvZ6i2nRSSxvXV0xtL5hvMqMl6tFF8Pe258h9Wa78cjb7s9g5OhT+tEOntOC+/nQwXMMiiZU2Zjdd0Ea7TraY0hqULJIj1U1YKQ69S+IJ7PVAr3bc9vz094I7LoQ1iwiBpjyoG1RHRRGG0oKbOGwCFKn/Qvdvc4rUWOmcSrd99s+U/L93XDXNjZjphSFaYpBit1CHMKYhWJUcLHlHgGd76t5faBEwL8lxTxxTBlSUy2SiS5l+7mV2xQqvC0TrRWJOK/DiMGSd3c2YasJEDlYT5Rcr3+OcvTNBJzqqoMT6HwYXoWViIrYdlS5KbpUUpxVgtOW1IIpCThPrlkeutx1mC1YmM9a5aO5zf9vnoNpRJiZzuk19fz/Xxg0zRYZXhaJxlIEPjd9MwxrbTWolfpFB98wzEI4x+LhObYquY4h4U5BjpreT+f2bmGRUVUKjUFv0gCs67d4mvCmxoSlaX+zhsJ19o3LUZZrFWkBL2zvLaeVktn6D8cP3KeRS7c0TDGmXEVxUUm/mAjegEymks1i0Ypw5ISjbM4FA/LgVwEjBqlMaql5MQZSRrNBdqkcMpjVe3cdoac4HU3MKaEU0o6wtf5qubQBrx17JqGqDK7puO0LCit+TQdhbWOhvFHzFkqGV0goQlBhiCFTGsNMVOzC2QAsxJ/sBG8hAdNRHosobapagT0xMrIggDoUBKqXHpuNW+HLVMIfJxP6FSw2lKswkbxsV6Sbr0y5JQ4hoXX3YY5rihl6K1hVZGU4bycWaJsuQuFkiRocWNaVAXAa5aE9t43hJRq2Jb4Z3VMWFdDxLThlMtVfJxSRJWJxnlU9QiboukVFCQtOGVQRWDABcz6F+/hjy2Rtkpg4cNiGLNIsd+0PXOSPaHWhmNYoTKQL4EGCGt5YdheAsH4o3//8br00L78704bXDEcX1TmXCLD4BKuFa8S3QuAvoBoj6c1jpCkWbev0v0LA3xhFUsdq13A6k+BWvjjflTxBpcqINdVKZB+ILn+Q393WS8HEZe+gcvrvQBgee2irLkoC0QRlWiM5pzkmnDp6b10eq9ZYLCOK6WqgWSs+s+z1jMCYsvVTPM5UOqPrT+1+uelr9qjGPns0YXPw5CXAFeS4xW3fuCu6fjX+7d485cHE//yXvFf2DoFCfQ+rtLhabUAuXe1FuUYJlptpbKl6TAIY2UvsrMYuPUth2ViTIF90zIY0clPVe4aS4JUWFVCK8XGNfxyd09rPAW46wY6I4mDl3Cp785PcnPTWipcUmTvW07rTMzS7rVvO5YYeZhPTDFKOnPO/Pb0RCbzZXeDU5pjWDiXTGMsMRd2TSvdsvMo4SU1UOpxOfM/7L+oss2JTkl/4OM844wRCV8Wb99hPfO70yNTWrnNPVqD1ZL+eGFpda0yAZF7v+625AK9tbUsXWRM3hiUVtw1HU4Zphi463ru2p7vzs8sOZByZs1Sy9EZc/Virlcvj4Rn/S8ff8sxzBzXsXa5BpYY+Nrc4q0hrJE5rQxaQlb2vmPj2ho+JbUUVkkImKkbnNftjp2LvJ8OvB+PZCUsWWc875cDr9tBzoG4QKJ2rip67RlsI53A7YDVmk/zmTedSDNvG2Hy9k2HqgxeAX6xv+euBiv11rP1HYdFpLtaKXINDuiM41W34cN04qbtsEpJiAeWwQ8SpKXAKCuAYC18HI/1s6msWSl0xrPqiNeOOa3sau1HTgplCr1x9bgYvj8f2PiW355OtRIjopSpScqIJBRRAJzCwpf9Dmssf7d/I0MNLZ9vyIlQvVatcWxsw+oS72PEG8+ApkgwsHg1S/WQp5XnVQDPqcy0dmBKK6d15BmkOxUYdCuBXuuJQTcUBa21OLPleR4lnAkZBFEKyks/qtfy74NrpEJIw6dxJKvM1rfc+g3PceJ350emGGoPsoCIC8hQSnPrN7zutkQKrXZ1QENVR4DSl67dzIfxzH2veJhHCvC4TjijWNZALiLX3bnMWSt0UbyfDoScOGrLl8OewyoS5pQLXw17ntdZGLWS6YxBOYerIO3rzS1TXFEoeitSUVC0xpKyKBCOYaGvAWpzilit+GqQzujHZcIpzdY6Wm2JJfE0n3hcVzal4WfDLWtJzHHhcZl5mM5sXEtvGoo6QYZfHx9QSsKRtFb0yrFRXqb8KbNo2fpOcUFT+DQfxWO9TjgjEMYozZf9De/nE0tWtYfbMLOyhLoVq4Fjz+vI3+xecai+fq0CG9cSk4g2jTbc+JbeeB6WM4WEQbzPU4ic7cp4/MjPN/dYo/mi3xFK5mEeWVPkxjuWGPnVIsnA5zWgtQR8eKNxeEKMdcOVmVLAa+mPfZrOeOPojGE2kjg7RhGdOjRJW0qS7a81lr3vSUmkvoP1DKrhptlw48XTvKTAHKUGrjGGoDKnMOOVFeCByOM77TmUhfM6cViyKD+0pM1rCg/LJAn89Xu/azso8GE60RmPKmC0Zg0SwrPmRKPlemKc4UZJjNEUA1pLonzMCWVgShGCVM/YLIOORjuWsNL4jqcw82kZiUU2p1qyoEglUUKm9x0Ny1Vqu3BhrCRrYi2RFitpz0Xz3fQsAWVNL13TQYLE4gsPKkjAkC6RkA13XYNGs28atDbcN4aPyxlrLU12qCKQxWpJUP/d6YltI+dUiDVUUNtr2F7D5zRZAyLzRrMWuW7IdR2OcaU3IkhtK3MoAPjzesmy7arKgoKE+Gl3DVpLSAfyWgqZgtfSX+6MJRbF1vecl5lEoVWOsYLFC/Mk4Y5SaaKB07rQWE+qQ9Wn+cxc2bNONyy1uiqUzPMy4q0M9nPIBOT+fOkO/8wkSudvTpmcxctNqZVoSTI1GiyNMxhl0Vok32NeiCkz50jKiiklCrHKtfPvMaT/XFLt5/crHu7e1QC0bsNpXXheJwqf66J+DPQWLsyvhADOJTDXZ788709JkzM/BEEFyNV28FOM5gUkX5i7CyMvFVOGQsQpxbZpmKNCBQF4HVLltqSVmcp0IwNKi2GsncU/tV4C258Ca5f3BqLeuAyd/jkv6svlgL3tpAYsx8r5SmWVRYLMLuBfQGB4wSAbSs6MZLGGISFdVpmaIhwZyRgyqohVJZCujPgfk2LP9R2KGkKA/08dJ3d976myrbpKi/+0JcMVOcqXz/fHr+2SDG0xdLbhm909v6gBlX+J66/A9l94hZw4rgvnKDO3KQVKrh4ha683sHNcuGkHbpuec1yYQuB1vyWXzNM60xjDq3ZDKYVfHR8qI6nZekdeZROPKpyDXB6+6PfcNj1jXDmsE78aP9IZx+BaOuvoTMM3mwGtFN+PB/ZNR2c9r7qNSKCAh2WkMebqZe2c43mZ6Jyr70XYrzUH6UX1EjA0R/FoDjWdGWodjG35OJ/ZeM9hXdBASIXGGV41G34dHwgp8mE8cAgzpyAS1kOYsEh3qDOaJSa2vkUpmZB9P4rf8AKez8Fw0/RoJRULKMXed8wxcipya/qFu+OrzQ2tdTwvI78bn7DKSKdqTvyvD9/ys80tIWacESYzlcR35yOd8aQiXZXeGHKBb0/PvO0l0OkUVgbbcFgn3o0HMpI2+6bbyiAiy7wvl0zIRaTgceX9fGTXDMxJ0qyhoIrmsC4MXYvFUupGYM6Jxotk9sJ0fDXsOVbW+uN0opDZe/HK/Xx3x13To5Xmrh3k3FxGCTVyLQ/zGac0r5tNPYaB3jQ02vFld8PbYcvDfCaUwt9udzhr+TiduE0dD8uZ786Hz4+bEw/rSRJNw0k2RVrz9dCSi3QzlpyFmU4Fry0b23IOK0uO3GrD63bDKSx8mk9Yo/mquxHWmcyrbkvOcvsdfFerfEQGfwG0G9/yvIwYJf7jkCQ0602/JRUZAOWcWbL43J2S1PDndWGKgTfthqVEHtaR4zJL+mJYCdbQGUNjNVOU3uJEptdNDZYKUnkBvGl39NbxaR6rL15YwSmtzDW12mlJJmxtzSs0mq/8Le/HJ/7x9J4vu1taZ1ljZk0S7mOV4VXXs/MdoDjFicF5ts7ztJ6FQYmFoLP0vVbWNZGlH9I3HOMiyaX1u35IK31ueYxTBRHCDp+DfF+8VqA0t75HaUngDCnR6obGO5xxvGoGNrW72ijNrd+yFOmM1Sge15FTrfgac+Q5TjTaMSAdn6EkbpqeW9ezb3uRBE9nQBNy4MZ3NNYR18xplbqnJQVaa3mYT6iiyEoGRq1zzCGKNy4EWu3IBaISb2FjRYYfVeEUpJR+65oaOiaWhq1v6V0jQVU58DSPrDlx42pnYSl0yqBMy8M8sSZhPJOTgcaiYt21iYfuWCbx05uOTduysa1sILViipFzXHjttux8z394/J5WOxoj3bLfTk8YZVhDQFupXWu15XW34xhmohOwmXJhLgud3zCFFV27UJuqlHHGkmvvpVZSB9L7GkKlEDmxbjAK3g47fnV4kG7VlEBlUBLENVbrysbLNeIUJs4hkEuiMw2jSmycZ8lSexLLirZwWkUeavRUvwOFhUDB01kvnuS0EtYqD1W2KkdkWLPxvmoii3ibTcfTIr5yZxSlCPg9zBNaGzbZYZWWJH8DXWn4MB+YlpWZtYJVkWavFbCYHNjbXl5f3fJeAuuMMhiUAEyVWGOWmiJEdSQbZ13TWzMNpqYZaxolCfCxJOknD4GYZTv9ptuxcS13zXoF+1bD8zLzFE9AoUySwp1I2CQ5vxdp8Et/IQg7v6Cq/NLQ2/q8UQCdQnOI83UD/lOb8AX4tBzwWIxWWO2YUpA0dBKBgs35c+BWVrRahvBTCrTaY9uOJQdEmiL9sxewlKrqxBsB9dpodl6UTyhFo91V7dVYi06SkDznhUSiRNBFvrsZYfRzLFVa/Tk4Zwkra/0MXLGSVFwyGotTmpyk7iSWVUCfg955HuMZjQzHdQXkl4Chi1/1wsr92FP5colM2bDEyGBl0GDQvB+fOa/yvb/xHR+X4w88sfAZmFoUrbOEVNBFY+u52uEYfy/HW9YlAOtlM3qiYIqAOlWB9MuwpQtDq+pnlevZZbTGl5bbTvaos3UkX0TlEgMpZRwORSYgKdRWGZxxbLPmIf9Uu+s/Hz51+fmlrzbXnOgLs/jHgGODhCWNcb0GwpX6vuCHYVGX13IZiIgcPNVn/FxxlcjXwcjL9OVYBNA2WGwV/S5/Eqf/mTG9yIxfgk/FpfpIXvUGRxYNAPxngNuXr+Ry3F4yyhep+M61bJseoyQ743mdrvu6v6T1V2D7L7xEEnZkcOKha43j3fm5bsLztROyq5PKU7gwu5VhKwN170nIicf1zLhK7U7OCqMEBITK8l58ehcJ9PvpSGMcb9odj+uZXx0/8nc3b/my31/ZThRVAibSw29PT5+7a40l5MKuba6vodUWlJKOxlzY+44lRR5qTcrWtzzO0utZapdiLJmvNzf8b0/vsGrPxnh+Nz6RSuHvhjcCOroNj/PIOa301nPfDbTasZbM83ImZblhbX3DXSuhTaXIl+/jdKq+yg3fjwf+4fCRrWs4rVKHMRjHqgxOSwXRb8+PaKX5OB35fjzQu0aOaZELf6Hwu+MTr9qBqTIVXgsrcYqTdDmWzBgDSxKG8C527Joeo6Qs/d3pyI3veNUOrDnzfjxy30kyb2OsTGov6anW8XV/w9Ny5jkIYPdGXnfS0lF603R8mE/EGvR1WBaMVXzd3YAqfDs+8TTLZzClhdO68nE68+Vmj1aKyTje9rvruemqxNdozRfdjg/ziXOYaa1n60Ux4LXhth+4awc2rpUAp5wZ15FTkKomVWuMOuvY2o6sxM/1aT1h6jnWVrbqxnUCppsNr9sdz3HisIw4qwmh8LbbYbV8Tp1zbJ3n3XgEJKG5ta6mU8pmZokrXwz7KnU/82E+8rrd8brdVJ/WKlVMOTDYBqcVvzsfeF5ncoqyaVH6Ci6MgdYafnN+YGM71hJ5XmdSihStaLRsnh/nsQID6Xy9bVqUhn+9f8Pbbs8/Hj7KZrrKezOFNSbmJEzXOYRalSV1UXvV0BknLH7tBk1VJtwqR1QLWSm+7Lbctht6KynBToFTUvXROi+BZ2FEaYUpQP2OWGVqDU9ird7ir4dbznHhw3hiDYHcyia/81I/9Kbb0WqRmoLirhGp9c83d3w/CkuVS+G+2xJL4nmdOcSZVjv2TcfrYeDdKfE0T0ypJkcDrRP2djAOrTS98yQyIWSSLnyfnjlH6R6+bXo2XsJ0jNIcFpGUJwRACfg2PM6jfF9sI75EY5lCgKLxuhG2Oyas1uybnt57CbxbJ4oRsNVZXwOsZMhilJaNfEmsKQkjrx1rqbaAbuDDciKuC61p+Kq/IZbI8zrx7nRg6xtMlq7bKc2UJNsj7x2JXFURlnMMeGsqEyHA+hAmjEKsKacHchbG4KwSPnmWGDmkWjGkNUpLLVggk5IhF2FmLp26D9Mo94UsUv2cM04ZGut51Q2UIv3Sg2nZNVJjEXKhtZY1wSHOaAqD6XhaZ5YsoW1LiHTWMgdDzMKatlqu9711bJ3lUSmsVrVyZ2VjDLfthlOYsdj6HRVZpoA+aIxiiZGsC411vB62aBRryigl98uI9AYbBVvXsCAp171rOC4TY5jqdXZmcA0Kzf/70+94mkcmwgumKLOUXDdDEnrY2+bKgLeqoahSA98saM2UF1rtKaqglZaQJlUoWTaIoTJLTlsG4yEXeV/O8arZoIoilsRhWjG177i3jod1RBfFvm14mkfer8cr2HjZljsS8JgfsFweAYy+hvoYNJlEoyxrkmqitYIOV9mqy9/NP9q3SIXRZTMvA9ZQMjml+hgWTcYYTUoZj6GgeFwn8cqblki+1vesMdbXlQUoo1iIqKRQ1eKx8S0P80hKCbQiqHRlC9csdWSxfGZLey29zaUoLI5MYqqMm60bm4sfUlYmlUjOAhQUGpSiqEKsbQGQpbFgnmiMoSiF1bayyJ/lxy/9iB7xLf+xUJ9QZJCag/iDUZIVAoolBwbTMKalynbzZWuGR7pzS81p8bhrEnCs/t+X6yWbaVC0lYlekwz6NIpeeZby+d+pbLqEIOUr2LowtzEXnBErwlyChI+RMNrwdtMypcR5nqpnW4C4UopQMt6YK4J6KdG9DGP2tJwqB/3yfP7x8XwZZPWHIOPlNV/8tKfab3z5u/UFB/nyMTyfZbuXgYhCIzz9D8Hg+uKIX35/rYyuxdJYw5wL5D8ObC+A1inHWgItElI55uWqFIHPQHcksFGeXMwPPvl/TpL+4/d6WZe/7hBLgdWW224g58LjMrGxDb85PvD1cPMXJ0f+y3q1f4FLobBVAgxgtaZ3DSlFkcAp+TLsfMPTMnGvDF5Zdn3Lx/nE0zKiCsw1+XhjG259zymubKwWj6GCN+1WElNrYFFjLP/+8Tu2tkMpkemAdKktMXwGtYgndk4y8f/2LF7aJYl8aYwrfY37jvlSZRKZ8sre9RSVWJNMrb+5vWNjG2LOfCyZD/Opvn9Fbz3HdWFnJXhpznIJe9X0knRrHHfNhrt24NvTgTfdIGmq60xTQ6t62/KL7R137ed+0uO6MMX1Cko/zqer/BQkYGOOifuup9eK4zrztMwc1on7ZkPIWQIpUiJZkX6ZrIgJjC4YbeityCbPQeSPKSfuuy1eO56SgLtS5XW99/xf7n/OwzKydz2tla9YgwDJTL4y6eewEHMh5IUUClMW8LyrCZ2+yl6Py0RW0o25byTMwCnDh+nEvR34uJ6kgzQGGu14n6RrdN90zGnlME982d9Izc+LC9TGNbwbnznXY+iMJi6FTSPhH42VQCuRlmW8sXSu4XenpzqkEYAypsDrbsvf3khdTC6F//DwjkThrumxSldAmgk58zf9zVU2/aoZ+Fl/g9WG9xzZeZFPPy0TIDf+m6aXapAYOS6TdAgqLYMGBY/LyGGZCTlWed7Kh1k8jblkntfAm3bHKS48LlNNgnYccqRxVm4u2lHUyt72FOA3p0dCSZQs6dRBSYq1xqAUfFzOeOW47wx7L2qHmAq/Oz/xi+09d90GGe5mAXxhlgCUnIn1DnTX9iwxSZJxjvV7JqFsT0ECpqYUabXltu1oo2NwnrtWapzOYalA2fG234vcMia0LowhCDON474ZaLThHBee17NI8auiwRlLLpBS5tvzgdYYbq2wZIcwEYyEkC0KbpqevloavHb0TSubyTATC7zutkCRju280hsJgpLqExnC7SozW0rEGyfqgLhWaTa8ae+QwCMBsL+wd+z9wI3veXeWGp2sYWs61pR4DmLRaGt66WA8x7wyRunC9tqg0GjrWI1YB0JK5AwUjSnCgHfW01jLp/nMw3JmCiKRvm17UgKnNE9hQpvEVkmQ2G/Pz6AyXwx7CS2zmiVAbzzKK0KJaKPY+oafWUkY/zSfGePCcZyZV+khv2k73nbiYf3d+RHq9TfkJGqEdaWxMlTbmK76vgxjWDgF2WY5JVL0zjlJxidjS6FzjvOyohW1M92zhIDEXxU6a3FGPO+3vsdqTSmKfzo+iFcfCZJ7Hw58muTcMUbRuQYfZgbr6G3D2Qb+VfOK3x4/Ya1GZUm/n4wMqbwytKYhGvEt6gooSsl4rShF1EzSwS6D2c7L4I1SsMoSqsS6s9WjnyNbJ/75TKZRllBkoHvKCwpqNZmAxCUFpjjXRNTP6xLWc9lkRhIhCgPjtcUqRUgiBEw5MC9BQl90BVVaEp9jlGFIQhyGG9PQ2oYlLRJMqA1eWyiiIBqTJMqvKWA1TFGSjLUSkP9xlgCry0Z7LZKgvCBdq9OPtqsr0KOI11eQMRjWkqDIkN2hcVga5zBBgPJMYkAzvZBQ+gqPzAUAl4ItDa1r0DFUFRNQ5DGcNhRVAUHRdNbyHBc6a2uqvOEcoMGBEgBOEGuLAe7aDTlnPoVVhq1ZYY2pEt1UfbYC6y/A9aJCcbXVIOTqda+/01YOTOqJDHsrlWRBZXQSFYOAbslM0ErjrMWkwBQiq5LX0WjDnIUHbuqw4yVLW/gxtPz95ZRmLYmPywGD2Br2zUAskaZYxjihir4+3iW9WFLzS5WpyjMtrBgEzCyU3wM1F2Cr6+eXS2brBnorHO4cgoSxRQH3axW5CjuYa3hQrXTjswx2TJm0ZE6rwWAIRaw+qRTOy1zVcJeApkzIkrxOlj2HBTrliCXVui1Z2cAmN2BERRD4aYj2MsTqxx7a/OJ3HNDSMLH8UcDHjx4v8DmJWbzOP/zrH3/S4rttWAm1G3khRMNPF4b9/pIBglwjY5KhQinwY377UlVUgMY1LOt4PQcuO/k/lb398VoRcBtT5NvTgZumY28cp3UBpfh+OvDN5u6/8NH/j1l/BbZ/hvWm2/CrwwNJJVrtaJXhfR755eY1vbWMMfKb0yOv2o2wDrXCRqa4HoWiR6qCtq5FKSm7711DyYWH5UTKmcM6MafIfbuhtxopYpfpi9eWu6bnqGY+zmd+mdMV3HbWcY4L/3R4wFXAcvHqem349vzE96PIZGJOnOIi9UO+4Xld0Bq+GG5IpcgNvkiK8SksDMbzHFbp9UqRkgtKi/TqxveMSXppbxoJH3peJkxNUnTasPUt53VBAiIVd+0gFRXLyBxlc3YIc904CxDvjON1t2HNiX3T85+e3zPFWXxvOYOCr/rbmr4og4BEqqy1uwYV2UsPZ85McQVV2LuGh3XkaR259ocUxX234bbZCFjJkWOYSCnzbpLLTWcE2H2cT5gaetFoy/twwGtLbxw70/GP4wdufM/bfss5LTzOE686SURdS2avG257kel6rSvIlfqdh3Bi1YHWe3a+RcJdJPhpDMKA3TXDD8CtQtFZRy6JT+eRxolcziiRMH497Gmsq3JiJeBOKZaafhmUDCW8VpzXhc4K8621Yu97BusxSsmkXllmVu7rZ3jT9DwtI8/LJLUXCr4dn0hZLveN0awpY7WE9EDBG8fGSFDRMcw8TxM5Z151G+ZcmPNKTkUqr5TcnMcwYZUmlsQ5rGx9Q6slcGznxH8zxsB5nUELyPvl7h5K4WE905WGO+srg7cwhpWUM6037FxD60Sa7o2wPUuKfD3c8OvDR749P/OqG/jK7fl+OpCSBGHsmw5VQFsBu0rDw3xm51tOMaDRkpipDXMO+GIoJfO78xNeNxQSgxX58882NxzWmZ1v2DcNU2zY2I5CIpWCViIZXWrNzFMY+ZBO0h3cy9Bg4zxJ5Wvf9RoCxlr2ruO+7TjEhY/zkTUn5rDS2oY3vVR4jWGhVQLk6knFx/mMVzOxRAElOVa2P7JWwPa8jlglaceqKJ7XmW82mldtTxolhOthmtj7HqNNZQEb1iQ9u61zXMpOjFGkJAmzm1I4xixM6RrofCOsYpZB2BoirbV8s71hjRmlC3fNwHfjM5S6WTDS4XtYJhazsvcD3wyvQIlC5Gkd6Wq/ttUyjDyu81U187rb8BxmeiM2E+2MMJQaxnVFGwm9MVozRmFvQinsXcv38xF9yQioFRchi3zSFE3Wco299T1FKUJascbhvWUJmcF1NcQEHscJ7xyaQtEw+Jb/ebjhw/TM4zzLub8GbpqWOSXm5UgeJdLkOYwIgxn5fjyxVNChjWEMK6aA1htuteVVu+Ftt2HjWt5NjxxzAKXxyrLmhPNalD6+JaTE3ncoFMcgkuEC5LRKjoQ27BphWJ+WCWsMqhQa7VhLImRojMYWW9O/e0oRKfgaInPtkE3Ac5pIOV/DjYT9NBWe/HjbKgE1Tkn4lima3hjOIRIpeGVxWjEl8WhTJbA6WZbK56micEjt3o3vmbJUMzlrCUnilShSjbck8Sy2vpP7Ti4Emwg58rBMkAstmqWyQU4ZdIGRPxweM/O5ZkhYRGESGy5eT4uTWgGy0ixFZLFWaVzJVxnvpVs1I40KjRb+t9EW4xoKmRwipyJJ2rk4vJLf81YzZrFz5FLwOqGUSKdtlcZD4b7TPK8zXmms0ZxylPCu2oPd+4aUCnNcOSexRBikHs1rA0qhkmQJGG3RqnCnZOg9EwnIUFBV1QSqoIpCJYGMa4qslRds8bKvMQpvPApNYy3nuDKGgFUKX2w9PoZCwCMZIQvCWLckVn4f/FhgqYngwvglTJZkdINUw81FfKgXie1FbktlDOtltf5E6mcShfnFOXwJSLokNBsUjXIYK13Vg22qhSLXSkEBsi+l6BfGU5h/hzYKpTTHek9CQcpJFAm5cFwLug4gHOb6rbrIehUZVSLtxSNayvU4ZKSOpuTCWjIhhhfn3++vlyDu4r39zM7qK5Paao9VCpU+B29dPMh/COReJNGXz+8C8i//7Z9buarHpvqbTR0K/OcUHqlCPZdAld/nVy/BXAbFuC402qKyBEvK563x9fkuSdgvfb7/HMBPCAvfWxFSRyQY1liNVYrfHB/+Cmz/un64CoUpRr7a7Kt/KPN+OrGxUvuilKK1lsF6euu4qdHaT9XfivIc1pnOWLzWUkXj28rqiZH/OYy8n46SrNlu0ErxcTrTO0dBcd9url5XbzyuSEXEq3ZDKlJUf9sMjEF8ilpr7n0nk7ec2fqOV53j+/MBpTWDhn3TS8qw93xazjS1X/Pic3Xa4JUApqKooRqLAFOlmeOKMxZfLI1x7H0ndT/GcNv0TOGzEMUZy9Z3vOm3V1DmtOEYF0JM10AA8S2trE429JdqjL3vOceVVCa0gtY49k2DtwJuYhZJ2zkvwoAXTesdX/R76Zdbzvjq59s1HTdNzyksvJuOfN3vedPvsKZWIRX4OJ8Y17Wy6jIV/nZ+JuTEbdNhlObTfMRrzZt2x5Q/SzT/1c1rprCy5sKtH/jZcMeURFI8WMdNM7CkxNM6MviG1ni+2kga8BAajutCVxRKK0oqvJ+EwS5FWJKH+XwdDpxqbdQ32zt+ffjE6z7jlWwYevtZmv28TNy3g2xKlOK+ho0VVXjltrTa87yMrCXx1rfS56pdrcPxnOOCygptFF+0++umHWQ2ICmuIjV+On3EKUsumVSUMFBKsXVdDSIzxCKs4GGd6Y3nkGbGtGLrUOW4zrzptvUxG+YcOFc/9BebvdQ9VYnuZTiUy4m+2zCmwDEv3LddBf2e78cDN74jkLm3PQ/jKJ3PqrBtWrZOKrzGKN7qmBO3jdQfnVNg63qc0bT2nt+qB6awsOQCVWZ827SsWRJVi9K8bXccw4Q3ApxUgsdloreOne9Ys8iYX3eenZWJeWscH6cTX/R77pqB9/OJ4yIyzY33OO1pnXx+a9Ox5CjMSdESJJZmbm0PKB6XM2MM3BhHUpnOShjYmiN731EKtMZy2/Qo4HkR2V6sMsWnecRpw5Il/OocVs5RGORb34OCh/UMSrNzLRvf8O58uB47Zyw71zGvkTGv+Ap81pLwSLpuptBbzxiEx/BGoyoDHVKid17YtI3BaJHFbWh43ew4rhNfDTd0xuO09DjHnEXyqKRrec2Jfdvgq/IhZXjbb8XyoS+90wuHMGO0xhrDGsWxVepgbu9a8aYF2XJOacWg2TUdORfWkti7hljE6tB4h6/s+4fxRG8cj8tE6xqOQXIWQon0qmEq8PWwp3OOj+MJawwahW5gYzvOceFhGiVR13huNsO1k9wpw6flyH3XY5SWtO0c5RoaM0Mj3wlQTHHh03KmlIQymlZZYXJqxsArLZUorbWsJfPFsGNMC60JPIeZmDK7ppWhVo40RhQPh3lm2zR461hT4LBM4k+u8taQpXKqdw073zCnQG88O+vZWk9jPM+reDn/p9sv+d+e3/HhfKy2HUWLvYqNC5kV+XylE7KglcGXxFo30groKqAdnJNQopw4pZl90xFSAC33mb11hCjBZ0bJNay3jrXoml4uCqzeNczJs4TImiMb2/DlsCeXwsNypjGGFamxa6xFo/FGKsW8EQYlR7BEYU5LpihNXzQzGYs0FizXApMLWJB8BmF2C7rChUKht1aGZ0G6sRuMfJ66YJLws7qKUze2I5DYmgZrNeMaUMZwY720GBTx6jZojLYVzA8EIjfNwM+HW57CGb0olpJokYq5WIfxu2Yjwz2lMMrSSx4Xp1WGEHduIJjEIxLSZoolqUxJhV074IziME/SwawtjTE8LjPGGGyKdNrTOnEPDs4zhUAuAWsNaxC20lW3akHAQc4FdMZZW73ghjkc0Eajiq6duhGPZfAtsWR0WCUpOEdyCVfpqniJZXXak3PGWqlFtJVUsEpzLtS9UsBVTzYI4OhqCnVDosGjjQDyjCITf5BwK0xpPZfxQoqowqZpsUq6tkNxfNFbPk5nUhZFVOFz/c/l+Rs8kgklg9cWUYx448AUCXVTcv80RvGYAk5J2r/XIq3W5DoUsRhVQ73yBfxJc4I2hiWK1/3H3tmLnPjy+5GEVw5TFGcWNJrBeGIuYrmhgm8uqcUyCGkq+Leoa+jWy6Xqf7MYDPmaanyqwWV/DKJeQuJAgKdS8r1UJV7B+B8aRMn1KJGyptENrdKfLSY/+j0nVFV9ZwqvPS7L/lqC2Ko6ibV62WWAJP//h/VLl6HA5TwdXI8GvJHwKGvkNza25Rz/S7ng/+PWX4Htv/BSKAm60Fakm0VqGO4bAaAhy0bpvh1Y0+evT6ieqs56rBbZmTeW53XlbfX/XB7/q+GWwzrRGifsWJFN8+tux2+OnxhoxfeTJbDoX29fseQkk3RtuGs7HpexSgm5guBSCh+Xkdu253W3FUmZlhtvAe6rzzXV6gaUuqYRN8bhraTZ7nXH0yKeTImdkVhzq8QL1BhzfS2Xjfk/Hj8yBZFDb13H4KQz8LI2rpFalYIwvesEFAbnOYeVmzZz63ucNny9ueHdeCCmzOCkPzQj8ujOiFdx53ue1xGtDTvn+T/dfklBQp+WHNnQolSp9SiKn21vaQ6Wu2agc05qMrQhpMRUWcFTlAvMmiNaiwRo426x1WP7OE+87npcMdy30rl6maytOVUAYXhrJVjEKtk83GnN4B2/Oz6TivjKliQTt/O64pRs7s9hZs2Jne9QWqSkCkmVvjNWqkKqjG7w4lcMNaFy30gK8hijTJaVrueGyJkbY8n1HJDjaIVBK5mQI99s9owpMFjPjW9Fyp1W/m7/liXJNuy0irNrSis739FZy63fkEuiMQ5rDF8PNzzOZ0Akf6mUmi5sROJPodHCglwqRHIFrdRAqH+1f82vD59qOJhhTcKQvRwOjWllTYmtazH6klqtuG8HVB1OdcZy63t67dn5hlNcGKykGzfGcgwz982AUZqYZbjyzXCL08LghJzprOdpnWmNZnAtYxRZ2Jddz9fDDbFknNL86viJNUdszoQYSUXyIO/bAaU0OySQ6wrCfCcbD2XJpvBlt8fqY725weA+D8+csXXYUKV9KrFzF9YoyWespft3Y1tyKex0g9Idv9jeS1p4ra/prL96UpWGHDPeOAqFTnsa51hy4s50dFaOszNSA9YaLam+WljbWz9In3Bd2ii2RgKd1pTY247OeTa5YQySOm2UQuHwuuG2cQzW82k+s3cNW9/xvE5Sa5MjY4p0xjNYJxVV3YZNVcf84+EDSonVY+tatj7UG794UZXO8ljGYJVh0zVsUotbHTkVTqsEjDXe8EV7wxgXdq6Vc9VIrcqt73g/j9w2PZee8SVFcpJz9sbLwOG+GTitC6FEXnUb+riydQ1rDDzHmaI1f7d/xV07oFBsXcvGtYxpISfZyP7q8JE3/Rat5B6xbzoaLRVC3li2tqEzDdYIWzenwKfpTNvIsGSpCdwSmiZuLqskwC+VjCqFogwxiRXh6+amSkw1N01PKZmbZpDhQq3kkiCSnpgk0ZwCN87zkCJbJ5aZw7KQk3xPlhy49T27KptvTfVaonnVDrTG8n4+YbXhX21e8TDNoGc2dSuriqLVcp0iJjprhTlL8bOElsumWZLos8o02nHXdtw0Eoyni+JplaAlpRRTDCiT6ZWrHjyxady44ap2GmxDKImvhlt8ZfTXLCLhJUqq/5okFscoe036l/uTx2iRgT7NJwYt96yYEo223LQ7fnP+RItFGU1Jpbo8BQxtfMscV1rtmGPEW0si0eqWWCJaaajBdarIfTADWi0oZVFZkbIcrzvX1wGxZ/ViH4glC/tsW9aSaazlvt2wBKk26mzL1/0ereW8/3KzwyOhXdJSAH+zecVdt+H9dOQcVu7qsFgrjatDmrXI9eXv+i2HdcQpx1M4c15XFAmLF+ULGmekIcGFlZ1uKLZBqus8MUljQ86lVvZpntWIqhL5pWSWGIgpEmMkt2KdGazlHAu7ZqBzhjEEYEVh0crwqt/Qace3pwNzXgXkotgodx2yjaHuS7yIu52xOGNJKbHmjEdjdGZrWr5wexpreT8eZHBSAkZJWGFA0rBbbfHK1H74LMnD2hByQlXVgOZzDsmlTaCpliijpJ/8VaOAI1MEWzS6iP+6VVIHZBVYa+mV5A7MCAGyMZL+e7+R/UvIEaUcDUYSrBVyjLOEqLmq+hmjuFuflzO3dlOHSdI8YZTmGKbq2oYWhVcWqyVnopQMWmOLdN33zsGouGt7yVgJkyh/aDhUC4+rVVaSRyId1lKgla/BXy+ZTU3BKY13noL0HXe1ZuoSPHVZl/Czi2Q6UWpDhVR8RTIUxU2WvYRCcU4Lc4WV7rpzl+Ghx3LbbxmMF+IKMCle/eIXAKqRY6KAu2bDkhNTWvFayJhQAlppfDaEFOkaL6GyReq9mkKtSxKLglYKjUjtt64VZQtZzqOc2TQNWZXrPfIvaf0V2P4Z1qt2I/K+uml8022JGWH46jqiyUj4hqlx7EuOvG6219/pbXPtIZxS4FW34a4ZeKzs68vneNVuKMDf7F7zfjoypkhjLD/v72iMZfciHReoPhXHMSyQwSjFkpIU3NfXeQEWGyf+35gzpUhnY6xy0NY4PkwHUs70tq9eNwGErXHSdVovclYrbNPy1XD7g9fijeXf3HzBKSyECng3rvmBhFbqfTZ8nI7Sw+taUsl1M1bYukbkp1l8Uv/29ku+n46ELIzHmtN1OCDgBX65v2ewzfW51lR9rZW9Fpl1vjJVIsHK14FCzJkly83Ya8M3m1seKvvVGsvrdoupQ4Ota/m0nJhjkl7TnCs73gigcM0P3v/fbF9dg8UEOGV2vsGornqoFLe+467tOa0LGql3uG8HvLZ8NUg3cKm9f5fPXKqlDK1xvOq2tbJEJChLSqjqrbz83sY1krS9zLRGgHzKhS83N1cJvfiSHQX4MB0ZY8Rpzd/sXnHbDqwpcgoLYwo1qbuhNTJ7lo2d5nW7uQ47lJKbw8Y1PC4ja4xXMGlr+vaxVtB80e34NJ8Y48qbfsdNI8ONfdMxx4A3lnNe2Nr2B8Ohv9u/4XEZOQaRrD+vIzmLTP/L4YaH5cRgJTwrlMxN03PTyDAq5owqilfNlt7LuaOV5lUnKebHVRwzViled1vmsDLnSExF/K/GsW+lEmqMgZAjP9/c8e34zJxW5iReJldTzZccyfV8uSgTtFJ8OewpRbyxYwx8PdyINFIbTmEhloxSii/6Ld+fFcciUtONb9k6YR9ykSHc1ARufM/Pt3c8zqNsLupwYXANSzyzpMBdM3A04tF/1W54mM8cw1KvC7105ZZAo2TTPjiRMPdWuri/HG6kVqod+Pb8jMeQc5YaDm25bXs669l6w1fDng/TkSUFYpSZ/Be9E/BWpLv6thloreNVu8Fqw+/OjzxWVufGtezbnq1rr9c7o6Rebec6tq5nSSvP68RgPc9hFumihaF2h9/aHqd1DTFSfDPccgoz76cDVlsabXjVbQhZNgqZ2rWbM6fgeFomhlpZVVRhTYob3+OUuXrWB9fyxbDl43RicA1uNVilabqBL8Ryym2tYlty5L7tBXjkSOdt5SBhYz0oYS/u/IYTEw/ryKAtr1oJ/JLhYhYvqTZ0xmONJHUbVXBK2IHGWAbbXMPbRN0DX/Q7fr69l+99TVY+xomSC3+7v6ssViHlwm0Uu0kpkmh8SXd3YeWm9VU51JFQxBRRWfNvbr7ktu1RFP7D83u8crg6CDVK839//XOOYaV3Df/D/jXfTgaDZcwrJYlIMMVMtgJylhhZdWRMKyFDj6dv5JqrFZQsVRp3zYaQI3sv97D7diDV63uhsNENMWYJ7ynSybrzHRvn2NqWKSe+9gNfDFv+6fSINZpf9G94WkbeT3Lv/3Y60ChHjNLDmlNh03ZsTEdRUptUUicsXcyYRvG3u9cUpeiN49enB/GvVjCyELg3PZumuXpP77utDJxKRmXNlCQ52zvPoJ3IM0tm27SU3GO0ZsmZmCIb7+mNeMd/PtzztI6sKfN+OkDhygRqrRmsxytNyIn7tqM1jra2Keh6H975VyQya5Lzbkwrv9jc8ZvTJyLC5lvTEJNcKyQ1WULdblwnTQDWcNYrRRdyhjddR0mgdaHR8lxzjFflh9OKmBM3zYbSFJYoYWdaGVKO0lOODFefppk5ibroxja01jPFzFdDK8FyOfA8T8JilszO9hjgq82Oc1z4fjzSlUJS0ChRosUUr0O+oqVe7s73PIWJkqHojFOOje/4YrO75jDoArkOlJ/WER0TnZf7SiqFOz+ICi1ljFGsMRJLZqMajHHc+o7BNex8yyFM3Pgeqwxfdk4C74wk0Fu11gGhZoormsLGNGycw1mLKuCTZZMkHLGzQhw4besASwY70Vp6pCIQxC+utebLflerx+SzKBR2tiUgBMDgZNAQc2TjG3KWtP3GyfDYas1pXVlyotMyPL/xPXd+I+0hSRLMUeIhuW3vKRSWlNhrizaG0zoyxMKaMx3iYx1sS5ekkzqVdJW+3zSy13ueF3RWMvzIiZIjx2pleMksa6AzLV8OuyuAt1rT24an5Vyr96CZXQ3vql3hWnSGkcLOeAbfSlvIw0Tv/n/t3UuMHFfVB/B/vZ/dPdPzih3HeEIcJfLnjRGC6BOKkAApQUECCSWCSLFgQ9YRSOwIj0WiyBtW2cACKSLsyCILBFECEopExIIIWQETx4nzJXbm2d3V9bpV9S1OdTNjz8Njz0ynp/8/yQuPPTO369br3HvuuTYCSyZGIhUPU7vD+t0ir2QN/bTnoVW6sowLQGg3UaLCWhKh0mRCzNel0nyOEigrGBrwcdyHZ8ga80xJUcyW5SAulSwTsQIEpgXLkIGHE+H0Lcc6nxYMbA+Y7B0rwdCAoWm42luT0VRdR1bKvpynW/PD2brQdpAXpqQyaDoa9frTwHY2BV/b/Q5VSrXX6frFfhAQFXX1y7brbWqnjCDLjT5WOeIiByrgnsb0MHV0EFigAqademufunBQYNrI6lngpu3XVRhlbelqGg8D5LKSdJbB95fYekTINky0d6nE1rI9uIaJpJAHmanLy6GmabB1c9OM9CCtcyWJZG/AuppyWqjhAMGNld9sQ1KVoQFLcQ+OYWJqQ4r2iWAKq2lfXt7rmdyG5cI2THSyGE4d3DbrdWVFBaBes6sBWPCa6KYJHE36uWE7wwBuq88/SB8enB+6NoWkyOHoJnK3GBbOOt1aQKxyXI87mHZCzHrBcD31YIuZQX+u1AVKAtNGrDI4uuxHOuj/E+H08LgBkjrVdnxU9VplVZWyJ/CG4zddV+S2dB0nw/aGcy64qW/LqkQ3T4f7+zqGVc8GFnUxtAJuPQOoAZiyPXQzCdxmnQAVZI1w0/Jkf04NuHdqTgrp1IGLbOXiIrQcqbbtBMM0xo19bxsm7NTEWtpHaLswNE1mynVZo1VUMpDjmRYSlaPt1mnhaR+qKnFPYxoLXnN4HAaVyRu2g0Tl6CsFx7Dwv8dPI1IZ3u+uwNR0tBwPTVsC7QWvgas9qdh9MmxLCqomAc5gP2JHl5kLs36RHAwsnQim0ctTzHnh8FqPlSRBXe5+gjQvMe3Ky2jb9RCWkgXRzTP0shSWYcgsY5FhOZE1uJlSKKoCfaVwPGghtBxYuoGmI0F4BWDBb2HaVejnGUzDwGJzBktxH5VWycxVUaLUKjiGLLWY8xpwDRNXe2uYsvy6CrSOXl29NsolZXfBb+CeeoZ4cE87FkzV59AqyrqPNehQlcK0I9kDtt5EL5fCIcf9KTi6jdVU1i8P+hvA8FoaPLxX0gh5UVcN1mSmVl6YNDRsD8dsmWWLVIpSKTQsV+438BCYDu5tzQ1/7idxF7qp4USjvan9i605XFlfQlLkiItMZlUqOT8raFhszUhKu+HCC2Xdpa0ZCG05D+fcBlRZYCXpQ+klpiwfn2nOwTdtTDkBrvZW4Bs2TgZt2SBC07DgN2SPxVKhrQXwTEvSZ3UH046PtMjRyzJEKoOrWSjKEpLUJnuRHg9Rn0cSGBRVAV03cCKYwj2NNu6fWhh+binMZmMp7kKHzJguJX0UVYETwRQ6dcXnY34T1+MebN2CFWhwDRvQgLbj1xX3ExjQMec30aqLAWq6jmtxdzgYNueGcAwTC76O0HLwQW8F5rIU+fILG5EWI68qBJ6NeSdEAdmhICkLBHkOVfjwbMk4aNoeskLBhAFdN+o6DwYalgNPt5EUkmC6niYotAJaBUz7vqRaGlIxODRdWUpjB8hLhcXWHGzDhKHL+nhD1+FZNo7rLdl2zWvUe6In6KR9NCwPM06Iu/wmojyDqRlYsrpIlILnWzjVmMGUE2A96+O434Sm6fgk6aKoizpOWQEWG7L3ZMv26uvUQ2DYSFSO1bSPBaOJtuOjrxRUve1Zw7LRyTJEKsGU7ePucEr2y4bslw6tQlHKAGfDkvXqH+kGdF2TbIiqQFlU0CxgzmxhsTkjW4YZJhqWi7RQiPIEs15juB2bpRvwLclyckwbH/ZW4FhWXcNBRzeXGXLXtKTQUuBjJeniw36GlisDcYHl4e664v+1fhf9ok6ZdOW5Yug6mrYLVJCt0eplSBUq/F9vrV5CZcExDVgwcNVYRVqkCC3JEPBMGwvTU5hy5P66nvXRtDzZHtFy0XY8xIVCUVR4aOYErvZW8UkSISlltty3HDQzD1mRwzdcVJBnWlwUOOY1YOuuFJhDibLepiqrn1UrSYRjQRNN24cfW1hJ+nBME207gGHI3vFraYRIpciLCi1fih7qumRIfKYxI1vuGAYWvBamHFeWe1g2QmcWa0mM5bSHvFhHUtRbyemy7/isJ4OJbSdAVhToFzlWki50XYPUIZOU4mNBE4auo2F6WM/6w+dgL4vRcnw0LRtTTgNJkeGk14KmafBMF7oG9PIMWSE7Pxi6gbsDCzN+CEuX7Rw1SI2ZtuNjxpalDoamodxQBE+VJT7qd+rJC0MmDTRZQ9+vC5TqMLDgNZCpHL0iRawU3HpNsKHpsgyqkvvatBtgzgsBAFfNVeRFAF1DXV/GhZ4m6COTdeq6pL/rmo6WG+CeYBrreb/O9rFh6Saatl1Xe1eYdxv1EoQedM1AnMnys5Zlomn7sAwD004D82GM61EHeSkB8LTjISkkM3Heb+J40JJlSZYsXZDJJxlcc3ULLdvBZZRwDLveWqyEqmSmfyXrI1MFToQWtKpCUioZ/IGBUqswa4eYDUKkqoCl62g7Iea8EAvef3fSGBdap9PZrWjYWPjyl7+Mt956a9TNuMng5fbGwNIxTKzUQZFrWFjwGght96bv3WnWcrffMVhLuZefc+P/A7DpZydFvm2AvfHnXOt3kBS5jOjVVT41SHEXU5NVP4PA6cbPfafHdvC5t/ueWzkWt/p92x2za/2OBCW6pPwu1QHOjBMgKdRNAwJ7bc+gTaupPFAAWaO6cbDDrmfqdjo+G9sPYLh+48a27PW43cr/H/RfhQqdTAqAVVVVB9ZqGIgOjunGdkrqtawB7mTJ8HhOO/6O/XI7fb/V57F145b6bafjsN2/9bIEV6O1YSq6rmnoZAlm64B1PYsR5Wk9I+IOj9FO13ovSzal9weWC6cuVBepFB9HUjjJNkzZGkWTQKybpbI2z7CwELTgGtaO19mgT2V/6S7KSraWsU0TnuFg1pO9s7e6B7YdeTnLSxmRzoti06zqXu5pt3OdZ4XCShrhWr+D631Z8zvrhbJnNrThwMzgnE1UjqTOajgRTG26j+10b8oKhWtxF708QVnJdmm+ZQ8zCAC5DlUpGSi2YQyXOWx3PAZ6WYJrcReraQ8rcYSFoIWW5SIr5R682JwdDlQNPkNXpeilCdpegNWkj04WIy4U2o6Pthtg3mvg0vp1/GdtCUkpa9vaXoBTjRmcbi1sef8etCMpchhaPaNnmMPPFeVSiT0rFYqyQjeLt23rVtf9dufE1WgVF5c/wkoWoSorzHgBGpaHhu0iVjl8U9bAmvWWWkuJVJR3DNlPVddkECsrFOIiQz/PEFquXHdpH+t5DEeXtYupkmJssma3Ql/lCOp9j0+35jBdny8bz4WyqvBx1EEnjzHrShXxtTSWoLdO6XUNS1LDkwiqLOAYNnQNMvujAQteQ2o89Nfwztp1RFmGwLRwV9BAVlaoygq2ZSLKU4SGi4btoAIQFSlOt+Zly8H+uqzz1SRLS9c1zLqyR2lcZ3elhRrus1uhQtNykSh5dl3ufoJMFfWguSZFK70Q/9O+W5aC7HJ93HjdbXxfGBTHHGxNN3jGqar877ZUloOW7Q3vJaElS0M+jtaRFJJtAmDTsW3aHuI8r7daVEiVzNyb9eyZbRh1Fo4slWk5HkJTBvN7eYL1ejcFw5C1nSUki+1Uow1TN7CU9PDO2scy4KgKQJclMVP17Govz5CWEkAuNudkAEOluBZ18WG0ClWU0HTZekyvDHiWJSnZpYKqKtiajqbrSdHGQsEydCzFMuAsmXqyRvj09DxsXZabxEqeiy3bG74PVKhwrd/B1d4arvXX6vojMrDccDzM202cbLVh6vowyynJU/yns4KoiOHpFooKaDsB7g5b6OUyECqZV5L5MSgyammy3jwvK5i6PN//s74kWx5qBj6K15FXBe4JpjFlh0jKDNOOh7ysl7TUA/GuKYNZgy0X87JAlKXwLUnf7aaDmtHAWtZHy/ZxPGihm6f4MFpFUVZouz4cw8D1fhedPEXb9uGYFuIiQ1VKZo1Rv5umSpZlNeuBmXc7S+gVKUpVQjc1VGWFthvCBORZatrQKilaaZl6Xd3dHGaoLCU9dFUMR5Nrr5cnMujoNmDrsgNFVcnM+eXudbkmNR2ubiB0XLTtEKHtStEoDbjSXYFn2ph1fPRLKXDWtDxJua9kgqnSgELJPdA1pVr+le4yoizFahbV2+JZmHVkmWHD8WBpsl1oUBcb28s70mE7d+4c3njjjS3/jYHtIbjdYOrT8jtu9yVxPwOL/WzbYbgp6KxHp7cKGg+6HZ/G4zMwTEtW2fAl/lZuqJ/2z3WnbjeQ3svP3MvAxV6O91Z9Ongh2cv5P8o+vpNjdVDt3+vP2xhc3jh4ut35td11eOP9rOV4W2a53K6d2rrXY7CXe8qdnPe3+3s2BvcbjyVw8/Nxq69tHNgZbBuXVwUsTXYXGAzu3XhMNw4cAbJdUr/eR3uQlbJb+yOVIisKqKrActzDehZLimvQwqnGDELb3bf3hdsZnN7uPB0cx0H7HcMcBrQAbvk6HtzDtvue1STCe91lrGV9GNBxV9AaZuNs9T2D9n4crWEpiWEbwLzXwrzXQFoqrNfb3m3s141tWstkV4FBttjGPt7pfO6rTKpHFxniPJOsFMvdNDh842cH/jvwPTh3VL0Ua7eJmY3fG6kUy3EPaSGV8n3Trvf0lc/Zsr09nTORSuutEyUIDixn2LdbXUdbXX+h6dz0fB0MQCZFXhenkgzFfp7DtyTbpe34yMpiy/vijZ8/KxT6KkNeKpi6DKTVpUAkS61eSqjV/aeqCqamo1EXosuKYlgDw6rv17JETPaCt3Xzps+78Xz36yVyO93nxwkDWyIiIiIiIhprOwW2+pZfJSIiIiIiIhoTDGyJiIiIiIhorDGwJSIiIiIiorHGwJaIiIiIiIjGGgNbIiIiIiIiGmsMbImIiIiIiGisMbAlIiIiIiKiscbAloiIiIiIiMYaA1siIiIiIiIaawxsiYiIiIiIaKwxsCUiIiIiIqKxxsCWiIiIiIiIxhoDWyIiIiIiIhprDGyJiIiIiIhorDGwJSIiIiIiorHGwJaIiIiIiIjGGgNbIiIiIiIiGmsMbImIiIiIiGisMbAlIiIiIiKiscbAloiIiIiIiMaaOeoG7JfLly/j3Llzo27GyC0tLWF2dnbUzaBDxn6fXOz7ycW+n1zs+8nFvp9c7Htx5cqVbf9N63Q61SG2hQ7Yww8/jDfeeGPUzaBDxn6fXOz7ycW+n1zs+8nFvp9c7PvdMRWZiIiIiIiIxhoDWyIiIiIiIhprDGyPmPPnz4+6CTQC7PfJxb6fXOz7ycW+n1zs+8nFvt8d19gSERERERHRWOOMLREREREREY01BrZEREREREQ01hjYHgEvvvgiHn74YczOzuIHP/jBpn+7cuUKms0mjh07Nvzz3HPPjailtN926nsAeP311/G5z30OCwsL+PrXv473339/BK2kw/Doo49ibm5ueJ1zX++ja2VlBd/5zndw11134cyZM/jd73436ibRIeF1Pjl2er7z2X60bdf3fKffnTnqBtCdO3bsGH74wx/iT3/6E+I43vL/fPDBBzBNdvdRs1PfLy8v48knn8Qvf/lLPPLII/j5z3+O8+fP47XXXhtRa+mgvfDCC3jqqadG3Qw6YM888wxs28alS5fw9ttv49vf/jbOnj2LBx98cNRNo0PA63wybPd857P96NvtvZ7v9NvjUTkCvvGNbwAA/v73v28b2NLRtFPfv/LKK3jggQfwzW9+EwDw4x//GIuLi/jXv/6F+++//9DbSkR3LooivPLKK3jzzTcRhiEeeughPPLII/jtb3+LZ599dtTNI6J9st3znc/2o4/v9bePqcgT4syZM3jggQfw9NNPY3l5edTNoUNw8eJFnD17dvj3IAiwuLiIixcvjrBVdJB+8pOf4NSpU/jqV7+Kv/zlL6NuDh2AS5cuwTAMnD59evi1s2fP8rqeILzOJxuf7cR3+u0xsD3iZmZm8Prrr+Of//wn/vznP6PX6+H73//+qJtFhyCKIjSbzU1fazab6PV6I2oRHaRnn30W//jHP/DOO+/g/PnzePzxx/Huu++Oulm0z3hdTzZe58R7wOTiO/3uGNh+yj366KNoNptb/vna17626/eHYYhz587BNE3Mz8/jhRdewGuvvYZOp3MIrac7cad9HwTBTf3c7XYRhuFBNZkOyK2cC5///OfRaDTgOA6++93v4gtf+AL+8Ic/jLjltN+CIEC32930NV7Xk4PXOfHZPrn4TpF09J8AAAIGSURBVL87rrH9lHv11Vf39edpmgYAqKpqX38u7b877fsHH3wQL7300vDvURTh8uXLLDAzhm7nXNA0jdf5EXTfffdBKYVLly7hvvvuAwC8/fbbvK4nFK/zycNnOw3wnf5mnLE9ApRSSJIEZVmiKAokSQKlFADgb3/7G/7973+jLEssLy/jRz/6Eb70pS+h1WqNuNW0H3bq+8ceewwXL17E73//eyRJgueeew5nzpxhcYkjaG1tDX/84x+H/f/yyy/jr3/9K77yla+Mumm0z4IgwGOPPYZf/OIXiKIIb775Jl599VU88cQTo24aHTBe55Nlu+c7n+1H33Z9z3f63TGwPQKef/55zM/P48KFC3j55ZcxPz+P559/HgDw3nvv4Vvf+haOHz+OL37xi7BtG7/61a9G3GLaLzv1/ezsLH7zm9/gpz/9KU6ePIm33noLv/71r0fcYjoISin87Gc/w7333ovFxUW8+OKLeOmllzYVGKKj48KFC0iSBJ/97Gfxve99DxcuXOBszQTgdT5Ztnu+89l+9G3X93yn353W6XQ4f01ERERERERjizO2RERERERENNYY2BIREREREdFYY2BLREREREREY42BLREREREREY01BrZEREREREQ01hjYEhERERER0VhjYEtERERERERjjYEtERERERERjTUGtkRERERERDTW/h8JiteUvoaOqwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "ax.scatter(year_j, drilled_j, alpha=.1)\n",
    "ax.plot(year_new,y_line, color=\"black\")\n",
    "ax.set_ylabel(\"Pr Drilling\")\n",
    "\n",
    "for i in range(nsim):\n",
    "    y_line_sim = invLogit(bs_sims[i][0] + bs_sims[i][1]*year_new + bs_sims[i][2]*1 + bs_sims[i][3])\n",
    "    ax.plot(year_new, y_line_sim, color=\"black\", alpha=.1)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e4a2a0d",
   "metadata": {},
   "source": [
    "We can also generate predictive uncertainty to the model. We recall, there is no $\\epsilon$ value in our model or correspond $\\sigma$ term. The extra, predictive uncertainty comes instead from the binomial distribution. \n",
    "\n",
    "Below, we will generate a predictive distribution for the probability of drilling in the year corresponding to 15.5 (2019) and an oil price that is two standard deviations over the mean value (about 100 dollars a barrel). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "d9802e0a",
   "metadata": {},
   "outputs": [],
   "source": [
    "#A new observation in the year 15.5 (2019) \n",
    "#with an oil price two standard deviations over the mean value (around 100 dollars)\n",
    "\n",
    "n=100\n",
    "year_new = 15.5\n",
    "oil_new = 2\n",
    "oil_l_new = 2\n",
    "\n",
    "nsim = 4000\n",
    "\n",
    "bs_sims = []\n",
    "drilling_sim = []\n",
    "\n",
    "for s in range(nsim):\n",
    "    param_sim = logSim(drill_mod3)\n",
    "    bs_sims.append(param_sim)\n",
    "    p_new = invLogit(param_sim[0] + param_sim[1]*year_new + param_sim[2]*oil_new + param_sim[3]*oil_l_new)\n",
    "    drilling_sim.append(spt.binom.rvs(100, p_new)) #a binomial with n=100 draws, and probability of success p_new\n",
    "\n",
    "\n",
    "drilling_sim = pd.Series(drilling_sim)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1c7407bb",
   "metadata": {},
   "source": [
    "What we get back are a set of simulations with different outcomes of how many drilling events we observe of the 100 that are completed. We can show this distribution below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "4430947b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "drilling_sim.hist(bins=100)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fa076ea0",
   "metadata": {},
   "source": [
    "By dividing by n=100, we get the mean predicted probability of drilling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "80ce6387",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.03848"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.mean(drilling_sim)/n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b7b6e8ed",
   "metadata": {},
   "source": [
    "We can also estimate the standard error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "211eaa08",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.019708871099075917"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.std(drilling_sim)/100"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "293b2e35",
   "metadata": {},
   "source": [
    "# Assignment\n",
    "\n",
    "## 1. Oil Drilling\n",
    "\n",
    "Consider the prediction of drilling based on the logistic regression above (drill_mod3). Say that there are 50 licenceses active in 2019 (year=15.5) and that the oil price (and its lag) is 1.5 standard deviations above its mean. \n",
    "\n",
    "Simulate the number of drilling events that will happen on those 50 licences and show the distribution of the number of drilling events. \n",
    "\n",
    "If the price increases to 2 standard deviations above its mean, how will that change the amount of drilling. Show the distribution of this difference. \n",
    "\n",
    "## 2. Free question \n",
    "\n",
    "Find your own data where you have a binary variable. Set up and interpret a logistic model using appropriate visualisations of the model results. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0a4dfcc5",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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