{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Linear Regression"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A major goal of this morning's lecture was to introduce the idea of intra-subject variability and how it affects the modeling of a particular data set. We will begin by reviewing (briefly) simple linear models, and we'll discuss how to do such a fit in R. Then, we will look more closely at the Rails example from this morning."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simple Linear Models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A simple linear model is of the form\n",
    "\n",
    "$$y_i = \\alpha + \\beta x_i + \\epsilon_i$$\n",
    "\n",
    "The goal of a linear regression is to find the line\n",
    "\n",
    "$$ y = \\alpha +\\beta x$$\n",
    "\n",
    "that best fits the data. I.e. we find the line such that the sum of the squared errors is minimized. A key assumption in such a model is that the errors follow a standard normal distribution. This is important, because when this assumption is invalid, applying the standard confidence interval calculation for the slope $\\beta$ will be wrong.\n",
    "\n",
    "We will use a sample data set from R to illustrate a simple linear regression."
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "# load the data set\n",
    "data(ToothGrowth)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>len</th><th scope=col>supp</th><th scope=col>dose</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>4.2</td><td>VC</td><td>0.5</td></tr>\n",
       "\t<tr><th scope=row>2</th><td>11.5</td><td>VC</td><td>0.5</td></tr>\n",
       "\t<tr><th scope=row>3</th><td>7.3</td><td>VC</td><td>0.5</td></tr>\n",
       "\t<tr><th scope=row>4</th><td>5.8</td><td>VC</td><td>0.5</td></tr>\n",
       "\t<tr><th scope=row>5</th><td>6.4</td><td>VC</td><td>0.5</td></tr>\n",
       "\t<tr><th scope=row>6</th><td>10</td><td>VC</td><td>0.5</td></tr>\n",
       "\t<tr><th scope=row>7</th><td>11.2</td><td>VC</td><td>0.5</td></tr>\n",
       "\t<tr><th scope=row>8</th><td>11.2</td><td>VC</td><td>0.5</td></tr>\n",
       "\t<tr><th scope=row>9</th><td>5.2</td><td>VC</td><td>0.5</td></tr>\n",
       "\t<tr><th scope=row>10</th><td>7</td><td>VC</td><td>0.5</td></tr>\n",
       "\t<tr><th scope=row>11</th><td>16.5</td><td>VC</td><td>1</td></tr>\n",
       "\t<tr><th scope=row>12</th><td>16.5</td><td>VC</td><td>1</td></tr>\n",
       "\t<tr><th scope=row>13</th><td>15.2</td><td>VC</td><td>1</td></tr>\n",
       "\t<tr><th scope=row>14</th><td>17.3</td><td>VC</td><td>1</td></tr>\n",
       "\t<tr><th scope=row>15</th><td>22.5</td><td>VC</td><td>1</td></tr>\n",
       "\t<tr><th scope=row>16</th><td>17.3</td><td>VC</td><td>1</td></tr>\n",
       "\t<tr><th scope=row>17</th><td>13.6</td><td>VC</td><td>1</td></tr>\n",
       "\t<tr><th scope=row>18</th><td>14.5</td><td>VC</td><td>1</td></tr>\n",
       "\t<tr><th scope=row>19</th><td>18.8</td><td>VC</td><td>1</td></tr>\n",
       "\t<tr><th scope=row>20</th><td>15.5</td><td>VC</td><td>1</td></tr>\n",
       "\t<tr><th scope=row>21</th><td>23.6</td><td>VC</td><td>2</td></tr>\n",
       "\t<tr><th scope=row>22</th><td>18.5</td><td>VC</td><td>2</td></tr>\n",
       "\t<tr><th scope=row>23</th><td>33.9</td><td>VC</td><td>2</td></tr>\n",
       "\t<tr><th scope=row>24</th><td>25.5</td><td>VC</td><td>2</td></tr>\n",
       "\t<tr><th scope=row>25</th><td>26.4</td><td>VC</td><td>2</td></tr>\n",
       "\t<tr><th scope=row>26</th><td>32.5</td><td>VC</td><td>2</td></tr>\n",
       "\t<tr><th scope=row>27</th><td>26.7</td><td>VC</td><td>2</td></tr>\n",
       "\t<tr><th scope=row>28</th><td>21.5</td><td>VC</td><td>2</td></tr>\n",
       "\t<tr><th scope=row>29</th><td>23.3</td><td>VC</td><td>2</td></tr>\n",
       "\t<tr><th scope=row>30</th><td>29.5</td><td>VC</td><td>2</td></tr>\n",
       "\t<tr><th scope=row>31</th><td>15.2</td><td>OJ</td><td>0.5</td></tr>\n",
       "\t<tr><th scope=row>32</th><td>21.5</td><td>OJ</td><td>0.5</td></tr>\n",
       "\t<tr><th scope=row>33</th><td>17.6</td><td>OJ</td><td>0.5</td></tr>\n",
       "\t<tr><th scope=row>34</th><td>9.7</td><td>OJ</td><td>0.5</td></tr>\n",
       "\t<tr><th scope=row>35</th><td>14.5</td><td>OJ</td><td>0.5</td></tr>\n",
       "\t<tr><th scope=row>36</th><td>10</td><td>OJ</td><td>0.5</td></tr>\n",
       "\t<tr><th scope=row>37</th><td>8.2</td><td>OJ</td><td>0.5</td></tr>\n",
       "\t<tr><th scope=row>38</th><td>9.4</td><td>OJ</td><td>0.5</td></tr>\n",
       "\t<tr><th scope=row>39</th><td>16.5</td><td>OJ</td><td>0.5</td></tr>\n",
       "\t<tr><th scope=row>40</th><td>9.7</td><td>OJ</td><td>0.5</td></tr>\n",
       "\t<tr><th scope=row>41</th><td>19.7</td><td>OJ</td><td>1</td></tr>\n",
       "\t<tr><th scope=row>42</th><td>23.3</td><td>OJ</td><td>1</td></tr>\n",
       "\t<tr><th scope=row>43</th><td>23.6</td><td>OJ</td><td>1</td></tr>\n",
       "\t<tr><th scope=row>44</th><td>26.4</td><td>OJ</td><td>1</td></tr>\n",
       "\t<tr><th scope=row>45</th><td>20</td><td>OJ</td><td>1</td></tr>\n",
       "\t<tr><th scope=row>46</th><td>25.2</td><td>OJ</td><td>1</td></tr>\n",
       "\t<tr><th scope=row>47</th><td>25.8</td><td>OJ</td><td>1</td></tr>\n",
       "\t<tr><th scope=row>48</th><td>21.2</td><td>OJ</td><td>1</td></tr>\n",
       "\t<tr><th scope=row>49</th><td>14.5</td><td>OJ</td><td>1</td></tr>\n",
       "\t<tr><th scope=row>50</th><td>27.3</td><td>OJ</td><td>1</td></tr>\n",
       "\t<tr><th scope=row>51</th><td>25.5</td><td>OJ</td><td>2</td></tr>\n",
       "\t<tr><th scope=row>52</th><td>26.4</td><td>OJ</td><td>2</td></tr>\n",
       "\t<tr><th scope=row>53</th><td>22.4</td><td>OJ</td><td>2</td></tr>\n",
       "\t<tr><th scope=row>54</th><td>24.5</td><td>OJ</td><td>2</td></tr>\n",
       "\t<tr><th scope=row>55</th><td>24.8</td><td>OJ</td><td>2</td></tr>\n",
       "\t<tr><th scope=row>56</th><td>30.9</td><td>OJ</td><td>2</td></tr>\n",
       "\t<tr><th scope=row>57</th><td>26.4</td><td>OJ</td><td>2</td></tr>\n",
       "\t<tr><th scope=row>58</th><td>27.3</td><td>OJ</td><td>2</td></tr>\n",
       "\t<tr><th scope=row>59</th><td>29.4</td><td>OJ</td><td>2</td></tr>\n",
       "\t<tr><th scope=row>60</th><td>23</td><td>OJ</td><td>2</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lll}\n",
       "  & len & supp & dose\\\\\n",
       "\\hline\n",
       "\t1 & 4.2 & VC & 0.5\\\\\n",
       "\t2 & 11.5 & VC & 0.5\\\\\n",
       "\t3 & 7.3 & VC & 0.5\\\\\n",
       "\t4 & 5.8 & VC & 0.5\\\\\n",
       "\t5 & 6.4 & VC & 0.5\\\\\n",
       "\t6 & 10 & VC & 0.5\\\\\n",
       "\t7 & 11.2 & VC & 0.5\\\\\n",
       "\t8 & 11.2 & VC & 0.5\\\\\n",
       "\t9 & 5.2 & VC & 0.5\\\\\n",
       "\t10 & 7 & VC & 0.5\\\\\n",
       "\t11 & 16.5 & VC & 1\\\\\n",
       "\t12 & 16.5 & VC & 1\\\\\n",
       "\t13 & 15.2 & VC & 1\\\\\n",
       "\t14 & 17.3 & VC & 1\\\\\n",
       "\t15 & 22.5 & VC & 1\\\\\n",
       "\t16 & 17.3 & VC & 1\\\\\n",
       "\t17 & 13.6 & VC & 1\\\\\n",
       "\t18 & 14.5 & VC & 1\\\\\n",
       "\t19 & 18.8 & VC & 1\\\\\n",
       "\t20 & 15.5 & VC & 1\\\\\n",
       "\t21 & 23.6 & VC & 2\\\\\n",
       "\t22 & 18.5 & VC & 2\\\\\n",
       "\t23 & 33.9 & VC & 2\\\\\n",
       "\t24 & 25.5 & VC & 2\\\\\n",
       "\t25 & 26.4 & VC & 2\\\\\n",
       "\t26 & 32.5 & VC & 2\\\\\n",
       "\t27 & 26.7 & VC & 2\\\\\n",
       "\t28 & 21.5 & VC & 2\\\\\n",
       "\t29 & 23.3 & VC & 2\\\\\n",
       "\t30 & 29.5 & VC & 2\\\\\n",
       "\t31 & 15.2 & OJ & 0.5\\\\\n",
       "\t32 & 21.5 & OJ & 0.5\\\\\n",
       "\t33 & 17.6 & OJ & 0.5\\\\\n",
       "\t34 & 9.7 & OJ & 0.5\\\\\n",
       "\t35 & 14.5 & OJ & 0.5\\\\\n",
       "\t36 & 10 & OJ & 0.5\\\\\n",
       "\t37 & 8.2 & OJ & 0.5\\\\\n",
       "\t38 & 9.4 & OJ & 0.5\\\\\n",
       "\t39 & 16.5 & OJ & 0.5\\\\\n",
       "\t40 & 9.7 & OJ & 0.5\\\\\n",
       "\t41 & 19.7 & OJ & 1\\\\\n",
       "\t42 & 23.3 & OJ & 1\\\\\n",
       "\t43 & 23.6 & OJ & 1\\\\\n",
       "\t44 & 26.4 & OJ & 1\\\\\n",
       "\t45 & 20 & OJ & 1\\\\\n",
       "\t46 & 25.2 & OJ & 1\\\\\n",
       "\t47 & 25.8 & OJ & 1\\\\\n",
       "\t48 & 21.2 & OJ & 1\\\\\n",
       "\t49 & 14.5 & OJ & 1\\\\\n",
       "\t50 & 27.3 & OJ & 1\\\\\n",
       "\t51 & 25.5 & OJ & 2\\\\\n",
       "\t52 & 26.4 & OJ & 2\\\\\n",
       "\t53 & 22.4 & OJ & 2\\\\\n",
       "\t54 & 24.5 & OJ & 2\\\\\n",
       "\t55 & 24.8 & OJ & 2\\\\\n",
       "\t56 & 30.9 & OJ & 2\\\\\n",
       "\t57 & 26.4 & OJ & 2\\\\\n",
       "\t58 & 27.3 & OJ & 2\\\\\n",
       "\t59 & 29.4 & OJ & 2\\\\\n",
       "\t60 & 23 & OJ & 2\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "    len supp dose\n",
       "1   4.2   VC  0.5\n",
       "2  11.5   VC  0.5\n",
       "3   7.3   VC  0.5\n",
       "4   5.8   VC  0.5\n",
       "5   6.4   VC  0.5\n",
       "6  10.0   VC  0.5\n",
       "7  11.2   VC  0.5\n",
       "8  11.2   VC  0.5\n",
       "9   5.2   VC  0.5\n",
       "10  7.0   VC  0.5\n",
       "11 16.5   VC  1.0\n",
       "12 16.5   VC  1.0\n",
       "13 15.2   VC  1.0\n",
       "14 17.3   VC  1.0\n",
       "15 22.5   VC  1.0\n",
       "16 17.3   VC  1.0\n",
       "17 13.6   VC  1.0\n",
       "18 14.5   VC  1.0\n",
       "19 18.8   VC  1.0\n",
       "20 15.5   VC  1.0\n",
       "21 23.6   VC  2.0\n",
       "22 18.5   VC  2.0\n",
       "23 33.9   VC  2.0\n",
       "24 25.5   VC  2.0\n",
       "25 26.4   VC  2.0\n",
       "26 32.5   VC  2.0\n",
       "27 26.7   VC  2.0\n",
       "28 21.5   VC  2.0\n",
       "29 23.3   VC  2.0\n",
       "30 29.5   VC  2.0\n",
       "31 15.2   OJ  0.5\n",
       "32 21.5   OJ  0.5\n",
       "33 17.6   OJ  0.5\n",
       "34  9.7   OJ  0.5\n",
       "35 14.5   OJ  0.5\n",
       "36 10.0   OJ  0.5\n",
       "37  8.2   OJ  0.5\n",
       "38  9.4   OJ  0.5\n",
       "39 16.5   OJ  0.5\n",
       "40  9.7   OJ  0.5\n",
       "41 19.7   OJ  1.0\n",
       "42 23.3   OJ  1.0\n",
       "43 23.6   OJ  1.0\n",
       "44 26.4   OJ  1.0\n",
       "45 20.0   OJ  1.0\n",
       "46 25.2   OJ  1.0\n",
       "47 25.8   OJ  1.0\n",
       "48 21.2   OJ  1.0\n",
       "49 14.5   OJ  1.0\n",
       "50 27.3   OJ  1.0\n",
       "51 25.5   OJ  2.0\n",
       "52 26.4   OJ  2.0\n",
       "53 22.4   OJ  2.0\n",
       "54 24.5   OJ  2.0\n",
       "55 24.8   OJ  2.0\n",
       "56 30.9   OJ  2.0\n",
       "57 26.4   OJ  2.0\n",
       "58 27.3   OJ  2.0\n",
       "59 29.4   OJ  2.0\n",
       "60 23.0   OJ  2.0"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Let's see what it looks like:\n",
    "ToothGrowth"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These data are the results of an experiment where 60 Guinea Pigs were divided in to 6 groups and then were given a specific dose of either vitamin C or orange juice over a period of time, and then their tooth length was measured. We'll do two separated fits: one for vitamin C and one for OJ."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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5Je2bbW1ugLSe/jbdWes5vmWrX03/mumwAVJzXi7JY3/Q9/j6S/Y4g9cafLcH8r+e5XapF7BXJE1fHtRbedNM67nW1J+W+Y8k/5W0z2m9gB23HJmGzfY+NOJB1aemXU0f3Wq73nO23uM5rK8vZXV2X93LW/3b3Ox6+r/RAVL16Y1JY1rPnZ2rslfq/2Kd32b9vzQretODW+uqTf38Gff53P//u/5/fjdp/iBU27s42S5pyksy0/Sl+TlbfxQ4qVVf62vQ1zy3q//tbdb6xyft0v7ZNGyAVAO2Zpv1f6722/Slpq9Nxik3TKP24546zoO0IUCAAAECsxI4IjtqflHVXzL7S/3V7pdGZIfWA9oDpNrmu5LfTOoF0t2SKvVXzeYXbLX5WHLbZOvk3km9OGj68/3Mb59U+dOkqX/7dTU//ecvWvXN+rv31tfVpfZfT+sv7Xsmv5o0bWt6SLJvsmtSpX+AdEbqbnfdmp9e3flc5pvHn96rH2fy4dbjLsr845J6Qbhb8jdJ+wXMU7Jc5WbJrZPqQ7PP/9Wr2zvTtZa1DJDW09/qz3rO8TZ5XJ2DDyTNcX6yV3eHTJvypcw062tabtv2VtZzrW34pF795ib/lgbNNt/T1/iZrXUnZf7neusPbdV/olfXTB7UW3dqph9M6v/QOGXcAVK9YL86afr8gtbG13vO1nM8O2e/7f/zb87yHkmdjycmTf/qRfzuyThlPf2vwUP9H3l+0uyz+lV1lRskmysPSIPmsTV9XOsB9+pbd8/Wupo9uG/9llke5/lcP4tqEFP7q+dtPW+aUs/ldn9+uVmRaXuAVG3enzTHWFfz2o+r58mvJ1Xq/1cNapr1767KVjkq8826F7fqH9qqr/VnJLWtKvXc/mbSPK4GYuOU+lncPKamTR/Heaw2BAgQIEBg6gLHZA/NL6p6gdZf7peKZv2gaQ2emtJ+sVS/iNt/9Wza1OCm2c7Jma8XU+3yC1lorgxUu+ZF7m0y3zzu7Mw3L1SPaNU365+Tuir3Tpq6GhhsUZUpeydNfU2bX/a1rkr/AOkRP63+2b+Pzlz78U1fftZgwMxt+x7TDIDaTQ9vtTm9vSLzP2yta0z6moy1WA5N31814hEb6e96z3F1542t/r13QP/aA6RvZX2//fGtx79owOMHVdUL08akrh7s0mp0dGtdeyDyB636GuzWQP3OSfMcq8HDWkv9/2v68aHNPLgGHU3b1/TabuScred4ntDqQ70Qv2mvH83kK631f9VUjphupP+12XZ/Th+xn0Gr6nlUj2lM68pOU/4hM039iZlvznGz/uDW+mq3ZbMi0ze21g16Pte2bpXUz6p2qZ+LlyTNfh/cWvmSVn39selGrXU3bq2rx762ta5ma7nZ5meqolWOynyz7sWt+v4B0sNa62q2/dy5om/dsMVDsqLZV037j3/Y49QT6KRA/QBSCBBYLIEzW93ZuzW/0dl6gVcvNvvLr7Qq3pL5y1vLNfud5POtul/szZ+Q6bG9+V0zrb9A1tWr5i+rR2a++eXc7OMhqWvKv2WmfhGvp3yz70Hn9C33D/L6Vl+3eFCrsl5MvqG13My+rpnJdPdkt9byrGcPau1wrf1t/GsTaznHrV2ONVvPh/rLe7u0z82gAXq7bTP/icyc1Fuoc/mo3vydMr1bb77f4IjU10C+yo7Ji5JvJPVHgsOTeu6Ne+UoTddUtkjr9rGd0Xv0Qa2t9Pe3WTXsObae47lts9FMT07Kql7IN/lu5ptSV3I2Vw5qNVhr/1sPXddsPY/e0XpkXVGqnzNlfUirvs7ten+OtDbzs9na1veTLyb1s+xZyf9NTku2T5pSz8tBpR57bmvFBa35mq1BT7u02w7bZrv9oPnP9VWe0VreOvPtfrdWbTJbx9cu9fNOIbCyAgZIK3vqHfgCC/yw1bc9Mr9Na7lmf5zU4KLJF6pyjPKDAW22TN1NW/XNi9JW1XWz9Vfaptyhmcm0+tCUehF276Tp7wcz3wysqn6rpNo05X3NzDqm/cfSDMSaTdWLqM2Vm7ca1IuD/m3U6vZx13L72Gt5lmW9/d3oOV7LMfafl3ps23Wc81KPqRfH7YHD71dlyuOu+/en/3wkk9Nby/XC9InJ1a26mq2/4D86eXtSbf4gmXS5STbYPrYTejtY7zmrh6/neG7T229NbpmUUTuH1opeqZ8tmysb6f/mtj3O+re1GtXPjxoYHZC0+17ndZKlBtevT2rgUj9bX5E8MqnBWbvUc3RQ6R8QXdnXqD4n1y7t/x/t+rXM92/zsrU8uNf2+L7H3KxvuX+xfhZ6DdmvYrkzAp7cnTmVDqRDAh9rHUv9H31Ma7lmv5n8disvrsoxSr0FqL/Ui8mLW5U3aM23Z3duLZzdmm8PkOptcPdvrfvPzH+yt1wvOurFzb695Rrkfa43v55J/7Gs5y/I7RcV4xx39bN97Ovp90Yes97+bvQcr6XP/eelHruec1OPe0PSvLisv+Tvkzwqacprm5nW9M2Zv1Xyv5PjWvXNbA2W6sXvrzQVE5oe2LedE3rL6z1nzebWejztF9tnZSOfGJHvNTsZMd1o/0dseqxVX0uruoLdlDr/v9MsZPpfSXt9a9W6ZnfKo45InpDUz6z62fi+5BlJ/eyqn1tNGTZAap6zTbv+afsc9a9bz3L9/+rf57C+jdr+eVnZPr77jWh8o6z7elJ/oHhNctdEIdApAQOkTp1OB9MRgQ/nONqDlhdmuX5ZDytbD1vRV39533KzeHIzk+k9WvPN7JaZaf8CrAFaU+oFyim9hf0yrUFQlRpI1C/QeoHWlJc0M5m+P6kX7sPKLH42ndza+S6ZrxfW/eXurYp6YfPd1vKsZ09u7XCt/W0/dq3nuLXbmf7F+EfZ8QdaO39Z5vfoLf8w04+11rVnf5CFP09+Ian2v5fUi9zm+bZF5usPDJMqtb0XtDZ2Wua/1Vs+uVW/1nPWPHQtx3Ni86BMr0p+NTl4SGoQsLlycqvBevvf2sS6ZttXiO6bLfxuayvtK0yt6rFn+3/OPCSPvFvv0Zdmesekfqa9Kqlz2v5DUfN8SvVcy3r/ADGo0x9uVT40880ftFrV180+Pf/W752bJE9KbpooBDol0P/DoVMH52AILKlA/WL+q1bfb575o5PmF3ezqgZNz0ve0lT0pvWCbVCpF0yDSr14bMqjM3NAs9Cb/nGm+/Tm65fxx3vzzaS5ilQ/T27Rq/x0ptW2+l1/mazSHoC091nr+vu2TVVOudRxXNLax99mvn7pN2W3zLygWcj0k8mVreVZz26kv23vR6fjB/R1ftQ5bp+bWZyXdtde01p4RGu+ri71v0B9ceo+n9TgvHlOnp75eoFdL3L/M2lK+zw3deuZ3joPqhfpd209+NmZb66kbeScred46vibcrPM3LdZyHTL5KikPlvzr0n77a5ZHFg20v+BG1xH5eF5TP0sqVI/Y+r/ZZU6//XZoLWWUc/ne7Y2dkzmT2kt/3Lm28//rVrrujL7ZzmQC3oHU79HPpLUcbfL47LwF62K72X+Y61lswQIECBAYGoC9ULgiKReGLRzapbrRcu3k3qB0F5X85clt0uaUm+zado8tqnsm9ZfAY9vtattvDp5TlIvNJvH1/Sfkv5y31S029T8k1qN3tO3/vwst19oVNOd+trUYOTlycOTKvX2vfY+rqts/dPfh+1b60bNPisr29utAd0Lkr9JyrpZd3Hm90na5YdZaNa3j7fdZpz5ehHWbOdVm3nAevu7kXP8ilb/Lsn8S5K3tPr5pdb6F7bqm9lPt9b/n6ZyzGm9SDuh9fhyquf9nkl/+dNUNI41rQHvfZJfSuq5fHnSrH905scpR6ZR85j6w8VpvZyR6YWtdU2bT6Suv6z3nK3neMqrXtg3/flB5h+T3D+pc9bU17Rsxinr7X9t+wlJs8/Tx9nZkDafa22n2d5/DGlb1Qf3td+y1XbU8/nP+h5Xfzi4RfLE5OSk2XdND02aUv8nmnXV1/7SrKtp/8D0r1LXrP9C3wOPaq17cWvdQ1v19f+hv9w3Fc02azruz8PazjP7HluPr0HQR5MT+9bVvn8jUQgQIECAwMwE6pfaW5P2L7pR8/Xi/q59vTur9fjH9q1rL9YL6G+22g7az6ey/gbtB/Xm68VHvXe9/Zhbtdo9uW/d21rr2rNf72tX26sXM1WmNUCqbT89uSZp9789X4OjRyb95YepaNrNaoBUfVhvf9d7jn+rdZzN8dZ0p+pMyjQHSLX9/oHCh6tyQNkudfWX7HYfB82/P21qIDFOOTKNBm1jUN0H0/bmQza6nnO23uO5S/rQHnQP6uvfDennsOr19L+29YSk2f9GBkhPaW2n2d7v1w6GlFEDpFHP572yvfOTZh/taQ0GaoDc1NWgqCldGiDVMf1hUn8MaY512PSp1VghQIAAAQLzEKjBwfuSK5L+X1TnpO7w5EHJoDLuAKkeu2vyz8mxSXvAcGqWn5GMelH5r1nf9O2kzLdLDZaadTX97fbK1vy9Ml8vopq29Xa2v++tn+YAqXbxiOTfk/aLo7qSVi+4b5kMKvMaIFVf1tPfetx6zvHWedwbkua81LQGxPskVaY9QNot+2hf/fnN6/Y6+J9tU/28pJ6z7f7WfP1feHZSA49xy6gB0o+yka8k707uN8YG13PO1ns8ZVZXf9vP5zI4OakXv+sp6+n/pAZI9bxt//yrF++D/ljTHNeoAdLmns/1NrtvJ+3nz7eyfGDy+FZ9XVVpStcGSHVct0vqjxFnJ22LGih+ILlbohDorMCoFzydPWgHRmBJBerFUv2FunJVcmZyclK/sCZdbpQN3j75blK/IGdVtsqO6hdzvYitgVoNUmZZfi472zcp3+N700wWtmykv2s9x/UitZ4TP0hqALLIpVx2T/bsdfLkTGtAUy/05l3Wc842cjy3yAHXz4w6Z6ckG/15sZ7+Z7cLV0Y9n+sY9072SI5LZvkzMLtbuFLPn1snZyQnJTVYVQgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAwDIKbLmMnZ5gn/fOtvZPbpBckFyVKAQIECBAgAABAgQIEOikwJNzVIcn1+87un2z/JXk2lbOz/xzk1UfNIZAIUCAAAECBAgQIECgiwJvyEHVIGjn1sHtmfkaDFV9DZJendQg6tSk6l6RKAQIECBAgAABAgQIEOicwKAB0ttzlDUQenrf0W6f5WbdA/rWWSRAgAABAgQIECBAgMDSCwwaIJ2Uo/rSkCOrt+Kdnbx0yHrVBAgQIECAAAECBAh0WODnOnxsww5tp6z45pCVl6b+uOROQ9arJkCAAAECBAgQIECgwwKrOEA6OuezbtIwqOyaynskZwxaqY4AAQIECBAgQIAAgW4LbNXtw/vZ0X05c19NanB0VPK/kt9IPpg0Za/MvCzZJjmiqZzh9O7Z19Yz3J9dESBAgAABAgQIEJiUwBXZUL3WXvqyxdIfwegDeHhWH5rcJblFX9MfZrkGRVUekrw/qQFjDaDuldSNHGZVanBUd9RTCBAgQIAAAQIECCyrQL2mXfpBUtevIL0nJ6lSpW71XQOlJu3BYX33UX3+6B3Js5KNDo52zDaek4x7RagZqN0gj6nRt0KAAAECBAgQIEBgWQTqHVgXJTVd+tL1AVL7BF2QhXrrXKW/fCIV9fmjK/tXrHN5hzzubsm4T5I9evupgZkBUg/DhAABAgQIECBAgACB2Qtsm13eNqmrSPMqh2XHNTiqgZVCgAABAgQIECBAYJkE6qJAvZY9YJk6Payvq3IXu/r80VOShyX19rcquyf19ruzk+OTC5OXJOO+LS5NFQIECBAgQIAAAQIECCyXQPOZohrVVk5Kdkve2Vs+L9N/T07vLVf9rIsrSLMWtz8CBAgQIECAAIFJCXTqCtKkUBZ1O7+ajl2TfCt5ZvLs5JykrhjVYOlPk+snVbZL3pJU/YOSWRYDpFlq2xcBAgQIECBAgMAkBQyQJqk55W29JtuvO2q0P9vzW1muQVDd5rv/c0c1WPpx8vfJLIsB0iy17YsAAQIECBAgQGCSAp0aIHX9M0j758x/LLmk9Qz4j8xflnw4ubpVX7N1q+/jktvUgkKAAAECBAgQIECAwGoJdH2AVJ8vqkFS+zh/kuUXJN9J+ssNU3GPpD6PpBAgQIAAAQIECBAgQKBTAs/L0dTb6eotczfdzJFtnfX/nFT7R2+m7aRXe4vdpEVtjwABAgQIECBAYFYCnXqL3azQ5rWfuvHC0UkNeuptdbskg8ohqfxRUu0+lWyRzLIYIM1S274IECBAgAABAgQmKdCpAVL7rWeTRFqUbdWg6F7JS5JjknrL3aBSN3GoE/vK5MFJDZQUAgQIECBAgAABAgQIrKRA3b2u/452s4RwBWmW2vZFgAABAgQIECAwSYFOXUHaapIyS7ytunudQoAAAQIECBAgQIDAigt0/S12K356HT4BAgQIECBAgAABAmsRMEBai5a2BAgQIECAAAECBAh0WsAAqdOn18ERIECAAAECBAgQILAWAZ9BWouWtgQIECBAgAABAgSWQ+BW6eaTk/163a2vvnlN8v3esskQAVeQhsCoJkCAAAECBAgQILCkAo9Lv7+d3Dc5qpear7rHJQqBhRdwm++FP0U6SIAAAQIECBBYCoEaCF2VPHVAb6uu1lWbSZZO3eZ7kjC2tX4BA6T123kkAQIECBAgQIDAfwt8NrP/+t+L/2Ou1lWbSRYDpElq2tZ1AgZInggECBAgQIAAAQIbFdg+G7g6ufeIDdW6alNtJ1U6NUDyGaRJPS1shwABAgQIECBAgMB8BXbK7uv1/VkjulHrqk21VQYIGCANQFFFgAABAgQIECBAYAkFfpw+X5zcaUTf9+21qbbKAAEDpAEoqggQIECAAAECBAgsoUC9de5dyZ8l9ba3/lJ1z0uqTbVVCCysgM8gLeyp0TECBAgQIECAwFIJ7J7enpZ8LNknaco+mam6WldtJll8BmmSmrZFgAABAgQIECBAgMDEBM7IlupGDPUZoxOT43qp+aqrddVGGSKw1ZB61QQIECBAgAABAgQILKdADYYOTO6R7Nc7hKMz/Upv3mSEgAHSCByrCBAgQIAAAQIECCyxQA2IDIrWeALdpGGNYJoTIECAAAECBAgQINBdAQOk7p5bR0aAAAECBAgQIECAwBoFDJDWCKY5AQIECBAgQIAAAQLdFTBA6u65dWQECBAgQIAAAQIECKxRwABpjWCaEyBAgAABAgQIECDQXQEDpO6eW0dGgAABAgQIECBAgMAaBQyQ1gimOQECBAgQIECAAAEC3RUwQOruuXVkBAgQIECAAAECBAisUcAAaY1gmhMgQIAAAQIECBAg0F0BA6TunltHRoAAAQIECBAgQIDAGgUMkNYIpjkBAgQIECBAgAABAt0VMEDq7rl1ZAQIECBAgAABAgQIrFHAAGmNYJoTIECAAAECBAgQINBdAQOk7p5bR0aAAAECBAgQIECAwBoFDJDWCKY5AQIECBAgQIAAAQLdFdiqu4fmyAgQIECAAAECBAisrMBeOfInJfv1BI7O9LXJKb1lkyECriANgVFNgAABAgQIECBAYEkFDk2/j08eknyzl5qvulqnEFh4gcPSw2uTHRa+pzpIgAABAgQIECCwyAL3TOeuTP54QCerrtZVm0mWbbKxei17wCQ3alurLWCAtNrn39ETIECAAAECBCYl8Ols6E0jNlbrqs0kS6cGSD6DNMmnhm0RIECAAAECBAgQmJ/A9bPr+yT3G9GFN2bdp5Jqe+mIdiu7ymeQVvbUO3ACBAgQIECAAIGOCdwwx1Ov788YcVxn9tpUW2WAgAHSABRVBAgQIECAAAECBJZQ4Mfp8yXJHUf0/Q69NtVWGSBggDQARRUBAgQIECBAgACBJRS4Kn1+T/K8ZNBHaaqu1lWbaqsQWFgBN2lY2FOjYwQIECBAgACBpRLYI72tt9F9KKn5ptR81dW6dn2zfiPTTt2kwRWkjTwVPJYAAQIECBAgQIDAYgmclu7UjRp2T36QHNNLzVddras2yhCBQZfehjRVTYAAAQIECBAgQIDAEgh8N328R3LPZL9ef4/O9PNJfV+RMkLAAGkEjlUECBAgQIAAAQIEllSgBkKf62VJD2E+3fYWu/m42ysBAgQIECBAgAABAgsoYIC0gCdFlwgQIECAAAECBAgQmI+AAdJ83O2VAAECBAgQIECAAIEFFDBAWsCToksECBAgQIAAAQIECMxHwABpPu72SoAAAQIECBAgQIDAAgoYIC3gSdElAgQIECBAgAABAgTmI2CANB93eyVAgAABAgQIECBAYAEFDJAW8KToEgECBAgQIECAAAEC8xEwQJqPu70SIECAAAECBAgQILCAAgZIC3hSdIkAAQIECBAgQIAAgfkIGCDNx91eCRAgQIAAAQIECBBYQAEDpAU8KbpEgAABAgQIECBAgMB8BAyQ5uNurwQIECBAgAABAgQILKCAAdICnhRdIkCAAAECBAgQIEBgPgIGSPNxt1cCBAgQIECAAAECBBZQwABpAU+KLhEgQIAAAQIECBAgMB8BA6T5uNsrAQIECBAgQIAAAQILKGCAtIAnRZcIECBAgAABAgQIEJiPgAHSfNztlQABAgQIECBAgACBBRQwQFrAk6JLBAgQIECAAAECBAjMR8AAaT7u9kqAAAECBAgQIECAwAIKGCAt4EnRJQIECBAgQIAAAQIE5iNggDQfd3slQIAAAQIECBAgQGABBQyQFvCk6BIBAgQIECBAgAABAvMRMECaj7u9EiBAgAABAgQIECCwgAIGSAt4UnSJAAECBAgQIECAAIH5CBggzcfdXgkQIECAAAECBAgQWEABA6QFPCm6RIAAAQIECBAgQIDAfAQMkObjbq8ECBAgQIAAAQIECCyggAHSAp4UXSJAgAABAgQIECBAYD4CBkjzcbdXAgQIECBAgAABAgQWUGCrBezTtLu0S3awc7JtcnFyfnJJohAgQIAAAQIECBAgsOICq3IF6a45z69PzkrOTU5KjktOTWqQ9P3kNcluiUKAAAECBAgQIECAwIoKrMIVpL/IuX1R7/yekukXkhok1cCoriTdKNkreVJySPLM5PBEIUCAAAECBAgQIECAQKcEfidHc23y0eRuI45si6y7T/KVpNofmMyyHJad1X53mOVO7YsAAQIECBAgQIDABAS2yTbqtewBE9iWTUxZ4O3Zfr19rj5vNE6pzyddmLx6nMYTbGOANEFMmyJAgAABAgQIEJipQKcGSF3/DNKd89Sot9RdPuZT5Ly0OybZY8z2mhEgQIAAAQIECBAg0CGBrg+Qzsi52i/ZesxzVleQalBVN3BQCBAgQIAAAQIECBBYMYGuD5DenPN5++S9yf4jzm19BuneyceS7ZP3JwoBAgQIECBAgAABAism0PW72NXd6H4++evk15PTkrq19zlJfdZop+RGyd7J7slVyZ8kn08UAgQIECBAgAABAgQIdFLgljmqdyQ1QKo7bLRTXxJ7QvLyZM9kkqWuTI2Tw9Ku+uQudpPUty0CBAgQIECAAIFZCHTqJg2zAFu0fdRVoxoI3Sap70GaRrlVNnpl0h6IjTNvgDSNs2GbBAgQIECAAAEC0xTo1ACp62+xG/REqLfWVZpStwDfO6nbgV/dVG5wemIef++knizjlIem0XPGaagNAQIECBAgQIAAAQIENipwi2zgKcnDkh17G6vPHL0nuSipqzv1VruXJFsnsy7eYjdrcfsjQIAAAQIECBCYlECnriBNCmWRt/OsdK799raTsrxb8s5efX330b8np/eWq37WxQBp1uL2R4AAAQIECBAgMCkBA6RJSc5gO7+afVyTfCt5ZvLspO5gd3xSg6Y/Ta6fVNkueUtS9Q9KZlkMkGapbV8ECBAgQIAAAQKTFDBAmqTmlLf1mmy/3kLXvvnBb2W5BkE/TLZM2qUGSz9O/r5dOYN5A6QZINsFAQIECBAgQGCFBH4xx/ra5Ohear7qplE6NUDq+hfF1pfD1pe/1ueLmvIfmbks+XDSf1OGS1N3XHKbRCFAgAABAgQIECCwjAL1zqn/SvZJDu+l5muwVOuUFRb4dI79lKR/IFhfBjvoyXHD1Nfg6XXJLIsrSLPUti8CBAgQIECAQHcF6iMmVyWPHnCIh/bWVZtJlk5dQZokzCJu63npVL2drt4yd9PNdHDrrP/npNoPekJt5uEbWm2AtCE+DyZAgAABAgQIEOgJfDHTV43QqHXVZpLFAGmSmlPe1nbZfl1KrEFPXRnaJRlUDknlj5Jq96lki2SWxQBpltr2RYAAAQIECBDopkB97r5uUHbgiMOrddWm/Rn9Ec3HWtWpAVL/W8/GEliiRjUoulfykuSYpG7pPajUE6RO7CuTByc1UFIIECBAgAABAgQILJPADdLZ+kP/OSM6XeuqTbVVCAwVqLvX9d/RbmjjKaxwBWkKqDZJgAABAgQIEFgxgXo9e34y6uMita7aTPK1rytIAe1aqbvX9d/RrmvH6HgIECBAgAABAgS6LVCvZw9Pnp803/XZPuKqq3XVxmvftoz5hRNwBWnhTokOESBAgAABAgSWUmDX9PrE5HPJnVtHUN+B9Pmk1lWbSRZXkCapaVsECBAgQIAAAQIECExMoD5jVJ/Bvyj5RnJmL1/P9MKk1o36jFJWr3bZarUP39ETIECAAAECBAgQ6JzA6TmiX0tuk+zXO7qjMz2hN28yQsAAaQSOVQQIECBAgAABAgSWWKAGRAZFazyBXb/N9xo5NCdAgAABAgQIECBAYJUFDJBW+ew7dgIECBAgQIAAAQIENhEwQNqEwwIBAgQIECBAgAABAqssYIC0ymffsRMgQIAAAQIECBAgsImAAdImHBYIECBAgAABAgQIEFhlAQOkVT77jp0AAQIECBAgQIAAgU0EDJA24bBAgAABAgQIECBAgMAqCxggrfLZd+wECBAgQIAAAQIECGwiYIC0CYcFAgQIECBAgAABAgRWWcAAaZXPvmMnQIAAAQIECBAgQGATAQOkTTgsECBAgAABAgQIECCwygIGSKt89h07AQIECBAgQIAAAQKbCBggbcJhgQABAgQIECBAgACBVRYwQFrls+/YCRAgQIAAAQIECBDYRMAAaRMOCwQIECBAgAABAgQIrLKAAdIqn33HToAAAQIECBAgQIDAJgIGSJtwWCBAgAABAgQIECBAYJUFDJBW+ew7dgIECBAgQIAAAQIENhEwQNqEwwIBAgQIECBAgAABAqssYIC0ymffsRMgQIAAAQIECBAgsImAAdImHBYIECBAgAABAgQIEFhlAQOkVT77jp0AAQIECBAgQIAAgU0EDJA24bBAgAABAgQIECBAgMAqCxggrfLZd+wECBAgQIAAAQIECGwiYIC0CYcFAgQIECBAgAABAgRWWcAAaZXPvmMnQIAAAQIECBAgQGATAQOkTTgsECBAgAABAgQIECCwygIGSKt89h07AQIECBAgQIAAAQKbCBggbcJhgQABAgQIECBAgACBVRYwQFrls+/YCRAgQIAAAQIECBDYRMAAaRMOCwQIECBAgAABAgQIrLKAAdIqn33HToAAAQIECBAgQIDAJgIGSJtwWCBAgAABAgQIECBAYJUFDJBW+ew7dgIECBAgQIAAAQIENhEwQNqEwwIBAgQIECBAgAABAqssYIC0ymffsRMgQIAAAQIECBAgsImAAdImHBYIECBAgAABAgQIEFhlAQOkVT77jp0AAQIECBAgQIAAgU0EDJA24bBAgAABAgQIECBAgMAqCxggrfLZd+wECBAgQIAAAQIECGwiYIC0CYcFAgQIECBAgAABAgRWWcAAaZXPvmMnQIAAAQIECBAgQGATga02WbJAgAABAgQIECBAgEAXBG6Tg3hKsl/vYI7O9NXJCb1lkyECriANgVFNgAABAgQIECBAYEkF/iD9PjY5MPlMLzVfdbVOIbDwAoelh9cmOyx8T3WQAAECBAgQIEBgkQUOSueuSp40oJNP7q07aMC6jVRtkwfXa9kDNrIRjyXQFjBAamuYJ0CAAAECBAgQWK/AkXng60Y8uNZVm0kWA6RJatrWdQIGSJ4IBAgQIECAAAECGxXYPhu4Jrn3iA3VumpTbSdVOjVA8hmkST0tbIcAAQIECBAgQIDAfAV2yu63SM4a0Y1aV22qrTJAwABpAIoqAgQIECBAgAABAkso8OP0+aJk3+ThyWeTS3qp+aqrddWm2ioDBNzmewCKKgIECBAgQIAAAQJLKHB1+vyu5J+TukL0muRlSZWDk7clFybVptoqAwQMkAagqCJAgAABAgQIECCwpALHpN+PT76a/ENyYlLlO8kvJ3dPqo0yRMBb7IbAqCZAgAABAgQIECCwhAL15bCvSq5MvpfUF8NWar7qal21UQgstIC72C306dE5AgQIECBAgMBSCNwwvazvI7pbr7f7ZVqvMytNXU2rzc7JpEqn7mLnLXaTelrYDgECBAgQIECAAIH5Cmzd2/1lvenRmVbapVlXgxplgIC32A1AUUWAAAECBAgQIEBgCQXOTp/PTO4zou+1rtpUW2WAgAHSABRVBAgQIECAAAECBJZQoN4697rkBclNBvS/6mpdtam2CoGFFfAZpIU9NTpGgAABAgQIEFgqge3S26OSk5JHJvW5pErNV12tqzaTLJ36DNIkYWxr/QIGSOu380gCBAgQIECAAIFNBbbP4t8lFyd1pahS81V3/WTSxQBp0qK2d92dReqJuwMLAgQIECBAgAABAhMSqCtFd+ll0leN2l3s1ADJXezap9Y8AQIECBAgQIAAge4I1B3rvt6dw5nNkbhJw2yc7YUAAQIECBAgQIAAgSUQMEBagpOkiwQIECBAgAABAgQIzEbAAGk2zvZCgAABAgQIECBAgMASCBggLcFJ0kUCBAgQIECAAAECBGYjYIA0G2d7IUCAAAECBAgQIEBgCQTcxW4JTpIuEiBAgAABAgQIEFijwI5pX18Ou1/vcUdn+s6kvg9JGSHgCtIIHKsIECBAgAABAgQILKHAQenz95KXJrv1UvNVd1CiEFh4gcPSQ18Uu/CnSQcJECBAgAABAgsvcMf08JLk75P2l8PWfNXVumozydKpL4qdJIxtrV/AAGn9dh5JgAABAgQIECDw3wIfzOyH/nvxf8x9ODXVZpLFAGmSmrZ1nYABkicCAQIECBAgQIDARgVqoHJFcvCIDT2o16baTqp0aoC06p9B2jvPinoC3SW5/qSeIbZDgAABAgQIECBAYA4Cu2afWycnj9j3Sb021VYZIND1AdKTc8yHJ/2Dn31T95Xk5OTjydeSM5LnJlsmCgECBAgQIECAAIFlEzgnHa4rSLcc0fFaV22qrbKCAm/IMdfND3ZuHfuemT+/V1+DpFcnNYg6tVf3ikxnXbzFbtbi9keAAAECBAgQ6KbAv+WwPjri0GpdtZlk6dRb7CYJs4jbGjRAens6WoOmp/d1ePssN+se0Ldu2osGSNMWtn0CBAgQIECAwGoI/EIO86Lkn5N6fduUmq+6Wnf7pnJCUwOkCUHOYjODBkj1vssvDdl5vRXv7OSlQ9ZPq9oAaVqytkuAAAECBAgQWD2Be+WQ691R9Ta6D/RS81VX6yZdOjVA2mrSOkuwvZ3Sx/8c0s9LU39ccqch61UTIECAAAECBAgQWHSBz6WDt00OSfbrdfY9mb43+Ulv2WSIwCoOkI6Oxb5DPHZN/T2SNw1Zr5oAAQIECBAgQIDAMgjUQOitvSxDfxemj12/i10D/eXM1OeLnp0cldw9+Y2kXfbKwquSukR4RHuFeQIECBAgQIAAAQIECHRB4OE5iPclJyZ1Y4Z2TslyUx6SmSuTWv/5ZItklsVnkGapbV8ECBAgQIAAAQKTFPAZpElqTnlb9V7LSpW61Xd9IWyT9iCovvuoPn/0juRZSQ2UNlLqLiFPT+rJMk5p3hs6TlttCBAgQIAAAQIECBCYksAqfQbpghjWW+cGvX3uE6mvzx/VVaRJlBqM/Wqy9Zgbu8mY7TQjQIAAAQIECBAgQIDAxAQ295mrupK0S7LdxPY43oa8xW48J60IECBAgAABAgQWT6BTb7Hb3IBh8fjX3qO6OvPO5NzkwuTTyT2TQaXublftnjtopToCBAgQIECAAAECBLot0PUB0o45fV9JHpHU1aFTk/smn01ekigECBAgQIAAAQIECBD4mUDXB0jPyZHumbwouXly+6S+5+hbyfOTVyQKAQIECBAgQIAAAQIErhPo+gDpwBzlWclfJxddd8TXu159Uex9kiOTumNdDaIUAgQIECBAgAABAgQIXK/rA6Q9co5rIHRV37muO9o9NDkmeVlSb8FTCBAgQIAAAQIECBBYcYGuD5B+kPP7gGTQXenqhg0PTupzSW9Oht24IasUAgQIECBAgAABAgRWQaDrA6T/zEms7yR6aXKzASf0tNQ9MKm33/178pBEIUCAAAECBAgQIECAQCcF6srRscm1ydXJo5JB5S6pPC+pdpUXJrMsvgdpltr2RYAAAQIECBAgMEkB34M0Sc0pb+uybH//5JXJKckVyaDy9VTePfnYoJXqCBAgQIAAAQIECBAg0EWBcd5SWLcBry+MnWVxBWmW2vZFgAABAgQIECAwSYFOXUHaapIyS7Cta8boY32xrEKAAAECBAgQIECAwAoKjHNFZQVZHDIBAgQIECBAgAABAqsoYIC0imfdMRMgQIAAAQIECBAgMFDAAGkgi0oCBAgQIECAAAECBFZRwABpFc+6YyZAgAABAgQIECBAYKCAAdJAFpUECBAgQIAAAQIECKyigAHSKp51x0yAAAECBAgQIECAwEABA6SBLCoJECBAgAABAgQIEFhFAQOkVTzrjpkAAQIECBAgQIAAgYECBkgDWVQSIECAAAECBAgQILCKAgZIq3jWHTMBAgQIECBAgEDXBR6UA/xIcmYvNV91ymYEDJA2A2Q1AQIECBAgQIAAgSUT+N/p74eTs5I/7qXmq67WKQQWXuCw9PDaZIeF76kOEiBAgAABAgQILLLAo9K5y5L7Dejk/Xvrqs0kyzbZWL2WPWCSG7Wt1RYwQFrt8+/oCRAgQIAAAQKTEjgmG/qbERurddVmkqVTAyRvsZvkU8O2CBAgQIAAAQIECMxPYKfset/kfSO6UOuqTbVVBggYIA1AUUWAAAECBAgQIEBgCQW26/X54t60Xuvv1Uvzur9Z17TtNTVpBLZqZkwJECBAgAABAgQIEFhqgR+n95V7Jw9PnpbcJKnyo+RVSd2soWmXWaVfwACpX8QyAQIECBAgQIAAgeUUqBslvCn5+6SuFP1l8h9JlYOTFyU7Jv+YVFtlgIAB0gAUVQQIECBAgAABAgSWVOCi9Hvr5MLk5OSUpMrJSdXdMGneZpdZhcBiCriL3WKeF70iQIAAAQIECCybQA2I/jR5fXJFcnUvNV91z02aQVNmJ1I6dRe7iYjYyIYFDJA2TGgDBAgQIECAAIGVF7hxBOqtc3fqSdTVovo8UqXmq9S6alNtJ1U6NUDyFrtJPS1shwABAgQIECBAgMB8Ba7p7X7L3vT8TI/s61Kzrq4sKQMEmtv9DViligABAgQIECBAgACBJRI4N339fvLgEX2uddXmvBFtrCIwdwFvsZv7KdABAgQIECBAgEAnBOrW3hckzdvs2gdVdbWu2kyydOotdpOEsa31Cxggrd/OIwkQIECAAAECBP5bYIvMHp7UHevqNt8H9FLzVVfrqs0kiwHSJDVt6zoBAyRPBAIECBAgQIAAgUkJ1ADoycmxSd2QoVLzVTfpwVE2eT0DpFJQJipggDRRThsjQIAAAQIECBDoCWyXaWWapVMDJHexm+ZTxbYJECBAgAABAgQIzFfgsvnufvn27i52y3fO9JgAAQIECBAgQIAAgSkJGCBNCdZmCRAgQIAAAQIECBBYPgEDpOU7Z3pMgAABAgQIECBAgMCUBHwGaUqwNkuAQKcF6mfnI5ODk12SE5N3JF9KFAIECBAgQGCJBVxBWuKTp+sECMxFYK/s9ejkn5ItkxOSOyRHJa9Oqk4hQIAAAQIEllTAFaQlPXG6TYDAXATqNqb/nvw4uV9yTtKUAzPzweTc5PlNpSkBAgQIECBAgMDaBXwP0trNPILAPASelJ3W4OiGQ3b+sNRfntxkyHrVBAgQIECgiwL1B8T6MtoDunBw3mLXhbPoGAgQmJXAr2VH707OH7LD96f+guT+Q9arJkCAAAECBBZcwABpwU+Q7hEgsFACu6U3p4/oUf317IzkxiPaWEWAAAECBAgssIAB0gKfHF0jQGDhBH6QHt1uRK/qLQa3SE4Z0cYqAgQIECBAYIEFDJAW+OToGgECCydQb697eHLrIT17WuqvSj45ZL1qAgQIECBAgACBMQTcpGEMJE0ILIjAR9KP7ye/1OpP3dr76ckVyeNb9WYJECBAgMAqCHTqJg2rcMKW4RgNkJbhLOkjgZ8KbJ/JW5Nrku8kn0nOSi5M6v+yQoAAAQIEVk2gUwMk34O0ak9fx0uAwEYFfpINPCZ5afLAZJfkX5O6slTfgaQQIECAAAECSyxggLTEJ0/XCRCYq0BdPaooBAgQIECAQIcE3KShQyfToRAgQIAAAQIECBAgsDEBA6SN+Xk0AQIECBAgQIAAAQIdEjBA6tDJdCgECBAgQIAAAQIECGxMwABpY34eTYAAAQIECBAgQIBAhwQMkDp0Mh0KAQIECBAgQIAAAQIbEzBA2pifRxMgQIAAAQIECBAg0CEBA6QOnUyHQoAAAQIECBAgQIDAxgR8D9LG/DyaAAECBAgQIECAwKIK3DEd26/XuaMzPXZRO6pfBPoFDkvFtckO/SssEyBAgAABAgQIEFijwJ5p/59Jvb48pZear7paN+myTTZY2z9g0huex/a8xW4e6vZJgAABAgQIECBAYDoCu2Wzn0u2TO6Q7NVLzVddras2CoGFFnAFaaFPj84RIECAAAECBJZG4DXp6deT7Qb0uOq+kVSbSZZOXUGaJIxtrV/AAGn9dh5JgAABAgQIECDwU4G6QnRB8sgRILWu2lTbSZVODZC8xW5STwvbIUCAAAECBAgQIDBfgXrr3E5JXUEaVmpdtfE2uyFCBkhDYFQTIECAAAECBAgQWDKBi9LfulnCjUf0u9ZVm2qrDBAwQBqAoooAAQIECBAgQIDAEgpckj5/Mfm9EX2vddWm2ioEFlbAZ5AW9tToGAECBAgQIEBgqQQekN5elTx2QK+rrtZVm0mWTn0GaatJytgWAQIECBAgQIAAAQJzFfhk9v6M5F+TxycfT6o8KLlXUuuqjTJEwFvshsCoJkCAAAECBAgQILCkAv+Sft85+VbyG73UfNXVOmWEgCtII3CsIkCAAAECBAgQILCkAt9Ov5++pH2fa7ddQZorv50TIECAAAECBAgQILBIAgZIi3Q29IUAAQIECBAgQIAAgbkKGCDNld/OCRAgQIAAAQIECBBYJAEDpEU6G/pCgAABAgQIECBAgMBcBQyQ5spv5wQIECBAgAABAgQILJKAAdIinQ19IUCAAAECBAgQIEBgrgIGSHPlt3MCBAgQIECAAAECBBZJwABpkc6GvhAgQIAAAQIECBAgMFcBA6S58ts5AQIECBAgQIAAAQKLJGCAtEhnQ18IECBAgAABAgQIEJirgAHSXPntnAABAgQIECBAgACBRRIwQFqks6EvBAgQIECAAAECBAjMVWCrue59PjvfJbuODUpoAABAAElEQVTdOdk2uTg5P7kkUQgQIECAAAECBAgQWHGBVbmCdNec59cnZyXnJiclxyWnJjVI+n7ymmS3RCFAgAABAgQIECBAYEUFVuEK0l/k3L6od35PyfQLSQ2SamBUV5JulOyVPCk5JHlmcniiECBAgAABAgQIECBAoFMCv5OjuTb5aHK3EUe2RdbdJ/lKUu0PTGZZDsvOar87zHKn9kWAAAECBAgQIEBgAgLbZBv1WvaACWzLJqYs8PZsv94+V583GqfU55MuTF49TuMJtjFAmiCmTREgQIAAAQIECMxUoFMDpK5/BunOeWrUW+ouH/Mpcl7aHZPsMWZ7zQgQIECAAAECBAgQ6JBA1wdIZ+Rc7ZdsPeY5qytINaiqGzgoBAgQIECAAAECBAismEDXB0hvzvm8ffLeZP8R57Y+g3Tv5GPJ9sn7E4UAAQIECBAgQIAAgRUT6Ppd7OpudD+f/HXy68lpSd3a+5ykPmu0U3KjZO9k9+Sq5E+SzycKAQIECBAgQIAAAQIEOilwyxzVO5IaINUdNtqpL4k9IXl5smcyj3JYdlp9che7eejbJwECBAgQIECAwEYEOnWThq5fQWpO9ImZeXRvoa4a1fcfbZfUF8dekEy61IDsa8nWY254yzHbaUaAAAECBAgQIECAwBQFVmWA1BDWZ67qrXWVQaUGKjWAujS5bFCDMetOTrvfTmo0PU55UBr90TgNtSFAgAABAgQIECBAgMBGBG6SB78zOTe5OPl0cs9kULlLKuutbn85aOUU67zFboq4Nk2AAAECBAgQIDBVgU69xa7rd7HbMU+FrySPSOrqUN2g4b7JZ5OXJAoBAgQIECBAgAABAgR+JtD1AdJzcqR144UXJTdP6pbf90i+lTw/eUWiECBAgAABAgQIECBA4DqBrg+QDsxR1o0Y/jq56Lojvt71js70PsmRybOSGkQpBAgQIECAAAECBAgQuF7XB0h75BzXQKi+36hd6s51D02OSV6W1FvwFAIECBAgQIAAAQIEVlxgPXexu1/MHpPUF7BeP9ki6S9vSsWb+yvnsPyD7PMBSd3Su/+udHUnuwcnX0iqr6cl9Z1ICgECBAgQIECAAAECBMYSqCstdZe3zeWFY21t+o3+v15f67NGNxuyu9ulvvk+pD/vtXcXuyFYqgkQIECAAAECBAj0CXTqLnZ9x7bZxePTom6VfWiye1J3hhuUQVeV0nTmpa4cHZvUgO7q5FHJoFK39z4vaQZ+LxzUaIp1bvM9RVybJkCAAAECBAgQmKpApwZIa/kM0g5hvU3y1uTw5IykBh2DUgONRSj1trr9k1cmpyRXJIPK11N59+Rjg1aqI0CAAAECBAgQIECAQL9ADabOT17ev2KJlscZENZtwPed8TG5gjRjcLsjQIAAAQIECBCYmMDKXkG6JoRHJI9OxhloTEx8ghuqY9hcqS+W/ebmGllPgAABAgQIECBAgED3BNY60KkrHT9J3pPUdwntlew6IHV3O4UAAQIECBAgQIAAAQKdFvhijq6+Q6i5mcGw6Qs7rTD5g/MWu8mb2iIBAgQIECBAgMBsBDr1Fru1fg/S12J8+hjO3xmjjSYECBAgQIAAAQIECBBYKIG1DpCeulC91xkCBAgQIECAAAECBAhMUGCtn0Fq77o+Z1R3e6vbaFep24ArBAgQIECAAAECBAgQWFqB9QyQ6sYM70ouSY5Jmtt+vy3zf51smygECBDoukBdga/vT3tgcquuH6zjI0CAAAECBAYL7J7qs5O6OcO3k5OTI5Mq70+q/lvJdokyvoCbNIxvpSWBRRCotxufldTPvPoC6pp+OakBk0KAAAECBFZNoFM3aVjryXt3HlBXju7Ve+D7Mm0GSFtmvq4g1QuFJyfK+AIGSONbaUlg3gJ/kw7U1x38cbJLrzO3y/TtyaXJgb06EwIECBAgsCoCKz1AOjdn+f+0znR7gFTVWyfnJ2+sBWVsAQOksak0JDBXgXtk7/WF0w8c0ovXpv6EpN5+pxAgQIAAgVUR6NQAaS2fQdopZ7j+Wnr8iDN9ZdYd22s3oplVBAgQWEqBP0ivP558Ykjvn5f6vZP6Im2FAAECBAgQWEKBtQyQLszxnZnUX1CHlRpE3TE5blgD9QQIEFhigTuk718Y0f+6yv7dpNopBAgQIECAwBIKrPVtIB/NMT4xqRsxvClplxtm4U3Jzsmwv65mlUKAAIGlFajPGO24md7X+mqnECBAgACBeQrUhZCDkv16nTg6088k9VZxZYICNQg6JakbMVyQ1BWl05L3J+ckVe/zR0FYYzks7cvOd0mtEU5zAjMWeEH2V28zrpvSDCr1S6j+L9dNGxQCBAgQIDAvgXonwzeSutPqV3up+aqbxrscOvUZpBitudw4j3h1cnlSLwSa1ADpGcmwFw5ZpQwRMEAaAqOawIIJ1M+/+ln3D8kWfX3bLcv13XDv6au3SIAAAQIEZimwZ3Z2VlI3U7tJa8c1X3W1rtpMsqz8AKnBrIHQLZMDk5s1labrEjBAWhebBxGYi8B9s9e6gv7F5A+TQ5IXJj9KvpzUlXaFAAECBAjMS+Ct2fHnk0EXLaruqKTaTLIYIE1S07auEzBA8kQgsFwCe6W7/5TULb3PTmpg9Kxk20QhQIAAAQLzEqj7C1yS/OaIDvxWr81a70UwYpPX69QAaXMw9cu+PuC11lK3+75qrQ/SngABAksiUJ/FfNqS9FU3CRAgQGB1BOrt3tsn3xlxyN/utam2Z4xot7KrNjf4+VJk6hvj15o/X1lRB06AAAECBAgQIEBgPgLnZ7dXJ6M+/lLrqk21VQYIbO4KUr1Hse5Ut9by/bU+QHsCBAgQIECAAAECBDYkUF8zcUTyxOQzyaBS66pNtVUILKyAzyAt7KnRMQIECBAgQIDAUgn8cnpbH3f506R9x9War7orkmozybJSn0GaJJxtESBAgAABAgQIECAwXYG6y+qhyZuS308+mVR5YLJP8rtJtVGGCGzuM0hDHqaaAAECBAgQIECAAIEFFXh3+nWb5F3JLXp5Z6+u1ikjBDb3GaQRD7WKAAECBAgQIECAAIEFFTg9/fqrBe3bQnfLFaSFPj06R4AAAQIECBAgQIDALAUMkGapbV8ECBAgQIAAAQIECCy0gAHSQp8enSNAgAABAgQIECBAYJYCBkiz1LYvAgQIECBAgAABAgQWWsAAaaFPj84RIECAAAECBAgQIDBLAQOkWWrbFwECBAgQIECAAAECCy1ggLTQp0fnCBAgQIAAAQIECBCYpYAB0iy17YsAAQIECBAgQIAAgYUWMEBa6NOjcwQIECBAgAABAgQIzFLAAGmW2vZFgAABAgQIECBAgMBCCxggLfTp0TkCBAgQIECAAAECBGYpsNUsd2ZfBAgQ6JDAzjmWxyY3TY5O3psoBAgQIECAAAECExA4LNu4NtlhAtuyCQIEpiuwRTb/oeSaXq7OtP7/Xpo8NVEIECBAgMCqCWyTA67fhQd04cC9xa4LZ9ExECAwS4H/ys4ekrw12S3ZMrlHclLyT8mzEoUAAQIECBAgQGADAq4gbQDPQwnMUOBJ2VddOXr6kH1+PfVXJNcfsl41AQIECBDookCnriB18QQt4zEZIC3jWdPnVRT4dg76zBEHvmfW1QDquSPaWEWAAAECBLom0KkBkrfYde3p6XgIEJimwM2y8W+N2MEPs+7yZL8RbawiQIAAAQIEFljAAGmBT46uESCwcAL19rm6e92oUncHvWhUA+sIECBAgACBxRUwQFrcc6NnBAgsnkDdzvsXk2GfMXpC1tVNG96WKAQIECBAgAABAusU8BmkdcJ5GIEZC+yV/dVtvb+TbN2373pbXb29ru5mpxAgQIAAgVUS6NRnkHxR7Co9dR0rAQIbFTglG6g72b02uSD5VHJactekBkj11roDE4UAAQIECBAgQGADAq4gbQDPQwnMQWDf7PNLyU+SK5Nzk7cm2yYKAQIECBBYNQFXkFbtjDteAgQI9Al8M8v799VZJECAAAECBDog4CYNHTiJDoEAAQIECBAgQIAAgckIGCBNxtFWCBAgQIAAAQIECBDogIABUgdOokMgQIAAAQIECBAgQGAyAgZIk3G0FQIECBAgQIAAAQIEOiBggNSBk+gQCBCYucAds8cvJJckVyTnJG9K3MUuCAoBAgQIEFhmAQOkZT57+k6AwDwE/iA7PSa5S3JE8uakvhz295Mzk5skCgECBAgQIECAwAYEfA/SBvA8lMAMBfbKvq5Ojku27tvv3bN8eXJiX71FAgQIECDQdYFOfQ+SK0hdf7o6PgIEJinw6mysBkh3TeoLYtvlq1l4erJP8iuJQoAAAQIECCyhgAHSEp40XSZAYG4CdZWo3l536ZAevC71NYD6vSHrVRMgQIAAAQILLmCAtOAnSPcIEFgogXoLwfmb6dFVWX+DzbSxmgABAgQIEFhQAQOkBT0xukWAwEIKnJFe1R3shpU9s6LuZHf0sAbqCRAgQIAAgcUWMEBa7POjdwQILJbAP6Q7dZe6pw3p1gdSX2+xe+WQ9aoJECBAgAABAgTGEHAXuzGQNCGwIAJfTz+uSd6Y7NLr036ZHptU/bN7dSYECBAgQGBVBDp1F7tVOWmLfpwGSIt+hvSPwH8LbJHZjyQ1GKrUFaNrk8uSYVeWskohQIAAAQKdFejUAGmrzp4mB0aAAIHpCNRg6CFJXT16XHLTpD5z9O6k1ikECBAgQIDAEgsYIC3xydN1AgTmKnBe9v53c+2BnRMgQIAAAQITF3CThomT2iABAgQIECBAgAABAssqYIC0rGdOvwkQIECAAAECBAgQmLiAAdLESW2QAAECBAgQIECAAIFlFTBAWtYzp98ECBAgQIAAAQIECExcwABp4qQ2SIAAAQIECBAgQIDAsgoYIC3rmdNvAgQIECBAgAABAgQmLmCANHFSGyRAgAABAgQIECBAYFkFfA/Ssp45/SZAYN4CB6YDByf1hbEnJu9LfpgoBAgQIECAwBILuIK0xCdP1wkQmIvADbPXDyefTR6Y7Jk8PTkheW6iECBAgAABAkss4ArSEp88XSdAYOYC9UelDyQ3Su6UHJc05dDMvD65NHllU2lKgAABAgQIECCwdoHD8pBrkx3W/lCPIEBghgKPyr4uTm4+ZJ/1f/nCZOch61UTIECAAIEuCmyTg6rXsgd04eC8xa4LZ9ExECAwK4GHZUfvSk4dssM3pv6apN56pxAgQIAAAQJLKLDqA6S9c87qQ9Z3Sa6/hOdPlwkQmK3AHtnd90fs8qqs+0FysxFtrCJAgAABAgQWWKDrA6Qnx/7wpH/ws2/qvpKcnHw8+VpyRlIfsN4yUQgQIDBI4MxU7pPU22H/OPlIclTytuQhSf1Mrbff/ShRCBAgQIAAAQILJ/CG9KjeD9n+PEDdcer8Xn0Nkl6d1CCq3jJTbV+RzLr4DNKsxe2PwPoEHpuH1WeM6ipR/cz4u+TPkvoZcnnypeQnya6JQoAAAQIEVkVgmxxovY7uxGeQun7SBg2Q3t47gXVb3nbZPgvNuge0V8xg3gBpBsh2QWACAjfINi5Lzk1u07e9p2T56qSuKCkECBAgQGCVBAyQluhsDxognZT+1195B5V6K97ZyUsHrZxinQHSFHFtmsAEBZ6ZbdXbcT+f1O28/z15Y/LVpAZH70jqc0jD7nKXVQoBAgQIEOicQKcGSF3/DNKgZ99OqfzmoBWpqxc89b0m9f0mCgECBPoFHpiKdyf3Sg5Jjk+2SD6Y3DF5dPLj5FcShQABAgQIEFhCga2WsM8b7fLR2UDdpGFQqc8N3CN506CV6ggQWHmBG0bgrKTeZ11Xjyr9pQZI1U4hQIAAAQIEllBgVa4gfTnn5u3Js5P6fMDdk99I2mWvLLwqqUuER7RXmCdAgEBP4MRM7zxCoz7LeKuk2ikECBAgQIAAgYUTeHh69L6kXqzUX3zbOSXLTXlIZq5Man19tqDeMjPLclh2VvveYZY7tS8CBNYs8KA8on5WDBsk/WXW1a3A6/OMCgECBAgQWBWBTn0GqetvsXtPnpWVKnWr77u00h4E1Xcf1eeP6gPWz0pqsLKRsl0e/ISknizjlP3HaaQNAQJzF/h4elA/U2pa/8c/mjR/3HhO5l+QPCKpnycKAQIECBAgsIQC7UHCEnZ/Yl2uv/bWnafqL8OTKHUHq3oRNe4A6UZpu3eyY3JJohAgsLgCW6drL0uekZyX1GeSbplckDwtqavWCgECBAgQWCWBes17eXJg8oVVOnDHOj0Bb7Gbnq0tE5iWwO7Z8KFJDYp+LakrxwoBAgQIEFhFAW+xW8Wz7pgJECDQJ3BGlg/vq7NIgAABAgQILLnAqtzFbslPk+4TIECAAAECBAgQIDALga7fpKHeurbTOiCPymO8f3IdcB5CYIUE6uYuv5jsktSdMk9KFAIECBAgQIDAQgt8Lb2rO0ytNX8546PyGaQZg9sdgQ0KPDmP/1FSP1uarwj4YubvligECBAgQGDVBHwGaYnOeH1wuu4odUDygeQNyTjl+HEaaUOAwEoKvCRHXV8HULf0fnNyTvILyV8kn0vun7gCHQSFAAECBAgQWEyBbdOt+stu3XrwrovZxeu5grSgJ0a3CPQJ3D3L1yQP6qtvFl+Xme8mXX/7cnO8pgQIECBAoAQ6dQVpVU7pHXOgNUCqv+4uYjFAWsSzok8E/qfAv6TqY/+z+mc1u2buiuRXflZjhgABAgQIdF+gUwOkVbmL3bF5Xj4/qRs27Nv956gjJEBgSgJ3yHbrJi7DSr3drq4gVTuFAAECBAgQWEKBVRkg1an52+TOyTdrQSFAgMA6BC7LY3bczONqfbVTCBAgQIAAgSUUWKUB0hKeHl0mQGDBBI5Mf34zqVt8Dyp1F7u9k0V9O++gPqsjQIAAAQIECCycgM8gLdwp0SECAwVunNpzk79LtuhrUeu+kby3r94iAQIECBDoukCnPoPkTktdf7o6PgIEJilwdjZ2SPL+ZP/kLUl9H1J9tvEPk1OTJyYKAQIECBAgQIDABgRcQdoAnocSmIPAPtln3dHu+0ldUfpq8ifJdolCgAABAgRWTcAVpFU7446XAAECfQInZ/mpfXUWCRAgQIAAgQ4IuElDB06iQyBAgAABAgQIECBAYDICBkiTcbQVAgQIECBAgAABAgQ6IGCA1IGT6BAIECBAgAABAgQIEJiMgAHSZBxthQABAgQIECBAgACBDggYIHXgJDoEAgQIECBAgAABAgQmI2CANBlHWyFAgAABAgQIECBAoAMCBkgdOIkOgQCBmQvsnj3+bXJM8sPkiOQpydaJQoAAAQIECCyxwFZL3HddJ0CAwDwEDsxOP5SckrwpOSvZN3lJ8nvJg5MLE4UAAQIECBAgQGCdAoflcdcmO6zz8R5GgMBsBHbJbmpA9Jqk/wp8XVX6TnJ4ohAgQIAAgVUS2CYHW69lD1ilg3as0xUwQJqur60TmJTAn2VD30uGXX3fP+vqF8StE4UAAQIECKyKQKcGSP1/AV2Vk+g4CRAgsB6B++RB70+uGvLgL6W+3npX7RQCBAgQIEBgCQUMkJbwpOkyAQJzE6i3wV6wmb3X54+230wbqwkQIECAAIEFFTBAWtATo1sECCykwHHpVb2Nbli5YVbcNql2CgECBAgQIECAwDoFfAZpnXAeRmDGAvXh06uTg4bs9x9Tf2Ky9ZD1qgkQIECAQBcFOvUZpC6eoGU8JgOkZTxr+ryqAq/IgV+UPDlp7jy5d+b/Nbk8uW+iECBAgACBVRIwQFqlsz2jYzVAmhG03RCYkMCzsp3zkrpZQ33mqO5cV18aW9+RpBAgQIAAgVUTMEBatTM+g+M1QJoBsl0QmLDAttnevZNfT+404W3bHAECBAgQWCaBTg2Qhn2XxzKdEH0lQIDAPATq7XRHzmPH9kmAAAECBAhMT8Bd7KZna8sECBAgQIAAAQIECCyZgAHSkp0w3SVAgAABAgQIECBAYHoCBkjTs7VlAgQIECBAgAABAgSWTMAAaclOmO4SIECAAAECBAgQIDA9AQOk6dnaMgECBAgQIECAAAECSyZggLRkJ0x3CRAgQIAAAQIECBCYnoAB0vRsbZkAAQIECBAgQIAAgSUTMEBashOmuwQIECBAgAABAgQITE/AAGl6trZMgAABAgQIECBAgMCSCRggLdkJ010CBAgQIECAAAECBKYnYIA0PVtbJkCAAAECBAgQIEBgyQQMkJbshOkuAQIECBAgQIAAAQLTEzBAmp6tLRMgQIAAAQIECBAgsGQCBkhLdsJ0lwABAgQIECBAgACB6QkYIE3P1pYJECBAgAABAgQIEFgyAQOkJTthukuAAAECBAgQIECAwPQEDJCmZ2vLBAgQIECAAAECBAgsmYAB0pKdMN0lQIAAAQIECBAgQGB6AgZI07O1ZQIECBAgQIAAAQIElkzAAGnJTpjuEiBAgAABAgQIECAwPQEDpOnZ2jIBAgQIECBAgAABAksmYIC0ZCdMdwkQIECAAAECBAgQmJ6AAdL0bG2ZAAECBAgQIECAAIElEzBAWrITprsECBAgQIAAAQIECExPwABpera2TIAAAQIECBAgQIDAkgkYIC3ZCdNdAgQIECBAgAABAgSmJ2CAND1bWyZAgAABAgQIECBAYMkEDJCW7ITpLgECBAgQIECAAAEC0xPYanqbtuUFE7hF+rNfr09HZ3rSgvVPdwgQIECAAAECBAgQIHCdwGH599pkhyl43CTb/GBv++dkWql9VV2tUwgQIECAAAECBAhsRGCbPLheXx6wkY0symO9xW5RzsR0+nGjbPbzyc8nd0927aXmq+5zSbVRCBAgQIAAAQIECBAgsDAC07qC9Koc4bHJ9gOOtOpqXbVRCBAgQIAAAQIECKxXoFNXkNaL4HGTFZjGAKmuDp6XHDqiq7Wu2riSOALJKgIECBAgQIAAgZECnRogeWE88lwv9cp6C90Nk7ohw7DyX1lRbXYb1kA9AQIECBAgQIAAgVUSMEDq7tm+uHdo9RmjGySvSL7YS81X3S5JlUt+OvEvAQIECBAgQIAAAQIE5i8wjbfY1VF9OflEcmVyTXJWLzVfdbWu2igECBAgQIAAAQIE1ivgLXbrlfO4mQt8IHu8f1IDo92TettdpearrtZVG4UAAQIECBAgQIAAAQILIzCtK0g/zBHWW+2uTj6S/FEvNV91ta7aKAQIECBAgAABAgTWK+AK0nrlPG6mAvWls3sk/yf5paSuGD2hl5qvulpXbabxBbXZrEKAAAECBAgQIEBguQS2Wq7u6u0aBG6dtlskdWOGupPd45P+Ul8cW22q7Tf6V1omQIAAAQIECBAgsGoC7mLX3TN+Yg7t2uSuIw6x1lWbaqsQIECAAAECBAgQIEBgIQSm9RmkH+XoTh9xhLXuzBHrrSJAgAABAgQIECCwOQGfQdqckPULI/CH6clNky8l12/1quarrtY9rVVvlgABAgQIECBAgAABAnMXmNYVpDqw5yZ1x7qrknorXaXmq67WKQQIECBAgAABAgQ2IuAK0kb0PHbmAi/LHvdJ3pVc0UvN75PUOoUAAQIECBAgQIAAgZ6Au9itxlOhvuvo0NU4VEdJgAABAgQIECBAYP0C7mK3fjuPJECAAAECBAgQIECgYwIGSB07oQ6HAAECBAgQIECAAIH1Cxggrd/OIwkQIECAAAECBAgQ6JiAAVLHTqjDIUCAAAECBAgQIEBg/QIGSOu380gCBAgQIECAAAECBDomYIDUsRPqcAgQIECAAAECBAgQWL/AKt7me5dw7Zxsm1ycnJ9ckigECBAgQIAAAQIECKy4wKpcQbprzvPrk7OSc5OTkuOSU5MaJH0/eU2yW6IQIECAAAECBAgQILCiAqtwBekvcm5f1Du/p2T6haQGSTUwqitJN0r2Sp6UHJI8Mzk8UQgQIECAAAECBAgQINApgd/J0VybfDS524gj2yLr7pN8Jan2ByazLIdlZ7XfHWa5U/siQIAAAQIECBAgMAGBbbKNei17wAS2ZRNTFnh7tl9vn6vPG41T6vNJFyavHqfxBNsYIE0Q06YIECBAgAABAgRmKtCpAVLX32J35zw16i11l4/5FDkv7Y5J9hiz/TI1u1M6u1+vw0dn+q1l6ry+EiBAgAABAgQIEJiFQNcHSGcEsQYFWydXjgFaV5BqUFU3bOhK2TMH8ubkV5If9g6q6j6dPLZV11tlQoAAAQIECBAgQGB1Bbp+F7saGNw+eW+y/4jTXJ9BunfysWT75P1JF0rdle9zSR3fLyR1M4pKzVddrXPnviAoBAgQIECAAAECBFZBoAYBz0ouSeqDY6cmX0w+kryjN6234J2e1Pq6yvRHyazLtD6DVFfCvp5sN+CAqq7Wdelq2YDDVEWAAAECBAgQIDBlgU59BmnKVguz+VumJzUgOi2pgVA7NXg6IXl5Um89m0eZxgBpyxzIBckjRhzQI3ttqq1CgAABAgQIECBAYD0CnRogdf0zSM0JPjEzj+4t7JRpff9RXUGpL46tQcSkyy2ywc8n9WQZp2w7TqM1tqm3ztWxfmPE4+oKUrWptmeOaGcVAQIECBAgQIAAgZUQWJUBUvtk1m28K9Ms9YW0T0m2HnMn90+7p47ZdtxmF6VhXSm7cXL8kAfVumpTbRUCBAgQIECAAAECKy+wigOkWZz0q7OTD65hRzdaQ9txm9ZbB7+YPCapq1mDSq2rz2BVW4UAAQIECBAgQIAAAQILITCNzyDVgT0guSp5XNJfHpeKWldtFAIECBAgQIAAAQLrFfAZpPXKzeFxNfCoz9istRyVB9SVlWUvn8wBPD15XfK45D+SKgcn90xqXbVRCBAgQIAAAQIECBBYAYGv5Rjbd6wbd/4vZ2wzrStIzWHcITOvSmrgV6n5qlMIECBAgAABAgQIbFRgm2ygXmcfsNENLcLju/4ZpF8L8vt6J+sDmb5hTPRhNzUY8+EL1+zb6VFdLVIIECBAgAABAgQIEFhxgbqFdt2s4PLkrgtqMe0rSAt62LpFgAABAgQIECDQAYFOXUH6uQ6ckM0dQg2MntBr9I+ba2w9AQIECBAgQIAAAQKrK7AKA6Q6u8cmz0/qhg37JgoBAgQIECBAgAABAgQILKiAt9gt6InRLQIECBAgQIAAgc0KeIvdZok0IECAAAECBAgQIECAwBIKrMpb7Jbw1OgyAQIECBAgQIAAAQKzFjBAmrW4/REgQIAAAQIECBAgsLACBkgLe2p0jAABAgQIECBAgACBWQsYIM1a3P4IECBAgAABAgQIEFhYAQOkhT01OkaAAAECBAgQIECAwKwFDJBmLW5/BAgQIECAAAECBAgsrIAB0sKeGh0jQIAAAQIECBAgQGDWAgZIsxa3PwIECBAgQIAAAQIEFlbAAGlhT42OESBAgAABAgQIECAwawEDpFmL2x8BAgQIECBAgAABAgsrYIC0sKdGxwgQIECAAAECBAgQmLWAAdKsxe2PAAECBAgQIECAAIGFFTBAWthTo2MECBAgQIAAAQIECMxawABp1uL2R4AAAQIECBAgQIDAwgoYIC3sqdExAgQIECBAgAABAgRmLWCANGtx+yNAgAABAgQIECBAYGEFDJAW9tToGAECBAgQIECAAAECsxYwQJq1uP0RIECAAAECBAgQILCwAgZIC3tqdIwAAQIECBAgQIAAgVkLGCDNWtz+CBAgQIAAAQIECBBYWAEDpIU9NTpGgAABAgQIECBAgMCsBQyQZi1ufwQIECBAgAABAgQILKyAAdLCnhodI0CAAAECBAgQIEBg1gIGSLMWtz8CBAgQIECAAAECBBZWwABpYU+NjhEgQIAAAQIECBAgMGsBA6RZi9sfAQIECBAgQIAAAQILK2CAtLCnRscIECBAgAABAgQIEJi1gAHSrMXtjwABAgQI/L/27gRYurMgEzAhfyJkBcI6CkYKEAEhEkAIMyTsA0giA+LCYkrBVBhlKlKK41YZI+WopWC5oINgcAGLUVDQEiGAMRCBEBASIMQZQFkCxBBMSMKazPuG7tD29O2/b9/b97/39PNVvX+f/s53Tp/v6T51++uz/AQIECBAYNcKGCDt2rfGhhEgQIAAAQIECBAgsNMCBkg7Le71CBAgQIAAAQIECBDYtQIGSLv2rbFhBAgQIECAAAECBAjstIAB0k6Lez0CBAgQIECAAAECBHatgAHSrn1rbBgBAgQIECBAgAABAjstYIC00+JejwABAgQIECBAgACBXStggLRr3xobRoAAAQIECBAgQIDATgvs2+kX9HoHTODWeeX7jV79vXm88oBtiRcmQIAAAQIECBAgsEsFHEHapW/MNm7W0VnXHySfSc4ZpdOt6zyFAAECBAgQIECAAIGRgAHSsD8KR6R75yYPSr4rucUonW5d57WNQoAAAQIECBAgQIAAgV0j8OxsyQ3J4du8Rb+S9X046el106V1ndc2CgECBAgQIECAAIFlBQ7Ngv0u+5BlV2A5AtMCqxggHZQXuTz5oekXm3jeeW3TtgoBAgQIECBAgACBZQQGNUByit0yH4G9sczts5m3Tf5hzuZ2Xtvcbk4bswgQIECAAAECBAisjYC72A33rb5u1LVeY9SB8EnJ8UnLhcnfJePrj76QaYUAAQIECBAgQIDA2gsYIA33I3BVuva+5EeS70zumfT23i0vSC5J3pG0TdsqBAgQIECAAAECBAgQ2BUCq7gGqR07Pbk+OS+5QzIunW5d57WNQoAAAQIECBAgQGBZgUFdg+QI0rIfg72x3EOzmZ9IekeR3q3uDUnLY5LWdd4JyYsThQABAgQIECBAgAABArtCYBVHkDr4vSY5JXl08rrkk6N0unWd1zYGykFQCBAgQIAAAQIElhJwBGkpNgvttEDvTHdY8sHk0uSNyXS5Ryrapm0vm57pOQECBAgQIECAAIF1E3Cb7+G+459L176a/Ic5Xey8tmlbhQABAgQIECBAgMDaCxggDfcjcF26dm7yrDld7Ly2aVuFAAECBAgQIECAAAECu0JgFdcgtWMPTr6U/GRyUDIunW5d57WNQoAAAQIECBAgQGBZAdcgLStnuR0XeHte8WnJ2ckPJuPrkHqDhmOTzmsbhQABAgQIECBAgACBCDjFbvgfg/+dLt49+dPk2FE63brOUwgQIECAAAECBAgQGAm4vfN6fBR6e++z1qOrekmAAAECBAgQIEBgeQFHkJa320tLnpSN/fPko6N0+qREIUCAAAECBAgQIEBgQsAAaQJjoJNnpl/nJL0hQ6ebTreu0woBAgQIECBAgAABAgR2lcCzszU3JIdv81Y9OevrYOhxM9bbus5rG4UAAQIECBAgQIDAsgKDuovdsgiW216BVQ2Q3pPN/NU5m9p5baMQIECAAAECBAgQWFZgUAMkp9gt+zHY/csdmU08Lpl3p7rOa5u2VQgQIECAAAECBAisvYAB0nA/AoeNunbVnC6O543bzmlqFgECBAgQIECAAIHhCxggDfc9vjxduyJ58Jwudl7btK1CgAABAgQIECBAYO0FDJCG+xG4Pl17efIzydEzutm6zmubtlUIECBAgAABAgQIECCwKwRWdZOGo9K7i5P3JQ9POiBuOt26ixLXHwVBIUCAAAECBAgQWFrATRqWprPgTgv0GqP/lHQw1P/36LpROt26hyVXJwoBAgQIECBAgAABAhHYR2HwAlemh09Pzkh6x7qWf0xcd3QjhX8IECBAgAABAgQIfF3AAOnrFkOf6nvdw58t3vevOfiXAAECBAgQIECAAIFdKLCqa5Da1WOSVyW9EcPnR+l06zpPIUCAAAECBAgQILAVAdcgbUXPsjsq0DvVvTW5W9LrjXpDhqbTreu8WXe4S7VCgAABAgQIECBAgACBAyOwqiNIL0p3PpTMulNd6zrvhYlCgAABAgQIECBAYFmBQR1BWhbBctsrsIoBUm/nfUXyjDmb+sxRG/8f1hwkswgQIECAAAECBOYKDGqA5Ivx3Pd6T8+8Xbb+NskFc3rxzlGbtlUIECBAgAABAgQIrL2AAdJwPwLXjro27xqj8bxx2+Fq6BkBAgQIECBAgACBBQQMkBZA2qNN+h/Avjt56pzt/95RG/9Z7BwkswgQIECAAAECBAgQ2FmBVVyD1B58d/Ll5OQ+mSqt67xTpuo9JUCAAAECBAgQILAZgUFdg7RvMz3Xds8J/EW2+MzkNaO8IY8tj0melPxc8peJQoAAAQIECBAgQIAAgV0jsKojSOMOnpCJVyaXjtLp1ikECBAgQIAAAQIEtirgCNJWBS2/4wLn5xUbhQABAgQIECBAgACBOQJOsZuDM6BZd0lfepTq+FGfLszjS5J/GT33QIAAAQIECBAgQIBABNzFbvgfgx9IFz+UPDG5OHn/aLp1nacQIECAAAECBAgQIEBgVwms6hqkh6aXvVPdGTN627rOaxuFAAECBAgQIECAwLICg7oGaVkEy22vwKoGSG/JZr58zqZ2XtsoBAgQIECAAAECBJYVGNQAad2vQfrmfAq+NflM0lPOrkuGUm6ZjjwsecScDr0s896ctO2Q+j6ny2YRIECAAAECBAgQ2Fhg6NcgnZauvyLpAGCyfHueXJB8NPnb5D3JZcnzk4OTIZRbpRN9f9uvjcqnMqNt2lYhQIAAAQIECBAgQGDgAj1CckNy9EQ/75zpz43qO0j63aSDqI+P6n49jztdVnGKXY8Ofj7pfwi7Uem8tln3I4kb+agnQIAAAQIECBDYv8CgTrHbf3f3dotZA6Q/SZc6aPrRqa4dlufjeY+amrfqp6sYIHWbe43R25NZA6DWdd68a5QyWyFAgAABAgQIECAwV2BQA6RZX5zn9n4AM09IH96Z/NZUX67N82clj0163c45ybKlH5KnJYcsuIL/uGC7zTb76SzQ//Po1cnpySeSlm9MXpwcmzw5UQgQIECAAAECBAgQiMA6DpCOSr/ftMG73xsVXJLcZ4P5i1bfIQ1/POlAaZFy+KhRb7u9naUDohOTVyT/nPT/QGq5d/Le5GHJeNCUSYUAAQIECBAgQIDAegus4wCpR1R6k4ZZ5ZhUPjA5e9bMTdR9LG03eo1Zq3lIKs+fNWMb6np3vgckPUp1/9H6avC2pKcaKgQIECBAgAABAgQIjATWZYDUU+relXRg0IHIzyUnJ69NxuUumfjlpEd9zh1XDuSxA6HzRhlIl3SDAAECBAgQIECAAIHNCjwlC/T6mw8nHSRM5l/yfFyekIme3tb5PbJyULKTpUeQ+todnCkECBAgQIAAAQIE9pJAv8P2u2y/0+75MvQjSH+Wd6hp6a2+j5vI5CCo//dRrz96ZXJG0jdYIUCAAAECBAgQIECAwFoK9D+SPeQA9twRpAOI76UJECBAgAABAgS2JOAI0pb4dufCPXqkECBAgAABAgQIECCw5gI3X/P+6z4BAgQIECBAgAABAgRuEjBAuonCBAECBAgQIECAAAEC6y5ggLTunwD9J0CAAAECBAgQIEDgJoGh38Xupo6auPE/wD1+5ND/D+oCJgQIECBAgAABAgQIENiNAqu8i91d0+Hzk+uTS0bpdOs6TyFAgAABAgQIECCwFYFB3cXOKXZb+Sjs/mXvlE08L7kq6WDonqN0unWd1zYKAQIECBAgQIAAAQIEdo3Aqo4gvTQ9fFfSUf10aV3ntY1CgAABAgQIECBAYFmBQR1BWhbBctsrsIoB0sHZxKuTJ8/Z1KeM2rStQoAAAQIECBAgQGAZgUENkJxit8xHYG8sc7ts5hHJxXM296JRm7ZVCBAgQIAAAQIECKy9gAHScD8CvcaoN2O4/Zwudl7btK1CgAABAgQIECBAYO0FDJCG+xG4Nl17W3LqnC52Xtu0rUKAAAECBAgQIECAAIFdIbCKa5DasROTrySn98lUaV3ntY1CgAABAgQIECBAYFmBQV2DtCyC5bZXYFUDpG7lqckXk3ckZ43S6dadmigECBAgQIAAAQIEtiIwqAHSvq1IWHZPCJydrTwvOS05IWk5N/mB5P/2iUKAAAECBAgQIECAAIHdJLDKI0i7qZ+2hQABAgQIECBAYHgCgzqC5CYNw/uA6hEBAgQIECBAgAABAksKGCAtCWcxAgQIECBAgAABAgSGJ2CANLz3VI8IECBAgAABAgQIEFhSwABpSTiLESBAgAABAgQIECAwPAEDpOG9p3pEgAABAgQIECBAgMCSAgZIS8JZjAABAgQIECBAgACB4QkYIA3vPdUjAgQIECBAgAABAgSWFDBAWhLOYgQIECBAgAABAgQIDE/AAGl476keESBAgAABAgQIECCwpIAB0pJwFiNAgAABAgQIECBAYHgCBkjDe0/1iAABAgQIECBAgACBJQUMkJaEsxgBAgQIECBAgAABAsMTMEAa3nuqRwQIECBAgAABAgQILClggLQknMUIECBAgAABAgQIEBiegAHS8N5TPSJAgAABAgQIECBAYEmBfUsuZ7HVCBy6mtX+u7Ue8u+eeUKAAAECBAgQIDB0gS+vuIM78R12xV34+uoNkL5ucSCnxh/aqw/kRnhtAgQIECBAgAABAlsQ+NIWlt01ix60a7bEhjwgBKs+unNmXuOI5OxEIUBg6wL3ySpOS35s66uyBgIERgK/mcffSy4mQoDAtgicmrV8PjkzWWXp4OjCVb6AdRNYhcDZWWmjECCwPQKPz2qu2Z5VWQsBAiOB7lPdtxQCBLZH4Oy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       "</svg>\n"
      ],
      "text/plain": [
       "Plot with title “Growth of Tooth vs Dose of Vitamin C”"
      ]
     },
     "metadata": {
      "image/svg+xml": {
       "isolated": true
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Let's see a scatter plot\n",
    "with(subset(ToothGrowth,  supp == \"VC\"), plot(dose, len))\n",
    "title(main=\"Growth of Tooth vs Dose of Vitamin C\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "</svg>\n"
      ],
      "text/plain": [
       "Plot with title “Growth of Tooth vs Dose of OJ”"
      ]
     },
     "metadata": {
      "image/svg+xml": {
       "isolated": true
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "with(subset(ToothGrowth,  supp == \"OJ\"), plot(dose, len))\n",
    "title(main=\"Growth of Tooth vs Dose of OJ\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "lm(formula = ToothGrowth$len ~ ToothGrowth$dose, subset = (ToothGrowth$supp == \n",
       "    \"VC\"))\n",
       "\n",
       "Residuals:\n",
       "    Min      1Q  Median      3Q     Max \n",
       "-8.2264 -2.6029  0.0814  2.2288  7.4893 \n",
       "\n",
       "Coefficients:\n",
       "                 Estimate Std. Error t value Pr(>|t|)    \n",
       "(Intercept)         3.295      1.427   2.309   0.0285 *  \n",
       "ToothGrowth$dose   11.716      1.079  10.860 1.51e-11 ***\n",
       "---\n",
       "Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
       "\n",
       "Residual standard error: 3.685 on 28 degrees of freedom\n",
       "Multiple R-squared:  0.8082,\tAdjusted R-squared:  0.8013 \n",
       "F-statistic: 117.9 on 1 and 28 DF,  p-value: 1.509e-11\n"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Fit for vitamin C\n",
    "fit.tooth.VC<-lm(ToothGrowth$len ~ ToothGrowth$dose,subset=(ToothGrowth$supp==\"VC\"))\n",
    "summary(fit.tooth.VC)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "lm(formula = len ~ dose, data = ToothGrowth, subset = (supp == \n",
       "    \"VC\"))\n",
       "\n",
       "Residuals:\n",
       "    Min      1Q  Median      3Q     Max \n",
       "-8.2264 -2.6029  0.0814  2.2288  7.4893 \n",
       "\n",
       "Coefficients:\n",
       "            Estimate Std. Error t value Pr(>|t|)    \n",
       "(Intercept)    3.295      1.427   2.309   0.0285 *  \n",
       "dose          11.716      1.079  10.860 1.51e-11 ***\n",
       "---\n",
       "Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
       "\n",
       "Residual standard error: 3.685 on 28 degrees of freedom\n",
       "Multiple R-squared:  0.8082,\tAdjusted R-squared:  0.8013 \n",
       "F-statistic: 117.9 on 1 and 28 DF,  p-value: 1.509e-11\n"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Fit for vitamin C\n",
    "fit.tooth.VC<-lm(len ~ dose, subset=(supp==\"VC\"), data=ToothGrowth)\n",
    "summary(fit.tooth.VC)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Discussion\n",
    "----\n",
    "\n",
    "* What is the biological hypothesis?\n",
    "* What is the statistical hypothesis?\n",
    "* How do we test the statistical hypothesis?\n",
    "* What is your conclusion?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Look at OJ and Tooth Growth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "lm(formula = ToothGrowth$len ~ ToothGrowth$dose, subset = (ToothGrowth$supp == \n",
       "    \"OJ\"))\n",
       "\n",
       "Residuals:\n",
       "    Min      1Q  Median      3Q     Max \n",
       "-7.2557 -3.7979 -0.0643  3.3521  7.9386 \n",
       "\n",
       "Coefficients:\n",
       "                 Estimate Std. Error t value Pr(>|t|)    \n",
       "(Intercept)        11.550      1.722   6.708 2.79e-07 ***\n",
       "ToothGrowth$dose    7.811      1.302   6.001 1.82e-06 ***\n",
       "---\n",
       "Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
       "\n",
       "Residual standard error: 4.446 on 28 degrees of freedom\n",
       "Multiple R-squared:  0.5626,\tAdjusted R-squared:  0.547 \n",
       "F-statistic: 36.01 on 1 and 28 DF,  p-value: 1.825e-06\n"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Fit for OJ\n",
    "fit.tooth.OJ<-lm(ToothGrowth$len ~ ToothGrowth$dose,subset=(ToothGrowth$supp==\"OJ\"))\n",
    "summary(fit.tooth.OJ)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "Note that the `lm` function (for linear model) takes arguments in a specific format:\n",
    "\n",
    "$$ y\\_values \\sim  x\\_values$$\n",
    "\n",
    "Or more formally stated: Dependent Variable ~ Independent Variable"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## R Formula Syntax"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A more complicated linear model might include more than one main effect and/or interaction terms such as:\n",
    "\n",
    "$$ y = \\alpha + \\beta_1 x_1 + \\beta_2 x_2 + \\beta_3 x_1 x_2 +\\epsilon$$\n",
    "\n",
    "Below is a table of R formula syntax and the corresponding model. There are others, but that is a topic for more advanced study."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "|       Syntax       | Model |\n",
    "| ------------------ | ----- |\n",
    "| $x_1 + x_2 \\;\\;\\;\\;\\;\\;\\;\\;\\;\\;\\;\\;\\;\\;\\;\\;\\;\\;\\;\\;$ | $y = \\alpha + \\beta_1 x_1 + \\beta_2 x_2  +\\epsilon$ |\n",
    "| $x_1:x_1$ | $y = \\alpha + \\beta x_1 x_2 +\\epsilon \\;\\;\\;\\;\\;\\;\\;\\;\\;\\;\\;\\;\\;\\;\\;\\;\\;\\;\\;\\;\\;\\;\\;\\;$ |\n",
    "| $x_1 * x_2$ | $y = \\alpha + \\beta_1 x_1 + \\beta_2 x_2 + \\beta_3 x_1 x_2 +\\epsilon \\;\\;\\;\\;\\;\\;\\;\\;\\;\\;\\;\\;\\;\\;\\;\\;$ |\n",
    "| $x_1 * x_2 *x_3$ | $y = \\alpha + \\beta_1 x_1 + \\beta_2 x_2 + \\beta_3 x_3 +\\beta_4 x_1 x_2 +\\beta_5 x_1 x_3 + \\beta_6 x_2 x_3 + \\beta_7 x_1 x_2 x_3 +\\epsilon$ |\n",
    "| $(x_1 + x_2 + x_3)^2$ | $y = \\alpha + \\beta_1 x_1 + \\beta_2 x_2 + \\beta_3 x_3 +\\beta_4 x_1 x_2 +\\beta_5 x_1 x_3 + \\beta_6 x_2 x_3 +\\epsilon$ |\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Work!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load the R data set called \"mtcars\". \n",
    "\n",
    "* Perform a linear regression on mpg using cyl and hp as main effects. \n",
    "* Add wt (weight) as a third main effect.\n",
    "* Add interaction terms for hp and weight\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Rails Example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>Rail</th><th scope=col>travel</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>1</td><td>55</td></tr>\n",
       "\t<tr><th scope=row>2</th><td>1</td><td>53</td></tr>\n",
       "\t<tr><th scope=row>3</th><td>1</td><td>54</td></tr>\n",
       "\t<tr><th scope=row>4</th><td>2</td><td>26</td></tr>\n",
       "\t<tr><th scope=row>5</th><td>2</td><td>37</td></tr>\n",
       "\t<tr><th scope=row>6</th><td>2</td><td>32</td></tr>\n",
       "\t<tr><th scope=row>7</th><td>3</td><td>78</td></tr>\n",
       "\t<tr><th scope=row>8</th><td>3</td><td>91</td></tr>\n",
       "\t<tr><th scope=row>9</th><td>3</td><td>85</td></tr>\n",
       "\t<tr><th scope=row>10</th><td>4</td><td>92</td></tr>\n",
       "\t<tr><th scope=row>11</th><td>4</td><td>100</td></tr>\n",
       "\t<tr><th scope=row>12</th><td>4</td><td>96</td></tr>\n",
       "\t<tr><th scope=row>13</th><td>5</td><td>49</td></tr>\n",
       "\t<tr><th scope=row>14</th><td>5</td><td>51</td></tr>\n",
       "\t<tr><th scope=row>15</th><td>5</td><td>50</td></tr>\n",
       "\t<tr><th scope=row>16</th><td>6</td><td>80</td></tr>\n",
       "\t<tr><th scope=row>17</th><td>6</td><td>85</td></tr>\n",
       "\t<tr><th scope=row>18</th><td>6</td><td>83</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ll}\n",
       "  & Rail & travel\\\\\n",
       "\\hline\n",
       "\t1 & 1 & 55\\\\\n",
       "\t2 & 1 & 53\\\\\n",
       "\t3 & 1 & 54\\\\\n",
       "\t4 & 2 & 26\\\\\n",
       "\t5 & 2 & 37\\\\\n",
       "\t6 & 2 & 32\\\\\n",
       "\t7 & 3 & 78\\\\\n",
       "\t8 & 3 & 91\\\\\n",
       "\t9 & 3 & 85\\\\\n",
       "\t10 & 4 & 92\\\\\n",
       "\t11 & 4 & 100\\\\\n",
       "\t12 & 4 & 96\\\\\n",
       "\t13 & 5 & 49\\\\\n",
       "\t14 & 5 & 51\\\\\n",
       "\t15 & 5 & 50\\\\\n",
       "\t16 & 6 & 80\\\\\n",
       "\t17 & 6 & 85\\\\\n",
       "\t18 & 6 & 83\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "Grouped Data: travel ~ 1 | Rail\n",
       "   Rail travel\n",
       "1     1     55\n",
       "2     1     53\n",
       "3     1     54\n",
       "4     2     26\n",
       "5     2     37\n",
       "6     2     32\n",
       "7     3     78\n",
       "8     3     91\n",
       "9     3     85\n",
       "10    4     92\n",
       "11    4    100\n",
       "12    4     96\n",
       "13    5     49\n",
       "14    5     51\n",
       "15    5     50\n",
       "16    6     80\n",
       "17    6     85\n",
       "18    6     83"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Rails example\n",
    "\n",
    "# Just loading some library functions\n",
    "library(nlme)\n",
    "library(lattice)\n",
    "\n",
    "# Get the dataset (it is part of R)\n",
    "data(Rail)\n",
    "\n",
    "# Look at the data\n",
    "Rail"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      ],
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/svg+xml": {
       "isolated": true
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     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plot the data\n",
    "\n",
    "xyplot(travel~Rail,data=Rail,ylab=\"Zero-force travel time (nano-seconds)\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "lm(formula = travel ~ 1, data = Rail)\n",
       "\n",
       "Residuals:\n",
       "   Min     1Q Median     3Q    Max \n",
       "-40.50 -16.25   0.00  18.50  33.50 \n",
       "\n",
       "Coefficients:\n",
       "            Estimate Std. Error t value Pr(>|t|)    \n",
       "(Intercept)   66.500      5.573   11.93  1.1e-09 ***\n",
       "---\n",
       "Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
       "\n",
       "Residual standard error: 23.65 on 17 degrees of freedom\n"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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       "</svg>\n"
      ],
      "text/plain": [
       "Plot with title “Normal Q-Q Plot”"
      ]
     },
     "metadata": {
      "image/svg+xml": {
       "isolated": true
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Linear Model ignoring random effect\n",
    "\n",
    "fit.rails.simple<-lm(travel~1,data=Rail)\n",
    "summary(fit.rails.simple)\n",
    "res<-fit.rails.simple$residuals\n",
    "qqnorm(res);qqline(res)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The above plot is called a 'QQ plot'. The straight line represents the quantiles of the normal distribution, while the dots are the quantiles of the residuals. If the errors were normally distributed, the dots would be close to or on the line."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note: In this example, we are fitting a one-parameter model, i.e.\n",
    "\n",
    "$$y_i = \\alpha + \\epsilon_i$$\n",
    "\n",
    "Where $\\alpha$ is the mean travel time along a rail."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "66.5"
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       "66.5"
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       "66.5"
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       "[1] 66.5"
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       "[1] 23.64505"
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     "execution_count": 10,
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   ],
   "source": [
    "mean(Rail$travel)\n",
    "sd(Rail$travel)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Linear mixed-effects model fit by REML\n",
       " Data: Rail \n",
       "      AIC      BIC   logLik\n",
       "  128.177 130.6766 -61.0885\n",
       "\n",
       "Random effects:\n",
       " Formula: ~1 | Rail\n",
       "        (Intercept) Residual\n",
       "StdDev:    24.80547 4.020779\n",
       "\n",
       "Fixed effects: travel ~ 1 \n",
       "            Value Std.Error DF  t-value p-value\n",
       "(Intercept)  66.5  10.17104 12 6.538173       0\n",
       "\n",
       "Standardized Within-Group Residuals:\n",
       "        Min          Q1         Med          Q3         Max \n",
       "-1.61882658 -0.28217671  0.03569328  0.21955784  1.61437744 \n",
       "\n",
       "Number of Observations: 18\n",
       "Number of Groups: 6 "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "# Linear Model incorporating random effect\n",
    "fit.rails.mm<-lme(travel~1,random=~1|Rail,data=Rail)\n",
    "summary(fit.rails.mm)\n",
    "res<-fit.rails.mm$residuals"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Simulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "sim.ranef=function(nk,n,se,sb,verbose=FALSE)\n",
    "    {\n",
    "        # n exp units with nk replicates each\n",
    "        N=n*nk\n",
    "    \n",
    "        # generate error from normal distribution with zero mean and variance se\n",
    "        e=rnorm(N,0,se)\n",
    "    \n",
    "        # generate random effect from normal with mean zero and variance sb\n",
    "        # here we get n different samples from the normal - but replicate those nk times\n",
    "        b=rep(rnorm(n,0,sb),each=nk)\n",
    "    \n",
    "        # assigning a label to each n sample (eg. each rail), repeat nk times\n",
    "        id=rep(1:n,each=nk)\n",
    "    \n",
    "        # Simulated output value\n",
    "        y=0+e+b\n",
    "    \n",
    "        # create a data frame with the id, errors and outcome\n",
    "        dat=data.frame(id,b,e,y)\n",
    "    \n",
    "    \n",
    "        # fit both models: standard linear model (lm) and linear mixed effects (lme)\n",
    "        mod0=summary(lm(y~1,data=dat))\n",
    "        mod1=summary(lme(y~1,random=~1|id,data=dat))\n",
    "        \n",
    "        # extract the pvalues\n",
    "        pval0=mod0$coef[\"(Intercept)\",\"Pr(>|t|)\"]  #each package returns a slightly different data frame\n",
    "        pval1=mod1$tTable[\"(Intercept)\",\"p-value\"] \n",
    "       \n",
    "    # Just changing output based on options passed to the function.  \n",
    "       if(verbose)\n",
    "            {\n",
    "                out=list(dat,mod0,mod1) # This is a list data type. Basically, you can put anything into a list.\n",
    "            }\n",
    "        else\n",
    "            {\n",
    "                out=c(pval0,pval1) # Output only the p-values from the two models.\n",
    "            }\n",
    "        out\n",
    "    }\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>id</th><th scope=col>b</th><th scope=col>e</th><th scope=col>y</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>1</td><td>-0.1488067</td><td>0.007527368</td><td>-0.1412794</td></tr>\n",
       "\t<tr><th scope=row>2</th><td>1</td><td>-0.1488067</td><td>0.3107647</td><td>0.161958</td></tr>\n",
       "\t<tr><th scope=row>3</th><td>1</td><td>-0.1488067</td><td>-0.1323212</td><td>-0.281128</td></tr>\n",
       "\t<tr><th scope=row>4</th><td>2</td><td>1.498304</td><td>-0.1476185</td><td>1.350686</td></tr>\n",
       "\t<tr><th scope=row>5</th><td>2</td><td>1.498304</td><td>-0.02297237</td><td>1.475332</td></tr>\n",
       "\t<tr><th scope=row>6</th><td>2</td><td>1.498304</td><td>-0.1831132</td><td>1.315191</td></tr>\n",
       "\t<tr><th scope=row>7</th><td>3</td><td>-0.5167083</td><td>0.4015476</td><td>-0.1151607</td></tr>\n",
       "\t<tr><th scope=row>8</th><td>3</td><td>-0.5167083</td><td>-0.2814648</td><td>-0.7981732</td></tr>\n",
       "\t<tr><th scope=row>9</th><td>3</td><td>-0.5167083</td><td>-0.1040145</td><td>-0.6207228</td></tr>\n",
       "\t<tr><th scope=row>10</th><td>4</td><td>0.1644428</td><td>0.4328612</td><td>0.597304</td></tr>\n",
       "\t<tr><th scope=row>11</th><td>4</td><td>0.1644428</td><td>0.4492927</td><td>0.6137355</td></tr>\n",
       "\t<tr><th scope=row>12</th><td>4</td><td>0.1644428</td><td>-0.111888</td><td>0.05255479</td></tr>\n",
       "\t<tr><th scope=row>13</th><td>5</td><td>0.1138402</td><td>0.524783</td><td>0.6386232</td></tr>\n",
       "\t<tr><th scope=row>14</th><td>5</td><td>0.1138402</td><td>-0.02295953</td><td>0.09088062</td></tr>\n",
       "\t<tr><th scope=row>15</th><td>5</td><td>0.1138402</td><td>-0.5665937</td><td>-0.4527536</td></tr>\n",
       "\t<tr><th scope=row>16</th><td>6</td><td>0.8765584</td><td>-0.0401512</td><td>0.8364071</td></tr>\n",
       "\t<tr><th scope=row>17</th><td>6</td><td>0.8765584</td><td>-0.05409372</td><td>0.8224646</td></tr>\n",
       "\t<tr><th scope=row>18</th><td>6</td><td>0.8765584</td><td>-0.04234974</td><td>0.8342086</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llll}\n",
       "  & id & b & e & y\\\\\n",
       "\\hline\n",
       "\t1 & 1 & -0.1488067 & 0.007527368 & -0.1412794\\\\\n",
       "\t2 & 1 & -0.1488067 & 0.3107647 & 0.161958\\\\\n",
       "\t3 & 1 & -0.1488067 & -0.1323212 & -0.281128\\\\\n",
       "\t4 & 2 & 1.498304 & -0.1476185 & 1.350686\\\\\n",
       "\t5 & 2 & 1.498304 & -0.02297237 & 1.475332\\\\\n",
       "\t6 & 2 & 1.498304 & -0.1831132 & 1.315191\\\\\n",
       "\t7 & 3 & -0.5167083 & 0.4015476 & -0.1151607\\\\\n",
       "\t8 & 3 & -0.5167083 & -0.2814648 & -0.7981732\\\\\n",
       "\t9 & 3 & -0.5167083 & -0.1040145 & -0.6207228\\\\\n",
       "\t10 & 4 & 0.1644428 & 0.4328612 & 0.597304\\\\\n",
       "\t11 & 4 & 0.1644428 & 0.4492927 & 0.6137355\\\\\n",
       "\t12 & 4 & 0.1644428 & -0.111888 & 0.05255479\\\\\n",
       "\t13 & 5 & 0.1138402 & 0.524783 & 0.6386232\\\\\n",
       "\t14 & 5 & 0.1138402 & -0.02295953 & 0.09088062\\\\\n",
       "\t15 & 5 & 0.1138402 & -0.5665937 & -0.4527536\\\\\n",
       "\t16 & 6 & 0.8765584 & -0.0401512 & 0.8364071\\\\\n",
       "\t17 & 6 & 0.8765584 & -0.05409372 & 0.8224646\\\\\n",
       "\t18 & 6 & 0.8765584 & -0.04234974 & 0.8342086\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "   id          b            e           y\n",
       "1   1 -0.1488067  0.007527368 -0.14127937\n",
       "2   1 -0.1488067  0.310764748  0.16195801\n",
       "3   1 -0.1488067 -0.132321250 -0.28112798\n",
       "4   2  1.4983041 -0.147618510  1.35068558\n",
       "5   2  1.4983041 -0.022972372  1.47533171\n",
       "6   2  1.4983041 -0.183113182  1.31519090\n",
       "7   3 -0.5167083  0.401547638 -0.11516068\n",
       "8   3 -0.5167083 -0.281464847 -0.79817317\n",
       "9   3 -0.5167083 -0.104014524 -0.62072284\n",
       "10  4  0.1644428  0.432861188  0.59730397\n",
       "11  4  0.1644428  0.449292702  0.61373548\n",
       "12  4  0.1644428 -0.111887994  0.05255479\n",
       "13  5  0.1138402  0.524783005  0.63862316\n",
       "14  5  0.1138402 -0.022959532  0.09088062\n",
       "15  5  0.1138402 -0.566593749 -0.45275359\n",
       "16  6  0.8765584 -0.040151203  0.83640715\n",
       "17  6  0.8765584 -0.054093725  0.82246463\n",
       "18  6  0.8765584 -0.042349736  0.83420862"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# run the first simulation\n",
    "\n",
    "set.seed(210)\n",
    "\n",
    "# simulate 3 measurements on each of 6 subjects\n",
    "\n",
    "ex1=sim.ranef(3,6,0.25,0.5,verbose=TRUE)\n",
    "\n",
    "#print the simulated data set - note that it is stored in element 1 of a list.\n",
    "ex1[[1]]\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "lm(formula = y ~ 1, data = dat)\n",
       "\n",
       "Residuals:\n",
       "     Min       1Q   Median       3Q      Max \n",
       "-1.15262 -0.48920  0.02518  0.47682  1.12088 \n",
       "\n",
       "Coefficients:\n",
       "            Estimate Std. Error t value Pr(>|t|)  \n",
       "(Intercept)   0.3545     0.1623   2.184   0.0433 *\n",
       "---\n",
       "Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
       "\n",
       "Residual standard error: 0.6885 on 17 degrees of freedom\n"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "Linear mixed-effects model fit by REML\n",
       " Data: dat \n",
       "       AIC      BIC    logLik\n",
       "  30.77925 33.27889 -12.38963\n",
       "\n",
       "Random effects:\n",
       " Formula: ~1 | id\n",
       "        (Intercept) Residual\n",
       "StdDev:   0.6534632  0.31193\n",
       "\n",
       "Fixed effects: y ~ 1 \n",
       "                Value Std.Error DF  t-value p-value\n",
       "(Intercept) 0.3544515 0.2767212 12 1.280898  0.2244\n",
       "\n",
       "Standardized Within-Group Residuals:\n",
       "        Min          Q1         Med          Q3         Max \n",
       "-1.80653704 -0.47853843  0.09922849  0.56888267  1.69225071 \n",
       "\n",
       "Number of Observations: 18\n",
       "Number of Groups: 6 "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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       "<path style=\"fill:none;stroke-width:0.75;stroke-linecap:round;stroke-linejoin:round;stroke:rgb(0%,0%,0%);stroke-opacity:1;stroke-miterlimit:10;\" d=\"M 54.148438 453.507812 L 474.992188 453.507812 L 474.992188 35.007812 L 54.148438 35.007812 Z \"/>\n",
       "</g>\n",
       "</svg>\n"
      ],
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/svg+xml": {
       "isolated": true
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the simultation data using xyplot (from the lattice package)\n",
    "xyplot(y~id,data=ex1[[1]])\n",
    "\n",
    "# print the output from the two fits.\n",
    "\n",
    "ex1[[2]]\n",
    "ex1[[3]]\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "0.247"
      ],
      "text/latex": [
       "0.247"
      ],
      "text/markdown": [
       "0.247"
      ],
      "text/plain": [
       "[1] 0.247"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/html": [
       "0.072"
      ],
      "text/latex": [
       "0.072"
      ],
      "text/markdown": [
       "0.072"
      ],
      "text/plain": [
       "[1] 0.072"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Run the simulation 1000 times\n",
    "set.seed(210)\n",
    "B=1000\n",
    "res=replicate(B,sim.ranef(3,6,0.25,0.5,verbose=FALSE)) #Note that verbose=FALSE means that the simulation will \n",
    "                                                                 # output only p-values\n",
    "\n",
    "# Compute the type I error rates\n",
    "mean(res[1,]<0.05) \n",
    "mean(res[2,]<0.05)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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iHaT+fyHKql8Y2eY9MVPZirlw11QXPS+BChN4cfKGk3RqhfNY1axZv1T1yZivKhBgWh2j08wO+3y0e1Q5q7KDNBWsV+TCX0U/nCpA1/lt8/1NXec6vzJCtXDnCY8lUBMCb0k+2aBBK49Av/XL/kn6oBmSX22G616WQBUJ/GsydXf0pypmrqZ5sn6p6YMz26URYOfdTofoefm+ZFS5eqaOIyebBOSmUa/29QR8xjS6Ldfs4e2VpuGqRIDe3cOrlKEG5KXf+uUjKTMdTVOJqcHUMZoE6kaA9sGJdct0xfNr/VLxB2T2hk6Av4EHIkaP5kX8j7wn0ipI4Mbk6bwK5sssSWA6AqwNoIJZa4pATPHYd4prnh4dAeuX0bE2pfII0MvLzlK8A2kys36ZjMroz1m/jJ65Kc6ewLK5lVkvOEa0X9iEbbIp6pWoX+o4xS48NQm0nsAuIYBjf3XrSQhAAhIom8DOifDR6LdlR2x8EpBAawkw46JzSQvLZS6pKo06TrGrKkvzJYFREsBBcvvdURI3LQm0h8A+KSprAt7XniJbUglIYMgE9uyInxGkEzu+V+6wiiNIx4cSa4amM3bAeON0AbwmgYYTYB0eW+Fr/RGwfumPl6HbSeCZKTav1TisncWfdamtX2aNzhsbToDRoj9GTN3F9+Dl9u+OKmtVdJDeHlpHRQztf2UKci56ngKMp1tB4Lkp5dLRGhHbSN8Sab0RsH7pjZOh2ktg+RR9/ehV0e/ai2FWJbd+mRU2b2o4AabVMSK9UMTIEc7SftF1kdYnARZtsasFlfSwzUWOwyZs/GUT+EQi/E3ESOrHp4i8Eoscp8jbuE9bv4z7CZh+lQnsm8yxkJo6Zqot6q1fpn6C1i9Ts/FKOwkcm2LjGHVqmWlQVKJ+qeoaJBZtvSVadxqAXpJAWwmw/uiI6JDo39sKYYByW78MAM9bG0+A+uW+iNFptuPV+iNg/dIfL0M3mwCjRZ27YRZOEtPtKm1VnGJXAPt+ceCnBCTwZwJzcrRR9PfRaX8+60G/BKxf+iVm+LYQYAe7G6LPRk5nn91Tt36ZHTfvah6B96ZInTvXUUKW0LDVd6Wtyg5SpcGZOQmMicBeSXeR6IIxpW+yEpBAcwmsm6IxrW6J6CnNLaYlk4AERkCANUcsA2AUCSvWH73osa/V/lnVKXbVpmbuJDA+Arsm6V9E7ATDXHdNAhKQQFkEmF5H3fJodFhZkRqPBCTQSgLvT6mZ9VIYjhK7191YnKjypw5SlZ+OeZPAEwnQgOH9Rx+K6JnZMNIkIAEJlEGA+oU1NG+L5pYRoXFIQAKtJXBgV8kZQWLDhlqYDlItHpOZlMB8AovmJ1NgcJBOjdgi88pIk4AEJDAoAXp3d49WijYZNDLvl4AEWk2AXXaZYtdpOEgf6TxR5WPXIFX56Zg3CTyewMvzlYWN9PB+NGKo+qFIk4AEJDAoAd57xNojOk6PGTQy75eABFpNYM+u0he719Vm/bQOUtcT9KsEKkyA6S8/i1gjwC4wl0eaBCQggTIIsDMmHTBHR2eUEaFxSEACrSQwJ6VmRLownCPs1xHvWKuFOcWuFo/JTEpgPoHN8pPpdc+P2M3uaZEmAQlIoAwCjEifFr2ijMiMQwISaC2BE1JyHKTCMQLE7dFRHNTFdJDq8qTMZ9sJ4AxtHOEg7RTRQ8M6JE0CEpDAoASWTwSbR08eNCLvl4AEWk1ghZR++wgHqRhFYlfM5SLaL7Uxp9jV5lGZ0ZYTYHrdvdFV0SejE6NfRpoEJCCBQQl8OBHQmDl30Ii8XwISaDUBtvYuHCNAMIo0L2JpwO+j2pgOUm0elRltOQEcpB9NMPhSPh+OWCugSUACEhiUACPU90QfHDQi75eABFpNYMGUHqeo00m6KN+viHCUamNOsavNozKjLSfwrJS/GJ5mc4bLWs7D4ktAAuURWCRRfTm6pbwojUkCEmgZgaVTXuqSTmNtI1N3i/ZL57VKH+sgVfrxmDkJzCeAc7R6xM51T4nWiFhMrUlAAhIYlMBiiWDL6OJBI/J+CUigtQRWSclvjd44QYBRJHRwtE5Uu+m7Okh5apoEKk6A6XU0Xpi/u3K0dvT0SJOABCQwKIGXJQKm27910Ii8XwISaC2Bb6bkTK9jal0hRo+2jq6KLoxqZTpItXpcZralBHCQiuHpV+X4jui4lrKw2BKQQLkE3pLo5kVnlhutsUlAAi0hsGbK+dyOsjJyhOEorRgV7RfO1cZ0kGrzqMxoiwk8M2U/fqL8jBw9Nbp24rsfEpCABAYhsGluZoOGfxskEu+VgARaS4CddYtRo04ID0580UHqpOKxBCRQCoEdEgvrjlh/tHv07OjmiC0zNQlIQAKDENgxN7OomtGjOyNNAhKQQL8EVs0NxagR9+IsMdPlBdGy0TlR7cwRpNo9MjPcMgJMr6PxcmO0d/RAdFikSUACEhiUwAaJgJc4fnzQiLxfAhJoLYFjU3LWG2E4SnTgnhJtE10QXRPVznwPUu0emRluGYFdU95iePqEHF8SfbdlDCyuBCQwHAKbJdpfRDRmNAlIQAL9EGCk6L+ifSMcpLsidrLDYfrX6CdR0X7JYb3MEaR6PS9z2y4CVD7PiIoK5vU53qldCCytBCQwRAJ7Ju6FojlDTMOoJSCBZhJg0yjaJQtH7GDHdLqlom9Hd0e8oqRov+SwXuYIUr2el7ltF4Hnp7iLR+dNFPsr+fQFsRMw/JCABAYisGruXjm6L2KnKabxahKQgAR6JbBbV0A6dVeKPhN9OsJZOieqpTmCVMvHZqZbQmCXlJPd6+iJeUl0UMSiR00CEpDAoASelwgeing/ic7RoDS9XwLtI3DtJEXGr2DjF9ovp0W3RbU0HaRaPjYz3RICVDDF8DQ9NU+KWPCoSUACEhiUAC+IZc3AjweNyPslIIHWETgoJT6wo9TFLnYP5xybvnS2XzqC1efQKXb1eVbmtF0EmNPLDlOFg8ROdldHx0WaBCQggUEJ8Ib7e6O5g0bk/RKQQKsIMJPlnyOm1HUaGzVgX46Yvvs+vtTVdJDq+uTMd9MJsKU3lc9FEwV9ZT7vnzj2QwISkMAgBHbOzawPYIvvWm7BO0jhvVcCEpg1gTm587BJ7qa9gujcXTvCWeL9jbU1HaTaPjoz3nACDE8fFRVvon5vjnWQGv7QLZ4ERkTg/UlnXnR4dPOI0jQZCUig/gS+kyLgBOEMdRvT7B6JmGZ3esQIdW1NB6m2j86MN5zApikfFVFhxUhS8d1PCUhAArMlsF1u5KXTOEqaBCQggV4JvDgBO50jnCI6W+jMPSG6Onp+xAZTtTYdpFo/PjPfUAJrplybR69paPkslgQkMD4C2yTpRaNjozvHlw1TloAEakgAhwjhJBXO0RI5ZtSI74tH74yK9dM5rKe5i109n5u5bjYBptfRu3tZs4tp6SQggTEQWCVp0rj5/BjSNkkJSKDeBJg612nn58tDEc4RxggT0+xqP+tFB4nHqUmgWgRwkH4SscixsB1ywLsFNAlIQAKDEFg/N/Py6V8OEon3SkACrSOwYEp8aHR3hEPE5z5Rp9F+OTrCSaq16SDV+vGZ+YYSeFbK1Tk8/cZ8/1rEsLUmAQlIYBACu+bm7l7gQeLzXglIoB0Ejksx/zNiSh3vT1smuibqNJYHdLZfOq/V6tg1SLV6XGa2BQQ2ThnXjTq3x9w03+mtOTHSJCABCcyWAKPQz474pHHjGqRA0CQggRkJHJkQzGQp7KU5YDc7ptcVtk4OaMPoIBVE/JSABEojwPD05dGFHTGekuNzo7M7znkoAQlIoF8Cz5m44fx8/rHfmw0vAQm0ksA/ptQv7Cg5HbZzo07niMu0X/4UXcGXuptT7Or+BM1/0whQwXT3vrwl5/ZqWkEtjwQkMHIC1C/3REtG80aeuglKQAJ1JLDHJJn+0STnqF9+FuFA1d50kGr/CC1Awwh0rz/aKuVbKDqnYeW0OBKQwOgJsP6I95R8b/RJm6IEJFBTAutN5LtwfNhAak7Epg2fjNj05aBoy6i7gzen6ml/Xc9sm2sJNJIAawNWin7TUbptc7xidHLHOQ8lIAEJ9EtgqdzAesa50ar93mx4CUigdQR4HcCZEe0SrHj30aM5/nr0tuhdEWuRNoxwmBrTmesIUp6mJoGKEGB4ms0Zru3ID9NgLoou7jjnoQQkIIF+Cew2cQMvcmQbXk0CEpDAdARel4tbTBLgGzl3WcSGUowkYThPt0e/50sTTAepCU/RMjSFAA5S9/D0F3LuxdHdTSmk5ZCABMZCgLWMD0e/jG4YSw5MVAISqBOBV02R2f+eOH9IPpluR72Cg8Q24I0xHaTGPEoL0gACTH/pdpAaUCyLIAEJjJkA/+u3j2jMfGzMeTF5CUig+gTY0nvHCMen0/h+y8SJs/K5fvTqiF0xD4saYzpIjXmUFqTmBJj+whoBpthpEpCABMoksE4iY33A6dElZUZsXBKQQCMJMEpUTJ+jgMUGDYwWMZWusGtycFPEe9Ua9SoSHaTiEfspgfESYHrdydFtXdlgCPtTXef8KgEJSKBXAvyfxzGigfPjXm8ynAQk0GoCy6X0naNHxfFXcv6uLjK0X3hX441d52v9VQep1o/PzDeIABVM9/S6RXJuzci/0wY9aIsigRETeErSWzS6Lzo40iQgAQlMR4AdrguHqDMcnSw4SN02WfulO0ztvtvwqt0jM8MNJEBltFHU7SCxVmD16NZIk4AEJDAbAh/JTQtFvNjxodlE4D0SkECrCOw+SWlxjg6Irui6hh+xWdTdfukKVr+vNMw0CUhgvAT2SvI0YM7vysYf8v3m6Htd5/0qAQlIoFcCvKOE//Wf6fUGw0lAAq0msGRH6XGMMDaRunD+0eN/7JavS0RMsWuUOYLUqMdpYWpKgOHpYyKmwHTaJ/OFN1PjJGkSkIAEZkOAjV+ujy6dzc3eIwEJtIoAbY6PR+x4iXOEXhZN5hzl9AK0X06Mutcl5VS9TQep3s/P3DeDQCPn7zbj0VgKCdSewHNTAt59pElAAhKYjsB3c/HMaLVoTsQ6JPyEk6KprLHtFx2kqR655yUwGgK81X69aLL5u2/M+T1Gkw1TkYAEGkiAjV5YT7ByA8tmkSQggfIILJuoXh11bs7A6BE7694RTWbUL5Otn54sbO3O6SDV7pGZ4YYReGnK80h0ySTl2ifnXjvJeU9JQAIS6IXAxgnE+sb/6SWwYSQggdYSuCclZ5p/Ma2uADHd1NwXJBAOVff66eLeWn/qINX68Zn5BhBgePpnEU5Sp22QLwxxN+rN1J0F9FgCEhg6AUaPboi+OfSUTEACEqgzgXnJ/CujP3YVYro2CO0XOl8e6LqnEV91kBrxGC1EjQk8K3mfbHodzhFb8nZv3FDjopp1CUhgxAQYhX442nvE6ZqcBCRQHwLvTlbppD0iYke6Ypod54rNF2iTMAXvfdFKEYaDNFn7Zf5Ff9SfAG/+Pa/+xbAENSSwfvLMcPZaQ8j73MS57xDiNcr+CFi/9MfL0OURYGodzhG7Ty1aXrTzY7J+KRnoLKOzfpklOG97HIFH862YWscnO9jhHLH2aLkI+3JEpy2jReysi5NEWKbxlm2VqF8cQSr7sRqfBHonQO/Ln6KrJ7ll9Zx74STnPSUBCUigFwLUL7z/aJmI6TOaBCQggckIdPsCjCDh/GwYsUkDxnppOl3YmGGF6B3R/dFk66dzuv7WDaX+JbIEEqgPARowU83vPTDX3hatWJ/imFMJSKBCBN6TvNDj+7mIkSRNAhKQQDcBZrIUU+qKazhHdN7eUpzI5+kR9QmdLThG60RHTnzPR/NMB6l5z9QS1YfAVOuPKMFaEX+fnRUU5zUJSEACMxGgp3e7iUA/nSmw1yUggdYSYCo+DlGn4TC9pfNEjl8XfTb6brRDtGnU6PVHDL9rEpDA6AlsniR5GdtvJkmayudp0VGTXPOUBCQggZkILJkAC0bHRNfMFNjrEpBAawnc21VynKV7ou6OFUaU/mkiLLvsrhedM/G9kR+OIDXysVqoGhBget3vossnyevf5Rw9OD+Z5JqnJCABCcxE4PUJQEPnX2YK6HUJSKDVBF45SemvzDk2apjKaL/Q8XLBVAGacN4RpCY8RctQRwJUMFMNT7NbDM7T8XUsmHmWgATGTuBVycGDY8+FGZCABKpKYI9k7CvRGhGdKYXROcsMlulsuvbLdPfV6pojSLV6XGa2QQSembJM5SCdlmv/FnVWWg0qukWRgASGSGD5xM3uUyym/u0Q0zFqCUigngTYAOrn0RoT2ccp6rTF8+VJnSe6jrfM96naL11B6/tVB6m+z86c15fAjsn6stG59S2COZeABCpK4BPJ15zoR9GjFc2j2ZKABMZDgHb/Z7qSLjpj+US8G3SNaDInaYucf2p0dtRo00Fq9OO1cBUlwPD0mREvW9MkIAEJlEWA3ev2jGjkvK+sSI1HAhJoDIFVUxJeHN09akQBOXdXxAjShREvIsYh6jTaLxdFk72/sTNc7Y91kGr/CC1ADQm0Yv5uDZ+LWZZA3Qm8OAVYKrohurvuhTH/EpBA6QTY3ZLpt1gxcoRjVIwesfPl6lyMLRZ9YP7RX360pv2ig/SXh+6RBEZBgL+5TaLp5u++NdefN4rMmIYEJNAoAn+b0rD50rcaVSoLIwEJlEXgu4moaPt3jiJxzPbeh3dcZye77o4WXlEyXfsll5thBaRmlMZSSKD6BJj+Qq/MVIunqaReEr0m0iQgAQn0SmD3BKR3Fwfp0F5vMpwEJNAqArzDqNMxKgrPCNK7It5/dHTEd0abaLOsGGE7RUtHZ/Ol6aaD1PQnbPmqRoAGzHHRH6fIGJXSOyIqKk0CEpBArwRWTsD7o7uiyd6v1ms8hpOABJpLgM2haGd0Gt/ptD04KkaNiml4OESvjjDaL2dEf+BL000HqelP2PJVjcBM83e3S4a/Gm1ftYybHwlIoNIE6OmlcXNkpXNp5iQggXES+O4kiTOiVDhEXL6l4zt+wq2cjM3UfnksVEN++qLYhjxIi1ELAosklwxv/2qa3NID/FB0zTRhvCQBCUigkwCvDVglord3uvql8x6PJSCB9hBYPUV9ecQOdd1T7GhznB4V9skc8C61Z0dMuft+hL+waXRA1ArTQWrFY7aQFSGw90Q+2CJzKntvLvB3ef1UATwvAQlIoIsAi6vpVOEFjidGmgQkIIGCwLo5uDQqZo0xpQ4nic8/RQdHH4oKYwnAi4ovE58vzOfC0W+6zjf2qw5SYx+tBasgAYanj4rorZnM5uTkGhEV152RJgEJSKAXAvsm0FYRTtLcXm4wjAQk0BoC/5GS4hx1jxwB4JURW3vPZLRfjo/ojGmFFd5kKwprISUwZgKbJf3ppr8wB5j1AwxvaxKQgAR6JUAjZ6Xo5F5vMJwEJNAKAjhFG3WVlJGjwq4tDmb4xEGarv0yw+31u6yDVL9nZo7rSWCtZPuZ0XQVzFK5zihS51zgfNUkIAEJTEmAmSD3RjSEDp8ylBckIIE2EnhVCr1C1D16xG6XTOln6t1MxrqlmdZPzxRH7a7rINXukZnhmhKg9+W+aLrtdxk5ekPEXF9NAhKQQC8EnpJAy0cLRo4g9ULMMBJoD4G1U9TOESOOH4yeHL0pWjaayfZKgEejC2cK2KTrOkhNepqWpcoEcJDYDYZteCczGjd7REtEP5ksgOckIAEJTEJguZyj3rggcu3iJIA8JYEWE+Cl0Q9HOEaINkix/8CaOf67aCaj/fKLiHhaYzpIrXnUFnTMBDZP+tNNr3sk1/8jenN0d6RJQAIS6IXA1gm0anRRL4ENIwEJtIYA0/ZxgraJ3h8xBZeRoMJByuECtD1msi0SYLr2y0z31/J6J6RaFsBMS6AGBJ6RPDLMPd32mMwTZqH1QZEmAQlIoFcChyUgnSvf7fUGw0lAAo0n8NSUkFFlptIxGNK9BonRpN9GX4ums7VykTZM6xwkR5Cm+7XwmgTKIcDw9OXR76aJ7mW5xi5UN00TxksSkIAEOgnwP/zsiM5ON3fpJOOxBNpNgA5Xpt7OmQbDC3Jtpm27ab/wrqTLpomnkZccQWrkY7VQFSNABTNT78uHEubp0bkVy7vZkYAEqktg5WRt6YhGzv3VzaY5k4AERkyAqfqTOUeMHGH/GvWyZpH2yxFRcV8O22GOILXjOVvK8RLYPMnP5CBdkjA/Hm82TV0CEqgZgbnJL42cz9cs32ZXAhIYHgF2wv1qxOZPD0WMAGFsssC0OtYUfTjqxbZMoJnaL73EU7swOki1e2RmuGYEnp388g6C6UaGmBv8reh1kSYBCUigVwLLJOC60TG93mA4CUig8QQOSgmLGWJzcswGDYtFC0d02E63HjqX/2ysPWKTB6bxts50kFr3yC3wiAkwPE2PzXXTpPufufY30SumCeMlCUhAAt0Eds0J3q/Wa4On+36/S0ACzSKwdoqzYlRMicNRoo0xm1Fm2i+sn740ap0VHmbrCm6BJTAiAlQwx8+Q1oO5/odo/xnCeVkCEpBAJ4ED8oWG0MbReZ0XPJaABFpJgPYGDhIzU6gb+MR4hcitEdPsvhrdEc1ktF9aOb0OMI4gzfTr4XUJDEZgs9w+UwXz3oRhGPvKwZLybglIoGUE2NiFBhANH00CEmg3ATZsWT2ibU+9UDhHOZzvLDHVjg2hTuZED9ba9Uew0UHq4TfEIBKYJYHdct+S0XTTX5gTzA4xn4s0CUhAAr0SYH3jQtEp0U293mQ4CUigkQRWSql+EHU7RRS2GEmivYHoWFk+ms6oX5aLzpouUJOv6SA1+elatnETYH3ASdF0Q9kMd18RnR9pEpCABHol8PwEpP74p15vMJwEJNBYAt9OyZgShzOEMJyledG/REzBfSiizrgqui2azoiL9dM3TBeoyddcg9Tkp2vZxk2ACubwGTLBNpxMwXMXqhlAeVkCEngcgb3y7d6oaAw97qJfJCCB1hBYJyXdKWJEGeusExgIuT3aI9o/ot3/hagzTL4+wWi/zLQ84Ak3NemEDlKTnqZlqRIBHJ+NIiqk6WyfXERLRN+fLqDXJCABCXQQWC/HV0cXdJzzUAISaB+Bg1Nk2hwYjk/nNDvOfSaivngnX3ownKpnRR/vIWxjgzjFrrGP1oKNmQC9u3RAzNR4uSZh2MHuyEiTgAQk0AuB1yQQvcU4SJoEJNBuAmun+J1OEU5SIc6z7ogpub3arglIp+05vd7QxHA6SE18qpapCgQYnmbaHO8omc7emotrRo9MF8hrEpCABDoI/H2OqTN4wbQmAQm0mwD1AA4RhkPUKc5TV/wy6tVov5wc3dnrDU0Mp4PUxKdqmapAoNf5ux9MZg+MeBeSJgEJSKAXArznhM1fftJLYMNIQAKNJbBISkYb4ozofztKWThMnPp69K6OazMd9tp+mSmeWl/XQar14zPzFSXA0PS6US8LHK9PuNMrWg6zJQEJVI/AnGRpsYj3mWgSkEB7CXwyRWeWCiM9P4/ujzodo3yd3w75VD4/HX02Yjvw6YzpeBtHvbRfpoun9tfcpKH2j9ACVJDAS5MnttO8pIJ5M0sSkEC9CeyX7C8Z0QmjSUAC7SSwfor9/omiUx98LHo0Yjod6xOZZoezdHF0UvTUCNstwgGaylirxOAJ24K32hxBavXjt/BDIsDwNC9/pbKayfZMABs6M1HyugQkUBD4txwwlebW4oSfEpBA6wj8TUeJcYYwBj0WnH/02A/Oc26NCKcJbRQtGk1ltF9Yr8RoVKtNB6nVj9/CD4nA5om3l+FppuK9O2L+sCYBCUhgJgJPT4DFoz9Gn5spsNclIIFGEmD0aLp2Ax0ojB79KfpAxG66rHNmZssp0QPRVIaD1Ev7Zar7G3PeKXaNeZQWpCIEqLg2iHqpYHjJI42cKyJNAhKQwEwErk0AeojfPlNAr0tAAo0lUEyXKwrYue7owpxkbdJS0Q8j2hk7RG+I5kXfiKYy7lkv6qX9MlUcjTmvg9SYR2lBKkKA3pe7o6t7zA8LKzUJSEACvRA4NIH4v31ZL4ENIwEJNJLAi1KqzhlgxRQ7CvvfEfVEpzHi/O+dJ6Y4Jl5Gl1i31HrrBNx6GAKQQAkEcJB63Xp354Q9PtquhHSNQgISaD6BzVJEpslc1PyiWkIJSGASAk/Kuf27zhcjSHwyi2W2Rvvl6KiX9dOzTaM29+kg1eZRmdGaENgi+cTp6cVWSiAqO+YJaxKQgASmI7B2Li4bnRsxbUaTgATaR4C1REyVKwynqBhB4vO04sIsPrfMPU6vmwCngzSL3yBvkcAUBDbP+VUiGjC92NsmAv2+l8CGkYAEWk3gnSk9u0+xxkCTgATaSYBtvOlULUaNcIqKYxynE6PDI9Y2/33Uqz0tARl90kGaIKaD1OuvjuEkMDMBhqeZ+nLlzEEX2Dth2JGK6TIP9xDeIBKQQLsJbJzisztV8e6TdtOw9BJoL4HJnBjaEm+K/jnaI1on+my0ddSL0X65M7qql8BtCKOD1IanbBlHRWDXJDRZxTVZ+gfm5JyICkyTgAQkMB0B6gp2l7olum+6gF6TgAQaT+AVKeE9HaVkFIl3HDGStPbEcT7mryVajYMeDAeJkSdtgoAOkr8KEiiPwDMTVS8O0pMTjp7g30VHRJoEJCCB6Qg8IxeXjJyOOx0lr0mgHQRwhBgZYrpdp30jX5iRMm9CN+bzmKgX2yqBemm/9BJXI8LoIDXiMVqIChDYKXlYJupl/RHO0ZkRw+GaBCQggZkI3JwAbOjy4ZkCel0CEmgkAd59RJvhB9EpEQ7N6yKcIYxRpDnR9hGzWZ4fbRR1jjTl66T2rJxdOTpr0qstPcn7FDQJSGBwAgxPnxExBWYmY3icYW8WRfq+gZloeV0CEnhLEDwQ/VYUEpBA6wismhJfGrFJC44Q2jY6IFozYjYKHSiFsU5xz+JLD5+0X2iLXNVD2NYEcQSpNY/agg6ZABXMr3pMg8ptXnRUj+ENJgEJtJcAjaJ/jKg31movBksugdYSeG9KvlhEm516oLCP5gAHic5ZjGtoQ770Yf20X/qItt5BdZDq/fzMfTUIzEk2Nol6dZBYq7RIhJOkSUACEpiOwOtyccFobuSIcyBoEmgZgZdPUl4cIdoeJ0S7TVxnbRJT+L868b3Xjy0SsNf2S69x1j6cU+xq/wgtQAUIMJRNL2+v01/enrDsOENFpklAAhKYjgC9xzSE9p8ukNckIIHGEqC9gENUGI5QYZ2jSpw/OfpEcbGHzx0Sho2jXH/UBcsRpC4gfpXALAjsknuOi3h5Wy9GZcd6Ak0CEpDAdARYZL1EdH907HQBvSYBCTSWwNdSsk6nqJhK1+k0UfhHo35Hgmi/4BzdGmkdBBxB6oDhoQRmSYAK5ns93stOMT+PqMTe0+M9BpOABNpJ4IcpNrtjntrO4ltqCbSaAJs5UQewzX+nFc4S0/TpmL0qYhbLz6JPRf0Y7Zd+nap+4q9tWB2k2j46M14RAlRKG0S9VjAvTljeZ0JPjyYBCUhgKgKMHBWzPL41VSDPS0ACjSXwmZSM9UG01XGKUDFqdGeO2ZyBHevY4W42RrybRQfO5uam36OD1PQnbPmGTQCHh7VEF/WY0HcT7o/Rj3oMbzAJSKCdBNZPsW+P6IA5vp0ILLUEWk1g05R+zgSBwjHiKx2sdLSyORSdtLO15+XGRaJzZxtBk+8reqeaXEbLJoFhEmB4+ujooR4TeXXC0WPD2641CUhAAlMR2C8X1ooui26eKpDnJSCBRhJ4c0q1dtTpGFFQRotwmtjZkin7/xHN1mi/nBD1un56tunU8j4dpFo+NjNdIQK8gbrX6XVke+OInuHuSo9rmgQkIIGCwDY5YP1RP/VLca+fEpBAvQm8I9kv2gmda46uz/niO9d5P9JsDQfJ+mUKejpIU4DxtAR6IEDvLkPgvU5/4e+NnuBPR0UFl0NNAhKQwBMIfHzizP884YonJCCBphPo3tqbqfxMzz8gYqMnjN1w3zf/qP8fi+cWXiirgzQFu6o6SOQLz3a1iXw/J5/fitjNY+eJc35IYNwE+B29N7q8x4zQG7xltE+P4Q02HALWL8PhaqzlEfj7RPXFaOHolPKiNaYRELB+GQHkFiRxXspYdKQyUsTv1ZMj6oPXRatET4l4xchs7AW5aV50wWxubsM9AK+arZUMXRnhDF0R0Zj8cYSxzuOoaCe+aBIYMwEcpJ9GRSU2U3ZWTwB6gb40U0CvD42A9cvQ0BpxiQTelbjoUKHz5e4S4zWq4RKwfhku3zbFflIKi2PUaXxnSt3W0Y3RIO9TpP1yTES7WqsJgY8kn5+IcN72iGh8viEq7L05YK/3soxfMjx1TQL9ErgqN7ymj5uOSNhbI9YWDNvmJoF9h51IDeO3fqnhQ2thlt+WMlO/fLSiZbd+mfzBWL9MzsWz/RFgGh2dqYg2cOfnI/nO6NGgRv2y/6CRDOn+StQvOCFVMzzjoyN+IU6I2O3rlKiwE3OwUvHFTwmMicAmSZfewl63x5yTsAyPE/6MSBsPAeuX8XA31d4JrJege0WrRcf3fpshK0DA+qUCD6HmWWDb7n+NGC1COEiI0aJbojdFN0SFsY7o7Oj6aL/i5Ayfy+Y67ZdfzRCu1Zer6CAdmSfywYiXY7FI9Z7oLRENTOz10YXzj/whgfER2CVJXxZd0mMWqIyWiq7pMbzBhkPA+mU4XI21PAIvTFTPjOgkPLO8aI1pBASsX0YAueFJPJryzesoY+EoLZJzdLJ+I9q24/ohOaa+WDXiGh0rM9mLE4C29e9nCtjm61V8Uez380DYGeykiMbnZtGp0csjRpPY2ePZkSaBcRLAQeqn92XPhKf359hxZtq0F7B+8Zeg6gToEGSdASPND1Y9s+bvcQSsXx6Hwy+zILBd7rkrWj7COcL4ZBQJJ4kpdi+NTouwFaNiAIFBD+67PprOaL/gzNMJo9WQwIIdeeaNwThIfxst3XG+jMMbE4lrkMog2a44WEv0kj6KvETC7h0VFVkft84q6Nzcte+s7mzHTdYv7XjOdSslu1KdEt0c/WOFM2/9Mv3DsX6Zno9XJyfAGnuclkI4RZ3HfMdBek1UGB0qjDgRjk5bnKSZ7KoE2G+mQGO8Xon6pYojSMUz4ZegsD/l4LCJL6/IJ970Dye+z/TBLxJvJJ7KmIvJyJQmgV4JbJuA9NKc0+sNCXdv9LM+wht0uATKql+em2zSeTOVMa3y/qkuel4CXQRo7DAdd4WonxHqrmj8OmYC1i9jfgA1TH6V5PlTUTFqRBFwiDoNR4h2xCEdJ7+W4+MiOldok+AoTWcb5SJ1zFnTBfLaAgtU2UGa6vlskgt4yL06SBcn7DFTRZbzG0cPTXPdSxLoJrBLTvwmopdDaxaBfuuXhVP8xadBwD+7zn940wT1kgTmO9v8TrE+4Dx5NI6A9UvjHmkpBZqTWI6KJvtfwTkcJZwjBgv+fuJ7Pv5sjAihXoz2y5XRJb0ENky7CTjFrt3PfzalPyk3fXI2N47wHpw3p9iNEPgUSVm/TAHG008gQA8yG79cGvF+tSqb9Us1no71SzWew6C5+GIiYOQHR6gQ34tzdOL/KGLmSi9T6BJsSjsyVxh1qrJVon4ZFHSVAZs3CQyDAL05bBzyq2FEbpwSkEBrCayUkt8QLRNZv7T218CCt5DAFh1lLhwkPo+Ibop+HP08YpSI0eXXRrO1LXOj9UsP9Ko6xY594PeJaIjyT+PR6Jro8ujQqHN+b75qEhgZgd2S0pMi3mek1ZOA9Us9n1vTc71mCnhHRC/x8U0vbIPLZ/3S4Ic7hKItlzjZubnbGE1+WTQvoq3O9Dp+t7CvR/8d9bvL5da5h/WNZ0XaDASqOIK0evLML8a7I7b0viLCOaJXjXOs/Vg70iQwDgK7JFGm2N3ZZ+KvTHh2qNHGS8D6Zbz8TX1qAgfl0s7RLRH/A7X6EbB+qd8zG2eOGQT4bsS6Q2anYHyi9aNnRRht9QXnHz32A4dpTsf3Xg9pv5wfXd/rDYarFoFvJTuHTJOlg3Pt09Nc7/eSc3j7Jdbu8DjoB/aJgIqMzULO7PO+QYLPzc2uQXoiQeuXJzLxTDUIHJxsXBB9pxrZmTYX1i+T47F+mZyLZ59IgFfWMCrEDCnWGhWf/5djxLlVo8L+IQeMJqEPFCf7/Dwh4T/T5z3jCF6J+gWvtGpGD8z3p8kUU+wYJtQkMGoC9PKwReav+kyYkSOGtW/u8z6Dl0/A+qV8psY4OIGdEgXb9K4R9Vu/5BatIgSsXyryIGqQjaclj0zXpwOVESPE+iIcIxwk1hzhKBT2uRwsGzEl7xPFyT4+ae9vHlm/9AitimuQ2JL7gOjCiMVpncbc7IOi0ztPeiyBERF4QdKhMmOIuh+j8cO6OXqAtPESsH4ZL39Tn5zARTlN44iXop8YafUkYP1Sz+c2jlzTxuUdnEydwznCKdo/og5gZtPhUbfd3X2ij+87JywO2dl93NPqoFV0kL6aJ7JGdF10bXR7xC/OMtGa0RHRgZEmgVET2CUJ8g/w/j4T/nbCrxBd2+d9Bi+fgPVL+UyNcXAC/J/jJY+bRa4PGJznuGKwfhkX+fqlS2cra+w3iHCQsGuiU+Yflf+D9sup0R3lR93MGKvoIN0X1O+IPhmtG+EU8YvEaBK9bDhOmgTGQYAKhn+A/Rq7zWjVIGD9Uo3nYC4eT4Be4xdHTn95PJe6fbN+qdsTG09+me52RrRehHPEIADnnhcN00H6ReLXJNAzAYYyfWN5z7haG5AGDHODN+6TAHOGfx69r8/7Bg0+NxG4ScOgFAe/3/plcIZtiOFrKSTTcPerSWGtX6rxoKxfqvEc+s0F091wirrFpg2LR6tHZdrCieyhaPsyIx1iXJWoX/BYNQlIYGYCL0mQB6NLZg76uBBUSndFbN2rSUACEpiMwDo5OSc6crKLnpOABBpFgPYEzhFWOEnsYndb9Ifo2ujYqJjltVDHcQ77tj1yB/XLb/u+s8U36CC1+OFb9L4I7JLQrH+b19ddCyxwb8IzknNIn/cZXAISaA+BVVJUGkauD2jPM7ek7SSwTYr9hoipdRgO0s3RiRFTNBeNsOdGdMryehDaEWzi8rfRbIz2y3ER8Ws9EtBB6hGUwVpPYIsQcH1A638NBCCB0gn8U2JcIzql9JiNUAISqBoB1tcz5a0wHCVmpnw3wgliKn9hc3KwZbRgtEj09Wg27XYcJNsvgdCPFcN3/dxjWAm0jcAGKfDTIiuYtj15yyuB4RKgcfSmiCk0roUdLmtjl0AVCHTPQqEOwIHZPmJK/g3RqhHGtU7je/e5zuuTHbN+ev3I9stkdKY5NxtPdJrovCSBRhKg8rpmQv0WkMpsjX5vMrwEJNAKApuklPQM02v8hVaU2EJKoL0EVkvRn9VVfKbY0U5gVIm64MvR1hGjSdi1EfUDm7iww3O3g5VT09peucpUvYumDeXFJxBwBOkJSDwhgScQGGR4+u2J7XnRx6PTnxCzJyQggTYTWDqFZ3E2jRfXB7T5N8Gyt4HAP6SQS0Q4RIVjRLmpA2iPM5XuoOjpEe9OXD6aG7GzHY4Rjk6/Rvvl5xFpaH0QcASpD1gGbS2BQdYf3R9qVHyXtpaeBZeABKYi8Opc4O32v5gqgOclIIHGEFi2oyQ4SUype190bVQ4TLTL9464hnOE0XkyG+eIe7eKnF4HiT5NB6lPYAZvHQGco5Wjc2ZZ8ufnPv7O2Opbk4AEJNBJ4OB8oUf56M6THktAAo0jMCcl+sFEqXCG0MnRZyPOPxxhZXaorpv4WEOtgwTZPo0HoUlAAlMTYHia6S9XTR1kyivL5AqNn7OmDOEFCUigzQRYU0DD6Nw2Q7DsEmg4gQ1TPpwUps0V0+ko8q7R6tEnIjZTYAvw70fHRmUY7Rc6Z68oI7K2xaGD1LYnbnn7JUAFM9veFxZW/jG6NtIkIAEJdBJYLF+oX26LWICtSUACzSTwzylWMb1uTkcRmWb3huio6B+jYhQph6UY9csRpcTUwkicYtfCh26R+yKweULP1kG6O/fuE32rrxQNLAEJtIHAHikku1ad2YbCWkYJtJQATtDTosIxKqbXgYPRpA9EZ0cXR4wilWlbJ7LZtl/KzEct49JBquVjM9MjIrBT0mGXqdmuP2JHmk1HlFeTkYAE6kWADVwWjz5dr2ybWwlIoA8Cr0nYZ0Q4SjhHbL6AsM7pdqvm+8vmny3nx2aJZpXIDphZ8tRBmiU4b2sFAYan2Zr71lmW9qO57/PRtrO839skIIHmEvhiisbUOtcHNPcZWzIJ7N6BACeJUWOWt9wb0YlaGO1xptuWZbRf2D33yrIibFs8Okhte+KWtx8CVDCDDE8/M/fTK3RBP4kaVgISaDwBGkhMp6FBxFRcTQISaCaBw7qKhZPE3z8bODHtrhhZOinHrEUqywZtv5SVj9rGo4NU20dnxodMgAqM6XGDOEjMK/5oRE+RJgEJSKAgwP/ehSJGmDUJSKC5BH6eotERUqw9Kj7n5RwjyEy3Y6rd26MybctENkj7pcy81DIuGoGaBCTwRAJ75tTC0W+feKmnM7x/gA0eeAnkt3u6w0ASkEBbCNAYWjqi91iTgASaS+BFKdpyUfffOqNHH44WjX4SXR6VZdsnIl4z4itGBiCqgzQAPG9tNAGGp4+L7pllKV+Q+9jW0y02ZwnQ2yTQYAI0mJha97UGl9GiSaDNBOhgZXTo/R0QGD3C2M77jxEjyPdFZRvtl3Oim8uOuE3xOcWuTU/bsvZDYND5u7smMXpwZjsC1U9eDSsBCdSLwL7JLg2josFUr9ybWwlIYCoC/N/HOXkwYgRnzagYPSo+f5dzW0TDcI4S7fz3qzm9DhIDmA7SAPC8tbEEFk/J1o8GqWAYfWJqHW+x1iQgAQkUBJhas0LElJrZjlAXcfkpAQlUi8A7k52NJ7LENHum0tIRUnSG4CSxBTfb/A/DmBnGBlGDtF+Gka/axekUu9o9MjM8AgLMGZ4XXTRAWgydaxKQgAS6CbwwJ9igwe29u8n4XQL1J0C7uhgpKgYhCueoKB3n3xWdHx0ZsVlDWfbcRMS6JkaxtAEIFA9vgCi8VQKNI8D0uqMj5glrEpCABMok8O+JjF2rfl1mpMYlAQlUgsCXkovJ2g78zReOEp//FB0aHR+VabRfToxY46QNQEAHaQB43tpYAgyLOzzd2MdrwSQwNgL07DK9jrUHh40tFyYsAQkMi8CtifgHEQ4RVjhFnSNLjDAhXhT7nGjVqCwbdP10WfmofTw6SLV/hBagZAJrJ75nRIM4SDSC6EWi4tMkIAEJFAR4fcAi0fcipvFqEpBA8wgcmCKdFN0dFWuNcIgKZymH84+pAxjpuY0TJdhiiWOjaJD2SwnZaEYUOkjNeI6WojwC9L78KWIB9WyNHuI1IuYCaxKQgAQKAnvkgIaS23sXRPyUQPMI/CFF2jV6XcR23/zNdxvO0lXR7hE73pVhz08k/xuxtkkbkABDfpoEJPAXAjhIh0edPT1/udrb0XUJ9oHo0t6CG0oCEmgJgU1TTnqVB+mAaQkqiymB2hHYKjl+fXR19PmI0WIcFow2BSNGcyIcJsTo0plRWUb75dioLIerrHzVMh5HkGr52Mz0EAlsmbgHHZ7+h8TxqajY6nOI2TVqCUigJgSY/rJOdGU02SLumhTDbEpAApMQWDXnToreGH0sYqOnn0WFA0THyH9EheEgPan4UtInDtKg7ZeSslL/aHSQ6v8MLUF5BDZJVGtEZw8Y5Wm5/6bougHj8XYJSKA5BJixQYPoiOYUyZJIQAITBNjcib9x2tWMEuGs7DChlfPJ1PsvRmzewEgSW3v/JCrLlklEdMDoIJVElIepSUACjxGgQrss+v2AQHi/AfOO6THSJCABCUDggIhpNr/jiyYBCTSGwGopCaNDOEb8jTM6hBP0rOi4iA5T7Jpo++jVEdNsvxqVZS9KRPdEl5QVYdvjcQSp7b8Blr+TAA7SoO8kWClxsAseFaQmAQlIoCBAL/It0QXFCT8lIIFGEKBTdPmOkuAk0b4uptd1XFrgrHx5R8RoEqNIGNPymXGCM7VKNBuj/XJ0VKx5mk0c3tNBQAepA4aHrSewRQgMOjzNMDcLJH/cepoCkIAEOgnsnS+sPbqx86THEpBArQnQGfq8iNEjjO8IRwVHaCZjat5nIkahdoh4RchsbOvcNGj7ZTbpNvYeHaTGPloL1ieBbRN+ueicPu/rDr5PTjCczkJsTQISkAAEaLwsMYGi6DWe+OqHBCRQYwK/SN43jHCKGDkqjCUsa0cx8O7yAABAAElEQVQvjf4n+nS0eNRtK+fEvImTC+Zz1e4APXx/esKQFqNTWkkEXINUEkijqT2BXVOCc6MbBiwJGz1QCZ4zYDzeLgEJNIcAvcL0KH+8OUWyJBJoPQFGjXbroICThBWO0g9z/KOIwYgdo0Wi/aNO+2W+0KH6tIj7Phn1a7vkhqsj1zf2S26a8DpI08DxUqsIUMEMOjxNL86G0R1RUUHmUJOABFpOYKGU/9boGy3nYPEl0CQCjPzcFzE6XIwgFU4SHSLPiQiDg8TGTTtF3fZATmwWMcp8XXRt1K+V0X7pN83Gh3eKXeMfsQXsgQB/B1RQgzpI9AJ9L3pDpElAAhKAAFNs6Di5NrLjJBA0CTSIwL92lKVwjvicEz0vYiCCv3u0QfTcqNseyomTomu7L/T4nRfUDtp+6TGp9gTTQWrPs7akUxNgiJweIKbYDWIstnxqNHeQSLxXAhJoDAGm2zJqRGPp9MaUyoJIQAKsF/pw9Nro0QkcOEGdRhsbZ6kQo0ov6AxQwvGWiWPFaLId80qIvr1ROMWuvc/ekv+FwC45PDG66y+nZnW0Xe5aNWLR5Z9mFYM3SUACTSJAA+nOiMbUe5tUMMsigZYTeE/K/8GI6bM4RoVzxCcOUWE4T8UoEufKdmRov1wYXUfkWnkEdJDKY2lM9SVABfPTErJ/e+I4Nrq0hLiMQgISqD+BV6UILMw+o/5FsQQSkEAHAabl0/HRaZ3OEbtV/jyig4TO01uig6NDozKN9ovT68okOhGXDtIQoBplrQjQeNkoensJuWbonJ6jL5QQl1FIQAL1J8AC7mWjH9a/KJZAAhLoIPCDHL9s4nsxYsQnjtFJ0cXRgdE90bCMEeotos8NK4E2x6uD1Oanb9khUDg155eA49uJg6FuTQISkAAEXhktHB3DF00CEmgMgSNSkmdHp0ZFW5oRpCui50ajsB2TyJKR7z8aAm03aRgCVKOsFQGGp3mJG1ttDmKb5uY3RX83SCTeKwEJNIrARSkNDaabGlUqCyOBdhNg++7To49H87pQXNP1fZhfab+QD6b3ayUTKLzekqM1OgnUhgAVzFdKyO2DiYPeI0aRNAlIQAJPCYI3R9eJQgISaAyBRVMS1haxQyX/84vpdTmcf3z8xCfXhm20X3457ETaGr8jSG198pYbAktH60ZlLHBk5GihiMpTk4AEJPCKIFgqYi2CJgEJNIMAHR9LRDhGnW1oHCLEeiA2a+q8lq+lG1N3mblSRvul9Mw1IcJhP8AmMLIMzSXw4hTtvuiSEoq4duJgwwfXIJUA0ygk0AAC26YMNKLYCliTgATqT2CxFGHziPcZFcbfeOEcFaNJu+Yc7ycapj0vkTML7NxhJtLmuHWQ2vz0LTvD00dF3XOI+yXDUDsV58n93mh4CUigsQToNGGL3+sbW0ILJoH2EKAD9LfRf0eFI9RZetYadrYlfpbvbALVaavmC22FMoz2C6NHdPJqQyCggzQEqEZZGwL08DBfeFBbMxGwycPDg0bk/RKQQCMIbJRSbBxd3YjSWAgJSIAd65iSv2DUOWpUkFk9B7dFjCZxfcWI7f0Z5aGtzbolOksIwwjToFY4SIPG4/1TEODBaRJoI4ENUuj1ojKGp3+XeN4e3RhpEpCABF4VBPQ4s4udJgEJ1J/ANSkCzg9GZ+iVEe2Iwvh7Xz4qHCTOsyaZtUJbRUyJwzj3qeiZfJmlsbU3aTOCpA2JgCNIQwJrtJUnQO8LvbsXlJRTeoY6h9dLitZoJCCBGhJ4UfJMQ+kdNcy7WZaABJ5IAAeJ95rRqcrU/GKAoXCacmr+yFHn9LvP5hxT4O6fuJaP+euXBp0W94LE81DkmmeIDsl0kIYE1mgrT4Ah7rJ6X/ZOXIdGy1a+1GZQAhIYNgGm3NKTfFc06PvVhp1X45eABHoncFiCbhG9LFonwhkqVIwc8Z3OUmaovD/Czoy+EDHyNDfaPxrE6OA9JnpkkEi8d3oCOkjT8/FqcwlsmaKV5SA9NXE9OSpr8WVzqVsyCTSfAKNH1AUnNL+ollACrSTAVt+dzknnKBLHOEhP6iLz7nxneh0dKOd3Xev369a5oaz2S79ptya8DlJrHrUF7SCAc7RSdHbHuUEOv5abnx/RM6RJQALtJnB/ik9D6IvtxmDpJdBIAiunVJdHvPewMJyigyO2/2YEiel3P4m6jeuD2tqJ4OmRDtKgJGe4XwdpBkBebiQBhqeZu3tNSaVjet13SorLaCQggXoT2C/Zpwf5jHoXw9xLQAKTEHhJztEBgiNUjBxx/OOoaFPzyS52wzDaL0zfxUnThkigWGQ2xCSMWgKVI0AFU2bvC7vYMbdYk4AEJMDmL/dEOEmaBCRQbwI4Q6+LaC9/O2L3uqLtjIPEhgsfiX4RHRmxgQIO02eiYRjtFzaJKJyzYaRhnCFQPGRhSKAtBKi4No8+V2KB/6XEuIxKAhKoN4Ftk312r9IkIIH6E/h5ivDsCIfkddGzog9Gr47YfOHWaL+IdySxy91mEU7ToOuMEsWkxvqjAye94kkJlEyAd9ecV3KcRlddAjsna1R0y5WUxSUSD7vTbFpSfGVFMzcR7VtWZMYzawLWL7NGV8sb6XyhfvmvWua+90xbv/TOapghrV+GSXeBBZ6W6Pl77tTe+c57iDCm2zF7hOsPRgdFw7RNEjlpsUNek60S9UsxX7LJoC2bBDoJ7JIvp0e8zboM2zWRoD3KiMw4JCCBWhOgLqDBxBQYTQISqDeBg5P9TueIY9YaMc2OzRrWjoqptAvmeN1omEb75bLo8mEmYtyPEdBB8jehbQSoYH5VYqE/lbgWjw4vMU6jkoAE6kngbck27z5iDZImAQnUm8A6yT7T8gtRGtrNy0Svjf47YuTokQhHqRg5pk0wDCu7/TKMPDYmTh2kxjxKC9IDAXp4GKIuy0HaM3EtHdEYujTSJCCBdhNg6u4fol+3G4Oll0AjCHwppShGkDoLRNt5++j6iFGjfSKmvTE75bjo3ojNWhhhKtO2SmRltV/KzFcj49JBauRjtVBTEGAa3ELRb6a43u/p3XMDjaH9+73R8BKQQOMIvDAlWiQ6tXEls0ASaB8BOj/nRKxRn+z9RcUo0e25zgySayM2acBxwlaJDpx/VM6PbRPNshEbQ2gjIPDXI0jDJCRQFQIMTx8f0btThq2QSG6MTiojMuOQgARqTeDvknvWH51T61KYeQm0mwBOETNNGD16VkQ7ebLBhO/kfLd1hmNaXuf37rD9fqf9QufuTf3eaPjZESjz4c0uB94lgdERoIIpc3ianqPfRgzBaxKQQLsJLJzi07v7zXZjsPQSqC0BnKFTIhyRbSL+pnGYcHaw+6Njov2iyf7OD835syOM7b8/Ov+onB9lt1/KyVWDY9FBavDDtWiPI8B23BtEjCCVYYsmkpujr5cRmXFIQAK1JkAjiikw9O4yiqRJQAL1I7BjsrzlRLZxiuj8fCi6PtouWili7fF3ordHV0RHR0+NMNrU34pwoFaPLo/KMBw3RrPK7OAtI1+NjgPomgTaQGCvFJKGy0UlFfYTiecVET1MB5YUp9FIQAL1JEBvM+uPWHegSUAC9SRwW7LdPXDw/Zz7YMSIEOuOWJu0ZvTFiLA4QkzHe3l0avT0iPO7Ra+KyjBGjxaLitGpMuI0jhkIdP8izBDcyxKoLQEqmJ9Hj5RUgosTD6KS1CQggXYT4IWRf4pY0K1JQAL1JHBBsn19VEyb5/O/IpwjRoXuju6M3hfNizB2x10rWiPaLKLTlHMvi/4qKsNov5wckb42IgI6SCMCbTJjJ8CweZnD0+xYRW8T0iQggXYTYPrLSdEB7cZg6SVQewIvTQmYKvto9OWIdYU4OowSMeuK47+JcKRwktjh7tMR9+DAcI6O2EuiwtHK4UCGg1Rm+2WgzLTlZqfYteVJt7uc66T4G0VlVjDHJb672o3V0ktAAiHAesRnR+dGz4jOiDQJSKCeBNig4Z3RhtGPIkaEWFfE33lhOD7bR7Qrro2uiLCdow9F90T/HJVhTK3bONq/jMiMo3cCOki9szJkfQnQ+/LHqKjEyijJDxLJ7WVEZBwSkECtCTxnIvdMz0GaBCRQXwLvSdZZY8wIEiPCX4heGTFyhGPEiNE/RDdPKB9/NqbYMgJVpu2RyEj3t2VGalwzE3CK3cyMDFF/AjhIh0dlDXdTWZ4SvT3SJCCBdhOgfmFqzeoR2wBrEpBAfQng4DB4wKYrtJH5+y4MJ4m/9S8VJ0bwSfrMWHlwBGmZRAcBHaQOGB42lsBWKVmZ0+v2SnxLRNc0lpgFk4AEeiVAA4Z3o3y71xsMJwEJVJbAScnZQxEjRThKX48Ko5P1/OLLiD6pX8psv4wo2/VPxil29X+GlmB6Apvm8mpRmdtjLpf4fh/9ItIkIIH2Elg6RaeOYX3A6e3FYMkl0BgCX0lJ+LumE/TgCOeEkSOm3l0avTUalS2ThNaNdJBGRbwjHR2kDhgeNpIAvS84M5eVVLqnJZ5loyNKis9oJCCB+hKgfnkgOqe+RTDnEpDABIHt88l0toUiRpBwkuhc/a8J5WOk9sKkdl908UhTNbH5BJxi5y9C0wmUPTzNEPsNUZkjUk1/BpZPAk0lQP1yRkSHCTtfaRKQQD0J0B5+V8Q7jBgxmhMxnf4n0biM+uXn0bxxZaDN6eogtfnpt6PsW6aYZQ5PE9/dEfOUNQlIoN0EaMAwtY6teG9tNwpLL4FaEmCUZm70SPSiiE7Qwmgj8ze+T3FixJ/bJL0y2y8jzn69k3OKXb2fn7mfnsB2ucx0uLOmD9bX1ZUn4mSHG4a+NQlIoJ0EnppirxdtFuEg0cjSJCCB+hBgyvzhESNGCIeIqXWoOMd237wTqdtoP3NtWLZ+Il4n0kEaFuEZ4nUEaQZAXq41AXp+zo1uKrEUn0xce0Z3lBinUUlAAvUjsFuyfHtE4+nJkdNuA0GTQI0IbDyRV5yhwjhmFAk9HM2Jdo7YDRejc/SXETvd8W6iFaNhGO2X26KrhxG5cc5MQAdpZkaGqC8BKpiye1++kDgPqC8Scy4BCZREgPrlyogGE9PshtmbnOg1CUigZAInJj7+bjun1eEgMd3uoxEOCteY6nZstGj0+ug5Ee1nOkf+MRqGUb8cOYyIjbM3AjpIvXEyVP0IzEmWnxmV7SAxxQ5pEpBAuwnsmOLjIF0TfTrSJCCBehFgBHiTCCeoU2zUcFi0fMRUOtoTS0UrRAtHhMVwpvg+DNs6kZbdfhlGPhsbpw5SYx9t6wv23BBgXcA5JZN4WeJ7R8lxGp0EJFAvAhsku6tEl0fscvW7SJOABOpHgNeAMF0OZ6fQ3+aYv+nvR4wmMdXuzOi66FsRHSPYbdFn5h+V+2PzRLdSxA6Z2pgI6CCNCbzJDp0Aw9MnRuw4p0lAAhIokwD1CyNHrGHYvsyIjUsCEhgZARyi10U4Q4wKsTkDo0o7Rryk9fXRS6LXRDtGG0Yfi34UrRetFl0dlW3UL+Tp2rIjNr7eCTB0qEmgiQSoYOjZLdMYiv9s9JXop2VGbFwSkECtCFC/MP2FEeqTa5VzMysBCRQEeHfZpyMcpWKKHTvf7hfxyfbeR0fY0tFpEeuQcKToHBnW9t9F/ZIktHER+H/jSth0JTBEAlRgVF5lz9+9J3H+Mboj0iQggXYS4P/mDtEV0Qui10eaBCRQPwK7JssLRgwWMJUORwmxrmi7qNMYPXpSRHiu7xgNw6hftozKbr8MI6+NjtMRpEY/3tYWjkYLvUHnl0xg9cR3VUQvkiYBCbSTwLNSbLb1/k7EWoSTI00CEqgfgWOS5d0jRoRoDz8a4QDhJC0frRzdGGEXREy/W5IvsaMe+yj953MSIxtCsOZJGyMBPFVNAk0jwPD0/0QPllywVyY+RqYYetckIIF2EqDX+cLoFdFbIpwlTQISqB+BvZJl2sE4SEy3uzPCOcI4v9r8o8d+3JsPOkf+LXpXxN/+MIz2C87RbcOI3Dh7J6CD1DsrQ9aHwLDm71JZPhDdWh8U5lQCEiiZQFG/3JJ4nXJbMlyjk8CICPwi6Twvoh3MlLn3RF+IcJaYbscmCedGnTY3X/4l+s+IcCtGZVtRv5Qdr/H1SUAHqU9gBq88AXpz14mGMX+XUakfVJ6AGZSABIZFYKFE/OyI+uVVEd/pddYkIIF6Edi5K7vMDPlExN/3yyPWAeEoTWbr5+QN0c3RWRGvFCnDqE82i4bRfikjf62KgzmXmgSaRODFKQxD4ZcOoVCfH0KcRikBCdSHAAu3acSwvpEF265HDARNAjUgsFzyuEZ0QfTCiL9j1ioXU+rm5JitvXF4ZrIPJcBTJgKxuy2dJd+Y+D7Ix265mTVQ7I6pjZmAI0hjfgAmXzoBhqePiuaVHrMRSkACbSdA/UID6kXR09sOw/JLoCYE+LudG50d4SB9K8IK54hPHKbuUSXCTGYP5yTOFca9fC/DyOevIzp5tTET0EEa8wMw+dIJbJUYhzE8vWTi/Ui0auk5NkIJSKAuBGjAUL+w/uDiqIxe40SjSUACQyRwQOJmZAZbK1okKpwjzmHMqOp15gltgasi6oHjokOjMqyoX8qIyzgGJKCDNCBAb68UAXp0WX9EL1HZtnUi3Dzaq+yIjU8CEqgFAabUsYsVDtJOEVv+Xh9pEpBAtQmwocq8iSzS7v12VIwAsdvt7yKmzdHp0Ytdl0AbRItGvFZksrVKpLNdxM63vRj1C+9aon7RKkBAB6kCD8EslEaA3pero4tKi/EvERH30tGP/nLKIwlIoEUEcIpoCJ0ZnRf9NtIkIIHqE3h/snhlxIjPo9GpEe852jZiyh2bLnw0Oijqx6aaWvdXieTo6KSI+A+MZrLnJ8BDEeG1ChDQQarAQzALpREY5vA0jSIWZt9dWm6NSAISqBOBXZPZk6NVIuqaP0WaBCRQfQL8314nos27SPTdaIeI7b2Zlv/XEdeYisdMkUFt3USwR0ScOEs4aDMZdcqx0VRO10z3e71kAjw8TQJNITCs9Ufw2SZi+H2yoXSuaxKQQLMJFB0wL04xmV5zV7OLa+kk0AgCTHHDQcEJKgyn5YfRYRFT7QqxTun4aLFoEGP6beHoMLWP7cBnMqbxO71uJkojvN75CzPCZE1KAqUT2DIxrhgx0jMMY27wUsOI2DglIIHKE1ghOWSN4+nRTyM6F0+JNAlIoLoEcI6YCouT0m20f3n3Ubfxf55R4su7L/Tx/c6EfUX0iYjRq7+LprM1c3GjSAdpOkojvqaDNGLgJjc0AvTuMnf3uiGlsHfiZe6yJgEJtI/ArikyI0YPRLdGl0Q3RZoEJFBdAnsma/zfZlpdsSlDZ245h/PEiBJihshl0ZXRoHZ4IkC9GO0XHKnf9xLYMKMhoIM0Gs6mMnwCxfSXYaTE3wk71TA/+L5hJGCcEpBApQlQv5wQ7RUxfeZDkSYBCVSbwHnJHu83KpwjPnGECvtGDti44Y4I52ROxLQ7zo3SqF/Y1KHI5yjTNq0pCOggTQHG07UiQIW3RfTvQ8o1iy1fF60UfTnSJCCBdhHYKcX9VMR2wMtFjh4FgiaBihN4R/LHCBGOD+0EhBOC/id6czQbWy83vSRiJPnI2UTQdQ9rnA/qOufXMRPQQRrzAzD5UgjsnFiWjM4uJbYnRvLrnGJXmh888ZJnJCCBhhNYJ+VbI2J9wIER0+zujzQJSKDaBHZP9ooXxBY5ZXRo/+hrxYk+P1dL+PMjnC3a0O+NvhDN1lgntXp0xmwj8L7hEHAXu+FwNdbREmB4+rSIqS/DsI8lUpwwKkRNAhJoFwHqlxsjFm3fMqF8aBKQQMUJnJP8FdPlGDXi7/eA6KsRO1GeGV0X7Rf1ajslIG2BRSIcpH2iQYz65YroskEi8d7yCegglc/UGEdPgAqG3t1h2TGJ+NLoj8NKwHglIIHKEtg1OTsuWiVaO6LRpUlAAtUn0DntHgfpmujTEQ4Oa4145xEjQqxFYhSnFzs3gRiVwvF6KDo5GsSG3X4ZJG+tvlcHqdWPvxGFXyil2CQapoPEXOX3RfMiTQISaA8BGlI7RNQvvFRy0WiJSJOABKpPAKeHv+HCVsjBYhH/058ezYkwwiw//2jmHxcnyJ4RU+4/PKF8zNq2zp3DbL/MOmNtv5HhQU0CdSbABgr8Hv9miIVgoefV0S+GmIZRS0AC1SOwabLEpgy/jp4X3RcdG2kSkEC1CeAcfWIii/+XT5ygNaJTI/6uC+PaSVE/bYhfJjwa1LZJBE+JXH80KMkh3O8I0hCgGuVICTA8fXxEw2UYRqXK1r5/O4zIjVMCEqg0AeoXpteyBomF3VtFdiwGgiaBihNghIj/352izdvpHDEr5OaIkSUcnnWiURr1C1uRU79oFSOgg1SxB2J2+iZABTPM4emNEv+c6NC+c+YNEpBA3QkU9ctSKciD0feiP9S9UOZfAi0gcHrKeGfE3y2jRIVxfHB0W3RTtFLEhg07RodEo7SifhllmqbVIwEdpB5BGaySBNjae/1omA4SzhELMR+INAlIoD0EWIi9XUT9wlQYRo5oVGkSkED1CbCp0jOiL0WMIhXGMbvGsY5o5ai4xv/6NaJRGfXJFtEw2y+jKksj09FBauRjbU2hXpiS4rxcNMQS08PDO0/ojdIkIIH2EGDx9GLRSdFLI6bxHh1pEpBAPQjcmmweGOEQzYuKtUgfyfEJUeEc5XD+tc9x0GF0kuwb7RexQUuZtlMio345q8xIjas8AjpI5bE0ptETwHlh44RHhpg085WXHmL8Ri0BCVSTAPULW/reFa0ZLRTxLiRNAhKoB4E1kk3WDn4+Ojtia26Mti+7UXY6SEfk+6eiTvtpvnwz+mqEQ1WmUb+cGlG/aBUkwBCfJoG6EmDB9H8MMfNzEjdD8PRCOcVuiKCNWgIVJLBr8sT0l3WjFaMydq1KNJoEJDACAvzNXhjxQldGgjAcJNYkLRx1OkfMQnlJ1Gl0iDw/KsIxokyct0RlGA6SI9JlkBxSHI4gDQms0Q6dwDpJ4ekRDZhhGUPy74neN6wEjFcCEqgkgcWTq2J9AB0lNIrK7kGuZMHNlAQaQmDHlANHqHCOKBbOzj9FjBTx/50p+qwr3D7q3MghXxd4OGJqHjNUHo3oKC1rDSLT9TaJhtl+SfTaIAR0kAah573jJEDvC0PTVGDDss0S8UejtYaVgPFKQAKVJLBDckWDibWHb45Yh3hBpElAAtUl8Jxk7eCIDRq+GNG50en44PT8IGIkiOmyh0QbRISfzHbPScL/ONo5wqkqw4gX6+fdS4/d4c+REXCK3chQm1DJBHCQjog6K7+Sk5jf20SPUzHEXnb8xicBCVSTAPXLaRFTa++IeJkj70vRJCCBahL4t2TrAxNZ4382bYMHI9YebRbxt/z26JPR30QLRU+LmKbP3/hkdk1Ovm6yCwOeo37h/Y1O3R8Q5DBvr+oIEt49PQHYMtHHop9F/AEwrUqTwNZBMOzhaSpRKrAzxN0oAtYvjXqcQykMDRjql82jf4g2jJhmo0lgJgLWLzMRGs51nJ/ODk2OmWLH3/JSEc/lJxHvNsQ5wvibXnf+0Wh/FPXLaFM1tb4IVNFB2i4luCzC42eXkbMitli9MnpmdHK0VaS1lwA7y60a8bsxLGN0ld+7LaM5w0rEeEdOwPpl5Mhrl+CyyTHvT8FBuiE6PWKqrSaBmQhYv8xEaHjX70nUnTNKOD4pmteV5Jfznc0amG53e3R8NEp7chJj5Ir6RZNAXwS+kdD7T9zxqnxeH3U2UA/I9+9OXC/j48ZEcl4ZERnHyAi8NyldMuTUnpr4j41eOOR0hhX93ES877Air3G81i81fngjyvo+SeePkVPQpwZu/TI5G+uXybmM4uz2SYS1gjhGfH4zWjSazOhs5+98HK/weHXSxZnrbNfmq9ZBoBL1SxVHkNYMpAs7QP0mx/M6vp+Y4zU6vnvYPgK7pMi/GnKxqTwZkl98yOkY/WgJWL+MlncdU6N++XX0aB0zb57HSsD6ZXz4r03Sx0S0Gd8R4SDxP/wTER3rzEgq7Lc5+FF0d3FihJ/UL+Szs107wuRNqs4EGB04J1o9YqoDu5TtFP1VhLf/y+hforLMEaSySI4unjuS1IuHnNzBif/k6ElDTmdY0VeiB2ZYhRsgXuuXAeC15NarUs79J8q6aT7Z5r+KnYkTWRzLh/XL5NitXybnMoqzJyURps0xfa7QQzl+cEI4JVWwy5KJv6tCRiqcB+uXKR4O/4i+FDEE+fvooogh01sj9qM/ImLhXVmmg1QWydHEs32S4fdhpSEnt0Li33zIaQwzeiuYyelav0zOxbOPEVgtH9QvxWZAv8oxax1XjbS/ELB++QuLziPrl04aoz3mXWX87U4lpt2N29ZLBsjfOuPOSMXTr0T9UsU51nj+9N6xY93W0coRQ6M3RedHndPv8lVrGYFdUl5GGG8eYrkZrfxIhHN+7hDTMerRE7B+GT3zOqX43GSWzrhLJjLNCPLdEf+wNQnMRMD6ZSZCw7v+lUT94Yj/31jxiUNC5/qvOTlmo/1yW3TlmPNh8j0QqKKDVGSbBjBbew9qCyaC5aeJxKkT08Cp4CUqGHp1h2n8Xawe3TvMRIx7rATKql/GWggTL50A9cvxE7HunM8/RSdNfPdDAr0SsH7plVR54S5OVDhDtOn47LSj8uW1nSfGdEz9cvSY0jbZPglU2UGaqiivyAV6Bn44VYCu8x/O93/qOtf9tfuPqfu636tBgN9Xdp/5yJCzs1PiXyg6ccjpGH31CPRbv3wwRfjnaYrB75H1yzSAKnZpx+Sn+H9Bg4v1At+LNAmUQcD6pQyKj8VB3fquaN3orug90ZyosKLepb3IWsJFovuKi2P63Cbpvn9MaZtsnwTq6CBtkjLSQ9Crg/TRhD04mspOzYU/THXR85UiwPQXtu1kit0wjYWe8yKHwYdJuZpx91u/fDPF+M00Rfl+rvHPW6s+gY2SRdY2/jrifyPPlQXe/A/RJFAGAeuXMig+FsfH8/HOqHCKcIQKK475P871NaOfRLtH/E2Pw+jcfWp0+jgSN00JzIbAjbnpvNnc6D0jJ/CZpHjCCFI9JGkwzWbxEaQ1rCTmJuJ9hxW58fZMwPqlZ1RjD/iu5OCKiVycls+HIjpJnIY9AaXjw/qlA8YYD9tcv1wX7owSdYt1YIh3mdHZWVzn+KBoXMZumIxKazMTqET9Qi9ZFY1Rgn2izSJ69B6Nrokujw6NWHCntY/ALinyj0dQ7JOTxsLRuIfjR1DUViZh/dLKxz5joalf6Bihl/8ZEQ7SzhGNLU0CvRKwfumV1GDhlsvtOD/FaFERG98ZOfpqxJTG1SPO0d7l73pcRv3yq3Elbrr9E6hizxi/zJdF746YY0qPHs7RMhHnmPawdqS1i8BiKS5TYIZdwTBX+V+j3SKteQSsX5r3TMso0ZxE8pyI+oUOuFOjl0fXR5oEeiVg/dIrqcHCsZ6ITsxu5+j/JqLlPNcZseEcnex8ficah5GfraJht1/GUTbTHCGBbyWtQ6ZJ7+Bc+/Q01/u91OYh6n5ZjTM8jRV6dKn0hmk4RhdGbxhmIiOIe27S2HcE6dQtCeuXuj2x0eR3myTDSBG90qxT4H8MTpM2OQHrl8m5WL9MzmUYZ7+fSOnMKMTf758iPnGG+KTNwDFhPhCNy56ThMnHdDsqjytvVUy3EvVLVUeQ+MWfyg7NBd6PpLWLwC4p7rERFd4wjVEq3rd18DATMe6xEVg9KVu/jA1/ZROmfuHv/rboI9Fzo6UiTQL9ELB+6YfWYGHpAPz76O5oTsQozZMmPvMx3yEplpEwgjSPk2My6pezIzcEG9MDmE2yVXSQjklBDojY7aPb8L4PivhF09pFgArm+BEUmamcS0RV/NsYQfEbn4T1S+Mf8awKSP3C9BcaWXdFv4vujDQJ9EPA+qUfWrMPy0ySc6MvRU+ZJho2ZihGlqbrGJsmilIuFfVLKZEZyWgIFN71aFLrLZWvJtga0XXRtdHtEUOTNFzXjI6IDoy09hBYNkVdJxr2/F0W1z4r+n3EkLzWPALWL817poOWiPUMzEr4ZPSCaKWI3xNNAv0SsH7pl9jswn85tz2z61baiRidHBjO0WsiRoVZu35PNA5jLT3tig+PI3HTnD2BKjpI96U474j4Z7VuhFM0J7opuijCcdLaRWCvFJfK7dIhF5vpe1dEvx1yOkY/PgLWL+NjX9WUt0/G+B9zanRxRGfc/ZEmgX4JWL/0S2x24beb5LbCMSouMcr0nWiFaFzOEXnZNVowcuYTNGpkVXSQCnxzc4A0CVDBHBUxVD5MI/53DjMB464MAeuXyjyKsWdkl+TgzIjGLZ1wD0THRZoEZkvA+mW25Hq77/AEe3dEGxbHiBkfrDNiFkjhKPHJ9+WicTpI1C8njTkPSV7rl4DrLPolZvhxEGD6y7Cn11Eu/h62mfjkuyYBCTSfAA0Y1jcuHp0QvSXSJCCB6hL4YLJ2SUf2+N/9veiCiKl1TLebF9HRcXU0TqN+GUX7ZZxlbGTaOkiNfKyNKtSGKc1a0VkjKNWrkgYbhLxsBGmZhAQkMH4CSycLvJCcBgxb/O8YvSTSJCCBahJgTc+mEUswCpuTgzdHz4jeFT072mNC+RibsaveRpEO0tgewewTrvIUu9mXyjubRIDel6si1gYM245NAutEVmbDJm38EqgGgZ2TjQcj1gfsM5GlQyY+/ZCABKpFYL1k59SIaXPFpgzksJhWR6f/v0WsI6yC4aQx/e+8KmTGPPRHgF8mTQJVJjDK4ek/BcQXozuqDMS8SUACpRGgfmF9AOsPPx4xYm3HYSBoEqgggfcmT0+eyBdOUeEYFVktnCZGbapg1C+/jJj2p9WMgA5SzR5YC7O7Vco8qhGdLyUt3pXAEL4mAQk0n0DRAfPCFBUniam89za/2JZQArUjwHswGUEqDGeocIg4VxyzlvCcaDVOjtmK+mXM2TD52RDQQZoNNe8ZFQGcI7boZIepURgLOnlfgr09o6BtGhIYL4GnJvmnRXTA7BzNiw6MNAlIoFoEFkt2eP0GGzbRbqUz48aInScLxyiH80eU6OBkZGmyrcAJM4gt0cfNOHRrR6Pq4O0jawbthYAOUi+UDDMuAvS+sCvN9SPKwGFJ50MjSstkJCCB8RLYNckznZbdsHaM7o+ujTQJSKBaBDZJdlaOeLcR7dY7ox9HvOS5c5odnRxs902YMjd2YjTqiojtwk+OFo1mshckwN3RpTMF9Ho1CfBLpEmgqgQcnq7qkzFfEqg/gaJ+YdoODZ6fRjSwNAlIoFoELkt2GC3i7/OhiNGjt0WsF+wcQTo63/8r2jG6KiqM0eJvRUdG2xQn+/j8YMKuPhF+y3y+tod7qV9+ETHapdWQgA5SDR9aS7LM7+YW0a9GWN79ktYzR5ieSUlAAuMjsFOS5v1HLOhm3RG7Y2kSkED1CDBixPbdJ0WsFb4lWjAqDCeJMG+IcJxOjzrtR/nyt9Ge0XHRUlE/1jlKxX3d3yeL69k5Ocr2y2R58JwEBiJAT4RbMA6EcCg30/tCpbfsUGJ/YqRL5tQvo4OfeKmWZ+Ym1/vWMufNyrT1SzWf5/rJFvXLWtHvoosiFndrvRGwfumN07BDtaV++feAZOocKkaS+Pst9EiOPxNNZexQW4Tlkyl7/dgaCXxNxL1nRItF09mGuUhY6hmtfwKVqF/czrT/B+cdoyGAg3RaNKott6lA/3MizXxoEpBAgwlQv1wf0cB8OKJHmoaXJgEJVI8Ao0JzJrJVOCc4IMVIDtPYOqfUTQT988chOXpTRLiro4ujfuzaBF4z4sXSrCuayahfyM/vZwro9eoScIpddZ9N23NGBTPK4ek3J723R8wv1iQggWYToH5hqs3e0c3R9yJNAhKoJgE6MnCIUKcV5+bl5LcnLuyeTxyif4zY0Q57R/Ty6K0R/+MZiZqN9eIcEe+o2y+zKYv3zEDAEaQZAHl5LAQWSaqbRu8dYep7Ja11Irb51iQggeYSoGNwh4hGEwu2V41G2RmT5DQJSKAPApcl7BoRf7s4RcXIUfHJJitfiT4fsVED55l2t0R0YMQ9R0SjMuoV6hetxgQcQarxw2tw1p+XsvG7OSpnhfVHT4muiuip0iQggeYSYCOWZSIaXa+O+NvvtWc4QTUJSGBEBHZNOldGO3akVzhFfOL4FPbaHLAxAo4R7Qe2BN8hGrXx/sblou6NIkadD9MbkIAO0oAAvX0oBBiePj66fyixPzHSDXLqydEPn3jJMxKQQMMIUL/8LmIh9TXRF6KHIk0CEqgOAdqnP47WihghKhyjTqcop+c7SZzjHUX/M/H9wXwyje6waNRG/XJBdMOoEza9cgk4xa5cnsZWDgF6jb5VTlQ9xfIvCcVueb7QrSdcBpJArQkU6wNodF0XfabWpTHzEmgmAdYPMUWucIyKEaPiO6Vm62+0YMQa4mujzaK9IzZiOCoatRX1y6jTNb2SCTiCVDJQoxuYwFKJYf1olGsCSOub0cmRJgEJNJcAja5tI0aod46Wjvw/GAiaBCpGgFEgptcVxihR4STNy/Ep0bERnZurRd+J1oqYOvuJaBzO0ZykyyYQo2y/JDltGAT8xzAMqsY5CIEX5uYHoosGiaSPe5+esGz/uUIf9xhUAhKoJwGcI9YmnBexDmluxJoFTQISqB6BJ02RJf5u3zyhYtvvxfP9jVOEH9XpHZMQ+ThzVAmazvAI6CANj60xz47ALrntFxHzh0dh2ycRGkijcshGUSbTkIAEJidA/XJ2xGYsh0asP9IkIIFqEvhRssX/Z8QIEiNH2KoR/7OfHHWuSbo138dp1C9sznDnODNh2uUQ0EEqh6OxlEdg60Q1yuHpLZLeXRFv6tYkIIFmE6ABQ/2ySbRHNKqNYJKUJgEJ9EGA6bCnRldEtFV5yet9EZ2ncybE1LqfRbdHbOjwtWicVtQv48yDaZdEQAepJJBGUwqBdRPLqNcfXZI0qYQ7e6FKKYyRSEAClSLAdJ3NIxwk6hkaV06tDQRNAhUjwFoj/k5/EG0Q4RD9dcQrOfjEcJRYb/TKiG21943WiBghviV6VzRKY9MX3t84yg7eUZavdWkVv2itK7gFriQBel/uiOgxGoUtm0R2jq4ZRWKmIQEJjJXAjkmdRtX5Edt8PxSdFmkSkEC1CKye7Gw3RZaKjRpwgj7UFea/8p1d7Gjbfi46LqITdBS2WxIhb+eOIjHTGD4BHaThMzaF3gngIB3Ve/CBQ96VGGgo2eMzMEojkEDlCVC/nBIxTefCiL9/HCZNAhKoDoGlkpVdo0eizjYqszxwQBDXDom6X/C8Ys4V9xCekaVRGfXLCZHTdkdFfMjpOMVuyICNvi8C2yT0KJ0V1iBsFF3cVy4NLAEJ1JEADRjql7Wi30e8N0WTgASqQ4BNFxjx+XpUODrk7owIhwdjLRKbIHyML112UL7PmzjHPaMcIS7ql4nk/ag7AR2kuj/B5uSfYfGVIyq1URkVLE7ZuqNK0HQkIIGxEFg+qW4YHR8dHO0b0aDRJCCB6hDYPVnhb7UYKSo++dudM3GedisbOEw2UsOapS9Et0ZM1+c9Z6MwHDvWSo2yg3cU5Wp1GjpIrX78lSo8jZVLo6tGlCvmOFPhnhOdNKI0TUYCEhgPAabs/DG6MuLv/uroZ5EmAQlUhwAOEX+fWDFixDHT7mgfMLWOEaKvRJPZ83LynRGbr+Bs0Qn6/9k7D3A7qrJt833HhN57Dwmh9w7pIRRBBFQQKQIigl1sIFhABAvqr6CCBcQPEOwU6YE0Qu8dQoAQeu89+D93mCXDzj7n7DYza/Y873U9mbJn1nrnnux11rvazsN2UCYEbAzdtXUJgXQXZpc8kh+jpAQIkPJsfdlF+Q2QLi0pL7ttAibQOAHKlzA/gEUapkgM1bGZgAnEQ4Agg+8lQRLBEkESxy9Jw6RREkt6XyHVM0ahEEBRt+XvOw2heRjly0WS5zTmQTunPNyDlBNoZ9MnAQrCzaU8AyQmcz4l/VqymYAJdDeBMXo8yhcqMqtIzEGymYAJxEWA7+jDEj1FBEYcnykRGLGoytlSb8GRPprdK8zwOu4ljZ9JedhWyiTP+ksez1T5PBwgVf6/QBQAhssLxvDmOf+I1qVHpNclmwmYQPcSGKJHIyiiAvOi9HIibWwmYAIREThevqwo0RPzdWkbaR8pDF3bV/uPSSystKlUawRRzAUaJw2WLpWytlWVweqSA6SsSeec/gdyzs/ZmUA9ArTq8uNutPzkZRS+NhMwge4nQPnyqHSPtJM0SWI+g80ETCAeArvKFQKg/5HmkX4qDZL+IfEDsQRFJ0s90lISCzIMlWqNYXoTak9meEz5wrC/ezPMw0kXQMABUgHQneUcBChg3PoyBxafMAET6AABypfxEhWvH0j8QOwvpf9INhMwgTgI7J9yg+8q9jnpi9IsiUYOgiOM0U/80HsMRvlyfgyO2IfOEvAQu87ydGrNE2Co28ZSngESK+IwlvkQyWYCJtC9BKhojZYoX1aSOKYnycGRINhMICICBEFp47tKI37YLqv9MAyfOUbfk2Iwzz+K4S1k4IN7kDKA6iSbIsAY47klltvOyxZURizS4PlHeRF3PiZQDIH1lC3DcS6XPio9I50j2UzABOIi8Hu5s3PiUmjACFsa8+k9Okhi/wXpQanWFtGJ1yR6ifOwDZTJ8tLUPDJzHvkScA9Svryd25wE6J6eKDF5Oi/7oTJaQLo/rwydjwmYQCEExilXVqx7WKKnelHpXMlmAiYQF4Et5Q69RVjY0vN7gXS7dKB0m3SL9KBUayzwwCINz0sh0Kq9ptPH1F8oX1yX6DTZCNJzD1IEL6HiLlDA/DVnBgRHb0p5DuvL+RGdnQmYgAhQvoTv+X3af0Tiu28zAROIiwC9QvQYERyFnqOztH+GlO4RGqXjT0l8n1nIgR6j1SXmKmEs8PBr6RwOMrZ0+ZJxVk4+bwLuQcqbuPNLEyBQWUcKFZj0Z1ntM7RuPmmKxFKiNhMwge4kQAPgcInyZWlpc4keJJsJmEA8BAbKFYbXfUV6KXFrlrYESZy/WeJvNjZYulTaWzpCIkDCuD4Y9+Xxt51Abgspz/pLeEZvcyDgACkHyM6iVwI76BMKMgrAvOxZZTRNujCvDJ2PCZhAIQSovMwvTZI2lFaRXJkRBJsJRETgIPmyj7S8NLd0jHSLRP0UDZV+JbHU9wYSxnmuHcmB7D7paIn6BMP1PyNlbcOUAQ0uV2adkdMvhoADpGK4O9d3CdA9fbGU7j7Pms0IZbCcdE/WGTl9EzCBQglQvtwo0SjyljRdYi6DzQRMIB4CK8gVemMwtgyRe1DiO4tRT91LoqHjCokhda9LfJ4env9dHdMgQm/xUxIBVSP2bV1E2UBazfQwU75cL+X5+43KzpYXAc9Byou086lHgAKGiZV52ibKbCUpdNnnmbfzMgETyI8A5ctlSXa7J9u78sveOZmACTRA4BRdQy8S9VEaS0+W6AUiwNlGImhiGB69RwyfY8v3maDm71LaWKGWoGWQRBqjpZuk3mx7ffA9ibwJ1Ah2wlwm7fZp6fKlzwv9YTkJuAepnO+tG7xeUg8xRAoVmLyeiWE3rHTDr3LbTMAEupMADSCbS6F8uVP77jXuznftpyo3Ab6XgyWCoVUkGjEekbaV+DvNoipohvS09ID0Y6k2ONKp2XOTlmFHRm/SV2fv9f7PivqIYXnYAIn8GzECNhpbQ/nSyD2+pmQEHCCV7IV1kbs76VlekPJu0T1KedIVbzMBE+heAiOTR5uqLS3Ro6SZyTlvTMAE4iHA9/Mw6XPSejVuETT9RvqtxHf4P9Ji0h+lq6V9pLQ9o4NQr52lfYba9WX/0ofPSlxLoHS81IiN1UUESdc0crGvKScBD7Er53vrBq/pnj5feifHh1laef1IulK6Ksd8nZUJmEC+BMYpO4KjV6UFJCZ0M3zHZgImEBeBE+UOP+JMDw4Np6tKNGZ8Q6Ix80np4xI9SNj/kzjmO72pxIIOt0rYmdIYifSuk46R6tn/6OSh0o7S7yXqA3dJD0mNGPWXKdKLjVzsa8pJIETa5fTeXpeZwJZyPu/uaZYQfUQKhWmZ+dl3EzCB3glQgQnly6e13yNRAbKZgAnERWBzuUOwQ32UIOl3Eo2nDKOjcWOQdLK0iIStI3E9Rq/ParP33v2HnqADJK7dRqJHqZ7tq5Pfl4ZL35JWlBoNjnTp+35fjWNbFxJwgNSFL7UEj7S2fFxFotUmT6M1mcLz7DwzdV4mYAK5ElhMuTFUJwRIH9L+GtJtks0ETCAuApfLHYbOIXp2tpN2kIJRTyUoYu7wnySG3DHyhHlJT0vjpWaNOgj5YeTJcaO2gC5Mly+N3ufrSkbAAVLJXliXuEvr7n2SW3S75IW28Rijde9p0t+kxaUDJf5g2UygVQKUL69I10urS4OlhyXmGtiqRWC0HtflS7zvnOF0+yXu9Vbuh8CJy/aW7pA2kz4pEdg8LzVrf9EN5Mdy4Ww5btRY+Y4lxm9s9AZfV04CDpDK+d7K7jUVmNC6W/Znsf+tE+CP3d8l/tiwItAHJIY7nCDZTKBVApQvE6W3pTMlAm+2tmoRcPkS//veSi7SG5QOjtL7fIaFc2wZRneDRFDTSnCk22Y3nhBcfV5aR2LBh0aN8mW85DmNjRLzdaUlwJyUm0rrfTkdZ9LlbgW4vrvyvFhiuE2320w9IBWEmO1uOfcxaQnpgcRRfqiP72S3NN64fElebI6bacrry9IQie8BvUcDJFvnCLh86RzLdlIqc/myih58fYlAg0CInqKg2mPOc46AiDnEB0lF2b3K+CtFZV6RfKMoX7qlElKR/zNd8Zhb6CmWlK4q4Gl2Vp506b9WQN7Ock4Cy+rUhJrTrApET9JSNed9aAKNEGCyNd9xeqh3kRhW9w2JXkpbtQi4fInzfVPvPF+6X7pG+mayH4IjtsHS5+gRnk9aV/qNtKmUt1F3GSp5BEze5AvIr5EAiS5NIn3+U6RVgLvOsgsIbK1nuFmiVTdve1oZTpVm5J2x86tLgDkiX5cGJJ/2aPs5iSEUjyfnvDGBZgiM08X0UN8hUZHi79d5kq16BFy+xPnOh8ut7RLX+C2ho6TBEt9V7CUpzE/mb8EB0iiJgCr8rSBY4p68bUdlyO83Ur7YupwALbV92Z768MfSCnUuCv+Z63zkUybQKwECpCJaX2h5mlfyXIReX03uH3xROV4qHSjxfmZKC0l7SDYTaIUAAdL45Maltb1Nejk59qZaBFy+xPm++T6mG+cp89P2lA7Wk5gbREPqM9JYaagUepdIg+HyeRv1lwslhvvZupxAfwHS4Xr+w6R/SowTtZlAOwR6dDPd4se1k0iL9zK3hUB/c4kCzlY8gTvlwurSTtIq0hMSf/T4o2gzgVYIjNZN35EOkjaU/F0XhIqay5c4X/wicov5p8wFrtfQfpLO03N0ixSMAIlhsnNLfHau9LyUtw1ThsfmnanzK4ZAfwESLe5XSq8V455z7TICY/Q880vXFPBcjyjP3aRXCsjbWfZOgPfBCkIMh8Eoc2gpnMaBzQSaILC2rl1OmiDRAn2f9EvJVl0CLl/ievcry52LJBpL6YUhQArS7uwg6ER2aoxRJ9+SCJLofSIN7gs9StrN3NZUDqtIUzPPyRlEQSDdzVnPoe/pJH9giN6XqZEObSbQFAG6pylcnm3qrs5d7OCocyw7kRJDeB+SGFt+b410aDOBpghQvkyXHpBonZ4oMd/RVk0CLl/ie+8fk0vUOxFBEr1BIdB5W/u/k+r9nZ6g8x+UfiXRO3yo9Kb0d6m/hn5d0hGjfKFsuasjqTmR0hPYQ0/wuvSfOir9wyUPQM+Cl/nO521eq2yOzCerOXIZoDMsKVoVm6kH3Tvyh71d/u0l0WsU/miGbeSuN+yey5eGUbV94TlK4bcSFS96JBmuacuGgMuXbLg2m2qZypcv6OEIiOg5QgRE9AhRv+T8dRJ/p/szvuMER9z3hrSP1Gnj71Ct/Usnfl970seZEIiifKn3nyD9tIy1PFJaTlq0Rjq0mUDDBKgEE6Bc1vAdnb3wGCVHb+iWnU3WqbVBgP8TYQhv+KMZtm0k61srSICgaKRE+TJYelQiALdVl4DLl7je/ZflDnVOeowo589PttrMDpAIej4vLciJPoxh+qSBESSxwE+nbFclxNwmVtI7sCbRrXRcVP2lxhUfxkDgQTnB0LputjK1wJT5Pewi5ykAO1mYNcNjvC6eLlG4VsGiaIHpBzQ9XEy2HSt16xBely/9/Cfo0MebKx0qXUtKwySW9l5ZsmVDwOVLNlybTbVM5cureji+owQ1bNeVzpZmSQyrY7QSukHqy9bRh09LpHOLtIDUCSPoekEiXUTv1kIStqnEuRU5sGVOIIrypb+xmz8Vhp9J35celugSDUbXps0EGiWwtS6k9YVCsgj7gTIlOKIgtsVBgPJkW2mnOu6EFsI6H/mUCcxBgPKFytJT0m4Sq10tKNmqS8DlSzzvnt68eaRQrrMluKPhlACHHptgG2lncemZcKJmS8/w8hIjm2ZIBFudMHq3BqYS6tF+qCNTvtwmzUx97t0uJ8B/iL5sD334Celu6WUpRPhsbSbQDAEKGAKkIozC+aNSuhAuwg/n+X4Cx+rwSIk/dIvWSIc2E2iYwDhdGcoXAqPrJA+xaxhfV17o8iWe1/qaXPmLRNCKJkmrSUtK1C1Z+IARJugBqb+FnGig57pOBUdKanZP1leTLb1FR0vBjyLrL3LDVgSBEB33ljcB0oDePvR5E2iQAJVfVpUKFZgGb+vYZUsrpUHSttJkyRYHARpoTpUej8Mde1FSArRMM7fwuMT/tbWlUcRWbQIuX+J6/3vKnSHSJtJI6SqJxvZdpR2lMEeJkUsEKEXYicr0TIm68dOJAz3abi79Mjn2puIE6P7sT92CqExjeMvKfG85Tu9NfwF5ls+3rBLvr8c0y/zzTnumMoR7zPYFOXeGtLo0v8SwqCDtdoW5fMn+NdJ7xHwBhupQmaEVmAYZW3YEXL5kx7aZlMtUvvCdJPBJa5aO6QUiUCKAitHGyCl8XCxG57rUpyjKl3oVRv648J+hP3Xpe/FjZUBga6V5oUTXehH2GWV6mkRF3BYPAXqoPYQ3nvdRVk8oX66WGKqzocQcpE9LtmoTcPkS1/unRyb0DIVtaIinYew3cbn7X29C+RKG2/33A+90N4F6Lfp/1COf392P7afLmcBWyu/nOeeZzu5eHTwu9TbpM32t9/MjQAVmQH7ZOacuJUAF5oLk2T6kLQ0x/huWAKnwxuVLXC+fRncCIixs3z169196k2I0ypfxMTpmn7IlUC9Aek5ZIpsJdILAUCXCZMyi5h/xDBMTsW8rnkD448jwEJsJtENgYd28kfS1JJGVk+2UZOtN9Qi4fInnnS8iV06SmHf0fxINlUtJvKPwngicXpOOl/jsSSkWYy4j5cu3YnHIfuRHoN4Qu/xyd05VIMD8ALrW76vCw/oZ+yXgIbz9IvIFTRAYo2vfkK5J7qGydYtU1HDexA1vCiLg8qUg8L1ke6TOs5T3EOk70lHSBOlViWF2fF9pkH9T+q70gHSwxHf4emkLqUij/kIgd22RTjjvYgjU60EqxhPn2q0E6J4+r+CH21n50xJ0VsF+OPu55vqjIHj4k/8ndIoA5cskiQrWZhIr2BXZW63sbQUScPlSIPw6WQ/WuTCMmiF0P5P4sXiCIwKPHmlRiQYNGuwHSr9K9rWZ6xxpaXYKMsqXiRIBna1iBBwgVeyFF/C4WyrPbxaQbzrL/XRAwesAKU2lmH1aC5HNBDpBgBbePyQJfU/bQdIdybE31SPg8iWu3SBIEgAAQABJREFUd36C3NleIiDib3Da6D3iPIFT2giagi2hHe6jAaQII0A6vYiMnWfxBDzErvh30M0eMHZ3OenKgh/yS8r/CwX74OxNwAQ6S2BZJbeGFHqMFtf+49JfJJsJmEDxBC6VCxtLIQii1whjSzBL8DFKYp7SQ9K9EoETRvB0s1RUcMT8qbWkUL5o11YlAu5BqtLbzv9ZaX25U3og/6zfl+PM9x35wARMoBsI0HvE0ru3ShtKDIO5SgqVMe3aTMAECiZAMFTbe4RLDHvfjx3Z1dKXJb7HfIdpvCdQ2l8qyj6ojFk8giDNVkECDpAq+NJzfGQCJLe+5AjcWZlAhQiE8oWKFMt7Mxzn3xV6fj+qCZSBAMERvUFY6EHi+PXZZ97/zz06/IbEvCN6lR6WijLKl0skL/hS1BsoOF8PsSv4BXRx9vzf2lyKIUDiB2L5ITqbCZhA9xAYo0cJ5QvDeelBoiXaZgImEA+BwxJX0sERpxaS9k0+Y0OD/TXScdKh0telIm2YMg/lS5F+OO+CCDhAKgh8BbIdrmdkDC/d5UXaasr8J9KRRTrhvE3ABDpKgO/1ShIVGIKjzaQFpVckmwmYQDwE+F7WGsES9c+xqQ9YgXIdicZMgqX9paJssDJOz28syg/nWyABB0gFwu/yrOme5rcDniz4OVlCdAXpgoL9cPYmYAKdI0D5MlO6T2IOEo0gO0s2EzCBuAgwkqS294iFFxgayxC2YDO0Qy8w59+SilyNkvLlGYkhf7aKEiBKt5lAFgQoYGLonh4lPx6TXsjiIZ2mCZhAIQQoX1ghC2OOwxSJYMlmAiYQD4EeucJiDMEIlD4mETRdKZ0tBXteOyyMcIT0tMQwu6KM8oVG1TB3qig/nK8JFErgEeV+U6EedF/mVFhekyhkijYKZJYDrprN1APvXbWHjvB5Xb50/qXwnaYCtWeS9LHanisxRMeWDwGXL/lw7i+X2MsXlvjmu0mvEMHG8RJD6BaQRkvhb/M+2mdFykel7aSijf/f6flRRftTtfyjKF/cg1S1/3b5PO84ZcOvZzPErmj7qhzAlx8V7YjzNwET6AiBjZQKv3k0IUmNVui3pXuTY29MwASKJ/A7uXCgFHphWHRhPol5gjRyYHxvd5VOkUJ99M/a5/tdlK2njFeQrijKAecbB4HwHzIOb+xFtxDYWg8ySXopggf6sHyg695mAibQHQQoX5ifwNDZQdI50gzpu5LNBEygeALLyAWCIywEQx/V/hapYz6jDvrFZMsxRhDF/Hh6nYowyhcaW6YXkbnzjIeAF2mI5110kycUMOMjeCBagl6U7ovAF7tgAibQGQKUL2F+I5O5H5du7EzSTsUETKADBF5XGvQOBaMXiUaNECyF81zD3+dfJicIig6XigqOcCNdvnBsM4HKEnhET+45SJ17/SzpSaHHsrtFG4XxftIKRTtSQP4zlefeBeTrLN9PwOXL+3m0e8T8xpcleoZtxRFw+VIc+3TOMZcv+8tRVqV7Q/qHtLrEYkkESwRArBLH8NjFJGxlKcxJmn2igH+oM+AXvV224gi4fCmO/ftyjrmAeZ+jJTnYXX5SKFKRsRVHwAVMcezTObt8SdNof3+UkqABZuEkqSW03THZ9yY/Ai5f8mPdV06xly8D5PxfJBZtelh6UyJA4vibUmy2lRzCP4YI2oojEEX54jlIxf0H6Nacx+nBLpEoCIs2eo52kE6WZhXtjPM3ARNom8DWSuF6iZZo7FvSUOlBqcjfTVH2NhMwARFYUqL3iLm/BBsfkahr0jvEMUZPzaLSlRILMnxb+ptUtFG+MFyXYbu2ihNwgFTx/wAZPD4FzC8ySLeVJA/WTcxDosCjUmUzARMoNwHKl/GpR6Dhg8Ua7kyd864JmEAxBBg5wuq1BEPMcZ8p9UgYQREiSKLu+TWJa/j8z9Ik6UmpSKN8CfMbi/TDeUdAwIs0RPASusiFpfQsg6VYCpifypeTJAdHgmAzgZITWED+byqF8oWhdZ+RwrAY7dpMwAQKJEBv7iBpbonhdatIwQiOEEZQRJAUgif2qT8UafibLl+K9MV5R0DAAVIEL6GLXNhJz0K3+l2RPNOr8iPd2hyJW3bDBEygBQKjdQ89Rlcl9/LbZrRG/zA59sYETKBYAvcr+/QKdCEgSnsVzrHl+8v1NHoUPUR2jHyYRwrli3ZtVSbgAKnKb7/zz0739PlSGGfc+RyaS/H/dPnpzd3iq03ABCIlQPlyhcQSwtgj0mSJ4Tk2EzCB4gmExRjSdYAQEOEd5wmisLelw6XR0rZS+h4d5m6hfOGnQWwmMLuL0xhMoFMEGOpyVKcS60A69GRRYNtMwATKT4AKTAiGhmmfhWCuKf9j+QlMoGsIMOR1+eRpCHjo8WUkx4ISgdLd0trSStJL0rNSLEb5cm4sztiP4gm4B6n4d9AtHqyjB1lZujKSB1pdfmwmMbbZZgImUG4CS8p9ypgw/+g67V8u0UtsMwETiIPArnKjRyIYoodoorSBxIp1g6W1JAKnGVJMwRHzG9eXQvmiXVvVCThAqvr/gM49P60v90n3dC7JtlJ6VHfPlCa1lYpvNgETiIEA5QtDX1iREqP3iNUyH+bAZgImEAUB/t7y3WReEYHSYdIDEsvys43VtpVj9HZdH6uD9it/Am5dz595t+ZIBSam1hdanOnO9xCcbv0f5+eqEgHKlwkSlRibCZhAnASOk1sMqdtIorGUXqQyWKi/vFEGZ+1jPgTcg5QP5yrksqUeMqYA6W/y50sSw3JsJmAC5SYwVu6PL/cj2HsT6HoCNGD8TtpCOlq6SWIxFQKPUySG3sVoIUCK0Tf7VBAB9yAVBL7LsqUwXEKKZf7RQPnylkQL1s2SzQRMoLwEmLuA0g0wNH5sJ+0vFf3jknLBZgKVJ8Cc3xWkX0vLpGgsq30Co72l8yTmIBEwXZTsazPb+I6PkVjQ4QZpipSHUXdhznK6fMkjX+cROQEHSJG/oJK4R+sLgQgtRTEYq+Q8JYX5CjH4ZB9MwARaI0D58ph0d3I7P+hIYDSvREXLZgImUCyBbyh7fpeMHiS+n8EIhoIxL+loaTWJgOkMaT8JGy6x6Eqok3LtlyWCraxtB2XAHKnbss7I6ZeLwP+Wy117GykBKjAxtb6MlT+0Cv05Ul52ywRMoHEClC/p4XVn6phK1jMSFRubCZhAsQTo0aU+SXCUDorSXk3TAY2XXEMgRI9Sj4TtJ7FP4ITYP1DKw7ZWJhdLBGU2E/gvAQdI/0XhnRYJUNDRtZ6uwLSYVMduG62UFpYe71iKTsgETKAoAqOVcWiAofLEUsH8vlleFShlZTMBE+iDwL36jGHtGN9RjEApBDwcHyzRoEEv09vSjGRfm7kInjgXjLTyGgEyXHmF8iXk760JzI74jcEE2iEwWjfPJ13dTiIdvpeWZcY3u3W5w2CdnAnkTGA95be0xPAbbFuJ1mUaZO6UbCZgAsUT2FcuXCCle49CoIR3LNF/q8S8wUkSPTYfkoKxZP+J0oPS/RILPRwiZW2rK4PBkgOkrEmXMP0w3rOErtvlSAjQPX2F9Hwk/mwoP5aTwnyFSNyyGyZgAi0QoHyhdXpmcu+O2jLviPkONhMwgTgIPCw3dpGukjaXCI7SwdIPdPySxM9u8J0OxjxCepYY8fET6StSnoYvj0vT88zUeZWDgAOkcrynmL0cJ+f+HZGDu8uXIdLxEflkV0zABFojQAUm3brL3KNXpNtbS853mYAJZEjgWKV9bpJ+ugeJBo3FpCelU6QwuuMv2qdXGDtA4m/3mxzkZJQv9HzZTGAOAp6DNAcSn2iCAEPr1pfSFZgmbs/kUpYRPT8ynzJ5UCdqAl1OgAa8kRLD6bBNJX7XjBUq0/MVdGgzAROIgMAV8iEEP2l36E36mkQAdaUUgicaWOdOtIK2q0p52jBlFlP9Jc9nd179EHCA1A8gf9wnge30KQUfv1kQi+0pRxiCwyRumwmYQHkJMFRnAYk5C9ge0jvScRzYTMAEoiGwlDz5uMT8oYWkMLyOLd9Z6pqsXjePtJa0ooRNkfh7Ta/RExL352UbK6OlJYI6mwnMQeADc5zxCRNonADd07S+xBKMLC5faJFiMqjNBEyg3AQoX1jJikVXBkp7SVS4bpNsJmACcRBYXm4w5JURJXxPa43eIsR3FzHM7lEJ201i3hFzkH4lvS7lZZQvd0gP5ZWh8ykXAQdI5XpfsXlLAfOHiJxaVr7MkCZH5JNdMQETaI1AaIDhbvZnSlOlWBaEkSs2E6g8ARZnYLEFgiMCoLRxTHCEsX1WGiGFIbIvav/7UhGWLl+KyN95Rk7AAVLkLyhi95hwyRKZMY3fpRXro9LLks0ETKC8BKhwbSEdkzwCcwV6pJ8lx96YgAnEQYBhcemeI4bU8V3FQnBEoDRL+px0n1S04R/ly6+LdsT5x0uAcaE2E2iFAMvtEojENNxlJfmzaysP43tMwASiIjAy8eaKZEs5w1xHhufYTMAE4iFAw2QIhNgigiGCIkQARQPHYOmvUgw2XE4sKNEjbTOBugTcg1QXi082QIDu6YskCsJY7KtyhEL4OunuWJyyHyZgAk0ToHzhN1VeTe7kRyVnSEzotpmACcRBgIUXmBtIY+n8iUshSGKL0RDPdzkmo3y5VmJ+o80E6hJwgFQXi082QIAWoZ82cF2el/xQmW0mOTjKk7rzMoHOE6ACc3aSLCvZrSW59ygB4o0JREBgbvnwc+kzUo8UAiLtzu45Yp4RDagXcyIyo3y5LDKf7E5kBBwgRfZCSuLOavJzVSm2AoZlQs8rCUO7aQImUJ/Aojq9gfSF5GOG2z0iTU+OvTEBEyiWwCBlT6/QMjVuhLlG9CidKU2TmOfzaWlLib/PoeFDu4UYS41vLH2nkNydaWkIOEAqzauKylFaX2jNjWGyZVRg7IwJmEDbBChfGFrHUFlsTWkRiQqXzQRMoHgCNF6wUBNGUISFHqQ/a/8w6TFOyg6STpDoZdpXGidNlIoyyheG/V1TlAPOtxwE+E9iM4FmCVDAnN/sTTlcf5zy+G4O+TgLEzCB7AhQvkyUGKKDzZKobHn+ETRsJlA8AZbnDoFR2OLVO9KFUrrxnQUROKa++ZbE8PwijfJlsvRKkU447/gJOECK/x3F6CEFXGzD6+C0grQiOzYTMIHSEqACE8oXWqW3k6iQhQUbtGszARMokMB05U2AQSPG9cm+NrOHwZ6p7QzpCE7IaEwlcOLagdIkqUhLly9F+uG8IyfgACnyFxShexvJJ8Ydx7g85g/k12cjZGaXTMAEGiNAI8dQKQRI82mf1meWEraZgAkUT4Ahr3+SGGI3S7pLWlz6hLSahNGwcZTEXB8CJBo3OEeQ9BWpKGOo7jpSKF+K8sP5loCAA6QSvKTIXKT15Q7pwcj82kL+/FA6JDK/7I4JmEDjBMbp0qekEBB9WPsESB5eJwg2E4iAAAESPULY3NJHJBZeOF1KD7ejfnmt9DmJ3xzqkehBGithBE9XSFwzUsrDtlMmr0k35ZGZ8yg3gTIFSN8U6u3LjbsrvI+1e5oK1Z3SuV1B2Q+RNwGXL3kTr59fKF+oaIVW6FW1f079y33WBEpBoJvKlwki/pxEbxDfU4If6mYEQHxng7FPHZPv9EtSGGZ3sfax86QtJQKlf0sET1kbvoyXmAtlM4E+CdAyF5vtJodql47Ex49LDO9i+MU06SLJli8BCjt6an6Tb7YN5TZYV70g3dfQ1b6oqgRcvsT95sfKve8lLg7XdnFphvRYcs4bE4iZQBXKF4KjtaXzpU1TL4NgKW0ESPT88nd5Xon6A0HSbRLB0FIS5zCCrIUleo+zNAKkX2SZgdPuHgIxBkgfFN79JbpA079yvLyOGY/OH8zJkgMkQcjZRig/CrGrcs63keyO0kVLSn+R7m/kBl9TSQIuX+J97WvKteWkyxMXGV73qvTZ5NgbE4idQFXKF3pgaKgmQHpdYqgdAVEwgiWGsj0q8Rtm9DZR36SXiTlAb0onSwdIGCM/sg6OllUegyXPPxIEW3kJsMb+dCk9pO4sHR+UwSPx5SUYs/VP4Pu65Or+L8v9CgreOyQCZ9u7BGZqs7dh1CXg8qUulsJPflEeUO4HO1U7NIRR+bLFRcDlS+/vowrlyyQ9PoERgRLBzi0SvUOI4IjtLInPn5a4hoCJcztKweglHiulg6vwWae3BGP4kkdenfa9aulFUb78b6TUfyW/PiQdKzGci54jW/EEtpYLlxXvxhweUMjS+sRkT5sJ9EfA5Ut/hIr5PF2+MORmC+kliWE6NhMoC4FuL18IMLaSaLigcXKAtIZ0u4TRW8Q11C/5fDGJgInG6I2l86VgV2jncql2eF74vJNbyhcaXPLIq5N+O62CCMQaIIHjLin8gbxB+0M5aSuMAIUhhVuMAdIr8utxiYDaZgKNEHD50gil/K7hb9EoKZQvH9M+wdE1ks0Eykagm8sXAozJEr1DIdhgTtE6yXGPtgRECCNYov4wRLpHKspoSA3lS1E+ON8SEYg5QAIj3bKHSgdLs6TnJFsxBMYpWwq+GHtp9pJf9DLS6mwzgUYJuHxplFT2122iLJjfOCHJaqS2tD7/KTn2xgTKRqCby5dd9DJOl+jd5TkJhgiWqFOG3iMCKBou2SJ6mF6TijCCtxWlKUVk7jzLSYA/QGWwSXJysxYdXU/3UbnvzebXB/P09qHP/5fA1trjPbz83zPx7BwhVwZJM+JxyZ6UiEA75ctKes7N+3hWyhaGoNj6JkD5cpv0ZHLZmdreKmU9cTvJzhsTyIxAN5Yv3xGt/VLELtX+aImeJAIlhtnR+8sxq9X9j3SeVJRRvtyXqCgfnG/JCJQlQEpj/bgO+LKdlT7Zxz6rrOwlcU89m1cnka1vAhQwjTLvO6XOf7q6kmSYnc0E2iXQbPmymzI8tI9M6RVhJTZb3wQoX8LwFypV35cImGwm0E0EuqV8YUGVdJ1qXR2fJG0lMdpnqsRvl02Sgh2sncOlBaQ1pDslysZPSpyfIR0kPSh12tLlS6fTdnomEA2BY+XJjzroDRMHvYpd30Cp5FHobdb3ZYV9epVy/ldhuceZ8Uy5tXecrkXtlcuX/F/P3MqSilJY3WoP7U+TfiXZ4iTg8qW199IN5QuBDvWBMKyOLeLcZ6RgS2mH4Xf0KL0lsdIdc8mfkTj3hMS8IO7jmGsvlzptBHLkSWOWrRwEXL5E8p4cIPX/Imj1oodmQP+X5n7FKOV4tfTL3HOOO0MXMHG8H5cv/b+HsbqECtSCyaV3aAu3FZNjb+Ij4PIljneSd/mysh47BDQENSE4Su/vlELzEe3zfZ4orSn9XGLeEte/Lv1JSqf3gI47bSz2RX7Ldjphp5cZgSjKl1iH2DHkbXdpQ4n/1Ixn5Ytzr3SmxB9TW34EtlZWl0oxcqf3b6r0a8lmAo0QcPnSCKX8rmGO6DUSq9Z9TFpeelZ6WLKZQNkIdHP5wjwiFmIIRu9MMPYJmHaWwnyjf2ofBWNOIcFKMHqV1pPWlbj/J1KnjfrLzdJjnU7Y6XU3gfR/9FiedGU5co/0VWmgNE0iOGItfc7dIA2RbPkRoIC5LL/smsrpGF1N4coQHZsJ9EfA5Ut/hPL/PF2+0GtEYLSNlK5I5e+VczSB5gl0c/myuHDwtzZtfEfT31N6g/pa6fZ4fX6h9IJ0tvQbaXPpgxJpnyh12tLlS6fTdnomkCuBU5TbaX3keKo+O66Pz5v9KO8u6mb9K/r6ZeQABeBaRTvSS/7X6Tw9i8xjsL1HYKZ2PQfpPR5hz+VLIBHHdiG5wQiBkYk7DJWlAuXvcwIk0o3Ll/ovptvLl+l6bIKgEBi9o33E/KErpS9IW0lfkViIoWgbIAeYHkAAZisPgSjKl1h7kM7o4z0yxI4xpbZ8CDBx+lnprnyyazqXU3XHt6Q3mr7TN1SRwMp6aJcv8bz5MXKF7y7zCBliM590uuTvsyDYSkeg28uXk/RG+J4SIGHso9clAqNHpSnSsRLD59aWirRRynweieDNZgJNEYgxQKL1kArvcnWehFVRjpT66sKtc5tPtUFga917gRQKxDaS6vit9GoRwFE420ygEQIuXxqhlN81lC9UqGiB3kv6sOSeT0GwlZJAt5cvH9dbCUFRqBOwDfN7dks+Zx4WPUsfkoo0yheCI4b02UygKQIxBkgn6gluk2ZIzD+6SuI/+N3SzETf0daWD4HhyuayfLJqOheG5qC3mr7TN1SVgMuXuN48FZhQvkzQ/j+kA+Ny0d6YQMMEur18oVeotneXAOmwhBBD3sPfY4a33ZCcL2qTLl+K8sH5lpTAByL0m/GijGP9sTRUWkXqkR6VQuCkXVsOBJg0uaI0NYe8WsniXt1Ei7PNBBol4PKlUVLZX7eMsqAXOARIj2j/c9ln6xxMIDMC3V6+fE3kaJTcRFpemk86WQq/Q8giDNQrh0l/l8ZLRdn8ynhDCZ9tJmACLRDgjzJLRdvmJMBES4IQW/kI0Nu6d/nc7jqPXb70/kr30kfPSDGOZOjda38CAZcvcfw/KKp8uV6Pz7DYWRJBIYutxGa7yCGG3zMHyVYuAlGUL/7DVK7/NHl7u7UyDK27eeft/EzABLqbwDg93uUScxUwJnQXPWdhtiP+xwRMoFcCa+qT9aUBEnVIepFWkGIz6i8M2yVIsplA0wQcIDWNrDI3MBFzSynmAInhOQdV5o34QU2guwiM0eOky5fDdcxv3c3dXY/ppzGBriBAfZGhdHdKPRJzjxALNDwgpW0HHXxdGpI+mfO+G3hzBt5t2TlA6rY32rnn2UJJLS5N7VySHU/pS0qROUiMhbaZgAmUh8BQubqyFAIkGmSel5izUDsJXKdsJmACBRM4WfnvnPjA9xVhS0g/m7337j9f1OYc6WiJRR0a7V1i5bvvS/+UdpLaMXzid5hC+dJOWr63ogRiXKShoq8iusem9YW5WbQOxWoUwotJjMO2mYAJlIcA5cvD0rTEZVqcd5euSI69MQETiIfApnLlk1IIiug5wjhmqN1YDhLbQ1vqlojGDr7rf5L6sx/ogs9LAyUCsQ0kFuZqxbbXTS9Jt7Zys+8xAQi4B8n/D3ojQKEWe+vLN+Tjrr09gM+bgAlES4Dyhd6itLEgzDHpE943AROIggDzA8NcQRwiQJqV6G1tz5aC0chBYMQ1BEk3So0YQ/oZXkvQ9ZZEgNSqUb5cIuGjzQRaIuAAqSVsXX8TLUKbSTEHSMxXWE+6VrKZgAmUhwAVoNFSunw5UMdUihiSYzMBE4iDAHXE86U/Sun6It/hnuQc+9OlYN/VDr1Bf5UYAt9oL9AZupaAhkUV3pTS5YMOm7IRurqd+5vKzBd3JwGie5sJ1BIYrRMsjXlV7QcRHW8oX2ihuj0in+yKCZhA/wRoGWaOwOXJpQtpu5TEcsEESTYTMIE4CIyVG9smrhAIBUvvEzgdKi0q/UKi94gAqVn7tW6gF3ktiR4pfvuyFRuqm4ZIDpBaoed7/kvAAdJ/UXgnRYDu6anSC6lzMe3OJ2fWl66ULojJMftiAibQLwHKlzulUAHieBnpN5LNBEwgHgKLyJWeOu7QOInNkvh8FeloiesZ3dGqXaobUTtGefKENK2dRHyvCaS7TE3DBAIBCpiYW192l38UzHcFh701ARMoDYFx8jRdvnBMi/Q/S/MEdtQEqkHgyOQxQ0AUtnxf0WSJXl/qkgOlUVJvxvV5GPWXC/PIyHl0NwEHSN39flt5uvl10wZSugLTSjpZ3jNciTMchy55mwmYQHkIDJCrfH/T5cvSOr5DekCymYAJxENgdbkSgqF0gMOCDaxw+xmJxkrmDbFYw9+kYJtoZ7REr9JEiXlFF0vUMbK02vIly7ycdhcTcIDUxS+3xUfbVvdR4F3f4v1Z30ZlajvpZWlm1pk5fRMwgY4SYKUqfu9kUpLq/tqOlahchdbp5CNvTMAECiQwQnnX1hFDkMT2YGm6xHzgo6XdpF9I2A8lFlAaL10jbSExpYMeps9KWRm+MFx3SlYZON3qEPAcpOq860aflO7pyyRahGK0b8qphaVHY3TOPpmACfRJgPKFxpfnk6sIkKhs/So59sYETCAOAt/rxw16fbF7pGNn7733z9e0y/e6R1pNovco2AJhJ4Mt5QtD72dkkLaTrBiB2taBij2+H7cOgRAg1fkoilMM/6Pw+0wU3tgJEzCBZgikyxdWvaKRjhZmWpptJmAC8RB4Vq4wmgSjdzeI4XWHSfQeYTtJHDMcD2OUB9/r9PVP84Hscemk2XvZ/JMuX7LJwalWhoADpMq86oYelKV3KeToQYrR+P/KhFBaoBliZzMBEygPAeYebCaF8mVN7dOa/EfJZgImEBcBRmuwZDeBTjB6hRDziu6UrpNYXOV70s3SIGmwhIVrWQ13kMTy26tKBElZWI8S3UoK5UsWeTjNChHwELsKvewGHnUHXfOSdHsD1xZxCYUy3ecejlMEfedpAu0RGKXbaX2+UhoonS3NLVHm2EzABOIiQA9Sb8PhCJ4ISPg+03BJXZJh+WOlMyR6l1aUuIYeIxo275OyNIKjBaUrsszEaVeHgAOk6rzrRp6U7umLpFmNXFzANcOV5xBppEQBbDMBEygPAcoXKi+vSYtJfIepVF0g2UzABOIi8KLceVRaVqI3KPQk8Z0lKCL44TxBEsYKlYzuoNdpI2lXid6iS6Q8jPKF/J/OIzPn0f0E+E9uM4FAgADksnAQ4XaqfPqz9KcIfbNLJmACfRMYp49D+cLfnr9K9FrbTMAE4iRQ2xvDYgtrSM9Ib0sER5MlRnZ8XbpVwugV/j+pv+CIRvplpE4YAVIoXzqRntMwgcoTeEQEbqo8hXfnHtFCNCRiFifLN3q4GGpn65vATH28d9+X+NMcCLh8eRfyEtpQmdosYX6LtrROO0BKgJRs4/IljheWZfmypR6R7yz1giCON5QWklic4XCJ4XP0KhEw0XPUqHEtgRZpXy4NkFq1eXQjPtAIYys/gSjKF6J3mwlAYGuJ7vDpHERqL8ovCsHnI/XPbpmACdQnQPlCq/IN0h7SYOll6WLJZgImEB8BAqFaY0jdVIlhsTtLfIepRyKGzo6VbpQasR/oIn6yAxsm7SKlf2iW843aGF3YI13d6A2+zgT6I/C//V3gzytDgApMzHMBKIDXlhaszBvxg5pA9xCgfJkgzZKoCNHQsWdyrI3NBEwgMgIXyR96h0LvUXCPhVX4DvM3mb/H9CrRe8T5KVKjxlwl0sYIvBi+16pRvpA3AZvNBDpCwAFSRzB2RSK04MQ8fpcC+BDpS11B2w9hAtUiQAUmlC8PaJ/GGAImmwmYQJwE7pdbR0hPSAQzwQiIQmDDOXqMfittJ/GbZo3aYbrwIYn0/imdJ7Vq6fKl1TR8nwmYQA2BLMfw1mQV7eHG8owCb6VoPZxrru/INypWu0bsY0yuzZQznoNU/Btx+TLXXCvrNVC+rJW8jkW0deNcAqOkG5cvcby4LMuX1fSI9Pjy3SWIYYj7qxLBzJ0S51+QNpDasQHt3Kx7GaZHA+oWbabj2+MhEEX54j9S8fyHKNITWl/ukGjNidF65NR+0qJSrD7KNZsJmEAdAuN0jvmNVKqWls6QjpVsJmAC8RJYX64x9A1jy0II80lHSUMlhsnyO0nLSe0Yw/jasW11Mz1czG+0mUDHCDhA6hjKUidEgBSGv8T4IARIMyW68V0IxviG7JMJ9E6A8mV88jGVLFp8r0qOvTEBE4iTAD07IUDCQ3ppsJ0l9vkuYx97d1PYv6H+0m6gVdgDOOM4CThAivO95OkVwQdd0zEHSHvLP7r66eWymYAJlIvAWLkbypfdtc+wHE+mLtc7tLfVIbCEHpW/tfT0MowOYxsaNZhzxAINGIESx8GW187AcJDTNgRIOWXnbKpCwAFSVd507885XB+xEs3U3i8p/JMvygPGQ4dKVuEO2QETMIGGCKyrqxhWd3ly9SbaMlQ2HCenvTEBE4iEwI/lxxqJL+kepJnJufO1vVIiOHpcOkeit2mi9LDEog6bSnnYMspkVcl1gzxoVywPB0gVe+F1HpfWl2ulZ+p8FsOpD8mJwdJz0iMxOGQfTMAEGiZA+TJNekjaXtpGojU6tExr12YCJhAJAeqEn5DSgVFw7ehkhyF2W0r0Iq0oXS/tI3EOo8H1/6SfSKtLWdoHlfizkkeXZEm5omnzZbBVmwAVmPERI6D3iJaqwyL20a6ZgAnUJ0D5Elp3qVixGtZZ9S/1WRMwgYIJzK/855FCgERDBt9ZeoymSxirUIbP2S4unSTRi4Rxbqj0ZYnG18WkrIzy5WLJDS5ZEa5wug6QKvzy9egUhCzxHSowMdL4vpw6RLogRufskwmYQK8EevTJSInyZV5pW2mGdIJkMwETiI/AS3LpTxJBUQg6CHioJzA0FvublB5xQj2S3iSuCwEV3/2BEqvcrS9lZSOUcMz1l6ye2+nmQMABUg6QI86C1hf+D9DKE6NRqfq2xLwFmwmYQLkIbCZ3GW4zUaIV+QFpimQzAROIl8D+cu3WxD2CHkRjKgswYK9I60kPcSBjhEfa/q2DN6Q3pZelW6QsbC0lupLkMiULuk7TP9ZX8f8D4/T8kyQKvBhtcTnFBO97YnTOPpmACfRJgAaYm6WnJb7L06UjJZsJmEDcBAg8CIyC0bN0VzjQ9klpsLSKtL30gkSvE0PtPi4dKv1SopGEOUJZGOXL/dK9WSTuNE2AblFbdQlQwPw54scfJt9YmOGxiH20ayZgAvUJUL6E+Y1jtU8LNHMTrpNsJmACcRLge3ultKMUgiR6glkxjr/HwWZp58FENIDQy/SqhBEcZW346eF1WVOucPoOkKr78ploubYUcwHzF/lHC7R7kATBZgIlIsDw2C2lHyU+L6wtlSsHRwkQb0wgQgJ/kE/7Sgy9rzWGyaYDpPTn9B6F4Ch9Pqt9Arfh0uezysDpmoADpOr+H6Bb/DWJACRW+6EcY5zxR6Xacc6x+my/TMAE5pprhCBQyboigcFEbX+HExjemECEBKgP7if11PjGwgsMw49pKNum8odeqymSzQQyIVCvlSCTjJxodATonr5Ueis6z95ziAKbSZ60TtlMwATKQ4Dy5SqJihXD6vgu99b6rI9sJmACBROgAYPvKEPnCIpQsMO1w8ILsRjlCwtJPBqLQ/aj+wg4QOq+d9roE1HAxDy8jsmfuyYP4wCp0bfq60wgDgLp8mW6XJoo/S4O1+yFCZhALwT4YXaGtNf+zR2scx+W1pFisHT5EoM/9qELCThA6sKX2sAjLadrCEBiDpBGyj9an8Nyo9q1mYAJlIDAovJxQymUL4do/yNSbaVLp2wmYAIRERgkX1aTemp8Yq7PP6RbpP2kIm2AMt9CCuVLkb447y4m4ACpi19uH4+2gz7jh97u7uOaoj9ijDEB0s+LdsT5m4AJNEVgjK5mwva1yV0ER7RAs1SwzQRMIF4CG8m1enMFGSKLqDN+RapnfM5qd1nbCGXAIjBTs87I6VebgAOkar5/uqcvlNJjjGMiQUFLV/6LUsxzpGJiZl9MIBYClC+TJb67S0msOPUvyfMFBMFmAhETuEm+zS1RN+B7G7bsYwRP9VaV3Vbnn5NekH4lZWmUL1dLz2eZidM2AQdI1fw/MFyPHXP3NL+nwAp7t1bz9fipTaDUBKjAjE+e4AvaDpWmJcfemIAJxEvg+4lrISAKQRLDY2dJF0hfTK5JbwiK5pe4nuF460lZGeVLzPWXrJ7b6eZMwAFSzsAjyG5d+bCCNCUCX3pzYQN9QGF8Rm8X+LwJmECUBJaXV6tLoQLDxG5aoc+VbCZgAvES4Lu7phSCozDChGNEffEY6Ump1sK14XztcTjf7pYgjGGAoXxpNz3fbwK9EnCA1Cuarv2A1hdac6dH/IQD5FuPxNZmAiZQHgLj5OrT0m3SGhItz3+V7pdsJmAC8RI4TK6F4Ch4GQKdcP7b4YOa7ed0zJB4vu/HS3z/szDqL+QR5jdmkYfTNIHZBBwgVe8/AgVM7K0vFLQsCXx99V6Pn9gESk0glC9UrPaRFpNY+cpmAiYQN4F0gyRByFs17hIkLZ06x/VbSvQ8Uafgu84iDV+W0sY8RD5njtKvpRBsabdpo3yZJDEE32YCmRJwgJQp3ugSp2AaJoX5AdE5mDj0B21pqeqJ1UH7ZQImUJfAWJ0NDTAMtZspnVb3Sp80AROIicCP5czjiUPUFQbWOEejxynSQhLzhGnAnCo9KO0iEVSxemWtHakTw6VFpAOlj0qtGgFSKF9aTcP3mUBDBBwgNYSpay7itwMWlSjUYjVaoehBomI1K1Yn7ZcJmMAcBBhSF1qTmaRN6zLf59clmwmYQNwEHpB7K0vXpdwMvT0ER+dJDKVjpbq7pDBfiVVnj5B6M3qQuAbjb/oSs/ea/2dx3bKW5ACpeXa+owUCDpBagFbiW2h9uVEKrUQxPspoOcUyoyfF6Jx9MgET6JUA5csM6X5pJ4lleL8i2UzABMpBgEDoBIneoLQ9poPbJRpBsBWkEPS8pf2+lvA/Tp+HIXFcd5bUim2nm16Sbm7lZt9jAs0ScIDULLFyX88E6thbX6hcTZfq/dZCuenbexPobgIESOOTR6QSwxCcq5Njb0zABOInsIdc/KNEzxHB0hsSw+ZGSvQGM+8I65H4O03gdJX0Jak3u0YfrChtItHrRMNJKxbKl1mt3Ox7TKBZAg6QmiVW3usZT7yZdFnkj0DFai/pgcj9tHsmYALvEeBvyWgpBEjMNWCuAi2+NhMwgXIQOExuEvzwfSYQ+Y20mjRdmiYRNGEEUARHy0mjJHqO+zIWaLhBerOvi/r5jCAt9vpLP4/gj8tEwAFSmd5We76O1u0ESbT2xGwUvKHrPmY/7ZsJmMB7BDbWLvMbJySn/qntv5J9b0zABMpBgPmCbyeuUj88TXokOT5PWz6jV4lhdX+X8rIhymhVyQFSXsSdjyuiFfo/QPc0izOwAELMRovVStKHpNBaFbO/9s0ETGCuuShfbpOeSGD8n6GYgAmUigBLcG8q0Uj5jjRROlWaLH1DogeJUSgflW6V8gyQKF8oWzz0XhBs+RBwS30+nGPIhQLm3Bgc6cMH/j+uLr0kOTjqA5Q/MoHICFC+hNZdht1Q2TpT+qtkMwETiJsAc4MOksKoIoKk0cnx2tq+Kh0q8ZtmKG+jfLk470ydX7UJhC9DtSl0/9Pz423rS6ECE+sT4ydd/LRU2UzABMpBYG65OUwK5cvByfGS5XDfXppApQnQMDlRoj6YbpgkSMI4vx87BdoI5R3KlwLdcNZVIuAepGq87W30mIwdZlWpmI0CmVai38fspH0zARN4H4GtdMT8xsnJWYbHUt78Izn2xgRMIF4Cy8i1pWrcI1AKARLb+Wo+z/OQxt1lpVC+5Jm386owAVoGbN1PgO7py6U3In/UX8i/z0r4azMBEygHAb6v10rMb6QnaWHpBOlxyWYCJhA3ARZhuEdK9x4FjzmHqD8UZZQv+PdgUQ4432oScIBUjfdOAVOW7ulX5OuF1XgtfkoT6AoC6fLlND0RLdIESTYTMIH4CRAAPSyFHqO0x5xDo5OtNrlbunzJPXNnWF0CDpC6/93Tdb66VIYA6UD5OUYKy4xq12YCJhAxAX7riB+AHC9tnPhJa+9hyb43JmACcRNYQu4RhNRaukdpXn1YRH2xR/mm5zfW+uhjE8iMQBH/4TN7GCdcl8D2OssvV99W99O4TjIEMPZlyOMiZm9MoFgCo5X9W9LV0t0Sv3+0j2QzARMoB4F55Cbf4WAERrUNqk/r3KxwQY7bLZQXjTBTcszTWZnAbAIOkLr/PwItQ5dI/K5BzDa/nDtLYg6SzQRMoBwEKF+ovNC4saO0vPSoZDMBE4ifwA/k4kNSj8TIDRooD5F+JwUjYJoWDnLeUr7cKD2Vc77OzgQK6TI19nwJjFB2ta1B+XrQWG50868h0VpkMwETKAcBKjChfNlT++tKtEjbTMAE4ibA8PsjJOYY0VhOkMT2FIlhs6HHiADpXqkIS5cvReTvPCtMwD1I3f3ymXu0isT8gNhtZzlIS1YZhgLGztL+mUAeBJZWJvyIZAiQqEjdKj0m2UzABOImQI9RemQJgdICEnMJPy4RMGFcd93svXeDKX4E+jmJle0oA7KyuZXwZlIoX7LKx+maQF0CDpDqYumak7S+UFm5vwRPRBf649LFJfDVLpqACbw7sZuK0k0SDTH8Vsqpks0ETCB+As/KxZ9KNGwEvab9vaTlJAImAqgJ0prSl6XdJBZTWkQaJh0lZWWjlTC/1XllVhk4XRPoi4B/KLYvOuX/jADpghI8BoXtcRJLfIdu/RK4bRdNoNIEKF+oPFGJ+p60kbShdIlkMwETiJ8Af3MxgiGM1eroFQrHb2l/jDRW4nt+VbLVZnbwwjC9rIzyZar0clYZOF0T6IuAe5D6olP+z4brEcrQPf2m/LxCOrH8yP0EJlAZAlSaQvnCcJjbpZ9V5un9oCZQfgL83cXoQcLYUi98lQPZIxLHAyS+4ytLMyXsdekns/ey+YcAKZQv2eTgVE2gDwIOkPqAU/KPmGRJ686UEjzH4vLxTukPJfDVLpqACcw11xBBGCSNT2DQyMH8QeYr2EzABMpB4HK5eWbKVXqOdpAYLjtDGicRCLFKJTpPYt4h85SWl66WsjAWa1pfcoCUBV2n2RABD7FrCFMpL6L1hRbdh0vg/a7ykYCO3zwIFa4SuG0XTaCyBKg40bp8b0LgJG1ZjtdmAiZQLgJfkbvbSgQl9BQRJFE3XFEiAJos3S1Nk2jEpBEk6+/6NsqDgOx6yWYChRBwD1Ih2HPJtEzd0wyt+7Hk4CiX/xrOxATaJkD5Er6vw7X/LYlJ3DYTMIHyEBgkV+kNXkvaV2KeUTACJUah8F0nKKIRhG3aVtHBl6Sx6ZMd2CfPCRI90zYTKISAe5AKwZ55prxXemNOyDynzmTwNyUzUKJr32YCJhA3ASpOo6WvJW4upi0Tu89Ojr0xAROInwAB0SkS32cWXxgjEZCwUEPa6FUalD6R7K+k7W1Sj8Q1B0t/kDphBEgEZDYTKIyAe5AKQ59pxrTo8nsGUzPNpTOJM7Ruc2mZziTnVEzABDImwNyAJSXmL2CbSU9LL3NgMwETKAWB78lL6oAESFtKF0lHSARJsyS+z2xZya5eYyvD8giO5km2e2rbCaMusJrk+UedoOk0WibgHqSW0UV9I60v10jPRu3lu86N0obK1W9K4KtdNAETeHfIzd0C8UgCg0nbz0iPJsfemIAJxE/gBbn4H4kACRst8ff4LulC6QfSphILKNX7bt+k8wMljPlCnVqwYTul9Zx0u2QzgcIIOEAqDH2mGRMglaX1hdbo+6WTMyXixE3ABDpFIF2+MKRmW+mcTiXudEzABHIh8E4qlxAksWU+EiJQWU/qzW7QB7tJn5Ruln4odcIoXy6R0v51Il2nYQJNEXCA1BSuUlzM+OGNJbrKY7cvy0EK2KckWrJsJmACcRNgrsEI6ffSctLuUo/EPEKbCZhAeQjQ61vPQrC0Tr0Pa879U8eokzZSiR3TyQSdlgm0QsBzkFqhFvc9tL5gDLGL3WilYhjgx2N31P6ZgAnMJsB8wfmkiRKTspmvcKz0L8lmAiZQHgIHJq7Wa5zk3Et1HmVlndtLGlLns06cWkOJkEdZRsB04pmdRqQE3IMU6Ytpwy0CpMnSq22kkdettDyzeg6ymYAJxE9gnFxkaA1zBGjguF86XrKZgAmUi8AsuRt6i4LnIViid4nvetoYDh8aXmlcpyc5HKeva2ef+gtzGylXbCZQKAH3IBWKP5PMKWDK0vpysnz9dCYUnKgJmEAWBEL5sogS30h6Qno+i4ycpgmYQKYECERel0JQRGYETIjg6BYpbXskB3MnW3qSOm2ULxd1OlGnZwKtEHCA1Aq1eO9ZVK6xolQZAqQh8vNw6SjJZgImED+B+eUiQ+woX5jnOF2aItlMwATKR4CfAmGJ7nQvEsESiyN8Sgor1Gl3trFy5QeS/bBNDjuywY8RUhnqLx15YCcSNwEHSHG/n2a92043MLTupmZvLOD6B5QnlauTCsjbWZqACTRPgMnTVJ6mSsxDYnGVX0o2EzCB8hFgjhE9wARF6K1kS73wIOnLUtoY9pYOpkanP+zAPo0uS0iTO5CWkzCBtgk4QGobYVQJ0D19qfR2VF7Vd4aK1Z5S6K6vf5XPmoAJxEKA8uVK6TXpk9JK0oKSzQRMoHwE6D0iICHoQfQKzZKwAdKas/fe++f193ZnB1Tp49RHLe9SvvDbRwz9s5lA4QQcIBX+CjrqwEilVobuaf7f0du1tOTCUBBsJlACAlRgQvmyuPbpQeJHnm0mYALlI8Df4XQdMARJrEz5jnRazSNdp2MWZKEB9nHpc1InLV2+dDJdp2UCLRFIfzlaSsA3RUNgsDxZTQoVmGgcq+MIq1+xCtbFEpUsmwmYQNwECIhYxYryhaV4aW3u9O+fKEmbCZhATgQYjn+nxPC6YLO081uJ30CaEE6mtodof15peen61Pl2d+mx2lIqQ/2l3Wf1/SUh4ACpJC+qATdpfSHYuKeBa4u+ZGc5wHjnM4p2xPmbgAk0RGCsrmLOApUihsVSuerthyb1kc0ETCByAofJv9VTPoZ5SN/Vub7qEVkM4R+mPJnXeEXKH++aQKEEsliJpNAHqnDmBEgXSenWoFhxrCjHeqQpsTpov0zABN5HYJyOJkpUjm6RtpdsJmAC5STA/MFjJYbVUWcI+oz2i1i2n/rLtRIjS2wmEAUB9yBF8Ro64sQIpVKG7ukF5OdwiYKw05M8laTNBEwgAwJUYEL5wvL8/5YWyiAfJ2kCJpA9AXqBCY6wsL1Z+6fPPvP+fxbWIUPrDpbmef9HHTtKly8dS9QJmUA7BBwgtUMvnnvXkyvLSZPjcalXT5jLMFOa2usV/sAETCAmArQ2D5FCgDS/9hkiy2RumwmYQLkIDJK7l9a4TJDE3GAWTToq9Rnnr5TobfqFxH27SYtInTKG1m0ihfKlU+k6HRMwgTYJUCDc1GYaRd9O605fY4aL9q82/6VqT/i44wQIQvfueKpOsFkC3VC+fEoP/Xjy4IOT/doKVrNcfH25Cbh8ieP9tVK+/Fqu07gRhtWFLcNn2afxYxsJo3EkfM72HekN6VFpUakT9iElQpos/mAzAQhEUb64B6k7/jNurccoS+vLl+TraRKtVTYTMIH4CaTLl2Xk7pPSJfG7bQ9NwATqEJilcwQ7GFsCI4KiUB/kc0akYARCNI7wOcERPUoDJUaC8FMdnTDKl8kSv69mM4FoCIQvRDQO2ZGmCfAOh0llCZBulK+h0G36YX2DCZhA7gTGKsdQvqys/SslhtvYTMAEykfgx3L5/sTt6dqyuFNPckzARDD0K2mStJg0QjpFukuipwdjga9ps/fm/IfA6QCp0R6mdAPMnKn5jAkURMABUkHgO5jtFkqL8cBTOphmlkl9WokzQfTZLDNx2iZgAh0hsLZSodcoBEg7aZ/eXw+HEQSbCZSQAMPy9pBuk5hPuKZEXZDeoVkSCzGwmNKW0q3S7dJC0mjpLOkG6cBkq8377EgdsYALw/i4l/T7MgKwdaRQvvR1rT8zgVwJ0ApgKzcBWl/olWHYS+xGYUnl6u7YHbV/JmACswlQvtwnzZCGSPQm3SK9KNlMwATKSeA0uc3f4h6JXiPmJDF0jmP2qRsi5gsTOO0uXSDtJ/Vl++vDcC/D9DaXLu/jhm312ctS2eeB9/GI/qisBNyDVNY3957fW2u3LK0vy8pXArneuubfeyrvmYAJxEBgnJwI5cvy2n9COj8Gx+yDCZhASwQW1F2rSARDGAEQ85AIjH4vPSTVGnVFepP7MwId0iHoojfqXqkvC/UX8reZQFQEHCBF9TqadoahaptJoQLTdAI53zBY+b0unZhzvs7OBEygeQJUoEZKoXz5sPYfk/4o2UzABMpJgGFyDKMjiMEIThgySw/SvtIm0vrSdClt9CD1ZwfoAsqHi6UdpYelvmyUPgzlS1/X+TMTyJ0AXaG28hKgcBkgMWm6DLaqnFxYYs7U02Vw2D6aQIUJbKpnZ+7BhIQBZc1L0qvJsTcmYALlI0CjR7ruR0MIvUgYja58z5k/9GnpbIky4CRpitSfPaMLDu7vouRzerGGSg6QGgTmy/IlkP6S5Juzc+sEga2VyFSJSksZ7DdykoL2nTI4ax9NoOIEKF+Yb0RjBpWodaXHpVmSzQRMoJwELpHbu0hhBBHB0X8ktidIBDnYJGlxid6mLBpFKF8Ycs/qeDYTiI5A+IJE55gdaogABUyZWl9Wk7+0GNlMwATiJ5AuX5aTuyzM4OGx8b83e2gCfRFgVTqCIYzAKIjh77/gZMpozMwiOCILyheCNZsJREnAAVKUr6Uhp+j23kAqS4DEsqEUhqdINhMwgbgJ0GrMMr+hfDlQ++tJLNRgMwETKC+BZVKuEyihUBfcIfVZ1rsM9QvlS9Z5OX0TaJpA+FI0faNvKJzANvLgTen6wj1pzAFaoBmqw5LBNhMwgbgJDJd7PdKUxE0mXNOSzG+c2EzABMpJYAm5/ZHEdXqO0jZABzenT2S4z3Bd6gQM47OZQJQEHCBF+Voacoru6cslgqQy2M5y8gXpB2Vw1j6aQMUJUL5cLb0s0RgzSHpY4thmAiZQTgLflNvMKwo9RzwFgdJT0r7SFVIeRvnCz308kEdmzsMEWiHgRRpaoRbHPRQwLHhQFqNyxeRPJmXaTMAE4iYwTu6F3iIqTm9JR8ftsr0zARPoh0DtbxkRHDGyYyWJOUh5GfUXD6/Li7bzaYmAe5Bawlb4TUvLAxY8KFMBs5f85bcW6EWymYAJxEtgEbm2oRTKl3O1f7pUlp8TkKs2EzCBOgTOTp0jOEJrSnkGR9Q7GcIbyhft2kwgPgIOkOJ7J414tL0uek66vZGLI7hmfvnwjuQCMYKXYRdMoB8CY/Q5FaZrkuv+qu3XJSpTNhMwgfISOFmuh0ZKhtnNkkbl/DibKz8aYSbnnK+zM4GmCDhAagpXNBfTPX2JRNBRBttDTtLjtWAZnLWPJlBxApQvVF4YVmczARPoHgLUGc6TwtzlHu0/lPPjUb7cJHm4fc7gnV1zBBwgNccrlqtHypEy9cZ8R/4uJlEw20zABOImQAUmlC+sbPUv6ei4XbZ3JmACDRI4J7ku9Aj/WcfLN3hvJy5Lly+dSM9pmEAmBBwgZYI100TXUOorS6ECk2lmHUic305hEugNUl5LiHbAbSdhApUkwNK7lDGhfKFhY7AUWpy1azMBEygpgYHy+wyJhg+G2FEHXFViEaVLJc5naXMrcYbYhfIly7yctgm0RcABUlv4CrmZ1pdHpPsLyb21TFka+Nut3eq7TMAEciRA+cJqk7ckeR6oLS3N/v2yBIg3JlBiAqxOSZBCcISFXiT2GZnCz3FkaeRBEDY1y0yctgl0goADpE5QzDcNKjAX5ZtlW7ntr7sJkF5rKxXfbAImkAeBMPwlVJy2VKbvSGFYTh4+OA8TMIHOE2A0x78lvtvh+x0CJXJj/212MjTKl6uklzLMw0mbQEcIOEDqCMbcEqEAGyGVqXt6sPylxepOyWYCJhA3gRAg4eWm0iYSq169KtlMwATKS+A3ievUI0JgRKDEPlt6dVjSP0tLly9Z5uO0TaBtAg6Q2kaYawIbK7clpMm55tpeZoxtvri9JHy3CZhADgRWVx4rSKEBZl/tMxzmL5LNBEyg3ASWSbkfepDCKY4Z5UFvcVa2kBLeUArlS1b5OF0T6AgBB0gdwZhbIrS+3C49kluO7WXEZMwVpXnaS8Z3m4AJ5ECA8uUhaXqS18va0ozFjtAAAEAASURBVKp8cnLsjQmYQHkJsEBD2tJBEkPrHk9/mME+5QuLvVybQdpO0gQ6TsABUseRZpogBcz4THPobOLbKjl+pfuSzibr1EzABDIgkC5fGHbD34dTJf8ekiDYTKDEBAiO6B0OQ+vClkd6UWJe0BEcZGiULxMlr4iZIWQn3TkCDpA6xzLrlBjqwoTpsnRPUwDvI9F7NE2ymYAJxEuAvwWjpVC+MKH7E1LWq1opC5sJmEDGBAhK7pPoNQo9R/yNZkjdt6TR0mNSlkaAFMqXLPNx2ibQEQIOkDqCMZdEhimX+SSGvJTB/iEnl5P47aPnyuCwfTSBChNgbgC/eXR5wuBj2r4uef5RAsQbEyg5gbASZbr3iP08RqUsrXzSv69WcpR2vwoEPhDpQy4rvz4t0dLxO+lJKdgO2llVOj6cqMh2nJ7zGqkMwQbvb7Q0S/qaZDOBmAi4fJnzbdC6e4cU5iGwgh3l7iWSzQRMoHECMZYvC8r9g2segfrVWdK9NeezOGS4PXWXW7NI3GmaQBYEYuxBYmjH/RJ/oPeUWB6a3pNgtEIMDwcV2pape3pJvRfe4c+lPArfCv038KO2ScDlS32AlC+hJXkl7a8iPSG9JdlMwAQaIxBr+bKl3J9fSvce8UQP8E8OFsqXd3LIy1mYQEcIxBgg7aUn+7b0YWmtZP9cbdeXqmoUbCzxXZbxuwzPeV46SbKZQEwEXL7M+TaYwE2jUyhfaO19UZok2UzABBonEGv58rYeIR0chXlIZzb+aG1dOUp3h/KlrYR8swnkRSDGIXYb6OGPSQGgks0CBRdLtIJU0cbqoWl5YYhdGYxhkItJr5TBWftYKQIuX+Z83Vvp1NzS5OQjtotI4Yclk9PemIAJ9EMg1vLlevlNkBTqfARL90h3SFnbaspgkOQAKWvSTr+jBGLsQbpAT3iQtEDqSU/Q/inSRdIgqWpG9zSVFn7ILXbjD8RC0iUSv6NiM4GYCLh8mfNtUL5cJ72QfHSUtjRyeDhMAsQbE2iQQKzly3LyPwRHPAo9SA+zk4NRvjwi3ZdDXs7CBDpGIMYAiUmDy0h8oWjlCHa4ds6XvhhOVGhLAVOW1hfe3avS6RV6P37U8hBw+TLnu0qXLwznXUF6Wpo156U+YwIm0AeBWMuXN2t8pm7FsDeG12ZtlC80mNpMoFQEYgyQmBjMF4rhdGGcbID6Ve3wpWZOUlVscT3o2lJZAiRanmdKMySbCcRGwOXL+98Iq1ttKoXyZZ7k4wnvv8xHJmACDRCItXy5X77/RUrXqehRoscrSyMQGymF8iXLvJy2CXSUQLrLtaMJdyCxO3tJY1mdZyxto7afLjy4j4uX0Ge1rSt9XJ77R0yYfkm6KfecW8vwAd02XSJIsplArAQ6Vb6wIMm+fTwkc/Fe7+Pzoj8aJQcoT69MHPmctlRqHk+OvTEBE2ieQIzlyxQ9xm4S3+9gNEYzpeEuiWH82CBpE4ky4VGpHeP31ZaUJrWTiO81gSIIxBwg9caD1ezo+aIruxG7RRf9q48L19RnMVdgKMBofZnVxzPE9BEBHXMZfhmTU/bFBBok0Gz5Qosxk517s9H6oJkGnd7Syeo85csV0htJBntoSy9S1i3LSXbemEClCBRZvkwT6XRwBHh6lI6XeqTvSpdLIZih3GL13LulVo3yhWDx4VYT8H0mYALFEWCu003FZd9vzhRqn+/3qnguWEGuMCzQViyBmcp+72JdcO4iEHv5cqt8PDR5U1/S9hnp2uTYGxPojYDLl97I5Hu+mfLlg3KNhlaCoqB3UvsEMSdKbyXnaDj+vtSOXaSbCcBsJtAMgSjKlxjnIDUDsduvHawHXFWiB6kMtpycPFZapQzO2kcTqDiBpfT860ihfJmsfXqT+C0XmwmYQHcRuE+Pw9BZgqO0hWOmL9B7HEar0NtEA22r9gHdOEwK5Uur6fg+EyiEAP+BY7R55dTuEuNXw5yjB7R/r8QPm9HCUQWje5ohPO10cefJaYgyI6BjUQl+d8FmAjEScPny7luhfGE47I3JS/qGtlSQqEjZTMAEWiMQY/lyqR6F7ztBD/WnHqm2gZzjMdLvpA9JF0qnS63aVrpxPmlKqwn4PhMokkDtF6RIX0LeK2uHMf1flQZK0ySCo8Ukzt0gDZGqYBRol5TkQek1Yt7CShKFsc0EYiTg8uW9t0L5MkFimA0/DLuu9KL0H8lmAibQPIEYy5fl9Bh81wmOsAHSkxJL+f9ICuf53i8v7SytKB0sfVJq1ciThtJnW03A95mACbyfwCk6PO39p953dKqOjnvfmfYOmhnD215Ozd/9mG5pp4BqPsfW76CX602J1XBiDLxbf7Jy3jlTbnsO0pzvzuXLe0zu126Y33ir9plz8Lv3PvaeCfRKwOVLfTQxli+ryVWCn7SeT7nP3+53ks/pXWKIXbj2Zu23alfoRobc20ygWQJRlC8xVmRXFskz+qDJELst+vi8Wz5aTw+yjDS5BA/EMEhaoKlwMbyOwtZmAjEScPny7lsZrA29vswPGCQtLLFAwyGSzQRMoDUCMZYv9+pR3q55nIV0zBxE7HyJxk2sRwo9Spzj3laMoXWbSp5/1Ao93xMFgRgDJMa9fktarg4hvtBHSlVYZWlrPSdDDR+UYrdPyUEKU3r2HBzF/raq7Z/Ll3ffP+XLoxKtxwypYS7S0dIrks0ETKA1ArGWL+fqcegVCkYQtFNycKS2zDXibzfnQ4A0UftflFqx0clNV7Vys+8xgRgIfCAGJ2p8OFHHg6QZ0oMS42T5Yi8mrSKdI31H6nYbpwcsS+vLbvKVCtY/u/2l+PlKT8Dly7uvkAAplC9nab9H+tO7H/lfEzCBFgnEWr7sr+fZXmIBiWBhrjA/RP9piTmIG0o0nL8m8SPYfNaKUb5cIb3ays2+xwRiIBBjgEQL5hekH0tDJYIi/njT2nmbNEPqduN5h0knl+BBKURXkOiKf64E/trFahNw+fJuC/EY/Tf4RvJf4WhtGc778+TYGxMwgdYIxFq+0MA8t/Q/Eg3Od0gPSWnjbzlzhrj2B1KrwZFunb0oxF/ZsZlAWQnEGCAFljO1g6pozLFijPCUEjz8EfJxlhQme5fAZbtoArPLlqqWL+vp/TNc+fLk/8Gd2qYnbSenvTEBE2iRQGz1l8P0HD3JsxAk0fhca/i8T+3JFo4JsOiNOqiFe32LCURDIOYAKRpIBTiytfK8UXqqgLybyZJV0laT6N1rZ7WbZvL0tSZgAu0RoHxhfuPDSTI3aHt6su+NCZhA9xHYXI9Ez1HoQeL7n5WNU8IMraNcsZlAaQnEuEhDaWF20HEqMGF+QAeT7WhSPUrtJxKFLr+XwNZmAiYQP4F0+cLwWFqXj47fbXtoAibQAoERuocenRAcsaIdf7s5zsIoX+idJh+bCZSWgAOk+F7dPHJpMyn2AGlkgm5CCXxNXPXGBCpPgFEDVJhC+UIv0rnS8ZLNBEyg+wh8Vo+UrutRBvxJ4jeP7pbWkDpp6QaYTqbrtEwgVwLpL02uGTuzXgmM0icUYFf2ekUcH1CxmigdHoc79sIETKABAgy1mV+amFw7VdvvSP5bkADxxgS6iMDyepY9pNBbxBb1JBqi7S+kThk90qQZGmA6la7TMYHcCVARt8VFgNYXKi0vx+XWHN7crzNMwmxnpZs5EvUJEzCBTAlQvtwkPSvx/d1Iekd6XbKZgAl0FwEWYwnBUb0no2GEBaE6ZdsqIeZOs/CLzQRKTcCthvG9PiowZWh9+bn8ZBlPWqNtJmAC5SCQLl8GyeVHpTHSdMlmAibQXQSeqHkc5goH8RHB06/Z6ZBRvlwqkYfNBEpNwAFSXK9vYbmzvlSGAOkK+cn4ZX5QzmYCJhA/gfnk4hbSeIm5jvzuCa2910o2EzCB7iNAA8gkKR2wEBQh7A2J30fqlI1SQmWov3TqeZ1OFxNwgBTXyx0ndyiwro/Lrbre0JXOUB2G59hMwATiJxAWVmEIL4HSAKkMZU38ZO2hCcRJYE25NUIKAVHYBm8Jjj4p0TDbrq2tBJjzNLHdhHy/CcRAwAFSDG/hPR/onp4gvfneqSj3jpVXn5D2jtI7O2UCJlCPAOXLlRK/UUKl6X7pNMlmAibQnQTWqXksepJo1GRLPWOWNFxiWFy79UHKl+kS5YrNBEpPoN0vROkBRPYAFDCXReZTPXdW1MmnpS/V+9DnTMAEoiSQLl/WSzy8JkpP7ZQJmEAnCFyuRAiG0saCLN+U6EFmoa4eaUlpEakdS5cv7aTje00gCgIOkKJ4DbOdWFb/riYxPyBmo1BdTOK3U5iDZDMBE4ifAN/ZML+RletY7ntm/G7bQxMwgTYIDNK9tfW8eXWOH4qdJL2V6GJtn5VaNfIYIZWhgbfVZ/R9FSPgZb7jeeHbypVnpNvjcamuJ8N0dgNpWt1PfdIETCBGAmPl1CvSddJJEgs2PC7ZTMAEupfATno0epDC3KOw5RzzEBkFwkIt50jt2Ka6eVGJoMtmAl1BoLZloSseqqQPQfc044Bru8Njexxan+6TTo3NMftjAibQKwHKFyovb0vLSDRwHCrZTMAEupfAY3q0EBTxlNQv0gETw+r+IVEutGOUL7dIT7STiO81gZgIOECK522Mlitl6J7eU35SmN4j2UzABMpBgAoM5QurVj0v/VGymYAJdDeBQTWP97qOZyXnerS9u+bzVg9D+dLq/b7PBKIj4CF2cbySNeXGilIZAiSC6qsk//6RINhMoAQEKFuGSuOlFaSFpEGSzQRMoLsJpBdeoOdounSRNFL6q3S21K7R6LKl9LN2E/L9JhATAfcgxfE2aH2ZKT0Qhzu9erGPPuG3mpjgbTMBEygHAb6zT0p3JNu/afs9yWYCJtDdBC5MHo/gCOO3is6XmEt8o7SW1K4NVwIDpSvaTcj3m0BMBBwgxfE2CJBYRSZ2W14Osrz3QbE7av9MwAT+SyAMf6GS9FVpN2nj/37qHRMwgW4lQKMrc5CCeM4vSjSY0KN8W3KsTctG+XK19GLLKfhGE4iQgAOk4l8KBdcI6bLiXenTA4ZjMv9olkRvl80ETKAcBMbKzVC+8COxDI+9oRyu20sTMIE2CBAI0TASRFK7SKw4R/0PHSq1Y6EBpp00fK8JREfAAVLxr2QTubC4NKl4V/r0gACJwOg86a0+r/SHJmACsRBgCM2yEj8YuZR0iDRE8ndYEGwm0OUEjtXzhd4jthiNnMEInDDmEbViC+omflctNMC0kobvMYEoCThAKv610PpCN/djxbvSpwf8QOw/pWP6vMofmoAJxESA8uV+iaE2f5Lmly6RbCZgAt1NYB493iekEASFp+1JnSNoouHkiPBhk9uxup7GlmuavM+Xm0D0BBwgFf+KqMCUofWFgpa5CzsVj8wemIAJNEgglC+sYkdv9dvSDxu815eZgAmUlwCLKdEzFHqOeBL275TSQRONn5tKjdq+uvAFiR+YPUCaLL0h2Uygqwg4QCr2dVIwbSnFHiDR4vRNaXXp35LNBEwgfgJ8b0dJlC8fkt6U+B6/JNlMwAS6m8B0Pd4sKR0MsX+UFIIkGky45jSpEWNI3R8kfipgCWkHifLFZgJdR8ABUrGvdLiypxt8SrFu9Jv7AbqCwpAfmXul36t9gQmYQAwENpYTC0vMP2L1yWulTvzuiZKxmYAJRE7gYfn3rxof39HxgRJzE+lNul0aKf1ZasTokWI+cjAaYSaEA29NoJsIOEAq9m1ureyptNBdHavxf+TzEitfjYnVSftlAiYwB4FxOnOrNJ/0U2mQ9IxkMwETqAaBHfWYBELB2N9WCnW/DbT/fPiwgS0NLccl1xFsvSrxe0o2E+g6AuFL0nUPVpIHIkCKvXuarnRajB5PpI3NBEygBARC+cL8AFqTLy2Bz3bRBEygcwQIYMIQO7a1dT6CnGYCJDxjmO4K0l+kCyXSsJlA1xGo/bJ03QNG/EALyDeGwMQeIJ0lHxled7hkMwETKAcBhu5uJVG+fEt6VjpFspmACVSHwLdrHjUES5xmf7r0KAdN2iO6fgsp9vpLk4/ly03gPQIOkN5jkfcew9VmSVfnnXET+S2ma4dKA6VbmrjPl5qACRRLYJiyp+f3LukT0jrSDMlmAiZQHQLMGWZxFozhdSgY+6tKXHOSlP5Mh30a960iOUDqE5M/LDMBB0jFvT2Gv0yWWPggVltUjjFn4QCplVamWJ/LfplAtxOgfOG3SXaRWC3z3xLzCG0mYALVIcDfbXqK0j1HtU/PHMVPSR+u/aCPY8oX0r63j2v8kQmUmoADpOJeHwVM7K0vX5ePDAV8uThMztkETKAFAqF8YX4BDTHfaSEN32ICJlBeAkvKdRpG6EkOFoKlEDCFLfOIaBBt1ChfPKexUVq+rpQEHCAV89oouNaWYg+QlpOPzF1wQSgINhMoCQGW9g7zG8dpn15gFlmxmYAJVIfAunpU5iISIKWHz7Gy5dLSThKLOGDTpL/N3uv/H9IaJcVef+n/SXyFCfRBwAFSH3Ay/Ggbpf2idHOGebSb9FJKgN88uE8KrUztpun7TcAEsicwWlmwct1N0oqSfxhWEGwmUDECd+p5a1eYI7hZT+LvO71LNIIyP3EDiblIjdj6uoj7JzZysa8xgbIScIBUzJsLw19mFZN9Q7lSsaIQ/GdDV/siEzCBWAjQa8SwupHS/NJTks0ETKBaBMbocUOAVNvIuWmCgsaTO6Rm6iLUX+6WZko2E+haAg6Qinm1o5XtZcVk3XCu++nKhaQnG77DF5qACcRAIDTAECgxf/DcGJyyDyZgArkS4AfoQx0vPcQOJ+hdbtVC+dLq/b7PBEpBIHx5SuFslzg5RM8xWIo5QGKO1MclWp9iXoZc7tlMwARSBJbV/poS5ct5EvMKmHNgMwETqBaBi/S4T0i1vUdQoHxgHlKzxnym4VLM9Zdmn8nXm0BdAg6Q6mLJ9CStL0yYvifTXNpL/JO6nTkMVLBsJmAC5SFA+RIWZThd+3uUx3V7agIm0EECuyutZSR6j9JBEsesTruz1KxtoRsYtjup2Rt9vQmUjYADpPzfGBWYS/LPtqkcN9fVr0lHNXWXLzYBEyiaAOXLBOkgaV7pBslmAiZQPQL0Joc6HkFR2ugJauU3jChfbpSeTSfmfRPoRgLhy9ONzxbrM42SY7F3T0+Vj2dJrLRnMwETKA8BKjCUL+tJVIDcyCEINhOoIIFVa56ZXqRZ0oPSIdJEqVkL5Uuz9/l6EygdAQdI+b4ylsdk3O/EfLNtKjdWrttOooXJZgImUB4CQ+XqitLT0lbSQMktvYJgM4EKEthez1zbc/Sgzq0inSA1a/RIM7ok9gbeZp/L15tAXQIOkOpiyewkrS/MPXoosxzaT3iEklhbmtl+Uk7BBEwgRwKUL3xv+V2TN6XDJZsJmEA1CdRr5FxJKLZtEQejXzBGmNhMoOsJOEDK9xVTgYm99eVjCZJL80Xj3EzABNokME73j5e2lJ6Xpkg2EzCBahJgHnHa6E0aIJ2WPtnEPvWXK6VXm7jHl5pAaQk4QMrv1fUoq9iXx2R5780kfljyPslmAiZQDgJUfkZLNMA8JhEo8RtINhMwgWoSOF+P/XadR2eoXCtGgBR7A28rz+V7TKAugXpdsHUv9Mm2CbA85oLSpLZTyi4BWoamSBdkl4VTNgETyIDAhkpzcely6YwM0neSJmAC5SLwXbm7uvRBKTSGv6P9r0nB9tIOgQ/lxunhZJ3tojrHHOrP1/nMp0ygKwk4QMrvtVIIseQuv1ESq70ix/aL1Tn7ZQIm0CsBypc7pdclJmCfmBxrYzMBE6ggAf6e05tM7zLGKnb0LP+eA9lHpVMlgqd9JH778G9SPaN8oQH1+nof+pwJdCOB0KrQjc8W2zNRwMTePf1D+cgEzEGSzQRMoDwEQvmym1ymxXib8rhuT03ABDIgsIPSPKAm3R4dr5acY6VLepSoBxI8DZN6M8qXidJbvV3g8ybQbQQcIOXzRsuwPOZnheKr0kYS/tpMwATKQWCg3Bwh0QAzRnpS+odkMwETqC6BP+jR6T0KPUiQoJy4WVpZYig9o4jodSZw6mtoPQFS7A28ctFmAp0j4ACpcyz7SonlMWHNCjCx2iA59px0hHSXZDMBEygHAeY3zi1NlJaS+IHnhyWbCZhAdQnMV/PoBEo0plBW7CgR8IyWfiTRsHKJVM+W18mhkgOkenR8rmsJOEDK59XS+sLQNcYEx2iflFNfkvDv5zE6aJ9MwAR6JUD5wtwAFoGhEvRHyWYCJlBtAgQ0DJ3D2IZ9yoiPcFI2RTpKmsxBL8ZwXX58+vZePvdpE+hKAg6Q8nmtsXdPf0UYKDx/lw8O52ICJtBBAuOUFpWh/yetJQ2SbCZgAtUmsEDq8QmKgrG/ZjhoYEv9hcUdQoDVwC2+xATKT8ABUvbvMCyPGWv39KpCMI90jfTj7HE4BxMwgQ4SoBK0mUT58lPpdOk4yWYCJlBtAumh8unghv0JTaAZo2tjrb808Ri+1ASaI/CB5i731S0QoPXlVen6Fu7N+hZaks6WlpOOyTozp28CJtBxAqOUIj8GyfzGxSS+x6xMZTMBE6g2gQdrHv9+HTM/8VrpGzWf9XZITxNzkJoJqHpLy+dNoFQEHCBl/7oIkCZKMS6Pear8Wk0igDtPspmACZSLAOUL8xtZiepk6XnpE5LNBEyg2gRY8j8YjaEEOvy9b6YBhfLlAWm6ZDOBShHwELvsXzcFTIzd0xSUu0pUrPg9BFqWbCZgAuUikC5fLpDrfy+X+/bWBEwgIwL8bU8b9b1m63zp8iWdlvdNoOsJNPtl6XogHX7AWJfH7NFzTpIGSsxZuFOymYAJlIvAknJ3XSk0wJygff/+Ubneob01gawIUBbMkv4j0WvEYkwMx23UqB8yhDeUL43e5+tMoCsIOEDK9jXGujwmv3fA4hGPSV/IFoFTNwETyIjAWKVLz+8NEj3C50i0+NpMwASqTWBlPf6vJBpDMcqJE6U9pd9KH5H6s411AfWEif1d6M9NoBsJeA5Stm+Vykpsy2MOlU8bSnS/j5CaGY+sy20mYAKREKB8mSDRSkxlZg1pXslmAiZQbQLD9PjMOwq2iHY+JREccf4A6cMSw3J7M8qX26THe7vA502gmwm4BynbtztaycfWPf2CfGJS96elhyWbCZhAOQmMk9uhfKGxY5oU42qZ5aRrr02gvAQoF/5/e2cCNkdR5vFAuJQrIIQrIQmHiEAiLggIQhIDeKGuiKII4rErCrrKitfKgvgo4IWiKHiBIOKuB4IIugJJCDciyCEQCPlyEJAQbiQEAvv/55tmejo9PVMz3TM9M7/3ef7p6urq6upf9/em3q7qHj/89PQ6m5cHrkgNjyp5qt3elfV6CwdIkX+pV4Z8CPQtAQKk4i6tP485RvIT3jLZqWrMJtJNZWoUbYEABIIIjFfpCVLUgXFnyL90z9NeQcAgMOAE/H6xR4rio0iePeL1Z6TVpT9J9cz7++NNkX+pV458CPQtAabYFXdp/fRlrjSnuEO0VPMrtde6kt8/wiAAgd4k4NEj/w1HPwa5pdKMCPfmtaTVEMibwOtUYTw4cv2zJb9zvI/k95BnSvXMU/TWlK6oV4B8CPQ7AQKk4q6wAyS/f1Qm21WNWSzZOfq3jzAIQKA3CcSnv+ygU/BsgPN781RoNQQgkDOBnVSfp9XFg6Qrte6A5y5pnpRl9i/+QVl/3AGDwEASYIpdMZfdXP2UpmzD0x5Wt34qYRCAQG8ScKdnqhT5l0lKb9Obp0KrIQCBAgh4Ol3cHCx5ar2n4A5JDpQ8ja6exR/A1CtDPgT6mgABUjGXN/o8ZtYQdjFHrl+rh8v9hHkraVn9YmyBAARKTmBHtW+0FAVIb1R6vvQ3CYMABCCwXgKBv1rrBynrVPJ309JfsUszT8HfRYr8S1oZ8iDQ9wQIkIq5xNNU7S1SmV6Y/rnaY+fo9xbukTAIQKA3Cfjprr9Yt0BaTZooPSs9KGEQgAAEPMUuMo8e+QMu/oKt0zb3/epNs5+sbf7K3TUSBoGBJUCAVMylL9vwtH8bZXfpCekNxZwytUIAAh0iYP8Svd/4TqX9993onYIONY3DQAACJSCwvtrgqbiRvUqJL0hzJAc/50iXSGlm/zJL8tfuMAgMLAECpPwvvef17iGVaXj6W2qPh82nS0skDAIQ6E0CHjHaR4r8i0er3ZH5hoRBAAIQMIEhKRotcqDkfokfpLxC8nT7D0rRdiVrzAFS5F9qNrACgUEiQICU/9XeS1XaAfkJTFns1WqIR4+OLEuDaAcEINASgddor7WlGZW9f6zlz6R7K+ssIAABCBxVQeAgyPJDlPmVPP9mWj3bWBv8VUwCpHqEyB8YAgRI+V9qP325TirL5zG3VltGSX+UHpYwCECgdwnYv9wsRSPB1yrN6FHvXk9aDoEiCFyhSmdIDoaelj4oPSQ1Mo9I+12lmxoVZDsE+p0AAVL+V9gdmDI9ffmy2rORNEPCIACB3iaQ9C8f0+ns39unROshAIGcCfihyWRppOSpdd+TmjH7l+nS8mYKUwYC/UyAACnfq+v3fPyJ7zIFSLuoPf5aze8lDAIQ6F0CL1XT4+83TtD6F6WP9+4p0XIIQKAAAvuqzugjDV56Fok/3NDIpqhAmfovjdrLdggURoAAKV+0di7+3K6nvZTB3J5HJP8wbFmm/JWBC22AQC8S8PuNtlnDixHjtJwr/aayzgICEICACSyW/O5RZA6S/H5Rlm2ljRYBUhYltg0MAX8RCcuPgIen3XnxC5FlsA+rEZtKfy5DY2gDBCDQFgH7Fz98iX6/ZCelF0q/kDAIQAACEQF/rS4yB0r+jbR7oow6S/uX+6U762wnGwIDRYARpHwvtx1MmZ6+vFzt8QuaZRnRypc2tUFgsAjYv1waO2V/0c5PhUfG8khCAAIQSBLwFDuPImVZ0r9klWUbBPqeAAFSfpd4tKp6pVSWAMmfGr9dOlZ6TsIgAIHeJbChmr6zFPkXB0VjpH9I0YiSkhgEIACBEYvEIAqIvHR/oNEUu8kqE/kXJTEIDDYBAqT8rn/ZPo95hk5tP2lCfqdITRCAQJcITNFxHQhdXzn+Xlr6pWs6NBUgLCAAgRcJePptZJ5i95TkaXb1bKI2bCJNr1eAfAgMGgHeQcrvint4+nIp60fY8jtadk0HavPB0lLp7OyibIUABHqAgP3LTCkaDT5Mab9feKuEQQACEIgT8MNvB0YePbL5ow1ZZv8yW5qfVYhtEBgkAowg5Xe1/YT30vyqa6umb1f2/pGWD7RVEztDAAJlIOAOTHy0yD/67Ke9fylD42gDBCBQKgLRg5SoUZsrsW60krJM+peUImRBYLAIECDlc723VjUTpHgHJp+aw2vZW7t4ZNBtOSZ8d/aAAARKRmCM2uMPrkT+xT8M+yFpC2m5hEEAAhCIE1hdK9HokZfuE7wuXiCWjrZF/iW2iSQEBpcAAVI+195PX/xSpIeou23+Be01pBO73RCODwEI5ELA/sVTZKLpdG9Xepl0ioRBAAIQSCPgKXa2aKrdfcOrK/3rr2F6dGnGSlvIgMAAEyBAyufiT1M1ZfitocPVjh2lxyQ+7S0IGAT6gIADJL/f6I7O9tJ7Jb/r+EcJgwAEIJBGID6C5LRnl6SZ/ctN0pK0jeRBYFAJECC1f+XteCZL3R6eHqk2fE1ye46XknOQlYVBAAI9SMAdmOj9Ro8a2W9/XyrLD1KrKRgEIFBiAn648tI67bN/6Xb/pU7TyIZA9wgQILXPfpKq8O8LTG+/qrZq+K72fol0vnR2WzWxMwQgUBYCHjHyC9buwPjv2+mF0lclDAIQgECSQFq/zg9O0/oo9im7SwRISYqsDzwBv5yHtUfAT1/ulNxp6ZZ59Gg/yaNGdJy6dRU4LgTyJ2D/MiTNldzJmSFdLHmKHQYBCEAgSeBlyrCviNssrUS/oRbPf51WHFBdGc8kDQEIDP9hwKE9Au7AdPvpy2fVBjtFv5Nwm4RBAAL9QcD+JZpe926lx0tZn+vVZgwCEBhgAn5Q6il1kTn9xWglsbR/uUbyD8liEIBAjEDaUGxsM8kGBDwCt5fUzQDJT4reJ9kpHi9hEIBAfxCwf54sRf7FT3t3kNyhwSAAAQikEYh/4jvavkmUSCzL8IA30SRWIVAOAgRI7V0Hz91dW5rZXjVt7b2m9n5C8lf07mqrJnaGAATKROBf1Jj1JX/BzjZHcrC0yCsYBCAAgRQCDyovPgXXD1HdT0jaKGXsLEUPYJLbWYfAQBMgQGrv8vvpy18l/6p9t+xtOvBDkt9LwCAAgf4hYP/iKbPu8PgLVPtK/v2jeOdHqxgEIACBGgLJKXbLa7YOr0zV4mkp7d2klOJkQWCwCBAgtXe9yzA8/QadwrYST4Hau5bsDYGyEYj7l0+pcR6xdrCEQQACEKhHYDNtGBnb6BGkL8XWo6T9i2e/PBtlsIQABKoECJCqLEJTfqK7m9TNwORoHf89kqf5LZYwCECgPwh4Ssye0qWV0zlMS48cXVhZZwEBCEAgjcBSZcZHkFxmbErB+AOYlM1kQWCwCRAgtX79967selXrVbS150e194mVGj6npT/SgEEAAv1BwMGRX7a+QvJHWPyVypsr0gKDAAQgkErg0ZTcfyby/Htq20ndfMCbaBKrECgXAQKk1q+Hn75cLSUdT+s1Nr/nmSr6XcnD6P5h2HMkDAIQ6B8C9i9+N8AfYPmLNF36uIRBAAIQyCIwXhs9rS4yjyadEa1UltO09LvLtyTyWYUABCoECJBavxXcgenG0xc/+flXydNtvi95ih0GAQj0F4G4f/EU2l9Kf++vU+RsIACBAgh4ur2Dori+kDiO/cvllTKJTaxCAAImQIDU2n2woXabJEXvB7RWS/heG2iXmyT//tIJ0ickDAIQ6C8C6+l0dpH8AMZPgn8qfVEaKWEQgAAEsghsqo32G5Hcz/OHG+I2VSvdeMAbbwNpCJSagDvaWDgBOxf/8rSnvnTS/FtHDs48x/gbnTwwx4IABDpGYLKO9Ix0jbS+5J8R8N/8cgmDAAQgkEVgncRGjyTFv37pd4/GSARICVCsQiBOwE8WsHACHp6eIT0XvmvLe7xTe24j2dF56S/VYBCAQP8RsH+5UvJvHnlK7RLp8xIGAQhAoBGBtJHmr8d2sn+ZL82J5ZGEAAQSBAiQEkCaXJ2mcp18+vIOHe8cyZ8W/6b0mIRBAAL9ScAdmMi/vFHpCZIDJQwCEIBAIwJ+oBI3T7X7QCzD/qXTrwfEDk8SAr1BgAAp/Dp5aNojOFEHJryGsD0OVvHzJH/y11PsviVhEIBAfxLw+wM7SFEHxh9k8Uj1DAmDAAQg0IjA1EQBT7G7rZLnPt9kqVP9l8phWUCg9wgQIIVfs321i6e53R6+a/Ae/kLd2ZKvk784c4CEQQAC/UvAT3f9zpF/8+gj0isld3D81UoMAhCAQCMCOycKeARpXckPWb3N7zG7P4FBAAIZBFbL2MamdALR9Bd3Woq0KarcX6+yc7tQOlDCIACB/iZg/zJdckD03sqpfqayZAEBCECgEYG/pRSYqLwjpJdIfrj7gIRBAAIZBBhByoBTZ5MDl6KHp/3ewR8lP/HxkuBIEDAIDACBqTpH+5dNpI2l+6QrJAwCEIBAMwSuq1PoFcqPHvDWKUI2BCAQESBAikg0t/R0F78sXfTwdPSekTtGTKtr7tpQCgK9TsDvNo6THCCNkuZLH5AwCEAAAs0SWKaCnuESn+Xi9GnSXlLRD3h1CAwCvU+AKXZh19BPX+6V5obtFlT6Ryq9peRh8KlBe1IYAhDoZQL2Lwul2dIMaXvJ7w5gEIAABJol4BknnpofmYMj/6aaR6TXlGZKGAQg0IAAAVIDQInNRQ9Pf0XHO6xyzM8ljs0qBCDQ3wQi/+Ifh/WL1HOk6f19ypwdBCCQMwF/4MVBUTxI8k+E2L/4x+0fkzAIQKABAabYNQAU22xW+0hFDU9/QnUfI9mpHS/9n4RBAAKDQcB/91Mk+xd/1tuf5T1TwiAAAQiEEPDsk3hw5H39oCV6AON1DAIQaECAAKkBoNjmXZT2k107mrzNjusk6XnpFOlECYMABAaHwCSd6kaSA6Qxkj/1/VsJgwAEIBBCYHyi8AtaP1XaVSrqAW/ikKxCoPcJECA1fw0dxNwq+TeQ8jTPCz5f8hfrLpU+K2EQgMBgEZim071DWiTtL71c2knCIAABCIQQGK3CDooi82iSP/G9XLo6ymQJAQhkE+AdpGw+8a1FDU+fp4M4OJolvSV+QNIQgMDAEIj8y3Y64+MkP4iZIWEQgAAEQgh8WIXjU+yc/k/pCmmphEEAAk0QYASpCUgqsqb0WinP4enNVd9D0hRpmfReCYMABAaPgB+QvE7y9N3LpfWkxyUMAhCAQCgB/xxJ0vww3B9qwCAAgSYJECA1B2pPFXMnxk9g8rD9VMndkn/rxMGRP8vJL1sLAgaBASSwu87Zv3Dv6bX+et1CyXkYBCAAgVACj6bs4FEkv+eIQQACTRJgil1zoDz9xb9O/URzxRuWOkclPCq1WBonOUjCIACBwSRg/3Kn5N898hfsPKocf4dAqxgEIACBpggsSSllf+J3qDEIQKBJAowgNQcqej+gudLZpX6jzX5afJW0mURwJAgYBAaYgP3Ls5IfmHxKGpIwCEAAAq0QSM50cXD0pHRQK5WxDwQGlUBZR5AcQLxL2llyEOGnqnOl2dJ5kjsTnTK/D+BPfH8mhwNepDreILn9R+dQH1VAAALhBMrkX9ZR83eTFkkeof6JhEEAAr1LoNv+ZZzQOSjytDqbl3+QFngFgwAEmiNQxhEk/3HfJTmAWEPyuzoOjjw333k3SltLnTJPd3lGuraNA3o63e2SgyMHe++TfB4YBCDQWQJl8y/+OIM7MA6U5kju2GAQgEBvEiiDfxmfgm6DlDyyIACBDAJlHEE6Tu2dKR1ap91nKf8I6Zg62/PO9vSXWVKrU+EO0b5+KuyPPCyXPil5mh0GAQh0nkDZ/Ms0IfDo0VOSfQMGAQj0LoEy+Bf7k7i9oBX3YTAIQCCAQFlHkM7NOAdPsevkF54cIF2W0Z6sTV/VxrMkB0cPS9tKp0sYBCDQHQLjdNgy+RePKnt0/HFpSMIgAIHeJVAG/7J+Cr6vp+SRBQEIZBAoY4B0idr7eWnzlHb7F6KPl65P2VZE1qaq1L8pEBIgTVT5eySPOPmzvZ4+80tpY2mehEEAAt0jUCb/spEwbC/5nUSm3HbvnuDIEMiLQBn8y7o6Gfc74tbqDJh4HaQhMFAEyjjF7ge6AuMlBxNDkn9M1UPEfso6QbpAOlbqhHn0yCM/Nzc4mDs6/yV5Ot3LJDsnt9lO6TjpaxIGAQh0n0CZ/Mt+wvG8dL/0ie6joQUQgECbBMrgX+xT3P9wPwSDAARaJFDGAMlz8Y+STpY8Jc1B0UjJ82r9Hf95UqfMAdJ0yQ4nbmO0cqQ0RdpOWk+y2SH5PaObJH+Fb0jCIACB8hAok395q7C4PQ9I9hsYBCDQ2wTK4F+SPxSb7L/0NmFaD4EOEShjgBSd+gIlrHZtDVXgT4XXMwdfDmyS5rx3SI9Jd0ujJH++0/Ul97EDekS6WHLg9KSEQQAC5SWQl3/xNOW0Of/Rmaf5Fm9zvt8/cnB0oIRBAAL9Q6Cb/sUzWuJWxlcp4u0jDYFSEihzgFQP2Lu1wZ0Lv9fTjP23Cnn6W5b509tJe7My3PGJz+f1sLXNAZEDJ3+O/ArpRMkvWWMQgEBvEwj1L1/S6X6xwSmnPcHdX/vYv/gDLltKyae+ysIgAIE+I9AJ/7JNnzHjdCDQFQK9GCBNEik/EWk2QDpBZX+cQfeH2jY7ZfsWynPQ45enH5Rukf4uecqdgyMMAhDoPwKh/sVTgX+VgeFUbfODlKRtrgz/MKxHnO1bMAhAoP8JdMK/fFMYT5KiB7o8fOn/+4ozLIBALwZIXwjksEzlhzL28XS4tPn/r1f++dLhEgYBCAwGgVD/Yv+RFeD4Iy9LU9BNU96F0jkp28iCAAT6k0An/Is/CuX3G/1zKHdKEyUMAhAIJFDWAMnv+vgjBztLfn/IU+DmSrOl86RnpSLNU/imSEcXeRDqhgAEukKg2/7FJz1V+nxXzp6DQgACRRIog3/xg+FvS58u8kSpGwL9TMBT1cpm49QgT0lxcOIPIvgDCQ6ONpSc5ylvW0tFmofB/aLj5UUehLohAIGOEyiDf9lRZ72JdFnHz54DQgACRRIog39ZSyf4Wgn/UuSVpu6+J1DGEaTjRH2mdGgd+mcp/wjpmDrb88j29Lo7pPvyqIw6IACB0hAoi3+5R0Tml4YKDYEABPIgUAb/spdOxA+/Z+VxQtQBgUElUNYRpHMzLoin2HlubZHmAImnL0USpm4IdIeAn/DiX7rDnqNCoN8JlMW/XCfQfj8SgwAEWiRQxgDpEp2L5+ZvnnJOo5V3vHR9yra8svzZ3b0lAqS8iFIPBMpDoNv+ZaRQ7CPhX8pzT9ASCORFoNv+xefBA968rib1DDSBMk6x+4GuyHhpnjQkPSS9IPkdpAnSBdKxUlHm0Sm/ZOlpfhgEINBfBLrtX3YVTv+2Gu839td9xdlAwAS67V/8g/avlv7TjcEgAIHWCZQxQHpKp3OUdLK0reSgyE9dF0m3Sg6cijQ/ffGHIB4p8iDUDQEIdIVAGfzLzTrzJV05ew4KAQgUSaDb/mWyTm6pdG2RJ0ndEBgEAmUMkCLuC5SwOm0OkJj+0mnqHA8CnSXQLf8yTaeJf+nsteZoEOg0gW75F/dfZklF/xRKp3lyPAh0nEAZ30HqOITYAddWejeJDkwMCkkIQCAXAp66u4eEf8kFJ5VAAAIJAg6Q8C8JKKxCoBUCBEi11Pxxhuelq2qzWYMABCDQNgE+v9s2QiqAAATqENhM+dtLBEh1AJENgRACBEi1tPz05Wrp6dps1iAAAQi0TcD+xe8G+D0FDAIQgECeBOxf/G6j33HEIACBNgkQINUCZHi6lgdrEIBAfgTwL/mxpCYIQKCWgP3LdMlf/cUgAIE2CRAgVQG+TMlJEsPTVSakIACBfAhsoGr8+V38Sz48qQUCEKglwAOYWh6sQaAtAgRIVXxTlXxCuqGaRQoCEIBALgQmq5Z/StflUhuVQAACEKgS8E+ijJV4AFNlQgoCbREgQKri89MX/zjs8moWKQhAAAK5ELB/uULi87u54KQSCEAgRsD+ZYF0dyyPJAQg0AYBAqQqPDsYnr5UeZCCAATyI8DvH+XHkpogAIFaAvRfanmwBoG2CRAgDSNcR4ttJAKktm8pKoAABBIE/Ptq20n4lwQYViEAgVwITFEt+JdcUFIJBIYJECANcxirxT+k24ZX+RcCEIBAbgTsXx6SbsmtRiqCAAQgMExgYy38kSkCJO4ICORIgABpGKY7MDiXHG8sqoIABF4kYP9yucTnd19EQgICEMiJgP3LHdL9OdVHNRCAgAgQIA3fBgRI/DlAAAJFEcC/FEWWeiEAgTFCcBkYIACBfAkQIA3z9DsCOJh87y1qgwAEhgn4HUf8C3cDBCBQBIEtVCn+pQiy1DnQBAiQRoxYRXfAo9K8gb4TOHkIQKAIAvYvj0tziqicOiEAgYEnMFIEZgw8BQBAIGcCq+VcXy9W5w7Mk9IRKY0/SHkPpOR3MmtNHWyU5I9IdNPchucld/a6aZvp4H7hvZu/J+N7xk/tFkrdtJfo4EulK1Ia4VELrPsEfK/4B6jxL9nXAv9S5YN/qbIglU0g6r8cnFLszcrzj1M/l7KtU1kO3jaV7uvUAescZ13lu7/7SJ3tnco2i4elZZ06YMpxyuJfXqq2+f/Gq1PaWIr+CwHSiBE36OL4E7z/kbhIq2t9a8k3cjdfrraDsbr5B6XDr3AuXnbT2fr4a1Ta4GCtW2YH43aU4d4wg539T8IWaf2eRB6rnSeAf2mOefR/Ef5leFYD/qW5+2bQS/1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       "</g>\n",
       "</svg>\n"
      ],
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/svg+xml": {
       "isolated": true
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "par(mfrow=c(1,3))\n",
    "qqplot(qunif(ppoints(500)), res[1,],cex=0.1,xlab=\"Uniform Distribution\",ylab=\"lm\")\n",
    "abline(0,1)\n",
    "qqplot(qunif(ppoints(500)), res[2,],cex=0.1,xlab=\"Uniform Distribution\",ylab=\"lme\")\n",
    "abline(0,1)\n",
    "plot(res[1,],res[2,],pch=19,cex=0.5,xlab=\"lm\",ylab=\"lme\")\n",
    "abline(0,1)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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      "text/latex": [
       "0.215"
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      "text/markdown": [
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       "[1] 0.215"
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     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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       "[1] 0.052"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      ],
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/svg+xml": {
       "isolated": true
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Increase Sample size\n",
    "B=1000\n",
    "res=replicate(B,sim.ranef(3,50,0.25,0.5,verbose=FALSE))\n",
    "mean(res[1,]<0.05)\n",
    "\n",
    "mean(res[2,]<0.05)\n",
    "\n",
    "\n",
    "par(mfrow=c(1,3))\n",
    "qqplot(qunif(ppoints(500)), res[1,],cex=0.1,xlab=\"Uniform Distribution\",ylab=\"lm\")\n",
    "abline(0,1)\n",
    "qqplot(qunif(ppoints(500)), res[2,],cex=0.1,xlab=\"Uniform Distribution\",ylab=\"lme\")\n",
    "abline(0,1)\n",
    "plot(res[1,],res[2,],pch=19,cex=0.5,xlab=\"lm\",ylab=\"lme\")\n",
    "abline(0,1)\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "0.049"
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      "text/markdown": [
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       "[1] 0.049"
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     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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      "text/markdown": [
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       "[1] 0.252"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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kYz9+8uXSJCABCUwk8G1OTPZ3yYA0kVR13ztgV9220TMJSKB7AmO/WZ814ZJGxaPMIWyyZW3R89CsLiuZO0jPQZd2md5kEpCABIZNILtuvgrtP+yCzH+oBBJbzkH3dVnK7aS7CC3VZXqTSUACEhgFgTwYNmv5/zCKwsoqo+kdpMMAuwL6Hlp9GshZg7Q2OhnNi45DmgQkIIEqEHgfTtyGfl4FZ/ShbwIO2PWNzgslIIGKEFgCPzZFDthVpEH6dSMdn73Q3SibL1yH8kCrE9HRnWNG9G5A+fwB9HY0ahu7XekUu1GTtzwJVJtABrH+gqZ6zkSjpjRUuykG9m5rckicOQF1M2CXHVYfRGuhUZrxaJS0LUsC9SLwGdy9DOX39UQzHk0kUoP3y+FjOkTXowSo8Urn6XK0L3oyKsMMSGVQt0wJVJ/Abrh4D1poClcNSFOAqeBpB+wq2Ci6JAEJdE1gLlLm8QRvnuIK49EUYOpyegEcTUfoaShz+6tgdpCq0Ar6IIHqEcgd7o9O45YBaRo4Ff3IAbuKNoxuSUAC0xLYnU+zNnK+KVIZj6YA4+n+CdhB6p+dV0qgqQReQcVyt/sZ01TQgDQNnBp85IBdDRpJFyUggX8TyKYxH5mGRaPi0f9MU9E2fpTpLLuiA9Egz0LKRg/paXe7e95TSKtJQAISGE9gT94cif40/qSvG0Ugz92LNAlIQAJVJvBKnHsm2rjKThbpmx2kR9PM7hzZijXHQSzrBfIlSm+6G1u8kyjtcX83F5hGAhJoNIHsqrk+ekeja2nlpiNQ1IBd4suXUa/xaDrf/EwCEmgPgZdQ1cPQqejatlTbDtKjWzp3jr6Pbnr06Z7f3cAV6/Rw1U6k/SqabFeQHrIxqQQk0BAC36QeD6FlGlIfq9E7gaIG7O6l6CtRtzMa5um4mvQO2HVgeJBAiwmcQN3nR/9sMQOrXhKBdJCy1mCqhW8luWWxEpBACQQySPMwyo/TZdF01qg539NVtIWfFdVB6hWd8ahXYqaXQLMJZKfnf6BFZ6hmo+KRd5BmaG0/loAEJDBCAtmQYZNOeT/geHXntYf2EchMhkFnM7SPmjWWgASKJJCBmiehHdGtRWZc9bz+X9Ud1D8JSEACLSKwaaeuF3HcvEX1tqoSkIAEJFA9AkfiUqbbPq96rg3XIztIw+Vr7hKQgAR6IZB1R1mLuFUvF5lWAhKQgAQkUDCBVcjvpShLQH5UcN6Vz84OUuWbSAclIIGWEFiWen4KZe3RX5AmAQlIQAISKIvAOyk4A3aZ6ntGWU6UVW7T1yBlsekCfcA9m2vyBHtNAhKQwKgIfI6C5kDXobtHVajljIyA8WhkqC1IAhIogMCy5JE7R5nR8CDSGkTgN9QltwZ71QdHzCCBMz66i92IwVucBCpCIHfz70MJQsv34FOjdg3qod51TGo8qmOr6bME2kkgz+LL79IVe6h+o+JR0+8gvYKGzZa5a6Lj0SGoG/PJ9d1QMo0EJFAEgUxhOBNlIWw2Z/gz0ppHwHjUvDa1RhJoKoE9qdhx6JKmVtB6zTbbXEA4F2V0NgvOqmjeQapiq+iTBEZD4FiKyXOPojf3WGSjRux6rHsdkxuP6thq+iyBdhF4ItXNWth90Gt6qLrxqAdYVUm6Eo6kg3RWVRya4IcdpAlAfCuBlhBYi3pmWl06R7nb3asZkHolVn5641H5baAHEpDA1AQ+z0cXozs6WnDqpI/6pFHxqC272P2RJnwfyoYNz35Uc/pGAhKQQDkEFqHYU1Cm2PVz96gcry11UALGo0EJer0EJDAsAvOQ8XZobFvvk3j992EVVuV829JBShtkh6jnoN/njSYBCUigZAIfoPyMuKVztB/KaJ3WDgLGo3a0s7WUQN0IZEZTBu3yTL5s0uBvZiBo5RFwil157C1ZAmUQWJpC70KZ+psg9AzUjzVqSkM/ALymcALGo8KRmqEEakMgd7g/hu5Et6P5UbfWqHjUpjtI3Taw6SQgAQkMm8DOFJBnHmUh7FHoT0iTgAQkIAEJlEXg1RT8dJSNGTLV7mqUgbxWmh2kVja7lZaABEomkAWwmeOdIHR4yb5YvAQkIAEJSCBbe38LPR5l86C3osxw0CRQGgGnNJSG3oIlMHIC2SEo645y9+jsAUufk+sTwNYcMB8vl8AYAePRGAmPEmgPgRWoamLJauhJaFnUqzUqHjX9QbG9Nq7pJSABCQyTwNxkvnOngASjbM6gSUACEpCABMok8B4K/xk6v0wnqlS2U+yq1Br6IgEJNJ1ANme4DOXh1f9EP0SaBCQgAQlIoCwCC1PwZmh/9HJ0LerlAbEkb555B6l5bWqNJCCBahLIgNS30fLoHvQJdC/SJCABCUhAAmUReDsF34LyzKMjUDpMT0etNjtIrW5+Ky8BCYyQwAcoK89iy/qjedFRSJOABCQgAQmURSD9gB3Rp1Cef/RKFDvgkUN7/7WD1N62t+YSkMDoCMyiqB1Qdga6EZ2IrkeaBCQgAQlIoCwC21LwQugIlPj0RpR4dTdqtdlBanXzW3kJSGCEBPI8iaw7ytSFw0ZYrkVJQAISkIAEJiOwKycPQnd0PjyeY2Y5tN7cpKH1XwEBSEACIyCwGGVkhC7PP8o8718hTQISkIAEJFAWgZdS8Gro4I4Dm3NMR2m7zvtWH7yD1Ormt/ISkMAICGRe9yloOZS/uRsjTQISkIAEJFAmgT0p/Hvo8o4TeXB5Hj+RNbKtNztIrf8KCEACEhgygdw9WgZlXvdt6GdIk4AEJCABCZRF4MkUnA0ZXjLOgUz9/j66c9y51r50il1rm96KS0ACIyKwF+Xcj7Kl9/+hh5AmAQlIQAISKIvAOyn4EvTLjgPP5pgBvAuQN0+EAAFNAhKQwPAIbELWO6G5UO4gfRdpEpCABCQggbIIzEfB2b1uj3EOZPe6x6EM4GVaeOvNO0it/woIQAISGBKB95HvcWgRNDf6HLodaRKQgAQkIIGyCOxCwQ+grD+KZfBuS/QPtDLKZ603O0it/woIQAISGAKBVcnzA518b+KYKQvf6rz3IAEJSEACEiiDQO4OpYO0P7qv40A6Rdmc4ffohs651h+cZ9j6r4AAJCCBIRB4F3kmEP0BXY9y5+hSpElAAhKQgATKIvBaCl4WHdJxIHePTkULoMNROkoaBOwg+TWQgAQkUCyBhchufZSNGfJciYzKubU3EDQJSEACEiiVQLb2PhT9teNF1hxdhh6PMg1c6xCwg+RXQQISkECxBFYiu8zlznbeb0N5KOzJSJOABCQgAQmUReBZFPwilLg0Zg/zYo2xNx7/S8A1SP9l4SsJSEACgxLIdIWj0RIoW6i+AWWutyYBCUhAAhIok8B7KDzT6X4zzomslz0erTLunC8hYAfJr4EEJCCB4gjkSeRzoNxBSmcpf2N/iDQJSEACEpBAWQQyhe51aOKA3as5lztIOWrjCDjFbhwMX0pAAhIYkMDdXJ/nS/wenY4+ie5BmgQkIAEJSKAsAll7dCM6ZYIDn+X9pciBvAlg7CBNAOJbCUhAAgMQ+BDXZgvV76MV0JFIk4AEJCABCZRFILMZ3ow+grLmaLxtx5sH0V3jT/raXez8DkhAAhIoksBVZJa7SGuhg9H1SJOABCQgAQmURWB7Cn4cmjhgtxPnDkB5HtKhKDuvah0CrkHyqyABCUigGALbkM1BaBbKbkGHIU0CEpCABCRQJoFdKfwr6B8TnNiE99nm+xvIztEEOE6xmwDEtxKQgAT6JJC1R3k47Hzox+g8pElAAhKQgATKIrA+BT8XbTbBgWwolC2/M+Mh65O0CQTsIE0A4lsJSEACfRD4BNesh7Ihw5xo4k5BnNIkIAEJSEACIyWQzs+x6MoJpSZWvRblDlLWIGkTCNhBmgDEtxKQgAR6JLAD6d/dueZijkuhn3bee5CABCQgAQmUQWBZCn05WneKwn8+xXlPQ8A1SH4NJCABCQxG4Jlc/gA6Bz0BfRhlVE6TgAQkIAEJlEXgXRT8K/SLSRzI9Lp0kF4wyWeegoAdJL8GEpCABPonkPVGG6HfosPRYug7SJOABCQgAQmURWB+Ct4a7TeFAxtzPoN7L5vi89afdopd678CApCABAYgsDLXZkpd5nC/ESUY3Y40CUhAAhKQQFkEdqPgrDM6bhIH5uLc5ihxa6oO1CSXteuUd5Da1d7WVgISKJbA58guD947C70Q5S6SJgEJSEACEiiLQH7b74w+jybbvjsdo1vQ1SjPQNImIeAdpEmgeEoCEpBAFwSeRJoV0BzoqegYdCnSJCABCUhAAmURyJbeiU/fnMKBrJFdB2WLb20KAt5BmgKMpyUgAQnMQGBhPj8fvQe9FHn3CAiaBCQgAQmUSiBbe38D3TyFFydz/la07RSfexoC3kHyayABCUigdwJ5IOzH0SpobvRr9GOkSUACEpCABMoikHWxa6BMsZvMtuFkNmbIzIfsvqpNQcAO0hRgPC0BCUhgCgIJLOkQPQdlisJKaHekSUACEpCABMok8F4KPwn9fhIn1uVcpt1l9tjXUKaFa1MQsIM0BRhPS0ACEpiCwAGcT+cod5GuRdnF7gSkSUACEpCABMoisAQFvwZlC+/JbENOZoOGG1Cm4WnTEEgvUpOABCQgge4JJLjcifboXPIpjtlOVZOABCQgAQmURWAvCs6g3U+mcOBjnM/jKJ6FjFlTQBo7bQdpjIRHCUhAAjMTeAlJ8nTyWzpakeORSJOABCQgAQmURSDPNnoT+jT61xROvJLz9yI7R1MAGn/aKXbjafhaAhKQwNQEshlDOkPzoOtRpih8FV2HNAlIQAISkEBZBN5MwekkHT2FAwty/iCUqeELoak6UXykhYAdJL8HEpCABLoj8HiSpXN0B8pUhgvR3kiTgAQkIAEJlElgVwrP+tipnm30dz77CLoL2TkCwkxmB2kmQn4uAQlI4BEC7+OQacnpFO2D8iyJc5EmAQlIQAISKIvAKyg4u6luMoMDn5/hcz8eR8AO0jgYvpSABCQwBYGncz4P1ZsTXY02Ra9FmgQkIAEJSKBMApnunal115TpRNPKtoPUtBa1PhKQQNEEctfoOyjT6/L8ozxkL9PsptopiI80CUhAAhKQwNAJLE8J66MXDb2klhVgB6llDW51JSCBngnkuRLPQHnqeO4ipWOUudwPIU0CEpCABCRQFoHsqvpLdHZZDjS13IyMahKQgAQkMDWB1/HRfehLaB20ODoWaRKQgAQkIIGyCGRnui3Rfl04kDW0V6C1u0hrEgh4B8mvgQQkIIHpCXyaj7Nj3YHoFLQ/uh1pEpCABCQggbII5GHleWj5D2dwYE0+/zDKTZHnojORJoFaENgJL7Pt4ny18FYnJdAOAgkm6RBlat0FKPO88/90RVQVy6YR8SkBUJNAEQSMR0VQNA8JDJfAHGR/NXrHDMXMy+dZM5sp4eehPAdpWNaoeOQdpGF9TcxXAhKoO4HDqEA6RbEElz3Rt9ElSJOABCQgAQmURWALCs5078Sp6exhPvwbyp2mjZHPQAJCN2YHqRtKppGABNpGIHdzV0P3oUyp+wL6C3L+NhA0CUhAAhIolcBulP41dOsMXmzF53nI+Tbo5hnS+vE4AnaQxsHwpQQkIIEOgSdwXAhdgd6LvoyuRD4YFgiaBCQgAQmURmAtSo527sKDlUiT6XgLd5HWJOMI2EEaB8OXEpCABDoE3srxn2h3NBfaHL0FaRKQgAQkIIEyCexF4Segi2dwYmk+3wEllh05Q1o/nkDADtIEIL6VgARaTyCbMOyC8vdxUZTOUl4fjzQJSEACEpBAWQSWpOBN0IZdOPBJ0syN/tBFWpNMIGAHaQIQ30pAAq0ncD0ETkZ/Qj9ACS6fQvcgTQISkIAEJFAWgb0pOFO/fz6DA4vw+UYomzJkwE/rkYAdpB6BmVwCEmg0gWyBeip6OjoEvR7ljtIRSJOABCQgAQmURSB3g7ZH+3ThwN9Jk4G+m9Afu0hvkgkE7CBNAOJbCUig1QSeTe3TIUogyijdV1F2CroOaRKQgAQkIIGyCOQZZRnEO7YLB7K997tQdl/V+iCQByFqEpCABCTwCIFbOPwI5c5RtvjOTkGHIk0CEpCABCRQJoFdKfxLKJsuzGRjmzhke2+tDwJ2kPqA5iUSkEAjCTyeWp2D8jC9edCH0SnoXKRJQAISkIAEyiLwKgrO1O/MaJjJlifB+mhedONMif18cgJOsZuci2clIIF2EViK6l6OMrXuXvRbNLYGiZeaBCQgAQlIoDQCe1LyESibCM1kGdx7AB2JfjpTYj+fnIAdpMm5eFYCEmgfgXSMMm97u47u5Hga0iQgAQlIQAJlEXgGBa+LVu/CgcyEyO51eTjsvl2kN8kUBOwgTQHG0xKQQKsIbE9t00F6KboI7Yc+gh5CmgQkIAEJSKAsAu+m4NPRr7pw4A7S/ARdhy7pIr1JpiBgB2kKMJ6WgARaRWBpajsnWhjlyeOLo252CiKZJgEJSEACEhgKgcSkzdGWXeb+IOk26zKtyaYh4CYN08DxIwlIoDUEdqem2eL7dLQ9+gK6DWkSkIAEJCCBsgi8lYJvRSd26cC8pHsRynbg2gAE7CANAM9LJSCBxhB4CjXJ1qnrobXQYUiTgAQkIAEJlEUgs7x2QllL1M107/lJl00cfoZ2RNoABJxiNwA8L5WABBpBYGtqcTC6GP0NZWqdc7eBoElAAhKQQGkEEpsyxe7wLj1YnXRzoQfQBV1eY7IpCNhBmgKMpyUggVYQyIjb51C2986Uug3Ri5EmAQlIQAISKJPAbhSewbtsvNCN5QHnd6GPogu7ucA0UxOwgzQ1Gz+RgASaTyDTEBZCN6Er0XLoHKRJQAISkIAEyiLwEgp+AdquBwduJe3x6Os9XGNSCVSaQOaY/gvNV2kvdU4CzSKQAaI/oTzvaGd0C+p2pyCSVsKy817+dqxZCW90ogkEjEdNaEXrUHcCx1GB7/VQiSeRNrMgMk28LGtUPPIOUllfI8uVgATKJvA6HHgiSlBZAOXvYYKSJgEJSEACEiiLQDo7r0Tr9uBABvnSQflSD9eYdBoC7mI3DRw/koAEGk1gF2qXuy+Z4/1G9Gl0D9IkIAEJSEACZRHYh4IvRWf24EDW02ZzhtN7uMak0xDwDtI0cPxIAhJoLIFnULOV0e3oWvRM9C2kSUACEpCABMoiMC8FZ93R23pwIDMhtkF3o5/3cJ1JpyFgB2kaOH4kAQk0lkC2T52FTkW5k5RFrdchTQISkIAEJFAWgcSjPPPouz04kA5S1h6d0MM1Jp2BgFPsZgDkxxKQQOMInESN/hfNg85HL0KHIk0CEpCABCRQFoHZKTgdpC+ge3tw4sukXQo5yNcDtJmS2kGaiZCfS0ACTSKQZx5tgLL26KcozzzKXaRzkCYBCUhAAhIoi8CmFLwc+kYPDryftM9HmRFxeA/XmXQGAk6xmwGQH0tAAo0hkJ3qtujU5giOb0U3oM065zxIQAISkIAEyiKwJwUfhm7s0oHsWpf1Sg+i3HX6B9Ik0CgCPneiUc1pZSpK4Iv4lV1+/tjxL08bTwepzgNFCZC5G+ZzkICgFULAeFQIRjORQE8EViJ1/pav2sNV3yZt1iuV+eyj8e42Kh45xW580/paAhJoKoHcPXoNug99GGWu97YonaSMvmkSkIAEJCCBsgi8m4J/gi7s0oGlSbdRJ+07urzGZD0QqPPIaQ/VNKkEJNByAukcLYiuQMeiHdATUEbgNAlIQAISkEBZBBal4Ez1zsPLu7VMw/seugxlyrhWMAHvIBUM1OwkIIHKEZgDj/6341Xmace2R3l9G9IkIAEJSEACZRF4OwX/FZ3cgwOZknczyoPOtSEQsIM0BKhmKQEJVIrA2njzeHQXyh2jl6EXoSyG1SQgAQlIQAJlEcjuczuiz6KHe3Bib9K+EfVy16mH7E3qFDu/AxKQQNMJvIUKZvHoe9DdKDsFfQddjDQJSEACEpBAWQSyC93jUK/T5D7KNZegY5A2BALeQRoCVLOUgAQqQ+B5eJKFrJlmdwZaAm2I9keaBCQgAQlIoEwCu1H4gejOHpxYiLQnojV6vK6HIkzqHSS/AxKQQFMJzEPFMqUud48yypbRti+hq9HZSJOABCQgAQmURSDTvVdBm/fowHyknx8t1uN1Ju+BgB2kHmCZVAISqBWBjLAth+5H/4fSUdoCZUGsJgEJSEACEiiTwF4U/l2U3VW7tUzHuwDl0RV5tp82JAJ2kIYE1mwlIIHSCdyKB9mYYQd0FcqzIrIg9jikSUACEpCABMoisCwFvxxlE6FebEkSz4vyLL/MitCGRMA1SEMCa7YSkECpBNai9Bejc1E2ZIi9CX0G/TNvNAlIQAISkEBJBPah3D+gc3osP5sN5YHnb0W/7fFak/dAwDtIPcAyqQQkUBsCG+NpRtnO7Hj8Wo7PRN/qvPcgAQlIQAISKINApsltg3bto/BTuWYFdFYf13pJDwS8g/TIuoSVYZZFb5oEJFB/AplG92qUtUcnd6qzJ8dvoL903nuQQBUJZJ2c8aiKLaNPEiiOQHauuxd9v48ss/nQe9GlfVzrJRJ4DIHsEHIAejdavvNpevDZ4SpbK/4LPYQORwuiUdtOFBgf7KSNmrzlNZHA56hUnnd0YadyT+WY/19rdt436ZAf1E2tW5PaaXxdjEfjafhaAu0ikLVDf0aZKtervYELMkW8qgN9xqNeW7TE9LlDdjzKD4gx3c7rpdHXOud+yvFg9KvO+zM55gs8SrODNEraltVkAutQudw5egBlU4ZYBj4yLaGJZkCqT6saj+rTVnoqgWER2IyMc/do8T4KOIZrsvFQfrNW0YxHVWyVKXzahfPpGJ2GXoV2R1eiy9HD6PVovP0vb5J+y/EnR/DaDtIIIFtEKwj8mlqmc3QGyg/SbIWagLIRaqIZkOrTqsaj+rSVnkpgWAR+ScYH9pn5Blz3fjRvn9cP+zLj0bAJF5j/SeSVrX7nHpfnJrxOJyjPSJlo+UF1LfryxA+G/N4O0pABm30rCLyZWmZk7g60ZKfGH+F4A2rqhjQGpE5D1+BgPKpBI+miBIZIIOsL8/vzOX2U8QyuuRn9vo9rR3VJo+JROgRNtmWo3M9QfjSNWabU5e7RxWMnxh1z/iq09LhzvpSABKpPYGFc3BelI5RpCDeiTJXdDn0MPYg0CZRJwHhUJn3LlkD5BLIO/mR0UR+uvI9rMiPiyj6u9ZI+CDS9g3QtTF6Gxt9BegXvU+9noomWH1eroqsnfuB7CUig0gS+j3fZYOWvKDvWxfLcoyegdJg0CZRNwHhUdgtYvgTKI5A1R69F+/XhwuO5Jr9d/4ne28f1XtIHgaZ3kLJBQ0aWM7XhNShfrP3Rb1G+bFuhMQuLr6Hsbnc60iQggfoQSMfoTpRnS4zdMU4H6YvoNqRJoGwCxqOyW8DyJVAegQzcZfe50/pwIVPXsvnQRWiy2U99ZOklbSeQTs9xKHM+x/Q3Xi+Bvto5dx7H76HrO+9P5Thqcw3SqIlbXpMIZGQuPz4znW7M1uVF/s9Pdqd4LE0Tjo2a892EBpmmDsajaeD4kQQaTCB/p29CO/dZx1x3Ccoapiqb8ajKrTOFb7l79Fm0G1qqk2YhjoeiLHrLD6ncusxo8zxo1GYHadTELa9JBF5OZRJ8cqd4zE7gxXfG3jT4aECqX+Maj+rXZnosgUEIZAfLO1BmKPVjX+eixLhX93PxCK8xHo0Q9iiKyqjeU9AcoyhsijLsIE0BxtMS6IJAgkbuAi/bSZs7xJmOsFbnfZMPBqRmta7xqFntaW0kEAK/RR8fAMXcXPvsAa4f1aXGo1GRblE5dpBa1NhWtXACF5Jjps6OdYhyJ/iywkupZoYGpGq2S529Mh7VufX0vWoENsSh7KK6TNUcG4I/jYpHTX02SL/tnil4u6ID0UH9ZsJ16e3viPJl6cZW7yaRaSQggUkJ7MzZVdHZKP/n8qDnPZEmAQlIQAISKJPAXhT+bXRNmU5Ydu8E7CA9mlmm5jwH5TiILcrF2U1rVpeZJL0mAQn0TuBpXPJRlDnaWUu4B8r/ux8gTQJ1JlDUgF2mkJ+Puh2w83dBnb81+l4lAk/FmQ3Q2gM4tSLXpoN1HPrAAPl4aY8E/EP4aGC5c5Tnqdz06NM9v7ueK9bo4aqdSJtd9TQJSKA3AtmYYTmUxa9Zh/Qm9FmUTVc0CdSZQFEDdhm57mXALj/o3lJncPougYoQeCd+nI1+OYA/X+DaldDCyA7SACC9tJ4E0kHK6Pd89XRfryVQCoF1KPUf6O8od35fgx5CT0ZtsdwVyN+ONdtS4RbVs6gOUq/IjEe9EjO9BB5LYAFOJT69/rEfdX3miaTM+toM2j+366vKS9ioeOQdpPK+SJYsAQkMRiDrjrL4NXeMLkJfQoegPIxPk0DdCeRH0aCzGerOQP8lUFcCe+D4nej4ASqQAb88+PxClJ3wtBESaGMHKbcpF0RzobvQHehupElAAvUhMAtX90QJID9Bmev9YvRepEmgLgSMR3VpKf2UQPcEsl3/zmg/9ED3lz0m5a2cWRu5wcNj0HiiKAKrkFEWcedWZaajTNQVnDsYLYbKMKc0lEHdMutM4DU4fwv6TacSh3E8rfO6TYdGTWloScMZj1rS0FaztQSyk+o9aNANuPK79Ga0AaqDGY/q0ErjfMyitrEOUXrhZ6MfoWPQj9F56EaUNPnBtRUatdlBGjVxy6s7gW9Sgb+jzdH8KHeDX4naZgakerW48ahe7aW3EuiHwJlclCnfg9o+ZHAtWnnQjEZ0vfFoRKCLKGYzMknHJx2hrFeYymbng0zPOR8l/QvRKM0O0ihpW1YTCORuUQY2noY+jG5AbZwybECi4WtixqOaNJRuSmAAAvn9mN+Rzxwgj1ya36XZTXIdVBczHtWlpfDzSJTpc1lv1I0tTKIsqhvkIbHdlDMxjR2kiUR8L4HpCeT/9OIoQeQqlAWxbTQDUn1a3XhUn7bSUwn0S+BYLvxhvxePu259XmeN/GXjzlX9ZaPiUdNHXLP17znovi6/VbeTLrthLdVlepNJQAKjJ5CRuRPQgeg2tCTKlFlNAlUmYDyqcuvomwQGJ5BYtCl6+eBZzbY3eeQ3+g8KyMss+iCQnTaabJmC8zw0q8tK5g5SgtilXaY3mQQkMFoCCUA/R09BL0JvQpnrnd1+NAlUmYDxqMqto28SGJzAXmRxJUqMGsTSOVoX3Y/2HyQjr5XAVAS25oPMBc1o8+pTJeJ8pulkK8Vs2JDnqqyFRmlOsRslbcuqK4EMdNyAHkZ5NsQWKP+/V0JttUZNaWh4IxqPGt7AVq/VBOam9jejNw9IYVWu/yd6CB0/YF6jvrxR8ajpU+yO4tuRdQofQ69C16PrUEab70QLoEXQMigj0+kcpef+S6RJQALVIrAL7uQu731offRO9D30R6RJoOoEjEdVbyH9k0D/BHbg0jnQoNO9P0Me6WhcizJdT5PAUAksR+5Ho3SQMuI8Xnfz/nK0L3oyKsN2otD4NF8ZhVumBGpCIB2hjKzl/8sSKNMPMs2uzdaoEbuWNKTxqCUNbTVbReAP1PbDBdR4c/L4Llq6gLxGnYXxaNTECy4vd43SEXoaWrDgvPvNzg5Sv+S8rk0E9qSy2SFoXvQFVKfdfXB3KGZAGgrWkWVqPBoZaguSwNAIvJKcH0BPGrCEp3L9DegnA+ZT1uWNikdNn2I32ZckU+siTQISqA+B5+LqxuiLKFNht0TvQJoE6kzAeFTn1tN3CTxCIJszHIWyhGMQm6tz8dWDZOK1xRBoYwepGHLmIgEJjIrAihT0S5RFsOkcZYpSRqq+jzQJSEACEpBAWQSeTsHrojULcCAzI/K7/PgC8jKLAQnYQRoQoJdLQAJDJZApSGejdI7uQnmyeDpGWTOY9UiaBCQgAQlIoCwC76LgM1B2QR7Eshvraijr0X8zSEZeWwwBO0jFcDQXCUhgOAReTbazUDZTWQM9CyWQHI40CUhAAhKQQFkEFqbgTPfOFv6D2k1k8Cd0Crpu0My8fnACdpAGZ2gOEpDA8AjkKeLLokw5uAQdiL6JrkWaBCQgAQlIoCwCmdGQx8b8qAAHPkUe2aQhHSStAgT+XwV80AUJSEACUxHYkQ+y42RG1pZDL0GHIE0CEpCABCRQFoHcYMgOxJ9HWRs7iGUq+YtRZku4idggJAu81jtIBcI0KwlIoHACu5JjpjE8Bb0H/RRlTZImAQlIQAISKIvAlhS8KDqsAAc+Sh6JcRej3xeQn1kUQMAOUgEQzUICEhgKgYymZTrdX9D16HUoQUmTgAQkIAEJlElgdwr/Krq9ACcWI49sQpSOklYRAnaQKtIQuiEBCTyGwBc4sx06CWUr1QSQk5EmAQlIQAISKItApsOtjrYvwIH5yCNT9D6BvltAfmZREAHXIBUE0mwkIIHCCWxEjnOgLFp9I/o4GnSuN1loEpCABCQggb4J7MmV2Tgoa2MHtdyJ2gxtNWhGXl8sAe8gFcvT3CQggeIIJGA8FaWTtCQ6GmkSkIAEJCCBsgg8iYJfhV5WkAPrks+96KCC8jObggjYQSoIpNlIQAKFE8hmDNEZ6ACU7VQ1CUhAAhKQQFkE3kHBuXOUuFSE7UYma6Bji8jMPIoj4BS74liakwQkUByBuchqR/QGtDbKZg2aBCQgAQlIoCwC81Lw9ugzBTmwNPlkZ9asZ3q4oDzNpiAC3kEqCKTZSEAChRGYm5zORM9Gt6Dvoz8iTQISkIAEJFAWgZ0o+CFU1N2ePPh8WbQm0ipGwDtIFWsQ3ZGABGbbAgbPRVl7tATaH2kSkIAEJCCBsgjMTsF5Lt8XUdYMFWF/IJPrUGZLaBUj4B2kijWI7kig5QQShLJD0H3otygdpNxN0iQgAQlIQAJlEdiEgp+Kvl6QA88kn+zOegFKR0mrGAHvIFWsQXRHAi0m8DTq/nf0nA6DZ3D8SOe1BwlIQAISkEBZBPai4G+hGwty4E7y+Se6sqD8zEYCjSSQea3/QnlgmCaBthI4lIrnOUfRt1E6S/6fAMI0Nief5W+Hc9ingeRHPREwHvWEy8QtIJC7Pfk7+7wC65qNiJ5SYH5VyKpR8cg7SFX4SumDBCQQAi9Fd6H82F8B7YvuRpoEJCABCUigLALvouDsNpfpcEXZEWR0LnphURmaT7EEXINULE9zk4AE+iMwP5f9EGW3uieiZ6FXIU0CEpCABCRQFoFFKTiPm4iKtIvIbGV0U5GZmldxBOwgFcfSnCQggf4JbM2lm6EFUZ5Ufii6FmkSkIAEJCCBsgi8jYLTiflxwQ58lPwiraIEnGJX0YbRLQm0jMD21DfPPzoJrYMOQZoEJCABCUigLAKzKHhH9DmU5x8VZfnt/Ra0WlEZmk/xBLyDVDxTc5SABHonkB19bkUbo5+hXyJNAhKQgAQkUBaBbSh4AZTd64q0F5HZ/6HMkrCTVCTZAvOyg1QgTLOSgAT6JrABVyYQXY+26jsXL5SABCQgAQkUQ2B3sjkIZUfVIu08MjsU/aLITM2rWAJ2kIrlaW4SkEDvBDLdYH30EpRd7Iqe602WmgQkIAEJSKBrAuuSclW0RddXdJ8wD0J/d/fJTVkGATtIZVC3TAlIYDyBbOe9Y+fE+znmOUiaBCQgAQlIoCwCe1Lw99EVZTlgueUSsINULn9Ll0DbCWQXnwSiPIQvi2CPQpoEJCABCUigLALLUPBG6MVlOWC55RPI1BZNAhKQQFkE9qDgdI6yScOXUDZq0CQgAQlIQAJlEdibgv+Azh6SA5uT79FokSHlb7YFELCDVABEs5CABPoisARXZZHqMWgh9E2kSUACEpCABMoi8DgK3g59ZkgOLEu+h6JN0PORVlECTrGraMPolgRaQGB/6pjNGW5BP0AZsdMkIAEJSEACZRHYhYKzicL3huTAfOSbzYiytum0IZVhtgUQsINUAESzkIAEeiawIle8pnPVUhwzYqdJQAISkIAEyiIwOwXvijJ4l07SMOyPZLoCytbhmV6uVZSAU+wq2jC6JYGGE9iM+t2PbkRXozOQJgEJSEACEiiLwGsp+MnoG0N0YGvyzrOVFhxiGWZdAAE7SAVANAsJSKBnAjtzxcNofpSd7DQJSEACEpBAmQT2ovDD0N+G5MS85PtJtB5aZUhlmG1BBOwgFQTSbCQggZ4IHELqP6FZaFhzvXtyyMQSkIAEJNBaAs+h5muhrwyRwOrkPQ/6K/rpEMsx6wIIuAapAIhmIQEJ9EQgO9bdixZAn0N3I00CEpCABCRQFoF3UfAp6HdDdCBTyT+EcnT9ERCqbHaQqtw6+iaBZhI4i2plkWruYGc6gyYBCUhAAhIoi8DiFPx6tOkQHViYvH+Dclx7iOWYdUEE7CAVBNJsJCCBrgjsRqp0jmInoWv+/cp/JCABCUhAAuUQeDvFXodOHWLxXyPvbADxEBrWDnlDdL99WbsGqX1tbo0lUBaBz1Lwl1H+7syBslhVk4AEJCABCZRFYE4K3gHti7Jx0LDsQTL+B3oVyvpbreIEvINU8QbSPQk0hEC29d67U5fbOWae9y877z1IQAISkIAEyiDwRgrNxglHDLnwbO+ddbeJf1oNCHgHqQaNpIsSaACB7A70APohyohdHsSnSUACEpCABMoksDuFZ+e6u4bsRKbW2TkaMuQis7eDVCRN85KABKYisB0f/BNdghKIfow0CUhAAhKQQFkENqDgbO99cFkOWG51CTjFrrpto2cSaAqBFanIZehklI5S1h7lbpImAQlIQAISKIvAnhR8LLq6LAcst7oEvINU3bbRMwk0hcAHqchKaA30RHQU0iQgAQlIQAJlEViOgjdE2Tho2LYEBfwcvW3YBZl/cQTsIBXH0pwkIIHHEjiEU29AuVudB8RmrvctSJOABCQgAQmURWAfCj4PnTVkB+Yn/2+hrMN93ZDLMnsJNI7ATtQoT1Wer3E1s0JtJpCAkK1Ns3XqL1C+489CWnEEsuFFuK5ZXJbm1HICxqOWfwFaUP3sJncnyuDdsO3XFJAYmGnlWfPUZGtUPHINUpO/qtZNAuUSWIXiE4RO77hxHMc/dF57kIAEJCABCZRBIA8sz2ZBPxhy4YmBWYObgcJsBDHMB9GSvVYkATtIRdI0LwlIYDyBzO3+FboOXYWaPnpGFTUJSEACEqgwgSwt2QXth4a9WVB2bs3DYY9GeyGtRgTsINWosXRVAjUjkKlf6SB9Hl2LzkCaBCQgAQlIoCwCeWj5kuibI3DgM5QxOzpgBGVZRMEE7CAVDNTsJCCB/xA4jFeLoBegd6F0mDQJSEACEpBAWQT2oOBsHjTszYLWoYzMmkgHaRbSakbADlLNGkx3JVATApnG8Ao0V8ff79bEb92UgAQkIIFmEsijJtZGWYM0bMuz/7JBw/fRpcMuzPyLJ2AHqXim5igBCcw221uAkJGz+1GmF9yNNAlIQAISkEBZBPJg2BPRH0fgwKqUcS46cARlWcQQCNhBGgJUs5RAywnk78p2aF40NzoUaRKQgAQkIIGyCDyBgl+DXjkiBz5IOUujHyLX344IepHF2EEqkqZ5SUACLwPBsWhh9BA6Cl2DNAlIQAISkEBZBLKL3NXopyNwIFPLs0HRz9BZIyjPIoZAIOsENAlIQAJFEHgPmZyG0jl6GM2B8uwHTQISkIAEJFAWgcxkeDP6LBrFZkHrU87r0WoosVCrIQHvINWw0XRZAhUkkL8l7+/4dQPHC1CeVu7oWQeKBwlIQAISKIXAmyg1A3aZ0TAKy12qg5APhh0F7SGVYQdpSGDNVgItI7Ay9c22qT9B26Hr0bZIk4AEJCABCZRJYHcK/zLKg1tHYfdQSNYgaTUm4BS7GjeerkugQgQSfJZAf0DZKehudBLSJCABCUhAAmUR2IiCV0BfHaED81HWciMsz6KGQMA7SEOAapYSaBmBp1HfZ6MH0X4oz374FHoAaRKQgAQkIIGyCGTA7hj0lxE5kM5RBgozxXwd9Huk1ZCAHaQaNpouS6BCBPI35FyUXXsOR9lC9YnoSKRJQAISkIAEyiLwdApeD71whA5kJ9fFUDaDuHmE5VpUwQScYlcwULOTQMsIZCvvq1ECwcfRDigPxst6JE0CEpCABCRQFoF9KPgslEG8UdkpFPRh9BL011EVajkSaCqBnahYRhtya1aTQN0IZIpdbG2U73Gm22mjITAnxYT5mqMpzlJaQMB41IJGbkEVF6KOd6HXtqCuValio+KRU+yq8rXSDwnUk0DWG62E3odehI5HzrkGgiYBCUhAAqUR2IOSb0cnlOaBBdeagFPsat18Oi+BUglk3VHmeM9CCUQbo/2RJgEJSEACEiiLQJ55tDP6PMrmQaO0rEH6X+QNiFFSH0JZNuAQoJqlBFpCILsD3Y++gjKt7i/oF0iTgAQkIAEJlEVgCwp+PDq0BAf2pcyl0Oko65+0mhKwg1TThtNtCVSAwO/wIZsxpFN0KHo3ynoYTQISkIAEJFAWgUyv+zrKzIZR27socFV0zqgLtrxiCTjFrlie5iaBthDI4MrnUJ51tDyaG30XaRKQgAQkIIGyCGQt7Boou6mO2tIxOhotjbLDq1ZjAt5BqnHj6boESiaQAZbZUbb2zgNis2OQJgEJSEACEiiLQKZ+Z2OGS0tw4OFOmWPHElywyKII2EEqiqT5SKBdBJ5FdS9CZ6IvoFcjTQISkIAEJFAWgaz9SSxavyQHtqbcG9HHSirfYgskYAepQJhmJYGWEMjfjVPRwuj56FvoGqRJQAISkIAEyiLwDgq+DJ1ekgMvptzF0KLoppJ8sNiCCNhBKgik2UigRQTyxz+bMdyGnoK2R5oEJCABCUigLALzUPD2aO+SHHgZ5S6Lfo0uRlrNCdhBqnkD6r4ESiCQh8HOhzJSdwk6E2kSkIAEJCCBsgjsSMEZuPt2SQ5cSbnXo1NKKt9iCyZgB6lgoGYngYYTyChZduqJ5SGx2/z7lf9IQAISkIAEyiGQzYJ2R19C95TjwmxXUe5YbCzJBYstkoDbfBdJ07wk0HwCL6WK2a3uws7xxOZX2RpKQAISkECFCbwK356KvlZhH3WtZgTsINWswXRXAiUTuIbyv4GyEPVTKM9B0iQgAQlIQAJlEcjW3keiG8pygHLfi36CFirRB4sukIBT7AqEaVYSaDiBx1G/PBx2FsqUhgQkTQISkIAEJFAWgRUpODMbVivLgU652V78KWhpdEfnnIcaE7CDVOPG03UJjJhAptbtgzJal22+b0aaBCQgAQlIoCwC76Tgn6PsHlempYOUzlGeD6g1gIAdpAY0olWQwIgIfIZy3oKynermIyrTYiQgAQlIQAKTEViEk1t0NNnnozx3E4VFWkMIuAapIQ1pNSQwZALzk/8eaG70G/R7pElAAhKQgATKIvBWCv4bcrOgslqgweXaQWpw41o1CRRIYF7y+hV6GJX1IL4Cq2NWEpCABCRQYwJZC7sTyrrYh2pcD12vKAE7SBVtGN2SQMUIvAt/XoCy+PR0pElAAhKQgATKIrAVBS+IDi/LActtNgE7SM1uX2sngaIIXEBG+XuRdUh5WrkmAQlIQAISKItApnx/Ff29LAfGlZu7WbugPDxdk4AECiSQ28T50TlfgXmalQSKIvBBMsrUuihbfWvVITAnruRvx5rVcUlPak7AeFTzBmyB++tQx8Sj5StS19fgRzZoOKki/pTlRqPikXeQyvoaWa4E6kEgmzOMrTn6M6+z1bcmAQlIQAISKItAHjXxfZSYVAV7Ek7cjr5SBWf0oRgCbvNdDEdzkUBTCeSOUXYJynGDplbSeklAAhKQQC0ILI2XG6N1KuTtDviyMLqxQj7pyoAE7CANCNDLJdBgAktQt8tRnnt0IboaaRKQgAQkIIGyCGRGwx/RWWU5MKHc5/D+PnQ4ylpdrSEE7CA1pCGthgSGQOAD5DkXmh19fgj5m6UEJCABCUigWwJZp70demu3Fww5XdbcnIYej5x+PmTYo87eNUijJm55EqgHgUynezPKBgAZFTsKaRKQgAQkIIGyCOxMwfej75TlwIRy9+X9Qiido10nfObbmhNoewdpDtpveZQvuCYBCfyXwOa8zB3m/B/5xH9P+0oCEhgSAePRkMCabSMIZCbDbuiLKFPaqmDr48SDaB+U6eiaBGpFYHG8PQh9c5zXebjYgehelBHyPIX5IjS2WxcvR2puqzpS3BY2A4FMF8jGDHeiv6JZSKsmgTlxy22+q9k2k3llPJqMiuckMDOB15IkHaOsja2KrYojW1fFmQr4YTyqQCN060J+6F2H8gPiF52L8mMvU4Yonst9AABAAElEQVTGOkY/53Vu117TOZeO06jvrNlBArpWGQKZNpBpDBlA2KsyXunIZAQMSJNRqeY541E120Wv6kHgDNz8WoVczc6uH0XPr5BPZbtiPCq7BXooPwvL0xF6D8pi81h+8OVcnsD8BDRmadgvoHy2/tjJER3tII0ItMXMSCADCNmx7h8oo3WLIa26BAxI1W2biZ4ZjyYS8b0EuiPwbJLlt9lzu0s+klRbUEoeDnvCSEqrRyHGo3q007+9PId/r0Tj7wh9n/d5oFd+CE60pLsWfXriB0N+bwdpyIDNvmsCi5DyRnQPyoCBVm0CBqRqt89474xH42n4WgLdEzicpKd2n3wkKVeglNzRWmUkpdWjkEbFo/Edh3rg783LLDL/DXp43GVZb5RO0APjzo29TLob0NPGTniUQMsI3EZ934bmRt9oWd2trgSGScB4NEy65t1UApnF8Aa0f8Uq+G382QRVZcOIiuGpvztN7yBlrdH6aNFxTXUGr5+OJps6lCl3mU/6O6RJoI0ENqDSB6DT0UVIk4AEiiFgPCqGo7m0i0AG7K5HJ1es2qfhz3ko69c1CdSOQDo76d3/Ba3d8X5ejmehn6Mnds7lkLmtl6F7Uea7jtKcYjdK2pY1HYEf82HupDq9bjpK1flsTlzJ3Pw1q+OSnkxBwHg0BRhPS2AKAvn7linfu03xeVmnX0HB2en10LIcqGi5xqOKNsxUbr2JD7KeIj/6cmfoEJR5o3l/P7oY3YTyIyPn0lkZtdlBGjVxy5uMwPaczDMdMg0104G06hMwIFW/jcZ7aDwaT8PXEpiewA58/Hc0//TJRv7pipR4KXrryEuudoHGo2q3z6TeLcHZT6KsPcoPwHSGxusu3h+NnoXKMDtIZVC3zPEE1uJNBgwySPDr8R/4utIEDEiVbp5JnTMeTYrFkxJ4DIELOfPpx5z1RFUJGI+q2jJd+pWnlS+FXoDSIVoIlW12kMpugXaXP4vqX4Vy5ygav2aPt1qFCRiQKtw4XbhmPOoCkklaSWA9ap149JQK1n5rfPo8SuzU/kvAePRfFr4qiIAdpIJAmk1fBLbjqtw9yt1VR+v6QljaRQak0tA3tmDjUWObtlYV+xHeHlNRjzO9LksznlNR/8pyq1HxyHUGj/4a7cbbXdGB6KBHf9TTu7lInR+d3Y4uvLCn3E0sgWIJvJ7sHkDZ2jvffU0CEmgWgWw81G08enKzqm5takhgOXx+BcrU7yratjj1DOROr1VsnYJ8soP0aJCZG54RgRwHscW5eHeU3nQ3VoVpft34aZrmEUjnaAOULf+PRFcjTQISKJ9AUQN2y1OV36L8H9ckUAcCe+NkvrPnVtDZ1fDpZPSlCvqmSxIYGoGiOki9OuiUhl6Jmb4IAvORyRUoW+Fnc4YXI61eBBo1paFe6Ifu7YcoIZsJfbCAkuYhj+wE1o2yM1fKzd8HTQKjJpDv6J1oi1EX3GV5LyHdrWj/LtO3KZnxqE2tPaK62kEaEWiL+Q+BjCZni/ssgs36ozORVj8CBqT6tVm3Hjtg1y0p0zWJwDupzI0of9uqapn1M3tVnSvRr0bFI2+5l/hNsmgJlEggUxdWQBkpzvqj/ZAmAQlUh8BNuJI1DjlqEmgDgfwm3RXl7kwG7qpo78apb6DcldUaTKCNa5AWpj0XRNlIIc8/ugPdjTQJtIXAV6jo81A6Ryei1VF2DNIkIIHREjAejZa3pVWbQNbEPhGlA1JV2xbHFkNLo+xmpzWUQFvuIK1C+30d/Q3dhq5C+WJfh9JJugIdjPKl1yTQZAL5P59F2xmdy0jYSugznfccNAlIYMgEjEdDBmz2tSWwJ54fim6paA3y7Mx5UTY0snNU0UbSre4JfICkGSmPrkFno4yWH4N+jM5Dme+az/Ofcis0anMN0qiJt7e8dI5uRn9B+a5ngwYHBoBQU2vUnO+atkEvbhuPeqFl2jYRyMBBfoelE1JVeyWOZaA9A+7aYwkYjx7LpLJnNsOz/IdLR2jVabzMYrvs4HU+SvoXolGaHaRR0m53Wblb9Dv0WvQz9EWk1ZeAAak+bWc8qk9b6enoCRxFkSeNvtieS8za3fzd1R5LwHj0WCaVPZPboJk+l/VG3djCJLoTHdRN4gLT2EEqEKZZTUngnXzyEHoQfRxlMMAngQOhxmZAqk/jGY/q01Z6OloCT6C4zGbYYLTF9lzaclyxds9XteeCRsWjpm/SkB9/56D8x+vGbifRRWipbhKbRgI1IrAEvn4QPYx+gZ6BMtU033dNAhIYPgHj0fAZW0I9Cbwdt69Gp1Xc/cTMRVE6SZdV3FfdG5BA0zdpuBE+2a1rVpeccgcpQczFd10CM1ktCGQKadY+5P97ptdtiTZG2UpVk4AERkPAeDQazpZSLwJz4e4OaF+UWQ1Vtu/gXJ4ZmDW8mgRqTWBrvM9/uBPQ6tPUJD8gMyKQDRsy/WgtNEpzit0oabevrG9S5dw5ynd7G5R1SFegfO+1ehNo1JSGejfFjN4bj2ZEZIIWEtiFOmf2znwVr/t78O9u9PmK+1mme42KR02fYncU35TF0cfQq9D16Dp0K8paowXQImgZtCTKD8i90S+RJoEmEJifSrwEPYQyUPBdlJG696MMHmgSkMBoCBiPRsPZUupFYA/czbP50vmoqj0Dxz6M8pt5jqo6qV8S6IdAFtYdjdJByo/C8cp/ystRfjQ+GZVh3kEqg3o7yswU09tQptbFdkMZHHhc3mi1J9CoEbvat0Z3FTAedcfJVM0n8HKqmIHppSte1c3wL3e5stOxMy+mbizj0dRsavFJ7hqlI/Q0tGBFPLaDVJGGaKAbGbW+BeU7FrsQffTfr/ynCQQMSPVuReNRvdtP7wcjcDKXHzFYFkO/Ojvs/QH9GWWzI21qAo2KR7ld2DbL6HmkSaANBI6lkvkRdip6BVoZvQ5pEpBA+QSMR+W3gR6UQyCD1BugUa/57rW2ucuVKXYPoLl7vdj09SXQxg5SfVtLzyXQO4G7uOQd6Br0VZQ7SlchTQISkIAEJFAWgX0o+Gx0TlkOdFnuMaRbBF2AEke1lhCwg9SShraarSSwArVOh+g2lFGw9dBLkSYBCUhAAhIoi8BCFLw12r4sB3oo922kfTY6oIdrTNoAAnaQGtCIVkECkxDIM4++jhKI8uyG96KM1p2BNAlIQAISkEBZBLJZ0B3ouLIc6KHcnUk7tlYwj8fQWkLADlJLGtpqto5ARryy3igdpaxDOgG9GWkSkIAEJCCBsghkm+xd0X4oO9hV2ZbCuZ+js5Cdoyq31BB8s4M0BKhmKYEKEFgOHzJf+pPohege9EOkSUACEpCABMoisDkFPx59sywHuiw3Pl6M8kiMvD4MaS0iYAepRY1tVVtDYDFqejjK/+/70Q7os53XHDQJSEACEpBAKQTyYNhDUNbGVtk2xblZ6D6U+Km1jECm32gSkECzCGS90TzoepQ/8Hnu17eQJgEJSEACEiiLQGYzrIm+XJYDPZSb5weegp6Lsn5XaxkB7yC1rMGtbuMJLEkNd0IPoSyETWcp23v/DWkSkIAEJCCBsgjsScE/QpeW5UAP5R5M2txEeLiHa0zaIAJ2kBrUmFZFAhDYC+X/9XnoLpRtvXNOk4AEJCABCZRFIBseZNpaHjlRddsSB+dClyA3Z6h6aw3JPztIQwJrthIogcD7KHNvlBGvA1BG605Ev0OaBCQgAQlIoCwCiUd/Rj8ry4Eeys36qJtQ4ui/erjOpA0iYAepQY1pVVpP4PkQyKYMmS/9C5SNGjZGmgQkIAEJSKAsAlkT+2a0T1kO9Fhu1kjNjxJHtZYScJOGlja81W4cgexc90z0Y/Qy9A6UTRp+ijQJSEACEpBAWQTSOcqdmGPKcqCHcrOp0b3oMnRzD9eZtGEE7CA1rEGtTmsJvJ+aPxU9CWXnujeiPAPJ6QFA0CQgAQlIoDQC2do7d2XyPL6qW2LpMijTAe+rurP6J4GmE8iuY/khO1/TK2r9hkLgeeSaEa9oQ5SnlN+JMkVAazaBOale/nas2exqWrsREjAejRB2C4rKNO9M/c4mDVW3F+HggygdudWr7mwF/WtUPHINUgW/YbokgR4IzE7aQ1HuGv0KnYIuRF9E/0CaBCQgAQlIoCwC2ZzhKHR9WQ70UO7ipP0nOgdlJ1itxQTsILW48a16Iwi8gFpkzvRd6HUoW6iu3HnNQZOABCQgAQmUQmBFSs2a2MSpOtjCOHkI8tEYdWitIfvoGqQhAzZ7CQyZwDPI/1aU3YFuQBmtOxpdhTQJSEACEpBAWQQSl7IT3PllOdBjuR8l/TYog45aywl4B6nlXwCrX3sCm1GDx6F0jpZF66N1kSYBCUhAAhIoi8AiFLwF2rosB/ood2euydrda/u41ksaRsA7SA1rUKvTKgJLUtuVUNYenYTegzJ32mc3AEGTgAQkIIHSCGTnulvQD0vzoLeCM7XuOyizMjQJzNbPHaTM0VwQzYWy7uEOdDfSJCCB0RJYleIWRfm/OB/aEu2ANAlIQAISkEBZBPLbchf0WfRQWU70UG42Ndq+kz67gmoS6JrAKqT8Ovobypdnoq7g3MEoD6vUeiewE5eEaX7kahLolsCpJLwZvRbl7tFNaE6ktYdA2jt/O9ZsT5Wt6ZAJGI+GDLgF2W9HHTOAvlAN6roCPmYb8nTkjqqBv1V2sXXx6AO0xliH6Bpen41+hPJE5B+jbIV4I0qa3E7dCmm9ETAg9cbL1LPNlul1mSedLb0XQH9GWRCrtYtA6wJSu5q3lNoaj0rB3qhC87twv5rUaDf8vB39pCb+VtnNRsWjmabYZQH4h9HJKE8Xzo+xyWx2Tq6NPoeORFejdKQ0CUigeALzkuWZKA/euw5thJ6MDkeaBJpKID/cMxjQqyUWndPrRaaXgAT6IvBirloNZTe4Olj+ppyFtq2Ds/pYHQLp7FyB5urSpaxPuhMd1GV6kz1CwBE7vwndEshgREa6HkIPoDxf4qfoAKS1j0CjRuxmaL7f8PnYbIZejh+cIV8/fjQB49GjefiuNwLfJ3lUF/srjuZRGU+oi8MV9rNR8WimO0jPoSEy8nZflw2S25QXoYxsaxKQQPEEXkSW0cNoR5SdKNdF70CaBJpM4BVULj+8st7qeHQI6sb+1E0i00hAAgMTWJocNkGJSXWweXAyA/oXo3SUNAl0TSCLwC9Bs7q8YuwOUnYu0bon4Ihd96zanjJrj45Db++AyFrAEzuvPbSPQKNG7LpovsxmOBdl0C6bB2nFEzAeFc+0LTnuR0UzSF4XeyuO3oS+UheHK+5nq+LR1jRGpjKcgFafpmHG1iCdR5oH0VrTpPWjxxIwID2WiWcmJ5D1gPmD/hL0eHQvWh9p7STQqoDUaeKVOKaDlHUDWvEEjEfFM21DjtmFN7OI6rKWJ387z0Zj8ZSX2oAEWhWP0vHZC92N0lG6DmX0LiPWR3eOmYJ3A8rnWRMxNrLNS61LAgakLkG1PNmK1P9OlN0iM431UyhrBDPNTmsngVYFpHFNvDevM1L97HHnfFkMAeNRMRzblkt+++VRMLnLWwd7C05mQP8utEgdHK6Bj62MR8vRMOkQXY/SERqvdJ4uR/uiJyOtdwIGpN6ZtfGKDal0Hsz8VTQL3Yjy3dHaS6CVAam9zT2SmhuPRoK5UYVkMD1r/f6vRrXKWqlfIx9NU1yjtT4eLQDLdISehhYsjmurczIgtbr5u6p8ttDPaNc/UTpKu6DcTZofae0l0PqA1N6mH1rNjUdDQ9vYjDelZpn2Wqed4DLAmNkYmaquFUOgUfFopl3s5oLZxOk7mUaXL9WYzTP2YtwxafJjTpOABAYjkP+jv0XP7GSTOd5no0+gL6F/IE0CbSAwWTzqpt7Go24omUYC/RPYk0u/hf7afxYjvfKFlDYL/Q4lpmoS6JlAfpiNn07X7esP9lxSuy9wxK7d7T9d7d/Ah9mI4SF0EkqHacPO+0x91dpNoFEjdjM0pfFoBkAFfWw8KghkS7J5FvXMb8M67Sr5DfzNDIxPIq04Ao2KRzPdQcpIdT8jAlcUx9ucJNBqAntQ+9yNfR/6fIdERuuOQVd23nuQQBsIGI/a0MrWsW4E3onDP0W/qYnjmY2xDcqd5S/UxGfdlEBrCThi19qmn7bi2c44U+iuQ2PzpJfhde4mvQRpEmjUiJ3NWQkCxqNKNEMtnFgML+9BG9fC20ec/DKHxNU8MkMrlkCj4tHE9UVFoJqDTJYoIiPzkEDLCfwf9Z8XnYXG1v29h9fnol8gTQISmJ6A8Wh6Pn4qgUEIvIWLb0CZ/l0X2xJHs+vernVxWD/LITDTFLvJvNqUk69D2cFuVidBvmzJKxs2LI8ORB9CmgQk0B+B/J96MroNfbSTxeM4ZkvSHTvvPUig7QSMR23/Blj/sgjkbsHO6GPo4bKc6KPcD3HNouhqpElgSgL/M+Unk3/wJk4fMvlH/zl7Oa+ymFaTgAT6J7Aely6P/thRcsp6pGzYcHzeaBJoOQHjUcu/AFa/VAJZxzMfOrxUL3orPIOMiaEH9HaZqSUwM4FLSPJ3tC16Iso8zkz5eTrKbcuMdn8Fab0RcM53b7zakHprKpkH723XqWzuKGXwIQtiNQmMEcgobnaQWnPsRIuOxqPhNLbxaDhcm5brBVToszWrVOLnTcjNGYbTcK2NR5nLfT/69jiuP+H1CePer8LrLCBfbdw5X85MwIA0M6M2pUhn6DJ0MxrbjGFzXt+HFkeaBMYItDUgGY/GvgHFH41HxTNtWo7rUqH81qvboyZ+h893oDYOKFHtoVuj4lEvmzTk1uQsdMY4xJfyeuVx77PNY37YvXrcOV9KQAK9EXg5yTNHOh2kMzuX7snx6+hvnfceJNBmAsajNre+dS+bQOLR91DdHjWRu+23oHSUNAlMS6CXDtLfySlfrBXG5ZgO0tJoiXHnruV19pnXJCCB/gjszmXZve5g9DB6NloDfQ1pEpDAI1O9jUd+EyQwegJPochXov1HX/TAJT6fHFZC/xw4JzNoPIFeOkiB8Vu0KVo9b7DfP3L497m8nB+tjfKEYk0CEuidQG5RL4ayvu/4zuXv4/hjlP9/mgQk8AgB45HfBAmMnsA7KDJ3YM4efdEDlfgCrj4LrTNQLl4sgSkIPJfzWYeUUe21UDpYV6B70XEo039yC3M7pHVPwDnf3bNqesqNqWAWkf6sU9E8IDb/vzbovPcggfEEGjXne3zFunhtPOoCUh9JjEd9QGvJJRkEz2yiLWtY37fjc2LrJ2voe11cbnM8+ncbrcu/J6Ond1psVY43oHSMoiNQr3emuKTVZkBqdfM/qvI78i6jcxt2zuaP+ZXI/1MdIB4eRaDtAcl49KivQyFvjEeFYGxkJntTqxtR/u7UyTIr4xz0CzR3nRyvma9tj0eTNld2FEpHablJP/XkTAQMSDMRas/n51HV3Il9IZqFEox2RpoEJiNgQHosFePRY5n0csZ41Aut9qTNIF1mDL23hlW+Cp8z8ylrjxaoof91cblR8ajXUemP00ovQdmGeLxlu8cLUUa6NQlIoD8C2bkunaND0dnoTWg+dDTSJCCBRxMwHj2ah+8kMEwCryXzpVB2U62T5fdqfqPehbZFdyJNAoUTSAco0+gyivB/aGmkDU7AEbvBGTYhh42oROZIZwpr7AL0iX+/8h8JTE6gUSN2k1dxyrPGoynRDPSB8WggfI29OBscHFTT2s2L31k/pQ2XQJvj0WzPgu1n0HUoHaX0yk9DW6F5kNYfAQNSf9yadtVbqdCv0LPRBij/v5y2CgRtSgJtDkjGoym/FgN9YDwaCF8jL86GKPnNl9ikSWAqAm2OR/9hkql566HDULYjzn+cO1BGF8a2AOel1iUBA1KXoBqcbBZ1y4h4nu2yGjoJHYU0CUxHwID0yAYmxqPpviW9fWY86o1XG1IfSSXHZja0ob7WsT8CxqMJ3LJGYmuUZ7bci9JZejfSuidgQOqeVVNTvpqK3YzOR8ug3D1aB2kSmI6AAenRdIxHj+bRzzvjUT/UmnvNElTtPvTymlYxd71OQGvU1P86ud2oePQ/BZCfRR5zoewcNGYPjL3wKAEJdEXg56T6NsrzxDLAkN3sTkeaBCTQPQHjUfesTCmBbgi8jUTXoFO6SVzBNN/CpxXQJejcCvqnSw0jkF7ia9D30Nhdo4x+74eeg7TeCDhi1xuvJqbOTnXZ0jt/yDNd9Q1Ik8BMBBo1YjdTZaf43Hg0BZg+TxuP+gTXwMsy+J2Ng3apad2yHCRr5m9DT6hpHerkdqvj0Vq01MEoX7ZMpXsQ/RBl+8eM3Gn9ETAg9cetSVd9l8qkg/RJlICUPzSaBGYi0OaAZDya6dvR3+fGo/64NfGqnanU7ShTV+tqL8bxTFvXhk+gzfHo34vI0zHKrcp3oSWHz7sVJRiQWtHMU1ZyKT75CdoRXY7yf0uTQDcE2hyQxrb5Nh51803pPo3xqHtWTU/5OyqYQbu62h44/jf0vrpWoGZ+Nyoe9boGKXM5T0bn1KzRdFcCVSaQUbosIF0QLY2yO6QmAQlMT8B4ND0fP5XAIAQ24OKV0KsGyaTkazek/HlQBlE0CYyMwCxKynqjddEiIyu1mQU5YtfMdu2mVouRKFMYsl3+H9FXkCaBbgk0asSu20pPks54NAmUPk8Zj/oE17DLTqI+R9W4Ttk4LHePsj6+zlME69QErY9HmVaX3UzuQ5luN6areL0r0nonYEDqnVlTrtiMiqSD9CeU/0t5IJ8mgW4JtD0gGY+6/aZ0n8541D2rpqZcnoo9jF5Y4wqmDseiTWtch7q53qh41OsUu1VprRPREug0dDG6Cz0JrYcORNmFay+UH3uaBCQwNYH8X/kGykjXtShrKn6LNAlIYGYCxqOZGZlCAv0Q2JuLzkVn93NxRa7ZCj/WQVej45AmgaESOJLcM9r9vElKSc/xAJSOUXYX0ron4Ihd96yakjL/hx5AGaXL9Lp7UOZLaxLohUCjRux6qThpjUc9AusyufGoS1ANTZa1sIlJmd1QZ3sTzmc97+J1rkTNfG9tPMoo961on2kaLGluQJ+YJo0fPZaAAemxTJp+5gNUMB2kv6OsO8rdozyzQZNALwTaGpCMR718S3pLazzqjVfTUr+bCl2HZtW4YnlOZwYf/4lcfzS6hmxUPOrlB1mm4z0OXT8N64f47Gr0lGnS+JEEJDDbbJsDIXdj10eZI/1plD/omgQkMDMB49HMjEwhgV4JZOBhN/QFlAG8utryOJ5ZGVkScnddK6Hf9SJwJu5mg4apOlbL8Fl67PkPpnVPwBG77lk1JeXzqch2KG1/J1oAaRLolUCjRux6rLzxqEdgXSY3HnUJqoHJtqBO+Q1X552JZ+H/TehGNBfSRkegzfFotqfDOV+89MpXQ4ERmxdtgrIT16/RE9Ci4zQPr7WpCRiQpmbT9E/y/+WTTa+k9RsagTYHJOPRcL5WxqPhcK1DrmfhZNaS19myDORedCmavc4VqaHvbY5Hs11Ag2V0IRsxRJlSlzUUY++nOr6XNNrUBAxIU7Np4ifLUqkz0GdQptUthzQJ9EOgzQHJeNTPN2bma4xHMzNqYoo1qFR+w61Y88qth/+XoA1rXo86ut+oeJR53L3Yr0h8TS8XdNLmzpImAQk8QiB3XxOEMk/62+hKpElAAr0RMB71xsvUEpiOwF58mNlB6VzU1XLH6CMoA/en1bUS+i0BCfyXgCN2/2XR9FdrUsFb0B0od2DXQZoE+iXQqBG7fiF4XaEEjEeF4qxFZk/Ey/tR7r7U2TLofwXKoOOsOlekpr43Kh79v5o2gm5LoI4E8nyJU1AWwGbd3oXodKRJQAISkIAEyiLwdgr+M/ppWQ4UVO4q5JOHrW+B6rwLX0E4zGYQAr1OsRukLK+VQNsJnAGAPJMht/+zneq+SJOABCQgAQmURSCbaO2A3o2yBqmuljtGGYDMjrDZoCFTcDUJ9E3AO0h9o/NCCfREIH+8E3zuQsegPKPhOKRJQAISkIAEyiLwJgrO2p2jy3KgoHKXIJ9sInYdcvCxIKhtzsYOUptb37qPksBmFLYkOhW9DH0e3Yc0CUhAAhKQQFkE9qDgr6B0Lupsu+N8BiKPQHkIuyaBgQg4xW4gfF4sga4JZD50doDMrf88M+xQpElAAhKQgATKIrARBT8dHVSWAwWWezB55TftVwvM06xaTMAOUosb36qPjMBylHQYSicpI1yHoJuQJgEJSEACEiiLwJ4UnKl115flQIHlZgDyXQXmZ1YtJ2AHqeVfAKs/EgJZa5TtL69Dz0VvRpoEJCABCUigLAIrUPB6aI2yHCi43A3IL+t8ff5RwWDbmp0dpLa2vPUeFYFtKCgPhc16o0yvy/MZfoM0CUhAAhKQQFkE9qbgs1ATdnubm3p8Dz2MHo/c4hsI2mAE7CANxs+rJTATgU+SIJuhHI62R69BmgQkIAEJSKAsAgtT8FYoA3h1t0WpQAYf00k6Gdk5AoI2OAE7SIMzNAcJTEUgu+oshi5DefbRjSi72GkSkIAEJCCBsggkNt2CTijLgQLLzaYM6fBlq/Js1KBJQAINIrATdcnc2TxEVGsGgfmpRjpFD6H90Q1oV6RJoEgCWduWvx1rFpmpebWagPGo2c2fgfG/oL1qXs0n4f/lKNPqcteoKWupqEptrVHxKFN/NAlIoHgCb+hkmT/gF6N0mI7qnPMgAQlIQAISKIPAFhSaOy7fLKPwAsv8GHkt18nvRI7nFpi3WUng33vGi0ECEiiewA/I8unoGPQ19GV0J9IkIAEJSEACZRF4CwV/Hd1RlgMFlJvZNq9E2fzoTejbSJNAoQRcg1QoTjOTwH8IvJhXmeOdBaSros2RJgEJSEACEiiLwIso+AVou7IcKKjce8jnTHQXsnNUEFSzeTQBO0iP5uE7CRRF4EtklF11/oCORVcgTQISkIAEJFAWgaw7ysYM2Tiozpb1RomvH65zJfS92gTsIFW7ffSungTGFouegfuvRhm10yQgAQlIQAJlEXgyBW+C1i/LgQLL3Z68VkMbot8hTQKFE3CThsKRmqEE/r0Zw5JwyANi/4hcPOqXQgISkIAEyiSwJ4Vfik4v04kCys6GRxl4nAN9sYD8zEICkxLwDtKkWDwpgb4JZGrd0uhWtBTaBWkSkIAEJCCBsghkU4NsZlD3rb3Dbxu0CMoapHuRJoGhEPAO0lCwmmlLCeSW/24o/6/+jLLDTnaz0yQgAQlIQAJlEdiBgh9Edd/QYBZ12KcD8eDO0YMEhkLADtJQsJppSwlk+9Q8sO4ktBj6PEonSZOABCQgAQmUQWB2Ct0DfRnV/Y7LXNQhnaS/oGx+pElgaATsID3yQ3YFCMtiaF+zVmScxaK59Z+neqeDtAyq+4P4qIImAQmMkEAGVoxHIwTegqJeRR2XRU244/JU6pGpda9B/0KaBIZGwE7BI7drL4HwQkOjbMZtIHBAp5InctwKpXN0U+ecBwlIQALdEMj0IeNRN6RM0y2BbM5wJPprtxdUOF3WUWUXvpdX2EddawiBpm/S8BzaKYsTp7MspI+thu7896tHbt9e13ntQQLdEMjuQA+hz6Dz0VuRJgEJSGCMgPFojITHURFYiYJeip43qgKHWE6m1j0fXY8OHGI5Zi2BVhD4LbXMbdhe9cER09mp4+NMnbkRu2VxXRLIsyWuRFujI9ApSJPAKAjMSSH5+7bmKAqzjIEIGI8GwufFfRD4Jtf8rI/rqnhJ/sbdhbL+SKsmgUbFo6bfQTqI79B+aG6Up0dn6sJEy+jKC1D207+n8+EvO0cPEpiJQL5b6RSlc7sBeh16LdIkIAEJjCdgPBpPw9fDJvB4CtgCvWHYBY0g/9kp4yudcr4xgvIsQgKtIJBbzHnS8j9Rpj3lP9p4+zRvMgK7yPiTI37tHaQRAy+wuFPJKzvXZUrmp9BVyLV9QNBGQqBRI3YjIVZuIcajcvm3qfQPUtnMbGhCPMrvs9tQ7iAtiLRqEjAeVbNdpvUqW0Pui7LDWH7Qjq074uVsdpBCQeuHQO4e5Y/2vWhTdAPaDWkSGBUBA9KoSBdXjvGoOJbmNDmBWZxOPGrSWth1qU/WimvVJdCoeNSEkYVuvir3kWgftB5aEf0e5dazJoFBCOzAxel0/wgtiuZHRyJNAhKQwFQEjEdTkfF8UQSyHvZx6LCiMqxAPllLdX4F/NCFlhBoSwdprDnzHyw7CZ2GjkZHoYWRJoF+CKTDnQ5S5kbv2jneyVGTgAQkMBMB49FMhPy8XwJ5aPlXkfGoX4JeJ4EWE9iWuv8dZf2Ra5Ba/EXos+qv4Lps630HykPr0lHKQ+w0CYySQKOmNIwSXMXKMh5VrEFq7M46+J7YtFyN66Dr9STQqHjUtjtI479y3+LNyui76HSUhfaaBLolsD4J70d5HsOb0XfQFUiTgAQk0CsB41GvxEw/FYG9+OAH6MqpEtTwfH6rPqOGfuuyBCQwIAF3sRsQ4IgvX4Xy0jn6B3o+ehD5HBogaCMn0KgRu5HTs8DJCBiPJqNSj3PL4mbi0Yvq4W7XXn6ElH9DGYzUqkugUfHof6rLudaezcL7bAKRL0s3tlY3iUxTGQL/hyeZUnc2eiP6IzoHaRKQgASKIpAdMbO2MXepDxog03m4Np2exKVubPVuEpmmkgRy9yibUJ1VSe/6d+oSLr0HNemuWP80vHIkBOwgPRpzUQFpSbJ9H+q2g5Tdz7R6EMht/o1QRumyhep5aHekSUACEiiSwBJklk2FchzE8gyZXgbssiOnVj8C+R2xPWpiPMqmWpEmAQmUROBDlJsNGz444vKd0jBi4AMU9xuuzfS649DeKLf950KaBMog0KgpDWUArHCZRXWQeq2i8ahXYtVI/w7c+CvqdmC2Gl7P7EUG8rOm6sCZk5qiZALGo5IbYJjFG5CGSbcZeecW/61oGfQn9F6kSaAsAgakssg3t1w7SPVr22xi8Gf0/vq5PqPH6fhlV76bZ0xpgrIJNCoeOcXu0V+nm3gbaRKYjEAWvmbtUTpF2ZxhWfRNpElAAhKQgATKIrApBT8Jfa0sB4ZU7jzkuw9KB2nUM3uGVCWzrQuBNnaQFqZxFkSZFnUXynNs7kaaBGYi8EwSLIBy92hbdCjKlAZNAhKQQD8EjEf9UPOaiQT25MThKFO+m2SzqEwewXIFygPZNQlIoGAC2Zb56yh/PP41ifKf72C0GCrDnNJQBvXeyzyUS36OVkb5HuV7pUmgTAKNmtJQJsgRlm08GiHsFhQ1Fo+yoUfTLL/JdkduHFKPljUe1aOd/uPlB3g11im6htdnox+hY9CPUXYhuxElzS1oKzRqs4M0auK9l/cGLslt/jtRvjunIk0CZRMwIJXdAr2VbzzqjZepZyaQhww3MR5lls/16B70dqRVn4DxqPpt9B8PN+NVOj7pCK36n7OPfTE7p16MzkdJ/0I0SrODNEra/ZX1VS67F30K5Q/2RkiTQNkEDEhlt0D35RuPumdlyu4ILEGyxKVXdJe8VqnWxdvE2iyFeGqtPG+vs8ajGrX9kfia6XPdbsOc+eC5QzDIQ/m4vGezg9QzspFe8C5Ky+YMd6PPoqtQdg3SJFA2AQNS2S3QffnGo+5ZmbI7Ah8l2eUog7xNs/wOy85172taxRpcn0bFo6Zv0pA5ueeg+7r8Qt5OuovQUl2mN1nzCeQ//Ic71cyzj7ZCH0fpMGkSkIAEuiVgPOqWlOm6IZCB353Rh1BmvjTNzqBCGbD+YtMqZn3qQaDpo+A30gzPQ7O6bI7cQUoQu7TL9CZrPoG3UcUH0QXop2gBdATSJCABCfRCwHjUCy3TzkRgWxKkk5Q1SE2z51OhbFn+RpQpdpoERk6g6R2kwyC6AvoeWn0aurk9vTY6Gc2LcqdAk0AIrIMyD3oftBs6EGVUS5OABCTQCwHjUS+0TDsTgbeQINPQmtiB2KVT+bNnguDnEhgWgaZPsTsKcIujj6FXoevRdehWlB+5uRuwCFoGLYlyp2Bv9EukSWBuEKyJ8hyG+VDuRm6JNAlIQAK9EjAe9UrM9FMRWI8PnoVePVWCmp8/Ev8zjX1senvNq6P7EqgugeVw7WiUDlLm6o5XFt5nkeO+6MmoDNuJQuNTfoRr1SGQ0bk8SDjHE9CxSJNAlQjMiTP525GOvFYPAsajerRTlb38/+2dB7gkRdm2RVgyuwSXnCWKoARFgiQRkRUUBSQpWUTiqgQFAQkGQJAsAvKDIElAcpIPRTKyEiXDkvMuccnwPw/bLXOGOXMmdHd1V9/vdT2np1PV+97VZ2qqq7r6Yjnn103EaCMVlIej3hljcJHHRH1U8QJ2r5EbQgtKI0oSCw2kkhREgxsefupexrclT8zg3sXlJQwCZSJAhVSm0ujeF+qj7pnV/YwFBOA9aYUIQUymmO6WXN/+O8L4Yg8pqvrIF2PdzD96LQwC7Qispp3+kj5P+pL0X+l6CYMABCCQFQHqo6xI1ied0Qr1Zum6CEP2IxG+ge1ecT9jhUEgGIE6NpCCwSbjShHw5B5uILlhtIu0vYRBAAIQgAAEQhHwqJfvS1uHciDnfH+o9D1p1o7SjTnnRfIQaEvAw4gwCEDg4wSO0qZVJc8Q5EkaPBMiBgEIQAACEAhFwLO7udfx3FAO5JivX7PiG5FTSg/mmA9JQ6AjAvQgdYSJg2pIwOO7h0k/kH4vvSVhEIAABCAAgRAEJlWmftXEEZJv2sVmnrXOkyLdLv09tuCIp3oEaCBVr8zwOH8CroguktxA8kOHf5IwCEAAAhCAQCgC31HGs0gnhHIgx3xd5x4jeVi7h7RjEAhOgCF2wYsAB0pIwF39N0i+m/X/pGckDAIQgAAEIBCKgBsO/0/yexxjs+MUkN8xuID0+diCI55qEqAHqZrlhtf5EfBNA08zOqPk/w+/AwmDAAQgAAEIhCLgl5T7XWdbh3Igx3zdezSf9IZ0mvRnCYNAcAI0kIIXAQ6UjIDfdTSd5GlGPYvOGAmDAAQgAAEIhCLwU2V8qeRZVWOzeRSQe43cM+ZnfjEIlIIADaRSFANOlISA72R59jo3jjzV6AESBgEIQAACEAhFYDZl7OePRoVyIOd891H6ft7Xk09gECgNARpIpSkKHCkBAY+DXlzybDpPSr5jh0EAAhCAAARCEdhJGT8kxTizm2eLXV/yb9F/SRgESkOASRpKUxQ4EpjArsp/88SH17U8WHJDCYMABCAAAQiEIOB3Am0tHSp5ZENM5ueO3OibQrpKuknCIFAaAjSQSlMUOBKQgIfS/Vby/8N9kofanSphEIAABCAAgVAENlfGrpc8eUFstp8C8tC6lyW/ABeDQKkIuFsTg0CdCUyv4N175LtzN0v+n/DMdf7SxiAAAQhAAAKhCOygjI+VJoRyIKd8hyvdFaUXpJWlxyQMAqUi4DsTGATqSsDX/y2Sl9dKP5c8naqfRcIgAAEIQAACoQisqYwXlmJ81YSH17mR9JTkURsYBEpHgAZS6YoEhwokMLnyGiH57d17SH4R3znSgxIGAQhAAAIQCEVgtDI+U3oilAM55ZsOYffwOveOYRAoJQGG2JWyWHCqIAIbKJ+ppJ0lz1rnaVTd3Y9BAAIQgAAEQhFwz9FXpeVCOZBjvh426Ph8Y/LyHPMhaQj0RYAepL7wcXKFCfg9R24YTSG9Lf1E8kv4rpMwCEAAAhCAQCgCP1bGrotim9ltpGI6MIF6kJaPJZ9ZQAACEGhJYBtt9SQB07Tcy8Y8CKyjRN0w8tu7p5PGS5tIGASqRMDDRP3dEeOd5iqVQ0y+Uh+FLc0ZlL1fNeGXw8Zm6ymg16Q7JW7Qx1a6n/hEVPURF2h8FygRDU3AvUf7S+9Jx0hbS+9Ifv4IgwAEIAABCIQisJ0y9o2780M5kGO+Htbuxp97j3jPYI6gSRoCsRDgjl2xJfl1Zefeo5ckP4fnWXT2lDAIVI1AVHfsqgY/Un+pj8IVrOsjDzvzkO8YbW4FtaXk7y0sPgLUR/GVafCIqJCKK4Jhyupp6S3pt9K6khtLs0oYBKpGgAqpaiVWfn+pj8KV0cbK2kPQPMwOg0DVCERVHzHErmqXH/72S2ALJTCz9Kq0l+SpvU+WnpEwCEAAAhCAQCgCOyrjP0l+JjY2c6PvLunE2AIjnjgJMM13nOVKVIMTmEq73DjaXVpQWkkaLWEQgAAEIACBUARWUMbLSpuFciDnfL+o9D3EbkLO+ZA8BDIhQAMpE4wkUiECd8vXDaXLJPccXSWNkTAIQAACEIBAKAIezXCRdH8oB3LOd1ul76Htx+WcD8lDIBMCNJAywUgiFSEwQn6eJXkWuwWk9SXPqoNBAAIQgAAEQhGYUxl/S1ojlAM55zu90l9IelhyHYxBoPQEaCCVvohwMEMCLyut46VXpJ2k56RLJQwCEIAABCAQioBfWn6vdHUoB3LOd0alb70heYg7BoHSE2CShtIXEQ5mSOB7SstTjN4ubS0dIvldSBgEIAABCEAgBIGplelW0qEhMi8oz9WVz0uS3/GEQaASBGggVaKYcDIjAq6EppG+KQ2X/ixhEIAABCAAgVAEfNPON+pOD+VAzvn61Rp+vmoOabac8yJ5CGRGgAZSZihJqOQEPAZ6CckPiX5O8oOiHnKHQQACEIAABEIQ8POwO0hHS2+GcKCAPBdVHjNJ46QLC8iPLCCQCQEaSJlgJJEKENhDProycq/RMtIfJAwCEIAABCAQisAoZTy/FPPMbk8qPr/baT0Jg0BlCNBAqkxR4WgfBPxw6E6Sh9WtKJ0rPShhEIAABCAAgVAE/A6+v0hPh3KggHxPUR4e3u53IGEQqAwBZrGrTFHhaB8E3LV/mOQGkh8S3UnCIAABCEAAAqEILKaMV5M8oiFWW1OBrSK9K42RMAhUhgA9SJUpKhztg8CBOncLaVbpHulaCYMABCAAAQiEIvBjZfwP6dZQDhSQ797Kw5M0/FN6tID8yAICEIiMwDaK5wPJM6xh2RLwXbq3Jc8S9Jq0qYRBIBYCkysQf3csF0tAxBGcAPVR/kXgSQsmSJ5RNVb7rALz6A2/b9CTJGHxE4iqPqIHKf4Lts4RTqrgz0kA+A3efkndX5N1FhCAAAQgAIEQBLZXps9KF4XIvKA8d1Q+nhjpBMnvQMIgUCkCPINUqeLC2S4JjNDxI6V3JH9RHy7FOpWqQsMgAAEIQKDkBDzkbFvpICnWF5X7uarNJN+kvF7CIFA5AvQgVa7IcLgLAlvqWFdAf5Q8g86JEgYBCEAAAhAIRWAjZTyddFIoBwrI1z1k70t/kWLuJSsAJVmEIkAPUijy5Js3AU/IsJ/kMbGeSecUKeapVBUeBgEIQAACJSfgoWcedvZKyf3sxz3fmHR8h/STCOdCICQBGkgh6ZN3ngR2U+LuIb1bWkJicgZBwCAAAQhAIBiBlZXzUtKGwTzIP2PXt2tLj0l35p8dOUAgHwI0kPLhSqrhCdwiF+6T/CX9gnSrhEEAAhCAAARCEdhFGZ8vPRTKgQLy9cx1ju+8AvIiCwjkRoAGUm5oSTgggeHK+9fSq9JXpO9KGAQgAAEIQCAUgXmVsXtWVg3lQEH5ejKkT0v0HhUEnGzyIeAhSBgEYiPwrgLylN7TSH4HwyUSBgEIQAACEAhFYGdlfJf0r1AOFJCv69w5Jd+c9EvZMQhUlgANpMoWHY63IeDG0dckT9DwO8kPjGIQgAAEIACBEASmVaZbSK6PYrbjFJyn+PbL2R+NOVBii58ADaT4y7iOEe6roD05w0zSKRIGAQhAAAIQCEVga2Xsd/CdFcqBgvJ1jK9JexaUH9lAIDcCNJByQ0vCAQk8obynkC6UXg7oB1lDAAIQgEC9Cfh3lt8LdJT0VsQoFlBs35CulZigIeKCrktoNJDqUtL1ivN+hTuZxF2sepU70UIAAhAoG4F15NBckl9YHrMtrOCmkl6MOUhiqw8BGkj1Kes6Reo7dZ7m+4E6BU2sEIAABCBQOgKj5dGpkicMitk8hbl7yM6JOUhiqw8B32XHIBATgRUVzGISQ+tiKlVigQAEIFA9An5p6krSTtVzvSuPl9TRi0sPSld2dSYHQ6CkBOhBKmnB4FbPBI7Ume9Lf+45BU6EAAQgAAEI9E/gJ0ri79Lt/SdV6hSOkHcjpSmlCaX2FOcg0CEBepA6BMVhlSAwvbx079E46cRKeIyTEIAABCAQI4GZFZRfUv6dGINriMlxzi49JH2rYTsfIVBpAvQgVbr4cL6BgK9lT+3tRv8wKfY7dgoRgwAEIACBkhLYQX49Ll1aUv+ycsuNo2mkJ6THskqUdCAQmgA9SKFLgPyzInCCEppN+kDyw6IYBCAAAQhAIAQBv2biB9L+kod8x2y3KbhVpadiDpLY6keAHqT6lXlsEU+ngJ6XNk8CO1DLk5PPLCAAAQhAAAJFE9hEGfp5nDrURcsqTg8jjPkdTwoPqxsBepDqVuLxxfszhTRjEtbDWu4dX4hEBAEIQAACFSKwo3z1e49eq5DPvbr6a53oZ3/dk3RRr4lwHgTKRoAGUtlKBH+6JeAZc6xpJT8Qi0EAAhCAAARCEfiKMvaU1+uGcqDgfPdRfqtJnq0Pg0A0BBhiF01R1jaQsYr8Oulq6VYJgwAEIAABCIQi4Gdgz5XGhnKgwHx3V16XSAtKbxaYL1lBIHcC9CDljpgMciSwq9L+lTSp9K0c8yFpCEAAAhCAwFAEPq0D1pJWHOrACPbvoRgOkHyjfY4I4iEECAwgQANpAA5WKkRgevnqcd42j/O++MNP/IEABCAAAQiEIeDeo/9IN4TJvtBcRyk3z9B3j7ROoTmTGQQKIMAQuwIgk0UuBM5Tqr5rNYm0l/SehEEAAhCAAARCEBiuTDeTfhci8wB5Hqk83SD8nPRqgPzJEgK5EqCBlCteEs+JwPxKdynJjaJ3pFMkDAIQgAAEIBCKgN975IbCX0M5UGC+yymvo6T1pNjf81QgVrIqEwGG2JWpNPClUwKese4BaWbJldFLEgYBCEAAAhAIQcDPwW4vuVfFN+1itwcV4J3SBbEHSnz1JUADqb5lX9XI/c6ja6XJEx1b1UDwGwIQgAAEoiDgKb1nlU6IIpqhg/DL2T2dOQaBaAkwxC7aoo02sIMV2dRJdJ6YwT1JGAQgAAEIQCAUgdHK+GTphVAOFJivfzeeJbkHaY4C8yUrCBRKgB6kQnGTWZ8EPLRuJcnvW5hCcmMJgwAEIAABCIQi4Odhl5f8DFId7CAF+W3Jzx7NIz0pYRCIjgANpOiKNOqAllB0I6U3pEekayQMAhCAAAQgEIrAT5TxZdLdoRwoMN9plNeG0rvScdL1EgaBKAnQQIqyWKMNaidF5i9mD7Gj9yjaYiYwCEAAApUgMJu8XF9auxLe9u/kGkrC9a+Htu/cf3KkAIHyEqCBVN6ywbOBBDykboTkl8LaPAYagwAEIAABCIQi4JeVPyxdEcqBgvP9kfLzjH2/LjhfsoNA4QSYpKFw5GTYI4FzdZ7vXs0uHSH5OSQMAhCAAAQgEILAlMp0G+kw6YMQDhSc567Kb2XpdemqgvMmOwgUToAGUuHIybAHAh7r/PXkvEm0PL6HNDgFAhCAAAQgkBWB7ysh96b8OasES57Oxkm8/9Xy2ZL7insQ6JsAQ+z6RkgCBRB4WXm8JT0v/V16WsIgAAEIQAACoQh4eN0fpAmhHCgw31mVl0dtnCJtXWC+ZAWBYAToQQqGnow7JOAHQheS/ijNJR0jYRCAAAQgAIFQBL6mjBeR6vKi8o0U6+KSh7i/J2EQiJ4APUjRF3HlA3SjaDnJ7z/6h/RvCYMABCAAAQiEIrCLMj5bejyUAwXn6wbS29LRBedLdhAIRoAGUjD0ZNwhgVd0nJ858rsmft/hORwGAQhAAAIQyIOARzS4B2n5PBIvaZpuEK4gXVJS/3ALApkTYIhd5khJMGMCnrHO71vw9N4XZZw2yUEAAhCAAAS6ITBaB98g3djNSRU+1q/X2FK6X/J7CDEI1IIADaRaFHOlgzxV3numIDeUGPtc6aLEeQhAAAKVJjCDvP+eVKfRDB7i7hfh+kXtGARqQ4AhdrUp6koGOpO8PkrydXpkJSPAaQhAAAIQiIXAtgpkvHReLAF1EMd9OsZTmf+xg2M5BALREKAHKZqijDIQd+3PLHl675eijJCgIAABCECgCgR8o+5H0uFSnYaaeTIK95r5hiUGgdoQoIFUm6KuZKC/k9fDpL0r6T1OQwACEIBALATWUyBuJJwYS0AdxPFDHbOY9Jb03w6O5xAIREOABlI0RRllIJ9VVJ5adEyU0REUBCAAAQhUhYCfwTlJ8hC7OticCvIQaXLpSskvbMcgUBsCPINUm6KuXKBby+NPS5455z+V8x6HIQABCEAgFgKeqOBL0haxBNRBHAvrGN+gfEJyTxIGgVoRoAepVsVdqWB/kXjrB0QxCEAAAhCAQCgCfg/QxVKd6qOlFe9D0teldyQMArUiQA9SrYq7MsEuIk/dve/JGTaujNc4CgEIQAACsRFwXfRtac3YAhsinm9q/9zS9EMcx24IREmAHqQoi7XyQf1BEUwi3Sq9XvloCAACEIAABKpKwM8euefoqqoG0IPfC+mc2aVzJYa49wCQU6pPgAZS9cswtgjcMFpCekM6ILbgiAcCEIAABCpDYGp5upV0WGU8zsZRP/87XBqRTXKkAoHqEWCIXfXKLHaPv6EAp5WWke6IPVjigwAEIACB0hLYXJ69L/2ltB7m49hBSdwH55M8qUKg/AToQSp/GdXNw58pYD8QekTdAideCEAAAhAoDQGPZthROlbyiIa62GYK1D1Ik0qP1yVo4oRAMwF6kJqJsB6SwJLKfDnpPemFkI6QNwQgAAEI1JrAWoreDQU/E1sn213B+ub5oRL1cJ1KnlgHEKhbD9JQ8fqOyQzSlAMosVIUgUuV0QdJZvsXlSn5QAACEAhAgPooAPQusvTU3mdIT3VxTtUPXVUBzCU9Jx1e9WDwHwL9EBjqC7qftMty7ixy5ExpnPSKdLW0gtTKFtdGH+c7KFixBPZQdjNL7j36nnS7hEEAAhCIiQD1UTVK8zNyc3WpbkO9XfcOk/4kvSphEIBApAT8sP9jknslXpbulfzApX+EHyg12+e1wcfu07wj5/VtknynyTmfsiY/nRxz49Vlc3pZncQvCJSQwOTyyd9ZHpqKlZsA9VG5y6fRu+O18s/GDTX4PK9i9O+klyS/ixCDQLcEoqqPYu9B2lWlO5f0S8kve/M//Reku6SfSx5ji4UnsIRcmFp6Udo0vDt4AAEIQCBzAtRHmSPNJcGZlOom0u9zSb28iS4q196WrpN8MxmDAAQiJnClYntWap6MwnP7XyP5zqsrrdToQUpJFLv8l7Jz75G79zEIQKBzAlHdses87EoeSX1UjWLbS24+IvmZ5DrZ+Qr2ecnDCzEI9EIgqvoo9h6kOVTC/vH9blNJuxv5G9Id0m+lDSQsHIEFlPXr0r/DuUDOEIAABHIlQH2UK95MEvfzN9tJh0seil8Xm0eBepiuG4Ue7o5BoPYEYm8gPaoS9oOWrWal85fAWtIT0snSChJWPIEtlaUfXHZj9Z7isydHCEAAAoUQoD4qBHNfmXxXZw+XTuorleqd/HW57Mbh/0n+TYRBoPYEYm8gXaUS9nC6X0mztyjtJ7Xtq5Jna7lEGiVhxRI4QNl5qONjxWZLbhCAAAQKJUB9VCjunjLbWWedKHmUSV1sNgX6G2kyqW7PXdWljIkTAh8j4J6juyX/AHd3+YZSK/OzR+MlH2ftKxVp2ygz51u3WezmU8wul2ek+SUMAhDojkBUY767C71yR1MflbvIviz3XB8tUG43M/fOz2FPkNzDOVXmqZNgnQhEVR/F3oP0Cyur0QAAPxBJREFUpq7MZaUjJPdQeIaWVnabNi4jXdZqJ9tyI+C7VW4YPiE9nFsuJAwBCEAgPAHqo/Bl0M6DXbTzAunBdgdFts+/j34tTSJtJb0hYRCAQA0JdNIg/IK4+IWxRVode5A8rfc7kr+QPawBgwAEuicQ1R277sOv9BnUR+UpvnnkiidzWrk8LhXiyY+Vixvu/5H8XYJBoB8C1Ef90OPclgTq2EDyLEGe2vtZye+dwCAAge4JUCF1z4wz2hOoY33kdyJ6JEnd7H4F7Dr483ULnHhzIRBVfeSH8rDsCZjrulKnd2S+mL0LpU7R3flbSh7vfabkF8RiEIAABCDwEYHt9PGH0rHSHz7a3PWnmZPzO62P5uo6h2qfMK3cd31Ut5EMayrmGaRrpdslDAIQaCBAA6kBhj5mVSH5fRcHScMGJj/omoeb1cl2UrCekOIxyZwwCEAAAhAYSGAWrS4hedmPeRjzPVKnDST/LnC+dTE3jt6SzqhLwEmcf9JyRsk3Kv0sMAYBCEBgUAL7ao+/KPYZ9Ih8dtRpSIOH0/nZIw+vuysfnKQKgdoQiGpIQ21KrbNAs2ogdZbbR0fVqT7yaAYPM9v7o/Br8cmvNPHrTTxz3fBaREyQRRCIqj6iB2ngJXOsVs+VPCYXy4fAGko2fVv3xvlkQaoQgAAEKk/A9RB1Ub7FuI6Sn1s6Lt9sSpf6+vLI9bBn+H2ldN7hEARKQIAG0sBCoEIayCOPtbWV6CPSitLTeWRAmhCAAAQqQsDPgIyQppBek16SXpewYgh4au+/SHVriHpShpel8yQMAhCAwIcEXCHNKy0s+VmhMryctS5DGuYTbw+t8w+AVSUMAhDoj0BUQxr6Q1GZs5eUpydIz0ke0t2sh7TNPRojpRBWl/rIz1mZfR1ncPuc4l40xMVFnlEToD6qYPFSIYUvNL9F3j1GbiB51jqm9hYEDAJ9EqBC6hNgwaf7WZe0QeTnP66XLpI8QcCl0k2Svyd9zAtSiGHIdWkgnSS+V0l1s+8qYNfBR9ctcOLNnQD1Ue6Is82ACilbnr2m5ilF3Tjyy/i+0WsinAcBCAwgQIU0AEepV9aXd274uCG0VBtPJ9G+laRbJB+/vFSk1aGB5KnP/YJUD/mum92ngF0P71e3wIk3dwLUR7kjzi4DKqTsWPab0k5K4G0pxB3Rfn3nfAiUlQAVUllL5uN+naZNHj7n5406MQ8H9wP0/bwDqZN8mo+pQwNpXwX9oPTJ5uAjX19Q8T0h3SNNF3mshFc8gajqo9i/HL6l6+Nhycsxba4V36W7RlpD8tSX35ewbAkcoOQ8vffj2SZLahCAAAQqQcDPvNwg+Z07ndh4HXSH5GdlsewI+EfcD6XfSx7VUCdzz+Uw6WbJv3UwCEBgEAKxN5CokAYp+II3+46k31b+unR3wXmTHQQgAIEyEPCzRUtL/oHaibkHyXXYvZ0czDEdE/Aohqmkkzs+I54DZ1Uo/5Z+HE9IRAKBfAjE3kCiQsrnuuk21W/qBE9he6Q0rtuTOR4CEIBABAT8g3wR6Rxp2Tbx+BmkL0uXSVNLf5Ow7AjsrKSOl+rYg7Kj4v6CNKOEQQACNSawiWL38LkLpE4qJM8g5IcXV5CKNPew2M8yTDmeddxzKsH3JA8XWTDrxEkPAjUnENWY78jL0g2f0ZJ70v1972dBbpQulk5Plh6C95Tk/e9I/jFftMVcH60qmK7j5y0aaknyW0x+eMIkDAJ5EKA+yoNqTmlSIeUEtotkXeF7nLfH3fvuKQYBCGRHgAopO5ZFpTS/MnKD6EnJDaFGufH0gHSINJcUwmJuIJ0voGeHgFqCPH8kH9xrtkcJfMGFOAlQH1WwXKmQwhSax3n7bp3vhP4ujAvkCoGoCVAhVbt4h8t9N4Tcuz6iJKHE2kDy7wCPZih6hEgZinVSOeFRHI7/hDI4hA9REqA+qnixUiEVV4D/UlbuPbqzuCzJCQK1IkCFVKviLiTYWBtIR4jerYUQLFcma8sdP/vrm5V3S7E/e64QsUAEoqqPJgsEMWS2ryhzC8ufwDLKwneszs0/K3KAAAQgAAEItCTgG6ObS9u13Bv3xpMV3vSSb1b+NllqgUEAAu0I1LGB1I4H+7IjsJuSmkLyM0j7ZJcsKUEAAhCAAAS6IrC1jvZMqmd1dVb1D3bvke/qPyp9T7pWwiAAgQ4I0NXaASQO6YnAVjrrbenSns7mJAhAAAIQgED/BPw7ZwfpKMnPw9bJPLRuguSX4tI4qlPJE2vfBGgg9Y2QBFoQ8Bh2P3TsyuiqFvvZBAEIQAACECiCwLrKZDbpj0VkVrI8HLdnRDy8ZH7hDgQgAIGOCMT2UOzLitrjnXkDfEfFz0EQ6JlAVA/F9kyBE7MkEFt95MmC6tg4mlRxvyC9KH1awiCQN4Go6iOeQcr7cqlf+qso5OmkxyVeSCcIGAQgAAEIBCGwlHJdUarj5Aw7Ke5h0h3SQxIGAQh0QYAGUhewOHRIAp/VEZcnR92u5djkMwsIQAACEIBA0QRGK8MrpLuKzjhwfvMp//0l39E/PrAvZA+BShKggVTJYiul06vJq0sk37Hy5Aw/kDAIQAACEIBACAKzKtMNpG+FyDxwnmcq/ymlZ6S6zdwXGD3Zx0KASRpiKcnwcXiMt+9W2b4k+YsZgwAEIAABCIQg4JnrxkqXhcg8YJ6+STmL5Pc9ri69KWEQgECXBGggdQmMw1sScE/kNZK/kE+QbpMwCEAAAhCAQAgC7j3xKIbDpA9COBAoz2mV772SZ6/zKzb8GYMABHogQAOpB2ic8jEC62iLhzH4beW/+9heNkAAAhCAAASKI7CpsvKNuz8Xl2UpcvLEDPNIk0jnlcIjnIBARQnwDFJFC65kbrv3yFN73y/dVzLfcAcCEIAABOpFwA0FD/t+vV5hf9hr9pZi3lb6a81iJ1wIZEqABlKmOGub2NcV+VzSVrUlQOAQgAAEIFAGAl+VE4tKo8rgTIE+LKa8/JvuHunsAvMlKwhESYAGUpTFWmhQVyq3r0ge5z2u0JzJDAIQgAAEIDCQwC5ade/J4wM3R702t6K7XppGulhyLxIGAQj0QYAGUh/wOPUTU4jB/AmHJ7X0EDsMAhCAAAQgEILAQsrUIxpWCJF5wDyvVt5+Qfsb0r4SBgEI9EmASRr6BFjz03+s+D1bzjvSwtIECYMABCAAAQiEIODeo5ukG0JkHihPT+udjuBYRp+fDuQH2UIgKgL0IEVVnIUHs7lydC+Su/R95wqDAAQgAAEIhCAwvTL9vlS3Z2F/ophHSGdIfv4IgwAEMiBAAykDiDVNwg+ETprEvmNNGRA2BCAAAQiUg4DfezReOqcc7hTihd/3tKvkZ4/+XkiOZAKBmhBgiF1NCjqHMC9Rmn7+6Bnp0RzSJ0kIQAACEIBAJwR8s2576Ujp3U5OiOSYOxWHe86elzySA4MABDIiQAMpI5A1S8YV0axJzB7zjUEAAhCAAARCEVhPGX9KOiGUAwHy3U55zie5QbiF5GeBMQhAAAJREdhG0fghS3eTV8HGysn3pDpNo1qFcsHH+hGYXCH7u2O5+oVOxDkRqFp9ZAyelOGYnHiUMdll5dTb0vvSHmV0EJ9qSSCq+ogepFpew30H/Vul4AaSHw7FIAABCEAAAqEIfFEZu8FwRCgHAuT70yTPB7Q8OED+ZAmB6AnQQIq+iHMJcAal6mePzs0ldRKFAAQgAAEIdEZgtA67VLq3s8OjOGp1RfGmtJLkm5UYBCCQMQFmscsYaA2S8zBA3736g1Snh2FrULSECAEIQKBSBOaQt37+aK1Ked2fs3Pq9P+TrpKe7S8pzoYABAYjQANpMDJsH4zAf7XDs+YsNdgBbIcABCAAAQgUQMCvmLhfurKAvMqSxffkyIrSE2VxCD8gECMBhtjFWKr5xeShdTNL7jk6Or9sSBkCEIAABCDQlsBU2usJJQ5re1RcO/1C2M9K/5EOiSs0ooFAuQjQg1Su8ii7N7+Xg1NIV0gXlt1Z/IMABCAAgWgJbKbIPIPjadFGODCwSbR6n+SblJ7B7jUJgwAEciJAAyknsBEm+ynFtJHkaUX9Mj4MAhCAAAQgEIKAGws7SX4W9o0QDgTIcwHl6WmUPTnDQdJ4CYMABHIiwBC7nMBGmOwOiskNar/7yDMGYRCAAAQgAIEQBNZUpm4wHBMi80B57qZ83TB0zPtKGAQgAIHoCZT9xXwe9/y65OlEV42+NAgQAtUhENWL+aqDPWpPy14fGf7l0p+jLoWBwZ2oVY/eeEuaZ+Au1iBQGgJR1UfuEcAgMBQBzxDkB2Jflm4c6mD2QwACEIAABHIisKjS/ar0xZzSL1uynjHWz1vZ/iE96g8YBCCQLwGG2OXLN5bUZ0kC8TNIdRnvHUvZEQcEIACBmAj4xbDXSf+OKag2sfi9g37u6Hzpa22OYxcEIJAhAXqQMoQZcVIeXneodFnEMRIaBCAAAQiUm8CMcm9Tye8CqoP5N9rakm9mb1uHgIkRAmUhQAOpLCVRXj9+JNcWkTwGGoMABCAAAQiEIvBDZfyc9LdQDhScr1/Kfok0RnLcGAQgUBABhtgVBLrC2ewj3/1wqBtJGAQgAAEIQCAEgWHK1DfsjpA8YVAd7DAFuYbkl7RjEIBAgQToQSoQdgWzWlg+j5Q8OcOvK+g/LkMAAhCAQBwENlAYnlG1LqMZllWsG0p+Ge5fJAwCECiQAD1IBcKuYFaHy+d3pQukhyvoPy5DAAIQgEAcBHZWGCdJvmEXu82tAP3Mr997dI10h4RBAAIFEqAHqUDYFcvKXfp+59Hb0s0V8x13IQABCEAgHgIrKJRlpE3iCaltJOdr73DJs8Z+p+2R7IQABHIhQA9SLlijSPQ3isJjvj3W2y/lwyAAAQhAAAIhCOyiTC+UHgiRecF5LqX8/K4nvxR2RakOPWYKE4NAuQjQg1Su8iiLN74utpI89tkV0oMSBgEIQAACECiagIebrSv55bB1sO8qSL9a40zptjoETIwQKCMBepDKWCrhfTpNLvjaeF7yDDoYBCAAAQhAIASBnZTp3dLVITIvOM9pld9mkkdu7FVw3mQHAQg0EKCB1ACDj/8j4Lt1tqOlcR9+4g8EIAABCECgWALTKDuPZvB013WwsxTkp6Q3pfF1CJgYIVBWAjSQyloy4fzaXVl7iN0t0gHh3CBnCEAAAhCoOYEtFL8nCjq9BhyWVoyrJ3FupKWHuGMQgEAgAjSQAoEvcbZ7Jr5drCVf0CUuKFyDAAQgEDEBT3Ht4XXHSp6wIGZbWcFdJ/k32V+Tz1pgEIAABOpNYBuF78aIhxOEtDmUucc+j5U8FhqDAATKTWByuefvjuXK7SbeVYhAWeqjtcXMDaNZKsSuF1e/rpPekd6XXpFmkjAIVJFAVPURPUhVvATz83kfJT1B2lZ6Lb9sSBkCEIAABCDQloCn9v6L9Gzbo6q9c5jcP1Hyb7EXpTmTpRYYBCAQkoCfNcEgYAL+YvbDsLYNpMs//MQfCEAAAhCAQLEEFld2q0lLFptt4bn5N5h7yZ6S5pPelTAIQKAEBGgglaAQSuLCIfLDY749e84vS+ITbkAAAhCAQP0IjFbI/5Bifw/Q9orRs9b9SKJxJAgYBMpCgAZSWUoivB++W/e0tKb0WHh38AACEIAABGpIYKRi3kjaMPLY/czxz6WpJT+DhEEAAiUiQAOpRIUR0BU3inwX6yXphYB+kDUEIAABCNSbwHYK30POLowcgxtFYyU/Y3WGhEEAAiUi4AcDMQj8WgjcvX+R5F4kDAIQgAAEIFA0gcmVoRtIh0ue1S1mc++RZ451vYtBAAIlI0ADqWQFEsCdhZXn55J8bwyQP1lCAAIQgAAETMBD6zzk7CSvRGyeunxLycPs7oo4TkKDQGUJMMSuskWXmeOXJCl5Jp0zM0uVhCAAAQhAAALdEdhZh3va61e7O61SR7sBeK80QhonXSNhEIBAyQjQQCpZgRTszgzKz1OL+kWTB0p+DwMGAQhAAAIQKJrAysrQoxm+U3TGBebn31znSMMlv3Pw25LrXwwCECgZARpIJSuQgt05Rvn5y/lU6TcF5012EIAABCAAgZSAXwz7N+mRdEOEy4sV01eTuH6oJb1HERYyIcVBgAZSHOXYSxST6qRRkidn+GcvCXAOBCAAAQhAIAMCHsmwjrRKBmmVNYnj5JgbR74p6RuSvjGJQQACJSXwyZL6hVv5E9hfWUwr+dkjZtHJnzc5QAACEIBAawJ+9sgvhf1X692V3zqzIthUcuPIIzf2lDAIQKDEBOhBKnHh5Ozarkn6rpCeyzkvkocABCAAAQi0IjCdNm4hbd9qZyTbHKNnib1J8vTeGAQgUHIC9CCVvIBycs+VkYfYPST5rhYGAQhAAAIQCEFgK2XqCQvOCpF5AXm6QXSftJLEzcgCgJMFBLIgQAMpC4rVS8Mv4ntb+qs0vnru4zEEIAABCERAwL9BdpSOllwnxWbLKqB9Jcf5unS+hEEAAhCAQIcEttFxHpvsl8blbbMrA0/McKs0Rd6ZkT4EIJArgcmVur87lss1FxKvE4Ei66N1BfYNaWSEgKdUTM9I70i3SMMkDAIxE4iqPqIHKeZLtXVsh2mzy31BaarWh7AVAhCAAAQgkDsBT+3t2dyezz2n4jPwRAxu+LkBOEpyQwmDAAQqQoBJGipSUBm56QbRNyQPZTheeknCIAABCEAAAkUTWFIZ+rmcHYrOuID8Zkziel9LP2PFs0cFQCcLCGRJgB6kLGmWP62t5aIbSb6jdUD53cVDCEAAAhCIlMBoxfV36c7I4vOMdQ9LI6RHpLMlDAIQqBgBepAqVmB9uvs7ne/nFfzlTe9RnzA5HQIQgAAEeiIwq876rvTtns4u90n7yj03kjykjlliBQGDQBUJ0INUxVLrzecf6TQ3iP1i2N0kN5QwCEAAAhCAQNEEXB+NlS4pOuOc8/NkKR6p4YmQ1pJuljAIQAACEOiRQBGzBj0t3/zs0W979JHTIACB8hGIatag8uGtpUd510eePfU5yY2kmGwPBeOGkZ87GithEKgbgajqI4bY1ePyXUJhziK9Kf2+HiETJQQgAAEIlJCAh515yuuTS+hbLy55JM4B0q6SP78grS5hEIBAhQnQQKpw4XXh+h917HvS5ZJ7kjAIQAACEIBACAI7K1PPouoXp1bdVlMAZ0ifSgK5Q0vPzscQ9gQICwhUlQANpKqWXOd+r6xDvyj5gVFP0oBBAAIQgAAEQhD4ijL9jOTXTVTdLlMAayRBuEF0nfR1icZRAoUFBKpMgEkaqlx6Q/s+kw7xl7jtFYkHRj9EwR8IQAACEAhAwC+GPUd6LEDeWWa5sRJz75HtWck3IleSYugVUxgYBCBAD1K818BwhXaF5AdiPTnDQslSCwwCEIAABCBQKIEFldsoaYVCc80nsx2VrCdkOEnaNp8sSBUCEAhJgAZSSPr55v1PJf+5JAt3+4/PNztShwAEIAABCAxKwM8e3SLdMOgR1dixvNxcTHpNco8YBgEIREiAIXYRFqpCcsN3Xsljof8tXS1hEIAABCAAgRAEplemm0mHhcg8wzz3Ulq++TiV9FfpDQmDAAQiJEAPUnyFOqNCuk2aWppEcqWEQQACEIAABEIR2FoZvyy5UVFV+7Mc97NHrlcnSL+VMAhAIFIC9CDFV7BHKKQ5JL9nYox0j4RBAAIQgAAEQhCYVJnuIB0l+bmdKtqecnpDyY0jDxGcVXpUwiAAAQhAIEcC2yhtD4ebps88ptX5Hhf9luRpvdMpSPURgwAEIiQQ1ZvLIyyfKoaUVX2Uxr6+PrjHxaMbqmb+//qN5ImO/C5Bz8CHQQACrQlEVR8xxK51IVd162g57obWU5LHRl8pYRCAAAQgAIFQBDyRwcnSuFAO9JjvkTpvOykdaXO7Pm/QY1qcBgEIVIwADaSKFVgbd931v4bkO10zSL+W3FjCIAABCEAAAiEIfEGZLif5GaSqmBtEZ0jfkVyvvi/dKrl+dS8SBgEI1IBAemekBqFGH+LiinApyY1ef4mfKmEQgAAEIACBUAQ8quFyqSrPwm4pXz36Yj3JjaMrpCmkZaWXJQwCEKgJAXqQ4iloP0DqL3b3Gh0vecw3BgEIQAACEAhBYA5l6obG2iEy7zJPT0N+s7RAcp7rUc9at4XESIwECgsI1IkAPUjxlLbHR18n+Yv+mHjCIhIIQAACEKggge3l84OSe2HKbl+Vg/MmTrq3y8PUN5doHAkCBgEIQCAUgX5nDfI7j16S/PzR6aGCIF8IQKBwAlHNGlQ4PTJsRaDf+shp+kWqL0g/8ErJbWH559lfPepij5L7insQKDOBqOojepDKfKl17tuuOtQVkodMHt75aRwJAQhAAAIQyJzA95Win+HxMLUymxuDt0muP91IOlbCIAABCECgJAT6uWPnIXX+YvdMO/eXJB7cgAAEiiEQ1R27YpCRyxAE+qmP0qTv1odfpSslXe4pv/ziWtedrkMXkjAIQKB3AlHVR/Qg9X4hlOXM3eSI31TuL/lflMUp/IAABCAAgVoS+JqiXlA6usTR/1K+We7lekCyv9xgFAQMAhCYSIBZ7Kp9JXj6UQ9lcAPpRekcCYMABCAAgWoQ8GQAIyR/l7sXw8+Svi5V2XaR82dLT5YwCN9QdMPIvG2e3GgZifcbmQYGAQj8j0AdG0gxVUifV0lOK3mmnUMlDxfAIAABCECgvASWlGue4W0daWQLNx/Wtr9Le0nPt9hf5k2LyDn3IPm9QWWy+eTMX6RGv67W+hoSjSNBwCAAgXoScIV0gvSc5MZEsx7StuOkVpWVNuduvY75/q088x3Ht6QZc/eSDCAAgbIRiGrMd9ng5uDP3kozrX8e1efrpYukM6RLpZukpyUf41ngNpaKtl7rI/v5B+m6oh0eIr/faL8bQR6G7uUt0swSBgEIZEuA+ihbnrmnFnOFNK/oPSj5xbAYBCBQPwJUSNUp8/Xlqhs+bggt1cZtPxezkuQf8j5+ealI67WB5Jt0Hh64XpHOtslrNe27W0obR76R6IkZMAhAIB8C1Ef5cM0l1ZgrpAVF7BXJd8UWzYUeiUIAAmUnQIVU9hL6yL/T9NGjFdLnXz7a0/qTh4P7O969MkVarw0kv0PIvWJ+JjakzarMPVrEdWMq98xhEIBAvgSoj/Llm2nqMVdI14mU74z5jh0GAQjUkwAVUnXK/U65emqX7l6r4y/s8px+D++lgeTnmR+Xftpv5j2e796rX0qeke5tKW0Y+RmufSX7h0EAAvkSiKo+iv1LYwldCzdI7lrvxMbroDukOTo5OOAxcylvP1floRg/COgHWUMAAhCAQGcE/GzR0tIw6Z0OTnEPkuswPx9bdvNoDfvrZ32LMvfEjZJ+LqX1YZq3+XqInW8kYhCAAAQg0ETgCq3fI7lC6sT8Be8hDQd3cnCGx3R7x85DLt6U3KBzIwmDAATqSSCqO3aRF+Emis/PFF0gNc6m1hy2v9O/LHlY2LvSClKR1m19ZN/s65EFOrm98npNSnuKvHSj6GHpd9LsEgYBCBRLgPqoWN595RZjhTSdiHjYgCuEfSUMAhCoLwEqpOqUvRs+oyUPi3ZD6QnpRuli6fRk6REPT0ne7x/8O0tFW7cNpOXkoOujBXN21C+2P1YyF+eX6mV93lvCIACBsASoj8Ly7yr3GCskD4u8S/Kwwam7osHBEIBAbASokKpXovPLZTeInpTcEGqUG08PSIdIHkodwrptIJ0lJ/N6TmohpX2M9IjkZ27TRpE/e3TIpyUMAhAoBwHqo3KUQ1dexFQh7ajIPezi7K4IcDAEIBAjASqkapfqcLnvhpB7X0aUJJRuGkhzy2f36HwlA999Q3M2yXXcNdIbUtogSpeu+86TPJICgwAEykUgqvoo9kka0kvnYX3YKFlxheSKaErJU4G6e74qNq0cPVDyUIN/VsVp/IQABCAAgZYE/MyrVVXbQY67J+eqLgKYR8d+WfLrKT4jLSP5xa3DpFbmWekek/4o+Tknj57AIAABCORKoC4NpEaIVa6QplIgfseEn0E6qjEoPkMAAhCAAAQKJOCJENzbc5t0muS6yXeQfSNvRsk3I6eXPBTcvzW83zf33FPUztxb9JJ0rbSLNFbCIAABCBRKoI4NpCIAuyIYJQ12R6zZhyWbNwyyfpC2u5F0/CD72QwBCEAAAnEQ2E5h/FDyxASeubRXm18n3iq58dKJuf6yuaHSzs7QzimkZRO1O7Z5n9P2c0QeRjdWuly6SLpZoodIEDAIQCAsARpIA/lnVSHNrWRdoXVaIaUNKY+vbme+IzdeOq7dQeyDAAQgAIHKE5hFESwhedmPjdXJG0hpPTNUWovqAE8S4QbMYOZeIA+Ve1Vyr5DNk0244eN6zJNNvCY9J3mChWelx6Wx0g2S6zEMAhCAAAQqQmBf+ekv+X0K9ne5JN92DSoPVXCFs2HBvpEdBCBQXgL+zvB3lr9DsLgIZNVA6pZKJ/WRR0i8Jc3abeIcDwEIREuA+ijaop14py6LO3bdIuqkQtpViT4h0evXLV2Oh0C8BKiQ4i3bUJF1Uh9dKedODuUg+UIAAqUkEFV9xI/tgdeYhwFYZTOPCd9e8sQMQw3DK5vv+AMBCEAAAq0JzKDNnlXVz/J4hIAnJ/DwtDLbZ+Xc6tJSZXYS3yAAAQhAoDsCrpDmlRaW5pCmkULbUHfs1pODEyTPDIRBAAIQSAlEdccuDSrypSflOUHy8zkeHtmsh7TtOGmkFMKGqo/s+z9DOEaeEIBAqQlQH5W6eFo7V/UK6VqF1c8sRq2psBUCEKg6ASqkapXg3nI3bRA9qs/XSxdJnhHuUukm6WnJx7wgbSwVbe0aSJ+SM29I3yraKfKDAARKT4D6qPRFNNDBqldIyygczwy06MCwWIMABCDw4UyZ/jHtH7VYuQmsL/dcVm4ItRueNon2ryTdIvn45aUirV0DaS858rCUzlxXpF/kBQEIlJsADaRyl88A72KokE5VRJcNiIoVCEAAAhMJUCFV50rwy1Q9fM7PG3ViHg7+ilT06IHBGki+1p6S/PJWDAIQgEAzAeqjZiIlXq96hTSb2L4trVlixrgGAQiEI0CFFI59tznfqRN8w6sb8/DqC7s5IYNjB2sgfU9pu8Hm9/FhEIAABJoJRFUfxd5N7im7b5Deai7FQdb98ro7JE/eUAbzzHW+43h5GZzBBwhAAAIQ6JmAny1aWur0ha3uQXIddq9UBnPP0YmSG0kYBCAAgagJxN5AqnKFNKWuvG2lwyWPQ8cgAAEIQKC6BE6W64tI50jLtgnDzyB9WfLQ6qmlv0mhzf58XjoytCPkDwEIQAAC/RPYREm4cXGB1EmF5BmE/J6hFaQirdWQhq3lwDjJFSQGAQhAoBWBqIY0tAowom1u+IyW/J4j10tPSDdKF0unJ8sbtHxK8v53pJ2loq1VfXSunDivaEfIDwIQqBQB6qMKFVeVKySPV/9NhVjjKgQgUDwBKqTimfeb4/xKwA2iJyU3hBrlxtMD0iHSXFIIa24gzScn3pNWDuEMeUIAApUhQH1UmaL6yNGqVUiry3XfPQxVQX5Ejk8QgECZCVAhlbl0hvZtuA7x9/yC0oihDy/kiOYG0qHKdUwhOZMJBCBQZQLUR1UuPflehQopfXFgxVHjPgQgkDMBKqScAdcw+cYG0nSK/2Xp+zXkQMgQgEB3BKKqjybrLvYojvYMPGWehcd3EteSin45YBSFSxAQgAAEIJAZgS2V0gTpjMxSJCEIQAACFSAQ+yx2FSiCj7noh3L9BnU/vItBAAIQgAAEQhDwM7w7SsdKfh8fBgEIQKA2BOrYg1TmwvUY9M2kH5TZSXyDAAQgAIHoCXxDEc4puYGEQQACEKgVAXqQylXcHs7g8d5nl8stvIEABCAAgZoRcO/RadLzNYubcCEAAQh8gh6kcl0E28mdoyW/iwmDAAQgAAEIhCLgab3dSMIgAAEI1I4APUjlKvKZ5c4fy+US3kAAAhCAQA0JXK2Y/T4+DAIQgEDtCNCDVK4i98sDX5U8VeJg5jLzw7MYBCAQN4EPFN5QvcntvivipkN0eRM4RhkMdX1RH+VdCqQPgXIQqF19RAOpHBeeXwpr8zNIFgYBCECgGwLMMtYNLY5tRyCtj3gWth0l9kEAAoMRiKI+oidisOItfvsyynLYENluqP3flvYb4riy755eDh4k7SlV/QHgnymGW6UrpCrbGnJ+aenXVQ5Cvo+UDpR2k16Sqmx7y/lzpaHeQePKyNcgBoGsCFAfZUWy2HSoj4rlPVRu1EdDEWI/BDIisJPSuT2jtEIm46lj3V27QEgnMsr7JqXjH+NVN8fgWKpuvqZ8bfkaq7r5f93/8xgEykiA+qh8pUJ9VK4yoT4qV3l05Q2TNHSFi4MhAAEIQAACEIAABCAAgZgJ0ECKuXSJDQIQgAAEIAABCEAAAhDoigANpK5wcTAEIAABCEAAAhCAAAQgEDMBGkgxly6xQQACEIAABCAAAQhAAAJdEaCB1BUuDoYABCAAAQhAAAIQgAAEYiZAAynm0iU2CEAAAhCAAAQgAAEIQKArAjSQusLFwRCAAAQgAAEIQAACEIBAzARoIMVcusQGAQhAAAIQgAAEIAABCHRFgAZSV7g4GAIQgAAEIAABCEAAAhCImQANpGqV7jty9+1qudzS2zSGdNnyoIpsdAwul6ob11b5StDXVgz/I+Uji0dZEOA7IwuK2aZBfZQtz35TS7+/02W/6YU83zHEEEdIhuSdI4EplfacOaZfZNILFJlZjnnNrrSnyjH9opJ2DI4lBovl2vL/uv/nMQiUkQD1UflKhfqofGVCfVS+MsEjCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCEAAAhCAAAQgAAEIQAACEIAABCAAAQhAAAIQgAAEIAABCECgXAQmLZc7tfXG5bCc9EXpXWmc1K3NqRNWlrx8TnpHCmH9+jG1nF5KWkGaXnpFeksq2vqNo9nf1bRhNunx5h05r2dxbQ2Tj5+XXCZTSc9KH0hFW79lMqUcXlpaXppWekF6Twpl8yrjUdKdPTjQL4sesuSUmhDI4jujLNdnv35QH2V70WdxbVEfZVsmaWrz6gP1UUqDZSkILCgv7pH8gzPV3fo8l9Sp/VIHukGUnv+uPu/W6ckZHtevH9+XL+mP7zQWN5B2ytDHTpLqN47mPNbSBsdzefOOnNezuLa+IR/HS2l5ePlvyWkXaf2WiRuoY6XGOB7RureHsOHK9L/Sqz1k3i+LHrLklJoQyOI7oyzXZ79+UB9le9FncW1RH2VbJmlq1EcpCZalITCJPLlGciNgU2kBaRtpgvSoNI00lH1VB/hH37nSkpJ7oS6TvG1HqSjr1w+f/77kH60/kz4ruWF0r+RYvicVYf3G0ezjSG14RnIMRTaQsri21pbPLhP3cKwr+fo6VnID3NuGSUVYv2Uyt5x8SXJDzzcOFpN2lV6UXpbmlYq0GZRZ+j/abQOpXxZFxkle1SKQxXdGWa7Pfv3w+dRH2V2/WVxb1EfZlUdjStRHjTT4XBoC28kT/3DetsmjbQbZ3nTYJ9z97wbFE5K7rlObXB+8/XGpcXu6P+tlFn5cLafMYo0m576QbHevWt6WRRzNPp6vDc9Jjq3IBlK/15bjuEVy431BrzTYmfrseFZp2JbXxyzK5Kdyzv7u1+Tkvsn2vZq257m6rhJ/Ksn3LS27aSBlwSLP2Ei72gT6/c4oy/WZhR9Xqyj9nUF9lM013e+1ZS+oj7Ipi8ZUqI8aafC5VARukjdvSn7WptHc3fmG5C+EdvZ17fSX+G9aHHRgsm9Ui31Zb+rXj0/KoZslN4JaNejci+Rei1b7tDkz6zeOZkd+oA0un28lS/caFGX9Xlsry1H7vkcLhz388yvSzC32Zb0pizLx/4djWafJudWS7Uc3bc9rNY3lBWVgX8ZI3TSQ0vND/7/nxYd0wxLo9zujLNdnv35QH2V/HfZ7bVEfZV8m6f8J9dEgbP1FgIUhMEzZ+sH3+yUP/2k037V3o+Bzko8bzDyczubGRbOl25Zp3pHDer9+eCiD01hMan5ofkptm00a22KfNmVq/cbR6Ix7XQ6V/OO7yIaRfcji2lraCcmumLj4xAgtPUnDSOlx6SrpOSlvy6JMrkyc3LzJ2c2S9XR/0+7MV93IP0BaSLqgh9SzYNFDtpxSAwJZfGeU5frs1w/qo2wv+CyuLeqjbMvEqVEfDcGUBtIQgHLc7XGfk0t+DqKVjdNGf7H4B+lgNkuyo1UaPt82x8RFrn/z9GN3eT5cOifXCCYmnlUckym50yQPfdxtYtKF/s3i2poz8djP7Vwo+Xq6VnKjyGUxk1SEZVEm/5Cj+0nrSHdJ7oEZI/m5tkOli6UizA2xX0hm2YtlwaKXfDknfgJZfGeU5frM04/ddSkMl6iPOv+fyOLaoj7qnHenR1IfDUHKP+SwMAT8JWtz92YrS39ETdNqZ7KtXRqdnN8m6a525eXHBvJib+kBaV8pb8sqjn3k6JKSp5OeILkXrEhrF4f96OTaSBvW/iHgoY0eLviatJH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      "text/plain": [
       "plot without title"
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   "source": [
    "# Clustering Effect on Two sample problem\n",
    "sim.twosample.clustered=function(nk,n,se,sb,verbose=FALSE)\n",
    "    {\n",
    "        N=n*nk\n",
    "        e0=rnorm(N,0,se)\n",
    "        e1=rnorm(N,0,se)\n",
    "        b0=rep(rnorm(n,0,sb),each=nk)\n",
    "        b1=rep(rnorm(n,0,sb),each=nk)\n",
    "        y0=e0+b0\n",
    "        y1=e1+b1\n",
    "        t.test(y0,y1)$p.value\n",
    "    }\n",
    "\n",
    "set.seed(2314)\n",
    "B=1000\n",
    "# Simulate with no clustering effect (sb=0)\n",
    "pval0=replicate(B,sim.twosample.clustered(3,10,0.25,0))\n",
    "# Simulate with no clustering effect (sb>0)\n",
    "pval1=replicate(B,sim.twosample.clustered(3,10,0.25,0.5))\n",
    "rm(B)\n",
    "\n",
    "mean(pval0<0.05)\n",
    "mean(pval1<0.05)\n",
    "par(mfrow=c(1,2))\n",
    "qqplot(qunif(ppoints(500)), pval0,cex=0.1,xlab=\"Uniform Distribution\")\n",
    "abline(0,1)\n",
    "qqplot(qunif(ppoints(500)), pval1,cex=0.1,xlab=\"Uniform Distribution\")\n",
    "abline(0,1)"
   ]
  },
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   "outputs": [],
   "source": []
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