Hypothesis_INT.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Hypothesis\n",
    "DV1=INT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>'ACYN'</li>\n",
       "\t<li>'Age'</li>\n",
       "\t<li>'Atti'</li>\n",
       "\t<li>'Atti1'</li>\n",
       "\t<li>'Atti2'</li>\n",
       "\t<li>'Atti3'</li>\n",
       "\t<li>'Atti4'</li>\n",
       "\t<li>'Attitude'</li>\n",
       "\t<li>'AwayS'</li>\n",
       "\t<li>'AwaySNY'</li>\n",
       "\t<li>'AwayW'</li>\n",
       "\t<li>'AwayWNY'</li>\n",
       "\t<li>'BillS'</li>\n",
       "\t<li>'BillW'</li>\n",
       "\t<li>'CashYN'</li>\n",
       "\t<li>'City'</li>\n",
       "\t<li>'ComfNS'</li>\n",
       "\t<li>'ComfNS1'</li>\n",
       "\t<li>'ComfNS2'</li>\n",
       "\t<li>'ComfNS3'</li>\n",
       "\t<li>'ComfNW'</li>\n",
       "\t<li>'ComfNW1'</li>\n",
       "\t<li>'ComfNW2'</li>\n",
       "\t<li>'ComfortS'</li>\n",
       "\t<li>'ComfortW'</li>\n",
       "\t<li>'CompR'</li>\n",
       "\t<li>'ControlN1'</li>\n",
       "\t<li>'ControlN2R'</li>\n",
       "\t<li>'ControlN3'</li>\n",
       "\t<li>'ControlN4'</li>\n",
       "\t<li>'ConvB1'</li>\n",
       "\t<li>'ConvB2'</li>\n",
       "\t<li>'ConvB3'</li>\n",
       "\t<li>'ConvB4'</li>\n",
       "\t<li>'DeviceType'</li>\n",
       "\t<li>'Educ'</li>\n",
       "\t<li>'EmerRForm'</li>\n",
       "\t<li>'EnergyC'</li>\n",
       "\t<li>'EnergyC1'</li>\n",
       "\t<li>'EnergyC2'</li>\n",
       "\t<li>'EnergyC3'</li>\n",
       "\t<li>'EnergyC4'</li>\n",
       "\t<li>'Ethnic'</li>\n",
       "\t<li>'Frugal'</li>\n",
       "\t<li>'Frugal1'</li>\n",
       "\t<li>'Frugal2'</li>\n",
       "\t<li>'Frugal3'</li>\n",
       "\t<li>'Gender'</li>\n",
       "\t<li>'HTdevice'</li>\n",
       "\t<li>'HTsource'</li>\n",
       "\t<li>'HabitC'</li>\n",
       "\t<li>'HabitC1'</li>\n",
       "\t<li>'HabitC2'</li>\n",
       "\t<li>'HabitC3'</li>\n",
       "\t<li>'HabitC4'</li>\n",
       "\t<li>'HabitC5'</li>\n",
       "\t<li>'HabitC6'</li>\n",
       "\t<li>'HabitC7'</li>\n",
       "\t<li>'HabitE1'</li>\n",
       "\t<li>'HabitE2'</li>\n",
       "\t<li>'HabitE3'</li>\n",
       "\t<li>'HabitG'</li>\n",
       "\t<li>'HeatYN'</li>\n",
       "\t<li>'HomeS'</li>\n",
       "\t<li>'HomeSYN'</li>\n",
       "\t<li>'HomeW'</li>\n",
       "\t<li>'HomeWYN'</li>\n",
       "\t<li>'HouseholdS'</li>\n",
       "\t<li>'ID'</li>\n",
       "\t<li>'INT'</li>\n",
       "\t<li>'INT1'</li>\n",
       "\t<li>'INT2'</li>\n",
       "\t<li>'INT3'</li>\n",
       "\t<li>'INT4'</li>\n",
       "\t<li>'IncAutoS'</li>\n",
       "\t<li>'IncAutoW'</li>\n",
       "\t<li>'IncAwayS'</li>\n",
       "\t<li>'IncAwayW'</li>\n",
       "\t<li>'IncDish'</li>\n",
       "\t<li>'IncEmer10S'</li>\n",
       "\t<li>'IncEmer10W'</li>\n",
       "\t<li>'IncEmer30S'</li>\n",
       "\t<li>'IncEmer30W'</li>\n",
       "\t<li>'IncHomeS'</li>\n",
       "\t<li>'IncHomeW'</li>\n",
       "\t<li>'IncWD'</li>\n",
       "\t<li>'Income'</li>\n",
       "\t<li>'Job'</li>\n",
       "\t<li>'Latitude'</li>\n",
       "\t<li>'Longitude'</li>\n",
       "\t<li>'MC'</li>\n",
       "\t<li>'MC1'</li>\n",
       "\t<li>'MC2'</li>\n",
       "\t<li>'MC3'</li>\n",
       "\t<li>'MC4'</li>\n",
       "\t<li>'MC5'</li>\n",
       "\t<li>'MCBill'</li>\n",
       "\t<li>'MCG'</li>\n",
       "\t<li>'NBillS'</li>\n",
       "\t<li>'NBillW'</li>\n",
       "\t<li>'OwnRent'</li>\n",
       "\t<li>'PBC'</li>\n",
       "\t<li>'PBC1'</li>\n",
       "\t<li>'PBC2'</li>\n",
       "\t<li>'PBC3R'</li>\n",
       "\t<li>'PBC4'</li>\n",
       "\t<li>'PBC5'</li>\n",
       "\t<li>'PBillStatus'</li>\n",
       "\t<li>'Political'</li>\n",
       "\t<li>'ReasonNeg'</li>\n",
       "\t<li>'ReasonPos'</li>\n",
       "\t<li>'RewardForm'</li>\n",
       "\t<li>'SN'</li>\n",
       "\t<li>'SN1'</li>\n",
       "\t<li>'SN2'</li>\n",
       "\t<li>'SN3'</li>\n",
       "\t<li>'SN4'</li>\n",
       "\t<li>'Sqft'</li>\n",
       "\t<li>'SqftCate'</li>\n",
       "\t<li>'State'</li>\n",
       "\t<li>'SubN'</li>\n",
       "\t<li>'SubNorm'</li>\n",
       "\t<li>'SubNorm1'</li>\n",
       "\t<li>'SubNorm2'</li>\n",
       "\t<li>'SubNorm3'</li>\n",
       "\t<li>'Summer_avg'</li>\n",
       "\t<li>'Summer_avgC'</li>\n",
       "\t<li>'Summer_avgF'</li>\n",
       "\t<li>'Trust'</li>\n",
       "\t<li>'Trust1'</li>\n",
       "\t<li>'Trust2'</li>\n",
       "\t<li>'Trust3'</li>\n",
       "\t<li>'Trust4'</li>\n",
       "\t<li>'Utility'</li>\n",
       "\t<li>'Winter_avg'</li>\n",
       "\t<li>'Winter_avgC'</li>\n",
       "\t<li>'Winter_avgF'</li>\n",
       "\t<li>'X.9to5'</li>\n",
       "\t<li>'cold'</li>\n",
       "\t<li>'hot'</li>\n",
       "\t<li>'row'</li>\n",
       "\t<li>'valid'</li>\n",
       "\t<li>'valid1'</li>\n",
       "\t<li>'valid2'</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'ACYN'\n",
       "\\item 'Age'\n",
       "\\item 'Atti'\n",
       "\\item 'Atti1'\n",
       "\\item 'Atti2'\n",
       "\\item 'Atti3'\n",
       "\\item 'Atti4'\n",
       "\\item 'Attitude'\n",
       "\\item 'AwayS'\n",
       "\\item 'AwaySNY'\n",
       "\\item 'AwayW'\n",
       "\\item 'AwayWNY'\n",
       "\\item 'BillS'\n",
       "\\item 'BillW'\n",
       "\\item 'CashYN'\n",
       "\\item 'City'\n",
       "\\item 'ComfNS'\n",
       "\\item 'ComfNS1'\n",
       "\\item 'ComfNS2'\n",
       "\\item 'ComfNS3'\n",
       "\\item 'ComfNW'\n",
       "\\item 'ComfNW1'\n",
       "\\item 'ComfNW2'\n",
       "\\item 'ComfortS'\n",
       "\\item 'ComfortW'\n",
       "\\item 'CompR'\n",
       "\\item 'ControlN1'\n",
       "\\item 'ControlN2R'\n",
       "\\item 'ControlN3'\n",
       "\\item 'ControlN4'\n",
       "\\item 'ConvB1'\n",
       "\\item 'ConvB2'\n",
       "\\item 'ConvB3'\n",
       "\\item 'ConvB4'\n",
       "\\item 'DeviceType'\n",
       "\\item 'Educ'\n",
       "\\item 'EmerRForm'\n",
       "\\item 'EnergyC'\n",
       "\\item 'EnergyC1'\n",
       "\\item 'EnergyC2'\n",
       "\\item 'EnergyC3'\n",
       "\\item 'EnergyC4'\n",
       "\\item 'Ethnic'\n",
       "\\item 'Frugal'\n",
       "\\item 'Frugal1'\n",
       "\\item 'Frugal2'\n",
       "\\item 'Frugal3'\n",
       "\\item 'Gender'\n",
       "\\item 'HTdevice'\n",
       "\\item 'HTsource'\n",
       "\\item 'HabitC'\n",
       "\\item 'HabitC1'\n",
       "\\item 'HabitC2'\n",
       "\\item 'HabitC3'\n",
       "\\item 'HabitC4'\n",
       "\\item 'HabitC5'\n",
       "\\item 'HabitC6'\n",
       "\\item 'HabitC7'\n",
       "\\item 'HabitE1'\n",
       "\\item 'HabitE2'\n",
       "\\item 'HabitE3'\n",
       "\\item 'HabitG'\n",
       "\\item 'HeatYN'\n",
       "\\item 'HomeS'\n",
       "\\item 'HomeSYN'\n",
       "\\item 'HomeW'\n",
       "\\item 'HomeWYN'\n",
       "\\item 'HouseholdS'\n",
       "\\item 'ID'\n",
       "\\item 'INT'\n",
       "\\item 'INT1'\n",
       "\\item 'INT2'\n",
       "\\item 'INT3'\n",
       "\\item 'INT4'\n",
       "\\item 'IncAutoS'\n",
       "\\item 'IncAutoW'\n",
       "\\item 'IncAwayS'\n",
       "\\item 'IncAwayW'\n",
       "\\item 'IncDish'\n",
       "\\item 'IncEmer10S'\n",
       "\\item 'IncEmer10W'\n",
       "\\item 'IncEmer30S'\n",
       "\\item 'IncEmer30W'\n",
       "\\item 'IncHomeS'\n",
       "\\item 'IncHomeW'\n",
       "\\item 'IncWD'\n",
       "\\item 'Income'\n",
       "\\item 'Job'\n",
       "\\item 'Latitude'\n",
       "\\item 'Longitude'\n",
       "\\item 'MC'\n",
       "\\item 'MC1'\n",
       "\\item 'MC2'\n",
       "\\item 'MC3'\n",
       "\\item 'MC4'\n",
       "\\item 'MC5'\n",
       "\\item 'MCBill'\n",
       "\\item 'MCG'\n",
       "\\item 'NBillS'\n",
       "\\item 'NBillW'\n",
       "\\item 'OwnRent'\n",
       "\\item 'PBC'\n",
       "\\item 'PBC1'\n",
       "\\item 'PBC2'\n",
       "\\item 'PBC3R'\n",
       "\\item 'PBC4'\n",
       "\\item 'PBC5'\n",
       "\\item 'PBillStatus'\n",
       "\\item 'Political'\n",
       "\\item 'ReasonNeg'\n",
       "\\item 'ReasonPos'\n",
       "\\item 'RewardForm'\n",
       "\\item 'SN'\n",
       "\\item 'SN1'\n",
       "\\item 'SN2'\n",
       "\\item 'SN3'\n",
       "\\item 'SN4'\n",
       "\\item 'Sqft'\n",
       "\\item 'SqftCate'\n",
       "\\item 'State'\n",
       "\\item 'SubN'\n",
       "\\item 'SubNorm'\n",
       "\\item 'SubNorm1'\n",
       "\\item 'SubNorm2'\n",
       "\\item 'SubNorm3'\n",
       "\\item 'Summer\\_avg'\n",
       "\\item 'Summer\\_avgC'\n",
       "\\item 'Summer\\_avgF'\n",
       "\\item 'Trust'\n",
       "\\item 'Trust1'\n",
       "\\item 'Trust2'\n",
       "\\item 'Trust3'\n",
       "\\item 'Trust4'\n",
       "\\item 'Utility'\n",
       "\\item 'Winter\\_avg'\n",
       "\\item 'Winter\\_avgC'\n",
       "\\item 'Winter\\_avgF'\n",
       "\\item 'X.9to5'\n",
       "\\item 'cold'\n",
       "\\item 'hot'\n",
       "\\item 'row'\n",
       "\\item 'valid'\n",
       "\\item 'valid1'\n",
       "\\item 'valid2'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'ACYN'\n",
       "2. 'Age'\n",
       "3. 'Atti'\n",
       "4. 'Atti1'\n",
       "5. 'Atti2'\n",
       "6. 'Atti3'\n",
       "7. 'Atti4'\n",
       "8. 'Attitude'\n",
       "9. 'AwayS'\n",
       "10. 'AwaySNY'\n",
       "11. 'AwayW'\n",
       "12. 'AwayWNY'\n",
       "13. 'BillS'\n",
       "14. 'BillW'\n",
       "15. 'CashYN'\n",
       "16. 'City'\n",
       "17. 'ComfNS'\n",
       "18. 'ComfNS1'\n",
       "19. 'ComfNS2'\n",
       "20. 'ComfNS3'\n",
       "21. 'ComfNW'\n",
       "22. 'ComfNW1'\n",
       "23. 'ComfNW2'\n",
       "24. 'ComfortS'\n",
       "25. 'ComfortW'\n",
       "26. 'CompR'\n",
       "27. 'ControlN1'\n",
       "28. 'ControlN2R'\n",
       "29. 'ControlN3'\n",
       "30. 'ControlN4'\n",
       "31. 'ConvB1'\n",
       "32. 'ConvB2'\n",
       "33. 'ConvB3'\n",
       "34. 'ConvB4'\n",
       "35. 'DeviceType'\n",
       "36. 'Educ'\n",
       "37. 'EmerRForm'\n",
       "38. 'EnergyC'\n",
       "39. 'EnergyC1'\n",
       "40. 'EnergyC2'\n",
       "41. 'EnergyC3'\n",
       "42. 'EnergyC4'\n",
       "43. 'Ethnic'\n",
       "44. 'Frugal'\n",
       "45. 'Frugal1'\n",
       "46. 'Frugal2'\n",
       "47. 'Frugal3'\n",
       "48. 'Gender'\n",
       "49. 'HTdevice'\n",
       "50. 'HTsource'\n",
       "51. 'HabitC'\n",
       "52. 'HabitC1'\n",
       "53. 'HabitC2'\n",
       "54. 'HabitC3'\n",
       "55. 'HabitC4'\n",
       "56. 'HabitC5'\n",
       "57. 'HabitC6'\n",
       "58. 'HabitC7'\n",
       "59. 'HabitE1'\n",
       "60. 'HabitE2'\n",
       "61. 'HabitE3'\n",
       "62. 'HabitG'\n",
       "63. 'HeatYN'\n",
       "64. 'HomeS'\n",
       "65. 'HomeSYN'\n",
       "66. 'HomeW'\n",
       "67. 'HomeWYN'\n",
       "68. 'HouseholdS'\n",
       "69. 'ID'\n",
       "70. 'INT'\n",
       "71. 'INT1'\n",
       "72. 'INT2'\n",
       "73. 'INT3'\n",
       "74. 'INT4'\n",
       "75. 'IncAutoS'\n",
       "76. 'IncAutoW'\n",
       "77. 'IncAwayS'\n",
       "78. 'IncAwayW'\n",
       "79. 'IncDish'\n",
       "80. 'IncEmer10S'\n",
       "81. 'IncEmer10W'\n",
       "82. 'IncEmer30S'\n",
       "83. 'IncEmer30W'\n",
       "84. 'IncHomeS'\n",
       "85. 'IncHomeW'\n",
       "86. 'IncWD'\n",
       "87. 'Income'\n",
       "88. 'Job'\n",
       "89. 'Latitude'\n",
       "90. 'Longitude'\n",
       "91. 'MC'\n",
       "92. 'MC1'\n",
       "93. 'MC2'\n",
       "94. 'MC3'\n",
       "95. 'MC4'\n",
       "96. 'MC5'\n",
       "97. 'MCBill'\n",
       "98. 'MCG'\n",
       "99. 'NBillS'\n",
       "100. 'NBillW'\n",
       "101. 'OwnRent'\n",
       "102. 'PBC'\n",
       "103. 'PBC1'\n",
       "104. 'PBC2'\n",
       "105. 'PBC3R'\n",
       "106. 'PBC4'\n",
       "107. 'PBC5'\n",
       "108. 'PBillStatus'\n",
       "109. 'Political'\n",
       "110. 'ReasonNeg'\n",
       "111. 'ReasonPos'\n",
       "112. 'RewardForm'\n",
       "113. 'SN'\n",
       "114. 'SN1'\n",
       "115. 'SN2'\n",
       "116. 'SN3'\n",
       "117. 'SN4'\n",
       "118. 'Sqft'\n",
       "119. 'SqftCate'\n",
       "120. 'State'\n",
       "121. 'SubN'\n",
       "122. 'SubNorm'\n",
       "123. 'SubNorm1'\n",
       "124. 'SubNorm2'\n",
       "125. 'SubNorm3'\n",
       "126. 'Summer_avg'\n",
       "127. 'Summer_avgC'\n",
       "128. 'Summer_avgF'\n",
       "129. 'Trust'\n",
       "130. 'Trust1'\n",
       "131. 'Trust2'\n",
       "132. 'Trust3'\n",
       "133. 'Trust4'\n",
       "134. 'Utility'\n",
       "135. 'Winter_avg'\n",
       "136. 'Winter_avgC'\n",
       "137. 'Winter_avgF'\n",
       "138. 'X.9to5'\n",
       "139. 'cold'\n",
       "140. 'hot'\n",
       "141. 'row'\n",
       "142. 'valid'\n",
       "143. 'valid1'\n",
       "144. 'valid2'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  [1] \"ACYN\"        \"Age\"         \"Atti\"        \"Atti1\"       \"Atti2\"      \n",
       "  [6] \"Atti3\"       \"Atti4\"       \"Attitude\"    \"AwayS\"       \"AwaySNY\"    \n",
       " [11] \"AwayW\"       \"AwayWNY\"     \"BillS\"       \"BillW\"       \"CashYN\"     \n",
       " [16] \"City\"        \"ComfNS\"      \"ComfNS1\"     \"ComfNS2\"     \"ComfNS3\"    \n",
       " [21] \"ComfNW\"      \"ComfNW1\"     \"ComfNW2\"     \"ComfortS\"    \"ComfortW\"   \n",
       " [26] \"CompR\"       \"ControlN1\"   \"ControlN2R\"  \"ControlN3\"   \"ControlN4\"  \n",
       " [31] \"ConvB1\"      \"ConvB2\"      \"ConvB3\"      \"ConvB4\"      \"DeviceType\" \n",
       " [36] \"Educ\"        \"EmerRForm\"   \"EnergyC\"     \"EnergyC1\"    \"EnergyC2\"   \n",
       " [41] \"EnergyC3\"    \"EnergyC4\"    \"Ethnic\"      \"Frugal\"      \"Frugal1\"    \n",
       " [46] \"Frugal2\"     \"Frugal3\"     \"Gender\"      \"HTdevice\"    \"HTsource\"   \n",
       " [51] \"HabitC\"      \"HabitC1\"     \"HabitC2\"     \"HabitC3\"     \"HabitC4\"    \n",
       " [56] \"HabitC5\"     \"HabitC6\"     \"HabitC7\"     \"HabitE1\"     \"HabitE2\"    \n",
       " [61] \"HabitE3\"     \"HabitG\"      \"HeatYN\"      \"HomeS\"       \"HomeSYN\"    \n",
       " [66] \"HomeW\"       \"HomeWYN\"     \"HouseholdS\"  \"ID\"          \"INT\"        \n",
       " [71] \"INT1\"        \"INT2\"        \"INT3\"        \"INT4\"        \"IncAutoS\"   \n",
       " [76] \"IncAutoW\"    \"IncAwayS\"    \"IncAwayW\"    \"IncDish\"     \"IncEmer10S\" \n",
       " [81] \"IncEmer10W\"  \"IncEmer30S\"  \"IncEmer30W\"  \"IncHomeS\"    \"IncHomeW\"   \n",
       " [86] \"IncWD\"       \"Income\"      \"Job\"         \"Latitude\"    \"Longitude\"  \n",
       " [91] \"MC\"          \"MC1\"         \"MC2\"         \"MC3\"         \"MC4\"        \n",
       " [96] \"MC5\"         \"MCBill\"      \"MCG\"         \"NBillS\"      \"NBillW\"     \n",
       "[101] \"OwnRent\"     \"PBC\"         \"PBC1\"        \"PBC2\"        \"PBC3R\"      \n",
       "[106] \"PBC4\"        \"PBC5\"        \"PBillStatus\" \"Political\"   \"ReasonNeg\"  \n",
       "[111] \"ReasonPos\"   \"RewardForm\"  \"SN\"          \"SN1\"         \"SN2\"        \n",
       "[116] \"SN3\"         \"SN4\"         \"Sqft\"        \"SqftCate\"    \"State\"      \n",
       "[121] \"SubN\"        \"SubNorm\"     \"SubNorm1\"    \"SubNorm2\"    \"SubNorm3\"   \n",
       "[126] \"Summer_avg\"  \"Summer_avgC\" \"Summer_avgF\" \"Trust\"       \"Trust1\"     \n",
       "[131] \"Trust2\"      \"Trust3\"      \"Trust4\"      \"Utility\"     \"Winter_avg\" \n",
       "[136] \"Winter_avgC\" \"Winter_avgF\" \"X.9to5\"      \"cold\"        \"hot\"        \n",
       "[141] \"row\"         \"valid\"       \"valid1\"      \"valid2\"     "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "\n",
       "  1   2   3   4   5   6   7   8   9  10  11  12 \n",
       " 99  79  33  33  25  64  86  71  43 112  22 156 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "\n",
       "  1   2   3 \n",
       "232 261 331 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "options(digits=2);\n",
    "# Read in the data\n",
    "survey <- read.csv(\"DR_Survey2_Share_Complete.csv\",header=T);\n",
    "#populate missing values\n",
    "survey$IncHomeS[survey$IncHomeS==99] = NA;\n",
    "\n",
    "data <- survey[,-c(1:7)];\n",
    "\n",
    "\n",
    "data1 <- data[,-which(names(data) %in% c(\"HomeWYN\",\"AwayWNY\",\"AwaySNY\",\"City\",\"Utility\",\n",
    "    \"ReasonPos\",\"ReasonNeg\",\"NBillS\",\"NBillW\",\"valid1\",\"valid2\",\"valid\",\"Trust\",\n",
    "    \"MCG\", \"MCBill\",\"Frugal\",\"ComfortS\",\"ComfortW\",\"SubN\",\"ACYN\",\"HeatYN\",\n",
    "    \"Longitude\", \"Job\",\"hot\",\"cold\"))];\n",
    "sort(names(survey))\n",
    "table(survey$Job)\n",
    "table(survey$Political)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"10\"            \" rows dropped\"\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>Estimate</th><th scope=col>Std. Error</th><th scope=col>t value</th><th scope=col>Pr(&gt;|t|)</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>(Intercept)</th><td>-0.0681</td><td>0.3168 </td><td>-0.22  </td><td>8.3e-01</td></tr>\n",
       "\t<tr><th scope=row>Age</th><td>-0.0045</td><td>0.0031 </td><td>-1.44  </td><td>1.5e-01</td></tr>\n",
       "\t<tr><th scope=row>OwnRent</th><td>-0.0111</td><td>0.0737 </td><td>-0.15  </td><td>8.8e-01</td></tr>\n",
       "\t<tr><th scope=row>SqftCate</th><td>-0.0267</td><td>0.0343 </td><td>-0.78  </td><td>4.4e-01</td></tr>\n",
       "\t<tr><th scope=row>Income</th><td>-0.0148</td><td>0.0186 </td><td>-0.79  </td><td>4.3e-01</td></tr>\n",
       "\t<tr><th scope=row>Educ</th><td> 0.0248</td><td>0.0305 </td><td> 0.81  </td><td>4.2e-01</td></tr>\n",
       "\t<tr><th scope=row>EnergyC</th><td> 0.0906</td><td>0.0284 </td><td> 3.19  </td><td>1.5e-03</td></tr>\n",
       "\t<tr><th scope=row>MC</th><td> 0.1396</td><td>0.0334 </td><td> 4.18  </td><td>3.4e-05</td></tr>\n",
       "\t<tr><th scope=row>Attitude</th><td> 0.3557</td><td>0.0377 </td><td> 9.42  </td><td>7.9e-20</td></tr>\n",
       "\t<tr><th scope=row>SubNorm</th><td> 0.1135</td><td>0.0265 </td><td> 4.28  </td><td>2.2e-05</td></tr>\n",
       "\t<tr><th scope=row>PBC</th><td> 0.2585</td><td>0.0358 </td><td> 7.22  </td><td>1.5e-12</td></tr>\n",
       "\t<tr><th scope=row>HabitC</th><td> 0.1090</td><td>0.0242 </td><td> 4.50  </td><td>7.9e-06</td></tr>\n",
       "\t<tr><th scope=row>ComfNS</th><td>-0.0470</td><td>0.0224 </td><td>-2.09  </td><td>3.7e-02</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llll}\n",
       "  & Estimate & Std. Error & t value & Pr(>\\textbar{}t\\textbar{})\\\\\n",
       "\\hline\n",
       "\t(Intercept) & -0.0681 & 0.3168  & -0.22   & 8.3e-01\\\\\n",
       "\tAge & -0.0045 & 0.0031  & -1.44   & 1.5e-01\\\\\n",
       "\tOwnRent & -0.0111 & 0.0737  & -0.15   & 8.8e-01\\\\\n",
       "\tSqftCate & -0.0267 & 0.0343  & -0.78   & 4.4e-01\\\\\n",
       "\tIncome & -0.0148 & 0.0186  & -0.79   & 4.3e-01\\\\\n",
       "\tEduc &  0.0248 & 0.0305  &  0.81   & 4.2e-01\\\\\n",
       "\tEnergyC &  0.0906 & 0.0284  &  3.19   & 1.5e-03\\\\\n",
       "\tMC &  0.1396 & 0.0334  &  4.18   & 3.4e-05\\\\\n",
       "\tAttitude &  0.3557 & 0.0377  &  9.42   & 7.9e-20\\\\\n",
       "\tSubNorm &  0.1135 & 0.0265  &  4.28   & 2.2e-05\\\\\n",
       "\tPBC &  0.2585 & 0.0358  &  7.22   & 1.5e-12\\\\\n",
       "\tHabitC &  0.1090 & 0.0242  &  4.50   & 7.9e-06\\\\\n",
       "\tComfNS & -0.0470 & 0.0224  & -2.09   & 3.7e-02\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| <!--/--> | Estimate | Std. Error | t value | Pr(>|t|) | \n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| (Intercept) | -0.0681 | 0.3168  | -0.22   | 8.3e-01 | \n",
       "| Age | -0.0045 | 0.0031  | -1.44   | 1.5e-01 | \n",
       "| OwnRent | -0.0111 | 0.0737  | -0.15   | 8.8e-01 | \n",
       "| SqftCate | -0.0267 | 0.0343  | -0.78   | 4.4e-01 | \n",
       "| Income | -0.0148 | 0.0186  | -0.79   | 4.3e-01 | \n",
       "| Educ |  0.0248 | 0.0305  |  0.81   | 4.2e-01 | \n",
       "| EnergyC |  0.0906 | 0.0284  |  3.19   | 1.5e-03 | \n",
       "| MC |  0.1396 | 0.0334  |  4.18   | 3.4e-05 | \n",
       "| Attitude |  0.3557 | 0.0377  |  9.42   | 7.9e-20 | \n",
       "| SubNorm |  0.1135 | 0.0265  |  4.28   | 2.2e-05 | \n",
       "| PBC |  0.2585 | 0.0358  |  7.22   | 1.5e-12 | \n",
       "| HabitC |  0.1090 | 0.0242  |  4.50   | 7.9e-06 | \n",
       "| ComfNS | -0.0470 | 0.0224  | -2.09   | 3.7e-02 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "            Estimate Std. Error t value Pr(>|t|)\n",
       "(Intercept) -0.0681  0.3168     -0.22   8.3e-01 \n",
       "Age         -0.0045  0.0031     -1.44   1.5e-01 \n",
       "OwnRent     -0.0111  0.0737     -0.15   8.8e-01 \n",
       "SqftCate    -0.0267  0.0343     -0.78   4.4e-01 \n",
       "Income      -0.0148  0.0186     -0.79   4.3e-01 \n",
       "Educ         0.0248  0.0305      0.81   4.2e-01 \n",
       "EnergyC      0.0906  0.0284      3.19   1.5e-03 \n",
       "MC           0.1396  0.0334      4.18   3.4e-05 \n",
       "Attitude     0.3557  0.0377      9.42   7.9e-20 \n",
       "SubNorm      0.1135  0.0265      4.28   2.2e-05 \n",
       "PBC          0.2585  0.0358      7.22   1.5e-12 \n",
       "HabitC       0.1090  0.0242      4.50   7.9e-06 \n",
       "ComfNS      -0.0470  0.0224     -2.09   3.7e-02 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<!-- html table generated in R 3.4.1 by xtable 1.8-2 package -->\n",
      "<!-- Fri Oct 27 16:12:52 2017 -->\n",
      "<table border=1>\n",
      "<caption align=\"bottom\"> N=652 Adj-R2=0.49 </caption>\n",
      "<tr> <th>  </th> <th> Estimate </th> <th> Std. Error </th> <th> t value </th> <th> Pr(&gt;|t|) </th>  </tr>\n",
      "  <tr> <td align=\"right\"> (Intercept) </td> <td align=\"right\"> -0.07 </td> <td align=\"right\"> 0.32 </td> <td align=\"right\"> -0.22 </td> <td align=\"right\"> 0.83 </td> </tr>\n",
      "  <tr> <td align=\"right\"> Age </td> <td align=\"right\"> -0.00 </td> <td align=\"right\"> 0.00 </td> <td align=\"right\"> -1.44 </td> <td align=\"right\"> 0.15 </td> </tr>\n",
      "  <tr> <td align=\"right\"> OwnRent </td> <td align=\"right\"> -0.01 </td> <td align=\"right\"> 0.07 </td> <td align=\"right\"> -0.15 </td> <td align=\"right\"> 0.88 </td> </tr>\n",
      "  <tr> <td align=\"right\"> SqftCate </td> <td align=\"right\"> -0.03 </td> <td align=\"right\"> 0.03 </td> <td align=\"right\"> -0.78 </td> <td align=\"right\"> 0.44 </td> </tr>\n",
      "  <tr> <td align=\"right\"> Income </td> <td align=\"right\"> -0.01 </td> <td align=\"right\"> 0.02 </td> <td align=\"right\"> -0.79 </td> <td align=\"right\"> 0.43 </td> </tr>\n",
      "  <tr> <td align=\"right\"> Educ </td> <td align=\"right\"> 0.02 </td> <td align=\"right\"> 0.03 </td> <td align=\"right\"> 0.81 </td> <td align=\"right\"> 0.42 </td> </tr>\n",
      "  <tr> <td align=\"right\"> EnergyC </td> <td align=\"right\"> 0.09 </td> <td align=\"right\"> 0.03 </td> <td align=\"right\"> 3.19 </td> <td align=\"right\"> 0.00 </td> </tr>\n",
      "  <tr> <td align=\"right\"> MC </td> <td align=\"right\"> 0.14 </td> <td align=\"right\"> 0.03 </td> <td align=\"right\"> 4.18 </td> <td align=\"right\"> 0.00 </td> </tr>\n",
      "  <tr> <td align=\"right\"> Attitude </td> <td align=\"right\"> 0.36 </td> <td align=\"right\"> 0.04 </td> <td align=\"right\"> 9.42 </td> <td align=\"right\"> 0.00 </td> </tr>\n",
      "  <tr> <td align=\"right\"> SubNorm </td> <td align=\"right\"> 0.11 </td> <td align=\"right\"> 0.03 </td> <td align=\"right\"> 4.28 </td> <td align=\"right\"> 0.00 </td> </tr>\n",
      "  <tr> <td align=\"right\"> PBC </td> <td align=\"right\"> 0.26 </td> <td align=\"right\"> 0.04 </td> <td align=\"right\"> 7.22 </td> <td align=\"right\"> 0.00 </td> </tr>\n",
      "  <tr> <td align=\"right\"> HabitC </td> <td align=\"right\"> 0.11 </td> <td align=\"right\"> 0.02 </td> <td align=\"right\"> 4.50 </td> <td align=\"right\"> 0.00 </td> </tr>\n",
      "  <tr> <td align=\"right\"> ComfNS </td> <td align=\"right\"> -0.05 </td> <td align=\"right\"> 0.02 </td> <td align=\"right\"> -2.09 </td> <td align=\"right\"> 0.04 </td> </tr>\n",
      "   </table>\n"
     ]
    }
   ],
   "source": [
    "#here we investigate only use people who use A/C when being at home in summer\n",
    "# EnergyC, MC, Att, SubNorm, PBC, HabitC - ComfNS extra from the full model below\n",
    "library(xtable)\n",
    "#Age, Gender, OwnRent, SqftCat, Income, Educ, EnergyC, MC, Attitude, SubNorm, PBC, HabitC, ComfNS,    \n",
    "IndepPred = c(\"Age\",\"OwnRent\",\"SqftCate\",\"Income\",\"Educ\",\"EnergyC\",\"MC\",\"Attitude\",\"SubNorm\",\"PBC\",\"HabitC\",\"ComfNS\")\n",
    "\n",
    "fmla <- as.formula(paste(\"INT\",paste(IndepPred,collapse=\"+\"),sep=\"~\"));\n",
    "data2 = data1[data1$HomeSYN==1,which(names(data1) %in% c(\"INT\", IndepPred)) ]\n",
    "a=dim(data2);\n",
    "data2 = na.omit(data2)\n",
    "b=dim(data2);\n",
    "print (c(a[1]-b[1], \" rows dropped\"));\n",
    "mod = lm(fmla,data=data2)\n",
    "smod = summary(mod)\n",
    "tbl = xtable(smod$coefficients, caption=paste(c(\"N=\",b[1],\" Adj-R2=\",round(smod$adj.r.squared,2)),collapse=\"\"))\n",
    "tbl\n",
    "print(tbl, type = \"html\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<dl class=dl-horizontal>\n",
       "\t<dt>Age</dt>\n",
       "\t\t<dd>1.1860003254769</dd>\n",
       "\t<dt>OwnRent</dt>\n",
       "\t\t<dd>1.42190876852727</dd>\n",
       "\t<dt>SqftCate</dt>\n",
       "\t\t<dd>1.42143110938964</dd>\n",
       "\t<dt>Income</dt>\n",
       "\t\t<dd>1.30454639875688</dd>\n",
       "\t<dt>Educ</dt>\n",
       "\t\t<dd>1.13512994072037</dd>\n",
       "\t<dt>EnergyC</dt>\n",
       "\t\t<dd>1.56766943908693</dd>\n",
       "\t<dt>MC</dt>\n",
       "\t\t<dd>1.27043420875129</dd>\n",
       "\t<dt>Attitude</dt>\n",
       "\t\t<dd>1.71499338151343</dd>\n",
       "\t<dt>SubNorm</dt>\n",
       "\t\t<dd>1.23492838130023</dd>\n",
       "\t<dt>PBC</dt>\n",
       "\t\t<dd>1.14540864737446</dd>\n",
       "\t<dt>HabitC</dt>\n",
       "\t\t<dd>1.15830650163808</dd>\n",
       "\t<dt>ComfNS</dt>\n",
       "\t\t<dd>1.07418859002558</dd>\n",
       "</dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[Age] 1.1860003254769\n",
       "\\item[OwnRent] 1.42190876852727\n",
       "\\item[SqftCate] 1.42143110938964\n",
       "\\item[Income] 1.30454639875688\n",
       "\\item[Educ] 1.13512994072037\n",
       "\\item[EnergyC] 1.56766943908693\n",
       "\\item[MC] 1.27043420875129\n",
       "\\item[Attitude] 1.71499338151343\n",
       "\\item[SubNorm] 1.23492838130023\n",
       "\\item[PBC] 1.14540864737446\n",
       "\\item[HabitC] 1.15830650163808\n",
       "\\item[ComfNS] 1.07418859002558\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "Age\n",
       ":   1.1860003254769OwnRent\n",
       ":   1.42190876852727SqftCate\n",
       ":   1.42143110938964Income\n",
       ":   1.30454639875688Educ\n",
       ":   1.13512994072037EnergyC\n",
       ":   1.56766943908693MC\n",
       ":   1.27043420875129Attitude\n",
       ":   1.71499338151343SubNorm\n",
       ":   1.23492838130023PBC\n",
       ":   1.14540864737446HabitC\n",
       ":   1.15830650163808ComfNS\n",
       ":   1.07418859002558\n",
       "\n"
      ],
      "text/plain": [
       "     Age  OwnRent SqftCate   Income     Educ  EnergyC       MC Attitude \n",
       "     1.2      1.4      1.4      1.3      1.1      1.6      1.3      1.7 \n",
       " SubNorm      PBC   HabitC   ComfNS \n",
       "     1.2      1.1      1.2      1.1 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA0gAAANICAMAAADKOT/pAAADAFBMVEUAAAABAQECAgIDAwME\nBAQFBQUGBgYHBwcICAgJCQkKCgoLCwsMDAwNDQ0ODg4PDw8QEBARERESEhITExMUFBQVFRUW\nFhYXFxcYGBgZGRkaGhobGxscHBwdHR0eHh4fHx8gICAhISEiIiIjIyMkJCQlJSUmJiYnJyco\nKCgpKSkqKiorKyssLCwtLS0uLi4vLy8wMDAxMTEyMjIzMzM0NDQ1NTU2NjY3Nzc4ODg5OTk6\nOjo7Ozs8PDw9PT0+Pj4/Pz9AQEBBQUFCQkJDQ0NERERFRUVGRkZHR0dISEhJSUlKSkpLS0tM\nTExNTU1OTk5PT09QUFBRUVFSUlJTU1NUVFRVVVVWVlZXV1dYWFhZWVlaWlpbW1tcXFxdXV1e\nXl5fX19gYGBhYWFiYmJjY2NkZGRlZWVmZmZnZ2doaGhpaWlqampra2tsbGxtbW1ubm5vb29w\ncHBxcXFycnJzc3N0dHR1dXV2dnZ3d3d4eHh5eXl6enp7e3t8fHx9fX1+fn5/f3+AgICBgYGC\ngoKDg4OEhISFhYWGhoaHh4eIiIiJiYmKioqLi4uMjIyNjY2Ojo6Pj4+QkJCRkZGSkpKTk5OU\nlJSVlZWWlpaXl5eYmJiZmZmampqbm5ucnJydnZ2enp6fn5+goKChoaGioqKjo6OkpKSlpaWm\npqanp6eoqKipqamqqqqrq6usrKytra2urq6vr6+wsLCxsbGysrKzs7O0tLS1tbW2tra3t7e4\nuLi5ubm6urq7u7u8vLy9vb2+vr6/v7/AwMDBwcHCwsLDw8PExMTFxcXGxsbHx8fIyMjJycnK\nysrLy8vMzMzNzc3Ozs7Pz8/Q0NDR0dHS0tLT09PU1NTV1dXW1tbX19fY2NjZ2dna2trb29vc\n3Nzd3d3e3t7f39/g4ODh4eHi4uLj4+Pk5OTl5eXm5ubn5+fo6Ojp6enq6urr6+vs7Ozt7e3u\n7u7v7+/w8PDx8fHy8vLz8/P09PT19fX29vb39/f4+Pj5+fn6+vr7+/v8/Pz9/f3+/v7////i\nsF19AAAACXBIWXMAABJ0AAASdAHeZh94AAAgAElEQVR4nOyddXxUR9fHz1xZy0pciBskIUKA\nEAgSIBAkBHfX4la0FKc4pWiBUqR4sVIoxaUUKRRocYpTvLgT23nv3V36yPvs3E17s5s08/0j\nM3w4mZkk97d35Mw5gCkUyt8GHD0ACuWfABUShSIDVEgUigxQIVEoMkCFRKHIABUShSIDVEgU\nigxQIVEoMkCFRKHIABUShSIDVEgUigxQIVEoMkCFRKHIABUShSIDVEgUigxQIVEoMkCFRKHI\nABUShSIDVEgUigxQIVEoMkCFRKHIABUShSIDVEgUigxQIVEoMkCFRKHIABUShSIDVEgUigxQ\nIVEoMkCFRKHIABUShSIDVEgUigxQIVEoMkCFRKHIABUShSIDVEgUigxQIVEoMkCFRKHIABUS\nhSIDVEgUigxQIVEoMkCFRKHIABUShSIDVEgUigxQIVEoMkCFRKHIABUShSIDVEgUigxQIVEo\nMkCFRKHIABUShSIDVEgUigxQIVEoMkCFRKHIABUShSIDVEgUigxQIVEoMkCFRKHIABUShSID\nVEgUigxQIVEoMkCFRKHIABUShSIDVEgUigxQIVEoMkCFRKHIABUShSIDVEgUigxQIVEoMkCF\nRKHIABUShSIDVEgUigxQIVEoMkCFRKHIABUShSIDVEgUigxQIVEoMkCFRKHIABUShSIDVEgU\nigxQIVEoMkCFRKHIABUShSIDVEgUigxQIVEoMkCFRKHIABUShSIDVEgUigxQIVEoMkCFRKHI\nABUShSIDVEgUigxQIVEoMkCFRKHIABUShSIDVEgUigxQIVEoMmAHIf16nEIpUPya+6c874X0\nM1AoBYyfc/2Y572QDkFGnvdBochIBhzK9fdQIVEo/wUVEoUiA1RIFIoMUCFRKDJAhUShyAAV\nEoUiA1RIFIoMUCFRKDJAhUShyAAVEoUiA1RIFIoMUCFRKDJAhUShyAAVEoUiA1RIFIoMUCFR\nKDJAhUR5s6B9cscv3zl6GAUbKqRCz9Vinu1HtXWL/t3RAynQUCEVdrKK13guFE8ql86xxfzZ\nkoF9FtzP4zEVQBwmpCfXCf9JhWQ/1usemcp7qu9tsN7i6l2nYYBmcd6OqQBiXyEdrBUYPzfb\nVB1CaoUKyX70rWOpVB0mbXxCOTwT45y53NY8HVMBxK5COsiDhofkJ2KdCimf0KGtpdK4p7Rx\n3Ybmsl+JPBtPAcWuQkrjvzG+m6tOeIWpkPINI5IslbhJkrZG9bfmykn4I+9GVCCxq5D8W4tf\n9ynScv6HkHL27fqTGVRIduMEc8RU7mXOSdq+gmPmyn04n5djKoDYVUj8SFOxDPr8DyFd83D5\nEw28+qt9UHJLJ8/NRpyz3q2PDbZO35jL4+hRno6p4GFXIfnVNZcfwRTy1G4+vPyrfVByS+YA\nhTZKoxyWbYNtw3Rz2aN0ng6pAGJXIfVBszPF0tgO+vWmQso3PNg6Z9tDmyxPqz98i3HWVG5X\nHg+pwGFXIT0KgGqmirEPABVSQWSXl0tKDS/9akePI99h33Okh937WWobQqmQrPH2ui2zLAfx\nau3wocufWP6RbZMzRKEgf7oIFWYhrS/BgjL1pKOHIU3Wp6XUTglzqZZMUCHlMybwgw/d2NFY\nme8XIW+reozbsW2kc3qmo0eSL6BCyl+cYTeYyv5+bxw8EilG+JrcxS+7T3X0SPIFVEj5i0EV\nzOUrp82OHYgUOV4LzJUpYY4dSD6BCil/UWeApZI42aHjkOQuXDRXjtHDcxEqpPxFvffbmqXz\n+Yzpd7hirpyA544dSf6ACil/MbyUuXyi3J4Hrf8+v8/Q1fIsvrKcLWdJ84vI0l5Bhwopf3FF\n8YVYGNuF524zzKZN6E8VIY1SXX0P/oVx/X96RpneRI+CPpKluYIOFVI+4wu23fojyyoZjuXi\ne1ZWclbFf/JWymypYoXw9U1X/fW/PLp/43FU1Oqrl5eFliq0f6r/gAopv3Ggpiv4t7lm+zcY\nu6gHbNw50a/UM7Jdjt8Es335D/7G8P7F0+4GANf+hfcv9R9QIeVDcreKWak2vb0eFpPQxxm4\nY67MD/5Lo/of3LwtV0sFHiqkAk/F/uZyk5q8D72PMZorW7R5PKLCCBVSgUdvuf79DMgOeufA\n8v6YF5LHIyqMUCEVeDSWiD6vgbxBYQwYZypzynbL6yEVQqiQCjwlx5jL/dxjsuEKfrEwuXvZ\nwflm3g+q0EGFVOCZ4W7yHs2o0EDKcrbKP62KPvCnvB9T4YMKqcCTUdX3y0u/by7rK/2iubto\nwKgNNFp+XkCFVPB5N9wdQN3yjqPHUaihQvpHcOdyPr6dXiigQqJQZIAKiUKRASokCkUGqJAo\nsnPrUOHLREaFRJGZxf4AUPQbRw/DzlAhUeRljGrC5Xfnh3ALHT0Q+0KFRJGVC5z5XTRX+8DB\nI7EvVEgUWRltyVOR4/uFYwdiZ6iQKLLSurOlUmuwQ8dhb6iQ8gOHpvWZ9YujByEPHVtbKlWH\nO3Qc9oYKyfE8TmVL1Y9BrfJ7kGKbmOtvDn/0XFu49u2okByOsVLcJaE4HtjK0SORgyduA8Qb\n7VmtQwuXlzkVksPZojbdJ8LH0SkHj0QWdmkrztw0Ld79pHFVLX//WquMjh6QfaBCcji9LHlZ\ncWw+j1JsI1e6xjmX6nc3u4Wm1/LlPTUtC4dfOhWSw2nW3VJJG+TQccjMZy6nxeK0ywxHj8Qu\nUCE5nJ71LJUS+TwBRe4Isfw0k0MdOw47QYXkcDZpzHdbf0UFIN+lzTw1Bwf7tVs01F1SCGZ3\nVEgOJ6dc6RtCcTq0qaNHIif34bzwdQFXoz+006e8dvRw8hwqJMfzIFlRvkUC0/AflbArW0z7\ncoxdjFc759wM7i79DQUcKqR8gHHP+K6T/2lBsrrGvsYt6+HXsd0w3qyQCPBf8KFCouQNf4Qk\n7AyeuSMh9A+MM9l9jh5OXkOFRMkj7jdnAdjm9zF+9TkX3XFxhqMHlKdQIVHyjLclOonZz34L\n9YCebV3j/tGB96iQKP8fubY9Zng+EB6xountYjB+VKHcP9lbiAqJ8l/8Ut8d3OvJcqb1rkzE\nzncrDG1UYtraW/weOdrMp1Ah5UOyl7dNTB911zGdb1bUX/vzugaKb+Vo7FkHjuMgxvyMlR8t\nR5P5FCqk/Mfzivp2kwdEO+9yROdPXEeYylEuEklibOTpj5Wbm6d0v0RGDVopmTG6oEKFlP9o\nFiWm1ssZqHPE6vwLH/PFvCzfBTK1OKSK+DW7B1IlpLmG/CpTq/kNKqR8xzV0xFTmxOTBZe3M\nhxIGvRtaKo16ydTlEfaE8PVjt2nsZfyymZc8L7p8BxVSvmOFt6UyrIrcTS8rwYN7O2Iq8l6N\nLZUmPeTqtY3Pd8anyr7OYjSUzKJj5Go2f0GFlO+YX8xSmZIgc8t91MP3nVkY5/kbwWZuQI6p\nzAmaI1e3Gf14rT+oR5saHl5JrmbzF1RI+Y5tGksUlE6N5G14J/djzqd+AIzrJetGD3TTTOV0\nnYzxu+9vbetpmdLNKS5fs/kJKqR8xxs385Xzm7qV8jbctKWxhcuMM3e+BB0hOsRKtuPuq7s7\nsStk7Xu72hILZXBVWdvNN1Ah5T+WcROe4+y9YVVy5G03es56lUlBbmVJk8b9lRSgqLhf3r5f\n6b40l/7d+6c2Hve7vK3nA6iQ8iErvZC/mu34QuZmo2endzFV3ObAOZJh1u9ZMneN8aeatUaM\n71TVs7U+6hnjtE72DhwMFVJ+5O2xr3bck73VZi2Kms6GLsIFl42yty7FJwrf6iV5X5djQt04\nUXHa7gPIW6iQCg+7uKC5QpFVqwLWbbZ/97eXffzpLv1i8z+qt7H/APIUKqRCRD82cs+plWU8\nfzuBbjhmBEfhufD1aisfYKrudswQ8ggqpMLEx4gDrw53Xpev7aAB7OKFL8f0lVdO0XZmZTuo\nyg9QIRUqRnEd1+2dUSyE6NyQh1yAGzizaDsjnhyLv+IvOmgUeQEVUuFia3U3vvigpw7rv1h/\nvFPxGL8O69y3mqH0zw4bh+xQIRU6HBqtcTs3fGI8vpTswlb/uKw7O8qRY5EVKiSKXdlchFEV\ngSjFdxgPrrVVudrR45ELKiSKfXk3hV90tsQQoVZpAB4a6+jhyAUVEsXOZAT2eAlHMN7I/rKp\nA0w44+jxyAMVEsXe7FfXgB0/DOQ/jNImgh/q/I8IsU+FVNh5d/oPe3d5ujYAV3JVYJ3pevBh\nUdl/QuhIKqTCzS+VWQC/WfaOONc06S2e5j9FGV4fZwxCTezce15AhVSoOaBu8sPDc5/qP7Bz\nv1dcG9+o0V2d4HoZ42wdK/OdDUdAhVSYyQ7raip/4uwd+ut0SeBVUNJ0PSoiWq44Kw6ECqkw\n8yMnBhUy7urvE3nQ3n2fiS9a2jSjzDLUTZcyzv9QIRVmvhTzu96PQiAslKLsncJopj7OVK5R\ntWlh567zACqkwsxXAcL0LgT1vT+u3BQ2wM6dv/FHR4Xie8Nw/1l27joPoEIqzJxCl/FyNALj\nqj3xGphr596vaZlSdUPZgZ29/gH5/KiQCjXlq7+rzr3Fy9nTGOvlDqMnya0gbYmmXSI8jti7\n4zyACqlQc9U/qoh+RSt2tlAP9bd792/mNI6rPcbuB8J5ARVS4ebRAA341T0gVt0iHD2YggwV\nUmHnUzAfhx4C2YJ9F0aokAo72QYnMdXKz3r+H53jNa+hQir0nHUC73hv4Dc5eiAFGiokyts+\nxV3C2jooQNd/cf3XAprTjwqJkm/IHOUKwKZecPQ4/gpUSJT8Qk4dr0XXnv6Qpi+I6TGpkCj5\nha+0l8XC2LiMo0fyF6BCouQXqvcxl8eAkL4pv0KFRMkvBC4Vvy4MBmAq/OToweQWKiRKfiH8\nC+HLQM2EXxSftuZ3OHo0uYQKiZJfaNoM45+Y3fgAcw8P8Ctg2+BUSJT8wn52C+5ZAz+Lb4Lx\nS/X3jh5O7qBCouQbxnIdopuOD4gW77/Hf+bo0eQOKqR/ABm/fnP8jaMHIQc701WKhLGvhdpz\n35Se8wqS8x8VUsFnvge4gH6SzDnQbce4e0LP6Sflaesj8+3CHa6Q1DhY9bk8jdoDKqQCzyTV\nZ4/x80WGvg7q/14FRbkmJVDrd3I0dkUhiueMOjw258a6VuwyOdq0C1RIBZ1bylWmci/zi0P6\nzy6V+LtQ/OzfQZbmFnNNl+0qqfc82opxjWaZmbI0ageokAo6c4ItlaSPHdL/Gv0DU3kYyeNs\n+lODAJ6tcadKscPCmwmUBWXPgQqpoDMwzVLp0sq2b/i9XxnP+EH35eq/YzNLpdhsuZrMRj98\nrb0pVJ7DSKcncrWat1AhFXRGJlsqzbvYZH/QOcAVgFFukan/uh9aKlVHytQixu4rW7YRy7Nw\nw2WtbK3mKVRIBZ3vVeYoPG88v7TF/IV3hH7qyd+/9WZkyoTc6f0bqajNb6Sny4d8tOoFwaBV\ntUpjxHJANI6f/ncGZz+okAo6WTFp4hlSVnvfVzjz7GWpTfCFLorjYvmUC5Wn/6915lniIXTR\nxu9YZ/CqUd3d7TvrFhe1QT2FGd4M7jscuOjvD9EeUCHlf66snbnjqfX/vhQYNGj+R1GeP99u\nygM49SH/6rr6tTNXyoONSSfvbp79/UPr/52dUEa8pX7Ur6NtzeEfuAlZwoM3XEF4JR4wMMk1\nvLVf4Z/hNxubdTBUSPmdp82QR6xaO8O6xbOJtSKqj3jwu2/Stj9+GFCkxGtSc+2cLZGJ66pt\nWn28683po51UI6y/6e5XUiQ2ikVtbT1HqtDJXDarSTC6ZygxcPkjfDOyqY2tOhoqpHxOTsXI\nY8LEbaFach+4aVLGwShwVUA0KXTpWLU5Yr0xWLPBlv5bFdkmDOJrlwHWTYx7J/WaYfMh1kvG\nkkFmmyKLYHbMJ7DziMaaqi/wrnp+LiWm5PdEs1RI+ZxVutumcpETYXYn8kKx85Cqyw2c1VsZ\n88q62UWUZCqXKOHyzcOPpLo/xJp9f3awl2wcsBTX4bq5cgYIE0bhTTyjVUq39Tl4GMPxfkrw\nlRyqY6FCyuc0a28us5zXkw3PwKN4k3PBftZ/PMGuA3S+abw2RhFWzBsAYnaSWx1cxVKJlGv3\n7AVjeeK286Q30ns2saolwtvoay7E3nlucwcVUj6nwjhLJY6wShK5CIfNC/MdinHxJMM6AAy4\n+umcpl99d6oXu47Yasv3h1PpHxLtckGSJWFty1RbrCuwq03lp/CNXAPIE6iQ8jlp/S0VvyVk\nwwznjzjTh/aQMhtdiZaby+nY8BbMXtM/xrkTf9XdGpnL711dfFLmybJQ2cNNE9rJGsvbFJdB\n7WJ+Ez2ERnJ0nmdQIdnMnUnN6w6xeyqfySEZpvIndEXCcpAXiGujY05fLZVM0JKB+1Yz194Z\niFPGVc6mpdkAjhm0ZqBriiy3nlbpfOvW8Xa27Q3DFTeXx8Bn8t58PLujQrKVDdrIDwZUYXrb\n+Y/5xLOduK98rWhLKcs3yajhxjW9VZ2NjZtIt5s20FIpO5FkllEs7QXG6xXFyxsfrB/q1t6W\nIUvyaNGHA5eY905+nDFs6U2Srben+DWzMwKfMooKd2XpPy+gQrKR04rxooR+NEyxc8fHivh3\n/KiBKlX6N5KVotB7Vf8aL2aPXJrZdchqYviQBr0tlfhPiY1eCvdqN9JTGX9nrNK1rDvUe2zb\nqB+etuXldas8VyLVnxtG+HDqCeJueXefBNUcfLNsSVv2JxwCFZKNtKptLue5Ztq552ez2tbo\ntcmW+68Z9TTtpo9N4eePZKNa1HANOEawHRdlbvEet4/c6OsFHarw/TLG6tYYhYVKWHkbBmJc\nEAjAVjgqZfcuqoL4NtqkH2Pd5pVetezZBaaMwvvl7mH1lT0zpLt3CFRINuK3xFw+ApkuVecF\nxnUtS1TqdWaG02bhH6/auRJmQredPhGLjLpxNuwgKHY+UH4tfIj4AkIxDyTN+zlNOvPwYCvF\nLgm7eZ7mLMyrVYT33A0vAARKnyNpfEp3P0WU1FLRQVAh2Yhus7nMYfbJ3vaBbhWr9D4uW3MZ\nLuZYBznxpC3rDarUz7+dXLzIRXykW/nEzntILUZNWeGRgxuCB+rljZTnJPo/xJhzAPb3l/Aa\nqtvTXGYTz8iylzcq4j77RbOw3zAeklKzaP4MeEeFZCMRlmOcKyDXEf97jP3Z9HGjUlnSKWqu\nOMRYrihMjSWZnW0fZSg9+CEezaZ9Mqkh14uwUPnEb3QCXgZdqiVEc4CU98j9d7NcNXyh2k42\nTJxkLh8FNvnmNslwfgg+h8RPmjZtzrrMJzfqIKiQbGRwlPnjtV+k3C0vcDJ9gG/i5Tpx/FZv\nKt5Mj+PK9b4sZb1esVUsDmoJIXtel/b2fBTqXF2DlC56DbD7iC3+ecMvdha569qmMzLjGDXy\nd2a7EnYnrjAH5hQVyrsqJ2GeV9bW+xr2xGFCekT6C+dDIT3yr3FDeKJGcRKfsrknxPIq6lvO\nNvt3Py74mvgoHUHi0uN+tE+lgAkV1FLyLGM58Z0YTDB63gLEJxgiklB0fwCGGJ4h9SNLJUIi\nnNanAaJ4hhkGc/fw7gDSgWsX324VMf7dhTWoPTWMhDeGQ3CYkIaQWsmHQsJXyqLgaIWX7I4q\n9+CsubKHtWlvd5MPW9QTqhOmQpkeoqd4auIfxYdiPFZDPKbBme/XfGeBOGNrEcA1SmGr6n1e\nYqYeeJJWP4PLmsvbzGFi1/hFQL1n+AY/zVuMJHaWJyzTMtoiRbMKPMMNe9204x++3DVyww6A\nCsl2TiyevVv+gKaX4ZaleXhug/lWboTwuzlfvijhqvYC5QrjWTjc2OsPYeIU/5F1QyzGFzlh\nrtwC4n7YqzSk1WjA7yw+Bit4xWKC6SWFaRmTmV5Saqv8fDFDrbJK1MF0olCrD8l0G5M2Lsan\nE77ltB6fgsYSDdsfKiRH84rfba6scrHB2hhm9kh4GTSOYDVN6R+rdIo4LdaHpZBbdF1pLncq\niBcCsbE+cE5+b7AxXJml8mpHMv2Sa7ps56xYb+m1TMbXg2PCLMddvRsSTQe5fueFjp+JrpiD\njZxBsmV7Y1chlfo3vKmQLKTXMu2XZZbpZIPxabDM6T4pRTK7s7ia51bzTHF8ErnFLqVNZ5w5\n1etJdJ3tA2zpe0sCYN4NiKlLND3SIIAv3se2iF+T3v8gLckRJnMGcQwEo7pP8LORCOK75rMr\n6HYVEsMo/4T971aue7n8iQZIMWb+YVwwNLuO8cVaPsQdYAvfqy2VNV5kw21qywumZWuy4Z0i\n1c8I07FGLpJP5uswENAtN1aH5G42jNXMrQ0zSSEf8GHWPKV84U6aLorcjIFxp4QHJdgHKadV\nVn9r8xDsgV2FNET3r2n4/5vaZW9e+yddCtMbCf8SD+4uUMGm86mDyLJK+zycbPjWy+x3c065\nWaLJq1VA5wxlbAmFEgLFt9/bWRpVV/Wu6Fu0qQ1OBm+6sC4xTuoxhEOqqqXFV9er+qGSJ607\nUBthipmYHB1Y86vBScqzNozYbthVSJnxpf90VKNrpH9hPL92g+R5j5k3TivMlWpSobbXc4Ou\n4+drvG24xnNjyze2dZ8ZKL6TUFqIE+KDfRk0SfI76gfuFWZlqwyEcMp/lNE3H9HeO+S8dP/1\noPqqqaiID6vzqpXGKdfYNGj7YN/NhvPq9877VEh/keEeYpgR43iFlKMO/i4MNKD5KJdeni+P\nkVIt5fTl1EV9kBfqKRi9TACpTK+7FII87oxvGs8QHvqsVR+ktJ9HiDPxL9ohnmHdVexo4QO5\nb6SUv609sfOu3fM/vRP3k67BUCFZJasNnz68V4zWhhBAOVe3nsjldv3v9RECthUhDNHd9ZNW\n7ALTLfHzq9W+Et50vdIw3qSL6v6Rmmkny/XaC5/EuU9LbiFWh1XvUl6OJuWBuggVOHb3SWk0\n1nT29ObbCRO+tVEqWRdtCMNz26/i/pfPd5QsSo5cvwiE+dqtaqBXgGEJ0bJBH3xBOca4uZ7a\nSVFXniuRG/WvzCnPa6e2Q7Nt2aCxC1RIBZddPrpySTpvqemVyMU0BUDADKkD0taJpjfMy4h+\nRLOJcAW/CC+mDioGBhhIsmzfGneqauyp6BTQPBWlyXKT66X7x6YYsQtBWx58lRIhYewGFVKB\n5YTqw9cYvx6klI6Gf1Jfa+dvXzZzkghb+k5tusf0QTEN24x062iD8EYa68NNz6mJfi0BuwmW\niz1eFp27THPoMtOoLCgayDK7+5pjFuXcnYAiXv3IvFimyCdJ/aiQCiy1LPtxzapLmpZonjNZ\ny4cpoR5x6+Ea3MT4jAYFlQKGI8S4f8OVwyWDOuNrDAs8KAj7CG9D6nutKT3kXiBKGa8ojlLI\nzhM2stUJWFAGZOHOFTAe7+ew3Ln/ARVSQSXDtFJ4NyPVE7X7lWz6K7oxSrskA2dXVRFPZ+/A\nRWw0aC/iH9FtH54Q2XUIpLujPdtV0OceViB+nnXL8yF8PKqsQdOFxr8Hv+7kgZp5MDjRs1TP\n69YNjvJtzwbPy5rI7RfHnD+Ok6iQCir34ALGj0t6DZoCVXiyU8DXXjf5jWJlTij3I8HO6DsL\nz4EDGI+MxXdRZ4JlNyRGmYQBwtQSwSQnwjzwVboW6ldME8TnHgAIGkj/YU97xUxcOy1Jt9e6\nyWZXT660t2EtxnvaQFirbZJt5j1USAWVt+KF7saxD/GPzKv5HNEvYb3bXNNlo4OlVKqg+YTL\nGhPdz1d3wviY9kuMA4qSmrxRHMpWLiNUlqu41z6kHEYvwpWjw+e9GoUYjklHSHuV1KxAZtGm\n4qaEsZ87Yevw+XLn1K+E//+QS4ehLRXdHB/wrvAJ6cauc/aOA5Q3VOyCb6HDGHcvh3G1riTL\ny9CphlBMZoskphR1TbZ+9JnVWOutW9RF1UV4MKP9iL2fY2KaChO1kx7R1XH1YSTLW4HAFuH1\nTHxiE6ydo/IlNiu8bTTmOWWG3xySWbdywhi/Uu8X10g/6SRuENqBwiakLWGgAMOE/J4kxBb2\ncLM2GozGudxOjKeWIH4mVwtOwHgv+xFzqGXHWyE9rBsal/ug4HTT5UW3kuTup4Cq2Md1uBjF\nUVx+LNHyWaiy9NZgLsnn5k2Yng4SG9YjK1sqbYhOUDcMnV/huGHmXbsJMmUf/BsUMiGt5gZd\nMf7xpastNxbyPV+pvdUtw9WL8YNubqCtQLi7e9MbjdmbEMZ98tJjEd6kJLnWH4QRpnItSARc\nwMuUyMVP67EVP1R92Kf1+BPWLR8liC56dW7gJMY1EZjyxDu7Q97nH/uAHFv2sL9zFfA2nyOd\nhNMSg81zCpeQXrqZ3SyPsvvzpH07c3cAaj3zDr5SJL5y+e/68gTH0Me+Gp6J2f6mSdAb/AYR\n/+RJqEcGzhnPBkh2f1tfdtT6V/hdJd6jYadE1MP6PnRG6SCUgq9VhKE5j6FOuXCSX91CX0s7\niSMwcbf87boPYZTo2XCzsQLAbaRjQ0cWLiFt0Ft8w9Jtv0+Tn8kJ6yV8rVT9onYFxjuYH6xb\n3o11U7bo5h9wRvgmjhjDLicFQIkg5pl09/sMZSauGB3KNBQvQPzoOtK65bP2gHTA9sPGHqL7\neBBhx+GBk3k3/Tu2rh84p5DGanQWj7CueFUcpTq30CfVoeGMC5eQpiZYKsOkDzELBHsUXS6c\nhRn+NcVP8UakQ6J3C939m00Xo0KchRvkRq9OaDZS4mTKws1+ZYskl48UVpx/TG0Ry5ECw3SB\nccsVr4yNEZRo74tYQiymBdzHl7KvT1OpKizbNb4KQ0pw1rmU8MFYs9rbCs0xvu7i0B2HwiWk\n2ZYcIbgf+ap0PuLhng3nCVsjP8YCD+oBpjtxM+KILX3mabr7bWxiY9gvW0kch/Fu14Bof0CJ\n1p3BMzzZNM/f+gAIv/n54Z4qwuxuXQgg8PZu+Xagki+CgLCTcdevyvFbzLKanuJHQ0+J3ZG8\npXAJ6SfG/GGcE0XeZ8o3PH8k6ycAACAASURBVG3LKtwgjBRE+/ZwN8vjOyuG2Na7suGbn2X+\n0lhnc95k2wj/Av+uTVVUGaMvjYKs33J9WkKc1JmclMaUO0KSB8a3fri2h3/Y3GdjBn4RxBJ2\nPW7UFD5HoMpl/KyHHsC5j+MiFBQuIRnLpZg+CUdo7+RJ+3KTkRi5NxPf7suTMr2eRpYob62a\nkVt70U0hPHZJpzB+PqVeTPpEiezOtlJxOB4QyS7Ar/h9XyDS2vMEV0/rJpTZ0cMwV1Gi1Zmx\nu/lTYmVItBMp5MO9mUhYcD0pHrm6j7qia4gNK7u8oXAJCd8IDR6xYnJFzZa8aV5u5ribnW/6\nhpGOiUo3NO1zHeElg8C+ObFffCh/CwroN/PDYD95vNQmBr4uEydM2Ga7vMtWKkjvhKHu+lCM\n33Z0vW9kiWluBT4r0T1dLI/EO/NVSHuszxTbMO4dcbcO49yuIiriqFRkhUxI+Pm4qr4JPWwM\nkOBwkgeby7uIlEvmtEuVTZePjnOydScyK6qOuK/8tnGoxP1W23gRUi3UfWHOUuU8jH3QAYJl\ndmdgujXx9v0JH5UM8bhDlTpIKEaybuUCI7l+hA+S9sUfZ7usaOCvmNsqSIlIjkV5SWETUsEi\naIml4rKRZHatsQ6YiIXiw5Z5ctUuwkVxE5uczJdlnzuv+tsjNHVfBjFRHurpQossmzp6O+Gh\nHw2xPb58id8mcFLhuzOCQ7ti/LVyFPNLzPTlmi+sWz4p4f8RDAJFGgdqNQBL3NzPM6iQ8jPF\nLevsbKXUNdhb5l2wDX5QRMl2JK+5h6RaKvWIQYJtx9iPLb/mPsYvowDqJinKEyJDJkC97T99\nEconSt4i+oHXbL4aUUYxZhfiAbhPrW9dvhkbCyrdF7xSndQLghAiRvjPK6iQ8jOdLcdd33O2\npW5dx418jLP2hFci+hL2eh+hq03HvzO4f+OtD38Q43exKMGziPDQe1rfHTA2RAg4SLdho+OQ\nggMIW3uAdd1xdyM4kxyGjEWq1x6INEONnwZ3TwEfR/iCUyHlZ85wJleyGyFE5+4/yfA2B4W8\nZVhKMpv6/jSttGyHADf14BrFQwLjPjrdTwkawiL0wbpPltn2zjjkHgKDunGGu8JvALapSHGT\nxugjSvBFs694TK7T24AO5m7wskCF5Egutg9XRnQm5ChZoaw4akYnXTXbrmjvVVjyWZg3vKxx\nmTNvWu5mbImuahuP0hCrBE+XhTzjFKEAlnR/0GYejOaCaoAYOHKb8m1nUmzyd+XAwNcZ6ZJ2\nWbXcwJReYH+/OyokB7JTU3XBts/L6wmfoBf7VYltvsLGsARLg0zFmY5+XJXxBNeBj7VfvMKv\nlxhIKWZzzR+7GyRHfqTgFufg7qWR0pYUNdJ0TPxaPHnKSWmI5xcjGWaVQcCXmXO6eAgjHvsq\n5NlGyQVUSI7jiZu4wYuNXf1kiQkiLJFcxdXBSkWNWkWHB0RYP1ExTjMgb0Y3QeawIdOi2das\nmOOsTicAm6IzSHLLJ16H8aWGrpdzurq3HrnL+urnXRVQ1I5mYpAzEu9sgGwZeW2ECslxzCti\nvqr72kWmz8/b4inOZeV0Y8IA/DyJ5Jf7+uiqIzbFCM4NZxAXyQh/uJvq5aCX6cPhciI4uUCZ\ns3cTWe+OVfhUgueCL0RPPuqkEl5IHHAABF/0vIAKyXF0fe/SU2uwTC22KnYLDyhrHKm5jvE5\nkIwOLjdtFS5OGF+IqVRfeCugWJs8yH/sXjG5508Eg8qRqy/jnIQIRviQuBKVZt3wnYcpIAuA\n57fPs9oA2PfKGRWS4+jYxlKpRw5sajsvkvUdQ8uX1Jo2E/y/kqlVm3lXFiCtBFOrPIOQJoxl\nVkh/yyC2zrgxtVjC6+N2SLEZewZxnGlD8gJ7xLpldm+l6Beru4PPNXMFUJ/K7fj/DlRIjmOS\nZRs6J4AQGC53ZC9v6VR0mPkqd9EFcrVqe/clwb/b500Qk4qAE94OUqnD8GKNyQ/he+XX1m2e\nDo7mVR7fm/+RQFz7ZG4AzjAE71TXbCxISiGVGUpOqJAcx3XFclM5x8m2JJG20bKVuXyuIMUS\nziNy/IHjNVwCQNAnqz4AIMXpEokYLX49NLNs4HVisy0/sNTqkncasxWMcsVzz4HGYDVwLVxs\nyBsgF1RIDuQzftivz0/2Z6Uet1yxRWk+HRri82E578T+dk7XkFnWlIoMJWdgbOQ4UrhWgcdw\nEuN7ldnYRGAHkfYQ+7+PiBI34TQxVU0fQF8s9XjSCNVFqIq6nv1+eiokR7IuQnjqYghRtv8K\nzTyWPsg+34M1xE5YNamkC2FRkScc66dgNfxjjG+UEn44LXGddBOu4swSidfwGVjtQgqOt0th\n9pXYJd7jYxvdsm4ZC8hDq0QV1aZNcNT+r/wIfwUqJMfy5BeZrtf9i8xRemChuHcbMRhIdhdf\nuX+VOXs/Hk+61YGrAJTA+AdhjSQ89UBysnin+h4vcRUmYOt0Od8o7hEsaxYT9wC38y6bHz3b\nXd6P8KaJBMQGJ3KCiCpFFTVAqnVLWaFC+geSdX7/3a8NZhfwNx5L5G18lQYQgNdx6xY7AZXC\n75TIi2XBhQGSi3mjlJymnYQBJ7XBRk/Sy+t5I1QsNQT0pouO78qSPFjTxVcRA8xuY5HSJVXw\nKfGnkQ0qpH8og2pZKg17ytruBuS/PTNjqY4npDSvB+zi3qBGykHKjnMQfGvd8rJrozKj8W91\nPG9iXIr8yP86/+OF3pbtza0q0jppO+/pB8yM7DLQYFpHQFOJzcoFFdI/lN4NLZXWtkaV/bZB\nWHCd1VJXEFy9TeHjHipLE4yqA4OAVS9UAuPFAkOIXnImAVQukHRRqBYhuqyLvAXLgu8O/Eay\nW8G2ANhYVnRuOAMcZ0tKw78NFZI9kMmXLjfMCLdUYklZr/+FsZuy4xeLumuakcOiXwLLS6EF\nSzKrI6YCi2KQt5tOWK1AfYLpSJdVpo2EvQwxkrFIFmPxVrgqEZpvbyIAy4lzyi0M6mSXGIZU\nSHnOL/U9wLOhTcfsDz9rX29o7v8g/4vfleZDqg28bQEqFmlNfjpn3SYTzdbAdXNlJpwiSW6q\nQtCPylUTqOc5cIN21i3fhNQSwyyc8LXhzlW8JSrzAk+pLAihsBLEHYlarPsmnXTDfx8qpLzm\nW0X9lTNaRfCke2kWdroGt+9bhekiS66MT5WfXMc3J6vG4a2dy6b0l4oYFGuOnY9n+BEnd7vM\ns6ucmQYAZb1L1g0fA5pdMi4wYDwkwHwAwvTqUnF9jQ7lmFY23CFapD0mFle8R0tZ7gFneIFf\ndOe4XntZe9yYpULKYx67jDocpElIUqKVUqbXnAaJEvrJbZQsPS/zE+ZXPl9mt1E0mTg8mZSf\nUuAdslzFuwDEgFYZjMnTtq3BS3d7W6qB8J5tLCx+nPhE4GJMBzqEcMqZ64e0HW9e/bzZ+/nX\nhOWPsbOq+7I1HxrqSIuuB4BXOK9gPf+YEyxpLANUSHnMPN/zus7PMX6pZQkx7k30KG8ulzvJ\ns6YyXtt7NQePdTdFVl1CvrT6AixpWW4A4cKuQE20GuNNyrYwSuigcSmCZW3TkaihKBTbJoZp\nqGDDiFe5875OkETwmFpfO8C72pe2XKRawgJiIPHaq2KDbLD+21Ah5TE9GreoZppa1I9OlDAt\nbknB9UZScrkg02WhudKCHO7cc4m53KImB7vLCIHAup4qMK3grwHpsvpq4VGuGQKl3qUAMAw0\nlnz8v+ZqKF2DdaAi7snZyklN0uyL2cfKhdkl0h0VUh7TvZnB7NncsCmS8KH0fX8iqSecvOSW\nU2AJc7fGnWjXJ8p00S+jbCupFkeGaBhvi3ugOzE83TEG6hVnX1djnIFPAEiSUFJWkRqasky5\ndmWBl0VJJ+LBWY3SzdGpjTJfB/5vqJDymFnBYNoOywmYIpXIPmGcuXyIfpav/0NgWU9sUxHt\nHoWX3v3yzYFkX4If259Em0+GnnzM6WM7nrdutwh4F3UJMCDdFBzsDBL7codYTVKguOrqxvjI\nE73k8qYdJhnlfJ6o1STMyMsESlRIecw9LW+6FjNNtx9IzmQCY0PMa6MxfjKmuL39PivkZ8Tg\nIRg/aM4gBqWLhzmX5vefvIe01dXKFBnvin8QzJlVTUWIAvsZAuTMgWepN9g7yJkh35lda9Ag\n057Dl3pe8nA2N2SmOw/fum20W3VZQjT/b6iQ8pqvUOjeG3s7sSs/ipKwfB5SWVjoZ0zj1srZ\nf1nzPdxX4R9JWb46dkSM/ZPTnwmrm6BM/N265QFmq2BXOrVC6pVJrUsqCH53h5xB0FL7p3iy\n6P+G0kmP8nbeI8xUmeLrSsqZlmumupv26W/6jJKz1f+ECinPmYNYUFTYv5yXCneNb1RgQkpq\nXJbJ2v1P6g+E6c3JpDBb3cw/chWTyNxOjiQ89KO47uvnMGFBo/mYTu2U/HLrls85tUd3jCch\nQUgsA1rCKJ5yClOyF2PZUoG1rJvlnhCLu908n7xbKFEh5T3rdP5N20XxM2wwPfnl9G25TJb1\nsrm3Qh9HOPA8GAGeOqht6x23BwpzBstnnqSTp++quTLKD7/ixf2RftEcIQfF1wi8elYG4JZy\nYdPGgg+h0W5gCmI3VBMYK+c9opdgWXOel5pc/w2okOzAg9kfdJxGPp75y1x1YuJapxiAcAU7\n58yaLRJpY/+N1e6Wj+3uJA85gUkJOHqIWBlaox3Jne0XDpCCge/LlWJ+xiVgvXXLjCCI+bhb\nhCHZU7vG5vFK8xQsOQovQ97dmKVCKuD4qkxRt2qBTREaDrcrWbThcqLLzMxYS2V8Ermtjfrb\n5ie0VtuP2Z2EyKqneGUJXuUcHVk7a10CCt1qvftMf9CGFHfxjUzM1XbL7f2XiXM2b8tR2irn\nvNu3o0Iq2PwIX5orOqkUeCIT2QafLuiqJXrYrPS0POg9JRJWv/LoC+Lm8naE9KDUz7FuecqL\nA1VJdaUz8boA1qCsYv2ENKsR0gYFsNWkUjz9O1uKAgPu0wlSGhJiSubxPFLeq1n/ARVSwaYf\nsjz21bTSn7Y7uW/ww8lNy2jqE566u5w58tVLn9kSza1j0cqsm7NZl582aDPmqQi3jt6OAGW/\njRlxybcDFLVuxNS0bokvfTF4Zq7CTKxkB17MvjVH39u6yYsS4SuvXFsTFfk4Z/PAuj2X5cUu\nOBVSwaYzZyrO1eNBUU4qikqtDvgH9/DuYxJRVcLvt5+n+Eg8rBH6OufwgnkHCPrcoQEAnfKm\nMbUpxl9oSYmQA2A/Xqu719kAKzK/Z0j5MXPJc5cppvIHhhCu9UUfZ2Gg3Z4+raKq06+xSyTh\ndu9fhQqpYDMTxBPUA5o0P4/dfbhpZGO3tQ+ce2aJVxwCCOc0WV1QfMuqTjFXjkey4RFcCMHZ\n9Qjf6mzT9k876S5eHVGXSydk1bjFoAZJYcUMvE8tMV1E7FXySG1njYs5gDqu3pdod/O68KVO\ntLjpciO5mPzvJCqkgs0bNgnjd0Hd90Ev4aHiyOG+NVtHRYmr+AyYh0jbeKemfTDi2+xLhtZ/\nbO1eIYTfZd1ym4+T1kcVcnipqnQ/z0imt/V9hBMqQJwSPN1RcjcvPcsS4xBZeDerZlCpLqeJ\nNn9uiQysI9necXQeZ38oxjXW7rWh+1xBhVTAGQ6ljnynGsC6i1OwJHI0/uJTUkzuDSfQXS/J\n21G4WcrbhsqGo3rpOcKU8e33Ecm7Mo9wczH2W/qjfrp1y5yJ/k41Pm8O86ortRVqI176nfSk\ntOeApVNr8EtIRtNKmsuXlYPTB5HyQIu2cdhYBrhSLQwAn0l2nzuokAo6n/BieKw4k2f5gFrE\nHYexASXFBYWxQTKOkAw3nuO0sa/v+SttgxGwpCDaE8Mycb1mGP+EgtUs05PwKO9S/GZUxtWL\nXMv8MCocPEiBgEw0jTHlov2cIzn77udMFxF/CeDi+tdSpBMbHV5NeLL8XmDcN02FSCu6vwAV\nUoEne2f1QNPD9LiXHpSlCe6er2INaW+zzzTRnXqrkQzv+hgOKjYd1CUvXgfODMG76bF7pwzX\nr/F1J0CMk7CkJzygaWG7oC1a6B2NxNCR3CbyAG4h86P5KKEdwSonPu0txs98iuvvYXwxmOgR\nMTcU+4tnsttcWQC/i+TucwkV0j+AbSrx6b0dXDyk3a6PNR9YN3ycBKwKyv6KZzq/yjx38i2p\n0Ux2supFQFcj/hlq6FSEp+4n7yCmdWMe+KWZb6ADeFm3fNkcgTPPJkAwGwgKALLz4TcG8e32\nbaSwpAklZGK75F903Jo6KvMnw4/oOqHFa+x2hQHj6SxCgpKYhcTucwkV0j+AjJDOwjNXN2kR\nf0F4lpSEaw3ZZYNm3MZvP+NndVUBsA1Jl48qpLqv173Cv7qhQBWjInjSPvlMG9HdCYQXzGm4\nnQ47CW2eV+qKX1H4aQcowUN4fe0j/VSrRLe8hdyg0zNCRimmWLd7PLy8lyHGEoelCDEp1ABX\nzh2fZ3mn0mKiWSCs6HINFdI/gcPa6mv3oAbszDejIjhGP9v6eeuzFoxzMd51bomIjQ+e7q5Q\nhHBXYjuLBlXBt/XMoqGV2pcmTsT6x7wGZ6HsmCBoiegQ0QG8d4CmD8upEELAfE8wPco8wPed\nPse4RxpeTQrsKlD+E0sldibJLHsIQDkdqALDePCsLOuOAxXSP4LfmroBVNrxvLT/ZweGGJzr\nE/Ycbn6zYN+rEUEmp5mM8k0Jjc5GWv8+3mjCE5/PPmgxNIxg+YdfNQjHT/spDuI7kEAaaHYR\n8ANWzyAvhFyE1wLhRZcT2gfPC8jB13TLBYFMILWKm1jCyWY5S9xVGQolSrhX9OX00CGZA/QN\n2ToXUCH9U/hGYcS9wx9ivMLvNxcp754Qiz/PDgXpFz0XcenOI38pFfs2fsw1IASxw1fKAxPG\nBO3G+CuoR+w5q6gYW8jVmfG+14FxZVlC9JTdiq4d6jzb4F9DeMG2I9+rWOZsjjz0lUYq0okf\naHg3Jx5UQaOChFciIVNg7qBC+qdwG/38TifePuiZisfGkG2z3jvp/EHO2LyUYZAO6j5YyQ9J\nAq86pIlYOHx8JFNo2QdJ5LvM7idmpQTPp0atsOIHF0J8ih9igAFV/zcYX4z0T+5O8G/PSow7\nLbzDlmkIaykL5U1RwjwqPRtqirdHDixrO1RIjubxZZkiNNSsclb0xj6lXoP3seQ2c957K/wO\n5IDGq1llwyNHB3GB3v1hYmeOcFv9JmKnv87YHgCekudDNQQhKTZmBIAu2RMhBWlz4nOng2Jz\nXyoUqaPrcZ2sr/0e1YWAMgb1JKm+sXgczcBWdLkVJ+ZA56CHDd9iA1RIDiX70wAAVQNZPM+u\nF4mGH36aqG9lzJmAqnfcRDrlTxhiLhe7SviMH/BEgGKrF3sw1ScH7+IJp097eNMnvLtUbGSM\njYGCoR8Hvj7x7gCsco910zcBongOs9Xdn2L8swspH8C5ZVM2PZTsW6QXQGv/kQhcqmmdkjUS\nm/C2UrCE9GTpoEFL7RLvzz4Ym7tM6FnR20W1X47W7rUVJv3F5uTcL4HEzV0fwp3cr5xMvtLX\nfYd980HFBqMJF0cvqDs9e67cskkt5kjvRAqlkDGmtH/Vz8SL8jtLOjFuaYR4qQnCp4eajagE\n5ZSwmmMJl2Z/ck6c9V2ch5PpDTpfSvY2Uk8QMosUSQaeC3AGRpac8gVKSOsN3mlp3gbC772A\nsVa92T9s2OKRek6eTK+doh4I87YSnKLHm6dLVLpXVg2NXVXdl68d7FItTdVkTN9o/Vbrbe5w\n860K0ewYsb6acNr6L0YirnSjOFZx2LpJE1DofX1Qa79EvwZKrYLwOXKze4yGrWLe6LgPZAdW\nm2kuzulieJY72rhDEMcTjnttpiAJ6Ud+vPCJlDWeJ7jr5yceSc400rpE1RPdC86BRy5Dnvxv\nHhaLWnZhFlIki9cETqCOBNMNtfzcq8zvHiA+osaPNYS319MF9dFEs2fDRhcbBnEUhd550SFM\nx3CEQ6qGoChSyqArwXCc8ExLhI5UbTeXP0GzWYTQX7lgvPDK9ub4PSf4nX4wyl+GdBUFSUiV\n25nLdlXyfAB/n9dDvAG8BpLXeqF91OYwxnqXL2Tp9WlPYdUBHc3XbYLJQYoFHlluw+KypESv\n+A6yRNgfkYizJSNa1UJXf1Gj0CoBwBCWVP0Qo9AVRQqPRYrd1UPFkPzWCTdt1r9sjKB6LNNQ\nlo+cFQga+4z+0q3tJeR2hxjB3EYKkJDesvvMlb0s0UksX/AyIXjhmbOLQuMJQUEwLppW2Vxx\nSu4sV88Par7/5VWUTAz0nZNld28SKa0ExlVrm+Rzy61hJMd69SNvCfoE5uh04otOoeQJHqw7\nWDffDznu15YRmWVTPDmS58KQCHHrrn5Y3QSMTxeVvndkC6tMqTLGP6mg74JZmwLHkClAQvoz\ncehvcCfPR/B3GRpkmtc9Dh1AsmoSkWYqj6EWkrHrbabT+7D5YQop09XelsrcwO9JgXguuKbu\nf3Zrpb+zMAtjATTE8HDu0TPM2cg0pVAXgt0iRjsSxZdz2ZIA/uGgIDi+PQ5OPocPsS2U4rN6\ngRRELxdMBrbK4qFFtG637gM5lLJNFCAh/flG2pP/30hGb8tUbYk7aSq0hzGt3l+Xq1NuuGx9\n7wHzacpxRMqXbOIgawp8mjNJCTy4LbBueLm2oB9deR4lKBVOCFhS1NY45xStWN6CNgERpN6/\n49Tg0ul8SKD789V8cyVh8+xmCrjqIWyf6R/Jw0iN2s5XPPBqFHsWT/OW4SSvAAkJV21rLttW\nzfMB/F0egyWX3QVycM8+UH3D/lnFQtcwNuWYtY1wTryId9CDIbiBm8kqYsoh2UPLKJOr6qAl\nwfTNycvZ7lBOrVCCEoAjpPWbB8EeYlkH7S0eQOx+HQdVf26hVm3HI1TzZrmQAilcXl+1hulx\nfzI5wLPFAlk+SS9pKs07ZsTrVV/80rNSqXak24vSFCQhHeTHZWKcOY6XJ11xXvJncM+z8IBo\n2IFRc5G9P9MTZ4C55JEPGKLcgTG3SXzm1nHjXuCfGMbtEc48VRnIJyoPgeF5pkkxUAMoCDuS\nEYg5/2BveVQFuxIdWIUprRIBH3EaP3SHsj6QQLzp93Gy+PVkkRC/yp09Yoj5OW3lgI9nnRaR\n3PgZXPWxU1sqW/6dF1NBEhLe6OxVs6aXs+QHbT7A3+IVOt9HYsG/2BucwGWaYLWna6XqH8qw\nf4Rx9pjieq8aYjjwH2vowaUaIW3XWm82RAmuD4yz3IRxkM8m74NKq2yq6nz5tLBQ8rf+/siM\nN/k4NHy9Cj6XGOkmiAn6ImNPUZYN5YVvqUiYB+8X07O/8mt1UbEbPy5fQZYEy6+WDfxg5tW9\nrOkg6ZT72L/RVIESEn66bPDgZbZmVXAo43zEMFn4tu8IKcus81tOZQjrlK5cvXHDkjkpv+1c\nsYhRKyMDGWaRdZO3hxcn6ubhj51G1tEJj3JjQms5CsYJRXYWmmUNDEe6y1Ma4pZcyx7NBGct\nbRaXMpBwSDWdAZZFHKutvlk5txeqRGg0Nfoynu99NjZFqN8gZ8TNHbUtS4aF7yN7/RUKlpAK\nDu9SPCft3TfZO1nShdPCNGeT085yVsZAUdd4buhrYVkRzhAd4JrzWy6yM/TVNkWjZCDts6UC\nq4Fr+HEAhCqdSJHBc6qJDt4Qf6eioXO/WgHK1dZNb5RQBdTU+jcxrla/wO3RFuuWT1P58iGe\nfDXTTarStrin2oiLxdvu/t85T6JCyiMyp0bzfPFJtn7G5XhZ5oLta8g3hpFO7UzlEyaZZDad\nm/dJieiWxtsseHBonHXDpywg1eXlQRzrjjTqgWsJP9z1ya3GnsGtI/bGcRGleESY4t137XAB\n0PUfXUf+Pqo8hGwmzNn2jQ8qZ/qcefKJm1uNsY9JP1QuUFhy4rwBQrBWKaiQ8o7MXMwUfgOL\nP803OvkGUAcsLnxhxPyxj5RFOtZk7jz3ZLQrE/RsZ+uP8kkkLH4YxJbmwVmfpo+RSFVzB230\nqn9PeEL9GUL+pqN+rqBKRD2+0UZFC/O8RNLmXT/Tx8w5v1BdqyHhRWTa6SxquZ5+Es0aPu+v\nuiBRIeUPToDFBWIfI19Wuarv995jyL/PlUjt4/GxC8MtxVWK+6gIgY9vM8A4B7nzwFZtiR9X\niyTnTN7g3LukyV97gnc0wezVfIYff+KSqrW+iMq7Bgom7DMe4H4RntmiDZcrb/4wq3QR6165\nueGjcNNvJ7sY8k+JYGpL5J63AhVS/uCP95nM55OPXnJFL8tp1msVt+WrY4SHfr0KkCfDTsvq\nDbySQ62tm95WAhJWP1xn9pgw1XMj50xe7h8kbgO+GeOJoOgGgmFt+AV3K6P5MKRYm4f9UTuC\nZSvvTVnrddM1HwTzUUXB5xixfwsZG4b3nEO4wPg0vOzPOfh6cSRu9FyIS/pLn2RUSPmESs1M\nxdvofvK1eRY1NJW9WND5I1/CscEjZ6gPP+CuShXoggACrL8UXhbjnJw15bkFgk5Sta4fkBYq\nBzjldqHtEGS63U1w57updN5ZvHyx6EAmXLxJVcJ6oxkDlAo9MgzSdHuKcc1IPWFn/z2/hulT\nmhRjh1ufsd5NRxpXQOZ9yDu6v5QLmwopn3Bc0+mO8OhXCchNji0pWkL64Zu7GiM034ifjuQI\nMXOOc07waVfgPRAKAE/wtb7ZmPNVY099t1M4Iwq0LkrEEYKIZ/lqlwuPO+JUo2B4IFSzbnlY\nLS6+IlgOMQrxAjgh0Mqj3SlVXtZsIFZbdU4lbdebeejZTJw1b9aSUnXc2b7+E39z8+tjyh7+\nC4dUVEh24tHgUvqirQnekYcjwdsFql6Xtdf2YvA4BTKfsw73Ixzd/6hBBj8di1xPLPDF4ZBK\nanV+sPClHJqPG3d+GMQQHvpNKOz+XYR8KsSDeyyCkdYtH/VSgqZqMOL7O5tOc0khi6ZGv+ZM\n19Pjx2/SSM7DPo4yC1WGOQAAIABJREFUX6tdqCefRHxSQfw6W6PTMCiQHMnif0GFZB8u+UZN\n2Ty/joJwopJzavVG2TNgXRlXv11YN6Hy+pOyeqi0z7rl7VAFMDr23LPwQRfLKRFp9XOd3YFv\nwAD8u2YjfqtIJljOQmAA1CmaGfR0XklgCRmj8XRlzxvAfIgERCcHwmN5hVsI14Xye/bCGZDc\nGkiwxI58ze0j2n0eLnxZqAgV1oBqQJKh0f8bKiS7kFO6tmlXd5rquv07D1+I8R/R/uM26Suy\nhHPM236+rjHlv4uJbIecNByqQ4iN0c99+0h4cyY6WXgfVNKT+l7v5AJ+xaDnbne/UqAFQgKl\nN77cp6B2F16hYFpTEQIKjNTAPvxsvm4o3suQ9w0FgpdYKh7ktc9FdBRnuBWDD9wWid6Hub2p\nQ4VkFw6x5ijbxnj5rkvYTPxUjBuVfIqzNVs3MoQ/9y0x5Bvfvk2RLdqi0c2jK1t/6LP7s04o\nnKkraM2Yys07QHia7w8C55i0K04fZrWGHjoV4dbRbWfxspMgImWKXlSS9VRkxhksuIHzp0bc\nvbz19iyUsZwwv+IkIsy0Cjn3AwuNUou9+KKmAQJzedxLhWQXZhe3VAbWtn/nvcrjO8xBYSrE\nPcINSVclcsJQXMYFtD0lgi0x/KaadK/gelP4THRwv1gamGKcPyk2nRNTadQHFfEVBdpYqqEr\n4ZD6USqI4Y/48p4lwB+AI7wUVnMDT7zFeCm3/db09k2nEIJD4BER5i7nGSTuXryuz0XxoI0+\nGs4wOmEYudu8o0KyC9MteeXwx4Stq//i5bHTkvMWkexxcW6BtS9YN7isGvOdxoivBAprpc+J\nV+1uKSG1ut41vGhlfh+uS4xI8hCJaWjveqeyaXsmVeQI6TFXANcgdOJXevDJCJoJxJOfksIb\nEVVxnYdYV+GVFEQI6DWVK9Oze0nF3MUKDQOIIeSPfeTTUJykrtfMIPVsYn8bBGszSzGdn453\n5QKY85Lf8G9QIdmFLU6vzZXa3W38jmu1xUlOV+m8cs98wTO2CIsIq59vtcHK8S00td9gvCiE\n2NjvaqRyiuArRKesq6BAYf0J66SG0DMH94xw4UIVJRJ5jnDeOty0D4cMp47DRSXBVwjjFwrB\n0j1UWCe5iRmMXAhZmS6MatxkzOVdLNNm140fqogZdK1xNsKpYt1gzpY7Ei94eHoY0nFOnK/2\nV17iMtV/QoVkF954f2wqD7A2hhK74ply4OWjTRElJb1gYpnZ5cCnCAAhocnNblCy03pxzdOr\nJrm1B8UZLr6EokpPZf/ydT+PDCaEjqwFjAsCJ33LRxgfA9I76VclUhTr++BGRNO7QPaPu8uJ\nomMhzXSEizRScezKqkxXfHFV5rp1o6zN4/otICWf/he9ofFYOPyui4ER45InnbDpm0xQIdmH\nzdwHJ95c+UxH+OT8D9KrZmH8x7qPXAj590z8Bv18UxqyCmEuRJq7lGxh2jq4pF3+eMfnWwlz\nJuNcqDNixzZu3x/6r/Gb8mmENn/tXQn17VJOPMl5AVWiCJYndHy7YQ3VKS9GBUic+7wQHmBv\nTzUCV2CgNehuEq3fIoN5AXSQHM/LZrJ9QA91fTwUMP52E2iitl0cVEh2Yn8p4SPOe5aNZ+ZP\nuB8w/lTtWsEDkklZ9TAeBd1jy0TuzcTJDCIs+Y9r6x96eWOJV51RanWklu9HWH01Cr+AG7S5\nW75kdsa+wWgLccTO63zE5BMLPACBP2F1ftXgX7nnN+9mcpIr+Bfi3jcCHSAlBDLgRAjXivE9\nsOzaXYaGUg3bRlYxACcNwBSM45kBMb423yKlQrIbT4+SNpf+k5PwDM9WLc3Bu9kKkcQT+Z5M\nQHN3MS5EKw6CCA/9maoMgPOoAc6rs7HxO5+21i1fpnMV9ZHqMnd2+PFRCMWTEr/UbcbsxXiE\nJt3rKXTkCBfVL8TxsUnO+iWkH8XMI9Y0rWOQVs0LEyzSVSacycabK7sY2cKZLQJdQpDw65kE\nfHpVMNgaEoUKKV9yDu6/1ovP5Xea5z7E7abZwMYNFiulDYCsH70IvDp+1XiZ3WaqH2dJwcb3\nj9PV2ZJzUDHwBdZ+Vd+TsE46wmnW4HPseO2cqzC3hYrgQprzw6xPNlg+37MvXSHM8LLCBB1p\nnFXI1R2aIQ6WEEZakjd/yjTWTCVY5Y5G0LvY/JzxgPbgi/p4WyPtUCHlSzIMy7erxGekb0U8\noDrJ8hXDeywRystMDdBLhoWZ/n73u/IQol1aV4wTO4pBkK5kJZC2wb9iDT2T9MzA5/HgEo2U\nn0oNQOBRB7UwfepufT/SOBABCz4eSQ1cGfHlNNd6W0dQnPCkvOrPaWQJK2QmFUDNCa/COzUA\n+SKlbTkbqJDyJ4P8Pw0Sih9Ua/Fs0qU4YW4H3CScs1ajGu9N3lsW+TDdUulCngqtU526Dydx\ndu1KGC8uQrL8ji3uG3vMGIeGYVyrug0Z8x6Gx32zpn9Ft0DC8qMXShLmduVZ5BxRV1ASIb/Z\ndMSGRCnVLMGHMfccCtWXgw2vIsp9DkEIECkr059QIclI5txawaU6/SJHU2+raxWrFnfi+wsr\nEFJoHWzK9qNgwH2Rrisn6dYyuoK5XOOhVJcab/2o39jK0B9Ob6roflEQMyLGe9uo1wV3CYYB\n+HFvFbCImFVcpGvM/Vp85Y4VkTdhytgWCaukkqgswwSJWw+EedupijrQ1T4q1WvuOM5Mh98n\nBuzmXBYshkiJcH9mqJDk41lZ9w+XTKvNyZJYIns6cgmu+52wZIgcJWE6FDRxjVOZjiFdcc7l\n7b+RHvs9CnEP0NhNpey7fbxvaevTq5yZAQDaZuLu8waiVyrGD5o6tSiZhm8HeyNwAihD3uDO\n1K+tF3FhYpB48krYhR8B4OKGFMpajEaM7DqI1OTr95Uba8avlMd/fhYLQ8KTef1d/J3yLnCE\ng+H3UCHJR+so05PxJSvLOwkP8BIDcbxt5y6ZZmk66xZaJV1X7fVSN+HjW9Xf+uadsWwF4a21\nRl2haIaYTYl0SGX0/cjcTnOp9A9PPfqmDMfpAazBdL81gvgC+x02MafSPGZ83hCQ7rp1u2nA\nKH08azshpCjBMjBGYgwCmb1Y7yRfpqOtAdCIHHY3MAHMNYwbp2F9BFHHZqiQZOM+s89cqdVB\nlvay2jHJPZp4+dkQl+BivyqxzVfkTGWZOlOHx0I565Z34lzbjvbWhJr21zapSH4TCzSmJdcs\njniUI7JP75q0ACEN2+dCYHNv0k1YjO/CwPjPXc7UVpQBH6QjbPO1AMYZWIZnGDHlE0jHsevs\nLZ6j/RjYRNLSFvZyXo2L44xhyuPv2JY2hEijQpKNre9va84k7w7YzuGRTbsvsv03cYtTmeKP\njgdCzvuMxR0r8d3MAnoORB+Yj5iK/bvFqpdJ93y9gsIZ6T1Gv20AXuEI6hKOe3N8UmslDG8W\nfmli0R7lUTDh9WFyE2JZJdsL6jIMmiUxhtOMIPinn7Usw4yTJQ7TGgWrS3V33yq8vwenSJtT\nIcnGejdL5ctQxwxgFm+5euPtTTZ0sqSMlYqIeHJY/aafiE5q97sI65VAglfCc58UtpTT63S+\nEl6m9dC0JzQ6Rheu/RwdP+/yWUIMKJsTErH1EpWkQMuKmIOntCGOFU+Mx/ioT2BKOSUTK0tU\n6585pv/KF/hXr6E1bHDsokKSjV+Q5QJNX+LBT97R7X0KjNrwmmhY0rLiOMDaFsPtgk5Yz+gQ\nELYPT3iDk1dVKPUM9/CJL8UQVokZFYCv4TNYV78ihIOKNeyzbtpekE9VNw0gtcmXNZI4yD4N\n8RPPpiV06ZHeyEOWIKwbGdcew9P5lt8zNmwKUiHJhjGim6n83UCIWZ+X9ATLllUqkPcnZrib\nnJUyK9Wzqd2cUIg/1yUYsdDAutFzP6QuGZmNT6mda9QsTYh7jLOTEMtVXFRb4cIjHcsgQk7x\nvqJ+XJE7INPJLDGn+siKeHJIXKU/cJ2+W6CCxI9kG+s4v5Kd5o5RDbXBlgpJPn5QdrqQ83xT\nUFUZEsD9Fb6GNabyjUFNXiVkVPFbfPn2liQf2+4WHAK3s+5lvlzTnwHC2eQlDsrUOzrJEFok\ndniTHsTuKwObGgpePqxzbKUhDPreuulYQC4qEEMhxUZVBQgitLqPv14nTfsHfuD0DfZl5El8\nfzKFB4j4yhZTKiQZORQHKlD2Ic+r8o4MrYe4ds/uqJDy4Hw7zBVA2YxwIvrvfA59SzR80BAM\nSgCCQg6yAMjV26OH+mZy51XbCRfFc1IhqroBcYYTSo3o601YfE0QNCQskXjfK8pgoSSEsTMm\nly5bpj5+WKlkNo4PJL0Sc0Pmb8Rs2v+CCklWbu087igZCWxjtL2WfVKMd7dBIbeIB7f/wVQY\nzNxMDPN0CwAW6lq3O6cDl5jqFVXrlyHwVDINrS/AjLVZFhjFbmfw6FnXCYAQu3EdI55NRZ73\nAtPsroj1mA9/lOM00Q308bfwU7VWnzDIvn8IKqR/EkcCxNVEhau5+Z6zzYswHrVJoX+3Q5Wi\nSwz6D577A89AO+uGT30NHvGdz69GXmVFryUX63rO+YhFvBpB4jtc30epQoT8TdvFaxWfeAJT\nTvSbAA/rltkDGLe+azLxJT0ggwFU+wg/k+xQIf2zuPn9NvJFwP/mO4UW+XohhnDtJ4NVRNaP\nKvuiuGkXGkKtL8DulNLV65vOeDjX/eXlzm6sO2FadI5n4iow9/EA0GmDQEHwWz8kvJFK8WxD\nFfCI8YZK1t+kOSXEnYvXzpDEnMPn3Uh5bmWHCqlw88igavVAKKIQ4UhpFECY68flAHwTWgcI\ndeuWWWv712+DkmvnfOPNevHgRdjNmAC6ID88AhU1BI119lUQNsznCgt+0XW1hIpVqAA1sC7k\n536gK85DvLfo+3QLNbPepuxQIRVuZmuqmp7L13wcwaqb+V0UsJM5aGBcgHzraJOeObSVK8+E\nxTKgJEQvqQnAe0FYZAR7wVAssUaWdctp4o6EwkWBoOoMUDPp1tdJr+ojN2dge5oswojb5TLz\n94UkvmkzfjopS5bp91Ah2YtOnDiputs7hoGmhAA/3zKgB/hQ1V14NQiL/jhSLsLdHDwLSzIs\nThW1xxGUlA7gCShWPbw3gBoC1lm3HAfm4EJF3w0DDtjKhH2Si0vDWHMiwcO+bNcFLwgDlZW/\nK6TsHo0xvh4CUMG2R994ddfGjXukghdQIdmLFmJ8rNMe8TPjoKqC8CgfEJf8UYvDGGDLIBZ0\nhPyUz3jYA8rPiwQjDesN7z15/xdDTKes81vwsG8P24MjnNccNrk2lHs9XkzyzICWcAEDdwbR\nkzCrA6NUNyviI+lxKxN/V0gT4UOMa6PuPRhbglo/GeBpmSSMJTq7UyHZi09gL86KbJqV7QGX\ne2kI2+ZbBAkNjRPeR8vGsoZYIE0EezIdeEPbACXbrMrXal5DcHxrA/DBjg4ItT8ULkze2OXW\nLc8jaADH5giPTjjXH0BFeD6OgeiJMNhzLmqO33VxuUcYqYz8XSFFN8T4NuqEcUfSr9bC3WAI\nbz9q6pThLYpAHCGIJxWS3biGUvBOxUM8nRODnHoRspnsZ0GvATTrKAteHRhoaP2T8G04Anee\nUQzlv53nHsyMJnQ/XjwcYsdt4tzr3j2sZAle61+bPVehfuVGv8AwIMXbS0Sjs54q+yi5Kzj7\nQoiMGRBJ/F0haeeLAYx2YzzXWfobO/0ZmDx7LiKEa6ZCsh9doXaf+J96Imh05mXTcHaxdcuT\nwLpD1+U8g47jCPAiBPTKKA0ImJrsSFyteAUgRv7dyXUoO+yFW3HR+y+hNUeIYP6bEyCkiKjp\nce0Lr9WACOEpMoXuRU/X/2PvLMCjRt4/PpH1bt3djRZaKBSKFHd3L8Vdi7tzuLu7Hu7uLod7\n4XCXAtXd+W82KXf3+7OTlJ1uLZ/nOTI89+5kaPPdjLyyL3WkBVNyM+NP+G9grJDUOiE1USVD\nOFvF/0HH1v+0G7n9z//83KP9T0qKQjIZ7ZiveiVorGv2qjnL7I1hy2Vs7kZiONTagrEE4gxX\nWx0Autlx7WiZUw/UbrmOLba0ozsIYkoZBs0uglofvPRm3kjlHry3ouS6cfggjp0PN/eSTXgP\nG9otfTHbs7X0EHIEeDB6atcUvjZjnILbBfB/UDL2n/YI6f/8z3dNG/ykEDDZbovI/dp09dL+\nTCu6r8Z1AcLysW4lQ1rtYXyRwG6H7ogMWGmhgOjfOURVyGOwLU8Jo28t7SoXYLbgHxIXuyBL\nwn4IoKjBD1fZEFR5IKsklaO2rI5Iv8HtshsQ9i8Du3uZwIvYWCGNA8WcwTEIV0gFxLV7NPyn\nXQvlyStO7YTwGdO3zVfbkTFMKN4e8iqs3gdlmSQnSuhW8iftpCSQSsjGhr3p0vIDqZu3Mt96\nMwfUGonhtXlJJurhS8lS+33NPSohylp8CtK9kiwoak5Ngrz4hEYFIidZz4ANW+j+ba6T4Qf6\nJM8QMGCskBJbKSyYIGCnUNTmAUcPYhK3bfptGEBlKBSFxMuPQe4AeA7jKZ4ljC10YOUvt8Yq\nBkFYusmyYwjHnpMEUNcKIWSgzikzT3sVIjW2tgBwrtS2icTbiffB2K8gBy3q4xLYhtLJE4CC\nhgPVk+Rg6CZp0RogyEcDGwCUg+BC6aLwKfBxyYDvEHohVn64wOXZcBZxMP2TTwWBulyrLl1i\nSitBSZRURCHxkVDYY97lS7Ndi2PJmXPEnanrtQSm9ga0p8RsvOHT9atqfWLu6hskgDnakVw0\naKltRMgsHBQBN/hvf9/C0a/q5IVSUtfdp+FEUcOWD2T6ci+BkgMQTpAgSxLMUtHuflQpZv7n\nuIZ/DMZijJCe/Rchd5sapk+RLim6CDltFYXER1+vt8zlletQLN19tIph+msjt/0Kk5apBxu2\nTCvg1nsNOCMhQIVZa/MBEqGT+7O7DtuK8oH4yTnzkktOupIkEyz7pSpAFHv9WpMAEuB/CGqm\nWQAgq4Io+/KhqtcCfQam68hXFyaMERL4L8I+nHj/8uUHfCUdc5+Q0ta1KV5//Ftc3WlsudnK\nXBc8He5Xlp2/py8w07uu7qQRO2JvK1AetO4h/hOmTguggArLb+pxrJdOILqbH9Sf2JdCdHqH\nCL+vgdomahqo1YBGnHzdouczl6/FBGTTMhpjhNTov2AcVa4T0pdos6aju/jbnsDU3yvAnbhc\nBVgy5kB4NzZAYevEfMFf6hgli9iGMD3XlfSTFoGvnYBMSgApolRfRngL8kO4nbCZcgw4kXaI\nr9rKxJ8QbpBLaOdUzQFryWPDlkvomnM3jvAIwJhg3yDYvL+/4XTFyHVCahjEzHxTO1tjeif9\nFBJTSAkbzdvq/phMVx6bL0jeBLHo/Sz1AwO1ntTaoj4SQJKIU9QMoFW6Q2jhmAq3Un7lQEXD\ny59kNxAY40BS9J7B5rq3lw1icnm5RbB9ydEmeZawCWmNk9Fj+YfcJqQHTDHvpDl1ApRRiC/Q\nDKCxX8w2Zv/vubYxdKyvm1sxRfVKDr9uiype3FUJBu4F01uC4jSoDeQZKv9tkNrE/ZO6CeNj\nFRHQ0RxUNLx3mNKK2XLwPF7FaeWDLRQhR5V6MhlGC+ndrD49dHRwUWMbU+4T0nJXCN8Xsus6\nJ8pCJbQEHJoBHnoH6OfOfKc0GWGV9RdYKRbCl7L9cJE14pWUGAGsChEFQdNB5uCxvzw/lgPP\nVzLLdiDlvBmlfgO7kkGI5BAw9Y4DuLtc/eiQs4oElBSxOWEyjBVSvB231UALSHMumNwmJKbE\nUc3wdxCOjRquRNcXFsi3Yq4zzp2Z6hSN5SCJI9Gn7g+LP+HnshEa3eQRVfJSawdkVJRXd1ru\nDoubS45iuf1Zle4xAoTyALyfj/Ag+qD+aTXA+fI9Lsl7HSPAGSBHl0o3CcYKqZl69mGweN8A\nl334xpT7hLRNnXwPMHUpWzXShgtJN6gj5cqGY4iNhMQRviTlP4Zv/zNj3PJwJ9u2cwh6Cr9M\nAZGdthgO6v6mZiL8LCSSv6Cne9hUPLf/2gWY2/s/gVsUcvUiO7MwRM6FfURzz2UVG3wv5psf\nqiP56mWYAGOF5D4AJgLdJPWqNZ6UfCy5TUhfLWavZPapn5qth0PKCPrIWifgIJF2R523fsdy\nGPsfvkw182w89we84moHetZTlja8k5FSljmYDX0EL4IOkfylIgTiKa/SFcbLK4LxsHLPQih9\nVAVmHajugU6y1Rr5aJkQdwAIP0yLqRaXSR6sxgpJslDXxXFdY6iAjP2CyW1CggukDfyh9rhf\nWQ38I1LIB5bRYz7A5B1uNbCG8AtgoF8CkxO/We1one6D6yIsiwE33eC2KZRv1by1a4XyUEHY\nDQuXg+IQBg6cBI4iTOsCAlh6UYPhcfIkQEXM/uSYnWdsn8p0Y0FnxBnFWCFZj4bQbJmusc4C\n15BgThRSyvG5iy8gHvrFauClJmO+Qhgj5MAtwYqdLd2Tow50MoNP/pHn06Y5NTa7qpu/rUHV\nfUkNAaSFBFj9NdweVWbpP2gWlrZxKL/a8A/qQzjQrZJGQbgQABsCVECkIZpPgPDOZ+HHAo32\nETXK9Y3nu/dz827Mi+svp15CR5sRjBVSFZejsFiE7rFvZ49vUDlPSIfc6UBvMgxxpPHBqs5O\nJpL7vkJIlext6UkRmvAUM8HPy1qEXALCL8FndUjd5K0Z4uSrKe1VZe75DvRWoX0nV7Pst2l9\nD2Vzw4svbYXAkIk6HRF+8dB/aGkPxO0nEAFLto5wKbCcYpKxAr4pUd9w9q7bJQL8qzOMsUI6\nJS8ElwK3OmGAL990RshpQjor66lbTbysa4cIkdlID3oJf2xzqy5ksjYjPXB/VEkc48sYrw4U\n6KKFL9yKH0ko1Kagv+ESKdoFbkwE6lHBPY900NfLuGaBSEf5pR5Ql3EnvJNhguxgYmh3RHd/\nEHZWUePPMiqidH9Yo29ehIuGS1XuFjxg4Rh9jnRpLtQOVACiJs60ljlNSCXY90Za0bYIo22e\nwJKS9RS0Q7DYi2vEVRE8iMvL5h5DJPfJCDFNIGxRJAlq7NYkBCGTHry6lAHPCo0jJ6BR+VBm\nUyVd5pK6x3KYUxJchPQlXCALatVSBoDSJm7lbAkyIwuEAfO5hnNmOIPj8WxIjMe7gZTDhPSO\n4Oq8rkDOb9Nubz0jsLbBLcDmg0sLFno8d68I4RkkcUGUSPnvWJDvxT+V8UnK7RCuUryDSwXP\n2d9f5Klb9jzdDfs0gVK8tqbLFPDhSRwzZTxJILcGnk5uFUsREv9XyZNLmgN05sqy/djrV0lm\nHOCKmVYxcB1w05/TANe5TtWCzOJA08dC0H4UhK+dqz7VPSP9BT0kKZMKylVF5iMWKuX9toAn\naUuVf+hedECY+NcyR/PmiAJKEMYDbu/gIvr3mxgnB0rgw8zApksad1yAHIBGt5Db8yXSYehq\nAAhUzofpTuzLc5It3sM3FmOFVO4nOCfzOUxIT8F9trFdiavLd4VsOs4YEGYh9NSjRwH26egQ\nzm/7o5TDmAN7hljUMXz68rU5CfwVqkm65ink2+MnEwhV20XtXABqwzxZxW1LLORzzPxq2+6h\nTueaLsCiY0NnB6TTPAXIlDYBb3RfZ8CC3mvY7ke+yDu6McyQCCocllGMFdLPaCS1M75B5TQh\nQS9uHduickY+9RZVwSd5QYMCFQcLLAUGoec89noT8GWxhXCAu74I2F3r6Qijx9Z19+l3t4YL\nqtH+lHJ9O9kKmAHQDWEVW1C/BPjsy5vgY4olU7d1pIrSKSO5kzkqatQPkJ+lurdXXQLY1UaV\n731ZEbiHKS0W8937tzBWSKl6vt+MKyVw9i+InCakxQr9N+E8Wni80bv2doD0my6okv3RQQ26\nrUA71UkPsFe9mwmaNBt9UGDShfruqNCXCbZ6p+6LZvPX1Q+M7IFI08UwAhztYz7/I7xCExMN\nW73yLLz7/eut+UJ4dyg07ST1xg+mKOadCLURqKOfgwAsI5K0Q4G+JJkL6kd6Y+W0fTif03+B\nbY00oKPRY/mHnCYkOIQs2btzmFx4ko3nHgVW3Tj3h1V9fiUl1qXLdqln44MoxgWh7TquX8Ab\n0/AUMPGv6xwJe0C1MpyIKLW+WbeVy9rLWxamgFIBqEXITqtSV8lDcK01Mzmpa3gj43VTKQDy\ndp90b7x2gTYhvRB7VAfaRoaR3LfCxDDUvWsziYzlTHb9nnPNmqpwnsMIB5uQzublqR2EVwfW\nbjAqA7FGdYrp3zC39V4haFp7MBJKqOuG+pnUq8depzvwKvMReArhanrM53Ngn3+04QgI7aoq\n7l7Vt1Sjo5vSzHc9ch+hGj2kGJxO0ISEJIALYksw5cYdZmm2S0qq/KyB6hqq0y3pJ0Mr3FFm\nsJY+cSWQlJoiBQoClMwUHyAesAnpgMTosfxDzhNSBnlHcZPAON49mniSNf3hOg1hdYHW+xQd\nVc/gvXeyejNMtJ0A4SwP+Mx8JY/1fRBcVCoBUjkAqLPRMaBG23cSSdg1uWegDYjmG8NzmWT1\n9dYFrCkpasp4huTc30fy+CcelzBvwrbDpcCl51Ab4JkFSjJWSJ9Y3h4N88Y3qNwvpFMEtwW7\n2YbPdHn6kWRXVKgbXKPI3ymuDNlbgN9E+9CE/fJv8K3bMF27No/xUjJWIg+7oGGqGSFiEr/Q\nlk1mArM3dQFtHkCC9jyhfgPIxRtkFUfVdwPKeMNWqfbseuuHNypcl+GWZdG2rpdp4K37sU7x\nwuplIxBsu3YA4fWRYXK9kE5zQnrdWFo0ZhUyCGBa+oY2j7fQ0zENa/Q/z/3lO6rLdwEhHTzu\nL/cq8l331BXkGekkEARcmAX6AGQhZDiPIINBhD9Q/6XYVR6YodJ/6igouS+f2JEgzACgDhg2\nWy6Zr1PkswqevJsT9yoxjkIezJprQpH8tGAvWmwYK6RqLLU7YQ3zyPVC+kAfYS7HbKxdx8eY\nF0c9J+tsuFUG7VU3AAAgAElEQVRP64YIq/903tUTyCKWGzb42EEBgE0c87QNLcXT2RagpvXh\nRrV0q3nUInAjU6GFVPxdK/iBB3Ag0Yc1fjYDC/UFNZ4Mk1GAvGTYbp6ZVfFguoiQMu2XQBPl\nHKZRLioA1EbEJGYOomdD1tAwQvcYv7FsolwN4YuQegjLd/L1+usbS4EHic+98i26cHCwsj3C\n5inBhmdowwby9PaFkpCM7ROpPYWMD4LnzIBXWEEft6kKiqgnk9RF+Q+UllboT5e86hBAulkS\nUpTT/ObRc04Ji8mK9pYwCSbHAwdfMkpZJpO2uQ0hCilreOUXuPBiK1t1C+YhuZTuGfFLRqk3\n6YzuFCwsLAwU1ozSbyqfl6HC7ZoGMmecmn5mvAlyOwOwQLecd6W6E2DvGdTewN8UIfcdfUYS\nSRBPCgxyjkOYrgW+DcE5z6YjqOGhQZQvFp+dJw6gzIG1jUGhj/bg2tMgZGEL/BgjpMj/IMA3\nRTC5X0jwU09PgrRfyH7Zui1DWGpHSO1K+pJV3sIvI0rYh7ZClDdmeElyZVPboxzHv0arYybE\nhVog6nWlUxoAaxlBtPEimGWIH6JaxBZA+C/IryRkbbR2s4ciN+T8CAew2qIHYfFcUZcwRxSv\nzQDvzQmpc7DDl2Zq+2hLCehk0oWSMUKiGCTsHj6wwJlgLQ8ISce3qPR6UaGzkIYvN4xaeFX3\nje/jPXLjrMrStUjjQxJuebAS+RtJW92yaPXhL4SMsyigHUs2UFOg5N3E2wNpxK7SZiazO0HW\nTZzGZOimGho+7v3mySRPoeyuDnGqRweVPYxlw/q+TFI/pICnmpD22nrY2iaExxkdK8ZO7T6W\n7HotEX491bgsxoyfuURITzdO3oR0lmscw16TzbYL6a9UtP47dqrsIcrqoJRbUqx2ufQAT4Wt\n2vpCfaCI/mlfqESo75ODk6z2cbiQsKGtCRlQI3yQygOJ++LLXegJJGFhK/U4jmOgT0IAISGs\nJMwzHTE6vyl3wY0VUusYrlGtDY7hcOQGISV1pGyL2NA9EN+1G1Xx+utMSyH/3KsEt5Iq0g9l\n9pxgS63cc9dNFMz6CgkUezuolEvxOIQ+rjcPDSyg9y74MLeDWU2EF9KjAqRnowLAyrIQDTzV\nQGo47XZaACPPkAUk2BY8+XNnJdLHQTCPooueLc94q6WoK+UnZmAKdBSAsUKyW8I1JqEOGTJK\nbhBSM5dDuhnMTNt2hk20FXwOa+C3SRK0HxvH4vQj78Ho7ASVyzBr91vm1Igvz9e6l+afNF13\nDB65amy49RmkVRsmCniPlXsjD3tymGGztFbmrQcAKsLXiqzf2w0oDMdTaYKAPMiLAGO3SB5B\nWEd4KDCSzaqnjut0gvcBzHa8GmeSOCTGCkmWntJsgAzLeFhygZDOUVfgrXLML7O94T2phLaU\n0oO0XSaoxznBXGNMCaRdvHPEulvnvOmmzBTvmc1svn6T/RoyI0xr54z8oXdqCOFt+cA0WKXv\nTsU8w3bfQwrNkNpTNsRmqJkoAQGIvetalKUPOX2GkokCPiDBkzNWU9bfchNMDQJ2O95Q4yzp\neCy98mOskMJd2Cjr8/bogPmMkQuENLgEvKquefLrUw91VcTh4Kt9y84KDNPfL+d+KPVboQ1f\nxdrovo4HsHcdjKh/x/KnGevR9sMeGamzyDEJtqioe8laroMjUK6xb2oTgALEOngmGBAEiDS8\nTNROt9F90djqj1EfAiGV6gTwpRlQhMqA5Wd4gXj5mo7C0ysvxgppJwV8K9So4AuIjfgGlRuE\nFNsSFm7IfBvXb65ehqXHJGf28PSyhH/P+vVeinvU+Z35BpbnGg2RkTBf7LtrXZZBTRuXplYA\neM5BvGluUHK3avCCok1lWzNaaYfYcEm+QCxjX9hnCGyF7Ccoh7aWzIOp5SpDWJLCn472lxh9\nIHuyslz3rSItLeb+/i+9qt1lj1lLD+5Zns9YGLvojjdSni+0binA9meAOH+5nV61uEarGKTd\nUXUJ6bDpRcxtItffJNqbt0QoqQEwj4VRTWcCwsImiLZCHTdHdWGvPSP4ximYtGr2FcC2ncUd\nHu2PpICiBJ6qMzxg8GzQPL//TOChu1BygZC2qVabMddnsgM80TTCOZpf951lNU7InrY++Joh\nthqf6SwfrlGIx8f6UQepPKxL8Qop8BG4f1WOOEVNsAI2U0E0oXKX+kyYqApCbHjspfXbVStp\nPOVu9KSMNgdA0ejZNJKUAleKXML/EaMxRkivPur++weMo8oFQkoLzy/Tza7eFIvSLvTF1uvb\nE0KPhtoE6nOU7kelA2F5LmdjknZSvF/d3QqlPgFXIeznD2EH1DbbZzMgAXbAwzuSvLlfar4B\nYTpPmr9d+zCJ/kj67RmBVSqTL63cgzqie0jU0MBbpGQYAWgKgMxJ0/DfERlTjLnSfwoyYxxV\nLhAS/DsYlO5TTx3xCjYS6raNky9FHIf9ubw1jShQns4U2bhn8OU0FSqXFcsLuwbrFTB5EvP6\nWOz8GDG5+24PgIWcLGrfAW60jiyLeugfj2/SeCxzxrwtgImEEOKau9UFuKrIJojUwxWJSdre\n0rYUUHab3QaA+YYtMWFUMebx/ynIjHFUuUFIMLmobcUu61LhdhLLqX1GSZpcwsqjhqCl6woX\nIAP2qO2DdK4H02SUpeVq+KS27ovevJ/hlXxiHUApLekeKR+ZnTlgyZ8ffBHd72bivdGyMbyW\nW+khH6HmVL4ihqeMqQWAjFm86/MCulA0tnryhhC9vzOP9/ldR21b1pIay2+a2aQ9uITK/aV5\nuO+esCmjZj3R6c8v8KF96UqVnqxyj0b4bfeR2W58BpNUoLaLj6MMzOHp+Y0Za7GYvsdjmebK\nvjvf2KKCSRcVpICM0BeK9pSBQTx9Go3xQmJ+AcnnrmCt45M7hAR/jC1m4VnrcFYPA/7oy9TX\nq8T3gDJo19T1C2txEmFRtUQihFXKn5TqpnfP7RB5JNJqgegJQx1BR0/QdO5gCXEUfecFrrol\n5d9lmSxDPHVXTlNMYttn/cpa2U5GeXg3A5Teb/cT7QL44heNxlghpXWuD2G8NwAlcD76uURI\n2YSUMu5rnp8fWcAcEUDHkVzTrMOC6fUpxP7d3x4hi/YRLRSdmb+MKITqrY7Mt4wsJEjC7Nfv\nAWq0M3bfaoznBFF8YD4rEIL8Wl7nqPvjiIV/oApIrBGVbq8ASr8h2U4WC3iPpY3FWCGNB711\nX1JEp84k/1JVOKKQcDLb+u87kcDBBagu8pkOdtK/tnbRiMon77t6AlB4lb69A1nLXjNMIQcU\n6KBfygBrROZI5tblIfShde/CZm0Wgh4oy50qDXxnVYZq0sB3tEKGKEVWDxAH7u2oSJv/IW2N\nvDcGjBVSSF3G37gNhK1FF6HsSrFBf9vXuDKstA3g84lItuQyPbRHnyGfTP/9bOapSfThABkY\npO95GlDYdLmDMN2i/nqbyXec4lipmkqCKmH0jtoPJ7pRK2DxbvAOQGVvKcdUTqJd11hSWP0F\nfoWxQjKbD+EScAjCOZb4BiUKCSu2m2KL3XHzG76KVNPoHDU3ABfVutUcaZeQXpGzM2/lYFfL\nYro/P0aoQCn/aPk6w4ZJXi1XgItQW40IjysBpI0RZ/ztvR7VCymrHSl/CKE/QGWgrQ3Mi7eo\nSysa8A3TaIwVklonpCaqZN38QYVvUKKQ4JNN0/fgCvB0Xm25pkD1RJhEzCCtkJ1eANzi/YAU\n3WUHf73iTsgQgecsM4BCJ4n6AVKfGp3gZCliw+OStQeYO6sQ6AjhUHDYAbHP9qOSytm8ZLgZ\no+Yo81Wo249XAZqQ9tM9oLtjCkV1OI+yNQqjp3ZN4WuzOrpGuwBsYxKFlBBD2uRXKcfh2Qqt\n3gzMlb7Wrfeld4DrVJTlW5J70qby/Da/RDqO3L6ukxS5lmEpA2xatAGkai+TgawEKlvr8+ZA\nHupXWtcqQaeuUSG8TTUbAqnAwU8hUxHADp1wPeWvLWe+6j4RK20yaVy1zDuKMFZI40AxZ3AM\nwhVS3kodGSCPC0lb2Ue36NasNONLMMpyaHCTvpsQM6G9NNk2UqeSwNY3QLOmyK7K19Br97Nn\n24quVvkRQk6aWNTcsaKgkuuNCIogqi61ZwIDx6JzDztYfPNaCOFBogL8RiAfzGNEJf11tpoS\nFLs3yUqfPW+bZKcQ69/AWCEltlJYzNRdnUJxlorO40LaKWezMmyUCXA9+1pFUrZDNXUBxO7V\nEMIu6M9hjoU/j/ZtUXjOEcRX/U2LOn+lJh4OsyfogKL2wA1LIp7VzoAklYOZvbsZ+ZGWpyi1\natzelqTZs7StVOmBexFv5HJgzFf4erQk2k/ISbLGaSbb6BQtdNQZBJdnw1ms/t95XEhtuYSR\nWqdl/Mb1Apgohfdl8yFcrEcSpFWJSUmHFPmAKlhih1jy3ygOZBRVFhT6vKSEpZxwE/RrvTiq\nadelCM2lrKAOsb/Q9rUMWzFccGX8ifI/flFYARpVkJUx/O2cWoAg1MCuqPwEhB+Obn+Azqz6\nKD1J7B4ZVs+Bf8AgpK83P2EazE/yuJCqpGc3KTGa1/Ya8Zf++tEKtegeCfwGDKlM2QST+2e1\njiBRPpyvDp7+HKpMaKDuv3VncVCcPwA8rQMR1b6evStiIZ/qxv6LHpnxFhTvb7/tFUyLiGoT\nCGF8/oqGDTXjbQAgS12GH1tQlAy4IlKIM9uR3CbLKXRx59/HaCEdKwTAXt2CVsz9jY/GbblG\n0Exe26nplSmbxKLMRpDeUd1bW6qrmHk1bmFLoPPoQVmlmVaMy8AnYD6UdwSDbZisKYmxNoi6\n0bvpHo/ht63ulXhTcicERl6DW5WdJQd1f3lAoZyV4Itr33U3jvCwtCxTTIqqFAg/pXe00AVh\nZQzGCum8VF1JJ6S3jtKM92OYPC6kuU6sh+lNgj9H1dD0k5ye6FnTJk8gBYpu9ETdo/yeoNDb\nBFSLIL0PdhooZ8+3BPkiZ6ON0kJQjqEHAoCKkPUQEPf9shqwVAMPNoyqKP92y1Rr6aAkeG2p\nK4ESXeXq+indj3wC9hl/C6OrUbg/e8W8kd6480ZiZoA8LqRvbg2YJ+5ZaA1+2znpUYN1OqAN\ntY8POi+pxOZMtK6FXvSbF2H3zK6Dkbw5SfYq9JOlw7VslC0R1So0j3Zd4H6p2kf7rqOyfT/+\nM6o2NwGr1ZPn7hAW824C40sCdz8gQSQ7v2nR8B7UXCrp+Y63w9/DWCHZjId6IcFxVtjGlOeF\nBK97OMUMqq8qKWDx+YhiJ9VPFPzZWvNPkeldb5Il8wHygapFAr1bXknyKrKUC8Mapuappiqg\nZARB9OYfMNzqBWgg74F608WlFyfP13DgxEPo6aAjdeiTZ9lHuvkogfIQvBYBLJSgKn/N93/z\ncFbngRuEpQkzVkj0ak5Iy8TSlxhJmBtbsdMmQSFC3ewYB7rrwWX4t6O6FAX605TN8ntgE+qR\nei8n2qfB+HKg/WYzvkoRR6TfIGwPPBRBXj1UgKfAmI5VtJskorIdCERsCB6R3NVfOwP7ShGy\nMFTyFOgJ7g3x173AkynQ0Q/1M3i4fR8ygfT/ZwQV0LCilccFIbbGCsl1MCekth4Z7scweV5I\nGSC1B+VWxpeoLeTtpZAwLj1/OTYJAgA4zjD82F1XAoIGRKuE/G0N2nAkWs2CSbST2zX3P6BW\nRfAFPX2xci52uh4TvBqCUFJ1X0bx3YnSqZs6RbtaoQTQhDgeyuwzbJeQ9wAiqOLfvJrSpB//\nOe5MJRPW+62ltZBEEsYKqb3VZUZIH0cRnTPcj2FEIWWExyuHLRSWOXuPRNVxUHVJaYl/ge8P\np5t3Mmz51cey6KCzf4b58sdoz5MtOwzopWV8E+CjKqAWz37CRqXVOdvSu5/f8gQVDc/ZEhoT\nPmXcQYk3JVX1B7ekLP4y3OElooS17uvhsUdwKShF7oH/pBkBpATwQBxhMyRbs0lq08KFTFiN\nFdIrN7ogCAuTAXfE5meGydFCwlMBInM4IfUt22O3c5SE2eE6TSGSSXztpgZAGStkbT5NYaZ7\nfxWNf1sLqABhh64684dNqzJV0mDC/DCSQlWOvrV4WD/6W43QZ/DoAD+5JeKl0BdIas1oow6k\nj34BgpxSm4L6XyBcJDNHHymdIbiif5NDBXRq9DnSm076tLOdUFWlMkzOFdKtJp6EZzNU3E3W\nctJdVSQY2LJJ5GqiqmNC7WMed4GfvBkL5Ke0SWHhV1oC80gSmZ1hhlk3cA1edXcKkFuTVVGJ\nJOA6x7+IG8mN6fLlzSiLs4bt/iBJC1dbszVwiYWQ6hOvCDZPz2UCmVn2n6DFtbw5NiEWzwbt\n6wc430YMOVZI+xSVlh9fVkF5MKsHYpDk3ROqe+rdeX6sKGI36CiWTrVS8A7Osv+wlSBsG9kQ\n0xGmZ4lomfazU9OEQIt29j4tUL0ekE0LhN2d/4Kjirb2skZ8U5+kI7vMfwPPWvEnINIxOP1N\nE4A+nD1HcMvOiUJiVvFlEcIZ6pFThfTJlt216mNv4lLAGWKePkbiho9NgFtpuh6WIhAjgO+P\nsnF7CWBZv7wTIIcbttT60LRmskfiQCU52f00gapX/k1VP+otvQumBg8eUDEY5WKxVR3UoW8F\nsoMGbqzl41cPnbS1cXrdlCpmSLtULrNLaiiyHhWHcUK6XsPara2+QNXXbmSG+zFMThXSQid2\n2p1kvyxrB4LkPPlU9wtzrffR1ZamJIWxVEKuBghSBggXM+u4NRZuxAjDlg8loH54VDGFTcfY\nGtB1GarT0QqbP80135rZva3fZigyD9CL8Y2q9T0J05op2i9aECvtgNoG75T+pEby1BdYIF+j\n6+dTQ3shyxajhPTQHEhp4P8Bwj9dAK4E1ww5VUhdOLdtISfyWYe2SOVEONXtky/R//jxTiAS\nS72GhWaAJghvj+cwTTkf0IgcCbcVgFTaEzEHJbthGCKdl26gHYCtWVVrz8sPFTtmClnxT7HS\nb++dM0NVbjsF2OpOSdKyPN1NkrpXL6HyR2wZ/oNRQmoDJiUnjQSDn9UCskHIdWMGyalC6tiY\na9TrmqXj4OGhW9DEImUDiRnMX+ytEPX3MkByUy+wSr6VSUG0BfijwqNeuUntO0zuJu0D06xQ\nWcF1dKfJHmsST/pU1jbwrFhvJM+GtdZ9CtsYFoIy85Se0P35I5jg3RN6vrjP6B3C3MWNEpKn\nvhRHhIMaVHmQ4V5Q5FQhTfNl5xQaT946eVnKh/6FKBvlAH27QANnPCE6T1SKkeA7vOvsSgJv\nkoozvOX3tTYpsS7zJ4QrFR/QfWpHE9JQazLmSywIHtjSV4GIpNLxOj0RymmAesu+sQaupYJp\nEpWnNcMYJSSJfv+wG/ASFHKcAXKqkF4o2EifWSqctTkyhQYtgH7KkmY9Ge13J5x9UjkxtK7M\nojCTLhUQpQ0fqKVF5buq+7pZofyDt9NJksYbn8A+lM9Ue6bTGSjbp+mOgdcA0s8jtV+wlUc1\nvN/9RgmJ9awaDvBU//wXOVVIcCHV49zrs90odEKO7MByS6BPvLpWfhrgyjB/WgoKduppXRc0\nKmdmKQdFDb/pPtQFroXMBegIwplm5kU8QVAHs+lP0u74EKjwxWQl57i7krdMIXawCAnjeFhy\nrJDg7oIkIAtlejpC40mNkIzWTZ02qscssccWfX1KRpdwkBNNypHl/twkB2UQTh53Vk/ZoY9a\n1WztXqXNPMTv++P2iSPAIVKfQn2FuSXqXdMiUr8F+T2ki/AxP53bpf8a4xf4opBw8/02zm2X\nzOOtN/AqaScb+dZLyDGJQC4rAx0izRtR4UkQFvSRISdiLF/KKmrHVbVyQ26NHSd6l9E3dprZ\noILVn7tEn0r8fjTSW/hkdbLEt0FlG+cTgj9gAFFIeZaEfDa1Jh1e5BWB82d9uwyzkolmunSu\n5u/P/4F6QbfKEbrPkIioPPgIlGfPE9pZmLm0RTyxT6sTFEnWF75CXS5lhJnYWY06GRaCcUIq\nPlxHNBiux8iR/BtRSKbg+wBnAJz6Z+wF+n3dgJ4LXiAMJqo8AbOvfISMKQ14+74FzjsSMoWb\nCgCUf0+oL7OvpWlFBNsH+pEob+zPp89loDy6xnWc/qotyRsuwoNxQvoPRo7k34hCMhEfeLaf\n/x/HnGwq1nCSIXb3vzsTQPf1ftW1fUBX8Jmvv3m+HQFVTSIldQ/QFMNmhykr3dpoMG2fH/hV\nsgGNDVtmjJuAC3Va6GFkT0YJadV/MHIk/0YUUjblvlnXXQWZyRsiQcRdBQiLLU426Ws+1YG3\nwwlFrRUVKCruaCdPABB10teQpL8L8HK3DejjR1FEk98Y+684RnCnXbuMTV0vlr4UyQAxZddQ\nAaSlLwkQuW4eKKjgeh2LmW32jYOfzyJrbsJVDhSwI7dC2LglINQIJ4Ltcv+6IJp28PSffXIs\nAdoIGu63AzOWXEYZ3AZsxP278lK5VwNBMeUGEIUkkgGc5lj6+p1mylagsjM8tlHbFWo9Nzjk\nryoEBeiWiAoYb+QUYMrpPVGt073nUAGu99sHAfPImoW/QXgWyFEZg36ywVZewIuIQuwjaD1G\nMpcHLoqoPUvq0UYc/4lCEskAkr4WqifwUAFmTTzY8PHTuxg5AMoO1xzKn/rxZV+BfIigkjEE\no8nzAWXnADkykAnCrxLvsfqg3qWO3qUr8w92Oz02USfR8h6ItPTrJIs0UFvQxZIpbTFXikyz\ngkQUkkgGcK7u1BRuob0BsAagCCKANvXegzRYN1qf3+SzzwDDhtqqANg6EE1uKeXhEp5zp+rW\nzag0CH+EdlaWVE2/wjNWrTd72x/+gxFWcxUuVQsCJt/yveH1rKNu83RqEFFIIhkg1sNy2Dc7\nz+B2vrE2lUAM2virPu0wTLvYwg71fPoDolKvyjRF5yePoDu8q1BQaWmXSrkGAU95fqIZ2jXt\nRvqO3B/IbJivl/Wt4ZwE4QxJ4a4RFvRk9BAMIgpJJAM8UJCttyiVE+gN3jYLw0h0FtZbeie+\n477AEYCSDw3b+TOVXuXqShJvvtoXZ2igVIDKAXSnnmW+rXRCBqrD/emRsJv5PO9mhUC4k14N\n4YjSGwQtvn6BKKS8wdMHwpIbXR9Wr+kEhD6OkIS3VKGYP9wM3OknX4zs6yHQLTzOyTu/PSC5\nW8EVEWZaEUgcPJUy/qLr8LqCimjgA1reUIYy7hAtUTuC5wB3Mjvfh6fX/fKvMJKpJVijPewT\nzjuIXyIKKQ/wPc4SAEVzASlqhpHFurQLViL82fYRUjpiSmWZWz3Y3bL5BdTvKc1uIYRRzSGM\ni4RJ+VFFL9cGSIBFI3Z37dsNlFvqXUunMgUKT7WQVj6Z8NLVuhQiTj7JYgnbKNca0SFDsluf\nH0wK/pPUiX/kl0FEIeV+EqM8Vzx8tr2wO8qzR89ixS7dn9ppNCL51S45IKzcFaW/7JMBKSHr\nhQihG+5w/zVxGZ5QrIVwAToVgZZ7fI8VIQHwRwj5RXNzALx8qzEbHZW62qK2J8ZaMs+2Zqic\nNxJ2v6QhOH93srqrbvLKWzXg14hCyv2Mc9Y7cSZG8nnWaD1YzzPYGFUG46MlVarjJs1OkgYr\nRlWxREQdpdRUNwIzW0mYUipHSCHBGpvpdmffXR0mQ+bVal7zOaHfsguZOqwIwk7TmSzTs62f\nhYCysWeL6SaKLrN1Q9wvFZIb7/8jCin3EziJve6T8fxUHwNuS2CLOcrsGq0etWO2nHJypIs0\nzg8KGj4l0q6IBp519TUitlh8e8RbR/OLDVui8E8KlcR7i9mfJLPiu0jc+BNdA+XMgFrNJwlL\nulgzSp/MVVujuiDz/4copFyPhuJ2ld+D62jLK+lOpicI5NbEOWtaYg4kNsHM+WVdM9Sjp3Hk\nDllLmJFAVoknRflaa27NUxR19KOJDGJyMlz1bAbXOqI7FM4d81bvdD+itmY3fu/zopByPdr0\n1PKvAM9i4TVxlW0s53k+k1Z2LWQxXvoIpk0NIgHRDFGIeZq5vuxDddDy/N/768iPIfsdXppr\ndKmPMntTHAQ2Kkg2+gFbV0UPNAOcD6D8A2jfM7/5cVFIOR3tgZGxY46iLAoPZK9rzfmm/5Gs\nL2ha0XY6saDXNBvs+pWDqdVsJrQN9bHKb3ijTduVqjakbyjopv9bF09kOsoxxblGe/RyTlvd\nttWki7oFDb0HaZch0k4tmH/ytysgiEIyMc9vYsls+pN30dLoliXoyojIn6Vm+hfNKy/erJUn\nJP11P/jX9W1vxflRZlGo5FfxoGZLOMP6IYzq2bBNECod/Ylu5aoVimLbn2X7UfffpWD/GZqA\nCeiBfi1mP3jz0lY0agZoWkQhmZLUMXYA0FXu4utRW7IgkzXxfjBijqNpqYr7c+8ox+KIGRjH\nXmdZWAAVesQvYPaJXXFyVJrLOvalYOhoOFH2IGr4ZhVPIqny6U98AaRfarJvS73/3ngzvp36\n5KnRNl61GFW+GVTGs+wwhIO5aRCFZEK0dezm3X97uAqqblYG2SNnA2ruUogKdNqVpaxUEROF\nvAqTDs2Yf1pTp4hec6ekiHT0H/xBDNm2lHzDLeoM7+qrUrrbasgspN1Fq6LzDi2rKUWE+P0P\nl+zyDV82NMDpN/cIsCEKyYSsUemfN2091OlHxuidHk5QDJG3PqO8JnWqTJtVTC2xXGp4pZQU\npAb5ut694VdLN88buPA8ak3Vl5vavaERtc0YnnYIoD0bXhU81O9uLZlN9eSGfnhnzBlGFJIJ\nqcylW7sPsE3uYmK5Rt1uAj+RdnjauG1oN5hDEg1MqmDuwsSUhxietH2uRrjUDSfrJGy1AAV8\nqUKIf9QdyXL9vRvmw1zPcIWN/t35eJ1iGrbsfL+FKCQke1oULNz6JK7evNMjMM234+qyb3mu\nUXi0sA9cCZDm81eYI+tTHpBq4VBbaYtLyxxHE+GIB7SHKmbKebiftm8F4fPqTgi/1DlU7OYz\nS4pa483rSggAACAASURBVJvUsnSpC5nYPWAhBSE4K3RlGFFICLTtpE0m/1GHwrU35L+A61eB\nbdf2MBfUeY3kd51meGpTtxph5UOCQQijv4krafb2HSHsXh52I7YYNkypZD/1/FVnq2AmGVFy\nftSu4NHKNoRn678FDTIDtGkB4VuP0tdh3dgYlfAZIX5EISGYYaH/ktsv24inv0Zs8VJ4huB1\nHxVM5UBmmX3Rs5Ew8/ZFwsIvQ5hQjECt58tXeAyoN/CWajU8DWojDFPG+xIAxLJOQrN90ff+\nPSc2NGMKQtiTmX4GTIX1y2TCDYQiCskwWnfOSa0Pps2BY5Te7exrRB08/TF8qU2GVg8mmgpM\n8+jSzF6/U3wb2CM83x46FAR2V6ZaNdDCCwBZawjCb7sB19MehbAx4OQutQu66V70G6Tx8ByJ\nqazG7yAKyTAv0jd1j5C87pbCGEG3WbfnD69ArCXgL83qPTd96fH9Gc+Smwrvq7/+ACRivxw+\nawwA8JqSBuE8i8I8978OOLfQFc5ChpsxHnUv5lVxIuIAbLBqOnnszRTFOAg/A740DpmIKCTD\nPEgP+r+IbTj7qjjJCw7NrH/csmASmNVBZsKxc1qov8YDO3TRroZA76H3wcsLkQtST5r9TLZR\nHVfaxn/YpYoat6yvc8BzgxbambZABuyZ1ecTgLfkUYYQhWSY7+nenitts3YgAumpGHH24Y4K\n5qjv5YYWbE2ice7K3cjO3ihVa1883RDgTv0FP544j9ovn27GlFzRjpHi3pKDL8yGaJYUkAAp\nakMwpVjF2/oZw0xHRFqjzEYUEoI65fSnHolhnbJ6JEI4qs/5BrVNQhHTu2uUK/Nv2irvSfN4\n1dy0IACQedPzHlYENEk2MVyNTBtHluzWxl+N2N77TUbk07RVDT96bSJwQJSPPUDrX67nLX83\nAxAORCEheGBT86Y27VK0u7DYsCymJVdS/TmJSr27kLBs3DaM6uHGW4vr28iCVgFNzj+2r3j2\n7aZ2Hh6IVAqXB9dpPvFlBscrgGp9tsr0/xg/P1RCyGl0uaHj6kra6V5IT7bMO5wlz44oJBS3\niwMzOaj8NKvHIYjC3B4jdF+BMluvsAooX1FWS+hmdN3SqYvNzSN9gHO8UcP7HcoOq9ZO3wjv\nTaCOoK71KBvV7iCEn5oQVkFSywWmGd1/yOtCOj9/7BbUHOfpnv34znwyl8j0iqyu6MIgL0fX\ni+64Q6hDTYL04CrJrBTdqkrm/Xv5dYygbV3PZcw1Sb1VLqCcaFqJoHM641nS+Zk8rl+Qt4X0\ndwnKv7iVaqZJbpbZtOUKRDwmls+buIc/ZEIYt8Fzx/FM4wzhiUxJkhkclDjrffQm2CTI9/Kb\nrzJnv/TmWJh+QpOnhfTNv1S87ntskSwr5gLYOUfqgx5So5V0UITKVmAkwsdTt5GHZPFgC6lP\nQn+IHl7U2CFmmGbSMp/gkwH02svIqR1HPa7YS5IZIvwjk8jTQprkyt5mhnVmeK+YnNF0151n\nlxYgy72CMHEMLeArHF5m0lCp+iPC8jQO7a31jbjIFejUdJlBakMAlMB7W3LpSgKsI9PjaoPn\nZOagfkmeFlJpLtzsm4Qne3sOYWcpNfAICWHLdfUK4v/AWUXjS8lv1rhURhzAjLGkGZ0dk6+d\nVADPMDNEK2XzdddWFXSJF2BbIb1mkyPO8pHCyNNCCkhflDqjas7nKL5Db+7b+D5A5K3nCG2l\nvzxSLzdsk1oblF88r4Wkt7ZID/juhqnf3dpFoTRwaCvoAGJUIDtLPU3EZ+aQfkmWCek9yp3D\nREIqysXwpOALa8h60v8tqYA3juovgtvY74aaOGnrSl0CG+xL6a4e7QYAXQZzsML7sTXDG8xG\nJD6GyUITMry17sgoKd6vGYZxZZAsE1J/VC8mEtLAUDZec7OMt/p2zsGZO0V6CW7ymf7MU7oY\nWa8hrT0Z3a2Zu10N9eSbb47XV2ALdGS46ODXup6f0g3LWd0pe58OwxsoK2TBKWSeFtIrq7bM\nTOW8HaKiXI6jKZdPaJoDb1T3biV3mjQ7+D3ytOzckLptZ2/lUuu398UYLp7gHNOFYCq00Bl/\nDn/B+8mNy3Tckmkud1fjKlWK+/UbOU8LCZ5xcm7YpRTZGlOURLbgumwk8yDtV83mNX1FntBf\nE/0VAFh1QpRaZWipz36qOTWJnCIw+EkA85x6kz57P32dDyhEzeRswhiqzIABZahfHqeZVEiF\n/oVjdhAS/LqwY4OhiBomOZFt5r4xnYuRQt6yjfIzMeKJgWDgjfur8/mj4+KKMpvLN0LpIJnU\nfhuOgTK0aEK76H/XYRRf3FOWs0GqT7WxXfqrgGmTCokkZT+hsoWQciVvpsY2GMGTrp7lQ7jT\n4PXzQsAo5i8J+dEFuUqMhvCFfd3X0LV7bUrQ7owAZ6S6VQm27F85PyqLE2rxEtaPvfb9VVE/\nkwqpv/qfHdlsMbXLA3w4hSp6mTipjGOgmsvktVWJzJfatSyEnSNSP9cCSneCXs9/670W+bqN\nqC+vieq1VyAb1qp1rQri+bvMShIAN3U5+6un06RCSgmPSElvi0IyBWcDdOt4Sf0UlE0KyW3D\nvUSn27tOrYJuC1OLqkK08Dyg0QG2OuKVA5nF2j33zgijUyS7S79a3ghkQhwGTl6Ce2zj7q9G\natrNhtuKuPTm/xfSX5d+MkgUEhaOUGTVmZNKE66o3ZQ0iqu18ownVHsW1Zya0IRyesSkfOho\nzzcT6xnJTup2I0MIG4OoZPhtlmKMlUXWZnjkJUW+i23sVPzii8nEu3ZfPqS3jo3/n//1kAL/\nQhQSBtIc2BpjO4imKLPQUex1obycX7khiKDuEzVISl2A2ZJ4Ci5LD/PcPYLzfEtT7UJYpXgD\n0oW0nhhNjuTpL8upX16/r64p/6viTdnIRej7x59MFYWEg1MEFyNfVIY6+pllpZ/SnaItBy4e\nEmyPyjTZoHZ+fczJJBeNJ8KtSE9Auk+9EzKta2oAMMsXKCErZfsziPuWjZ9D+LyR5a/Sy2Qj\nIf0LcY2EhWUEl71lCEAd0qTVsRxx4MgftBXzrkmNcUOEMl2RuDMvjr3K+VqrzTx3L8dN4z9R\nPK4Q04LV5gWXZdbE7tXAsn4Vx2JxXbmaH7i5ggK/PJHNCiFNKs5nIQoJC6sAl7tuEEAVN4aa\nuYXkEncps4R+Mb+zsj3ih79ZKo/tXIwcAo+SfJHDs9lUlHCUbYsQ++Kjs+g3esYmdOji/l4e\nWDJ1aa+uWnX114rPCiF14O1AFBIW7oOhbCOM5IsST0sZVE53mSv3rOeosD9k2PCSNLT+iOvw\niW8M392TwsMuQfhtLEWF2ZGAVGFP1iWEr47tmFnt67L5MZfB+F9EIeVmvOT6jdoFRDl+2561\nINxEL9bC2Oa9lbcN2+21CO09rpmqvG4C+Hj9HxufGbZ8V4ew8qVsqEiSLtokjCB/t86xMcxz\nSoTa2b4AgOKZ64IkCik3c1cqbbV6VilCLeAhmuEHoT9Td6PICFgJtcv3fHjNYrHrNfBHG9Kx\nqC3dC7FJEL9l0amuwaQfEyZ+FKiQx1mZQ2xzCFuZ/3H5SZCXVaYW9ROFlKuJzw8AASKFLBCe\nStfHM0eO+6mbcI2dgA/Ud2cSUu6258meWdyNYHe5bIDpA8Bho45wu/SyrlG5fx18dRJ/QVYI\n6RNiOsAiCgkbX88dExgXN17eCyR8nKfup3t7kPx7aCfp6xB+mNaiKDEfaRwh92IbPkQ1YQOB\nMOUhriRIA0rCOkwYsNZtwQP0jouRiNvfBuEp1J37mG8DVMBqik4Wq+z5rfuV1YnJ3rNNf3Oq\nNupH1VjCpnr4KCFLCRvHpXJSQIZuEGJ6tJ6PbalJiPD3K+SxoHm663LFS2jDt2FvDKKQfs3F\nWvbApRFPre7cRop33avMQ6kt14LfuHkb+NqyU+reWkq5vARinbSDMNdfezmBNoJGcUDa6NCz\ncwOlo/hNx1LNF20e6lQIkU25u4XzJPjmD9lUCC23Crr/7yEK6ZdsktTbcGZ1RWXuyC4kmG30\nbA2E3zub3eO37VoLDglJ60fH+jZoBIohQv3CQasXKX+1lQSSB4WM4YdLH3YsFO9++TFKHyD0\nLh9C95oJEqAGjksh/At5Km0sopB+xWs16wnYwxnXXD2HsFTlXKWshctxAaab1e9KDd0mPRwv\nOaYxt+9u2DDFlnGe9PSgBezB69iu4n7mJePQhhDWa8xeDyLdYg+QI26m6Gbq0eURRkYjCulX\nTPVmw/5/WCHdxHIhb5f3HboJldLnJ6n5y4RML9fpZUS0Fnp3UiE+k1KWAIAE9YV9Kf3Bba79\naF7wNM8xstcS9ppGIx1oB0u6bz85L597ptZCEIX0K2Jbco2KA7N0HNmap6ESX1mkquhb+EO+\nGV118vmqQauRhQT/xeRC+sssayCjVMORnqwuq7mGAp1Vdlu0BeXbQ2hSr99DFNKvaBnLNar0\nR9rlbZLbyKlam9IgnGH1EWBLfHFAxoTajFPOKjAkcY0Nsu5mNFsPF97lr3mZ6XktRSH9ivH5\n2GuqPV+sQJ4muaBCtzZKni1ddJYcEjtoOxZ3thT/5hr4TLZ+vuwR/LKIPIcwXWipr+OnbRCJ\n48bGIQrpVzyRsxk5xljxpKj6XVKyeVi1QN4FA4dQucWC705EZMvyqrB4HJ1esiy+LM6uObX4\nWikAgHSw4ZdJannXtS+/n6mlxpz89XcQhfRL5lLdT/59JIbOnCO87UWkwLwWwjE0x5BYwLH1\nxpcnXUjmiOZtuUAsM6gnsZ5AWu3UBVW9ngVIQhJkuNPEfmY6rZXhTSlrAkQh/Zo9hWkgKYU1\nOe9PJtC9Dt/ZVlV5KlN6Ny0JXeUAEASbCeWz3SJM3Q4rDmFY04q2Y0qElyR8EI4TaffO/dza\ne3czCxN6iUIyRNKjTHJWvk6x77n23vh/768fZlq6XkOk3Lowy4Nrt26MqdOD0pc3QJzDo/6E\nWTEVCBYQ36qdyWT4L38d0wAyjCgkk9Obczn7LNuPt+PkYfYAKJuZfvk1Pr2U32BcZ56aQuXX\nWrpP7y+1SYBLLOmy/D60bc2n3Hx9pI4yK4KeGEQhmZzK6Vvq4VOx9ptS3mnhnafbIl1MXoR9\nqSvXaImtnkq8nw0N6hNWlyGc4w0UvF5y+yXn9dfWgSZ/JbOIQjI5VbjMtzBsmtCPaOP3XuJ1\nN5hpo1dQconavzeu3+cZV2bzrSW+SnnfRhLA35xJx1KnBqjB6+7alJtUvqayKJO7KCST05fL\n/fJBKsiJU8fBQKAEijieuI5Cw9nrMeoD0i4T6G3LZHl4VKQQzpRaDehqJXWXjeRQm75V+Iwj\nJnMN3ixhmYQoJJNzi9YX2tS28hO4m7GL7v5Q+2WTS3X0SiE9D+N3cN6o8f0Gad1In2rhdJlX\nODt9b0/abFnYhBrt16O0X5X2y5Bb60XT843+dBsyMaKQTM80qtOea+vLqgU+7ylu7KLqvvJX\n5UT+wYKrtfIFXDJmdL/Hg4V9p+Hezn9jD5TulQf7BYcRhQY0tgl+jLDtWJG93uOvU5g5iELK\nAvaVUgG7xkIzrR2TcHFrresh7Ur1Yq875Lnlh5fgRwFg0zPSykO3QPxcIR/iDX6F0pfHSCxX\n0lSD+x9EIWUJWkRM5/+ylMt5AKf+qi7PP6xR6pMNfwhq+7ujynZ8rSAt1zMaeOlTKn8wR0Wf\nT6Vi1h2cEeyGem1lJqKQsj3r0hMojI5C2mnbKvpuPzTRLfwTfLekT78VXzJ/aJmOdnffmoX9\nuF2W2l1QpkerO0lCemdurAQCUUjZnkfpa56onjyWq0tYSAuM/AFXmbnUrOpgvTPTh2YSetXk\nGm2xnVJlAqKQsj+1Cuq/ZydLBcTGMZEMB+hpGghThkizYNOB43jn0hX6YHLXmRzCNcr0Q9pl\nLaKQsj/vwhz6LJ1QRsZbI4+jMDcFqi84jxxmtN2p6sMHRtPTsfR2l2RT0Fyjs7OXryikHEDi\njCreRToLDbv4SFxgGzvlWeQuM0utd5tfS+NxJuxms10L4WFXXB6xmYIopFzHffCcbVwBWKoC\n/ZtPoyt4lx7A4xardZvENtqVxXLTtH5Sy3AbqmO2ztgpCinX8ZHgTnp3yHEX77rn5jNw6fD8\nNmgX6yfpKRR24xrAq61TN/+Np6vMQhRS7iOyI3utWwNzx6khNZi3Qlo7R2SerBvgHds4DbIw\n0s7EiELKfRyiJ6VCmDRAhkyR9RvskbMKSXSajzL7SHLP1DJHzAPIxohCyoWsM3esUtHWdg/u\nfoenZ8Fv1hppV471ZUouyFPxJTchCik38mFFv4Fr+apdZpx+6dEM7Zsg7a6qYl/oFlSVXLB6\ng2dvRCGJCGa+B7d5UHwQ2vBcMHC2ASX1ew4fTt0RFKX0dmh5vwojBYVSJW0Z3mdxNktoJgpJ\nRDAvFSv018MkXyI5zbW1m/SepheKAADMBvGn6briEDR4yUA/ZwFREOc8zMtUc5PP4reE8PXo\n2kVjVuGMNzSAKCQR4UyVTXgNPyww7yX0AyflzVqrCUBY8Snph0czJkgiqb4f70bfU8vWuqdD\nu1Syhv/+x2wCe4yPMS+O/UDt/yEKSSQDLHNiivpNEuoxoQ1qEwgAIddJicdPcJU1+xv/pObN\nydmxGHv7Ue68p1RvLLsxzocvQtCRXDgQhSSSEVLv7LzGvjOe/tG88RgeeVwiYgG5UDexigAS\n9FPfLT1jS6W+fEPw4vben/HXhB0VyKYjvwSE1sL4bUQhifwWy+TBbToUpCcjjTbYS8FKpjFP\nBWYgLds05xr1u/Ld2YwLD9EQR/lMf6rSbRmfqbGIQhL5H76cPfCC1+gYPYe5rJcg80hsUwOJ\nfh42LRAEIvsbkx79GzSF79aeC9jrc/70DMXHco1QQTsTxiAKSeQ/fGpFkzJQhM8pohxXQWpA\nPpTVMwJYMFdtiCUA3n0RJ1t3qN3662YJb6x4++LsLHGcK+9SrXEMe002285naiyikLIlP57h\n9jeF8MneU/yZIn4UDD7wPe1mIzO0kjSSfWzjKniLsqsLaMa6KCgB/Ob4Br0zbDnIbM4H+H66\nkr+W+WPzDj902lwtXcFrulEVr7/OtMz050kUUjZkWT4SqOsKzTIkjAvhQEHRMXxSmuCij8bV\nNkDnh/gCLrONF+hl/DspqLV+biHQVwUmwi/5Wxq21E63Bmpgq58wvj249goiY9ApF+uK9byl\nAhI+ayv4HNbAb5MkuKpkGEYUUvajp2L4mfvbylngLJ91XtnijjbxYHAhnqCesDHs9TpAhi1o\nzbawjVMkOsdKPAByH6siKqDU2e2VooyTr22/zmwIfm1NyZyB6xbDlj/WD+g+X1BYRUJbSulB\n2i4TYmscopCyHUep48xF26gAxuldYXZX7J3TJLRdepbJNPI40q5xeXZwTUvz3PgMBRhUzBss\nAVzkH2latN/hVPhhGL2J31YAr/YtOyuoSruRiELKdrSoz16fEQIeO4E8AnfYxsgItKHjWvb6\nFVxA2t0zb/VBp4zeMt50sWnjQomACXrXgm88nepZYfFMfx3lmKOCmUQhZTsi0l8abiux9XmI\n5t5um23QhjW585yNyu9ow/O+0tBwuYugOgBFBnOjkAjIi1mDC0v8Kj0ipO/sgigkHGgOTOiz\nKB5TZ0Umcg2M+eBPE9z0Zrkb2vAIW07wsRuvO13q0VlTDwirGTvfUr8j8aNIIwHGBdJzD3ku\nE9R5NkEUEgYehsuL1PCih+BZ07ThIsQfEdew9MeQoODW7o34vM4mUbWnLupsXilDmUZebBy3\n8o7h/51Ww3bqxZur8nsJCX0ozm2Aa63xLJJMhCgk40nwrvhad9muHoelu7Okvj5LarVILN2x\ndPeIZy5rKN7ccGdbFfStvTwjibw0AyS2Ue5EI8NbcqkTfQhg20FQPuG4wuz30UniWQbGkOXk\nRSF9ndm0ZOvl+Jayk9zY9cRKJZ502yPpbrvOLY1wuIulN5Yflcw7zp9YjUZ7vP0efa226Z79\nSwEVUG/kr28E9vZEOZTp53lgdk5Q/P/Jg0K66eHSbmQLy4KvcXVYnnONTE4v9WUs20uaAfe2\neENANSvqBka0zYwkxk9o1rvnsUJQsvHvYwtYuVVFuMntVBfsP6W1eSn8ofKZSd4T0g+veszC\n+23RaFzHNPnTv+a9l2LqEWp59syyE/M9uUadDgKsX7qSymAfmhhh2OTp4EqFmq5MwzE205H3\nhLTEju37MXUSU49lBrDXVLMdmHrMUQwvwzV6C8mjF04MToEwMQrszcwxofgQV0DqVhPXLz+d\nvCek2PS5d8R4pJ1wxnmzu8AbZRkoH6ZbNWC6fVYzLb1aRAuEK106VwG7baix8Mu8ESF57B40\ndd+qZhTmwIq8J6R66ZFjFXlS4Qjms0sd5uD+qPUQ4Z85VNYcODZ5iGkEWco14ob++sVWwMx2\nBuBeBfVIgXO3K3P6zP3rN4f2K0qW0+/sr6RwdpoXhdSzEtfwmoury1sB5hWaFiC6C98znk21\n3XFpbRn1OVxDyEpqBcfr/vxc1U/A8exQEM82OgFETMU/fK1H5KsWRDTFtma8nu6uXhZZ/y/D\n5D0hHaPZr6KtkqfY+kzZMqj9lAyU074nWc5ctLG+iGiBzOVt73ClbxMsDuZfysmq9qhvHSgk\nL8J6cIxtlCQF5ciq5s/8ti55Nfz94f2XlemuHWOK4+pST94TEmzkslcLU1eoh2beLfgYwJ21\nfpLhqSCUce46hUzZvbCmZC2OzrS7+tbqslKQu9A3mv2n/0UWFGJ+VHKPMxfg7iqIJd5c448i\nmHpkyYNCSuoqMQuSqcbhj0EVTPU+XKMQOnlIpqEJq6k/kJ4if2LiOw8C5Z/AL6tUJLo0DEf/\n9ApLkfyRs8I4RXNTykYtMPXIkgeFBOGr3fMOZmiDDTfV4rhGBE94UGZxgmKPe7VhJn8v9yIA\nDQgZMmnKT2JjuEZ9XCuaND/2tOs8fQBTjyx5UkhZTt8S7PWrYnfWDGBGKNfoXR1737cntuq+\nBLG3/3pMzWbzBOX4hjCuItcoPszocXGcVDQ48f7OVPO2uDpkEYWUFdygWM/mLh7C4hCwMzk9\nvm9gRaTdbzCELNCyroPDMSyd7ZOxO0L36RNY+mO4UpoCwGUG5vq6opCyhAl0n2P3d9VU4Hnc\nMs4OMy4+qRJvPsYMMkPFvGSTu6rjcfSmLRXOLOIe5quMo7d0Eq9j87P8iSikrGFrhASoql3P\nqtv/cGSDVo+SZ/F2nGLDegxoozpi6e9dtLR0y5KSilm6pBWCKKSsIvl5Fm4bwh10u4sJ9yaZ\nCa4rIZCL4CPbmO2Pp0PtgRGtRh3G01dmIgopj3K8MNCtFObhFvM+GdfgSw6R2xCFlGf5cikT\nit5dA9zyYyoyl3HuQxSSCE40rqP115TQOB7LXIYoJBGsrJXMS4PwXV0HoaHluQRRSCJ4WaCy\nLVtIlu9GVo/DxIhCEsHMu/XDJx3MYYHixiMKSSQz0f5tisTb2QBRSCKZx91aKkDmw5d5ORsj\nCkkk07igrrTz4Zmh8rywgScKSSSz0AS30J/3HiZxp+zJhohCygt8yJKI9tMUdzhbq01W3N60\niELKXqRcXr0Ps8PB81b2QFJQWGWLH0dmr72F68aLfbjGuGK4usy+iELKVuxwA85KstlHjF3e\ntY9ce/3IYHlPAbbr7STBzqDCczx3XurFNTDnGcmWiELKTmynB72HmpP5IjFOxYpX1afrOUHz\n1wTbQo/9AeGdqIBvWO58keTyNFXCE1KRrRGFlI1Ic2NzVr6xxZZyD94GXFGLJrxVvjRubAKH\nr+54ctBqC9XSa/hPMjNy92czRCFlI85QXAWh3uWx9bnJlmvMCkHa6bhIvGUbw4viufctuyLL\nzu3oTOPKDZ2dEYWUjVjvwDUW4kuMnQEhbbPkGqt46mMK5nkbD2AevQdTb9kaUUjZiF0qLiPH\npHBsfd4BbIpFAVO7IzSXimW60FiiH2OLmnvUPIQyyUH1aYxCFFI24h29j22UxJiXWvhmQ4Ji\nA3f7TsK6fp/fddT2Fa3o0b8/ulyDKKTsRDuvx7o/tWNkQtJoCyQD298D7Jlc4JrBigfCum5c\nQL9Pv5M6+vvDyy2IQspOfK+oajGxf4TqT5yd/vtANuX2A0Q+t9TmdNUBHQItBGatfENx2cQa\n1zdyiLkAUUjZCs36mCKVBsbj7pZzEXrVVAqAqguiZPThXpUbTXglsNcDUk6Ui3zQhnkBUUjZ\nlgNx1VrNwOnj8NKjyK43zzb6F8T0w92t4horBe/ynR8XM2BzlpWyyUxEIWVTkupLqsS1crfH\n6DjdvLC+Vt17jwxUFkRxP31DsGc5YR9Ibk4WbVVRnU/gEixHIQopm9LVlSlcltLRUuhEi5cf\nip1sY5Yn2lAwkfX1YRIP1cuE2Xd0YVwcPlTxyYVRs6KQsidvafYYMy0UV6VbeA9wbuWnCUyp\n+6+ZVz/x5clypyrCEtI/JdmMqQlOs/HcPzshCil7stWceziHl8DV5WPAFRU7SgmqOimA2xVI\nACyHJguzXu7MNTrVwXT/bIQopOzJ8vTpF79nj1BSbZawjaFhuLqE8PuVx4KzHk9Jr3Y5spTA\nT9weWKNSXM7weBWFlD05IOd8a34WYTeeQS76sIar6oXYuswQq+05zbVpIOwDM+liffqXJQdn\n3pDwIQope5JoNV1//WA/B1+f5W0G/7mxp7Il5hpbQnkt3aa/vreet3nE6K28Ow77aP0p8j7F\nsswdFxZEIWVTFknnpEB4K6IAxpp+qbOKW9qVW4Ovwwwy0IrZQXlc1MvGsnRJcyeks6uOUlw8\n4Eh8vvCZhyik7Mp8c2WYK6iCv7Zc1qGJozwrh1FhkmG6b4fvvRTXkNZp6eWSbwBsRwCZhyik\nbMvnvVNX3czqQWDm8ZIB00+VasU047cVLIXc7ksA3DbDi/SD3+yMKCQRE/OVPAXhm1rAwh64\nh1uDVgAAENtJREFU7kQZWq5nr8cpRI307IIoJBET8wg8hT9CCl2Cf4GeNCp6tlVxNhV/HeyV\n1zMBUUgiJuYTcR5OdPkE4T5JWpw34hTqiW2dZxC+batCr6WyB6KQRExN4W6w2DDdtUUF+BJc\nRRjeLAjcvAj/M6YamDGIQhIxNXvpua6roeYPWvfomW9HWWqvrlxyIYtOvTKIKCQRk7NEIS3Y\nwEO9Qff40UeyejCYEIUkYnpeRrl0nsck0dsszwEbcoIQhSSSBdyW6pNG3nbuk9UjwYUoJJGs\nYLMyvM+o+rJ6AiMwsj9ZJqSP8Yj/KQop1/NkSPWS7Xdk9SjwYVohnariET6HPWXrj+pFFJJI\nDsOkQjolAUoJiNZnxhGFJJKbMKmQqkm2apPmKAoz5XdEIZkC7dusHkFewaRCcmvO/HlUWk0j\nCskUnChnBiyqXcnqYeQJTCokyTD9ZSXoLgrJBKygYnbf3FZXmifKqmQ1JhWSa032OhBMFIWU\n6TxXztBfB9ojchSLYMKkQupOzNKnq9XGgJ7dRCFlMpP8Wc/qZJtVmHv+q5mvIn/3HBC2akJM\nKqT37oCt6ajtDsD/9vJ3kPdP7EQhGU+rVlyj0gC8HW+SVVu4Z0aY3Q283eZsTHuO9K5TepWe\nLT7/20vy8gU/6QNyzYl31hGTSUJ6rtK796Q2CMaVZzI3kD1dhE6LQjKeSQHc1M4W79RuTDDb\n7zvpAaz95mxEIeVanitn6a+D7PBuNtRLr8tZeCLWfnM2WSGkScX5LEQh4WA5Fbv31o76UoEF\n+IRSsxfXKD4Gb8c5mqwQUgfeDkQhYeFYGSVQV7mMude40uw12WIj5p5zMqKQcjWaTMgveZVk\na6+Pss3yoDzt82xT/U8UkkhGGagYf/vrpY70liwex9UqKiCNxDxx/V1EIYlkmMUeAIBCWZ1t\n4aCszu57h7vR07N4HCxZIaRPz/gsRCFlc15f/pzVQ/ju3Ft/XSXJFgmNxe1vkZzJn2quglQE\nptrSxiEKSSRnMib9EKVb3SwdB4coJJGcydgortGlfpaOg0MUkkjOZLuKc2wOG5G1A2ERhSSS\nM0n06KT3+Vsge5zVQ2EQhSSSQzmpqrj+yo5YKotKS/8PopBEcip3G9oB83LHsnoYLKKQRHIw\n2SeIXhSSiAgGRCGJiGBAFJKICAZEIYmIYEAUkogIBkQhiYhgQBSSiAgGRCGJiGBAFJJILuPv\nu1mRuFIUkkhuInGgFQCyhrwx2NgRhSSSi0gu7brs4YtdxZ3iTX5nUUgiuYdpdvp3UUp0TVPf\nWRSSSC4ifCR7PUG9N/GdRSGJ5CJUu9jrD3DOxHcWhSSSKTzZte2h6e9qsY29fgG4EzXzIQpJ\nJBN4VAaoLUDRm6a+b3QP9rpN8c3EdxaFJIKfF84Vrmvh3drWD0x84/WKs8zlnX8HE99YFJJI\nJtCmsP73pyln6pRz2o7yHpv2jnEubPLQWVFIItjRWq5lG/tkP0x97w1lbZSFxiWa+raikETw\n8wlcZRtPQbZIlWUKRCHlbp7v23xPa+qbJhPH2cZ18MbU984qRCHlZl5UB0prkP+Cqe9bOI69\njvMx9Z2zDFFIuZiPvsUuauDjlqorJr7xBtle5nLSbL6Jb5x1iELKxfT3Z09TGpQy9Z2HUjXG\nTahHd9PCLyv79V781tT3Nz2ikHIxPjPZ6yUiE0rJojndIapIm8MQ7raxr1LTVbXC1Pc3OaKQ\ncjGSg+z1GzD5KonjimyQ7jepmUHvy6IBmAxRSLkYC65c8ktwK4tGUJM7ke1WMIsGYDJEIeVi\nKrdirwtssiL4WodWsZ1tXAKmDmswNaKQcjGHqHXM5ZrNGPhq//JzJvcygAngItt4Be6Y/Oam\nRRRSbmYaXXHUpKayZp/bUgp30s7kS36tkgtruEiIb6T/jyikHMPVLqUKxezUVPA+pIEJEyVL\nTH3/2rXZa5cIU9/Z1IhCygNsUMXrr9MtE0x852vyfkkQpk2hD5j4xiZHFFIeoFEMe00y24G5\n5zdxERb5Ym8bNthnZ1OhipN6Deb7Zj9EIeUBosZxjZDZeDu+5Rgycfuc8vLthk0S1g3suzyb\nLJASMjFsVhRSHqBiP67huhxrv2khdVOY6wj1K6z9Zgo/hnoRhM/IpEzqXhRSHmBkUJr+ehHg\nDf0+KGWd6DQB47H2mxkkRLrNvnB+hnPJTDoEEIWUB3ht0YNR0ouQenj7/aMw1+jUAG/HmUB/\nT31o1EuX4ZnTvyikvMBR6+BeE2LMi3/G2+3oklyjZy28Hf9fe3ceHGV9BnD8t0k2ByQEArE2\nQmKJ02kpcldaBEQoNwxQZUAQDxQphxMsGKCSUq0CA22pgxytHRDSAk4BS2mBwXINymGA0Co4\nLSqFRG4IyBUCya/vu5vLYEJjnuyzId/PH+9uht33eXfgy7777mZfefnxhYf+32hcPQMIqVY4\n+cqAHzyxTPqDQivi8vxXukwSXrO44o9WZJqcahlASChX/r6lS/dX8IvqF+Nm+S43hQT66xgr\njZCgZl9zk5RoWmSWf4sVoSkf5n7yq7qp5d8kSBTv2s1n1w6B9XHs8OPWfj60QQWH+jY2N8Yk\nLAz416tUHgcboGRQT18f+d0qPCR3duexwGxOFbmHvzM4/I2Aux6x3n9lbZTSbzPJ4g1ZqMgu\nevf2kAn4Nz5UEz4ihMC7aPb4r7znuaK7JTUCIaEcLSf7Lye21d2OmoGQUI63w30f6l7tXa29\nJTUBIaE8r4Z2SU3tHDpLeztqBEJCuTJTe/dO/af2VtQMhAQIICRAACEBAggJEEBI6vIzFlf4\nywqoCQhJ257veL6VaFpxcKxmIyRlH8Y8dcra7MENa81pi+9MhKSsb3/fXt3Nh4ZrbwmqgpB0\nXfH+w39lVTQvk2oyQtL1mTnqv3LAnNfdElQJIek6awq/EmFLSJ7ulqBKCElZszT/5fgOutuB\nqiEkZemRf3MvVoat094SVAUhaftFyMOpkx4M+432dqBKCEnd/hd795vykfZWoGoICRBASIAA\nQgIEEBIggJAAAYQECCAkQAAhAQIICRBASIAAQgIEEBIggJAAAYQECCAkQAAhAQIICRAQnCFl\nGKCGyaj0P/PqD8ke2Fsxz8/SNcX9RHV88hDV8e16qo7v/oDq+MHNvvqf5IHK/ysPQEi349mi\nOr5xuur49rqndR2Uojp+/KOq41+T+940QiIkRYQkiJAUEZIQQiIkRYQkiJAUEZIQQiIkRYQk\niJAUEZIQQiIkRYQkiJAUEZIQQiIkRYQkKOI91fFN31Yd30n3HDBDXlQd/9NhquPndBFbVRCE\n9JnumYuP3lAdf/yq6vgzF1XHXzirOv7qcbFVBUFIQM1HSIAAQgIEEBIggJAAAYQECCAkQAAh\nAQIICRBASIAAQgIEEBIggJAAAYQECCAkQAAhAQK0Qzo/MTGsYf9dWuM/fbZpeKMBe7TGu14w\nzyhNXlJ46oVfKs23dn3n6NiHtyoNjyg69cQRibUph3TuXtM3bXhYeOXPRyMiMyb88enDvd6d\nOuNdGaFqIc01j012qX1nxmKTPG1SvNZf/jTfg598b+Q5ibUphzTOzHOWq01vnfHdPdud5RrT\nX2e840arlmohTf8apwGSdCq69WVrD8eM09yIjNBXRdajHNKEbnnOsiAqSWf8tKnu8qb3ezrj\nHbM8G9RCSjGHlSb7zTEb3QvVr+y42fq7MieU1H6N5JPrba05PtsM1Br9SdSYHLWQnjRnbmad\nURru6BmVZ3N1v3zF2b3dKrOioAhpgW8HT8mVrS1i1HZxuiVc0AtpoHmpgTHf/pPSeJvUbN+D\nHpO8RGu+43J8N6E1BUNI2+t01PtKrFhjhn+qNXyJWWX1Qupims5cNrWeWaQ0PybpmxNXvZ5o\nFijNd8wyO4TWFAQhLY9oI3Lc5OuZ8lyHkI5KJZ2K628VQ9q8ynmtbw9GxCmddj7CLHOWx6Mb\n3dSZb+3VRp2lVqUeUkGa6fWF7iZsq9siX2Xw0OijmiEVGmQ+0BncMNxX0GDzL5351v7RLJVa\nlXZIBSPN82r/IRUZZg5pjF1v0rKysg6ax7JUX3GPNkpvJLUNdQ/Z2rFG6Y0ka/uH5kitSjuk\nFDNDb3h2ixG+yx/rvKEyseitdTNZY/ylBct9lx2N0p7teLPbvehhjunMt9frthNbl3JIq43q\n2RAah7t/lf+Ojr6mMf3QOtdK02Pdxxrj8++Jduf+xWi997DX0zXX2oyQFkrzbabgXrVySMnm\nef8HNc6rjH8n1Dv0pafqmjdUpvvpvUZa66k7Mm2Qp94+pfl2gmn18qio8K1a81camU81uJRD\nMqIfHKy83QPjQ+v/6K86w/0UDzbs7F0/LOEJvY83FCxqGRnbR+lQh2OheV1sXdqvkYA7AiEB\nAggJEEBIgABCAgQQEiCAkAABhAQIICRAACEBAggJEEBIgABCAgQQEiCAkAABhAQIICRAACEB\nAggJEEBIgABCAgQQEiCAkAABhAQIICRAACEBAggJEEBIgABCAgQQEiCAkAABhAQIICRAACEF\nmyHmxG1uEdr+NivIktsa/J8IKRikF58CdJ6d2fO8tTN956Oc+dVnpSSkIERIwSDdtE/x2+H7\n+bjZULy8FSEFIUIKBulm+pd+XutLaC0h1RyEFAxKh+S8Rurr7uTt8C+tPTk20dtogO/c339v\nExn/TE5xSB09n7sXWZ5O1r7fu6E36fEj1h9SX5PjXLthutnS98+d3aJe9P2z8wP50GoLQgoG\nZULaNcL8/J1z/qU9nRQ7OX1G44ht1u4ITZjx5vBO3qKQ5jsvqRxzze/s3siEV34/Jeaus7eE\nVOr+T5thCxcNMuMC/wDvfIQUDMqEZGf6dur8yzFhGc7yWEw7a3sZ93llrCkK6XRYF/eiQ8R5\nu6DNVufaPLesMiGVun+dH7o3f+GRmwF7YLUHIQWDCkIqaNjmhKunuZQfmezeILM4JNsr9JS7\nZzfI/1Petc1mYtmQSt3fxiacCuSjqlUIKRiUHP7OLBvSyeI/Ophturs3vlYS0lJnp87Zs1vt\nXH2zfX33RillQyp1f/tbU2/E4mylx3iHI6RgkG6+P84vu2xIh02rDX45/zH9fbf2FIf0RWQP\nZ8+ufq61U027Jdt2/eHWkErd39rNA+saT5//Kj3KOxohBYMKdu1OmlZFf5Llf0a6VPKMZB/1\nns/yjHKepaKaXHJ+3PjlkK74npGK7+/KffdJz33Xq/fR1EqEFAwqOtjQKNJtwp52nmC897nX\n3i8V0hqTPtdst/aI8b1OmloU0kDj3N5+5B5sKLl/oTFmT7U/oNqHkIJB2ZBmmzXONf9yjHnF\nWZ6+u5+1XXxH7YaVCik3dthDSQXOc4+ntfNT5j1mtD+kMW5dNtV31K74/rsSlrr3GWf2B+6R\n1RqEFAzKhrTKPPDrDwqXpxI9z741I9G7ydr1nrumzOnXNbbUJxuejgub6l72M6NXpDVYH9Z4\n+WU3pHdN2y27p3aKcUIquf+N5uGj5i8YGdKxINCPrxYgpGBQNqS8R6Ia/LlwaU+MaRJWv4/v\nQ3gr7w+PH5nTpHXJPTe5R+Mcp4fFx3bdYV+OvvuE7yNCbyV7v/HchYROtvT9z01IrhPbctql\nQD602oKQAAGEBAggJEAAIQECCAkQQEiAAEICBBASIICQAAGEBAggJEAAIQECCAkQQEiAAEIC\nBBASIICQAAGEBAggJEAAIQECCAkQQEiAAEICBBASIICQAAGEBAggJEAAIQECCAkQQEiAAEIC\nBPwP3WcB2qOfPT8AAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA0gAAANICAMAAADKOT/pAAADAFBMVEUAAAABAQECAgIDAwME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\nz/AG2/kDPekAAAAASUVORK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA0gAAANICAIAAAByhViMAAAACXBIWXMAABJ0AAASdAHeZh94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",
      "text/plain": [
       "Plot with title \"\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA0gAAANICAMAAADKOT/pAAADAFBMVEUAAAABAQECAgIDAwME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\n41jrrQAAAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title \"\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA0gAAANICAIAAAByhViMAAAACXBIWXMAABJ0AAASdAHeZh94\nAAAgAElEQVR4nOzdeSBV+f8/8HNd3Oz7WnaRNQqVJZTKkiUy0dCUaqK9aVNjVKO9aU+TKa3a\n07SQkpIRLRQhKSIh2cl+uff+/rjf3/3eL6aa4l6u5+Ov8Xqfc96v8/k0zdNZ3ofEYDAIAAAA\nABj4+LjdAAAAAAD0DgQ7AAAAAB6BYAcAAADAIxDsAAAAAHgEgh0AAAAAj0CwAwAAAOARCHYA\nAAAAPALBDgAAAIBHINgBAAAA8AgEOwAAAAAegWAHAAAAwCMQ7AAAAAB4BIIdAAAAAI9AsAMA\nAADgEQh2AAAAADwCwQ4AAACARyDYAQAAAPAIBDsAAAAAHoFgBwAAAMAjEOwAAAAAeASCHQAA\nAACPQLADAAAA4BEIdgAAAAA8AsEOAAAAgEcg2AEAAADwCAQ7AAAAAB6BYAcAAADAIxDsAAAA\nAHgEgh0AAAAAj0CwAwAAAOARCHYAAAAAPALBDgAAAIBHINgBAAAA8AgEOwAAAAAegWAHAAAA\nwCMQ7AAAAAB4BIIdAAAAAI9AsAMAAADgEQh2AAAAADwCwQ4AAACARyDYAQAAAPAIBDsAAAAA\nHoFgBwAAAMAjEOwAAAAAeASCHQAAAACPQLADAAAA4BEIdgAAAAA8AsEOAAAAgEcg2AEAAADw\nCAQ7AAAAAB6BYAcAAADAIxDsAAAAAHgEgh0AAAAAj0CwAwAAAOARCHYAAAAAPALBDgAAAIBH\nINgBAAAA8AgEOwAAAAAegWAHAAAAwCMQ7AAAAAB4BIIdAAAAAI9AsAMAAADgEQh2AAAAADwC\nwQ4AAACARyDYAQAAAPAIBDsAAAAAHoFgBwAAAMAjEOwAAAAAeASCHQAAAACPQLADAAAA4BEI\ndgAAAAA8AsEOAAAAgEcg2AEAD/Lx8SGRSKWlpdxupDcxT+rjx4/cbgQA+i8EOwDgNDqdfvLk\nycmTJ2toaAgJCQkJCWlpafn7+2dmZnK7tf8VFRVFIpE2btzIxR62b99eUFDA+tHExGTKlCkU\nCoWLLQFAP8fP7QYAYNDx9fW9dOmSrq6ul5eXoqJiQ0PDs2fPzp8/f/HixZiYmMmTJ3O7wX6h\nvLx83bp1JiYm2trazEpwcHBwcDB3uwKAfg7BDgA4KjEx8dKlS7a2tgkJCfz8//tX0M2bN93c\n3IKDgxHsmNLS0rjdAgAMPLgVCwAclZubSxCEt7c3e6ojCMLV1fXMmTM7d+6k0+nMysePH+fN\nmzd06FBBQUFtbe39+/d3dnaytk9NTXV2dpaVlRUUFFRXV/f393/37t2/TVpRUbFo0SI1NTVB\nQUE5OTkPD49eiU3FxcVz5sxhdigrK+vm5vb06VP2Db75FKZOneru7k4QhJOTE4lEevjwIdHt\nGbvPzz5z5kwSidTU1LR27Vp1dXUKhaKiovL7778zGIzvP3EA6LdwxQ4AOEpFRYUgiLt37y5Y\nsKBLtvPz82P9c1VVlZmZWVNTU2BgoIKCwv3795cvX56dnX3s2DGCIJ49ezZx4kRpaelly5Yp\nKioWFhaGh4fHx8fn5ubKyMh0mbGqqmrMmDH19fWBgYGGhoYlJSWHDx+2sbG5c+eOra3tN59I\nSUmJhYVFS0tLUFCQgYFBWVnZ4cOHx48fn5CQYG1t/Z2nEBISIi0tfebMmdDQUFNTU319/f86\nu6CgIEEQ06dP19TUvHDhAp1O37Rp04YNG1RUVObMmfPNZw0A/R0DAICDqFSqqakpQRAmJiYH\nDhx4+fIlnU7vvllQUBBBEPfv32dVXFxcCILIyclhMBiHDx8eNWpUYmIia/TgwYMEQRw8eJD5\n44wZMwiCKCkpYR6Kn58/LS2NtfH79+/FxMTMzMw+0+eZM2cIgtiwYcO/bfDTTz8RBHH16lVW\nJTc3l0wmjx07tldOYdu2bQRBxMXFsTZgnlR5efnXzD537lyCIHx9fVkbvH37liCIqVOnfuas\nAWCgw61YAOAoAQGBBw8eLF68+PXr10uXLjUwMJCTk5s2bdrx48dbWlqY2zAYjEuXLmlqatrb\n27N2PHDgwP379xUUFAiCCAoKevbsmZ2dHUEQHR0dbW1tzGta3e/GMg9lbGw8bNiwj/+fgICA\npaVlenp6U1PTt50Fg8G4du2aoqKih4cHq6inpzdu3LjHjx/X1NT04il8w+ysIjP/MWlqagoL\nC/PYEjAA0AVuxQIAp4mLix88eHD79u33799PSUlJTk6OjY29du1acHDwuXPnHBwcysvLa2pq\nRo0axb6XpqampqYm68djx44dO3bs9evX9fX1rCL7E2xMlZWVNTU1NTU1SkpK3Tt5//69srIy\n+6um2traq1at+uIpfPz4saGhYfTo0SQSib2uq6v78OHDN2/eqKmp9dYpfMPs48aNY1ZUVVXZ\nNxAQEOjo6Pji8QFg4EKwAwDuEBERcXV1dXV1JQiirq4uKipq9erV06dPLygoaG5uJgjiMwu2\nrV+/ftu2bWZmZnv37tXQ0KBQKC9fvpw3b173LRsbGwmCMDExYd7Z7EJZWbmpqSkiIoJVsbKy\n+ppgx+xQRESkS11ISIg52oun8A2zsyoCAgJfc0AA4BkIdgDAfVJSUkuWLCkuLt69e3dSUhLz\n8X/261js2tra9u3bp6KikpiYKCoqyiw2NDT0uLGYmBjzHxwdHXvcQFJSkvHfXxRlzsseoZiY\nFTExMXFx8d46hW+Y/SuPAwC8B8/YAQDn0Gi0oKAgV1dX1pom7CQlJQmCaGpqUlBQkJaWfvXq\nFft9w9evXx86dOjly5cfP35sbW01MzNjRSKCIJKSknqcUUFBQVZWNi8vr0vGqqqq+p4TUVRU\nZHbYJRTm5uaSSCRdXd1ePIVvmP07zgwABjYEOwDgHDKZXFRUFBMTs27dOhqNxj709u3biIgI\nfn5+5vsEnp6eNTU1p06dYm2wcePGJUuWtLe3y8vLk0gk9pcMMjMzT58+TRBEW1tb90m9vb3b\n2tqY75wyVVVVGRsbM+8CfzNPT8/y8vLr16+zt/H06dMJEyYwE+p3ngKZTCYIorW19dtmB4DB\nCbdiAYCjjh49amdnt3PnzvPnz7u4uCgoKDQ1Nb1+/To+Pr6jo2PPnj1qamoEQWzYsCEmJiYo\nKCgrK0tVVTUpKSkmJmbWrFnM1xFcXFxiYmICAwPt7Oxyc3MPHTp09uxZNze32NjY8+fPu7m5\nsc+4cePG2NjYDRs2vH//3tra+sOHD0eOHKmpqVm6dOkXu719+3b326nu7u729vabNm2KiYnx\n9/dfunSprq7uu3fvwsPDRUVF9+zZw9zsO0+B+ZrF9u3bi4qKbGxszM3N2Xv44uwAMEhxb6UV\nABikPn36tH37dktLS2lpaTKZLCQkpKOjExAQwL7UHIPBePfunZ+fn7y8vICAgKam5u7duzs7\nO5lDlZWVM2fOlJOTk5CQmDBhQnJyMoPB2LRpk6ioqKKiYnl5Ofs6dgwGo7y8PCgoSEVFhZ+f\nX1JS0tnZmbnLZzDXsevRrl27mNu8f/9+zpw5SkpK/Pz88vLyPj4+ubm5vXUKVCrVy8tLSEhI\nSkrq8uXLjP+7jt0XZ2euY5efn8/ej4SEhIGBwdf/PwUAAw6Jgc/LAAAAAPAEPGMHAAAAwCMQ\n7AAAAAB4BIIdAAAAAI9AsAMAAADgEQh2AAAAADwCwQ4AAACARyDYAQAAAPAIBDsAAAAAHoFP\nin2VFy9edHZ2crsLAAAA6Bf4+flHjhzJ7S56gGD3Zenp6V2+0ggAAACDXFpampmZGbe76ArB\n7suoVCpBEO3t7YKCgtzuBQAAALiMSqVSKBRmPOhv8IwdAAAAAI9AsAMAAADgEQh2AAAAADwC\nwQ4AAACARyDYAQAAAPAIBDsAAAAAHoFgBwAAAMAjEOwAAAAAeASCHQAAAACPQLADAAAA4BEI\ndgAAAAA8AsEOAAAAgEcg2AEAAADwCAQ7AAAAAB6BYAcAAADAIxDsAIAoKCiYPn26nJycuLj4\n2LFjb9y4way/f//e19dXSUlJWFh4ypQpBQUFzHplZWVAQMDQoUNFRUXNzc1v3brFvd4BAOB/\nIdgBDAoZGRlr1qxxcnJydXVdt27dy5cvWUOdnZ0TJkwgkUgPHjzIysqytbX18vJ69epVZ2en\ni4tLZWXl3bt3X7x4ISsrO2XKlPb2doIgPD09s7Ky/v7775ycHFtb22nTprEyHwAAcBGCHQDv\n27Rpk5mZWVpamrGx8YgRI5KTk01MTPbu3cscbWhoWLZs2ZEjRwwMDNTV1cPCwuh0elZWVlZW\nVk5OzuHDhw0NDYcPH37s2LHq6urY2NiGhgYFBYWIiAgLCwt1dfUdO3aQSKRHjx5x9xwBAIAg\nCH5uNwAAfSsqKmr79u03btxwcXFhFS9evOjn5zd8+PCpU6fKyMisXLmSWW9sbDxw4ICEhISN\njU1JSQlBEEOGDGEOCQkJycrKpqWleXp6RkdHsw5VUVHR0dGhqanJwXMCAICe4YodAI/bunXr\nqlWr2FMdQRAzZswIDAzctm0be1FWVlZcXPzKlStJSUnKysrGxsbKysqhoaHNzc10Ov3IkSOl\npaXV1dXsu7S2tvr6+np4eFhZWXHiZAAA4LMQ7AB4WXV19atXr7y8vLoPeXp6Pn78uKOjg1VJ\nTU39559/Ro8e7eDgkJeXJyQkFB0dnZaWJiEhISUl9eLFi/HjxwsICLC2LykpsbGxkZCQiIqK\n4sTJAADAlyDYAfCyxsZGgiCkpaW7D0lLS9Pp9KamJlZFR0fHxsbm2LFjWlpa+/fvJwhi7Nix\nubm5tbW1lZWVf/7557t379TU1JgbP3r0yMzMbMqUKdeuXRMSEuLI2QAAwBcg2AHwMgUFBQEB\ngR5fWS0oKBAVFZWUlLx3756Ghgb7PVYajcZgMOh0+uXLl0tKSsTFxSkUSl5eXkFBgb29PUEQ\nT58+dXFx2bdv35YtW/j48NcIAEB/gb+RAXiZsLDw5MmT9+3bx2Aw2Os0Gu3gwYPu7u4kEsnM\nzIxKpf70009ZWVnFxcU7duxIS0ubPn06Hx/f/v37FyxYUFxcnJubO2vWrMmTJ1tYWLS1tfn5\n+QUEBNjY2JT+f/X19dw6RwAAYEGwA+Bx27dvf/DgQUBAQGVlJbNSVlbm6+ubk5MTFhZGEISE\nhMS9e/fIZLK1tbW+vv758+fPnTvn4OBAEMTZs2dpNJqBgYGVlZW+vv7FixcJgnjy5El+fv7u\n3btV2AQHB3PxHAEAgInU5fd46C41NdXKyqq9vV1QUJDbvQB8i6dPn/7000+vX79WV1en0Wjv\n3783MTE5deqUsbExt1sDABh4qFQqhUJJSUmxtLTkdi9dYR07AN5nYWHx8uXL58+fZ2dnk8lk\nIyMjExMTEonE7b4AAKCXIdgBDAp8fHxmZmZmZmbcbgQAAPoQnrEDAAAA4BEIdgAAAAA8AsEO\nAAAAgEcg2AEAAADwCAQ7AAAAAB6BYAcAAADAIxDsAAAAAHgEgh0AAAAAj0CwAwDgHQ8fPiR1\nExgY+G91giAaGxsDAgJUVVUlJCTs7e3T0tK4fRIA8O3w5QkAgAGppaWFIAhhYWH2ooWFRUlJ\nCevHhoaG8ePHOzs7/1udIIi5c+cWFBRER0fLysru37/f0dHxzZs3MjIynDoPAOhNJAaDwe0e\n+rvU1FQrK6v29nZBQUFu9wIAg11bW9uOHTuioqIKCwsJgtDU1Jw1a9aaNWsoFEr3jefOndvS\n0nL+/Pl/q3/48EFFReX+/fu2trYEQdBoNBUVlfXr1y9evJgD5wIwQFGpVAqFkpKSYmlpye1e\nusIVOwCAAaOlpWXSpEnFxcVr1qwZM2YMQRCPHz/euXPn3bt379y5IyQkxL7xP//8c/ny5YKC\ngi4HYa8/e/aMIIhx48Yxh8hk8tixY588eYJgBzBAIdgBAAwYW7ZsKS0tTU9PV1RUZFbGjBnz\nww8/WFhYbN++fdOmTewbBwcHL1u2TF5evstB2OtVVVViYmLstyPk5OTevXvXt6cBAH0GL08A\nAAwMdDo9MjIyJCSEleqYlJSU1q9fHxkZyf5oTXx8fGZm5sqVK7scpEudRCL1ddsAwEkIdgAA\nA0N1dXVFRYWVlVX3IUtLy7Kysvr6elYlKirKyclJUlKyy5Zd6vLy8o2NjVQqlbXBx48fuwRH\nGEAqKysDAgKGDh0qKipqbm5+69YtZn3MmDFd3okuLS1l3zE+Pp5EIv3xxx/c6Bp6E4IdAMCA\nx7zwxrpiR6VSr1275unp2WWz7nUzMzOCIFJTU1kbpKamsh65gwHH09MzKyvr77//zsnJsbW1\nnTZtGvNhytra2s2bN5ewUVJSYu3V2Ng4f/58cXHxLkfLyMhYvXq1o6Ojs7Pz2rVrs7KyOHoy\n8E0Q7AAABgZZWVl5eflHjx51H0pNTVVWVpaSkmL+mJub29jYOGrUqC6bda8rKCj4+vquWLEi\nPT29sLBw6dKl/Pz8M2fO7LuzgL7T0NCgoKAQERFhYWGhrq6+Y8cOEonE/ANTW1urpaU1jA2Z\nTGbtuHLlSisrq+HDh7Mf7ffffzc3N3/27JmJiYmRkdGTJ09GjRq1Y8cOTp8V/Ed4eQIAYGDg\n4+MLCAjYvHmzq6sr+ysRHz9+3Lp1a0BAAOuBOeZdNgUFhS5H6LEeERGxYsWKKVOmtLS0jBs3\n7u7du6wrN0VFRcnJyQUFBcOGDTM3Nzc1Ne27s4PvJyEhER0dzfqxoqKio6NDU1OTwWDU19ff\nvn17z549Hz580NPT27RpE2udjrt3716/fv3ly5eOjo6sfc+fP79169Zr165NnTqVVbx69aqP\nj4+urq6HhwfHTgr+MwZ8SUpKCkEQ7e3t3G4EAAa7pqamMWPGqKqqHj58OD09PS0t7dChQ8OG\nDbO0tGxubu7FiTo7O5cvX04mk1VUVCZMmKCjo8PHx+fq6lpbW9uLs0DfaWlpGT9+vKenJ4PB\nYF7J8/HxefLkybNnz2bPni0oKJibm8tgMD59+qSqqnrp0iUGgzF69Ohdu3Yxdzc0NFy3bl33\nw65YscLc3JyD59FPtbe3EwSRkpLC7UZ6gGD3ZQh2ANB/tLS0hISEqKurEwRBIpE0NDRCQ0Nb\nW1t7d5bly5fLysreuXOHVcnJyTE0NBw/fjyNRuvduaDXvX//fvTo0a6uri0tLd1HaTSatrb2\n8uXLGQzGzz//7OXlxayzgl1dXR1BEGlpad33TU5OJpFIvf7nbcDpz8EOt2IBAP6PkpIS5vWw\njx8/jhgxwsHBYc6cOf3nwzNCQkJhYWFhYWGNjY0EQYiJifX6FEVFRQcPHoyLi5s0aRKraGBg\ncOvWLT09vevXr0+bNq3XJ4Xe8ujRIw8Pj3nz5oWFhfHx9fAkPR8fn56eXklJSUJCwrVr17q/\nEsH8o8V6ZJOdlJQUg8FobGwcMmRIXzQP3w8vTwAA/K87d+4YGhrevXvXwsJiwYIFcnJyv/76\nq5WVVU1NDbdb60pMTKwvUh1BEHfu3FFVVWVPdUwqKipOTk6sFTSgH3r69KmLi8u+ffu2bNnC\nSnU5OTlz585tampi/kij0bKzs7W0tCIjIxsaGgwMDGRlZWVlZV+8eLFhwwYDAwN5eXkKhdL9\nmyUEQeTn5wsLC0tLS3PulOA/whU7AID/8eHDB29v70WLFm3dupX1IsKmTZumTJkyZ86cGzdu\ncLc9jqmoqFBTU+txSE1N7fXr1xzuB75SW1ubn59fQECAjY0Na5k6UVHRoUOHxsTENDQ0bNu2\njUwm79y5s6KiIigoSFxcfNeuXazdXVxc3NzcFi5cSKFQnJyc9u3bN3nyZPYlrOl0+oEDB9zc\n3NjfqIX+BlfsAAD+x5EjR9TV1bds2cL+HzM5ObkTJ07cvHkzLy+Pi71xkpSUVEVFRY9DFRUV\nuFrTbz158iQ/P3/37t0qbIKDg6WkpO7du9fc3DxmzBgDA4Pc3Nzk5GR1dXVpaWn2BVAEBAQk\nJCSY69tt27YtNTXV39+/vLycefCysjJfX98XL15s3ryZq2cJX4ArdgAA/+Px48cuLi7dH0sa\nOXKkiorK48ePR4wYwZXGOGzixInLly/PyMjosr5JfX39rVu39uzZw63G4PNsbW0ZbJ+VY2do\naBgXF/f53dPT01n/PGLEiPv378+ePVtZWVlVVZXBYJSUlJiYmCQmJmppafVm09DbEOwAAP5H\nc3Pzvz21Ji4u3tzczOF+uMXAwMDb23vGjBk3b97U1dVlFmtqanx8fJgLGnO3PeCM0aNHv3jx\n4sWLF9nZ2Xx8fIaGhiNHjsTHhfs/BDsAGKTKysqioqKysrJaW1v19fW9vLzU1dV7vN/a1tZW\nVFTEXGFkkDh+/LiPj4+RkZG1tfXw4cNLS0uTk5M1NDRu3brVuy8INzc337p1Kysrq7Oz08DA\nwMXFpceXMYEr+Pj4TE1NsTD1wIJn7ABgMLp48aKuru6pU6dERESGDRuWlJRkZmbW1tZ25cqV\n/Pz8LhsfOHBASEjI3t6eK61yhYiIyM2bN2/fvm1tbd3U1GRgYHD8+PH09PTeTbcJCQlaWloL\nFix49OhRRkbGqlWr1NXVL1y40ItTAAw2uGIHAINOenq6v7//1q1bV65cybq1FB8fP23aNC0t\nrYkTJ4aHh0+ZMkVQULC6ujo8PHzz5s0nT54UFhbmbtucN2HChAkTJvTRwbOyspjvYG7evJm5\nKFpnZ+fevXv9/f3l5OQmTpzYR/MC8DbSvz1oCSypqalWVlbt7e39Z4VSAPgeXl5eBEGwf1WT\naffu3bt3754+fXpERASdTpeSkqqqqho6dOjevXu9vb250Skv8/T0pNFo169f71JfuHBhenr6\n06dPudIVwNegUqkUCiUlJYX1yd3+A7diAWDQSUpK+uGHH7rXvb29y8vLFy9eXFFRcf/+/cOH\nD7948eLdu3dIdb2OwWDcuXNnzpw53YfmzJmTnp5eW1vL+a4AeABuxQLAoNPQ0CArK9u9Licn\nRxBEfX29jo6OjY0Nx/saRJqbm1taWoYNG9Z9SEVFhcFgVFZWYsE8gG+AK3YAMOgoKysXFhZ2\nr799+5Y5yvGOBh0REREhISHW4rfsPnz4QBBEj8kbAL4IwQ4ABh1XV9eIiIjOzs4u9fDwcFNT\n0x4vI0HvIpFIDg4Op06d6j50+vRpU1NTBDuAb4NgBwCDzvr160tLS6dPn866YtTc3Pzrr79G\nRkbiswp9gUajPXz48MiRI4cPH37w4EFHRwdBEBs2bLh582ZoaCjzR4Ig6HR6eHh4eHj4li1b\nuNovwACGZ+wAYNBRVla+f//+jz/+qKKioqGhISIikpeXJy0tffXqVTs7O253x2vS09P9/Pze\nvn2rra3Nz8//+vXroUOHnjx50tbWNjo6+qeffjp69KiZmZmgoGB6enp1dfXRo0ednJy43TXA\nQIVgBwCDkb6+/vPnz58+fZqVldXW1qanp2dtbc1cTQ160Zs3bxwcHNzd3R8+fMi8u9rQ0PDr\nr786OTmlpKRMnTq1sLDw77//zsnJ6ejocHR0dHNzU1BQ4HbXAAMY1rH7MqxjBwDwbXx8fGpq\nauLj47t8Y9Tb27uhoSE+Pp5bjQF8D6xjBwAAgw6DwYiJiVm4cGH3L8cvWrTo/v37zc3NXGmM\nh12/ft3JyWno0KGSkpJWVlZ79uyhUqncbgo4CsEOAAD6RH19fXNzs6amZvchLS0tGo1WUVHB\n+a542PLly3/44Qd1dfVdu3adPHnSwcFhx44d9vb2TU1N3G4NOAfP2AEAQJ8QExMjk8nV1dXd\nh6qqqgiCkJSU5HhTPCs6OvrIkSMJCQmstbU9PDyCgoKsra2Dg4MPHTrE3faAY3DFDgAA+gQ/\nP7+VldWlS5e6D12+fNnIyAjfluhF4eHh8+fP7/LFFEVFxZ07d544caKlpYVbjQGHIdgBAEBf\nCQkJOX78eGRkJHvxypUru3fv/u2337jVFU/KyMiYOHFi9/rEiRNbWlry8vI43xJwBW7FAgBA\nX5k0adKhQ4cWLlx46NChsWPH8vHxpaenP3/+fOvWrd7e3tzujqdQqdQel25gFlmrQAPPwxU7\nAADoQwsWLHj16pWXl1ddXV1lZaWTk1NWVtbq1au53Rev0dHRycjI6F7PyMggk8laWlqcbwm4\nAlfsAACgb2lqaoaEhHC7Cx7n5+e3a9eugIAAJSUlVrGzszM0NNTR0RHf3h08cMUOAABgwFu8\neLG2tralpeX58+dLSkrq6uoSEhImTZqUnZ29f/9+bncHnIMrdgAAAAMehUKJj4//7bffFixY\n0NjYSBAEPz+/i4vL06dP1dTUuN0dcA6CHQAAAC8QFhbevXv3rl27ioqKmpubdXV1KRQKt5sC\nTkOwAwAA4B18fHx4VWIwwzN2AAAAADwCwQ4AAACARyDYAQAAAPAIBDsAAAAAHoFgBwAAAMAj\nEOwAAAAAeASCHQAAAACPQLADAAAA4BFYoBgAAKC/oNPpMTExSUlJb968GTZs2JgxY3x8fIYM\nGcLtvmDAwBU7AACAfqGhocHBwWHGjBn5+fk6Ojq1tbWrVq0aOXLkmzdvuN0aDBi4YgcAANAv\n+Pv7V1ZW5uXlqampMSufPn368ccfXVxcsrOzcd0Ovgau2AEAAHBfRkZGTEzMxYsXWamOIAhx\ncfFz587V19efO3eOi73BAIJgBwAAwH1JSUkGBgYGBgZd6mJiYk5OTg8ePOBGUzDwINgBAABw\nX319vZycXI9DcnJy9fX1HO4HBig8YwcAwAmlpaW7d+9OTU0tLi5WV1e3sbFZuXKloqIiF1tq\namo6c+ZMWlpaWVmZlpbWhAkTpk2bRiaTudjSYKasrFxUVNTjUGFhobKyMof7gQEKV+wAAPrc\no0ePjI2Nk5OTvby89u/f7+HhcffuXSMjo+fPn3OrpZycHCMjo7CwMDqdbmZmVlVVNXv2bDs7\nu7q6Om61NMg5OjqWlpbGxMR0qRcWFt6+fdvV1ZUrXcGAQ2IwGNzuob9LTU21stUmwsUAACAA\nSURBVLJqb28XFBTkdi8AMPA0NTXp6upOnTr1zz//5OP7n1+nOzs7AwICkpOTX716xfm3HVta\nWvT19c3NzU+dOiUsLMwslpWVubi4DBs2rHu2AM4IDg6OiIiIjIycNm0aiUQiCOLp06d+fn6a\nmppxcXHMCvQHVCqVQqGkpKRYWlpyu5eucMUOAKBvXb58uaOjY9++faxURxAEPz9/eHh4XV3d\njRs3ON/SmTNn2tvb2VMdQRBDhw49d+7crVu3MjIyON8SEASxdevWRYsW+fr6ysrKjh07dtiw\nYWPHjjU3N798+TJSHXwlBDsAGLw480D6s2fPxo8fLyQk1KUuJiY2bty49PR0DvTAUlRUtGXL\nlm3btg0ZMmT79u05OTnso/r6+vr6+v/88w8nWwIWPj6+zZs3FxcX//XXX56enjt37nz9+vXZ\ns2fFxMS43RoMGAh2ADDopKamOjo6SkpKSklJycjITJs2LSsrq++ma2tr657qmISFhdva2vpu\n6i4iIyP19PQuX75MEIS0tHRCQoKJicmWLVvYt5GRkWloaOBYS9CdoqKil5fXmjVrZs6cOXz4\ncG63AwMMgh0ADC5nz561tbWVk5M7depUZmbmX3/9RafTLSws4uPj+2hGLS2tfwuOWVlZ2tra\nfTRvFw8ePAgMDNy/f39mZuaUKVPU1NRSU1Ojo6PDwsLOnj3L3IbBYLx9+3bYsGGcaQkAeh8D\nviQlJYUgiPb2dm43AgDfq6ysTEREZM+ePV3qq1evVlBQ+PTpU19Mmp+fLyAgEB0d3aV++vTp\nIUOGvH//vi8m7c7BwWHOnDnMf46NjR0yZEh+fj6DwQgNDdXR0WHWr1y5IigoWFZWxpmWAAao\n9vZ2giBSUlK43UgPcMUOAAaR8+fPKysrL1u2rEs9LCyso6Ojj95j0NbWDg0N/fHHH3fu3Flc\nXMxgMIqKisLCwubNm7d161YVFZW+mLQLBoPxzz//eHt7M390dnaeMGHClClTHj586O3t/ebN\nm7KysqioqDlz5qxfvx5LpgEMXFigGAAGkZycHEtLS/a3U5koFIq5uXmXNwl6UUhIiJKSUmho\n6Nq1a8lkMo1GU1FRiYyM9PPz66MZu2hpaaFSqbKysqzKpUuXFi9ebGtrKyEhQRAE81mukJCQ\ndevWcaYlAOgLuGIHAIMIg8H4t2UjSKS+Xddz7ty5paWlhYWFCQkJRUVFxcXFHEt1BEGIiIhI\nSkoWFhayV06cOFFUVLRq1SoSiXT69OmSkpL169djWQ2AAQ3BDgAGEX19/cePH3cPcB0dHc+e\nPev+/fXeRSKRNDQ07Ozs1NXVOZ+fXF1dDx8+TKfT2Yuqqqo5OTm2trbTp0+XkZHhcEsA0OsQ\n7ABgEPH19S0uLj5y5EiXelhYGIPBcHNz40pXnLFp06bs7Gw/P7/Kykpm5dOnT8uWLfv77793\n7tzJ3d4AoLfgGTsA6IpKpV65ciUtLe3Dhw/Mb8M7ODhwu6neoaKicujQoZ9//jkzM9Pb21tF\nRaWwsPD06dPR0dHR0dHMp814lYaGxv379/38/JSVlbW0tAQFBV+/fq2kpBQbG2tubs7t7gCg\ndyDYAcD/kZ+f7+7uXl5ebmtrO3To0KdPn/7xxx+TJ0++ePGiiIgIt7vrBQEBAerq6hs3bpw6\ndWp7e7uwsLCVlVVKSspgCDcmJiZZWVlPnjzJzs7u7OzU19e3tLTs8hXs9PT0c+fO5eTk8PHx\nGRkZ+fv7Gxsbc6thAPiv+vZhYd6QmppqZWXV3t7e5a8/AN7T1tZmZGSko6Nz7tw51uWrN2/e\nuLi4mJmZnT9/nrvt9S4ajVZRUaGoqNj9JdlB67ffftu2bZu9vb25uTmdTn/8+PHDhw+3bt26\nZs0abrcG0I9QqVQKhZKSkmJpacntXrrCFTsA+F9nzpz59OnThQsX2L9NqaOjc/78eQsLi9DQ\nUD09PS6217vIZDIWbGN35syZP/74IyYmxtHRkVWMjo729fXV1dV1d3fnYm8A8JXweyoA/K/E\nxEQXF5fuXxw3MzPT1tZOTEzkSlfAGdu2bVu9ejV7qiMIwsvLa+HChdu2beNWV19Ep9Pfvn1b\nVFSEG1AABIIdALCrq6tTUFDocUheXr6uro7D/QDH1NTUvHr1ytPTs/vQtGnT0tLSqFQq57v6\nvJqamnnz5omJiWlra2tqaoqLiy9ZsuTTp0/c7guAmwZ2sKNSqWlpaYmJiUVFRdzuBYAXKCoq\nvnv3rseh4uJiJSUlzrbTX9Dp9BMnTri7u2tpaZmams6aNSs1NZXbTfWyxsZGgiAkJSW7D0lJ\nSdHp9KamJo439TnV1dWWlpZpaWlnzpx5//59VlaWj49PVFSUmppaSEjI8+fPud0gAHcMmGC3\nefPmLreBIiIiFBUVLSwsJkyYoKmpaWZmlpmZya32AHjD1KlTY2JiysrKutRjYmIqKiomT57M\nla64q62tzcnJacWKFaqqquvXr589e3ZLS8v48eN37NjB7dZ6k4KCgqCgYH5+fveh/Px8UVFR\nKSkpznf1GSEhIcyn1z09PQsLCx0cHOLi4uzs7Oh0+smTJ83MzJYtW9ZlNWaAQYExQBAEsXbt\nWtaPZ86cIQiCQqFMmzZtwYIFVlZWBEFISEgUFBT0+tQpKSkEQbS3t/f6kQH6GxqNZm1tbWho\nmJ2dzSreuHFDSkqK/V9ALmpoaHj06NHdu3fLy8s5M+Py5ctVVVWZj3CxXL16lUwmJyQkcKYH\nznB1dXV2dqbT6ezFzs5OGxsbPz8/bnXVIyqVKiYmdunSJQaDUVxcLCYmtnjxYiqVymAwIiIi\nlJSUkpKSJCQktmzZwu1OgTe1t7cTBJGSksLtRnowUIOdlpaWhIREbm4uqxIdHU0ikebMmdPr\nUyPYwaBSW1vr5uZGIpG0tLTGjx+vqKgoICCwdu1aGo3G3cZqamr8/f3JZDIfHx+FQiEIwsrK\nij2A9oXm5mZhYWFmgOhi1qxZU6dO7dPZOSw3N1dcXNzPz6+srIxZKS4u9vT0lJWV7ZJrua64\nuJggiLdv3zIYjCVLllhYWLDy6LNnzwiCaGhoOHHihJiYWEtLSx/1QKVSs7Oznz9/3tra2kdT\nQL/Vn4PdgLkVy66qqurt27eLFi1iX3nB09PT3d09Pj6ei40B8AApKanr16+/ePEiODh4woQJ\ne/fuffv27fbt27m72FtTU5O9vX1mZubt27ebmpqamppevHihoKBgbW2dk5PTd/O+fPmypaWl\ny4uiTI6OjmlpaX03Nefp6endv38/MzNz6NChqqqqQ4cOVVNTKy4uTkxMVFdX53Z3/wc/Pz9B\nEB0dHQRBJCYm+vj4sL69yywKCAj88MMPzc3N6enpvT57XV3d3LlzRUVFjYyMRo0aJSoq+sMP\nP3z48KHXJwL4BgNyHbu2tjaCILqvp2VkZBQbG8uNjgB4jZGRkZGREbe7+F979uxpaGjIyMhg\nPellbGx85coVDw+PZcuW3bt3r4/mbW1t5ePjExYW7j4kIiLS2traR/Nyy+jRo7Oysl68eJGT\nk0Mmkw0MDIyMjFiZqf9QVFRUVFRMTEzU1dWtq6uTl5dnDSUmJuro6AgJCREEISYm1uuvcjc0\nNNjY2JBIpCtXrlhaWpLJ5PT09A0bNowdO/bx48dYGRG4bkAGO2VlZQkJidLS0i71srKy7utv\nAQAPuHjx4uLFi7s8v08ikUJCQsaMGVNRUfFvq7R8J01NTTqd/vLly+6f1crOztbS0uqLSbmL\nRCKZmJiYmJhwu5HP4ePjW7Bgwe+//+7o6KikpMS8M0sQRF5e3s6dOzds2EAQRG1t7adPn3r9\nVe6tW7e2t7enp6ezPs3i4OBgY2Mzfvz4tWvXMp//BuCigXQr9v379+np6QUFBXV1dQsXLoyM\njGxpaWGN5uXlXbx4kfkWBQDwmMLCQkNDw+51IyMjBoPxb0u0fL9hw4ZZW1uHhYUx/u/it9XV\n1YcPH54xY0YfzQs96uzsfPv2LXPhlXXr1hkZGY0ePVpYWDg8PPzy5cvr1q0bM2bMhAkTFi9e\nTPz/lRNGjRrVuz1ERUWtXr2aleqYKBRKSEhIdHQ084YSADdx+yG/r9Vj81euXGGOnj17VkRE\nhI+P7+nTp70+NV6eAOA6KSmp6Ojo7vXq6mqCIDIzM/tu6oyMDDExMW9v76ysrI6Ojqamptu3\nb+vr648ePbrvHsyHLjIzM6dMmcL8YDeJRNLX1z9z5kxnZ+fBgwfNzMz4+Pj4+fnNzc2PHTtG\np9M7OjrCw8MFBASioqJ6t43m5maCIJ48edJ9qKSkhCCI/Pz83p0R+qf+/PLEgLkVe+LEiXo2\nDQ0N9fX1rPsy9fX1kpKSFy5cMDc3526fALzt1atX8fHxeXl5srKyo0aNmjp1qoCAAAfmtbCw\niIuL6/5dhLi4OHFx8REjRvTd1CYmJsnJyUFBQcbGxhQKpaOjg4+Pz9/ff8+ePcwHuaCvJSUl\nOTo6Ojs7x8TEjBgx4uPHjzdv3pw/f/6rV6+2bNmyePHigoICX1/fjIyMvXv3njhxIjc3l5nt\nfvzxx97tREBAgEQiMf+j3gXzWh3zfW0AbuJ2suwdjY2NfbcWA67YATAYDBqNtmLFChKJZGho\n6OPjM3HiRDExsREjRrx8+ZIDs8fFxfHz89+4cYO9mJ+fr6ysHBwczIEGnj59GhQUZGZmZmNj\ns2rVqry8PA5MCgwGg0qlamhoLFy4sEv99u3b7Hdp6HT6w4cPw8PDw8LCoqOja2tr+6ifkSNH\nhoaGdq//+eefCgoKXF8VCDijP1+x45Fg16cQ7AAYDMaGDRskJSXZl+Stq6vz8PAYOnRofX09\nBxoICwsjk8nTp0/ft2/f0aNHg4KCxMTEXFxcOPDvZnBwMB8f38SJE9euXfvLL7+MHTtWQEAg\nPDy8r+cFBoMRHx9PoVDq6uq6D02ePHnRokUc7ufo0aNiYmLp6ensxfz8fAUFhU2bNnG4GeCW\n/hzsBsyt2L7T3Nz8+Y9bMz+hCDCYNTQ07Nix48SJExMnTmQVmc8/6Ovrh4eHr1+/vq97CAkJ\nsbOz++uvv06ePNnU1GRoaBgeHu7n59fXi3EcO3bswIEDt2/fnjRpEqt4+vTpuXPn6ujoODg4\n9OnskJeXp6Oj0+NHbC0sLB49esThfubOnfvo0SMbG5s5c+ZYWlry8/M/ffr02LFj48ePX7du\nHYebAeiOd4Ld27dvFyxYQBBEQkLCf9pLR0fna74n2NnZyXxuF2AQSk5OJpPJXl5eXeoUCmXG\njBl3797lQLAjCMLa2tra2poDE7Hbtm3b+vXr2VMdQRCzZs1KTk7etm0bgl1fI5PJNBqtxyEa\njcb5dbNJJFJkZKSjo+OJEydu3LjR0dFhaGi4Z8+eOXPmcHcRbwAm3gl2jY2N37BIqZaWVmZm\n5uev2F29enXr1q34mDQMZtXV1XJycj2+J6GsrMx8NZUnlZWVFRYWdk+0BEF4enp6eHgwGIx+\nuH4vLzE2Nn7z5s3Hjx8VFRW7DP3zzz9jx47lSlfe3t7e3t5cmRrg83gn2I0YMSI7O/sbdvzi\n8vp98UUagIFFXl6+srKSSqV2v25dWlrKvu4/j/n06RNBENLS0t2HpKWlqVRqW1sbr74bS6PR\ncnJycnNzpaWljYyMuPVNBUtLSz09vSVLlly4cIFMJrPqp0+ffvLkydGjR7nSFUC/xTvBbsiQ\nIT2uXwoA38/GxoYgiIsXL/r7+7PXW1tbL1y4sHDhQi711eeUlJT4+PgKCgq6h9eCggIZGRle\nTXXx8fGBgYFFRUWKioqfPn1qbW319vYODw+XlZX9yiMUFBQ8efKkuLhYS0vL0tJSRUXl2zrh\n4+M7e/asvb29lZXV/Pnz9fT0Pnz4EBsbe+bMmQMHDnT/tiTAIMdTDwTU1NQUFBRwuwsAHiQm\nJhYSErJo0aKbN2+yipWVlV5eXiQSKSgoiIu99SlJSUl7e/t9+/Z1qXd2dh46dMjDw4MrXfW1\nu3fvTp06ddq0aRUVFeXl5Y2NjSkpKa9fv540adLXfFmhpaXlp59+0tHRCQ4Ojo2NXbZsmaam\n5ooVKzo7O7+tHyMjo8zMTCMjoy1btlhbWwcGBn78+DEhIYGHf6MA+Hbcfi23N61du7YvzujI\nkSMEQTQ2Nvb6kQH6lYaGhnXr1pmYmFAoFCUlJWdn5/j4eNYonU7/9ddfyWSypqamm5vbuHHj\nhISERo4c+ebNGy72zAHPnz8XFhb++eefq6qqmJX379+7u7vLy8u/f/+eu731BTqdrqOjs2zZ\nsi71mpoaJSWl3bt3f/EI7u7uGhoaqamprEpcXJy8vHz3tei+QVtb2/cfBOA79eflTnjqih0A\nfLMPHz6MHj368uXLfn5+169f37Nnj4KCgrOz89atW5kbkEikzZs35+fnBwcHa2lpubq6Xr16\n9fnz58OHD+du533N1NQ0Pj4+MTFRXl5eS0tLVVVVVVW1rKwsMTHxm28v9mfZ2dlv3rxZvXp1\nl7q0tPTcuXOjo6M/v3tiYuKtW7diY2PHjRvHKjo6Ol6+fPnIkSN5eXnf2R4+7QDwebzzjB0A\nfI/58+fLy8vHx8eLiIgwKz4+Pu7u7p6ennZ2dpaWlsyihobG/Pnzuddm36LT6SUlJdLS0mJi\nYux1KyurV69ePXv2LCcnR1BQ0MjIyNjYmFdfhi0uLhYTExs6dGj3oREjRpw4ceLzu8fExNjb\n23d/9G38+PF6enq3bt3q0++/AcCACXZmZmZf3KasrIwDnQDwnnfv3t26devZs2esVMfk7u7u\n7u7+559/soIdryosLFy9evWdO3eYX3kfPnz4ihUrAgMDWemNTCZbWFhYWFj0aRulpaXMt1D1\n9PS6/H/BMaKioq2trR0dHd1Xt2loaBAVFf387uXl5erq6j0OaWhofPjwoVeaBIB/M2CCXUZG\nBkEQn//c+Dc/mQsweHz48CE9Pf39+/fa2tpmZmbMlxxfvHghISExatSo7tvb29v/9ddfHG+T\no7Kzs21tbU1NTc+fP29kZFRTU3P37t21a9c+f/6cY6tpPH78OCgoKDMzc8iQIe3t7QICAvPm\nzduxY8cXg1SvGz16NJlMjo2N7f5qyI0bN74Y8SUlJSsqKnocqqqq4taycwCDx4B5xm716tUi\nIiIvX75s+3erVq3idpsA/Vd7e/vixYvV1NT8/f0jIiK8vLxUVFQ2btxIp9N7vDzDJCAgwPO/\nMgUEBNjb29+9e9fV1VVdXX306NHBwcH37t07ffp0bGwsBxpISUmxt7c3NTV99epVc3Pzp0+f\noqOj79y54+zs3NHRwYEG2ImLiwcGBi5dujQ/P5+9vm/fvvv3769YseLzu9vb2yckJNTU1HSp\nv337Nj093c7Orne7BYCuuP32xteiUqmmpqZmZmZUKvXftsFbsQCf4ePjM3To0Dt37jB/pNFo\nFy5ckJSUXLNmTVZWFolEevfuXfe95s2b5+7uztlOOYq5sPnbt2+7D82aNWv69Okc6MHQ0HDe\nvHldimVlZdLS0n/++ScHGuiira3N1dVVWFjYz89v586d69atGzdu3JAhQ86ePfvFfTs6OoyM\njOzt7WtqaljFkpISU1NTBweHvuwagHPwVmwvEBAQOHv27MuXLznzSUoAHpOcnHzlypVbt25N\nnjyZWeHj45sxY8a5c+f27NkjIiJiYmKybt06BoPBvldOTk5UVFSXRYl5zKtXr+Tk5DQ1NbsP\nWVhYvHr1qq8byMnJycnJ+e2337rUlZWV586de/Hixb5uoDsKhXL9+vXTp0+TyeQrV66kp6db\nW1tnZ2fPnDnzi/vy8/PHxMTU1NRoamp6eXktX77czc1NR0dHRETkwoUL7Ft2dnbm5uZeu3Yt\nJSWloaGhz84GYHAZMM/YEQShp6f38ePHz9wVcnJykpSU5GRLAAPF9evX7ezsjI2Nu9SdnJw0\nNTVjYmKOHTtmZ2fn5ub2yy+/GBoa1tbWJiQkhIaGenh4eHp6cqVnziCTyf/2JWjOfGO+sLBQ\nXFxcVVW1+5ChoSFXgh1BECQSycvLq8eP5H6Rqqpqenr6lStXHj9+/O7dOx0dnYCAADc3N/b/\nMa9fv75s2bLi4mIpKalPnz7x8/MvWLBg+/btvPolDwCOGUjBjiAIcXHxz4za2tra2tpyrBmA\nAaS0tFRbW7vHIW1t7dLS0lGjRj158mTFihWTJ09m/vqkqKi4du3alStX8uq6HkzMtyVevnxp\nYGDQZSg5Obl7FO51QkJCbW1tNBqN/UOoTM3NzQM06AgICPj6+vr6+nYf6ujoCAsL27Jly8SJ\nE3ft2uXh4UGj0eLj45csWVJQUBATE8Pbf94A+tqAuRULAN9DXFy8tra2x6Ha2loJCQmCIPT0\n9G7fvt3c3JyTk1NeXl5eXr5mzZruaYPHDB8+fMKECUuXLmU+NMNy586dv//+++eff+7rBkaN\nGkWn0+/du9d9KC4urq8XWOGw5OTk4cOHb968WUFBoaqqyt/fX0dHJy0tzc3N7f79+w8ePPji\nAsgA8HkIdgCDwvjx4xMSEro/yVRcXJyenm5jY8OqCAoKGhgYKCoqcrZBboqMjMzPzzc3N4+I\niEhNTb1x48ayZctcXV3XrVs3fvz4vp5dRkbG399/yZIl5eXl7PVTp07dunVr6dKlfd0Ax2Rl\nZTk6OhoZGVEolPz8/IyMjIqKCicnJycnp+zsbC0trR9++OHy5cvcbhNgYCN1eVYauouIiAgM\nDGxsbOT8glIAvaW9vd3IyGjEiBHnzp1j/Umuqqpyc3MTEBBISkoa5Pe/qqurf//991u3bhUV\nFYmKipqYmPzyyy/u7u6cmb2xsdHZ2Tk3N9ff33/kyJG1tbWJiYl37tw5ePBgYGAgZ3rgAFdX\nVzKZ7OzsvHv37tevX7PqzLuxN2/e3LVr15UrV548ecLFJgG+BpVKpVAoKSkp/XDx9gH2jB0A\nfBsKhXLz5s2pU6dqa2s7OTmpqqoWFBTExsZqaWldu3ZtkKc6giBkZWUPHDhw4MCBtra2IUOG\ncHh2MTGxxMTEyMjImJiYmzdvSklJmZiYPH361NTUlMOd9B0qlRofH3/jxo2qqqqmpib2ocDA\nQHd3dyqV2tjYKCwszK0OAXgDgh3AYKGrq/vixYszZ848fvw4OTlZW1v74MGDPj4+n/+gy2DD\n+VTHxHwtdMGCBVyZnQOqq6upVKqGhoaWltaHDx+eP38+atSoR48eHTp0KC0tjUqlTpo0qaio\nqMf3LQDg6yHYAQwiwsLCvJ0eoN+SlJQkkUhVVVVWVlbu7u5z586dNm3a77//7uHh4erqunfv\n3vb29tLS0oSEhE+fPn1+AQQA+Ay8PAEAAH1OWFjYwsKCuSzf8ePH29raNmzY4ODgYG9vn5yc\nLCIikpOTc/Lkyebm5i9+tQwAPgNX7AAAgBNCQ0Pd3d1HjRo1e/ZsQ0NDYWFhERGRrVu3lpeX\nT5s27Y8//tDQ0FBQUHB1dd21a5e0tDS3+wUYkHDFDgAAOMHZ2fnAgQMLFiwYOXLknTt3REVF\nCwoKqqurw8PDo6OjNTQ0CIKYOHEig8F48eIFt5sFGKgQ7AAAgEOCgoLy8vJ8fX07Ozs7Ozt9\nfX3z8vKCgoJYG/Dz8wsICLS1tXGxSYABDbdiAQCAczQ0NIKDg+Pi4saNGxccHNxlND8/v7W1\nlSAIrqw7A8ADcMUOAAA4zcfH5+jRo2VlZezF69evjxkzhiAIZ2dnUVHRsWPHPnjwgDv9AQxY\nCHYAAP1RZ2fn69ev4+LiXr9+3dnZye12/pvq6uqLFy9u2LBh165dd+/epdFoXTaYN2+ekZGR\njY3N1atX6+rqOjo61qxZM23atKamppMnT5aXlyclJY0cOdLBwYH5Ii0AfCXcigUA6DWdnZ3F\nxcWKiooiIiLfc5y//vorNDS0oqJiyJAhbW1tCgoKmzZtGigLEEZERKxcuVJYWNjY2LihoSE0\nNFRTU/PixYuGhoasbQQEBG7durVu3boff/yxra2NTCbTaDRtbe1Lly4xv7ehqKhoZWWlpaUV\nGBg4adIkvCQL8JVwxQ4AvqyqqmrAXTTisIyMjMmTJ4uIiGhra4uJiRkaGl64cOHbDrVly5bl\ny5evXr36w4cPra2t5eXla9asWbFiRVhYWO/23BfOnTu3ZMmS3bt3l5eXJyQkpKWllZaW6unp\nOTg4VFZWsm8pLCy8f//+hoaGzMzMgIAAPT29/Pz8Ll9RW7ly5ZAhQ65fv87ZkwAYwBDsAOBf\nFRUVzZw5U0ZGRl5eXkRExMLC4sqVK9xuqj+6f//+uHHjJCUlY2NjS0pKHj9+7OHhMXv27I0b\nN/7XQxUWFm7atOnMmTMrV65UUlIiCEJRUfGXX36JiooKCwt7+/Zt73ffe+h0+tq1a0NDQxcs\nWEAmk5lFGRmZCxcuKCgo7Nq1q/sugoKCI0eObG9vHzt2bPdRMplsamqal5fXt30D8BAEOwDo\n2YsXL0aNGvXhw4cjR47k5OTExcXZ2dn9+OOPoaGh3G6tf2lvb589e3ZgYOClS5ccHByGDRtm\nYWGxefPm6OjosLCwjIyM/3S06Ojo4cOHe3l5dal7enrq6upGR0f3XuO9Lysrq7S0dP78+V3q\n/Pz8s2fPjouL+7cdmbdiexzq7Ozk58dTQwBfC/+2AEAP6HT6rFmzpkyZcu7cOT4+PoIgDAwM\nJkyYMGHCBBcXF2dn5x6vrwxO9+7dq66u7n6f1MXFxdbW9vTp011uL35eUVGRkZFRj0OGhoaF\nhYXf3mjfq6iooFAoCgoK3YdUVVU/fvz4bzuOHDly//79NBqNdZ2PIAg6nX727NmkpKTi4uKc\nnBxTU9Off/5ZWVm5T1oH4BW4YgfACyoqKjZu3Ojs7GxiYvLDDz/8+eef37nEa1paWk5Ozp49\ne5ipjsXR0dHJyen48ePf1+9AVVxcnJGR0dLSwl7My8vT09MTExPrvr2FsQLKyQAAIABJREFU\nhcV/vY04ZMiQ5ubmHoeam5uFhIT+09E4TEZGpr29va6urvvQx48fZWRk/m3HmTNn1tbWbt26\nlVVpaWlxcnKaO3cuPz+/r6+vlpbW1atX9fX1b9++3Setf5/29vaCggIqlcrtRgAQ7AAGvocP\nHxoYGFy5csXIyGjOnDmysrIbNmwYM2ZMRUXFNx/z5cuX6urqPV4dsbS0fPny5Xf0O/B0dnZu\n2bJFVlZWXV191KhRoqKiWlpa+/fvZyaYz9xGpNFoXZLxF1lYWDx8+LCxsbFLvamp6eHDh+bm\n5t92CpxhYmIiKyt79uzZLnUGg3Hu3LmJEyf+245ycnInT57cvHmzu7t7VFRUcnKyo6NjcnKy\ngIDA7du3N27cuGfPnszMzIULF06fPv39+/d9fB7/QXx8/JgxY0RFRYcPHy4qKmplZYW194DL\nGPAlR44cIQiisbGR240A9KCmpkZGRmbhwoWdnZ3sxbFjx06YMOGbDxsZGampqdnj0JYtWywt\nLb/5yAMOnU6fPn26rKzstm3bRo8eTSaThw0bJi0tTSKRhIWFjxw5cv/+fQEBgaqqqu77WlhY\nBAcH/6fpWltb1dXVf/zxRyqVyip2dHT4+/urqam1tLR87/n0sQMHDoiIiMTExLAqbW1tixYt\nEhMTKyoq+vy+mZmZ3t7eKioqJBKJIIhJkybl5+ezb0Cn083MzFatWsX8kUaj0en03j6D/+DY\nsWNkMnnRokX//PNPSUnJgwcP5s+fTyaTz549y8WuOKO5ufmff/45duzY9evX379/z+12OK29\nvZ0giJSUFG430gMEuy9DsIP+bNeuXRoaGuwhgOnNmzckEiktLe3bDvvkyRM+Pr7S0tLuQy4u\nLj///PO3HXYgunz5spCQUFpamra2tp2dHSud+Pv7KysrCwgIREZG6unpMb9/yr7jsWPHBAUF\n37x5819nfP78uby8vIGBwaZNm06dOrVp0yZDQ0M5Oblnz571yhn1td9++42Pj2/kyJH+/v7T\npk1TUFBQUFBISkr6+iNcuXJFQkKix9AWFhY2duzYffv2mZubCwsLi4qKjhkz5vDhwzQarffO\n4KuUlpYKCwsfPny4S/2PP/4QFxevrKzkcD+cdPLkSRkZGX5+fm1tbQkJCT4+vpkzZ9bV1XG7\nL85BsBvYEOw+49mzZ4cPH163bt3Ro0dfv37N7XYGI09Pz4ULF/Y4pK+vf+DAgW87LJ1OHzly\npLe3d5f/XsbGxvLx8T1+/PjbDjsQubm5zZ8/f9u2bWpqak1NTax6SUkJiURasWKFnJxcWlqa\ntLT0uHHjIiMjU1JSLl++PGvWLDKZHBER8W2TVlRUrFu3ztbWVkVFxdbWNjg4+OPHj710QpyQ\nl5e3c+fOOXPmLFu27Pjx458+ffpPu586dUpVVbXHob1794qKisrKym7cuDEuLi42NjYkJERS\nUtLNza37rzd9as+ePcOHD++ePjs7O4cNG3bkyBFONsNJJ06cEBAQ+OOPP5qbm5mVlJQUPT09\nKyurLr/b8LD+HOzwVix8o/r6+lmzZsXGxurq6qqqql68eHHBggXz588/ePCggIAAt7sbRJqb\nm8XFxXscEhcX/7fH8L+IRCKdPn3azs7Ozs5u0aJF+vr6FRUVt2/fPnDgQEhICPODnoNEfn6+\no6Pj2bNnZ82axf49iWHDhsnJyRkbG9fW1ra1tWVkZGzatGnz5s3v3r2TkZGxsLBITEy0sbH5\ntknl5eXZ3yQYcHR1dVevXv3NuzNfoW1sbOz+Ssr58+c7Ozt/+eWXjIyMq1evKikpmZubx8TE\neHh47N+/f9WqVd/X+H/w6tUrc3Nz5l1jdmQy2czMjFfX3mttbV25cuWOHTtWrFjBKlpaWiYk\nJOjr60dFRf30009cbA8ILHcC34bBYHh6elZWVmZlZRkYGDCLSUlJvr6+DAYjIiKCu+0NKmpq\naj3+J4RGo+Xn56upqX3zkY2NjZ8/fx4SErJ48eLq6moKhWJiYnLhwgVPT8/v6HfgERQUpFKp\n5eXl6urqXYaoVKqkpKSMjEx5ebm1tXVkZCRBEO3t7RQKhQuN8hBLS0spKakDBw78+uuv7PUP\nHz6kp6dTKJTQ0FAGgzFkyJCGhobXr18fOnRoxowZR44c4WSw692XZgaKpKSk1tbWwMDALnVl\nZWUfH59r164h2HEdgh18i9jY2MePH7969Yo9N9ja2l66dMnW1vaXX37R1dXlYnuDyvTp06dO\nnZqTk8P+IU6CII4dO9be3j5lypTvObi6unpUVBRBELW1teLi4oNznVhTU9N79+5JSUlVVVWx\n1589e1ZfX29gYFBfXy8lJcWqI9V9P0FBwf379/v5+REEsWTJEnFxcQaDkZqa+tNPP9Hp9M7O\nzl9//dXKyurTp09JSUkRERGGhobnzp1rbGxsamoSFRXlTJPGxsbbtm3rvn5ye3v748ePuy8x\nzRtKSkqGDRvW47I7Ojo66enpnG8JuuDNXymgr8XFxU2ePLn71SBra2sdHZ3+udBUbykqKlq9\nerWDg4OxsfGMGTOOHz/O3Y+oTpo0yd3dffLkydeuXWMuo9XQ0PDHH38sXbp0586dvfXpdGlp\n6cGZ6giCCAoKio2NVVZWvnTpEoPBYBYbGxsXLVo0derU58+fk8nkQXJvurKyctWqVWZmZpKS\nkoaGhgEBAX13w3HGjBlnz549dOiQlJSUurq6hITE+PHjmY8WnPt/7J1nXBPrE+93Nw0SeiCE\n3pTeRLpSRBQUqaKIioKABQWPFbEcrIhiQUA8FuwFxC42ULECKogVRAUEBKT3GpLcF/u/ublJ\nVIQUwP2+OB+YJ9mZ5GAy+zwzvzl/fvPmzZMmTZo+fXpcXFxGRsaHDx/gVOP+/fvp6elVVVU8\nioqZmTNntrW1bd++ncW+ceNGEAQ9PT35EAP/ERUVbW5u5rjU2NjIUc0Rgc/8pZ/UCIOkpqZG\nWVmZ45KysvJg5NOGONevX58zZ46+vv6kSZNIJNKHDx9WrVqVlJR0+/ZtcXFxQUV15syZDRs2\nzJo1i0qlysjIVFdXk0ik//77LyAgQFAhjSTMzc1jYmLWrl0LQZCjo2NoaGhhYeHRo0exWOy/\n//47f/78lStX/g3fZx8/fnR0dJSRkfHz89PS0vr+/fuVK1dMTExSUlJcXV154XHmzJlubm7v\n3r0rLCyUlpZWUVExMjICQZDlVsrW1tbLywsetubr6wuCYFdX18SJEw8fPqyhocGLwGCIROKp\nU6dmzJjx5s2bWbNmqaiolJaWnj17NjMz8/r16z+rfB3ujBs3rr6+/unTpyz1ozQa7caNG+7u\n7oIKDOH/IdDWjeEB0hXLTnBw8IwZMzguGRoa7tmzh8/x8IeSkhJhYeGtW7cy98FVVVXp6urO\nmjVLgIHBNDc3P378+MKFC7m5ud3d3YIOZ6Tx+PFjGxsbFAoFgqCUlJS5ufn48eMhCAoKCvob\nOgEpFIqenp6XlxdL52lkZKSoqGh1dTUfYnjy5AkIgjIyMrq6ui0tLbDx4cOHoaGhcMOWuLh4\nZ2dnX1/f69evJ0+eTCaT+aCvlp+f7+XlRSaTAQCQl5efOXPmhw8feO1UsPj5+Y0ePZpZlbCv\nr2/58uXi4uJVVVWCi4uvDOWuWCSx+z1IYsdOSkqKmJgYuyLr27dvQRB8/fq1QKLiNStXrjQ3\nN2e3P3/+HATBsrIy/oeEwGeam5sTExMXLlw4ffr0jRs3ZmdnCzoiPpGeno7FYtn/yVOpVE1N\nzejoaD7E8PDhQwiCREVFtbW19fT0Tp8+PWnSJBQKBeuoAQCAxWK1tbVh3aXe3l4rKys/P79B\nOq2trX3//n1PT89vH/n33E21t7c7Ojri8XgfH5+tW7cuXbpUS0tLSkrq4cOHgg6NfwzlxA6p\nsUMYCF5eXurq6p6ensynrkVFRTNmzPDy8vqjkefDiJycHI5HTtbW1lJSUi9evOB/SAh8Rlxc\nfMmSJYcPH7506RKslCvoiPjE69ev4XFhLHYIghwcHF6/fs2HGLS0tOh0OgAA8+fPt7GxCQwM\nzMjIoFKpra2tCgoKEASdPn1aQ0NjypQpXV1dGAxmzZo1V65cGVgJLI1GO3DggKKiIolEMjAw\nIBAIjo6O79+//8VT/p6mGQKBcO/evVOnTomJiWVkZNTU1MybN6+wsHDChAmCDg0BAJDmCYSB\ngUaj09LSuru71dXVJ0+eHBgYaGdnp6+vP3r06JMnTwo6Ol7R0dHxs1IqUVHRASvGISAMfXp7\ne4WEhDgu4XA4uGuH18jLyzs6OiorK//77794PL6vr+/q1auwVnZlZSXczJScnNzZ2Xnq1CkA\nAHR1dTs6Olh6mftJUFBQZGTk6tWrP378WFNTk5GRISoqamlpmZOTw+2XNSyBIMjb2/vIkSNP\nnjxJTU1dv349iUQSdFAI/wNpnkAYIAoKCi9evEhLS8vJyfn+/buDg8PmzZtH9h2bqqoqxx7A\n1tbWyspKdpGzkcHnz5/z8/Nramp0dHQsLCxGakk4O3Q6/eLFi9euXSsoKBATEzM0NFy8eLGB\ngYGg4xIMo0aNOnDgAIVCYZcff/Pmjbm5OX/COHjw4Lhx40aNGgXPdQgKCmpqagIAQFZW9tmz\nZwAAiIiITJs2LTMzc/Hixe3t7QAA4PH4P/Vy586ds2fPZmVlmZqawhYSiWRvb79gwYIFCxZ8\n+PBhpGrUIYwMkL9OhIEDQZCbm1tUVNTp06cjIyNHdlYHAIC3t/e5c+fKy8tZ7Hv37pWWlh43\nbpxAouId9fX1Hh4eWlpay5cvP3bsmJubm7Ky8tGjRwUdFz/o6elxd3cPDAwUFhZesGCBs7Pz\n58+fTUxM4Irbv5CpU6fSaLT9+/ez2NPT058+ferr68ufMEaPHv3q1StdXV14j7ChoUFcXFxa\nWjooKIgxFERWVraxsREAgFu3buno6AygXf306dMzZsxgZHUMoqKiioqKXr16NejXgYDASwRb\n4jcsQJonEGCoVKqDg4O6uvrdu3fhYuofP35ERESg0egrV64IOjou09vbO3bsWGNj4zdv3sCW\nnp6e+Ph4LBZ77NgxwcbGB1atWqWoqPj582dm44kTJ1Ao1N/TMMHC+fPnUSjU8uXL379/393d\n/fXr15iYGAKBEB4ezv9gkpKSZGRkKisr4Z8JBMKTJ0/gpTlz5vj5+T19+pRAIBw9enQAFzcx\nMdm3bx/HJWVl5VOnTg04bIQRw1BunkASu9+DJHYIDNrb2xctWoTBYDAYDFxIrqKicv36dUHH\nxX0OHz5MJBLZuyBjY2MlJSU7OzsFEhV/aG9vx+PxKSkp7EvTp0//mdAPdwM4c+bMmjVrFi9e\nHB8fz6wrIVju3LnDPOBEXl7+v//+Y1b/4QovX74MDg42Nzc3MDDw8fG5ePEiu4uqqioMBnPt\n2jU6nU6j0ZYvX47BYHx8fCIjI3E4nJWVFQaDCQ0NHVhs5ubmu3bt4rgkJyd3/vz5AVwTYYSB\nJHbDGySxQ2ChsbHx0aNHly5dev/+PYVCEXQ4PGHq1KmhoaHs9o6ODiEhoXv37vE/JL6RlZUF\ngmBHRwf70okTJ5SUlHjq/cmTJ3JyctLS0lOnTvXx8dHU1MRgMD/LMwRCfX19VlYWjyTi9uzZ\ng0KhXFxcoqOj4+Li/P398Xg8u34enU5fv369hIQE47YqIyPD3d1dWFiYQCDMnTs3PT19wDEs\nXLjQ2dmZ3V5YWAgAQEFBwYCvjDBiQBK74Q2S2CH8hRgZGcXGxnJcUldXT0pK4nM8/OT+/fsY\nDIbjZs/ly5eJRCLvXBcXF4uKioaEhHR1dTGMycnJOBxuZL/nMPfv30ehUPDoNgaFhYVkMnnj\nxo0sD6ZSqevWrcNgMHJycnZ2dqNGjYIgyMXFpb6+Hn5AT0/PwPRy8/LyIAhKTk5mNnZ1dU2Y\nMMHe3n4AF0QYeQzlxA5pnkBAQOCAuLg4XIHOAp1Ob2pqEuD8ND6gqqpKoVC+fv3KvlRQUMDT\n9ufo6GgjI6OEhARmbRFYBnbTpk00Go13rhlUVFTAh7988MXCvn375s6dO2PGDGajtrb2rl27\n4uPjWURVIAjauXNncXHx3r177e3t165dm5eXl5aWRiQSk5OTx4wZQyAQ5OXlJSQkZsyYUVxc\n3P8wTExMYmJi5syZ4+/vf+HChYyMjNjYWBMTk5KSkhEs54QwchBwYjkcQHbsEP5CNm7cqK+v\nzz4sKyMjA4VC8WeElAAxMTHx9/dnMTY2NiooKOzcuZN3flVVVQ8fPsxuh6fav3v3jneu29vb\nV6xYISkpCX81iIiIBAcHNzQ08M4jO1JSUizbdTCwFh2jj+fXrFu3DofDRUREXLt2LS4ubt68\neXp6eqKion86ESczM3PatGny8vJYLNbAwGD16tV8fjcQhjJDeccO0bFDQEDgwNKlSxMSEsLC\nwg4cOIBG/++DoqioKCgoKCgoCJ6MOYJJSEhwcHBAo9EbNmxQVVXt6+vLzs4ODQ2VlpYOCwvr\n/3V6e3uTkpLu379fWFgoKys7ZsyY0NBQNTW1nz2+oaFBTk6O3U4mkyEIamhoGMiL6QcdHR32\n9vaNjY0HDhywtrZGoVCvXr3atm2blZXV8+fP2QdOcJfOzs67d+9++PChtbX1zZs3zs7OLErg\n8K+dnZ2/vVRWVtbu3bvv3Lnz7NkzHx8fPB4/evTopqamtrY2BweHb9++9X+z2d7e3t7e/s9f\nDQKCoBF0ZjkMQHbsEP5Onjx5IiMjo6amFhQUtG7dOjc3NywW6+7uzlz+NYJ5/vy5np4eAAAS\nEhJYLBaCIF9fX0b9Vn9oaGgwNTWVlpZetmzZwYMHIyMjLS0tCQTCL9qoNTQ0EhMT2e0VFRUA\nAHz8+HEgr6QfbNy4UUVFhaUJuq2tzcDAIDg4mEdOYdLT02VkZOBOc/hbCYPB7Nixg/kxr1+/\nBkGwPwVzgYGBrq6uEREREhISly5dYhRKpqWlAQBgYWHB9R7eYU1jY+P+/ftnz549ceLEJUuW\nXLlyhUqlCjqo4cFQ3rFDErvfgyR2CH8tDQ0NcNmTk5NTWFjYrVu3/qrvRRqN9uXLl+vXrz94\n8KC2tvZPn+7h4WFsbMz8RBqNtmXLFjwe/+3bN45PWbp0qbm5OfuX65YtW5SVlXn35ispKSUk\nJLDbL126JCIiAqs28oL8/Hw4aQYAAIIg+AcUCgUAwKpVq+DH0Gg0b29vGxub/lzQysoqPDwc\ng8HcuHGDZUlJSQmDwdy8eZPLr2HQfP/+vaioiP/99dnZ2WQyWVVVNTg4eNOmTd7e3sLCwo6O\njsiXXX9AErvhDZLYISAg/ClfvnwBACA3N5fFTqPRxo4du3btWo7PKi8vl5KS8vPza2lpgS1U\nKvXo0aMYDObChQs8ChUec/zixQv2pbKyMgAASkpKeOSaMYsMzupQKBQWiwVBEAAAEAQ/ffr0\n6dOn2bNni4iI5Ofn9+eC1tbWHh4eysrK7EtqamomJiaLFi3i9osYIN3d3Zs2bSISifA7gMPh\nZsyYwSMRGXbq6+vhiR3MOjKlpaWampqzZ8/mTwzDmqGc2CFdsQgICAjc58WLF3JycmPHjmU2\nNjU1paWlEQiEmzdvwpkfC0pKSvfu3Xv+/LmioqKNjc2UKVOUlJTgSsdZs2bxKFQUCgWCYF9f\nH/sShUIB/u8WGte5ffv2y5cvAQAICgqiUqmdnZ1paWkKCgpwAwedTjc0NNTW1i4qKnr8+LGx\nsXF/rqmvr//x40d1dXUW+/fv38vKynR0dCorKxnGmpqaiIgIe3t7FRUVBweHjRs31tfXc+/1\n/Yq+vj5XV9ekpKTo6OjPnz9XVlZeuXKlurrazMyspKSEDwEcOXJEQkIiMTGRefivqqrqqVOn\nLly4wJ8YEHgE0jyBgICAwH06OztFRESYLUFBQSdOnGBIlmhqak6cODE1NZXRiApjampaWFh4\n9+7dd+/etbW1+fr6Ojk5ycrK8i5UHA6nra396NEja2trlqXHjx9LS0srKChw3SmNRgsJCQEA\nAI1GwwOIcTics7Pz06dP9fX1Z82alZycLCcnl5mZ+YteE3aCgoKOHj3KIoxCpVKXL19uZGSE\nQqEkJCRgY25u7tSpU8lksre3t6qqaklJycWLF5OSku7du2doaMi9F8qZI0eO5OXlvX79WkVF\nBbbIy8tPnjzZyclp2bJlt2/f5nUAT548cXd3Z87qYCwtLeXl5Z89e8aeHCMMGwS9ZTgMQI5i\nERAQ/pT09HQhISHG54a7uzsAAJMnT3706NGMGTNsbW2dnJxAENTV1WXXlOE/Bw4ckJSULCws\nZDZWVFQoKipGRETwwmNOTg5cUSciIsKyFBYWZmFhAQAAxxPV3wLni3Pnzr17925eXt7Zs2et\nra2JRGJOTo6MjAw8Pbajo0NJSWn+/PnMlW09PT2zZs3S0NDo7u4ezEvrDxYWFuySy3Q6PTs7\nG4KgmpoaXgdgbW3N0qHCwMDAIC4ujtcBDHeG8lEsktj9HiSxQ0BA+FO6u7tlZWW3bNlCp9Ph\nA8eFCxfS6fSvX7/i8XhYrW3ZsmUgCB47dkzAsdLpFArFy8tLXFx8w4YNaWlpd+/e3bp1q4yM\njL29PY/mAicnJ8vKykIQBIJga2sr89Lhw4fhXcyxY8cO7OLm5uZ4PF5YWBgAADk5ufnz5xcU\nFLi6umpoaMAv5/Tp00Qisb29neWJLS0tYmJiHLX0uIuEhMTVq1fZ7b29vSAIPn36lNcBzJw5\nMyAggGMAYmJiV65c4XUAw52hnNghNXYICAgI3AeHwx08eHDbtm3r16/fsmULCoXas2fPjRs3\nHBwc7O3tvb29AQCIiYlBo9HHjx8XdLAAGo1OTU3dvXv3gwcPfH19vby8rl+/vm7duvT0dDg9\n4jp4PL6zs5NEItHpdGdnZyqVCttpNNrdu3ebmpoAAJg/f/7ALp6eng7v+U2dOtXX17e7u9vW\n1vbTp0+3bt2CX87Lly9tbW0JBALLE8XExKytrV+9ejXwF9Y/0Gj0z4oa6XQ6+wkp1/Hw8Lh0\n6RJzxSHMiRMn6HT6xIkTeR0AAu9AEjsEBAQEnjB9+vTLly9fuHABlomRlJScOXMm/IUKN34K\nCQkpKCh8//5d0JECAABAELRw4cLs7OyWlpa2trbc3NyVK1fyLsMwNzfv6Ohwc3MDQTArK0tU\nVNTGxsbFxUVJSenatWsAAGCxWPhQdQCIi4vfv3//woULWlpanz9/lpCQ2L1799u3b7W0tOAH\ndHd3s2d1MAQCoaura2B++4+xsXFmZia7/dGjRzgcTkdHh9cBzJw509jYeNKkSfB2MgAAFArl\n0KFDYWFhUVFRYmJivA4AgXcgzRMICAgIvMLNzc3FxcXExOTz588PHjzQ19dn+crs7e1l6bHg\nKTQarbS0tLi4WEVFRUNDgzFThBkQBOG8k6fIysrOnTv30aNHo0aNKi4u7uvrg0+1QBCE/3vu\n3LnBdONCEOTu7g6XNrKjrq5+8eJFjksfPnwYN27cgP32kyVLlsyePXvOnDnMDSuNjY1r1qyZ\nPXs2H/IqFAp18+bNJUuWWFpaSkpKysvLf/nyBYfD7d27d+nSpbz2jsBTkB07BAQEBB6CQqEc\nHR3henyWL+zGxsbq6mpLS0v+RHL+/HlVVdVRo0a5ublpa2vLycnBNfL88c5OQkKCrKxsbW0t\nPLQNAAA4qxMVFb1+/Tp8Ws0jpk+f/uHDhxs3brDYL168WFpa6unpyTvXMF5eXsHBwQ4ODsuX\nL798+XJ6enp0dLSRkREOh9u3bx+vvcOIi4ufP3++pKTkyJEjixcvTktLq6ioQLK6kYDAqvuG\nD0jzBAICwmAoKytDoVAyMjJfv35lGLu6ujQ1NVEoVHV1NR9iiI+Px2KxW7duLSsro9Pp1dXV\n8fHxIiIiP5NK5jodHR3sEywoFMqxY8e8vb01NTUNDAycnZ2vXbvGnxkM//77Lx6Pj42NhVtQ\nq6urY2JihISEoqKi+OAdJjU11cHBgUgkCgsLm5iYbN26lUetKghcZyg3TyCJ3e9BEjsEBIRB\ncvjwYRAEIQgyMzPz8/OzsbHB4XAgCCYlJfHBe3V1NR6PZ2+/vXfvHgRB7969453rjo6O9evX\na2hoQBCERqP19PT2798/FBReaDTawYMHZWRkAACAOypkZWVhMRQEhN8ylBM7pMYOAQEBgecs\nXLhQT0/vn3/+ef/+/atXrwgEgoGBwdGjR/s5UGGQ3Lhxg0gkLliwgMU+efJkCwuLixcvGhgY\n8MJvS0uLvb19c3PzqlWrzMzMenp6srKytm/f/uDBg6tXr3Ks8OMbIAiGhIQsXLjwy5cvpaWl\nGhoaPys6REAYXiB/xAgICAj8YNy4cbCORldXF480RH5GSUmJvr4+x5YIAwOD4uJiHvldv359\nV1dXXl6elJQUbLG1tfX29rawsDh48ODy5ct55Lf/oNFoHR0dPnShIiDwDaR5AgEBAYGv8Dmr\nAwBASEios7OT41JnZyeP4unp6Tl9+vS2bdsYWR3MqFGjVq5ceezYMV44RUBAQBI7BASEkQ+V\nSmUMaf0LMTMze/nyZUNDA4u9p6cnMzPTzMyMF06/ffvW3t4+fvx49qVx48YVFhYyRImHDt3d\n3TU1NYKOAgFhUCCJHQICwoiFQqHExMSYmJgQCARRUVFzc/NDhw79hRne5MmTVVVVg4OD4Ypv\nGBqNtnLlSgqF4uvryzvXHM9/YVkTuuCUVlig0+mHDx/W1dUVEREhk8nS0tL+/v7V1dWCjgsB\nYSAgNXYICAgjk66uLmdn56KiorCwMDMzMyqVmp2dvX79+nv37l26dOmvKpPHYDCXLl2aNGmS\nkZGRr6+vhoZGRUXF5cuXi4uLb9y4IS4uzgunKioqBAIhOzubXRYuJydHS0tr6PwvCAwMTE1N\nDQ8Pd3BwkJCQePfu3f79+01MTJ49e6ahoSHo6BAQ/hA6nf7w4cP2EXD1AAAgAElEQVSwsDBB\n9uYObRC5EwSE4UhERISSklJlZSWzsaioSEpKav/+/YKKSoDU19dv3LjRzs5OQUHByspq5cqV\nFRUVPPUYHBysp6fX0tLCbCwrK5ORkYmJieGp6/5z5coVHA6Xm5vLbOzt7XV0dJw4caKgokIY\n4gxluROQTqfHx8cfPXr03bt3gk4yhyiHDx9evHhxW1sbPyf/ICAgDAYqlUomk3ft2sWu8REd\nHX3y5MlPnz4JJLC/isbGRhsbm76+vnXr1pmYmFAolKysrKioKAMDg1u3bmGxWEEHCAAAMG3a\nNHl5+SNHjrDY3759a2xsXFpaqqqqKoi4EIY0vb29OBzu+fPnzEPhhgisO+F0Ol1PT+/Hjx/9\nfD4Oh8vOzkb+7hEQEIYUVVVV9fX1dnZ27Et2dnbr16/v7u4WEhLif2B/FVJSUtnZ2ZGRkRs2\nbIBL1tTU1EJDQ9euXYvBYAQd3f8oKCiYPn06i7G5ubmlpQWHw928eXPRokX9z0Grq6uzs7NL\nS0uVlZXNzc1VVFS4HS8Cwm9gTexAEExMTKyrq+vn83E4nJKSErejQkBAGJZQKJRTp06lp6cX\nFhaSSCQTE5OQkBA1NTX+RwJ3XHKs4kKhUHQ6/S9soRAIYmJi+/fv379/f2NjIwaDERUVFXRE\nrMCdHIxfu7u7169fn5iYSKVSqVRqWFhYVFRUTEzM3Llzf32dvr6+iIiIAwcOiIiIaGhofPv2\nrbGxMSgo6MCBA8gtBAI/4fCpZ29vz26kUqkoFAr+ube3Nz8/H4vFGhsbc+x4QkBA+Atpbm6e\nOnXqp0+fZs6cuWjRotra2vT09EOHDp07d87d3Z3PwcjLy4uKir569Yp9y+TVq1fKysp4PJ7P\nIf3lsKjZDR309fWfPXvGOLKfPXv2y5cvU1JSZGVlra2t379/n5aWtmDBgu7u7qCgoF9cZ8WK\nFcnJyZcvX3Z1dYUtjx49mjdvXnNzc0pKCs9fBgICAzqdHhcXZ2Bg8LMqvL6+vpCQEG9vb/jX\n0tJSdXV1+Lnjx4//G1oKkOYJBIT+MHPmTH19feaR9jQabcuWLcLCwqWlpfyPZ9GiRfr6+q2t\nrczG2tpaZWXlTZs28T8ehKHJzZs3sVhsVlYWnU6/desWDocrKCjo7u62tbV1dnaGHxMfHy8u\nLt7c3PyzixQWFkIQlJmZyWJ/+/YtGo1++vQpz8JHEAxDuXni9zp2MTExiYmJysrK8K9Lly4t\nLS1dsmRJSEhIVlbWrl27eJZzIiAgDBvKyspSU1OPHj1KJpMZRhAEN23aZGBgkJCQwP+QduzY\n0dfXZ2VllZycXFxc/Pnz55MnT1pYWJDJ5PDwcP7HgzA0mTZtWlBQ0MSJEzds2BAXF2djY5OT\nk2NhYVFaWnr48GH4MYsWLQIAICMj42cXSUtL09XVZT/vMjQ0tLGxuXnzJs/CR0Bg5fcyQufO\nnfPy8tq7dy8AAJWVlXfu3FmwYEFiYiIAAN3d3Tdv3ty2bRvPw0RAQBja5OTkSEtLW1pasthB\nEHRxcUlPT+eKl56eno8fPxYXF6uoqOjp6REIBMZSSUnJ27dvu7q6dHR0DA0NUSgUkUjMzs6O\niIhYvHhxS0sLAABEIjEgIGDLli3IOSwCMwcPHrS0tIyPj8/Ly6PRaJ8/f3Zxcdm6dau0tDT8\nAAwGM2rUqLKysp9doaqqinGWxYKGhkZlZSVP4kZA4MTvE7tv374tW7YM/vnevXt0Op0hUz52\n7NgrV67wMDoEBIRhQmdn58/q4sXExDo6Ogbv4uDBg5GRkQ0NDSQSqa6uTkREZO3atREREVVV\nVYGBgRkZGZKSksLCwlVVVaNHjz527Jitra2EhMShQ4cOHTpUXl6OwWDk5OQGHwbCiMTPz8/P\nz8/V1VVFRYXjBnNzc3NtbW1mZqaBgQEj4WMgLi7OPrENpr6+XkFBgfsRAwAAAEVFRfn5+TU1\nNTo6OhYWFjzSmkYYXvz+KJa5PeL+/fsEAsHGxgb+lU6nUygUXoWGgIAwfFBVVf3+/XtbWxv7\nUkFBweAVkaKiotasWRMZGdnc3FxTU9PW1paQkLBv374lS5bY29v39PS8e/eusbGxsrLyx48f\njo6OTk5O2dnZjKcrKysjWR3Cb7G2ts7IyGAZYltfX+/q6lpcXLxnzx4nJycZGRkHB4eioiLm\nx9jb2798+ZJ9S6+hoeHhw4ccZXcGSX19vYeHh7a29ooVK5KSktzd3ZWVlRlnxwh/NfTfNU/o\n6+vPnj2bTqf/+PFDRETE09OTsRQcHKylpcXzOkBBgzRPICD8lp6eHjk5ucjISBb7t2/fRERE\nzp07N5iLl5eXY7HYlJQUFvvjx49BEFRRUeno6GBZmj9/vrm5+WCcIvyF1NbWSkpKLl++nEql\nwpaWlhYtLS08Hm9qatrR0dHb25ubm+vi4kIkEouKip4+fbpt2zY/P7+IiAg9PT0zM7MfP34w\nrtbU1OTo6Kivr0+hULgbZ29v79ixY42Njd++fcuwJCQkYLHYI0eOcNcXAkeGcvPE7xO7qKgo\nAACsrKzk5eUBAHj06BFsP3XqFBaLXbNmDZ8iFRxIYocwZMnJyfH09FRSUkKj0dra2iEhIVVV\nVYIK5vLly2g0OiIiAv5u6+npuXXrlpqamqOjI+NrcmDEx8erq6tzXBIWFp40aRK7HR6lw+uR\nWX8bXV1deXl5169fLygo4HqyMkTIzMyUlJQ0NDQMDw8/cOCAiYkJCoUyMDCoqalhPKavr8/R\n0ZFMJqNQqHHjxgUEBEyePJlAIODxeAKBMH369DVr1sycOVNSUlJPT48XLeFHjhwhEol1dXUs\n9ri4OAkJCfb7HASuM5QTu98fxa5YscLf3//NmzcdHR1xcXGMLeV169ZpaWlFRETwai8RAQHh\nl5w8eXL8+PEYDCYqKuru3buhoaE5OTlGRkYfP34USDxeXl6XL18+f/48mUyWlpYmEAgeHh7O\nzs7Xrl2DoN9/1PyCsrIyHR0djku9vb19fX3sdi0tLQAAysvLB+MXgQGVSt2+fTuJRBo7duzc\nuXN1dXVVVFTOnj0r6Li4j729/YcPH9zd3d+8eZOUlFRUVDR9+vRXr16RSCQKhZKamhoeHh4Q\nEFBaWvrjx4+goCBnZ2c3N7erV6+WlpZaWFhISkqSSKSPHz9KSUnFxsbm5eXxYjLT9evXfX19\n2Uv9goKCenp6njx5wnWPCMMJ+u927H5Gdnb2SL1jYwHZsUMYghQXF+NwuIMHDzIbKRTK9OnT\nDQwM+vr6BBVYX1/fhw8fLl++/Pjx46amJq5cMzIy0tbWluMSDofjOKm9pqYGAIB3795xJQCE\nhQsXSklJnTx5EtZyKykpCQoKQqFQy5YtY1YuHGHAyvywOl1RUZGOjo6YmJizs/O4cePgL1AR\nEREzMzMxMTESiXT79u2mpiYikXjixAleB2ZsbLx//36OSxoaGseOHeN1AAhDeceOc1fs9+/f\nf5sRKioqwiNlFRUVuZVlIiAg9JOkpCR9ff2QkBBmIxqNPnjwoKKi4rNnz3hRr90fUCiUnp6e\nnp4eF69paWm5a9eu2tpaEonEbO/s7AQAgGPHxrVr16SkpH62z4fwR2RnZyclJT179gyWszl4\n8ODGjRvb29ulpKQOHjz433//BQYG7tu3b+SJyEAQhMViOzs7Ozs7nZ2ddXV1s7Kyzp49GxYW\nBj+go6MjNzd35syZcnJynp6eT548cXFxefDggb+/P08D+1kTLp1Ob2xsRHpj/3I4n48o/Ql8\njhgBAQEAgLdv306YMIHdLisrq6Oj8/btW/6HxDsmTZqkpaXl7+/PLJtCoVAWL14sLi6el5d3\n7Ngx5sfn5eVFRESsWrWK46xYrvD9+/dVq1ZZWVkpKCjY2NhERETU1tbyyJfAuXjxooODA5zV\nxcbGrl69eseOHW1tbT9+/CCRSCtXrrx7966Pj4+gw+QJZmZmd+/ePX78eHd3d0pKSk5OTlhY\nGJFIVFdXJxKJd+7cAUHwzZs3z5498/Dw2LBhA5lM/pnuCRextbW9evUqS/cuAAAPHjxobW0d\nP348rwNAGMpw/tQbqf9EERBGDH19fRgMhuMSFovlWHY2fEGhUJcvX548ebKurq63t7e6unp5\nefm1a9daWlru3LmTl5e3dOnSkydP2tjYEAiEvLy8W7duzZ07l3fjJbKysqZNm6ampjZjxgxl\nZeWSkpLk5OQTJ06kp6cbGhryyKkAKS0thbdgGxoaNmzYkJiYGBAQAC/p6OgICwunp6cbGRml\npaVNmzZNoJFyn3/++WfWrFmmpqaenp7CwsIhISEgCE6dOvXcuXMbNmxwcnIik8mhoaFbt261\ntLS8fPmypKSkrKwsr6NaunRpQkLCsmXL4uLiGJ8DRUVFQUFBgYGBzNNfEP5COCd2ycnJ/Xly\nR0cHx0MQBAQEXqOlpZWbm8tu7+joKCwshFsHRhIaGhpv3rz577//nj17du/ePSUlpblz5y5Z\nskRaWtrExMTGxubEiROvX7/u7u7W0dG5devWpEmTeBRJW1ubt7f3zJkzw8PDjx8/fv78+cbG\nRjMzs8+fP0+fPv3jx49YLJZHrgUFHo9vb28HAODevXt4PH7evHmMpfb2djwer6mpOW3atKtX\nr468xM7T03P16tU7d+5sa2tbsWLFt2/f6HR6cnIyjUaDtzDJZHJvb29AQEBmZmZfX9+dO3eS\nkpJ4HZWsrOzNmze9vLzu3Lnj6OgoLS1dUFBw7969KVOmHDhwgNfeEYY4gzqnuH79+urVq6uq\nqrgVDQICQj/x8/OzsLDIyMhgyWC2bNkiKSk5ceJEQQXGO0RFRdesWbNmzRr2JW1tbb7NrU5J\nSaHRaI6OjoaGhqNGjXJ0dJSSkvrw4cObN296enquXr068k48LCws9u/fT6FQKioqNDQ0UCgU\nbK+srHzz5s2ePXsAANDU1Hz16pVAw+QVO3bseP78+fv37+Pj4+l0OmwEQXD69OmXLl2qqKiQ\nlZWVlJQ8fvw4AAC6urrTp0/nQ1Tjxo379OnTqVOnXr9+/e7dO01NzWvXrjk7OzPPFED4O+lX\nYldfX5+cnPzt2zfm853u7u60tDT4Ng4BAYHPmJqarlmzxt3dfcOGDdOmTZOXly8qKjp8+HBK\nSsrNmzeFhIQEHSD/oNFoJ0+evHjxYkFBARaLNTQ0DAoKmjp1Ko/c5ebmmpqa+vn5rVu37t9/\n/2V8j5aUlOjr60dHR4+8xG7evHnbt29fuXKltrZ2c3MzbOzo6AgICBgzZgw8i6i5uflnM+V4\nzbdv3yAIUlZW5p0LAoHQ1NQUFhb233//WVhYjB492tPTc9asWS4uLiAIHjt27NOnT3V1dRIS\nErdu3WIkvrxGUlLyn3/+4Y8vhGFEv2bFmpub19XVcXgyGr1p0yYeRIWAgPB7oqOjtbS0duzY\nsXHjRgAAUCiUlZXV06dPLSwsBBJPTU3N27dvq6urtbS0jIyMhIWF+eC0t7fX09Pz+fPn/v7+\nc+fO7e7uzsrK8vDwWLp06f79+3nhsbu7u6SkxMTEJDIyktmurq5ubGyck5NTV1cnIyPDC9eC\nQkxM7MCBA4sXL4bvH7Zu3drR0ZGcnIzBYO7fvw9BUG9v761btxi9ovyhubk5IiLi3LlzcEWQ\nhITE/Pnzt23bxvX8srS0ND09XU1N7dmzZ1QqdcqUKZs2bdLX14+KigoLC7OysrK0tPz48SME\nQRcvXmTXlkNA4Df03+nYzZkzR1RUNCEh4cGDBwAAHDt27O7du+vWrVNQULh79y6/ZFkECaJj\nN0R4+vTp7t27Q0ND9+/fn5ubK+hwhhCNjY3v37/v6uoSVADt7e0LFy5Eo9HCwsLKysoQBElL\nSx8/fpwPrjds2CAnJ/f161dm4+PHj4WEhJKTk3nhcevWrXg8fteuXSx2Go2mpqaGxWJv3rzJ\nC7+/pr6+PiMjIykp6eHDhy0tLdy6bHt7+z///EMgEODvCxAEsVgsFou1t7ePjo5ubW2l0+m9\nvb0LFiyQlZXllmxhf2hoaNDR0dHT00tJSSkpKfn69evZs2dHjx49ZswYOCouEhcXN3r06Orq\nant7e/gd0NLSAkEQBEECgaClpUUkEgEA2LFjB3f9IgxlhrKO3e8TO2Vl5XXr1tHp9K6uLgAA\nsrOzYXt+fr6UlNSzZ8/4E6gAQRI7gdPQ0DB58mQ0Gm1qaurl5WVsbAyC4MyZM5HJOUMBGo3m\n5OSkpqaWkZEBCyO3tbXt2bMHg8Hwemxlb2+vlJQUSwbZ3d1NpVJXrlxpbW3NC6eFhYUAACxd\nupTFfvLkSSEhIRKJdP78eV74/Rm9vb1r167F4XA4HE5DQwODwYiIiERFRdFotEFeubu729ra\nWk1NLTk5ubKysqmp6eHDhzY2NhgMRlRUFD6fDQkJ0dDQkJWVffHiBVdeTj9ZunSprq4uSwrb\n0NCgrq4eHh7OXV9r166dMmUK/HNmZqaOjg4GgzE3N3dycpKWlhYSEsJgMP/99x/8gLq6ukEO\n0GOmra3txYsXd+/eLS8v59Y1EbjC8E7sGJ/O8Mt4/PgxY2nTpk0cNd9HGEhiJ1hoNJqdnZ2h\noeGXL18Yxvz8fDU1NR8fHwEGhgBz6dIlPB5fXFzMYo+PjxcXF+f69gkzRUVFAAB8//6dTqe3\ntLSsXbt29OjRKBQK3kdBo9GDT244oq6ujkaj9+3bB7v+9u3btm3bsFjsjh07UCgUnz/rFyxY\nQCKRrl69Co8C6unpOXXqlJiY2Pr16wd55ZiYGDKZzDJYgkKhTJw40cjIyN/f39raesaMGbt2\n7WpoaBikrz+CQqGIi4tzTKCPHDlCJpO55aisrOz8+fMODg7q6upv3ryBjTQaLTk52c/Pz9TU\nlEwmGxoafv36dffu3dLS0nDBJQRBqqqqaWlpg3Hd2tq6cOFCDAYDQRBcMjtmzBg+Z88Iv2B4\nJ3ZSUlLbtm2DfxYREWEelnLhwgVxcXEeRyh4kMROsNy6dUtISKisrIzFnp+fD0FQXl6eQKJC\nYDB79uy5c+ey23t6esTExK5evco71+/evQMAoKGhoaamRktLa/To0fHx8U+ePLlz587s2bMB\nAAgODuaF38TERBEREbiQDlYRU1RUPHPmzKZNmxQUFPg5a/HFixcoFIr9+/7mzZtoNJo92/4j\njIyMtm/fzm5//vw5BEHsE+j5RkVFBQAAzHd6DPLz8wEAgOeeDQYqlbp27Vo0Gi0nJwcfEUAQ\n5OrqypzCtrS0EInEkydPwiIvqqqqa9asOXz4sL+/P4FAAEFw9+7dA/Pe09NjZWU1evToW7du\ntbe3U6nUwsLC+fPnCwsLMw7NEATL8E7spkyZoqCgAA/Ls7KyMjU1ZaQ4wcHBJBKJL3EKEiSx\nEyzLly+fOnUqxyUTE5OdO3fyOR4EFmxsbBj3fiwYGRkdOHCAd65bWlowGMzDhw99fHzGjh3L\n/I80Li5OUVFRSEgoNTWV6357enrMzc3hAq/09PTi4uLGxsZ///0XjUZfuXKF6+5+QXh4uJ2d\nHcclTU3N2NjYwVxcSEho2rRpFhYWGhoaU6dOjYuL6+7uptPp8CS3nJycwVx8MFRXVwMAUFhY\nyL708uVLrnxch4eHS0pK3rhxg06n02i08ePHGxkZ6ejojB8/Hj5pbW9vd3d3HzVq1JEjR0AQ\n9PLyYt4erqurI5PJEAQVFRUNwHt8fLyMjAz7EF5/f38jI6NBvCwErjGUEzvOI8WY2bBhQ0ND\nw+rVq+Hb39zcXF1dXS8vrzFjxhw9epR3KqAICDB1dXU/m0esqKjIsV8bgZ+IiIgwJDBYaG5u\nFhER4Z1rMTExFxeXTZs2Xb58OSYmhuGrqalp//79/v7+CxYsOHLkCNf9YrHYu3fvGhgY+Pr6\nenl52dnZEYnEpKSkixcvjh8/fvv27e7u7mZmZr6+vkePHoW/AHhERUWFpqYmxyUtLS14Z2tg\npKSkdHd3f/v2zcPDY/369dra2tu3b7eysmpoaIBfkQB1mEkkkpyc3KNHj9iXHj9+rKGhMci/\nuu/fv+/bt+/06dOurq4AAIAgmJqaCkFQZWVlTk7OrFmzAgMDR48e/f79+5s3b8bGxqJQqBMn\nTjALyElLSycmJgIAwDLsrp8kJycHBwezD5DYtGnT27dvP336NIgXhzDy+X1iN27cuGfPngUG\nBgIA4O/vHxERUV9ff/Xq1bdv37q5ucXGxvI+SIS/Gmlp6Z+JYFdWVo4wXYnhyLhx49LS0tjH\nVubn55eVlY0bN46n3vfu3VtQUEClUkEQ7OzsbG5uvn37tq2traio6Nq1a21sbODjWq4jKSl5\n4cKF8vLylJSUqKioly9flpSUyMnJ6enpnT17VkNDY9asWaKiouvXr7e0tKypqeFFDAAAiIqK\n/iyrbmpqGrDwx5cvX+bNm6esrDx+/Ph169YtWLAAfp8BAAgKCnrw4AEejxfgdBMIghYuXLht\n27by8nJm+5cvX3bt2rV48eJBXj89PV1WVtbFxYVhIZPJOTk58fHxKioqT58+pVAoGzdufPfu\nnba29tevX9XV1cXExFguYm9vT6PRBibazJjhxoK6ujoejy8tLR3ANRH+Iui/O4plp6urq7S0\ntLOzk2f7iEML5ChWsKSlpQkLC7M3hb19+xaCIET3RODU1tZKSkouW7YMbomFqaqqMjQ09PDw\n4EMAFy5cAP8vAABgMJiAgIDGxkY6nX7x4kUZGRk+xECn05uamkgkUnBwMHONXX19vYWFhYOD\nA4+cnjlzRkpKil3fpLKyEovFZmRkDOCa169fZ75f0tHRefjwIbwEpynKysrLli0bbOiDo7u7\nGx6ltXnz5jt37ty6dWvjxo0SEhJubm69vb2DvPiOHTvGjRvHcWndunVOTk7MFjQaraWlxf5I\nWF3P1tZ2AAFoaGgcPXqU3d7b24tCoeDKKATBMpSPYgeS2P1tIImdYKHRaDY2NmPGjGGuBH/3\n7p2Ghoa3t/dvn56Wlubi4qKkpCQuLm5tbR0TEwPXCSFwkcePHxOJRB0dnX/++Sc6Otrf319c\nXNzKygrOrnhNdXU1BEEPHz7Mycl5/fo1s57fqlWrBvbNOgD27dunoqLS09PDYv/8+TMIgq9e\nveKF066uLg0NDU9PT+Y77aamJhsbm9GjR2/btg2W8K2vr+/nBePj49FotLy8/KJFi6qrq318\nfCAIAkEwJCTk8uXLmzZtgiBIS0uLF5+HlZWVkZGRcFWfh4fH8ePHmW8V2KFQKLGxsWZmZng8\nXkRExMLCIjExkStSI4mJiaNHj+a4FBAQ4Ovry2xRV1fHYDAs3d+1tbUzZ84EAACLxero6Myf\nP//Dhw/9D8DX19fT05PdfuvWLQwGwzu9wKampoSEhKCgIE9Pz/Xr1/8NcmYDZngndhN/iY2N\nDR+jFQxIYidw6urqHBwcMBiMpaUlXCYPQZCXl1d7e/uvn7h27VoMBhMcHHzmzJmrV69GRkaS\nyWQLCwsuKrgiwNTU1Gzbts3Dw8PS0tLPz+/UqVP8bA51cXGxt7dnSao+ffokKirK3MjPU7y9\nvRcvXsxxSU9Pr59NJDQaraCgIDU1NS0tjb0TnCMfP35UUVFRUlJavHhxVFRUYGCghIQErGY3\nfvz4SZMmycrKioiInDx58reXKi0txeFwJ06cGDNmzP79+2HjjRs3tLW1IQiSkJCwsbEhEonH\njh3rT2B/xL1798TFxdXV1WVlZSHofzVCBALhwoULv30ulUrlrq5NYWEhx1y8tbWVRCKxqDPu\n3r0bhULNmzeP+elkMhmHw4EgmJiYmJiY6OTkhMPhLl++3M8AcnJyIAg6c+YMs/H79+8aGhoL\nFy4c0Gv6PU+ePCGRSEpKSnPmzAkLC5swYQIEQQEBAfz8hzyMGN6J3S+OcUVFReXl5fkYrWBA\nErshQmZm5s6dO0NCQnbv3t0fPacbN25gMJgHDx4wG2FdDB6pYCAIitLSUnl5eXNz89TU1K9f\nv75+/Xr//v1EItHT05OLarG/ZsqUKT+Txh03blx/xhK8ePHCwMAAAABpaWm4PM7Z2bk/yrSt\nra2xsbE+Pj5WVlbu7u7CwsL+/v6tra1dXV1xcXEeHh5kMhkeWl9RUfGL6+zcuVNPT49Op3t5\neQUGBjLsfX19cnJyx44da2pqwmAwjx49+m1If8T3799FREQYA+ylpKQ0NDRQKBS8WTjI3t6B\n4evrq6Gh8enTJ4alqalpypQpo0aNYhnx0tPTA+uhGBoaJiYm3r9/X1ZWFofDAQAQGRnJeNj2\n7dsJBAIsfNgfEhIS0Gj0tGnTYmJijh07FhoaKikpaWdn99u72YHx/ft3cXHxkJAQ5oPsV69e\nycjIwBMKEFgY3okdhY2Ojo4PHz6sXr3a1tb2b9j5QBK7YYqTkxPHBO7GjRs4HI6nwrkI/Keq\nqsrPz09cXBy+7VRVVY2Jifn1WR53WbRokbu7O7udSqXKyMiw7L6w8/r1awKBMH/+fHijjkaj\n5efn29jYqKmp9f8glU6nBwQE2Nra0mi0Hz9+GBgYyMrKhoaGJiQkWFpaCgkJiYuL379//2fP\n9ff3nz9/Pp1OT0lJwePxzEJxLi4uq1evDg8PV1RU5PoWTkREhK6uLgqFUlFRYYiYtLW1BQQE\nAACARqNZRsb9KQNIhjo6OlxdXTEYzMSJE5csWeLm5iYhIaGjo8NRPK+rq2vhwoXMbcJEIvHs\n2bPMj6HRaLq6uj8TBuJIbm5uYGDg2LFjR40a5ebmdvToUR79PTc0NIwfP15cXNzIyGj69OkH\nDhxgDPVJTU3F4XB/wxf9nzK8E7tfsG7dup8dPYwkkMRumEIikThOC+3o6AAEqsKFwFMqKirY\n9WkpFMqnT59qamp45zc9PR2LxbKXUiUlJREIhN/K+drZ2c2YMYPF2NnZqaOjs2rVqv6HIScn\nB58+T5w40dLSklHmCE/pCAoKkpCQ+Nn7EBgYCGtN02g0F3T9rMoAACAASURBVBcXRUXFy5cv\nw7dAtra2pqamaDR6kAMVOGJnZ6ejo4NCodiLMvF4PBqN3rJlywAue/v2bTs7O3jvU0lJKSAg\n4Ncbluw8ePBgw4YNPj4+K1asOH/+PHsBJQuVlZVhYWFjxozhuBoaGsqxck6wvH79Wk5ODofD\njR8/PjY2dtmyZXJyclpaWt++faPT6b29vUJCQn/JXPg/YsQmdtnZ2chRLMKQRUJCguPYAwqF\nAkHQkydP+B8SAv8pLi728PCAj8YAAJCTk9u5cyePyoa8vb3l5eVv3LgBn2e1t7fHxsbicLjf\nFtjV1taCIPjy5Uv2pcTERFVV1f7HgEKh7t+///r1axAEmU8SYVXhrKwsLS2tn50Lx8XFqaio\nwNtCXV1dq1atEhYWBgAAj8fDb116enr/I2FQV1d3//79M2fOvHz5kuUcE2bs2LFiYmIaGhrs\nS2pqagAA/Eyi/BdER0ej0eiQkJCbN2++ePHi1KlTlpaWRCLx/fv3A3gJ/Wfnzp1WVlYsxtbW\n1vz8/JCQEBcXF556/1Pa29uVlJTmzp3L3Ifb0tIyceJEU1NTuIxBVlaW4x3yX86ITezS09Mx\nGAy3QxpyIIndMMXc3Pzff/9lt7969QoEwaqqKv6HNESgUCj8PKMUIB8/fpSSkpo4ceKdO3cq\nKysLCgoSEhKkpaVZ5gRwi+7u7n/++QeLxWKxWEVFRQiCiETi4cOHf/vE48ePAwCwYMGCqKgo\nhrYIzMOHD1EoVP+jJZFIZ8+eTUxM1NTUZLbn5eUBABAeHj5r1qxp06ZxfG5dXZ24uPjmzZsZ\nlo6OjlevXrm6usrKyg7gM7CzszMkJASDwcBvCAiCJBKJvY3D09MTjUbD5X3MdHR0CAkJoVCo\nP9WLef36NQRBLM0KfX19Xl5exsbGPJogDJOamiouLs5ovX/8+LGZmRlDu1hMTCwpKYl33v+U\no0ePkkikjo4OW1tb5uHCsFzO/fv3W1pa0Gg0chvMzvBO7Jo4UVtbm5mZaWxsrK6uzsdoBQOS\n2A1T4uLipKWlWaqV+/r6nJ2dHR0dBRWVAOnp6dm5c6ehoSEWixUSEjIxMYmPjx/ZGd748eNd\nXV1Z+icKCwsJBAJLCRQXaWhoePDgwenTp1+8ePFbvc/W1lY3NzcUCgUAgIeHh5WVFVzXxair\nu3r1qqioaP+9z5kzx8nJac+ePWPHjoUtjY2NY8eOZe57gyAoPj6e49OvX7+Ow+FcXV3PnDnz\n5MmTEydOODg4EAiEATRMwOe5ysrKd+7cgbdIW1tbd+/ejcFgWETazpw5A4IgDodjKYaLjo4m\nEokAACxduvSPXIeEhEyaNInd/v37dwiCeFqG0dbWJi0tDdfSXb16FY1GBwcHv3jx4saNGxAE\nLVmyRFhYOCIigncB/BELFiyYPXs2nU7fvXu3kpIS89ectbX1tm3bYmJiZGRkfnsG/RcyvBO7\nX3TFAgCQmJjIx2gFA5LYDVN6enrs7OyUlZXPnTtXXl7e1NSUmZnp6OhIJBKZj6j+Ejo6OsaP\nH08mk6Ojox88eJCenr5lyxZJSUlXV9fBC7oOTb5+/QoAAEf9sNDQ0MmTJ/M5nt7e3oyMjH37\n9u3evfv27dvwoaS7u7umpua7d+9IJNLBgwfpdHpxcbGxsbGdnR28sRQQEMCiiPtrCgoKhIWF\n4WL/3t7e3t5eaWlpCIJQKFRsbGxHR4e1tTXcYhITE8PxCm/fvp05c6aSkhIIgqqqqn5+fp8/\nfx7A67127ZqwsDB7t0F8fLy4uDhzPX5fX5+srCwIgm5ubvCdRktLy44dO9BotKWlJQiCJSUl\nf+TaxsbmZ2V5GhoavJBrYSY1NRWFQi1cuFBKSmrDhg1fv37du3eviIjIypUr6XT6nTt3IAh6\n/fo1T2PoJz4+PnChfHt7u6ampo2NDUMu1MnJafLkyRgMhm+CQcOL4Z3YuXDCw8NjyZIlv+iu\nGkkgid3wpbOzc82aNYzBSigUysXFZZAddsOU8PBwZWVllgPoL1++EInEvXv3CioqnnLr1i08\nHs9x6dSpU8rKynQ6vaqqasOGDZMmTZoyZcrWrVtLS0t5FExWVpaamhq8UWpqakogEOTk5OAx\nox8/fqTT6dHR0VJSUvAklbKyMiEhodu3b1+4cAGNRv/pJ216ejqRSIQgSF9ff9SoUXBjKaxL\n9/79eywWe/v2bX19fQwG8+udmEHu5vr5+bFo+cL09PSIiYmxnJO+fPkSlq+DIEhKSgoEQQkJ\nCX19fQAApk+f/qeu4Ym9HJdGjx7NIkTHCzIyMlRVVRk7IHJycomJiYwjYHt7+z9qiOEda9eu\nnTBhAvxzeXm5ra0tBEEaGhrm5uYQBAkJCf3333+CjXDIMrwTOwQksRvuUKnUr1+/5ufncyzc\n/hvo6+sjEonHjx9nX4qOjmYpxhox3Lt3D4fDcSyoOnbsmLq6enh4OJxM4HA4WDINgqBdu3Zx\nPZLCwkJRUdGgoCBGu257e/vatWuZC8uoVGpAQAAWi50xY0Z0dPSoUaOUlZUZCdmf0tLSEhgY\nCEEQBoORlZUtKyvr7Ow8f/68mJiYlJQUmUyWk5MDACAsLIx3Z/F2dnbM5XrMMAsgM7hy5Yqw\nsLCIiIiQkBD8PwUEQRcXlwFEGBwczLGOED6K3blzZ25uLq+nYkZFRZmZmWVnZ7MrEa5atcrV\n1ZWn3vvJixcvIAjKzs5mWPLy8o4ePTpnzhw0Gg3fciBwBEnshjdIYocw3CkrKwMAgHkmG4Os\nrCwAAEZkyguPGuP4yTt79mx4K8ve3r66uppOp/f29t69e5dEIoEgmJKSwt1IZsyY4eTkxJ5i\namtrS0tLM1vu3LkTGBhobm4uJyenra395s2bwfg9f/48XLYPb+AxNpCwWCxc1QeCoIqKytWr\nV3nxB+Di4gIfPrKjpqa2ZcuWM2fOxMbG3rt3j3EsW1FRsW3bNm9vbwcHh+XLl7Ooi/efrKws\nCIJYeniTkpLglBE+iRYVFd2+fTvv8tqYmBhTU1NmC+PVKSkpjRo1asCvjrsEBQVJS0tfuHAB\nbvhob28/ePAgHo/vj6T238zwS+ws+s3PBHtGEkhihzDcKS0tBQAAFqZi4cWLFwAAMPRIRxhe\nXl5mZmbM/3jz8vIMDQ0ZKY6ysjLzGVlZWRkWi+WuihONRiMQCFeuXGFfCg4OBgCAo/rr5MmT\nuXJaJywsbGdnd+LECQwGAw+B/fjxY1NT06xZs+B3AARBuFn1/Pnzg3fHzI4dOzQ1NdkzpwcP\nHsCuFRUVDQ0NhYWFJSQkOG4nD4Z169bhcLiNGzc+f/78y5cvwcHBEARhsVhYkq2lpeXkyZOS\nkpJLlizhrl8G9+/fx2KxDP3CK1euiIiI6OvrT58+XVRUVE5ODh5EJvDuJQqFsnHjRlgvUF5e\nHoIgSUnJuLg4wUY19Bl+iR3q/weDwTA+Bxlt2/B9j5KSkoAi5x9IYocw3Ont7RUTE+O4ERUf\nH6+iosL3iOjFxcXx8fFLliwJDw+/cOECj87Ffvz4oaWlpaGhsXfv3vv372/evBkeVOXo6AgA\nwK5du3bv3i0iIrJs2TLGU+DZ7ZWVldyKobm5GQAAjsXyt2/fBgDg5s2bLPaSkhIcDnfv3r3B\ne9fW1paSkgoMDIQ/vfPy8igUirGxsaSkJAAAvr6+AADg8XgfHx80Gn3u3LnBe2RQW1srKSkZ\nGhrKnLvA5YMSEhKMCRM9PT2xsbEYDOb06dNc9E6n08+dO2dgYADvTQIAoKuru3z5ch8fH29v\n78jIyIKCgmfPnkEQ1J/5hAOAQqHo6urOmDGDQqF8/PgRi8UGBgaqq6vDmbSCggJc+8i7zPKP\naGlpefr06dmzZ1+8eDFSb/O4y/BL7JhpbGy0sbFZtmzZmzdv4O361tbWZ8+ezZo1y8HBgV3h\nfeSBJHYII4AlS5bo6uqybA7V1NQoKioyT7TkD1u3bkWj0dra2j4+Pk5OTlJSUkpKSjwSoWht\nbV2/fj0s8gJBkKKi4o0bN44ePQoAQFZWFp1Of/r0KQqFYsh57NixAwCAd+/ecSuAvr4+DAbD\nUbsf1pZTUVHJz89nGAsLC/X09BwdHbkit5aamgqnbuLi4rq6ut++fdPW1oaTPEbGIysrGxAQ\nsHPnThkZGYYAG1d49OiRlJSUrq7uqlWr9uzZExgYiMfjMRgMe5frrl27eCSr0dXVFRMTIyEh\ngcVijY2NFy9eHBISYm5ujkajd+/ePWHChNWrV3PdKcy7d+9kZGTGjBljaWmppaWFwWDU1NSw\nWCys91teXm5iYgKC4N/ZzjXcGd6J3YIFC+Dpgey4uLgwD4oeqSCJHcIIoKGhQVdXV0dH5+zZ\ns58/fy4oKEhKSlJRUbG0tOTzDXpCQoKwsDDz0WRHR8eCBQskJSX7PyJ9ADx48ACDwcBDqy5e\nvAiCIENP38PDg/FRtmTJEgAAamtrueja0dHR39+f3b5mzRp9ff2ZM2eCIGhkZOTh4WFiYoJC\noaZOndrU1MQt7/PmzYO7TYlEooiICBqNBkEQj8cXFxfX1NTAv9rY2LS1tWGxWK4Xfv348WPz\n5s3Tpk0zNTX19fXV1tbmmEjBQriPHz/mrneY2bNngyDIonKSmpqKwWCcnZ29vb154RSmqqoq\nNDQUi8WCICgiIjJr1izmJL6lpQUAADc3N94FgADz6NGjoKAguIQsKCho8H9pwzuxk5GR+ZlS\nNixdyKvQhgxIYocwMmhubl66dKmUlBS8T0MikcLDw3ndG8gCLKvGXsFDpVJNTU2XL1/OO9eH\nDh3S1taGfy4vLwcAwNTUFN4V27Zt2/jx4+l0Oo1GI5FIZDKZu64fP36MRqPj4uJoNNr9+/d9\nfX0NDAzIZDIEQatXr6bRaHl5ebGxsWFhYXv37mVuUeQWsJQdQ/TH0NAQngDb0dEBQRAejyeR\nSHQ6XVVVldeiZZqamj8bxSEnJ8f1Oj8YVVVV+AWysG7dOgkJiXnz5vHCKTMyMjIgCLKc+dbX\n169duxY+mdXW1vbz8+PiPjECM6tXr0aj0Z6entHR0dHR0Z6enigUapA7tUM5sUMDv6O1tbWu\nro7jUkNDQ2tr62+vgICAMBQQFxdPSEhISEioqqpCo9EkEon/MeTn59fX1/v5+bHYIQiaM2cO\nfELKIzAYDIVCgX9WUlJycXG5c+fO3LlzDx06RKFQ0Gh0d3e3i4tLbW3t+fPnueva1tb2+PHj\nixYt2rx5c1NTk7q6eldXV11dnYWFRWJiYkVFxdmzZ01MTLjrlBlPT0/4vV2+fHlubq6TkxMs\n7gjnmlQqtba2trKysrm5WUxMjHdhAAAgLi7e0NDAbu/r62tpaYH7VblLX19feXk5BEHl5eV1\ndXWfPn2SlZU1MjKSkZFxd3ePjo6G1fJ4ioyMTF1dHdyIDfPly5cJEyYQCAQ6nQ4AwNKlS2/f\nvm1qanrmzBm4yhOBW5w8eTIxMTEjI8Pe3p5hzMzMdHFx0dfXnz9/vuBC4xn03+3YjRkzRkFB\ngX069YsXL0gkkpGREU8Tz6EAsmOHgMAtfiEanJKSwnFbhVvk5uaCIMhoDW5ubjY0NIQgCI1G\n43A4UVFRFAoFgiDvxj0dOnQIjUY7OzvPnTs3OjoaVp/58OGDtLR0VFQUj5zCtLa2CgsLAwAg\nKio6a9YsExMTKpWakJAAN4paW1sDAHDw4EEIgng9Q3n16tUmJibs5YMpKSkYDObHjx9c99jY\n2AgAgIKCAg6HY/yARqODgoLgFGqQmjL9YeXKlQAAvH37Fv6VSqWamJi4uLisWLGCTCYz/kXs\n2rVLWFi4rKyM1/H8Vejp6W3atIndvmnTJvbxxP1nKO/Y/T6xu3nzJlxjO2rUqEmTJrm6uk6a\nNAm+8wBB8OLFi3yMVjAgiR0CArd49eoVAAANDQ3sS3v37tXX1+edaxqNZm5uPmXKFEaFPoVC\nOXLkiKamJgAASkpKnp6ePFVktbS0XLFiBbv94MGDsrKyLANtuU5eXh6zpgHjZwcHh48fP8Lv\nQEBAAE9joNPpFRUVoqKiy5cvh6fH0un0K1euaGlpwcFgMBhbW1u4qYVb0Gg0WOsYVj+eMGFC\nRETEnDlzsFgsGo2GIIhlQC0vgCsIVVVV4V5guF9nxYoVaDR64sSJ8HQ7eOvUyMjo33//5XU8\nfw9wFSP7zhSdTn/58iUAAHBNwgAY3okdnU5/+vSps7MzLO0Ig8Vi7e3tOfZ5jTyQxA4BgVvA\nU0HZp5RSKBQjIyNez1n6/PmzvLy8gYFBXFxcenr62bNnZ8+ejUKhDh06xFO/dDqdSqWi0eiM\njAz2pZKSEgAA/nQc6p9SXFw8duxYRUVFXV1dKSkpCIIkJCR8fHy2bt06duxYEAQnTZrEnzaa\nhw8fSktLq6mpBQYG2tnZwQM/Jk2a9O3bt8zMTD8/PzQafePGDW65g89hQRA0NTU1MDCAz5rJ\nZPLixYvRaDTfxPmjo6PhLRIymQzrYMvJyS1duhSNRq9YscLS0lJUVJRAIJDJZD09PUbWizBI\nqqqqAADgOBy8sLAQAABYn3wADPvEDoZKpX7//v3z588VFRV/1Z8dktghIHCRpKQkLBZ7+vRp\nxnlcU1OTj4+PjIwML07iWKitrf3nn3/09PQwGIyioqKbm9uzZ8947ZROp/f09IAgyPFroKam\nBgAA3m0WNjY2zpgxAwRBcXFxEATRaLSEhMTu3bu3bt3q6elpZGSExWLNzMwsLS1lZWXV1NRc\nXFx4XcVfX1+/b98+d3d3EASnTZvGMgx306ZNMjIyA95KYaavr09LSwvuSJ03bx4sF5ybm6uo\nqKilpYVCoSZO/D/snXdcE9n39+9MJo0kEAgQAgSkSu+9iSigCIqAgiCoWClrYxVZC4jYVrHr\n2svaFRu6drGAsiKuDUURRUSlSFFE6bnPH/N9svkliAgJiJv3H77g3pncMzFkzpx7zucM6Poq\nHQRvYWdsbKyvry8vL29jY0MikczNzZlM5ty5c0+fPn327FkXFxcikejp6Sle3Zn/LM3NzTQa\n7eTJk6JTJ06coNFonXZmep9jV1paiosC4D+3Tw9Y3b1IHTspUsTLqlWryGQyl8v18fFxcXGh\n0Wh6enrdkOrUs6irq7dZEIrrsIjFjxGlubnZ0dHRxMTkzp07EMKtW7eSSCQtLS0CgeDr6zt0\n6FDcz8PT78zNzfX19XFtDsnlGvKZP3++UNMtnIaGBnl5eb4YTVdIS0sjk8na2tp37tzp27cv\nrp5oYmKCYRgAICQkpE0DJEdOTs6sWbOsrKwwDEtISJgzZ46iomJBQQH/gMGDB0dERHA4nK+1\n2ZXyvYSFhbm4uAg5cM3Nzc7OzmFhYZ1+2d7n2AEAvL29+T9/s/zi50bq2EmRInbevXu3c+fO\nX3/9NSUlJT09vampqactkjhxcXEGBgZC3yQtLS0eHh7+/v4SWnTXrl1MJlPwCTw/Pz8+Pt7I\nyAgvILCwsEAQZMmSJfwAanNzc79+/QAAx44dk5BVOCNGjIiOjhYcef/+/ZUrV06cOGFnZyeW\nVLOJEyfa2dnh+jUtLS2ZmZl//PHHxo0br169amBg4OXl5e7u3vVVvpfPnz+z2ewFCxbo6OgI\npiVcv34dRdFbt25t2rSJw+FIOu3yP8KrV6+UlZV9fHzy8vLwkby8PB8fH2Vl5a7UqfzIjl3b\ncifBwcEWFhb8n7/p20mRIkXKd8HhcMaNG9fTVkicsrKyjIyM/Px8JpPp5uZ2+vRpDw+PFStW\nODg4oCj68OHD+fPnP3z48O+//5aQAadOnQoODlZRUeGPGBgYLFu2LCkpicViOTo6bt++PTAw\nMCEhgX8AhmFXrlxRUlKaOXNmQECAhAwDABAIhNbWVvzn6urqqVOnHjx4EMMwGo1WU1Pz8uXL\nAQMGuLm5dWWJyspKY2PjnJyc27dv29vbu7i4uLi44FPq6uoPHjzAm611MzIyMlu2bAkKCmpp\naVFVVW1oaHj37l16evqCBQtiY2MdHR2ZTGZ0dHRFRYXgf5yUzqGpqZmZmTlhwgQTExNc5efT\np0+urq6ZmZkaGho9bZ1EaNuxO3ToUJs/S5HyXVy+fHn16tX37t2rqqoyNDQcNGhQQkKCJKSq\npEgRBUKYnZ398OHDuro6ExMTV1dXGo3WnQasXr36t99+YzKZxsbGNTU1eXl5+vr6LBbLw8MD\n7+jV1NTk4eFx8+ZNHR0d/JScnJyDBw8+fvwYRVEzM7Pw8HBTU9Ou2PDmzRtnZ2fRcQqFwuVy\nr127BgDAxTgEIRAIgwcPPnjwYGNjI64SIgnMzMz27dsHIWxsbPT09Gxqarp69aqjo2NDQ4OK\nioqtra2np+elS5e64tspKSlVV1ePHDly/PjxFy9eVFVVxcchhPfu3aurq4uOjhbT1Xwfw4YN\nO378+NChQ8PCwvARFRWVxYsXx8bGAgDw/ux8r1dKF9HX179x48arV6/y8vIAACYmJn369Olp\noyTItwWKcVpbW/mNBZuamu7du4f33ROsn5ciRZBly5bNmzcvIiJi1apVCgoKjx8/3rx589Gj\nR69fv66urt7T1kn5ycnPzw8NDc3Ly9PV1aXT6YmJiTIyMps3bw4MDOweA7Zs2ZKQkLB169bR\no0fjXR/Ky8sjIyMfPXr08uXLN2/eNDY2mpqaKikp8U+ZO3fu8uXLPTw8bG1tW1tbs7OzV69e\nvWzZsri4uE6bIScnhwu5CQEhrK6uxhWb2Wy24NT9+/cfPHiA796WlpZK7hYYHh6ekpKyevVq\nAEBpaemjR49YLBaEcPr06fLy8omJiWpqatHR0fjNuHN4eXmNHTv27t27kZGRRkZGgYGBRkZG\nFRUVJ06cqKqq2rp1q5qamvgu6Pvw8/NTUVFJSEiwt7fncDiC0aM7d+4wmUyh/xcpXaRPnz4/\ntz/3L/BbVbEtLS3R0dH8bnpFRUXa2tr4uS4uLv+FzDNpjl0nyM7ORlH0xIkTgoOfP392cXHh\np29KkdIONTU1WVlZWVlZneiaWlpaqqKiMmzYML7cbn19/aJFizAMO3fu3DdP5/F4R44cGT9+\nvJOTk6+v74IFC0pKSr7LgMbGRhaLtWbNGqHx+vp6XV3dNvPid+3aRaVSL1y4IDh45MgRIpF4\n+vTp71pdkKSkJENDw5aWFqHx69evIwiydetWAABfuOrVq1eurq4AAE1NTTy6qaioePjw4U6v\n/k3279+PYRiLxQoMDMzKysJzy/i3JzyacPXq1U6/fktLi52dna2tbWFh4Z49e0JDQ21sbJyc\nnOTk5CTaIraDzJ49W0dHR1DW8Z9//omMjKRSqSwWKzg4+NChQ6JizlJ+BH7kHLtvO3ZLly4F\nAMycORP/1cfHB0GQqKio6OhoFEXnzZvXTZb2HFLHrhNEREQMGzZMdPz+/fsAgMLCwu43SUpv\noaSkBBfCIBAIeDcIPz+/169fd/wVpk2bZmFhIVqQMX36dCMjo/bP/fLly6BBg2RkZEJDQxcv\nXhwXF2dubs5gML7Lu7px4waBQGiz0HXhwoUODg6i4/r6+oIOX1NT0+7duyMjI1VVVfHuup0r\nmy0vL5eXl4+KihKsCiwsLNTR0Rk7duznz5+JRKKlpSWE8MOHD9ra2v369YuJieHHsWRlZREE\n2bhxo+Tci9u3b5PJZLwyl0QiycnJbd68uaKioqam5tKlSyiKKioqfq9jLUh5eXm/fv1IJJK9\nvX1QUBC+0RQWFlZfXy/Gq+gctbW1FhYW+vr6Bw4cePHiRVJSEoFAoNPpysrKS5cuHTduHI1G\nGzp0KF9SW8qPQ+927ExMTAICAvCf37x5gyDI+PHj8V8jIyOlLcWktIm5ublouAJHQUFB0tV2\nUnovpaWlGhoazs7OmZmZ9fX1DQ0NWVlZrq6uXC63492utLW1N27cKDpeUFDwzeeKiRMnamlp\n4f2+cHg83oIFC6hUasc1hI8ePaqoqNjm1K5du/r06SM0iEvZ8dXjysvLra2tmUzm0KFDBwwY\ngCCImpqapqbmo0ePOmiAIJmZmcrKytra2pMmTZo3b15AQACFQhk0aBAuRzxv3jwAgLu7+6xZ\ns7S0tOzs7JSVlWVkZBAEwTPNcTQ0NCQXutPR0dm6dWt8fLyWlhZfaQtC2NDQgKKokZFRcHBw\nV+RgeDxeRkbGsmXLYmJiVq1adffuXXFYLR5qa2t/+eUXfuYxhUKZPHky/0149uyZqqrq7Nmz\ne9ZIKaL0bseOTqdv3rwZ/3nHjh0AAL6Y5MaNG5lMZjdY2bNIHbtOYGxs3OadFULIZrPFolAl\n5adk4sSJVlZWQtGUhoYGGxubjje8olKpZ8+eFR3HU8oyMzO/dmJ5eTmBQLh48SJ/pKSk5Pr1\n6y9evHBwcJg2bVoHDcjIyCASiW3GhJYuXWptbS00WFhYCADgRyXd3d21tbWVlZUBAHiPVzk5\nOTMzsz59+nz58qWddevr61esWOHu7s5ms/X19UNCQvAbT1VVVWpq6qhRowYOHBgdHX3q1CnB\nCFxcXByeBYj/CwDAMIxCoaxfv/7t27cPHjwAAFhYWBCJRP69QLyEhYUNHTpUU1OT/6Vx7tw5\nHx8fFouFh/Fwq/r06fPrr79KSPCvx/Hy8vLz8xONjB44cIBGo7X//86nrq4uJycnPT29oKBA\ndP9dihjp3Y4dg8Hg/zGPGjWKRqPxw8IbNmyg0WjdYGXPInXsOkFAQECbt+Hi4mIEQX56KVop\nnaO1tVVOTq5Nvz8tLY3BYHRQJl5VVXXPnj2i43h/oXbiXunp6XQ6HdcPO3bsGF6sipeI0el0\nTU3NDu5Ifv78mU6n7969W2i8paXF3NxcNABTV1dHJBKvXLkCIbx58yaKoiQSafny5WVlZYcP\nH5aVlf3jjz8YDIaMjMy2bdu+tmhVVZWlpSWHw5k7d+7hw4c3b948cuRIAoGwatWqbxpcVVVF\np9OJRKKjo2NycjKKooLdz4hEIpPJ3LRpE51Or6iozZzUYAAAIABJREFU6Mg78F3k5ubie+74\nbTIxMRHDsKCgIBKJhLevxEOGK1eu1NXVNTY2brPXcG+Hw+HgNcJCtNPtVJCGhoZZs2ZRqVS8\nzQYAQFtbW4yd2aQI0bsdOxMTk9DQUAhhWVkZnU4fPnw4f2rixIl9+/btBit7Fqlj1wlOnDhB\nJpOFHDgejxcaGmpubi5NB5bSJl9rrvXu3bs///wTANBBQdHQ0NAhQ4aIjq9Zs4bNZrcTydi/\nf7+qqiqEcPv27RiG/fbbb3jk49WrV0FBQSiKdrwfw+LFi+Xk5HBfDefLly/jxo1TUFBos2GP\nj48PHrCZO3cuiqK4Y9rS0uLs7BwREQEhvHz5Mp5u+LUVQ0JCTE1NKysrBQcPHTqEomh2dvY3\nDcar4h49ejRnzhwXFxf+eF1dHe7alpWVcTicHTt2dODqv5tt27bhccGxY8firWPJZDKRSHz0\n6FFRUREAwNjYeOTIkR8/fjQxMeGnA0ma4uLiQ4cOpaSk/Pnnn8+ePfvaYQUFBb/++uvAgQNt\nbGwiIiKOHj3aia84WVnZU6dOiY63tLSgKHrt2rV2zuXxeP7+/qqqqmlpafit6vXr1/Hx8RiG\npaWlfa8lUjpC73bslixZAgBwdHTEFYD4H689e/aQSKRZs2Z1k6U9h9Sx6xxhYWHy8vLr1q3L\nz88vLy+/cuWKr68vnU7Pzc3tadOk/KDU1tYCAPDmVzhZWVm4WDreA4pKpc6aNeubae8PHz4k\nkUjJycmC2v0XL16k0Wjr169v58TMzEwMwwoLCxkMxoYNGwSnZsyYYWVlRSAQOthHlcfjzZw5\nE0EQKyurMWPGDB06VFFRkcvl3r59u83j8/LyGAxGRERE//79KRQKj8d79eqVv7+/kpIS353l\ncDgGBgZtnl5aWoogSP/+/Y2NjS0tLcPDw/nf1f7+/h1pnRQeHo7n+Y0cOTIqKoo/vnv3brxC\n9v37956enr/99ltHLr8TGBkZ2djYKCoqMpnMkJAQTU1NvPnEtm3bFBUVr169iqJoWVnZqVOn\nqFQqniAoOZqbm6dPn45hGJvNdnZ25nK5CIKMHj26rq5O6Mh9+/ZRKBQnJ6fffvttxYoV4eHh\nMjIyvr6+39vs1dzcfOnSpaLjuNrLq1ev2jn35MmTFApFtNX9woUL2Wz2j1Am8vPRux27+vr6\nsWPHUqlUOTm5devW8cc5HI6pqalgouvPitSx6xwtLS0rV67kK4JiGObt7S25TudSfg4MDAwW\nLVqE/5yRkUEikcaPH5+Xl5eSkqKlpXXo0CE1NbXBgwd/s9vSyZMnZWVl9fT0xo4dGx0d7eTk\nhKJofHx8+2c1NzerqqoOHTpUqKFTeXk5i8XavHkzfv/u+OU8evRo+fLlY8aMmTlz5p49e9p3\nR3JycoyNjfHNX1z1w8bGRvBPhsvltrlJ0tLS0r9/fwBARETExo0bV61aNWLECLwbKYRw06ZN\nX3MHBcnPz0cQxMfHJzw8fOzYsfjg33//raCg4Ofnx+FweDyes7NzcnJyxy//u9i5cyedTldT\nU9u+fTuPxyORSBcvXnz58iWHw5k/f35rays+8v79+/b308VCdHS0srKyoDhOdna2jo6OUMT0\nwYMHGIYJFYo9f/6cy+V2PCMTJyUlhcvlCon71NbWOjs7q6qqxsfH792792vSP6NGjRo9erTo\neF1dHYVC4cvZSBEjvdux+xrZ2dkdzHfp7UgdOyFwec8VK1bs27dP9BlRlLKysry8PGnFvpSO\ngCeT5eTktLa26unpxcTEQAhzc3NlZWXxEFphYSGdTt+/f/83X6qsrCw1NXXs2LFBQUGJiYkd\nzOxMS0tDUVRHR+fDhw8QQh6Pd/PmTS0tLQUFBX19fRqNpqKismHDBgl9+7W2toaFhSEIMnPm\nTKHQ4MOHD1EU9fHxET1r2bJlDAaDTqcLDl68eJFMJh89enTnzp1aWlodWT0kJASXF6HT6TNm\nzBg4cCCKomFhYVwud968ee/fv6dQKB0RAuwcPB5vwoQJCIIMGDBg7969GIaNHDmSyWQ6Ojqm\npqbOmDGDRCKtX7++srJSsIJYEjx9+rTN3c+nT5+SSCR++SCEcOzYsYMGDRJ9BTwX5ePHjx1f\ntK6uztTU1MLC4saNG7hSz9atW8lkMoIg9vb23t7ebDabyWS2ubXq6OjYZrQPQmhoaLhp06aO\nmyGlg/wkjl1tbW1eXl4nxEJ7O1LHjg+Px1u0aBGFQmEymba2trjY1YgRI/6DnwopEoLH402c\nOJFMJvv6+iIIsmLFisjISAqFMm7cOH4IbcqUKb6+voJnXbt2zdfXV1VVlUQimZqaxsXFdSW/\nPjg4mEQiIQiioaFBp9MRBEEQJCAgYPPmzW5ubsbGxiwWS3Ly7H/99ReGYXQ6fc+ePbj7yOPx\nzp8/r6amRqFQtm7dKnR8a2srh8P57bffAABFRUWCU9OnT3d0dJw2bZqnp2dHlv7y5Yu9vT2d\nTscwTFVVNSws7JdfflFVVXVxcampqfH39zc2Npb08zxe/Kuuro5hmKamppmZGYqi5ubmeEgS\nQRA3NzcqlSq6JSpGVq1a9TW9Q29v7xkzZvB/1dfXb9NtamxsxDDse6WV379/j/vWRCJRRkYG\nAMBms7OysvDZpqamxYsXYxh2/fp1oRM9PDzmzp3b5mtyuVzRIh4pXafXO3bXrl2ztrbGN9T4\nj2u+vr6CDy4/MVLHjk9ycjKDwThw4AD/Fnv37l0jI6N+/fp9c2tMipSOc+rUKXt7ewzD9PT0\nAgMDhVqYbNq0ydDQkP/r6tWrCQRCRETE/v37L168uGbNGiMjIw0NDSEvp+P89ddfVCr18uXL\ne/bsWbx4MYFAwLPam5qaNDU1165d++7dO11d3cmTJ3fhEr9Kc3OzsbGxoaEhjUYjk8mGhoa4\np2VkZKSioiIq9oHXFrx48cLc3Dw8PFxw6uLFixiGycrK7tq1q4OrNzY2pqSk4E3/EARRVFQc\nMWLE/Pnz+/btq6am9uTJE7FcYzvs2bOHwWA8f/583bp1RCJRR0fn8ePHPB5v+PDhjo6OmZmZ\nJBKpgwHITjNr1qw2i28ghFOmTAkODub/yuFwgoODg4KCnJycxo0bt3fvXr7jS6fTO9cypLKy\nMiMjw9raesiQIaJFGOPHjxcsbcFJSEiwsrISPfjhw4cAgPz8/E6YIaV9erdjd/v2bRKJxGAw\nvL29+Y5dRUWFiooKiUT6Ma9KvEgdO5zy8nIymSwqUvr69Ws6nX7kyJEesUrKz8qJEyfalMms\nqamJjIxUU1PbuXPn/fv37927RyAQDh48KHhMfX39gAED3NzcOrd0U1OTgYFBUFBQU1PT0KFD\ncW+Jx+PFxcUpKCjgscD09PTv3WvrOE+fPuVyuVpaWqNGjYqIiAgNDTUyMmKxWG0Wtz558gQv\nWb19+7aMjMzIkSPv3LnT0NBQVlaWlJQEAPD09OyEpNmzZ89iYmLs7e1VVVXd3Nzmzp0rVG8r\nIVpbW319fdls9owZM1AUZTKZU6ZMcXBwoNPpycnJenp6qqqqKIp+U/6jKyxevNjOzq7NqYCA\ngClTpuA/37p1i0gkKigoxMTEpKSkhIeHy8rKOjk5VVdXv3nzpiv7xc3NzUQisc3cuMzMTBRF\nhe5HxcXFMjIyCxcuFBysqqqysbFpc+9eStfp3Y7dkCFDNDQ0SkpKSktLBSN25eXlGhoaX3us\nkRw8Hu/FixeXLl06fvz48ePHr1y58l29hjqB1LHD2bt3L5vNbjMyFxoaiisySJEiLkpKShAE\nEXJl8Aw8DMOUlJS0tLTwlgz9+vUTPf3p06cAgLy8vM6tnpeXp6KiYmxsLCsr+8svv6xcudLZ\n2ZlOp/PV3err6/m6a5Kguro6OTnZ09NTW1u7f//+c+bM+VrjjdraWiKRmJGRASG8d++es7Mz\nv10EmUxmMBi9riiyqakpKSkJV2bGA4e43gqZTOZfGpVKXbRokYT2hW/dukUgEAoKCoTGKysr\nZWVlcZ3FqqoqRUVFBwcHDofD3/d/9+6dmZnZsGHDpk6dqq+v32ldp3YKRPAArWg0+uTJkzIy\nMk5OTosWLdq6deuMGTPYbLa5ubkkdAelwN7u2LFYLDwrU8ixgxAuWbJEXl6+G6zEqa6ujouL\nw9XYhdDQ0EhOTu6gNvf3InXscJYvX25vb9/m1Lx58wYMGNDN9kj56QkMDLSwsOAHirZv304i\nkcLCwjAMw2MhBQUFDAZDWVm5zb99NTW1NhVfO0hFRQWuBCYnJ2dlZRUdHS3YZ6y1tRXDMEGZ\nuh5k2LBhAwcO5Iflampqbt68ee/ePUNDQ8GEsN5FRETEyJEjHz161NDQcPXqVSqVOmLEiOzs\n7E+fPnl7ew8YMEBJSSkoKEhCopheXl7m5uaCUYOqqioPDw9TU1Pcm1y+fLmOjg7e7NXc3PzW\nrVv4Q++VK1dwEQBBhefvBY/YXbhwQXQqKysLRdE2228UFhZOmzbNxcVFX1/f19d37dq1vc6n\n70X8yI4dJuokCfHx40cul9vmFIfDqaur++YriIXS0lJnZ+eioiI9PT0fHx9NTU28BKy2tvbF\nixfXr19fsGDBsWPHrl69Ki8v3z0m/ddgMpl4PZoo79+/x3t4dzOvXr06duzYkydPCASCiYnJ\nyJEjVVRUut8MKRJiy5Ytnp6eJiYmY8aMMTAwmDZtmq6uLt5TwdTUFACgp6enq6v74sWLLVu2\nTJ8+Xeh0IpHY0tLS6dWVlJSWLVt27do1b2/vhQsXCs0+efKkpaWlvr7+0qVLBgYGX/uS7B5W\nrFjh6Ojo7++fkpJiYmKCNwSKiopqamqaO3euGBcqLS3Fd8ArKysNDAyGDBkyZMgQPJwmdlgs\n1tOnT01MTCCEMTExISEhO3fuxKc+fvzo4+Ozbt06GxubY8eOBQUFiX31gwcPDh8+vG/fvh4e\nHrq6uq9fv87IyNDU1Dx9+jQuqZiVlTVkyBAGg3H58uXo6GgXFxcymSwrK1teXk4kEmNiYgYO\nHNjp1TEM69+//549e7y8vISm9uzZY2FhUV9fL9jJF0dHR2fNmjWdXlTKzwP8VsROXV0dL7cR\njdhNmDBBU1NTwq7n/xg/fjyRSPxaIldLS8vGjRsRBPle6aCOII3Y4eB7W4LisThfvnxRU1MT\n1DjsHtavX08ikYyMjMaMGRMaGqqjo0Oj0Q4cONDNZkiRKPX19atWrfL09FRSUkIQJCws7N69\ne4IHhIWFGRgYeHh4CJ1YVlZGIBA60nGhfdasWaOkpCS0Dfr582ddXV28syqFQgEAmJmZtdOC\nthvIz893c3MDAOANGxAEGT58+Nd2bzvHuXPn5OTkjIyMYmNjExMTAwMDyWSyv7//9yrxdpCz\nZ89SKJTXr1/n5uYiCPLmzRt8PD8/n0Ag3Lp1C0I4YcIEf39/SawOIWxtbT116tSvv/7q7+8/\nderUgwcP4iokOP37909MTOT/+u7duwsXLhw8ePDBgwdWVlYrV67s4urZ2dlEIjE5OZm/3Vxc\nXIyLdeOw2ezk5GRBk6R0Jz9yxO7bjt2kSZPk5eXv3r0r6Njh+R8IgkRHR3ePoSoqKpGRke0f\nExwczOVyxb601LHjExwcrK+vL7ghVVdXFxQUxOVyu/n9OXHiBIZhgmX8ra2tqampGIbx1QGk\n/Ezs27dPXV1ddPz8+fMEAqFPnz5C45GRkX379u16sXZjY6Ozs7OOjs7x48erqqoaGhr+/vtv\nFouFIIiNjY2/v39iYmJ6evrEiRNJJBKe6NaDvHv37uLFi1evXhV7oUNRUZGMjExCQoLgW4oX\necTGxop3LRwej+fq6mppabl+/XoVFRX+ilpaWmw2W01NTVZWVklJSV5eXtJdKIT49OlTRkaG\no6Ojm5sb393k09zcLC8vL5ZiMrx+SEVFxdfXd+DAgQQCgUAgeHp6mpqakslkFEUxDNPV1W1z\nW1aKpOndjl1paSmXy8UwzMrKCgBgYWFhYWGBJ7FqaGiUlZV1j6FEInHx4sXtH5OUlEQikcS+\ntNSx44Nnt+AaYzNnzgwJCWGz2VpaWpJWgRfFzMyszXZ24eHhXl5e3WyMlG7gzJkzNBqtzWR5\nvNPXqlWrHj9+XF5efvXq1YCAABkZGTyo03U+ffoUGxuLf+nhUToAgJqa2rhx46Kjox0dHVEU\nnTdvXkxMjJ6e3s+q+zNt2jR7e3vRhLYzZ85gGNYV1cB2eP/+vbu7O4ZhGIaNHj0af6sBAAiC\n6OjouLm5KSgoAABkZGQ6qD7ddTZs2CAnJ0ckEvGeOgQCYfz48YJ3h61bt9LpdHFJe9bU1Oze\nvfvXX3/V0tIyMDDw8/OTlZVdsGDBxYsXr127hrcV1tDQwMW0pXQnvduxgxCWl5dHRUWxWCx+\nEFhRUTEqKqq8vLy77ISampojR45s/5hhw4aJPrh3HaljJwiPxztz5kxcXJyvr++kSZO2bdvW\nzY/L8P+XjP3zzz+iU2fPniWRSD/rzfW/THV1NYlEOnnypNB4a2urmZnZwIEDcek1AACGYQMG\nDHjw4IF4DWhsbHzw4MHOnTsRBHF0dBR0cc6ePUulUlesWIGiqGiugtjJzs5OTEwMCQmJjo7e\nsWOHRKV6+VhbWy9fvhxC2NDQkJGRkZiY6O3tbWtra2pqSiAQZs6c2QlFlY7A4/H27dsHAPD3\n94+JiUEQRElJiS/MNmTIkOHDh8vIyMjKykqoeE6Q1atXUyiUTZs2NTQ08Hi8QYMGcTgcDofj\n7e3N4/G+fPmybt06Mpncfj/iTlBWVoY3xJOTkxPqyjh9+nQKhSLY21dK99DrHTscHo9XVlb2\n/PnzbovSCTJt2jRchr7NfI66uroFCxYAAL7ZC7ITSB27H41nz54BAN6+fSs6dffuXQCAhNTF\npPQsM2fOVFFREcyxa2pqmjJlCpPJxJPJKioq8CJKydkQGBhIp9M3b94sNP7777+rqamx2WxR\noUcx0tzcPGrUKFzkxdzc3MbGRllZWV1dXaKibjj6+vpbt249ffo0h8MhEAgIgvD3bchksoyM\nTL9+/ST3JTlkyBB7e3sfHx8AwN9//40PHjx4EPek09LSAACrVq2S0Oo4VVVVNBptx44dEMLm\n5ua0tLSZM2fyUy1VVFQwDJOXlxf9bHSdzMxMBEEsLS3nzZsnNHX8+HE6nU6j0aQFsN3Mj+zY\nfbsqNj09XUdHx9jYGEEQNpvNZrO/rzpDTCQlJWVmZs6aNSs5OdnOzo7L5dJoNABAXV1dcXFx\nTk7Oly9fXF1d582b1yPmSelO2Gw2iqLFxcX4boggxcXFNBpNtF7sp6G4uPj+/fsfPnwwMjIy\nNzcnkUg9bRG4e/fuvXv3Pnz4YGho6OLiIicnJ6GFli1bVl5ebmNj079/fxMTk8rKyuvXrzc1\nNeHeBgBASUlJSUlJQqvjXLt2jcViffnyRWh85MiRs2fPptFofPU1STBs2LBz584pKSnZ2tq2\ntLTk5uY2NTWZmJj4+Pjk5+crKipKbml1dfXLly8fP3584sSJO3bsSElJYTAYq1evfvnyJYSQ\nTqffv39//Pjxhw8flsTq27dv79+/f25uroyMTEVFxc6dOy9fvnzkyJFVq1bZ2NiYm5ujKJqe\nnj5jxgxJrI6D994dM2ZMUVGRv79/UVGRk5OTm5sbi8XKyclpamo6d+6co6MjfmMSLwQCAQDw\n+PHj5cuXC001NzeTyeSqqqqXL18aGRmJfWkpvRL4rYgdhUJZtmxZ97maX6exsXHVqlUWFhb4\np5wPkUh0cHDYtm2bhPYCpBG7HxBXV9cxY8YIDeKbIyNGjOgJiyRORUXF8OHDEQSRk5PT1NTE\nwzZ4q6ueori42MXFBUVRHR0dW1tbOp0uJyeHhzQkx7Vr1+bMmTN06NDx48evX7++m/sUYxjm\n4+Mj2noVd/VQFG0zkCwWjh49CgCYMGECP9OgqakpMTERb7G1YMECCa2Ls27dOgzDJkyYEBMT\n4+rqGhYWJisru2TJksjISPw90dfXBwBILnb46dMnCoVCoVBkZWW1tbUDAwMFy5BJJJKFhYWE\nlsZZsWKFjY1NQ0ODgYHBwIEDBctToqKiqFTq6NGjJbR0TU0NiUQS0k3866+/Ro0axWKx6HQ6\nAEASkUIp7fAjR+y+7dgNHDjQx8fnh0paqq+vLygouHv37t27d58/f97Y2CjR5aSO3Q9IVlYW\nkUicO3cuP7Hm48ePkydPptPp3dDOsvv58uWLmZmZlZUVP4WrpqZm3rx5GIZ1rh9l16mtrdXV\n1XV3d8djNhDCpqamtWvXYhi2f//+HjGpG+ByuUlJSQQCYcuWLfzBp0+fzpkzBwBgbm4ulAIl\nRnR1dYlEomj5yIgRI/T09FxdXSW0Lk5+fj4AwMjIyNDQMCwsjEqlZmdn4z3px40bp6enV19f\nTyAQrK2tJWeDvr4+nU4XLeB49eoVAMDPz09yS0MIt2zZoqOjs3PnThaLJVSsEBsb6+bmhiCI\n5LqyRkREUCiUmJiYxsZGHo83adIkEonk7e2NYZiXlxeBQCASiVOnTpWQXLMUUXq3Y1dWVjZq\n1KhBgwYdOHAgNzf3uQjdaG3PIHXsfkzOnDmjrKzMYDAcHBxsbGxkZGQ0NTV/Vq2T1NRUDodT\nXV0tNB4fH9+nT58eee5avHhxnz59RDP3lyxZoqKiIqFeTz1OVFSUra3ttm3biETi4MGDly5d\n6urqCgBAEIRAIOBdzsLCwsReUVRVVYUgCIfDEZ3C61KNjY3Fu6IQmZmZAIBhw4YBAAgEApPJ\nxDBMWVn50KFDeO0IhFBRUVFQcE7spKSkAAAERY5wRo8ejaIo3ulLcjx+/BgA4OPjI7RX0NjY\nqKWltWLFCl1d3Y0bN0pi6fPnz1taWuJC0CiKcjgcMpkcGhpKJpOtra0ZDAaNRjM3NycSiamp\nqZIwQIoovdux68hm7s+N1LH7Yfn8+XN6evrSpUt///33c+fOSTp224O4uLjgOuFClJeXIwiS\nm5vb/SY5OjoKCrTyqa6uRlG068rAPyZv3rxRUlIKDAzMyMiYMGGCgoIChmHq6uooiuIt23Ny\ncrS1tYcPHy7GRRsbG/EGEgiC6OvrBwcHC+5C/vPPPwAAd3d3Ma4oysOHDwEA5eXl/fr1o1Ao\n48ePz8zMxOPlf/75J4fDqaysJBAIXWyl1T6NjY2qqqoEAiEpKQkvkSksLBwxYgSCICYmJhJK\nxRFk2LBhDAYjJiZG0KTIyEhlZeWamhpXV9dFixaJfdFt27YRCITY2Nhz585xuVx+JhKXy6XT\n6WQyWV5eft26dYsWLVJRUSEQCD/rw+2Pxo/s2H27eCI4OJhEIuFS5t88uAd58eLF5MmTAQCX\nL1/u+FktLS2nT59uv+8QXmgp5QdERkbGz8/Pz8+vpw2ROCUlJXgOkxDKyspMJvP169fW1tbd\nbNK7d++0tLREx+Xl5eXl5d+9eyfGtSorKzdu3Hjr1q3Xr19raWm5urpGRUX1SBc7NTW1jIyM\n0NBQLy8vLpdbXV1NJpObmpqOHz/u7e0NALC1tU1PT7ewsMjKynJxcen6irW1td7e3i9evAAA\nkMlkGxub1tZWd3f3JUuWzJ49GwBQUFCAIMjQoUO7vlY7GBkZKSkpHT16NDw8PDMz09zcnH91\naWlpbm5uK1asUFNTKy0tldydgkQi5eXlubu7JyUl4Rvira2tAAAnJ6f09HSh3GtJsHv37r59\n+27durWmpsbAwACXg66qqurbt6+hoWFFRUVFRQWHwxk3bhxf77CLvH37durUqRs2bJgyZQoA\noLCwcP78+b///jsAoKSkhEgkjhkzZvny5bien4eHh7Ozc0BAQEFBgeRqmKT0AmCH5U5+cO7d\nu8e/oo7z6tUrPT097XbBa82kETspPYiJicnatWtFx5uamohEouRiJO1gbm7eZt+khoYGIpEo\nmOXdRe7du6eiotK3b985c+b88ccfs2bN0tLS0tDQkFw+0zdpbW3Nysry8/PT0NA4f/686MZr\nv379EhISxLLWuHHjDAwMysrKHBwcnJ2dKRTK7t27jx07RiAQrl+/XlRUhKfPd4OKW2pqqqys\nbEZGhry8vJyc3KVLlxobG5cvX467FxiGrVy5EkVR8fYxa5PHjx8nJSWFhoYuWbJEqMWcpDl4\n8CCFQgkNDXV1dR0xYoSVlRWVSp02bVpCQgKKopMmTZKVlR06dKi4On2lpqbq6ekJZs6VlJQA\nANasWYMgCP4H+Pz586CgIHV1dby7HYVCWbFihVhWl9IOP3LE7udx7Orr6x89eiSJFgjSrVgp\nPc7kyZPb3Gs7ceIEiUTqEd35adOm2dnZiSZrHzhwgEqliuvv5cuXL5qamqGhoYL77F++fBk2\nbJihoWHPNsqMiYn5Wgl2RETEuHHjur5EdXU1kUjEN3mvXLmCYZivry+VSmWxWEpKSgwGA0EQ\n/i6wJHj06FFcXJyXl5e7u3t0dHRQUBCKokZGRogAAAAtLa2TJ0+ampoaGhqOHz8+OTn5woUL\nP2Uif2trq6Ojo4WFxdOnT/EuFA8ePLhw4YKiouKMGTMghAUFBcrKyt/sk9RBJk6cGBoaKjjS\n1NQkIyOD18NOmzbt+PHjGIYBALhcroaGBv4/gqJoj3e3++n5kR078YSLfwQoFIqJiYmJiUlP\nGyJFiviZMWMGXoQIBdJenz59GhsbGx0d3SPbLjNnznzy5MmMGTMEMxlycnKmTp0aFxeHSzB0\nnbS0tLq6ui1btggq9lGp1J07d75+/frs2bOip/B4vOLi4rq6OrEY0A4KCgrl5eVtTpWXl+O7\nY13kwYMHPB5vwIABAAAPD4/9+/dnZmbS6XQul4sgSF1dHZPJPHv2LL4LLHbWrVtnaWmZm5tr\nbW3t7u7++vXrEydOBAYG4qFKFEXNzc2nT59++PDhmTNnRkREPHr0iEqlNjY2Xr58eejQoW5u\nbl97fzrOx48f8/Pzm5qaxHJFXQcXzFNRUTGOcdfaAAAgAElEQVQyMoqLi1NSUho6dKiPj09Y\nWNiKFSsAAHp6evPnz8erKLq+HH+7mQ+RSAwICLhx4waKovX19cHBwVQqNSwsrKKioqSkREZG\nBr+1e3l5ffr0qesGSOmVwJ8lYgchrKyslESVrjRiJ+VH4Pjx4zQazcLCIi4uLjk5ecSIERQK\nxd/fX6KNFtonIyNDUVFRU1MzPDx86tSp/fv3R1F0woQJYkxjj46ODgwMbHNq4MCBQtudBQUF\nw4YNk5GRAQAgCNK3b99t27ZJLm509epVIpHIV3vh8+bNGyqV+tdff3V9ifPnz1MoFMGR6urq\nvXv3xsfHDxs2jMlkSu576eLFi6LKNVlZWQwGY926dTweb9euXdbW1rjDLSMjIycnh0cvGhoa\n7t27l56ebm1tbW9v3+mS7V27dvHzSjEMc3d375Eioa+RlZUFABg7duzOnTtfvHgBIbxw4cL0\n6dO9vb3xDhli2T7atGkTl8sVqjF//fq1nJwc3toOQRBXV1dFRUUTExM1NbV37945ODg4OjoC\nAPr37991A6R8jR85YvdTOXbx8fFAAlW6Ynbs/vgDurjA0FA4ezZctw6ePAlzc2FPdGmT0uso\nLi6eP3++n5+fi4vLxIkTT5482eO7XVVVVevWrRs/fry/v39CQsKtW7fE+/pjx44VVaLGGT58\n+NSpU/m/3r17V1ZW1svL68yZM0VFRXfu3ElJSaHRaII1jGLHw8PDwsKiuLiYP/L27Vs7Ozsn\nJyexaNAUFhYCAJ4+fSo6NWfOHIlq1w0YMGD8+PGi46mpqWpqavwPXnNz882bNxEEefDgQXV1\ndWRkJJFIxL0xXALmjz/+6MTq8fHxVCo1OTn5n3/+KSsru3r1anBwMJlMvnz5cpeuSnx8+PAB\n/P+O1Y2NjSNHjiQSib6+vgkJCaNGjQIAyMnJXbx4sYurVFZWysvLi6pPh4WFCcVofHx8iouL\nL1++jKLo/fv3ZWRkUBR9//59Fw2Q8jWkjl030TscuwcPYFISnDABDhoEjY0hgwEBgABACgXq\n6kJ3dxgeDufOhZs2wdOn4YMHsKpKPOtKkdILWbhwoZ2dXZtTffv2Xb16Nf4zj8czMzMbNWqU\nkKd78+ZNiQpwVFZW9uvXj0wme3p6Tp482cvLi0qlOjo6irGhtp2dXXBwsNB1lZSUKCgobNq0\nSVyriEKlUvfs2XPz5k2ha8HrcwXjlMuXL7ewsKitrTUzMzM2Nj59+vShQ4cmTJhgaWlJJpOJ\nRCK/u2sHuX37Noqiol7RtGnTNDQ0ejBELQSbzcb7rMyYMUNVVZUfojt27BidTo+Li6PRaK9e\nveriKunp6WQyeejQoQcOHLh58+a+ffsGDRpEpVKjo6MRBMEwzNbWtqKi4v3795s2bZKVlY2L\ni4MQ4row+/bt6+LqUr6G1LHrJnqHYyfKly/wxQt46RLcswcuWwYnTYK+vtDaGsrK/uvzaWtD\nZ2c4YgSMj4dr1sAjR2BuLuzeZkpSpHQ/eXl5bd7j09LSiERiUVER/mtubi6CICUlJaKvEBwc\nHBYWJjkLeTze2bNnExISQkND58yZk56eLl696Lt379Lp9MDAwJycnIaGhsrKyiNHjvTp06df\nv36Sqx35888/BaNBurq6R44cwaeqqqoAAA8ePOAfPHv2bB8fn3nz5mlpaZWWlg4fPpxEItnb\n2w8ePFhTUxNvivBdG9MxMTHe3t6i47W1tRQK5dy5c128OnExc+ZMfX39169fk0ikEydO4INf\nvnyxtLSMjIzk8Xh2dnbTp0/v+kL3798PDAzEW2Orq6sHBwfjDU74zWHxDsUKCgqpqak8Hq++\nvp5IJDIYDHHVcEgR5Ud27L6tY/eDYGNj881j3r592w2WiB8qFWhrA23tNqbq60FpKXj5Erx8\nCd69A6Wl4O5d8O4deP0a4LnhFApQVQXa2oDD+T8/6OkBWdluvg4pPxTv3r1btWpVdnb2q1ev\ndHR0nJ2dZ8yYoays3NN2fR/GxsYzZ84MCgpKTU0dOXKkrKzshw8f9u7dO2fOnPnz5/fp0wc/\nLD8/X01NTV1dXfQV7Ozs9u/fLzkLEQQZPHjw4MGDJfT6VlZWN2/ejI2NtbOzQxAEQkilUidP\nnrx48WL+pqd4WbRoUXJyMh4lmjNnjoyMzL59+8LCwsrLy2NjYwsKClAUFXyrlZWV37x58/Tp\n0xkzZiQlJV24cKGlpeX58+eqqqolJSUoira0tAQFBT1+/LhN4UNRnj17Zm9vLzrOYDD69u37\n7NmzQYMGie1q/y88Hi89Pf3GjRvPnz/ncrn29vYhISFkMrnNg+fPn3/+/Hk3NzcAgJ2dXVVV\nVU5OTmJi4ocPH5YsWYIgSGBg4OHDh7tulbm5eVpaGgCgsbFR0JhFixYFBgZaWFgsXrxYU1NT\nX18f/0gsXry4paWFTqeLq4ZJSu+ibcfOwcGhg+c3NTXhuueSBpepa/+LrH2d4V5JOz5fTc3/\nXD2+23f3Ljh6FJSUgOZmAAR8PiG3r08fQKN183VI6Wb+/vvvIUOGaGpqBgUFaWpqFhUVHTp0\naNeuXRcvXjQzM+tp676P5cuXKysr//rrrxMnTmSxWFVVVSwWa/ny5bGxsfxjCAQCj8dr8/TW\n1lZxqcX2FGZmZjdu3KipqcnPz5eVle3bt6+EXDoAQHJycmJiIoVCYTAYp06dOnr06ODBg3ft\n2qWtrR0bGzt8+PDU1NR+/foJ1vx6e3vPmjULQRAtLa1p06apqqoePXrU0dHx9evXBgYG4eHh\nW7dulZeXX7Nmzdq1aztiA4ZhX/syb2lpwdU9JMGHDx/8/f1zcnI8PT319fXfvHkTFxe3bNmy\n06dP6+rqih7PZDIzMzODgoKKi4vV1NQAAEQiccSIEadPn2az2QAAFotVW1srRguFXMyAgAA1\nNbX79++fO3cuKSkJw7CXL18uW7Zs+/btCgoKZWVljx49ys7OxmsppPyHgG1txRL+L4JfIoKq\n4nJyclwut3tCi/Hx8QwGo7CwsP1jQG/cihU71dUwNxemp8MtW2B8PAwPhwMHQm1tSCD8b29X\nXh4aGcGBA+GkSXDZMrhnD7x0Cb54AX/S/p7/NT59+qSqqjpx4kTB6tSmpqaQkBAdHZ0fJ0Xp\nu6ivr8/NzT1+/Pg///wjegmPHj0CABQUFIie6OXlNXz48I7r9z558iQ+Pn7w4MEeHh6//PKL\nYPOun57NmzdjGMbhcJqbm0tLS9XU1JydnU1MTMzNzRsaGvr06ePg4ECj0UQ1gSMiIhAE8fT0\nBADgJaJPnz41NTXFRVIAAEQi0czMrINmxMfHOzg4iI6XlpYSCATJ/Y/4+PiYmpq+fv2aP/Lx\n40cfHx99ff12/mqysrIIBMLff//98OFDoa6GoaGh2traMTExK1asyMnJkYTNFRUV/Bs0/wFG\n6ElGQUHhP/Ux7h5+5K3Yb+fYVVdXu7q6xsbG3r9/v76+HkJYW1ublZUVEhLi4eHRbcqoTU1N\nlpaWNjY27aSVSB27b9DUBN++hbm58MgRuGYNjI+HI0ZAZ2eorQ1R9F+fz9oa+voK+3yS78Mo\nRVzs3LlTWVlZ1JX58OEDg8FIS0vrEaskjbOz86BBg/h3Vh6Pt27dOhaLhd/bCARCv3797t69\n2/6LbNq0iUgkOjs7z549e968eT4+PgQCYerUqd1WfZyfn7948eKQkJBx48alpqaWlpZ2z7oQ\nws+fPzOZTCcnJ35KYmFhIb7PiKIorpWooKDQZhfg+vp6JSUl/Mnfz8/PwsKCQCAMHjy4qqpq\n586dCgoKNBpNRUWlg5Y8e/aMSCRu27ZNcLC5uTkgIMDMzEy8KYx87ty5gyDIkydPhMY/fvzI\nYrF27979tRObm5tVVFRSUlIEB/GqGgCAhobGyJEjraysUBQNDAysq6sTu+W3bt1isViKiooG\nBgYWFhb4/5empmZmZubp06dnzZolJydHIBAE0yKldJ3e7dhFRkZ+TW5gyJAhbdbDS4gnT55Q\nqdRff/31awdIHbvOU18PCwrg1atwzx6YkgKnTIFDhkBTUygv/z+Hj0SCffpAFxcYFgbj4+H6\n9fDUKZibC9+9gz2tuCFFiKioqK91RPDy8oqPj+9me7qH58+fczgcS0vLrVu33rx509vbm0Qi\noSg6derUysrKzMzM4OBgCoVy/fr1r71CRkYGgUAQuoVnZmbiym2SvwKYkpJCIBCsra0nT548\nZswYPT09Op1++PDhblgaQnj+/Hk8e09IOPDZs2c+Pj4WFhaurq4zZ8782ukHDhzA2x5ERUWt\nXr0a9/9evHjB4XDmzp2roqKio6PTcWO2bt1KIBBCQ0MPHjx47dq1P/74w9raWklJKS8vr9MX\n2D4rV640Nzdvcyo0NHTs2LHtnHvw4EEMw37//Xc89sHj8aytrWVkZPT19fnPVw8fPtTR0fna\nHyaE8OPHj+np6UuXLt24ceONGze+y3+tqKhYtGiRn58fhmFEIjE5OTkkJARFUf6GG4qiffr0\n6fgLSvkmvduxU1JSwiu6RVmxYoWSkpKkTGuLjx8/Vn1d/uPatWtLly4V+6L/CceuHerq4JMn\n8MIFuHMnTEqC48dDb29oZATp9P/5fEQi5HKhkxMMDIRTp8Lly+HevfDaNfjsGRTpoSmlGxg3\nblxERESbU/7+/tOmTetme7qNsrKyqKgobW1tPGPEyspKqBgzKipKR0en+SspB15eXm3ev1NT\nU1VVVSUdtNu9ezeZTOYXV0IIeTwe3olVQrt4QuzcuVNbW3vHjh1sNht3UPisXbvWxMREXl5e\nSK9YCG1tbQCApaXl9u3b9+/fP336dDk5OR8fH3wLNSQk5LvswbvxcjgcAoGgp6cXFRX19u3b\nzlxYx5g3b97AgQPbnJo2bZq/v3/7p+/du5fFYpFIJGNjYzwBsX///kIB1wcPHqAo2qbM8v79\n+5lMpqysrIODg7GxMZFINDc3Fw0fts+TJ08AAHPmzDE2NsYVjNlstpqaGi7ZDQDokabSPys/\nsmP37SzU2tra9+/ftzlVVVUl3szQbyLbbqVnv3798Oi3FHFCowFDQ2Bo2MbUp0+gpAS8ewfe\nvgVv3oDSUvDqFcjOBm/fgrIygCezM5lATQ2oqQEVlTb+pVC6+Wr+C+jo6Bw/frzNqUePHnl4\neHSzPd0Gm83etGkTACA8PLyhoeHo0aNCByxatGjbtm23bt3CdxiFuHnz5oEDB0THhw8fHhcX\nV1RUpN1mGZOYWLhw4bx58/z9/fkjCILMnj07Nzd38eLFJ0+elNzSOHJyctXV1YGBgb/99tus\nWbPWrVvHz6h+//59ZWUlnU4XNE+U6OjoRYsW3b9/f/bs2VQq1djYeNWqVWZmZg4ODq2trWw2\nOz09vV+/fm12wPvy5cv169cfPXokIyNjamrq6urq7Oycnp4OAGhtbSUQCJK4ZEFUVVVfvnzZ\n5tTLly+5XG77p48ePTogIODvv//Oz88/c+ZMfX19RkaG0DFmZmYWFhaXLl2ytrYWHD916tSY\nMWOWLl06depUvJNHWVnZ5MmTBwwYcP/+/Y5Xsr958wYAUFlZ+eLFCxaLBSGk0Wju7u6ysrKn\nTp0qKioaMmRIfX19b68lkvJt4LcidpaWlmpqaqKPjLdv31ZWVv5a7Ppn4r8esesczc3wzRuY\nnQ1PnIDr1sGEBDhmDPTygiYmkMX6X6gPAMhiQWNj6OUFIyJgQgJcuxampcGsLFhUBP9vzEBK\nx3n69CmGYadOnRIa37t3L5lMFswN/1lxdHT8WvBeT09v69atouMtLS0Igty4cUN0qqamBgAg\nWjEgRoqKisBXij/S0tJkZWUltzSf8vJyDMPOnTt3/fp1WVlZJyenNWvWnDp1KjU1lUqlUiiU\nNrPrBPnw4QObzXZzc1NSUsIwTE9Pj+/D0el0Y2NjOp0uJycnmq928uRJJSUlGo1ma2trampK\nIpGMjIzE+4a3tra2H3MtKirCMOzs2bNC48+fPyeTyd8lnhcaGjpp0qQ2p/z8/IS2s3k8no6O\nzpw5c4SObGpqMjMzw9WGO0hOTg4AgM1mEwgEKpUaHx/PL5/C+9gCAEaPHt3xF5TSDj9yxO7b\njt3p06fxpyVdXV1PT08/Pz9PT0+89htBEL5q5U+M1LETPw0NsKgI3rwJ09I64/a9fAk7XOT4\n32TBggUyMjKrVq3Cd69ev369ePFiMpmcmpra06Z1B66ursnJyW1OaWpq7tq1q80pNTW17du3\ni47fvn0bQRCJdmfCRaParEW7ceMGgiBibL/bDjExMerq6nl5eUVFRVFRUebm5rKysiwWi0Kh\n4L2zvklubi4uKOjr6+vl5UUmk1EUxXda8PgfhmEoiu7du5d/ypUrVzAMS0xM5KejvX//Pjg4\nmMVidf0hpLm5ec2aNba2tjQajU6n29vbb9q06Wvpa7/++qu8vPyJEyf4LmB2draurq6Pj893\nLTpt2rQhQ4a0OWVlZSX0yIHvnxYXF9eLPMquWbPGwMCg4+s2NTXhb6+ioqJQuzkTExM8Fkgk\nEjteId49FBQUHDt2LC0trc3WeT8svduxgxBmZmYOGjSIIrBrRiKR3N3dz58/31129iRSx667\n6aDbx2RCQ0Po7g7DwuCMGXDlSvjnn/DSJZiXB//zHRJ5PN4ff/yBi2nhX+hqamp79uzpabu6\nialTp7q7u4uOFxYWIgjytVBQbGyshYWFkGIFhDAkJMTNzU38VgpQWloKALh//77o1J49e9hs\ntkRXhxB+/vwZQtjQ0DBixAgikTho0KAZM2aEh4dzuVwVFZXvagH84cOHtWvXhoeHa2lpMRgM\nKpUaEBDAb5tx9OhRJpNJJpP5AiKWlpbR0dFCL9LS0uLg4DBx4sSuXFRDQ4OnpyeLxUpKSjp3\n7txff/01f/58JpPp5+fXprpCa2trQkICiURSUFCwt7dXVVVFEGT06NHf++X/119/USgUwQ7C\nOPfv30dRVKg0e8OGDQiCKCoqAgDU1dVDQ0P5gdtTp059b7A2ODgY/5Pnl/vweLzx48cjCGJp\naYm71z+O9El+fj6usScvL48nJtrZ2UmuPka89HrHDqe1tfXNmzcFBQUlJSVfyz7+KZE6dj8W\nDQ2wuBjeugVPnoQbNsAFC+CECdDXF9rYQDU1SCT+W8arrg7t7KCfH5w0CSYmwk2b4MmT8NYt\nWFwMe6eW2/fS0tJSUFBw8eLFwsJCCYlE/Jg8evQIwzChLT/8Nu/k5PS1s3DlNm9v7+fPn+Mj\n5eXlkyZNolKpbSa8ixcbG5vJkycLDba2tjo7O0dGRkpo0RcvXvj5+eHJ9QiCyMrKhoSEpKWl\nzZo1y9fXNzIycv369Z3WtDI3N8fFPng83pMnTxISEoYMGeLp6Tl69GgAQEJCAoQQTwt7+PCh\n6Ok7d+5UVVXtytUlJSVxOByhbq3Pnz9XVFT8/fffv3ZWaWlpWlra8uXLDxw4wP8kfBc8Hq9f\nv37m5uaCp9+/f19bW3vkyJGCR+7fvx/fENuxY8etW7f27t07YMAAOp2O+17btm373lLW1tZW\n/EFOXl5+0KBB/fv3xyMyGIbxNZa9vb1Fo4PdT1FRkZKSkp+f37Nnz/CR58+fDx8+nMVitS9Y\n+4Pwkzh2tbW1eXl5Nf+9/qRSx66XUV4OHz2CFy7APXvg8uVw+nQYGgr79YOGhlBO7t+An4IC\nNDKCHh5w9Gg4cyZMTYX79sGMDPj4Mayu7ulrkNJVNm7ciOtl/Pnnn+fPn1+9erWRkRGXy8Xl\nc7/G8+fPXVxcAADKysqampoAAH19/aysrG4w+OrVq0Qicf78+YI7kqGhoQoKCl1vJN8mOTk5\nMjIyKIqamJjMmjVrzpw5eOdGOTk5sWyK4SKC+fn5GzZsIBKJ2traRkZG6urqKioqAAA8u//O\nnTtf+3a9evUqiqKdLkZubW3lcDibNm0SnVq5cqW2tnbnXraDVFVVeXp6Yhhma2sbGBhoaWmJ\nouiIESM+CwgFvHnzRkZGZuXKlYqKiuvXr8cHeTzelClTNDQ0vnz5MmDAgPZlVtpk6dKlAAAZ\nGRkKhYIrnkRGRj59+pTNZuO74Ww2e9SoUWK71M4SFhbm4uIiFCRqaWnp379/O6IwPw693rG7\ndu0av4qHn0Pq6+t7+fLl7rCxp5E6dj8VDQ3/U2nGO3MkJsKpU/8VauYH/MhkyOH8T6s5PBzG\nx8M1a+CRIzAzE754ASXWfF2KGMnKyho2bJiGhgaJRMLz0CsrKzty4pMnTw4fPvznn3/m5uZ2\nZ6QzPT1dWVmZRqPZ2NjgNQQGBgYdTG77XpqamrS0tDAMW7hwoeD4li1bUBQ1MDDoelafuro6\nhmGXLl3CMIzL5SoqKkZGRqakpERGRuJ3k8TExMLCQgDAy5cvRU8/fPiwgoJCp1cvKysDALSp\nGIJ7k7W1tZ1+8Q5y48aN33//PTY2NjU19c6dO0KzS5cuNTAw4PF4a9asodPpFy9exMfr6uro\ndHpAQACVSu2Eh93a2spkMgEANjY2CILMmjVr/PjxMjIyDAZDV1eXy+XevXuXQCDgpTB1dXU9\nsv/W0tJCo9G2b98umvlw+vRpKpUqOv6j0bsdu9u3b5NIJAaD4e3tzXfsKioqVFRUSCTSj3lV\n4kXq2P2HaG2FpaXwwQN49izcvRsuXvw/t8/FBerpQRrt34Afmw1NTeGgQXDsWDhvHly/Hp48\nCbOz4Zs3Urfvx4fH45WVlXVbP4mO8/nz57Nnz/7+++/r1q27evWq5GomLly4gGGYvr6+qOdq\nYWGBoujVq1e7uMTQoUMRBOnfv7+ysrKLi0v1/w+Eb9u2jUqlEolEAoGwePFiOp1uZ2e3YcOG\niooKwdMDAgICAgI6vTq+yStYaFxbW7tx48bIyEg8KHvw4MGe/QCEhobiSYQ8Hi8+Ph5BEAcH\nhylTpoSFhVEoFCqVKlqi20GeP3+Ob8iiKCovL6+kpEQgEPT19TEMwxvPODo62tra4jFpEolk\nZWW1Y8eObns3njx5MmjQINy5xzDM0tJSsArz+fPnAICSkpLuMabT9G7HbsiQIRoaGiUlJXh6\nLz9iV15erqGh8bXan58JqWMn5V/q6uCzZ/DGDXj48P/asoWHwwEDoJHRv/u8KAo5HGhlBf38\nYHQ0TEmBe/bAK1dgfr5UsbnHuX37tre3N51OBwDQaLQBAwZ0z07rj8bKlSuZTGZsbKzo1MyZ\nM+Xk5FauXNnFJfBSXwRBCAQCv7712rVrcnJy5ubm+vr6AAAVFRUnJycCgcBms/n97lpbW5cs\nWUIkEr/ZAq4dWlpamEzmgQMH+MZwuVxVVdWIiIhBgwaRyWQKheLl5dWDX+zBwcFTpkzh//rg\nwYPk5OTg4OCJEyfq6+vPmjWrKy/+8uVLvByBwWBwOBwymaygoLBv3z4I4du3bxkMBpPJ3LZt\n2507dy5fvjx//nwajRYZGdkNvl12djaNRvPy8gIAHDp06Pr16/Hx8SQSKTExET8gNzcXAPDj\nJ331bseOxWLh5dlCjh2EcMmSJfLy8t1gZc8ideykdJTPn2FBAbx+He7fD1euhNOmwaAg6OQE\n1dUhhv1bzGtsDAcPhhMnwoUL4e7dMCMDFhbCH37r4Sfg+PHjGIaFhIScOXPm8ePHZ8+eDQ8P\nxzCMf/v/77BgwQIKhaKjo2NraxsaGrpjxw5+oSiu+rFkyZKur4Lfv4lEYmhoaHR0tLOzM4qi\nPj4+CILgMrnDhg2DECYnJxMIBHV1dXxWT09PLE2NY2NjDQ0NP378+OHDBw6HExYWVl9fX1VV\npa2tPXv27JcvX+rr6/dItllxcXFhYWFiYqKVlZXobGNjo7y8fNc/k3PnzrWxsdmxY8fq1avP\nnz//6dOnK1eujBs3jslkEggEQ0NDwfLY3NxcCoUiaf2y5uZmPT093IO0sLDgq/edOXMGRVF8\nt3r+/PlGRkYSNUMs9G7HDsMw3M0Xdex27dpFJBK7wcqeRerYSREDra3w7Vv499/w+HG4di2c\nNQuOGgWdnSGXCwkECABEEKiqCh0dYXAwjI+Hf/wBz52DT5/+Rwp4u4Gqqip5eXlRfbsVK1Yw\nGIyysrIesapHyMjIwIslSSSSubm5g4MDk8m0tbXFcxBdXFzIZLJY7vEfP35EURRFUXNzc3t7\ne19f3759+woq5CMIEhoa2tzc/OTJk5SUFC6Xy+VyV61aJZb/jqqqKiMjIyMjo/DwcDU1tfz8\n/P379+vp6VlYWOAJdrhCYZu60JKgrq5uxowZfNFmvJTByclJqOZ6/vz5SkpKXU8BvHTpEolE\nwmOlPB7vl19+IRAIDAZD8M0XrNKNjo728vLq4qLtk5GRQSQS8Y/ZgQMHKBQK36Pw8vKKiYm5\ndOkSlUrtFcJMvduxU1dXnzt3LmzLsZswYYKmpqbkjexhpI6dFMnS3AxfvYI3bsA//4QpKXDS\nJOjlBfX0IIn0r8Pn4gIjIuDChXDvXnjrFvy/2UhSOsK2bds4HI5oqnhra2ufPn34ul8/PXl5\neQQCgUwmU6lUAICPjw+Xy1VTUzM0NPTx8Tl27BiKokwmU1y1BY6OjhiGeXh4qKqqslgsBEEw\n7N9WlniLen7g6sSJE3Q6XSzr4tTU1ERFRfFXlJOTmzp1quClaWhofK0Zunipq6uztbXV0tIy\nNjZmMBgRERFTpkzBnTwURadPn/769evLly+PHj0aw7D09PSur8jj8VxcXOzs7EpLS7ds2UIm\nkwkEAr4igUDgC9OGh4fjx+/fv7+L+jLfZOPGjcbGxvxf582bRyAQfHx8Fi78f+ydd1hT2dPH\nzy3pDRJ6L9IE6QiIFOkiih0UVFRsK9a1dyyIFRXFzloRuyiiou7asCIqNmyAiBQVUIrU5Lx/\nnN28/AAVNUHUfB4fn3DuzZ25oWQyZ2a+EV26dBEIBARBTJ8+Xao+SIq2HNh9WSvWz88vNja2\nd+/eampq4sXS0tL169dv3759zJgxXyTMpoQAACAASURBVLyCDBkyPgdJAm1toK0NnJ3/Z10k\nAvn5ICcHZGeDrCzw4gVISQEvXoDCQgAA4PGAgcG//wwN//1fTu6H3MFPwcOHDzt27NgwqkDg\nOO7g4PDw4cMf4lUrAyHs1q0bhUKxsrK6ffs2ACA5OZlCoSgoKLx9+/bx48enT58GAGzZsqVh\naud7iI6OdnBwKC8vP3z4sJOTE0EQWlpaWVlZFAqlvr7e1NT0wYMH6enpGzZsGDt2rLKyckVF\nRU1NDY1Gk4h1OTm52NjYR48eWVlZTZo0SUtLKz8/f8WKFTdv3iwoKEDpw3fv3knE1udZvnx5\nUVGRl5fXmTNnVq1ahWGYkZHR4sWLO3bs+Pbt2zVr1qxZs4ZKpTo5OV2+fNnBweH7LWIYdujQ\noYCAAAMDA5FIVFtbi+N4ZWUlhmHZ2dnq6up37tzx8PDYvXv33LlzDQwMMAyDEH6/3c+7JEIa\n4gAAABYtWtStW7fdu3efP38+JyeHwWAcP368U6dOUvXhtwB+KWNXUFCgqalJkqS1tTUAwNLS\n0tLSEv3WaWlp/Q77F7KMnYy2RWUlzMiAhw/DqCgYFgZdXaGa2r8FfEpK0NUVjhgBV62Cp09D\n6cw/+0mZNGkSquhqSlBQUNPhwL8kJ0+ebPQWgHJmYvh8/pkzZyRrdMyYMWgMLwCASqWiLUgk\nt+Du7o4Ex1C59r59+6RRtz1w4MDBgwdDCM+dO8dkMtlsNovFEggEurq6GIbp6OgUFRVJ3Ggj\ndHR0IiIicBzHMExOTs7AwIAkSQUFhYkTJzKZzJ49e/r5+TWrh/Gd1NfXx8XFAQAIgmjXrt3G\njRtxHL9+/To6evbsWQCAp6cnhHD8+PEeHh4Sd6Ahly9fJkmy2bDBzc1twoQJUrUuWdpyxq5F\nc+yKiorGjBmDpk0iFBQUxowZ0wq/DG0BWWAn4yegrAympcH4eDh3LuzfH5qb/7uTy+FAOzsY\nGgqXL4enTsE2P0RAemzbtu0334qtrKxEMlkYhl24cKGqqurq1at+fn58Pn/06NEAABqN9v3N\nsE0RiURLly5FsZ24wszMzAzNKqutrUWx3alTp9zd3YODgyXuQEJCAofDuX79OkmSFArFxMSk\na9euQ4cORXpWysrK0q4tq6qqAgDo6uoCADZu3Hjr1q2KiorKysrly5ejFHJUVJSWlpaUrOfk\n5KDX/ObNmxBCPz8/Q0NDLy8vTU1NLS0tAACTyczIyGAymXv37pWSDwiUow0KCmo0ZGf//v0E\nQdy7d0+q1iXLTx/YIdDkp2fPnv0OWbqGyAI7GT8ldXXwyRN45AiMjITBwdDKCtJoEAAoLw9d\nXODYsXDLFnjzJmxjiuDSo6SkhM/nL1iwoNH68uXLORzO7/AxdfHixWiD1cDAQLwoFAp9fX19\nfHyQsrD0+iJdXV0BAJ06dTI3N0ftyREREa9fvz5//ryqqiqGYXw+n8vlfpuK1+cRCoXOzs7i\nrCHKF5IkiWGYr68vetCsUK+kqK2tRWNfUOYMPQ4ODn779u3MmTMBAGvWrFFUVJSS9erqamS6\nvLy8urrazc0Nx3ElJaUxY8b069cPJVBpNNqAAQNaYdzJnTt35OXlO3fuvGfPnrS0tKSkJFQE\nuWLFCmmbliy/SGDXlFevXjXspfhVkQV2Mn4R6urgw4dw/344Zw4MCIC6uhAASBCwfXs4YABc\ntgyePQtbps3wk3Ls2DEKhdK/f//jx48/ePAgKSkJ1aonJCT8QK8eP3588ODBhISE+/fvS/Wd\n1dTUFOWoaDSaWKATQnjt2jUcx5EOfUFBgZSsT5kyBQAgJye3e/duCOHu3btRSQ8KLBBotJY0\naFS1htKWBEFQqdS+ffsymcyNGzdKyTSEMDs7G8MwND3x3r17ZWVlKSkpVlZWJiYm0dHRGIaF\nhITY29tLz4H27dsDALKysmbMmKGurn7r1q3hw4ej77g4zD148KD0HGhIdnb2oEGDUNU+h8Nx\ndXX9GQOJnzuwEwgETk5OL1++bHpo69atqErv10YW2Mn4ZSkthRcuwLVr4dCh0NLyX0U1bW3Y\nsydcuBCePAl/ufT8rVu3unbtivb+OByOl5fX1atXf5QzmZmZKNJSUFBACTMLCwspaYhBCOl0\n+vjx4wEAHTp00NLSOnXqFNqYLioqEkc80pOHz87ORiaSk5Orqqqsra3bt28/adIkRUVFAIBY\nq/7ixYsSN52YmIhM29vbR0ZGzpgxY/r06RYWFkwmk8Viob5daexBi+nXrx+VSmUwGGj2Clos\nKyvT09PjcDhcLpfH461atUp6DiAVNUVFRQ6Hs3PnTpFIdO/ePS8vLwaDwWQyPT09x40b5+Li\nIiXr5eXlSE9l48aNqamp4k8v5eXlbVD9pYX83IGduKiuqTKsLLCTIeOXoqYGpqXBrVvhmDHQ\n3h7S6RAAqKEBAwJ+vTjvzZs3P/ZNJTc3V1lZ2d/fX7z5+PLlywEDBvB4vGYVTr8fHo+3bds2\n1MHg4eFBoVBoNJqmpibKmXG5XCqVKg27YlAHHoVCMTc353A4nTp1EjdSeHh4oAcCgUDidlG+\nCl1fXV09ICDg+vXr1dXVHTt2BAAwGAzUQCpxu4iKigoqlWpqampmZsZkMikUSpcuXbZs2bJg\nwQI2m42k1dq1aye9kBrRs2dP9CKIJ93IycnR6XSCIM6ePXvixAkmkykNuwcOHBAIBCwWy87O\nztjYmCRJS0tLKf2EtyZtObDDQQsIDw/ncrk+Pj7Lly9vyfkyZMj4BgoLC0+cOBETE5OUlNQw\nidJq3LhzZ3Na2rLi4uO+vh/OnAHl5eDuXRARAdTVwcmToE8foKICNDRAQABYuBAkJYHXr1vf\nSUmhqKjYcBOw9Zk3b56ent7Ro0fbtWuHVrS0tPbu3dupU6fp06dLw6Ktre3t27c1NDQAANev\nXwcACASCwsJCHMcpFEpFRYWbm5s07Io5dOgQjUYTiUQZGRnl5eVXr17FcZwgCBUVlZs3b1Io\nlI4dOxYXF8+bN0+CRu/fv//48WPwn7jZhAkT6HR6586d9+3bFx0dDQCoqqrCcdzT01OCRhuS\nl5dXW1vr7u5OkuS6devat29/6dKlkSNHLly4sLKysq6uTiQSJSUliQfLSYlDhw6hMkcMw5C4\nBYvFqqurW758uaenJ4PBQD25kjV68uTJgQMHTp48ubi4+ObNm48fP87NzdXS0vLw8Pghf+J+\nF2ALMnZbt24tKSnp2rUrAKB3797i6Y6yjJ0MGRKhtrZ28uTJFAqFy+WamZlxOBwqlTp16tSm\nLZxS4sWLFw4ODkgp3MHBgcvlcrncxoNb6+rg3bswLg6OHQsdHCCT+e+AFR8fOGMG3L8fZmZC\nqYnW/2KIRCIej9dsbd/Zs2cpFEqlFGSFExMTqVTq2rVrCYJgMpkhISFz5syZNWsWi8XCcZzN\nZpeUlEjcKISwsrIyMTExMjIyKipq8eLFqHsAAIBhGBo+0q1bN4IgRowYERwcDABgMpmSSqai\nNkyxxoOysrK6uvqxY8fWrl1Lo9HQBiUAoE+fPhIx1yxoD/rq1ascDmfy5Mn19fUQwpycnFOn\nTs2fPx8AMHToUOlZb0hJSQmO4127drW1tXV2dv7jjz/E+/6rV682MjKSuEUjI6MpU6Y0Wqyt\nrbWwsJg0aZLEzbUmbTlj19LADkIoFArnzZuHYZixsfHjx4+hLLCTIUNChIWFKSkpnThxAr2f\nffz4MSEhQVFRccyYMa1g/f379zo6Op6enmKl9tra2rVr135BRLW+Hj58CPfsgX/+Cd3dIZ8P\nAYAMBrSzg2FhcO1aePYszMtrBf8lxcePH1NSUtasWbNly5br169LdaP2/fv3AIBmy+lyc3MB\nAM+fP5eG3ZkzZ5Ik6efnJy8v3/ATvpWVlZT6gpOTk5WVldHGq729PYvFUlBQQL0LSkpKHA6n\nXbt2FAplzZo1EMKamhqkIbtjxw6JWEcaVnQ6ncFgDBkyRF5eXkdHh0KhkCQpHlVNp9Olug0q\nFAqVlZU3btx47tw5eXl5Y2PjsWPHRkRE9OvXjyRJHo8njSD+U/j7+3t6etb/7wew4uJibW3t\npg3j38nTp08BAC9evGh6KCYmpmFr9s/ILxLYIZKSkuTk5DgczuHDh2WBnQwZ3096ejqO49eu\nXUPbIkZGRiilgWZA3LhxQ9oOLFiwQF9f/2OTuSeLFy9WU1Orb3kSLjcXJiXByEgYGAjbt/+3\nFYPHgx07wtBQGBUFExPh06dQClNYv59jx44pKSnR6XQrKysDAwOCIKytrdEnWGmAZAD++eef\npocyMjIAANIbv5KSktK3b18DAwN1dXUrK6spU6Z8+PABQpiXl5ecnLxr1660tDQ0Ye77uXbt\nGpVKHTRo0JYtW1JSUt68eVNeXo5ESwEAOI57e3tHR0fn/DdJ+9ixY6hV1tnZWSIOREdHW1hY\n2NnZAQAIgpg5c6a3t3ejLfhmvwuSory8/Nq1a0FBQXw+PyMjo7CwMDIysm/fvi4uLj169KBS\nqbt27ZKe9aY8e/ZMQUHBx8cnNTX148ePpaWlSUlJ7du3t7S0rKiokKytixcvYhjWaGQdIikp\nicViSdZcK/NLBXYQwhcvXlhYWAAALC0tZYGdDBnfyfz58+3t7Wtra319fRUVFVesWJGamnrr\n1q3Y2Fgajaaqqvr+/XupOmBra7t48eKm6+/evcMwDA01/RZqa+GjR/DwYbhkCQwOhjY2kMWC\nAECShLq60MMDjhwJo6Lg3r3w0iX4/DmUcvH4Z0hJSSFJcv78+eLcyevXr7t3766qqiq9sZ2O\njo7NjtpfuHBhKyczSkpKBgwYgOM4i8VCFXgaGhrHjh37/isbGhpSqVQkI0aj0SgUSnh4eFVV\nlYuLC9qKbfhx4uHDhyoqKg4ODhiGKSsrf791COHKlSttbW0TEhIoFAoqJeRyuRYWFhoaGii8\nc3JykoihptTV1c2ePZvJZOI4jjp/MQxzd3ePi4vbsmVLaGgohUIZP368lKx/hmfPnvn4+KDA\nGgBAoVCGDRtWWloqcUP37t371EeUuLg4DQ0NiVtsTX61wA5C+PHjx0GDBomr9H5tZIGdDKkS\nFhYWHBy8atUqRUXFrKyshod69eolJyc3duxYqTqgrq6+Z8+eZg/xeLzExESJWRKJYE4OPH8e\nbt0KZ8yA/ftDW1uoogIx7F9JNIEAdugA/fzgsGFw7lwYEwMPHYIXLsAHD2BhofRSfR06dBg3\nblyjxdraWktLS+m99aKhekePHm24eP78eSaTuW3bNikZbUpNTY2dnZ2pqWlqaipKrpSUlMyZ\nM4ckye+M7ZYtWwYAGD9+PAqX6+vrk5OTNTU1e/XqdeLECRRVuLq6RkRErF692tTUtFH9t0QE\npk6cOMFiscrLy4cNG0an0/X09NhsNo7jXC6XIAgej9cw7CgpKTl69GhkZOSmTZu+P1M+ZMgQ\nRUXFffv2odsvLi5G0TOfzzcwMOjdu/fJkye/08T38P79+2vXrqWnp0tvG7q+vl5JSalZTRdf\nX9+QkBAp2W0d2nJg11gPuynZ2dniMYZiGAzGrl27vLy8njx58sUryJAh4zPweLzXr19v3bp1\n8uTJSHRITHl5uaur665du1avXk2lUqXkgLy8/Nu3b5uuf/z4sby8vFEx1neBYUBbG2hrA3f3\n/1mvqwOFheDVK5CfD16/Bnl5oLAQpKaCwkLw9i149w6Im/V4PCAQAB4PcLlATg5wuYDBAPLy\ngMEAdPq/DwQCIBAAeXnAZAIWC8jJgc92v2ZnZ9+/f//gwYON1ikUysiRI1euXLl27VqJvQIN\nCAgIWLhwYd++fbt06WJvb0+S5K1bt86cOTN58uThw4dLw2KzbN++PTs7++HDh0pKSmhFXl5+\n0aJFEMLw8HB/f/+Ggg0tp7i4OCIiAgDw/v37wYMHGxgYeHp6du3a9cyZM1ZWVt7e3kgM/vnz\n59XV1ZmZmR8+fFBXVzczM/vnn386d+5869attWvX5uTkHDt27HvuztPTU05ObuHChdu2bXN2\ndt6wYUN+fj4AAEV7x48fF9/1pk2bpk6dSpKkiYlJcXExaifau3evtrb2N9i9fPnynj17xo0b\nd+7cuevXr5ubm/ft2zc+Pt7Dw2P8+PGpqakoh/cD4fF4jYY2SxyCIGbPnj1r1iwTExNx07FI\nJIqIiPjnn39u374tVeu/M80HdoWFhTQaDf1Bp9PpFRUVFRUVTU/z8vLy8vKSroMyZPzqODs7\nb9q0qaqqysnJqeF6YWFhamrqxo0bExMTc3NzxUMxJI6bm9v+/fsnTJjQqPbo0KFDTCbT1tZW\nSnb/HwoFaGoCTc3mj4pEoLgYvHsH3r4FxcWgtBS8fw/KysCHD6CsDJSWglevQHU1KCsDFRWg\nogIUF4Pq6v+5AoMBmEzA4wF5eSAnB3g8ICcH5OSAvDyQl697984HAP3ycvDmDfjvbR6hp6f3\nWpojXWbMmOHj47Nr1y7Uq4EGYXTq1El6Fpty5MiRwYMHK/3vjQMAJk+eHBUVdfPmTTRC+WvZ\ntm0bSmnk5eWZmpqmpaWtWrWqW7du8fHxfn5+J06cIEnSwsLixYsXaK+fzWYXFRURBLF79+7w\n8PDx48dnZGQkJiZeuHDhe4aw0On07du39+jRIz8/f9SoUUlJSXl5eYmJiStWrJg5cybaEQYA\n/PXXX+PHj1+3bl1YWBhJkjU1NYWFhaGhoZ6ennfu3EGKEV/F9OnTRSLR2bNnLS0tS0pK9u/f\nP2PGjH379g0dOnT27NnJyclDhgz55pv6iRg3btzr1699fHwcHBwsLS0rKyuvXLny7t27gwcP\nNs3RypAYsLmtWACAj4+P+PEXr/BrI9uKlSFV6uvrzc3NMQxrqKtTUlLi5uZmY2ODeiSfPn0q\nPQeys7PZbPbEiRMbTle5cuWKvLz8woULpWdXilRWwvx8+Pw5TEuDFy/CU6fggQNw61a4YgWc\nMweGh8OQEOjvD52coIlJnUBQizaCAYA0GtTTg87OMDgYzpp1cfx4O6kpeLYRDA0Nt2zZ0uwh\nFRWVbxNbKysr4/F4AoHA2tpavKP66NEjHR2d0NBQpGrl7u6ekZHB4/HQQMFly5YlJSXt3LkT\nzV4B/1WAMRiM75e6un79uouLi7gN1tDQcOfOneKjNTU1ioqKK1euLCwsHD16tJ6eHo7j8vLy\nbm5uSkpK36BytmXLFhzHu3fv3tDEpEmTWCzW06dPXV1dJd5/2sa5e/fuggUL+vbtO3To0Ojo\n6F9Dl/nn24oNDAxEjRHo8feHjzJkyPgUBEEcP37cyMioT58+vXv31tXVzcrKOnXqlJqaWnJy\n8vXr1zkcjpaWlvQc0NHRSUxMDAwMPHLkSOfOneXl5TMyMlJTU0ePHj179mzp2ZUiTCZgMlt4\nLiYUaqirL5gwYXT37v9uB796BV6/BqmptqmpN+vrgaIisLYGVlb//t+u3ef3dn8u2Gw2mr3S\nCKFQWFZW9g3JKgDA9u3bkcz8okWLAgICTE1NR4wYYWJisnv3bhcXF2tr6/z8/Pj4+A4dOly9\nehVppIpnMmMY1rFjx86dOxcVFcXHx9fW1g4YMODDhw/fsz1tb29/8eLFmpqaFy9eqKmpycnJ\nNTx648aNkpKSLl26WFpaqqmpTZs2jcfjZWRkPHv27N27d5s3b54xY0bLbYlEovnz51tYWCCN\nOASVSl29evXdu3eXLl1aVlbGYrG++V5+RiwsLFDDpYxWAn6peUKGLGMnoxWIjIzkcrmBgYHu\n7u5hYWFxcXHV1dWlpaXGxsatM82upKRk/fr1I0aM6Nu379y5c7+9GfYnZN26dWw2u6Fqokgk\nioyMpFGpj44ehXv3wilToIcHlJeHAEAuF7q6whkz4PHj8O3bH+i2RBg3blyznaGnT58mSfLt\nN91gQEBAYGAghmGZmZmbN2+m0WhGRkYhISEDBgwgSRLDsODgYPHJdnZ2fD7/4sWLysrKjfLW\nKioqDAZDX1+fw+G8e/fuGzxpCfv371dSUnJwcPDz89uzZw/qC0YRLYVCAQBcv3695Ve7f/8+\nAGDRokVaWlqNpsZs3bpVTU2NIIjLly9L+iZktDZtOWMnC+y+jCywk9EK1NTUeHp6KisrR0dH\n37hxIz09fcuWLfr6+h06dJDGJAIZDRGJRNOmTcNxvHPnzuPGjQsLCzMyMmKz2c3oh2ZlwcOH\n4cyZ0NX1X+0NQ0MYGgp37IDZ2eKzDh8+3LNnT319fX19/YCAgMOHD7fm7XwVz549o9PpCxcu\nbDiQ+cWLF7q6uiNHjvy2azo5OY0YMcLR0dHGxubNmze5ubnR0dFhYWFhYWEsFovFYjX8kR4/\nfjyGYTExMUjpS7yOtM78/f1JkpSXl2+4eSpZUlJSqFQqhmGRkZEUCiUiIiI/Px9C+P79+379\n+mEY9lWSDBcuXMAwrLi4WElJadSoUQ3LGw4cOEAQhKOj448VKW4hpaWlxcXFP9qLtktbDuww\nCGFMTMzWrVvRVExEy5tlamtr09PTJZtEbGts3rx59OjR5eXl37YrIUNGC6mrq1u5cmVcXFxW\nVpZIJNLU1AwMDJw/f77sB691uHPnzpEjRx49esRkMs3NzUNCQlRVVT/3hPp6cPcuuHoVpKaC\nixdBURHQ0YEuLnFZWStv3eo8aJC9vT0A4ObNm7t37w4MDIyLi0N1Y22NxMTEkJAQQ0NDDw8P\ngUBw//79Y8eO2draBgcH5+bmqqmp2draohm/XyQzMzM8PPz8+fPoSxzHqVRq//79TU1NX79+\nferUqRcvXkRERMyZM0f8lOLiYiRNwWaze/XqtW7dOgDAx48fO3XqlJGRkZGRERYW9vbt25CQ\nENRmK3HKy8sVFBTYbHZ9ff2SJUvCw8PRukgksrW1hRDeu3fv4sWLzs7OLblaZmamiYnJy5cv\n8/LyevTooaqq6u/vr6Gh8ezZsx07dnz8+DErKwslBSWOUCiMjY3du3fvo0ePcBw3NTUNDQ0d\nPnz4V/3UVVVVLVmyZOfOnXl5eQAAVVXVkJCQ+fPn/27bx1+ktraWRqOlpqa2crdTi4DNZeyI\n/wWloxEN++Z4PJ6mpuYPCUhbE1nGTkbLqa6u3r59+/DhwxvuqH7tRSoqKqQ9lFiG5Hn4EMbG\nPrW2LsAwCECtikpdUBDcsgVmZqanp/N4vJiYmB/t4id5+fLlnDlz/Pz8HBwcQkND0ZQTTU1N\nT0/P9u3bI4mIN2/efP4iDx48kJOT8/f3nz9/PpfLffToUUJCgpKSkqKiop2dXa9evYKCgmg0\nWtPt3S1btgAAcBzX1dWdN29ev379OBwOhmGzZ8+GEHbt2lVVVTUyMlJaNw9h9+7dcRzn8Xji\nBFtNTc2YMWN4PN6sWbN4PF54ePjnr4ByHPHx8SkpKdra2nPmzIEQFhYWzps3z9vb29TUNCAg\nQEtLa9SoUVK6herqam9vb4FAMG/evKSkpMTExJkzZ/J4vF69erVccrqystLR0VFLS2vjxo13\n7ty5d+/e1q1b9fT0rKyskDyJDDFtOWP35a3YkpISZ2fn8PDwu3fvokmGZWVlV65cCQoKcnd3\n/x3efmSBnYwWkpOT0759e4FAEBISMnfu3ODgYD6fb2ZmJtZglfFrIxKJFBUVuVyuEQAjANgD\nQBGVCgGAKiqZpqZLFRRgair8+kC/lZk2bRqfz09OThavPHnyxNraumPHjp/Xl3Nzc+vRo4dQ\nKKyrq+vYsaOlpeXDhw8LCgqUlJRWrVq1f/9+DoeDJuQ1JSgoCO2HoghPW1tbvH+tq6tLEMTZ\ns2cleI+NuHr1KjLt4uIyduzYoKAgdXV1ZWXly5cv9+nTx9TUtFu3bp95+uHDh1ESTk1NjUaj\n4TiO4/jKlSvFL1dJScnAgQMFAkGe1NSTFyxYoKqqKhZnQ2RmZvL5/NWrV7fwInPnztXU1Gyk\ntlJcXNyuXbtJkyZJzNdfgp87sBs2bNiQIUOaPdStW7fhw4dLybO2gyywk9ES6uvrLSwsPDw8\nGtYPiaeWNCuYKOMXY8SIEQCASZMmZWZmvn///vr164MHDzYgyQdTp77r3fsBABDHIY0GO3WC\nkyfDAwfg8+fw0+VWQqHwwIEDI0eOdHNzCwwMXLlyZSvUPOXl5VEolBMnTjRaLyws5PF4e/fu\n/cwTkbTx/fv3b926lZub261bNxzH9fT0tLS0SJKk0WgRERGfKi+7dOkSSZI8Hu+PP/5AGabc\n3NwRI0aoqKgAAEiSDAgIkJ5uslAoVFZW5nK5c+fO7dev38iRIzdu3Pjhw4dLly4RBNGjR4++\nfft+6rkHDx4kSXLevHnou1NXV3f+/HllZWWCIBQVFT08PDp27MhkMg0MDNLT06Xnv4qKysaN\nG5seioqKarlCnbq6emxsbNP1nTt3CgSCr5CN/g34uQM7RUXF7du3N3toxYoVir/6kCcoC+xk\ntIxjx46xWKym21UFBQUMBiMpKemHeCWj1UBBAADg0aNHDdcnT56sqamJipgLnzyBp07BefOg\nlxeUk4MAQB4PurrCiRPhX3/BtDT4n3ZqWVmZu7s7i8Xq37//ggULRo0apaenp6SkdPXqVane\nxV9//aWmptZs+BUSEvIZGajk5GQMw2g0GirUQYPcTp8+vW3btuDgYBaLVVBQ8HnTQUFBCgoK\nDAYDqeiyWCw+n49hGIPBmDp1au/evUmS3LVr1+cv8s0CWVu3bgUAuLm5JScnv3z58tatW4sW\nLWIymeHh4fr6+itWrGj2WTU1NSoqKhEREY3WX716xeVyx4wZM3fu3KioqFOnTrV8P/QbQHIa\njx8/bnroxo0bAICKioovXgRNvWk2+kQSU69fv5aAr78KbTmw+7KkWFlZWbNyQwCA4uLisrKy\nFpfzyZDxK3Pp0iUXF5emSkEqKipOTk6XL1/u1q3bD3FMRuuwe/duPz+/S5cu3b9/38TERLy+\nYMGCDRs27N+/n8vlKujrA0ND/xvPYgAAIABJREFU4Ov777GsLHDnzr//DhwA+fmAIEC7dsDc\n/NTjx6alpbuTk9U6dwY4DgCoq6sLDw/v3r37kydPBAKBlO6isLBQS0tLXEtdUFBw9OjRBw8e\nkCRZUlJSWVnZ7LMqKiomTpwIIdy1a5eHhweVSk1PT1+wYEFoaOi1a9dYLNa5c+dQ7u0z7Nix\nY8qUKRs3brx9+zaaMPLx40cajVZVVbVixQoMw5SVlcPCwlxcXJrKfP39999RUVFpaWmlpaU6\nOjru7u4RERFf1aMwfPjw9evXP3jwoE+fPlVVVRiGGRoarl279tGjRyUlJaGhoc0+KzU1taSk\nZOLEiY3WNTQ0goOD8/LyYmNjW+7DN1NfXw/+G87SCLSITvg8qMcCNqdKgBaxX2h846/Nl5tl\n2rdvHxMTc+vWrUbrN2/ejIuLMzY2lo5jMmT8ZJSVlfH5/GYPCQSCDx8+tLI/MlqZp0+f2tjY\n9O/fPyoqqrqBphmHw2nXrt2uXbv69evXWHdVTw/06QMWLwYnT4LXr0FxMTh3DoSHlxGE1oMH\n0aWlaq6ugMMBdnZg2DDK2rWxPXu253I3b94svbsQCARFRUXo8fbt2/X19VetWlVcXPz69euL\nFy9evXr16NGjTZ+1cuXKsrIykiSTkpIuX75cX1/v6uqakpJiZGQ0efLks2fP2tjYfNE0jUaL\niYnJy8ubM2cOQRBBQUEAgJqaGmNjY19fX11d3cLCwtra2kmTJjV64rp167y9vbW0tLZt23b1\n6tV58+Y9evTI0tISjZRrIRiGHT9+XE5OTlFRcdSoUTExMQMHDty0aVNcXNyhQ4eaCqYjUNcw\nl8ttesjY2Pjly5ctd+B7UFVV5fF4zaqvpqWloaNfvAiHw9HW1r58+XLTQ1euXFFSUmo4cllG\nmwZ+aSv2xIkT6I9Ru3btvLy8unfv7uXlhWQrMQw7cOBAK+UWfxyyrVgZLWHBggUODg7NHrKx\nsVm8eHEr+yOjlfH09Jw1a1ZhYaG2tnanTp0uXLhQWVlZWVl54cIFBoMhEAi+uBcpZseOHRoa\nGlAkgllZ8MQJGBkJBwyA5uaQSoUAVFAosHNn+McfcMsWmJYm2W6MZ8+eYRiWmpqalJREkuSm\nTZvQtmxZWZmSklJAQACFQmlU65abm8tgMFBXKZ1O53K5bDZ7w4YNEMLz58+TJEmSZMOxw19k\n+fLlHTp0wDBMS0uroZjerVu3UGtCw1pDlE3cs2dPwyvU19f37du3Q4cOX1vbWl5evmzZMh8f\nn3bt2rm6uk6ZMuXznU8HDx7k8/nN7lwvXLiwU6dOX2X9exg9erSZmVmj96mSkhI9Pb1p06a1\n8CKLFy9WUVF5+fJlw8WCggItLa2ZM2dKzNdfgra8FduiAcWXL1/29fWl0+nicJBKpbq5uZ0+\nfbq1/PyRyAI7GS0hPT0dx/GmJVCXL1/GcTwjI+OHePVrIBQKly5dam1traCgoKur27t37+fP\nn/9op/4foVD44sULFElUVVW9fv26d+/e+H9gGIZh2FcVWX7yb3Jd3eaJE+cYGcF582BAANTW\nhgBACgWam8MhQ+DWrTAz8/tvJzQ0VFtb28TEBO2uQghLSkp8fX0NDAyqqqqCgoK6du0qPrmi\nosLQ0BDDsPj4+PLy8s6dOysoKPj4+JAkOXjw4P79+wMAvnbGx9KlSxUUFHAcbxpUDRgwAADQ\nUMJ40qRJzs7OTS9SUFDQChoPqGVk3759J0+evHv3rlhqQiQS2dnZ/fnnn1K13pB3794ZGRl1\n6NDh0KFDL1++zM7O3rdvn6GhoYWFRVlZWQsvUl1d7eHhoaSktHz58osXL16+fHnVqlVqampO\nTk6VlZVNzxcKhceOHRs7dqyzs/PAgQPXrFnzOwzKQPz0gR1CKBTm5eU9ffr01atXUq0DbWvI\nAjsZLSQsLExJSenEiRPoE7xIJDp27JiiomLraIL9qrx//15dXR0AIBAIbGxs0PALHMfbyFi4\n48eP6+npAQAYDAYAgEajzZ07t7a2tqys7Pr165cuXfLy8urYseNXiQ0cOXKEy+XW1tY2PRQa\nGhoYGPj/X5eUwHPn4MqVcOBAqKGBRqvA/v3h+vUwI+MzLbefoaqqqkePHgAAKyur4cOHd+3a\nlcvlmpqaomA6KSmJRqOJM2ErVqzQ0NCg0Wjoc35tbW1MTIyHhweXyyUIomvXrgCAzK8MN48c\nOYLjeLNDUp2dnalUapcuXcQrnp6eaNxdU0xMTJrt8ZQgBw8eRJN70Xefy+UuWrSorq5u3rx5\nTCYzu4EYSStQXFyMtD1Q/oXD4YSHh3/t/Lna2tply5a1b98epVqNjIwWLVrU7DDO8vJyJycn\ngiBIkkQ7eBQKRU5OTnrNy22KnzuwS0xMfPDgQSu61OaQBXYyWkhtbe3kyZOpVCqXyzUzM+Nw\nOFQqderUqb/VByGJ06FDB4IgGqpylZSUGBsbYxh27969H+gYhDAhIYEkyenTp6O38PXr1xME\nQaPR7O3tk5OTV69ebWpqqq6u/uzZs6+67IcPHzgczqZNmxqt5+bmcjicffv2ffKZL17Av/6C\noaFQTw8CAFVVYWgoTEiAXzknBXVBTpkyJTg4eNq0aQcOHBBHmaiQSxwuuLq6zpw509HRsVF2\nqry8nEKhzJgxQ15evtkI9TNUVlYSBCEQCBqtHz9+nCAIOTk5R0dH8aK9vb2Hh8fgwYPDw8O3\nbdvWMDtlZmYm1ej/r7/+Qt99BwcHLpcbHBwcFBSEtt3ZbHbTkTGtA8ofZ2dnf6dwWU1NzeeH\nq/v6+uI47uTkdOzYsSdPnly5cmXWrFkEQTCZzJKSku8x/VPwcwd2dDo9KiqqFV1qc8gCOxlf\nRUFBwfHjx9etW3fixIlGoz5lfC0PHz4EADSdaov6JRtKi7Ya1dXVaFRhZWWlgoLCkiVLGh69\nefOmt7c3hmFUKtXS0vLPP/9sKrTQEjZs2ECj0davXy9+c01NTTUyMnJzc2tp3djLl3DrVtin\nD+TxIEFAR0e4cCG8cqUlNXmlpaUYhqHW1EYcO3aMyWSKgwZDQ8PNmzfHx8czGIwrV640PFNJ\nSYnP58+YMaNF3v4vpqamAICQkJBLly4VFhampaXNnTuXRqOh0AFNXRGJRNOnT0d5sqFDh/bp\n00dFRUVZWfnixYsQwpKSEiqVeu7cuW+w3hLev3/P4/Gio6MhhPX19bt37x44cKCNjY2DgwOG\nYQcPHpSS3TbC06dPAQDe3t6NwsczZ858w+b7z8jPHdh5enr6+fn9zuNVZYGdDBk/imnTpmEY\n1mzK09nZmcfjtZonQqFw3bp1JiYmqJlMQ0Oje/fuTCaz2cFpffv2HTp06Hda3Lhxo5ycHJVK\nNTY2lpOTw3E8JCTkW5Sd6urgxYtw5kxobQ0JAtLp0MUFzpoFk5Php6/m6Og4YsSIhitCoTAl\nJcXExERfXz82NhZNTbO3t0eNQePGjaNSqSNGjPjrr78SEhImTZqEYZi1tfU3SOpBCHfu3Ilh\nmIaGBtrmAwCYmJhs3769S5cuAIAdO3ZUV1evWrWKzWbHxMTgOI42gmtqasaOHcvhcHJyctDk\nv69NFrachIQEOTm5ffv2RURErF+//sqVK+IQx8/Pb+zYsVKy20aYO3cu+MRkO319fQ0NjVbw\noba29vHjxy3vSZIsP3dgV1hYOGDAAF9f3/j4+LS0tGdNaEVvfwyywE6GjB/FsGHDSJJs9lDv\n3r3pdHrruCEUCvv27SsnJ7d06dLLly+np6fHxcUpKyvTaLRmk7ILFixwdXX9frvl5eV///33\npk2bjh49KhlhutJSmJQEZ86EnTtDGg0SBLSwgOHhMD4e/u/1L1y4QJLk4sWLUUNATk6OjY0N\nSZI4jru7uxsbG+M47u/vb25uzmKxevToMW/evLi4uO7du+vo6KioqHTo0IEkyW+WyhAKhUZG\nRhiGdenSJTIy8sSJEwEBAWjQGpVKRQWXdDq9Y8eOBgYGFAoFwzAHB4fTp09nZ2cbGxvr6uoy\nGAypdk74+/vjOC4QCJydnU1NTUmStLe3z8rKghBOmzatYX+JpCgpKTlz5kxMTMyRI0devXol\n8et/FQMHDqRSqc0e8vb25nA4UrX+/PnzHj16oJ8EAICysvKSJUtaueLl5w7sWjIw5ddGFtjJ\nkPGjiIyMBAA0Kz9vaWnZaso327ZtQ6r2DRfXrVtHo9EGDBjQ9PypU6f6+vq2jm/fTlUVvHIF\nLl0K/f0hnw8BgJqacMAAuHYtPHsWvnp1+PBheXl5gUDg5ubGZDJJklRWVj5//jyE8N27d2j8\nLxpay2KxtLW12Wz2sWPHIIQ3b95UVFScPn3693hXVFRkY2OD47h4IAOGYR4eHhUVFe/fv/fz\n8wMAaGpqDh48eOHChSjKR6dRKBQ2my3VPvTNmzeTJKmhoSHey3r16pWHh4eenl55efnYsWN7\n9+4tQXMikWjZsmUsFovBYJiZmaH07fDhw1uiJyFx8vLyLl68OGjQIBzHm42lrK2tm9ZHSpCH\nDx/y+XxPT8/Tp0/n5+dnZmbGxsYqKir27NmzNbcWf+7ALjAwcNCgQcOGDRv+CVrR2x+DLLCT\nIeNH8ebNGwzDevXq1Wj96dOnOI43G1RJA0dHx6Zhyt27dzEMI0myoTowhFAkEpmbm8+bN691\nfJMMIhF88ABu3gwHD4YmJpBCgQBALrfexibb1fUvI6MwGu38tGnVN2/CgoI3BQV8Pp8kSWdn\nZxzHvb296XQ6hmEKCgoEQdjb2+M4PnTo0O/PoIhEonPnzv3xxx8Yho0aNUo8SygnJ4ckSRRT\namlpoaBz1KhRPj4+pqam8fHxSkpK3/2KfJLq6mo+nz9p0iSCIBqOfKusrNTW1l6yZImBgYFk\nC9MXL17MZrN37NghVmu9cOGCrq5ut27dJGjlixw7dkw8whbF0D179mxUY5eXl0eSpLu7u/Tc\n6Ny5c48ePRrFcJmZmWw2+4uKcxLk5w7sPkNFRcWP2t5uTWSBnQwZPxA0uqx///5oX6++vv7w\n4cNMJpPBYHxLwdk3weVyExMTxV+Wl5ffuHEjMTGxY8eOAIC///674cnz589nsVg/fLPsu6it\nhY8fw8OH4ZIlMCTkibx8KZsNaTQIAARABEAhAFkEcRvDLmHYRTr9EI7vpVI3Ylg0jRarppYz\ndizcvBnu2QNPnICpqTAzExYVwW+N82bOnNloUh1qT0FR3YYNG4RC4ZkzZ7S0tLy9vQmCGDNm\njLm5uSReheb5559/KBRKWVmZg4ODh4dHw7eG2bNna2ho8Hi8oqIiSZkrKCig0WgJCQmN1h8/\nfkyn00+ePCkpQ59H3AL85MmT+vr67OxseXl5AICXl5c4gr9x44ampiYA4Nq1a1Jy48WLFwCA\nZid1jB8/3tPTU0p2m9KWA7sva8V+hsTExClTpiD5YRkyZMiQBnv37q2rqztw4MCBAwfodHpt\nba1IJFJQUDh06NC9e/fU1NR0dXVR9ZVUQZFEdXX17NmzY2Nja2trmUxmRUUFAKB3794jR440\nMTEpKCg4efLknTt3EhISvkqotM1BoQBjY/CfYuSwzp39/PxmzZoFSktLHz/u4+ysJBL1dHHp\n5eGxbf16BzMzey2t21euFDx/rkQQzA8ftK9fBykpoKoKlJaChvKyHA5QVgYqKkBd/d//VVWB\npiZQVQUaGoDJbNaXnJychtq7xcXF58+f9/b2fvDgAYPByMnJQVnDlJQUCwsLDQ2No0ePfkra\nVSIUFhYKBAIOh5OQkODp6WlmZjZgwAAjI6P8/Pz4+Pj8/PzTp08rKSlJytzp06f5fD4a9QwA\ngBDGxcVt2LDh4cOHtbW1gYGBw4YNW7BgAQqzpERJScmECRNWrlw5YcIEtKKjo3PlyhVbW9uz\nZ88yGAwdHZ03b96UlZVhGDZ79mwHBwcpefLkyRMGg4Gaphtha2vbrN7db0iLArt3794lJCTk\n5OQ0FBKurq5OSkpCf9dkyJAhQ0qg4REvXrzYvXv37du31dTUlJWVDx065Obmhk5QUFCYNWvW\nhAkTpBfemZqapqam+vv79+/fPz09fe/evT4+PiwWa9++fSEhIWVlZSkpKQcPHlRRUbGzs9u5\nc6e+vr6UPPkhKCgo/PsBXl4+o67uAoQUKjXh778hhBFr164ZOtRm4EBHCK2srB49eqShoZGV\nlvb/T66uBqWloKTk33/v3oG8PFBYCLKyQGoqeP0aFBUBkQhdHKipAQ0NoK0N9PSAjg7Q0wO6\nuiwWq7y8XHy906dPEwRhaWkZHBw8ZMiQx48fC4VCgiCMjIy8vLxSUlLodPqff/4pvVeDz+e/\nf/++trZWW1s7PT19w4YNf//99/79+9XU1FRVVblcrpeXlwTN5eXl6evro88VEMLhw4cfPHhw\n8uTJK1as2LVr1507d86dO4cketXU1CRotyFJSUl0Oj08PLzhYvv27Z89e2ZtbV1RUfH8+XM6\nnW5nZzdv3jx/f38puQEAIElSKBSKRKKmv+x1dXXiHurfnC+/Cjk5OR07dnz79m0zTyZJ1PMs\nQ4YMGVJFX19/wYIFAIADBw4MHDhw3Lhxhw8fNjAwyM/PP3HixKxZs7KysmJiYqRkffjw4ZMn\nT1ZTUzt37tzdu3cNDQ0BAJWVlatWrQoMDDQyMtq4cePLly9pNJqUHGhEZmbmnj17Hjx4IBQK\nzczMgoKCLCwspGfO29t70aJFS5cu5XA4Hz9+hBDW1dW9e/fu5s2bpaWlaAQJhmHe3t737t1D\nm3H/D50OVFWBquonr15fD4qKwKtXoKAA5OWBvDyQkwMOHwZZWaC4GAAQy2Ck19fXy8mRHTsC\nK6tXWVk0Gm3jxo2oXffkyZM8Hs/Gxqa8vDwjI0MkEkVHRysoKEjv1XB0dMQw7MiRI0FBQWVl\nZePHj58xYwYAQCgUWltbo64OCcLlcktKStDjgwcPJiQkXLlyxdraGgCwb98+U1PT7du3u7u7\no98IyZoW8+LFC1NTUzTopyHq6uqBgYH5+fk7d+5kMpni2jvpYW5uXl9ff/Xq1c6dOzc6dOHC\nBUtLS2k78HMAv1RjFxwczOFw1q9ff/78eQDAtm3bTp8+PWPGDHV1dZlWrAwZMlqT8vJygUDQ\naCYw/E+Qt6lQr6RA404oFIq1tfWVK1eOHj06duxYdXV1bW3tgoKC8vJyOp1+5swZKVlvxJo1\na0iSdHBwmDRp0pQpU5ydnQmCaDrDWYJ8/PjRwMDAy8vrzZs3165dAwAoKCi4uLgwmUwbG5tt\n27ahYuugoCAAABprJxk+fIB371bHx0dzuXc0NERqahCAGgy7BcBmAMYzGE4MhoujI4vF0tPT\nW758uaGhIY1Ga1bVVLKgoX1IvAvHcaRdNnz4cD6fL/G68zt37mAY9vDhQwihp6eneELex48f\n1dTUNmzYACG8dOkSQRDNNo9LhCVLljRU+2hIWFjYwIEDpWS3Wfr27WtjY9Oovvbs2bMkSaak\npLSaG225xu7LgZ2WlhYaHV5VVQUaFEXeuXOHz+c3GjX+SyIL7GTIaCMcOnSIx+M1O/PWx8dn\n3Lhx0jMtFAq1tbUVFBRQWgLHcSQPamFhcfv2bSMjo6YKYBJHJBLFxMQQBDFy5MibN2+KGwMT\nExNpNFp8fLz0TGdlZVlaWjIYDCcnJ/BfxSGXy/X19dXU1GQwGKNGjcJxHMOwlkvOt5y0tDRl\nZWUjI6MAB4ceVOosAA4DkAMABKAWx28AsJkgZunoKALQCoMa7t+/z+fz1dTUMAyzsrLq2bOn\nqakphmEsFktKTQN+fn4WFhZ5eXl8Pt/Nzc3V1bVnz562trbq6urojamuro4giAsXLkjDOoTw\nzJkzNBpNrKHy8uXLQYMG6ejooAHa0hja9xmKiopMTEx0dXVXrFiRkpJy4MCBMWPGUCiUmTNn\ntqYbP3dgR6FQtmzZAv+7DaTWgpg7d66Hh0crePljkQV2MmS0EaKiouzt7Zs9NH36dGm/wTg6\nOrLZbB8fn1u3bqGVly9fDhw4kMvlKisrS3vUwv37962srAAAHA5HV1cXwzBlZWUnJyd9fX1b\nW1srKyt9fX2pOlBfX5+UlDR+/HgMw3Ac19XV5fP5OI5raGigUbE0Gs3BwUFK1t++fRsREUGn\n01FIra6uPnfuXGOBoCsAcwA4BkAxAEIA6q2s4OzZ8PLlb27C/SJ2dna9evUSCoVpaWmLFi0a\nOHDg2LFjZ8+eTaFQTp06JQ2LxcXF1tbWqKoMqdWhDTcGg3H06FEIYX19PUEQ//zzjzSsQwjr\n6upMTU179epVU1Oza9cusSfizVkOh9Oa8onl5eVz5syxtLSk0WiKiopeXl6tr8z7cwd2fD5f\nnORns9l//fWX+NC+fftaU9LnRyEL7GTIaCNER0dbWFg0e2j8+PE9e/aUqnULCwsWi4VKu8SI\nRCJnZ2cAwJMnT6RnOjs7W0FBoVevXjiO//333x8+fLC1taXRaBQKJSIiYvny5Z06dQIArFmz\nRno+QAgvXbrUoUMHLpeL47iOjo54JrC8vLyenh6GYWfPnpWe9dLSUgCAgYFBUVGRtrY2hmEY\nhnE4HJQpJAA4u3AhnD8f2ttDgoA8HuzTB27bBpuTvfpm7t+/DwB48eJF00PBwcH9+/eXoC0x\nJSUlysrKGIax2WwNDY1BgwatWbMmMjISx3GCIK5evXr16lUcx6UaWj169EhVVRV1BWEY1qdP\nH2dnZxaLderUqalTpwIAeDxeo5l2vzY/d2DXtWtXdXV19FHA0dHR1tZWHOKMGDFCqnMg2wiy\nwE6GjDbC5cuXCYJoqlApFArbt28v1TozCCGHwyEIQl1dvV27dt27d9+0aRPqITAwMMAwTKp/\nIgYNGuTs7Iya2O7duzdo0CATE5P8/PyAgAAkcZGTkwMAIAji7t270nCgrq5u8ODBBEHQaDRv\nb29bW1s0nNnDwyMkJMTMzAylkZqNeCRFcXExAOCPP/5YtmwZg8EYNGhQcHCwo6Nj7969u3fv\nDgBwcnISnwoTEmBoKFRWhgBAS0s4Ywa8eBH+N+D3a6mtrY2Pjx83bpytrS2TyTx8+HB9k0vF\nxMSYmZl9zw1+irlz5zKZzIEDB+7Zs4fFYt2/fx9CWFlZ2bNnT5IkFRQUNDQ0PlUDJ0Hevn2L\nOmN4PJ61tfXo0aOfP3+ODo0ePRoAsHnzZmn70Hb4uQO7K1eu0Ol0GxsbCGFcXBwAQFNTs1ev\nXqj9JDg4uPWc/UHIAjsZMtoIQqHQxsama9euVVVVDdcjIiLYbHazkuSSYv369QAAY2NjCoWi\nr6/v6OjIYrHU1NQUFRXNzMykmrETiURcLnf//v0ikYjNZm/fvp0gCDQV+e+//yZJsry8/Ny5\ncxQKxcvLa9iwYdLwYerUqcrKyrdv3yZJEqXlMjMz7e3tKRRK7969o6Kinjx5AqQ5mRZCKBKJ\nSJLs06cPnU7fs2ePeL2qqmrRokVoZ7BhsRCEEAqFMC0NLl4MO3WCBAEFAjh0KDx+HP7vz8/n\nyc3NtbCw4HK5vXv37tatG5VKZTKZnTp1EtecIdauXSulwcgWFhYoUysSiYKCgng83oQJE1RV\nVcWz6+h0OkmSvXr1qvqa+/oGmExmswLNKMqxsrKSqvU2xc8d2EEI09LSYmNjIYQikWjmzJmo\nZBjDsB49ejT6yf4lkQV2MmS0BfLz8w8ePDh16lSBQKCrq7t48eIDBw6sWbPG3d2dwWAglVIp\nkZ6eThAEjuPnzp17/vz5xIkTnZ2d9fX12Wy2vb39nTt3AAD5+flSsv7hwwcAQHp6OoRwwIAB\n5ubmTCYTdU5kZ2cDAAYMGKCoqKipqRkUFNS+fXuJO1BaWkqlUo8cOQIhVFVV3blzJ1oXCoXm\n5uaOjo6enp42NjYAAKluxUIItbW1mUymqqoq2vV78uRJx44dxVM2MAzr0KFDs701EEL47h3c\nsQMGBEAGA7LZsH9/uG8ffP/+8xbr6uosLCzc3NzevXsHIczMzAQAXLhwwcbGpkuXLg3P7Nu3\nr5QyHWjcMfrkIBQKly9fLlZUQ//fu3fv4cOH2tra0u4dIUnyUwLNOI5raWlJ1Xqb4qcP7BpR\nVVWVnZ2Nphn9DsgCOxkyfixCoXDGjBlUKlUgEDg4OKiqqqKJGwoKCpaWlqGhoWPHjrW2tmYw\nGEpKSt7e3hKvpA4NDfXz83NycgoPD2+4fvbsWYIgZs+eraenJ1mLDUE9j6tWrZo2bVqfPn1o\nNBqVSi0oKHjz5g1KFmppaVGp1O7du3M4HAqFIvHcYXJyMoPBQMpRQ4YMcXd3R3HVtm3bUB29\nOM4AAAQGBkrWekOioqIIgmAwGDt27Dhx4gSVSsUwjMFgsNlsGo0mJycHADAxMWm6T/o/VFTA\nQ4dgcDDk8SCFAj084OrV8OnTZs89dOgQm81uOEnE1dXVy8vryZMnJEmKG1FTUlKk15dqbGyM\n47i4N2LlypXa2tolJSU5OTmokQUl6i5evIjjeE5OjjR8QLBYLAaD0WhRKBSiePdT9a+/JL9a\nYPe7IQvsZMj4sUydOlVeXv7o0aPi6uwbN24YGBj4+vqi4EZbWzsqKurUqVP79+8fPXo0hUJB\nQ5okRfv27WNiYo4fP06hUA4fPixer6+vp1KpdDpdqtVF9+/fRxVsqKxNnJ1CG3AAAENDQ7QH\n+scffygqKhoaGn4ya/VNxMfHq6mpocdPnz5ls9nh4eEpKSkoqqBQKD169CAIol+/fii0kl6J\nzsePHxUVFSkUingXksvlenh4UKnUiIiIoKAgNLl3ypQpLbpcTQ08exZOnAjbtYMAQENDOHky\nPH8eNuiPCQ8PDwgIaPik58+fq6mpoTbkESNGJCcnT5w4kUqlSm/cxpgxY3g8XmhoKPqyW7du\nEyZMgBDGxcVRKBRXV1fxmaqqqlLtzvb09AQAnD9/Hn15+vRpZ2dn5n9acObm5lJtIWpT/HyB\nnX2L+R321GWBnQwZP5AwhrqNAAAgAElEQVTs7GySJJOTkxutIxUjFxcXS0vL9/+7oXbu3DmS\nJCU4QV1XVxcNBEAZI09Pzzlz5kRERCD1pB49ekjKUFPevHlDp9OpVCpBEOg9Oy8vD72Vojhv\n3rx5KEGVm5srJycXExPD5/Ml++6OZO/FfwMvXLigqqpKEAQa3kaj0eh0OirXEQqFysrKAAC0\ncSkNjh49igJKAICKigqHwyFJUjx3g8fjKSsr8/n8r75uZiZcsQJ26QJJEnI4sHdvuHUrzMsL\nCQlpur9ZVFQ0atQo9F1gsVidOnVavXp1YmJienq6ZENqxIsXL9Ccl8WLF9fV1Tk5OS1evPif\nf/6h0+kEQVy+fFl8prm5+dq1ayXugJji4mIcx3EcT0hIiI6OJghi2LBhdnZ2KGtrbm7OYrGk\nNye8TfHzBXbE/0KhUMRKFQ01Q3g8nqam5g/yvPWQBXYyZGRlZR04cCA6OjopKamVK2tjY2N1\ndXWbPeTr64thWLPju4YMGSLBeMvd3f3PP/9Ej9PT0ydMmODh4eHq6jpkyBAMw6TUiIoICAjA\nMOzRo0dIcKJTp05TpkwZMGAA+iM8cuRIoVBYXl5+/PhxHR0dW1vbK1eu9O7dOywsTII+1NTU\nCASCVatWiVcqKyvRtBEWi9WvX7+G9YVJSUkAgIkTJ0rQgYaIRCInJyctLS0AwLBhw5hMpoeH\nR3Jycr9+/ZSUlFasWEGj0TAM+/bRG6Wl8MABOHQoVFGBALxWUorX0YFJSbCoqNGJ5ubmS5Ys\niY2NVVRURLlDAICcnNzKlSslPvjj7NmzaLALg8FgMplIvI5KpR48eFB8Tn19vby8/IEDByRr\nuhFo0xn9+IkfYBhma2vL5/MpFIqSklKjkUC/JD9fYNeQkpISZ2fn8PDwu3fvoo38srKyK1eu\nBAUFubu7v/9S5ekvgCywk/E7U15ePmjQIBzHUUEbm81mMBiLFy9utZlVnxmE3qdPHwzDmi2o\n2rFjh7a2tqR82Lx5s7y8fF5eXqP1UaNGmZiYiF+KV69enTp16ujRo8+ePZOUaS6Xa2trix4/\nfPhw5syZ/v7+vr6+aKIYAIDBYKCGUPQui1JZSkpKjx8/lpQPEMLt27dTKJTY2FhUaVdZWQkA\noNFoxsbGjSS8ioqKAACdOnWSoPVGvH79GgneKygoWFhYTJw4UUVFhU6n6+vr29nZISXfhhHP\nNyISwbS07LCwKxgmpNEgAFBHBwYFwdWr4aVL106dwnF84sSJDAYjOjoafdopLS3dtGkTh8OZ\nOnWqBO7zfykuLl62bJmLi4uKigpJkn/++WdJSUnDE3bv3s1gMIqLiyVotL6+/unTp43q9ior\nK83NzVEAzeFw/vjjj5SUlDVr1syZMyc4OBgAMHv2bAn60Db5uQO7YcOGDRkypNlD3bp1awX9\nlh+OLLCT8dsiEol8fHzatWsn/vslFAr37NnD4XAWLFjQOj6sWrXqU1Mk3N3dCYJoNsTcu3ev\nuCzs+6mrq3NxcdHX109KSqqoqBCJRE+ePAkLC6PRaGi+Rm5urq+vLwCAyWSiOjMbG5s7d+58\nv2mCIAYNGtR0fe3atShldfz4cVNT03bt2iUmJpaUlFRXV9vb2+vp6cnJySGBUUmBQhYOh2Nn\nZ6enp4cCu6bB7oULFwAADQu/pMHdu3dRXGtqaqqqqkqlUoODgzds2LB8+XJUfmdiYiIpW336\n9NHX0rqzfTuMjYVDh8L27UUYBgEoZjLP4nimvz/cvh3evAn/C7POnDlDEASaNicN6urq7Ozs\nrKysxN9foVAYHx/PZrOXLl0qKSuFhYUhISHiGdQ8Hm/y5MkVFRXoaLdu3Wxtbc3NzZGeHkEQ\nYj0MlEqsra2VlCdtk587sFNUVNy+fXuzh1asWPGpzudfCVlgJ+O35fjx4wwGo+nU2YMHD1Kp\nVOkN+GjI7du3xSLoDfnw4QN6C8/IyGj6rMmTJzeaRvGdlJeXjxkzRtyGCQDo0KEDEst+8+aN\njo6Oi4vL7du30RSSp0+fBgYG8ni8Bw8efKddGo3m5+fXdD0tLQ0AEBISsmzZMlVV1aL/Ngrv\n379PoVDOnz/v7+/v7u7+ndYbUVpaeuLEiRUrVmzbto3H4+E43jRd2qVLFwzDJNu80ixcLhfD\nsMmTJ6uoqGRmZqLFrVu3YhiGJNckNXvl48ePQ4cOxXFcTU3N0dFRSUmJR5KrgoLOBAVtlZOD\nPj5QUxMCAAGAfD60tYX9++9QUzveowe8eBEWFEjEh0a8ffvWz88PwzA9Pb1OnTrx+Xw6nb5k\nyRJJ5dFfv36tra1ta2ubmJj46tWrrKysPXv26Orq2tvbo4EY3bp1EwgECxYsEAgEPB5PV1d3\n8+bNt2/fvnjxIofDQQH3rx3b/dyBHY1Gi4qKavbQjBkzaDSatFxrM8gCOxm/LWFhYX369Gm6\nLhKJ1NTU4uLiWscNf39/MzOzly9filfev3/v5+dnaGjYuXNnf39/FE5BCJ88eRIZGdm9e3cK\nhRIYGCjx0LO8vPzGjRunTp1quDk1YcIEMzOzRhOgRCKRv7+/j4/Pd1rs0KEDh8MR36CY2bNn\nAwA4HI6Ojo5YcuP8+fOampp9+/aFEKalpWEYViCdwAJCuGvXLgCAtrZ2WVmZeHHMmDGo4koi\n2crPs2jRImTLz8/v4MGD6Jsurv2iUChubm4SNPf8+fP4+PjIyMj9+/fn5uZCCCdOnPj/DbMf\nPsD0dHjgAIyKgiNGPFRVfctmQxyHAEAuF9rawoEDYUQE3L8fZmRACZWgZWRkbN++PTIy8tCh\nQ0VNSgC/h+DgYDs7u0bjjouKitTV1dEP29SpU0mS9PX1VVRUbN++vbgo6/3793Q6HXW3REdH\nS9CltsbPHdhZWVmpq6vfvHmz0fqNGzeUlJR+h7k1ssBOxm9L165dp02b1uyhzp07S1vCS0xp\naambmxudTu/evfukSZP69evH5/ONjY2fPn366NEjPp/v6el55syZuXPnEgShqanJYDA0NDQM\nDQ1ZLNa+ffu+2W5ubu6+ffsWLlwYFxf36NGjT52mpqa2devWpuuXLl0iCKK0tPSbHYAQnjt3\nDgDg7OzcMDd2/PhxgiBMTU3nzp2LyuzMzc3l5eWJ/2PvvAOaypq/f256AUIoIaFILwIKSO8W\nUBQUVFSkuCIWyqor8AhYUFdsgBV7LygqFiyIWNC1oFjWCgoiCqwooiwgKIQk9/3jPE/e/JKg\nlISi+fwF55aZUJK5c2a+g8XOmjULhpgtLS0IgsCcopQYM2YMDK1UVVX79esH4yocDhcdHS09\no3ygihv4v/Tv3//hw4eurq4wocifedVpvpN2WrBgQVvVn/7+/uHh4WhzM/r8OXryJLp6NTpt\nGursjNLpKAAoDocaGaFjx6JLlqBZWajAE0tvoLGxkUgkivahoyi6du1aQ0NDFEULCwvh7Foi\nkSgoADRz5kxtbW34u4Bn/qz07cDu3LlzsCbXwMDA09Nz9OjRnp6eBgYG8P9Z2g04vQFZYCfj\nlyUgIKCtOtr+/ftv2rSp2zzhcrlnzpyJiYkZPXp0RETEgQMH+LoSr1+/hjpq8ONERUVl2bJl\nbDabx+OlpKTgcLhOzLnicDgxMTE4HI7JZLq6usKtvQkTJtTX1wudyWaz24qf4GjXrtdaLV68\nGKrWWVpaDhkyBPYNqKmpQUkRJSWl+Pj4DRs2nDx5srKykn8VnFfx4MGDLlr/PmlpaVQqlS+Y\nQKPR1q1b1/UNwS9fvixbtszR0ZFOpxsaGgYEBNy9e1f0NCcnJwDAnDlz5OXld+zYsWHDhpEj\nR6qoqAAAjIyMYDKvcw4cO3bMzc2NRqPh8XhTU9OEhATBxCTkzJkzFApFtFmhqalJRUUF6uOI\n4f179OpVdMsWNCICdXZG5eRQAFBlZdTDA42LQ0+c6PE4r7CwEAAgNgUINZBhA429vT38jzt2\n7FhRUdGpU6esrKxwOJyWlhZs2hW7U//T0LcDOxRFb9686eXlxS+ihKWRgwcPlqBMVG9GFtjJ\n+GXZtm0bi8USantEUfTZs2cIgjx58qRHvBKLgYFBZGSkaC1/QECAt7d3R+82b948ZWXl8+fP\n81dgkbinp6dQ1MLj8YhEYk5OjuhNysrKAABlZWUdtS7KgwcPhg4dymKxaDSaiYnJggUL+Jkk\nLy8vseImmZmZFApF9Hcncbhcbmlp6cWLF4uKiuBHfhepqqoyNjaGW8ynT5/esWOHv78/Dofb\ntm2b0JlwmBuBQBg+fLinpyeBQDA1NcVisePHj3d1dcVgMAiCdGI7fs6cOUQicd68eVlZWdeu\nXduwYYO+vr6JiYlQrMNms/v37+/n5ye4Zclms6dMmaKlpdXenzyXi754gR45gv7nP+jgwai8\nPAoAymSio0ejf/6JXryIdi3j2wng2F/RfyUUReFIYlgYUFpaCqN52DYB1QStra3xeLyNjQ0M\nFX5iTbs+H9hBuFzuP//8U1JSUllZKZH/3r6CLLCT8cvS2NjYr18/f39/wU+piooKc3Nzqary\ndpTKykoAgNjd0qysLCqV2qG7lZWVYbHY3Nxc0XUymSw6r8zd3T0iIkL0Phs3bmSxWKLlcZIl\nOzsbh8MJRZYVFRU6Ojpz5syRqmkp4eXl5ejoKJQh27dvHxaLFX2WcHZ2xmAwSkpKAAA6nT5i\nxIicnJy6ujodHR1Y8Cf2V/Mdzpw5QyAQBFV/URRtaGgYNGjQxIkThU5+8eKFlpaWvr5+fHz8\nrl27Fi5caGpqymAwOp8o5XLRwkJ0/340Kgq1tUUJBBRBUCMjNCQETUtD791Dpd+RwGazFRUV\nDx06JHpo4cKFgwYN4n87ZMgQAICSkpK6ujqNRjMzM8NgMAsXLkxOTpaXl6fT6SoqKpKVX+k9\n/CSB3S+LLLCT8Svz7NkzHR0dJpMZEhISHx8/btw4CoXi7u7exdIxyfL06VPQxrSD/Px8AECH\n5gFs2bJFW1t748aNM2bMmDZtWmpq6ps3b+AhPz+/8PBwofPPnTuHx+OzsrIEF+/fvw+1ajv2\nSjpFYmIiDocLCgrasWNHenp6dHS0kpKSu7v73bt3X79+Le3IUrKUlJQAAMRqPnt4eIj+8B8/\nfgz7lGfPns3j8VpaWv766y8rKyszM7P3799DSb8ObQ2PHDlSbAb0+vXrWCxWcGgspLa2Nikp\nafjw4UZGRh4eHosXLxY9p/O0tKB376KbNqHBwaiREYogKJGI2tmhs2ejBw+iL1+i0pGTjImJ\n0dbWfvfuneDi48eP5eXld+/ezV959uwZFouFe/GjRo1avXp1YWHh2bNnSSQSlUpNTU01MDCQ\noAJLr6JvB3Y8Hm/Pnj3e3t6WlpZm4uhGb3sGWWAn4xensbFx+/btYWFhXl5ev//++8mTJ3tb\nrFBTU4MgiNg0yeHDh5WVlTt0t7Fjx2KxWH19/cDAwN9++83U1JRAIGzevBkVaoQUYOXKlVgs\ndtSoUStWrEhOTp40aRKBQJg2bVq3/aCuXr06YcIEIyMjTU1NFxeXAQMG8IsOFRQU4uLihDoc\ney3Hjh1jMBhiD61evdrOzk50nb/xRyaT8Xg8BoOZNGkSnNUBi70+fPjQfgc0NDTEJqtaW1ux\nWKzYMSdiYbPZnfvUqKuru337dlZW1osXL4Rr1D5/RnNy0GXLUG9vlMFAAUAVFVFPTzQhAT11\nCq2o6IQ5sTQ1Nbm6ujIYjGXLlmVnZ588eTI2NpZKpYaEhAj9SR89ehRqYtva2o4dO9bY2BhB\nEAKBAB+NpkyZ0ukyx15O3w7sUlJS4P8MhUKhiaMbve0ZZIGdDBm9HwcHB9FEC5fLdXd3nzJl\nSvvvc+vWLQwGw2KxBNM8+/fvx+Fwp0+fDgwM5M9iF+LevXvh4eHOzs42NjZTp04V21TYTjgc\nzqtXrwQ7IdrPy5cvlZWVPTw88vLy/v333/Ly8kOHDmlpaQ0ZMqRP6IodPHiwrUmVGzZsEKvD\nAIVXUlJScnJyrl+/vn79ejhwjE+HplAwmUyxndRcLhePx1+5cuX7l3O53C1btgwYMACPxyMI\noqOjEx0dLdpzI5avX7/Onj0bzgWGMte6urqiW///nzdv0KNH0ZgY1N39/xfn+figS5ei586h\n/zff1lHYbHZqaqqdnZ2cnBydTndzczt48KDY3OfSpUvl5OTk5OTgTxtBEBaLZWNjo6mpCb/+\nKVso+nZgp6mpOWLECFGF0l8HWWAnQ0bv58aNG3g8fuHChXw9uc+fP4eEhCgqKnbo7Wv48OHe\n3t4Iggh1s8bGxpqZmSkpKR04cECSfv9fqqqqAgMDoQAyrF5KSEjoULJt2LBhI0eOFPooraio\nUFZWTktLk7S/kufOnTtYLFZsS+bUqVOhRJ8oZDIZh8NFRUWNGTOGSCR6enoyGIxBgwb9+eef\neDweh8OdPXv2h6Z5PN6hQ4eUlJTk5ORYLNbw4cMPHTrED2WgUPb3o20ulztx4kQajbZ8+fJr\n167dv39/+/btRkZGJiYmP9yfhQ8hCgoKFhYWxsbGo0ePXrp0aXR0NA6HO3Xq1A+d/29x3oED\n6O+/o46OKIXy3zjP2xtdvBg9fRr9XzmBxDl58iSNRvvy5YuxsbGlpaWxsTHs2ob64RgMRrKT\ni3sJfTuww+PxYvvMfx1kgZ0MGX2Cc+fOqampUalUW1tbCwsLAoFgZGR0//799t+By+USCISY\nmBgDAwNFRcVFixbxp77CSVmGhobSG3BeUVGhqalpb29/9uzZysrKV69e7d27V1NT093dvZ1G\n371719aW9KJFi+zt7SXtsuThcrmGhoaitXTPnj0jkUinT58We9XcuXM1NTXhniyZTLa1tV29\nenVdXd2gQYNCQ0MXLVqkpqb2/TZVDofj7+9PIBCUlJQQBGEymSYmJmQyeeLEiRwOp7W11dPT\n09PT8/vO7927V15eXmjcSENDg6WlZXBw8PevTUxMRBDE1NR04cKFW7dunTdvnrq6uomJybx5\n81gsVof/6jgc9Nkz9MABdM4c1MXlv6IqdDo6ZAgaHY0ePIg+eSKpPoy6ujo5Obng4GA6nU6h\nUKZOnQo7aisqKqhUqo6ODgCgV3XQS4S+Hdhpamp2QgXqZ0IW2Mno63A4nG6QvegNfP369cKF\nC8nJyRs2bLh69WpH+/dzcnJgnszLy4vJZCIIgiCIg4ODn58fHJT0w524rjB+/HhnZ2ehj/B/\n/vmHwWCsXbu2PXeAMmNid75OnTqlpKQkGUelBpfLffXq1Zo1a4hE4uTJk+/fv//t27fy8vLd\nu3erqKiINqXy+fz5s7GxsaqqqpWVVW1tbV1d3eXLlx0cHLS1tf/+++8vX77Iycm1FRRCkpKS\nsFgsg8FISEiwsbGRk5MbOHAgFoslk8nTpk1zcXFhMBj8KL8tHB0dxQp6X7x4kUAgfGdD9tOn\nTwQCwczMTLCCrb6+3s3NzdHRkUAgXL169fumfwCXi5aUoMeOofHxqJcXymSiAKAEAmphgYaE\noCkp6KVLXdm63bRpE9w+Hjt2LFzJz883NjZ2d3dvamrC4XA/jIn7HH07sPvPf/4TGRnZjS71\nOmSBnYy+y5EjR+zt7eHWnra2dkREhCRb9voCHA6nuLj44sWLr169+n4rw5s3b+Tl5fF4PNRd\n5/F4OTk5sJFi6NChS5cuxWAw/NFJEufff//F4XB5eXmih5KSkto54yc/Px9BELFbtxkZGWpq\nal31UppkZmbCoQUUCgUAwG/+gDomy5cv/36YXlNTo6GhAQv54Q6giooKHIZBJBIVFBS+/0FG\npVLV1dWhNkdra+vq1as1NTX5RWOTJk2qaEdrgry8vNg93y9fvgAAvpM8TklJIRKJKSkpQutv\n3rzBYDAaGhqCvaiSoboavXQJTUlBp0xBLS1RPP6/s27d3dHISHTbNvTGDbS2tv3309XVBQDg\n8XgzMzM6nY7BYAIDA+H/i7a2toKCgoT972l6c2CHAT8iMTHx9evXQUFBubm5L168KBXhh3eQ\nASkvL09NTZ06derUqVNTU1MrKip62iMZPzl//PHHtGnT3N3dT58+ffLkyXHjxuXl5VlbW5eX\nl/e0a90BiqLbt29XV1c3Njb29fU1NDTU0tLav39/W+evWbNmwIABfn5+cAYugiBeXl6nTp1K\nTU19/vx5WVmZs7MzjUaTkrevX7/mcDj8Bk9BbGxsoGbsDzEzM4PZHdFDV69etbKy6qqXUmP/\n/v2TJ0+eMmVKRUVFU1NTbW3t7t27lZSUxowZ8/r160+fPi1atAiHw33nDioqKtbW1lFRUY8e\nPVqyZAmCIOPGjcvJySktLT137hwOh9u+ffvJkyfFXltUVNTU1LRy5Uqoh4fD4eLi4iorKz99\n+mRtbY2i6LZt27S0tNrzQkSnnPEXURRt66q7d+8qKSl9/fpVaF1HR8fMzKy+vh5KikgSBgN4\neoLYWHDgAHj0CDQ1gefPwdatwMUFVFWB1FQweDBQUgIsFhg2DPz+O9i2DVy/Dmpq2rqfnp4e\nAOD48eORkZG7d+9++vTpsGHDEhMTw8LCampqvnz50traKuGXIKMt0B9l7Npzh58biWTsduzY\nQSQSTU1NQ0NDQ0NDTU1NiUTijh07JOWkDBlC5OTk4HC4GzduHDx4UENDAwAApR/weLyJiUnX\nhz71fhITEykUSkxMzJw5c8aOHTtmzJgRI0YQCATRvAjEwMBg69atRUVFcnJys2bN4gvkQvVj\nPB7flafzHzYGPn78GABQKy5Hcu7cufZrLIeFhYmW6l+9ehWPx3+vv1JqvHjxIiMjY9OmTZcv\nX27rXbSuro5GoyUmJp47dy49Pf3vv/+GybmCggIsFnvjxo122lqyZImFhUVlZSWFQoHyNJAP\nHz7gcLiwsDA6nS5WL/fAgQMAAKHaOEh8fDwA4P379+1xwN7efsGCBaLrly9fxuPx30n3jhw5\n0s7Ozs7OTvQfc+DAgUBC80s6RlMT+uABeugQmpCA+vqiBgYoFvvfrJ6TExoWhiYno2fPosXF\nsFYvKSkJAPD06VMURfPy8hgMBpPJHDt27LBhw2Bcu3Tp0u5+CdKkN2fsfhzYTZ48+bfffgtr\nm270tmfoemAHP2KFxoTv3LkTh8P9ImPZZHQ/48aNCwkJ2bBhA4FASEpKgt18Hz58iIuLAwCI\nFqf/ZBQXF+NwuPHjx2MwGBcXlzlz5sycORMq0uHx+HJx4zjpdDpsP7x586a2tjaFQrG1tXVw\ncIDVdUlJSZ1wo7a2NjY21tTUFI/Hq6ioDB8+vC0ZlKamJgqFIjhPnU9MTIyzs3M7LdbV1dna\n2rJYrKVLl2ZlZaWnp8+YMQOPx8fFxX3nKjabvWHDBjc3NyUlJW1t7dGjR2dnZ7fTYltUV1d7\ne3sDAOh0OovFwuPxNBoNZkOFgG+GAAAsFgu/UFFRgT+oUaNGRUVFtdNieXk5mUwePXq0oaEh\nP0Jis9ljx44dMGBAc3Mzk8ncs2eP6IVHjx5FEOTw4cOih8LCwrBYbDsFO3bs2EGj0YqLiwUX\nm5qabGxsAgICvnNhZGTk0KFDyWTy8uXLBderqqqwWKytrW17rEud5mb0yRP02DF02TJ08mR0\n0CCUSkUBQPF41MiIM2rUWgxmEYNRtHmzMYXyx9y5LS0tt27dYjAY5ubmFhYWZDJ569atPf0a\nJEbfDuy+Q2NjYzufY/o0XQ/sHBwcxL43RUVFOTo6dsE1GTLaxNDQMCUlhUwmiw4jJ5PJGAym\n68PpezNJSUlaWlpUKvXSpUv8RR6Pl5qaiiBITEyM6CXGxsabNm2CX7e0tOTk5CQnJ69atQru\n3naira+iokJXV9fExGTjxo15eXmZmZmzZs3C4XB//vmn2PMjIiIMDQ2Fkm3379+nUChiJXPb\norm5OTk52dHRkUajaWpqjho1SnDorShfvnxxdnZWVVVduHDhiRMn9u/fP336dDweL7YPoP0+\nDBw4kMlk4vF4BQUFS0tLJSUlDAaDwWCEysUaGxth6Ozi4pKcnLx79+7p06eTSCQEQc6fPz9/\n/vyRI0e2325GRgYGg9HS0tq9e/eFCxeg9J2amlphYSGKoj4+PmJ/9Q8ePEAQxMTEpLGxUXC9\nqalJWVlZW1u7ndY5HI6vr6+SklJKSkpBQcGTJ08OHDhgbm6ur6///c/Ka9eu4XC4tWvXUigU\nR0fHpUuXbtmyJSoqikqlYrHYHkjXtZ+KCvTKFXTrVnTu3BIDg1cAtAKAAtCCxRaTSCcAOKKt\nPQODuZ+aumvpUgaD8dNo2v20gd3hw4dZLJakXep1dDGwa2pqQhBEaPIg5MaNGwiC/CLtijK6\nGQMDg+DgYG1tbdHNHXl5eSMjo8WLF/eIY91DaGgomUwWO9FLXV1dX19fdP2PP/6wsrIS/eBZ\nvny5pqZmJ2ZIDB8+3NXVla+rBzl37hwGg7l165bo+fX19XZ2durq6itWrMjNzT116lRMTAyZ\nTA4LC5Pq1nlkZKS+vn5VVZXg4tWrVwkEwpkzZzp3z7S0NAqFApOgfOevXr2qqKhIJBIFJ7xF\nRkYCADQ0NAQv/+eff2g0mqKiYlRU1Lhx4zpkeuzYsdra2vr6+iQSaeDAgaGhoWvWrJkzZw6c\ncxodHS10fl1d3cqVK6lUKgaDUVBQCAoKKi4u/vz5c05Ojrm5OQaD2b59e/utczictWvXGhoa\nwjYONTW1yMjI78xL5fF4J0+enDFjBoPBIBAIXl5eoaGhgwcPNjIyMjMzw2KxW7Zs6dDL70F4\nPF5ERAQeACcVlWhj421GRicYjMsIUq+sDLdxvwLwzdAQ9fNDY2LQbdvQS5fQ0lK0b46e7/OB\nXU1NTVpaWkxMzFwBZs2apaGhIS8v312u9hhdDOzevXsHABBKzkNgQfS7rumDy5AhljFjxgwY\nMMDb21to/fnz5wCAiRMnBgUF9Yhj3UNgYCAAQOyWq4WFBYlEEl2vqqpSUVEJCAjgj8Hlcrk7\nd+7E4/FiN+m+z/tRwLwAACAASURBVOvXr0EbM0/HjRvXlqpZc3PzypUrBw0aRCaTodx/J0x3\niMbGRjKZLFYCNzw83MPDo3O3dXJyQhDk8uXLQut37twBAGzcuJG/Ajd/sVis0C8LJkq1tLRW\nr17dIdMbN27U1dWFAfqKFStwOJyGhoa5uTkchECn0wW7U0tKSnR0dHR0dAICAnA4nKKiIr/7\nAWqdeHp6dm4uXFNTk9jhxYJ8/frV29ubTCZPmjRp6dKl9vb2MByEUxxYLFZ6enonTHcILpdb\nWlp64cKFR48edWikcltQqVQvLy83NzcPD4958+bBqju0pYX34oUPBlMcFYXOno2OGoUaGaEE\nAgoAisOh+vroiBFoZCSamoqePo0+fYr2+nxH3w7s3rx5o6qqKrZtAofDLVu2rBu97Rm6GNi1\ntLTg8fjc3FzRQ7m5uQQCQXp6pzJ6G7m5uUFBQZaWlhYWFoGBgV2ZOvVDsrKysFisjY2N4GJr\na6uXl5e7u/vkyZN/Sjl4PosXLwYAiH6y1tfXUygUDAYjNgf26NEjIyMjKpXq4OAwYsQIFotF\noVA6Vxh06tQpOp0u9tDGjRt/uEnSbd0t9+/fBwDwO0UEyczM7OiYXT5qampMJpP/LZvNvnr1\n6sqVK7Ozs4lEouD8UCwWO2PGDAcHh2HDhgm+zbLZbAAAiUQSO4XiO1RXV8vLy69atWrr1q0k\nEsnIyIhIJNrb2xsaGkIJFRKJBLVLWltbzc3Nvb29YVa1oKDA1tYW/K+JlUKhxMfHSyTWaYvw\n8HBtbW1BebwvX76EhYURCIQLFy50wwi406dPQ5kSKDEjLy+/dOnSjqo/CmFkZCR2xglsQvo/\nHSqtrWhZGXr5Mrp9Ozp/PjpuHGph8V8tZTg2w9kZnTIFXbYMTU9H79xBe5NUU98O7IKCguTl\n5Tdv3gxb6Hfv3n3x4sX4+HgNDY1fpPC/6zV2o0aN4ss2CjJ27NifdUCyDCF4PN7s2bPxePzk\nyZM3bNiwcePGoKAgAoEQHh4uvY9wT09PAMDChQvv3Lnz4sWL48ePOzo6MhiM58+fs1isn7sp\nu6SkBAAwbtw4wa1VNpsdEBCgqqqqqanZ1oWtra0XLlxYtWpVQkJCenp6R6MKPpmZmaqqqmIP\nbd26tX///p27rcS5ffs2AEDs4+W5c+fk5OQ6d1sWi2VsbAy/joyMFBSlg70R/N8LDoebNm3a\n27dvDQwMtLW14+Pj9+3bt2LFCqj8MmPGjE5YP378OA6HIxKJdDrd0tJy+/bto0ePJhKJFy9e\nhNVsgwYNQlE0OzubRCLV1NQIXltTU3Pp0iUlJaWdO3d27rULweVyL1y4sGDBgsDAwISEhPPn\nz8MUYE1NDQ6Hy8nJEb3E0dFxzpw5ErH+HQ4dOoTBYNTU1PB4PAaD0dPT8/HxUVZW7tBsZVFg\nSYNodLhkyRKxlSFi+PABzc9H09PRpUvRkBDUyQlVU/tvtEejoYMGoRMmoHFx6M6daF4eWlGB\n9kSPf98O7Pr16xcfH4+i6Ldv3wAA/CkUjx49UlJSElsp8pPR9cDu0aNHZDJ59uzZ/MfihoaG\n2bNnUygUsTs1Mn4+9uzZQ6VShUot79y5Iy8v36EKng7R0tLCZDLl5eXh/g6dTg8KCnr79m14\neDiTyWznYPK+i4mJCYlEsrS0TEpKOnTo0J9//mlmZqampmZqatr+RstO8/TpUwRB3ogb0Bka\nGir2Sa9H+PDhAwaDKSgoED30559/WllZde62rq6uVCoVzk4FAAwdOvTOnTvNzc1paWkwH2Zn\nZwfPZDAYsOSxoaFh1apVnp6eurq6zs7OQ4YMAQA8fPiwcw7s27ePn3tTUVEZN24cv/1lxowZ\ncOrr4sWLBw8eLPbySZMmzZw5s3OmBampqXFzcyMSiR4eHjNmzPD09CSRSM7Ozh8/fjx//jyV\nShXbTLBmzRqonyc96urqCAQCiURatmzZlStX8vPz09LS9PT09PX1cThcVwZdVFVVqaqqTpw4\nkV9ZyOFwtmzZgsPhjh071nmPv3xBHz9GT51CU1LQ8HDUwwPV1UVxOBQAlERCzcxQX9//lu5d\nvoyWlaFS7tLo24EdHo+HDy7wZfz111/8Q4sXLx42bFg3eNmzSETH7tq1a1paWmQy2dra2tra\nmkwma2lpXbt2TUI+yujtmJmZJSYmiq4nJSUZGhpKz25hYaG6urqhoWFMTMzBgwdXrFhhZWVF\np9N/hUcymJtxcHBwcHDQ0NBwc3ObPXu2l5eXmpqaUKOAlBg0aNDEiROFUhSPHj0iEolZWVnd\n4EA7GT58+IgRI4QijKqqKjU1NbHdJ+0BSgH7+fkBAH777Te4CP8aiUTipEmTAABwwkdCQgIA\nQKhTuKioiEKhtJXybA/nz5+H2nWib92wc3b//v0xMTE+Pj5iL58+fXrXi1B5PN7gwYOtrKwE\np1ZUVlba2Ni4uroeOXJEcLdakB07dhgZGXXR+veJjIxEECQ5OXnZsmVr1669cuUKl8utq6sz\nMzPr169fF4PaJ0+ewEm7tra2Q4cOVVFRoVKpkh+egaIom42WlKAXLqCbNqFz5vyf0j0CATU2\nRkeNQufORdPS0JwctKREUuNx0b4e2CkpKfGVdeTk5ASlEzIyMmg0mpQ97HkkNVKspaUlNzc3\nNTU1JSUlNzdXVlr36wAHColNivz9999tydJKik+fPsHMhKamprOzc2xsLBzR/SuQnZ3NYrEI\nBMLAgQMNDAwwGIyVlRVUvugGHj16pKCg4OXllZubW1VV9fTp0/Xr1ysqKoaEhHSPA0LU1tYe\nOHDgP//5z/z58w8cOMDvESkuLlZWVvb09Pzrr7/q6+urqqqOHTsG02adrjDj8XgWFhYwYTZ9\n+vT4+HgfHx8CgaCmpmZiYtLS0iIvLw/F+VpaWgwNDaHaSHR09MqVK0eOHInFYrFYrGAeoaMU\nFBQAAMSq961du5ZMJqekpKSlpYntj0ZR1MnJadGiRZ22Drly5QqBQBDN2lZUVBCJxHXr1mGx\nWLH/+zExMZ1uW2knSkpKCILIyckZGhoaGBgQiUQzM7Pnz5+fPXsWh8MNGTKki/dvbW3Nzc1N\nTk5OTEw8evToD/tIJAmHg5aVoZcuoVu3ojExqK8vamaGkkj/bdRYuVIiRvp2YDdy5EgNDQ2Y\nW3J0dLSxseGHOLBDu1v87Elks2JldJGPHz8CAMTGE7AU7NeJtLqf5ubmq1evpqWl7dy5s6Cg\noJtHbhQXF8OABtaWaWlprV+/vnNdll3kxIkTNBqNyWTC7hkGg6GoqHj69Gl4tLS0dNSoUfxB\nqxQK5Y8//hASdeso1dXVVCoVQZB+/frp6emZmJgoKCgYGxuXlpaiKNq/f3++PlxDQ8PkyZNh\nHR70QU9P7+7du12x3traSiQSHRwcBBeLi4szMjI0NTXJZPKOHTsqKioIBMLRo0eFrs3Ly8Ng\nMF2vk1mwYEFbW70eHh6xsbEaGhpLliwROlRTU6OqqipVlRP+YD06nW5ubk4ikeTk5AYOHKim\npgbfkdzd3aVnvWfg8dCKCjQvDxXXKd8J+nZgd+vWLRKJBPf79+7dC9+bxo4da2lpCQD4uRUT\nILLATkYX4XK5CgoKcONJiNOnT1Op1G5of5PRg7S2tr58+bJbkxb/lxs3buDx+ClTpmhpacEs\nGoIgUPw2Pz+ff1pTU9ODBw9evnzZxb5IPu7u7hQKJSIiwsvLa8aMGXv27Pn27Rs8pKura2ho\n2NLS8urVK5gX/PLlS0FBwcWLFwU3LrtCSEgIgiBw1ER1dbWPjw9siYWxo5KSUnp6+qpVq8hk\n8oYNG2DmrL6+fs+ePTQabe7cuV13IDw8vK2BE0FBQdOnTz958iQUl+AXvN69e3fgwIE2NjbS\n29LhcDgkEgn+Dbx+/RpF0dbW1l27dpHJZBaLFRUVBQCIjIyUkvWfhr4d2KEo+uDBA9jwz+Px\nEhISyGQy/JsYM2aMUD/RT4kssJPRdaZNm2Zrayv0Zs1msx0dHduSNJMhQ1K4u7vb2dlBgbQp\nU6Zs2rTp999/ZzKZAAAqlTp//vzDhw8LCSlLhKVLlwIASkpKhNYbGhowGIyKigoej4fKWXZ2\ndhKXWWhubmYwGAiCaGpqKigoyMvLU6lUDQ0NZWXliIiINWvW4HC4jIyMrVu3qqiowFAPAKCg\noLBq1SqJZFWXLFnS1mwhFxcXuNV74sQJFouFwWB0dHQUFBQQBJkwYYJUnwHWrVsHADA2Nu7X\nr5+7uzu/pW///v0EAgFOARErvCpDkD4f2Anx7du3N2/eSONdoHciC+xkdJ13795paGgMGTLk\n/v37ra2tra2tDx488PDwYLFYkspPyOgrNDQ05OfnHz9+/OHDh91Qa9vU1ARneenp6TU0NFRU\nVGRkZLi7uyMIAjM3jo6OysrKWlpaXdz9FOXr169EIlFdXb2uro6/yGaztbS0AAABAQHXr1+v\nrKy8efPm77//jsViJaUwwuft27cDBgyAFXv9+/fX0dFBECQsLIz9v7n1TCaTzWa3tLQ8evTo\n1KlTDx48kOBHW0FBgdgt3WfPngnmSpubmwsKCvbv33/27FmxktqSxcPDA4PBpKWlKSoq6urq\namlpxcXF7du3LykpCe6Gt7V9LEOQvh3Y3bx5s61xKAUFBZmZmdJyrdcgC+xkSIS3b996eXkB\nAAgEApFIBAB4enrCrRAZvwitra0LFy6kUChYLJbBYAAAVFVVd+3aJVWjUBgWAPDs2bO4uDg8\nHi8vL4/FYplMJtyWdXJyampqCg0NpdPpEh+Ec/bsWSwWSyAQ3N3dw8PDPT094Z6Pn5+f0Jnb\nt28nk8mVlZWSdYDL5Q4cONDFxSUiImLdunWCM3///fdfLBYrdt6jpJg0aZK2tjZfJgxF0YKC\nAl1dXX9/f+kZ/T5QILC6unrkyJEqKipjxoxxcHDQ1NSEY9AwGMyHDx96yrc+RN8O7AAA/AJb\nIVJTU9uSVv+ZkAV2MiTIhw8frly5cvny5e8PBZfxUzJ16lRVVdWjR4/m5+fv3bs3OTk5IiKC\nSCRu2LBBekbhuGoSiTR//nw6nZ6cnEwgEJhMJoPBMDQ0BAAQiUQul8vlcsWOUu06xcXFLi4u\nNBoNi8XKy8v369dPUVFx3rx5w4cPHzt2bGJiIhxyz+PxjIyMOi2w8h0MDQ3bygUymcyMjAyJ\nW+Tz9evXKVOmIAiir6/v4eGhr6+PIEhwcHAPjggfM2YMiURKS0trbW1dtWoVnDwB1f6wWKyT\nk1NPOda36M2BHQ60QWlpaWlpKfz60aNHMGMvyLdv344fPw5fmwwZMtqJmpqamppaT3showe4\ndevWoUOHMjMzk5OTCwoKdHR0qFRqSUkJiUSKi4ubPHkyzOFJHAqFQqPRGhsb161bFxERkZCQ\nwOPx/Pz8Wlparly5giBIS0vL/v37p02bFhgYePDgQYk7YGRkdPPmTfg1iqKDBg2qrKwsKiqy\ntrZuamo6f/58cnLyjh07pkyZYmdn9/LlS4k7QKPRamtrRdc5HE59fT2NRpO4RT5kMvnAgQMJ\nCQm3b99++/btpEmTnJycTE1NpWfxh7i7u9+6dSs+Pl5fXz8+Pj4+Pr6hoeHLly/z588/cuQI\nLIuU0bdB28jYrVq1qj2X92A+uduQZexkSJyGhoaFCxdaWloSiURVVdXhw4efP3++p52SIV3m\nzJkzZMgQTU3NESNG8EupGhsb4VjbmJgY6Zn29/cHAMjJyWGxWE9PTwRBiESimpoav0NWXV0d\nRdHDhw/DL6TH2rVrCQSCUEtBWloaDoe7e/fu5MmTJTLvQYh58+bZ2dmJKt2cPXsWj8dLVUVS\nlOLi4unTpw8YMEBRUdHGxiYmJqabtz7r6uqYTOaAAQMwGIylpWVoaKi/vz+DwcBisW5ubtK2\nXl9fv3fv3nnz5s2cOXPTpk1iR7P0CXpzxg5BUTQtLW3Xrl1Pnz4VCtrev39///59X1/fkJAQ\n0ScMLBarp6c3ZswY2Nb0E7Njx47w8PAvX77Iycn1tC8yfgaqq6sHDx7MZrMjIiIsLCzq6ury\n8vJ2794dFxeXlJTU097JkBZ+fn7//PNPc3Pzw4cPYZElHy0trZaWFqh3KA0+fPgAIzYcDgf7\nPSkUCuzb4PF4OByOw+E8e/YsOzv72LFjUDRbGnC5XHV19REjRuTk5Pzzzz+CP4SJEye2trb+\n/fff8+fPh4obEqS8vNzMzCwqKmrVqlV8rb6ioqLhw4ePHz9+48aNkjX3HS5cuDBhwgR7e/tx\n48ZpaWmVlJTAecRXrlwxNzfvNjcePnw4ZswYFEU1NTXZbHZTU1NlZaWtrW12draCgoL07F6+\nfDkoKAiLxdrb25PJ5EePHpWVla1evTo6Olp6RqUEm80mEom3b992cnLqaV9EQH9UY+ft7S1Y\n+PkLIsvYyZAs48aNs7Gx4asMQHJzc7FY7JUrV3rKKxnSJjAwkEajiS2nMzMzAwC8evVKetZH\njhwJAIBywTBjB5snzMzMjIyMAACmpqampqYJCQnS86GwsBAAUFJSoqamJpShzMjIoFAoioqK\nUpLQys3NpdPpxsbG4eHhCxcu9PX1xePx9vb2x44dk+qPXZCPHz/SaLQFCxYILrLZ7AkTJvTv\n378bxCwLCwvj4+O9vb2HDx8eFRUVHR0dHBw8bNiw8PDwzMxMaetmv3jxgkKhxMbGCnaCHz58\nmEAgHDp0SKqmpUFvztj9OLAT+mV//PjxxIkT+/fv74au7F6CLLCTIUGqqqowGIzYUa1BQUHj\nx4/vfpdkdA+bNm1CEES0F62iogKLxSIIcv36delZh0GVIFgsNjIysra2VlVVFc7GoNPpUpUm\nvXPnDgDg27dvp0+fJpPJXl5ehw8fzs/Pz8jIcHR0BABIdYRudXX1mjVrJk2aZG9vr6ysDABg\nMBh0Oh0A4O7uDudhSJXU1FR9fX2OyHD6T58+kUiknJwcqVrftGkTDodzdnaeO3duQkKCp6cn\nFosVO3JNSgQHB3t6eoquL1++XFtbu5tHwnSdvhrY5ebmWlpaCqYQLl26xM/T4nC4TZs2dZ+n\nPYcssJMhQQ4fPozD4ZycnNTV1V1cXOLj46urq+GhXbt2tTW5UoZkaW5u7v65XnV1dRgMhsVi\nmZiYEIlEAwMDd3f3gIAAZWVl2E/z8OFDqToAx4MKxnYUCkVZWRluiWIwmK5PCP0+Z86cAQDA\nmhYajaaurg77RZhMpqWlpaamplStQ54+fSovLx8cHFxWVvbw4cP09PRdu3a5u7traGhIu1E9\nMDBw+vTpYg85OTklJSVJz/TFixexWKydnZ2qqioAQFFRccSIERs2bKBQKLt375aeXUGYTObB\ngwdF19+8eQPEqVj3cnpzYNdmV+zDhw99fHxaW1vfv38PVxobGwMDA9lsdmxsLI1G27Zt2x9/\n/OHk5GRtbd3JbWAZMn4xCgoKwsPDeTyet7e3trb2mzdvjh07tnfvXvgQhcfjORxON7tUVVV1\n7ty558+fk8nkAQMG+Pn5Qen5n5KGhoYVK1acPn26rKyMRCIZGxtra2s3Nze/e/fO0NBw8ODB\nYWFhUGVNGhQWFkKRMACAp6fn7du3y8rKeDyevLy8mprax48fw8PDz507J6WmaS6XS6fTYXOo\ng4ODgYHB8+fPnz592tzc3L9//8rKSjqdXlZWJg3TkGPHjgUHByspKVlbW6ekpLx+/frQoUM5\nOTlZWVleXl62trYTJkyQnnU+sbGxQ4cOHT9+vJub2z///KOurv7vv/+2tLQoKiouWLAAjs2U\nEmw2Gw63EIVIJLLZbOmZjouLQxBEWVk5JibGwMCgoqLi1KlTsbGxvr6+K1euDAsLk55pPp8/\nf4bDToRgsVgAgE+fPkHxHRkSAG0jYzd58mQcDpednc1f2bFjBwAgLS0NfltcXIzH48PCwrot\nCO0pZBk7GRKhsbFRQ0MDfnq9ePECLrLZ7MDAQD09vW/fvv3+++/Dhw/vTpe2bt1KIpGgXOqo\nUaMYDIaqquqlS5e604duo7q62tjY2NDQMC0t7caNG2vXriWTyQiCqKmpWVhYGBgYyMnJGRoa\nSlyhF9LU1KSlpeXv74/H44cOHaqgoEChUEaNGjVs2DA47SoxMdHe3t7Z2VlKe1I7duyAE6sA\nAD4+Pt7e3r///vuyZctUVVUxGIyJiYmXl5eGhoY0TKMo+uHDB3l5+WnTpgUHB2MwGFtb2yNH\njnC53ISEBCUlpaFDh2pqan78+FFK1vnU1dVhsdgVK1bgcLhFixZB7X0ul3vjxg11dXU8Hi/V\nQrf4+HgXFxfR9dbWVlVVVbHZLInw5csXBEF8fX2F1jdu3AiFzKT0Ny+EhobG3r17RddLSkoA\nAH1Oqr03Z+zaDOy0tbVh1wwfX19fAoEgOBnG29vbyMioG7zsWWSBnQyJsH//fhUVla9fvzo5\nOfn6+vK3Auvr6xUUFNavX0+lUtPT07vNn8zMTBwOt2fPHn4k0dLSEhMTQyaTCwsLu82NbmPS\npEnW1tbwH/nff/9VVVW1tbWFUvteXl7h4eHm5uYYDMbIyEgaoVVGRoaiomJTU9OJEyfgHPrg\n4OCYmJhBgwYBAJhMZkxMzMaNGwkEgpQCawcHh4SEBJibEcxKmpiYIAhCpVLDwsKGDh0qDdMo\niq5cuZJEIhGJRE9PTx8fHxhPkEgkmJ40NDTshhI39H+FhiwWa/HixUKHzp8/DwDYvHmz9Kw/\nefIEg8GI1tKtXbsWKu1Jye6hQ4cAADdu3BBa5/F4MEnGf86UKtOnT3dxcREtgYiLizM2Nu4G\nByRLnwzsiETikiVL+N/yeDwlJSUhkZvo6GgKhSJ9J3sYWWAnQyJERUXB3ojnz5/T6XRPT8/c\n3Nz379+/fPnS1NSUTCaPHTu2OyuIjYyMhBr0IF5eXgEBAd3mRvfw6dMnHA6Xl5cHv12/fr2K\nigqRSMzKyoqMjOTXdK9YsQIAsGXLFok7EBcXN2LECPj1zJkzjY2NJ02a1K9fPwCAoqKisbHx\n6NGjlZSUyGTyjBkzJG4dRVEajZaVlcVmsxkMBoIgbm5ukydPDgkJ0dPTAwAsWrRIXl5+//79\n0jCNoqi6urq8vDxsw4yLizt27FhWVpauri6DwVBRUVFWVnZ3d587d65UC61ev369a9cuAAAW\nixWNonJycrBYLP93JCUSEhIoFEpKSkppaWlzc/Pz58+jo6OxWKxU20ITExPxePzhw4dFD/n4\n+CAIUl9fLz3rfN68eUOj0UJDQ/mCABwOB7Z0SLVpRkr05sAO851dWsFSm6KiotraWmdnZ6ET\npFoWIEPGz0RzczOFQgEAmJmZ3bt3j0QijR49GpbSv3792tLS8vjx40K17dKjvLy8pKRkypQp\nooemTJly+fLl7nGj2ygqKuLxeC4uLvDbO3fucDicuLg4X19fV1dXvornggUL6HT6hg0bJO5A\na2sr7DwFAHA4HDs7O3V19ZaWloKCAl9fX0dHRzgAXllZ+ciRI/X19RJ3AIPB8Hg8PB5//fp1\neXn5t2/flpaWNjU1+fn5AQC2bNkyZMiQkJAQidsFAFy6dOn9+/eNjY33798nEAiPHz+ePn36\nwoULqVRqTU0NlMkdOnTow4cPLSwsMjMzJe5ASUmJq6urvr5+bGwsgiBcLtfb2/vFixeC55w5\nc0ZPT6+8vFzi1gVZuXLl+vXr169fb2BgQCKRzM3Nc3Jyzpw5ExwcLD2jKIqqqqqmpaWJlvAW\nFhaqqalJVbuOj46OTm5u7rVr12Df2PDhw9XV1RcsWLBr1y5fX99ucODXoc3AjslkCqplXr16\nFQDg6uoqeE51dbVUh7HIkPEzoa+v/+zZM/i1gYHB2bNnGxsbX7x48f79+379+k2aNAmHa7OZ\nSeJ8+vQJAKCuri56SF1dvba2lsfjdZsz3QCPx0MQhC9OW1tbW1dXB+sdsVis4ItVV1eHPQ2S\ndcDIyOjx48fwturq6q9evdq8efPu3bvt7OwePnxobGwMAJCTk1NTUyMSidu2bZOsdQDAgAED\n4Fyv/v37P3r0yMrK6smTJ6dOnVq3bh2CIFFRUSdPnuT/fCRLbGwsBoNRUFBQVlbm8XheXl4P\nHjz4/Pnzq1ev3NzcGhsbg4KCEhMTr1+/vnTp0pCQkFevXknQekVFhaurK41GKyoqqqurmzFj\nBvxLcHNzg/2YAIDMzMzdu3e7uLh0gwr9zJkz3717V1FRcfv27Y8fPxYVFXl7e0vVoqmpaVNT\n0+vXr/39/fmR68ePH6dPn15eXj5+/HipWhfE3t6+uLj4yJEjo0aNsrGx2bBhw9u3b6dOndpt\nDvwqoG1sxXp6evbv3x8q7rDZ7AEDBlCp1K9fv/JP4HA4WlpaYktBfzJkW7EyJEJJSQkOhxOV\nMTt8+DCRSOxmYciKigoAQFFRkeih9PR0VVVVyZpraGhYvny5u7u7mpqapaXltGnTnj9/LlkT\n3+f9+/cYDObu3bvw28mTJwMAoLxFTEwMv8iEy+XCvsXGxkbJOlBdXS0nJwebz+7evQsDHS6X\nm56eTiAQYOU4XP/tt9/Eyn11kfT0dAqF8vfff/NXWltb79+/b2pqGhISInFzfIqKigAACIJg\nsVh3d/epU6fq6enRaDQEQWg0Wr9+/XA4nIODA41GIxAIFhYW/fr1i4iIkKADwcHBzs7Ora2t\n8NsPHz5AZ5SVlQcMGLBo0aJhw4bhcLiUlBQnJ6c5c+ZI0HQvoaGhQVVVNSQkxNbWFgCgoaGh\no6ODIAiTycTj8WVlZT3tYJ+kT27FBgYGvnjxwsPDY8uWLePHj3/27JmgEACPx4uPj6+srJRl\nUGXIaCeGhoaLFi0KDAxct27du3fvAACVlZWrV6+eNm1aUlISLLfqNrS0tExNTfft2ye0jqLo\nvn37RowYIUFb//zzj7W19Z49e9zd3devX//bb7/BlWPHjknQyvdhMpkjR46Mj4+H1SOBgYEA\ngEuXLhUXbocqSgAAIABJREFUF+/cuTM0NBSetnfv3qamJgUFBSqVKlkHGAzGpk2b/vjjj+jo\naDweb2lp2dTUNHXq1NDQ0FWrVunp6eXm5o4ePXr8+PEDBgz4/PmzZK2/efMGtr46OjrOmTPn\n0qVLN2/e3LZtW0BAAABg3bp1kjUnCBTaMDY23rNnz61bt7BY7NatW+3s7AAACgoKFRUVKIq6\nuLgcPHjwwoULQUFB9fX1Bw4cqKurk4h1LpeblZUVHR3NT4erqamFhoaqqakNGDCgsLAwPz/f\n3Nw8PT399u3b9+7ds7Ky+vLli0RMt5+7d++mpqb+/vvvKSkp+fn5Erwzl8tdv369lZXVp0+f\nDh069OTJE0dHxxkzZkycONHf37+mpmbjxo26uroStCijV4C2kbHjcrlwbjTE2tpacAISTB0b\nGBj8CnksWcZOhgTZvn077ASEFVfq6ur79u3rEU/Onj0LZcb5fWpNTU2RkZFycnLFxcUSNDR4\n8GA3Nzeh/6CUlBQSidSd2YI3b96oq6vb2dllZmaWlpYqKyvjcDh5eXnYoVxXV5eamgp1g6WX\nwcrOzh44cKDgOzCdTrexsYFdohA8Hq+trS2pevZv377NmDEDg8EwmUxHR0eoeILD4bBYrKGh\nYXx8PPy9NDU13blz58CBA1evXoUiIJKyTiQS+/Xrh8Fg7t+/f+3aNXd3d/6LhcLIO3fuFLwk\nOTmZSCS2JeTbUaqrqwEAQl3eTU1NHh4esOB1zpw58JkKg8Ho6uqSyWQ6nX7gwAGJWP8hDQ0N\nY8aMwWAw1tbW/v7+NjY2WCx21KhRguoTnQZ+iNPp9JSUlPv372dmZg4cOBDutuPxeEdHx4sX\nL3bdyi9Lb87YfW/yBI/Hy8vL27x585kzZ/h5bMisWbO8vLwqKyu7yc0eRRbYyZAsHA7n1atX\nly5dKi0t7f75B4Ls27ePSqWyWCwvL68hQ4bQaDQNDQ1RWYSu8PjxYwRBxEaKNjY23TnRCEXR\nqqqqkJAQwcpgDAaDw+GgbqqysrKdnR2dTpe2pFZdXd2tW7fIZHJqaur27dvpdLqent7u3bvf\nv39fWFioqKjIYDBg6qjrtgICArS0tASHleXm5jKZzNDQUP7K5s2b6XQ6BoPR0tIiEAhEIjE6\nOrq5ubnr1m/duoUgiJaWVkhIiKam5s2bN1EU5XA4p0+fhhGGvLy80CWRkZG2trYkEkkiL7+x\nsREAIDrunMvlrly5EgBAIpHodHpERMTbt29RFG1paVm7di0Oh8vIyOi69R/i4+NjbGwsGHfC\nHnmJNOfu379fTk5OqNzi27dv9vb23t7eXb//L04fC+yam5trf0RNTQ38oqmpqeec7yZkgZ2M\nn5iampoDBw7Mnz8/MTHxxIkTgnW0EmH37t26urpiDy1YsGDYsGGSNddOKisr6+rq8vLyNDU1\ncTiclpZWv379sFisqampYBWaVFm9erWcnNzgwYMHDRoEf+xv3751dXXt379/VVWVjo6OWDGa\nDpGfn4/FYh8/fiy6jsFgnjx5gqJoSkoKmUzevHkzfDNns9lnzpxhsVgSkbzJzs6mUChYLPbc\nuXNhYWEYDEZHR2fIkCH87b8//vhD8Pzy8nIFBQX4lvvgwYOuO4CiqIWFRUJCguj6kiVLGAxG\nv379vnz50tDQsHPnzvDw8AkTJixevHjmzJksFksonSFxbt68icPhRDXkXr16hcfj+dI8ncbN\nzS06Olp0/fbt23ACShfv/4vTxwI7FRWV9u/kYrHY7hGW7EFkgZ0MGZ1my5YtpqamYg8lJSX1\nePcVm82+du3ali1bduzYcfv27e5MoPJ4vMWLFwMA4OiFAQMGwBntcCdky5YtWlpaXTSRkJAg\nJD7Kx8rKauXKlR8+fCCTyaIzD548eSKR2OLRo0cAgFmzZqmoqOTm5paUlOzbty8xMTEpKQnm\nTf38/ODrbW5uzs7O1tXVHTp0aENDAwCgoKCgi9Yh6enpJBJJSPY5Ly+PQqEYGBgkJibm5+ez\nWCwWizVx4sSoqCg3NzcMBoMgiLQ/sxcvXtzW3/+QIUPi4+O7eH9VVdXjx4+Lrre2tmIwmL/+\n+quL95cgHz9+PHPmTGpqakZGxqtXr3ranXbRmwM7MfIKd+7cab+KEh6P19fXb38gKEOGjF8K\nfX39srKyxsZGUSGJp0+f9vi7Bx6PHzx48ODBg7vfNIIgv/322/Lly5cuXVpTU6Oqqjpo0CC+\nVqi1tXVlZeW3b9+6Mrv2/fv3bZXG6+npVVVVXbhwQVFRUVREbeDAgcOHDz958uSQIUM6bR3e\np1+/fgwGIzg4eNSoUZqamkZGRu/evXv58iXcA/3rr7+0tLRoNFpjYyMGg5k+fXpKSsrDhw9x\nOJyBgUFXTPMJCgoqLCwcOXLkqFGjHBwcEAS5e/dudnb2vHnzMjMzlZWVvb29x48fv3nzZljz\nBwC4d++eg4NDamrqqVOnJOKDWD59+qShoSH2kIaGRk1NTRfvj8FgUBQVXYeL3SaZ+X1QFE1K\nSlq5ciUsb3337l11dfXkyZO3b9/+Ew+tljZiAjtJ/TvJkCFDxuDBg+l0+urVq5OSkgTXHz9+\nfPr06XPnzvWUY70BPB4PAPD29objHwRhs9mwy6Er91dUVGxLE66mpsbU1LSiosLIyEjsZ7yx\nsXHX9eQwGMy6desCAgJWrVr1/Pnzu3fvlpaWksnks2fPfvz4MSIiIjk5+dq1a/X19SoqKubm\n5jQajc1mL1y40MfHB+rOSISVK1f6+PgcOnTowoULKIqam5tfu3bN1dX18uXLZ8+e1dTU3L59\nOxaL5Z9vYWGBwWDOnz9fX18vPa1WFRUVvrClEO/evbO3t+/i/c3NzW/evDlx4kSh9du3byMI\nYmpq2sX7S4Rly5atX79+3759EydOhGWX9+7dCwkJGTdu3KVLl3pJ9Nn3QFF0y5YtZDJ5/Pjx\nS5YsyczMfPnypbRrC/oWsq1YGTK6Amy/jYqKKioq4nA479+/37Nnj7KycnBwcE+71sNwOBxV\nVdVdu3bxV549e7Z9+/b58+f7+PgYGBh08f5ZWVlUKrW6ulpovby8nEAgXLlyZe3atZaWlmKv\nDQsLmzx5clest7a2Zmdnw6CKSqVSKBRra2t9fX0MBuPo6FhWVsZmsz08PFgs1s6dO1+8eFFe\nXp6VlWVvb6+hodE9so5z5syRk5P7888/hdaPHj1KJpPJZDIMBKXErVu3BGvsLl68GBISMmjQ\nIDizeN26dV25+efPn4OCgrBYrKWlZVhY2OHDh+HHemNjo42NzYQJEyTwArpMVVUVgUA4efKk\n0HpZWRmZTO7lc8Z681YsQFH08+fPmzdvnjVrlrOzM3w6IRKJVlZWwcHBa9asyc7Ohu1Cvyyy\nwE6GjC5y5coVc3NzAADMi9BotOXLl3fPA2Rtbe3t27efPXvGZrO7wVxHWbRokbq6+tu3b79+\n/RoUFAQl31xdXWGZ14QJE7ryzsPhcAYNGuTm5lZTU8NffP/+vZ2dnYuLC4/Hu3PnDgaDEe0C\n/vbtm6amJpRT7hxPnz41MTGhUCiOjo4jR47U0NDA4/G+vr67du26f/8+/7SWlpbExEQGgwET\nDRQKxdfX9+DBg/n5+V2U/Ghtbc3MzIyOjvbz84uJiTl16hTU2xcEyvt5enoKHnrw4IGqquqC\nBQvU1dXFzleVILAr9vnz5xEREXg8PiAgIC4uTk1NTU1NDYfDxcbGdu62d+/eVVNT09PTMzEx\nIRAI5ubmZDJ54MCB69atMzY2NjQ07CWdE3v37lVXVxc7INvf3z8sLKz7XWo/vT2wE+Ldu3eX\nL1/esGHDzJkznZ2dodiPgoKCtbV1SEjI6tWrz549CxXbfxFkgZ2MvguXyy0tLb1169anT596\n2he0qqrq+vXrL1686J6Q7smTJ3A4LNzQIZPJf/zxR29r5P/27Zunp6eysrKpqSmDwVi9enVM\nTAyFQhk5cuT169cNDQ1Hjx7dlftXVlZaWloqKCiMHz9+3rx5fn5+cnJy9vb2/DSeu7u7k5OT\noHYdm82eOnUqi8XqtJbex48f1dTU/P39a2tr4QqPxzt48CCRSNy9e7fYSz58+JCRkWFmZgYz\nC1CGZubMmYL6qe2nqqrK1tZWTk5uzJgxc+bM8fHxoVAoDg4OoslLCwsLMpmsp6c3bdq06Oho\nDw8PLBY7derUuro6ibSPfB+oYwcnYQwdOlRQxy4vL49MJh86dKij96ytrVVVVQ0LC2Oz2Twe\nb+/evTY2NrB8kEqlzps37/sRc3V19YsXL7rnKSgpKcnZ2Vnsobi4OC8vr27wodP0scBOCA6H\n8/Lly8zMzKVLl/r7+xsbG8NnbiaT6eHhERsb+9NHPLLATkZfhMPhrF69WrBQydLSUlDP7Ofm\n4cOHcnJy48ePv3fvXnNz86dPn44fP66jo+Pu7v79D63W1tbz58+vWLFi3rx5O3fu7Ib9Cg6H\nExsbCwCQk5OTk5MT7JYwMjLC4XBd/K2x2eyMjIzZs2ePHj167ty5mZmZggmq9+/fDxw4UEVF\nZcaMGSkpKXPnzjUwMFBTU7t3716nLcbFxZmbm4uG72vXrmUwGGLD+mvXruHxeF1dXQRBCAQC\nnPwB9446+hjA5XLt7e2dnJwE81Iw1IN5SsGTU1NT1dXVV61aNWXKlNGjR8+ZM2fZsmXLli3z\n8/OTl5fvnscADQ0NLy+vqKio5ORkwUAhISGhrY3y75CcnKyrqyv0R87hcAoKCgAAbY3y43A4\nycnJ/OHRBALBx8enpKSko9Y7RFpamomJidhDYWFhEhHckR59O7AT5c6dO15eXvA52N7evpck\ndaWHLLCT0RcJDQ2l0+nbt28vLy9ns9lPnjyZNWsWDofLzs7uade6Azs7u0mTJgl9ildWViop\nKW3durWtq4qKikxNTSkUirOz85gxY3R1dXE43LJly6Tt7bJly+zt7VNSUggEwuLFi58+fdrQ\n0PD333/PmzcPQRBpy8k2Nzfv2LEjICDA1tbWz89v5cqVXczvWlhYJCcni67X1tYiCCKqY8Lj\n8QwNDRUVFU1NTe3t7WFFkIKCApPJRBBk8eLFHbJ+/vx5Mpn87t07ofWKigoCgSCke9LY2Ghk\nZOTm5vbmzZs9e/bIycnR6XRtbW3YuWJmZvbs2bMOWe8osPsVagoKcevWLQDAt2/fOnRDX1/f\n2bNniz2kr6+/Y8cO0XUejzdp0iQlJaVNmzYVFha+f//+0qVLI0aMoNFoYh2TFLB3RNREY2Mj\nk8nctm2b9Ex3nZ8ksHv+/PmSJUtMTEwAAKampkuWLJF2ON9LkAV2Mvocly9fxuFwgsVMkPj4\neA0NDYkMFejNwHbOly9fih6Kj493dXUVe1Vtba2Ghoavr6/gvuTJkyepVGoXK9l/SFRU1MiR\nI/F4/JEjR+BKeXn5jRs3Kisr7ezs8Hi86B6ilGhqagoNDdXU1CQQCDQazdra+urVqx29CYvF\n4r8QIeTl5c+ePSu0COXuGAwGDocLCgo6c+bMkydPTp486efnhyCInJxch6zHxMR4eHjk5OQs\nWbJk06ZNBQUF/Ph+8ODBorLPFRUVLi4usKiRRqPBjXvYoamoqKikpCTV5EV5eTkAQOxsvSdP\nngAAOjrhbejQoYmJiWIP2djYpKSkiK4fP36cTCYLhbA8Hm/8+PG2trYdst5R/Pz8TE1NBfPi\njY2N48aN09bW7m1VE0L8DIHdtm3bAABWVlarV6+W9ryd3oYssJPR55g6der48eNF1xsaGkgk\nUm5ubve71J1cvHiRRCKJPXTkyBEWiyX20NKlSw0NDVtaWoTWd+7cqaCgIPGZHIIkJibq6OgM\nHDgQRdEDBw5oaWnxd2NJJBKJRBKbaJE4lZWVcJisoaGhr68vv8Y6JiamQ/cxNzcXGwrX19cj\nCJKfny+0furUKQwGQyQSU1NThQ5BYb8OzRR2cnKCURr/Z6itrQ2H2k2cODEiIkL0Eh6Px2Qy\nVVRU5OXl9fX14W44BoOh0+kIgkyaNKn91jtKc3MzmUw+f/686KGMjAwajSa2t+A7TJkyRWw7\nM4fDUVJSOnbsmOghHx+fmTNniq7DByShoWSSpb6+fujQoWQy2dfXNzY2NjAwkMFg6OnpCY33\n7YX05sAO005VlBEjRpDJ5JiYmLi4OFHJJRkyZPQqXr9+bWlpKboOP7e6rk/WyyESia2trRwO\nR/RQc3MzX4dWiNzc3KCgIAKBILQeFBT07du3O3fuSN7R/zFs2LDy8nIDA4Pk5OSZM2fOnDmz\ntLS0tbX1xo0bHA6npaUlIyNDetb5uLq6Njc33717t6SkJCsr69atW/X19cOGDVu7dm1eXl77\n7+Pp6Zmens7j8YTW09PTFRUVra2thdbJZDKPx1NWVp43b57QIR8fHwDAoUOH2ml6586d+fn5\neDz+4MGDL1++vHfvXkJCwrt376ysrD5//vzmzRsWiyV6VWFh4YcPH75+/crlco2NjTMzM0tL\nS2/evBkZGYkgyIkTJ1BxSr8SgUgkjhkzJjk5WejPlc1mr1271t/fv6NabmPHjs3KyiorKxNa\n379/f0tLi6enp+glxcXFNjY2ousGBgZ0Or24uLhDDnQIBQWFy5cvZ2Rk6OjoFBUVUanUpKSk\nZ8+e9RKZvb5K+2PAJUuWqKur/4KJK1nGTkZP8enTp/Pnz69bt+7o0aMdmrQzbNiwhQsXij2k\np6cnKJz2U1JbW4vH4y9evCh6KCAgwN/fX+xVBgYGbfVsMplMaU+F19DQUFBQwOPxR48ehSvl\n5eWDBg1ydXU1NzfH4XAVFRVSdeDBgwcAgE2bNgmtc7lceXn5DlXx3717l0qlOjg4QI1fuHj2\n7Fkqlbpx40bR82GdGUxYQjgcTnFx8fXr152cnAAA06ZNa49dHo9HJpNZLJbQhNwHDx5gMBh3\nd3cMBvPw4UPRCy9fvowgiKKioqghGGuKTl2TIG/evGEwGKNGjXry5AmXy+VwOA8fPhw6dKiG\nhkZVVVVH78bj8UaMGKGnp5eXlwezfc3NzVu2bCGRSGJ/+CiK9u/fv63CUzk5uXPnznXUh07T\n2Nj4559/2tvbKygo6Orqjh07tleNPhOkN2fsOhDYff36dfLkyZ34O+vryAI7GT3CmjVrKBSK\nnJycpaWlmpoa3BJqp7jX/Pnz7ezsRNdLS0sRBOm2Ofc9SGhoqImJiVB11KlTp7BYbFsfFQ4O\nDqJatSiKfv36Fcr5SsXR//H/2HvvgCa25/97d7NJSEISOqFL70iv0hVFwIZiQ0VURAX7xYK9\nXgV7B0VRbCiiXERREBuK2K5SFEFFQEBBEKQTkueP8/vm4ZNEL2qauq+/cE6yM8GQzJ4z856Y\nmBgURWEYdnd3DwkJ8fT0JBKJbm5u5eXldDpdRUVl586dQg0gKioKhmG+03J9fHz6WOj2+fPn\n8ePHwzAMklTQgmBra2tqaorD4b5W+8Vms8lkMoFAqKqqYjKZmzdvlpWVhf6v0A2G4VGjRvXF\ne1ZWFgRBgwcPlpWVBdq869atA5mlmZkZDMOTJ0/m+8THjx9DEITD4err61ks1rlz54KDg01N\nTe3t7T09PWEYHjx4cF8C+GFKSkrc3d0hCCKTyVJSUhAE+fj4vH379seu1tLSMm3aNBwOR6VS\n9fX18Xi8jIzMvn37vvb4cePGBQUF8dofPnwIw7BoxKLZbPaHDx9MTEy0tLQ2bNhw6dKlhIQE\noLHMe0AvCfwmid0fC5bYYYiezZs3UyiUxMREjjJFfn6+kZGRh4dHXwbVl5WVEYnEHTt29Da2\ntrZ6enp+be74b0ZTU5Ojo6OSktKSJUtOnTp18ODBsWPH4nC4LVu2fO0pq1atMjIy4hVDSUhI\nkJaWFnYp96dPn4hEopaW1po1ayZPnrxq1aqrV68ymczp06dramqOHDkyIiKiL9eprq7esmXL\nhAkThg0btnTp0ry8vD4GEB4ejsPh+C6NGTOGSCT+5xV6enrc3NyMjIyA07a2thMnTvj4+OBw\nuFGjRn272S4kJASCIGlpaWNjYzKZPGrUKFdXVxRFKRQKHo9HEIR3PgEvEyZMgCBo4MCBMTEx\nHh4eIK2UkpIC3bUwDH+tbai7uxtBECqV2tHRMXjwYJBh9z7a+lpdpmCprKy8evVqZmYmb0vv\nD/D+/fv09PT4+PicnJxvf3/dunULh8NxjdloaWlxcnLy9/f/+Uj6yPDhw21tbTlbvKAdODk5\nGUGQvr+NRQaW2P3aYIkdhoipq6sjkUhJSUlc9oqKCmlp6eTk5L5c5OTJkwQCYejQofv27Tt/\n/vyGDRt0dXV1dHREdv8tdjo7O3fu3Ont7a2qqmpoaDh27Ng7d+584/H19fXKyspBQUG9hXkv\nX75MpVL//vtv4cfLHjZsGA6H8/b2PnToUEZGxr59+5ycnOh0+v379/38/PrSwXDhwgVpaWl1\ndXUHB4chQ4bY29sjCBIZGdmXAvy9e/dCX2lTMDMzU1JS+s8rnDp1ikqlVlZWctnj4uKkpaW/\nvdn8/v17sMMHQZCsrGy/fv0MDQ2JRKKZmZmcnNyyZcuUlJS+nVu/ffsWzN7lqCKXlZUdOXJE\nW1vbyMgoMDAQRdFvPF1bWxuCID8/PyCn5+Hhoa6uDv2fujUEQXxP9iWNzs7O58+f371793t7\naVevXo2i6MyZM5OTk69fv759+3Z9fX09PT2BpJh9oaKiAobhvLy88vLyUaNGgS1bKSkpMzMz\nR0fHr221ihEssfu1wRI7DBFz8uRJBQUFvjtzEydO7PuI1WfPnk2ePNnU1FRBQcHJyWnVqlU/\nOabpt+fZs2d6eno0Gs3b2zsoKMjY2BhBkGXLln1vZ+KPcezYMTk5uUmTJhkYGEhJSZmYmISF\nhZWXl7e0tMjKyn5NQIRDQUEBDofD4/F0Ot3Ozg7kJe7u7jQaja+qHBdtbW04HM7Z2ZnL/uDB\nAxiG+zLfaezYsSEhIbz2rq4uOp3+n1tux44dA+ImhoaGYHPa1dUVj8dfvHixra2NQqHw6qT0\nZtmyZWBs3dKlS3vbS0tLYRhWVFRUV1f/xtMTEhJAAofD4XA4nLKysoyMDJ1OV1RUBP00ysrK\n345fvLS1tc2fP5/TzwtBkLOz89OnT/t+hYyMjMGDB4PXa25uvnTpUlF+XFy6dIlKpT558oRE\nIsEwrKamNnjwYDs7O3AwraCgILJI+giW2P3aYIkdhoiJiYmxtbXlu7Rq1SpPT08Rx/NH0dnZ\nmZKSEh0dPX369EGDBhkaGhIIBEVFRR8fH2FrO3/58kVFRWXmzJm9c3omkzllyhQNDY3/PAu2\nsrLC4XDh4eGLFi0KDQ2NjY1NTU01MzPT1dWVk5Pry5CopUuXQhBkb2//8OHDrq6u2trajRs3\ngkyxLzK5Li4uGzZsYLPZvKFaWFh8rXKf6yVoaWmB73IKhTJo0CCOmrGVldW31QR9fHyWLl1q\nYmKCw+F6qxD39PTQaDQIgvbu3fuNp/f09CgoKICsSEVFxd3dXV9fn0gkEggEGIZBL63Elph3\nd3d7enpqaWklJydXV1d3dnY+evRozJgxFAqFV8zyPxHNbQwX58+fV1BQYDAYOBzu4sWLHHtH\nRwdQzxV2kev3giV2vzZYYochYuLi4rS1tfkuzZ49e+TIkSKO5w+kuroaHEVt3779+vXrycnJ\nYG7HN8r/BUJubq6MjIy9vX1sbOy+ffusrKzAdpGMjExAQADvzAYO9fX1MAxTKBQFBQV/f//g\n4GALCwtwDkulUiEI4tsNykt0dDQYGslBX1+/qqqqL8+1t7fX1NQEcyM0NDSmTJnCOfdXV1c/\nduzYf15h6NChixcvZjKZ1dXVJSUlS5YsGTx4sIuLy4wZM9TV1b8xMoTNZru4uHh4eFhaWoLD\nUyqVOnDgwEGDBsnIyEAQZGJi8p/ed+7cCRI70KvEOYSFYRjsgUVFRfXl9yB6Dh48SKfTga4v\nBEEMBmP48OH5+fkTJkywsbERd3R94tmzZ+AXDu4NehMeHo6iqJWVlVgC+xpYYvdrgyV2GCLm\n5cuXEAQ9evSIy97e3q6hocHVEoEhDAICAhwdHVtaWnobr1y5gsPhcnJyhOq6oqIiMjLS0NAQ\n9JYOHjz40qVLycnJY8eORVH05MmTfJ8FNOS9vb17CylnZGRIS0vb2trCMNz3efbNzc0pKSnz\n5s3btm1b33Vid+zYgSAIgUDo37+/l5dXYGCgjY2NnJzcv//+m5eXB8NwWVnZf15k1apV/fv3\nZ7FYJ06ckJKScnR0XLJkycaNG4cOHQq6Ir6271hZWUmlUgkEgoWFhYmJiaKiIkhPEQTR0NDA\n4/FcnQF8AZMe5OXlQRoHQRCRSNTR0VFTUwM5B41G6+NvQ8SAGwB3d/djx47dvXv3zJkzY8aM\nQVF0x44dEAQBcWbJR1FREYIgrnF2L1++JJPJ5ubmZDJZXIHxBUvshEVnZ2d+fv6NGze+S5f8\ne8ESOwzRExQUZGho2FvvAOgNqaqqNjc3iy+u/wYMOZXYQ6u+AOq4+W6PjR079ttzCKqrq3Ny\ncgoKCvpy9Pk12traNDQ0Zs2axXUotm3bNgqFwnf/DIi0bdmy5cmTJ/n5+ZzPq0OHDgFBZqF+\nu4PtFrCzRSQS1dXVlZSUyGSys7OzgYGBoaEh31kIvFRUVJDJ5Dlz5qAoylHUa21t9fLysrS0\nZDAYy5Yt4/tEW1tb0Mo6atSo1atXBwUFUSgUQ0NDFEXDw8MZDEYfJ67icDhQpgZK/VAUNTIy\nsrKy4uze9SVBFDHt7e04HM7T05Pr3RIbG0uhUEgk0q8yHnrUqFEQBAUGBt67d+/Lly9geq+S\nktKIESNGjRqFx+PFHeD/gCV2AmD9+vVcd5wHDx4EjTMAGxub7yoU7TtYYochepqbmwcOHCgl\nJTV8+PCoqKhJkyapqKhoamoK6U0uEHJzcx0dHTlfgaqqqnv37hVLvc5Pkp6eTqFQ+EZ+4MAB\nQ0Ofor1PAAAgAElEQVRDvs/KyckxNzeHIAhFUZAZrFixgndAWV9ISUmhUqlc+4VsNpvFYhkZ\nGfFt0VVTU8PhcL1PD4cNG/bu3bsvX75AEEQikX4gjL4DUh8VFZWJEyfSaDQ6nS4rKwtkSiAI\nsrW17fvnZ0pKCg6HU1BQ2L59++nTp9esWaOjo6Ojo1NeXn7q1CkKhcI72+3evXsQBI0ePTo4\nOFheXv7w4cM1NTVv3rzR0dEhkUgIgvSu2fo2nMEMcnJy/v7+lZWV9+7dMzY2RlEUTFfT09P7\njt+LSEhNTUUQhLeCELxbEAT5gWm/YmH//v2gxJPzNpaVlV27dm1XV5e+vr6cnJy4A/wfsMRO\nAEAQtGTJEs4/wYQZIpE4cuTImTNngnmCdDq9L7v93wuW2GGIhZ6enkuXLs2dO9fX13fatGn7\n9+/vy5uwu7v75cuXvJITwubq1at4PD4kJOTBgwdNTU0lJSXbtm2jUql9VF+TKC5evEin0/ku\nHT58WFdXl9d+5coVPB4fHh5eXFzMZDLr6uqOHz+urKzMd2Lvf7JmzRp3d3e+SzNmzJgwYQKX\nsbGxkXN6SCKRyGQygiAMBoPBYERGRkIQJFR93dbWVtB2CjLRhoaGHTt2gN1lsAH2DWlcvqip\nqbm5uVlZWSkrK7u5ua1Zswa0Z7a0tPAdNRsUFISiaFdXF5PJ3LhxIyiq41QK6uvr9911dXU1\nZ7OARqOBAkccDqejo0Mmk0HD7He9FhGwdu1aRUXFMWPG8C4NHToUhmGuw02Jpb29HUVRR0fH\nL1++PHr06M2bN+Dm6ty5cxAETZw4UdwB/g9YYicAuBI7XV1dOp3eezhxSkoKDMNTp04VuGss\nscP4JXj37l1gYCBn1Km8vPzKlSu/psgqWDo6OtTV1RcvXsxlv3PnDg6Hu337tghiECCgxpGv\noG54eLifnx+Xsbu7W1NTk/flFxUVSUlJpaamfm8AK1eu9PLy4rs0c+bMcePGcRl9fHzAFqmm\npiboHlBRUQHvBJDwCbWjcM+ePRAE8Wbw7e3tMjIyOBzu2+2ovCgoKJw7d47vEoFAyMzM5DJa\nWFj0TsTBvc3Nmzerq6tlZGT69ev3Xd5BC62MjIysrKyUlBQnY0YQBOwkvXjx4rsuKGyWL1+u\nrq4Ow7CSkpKdnV14eDiojPzw4cMPvHzxsmLFCgiCrKysrl69evv2bV9fX9D6A8PwoEGD7t+/\nL+4A/3+wxE4A9E7sPn78CEHQ8uXLuR4zYsQINTU1gbvGEjsMyaesrExJScnNzS0jI6O6urq0\ntPTw4cOqqqqDBg3q7u4WtvcrV65ISUnxLf4LCAgICwsTdgACx8HBYdSoUVynsYWFhSQS6ezZ\ns1wPzsnJwePxjY2NvNeZPHnyt2vy+HLq1Ck5OTm+x7hWVlZr167tbWlqaoJh2NTU1NDQ0NfX\nl0AgDBgwwMfHx9zcHCQiMjIyP/MeKCsrW7FixfDhwwcNGrRw4ULebzIwNMLHx4f3ueAs5XuP\nAq2trTdu3MhrB4PtX758yWUH/b9896VkZWWtra2/y/vAgQNBVy/nUNvc3Pz8+fN//fUXsPAq\nh4uRuro6LS0tBEHc3NwQBLGwsDAyMsLj8QEBAUpKShQKhUvVT/JZsWIFV182Ho83MDAwMjLC\n4XBCHdr7XUhyYodAvyAdHR0QBBkbG3PZzc3NQc6HgfGnERERYWFhkZ2d7evrq6KioqenN23a\ntHv37j169Cg+Pl7Y3ktLS/X19cG9NRfW1tavXr0SdgACJz4+/saNG0OGDLl27VpNTc2LFy/2\n7t3r5uYWEBAwZswYrge/efNGU1MTnAByYWFhUVZW9r3e/f39cTjchg0buOxJSUlFRUVgcBaH\nK1eusNnsrVu3Njc3E4nE48ePOzo6EggEBwcHIH7x119/gbK/HyAhIcHU1DQzM1NbW9vW1rao\nqMjV1XX+/PlsNpvzGLA1mJWVdeXKFa6nl5aWgpzju5yOGjUqLi6uubmZyx4bGwvyVy67iYkJ\nhUJZs2YNl/3Ro0eNjY1Dhgz5Lu/bt2+HIAjs9t28ebOlpSUvL6+mpmb79u0gUQa3+hLC9OnT\nweaip6fn7du3TU1NYRgGDRPOzs5dXV1Tp04Vd4zfx/r169+9e6eoqCgnJ4cgiL29/dKlSwMD\nAxkMBpvNnjZtWkVFhbhjlHjEnFj2GajXjh2TyaTT6Zs3b+Z6TGhoqDDqK7EdOwwJp6amBkEQ\nvl2c0dHRjo6Owg7gGy0FS5cu5buXI/m8evUqICCAc7StoqKyZcsWzuje3pw8efJrs0TXrVvn\n4uLyA94vXbqEomhwcHBWVlZFRcXdu3cXLFiAoujOnTu5HgkkLXJycoqKikxNTUkkkp2d3eDB\ng1VVVUE+V15e/gMBsNnsu3fvoih68ODB3sZbt25RqdTeasPr1q2DYZgzIWDEiBF37ty5fPmy\nr68vBEHm5ubf6/fLly/Gxsb29vYc7b2PHz8uWLAAj8fzFW05c+YMiUQiEAiTJk16+PBhW1vb\n27dvDx48SKFQUBT9gfEJnGFiKIoyGAwEQcC4M3l5eTqdjiBIXV3d915TGLx+/RqCoIcPH168\neBFF0cmTJ9+8ebOqqur+/ftqamoIgmzbtk3cMf4IaWlpBAKBQqHcunWrt/306dMwDE+aNElc\ngfVGknfsfqXEbvz48Q8fPiwtLa2rq1u2bJmenl5vffMXL15QKJSAgACBu8YSOwwJ5/bt2wiC\n8D1uu3DhgqysrLADyMvLQxCkoqKCd8ne3r53dewvR1dX14sXLz58+PCNx5SUlEAQ9OzZM94l\nFxcXsL/1A9y/f9/T05NTv29jY8N3plZCQgKBQAA6IEwmMzMzc8uWLcuWLTtx4oSbmxuRSOQ7\nm64v+Pv78zZqsNnsHTt2qKiogMtmZGSAQjQEQZydnVVVVcG2FpFIBErFfdfP601NTU1AQAAE\nQTQaTVVVFYIgbW3t3vMketPT0+Ph4aGpqWlqasrZswBZXV/GXfBSWFgILgJeCw6HQxBET09P\nWlp669atEAR9Qyla4Fy5cmX8+PHm5ubm5ubjxo3rrV1y5swZRUVF8HNubq6bmxuYlgtaZ752\nryX5bNiwgUgk8u3+NjU15bxk8YIldgKA73bj+fPnwerJkycpFAqCIPn5+QJ3jSV2GBIOkHvg\nq9R19uzZvoxv7zvl5eUZGRnZ2dkfP37kGFkslp2d3dChQ7l6Nfbu3UsgEEpLSwUYgGTi6+vr\n4ODAtTm0a9cuAoHwkwJy3d3dr1+//kYTDDjpJpFIXKXlxcXFOBzO29v7h13T6XTOZ2xv3r17\nB0FQSUlJfX29rKzssmXLtm3bhsfjaTQaiqJg0C0EQWAP6Ye9s9ns8vLytLS0pKSkx48ff7tM\nsKmpKTg4GEEQ0C4AxqB9bzdubygUCplMVlRUNDIycnZ21tPTg2F4wIABiYmJEASJRnWIxWLN\nnj0bj8cHBgaGhYUFBgaC1G3mzJmg+vPo0aNcvRGdnZ2vXr1qbW3dsWOHpaWlCIIUBosXL4b4\nFVOy2exhw4YhCPLD9yoCRJITux8svBA9R48e/dyLpqamz58/c3TsPn/+LCMjc+bMGTs7O/HG\niYEhekxMTAgEQk5ODjj86k1OTk7//v0F4uXZs2dhYWH5+fkUCqW7u7u7u3vEiBH79+9nMBgw\nDJ86dcrDw8PGxiY0NNTY2Li6ujojIyMtLe3w4cN6enoCCaCgoODatWslJSVKSkq2trZ+fn5g\nf0ISOHr0qLe3t5mZ2eTJk01MTOrq6jIzM2/cuHHkyBEDA4OfuTKKojo6Ot94gL6+fmBgYE5O\njru7+5QpU0CB3YMHDw4dOoTD4YAy1A/AZrNbWlrk5OS47CwWCxibm5uvXbtGpVLXrVuHoiid\nTl++fHlzc3NVVVVHRwcMw2PGjElISPgx7wAtLS1QJvif0Gi0EydObNq06dGjR7W1tQYGBvb2\n9nyLPvuIvb29tra2hYVFXl5ednZ2fX29uro6m82eM2cOBEHXrl2ztLT84Yv3kSNHjhw/fnzi\nxImnT58mEona2tqVlZU9PT2g8DEyMlJHR+f9+/eNjY2cr0ICgaCvrw9BUGFh4bffNpIMOAoH\nStFclJWVsViszs5OvqsY/w9xZ5aC4cuXL8JL4bEdOwzJJyQkxMTE5NOnT72Nd+7cIRAIFy5c\n+PnrFxQU0Gi0oKCg4uJiFovV1dWVm5trb29vYGDA6Qatq6tbtGiRlZUViUTS0dEJCgr6gQHk\nfGEymbNmzYJhWE5OTl5eXk5OjkAg6Onp8b2nFxetra1///23t7e3qqqqlZVVaGjo8+fPReP6\n8+fPrq6uJBJJXV1dVlZWWlqaQqFQqdSfFJrR1NSMi4sDP584ccLV1VVGRkZKSsrY2BiG4Xfv\n3oWGhgYHB3Me39XV9ezZs9TU1EePHnl5eUVHR//UqxIr58+fJxKJ169fNzU1dXJyArvO79+/\n19bWBsrhe/bs4Ty4qalJGL3nxsbGzs7OsrKy58+f5zRoZ2dn0+l0KpXK/j+dnb/++ovria9e\nvSKTybzt278KQE2w91sLcObMGRwOJyFKxZK8Y/ebJHZCBUvsMCSfhoYGKysrDQ2NTZs2Xb16\n9dy5c5GRkUQice7cuQK5/sCBA4cNG8Yl//Hlyxd9fX0R6CksWrSIQCBISUkFBwfHxMRER0c7\nODggCKKgoCAJf5jgeDozM/P9+/fiioHJZJ48eTI0NNTZ2TkwMHDTpk29z8p/jLlz51paWnZ0\ndISEhJDJ5MWLF6empmZmZlpbW4Ou23HjxgUGBm7fvn3GjBlRUVGnTp3ijIUYOnQob8Lxa7Fg\nwQIcDkcmkw8ePHj+/Pno6GgFBQVXV9eWlpYDBw7QaLS3b9+GhYWpqalBEEQgEGxsbAQoxgGa\nghEE4dXtO3v2LARBoNguIyMDRdGIiAiwlfX58+dz586pqan5+/v/ikNfOFhbWyMIMmHChKys\nLDD/AzR3q6urS4h8EpbY/dpgiR3GL0FbW9v69ettbGxIJJKCgoK3t3dKSopArlxXV4cgCF91\n0D179vCdxCBAPn78iCCIvLw8V7EakKVYuHChUL1/m+LiYiDVJi0tDQrLhgwZ8u7dO2H4ysnJ\nGTlypLa2toyMjJOT06ZNm3iHawmW2tpaNTU1MH8dNKg2NDTMnTuXSCRevnxZT08PtDUYGxsP\nHjzY29tbXl5eU1MzPz+/p6dHVVX18OHDQg1PBFhbW2tra2tqasrJybm5ue3cuROMAG5vb5eS\nkpKXl7eysjp27NiTJ0+ysrKio6NJJNLs2bMF4vrDhw8QBGlra/MugWadmTNngn9mZWUB8S9w\nOkkikf76668+zsaVWJ49e0YikRgMBii3wOFwxsbG1tbWKioqYrx96g2W2ImCsrIyb2/v760U\nrq+vDw4OHvNNbGxssMQO40/m8ePHEAQ1NTXxLmVnZ+NwOKHuDRw/fhyGYb6jCLS1tVVVVYXn\n+tuUlpbKy8sPGzassLCQxWIxmcxHjx65u7tramrW1tYK1tfmzZtxONykSZMSEhJSU1PXrl2r\nrq5uYWEh7GlRr169ApVqampqurq6CIJoa2uDRtdJkyZxZnoC9PT0PDw85OXl161bR6VSJUQT\n5GewsLDg9NX29PQ8ffr01KlTKSkpZWVlJBLJ2NiYS0Q6NzcXj8enp6f/vGsmk0kgEKysrHiX\nLly4gMfjg4KCehvLy8uvXr36+PFjYaf7IiM/Px+0OSspKcnLy0MQ5OLiwncejFiQ5MTul2me\n+E++fPmSnZ39vc/C4XAyMjJdXV3feAyY/YyB8ccC/gRaWlrAtKXetLS0kEgkri94wfLvv/+y\n2WwgfpGenh4XF1dQUNDW1mZmZiYjI1NcXCw8198mKirK0tLywoULQCgfKJJcvXrVyclp7dq1\nYKK5QLh79250dHRKSsqIESOAZcSIEZGRkZ6enrNnzwYHc0JCX1+fyWTu37+fTqeD37mtrS2K\noh0dHSDVdnBwePLkyV9//WVnZ5ebm7tjxw4SibR69eqjR48qKCgILzDRICsrW1dXB0FQbm7u\ntGnTSkpKVFVV29vbGxsbIQgaM2YMR+YQ4OzsPHHixMOHD/v5+f2kaxwOZ25u/vLly87OTiKR\nyLF3dXVt2bJFVVUVCGKz2Wzw19f3RpNfBTs7u4KCgoKCgqKiItBz3dTUlJ2d/f79ewcHB6x5\n4luIObEUHO3t7eBNIPArY0exGH843d3d8vLynDr63oSFhf2MoEZfiI6OhmGYyWTOnz8fj8dP\nnz792LFjZ8+ejYqKwuPxCIKIZYuitbWVQCDwVVZLTExUUFAQoK9x48aNHj2a1w70C2tqagTo\niwsWi8X3ZSYnJ4NvkKdPn54+fRp0YgJgGNbS0hJeSKJkzZo1RkZG9+/fJ5FIM2bMqK6uBvZZ\ns2ZBEKShocG7KxkfH6+npycQ7xcuXIAgyNHR8cGDB11dXV1dXfn5+V5eXgwGg06njxo1ysrK\nikgkysnJeXl5CaruQgL58OEDuK9TVFQ0NjbG4/EKCgonT54Ub1SSvGP3+yR2wgNL7DAw1q1b\np6ioyHXjBPTuMzIyhOoaqPRNmzZNSkqqtxJ9c3MzhULB4XB+fn7x8fF5eXmg/kk0lJaWQhBU\nVVXFu/Tw4UPBfmIYGBhwjX8A9PT0SElJXb16VVCO+GJubr5p0yYu45QpU8A8Bs4BfX19/ZMn\nTxoaGpSVlWVkZIQaksioq6tTUFBQUlLqfe755MkTOTk5PB5vamrKW+IpwMSOxWI5ODgAnWcC\ngQB2BwcOHDhgwAAikaipqblly5Zr166dP38edErNmzdPIH4livb2dgsLCxsbG44AeFtb299/\n/42i6JkzZ8QYmCQndr/eUSybzX779u2bN2++fPkCQRCdTtfX1+cMbMbAwBAGy5YtKyoqsre3\nDwoKsra27ujoyM3NvXz58vr163nF8wSLk5OTgoJCQkJCQEAAmDr6+PHjmzdv7tq1C+zVZWRk\nvHjxory8XFNT8/Dhw97e3kKNBwCOp8GnEBdfvnxBEAT0UgiErq6u3odxHEBq9e1Kkp9n8uTJ\nsbGxkydPBu2fgMbGRhaLNXz4cM7pvLy8PCiEUlRU/G1mdisoKCQlJQ0ZMuTGjRtjx45VUlIq\nKiq6devWsGHDLl68OHLkyKSkpG3btvV+yv37901MTATiHYbhtLQ0f3//ly9f2tjYqKqqdnV1\n3bp1q7Ozs1+/fnl5eZzxxIGBgWPGjBk4cKCnp+fw4cMF4l1CiIuL+/jxY3FxMUerj0QiLVmy\npLu7e/78+aNGjZIcMUsJQtyZ5XfQ0NCwaNEiJSUl3lehqam5bt06IZ3IYDt2GBiAlJSUcePG\nWVhY2NnZTZ8+nW+frDDIysqCIAiGYTU1NaCOC+qKYBimUCgQBBUUFDQ0NMyfP59AINy9e1cE\nIbFYLC0trZiYGN6lRYsW2dvbC9DXoEGD+G7GlJWVQRD04sULAfripaOjw83NTUNDIyEh4dWr\nVxUVFRcvXlRSUoJheO3atVwP7uzslJaWdnBwEGpIogTsv+7duzc8PHz06NHR0dF37txhs9me\nnp42NjZcnUMPHjwgEAiXLl0SYADd3d2nT58ODw8fPHjw9OnTd+3ahcfj+dYAhIWFDRkyRICu\nJQFPT8+oqChee2NjIw6HA/8XYkGSd+x+mcSuurpaW1sbgiB9ff2QkJDVq1fHxMRs3bp1xYoV\n48ePB133/fv3b2hoELhrLLHDwBAvLBYLRVFFRUUIgnA4HLhHp9Fo5eXlYHbnhg0bwCNDQ0Nt\nbW1FE9WuXbvodDrX2NDMzEwikShYbdjExEQqlVpWVtbbyGKxxo0bZ2NjI0BHX6O9vX3ZsmVg\nQw6CIDKZ7OTkBBRekpKSOJlNfX19QEAAgiAHDhwQQVSi4eXLlxC/M/eysjIZGRkcDnfq1KnC\nwsI7d+6sXbuWQqHMmDFDqPHcuXMHhmGublzAqVOnGAyGUL2LHn19fb7VvWw2m8FgnD59WsTx\ncMASOwEwbdo0PB6fnJzMd5XJZO7btw+GYWEUGWCJHQYGF9euXVu8eLGfn19ISMiuXbuEcUPF\nhYmJyeDBg1VVVRMTE69evaqlpQUmgYIGAiUlJSD9//z5cwiCKisrhRpMY2NjVlZWXFycr68v\ngUAYP358bGzsli1bRo4cicPhBD5xoaenZ+jQoSoqKomJie/evfvy5Utubu6IESOoVCqQlxMZ\nVVVVZWVlPT09zc3NDAbD2dmZSCSqq6uDUbkkEklWVlZZWbmlpUWUUQkVJpOppKS0d+9ejuXV\nq1cpKSkXL1709fVVV1cHzb8oipqZmR0+fFjYssA5OTk4HI7JZPIunTt3TrBdO5KAra3t33//\nzWvv7u4mkUjCLvD9BlhiJwAYDEZoaOi3HzN27FgNDQ2Bu8YSOwwMDh0dHaNHj8bj8b6+vosX\nLw4JCdHU1FRSUhL2mciGDRsIBAJnmAFo1ezu7vby8hoyZAhHP7m9vR2CIOGdEbNYrA0bNlAo\nFAKBYGBgQCKRUBQ1MTGxsrKys7MLDQ0V0u+hs7NzxYoVoI4enEF7eXkVFhYKw9d/RpKUlDRn\nzhxnZ2cw2G3ixImBgYEBAQFGRkZ0Ol00R+GiJCYmRkZG5sGDB8+fPwfjyOXk5IDcRv/+/UtL\nSz9+/NjR0SGaYN6/fw/DcGRkZEhIyNy5c48cOdLc3AyWlixZMmDAANGEITIWLFhgb2/Pmy6n\npaXh8XiuIYqiBEvsBAAej9+4ceO3H7NmzRoCgSBw11hih4HBISIiQl1dvXdK0dXVFR4eLiMj\nI1TdDSAvwmAwLly48PHjRzk5uTVr1nh5eSkpKb1+/VpeXh7IPbx//x6CoKKiIiGFsXTpUjqd\nfuLECdCBy2QyL168qKysPHXqVCF57E1PT09ZWdnDhw/F9XFUXl4O5ANHjx69YMGCQYMGoShK\nJpMpFIqFhcWsWbPKy8vFEphQ6enpCQsLAzUAJiYm4eHhrq6ueDx+5cqVgwcPVlFR4dscLQxY\nLNayZctgGKZSqZMmTRo5cqSysjKDwbh9+/br16/pdPrXTi1/XcrLyykUSlRUFGccfGNjY1JS\nkqKiYnh4uBgDwxI7AaClpcUltM3L8OHD+/XrJ3DXWGKHgQH4+PEjX30TJpNpbm6+fPlyoXo3\nNzd3dnbmdJvCMOzv7//mzZuOjg48Hp+dnc1ms/fu3aukpMT3oOrnKSsrQ1EUzOjsTX5+Pg6H\ny8vLE4bTb9DW1iZKhZfu7m4zMzNvb+/eJ+9VVVXW1tbC1jKUBFxcXNTV1d3c3Hx8fObMmXPs\n2LE7d+58+PDB3t7+P0+TBMX27dulpaW3bNlCp9NNTU0TEhLevHkzYcIEKSkpBQUFX19fIb3z\nxUtmZqaMjIyRkdHEiRP19PQ4f/4IgowePVqo95PfAEvsBMC8efNgGI6JieG7493S0rJq1SoI\ngpYsWSJw11hih4EBSE1NpdFonFvn3qxevVrYx0Dz5s2zt7fv7OwsKipKSEhAURSU2Z06dYpE\nIoHKMzqdHhsbK6QAduzYYWhoyHfJ3d196dKlQvLLRUtLy7Jly8CALzweb25uvnv3br7/KYLl\n7NmzNBqNd4hZWVmZePsTRUBbWxuBQMjMzHz79u2QIUMgCMLj8SiKwjBsa2tLo9GEXVrHZrM7\nOztpNBrfeR54PN7e3l6UWb6Iqa2tXbp0KSjiDAwMvHTpUltbW05OjoODg66urliG10lyYvfL\n6NitWbPmzp07f/3117p16+zt7TU0NIDMQUtLy7t37/Lz89va2lxdXVesWCHuSDH+FKqqqoqK\niggEgrm5+W8wPakvNDU1ycnJIQjCu6SgoPD582ehel+4cKGpqWlUVFRsbKyJiQkMw7Nmzdq7\nd295ebm1tXVQUFBmZuasWbMWLlwopAAqKysNDAz4LhkYGFRWVgrJb28aGxs9PDxaWloWLFhg\nZ2fX3t6em5u7evXqnJycc+fOgeFmQuLmzZsDBw7k9MZy0NXVtbW1vXnz5oABA4TnXbzU1NR0\ndXXRaDRnZ2djY+P79+9bW1uz2eyHDx9GREQ0NzeXlZX1Hr8hDDIyMpqbmyEIkpWVtbGxQRDk\n8ePHnz59wuFwixcvvnjx4m+s6KasrFxRUWFpaXnz5k3OGDcPD48bN244ODisXbt2z5494o1Q\novhlEjsZGZn79+/v27fv+PHjN2/e7Onp4Szh8XgbG5tp06ZNnTpVqJ9rGBiAoqKisLCwe/fu\nSUlJ9fT0MJnM4cOH79+/X0VFRdyhCRdVVdXa2tq2tjbeAcqvX7/uLWArDDQ1NdPS0oKCgi5e\nvOjm5iYrK2tpafngwQNNTU0pKSlDQ8Ply5cLNbegUqlfS14bGxtFk9wvWbKkrq5OR0dnzZo1\nYJxoSEjIvXv3nJyc4uLiwKgrIfH58+evvUZFRUVhp/XiRVpaGoKgDRs2aGtrp6enX7x48ciR\nI69evVJVVXV0dHz27Nm2bdvA2Y7wiIyMhCBo1apVy5cv//z5s7KyMgRBMTExUVFRcXFxv/d3\nX2dnZ2pqanJyMtdwXjKZvHjx4sWLF2OJXW/43HlLLAQCYcGCBU+fPm1paXn16tXjx48fP35c\nWlra0tJy//796dOn/97vbAwJoaSkxNXVVUlJqaCgoLW1tbW19e7du7W1tW5ubg0NDeKOTri4\nurqSSKT4+Hgue0NDw6lTp4YNGybsADw9PUtKShYtWkQgECoqKjw9PXNzc8vLy7Oysnbs2CHs\nHaMBAwY8ePAA9Gf0prm5OTs728XFRajeIQhqampKSEhobm4eMGDAoUOH9uzZY2FhER4evn79\n+sjISN7/F8GiqqpaXl7Od+nt27dATPR3RUlJSVdX99q1axEREYMGDZo5c2ZbW5u3tzedTj99\n+jQOhwOCasILoLu7u6qqCoKgI0eOkMlkBoNBpVLHjh07YcIES0vLT58+AZXH35Xq6ur29lzC\nCTwAACAASURBVHZzc3PeJQsLi/r6erCXifH/EPdZ8C8AVmOH0Rs/P78hQ4ZwlTS1tLQYGRkt\nWrRIXFGJjPj4eAKBsG/fPk5BT1FRka2tbf/+/UWm+CAuenp67O3tQQbPMba2tg4fPlxPT08E\nLz8iIgKCoPz8/N7G58+f0+n0iIgIAoEg1EqvnJwcPB7P23Gck5ODIMjLly+F55oDi8V6/vz5\n6dOnk5OTi4uLReCRw6ZNmyAIsrGxsbCweP/+PTCmp6cTCARbW1sIgoTaEVxcXAy+svF4vK2t\nrbu7OyiKoNFoK1euhCDoP5sLf2mqq6shCOL7Pw4Um0X/4SPJNXZYYvffYIkdBofPnz+jKNp7\nFD2HgwcPCkNGUQI5ePAgjUYjk8mWlpbq6uoQBPn6+tbW1oo7LlFQWVlpZmamoKAQGhq6fv36\nsLAwNTU1bW1tYc/1YrPZPT09YFeGt31h/fr1mpqaeDxe2CX8I0eO7NevX2+lusuXLysqKs6Z\nM0eofgGPHz+2sLCAIEhFRQX8KhwdHUXwmwfU1taC1MrT03PTpk3r1q3z9fXF4XBr1qy5efMm\nBEFbtmwRnndQPq6uro7H4w8dOtTT09PT07Nnzx4YhkGfeFJSkvC8ix0Wi6WhobF9+3bepRUr\nVvTv31/0IWGJ3a8NlthhcCgoKIAgiG8TFrhx/I0b03rz+fPnK1eubN++/cSJE2KRyRUj7e3t\ncXFxkyZNcnFxGTdu3O7du0Xz4QCOgIlE4j///MO1dO/ePQiCzM3NhR1Da2trSEgIgiAqKipO\nTk4KCgooii5cuBCM/RAqRUVFNBptwoQJnLEiZWVlAQEBSkpKFRUVwvYOkJWVlZKSMjAwUFZW\n1tXVnTp1KtC4Wblypby8/KhRo4TnGtxBWVpaHjhwgEwmKyoqenl5gWG1IN38+PGj8LxLArGx\nsXJycs+ePQP/7OrqKioqOnToEJlMTkhIEH08kpzY/TLNExgYkgBoGmhtbeWtIm9paSEQCCj6\nR/xN0en0IUOGAN2HPw0pKakZM2bMmDFDxH67u7shCAoICFixYoWHhwco5wfU19dDEBQcHCzs\nGMhk8tGjR1esWJGfn19UVKSurt7Q0HDz5s3g4GAvL6+QkBCu2nYBAsYqJCUlwTAMLLq6uhcu\nXHBzc1u1atXRo0eF5JdDbGwsaBAxNjamUCh5eXnnzp0zNDS8e/futm3bvLy8hFrmVVNTQyKR\n/v33XwUFhXfv3mVnZ7948YJKpXp4eGzbtg2kesLzLgnMnz//yZMnjo6O48ePf//+fU5OTldX\nF1g6cuSItbV1//79xRuh5PArNU9gYIidfv36KSsrX758mXcpIyPD3t6e862DgSFYVFRUpKWl\n/f39Ozo67O3tExMTCwoKHj16tGvXrokTJxKJxAULFogmEl1dXXV19YMHDxYVFVlZWQUHB9Pp\n9OXLlzs6OtbV1QnDY2tra2Zm5sKFC3v/fb18+XLjxo0sFuvkyZMbNmx4/fq1MFwDTp8+HR0d\nDQoZMzMz8Xh8v3792trali5dunjx4ra2ttu3bwuve4/FYvX09IwYMQKG4TFjxvj4+Dx58qSn\npyc5OXnbtm0QBE2ZMkVIriUHHA538uTJo0eP/vPPP9nZ2fLy8gEBAampqQ8fPlRVVXVxcXn0\n6JG4Y5QYxL1l+AuAHcVi9Gbz5s3y8vKcEwFARkYGgUBITU0VV1QYfwKhoaFWVlY1NTURERFA\n7QKCIC0tLXl5+YULF4osjPr6ejk5uTlz5vSec1BXV2dnZ+fj4yMMj2VlZRAE9T5yjYmJQVHU\nzs4uKCgIgiBzc3MCgXDgwAFheGez2fr6+qtWraqvryeTyZGRkcrKyjgcDmRynFwTQZCrV68K\nKQAikejq6nrlyhUg4MoBbJH+3urQvYmPj5eRkeHtU5kwYQJQFhQZknwUiyV2/w2W2GH0hslk\nghk+U6ZM2bNnT2xs7KhRo3A43KpVq8QdGsZvTm1trba2tq2tbXp6el1dXVFR0cmTJ01NTc3M\nzD5//iyyMLZs2aKrq8tbV/fixQsYhp8+fSpwjx8+fIAgqKCgAPzz/PnzeDz+7NmzbDb7xo0b\nCIJ0d3eDYSSZmZkC915RUQFBEOjSiI2NBRUXBAJh06ZNBw8eJJPJmpqaBgYGKIrKysoKaaiX\nh4cHDMN37tzp7Oy8fv36qlWroqOjr1y5oqWlRSaTheFRMvH09OQrPgBSf5F10rCxxO5XB0vs\nMHi5cOHCuHHjLCwsbGxsQkJC/pw7Zgzx8uHDh4kTJ3JK2UDBX2NjoyhjGD58eGRkJN8lQ0PD\n/fv3C8Opvr7+unXrwM8WFhZRUVHg57lz5zo5OYGfw8PDhTHX7t9//4UgiKNxA6aPoChqZGQE\n9s+mTp3a0tJy+PBhCILOnz8v8ADYbHZxcTGKoiiKRkVFXb9+/fHjx0ePHtXU1IQgSHj7lBz+\n/fff0NBQa2trTU1NHx+fnTt3ikvbSEND4/jx470tnz59AuJT0tLSvH1FwgNL7H5tsMQOAwND\noujq6iosLHz58qUI2lF5GThwYHR0NN8lOzu7rVu3CsPp4cOHyWRydnY2kAF/9OgRm81OSUnB\n4/GXLl0Cj8nOzsbhcALvTAdCJ5ydSAaDoaysnJ2dffDgwYULF8rJyXEeicfjx48fL1jvHLKy\nsuh0OoqiYKYfDodDUTQmJkZI7jgcOXIEj8cPHTp027ZtiYmJf/31l7Kyso2NzadPn4Ttmhd9\nff1Dhw6x2ezS0tKxY8eCAXckEsnZ2RlF0evXr4ssEklO7P6IDj4MDAyB8Pjx46ysrJKSEgaD\nYWdnFxAQ8Id0AUsaeDze1NRUXN61tLRKSkp47Uwms6ysTEtLSxhOp02b9urVKx8fH1dXVwiC\njh49GhUVdevWrY0bN3p7excWFqqrqysqKvb09Hz58kVOTk6ArpWVlW1tbQ8dOnTgwAEIglgs\nFoPB8PLy8vDw8PLy8vf3//LlC5FIxOPxMAx/+vRJgK574+3tXVVVlZaW9u+//7a1tfXv3z8g\nIIDBYAjJHaCgoGDmzJl79+6dOXMmxxgVFeXt7R0eHp6cnCxU77zY2Nhcv37dyspq4MCBtra2\n+/fvNzY2rqmpOXDgAJPJvHv37sCBA0UckiQi7szyFwDbscPA6OrqCgkJgWHYzs5u8uTJgwYN\nolKpZmZmpaWl4g4NQ9RkZGQQiUTeMQD79++nUqlCPRe+d+9eeHg4DMM2Njbz588/dOiQra0t\np31BTU2NSCRyTYURCDdu3EBRdM2aNR0dHZaWlvLy8o2NjePHjycSiWBEMoqiOjo6EASFhoYK\n3LsYCQsLGzhwIK89NzcXhmGOpqDIyM3NRRBEVVV18uTJHDnuuro6U1NTV1dXHA73/Plz0UQi\nyTt2mNwJBgbGf7Nw4cLMzMwHDx7k5+cnJiZeu3atvLxcQ0Nj8ODBbW1t4o7u9+fp06fjx4/X\n09Mjk8lWVlYLFy78+PGjuILx9fUdOnSoj49Peno6UNdrbm6OjY2dP3/+1q1bZWRkhOfaycnp\nwIEDPj4+/fr1c3R0nD17tq2t7f379+vq6h4/fkwgELq7u2NjYwXu19PT89y5c3v37lVSUmpo\naPj06ZOSktL58+cZDMaqVasePXqUkpLS0tICQVBhYSGLxRJ4AOLi4cOHfOUqnZycaDSa6BVG\nnJ2dw8LCqqurm5ub4+Lizp49u3z5cjMzMxKJlJaWNmDAABEoGko+WGKHgSEYPnz4cPr06VWr\nVu3YsePmzZu/04d7VVXVgQMHEhMT7ezsOEY5Oblz5861t7cnJCSIMTZJgMVi3b59e+/evVu2\nbElPTwdf8ALk1KlTDg4O7e3tS5cuTUlJmTJlSlZWlqWl5cuXLwXr6LtCCgwMDAwMpFAo8vLy\ndDp92bJlOjo6L1++fPHihbC9//333xkZGVOmTFm5cuWBAwccHBxgGN69e/enT5+2b9++YsWK\nV69eCdzpiBEjysvLT5w4MW3aNAqFwmQyiURiaGgogiBJSUnTpk1jsVjKysrFxcW/U27R0dEB\nVNm5gGGYRCJ1dHSIPiQTExNdXV0pKakdO3bMnz//wYMHUVFRd+/elZGRcXFxKSwsFH1IEoe4\ntwx/AbCjWIz/ZPv27VJSUsrKyt7e3lZWVgQCwdra+tWrV+KOSzAcP36cwWDwnUM6e/bsESNG\niD4kyeH58+dmZmZ4PN7c3NzBwYFKpcrLyycnJwvq+m/fvgXfYb2NnZ2dw4YNs7S0FMaxY9+p\nqalxcHAgEon+/v5bt25dvXq1u7s7gUA4duyYsF0vX74ch8OBWkNjY2MURQ0MDPLz89lsto2N\nzZo1a4TqPScnB4IgGo2mqamprKyspqYGpifv27cvKirK0dFRqN5FiZ+f3+zZs3nttbW1CII8\nePBA9CHt3r37a9Pzli9fPmjQINGEIclHsVjhMwbGz3Lo0KFly5bFxcUFBweDhrXa2tqpU6cO\nHDjw+fPndDpd3AH+LJ8+fWIwGHyHaqioqDx//lz0IUkI1dXV3t7ebm5u2dnZSkpKEAR1dnZu\n27ZtwoQJVCpVICPXjhw5YmxsPG/evN5GAoFw8OBBDQ2N3Nxc0EwgFjZv3lxTU1NUVKSrq8sx\nHjhwYPr06RYWFlZWVkL17unpuWLFiqKiIgRBTE1NnZ2dgWKwjY0N394OAQLmuU2dOjU9Pb2y\nshJBEAaDISsru2DBAgaDASa8/R6MGzdu1qxZixcv1tbW7m3fsGGDjo6Ora2t6EMyNTUtKSlp\naGjgbZG5f/8+NlgMwo5iMTB+kq6uruXLl2/dunXy5Mkgq4MgiMFgpKam4vH43bt3izc8gaCs\nrPz+/Xu+h8uVlZWcEQh/IJs2bdLU1Dxz5gzI6iAIIhKJy5cvj4yMXLRokUBcPH361MvLizer\nVlFRMTExARJrYqG5ufnQoUO7du1iMBg7d+4MDAzs37//sGHDGhsbvby8duzYIVTveDyeyWS6\nu7vPnj07PDzc1dWVxWK1t7dDENTd3S3YZu179+7t3bt31apVJ0+erKqq4tgdHBzevXu3ffv2\n9vb2qqqqgoKC9+/fq6urt7e3A4WU34AJEyYMGDDA3d39/Pnznz9/7unpefHiRVhYWFxcXFxc\nHOcTT5S4ublpaWktXryYzWb3tqempt6+fTskJET0IUkc4t4y/AXAjmIxvsHt27dRFG1ubuZd\nWr16NUc69Zfmw4cPfAemNTQ0KCgoxMfHiyUqSaBfv34HDx7ktYMdozdv3vy8Cx8fn2XLlvFd\nsrGxiY2N/XkXP0ZOTg4Oh3v16pW+vr6qqmpkZOTOnTsXLVqkp6dHp9M1NTWF6j01NVVaWrq5\nuZnFYh04cMDS0pJAIMAwrKOjIyMjs3HjRoF4qaqqGjBgAIqi5ubm3t7eqqqqBAJhzZo1jY2N\nBAJBRUVl+fLlXE9ZunQpmUyeP3++QAKQBNrb2xctWkQikSAIIhKJEARZWFiIV5I9Ly9PWlra\nx8cnJSWluLg4KytrwYIFKIpu3rxZZDFI8lEsltj9N1hih/ENkpOTFRUV+S4lJCRoa2uLOB4h\nsXz5cllZ2StXrnAs7969c3FxMTc37+zsFGNg4oVIJPIdD9rV1SWoD/2IiIghQ4bw2ltbWykU\nSlpa2s+7+DEuX75MoVCsra0HDRrU+8ams7PTxcUFh8O1trYKz3t7e3u/fv2mTp06duxYGo22\ndu3a7OzsBw8e+Pv7Iwiir69fV1f38y5MTEwGDBjAmUzKYrHOnz8vLS29efNmPz8/CIJevnzJ\nZrOLioo2btw4fvz4MWPGkEikESNGGBgY/OwrlDA6OjqePHmSlZVVVVUl7ljYbDa7pKQkMDAQ\ntGATCARHR0eOTrVokOTEDquxw8D4KeTl5Zuamjo6OqSkpLiWamtrgTD6b8D69eu7urr8/f01\nNTWNjY1ra2sLCgocHByuXLnCGW/1ByIrK1tXV8drB1oksrKyP+8iODjY2dn55s2bHh4eve0b\nN26k0WhilGPV0tJqbW0tKCioqKigUqkcO4FAcHV1zc/PP3PmTGhoqJC8S0lJnTlzxtPTs6ur\nKzo62sXF5d27dykpKVlZWUlJSVu2bFm4cOHx48d/xkVCQsKnT5/u3bvHKZOFYTgwMLC9vT0s\nLOzQoUOXL18ODAzU09P7559/DA0NaTTa06dPURS9du0a+39PCYXNhw8f8vPz37x5o6WlZW9v\nr6qqKnAXRCJR2EWT34WBgcH58+chCPr48aOcnBymlP4/iDuz/AXAduwwvgHYOElMTOSyM5nM\n3hMtfw9ev34dHx8fFRW1bdu227dv8+2TFRdv374NCwszMTGRkpIyMDAICQkpKSkRttPx48f7\n+fnx2mNjY1VUVATVsrpgwQIKhbJ169aXL182NTXl5+dPmzYNRdH09HSBXP+HUVRUZDAY4OeK\nioqkpKSVK1fGxsbKy8tbWVlNnz5d2AFYW1v379/fwMAARVFtbe1x48YBfVpwv9HU1PQzF/fz\n8+M7Ererq4tKpe7cuROCIBcXF1D+iCCIgYHB9u3bu7q6AgICYBgWjVIuk8lcsmQJgUCg0WgW\nFhYyMjIoikZGRv7J++iiQZJ37LDE7r/BEjuMb7N+/XoZGZkbN25wLG1tbVOnTpWTk6upqRFj\nYH8Oubm5NBrN2dl53759GRkZBw8e9PT0JJPJYO9EeDx//pxIJK5evbp3Dnf58mUymcy39u7H\nAGVk6urqnBtye3t78RY5AcaNG4cgSERERGRkJB6PV1VVtbKyIhKJMAyrqamJQAeHSqXyPYz+\n8uULBEEPHz78mYvb2tp+rYTRyMho//79SkpKdDo9Jibm06dPvc+dvby8NDQ0hDc0tjcRERHy\n8vKpqamcu6wrV66oqqpOmjRJBN7/ZLDE7tcGS+wwvk1PT8/8+fPBmKOQkJDhw4crKiqqq6uL\nReTpD6S1tVVdXT0sLOzy5csTJkywsLCwtLScOHHimDFjFBQUGhoahOr90qVLdDpdR0cnODh4\n5syZdnZ2CIKsXLlSGL5qamqePHnCt1NHLOzbt09FRQXUG9BoNCKRiCDIhAkTHj58SKVSGQxG\nd3e3UAOQlpb+559/elvALh3QiAaydj+Mj48PaL3koqenR05OLjk5ecWKFRAE9d6t7+7u/uuv\nv8hk8tatWzl7mcKjuLgYQZCcnBwu+6NHj3A4XF5enrAD+JOR5MQOkzvBwPhZEATZsWPHv//+\nO2bMGBaLpaOjExMTU1JSYm9vL+7Q/gjS0tJaWlp6enpGjhwJw/C0adNCQkJ6enouXrzY0dFx\n9uxZoXofNmxYaWnpvHnzpKSkmpqahg8f/vz583Xr1gnDF4PBsLKy6l3QJl4CAgLq6+ubm5t3\n7tyZkJCQnp5eU1Nz8uTJrq6u1tbW1tbWkydPCjUAExOTvLw8CIJKS0vHjx+vrKxMp9NpNBpo\nZdXX1/+Zi3t7e6ekpIDv795cvXq1ubnZ3d3d19cXgqCpU6fa2NhMnz597Nix2traCQkJqamp\n/fv3b2ho+BnvEATV19cfPnx4/vz5CxYsOHLkyKdPn7ge8M8//5iZmXEVX0IQZGNj4+zsnJaW\n9pMBYPyiYPWGGBiCwcLCwsLCQhhXbm1tzc/Pf/XqlZKSko2NjaampjC8/Lo8ffpUVVU1OTn5\n9u3bDg4OwDhv3ry7d+96eHicPXs2PDxcqAEoKirOnTtXqC4kEw0NjREjRpw/fx5F0cGDB0tL\nS3d0dJw6dWru3LkzZszo7u4Gg7+EF0BoaOiSJUv69+8/bdo0e3v7Xbt2GRgYlJeXh4eH9/T0\nnDp1avbs2T988ZkzZ+7evXvixIlHjx7lJNMPHz6cNm1aRESEkpJSa2srBEHp6enPnj178eIF\niUQaNWqUrq4uiqIFBQUqKio/89JOnz4dFhYmIyNjZ2fHZrPPnTu3cOHCw4cPjxkzhvOY9+/f\n95aG7o2enl5vyT2MPwtxbxn+AmBHsRhiJD4+XlZWFo/HGxkZycrKwjA8fvz4xsZGccclQYDe\nAr7SZRYWFrKysqIP6c9h+/btGhoa4J2poqKCw+HIZPKqVau6u7vXrl3r5uYmVO9MJtPf3x+H\nwzk4ODx48KCgoODEiRPm5uY6Ojo7duzA4/E/2UBTUFCgq6srKysbEBAQGhrq5OSEIEhISEhX\nVxd4gImJyYIFCzo7OxcuXEggEEgkkr6+PoFAQBDEwcHhh7uLbty4gaJobGwsp3aTyWRu3rwZ\nj8ffvXuX87CVK1e6u7vzvcKwYcP4dn5gCApJPorFErv/BkvsMMRFXFwcgUDYtWtXR0cHsNy/\nf9/Y2HjAgAFMJlO8sUkOsbGxEAQ9efKEd0lHRweCIKEKqv3hHD16VE1Nra2tLT8//9SpU3fv\n3uWUAIpmjvDly5dBSyzoTlVUVAwPD6+vr2ez2fb29rwCwt9LR0fHyZMnFy1aNHHixA0bNnAV\nzmZkZKAoamVlpaysnJaWxmQyP378GBgYSKVSqVRqdHT0jzkdMGDAjBkzeO1Tpkzx8vLi/PP6\n9etEIrGyspLrYfX19VQq9dy5cz/mHaMvYIndrw2W2GGIhZaWFhkZmT179nDZ379/T6fTjx8/\nLpaoJJCnT59CEMQ79z0pKQmPx0MQ9PNatRhfo7y8HEGQmzdvctlbW1tVVVV3794t7ABiYmJs\nbW3ZbPaXL18+fvzYe2nBggXDhg0TdgAbNmyAIIhMJjs4OFhYWBAIBFNT02fPnqWlpaEo+gPT\nR1paWhAE4dv1nJWVhcPhOFImLBbL0dHRxcWl9zv88+fPgwYNMjMzE3bnyh+OJCd2WI0dBoaE\nkpOT093dPWPGDC67qqpqUFDQxYsXJ02aJJbAJA1TU1MCgbBu3brm5uZJkybp6uq+ffs2OTl5\n69at48aNS0tL4x0WjiEotLS0QkNDJ02alJ6eTiQSN23alJubW1FRAQZ88db1Cxw2mw0mlkpL\nS0tLS/deQhCE74DjvtDS0pKYmJiXl1dRUaGvr+/q6jphwgRwn8BFU1OTm5vb4sWLi4qKKBSK\nubm5m5sbgiAWFhba2trp6emRkZHf5bqhoYHFYvEt0VNVVe3p6WlsbAQDmmEYvnDhgp+fn76+\n/pAhQ/T09N6+fZuZmamoqAg2Mn/stWP86mBdsRgYEkpVVZWGhgYYzsiFvr4+VhnNAY/Hjxkz\nxtDQ8Nq1a1ZWVjQarX///ufOnTt27FhxcfHo0aPFMqr896C7u7u6upr9zTkKe/fudXJysrKy\nMjExyc7OlpaWJhKJVCrV2NjY2dn51q1bQo3QxMSksLAQCNdxcf/+fVNT0x+4ZnFxsbm5+aZN\nm6SkpLy8vLq6uubPn+/o6PjhwwfeB1dWVhobGwcEBCxdujQyMtLDw4PzfjMwMKisrPxe7/Ly\n8jgcju8feGVlJR6P732joqKikpeXt2fPHhqN9uDBAxKJtGXLlidPnmhra3+vX4zfBuzzDgND\nQqHRaI2NjXyXGhoaaDSaiOORZDZt2tTY2KiionLz5s2HDx9++PAhKSkpPj7+w4cP69evF3d0\nvyT//POPo6OjtLS0mpoanU4PCAgoLCzk+0gikXjo0CEqlerk5OTu7j5w4MC4uLh37949ePBg\n6tSp48ePB6pyQmLgwIEKCgrLly/nsicnJ+fn50+ePPl7L9jR0REQEGBlZVVaWhofH7969erj\nx4+/evWKQCAEBQXx5rg0Gu3z5898L9XY2PgD2jRkMtnNzS0hIYHJZDY3N/deOnr0qJeXF9fG\nIYFACA4OPnTo0LVr1+Lj40NDQ3nHG2L8WYj3JPiXAKuxwxAL7969g2G4dxMcgMlkGhsb85aU\n/eG8fv0aDE4lEolgfK2vry9nfDvGdxETE4Oi6Pz587Ozs1++fJmWlubv708ikXhr6QBxcXEq\nKiq8Y6za29vl5eWFXQ+ak5NDIpGGDRuWnp5eUlJy48aNBQsWoCgaExPzA1dLSEhQUFDgVYF+\n+/YtDofjLX1LTEyUl5fnfTzYXcvOzv6BGFasWAHDMA6HgyBITU1t5syZlZWV0dHRBALhG6rL\nbW1tiYmJERERo0ePXrZs2Y+5xugjklxjhyV2/w2W2GGIi+DgYH19/bdv33Is3d3ds2fPlpWV\n/fDhg/jiklxqamquX7+elZVVW1sr7lh+VYqKilAUPXv2LJd9zpw5WlpanAbt3syePXvMmDF8\nr+bv779w4ULBR/m/PH/+3M/PD9TY4fF4Ozu7S5cu/dilQkNDJ0yYwHfJzs5u06ZNXMb29nZd\nXd2RI0e2tbWx2ezCwsLExMR169aZmpra2dn9gOLJrFmzSCRSUFAQlUqVkZExNTWlUqkIgsjK\nyn5jOnBhYaGurq68vHxgYGBERIS3tzeKopyoMASOJCd2WHElBobkcvDgwZEjR5qamvr5+Zma\nmtbW1mZlZTU1NV26dElJSUnc0UkiDAaDwWCIOwoBUF5efvz48YKCgra2NlNT08DAQI72srBJ\nTEy0t7cPCgrism/evDkhISErK8vPz49rqbu7m29jAQRBeDyeyWQKJdBemJubg6SnurpaSUnp\na8H0hebmZtCawIucnBzX2SgEQVJSUmlpaX5+fnp6eiiKVlRUAKFmFoslJSW1e/fuefPm9d17\nenr6kSNHbt265ejo2NzcnJGRUVBQwGKx0tLSGAwG728e0NLS4uvra2dnl5iYyOkgKS4u9vPz\nmzNnTkJCQt8DwPgNwGrsMDAkFwqFcvXq1RMnTsjJyd28ebOhoSEsLKy4uNjV1VXcoWEIkRMn\nThgbG6empiorK5uZmT158sTZ2Rnse/X9Ij/cEFpcXOzk5MRrp1KpZmZmxcXFvEuGhoZAR5DL\nzmaznz59amho+GORfC8wDKupqf1MVgdBkIaGRllZGd+l0tJSDQ0NXruJicmjR48QBGlqaqLT\n6V1dXUwmk0gkqqurR0VF7du3r+/e4+PjJ06c6OjoCEEQjUYbN27cxo0bN2/enJSUmHVdAAAA\nIABJREFUdOPGjXfv3vF91pEjR9hsdlJSUu++YBMTkxMnThw7duzt27d9DwDjd0Cs+4W/BthR\nLAYGhsjIy8tDUZRLAS4nJ4dKpfZFFq66unrOnDkGBgYoiqqqqgYEBHzvaVFAQMDXDk9tbW35\nFq5VVFRISUklJCRw2fft20ehUGpqar4rAPFy69YtFEWfPXvGZb906RIej/9a1eahQ4fodLqU\nlJS/v39qamphYeHVq1fDwsIQBJGSkur714euru7hw4f5LpHJ5MuXL/NdGj58eEREBN8lNTW1\no0eP9tE7Rt+R5KNYbMcOAwMDQ4LYvHnzqFGjuMTPPDw81q1bt2nTpm/vwxUXF1taWt6/f3/u\n3LkHDhwICwujUChubm7x8fF9D8DMzCw3N5fX3tTUVFhYaPb/sXfngVC9bcD47zNmhjEYa7Kv\nk53sUmmhTSotqLRJi9KmtGjft6dFi6RvqbRpU1pEGxWSsoaEskS27PsyM78/5n39vJSkZg7j\n+vz1fO8z51zXaLue+z73fenqdr6koKBw5MiRJUuWbNiwIT4+vry8PC4uzsPDY9WqVSdOnODm\n4nhzc7Ofn5+Dg4O+vv64ceO2bNlSUFDwR0+wsrKaPn26ra1taGgoi8VCCDEYjKtXr86dO3fj\nxo1KSko/vev+/fsMBmPJkiUPHz60t7fX0dEZN26cn5+fr69vY2NjYGBg9xNgt9D46TjrF1O2\nFRUVUlJSCKGioqLNmzePHj1aTU1tzJgxe/bskZCQ+NXmesCz8K4s+wCYsQO4aG1tzcjIePDg\nQWxsbG1tLd7pAC4RFxfvvHGBxWLl5eUhhNLT0391I4PBGDx4sK2t7ZAhQ9qKAwzDBg4cSCQS\nu7ixg9TUVD4+PhMTE01NzREjRqxZsyYrK4vJZLq6uqqpqXXe+trm/v377cs+AwODX80wcUhp\naamRkZGkpOSyZctOnjzp5eU1ePBgGo327NmzP3pOY2PjihUriEQi+zQ+AQEBQUHBvXv3drET\nQlVVlZ+f/6d/Tvn5+SdNmtTN0JMmTVq0aFHn8cTERIRQ+31U7Tk5OS1cuDAmJkZCQkJPT2/H\njh3+/v6bN29WV1cnEAhHjx7tZnTQfb15xg4Ku9+Dwg5wX3BwMPuIUSEhIQzDKBTKhg0bfroh\nEfAYIpH4/PnzzuN1dXUIoQ69StuLjIzk4+MTFhbm4+ObO3ducHDwixcvVq5cKSAggGGYi4tL\nd6JXVFQYGBi0NS0QEBCg0WgkEklfX19ISOjt27e/fUJlZWVycnJVVVV3wv1btra2xsbG7ftr\nMRgMT09PERGRHiwHFxYWPnr06MyZM0+fPi0vL+/6w6qqqvLy8iwWq7Gx8fz58wsXLhwxYsSC\nBQvOnj0rICBgYWHRzaD379/n5+fvcKZJc3OzjY2NtbX1r+4KCAig0WgDBw50dXVt30nsypUr\nBAJBQ0MD2ov9c1DY9W1Q2AEuu3nzJpFI3LRpE7u9d01Nza1bt2RkZKZNm4Z3aoDjlJSU/Pz8\nOo8nJycjhPLz8391o4+Pj5CQEIFA+PDhQ/vxkpISIpEoKCjYnejsxgnDhw/fuHGjkZFR21G3\nBAKhl5+Lxj4/+ePHjx3GGQyGtrb2rl27OBp99OjRFArl69evurq6EhIS8+bN27Fjx4IFC0RF\nRRFCo0eP7v6jFi1aJCQktHv37jdv3qSkpFy/ft3U1FRGRubLly+/uqWlpUVFRYVIJLK3sLBY\nLCaTeevWLWFh4U2bNlEolIcPH/7tNwT/Lyjs+jYo7AA31dfXS0lJ7d27t8N4WloaPz//gwcP\ncMkKcM2qVasGDx7cecXT1dWV3e3+V06ePIlhmK2tbedL7G3UP3786Dr0p0+fEELTp09vW3Nk\nMpmVlZUHDx7k4+NbsmTJn3wPbjt//ryKikrbfzKZzG/fvrEnuT09PSdMmNCdhzAYjL179+ro\n6NBotAEDBlhZWXU+kfinLl++jGGYhISElZVV2/ReSkqKnJwcmUweMGBA9+fMmEzmf//9p6ur\ny543lZSUdHFxYTd268LcuXNlZWUJBIKamtrw4cOlpKT4+fl37tzJZDJHjhy5bdu2bkYH3dSb\nCzvYPAFA7xIeHl5XV+fh4dFhXEtLa9q0abdu3cIlK8A1mzdvLikpmTp1KvulOoRQdXW1p6fn\nlStXjh8/3sWNqqqqLBZrxIgRv/pATExM16HPnTuHYVhAQED7V/RoNNr69etpNNrTp0//8Ktw\nVV1dHbt/1+fPn6dOnUqj0RQUFKhUqoGBQW5ubnfamtXX16upqW3durWkpERHR0daWvrdu3fD\nhw/v/IexMwcHBxqNVlZWlpGRYWtryz51RVdXt7KyksFg1NXVBQcHd+dbfPr0afv27SEhIXQ6\nff369ZGRkaWlpf7+/jIyMl3fyGKxbG1tExISNm3aNHbsWB8fn+zs7B07dmAYJiQk1NDQ0J3o\ngDdAYQdA75Kdna2ioiIoKNj5ko6ODhxJxfOkpaXDw8PLysqUlJSUlZU1NTUlJCRu3br18OHD\nYcOGdXHjqFGjEEKPHj3qMP7ixQv2Lte2N+d+JSsri5+fv/PvPQKBoK6u3vls3l5FSUkpOzs7\nKirK1NS0oaHh6tWrGRkZERERdnZ2d+/e7c7O0LFjx+bl5V25cqWkpCQqKio5Obm6utrGxsbb\n2/vevXtd30uhUGxtbQkEQn19/fv374lEorm5uampaX19PYVCYXdj+20CR48e1dfXf/78uaKi\noqKiYnh4+MiRI48dO9adr6+iopKamqqvr79o0aKtW7c6ODi01YIpKSnsF3ZBf4H3lGEfAEux\ngJv8/f2VlZV/emnTpk1jxozhcj4ALwkJCZcvXz579uzr16+72IvaHj8/P4FAmDlzZkRERFFR\nUUJCwt69eykUipGREYZhv93Q4OzsTCAQKisrO1/S1NRUUFDoydfglpqaGjExMWlp6Xnz5rXf\nvpqenk4mkzEM63rnR2lpKUJo+fLlHcaZTKa4uLi6uvpvE3B3d9fQ0CCTyeyJQxKJxG7zGhQU\nJCgoOHjw4K5vv3fvHolE6rAhOjAwkEQi3b9//7fRk5OTCQRC5/2/V65cERAQ6OLVTNAzvXkp\nFgq734PCDnBTamoqQiglJaXDOJPJHDx48JYtW3DJCvQJs2bNwjCs7fUshNDAgQMXLlxIJBIN\nDAx+e/vFixcJBMLmzZs7jGdnZxMIhF91g+09Nm/ejBDatGlTWVkZi8UqLy8/deqUnJzc5MmT\nJ06c2PU7gr6+vgihkpKSzpdmzZpFIpF+G/3AgQP8/Py7d++eP38+hmHa2trjxo0bPHgwkUik\nUCiCgoIMBqOL242NjX96LrSHh0fX71a2WbdunbCwsK+vL/vrFxUVHT58mJ+f/8iRI925HfwR\nKOz6NijsAJeNGzfOzMys/QkLTCZzx44dVCo1Ly8Px8RAL9fU1CQvL49h2KBBg6hUKkKITCaz\nK7yFCxf+th98RUUFe1/thg0b2HM8DQ0NDx8+lJSUJBAIWVlZXPkSPXfu3DkZGRlZWVn0/647\n6+rqzp49e9iwYV3cu2fPHoTQT0+qW716NYFA+G30+Ph4hNCQIUNkZWWnTJkiISGBEMIwrK3z\nbBd/eGtrazEMe/jw4YEDBxwdHceOHbtmzRr2qTdRUVEYhnXnJEsmk3n06FExMTGEEPtXf+DA\ngexuY+Cf682FHbxjB0CvExAQ0NDQoK2tvW7duv/++2/v3r1Dhw49cuTIjRs3ftqqEgA2Mpmc\nnZ09ZMiQjIwM9rl3GIaNGjUqMDDw+fPnjo6OrC67zYqKirJ3d/r6+srLy4uIiFCpVHt7+/Ly\n8sOHD6upqXHre/QQhmFUKnXfvn0EAsHa2trX1zcjI+P9+/fjx48PDAwsLCzs4l4dHR2E0Pv3\n7ztfSk1NbTv2pQt0Oh0h9Pbt24aGhpycnBMnTqSkpBw5cqSuro5dXj9+/PhX97JXyWfNmhUQ\nECAuLm5iYpKZmTl+/Pg5c+aIioqyWKzuvOCIYdjatWuLioqSkpICAwPT0tK+ffu2cOHC394I\neA3OhWVfADN2gPvq6+u9vb3t7OwGDRo0fPjwNWvWdHGKFQBtamtrxcXFjxw5Ultb237SNyMj\ng0KhBAUF/fYJb968GTZsGHvGi0AgGBgY9JVDdmJiYggEgpCQ0LFjxzpc0tHR4ePj+1XnBhaL\n1draSiKRDA0NO4zn5+cTicQuDgduj0ajEYlEAoEgKCiora0tJCREJpM9PT3Z25mtrKx+dWNa\nWhpCaObMme2nDBMTEwcMGODg4MDPz9/c3NydBADX9OYZOyjsfg8KOwBAX/HgwQP28RadLzk7\nOzs7O3fzOU1NTZmZmT99Tq/FZDIVFBQoFEqHMuju3bsEAkFVVfXgwYNd3L5jxw6EkIWFRWpq\nKpPJbGhouHXrFrs4Kygo6E4CZmZmCKErV648efLk9OnTjx8/Li4urqmp0dPTk5KSEhcX/9WN\nbm5uEhISEyZM6LAWfOPGDT4+Pjs7u+5EB9zUmws7WIoFAADekZubq6Ki8tOlQy0trZycnG4+\nh0wmq6urd2cJsvdgrzszGIwRI0ZcuXLl/fv3jx8/dnd3d3Jy2r9//7Bhwz5//tzF7Tt37ty4\ncWNsbKyOjg67V4ejoyOJRIqMjGS/t/dbRkZGCKFdu3aVl5fb2trq6Oi8efNm6NChTU1NSkpK\nXZyl9+bNmyVLlkRGRi5cuPDHjx/swdLS0pCQEAaDMWPGjD/5MYD+Dgo7AADgHVQq9VfvY1VX\nVwsJCXVx7507dwYPHiwsLEwmk1VVVbds2dLY2MiZNDlFRkbG0tJSQ0Nj8+bNZmZms2bNSklJ\nCQ4O3rhxY2tr629P8jt48GBxcfHp06dnz569cuXKhw8f/vjxw9TUtJvR2R0+DA0Nly9frqqq\nqqysPH/+fDMzswcPHqSmppJIpF/dWFVVpa2t/fz587dv3w4cOJBOp9PpdBkZmdjYWCEhIXZf\nMgC66Te/ywEAAHAZg8Hg4+Pr2b1DhgzJzc1NTk7W19dvP85kMh8/ftzF3M/MmTNv3bpFJpMH\nDRpEoVA+f/584MCBa9euJSUl0Wi0niXDfQYGBufOnQsJCaFQKHV1dYKCguwuGq2trW/evNm4\nceNvnyApKenu7u7u7t6D6Owzit+8efPmzRsREREGg6GiolJQUODg4CAiIsLeXfFT8vLyWVlZ\nc+bMSUtLe/fuHbvvra6urqqqqoyMjLy8fA+SAf0X3mvBfQC8YwcA4ILExEQHBwcFBQUMw1RU\nVObOnZuRkdGD59jZ2RkaGrY/ko3BYHh6eoqIiPyq5Sj7b7nJkyfX1dW13XL8+HEMw/6ogT3u\namtrZWVl3d3dO7ystmXLFjExsd92y/17jo6OoqKiBALBzMzM2dnZysqKn5/fwMBAUFAwICDg\nV3cdOHBAUVGxurq6w/jWrVsVFRW7PgAP4KI3v2OHsbrc/Q4QQn5+fm5ubjU1NV2vYgAAQI8F\nBwc7OTmNHTvW0dFRSUkpKyur7S0xKyurP3pUWVnZ+PHjs7Ozx48fX1xcnJWVVVxc3NraumLF\nikOHDv10QVBeXp7JZBYUFLR1iWWbNWvWzZs3KysrRURE/urrcdHr168nTpxoYmIyZ84cNTW1\nnJycW7duhYeH37lzZ+LEiZyOXlpaamVlVV9fb2RkxGKxxMTEWltbg4ODp0yZ0r4Jbwd1dXUm\nJibi4uIXLlzQ1NRECNXX1x8/fnznzp23b9+2t7fndNrgTzU3N/Pz80dFRVlaWuKdSyd4V5Z9\nAMzYAQA4qqSkhEaj7dq1q/0gk8l0d3eXk5PrzuG0HTQ1Na1atYrd80BFRWXs2LFz5swRFxc3\nNzdvfwZKGwKBsGzZMhaL1dLSwu5bwMbug3L79u0//054yszMXLBggZqaGh8fn6Ki4sSJExMS\nErgWvaqqytPTU1VVlUAgkMlkIyOjc+fO/fTo4/YKCgrGjh2LEJKRkdHS0iKRSFJSUh06jIHe\nozfP2EFh93tQ2AHATZWVlb/taspjTpw4oays3Nra2mG8vr5eVFT0xo0bf/rAb9++UanULVu2\ntK8nioqK9PX1p06d2vnzCCFHR0dzc3N+fn6EkKSkpLOzc3Z2Nnsj55kzZ/40AdwxmUw/Pz9V\nVVX2FAaJRLK2tuZmecdiserr61taWv7olrS0tBs3bvj4+ISHh/+2UwjAUW8u7GDzBACgV6iv\nr9+7d+/Vq1e/ffuGEFJSUpo3b97mzZv71okbPZOUlDRs2LDOGyYoFIqZmVlycvLMmTP/6IFn\nzpyh0+l79uxpv/YnLS3t7+9vYmKSlZWlrq7e/vN8fHy3b99eu3bt3r17paWl09LSfHx8jIyM\n2Ee7GRgY9PSb4WbNmjUXLlxYvny5iIhIeXk5Qujjx49Dhgx5+vQpe+8qF0RFRQUGBn78+JFM\nJuvp6S1YsIB90F0XtLS0tLS0uJMe4FVQ2AEA8FdTUzN69OgfP35s2bLFzMyMxWLFxMQcOHDg\nxYsXz549ExQUxDtBzmIwGL86iYNIJLa2tv7pA2NiYuzs7Dq/0WVsbCwjIxMTE9O+sHv37h2T\nySQQCKtWrVJUVEQI6enpOTg4ODk5bdiwgUKhDBky5E8TwNfr1699fHzs7e2PHj0qLy9Pp9Pz\n8/MzMzMVFBTmz5+fkZHR4afNYrHCwsLCw8MzMzNlZWXNzMwcHR3/5v9RsFgsd3f38+fPT548\nedq0aa2trdHR0ZaWljt37ty6detffz8AugLn2AEA8Ld79+7y8vL3798vXbrU0NDQyMho+fLl\n79+///bt28GDB/HOjuM0NTU/fPjQeZzBYCQkJLDfpv8jdXV1wsLCCKGcnJzt27fb29uPHj16\nxYoVz58/FxERYbeRbXPhwgX2/gwdHZ3z589nZ2eXlZU9f/48MTGxubnZzc3tV6/891oBAQFK\nSkpv3rwJCwvLzc19/vx5enp6cnKyoKBgTk7Omzdv2n+4trbW1tZ2ypQpSUlJioqKxcXFa9eu\nNTAw6Po04675+Phcu3bt3LlzVCr1+vXrZ86caWpqmjdv3u7du+/fv//X3w+ArkBhBwDAGZPJ\nvHTp0tatWyUlJduPDxw40MvLy9/fH6/EuGbmzJmZmZmXL1/uMH706NH6+vopU6b86QOVlZXT\n09MDAwO1tbUfP36sqqo6bNiwb9++2draZmVlsafl2qSmpo4dOzYsLAwhtGTJElVVVUlJyfHj\nx3/9+lVMTExPT+9vvlpra2tiYuL169dDQ0MLCgr+5lHdl5SUlJOTc/36dRsbm7ZBHR2dsLAw\nDMNu377d/sOurq5fv35NTU0NDQ319va+ffv2169fNTQ0bG1tGxoaehCdxWL973//Gzt27OLF\niysqKlxdXQ8fPmxmZhYaGkqj0fbv3/+3Xw+AruH7il+fAJsnAOCowsJChFB6enrnSwkJCQih\niooK7mfFZSdPniQSievWrXv37l1hYWFUVNSSJUv4+Ph6sHOCxWLdunWLQqEQicQjR460H1+x\nYgWBQNiyZUv7QUtLy/3797NYrLq6usDAwOXLl8+bN+/MmTMFBQUqKir+/v49/lJPnjxRVlZG\nCMnIyFCpVAzDHB0duXCYHJ1OFxMT++klKpVqZWXV9p/sbb9xcXGVlZVRUVFv3rxh7xquqamR\nlpY+e/ZsD6Ln5+cjhPj4+P777z/2CHsbRFlZmbq6OoZhnXfJgD6nN2+egBk7AECvwPrZmZrs\nwT63FNgDK1euvHv37osXL4YMGSIjI2NlZZWUlPTs2bM/3TbBNmPGDFFRURKJpKWl1dzcjBD6\n8ePHjh07zp49u3Tp0pMnT7L/WWLT0dGJjo5GCAkKCjo5Ofn4+Fy+fHnZsmUIodzcXB0dnZ59\no7CwsEmTJs2YMaOkpOT79+/V1dVRUVGfP38eM2YMpzuViYuL//S3U15eXodl6IiICBUVlX37\n9omLi1tZWY0aNUpCQsLOzq6srGzixIkRERE9iM7eSjx06FA7Ozs3NzdVVVUqlSoqKjpt2jQ7\nOzsWi5WVldWjrwVAt0BhBwDA2YABAwYMGBAVFdX5UlRUlIKCQh9qafU3Jk+enJCQUF1dnZaW\nVltbGxMTM2rUqJ49CsMwEolkYWExdepUISEhaWlpKSkpf3//wMDAgwcP1tTUJCUltX144cKF\nISEhoaGh7Z/AZDI9PDx0dXW73ym1PRaLtWLFilWrVv3vf/+TkpJCCBEIhCFDhrx8+bKwsNDX\n17dn36ubRo0aVVVVdeXKlfaDLS0ty5cvl5CQaDsDBSFUUFBQWFhYWFgYHh5eW1tbW1sbGRlZ\nV1dnaWlJoVAqKip6EF1OTg7DMFlZWUNDw/fv32/evDkqKiogIEBHR+fUqVMYhqWlpf3tNwSg\nC7jOF/YNsBQLAKd5eXkpKioWFRW1H8zPz5eVle1wbC/oJnFx8aCgoPLy8oiIiFu3biUmJrLP\nVGMymSQS6dmzZ+0/vHXrVjKZvGTJkvv376ekpNy6dWvEiBGioqKJiYk9ix4fH49h2E87mG3e\nvHnYsGE9e2w3JScnYxhGIBDmzp1748aNly9f+vj4GBgYSEtLi4iIXLlype2To0ePJpFIbY3U\n2JqamiwsLJSUlFxcXHqWgLCwMIVCmTBhQnNzc9tgY2Mju6bcs2dPzx7bA0VFRY8fPz516lRI\nSEj7LnPgL8FSLAAAdGXr1q3y8vLGxsYnTpyIiYmJjo4+duyYiYnJoEGDNmzYgHd2fZK8vHxm\nZqaYmNiIESMcHBwMDAzYZ3zk5OS0tLQoKCi0fTInJ+fTp08IoXPnztnb2+vq6i5YsEBGRiY+\nPr7HJ9jl5eWJiIjIyMh0vqSpqZmbm9uzx3aTnp7ejBkzZGVlv337tnbt2rFjx546dcrU1JRO\npysoKDg5ObE/xmKx4uPjmUzms2fP2t9OJpMXL16cm5s7bty4niWgqanJ3njB/qYsFis5OXni\nxIkNDQ0Yhv10B/Q/19LSsn79ekVFRScnp7Nnz7LbEHt5efXg9BzQt0BhBwDAn6Cg4MuXL5cs\nWeLj4zN06FArK6tz586tXLkyLCysPxxQzAlTp049d+5ch1fKEELHjx/X1tbW0NBg/+enT59M\nTEzKysqCgoLy8vLi4+P37t3Lz8/PYrHY+x56RkhIiN13ofOlqqoqLvTd9vf3Hzx4cGRkpIaG\nxoIFC1RUVAIDA2trax8/ftzWLbeysrKystLFxWXBggX37t1j/d/X8hITE9mH7Jibm/csuqmp\nKYZh+fn5dDpdXFycRqOxS2Rra2sJCQn2biFOW758eUBAwLVr1x4+fOju7n7u3LnDhw+fP39+\nzZo1XIgO8ITvhGGfAEuxAHBTfX19Q0MD3ln0eVVVVerq6sOGDUtNTWWPVFRUbNiwocM67LBh\nw+zs7Drs0/z48SOFQgkMDOxx9MrKSjKZHBwczGKxmpqawsPDfXx8zp8/Hxsba2Nj4+rq2uMn\n/5EXL15s37599uzZGzZsuHPnTocGX/X19QihyMjILVu2kMlkSUnJoUOHKisrYxjGPieluLi4\nZ3EvXbpEoVBkZWWPHz9++fLl4ODg0NBQFxcXfn5+Nzc3ExOTf/HluhIfH08gEPbv3y8tLc3e\nQyMrK4sQMjY2JhAIHz9+5HQCPK83L8VC5wkAQO9CoVDwToEXiIiIhIeHL1y4UEdHR1JSkkaj\nZWdny8nJBQcHt53ulpWVFRkZmZqa2qGbGXs19vLly22rln+KRqMtXbp0xYoVP3782L59e0lJ\nCZ1Ob2xszM7ORggFBwf/5bfrptGjR48ePfpXVykUip6e3tOnT/fu3evu7h4ZGdnWeSIkJCQr\nK2vAgAE9i6utrd3U1DR16tStW7fW1dXx8fExGAxDQ8Pw8PBjx45xoWlYcHAwnU7fvn37tm3b\n1q1bR6VSEUKfP39etGgRiUS6c+eOrq4up3MAeIHCDgAAOC4lJeXt27d5eXkqKirDhg0bNGgQ\nF4LKy8s/ffo0MzMzMTGxpqZGR0fH0NCQTCa3feDz589CQkLa2tqd72UfqPs30Q8fPhwXF+fq\n6qqtrb106dL6+vrw8PDv37/r6uouXrw4Pj6ePYeEr9WrV69Zs2bChAkWFhYODg7swcTExH37\n9rH75PaMiYmJjo5ORUVFeXl5RkZGeXm5pqbmgAEDIiMj79271+GVPk7Iz88vKChYt27d9u3b\n2wY1NDRCQ0OlpaWfPHmyc+dOTucA8AKFHQAAcFBtba2rq+vt27fV1NSUlZWvXbuWk5Pj6up6\n+vRpfn5+LiSgrKz8+PHjoKCglJQUISEhPT09Nze3SZMmIYTYM0ksFqvzSYGtra0dpvH+lICA\nQEtLi7W1tYKCwuPHj2k02siRI69fv66oqDhkyJC9e/eeOXPmb57/TyxcuDAuLm7EiBGzZ8+2\nsLAgEAixsbHXrl2bMWPGqlWrevxYDMMuXbo0atSoSZMmrVy5kkAg+Pn5JSQkPHnyZPny5T0+\nxab7mpqaamtrV69e3WGcSqUOHDgwLy+P0wkAPOG9FtwHwDt2AIAemzhxIp1Oj4+Pbxt58+aN\nnJzcggULuBC9pqZm6NChUlJS27Ztu3v37pUrV5YsWUIikdauXctisfLz8zEMi4mJ6XzjnDlz\npk2b9jehv3//jhD66YEp58+fl5eX/5uH/1uPHj1ycHDQ0NCg0+lTp069c+fOP3ns58+fra2t\nCYT/s0mRRCJhGKahoREdHf1Pnt+FrVu3IoRKS0s7jBcWFpLJ5F+15QDd15vfsYPC7vegsAMA\n9MyLFy9IJNLnz587jL97945AICQlJXE6AXd3dzU1tQ7nyUVERPDz89+9e5fFYk2ePNnCwqLD\nQW4vXrwgEolPnz79m9DsQz1++jdneHg4gUBgMpl/8/xuYjKZ169fnz59uoaGhqGh4bx58968\necOFuCwWKzc3V0pKasqUKW/fvq2trWWxWCUlJa6urlQqtccHBHYTu2eGtbWXwSNSAAAgAElE\nQVR1ZWVl22B5efmoUaMUFRUHDRrE0ej9QW8u7GApFgAAOCUkJGTkyJFtb9RVVFQwmUwJCQkz\nMzN9ff0nT57o6+tzLnp9ff3FixcDAgLY58nl5+ezD+AYMWKEq6urj4/PtGnTfH19R4wYYWRk\n5O7urq+vX1FRER4efvbs2bVr144ZM+ZvorP7hZSVlXU+3OTHjx8iIiJc6BTX0tLi6Oj47Nmz\n2bNne3h4NDQ0REZGjhw5cseOHdu2beN09J07d9Lp9Dt37rBPEEQISUlJnT9/vqKiYv369U+f\nPuVcaDMzM0FBwU+fPtHpdFtbW2Vl5a9fv4aEhAwcOFBeXv6nb1UCngHn2AEAAKcUFxcrKSk1\nNjayT2AWFxeXlJSUkZHx9PSUk5MrKiriaPT09PT6+nobG5tz587Jy8srKCgMGTJEUlJST09P\nUlIyPj4eISQrK/vhw4fJkyf7+vra2Ni4uLgkJyffvHnz0KFDfxldTU1NXl7+9u3bnS/dvn3b\nysrqL5/fHbt3746JiYmLizt37tzSpUvXrFlz586d+/fv79mzJyQkhNPR79+/v2LFiraqrs3q\n1atfvnxZXV3NudAUCmXdunXNzc1ubm4EAiEiIoJEIh06dGjatGlxcXHr1q3jXGiAP7ynDPsA\nWIoFAPTMqlWrbG1tLS0tFRQUzp49m5CQkJycfOHCBXV1dUFBwc2bN3M0+tu3bxFCnp6egoKC\nhw8fzszMbGhoSE5OXrVqFYFAYJ9C3F77/lf/hK+vL5VK7bCk6+3tTSQSf/pi37/V3NwsKirq\n7+/f+dKSJUusra05Gr22thYh9P79+86X2G8fpqenczSB1tbW+fPnE4lEW1tbLy+vZcuWaWtr\nCwsL379/n6Nx+wlYigUAgP5o9OjRvr6+7OmxgQMHsgf19PT09fVNTU0zMzM5Gl1NTY1AIBw7\nduzevXvp6elubm7p6enS0tKGhoZDhgyJiYmpqqpiL5iytbVk+Ffc3Nxyc3PHjx8/bNgwY2Pj\nhoaGqKiorKysixcv9ripQ/dlZGRUVlba2tp2vmRrazt37lyORqdQKCQSqby8vPMl9qCIiAi7\ndV58fHxJSYmmpua4ceM2bNjQ/lfkb/Dx8V26dGn+/PkPHz6Mj4+n0WjOzs4LFizoDafMAI6C\nwg4AADhl0qRJGIYJCAiw/m+7KoRQdna2i4uLvr7+8+fPW1tbOy/V/StSUlJKSkrl5eVeXl5V\nVVXz5s1zcXEpLi5++PBhdHQ0iUQKCQmZNWsWh6KzHThwwMHB4c6dO58+fSKTyU5OTnPnzlVU\nVORoUDZ2t1b22bwdUKnUxsZG1s/OeflXCASCpaVlUFDQ2LFjO1y6d++eurr6vXv3Vq1aNWPG\njK1bt0pLS6ekpFy4cCEwMDAiIqJ9J9+/NGrUKC6crgJ6F7ynDPsAWIoFAPQM+z0qXV1dQUHB\nsWPHLl682NramkwmW1tbs19x+/btG0cTGDt2LB8fn4iIyMOHDysqKgoKCgIDA1VUVFRUVDAM\nW7VqFUej46u0tJRAIPx0zff48eNc2BkaGhpKJBKvXr3afjAsLIxCoezatYs9o9b+Ul1dnZWV\n1ejRozmdGPh7sBQLAAD9EfsMs/PnzxcXF7M7T1hYWGzYsGHMmDFZWVkIIU7vDCUSiexmVvb2\n9gwGAyFEpVKXLFmyd+/egQMHxsXFcTQ6viQlJa2trfft2xccHNz+51xVVXXy5Mk5c+ZwOoFx\n48YdO3ZswYIFZ86csbS0JBKJHz58ePny5caNG4uKikaOHDl//vz2nxcUFDx79qy2tvanT5+4\n0HYM8Coo7AAAgFOoVKqKikp0dLSHh8fkyZPbX3rz5o2UlFTbi3ccQqPRiETiy5cvm5ubP336\nJCQkpKqqysfH9+PHj4aGhqqqKo5Gx523t7elpeX06dN37dqlra3d2toaHR29bt06QUHB9evX\ncyGBlStX2tjYXLly5ePHj83NzQYGBvv37zc1NbW0tGQ3/ygoKMjMzBwwYACdTieRSFpaWrKy\nsgkJCVDYgR6D404AAICDlixZcujQodzc3PaDRUVFu3fvXrhw4V+27fotU1NTJpO5e/duAQEB\nQ0NDOp3Ox8fX0tKybNkyCQmJ9n1juaO4uLiuro5r4bS1tSMjI0tKSvT19alUKpVKtbGx0dTU\njIiIEBYW5k4OWlpa+/fvf/jwYVhY2JEjR0xNTRFCzc3Nubm5Ojo68vLyY8aM0dHRkZCQ2LVr\nV2trK5lMbm5u5k5ugCfBjB0AAHDQ2rVrX758aWpqum7dOgsLCz4+vtjY2KNHjyorK7dv0M4h\nhoaGGIYdPHgwKipq2rRp8vLyGRkZAQEBxcXF5ubmAgICnE6AraioyMvL68GDB+Xl5QQCQV1d\nfcWKFe7u7m3ttjhHV1c3MjKysLAwJSVFUFBQR0dHVFSU00F/i0qlnjt3zt3dPSgoSF1dvby8\nPCQkZP369cnJyd++fWs70RqAHsBY7fZqgZ/y8/Nzc3OrqanpfH46AAD8Vmtrq7e396VLlzIy\nMlgslrq6urOz8/r16/n5+bkQWlVVdcyYMSwW6927d/n5+erq6iNHjpw6deqYMWNu3Lhhb2/P\n6RxycnKGDh0qJye3du1aAwODmpqa8PDwAwcO2NraXrt2jQv9J3qbpqYmWVnZqqqq9+/fGxoa\nto0nJycbGhoOHDgwLy+P01O54C81Nzfz8/NHRUVZWlrinUtHMGMHAACcRSQSPT09PT092ScA\nc6Geax/az89vypQpixYtunv3Lp1Or6ysDA0NnTFjhq2t7ZQpU7iQw7JlyzQ0NEJDQ9tWfs3M\nzGxtbS0sLAIDAzl93kov9OrVq/r6egcHB2tr6717944bN05KSiotLe3EiRMYhunp6UFVB/4G\nFHYAAMAl3H+nDSE0YcKEsLCwVatW+fr6kkiklpYWISGh1atXb9++nQuzZQUFBWFhYe/evevw\n3fX09BYuXOjv799PCjsmk5mYmJiSkkIgENLT01VUVK5evXrs2LFdu3a5u7sjhDAMGzZsmJub\nG/scHAB6DAo7AADgcaNGjfr48eP3798/f/4sKSmpoaHBtRLz06dPRCLRxMSk86UhQ4YEBQVx\nJw18ffjwYcGCBampqUpKSgwGIz8/n0wmp6WlrV+/fv369d++ffvx4wedThcSEtq2bRvXXnwE\nvAoKOwAA6BdkZWW5306KQCCwD03tPDvIZDK5sHkCd2lpadbW1lOmTHn+/Dn7dJsXL17Y2NhY\nWVnFxcWpqqoqKCi0tZp4+vTpyJEjuZBVSUmJv79/+25m9vb2/fB9R57E+3+oAAAA4EVbW5vJ\nZMbExHS+FBkZqaury/2UuGzTpk3Dhg27fPly25mF1tbW7PYSmzZtav/JI0eOJCcnL126lNMp\nhYeHa2lpXbp0SVJScvTo0eXl5c7Ozra2tvX19ZwODbgAZuwAAABwysCBAydNmuTp6fnixQsK\nhVJWVvbp06eBAwf++PHj0qVL169fxztBzmpoaAgLC3v06FGHybArV66YmpreuXNn69at2tra\nRUVFoaGhr1+/vnz5sqqqKkdTKiwstLe3X7hw4ZEjR9p2aXz9+nXMmDErVqzw9/fnaHTABVDY\nAQAA4KAzZ84MHz6cPXWXl5fHHsQwzMTEpEM3Dt5TUlLS3Nysrq7eYVxWVjYoKMjCwuL169f+\n/v4yMjJGRkbx8fHa2tqcTun06dPKyspHjx5tvw6uqqp64cIFa2vrPXv2yMnJcToHwFGwFAsA\nAICDZGVl//e//+Xl5VVUVGAYxs/Pr6+v7+Likp2d3aFZKu9h97eorKzsfKmpqQnDsGfPnn3/\n/j0uLu6///7jQlWHEIqMjLS3t+/8duOIESNERUWjo6O5kAPgKCjsAAAAcFBLS8vatWvXrFlT\nXV1dW1tbV1eXlJR04cKFFy9e3Llz5/Hjx3gnyEHi4uI6Ojo/3fwbFBRkZmbGzUMN2WpqasTE\nxDqPYxgmJiZWXV3N5XzAPweFHQAAAA6Kior6/v37tm3bEEKCgoJt73Xp6+vPmDGD51+z8/Ly\nOnLkSEhISPvBO3funDlzxsvLi/v5yMvLZ2Zmdh6vr68vKCho258L+i54xw4AAAAHZWVlKSkp\n/bRDq4GBwd27d7mfEjc5OztnZmZOnjx5xIgRZmZm7D3CUVFRBw4c4E7njw7s7e09PT23b98u\nLS3dftzX15dKpQ4fPpz7KYF/C2bsAAAAcBA/P39jY+NPLzU2NnJ/LZL7du7cGRsba2RklJCQ\n8PHjRwsLi4SEhPXr1+OSzLx58zQ0NKytrWNjY9kjDQ0NR48e9fLyOnr0KIVCwSUr8A/BjB0A\nAAAOMjY2zs/PT0tL67w54NmzZz9tSsF7jIyMjIyM8M4CIYSIRGJISIibm5uFhYWoqKiUlNTX\nr19pNNp///3H83tZ+gmYsQMAABx8/vzZxcVFQ0ODQqHo6OgsXbo0NzcX76Q4Qltb29raeunS\npbW1te3Hz5w58+7dOzc3N7wS67fExMRu3ryZnZ194cIFT0/P58+f5+XlQVXHM2DGDgAAuC0s\nLGzatGlDhgxZt26dgoJCdnb21atXDQwMQkNDLSws8M7u37t8+fLo0aP19PRcXFy0tLRKS0uf\nPHkSFhb233//aWho4J1dP6WkpKSkpIR3FuDfg8IOAAC4qry8fPbs2StXrjx48GDboJub29Kl\nS52cnNLT03nvPSc5ObkPHz54e3s/ffrUx8dHSkrKyMjo3bt3hoaGeKcGAK+Bwg4AALgqMDBQ\nUFBwz5497QcJBIK3t7ecnNzDhw8dHR05Fz0nJycuLq6wsFBDQ8PU1PSnm1U5QVhYeNu2bexD\nTwAAnAPv2AEAAFclJCRYWVmRSKQO41Qq1dzcPDExkUNxq6urnZ2dVVVVlyxZ4ufnN3nyZEVF\nRW9vbw6FAwDgAgo7AADgqpaWFjKZ/NNLZDK5ubmZE0GZTKa9vX1cXFx0dHRZWdnHjx/j4uIc\nHR03bNjg4uJSXFzMiaAAAO6Dwg4AALhq0KBB8fHxnceZTGZiYiKHNhPcvXv3/fv3T58+tbCw\nqKqqcnJy0tXVDQsLU1BQuHz5spKS0s6dO1ksFidCAwC4Cd6xAwAArnJyctq5c+eNGzdmzZrV\nftzHx6eyspJD3QiCg4Pt7e0VFRVZLNa0adO+f//+/v17Y2NjBoMhJSW1YMECb29vJpO5e/du\nTkRv8+HDh6tXr6ampiKEdHR05syZw81z7EpLS/38/D58+PD9+3d1dXVra+u5c+f+avYUgD4K\nZuwAAICr1NTU9u/fv2DBgu3bt3/8+LGmpiYhIWHt2rUeHh6nTp0aMGAAJ4Lm5+erq6sjhIKD\ng2NiYkJDQ42NjRFCfHx8Kioq8vLyFy9ePHTo0Pfv3zkRnW3Xrl0WFhZpaWnm5ubm5uZpaWkW\nFha7du3iXMT2oqKitLW1r127pqqq6ujoKCgouGHDBktLyx8/fnAnAQC4A2bsAACA2zw9PRUU\nFLZv3962N1ZPT+/Bgwe2trYcikij0crLyxFCDx8+tLOza3+AWVlZGY1Gs7e3l5SUDAsLc3Fx\n4UQCgYGBBw4cCA4OnjhxYtvg48ePp0+frqmp6eTkxImgbcrLy6dMmeLg4HDq1Cki8f/8w3fg\nwIEJEybMnTv3yZMnHI0OADfBjB0AAODAycnp8+fPP378iI+Pr6ioSE5O5lxVhxAaPnz4w4cP\nm5ubv3//rqKi0jb+4cOH3Nzc4cOHYximoqLCuRm7gwcPenh4tK/qEEITJ05cs2bNgQMHOBS0\nzYULF2g02smTJ9uqOoSQlJTUlStXwsLCkpKSOJ0AAFwDhR0AAOBGQkLC0NCQC4fJLVq0qL6+\nfsmSJSIiIm2Lj7m5ufPmzXNwcBg0aBBCqLS0lEOZ1NTUJCUl2dvbd75kb2+flJTUodvYPxcd\nHW1ra9v5iBktLS06nR4dHc3R6ABwEyzFAgAA97S0tFy7du3Vq1eZmZlycnLm5uYLFy7kQmEn\nKir66NGjKVOmNDQ0NDY2SkpKfvnyJSQkxMLC4vz58wihxMTEjIyMkSNHciI6u2776dcUExND\nCNXU1AgJCXEidFsCv/oh02g0TpeVAHATzNgBAACXlJaWWlpaenh4sFis8ePHi4uLnzp1SldX\nNyEhgQvRTUxM0tLSFi1axGAwvL293717N3bs2MOHD4uIiGRnZ8+aNWv69Ok6OjqcCC0pKUmh\nUDIzMztfysjIoFAoUlJSnIjbRlFR8fPnz+z/XV1dvX///nHjxqmpqY0YMeLjx48crSkB4DKY\nsQMAAC6ZPXs2hmGfP39u2/ra1NTk6uo6adKk9PR0LpQXAQEB3t7e2traOTk5paWlUVFRpqam\ndDqd/ZrdxYsXORSXRCJNmjTp+PHjtra2BML/P6HAZDK9vb0nTZrU/tU3Tpg+ffq0adM+f/5M\nIpFsbGwQQk5OTjNnzrx3715zc7OXl5eOjo6VlRVHc2jT2NhYUVEhIyPDnXCg32GB3zl79ixC\nqKamBu9EAAB9WGxsLIFAyMjI6DBeX18vKyt7+vRpTifw5MkTIpE4Y8YMOTk59t//JBJJUlKS\nj49v7dq1TCaTo9EzMzPFxcVnzJiRk5PDHsnJyZkxY4a4uHhWVhZHQ7NNmTJFQUFBTU1t3Lhx\ndXV1NTU1x44dI5PJp0+fdnd3l5SULC8v52gCTCbz/Pnz2trafHx8CCExMbHZs2fn5eVxNCjg\nkKamJoRQVFQU3on8BCzFAgAAN0RGRuro6NDp9A7jFApl/PjxUVFRnE5g3759srKyb9682bJl\nS3Jy8tevX2/cuKGsrEylUoODgzEM42h0dXX1iIiIr1+/Kisry8jIyMjIKCsrf/36NSIiQk1N\njaOh2QIDA42Njb98+RIeHq6pqUmj0fbv3+/j4+Pu7n7s2DFBQcErV65wNIHly5evXr3ayckp\nPDw8KirKz88vNzfXyMgoPT2do3FBfwNLsQAAwA01NTXsjQKdiYmJlZSUcDR6a2trdHQ0lUpN\nSkpqO+5ERUXFzs7OwsIiMTGxpKSEQ2cjt9HT0/vw4UNqampb5wkdHR1OF5RtBAQEzMzMvn37\ndujQoYKCAg0NDX19fQqFghAik8k2NjaxsbGcix4SEnLhwoX9+/cHBQXt37+/qalJTExs1KhR\nZDLZ1dWVC2U927t370JDQ9PT08XFxY2MjJycnOD9Qt4DM3YAAMANCgoK7DXHzpcyMzMVFBQ4\nGr2+vp7JZM6cObP9IXYIIX5+/i1btiCEvn37xtEE2DAM09XVdXJyYjer5VpVx9bQ0ECj0ayt\nrefNm2dubs6u6tioVGpDQwPnQvv7++vp6Xl5eZmZmT169Cg1NfX8+fO1tbXv3r2Ljo7mwqQd\ng8FYvHixpaXl8+fPRUVFS0tLt27dqqmp+e7dO06HBlwGM3YAAMANEyZMWL58eWBgYIcWsWlp\naaGhoY8ePeJodGFhYQzDxMXFf3oJIVRTU8PRBNp8//795cuX6enpYmJixsbGVlZW7bdTcJSq\nqur58+eZTGbniKmpqYaGhpwLnZCQkJOTc/PmzRkzZrBHtLW1p06dumjRosuXL3/8+FFTU5Nz\n0RFCW7duvX//fnR0tLm5OXuksbHR3d3d1tY2LS1NWlqao9EBN8GMHQAAcMPAgQN37NixaNGi\n//77r7m5GSHEZDLDwsLGjx9vZ2c3ZswYjkbHMIxIJD569IjBYHS45OPjgxDizpLcoUOHVFRU\nNm7cGBsbe/369XHjxpmamn758oULoRFCEydOrK6uvnDhQofxyMjIiIgIR0dHzoWuqqpSU1Nr\nq+rYMAz73//+x2Aw0tLSOBeaHf348eO+vr5tVR1CSEBA4Ny5c7KysidPnuRodMBlUNgBAACX\nbNq0ae/evZ6enkJCQoMGDRIREbGzs5s0adK1a9e4EH3w4MFfvnyZOXNmW9+wHz9+LF68+Nmz\nZ2QyWUNDg9MJnDp1ateuXZcuXcrPz3/69GlcXFxOTo6UlJSNjQ135gulpKQOHz7s7u6+b9++\nwsJChFBFRYW/v/+kSZPc3NzMzMw4F5pEInXue4EQYqfRudr+t6KioggEwpQpUzqM8/HxOTg4\nhIeHczQ64DIo7AAAgHs8PDzYZc2GDRvu3LmTn5/v4+MjICDAhdCrV69GCCUnJ8vJyamoqKir\nq0tLS0dERMjIyDg7O7MXZDmnoaFh27Ztx44dmzVrVturdTIyMvfu3UMInT59mqPR2yxfvvzi\nxYu+vr6ysrJCQkLi4uJr167duHEjp2et5OXlP336FBER0X6wubl5zZo1QkJCkpKSHI1eUVEh\nLi7+08pSWlq6vLyco9EBl8E7dgAAwFXCwsIjR47kUPOuLsyePfvFixe3bt1asGCBuLg4Hx9f\nS0vL/fv3RUREjh49yuno0dHRDQ0N8+bN6zBOoVCcnZ2fPHni5eXF6RzYnJ2dnZycvnz5kpmZ\nKS8vr6Wlxc/Pz+mgVlZWRUVF48ePX7VqlY2Njbi4eEpKyqlTp75//97U1MShhh9tZGRkSktL\n6+rqqFRqh0s5OTlwVDKPgcIOAAD6BQzDLly4MHLkSF9f35SUlKamJjqdPnfu3E2bNgkKCnI6\nenFxsaSk5E8DKSoqFhcXczqB9ohEooaGBhdWn9u4uLicOHFi5cqVr1+/Pn36dENDg4KCwoQJ\nE6qrq+Pi4kaMGMHR6JaWllQq9eLFiytWrGg/Xltbe+3atVWrVnE0OuAyKOwAAKC/wDBs3rx5\n8+bNY7FYLS0tZDKZa6ElJCTKy8ubm5s7By0qKpKQkOBaJrjQ1dU9cODA5s2bly1btnPnTgkJ\nidzcXD8/v3fv3j179ozTHdUEBAT279+/Zs0aKpU6f/589qbg3Nzc+fPnCwgILFu2jKPRAZfB\nO3YAANDvYBjGzaoOIWRpaYlh2J07dzqMt7a23rx509rampvJ4GL9+vX379+Pj4+fNm2amZnZ\n0qVLxcTE4uLi2u9U5Rw3N7dDhw6tWLFCSkpq+PDh2tra6urqra2tz58/77w+C/o0mLEDAADA\nccLCwhs3blyxYoWcnFzbymNdXd3SpUtLS0vZGzt43sSJEydOnMhgMCorK7k/Sbl69WpnZ+eI\niIhPnz5JSUkNHjzYwsKCyzkALoDCDgAAADds27atvLx81KhRRkZGurq6ZWVlb9++FRYWDg0N\n5fS20F6Fj48Pr6VnSUnJDmfpAd4DS7EAAAC4gUAgnDhxIjExkX0UsKam5okTJ9LS0oyMjPBO\njXsiIyMdHBzU1dXFxcUtLS337dtXX1+Pd1KAp8CMHQAAAO7R19fX19fHOwt8HD9+fP369Y6O\njps2bZKUlPz48aOfn9+NGzfCw8OlpKTwzg7wCCjsAAAAAI6LjY319PS8ceNGW+8ye3v7VatW\nWVtbL126NCgoCN/0AM+ApVgAAACA43x8fOzs7Dp0pKXRaKdPn75//35+fj5eiQEeA4UdAAAA\nwHHx8fE2Njadx83NzYWEhBISErifEuBJfW8plsViZWdnf/36ld00mkaj0el0BQUFvPMCAAAA\nfqm5ufmnvcvYZwo2NzdzPyXAk/pSYVdRUbFv374rV66UlJR0uKSoqLho0SJPT08KhYJLbgAA\nAEAX6HR6YmJi5/G8vLzy8nI6nc79lABP6jOFXWFh4dChQ7Ozs+l0uq2trZKSkpCQEIvFqq6u\n/vLly6tXr7Zv33737t3w8HAxMTG8kwUAAAD+H87OzosXL16zZs2gQYPaj2/btk1XV7ff7hQG\n/1yfKey2bduWn59/69YtBweHzlcZDIafn9+KFSt27drl7e3N/fQAAACALsycOTMwMNDKyurg\nwYOjR49mH3dy5MiRkJCQ8PBwvLMDvKPPbJ54/Pjx3Llzf1rVIYT4+PiWL1/u6OgIO8YBAAD0\nQuxWuW5ubh4eHkpKSlQq1cLCoqSkJDo62szMDO/sAO/oM4VdWVmZmppa15/R0tIqLi7mTj4A\nAADAHyGRSDt37iwrK8vKyoqNja2urn716pWBgQHeeQGe0meWYmVlZZOSkrr+TEJCgqysLHfy\nAQAAAHqAQCCoqan9dqoCgJ7pMzN29vb2t2/fPnLkSFNTU+erdXV1O3bsCA4OdnJy4n5uAAAA\nAAC9QZ+Zsdu5c+ebN2/Wr1+/e/duMzMzBQUFKpWKEKqtrc3NzY2Nja2vrx8+fPjWrVvxzhQA\nAAAAAB99prATFRV9+/atj49PQEBAREQEg8Fou0QikYyNjV1dXV1cXPj4+HBMEgAAAAAAR32m\nsEMIkclkDw8PDw+PxsbGb9++sTtPiIiIKCoqkslkvLMDAAAAAMBZXyrs2ggICMAh3QAAAAAA\nHfSZzRMAAAAAAKBrfXLG7qe+fPmydOlShNDz58+7f1d2dra5uXlra2sXn2Hvw8Uw7C8zBAAA\nAADgKN4p7Gpqal68ePGndykpKd26davrwi41NXXNmjUkEukvsgMAAAAA4DjeKew0NTU/fvz4\np3cRCISRI0d2/RlBQcEe5gQAAAAAwEW8U9gJCAjo6urinQUAAAAAAG76XmHHYrGys7O/fv3K\nPu6ERqPR6XQFBQW88wIAAAAAwFlfKuwqKir27dt35cqVkpKSDpcUFRUXLVrk6elJoVBwyQ0A\nAAAAAHd9prArLCwcOnRodnY2nU63tbVVUlISEhJisVjV1dVfvnx59erV9u3b7969Gx4eLiYm\nhneyAAAAAAA46DOF3bZt2/Lz82/duuXg4ND5KoPB8PPzW7Fixa5du7y9vbmfHgAAAAAA7vrM\nAcWPHz+eO3fuT6s6hBAfH9/y5csdHR2DgoK4nBgAAAAAQC/RZwq7srIyNTW1rj+jpaVVXFzM\nnXwAAAAAAHqbPlPYycrKJiUldf2ZhIQEWVlZ7uQDAAAAANDb9JnCzt7e/vbt20eOHGE3+Oqg\nrq5ux44dwcHBTk5O3M8NAAAAAKA3wFgsFt45dEtlZaW1tXV8fLywsOh4BKAAABfUSURBVLCZ\nmZmCggKVSkUI1dbW5ubmxsbG1tfXDx8+PCQkREhI6N+Gjo6OHjp0aFNTE5lM/rdPBgAAAECf\n09zczM/PHxUVZWlpiXcuHfWZXbGioqJv37718fEJCAiIiIhgMBhtl0gkkrGxsaurq4uLCx8f\nH45JAgAAAADgqM8UdgghMpns4eHh4eHR2Nj47ds3ducJERERRUVFmEsDAAAAAOhLhV0bAQEB\nOp2OdxYAAAAAAL1Ln9k8AQAAAAAAugaFHQAAAAAAj4DCDgAAAACAR0BhBwAAAADAI6CwAwAA\nAADgEVDYAQAAAADwCCjsAAAAAAB4RJ88x47L2Kcf8/Pz450IAAAAAHqL3tkcoc/0isVXUlJS\na2sr555vamrq5eWlpaXFuRDgV1avXu3o6Dh06FC8E+mPdu7caWJiYmdnh3ci/dGJEyckJCTm\nzJmDdyL9UUBAQFVV1cqVK/FOpD968OBBampqQEDAXz6HSCQaGBj8k5T+LZix6xYu/OLZ2NiM\nGjWK01FAZ15eXkOHDoV/3nBx+vRpQ0ND+OHjIigoSFFREX74uHj37l1RURH88HGRl5dXUFBg\nbGyMdyKcAu/YAQAAAADwCCjsAAAAAAB4BBR2AAAAAAA8Ago7AAAAAAAeAYUdAAAAAACPgMIO\nAAAAAIBHQGEHAAAAAMAjoLADAAAAAOARUNgBAAAAAPAIKOx6BTKZ3DtbzvUH8MPHEfzwcQQ/\nfBzBDx9HPP/Dh16xvUJ2draysjKGYXgn0h/l5eXJysoSidBeDweFhYWioqIUCgXvRPqjHz9+\nkMlkERERvBPpj6qqqlpbWyUkJPBOpD9qaGiorKyUkZHBOxFOgcIOAAAAAIBHwFIsAAAAAACP\ngMIOAAAAAIBHQGEHAAAAAMAjoLADAAAAAOARUNgBAAAAAPAIKOwAAAAAAHgEFHYAAAAAADwC\nCjsAAAAAAB4BhR0AAAAAAI+Awg4AAAAAgEdAYQcAAAAAwCOgsAMAAAAA4BFQ2AEAAAAA8Ago\n7AAAAAAAeAQUdgAAAAAAPAIKOzxVVFR4enoqKSmRSCRJScnJkyfHxMTgnVR/8fXr18WLF6up\nqfHz80tJSdnb28fGxuKdVH+0du1aDMMWLVqEdyL9wqVLl7Cf2bt3L96p9SNPnjwZMWKEsLCw\nqKjo6NGjIyIi8M6oXxAQEPjpb34Mw3JycvDO7l8i4p1A/1VeXm5sbJyTkzNx4sT58+d//fr1\n5s2bYWFh4eHhlpaWeGfH4xITE62srJqamhwdHdXU1LKysm7duhUSEvLq1ashQ4bgnV0/8uHD\nh5MnT+KdRT9SWVmJEJo1a5aiomL78aFDh+KUUb9z8eLFhQsXqqmprVmzprGx8fLly+PGjYO/\n9rlg/fr1LS0tHQZv3rxZVFQkIiKCS0qcwgI4cXd3RwidOnWqbeTu3bsIoQkTJuCYVT8xZswY\nDMNevXrVNhIUFIQQmjRpEo5Z9TctLS2DBw82MDBACLm6uuKdTr+wY8cOhND79+/xTqSfKi4u\nFhISMjQ0rK2tZY9kZmYKCwu7u7vjm1j/9P79ez4+vr179+KdyD8GM3a4IZFI1tbWS5cubRuZ\nOnUqhUJJS0vDMat+wtzc3MTExMrKqm1k8uTJJBLp69evOGbV3xw9ejQpKSkkJGTChAl459Jf\nsGfsREVF8U6knwoICKitrT1w4ACVSmWPqKurV1VVYRiGb2L9EIPBWLJkyaBBg9avX493Lv8Y\nFHa4OX78eIeR5ubm1tZWcXFxXPLpV/bs2dNhpKioqKWlhU6n45JPP/Tly5ddu3a5ublZWFjg\nnUs/0lbYMRiMwsJCAQEBSUlJvJPqR54/f06hUEaPHo0QampqampqEhERgaoOF6dOnUpISAgP\nDyeTyXjn8o/B5olexN/fv6WlZeHChXgn0r/U19dHRETY2toKCwtv2bIF73T6i6VLl4qJiR04\ncADvRPqXqqoqhJC3t7eUlJSCgoKUlJSGhsb169fxzqu/SE9PV1FR+fjx47BhwygUCo1GU1dX\nv3TpEt559Tt1dXX79++3trYeOXIk3rn8e1DY9RavX7/29PQcNmyYm5sb3rn0I6KiolQqddSo\nUXp6eomJiSYmJnhn1C9cunTpxYsXJ0+epNFoeOfSv7Bn7G7cuLFhw4aAgAAvL6+ioiJnZ2c/\nPz+8U+sXysvL6+rq7OzsLCwsbt++feLEiZaWFhcXF19fX7xT619Onz5dWlq6c+dOvBPhCIzF\nYuGdA0A3btxwcXHR0dF59uwZLMVyk5eXV3l5eUpKSkxMjKWl5eXLl1VVVfFOiseVlJRoaWkN\nHTr0wYMHCKHKykoxMTFXV9fz58/jnRrve/nyZUVFxfjx49ve8UpLSzMyMqJSqYWFhby3JtXb\nCAgINDU1BQQEzJ07lz1SWFg4aNAgAQGBoqIiPj4+fNPrJxoaGhQVFbW1tV+9eoV3LpyB9+6N\n/o7JZG7btg0hNH78+OrqarzT6b8iIiKoVKq+vj6DwcA7Fx43c+ZMISGh3Nxc9n9WVFQg2BWL\nq6lTpyKEYmNj8U6E90lISJDJ5NbW1vaDDg4OCKHk5GS8supvrl69ihC6fPky3olwCizF4onF\nYi1atGjPnj0rV6589OiRsLAw3hn1XyNGjJgyZUpycvLnz5/xzoWXPXnyJDAw0MPDg0Ag5Ofn\n5+fnf//+HSFUX1+fn59fXV2Nd4L90YABAxBCtbW1eCfC+5SVlRkMBpPJbD8oJSWFEKqpqcEp\nqX7n5s2bfHx8kydPxjsRToHCDk8eHh7+/v779+8/efIkTMJzTUFBgYGBwbx58zqMNzY2IoTq\n6urwSKq/ePHiBUJoz549Cv+Xjo4OQujGjRsKCgr79+/HO0FeVltb6+vre+PGjQ7jqampCCEl\nJSU8kupfhgwZwmAw4uPj2w9mZWUhhBQUFHBKqn9pbm5++fKloaEhDx/6A+/Y4SYoKGj69Omr\nV6/29vbGO5d+R0FBoaSk5PXr1+bm5uyRjIwMY2NjhFBpaamAgACu2fGyT58+ffnypf1IXV3d\nzJkzx44du3LlSnV1dU1NTbxy43lMJlNRUbGqqur9+/dtP+fg4GB7e3tDQ8MO1QbghLi4OFNT\n01GjRoWEhPDz8yOEPnz4YG5urqurm5SUhHd2/UJiYqKhoSFvv9QL59jhZsOGDQghJpO5adOm\nDpc2btwoJiaGR1L9xalTp2bMmDF8+PDp06erqakVFBTcvn27rq7u9OnTUNVxlJaWlpaWVvsR\n9j5NBQUFOzs7nJLqLwgEwpkzZ+zt7U1MTJycnOTk5FJSUu7fvy8iIsLD/8j1KsbGxuz/M29h\nYTF16tT8/PyrV68SicQTJ07gnVp/wX7ZRkVFBe9EOAnvl/z6ry5+UbKzs/HOjvfFxMTY29tL\nSUnx8fGJiora2Ng8ePAA76T6I9g8wWXR0dETJkwQFRUlEomysrLz5s3LzMzEO6l+hMlknj17\n1sDAQEBAgEaj2drawrYVbmKfLHPixAm8E+EgWIoFAAAAAOARsHkCAAAAAIBHQGEHAAAAAMAj\noLADAAAAAOARUNgBAAAAAPAIKOwAAAAAAHgEFHYAAAAAADwCCjsAAAAAAB4BhR0AAAAAAI+A\nwg4AAAAAgEdAYQcAAAAAwCOgsAMAAAAA4BFQ2AEAAAAA8Ago7P6/9u42pqmzjQP4dbQt0JQV\nkFImEHDIRojyomVFZjdSyITC0MF8gc1lYaCtk+FMNGIUJEsmC5kv4UWTsYmgQ6cyMUMGWQQC\n0gXEgQluGWQIMoowRhGUKi99PpytTx9QRB8Zcvz/PtGL0+u+6Afz99znnAIAAABwBIIdAAAA\nAEcg2AEAAABwBIIdAAAAAEcg2AEAAABwBIIdAAAAAEcg2AEAAABwBIIdAAAAAEcg2AEAAABw\nBIIdAAAAAEcg2AEAAABwBIIdAAAAAEcg2AEAAABwBIIdAAAAAEcg2AEAAABwBIIdAAAAAEcg\n2AEAAABwBIIdAAAAAEcg2AEAAABwBIIdAAAAAEcg2AHAXLJhwwaGYbq7u2d0FR6PFxAQMEPN\n2T+hs7NzhvoDwPMMwQ4AnhUnTpxgHi4rK4uIfH19V61aZWFhwb4lPT29tbXVvMnkCgDA84M3\n2wMAAPwPuVz+wLNlvr6+RLRr165du3axFZ1Ol5yc7Ovru3jx4odVAACeKwh2APBsCQ0N3bdv\n33SOrK+vf2QFAOC5gq1YAJhLTNfYRURErF69mojCwsIYhqmpqZlcYd9y69atjz76yNXVVSAQ\nSCSSNWvWTMh/Fy9eXL58uZWVlYODQ3x8vF6vn2IAhUIxb968rq4u82JnZ+e8efNef/119mVt\nba1KpbK3txcIBG5ubhs3brxx48YDu0VERDAMY77i6OgowzAhISGmytTz37t3LyMjw8fHRywW\nW1tbe3t7Z2RkjI+PP/qjBAAuwhk7AJiT9uzZY2dnV1BQkJKS4ufn5+XlNblCRL29vXK5XK/X\nq9XqJUuW3Lx5MycnR6FQlJWVvfHGG0RUU1MTGRkplUpTUlIkEkllZWVkZOS8eQ/9T29MTExN\nTU1RUdHWrVtNxbNnzxqNxvfee4+IGhoagoOD7ezskpKSHB0df//99+zs7PLy8uvXry9YsOBx\n/8xHzq/RaI4dOxYbG6vRaBiGKSsr27lzZ3t7O3tJIgA8d4wAAM+GgoICIkpNTZ3imPXr1xOR\nTqczGo379+8notLSUtNvJ1c0Gg2Px6uvrzdVOjo6rK2tZTIZ+zI0NJSI6urqTAds2bKFiORy\n+QMH6Onp4fF4QUFB5sXAwEALC4u//vrLaDTm5OQsW7asoqLC9NvMzEwiyszMNP8Tbt68aTQa\nw8PDiai/v9908MjICBEFBwdPc36hULhixQrzYT755JPo6OjR0dEHf4IAwGnYigUAzjIajd9+\n+623t7ezs3P3P/h8fmBg4JUrV4aGhsbHxysrK93d3f39/U3vSkhImKKnRCIJCQmprq7u6elh\nK52dnVqtVqVS2draEpFGo2loaAgKCiKikZERg8HAnjt82G7s/zM/EfH5/Pb2dtMwRHTgwIGz\nZ8/Onz//cZcDAA5AsAOAZ0taWtoDH3fS2Nj4uK16enr6+vquXr364v8qKysjoo6ODp1OZzAY\nXnrpJfN3eXp6Tt02JiZmbGzs/Pnz7EvzfVhWbm5uQECAra2tQCCwsrIKDg4motHR0ac+PxGl\npaV1dXV5eHi8//77x44d++OPPx53FQDgElxjBwDPFn9//1dffXVyXSKRPG6rwcFBIvL19WW3\naCdYuHBhb28vEVlaWprXLS0tGYaZou3bb7+9efPmc+fObdq0iYjOnDljY2PDbqoS0e7du/fv\n3y+TyQ4ePLho0SILC4vm5ub4+PjHHX468xNRUlLS0qVLMzMzi4qKCgoKGIYJCwvLyclxdXV9\nghUBYK5DsAOAZ4tKpZrm404eydramv2BvZBuMnY302AwTCgajcap20ZERBQXF/f399+5c0er\n1cbHx7PPTDYYDIcOHXJxcamoqBCJROzxAwMD05/5/v3705+fpVQqlUrlvXv3qqurT5w4kZ+f\nHxIS0tzcLBAIpr8uAHADtmIBgLOkUqm9vf2vv/464Qkm7Ik6InJ0dOTz+W1tbea/vXbt2iM7\nx8bGjoyMlJSUTNiH7e7uHh4elslkplRHRFVVVQ/rw+fziYi9YYJlPswj5zdnYWEREhKSl5en\nVqtbW1ufYOcaADgAwQ4A5ir2/oDh4eEpKmvXrjUYDOx9qaze3l5vb++33nqLiHg83muvvdba\n2mr+ZLjs7OxHLq1SqcRicWlp6fnz511dXRUKBVt3cHBgGMb8PonGxsb8/HyadF6Q9eKLLxLR\nL7/8YqqwB09z/p9++snJyWnCW9hntbCREQCeN9iKBYC5ir3pIT09va2tTaFQ+Pv7T67s27ev\npKQkNTW1o6Nj5cqVXV1dR48e7evr+/jjj9kmO3furKqqioiIiIuLW7BgQVVV1d27d8Vi8dRL\nW1hYREVFFRcX3759e8eOHaZr8oRCYXh4+Pfff69Wq4OCgq5fv56VlXXy5MnIyMiSkpLCwsLI\nyEjzPlFRUUeOHNm+fXtGRoZQKCwuLtZqtaYdWCKaen6ZTGZnZ5eQkFBTU+Pr68swzJUrV/Ly\n8lauXMl+AxsAPHdm9WErAAD/9bjPsbt//350dLSVlZWtre2ZM2ceWDEajTqdTqPRuLi48Hg8\nGxsblUpVXV1t3vPUqVNLly5lv9chLi6uv7/fxcXFz89v6mnLy8vZf0Wbm5vN6z09PbGxsRKJ\nRCwWK5VKdq20tDSRSOTo6KjT6cyfY2c0GvPy8tzd3fl8vlQq3bRpk16vX7hwoUKhMDWcev6+\nvr5t27a5u7sLhUKxWOzj47Nnz57BwcFHfNYAwFGMccprhAEAAABgrsA1dgAAAAAcgWAHAAAA\nwBEIdgAAAAAcgWAHAAAAwBEIdgAAAAAcgWAHAAAAwBEIdgAAAAAcgWAHAAAAwBEIdgDABRs2\nbGAYprOz8//sk5iYKBKJmpqa2JfffPONs7Mzj8fbsWPHTA+WkpIiEAiqqqqebCEAAEKwAwAw\nKSwszMrKOnz4sI+PDxENDAzEx8cPDQ19+umnq1atmunVU1NTAwIC1q1b19vbO9NrAQBXIdgB\nABARDQ0NJSYmBgQEfPjhh2ylpaVleHj43XffTU5ODgkJmekB5s+ff/z4cb1ev3379pleCwC4\nCsEOAICIKDs7u6+vb+/evaaKwWAgImtr639thkWLFsXFxZ08ebK5uflfWxQAuATBDgC4JjY2\nlmEYvV6/efNmqVQqFAoDAgLq6uru3r27bds2JycnkUgkl8svX75sesv4+PjBgwc9PT1VKhVb\nCQ0NVSgURPT5558zDKNWq5+s8wS1tbUqlcre3l4gELi5uW3cuPHGjRvmByQkJBiNxpycnJn4\nZACA8xDsAIBrBAIBEa1du9bZ2fmHH344cuRIU1PTO++8s379ektLywsXLhw/fvy3336Ljo4e\nGRlh33L16tVbt269+eabpiapqamfffYZEUVFRX333XcajebJOptraGgIDg5uampKSkrKzs6O\niYkpLi6Wy+V9fX2mY/z8/CQSyblz52byEwIAzuLN9gAAAE8Zj8cjIg8PD3Zf1c/Pr7S09PTp\n03K5PD09nYiWL19eXV19+PDh+vr6wMBAIvrxxx+JSKlUmpqsWLFibGyM7bNmzZon7myurq7O\ny8vriy++CAoKYitOTk6JiYmFhYVbt25lKwzDKJXK06dPt7S0eHh4zNRnBAAchTN2AMBNUVFR\npp8XL15MRKtXrzZVXnnlFSLS6XTsy5aWFtNhT7ezOY1G09DQwKa6kZERg8Hg5eVFRBN2Y9k8\n197ePp1hAADMIdgBADc5OTmZfmbPtJlX+Hw+EZk2TP/8808isre3f+qdJ8jNzQ0ICLC1tRUI\nBFZWVsHBwUQ0OjpqfoyDg4NpJACAx4JgBwDcxAasqSsmt2/fJiKxWPzUO5vbvXt3QkLC2NjY\nwYMHKysrtVptbm7u5MNsbGyIaGBgYDo9AQDM4Ro7AAB64YUXiGhgYMDS0nKGljAYDIcOHXJx\ncamoqBCJRGzxgelNr9fTtFMmAIA5nLEDAPh7E9b87tSnrru7e3h4WCaTmVIdET3wC8TYb56Y\n5r4wAIA5BDsAgL/vV2htbZ25JRwcHBiGMb9PorGxMT8/n/55ErIJeyeHq6vrzA0DAFyFYAcA\nQOw3hl26dGnmlhAKheHh4T///LNarT516lRKSopSqfzyyy95PF5JSUlhYeGdO3eIyGg0Xrp0\nSSqV4lknAPAEEOwAAGjZsmVSqbS8vHxGV/n6669jY2OLiorUavXly5cvXLgQFha2d+9e9vth\nBwcHiaixsbGnp8f8iSoAANPHGI3G2Z4BAGD2paenJycnX7x4MSwsbBbH2LJly9GjR69du7Zk\nyZJZHAMA5igEOwAAIqKhoSE3N7eXX365trZ2tmZoa2vz9PRct25dQUHBbM0AAHMatmIBAIiI\nRCJRZmamVqv96quvZmWAsbGxDz74wMbG5sCBA7MyAABwAJ5jBwDwt5iYmNra2qSkJJlM5uPj\n8y+vnpaWptVqy8vLJRLJv7w0AHAGtmIBAAAAOAJbsQAAAAAcgWAHAAAAwBH/AUlTvELjRuZA\nAAAAAElFTkSuQmCC",
      "text/plain": [
       "Plot with title \"\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA0gAAANICAIAAAByhViMAAAACXBIWXMAABJ0AAASdAHeZh94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\nNu5FpuwxAAAAAElFTkSuQmCC",
      "text/plain": [
       "Plot with title \"\""
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Diagnostics\n",
    "library(car)\n",
    "vif(mod)\n",
    "plot(mod$fitted.values,mod$residuals, xlab=\"Fitted values\", ylab=\"Residuals\")    \n",
    "plot(data2$INT,mod$residuals, xlab=\"Response\", ylab=\"Residuals\")\n",
    "\n",
    "plot(mod)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"13\"            \" rows dropped\"\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>Estimate</th><th scope=col>Std. Error</th><th scope=col>t value</th><th scope=col>Pr(&gt;|t|)</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>(Intercept)</th><td>-0.2684</td><td>0.2843 </td><td>-0.944 </td><td>3.5e-01</td></tr>\n",
       "\t<tr><th scope=row>Age</th><td>-0.0028</td><td>0.0029 </td><td>-0.990 </td><td>3.2e-01</td></tr>\n",
       "\t<tr><th scope=row>OwnRent</th><td>-0.0143</td><td>0.0682 </td><td>-0.210 </td><td>8.3e-01</td></tr>\n",
       "\t<tr><th scope=row>SqftCate</th><td>-0.0258</td><td>0.0308 </td><td>-0.838 </td><td>4.0e-01</td></tr>\n",
       "\t<tr><th scope=row>Income</th><td>-0.0148</td><td>0.0167 </td><td>-0.889 </td><td>3.7e-01</td></tr>\n",
       "\t<tr><th scope=row>Educ</th><td> 0.0013</td><td>0.0276 </td><td> 0.048 </td><td>9.6e-01</td></tr>\n",
       "\t<tr><th scope=row>EnergyC</th><td> 0.0751</td><td>0.0263 </td><td> 2.861 </td><td>4.3e-03</td></tr>\n",
       "\t<tr><th scope=row>MC</th><td> 0.1478</td><td>0.0306 </td><td> 4.836 </td><td>1.6e-06</td></tr>\n",
       "\t<tr><th scope=row>Attitude</th><td> 0.3801</td><td>0.0351 </td><td>10.822 </td><td>1.4e-25</td></tr>\n",
       "\t<tr><th scope=row>SubNorm</th><td> 0.1050</td><td>0.0241 </td><td> 4.350 </td><td>1.5e-05</td></tr>\n",
       "\t<tr><th scope=row>PBC</th><td> 0.2780</td><td>0.0331 </td><td> 8.397 </td><td>2.1e-16</td></tr>\n",
       "\t<tr><th scope=row>HabitC</th><td> 0.0797</td><td>0.0207 </td><td> 3.841 </td><td>1.3e-04</td></tr>\n",
       "\t<tr><th scope=row>ComfNS</th><td>-0.0186</td><td>0.0187 </td><td>-0.998 </td><td>3.2e-01</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llll}\n",
       "  & Estimate & Std. Error & t value & Pr(>\\textbar{}t\\textbar{})\\\\\n",
       "\\hline\n",
       "\t(Intercept) & -0.2684 & 0.2843  & -0.944  & 3.5e-01\\\\\n",
       "\tAge & -0.0028 & 0.0029  & -0.990  & 3.2e-01\\\\\n",
       "\tOwnRent & -0.0143 & 0.0682  & -0.210  & 8.3e-01\\\\\n",
       "\tSqftCate & -0.0258 & 0.0308  & -0.838  & 4.0e-01\\\\\n",
       "\tIncome & -0.0148 & 0.0167  & -0.889  & 3.7e-01\\\\\n",
       "\tEduc &  0.0013 & 0.0276  &  0.048  & 9.6e-01\\\\\n",
       "\tEnergyC &  0.0751 & 0.0263  &  2.861  & 4.3e-03\\\\\n",
       "\tMC &  0.1478 & 0.0306  &  4.836  & 1.6e-06\\\\\n",
       "\tAttitude &  0.3801 & 0.0351  & 10.822  & 1.4e-25\\\\\n",
       "\tSubNorm &  0.1050 & 0.0241  &  4.350  & 1.5e-05\\\\\n",
       "\tPBC &  0.2780 & 0.0331  &  8.397  & 2.1e-16\\\\\n",
       "\tHabitC &  0.0797 & 0.0207  &  3.841  & 1.3e-04\\\\\n",
       "\tComfNS & -0.0186 & 0.0187  & -0.998  & 3.2e-01\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "| <!--/--> | Estimate | Std. Error | t value | Pr(>|t|) | \n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| (Intercept) | -0.2684 | 0.2843  | -0.944  | 3.5e-01 | \n",
       "| Age | -0.0028 | 0.0029  | -0.990  | 3.2e-01 | \n",
       "| OwnRent | -0.0143 | 0.0682  | -0.210  | 8.3e-01 | \n",
       "| SqftCate | -0.0258 | 0.0308  | -0.838  | 4.0e-01 | \n",
       "| Income | -0.0148 | 0.0167  | -0.889  | 3.7e-01 | \n",
       "| Educ |  0.0013 | 0.0276  |  0.048  | 9.6e-01 | \n",
       "| EnergyC |  0.0751 | 0.0263  |  2.861  | 4.3e-03 | \n",
       "| MC |  0.1478 | 0.0306  |  4.836  | 1.6e-06 | \n",
       "| Attitude |  0.3801 | 0.0351  | 10.822  | 1.4e-25 | \n",
       "| SubNorm |  0.1050 | 0.0241  |  4.350  | 1.5e-05 | \n",
       "| PBC |  0.2780 | 0.0331  |  8.397  | 2.1e-16 | \n",
       "| HabitC |  0.0797 | 0.0207  |  3.841  | 1.3e-04 | \n",
       "| ComfNS | -0.0186 | 0.0187  | -0.998  | 3.2e-01 | \n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "            Estimate Std. Error t value Pr(>|t|)\n",
       "(Intercept) -0.2684  0.2843     -0.944  3.5e-01 \n",
       "Age         -0.0028  0.0029     -0.990  3.2e-01 \n",
       "OwnRent     -0.0143  0.0682     -0.210  8.3e-01 \n",
       "SqftCate    -0.0258  0.0308     -0.838  4.0e-01 \n",
       "Income      -0.0148  0.0167     -0.889  3.7e-01 \n",
       "Educ         0.0013  0.0276      0.048  9.6e-01 \n",
       "EnergyC      0.0751  0.0263      2.861  4.3e-03 \n",
       "MC           0.1478  0.0306      4.836  1.6e-06 \n",
       "Attitude     0.3801  0.0351     10.822  1.4e-25 \n",
       "SubNorm      0.1050  0.0241      4.350  1.5e-05 \n",
       "PBC          0.2780  0.0331      8.397  2.1e-16 \n",
       "HabitC       0.0797  0.0207      3.841  1.3e-04 \n",
       "ComfNS      -0.0186  0.0187     -0.998  3.2e-01 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<!-- html table generated in R 3.4.1 by xtable 1.8-2 package -->\n",
      "<!-- Fri Oct 27 16:13:19 2017 -->\n",
      "<table border=1>\n",
      "<caption align=\"bottom\"> N=813 Adj-R2=0.49 </caption>\n",
      "<tr> <th>  </th> <th> Estimate </th> <th> Std. Error </th> <th> t value </th> <th> Pr(&gt;|t|) </th>  </tr>\n",
      "  <tr> <td align=\"right\"> (Intercept) </td> <td align=\"right\"> -0.27 </td> <td align=\"right\"> 0.28 </td> <td align=\"right\"> -0.94 </td> <td align=\"right\"> 0.35 </td> </tr>\n",
      "  <tr> <td align=\"right\"> Age </td> <td align=\"right\"> -0.00 </td> <td align=\"right\"> 0.00 </td> <td align=\"right\"> -0.99 </td> <td align=\"right\"> 0.32 </td> </tr>\n",
      "  <tr> <td align=\"right\"> OwnRent </td> <td align=\"right\"> -0.01 </td> <td align=\"right\"> 0.07 </td> <td align=\"right\"> -0.21 </td> <td align=\"right\"> 0.83 </td> </tr>\n",
      "  <tr> <td align=\"right\"> SqftCate </td> <td align=\"right\"> -0.03 </td> <td align=\"right\"> 0.03 </td> <td align=\"right\"> -0.84 </td> <td align=\"right\"> 0.40 </td> </tr>\n",
      "  <tr> <td align=\"right\"> Income </td> <td align=\"right\"> -0.01 </td> <td align=\"right\"> 0.02 </td> <td align=\"right\"> -0.89 </td> <td align=\"right\"> 0.37 </td> </tr>\n",
      "  <tr> <td align=\"right\"> Educ </td> <td align=\"right\"> 0.00 </td> <td align=\"right\"> 0.03 </td> <td align=\"right\"> 0.05 </td> <td align=\"right\"> 0.96 </td> </tr>\n",
      "  <tr> <td align=\"right\"> EnergyC </td> <td align=\"right\"> 0.08 </td> <td align=\"right\"> 0.03 </td> <td align=\"right\"> 2.86 </td> <td align=\"right\"> 0.00 </td> </tr>\n",
      "  <tr> <td align=\"right\"> MC </td> <td align=\"right\"> 0.15 </td> <td align=\"right\"> 0.03 </td> <td align=\"right\"> 4.84 </td> <td align=\"right\"> 0.00 </td> </tr>\n",
      "  <tr> <td align=\"right\"> Attitude </td> <td align=\"right\"> 0.38 </td> <td align=\"right\"> 0.04 </td> <td align=\"right\"> 10.82 </td> <td align=\"right\"> 0.00 </td> </tr>\n",
      "  <tr> <td align=\"right\"> SubNorm </td> <td align=\"right\"> 0.11 </td> <td align=\"right\"> 0.02 </td> <td align=\"right\"> 4.35 </td> <td align=\"right\"> 0.00 </td> </tr>\n",
      "  <tr> <td align=\"right\"> PBC </td> <td align=\"right\"> 0.28 </td> <td align=\"right\"> 0.03 </td> <td align=\"right\"> 8.40 </td> <td align=\"right\"> 0.00 </td> </tr>\n",
      "  <tr> <td align=\"right\"> HabitC </td> <td align=\"right\"> 0.08 </td> <td align=\"right\"> 0.02 </td> <td align=\"right\"> 3.84 </td> <td align=\"right\"> 0.00 </td> </tr>\n",
      "  <tr> <td align=\"right\"> ComfNS </td> <td align=\"right\"> -0.02 </td> <td align=\"right\"> 0.02 </td> <td align=\"right\"> -1.00 </td> <td align=\"right\"> 0.32 </td> </tr>\n",
      "   </table>\n"
     ]
    }
   ],
   "source": [
    "#We investigate all people: EnergyC, MC, Att, SubNorm, PBC, HabitC\n",
    "data <- survey[,-c(1:7)];\n",
    "data1 <- data[,-which(names(data) %in% c(\"HomeWYN\",\"AwayWNY\",\"AwaySNY\",\"City\",\"Utility\",\n",
    "    \"ReasonPos\",\"ReasonNeg\",\"NBillS\",\"NBillW\",\"valid1\",\"valid2\",\"valid\",\"Trust\",\n",
    "    \"MCG\", \"MCBill\",\"Frugal\",\"ComfortS\",\"ComfortW\",\"SubN\",\"ACYN\",\"HeatYN\",\n",
    "    \"Longitude\", \"Job\",\"hot\",\"cold\"))];\n",
    "fmla <- as.formula(paste(\"INT\",paste(IndepPred,collapse=\"+\"),sep=\"~\"));\n",
    "data2 = data1[,which(names(data1) %in% c(\"INT\", IndepPred)) ]\n",
    "a=dim(data2);\n",
    "data2 = na.omit(data2)\n",
    "b=dim(data2);\n",
    "print (c(a[1]-b[1], \" rows dropped\"));\n",
    "mod = lm(fmla,data=data2)\n",
    "smod = summary(mod)\n",
    "tbl = xtable(smod$coefficients, caption=paste(c(\"N=\",b[1],\" Adj-R2=\",round(smod$adj.r.squared,2)),collapse=\"\"))\n",
    "tbl\n",
    "print(tbl, type = \"html\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Older analysis below"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "tmp <- cbind(INT1=data1$INT1,INT2=data1$INT2,INT3=data1$INT3)\n",
    "data1$INT <- rowMeans(tmp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"HomeW\" \"80\"   \n",
      "[1] \"HomeS\" \"164\"  \n",
      "[1] \"AwayW\" \"151\"  \n",
      "[1] \"AwayS\" \"264\"  \n",
      "[1] \"IncHomeS\" \"63\"      \n",
      "[1] \"IncWD\" \"98\"   \n",
      "[1] \"IncDish\" \"271\"    \n",
      "[1] \"Age\" \"4\"  \n",
      "[1] \"OwnRent\" \"2\"      \n",
      "[1] \"BillS\" \"2\"    \n",
      "[1] \"BillW\" \"2\"    \n",
      "[1] \"Sqft\" \"2\"   \n",
      "[1] \"SqftCate\" \"2\"       \n",
      "[1] \"HouseholdS\" \"2\"         \n",
      "[1] \"Political\" \"2\"        \n",
      "[1] \"Ethnic\" \"2\"     \n",
      "[1] \"Income\" \"5\"     \n",
      "[1] \"Educ\" \"7\"   \n",
      "[1] \"Latitude\" \"26\"      \n",
      "[1] \"Summer_avgF\" \"42\"         \n",
      "[1] \"Winter_avgF\" \"42\"         \n",
      "[1] \"Summer_avgC\" \"42\"         \n",
      "[1] \"Winter_avgC\" \"42\"         \n",
      "[1] \"Summer_avg\" \"42\"        \n",
      "[1] \"Winter_avg\" \"42\"        \n"
     ]
    }
   ],
   "source": [
    "#Fields with lots of missing values\n",
    "for (n in names(data1)){\n",
    "    nmis = sum(is.na(data1[,n]))\n",
    "    if(nmis >1)  print (c(n, sum(is.na(data1[,n]))))\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] 826 106\n",
      "[1] 597 106\n"
     ]
    }
   ],
   "source": [
    "#lets remover these\n",
    "data2 <- data1[,-which(names(data1) %in% c(\"HomeW\",\"AwayW\",\n",
    "                    \"AwayS\",\"IncWD\",\"IncDish\"))];\n",
    "print(dim(data2))\n",
    "data2 <- na.omit(data2)\n",
    "print(dim(data2))\n",
    "#table(data2$Political)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#names(data2)\n",
    "#These are only variables we really care about\n",
    "IVS = c(\"Age\",\n",
    "\"Gender\",\n",
    "\"OwnRent\",\n",
    "\"SqftCate\",\n",
    "\"HouseholdS\",\n",
    "\"Political\",\n",
    "\"Ethnic\",\n",
    "\"Income\",\n",
    "\"Educ\",\n",
    "\"EnergyC\",\n",
    "\"MC\",\n",
    "\"Attitude\",\n",
    "\"SubNorm\",\n",
    "\"PBC\",\n",
    "\"HabitC\",\n",
    "\"HabitG\",\n",
    "\"ConvB1\",\n",
    "\"ComfNS\",\n",
    "\"ComfNW\",\n",
    "\"INT\",\n",
    "\"CashYN\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>'Age'</li>\n",
       "\t<li>'Atti'</li>\n",
       "\t<li>'Atti1'</li>\n",
       "\t<li>'Atti2'</li>\n",
       "\t<li>'Atti3'</li>\n",
       "\t<li>'Atti4'</li>\n",
       "\t<li>'Attitude'</li>\n",
       "\t<li>'BillS'</li>\n",
       "\t<li>'BillW'</li>\n",
       "\t<li>'CashYN'</li>\n",
       "\t<li>'ComfNS'</li>\n",
       "\t<li>'ComfNS1'</li>\n",
       "\t<li>'ComfNS2'</li>\n",
       "\t<li>'ComfNS3'</li>\n",
       "\t<li>'ComfNW'</li>\n",
       "\t<li>'ComfNW1'</li>\n",
       "\t<li>'ComfNW2'</li>\n",
       "\t<li>'ControlN1'</li>\n",
       "\t<li>'ControlN2R'</li>\n",
       "\t<li>'ControlN3'</li>\n",
       "\t<li>'ControlN4'</li>\n",
       "\t<li>'ConvB1'</li>\n",
       "\t<li>'ConvB2'</li>\n",
       "\t<li>'ConvB3'</li>\n",
       "\t<li>'ConvB4'</li>\n",
       "\t<li>'Educ'</li>\n",
       "\t<li>'EmerRForm'</li>\n",
       "\t<li>'EnergyC'</li>\n",
       "\t<li>'EnergyC1'</li>\n",
       "\t<li>'EnergyC2'</li>\n",
       "\t<li>'EnergyC3'</li>\n",
       "\t<li>'EnergyC4'</li>\n",
       "\t<li>'Ethnic'</li>\n",
       "\t<li>'Frugal1'</li>\n",
       "\t<li>'Frugal2'</li>\n",
       "\t<li>'Frugal3'</li>\n",
       "\t<li>'Gender'</li>\n",
       "\t<li>'HabitC'</li>\n",
       "\t<li>'HabitC1'</li>\n",
       "\t<li>'HabitC2'</li>\n",
       "\t<li>'HabitC3'</li>\n",
       "\t<li>'HabitC4'</li>\n",
       "\t<li>'HabitC5'</li>\n",
       "\t<li>'HabitC6'</li>\n",
       "\t<li>'HabitC7'</li>\n",
       "\t<li>'HabitE1'</li>\n",
       "\t<li>'HabitE2'</li>\n",
       "\t<li>'HabitE3'</li>\n",
       "\t<li>'HabitG'</li>\n",
       "\t<li>'HomeS'</li>\n",
       "\t<li>'HouseholdS'</li>\n",
       "\t<li>'INT'</li>\n",
       "\t<li>'INT1'</li>\n",
       "\t<li>'INT2'</li>\n",
       "\t<li>'INT3'</li>\n",
       "\t<li>'INT4'</li>\n",
       "\t<li>'IncAutoS'</li>\n",
       "\t<li>'IncAutoW'</li>\n",
       "\t<li>'IncAwayS'</li>\n",
       "\t<li>'IncAwayW'</li>\n",
       "\t<li>'IncEmer10S'</li>\n",
       "\t<li>'IncEmer10W'</li>\n",
       "\t<li>'IncEmer30S'</li>\n",
       "\t<li>'IncEmer30W'</li>\n",
       "\t<li>'IncHomeS'</li>\n",
       "\t<li>'IncHomeW'</li>\n",
       "\t<li>'Income'</li>\n",
       "\t<li>'Latitude'</li>\n",
       "\t<li>'MC'</li>\n",
       "\t<li>'MC1'</li>\n",
       "\t<li>'MC2'</li>\n",
       "\t<li>'MC3'</li>\n",
       "\t<li>'MC4'</li>\n",
       "\t<li>'MC5'</li>\n",
       "\t<li>'OwnRent'</li>\n",
       "\t<li>'PBC'</li>\n",
       "\t<li>'PBC1'</li>\n",
       "\t<li>'PBC2'</li>\n",
       "\t<li>'PBC3R'</li>\n",
       "\t<li>'PBC4'</li>\n",
       "\t<li>'PBC5'</li>\n",
       "\t<li>'Political'</li>\n",
       "\t<li>'RewardForm'</li>\n",
       "\t<li>'SN'</li>\n",
       "\t<li>'SN1'</li>\n",
       "\t<li>'SN2'</li>\n",
       "\t<li>'SN3'</li>\n",
       "\t<li>'SN4'</li>\n",
       "\t<li>'Sqft'</li>\n",
       "\t<li>'SqftCate'</li>\n",
       "\t<li>'State'</li>\n",
       "\t<li>'SubNorm'</li>\n",
       "\t<li>'SubNorm1'</li>\n",
       "\t<li>'SubNorm2'</li>\n",
       "\t<li>'SubNorm3'</li>\n",
       "\t<li>'Summer_avg'</li>\n",
       "\t<li>'Summer_avgC'</li>\n",
       "\t<li>'Summer_avgF'</li>\n",
       "\t<li>'Trust1'</li>\n",
       "\t<li>'Trust2'</li>\n",
       "\t<li>'Trust3'</li>\n",
       "\t<li>'Trust4'</li>\n",
       "\t<li>'Winter_avg'</li>\n",
       "\t<li>'Winter_avgC'</li>\n",
       "\t<li>'Winter_avgF'</li>\n",
       "\t<li>'X.9to5'</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'Age'\n",
       "\\item 'Atti'\n",
       "\\item 'Atti1'\n",
       "\\item 'Atti2'\n",
       "\\item 'Atti3'\n",
       "\\item 'Atti4'\n",
       "\\item 'Attitude'\n",
       "\\item 'BillS'\n",
       "\\item 'BillW'\n",
       "\\item 'CashYN'\n",
       "\\item 'ComfNS'\n",
       "\\item 'ComfNS1'\n",
       "\\item 'ComfNS2'\n",
       "\\item 'ComfNS3'\n",
       "\\item 'ComfNW'\n",
       "\\item 'ComfNW1'\n",
       "\\item 'ComfNW2'\n",
       "\\item 'ControlN1'\n",
       "\\item 'ControlN2R'\n",
       "\\item 'ControlN3'\n",
       "\\item 'ControlN4'\n",
       "\\item 'ConvB1'\n",
       "\\item 'ConvB2'\n",
       "\\item 'ConvB3'\n",
       "\\item 'ConvB4'\n",
       "\\item 'Educ'\n",
       "\\item 'EmerRForm'\n",
       "\\item 'EnergyC'\n",
       "\\item 'EnergyC1'\n",
       "\\item 'EnergyC2'\n",
       "\\item 'EnergyC3'\n",
       "\\item 'EnergyC4'\n",
       "\\item 'Ethnic'\n",
       "\\item 'Frugal1'\n",
       "\\item 'Frugal2'\n",
       "\\item 'Frugal3'\n",
       "\\item 'Gender'\n",
       "\\item 'HabitC'\n",
       "\\item 'HabitC1'\n",
       "\\item 'HabitC2'\n",
       "\\item 'HabitC3'\n",
       "\\item 'HabitC4'\n",
       "\\item 'HabitC5'\n",
       "\\item 'HabitC6'\n",
       "\\item 'HabitC7'\n",
       "\\item 'HabitE1'\n",
       "\\item 'HabitE2'\n",
       "\\item 'HabitE3'\n",
       "\\item 'HabitG'\n",
       "\\item 'HomeS'\n",
       "\\item 'HouseholdS'\n",
       "\\item 'INT'\n",
       "\\item 'INT1'\n",
       "\\item 'INT2'\n",
       "\\item 'INT3'\n",
       "\\item 'INT4'\n",
       "\\item 'IncAutoS'\n",
       "\\item 'IncAutoW'\n",
       "\\item 'IncAwayS'\n",
       "\\item 'IncAwayW'\n",
       "\\item 'IncEmer10S'\n",
       "\\item 'IncEmer10W'\n",
       "\\item 'IncEmer30S'\n",
       "\\item 'IncEmer30W'\n",
       "\\item 'IncHomeS'\n",
       "\\item 'IncHomeW'\n",
       "\\item 'Income'\n",
       "\\item 'Latitude'\n",
       "\\item 'MC'\n",
       "\\item 'MC1'\n",
       "\\item 'MC2'\n",
       "\\item 'MC3'\n",
       "\\item 'MC4'\n",
       "\\item 'MC5'\n",
       "\\item 'OwnRent'\n",
       "\\item 'PBC'\n",
       "\\item 'PBC1'\n",
       "\\item 'PBC2'\n",
       "\\item 'PBC3R'\n",
       "\\item 'PBC4'\n",
       "\\item 'PBC5'\n",
       "\\item 'Political'\n",
       "\\item 'RewardForm'\n",
       "\\item 'SN'\n",
       "\\item 'SN1'\n",
       "\\item 'SN2'\n",
       "\\item 'SN3'\n",
       "\\item 'SN4'\n",
       "\\item 'Sqft'\n",
       "\\item 'SqftCate'\n",
       "\\item 'State'\n",
       "\\item 'SubNorm'\n",
       "\\item 'SubNorm1'\n",
       "\\item 'SubNorm2'\n",
       "\\item 'SubNorm3'\n",
       "\\item 'Summer\\_avg'\n",
       "\\item 'Summer\\_avgC'\n",
       "\\item 'Summer\\_avgF'\n",
       "\\item 'Trust1'\n",
       "\\item 'Trust2'\n",
       "\\item 'Trust3'\n",
       "\\item 'Trust4'\n",
       "\\item 'Winter\\_avg'\n",
       "\\item 'Winter\\_avgC'\n",
       "\\item 'Winter\\_avgF'\n",
       "\\item 'X.9to5'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'Age'\n",
       "2. 'Atti'\n",
       "3. 'Atti1'\n",
       "4. 'Atti2'\n",
       "5. 'Atti3'\n",
       "6. 'Atti4'\n",
       "7. 'Attitude'\n",
       "8. 'BillS'\n",
       "9. 'BillW'\n",
       "10. 'CashYN'\n",
       "11. 'ComfNS'\n",
       "12. 'ComfNS1'\n",
       "13. 'ComfNS2'\n",
       "14. 'ComfNS3'\n",
       "15. 'ComfNW'\n",
       "16. 'ComfNW1'\n",
       "17. 'ComfNW2'\n",
       "18. 'ControlN1'\n",
       "19. 'ControlN2R'\n",
       "20. 'ControlN3'\n",
       "21. 'ControlN4'\n",
       "22. 'ConvB1'\n",
       "23. 'ConvB2'\n",
       "24. 'ConvB3'\n",
       "25. 'ConvB4'\n",
       "26. 'Educ'\n",
       "27. 'EmerRForm'\n",
       "28. 'EnergyC'\n",
       "29. 'EnergyC1'\n",
       "30. 'EnergyC2'\n",
       "31. 'EnergyC3'\n",
       "32. 'EnergyC4'\n",
       "33. 'Ethnic'\n",
       "34. 'Frugal1'\n",
       "35. 'Frugal2'\n",
       "36. 'Frugal3'\n",
       "37. 'Gender'\n",
       "38. 'HabitC'\n",
       "39. 'HabitC1'\n",
       "40. 'HabitC2'\n",
       "41. 'HabitC3'\n",
       "42. 'HabitC4'\n",
       "43. 'HabitC5'\n",
       "44. 'HabitC6'\n",
       "45. 'HabitC7'\n",
       "46. 'HabitE1'\n",
       "47. 'HabitE2'\n",
       "48. 'HabitE3'\n",
       "49. 'HabitG'\n",
       "50. 'HomeS'\n",
       "51. 'HouseholdS'\n",
       "52. 'INT'\n",
       "53. 'INT1'\n",
       "54. 'INT2'\n",
       "55. 'INT3'\n",
       "56. 'INT4'\n",
       "57. 'IncAutoS'\n",
       "58. 'IncAutoW'\n",
       "59. 'IncAwayS'\n",
       "60. 'IncAwayW'\n",
       "61. 'IncEmer10S'\n",
       "62. 'IncEmer10W'\n",
       "63. 'IncEmer30S'\n",
       "64. 'IncEmer30W'\n",
       "65. 'IncHomeS'\n",
       "66. 'IncHomeW'\n",
       "67. 'Income'\n",
       "68. 'Latitude'\n",
       "69. 'MC'\n",
       "70. 'MC1'\n",
       "71. 'MC2'\n",
       "72. 'MC3'\n",
       "73. 'MC4'\n",
       "74. 'MC5'\n",
       "75. 'OwnRent'\n",
       "76. 'PBC'\n",
       "77. 'PBC1'\n",
       "78. 'PBC2'\n",
       "79. 'PBC3R'\n",
       "80. 'PBC4'\n",
       "81. 'PBC5'\n",
       "82. 'Political'\n",
       "83. 'RewardForm'\n",
       "84. 'SN'\n",
       "85. 'SN1'\n",
       "86. 'SN2'\n",
       "87. 'SN3'\n",
       "88. 'SN4'\n",
       "89. 'Sqft'\n",
       "90. 'SqftCate'\n",
       "91. 'State'\n",
       "92. 'SubNorm'\n",
       "93. 'SubNorm1'\n",
       "94. 'SubNorm2'\n",
       "95. 'SubNorm3'\n",
       "96. 'Summer_avg'\n",
       "97. 'Summer_avgC'\n",
       "98. 'Summer_avgF'\n",
       "99. 'Trust1'\n",
       "100. 'Trust2'\n",
       "101. 'Trust3'\n",
       "102. 'Trust4'\n",
       "103. 'Winter_avg'\n",
       "104. 'Winter_avgC'\n",
       "105. 'Winter_avgF'\n",
       "106. 'X.9to5'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "  [1] \"Age\"         \"Atti\"        \"Atti1\"       \"Atti2\"       \"Atti3\"      \n",
       "  [6] \"Atti4\"       \"Attitude\"    \"BillS\"       \"BillW\"       \"CashYN\"     \n",
       " [11] \"ComfNS\"      \"ComfNS1\"     \"ComfNS2\"     \"ComfNS3\"     \"ComfNW\"     \n",
       " [16] \"ComfNW1\"     \"ComfNW2\"     \"ControlN1\"   \"ControlN2R\"  \"ControlN3\"  \n",
       " [21] \"ControlN4\"   \"ConvB1\"      \"ConvB2\"      \"ConvB3\"      \"ConvB4\"     \n",
       " [26] \"Educ\"        \"EmerRForm\"   \"EnergyC\"     \"EnergyC1\"    \"EnergyC2\"   \n",
       " [31] \"EnergyC3\"    \"EnergyC4\"    \"Ethnic\"      \"Frugal1\"     \"Frugal2\"    \n",
       " [36] \"Frugal3\"     \"Gender\"      \"HabitC\"      \"HabitC1\"     \"HabitC2\"    \n",
       " [41] \"HabitC3\"     \"HabitC4\"     \"HabitC5\"     \"HabitC6\"     \"HabitC7\"    \n",
       " [46] \"HabitE1\"     \"HabitE2\"     \"HabitE3\"     \"HabitG\"      \"HomeS\"      \n",
       " [51] \"HouseholdS\"  \"INT\"         \"INT1\"        \"INT2\"        \"INT3\"       \n",
       " [56] \"INT4\"        \"IncAutoS\"    \"IncAutoW\"    \"IncAwayS\"    \"IncAwayW\"   \n",
       " [61] \"IncEmer10S\"  \"IncEmer10W\"  \"IncEmer30S\"  \"IncEmer30W\"  \"IncHomeS\"   \n",
       " [66] \"IncHomeW\"    \"Income\"      \"Latitude\"    \"MC\"          \"MC1\"        \n",
       " [71] \"MC2\"         \"MC3\"         \"MC4\"         \"MC5\"         \"OwnRent\"    \n",
       " [76] \"PBC\"         \"PBC1\"        \"PBC2\"        \"PBC3R\"       \"PBC4\"       \n",
       " [81] \"PBC5\"        \"Political\"   \"RewardForm\"  \"SN\"          \"SN1\"        \n",
       " [86] \"SN2\"         \"SN3\"         \"SN4\"         \"Sqft\"        \"SqftCate\"   \n",
       " [91] \"State\"       \"SubNorm\"     \"SubNorm1\"    \"SubNorm2\"    \"SubNorm3\"   \n",
       " [96] \"Summer_avg\"  \"Summer_avgC\" \"Summer_avgF\" \"Trust1\"      \"Trust2\"     \n",
       "[101] \"Trust3\"      \"Trust4\"      \"Winter_avg\"  \"Winter_avgC\" \"Winter_avgF\"\n",
       "[106] \"X.9to5\"     "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>'Age'</li>\n",
       "\t<li>'Attitude'</li>\n",
       "\t<li>'CashYN'</li>\n",
       "\t<li>'ComfNS'</li>\n",
       "\t<li>'ComfNW'</li>\n",
       "\t<li>'ConvB1'</li>\n",
       "\t<li>'Educ'</li>\n",
       "\t<li>'EnergyC'</li>\n",
       "\t<li>'Ethnic'</li>\n",
       "\t<li>'Gender'</li>\n",
       "\t<li>'HabitC'</li>\n",
       "\t<li>'HabitG'</li>\n",
       "\t<li>'HouseholdS'</li>\n",
       "\t<li>'INT'</li>\n",
       "\t<li>'Income'</li>\n",
       "\t<li>'MC'</li>\n",
       "\t<li>'OwnRent'</li>\n",
       "\t<li>'PBC'</li>\n",
       "\t<li>'Political'</li>\n",
       "\t<li>'SqftCate'</li>\n",
       "\t<li>'SubNorm'</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'Age'\n",
       "\\item 'Attitude'\n",
       "\\item 'CashYN'\n",
       "\\item 'ComfNS'\n",
       "\\item 'ComfNW'\n",
       "\\item 'ConvB1'\n",
       "\\item 'Educ'\n",
       "\\item 'EnergyC'\n",
       "\\item 'Ethnic'\n",
       "\\item 'Gender'\n",
       "\\item 'HabitC'\n",
       "\\item 'HabitG'\n",
       "\\item 'HouseholdS'\n",
       "\\item 'INT'\n",
       "\\item 'Income'\n",
       "\\item 'MC'\n",
       "\\item 'OwnRent'\n",
       "\\item 'PBC'\n",
       "\\item 'Political'\n",
       "\\item 'SqftCate'\n",
       "\\item 'SubNorm'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'Age'\n",
       "2. 'Attitude'\n",
       "3. 'CashYN'\n",
       "4. 'ComfNS'\n",
       "5. 'ComfNW'\n",
       "6. 'ConvB1'\n",
       "7. 'Educ'\n",
       "8. 'EnergyC'\n",
       "9. 'Ethnic'\n",
       "10. 'Gender'\n",
       "11. 'HabitC'\n",
       "12. 'HabitG'\n",
       "13. 'HouseholdS'\n",
       "14. 'INT'\n",
       "15. 'Income'\n",
       "16. 'MC'\n",
       "17. 'OwnRent'\n",
       "18. 'PBC'\n",
       "19. 'Political'\n",
       "20. 'SqftCate'\n",
       "21. 'SubNorm'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       " [1] \"Age\"        \"Attitude\"   \"CashYN\"     \"ComfNS\"     \"ComfNW\"    \n",
       " [6] \"ConvB1\"     \"Educ\"       \"EnergyC\"    \"Ethnic\"     \"Gender\"    \n",
       "[11] \"HabitC\"     \"HabitG\"     \"HouseholdS\" \"INT\"        \"Income\"    \n",
       "[16] \"MC\"         \"OwnRent\"    \"PBC\"        \"Political\"  \"SqftCate\"  \n",
       "[21] \"SubNorm\"   "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sort(names(data2))\n",
    "paste(sort(IVS))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data1 <- data2[, which(names(data2) %in% c(\"IncHomeS\",IVS))];"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Check to see if there are anymore missing values\n",
    "for (n in names(data1)){\n",
    "    nmis = sum(is.na(data1[,n]))\n",
    "    if(nmis >1)  print (c(n, sum(is.na(data1[,n]))))\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>'IncHomeS'</li>\n",
       "\t<li>'ConvB1'</li>\n",
       "\t<li>'Age'</li>\n",
       "\t<li>'Gender'</li>\n",
       "\t<li>'OwnRent'</li>\n",
       "\t<li>'SqftCate'</li>\n",
       "\t<li>'HouseholdS'</li>\n",
       "\t<li>'Political'</li>\n",
       "\t<li>'Ethnic'</li>\n",
       "\t<li>'Income'</li>\n",
       "\t<li>'Educ'</li>\n",
       "\t<li>'EnergyC'</li>\n",
       "\t<li>'Attitude'</li>\n",
       "\t<li>'PBC'</li>\n",
       "\t<li>'CashYN'</li>\n",
       "\t<li>'MC'</li>\n",
       "\t<li>'ComfNS'</li>\n",
       "\t<li>'ComfNW'</li>\n",
       "\t<li>'SubNorm'</li>\n",
       "\t<li>'HabitG'</li>\n",
       "\t<li>'HabitC'</li>\n",
       "\t<li>'INT'</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'IncHomeS'\n",
       "\\item 'ConvB1'\n",
       "\\item 'Age'\n",
       "\\item 'Gender'\n",
       "\\item 'OwnRent'\n",
       "\\item 'SqftCate'\n",
       "\\item 'HouseholdS'\n",
       "\\item 'Political'\n",
       "\\item 'Ethnic'\n",
       "\\item 'Income'\n",
       "\\item 'Educ'\n",
       "\\item 'EnergyC'\n",
       "\\item 'Attitude'\n",
       "\\item 'PBC'\n",
       "\\item 'CashYN'\n",
       "\\item 'MC'\n",
       "\\item 'ComfNS'\n",
       "\\item 'ComfNW'\n",
       "\\item 'SubNorm'\n",
       "\\item 'HabitG'\n",
       "\\item 'HabitC'\n",
       "\\item 'INT'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'IncHomeS'\n",
       "2. 'ConvB1'\n",
       "3. 'Age'\n",
       "4. 'Gender'\n",
       "5. 'OwnRent'\n",
       "6. 'SqftCate'\n",
       "7. 'HouseholdS'\n",
       "8. 'Political'\n",
       "9. 'Ethnic'\n",
       "10. 'Income'\n",
       "11. 'Educ'\n",
       "12. 'EnergyC'\n",
       "13. 'Attitude'\n",
       "14. 'PBC'\n",
       "15. 'CashYN'\n",
       "16. 'MC'\n",
       "17. 'ComfNS'\n",
       "18. 'ComfNW'\n",
       "19. 'SubNorm'\n",
       "20. 'HabitG'\n",
       "21. 'HabitC'\n",
       "22. 'INT'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       " [1] \"IncHomeS\"   \"ConvB1\"     \"Age\"        \"Gender\"     \"OwnRent\"   \n",
       " [6] \"SqftCate\"   \"HouseholdS\" \"Political\"  \"Ethnic\"     \"Income\"    \n",
       "[11] \"Educ\"       \"EnergyC\"    \"Attitude\"   \"PBC\"        \"CashYN\"    \n",
       "[16] \"MC\"         \"ComfNS\"     \"ComfNW\"     \"SubNorm\"    \"HabitG\"    \n",
       "[21] \"HabitC\"     \"INT\"       "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "names(data1)\n",
    "\n",
    "#Fields with lots of missing values\n",
    "for (n in names(data1)){\n",
    "    nmis = sum(is.na(data1[,n]))\n",
    "    if(nmis >1)  print (c(n, sum(is.na(data1[,n]))))\n",
    "}\n",
    "    \n",
    "    \n",
    "# What about high correlations?\n",
    "hiCor <- function(x, level){\n",
    "  res <- cor(x,method=\"spearman\");\n",
    "  res1 <- res; res1[res<0] <- -res[res < 0];\n",
    "  for (i in 1:dim(x)[2]){\n",
    "    res1[i,i] <- 0;\n",
    "  }\n",
    "  sel <- apply(res1,1,max,na.rm=T) > level;\n",
    "  res[sel,sel];\n",
    "}\n",
    "#hiCor(data1,.75)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message in cbind(f_parts$left, ellip_h, f_parts$right, deparse.level = 0L):\n",
      "\"number of rows of result is not a multiple of vector length (arg 2)\"Warning message in cbind(f_parts$left, ellip_h, f_parts$right, deparse.level = 0L):\n",
      "\"number of rows of result is not a multiple of vector length (arg 2)\"Warning message in cbind(f_parts$left, ellip_h, f_parts$right, deparse.level = 0L):\n",
      "\"number of rows of result is not a multiple of vector length (arg 2)\""
     ]
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th scope=col>IncHomeS</th><th scope=col>ConvB1</th><th scope=col>Age</th><th scope=col>Gender</th><th scope=col>OwnRent</th><th scope=col>SqftCate</th><th scope=col>HouseholdS</th><th scope=col>Political</th><th scope=col>Ethnic</th><th scope=col>Income</th><th scope=col>...</th><th scope=col>Attitude</th><th scope=col>PBC</th><th scope=col>CashYN</th><th scope=col>MC</th><th scope=col>ComfNS</th><th scope=col>ComfNW</th><th scope=col>SubNorm</th><th scope=col>HabitG</th><th scope=col>HabitC</th><th scope=col>INT</th></tr></thead>\n",
       "<tbody>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|llllllllllllllllllllll}\n",
       " IncHomeS & ConvB1 & Age & Gender & OwnRent & SqftCate & HouseholdS & Political & Ethnic & Income & ... & Attitude & PBC & CashYN & MC & ComfNS & ComfNW & SubNorm & HabitG & HabitC & INT\\\\\n",
       "\\hline\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "     IncHomeS ConvB1 Age Gender OwnRent SqftCate HouseholdS Political Ethnic\n",
       "     Income ... Attitude PBC CashYN MC ComfNS ComfNW SubNorm HabitG HabitC INT"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data1 [is.na(data1$IncHomeS), ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. \n",
       "    1.0     3.0     4.0     4.2     5.0     8.0 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "\n",
       "  1   2   3   4   5   6   7   8 \n",
       " 50  41 115 202  54  56  45  34 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "\n",
       "  1   2   3   4   5 \n",
       " 66 213 133 111  74 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "summary(data1$IncHomeS)\n",
    "table(data1$IncHomeS)\n",
    "table(data1$HouseholdS)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<ol class=list-inline>\n",
       "\t<li>'IncHomeS'</li>\n",
       "\t<li>'ConvB1'</li>\n",
       "\t<li>'Age'</li>\n",
       "\t<li>'Gender'</li>\n",
       "\t<li>'OwnRent'</li>\n",
       "\t<li>'SqftCate'</li>\n",
       "\t<li>'HouseholdS'</li>\n",
       "\t<li>'Political'</li>\n",
       "\t<li>'Ethnic'</li>\n",
       "\t<li>'Income'</li>\n",
       "\t<li>'Educ'</li>\n",
       "\t<li>'EnergyC'</li>\n",
       "\t<li>'Attitude'</li>\n",
       "\t<li>'PBC'</li>\n",
       "\t<li>'CashYN'</li>\n",
       "\t<li>'MC'</li>\n",
       "\t<li>'ComfNS'</li>\n",
       "\t<li>'ComfNW'</li>\n",
       "\t<li>'SubNorm'</li>\n",
       "\t<li>'HabitG'</li>\n",
       "\t<li>'HabitC'</li>\n",
       "\t<li>'INT'</li>\n",
       "</ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item 'IncHomeS'\n",
       "\\item 'ConvB1'\n",
       "\\item 'Age'\n",
       "\\item 'Gender'\n",
       "\\item 'OwnRent'\n",
       "\\item 'SqftCate'\n",
       "\\item 'HouseholdS'\n",
       "\\item 'Political'\n",
       "\\item 'Ethnic'\n",
       "\\item 'Income'\n",
       "\\item 'Educ'\n",
       "\\item 'EnergyC'\n",
       "\\item 'Attitude'\n",
       "\\item 'PBC'\n",
       "\\item 'CashYN'\n",
       "\\item 'MC'\n",
       "\\item 'ComfNS'\n",
       "\\item 'ComfNW'\n",
       "\\item 'SubNorm'\n",
       "\\item 'HabitG'\n",
       "\\item 'HabitC'\n",
       "\\item 'INT'\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. 'IncHomeS'\n",
       "2. 'ConvB1'\n",
       "3. 'Age'\n",
       "4. 'Gender'\n",
       "5. 'OwnRent'\n",
       "6. 'SqftCate'\n",
       "7. 'HouseholdS'\n",
       "8. 'Political'\n",
       "9. 'Ethnic'\n",
       "10. 'Income'\n",
       "11. 'Educ'\n",
       "12. 'EnergyC'\n",
       "13. 'Attitude'\n",
       "14. 'PBC'\n",
       "15. 'CashYN'\n",
       "16. 'MC'\n",
       "17. 'ComfNS'\n",
       "18. 'ComfNW'\n",
       "19. 'SubNorm'\n",
       "20. 'HabitG'\n",
       "21. 'HabitC'\n",
       "22. 'INT'\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       " [1] \"IncHomeS\"   \"ConvB1\"     \"Age\"        \"Gender\"     \"OwnRent\"   \n",
       " [6] \"SqftCate\"   \"HouseholdS\" \"Political\"  \"Ethnic\"     \"Income\"    \n",
       "[11] \"Educ\"       \"EnergyC\"    \"Attitude\"   \"PBC\"        \"CashYN\"    \n",
       "[16] \"MC\"         \"ComfNS\"     \"ComfNW\"     \"SubNorm\"    \"HabitG\"    \n",
       "[21] \"HabitC\"     \"INT\"       "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data2 <- data1;\n",
    "data2 <- na.omit(data2)\n",
    "names(data2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Check to see if there are anymore missing values\n",
    "for (n in names(data2)){\n",
    "    nmis = sum(is.na(data2[,n]))\n",
    "    if(nmis >1)  print (c(n, sum(is.na(data2[,n]))))\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<dl class=dl-horizontal>\n",
       "\t<dt>IncHomeS</dt>\n",
       "\t\t<dd>1.80530173759545</dd>\n",
       "\t<dt>ConvB1</dt>\n",
       "\t\t<dd>1.24800831738681</dd>\n",
       "\t<dt>Age</dt>\n",
       "\t\t<dd>11.2136471612555</dd>\n",
       "\t<dt>Gender</dt>\n",
       "\t\t<dd>0.500789120187265</dd>\n",
       "\t<dt>OwnRent</dt>\n",
       "\t\t<dd>0.519579435060886</dd>\n",
       "\t<dt>SqftCate</dt>\n",
       "\t\t<dd>1.11883935985406</dd>\n",
       "\t<dt>HouseholdS</dt>\n",
       "\t\t<dd>1.20931187813508</dd>\n",
       "\t<dt>Political</dt>\n",
       "\t\t<dd>0.826486435867867</dd>\n",
       "\t<dt>Ethnic</dt>\n",
       "\t\t<dd>0.381036786164242</dd>\n",
       "\t<dt>Income</dt>\n",
       "\t\t<dd>1.99865614244334</dd>\n",
       "\t<dt>Educ</dt>\n",
       "\t\t<dd>1.1043673387367</dd>\n",
       "\t<dt>EnergyC</dt>\n",
       "\t\t<dd>1.39050591810558</dd>\n",
       "\t<dt>Attitude</dt>\n",
       "\t\t<dd>1.09619622525647</dd>\n",
       "\t<dt>PBC</dt>\n",
       "\t\t<dd>0.939759684009595</dd>\n",
       "\t<dt>CashYN</dt>\n",
       "\t\t<dd>0.272142578592916</dd>\n",
       "\t<dt>MC</dt>\n",
       "\t\t<dd>1.07767943764375</dd>\n",
       "\t<dt>ComfNS</dt>\n",
       "\t\t<dd>1.45684092456003</dd>\n",
       "\t<dt>ComfNW</dt>\n",
       "\t\t<dd>1.74234055830498</dd>\n",
       "\t<dt>SubNorm</dt>\n",
       "\t\t<dd>1.34787551568657</dd>\n",
       "\t<dt>HabitG</dt>\n",
       "\t\t<dd>1.17479285287417</dd>\n",
       "\t<dt>HabitC</dt>\n",
       "\t\t<dd>1.42314150016437</dd>\n",
       "\t<dt>INT</dt>\n",
       "\t\t<dd>1.13771324163349</dd>\n",
       "</dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[IncHomeS] 1.80530173759545\n",
       "\\item[ConvB1] 1.24800831738681\n",
       "\\item[Age] 11.2136471612555\n",
       "\\item[Gender] 0.500789120187265\n",
       "\\item[OwnRent] 0.519579435060886\n",
       "\\item[SqftCate] 1.11883935985406\n",
       "\\item[HouseholdS] 1.20931187813508\n",
       "\\item[Political] 0.826486435867867\n",
       "\\item[Ethnic] 0.381036786164242\n",
       "\\item[Income] 1.99865614244334\n",
       "\\item[Educ] 1.1043673387367\n",
       "\\item[EnergyC] 1.39050591810558\n",
       "\\item[Attitude] 1.09619622525647\n",
       "\\item[PBC] 0.939759684009595\n",
       "\\item[CashYN] 0.272142578592916\n",
       "\\item[MC] 1.07767943764375\n",
       "\\item[ComfNS] 1.45684092456003\n",
       "\\item[ComfNW] 1.74234055830498\n",
       "\\item[SubNorm] 1.34787551568657\n",
       "\\item[HabitG] 1.17479285287417\n",
       "\\item[HabitC] 1.42314150016437\n",
       "\\item[INT] 1.13771324163349\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "IncHomeS\n",
       ":   1.80530173759545ConvB1\n",
       ":   1.24800831738681Age\n",
       ":   11.2136471612555Gender\n",
       ":   0.500789120187265OwnRent\n",
       ":   0.519579435060886SqftCate\n",
       ":   1.11883935985406HouseholdS\n",
       ":   1.20931187813508Political\n",
       ":   0.826486435867867Ethnic\n",
       ":   0.381036786164242Income\n",
       ":   1.99865614244334Educ\n",
       ":   1.1043673387367EnergyC\n",
       ":   1.39050591810558Attitude\n",
       ":   1.09619622525647PBC\n",
       ":   0.939759684009595CashYN\n",
       ":   0.272142578592916MC\n",
       ":   1.07767943764375ComfNS\n",
       ":   1.45684092456003ComfNW\n",
       ":   1.74234055830498SubNorm\n",
       ":   1.34787551568657HabitG\n",
       ":   1.17479285287417HabitC\n",
       ":   1.42314150016437INT\n",
       ":   1.13771324163349\n",
       "\n"
      ],
      "text/plain": [
       "  IncHomeS     ConvB1        Age     Gender    OwnRent   SqftCate HouseholdS \n",
       "      1.81       1.25      11.21       0.50       0.52       1.12       1.21 \n",
       " Political     Ethnic     Income       Educ    EnergyC   Attitude        PBC \n",
       "      0.83       0.38       2.00       1.10       1.39       1.10       0.94 \n",
       "    CashYN         MC     ComfNS     ComfNW    SubNorm     HabitG     HabitC \n",
       "      0.27       1.08       1.46       1.74       1.35       1.17       1.42 \n",
       "       INT \n",
       "      1.14 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#convert all data to numeric values\n",
    "\n",
    "sapply(data2,sd)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [],
      "text/latex": [],
      "text/markdown": [],
      "text/plain": [
       "<0 x 0 matrix>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "hiCor(data2,.7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] 0.17\n",
      "    ConvB1 EnergyC Attitude   PBC   MC SubNorm HabitG HabitC   INT\n",
      "PC1   0.32   -0.34    -0.38 -0.24 -0.3   -0.28  -0.27  -0.24 -0.41\n",
      "[1] 0.27\n",
      "     Age OwnRent SqftCate HouseholdS Income\n",
      "PC2 0.36     0.5     0.51       0.25   0.43\n",
      "[1] 0.34\n",
      "    IncHomeS Gender HouseholdS Ethnic Educ ComfNS ComfNW HabitC\n",
      "PC3    -0.23  -0.42      -0.37   0.29 0.29  -0.27  -0.47   0.28\n",
      "[1] 0.41\n",
      "    IncHomeS ConvB1 Political Ethnic  Educ EnergyC  PBC   MC ComfNS HabitG\n",
      "PC4      0.2  -0.25     -0.41   0.27 -0.28   -0.27 0.37 0.22   0.34   0.23\n",
      "[1] 0.47\n",
      "    IncHomeS  Age HouseholdS Political  Educ CashYN ComfNS\n",
      "PC5    -0.46 -0.3       0.41     -0.26 -0.39   -0.3   -0.3\n",
      "[1] 0.52\n",
      "    IncHomeS  Age Gender Income   PBC CashYN HabitC\n",
      "PC6     0.24 0.28   0.36  -0.28 -0.21  -0.58   0.22\n",
      "[1] 0.57\n",
      "    IncHomeS ConvB1 Ethnic EnergyC ComfNW SubNorm HabitG HabitC\n",
      "PC7    -0.23  -0.28   0.49    0.22  -0.22    -0.3  -0.41  -0.37\n",
      "[1] 0.61\n",
      "    ConvB1 Gender Political Ethnic  Educ ComfNW SubNorm\n",
      "PC8  -0.27  -0.28      0.35  -0.52 -0.33   -0.3   -0.39\n",
      "[1] 0.65\n",
      "    IncHomeS  Age OwnRent HouseholdS ComfNS ComfNW SubNorm\n",
      "PC9     -0.3 0.42    0.22      -0.35  -0.34   0.46   -0.32\n",
      "[1] 0.69\n",
      "     Gender PBC CashYN ComfNS\n",
      "PC10  -0.27 0.5  -0.63   0.34\n",
      "[1] 0.73\n",
      "     Gender Educ EnergyC  PBC    MC HabitG HabitC\n",
      "PC11   0.53 0.25   -0.25 0.32 -0.24  -0.21   0.43\n",
      "[1] 0.76\n",
      "     ConvB1 Political Educ   PBC CashYN   MC SubNorm\n",
      "PC12  -0.26     -0.22 0.39 -0.24  -0.25 0.52   -0.34\n",
      "[1] 0.8\n",
      "      Age Political Ethnic Attitude HabitG\n",
      "PC13 0.23     -0.55  -0.36     0.27  -0.37\n",
      "[1] 0.83\n",
      "     IncHomeS Income  PBC ComfNS SubNorm HabitG\n",
      "PC14     0.38  -0.41 0.23  -0.47    0.25  -0.51\n",
      "[1] 0.85\n",
      "     IncHomeS OwnRent Political Income   MC ComfNS HabitG HabitC\n",
      "PC15    -0.28    0.23      0.31  -0.34 0.53   0.31  -0.24   0.22\n"
     ]
    }
   ],
   "source": [
    "res<-prcomp(data2, retx=F,scale=T)$rotation[,1:15];\n",
    "resAbs <- res;\n",
    "resAbs[res<0] <- -res[res<0];\n",
    "z <- cumsum(prcomp(data2, retx=F,scale=T)$sdev^2)/\n",
    "     sum(prcomp(data2, retx=F,scale=T)$sdev^2)\n",
    "\n",
    "for (i in 1:15){\n",
    "  print(z[i]);\n",
    "  print(t(res[resAbs[,i]>.2,i,drop=FALSE]));\n",
    "}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA0gAAANICAMAAADKOT/pAAADAFBMVEUAAAABAQECAgIDAwME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\nrkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(1:dim(data2)[2],cumsum(prcomp(data2, retx=F,scale=T)$sdev^2)/\n",
    "     sum(prcomp(data2, retx=F,scale=T)$sdev^2),\n",
    "     ylim=c(0,1),xlab=\"Number of coponents\",\n",
    "     ylab=\"Fraction of variance\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "res <- c();\n",
    "vnam <- names(data2);\n",
    "for (i in 2:dim(data2)[2]){\n",
    "  fmla <- as.formula(paste(vnam[i],paste(vnam[-c(1,i)],collapse=\"+\"),sep=\"~\"));\n",
    "  res <- rbind(res,c(i,round(summary(lm(fmla,data=data2))$r.squared,2)));\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>INT</th><td>22  </td><td>0.52</td></tr>\n",
       "\t<tr><th scope=row>Attitude</th><td>13  </td><td>0.51</td></tr>\n",
       "\t<tr><th scope=row>EnergyC</th><td>12  </td><td>0.41</td></tr>\n",
       "\t<tr><th scope=row>SqftCate</th><td> 6  </td><td>0.38</td></tr>\n",
       "\t<tr><th scope=row>ConvB1</th><td> 2  </td><td>0.35</td></tr>\n",
       "\t<tr><th scope=row>OwnRent</th><td> 5  </td><td>0.33</td></tr>\n",
       "\t<tr><th scope=row>MC</th><td>16  </td><td>0.28</td></tr>\n",
       "\t<tr><th scope=row>HabitC</th><td>21  </td><td>0.28</td></tr>\n",
       "\t<tr><th scope=row>Income</th><td>10  </td><td>0.27</td></tr>\n",
       "\t<tr><th scope=row>HouseholdS</th><td> 7  </td><td>0.26</td></tr>\n",
       "\t<tr><th scope=row>PBC</th><td>14  </td><td>0.25</td></tr>\n",
       "\t<tr><th scope=row>SubNorm</th><td>19  </td><td>0.25</td></tr>\n",
       "\t<tr><th scope=row>HabitG</th><td>20  </td><td>0.24</td></tr>\n",
       "\t<tr><th scope=row>ComfNW</th><td>18  </td><td>0.22</td></tr>\n",
       "\t<tr><th scope=row>Age</th><td> 3  </td><td>0.21</td></tr>\n",
       "\t<tr><th scope=row>Educ</th><td>11  </td><td>0.17</td></tr>\n",
       "\t<tr><th scope=row>Gender</th><td> 4  </td><td>0.15</td></tr>\n",
       "\t<tr><th scope=row>Political</th><td> 8  </td><td>0.15</td></tr>\n",
       "\t<tr><th scope=row>ComfNS</th><td>17  </td><td>0.11</td></tr>\n",
       "\t<tr><th scope=row>Ethnic</th><td> 9  </td><td>0.09</td></tr>\n",
       "\t<tr><th scope=row>CashYN</th><td>15  </td><td>0.04</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ll}\n",
       "\tINT & 22   & 0.52\\\\\n",
       "\tAttitude & 13   & 0.51\\\\\n",
       "\tEnergyC & 12   & 0.41\\\\\n",
       "\tSqftCate &  6   & 0.38\\\\\n",
       "\tConvB1 &  2   & 0.35\\\\\n",
       "\tOwnRent &  5   & 0.33\\\\\n",
       "\tMC & 16   & 0.28\\\\\n",
       "\tHabitC & 21   & 0.28\\\\\n",
       "\tIncome & 10   & 0.27\\\\\n",
       "\tHouseholdS &  7   & 0.26\\\\\n",
       "\tPBC & 14   & 0.25\\\\\n",
       "\tSubNorm & 19   & 0.25\\\\\n",
       "\tHabitG & 20   & 0.24\\\\\n",
       "\tComfNW & 18   & 0.22\\\\\n",
       "\tAge &  3   & 0.21\\\\\n",
       "\tEduc & 11   & 0.17\\\\\n",
       "\tGender &  4   & 0.15\\\\\n",
       "\tPolitical &  8   & 0.15\\\\\n",
       "\tComfNS & 17   & 0.11\\\\\n",
       "\tEthnic &  9   & 0.09\\\\\n",
       "\tCashYN & 15   & 0.04\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "1. 22\n",
       "2. 13\n",
       "3. 12\n",
       "4. 6\n",
       "5. 2\n",
       "6. 5\n",
       "7. 16\n",
       "8. 21\n",
       "9. 10\n",
       "10. 7\n",
       "11. 14\n",
       "12. 19\n",
       "13. 20\n",
       "14. 18\n",
       "15. 3\n",
       "16. 11\n",
       "17. 4\n",
       "18. 8\n",
       "19. 17\n",
       "20. 9\n",
       "21. 15\n",
       "22. 0.52\n",
       "23. 0.51\n",
       "24. 0.41\n",
       "25. 0.38\n",
       "26. 0.35\n",
       "27. 0.33\n",
       "28. 0.28\n",
       "29. 0.28\n",
       "30. 0.27\n",
       "31. 0.26\n",
       "32. 0.25\n",
       "33. 0.25\n",
       "34. 0.24\n",
       "35. 0.22\n",
       "36. 0.21\n",
       "37. 0.17\n",
       "38. 0.15\n",
       "39. 0.15\n",
       "40. 0.11\n",
       "41. 0.09\n",
       "42. 0.04\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "           [,1] [,2]\n",
       "INT        22   0.52\n",
       "Attitude   13   0.51\n",
       "EnergyC    12   0.41\n",
       "SqftCate    6   0.38\n",
       "ConvB1      2   0.35\n",
       "OwnRent     5   0.33\n",
       "MC         16   0.28\n",
       "HabitC     21   0.28\n",
       "Income     10   0.27\n",
       "HouseholdS  7   0.26\n",
       "PBC        14   0.25\n",
       "SubNorm    19   0.25\n",
       "HabitG     20   0.24\n",
       "ComfNW     18   0.22\n",
       "Age         3   0.21\n",
       "Educ       11   0.17\n",
       "Gender      4   0.15\n",
       "Political   8   0.15\n",
       "ComfNS     17   0.11\n",
       "Ethnic      9   0.09\n",
       "CashYN     15   0.04"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "row.names(res) <- vnam[res[,1]];\n",
    "o = order(-res[,2]);\n",
    "res[o,][res[o,2]<.7,]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Call:\n",
      "factanal(x = data2, factors = 2, rotation = \"varimax\")\n",
      "\n",
      "Uniquenesses:\n",
      "  IncHomeS     ConvB1        Age     Gender    OwnRent   SqftCate HouseholdS \n",
      "      0.96       0.72       0.84       0.95       0.55       0.45       0.88 \n",
      " Political     Ethnic     Income       Educ    EnergyC   Attitude        PBC \n",
      "      0.93       0.99       0.73       0.98       0.63       0.44       0.84 \n",
      "    CashYN         MC     ComfNS     ComfNW    SubNorm     HabitG     HabitC \n",
      "      0.99       0.73       0.95       0.97       0.77       0.83       0.85 \n",
      "       INT \n",
      "      0.39 \n",
      "\n",
      "Loadings:\n",
      "           Factor1 Factor2\n",
      "ConvB1     -0.52          \n",
      "EnergyC     0.61          \n",
      "Attitude    0.75          \n",
      "MC          0.52          \n",
      "INT         0.78          \n",
      "OwnRent             0.67  \n",
      "SqftCate            0.74  \n",
      "Income              0.51  \n",
      "IncHomeS                  \n",
      "Age                 0.40  \n",
      "Gender                    \n",
      "HouseholdS          0.34  \n",
      "Political                 \n",
      "Ethnic                    \n",
      "Educ                      \n",
      "PBC         0.39          \n",
      "CashYN                    \n",
      "ComfNS                    \n",
      "ComfNW                    \n",
      "SubNorm     0.48          \n",
      "HabitG      0.41          \n",
      "HabitC      0.38          \n",
      "\n",
      "               Factor1 Factor2\n",
      "SS loadings       3.03    1.63\n",
      "Proportion Var    0.14    0.07\n",
      "Cumulative Var    0.14    0.21\n",
      "\n",
      "Test of the hypothesis that 2 factors are sufficient.\n",
      "The chi square statistic is 784 on 188 degrees of freedom.\n",
      "The p-value is 1.2e-73 \n"
     ]
    }
   ],
   "source": [
    "fit <- factanal(data2, 2, rotation=\"varimax\")\n",
    "print(fit, digits=2, cutoff=.3, sort=TRUE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#Age, Gender, OwnRent, SqftCat, Income, Educ, EnergyC, MC, Attitude, SubNorm, PBC, HabitC, ComfNS,    \n",
    "IndepPred = c(\"Age\",\"OwnRent\",\"SqftCate\",\"Income\",\"Educ\",\"EnergyC\",\"MC\",\"Attitude\",\"SubNorm\",\"PBC\",\"HabitC\",\"ComfNS\")\n",
    "\n",
    "fmla <- as.formula(paste(\"INT\",paste(IndepPred,collapse=\"+\"),sep=\"~\"));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "lm(formula = fmla, data = data2)\n",
       "\n",
       "Residuals:\n",
       "    Min      1Q  Median      3Q     Max \n",
       "-2.5551 -0.4512  0.0745  0.5189  2.0059 \n",
       "\n",
       "Coefficients:\n",
       "            Estimate Std. Error t value Pr(>|t|)    \n",
       "(Intercept)  0.04399    0.33605    0.13   0.8959    \n",
       "Age         -0.00540    0.00321   -1.69   0.0924 .  \n",
       "OwnRent     -0.00573    0.07709   -0.07   0.9407    \n",
       "SqftCate    -0.04148    0.03544   -1.17   0.2423    \n",
       "Income      -0.00548    0.01888   -0.29   0.7718    \n",
       "Educ         0.01604    0.03179    0.50   0.6140    \n",
       "EnergyC      0.07834    0.02954    2.65   0.0082 ** \n",
       "MC           0.12796    0.03420    3.74   0.0002 ***\n",
       "Attitude     0.38177    0.03902    9.78  < 2e-16 ***\n",
       "SubNorm      0.11718    0.02740    4.28  2.2e-05 ***\n",
       "PBC          0.25470    0.03753    6.79  2.8e-11 ***\n",
       "HabitC       0.10786    0.02490    4.33  1.7e-05 ***\n",
       "ComfNS      -0.05905    0.02353   -2.51   0.0124 *  \n",
       "---\n",
       "Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n",
       "\n",
       "Residual standard error: 0.8 on 584 degrees of freedom\n",
       "Multiple R-squared:  0.511,\tAdjusted R-squared:  0.501 \n",
       "F-statistic: 50.8 on 12 and 584 DF,  p-value: <2e-16\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mod = lm(fmla,data=data2)\n",
    "summary(mod)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>Df</th><th scope=col>Sum Sq</th><th scope=col>Mean Sq</th><th scope=col>F value</th><th scope=col>Pr(&gt;F)</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Age</th><td>  1    </td><td>  0.40 </td><td>  0.40 </td><td>  0.62 </td><td>4.3e-01</td></tr>\n",
       "\t<tr><th scope=row>OwnRent</th><td>  1    </td><td>  0.86 </td><td>  0.86 </td><td>  1.34 </td><td>2.5e-01</td></tr>\n",
       "\t<tr><th scope=row>SqftCate</th><td>  1    </td><td>  4.80 </td><td>  4.80 </td><td>  7.44 </td><td>6.6e-03</td></tr>\n",
       "\t<tr><th scope=row>Income</th><td>  1    </td><td>  0.93 </td><td>  0.93 </td><td>  1.44 </td><td>2.3e-01</td></tr>\n",
       "\t<tr><th scope=row>Educ</th><td>  1    </td><td>  6.24 </td><td>  6.24 </td><td>  9.66 </td><td>2.0e-03</td></tr>\n",
       "\t<tr><th scope=row>EnergyC</th><td>  1    </td><td>142.11 </td><td>142.11 </td><td>219.96 </td><td>1.8e-42</td></tr>\n",
       "\t<tr><th scope=row>MC</th><td>  1    </td><td> 67.81 </td><td> 67.81 </td><td>104.95 </td><td>9.2e-23</td></tr>\n",
       "\t<tr><th scope=row>Attitude</th><td>  1    </td><td> 98.30 </td><td> 98.30 </td><td>152.15 </td><td>3.1e-31</td></tr>\n",
       "\t<tr><th scope=row>SubNorm</th><td>  1    </td><td> 20.49 </td><td> 20.49 </td><td> 31.72 </td><td>2.8e-08</td></tr>\n",
       "\t<tr><th scope=row>PBC</th><td>  1    </td><td> 33.18 </td><td> 33.18 </td><td> 51.36 </td><td>2.3e-12</td></tr>\n",
       "\t<tr><th scope=row>HabitC</th><td>  1    </td><td> 14.96 </td><td> 14.96 </td><td> 23.15 </td><td>1.9e-06</td></tr>\n",
       "\t<tr><th scope=row>ComfNS</th><td>  1    </td><td>  4.07 </td><td>  4.07 </td><td>  6.30 </td><td>1.2e-02</td></tr>\n",
       "\t<tr><th scope=row>Residuals</th><td>584    </td><td>377.30 </td><td>  0.65 </td><td>    NA </td><td>     NA</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllll}\n",
       "  & Df & Sum Sq & Mean Sq & F value & Pr(>F)\\\\\n",
       "\\hline\n",
       "\tAge &   1     &   0.40  &   0.40  &   0.62  & 4.3e-01\\\\\n",
       "\tOwnRent &   1     &   0.86  &   0.86  &   1.34  & 2.5e-01\\\\\n",
       "\tSqftCate &   1     &   4.80  &   4.80  &   7.44  & 6.6e-03\\\\\n",
       "\tIncome &   1     &   0.93  &   0.93  &   1.44  & 2.3e-01\\\\\n",
       "\tEduc &   1     &   6.24  &   6.24  &   9.66  & 2.0e-03\\\\\n",
       "\tEnergyC &   1     & 142.11  & 142.11  & 219.96  & 1.8e-42\\\\\n",
       "\tMC &   1     &  67.81  &  67.81  & 104.95  & 9.2e-23\\\\\n",
       "\tAttitude &   1     &  98.30  &  98.30  & 152.15  & 3.1e-31\\\\\n",
       "\tSubNorm &   1     &  20.49  &  20.49  &  31.72  & 2.8e-08\\\\\n",
       "\tPBC &   1     &  33.18  &  33.18  &  51.36  & 2.3e-12\\\\\n",
       "\tHabitC &   1     &  14.96  &  14.96  &  23.15  & 1.9e-06\\\\\n",
       "\tComfNS &   1     &   4.07  &   4.07  &   6.30  & 1.2e-02\\\\\n",
       "\tResiduals & 584     & 377.30  &   0.65  &     NA  &      NA\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "          Df  Sum Sq Mean Sq F value Pr(>F) \n",
       "Age         1   0.40   0.40    0.62  4.3e-01\n",
       "OwnRent     1   0.86   0.86    1.34  2.5e-01\n",
       "SqftCate    1   4.80   4.80    7.44  6.6e-03\n",
       "Income      1   0.93   0.93    1.44  2.3e-01\n",
       "Educ        1   6.24   6.24    9.66  2.0e-03\n",
       "EnergyC     1 142.11 142.11  219.96  1.8e-42\n",
       "MC          1  67.81  67.81  104.95  9.2e-23\n",
       "Attitude    1  98.30  98.30  152.15  3.1e-31\n",
       "SubNorm     1  20.49  20.49   31.72  2.8e-08\n",
       "PBC         1  33.18  33.18   51.36  2.3e-12\n",
       "HabitC      1  14.96  14.96   23.15  1.9e-06\n",
       "ComfNS      1   4.07   4.07    6.30  1.2e-02\n",
       "Residuals 584 377.30   0.65      NA       NA"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "anova(mod)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<dl class=dl-horizontal>\n",
       "\t<dt>Age</dt>\n",
       "\t\t<dd>1.19172880832848</dd>\n",
       "\t<dt>OwnRent</dt>\n",
       "\t\t<dd>1.48005113670403</dd>\n",
       "\t<dt>SqftCate</dt>\n",
       "\t\t<dd>1.45036972782085</dd>\n",
       "\t<dt>Income</dt>\n",
       "\t\t<dd>1.31347148119746</dd>\n",
       "\t<dt>Educ</dt>\n",
       "\t\t<dd>1.13675314618415</dd>\n",
       "\t<dt>EnergyC</dt>\n",
       "\t\t<dd>1.55614272432536</dd>\n",
       "\t<dt>MC</dt>\n",
       "\t\t<dd>1.25340680035282</dd>\n",
       "\t<dt>Attitude</dt>\n",
       "\t\t<dd>1.68763067820528</dd>\n",
       "\t<dt>SubNorm</dt>\n",
       "\t\t<dd>1.25849876125969</dd>\n",
       "\t<dt>PBC</dt>\n",
       "\t\t<dd>1.14722870547427</dd>\n",
       "\t<dt>HabitC</dt>\n",
       "\t\t<dd>1.15882960085114</dd>\n",
       "\t<dt>ComfNS</dt>\n",
       "\t\t<dd>1.08387568512742</dd>\n",
       "</dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[Age] 1.19172880832848\n",
       "\\item[OwnRent] 1.48005113670403\n",
       "\\item[SqftCate] 1.45036972782085\n",
       "\\item[Income] 1.31347148119746\n",
       "\\item[Educ] 1.13675314618415\n",
       "\\item[EnergyC] 1.55614272432536\n",
       "\\item[MC] 1.25340680035282\n",
       "\\item[Attitude] 1.68763067820528\n",
       "\\item[SubNorm] 1.25849876125969\n",
       "\\item[PBC] 1.14722870547427\n",
       "\\item[HabitC] 1.15882960085114\n",
       "\\item[ComfNS] 1.08387568512742\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "Age\n",
       ":   1.19172880832848OwnRent\n",
       ":   1.48005113670403SqftCate\n",
       ":   1.45036972782085Income\n",
       ":   1.31347148119746Educ\n",
       ":   1.13675314618415EnergyC\n",
       ":   1.55614272432536MC\n",
       ":   1.25340680035282Attitude\n",
       ":   1.68763067820528SubNorm\n",
       ":   1.25849876125969PBC\n",
       ":   1.14722870547427HabitC\n",
       ":   1.15882960085114ComfNS\n",
       ":   1.08387568512742\n",
       "\n"
      ],
      "text/plain": [
       "     Age  OwnRent SqftCate   Income     Educ  EnergyC       MC Attitude \n",
       "     1.2      1.5      1.5      1.3      1.1      1.6      1.3      1.7 \n",
       " SubNorm      PBC   HabitC   ComfNS \n",
       "     1.3      1.1      1.2      1.1 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "library(car)\n",
    "vif(mod)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "lm(formula = fmla, data = data2)\n",
       "\n",
       "Residuals:\n",
       "    Min      1Q  Median      3Q     Max \n",
       "-2.5900 -0.4459  0.0784  0.5318  2.2101 \n",
       "\n",
       "Coefficients:\n",
       "            Estimate Std. Error t value Pr(>|t|)    \n",
       "(Intercept) -0.09248    0.35009   -0.26  0.79176    \n",
       "Age         -0.00557    0.00322   -1.73  0.08408 .  \n",
       "Gender      -0.03129    0.06899   -0.45  0.65033    \n",
       "OwnRent      0.00360    0.07711    0.05  0.96277    \n",
       "SqftCate    -0.03916    0.03542   -1.11  0.26934    \n",
       "Income      -0.00834    0.01896   -0.44  0.66004    \n",
       "Educ         0.01375    0.03177    0.43  0.66536    \n",
       "EnergyC      0.08102    0.02968    2.73  0.00652 ** \n",
       "MC           0.12386    0.03422    3.62  0.00032 ***\n",
       "Attitude     0.38026    0.03926    9.69  < 2e-16 ***\n",
       "SubNorm      0.11714    0.02737    4.28  2.2e-05 ***\n",
       "PBC          0.25126    0.03751    6.70  4.9e-11 ***\n",
       "HabitC       0.11137    0.02492    4.47  9.4e-06 ***\n",
       "ComfNS      -0.06052    0.02357   -2.57  0.01051 *  \n",
       "CashYNTRUE   0.24251    0.12254    1.98  0.04829 *  \n",
       "---\n",
       "Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n",
       "\n",
       "Residual standard error: 0.8 on 582 degrees of freedom\n",
       "Multiple R-squared:  0.514,\tAdjusted R-squared:  0.503 \n",
       "F-statistic:   44 on 14 and 582 DF,  p-value: <2e-16\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#added CashYN to model\n",
    "IndepPred = c(\"Age\",\"Gender\",\"OwnRent\",\"SqftCate\",\"Income\",\"Educ\",\"EnergyC\",\"MC\",\"Attitude\",\"SubNorm\",\"PBC\",\"HabitC\",\"ComfNS\",\"CashYN\")\n",
    "fmla <- as.formula(paste(\"INT\",paste(IndepPred,collapse=\"+\"),sep=\"~\"));\n",
    "mod = lm(fmla,data=data2)\n",
    "summary(mod)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>Df</th><th scope=col>Sum Sq</th><th scope=col>Mean Sq</th><th scope=col>F value</th><th scope=col>Pr(&gt;F)</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Age</th><td>  1    </td><td>  0.40 </td><td>  0.40 </td><td>  0.62 </td><td>4.3e-01</td></tr>\n",
       "\t<tr><th scope=row>Gender</th><td>  1    </td><td> 13.04 </td><td> 13.04 </td><td> 20.26 </td><td>8.2e-06</td></tr>\n",
       "\t<tr><th scope=row>OwnRent</th><td>  1    </td><td>  0.68 </td><td>  0.68 </td><td>  1.05 </td><td>3.1e-01</td></tr>\n",
       "\t<tr><th scope=row>SqftCate</th><td>  1    </td><td>  5.03 </td><td>  5.03 </td><td>  7.81 </td><td>5.4e-03</td></tr>\n",
       "\t<tr><th scope=row>Income</th><td>  1    </td><td>  0.31 </td><td>  0.31 </td><td>  0.48 </td><td>4.9e-01</td></tr>\n",
       "\t<tr><th scope=row>Educ</th><td>  1    </td><td>  6.69 </td><td>  6.69 </td><td> 10.40 </td><td>1.3e-03</td></tr>\n",
       "\t<tr><th scope=row>EnergyC</th><td>  1    </td><td>130.13 </td><td>130.13 </td><td>202.17 </td><td>1.4e-39</td></tr>\n",
       "\t<tr><th scope=row>MC</th><td>  1    </td><td> 67.19 </td><td> 67.19 </td><td>104.39 </td><td>1.2e-22</td></tr>\n",
       "\t<tr><th scope=row>Attitude</th><td>  1    </td><td> 98.31 </td><td> 98.31 </td><td>152.74 </td><td>2.5e-31</td></tr>\n",
       "\t<tr><th scope=row>SubNorm</th><td>  1    </td><td> 20.70 </td><td> 20.70 </td><td> 32.15 </td><td>2.2e-08</td></tr>\n",
       "\t<tr><th scope=row>PBC</th><td>  1    </td><td> 32.96 </td><td> 32.96 </td><td> 51.21 </td><td>2.5e-12</td></tr>\n",
       "\t<tr><th scope=row>HabitC</th><td>  1    </td><td> 14.96 </td><td> 14.96 </td><td> 23.24 </td><td>1.8e-06</td></tr>\n",
       "\t<tr><th scope=row>ComfNS</th><td>  1    </td><td>  3.93 </td><td>  3.93 </td><td>  6.11 </td><td>1.4e-02</td></tr>\n",
       "\t<tr><th scope=row>CashYN</th><td>  1    </td><td>  2.52 </td><td>  2.52 </td><td>  3.92 </td><td>4.8e-02</td></tr>\n",
       "\t<tr><th scope=row>Residuals</th><td>582    </td><td>374.61 </td><td>  0.64 </td><td>    NA </td><td>     NA</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllll}\n",
       "  & Df & Sum Sq & Mean Sq & F value & Pr(>F)\\\\\n",
       "\\hline\n",
       "\tAge &   1     &   0.40  &   0.40  &   0.62  & 4.3e-01\\\\\n",
       "\tGender &   1     &  13.04  &  13.04  &  20.26  & 8.2e-06\\\\\n",
       "\tOwnRent &   1     &   0.68  &   0.68  &   1.05  & 3.1e-01\\\\\n",
       "\tSqftCate &   1     &   5.03  &   5.03  &   7.81  & 5.4e-03\\\\\n",
       "\tIncome &   1     &   0.31  &   0.31  &   0.48  & 4.9e-01\\\\\n",
       "\tEduc &   1     &   6.69  &   6.69  &  10.40  & 1.3e-03\\\\\n",
       "\tEnergyC &   1     & 130.13  & 130.13  & 202.17  & 1.4e-39\\\\\n",
       "\tMC &   1     &  67.19  &  67.19  & 104.39  & 1.2e-22\\\\\n",
       "\tAttitude &   1     &  98.31  &  98.31  & 152.74  & 2.5e-31\\\\\n",
       "\tSubNorm &   1     &  20.70  &  20.70  &  32.15  & 2.2e-08\\\\\n",
       "\tPBC &   1     &  32.96  &  32.96  &  51.21  & 2.5e-12\\\\\n",
       "\tHabitC &   1     &  14.96  &  14.96  &  23.24  & 1.8e-06\\\\\n",
       "\tComfNS &   1     &   3.93  &   3.93  &   6.11  & 1.4e-02\\\\\n",
       "\tCashYN &   1     &   2.52  &   2.52  &   3.92  & 4.8e-02\\\\\n",
       "\tResiduals & 582     & 374.61  &   0.64  &     NA  &      NA\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "          Df  Sum Sq Mean Sq F value Pr(>F) \n",
       "Age         1   0.40   0.40    0.62  4.3e-01\n",
       "Gender      1  13.04  13.04   20.26  8.2e-06\n",
       "OwnRent     1   0.68   0.68    1.05  3.1e-01\n",
       "SqftCate    1   5.03   5.03    7.81  5.4e-03\n",
       "Income      1   0.31   0.31    0.48  4.9e-01\n",
       "Educ        1   6.69   6.69   10.40  1.3e-03\n",
       "EnergyC     1 130.13 130.13  202.17  1.4e-39\n",
       "MC          1  67.19  67.19  104.39  1.2e-22\n",
       "Attitude    1  98.31  98.31  152.74  2.5e-31\n",
       "SubNorm     1  20.70  20.70   32.15  2.2e-08\n",
       "PBC         1  32.96  32.96   51.21  2.5e-12\n",
       "HabitC      1  14.96  14.96   23.24  1.8e-06\n",
       "ComfNS      1   3.93   3.93    6.11  1.4e-02\n",
       "CashYN      1   2.52   2.52    3.92  4.8e-02\n",
       "Residuals 582 374.61   0.64      NA       NA"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "anova(mod)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "lm(formula = fmla, data = data2)\n",
       "\n",
       "Residuals:\n",
       "   Min     1Q Median     3Q    Max \n",
       "-4.845 -0.550  0.139  0.672  3.484 \n",
       "\n",
       "Coefficients:\n",
       "            Estimate Std. Error t value Pr(>|t|)    \n",
       "(Intercept)   3.2424     0.2673   12.13   <2e-16 ***\n",
       "OwnRent      -0.0503     0.0960   -0.52     0.60    \n",
       "SqftCate     -0.0698     0.0452   -1.55     0.12    \n",
       "Income       -0.0102     0.0235   -0.43     0.66    \n",
       "MC            0.4247     0.0397   10.71   <2e-16 ***\n",
       "---\n",
       "Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n",
       "\n",
       "Residual standard error: 1 on 592 degrees of freedom\n",
       "Multiple R-squared:  0.17,\tAdjusted R-squared:  0.164 \n",
       "F-statistic: 30.3 on 4 and 592 DF,  p-value: <2e-16\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#economic factor model\n",
    "econ = c(\"OwnRent\",\"SqftCate\",\"Income\",\"MC\")\n",
    "fmla <- as.formula(paste(\"INT\",paste(econ,collapse=\"+\"),sep=\"~\"));\n",
    "mod = lm(fmla,data=data2)\n",
    "summary(mod)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>Df</th><th scope=col>Sum Sq</th><th scope=col>Mean Sq</th><th scope=col>F value</th><th scope=col>Pr(&gt;F)</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>OwnRent</th><td>  1    </td><td>  1.20 </td><td>  1.20 </td><td>  1.11 </td><td>2.9e-01</td></tr>\n",
       "\t<tr><th scope=row>SqftCate</th><td>  1    </td><td>  4.87 </td><td>  4.87 </td><td>  4.50 </td><td>3.4e-02</td></tr>\n",
       "\t<tr><th scope=row>Income</th><td>  1    </td><td>  0.93 </td><td>  0.93 </td><td>  0.86 </td><td>3.5e-01</td></tr>\n",
       "\t<tr><th scope=row>MC</th><td>  1    </td><td>123.98 </td><td>123.98 </td><td>114.60 </td><td>1.4e-24</td></tr>\n",
       "\t<tr><th scope=row>Residuals</th><td>592    </td><td>640.48 </td><td>  1.08 </td><td>    NA </td><td>     NA</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllll}\n",
       "  & Df & Sum Sq & Mean Sq & F value & Pr(>F)\\\\\n",
       "\\hline\n",
       "\tOwnRent &   1     &   1.20  &   1.20  &   1.11  & 2.9e-01\\\\\n",
       "\tSqftCate &   1     &   4.87  &   4.87  &   4.50  & 3.4e-02\\\\\n",
       "\tIncome &   1     &   0.93  &   0.93  &   0.86  & 3.5e-01\\\\\n",
       "\tMC &   1     & 123.98  & 123.98  & 114.60  & 1.4e-24\\\\\n",
       "\tResiduals & 592     & 640.48  &   1.08  &     NA  &      NA\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "          Df  Sum Sq Mean Sq F value Pr(>F) \n",
       "OwnRent     1   1.20   1.20    1.11  2.9e-01\n",
       "SqftCate    1   4.87   4.87    4.50  3.4e-02\n",
       "Income      1   0.93   0.93    0.86  3.5e-01\n",
       "MC          1 123.98 123.98  114.60  1.4e-24\n",
       "Residuals 592 640.48   1.08      NA       NA"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "anova(mod)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "lm(formula = fmla, data = data2)\n",
       "\n",
       "Residuals:\n",
       "    Min      1Q  Median      3Q     Max \n",
       "-2.5601 -0.4589  0.0633  0.5285  2.3070 \n",
       "\n",
       "Coefficients:\n",
       "            Estimate Std. Error t value Pr(>|t|)    \n",
       "(Intercept)  0.24835    0.30921    0.80   0.4222    \n",
       "Age         -0.00592    0.00301   -1.97   0.0498 *  \n",
       "Gender      -0.03205    0.06923   -0.46   0.6436    \n",
       "EnergyC      0.08968    0.02986    3.00   0.0028 ** \n",
       "Attitude     0.41310    0.03879   10.65  < 2e-16 ***\n",
       "SubNorm      0.12837    0.02743    4.68  3.6e-06 ***\n",
       "PBC          0.28640    0.03690    7.76  3.7e-14 ***\n",
       "HabitC       0.11356    0.02499    4.55  6.7e-06 ***\n",
       "ComfNS      -0.06033    0.02373   -2.54   0.0113 *  \n",
       "---\n",
       "Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n",
       "\n",
       "Residual standard error: 0.81 on 588 degrees of freedom\n",
       "Multiple R-squared:  0.497,\tAdjusted R-squared:  0.49 \n",
       "F-statistic: 72.6 on 8 and 588 DF,  p-value: <2e-16\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#non economic factor model\n",
    "non_econ = c(\"Age\",\"Gender\",\"EnergyC\",\"Attitude\",\"SubNorm\",\"PBC\",\"HabitC\",\"ComfNS\")\n",
    "fmla <- as.formula(paste(\"INT\",paste(non_econ,collapse=\"+\"),sep=\"~\"));\n",
    "mod = lm(fmla,data=data2)\n",
    "summary(mod)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>Df</th><th scope=col>Sum Sq</th><th scope=col>Mean Sq</th><th scope=col>F value</th><th scope=col>Pr(&gt;F)</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Age</th><td>  1    </td><td>  0.4  </td><td>  0.40 </td><td>  0.61 </td><td>4.4e-01</td></tr>\n",
       "\t<tr><th scope=row>Gender</th><td>  1    </td><td> 13.0  </td><td> 13.04 </td><td> 19.76 </td><td>1.0e-05</td></tr>\n",
       "\t<tr><th scope=row>EnergyC</th><td>  1    </td><td>138.8  </td><td>138.83 </td><td>210.40 </td><td>5.6e-41</td></tr>\n",
       "\t<tr><th scope=row>Attitude</th><td>  1    </td><td>138.4  </td><td>138.40 </td><td>209.76 </td><td>7.1e-41</td></tr>\n",
       "\t<tr><th scope=row>SubNorm</th><td>  1    </td><td> 27.3  </td><td> 27.26 </td><td> 41.32 </td><td>2.7e-10</td></tr>\n",
       "\t<tr><th scope=row>PBC</th><td>  1    </td><td> 44.4  </td><td> 44.39 </td><td> 67.28 </td><td>1.5e-15</td></tr>\n",
       "\t<tr><th scope=row>HabitC</th><td>  1    </td><td> 16.9  </td><td> 16.89 </td><td> 25.59 </td><td>5.6e-07</td></tr>\n",
       "\t<tr><th scope=row>ComfNS</th><td>  1    </td><td>  4.3  </td><td>  4.27 </td><td>  6.46 </td><td>1.1e-02</td></tr>\n",
       "\t<tr><th scope=row>Residuals</th><td>588    </td><td>388.0  </td><td>  0.66 </td><td>    NA </td><td>     NA</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllll}\n",
       "  & Df & Sum Sq & Mean Sq & F value & Pr(>F)\\\\\n",
       "\\hline\n",
       "\tAge &   1     &   0.4   &   0.40  &   0.61  & 4.4e-01\\\\\n",
       "\tGender &   1     &  13.0   &  13.04  &  19.76  & 1.0e-05\\\\\n",
       "\tEnergyC &   1     & 138.8   & 138.83  & 210.40  & 5.6e-41\\\\\n",
       "\tAttitude &   1     & 138.4   & 138.40  & 209.76  & 7.1e-41\\\\\n",
       "\tSubNorm &   1     &  27.3   &  27.26  &  41.32  & 2.7e-10\\\\\n",
       "\tPBC &   1     &  44.4   &  44.39  &  67.28  & 1.5e-15\\\\\n",
       "\tHabitC &   1     &  16.9   &  16.89  &  25.59  & 5.6e-07\\\\\n",
       "\tComfNS &   1     &   4.3   &   4.27  &   6.46  & 1.1e-02\\\\\n",
       "\tResiduals & 588     & 388.0   &   0.66  &     NA  &      NA\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "          Df  Sum Sq Mean Sq F value Pr(>F) \n",
       "Age         1   0.4    0.40    0.61  4.4e-01\n",
       "Gender      1  13.0   13.04   19.76  1.0e-05\n",
       "EnergyC     1 138.8  138.83  210.40  5.6e-41\n",
       "Attitude    1 138.4  138.40  209.76  7.1e-41\n",
       "SubNorm     1  27.3   27.26   41.32  2.7e-10\n",
       "PBC         1  44.4   44.39   67.28  1.5e-15\n",
       "HabitC      1  16.9   16.89   25.59  5.6e-07\n",
       "ComfNS      1   4.3    4.27    6.46  1.1e-02\n",
       "Residuals 588 388.0    0.66      NA       NA"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "anova(mod)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "lm(formula = fmla, data = data2)\n",
       "\n",
       "Residuals:\n",
       "    Min      1Q  Median      3Q     Max \n",
       "-2.6717 -0.4323  0.0774  0.5373  1.9727 \n",
       "\n",
       "Coefficients:\n",
       "            Estimate Std. Error t value Pr(>|t|)    \n",
       "(Intercept)  0.26479    0.34485    0.77  0.44289    \n",
       "Age         -0.00401    0.00323   -1.24  0.21428    \n",
       "Gender      -0.02885    0.06872   -0.42  0.67473    \n",
       "OwnRent     -0.00151    0.07666   -0.02  0.98430    \n",
       "SqftCate    -0.04330    0.03528   -1.23  0.22024    \n",
       "Income      -0.00792    0.01886   -0.42  0.67473    \n",
       "Educ         0.01655    0.03164    0.52  0.60107    \n",
       "EnergyC      0.07803    0.02956    2.64  0.00853 ** \n",
       "MC           0.12794    0.03401    3.76  0.00019 ***\n",
       "Attitude     0.37667    0.03913    9.63  < 2e-16 ***\n",
       "SubNorm      0.12110    0.02728    4.44  1.1e-05 ***\n",
       "PBC          0.24829    0.03738    6.64  7.1e-11 ***\n",
       "HabitC       0.10232    0.02483    4.12  4.3e-05 ***\n",
       "ComfNS      -0.03901    0.02434   -1.60  0.10949    \n",
       "IncHomeS    -0.05721    0.01941   -2.95  0.00333 ** \n",
       "---\n",
       "Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n",
       "\n",
       "Residual standard error: 0.8 on 582 degrees of freedom\n",
       "Multiple R-squared:  0.518,\tAdjusted R-squared:  0.507 \n",
       "F-statistic: 44.7 on 14 and 582 DF,  p-value: <2e-16\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#added CashYN to model\n",
    "IndepPred = c(\"Age\",\"Gender\",\"OwnRent\",\"SqftCate\",\"Income\",\"Educ\",\"EnergyC\",\"MC\",\"Attitude\",\"SubNorm\",\"PBC\",\"HabitC\",\"ComfNS\",\"IncHomeS\")\n",
    "fmla <- as.formula(paste(\"INT\",paste(IndepPred,collapse=\"+\"),sep=\"~\"));\n",
    "mod = lm(fmla,data=data2)\n",
    "summary(mod)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>Df</th><th scope=col>Sum Sq</th><th scope=col>Mean Sq</th><th scope=col>F value</th><th scope=col>Pr(&gt;F)</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Age</th><td>  1    </td><td>  0.40 </td><td>  0.40 </td><td>  0.63 </td><td>4.3e-01</td></tr>\n",
       "\t<tr><th scope=row>Gender</th><td>  1    </td><td> 13.04 </td><td> 13.04 </td><td> 20.42 </td><td>7.5e-06</td></tr>\n",
       "\t<tr><th scope=row>OwnRent</th><td>  1    </td><td>  0.68 </td><td>  0.68 </td><td>  1.06 </td><td>3.0e-01</td></tr>\n",
       "\t<tr><th scope=row>SqftCate</th><td>  1    </td><td>  5.03 </td><td>  5.03 </td><td>  7.88 </td><td>5.2e-03</td></tr>\n",
       "\t<tr><th scope=row>Income</th><td>  1    </td><td>  0.31 </td><td>  0.31 </td><td>  0.48 </td><td>4.9e-01</td></tr>\n",
       "\t<tr><th scope=row>Educ</th><td>  1    </td><td>  6.69 </td><td>  6.69 </td><td> 10.48 </td><td>1.3e-03</td></tr>\n",
       "\t<tr><th scope=row>EnergyC</th><td>  1    </td><td>130.13 </td><td>130.13 </td><td>203.81 </td><td>7.3e-40</td></tr>\n",
       "\t<tr><th scope=row>MC</th><td>  1    </td><td> 67.19 </td><td> 67.19 </td><td>105.24 </td><td>8.2e-23</td></tr>\n",
       "\t<tr><th scope=row>Attitude</th><td>  1    </td><td> 98.31 </td><td> 98.31 </td><td>153.98 </td><td>1.5e-31</td></tr>\n",
       "\t<tr><th scope=row>SubNorm</th><td>  1    </td><td> 20.70 </td><td> 20.70 </td><td> 32.42 </td><td>2.0e-08</td></tr>\n",
       "\t<tr><th scope=row>PBC</th><td>  1    </td><td> 32.96 </td><td> 32.96 </td><td> 51.62 </td><td>2.1e-12</td></tr>\n",
       "\t<tr><th scope=row>HabitC</th><td>  1    </td><td> 14.96 </td><td> 14.96 </td><td> 23.43 </td><td>1.7e-06</td></tr>\n",
       "\t<tr><th scope=row>ComfNS</th><td>  1    </td><td>  3.93 </td><td>  3.93 </td><td>  6.16 </td><td>1.3e-02</td></tr>\n",
       "\t<tr><th scope=row>IncHomeS</th><td>  1    </td><td>  5.55 </td><td>  5.55 </td><td>  8.69 </td><td>3.3e-03</td></tr>\n",
       "\t<tr><th scope=row>Residuals</th><td>582    </td><td>371.58 </td><td>  0.64 </td><td>    NA </td><td>     NA</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllll}\n",
       "  & Df & Sum Sq & Mean Sq & F value & Pr(>F)\\\\\n",
       "\\hline\n",
       "\tAge &   1     &   0.40  &   0.40  &   0.63  & 4.3e-01\\\\\n",
       "\tGender &   1     &  13.04  &  13.04  &  20.42  & 7.5e-06\\\\\n",
       "\tOwnRent &   1     &   0.68  &   0.68  &   1.06  & 3.0e-01\\\\\n",
       "\tSqftCate &   1     &   5.03  &   5.03  &   7.88  & 5.2e-03\\\\\n",
       "\tIncome &   1     &   0.31  &   0.31  &   0.48  & 4.9e-01\\\\\n",
       "\tEduc &   1     &   6.69  &   6.69  &  10.48  & 1.3e-03\\\\\n",
       "\tEnergyC &   1     & 130.13  & 130.13  & 203.81  & 7.3e-40\\\\\n",
       "\tMC &   1     &  67.19  &  67.19  & 105.24  & 8.2e-23\\\\\n",
       "\tAttitude &   1     &  98.31  &  98.31  & 153.98  & 1.5e-31\\\\\n",
       "\tSubNorm &   1     &  20.70  &  20.70  &  32.42  & 2.0e-08\\\\\n",
       "\tPBC &   1     &  32.96  &  32.96  &  51.62  & 2.1e-12\\\\\n",
       "\tHabitC &   1     &  14.96  &  14.96  &  23.43  & 1.7e-06\\\\\n",
       "\tComfNS &   1     &   3.93  &   3.93  &   6.16  & 1.3e-02\\\\\n",
       "\tIncHomeS &   1     &   5.55  &   5.55  &   8.69  & 3.3e-03\\\\\n",
       "\tResiduals & 582     & 371.58  &   0.64  &     NA  &      NA\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "          Df  Sum Sq Mean Sq F value Pr(>F) \n",
       "Age         1   0.40   0.40    0.63  4.3e-01\n",
       "Gender      1  13.04  13.04   20.42  7.5e-06\n",
       "OwnRent     1   0.68   0.68    1.06  3.0e-01\n",
       "SqftCate    1   5.03   5.03    7.88  5.2e-03\n",
       "Income      1   0.31   0.31    0.48  4.9e-01\n",
       "Educ        1   6.69   6.69   10.48  1.3e-03\n",
       "EnergyC     1 130.13 130.13  203.81  7.3e-40\n",
       "MC          1  67.19  67.19  105.24  8.2e-23\n",
       "Attitude    1  98.31  98.31  153.98  1.5e-31\n",
       "SubNorm     1  20.70  20.70   32.42  2.0e-08\n",
       "PBC         1  32.96  32.96   51.62  2.1e-12\n",
       "HabitC      1  14.96  14.96   23.43  1.7e-06\n",
       "ComfNS      1   3.93   3.93    6.16  1.3e-02\n",
       "IncHomeS    1   5.55   5.55    8.69  3.3e-03\n",
       "Residuals 582 371.58   0.64      NA       NA"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "anova(mod)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "lm(formula = fmla, data = data2)\n",
       "\n",
       "Residuals:\n",
       "    Min      1Q  Median      3Q     Max \n",
       "-2.6187 -0.4645  0.0651  0.5435  2.3347 \n",
       "\n",
       "Coefficients:\n",
       "            Estimate Std. Error t value Pr(>|t|)    \n",
       "(Intercept)  -0.3438     0.2576   -1.33   0.1825    \n",
       "EnergyC       0.0974     0.0298    3.27   0.0011 ** \n",
       "Attitude      0.4101     0.0385   10.64  < 2e-16 ***\n",
       "SubNorm       0.1298     0.0276    4.70  3.3e-06 ***\n",
       "PBC           0.2785     0.0370    7.52  2.0e-13 ***\n",
       "HabitC        0.1213     0.0248    4.90  1.2e-06 ***\n",
       "---\n",
       "Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n",
       "\n",
       "Residual standard error: 0.82 on 591 degrees of freedom\n",
       "Multiple R-squared:  0.487,\tAdjusted R-squared:  0.482 \n",
       "F-statistic:  112 on 5 and 591 DF,  p-value: <2e-16\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>Df</th><th scope=col>Sum Sq</th><th scope=col>Mean Sq</th><th scope=col>F value</th><th scope=col>Pr(&gt;F)</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>EnergyC</th><td>  1    </td><td>151    </td><td>151.07 </td><td>225    </td><td>2.1e-43</td></tr>\n",
       "\t<tr><th scope=row>Attitude</th><td>  1    </td><td>137    </td><td>136.54 </td><td>204    </td><td>6.1e-40</td></tr>\n",
       "\t<tr><th scope=row>SubNorm</th><td>  1    </td><td> 27    </td><td> 27.35 </td><td> 41    </td><td>3.4e-10</td></tr>\n",
       "\t<tr><th scope=row>PBC</th><td>  1    </td><td> 44    </td><td> 44.47 </td><td> 66    </td><td>2.2e-15</td></tr>\n",
       "\t<tr><th scope=row>HabitC</th><td>  1    </td><td> 16    </td><td> 16.08 </td><td> 24    </td><td>1.2e-06</td></tr>\n",
       "\t<tr><th scope=row>Residuals</th><td>591    </td><td>396    </td><td>  0.67 </td><td> NA    </td><td>     NA</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllll}\n",
       "  & Df & Sum Sq & Mean Sq & F value & Pr(>F)\\\\\n",
       "\\hline\n",
       "\tEnergyC &   1     & 151     & 151.07  & 225     & 2.1e-43\\\\\n",
       "\tAttitude &   1     & 137     & 136.54  & 204     & 6.1e-40\\\\\n",
       "\tSubNorm &   1     &  27     &  27.35  &  41     & 3.4e-10\\\\\n",
       "\tPBC &   1     &  44     &  44.47  &  66     & 2.2e-15\\\\\n",
       "\tHabitC &   1     &  16     &  16.08  &  24     & 1.2e-06\\\\\n",
       "\tResiduals & 591     & 396     &   0.67  &  NA     &      NA\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "          Df  Sum Sq Mean Sq F value Pr(>F) \n",
       "EnergyC     1 151    151.07  225     2.1e-43\n",
       "Attitude    1 137    136.54  204     6.1e-40\n",
       "SubNorm     1  27     27.35   41     3.4e-10\n",
       "PBC         1  44     44.47   66     2.2e-15\n",
       "HabitC      1  16     16.08   24     1.2e-06\n",
       "Residuals 591 396      0.67   NA          NA"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#nudge factor model\n",
    "non_econ = c(\"EnergyC\",\"Attitude\",\"SubNorm\",\"PBC\",\"HabitC\")\n",
    "fmla <- as.formula(paste(\"INT\",paste(non_econ,collapse=\"+\"),sep=\"~\"));\n",
    "mod = lm(fmla,data=data2)\n",
    "summary(mod)\n",
    "anova(mod)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "lm(formula = fmla, data = data2)\n",
       "\n",
       "Residuals:\n",
       "    Min      1Q  Median      3Q     Max \n",
       "-2.4946 -0.4600  0.0517  0.5334  2.3491 \n",
       "\n",
       "Coefficients:\n",
       "            Estimate Std. Error t value Pr(>|t|)    \n",
       "(Intercept)   0.0746     0.2968    0.25   0.8017    \n",
       "EnergyC       0.0911     0.0297    3.07   0.0023 ** \n",
       "Attitude      0.4034     0.0384   10.51  < 2e-16 ***\n",
       "SubNorm       0.1295     0.0275    4.72  3.0e-06 ***\n",
       "PBC           0.2877     0.0370    7.78  3.2e-14 ***\n",
       "HabitC        0.1097     0.0250    4.40  1.3e-05 ***\n",
       "ComfNS       -0.0658     0.0236   -2.79   0.0055 ** \n",
       "---\n",
       "Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n",
       "\n",
       "Residual standard error: 0.81 on 590 degrees of freedom\n",
       "Multiple R-squared:  0.493,\tAdjusted R-squared:  0.488 \n",
       "F-statistic: 95.8 on 6 and 590 DF,  p-value: <2e-16\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>Df</th><th scope=col>Sum Sq</th><th scope=col>Mean Sq</th><th scope=col>F value</th><th scope=col>Pr(&gt;F)</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>EnergyC</th><td>  1    </td><td>151.1  </td><td>151.07 </td><td>228.1  </td><td>8.3e-44</td></tr>\n",
       "\t<tr><th scope=row>Attitude</th><td>  1    </td><td>136.5  </td><td>136.54 </td><td>206.1  </td><td>2.6e-40</td></tr>\n",
       "\t<tr><th scope=row>SubNorm</th><td>  1    </td><td> 27.3  </td><td> 27.35 </td><td> 41.3  </td><td>2.7e-10</td></tr>\n",
       "\t<tr><th scope=row>PBC</th><td>  1    </td><td> 44.5  </td><td> 44.47 </td><td> 67.1  </td><td>1.6e-15</td></tr>\n",
       "\t<tr><th scope=row>HabitC</th><td>  1    </td><td> 16.1  </td><td> 16.08 </td><td> 24.3  </td><td>1.1e-06</td></tr>\n",
       "\t<tr><th scope=row>ComfNS</th><td>  1    </td><td>  5.1  </td><td>  5.15 </td><td>  7.8  </td><td>5.5e-03</td></tr>\n",
       "\t<tr><th scope=row>Residuals</th><td>590    </td><td>390.8  </td><td>  0.66 </td><td>   NA  </td><td>     NA</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllll}\n",
       "  & Df & Sum Sq & Mean Sq & F value & Pr(>F)\\\\\n",
       "\\hline\n",
       "\tEnergyC &   1     & 151.1   & 151.07  & 228.1   & 8.3e-44\\\\\n",
       "\tAttitude &   1     & 136.5   & 136.54  & 206.1   & 2.6e-40\\\\\n",
       "\tSubNorm &   1     &  27.3   &  27.35  &  41.3   & 2.7e-10\\\\\n",
       "\tPBC &   1     &  44.5   &  44.47  &  67.1   & 1.6e-15\\\\\n",
       "\tHabitC &   1     &  16.1   &  16.08  &  24.3   & 1.1e-06\\\\\n",
       "\tComfNS &   1     &   5.1   &   5.15  &   7.8   & 5.5e-03\\\\\n",
       "\tResiduals & 590     & 390.8   &   0.66  &    NA   &      NA\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "          Df  Sum Sq Mean Sq F value Pr(>F) \n",
       "EnergyC     1 151.1  151.07  228.1   8.3e-44\n",
       "Attitude    1 136.5  136.54  206.1   2.6e-40\n",
       "SubNorm     1  27.3   27.35   41.3   2.7e-10\n",
       "PBC         1  44.5   44.47   67.1   1.6e-15\n",
       "HabitC      1  16.1   16.08   24.3   1.1e-06\n",
       "ComfNS      1   5.1    5.15    7.8   5.5e-03\n",
       "Residuals 590 390.8    0.66     NA        NA"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#nudge factor model (with comfort needs)\n",
    "non_econ = c(\"EnergyC\",\"Attitude\",\"SubNorm\",\"PBC\",\"HabitC\",\"ComfNS\")\n",
    "fmla <- as.formula(paste(\"INT\",paste(non_econ,collapse=\"+\"),sep=\"~\"));\n",
    "mod = lm(fmla,data=data2)\n",
    "summary(mod)\n",
    "anova(mod)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "lm(formula = fmla, data = data2)\n",
       "\n",
       "Residuals:\n",
       "   Min     1Q Median     3Q    Max \n",
       "-4.159 -0.737  0.178  0.823  1.952 \n",
       "\n",
       "Coefficients:\n",
       "            Estimate Std. Error t value Pr(>|t|)    \n",
       "(Intercept)  4.96514    0.20205   24.57   <2e-16 ***\n",
       "Age         -0.00369    0.00415   -0.89   0.3736    \n",
       "Gender       0.29697    0.09291    3.20   0.0015 ** \n",
       "---\n",
       "Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n",
       "\n",
       "Residual standard error: 1.1 on 594 degrees of freedom\n",
       "Multiple R-squared:  0.0174,\tAdjusted R-squared:  0.0141 \n",
       "F-statistic: 5.27 on 2 and 594 DF,  p-value: 0.00541\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>Df</th><th scope=col>Sum Sq</th><th scope=col>Mean Sq</th><th scope=col>F value</th><th scope=col>Pr(&gt;F)</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Age</th><td>  1   </td><td>  0.4 </td><td> 0.4  </td><td> 0.31 </td><td>0.5755</td></tr>\n",
       "\t<tr><th scope=row>Gender</th><td>  1   </td><td> 13.0 </td><td>13.0  </td><td>10.22 </td><td>0.0015</td></tr>\n",
       "\t<tr><th scope=row>Residuals</th><td>594   </td><td>758.0 </td><td> 1.3  </td><td>   NA </td><td>    NA</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllll}\n",
       "  & Df & Sum Sq & Mean Sq & F value & Pr(>F)\\\\\n",
       "\\hline\n",
       "\tAge &   1    &   0.4  &  0.4   &  0.31  & 0.5755\\\\\n",
       "\tGender &   1    &  13.0  & 13.0   & 10.22  & 0.0015\\\\\n",
       "\tResiduals & 594    & 758.0  &  1.3   &    NA  &     NA\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "          Df  Sum Sq Mean Sq F value Pr(>F)\n",
       "Age         1   0.4   0.4     0.31   0.5755\n",
       "Gender      1  13.0  13.0    10.22   0.0015\n",
       "Residuals 594 758.0   1.3       NA       NA"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#other model\n",
    "IndepPred = c(\"Age\",\"Gender\")\n",
    "fmla <- as.formula(paste(\"INT\",paste(IndepPred,collapse=\"+\"),sep=\"~\"));\n",
    "mod = lm(fmla,data=data2)\n",
    "summary(mod)\n",
    "anova(mod)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "lm(formula = fmla, data = data2)\n",
       "\n",
       "Residuals:\n",
       "   Min     1Q Median     3Q    Max \n",
       "-4.300 -0.695  0.089  0.794  2.200 \n",
       "\n",
       "Coefficients:\n",
       "            Estimate Std. Error t value Pr(>|t|)    \n",
       "(Intercept)  5.66410    0.24676   22.95  < 2e-16 ***\n",
       "Age         -0.00220    0.00409   -0.54  0.58980    \n",
       "Gender       0.30795    0.09128    3.37  0.00079 ***\n",
       "ComfNS      -0.14922    0.03131   -4.77  2.4e-06 ***\n",
       "---\n",
       "Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1\n",
       "\n",
       "Residual standard error: 1.1 on 593 degrees of freedom\n",
       "Multiple R-squared:  0.0537,\tAdjusted R-squared:  0.0489 \n",
       "F-statistic: 11.2 on 3 and 593 DF,  p-value: 3.65e-07\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<thead><tr><th></th><th scope=col>Df</th><th scope=col>Sum Sq</th><th scope=col>Mean Sq</th><th scope=col>F value</th><th scope=col>Pr(&gt;F)</th></tr></thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Age</th><td>  1    </td><td>  0.4  </td><td> 0.4   </td><td> 0.33  </td><td>5.7e-01</td></tr>\n",
       "\t<tr><th scope=row>Gender</th><td>  1    </td><td> 13.0  </td><td>13.0   </td><td>10.59  </td><td>1.2e-03</td></tr>\n",
       "\t<tr><th scope=row>ComfNS</th><td>  1    </td><td> 28.0  </td><td>28.0   </td><td>22.72  </td><td>2.4e-06</td></tr>\n",
       "\t<tr><th scope=row>Residuals</th><td>593    </td><td>730.0  </td><td> 1.2   </td><td>   NA  </td><td>     NA</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "\\begin{tabular}{r|lllll}\n",
       "  & Df & Sum Sq & Mean Sq & F value & Pr(>F)\\\\\n",
       "\\hline\n",
       "\tAge &   1     &   0.4   &  0.4    &  0.33   & 5.7e-01\\\\\n",
       "\tGender &   1     &  13.0   & 13.0    & 10.59   & 1.2e-03\\\\\n",
       "\tComfNS &   1     &  28.0   & 28.0    & 22.72   & 2.4e-06\\\\\n",
       "\tResiduals & 593     & 730.0   &  1.2    &    NA   &      NA\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "          Df  Sum Sq Mean Sq F value Pr(>F) \n",
       "Age         1   0.4   0.4     0.33   5.7e-01\n",
       "Gender      1  13.0  13.0    10.59   1.2e-03\n",
       "ComfNS      1  28.0  28.0    22.72   2.4e-06\n",
       "Residuals 593 730.0   1.2       NA        NA"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#other model (with comfort needs)\n",
    "IndepPred = c(\"Age\",\"Gender\",\"ComfNS\")\n",
    "fmla <- as.formula(paste(\"INT\",paste(IndepPred,collapse=\"+\"),sep=\"~\"));\n",
    "mod = lm(fmla,data=data2)\n",
    "summary(mod)\n",
    "anova(mod)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R",
   "language": "R",
   "name": "ir"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "3.4.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}