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@fonnesbeck
Created May 12, 2016 15:19
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{
"cells": [
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"%matplotlib inline\n",
"import numpy as np\n",
"import pandas as pd\n",
"import pymc3 as pm\n",
"import seaborn as sns\n",
"import matplotlib.pyplot as plt\n",
"import pdb\n",
"sns.set()"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Author</th>\n",
" <th>RefID</th>\n",
" <th>LMS Total</th>\n",
" <th>Pre-op</th>\n",
" <th>Initial Surgery</th>\n",
" <th>Morcellation</th>\n",
" <th>Power</th>\n",
" <th>Cancer Stage</th>\n",
" <th>Upstaged</th>\n",
" <th>Months follow-up</th>\n",
" <th>Outcome</th>\n",
" <th>Age</th>\n",
" <th>Menopausal Status</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Einstein</td>\n",
" <td>405.0</td>\n",
" <td>5.0</td>\n",
" <td>Benign</td>\n",
" <td>LSC SCC</td>\n",
" <td>Yes</td>\n",
" <td>Yes</td>\n",
" <td>I</td>\n",
" <td>No</td>\n",
" <td>30.0</td>\n",
" <td>NED</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Einstein</td>\n",
" <td>405.0</td>\n",
" <td>NaN</td>\n",
" <td>Benign</td>\n",
" <td>LMYOM</td>\n",
" <td>Yes</td>\n",
" <td>Yes</td>\n",
" <td>I to III</td>\n",
" <td>Yes</td>\n",
" <td>61.0</td>\n",
" <td>NED</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Einstein</td>\n",
" <td>405.0</td>\n",
" <td>NaN</td>\n",
" <td>Benign</td>\n",
" <td>SCH</td>\n",
" <td>Yes</td>\n",
" <td>No</td>\n",
" <td>I to III</td>\n",
" <td>Yes</td>\n",
" <td>31.0</td>\n",
" <td>AWD</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Einstein</td>\n",
" <td>405.0</td>\n",
" <td>NaN</td>\n",
" <td>Benign</td>\n",
" <td>SCH BSO</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>I</td>\n",
" <td>No</td>\n",
" <td>37.0</td>\n",
" <td>NED</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Einstein</td>\n",
" <td>405.0</td>\n",
" <td>NaN</td>\n",
" <td>Benign</td>\n",
" <td>SCH BSO</td>\n",
" <td>No</td>\n",
" <td>No</td>\n",
" <td>I to IV</td>\n",
" <td>Yes</td>\n",
" <td>6.0</td>\n",
" <td>AWD</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Author RefID LMS Total Pre-op Initial Surgery Morcellation Power \\\n",
"0 Einstein 405.0 5.0 Benign LSC SCC Yes Yes \n",
"1 Einstein 405.0 NaN Benign LMYOM Yes Yes \n",
"2 Einstein 405.0 NaN Benign SCH Yes No \n",
"3 Einstein 405.0 NaN Benign SCH BSO No No \n",
"4 Einstein 405.0 NaN Benign SCH BSO No No \n",
"\n",
" Cancer Stage Upstaged Months follow-up Outcome Age Menopausal Status \n",
"0 I No 30.0 NED NaN NaN \n",
"1 I to III Yes 61.0 NED NaN NaN \n",
"2 I to III Yes 31.0 AWD NaN NaN \n",
"3 I No 37.0 NED NaN NaN \n",
"4 I to IV Yes 6.0 AWD NaN NaN "
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"kq4_data = pd.read_excel('data/KQ4 Workbook.xlsx', sheetname='Sheet1', na_values=['NR', 'NA']).drop(['Notes'], axis=1)\n",
"kq4_data.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Some studies show event time truncated to the end of the followup period"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"True 127\n",
"False 70\n",
"Name: followup_event_time, dtype: int64"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"followup_event_time = ['Lin', 'Perri', 'Park']\n",
"kq4_data['followup_event_time'] = kq4_data.Author.isin(followup_event_time)\n",
"kq4_data.followup_event_time.value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"Author 0.00\n",
"RefID 0.48\n",
"LMS Total 0.91\n",
"Pre-op 0.19\n",
"Initial Surgery 0.01\n",
"Morcellation 0.01\n",
"Power 0.22\n",
"Cancer Stage 0.17\n",
"Upstaged 0.81\n",
"Months follow-up 0.14\n",
"Outcome 0.01\n",
"Age 0.27\n",
"Menopausal Status 0.46\n",
"followup_event_time 0.00\n",
"dtype: float64"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"kq4_data.isnull().mean().round(2)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"kq4_data = kq4_data.dropna(axis='rows', subset=['Months follow-up'])"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"Alive 78\n",
"Dead 51\n",
"NED 20\n",
"AWD 13\n",
"Died 8\n",
"Name: Outcome, dtype: int64"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"kq4_data.Outcome.value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"Benign 133\n",
"Name: Pre-op, dtype: int64"
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"kq4_data['Pre-op'].value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th>Power</th>\n",
" <th>No</th>\n",
" <th>Yes</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Morcellation</th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>No</th>\n",
" <td>76</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>Yes</th>\n",
" <td>22</td>\n",
" <td>30</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
"Power No Yes\n",
"Morcellation \n",
"No 76 0\n",
"Yes 22 30"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pd.crosstab(kq4_data.Morcellation, kq4_data.Power)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"TAH 73\n",
"LSC ASST VH 18\n",
"ABD MYOM 12\n",
"LSC SCH 11\n",
"LSC TVH 8\n",
"Varied 7\n",
"LSC MYOM 6\n",
"H'SCOPE MYO 6\n",
"LSC HYST 6\n",
"SCH 5\n",
"LMYOM 3\n",
"TAH UT INJ 2\n",
"VAG HYST 2\n",
"MIS HYST 2\n",
"SCH BSO 2\n",
"TVH 2\n",
"LAVH 2\n",
"TAH BSO 1\n",
"LSC SCC 1\n",
"Robotic TLH 1\n",
"Name: Initial Surgery, dtype: int64"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"kq4_data['Initial Surgery'].value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.text.Text at 0x115478ac8>"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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AABiAQAYAwAAEMgAABiCQAQAwAIEMAIABCGQAAAxAIAMAYAACGQAAAxDIAAAYgEAGAMAA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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x11535a1d0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"axes = kq4_data.Age.hist(bins=15)\n",
"axes.set_xlabel('Age')"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.text.Text at 0x1156c4550>"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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zAACGIc4AABiGOAMAYBjiDACAYYgzAACGIc4AABiGOAMAYBjiDACAYYgzAACGiQnnwX0+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\nAGAY4gwAgGGIMwAAhiHOAAAY5v8BCT75AdBLnIEAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x11562c6d8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"axes = kq4_data['Months follow-up'].hist()\n",
"axes.set_xlabel('Followup (months)')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Create death outcome column"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"0.0 111\n",
"1.0 59\n",
"Name: died, dtype: int64"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"kq4_data['died'] = kq4_data.Outcome.isin(['Dead', 'Died'])\n",
"kq4_data.loc[kq4_data.Outcome.isnull(), 'died'] = np.nan\n",
"kq4_data.died.value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"kq4_data = kq4_data.dropna(subset=['Morcellation', 'Power']).reset_index(drop=True)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"from lifelines import KaplanMeierFitter\n",
"kmf = KaplanMeierFitter()"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<lifelines.KaplanMeierFitter: fitted with 128 observations, 87 censored>"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"kmf.fit(kq4_data['Months follow-up'], event_observed=kq4_data.died)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x115b3c588>"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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+/fvRp08fmEwNB+/Xrx+Ki4tli7An/RI7uP9fZTND3a5dq47jC4fUDZdT+nSPkdmz5Vra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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x115a61d68>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"time = kq4_data['Months follow-up']\n",
"event = event_observed=kq4_data.died\n",
"ix0 = kq4_data.Morcellation=='No'\n",
"ix1 = (kq4_data.Morcellation=='Yes') & (kq4_data.Power=='No')\n",
"ix2 = (kq4_data.Morcellation=='Yes') & (kq4_data.Power=='Yes')\n",
"\n",
"\n",
"\n",
"kmf.fit(time[ix0], event[ix0], label='no morcellation')\n",
"ax = kmf.plot()\n",
"\n",
"kmf.fit(time[ix1], event[ix1], label='non-power morcellation')\n",
"kmf.plot(ax=ax)\n",
"\n",
"kmf.fit(time[ix2], event[ix2], label='power morcellation')\n",
"kmf.plot(ax=ax)"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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p3+F/exZuzUJEqcxgMECrPTnDRiaTweVyeRJhAMAHH3yAkSNHorg4\nebYDG5E1GPvtvttlxVOn04L9rhZUKkd5EhNFY+lLb5bCIVAeOpnpUiYR4XAFHgjwyt3A/AxElMbS\nIgAlX0U6K450Zns+d1lFNLQ7MKUkYVXqH4cdqN/Rp1v1fo6ZLHZ0tvXj7XUMkzokHbY1faVLe3NU\n0J93bqJrEVcajQZGo9HzuXfwCQAbN27EjTfeGHaZer0WWpMKOpW63/WzZisg0fgOeF6sqcDFSGzS\nmme+fw+Aey3oiBN1PHC4AypFdH8lcv74TBh/fKbXMbPDjNKcYX6vf/zjdgDAgso8mF/+KwBApfE/\n1TYQUSJAp/P9/vk7Fg020ZZ0a7CTrT6xxLamr3RvLwPQNDW+wIT/GT7I87nnm1AfJoMnGZGXZJr+\noxsQ1eJEqQ2y3NzQFwYg16khE+RRrFHyYlvTV7q0Vx6jX66T2YQJE7BlyxZcfPHFqKurw8iRI32u\nqa+vx/jx48Mus7W1C12d5r4nI+rJaAWk0X2jGE0ul+hJRAQAVosdQq9tDmLB6rTBIPGfrM91Iiek\nwWCF4Dr590iYzDafhEMxTULUaQaSKFlKuiRvCQfbmr7Spb1MQpRiuqcEdYvF1CCP4jL3NJ/eOP2H\niChpTZs2DVu3bsWsWe4N4qurq1FbWwuz2Yyqqiq0t7d7TdGlzGB3idjb1O51TJ1thMkYOJD1lzmX\niCiWGIDG0HGnGR9bGiJOdNC9V1m3WGbFFSdO9htk+n0jSkRESUEQBCxdutTrWGlpqefveXl5ePPN\nN+NdrZMiTeoXDBP+hc1fdlyNWu55o+oPM+cSUbwxAI2REVmDscPWhP32lrhk2iMiIkoakSb1CyYO\nCf96zzyKRExnKRERpaGQAWiwza4B4IsvvsCjjz4KwL332GOPPQa5PPXXFIUlyAhvJYbga6EFoij6\nvybGI7pOOHHY1Hjys+sUAPA6FkyB6AAANId5PQAoXHJYLakxkmqxOSFpbw99YQBqqxwmY2q0tZtC\nKkdJblGiq0FElHR6zzyKRDRnKXVaRWxpsmBq1EqMLZfdhs7P/pvoapyULonVwsG2pq90aW+QBIEh\nA9Bgm10DwOLFi/H000+jsLAQr7/+Opqbm1FSUhK1ukdL771C+7TZdm8hRniFvbshulxA+VjfkzEe\n0VVLNd51EQQYbQI27g2vzTfY3dkUw72++xmiGHiaT6yV6Bw4a6g9rGvtsKOtvW+j3QCgMDlgtfT9\n/nBlyST9+sWoJ6MtNkkoiIio/0blybDtOzsa2h3uADQFEgTK8/3lmU+cdEmsFg62NX2lS3uDJQgM\nGYAG2+y6sbEROp0OL7zwAvbv348LLrggKYNPwHev0Hhstp1MSnQONHWk74xro01AU4cs7AC0v9Ol\nVApZXDIm9nVKGBERJZ/es5N6GjEQ+LLtFDhdQFdBPtRHHMCJ2UjdpGYLnE0NaB5TEPYzQ81O6u+M\noGTC2UlEqSFkRBJss+tjx46hrq4ODz30EAoLCzF37lyMHTsWZ599dkwrTZE7a6g97OAMALKb3G8y\nq8aGPwVApZLDnKBkBq/VqxLyXCIionD1np3UmyAIAADz+Akw+9lBJ792EwQACmn4fZ5KJgek0oDn\nRakT2fL02MooW6GEYLeEvjCJcHYSZaKQAWiwza51Oh2Kioo8mfcqKytRX18fMgBNhs1Vo7XZdigS\nicTvBtCBNun2R6G0RH2D7FAEQYBgMkH/9jueY/aSQljPDL6nnEqVmCkD3Z12PJ8fj2eJEgeyw/zv\nJGRZVkefNyOP1SbmySiT2gpkXnuJiIgosUJGNcE2uy4sLITJZMKhQ4dQWFiI7du346qrrgr50GTY\nXDVqm22H4HK5/G8AHcEm3fHaILsn6dACKA8dAU6s6ZSYzZA1fouO8vKA9yTyDagoukd34/X8eLXV\nanN6bZbeHyab7wbl4YjlJubJJpPaCqRPexlER0/vfAm9RSV/QqQi3dIlztu2BMugmwoZch1OV0y3\ne4uVaOZIIKL4ChmAhtrsetmyZViwYAEAYPz48Tj//PNjW2OKC0PFOBgqxnk+59duSmBtiIgoHnrn\nS+gtIfkTIt3SJQ7btvQULAhKhcAu2QPkQJgjgSh1hQxAQ212ffbZZ+O1116Lfs3II9VHV4mIKLq4\nRVr/GEQr1nR9GPD8iKzB3MObiChG0jctapLoshnw8ZFPUTlkkveJCKYUFcgByN1rHHtPLUqF0VUi\nIoqudNkiLRFGK4fgS9PhgOcNohX77S0JC0CNNiFgYr0b7O7fBbYdzooosSARUTJhABpDp+lH4NND\n27G/4xvfADTSKUXd4jy1iIiIkk+6bJGWCBfmluPH0rKA54O9GY21cLZM09hNOG/bW8iuc+dosBQO\n8VoyQ0SU7BiAxtBPh5+H+u8bEl2NjBFo1LhE5+BIMRGlFW6Rlp5CbZkmdRbA8E2z57PEbIby0BEG\noESUUjI2AFXJVGgzt8c/m18Kk5jNQZMRCYKA7BNZc6Mt1AhvoFFjo01AU4csZQPQaGYntDrNcHVG\nvtm4OtsIk9EalToku0xqK5D87VXIpRhWkJvoaiSlRG2RFq8tzPojnG3Ogm1vJTEKIa8JV7S3UXP+\n+Ey8JHOXN/tMBzSvb4SA0NuCJWqLtFgKtE1ZtLYuixdukRaeTGorkP7tzdgAtDx/dGKy+aUoS+EQ\n97YsCRDOCG+gUeNA62hSRTQTTAlOKbL78EuIRi2H4IrNwEKyyaS2AsnfXmOCtnVKBYnaIi1eW5j1\ni0sAmtsCnlZlK2AOMvDignvbM2OQMnwE2PolFtuo9dx2rHvQN9i2YIncIi2W/G1Tlq1RRm3rsnjh\nFmmhZVJbgfRpb7AgOmMDUIpM721Z/IlVJ8ctYIiIvHGLtCBC5FhQ6NQwB/vlbs8u9/+Xjw3/mczP\nQEQUNgagqaZX9lyl1QyH0QU4HHDkek9V4xYtRETpiVukpYbe26ixXyYiYgCaenqN7A7q/svOeiBH\n43WOW7QQEVE0qWQqdFo7vY7ZXA7mUwigID/b63O0+uXupHvd27J0LzfJpKR7/nIkKJQWWC2p1X7m\nZwgtk9oKJH97o5GfgQEoERERhaU8f7TPMeZTiK90TboXKX9vklUKWdTX3MYa8zOElkltBZK/vdHI\nz8AAlIiIiChF9Ey6l90kQmI2446mdTCeeBua3eT9i2siM9QTEfnDADQOumwGrNnzSoyfYge6BM+n\nEVmDUYSCGD+TiIiIEiXZM9QTEfnDADTGRuiGYX/HN3F9pkG0Yr+9hQHoCd1rZXrKpHUyRESUnnpm\nqO/u56rGmr2uYYZ6Iko2GR2A9k6mEItECpVDJqFyyKSolunXznpA605CtKbrQwDMvgf4XyuTaetk\niIgoxnplqPcIsD8oEVEmy+gAtHcyhZROpODV+bnXehTIRUB+clrukVYzJC7fUVDB4YAzt3/ZrJJV\nz7Uy3Xq/DSUiIuqXQHuPcn9QIiIfGR2AppWenV+ATbQ7m9qR7S9r3N59sawZERERwXdmUm+ZOFOJ\niDIPA1AiIqIUI4oilixZgoaGBsjlcixbtgyFhYWe82vXrsXrr7+OvDz3spLf//73KCkpSVBtqVvv\nfUF76+8+of5yHgiCAFGUBryHORGIKN4YgBIREaWYzZs3w2azoaamBrt27UJ1dTVWrVrlOb9nzx6s\nWLECp512WgJrmboMNmOUstf7ZqivVI6KQrm+Au0PGgxzIhBRIjAAJSIiSjHbt29HZWUlAKCiogL1\n9d5rDffs2YPnnnsOra2tuOCCC/CLX/wiZnXpndAvlFgk/IumWGWv785QH6sA1F/OAyB4FlzmRCCi\nRGAASkRElGIMBgO0Wq3ns0wmg8vlgkQiAQBcdtlluO6666DRaDBv3jx8+OGHOP/882NSl94J/UJJ\n9oR/Uc1e7ydDPRFRpmMASilBYjZHbc+xG+zu6VDZTWKfyxAEAdli3+9PBBEiBOHjiO8zSwQIrtRq\na19lUluB5G9vtijiO5kk5HW639wTh9okF41GA6PR6PncM/gEgBtvvBEajTvwOf/88/Hll1+GDED1\nem3Q89GiNamgU6nj8qxAdLr4PN+arYBEowQASIwn+p4Tn/1RKC1QKaL/q5lKJfd7XBCEoOeD6c+9\nsZRs9QnJ4YRGo+jTrX29LxVlUluB5G6vKBH6/TOUAWgPkU4jCsVmMEGOxHay6cBSOATKQ0eiWqYo\nAka7EPrCoPp7f2gyiQhF4NwRRJShJkyYgC1btuDiiy9GXV0dRo4c6TlnMBgwffp0bNq0CUqlEv/9\n739x1VVXhSyztbV/CXDC1dVphmBNXKZXnU6Njg5TfB7mEoDmNvdf4QIAGE989sd51ACr3P1DP1pb\npAWbgtudnCjQ+WC6B2H7cm+sBGtrsrI6bTBIrBHfp9EoYDBEfl8qyqS2AsnfXpPZFtbP0GBBKgPQ\nHiKdRhRKg2kf4Ihqkf2ikEthNPuuD5HanHBkBU4LHy5R4oA1SHr5vrKMKQfGlIe8Ltz09dsOZ0Wc\nqKE3d1bB2L45MtoEZMtFVI01R6U8q9OMoerSiO9TJfkPwmjKpLYCyd9eo9mGMSXJu1YwkaZNm4at\nW7di1qxZAIDq6mrU1tbCbDajqqoKCxYswOzZs6FQKDBp0iScd955Ca5xhgpji7Seem6Xxi3SiChd\nhfwtPFSq926LFy+GTqfDggULYlJR6r9hBQFGUi35gNnie9zuAAbowi4/W6OE0eCnnDgJN319oEQN\nkYjHKCuTQxBRIIIgYOnSpV7HSktPDjDNmDEDM2bMiHe1iIiIQgoZgIZK9Q4ANTU1+Oqrr/CjH/0o\nZhWlGOo5QtvTznr/x4mIiCjqFHIpOgxW6JJ4/RcRUX+FzO4QKtX7zp07sXv3bs80ICIiIiKK3LCC\nXGRJQyfeIiJKZSF/ygVK9Q4Ara2tWLlyJRYvXhzz9XBERERERESU2kJOwQ2W6v2dd95BR0cHbrvt\nNrS2tsJqtWLYsGH42c9+FrTMeKV6T7SGg/FL9d5T9/env8/umT4+XMHSy8darNLXBxLrVO9RT3HP\nVO9hyaS2Asnd3mikeiei4Iw2oU85B7q3NEtUvoISnaPf+RyIKDFC/rYeLNX77NmzMXv2bADAm2++\nicbGxpDBJxC/VO/JIG6p3nvofkPd72cbrYA0/FT5iU5CZLXYIZxoe6zFIwlRf9Lj+8NU76FlUluB\n5G9vNFK9U/KJ9pZnkRLNdhw1dyFfxQzLJTpHv7LCa+wm3LD/zSjWKDyiCAgCkF3nPfuOe3Snp0xq\nK5D87Y3GHt0hf+qESvVOyclgM2LNnlf6WYod6Ap/r0uJUYArgf9gHEoRQuy35gQASOwCXNLYttV5\nmrsxG0M8p0jMxxmuYTGtCxFRtER7y7NI6fVabOr8KKF1SBb9yQovdRZAPHQE2Yh/v9//fbyJKJFC\nBqChUr13u+KKK6JXK+qXEbph2N/xTf8LEgT3MGM3UQQkTI5ARESU6QwV42CoGJeQZ3dP++29T3Y8\nZidFG/foDi2T2gokf3ujsUd3/BbMUdxUDpmEyiGTol/wznpAqwl4OtFTcA+2dEEpl8blWXHZB/RL\ndwc7o1cHS0RE6c+lUEDSIwdHN8HhgDM3wL7eREQpgAFoDGVnqfBtxw9cZ0JERFEliiKWLFmChoYG\nyOVyLFu2DIWFhT7XLV68GDqdDgsWLEhALak/rMP8vxVT7d0X55oQEUUX51PG0PiCsZBLGOMTEVF0\nbd68GTabDTU1NbjnnntQXV3tc01NTQ2++uqrBNSO+kMhl8Jotgf8Y7M5YTAz+ysRpS5GR5Q2smQS\nWGxOn+MOpwsaVfjZfImIkt327dtRWVkJAKioqEB9fb3X+Z07d2L37t2YNWsWvvkmCjkBKG6GFYSY\nXntMg4Om5M2QSUQUCgNQShsF+dl+jx9syZxtf4goMxgMBmi1J/fUlslknn26W1tbsXLlSqxatQr/\n+te/ElhLIiIiXwxAiYiIUoxGo4GxR4Ka7uATAN555x10dHTgtttuQ2trK6xWK4YNGxZyn269Xhv0\nfDrR5qigU8V3/9ju709/9621ZiugcDmhUoT/K5xKJe/XM5ONcGLPNX/tSrm2OpzQaBR9urWv96Wi\nTGorkNztFSVCv3+OMQCl8KmUQKch4GmX0w4YY5Q22u4ABuhiUzYRUYqZMGECtmzZgosvvhh1dXUY\nOXKk59zs2bMxe/ZsAMCbb76JxsbGkMEnALS2ZsZsEb1ei65OMwRrfJdmuFwuAEBHh6l/BRmtsFpE\nCCfKCyUVtyYJRRTdGe97tysV22p12mCQRP67kybJt+qIpkxqK5D87TWZbWH9HAsWpDIApfCNHh70\ntEKnhrm/HWsgO+tDX0NElCGmTZuGrVu3YtasWQCA6upq1NbWwmw2o6qqKsG1o0AMNiPW7Hmln6XY\n4VC6t+oOh8QuwCVNrzWjztPcjd/Yq13J1NYiMR9nuIYluhpESYkBKBERUYoRBAFLly71OlZa6rtt\nxxVXXBGvKlEII3TDsL8jCgmhBAGC6ISAExGoKEKUcFMDIkodDECJiIiIYqxyyCRUDpkUlbK+aT4O\n64ms7zlffQVHtjsJn7+s76k4LTWU175UAQBmjDV7HU/HthKlIwagRERERCnEa6uWYxogRwOAWd+J\nKDVwzkaMqWQqtJnbE10NIiIiIiKihGMAGmPl+aMhl/BFMxERERERESMjSntZMgksJ9bKdPO3ToaI\niIiIiGKLASilvYL8bJ9jXCdDRESUuow2Aa/Vq7yOCYLg2SM0VYiiElJJ4D3WA5EIRrjE5NhyJtYy\nqa1AcrV3VJ4MU0qUUS+XASgRERFlFJVMhU5rZ8DzNpcD+aq8ONaIIlGic6Cpg7/CEqUq/uslIiKi\njFKePzro+c9bdsapJlGgUgKd7jdoMqMRErv3G0CJ0waJxR6TRwsOB5y5uaEvjLKzhtpx1lDfNqXi\nNixWpxlD1b57+Iai0ShgMFhjUKPkk0ltBTKjvQxAiYiIUowoiliyZAkaGhogl8uxbNkyFBYWes6/\n++67eP755yGRSDB9+nTccMMNCawtxdTo4Z6/dja1I7tXfgOpRgmzwRKTR6v27otJuUSU3hiAEhER\npZjNmzfDZrOhpqYGu3btQnV1NVatWgUAcLlcePzxx7Fu3TqoVCpceumlmDFjBnQ6XYJrTbGmkEth\nNHu/GRQlEpjMgd+A2p0u6DSKWFeNiMiDAWgchFprEgtcv0JElL62b9+OyspKAEBFRQXq6+s95yQS\nCTZt2gSJRIKjR49CFEVkZTHrdyYYVuA7HVanU6OjwxTwnr1N3KuciOKLAWgchFprEgsptX6FiIgi\nYjolJEYAACAASURBVDAYoNVqPZ9lMhlcLhckEvf23hKJBO+//z6WLl2KKVOmQK1WJ6qqREREXkIG\noKHWmdTW1uLFF1+ETCbDyJEjsWTJkljWlygq/O0NGglR4oC1H/eH9QwRMNl908z3vTymeg8lk9oK\nJFd7Y5XqPV1pNBoYjUbP557BZ7dp06Zh2rRpuO+++7B+/XpcccUVQcvU67VBz6eTUG3VmlTQqdIn\naNfpArdFnW2ERi3vU7lyZRZcqr7dGyuqJKtPSA4nNH2cAt3X+1JRJrUVSO72ihIh6M+UcIQMQIOt\nM7FarXjqqadQW1sLuVyOe+65B1u2bMGUKVP6VSmiWPO3N2gksjVKGGOU1KFbeRewpzk5ggMiSi4T\nJkzAli1bcPHFF6Ourg4jR470nDMYDLjjjjvwt7/9DXK5HCqVCoIghCyztTUz9kfW67Uh29rVaYZg\nTY9py6Gm4JqMVgguV5/KVlnscEmTJ+tsambBtcEgiTzjaSZkSu2WSW0Fkr+9JrMt6M+UbsGC1JAB\naLB1JnK5HDU1NZDL3aNNDocDCkXyRuxEqWTqCKBMa4BSHp1NtZnqPbRMaiuQee1NJ9OmTcPWrVsx\na9YsAEB1dTVqa2thNptRVVWFGTNm4Prrr0dWVhZGjRqFyy+/PME1JiIicgsZgAZbZyIIAvLy3Ilu\nXnrpJZjNZpxzzjmxqy0RERFBEAQsXbrU61hp6ckBpqqqKlRVVcW7WkRERCGFDEBDrTMRRRErVqzA\nwYMHsXLlyrAeynUmsZeo9Sv9nRMeiDVbAYkmudaHZcehPgqlBSpFlHKFcZ1JWDKprUBytzca60yI\niIgouYT8zTbYOhMAePDBB6FUKj3rQsPBdSaxl4j1K6HWmfSLSwCa22JTdh+oshUwG2M/ddF51ABr\nlKbgOpxWGEytEd+nzpbDZEytNTV9lUltBZK/vWaLHW1yR8jrcnKik6iLiIiIYi9kABpsnUl5eTnW\nrVuHiRMnYvbs2RAEATfccAN+8pOfxLzilGFGD090DbwodGqYYxVs99DZ1I5sVXQGEkwOA07Vlkd8\nn1ynhikObU0GmdRWIPnbazdYkVM+OOR1mTSrhoiIKNWFDEBDrTP58ssvo18rIiIiIiIiSjuS0JcQ\nERERERER9V+UspsQERERUapRyKUwmu19uldqc8KR5YxyjcLjcLqgidISFSKKLwagRERERBlqWEFu\n328+pgFyNNGrTAQOtmRGQkuidMQpuERERERERBQXfANKRERE1INKpkKntTPq5dpcDuSr8qJeLhFR\nKmEASkRElGJEUcSSJUvQ0NAAuVyOZcuWobCw0HO+trYWL774ImQyGUaOHIklS5YkrrIpqDx/dEzK\n/bxlZ0zKJSJKJZyCS0RElGI2b94Mm82Gmpoa3HPPPaiurvacs1qteOqpp/Dyyy/jH//4B7q6urBl\ny5YE1paIiOgkvgFNU7GaPhSMaLajy2qO6zMTJV5tNTuNEBzR+WeqkCijUg4RJd727dtRWVkJAKio\nqEB9fb3nnFwuR01NDeRyOQDA4XBAoVAkpJ5ERES9MQBNU7GaPhSMXq9Fa2tmZKWLV1udR1uQq+Ev\njkTkzWAwQKvVej7LZDK4XC5IJBIIgoC8PPc6w5deeglmsxnnnHNOoqpKRETkhQEoERFRitFoNDAa\njZ7P3cFnN1EUsWLFChw8eBArV64Mq0y9Xhv6ojSRqLZqTSroVOq4P1eni80zrdkKSDSJmV2jUFqg\nUvj+GqtSyRNQm35wOKHp40BzX+9LRZnUViC52ytKhH7/TGEASkRElGImTJiALVu24OKLL0ZdXR1G\njhzpdf7BBx+EUqnEqlWrwi6TM1hir6vTDMGaFddn6nRqdHSYYlO4SwCa22JTdgjOowZY5VKvYypl\nFswWe0Lq01cOpxUGU2vE96mz5TAZbTGoUfLJpLYCyd9es8WONrkj5HU5OaqA5xiAEhERpZhp06Zh\n69atmDVrFgCguroatbW1MJvNKC8vx7p16zBx4kTMnj0bgiDghhtuwE9+8pME15rSzujhCXt0Z1M7\nslXewbxUo4TZYElQjfrG5DDgVG15xPfJdWqYYjWwkGQyqa1A8rfXbrAip3xwyOuCzTRhAEpERJRi\nBEHA0qVLvY6VlpZ6/v7ll1/Gu0pERERh4TYsREREREREFBcMQImIiIiIiCguGIASERERERFRXDAA\nJSIiIiIiorhgAEpERERERERxwQCUiIiIiIiI4oIBKBEREREREcUFA1AiIiIiIiKKC1moC0RRxJIl\nS9DQ0AC5XI5ly5ahsLDQc/6DDz7AqlWrIJPJ8POf/xxVVVUxrTAREVGmC9U3A4DZbMacOXOwfPly\nlJaWJqimRLGhkEthNNu9jokSCUy9jiU7s9OB44I14vtcUgm6DJHfl4oyqa1A8rdXrQwZPoYUsoTN\nmzfDZrOhpqYGu3btQnV1NVatWgUAcDgceOSRR7Bu3TooFApcc801uPDCC5GXl9fvihGR+x/58QT/\nEEr2H4TRlEltBZK/vdHo5NJVsL4ZAOrr6/HQQw/h+++/T2AtqTeVTIVOa2dcnyma7eiymuP6zHjI\nHyCg96+x2hw5ujqdialQH6lkg1GePzji+/R6LVpbu2JQo+STSW0FMqO9IXv37du3o7KyEgBQUVGB\n+vp6z7kDBw6guLgYGo0GADBx4kRs27YNF110UYyqS5RZTi/LT3QVMuIHYbdMaiuQee1NJ8H6ZgCw\n2+1YtWoVFi5cmIjqUQDl+aPj/sxM+neeSW0lSmUhA1CDwQCtVnvyBpkMLpcLEonE51x2dja6uvgP\nn4iIKJaC9c0AMH78eADuqbpERETJJGQAqtFoYDQaPZ97dnAajQYGg8Fzzmg0IicnJ+RD9XptyGvS\nRSa1Fcis9rKt6SmT2gpkXnvTRbC+ua8y6b+FTGorkFntZVvTUya1Ff+fvTsPj6o8+wf+PbPPZCYZ\nIAEkZIGQsEoEROXFUNRStfLWao3igrZYCxaqdfshoICtEEWt1oVXaUUqtUVQFBtLVQp1QYsIBA1C\nQCBhDQZClplMZubMnN8fkxkyyWxJZp/v57q4dOZsz51l7jzPec79IPnjDZqtxo4di48//hgAUFFR\ngaKiIs+2goIC1NTUoKmpCTabDdu3b8cFF1wQudYSERFRwNxMREQUz4LeAZ0yZQq2bt2KadOmAQDK\nyspQXl4Oi8WC0tJSzJs3DzNmzIAkSSgtLUXfvn0j3mgiIqJUFiw3uwmCEKsmEhER+SRIfECEiIiI\niIiIoqBnD4wQERERERERhYgdUCIiIiIiIooKdkCJiIiIiIgoKoIWIQoXSZKwePFiVFVVQaVSYcmS\nJcjJyYnW5SNOFEXMnz8fx48fh91ux6xZszBkyBA8/PDDkMlkKCwsxKJFi2LdzLA6c+YMfvazn+G1\n116DXC5P6lhXrFiBzZs3w26345ZbbsH48eOTMl5RFDF37lwcP34cCoUCv//975Pye7t79248/fTT\nWL16NY4cOeIzvrVr1+LNN9+EUqnErFmzMHny5Ng2upvax7p37148/vjjkMvlUKlUWLZsGXr37p00\nsVLXMTcnx2dae8zNyRcvczNzcyLH6pMUJR9++KH08MMPS5IkSRUVFdLdd98drUtHxdtvvy0tXbpU\nkiRJamxslCZPnizNmjVL2r59uyRJkrRw4ULpo48+imUTw8put0uzZ8+WrrzySunQoUNJHeu2bduk\nWbNmSZIkSWazWXrhhReSNt5NmzZJv/3tbyVJkqStW7dKv/nNb5Iu1j/96U/S1KlTpZtuukmSJMln\nfHV1ddLUqVMlu90uNTc3S1OnTpVsNlssm90tHWO97bbbpH379kmSJElr1qyRnnjiiaSJlbqHuTnx\nP9PaY25OzniZm5mbEzVWf6I2BXfHjh0oKSkBABQXF6OysjJal46Kq6++Gvfeey8AwOFwQC6X49tv\nv8WFF14IAJg0aRK++OKLWDYxrJ588kncfPPN6Nu3LyRJSupYP/vsMxQVFeHXv/417r77bkyePDlp\n483Pz4fD4YAkSWhuboZCoUi6WPPy8vDSSy95Xu/Zs8crvs8//xxff/01xo0bB4VCAb1ej/z8fFRV\nVcWqyd3WMdZnn30WQ4cOBeAaUVepVEkTK3UPc3Pif6a1x9ycnPEyNzM3J2qs/kStA2oymWAwGDyv\nFQoFnE5ntC4fcVqtFjqdDiaTCffeey/uu+8+SO1WuElLS0Nzc3MMWxg+69evR58+fTBx4kRPjO2/\nl8kUKwCcPXsWlZWVeP7557F48WI8+OCDSRtvWloajh07hquuugoLFy7E9OnTk+7neMqUKZDL5Z7X\nHeMzmUwwm81en1c6nS4h4+4Ya2ZmJgBg586d+Nvf/oaf//znnT6bEzVW6h7m5sT/THNjbmZuTmTM\nzamVm6P2DKher4fZbPa8djqdkMmSqwbSyZMnMWfOHNx222245ppr8NRTT3m2mc1mpKenx7B14bN+\n/XoIgoCtW7eiqqoKc+fOxdmzZz3bkylWADAajSgoKIBCocCgQYOgVqtx6tQpz/ZkinfVqlUoKSnB\nfffdh1OnTmH69Omw2+2e7ckUq1v7zyF3fHq9HiaTqdP7yeCf//wnXnnlFaxYsQK9evVK6lgpOObm\n5Pl5Z25mbk4mzM3JGysQxTugY8eOxccffwwAqKioQFFRUbQuHRWnT5/GnXfeiYceegjXXXcdAGD4\n8OHYvn07AOCTTz7BuHHjYtnEsPnrX/+K1atXY/Xq1Rg2bBiWLVuGkpKSpIwVAMaNG4dPP/0UAHDq\n1ClYLBZccskl+PLLLwEkV7wZGRnQ6/UAAIPBAFEUMWLEiKSM1W3EiBGdfnbPP/987NixAzabDc3N\nzTh06BAKCwtj3NKe27BhA9544w2sXr0a2dnZAIDRo0cnZawUGubm5PlMY25mbk4mzM3JnZujdgd0\nypQp2Lp1K6ZNmwYAKCsri9alo+KVV15BU1MTli9fjpdeegmCIGDBggV4/PHHYbfbUVBQgKuuuirW\nzYyYuXPn4tFHH03KWCdPnoyvvvoKN9xwg6diZHZ2Nh555JGki/eOO+7A/Pnzceutt0IURTz44IMY\nOXJkUsbq5utnVxAETJ8+HbfccgskScL9998PlUoV66b2iNPpxNKlSzFgwADMnj0bgiDgoosuwpw5\nc5IuVgodc3Pyfaa1x9ycHPEyNzM3J0Os7QlS+0nWRERERERERBGSXA96EBERERERUdxiB5SIiIiI\niIiigh1QIiIiIiIiigp2QImIiIiIiCgq2AElIiIiIiKiqGAHlIiIiIiIiKKCHVCiMDKZTJg9ezbq\n6uowc+bMHp/vyy+/xPTp0wEAjzzyCPbs2dPjcxIREaUS5mai+KKIdQOIkklDQwP27duHrKwsvPLK\nK2E5pyAIAIDHH388LOcjIiJKJczNRPGFHVCiMFqyZAm+//57zJkzB99++y02b96MefPmQavVYseO\nHWhubsb8+fOxYcMGVFVV4YorrsDcuXPhdDqxbNkyfPnll3A6nbjuuutwxx13eJ17+vTpuOeeeyBJ\nEl555RVoNBocPHgQQ4cOxTPPPAOFQoF3330Xr7/+OiRJwsiRI7Fw4UKoVKoYfTWIiIhij7mZKL5w\nCi5RGD3yyCPo27cv5s+f7xkdBYC6ujps2LAB99xzD+bNm4ff/e53eOedd7B27VqYTCasXbsWgiBg\n/fr1WLt2LTZt2oQdO3b4vc6uXbuwaNEibNy4ESdOnMBnn32G7777DuvWrcOaNWvwzjvvoHfv3nj1\n1VejETYREVHcYm4mii8h3QHdvXs3nn76aaxevdrr/c2bN2P58uVQKBT42c9+htLS0og0kijRSJLk\n9XrSpEkAgAEDBqCoqAi9evUCABiNRjQ1NeHzzz9HVVUVvvjiCwCAxWLB/v37UVBQ4PP8RUVF6Nu3\nLwCgoKAADQ0NOH78OGpqanDTTTdBkiSIoogRI0ZEKkQiijHmZqKuYW4mig9BO6B//vOfsWHDBqSl\npXm9L4oinnjiCaxfvx5qtRo333wzrrjiCvTu3TtijSVKFO1HWAFAqVR6/l8ul3fa3+l04qGHHsIP\nf/hDAMDZs2eRlpaGiooKn+dvP3XHfS2Hw4Grr74aCxYsAOBKlA6Ho2eBEFFcYm4m6jrmZqL4EHQK\nbl5eHl566aVO7x88eBB5eXnQ6/VQKpUYN24ctm/fHpFGEiUKhUIBh8MBSZI6jbT64t7nkksuwZtv\nvglRFGE2m3HLLbdg9+7dXbr2RRddhE2bNqG+vh6SJGHRokVYtWpVd8IgojjH3EwUOuZmovgS9A7o\nlClTcPz48U7vm0wmGAwGz+u0tDQ0NzeHt3VECaZPnz4477zzMG/ePMhkwR+xdo+QTps2DTU1Nbju\nuuvgcDhwww03YPz48fjyyy877evPsGHDMHv2bNxxxx2QJAnDhw/Hr371q54FRERxibmZKHTMzUTx\nRZBCGAo6fvw4HnjgAaxZs8bzXlVVFZ555hmsWLECAFBWVoZx48bhRz/6UcBz/fPmGyHYtTDoVBAE\nQK3ynvJgPX0G6sw+uPBPL3cnHiIiopQQzty88eYbAQASAAGA3uKAWafAWzcMglrZeWpiV5yxNKCP\n1oiX/ndJj85DRETJIeRlWDr2UwsKClBTU4OmpiZoNBps374dd955Z9DzrLpmIForfgCtRsDg/r0w\ncVR/AIBOo8D5BZk4NPcBiBYrDpZ/1OlYmU4L/fnFoTY55rKyDKirS52R51SKl7Emp1SKFUieeLOy\nDMF3SlLhys1X/30t6uqa8dDyz1Hf3Iq7q9cDNgn9K8ejpK/TdS21FuKgoV7HuXN3II9+XoZW0RY3\nP2vJ8nMfqlSKl7Emp1SKFUieeAPl5pA7oO4pBuXl5bBYLCgtLcW8efMwY8YMSJKE0tJST+WvQJQK\nAVALsLRKOPK9CT/WqwEAdY0WbNtTi3S7AzLRAUVGRqdjbafr0LTtv6E2ucsSrYNLRESpLVy52W38\nsL747JuTAABJAg63KnFlpt61seEMUL3Ha/+mFht27NV16pgCoXVOiYgo9YTUAc3OzvZM8Zk6darn\n/cmTJ2Py5MlduqBGLcNlP9Djw0+a0dxiwwvv7nJd4zwZRo1QQC+JcEoiNledqzCmVMrR16gFZIAa\nKuRn5HbpmqESGxsjcl4iIqJwC2dudrvx8iHI66eH4YgSzS02NFslvLzT1LZV3Wn/ob31uExnA/Sd\nt7kHlm12B4SezeIlIqIkEvId0HDLz9bgyHEbAKCl1YmTJ4GLRushCALkVhsK/v2pZ1+nJEEQBCgK\n82EeNzxWTSYiIkoZensL7q552/P6YHo+vuh/oed1s1VCVb2Iy/zc5MzK0AIAnHUSnHYH1nz1H6/t\nKpUcuX31Po/VKrQYmTmsZwEQEVFcinoH1GQz4xPxfQzMycO1o8YAADZ80ICWVic2fNCAiapcDFMe\n9hpnlQkCZBYLxP2H8X1BPoZGaDkzp92Gpm3/5VRcIiJKbSMugLD7SxiEtoqhLSZc0HoExWMne3Z5\neafJdYd0H4B9OzudYmgGcNl5gFxtByQHco7Wem232RxIP+27A9oiWtCU0QCAj8cQESWbqHdA9ao0\nmGxmnGg9gvMzXB3Q3GyV527oR73G4fPMC1A6utXruMzyjRAA2O2RW7xXlZkFgFNxiYgotUk//AnQ\nfyCgTwcACOtf77TP0N4KVNWLcNXN9dZslVDVLOCyQj3gkAGSE860NK99WmV21LScK6KkVMgwINO1\nj2STeWpBMCcTESWXqHdAfzH2Rqz4co3Xe2NG6TBmlA6A626o2SJhXaXWsz3fKOLqtv+3d3g+tD2l\nTIVMZX+/11ar5Bg8oHNxIyIiIuqay/I1uCzf9zbP3dGdJmCkBF8ruei1Sq/XJosdNbWuyo9WhwXK\n1kbmbCKiJBSzZ0D9yc1W4Wi1Ge4RVbNNQHXDuWZm6ox+j7U6LEjTqvxubzBbsbe6PmhH1D0VNxhO\nCyIiIurMfXe02SpB44TPDmhH7TukTgdQ3XwY9no9hLONwIfVnfZXyZQYaMj2vGZOJiJKDHHXAR0z\nSof/kR/xTNVZV6mFySaD1QFobRZklm/0e6wECYLwqd/tvdz7SRJOKmSdtmuLhsE4+TLPVNxgOC2I\niKJh5coV6NMnE7m5eXj33bfx2GNLfe5ns9nw4Yf/xNSpP8XGjeVIT8/AxIklUW4tJa0Wk8+puMgr\ngDRuotdb7rujL+80wSZJaLHJsG6v1muffKOI8QPtPi+lk+vRKncgTaUD+ul87mO2tXgt2cacTETR\nxNzcfXHXAe0o3yii8nsV9unzUGypCcs5JQB20en1nmAxo+nbb3EyP/TRU8HcDLu+ttP7XPuMiCLF\nve6jL2fOnMY//rEBU6f+FFdfPdXvfkRdllcA1Bzs/H6LyfV+hw6o29DeClQKgmtR0Xbcs5v8dUCJ\niBIJc3PXxH0HdPxAO6obFPio14X4vN+4gCOmVocFA3WDgp7T54/I+tchAAGn8Ha+IDotyg0AZkkB\nFPwg9PMQEdZu/g7b930f1nOOH9YXN14+xO/2jRvL8cUXW9Ha2ooTJ47j7rtnYuLEK7B//z4899zT\nkMvlUKnUmDt3Afr27ed13Natn8BqteLMmTMoLZ2GTz/9GIcPH8Ts2b/FpZdOwocfbsS6dX+HSqXG\nwIE5eOih+fjoo3/h/fffgyRJuPPOmThx4jjeffdtOJ1OXHrpJMyY8Sts3rwJa9f+DXK5HKNHX4CZ\nM2f7bPvbb6/FJ59sQWtrKzIyjFi69Cm8/vprqKk5jFWr/gyn04k+fTJx7bXX48UXn8PXX1dAEARM\nmXIlbrhhGpYufQwGgw6HDx9Bff0ZLFiwCIWFQ8P69afkIY2b6LOT6fOOaDuX5WtQ4xDgkBz4ySiL\n5/32dR78ER1OzzOhvlgdFjib6j2vZY1nIR37FyS1FuIg/z/LhoxGNDe62sIBY6LAmJuZmyMhZh1Q\ni6MFH5za4HObYLBDajeSIIwSoHECogQcauyH8ciNVjMDM/bx+bbj+9P45uBpXJ5liHKDiKirzGYz\nnnnmeRw7dhQLFjyIiROvwLJlSzFv3kIUFAzBZ599jOef/wMef/xJr+NaWiz4wx9ewL///SHWrv07\nXnnlNezc+RXeeutNjB5djJUrV2DVqr9Do9HghReexYYN66HT6WAwpKOs7GmcPXsWy5YtxerVb0Kp\nVOKVV17CqVO1WLlyBV59dTXUajV+//uF2L59m892NzU14o9//D8AwP33/wb79n2LO+6YgcOHD+Ln\nP/8lVq5cAQD4/PPPUFt7AitWrIIoipg9+y6MHetay3HgwIH4zW8ewj/+8S42bHgHDz74cAS/0kTe\nzDahU8HB9gPMHYsUdSQ45N6Dxtq2P0RNTYBe7fsgAEaDBjKHaxZUo8najZYTUaQxNyd3bo5JBzRb\nk4vjrUfgdEqQyfzfsnZTySWo5ECLYIUz4xTWVfoeCXBKGgho8H5TECAXXNUPhvZW4LJ8TY/bH0y6\nToXGVjHi1yFKJjdePiTgiGikFBYWAQD69u0Hq9X1x+jp03UoKHC1pbh4LF5++aVOxxUVuT6H9HoD\n8vLyAQAGQzpsNitOnDiOQYMKoNFo2s4xBtu3b8OIESORm5sHADhx4jgKCgqgVLr+yJ45czb27t2D\nhoazeOiheyFJEiwWC06cOO6z3QqFEosWzYdWq8Xp099DFH1/5lRXH8bo0WPajlFgxIhROHz4MABg\n+PDhnti/+WZ3F75qlMx0GgUaTVYoW+2wCVYY0/x35gD4fza0TSlaXOeVztVwmOEAROe5/C9JgCAA\naRVSp+Nbc7JhKh7d6X0HHDjWcrjT+3KLBc3NaqhlGuSlFQRsus3hxLY93o/S8K4o0TnMzczNkRCT\nDujUoa7pqXur65HmY4RTu3dfp/XCAOAtbIcYoL8q8zH/WpIkQGhbk6xe9FsyHsC5JOqjoAIRJSdf\nz21kZWXh4MHvUFAwBLt27UBOTudZF4Ge9zjvvAGorj4Eq7UVarUGFRXnziGTuQqgZWcPRE1NDURR\nhEKhwCOPzMWcOfehX7/+ePbZlyCXy7FxYzkKC4fik0+2eJ3/4MHv8Omn/8GKFatgtbbizjunQ5Ik\nCIIAp9P7+fZBgwbh/fffw4033gxRFFFZuRs//vFUbNv2ecAYKHW5O19NJiMOnA2y9ra/Z0ODUMsB\ntfxcZ9NsFyBJrv+6KWQStDYLNEeP++yA6uR6n+eWyZ3QKfRoEU1B25GV0XkqMO+KEsUec3Nyi+kz\noGqVHGaLa7qN3eGEMcCUGeDcndD2z5EE434u9OWdQRKRO4kGKagQEtEO4dtd2HZyPzINXXimNAQs\nM08Uef/v/y3As88uAwDI5XI8/PCjXTo+I8OIGTN+hTlzZkIulyM7eyDuvvsebNr0gWcfo9GIW2+9\nHbNn3wWZTMDEiZPQv39/3HTTLZgz5y44HE6cd94AXH75lE7nHzgwB1qtDr/+9S8hSRL69MnC6dN1\nGDnyfIiiHS+//CLUatfn6YQJl2Lnzh2YNWsGRFHE5ZdPScrnSSg2/D0b2t46x/swSS3Qwn+OtzkE\ntK8NKJ7pD/WpItxdvb7LbRJEEdq9+yB3WAFt586kLU0FmG3+j2+xYec+ASqlHLn9QnuUhrmZKPKY\nm5OHIElS5/kuEfRZzXYI1s53PdvfDfV3B/Q9+ZcAgJ84Lgr5eu07oM1WCQa1EHAqrnsakXT97SFf\nwx9JJiAvq3McPSE2NiL94kvCes5wycoyoK7Of8GIZMJYk1MqxQokT7xZfN4+LDr+LDRt+y+OmAGr\nzf9dULtTCjpF9zPnblQ5q+GnBGAnFlgh2TWQfzvJ0wE9PfXqkI5tz19hQr1eDVMIdznNFhuG5/cO\n6VrMzfGBsSanVIoVSJ54A+XmuKmC2/5uqNQqQhPefpvXothBp+KGid3hxN7qep/b1Co5Bg/IgCCH\nfAAAIABJREFU8LmNiIgoHgTLU/5yXHuXyoqR35oOtTx45VvANdjcEtKeRESUiOKmA9o+yR3fH765\nz+4iBYV9gcK+wIZve6HZKsNLX7UrVtSuUNFtNtccoL8Gm7IbgPsOa2+DBiY/87jNFv/Tf4iIiBKB\na/DYdz4L5e5oPLM7pZA62ID/dcF9YZEjIkp1cdMBjZSORQoG9XKgukFA+6lA7kJFbnp7C27b/1bQ\ncx9Mz8cX/S/0ei/Sd1iddhuatv230/t8/oSIiKIt0B3SUDtv/phtAsx2AXp7C7Tv/Cvo/t+l5+Lz\nfuM8rz2V8dsNMgOATDDD2fb0UaBHcrrUefazLjg0WmDIcK+3WOSIiFJdXHZAFQoZWts9cyI6nEHX\nAwvV+IF2r3XGAO/nRASpEKg5iKBPFLWYcEHrERSPnez1dtBiR226MrLqTQ7A9bVpP41XbGzsxrmI\niIjij0IGpKkkfJeeiyFNR4Lur7e3YEjTEa8OqLsyfsdBZrewDhj7WRccpqYwnJyIKLnEZQe0Xy8d\nkH7uzmVNbfQexA2loh+AgGuehSIc05I4jZeIiOKVe3qu3em7AxiISi65Kt6PGgELRgTdP618I9Ig\nodRHlfyOxYjcRYhCHTAON19rjwKcmktEqSMuO6CBWGD1VMPtKFfKxAXOwVFuUWdNVglbqlvxv6MS\n99kXIiKinnDP0NlbXQ9Etd5+6JqtUqeOaKBpueHga+1RgFNziSh1yGLdgFAoFTKYLHbkSpl+1xGz\nwIojwukot6yzob1dffqqejHi13JP491bXY8jpxK/XDMRJYZdu3Zg0aL5AIBrr70y4L7vvfcOHA4H\nDhzYj1Wr/hyN5hGFZGhvBQxq71uz7mm5YSPagcqdIf1T7qtA07b/ev6ZvtkdvnYQUdJLpNycEHdA\nB2Smoaa2GRc4B+MC+L7D6e+uaLRdlq+JSucT8J7Ga2k867M4UShYwIiIukrwVPgOPLdy9erXcPXV\nU1FYWITCwqLIN4zijlolR2uzA5Lcez3RQPUdAs12cus460lmsSCzfCNac7JhKh4dtF2X5Ws6Pf8Z\n9mm5/p4N9UGS26DIOFfUibUdiKirEiU3B+2ASpKExYsXo6qqCiqVCkuWLEFOTo5n+3vvvYdVq1ZB\nLpfj+uuvx8033xyRhirbChOFsyCRm3uplpDaIVOhnybb9aLF5PNZ0AmaXHzQaxw+2G/GxAHR6eM7\nM3p5Ja6uYJKjeLD+u3Ls+v6bsJ5zTN/zcf2QqX63b9xYji++2IrW1lacOHEcd989ExMnXoH9+/fh\nueeehlwuh0qlxty5C+B0OrF48QL069cPx44dw/DhI/Hggw97na+29iQefXQuMjOz8P333+Piiyfg\nV7/6NWprT6Ks7HdwOBwQBAH33vsgdu3aAVEUcfPNt+Hpp8ugVKpw770P4PXXV2LAgGwMHlyA5557\nGgCQnp6B+fMXoqpqH/7v/16ASqXCT35yHX70o6s91124cB769u2HU6dO4vLLf4TDhw9i//4qTJgw\nETNnzvYZk83WhF/+8i4Yjb1wySUTccEFY/D883+AJEnIysrCwoWP49ixI53a4c01t7KiYidee+1P\nkCQJFksLFi1agoqKnThz5gwWLZqP0tJpePfdt/HYY0vx4YcbsW7d36FSqTFwYA4eemg+PvroX17f\ni1tvvR1XX+3/e5fq4iU3h2LwgAzY6/VIU+m83vdX3yFXygw6o8k968k9KN2akw3N0eOQWSzQHD0e\nUgc03tidEg6daOQa4RRXmJuZmyORm4P2jjZt2gSbzYY1a9Zg9+7dKCsrw/Llyz3bly1bho0bN0Kj\n0eCaa67B1KlTYTAErSHbZQMy0wBEpiBRx6VaArE62goc5BUANQc779BiwjCxBh/0Goc9p6xR64AS\nUfeYzWY888zzOHbsKBYseBATJ16BZcuWYt68hSgoGILPPvsYzz//B8yZ89u2D/zlUKlUuPHGa3H2\nbD169ertdb7a2lo8++xy6HQ6zJ79S+zfvw+vv/4abrzxFkycWIIDB/bjiSd+j6VLn8LSpY/h5ptv\nw5EjNbBaXc9/bdv2BZ566o+4777ZmD9/EfLy8lFevgF//etfMH78xbDbbVixYlWnOE6ePIHnnluO\n1lYLSkt/gg0bPoBKpUJp6f9i5szZPmNauHABzp49i9de+xvkcjl+8Ytb8NhjZcjNzcP777+H6upD\neOaZJ3224xzXKOvhw4ewcOHv0adPJlavfg1btmzC9Om/wF/+shK/+10ZvvlmNwRBQFNTI1auXIFV\nq/4OjUaDF154Fhs2rIdOp/P6Xsydex87oAHES26OhECzndw63h01FY+GqXg0Mss3dtrXPcjsNYAc\ngPu50Eg/C9qRMU3N4oJEbZibkzs3B+0d7dixAyUlJQCA4uJiVFZWem0fNmwYGhsbPbd8z936TW7+\nquUK61+HBkC6Orpfh+4v69K1BbQBVuqjyLh+yNSAI6KR4p560rdvP0+iOX26DgUFQwAAxcVj8fLL\nLwEAsrNzoNG4/iDNzMyC1WrDk08+jmPHjqJXr9749a/vwZAhhdDrXYNaw4ePxJEjNThypBrFxWM8\n16urO9V2vVbs3bsHeXmD8P33tdi371vo9XrodDrU1BzGM888AQAQRREDB7rubuXm5vmMY8CAbOh0\nOigUCvTunelpgzsJ+YvpvPMGQC53rZFYX1/vOf811/wEAPy2o6OsrCw8++xT0Ol0qKv7HqNHX9C2\nRXItg9HmxInjGDSowPN1LC4eg+3bt2HEiJFe3wubzd7xEtROMuRmZQSXXGvPPcjsGUAOYGhvBarq\nxYiv6U2UKJibmZsjkZuDdkBNJpPXqKlCoYDT6YRM5qpfVFhYiJ/97GfQ6XSYMmVKuy9sZHRMWG5S\n2yClr21ukUpu8aBHy7o4lIA+9ONZqY+Sia8/zLOysnDw4HcoKBiCXbt2ICcnt9M+7g/uuXMf8bxX\nW3sS1dWHYbVaoVAo8O23e3DNNdciL28QKip24tJLJ+HAgSr07u16LmzChEuxfPnzuOmmW1BbexLP\nPvsUrr32egBAbm4+HnnkMfTt2w/ffLMb9fVn2tobSu24ziVH/cXUPv7MzCwcP34M2dkD8cYbf0FO\nTp7fdnS81pNPLsHatRug1WqxZMliz9dHJpPB6Tz3uXzeeQNQXX0IVmsr1GoNKip8tyVuy6bGiXjL\nzd3hntnkFs0l1/xxPxcaqyVa2nPabT5rO7BuA6UC5ubkzs1BO6B6vR5ms9nzun2Cq6qqwn/+8x9s\n3rwZOp0ODz74ID744ANceWXgyktGoy7gdmuaGjK972kvhX7e33LK1aYRA7P8nvfgsQZo1T2cEis6\noA/QWbPIXN8kmSCgyerEil1mn/uN7KfGlUVpPrdFm9MmAIcrO70vaHRQDh/VeX+5DFlZvqdy+Xs/\nGTHWxGcwaKDTqZCVZYDN5pr6lpVlQFnZUixZsgSSJEGhUGDJkiUQBAEqlcLztVCpFOjTJ83ra2Oz\nNUGtVuHxxx/B6dOncfXVV+GSS8YgJ2c+Hn30Ubz99t8hiiKefPIJZGUZ8NOfTsVrr/0Jr776J3z/\n/fd46aU/4tprfwyj0YDHH/8dnnjiMTgcDshkMixZsgSnTp2CRqPs9P2w2Zo8bbPZbJC3+x2VyQS/\nMbnjcO+7dOnjKCt7HDKZDH379sXs2TMxbNjggO2QyVzXuu66n+Kee34FnU6HzMxMmM2NyMoy4KKL\nxmP+/AcwZ84caDRKDBmSg9/+9l7cd9+vIZfLkZubi7vu+jnef/99r++FPMDnDEUmN3f6eqdroQqS\nr0Ols6qQpg48nVWtaQ05R8vsrlyr1aq83nf/odTxfQBe+TtQHgcAmWAOab9ws0kSaurc31cd0DYj\nV6NSYGheL9c+Zxu6/LuRSr9LjDXxMTcnf24WpPb3X3348MMPsWXLFpSVlaGiogLLly/HihUrAAAn\nTpzAnDlz8Oabb0KpVGLJkiUoKipCaWmp3/N9VrMdgjXIXchdlUB610ZrVzZ/DACYYfiB331qapuh\nUcm7dN6OOi5o3ZG7KNHmsTfiwFkHnD6+vM1WCQa1gFlj429E2oupCRg1ttPbjSYrLh7Zv9P7WVkG\n1NXFfgQ7GhhrcupprLW1J7F48QK8/PLKMLYqcpLle5usf4QFEu7cDKDTz0LTtv92u7hdR1X133Uq\nQtTRidNm2EWn53WgWUvuZ0B/4rjI6/3M8o2QWSxwajuvtSlBglxQQCYT4HQGHsVvtjkhSUCoM5cP\npufji/4XhrRvd54tNVtsGJ7veqZNbGxE+sWXhHxssvyeh4KxJifm5sQUKDcHHWqcMmUKtm7dimnT\npgEAysrKUF5eDovFgtLSUtx444245ZZboFKpkJubi+uuu67nLdZqgCYf01/sItDH6Pcwk2T1dETd\nCpX9UaIZCiCylXS9tJhw+c61+KGfJNdscyVYoboby7DmFbiePyUiopQVjdws02m9qqQ77TaoMv3P\nMuqpcEzJdVfD7SmlTIA9SCfVTW9vQUFTdUgdUD5bSkQUwh3QcAvpDqg/Ae6MftpahQN270I6JskK\nvaDudFe0J3dCWxwmyOH/WOPXe6E77mqHUq702wHtysiqm97eApNSh78W3QCge6OoXeLnDmhdowUq\neefOsyFDi+bG4EUeElHHwkvJMjoVCsaavJIl3lS8AxoJwX4WenJHNJQ7oB0FytXvyb+EBVZo4X+K\nbMd1Qt0zmPR6NUxhrGXgnvkkXX970H3dz5Z2dQYU74CGhrEmp1SKFUieeHt0BzRRlGiGeu50unW8\nGxoOwZZssYwZC8sYV6Ib1neYzyS3vboVVfVil6992/63PP8fy1HUrIzOU5sAwGjQQOZw+tyW6Fh4\niYgofgRbK7RFsOIITnst5+JejsUAPTIQuTu5REQUWNJ0QBOJu8peV7mn7M4aq49OhT7RDlTuPPda\nowWGDI/8dYmIiAIItlZox3VCgXMDyDanDejGEzCx1H6pNVnjWUjH/gWVUo7cfgZWxSWihJNYHVB/\nz4b61Tb9tcMxGqsFotnHnTpRhBiGgguiwwmljwJ8CcfYx/u1qSk27SAiopjr+EyoW6SfDU02zVbJ\n5yByoMdqvJZa0/YD4JqWq8jI8Pk9ISKKZ4nVAR02pGv779nt+u9I76VE+vnbvxvVd32Jh7XMiIiI\nwsnfXTZfa1WGg791v0MRaG1wSRJhllxLO9idUs/W0XZrMXmeBfXSoXDg0N4Kn4/gsDgREaWSxOqA\nkifJ3dZWyMi03/X22b6DkXP5pNi2jYji0sqVK9CnTyZyc/Pw7rtv47HHlvrcz2az4cMP/4mpU3+K\njRvLkZ6egYkTS6LcWiKXjlVxu0LR7Kryl9e/cxEMSSkiR+0q6OOe1tojeQVAzcHO77eYXO+364D6\newQnKo/VEFFcSeXczA5oImmX5NqXiNfbW4DvDwFgBzRSbA4ntu05V2XZkNGI5kZLp+q4RPFOCFB+\n+8yZ0/jHPzZg6tSf4uqrp0axVUSJSxo30auT6ebzjigRkQ+plpvZAU0g7ZOcuu0fAJjWrIpVk1JG\nx8q/7oq/rI4bPnXr1qD5q+1hPafhwvHIKp3md/vGjeX45JP/oKWlBU1NDbjnnt9gzJgJ2L79v/jT\nn16GWq1GRkYGHn54IZYufQx33HEnhg4dhltvvQEzZ87BpEmTcf/9czB//mJ8/XUF1q79G+RyOUaP\nvgAzZ87GypUrUFn5NSwWC+bNexS5ufme627d+gmsVivOnDmD0tJp+PTTj3H48EHMnv1bXHrpJHz4\n4UasW/d3qFRqDByYg4cemo+PPvoX3n//PUiShDvvnIkTJ47j3XffhtPpxKWXTsKMGb/C5s2bOrXD\nl7ffXosvvvgEzc1mZGQYsXTpU3j99ddQU3MYq1b9GU6nE336ZOLaa6/Hiy8+h6+/roAgCJgy5Urc\ncMM0LF36GJRKJU6ePIn6+jNYsGARCguH+rwWEYWfuzCRYG6GXV/baTsHSCkcmJuZmyMh6TugJpsZ\nK/e8EXCfQuNglGRPCNs1lQoZGlq7vsxK3OtYFbcDW5oKMNsic21W4KUIsVpb8cc/LsfZs/WYNesX\neOONt7FsWRlefvlV9OmTibfeWoO//OVV/OAHl+GLLz5Deno6lEoVvvpqG8aNuxA2mw0qlQorV67A\nq6+uhlqtxu9/vxDbt28DAOTnD8I99zzQ6botLRb84Q8v4N///hBr1/4dr7zyGnbu/ApvvfUmRo8u\nxsqVK7Bq1d+h0WjwwgvPYsOG9dDpdDAY0lFW9jTOnj2LZcuWYvXqN6FUKvHKKy/h1Klav+3oqKmp\nEX/5y19QV9eM++//Dfbt+xZ33DEDhw8fxM9//kusXLkCAPD555+htvYEVqxYBVEUMXv2XRg79kIA\nQP/+A/DQQ/Pxj3+8iw0b3sGDDz4coe8SxTN/xYnaE0xmQNHNZbrsItDH2L1jfRCdDlTVfwcAOGk1\nQSN1b13wYAZIrr8DTrQc9rynlKnQT5MdlvN7nl21Aqje02l7S6sdTaeNQLoWTU2RWaObFXgpUpib\nkzs3R70DmqbUorapHjaniExt74heq9A4GAcaDgXcx2Qz40DDIVcH1F1lt4fJbkBmGpqON+Fw0yFY\nWyPUIWvH3dJjEUpy5y7UJ+BmmV4NCBG6I8gKvEkvq3RawBHRSLnggrEAgF69eiMjIwP19WeQlpaG\nPn1cdw6Ki8dgxYrluOOOO/Hww/fDaOyF2267A2vWvIH//vdzTJw4CcePH0VDw1k89NC9kCQJFosF\nJ04cBwDk5ub5vG5RkWtEUq83IC8vHwBgMKTDZrPixInjGDSoABqNxtOG7du3YcSIkZ7znThxHAUF\nBVAqlQCAmTNnY+/ePX7b0ZFCocT9998PQVDg9OnvIYq+B82qqw9j9OgxbccoMGLEKBw+fNgrhr59\n++Gbb3aH+BWnZBNKB0SsVQPq9O5dYFdl947zw6jNgNnRCgDQqyXYRe+OsehwQq9V9vg6AlxT6tTy\nczNorA7/HcEmq4Qt1a1+K+H65Sc3S3JXlVyVUQeFEJnS/KzAm/yYm5mbIyHqHdAxA0ahTtmMr2p3\nRfxaJdkTgt7Z9Lo76q6yG4Zkp5XroVVoAXlkRlZ9CTXJEdE5VVV7AQD19WdgMpmQldUXLS1m1Nef\nQe/efbBr107k5ORCr9dDrdZg8+aPsGTJU9iyZRPeemsNHn3099Dp0tCvX388++xLkMvl2LixHIWF\nQ/HJJ1sgCL4XHAz0vMd55w1AdfUhWK2tUKs1qKjYgZycXACATOY6X3b2QNTU1EAURSgUCjzyyFzM\nmXOf33a0d/Dgd/j00//gnXfexrFjdbjzzumQJAmCIMDp9P5jfNCgQXj//fdw4403QxRFVFbuxo9/\nPBXbtn0eMAaiWDNJVqxs/hiFyv4o0fieguar0FE4K9nLLBZklm/0vJYgQRA+7bTfL0QJNocEoQYQ\ndrZ9ZnSooEuUSpibkzs3J/0U3FSht7cA7/zL81oLwISPQzr2YHo+vuh/YcjXCrRWGVGiOXPmDO69\n99doaTFh8eLFEAQBc+c+gvnzH4JMJoPBYMCCBYsBACUlk/DPf5bDYDDgoosm4N1338KAAa6ZBjfd\ndCvmzLkLDocT5503AJdfPqXbbcrIMGLGjF9hzpyZkMvlyM4eiLvvvgebNn3g2cdoNOLWW2/H7Nl3\nQSYTMHHiJPTv3x833XRL0HYMHJgDrVaHW265BTabiD59snD6dB1GjjwfomjHyy+/CLXaNb1vwoRL\nsXPnDsyaNQOiKOLyy6fE5fMkRO0VKvvjgL0WJsmKA/Zavx3QSGrNyYbmqO+7HB1pFOcKCwLwWUGX\nKJUwNyd3bhYkSZKC7xZedXWuO6Dp3Z2OE0buO6AzRt567s0wrAdaU9uMXhlaWCyRn4Jr+mwPsuqO\ndutYvb0FJqUOfy26IaT9m60SDGoBs8Z2/vro9WqYIlWUx9QEjBobmXN3g9GoQ0NDCxpNVlw8sn+s\nmxNRWVkG1NUl59q2GzeW48iRGk8xgGSO1ZdkiTcrq/NSG9R1kfxZ6FHO70FOXtnsGoidYfiB5700\nvQZmU6vfY2pqm6FRRWb2ktVhwUDdIJ/b3EuxzBqr91TQla6/vdvXMltsGJ7f25OvIkFsbET6xZdE\n5NzdkSyfaaFI5liZm5Mj3kC5mXdAI0SpkKG5xQZFFO6C6y8dCQtGer0XKMm1J6x/HQbAZ4fSF65V\n5q3j8ixurD5IRESx5K6Sq0szo8XsGhxWq+QYPCAjxi0jolQXsw6oVqFFk7XrhWWiUbwoHAZkpqG2\noRVwdrPqHyWEjsuzuHF5lsSQLOtpEVH4KBUytNocYStGFCvuKrl6nQpC2/RecxRmZRH1FHNz8otZ\nB3Rk5rBuHReN4kVEREQUJ9wV6oMJ03It7sJE4SxGFKpmq4SXd5pwm801eP3XtllHrL1ARMmEU3B9\niXKyIyIiIj/cFeqDCfNyLdE2tLcCVfWdl1xotkqoqhdxWX7Um0REFBHsgPoSpmSnUsjQbLL73Jbo\nU3uiTrQDlTtj3QoPW5oKMPufyqRstaPJlCSDExFcxDzupFKsQPLEm65F1qRLY90Koh65LF/j6WQK\n1a4lHWaN1cd17QWn3Yambf+NdTPOSZbPtFAw1uSVLPEGyM3sgAIw2cze64EGUGgcHHRtUbec/ul+\nK+3FYmqPXy0mT8U9L/G0BpmfhbZjRaZXA4L/5zzdC4Ang0guYh5vUilWIHniVRl1sW4CUfi15Wb3\ndFx3pzSecrMqMyvWTfCSLJ9poWCsyStZ4g2Um1O+A1poHIwDDYdC2tdkM+NAw6GQO6AJIa/AtdZY\nRwHWIHM/o9KRTDDDGf1VfaKCz98QESUmk2TFyuaPUajs36X1QN3FiMLJ6nCgQbJ6CgT51Y3cTESU\nKFK+A1qSPSHkDmWod0kTiTRuos9E5vOOKPw/o5LM+PwNEVFiKlT2xwF7LUySFQfstV3qgLqLEYVT\noxU4dfooTC1B1hkdPsD1D8CGb3sBAK4dcRYDNm4BJBEnWg6HfE21UwVrq+uREZNVxMmqI91rfAJQ\naZSwtfp+9MkXpVKOvkbf1eyjRS1XIT8jN6ZtIIq2lO+AJisHHDjWhQTV0QDJ1cnsmOQK+7r++aLW\nnEtyyWTDt73gcMLr69k+ofvSanNAVl8fjeaFjEmOiFJNiWYoSjRDsbL541g3BQCQoTagQQ6o5UE6\noO0IgmtBcbVcCwHn/j9UWoUKaLueOslnq2u1KliE0P8OabU5kKaK7RfFbGuJ6fWJYiFoB1SSJCxe\nvBhVVVVQqVRYsmQJcnJyPNu//vprPPnkkwCAzMxMPPXUU1CpEn/ecqSFY2pPoEJGOrm+R+fuaZJL\nJu2Tv1uwWO2w43R997+/SoUs7KPvTHJEyYO52Qd3BfskrFBvtglYV6nF7XZXPlpXqUW+UcT4gaHf\n7SMiihdBO6CbNm2CzWbDmjVrsHv3bpSVlWH58uWe7QsXLsQLL7yAnJwcvPXWWzhx4gTy8/Mj2eb4\n4W+5lhCSXzg6F3FVyIi89LTCcbifOyKi5JJouVmr0KLJ2hTy/janiExt765dxF3BPsGXY+ko3yii\nusH7zzWzTUB1g4IdUCJKSEE7oDt27EBJSQkAoLi4GJWV5z7YDx8+DKPRiNdeew0HDhzA5MmTU6fz\nCfhfriXJkh8REcWXRMvNIzOHdWn/r2p3RagliWf8QLuno5lW7Sr0l6ZKzoJ/RJQagnZATSYTDAbD\nuQMUCjidTshkMpw9exYVFRVYtGgRcnJyMHPmTIwaNQoXX3xxRBtN0SGzWJBZvtHzujUnG6bi0TFs\nERERAczNqUxmseD2A+8AcHVImZuJKNEE7YDq9XqYzWbPa3eCAwCj0Yjc3FwMGjQIAFBSUoLKysqg\nSS4ryxBweyCGFi2M2tg8MH4u7sDXt6apIdO7luxI00du6Q61phVadWTqSImDcqGsPtr2JCggtLRA\ne+wEHJdcGPA4rTb5njFyPwPaMbZIxirJxLD/7EhWMejPrj/dPS4RpVKsQOrFmyziLTeHW09yffsc\n7CYzuz7H06KQm4Mx6G2wic5O7zscThh0gfOKOzejrc6OzGJJ2dzsT1dijUSu7Srm5tCkUqxA8scb\ntPcyduxYbNmyBVdddRUqKipQVFTk2ZaTk4OWlhYcPXoUOTk52LFjB2644YagF62r6/6zi81NFgjW\nnj1f111OpythNDQEKeZitgJyJdL0GphNrRFrj7XVDsHZOYmFg2XkSGDkSM/rzPKNgCTBYvFfXU6r\nVQXcnqgkyVVsqH1skY7VanOE/WenxWYL/rPrg9Go69ZxiSiVYgWSJ95kT9S+xFtuDrce5fq2HNye\n0+masmo2tUY8NwfTW++7g1RT2xw0r7hz87pKV1G8u6vXp2xu9qWrsUYi13YVc3NwqRQrkDzxBsrN\nQTugU6ZMwdatWzFt2jQAQFlZGcrLy2GxWFBaWoolS5bg/vvvBwCMGTMGP/jBD8LU7PhksplDWA/U\njsLW83CVvjgqbSIiotTC3Nx1JsmKlc0fY4RjIC6RF8S6OUREKStoB1QQBDz22GNe77mn9QDAxRdf\njHXr1oW/ZX4EqqTXrap5XVBoHIwDDYeC7tcM14LXVyGyHdD2S7kEWpKFes5dAt9NEARIkpxl8Iko\nJuItN8cVHxXqC9EbB3AGJqkVe1uO4RKpX3ivGYOlX8w2AeZ2y7J0xPwUnOhwxnxFAavDAmdT19cN\n16WZ0WK2RqBF8SeVYgXiP161So7BAzJ6dI7IPEAYQYEq6UW6al5J9gSUZE8Iut/Kir8AkgRnY7Nr\nKlA4tUty7ZdyifUHaDLzVQIfYBl8IqK45KNCfQlGoQTAyj1vQJDJgOGjwnvNKFe/95eX3JifQhMP\nA/eCQ460bjyjq9epIDhToxpyKsUKxH+85jBM6U+4DmhCULq+rOqLimEJ9xxuLvESde00bup4AAAg\nAElEQVRL4LtptSq8vl0eoxYREVEqc+cl97IspaMsXtt93RElIooX7IASERFRXAn0uI1bpB+7SRQd\nl0wDgNvbpuamVUsQBAFpUmTupnAJGCLqDnZAKWS+klx7THJERBQOgR63cYv0YzeJoDUnG5qjx2Ny\nbZnFAs3R48zNRNRl7IBSSJjkiIiI4oupeLTP3Oiegls6yhKxZVgCDUgTEQXCDmiSaF8RNxJah48E\nhrvWBfVXcZdJLnwiUZmPlfaCS6VYgfiPNxyV9ogShVIhg8lij4vCOEREkcQOaKLxUV4eAAYIItA/\nOiXgWXE38iLxBwgr7QWXSrEC8R9vOCrtEUWFn9zcleVZBmSmMb8SUUpgBzTR+CgvD4DVcYmIiGKF\nuZmIKGTsgBIREVHKaLI2Y+WeN6J0NTvQLHheFSr7o0QzNCpXNtsErKvUQhAESJJr2bB8o8i1QYko\n5mSxbgARERFRNBQaByNdbYjJtU2SFQfstVG5Vr5RRJrKe3q92SaguoH3HYgo9pLqk8jXumGxWifM\nZDPjuS9ehdPpjNIVYzfKSkRElAhKsifgf0degYaGluhccFclYNADAFY2fxydawIYP9DuudPpLhDo\nroxLRBRrSdUB9bVuWCzWCSs0DsaBhkNRv66be5SVHdDIc09x6ojTnIiIIsvXoHN7sRqAJiKiwJKq\nAxovSrInoCR7AoxGXdKPsqayfKPoczqTe5oTO6BERJHja9C5vVgMQBMRUXDsgCYLrxLwbc99+CoJ\n70sXysTTOe2nOLXHaU5ERASgy7lZY7VANLc9uiOKEDNc6+D6W3+biCgRsQOaLNqXgN+z2/XfkaNC\nO5Zl4omIiMKvi7m5X/sXuyqBdNfMJq4PSkTJhFVwiYiIiIiIKCp4B5SIiIgoBfgrnNcdt9tdlffj\n6bGT9muehoIFA4lig3dAiYiIiJKcr7VBUxnXRSWKHf7mUZcpFTK02hyd3pdkIqw+3u8pSXIlTF/X\njBYWgCAiokTmr3Bed6VVS5BZLLi7en3YztlTrjugoXWyzW13cNOqY9splyBBED7t8nEWmQDBmRoD\nCqkUKxD/8aZJEk4qgt/DNP6/B/xuYweUumxAZprP99P0GphNreG/oFwGmFuQt+mj8J87RKLDCUEQ\nPK8FQUCanyR3e5wktY6Y5IJLpViB+I83HEmOiCKjNScbmqPHY90MIkpASd8BDbZQNcDFquNeQR5w\nsCbWrSAiIqI2puLRMBWPjnUzvGi1KlgstpD2dT+7WjrKEskmBWV1WDBQN6jLx2n1aphM1gi0KP6k\nUqxA/MdrttgwPL9n/aagHVBJkrB48WJUVVVBpVJhyZIlyMnJ6bTfwoULYTQacf/99/eoQeEWbKFq\ngItVe69T1k68rA86YZzrXwwdr22GRnWusEGgJBcvSa0jJrngUilWIP7jDUeSS1aJnpujwT0AnbCD\nzO1ys8JshszuykGCKMLRtj4oEVEiCtoB3bRpE2w2G9asWYPdu3ejrKwMy5cv99pnzZo12L9/Py66\n6KKINZQiqP06Ze1xfVAiorjE3BycewA6YQeZ2+Vm64lGNLXVQUjfvx+izcHaBESUsIJ2QHfs2IGS\nkhIAQHFxMSorvTslu3btwjfffINp06bh0KFDkWklUYLpaal7loYnokCYm1PL4AHt7nie1QPpetTU\nNseuQUREPRC0uoPJZILBYPC8VigUcDqdAIC6ujq8+OKLWLhwYchVx4iSXU9L3bM0PBEFw9xMRESJ\nKuhfuXq9Hmaz2fPa6XRCJnP1W//1r3+hoaEBd911F+rq6mC1WjF48GD89Kc/DXjOrCxDwO3RZmjR\nwqjVReTcRmNkzhuI+/vT02tb09SQ6TVdOiati/snCrWmFVq196+LVqvyue+kQmASur9kzOqvFAAE\nv+fvNtEBvV7drUO7e1wiSqVYgfiOV5IJMfkMTQSpkJvDxVeOT4bc7Csv+RP2fBLHQo3VXdk+5l8b\n5uaQpFKsQHzHG47cHPSTa+zYsdiyZQuuuuoqVFRUoKioyLNt+vTpmD59OgDgnXfeweHDh4MmOACo\nq4uvaSPNTRYI1vA/R2E06tDQ0BL28wbjHgXv8bXNVkAe+tclYsuwxAFrqx1C29cV6Fqlva6SJFeh\niXCf3+qwwSTresEZfZwXqgmnVIoViP94Wyy2kD7HUrGTmgq5OVw65vhY5maTzYw/bP1Tz05kswMt\nAkRIEEJIEzJBgDNF7oR3JVZxuKsD+qYtMl+bXCkTFzgHB92PuTm4VIoViP94w5Gbg3ZAp0yZgq1b\nt2LatGkAgLKyMpSXl8NisaC0tLQLzSUiIqJwYG5OPIXGwTjQwOdxiYgEKQYPiMTbKOtXtbuQrk4P\n+3ljNcq6cs8bMNnM0KvSenYimx1om6ISCplMgDOOF7XvCdEheX0pIjmi3GJ3XUinDO38oY+ydm8Z\nlngfiQunVIoViP94Q12GxWjUIeP8UVFoUXKLt9wcLh1zfKxyc9jsqvQUIWq/PJg/kZyxE29SaR3Q\neP/8DqdUihWI/3jDkZtZ6QTn1goLRSKsJxa2UVZBANp3siQJkAWtW0VERESR0rY+qMZqgWh2AqII\n0ce6oFymhYjiFTugOLdWWCgSYT2xkuwJKMmeEP4T76oEDHq/m5P5GdCOI82RHFFe961rVPYnMR6V\nJSJKBu5B5kQYQA5J2/qg/dyv2+6IdsRlWogoXrEDSkREREnLPcicCAPIRESpgB1QohAoFTK02s4t\nrSLJRFhtDk5xIiIiIiLqAnZAiUIwINO7oJN7ujGnOBERERERhY4VZYiIiIiIiCgq2AElIiIiIiKi\nqOAUXApdW+l3f5wOO2CO0LpFdhHoY4zMuYmIiBKVn9ysMJshs8shc9gga7VH5NKCKMLhYwkYIqJA\n2AGl0LWVfvdHbdTBEqnFvXdVRua8REREicxPbm6qrkeaVgm5XgNLhJZI0+7dF5HzElFyYweUiIiI\nkp5nPVBTC1TQxbo5FAfMNgHrKrUxbYMkaSCX+Z9d5o9MMMMpSRFoUfxJpViB+Ip3aG8FLsvXhP28\n7IB2kTuBBWNzijAameCIiIjigXs90KqWfYAY48ZEgVolh9lihySTocXimoJrdzhh1Ktj3LL4kG8U\nUd3AP4OJYoG/eV3kTmDBcMFrIiIiipXBA1zPZhqNOjS0PR6zt7o+lk2KK+MH2jF+YGSeje0Kq8OC\ngbpBXT5Or1fDZIpQ3Y04k0qxAqkRL6vgEhERERERUVSwA0pERERERERRwQ4oERERERERRQU7oERE\nRERERBQV7IASERERERFRVLAKLlEPKBUytNocnd4XHU7otcoYtIiIiAJJU2pR2xSbarA2p4hMbe+Y\nXJuIKF6wA0rUAwMy03y+X1PbHOWWEBFRKMYMGIU6ZWw+o2O9RJt7bdBwkdscEJWdB2FjRZKJsPoY\nFPaHg8VEscEOKBEREVEKcK8NGjZn9UC6Przn7IE0vQZmU2vI+3OwmCg2+AwoERERERERRUXQO6CS\nJGHx4sWoqqqCSqXCkiVLkJOT49leXl6O119/HQqFAkVFRVi8eHEk25swtAotzloa0Wy1xOT6fM6E\niCh5MTcTEVGiCtoB3bRpE2w2G9asWYPdu3ejrKwMy5cvBwBYrVY8//zzKC8vh0qlwgMPPIAtW7bg\nsssui3jD493IzGHIyjKgri41nzMhIqLIYW4mIqJEFXQK7o4dO1BSUgIAKC4uRmVlpWebSqXCmjVr\noFKpAACiKEKtVkeoqURERAQwNxMRUeIKegfUZDLBYDCcO0ChgNPphEwmgyAI6N3bNc1z9erVsFgs\n+J//+Z/ItZYoRZhtAtZVasN6TknSQC4zdfk4mWCGU5LC2pZ4lUqxAvEV79DeClyWr4l1MxIGczMR\nESWqoB1QvV4Ps9nsee1OcG6SJGHZsmWoqanBiy++GNJFs7IMwXdKErGK1dCihVGri/p1jcbIXNOa\npoZMH19/nKYFaI9a0wqtuntFpodkSjh4RgAgdLNl/smE7p2zu8clolSKFYifeFUqBfR677t0kkyI\n2GdKomNu7hnm5vBItNzcUU9yddiIjk6ffaHq7nGJKJViBeI73nDk5qC/dWPHjsWWLVtw1VVXoaKi\nAkVFRV7bH330UWg0Gs+zJ6GI1XOR0RbLZ0CbmywQrNFd28po1KGhoSUyJzdbAXn8rNUVrNS7tdUO\nwens1rnH9Hf9Czerw4KBukFdPk6vV8Nksoa/QXEolWIF4i/ejm1psdhC+kxJxU4qc3P3MTeHUYLl\n5o56kqvDxeqwwSTr+udwvH1+R1IqxQrEf7zhyM1BO6BTpkzB1q1bMW3aNABAWVkZysvLYbFYMHLk\nSKxfvx7jxo3D9OnTIQgCbr/9dvzwhz/sQhhEIdBqgKauTx+NFKfD7kq8fijMZsjs8ii2KDi5wwo4\nm7p8nFNSAWZbBFoUf1IpViD+4xVa7RAbg/8e2aT4jSFSmJspLiRYbu4oHnI1c3NwqRQrEP/xhiM3\nC5IU/QeAOMoaeV/V7kK6Oj2q14zoKGucCRbroRONsNoc3T6/3eGEMczTL1pEE4oMI7t8HL+vySve\n4200WXHxyODTAVJp6mgkMTdHHnNzZHU11r3V9UjTxvYOLnNzcKkUKxD/8YYjN8d44jtRcho8IKNH\nx++trg9TS4iIiIiI4kfQZViIiIiIiIiIwoEdUCIiIiIiIooKdkCJiIiIiIgoKtgBJSIiIiIioqhg\nB5SIiIiIiIiigh1QIiIiIiIiigouw0JEREQUBVqFFk3WpqheU7LY0Wy1RPWasdLVWC0OMwQxtn8K\nq2WamF6fKBbYASUiIiKKgpGZw6J+zawsA+rqmqN+3VjoaqyOM7XI0Ksj2CIi8oUd0CTFUdbIinSs\nkRiV5SgrEREREcUaO6BJiqOskRXpWDkqS0RERETJiEWIiIiIiIiIKCrYASUiIiIiIqKoYAeUiIiI\niIiIooLPgBIRERFRytFpFGg0WWPdjG5xymVoTtC2d1UqxQrEf7w6Tc+7j+yAEhEREVHKOb8gM9ZN\n6DYWfkxeqRAvp+ASERERERFRVLADSkRERERERFHBDigRERERERFFBTugREREREREFBXsgBIRERER\nEVFUBO2ASpKERYsWYdq0abj99ttx9OhRr+2bN2/GDTfcgGnTpmHdunURaygRERG5MDcTEVGiCtoB\n3bRpE2w2G9asWYMHHngAZWVlnm2iKOKJJ57AqlWrsHr1arz55puor6+PaIOJiIhSHXMzERElqqDr\ngO7YsQMlJSUAgOLiYlRWVnq2HTx4EHl5edDr9QCAcePGYfv27bjyyisj1Fyi1BBPi2PH+4LI4ZRK\nsQLxH284FrtOVszNRESUqIJmd5PJBIPBcO4AhQJOpxMymazTtrS0NDQ3J/fCqUTREE+LY6fCgshu\nqRQrkHrxJhPmZiIiSlRBO6B6vR5ms9nz2p3g3NtMJpNnm9lsRnp6etCLZmUZgu6TLFIpViC14mWs\nySmVYgVSL95kwdzcM6kUK5Ba8TLW5JRKsQLJH2/QZ0DHjh2Ljz/+GABQUVGBoqIiz7aCggLU1NSg\nqakJNpsN27dvxwUXXBC51hIRERFzMxERJSxBkiQp0A6SJGHx4sWoqqoCAJSVlWHPnj2wWCwoLS3F\nf/7zH7z44ov4/+zdeXxU1fk/8M+dfSaTZAwJICEQCAEEBQVRKcaiLVUr37qBIoq2WgsW3PWHorJU\nIIpaWxe+ihWo1BbBDYvSIl+oC1pEICgIEYEESYgGQkhmMpn1/P4IGTJbZpLc2e583q8XL5g7dzlP\nEubJufec5wghMGHCBNxwww1xaTgREVG6Ym4mIqJUFbEDSkRERERERCSHiENwiYiIiIiIiOTADigR\nERERERHFBTugREREREREFBfsgBIREREREVFcRFwHVC5tK/bpdDosWLAABQUF8bp8zLndbsyaNQtV\nVVVwuVyYNm0aBgwYgIceeggqlQrFxcWYM2dOopspq2PHjuHaa6/FsmXLoFarFR3rkiVLsHHjRrhc\nLkyePBmjRo1SZLxutxszZ85EVVUVNBoNHn/8cUV+b3fu3Imnn34aK1aswKFDh0LGt2rVKrzxxhvQ\narWYNm0axo4dm9hGd1LbWPfs2YP58+dDrVZDp9Nh0aJFyMnJUUys1HHMzcr4TGuLuVl58TI3Mzen\ncqwhiThZv369eOihh4QQQpSVlYk77rgjXpeOi7feekssXLhQCCHEiRMnxNixY8W0adPE1q1bhRBC\nzJ49W3z44YeJbKKsXC6XmD59urj00kvFgQMHFB3rli1bxLRp04QQQthsNvH8888rNt4NGzaIe+65\nRwghxObNm8Wdd96puFhfeeUVMX78eHH99dcLIUTI+Gpra8X48eOFy+USjY2NYvz48cLpdCay2Z0S\nGOtNN90k9u7dK4QQYuXKleKJJ55QTKzUOczNqf+Z1hZzszLjZW5mbk7VWMOJ2xDcbdu2oaSkBAAw\nfPhw7Nq1K16XjovLL78cd999NwDA4/FArVbjm2++wbnnngsAuOiii/D5558nsomyevLJJ3HDDTeg\ne/fuEEIoOtZPP/0UAwcOxO9//3vccccdGDt2rGLjLSwshMfjgRACjY2N0Gg0iou1b9++ePHFF32v\nd+/e7RffZ599hq+++gojR46ERqOB2WxGYWGhb73FVBIY67PPPotBgwYBaLmjrtPpFBMrdQ5zc+p/\nprXF3KzMeJmbmZtTNdZw4tYBtVqtyMzM9L3WaDTwer3xunzMGY1GmEwmWK1W3H333bj33nsh2iyx\nmpGRgcbGxgS2UD5vv/02unXrhjFjxvhibPu9VFKsAHD8+HHs2rULzz33HObOnYsHHnhAsfFmZGTg\n8OHDuOyyyzB79mxMmTJFcT/H48aNg1qt9r0OjM9qtcJms/l9XplMppSMOzDW3NxcAMD27dvx97//\nHb/+9a+DPptTNVbqHObm1P9Ma8XczNycypib0ys3x20OqNlshs1m8732er1QqZRVA+nIkSOYMWMG\nbrrpJlxxxRV46qmnfO/ZbDZkZWUlsHXyefvttyFJEjZv3ozy8nLMnDkTx48f972vpFgBwGKxoKio\nCBqNBv369YNer8cPP/zge19J8S5fvhwlJSW499578cMPP2DKlClwuVy+95UUa6u2n0Ot8ZnNZlit\n1qDtSvDBBx/g5ZdfxpIlS3DaaacpOlaKjLlZOT/vzM3MzUrC3KzcWIE4PgEdMWIEPvroIwBAWVkZ\nBg4cGK9Lx8XRo0dx22234cEHH8TVV18NADjjjDOwdetWAMDHH3+MkSNHJrKJsvnb3/6GFStWYMWK\nFRg8eDAWLVqEkpISRcYKACNHjsQnn3wCAPjhhx9gt9txwQUX4IsvvgCgrHizs7NhNpsBAJmZmXC7\n3RgyZIgiY201ZMiQoJ/ds846C9u2bYPT6URjYyMOHDiA4uLiBLe069asWYPXX38dK1asQH5+PgBg\n2LBhioyVosPcrJzPNOZm5mYlYW5Wdm6O2xPQcePGYfPmzZg0aRIAoLS0NF6XjouXX34ZDQ0NWLx4\nMV588UVIkoRHHnkE8+fPh8vlQlFRES677LJENzNmZs6ciccee0yRsY4dOxZffvklJkyY4KsYmZ+f\nj0cffVRx8d5yyy2YNWsWbrzxRrjdbjzwwAMYOnSoImNtFepnV5IkTJkyBZMnT4YQAvfddx90Ol2i\nm9olXq8XCxcuRK9evTB9+nRIkoTzzjsPM2bMUFysFD3mZuV9prXF3KyMeJmbmZuVEGtbkmg7yJqI\niIiIiIgoRpQ10YOIiIiIiIiSFjugREREREREFBfsgBIREREREVFcsANKREREREREccEOKBERERER\nEcUFO6BEREREREQUF+yAEsnIarVi+vTpqK2txdSpU7t8vi+++AJTpkwBADz66KPYvXt3l89JRESU\nTpibiZKLJtENIFKS+vp67N27F3l5eXj55ZdlOackSQCA+fPny3I+IiKidMLcTJRc2AElktGCBQvw\n448/YsaMGfjmm2+wceNGPPzwwzAajdi2bRsaGxsxa9YsrFmzBuXl5fjZz36GmTNnwuv1YtGiRfji\niy/g9Xpx9dVX45ZbbvE795QpU3DXXXdBCIGXX34ZBoMB+/fvx6BBg/DMM89Ao9Hg3XffxWuvvQYh\nBIYOHYrZs2dDp9Ml6KtBRESUeMzNRMmFQ3CJZPToo4+ie/fumDVrlu/uKADU1tZizZo1uOuuu/Dw\nww/jD3/4A9555x2sWrUKVqsVq1atgiRJePvtt7Fq1Sps2LAB27ZtC3udHTt2YM6cOVi3bh2qq6vx\n6aef4rvvvsPq1auxcuVKvPPOO8jJycGrr74aj7CJiIiSFnMzUXKJ6gnozp078fTTT2PFihV+2zdu\n3IjFixdDo9Hg2muvxcSJE2PSSKJUI4Twe33RRRcBAHr16oWBAwfitNNOAwBYLBY0NDTgs88+Q3l5\nOT7//HMAgN1ux7fffouioqKQ5x84cCC6d+8OACgqKkJ9fT2qqqpQWVmJ66+/HkIIuN1uDBkyJFYh\nElGCMTcTdQxzM1FyiNgB/ctf/oI1a9YgIyPDb7vb7cYTTzyBt99+G3q9HjfccAN+9rOfIScnJ2aN\nJUoVbe+wAoBWq/X9W61WB+3v9Xrx4IMP4uc//zkA4Pjx48jIyEBZWVnI87cdutN6LY/Hg8svvxyP\nPPIIgJZE6fF4uhYIESUl5maijmNuJkoOEYfg9u3bFy+++GLQ9v3796Nv374wm83QarUYOXIktm7d\nGpNGEqUKjUYDj8cDIUTQndZQWve54IIL8MYbb8DtdsNms2Hy5MnYuXNnh6593nnnYcOGDairq4MQ\nAnPmzMHy5cs7EwYRJTnmZqLoMTcTJZeIT0DHjRuHqqqqoO1WqxWZmZm+1xkZGWhsbJS3dUQpplu3\nbjj99NPx8MMPQ6WKPMW69Q7ppEmTUFlZiauvvhoejwcTJkzAqFGj8MUXXwTtG87gwYMxffp03HLL\nLRBC4IwzzsDvfve7rgVEREmJuZkoeszNRMlFElHcCqqqqsL999+PlStX+raVl5fjmWeewZIlSwAA\npaWlGDlyJH7xi1+0e67NV16LEyY1ll+e77ddq5aQZVBDFYeqYMfs9ehmtODF/1kQ82sRERHFgpy5\n+YMbrgMASADMdg+sRjXOveMuv300GSacNnKEvEEQEVHaiXoZlsB+alFRESorK9HQ0ACDwYCtW7fi\ntttui3gel9kCqdkF7d6LfdsaHQJqLXBVoRPas8/FWUW5HQih4x77rBTNLifWff2xb5tRY8TQ3MGy\nXicvLxO1telz5zmd4mWsypROsQLKiTcvLzPyTgolV26umTwHH26phEol4aZ9ywAAa7/9BlqtGt0t\nRgCA9L0Nbp01qnbFIqfKRSk/99FKp3gZqzKlU6yAcuJtLzdH3QFtHWKwdu1a2O12TJw4EQ8//DBu\nvfVWCCEwceJEX+Wv9phNWqg9TkwbYfZte2m7FY0OgdcqtOj343Y4C/Rw9xvkd5zJoJG1YyogkKXP\n8r1ucDTIdm4iIqJ4kCs33/o/Q9E9U4dssx7WZ1q2rd+fh95ZLlzV/eTIJOEEvjkUfLDRAAwe4LeJ\nOZWIiMKJqgOan5/vG+Izfvx43/axY8di7NixHb6o1GwH3n7N9/o3bgGXV2BPRl9syx+FSyU3YNb7\nHVN7wo4tu2vCnlPuDioREVEykzs3nyLBbHdjyrfvQJIA7Dq5uagvMHpk8O4NwU9FnV43vqzZ4Xud\nzE9EiYgovqJ+AiqXbj8ZjcP/3oC2U7YNGgmGJhvOsFViG0YBbhewa7vfcXkAYDACA84Ied7aE3Z8\nvf9opzuhgckyEJMnERGlg8pCMworGiG5Wl67PV6om5vh+fYgqvoN9O2n1ajQKzcDcLmBHbv8zhGY\niZvcdjRk10e8tspkhPms4V0NgYiIkljcO6D9fnMLvnWYYMrt5rddevs1wOlFo0PgpQP6oOMG5Whw\nca497Hnzso1hn5JG83Q019j+GmkcTkREROlg67l52DRcB+EyAABMWoFJ71UDcGK9cZtvPyEEUC8B\nakASgFp16tZysbYnSgynptIIpwqa7OyI13afOCFfIERElJQi16KOI61KQqY+uJx1o0OgvM4d8fi8\nbCOyzfqgP03NkY8lIiIiYEDGYBi92oj7SZIESQIkqaUz6va0/LF6m7HXcSQOLSUiolQU9yeg7TFo\nJL/iRK1aixS9tBfA3u3BBwIYlA1cfHro80pNTmzfe6pj68yywwM3qtb/FxqNCj1OM7W8EaKQAhER\nUTq5MPcSFB204p1DLcul/epMO0xiXcu/PedFPP499RcIXODNLTwor/vO91qv1qEwu0/QsV6XEw1b\n/uu3jcNyiYiUJak6oGiytgzF7VsEMXKMb/OgHM3JJ6ChF/ttdAiUN0q4uDi48woAWQGbJY8KzcKN\nD3L3QghAI0ktw4Xs+SGPJyIiSkc2p4TVu4y42SXB7GqC8Z1/+d7TqAT0aqC5IB/W4cPaPU+23r8c\nv83ZFHI/XW5e0DYOyyUiUpbk6YD2LQIq9wNN1pa/23RALy404OLC8Ie+tN2KBofApopmXFxoiHip\nAVJvlIuKk68ErF4H9jQfQf9j2XBUn0D/XsHzVFikiIgSZenSJejWLRd9+vTFu+++hXnzFobcz+l0\nYv36DzB+/FVYt24tsrKyMWZMSZxbS0pRaHGjor7l14TvsvpgQMOpJViEANxeCUZnEwzfV4XogApU\n1vivY+crWkREpADMzZ2XNB1QMXIMMHJMyxPQDhqUo8HWIy6U17nb7ai2ulA1HIXNWdCrWxbXfk/9\nBSABepWA+6tvULUr9JNWBxB2yC6LFBFRPLSu+xjKsWNH8c9/rsH48Vfh8svHh92PKBqjerswqvfJ\nUrhnDoEdQ3zvrd5lhM0p4Y7KtwEXsPWw9tS+aPk5NejUfudrdnri0m4ionhjbl6hGeIAACAASURB\nVO6YpOmAdsXFhQaU17lb5oluD16PbFCOJqono57sbETaq9npOTWmN8TaZ0TUOas2foete3+U9Zyj\nBnfHdZeEn9e9bt1afP75ZjQ3N6O6ugp33DEVY8b8DN9+uxd/+tPTUKvV0On0mDnzEXTv3sPvuM2b\nP4bD4cCxY8cwceIkfPLJRzh4cD+mT78HF154EdavX4fVq/8BnU6P3r0L8OCDs/Dhh//C+++/ByEE\nbrttKqqrq/Duu2/B6/Xiwgsvwq23/g4bN27AqlV/h1qtxrBhZ2Pq1Okh2/7WW6vw8ceb0NzcjOxs\nCxYufAqvvbYMlZUHsXz5X+D1etGtWy6uvPIavPDCn/DVV2WQJAnjxl2KCRMmYeHCecjMNOHgwUOo\nqzuGRx6Zg+LiQSGvRRSo7dNRIYCKeo1fBzQUt8freypq91hRVVsW1bVM1mZYDodewkWnVaNPD//h\nvZwzSiQf5mbm5lhQRAcUaDtP1F9rBd2LC+W5TtsEqrHZ0FBRB71Ojdxu4e98EFHystlseOaZ53D4\n8Pd45JEHMGbMz7Bo0UI8/PBsFBUNwKeffoTnnvsj5s9/0u+4piY7/vjH5/F//7ceq1b9Ay+/vAzb\nt3+JN998A8OGDcfSpUuwfPk/YDAY8Pzzz2LNmrdhMpmQmZmF0tKncfz4cSxatBArVrwBrVaLl19+\nET/8UIOlS5fg1VdXQK/X4/HHZ2Pr1i0h293QcAJ//vP/AgDuu+9O7N37DW655VYcPLgfv/71b7F0\n6RIAwGeffYqammosWbIcbrcb06ffjhEjzgUA9O7dG3fe+SD++c93sWbNO3jggYdi+JUmJWl9OppR\nIWBzSb65ogDgGSJBE6LGvtl4qrKuAZGXZGnl0KlhMnUL+Z7N7gxa3oVzRolSH3OzsnNzQjqgOq0a\nNrvTb5vLK2DJOLn+Z2sxokABxYnaCjdPNNQT0a5om0BVLjUyjFrY7C4oqC9PlBDXXTKg3TuisVJc\nPBAA0L17DzgcDgDA0aO1KCpqacvw4SPw0ksvBh03cGDLHUmzORN9+xYCADIzs+B0OlBdXYV+/Ypg\nMBhOnuMcbN26BUOGDEWfPn0BANXVVSgqKoJW2/KZMnXqdOzZsxv19cfx4IN3QwgBu92O6uqqkO3W\naLSYM2cWjEYjjh79EW536OWmKioOYtiwc04eo8GQIWfi4MGDAIAzzjjDF/vXX+/swFeNlMhk0OCE\nteX/QJPTjawojzO7mlqG4raqaAYkAQmnfnY1Qg1dFHkymoJGbbm8AntO3ggOVb+BiLqGuZm5ORYS\n0mvq0yMz6I7lnoq6ln+0FiMKFKI4UbRCDc31eE+DJEkotLiBvh0+JQBAcrth3LMXotmNY3ud2K77\nwe99o0kHe5Mz5LGhhg1Fg0OLiOQVat5GXl4e9u//DkVFA7BjxzYUFAQvF9HefI/TT++FiooDcDia\nodcbUFZ26hwqVcujofz83qisrITb7YZGo8Gjj87EjBn3okePnnj22RehVquxbt1aFBcPwscfb/I7\n//793+GTT/6DJUuWw+Foxm23TYEQApIkwev1+u3br18/vP/+e7juuhvgdruxa9dO/PKX47Fly2ft\nxkDp56yiXN+/N3yjRrPTA7fH63fjNVBzQT4M31chA6fWXbF51YDK4ytcLyDgljzQifZ/5VDZ7WEK\nGoXXeuO67U3tUEu5+MkyoqHBHvU1osHcTCQv5mZlS5rHdnpdy1NR1+BzYQnRyexMcSIg/NBcoKW8\nfEW9BvpOdkA9JzvRhgygyWNFHfwLEekNOjhwKilqVTr0MLQs9RJq2FA0OLSIKPb+3/97BM8+uwgA\noFar8dBDj3Xo+OxsC2699XeYMWMq1Go18vN744477sKGDf/27WOxWHDjjTdj+vTboVJJGDPmIvTs\n2RPXXz8ZM2bcDo/Hi9NP74VLLhkXdP7evQtgNJrw+9//FkIIdOuWh6NHazF06Flwu1146aUXoNe3\n/GI+evSF2L59G6ZNuxVutxuXXDJOkfNJSF652QaYcjKDKtkGsg4fFtRhbB2KO/HMlk7ee+ovAERe\nQzR37brONtdPqKVc/N63mKCRdLJcqxVzM1HsMTcrhyRE4HLRsbd/7YdhO197KuqQYQxODK0dUHHN\nzbK04XDTQby3Jwc2pwTD2R8BANTfXIRCiztiIYVoGY062NvclXV47Oht6gegpQN6RmFOh8/pPnEC\nWedfIEv75JaXl4na2vZ/WVEKxqpM6RQroJx48/I6PpqEgrX9WShbvxKmnDxU1jQGVbONpKsd0KPj\nL/fb3jZ3htORnGqxmFBfH3od0s5ibk4OjFWZ0ilWQDnxtpebk+YJaKvWJ6GBTEJAJfMj6dYqfh4A\n0DrgPuNj7JeAI+rgPnkfkYuzvf1lu3brvJWOkmyNcJlr2t3HZND4DaUiIiKKp8CiRACwtVrbqRu8\nHnjwQ3OVbwRRKIE5lXNCiYiSV9J1QMMljENA+OJEndBLuJF/coKKs8INt+TBt/kmfDrstKB97XDg\nkHQUZ0O+Dqiv4FJHOQBU7A7ebjACA1omLbcWkSAiIoq3tku0tIp2qRaV3R40FLe5IB/Hzixu97jA\nnBrqRnYshZt3yrmhRETBkq4DGo67d39oqw7G5Nw6aGBocqH4oBcbvD+FWuf/BFQM+RhNAFZ/Y5R1\niG6nWEKXooe1IfR2IiKiOGpdoqXVe2qBpoClWkL5ibEvBrgOAW1SrNnVBM+BaqxRnQe1qvPrfMda\nuHmnnBtKRBQsZTqgOPcnsA47P+zbfsu4RKG66SD06lOJMHftOmg8Ahm68FNiW4sWJbQDGgWnx4uv\n9x/lMFwiIkoKGhXaza8A8FmPkfisx0i/bTfveyfs/u2t893eNBdThg1Ntq6NFOIQXyKizkuZDmik\nD/rOzKcMpFefKprQ1nsn54SqdSLkHdyEPxUNkJdt5DBcIiJKGh51M4zDP/K9jrauQkZFS/69csjx\noEJE7a3z3d4NabNJB8nbtfqL8R7iS0SkJKpENyCVFFrcQXdwW5+KRqO1kAIREVEq0GpUaHZ6Qv6x\n2qO78dpH5MKIUx3C1roKcmhd53tTRbMs5yMiothLmSegkeh1atTbHJ0v7oPQxQ8AYJLU8jTRJN7z\n295ckI9luvDDggOZ1GY4PPIufu3jdgG7tvteSk1ObN8bXDVYp1WjTw//ssgskkBEHbFjxza8++5b\nmDdvIa688lKsWfPvsPu+9947uOKKX+HAgf3YvPlj/PrXv41jS6mreuVmhH0v0hqhrc729vcr4te6\nLEtXta7z3d5Q3FiJtpK96sRxiMP/6tQ1hN4Id7/gdQFZ6Z6IQkml3KyYDmj/XtldGobbXJAPw/fR\nP51U2e0t+xcibGEFSZIghP/6aUIYoFZZ5S+cEFCcKMscejeb3Rm0BiuLJBBRR0m+ZbHaXx5rxYpl\nuPzy8SguHoji4oGxbxjFTevTUQBwe7wwG7UxuY7Kbsfp6zbCG/CzdomkwSUAGp1eAIBUcXJQV98i\niJFjYtKWVlHf7Db26PxFrA2AOfg6nGJDROGkSm6O2AEVQmDu3LkoLy+HTqfDggULUFBQ4Hv/vffe\nw/Lly6FWq3HNNdfghhtuiGmDY8U6fBisw4eFfC/UItqtT0pDlZuPJBF3a4mS3dvfrcWOH7+W9Zzn\ndD8L1wwYH/b9devW4vPPN6O5uRnV1VW4446pGDPmZ/j2273405+ehlqthk6nx8yZj8Dr9WLu3EfQ\no0cPHD58GGecMRQPPPCQ3/lqao7gscdmIjc3Dz/++CPOP380fve736Om5ghKS/8Aj8cDSZJw990P\nYMeObXC73bjhhpvw9NOl0Gp1uPvu+/Haa0vRq1c++vcvwp/+9DQAICsrG7NmzUZ5+V787/8+D51O\nh1/96mr84heX+647e/bD6N69B3744QguueQXOHhwP779thyjR4/B1KnTQ8bkdDbgt7+9HRbLabjg\ngjE4++xz8Nxzf4QQAnl5eZg9ez4OHz4U1A5/LdMSysq2Y9myVyCEgN3ehDlzFqCsbDuOHTuGOXNm\nYeLESb47s+vXr8Pq1f+ATqdH794FePDBWfjww3/5fS9uvPFmXH55+O9dukuG3Nz26Wi0T0M7qvXm\ncOB8IYEwczibrEDlfiDGHVCidMHczNwci9wcsee0YcMGOJ1OrFy5Ejt37kRpaSkWL17se3/RokVY\nt24dDAYDrrjiCowfPx6ZmZntnDF29Dp1yMIAHa2QG4odDr9hQ63Dco/03Qx939AFFYxGHewB7XF4\n7Fi7N3S5diKKP5vNhmeeeQ6HD3+PRx55AGPG/AyLFi3Eww/PRlHRAHz66Ud47rk/YsaMe05+4C+G\nTqfDddddiePH63DaaTl+56upqcGzzy6GyWTC9Om/xbff7sVrry3DdddNxpgxJdi371s88cTjWLjw\nKSxcOA833HATDh2qhMPR8pmyZcvneOqpP+Pee6dj1qw56Nu3EGvXrsHf/vZXjBp1PlwuJ5YsWR4U\nx5Ej1fjTnxajudmOiRN/hTVr/g2dToeJE/8HU6dODxnT7NmP4Pjx41i27O9Qq9X4zW8mY968UvTp\n0xfvv/8eKioO4JlnngzZjlNa7rIePHgAs2c/jm7dcrFixTJs2rQBU6b8Bn/961L84Q+l+PrrnZAk\nCQ0NJ7B06RIsX/4PGAwGPP/8s1iz5m2YTCa/78XMmfeyA9qOVMrNXRHu5rDDY/cVJfrbyWJE00aY\nZVsrnIgSi7lZ2bk5Ygd027ZtKCkpAQAMHz4cu3bt8nt/8ODBOHHihO+R76lHv/EXrlJuVyvk9hG5\n7RZMaJIcOISjfnNciKhjrhkwvt07orHSOvSke/cevkRz9GgtiooGAACGDx+Bl156EQCQn18Ag6Fl\n6Hxubh4cDieefHI+Dh/+HqedloPf//4uDBhQDLO5ZQz8GWcMxaFDlTh0qALDh5/ju15t7Q8nr9eM\nPXt2o2/ffvjxxxrs3fsNzGYzTCYTKisP4plnngAAuN1u9O7d8nSrT5++IePo1SsfJpMJGo0GOTm5\nvja0JqFwMZ1+ei+o1S1TBerq6nznv+KKXwFA2HYEysvLw7PPPgWTyYTa2h8xbNjZJ98REOLU06rq\n6ir061fk+zoOH34Otm7dgiFDhvp9L5zO5KksnoySLTe3HY4LxHZIbrpzerzYsrsm6v0zs0+g8YT8\n9Sc4FzU9MDczN8ciN0fsgFqtVr+7phqNBl6vFypVy4CY4uJiXHvttTCZTBg3blybL6xyBBZQAACT\naBmC+yvPeZ0qqNBauS8WOjq/1OtyomHLf4O2szgRpYNQv5jn5eVh//7vUFQ0ADt2bENBQZ+gfVo/\nuGfOfNS3rabmCCoqDsLhcECj0eCbb3bjiiuuRN++/VBWth0XXngR9u0rR05Oy5zt0aMvxOLFz+H6\n6yejpuYInn32KVx55TUAgD59CvHoo/PQvXsPfP31TtTVHTvZ3miKlwcPTwwXU9v4c3PzUFV1GPn5\nvfH6639FQUHfsO0IvNaTTy7AqlVrYDQasWDBXN/XR6VSwes91TE5/fReqKg4AIejGXq9AWVlodsS\nKgY6Jdlyc2CxokhDcgNHFbUn2iVbFCeguGCrPIMRGHBG1KexZBqg8njlbBkAzkWl2GJuVnZujtgB\nNZvNsNlsvtdtE1x5eTn+85//YOPGjTCZTHjggQfw73//G5deemm758zKMkJnMXWx6dHLOc2BZqfb\nb5tXpYJQqeDxeJFp0nX4nJIkQWpqQt77/8IktJR/z0BwpbvAlC/gxa0eNVyezn0D92cX4r89R4V9\nv8Hhxb7jHvzPmaGHHAuVBEvg194S+q6N83g98vI6NmSro/unMsaa+jIzDTCZdMjLy4TT2TJcPi8v\nE6WlC7FgwQIIIaDRaLBgwQJIkgSdTuP7Wuh0GnTrluH3tXE6G6DX6zB//qM4evQoLr/8MlxwwTko\nKJiFxx57DG+99Q+43W48+eQTyMvLxFVXjceyZa/g1VdfwY8//ogXX/wzrrzyl7BYMjF//h/wxBPz\n4PF4oFKpsGDBAvzwww8wGLRB3w+ns8HXNqfTCbVa5dtHpZLCxtQaR+u+CxfOR2npfKhUKnTv3h3T\np0/F4MH9222HStVyrauvvgp33fU7mEwm5ObmwmY7gby8TJx33ijMmnU/ZsyYAYNBiwEDCnDPPXfj\n3nt/D7VajT59+uD223+N999/3+970TYGChaL3Nz26200apFh7nyhPL2hGUZ96F8x+nt6oML7Y1Tn\nscGBw9IxjNYP9n/D7YH5ZIEelWRDg8OLJTtsuNHpRYarCc7Vf4VRG/oXQjsAdch3Ok/dvxi6n/xU\n3pOae4Xc7G080eHfoYLyvgy8Sfp/NBnbFCtKjZW5Wfm5WRJtn7+GsH79emzatAmlpaUoKyvD4sWL\nsWTJEgBAdXU1ZsyYgTfeeANarRYLFizAwIEDMXHixHYvun/th0GVWOOtvO47ZOhMqKxphEHX8VRk\n3vmVr2puk2+ZFv9OX0sVXP8vr4CAWupk8eEmK2AyQ1xzc9hdXmozFyYUm92JMwpzQr4XyH3iBLLO\nvyDq5uXlZaK2NjaFKJINY1WmrsZaU3MEc+c+gpdeWipjq2JHKd9bpf4S1p5Y5Oa2Pwtl61fClNP5\negWdza2BQhUBBPzngG6qaEZ5XctN5tE1X6L/iQpIEpCpC90BVakkeL0yPmGPIjfLytoAnDki6t0t\nFhPq65tkb8YJqwPnD+0p+3m7QimfadFgrNFjbk6M9nJzxJ7QuHHjsHnzZkyaNAkAUFpairVr18Ju\nt2PixIm47rrrMHnyZOh0OvTp0wdXX311xAapTMaQS394XU7oclOjQE/bwgjhEmSoIkRNHisMKiN6\nGPI7fE05iitEu3YZAEi2RrjMXZ9nwnkiRETyikVubksY9EBDwDQRlxvoZpErBNlcXGhoU1V+bMQb\nsUazHlYZh4+y8BERUcdE7IBKkoR58+b5bevXr5/v35MmTfIlwGiFm1cYah6i0pjUZjg88hcDaKvB\nIbCpojnkPNAOVQP2aEOuQRZOuHkmnCdC6aJnz9NT5g4rpbZY5Oa2PAMLAX2W/8Ydu0LumwgeeHC4\n6aDfNq1K57u5216dBZVkg7f9wV8Ryb6WNxHFDHNz8unkWFDlUFrlvkE5Gmw94pJnndHAAggdLHxA\nRETpKTC3AvLmV5M6+Olm683dQTka35DcWEj4Wt5JkpvbVuPlSCci6oi074B2tHJfsru40CBf4rV0\n839tbZDnvEREpGiBuRWIX371H5IbzNzFIbixqmAftSTJzXnZRt+/OdKJiDoiqTqgrXNDU2kuaNw1\nWUPPN+lbBDFyTPzbQ0RE6cFoCJ4XCiTt3NC4Ym4mIopaUnVAW+eGJnIuaKhhQ20ldIhu3yKgcn/w\n9iZry/YkTXKhFs3mcB0iohQzeEDo7VHODY2UX0MRJ6dZhjsuUTm57RzT0YY+KHJWAE7/GghmVxOs\n+/bhb5K862lz/ikRpbqk6oAmg1DDhtoKN4Qo1KLaKpcEr/pUoYOuLqYtRo4J2ckMddc1XAGGRCSu\ntsN0WnG4DlH8LF26BN265aJPn7549923MG/ewpD7OZ1OrF//AcaPvwrr1q1FVlY2xowpiXNrSaki\n5ddQNI0tC6D37Rm6nH8ips0EzjH9vOe5+LznuUH73fTtm7JfO+HzT4lINumcm9kBlUEfkYtD0tF2\n92mSHDiEozgbne+ARitcAQYmLiKSJCnse8eOHcU//7kG48dfhcsvHx/HVhGF1yia8UlzOUoMgxLd\nFACR55i2kipa1iENtxxMZyR8/ikRxUS65WZ2QDso1BCiAZ4CnG0M7li2XQc08OloLIVLjl1OXIGV\n9wI4M3SAzRn2/ba0zS40WKOfM6QyGcMu30PKULt6JRq/3CrrOTPPHYW8ieGXoli3bi0+/vg/aGpq\nQkNDPe66606cc85obN36X7zyykvQ6/XIzs7GQw/NxsKF83DLLbdh0KDBuPHGCZg6dQYuumgs7rtv\nBmbNmouvvirDqlV/h1qtxrBhZ2Pq1OlYunQJdu36Cna7HQ8//Bj69Cn0XXfz5o/hcDhw7NgxTJw4\nCZ988hEOHtyP6dPvwYUXXoT169dh9ep/QKfTo3fvAjz44Cx8+OG/8P7770EIgdtum4rq6iq8++5b\n8Hq9uPDCi3Drrb/Dxo0bgtoRyltvrcLnn3+MxkYbsrMtWLjwKbz22jJUVh7E8uV/gdfrRbduubjy\nymvwwgt/wldflUGSJIwbdykmTJiEhQvnQavV4siRI6irO4ZHHpmD4uLk6CCQchRre2K7swL7XDVJ\n0wFNOjLm5g5jdXzFY25mbo6FpOyAthYjCpQMxYnkqOwXuH5Z27XLklpg5b0AKrMekKIbWivUTmiy\ns6O+dKifByI5OBzN+POfF+P48TpMm/YbvP76W1i0qBQvvfQqunXLxZtvrsRf//oqfvrTi/H5558i\nKysLWq0OX365BSNHngun0wmdToelS5fg1VdXQK/X4/HHZ2Pr1i0AgMLCfrjrrvuDrtvUZMcf//g8\n/u//1mPVqn/g5ZeXYfv2L/Hmm29g2LDhWLp0CZYv/wcMBgOef/5ZrFnzNkwmEzIzs1Ba+jSOHz+O\nRYsWYsWKN6DVavHyyy/ihx9qwrYjUEPDCfz1r39FbW0j7rvvTuzd+w1uueVWHDy4H7/+9W+xdOkS\nAMBnn32KmppqLFmyHG63G9On344RI1qGG/bs2QsPPjgL//znu1iz5h088MBDMfouUVILV5yoMwIK\nGpUYBmGfqybs7q03hd0eL1S64LVBQ9F7dXA0x6hD1kYv0TISqTrW+V7G3NxhJyvwhqr1IBfWjEhP\nzM3Kzs1J2QEN96QrkcWJ5BS4flnr2mVdEq4CXxs3nSyQ0DosyIdV+igJ5E2c1O4d0Vg5++wRAIDT\nTstBdnY26uqOISMjA926tfzCM3z4OViyZDFuueU2PPTQfbBYTsNNN92ClStfx3//+xnGjLkIVVXf\no77+OB588G4IIWC321FdXQUA6NOnb8jrDhzYckfSbM5E376FAIDMzCw4nQ5UV1ehX78iGAwGXxu2\nbt2CIUOG+s5XXV2FoqIiaLUtBVimTp2OPXt2h21HII1Gi/vuuw+SpMHRoz/C7Q69fFNFxUEMG3bO\nyWM0GDLkTBw8eNAvhu7de+Drr3dG+RWnVGDUGNHgiHJ5j37dgzY5vW7kGnM6fuEoCxq1ar0pXFnT\nCEOItUFDMWp0gFrd4aZ1lISWIXV69ak6CLLk+yQUqtaDXFgzIrGYm5mbYyEpO6DUQeGq40YjQRV0\nXV6BPRV1vtd6nRr9e0X/RJRILuXlewAAdXXHYLVakZfXHU1NNtTVHUNOTjfs2LEdBQV9YDabodcb\nsHHjh1iw4Cls2rQBb765Eo899jhMpgz06NETzz77ItRqNdatW4vi4kH4+ONNkCRVyOu2N9/j9NN7\noaLiAByOZuj1BpSVbUNBQR8AgErVcr78/N6orKyE2+2GRqPBo4/OxIwZ94ZtR1v793+HTz75D955\n5y0cPlyL226bAiEEJEmC1+tfybNfv354//33cN11N8DtdmPXrp345S/HY8uWz9qNgVLb0NzBXTr+\ny5odMrUktansduSuXed7LSAgSZ9EdzBvDlMaY25Wdm5mB1QG4UrLC5UbjpPbA0vJy1k6Plx13EB/\nOzkHtG1BhEhPTWPFkqH3e22zx344FFEox44dw913/x5NTVbMnTsXkiRh5sxHMWvWg1CpVMjMzMQj\nj8wFAJSUXIQPPliLzMxMnHfeaLz77pvo1atlON3119+IGTNuh8fjxemn98Ill4zrdJuysy249dbf\nYcaMqVCr1cjP74077rgLGzb827ePxWLBjTfejOnTb4dKJWHMmIvQs2dPXH/95Ijt6N27AEajCZMn\nT4bT6Ua3bnk4erQWQ4eeBbfbhZdeegF6fcv/0dGjL8T27dswbdqtcLvduOSScUk5n4Qo2TQX5MPw\nfeinHBEl+fJqRLHG3Kzs3CwJIUTk3eRVW9u5sukNW/7boXmD7Smv+w4ZOpMs5wonw2yAzdoMAFja\n+BEA4NbMnwI4OVxI1zIEyOGxo7epX0zbApwqQhSqAyquubnL5zeb9bB2cqiMze7EGYXhh2u5T5xA\n1vkXdLZpssvLy+z0z3GqUXKs69atxaFDlb5iAEqONRSlxJuXF3qJDuoYOX8WvqzZgSx9VscP3LEL\nyPIfShuYP0Npm1MjaVsgMN6izffhcnOoPB5JV3JzRNYG4MwRsTn3SSesDpw/tGdU+yrlMy0aSo6V\nuVkZ8baXm/kElIiIiChFhFvnOxyVZIM3Bs8aBuVocDFrAxFRJ6RUBzRcddzOkKw2QOM/njqw+h4R\nKZtS1tMiovQQbp3vePOtK84OKMUAc7PypVQHVM51IN01eiBweFAHq+8RERGRjEIt6SK8gCp0wZB0\nE26d7/bEYghul9cVJ6K0llIdUCVpW7jI4fHAJsk3H8XlFUFFfpJdYFXcQKoTxyEO/0u26+m0avTp\n0YV5Y1lGNDQos5x+EMaqXEqJN8uIvIsuTHQrSA6DBwRv2/ElGkWzby4oABRre6LEcKrgRmAxQDkL\n/VE73C5g1/aYXkLb7EKDNcrRaUr5TIsGY1UupcTbTm5mBzSOGkUzPmkuR4lhkG/tMgCwOdUYlNOJ\n9dLCaK8jFzh35CanF2ZXE6wrlwftuz+rEJ/3PDfq64abZzIoR4OLCw3tHhuxw2zsEXU7omGzO7tU\n0EpnMUEj6WRsUfJirMqllHh1ltgWlKOOC1xHtNPrggIoRjfsk07lNatwYJ+rxq8D2janAi1FiVJe\nuPW9k2l5Fku3mF/CKTmw73jwSgNttS7lppTPtGgwVuVSSrzt5WZ2QOOkWNsT250VQUkTANzCg/K6\n72S71hGHFZmSET0M+X7bQ80d2Z9ViKKGiqBzmF1NKGqo6FAHNBTfPJHCfX7N7QAAIABJREFULp2G\niIhSSOA6ol1ZF7QE/VCSeZbvddsnoYoVbn3vNFyeJZoRXVzKjSi1sAMaJyWGQdjnqgn5XrZe3iUE\n9GoPXN7gD+PQc0fGhjyH9PZryETXS71znggREVHHhFvfO1FrdxMRyYkd0LZCFT9oD6vmEhERJZ3A\nOaFtCZUbjjDvRauzc0w98OBw08FOX7eXaBnFVN2Bc+i9Ojia5X1C6PGeBgBdikVOzU4PVHV1MDl0\naLKl1tNQvVqHwuw+iW4GUVylbQc05PyUUMUP2sOquURERLEVdHP4ZK2BcDeMXW70yg1/czjDbIDN\n2tylJnV2jqlJHf2oolAkSAAAvdoY9TFGjQ5Qq7t03aB2SB1vRywJtQcZOhMy9AZIrq59b+PN5mxK\ndBOI4i5iB1QIgblz56K8vBw6nQ4LFixAQUGB7/2vvvoKTz75JAAgNzcXTz31FHS65J84K+f8lGSj\n1ahQ3+wGWJeDiEiRlJqbQwq8Obx7Z8vfQ88MvT9vDhMRJbWIHdANGzbA6XRi5cqV2LlzJ0pLS7F4\n8WLf+7Nnz8bzzz+PgoICvPnmm6iurkZhYWEs20wR9MrNgLXKluhmJLVIy75EYsqwockm77pqyYqx\nKleyx9ta2ZKCMTdTotmcElbvankCWmhxY1RvV4JbRESpImIHdNu2bSgpKQEADB8+HLt2nbqzePDg\nQVgsFixbtgz79u3D2LFjmeCUJLAEfDKVfu+irq6TajbpIHmDl5xRIsaqXMkeLytbhsfcnL5Udjty\n167zvW4uyId1+LC4tqHQ4kZFfcuvkDanhIp6DTugRBQ1VaQdrFYrMjNPVWnVaDTwer0AgOPHj6Os\nrAxTpkzBsmXL8Nlnn2HLli2xay3FT98iwNRmrkpr6fdOaF17tO2fTRWpNUeDiCiZMDenp+aCfHiN\np+Zdqux2GL6vins7RvV2YeKZdkw8044MXfLexCKi5BTxCajZbIbNdmo4p9frhUrV0m+1WCzo06cP\n+vXrBwAoKSnBrl27cP7557d7zrw8eZcdkUNmkxEWY8cmTToy9FCZDe3uk9HmfZVNCtoWKzqDFmZz\nF57y/fQSAJf4Xtr/9hcAgDHCOQOveVZPN3b/4D/Er8Hhxb7jHvzPmV17CploXfr6phjGqlzJHK9Q\nSbC0s5B1Oku13NzTlQOby+577fK40N2c26lznYoz9M9GR3NzZ2SanXC6vV06R2c0nnM26ocNQ6ap\nZT6v+c33IAEwGtuf3xvp/a5oLUgUy2tEIlRu3/c0Hr9jyUk43J3+nEunz8d0ihVQfrwRO6AjRozA\npk2bcNlll6GsrAwDBw70vVdQUICmpiZ8//33KCgowLZt2zBhwoSIF62t7Vz1uFhqbLBDcnSwpLpX\nAqqPhn3bmKGHvc38Ki9akpWtnWMiinLpF2ezK2hNzq5oHabX3jlDrQM6ppcGY3r5/5i9tN0KrxCy\nti/eQsWqVIxVuZI93ia7E/X1kStEKj1Rh5Jqubm3ti/QJsV+WbMD9e7OVf9sfdIb9mfD5gDU4fO5\nHFVwc8yJ62xV1jTCfnJ4eoZoyc32doarG426dt/vKiHUEdsQaw6nBzZrsyzf23hrckb3ORfIYjF1\n6rhUlE6xAsqJt73cHLEDOm7cOGzevBmTJk0CAJSWlmLt2rWw2+2YOHEiFixYgPvuuw8AcM455+Cn\nP/2pTM2Or8BlWQI5vW7kGnP8N0ZYtkVvMcHe9gdo9040Oq34pHsjSvJHd66hrO5HRJT20iU3h2N1\n2rB09+t+24ot/Vtya4Q1vb0eV0snVU5cF5yIKGoRO6CSJGHevHl+21qH9QDA+eefj9WrV8vfsjgL\nXJYlkBzLtBRb+mP7j19hX/2BzndAo6TVqkMW8HB5RZcL8BARUWKlS24OpdjSH/vqD/htszptp3Jr\nR28Oy4E3hxPK7fGisqYRekMzHM2pVQzJ4bHD29DxqvzJXsVcTukUK5D88cpRoT5iB5TkU5I/Oihp\nxkpOtg4qKfgD7WitFdamji9I3Uu4AQDVTQfD7qP36uBojjwEx+M9DQBwuJ1zJbtoY00mWpUOPQz5\niW4GEVGXlOSPDrqJG/g0lNKL2dgy5Nqo10Dyxn9ubldIHjUyOjF/NtmrmMspnWIFkj9eOSrUswOq\nUNn60MUk9GoP9OqOd0AlSFDZ7chf95/w+0gShIj8H+YW18liTJXR/+dKRJn59hg1OqATX8dEcnjs\nkXciIiIiIoohdkApKs0F+bKWehcCsJ3siAKARiWgD9Ofay0zn0wdUCIiomQQuC5oIEmSfMWK5NZc\nkA+o26+uTEQUiB1Qiop1+LCIHcBoK+1tPaz1LWANtCxinaETmHhm6Cd07SVWIiKidCX3zeGO8K1B\nWpiQyxNRCmMHNNWEq+6XQhX4RvV2YVTvU0UCVu8ytrM3EREpTaTK822FrEJPAOS9OdxRbW8O25xS\nzHJ5ocXt9zsDEaU+dkBTTbjqfqzAR0REKSJS5fm25KhCH3MKuDncWYUWt9+oJjnZnBIq6jXsgBIp\nDDugRERERF2RxjeHA0c1yYkjpIiUiR3QKEUaLsQhQkRERERERO1jBzRKkYYLpcQQISIiIiIiogRS\nJboBRERERERElB74BDQBrE4blu5+3fe62NIfJfmjE9iixGuvgt7NJ9cLlXMuCKvqEREpS2BuDUel\nUsHr9cahRQDgAhpPrXldrO2JEsOgOF2biCg58QlonBVb+sOsy/C9tjpt2Fd/oOsnbq3AF+GPxmaD\nKuCP+sSJrl+/CwotbmToYrNIdiitVfWIiEgZAnNrMrIKB/a5ahLdDCKihONv4XFWkj/a72lnNHdr\noxKuAl+Ahoo6ZBi1ftuMe/bK04ZOilRBL6OipXM68Uy7LNdjVT0iImUJzK3tsVhMqK9vinGLTtr7\nHWBvBgAsxZeAEKGXawklzBIuWo0KzU5P1E0QKjccHdg/Wl4hoJKkyDsSEQVgBzTN6HVq2Oz+nT21\n0wO3tuvJKVySc3u8MAd0eomIiBSv7c3h3Ttb/h56ZnTHhlnCpVdux570ZpgNsFmbO3RMNNyyn5GI\n0gU7oGmmf6/s4I3HzUCWucvnDpfkKmsau3xuIiIiIiJKfZwDSkRERERERHHBDigRERElLaPGiKP2\nukQ3g4iIZMIOKBERESWtobmDoVNxxhARkVLwE51SgspuR+7adbKcq3Vd0dbqup0hSRIyRPyWjpGD\ngIAkfdLh4+wqCZI3tWLtrHSKFUj+eDOEwBFN5Puklv93fxxaQ0SB5MzNoXQ0XzM3K1M6xQokf7xy\n5GZ2QGVi1BjR4Gjw2ybsLjQ6Ti0d4vS6kWvMiXfTUl5zQT4M31cluhlERER0ki0/H+bq6kQ3g4hS\nEDugMhmaOzhoW15eJmprT1WA/bJmRzybFD2jIfS6ZGHWIIs36/BhsA4fJtv5WtcB7cq6okajDna7\nU64mxYXDY0dvU78OH2c062G1OmLQouSTTrECyR+vze7EGYW8aUdpKslzc/2ZZ6J5xPCYXmP1LiNs\nTgkZuvafBhVa3BjV28XcrFDpFCuQ/PHKkZsjdkCFEJg7dy7Ky8uh0+mwYMECFBQUBO03e/ZsWCwW\n3HfffV1qECVA23XK2gqzBpkS2JySryPaGZIkQQi1jC2KPSEMUKuiXAC9DZVkgzfFhjR1VjrFCiRX\nvINyNLi40JDoZqQM5uY0kIa5OVChxY2K+vZ/VbU5JVTUazCqt6vd/YgoeUTsgG7YsAFOpxMrV67E\nzp07UVpaisWLF/vts3LlSnz77bc477zzYtZQJbM6bVi6+3VZz1ls6Y+S/NGynlMpokloRETJjLmZ\n0sGo3q6IHcuu3EwmosSI+Fv4tm3bUFJSAgAYPnw4du3yv/O2Y8cOfP3115g0aRIOHDgQm1YqWLGl\nP/bVy/t1szpt2Fd/gB3QMKJJaJGk0zAfc5IPBZFTOsUKpF+8SsLcTEREqSpiB9RqtSIzM/PUARoN\nvF4vVCoVamtr8cILL2Dx4sX44IMPYtpQpSrJHy17R1Hup6ldpdWo0Oz0+G1ze7wwG7UJahERUWpj\nbiYiolQVsQNqNpths9l8r1sTHAD861//Qn19PW6//XbU1tbC4XCgf//+uOqqq9o9Z15eZrvvK0nb\nWDObjLAYTTG/Zuv3x2Lp2rUcGXqozB2bk5URYv/iENv2H66HUZ/aw2CNRl2im9Axbg/MZn2nDu3s\ncakonWIFkjteoZK6/DmmVOmWm+XOn4n4uUq23NxVekNzUuRxSWpZqqU1JzM3K1M6xQokd7xy5OaI\nnxwjRozApk2bcNlll6GsrAwDBw70vTdlyhRMmTIFAPDOO+/g4MGDERMcAL/KsEoWWAW3scEOyRH7\np35erxcAUF/f1LUT2RyAOvr2ZpgNsFmbo9rX0eyCdLKdqSg1h+A6YVV1fLhlOg3TTKdYgeSPt8nu\njOpzLB07qemWm91NwKGGGt/rrixrZrGYup4fOyEVcnNHeN0eHG9umc6SyFFNrQUB7XYnc7NCpVOs\nQPLHK0dujtgBHTduHDZv3oxJkyYBAEpLS7F27VrY7XZMnDixA80lIiIiOaRbbg5c6ixplzVLI71y\nM3z/rqxJ3psXRJR8InZAJUnCvHnz/Lb16xdcyOTqq6+Wr1WUHALXIEuStceIiNIdc3NqkqXqveQG\nGtosnyQEcHJ4bygqmwSvN7bLLbkNAidHwsadZ0jLhd9TC6hcErzq5Fhaqo/Ixdne/oluBlFSSvzg\nfUpegWuQpdHaY0RERHKSreq9NuBXNyfXvySi1MIOKBEREVGMxaLqPYCWm8OZ5rBvx2oOaFuVNY0w\n6NQxvUY4q79pWQf0V2faU3IOKFE6Cj9mg2Rn1Bhx1F6X6GYQERERERElBDugcTQ0dzB0Kj50JiIi\nIiKi9MTeECWEVqNCs9Pje53IEu5ERERERBQf7IBSQrQt3w6whDsRERERUTpgB5SiF7gsSwCvx9Wy\nQHYnaGw2qFzhCxhIbjc82dmdOjcREZFixTA3R5Qky7PZnBJW7zJCkiQIkZhiSJ0lhAFqVfjvXzgq\nyQavSI4lZ2ItnWIFkiveQTkaXFxokP287IBS9AKXZQmgt5hgr2/q1KkbKuqQ0c4QXOOevZ06LxER\nkaLFMDdHlATLsxVa3Kio56+zRKmE/2MVSpbFrjtIpVLB6/V26liX2wtVQ/hVrKVMF0SiVrkOgYtd\nExERJd6o3i6M6t2yFmoqLsPi8NjR29Svw8eZzXpYrTF6sp1k0ilWID3iZRVcBSq29IdZlxF5RyIi\nIiIiojjiE1AFitli1xFYLCbUd3KYz54ohuB6M5KnU52Kd1mJiJTCqDGiwdHgt83pdSPXmJOgFqW3\nwMr2cmKVfCLlYQeUiIiIUsrQ3MFB276s2ZGAlhAQXNleTqyST6Q87IBSUtDr1LDZXWHfVzs9cGvl\nu7vKO6pERERERPHHDmicGTVGHLXXcZhQgP69IiyxctwMZJllux7vqBIRERERxR+LEMXZ0NzB0KnY\n7yciIiIiovTDDigRERERERHFBTugREREREREFBfsgBIREREREVFcsANKREREREREccEOKBERERER\nEcUFO6BEREREREQUFxHXAxFCYO7cuSgvL4dOp8OCBQtQUFDge3/t2rV47bXXoNFoMHDgQMydOzeW\n7SUiIkp7zM3BjBojGhwNEfcTdhcaHfY4tCiY0+vmOuBElPYidkA3bNgAp9OJlStXYufOnSgtLcXi\nxYsBAA6HA8899xzWrl0LnU6H+++/H5s2bcLFF18c84YTERGlK+bmYENzB0e1X15eJmprG2PcmtC+\nrNmRkOsSESWTiB3Qbdu2oaSkBAAwfPhw7Nq1y/eeTqfDypUrodPpAAButxt6vT5GTVWOwLu0vCMa\nf1qNCs1OT6ePFyo3HF04PhEcHg9skrPDxwmVhCZ7x49LRekUK5D88ep16kQ3IWkxNxMRUaqK2AG1\nWq3IzMw8dYBGA6/XC5VKBUmSkJPT0nFasWIF7HY7fvKTn8SutQoReJeWd0Tjr1duRpeOzzAbYLM2\ny9Sa+LA51RiU0/EbHRaLCfX1TTFoUfJJp1iB9ItXSZibiYgoVUXsgJrNZthsNt/r1gTXSgiBRYsW\nobKyEi+88EJUF83Ly4y8k0JEE2tmkxEWoykOrYk9iyU2cTgy9FCZDTE5d2dlJFl7IhEOd6e/P7H6\nviajdIoVSL94lYK5uWsSFWui8n0q52a9oRlGfcRfV32MRl0MWxMDbg/M5s6NUOjscakonWIFkjte\noZK6/JkS8X/0iBEjsGnTJlx22WUoKyvDwIED/d5/7LHHYDAYfHNPopGouRfxFu08k8YGOySHNg4t\niq2YPk3xSkD10dicuxOMGXrYbY5EN6ND7G47jjYf6fBxWVlGNDQkpmBHvKVTrIBy4s3KMia6CXHH\n3Nx5iZwDmoh8n+q52XPMCkeUw/GNBi3sza6Ytkdubo8D1qbaDh9nytChyZa8UyjklE6xAskfr73Z\nhaM6d8T92svNkhBCtHdw20p7AFBaWordu3fDbrdj6NChmDBhAkaOHNlyMknCzTffjJ///OftNohJ\nzt+XNTuQpc+KQ4tiK52G86VirA2OBpzb85wOH5fIX9biLZ1iBZQTbzo9uWvF3Nx5iS5CFO98n4r5\nqq09FXXIMEbXaTebDbCm2PSYJrcVAzOHdvi4VP++dkQ6xQokf7wnrA6cP7RnxP3ay80Rn4BKkoR5\n8+b5bevXr5/v3998803EBhAREZF8mJspXeh1atjs7T/VdHm8sCTxkEUi8hf9oHoiIiIiojjq3ys7\n4j57Kuri0BIikosq8i5EREREREREXccOKBEREREREcUFh+AmAaPGiAZHg6zndHrdyDV2fM1HIiIi\nIiKiWGEHNAkMzR0s+zm/rNkh+zmJiIiIiIi6gkNwiYiIiIiIKC7YASUiIiIiIqK4YAeUiIiIiIiI\n4oJzQImIiIjiIBZFByMRdhcaHfa4XjPe7B4bJLcGcLrQ5HYkujkdolcZEt0EorhjB5SIiIgoDmJR\ndDCSvLxM1NY2xv268eQ5VoNssx4Wiwn16qZEN4eIIuAQXCIiIiIiIooLPgElIiIiopRlMmhwwuqA\nV61CozW1huB2FmNVrmSP12ToeveRHVAiIiIiSllnFeUCSI/hxq0Yq3KlQ7zsgCoUCx3EVirGatQY\nE90EIiIiIkpz7IAqFAsdxFY6xUpEREREJBcWISIiIiIiIqK4YAeUiIiIiIiI4oIdUCIiIiIiIooL\ndkCJiIiIiIgoLtgBJSIiIiIiorhgB5SIiIiIiIjiImIHVAiBOXPmYNKkSbj55pvx/fff+72/ceNG\nTJgwAZMmTcLq1atj1lAiIiJqwdxMRESpKmIHdMOGDXA6nVi5ciXuv/9+lJaW+t5zu9144oknsHz5\ncqxYsQJvvPEG6urqYtpgIiKidMfcTEREqSpiB3Tbtm0oKSkBAAwfPhy7du3yvbd//3707dsXZrMZ\nWq0WI0eOxNatW2PXWiIiImJuJiKilBWxA2q1WpGZmel7rdFo4PV6Q76XkZGBxsbGGDSTiIiIWjE3\nExFRqtJE2sFsNsNms/lee71eqFQq33tWq9X3ns1mQ1ZWVsSL5uVlRtxHKdIpViC94mWsypROsQLp\nF69SMDd3TTrFCqRXvIxVmdIpVkD58UZ8AjpixAh89NFHAICysjIMHDjQ915RUREqKyvR0NAAp9OJ\nrVu34uyzz45da4mIiIi5mYiIUpYkhBDt7SCEwNy5c1FeXg4AKC0txe7du2G32zFx4kT85z//wQsv\nvAAhBCZMmIAbbrghLg0nIiJKV8zNRESUqiJ2QImIiIiIiIjkEHEILhEREREREZEc2AElIiIiIiKi\nuGAHlIiIiIiIiOKCHVAiIiIiIiKKi4jrgMqlbcU+nU6HBQsWoKCgIF6Xjzm3241Zs2ahqqoKLpcL\n06ZNw4ABA/DQQw9BpVKhuLgYc+bMSXQzZXXs2DFce+21WLZsGdRqtaJjXbJkCTZu3AiXy4XJkydj\n1KhRiozX7XZj5syZqKqqgkajweOPP67I7+3OnTvx9NNPY8WKFTh06FDI+FatWoU33ngDWq0W06ZN\nw9ixYxPb6E5qG+uePXswf/58qNVq6HQ6LFq0CDk5OYqJlTqOuVkZn2ltMTcrL17mZubmVI41JBEn\n69evFw899JAQQoiysjJxxx13xOvScfHWW2+JhQsXCiGEOHHihBg7dqyYNm2a2Lp1qxBCiNmzZ4sP\nP/wwkU2UlcvlEtOnTxeXXnqpOHDggKJj3bJli5g2bZoQQgibzSaef/55xca7YcMGcc899wghhNi8\nebO48847FRfrK6+8IsaPHy+uv/56IYQIGV9tba0YP368cLlcorGxUYwfP144nc5ENrtTAmO96aab\nxP9n797jm67ux4+/PkmaW5M2lBawpaVQLnIRBLwOwduYOvnq9CuKF6bzMlSYToSBqAhTqJd5+Xph\nghOZzo2JojgcU/nJvKBzCBQtQlHkItRiSylt0jRpks/vj9DQS9KkbZKm6fv5ePCAfK7ntCEn53zO\neb937typqqqqrly5Un344YeTpq6ifaRt7vqfaY1J25yc9ZW2WdrmrlrXUOI2BXfz5s2MHz8egFGj\nRlFcXByvW8fFRRddxJ133gmA1+tFq9Xy9ddfc8oppwAwYcIEPvvss84sYlQ98sgjXH311fTq1QtV\nVZO6rp988gmDBw/m9ttv57bbbuOcc85J2vrm5+fj9XpRVZWamhp0Ol3S1bVfv34899xzgdfbt29v\nUr9PP/2UL7/8krFjx6LT6bBYLOTn5wfyLXYlzev65JNPMmTIEMA/oq7X65OmrqJ9pG3u+p9pjUnb\nnJz1lbZZ2uauWtdQ4tYBtdvtWK3WwGudTofP54vX7WPOZDJhNpux2+3ceeed3HXXXaiNUqympqZS\nU1PTiSWMntWrV9OzZ0/GjRsXqGPj32Uy1RXgyJEjFBcX8/TTT7NgwQJmzZqVtPVNTU3lwIEDXHjh\nhcyfP5+pU6cm3ft44sSJaLXawOvm9bPb7TgcjiafV2azuUvWu3ldMzMzAdiyZQt//etfueGGG1p8\nNnfVuor2kba563+mNZC2Wdrmrkza5u7VNsdtDajFYsHhcARe+3w+NJrkioH0ww8/MGPGDK677jou\nvvhiHnvsscA+h8NBWlpaJ5YuelavXo2iKGzcuJGSkhLmzJnDkSNHAvuTqa4ANpuNgoICdDod/fv3\nx2AwcOjQocD+ZKrvihUrGD9+PHfddReHDh1i6tSp1NfXB/YnU10bNP4caqifxWLBbre32J4M/vnP\nf7J06VKWLVtGjx49krquIjxpm5Pn/S5ts7TNyUTa5uStK8TxCeiYMWP48MMPASgqKmLw4MHxunVc\nVFRUcNNNNzF79mwuu+wyAIYOHcqmTZsA+Oijjxg7dmxnFjFq/vKXv/DKK6/wyiuvcOKJJ/Loo48y\nfvz4pKwrwNixY/n4448BOHToEE6nkzPOOIP//ve/QHLVNz09HYvFAoDVasXj8TBs2LCkrGuDYcOG\ntXjvnnTSSWzevBm3201NTQ3fffcdgwYN6uSSdtyaNWt49dVXeeWVV8jJyQFg5MiRSVlXERlpm5Pn\nM03aZmmbk4m0zcndNsftCejEiRPZuHEjU6ZMAaCwsDBet46LpUuXUl1dzZIlS3juuedQFIV7772X\nhx56iPr6egoKCrjwwgs7u5gxM2fOHO6///6krOs555zDF198wRVXXBGIGJmTk8N9992XdPW9/vrr\nmTdvHtdeey0ej4dZs2YxfPjwpKxrg2DvXUVRmDp1Ktdccw2qqjJz5kz0en1nF7VDfD4fixcvJjs7\nm+nTp6MoCqeddhozZsxIurqKyEnbnHyfaY1J25wc9ZW2WdrmZKhrY4raeJK1EEIIIYQQQggRI8m1\n0EMIIYQQQgghRMKSDqgQQgghhBBCiLiQDqgQQgghhBBCiLiQDqgQQgghhBBCiLiQDqgQQgghhBBC\niLiQDqgQQgghhBBCiLiQDqgQUWS325k+fTrl5eVMmzatw9f773//y9SpUwG477772L59e4evKYQQ\nQnQn0jYLkVh0nV0AIZJJVVUVO3fuJCsri6VLl0blmoqiAPDQQw9F5XpCCCFEdyJtsxCJRTqgQkTR\nokWL+PHHH5kxYwZff/01H3zwAffccw8mk4nNmzdTU1PDvHnzWLNmDSUlJZx//vnMmTMHn8/Ho48+\nyn//+198Ph+XXXYZ119/fZNrT506lTvuuANVVVm6dClGo5Hdu3czZMgQHn/8cXQ6HW+99RYvv/wy\nqqoyfPhw5s+fj16v76SfhhBCCNH5pG0WIrFENAV327ZtgakGjX3wwQdcccUVTJkyhVWrVkW9cEJ0\nNffddx+9evVi3rx5gdFRgPLyctasWcMdd9zBPffcw+9//3vefPNNXnvtNex2O6+99hqKorB69Wpe\ne+011q9fz+bNm0PeZ+vWrTzwwAOsW7eO0tJSPvnkE7799ltWrVrFypUrefPNN8nIyODFF1+MR7WF\nEJ1A2mYhIiNtsxCJJewT0D/96U+sWbOG1NTUJts9Hg8PP/wwq1evxmAwcPXVV3P++eeTkZERs8IK\n0VWoqtrk9YQJEwDIzs5m8ODB9OjRAwCbzUZ1dTWffvopJSUlfPbZZwA4nU527dpFQUFB0OsPHjyY\nXr16AVBQUEBVVRUHDx5k3759XHXVVaiqisfjYdiwYbGqohCiE0nbLETbSdssRGII2wHt168fzz33\nHL/73e+abN+9ezf9+vXDYrEAMHbsWDZt2sQFF1wQm5IK0YU0HmEFSElJCfxbq9W2ON7n8zF79mx+\n+tOfAnDkyBFSU1MpKioKev3GU3ca7uX1ernooou49957AX9D6fV6O1YRIURCkrZZiLaTtlmIxBB2\nCu7EiROD/qe02+1YrdbA69TUVGpqaqJbOiG6GJ1Oh9frRVXVFiNYfCDnAAAgAElEQVStwTQcc8YZ\nZ/D3v/8dj8eDw+HgmmuuYdu2bW2692mnncb69euprKxEVVUeeOABVqxY0Z5qCCESnLTNQkRO2mYh\nEouiRvA/8eDBg9x9992sXLkysK2kpITHH3+cZcuWAVBYWMjYsWP52c9+1uq1Nl76v1SbtVz0t9c6\nWHQhhBCi+4pm27zu6ivRaPxPbHyqD42ioae5R2C/q+IwhsyenPLC8zGoiRBCiO4k4ii4zfupBQUF\n7Nu3j+rqaoxGI5s2beKmm24Ke51qs3/E9qrfvQGAAmgULQMtPsZl+ackqAYTnv5Dgp5vNuo4qSAz\n0mJ3qqwsK+Xl3WfkuTvVV+qanLpTXSF56puVZQ1/UJKKVtv8x5xrSTX6pyN6h6z3X3vn2fTuDUMG\naRj+l1XU19TwtyXPkN3DSl9rTuBcjdmE5aRRUaxVbCXL+z5S3am+Utfk1J3qCslT39ba5og7oA1z\n2deuXYvT6WTy5Mncc8893HjjjaiqyuTJkwMLr8NdR1VVNFr/7F9VVbHXK+x26piYafMfZK8GiyHo\n+eVHnXy1u6LLdEKFEEKIWIlW22w1H1+7dmwoGJcLKn7UMG60Da1Gg+L1Uq9P4zuHC6fn+Bo2w6Ef\nGXFSlCsmhBAiaUXUAc3JyQlM8Zk0aVJg+znnnMM555zTphsqCqDC5BFOAFxeJ2t3ZjU9yFMPxVuO\nvzaaYOBQALLSTRy1u9p0TyGEECLZRLNt/vVlJ6Hx+gBYse9D6n1uNEYNtXU+1rxbxfVOH6hadhw2\nM/IED6mm4x3WmqrDbHnjXy2uqU/Rkte740+nu9oTViGEEK2L+AlorHjx4vV5qK3X8NwXVce2agHf\n8YNUO77irQDkZev5yZABfL69rMW1utL0XCGEECKR5eXo2X/QHXht8dQyYdM/MKV48XE8mqiS04fK\nkUNbnF/n9lLvrWv1Hgatnvz0vFaP8Rw92saSCyGESGSd0gFNdXoxr10XeH2TFzy+443Zt2l5fNp7\n7PETVNDgH4ndX+rm0tNMQa9bftQZ6JhKZ1QIIYRov9EjzIweYfa/MJyIvWgnqgrO+uPRdy31tej2\nH8IwekyL8+up52i1SnZmaot9DRzu2rDl8NW7qf78PxGXW56YCiFEYot7B3R//zRydx/F3GibQQsG\nrT+QgsbpZJRzHzkjjifp1R49iqrT8ffvMrE7NWzYepBzR+fQXFb68Y6pTNMVQggh2sflq+PdQ2uO\nbxgK7v4ZeFQFpao3mlJ/oMCpu95E8QW/hsWUgt1Zz76y0ME0XF4nvupKAAx6LQOy01sco8/MarGt\nNfLEVAghElvcO6BFp/di/QgdJvxBhvLUTE72DQjsz2z0ZLSBN93fIPW3OPnqSCol31cF7YA25vb6\ngk7TBXk6KoQQQoQyMPVEdtR82WK7Qavi0bgwZZVxSYZ/2qzyDagqrCpuOTMp3+bh1L6t30vxagPr\nSR1Od+sHCyGESApx74CekTuG9V//GzTgxMV+pYKTGRD2PIDTejn4ti6Vmlo3z7y1NbBdQUGnSWFI\nri3QMW38NLQ5eToqhBBCBHdW5nn0MvTGrLM02W7asZO30rY32abTqE2W0DRwuBX2Vuk4tW99q/fy\n4uVA7R4A7C4PP5Tsb/X4lBQtvWymiNaOCiGESExx74BOPfl/UT46gLlnFm9r/9umcxWPh4FGB3vq\njdCoTVNRqfH4KNl9iHNTDoW/Tq2bLTtbNph6q4URPzurTWUSQgghuiuDFkzuWm7bu7rJdke9v41N\n3asGO61N6nJzsI8aCYDdWU9FpReXtxKfIz3olF0hhBCJrdOj4AajcTqbTMVtaHy86emckg6n0DSq\nXpNULpamI7bBpIU4pLbicLvLLIQQsbJ8+TJ69swkL68fb731BgsXLg56nNvt5r33/smkSb9g3bq1\npKWlM27c+DiXVnQndbk5GL8/GHSfqoLL6++ktpfG6cT4/cFAB9RiSgH8U3ddbm9rpwohRExJ29x+\nCdcBbd6YNW98WlPjUnl+ix2AIRk6zs03tuneHp8q60aFEAlNUVrO3mhw+HAF//jHGiZN+gUXXTQp\n5HFCRIt91Mig7fOmAykU/6jHovcF8n63R7C4EA3qfSrflR6Vp6BCiE4nbXPbhO2AqqrKggULKCkp\nQa/Xs2jRInJzcwP733rrLZYvX05aWhq/+MUvuOKKKzpUoOaNWWuNT2NDMnSUVHoAf0e0pNLDuflt\nu3eaXoG924Puq62rp7rC1mSbhHoXInpe++BbNu38MarXPPXEXlx53sCQ+9etW8tnn22krq6O0tKD\n3HbbNMaNO59du3by1FN/QKvVotcbmDPnXnr16t3kvI0bP8LlcnH48GEmT57Cxx9/yJ49u5k+/bec\nddYE3ntvHatW/Q293kDfvrnMnj2P99//F++88zaqqnLTTdMoLT3IW2+9gc/n46yzJnDjjb/mgw/W\n89prf0Wr1TJy5MlMmzY9aNnfeOM1PvpoA3V1daSn21i8+DFefvkl9u3bw4oVf8Ln89GzZyaXXno5\nzz77FF9+WYSiKEyceAFXXDGFxYsXYrWa2bNnP5WVh7n33gcYNGhIVH/+ovs6tW89e6t0ONxK0ABF\nwfiDFrW+ZrQxW6ohaOCisGlb0kxUVzulDRciAtI2S9scC2E7oOvXr8ftdrNy5Uq2bdtGYWEhS5Ys\nAeDIkSM8/fTTrFmzBovFwg033MBPfvITsrOzY17wxrx4GdTrBwb18r9e83UPvD44VHeQ3sbWo+U2\nYesZcpdbcfHNkabTfQyHfmTESe0psRAiUTgcDh5//GkOHPiee++dxbhx5/Poo4u55575FBQM5JNP\nPuTpp5/goYceaXJeba2TJ554hv/3/97jtdf+xtKlL7Flyxe8/vrfGTlyFMuXL2PFir9hNBp55pkn\nWbNmNWazGas1jcLCP3DkyBEefXQxr7zyd1JSUli69DkOHSpj+fJlvPjiKxgMBh58cD6bNn0etNzV\n1Uf5v//7IwAzZ/6GnTu/5vrrb2TPnt3ccMPNLF++DIBPP/2EsrJSli1bgcfjYfr0Wxgz5hQA+vbt\ny29+M5t//OMt1qx5k1mz5sbwJy0SWaoxhbJD1YHXtXUeVG099V4fNouhybFOXBHFcFBGKBh90NpE\n2YaULpEGLWrQELyoceCihgBFaGj1phk+K1npvSVdixAJTNrm5G6bw3ZAN2/ezPjx/nnKo0aNori4\nOLDv+++/Z+jQoVitVgBOOukkioqK2tQBDdeQTVH8EWsbjmmetgXArG26qFNRFBxuhdeLU9Fq7C2u\n2Z7pubZUQ4tttY7Quc2EEG1z5XkDWx0RjZVBgwYD0KtXb1wu/+dNRUU5BQX+sowaNYbnn3+uxXmD\nB/tHJC0WK/365QNgtabhdrsoLT1I//4FGI3GY9cYzaZNnzNs2HDy8voBUFp6kIKCAlJS/Gvapk2b\nzo4d26mqOsLs2XeiqipOp5PS0uDr63S6FB54YB4mk4mKih/xeDxBj9u7dw8jR44+do6OYcNGsGeP\nP+ro0KFDA3X/6qttbfipiWRzytDelGcez9CtLfuBNEMaO/ZWNjkuT81kv1IR0TX1WhV9K+s/nRxP\n6bKq2BT0aekv6xUs9bWY3vwX4I+6G2pNqaqq6LQaKOgHZ44Ned86jws6sC5ViO5E2mZpm2MhbAfU\nbrcHOpjg/yH5fD40Gg35+fl8++23VFZWYjKZ+Oyzz+jfv3/Ym2p1GurcXrJTenJQexh/jDw15Pzp\n1FovU94uZVeugS2jCZu2Jd/mYW+VDjVI8L32Ts8NpvGaUVkjKkTXFOxzJysri927v6WgYCBbt24m\nN7dluofW1nuccEI2e/d+h8tVh8FgpKjo+DU0Gg0AOTl92bdvHx6PB51Ox333zWHGjLvo3bsPTz75\nHFqtlnXr1jJo0BA++mhDk+vv3v0tH3/8b5YtW4HLVcdNN01FVf2foT6fr8mx/fv355133ubKK6/G\n4/FQXLyNn/98Ep9//mmrdRACwKDX4nD6n0pq3V4GOnI52RRZ6rRwGg8+N7TbzX2blsfAav8TTlUF\nj0/BoA0eWVcFVEct3l17ONh/cMj7qike7GoliqOGlMwKabuFSEDSNie3sB1Qi8WCw+EIvG7ofAKk\npaUxd+5cfvOb32Cz2Rg+fDg9evQIe9PcPlYsWVkMIyuwbfeBKsz6lsXR52+Fvd9jqa1l8PcuisYo\nmI4lrQ5lwiCYgBenx0n/tKYN5RMfVx6rV8snmm1ldhug/BsAfwPtbjqFt3xHh2/Rgi7VTI+xY6J/\n4SjJyrKGPyhJSF27PqvViNmsJyvLitvtX0uWlWWlsHAxixYtAkCr1bJo0aImP4PG56WnmzAaU8jK\nsnL4cCp6vY6BA3P57W/v5K67bker1ZKXl8ctt9zAO++8EzgvK8vKbbdN47e/vRVFUTjvvPM46aRB\n3Hzzjfz2t7fi8/no27cvV111OZs3f4rVasRmM2M0pjB69DDS063ceec0VFXlhBP64HbbGTy4H+Dj\n5ZeXkZpqwGo1csklF7Fjx5f85je3UF9fz//8zyR+8pNT+Mc/3gjUt3EdhGisSYCfIxb21XY8rUow\np/atDz79dsQwnAwDCDwdbS2oUebadSiAsbVHrymQqtGDC2qLvmgR36E9ZD2pELH3u9/dy5NPPgr4\n2+a5c+9v0/np6TZuvPHXzJgxDa1WS05OX2677Q7Wr383cIzNZuPaa3/J9Om3oNEojBs3gT59+nDV\nVdcwY8YteL0+Tjghm/POm9ji+n375mIymbn99ptRVZWePbOoqChn+PCT8Hjqef75ZzEY/P2PM888\niy1bNnPrrTfi8Xg477yJSbnWMxRFVYM9JzzuvffeY8OGDRQWFlJUVMSSJUtYtsw/f9nr9fLHP/6R\nGTNm4Ha7uemmm3jmmWew2Vr/MH//1RcwZ2Q12VZa4aDe4wtxBuS8+y5Oxc3fLjmBS32nR1Q5l9dJ\nX3PTJ7LPb7FT41KxGlqOLrRnam6DKoeLFE3Ta5pTDdQ6XK2eZ9Br2xTBz3P0KGmnn9GuMsZaVpaV\n8vLuMS1Z6pqculNdIXnqKx3n6Gj8XviibCtphrSmB2wtZl+t2nrnrg0anoBe4j0touMbpumm6v1f\nW4IFLWoIXFgx6aLQF0rxkqXxx4dwON0Mzc9oa9FbkLY5MUhdk1N3qiskT31ba5vDPgGdOHEiGzdu\nZMqUKQAUFhaydu1anE4nkydPBuCyyy7DYDBw4403hu18hpKdmdr6AVqNf34NHXss3ThabmMdnZob\nbI2oxaxH8bU+Whwsgp8QQgiRiFKOLaFpzOP1BfJzxlLjabptDVoUSr1PbbLOta2DwkIIIdoubAdU\nURQWLlzYZFvjdZ4zZsxgxowZ0S9ZjJybbwzayWzIHyqEEEKI4IINFu8ri89IfeNpupGmdgnGq/oj\n6AKgQIqiD0TMl0FhIYSIvbAd0ESjKGB31sdktLXGpYbsiHZkem5rmo++NiejsUIIIURLdreGTQdS\n2vwU1JJiwek53tF0eUOvKY1UqNyjsjZUCCFa6lId0IZouCZfRUQRolRUFOXjiK79K4/KTks/Putz\nSot90Yyc21ywqbuNNR+NlUZOCCFEIgk2LRdiOzU33+ah+Ed9VKbhNhZuUDg0LcGSjyoHfqBe07vJ\nNomaL4To7rpOB7SgH45vS1BRcSruJktBdaoWfQerYnQ7OLluP6PGnNNiXyJNz9VnZgXdLgm1hRBC\ndIZQMRwimZobLhd4KHl5mViqhrf5vHDCDQq3mTcFmkXdP2pvPTihEEIku67TAT1zLEWjLXxTX4bX\npwZyfNYpLoyqgQvqxrYYbQ0WBTcUZfXLre4PNj03VtNyhRBCiGSXp2ayX6lo83lOXIHzHG4lsB40\n3+ahldi3QgghEkTX6YAC441DGG9smiNnec2HAPTrY20x2urFy6G6g4HgAu0VLHJuLKflNlbvU/mu\n9KisAxVCJIytWzfz1ltvsHDhYi699ALWrHk35LFvv/0mF198Cd99t5uNGz/ihhtujmNJRWdK0Wla\njdlwsm8AJzMg6L7WNDwxDRYVN+F46qF4S5NNSq2bLTsV9Cla8nqHTlMgS2uEEG3RldrmBPy0jh6z\n1hKV4ALBIufGa1quLdUgUfmEEAnn+Dr81tfjv/LKS1x00SQGDRrMoEGDY1+wbkJVVRYsWEBJSQl6\nvZ5FixaRm5sb2P/222+zYsUKtFotl19+OVdffXXcy5idmRrTCLnRioobU7aeLTalWfx/O5xudOmh\nB5dlaY0Qoq26Stuc1B3QWGs8Lbezp+OGCk4UCRllFYlg9bdr2frjV1G95uheJ3H5wEkh969bt5bP\nPttIXV0dpaUHue22aYwbdz67du3kqaf+gFarRa83MGfOvfh8PhYsuJfevXtz4MABhg4dzqxZc5tc\nr6zsB+6/fw6ZmVn8+OOPnH76mfz617dTVvYDhYW/x+v1oigKd945i61bN+PxeLj66uv4wx8KSUnR\nc+edd/Pyy8vJzs5hwIACnnrqDwCkpaUzb958Skp28sc/PoNer+eSSy7jZz+7KHDf+fPvoVev3hw6\n9APnnfcz9uzZza5dJZx55jimTZsetE5udzU333wLNlsPzjhjHCefPJqnn34CVVXJyspi/vyHOHBg\nf4tyNOVfD1FUtIWXXnoBVVVxOmt54IFFFBVt4fDhwzzwwDwmT54SGJl97711rFr1N/R6A3375jJ7\n9jzef/9fTX4X1177Sy66KPTvrrtbv349breblStXsm3bNgoLC1myZElg/6OPPsq6deswGo1cfPHF\nTJo0Cas19NO2ZOBwKzjqFSz1tZje/Ferx5qAb9PyKB0yipEndHygWohkJW2ztM2xaJuTqgPaOBJf\nu6Lv1drDrgVt0Dhqbrym47YmVHCiSMgoq+jOHA4Hjz/+NAcOfM+9985i3LjzefTRxdxzz3wKCgby\nyScf8vTTTzBjxm+PfeAvQa/Xc+WVl3LkSCU9emQ0uV5ZWRlPPrkEs9nM9Ok3s2vXTl5++SWuvPIa\nxo0bzzff7OLhhx9k8eLHWLx4IVdffR379+/D5fIHJvn888947LH/4667pjNv3gP065fP2rVr+Mtf\n/sypp55Ofb2bZctWtKjHDz+U8tRTS6irczJ58iWsWfMuer2eyZP/h2nTpget0/z593LkyBFeeumv\naLVafvWra1i4sJC8vH68887b7N37HY8//kjQchznH2Xds+c75s9/kJ49M3nllZfYsGE9U6f+ij//\neTm//30hX321DUVRqK4+yvLly1ix4m8YjUaeeeZJ1qxZjdlsbvK7mDPnLumAtmLz5s2MHz8egFGj\nRlFcXNxk/4knnsjRo0cDo+GRRI6PhVARcoPpSNTchum436blMbB6f9jj0+odFBzdz6dVYxl5Qrtu\nKYSIIWmbk7ttTqoOaONIfG2e9tOvAPbtjvjwxlFzYz0dty1h4SVvqOiqLh84qdUR0VhpmHrSq1fv\nQENTUVFOQcFAAEaNGsPzzz8HQE5OLkajf6ZDZmYWLpebRx55iAMHvqdHjwxuv/0OBg4chMXin2M3\ndOhw9u/fx/79exk1anTgfuXlh47dr44dO7bTr19/fvyxjJ07v8ZisWA2m9m3bw+PP/4wAB6Ph759\n/dMr8/L6Ba1HdnYOZrMZnU5HRkZmoAwNjVCoOp1wQjZarRaAysrKwPUvvvgSgJDlaC4rK4snn3wM\ns9lMefmPjBx58rE9KmpD1DigtPQg/fsXBH6Oo0aNZtOmzxk2bHiT34XbHb3UGsnIbrc3eaKp0+nw\n+XxoNBoABg0axP/+7/9iNpuZOHFio/dDfIWKkBtMR6brBqbjjhiGk2GtHmsy6fGuWoMibzEhwpK2\nWdrmWLTNYTugXWGdSTSoY8fB2HERH9/8SWmwKLkaxYGv0S83mEim7rYlLLysFxWibYI9GcrKymL3\n7m8pKBjI1q2byc3Na3FMwwf3nDn3BbaVlf3A3r17cLlc6HQ6vv56OxdffCn9+vWnqGgLZ501gW++\nKSEjw78u7Mwzz2LJkqe56qprKCv7gSeffIxLL70cgLy8fO67byG9evXmq6+2UVl5+Fh5NRHUquXn\nTqg6Na5/ZmYWBw8eICenL6+++mdyc/uFLEfzez3yyCJee20NJpOJRYsWBH4+Go0Gn+/4E7ATTshm\n797vcLnqMBiMFBUFL0uwOojjLBYLDocj8Lpx57OkpIR///vffPDBB5jNZmbNmsW7777LBRdc0Oo1\ns7KOd2ittSZsJnOT/a5UAxpL7JaaGIx1mAzhx8U19f73icmkb/e9Gt5rDrfC2zsy0Gn8P8vhvQ1c\nMDjyTnNHuFWVfeX++xr1Oob069Fkv9Nlhx3bWpynSzXTY+yYNt2r8e822Ulduz6r1UhqqoGsLCtu\nt/97bVaWlRNO6ENlZSlDhgxh27bPGThwABkZqaSkaAM/C51OQ8+eqfzhD48Ernfw4EH2799LWpoe\nnU7HN9/s5LrrruY//xnEnj07OO+889ixYwe9evUiK8vKT396Pi+88Bw33HADpaWlPPvsE1x11VVk\nZVkpKCjgyScfp0+fPmzZsoWKigpsNjMmk6HF78Ptrg6Uze12o9Ec/51pNErIOgHo9brAsX369Mbp\nPEJeXh4vvPAC/fv3D1kOozGFrCxr4PqPPbaY9evXYzabmTt3LmaznqwsKykpOjIyzIFzRowYzPff\n78VqTcFoNFJS8hVDhw5q8btoXIeOCPtJ3xXWmdhVVyAabgOPUaUfmQz1xn5uTbAouZFIhKm7QoiW\nfve7e3nyyUdRVRWdTsfcufcDTTtIoaY06nQp3H//XI4cOcy55/6UgoKBTJ9+J4888hArV/4Fr9fD\n3Ln+tRpnn30eL730Ao888iQVFeU8++xTnHXWBADuvnsuDz44H6/Xi0ajYe7c+ykv/zFkmZuWp2XZ\nIqnT7NnzWLx4IRqNhp49M7nqqmvp3btPmHL4z7/ggp9z++03YTKZycjIoKKiHICRI09m9uzf8qtf\n3QJAerqNG2/8NTNmTEOr1ZKT05fbbruD9eubR+vrnCmjXcWYMWPYsGEDF154IUVFRQwefDyIhNVq\nxWQyodfrURSFjIwMqqurw16zvPz4E8iaaieKq9l0WIcLtO2bIhsJn8fLkbrWR9c9Xh8+i39wwtnO\nAVeTSe//f6CBVL3/KYBPValxqXxVVse47PhMDtMrCvj8dak84qAqvdlgsyH4U2vPD4fxlEf+tDgr\ny9rkd5vMpK7JoaamjtpaN+XlNYEOaHl5DTNnzmX+/AVN2rHKSgcejy/ws/B4fBw+7CAl5fjPprLS\ngUaj49Zbpwfa5oyMbG6+eTqPPPIQS5e+gNfrYdaseykvr+GUU8bx7LPP8tBDf8Bm683DDz/M4sWP\nU15ewx13zOa3v53Zok2sq6tv8ftoXDa3243Pd/xz1udTQ9apoR4Nx95111xmzfpdoG2eNOmKsOVo\nuP7EiRdx5ZVXBdpmr9dfhuHDR/KrX93Er351C3V19Xg8Oq6//mamTLkm0DbfcMOtrF//bpPfReM6\nhNNaR1VR1dYf0T388MOMHDmSn//85wBMmDCBjz76KLD/5ptvZsGCBdhsNi6//HJWr14ddqrP+6++\ngDmj/WsWG/u4roRv6stabLf76jCqBiY4hqBB22SfR1WxRDDK2prsdRsAKL3o3JDHGIx6XHX+/zgp\nGn2LdDANT0xvHRO9qVEOp5uh+RnhD2zEc/Qoaaef0eF7J/OHYXNS1+TU0bqWlf3AggX38vzzy6NY\nqthJlt9tsj4FaE3j2UkAhYWFbN++HafTyeTJk1m5ciVvvPEGer2evLw8HnzwQXS61tu9xu+FL8q2\nkmZIa3rAzm/BWdfyxHoP9LR1uE6R2FdWw3umzThxYSLy2UGNDdD25pzVX6NxOvGZTKioaBUdNW4f\nAFZ9JLMMmulX4J9J1U5tabvb2mYny//zSEhdk5O0zV1Ta21z2F5Yoq8zCZYbFI7nBz0xp+UT0H1l\nNRi02hbb20I5Njpv0IYO/W7S6eHYfaKRDiYSDetF27IWNFQEXYmOK4QQiUlRFBYuXNhkW//+/QP/\nnjJlClOmTInuTU8cGHz71uLg22MkT81kv1LRrnNrFRd7fT9Sl5uD8fuD0SlQrd0fQ6IDHVAhhOhO\nwnZAY7HOxGRKITWG60gANA5/BzHYfSJdZ9IaRVFQamvJeqf1UO8N3XEVH1rNJ032Ta3z4lPBsSv0\n+SlaBVPK8dFY7YBB6H9yduj7WfwjwjW1bmw2c8jjmrAFXzjtPlLV5icL3elJhNQ1OXWkrllZVt54\nY1UUSxN73el3K5LDyb4BnMyAdp37tva/oIB91Ejso0YCUOu1o0XLmq97UFuvwWpo2xPQ63a9Dm4f\nf4kwIGGw2A9tCTaoOGqot7Sc+RWKNf0oNUebDoKbjTpOKsiM+BpCdGV9+pzQZZ5+dhdhe2GxWGfi\ndNaj2INM44ki37F1FY4g93HV1aP4fB26vrZvtn/0tJUZzIqiBAJxqI3K1ECnUaj3qSFDbagquL0q\nBu2xI2rt+L7dhXtk+Kk3tU43VVW1kVQlJE+1E2SdSVBS1+TUneoKyVNf6UR3Hx1OtxaEWesfKu7f\nw8ueIwDtmIIboVCxH9oSbBBvClgiP95mNaLxNv3Oc9Tuivx+QggRZWE7oBMnTmTjxo2BqTyFhYWs\nXbs2sM7kyiuv5JprrgmsM7nsssvC3lQ1GqC6lZHCGK8nCZWXrC2NWePR01BMJn0gSILL66SvuX+T\n/YZjf0JpvkY00hylQgghRNyYjK236R3V6DtBh9KthXFq33pGnlDdoq0OR9nr77BGEs8hKmnbPPVQ\nvOX4a6MJBg7t+HWFECJOwnZAY7HOxDs4H5oHN2gsxutJQuUli3ZjJoQQQiS9UGtDoyXOa0wTnq1n\n09f28DPPhBAikcQn1riIu3qfynelRyMORCSEEEKIdqq1B4Kth3kAACAASURBVJ+l1MHouEIIkYxi\nt9BBdCpbqgFXkGnGbdEQHbfhj/2rlgmxhRCJb/nyZaxZs5qtWzfzwAPzQh7ndrtZu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21tbi8McIIUQzYTugXZ1JZ6LaVd0p91ad9dS4/JHR3D4PmaaMTilHuzVv1KShEUIIIYQQQnRA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\nAAAALMEEFAAAAABgif8DT/JYo7D/hIgAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x115bde320>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig, axes = plt.subplots(4,2,figsize=(16,12))\n",
"\n",
"for ax in axes.flatten():\n",
" \n",
" time_sim = kq4_data['Months follow-up'].copy()\n",
" event = event_observed=kq4_data.died\n",
" time_sim.loc[kq4_data.followup_event_time] = np.random.uniform(0, time_sim[kq4_data.followup_event_time])\n",
" \n",
" ix0 = kq4_data.Morcellation=='No'\n",
" ix1 = (kq4_data.Morcellation=='Yes') & (kq4_data.Power=='No')\n",
" ix2 = (kq4_data.Morcellation=='Yes') & (kq4_data.Power=='Yes')\n",
"\n",
" kmf = KaplanMeierFitter()\n",
" kmf.fit(time_sim[ix0], event[ix0], label='no morcellation')\n",
" kmf.plot(ax=ax)\n",
"\n",
" kmf.fit(time_sim[ix1], event[ix1], label='non-power morcellation')\n",
" kmf.plot(ax=ax)\n",
"\n",
" kmf.fit(time_sim[ix2], event[ix2], label='power morcellation')\n",
" kmf.plot(ax=ax)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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sWUvSidOI5s59RgMHDtHo0Q+oevUE3X77QL388kv6+OMP1bFjZ23f/r327y9QSsrIX84D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\nAQAwAA0ZAAAD0JABADAADRkAAAP8f77hqjq899AyAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x116a0ba20>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig, ax = plt.subplots(figsize=(8, 12))\n",
"n_patients = kq4_data.shape[0]\n",
"\n",
"blue, green, red = sns.color_palette()[:3]\n",
"\n",
"ax.hlines(kq4_data.index[ix0], 0, time[ix0],\n",
" color=blue, label='no morcellation')\n",
"\n",
"ax.hlines(kq4_data.index[ix1], 0, time[ix1],\n",
" color=green, label='non-power morcellation')\n",
"\n",
"ax.hlines(kq4_data.index[ix2], 0, time[ix2],\n",
" color=red, label='power morcellation')\n",
"\n",
"ax.scatter(time[kq4_data.died == 1], kq4_data.index[kq4_data.died == 1],\n",
" color='k', zorder=10, label='Death');\n",
"\n",
"ax.set_xlim(left=0)\n",
"ax.set_ylabel('Subject')\n",
"ax.set_xlabel('Followup')\n",
"ax.set_yticks([])\n",
"\n",
"ax.set_ylim(-0.25, n_patients + 0.25)\n",
"\n",
"ax.legend(loc='upper right');"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"model_data = (kq4_data.assign(non_power_morcellation=(kq4_data.Morcellation=='Yes') & (kq4_data.Power=='No'))\n",
" .assign(power_morcellation=(kq4_data.Morcellation=='Yes') & (kq4_data.Power=='Yes')))"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"time = model_data['Months follow-up']\n",
"event = event_observed = model_data.died.astype(int)\n",
"n_intervals = int(time.max()+1)\n",
"n_patients = model_data.shape[0]"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"time_missing = model_data['Months follow-up'].copy()\n",
"time_missing[model_data.followup_event_time] = 1\n",
"time_masked = np.ma.masked_values(time_missing, value=1)\n",
"\n",
"non_power, power = model_data[['non_power_morcellation', 'power_morcellation']].values.astype(int).T"
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"from pymc3 import Normal, Deterministic, sample, NUTS, Model, DensityDist, Uniform, Metropolis, find_MAP, Gamma\n",
"from pymc3 import traceplot, forestplot, summary, sample_ppc\n",
"import theano.tensor as tt"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"with Model() as model:\n",
" \n",
" # Impute missing event times\n",
" time_imputed = Uniform('time_imputed', np.zeros(n_patients), time.values, \n",
" observed=time_masked, testval=2)\n",
"\n",
" # Linear model parameters\n",
" β = Normal('β', mu=0.0, tau=0.0001, shape=3)\n",
"\n",
" # Survival rates\n",
" λ = Deterministic('λ', tt.exp(β[0] + β[1] * non_power + β[2] * power))\n",
"\n",
" # Exponential survival likelihood, accounting for censoring\n",
" def logp(event):\n",
" return event * tt.log(λ) - λ * time_imputed\n",
"\n",
" survival = DensityDist('survival', logp, observed={'event':event})\n"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"n_iterations = 20000\n",
"n_burn = 10000"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" [-----------------100%-----------------] 20000 of 20000 complete in 4.7 sec"
]
}
],
"source": [
"with model:\n",
" trace = sample(n_iterations, step=Metropolis())"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
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hAGY+D21Lv2cBgjs76jnfujchBNM//yGgG9jathmYmgOTy4OIVWg76ttIlOQS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"text/plain": [
"<matplotlib.figure.Figure at 0x115bcf550>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"traceplot(trace[n_burn:], varnames=['β']);"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"β:\n",
"\n",
" Mean SD MC Error 95% HPD interval\n",
" -------------------------------------------------------------------\n",
" \n",
" -4.070 0.254 0.015 [-4.578, -3.590]\n",
" 0.200 0.421 0.021 [-0.643, 0.959]\n",
" -0.363 0.403 0.022 [-1.117, 0.436]\n",
"\n",
" Posterior quantiles:\n",
" 2.5 25 50 75 97.5\n",
" |--------------|==============|==============|--------------|\n",
" \n",
" -4.573 -4.239 -4.065 -3.897 -3.577\n",
" -0.626 -0.077 0.201 0.508 0.981\n",
" -1.168 -0.641 -0.354 -0.083 0.398\n",
"\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/fonnescj/anaconda3/lib/python3.5/site-packages/numpy/core/fromnumeric.py:225: VisibleDeprecationWarning: using a non-integer number instead of an integer will result in an error in the future\n",
" return reshape(newshape, order=order)\n"
]
}
],
"source": [
"summary(trace[n_burn:], varnames=['β'])"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.gridspec.GridSpec at 0x116e15ac8>"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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y4Oa/PM65vrA6MpZQCLXIZqsQc5ntxYsXOXHiBKtXr6ZVq1aMGzeObdu20a1b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\nRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x11ee36630>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"forestplot(trace, varnames=['time_imputed_missing'])"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"baseline_hazard = np.exp(trace['β'][n_burn:, 0])\n",
"non_power_hazard = np.exp(trace['β'][n_burn:, 0] + trace['β'][n_burn:, 1])\n",
"power_hazard = np.exp(trace['β'][n_burn:, 0] + trace['β'][n_burn:, 2])"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"hazard_df = pd.DataFrame({'baseline':baseline_hazard, 'non-power':non_power_hazard, 'power':power_hazard})"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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CAadrAwAA/RTWofjx48frqaee0je/+U09+uijkqRjx445WhiA6EeveCD6hLXH/vDDDysl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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x11f00e208>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"hazard_df.boxplot()\n",
"plt.ylabel('Hazard');"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def cum_hazard(hazard, n=n_intervals):\n",
" return (np.arange(n) * hazard.reshape(-1,1)).cumsum(axis=-1)\n",
"\n",
"def survival(hazard):\n",
" return np.exp(-cum_hazard(hazard))"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def plot_with_hpd(x, hazard, f, ax, color=None, label=None, alpha=0.05):\n",
"\n",
" mean = f(hazard.mean(axis=0))\n",
" \n",
" percentiles = 100 * np.array([alpha / 2., 1. - alpha / 2.])\n",
" hpd = np.percentile(f(hazard), percentiles, axis=0)\n",
" \n",
" ax.fill_between(x, hpd[0], hpd[1], color=color, alpha=0.25)\n",
" ax.step(x, mean.squeeze(), color=color, label=label);"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"interval_bounds = np.arange(0, time.max() + 2, 1)"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {
"collapsed": false,
"scrolled": false
},
"outputs": [
{
"data": {
"image/png": 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hL26//VbOOacbgwYN5aGHpnL55VcRiYSZM+cpXC4Xbdq0YtSoO/jXv/7JP/7x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\nj1BTuyb39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a7RSCL+66nv8+jQrwGohylR5KZ/kZ8tpONBbPY5FzxY47R9DVQryO3A6iME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\nb//2b/zDP/wDN9xwA0NDQ5O+t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"text/plain": [
"<matplotlib.figure.Figure at 0x124699f28>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig, (hazard_ax, surv_ax) = plt.subplots(ncols=2, sharex=True, sharey=False, figsize=(16, 6))\n",
"\n",
"plot_with_hpd(interval_bounds[:-1], baseline_hazard, cum_hazard,\n",
" hazard_ax, color=blue, label='Baseline')\n",
"plot_with_hpd(interval_bounds[:-1], non_power_hazard, cum_hazard,\n",
" hazard_ax, color=green, label='Non-power morecellation')\n",
"plot_with_hpd(interval_bounds[:-1], power_hazard, cum_hazard,\n",
" hazard_ax, color=red, label='Power morecellation')\n",
"\n",
"hazard_ax.set_xlim(0, time.max());\n",
"hazard_ax.set_xlabel('Followup time');\n",
"\n",
"hazard_ax.set_ylabel(r'Cumulative hazard $\\Lambda(t)$');\n",
"\n",
"hazard_ax.legend(loc=2);\n",
"\n",
"plot_with_hpd(interval_bounds[:-1], baseline_hazard, survival,\n",
" surv_ax, color=blue)\n",
"plot_with_hpd(interval_bounds[:-1], non_power_hazard, survival,\n",
" surv_ax, color=green)\n",
"plot_with_hpd(interval_bounds[:-1], power_hazard, survival,\n",
" surv_ax, color=red)\n",
"\n",
"surv_ax.set_xlim(0, time.max());\n",
"surv_ax.set_xlabel('Followup time');\n",
"\n",
"surv_ax.set_ylabel('Survival function $S(t)$');\n",
"\n",
"fig.suptitle('Bayesian survival model');"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Cox model"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"with Model() as cox_model:\n",
" \n",
" # Impute missing event times\n",
" time_imputed = Uniform('time_imputed', np.zeros(n_patients), time.values, \n",
" observed=time_masked, testval=2)\n",
" \n",
" interval_bounds = np.arange(0, time_masked.max() + 2, 1)\n",
" n_intervals = len(interval_bounds) - 1\n",
" \n",
" # risk set equals one if obs_t >= t\n",
" Y = tt.ge(time_imputed.dimshuffle(0, 'x'), interval_bounds[:-1].reshape(1, -1))\n",
" \n",
" import pdb;pdb.set_trace()\n",
" last_period = tt.cast(tt.floor(time_imputed), 'int32')\n",
" \n",
" dN = tt.zeros((n_patients, n_intervals))\n",
" dN = Y * tt.set_subtensor(dN[tt.arange(n_patients), last_period], event)\n",
" \n",
"# dN = tt.ge(time_imputed.dimshuffle(0, 'x')[1:], )\n",
"# # counting process. jump = 1 if obs_t \\in [t[j], t[j+1])\n",
"# dN = np.array([[Y[i,j]*int(t[j+1] >= obs_t[i])*fail[i] for j in range(T)] for i in\n",
"# range(nsubj)])\n",
"\n",
" c = Gamma('c', .0001, .00001)\n",
" r = Gamma('r', .001, .0001)\n",
" \n",
" dL0_star = r*tt.extra_ops.diff(time_imputed)\n",
" \n",
" # prior mean hazard\n",
" μ = Deterministic('μ', dL0_star * c) \n",
" \n",
" dL0 = Gamma('dL0', μ, c, shape=μ.tag.test_value.shape[0])\n",
"\n",
" β = Normal('β', np.zeros(2), sd=np.ones(2)*1000, shape=2)\n",
" \n",
" X = model_data[['non_power_morcellation', 'power_morcellation']].values\n",
"\n",
" linear_model = tt.exp(tt.dot(X, β))\n",
"\n",
" idt = Y[:, :-1] * tt.outer(linear_model, dL0)\n",
"\n",
" dn_like = Poisson('dn_like', idt, observed=dN)"
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"array([1, 1])"
]
},
"execution_count": 52,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.diff([2,3,4])"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.5.1"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
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