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cmrivers/checkerboard_example.ipynb

Created February 4, 2016 13:53
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checkerboard_example.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Populating the interactive namespace from numpy and matplotlib\n"
]
}
],
"source": [
"import pandas as pd\n",
"import epipy\n",
"import seaborn as sns\n",
"%pylab inline"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Simulate line list data"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"data = epipy.generate_example_data(8, 90, 5, 4)"
]
},
{
"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>ID</th>\n",
" <th>Date</th>\n",
" <th>Cluster</th>\n",
" <th>sex</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>0</td>\n",
" <td>2014-03-05</td>\n",
" <td>ClusterT</td>\n",
" <td>Male</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1</td>\n",
" <td>2014-03-12</td>\n",
" <td>ClusterT</td>\n",
" <td>Male</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2</td>\n",
" <td>2014-03-18</td>\n",
" <td>ClusterT</td>\n",
" <td>Male</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>3</td>\n",
" <td>2014-03-25</td>\n",
" <td>ClusterT</td>\n",
" <td>Male</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>4</td>\n",
" <td>2014-03-25</td>\n",
" <td>ClusterT</td>\n",
" <td>Female</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" ID Date Cluster sex\n",
"0 0 2014-03-05 ClusterT Male\n",
"1 1 2014-03-12 ClusterT Male\n",
"2 2 2014-03-18 ClusterT Male\n",
"3 3 2014-03-25 ClusterT Male\n",
"4 4 2014-03-25 ClusterT Female"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Find the earlist date in each Cluster grouping. \n",
"Rename the column to t0 & reset the index so it won't interfere with the next merge step."
]
},
{
"cell_type": "code",
"execution_count": 4,
"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>Cluster</th>\n",
" <th>t0</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>ClusterB</td>\n",
" <td>2014-04-01</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>ClusterP</td>\n",
" <td>2014-03-04</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>ClusterT</td>\n",
" <td>2014-03-05</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>ClusterW</td>\n",
" <td>2014-01-25</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>ClusterX</td>\n",
" <td>2014-03-17</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Cluster t0\n",
"0 ClusterB 2014-04-01\n",
"1 ClusterP 2014-03-04\n",
"2 ClusterT 2014-03-05\n",
"3 ClusterW 2014-01-25\n",
"4 ClusterX 2014-03-17"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"t0 = pd.DataFrame(data.groupby(\"Cluster\").min().Date)\n",
"t0 = t0.rename_axis({'Date':'t0'}, 1).reset_index()\n",
"t0"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Merge the dataframes and the new lookup table."
]
},
{
"cell_type": "code",
"execution_count": 5,
"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>Cluster</th>\n",
" <th>t0</th>\n",
" <th>ID</th>\n",
" <th>Date</th>\n",
" <th>sex</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>ClusterB</td>\n",
" <td>2014-04-01</td>\n",
" <td>24</td>\n",
" <td>2014-04-01</td>\n",
" <td>Male</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>ClusterB</td>\n",
" <td>2014-04-01</td>\n",
" <td>25</td>\n",
" <td>2014-04-01</td>\n",
" <td>Male</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>ClusterB</td>\n",
" <td>2014-04-01</td>\n",
" <td>26</td>\n",
" <td>2014-04-05</td>\n",
" <td>Female</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>ClusterB</td>\n",
" <td>2014-04-01</td>\n",
" <td>27</td>\n",
" <td>2014-04-06</td>\n",
" <td>Male</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>ClusterB</td>\n",
" <td>2014-04-01</td>\n",
" <td>28</td>\n",
" <td>2014-04-07</td>\n",
" <td>Female</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>ClusterB</td>\n",
" <td>2014-04-01</td>\n",
" <td>29</td>\n",
" <td>2014-04-10</td>\n",
" <td>Male</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>ClusterB</td>\n",
" <td>2014-04-01</td>\n",
" <td>30</td>\n",
" <td>2014-04-12</td>\n",
" <td>Female</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>ClusterB</td>\n",
" <td>2014-04-01</td>\n",
" <td>31</td>\n",
" <td>2014-04-13</td>\n",
" <td>Female</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>ClusterP</td>\n",
" <td>2014-03-04</td>\n",
" <td>32</td>\n",
" <td>2014-03-04</td>\n",
" <td>Male</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>ClusterP</td>\n",
" <td>2014-03-04</td>\n",
" <td>33</td>\n",
" <td>2014-03-08</td>\n",
" <td>Male</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>ClusterP</td>\n",
" <td>2014-03-04</td>\n",
" <td>34</td>\n",
" <td>2014-03-15</td>\n",
" <td>Male</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>ClusterP</td>\n",
" <td>2014-03-04</td>\n",
" <td>35</td>\n",
" <td>2014-03-21</td>\n",
" <td>Male</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>ClusterP</td>\n",
" <td>2014-03-04</td>\n",
" <td>36</td>\n",
" <td>2014-03-25</td>\n",
" <td>Female</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>ClusterP</td>\n",
" <td>2014-03-04</td>\n",
" <td>37</td>\n",
" <td>2014-03-26</td>\n",
" <td>Female</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>ClusterP</td>\n",
" <td>2014-03-04</td>\n",
" <td>38</td>\n",
" <td>2014-03-26</td>\n",
" <td>Male</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>ClusterT</td>\n",
" <td>2014-03-05</td>\n",
" <td>0</td>\n",
" <td>2014-03-05</td>\n",
" <td>Male</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>ClusterT</td>\n",
" <td>2014-03-05</td>\n",
" <td>1</td>\n",
" <td>2014-03-12</td>\n",
" <td>Male</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>ClusterT</td>\n",
" <td>2014-03-05</td>\n",
" <td>2</td>\n",
" <td>2014-03-18</td>\n",
" <td>Male</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>ClusterT</td>\n",
" <td>2014-03-05</td>\n",
" <td>3</td>\n",
" <td>2014-03-25</td>\n",
" <td>Male</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>ClusterT</td>\n",
" <td>2014-03-05</td>\n",
" <td>4</td>\n",
" <td>2014-03-25</td>\n",
" <td>Female</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>ClusterT</td>\n",
" <td>2014-03-05</td>\n",
" <td>5</td>\n",
" <td>2014-03-27</td>\n",
" <td>Female</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>ClusterT</td>\n",
" <td>2014-03-05</td>\n",
" <td>6</td>\n",
" <td>2014-04-01</td>\n",
" <td>Female</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>ClusterT</td>\n",
" <td>2014-03-05</td>\n",
" <td>7</td>\n",
" <td>2014-04-03</td>\n",
" <td>Female</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>ClusterW</td>\n",
" <td>2014-01-25</td>\n",
" <td>16</td>\n",
" <td>2014-01-25</td>\n",
" <td>Female</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>ClusterW</td>\n",
" <td>2014-01-25</td>\n",
" <td>17</td>\n",
" <td>2014-01-25</td>\n",
" <td>Female</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>ClusterW</td>\n",
" <td>2014-01-25</td>\n",
" <td>18</td>\n",
" <td>2014-01-28</td>\n",
" <td>Male</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>ClusterW</td>\n",
" <td>2014-01-25</td>\n",
" <td>19</td>\n",
" <td>2014-01-29</td>\n",
" <td>Female</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>ClusterW</td>\n",
" <td>2014-01-25</td>\n",
" <td>20</td>\n",
" <td>2014-02-05</td>\n",
" <td>Male</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>ClusterW</td>\n",
" <td>2014-01-25</td>\n",
" <td>21</td>\n",
" <td>2014-02-08</td>\n",
" <td>Male</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>ClusterW</td>\n",
" <td>2014-01-25</td>\n",
" <td>22</td>\n",
" <td>2014-02-09</td>\n",
" <td>Female</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30</th>\n",
" <td>ClusterW</td>\n",
" <td>2014-01-25</td>\n",
" <td>23</td>\n",
" <td>2014-02-09</td>\n",
" <td>Male</td>\n",
" </tr>\n",
" <tr>\n",
" <th>31</th>\n",
" <td>ClusterX</td>\n",
" <td>2014-03-17</td>\n",
" <td>8</td>\n",
" <td>2014-03-17</td>\n",
" <td>Female</td>\n",
" </tr>\n",
" <tr>\n",
" <th>32</th>\n",
" <td>ClusterX</td>\n",
" <td>2014-03-17</td>\n",
" <td>9</td>\n",
" <td>2014-03-21</td>\n",
" <td>Male</td>\n",
" </tr>\n",
" <tr>\n",
" <th>33</th>\n",
" <td>ClusterX</td>\n",
" <td>2014-03-17</td>\n",
" <td>10</td>\n",
" <td>2014-03-26</td>\n",
" <td>Female</td>\n",
" </tr>\n",
" <tr>\n",
" <th>34</th>\n",
" <td>ClusterX</td>\n",
" <td>2014-03-17</td>\n",
" <td>11</td>\n",
" <td>2014-04-01</td>\n",
" <td>Female</td>\n",
" </tr>\n",
" <tr>\n",
" <th>35</th>\n",
" <td>ClusterX</td>\n",
" <td>2014-03-17</td>\n",
" <td>12</td>\n",
" <td>2014-04-02</td>\n",
" <td>Female</td>\n",
" </tr>\n",
" <tr>\n",
" <th>36</th>\n",
" <td>ClusterX</td>\n",
" <td>2014-03-17</td>\n",
" <td>13</td>\n",
" <td>2014-04-08</td>\n",
" <td>Female</td>\n",
" </tr>\n",
" <tr>\n",
" <th>37</th>\n",
" <td>ClusterX</td>\n",
" <td>2014-03-17</td>\n",
" <td>14</td>\n",
" <td>2014-04-15</td>\n",
" <td>Female</td>\n",
" </tr>\n",
" <tr>\n",
" <th>38</th>\n",
" <td>ClusterX</td>\n",
" <td>2014-03-17</td>\n",
" <td>15</td>\n",
" <td>2014-04-16</td>\n",
" <td>Female</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Cluster t0 ID Date sex\n",
"0 ClusterB 2014-04-01 24 2014-04-01 Male\n",
"1 ClusterB 2014-04-01 25 2014-04-01 Male\n",
"2 ClusterB 2014-04-01 26 2014-04-05 Female\n",
"3 ClusterB 2014-04-01 27 2014-04-06 Male\n",
"4 ClusterB 2014-04-01 28 2014-04-07 Female\n",
"5 ClusterB 2014-04-01 29 2014-04-10 Male\n",
"6 ClusterB 2014-04-01 30 2014-04-12 Female\n",
"7 ClusterB 2014-04-01 31 2014-04-13 Female\n",
"8 ClusterP 2014-03-04 32 2014-03-04 Male\n",
"9 ClusterP 2014-03-04 33 2014-03-08 Male\n",
"10 ClusterP 2014-03-04 34 2014-03-15 Male\n",
"11 ClusterP 2014-03-04 35 2014-03-21 Male\n",
"12 ClusterP 2014-03-04 36 2014-03-25 Female\n",
"13 ClusterP 2014-03-04 37 2014-03-26 Female\n",
"14 ClusterP 2014-03-04 38 2014-03-26 Male\n",
"15 ClusterT 2014-03-05 0 2014-03-05 Male\n",
"16 ClusterT 2014-03-05 1 2014-03-12 Male\n",
"17 ClusterT 2014-03-05 2 2014-03-18 Male\n",
"18 ClusterT 2014-03-05 3 2014-03-25 Male\n",
"19 ClusterT 2014-03-05 4 2014-03-25 Female\n",
"20 ClusterT 2014-03-05 5 2014-03-27 Female\n",
"21 ClusterT 2014-03-05 6 2014-04-01 Female\n",
"22 ClusterT 2014-03-05 7 2014-04-03 Female\n",
"23 ClusterW 2014-01-25 16 2014-01-25 Female\n",
"24 ClusterW 2014-01-25 17 2014-01-25 Female\n",
"25 ClusterW 2014-01-25 18 2014-01-28 Male\n",
"26 ClusterW 2014-01-25 19 2014-01-29 Female\n",
"27 ClusterW 2014-01-25 20 2014-02-05 Male\n",
"28 ClusterW 2014-01-25 21 2014-02-08 Male\n",
"29 ClusterW 2014-01-25 22 2014-02-09 Female\n",
"30 ClusterW 2014-01-25 23 2014-02-09 Male\n",
"31 ClusterX 2014-03-17 8 2014-03-17 Female\n",
"32 ClusterX 2014-03-17 9 2014-03-21 Male\n",
"33 ClusterX 2014-03-17 10 2014-03-26 Female\n",
"34 ClusterX 2014-03-17 11 2014-04-01 Female\n",
"35 ClusterX 2014-03-17 12 2014-04-02 Female\n",
"36 ClusterX 2014-03-17 13 2014-04-08 Female\n",
"37 ClusterX 2014-03-17 14 2014-04-15 Female\n",
"38 ClusterX 2014-03-17 15 2014-04-16 Female"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"merged_df = pd.merge(t0, data)\n",
"merged_df"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"merged_df['day'] = merged_df.Date - merged_df.t0\n",
"merged_df['new_visit_date'] = merged_df.t0 + merged_df.day"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"c:\\users\\caitlin.rivers\\downloads\\epipy-master\\epipy-master\\epipy\\checkerboard.py:57: FutureWarning: order is deprecated, use sort_values(...)\n",
" for casedate in group[date_col].order():\n"
]
},
{
"data": {
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bkiRJUiaGbUmSJCkTw7YkSZKUiWFbkiRJysSwLUmSJGVi2JYkSZIyMWxLkiRJ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\nfeJi28zMzMysT1xsm5mZmZn1yb8J7zNb9XL2sAAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xe2a74a8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"epipy.checkerboard_plot(merged_df, 'ID', 'Cluster', 'new_visit_date');"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"merged_df['int_day'] = (merged_df.day/np.timedelta64(1, 'D')).astype('int')"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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bVtdz46r6cT2+uKiA65bWEApH2H24TU4FT5IUgFOgY3gNwKk9BQzgLLPgHgww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"text/plain": [
"<matplotlib.figure.Figure at 0xe61ab70>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"g = sns.FacetGrid(merged_df, col='Cluster', col_wrap=3, sharex=True, sharey=True)\n",
"g.map(sns.distplot, 'int_day');"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"merged_df['recovery_date'] = merged_df.Date + pd.DateOffset(days=np.random.randint(2, 5))"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"c:\\users\\caitlin.rivers\\downloads\\epipy-master\\epipy-master\\epipy\\stripe_plot.py:54: FutureWarning: order is deprecated, use sort_values(...)\n",
" for ix in df[date1].order(ascending=False).index:\n"
]
},
{
"data": {
"image/png": 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NzH4JfAE4aUPvq6uromIz1u/d2KLaSZKGnEnNWL28T+y5TDlkMvlZ5znT1sXPrOnT4/2R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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0xe4cad30>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"epipy.stripe_plot(merged_df[merged_df.Cluster == 'ClusterT'], 'ID', 'Date', \\\n",
" 'recovery_date', 'sex');"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"image/png": 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5rrKCD3bswNkxlaHDR3DahRczbshQBbVfWLlyBffddzceTwV79uTSsWNHoqOj\nmTlzDiefrDaEo6GAKyIiIo2irKyUDRvWUVFRQTCiHfl2B1fcejspKalml9bsZGauZs6cmXg8HnJz\nc0hNTSUqKoqpU2cwYsSpZpfX4qhFQURERBrFypXLCQYNPB4PUVHR9OjRQ+H2ADZsWM/MmdMoLy8n\nJyeblJQUoqKiue22OxgzZqzZ5bVICrgiIiLSKJYt+wafz4ff7yMiIoKhQ08xu6RmZ+vWLcyYMZWy\nslJycnaTnJxMdHQMkybdwjnnnGd2eS2WAq6IiIiEXE1NDatWraSiooKoqCgsFgvDh48wu6xmp337\nOCIjo8jOziYhIYmYmFgmTLiRceMuNbu0Fk09uCIiIhJymZmrqaqqoqLCQ2xsLB06dKBXL6fZZTVL\nwWCQ3r37UFNTw+9///+44oqrzS6pxdMMroiIiIRc7959uPXWKdjtdhISEhk+fARhYYodP1dUtJc7\n7riNSy75Da+99gZ/+tOt/O5315ldVqugGVwREREJuZiYWGJj23POOedx770PUFVVaXZJzUpZWSnT\npk1h1KgxXHnlNQBcdNElJlfVeijgioiISKNYvnwZp5wyEofDgcPhMLucZsPj8TBt2u0MGTKUa68d\nb3Y5rZK+KxAREZGQCwQCrFixnGHDtHLCz1VWVjJz5h306XM8f/zjjdrsopEo4IqIiEjI/fjjRhIS\nOmjd25/xer3Mnj2DLl3SufnmyQq3jUgBV0REREJu+fJvGDZMy4LtV1NTwz333EV8fDy33nq7brhr\nZBpdERERCblvv12mdW/3CQQC3H//vdhsdqZOvROr1Wp2Sa2eAq6IiIiEVHb2bjyecq17S224feih\nuXi91cyYMRubTff3NwWNsoiIiITU8uXLtO4ttRs4PPbYw+zdW8TcuQ9qJYkm1LZ/80RERCTkvv12\nWZtfPcEwDJ566gl27tzBPffMIzw83OyS2hTN4IqIiEjIlJWVsnXrZgYNGmx2KaYxDIPnnnuGDRvW\nMX/+o0RGRppdUpujgCsiIiIh8913KxgwYFCbnrF89dWXWLlyOQsWPEZ0dLTZ5bRJCrgiIiISMt9+\nW7t7WVu1aNFrfPbZJzz88GPExrY3u5w2Sz24IiIiEhI+n4/vv/+Ok08eanYppnj33bd47713ePDB\nhXTokGB2OW2aZnBFREQkJNauXUOXLultMtx9+OH7vP76v1iw4DGSk5PNLqfNU8AVERGRkGirmzt8\n8cVnPP/HczlmAAAgAElEQVT8syxY8BgdO3YyuxxBLQoiIiISAoZh7Nuet20tD/bNN0v429+e4P77\nF9ClS7rZ5cg+msEVERGRY7Z9+zbCwqxkZHQzu5Qms3LlCh55ZAHz5j1E9+49zC5HfkYBV0RERI7Z\n/vYEi8VidilNIjNzNQ8+OJc5c+ZqS+JmSC0KIiIicsy+/fYbhg0bbnYZTWLDhvXce+/dzJw5mxNO\n6Gd2OXIACrgiIiJyTPbu3Utubg79+g0wu5RGt2XLZu6+ewZTp97Zpndra+4UcEVEROSYLF++jJNO\nOhmbrXV3Pm7fnsWMGVO55ZYpbXat35ZCAVdERESOyfLl37T65cF2797F9Om3c+ONkxg58jSzy5HD\nUMAVERGRBquurmbt2kyGDDnZ7FIaTV7eHqZNm8L48X9kzJixZpcjR0ABV0RERBps9erv6dWrN9HR\nMWaX0ijcbjdTp97GFVdczTnnnGd2OXKEFHBFRESkwZYtW8rw4a1zc4eior3cccdtnH/+hYwbd6nZ\n5chRUMAVERGRBgkGg6xY8W2r7L8tKytl2rQpjBo1hiuvvMbscuQoKeCKiIhIg2za9CNxcXF07NjJ\n7FJCyuPxMH36XxgyZCjXXjve7HKkARRwRUREpEFqN3doXbO3lZWVzJx5B7179+WPf7yxzezM1tq0\n7gXrREREJGQqKipY+eH/8O7eDcEAmV9/yQUTbjK7rJDxer3Mnj2DLl3SufnmyQq3LZgCroiISDMR\nCATYtPlHqrzVZHTJIDEh0eyS6mxas5qtb/ybPvZwbGFh+Hw+LonvQOQ3S3gvN4fzrr+BsLCW+8Ww\nz+fjnnvuIj4+nltvvb1FfxZRwBURETFdMBjkzU8Xs6loM74OYHNY8W3zkmpJ4vwh55LRJcPU+gry\n9rDzjUX0C4+oe67C4yEqKpqUiEhid+/my/+8zpgrrzaxyiOz2bWBPTmbiY4Op11kKn2PH0QwGGTe\nvHuw2exMnXonVqvV7DLlGCngioiImMgwDJ5+42mKOlbi6BGF3QADg/Codnio4cVvX+Ha4DV079rd\ntBozP/4Qp8NR7zlPhYf4+HgAIu12KtetpeaS3+D4xXHNRXb2DtaseJsuyUGcnWKw2a3k5bt4780v\nWP5DDgZW7r57bqvfbritOOxP0el0/gCU7nuY5XK5rm/ckkRERNqOpd8toTDRgz/op7i4BF/QBxYI\nI4xwazjt09vzzop3+XPXW02r0btzR10/aklJMREREVRXVxMZEVl3TC+rldXLljB01BlmlXlQ+fm5\nbPz+P5x0fFy95xM6ROP35ZGbVMaZF93ebMO5HL1DBlyn09kOwOVyjW6ackRERNqWNbvXUhlXRZWv\nmjBHGNaf/dXsxUdBSQFRjnZk7ciie4ZJs7g+P9jtVFVVUlBQQCAQIDIyst5NWOE2G16Px5z6DmPt\n95/S31k/3GIYuN0F1NTUcOHZQ1i/6Ru69+htToEScofroB4ARDqdzo+cTudnTqdzaFMUJSIi0lbs\nLs6myqgmzBZGIBgkGAxiGAYAFoB2YVRH+vgxa6NpNVoiIzCMIPn5eRiGgd/vo7q6mrz8PXXHlNZ4\niUvpaFqNB+Pz+QhU5wBgAMUlxQSCQQrcbqqqKklLSyMsLAxrsACPp9zcYiVkDhdwK4D5LpfrbOBG\n4FWn06nbCkVEREKkyFNCmK32r1a/z4e3xkt1dTXVXi+GYWABagwfnooK02qM6uWkwO2mpsaH3+/D\nZrNhsVho3/6nWdGd4eH0O2mIaTUeTHl5GTFRFgygsNCN211AVtY2PB4PnTt3wRpWe0NZQnsbbneB\nucVKyByuB3czsBXA5XJtcTqde4GOQM6BDo6Pj8Rm052HDZWUFGN2CW2Wxt5cGn9zafzNk5QUg+Hz\ng8UCGHUzt7VTtwaWMAtgwbOnlOh0h2k/K+fwk1jw9JOcmZiMYYDNZiM+Pp6YmNp68muq6TvuQpKT\nY02p71AiI8NYtwJKS4spKS4iEAjg93ux221YwyzY7LW5xRcwSE9P1X8PTagxx/pwAff/Af2Bm51O\nZycgFthzsIOLiytDWFrbkpQUg9utr0bMoLE3l8bfXBp/8+wf+5jwWCoKyohIjCZoGNR+kV7LCNY+\nDnr8gN2Un1UgEGDu3AdYV1VNjutHzknPoGtkJB06JFBR7WVzMEjSaafTY+CwZvu79OOWvVi6GfvC\nrR+Hw0EwGKTG52f/l9mFpeFYrVHN9jO0NqH4/55DBeTDBdzngOedTufX+x7/P5fLFTymakRERKRO\nj7TurC/eRIVRjjXmZ38tG2AYsHfdHtI6pdGne19T6nv77TdxuTaxt7iIMrsNd1Eh1ww5GaNrBu0S\nEzlr9NhmvfrA559/yjvvLyNqnJPUpCjsdgdWq5X09HRsVjsAe0sqSeo0wORKJZQOGXBdLpcfuLaJ\nahEREWlzBnbpT3F8Jds2bSbfVYQ9wk6Y3Uqg2k9iXALOQX2IznOYsoJCXt4enn/+H3g8Hqqrq0lJ\nyeD000dz/Z2zmryWhli+/Fvmz59HWbmXv72whPFXDqVPr4506pRGu3bt8PsC7N5TSkWgG6PGjjK7\nXAkhrWYsIiJiopFDTmXdf9azO7YdseFxBPwBLEBCahLdu3enens544Ze1uR1GYbBY489vG9psHxS\nU1OJiYnh5ptvafJaGiIzczX33jsLj8fDnj176NixE298uJOro/tSjZXwwhq8vgiO6zOOId16ml2u\nhJgCroiIiIksFgs3XnYjYy4+DX8HSB7QGZvDTvUeDzF2B1cO/50pW/V+/vknrFr1HYWFhURFRRIZ\nGcWECTeRkJDQ5LUcrc2bXcyadSfl5eXk5OSQkpJKVFQk06fPYvTo2o0o1H/euingioiImMxisVC8\nsxD3qgK2fbKR8IhwZs24hz9cOsGUekpKinnqqSepqqrE4ymna9cM+vcfyLnnnm9KPUdj166dTJ/+\nF0pLS8jJySYpKYno6GgmT55SF26l9VPAFRERMZnb7aayshLDMDCCBpaAhSEnmbe30tNP/5XS0mLy\n8/NJSkqmXbsIbr11CmFhzXsp/Pz8PKZNm0JR0V6ys7Pp0KEDsbHtuf76G7jggovMLk+aUPP+TRUR\nEWkDdu/eic9Xg2EYhIWF4XA4yMjIMKWW775bwWeffUJRURF2u52YmBiuvXY8Xbqkm1LPkSoq2svU\nqbeRl7eHnJzdtG/fnri4eK688mquuuq3ZpcnTUwBV0RExGRbtmwGam/ssljCiI2NJSam6TdNMAyD\nl156Hq/XS0lJMcnJKXTv3oPLL7+qyWs5Wt9//x3Z2bvIyckhMjKKDh06cP75F3L99RPNLk1MoIAr\nIiJisvT0rnTv3oOwsDBSUlLo18+cNVktFgv33ns/druNhIREwsMd/PnPU7HZmn9H4+mnj9nXThFO\nUlISo0adwZ/+9GcsFovZpYkJmv9vrIiISCsXG9uewYOHsGXLZlJSUhk4cJBptXz99Zf06zeA3/1u\nPNu2baF37z6m1XKkAoEA8+bdQ9++J3DjjZP4/PNPmTr1TqxWq9mliUkUcEVEREx2wgn9OOWUU/n8\n80/53/8+wev1mlJHQUEBL774PA8//BgZGd046aQhptRxNILBIAsXPkR1dRX33HM/DoeD008frZnb\nNk4BV0REpBnYsGEdHTt2IiwsjIiIiCa/vmEYPPHEI4wbdwkZGd2a/PoNYRgGTz/9V3Jysrn//gV1\nWwYr3Ip6cEVERJqBLVs2061b02/Hu9/XX3/Jnj25LWrFgZdffoG1a1dz330PmPKPAmm+FHBFRESa\ngd27d+F09jbl2mVlpTz11OPceuvtdbOgzd3ixf/h888/Zd68+URHx5hdjjQzalEQERExmWEYFBTk\nM2CAOTeXPfvs04wceTonnNDPlOsfrY8//oA331zEwoVP0KFD8986WJqeAq6IiIjJ3G43Pp8Pp7Pp\nVyxYvfp7fvhhFX//+wtNfu2G+OabJTz33N+ZP/9RUlJSzS5HmikFXBEREZNt2eLCbreTlJTUpNf1\ner088sgCJk26laioqCa9dkP88MMqHnlkAfPmPUR6elezy5FmTD24IiIiJsvMXE1ycnKT3/3/8svP\n06uXk+HDRzTpdRvixx83Mm/evcyaNYdevZxmlyPNnGZwRURETOZybaJz5/QmvebWrVv48MMP+Pvf\n/9mk122I7duzmD37Tm6/fRr9+w80uxxpATSDKyIiYrLt27Po2bNnk10vEAiwcOFD/PGPE5v9TVp7\n9uRy551/4cYbJzFs2HCzy5EWQgFXRETEZHv25HL88f2b7HqLF/+HqKhozj773Ca7ZkMUFhZyxx1T\nuOaa3zNmzFizy5EWRC0KIiIiJvJ6vZSWljBwYNMsEbZnTy7//ve/ePzxp5r1jl9lZaVMn3475557\nPhdeOM7scqSF0QyuiIiIiXbs2I7FYmmSVQEMw+DRRxdwxRVXkZbWudGv11AVFRXceedUTj55aIva\nWU2aDwVcERERE2Vm/kB8fAdstsb/UvXTTz+irKyMyy67stGv1VBer5fZs2fQo8dx/PGPNzbrWWZp\nvhRwRURETLR+/Xo6dUpr9OsUFxfx97//jT//+S9YrdZGv15DBAIB5s6dQ1xcHJMn36ZwKw2mgCsi\nImKibdu20q1b90a/zt/+9iRnnnl2s11DNhgMsmDBA/j9Pu64Y0azDeHSMijgioiImCg7ezd9+vRt\n1GusWLGcTZt+5Pe//0OjXqehDMPgqaeeIC9vD7Nm3Yvdbje7JGnhtIqCiIiISQzDwO0uYODAExvt\nGhUVFTz++MNMmXIH7dq1a7TrHIuXXnqe9evXsmDBo822RmlZFHBFRERMUlRUhNfrpW/fExrtGi+8\n8BwDBgzixBNParRrHIs331zEF198xsKFjxMdHWN2OdJKKOCKiIiYJDNzNdHR0URGRjbK+Tdu3MDX\nX3/Bs8++0CjnP1Yffvg+ixf/h4ULn2z2O6pJy6KAKyIiYpJ16zJJTU1tlHP7fD4efXQ+N944idjY\n9o1yjWOxZMlXPP/8s8yf/ygpKSlmlyOtjAKuiIiISVyuTXTp0jgbPCxa9BpJScmMGjWmUc5/LH74\nYRWPPbaQ+++f3yQbXEjbo1UURERETLJjx/ZGWbZr166dLF78BpMnT2l2a8lu2LCeuXPvYfbse+jZ\ns5fZ5UgrpRlcERERk+Tl7aFfv/4hPWcwGOTRRxdw7bXXNbuv/rOytnL33TOYOvVO+vUbYHY5pjEM\ng1WrM9m4NZtgEOJjwjlr9IhG68VuixRwRURETOD3+yktLWHw4NCubvD+++/h9/u58MKLQ3reY5WT\nk82dd07l//5vMkOHDjO7HNNk5+TwwpufU2lNJTyq9h8g2yv8rPzbO4zs35HzzhxlboGthFoURERE\nTLBhwwbsdgfJyaG7ycztdvP88/9odtvxut1upk2bwu9+N57Ro88wuxzTlJaV8uyiLwjE9iY8Kq7u\neavVRnjCcXzjqubzr781scLWQzO4IiIiTcgwDHbs3M477/2HuPi4w7/hKDz55KNceOG4Jtn695cC\ngQA/rFqCpywXgPDIJIacPIrKygqmTZvC+edfxAUXXNTkdTUnH3y6FNofd9DXHdEJLF2zmdGnDmt2\nvdMtjQKuiIhIE/ls2aes2r0GT3QVhQl7yfjN8Tz25uOMPn4U/XsfWy/ukiVfsXv3LmbMmB2iao/c\nls0bcK39H727R9KlSzgAVdXFfPDWd/z347UMHz6Kq676bZPX1dxszSklLCYZqP2HzoFCbLUtlVWr\n1zDkxEFNXV6rooArIiLSBN78+E02hG0hvHsE0dhxVxSSfFxHqtMMFrv+S7W3ipMHDG3QuT2ecv76\n18eYMeNuHA5HiCs/tOzdO8jd+gEnnRBf7/nwcDsdO1Rz1shUBgwf0aQ1NVfVNQZ2AMNgx/YsrDYb\nUZFRdEhIqAu74ZGxFLiLTK2zNVAProiISCPblbOLNRUbCG8fUfdcTU0N7drVPo7oFM2HGz4lEAg0\n6PzPPvs0w4ePCPmKDEdi49ovcHavv5GEgcGePbnYbFZGDutL1uZvmryu5shuqw2xlZWV+P1+ysvL\ncLsL2LFjOxgGADXeKuLaR5tZZquggCsiItLIvlz9FdGd64dAn99Xb1koS5qDr1d+fdTnzsxczcqV\ny7n++onHXOfRqqmpwajJq/ecAeTl5YFhkJrSEQsWIq1FFBdrVrJbpxgMw6C0rBTDMAgGg4RZw2p/\nD/bN4Nqqshk2JLQra7RFCrgiIiKNrMRXCtRO0uVm72bPjh1Ehdmo8XioqqzEAByRDnJL9xzVeb1e\nL488soA//enPREc3/ayfx1NO1L6MbgD5BXnk5uZQWVlB+7i4utAWHxtO0d7CJq+vuTn79KF4C7dQ\n4fEQCASwhlmxYCE2JhYAX7WHQb2Sm9UKGC2VAq6IiEgjs1gs+Hw+inJziKzxERkM0iE8HFtVFcHi\nYkry8wkGDcI4ujvnX331Jbp378Epp4xspMoPLSoqmqrq2q/WA4EApaWllJQU4/V6ydvzU1gvq6gh\nJja0K0a0RCnJyXRtX0Helm/w+bxYrVbsdjsRERFUFWfj7FDOuHPb7jJqoXREN5k5nc5k4HvgDJfL\ntblxSxIREWldEuxxZOfvpF0wQMBiIRgMYgmr/V+HzYYtECB/2y7GHn/wm7H2FhayYeVyMAyO6z+A\nqhov77//Hs88888m/CT1hYeHY1iTAPD7fUDt6gBhYWHY7Pa6uF5eHUNycrJJVTYvG9evpip3Fbs2\nfk2njH706XsCGZERjB47hPQunc0ur9U4bMB1Op124BmgovHLERERaX0S/e3wbcrH1iN+3/JQYMGC\n1Wat+xqfNbl0Pu3Xmz4UFxXxzb9eIjInh+4RkVgsFrYu/Zr3Nv3IpZdeTkJCQhN/mvoyeg5nx+6P\nSIir/Rz7l7+y22ojxh63h05dh5tZYrOxe/cufvxxIx6Ph0i7BZs3l7v+/DAdO3Yyu7RW50haFOYD\nfwOOrjFIREREADB2Z9N/ux/Pzr0YGIAFiwWsYbW9llXr8riUVDYuXVLvfeVlpXz5xCOcUFRMj8io\nuqWkYr1exiWnELvFRX5uTlN/nHp6OU8gPP5kVq7eTSAYhH0BN8xqY+PWQqotfeg/sO1uzftzH3/8\nIYZhUF5eRmxsLP37D1S4bSSHnMF1Op3jAbfL5frY6XROh6NsDhIREREC1VV0rbEQWFnMpg2FeDpG\nQKQdq8fHcf4YzgtPJikmim2+mnrvW/7OWwyyhNXbEMDn81FUVER6l3Q62x2sfvdtzrnx5qb+SPUM\nGnwqX369nDf++zaR4X7i4uLp1mMAf7hhKh06mDvD3FwEAgE+++xjKisrsNnsOBzhnHnm2WaX1Wod\nrkXh/wGG0+kcCwwEXnQ6neNcLlf+gQ6Oj4/EZtOdfw2VlBRjdgltlsbeXBp/c2n8G19ucSEZwQAd\nreEkVwQwtgbxBauIjYykb9/arVsDwSDtUxLqfh6BQABj13bs9p//VW2wZ08BiYkJRETWrqFrz91N\nRITFlFUUfs7nq6LUY7Bh0x569Ijk+pvG4XRmmFrT4TTl7/7KlSspLt6Lx1NOfHwc0dGRXHrpBURF\nRTVZDc1NY47/IQOuy+U6ff+fnU7nF8DEg4VbgOLiyhCW1rYkJcXgdpebXUabpLE3l8bfXBr/xhcI\nBPhs4yYusdmICqudjbVZrYQFAoAFv792c4dNlRUMG3pq3c+jrKwUW5kHf3Tt2qn5+XsIC7Pi9daQ\nmtqp7n1xNX7Wrt5Iz959zPqIAGzfvovqai82mw2/P4jD0bx/t5r6d//119/A6/VRXu4hMTGZYcNG\nUlkZpLKy+Y5RYwrF+B8qIGurXhERkUb0zTdLcJeX8WZJCdf17IURCGC12urtWlbh8xF2Qj/at/9p\nKS2bzY5v3+5W1dVVlJWV4/PVYLVayc3NIS2t9o57n2EQHhGB2QoKCvD5fNhsdgCSk1NMrshcpaUl\nfPj5t+zIK6PK62fpyq2UeLxERkZitVrVntDIjjjgulyu0Y1ZiIiISGtjGAaLFr2Gz1fDyr2FOCIj\nGRYTS6/wdgAEDQNXVSX0PZ4zr7m23nsjIyPxJ6dAVRUejweo3fnKbrfX2wjAHRXNyV3Sm/Jj/UpV\nVRVlZaX4/X7sdjs2m9X01R3M9OOmzbz6v++wxvcgLCKR8ppSUnufSfsuw8hzfU6H9n4GDjzR7DJb\nNc3gioiINJK1a9fgcm2iuLiY+Ph48sLDea24iI6eMjxFRYTHxfPCE08RF9/hgO9PHTKEok8+oaKi\nonbtXEsYYCEqqrbftsLnI3bQIMLCzN23qaCgtnvR5/MRFRVFYmJSm92Nq7KyklfeW4EjsXfdc94a\nb+36wDY7XQddRFSVy/SfWWun0RUREWkkr7/+L/x+Px5POXFxcQwbdgoRUVGUOML5sbyMinbtDhpu\nAQafPoataZ3ILi0lGAxitYZhsUBUVBSlXi/b0tI47eLfNOEnOrD8/NqA6/f7sNvtJCf/ej3ftuLD\nz5dijT+u3nNJScnExcURE9uecIeDmE792blrt0kVtg2awRUREWkEWVlb+e67lZSUFBMTE4vVauPK\nK69h+fJlR3eixCReKNhDrMeDs0MiHTp0oCauPamDh3DBiFPrLSFmlp9mcP3YbPY2vWvZzrwyrLZ4\nAGq8Xmx2O2EWCxUVFaSldcYRHg7A8h820DW9i5mltmoKuCIiIo1g0aLXCAYDlJaWkJ7eleOPP4ET\nTuh31OdZvvxbvEBmWRllCQn839W/5bxLLgt9wcegoCAfwzAIBPzYbLY2fYNZIPjTn/fsycXr9WKx\nWLBardgdjrrX/MHgAd4toaIWBRERkRArLi7iq6++oLS0lMjIKOx2B1deec1Rn6e8vIwNG9ZSUVGx\nb71UC8OGnRL6go9RampHevfuQ3R0NA6Hg5SUttuiENWuNlrVeL3U1NTg9/vx7vtzMFi7ckbAX0OH\n2Egzy2z1NIMrIiISYvHxHVi48Emuu+5qEhIS6dIlnaFDhx/1eb77bgWBQBCPx0NiYiJdu2Y0y61d\nzzvvAtLS0rDb7Tz88OME2/Ds5Mn9j+PNpXmUV/sxgEAwAAZER0djtdbGrkDZTsacan7vdGumgCsi\nItIIdu3ayejRZ3DrrbdTVFTUoLvmly//Fr/fT01NDREREQwbdvQhuakUFOSTkpJCWFhYm14h4MQB\n/Vi6ch3ZeUbdjG2YNYz27dsD4K0oYsTxHQnf14srjaPt/gaKiIg0kmAwyKJFr3HlldfQsWMnjj/+\nhLrXPvnkKz755Cv69OnDJ598ddBz+P1+Vq5cvq89IRKLJYxhw0Y0RfkNkp+fT1JS2+293c9isTB6\n2AlsX/Fv3DsyMYJBbDYbDoeNQPFmTusdwflna2uBxqYZXBERkRBbseJbHA4HgwYNbvA5CgvdJCYm\nsWXLZqKjo4mNbU+fPn1DWGVoFRTk06tX78Mf2AYsWfIVjmApW759FUdUAiNOHc1Z5x3HyOFXYrMp\nejUFjbKIiEiI7Z+9PZYlvFJTO/LXv/6diy8+j9/+9vc4HI5mvXlCfn4eI0eebnYZpgsEAnz99RdU\nVlYQFhZGpD3I9b+7glNPbX43B7ZmCrgiIiIhtH79Ovbu3cuppx572MvMXEPv3n343e+uC0Fljaug\noKBNr3+7X2bmaoqKiigrKyMYDJKSksrJJw8zu6w2Rz24IiIiIbRo0WtcfvmVIZltXb58WYNWX2hq\nhmHsu8ms7S4Ptt8XX3xGMBjA4ynH4XBwxhln6oYyEyjgioiIhMjOnTvYtGkjZ5117jGfyzAMVqxY\n1izXvf2lkpJi2rWLICIiwuxSTBcVFYXf78disdC+fRyjR481u6Q2SS0KIiIiIfKf//ybceMuDcmM\nXVbWVqxWG127Zhx7YY0sPz9f7Qn73HjjJLZscVFZWcW4cRdz4okNv9FQGk4zuCIiIiHgdrtZtmwp\nF144LiTnW778W4YNO+WYblRrKm53QZvenvfnSkqK+e677xg79kxmzpyjVRNMooArIiISAm+99R/O\nPPMcYmPbh+R8y5cva9YbO/xcfn6e+m/3WbLkK+x2O+eee4HZpbRpCrgiIiLHyOMp56OPPuDSSy8P\nyfmKivaSnb2bfv0GhOR8jU0tCj/53//+i8ViaRG9062ZAq6IiMgxeu+9dxkyZCgpKaH5mn7lyhWc\neOJJ2O32kJyvsWkFhVoFBQWsW5fJ+edfhMPhMLucNk0BV0RE5Bh4vV7eeusNrrji6pCd89tvv2H4\n8JYzA1hQkE9SkmZwv/jiUwDOPfd8kysRBVwREZFj8OmnH3PccT3p3r1HSM7n9XrJzFzdojYHKCgo\nCNnsdUv29tuLSUlJxenUlsVmU8AVERFpoEAgwBtvvB7S2dvMzDV069Y9ZDerNbaqqiq83mri4uLN\nLsVUu3fvIitrK5dfflWLWPmitVPAFRERaaBly5YSHR1N//4DQ3bOlrJ72X75+XkkJSW3+VD3yScf\nYRgGY8eebXYpggKuiIhIgxiGwaJFr3HFFVeHLNy1pN3L9isoKGjzKygYhsHixW8wcOCJJCUlmV2O\noIArIiLSIGvXrqG8vJxTThkZsnO2pN3L9tMKCrBt21by8nK56qprzC5F9lHAFRERaYBFi17j8suv\nwmq1huycLWn3sv3y8/Pa/C5m//3v29hsNkaMOM3sUmQfBVwREZGjlJW1ja1btzB27FkhPW9L2r1s\nP7c7v02voBAMBnn33bcYO/ZswsPDzS5H9lHAFREROUr/+c+/ueSSy0IaaFra7mX71e5i1nYD7vr1\n6ygqKuKqq35rdinyMwq4IiLy/9m77/imq/2P46+sznSke9IyKwiIIg6GioiKA7de9ed1XLleByrK\nkKkgeysgQ1HUqygqQ1QUlCEbZCNSmYWupDvNaMY3398fgSpXZLRpv0l7no+Hjwem4eSdb0v6yck5\nn4JW+agAACAASURBVCNcBKPRyLZtW7jjjt4+HTfQTi87zWRq3AXuF198RlxcPJde2lbpKMKfiAJX\nEARBEC7C4sVfcMstvdDrI3w6bqCdXgbePsClpSWN9hQzSZJYuXIF9957f0Ctm24MRIErCIIgCBfI\nbK5g1arvueeeB3w6biCeXgZQXFyEwRCDVqtVOooitm7djM1m5f77H1I6ivA/GudPpNDgWK1W8vPz\nCQ4OIj29iXgnLQhCnVi+fBmdO3f1ea/TQDu97LTG3kHhk08+olWrSxp9mzR/JApcIaAVFhSyetVm\nyopcBGsjkTxuZM1GmrZM5OZbbxSFriAIPuNwOFi2bDGTJk33+dje7gmBtTwBGvf6W4fDwYYNPzNi\nxCilowhnIZYoCAErNzeXrz5bTZAnncTYZkRGxBATnUhcZCuKTuj45KMvkWVZ6ZiCIDQQK1eu4JJL\n2vj8EIbTp5cF0vG8p5lMpkbbIuynn1bi8Xjo1esOpaMIZyEKXCFgrfpuI3GRLSgrq8BkLKXYVIHJ\nWEZxURmSGyRbLFu3bFc6piAIDYAkSXzxxec8+ODDPh87EE8vO60xL1H45JOPueaazoSFhSkdRTgL\nsURBCBiVlWayDx5Co1ETERGBzazFLpWh1YSi05zZVsdudaMNgt9/PcE1116lUGJBEBqK9evXERsb\nS9u27Xw+diCeXnaayWSkc+duSseodxaLhZ07f2H+/A+VjiL8DVHgCn6vrKyM775eTXmxRGR4Isgy\n+w5+S2p8B0JDQpA9HlySG41Gi0bt/VBCo9bidropyS9VOL0gCIFOlmUWLVrIY489USfjb9myiSef\nfLpOxq5r3kMeGl+LsMWLFxEeHs4113RROorwN0SBK/i18vJyPl2wnITo1iTG/jG7EaSNAFmL2y0h\nezx4PB4ktwONVoNOq0OlUqFRazFXWBRMLwhCQ7Br1w4cDkedrJEN1NPLwFv4N9ZNZl988Tk9e96C\nWi1WevorUeAKfu37b9eSEN36Lx/dybJMaXkBSfGZSB6PdzOZynsmuIyMCu/9nc4qJWILgtCALFq0\nkAce+EedFDPbtm2lY8dOAXd6GXh7AgcFBREeHq50lDpntVpZtXYTZpsTh93Gb9nZTJ8+S+lYwjmI\nAlfwW1VVVZQYq0iM+eu6tNBQPRVl5Xg8HlCpkGUPyKBSqVCpvL+EKizFhOl9d068IAiNz+HDh8jJ\nOc6NN97kk/FsNhvbV67AduQI7TwyWz5eQGqnq5AkCY1G45PHqC/e5QkNf/Z28Tcr2Z5dQlB0U9Qa\nDcbCQtr2eI4lK7fy9MNxREdHKx1ROAsxty74rfz8PII13qbnbrdEbm4u5eXlyLJMQlwywcFhHD6+\nE/7cCUwG2ePBYivDYjfRtHkTZcILgtAgLFq0kHvuuZ+goKBaj3XiyGFWjR9D2u7dtLHZuDkxmeu0\nOq4pKmLJxLFYLIG1pKoxLE/4+vvV7DihIiS2BepTb0AqKspJyWyNJaQlMz9chsvlUjilcDaiwBX8\nlkajwSN7AO8Lis1m5eTJExw5chiNOoTKylJSEltw6PhOjhzfjbH4OAWmI+QaD+D2mGmWeQmtWosC\nVxCEmikoyGfHjl+4/fbetR7L4XCw48P36aDToT1VKHk8HoKCg4kMCaWjy82P786p9ePUp4beIszp\ndLLtQCFBYX/M0DocDpxOJ3GxcahUKqpCm7H6500KphT+znmXKGRlZWmAd4FWeOfK/pOdnf1rXQcT\nhLS0dNxsQpYTqKjwLkdQqVR4PB4sFgshIXryjUdIis/EZjejUstkZjYnKjIKh7MKSZfPtZ19e168\nIAiNx1dffcFtt93ukzWm239cxaWq03NK3o+dJElCH64HQK1SEWcyknPsCBlNm9f68epDQz/kYd3G\nLagivJMkHklCkiSKi0yEhoai0XrLJ11QCL8ezeGWHkomFc7mQmZw7wA82dnZXYFhwJi6jSQIXhqN\nhrQMA2Xlpbjdbtxu7xo1lUpNVZWd4KBwXK4qVq3/kIKiw+gj9ICLovJsopNt/N/j9wdkX0lBEJRX\nXl7G6tWruPvu+30ynvXoYYK1WpBljEYjJpMJj8dDuP6P4jk9LJzDWzb75PHq0tEj2az98UtOHtuJ\nuawAp9OpdKQ6UV5pR6vz7uMoKSnheM5xLBYLhpiYM+5nd0pKxBPO47wzuNnZ2cuysrK+OfW/mUBZ\nnSYShD+5vffNPPnYMzRL7Ywsg1qjQ6fTYbPZqKqqZNPOZZhKjoGugn/26UVKSirNmvcMuM0agiD4\nl6+/Xkq3btcTGxvrmwHdLpBlCo2FmM1m3G43Oq3uL2t7VZLbN49XB0pLS9iw+hNS41xckhZJ6E0p\nREbJrP52OrEpV9Lp6huVjuhTwToNHo+E2+WmvKIMt9uNR/JQUV6OPlxPULC3+NVpxUSKP7qgLgrZ\n2dlSVlbWAuAewDdvZwXhAhw5cph80+8czN5DckJL4mJSQQUncn/n2Ml9WKylJCYm8fDDj3L9DTco\nHVcQhAAlSRK5eSfxSB4Mhhi+/nop06bN8Nn4npBQCg4dorKy0lsoeSS0Wg2lpaXExHiLaLfHgyYi\n0meP6Ut2u50NP86nU7toVKpQANwuFxH6UDq01pJv2s2uHTou79hwTjXr3vUqNs9bQbFNh+yRkdxu\ndEFBoFJVt3XzSBLNU6IUTiqczQW3CcvOzn4iKytrELA1KyurdXZ2tv1/72MwhKHVipmzmoqPj1A6\ngt+ZNesbNBoVJeX5RBqC0TnMHD58GKPRiCzLBAcH07x5M/r2fZbIyJpfP3HtlSWuv7Ia8/V3uVx8\n/PVCDhT/ji3cBagoO2wkupmBVq0y0Ov1tX4Mt9vNxqPZtC0yEa3T4fF4CA4KRhekwxAdXf1781CV\nk94P3++XfWW//+57rrrMUJ31dM/x4OAgVCoVTVKj2Zu9m7i4XgG1NOxcP/vx8RFEYCTHGoHH4102\np1arSU5KIijIWz5JliM89tAjfvk9CwR1+dpzIZvMHgPSsrOzxwF2wHPqv78oK7P5Nl0jEh8fQVFR\npdIx/EpZWSnffPMdpaVlhISEIkkyBQWFlJSUIMsyKpWK2Ng4HnnkcRwOVY2vn7j2yhLXX1mN+fq7\n3W7e+vxtHE1lNOkhhBGCLENhvInUtpcwbN5YXrqnb62KXKfTyejRb7Bl124OlFfweNNmhIWEoNVp\nycjIQKXS4HZLVDgd6C6/ApvNg83mf98PU142qRFhuFwSpSXF6IKC0Gi0SO4/yoHkWA9rV6+lbfsr\nFUx64c73s2+329n3yzpyTHZimnUjKi6NsNAwQkLDsNurUJmP8Njd3fz2e+bvfPHac64C+UI2mX0J\ndMjKyloHfA+8lJ2d7ahVIkG4ACtWfIvL5aK8vIzoaAOS5Ka8vLy652BwcDBZWZfQu/c9CicVBCEQ\nfb3ma6qaymh0f8z1VFrM6LQ6wsJC0bQK4YvVX9R4fIfDwahRw9m0aQNFRUXsN1fwSUE+2VYrqanp\n6HRBOCU3+x1VlHfsxPX3+m/XFxUOZLxH85aUlpCXl/eX9cOGqDDKykwKJfS9hQv/S3FxEaV5B8jf\n9Tn5e5eSrjcTI+dybaaTYX3/QcvmTZWOKfyNC9lkZgceqocsglDN7XazfPlSbDYrKpWKsLBQrr22\nG59++iEAarWauLh4+vR51icN2AVBaFxkWeb3ksNoo70bhZwuFzqdjrLSUuLi4gFQqdUct+XicDgI\nDr64UxEdDgdvvDGU7du3YTIZcTodpKenE5rWhJuHvk7+gf2EBalwaUK46YYeFz1+ffN4VBQUFGCx\neNcQS5KE3W7D5Xah03rXozocLoKCQhVO6ht5ebl88cVnmM1mZBlioiN58K4e/PvfTygdTbhA4qhe\nwS9t2PAzxcXFlJeXEx1tIDg4BIPBgMcjExQUhF4fQceOnbjhhoa1a1cQhPphtVoxq61EEYzdbic3\n9yShYWHIMoT9aT2lx6Di+IljZLW85ILHrqqqYsSIwezcuQOjsRCXy0VqahoZGU2ZOHEacXFxtGqV\nFTDLQ6xWKz+u28ldN6bgltzeAyqCglChQpKk6gL3t6OVdL+ts8JpfWPOnJk4nQ6Ki4tISUklNjaW\nRx99XOlYwkUQBa7gl5YtW4zT6aSqyk5ycgo9e95CamoaaWnp6HRa1GoNzz77Amq1OIxPEISLd3oj\nlMPhJC8vD4/HQ1lpKdHR0dVr/AFkj4xadeGvMzabjeHDB7Nnzy6MxgLcbjepqWk0bdqMiROnVndM\nCBQVFeUMHTqIA7/mEB9pp1OHJgQFBaHT6UhNTSf41CdotionQfrmfj8TfSG2bt3Cli2bKSkpISws\nnJCQUPr0+Y/YSBZgRIEr+B1Zlrn//ofIzj5IVFQUarWanj1vZeDAfkRERPLpp4v4/fdsOnS4Qumo\ngiAEqLCwMEKqdOTl5SJJbpxOJ1qtFrvdjt1mqy5mgipUZGZc2DpLq9XKsGGD2LdvL4WFBUiSREpK\nGs2bN2fixGlERxvq8in5nNFoZPDg/uTkHKfQaOTLb4vxeNTc0KUV6elNqmduC01m8soM9LrzXoUT\n157T6eSdd97G6XRgNleQkdGUtm3b0aPHzUpHEy6SKHAFv6NSqbj88o6Ehoby7rsfcvz4MXbs2I7b\n7aJPn2eJioqmU6erlY4pCEIAs1qt7PlpO+HXJSKrPWg0WjQaDbFx8dXFrUeSaBaRWd3z9FwsFgtD\nhgzgwIH9FBQUIMsyKSmptGzZigkTphAVFV3XT8mncnKOM3hwfwoLC8nPz0On02GISeJEcTRmTzsO\nHq8EXKAOI7NFL26/ro3SkX1i8eIvyM/PxWQyERMTi06n5fnnXwqo1meClyhwBb/0008radfuMq68\n8ipatmzFgw/eTVRUNHfeebfS0QRBCHAul4uRI4dTnlvC8UU5ZN13OUHhQURFRRNz6hhWjyShPiTx\nwIMX1tlg/Pg3TxW3+cgypKSk0KrVJYwfP5nIyMA6CODgwd8YOnQQpaXF5OXlEhYWTlxcPFdc0ZHX\nXx/doD+qT0pKRqVS43a7iY42cPvtvWnRoqXSsYQaEAsYBb8jyzJLly7m7ru9H3ctXPhfXC43zz7b\nV3RMEAShVjweD5Mnj2PXrh2YTEbsJyvJXXKQqgMVhFTpMJ8ow3XYSrOyVPo99NIFryl97LEnKS4u\nBlSkpKTQuvWlTJw4NeCK2x07tjNgwMsUFxdx8uQJIiIiiY+P57rrbmD06AkNurgFuPbaLsTGxvLw\nw48SExPDk08+rXQkoYbEDK7gd3bt2oFGo+ayyy7HZDLx+ecLadGipeiYIAhCrc2fP5fVq3+ipKTo\nVHeDdC5t2ZYJw6bicjmRJImoqOiL2sDqcDj44IN3ufHGmzh27CiZmU0Dshg8efIEw4YNwmq1kpeX\nS0xMHNHR0dxxR29eeOFlNJqGf1Lp559/Sps2bRk+fCR2u53Q0IbR9qwxEgWu4HeWLl1M7973olKp\n+PjjD5AkNy+8INZACYJQO0uWfMmiRZ9RXl6GxWIhPb0J6elNePPNcYSGhtaomLHb7YwYMYSYGAMD\nBw7lxIkcEhOTCAsLq4NnULfS05tw9dXX8tFHC0hISCQiIoJHHnmMJ574V6N4/S0sLGDZsiW88867\nAKK4DXBiiYLgVwoK8vn11/306NGT3NyTLF26mGuv7cpll12udDRBEALYzz+vZfbsGVgslZSWlpCa\nmkZcXDzjxk2q8QYwm83GsGGDiI+PZ+DAoWg0Gpo2bRaQxS3A5s0b2bdvH/fccx8RERE8++wLPPnk\n042iuAWYM2cW9957P4mJiUpHEXxAzOAKfuXrr5dw8823nOqgMAdZlnnuub5KxxIEIYDt27eH8eNH\nY7PZMBqNpKWlERkZxZgxE0lOTqnRmKdbgqWnN+Hll/sHfE/uH35Ywfvvz2Ps2Im0aNGSvXt3c/nl\nHZWOVW927NjO0aNHGDx4uNJRBB8J7H+RQoNit9tZufIHeve+h8OHD7Fq1ffcddc9ZGRkKh1NEIQA\ndfz4MUaMGILVaiE/P5+kpGTCw8MZPnwkLVu2qtGYFkslgwf3p2nTZg2iuF20aCEff/wBkyZNJyvr\nEjQaTaMqbl0uF7Nmvc2zz77QIA6qELzEDK7gN376aRWXXtqW5OQU+vV7Aa1Wy7/+9W+lYwmCEMAK\nCvKxWCzk5eUSH+/tcduv34Aa99I2mysYPHgArVtfyvPPvxjQH9/Lssz8+XPZvHkTU6fOJCEhQelI\nili69CuSkpK45pqGccyw4BXYbzuFBkOWZZYt87YG279/H5s3b+SJJ54OuGMtBUHwL+3bd8BgMJCQ\nkEhkZBRPPvk0N9/cq0Zjmc0VDBz4Cu3atQ/44laSJKZOnciePbuZNm1Goy1uS0pK+OyzT3n22b4B\n/f0U/krM4Ap+YffunXg8Hjp0uII+fR4nPFzPP/7xqNKxBEEIYN4DHYbRtev13Hlnb9atW8vDD/9f\njcYqKytl0KBXuPrqa3nqqX8HdDHkcDgYO3YUVVV2JkyYGrCb4nzhvffm0KvXbaSnN1E6iuBjosAV\n/MLpgx1++WUbe/fuYfjwUY36RVcQhNrxeDxMmTKe0NAwnn/+xVMdDprXaKzS0hIGDnyFrl2v4/HH\nnwro4tZqtTJixBAMBgNDh77eqA/P2bNnD7t372T+/I+VjiLUAbFEQVBcYWEB+/fvpXv3m5g8eTzJ\nySncfvudSscSBCGAvf/+PAoLCxkyZEStDigoLi6mf/+XueGGGwO+H2xZWSn9+79ERkYGgwcPb9TF\nrSRJTJo0iT59/iMmUxooMYMrKG758qX07HkL27Zt4ciRw8yYMadRnJgjCELdWLr0KzZt2sj06TNr\ntSveZDIxYMDL9Op1e8AvmSosLOC11/rTvXsP/vnPJwO6UPeFFSu+JTQ0lO7db1I6ilBHRIErKKqq\nqorvv1/B9OkzeeaZp2jbth3XXttF6ViCIASo9evX8dlnnzB9+iwiI6NqPI7RWMiAAf248867eOCB\nf/gwYf07duwoQ4cO5MEHH+buu+9TOo7izOYKPvxwPvPmzWn0hX5DJpYoCIpavfpH2rRpw44d28nP\nz+O114aLFxxBEGpk3769vPXWVEaPnkBSUnKNxykoyKd//5e45577Ar643b9/HwMH9uPpp58Rxe0p\nCxa8T7duN9CqVc36IAuBQRS4gmJkWWbp0i+57bY7mDZtMt2796B16zZKxxIEIQAdP36MUaOGM3jw\nMFq0aFnjcXJzT9K//0s8+ODD3HPP/T5MWP+2bdvK668PZcCAIdx4Y0+l4/iFI0cOsWHDOp544iml\nowh1TCxREBSzd+9u3G6J7OzsU/0lhygdSRCEAFRcXMywYYN45pnn6NixU43HOXnyBIMGvcL//d8T\n3HbbHT5MWP9Wr17F7NkzGTVqLJde2lbpOH5BlmVmzXqbf/7zqVotXxECgyhwBcUsW7aEW2+9jSlT\nJnL//Q/V+Ex4QRAaL4vFwtChA7jjjru46aZbajzO8ePHeO21V3nqqT41PgjCXyxd+hWLFi1k4sRp\nNG3aTOk4fmPNmh+x2+306nW70lGEeiAKXEERRqOR3bt3Ehoaitvtpm/fl5WOJAhCgHG5XIwaNZxL\nL23PQw89UuNxjh49zODBA/j3v5+lR4+bfZiwfsmyzIcfvs/atauZOnVGrdYhNzRWq5V3353DsGEj\nRZeeRkIUuIIivvlmKV26dOOTTz7imWeeEx8XCYJwUf73IIeabk49fPgQQ4YM4Nln+9K9ew8fp6w/\nkiQxa9Zb/PbbAaZNm4HBEKN0JL+ycOHHdOhwhViu0YiIAleodw6HgxUrviMjI4OQkBCeeOJppSMJ\nghBgTh/kMGHC1BrPyGVnH2TYsEG8+OIrdOt2vY8T1h+n08nEiWMpKytj8uS3CA8PVzqSXzl58gQr\nVnzHu+9+oHQUoR6JAleod2vW/ERaWho//LCCUaPG1qoRuyAIjY8vDnL47bcDDB8+mFdeGUDnzl19\nnLD+2Gw2Ro4cRmhoGGPHThSvp/9DlmVmz57BP/7xCDExsUrHEeqRKHCFeuVtDfYVZrOZ5ORk0ZdR\nEISLsn79Oj7//FOmTZtZ46VN+/fv4403hjFgwGCuvvoaHyesPxUV5Qwb9hqZmU15+eX+Ym3pWWzZ\nsonCwkLxu6YREgWuUK/2799LSUkx+/fvZd68BajVohWzIAgXZt++Pbz11lTGj59c4w1Ue/fuZtSo\n13nttaFceeVVPk5Yf0wmE6+99iqdO3fhX/96RhyQcxYOh4PZs2fy0kuvoNPplI4j1DNR4Ar1aunS\nxZSXl9OmTduAXvMmCEL98h7kMKJWBzns2rWD0aNHMnToCK644kofJ6w/J07kMHhwf+6+O/BPWqtL\nX375Oc2bt6hVb2QhcIkCV6g3JpOJ9evXkpNznKVLv1U6jiAIAaKoqIihQwfW6iCHX37ZxvjxYxgx\nYiSXXXa5jxPWn4MHf+P114fw1FP/5pZbArtfb10yGo0sXvwls2bNVTqKoBBR4Ar15ptvllFWVka3\nbtfTpo1o1SIIwvlZLBaGDRvInXfeXeODHLZu3cKkSeN4443RtG3bzscJ68/Onb8wduybvPrqQK69\ntovScfza3LmzuOuue0Qv4EZMFLhCvXA4HHz66UdUVJQzatRYpeMIghAAXC4XI0cOp23by2p8kMPm\nzRuZMmUio0aNpU2bS32c0LdMJiN7d63G4ygCPMiqMBJS23JZh2vYsOFn3n57GiNGjKR9+w5KR/Vr\nO3f+wqFD2QwaNFTpKIKCRIEr1Iu1a38iLy+Xu+66j9TUNKXjCILg5zweD5MnjyM8PJznnutbo01U\n69ev4+23pzJmzASysi6pg5S+s3f3Fkry1nFpMwMqVWj17RWV23lr8lds/uUI48dPrvH648bC7Xbz\nzjszeOaZ50XLtEZOFLhCnZBlmYMHsykpLiExMYEZM6YjSR6GDXtD6WiCIASA99+fh9ForPFBDmvW\n/MTs2TMYN87/i8L8vBOUF/xM6+Znnj4mA26XnY6tNaQ3udnvn4c/WLZsMbGxsXTp0k3pKILCRIEr\n+Ny6tRs5uO8EWmIIC41g18a9SPYI7rzzfqKixJG8giCc25IlX9bqIIefflrJvHmzGT9+Ms2ataiD\nhL51YN/PtG1qOOM2GSgqMmGz2WjWrCmOwxXYbDbCwsKUCemHZFkmO/t3ysxm0lKSCQ8L5dNP/8u0\naTNE2zRBFLiCb634ZhXGExAb8cdMg83q5urL7yAtI4F1azZwfffAPTVIEIS6tX79OhYtWljjgxxW\nrlzB+++/y4QJU8nMbFoHCX3P7TABEQAUFReh1+spLy/H7XKRnp6ORq3hkubR7N61kc5deiob1k+s\n+HEdvxzIw4IBbXA47o2/UHBkG+0v70STJhlKxxP8gChwBZ8pLi7h2O8VJMRkVt/mcrmwWi0kJ6cQ\nHRHPvh2/0+lqMQshCMJfXchBDuVlpfzy3TdUHT0CNjsEBxGU0ZT2N9/Czj27+fjjD5g4cVpgFTmy\nG4DKykrKykopKjIRHBxCZmYmGrV3eYZOq0FyO5VM6TcWfvUtv5pC0EW25PRvEo8nBlVMe+zhOrb8\nsotrrgzcVnCCb4gCV/CZ9Ws3E2/w/lKRJAmVSs3JkydQq9XEx8cDEG9oxs9rNnHr7TcpGVUQBD9z\nIQc55B0/zq4P3qWtRuv9CPr0G+Xck6x+8w2+Lsxn8sy5pKWl12Py2lOpw3BLbkwmIx6PB8kt4da4\nMJlMJJ8q9EvKrMTGpyqcVHnHjh9jzwkXoYaEP26UZUxFJuLj4giNjGLF+l/pdHl7cXRxIyfOSRV8\nxmZ1o1KpkGXIz8/nxIkcLBbLGTMxGo2WSrNdwZSCIPiboqIihg0bdM6DHGRZZtt/F9BOq/vL+sry\n8jJSnA7ua9GKuLj4+ojsU+FRTTmZm4dbknC5XGh1WtQqNTExf2w6O2GE1q0vUzClf1izeS+hhjML\nfbO5ApVKRcSpJS1SaDo/b9yqRDzBj4gCV/AZ9alfOqWlJdjtNqxWC1qtlqCgoDPup1KJHztBELxO\nH+Rwxx13nfMgh73bt9LcUfWX28vKSikrKyM9rQkd9Hq2rfq+LuPWiUqbzMdfbMPpdKJWqdFoNMTG\nxREc5N1gl5NnJr1ZZ7FxCiizuKr/XFVVhd1mo6SkhIT4P2Z0dSFh5BeXKxFP8COi0hB8JiY+HLPZ\nTElJCZIk4fHIaLRazGYzsuy9j73KSkp6nLJBBUHwCxdzkEPJwYNEBYUA3qK2oCCf0pISKsrLSU9P\nR6vTEaTR4jhxsj6i+4zJZGLu3HfYfaCEdxas59CxEoKDgzEYDFRU2th5wExIbBfatr9K6ah+4c81\nfklxMSdO5GC1WTlx8gQ2q7X6a2rEm4HG7pxrcLOysnTA+0AGEAyMzs7OXl4fwYTAc3nHdiz6ZALN\n0q/A7XajCwpCq9GSlJRc/aJktp/gmmsfVTaoIAj1zmaz4fF4CA8PR6VSXfRBDrIkVY9TXFxU/Sa6\nadOmaLW6P+7nker0efiSLMtMmzaRykozJpMJWU5g6Y+5JDW7iar8aKIMidx699Wo1WIu6rQkQwjm\nCg8qtRq324Usy96fHVlGo/WuuXVYSmlzRWCtwxZ873ybzB4FirKzsx/LysoyALsBUeAKfyHLMm+/\nPZVjuTtwO6FF0w6oVSqSkpLRajXIskxxxVFuvbOLeLEWhEZClmVW/LyC/YUHKKcSVKD3hNHK0Jzi\nY4WYTCbGj59yQZuBdLGx2I8coqAgH4/Hg8vlIigoiMLCAjIzm51a/y+jCqBe20uWLOGXX7ZTXFxE\naGgoer2ePn2e4+57H1Q6mt+69cbO7H1/JaGxzXG5/lTgArpTb3T0chHt292sZEzBD5yvwP0C+PLU\nn9WAu27jCIFq8eIv2Lp1CyVlRkxFyykxH6Ft62sIs3iwONQkpERw723dSUxMOP9ggiAEPFmW2S1e\n2gAAIABJREFUmfPlXEoSLOia6Yjijw1T24r2cGDHThaMW3DBBzl0uOFG3vvofdqFhnk3Yml1qFVq\nEhKSqgucHJuNdj0Co09sYWEB06dPx2azYrFYycjIpH37Dtxzz/1KR/NrMYYYbr+2Ocs3H0eW5eoC\nV61Wo1Kr8ZQf4tF7rxfrlYVzF7jZ2dlWgKysrAi8xe7Q+gglBJbs7IO8994cLJZKrFYLTZpk0jwr\nldGTBqBWq8WMrSA0Qj+s/95b3Ibpzri9srKSisoKrvrnDfywdSWP3n5hS5YWLHiP1SYjEVEG0vR6\nNBoNMbGxhIeHA1DhdODq0IGk1DSfPxdf83g8TJo0HovFQmFhIYmJSYSHh9O//yDxenkBunXuhKWy\nlAlvzUMOjiM4NILQIJlm7fT0uvNm4uPEPg/hAvrgZmVlpQOLgVnZ2dmfneu+BkMYWq3oO1dT8fER\nSke4aFarlcmTx+ByOTGZjKSnpxMXF8PkyRNITjacfwA/EYjXviER119ZdXH9D5UfIjTduynM6XIR\npNNhs9koKjLRpEkTQkJCOFl0kujoEHQ63TnH+uabb1ixYjklVXbeKymmS0oqPdIySEiIp9Lp5ERI\nEMnXd+fh++7z+fOoC59//jkHDuzFaDQSGRlBVFQEAwa8Svv2WUpHCxjJiVGEyqUc+XU7KSkpdL/l\nFl594eL3d4jXHmXV5fU/3yazRGAl8Fx2dvaa8w1WVmbzVa5GJz4+gqKiSqVjXBRZlhk37k2OHcsh\nNzeX6GgDOl0wffu+ik4XOM8nEK99QyKuv7Lq4vrb7XYK7MVEuWOx2Wzk5eURERFRfaqhVqvD7Zaw\nhrvZsm0Xl7Rq/bdjHT58iFGjRmM2V1JSUkJ6egZFSSkkPfMsx8rLiYqLo+cVV6JWqwPi5+jkyRNM\nnTqdigozVquVJk0yaN/+crp16xkQ+f1FdvZR3G5v32C1WktERMxFXz/x2qMsX1z/cxXI55vBHQJE\nASOysrJGnLqtV3Z29l+bEQqNzg8/rGDNmp8oKSlGrVZjMMRw55130a3b9UpHEwRBQR6PB1QqrDYb\n+Xl5SB6JoiITMbGxZxzTfXpj2N8xmysYNWo4VquVwsICkpKSCQ8P54033qR587OfdubvZsyYhs1m\nxWgsJC0tjYiISF599TWxZvQiGY1GJEkCVGg0GhITE8/4usvlYv+vv2F3VNGyWTPi48WyhcbmfGtw\nXwJeqqcsQgDJyTnOzJneDRJmc4V33W3z5jzzzPNKRxMEQWFhYWE4i6swuYuRPB5cTidarQ6rxYLd\nXkVoqHfpgqpUIrNb07OO4fF4GD9+NPn5eRQU5BMdbSAsLJx+/foHbHEL0LdvPx577CH0+gjCwsJ4\n9tm+JCSIzbcXy2gswOVyVy9vOX1ipiRJfL50Bb+dqMAdlIhGF4Rr4zpSozz07nE1mZlNlIwt1KPz\nrsEVhP/lcDgYM+aNv8yqDBny+gXviBYEoeHaunUzO77fRJN7WiPJElqdDo1aTXx8QnVxK8syTUJS\nCQ0NPesYH3+8gO3bt2EymdBqtcTExNC79z3nPO0sEBw/fozMzGb86189MRpzufnmW5WOFJBMJhNu\ntwudzlvGJCQk4vF4mDn/c4pVGWgNidUFji6mCWXAe0s28dTdHpo1zVQotVCfxHZN4aLNmTOTo0eP\nUlhYQGRkFGFh4bzwwstkZGQqHU0QBIVt3LiekSOH4SqtYv9X21GrNdXFrcHg3XgqyzLubBsP9Dh7\nS6wtWzbx3/9+SEVFBXa7jaSkJNq0act//hPYnxCVlZUyc+Z0BgwYzGOPPcH48ePF0oQakGWZwsKC\n6nZxAElJSaxZv4kiTwpaXdBZ/57O0JzFK7fUZ1RBQaLAFS7KunVr+OabrykrK0WWZWJj4+jR4yZu\nuaWX0tEEQVDYzz+vZfTo16mstJCfn09QiYqcJQcILlKjlTRYSyuxHTWTUBBJ37ueIzLir4cy5Ofn\nMWHCGKqqqiguNpGSkkpMTCzDho08b7cFfybLMm+9NZWePW/h0kvbAojitoYqK81UVVXhcrnQ6XSE\nhIQQGRnF7ux8dCHh5/y7xfZQjh/PqaekgpLEEgXhghUU5DNt2iTsdjtlZWU0aZJBamoaffu+Il6o\nBaGRW7PmJyZMGI3F4i1uk5KSCA/X81KfV7n11ts4nnMMl+QmMz3zb5clVFVVMXLkMCoqyikoyCMh\nIYnQ0FCGDXuD+Pj4en5GvrV69Sry8nIZMmTE+e8snFNhYSEAbreLsLAwEhO9h32UW91oT03eFhcX\nodPqCNfr0Wr/KHVCopL59ffDZGZmKBFdqEdiBle4IJIkMXbsKMxmM4WF+SQmJhIaGsKwYW9UN1oX\nBKFx+umnlYwf/+apmds8kpOT0ev1vPrqIO64ozdarZYWzVvSulXrvy1uwTuj2aJFFgUFBej1EURE\nRPD00//hsssur8dn43vFxcXMnj2LAQMGExR09o/PhQsXFhbGXXfdS1RUNE2bNiMz07tR8fQ8i9vt\npqy0lPz8PA79nk1+Xu4f3TpkGbWYkGkUxAyucEHUajW3396bn39eS3i4Hr0+gj59nqVly1ZKRxME\nQUErV65g8uTxWK1WCgoKSE5OQa/XM2DA4IveEBYcHExcXBzt2l1GZaWZLl26cd99D9ZR8vohyzLT\npk2kd++7adVKHOTgC2lp6bzwwkv8+OMPzJkzn8hI71KXZEMIJhksFm9vVUmS0Ol0SJJU/SljVVkO\n19wbGMc5C7UjClzhgqhUKlwuF+3bdyA4OJjk5BRxZrogNHIrVnzLtGkTTx05W0BKSirh4eEMGjSM\nG2+86aLH27RpAz/++ANz586nuLiY1NS0gF/+9P3331FaWsojjzymdJQGxWKpxOPxEBERWX1blyta\nsXBtDpZKBx7ZA3gnZ/R672EAssdDkxgVhujAOWVTqDlR4AoX5OjRwyxYMJ/p02eSkJCIy+UM+F88\ngiDU3PLly3j77alYrRYKCwtJSUlFr9czePAIrr+++0WPl5t7kqlTJ/Hmm+MwGGIwGGLqIHX9MhoL\nee+9uUyaNO2MdaBC7RmNhSQlJZ3xe6h9u7bs/e0wS7KPowuLQa32rsLU6/V4PBJa80H++bSYmGks\nxL844bzsdjujR4/k2WefJz3d2yRb9LsVhMarvLyM+fPnYrFYMBq9xW1EhJ4hQ16v0UmGdrudUaOG\n8/jjT9G6dZs6SFz/PB4PkydP4IEHHqJZs+ZKx2lwjEYjCQmJf7k9Rq+l6NdlWD3hGJJaoo+IJDhJ\nzSUZMdz5yD8ICQlRIK2gBLHJTDivd955m6ysSwK+wbogCL4RHW3gvvsepKjIRGqqt7gdMeLNGhW3\n3jWqk2jZMos77uhdB2mVsXz5Uqqq7DzwwD+UjtIgGY2FJCYm/+X2DRvWoZadlJ3cg1y8k3u6NWX4\ni4/wwF23iuK2kREFrnBOq1evYv/+ffTt20/pKIIg+Il169awfPlSpk+fRXx8Am+8MZZrr+1So7GW\nLPmSkydP8OKLDafdYF5eLh99tICBA4eg0WiUjtMgeQvcM2dwLZZKdu3aQWVlJXq9HrVazXXX3aBM\nQEFxYomC8Lfy8nKZNWsGEyZMISwsTOk4giD4gdWrf2Tu3FmMGzeJ5s1b0r17jxq3Cty3bw8LF/6X\nt9+e3WCWPUmSxOTJ43nkkf+rXtIl+J7RaKR160vPuG3Llk243RIWi4XY2DjS0tKrW4gJjY8ocIWz\ncjqdjB79Bv/85xO0aNFS6TiCIPiBH3/8gXffncP48VNo2rQZQI2L25KSEsaMGcmAAUNITk7xZUxF\nLV78BWq1WnSZqWOFhQUkJiadcdv69T/jcrlwuZyEhYXRtWu3BvOpgHDxRIErnNX8+fNISEikd+97\nlI4iCIIf+P7771iw4D0mTpxGRkZmrcZyuVyMHv06d9xxF1dddbVvAvqBnJzjfPbZp8ycOad6B79Q\nN0wm4xlLFFwuF3v27MJiqSQ8XI9KpaJr14tfEy40HKLAFf5i8+aNbNiwjtmz3xPvfgVB4Ntvl/PJ\nJx8yadJ0n3zsPm/ebPR6fYPqDStJEpMmjeOJJ55qUDPS/shqteJwOIj+Uz9bnU7Hxx9/Rp8+TxAR\nEYkkSeJgjUZOFLjCGUwmE9OmTWLEiDerT4cRBKHx+vrrJXz++adMmjSd1NS0Wo+3evUqtm7dzDvv\nzGtQs5yff/4p4eHh3HHHXUpHafC8s7dJf5mAcbvdVFVV8eGHC9FqtWKCppETBa5QTZIkxo9/k7vv\nvo+2bdspHUcQBIUtWfIlX321iMmT3/LJrOTRo4eZNWsGkyZNrT5dqiE4cuQQX331hfjUq54Yjca/\ndFAA2LhxA506Xd1gNiwKtdNw3j4LtfbJJx+h1Wp56KFHlI4iCILCvvzyc5Ys+YopU972SXFrsVQy\ncuQInnvuBZo1a+GDhP7B5XIxadI4+vT5DwkJCUrHaRSMxr9uMAPYuPFnunTppkAiwR+JAlcAYM+e\nXXz77de89tow0bdREBq5zz77hOXLlzF58ltnLSQulsfjYcKEMXTqdDU9etzsg4T+47///ZD4+ARu\nuaWX0lEaDW8P3DN/LisrzRw48CtXXXWNQqkEfyMKXIHy8jLGjx9N//6vERMTq3QcQRAU9MknH/HD\nDyuYPPktn81ILlz4XywWC88885xPxvMXBw/+xnffLefllweIpQn1yLtE4cwCd8uWTVx22eWiZ7tQ\nTazBbeRkWWbSpHH06NGTTp0aTrseQRAujizLfPzxAtatW8PkyW8RG+ubN7vbtm1l+fKlzJw5D51O\n55Mx/YHD4WDSpHE8+2xfn10r4cKcbQZ3/fqf6dbtOoUSCf5IzOA2cl99tQiz2cwTTzytdBRBEBQi\nyzILFsxnw4Z1TJo0zWcFW0FBPpMmjWXo0NeJi4vzyZj+4sMP55ORkUn37j2UjtLoFBaeWeDabDb2\n7NnFNdd0VjCV4G/EDG4jdvDgb9VNybVa8aMgCI2RLMvMnz+X7du3MnHitDN6i9aGw+Fg1KgRPPzw\n/9Gu3WU+GdNf7N+/j59+WsXcue+LpQn1rKqqCrvdhsHwx8/ptm1baNPmUiIiIhVMJvgbUdU0UhaL\nhbFjR/Hii/1ISkpWOo4gCAqQZZnp06ezY8cvTJo03We9r2VZ5u23p5Ke3qTBHVlrt9uZNGkcffv2\n89mbAeHCGY2FJCQkntFDeePG9XTpIpYnCGcSSxQaIVmWeeutKXTseCXXXXeD0nEEQVCALMvMmvU2\nu3btYuLEqT492OXbb5dz6FA2/fo1vM1X8+fPo3Xr1nTtKgoqJRiNxjM2PzocDrZv30qXLl0VTCX4\nIzGD2wh9//135OQcY8aMuUpHEQRBAR6Ph5kzp3Po0O+8++4cqqp8N/Zvvx1gwYL5TJ8+k9DQUN8N\n7Ad27drBxo0/M2/eB0pHabSMxsIzPnXcufMXmjdvicEQo2AqwR+JAreROXbsKO+9N5epU98Wp70I\nQiPk8XiYPn0yJ0+eYPz4KURERFBVVemTscvKShk9+nVeeWUAaWnpPhnTX1itVqZMmUC/fgPFWk8F\n/e8hD+vXr6NrV3G4g/BXYolCI+JwOBg7dhR9+vyHjIxMpeMIglDPJEliypQJ5OXlMmbMRMLDw306\n9pgxo+jR42Y6d254HxfPm/cOl1/ekauuEu0UlWQymaqP6XW73WzdulmsvxXOSszgNiKzZ8+gWbNm\n4sQdQWiEJEli0qRxFBcXM3r0BJ8vH/jgg3fRajU8/vhTPh3XH2zbtpUdO7Yzd65YmqC0wsICEhO9\nSxR2795JSkqqOCJZOCtR4DYSa9euZufOHcye/V6D2/QhCMK5SZLEhAljqKgoZ/To8YSEhPh0/PXr\n17F27WreeefdBnfUd2WlmenTJzFgwGCfzngLNXO6iwJ4uyeIzX7C3xFLFBqBgoJ8Zs58i6FDXxcv\n0ILQyLjdbsaMGYnFUsmoUeN8Xtzm5Bxn+vQpjBjxpk87MfiLd96ZwbXXduXyyzsqHaXRczgcmM1m\nYmNjkSRJFLjCOYkZ3AbO5XIxduwoHn74UbKyLlE6jiAI9cjlcjFmzEgkyc0bb4whKCjIp+NbrVZG\njhxOnz7/oVWrLJ+O7Q82blzPr7/uZ+7c95WOIgAmk5H4+AQ0Gg179+7GYDCQmpqmdCzBT4kCt4Fb\nsOA9oqOjuffeB5SOIghCPXI6nbz55uuoVCpGjHgTnU7n0/FlWWbKlAm0a9eeW2+9zadjK8FYmE/2\nwZ0ANMlsjcEQy9tvT2X48FENrt1ZoDKZjNUdFDZsWE/XrtcrnEjwZ6LAbcC2bdvKmjU/iXW3gtDI\neI/JHU5wcAhDhoyok6O4v/jiM0wmI6+9NsznY9enkpJitm74guhQMy3TDahUKnKP/cZ/3/+VTld2\npG3bdkpHFE4pLCwkKSkJWZbZuPFnRo+eoHQkwY+JAreBKi4uZsqU8QwZMoKoqGil4wiCUE8cDgcj\nRgwmMjKKQYOG1klxu3v3Tr76ahFvvz3H58se6lNFRRmb17zPlW0NwB8HBUTq1dzUJYUKu478/BOk\npDRRLqSfkWWZnXv28euhk0iSjCEimJu7dyEsLKzOH/v0BrPs7IMEBQWTmdm0zh9TCFyiwG2ATu+Y\nvv323lx22eVKxxEEoZ7Y7XZGjBhCbGwMAwYMqZOOBiaTiXHj3mTQoKHV/UgD1fYtK+h46ZkTAG7J\nTVGRiZSUNDJDQti7axUpKf9SKKF/yS8oZMEXq7BoEgkO97bmOmZ1s232Mrq0TeL2W7rX6eObTIV0\n7NiJDRvW0bXrdeKTSeGcRBeFBuizzz7B4/Hw6KP/VDqKIAj1xGazMWzYIBISEuqsuPWu6x3BPffc\nzxVXXOnz8euTx+PBbcurLpJkZGS8s4RRUdGEnuo2oZOLMJsrFEzqHyyWSuZ+tgpX5CUEhxuqb9do\ntATHtmDTIQc/rttYpxmMRiMJCYmsX/8z3bqJ9bfCuYkCt4HZt28Py5Yt5rXXhjW4fpSCIJyd1Wpl\n6NCBpKam8eqrg+rs3/7s2TOIjY3joYceqZPx65PFUklokAsAtyRx9OhR8vNzcbncxMbEVt8vISaI\nwoI8pWL6jRU/bYSoln/79SB9LBt3H8fj8dRZhsLCAhwOB5LkpmXLVnX2OELDIArcBsRsrmD8+NG8\n8sog4uPjlY4jCEI9sFgsDB7cn8zMprz8cn/U6rp5Wf/hhxXs2bObAQMGN4iPhoODQ3C6ZQDKy8uQ\n3G5KS0txOKooLSutvl+V001wiOiicCi3HLX63G+cnEHJbN+xq04e3+VyUV5ezoEDv4rlCcIFEWtw\nGwhZlpk8eQLdul3PNddcq3QcQRB8rLy8DIfDgcEQU72xq7LSzODBA7jkkjY8//yLPvmlfzT7IIc3\nbURVZUfWBZF6+RUERUYyb95spkx5q8EcFhMcHIxHHYPkkbwFrkdChQqVSnXGmwRjmZYrrs9ULqif\nsDs9aM/zrQ8KjaCopKxOHr+oyERcXBybNq3nxRdfrZPHEBoWUeA2EMuWLaakpJjhw0cqHUUQBB9a\nvXk1u3L3UKKqAB3o7Boyw9K4vt11TJo4jssu68Azzzxf6+LW6XSyYt47JOTnkxX6x474osOHmLtn\nF0+/8FKD27WemNaB3498iwYPbrcbrVaHRq0hKsp7IlultYrImFZithAI0qo4vfjg0O/ZAKeumZaW\npw75cDntREbUzRsgo7GQsDA95eWltGlzaZ08htCwXFSBm5WVdTUwPjs7u263SgoX5dCh3/n44w+Z\nMWO2z5u5C4KgnM++W0h20AlCMkOI4o+NPflSGQPmDKJzq04+KW4Bfpg/j7bFJWj/VNwiyzjLy3is\nRUty9u5Gvu2OBlXstcq6jKfHv06v61NJStCj0aiJNhhQq9SUlFnJKYqm1523Kx3TL2Qk6jlqlc/4\n/p8ucE9TWU9y7VUP+uwxyyvK+e7HDRzNr+RkvpF8WwQpSbGUlJYSHxfns8cRGqYLXqyVlZU1EHgX\nCK67OMLFslqtjBkzkhdeeImUlFSl4wiC4CN7ft3Fb+pjhESFnHG72y2Rm3uSZje0RpMa6pOCsyD3\nJJE5OWj/Z3NaSWkJsiyTEJ9AK6uNPVs21/qx/Ml33y2nqLSKCe+s5cNFu/lp41GOF6jZc0hGCu1M\nrzsfb1AFfW3cdmNn3OVH/vbrriorHVrE+2yS5fiJk0yd/w2/V8QjRbQgODaLqCZXEtWqF299vIrf\nDv7uk8cRGq6L2Y1wGLgXEP/a/cjMmdNp16493bv3UDqKIAg+tOXQdsJiz/y493RxG6GPIDYujtIQ\nMzm5ObV+rAPr15FxqlG/1WqluLgIq9WCuaKC5KRkUKmICg7GtHd3rR/LXzgcDr744jNsNhsOh5vC\nUhWZWbdx+30DueXOf9O+w1WiuP2TuLhYHunVEVfJb3gk1xlfqyrPp2V0Offe0dMnj+XxePho8Wo0\nMVmoTq2HdjgcyB6Z8LBwdIYWfPLtFlwu13lGEhqzC16ikJ2dvTgrKyuzDrMIF2nlyhX8/ns2s2bN\nUzqKIAg+VuIsRUMoMlBQkE9ISCjmigoiIiKIjfW2sQpPjmDv73vJSMuo3YNVOVCpVNjtNgry85A8\nEmqVmrT0Jmj+fBKaw1G7x/EjK1euoLS0lNLSEmJiYgkJCeHee+9XOpZfa3NJK4Y3zeCmXr3QhidR\nYTajD1Yx+t1ZZGb47rS3Lb/spCoo7YyPi+1VNsLCwuHUmw5VZDNWr9vELTeJfrjC2fl0k5nBEIZW\nK3qv1lR8fMQF3zcnJ4cPPpjHnDlzSE8XLcFq62KuveB74vr/VVCQDpVWQ2VlJVaLhfKyMrRaLeHh\niWe8zkbog2t9/fTxUTiPHiI/Pw+P7MHlcqHT6rBYzEREhHP6g7swQ2SD+F653W6WLFmEy+XA7XZj\nMETzj388SIsW6fWeJfCuZwT6YBncBRzL+Y3E1q3pdKVvN33lGkvRR3rfxJkrK5EkCafDSWJiIjqt\nd0ZXpw2lsNxY6+sXeNe/YanL6+/TAreszObL4RqV+PgIiooqL+i+DoeDfv1e5dFHnyQqKvGC/55w\ndhdz7QXfE9f/7MJlPRWuKgqNRiSPB0mS0Gi0lJSUEnKqL6slv4LMDi1rdf3i4yMgNpmf9u+nWbge\np9OJTqdFpVaj0wXhdnv3zpc7qojMurRBfK9WrlzByZN5mExFREfHoFJpuPXWu+v9uQXqz/7pnwlZ\nlnG7PT5/DmaLA5fbg+zxUFBQiMvpRJZlVKhxuf84SMJiddb6Zz8Qr39D4Yvrf64CuSYdweWaRxF8\nYd682aSlNeH22+9UOoogCHXkqhZXUngsD5fTidvtRqPVolKpiIv74xObGEcUmRm1a9119OhRJk6e\nwJoiE9aqKrRaLWq1hvi4eKKjvZ0bPLLM4YhI2nW6ulaP5Q8kSWLhwk9wOKpwOKqIjIzk1ltvI07s\nyvcb0eE6PB6J0rJSJLcbt9uNWq0mvyAfye0GvMV1ZJjodCr8vYv66cjOzj4OdK6bKP5PkiT27tmH\npdJCRmYTmtRyzZHFYmHdmo3YLE70+hBiEw106tTxnBsbNmz4me3bt/DOO++KDRCC0IBd0uwSDry5\nk7gb0lCHaNDqdERFRREc7D3koeqwhUdveLxWj5GXl8trr/WjtLSYEwX5uJxOeqWm0jGjKYaYGACM\nVXbyDAZu+Y9v2pEpbf36deTmnqSkpASDIQadTsuDDz6sdCzhT269sSubZyymzKJBkiRkZNQaDYZo\nQ/Wa8Kryk/S8rYvCSQV/Jt7+XABZlvnum1XkHClGH5RMUFAIv+3agy50K1d3bUubS1tf9Jgrv1/N\noQNFxEdnolZrcEgafjtZxvZNH9P73u6kN0nn6NGj5J7IIzI6knbt2lJcXMRbb01h1Khx6PVi3ZAg\nNGSff/4pnlInu9/fSGLbVOLbpBAXHoftSAXpoancceODJCUm13h8o9HIwIH9KCoykpubS3R0NJVR\nUZRffS0lKWmUVNlRBQXRpNPVXHVpWx8+M+XIsszChR/jdDqw2+0kJSVz4409SU5OUTqa8Cd6vR5r\n/i6schM0wZHodDq0Gg0xp950Oe1mLmsSQlJiksJJBX8mCtzzkGWZTz76EpUjmYToVtW3x0R7f7Gs\nX3UQt1ui/WUX/gtg3dqN5B1xkxjT/Izbw8MiCQ9rw/zZi0hMTkArxxCpj+VoVQmb1nzG1p2ruO++\nB2nduo1vnpwgCH7JZDLx1VeLqKw0I1W60OZ5uL7T1dx15b3ExsYRGhpaq/FLSkoYOLAfBQUF5Ofn\notfriYmJ5c4776Jv334NYqb2bLZs2cTRo0cpLS3FYDCg0ah5+OH/UzqW8D+ysw9y5OBOSio2ERrf\nktSsLiQltUByVUFlPte0TuLOW8QBHMK5iQL3PPbu3Y+rMpoIfchZvx4bnc7GtXto1/7SC/ql4PF4\nOLAnh/ioVmf9ek7uIYLVyeikRKIN3uMi9eGRVNmdXJJxE2o57Kx/TxCEhmPBgveoqqqiuLiY5ORk\nDIYYnnyyD2Fhtf/3X1FRzqBBr5Cbe4K8vFzCw8OIjY2jZ89beOGFlxtscQvQrFkLrr++Ox988B7x\n8Ql063YD6em+a28l1J4sy8yZMxO320158Un0ISrkfAc33tySGEMYV1/5EBqN6NYknJ8ocM9j/+5D\nROjP/QIYFpTMzh276HjlFecdb9fO3YQHeWd/PR4ZSXJXn/zi8UiUlZSSkdoOl6uq+u/YbDbM5gqa\nZrak3FTEod8P07JVi1o8K0EQ/NXhw4f48ccfKC8vIyQkhNDQMP75z6d8UtxaLJW89lp/jh07Sl5e\nHsHBwSQmJtK583W8+uog1Oqa7DsOHImJiej1evr1649Op+Omm25WOpLwP9avX8f+/fsoKSkmMjKK\n4OBgBr7an04NYIOjUL9EgXsedoub4PBz3yc8NJKC/KILGq+0pIywUO/MrNlcQVGRCZ3feis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/6J2bPf5IILBm332pdffpHnnnuW4cMfcGOtghQWrmf69Jfo129A2KI422DEiIcZMOB8mjRpGrYo\nTh3HDdwqEo/eHn98X8aNG8MNN3jPSsepy4wc+Sj9+vXf7gI/a9ZMnnrqSYYNu5/WrVvXkHTJz7Rp\nUznkkMNo06Zt2KI45fjoo3ksXbrU27Y5tQI3cKvI/PmfUFBQwHvvvcOgQRfSoUPHsEVyHCckPv98\nPgsXfsfpp5/1m9e9885sRo58lKFD76lQGoNjFBUVMW3aVPr3Pz9sUZxyRCIRHnvsYS699Apvb+fU\nCjwHtwrEo7ft27enrKyMU045PWyRHMcJiWg0yogRj3DRRZf8ZoHpvHlzefDB+7n77nvZddcuNShh\n8vPSS8+z//4HeCChFjJ9+ks0bdqMQw89PGxRHAdwA7dKzJ//CT/99CMADz/8OPXqeUDcceoqs2e/\nSTQa5aijjvnVaz777FOGDx/KbbfdRdeu3WpQuuSnpKSEqVOf4e677wlbFKccGzZsYNy40Qwdek+F\nej47Tk3gBm4FiUajfDTvIxYtXE5Og7ZMefpFZs56jpKSEq655jpatWoVtoiO49QQhYXrefWDV1ld\nso60NGjVII/Jo8dyww1/pyB/JZ/PepVYYSFkpNOs2x4c0Pt3fP31V9xxx63cfPOtFe6NW5dZsWI5\nC+a/RVrsF2Kk8/W3P9Otm9ClS9ewRavTRCIR3n5vLt8tLqAsqy0TprxE/hKlV69D3WlzahXbNXBF\npB7wMNADKAEuUdXvd7ZgtYnlPy9n6uRXycnqQMPsXThon1PYkN+ErOiutGuT/ZsRG8dxUotZ773G\nW4vfp1HnJtRLt12br1b8QLRrFnPemEG3Favp2rDR5kjWhh9/YvxLz/Pc11/xt5tvY9999w9T/FpP\nLBZj1szJNOBHundqTlpaGrFYKZENy2mSncPSpT/Srl2nsMWsk3y38Aeeev5tyrI7k9mgLe16nMyX\nq5qzYEERpx3ZPWzxHGcrKrKnfjpQX1UPA24C7tu5ItUuSkpKmDLpNVo1607D7C0N2FeuXEnbVl04\n7IBzeOG5GSFK6DhOTfHBpx/w3rqPaLxbs83GbSQSoXDDOjod0oXvot+TGYtstU1bPxajQ0E+p3bq\nRPfubgRsj7fffJ7Oefl069xisx7XF66nRfPGHNu7I/PnTKaoqChkKesea9etZczzH5DWvDuZDRpu\nPr6qoIDOex7MwvXNeXHmGyFK6DhbUxED93DgFQBVnQv03KkS1TLeevNdWjTebatjkWiUjRuL2GWX\n9jTMzmHpokI2btwYkoSO49QUH3w3lwZ5Dbc6tnr1anJyGpO2aRONu+UxL7p687nS0k0sWbqEvLxW\n/D6vNfNmTK9pkZOKkpISitd/Q+NGDTYfixFj9erVtGhhfYL3lSZ8NPe1sESss0yf9S7pTbdeC6PR\nKMXFv9C8WXMys5vw0VfLiUQiIUnoOFtTEQO3CbA+4edIkLZQJ/h58RoyM+pvdax00yYaN25MTo7N\ni2/ZrDPvvTs3DPEcx6khli5bwqr667Y6Vlpayvr168jOyiJuki1vZk5wWWkpS5YsJjc3l8aNm5Be\nrx7FC7+recGTiE8/eZc9ds3Z6lhhYSHp6elkZ5tjkZGRTsmGJWGIV6f5YVkhaYmF1LEYZWWltGyZ\nt/l4pEE75sz7KCQJHWdrKlJkth5IHI5eT1Wj27qwefOGZGSk1pCDemnpW/1O0WiU7OxsOnXqtHmg\nQ0ZGOvUzSsjLq9oM+are71Qe1324JIP+Fy0uIrtZ9lbvg7KyUlq3bk29WJR68bSEhhlEC2PEYhFa\ntmxJ8+YtNl9fP1ZWK3/X2iJT/cwyGuU02OpYZmYGbVq3IjNzi97r14/WGpmrSrL8HtF69cjM2GLg\nRqNRmjRtSosWW8ZLZ+bkUBYtTprfCZJH/6nKztR/RQzc94BTgGdE5BDg81+7cM2a1Numj8YilJVt\nveXSrdvuxGJsPh6JlFEaiZGfX1jp/5+8vMZVut+pPK77cEkW/dfPyOGXtcVkNtzS4zYjI5OcnEyK\nCguJxmKkpaWRVlRGvVga6fUbUL9+g63eH5vqZ9a637U26b+0NJOiDcVkZW0ZFJAd5HuWlSbocVO9\nWiNzVahNut8e9aJRSsu2jm116NBpq2OlxUVkZjRMmt8pmfSfilSH/n/LQK5IqsFzQLGIvIcVmP2l\nStIkGe06tKC0bNNvXlOwbhGH9+5VQxI5jhMGu7RtR+6mJts81zAnh+Lg323WQfo2emJHolEaeIur\n32T/A3vz9Q8bfvOasrIIDRr7oIeapssuTYhFt7l5u5n04qX06nlgDUnkOL9NWiwWC1sGx3Ecx3Ec\nx6k26kyxmOM4juM4jlM3cAPXcRzHcRzHSSncwHUcx3Ecx3FSCjdwHcdxHMdxnJTCDVzHcRzHcRwn\npXAD13Ecx3Ecx0kp3MANgbo06thx4ojIQcF//fkPARFptv2rHCf1EJFWYctQlwlL/77Q1BAi0kRE\nnhWRJr826tjZeYhIhohME5HDwpalLiIiewEfiMheqhoVkbSwZapLiMj9wP+ISE7YstRFROT3IpK5\n/Sud6kZEJgPXu4MXDmHq3w3cmqMlcBLwD/AoVk0iIhlABDgAOFdEtj2OytmZdAB+Bu4FUFWfMFMD\nBM8+QGegO9A7PGnqJiKSDczA3v9ODSEi9YN/5gDdAB+xVoPUBv27kbWTSVhgGgPDgQEisqtHcWsO\nVS0D2gKvAfsAPcKVKPURkX2C/2YFh/bFjKvmInKuiLQLTbg6QDxaoqplItIUKAa+BXYVkV0SFh9n\n59MdWA6cIyLNwxYmlRGRRiLSEkBVNwXr7xfAN8B+IrKH72LsPGqb/t3ArWZEJE1E2ojIGNhsXAFc\nAIwCbgZeFpE7wpIxlQn031hEnhSRDgmnjgeeBO4CHhCRib5ltXMQkcOBGSKSqaolweEcVf0RmI59\nD4PDki9Viad9iMitmDEVTwNpC8wERgInA5Mwh8OpRhL03yt4D8XX1/bAVcAmbAfJ06R2Ho8DZyQ4\n1vsDi4DbgAHA84CEI1qdoFbp3w3caibYeu0MDBSR8xJOFQB7AodjC04ZgIik17SMqUh8cQn03xLo\njy3y8Qj6GszI7Q+0Alao6towZE1lAu98ANAEuDs41hw4XESew15uH2MpI4jn4lYbqhoTkdaY/nsC\n+wWnGgIDgVuwd88iYFUYMqYygf47AU8DPRJ26Tph6TkfAMOAKzwft3oRkXoi0hU4GjgK2CM4tRE4\nG5gMrAPew6LpTjVSW/XvBm41EBQwZQb/zgXOAO4HhiV4Mkdg+YcvAv2AawBUNVLzEqcWItIASwGJ\ncxIWLT8RcyrAPMkTgBeAs4BDRWS3mpQzFQm2pM4JisgAsoHPsUV9gIjsqaprgA+BV1T1fOBMYJCI\n5HgubtUQkYYi0iHBUT4ES8VZhj3jDYGmQAkWxT0JyAeOSHD+nGogSPu4BNP3H0QkO/he2gIPYgv/\nK8D3qloanqSpQbDdfaSIZAfORBvgJsyA+l2wLuRiz/vNqtoHqI/9XfizX0WSQf9psZivL1VBRP6C\nRWUXAv9S1WUicpKqviwi44FCVb1cRPYAflLVjcF9V2BbhhFf5CuPiFyKRay+At5T1fEi0lNVPwrS\nQFqo6pUi0gL4RVV/Ce47G5iWkELi7CDBVusTwCygC/Y8vwS0V9VFInIbcKiqHici9eLdE4JIV6Yv\n8lVDRAYANwJzgExVvVhE8oBC4FjMoHoWmAekx9NFRKQnMN+f/aoROA9XAvOBT1R1lYicDnwKjADu\nV9WZIvInoFhVR4lIYyyadYmqLgtN+CQlYcfnb0BfLL8zC7gPWKyqhUGK1GXAI6r6Qbn7O6vqohoU\nOaVINv27gVsFROQQYAiWX/Wn4PALqvp+cL4l9rI7RlU1OJaVkJfoVAERaY9Faq/C0hIuBj5U1UeD\n802xBX64qr4WHKuvqptCEjmlCBbu1ao6KVjYe2GG0+SEa74E/ldVnw12Ocrcoas6QSrIU8Btqvpp\nkP6hqnpTcD4LuA4oBSaq6hJ/9quPYMdiFPAullvbFPg7UC8wdAcDxwEXqmpRuXvTfeeuaojIOOAu\nVf06CDKdqqpHJZy/BYgBY1T1JxHJSHTo4o52zUueGiSL/j1FYQcRkU4i0jEoIDgQ+EZVfwIeApYC\nfQMvHVUtAEYDE+L3u3FbNURk12BbpAXQDvhKVb8B5mIRxPOCPERUdR1m4F4vQWswX+ArT6D70SJy\npYjsiqUjnBqcngUo0EO2buo9DNu2RVVLfVGpPCLSWUSuFpHdMYNqEZZfC/A/WEpIJ9j8npkN7A7s\nFRzzZ7+KiLX8Assxf1VVr8Oe8XWYI7cKQFVHYuvrwIR743UCbtzuICJyvIjcKSInBKllhUBmYCg9\nADQSkQsSbpmArc9tYatib4Kf/T20AySr/t3ArSBBEvUQYBpWrPEI8Axm0Oaq6lJsqyoDKzIDQFVv\nAR6ueYlTDxG5FqvCvBAYA/yA5RJ2DBaNj4H3saR2AFT1MeBhVV1f8xKnDiJyLBYx/BArkHwGq5jt\nLCIHqOoGzMBtBWQkLOZjVfWEkMROGYJUnKlY8cYQ4GAsQtI2yGVegnVH2NydRVXfw7YJZ4Ygckoh\nIl2ClLN/isiRQB5b3vPrsZSEPUUksQXhE0CvuFHsRtWOIyLpInIdtiW+BKvGb47lch6Orbdg3XFO\nid+nqt8Bf1bVuTUrcWqR7Pp3A7fiHAwcBvxOVS/Beqk2wdoe3QKgqu9gPQ/rwZYeuKr6RBgCpxIi\n0hHrgnCQql6IFTHlYQbvXWARQiyKviq4J67/aSGInBLIllZHuwDPq+rD2ML9NWboTiYwqoJ8q12A\nLF/Mq49gR+hE4ChV/RMWPUnDisl+TxChxdqvLQsWpXoAqvpJzUucWojInlhAYybwBpaa8Dqwj4j8\nPiiwWYblQse/C1R1uqpeFM/7dypFJvbsXxiknr2NpUI9gBlU+wTXrQY+gy3vrKAtoXdqqRpJrX83\ncCtOd+Bl4BexJvUbgBVYcnVfETlGRPbGPJq4YeVFHNVHFhYhjzdK/wpohBm37UTkKhE5AavQj4Lr\nvyoEBTQktDoqwjqAgLWgaglsUtV/Y8MbhonIm8Bi7GXnVBOqWoi1uWsZHFoP7IZNx1oGDA5yPh/B\n2t9F1AfJVJkE5645UBLsRjyPNa1vgXXKGSIiLYOUkI5Y2ohTDQTb38XAeIK2gti7vVRVvwTeAi4S\nkfuwNJEi2OqdRfCzO9uVICgMTmr9e6uMbSAijeKFAQnJ0C8Ca1U1EkRUVgQLT6GI3IC1oOoN3Keq\nH4cmfAoQ6LdUVYuDP7IotnAMCfSfixm336hqabCFsj+Wh/iQqk4NTfgkR0TaArcC74rNEC9T1aiq\nPptwWX9gum7pgnA0lm/1gUfLq0aQW14aVCOnA7Hg+b9YrQtFNtbf9nq1bhQjsbSFAdizPyU86VMD\nEWmtqisSFuolbBmx3gZb7AtVdayI7AfcLDa5Lx/4KRShUwAR6QWkA58HKU9p2PM/KjjfFHvPjwpu\neQJrDzkAuFxVP695qVMHEemNpZgtCOpa4mlmSat/N3DLISK3Y1tPnwH/VuvhiarmJ1x2AdbPEBG5\nDBjnC3v1IDZd7E6sIfRELM8Q3bql1MnAO6q6NsjLnRX8EY4q/3lOxRGRi4G/YikHE7fleQfbTfWB\np0Xkz9h3cV6Q7+lUnduxqvxrgWj8O0gwtvaxH/U/IvJXYKWqjsWq+Z0qEDh3twCrReQeYJ2qxoIi\n4rjhejawKHj3ZGPOYBNgD1WdFYbcyUzwPskChmJO8gLgAhEZov89iGc3rJh4pYg8BnysqiOAfwaf\nFd8a992LClJO//tjqTdDReRotZanid0Okk7/nqKQgIicBXQDrsaisWcFx9MTrskMznUUkWnYH2W6\n5/lUG0dg7XUOEZFOQZSq/HN6OlbQMQXLhfaoSRURayuVh73olgD/EpELRESC8/HvoBlW5PcisCsw\nqJzz51QSETkAK9z4vYgcFDz76cG5+PulD9BbrC3YnljalFNFRKQ/1tJxBtaUfo36aYsAAAzkSURB\nVG18YRcbuxtfA9oCU4LAxhtAO1Vd4sZt5Qh0XB8bZ3wGcD0WxW20jcsHAH8ExmI95UfET8R3+mqT\ncZUMBPrPAToAZ6nqnViuea+E83GSTv91PoIrNoBhraouBw4A5qnqYhGZhUVys3XLcIB6mBGwG2bY\nDlXVeWHJngoE6Qh/xoZkbMCMpjFAMXAa8GD8j0a29I9sjLVJ+qsX0VQeEdkf65X6NmawKpbmsQSb\n+HYYZmz9Ta3lHVgRzUzgdlX9tOalTg0CgzUdq76/Ltgp6gjcg20NDgHO0C0tpdIIuiZgEZf/rY1b\ngslGwvt9MTakZCMwMdjB+yZIzamX8D0MBs7FOlqcpT6soVKIyDlYqsd8LHdzLRZQKsVaD84RkU9V\ndb5s6R2/Emt99+e4U11bDavaTqD/fbAi+UaYs1YSBPAOItgNDd5TaYF+k07/dXbQg4g0wraj+mDT\nOBZhW+IPYh7NLtiXXx/LN5wW3JcF9FHV6SGInXKIyO+wHsL/UtUnxXqolgDHYNHccWpTyeKTsNKB\nvVX1sxDFTnpEZCC2WI/AppAdjEVQHsMct+/Eet3+BUtX+OBXP8ypFCLSHJuAOFpVrxUb3tCEwMgC\nnlTVyQmOHSLSQlW9iK+KiMiB2FjRxVjPznysUKYxNlK9GTAcOE5VfwiCG60xZ/w59fZTlUJsnPGt\nWITwVeydMxDT7Q2YA3cjFkC6WFX3SLg3JwiCxINNMS8g2zEC++UOrGj+VaAfNlXv6+B8Z6y1YN9t\n3Jt0+q/LEdzjgY6q2jMwdt/EqmIvxiZ09AYQ630b3yaMj7t047aKBJ5hDjbS71PgBBF5R1W/D87P\nwQyvviLyiW4Z8xohaEfi7DgJRXttMMPqqaBwpnNQsHcT1iEErOVaHtZv2KlGgoV+IOZgDBCRyYHR\nFF9AHgauFZEpqloWz4Vz47bqiI0SvR1733fCvoODsDzmL1R1dnDdoVg61APB38zPmFHsVJ5GmPF6\nfPBcNwMGYW2n3sDyy98Qm4C4W+IOaoJx5ZPgKk9TLMXy8CAFqmfw89fB+QOAFwJn+3asNeRsSE79\n1+Uc3C5YD1WwlIMV2FZJJtBfRFqLNfQ+AWvR4xNoqpFgsS7E+qjehW1VXZJwfinwOZabtX/8nhBE\nTSkStpKWYQUFAEeypbXdSuA1ERmOFVL+hHUK8RzzKlBef2pTxb5S1RuBu7EFPvHaGVg/5zOC6/3Z\nryIJ30FbYKmqvqzW13k15vA9AcwNnA+wKXFv1bigKUrgpK3B1trzg8P/h6Xm7IGlPx0lIndiKVLz\ndRs9hH0drhKrsBTAFsHPJdj3EWdA8L9nsHaE/1U8nEz6r3MGbsJLbjzwdPDvNsB3QS7JImxaxwOY\nB3OLqr5R44KmEOWKNDYfC/75ktrUkzeADkHKQpz3gTvU265VmvK6T6h0Ha82IzwNqwx/OuG2flhe\n7t2qeqOqFrmBVXmCiEe8YCnxnfsmgKo+AmQHaSMA8bntF6nqMzUrbeohW6bqxZ/hzwiGwwR56Guw\nto+/YBXhj4jIW1h62qKaljdVEJv+ufl5DyKGWZhjvbeItA0CGd9jec1XB+caAOeqDRZwKkl5/YMZ\np6r6mKquEpEuWM3Lm8H1rbEdu/8Al6nqrfHdoxoXvppI+Rzc8uH0hC3axGtGYVOAPgIGqupjItJU\nVdfVrLSpRRAJ2U1Vvwp+ztSt231t7jMcFJtdABytqueEIG5KURHdB8ezsbzzG7B8272A89UafDvV\nRKDnq4HZqjon4XhGsIgcC0xT1W1VjzuVpFz+8n9trQY7FWtVdWjwHTXBBmq0UJtM6VQREemGdfx4\nVa23eQ+soCyiqreLyBHYVKwhie+oZMnzrO0k6H9mkGIZP34SIFiw735sB2NZQj5urWv7taOkbAQ3\niFylJbzczhRrOxWvyE8L/tsM2BfLwZoKdA1ehG7cVp0TsC0oROQPwHQRuUJEDg6ObY5sBekKbwLP\nlY/2OpViu7oPruuI5Z3H200NcuO2aoiNyk1L+Hl3bBHZN9G4BZu2F7ynXsNybjOTOWJS21AbDJMt\nIjdi73hgyxhvLFr4uoj8HeuikK6qX7pxWznK7RaliciF2LtlHdYhAazX7QTguCC4NBp4vbxxG+yo\nunG7A2xH/5vKXX4hcAUwEpijqm8kGLfpWou7I1SUlIvgytaNiQm8xcux8aLfY5XJM+PXYhGrt7A2\nScPiX7BTOQKvL9GxGIVVJC/FHIi9sclX/RO9SafqVEb3InI2lud5q6p+G4rgKUS5iOEhWNHYeqy/\n5zpV/cc27vmvXSWncgQL/GbDKHAu/gkUq+p55a7NxuouPsf+Pu7TYIKls2OUf4ZFpCuW3vEnzGnu\nWf46scEa3YBP4gVMTuXYAf2nEbS9ExuxmwXcoKob4+dTyalIKQN3G+kIPTHD9X9U9VmxjggxYIKq\n/hhc0wrYS1XfDEXoFEVEWqnqyiDPZzxwjarOFZGW2DCBcR4l2TnsiO5T7YUWBsFCPRB4Sm36T1us\nn21n4BdM5/Hq5WdVdY4btdXPjjoXIiLY7sUoD2xUDhFpkLjjIyJ7YW3WGgDvYHUUxwL/UdUnfu25\nL++YOBWjKvoXkUZxhy5V9Z9SbcICryQDGzf6tapOE5EPsTwTsMrkC7FKzbFBCH4l1sDYqQRB1PAi\nbGzf/ODnO7ABAd8D/8JSD/pgY/6iWK/JL0MSOWWoDt2n2gstJC7Cxkv/gvV07ge8pqpjRGQ81mrq\ncaxzy7ki8lFQROZUkQo6F69j098OCZyL9KDYRrHcc2cHCdbZ24H9ROTPqvqtiPwNGx5wH/aOGYRV\n5I8F/iQi01X152181uZdJ6diVEX/sqXlYFFiRDes32VnktQ5uCLSVUQeDyJTiEhfLI+qA3CS2Kz2\n64GBItJQbfLSQqAQmwzkVIFge3sW5kDEt7fPBxqq9RHegA3TmAQcLSLDsEECS4ENnmtYeVz34SI2\n8SfOC1hLtd+JyN5YX+dcEXkc2/4+DmtsvwTrteq6rz4uwlIQzgp+jjsXvbHAxelYatoyzLnISNXF\nPAR2B5YDV4tNxvoP0Bx4JzBkZ2ITylYC32BOx3/hTnalqZT+E/UdGLop+/eQ1BFctWlL7bDRfqOw\naSj3YQvM9cCZWGXg21gi9fnAw9uqJncqTlCYNxNbsK9W1QXlLmkvIk9i43b/gzkUY7DJZH9Tawvm\nVALXfbgEEcLngWki8qja4IVczHH+EJsKdI3YMIFJqjpLRA7D3rWz1Ac1VBnZuiPIC1jqx+9E5E3s\n3d8zwbm4EJtUuQT4EXcuqkwQAS8TkXnYxM/hmCM9GhvecxTm8B2Dtbz7QkRu9l2L6sH1X3GSNoKb\nUC04HPPMd8W8lP2wHrZvYxOYRmLjFScDuHFbLazDFox3VHWBiLQXkfvFxvytw/oKf6uql2O5h79T\n1XGqOtgNrCrjug+XUsx5uAxLBwHLdeuC5XumichZ2HcxUkReAx5X1UfduK0aItI2WNSvF5F4o/q4\nc/Ey5ly8jRXOTFLVYdiaEHcupvj7v1qI59B+B3wFZGOpTydjnSqGichYoAc2JW5zt5AQZE1FXP8V\nJCWKzETkMWzi0n1Y5HYGNp2sG7BeVR8MUbyUJNiKHYltuXbH8kBvCdJFTgYOw/T/gaoOCU/S1MN1\nHy4ichzWs7kN9q6Zj/VP3Yg1Sj8L2zo/0ItXq4/g+Z6Kjdd9SVWvDPLOX8L+Ho7EAhutsXXgO+BB\nVX0xHIlTGxE5F/g3luc/SVWfF5GRwPFYz9tLguu8kHUn4PrfPklt4MqWJuldgYlYSsKl2AKfD1yl\nqgVhypjKiI1U/AOwu5YbqRhUKK9W1fxQhEtxXPfhEaSJDMZy2p7CBmV8j43c/RlzMibFW+841Yc7\nF7UHsTZrLwFX6pb+qVnYoIxp2NAk706xk3D9b5+kTVGAzWH3lsHW62fA4ap6M9bns78btzudB4Gv\nscpNRKS+bBmLqW5g7VRc9yGhqmuB2dg89+VYqsJewGmqulJVR7lxu9OYh+XUfgvMwVLUBmCFNLOw\nVIUyN25rhDxszHFRQspgRG387p3AitAkqxu4/rdDskdw22GtkGJAO8yTmR+uVHULEbkYm1t9cNiy\n1DVc9+EhNgr5aqyH9kUi0l5Vl4QtV11AbBrfX4AhmIN3F/CMqt4eqmB1kCDX8wZVXR78XGe3w8PA\n9f/bJLWBC5sndhwKPK0+GavGEZEGQH+sUt9bvtQgrvtwEZvx3lNVJ4YtS13CnQvHcSpC0hu4juM4\nTt3CnYvag/hUvlBx/f86buA6juM4juM4KUVSF5k5juM4juM4TnncwHUcx3Ecx3FSCjdwHcdxHMdx\nnJTCDVzHcRzHcRwnpXAD13Ecx3Ecx0kp3MB1HMdxHMdxUgo3cB3HcRzHcZyU4v8DSDe468eySDMA\nAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x115b4908>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"epipy.case_tree_plot(merged_df, 'Cluster', 'ID', 'Date', 'Cluster', 3, 1);"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 2",
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