Skip to content

Instantly share code, notes, and snippets.

@olgabot

olgabot/shalek_sujita_2013.ipynb

Created October 30, 2014 18:21
Show Gist options
  • Save olgabot/e694908e7cba4996f399 to your computer and use it in GitHub Desktop.
Save olgabot/e694908e7cba4996f399 to your computer and use it in GitHub Desktop.
Download ZIP
Display the source blob
Display the rendered blob
Raw
shalek_sujita_2013.ipynb
{
"metadata": {
"name": "",
"signature": "sha256:04ea795d3bfb20dd56e0fd467d01c4f640c0d80d4f4fb71fa0b9659445a667b4"
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Before we begin, let's import everything we need."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Import the flotilla package for biological data analysis\n",
"import flotilla\n",
"\n",
"# Import \"numerical python\" library for number crunching\n",
"import numpy as np\n",
"\n",
"# Import \"panel data analysis\" library for tabular data\n",
"import pandas as pd\n",
"\n",
"# Turn on inline plots with IPython\n",
"%matplotlib inline"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Couldn't import dot_parser, loading of dot files will not be possible.\n"
]
}
],
"prompt_number": 1
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Shalek and Sujita, *et al* (2013)\n",
"\n",
"In the 2013 paper, [Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells](http://www.ncbi.nlm.nih.gov/pubmed/23685454) (Shalek and Sujita, *et al*. *Nature* (2013), Regev and colleagues performed single-cell sequencing 18 bone marrow-derived dendritic cells (BMDCs), in addition to 3 pooled samples.\n",
"\n",
"## Expression data\n",
"\n",
"First, we will read in the expression data. These data were obtained using,\n",
"\n",
" wget ftp://ftp.ncbi.nlm.nih.gov/geo/series/GSE41nnn/GSE41265/suppl/GSE41265_allGenesTPM.txt.gz\n",
"\n",
"We will also compare to the supplementary table 2 data, obtained using\n",
"\n",
" wget http://www.nature.com/nature/journal/v498/n7453/extref/nature12172-s1.zip\n",
" unzip nature12172-s1.zip"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"expression = pd.read_table(\"GSE41265_allGenesTPM.txt.gz\", compression=\"gzip\", index_col=0)\n",
"expression.head()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>S1</th>\n",
" <th>S2</th>\n",
" <th>S3</th>\n",
" <th>S4</th>\n",
" <th>S5</th>\n",
" <th>S6</th>\n",
" <th>S7</th>\n",
" <th>S8</th>\n",
" <th>S9</th>\n",
" <th>S10</th>\n",
" <th>...</th>\n",
" <th>S12</th>\n",
" <th>S13</th>\n",
" <th>S14</th>\n",
" <th>S15</th>\n",
" <th>S16</th>\n",
" <th>S17</th>\n",
" <th>S18</th>\n",
" <th>P1</th>\n",
" <th>P2</th>\n",
" <th>P3</th>\n",
" </tr>\n",
" <tr>\n",
" <th>GENE</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>XKR4</th>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td>...</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.019906</td>\n",
" <td> 0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>AB338584</th>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td>...</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>B3GAT2</th>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.023441</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.029378</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.055452</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.029448</td>\n",
" <td>...</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.031654</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 42.150208</td>\n",
" <td> 0.680327</td>\n",
" <td> 0.022996</td>\n",
" <td> 0.110236</td>\n",
" </tr>\n",
" <tr>\n",
" <th>NPL</th>\n",
" <td> 72.008590</td>\n",
" <td> 0.000000</td>\n",
" <td> 128.062012</td>\n",
" <td> 0.095082</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 112.310234</td>\n",
" <td> 104.329122</td>\n",
" <td> 0.119230</td>\n",
" <td> 0.000000</td>\n",
" <td>...</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.116802</td>\n",
" <td> 0.104200</td>\n",
" <td> 0.106188</td>\n",
" <td> 0.229197</td>\n",
" <td> 0.110582</td>\n",
" <td> 0.000000</td>\n",
" <td> 7.109356</td>\n",
" <td> 6.727028</td>\n",
" <td> 14.525447</td>\n",
" </tr>\n",
" <tr>\n",
" <th>T2</th>\n",
" <td> 0.109249</td>\n",
" <td> 0.172009</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.182703</td>\n",
" <td> 0.076012</td>\n",
" <td> 0.078698</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.093698</td>\n",
" <td> 0.076583</td>\n",
" <td>...</td>\n",
" <td> 0.693459</td>\n",
" <td> 0.010137</td>\n",
" <td> 0.081936</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.086879</td>\n",
" <td> 0.068174</td>\n",
" <td> 0.062063</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.050605</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows \u00d7 21 columns</p>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 2,
"text": [
" S1 S2 S3 S4 S5 S6 \\\n",
"GENE \n",
"XKR4 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"AB338584 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"B3GAT2 0.000000 0.000000 0.023441 0.000000 0.000000 0.029378 \n",
"NPL 72.008590 0.000000 128.062012 0.095082 0.000000 0.000000 \n",
"T2 0.109249 0.172009 0.000000 0.000000 0.182703 0.076012 \n",
"\n",
" S7 S8 S9 S10 ... S12 \\\n",
"GENE ... \n",
"XKR4 0.000000 0.000000 0.000000 0.000000 ... 0.000000 \n",
"AB338584 0.000000 0.000000 0.000000 0.000000 ... 0.000000 \n",
"B3GAT2 0.000000 0.055452 0.000000 0.029448 ... 0.000000 \n",
"NPL 112.310234 104.329122 0.119230 0.000000 ... 0.000000 \n",
"T2 0.078698 0.000000 0.093698 0.076583 ... 0.693459 \n",
"\n",
" S13 S14 S15 S16 S17 S18 \\\n",
"GENE \n",
"XKR4 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"AB338584 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 \n",
"B3GAT2 0.000000 0.031654 0.000000 0.000000 0.000000 42.150208 \n",
"NPL 0.116802 0.104200 0.106188 0.229197 0.110582 0.000000 \n",
"T2 0.010137 0.081936 0.000000 0.000000 0.086879 0.068174 \n",
"\n",
" P1 P2 P3 \n",
"GENE \n",
"XKR4 0.000000 0.019906 0.000000 \n",
"AB338584 0.000000 0.000000 0.000000 \n",
"B3GAT2 0.680327 0.022996 0.110236 \n",
"NPL 7.109356 6.727028 14.525447 \n",
"T2 0.062063 0.000000 0.050605 \n",
"\n",
"[5 rows x 21 columns]"
]
}
],
"prompt_number": 2
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"These data are in the \"transcripts per million,\" aka TPM unit. See [this](http://haroldpimentel.wordpress.com/2014/05/08/what-the-fpkm-a-review-rna-seq-expression-units/) blog post if that sounds weird to you."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"These data are formatted with samples on the columns, and genes on the rows. But we want the opposite, with samples on the rows and genes on the columns. This follows [`scikit-learn`](http://scikit-learn.org/stable/tutorial/basic/tutorial.html#loading-an-example-dataset)'s standard of data matrices with size (`n_samples`, `n_features`) as each gene is a feature. So we will simply transpose this."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"expression = expression.T\n",
"expression.head()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th>GENE</th>\n",
" <th>XKR4</th>\n",
" <th>AB338584</th>\n",
" <th>B3GAT2</th>\n",
" <th>NPL</th>\n",
" <th>T2</th>\n",
" <th>T</th>\n",
" <th>PDE10A</th>\n",
" <th>1700010I14RIK</th>\n",
" <th>6530411M01RIK</th>\n",
" <th>PABPC6</th>\n",
" <th>...</th>\n",
" <th>AK085062</th>\n",
" <th>DHX9</th>\n",
" <th>RNASET2B</th>\n",
" <th>FGFR1OP</th>\n",
" <th>CCR6</th>\n",
" <th>BRP44L</th>\n",
" <th>AK014435</th>\n",
" <th>AK015714</th>\n",
" <th>SFT2D1</th>\n",
" <th>PRR18</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>S1</th>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0.000000</td>\n",
" <td> 72.008590</td>\n",
" <td> 0.109249</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td>...</td>\n",
" <td> 0</td>\n",
" <td> 0.774638</td>\n",
" <td> 23.520936</td>\n",
" <td> 0.000000</td>\n",
" <td> 0</td>\n",
" <td> 460.316773</td>\n",
" <td> 0</td>\n",
" <td> 0.000000</td>\n",
" <td> 39.442566</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S2</th>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.172009</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td>...</td>\n",
" <td> 0</td>\n",
" <td> 0.367391</td>\n",
" <td> 1.887873</td>\n",
" <td> 0.000000</td>\n",
" <td> 0</td>\n",
" <td> 823.890290</td>\n",
" <td> 0</td>\n",
" <td> 0.000000</td>\n",
" <td> 4.967412</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S3</th>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0.023441</td>\n",
" <td> 128.062012</td>\n",
" <td> 0.000000</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td>...</td>\n",
" <td> 0</td>\n",
" <td> 0.249858</td>\n",
" <td> 0.313510</td>\n",
" <td> 0.166772</td>\n",
" <td> 0</td>\n",
" <td> 1002.354241</td>\n",
" <td> 0</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S4</th>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.095082</td>\n",
" <td> 0.000000</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td>...</td>\n",
" <td> 0</td>\n",
" <td> 0.354157</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.887003</td>\n",
" <td> 0</td>\n",
" <td> 1230.766795</td>\n",
" <td> 0</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.131215</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S5</th>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.182703</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td>...</td>\n",
" <td> 0</td>\n",
" <td> 0.039263</td>\n",
" <td> 0.000000</td>\n",
" <td> 131.077131</td>\n",
" <td> 0</td>\n",
" <td> 1614.749122</td>\n",
" <td> 0</td>\n",
" <td> 0.242179</td>\n",
" <td> 95.485743</td>\n",
" <td> 0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows \u00d7 27723 columns</p>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 3,
"text": [
"GENE XKR4 AB338584 B3GAT2 NPL T2 T PDE10A \\\n",
"S1 0 0 0.000000 72.008590 0.109249 0 0 \n",
"S2 0 0 0.000000 0.000000 0.172009 0 0 \n",
"S3 0 0 0.023441 128.062012 0.000000 0 0 \n",
"S4 0 0 0.000000 0.095082 0.000000 0 0 \n",
"S5 0 0 0.000000 0.000000 0.182703 0 0 \n",
"\n",
"GENE 1700010I14RIK 6530411M01RIK PABPC6 ... AK085062 DHX9 \\\n",
"S1 0 0 0 ... 0 0.774638 \n",
"S2 0 0 0 ... 0 0.367391 \n",
"S3 0 0 0 ... 0 0.249858 \n",
"S4 0 0 0 ... 0 0.354157 \n",
"S5 0 0 0 ... 0 0.039263 \n",
"\n",
"GENE RNASET2B FGFR1OP CCR6 BRP44L AK014435 AK015714 SFT2D1 \\\n",
"S1 23.520936 0.000000 0 460.316773 0 0.000000 39.442566 \n",
"S2 1.887873 0.000000 0 823.890290 0 0.000000 4.967412 \n",
"S3 0.313510 0.166772 0 1002.354241 0 0.000000 0.000000 \n",
"S4 0.000000 0.887003 0 1230.766795 0 0.000000 0.131215 \n",
"S5 0.000000 131.077131 0 1614.749122 0 0.242179 95.485743 \n",
"\n",
"GENE PRR18 \n",
"S1 0 \n",
"S2 0 \n",
"S3 0 \n",
"S4 0 \n",
"S5 0 \n",
"\n",
"[5 rows x 27723 columns]"
]
}
],
"prompt_number": 3
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The authors filtered the expression data based on having at least 3 single cells express genes with at TPM (transcripts per million, ) > 1. We can express this in using the [`pandas`](http://pandas.pydata.org) DataFrames easily.\n",
"\n",
"First, from reading the paper and looking at the data, I know there are 18 single cells, and there are 18 samples that start with the letter \"S.\" So I will extract the single samples from the `index` (row names) using a `lambda`, a tiny function which in this case, tells me whether or not that sample id begins with the letter \"S\"."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"singles_ids = expression.index[expression.index.map(lambda x: x.startswith('S'))]\n",
"print('number of single cells:', len(singles_ids))\n",
"singles = expression.ix[singles_ids]\n",
"\n",
"expression_filtered = expression.ix[:, singles[singles > 1].count() >= 3]\n",
"expression_filtered = np.log(expression_filtered + 1)\n",
"expression_filtered.shape"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"('number of single cells:', 18)\n"
]
},
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 4,
"text": [
"(21, 6312)"
]
}
],
"prompt_number": 4
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Hmm, that's strange. The paper states that they had 6313 genes after filtering, but I get 6312. Even using \"`singles >= 1`\" doesn't help.\n",
"\n",
"At the appendix of this post, I also tried this with the expression table provided in the supplementary data as \"`SupplementaryTable2.xlsx`,\" and got the same results."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now that we've taken care of importing and filtering the expression data, let's do the feature data of the expression data.\n",
"\n",
"## Expression feature data\n",
"\n",
"This is similar to the `fData` from `BioconductoR`, where there's some additional data on your features that you want to look at. They uploaded information about the features in their OTHER expression matrix, uploaded as a supplementary file, `Supplementary_Table2.xlsx`.\n",
"\n",
"Notice that this is a `csv` and not an `xlsx`. This is because Excel mangled the gene IDS that started with `201*` and assumed they were dates :(\n",
"\n",
"The workaround I did was to add another column to the sheet with the formula `=\"'\" & A1`, press `Command`-`Shift`-`End` to select the end of the rows, and then do `Ctrl`-`D` to \"fill down\" to the bottom (thanks to [this](http://superuser.com/questions/298276/excel-keyboard-shortcut-to-copy-fill-down-for-all-cells-with-non-blank-adjacent) stackoverflow post for teaching me how to Excel). Then, I saved the file as a `csv` for maximum portability and compatibility."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"expression2 = pd.read_csv('nature12172-s1/Supplementary_Table2.csv', \n",
" # Need to specify the index column as both the first and the last columns,\n",
" # Because the last column is the \"Gene Category\"\n",
" index_col=[0, -1], parse_dates=False, infer_datetime_format=False)\n",
"\n",
"# This was also in features x samples format, so we need to transpose\n",
"expression2 = expression2.T\n",
"expression2.head()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr>\n",
" <th>'GENE</th>\n",
" <th>'0610007L01RIK</th>\n",
" <th>'0610007P14RIK</th>\n",
" <th>'0610007P22RIK</th>\n",
" <th>'0610008F07RIK</th>\n",
" <th>'0610009B22RIK</th>\n",
" <th>'0610009D07RIK</th>\n",
" <th>'0610009O20RIK</th>\n",
" <th>'0610010B08RIK</th>\n",
" <th>'0610010F05RIK</th>\n",
" <th>'0610010K06RIK</th>\n",
" <th>...</th>\n",
" <th>'ZWILCH</th>\n",
" <th>'ZWINT</th>\n",
" <th>'ZXDA</th>\n",
" <th>'ZXDB</th>\n",
" <th>'ZXDC</th>\n",
" <th>'ZYG11A</th>\n",
" <th>'ZYG11B</th>\n",
" <th>'ZYX</th>\n",
" <th>'ZZEF1</th>\n",
" <th>'ZZZ3</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Gene Category</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>...</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>S1</th>\n",
" <td> 27.181570</td>\n",
" <td> 0.166794</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0.000000</td>\n",
" <td> 178.852732</td>\n",
" <td> 0</td>\n",
" <td> 0.962417</td>\n",
" <td> 0.000000</td>\n",
" <td> 143.359550</td>\n",
" <td>...</td>\n",
" <td> 0.000000</td>\n",
" <td> 302.361227</td>\n",
" <td> 0.000000</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0.027717</td>\n",
" <td> 297.918756</td>\n",
" <td> 37.685501</td>\n",
" <td> 0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S2</th>\n",
" <td> 37.682691</td>\n",
" <td> 0.263962</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0.207921</td>\n",
" <td> 0.141099</td>\n",
" <td> 0</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.255617</td>\n",
" <td>...</td>\n",
" <td> 0.000000</td>\n",
" <td> 96.033724</td>\n",
" <td> 0.020459</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0.042430</td>\n",
" <td> 0.242888</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S3</th>\n",
" <td> 0.056916</td>\n",
" <td> 78.622459</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0.145680</td>\n",
" <td> 0.396363</td>\n",
" <td> 0</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.024692</td>\n",
" <td> 72.775846</td>\n",
" <td>...</td>\n",
" <td> 0.000000</td>\n",
" <td> 427.915555</td>\n",
" <td> 0.000000</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0.040407</td>\n",
" <td> 6.753530</td>\n",
" <td> 0.132011</td>\n",
" <td> 0.017615</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S4</th>\n",
" <td> 55.649250</td>\n",
" <td> 0.228866</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0.000000</td>\n",
" <td> 88.798158</td>\n",
" <td> 0</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 93.825442</td>\n",
" <td>...</td>\n",
" <td> 0.000000</td>\n",
" <td> 9.788557</td>\n",
" <td> 0.017787</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0.013452</td>\n",
" <td> 0.274689</td>\n",
" <td> 9.724890</td>\n",
" <td> 0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S5</th>\n",
" <td> 0.000000</td>\n",
" <td> 0.093117</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 131.326008</td>\n",
" <td> 155.936361</td>\n",
" <td> 0</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.031029</td>\n",
" <td>...</td>\n",
" <td> 0.204522</td>\n",
" <td> 26.575760</td>\n",
" <td> 0.000000</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1.101589</td>\n",
" <td> 59.256094</td>\n",
" <td> 44.430726</td>\n",
" <td> 0.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows \u00d7 27723 columns</p>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 5,
"text": [
"'GENE '0610007L01RIK '0610007P14RIK '0610007P22RIK '0610008F07RIK \\\n",
"Gene Category NaN NaN NaN NaN \n",
"S1 27.181570 0.166794 0 0 \n",
"S2 37.682691 0.263962 0 0 \n",
"S3 0.056916 78.622459 0 0 \n",
"S4 55.649250 0.228866 0 0 \n",
"S5 0.000000 0.093117 0 0 \n",
"\n",
"'GENE '0610009B22RIK '0610009D07RIK '0610009O20RIK '0610010B08RIK \\\n",
"Gene Category NaN NaN NaN NaN \n",
"S1 0.000000 178.852732 0 0.962417 \n",
"S2 0.207921 0.141099 0 0.000000 \n",
"S3 0.145680 0.396363 0 0.000000 \n",
"S4 0.000000 88.798158 0 0.000000 \n",
"S5 131.326008 155.936361 0 0.000000 \n",
"\n",
"'GENE '0610010F05RIK '0610010K06RIK ... 'ZWILCH 'ZWINT \\\n",
"Gene Category NaN NaN ... NaN NaN \n",
"S1 0.000000 143.359550 ... 0.000000 302.361227 \n",
"S2 0.000000 0.255617 ... 0.000000 96.033724 \n",
"S3 0.024692 72.775846 ... 0.000000 427.915555 \n",
"S4 0.000000 93.825442 ... 0.000000 9.788557 \n",
"S5 0.000000 0.031029 ... 0.204522 26.575760 \n",
"\n",
"'GENE 'ZXDA 'ZXDB 'ZXDC 'ZYG11A 'ZYG11B 'ZYX 'ZZEF1 \\\n",
"Gene Category NaN NaN NaN NaN NaN NaN NaN \n",
"S1 0.000000 0 0 0 0.027717 297.918756 37.685501 \n",
"S2 0.020459 0 0 0 0.042430 0.242888 0.000000 \n",
"S3 0.000000 0 0 0 0.040407 6.753530 0.132011 \n",
"S4 0.017787 0 0 0 0.013452 0.274689 9.724890 \n",
"S5 0.000000 0 0 0 1.101589 59.256094 44.430726 \n",
"\n",
"'GENE 'ZZZ3 \n",
"Gene Category NaN \n",
"S1 0.000000 \n",
"S2 0.000000 \n",
"S3 0.017615 \n",
"S4 0.000000 \n",
"S5 0.000000 \n",
"\n",
"[5 rows x 27723 columns]"
]
}
],
"prompt_number": 5
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now we need to strip the single-quote I added to all the gene names:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"new_index, indexer = expression2.columns.reindex(map(lambda x: (x[0].lstrip(\"'\"), x[1]), expression2.columns.values))\n",
"expression2.columns = new_index\n",
"expression2.head()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr>\n",
" <th>'GENE</th>\n",
" <th>0610007L01RIK</th>\n",
" <th>0610007P14RIK</th>\n",
" <th>0610007P22RIK</th>\n",
" <th>0610008F07RIK</th>\n",
" <th>0610009B22RIK</th>\n",
" <th>0610009D07RIK</th>\n",
" <th>0610009O20RIK</th>\n",
" <th>0610010B08RIK</th>\n",
" <th>0610010F05RIK</th>\n",
" <th>0610010K06RIK</th>\n",
" <th>...</th>\n",
" <th>ZWILCH</th>\n",
" <th>ZWINT</th>\n",
" <th>ZXDA</th>\n",
" <th>ZXDB</th>\n",
" <th>ZXDC</th>\n",
" <th>ZYG11A</th>\n",
" <th>ZYG11B</th>\n",
" <th>ZYX</th>\n",
" <th>ZZEF1</th>\n",
" <th>ZZZ3</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Gene Category</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>...</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" <th>NaN</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>S1</th>\n",
" <td> 27.181570</td>\n",
" <td> 0.166794</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0.000000</td>\n",
" <td> 178.852732</td>\n",
" <td> 0</td>\n",
" <td> 0.962417</td>\n",
" <td> 0.000000</td>\n",
" <td> 143.359550</td>\n",
" <td>...</td>\n",
" <td> 0.000000</td>\n",
" <td> 302.361227</td>\n",
" <td> 0.000000</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0.027717</td>\n",
" <td> 297.918756</td>\n",
" <td> 37.685501</td>\n",
" <td> 0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S2</th>\n",
" <td> 37.682691</td>\n",
" <td> 0.263962</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0.207921</td>\n",
" <td> 0.141099</td>\n",
" <td> 0</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.255617</td>\n",
" <td>...</td>\n",
" <td> 0.000000</td>\n",
" <td> 96.033724</td>\n",
" <td> 0.020459</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0.042430</td>\n",
" <td> 0.242888</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S3</th>\n",
" <td> 0.056916</td>\n",
" <td> 78.622459</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0.145680</td>\n",
" <td> 0.396363</td>\n",
" <td> 0</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.024692</td>\n",
" <td> 72.775846</td>\n",
" <td>...</td>\n",
" <td> 0.000000</td>\n",
" <td> 427.915555</td>\n",
" <td> 0.000000</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0.040407</td>\n",
" <td> 6.753530</td>\n",
" <td> 0.132011</td>\n",
" <td> 0.017615</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S4</th>\n",
" <td> 55.649250</td>\n",
" <td> 0.228866</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0.000000</td>\n",
" <td> 88.798158</td>\n",
" <td> 0</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 93.825442</td>\n",
" <td>...</td>\n",
" <td> 0.000000</td>\n",
" <td> 9.788557</td>\n",
" <td> 0.017787</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0.013452</td>\n",
" <td> 0.274689</td>\n",
" <td> 9.724890</td>\n",
" <td> 0.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S5</th>\n",
" <td> 0.000000</td>\n",
" <td> 0.093117</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 131.326008</td>\n",
" <td> 155.936361</td>\n",
" <td> 0</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.000000</td>\n",
" <td> 0.031029</td>\n",
" <td>...</td>\n",
" <td> 0.204522</td>\n",
" <td> 26.575760</td>\n",
" <td> 0.000000</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 0</td>\n",
" <td> 1.101589</td>\n",
" <td> 59.256094</td>\n",
" <td> 44.430726</td>\n",
" <td> 0.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows \u00d7 27723 columns</p>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 6,
"text": [
"'GENE 0610007L01RIK 0610007P14RIK 0610007P22RIK 0610008F07RIK \\\n",
"Gene Category NaN NaN NaN NaN \n",
"S1 27.181570 0.166794 0 0 \n",
"S2 37.682691 0.263962 0 0 \n",
"S3 0.056916 78.622459 0 0 \n",
"S4 55.649250 0.228866 0 0 \n",
"S5 0.000000 0.093117 0 0 \n",
"\n",
"'GENE 0610009B22RIK 0610009D07RIK 0610009O20RIK 0610010B08RIK \\\n",
"Gene Category NaN NaN NaN NaN \n",
"S1 0.000000 178.852732 0 0.962417 \n",
"S2 0.207921 0.141099 0 0.000000 \n",
"S3 0.145680 0.396363 0 0.000000 \n",
"S4 0.000000 88.798158 0 0.000000 \n",
"S5 131.326008 155.936361 0 0.000000 \n",
"\n",
"'GENE 0610010F05RIK 0610010K06RIK ... ZWILCH ZWINT \\\n",
"Gene Category NaN NaN ... NaN NaN \n",
"S1 0.000000 143.359550 ... 0.000000 302.361227 \n",
"S2 0.000000 0.255617 ... 0.000000 96.033724 \n",
"S3 0.024692 72.775846 ... 0.000000 427.915555 \n",
"S4 0.000000 93.825442 ... 0.000000 9.788557 \n",
"S5 0.000000 0.031029 ... 0.204522 26.575760 \n",
"\n",
"'GENE ZXDA ZXDB ZXDC ZYG11A ZYG11B ZYX ZZEF1 \\\n",
"Gene Category NaN NaN NaN NaN NaN NaN NaN \n",
"S1 0.000000 0 0 0 0.027717 297.918756 37.685501 \n",
"S2 0.020459 0 0 0 0.042430 0.242888 0.000000 \n",
"S3 0.000000 0 0 0 0.040407 6.753530 0.132011 \n",
"S4 0.017787 0 0 0 0.013452 0.274689 9.724890 \n",
"S5 0.000000 0 0 0 1.101589 59.256094 44.430726 \n",
"\n",
"'GENE ZZZ3 \n",
"Gene Category NaN \n",
"S1 0.000000 \n",
"S2 0.000000 \n",
"S3 0.017615 \n",
"S4 0.000000 \n",
"S5 0.000000 \n",
"\n",
"[5 rows x 27723 columns]"
]
}
],
"prompt_number": 6
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We want to create a `pandas.DataFrame` from the \"Gene Category\" row for our `expression_feature_data`, which we will do via:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"gene_ids, gene_category = zip(*expression2.columns.values)\n",
"gene_categories = pd.Series(gene_category, index=gene_ids, name='gene_category')\n",
"gene_categories"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 7,
"text": [
"0610007L01RIK NaN\n",
"0610007P14RIK NaN\n",
"0610007P22RIK NaN\n",
"0610008F07RIK NaN\n",
"0610009B22RIK NaN\n",
"0610009D07RIK NaN\n",
"0610009O20RIK NaN\n",
"0610010B08RIK NaN\n",
"0610010F05RIK NaN\n",
"0610010K06RIK NaN\n",
"0610010K14RIK NaN\n",
"0610010O12RIK NaN\n",
"0610011F06RIK NaN\n",
"0610011L14RIK NaN\n",
"0610012G03RIK NaN\n",
"...\n",
"ZSWIM5 NaN\n",
"ZSWIM6 NaN\n",
"ZSWIM7 NaN\n",
"ZUFSP LPS Response\n",
"ZW10 NaN\n",
"ZWILCH NaN\n",
"ZWINT NaN\n",
"ZXDA NaN\n",
"ZXDB NaN\n",
"ZXDC NaN\n",
"ZYG11A NaN\n",
"ZYG11B NaN\n",
"ZYX NaN\n",
"ZZEF1 NaN\n",
"ZZZ3 NaN\n",
"Name: gene_category, Length: 27723, dtype: object"
]
}
],
"prompt_number": 7
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"expression_feature_data = pd.DataFrame(gene_categories)\n",
"expression_feature_data.head()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>gene_category</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0610007L01RIK</th>\n",
" <td> NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0610007P14RIK</th>\n",
" <td> NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0610007P22RIK</th>\n",
" <td> NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0610008F07RIK</th>\n",
" <td> NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0610009B22RIK</th>\n",
" <td> NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 8,
"text": [
" gene_category\n",
"0610007L01RIK NaN\n",
"0610007P14RIK NaN\n",
"0610007P22RIK NaN\n",
"0610008F07RIK NaN\n",
"0610009B22RIK NaN"
]
}
],
"prompt_number": 8
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Splicing Data\n",
"\n",
"We obtain the splicing data from this study from the supplementary information, specifically the `Supplementary_Table4.xls`"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"splicing = pd.read_excel('nature12172-s1/Supplementary_Table4.xls', 'splicingTable.txt', index_col=(0,1))\n",
"splicing.head()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th></th>\n",
" <th>S1</th>\n",
" <th>S2</th>\n",
" <th>S3</th>\n",
" <th>S4</th>\n",
" <th>S5</th>\n",
" <th>S6</th>\n",
" <th>S7</th>\n",
" <th>S8</th>\n",
" <th>S9</th>\n",
" <th>S10</th>\n",
" <th>S11</th>\n",
" <th>S13</th>\n",
" <th>S14</th>\n",
" <th>S15</th>\n",
" <th>S16</th>\n",
" <th>S17</th>\n",
" <th>S18</th>\n",
" <th>10,000 cell Rep1 (P1)</th>\n",
" <th>10,000 cell Rep2 (P2)</th>\n",
" <th>10,000 cell Rep3 (P3)</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Event name</th>\n",
" <th>gene</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>chr10:126534988:126535177:-@chr10:126533971:126534135:-@chr10:126533686:126533798:-</th>\n",
" <th>Os9</th>\n",
" <td> 0.84</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 0.01</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td>NaN</td>\n",
" <td> 0.03</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td> 0.02</td>\n",
" <td>NaN</td>\n",
" <td> 0.01</td>\n",
" <td>NaN</td>\n",
" <td> 0.27</td>\n",
" <td> 0.37</td>\n",
" <td> 0.31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>chr10:14403870:14403945:-@chr10:14395740:14395848:-@chr10:14387738:14387914:-</th>\n",
" <th>Vta1</th>\n",
" <td> 0.95</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 0.84</td>\n",
" <td> 0.95</td>\n",
" <td> 0.91</td>\n",
" <td> 0.87</td>\n",
" <td> 0.86</td>\n",
" <td> NaN</td>\n",
" <td>NaN</td>\n",
" <td> 0.93</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td> 0.96</td>\n",
" <td>NaN</td>\n",
" <td> NaN</td>\n",
" <td>NaN</td>\n",
" <td> 0.83</td>\n",
" <td> 0.85</td>\n",
" <td> 0.64</td>\n",
" </tr>\n",
" <tr>\n",
" <th>chr10:20051892:20052067:+@chr10:20052202:20052363:+@chr10:20053198:20053697:+</th>\n",
" <th>Bclaf1</th>\n",
" <td> NaN</td>\n",
" <td> 0.04</td>\n",
" <td> 0.02</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 0.14</td>\n",
" <td> NaN</td>\n",
" <td> 0.02</td>\n",
" <td> NaN</td>\n",
" <td>NaN</td>\n",
" <td> NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td> 0.01</td>\n",
" <td>NaN</td>\n",
" <td> NaN</td>\n",
" <td>NaN</td>\n",
" <td> 0.40</td>\n",
" <td> 0.49</td>\n",
" <td> 0.59</td>\n",
" </tr>\n",
" <tr>\n",
" <th>chr10:20052864:20053378:+@chr10:20054305:20054451:+@chr10:20059515:20059727:+</th>\n",
" <th>Bclaf1</th>\n",
" <td> 0.02</td>\n",
" <td> 0.98</td>\n",
" <td> 0.55</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 0.98</td>\n",
" <td> NaN</td>\n",
" <td>NaN</td>\n",
" <td> NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td> 0.06</td>\n",
" <td>NaN</td>\n",
" <td> NaN</td>\n",
" <td>NaN</td>\n",
" <td> 0.62</td>\n",
" <td> 0.63</td>\n",
" <td> 0.70</td>\n",
" </tr>\n",
" <tr>\n",
" <th>chr10:58814831:58815007:+@chr10:58817088:58817158:+@chr10:58818098:58818168:+@chr10:58824609:58824708:+</th>\n",
" <th>P4ha1</th>\n",
" <td> 0.42</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 0.94</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 0.03</td>\n",
" <td> 0.97</td>\n",
" <td>NaN</td>\n",
" <td> NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td> NaN</td>\n",
" <td>NaN</td>\n",
" <td> NaN</td>\n",
" <td>NaN</td>\n",
" <td> 0.43</td>\n",
" <td> 0.36</td>\n",
" <td> 0.52</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 9,
"text": [
" S1 \\\n",
"Event name gene \n",
"chr10:126534988:126535177:-@chr10:126533971:126534135:-@chr10:126533686:126533798:- Os9 0.84 \n",
"chr10:14403870:14403945:-@chr10:14395740:14395848:-@chr10:14387738:14387914:- Vta1 0.95 \n",
"chr10:20051892:20052067:+@chr10:20052202:20052363:+@chr10:20053198:20053697:+ Bclaf1 NaN \n",
"chr10:20052864:20053378:+@chr10:20054305:20054451:+@chr10:20059515:20059727:+ Bclaf1 0.02 \n",
"chr10:58814831:58815007:+@chr10:58817088:58817158:+@chr10:58818098:58818168:+@chr10:58824609:58824708:+ P4ha1 0.42 \n",
"\n",
" S2 \\\n",
"Event name gene \n",
"chr10:126534988:126535177:-@chr10:126533971:126534135:-@chr10:126533686:126533798:- Os9 NaN \n",
"chr10:14403870:14403945:-@chr10:14395740:14395848:-@chr10:14387738:14387914:- Vta1 NaN \n",
"chr10:20051892:20052067:+@chr10:20052202:20052363:+@chr10:20053198:20053697:+ Bclaf1 0.04 \n",
"chr10:20052864:20053378:+@chr10:20054305:20054451:+@chr10:20059515:20059727:+ Bclaf1 0.98 \n",
"chr10:58814831:58815007:+@chr10:58817088:58817158:+@chr10:58818098:58818168:+@chr10:58824609:58824708:+ P4ha1 NaN \n",
"\n",
" S3 \\\n",
"Event name gene \n",
"chr10:126534988:126535177:-@chr10:126533971:126534135:-@chr10:126533686:126533798:- Os9 NaN \n",
"chr10:14403870:14403945:-@chr10:14395740:14395848:-@chr10:14387738:14387914:- Vta1 NaN \n",
"chr10:20051892:20052067:+@chr10:20052202:20052363:+@chr10:20053198:20053697:+ Bclaf1 0.02 \n",
"chr10:20052864:20053378:+@chr10:20054305:20054451:+@chr10:20059515:20059727:+ Bclaf1 0.55 \n",
"chr10:58814831:58815007:+@chr10:58817088:58817158:+@chr10:58818098:58818168:+@chr10:58824609:58824708:+ P4ha1 NaN \n",
"\n",
" S4 \\\n",
"Event name gene \n",
"chr10:126534988:126535177:-@chr10:126533971:126534135:-@chr10:126533686:126533798:- Os9 NaN \n",
"chr10:14403870:14403945:-@chr10:14395740:14395848:-@chr10:14387738:14387914:- Vta1 0.84 \n",
"chr10:20051892:20052067:+@chr10:20052202:20052363:+@chr10:20053198:20053697:+ Bclaf1 NaN \n",
"chr10:20052864:20053378:+@chr10:20054305:20054451:+@chr10:20059515:20059727:+ Bclaf1 NaN \n",
"chr10:58814831:58815007:+@chr10:58817088:58817158:+@chr10:58818098:58818168:+@chr10:58824609:58824708:+ P4ha1 NaN \n",
"\n",
" S5 \\\n",
"Event name gene \n",
"chr10:126534988:126535177:-@chr10:126533971:126534135:-@chr10:126533686:126533798:- Os9 NaN \n",
"chr10:14403870:14403945:-@chr10:14395740:14395848:-@chr10:14387738:14387914:- Vta1 0.95 \n",
"chr10:20051892:20052067:+@chr10:20052202:20052363:+@chr10:20053198:20053697:+ Bclaf1 NaN \n",
"chr10:20052864:20053378:+@chr10:20054305:20054451:+@chr10:20059515:20059727:+ Bclaf1 NaN \n",
"chr10:58814831:58815007:+@chr10:58817088:58817158:+@chr10:58818098:58818168:+@chr10:58824609:58824708:+ P4ha1 0.94 \n",
"\n",
" S6 \\\n",
"Event name gene \n",
"chr10:126534988:126535177:-@chr10:126533971:126534135:-@chr10:126533686:126533798:- Os9 0.01 \n",
"chr10:14403870:14403945:-@chr10:14395740:14395848:-@chr10:14387738:14387914:- Vta1 0.91 \n",
"chr10:20051892:20052067:+@chr10:20052202:20052363:+@chr10:20053198:20053697:+ Bclaf1 0.14 \n",
"chr10:20052864:20053378:+@chr10:20054305:20054451:+@chr10:20059515:20059727:+ Bclaf1 NaN \n",
"chr10:58814831:58815007:+@chr10:58817088:58817158:+@chr10:58818098:58818168:+@chr10:58824609:58824708:+ P4ha1 NaN \n",
"\n",
" S7 \\\n",
"Event name gene \n",
"chr10:126534988:126535177:-@chr10:126533971:126534135:-@chr10:126533686:126533798:- Os9 NaN \n",
"chr10:14403870:14403945:-@chr10:14395740:14395848:-@chr10:14387738:14387914:- Vta1 0.87 \n",
"chr10:20051892:20052067:+@chr10:20052202:20052363:+@chr10:20053198:20053697:+ Bclaf1 NaN \n",
"chr10:20052864:20053378:+@chr10:20054305:20054451:+@chr10:20059515:20059727:+ Bclaf1 NaN \n",
"chr10:58814831:58815007:+@chr10:58817088:58817158:+@chr10:58818098:58818168:+@chr10:58824609:58824708:+ P4ha1 NaN \n",
"\n",
" S8 \\\n",
"Event name gene \n",
"chr10:126534988:126535177:-@chr10:126533971:126534135:-@chr10:126533686:126533798:- Os9 NaN \n",
"chr10:14403870:14403945:-@chr10:14395740:14395848:-@chr10:14387738:14387914:- Vta1 0.86 \n",
"chr10:20051892:20052067:+@chr10:20052202:20052363:+@chr10:20053198:20053697:+ Bclaf1 0.02 \n",
"chr10:20052864:20053378:+@chr10:20054305:20054451:+@chr10:20059515:20059727:+ Bclaf1 0.98 \n",
"chr10:58814831:58815007:+@chr10:58817088:58817158:+@chr10:58818098:58818168:+@chr10:58824609:58824708:+ P4ha1 0.03 \n",
"\n",
" S9 \\\n",
"Event name gene \n",
"chr10:126534988:126535177:-@chr10:126533971:126534135:-@chr10:126533686:126533798:- Os9 NaN \n",
"chr10:14403870:14403945:-@chr10:14395740:14395848:-@chr10:14387738:14387914:- Vta1 NaN \n",
"chr10:20051892:20052067:+@chr10:20052202:20052363:+@chr10:20053198:20053697:+ Bclaf1 NaN \n",
"chr10:20052864:20053378:+@chr10:20054305:20054451:+@chr10:20059515:20059727:+ Bclaf1 NaN \n",
"chr10:58814831:58815007:+@chr10:58817088:58817158:+@chr10:58818098:58818168:+@chr10:58824609:58824708:+ P4ha1 0.97 \n",
"\n",
" S10 \\\n",
"Event name gene \n",
"chr10:126534988:126535177:-@chr10:126533971:126534135:-@chr10:126533686:126533798:- Os9 NaN \n",
"chr10:14403870:14403945:-@chr10:14395740:14395848:-@chr10:14387738:14387914:- Vta1 NaN \n",
"chr10:20051892:20052067:+@chr10:20052202:20052363:+@chr10:20053198:20053697:+ Bclaf1 NaN \n",
"chr10:20052864:20053378:+@chr10:20054305:20054451:+@chr10:20059515:20059727:+ Bclaf1 NaN \n",
"chr10:58814831:58815007:+@chr10:58817088:58817158:+@chr10:58818098:58818168:+@chr10:58824609:58824708:+ P4ha1 NaN \n",
"\n",
" S11 \\\n",
"Event name gene \n",
"chr10:126534988:126535177:-@chr10:126533971:126534135:-@chr10:126533686:126533798:- Os9 0.03 \n",
"chr10:14403870:14403945:-@chr10:14395740:14395848:-@chr10:14387738:14387914:- Vta1 0.93 \n",
"chr10:20051892:20052067:+@chr10:20052202:20052363:+@chr10:20053198:20053697:+ Bclaf1 NaN \n",
"chr10:20052864:20053378:+@chr10:20054305:20054451:+@chr10:20059515:20059727:+ Bclaf1 NaN \n",
"chr10:58814831:58815007:+@chr10:58817088:58817158:+@chr10:58818098:58818168:+@chr10:58824609:58824708:+ P4ha1 NaN \n",
"\n",
" S13 \\\n",
"Event name gene \n",
"chr10:126534988:126535177:-@chr10:126533971:126534135:-@chr10:126533686:126533798:- Os9 NaN \n",
"chr10:14403870:14403945:-@chr10:14395740:14395848:-@chr10:14387738:14387914:- Vta1 NaN \n",
"chr10:20051892:20052067:+@chr10:20052202:20052363:+@chr10:20053198:20053697:+ Bclaf1 NaN \n",
"chr10:20052864:20053378:+@chr10:20054305:20054451:+@chr10:20059515:20059727:+ Bclaf1 NaN \n",
"chr10:58814831:58815007:+@chr10:58817088:58817158:+@chr10:58818098:58818168:+@chr10:58824609:58824708:+ P4ha1 NaN \n",
"\n",
" S14 \\\n",
"Event name gene \n",
"chr10:126534988:126535177:-@chr10:126533971:126534135:-@chr10:126533686:126533798:- Os9 NaN \n",
"chr10:14403870:14403945:-@chr10:14395740:14395848:-@chr10:14387738:14387914:- Vta1 NaN \n",
"chr10:20051892:20052067:+@chr10:20052202:20052363:+@chr10:20053198:20053697:+ Bclaf1 NaN \n",
"chr10:20052864:20053378:+@chr10:20054305:20054451:+@chr10:20059515:20059727:+ Bclaf1 NaN \n",
"chr10:58814831:58815007:+@chr10:58817088:58817158:+@chr10:58818098:58818168:+@chr10:58824609:58824708:+ P4ha1 NaN \n",
"\n",
" S15 \\\n",
"Event name gene \n",
"chr10:126534988:126535177:-@chr10:126533971:126534135:-@chr10:126533686:126533798:- Os9 0.02 \n",
"chr10:14403870:14403945:-@chr10:14395740:14395848:-@chr10:14387738:14387914:- Vta1 0.96 \n",
"chr10:20051892:20052067:+@chr10:20052202:20052363:+@chr10:20053198:20053697:+ Bclaf1 0.01 \n",
"chr10:20052864:20053378:+@chr10:20054305:20054451:+@chr10:20059515:20059727:+ Bclaf1 0.06 \n",
"chr10:58814831:58815007:+@chr10:58817088:58817158:+@chr10:58818098:58818168:+@chr10:58824609:58824708:+ P4ha1 NaN \n",
"\n",
" S16 \\\n",
"Event name gene \n",
"chr10:126534988:126535177:-@chr10:126533971:126534135:-@chr10:126533686:126533798:- Os9 NaN \n",
"chr10:14403870:14403945:-@chr10:14395740:14395848:-@chr10:14387738:14387914:- Vta1 NaN \n",
"chr10:20051892:20052067:+@chr10:20052202:20052363:+@chr10:20053198:20053697:+ Bclaf1 NaN \n",
"chr10:20052864:20053378:+@chr10:20054305:20054451:+@chr10:20059515:20059727:+ Bclaf1 NaN \n",
"chr10:58814831:58815007:+@chr10:58817088:58817158:+@chr10:58818098:58818168:+@chr10:58824609:58824708:+ P4ha1 NaN \n",
"\n",
" S17 \\\n",
"Event name gene \n",
"chr10:126534988:126535177:-@chr10:126533971:126534135:-@chr10:126533686:126533798:- Os9 0.01 \n",
"chr10:14403870:14403945:-@chr10:14395740:14395848:-@chr10:14387738:14387914:- Vta1 NaN \n",
"chr10:20051892:20052067:+@chr10:20052202:20052363:+@chr10:20053198:20053697:+ Bclaf1 NaN \n",
"chr10:20052864:20053378:+@chr10:20054305:20054451:+@chr10:20059515:20059727:+ Bclaf1 NaN \n",
"chr10:58814831:58815007:+@chr10:58817088:58817158:+@chr10:58818098:58818168:+@chr10:58824609:58824708:+ P4ha1 NaN \n",
"\n",
" S18 \\\n",
"Event name gene \n",
"chr10:126534988:126535177:-@chr10:126533971:126534135:-@chr10:126533686:126533798:- Os9 NaN \n",
"chr10:14403870:14403945:-@chr10:14395740:14395848:-@chr10:14387738:14387914:- Vta1 NaN \n",
"chr10:20051892:20052067:+@chr10:20052202:20052363:+@chr10:20053198:20053697:+ Bclaf1 NaN \n",
"chr10:20052864:20053378:+@chr10:20054305:20054451:+@chr10:20059515:20059727:+ Bclaf1 NaN \n",
"chr10:58814831:58815007:+@chr10:58817088:58817158:+@chr10:58818098:58818168:+@chr10:58824609:58824708:+ P4ha1 NaN \n",
"\n",
" 10,000 cell Rep1 (P1) \\\n",
"Event name gene \n",
"chr10:126534988:126535177:-@chr10:126533971:126534135:-@chr10:126533686:126533798:- Os9 0.27 \n",
"chr10:14403870:14403945:-@chr10:14395740:14395848:-@chr10:14387738:14387914:- Vta1 0.83 \n",
"chr10:20051892:20052067:+@chr10:20052202:20052363:+@chr10:20053198:20053697:+ Bclaf1 0.40 \n",
"chr10:20052864:20053378:+@chr10:20054305:20054451:+@chr10:20059515:20059727:+ Bclaf1 0.62 \n",
"chr10:58814831:58815007:+@chr10:58817088:58817158:+@chr10:58818098:58818168:+@chr10:58824609:58824708:+ P4ha1 0.43 \n",
"\n",
" 10,000 cell Rep2 (P2) \\\n",
"Event name gene \n",
"chr10:126534988:126535177:-@chr10:126533971:126534135:-@chr10:126533686:126533798:- Os9 0.37 \n",
"chr10:14403870:14403945:-@chr10:14395740:14395848:-@chr10:14387738:14387914:- Vta1 0.85 \n",
"chr10:20051892:20052067:+@chr10:20052202:20052363:+@chr10:20053198:20053697:+ Bclaf1 0.49 \n",
"chr10:20052864:20053378:+@chr10:20054305:20054451:+@chr10:20059515:20059727:+ Bclaf1 0.63 \n",
"chr10:58814831:58815007:+@chr10:58817088:58817158:+@chr10:58818098:58818168:+@chr10:58824609:58824708:+ P4ha1 0.36 \n",
"\n",
" 10,000 cell Rep3 (P3) \n",
"Event name gene \n",
"chr10:126534988:126535177:-@chr10:126533971:126534135:-@chr10:126533686:126533798:- Os9 0.31 \n",
"chr10:14403870:14403945:-@chr10:14395740:14395848:-@chr10:14387738:14387914:- Vta1 0.64 \n",
"chr10:20051892:20052067:+@chr10:20052202:20052363:+@chr10:20053198:20053697:+ Bclaf1 0.59 \n",
"chr10:20052864:20053378:+@chr10:20054305:20054451:+@chr10:20059515:20059727:+ Bclaf1 0.70 \n",
"chr10:58814831:58815007:+@chr10:58817088:58817158:+@chr10:58818098:58818168:+@chr10:58824609:58824708:+ P4ha1 0.52 "
]
}
],
"prompt_number": 9
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"splicing = splicing.T\n",
"splicing"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr>\n",
" <th>Event name</th>\n",
" <th>chr10:126534988:126535177:-@chr10:126533971:126534135:-@chr10:126533686:126533798:-</th>\n",
" <th>chr10:14403870:14403945:-@chr10:14395740:14395848:-@chr10:14387738:14387914:-</th>\n",
" <th>chr10:20051892:20052067:+@chr10:20052202:20052363:+@chr10:20053198:20053697:+</th>\n",
" <th>chr10:20052864:20053378:+@chr10:20054305:20054451:+@chr10:20059515:20059727:+</th>\n",
" <th>chr10:58814831:58815007:+@chr10:58817088:58817158:+@chr10:58818098:58818168:+@chr10:58824609:58824708:+</th>\n",
" <th>chr10:79173370:79173665:+@chr10:79174001:79174029:+@chr10:79174239:79174726:+</th>\n",
" <th>chr10:79322526:79322700:+@chr10:79322862:79322939:+@chr10:79323569:79323862:+</th>\n",
" <th>chr10:87376364:87376545:+@chr10:87378043:87378094:+@chr10:87393420:87399792:+</th>\n",
" <th>chr10:92747514:92747722:-@chr10:92727625:92728425:-@chr10:92717434:92717556:-</th>\n",
" <th>chr11:101438508:101438565:+@chr11:101439246:101439351:+@chr11:101441899:101443267:+</th>\n",
" <th>...</th>\n",
" <th>chr8:126022488:126022598:+@chr8:126023892:126024007:+@chr8:126025133:126025333:+</th>\n",
" <th>chr14:51455667:51455879:-@chr14:51453589:51453752:-@chr14:51453129:51453242:-</th>\n",
" <th>chr17:29497858:29498102:+@chr17:29500656:29500887:+@chr17:29501856:29502226:+</th>\n",
" <th>chr2:94198908:94199094:-@chr2:94182784:94182954:-@chr2:94172950:94173209:-</th>\n",
" <th>chr9:21314438:21314697:-@chr9:21313375:21313558:-@chr9:21311823:21312835:-</th>\n",
" <th>chr9:21314438:21314697:-@chr9:21313375:21313795:-@chr9:21311823:21312835:-</th>\n",
" <th>chr10:79545360:79545471:-@chr10:79542698:79544127:-@chr10:79533365:79535263:-</th>\n",
" <th>chr17:5975579:5975881:+@chr17:5985972:5986242:+@chr17:5990136:5990361:+</th>\n",
" <th>chr2:29997782:29997941:+@chr2:30002172:30002382:+@chr2:30002882:30003045:+</th>\n",
" <th>chr7:119221306:119221473:+@chr7:119223686:119223745:+@chr7:119225944:119226075:+</th>\n",
" </tr>\n",
" <tr>\n",
" <th>gene</th>\n",
" <th>Os9</th>\n",
" <th>Vta1</th>\n",
" <th>Bclaf1</th>\n",
" <th>Bclaf1</th>\n",
" <th>P4ha1</th>\n",
" <th>Bsg</th>\n",
" <th>Ptbp1</th>\n",
" <th>Igf1</th>\n",
" <th>Elk3</th>\n",
" <th>Nbr1</th>\n",
" <th>...</th>\n",
" <th>Afg3l1</th>\n",
" <th>Tep1</th>\n",
" <th>Fgd2</th>\n",
" <th>Ttc17</th>\n",
" <th>Tmed1</th>\n",
" <th>Tmed1</th>\n",
" <th>Sbno2</th>\n",
" <th>Synj2</th>\n",
" <th>Tbc1d13</th>\n",
" <th>Usp47</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>S1</th>\n",
" <td> 0.84</td>\n",
" <td> 0.95</td>\n",
" <td> NaN</td>\n",
" <td> 0.02</td>\n",
" <td> 0.42</td>\n",
" <td> NaN</td>\n",
" <td> 0.57</td>\n",
" <td> 0.31</td>\n",
" <td> 0.93</td>\n",
" <td> 0.57</td>\n",
" <td>...</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S2</th>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 0.04</td>\n",
" <td> 0.98</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td>...</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S3</th>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 0.02</td>\n",
" <td> 0.55</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 0.20</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td>...</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S4</th>\n",
" <td> NaN</td>\n",
" <td> 0.84</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 0.95</td>\n",
" <td> NaN</td>\n",
" <td> 0.04</td>\n",
" <td>...</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S5</th>\n",
" <td> NaN</td>\n",
" <td> 0.95</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 0.94</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 0.73</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td>...</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S6</th>\n",
" <td> 0.01</td>\n",
" <td> 0.91</td>\n",
" <td> 0.14</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 0.61</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td>...</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S7</th>\n",
" <td> NaN</td>\n",
" <td> 0.87</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 0.62</td>\n",
" <td> NaN</td>\n",
" <td> 0.85</td>\n",
" <td> 0.73</td>\n",
" <td> 0.55</td>\n",
" <td>...</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S8</th>\n",
" <td> NaN</td>\n",
" <td> 0.86</td>\n",
" <td> 0.02</td>\n",
" <td> 0.98</td>\n",
" <td> 0.03</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 0.89</td>\n",
" <td> 0.82</td>\n",
" <td> 0.83</td>\n",
" <td>...</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S9</th>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 0.97</td>\n",
" <td> NaN</td>\n",
" <td> 0.97</td>\n",
" <td> NaN</td>\n",
" <td> 0.90</td>\n",
" <td> NaN</td>\n",
" <td>...</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S10</th>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 0.06</td>\n",
" <td> 0.98</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td>...</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S11</th>\n",
" <td> 0.03</td>\n",
" <td> 0.93</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 0.97</td>\n",
" <td> NaN</td>\n",
" <td>...</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S13</th>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td>...</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S14</th>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 0.88</td>\n",
" <td>...</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S15</th>\n",
" <td> 0.02</td>\n",
" <td> 0.96</td>\n",
" <td> 0.01</td>\n",
" <td> 0.06</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 0.44</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td>...</td>\n",
" <td> 0.91</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S16</th>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td>...</td>\n",
" <td> NaN</td>\n",
" <td> 0.27</td>\n",
" <td> 0.99</td>\n",
" <td> 0.99</td>\n",
" <td> 0.98</td>\n",
" <td> 0.98</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S17</th>\n",
" <td> 0.01</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td>...</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 0.96</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 0.99</td>\n",
" <td> 0.98</td>\n",
" <td> 0.67</td>\n",
" <td> 0.07</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S18</th>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td>...</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10,000 cell Rep1 (P1)</th>\n",
" <td> 0.27</td>\n",
" <td> 0.83</td>\n",
" <td> 0.40</td>\n",
" <td> 0.62</td>\n",
" <td> 0.43</td>\n",
" <td> 0.78</td>\n",
" <td> NaN</td>\n",
" <td> 0.60</td>\n",
" <td> 0.76</td>\n",
" <td> 0.52</td>\n",
" <td>...</td>\n",
" <td> 0.92</td>\n",
" <td> NaN</td>\n",
" <td> 0.81</td>\n",
" <td> 0.77</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 0.84</td>\n",
" <td> 0.50</td>\n",
" <td> 0.56</td>\n",
" <td> NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10,000 cell Rep2 (P2)</th>\n",
" <td> 0.37</td>\n",
" <td> 0.85</td>\n",
" <td> 0.49</td>\n",
" <td> 0.63</td>\n",
" <td> 0.36</td>\n",
" <td> 0.72</td>\n",
" <td> 0.47</td>\n",
" <td> 0.60</td>\n",
" <td> 0.73</td>\n",
" <td> 0.68</td>\n",
" <td>...</td>\n",
" <td> 0.67</td>\n",
" <td> 0.15</td>\n",
" <td> 0.52</td>\n",
" <td> 0.67</td>\n",
" <td> 0.63</td>\n",
" <td> 0.73</td>\n",
" <td> 0.82</td>\n",
" <td> 0.90</td>\n",
" <td> 0.71</td>\n",
" <td> 0.55</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10,000 cell Rep3 (P3)</th>\n",
" <td> 0.31</td>\n",
" <td> 0.64</td>\n",
" <td> 0.59</td>\n",
" <td> 0.70</td>\n",
" <td> 0.52</td>\n",
" <td> 0.79</td>\n",
" <td> NaN</td>\n",
" <td> 0.65</td>\n",
" <td> 0.42</td>\n",
" <td> 0.64</td>\n",
" <td>...</td>\n",
" <td> 0.58</td>\n",
" <td> 0.79</td>\n",
" <td> 0.74</td>\n",
" <td> 0.85</td>\n",
" <td> 0.73</td>\n",
" <td> 0.39</td>\n",
" <td> 0.56</td>\n",
" <td> NaN</td>\n",
" <td> 0.64</td>\n",
" <td> NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>20 rows \u00d7 352 columns</p>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 10,
"text": [
"Event name chr10:126534988:126535177:-@chr10:126533971:126534135:-@chr10:126533686:126533798:- \\\n",
"gene Os9 \n",
"S1 0.84 \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 NaN \n",
"S5 NaN \n",
"S6 0.01 \n",
"S7 NaN \n",
"S8 NaN \n",
"S9 NaN \n",
"S10 NaN \n",
"S11 0.03 \n",
"S13 NaN \n",
"S14 NaN \n",
"S15 0.02 \n",
"S16 NaN \n",
"S17 0.01 \n",
"S18 NaN \n",
"10,000 cell Rep1 (P1) 0.27 \n",
"10,000 cell Rep2 (P2) 0.37 \n",
"10,000 cell Rep3 (P3) 0.31 \n",
"\n",
"Event name chr10:14403870:14403945:-@chr10:14395740:14395848:-@chr10:14387738:14387914:- \\\n",
"gene Vta1 \n",
"S1 0.95 \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 0.84 \n",
"S5 0.95 \n",
"S6 0.91 \n",
"S7 0.87 \n",
"S8 0.86 \n",
"S9 NaN \n",
"S10 NaN \n",
"S11 0.93 \n",
"S13 NaN \n",
"S14 NaN \n",
"S15 0.96 \n",
"S16 NaN \n",
"S17 NaN \n",
"S18 NaN \n",
"10,000 cell Rep1 (P1) 0.83 \n",
"10,000 cell Rep2 (P2) 0.85 \n",
"10,000 cell Rep3 (P3) 0.64 \n",
"\n",
"Event name chr10:20051892:20052067:+@chr10:20052202:20052363:+@chr10:20053198:20053697:+ \\\n",
"gene Bclaf1 \n",
"S1 NaN \n",
"S2 0.04 \n",
"S3 0.02 \n",
"S4 NaN \n",
"S5 NaN \n",
"S6 0.14 \n",
"S7 NaN \n",
"S8 0.02 \n",
"S9 NaN \n",
"S10 NaN \n",
"S11 NaN \n",
"S13 NaN \n",
"S14 NaN \n",
"S15 0.01 \n",
"S16 NaN \n",
"S17 NaN \n",
"S18 NaN \n",
"10,000 cell Rep1 (P1) 0.40 \n",
"10,000 cell Rep2 (P2) 0.49 \n",
"10,000 cell Rep3 (P3) 0.59 \n",
"\n",
"Event name chr10:20052864:20053378:+@chr10:20054305:20054451:+@chr10:20059515:20059727:+ \\\n",
"gene Bclaf1 \n",
"S1 0.02 \n",
"S2 0.98 \n",
"S3 0.55 \n",
"S4 NaN \n",
"S5 NaN \n",
"S6 NaN \n",
"S7 NaN \n",
"S8 0.98 \n",
"S9 NaN \n",
"S10 NaN \n",
"S11 NaN \n",
"S13 NaN \n",
"S14 NaN \n",
"S15 0.06 \n",
"S16 NaN \n",
"S17 NaN \n",
"S18 NaN \n",
"10,000 cell Rep1 (P1) 0.62 \n",
"10,000 cell Rep2 (P2) 0.63 \n",
"10,000 cell Rep3 (P3) 0.70 \n",
"\n",
"Event name chr10:58814831:58815007:+@chr10:58817088:58817158:+@chr10:58818098:58818168:+@chr10:58824609:58824708:+ \\\n",
"gene P4ha1 \n",
"S1 0.42 \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 NaN \n",
"S5 0.94 \n",
"S6 NaN \n",
"S7 NaN \n",
"S8 0.03 \n",
"S9 0.97 \n",
"S10 NaN \n",
"S11 NaN \n",
"S13 NaN \n",
"S14 NaN \n",
"S15 NaN \n",
"S16 NaN \n",
"S17 NaN \n",
"S18 NaN \n",
"10,000 cell Rep1 (P1) 0.43 \n",
"10,000 cell Rep2 (P2) 0.36 \n",
"10,000 cell Rep3 (P3) 0.52 \n",
"\n",
"Event name chr10:79173370:79173665:+@chr10:79174001:79174029:+@chr10:79174239:79174726:+ \\\n",
"gene Bsg \n",
"S1 NaN \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 NaN \n",
"S5 NaN \n",
"S6 NaN \n",
"S7 0.62 \n",
"S8 NaN \n",
"S9 NaN \n",
"S10 NaN \n",
"S11 NaN \n",
"S13 NaN \n",
"S14 NaN \n",
"S15 NaN \n",
"S16 NaN \n",
"S17 NaN \n",
"S18 NaN \n",
"10,000 cell Rep1 (P1) 0.78 \n",
"10,000 cell Rep2 (P2) 0.72 \n",
"10,000 cell Rep3 (P3) 0.79 \n",
"\n",
"Event name chr10:79322526:79322700:+@chr10:79322862:79322939:+@chr10:79323569:79323862:+ \\\n",
"gene Ptbp1 \n",
"S1 0.57 \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 NaN \n",
"S5 NaN \n",
"S6 NaN \n",
"S7 NaN \n",
"S8 NaN \n",
"S9 0.97 \n",
"S10 0.06 \n",
"S11 NaN \n",
"S13 NaN \n",
"S14 NaN \n",
"S15 NaN \n",
"S16 NaN \n",
"S17 NaN \n",
"S18 NaN \n",
"10,000 cell Rep1 (P1) NaN \n",
"10,000 cell Rep2 (P2) 0.47 \n",
"10,000 cell Rep3 (P3) NaN \n",
"\n",
"Event name chr10:87376364:87376545:+@chr10:87378043:87378094:+@chr10:87393420:87399792:+ \\\n",
"gene Igf1 \n",
"S1 0.31 \n",
"S2 NaN \n",
"S3 0.20 \n",
"S4 0.95 \n",
"S5 0.73 \n",
"S6 0.61 \n",
"S7 0.85 \n",
"S8 0.89 \n",
"S9 NaN \n",
"S10 0.98 \n",
"S11 NaN \n",
"S13 NaN \n",
"S14 NaN \n",
"S15 0.44 \n",
"S16 NaN \n",
"S17 NaN \n",
"S18 NaN \n",
"10,000 cell Rep1 (P1) 0.60 \n",
"10,000 cell Rep2 (P2) 0.60 \n",
"10,000 cell Rep3 (P3) 0.65 \n",
"\n",
"Event name chr10:92747514:92747722:-@chr10:92727625:92728425:-@chr10:92717434:92717556:- \\\n",
"gene Elk3 \n",
"S1 0.93 \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 NaN \n",
"S5 NaN \n",
"S6 NaN \n",
"S7 0.73 \n",
"S8 0.82 \n",
"S9 0.90 \n",
"S10 NaN \n",
"S11 0.97 \n",
"S13 NaN \n",
"S14 NaN \n",
"S15 NaN \n",
"S16 NaN \n",
"S17 NaN \n",
"S18 NaN \n",
"10,000 cell Rep1 (P1) 0.76 \n",
"10,000 cell Rep2 (P2) 0.73 \n",
"10,000 cell Rep3 (P3) 0.42 \n",
"\n",
"Event name chr11:101438508:101438565:+@chr11:101439246:101439351:+@chr11:101441899:101443267:+ \\\n",
"gene Nbr1 \n",
"S1 0.57 \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 0.04 \n",
"S5 NaN \n",
"S6 NaN \n",
"S7 0.55 \n",
"S8 0.83 \n",
"S9 NaN \n",
"S10 NaN \n",
"S11 NaN \n",
"S13 NaN \n",
"S14 0.88 \n",
"S15 NaN \n",
"S16 NaN \n",
"S17 NaN \n",
"S18 NaN \n",
"10,000 cell Rep1 (P1) 0.52 \n",
"10,000 cell Rep2 (P2) 0.68 \n",
"10,000 cell Rep3 (P3) 0.64 \n",
"\n",
"Event name ... \\\n",
"gene ... \n",
"S1 ... \n",
"S2 ... \n",
"S3 ... \n",
"S4 ... \n",
"S5 ... \n",
"S6 ... \n",
"S7 ... \n",
"S8 ... \n",
"S9 ... \n",
"S10 ... \n",
"S11 ... \n",
"S13 ... \n",
"S14 ... \n",
"S15 ... \n",
"S16 ... \n",
"S17 ... \n",
"S18 ... \n",
"10,000 cell Rep1 (P1) ... \n",
"10,000 cell Rep2 (P2) ... \n",
"10,000 cell Rep3 (P3) ... \n",
"\n",
"Event name chr8:126022488:126022598:+@chr8:126023892:126024007:+@chr8:126025133:126025333:+ \\\n",
"gene Afg3l1 \n",
"S1 NaN \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 NaN \n",
"S5 NaN \n",
"S6 NaN \n",
"S7 NaN \n",
"S8 NaN \n",
"S9 NaN \n",
"S10 NaN \n",
"S11 NaN \n",
"S13 NaN \n",
"S14 NaN \n",
"S15 0.91 \n",
"S16 NaN \n",
"S17 NaN \n",
"S18 NaN \n",
"10,000 cell Rep1 (P1) 0.92 \n",
"10,000 cell Rep2 (P2) 0.67 \n",
"10,000 cell Rep3 (P3) 0.58 \n",
"\n",
"Event name chr14:51455667:51455879:-@chr14:51453589:51453752:-@chr14:51453129:51453242:- \\\n",
"gene Tep1 \n",
"S1 NaN \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 NaN \n",
"S5 NaN \n",
"S6 NaN \n",
"S7 NaN \n",
"S8 NaN \n",
"S9 NaN \n",
"S10 NaN \n",
"S11 NaN \n",
"S13 NaN \n",
"S14 NaN \n",
"S15 NaN \n",
"S16 0.27 \n",
"S17 NaN \n",
"S18 NaN \n",
"10,000 cell Rep1 (P1) NaN \n",
"10,000 cell Rep2 (P2) 0.15 \n",
"10,000 cell Rep3 (P3) 0.79 \n",
"\n",
"Event name chr17:29497858:29498102:+@chr17:29500656:29500887:+@chr17:29501856:29502226:+ \\\n",
"gene Fgd2 \n",
"S1 NaN \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 NaN \n",
"S5 NaN \n",
"S6 NaN \n",
"S7 NaN \n",
"S8 NaN \n",
"S9 NaN \n",
"S10 NaN \n",
"S11 NaN \n",
"S13 NaN \n",
"S14 NaN \n",
"S15 NaN \n",
"S16 0.99 \n",
"S17 0.96 \n",
"S18 NaN \n",
"10,000 cell Rep1 (P1) 0.81 \n",
"10,000 cell Rep2 (P2) 0.52 \n",
"10,000 cell Rep3 (P3) 0.74 \n",
"\n",
"Event name chr2:94198908:94199094:-@chr2:94182784:94182954:-@chr2:94172950:94173209:- \\\n",
"gene Ttc17 \n",
"S1 NaN \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 NaN \n",
"S5 NaN \n",
"S6 NaN \n",
"S7 NaN \n",
"S8 NaN \n",
"S9 NaN \n",
"S10 NaN \n",
"S11 NaN \n",
"S13 NaN \n",
"S14 NaN \n",
"S15 NaN \n",
"S16 0.99 \n",
"S17 NaN \n",
"S18 NaN \n",
"10,000 cell Rep1 (P1) 0.77 \n",
"10,000 cell Rep2 (P2) 0.67 \n",
"10,000 cell Rep3 (P3) 0.85 \n",
"\n",
"Event name chr9:21314438:21314697:-@chr9:21313375:21313558:-@chr9:21311823:21312835:- \\\n",
"gene Tmed1 \n",
"S1 NaN \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 NaN \n",
"S5 NaN \n",
"S6 NaN \n",
"S7 NaN \n",
"S8 NaN \n",
"S9 NaN \n",
"S10 NaN \n",
"S11 NaN \n",
"S13 NaN \n",
"S14 NaN \n",
"S15 NaN \n",
"S16 0.98 \n",
"S17 NaN \n",
"S18 NaN \n",
"10,000 cell Rep1 (P1) NaN \n",
"10,000 cell Rep2 (P2) 0.63 \n",
"10,000 cell Rep3 (P3) 0.73 \n",
"\n",
"Event name chr9:21314438:21314697:-@chr9:21313375:21313795:-@chr9:21311823:21312835:- \\\n",
"gene Tmed1 \n",
"S1 NaN \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 NaN \n",
"S5 NaN \n",
"S6 NaN \n",
"S7 NaN \n",
"S8 NaN \n",
"S9 NaN \n",
"S10 NaN \n",
"S11 NaN \n",
"S13 NaN \n",
"S14 NaN \n",
"S15 NaN \n",
"S16 0.98 \n",
"S17 NaN \n",
"S18 NaN \n",
"10,000 cell Rep1 (P1) NaN \n",
"10,000 cell Rep2 (P2) 0.73 \n",
"10,000 cell Rep3 (P3) 0.39 \n",
"\n",
"Event name chr10:79545360:79545471:-@chr10:79542698:79544127:-@chr10:79533365:79535263:- \\\n",
"gene Sbno2 \n",
"S1 NaN \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 NaN \n",
"S5 NaN \n",
"S6 NaN \n",
"S7 NaN \n",
"S8 NaN \n",
"S9 NaN \n",
"S10 NaN \n",
"S11 NaN \n",
"S13 NaN \n",
"S14 NaN \n",
"S15 NaN \n",
"S16 NaN \n",
"S17 0.99 \n",
"S18 NaN \n",
"10,000 cell Rep1 (P1) 0.84 \n",
"10,000 cell Rep2 (P2) 0.82 \n",
"10,000 cell Rep3 (P3) 0.56 \n",
"\n",
"Event name chr17:5975579:5975881:+@chr17:5985972:5986242:+@chr17:5990136:5990361:+ \\\n",
"gene Synj2 \n",
"S1 NaN \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 NaN \n",
"S5 NaN \n",
"S6 NaN \n",
"S7 NaN \n",
"S8 NaN \n",
"S9 NaN \n",
"S10 NaN \n",
"S11 NaN \n",
"S13 NaN \n",
"S14 NaN \n",
"S15 NaN \n",
"S16 NaN \n",
"S17 0.98 \n",
"S18 NaN \n",
"10,000 cell Rep1 (P1) 0.50 \n",
"10,000 cell Rep2 (P2) 0.90 \n",
"10,000 cell Rep3 (P3) NaN \n",
"\n",
"Event name chr2:29997782:29997941:+@chr2:30002172:30002382:+@chr2:30002882:30003045:+ \\\n",
"gene Tbc1d13 \n",
"S1 NaN \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 NaN \n",
"S5 NaN \n",
"S6 NaN \n",
"S7 NaN \n",
"S8 NaN \n",
"S9 NaN \n",
"S10 NaN \n",
"S11 NaN \n",
"S13 NaN \n",
"S14 NaN \n",
"S15 NaN \n",
"S16 NaN \n",
"S17 0.67 \n",
"S18 NaN \n",
"10,000 cell Rep1 (P1) 0.56 \n",
"10,000 cell Rep2 (P2) 0.71 \n",
"10,000 cell Rep3 (P3) 0.64 \n",
"\n",
"Event name chr7:119221306:119221473:+@chr7:119223686:119223745:+@chr7:119225944:119226075:+ \n",
"gene Usp47 \n",
"S1 NaN \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 NaN \n",
"S5 NaN \n",
"S6 NaN \n",
"S7 NaN \n",
"S8 NaN \n",
"S9 NaN \n",
"S10 NaN \n",
"S11 NaN \n",
"S13 NaN \n",
"S14 NaN \n",
"S15 NaN \n",
"S16 NaN \n",
"S17 0.07 \n",
"S18 NaN \n",
"10,000 cell Rep1 (P1) NaN \n",
"10,000 cell Rep2 (P2) 0.55 \n",
"10,000 cell Rep3 (P3) NaN \n",
"\n",
"[20 rows x 352 columns]"
]
}
],
"prompt_number": 10
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The three pooled samples aren't named consistently with the expression data, so we have to fix that."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"splicing.index[splicing.index.map(lambda x: 'P' in x)]"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 11,
"text": [
"Index([u'10,000 cell Rep1 (P1)', u'10,000 cell Rep2 (P2)', u'10,000 cell Rep3 (P3)'], dtype='object')"
]
}
],
"prompt_number": 11
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Since the pooled sample IDs are inconsistent with the `expression` data, we have to change them. We can get the \"P\" and the number after that using regular expressions, called `re` in the Python standard library, e.g.:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import re\n",
"re.search(r'P\\d', '10,000 cell Rep1 (P1)').group()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 12,
"text": [
"'P1'"
]
}
],
"prompt_number": 12
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"def long_pooled_name_to_short(x):\n",
" if 'P' not in x:\n",
" return x\n",
" else:\n",
" return re.search(r'P\\d', x).group()\n",
"\n",
"\n",
"splicing.index.map(long_pooled_name_to_short)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 13,
"text": [
"array([u'S1', u'S2', u'S3', u'S4', u'S5', u'S6', u'S7', u'S8', u'S9',\n",
" u'S10', u'S11', u'S13', u'S14', u'S15', u'S16', u'S17', u'S18',\n",
" u'P1', u'P2', u'P3'], dtype=object)"
]
}
],
"prompt_number": 13
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"And now we assign this new index as our index to the `splicing` dataframe"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"splicing.index = splicing.index.map(long_pooled_name_to_short)\n",
"splicing.head()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr>\n",
" <th>Event name</th>\n",
" <th>chr10:126534988:126535177:-@chr10:126533971:126534135:-@chr10:126533686:126533798:-</th>\n",
" <th>chr10:14403870:14403945:-@chr10:14395740:14395848:-@chr10:14387738:14387914:-</th>\n",
" <th>chr10:20051892:20052067:+@chr10:20052202:20052363:+@chr10:20053198:20053697:+</th>\n",
" <th>chr10:20052864:20053378:+@chr10:20054305:20054451:+@chr10:20059515:20059727:+</th>\n",
" <th>chr10:58814831:58815007:+@chr10:58817088:58817158:+@chr10:58818098:58818168:+@chr10:58824609:58824708:+</th>\n",
" <th>chr10:79173370:79173665:+@chr10:79174001:79174029:+@chr10:79174239:79174726:+</th>\n",
" <th>chr10:79322526:79322700:+@chr10:79322862:79322939:+@chr10:79323569:79323862:+</th>\n",
" <th>chr10:87376364:87376545:+@chr10:87378043:87378094:+@chr10:87393420:87399792:+</th>\n",
" <th>chr10:92747514:92747722:-@chr10:92727625:92728425:-@chr10:92717434:92717556:-</th>\n",
" <th>chr11:101438508:101438565:+@chr11:101439246:101439351:+@chr11:101441899:101443267:+</th>\n",
" <th>...</th>\n",
" <th>chr8:126022488:126022598:+@chr8:126023892:126024007:+@chr8:126025133:126025333:+</th>\n",
" <th>chr14:51455667:51455879:-@chr14:51453589:51453752:-@chr14:51453129:51453242:-</th>\n",
" <th>chr17:29497858:29498102:+@chr17:29500656:29500887:+@chr17:29501856:29502226:+</th>\n",
" <th>chr2:94198908:94199094:-@chr2:94182784:94182954:-@chr2:94172950:94173209:-</th>\n",
" <th>chr9:21314438:21314697:-@chr9:21313375:21313558:-@chr9:21311823:21312835:-</th>\n",
" <th>chr9:21314438:21314697:-@chr9:21313375:21313795:-@chr9:21311823:21312835:-</th>\n",
" <th>chr10:79545360:79545471:-@chr10:79542698:79544127:-@chr10:79533365:79535263:-</th>\n",
" <th>chr17:5975579:5975881:+@chr17:5985972:5986242:+@chr17:5990136:5990361:+</th>\n",
" <th>chr2:29997782:29997941:+@chr2:30002172:30002382:+@chr2:30002882:30003045:+</th>\n",
" <th>chr7:119221306:119221473:+@chr7:119223686:119223745:+@chr7:119225944:119226075:+</th>\n",
" </tr>\n",
" <tr>\n",
" <th>gene</th>\n",
" <th>Os9</th>\n",
" <th>Vta1</th>\n",
" <th>Bclaf1</th>\n",
" <th>Bclaf1</th>\n",
" <th>P4ha1</th>\n",
" <th>Bsg</th>\n",
" <th>Ptbp1</th>\n",
" <th>Igf1</th>\n",
" <th>Elk3</th>\n",
" <th>Nbr1</th>\n",
" <th>...</th>\n",
" <th>Afg3l1</th>\n",
" <th>Tep1</th>\n",
" <th>Fgd2</th>\n",
" <th>Ttc17</th>\n",
" <th>Tmed1</th>\n",
" <th>Tmed1</th>\n",
" <th>Sbno2</th>\n",
" <th>Synj2</th>\n",
" <th>Tbc1d13</th>\n",
" <th>Usp47</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>S1</th>\n",
" <td> 0.84</td>\n",
" <td> 0.95</td>\n",
" <td> NaN</td>\n",
" <td> 0.02</td>\n",
" <td> 0.42</td>\n",
" <td>NaN</td>\n",
" <td> 0.57</td>\n",
" <td> 0.31</td>\n",
" <td> 0.93</td>\n",
" <td> 0.57</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S2</th>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 0.04</td>\n",
" <td> 0.98</td>\n",
" <td> NaN</td>\n",
" <td>NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S3</th>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 0.02</td>\n",
" <td> 0.55</td>\n",
" <td> NaN</td>\n",
" <td>NaN</td>\n",
" <td> NaN</td>\n",
" <td> 0.20</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S4</th>\n",
" <td> NaN</td>\n",
" <td> 0.84</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td>NaN</td>\n",
" <td> NaN</td>\n",
" <td> 0.95</td>\n",
" <td> NaN</td>\n",
" <td> 0.04</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S5</th>\n",
" <td> NaN</td>\n",
" <td> 0.95</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td> 0.94</td>\n",
" <td>NaN</td>\n",
" <td> NaN</td>\n",
" <td> 0.73</td>\n",
" <td> NaN</td>\n",
" <td> NaN</td>\n",
" <td>...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>5 rows \u00d7 352 columns</p>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 14,
"text": [
"Event name chr10:126534988:126535177:-@chr10:126533971:126534135:-@chr10:126533686:126533798:- \\\n",
"gene Os9 \n",
"S1 0.84 \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 NaN \n",
"S5 NaN \n",
"\n",
"Event name chr10:14403870:14403945:-@chr10:14395740:14395848:-@chr10:14387738:14387914:- \\\n",
"gene Vta1 \n",
"S1 0.95 \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 0.84 \n",
"S5 0.95 \n",
"\n",
"Event name chr10:20051892:20052067:+@chr10:20052202:20052363:+@chr10:20053198:20053697:+ \\\n",
"gene Bclaf1 \n",
"S1 NaN \n",
"S2 0.04 \n",
"S3 0.02 \n",
"S4 NaN \n",
"S5 NaN \n",
"\n",
"Event name chr10:20052864:20053378:+@chr10:20054305:20054451:+@chr10:20059515:20059727:+ \\\n",
"gene Bclaf1 \n",
"S1 0.02 \n",
"S2 0.98 \n",
"S3 0.55 \n",
"S4 NaN \n",
"S5 NaN \n",
"\n",
"Event name chr10:58814831:58815007:+@chr10:58817088:58817158:+@chr10:58818098:58818168:+@chr10:58824609:58824708:+ \\\n",
"gene P4ha1 \n",
"S1 0.42 \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 NaN \n",
"S5 0.94 \n",
"\n",
"Event name chr10:79173370:79173665:+@chr10:79174001:79174029:+@chr10:79174239:79174726:+ \\\n",
"gene Bsg \n",
"S1 NaN \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 NaN \n",
"S5 NaN \n",
"\n",
"Event name chr10:79322526:79322700:+@chr10:79322862:79322939:+@chr10:79323569:79323862:+ \\\n",
"gene Ptbp1 \n",
"S1 0.57 \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 NaN \n",
"S5 NaN \n",
"\n",
"Event name chr10:87376364:87376545:+@chr10:87378043:87378094:+@chr10:87393420:87399792:+ \\\n",
"gene Igf1 \n",
"S1 0.31 \n",
"S2 NaN \n",
"S3 0.20 \n",
"S4 0.95 \n",
"S5 0.73 \n",
"\n",
"Event name chr10:92747514:92747722:-@chr10:92727625:92728425:-@chr10:92717434:92717556:- \\\n",
"gene Elk3 \n",
"S1 0.93 \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 NaN \n",
"S5 NaN \n",
"\n",
"Event name chr11:101438508:101438565:+@chr11:101439246:101439351:+@chr11:101441899:101443267:+ \\\n",
"gene Nbr1 \n",
"S1 0.57 \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 0.04 \n",
"S5 NaN \n",
"\n",
"Event name ... \\\n",
"gene ... \n",
"S1 ... \n",
"S2 ... \n",
"S3 ... \n",
"S4 ... \n",
"S5 ... \n",
"\n",
"Event name chr8:126022488:126022598:+@chr8:126023892:126024007:+@chr8:126025133:126025333:+ \\\n",
"gene Afg3l1 \n",
"S1 NaN \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 NaN \n",
"S5 NaN \n",
"\n",
"Event name chr14:51455667:51455879:-@chr14:51453589:51453752:-@chr14:51453129:51453242:- \\\n",
"gene Tep1 \n",
"S1 NaN \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 NaN \n",
"S5 NaN \n",
"\n",
"Event name chr17:29497858:29498102:+@chr17:29500656:29500887:+@chr17:29501856:29502226:+ \\\n",
"gene Fgd2 \n",
"S1 NaN \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 NaN \n",
"S5 NaN \n",
"\n",
"Event name chr2:94198908:94199094:-@chr2:94182784:94182954:-@chr2:94172950:94173209:- \\\n",
"gene Ttc17 \n",
"S1 NaN \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 NaN \n",
"S5 NaN \n",
"\n",
"Event name chr9:21314438:21314697:-@chr9:21313375:21313558:-@chr9:21311823:21312835:- \\\n",
"gene Tmed1 \n",
"S1 NaN \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 NaN \n",
"S5 NaN \n",
"\n",
"Event name chr9:21314438:21314697:-@chr9:21313375:21313795:-@chr9:21311823:21312835:- \\\n",
"gene Tmed1 \n",
"S1 NaN \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 NaN \n",
"S5 NaN \n",
"\n",
"Event name chr10:79545360:79545471:-@chr10:79542698:79544127:-@chr10:79533365:79535263:- \\\n",
"gene Sbno2 \n",
"S1 NaN \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 NaN \n",
"S5 NaN \n",
"\n",
"Event name chr17:5975579:5975881:+@chr17:5985972:5986242:+@chr17:5990136:5990361:+ \\\n",
"gene Synj2 \n",
"S1 NaN \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 NaN \n",
"S5 NaN \n",
"\n",
"Event name chr2:29997782:29997941:+@chr2:30002172:30002382:+@chr2:30002882:30003045:+ \\\n",
"gene Tbc1d13 \n",
"S1 NaN \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 NaN \n",
"S5 NaN \n",
"\n",
"Event name chr7:119221306:119221473:+@chr7:119223686:119223745:+@chr7:119225944:119226075:+ \n",
"gene Usp47 \n",
"S1 NaN \n",
"S2 NaN \n",
"S3 NaN \n",
"S4 NaN \n",
"S5 NaN \n",
"\n",
"[5 rows x 352 columns]"
]
}
],
"prompt_number": 14
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Metadata\n",
"\n",
"Now let's get into creating a metadata dataframe. We'll use the index from the `expression_filtered` data to create the minimum required column, `'phenotype'`, which has the name of the phenotype of that cell. And we'll also add the column `'pooled'` to indicate whether this sample is pooled or not."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"metadata = pd.DataFrame(index=expression_filtered.index)\n",
"metadata['phenotype'] = 'BDMC'\n",
"metadata['pooled'] = metadata.index.map(lambda x: x.startswith('P'))\n",
"\n",
"metadata"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>phenotype</th>\n",
" <th>pooled</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>S1</th>\n",
" <td> BDMC</td>\n",
" <td> False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S2</th>\n",
" <td> BDMC</td>\n",
" <td> False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S3</th>\n",
" <td> BDMC</td>\n",
" <td> False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S4</th>\n",
" <td> BDMC</td>\n",
" <td> False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S5</th>\n",
" <td> BDMC</td>\n",
" <td> False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S6</th>\n",
" <td> BDMC</td>\n",
" <td> False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S7</th>\n",
" <td> BDMC</td>\n",
" <td> False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S8</th>\n",
" <td> BDMC</td>\n",
" <td> False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S9</th>\n",
" <td> BDMC</td>\n",
" <td> False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S10</th>\n",
" <td> BDMC</td>\n",
" <td> False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S11</th>\n",
" <td> BDMC</td>\n",
" <td> False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S12</th>\n",
" <td> BDMC</td>\n",
" <td> False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S13</th>\n",
" <td> BDMC</td>\n",
" <td> False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S14</th>\n",
" <td> BDMC</td>\n",
" <td> False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S15</th>\n",
" <td> BDMC</td>\n",
" <td> False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S16</th>\n",
" <td> BDMC</td>\n",
" <td> False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S17</th>\n",
" <td> BDMC</td>\n",
" <td> False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>S18</th>\n",
" <td> BDMC</td>\n",
" <td> False</td>\n",
" </tr>\n",
" <tr>\n",
" <th>P1</th>\n",
" <td> BDMC</td>\n",
" <td> True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>P2</th>\n",
" <td> BDMC</td>\n",
" <td> True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>P3</th>\n",
" <td> BDMC</td>\n",
" <td> True</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 15,
"text": [
" phenotype pooled\n",
"S1 BDMC False\n",
"S2 BDMC False\n",
"S3 BDMC False\n",
"S4 BDMC False\n",
"S5 BDMC False\n",
"S6 BDMC False\n",
"S7 BDMC False\n",
"S8 BDMC False\n",
"S9 BDMC False\n",
"S10 BDMC False\n",
"S11 BDMC False\n",
"S12 BDMC False\n",
"S13 BDMC False\n",
"S14 BDMC False\n",
"S15 BDMC False\n",
"S16 BDMC False\n",
"S17 BDMC False\n",
"S18 BDMC False\n",
"P1 BDMC True\n",
"P2 BDMC True\n",
"P3 BDMC True"
]
}
],
"prompt_number": 15
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Mapping stats data"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"mapping_stats = pd.read_excel('nature12172-s1/Supplementary_Table1.xls', sheetname='SuppTable1 2.txt')\n",
"mapping_stats"
],
"language": "python",
"metadata": {},
"outputs": [
{
"html": [
"<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Sample</th>\n",
" <th>PF_READS</th>\n",
" <th>PCT_MAPPED_GENOME</th>\n",
" <th>PCT_RIBOSOMAL_BASES</th>\n",
" <th>MEDIAN_CV_COVERAGE</th>\n",
" <th>MEDIAN_5PRIME_BIAS</th>\n",
" <th>MEDIAN_3PRIME_BIAS</th>\n",
" <th>MEDIAN_5PRIME_TO_3PRIME_BIAS</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0 </th>\n",
" <td> S1</td>\n",
" <td> 21326048</td>\n",
" <td> 0.706590</td>\n",
" <td> 0.006820</td>\n",
" <td> 0.509939</td>\n",
" <td> 0.092679</td>\n",
" <td> 0.477321</td>\n",
" <td> 0.247741</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1 </th>\n",
" <td> S2</td>\n",
" <td> 27434011</td>\n",
" <td> 0.745385</td>\n",
" <td> 0.004111</td>\n",
" <td> 0.565732</td>\n",
" <td> 0.056583</td>\n",
" <td> 0.321053</td>\n",
" <td> 0.244062</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2 </th>\n",
" <td> S3</td>\n",
" <td> 31142391</td>\n",
" <td> 0.722087</td>\n",
" <td> 0.006428</td>\n",
" <td> 0.540341</td>\n",
" <td> 0.079551</td>\n",
" <td> 0.382286</td>\n",
" <td> 0.267367</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3 </th>\n",
" <td> S4</td>\n",
" <td> 26231852</td>\n",
" <td> 0.737854</td>\n",
" <td> 0.004959</td>\n",
" <td> 0.530978</td>\n",
" <td> 0.067041</td>\n",
" <td> 0.351670</td>\n",
" <td> 0.279782</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4 </th>\n",
" <td> S5</td>\n",
" <td> 29977214</td>\n",
" <td> 0.746466</td>\n",
" <td> 0.006121</td>\n",
" <td> 0.525598</td>\n",
" <td> 0.066543</td>\n",
" <td> 0.353995</td>\n",
" <td> 0.274252</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5 </th>\n",
" <td> S6</td>\n",
" <td> 24148387</td>\n",
" <td> 0.730079</td>\n",
" <td> 0.008794</td>\n",
" <td> 0.529650</td>\n",
" <td> 0.072095</td>\n",
" <td> 0.413696</td>\n",
" <td> 0.225929</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6 </th>\n",
" <td> S7</td>\n",
" <td> 24078116</td>\n",
" <td> 0.730638</td>\n",
" <td> 0.007945</td>\n",
" <td> 0.540913</td>\n",
" <td> 0.051991</td>\n",
" <td> 0.358597</td>\n",
" <td> 0.201984</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7 </th>\n",
" <td> S8</td>\n",
" <td> 25032126</td>\n",
" <td> 0.739989</td>\n",
" <td> 0.004133</td>\n",
" <td> 0.512725</td>\n",
" <td> 0.058783</td>\n",
" <td> 0.373509</td>\n",
" <td> 0.212337</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8 </th>\n",
" <td> S9</td>\n",
" <td> 22257682</td>\n",
" <td> 0.747427</td>\n",
" <td> 0.004869</td>\n",
" <td> 0.521622</td>\n",
" <td> 0.063566</td>\n",
" <td> 0.334294</td>\n",
" <td> 0.240641</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9 </th>\n",
" <td> S10</td>\n",
" <td> 29436289</td>\n",
" <td> 0.748795</td>\n",
" <td> 0.005499</td>\n",
" <td> 0.560454</td>\n",
" <td> 0.036219</td>\n",
" <td> 0.306729</td>\n",
" <td> 0.187479</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td> S11</td>\n",
" <td> 31130278</td>\n",
" <td> 0.741882</td>\n",
" <td> 0.002740</td>\n",
" <td> 0.558882</td>\n",
" <td> 0.049581</td>\n",
" <td> 0.349191</td>\n",
" <td> 0.211787</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td> S12</td>\n",
" <td> 21161595</td>\n",
" <td> 0.750782</td>\n",
" <td> 0.006837</td>\n",
" <td> 0.756339</td>\n",
" <td> 0.013878</td>\n",
" <td> 0.324264</td>\n",
" <td> 0.195430</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td> S13</td>\n",
" <td> 28612833</td>\n",
" <td> 0.733976</td>\n",
" <td> 0.011718</td>\n",
" <td> 0.598687</td>\n",
" <td> 0.035392</td>\n",
" <td> 0.357447</td>\n",
" <td> 0.198566</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td> S14</td>\n",
" <td> 26351189</td>\n",
" <td> 0.748323</td>\n",
" <td> 0.004106</td>\n",
" <td> 0.517518</td>\n",
" <td> 0.070293</td>\n",
" <td> 0.381095</td>\n",
" <td> 0.259122</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td> S15</td>\n",
" <td> 25739575</td>\n",
" <td> 0.748421</td>\n",
" <td> 0.003353</td>\n",
" <td> 0.526238</td>\n",
" <td> 0.050938</td>\n",
" <td> 0.324207</td>\n",
" <td> 0.212366</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td> S16</td>\n",
" <td> 26802346</td>\n",
" <td> 0.739833</td>\n",
" <td> 0.009370</td>\n",
" <td> 0.520287</td>\n",
" <td> 0.071503</td>\n",
" <td> 0.358758</td>\n",
" <td> 0.240009</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td> S17</td>\n",
" <td> 26343522</td>\n",
" <td> 0.749358</td>\n",
" <td> 0.003155</td>\n",
" <td> 0.673195</td>\n",
" <td> 0.024121</td>\n",
" <td> 0.301588</td>\n",
" <td> 0.245854</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td> S18</td>\n",
" <td> 25290073</td>\n",
" <td> 0.749358</td>\n",
" <td> 0.007465</td>\n",
" <td> 0.562382</td>\n",
" <td> 0.048528</td>\n",
" <td> 0.314776</td>\n",
" <td> 0.215160</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td> 10k_rep1</td>\n",
" <td> 28247826</td>\n",
" <td> 0.688553</td>\n",
" <td> 0.018993</td>\n",
" <td> 0.547000</td>\n",
" <td> 0.056113</td>\n",
" <td> 0.484393</td>\n",
" <td> 0.140333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td> 10k_rep2</td>\n",
" <td> 39303876</td>\n",
" <td> 0.690313</td>\n",
" <td> 0.017328</td>\n",
" <td> 0.547621</td>\n",
" <td> 0.055600</td>\n",
" <td> 0.474634</td>\n",
" <td> 0.142889</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td> 10k_rep3</td>\n",
" <td> 29831281</td>\n",
" <td> 0.710875</td>\n",
" <td> 0.010610</td>\n",
" <td> 0.518053</td>\n",
" <td> 0.066053</td>\n",
" <td> 0.488738</td>\n",
" <td> 0.168180</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td> MB_SC1</td>\n",
" <td> 13848219</td>\n",
" <td> 0.545000</td>\n",
" <td> 0.007000</td>\n",
" <td> 0.531495</td>\n",
" <td> 0.127934</td>\n",
" <td> 0.207841</td>\n",
" <td> 0.728980</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td> MB_SC2</td>\n",
" <td> 13550218</td>\n",
" <td> 0.458000</td>\n",
" <td> 0.010800</td>\n",
" <td> 0.569271</td>\n",
" <td> 0.102581</td>\n",
" <td> 0.179407</td>\n",
" <td> 0.694747</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td> MB_SC3</td>\n",
" <td> 26765848</td>\n",
" <td> 0.496000</td>\n",
" <td> 0.007900</td>\n",
" <td> 0.535192</td>\n",
" <td> 0.141893</td>\n",
" <td> 0.231068</td>\n",
" <td> 0.722080</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"metadata": {},
"output_type": "pyout",
"prompt_number": 16,
"text": [
" Sample PF_READS PCT_MAPPED_GENOME PCT_RIBOSOMAL_BASES \\\n",
"0 S1 21326048 0.706590 0.006820 \n",
"1 S2 27434011 0.745385 0.004111 \n",
"2 S3 31142391 0.722087 0.006428 \n",
"3 S4 26231852 0.737854 0.004959 \n",
"4 S5 29977214 0.746466 0.006121 \n",
"5 S6 24148387 0.730079 0.008794 \n",
"6 S7 24078116 0.730638 0.007945 \n",
"7 S8 25032126 0.739989 0.004133 \n",
"8 S9 22257682 0.747427 0.004869 \n",
"9 S10 29436289 0.748795 0.005499 \n",
"10 S11 31130278 0.741882 0.002740 \n",
"11 S12 21161595 0.750782 0.006837 \n",
"12 S13 28612833 0.733976 0.011718 \n",
"13 S14 26351189 0.748323 0.004106 \n",
"14 S15 25739575 0.748421 0.003353 \n",
"15 S16 26802346 0.739833 0.009370 \n",
"16 S17 26343522 0.749358 0.003155 \n",
"17 S18 25290073 0.749358 0.007465 \n",
"18 10k_rep1 28247826 0.688553 0.018993 \n",
"19 10k_rep2 39303876 0.690313 0.017328 \n",
"20 10k_rep3 29831281 0.710875 0.010610 \n",
"21 MB_SC1 13848219 0.545000 0.007000 \n",
"22 MB_SC2 13550218 0.458000 0.010800 \n",
"23 MB_SC3 26765848 0.496000 0.007900 \n",
"\n",
" MEDIAN_CV_COVERAGE MEDIAN_5PRIME_BIAS MEDIAN_3PRIME_BIAS \\\n",
"0 0.509939 0.092679 0.477321 \n",
"1 0.565732 0.056583 0.321053 \n",
"2 0.540341 0.079551 0.382286 \n",
"3 0.530978 0.067041 0.351670 \n",
"4 0.525598 0.066543 0.353995 \n",
"5 0.529650 0.072095 0.413696 \n",
"6 0.540913 0.051991 0.358597 \n",
"7 0.512725 0.058783 0.373509 \n",
"8 0.521622 0.063566 0.334294 \n",
"9 0.560454 0.036219 0.306729 \n",
"10 0.558882 0.049581 0.349191 \n",
"11 0.756339 0.013878 0.324264 \n",
"12 0.598687 0.035392 0.357447 \n",
"13 0.517518 0.070293 0.381095 \n",
"14 0.526238 0.050938 0.324207 \n",
"15 0.520287 0.071503 0.358758 \n",
"16 0.673195 0.024121 0.301588 \n",
"17 0.562382 0.048528 0.314776 \n",
"18 0.547000 0.056113 0.484393 \n",
"19 0.547621 0.055600 0.474634 \n",
"20 0.518053 0.066053 0.488738 \n",
"21 0.531495 0.127934 0.207841 \n",
"22 0.569271 0.102581 0.179407 \n",
"23 0.535192 0.141893 0.231068 \n",
"\n",
" MEDIAN_5PRIME_TO_3PRIME_BIAS \n",
"0 0.247741 \n",
"1 0.244062 \n",
"2 0.267367 \n",
"3 0.279782 \n",
"4 0.274252 \n",
"5 0.225929 \n",
"6 0.201984 \n",
"7 0.212337 \n",
"8 0.240641 \n",
"9 0.187479 \n",
"10 0.211787 \n",
"11 0.195430 \n",
"12 0.198566 \n",
"13 0.259122 \n",
"14 0.212366 \n",
"15 0.240009 \n",
"16 0.245854 \n",
"17 0.215160 \n",
"18 0.140333 \n",
"19 0.142889 \n",
"20 0.168180 \n",
"21 0.728980 \n",
"22 0.694747 \n",
"23 0.722080 "
]
}
],
"prompt_number": 16
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Create a `flotilla` Study!"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"study = flotilla.Study(# The metadata describing phenotype and pooled samples\n",
" metadata, \n",
" \n",
" # A version for this data\n",
" version='0.1.0', \n",
" \n",
" # Dataframe of the filtered expression data\n",
" expression_data=expression_filtered,\n",
" \n",
" # Dataframe of the feature data of the genes\n",
" expression_feature_data=expression_feature_data,\n",
" \n",
" # Dataframe of the splicing data\n",
" splicing_data=splicing, \n",
" \n",
" # Dataframe of the mapping stats data\n",
" mapping_stats_data=mapping_stats, \n",
" \n",
" # Which column in \"mapping_stats\" has the number of reads\n",
" mapping_stats_number_mapped_col='PF_READS')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"2014-10-28 15:29:35\tInitializing Study\n",
"2014-10-28 15:29:35\tInitializing Predictor configuration manager for Study\n",
"2014-10-28 15:29:35\tPredictor ExtraTreesClassifier is of type <class 'sklearn.ensemble.forest.ExtraTreesClassifier'>\n",
"2014-10-28 15:29:35\tAdded ExtraTreesClassifier to default predictors\n",
"2014-10-28 15:29:35\tPredictor ExtraTreesRegressor is of type <class 'sklearn.ensemble.forest.ExtraTreesRegressor'>\n",
"2014-10-28 15:29:35\tAdded ExtraTreesRegressor to default predictors\n",
"2014-10-28 15:29:35\tPredictor GradientBoostingClassifier is of type <class 'sklearn.ensemble.gradient_boosting.GradientBoostingClassifier'>\n",
"2014-10-28 15:29:35\tAdded GradientBoostingClassifier to default predictors\n",
"2014-10-28 15:29:35\tPredictor GradientBoostingRegressor is of type <class 'sklearn.ensemble.gradient_boosting.GradientBoostingRegressor'>\n",
"2014-10-28 15:29:35\tAdded GradientBoostingRegressor to default predictors\n",
"2014-10-28 15:29:35\tLoading metadata\n",
"2014-10-28 15:29:35\tLoading expression data\n",
"2014-10-28 15:29:35\tInitializing expression\n",
"2014-10-28 15:29:35\tDone initializing expression\n",
"2014-10-28 15:29:35\tLoading splicing data\n",
"2014-10-28 15:29:35\tInitializing splicing\n",
"2014-10-28 15:29:35\tDone initializing splicing\n",
"2014-10-28 15:29:35\tSuccessfully initialized a Study object!\n"
]
},
{
"output_type": "stream",
"stream": "stderr",
"text": [
"No phenotype to color mapping was provided, so coming up with reasonable defaults\n",
"No phenotype to marker (matplotlib plotting symbol) was provided, so each phenotype will be plotted as a circle in the PCA visualizations.\n"
]
}
],
"prompt_number": 17
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"As a side note, you can save this study to disk now, so you can \"`embark`\" later:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"study.save('shalek2013')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"Wrote datapackage to /Users/olga/flotilla_projects/shalek2013/datapackage.json"
]
}
],
"prompt_number": 18
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Note that this is saved to my home directory, in `~/flotilla_projects/<study_name>/`. This will be saved in your home directory, too.\n",
"\n",
"The `datapackage.json` file is what holds all the information relative to the study, and loosely follows the [datapackage spec](http://data.okfn.org/doc/data-package) created by the Open Knowledge Foundation."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"study2 = flotilla.embark('shalek2013')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"2014-10-28 15:29:36\tReading datapackage from /Users/olga/flotilla_projects/shalek2013/datapackage.json\n",
"2014-10-28 15:29:36\tParsing datapackage to create a Study object\n",
"2014-10-28 15:29:36\tInitializing Study\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"2014-10-28 15:29:36\tInitializing Predictor configuration manager for Study\n",
"2014-10-28 15:29:36\tPredictor ExtraTreesClassifier is of type <class 'sklearn.ensemble.forest.ExtraTreesClassifier'>\n",
"2014-10-28 15:29:36\tAdded ExtraTreesClassifier to default predictors\n",
"2014-10-28 15:29:36\tPredictor ExtraTreesRegressor is of type <class 'sklearn.ensemble.forest.ExtraTreesRegressor'>\n",
"2014-10-28 15:29:36\tAdded ExtraTreesRegressor to default predictors\n",
"2014-10-28 15:29:36\tPredictor GradientBoostingClassifier is of type <class 'sklearn.ensemble.gradient_boosting.GradientBoostingClassifier'>\n",
"2014-10-28 15:29:36\tAdded GradientBoostingClassifier to default predictors\n",
"2014-10-28 15:29:36\tPredictor GradientBoostingRegressor is of type <class 'sklearn.ensemble.gradient_boosting.GradientBoostingRegressor'>\n",
"2014-10-28 15:29:36\tAdded GradientBoostingRegressor to default predictors\n",
"2014-10-28 15:29:36\tLoading metadata\n",
"2014-10-28 15:29:36\tLoading expression data\n",
"2014-10-28 15:29:36\tInitializing expression\n",
"2014-10-28 15:29:36\tDone initializing expression\n",
"2014-10-28 15:29:36\tLoading splicing data\n",
"2014-10-28 15:29:36\tInitializing splicing\n",
"2014-10-28 15:29:36\tDone initializing splicing\n",
"2014-10-28 15:29:36\tSuccessfully initialized a Study object!\n"
]
}
],
"prompt_number": 19
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"study2.expression.feature_subsets.keys()"
],
"language": "python",
"metadata": {},
"outputs": []
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"cat /Users/olga/flotilla_projects/shalek2013/datapackage.json"
],
"language": "python",
"metadata": {},
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"One thing to note is that when you save, the version number is bumped up. `study.version` (the one we just made) is `0.1.0`, but the one we saved is `0.1.1`, since we could have made some changes to the data."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"Let's look at what else is in this folder:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"ls /Users/olga/flotilla_projects/shalek2013"
],
"language": "python",
"metadata": {},
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"So this is where all the other files are. Good to know!\n",
"\n",
"We can \"embark\" on this newly-saved study now very painlessly, without having to open and process all those files again:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"study2 = flotilla.embark('shalek2013')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"2014-10-28 11:42:55\tReading datapackage from /Users/olga/flotilla_projects/shalek2013/datapackage.json\n",
"2014-10-28 11:42:55\tParsing datapackage to create a Study object\n",
"2014-10-28 11:42:55\tInitializing Study\n"
]
},
{
"output_type": "stream",
"stream": "stdout",
"text": [
"2014-10-28 11:42:55\tInitializing Predictor configuration manager for Study\n",
"2014-10-28 11:42:55\tPredictor ExtraTreesClassifier is of type <class 'sklearn.ensemble.forest.ExtraTreesClassifier'>\n",
"2014-10-28 11:42:55\tAdded ExtraTreesClassifier to default predictors\n",
"2014-10-28 11:42:55\tPredictor ExtraTreesRegressor is of type <class 'sklearn.ensemble.forest.ExtraTreesRegressor'>\n",
"2014-10-28 11:42:55\tAdded ExtraTreesRegressor to default predictors\n",
"2014-10-28 11:42:55\tPredictor GradientBoostingClassifier is of type <class 'sklearn.ensemble.gradient_boosting.GradientBoostingClassifier'>\n",
"2014-10-28 11:42:55\tAdded GradientBoostingClassifier to default predictors\n",
"2014-10-28 11:42:55\tPredictor GradientBoostingRegressor is of type <class 'sklearn.ensemble.gradient_boosting.GradientBoostingRegressor'>\n",
"2014-10-28 11:42:55\tAdded GradientBoostingRegressor to default predictors\n",
"2014-10-28 11:42:55\tLoading metadata\n",
"2014-10-28 11:42:55\tLoading expression data\n",
"2014-10-28 11:42:55\tInitializing expression\n",
"2014-10-28 11:42:55\tDone initializing expression\n",
"2014-10-28 11:42:55\tLoading splicing data\n",
"2014-10-28 11:42:55\tInitializing splicing\n",
"2014-10-28 11:42:55\tDone initializing splicing\n",
"2014-10-28 11:42:55\tSuccessfully initialized a Study object!\n"
]
}
],
"prompt_number": 32
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now we can start creating figures!\n",
"\n",
"## Figure 1\n",
"Here, we will attempt to re-create the sub-panels in [Figure 1](http://www.nature.com/nature/journal/v498/n7453/fig_tab/nature12172_F1.html), where the original is:\n",
"\n",
"![Original Figure 1](http://www.nature.com/nature/journal/v498/n7453/images/nature12172-f1.2.jpg)\n",
"\n",
"### Figure 1a"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"study.plot_two_samples('P1', 'P2')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stderr",
"text": [
"/usr/local/lib/python2.7/site-packages/matplotlib/font_manager.py:1279: UserWarning: findfont: Font family ['Helvetica'] not found. Falling back to Bitstream Vera Sans\n",
" (prop.get_family(), self.defaultFamily[fontext]))\n",
"/usr/local/lib/python2.7/site-packages/matplotlib/figure.py:1644: UserWarning: This figure includes Axes that are not compatible with tight_layout, so its results might be incorrect.\n",
" warnings.warn(\"This figure includes Axes that are not \"\n"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAagAAAGoCAYAAAATsnHAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nJQkoIYQQWUkCSgghRFaSgBJCCJGV/h8XSgaak8ZI4AAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x115bcd490>"
]
}
],
"prompt_number": 18
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Without flotilla, you would do"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import seaborn as sns\n",
"sns.set_style('ticks')\n",
"\n",
"x = expression_filtered.ix['P1']\n",
"y = expression_filtered.ix['P2']\n",
"jointgrid = sns.jointplot(x, y, joint_kws=dict(alpha=0.5))\n",
"xmin, xmax, ymin, ymax = jointgrid.ax_joint.axis()\n",
"jointgrid.ax_joint.set_xlim(0, xmax)\n",
"jointgrid.ax_joint.set_ylim(0, ymax)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 19,
"text": [
"(0, 12.0)"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAagAAAGoCAYAAAATsnHAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x115d351d0>"
]
}
],
"prompt_number": 19
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Figure 1b\n",
"\n",
"Paper: $r=0.54$. Not sure at all what's going on here."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"study.plot_two_samples('S1', 'S2')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAagAAAGoCAYAAAATsnHAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x116a86490>"
]
}
],
"prompt_number": 20
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Without `flotilla`"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"import seaborn as sns\n",
"sns.set_style('ticks')\n",
"\n",
"x = expression_filtered.ix['S1']\n",
"y = expression_filtered.ix['S2']\n",
"jointgrid = sns.jointplot(x, y, joint_kws=dict(alpha=0.5))\n",
"\n",
"# Adjust xmin, ymin to 0\n",
"xmin, xmax, ymin, ymax = jointgrid.ax_joint.axis()\n",
"jointgrid.ax_joint.set_xlim(0, xmax)\n",
"jointgrid.ax_joint.set_ylim(0, ymax)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 21,
"text": [
"(0, 12.0)"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAagAAAGoCAYAAAATsnHAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
"text": [
"<matplotlib.figure.Figure at 0x116bbfc50>"
]
}
],
"prompt_number": 21
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"By the way, you can do other kinds of plots with `flotilla`, like a kernel density estimate (\"`kde`\") plot:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"study.plot_two_samples('S1', 'S2', kind='kde')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAagAAAGoCAYAAAATsnHAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\niCTp/wG3FGVo2vdfhwAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x116bbb210>"
]
}
],
"prompt_number": 22
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Or a binned hexagon plot (\"`hexbin\"`):"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"study.plot_two_samples('S1', 'S2', kind='hexbin')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAagAAAGoCAYAAAATsnHAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nrkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x116bb9c50>"
]
}
],
"prompt_number": 23
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Any inputs that are valid to `seaborn`'s [`jointplot`](http://web.stanford.edu/~mwaskom/software/seaborn/generated/seaborn.jointplot.html#seaborn.jointplot) are valid."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Figure 1c"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"x = study.expression.data.ix['P1']\n",
"y = study.expression.singles.mean()\n",
"y.name = \"Average singles\"\n",
"\n",
"jointgrid = sns.jointplot(x, y, joint_kws=dict(alpha=0.5))\n",
"\n",
"# Adjust xmin, ymin to 0\n",
"xmin, xmax, ymin, ymax = jointgrid.ax_joint.axis()\n",
"jointgrid.ax_joint.set_xlim(0, xmax)\n",
"jointgrid.ax_joint.set_ylim(0, ymax)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 24,
"text": [
"(0, 12.0)"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAagAAAGoCAYAAAATsnHAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
"text": [
"<matplotlib.figure.Figure at 0x11743b7d0>"
]
}
],
"prompt_number": 24
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Figure 2\n",
"\n",
"Next, we will attempt to recreate the figures from [Figure 2](http://www.nature.com/nature/journal/v498/n7453/fig_tab/nature12172_F2.html):\n",
"\n",
"![Original figure 2](http://www.nature.com/nature/journal/v498/n7453/images/nature12172-f2.2.jpg)\n",
"\n",
"### Figure 2a\n",
"\n",
"For this figure, we will need the \"LPS Response\" and \"Housekeeping\" gene annotations, which weren't very trivial to obtain, so I've moved them to the Appendix."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"# Get colors for plotting the gene categories\n",
"dark2 = sns.color_palette('Dark2')\n",
"\n",
"singles = study.expression.singles\n",
"# Get only gene categories for genes in the singles data\n",
"singles, gene_categories = singles.align(study.expression.feature_data.gene_category, join='left', axis=1)\n",
"\n",
"mean = singles.mean()\n",
"std = singles.std()\n",
"\n",
"jointgrid = sns.jointplot(mean, std, color='#262626', joint_kws=dict(alpha=0.5))\n",
"\n",
"for i, (category, s) in enumerate(gene_categories.groupby(gene_categories)):\n",
" jointgrid.ax_joint.plot(mean[s.index], std[s.index], 'o', color=dark2[i], markersize=5)\n",
"\n",
"jointgrid.ax_joint.set_xlabel('Standard deviation in single cells $\\mu$')\n",
"jointgrid.ax_joint.set_ylabel('Average expression in single cells $\\sigma$')\n",
"\n",
"xmin, xmax, ymin, ymax = jointgrid.ax_joint.axis()\n",
"vmax = max(xmax, ymax)\n",
"vmin = min(xmin, ymin)\n",
"jointgrid.ax_joint.plot([0, vmax], [0, vmax], color='steelblue')\n",
"jointgrid.ax_joint.plot([0, vmax], [0, .25*vmax], color='grey')\n",
"jointgrid.ax_joint.set_xlim(0, xmax)\n",
"jointgrid.ax_joint.set_ylim(0, ymax)\n",
"\n",
"jointgrid.ax_joint.fill_betweenx((ymin, ymax), 0, np.log(250), alpha=0.5, zorder=-1)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 25,
"text": [
"<matplotlib.collections.PolyCollection at 0x1164c5e90>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAagAAAGoCAYAAAATsnHAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\noijKJf0fETa2STezm7sAAAAASUVORK5CYII=\n",
"text": [
"<matplotlib.figure.Figure at 0x116ae0490>"
]
}
],
"prompt_number": 25
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"I couldn't find the data for the `hESC`s for the right-side panel of Fig. 2a, so I couldn't remake the figure.\n",
"\n",
"### Figure 2b\n",
"\n",
"In the paper, they use *\"522 most highly expressed genes (single-cell average TPM > 250)\"*, but I wasn't able to replicate their numbers. If I use the pre-filtered expression data that I fed into flotilla, then I get 297 genes:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"mean = study.expression.singles.mean()\n",
"highly_expressed_genes = mean.index[mean > np.log(250 + 1)]\n",
"len(highly_expressed_genes)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 26,
"text": [
"297"
]
}
],
"prompt_number": 26
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Which is much less. If I use the original, unfiltered data, then I get the *\"522\"* number, but this seems strange because they did the filtering step of *\"discarded genes not appreciably expressed (transcripts per million (TPM) > 1) in at least three individual cells, retaining 6,313 genes for further analysis\"*, and yet they went back to the original data to get this new subset."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"expression.ix[:, expression.ix[singles_ids].mean() > 250].shape"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 27,
"text": [
"(21, 522)"
]
}
],
"prompt_number": 27
},
{
"cell_type": "code",
"collapsed": true,
"input": [
"expression_highly_expressed = np.log(expression.ix[singles_ids, expression.ix[singles_ids].mean() > 250] + 1)\n",
"\n",
"mean = expression_highly_expressed.mean()\n",
"\n",
"std = expression_highly_expressed.std()\n",
"\n",
"mean_bins = pd.cut(mean, bins=np.arange(0, 11, 1))\n",
"\n",
"# Coefficient of variation\n",
"cv = std/mean\n",
"cv.sort()\n",
"\n",
"genes = mean.index\n",
"\n",
"\n",
"# for name, df in shalek2013.expression.singles.groupby(dict(zip(genes, mean_bins)), axis=1):\n",
"def calculate_cells_per_tpm_per_cv(df, cv):\n",
" df = df[df > 1]\n",
" df_aligned, cv_aligned = df.align(cv, join='inner', axis=1)\n",
" cv_aligned.sort()\n",
" n_cells = pd.Series(0, index=cv.index)\n",
" n_cells[cv_aligned.index] = df_aligned.ix[:, cv_aligned.index].count()\n",
" return n_cells\n",
"\n",
"grouped = expression_highly_expressed.groupby(dict(zip(genes, mean_bins)), axis=1)\n",
"cells_per_tpm_per_cv = grouped.apply(calculate_cells_per_tpm_per_cv, cv=cv)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 28
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Here's how you would make the original figure from the paper:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fig, ax = plt.subplots(figsize=(10, 10))\n",
"sns.heatmap(cells_per_tpm_per_cv, linewidth=0, ax=ax, yticklabels=False)\n",
"ax.set_yticks([])\n",
"ax.set_xlabel('ln(TPM, binned)')"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 29,
"text": [
"<matplotlib.text.Text at 0x117151210>"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAp4AAALICAYAAADWofB5AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
"text": [
"<matplotlib.figure.Figure at 0x11649fb90>"
]
}
],
"prompt_number": 29
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Doesn't quite look the same. Maybe the y-axis labels were opposite, and higher up on the y-axis was less variant? Because I see a blob of color for (1,2] TPM (by the way, the figure in the paper is not TPM+1 as previous figures were)\n",
"\n",
"This is how you would make a modified version of the figure, which also plots the coefficient of variation on a side-plot, which I like because it shows the CV changes directly on the heatmap. Also, technically this is $\\ln$(TPM+1)."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"from matplotlib import gridspec\n",
"\n",
"fig = plt.figure(figsize=(12, 10))\n",
"\n",
"gs = gridspec.GridSpec(1, 2, wspace=0.01, hspace=0.01, width_ratios=[.2, 1])\n",
"cv_ax = fig.add_subplot(gs[0, 0])\n",
"heatmap_ax = fig.add_subplot(gs[0, 1])\n",
"\n",
"sns.heatmap(cells_per_tpm_per_cv, linewidth=0, ax=heatmap_ax)\n",
"heatmap_ax.set_yticks([])\n",
"heatmap_ax.set_xlabel('$\\ln$(TPM+1), binned')\n",
"\n",
"y = np.arange(cv.shape[0])\n",
"cv_ax.set_xscale('log')\n",
"cv_ax.plot(cv, y, color='#262626')\n",
"cv_ax.fill_betweenx(cv, np.zeros(cv.shape), y, color='#262626', alpha=0.5)\n",
"cv_ax.set_ylim(0, y.max())\n",
"cv_ax.set_xlabel('CV = $\\mu/\\sigma$')\n",
"cv_ax.set_yticks([])\n",
"sns.despine(ax=cv_ax, left=True, right=False)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAApwAAAJ6CAYAAACFVpI6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
"text": [
"<matplotlib.figure.Figure at 0x116977bd0>"
]
}
],
"prompt_number": 30
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Figure 3\n",
"\n",
"We will attempt to re-create the sub-panel figures from [Figure 3](http://www.nature.com/nature/journal/v498/n7453/fig_tab/nature12172_F3.html):\n",
"\n",
"![Original Figure 3](http://www.nature.com/nature/journal/v498/n7453/images/nature12172-f3.2.jpg)\n",
"\n",
"Since we can't re-do the microscopy (Figure 3a) or the RNA-FISH counts (Figure 3c), we will make Figures 3b. These histograms are simple to do outside of `flotilla`, so we do not have them within flotilla."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Figure 3b, top panel"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fig, ax = plt.subplots()\n",
"sns.distplot(study.splicing.singles.values.flat, bins=np.arange(0, 1.05, 0.05), ax=ax)\n",
"ax.set_xlim(0, 1)\n",
"sns.despine()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAagAAAEYCAYAAAAJeGK1AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x117155f50>"
]
}
],
"prompt_number": 31
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Figure 3b, bottom panel"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"fig, ax = plt.subplots()\n",
"sns.distplot(study.splicing.pooled.values.flat, bins=np.arange(0, 1.05, 0.05), ax=ax, color='grey')\n",
"ax.set_xlim(0, 1)\n",
"sns.despine()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAAAagAAAEYCAYAAAAJeGK1AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nxIAiIiKbxIAiIiKb9L9cvkWRuSH15wAAAABJRU5ErkJggg==\n",
"text": [
"<matplotlib.figure.Figure at 0x1127ad7d0>"
]
}
],
"prompt_number": 41
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Figure 4\n",
"\n",
"We will attempt to re-create the sub-panel figures from [Figure 4](http://www.nature.com/nature/journal/v498/n7453/fig_tab/nature12172_F4.html):\n",
"\n",
"![Original Figure 4](http://www.nature.com/nature/journal/v498/n7453/images/nature12172-f4.2.jpg)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Figure 4a\n",
"\n",
"Here, we can use the \"`interactive_pca`\" function we have to explore different dimensionality reductions on the data."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"study.interactive_pca()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"savefile : data/last.pca.pdf\n",
"y_pc : 2\n",
"data_type : expression\n",
"featurewise : False\n",
"show_point_labels : True\n",
"sample_subset : all_samples\n",
"feature_subset : gene_category: LPS Response\n",
"plot_violins : True\n",
"x_pc : 1\n",
"list_link : \n"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": "iVBORw0KGgoAAAANSUhEUgAABZgAAALICAYAAADyhJW9AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzs3XlYzen/P/DnOS3WoShhSojpGFpOixbZlwxFZazZB5Vl\nGHwwNJJ9ZjBjLGUdDFIhoagZZqxpU2nGFFnLNqVIlk7L+f3h2/vnqAgnOXk+rutc15x7e9/3mUuv\n877P/b5vkVwul4OIiIiIiIiIiIiI6A2Jq7oDRERERERERERERKSaOMFMRERERERERERERG+FE8xE\nRERERERERERE9FY4wUxEREREREREREREb4UTzERERERERERERET0VjjBTERERERERERERERvhRPM\nRERERERERERERPRW1Ku6A0RERERE9HGKiorC9u3bceHCBeTm5kJLSwuWlpYYNmwYbGxsqrp7KmXN\nmjWws7ODlZVVVXdF8PjxY6xZswYXLlzAxYsX8ezZMxw/fhxNmzat6q4REdFbYuxWng8xdp89exbB\nwcFISkrC/fv30bhxY/Ts2RNeXl6oU6dOufW4gpmIiIiIiN47Pz8/jBkzBgDg7e2Nbdu2Ye7cuRCL\nxRg9ejTy8vKquIeqZd26dYiLi6vqbijIyclBSEgIateujfbt21d1d4iI6B0xdivXhxi7AwMD8ejR\nI0yZMgWbN2/GyJEjERwcjK+++gpyubzcelzBTERERERE79XZs2exevVqjBs3DjNnzlTI69OnDwYP\nHgx1dd6qvKlX3fhVBX19fURHRwMAQkNDcfLkySruERERvS3G7srxocVuHx8fNGjQQHhvbW0NbW1t\nTJ8+HfHx8eWutuYKZiIiIiIieq+2bNmChg0bYtq0aWXm29raombNmsL7ffv2oW/fvjAxMYGDgwN8\nfX0VVkllZGRAIpFg7969WLJkCWxtbWFtbY3vv/8ecrkc586dg5ubG6RSKb788kukpKQoXE8ikWDd\nunVYtWoV7O3tIZVK8fXXX+P+/fsK5XJzczF//nx06NABJiYmcHZ2RmhoqEKZNWvWoG3btrh+/TrG\njBkDqVSKXr16Yffu3aXG+ffff2PcuHGwsrKCVCrFV199hbS0NIUy3bp1g7e3N/bv349evXpBKpVi\n+PDhCuUkEgkAYPXq1ZBIJJBIJDhw4EC5n39Jm9u2bUOXLl1gZmaG0aNH48aNGwrl5HI5du7cCWdn\nZ5iamsLOzg6enp64fft2uW0TEVH1xNj9XHWP3S9OLpf4/PPPAQD//fdfufU4wUxERERERO9NYWEh\nYmNjYW9vX6GVTrt378a8efNgbm4OPz8/eHp6IjQ0FJ6enqVW/axbtw4FBQVYtWoVRo0ahV9//RW+\nvr5YuHAhxowZg59//hn5+fmYPHkyiouLFeoGBQXhn3/+wbJlyzBv3jzExMRg0qRJQn5RUREmTJiA\n8PBwTJw4EX5+fmjbti1mz56N4OBghbbkcjmmTJmCHj16YP369TA3N8fChQsRExMjlElOTsawYcMg\nl8uxfPlyrFy5Ek+fPoW7u3upG7izZ89i3759mD17Nn744Qfcu3cPEydORFFREYDnj7MCwJAhQxAU\nFISgoCB06tTplZ/rqVOncPDgQXh7e2Pp0qVIT0/H2LFjIZPJhDKLFy/GkiVLYGNjg3Xr1mHRokVo\n1qwZsrOzX/e/jYiIqhHG7uc+1tgdGxsLAGjZsmX5heRERERERETvSWZmptzY2Fi+atWq15YtLCyU\n29rayj08PBTSDx8+LDc2NpafPHlSLpfL5enp6XJjY2O5p6enQjk3Nze5sbGx/OLFi0Lan3/+KTc2\nNpYnJSUJacbGxvKOHTvKZTKZkHbs2DG5sbGx/PTp0wrvjx49qnCNsWPHyh0cHIT3v/zyi9zY2Fh+\n5MgRIU0mk8ltbGzkCxYsENJGjBghd3FxkRcVFQlpjx49ktvY2Mh//PFHIa1r165ye3t7+ZMnT4S0\nyMjIMsfg5+dX5uf4sq5du8rNzMzk9+/fF9JSUlLkxsbG8sDAQLlcLpdfvXpVLpFI5D///HOF2nyd\nAwcOyI2NjeW3bt1SSntERPT+MHY/97HFbrlcLs/KypJ36NBBPnbs2FeW4wpmIiIiIiL6IF29ehU5\nOTlwcnJSSHd0dIS6unqpg3EcHBwU3jdv3hza2tpo06aNkGZoaAgAuHv3rkLZrl27QkNDQ+G9pqYm\nkpKSADxfvaOpqQlHR0eFen379kVmZmapR1RfXIWkoaGB5s2b486dOwCAZ8+eIT4+Hl988QWKi4tR\nWFiIwsJC1KxZE+bm5qXGZWlpiVq1agnvjYyMyhzDm7CyslJ4DNbY2BiGhobCeM+dOwe5XI5Bgwa9\n9TWIiOjjw9j9XHWI3fn5+ZgyZQoAYOnSpa8sy923iYiIiIjovdHS0kKNGjUqtBfgw4cPAQA6OjoK\n6erq6tDS0kJubq5Cer169RTea2holJkGPL9pelHDhg0V3otEIjRo0ACZmZkAnu/hWNa+hCV9K+kr\nAKipqaF27dqlrlvyCOvDhw9RVFSEVatWYdWqVaXabNGihcL7+vXrK7zX1NQscwxv4uXxlqSVjPfB\ngwcAAD09vbe+BhERVQ+M3R9f7C4sLMTUqVNx+fJl/Pbbb69tkxPMRERERET03qirq8PKygpnzpxB\nQUGBwsqjl5XcnGVlZSmkFxYW4sGDB6Vu3soir+Dp7C8fCiSXy5GdnQ1dXV0Az2+Ay9q/sKRvWlpa\nFboOAHzyyScQi8UYM2YM+vTpUyq/Ro0aFW7rbb38mQLPP4OSG2RtbW0Az1daNW3atNL7Q0REHy7G\n7o8rdsvlcsyZMwfnzp3Dpk2bhAMJX4VbZBARERER0Xv11VdfITs7Gz///HOZ+VFRUXj27BlatmyJ\nhg0b4vDhwwr5kZGRKCwshJWV1WuvJRKJKtSnP//8U+GQnOPHj0Mmk8Hc3BwA0L59e8hkMkRGRirU\nCw8PR6NGjdCsWbMKXQcAateuDQsLC6SmpqJt27alXq1atapwWyU0NDTeaFVUXFycwk13SkoKbty4\nIYzX1tYWIpEIe/fufeO+EBFR9cPY/fHE7sWLF+PIkSNYtWoVrK2tK1SHK5iJiIiIiOi9sre3x9Sp\nU7F69WpcuXIF/fv3h66uLjIzM/HHH3/gyJEjiImJQc2aNTF58mT4+vrC29sbjo6OuHHjhnDD8/K+\njWWp6CoosVgMT09PjBw5EpmZmVixYgWkUins7e0BAJ07d4a5uTnmzZuHzMxMNGvWDOHh4Th9+jQW\nL15coWu82Jc5c+ZgxIgR8PT0RP/+/dGwYUNkZWXh/PnzaNGiBdzd3SvUZgkjIyMcO3YMNjY2qFOn\nDgwMDF65MktLSwvjxo3DxIkTkZ+fj1WrVkFfXx+urq4Anu+B6e7uDn9/fzx69AgdO3ZEUVERoqKi\n0K9fP7Rr165C/Tpx4gSePn2K5ORk4b22tjYaNmxY4ZtWIiKqeozdH0fs3rhxI3bt2oWhQ4eiQYMG\nSExMFPKaNGlS7lYZH+wEc1hYGHbt2oXU1FQ8e/YM//zzj5C3f/9+zJ07V2Gz7G7dumHlypVV0VUi\nIiIiInpDXl5eMDc3x/bt2+Hr64u8vDxoaWnB2toaO3bsQN26dQEAQ4cORY0aNbB161YcOHAAWlpa\ncHFxwYwZM157DZFIVOFVUIMGDUJ+fj7mzp2LJ0+eoFOnTvDx8RHyxWIxNm3ahB9//BHr1q3Do0eP\n0KJFC3z//ffo379/ha75Ynq7du0QGBiItWvXYsGCBXj69Cl0dHQglUoV2qsoHx8fLFu2DF5eXnj2\n7BmWLVsGFxeXcst36tQJrVq1wuLFi5GdnQ1LS0ssWLAA6ur//xbR29sb+vr6CAoKwp49e/DJJ5/A\n3Ny81L6ar+Lr6yvs2SkSieDr6wvg+aqyHTt2vPE4iYio6jB2V//YferUKYhEIgQEBCAgIEAhb/Lk\nyZg8eXKZ9UTyiv4s8J6dPn0aubm5ePr0KebPn19qgnnDhg2IiIiowh4SEREREVF1IJFIMG3aNHh6\nelZ1V96Lbt26oUOHDli0aFFVd4WIiOitMHZ/WD7YFcwlS+ajo6PLzP9A58WJiIiIiIiIiIiIPhoq\necifSCTCnTt34ODggC5dumD69OnIyMioUN3CwkJkZGSgsLCwkntJRERERETl4fdy1VZUVITCwsJy\nX0REVD0xfquuyozdH+wWGSWio6MxduxYhS0y0tPTUVxcDENDQ2RlZWHlypWIj49HaGiowr7MZcnI\nyED37t1x7Ngx6OvrV3b3iYiIiIioDPxertq6desm7K1clt9++42H+BERVUOM36qrMmP3B7tFxqsY\nGBgI/62jo4NFixbB2toaSUlJsLW1rcKeERERERERVX8bNmyATCYrN7958+bvrzNERET0WpUZu1Vy\ngrk8H/hibCIiIiIiomqhdevWVd0FIiIiegOVGbs/2D2Yi4uLkZ+fj4KCAgCATCZDfn4+AOCvv/7C\n3bt3IZfL8eDBA/j6+kJbWxvm5uZV2WUiIiIiIiIiIiKij8oHu4L5wIEDmDt3LoDnh/qZmppCJBLh\njz/+QExMDL777jvk5eWhTp06sLS0xK+//vra/ZeJiIiIiIiIiIiISHk+2AlmNzc3uLm5lZk3a9Ys\nzJo16z33iIiIiIiIiIiIiIhe9MFukUFEREREREREREREHzZOMBMRERERERERERHRW/lgt8ggIiIi\nIqoO4uLiMH78+FLphYWFKCgowM6dO7F69WokJiZCQ0MDYrEYWlpakEqlGDVqFNq1ayfUGTFiBOzt\n7eHl5aXQ1svpEokEu3fvhoWFhUK5l9NlMhm2bNmCsLAw3Lp1C3Xq1EHLli3h7u4OR0dHXLt2DT/9\n9BMSExORl5eHpk2bYtSoURg4cKDQ5o4dO3Do0CFcvnwZjRo1QmRkpNI+O1JdUcm34b//AgDA080M\ndiZNqrhHRESq58X4LpFIULNmTYhEImhqasLY2BgzZ86EqampQp0jR45g165d+PfffyEWi9GwYUPY\n2dlh1KhRaN68OQDGbirbu8RuTjATEREREVUiKysrJCQkKKTJZDIMHz4cDRs2hKWlJQBg0qRJ8PT0\nBADcvn0bQUFBGDJkCH7++Wf06NFDqCsSicq8Tnnp5SkqKoKHhwf+++8/zJ8/H1KpFOrq6oiJiUFw\ncDAcHR3x6NEj2Nra4rvvvoOuri7i4+Ph6ekJLS0t9OzZEwCgp6eHCRMm4MqVK9i/f/8b9YGqp4DI\nVOyOSBHeL90Wg2GOEgztZVyFvSIiUk0vxvetW7fCwsICjx8/xvz58zFp0iScOnVKyF+7di127NiB\n2bNnY82aNdDW1kZmZiYiIiJw+vRpYYKZsZte9q6xmxPMRERERETv2bfffov8/HysWrWqzInhpk2b\nYtq0acjMzMSiRYsUJpiV5fDhw4iLi0NYWBiaNWsmpNva2sLW1hYAYGpqqrAyytLSEh07dkR0dLQw\nwezo6AgAePTokdL7SKrn5RvUEiVpnGQmInp3derUgbOzM8LCwpCTkwNtbW1kZGTAz88Py5cvh7Oz\ns1BWV1cXw4cPV6jP2E0vUkbs5h7MRERERETv0dq1axEdHQ1/f3/UqlXrlWX79OmDe/fu4dq1a0Ka\nXC6v0HVeLvfy+5MnT8LU1FRhcvl1nj59isTERLRp06bCdejjEZV8p8wb1BKvyiMiotcrieW5ubkI\nCQlB8+bNoa2tDQA4c+YMAOCLL76osv6R6lFW7OYKZiIiUlnFxcUAALGYv5cSkWo4cuQINm/ejO3b\nt6NJk9fva9e4cWMAwIMHD4Q0f39/bN26VaHckydP0KFDB4W08ePHQ01Nrdy2s7OzoaenV+G+FxUV\nYdasWWjatClcXFwqXI8+Hv77k6q6C0RE1dr48eMhEonw+PFj6OvrY9euXUJednY2tLW1oa7+/6f6\nfvjhBwQHB6OoqAhSqRRbtmypim7TB0xZsZsTzEREpDLkcjlSM24gJecuUnLu4fKDewCA1lp6kGjr\nQaLdGMb6hm+8DykR0fuQnJyMuXPnYvHixTAzM6tQnbt37wIAtLS0hDQvLy9hr+YSI0aMKFV38+bN\nZR7yV6JBgwa4c+dOhfpRUFCAmTNnIisrC5s2bXrlxDURERFVjpLYfuPGDUyYMAEBAQGYNm0aAEBb\nWxvZ2dkoLCwUJplnzZqFWbNmwc/PD2fPnq3KrlM1xyVfRESkMlIzbsD7wlHsunUB8U/uIVcTyNUE\n4p/cw65bF+B94ShSM24o7XojRoyAiYkJpFIppFIpevXqhe3btwv53bp1g6mpKSwsLGBlZYXevXtj\n/vz5uH79ukI73bp1g0QiwYULFxTSw8PDIZFISk0MJScnY+LEibCzs4OlpSUcHR2xdOlSZGZmKm1s\nRPR+3bt3D5MmTcLYsWPh5ORU4Xrh4eFo3LgxWrRoofQ+de7cGcnJybh58+Yry+Xn52Py5MnIycnB\n1q1bUbduXaX3haoHT7eK/XBCRETvxtDQEAsXLsTmzZuRnp4OAHBwcIBIJEJ4eHip8hXdXos+PsqK\n3ZxgJiIilZGScxeiV2yHIRKLkZJzV6nXnDRpEhISEpCQkIAff/wRP//8M6KiooT8JUuW4Pz584iL\ni4Ofnx8AwMXFBUlJio8atWrVCsHBwQppQUFBMDIyUlhxfebMGbi7u8PIyAihoaGIj4/Hzp07oa2t\njdjYWKWOjYjej6dPn8LLywtSqRRTpkwpt9yLN3937tzBL7/8ggMHDmDevHnllqtIenmcnJxgZWWF\niRMnIiYmBvn5+SgqKkJMTAxmzJgBAHj8+DHGjRuHwsJCbNq0qcw9o4uKipCfn4/CwkLI5XLIZDLk\n5+e/UV+oerAzaYJhjpJy81+VR0REb8bGxgZWVlZYv349AEBfXx8TJkzA4sWLsXfvXuTk5AB4vnXG\n5cuXFe45GLuphLJiN7fIICIilZGSc++1ZVIfvL7M2zIzM4ORkRFSU1NhZ2dXKr9FixZYuHAh0tPT\nsXz5cgQEBAh5Li4u2LhxI7799lvUrl0b6enpSElJwdChQxEXFyeU8/X1hbOzszC5Azw/+dnLy6vS\nxkVElSsiIgIXL17EtWvXIJVKS+UvXLgQALB+/Xps2rQJIpEIWlpasLCwwJ49e2BiYqJQvrxtgN50\neyCxWIyNGzdiy5Yt8PX1xa1bt1C3bl20atVKOG0+MjISsbGxqFWrFmxtbYW6/fv3x4IFC4R+r1u3\nTuiDqakpRCIR/v333zfqD1UPJSfNv3wokHtvCYb0fP0p9EREVHFTpkzBqFGj4OnpCUNDQ0ydOhWt\nW7fGrl27sHTpUojFYujq6sLOzk7YSgNg7CZFyojdnGAmIiKVUFxc/HzPZc1Xl7uUcw/FxcVKO/iv\nZEWgXC5HfHw8rl69WuYE0Yu++OILLFiwAPn5+ahRowYAoFGjRrCyskJYWBgGDhyI4OBg9O/fH5qa\n/39A165dw82bN+Hr66uUvhPRh8HFxeW1h+I5OztXqK3ffvutQukpKWWf+P1yuoaGBjw9PUvt6VzC\n1dUVrq6ur+zTlClTXrkymz4+Q3sZo3mTev93cJAIXgNMYdvu9YdaEhGRohfje1mx3dLSEn///bdC\nWp8+fdCnT59XtsvYTS9719jNCWYiIqJX8Pf3x9atW1FQUIBnz55hyJAhpVYTvkxPTw/FxcV4+PAh\nGjVqBOD5yoBBgwZh7dq1cHNzQ0hICLZt24aIiAihXnZ2tlCfiIhIldmZNIGdCSeViYiIVMW7xG7u\nwUxERCpBLBajtdbrJ14/09ZT2uplAPDy8kJsbCwSExNx4sQJpKWlYe7cua+sc+/ePYjFYtSvX18h\nvVOnTsjKysK6deugr68PIyMjhfwGDRoI9YmIiIiIiIhUASeYiYhIZUi0Xz/BbFyBSei3paenh969\neyMyMvKV5cLDw2FmZiZsj1FCLBZjwIAB8PPzw+DBg0vVa9GiBQwNDXH48GGl9puIiIiIiIiosnCC\nmYiIVIZEuzHkxcXl5suLiyHRbqzUa5bswQwAmZmZOHr0KNq0aVNm/vXr1+Hj44PExETMnj27zPZG\njRqFrVu3lrsvmo+PDw4dOoSffvoJ//33HwAgKysLGzZsQHh4uDKGRETvmZ+fHyQSCQ4cOKCQ3q1b\nNxw8eFB4f+fOHfTt2xdTp06FTCbDvXv34OXlhW7dukEikSiUBYCHDx/C3d0d9vb2sLCwQJcuXbB0\n6VKFU+AzMjLg5eUFW1tb2NraYuLEibh165aQP27cOEilUuFlbm4OiUSCP/74QygTEBAAR0dHSKVS\nuLq6IiYmRsi7du0avv76a3Tq1AkWFhZwcnJCcHCw0j47Uk1RybcxyvcoRvkeRVTynaruDhGRShox\nYgT8/PzKzLt+/TpmzpwJBwcHSKVS9OjRA3PnzsWNGzcAAGvWrMHnn38uxPeePXsKh/oBwNatW+Hm\n5gYrKyt06NAB06ZNw507/Hv9MXvX2M0JZiIiUhnG+oZYbNob7p+awqqOHurJgHoywKqOHtw/NcVi\n094w1jdU6jXXr18vfDFzcXGBrq4uVq5cKeR7e3vDwsIClpaW8PDwgFwuR0hICMzNzctsr169erCz\nsxMO9xOJRBCJREK+vb09du/ejbS0NDg7O8PCwgLu7u7IycmBjY2NUsdGRJWvuLgYwcHBaNOmDQID\nA0vll/z7T01NxeDBg2FnZ4fVq1dDU1MTYrEYHTt2xIoVK9C4cWOFvxUAUKtWLSxcuBCnTp3C+fPn\nsXPnTpw+fRqbNm0SysycORP16tXDiRMn8Oeff6JOnTqYOXOmkL9582YkJCQIr3nz5kFLSwudOnUC\nABw5cgS//PILVq9ejfPnz2Pw4MHw8PAQbkIfPXoEW1tb7Nu3D+fPn4evry9++OEH/P7770r/LEk1\nBESmYum2WGTn5iM7Nx9Lt8UgIDK1qrtFRKSSXo79wPPvDAMGDICmpib27NmDhIQE7Nu3D23btsXJ\nkyeFcra2tkJ8X7RoETZu3Ih9+/YBAAoLC/Hdd9/h7NmziIyMRK1ateDh4fHexkUfFmXEbh7yR0RE\nKkMkEkFi0BwSg+YAnk/cAFDqnssvevHU5rIcP368Qu28qpyXlxe8vLwU0tq1a6ewwoCIVNepU6eQ\nk5ODjRs3wtnZGZcvX0br1q2FfLlcjujoaEyZMgXjxo3DhAkThDxdXV0MGzYMQNl/5zQ1NRX2cpfL\n5RCLxQoHhaampmLKlCnClj39+vXD119/XW5/AwIC4OrqKvwIdvToUfTv3x8SiQQAMGTIEGzatAn7\n9+/HpEmTYGpqClNTU6G+paUlOnbsiOjoaPTs2fONPitSfQGRqdgdkVIqvSRtaC/j990lIqJqZ9my\nZTAxMcHSpUuFtPr168Pd3V2h3ItPWtra2qJVq1b4999/AUDh+4ampibGjRuHvn37Ijc3F/Xq1avk\nEdCHRFmxmyuYiYhIZYnF4kqbXCYiUoagoCD06tULrVq1gpWVValVzH/88Qe8vLwwb948hZu9N+Hh\n4QEzMzP07NkTHTt2xMCBA4W8Hj16ICQkBI8fP0ZeXh5CQkLQq1evMttJTk7GxYsXS+0RX/zS1kRy\nuRypqWWvann69CkSExMVthKij0NU8p0yb1BL7I5I4XYZRETv6OnTp4iNjYWTk1OF6xQXFyMqKgqX\nL1+GiYlJmWXOnTuHJk2acHL5I6PM2M27ciIiIiKiSnDv3j2cOHEC/fv3B/B89fDBgwchk8mEMmfP\nnkWTJk3QpUuXt77Ohg0bkJiYiD179iAsLAy7d+8W8mbNmoW0tDRYW1vD2toa165dw6xZs8psJzAw\nEDY2NmjevLmQ1rVrVxw8eBB///03CgoKsHPnTty5cwd5eXml6hcVFWHWrFlo2rQpXFxc3no8pJr8\n9ycppQwREZUvNzcXRUVFCk8rlSc2NhbW1taws7PDkiVLMHXqVOE7yYvOnz+PlStXYsGCBZXQY/qQ\nKTN2c4KZiIiIiKgS7N27F9ra2rC1tQUA9O7dG/n5+QgLCxPKzJ49G3p6ehg+fDiysrLe+loikQjm\n5uYYOXKksL/is2fPMHToUPTu3RuJiYlISEhA9+7dMWzYMIVJbgDIy8tDWFgYhgwZopDu4uKCr776\nSjhIKCUlBfb29tDW1lYoV1BQgOnTpyMrKwv+/v5QU1N767EQERFR2erVqwc1NTXcvXv3tWXbt2+P\n2NhYREdH4/Dhw/jqq69KlYmLi4OXlxcWL16Mzp07V0aX6SPBCWYiIiIiIiUrLi7Gvn378ODBA3Tq\n1AkODg744osvUFRUpLBNRs2aNeHv7w8DAwO4u7tX6IbxVQoLC1G3bl0AwOXLl5GRkYGxY8dCU1MT\nNWvWxOjRo3Hjxg1cvXpVoV5oaCjq1KlT5vYZ48ePx9GjRxEdHY358+fj0qVLaN++vZCfn5+PyZMn\nIycnB1u3bhWuTx8XTzczpZQhIqLy1apVC+3bt1f4sbo8L+7BXJZTp07By8sLS5YsQZ8+fZTVRVIh\nyozdnGAmIiIiIlKyU6dO4e7duwgMDERoaKjw8vf3R2JiIi5duiSU1dTUxJo1a9CuXTsMGzYM6enp\nQl5+fj7y8/Mhl8tRUFCA/Px8FBUVAQCSkpIQFRWFZ8+eoaioCLGxsfjtt9+EfRmbN2+O2rVrY9u2\nbSgoKIBMJsO2bdvwySefwNDQUKG/gYGBGDBgQKmVx3l5ebhy5Qrkcjmys7OxYMEC1K9fH66urgCA\nx48fY9y4cSgsLMSmTZtQq1atSvk86cNnZ9IEwxwl5eYPc5TAzqTJe+wREZHqKywsFL4LlLzmzJmD\nv//+G97e3sjIyIBcLkdubi4CAgKwY8eOCrUbERGBqVOnYsWKFejRo0clj4I+VMqM3erK6hQRERER\nET0XGBiIHj164PPPP1dId3BwgLm5OQIDAyESiYR0NTU1rFixAt999x2GDRuGbdu2wcjICGZmz1eN\niEQizJ07F3PnzsXkyZMxefJkFBQU4Mcff8T169ehpqaGTz/9FNOmTRMO+fvkk0/g5+eHn3/+GZs3\nbwYAfPZPk/7IAAAgAElEQVTZZ/D391eYCE5MTERaWhr8/PxKjSMvLw/Tpk1DRkYGNDU10aVLF+zY\nsQOampoAgMjISMTGxqJWrVrCViAA0L9/f+7l+BEqOWn+5QOD3HtLMKRnxU6hJyKi/2/t2rVYu3at\n8F4kEuH06dPYu3cv1q5diyFDhuDx48do0KAB7O3thQODRSKRwveMl/3www+QyWSYNm2aQtvh4eFo\n3Lhx5Q2IPjjKit0i+evWzFczGRkZ6N69O44dOwZ9ff2q7g4RERER0UeJ38urr6jkO/93KJAIXgNM\nYduOK5eJiKoLxu/q6V1jN1cwExGRypDL5UhPT0diYiISExNx4cIFAICpqSnMzc1hbm4OAwODV/5a\nT0RERJXLzqQJt8MgIiJSIe8auznBTEREKkEul2Pq1KmIT0rEk4J8PC6Q4XGhDABw4cYVhBwNQ22N\nGrA0M8fq1as5yVwJoqOjMXbsWPzzzz9v3cbo0aNhZWWFyZMnK7FnREREREREVFU4wUxERCohPT0d\n8UmJuPL4Phq2aQXdlvpo3dIAAPDgajoeXM3AnYtpQFIiMjIyYGBgoJTrjhgxAomJiVBXfx4ydXV1\n4e7ujlGjRgllunXrhqysLKirq0MsFkNHRwft27fH2LFj0bx5c4Vyt2/fRlBQEExNTYX08PBwTJ8+\nHdbW1vjtt9+E9OTkZPj5+SEhIQEymQw6Ojro3Lkzxo8fD11dXaWM733jxD8RkWqKSr4N//3Pnxzy\ndDPjCmUiIqJqQhkxXqzsThEREVWGxMTnK5cbtmmFz4f1RVNbM9Ru1AC1GzVAU1szfD6sLxp+boQn\nBflISEhQ6rUnTZqEhIQEJCQk4Mcff8TPP/+Ms2fPKpRZsmQJzp8/j7i4OOGgLBcXFyQlJSmUa9Wq\nFYKDgxXSgoKCYGRkpDD5eubMGbi7u8PIyAihoaGIj4/Hzp07oa2tjdjYWKWOj4hUz4gRI2BiYgKp\nVApLS0v069cPBw8eVCjz9OlTWFlZoWfPnqXq79+/HxKJBFKpFFKpFHZ2dpgxYways7MVyq1Zswbd\nunWDpaUlnJ2dERERIeRFR0crtGFjYwMPDw/cvHmzcgZNVSYgMhVLt8UiOzcf2bn5WLotBgGRqVXd\nLSKiKpGeno6vv/4aDg4OkEql6NKli3D47v79+9GrV69y68pkMvj5+cHJyQlSqRQODg4YOXKkEF/j\n4uKEuFry+vzzz9GvX79SbXl7e0MikZR5b/DTTz/B1dUV7dq1w5gxY0rlh4WFYdiwYbC0tETbtm3f\n4dMgVaesGM8JZiIiUgmJiYl4XCCDVsvyD5LQammAxwWyUpO6ymRmZgYjIyNcunSp3DItWrTAwoUL\nIZVKsXz5coU8FxcXRERE4MmTJwCef0FNSUlBr1698OK5u76+vnB2dsaMGTPQqFEjAM9XT3t5eaFP\nnz5lXnfOnDmYMWMGZs2aBUtLS/Ts2RMhISEKZSIiItCvXz9YWVmhf//++OOPP94o/2VBQUFwdnaG\nlZUVXF1dcebMGYX8DRs2oHPnzrCxscGyZcvwkZ0tTFSpSn78iomJwYABAzBnzhxcuXJFyA8LC4O2\ntjZycnJK/SgGAIaGhsKPZ0ePHkV2djaWLFki5AcFBSEoKAhbt25FfHw8pk6dihkzZuDq1atCGTU1\nNaGNv/76C/Xr18esWbMqd+D0XgVEppY6WR54fto8J5mJ6GM0fvx46Onp4ejRo0hISEBgYCA6duz4\n2u+5RUVF8PDwwOHDh/Hdd98hOjoaJ0+exMSJExEZGQkAsLKyEuJqQkICzp8/j8aNG6N///4KbeXl\n5SEsLAxt2rRBYGBgqWsZGhpi6tSpGDx4cJlPENavXx/Dhw/H3Llz3+GTIFWnzBjPCWYiIlIJFy5c\nwONCGbRalr/1hVZLAzwuVP4Ec8mXRblcjri4OFy9ehVSqfS19b744gskJSUhPz9fSGvUqBGsrKwQ\nFhYGAAgODkb//v2hqakplLl27Rpu3rwJJyenN+5rREQEOnbsiNjYWCxcuBALFiwQVnSfP38e//vf\n//C///0PMTExmD59OqZPny4clvi6/JcFBQVh8+bNWLFiBeLi4jBt2jRMnjxZWL144MABbN++HX5+\nfjhz5gy0tbURFxf3xmMioldTU1PDwIEDUVxcjLS0NCE9MDAQLi4u6NmzJ/bs2VOq3os3wvXr10eP\nHj1w+fJlIS01NRXt27cXtvrp0aMHtLS0FK7xolq1aqFPnz4KbZBqi0q+U+aNZ4ndESmISr7zHntE\nRFS1cnJycP36dQwZMgR169YFAOjp6WHw4MEK3+fLcvjwYeFpRxsbG2hqakIsFsPW1hYrV64ss85f\nf/2FzMxMuLm5KaQfPHgQOjo6mDt3LiIjI/HgwQOFfDc3N3Tp0gVaWlplTnw7ODigT58+0Ncvf/EO\nVW/KjvGcYCYiInoNf39/WFtbQyqVYvjw4ejXrx9MTExeW09PTw/FxcV4+PChkCYSiTBo0CAEBgai\nqKgIISEhGDRokMIXv5JH1PX09N64r+bm5nB2doZYLIadnR169eolrGIOCQmBo6MjOnbsCLFYjM6d\nO6Nnz57Yu3dvhfJftmPHDkycOBHGxsYAIKxULpk8Dw0NxZAhQ/D5559DXV0dHh4e0NHReeMxEVHZ\nSv5uyGQyBAQEQFNTU3jMNSUlBcnJyejXrx9cXFxw/Phx3L9/v9y2srOzERkZCSsrKyGtW7duiIuL\nw5UrV1BUVISjR4+iuLhYocyL8vLycOjQoXLzSfX473/9D7YVKUNEVF1oa2ujdevWmDdvHg4cOIC0\ntLQKP6F38uRJmJqaolmzZhW+3p49e+Do6AhtbW2F9JKnCK2traGjo1PqqUWi11F2jOcEMxERqQRT\nU1PUUdfEg6vp5ZZ5cDUdddQ1YWZmptRre3l5ITY2FomJiThx4gTS0tIq9DjZvXv3IBaLUb9+fYX0\nTp06ISsrC+vWrYO+vj6MjIwU8hs0aCDUfxMikQhNmzZVSGvatKnQzt27d0utUtDX139t/t27d8u8\nXkZGBhYuXAhra2vhFRMTg//++0/o/6effvrK/hHR2yv58cvc3By//PILNmzYIPwb3rNnD6RSKQwM\nDGBjYwNdXV3s27dPoX5GRobwb9fe3h6ZmZkK+zR26NABTk5O6Nu3L0xNTfHtt99i4cKFwt8o4Pnj\nviVttG/fHnFxcZg0adL7+QCIiIiqwI4dO2BjY4MdO3bAxcUFDg4Owhksr5Kdnf1GC0hu376NU6dO\nYciQIQrpFy5cQEpKirBtRr9+/RAUFPRmgyBSMk4wExGRSjA3N0cdDU08uJpRbpkHV9NRR0P5E8wv\n0tPTQ+/evYV90l4lPDwcZmZmqFGjhkK6WCzGgAED4Ofnh8GDB5eq16JFCxgaGuLw4cNv1De5XI5b\nt24ppN26dUv4ItukSRNkZCh+fhkZGWjcuPEr85s0KfsU4U8//RTLli1DbGys8Dp//jx8fHwAPP+s\nXmyvrP4R0dsr+fHr3Llz6NSpE9atWwcAePLkCQ4dOgRnZ2ehrJOTU6mbT319feHf7oULF+Dm5oZB\ngwYJT1GsXLkS8fHx+PPPP/HPP/9g69atmD9/vsJe62pqakIbycnJ+N///oeRI0cq7AVNqsvT7fXx\ntCJliIiqE21tbXzzzTfYv38/4uPjMXPmTKxbt67UD7kva9CgQbkLN8oSHByMli1blnoyaM+ePTAx\nMYGhoSGA5xPM165dQ0xMzJsPhj5ayo7xnGAmIiKVYG5ujtoaNXD/Yhou7j6M2+eS8OS/bDz5Lxu3\nzyXh4u7DuH/xCmpr1KjQ/shv4sXH3jIzM3H06FG0adOm3DLXr1+Hj48PEhMTMXv27DLbHDVqFLZu\n3VrugX0+Pj44dOgQfvrpJ2FFcFZWFjZs2IDw8PBy+5qUlISwsDAUFRUhKioKv//+O1xdXQE8P2Aw\nMjISp0+fRlFREU6cOIHff/8dAwYMqFD+y0aPHo01a9YgJSUFcrkcz549E/aoBoD+/fsjKCgIFy9e\nREFBATZu3PjKR/SJ6O3Uq1cPixcvxqVLl3Dw4EGEhYXh8ePHWL16NRwcHODg4IDAwEBkZGTg9OnT\nZbahqamJoUOHIicnB/Hx8QCe7/vo6uoq/MgklUphZWWFEydOlNmGmpoanJycULNmTZw6dapyBkvv\nlZ1JEwxzlJSbP8xRAjuTsn+EJCL6GNSoUQOurq747LPPkJKSUuaBeiU6d+6M5ORk4bySVyksLMTe\nvXtLLUbJy8vDkSNHkJaWJsT4kSNHQiQSlXnY36v6Qx83Zcd4dWV0ioiIqLIZGBjA0swcSErEkyv3\nkJmSjuuFMgBAHXVN1NHQhFHdhrA0M1f6YRXr16/Hxo0bAQC1a9dG+/btS00ce3t7Y8GCBRCJRNDR\n0YGNjQ1CQkLQokWLMtusV68e7OzshPcikUjhC6C9vT12794NPz8/ODs7o6CgALq6uujatSu+/PLL\nMtsUiUTo3bs3Tpw4gfnz50NbWxs+Pj7ChLuFhQWWL1+O77//Hrdv38ann36KFStWwNTUtEL5Jdco\nMXDgQGhoaODbb79FRkYG1NXV0bZtW+GzcXFxwZ07d+Dp6Yn8/Hy4uLjA2tq6wp87Eb3ay4f0jR49\nGmvXrkXdunXRr18/hb9Tcrkcs2bNQlBQEBwcHEq1VVBQgD179kBdXR2tWrUCALRp0wYHDx5Ely5d\noKenh6SkJERHR2PevHll9qeoqAgRERF48OCBsDc7qb6hvZ7/v3z5ICD33hIM6cn/z0T0ccnNzcWm\nTZvQr18/NG/eHCKRCMeOHcPly5fh4eGBx48fQy6XQyaTKcRpDQ0NODk5ISQkBBMnTsT8+fNhZmYG\ndXV1xMfHIzAwUOGgvz///BOPHj0SFoqUCA0NhVgsRmhoKGrVqiWkHz9+HIsWLUJOTg60tbVRWFiI\noqIiFBQUoLi4GDLZ8/umkoMIi4uLUVBQgIKCAgAQ+vvyk5dUvSkzxovkFd2NvJrIyMhA9+7dcezY\nMZ6WSUSkYuRyOTIyMpCQkICkpCQkJT0/dMDMzAxmZmaQSqXQ19f/aH+p//bbb6GmpobFixdXdVeI\nqJKNGDECHTp0gKenp5CWl5cn/IgTGhqKzz77TKHOmTNn4OHhgb/++gunTp3C3LlzUbNmTQDPVx+3\naNECHh4e6NGjBwDgwYMH+P7773Hq1Ck8efIEOjo6+PLLLzFhwgQAQExMDEaOHCnc4IpEInz66acY\nOXIkBg4c+Nox8Hu5aolKvvN/h/2I4DXAFLbtuHKZiD4+T58+xeLFixEXF4fMzEyoq6tDX18fQ4YM\nwaBBgxASEoJvv/22VL0ZM2Zg/PjxKCgowJYtW3Do0CHcunULdevWRatWrTB8+HAh/gLAuHHj0KhR\nIyxdulShHRcXF9jZ2ZVa7FJUVISePXtixIgRGDNmDObMmYMDBw4olPn0009x7NgxAMD+/fuFM2VE\nIhHkcrkwWf66M1MYv6sfZcR4TjATERFVE3PmzIG6ujonmIlIJfB7ORERkeph/KaycA9mIiKiauLl\nbTaIiIiIiIiIKhv3YCYiIqomli1bVtVdICIiIiIioo8MJ5iJiIiIiFRYcnIy/Pz8kJCQAJlMBh0d\nHXTu3Bnjx4/HypUrcfjwYWhoaAjlLSwssGXLFkRHR2Ps2LH4559/Xtm+t7c39u7di99++63UQZ0S\niQQ1a9aESCSCpqYmjI2NMXPmTIXDQUl1RSXfhv/+CwAATzezNzpNnoiI3lxFY7pYLMYnn3wCU1NT\nDB06VOHw8KioKPj7+yMlJQUPHz7EiRMnoKenV+b1du/ejYULF2Lq1Knw8vJ6X8OkD4iyYj23yCAi\nIiIiUlFnzpyBu7s7jIyMEBoaivj4eOzcuRPa2tqIjY2FSCSCq6srEhIShNeWLVsq3H5eXh7CwsLQ\npk0bBAYGlllm69atSEhIwPHjx6Grq4tJkyYpa3hUhQIiU7F0Wyyyc/ORnZuPpdtiEBCZWtXdIiKq\ntt4kpsfHx2Pfvn2wsLCAh4cHfvvtN6Gd2rVrw9XVFT/88MMrr3fr1i1s27YNxsbG3GbvI6XMWM8J\nZiIiIiIiFeXr6wtnZ2fMmDEDjRo1AgDo6urCy8sLffr0eef2Dx48CB0dHcydOxeRkZF48OBBuWXr\n1KkDZ2dnZGZmIicn552vTVUnIDIVuyNSSqXvjkjhJDMRUSWpSEyXy+VC+YYNG2L06NHw9PTEqlWr\n8OjRIwCAmZkZXFxcYGRk9MrrzZs3D9988w3q1atXSSOiD5myYz0nmImIiIiIVNC1a9dw8+ZNODk5\nvbLcizejbyooKAjOzs6wtraGjo4OQkJCym0/NzcXISEhaN68ObS1td/6mlS1opLvlHnDWWJ3RAqi\nku+8xx4REVV/FY3pZenTpw+ePn2KpKSkCtfZs2cP6tSpgy+++OKNr0eqrzJiPSeYiYiIiIhUUHZ2\nNgCUu68i8HzyNzQ0FNbW1sLr6NGjFWr/woULSElJQf/+/QEA/fr1Q1BQUKly48ePh6WlJdq3b49/\n/vkH27dvf4vR0IfCf//rJygqUoaIiCquIjG9PI0bNwaAVz5l9KLbt2/D398fPj4+b3wtqh4qI9Zz\ngpmIiIiISAU1aNAAAHDv3r1yy4hEIri4uCA2NlZ49e7du0Lt79mzByYmJjA0NATwfIL52rVriImJ\nUSi3efNmxMfHIyIiAmpqaggICHjLEREREX2cKhLTy3P37l0AgJaWVoXKe3t7w8vLS9iGA3i3p52I\nAE4wExERERGppBYtWsDQ0BCHDx9+Zbm3uWnMy8vDkSNHkJaWBgcHBzg4OGDkyJEQiUTlHvZnaGiI\nhQsXYvPmzUhPT3/ja9KHwdPNTClliIio4ioa08s6jC88PBy1atWCubl5ha519uxZrFq1Cra2trC1\ntUVCQgI2btyI4cOHv1XfSfVURqxXf9vOEBERERFR1fLx8YGnpyd0dHTg7u6ORo0aISsrC/v27YOB\ngUGF2pDJZAqT0GpqaggNDYVYLEZoaChq1aol5B0/fhyLFi1CTk5Omfss29jYwMrKCuvXr8eyZcve\nfYD03tmZNMEwR0m5ezMOc5TAzqTJe+4VEVH1V5GY/mK8vn//Pg4fPowNGzZg+vTpqFu3rlBGJpNB\nJpMBeB7n8/PzoampCZFIhBMnTihcd+rUqbCyssLYsWPf00ipqlVGrOcKZiIiIiIiFWVvb4/du3cj\nLS0Nzs7OsLCwgLu7O3JyctC+fXsAZa92KkkvKiqCqakpzMzMhNeiRYsQHByMQYMGQV9fHw0bNhRe\nbm5u0NHRwYEDB8rt05QpU3Do0CHcuHGjUsZMlW9oL2MMc5SUSnfvLcHQXsZV0CMiouqvIjH9wIED\nkEqlsLS0hJubG+Li4uDn54dRo0YJ7cTExMDMzAx9+vSBSCRCz549YWZmhri4OADP93l+8aWhoYG6\ndesK23TQx0HZsV4k/8g2WsnIyED37t1x7Ngx6OvrV3V3iIiIiIg+Svxe/uGLSr7zf4f8iOA1wBS2\n7bhymYjoY8f4Xb0oK9ZziwwiIiIiIiIqxc6kCbfDICIiqsaUFeu5RQYRERERERERERERvRVOMBMR\nERERERERERHRW+EWGUREREREKmbEiBFITEyEuro61NTUYGBgAC8vL/Tq1QsXL17EqlWr8M8//yA/\nPx8NGjSAjY0NlixZAgBYs2YN1q1bh6FDh8LHx0doMz8/Hx07dkRubi6OHz+Opk2bYv/+/Zg7dy5q\n1aqlcP3hw4djxowZSExMxPr164VrNWvWDBMnTkSPHj3e6+dB7y4q+Tb8918AAHi6mXFrDCKiSpSc\nnAw/Pz8kJCRAJpNBR0cHnTt3xvjx46Grq4vr169j7dq1OHfuHB4/foyGDRuiffv28PDwgKGhIdas\nWQM/Pz/UqFEDAKCtrQ1nZ2dMmzZNONx3zZo1OH/+PH799ddS1z9x4gS2bNmCS5cuobi4GK1bt8Y3\n33wDKyur9/o5UNVSZuznCmYiIiIiIhU0adIkJCQkIDo6Gn379sU333yD1NRUjBkzBra2tjhx4oRw\nY2lmZibUE4lEaN68OcLDw/Hs2TMh/ejRo9DV1RVuTEsYGhoiISFB4TVjxgwAwMOHD9G3b1+EhYUh\nLi4OEydOxIwZM5CcnPx+PgRSioDIVCzdFovs3Hxk5+Zj6bYYBESmVnW3iIiqpTNnzsDd3R1GRkYI\nDQ1FfHw8du7cCW1tbcTGxiI1NRUDBgyApqYm9uzZg4SEBOzbtw9t27bFyZMnhXZsbW2FuPzDDz9g\n+/btCAoKqlAfcnNzMXLkSPzxxx84d+4cnJycMH78eNy9e7eyhk0fGGXHfq5gJiIiIiJSYWpqahg6\ndChWrFiBs2fP4uHDhxg+fDg0NTUBAAYGBjAwMFCo06RJExgaGuLIkSNwdXUFAOzduxcDBw7E8uXL\nFcrK5fJyr925c2eF9z169IBEIkF8fDxMTEyUMTyqZAGRqdgdkVIqvSRtaC/j990lIqJqzdfXF87O\nzsKPtQCgq6sLLy8vAMDo0aNhYmKCpUuXCvn169eHu7u7QjsvxmcrKyu0atUKly5dqlAfnJ2dFd4P\nHToU69atw99//43GjRu/8ZhItVRG7OcKZiIiIiIiFVRyYymTybBr1y5oaGigQ4cO0NHRwdSpUxEe\nHo6bN2+WW2/gwIHCSqerV6/i6tWr6N69+zv1KTMzE5cvX4ZEInmnduj9iEq+U+YNZondESmISr7z\nHntERFS9Xbt2DTdv3oSTk1OZ+U+fPkVsbGy5+WUpLi7GuXPncPnyZZibm79Vv1JTU5GTk4PPPvvs\nreqT6qis2M8JZiIiIiIiFeTv7w9ra2t06dIFf/75J9asWYPPPvsMQUFBaNasGdatW4fevXuja9eu\nCA4OVqgrEonQtWtXpKenIy0tDcHBwXBxcRFWPb8oIyMD1tbWCq+wsLBS5Z48eYIpU6aga9eusLW1\nrbRxk/L4709SShkiIqqY7OxsAICenl6Z+bm5uSgqKio3/0WxsbGwtraGmZkZRo8eDS8vr1Irkyvi\n/v37+Prrr/HVV1+hWbNmb1yfVEtlxX5ukUFEREREpIK8vLzg6elZKr1p06aYN28eACAvLw8BAQH4\n7rvvYGBgIEz8yuVyqKmpwc3NDTt37kRkZCQCAgLK3A5DX18fkZGRr+xLXl4ePDw8oKuri++//14J\noyMiIqp+GjRoAAC4d+8eWrZsWSq/Xr16UFNTq9BeyO3bt8fWrVtRUFCAX3/9Fb/++isGDBgAXV3d\nCvfn3r17GDt2LDp27Ijp06dXfCBEL+EKZiIiIiKiaqpu3boYP3486tevj5SU0o9DlmyT0apVKxga\nGr7VNXJycjB69Gg0btwYq1evhro617CoCk83M6WUISKiimnRogUMDQ1x+PDhMvNr1aqF9u3bl/mk\n0MtKfhTW0NDAhAkT0KpVK6xevbrCfcnIyMDw4cPRuXNneHt7V7geqbbKiv2cYCYiIiIiUkFlrTa+\nevUq/P39cePGDRQVFSE/Px+7d+/Go0ePYGFhUaq8gYEBdu3apXCQ0JvIzMzEiBEj0KpVK/z4448Q\ni3l7oUrsTJpgmGP5+2UPc5TAzqTJe+wREVH15+Pjg0OHDuGnn37Cf//9BwDIysrChg0bEB4ejjlz\n5uDvv/+Gt7c3MjIyIJfLkZubi4CAAOzYsaPcdqdOnYoDBw4onL9QXFwMmUyG/Px84SWXy3HlyhUM\nGzYMTk5OmDVrVqWPmT4clRX7ubyAiIiIiEgFiUSiUml16tRBWloaxo4di+zsbGhqaqJly5ZYvXo1\nTE1NhXov1pVKpeW2KxKJkJ6eXqpMt27dsHLlSgQGBiItLQ23bt1CRESEkO/l5YUJEyYoZZxUuUpO\nin/5wB/33hIM6fnmp8gTEdGr2dvbY/fu3fDz84OzszMKCgqgq6uLrl274ssvv0TDhg2xd+9erF27\nFkOGDMHjx4/RoEED2NvbC7H15VgOAFZWVrC2tsb69euxfPlyiEQiREdHC/G/pN7KlStx6tQpZGZm\nYtu2bdi2bZuQv2jRojc6YJBUU2XEfpG8rKUP1VhGRga6d++OY8eOQV9fv6q7Q0RERET0UeL38g9L\nVPKd/zvURwSvAaawbceVy0REVBrjd/WhzNjPFcxERC/x8/NDWFgYxGIxxGIxFi5ciAsXLmD79u1I\nT0/HuXPnoKWlJZRfvHgxTp48iZo1a2L58uX4/PPPq7D3RERERG/OzqQJt8MgIiL6iCgz9nOCmYjo\n/xQXFyMhIQEnTpxASEgINDQ08ODBA8hkMmhoaKBr164YMWKEQp0TJ07gxo0biIyMRFJSEhYsWICg\noKAqGgERERERERER0fvFCWYi+mjJ5XKkZtxASs5dpOTcw+UH95D192U8LnqGsH/jIdFuDGN9Q4hE\nIjRq1KjMNo4dOwZXV1cAgJmZGXJzc5GVlQUdHZ33ORQiIiIiIiIioirBY56J6KOVmnED3heOYtet\nC4h/cg+5moB62+bIvJ+F7yZOwxifWdgffviVbfz3339o3Lix8L5x48a4e/duZXediIhUjJ+fHyQS\nCQ4cOAAAGDNmDObMmaNQ5smTJ3B0dMTGjRsBAPfv38fkyZNhYWEBOzs7rFixAi8en5KTk4PZs2fD\nwcEBVlZWmDFjBnJzcxXavHnzJiZNmgQrKytYWVlh8ODBKCwsFPKTk5Px5ZdfwtzcHD179sTBgwcV\n6r+uDz/99BO6d+8OS0tL2NjY4KuvvsK///6rnA+NKkVU8m2M8j2KUb5HEZV8p6q7Q0RU7YwYMQJ+\nfn5l5t24cQOzZ89Gp06dIJVK0aVLF4wfPx6///57qbLx8fGQSCT49ttvS+XNmTMH3t7eZV7j6dOn\nWLZsGbp16wapVAp7e3uMGjUKly5dEsrExMRg0KBBsLS0RLdu3bBr1663HC2pMmV+J+AEMxF9tFJy\n7p2m5YIAACAASURBVEIkVvwzKK6hgdYzRkB/cE+o162NZQsXISQk5JXtvHxW6sun+RIR0cetuLgY\nwcHBaNOmDQIDAwEAy5cvx59//omIiAih3PLly9GoUSPhhPiZM2dCLBbj5MmTCAoKwu+//47NmzcL\n5WfPno2nT58iMjISx44dw4MHDzBr1iwhPzs7G8OGDUObNm3w119/ITY2FvPnz4eamhoA4NGjRxg/\nfjx69+6N2NhY+Pr6wsfHB4mJiUIbr+tD//79ERoaivj4eJw8eRKtW7fG5MmTK+eDpHcWEJmKpdti\nkZ2bj+z/x959R1VxbQ8c/14QbEDEAhbALjeoCLEbSyxgBUFi7w3B+gz+FDXBFzXYkxclgr3EYEmw\n47MbxViCiDVSTFRABVEgioUrcH9/8JjkBlRMaOr+rHXXyp05M7PnGp0ze87s8zAN3/U/s/lgZFGH\nJYQQb53c7gkjIyPp1asX+vr6bNq0ifPnz3Pw4EGGDBmSa4J569atqNVq9u/fT2pqao79v+i+c968\nefzyyy989913hIeHc+DAAQYOHKhc/+Pi4hgzZgzDhg0jLCyMr776iiVLluj0ScTbL7/7BJJgFkK8\nsyKSE3JdrtJTYVTHkspdW9G0n/NLL7RmZmY6I5bj4+MxNzfP91iFEEK8uUJCQkhOTmbRokVcuHCB\n6OhozM3NmTNnDrNmzeLevXscP36c/fv3s2jRIgBiY2M5ffo0//d//4eRkRGWlpaMHj2aLVu2AFmj\nnUNCQhg3bhxlypThvffew8PDgx9//FG5Lq1btw4LCwvGjx+PkZERKpWK+vXrKzekBw8epEyZMowa\nNQoDAwNatWqFg4ODkgR/VQwAtWrVwsjICICMjAxUKpVcB4upzQcjCTwQkWN54IEISTILIUQh8PX1\npVGjRvj6+mJlZYVKpcLQ0JA2bdqwcOFCnba///47Bw4cYObMmVSoUIFdu3bl2N9fBzplCw8Pp2vX\nrlSpkjV5m7GxMY6OjtSuXRvImkeoZs2adOvWDcgq9di5c2cCAwPz83RFMVYQfQJJMAsh3kmZmZlE\np+RMMKfdSyItMVn5Hh0VRbVq1XTa/PlC3rFjR+V15wsXLmBiYiL1l4UQQujYtm0bjo6O1KlThyZN\nmigJXEdHRzp27IiXlxczZ87k3//+t1J2KTIyEmNjYywtLZX92NjYcPv2bR4/foxWq1U+2TIyMgCU\nEhVnz57F3NycMWPG0Lx5c5ydndmzZ4/SPiIiAhsbG51YbWxsiIyMzFMM2fbs2UOTJk344IMPOHny\nJP/5z3/y5XcT+ef05bu53khmCzwQIeUyhBCiAD179oxz587RvXv3PLXfuXMnFSpUoGnTpvTs2VPp\nO+RF06ZNWbVqFRs3buTixYtoNJocbTIzM3N8j4h48XVCvD0Kqk8gCWYhhPiTjLTnxAbuJ3L+eqIW\nbuRJYhLjxo1j48aNtGvXjnv37uHs7Mxnn30GQLt27bC0tMTBwQEfHx9mzZpVxGcghBCiOElISOD4\n8eP07NkTAGdnZ3bv3k1aWhoAM2fOJC4ujqZNmyojiQBSU1MxNjbW2Vf299TUVMqWLUuzZs1YtmwZ\njx49IikpiRUrVijrIatG86FDh3Bzc+P06dN4e3szc+ZMwsLCAHj8+LEy+vjPx8je/lUxZHNycuLc\nuXOcPHmSOnXqMGHChH/wi4mCELD9Yr60EUII8ff8/vvvZGRk6Lzlc+3aNZo2bUrTpk2xtbXlzp07\nyrpt27bh5OQEZPUdoqKidEpYvcyMGTMYNWoUhw8fZvjw4TRv3pzp06cr8zR8+OGH/Prrr+zatYv0\n9HTOnTvHoUOHdB4ei7dXQfUJJMEshHgn6enpUbdczld4y1iaU2dSf6y9h1Fv6hB6ThxN+fLlGTJk\nCMePH+fKlSuEhIQwZ84cZRsfHx8OHTrE7t27qV+/fmGehhBCiGLuhx9+wNTUlBYtWgDQpUsX0tLS\n2LdvHwBlypTBwsICa2trne2MjIx49OiRzrLs72XLlgVg0aJFGBoa0rVrV/r06UOnTp0AMDU1VdrZ\n29vj6OiInp4erVq1ok2bNhw9elRZn9sxspPOeYnhzypWrMhnn33GxYsXuX79+uv8TEIIIcRbzcTE\nBH19fe7e/WNk6Pvvv09oaCh79+7VGWV87tw5fv31V5ydnQGoXr06jRo1yvMo5hIlSjBw4EA2btxI\nWFgYK1as4MyZM3zxxRcA1KhRAz8/PzZu3MiHH37I119/jZubG+XKlcvHMxbvGkkwCyHeWWrTV9eI\ntM4lCS2EEELkRWZmJkFBQaSkpNC2bVtat25N165dycjIeOVNorW1NY8ePSI2NlZZdvXqVSwsLJQE\nsLm5OV999RUnT57k8OHDVKtWjZIlS2JnZwdk3bj+lVarRe9/E9y+//77SjmNPx9DrVbnOYa/ev78\nOZB7AloUHY9ejfKljRBCiL+ndOnSNGnSRHnA/Gd/raWc3UcYOnQorVu3pnXr1kRFRfHf//5X5w2i\nvEwur1KpaNasGZ07d9a55rdr146goCDOnj3Lt99+S0JCAs2bN/+7pyfeIAXVJ5AEsxDinaU2rYz2\nL7Wn/kybmYnatHIhRiSEEOJtEhISQnx8PFu3bmXXrl3KJyAggAsXLhAVFaW0/evNpaWlJa1atWLR\nokWkpqYSGxvL6tWr6du3r9Lmxo0bpKSkkJmZyaVLl5g3bx7u7u5K8rdfv35cvHiRw4cPk5mZyZkz\nZzh16pQy0tnBwYGnT5+yZs0aNBoNp06d4vDhw8oxXhWDVqtl06ZNJCUlAVkT3c6ePZvGjRsrEwuJ\n4qFlwyoM6Kx+4foBndW0bCh/ZkIIkV/S09NJS0vT+UyfPp2LFy8yY8YMYmJiyMjIQKPRcP78eSVZ\nnJKSwoEDB5g1a5ZO3yE4OJiSJUsq8/9otVrS09PRaDQ6x9BqtSxdupRz584pczb88ssvHD58mKZN\nmyrxXbp0iefPn/P06VMCAwM5efIkY8eOLZLfShSuguoTlPgnQQkhxJvM2qI6c+lCRHI8kSkJRCVn\nTfpXz9Qc63LmqE0rY21RvYijFEII8abaunUrnTp1yjGRXuvWrbGzs2Pbtm18+umnQO6jkBYvXsys\nWbNo27YthoaGfPzxx4wePVpZf+7cOb7++mtSU1MxNzdn0KBBDB48WFnfqFEjFi9ezOLFi/m///s/\nLCwsWLBgAY0aZY1KMTY2ZuXKlcyePZulS5diZmbG7NmzlfUvimHUqFHK+hMnTrB8+XKePn2Kqakp\n7dq10ykjJYqP/o5ZZVj+OrHPwC5q+jlY57aJEEKIv8nPzw8/Pz/lu0ql4uTJkwQFBeHv78/AgQN5\n9OgR5cqVo27duvj5+VG1alXWr19PuXLl6N27NyVK6Kbs+vXrx9atWxk0aBAqlYodO3awY8cOnWNs\n2bKFkiVL4uvrS2xsLBkZGVSsWJEuXbowceJEnfjOnz9PRkYGdnZ2fPvtt9SuXbvgfxhRLBREn0Cl\n/etwibdcXFwcHTt25MiRI1hYWBR1OEKIYiR7Jt3sV4eFEEIIUXCkX140Tl+++7/Je1R4utnSooGM\nXBZCCJF3cv1+e+Rnn0BGMAshxP9IYlkIIYQQb7uWDatIOQwhhBBC5GufQLIpQgghhBBCCCGEEEII\nIf4WGcEshBBCCCGEEG+x05fvELD9EpA1M7yMYBZCCCHeXQXRL5ARzEIIIYQQQrwDBg8ejL+/PwBq\ntZrmzZvz6NEjZX18fDxqtZrbt2/j4+ODvb099vb22NnZoVarle/29vbs2bOHZcuWMXz48BzHedFy\nUTQ2H4zEd30oSQ/TSHqYhu/6n9l8MLKowxJCCPESgwcPpmHDhtjb29OkSRNcXV05ePAgAB06dGD3\n7t2v3O7Pn+joaAC8vb2VCYYBNBoNEydOpHv37sTHxxf8iYkiV1D9gmKZYA4ODmbAgAE0btyY+vXr\n51i/c+dOOnXqhJ2dHX369OHq1atFEKUQQgghhBBvFpVKpfy3np4ey5cvz7XN7NmzCQ8PJzw8nDVr\n1gAo38PDw3Fyciq0mMXft/lgZI4Z4iFr1nhJMgshRPE2btw4wsPDOXv2LN27d2fy5MncvHkT0L2e\nv2i7P3/q1q2rbJe97cOHDxkxYgQPHjxgy5YtVK5cucDPSRStguwXFMsE83vvvcegQYOYMWNGjnXn\nzp3j888/Z/bs2YSGhuLo6Ii7uzupqalFEKkQQgghhBBvJk9PTwIDA7l9+/ZL22m12kKKSOSn05fv\n5noTmS3wQASnL98txIiEEEL8Hfr6+vTv35+MjAyioqL+8f60Wi3x8fEMGDAAU1NT1q1bh7GxcT5E\nKoqzgu4XFMsEc+vWrenWrRsWFhY51n3//fc4OjrSqlUrDAwMGDVqFCVLluTw4cNFEKkQQgghhBBv\npvr16+Po6MiSJUuKOhRRAAK2X8yXNkIIIYpG9gNejUbDd999h4GBAWq1Os/bvcitW7fo27cvzZo1\nY9myZRgaGuZLvKJ4K+h+wRs3yV9kZCS9evXSWaZWq4mIeHEWXgghhBBCCKFLpVIxefJkunXrxqVL\nlzAzMyvqkIQQQgjxPwEBAaxduxYDAwOqV6/OsmXLsLKyyvN22VQqFT///DOQlXy+du0a6enpuLm5\nFVjs4t1TLEcwv8zjx49zDN03MTGREhlCCCGEEEK8pqpVqzJo0CAWLFjw0nqOuSlRogTp6ek5lqen\np1OixBs3juWt49GrUb60EUIIUTQ8PT0JDQ3l1KlTbN68mY8++ui1tsv+ZCeXISvZ3KVLF4YOHcqw\nYcMIDw8voOhFcVPQ/YI3LsFctmxZndmuAX7//XepFyOEEEIIIcTf4OHhwW+//abMTp9XFhYWxMbG\n5lh+69atPI2wEgWrZcMqDOj84lepB3RW07JhlUKMSAghRHGQ/QbT6NGjGTFiBKdPny7qkEQhKOh+\nwRuXYFar1Vy9elX5nj2839raugijEkIIIYQQ4s1kZGTEuHHj+Oabb15ru3bt2qHRaPDz8+Pp06c8\nf/6cw4cPc+zYMXr27FlA0YrX0d/ROtebyYFd1PR3lPsnIYQozl5WS/n58+ekpaUpH41Gk6fttFqt\nst7d3R0vLy88PT358ccf8y1uUXwVZL+gWCaYMzMzSUtL4/nz50BWQfO0tDQAevfuzcGDBzl9+jQa\njYbVq1eTnp6Og4NDUYYshBBCCCHEG6tfv3689957LyyTkdtyExMT1q1bx+XLl+nUqRMffvghq1at\nYunSpdja2hZ0yCKP+jtaM2NYM8qblKS8SSlmDm9GPwdJLgshRHH3stJVM2bMoFGjRsqnadOmyrrl\ny5djb2+v8zl+/Liyzz/vd9CgQfj4+DBp0iT2799fcCcjio2C6heotK+aXrIIbN++nRkzZgBZ//Nr\ntVpUKhVHjhyhatWq7Ny5Ez8/PxITE7G2tubf//43NjY2edp3XFwcHTt25MiRI1hYWBTkaQghhBBC\nCCFeQPrlQgghxJtHrt8iN8Vy9o1evXrRq1evF653cXHBxcWlECMSQgghhBBCCCGEEEII8VfFskSG\nEAXB3t4eyHraZmtri4uLCz169GDmzJlkZmYq7S5dusTgwYPp3LkzvXr1YsyYMURFRQEQGhqKq6sr\n9evX58CBA0VyHkIIIYQQQgghhBBCFBeSYBbvpOrVq7Nz5052795NXFwchw4dAuD+/fv861//wsvL\niwMHDrB9+3bc3d2JiYkBoGrVqsyfP58ePXoUZfhCCCGEeIP4+/ujVqvZuXOnzvIOHTqwe/du5fvd\nu3fp3r07kyZNQqPRkJCQgKenJx06dECtVuu0zaZWq7Gzs1NqLH7wwQekpqYq6zdu3Ejv3r2xs7PD\n0dExx/ZpaWnMmTOHNm3a0KRJE/r06cPZs2eV9fkRgyhcpy/fYejn+xn6+X5OX75b1OEIIYR4hcGD\nB+Pv7w9kXVPPnz+fa7tXXdO9vb1p0KCBci3u0qUL69evz9Emtz7JsGHD8PPzy58TEsVaQfUTJMEs\n3ml6enrY2toqCeRNmzbRq1cv7OzslDaNGzemU6dOAFSrVg1ra2v09OSvjhBCCCFeLTMzk++//573\n33+frVu35lifPdFOZGQkffv2pWXLlnz99dcYGhqip6dHmzZtWLx4MZUrV37hZD9r164lPDyc8PBw\nzp8/j5GRkbLO3Nwcd3d3PDw8ct12+fLlhIaGEhQURGhoKM7Oznh6evLw4UOAfIlBFJ7NByPxXR9K\n0sM0kh6m4bv+ZzYfjCzqsIQQQrzCyyb0y/aqa7pKpcLV1VW5Fn/yySfMnz+fkydP6rQpV64cX3/9\nNWlpaa91fPHmK8h+QrGswSxEfrG3tyc8PDzH8ocPH+Lk5ERmZia3b9+me/fuAOzatYu0tDQOHz6M\nnp4ePj4+2NnZsWDBAn788UcMDAywsrKiVKlShX0qQgghhHgDhYSEkJyczMqVK3FyciI6Opq6desq\n67VaLWfPnmXChAmMGjUKd3d3ZV2lSpUYMGAAwEsfbr9szu7OnTsD8OjRo1zXR0ZG0r59e8zMzADo\n3bs3c+fOJTY2lvr16+dLDKJwbD4YSeCBiBzLs5f1d/znM8QLIYQoOq+6pv+Vo6MjpqamREVF0bp1\na2V5hw4d+OWXX1i/fj1jxowpkFhF8VPQ/QQZhineOWfPniUhIQGtVktCQgIffvihzohlNzc3du7c\niZeXF0OHDqVbt27ExMQQHBzM7t27qVGjBpGRMhJECCGEEK+2bds2HB0dqVOnDk2aNMkxivnw4cN4\nenoyc+ZMneTy65g0aRItWrSgT58+StmvvOrYsSNHjx7l7t27pKens3nzZqpXr66TBC/oGMQ/d/ry\n3VxvGrMFHoiQchlCCPEOyH7gm5GRwb59+/j999+xtbXVaaOnp8e0adNYtWoVSUlJRRGmKGSF0U+Q\nBLN452zevJlq1aqxd+9eDh06xM2bN1Gr1QCYmJgo5TKaNGmCSqVi0qRJmJiYKKN2GjVqxNOnT+UV\nEiGEEEK8VEJCAsePH6dnz54AODs7s3v3bjQajdLm1KlTVKlShY8++uhvHWP9+vUcPXqUEydOMGzY\nMKZMmUJISEiet3d1daVevXq0b9+eRo0asWLFCubNm4ehoWGhxSD+uYDtF/OljRBCiDeXVqtl165d\nNG3alEaNGjFlyhR8fX1p0qSJTjuVSkXLli2xt7dn2bJlRRStKEyF0U+QBLN459y8eZOSJUsCYGpq\nyuTJk/nqq68AqFWrFj///DPh4eEcPXoUa2trnj59qrN9UFAQ5ubm8iqoEEIIIV7qhx9+wNTUlBYt\nWgDQpUsX0tLSCA4OVtpMmzYNc3NzBg0axP3791/7GC1atMDQ0BBDQ0O6detGz5492bNnT563nzp1\nKhqNhlOnTnH58mV8fX0ZM2YM169fL7QYhBBCCPHPqVQqXFxcCA0N5dy5c/Tv35+AgACePXum0y47\nlzF16lSCgoK4ceNGUYQr3jKSYBbvjD+POP7zf3fq1IkHDx5w6dIlSpYsib6+PiNGjMDb25u0tDQO\nHjzIoEGDAJg1axanTp3il19+wcfHBycnp0I/DyGEEEIUf5mZmQQFBZGSkkLbtm1p3bo1Xbt2JSMj\nQ6dMRqlSpQgICMDS0pKBAwcSHx9fqHEeO3aMvn37Ur58efT09Gjfvj2WlpacOnWqUOMQ/4xHr0b5\n0kYIIcSbLTt5XKpUKby9vdFqtaxbty7XtnXr1qVnz54sXLiwMEMURaAw+gkyyZ94Z5w/fx4Aa2tr\nJkyYoLNu165dQFb5DB8fHxwdHXNsv337diIjIwkNDVVGQAshhBBC5CYkJIT4+Hh++OEHzM3NleXX\nrl1j1KhRREVFKcsMDQ1ZtmwZU6dOZcCAAWzYsAFLS0sAZYZ3rVbL8+fPSUtLo0SJEujr6xMdHc3T\np09Rq9WoVCqOHz/O7t27lTezIKsGY3p6Ounp6Wi1WjQaDVqtVunL2NjYsG3bNho2bIixsTEnTpzg\n+vXr2NjYKPv4pzGIgteyYRUGdFa/sL7igM5qWjasUshRCSGE+Ds0Go1y7YWsAXKGhoavvKb/9S1r\nAwMDxo4dyxdffMGgQYMwNjbO0WbSpEk4OjpSsmRJGjduXPAnJ4pEYfQTJMEs3iqJiYn4+vpy5coV\njI2NefbsGTdv3sTZ2ZnatWuTlpZGRkYGM2bMYNu2bVSsWJGIiAjGjx9PQkIC1tbWOWogZmRk0Llz\nZx48eMCRI0ckuSyEEEKIV9q6dSudOnXSSdQCtG7dGjs7O7Zu3arzRpW+vj6LFy/ms88+Y8CAAaxf\nv57atWvTqFHWaBKVSsWMGTOYMWMG48ePZ/z48SQlJTFnzhxu376NgYEBVlZW+Pr60r59e2W/y5cv\n55tvvlH2YWtri0ql4tq1awAsXLiQ+fPn06VLFzQaDVWrVsXHx0enXuM/jUEUjuzZ3/968ziwi5p+\nDv9sZnghhBCFZ9iwYTrfa9Wqxb59+155TVepVDnminJycsLf35/169czYcKEHG0qVqzIiBEjlP2K\nt1dB9xNU2neskGxcXBwdO3bkyJEjWFhYFHU4Ih9ptVr69etHr1696Nu3LwBqtRpTU1MePnxIxYoV\nGT58OB07dmTw4MFkZmZiYmJCRkYGbdu2pVSpUvz000+4u7vrjGBet24dS5cuJSMjg1q1agFgZ2fH\nv//976I4TSGEEEKIt4L0ywvG6ct3/zdRjwpPN1taNJCRy0IIIfKPXL/fbAXVT5ARzOKtcebMGQwM\nDJTkMkBERARxcXF4enrqTDYzf/58FixYwI4dO5Rlfn5+dOvWTSe5HB8fz/Hjx5UnfgEBAa+M49y5\nc9SrVw8TE5N8OjMhhBBCCCHypmXDKlIOQwghhBC5Kqh+gkzyJ94a0dHR1K9fP09tbWxs+O23317Z\nztfXl6lTp6Knl/e/Kps2bZK6g0IIIYQQQgghhBDinSAJZlGs2Nvb57p8165dODs706NHD3r27Mmn\nn37Ko0ePlPVJSUnMmzePyMhIne06dOjAw4cPdZbdv3+ff/3rX6SlpdG9e3fc3d2VdceOHcPJyQkn\nJycWLVpEhQoVsLGxyVEI/2VGjBjBqlWrSE9Pz/M2QgghhBBCCCGEEEK8iaREhij2Tpw4wYYNG1i9\nejVmZmZkZmayY8cO7t+/j7GxMQD79+/H1taWK1euvHJ/S5cupUaNGqSkpLB9+3ZlFvcbN25w7949\n/vvf/5KWloaDgwN6enocP34cjUZDamoqU6dOZeHChTn2mZ6eTkxMDLVq1cLW1hYrKyuCg4Pp2bNn\n/v4YQgghhBB5dPnyZfz9/QkPD0ej0VCxYkXatWvH6NGjWbJkCXv37sXAwAA9PT2MjY2xtbWlf//+\ntGzZUtlHWloaCxcu5ODBgzx9+pRatWrh5eVF8+bNlTYnTpxgwYIFxMXFYWVlhbe3Nx9++GFRnPI7\n7/TlOwRsvwSAR69GUipDCCGKsdjYWBYtWsT58+d5/Pgx7733Hg0aNOCrr75iz549BAQEcPDgwRzb\nnT17lqFDh1K6dGllmUqlYvfu3VhYWNChQwfu3bvHvn37sLKyUtrY2NiwYcMGmjZtyoULF1i+fDlX\nr14lLS0NKysrxo4dS6dOnQrl3EXRKai+goxgFsVeQEAA3t7emJmZAaCnp4ebmxs1a9ZU2uzbt4/P\nP/8cjUbD6tWrleXPnz8nISFBZ38xMTGcOHGCwYMHA1CvXj0gaxS0paUlenp6lC5dmnbt2jF9+nSO\nHj3Kl19+SYsWLXJNLgMkJibSvHlznj59CoCHh0ee6jULIYQQQhSEn376iYEDB1K7dm127dpFWFgY\nmzZtwtTUlNDQUFQqFa6uroSHhxMWFkZQUBAffPABY8aM4dtvv1X2s3z5ckJDQwkKCiI0NBRnZ2c8\nPT2VN8RiY2OZOHEiHh4ehIWF4e7uzvjx47l9+3ZRnfo7a/PBSHzXh5L0MI2kh2n4rv+ZzQcjX72h\nEEKIIjF69GjMzc3Zv38/4eHhbN26lTZt2uTpDWp9fX3Cw8OVz/nz53Um3DM2Nmbx4sU626hUKuW/\nf//9d7p3705wcDDnzp1j7NixeHl5cfny5fw7QVHsFGRfQRLMotj79ddfsbGxeeH6u3fv8uDBA9Rq\nNf369WPPnj04ODjQo0cPHj58SMWKFYmJicHV1ZVu3boRHx9PYmIiO3bsICAggGvXrtGuXTvCw8M5\ndeoU7dq1Iy4ujrNnz+ZITr9IlSpVaN68OZs3bwagd+/ehIaGcuPGjXz5DYQQQgghXsfnn3+Ok5MT\nXl5eykP6SpUq4enpSbdu3QB0bmArVKjAsGHD8PDw4MsvvyQ1NRWAyMhI2rdvj5mZGSqVit69e/Pk\nyRNiY2MB2LFjBw0aNMDJyYkSJUrg5OSEjY2NzkTKouBtPhhJ4IGIHMsDD0RIklkIIYqh5ORkbt68\nSb9+/TAyMgLA3Nycvn37Ymho+I/3P2LECEJCQggPD891fbt27ejZsyflypUDoFOnTqjVasLCwv7x\nsUXxVNB9BUkwizdKZGQkLi4uODg4sG/fPiBr9HLnzp0BcHNzo0SJEhw6dIi9e/dSoUIFLC0tuXjx\nIjt27GDfvn3s37+fEydO0KdPH3777TdGjRrFjh07uHDhAhMnTsTU1BQfHx/s7OyUJ3zNmjV75Yjk\niRMnsnTpUrRaLaVLl2bIkCGsWrWqYH8QIYQQQoi/uHHjBjExMfTo0eO1t+3WrRtPnz7lwoULAHTs\n2JGjR49y9+5d0tPT2bx5M9WrV6du3boARERE5Jhk2cbGJse8GKLgnL58N9cbxmyBByI4ffluIUYk\nhBDiVUxNTalbty4zZ85k586dXL9+/bXmfnoVc3Nzhg4dyoIFC/LUPjExkejoaNRqdb7FIIqPwugr\nSIJZFHt16tTh6tWrAFhbW7Nz507atm2LRqMBIDg4mO3bt9OhQwc8PT2JiooiJibmpft87733XJtE\n+AAAIABJREFU6NGjBwsXLqRhw4acO3cOyCptsXPnTtauXYtWq9Upw/EqnTp14tmzZ4SEhADg7u7O\n2rVrlTiFEEIIIQpDUlISkHVz+boqV64MQEpKCgCurq7Uq1eP9u3b06hRI1asWMG8efOU0VVPnjxR\n5sTIZmxsrIyAFgUvYPvFfGkjhBCicG3cuJHmzZuzceNGXFxcaN26Nf7+/nnaNiMjg6ZNmyqf8ePH\n66xXqVSMHj2a2NhY/vvf/750X0+ePGHChAm0b9+eFi1a/O3zEcVXYfQVJMEsij13d3cWLFigU67i\n2bNnQNYInSdPnnDixAmOHj3K0aNHcXd3Z8+ePUrbvz4FPHPmjFIrOTU1lZiYGKpWrUpmZibJyclA\n1micqKgoWrdunec49fT0mDBhAkuXLgVArVbz/vvvs3Pnzr934kIIIYQQf0P58uUB8lzq68/i4+MB\nlFdmp06dikaj4dSpU1y+fBlfX1/GjBnD9evXAShbtqxSjznbw4cPcySdhRBCCKHL1NSUyZMns337\ndsLCwpgyZQrffPMNQUFBr9xWX1+f0NBQ5ePn55ejTdmyZRk/fjxffvklz58/z3U/qampjB49mkqV\nKuV5tLMQuSnxuhtkZmaSmpqKkZERenqSnxb569mzZ7Rr1075Pnz4cIYNG0ZycjKjRo0iMzMTY2Nj\n6tWrx4cffsjWrVtxdHTU2YejoyOffPIJ48aNA8DZ2Vn5f7Vr165UqlSJOXPmoK+vj1arpU+fPjRo\n0IC0tDQGDRoEZI28WbRoUZ7+Hw8KCqJatWq0aNGCIUOG4OPjQ0xMDFZWVnh4eLBixQr69OmTXz/R\nO8/f35/g4GD09PTQ09Nj9uzZbN26lStXrpCZmYmVlRXz58+XG1shhBDvrJo1a1K9enX27t1Ly5Yt\nX9juz5P9ZNu3bx+lS5fGzs4OgGPHjrFs2TIlad2+fXssLS05deoUderUQa1Wc/bsWZ19/PLLL3z4\n4Yf5eEbiZTx6NcJ3/c+vbCOEEKL4KlmyJK6urnz77bdERES8dB6q19GnTx++/fZbvvvuuxzrkpOT\nGT16NNWrV89z/kO8mQqjr5CnBPPp06fZs2cPoaGhxMXFodVqUalUWFpa0qRJE5ycnF7aeRUir65d\nu5brchcXF1xcXHIs/+trIJBVRiM4OBiAo0eP5rq/kSNH5lhWsmRJZbvXodFo8Pb25scff8TY2Jgh\nQ4bg7+/PvHnzcHV1ZeLEiURGRmJtbf3a+xZ/yMzMJDw8nOPHj7Njxw4MDAxISUlBo9EwY8YMypYt\nC8D8+fP59ttvGTt2bBFHnLvcEuSXLl1iw4YNxMbGcubMGWXU2Jo1a5TR+BkZGfz666+cOXMGExOT\nojwFIYQQb4BZs2bh4eFBxYoVGThwIGZmZty/f5+goCAsLS0B3be8Hjx4wN69e1mxYgWffPKJMuGQ\njY0N27Zto2HDhhgbG3PixAmuX7+u3Pi6uLiwZs0agoODcXBwYP/+/Vy7di3HzPWi4LRsWIUBndUv\nrK04oLOalg2rFHJUQgghXubhw4esWrUKZ2dnatSogUql4siRI0RHRzNmzBgeP36MVqtFo9HoXK8N\nDAxe6zj6+vr83//9H97e3jr7SUxMZPjw4TRo0ABfX19JLr/lCqOv8NIE87Fjx/jyyy+Jj4+nbdu2\nDBw4kKpVq2JkZERqaip37tzh0qVLTJo0CTMzM7y8vGjfvv0/CkiIV7G3tyc8PJy4uDg8PT11ymEA\n/Pe//8XPz4/ffvuN77//npCQEIKDg3n27Bm3b9/GysqK+Ph4unfvjq+vLwDbt29nxowZlC5dmurV\nqwNw69YtgoODCQoKYs2aNRw9elQZvZMdw927dwkODub27dt07NiRoUOHMm7cOFq2bImPjw+lS5dm\n+PDhrFy5kiVLlhTuD/WGyC3hamtri1arxct7Gof2H2Dg0tlEpyRw/0o0jzOeEXwtDLVpZawtquuM\nvtJqtTx79kz5MyxOXpYgNzAwoH379gwePFhnm5EjRyoPQ44dO8aGDRskuSyEECJPWrVqRWBgIP7+\n/jg5OfH8+XMqVapE+/btcXNzIyQkhJ07dyrXYCMjI2xtbfH396dVq1bKfhYuXMj8+fPp0qULGo2G\nqlWr4uPjQ5MmTQCwtLRk2bJlLFiwgBkzZmBlZcU333xD1apVi+rU30n9HbMGMvz1xnFgFzX9HGSQ\ngxBCFDcGBgYkJSUxfvx4EhMTKVGiBBYWFnz22Wd07tyZHTt2EBsbi62trc52Xl5eNGrUKNe3kF6k\nffv2qNVqfv75jxGsW7du5fr169y+fZsDBw4oyz09PXF3d//nJyiKnYLuK7w0wbxkyRI8PT1xcHBQ\nJvLIjUaj4eDBgyxZskQSzKLI1atXDz8/P3x8fIiKilISeufPn2flypXMmzePTz75hDNnznDlyhUa\nNGgAZNUr1NfXV2omOzk5Kfs0NTVl7dq1TJkyRedYJUqUYObMmezfv59Tp07x3Xff8eGHH9K8eXMC\nAwMZOXIk7u7uNG/enLlz51K6dOnC+yGKuZclXAH2HjnET3FRpGszCXuSAIZQon4NEo+c5rOx/8Ko\nnhVT3Abj1j3rz2n69OmcOHECKysrPv3006I8NSAr2R0Zd4uI5HgikhNemiA3MzN75f727t1L9+7d\nCyFyIYQQb4sGDRrwzTff5Lpu3rx5zJs375X7qFatGsuWLXtpmzZt2tCmTZu/FaPIP/0dralRxeR/\nk/So8HSzpUUDGbkshBDFUenSpfniiy9euN7V1RVXV9cXrr9y5coL1+X2JveGDRt0vo8fPz7XN8LF\n260g+wovTTDv3r07T8PkDQ0N6dGjB926dcuXoIRITEzE19eXK1euYGxsTMWKFZkxYwZarZa0tDQ6\nd+6MgYEBd+/e5cGDB1y/fp1169YREBBA7dq1lf0kJydTrlw5FixYwLZt22jVqhVmZmaoVCpq1qxJ\nbGwsDRo0QKVSYWdnx5kzZ7hx4wY1a9ZU9qFSqXBzc2P79u24u7uTmZmprKtUqRKVKlXCwsKCuXPn\n4uTkxL1795g4cSJTp05lxIgR1KpVi8aNG/PDDz/kGKH6LnmdhGtGRgb+y5dTpW87Hl6+ruxDr6QB\ndb0G8/i3OFKjY5k3ew56mnRcXV2ZN28emZmZzJ49m4CAgCK/WEbG3eLTS/tRZf8b+ooE+cs8ffqU\nkydPMmvWrAKOWgghhBBvspYNq0g5DCGEEEK8UEH1FV6aYH7dGixSs0XkB61Wy/jx4+nVqxdfffUV\nAJGRkdy/f5+ZM2dSokQJDhw4QFxcHEOHDiUpKemFr4fY2dmxbds2fv75Z9LT00lJSQEgPT2dW7du\nUadOHaVtdmKzb9++VK1alaSkJGVdmTJlcHNzY8OGDahUKp49e6ZzHGNjY/r3709ISAi2traUKVOG\ntLQ0QkJCaNu2LR4eHixevPidTjC/TsJ106ZNVGhQl2cmZXPsR6WnwqiOJUZ1LKlYsw4HDhxQnuzq\n6enRvXt3Vq9eXZinlquI5Pg/zvV/XpYgf5ljx47xwQcfSHkMIYQQQgghhBBCFDuvlRHevHkzPXr0\nwNbWltjYWABWrlzJvn37CiQ48W46c+YMBgYG9O3bV1lmbW3NzZs3sbe3R19fX1lepkwZ6tatq1Os\n/s8MDQ0xMzNj/vz5AFy4cIGPPvqICxcu0KxZM+rWravTvkWLFpQvXx4/Pz+l3jJkJZ+HDBnCjh07\ncHNzIyMjg+vX/xhZ+/jxY27dukVCQgIajQaVSsX48eNZunQpAD169ODmzZtcvnz5n/9Ab6iXJVwt\n+jpQwqgM82bPISAggAMHDmBgXzvHn2vavSTSEpOV79FRUVStWpWYmBgg6+HE0aNHef/99wv+hF4h\nIjkh1+XZCfLKXVvRtJ+zTr2rFwkODqZHjx75HaIQQggh3iKnL99h6Of7Gfr5fk5fvlvU4QghhBCi\nmCnIvkKeE8zffvstS5cuxcXFRWd5pUqVCAwMzNegxNspMTGRyZMn4+DgQK9evXB3d+fmzZs6tY4B\noqOjSUpKomPHjri4uODi4kL//v25fv069evXJyMjAzc3N0aMGMGtW7dYsGCBzvYHDhxArVbz5MkT\n9u3bR5MmTZgyZQoZGRmULFmSR48eYWFhwZkzZ7h7V/cvlEqlYsSIEaxcuVJnuVarxdjYGCcnJ/bs\n2YOBgYEyQeDz58+ZOHEibm5udO7cmRUrVgAwZMgQjh07RkxMDCVKlGDkyJHKundRXhOufn5+xMTE\ncG7BGiLmrCZTk07EF2sByEh7TmzgfiLnrydq4UaeJCYxduxYpk2bhpOTE87OzqSkpODh4VGYp5ZD\nZmYm0Sk5zze3BHm1atV02vw1qf7o0SPOnTtHx44dCyZYIYQQxc6VK1eYMGECrVq1wt7eng4dOjBx\n4kTOnDkDgLe3N2q1OscbOwkJCdjY2KBWq5VlPj4+2Nvb63zUajXr169X2jx58oS5c+fSunVr7O3t\n6datG9euXVPWP3jwgPHjx/PBBx/QsmVLFi9erHO9Sk5OZtq0abRu3ZomTZrg5eXFw4cPC+jXEbnZ\nfDAS3/WhJD1MI+lhGr7rf2bzwciiDksIIcTfdPnyZcaOHUvLli1p3LgxnTt3xtfXl8TERABu3rzJ\nlClTlGt3p06dmDFjBrdu3QJg2bJlDB8+/JXHCQwMRK1W4+/vX6DnI4peQfcV8pxgDgwMZM6cOYwa\nNUpnBKmNjQ3R0dH5FpB4O2WXvWjRogWHDh1i+/bteHl5cf/+/RxtVSoVKpWKadOmsXPnTnbu3Mnm\nzZsBlBHCixcvZu3atVhZWWFlZaVsm5qaysaNG7Gzs+P58+f8+OOPNG3aFCsrK0qWLIm5uTkuLi5U\nrlyZ7t27s3z5ciW+bK6urpw+fVqnREa2YcOGsWXLFvT19dm1axe//fYbM2fOpHbt2gwbNgwvLy+W\nLl1KWloaxsbGDBkyRPmHetSoUQQGBvL48eN8/W3fBK+TcO3bty8nT55kwIJPed9nNHqGJVDPHAFA\nGUtz6kzqj7X3MOpNHULPiaOpWLEimzdvZs+ePezZs4d58+ZRqlSpQju315FbgnzcuHFs3LiRdu3a\nce/ePZydnfnss8+UbQ4fPkzr1q2L7TkJIYTIXz/99BMDBgygevXqbN++nfDwcPbs2UOPHj04fPgw\nkNVXql27Nt9//73OtkFBQdSsWVOndNjs2bMJDw9XPt988w0lSpRQJo7VarWMGzeOO3fuEBQURHh4\nOCtXrtSZgHbKlCno6elx4sQJtm3bxqFDh3SS29OmTePp06ccPHiQI0eOkJKSwtSpUwvyZxJ/svlg\nZI4Z4SFrlnhJMgshxJvnp59+YuDAgdSuXZtdu3YRFhbGpk2bMDU1JTQ0lMjISNzc3DA0NGTLli2E\nh4cTFBRE/fr1OXHiRJ6Pc/v2bdavX4+1tfULy46Kt0Nh9BVeWoP5z27fvp3ra+clS5bkyZMn+RKM\neHu9qOxFXFxcjrZ16tQhJSUlx0jOOnXqEBAQgKGhITVr1iQuLo6bN28SEBCARqPh8ePHfPLJJzRt\n2pQ1a9aQmZlJeno6I0aMUPYVGxvL+PHjmThxInv27CE5OZljx45RpUoVKleuTEZGBgYGBgwZMkQZ\noQwo/9iampri6OjIhg0b8PT0ZPr06Vy8eBFra2tldH/t2rXZvHkzw4YNY9y4cbRs2RIfHx8sLS1p\n06YNW7ZsYeTIkfn+G7+JMtKec2f7UTKepqHS06NshXKM+2IcAGpTc8KeJAAvvtBZlzMvpEhfj56e\nHnXLZcf/h+wEebYmZc0pX748Q4YMYciQIbnu61WzBwshhHi7/Pvf/6Znz55MmTJFWVa2bFkcHR1x\ndHRUltnb2xMeHs7PP/9Ms2bN0Gq1BAUFMXjwYKU0WG62bNlChw4dqFSpEgAnT54kPDycEydOKLX+\nLSwslPaxsbGcPn2aQ4cOYWRkhJGREaNHj8bf35/Ro0fz5MkTQkJC2LlzJ2XKlAHAw8ODwYMHEx8f\nT+XKlfP19xG6Tl++m+sNY7bAAxHUqGIiE/8JIcQb5PPPP8fJyQkvLy9lWaVKlfD09ASyBr41bNhQ\nJ2fx3nvvMXDgwNc6zsyZM5k8ebJUJXjLFVZfIc8J5sqVKxMdHZ3jde6zZ89So0aNfxSEePtFR0dT\nv379PLVt2bIlGRkZzJo1Sxn9a25uzujRo0lISMDb2xvIuvlZt24d5cqVIykpiaVLl1KqVCn+9a9/\nERYWhre3N/Xr1ycuLo7u3buTlpaGtbU1w4cP57PPPqNx48YvjGHw4MHKhHzjx4/XWeft7Y23tzcP\nHjygbt26hIeHU716dWX9oUOHmDx5MkOHDqVOnTo0b96cwMBARo4ciYeHBz4+Pu9cgvl1E64AatPK\naGMv0GDBhFz3qc3MRG1afG9a/0iQv1hxTZALIYQoGjdu3CA2NpY5c+bkqX3v3r3Ztm0bzZo146ef\nfsLExISGDRu+sH1iYiJHjx7VKQV29uxZLCwsWLp0Kfv27aNs2bJ069aNCRMmUKJECSIjIzE2NsbS\n0lLZxsbGhtu3bytvZWm1Wp2BARkZGQBcu3ZNEswFLGD7xTy1kQSzEEK8GW7cuEFMTAyff/55ruuf\nPn1KaGjoC9fn1ZYtWyhbtixdu3aVBPNbrrD6CnkukTFgwADmzp2r1H6LjY1l27ZtLF68mEGDBv2j\nIMTb73Vft2jRogU1atTg8ePHpKeno1KpMDMzw8rKir1799K5c2e6d+/Oli1bKF++PFqtlrCwMM6f\nP0+7du24cOECUVFRyv6srKwoU6aMUnLjZcnlvKpQoQLu7u45akB36tQJfX19ZfK2iRMnsmzZMrRa\nLY6OjiQmJnLu3Ll/fPw3jdr01cnUPydcrS2qM9e2CwOr2dKkrDkmGjDRZCWhB1azZa5tF6wtqr9k\nb4XH39+fHj164OzsjIuLC5cuXeLX42eJmLOaS5OXkP74qdL2WcIDrn8VyOUp/yHi8MkijFoIIURx\nk12ey9z8j+vhkSNHaNq0KU2aNMHW1hbISuiqVCpcXFw4fvw4v//+O9u2baN3794vnPgY4IcffqBq\n1aq0atVKWZacnMz169cxNDTkxx9/ZPXq1ezfv18pgZGamoqxsbHOfrK/p6amUrZsWZo1a8ayZct4\n9OgRSUlJypwTqamp+fCrCCGEEO+O3PoCf/bw4UMyMjJeuD4v7ty5Q0BAALNmzfrb+xDir/KcYB42\nbBhOTk54eHjw9OlTRowYwRdffMHQoUN1yh4IkZs6depw9epV5bu9vT0A8fHxREdHK5P5ubq68vz5\nc+7du4exsTFubm6UKFGC+Ph4OnfuTGJiInfv3mXQoEF06dKF4OBgHj9+TP369SlXrhwajYb4+Hi0\nWi1ffvklffv2VSYT7NKlC8+fP8/X8/rkk0/YsmWLTqkPlUrFlClTWLx4MQAODg6kpaUREhKCvr4+\n7u7u7+Rkf2rTymgzM1+4/q8jklUqFWrLGrjYtmBa256schrFKqdRTGvbExfbFqgtaxR5najMzEzC\nwsI4fvw4O3bsYPfu3axfv57KlSvTtaMD3yxdhmnFitiXNVMS5I0rWTHScwwf9+lDpfdMizR+IYQQ\nxYupadZ1IT4+XlnWsWNHQkNDWbFiBRqNRqd9uXLlaNu2LatXr+b06dM4Ozu/cN+ZmZl8//339OnT\nR2d52bJl0dfXZ/LkyRgaGlK9enUGDBjAkSNHADAyMuLRo0c622R/L1u2LACLFi3C0NCQrl270qdP\nHzp16qRzPqLgePRqlC9thBBCFA/Zb/QmJOT+NqyJiQn6+vo6fYXX9emnn+Lp6akz38LLHlCLN1th\n9RXyXCIDYNKkSbi7uxMdHY1Wq6VOnTpKx1KIl2nZsiVfffUV27ZtU25sIiIiSExMxMDAgJ07d+a6\nnYeHBx4eHkBWUvrbb79lwoQJtGnThr1791KvXj3mzZuHv78/Z86coV+/fjx+/BgDAwPmzJlD9erV\nSUlJwdPTk9TUVPbt20fPnj3/9nlotVru3LmjlIoxMzNjxIgRLFy4kKVLlyrt+vbty/Tp0wkPD8fe\n3p7x48ezdOlS2rZty4gRI3j//fdZvHgx77333t+O5U1jbVGduXQhIjmeyJQEopKzLpj1TM2xLmeO\n2rTyS0ck6+nl+XlYgdFqtUTG3SIiOZ6I5ASiUxK4fyWaxxnPCL4WppxD9oh7gDKGJZnYsqtS1zL7\nPPxu+xV5glwIIUTxUqtWLSwtLQkODqZly5Y6615049enTx+GDRuGi4sLRkZGL9x3SEgIiYmJuLm5\n6Sy3sbHJsX+tVqtcr6ytrXn06BGxsbFKmYyrV69iYWGhHM/c3JyvvvpK2f7HH3+kZMmS2NnZ5fXU\nxd/UsmEVBnRWv7C24oDOaimPIYQQb5CaNWtSvXp19u7dm6MvAFC6dGmaNWtGcHAwvXv3/lvHOHXq\nFFevXlWu3ampqVy5coWffvqJTZs2/aP4RfFTWH2FPCeYNRoNmZmZlC5dWnk9D+DZs2fo6elhaGj4\nj4MRbzc/Pz98fX1ZtWoVT58+5T//+Q/Dhw9Ho9HQrl07pd306dMBCAsLUybOy07EWVtbM2PGDD75\n5BPu3LkD/PEKSUxMDCYmJhgYGCg1AY2MjEhJSeHWrVvcuXOHX375hXXr1vHxxx//rdIuGo0GW1tb\nwsPDsbKyArJmVrexsWH69OlUqZL1l9LQ0JBJkyaxZMkSNm3aRNOmTfHy8iImJgYrKyscHBz47rvv\nGDt27N/5Kd9I2SOS1ZY1gKyRVFA8Esd5FRl3i08v7UeVHbMhlKhfg8Qjp/ls7L8wqmfFFLfBuHV3\nyrHtm3SeQgghio6Pjw9jx46lXLlyDBo0CHNzc549e8alS5d0HkxmJ4SbN2/OunXrqFOnzkv3u2XL\nFhwdHXOMKnZwcGDx4sUsW7aMiRMnEh8fz5YtW/j4448BsLS0pFWrVixatAhfX1+Sk5NZvXq1zhuM\nN27cwNTUFBMTE65cucK8efNwd3d/acJb5J/+jtYAOW4cB3ZR08/BuihCEkII8Q/MmjULDw8PKlas\nyMCBAzEzM+P+/fsEBQVhaWmJt7c3AwcO5NNPP8XDw4Nq1arx6NEjgoODef78uTKBfGZmJhqNRuch\nsqGhIcePH9c53qRJk2jSpAkjRowo1PMUhacw+gp5TjBPnDiRFi1aMGzYMJ3lW7ZsITQ0lG+++SZf\nAhJvLzMzM/7zn/8AWaORAwICiIuLo1SpUsrNTuPGjenSpQtPnjzh6tWrfPbZZ8r22WU1PvroIz76\n6CP8/PwoU6YMFy5cIDo6miNHjtCtWzeCgoKYPXu2MqngrFmzKFWqFK1atVKO/2ePHz8mJCSELl26\nvPIcSpYsyZgxY/j8889Zs2YNkDUB5tChQ1m0aBFffvml0tbd3Z1atWoRGxtL/fr1UalUymjrMWPG\nMHnyZDw9Pd/ZUaxvYsI1Ijn+j+Ty/+iVNKCu12Ae/xZHanQs82bPQU+TjquraxFFKYQQ4k3Wpk0b\nAgMDWbFiBa6urjx79ozy5ctTv359NmzYAGQ9tP1z/6FFixY6+/hr3yIhIYETJ04o2/9Z2bJlWbNm\nDbNnz6ZZs2aYmprSq1cvnZvMxYsXM2vWLNq2bYuhoSEff/wxo0ePVtafO3eOr7/+mtTUVMzNzRk0\naJAyWbIoHP0dralRxeR/E/mo8HSzpUUDGbkshBBvolatWhEYGIi/vz9OTk48f/6cSpUq0b59ez7+\n+GMqVKjADz/8gJ+fn/IWd/ny5WnVqhXu7u5AVl/g7NmzOgNEAb788ku6deums8zAwAAjIyOlPId4\nOxV0X0GlzWOhlRYtWrBx40bq1aunszwqKoqhQ4dy+vTpfAuqIMXFxdGxY0eOHDmChYVFUYfzzrK3\ntyc8PJy4uDg8PT3Zs2ePzvodO3Zw5coVtm/frrTr1KkTERF/PG3x8/MjJiaGs2fPkpCQQO3atdm6\ndSuenp54e3tTv359vvjiCw4cOMChQ4eYPHkyDg4OORJ/v//+O/Xq1ePQoUM5/vHNTXJyMvXq1SMk\nJAS1Wg1kFclv0KAB165d0ym27+XlhUqlYvHixYwePZpNmzaRlJREyZIlUavVrF+/XmeiHVG8zT++\ni7AnudfCylYx4h7ayDgCAgIA6NChA9u3b6dcuXI67bIfkMhTYiGEEO8q6ZcLIYQQbx65fovc5HkI\n4ZMnTzAwMMixXF9fX2aIFq90+PBh1Go1v/32G5D1qoaT0x9lBLZt20avXr149OgRKSkprF69ml27\ndvHs2TMePnyos687d+5gb2/P+fPnMTMzU2of3759m379+hEbG6sc48iRI6Snp+Pg4EBUVJTOg5CR\nI0fStGlTpk2bxpw5c/D09CQzM5PY2Fh69+6No6MjkydPzjExoKmpKV5eXjqjq6tWrcrAgQNZsmSJ\nTttJkyaxbt06fv/9dz799FMyMjJYu3Ytenp6jBkz5p2c7O9NlZmZSXRKzuRy2r0k0hKTle/RUVFK\nje5suT3Hy8uzPX9/f3r06IGzszMuLi5cunQJLy8vunTpgpOTEzNmzCA9Pf1vnI0QQgghhBBCCCFE\n/shzgrlWrVocPnw4x/KjR49So0aN/IxJvIX27t3LRx99RHBwcI51Dx8+ZNOmTaxduxZjY2NWrlxJ\nnTp16NmzJ/r6+qxcuVKn/fz585WazeXLl8fa2pqqVasyd+5cduzYQWpqKufPn+fEiROUKlUKa2tr\n2rZtS4UKFZQEN8CoUaNYuHCh8t+ZmZmsW7eOxYsXM3z4cA4ePIiJiQk//PBDjpgnTpzITz/9RFhY\nmLJs2rRprF69msTERGWZlZUVXbp0YdWqVVSvXp1mzZrh6+uLVqtl6NCh7Nq1S6khLd5MGWnPiQ3c\nT+T89UQt3MiTxCTGjRvHxo0badeuHffu3cPZ2Vl5IJGYmEi7du1Yv349/v7+fPTRR0pPwdb9AAAg\nAElEQVTN8GyZmZmEhYVx/PhxduzYwe7du1m/fj2VK1emZ8+e7N+/nz179pCWlsb3339fFKcthBBC\nCCGEEEIIAbxGDeaRI0cyffp0kpKSlFf6s2eYnDt3boEFKN58jx8/5tKlS2zatImRI0cyYcIEpTbg\njz/+SFJSkk4JgaNHjzJgwABiYmIoUaIEhw8fpl+/fkDWSGgLCwvKlCnD+fPnUalUlCpVimrVqlGz\nZk0MDAwoU6YMSUlJXLx4kdu3b6PRaPj5558ZMGCATimOli1bcvbsWSCrHnCrVq345JNPUKvVymyq\nrq6uLFu2jP79++ucU5kyZfj000+ZMWMGBw4cAMDCwoK+ffvy5ZdfMm/ePKWtl5cXPXv2ZOLEicyd\nO5fOnTtz/PhxPvroI3r06MGGDRuYPHlyAf36Ir/o6elRt5x5jhIZZSzNqTPpj/8/mpQ1p3z58gwZ\nMkSZXOHPKlWqlGNSBa1WS0TsTSKS44lITiA6JYH7V6J5nPGM4GthqE0rY21RHZVKhZmZmbLd/7N3\n31FRXG8Dx79LEwVRbFijRJQlQZGmoCAGFeyiiaIUWxDBGpCfih0LomIXAUEFO9ixRI0axYIFBSwR\nW4xij4ixIXXfP3idZAMaklAScz/n7Dlh5s7MMxNk7zxz57nNmjXj0aNHJXymgiAIwsfI3d2d1q1b\n4+3tDRSUCBs+fDgymYxBgwYxZswYrly5Umi7d2XKKlasqLR85cqVWFpakpGRQWBgIKdOnSInJwcj\nIyP8/f2lMmJC2Ui49ICw7RcB8OptUiKzwQuCIAh/3aVLlwgNDSUpKYns7Gxq1KiBnZ0dQ4cOZcGC\nBaipqRWZS1u2bBmhoaFUqFBBafm4ceOkvMSrV69YsWIFhw8f5smTJ1SuXBkjIyMGDRqEtbW10nbH\njh1j2LBhfPXVV0rHk8vlaGpqKs3bUKVKFY4ePVqCV0H4JyntvkKxE8zdu3fn7du3LF++nDVr1gCg\np6fH1KlTcXJyKtGghI/L4cOHsbGxoW7dulSrVo0rV66wZ88eunfvLv1RrF69utQ+PT1dSsxt3bqV\n9PR0fvnlF9TV1fHz80NLS4vMzEy0tLR49uwZc+fOleoev3jxgqysLF68eMHZs2epVKkSmZmZVKxY\nke+//568vDyeP39eqB4uFNx4rVy5kszMTGkCOj09PZ48eVLkeXl4eBAcHMzRo0dp164dABMmTMDM\nzAw/Pz/pnMzMzGjatCmxsbG4urpSs2ZNJk+ezIkTJ/Dy8sLDw4NvvvnmPzvZ37+JXLdwgvn3DKvq\nfXB9Ua7du8Pki/t/nUBQA9Q+b8TPhxOYMvwbtJt+gt+X7nzZ9deyMjk5OcTFxTFp0qQ/fTxBEATh\nv+ldX+Phw4cMHTqUTz/9lODgYJKSkv5w2/379yvNM/HOrFmzeP78Ofv370dTU5PFixfj5eUlblDL\n0KaD15RmhQ+MOouLo1yaMV4QBEEoWydPnsTb25uBAwcyffp0atWqxc8//8zWrVs5d+5cocl6f8/K\nyorVq1cXue7169f0798fLS0tFixYgFwuJz8/n+PHj3Pw4EGlBPPLly8JDAzE3Ny8yOOtXr0aMzOz\nv3/Cwj9eWfQVil0iA6BPnz4cO3aMkydPcvLkSY4dO0bfvn1LLBjh47R37146d+4MQKdOndizZw8y\nmYzq1atTt25d9u3b995t3/3hrVKlClpaWsyZM4f+/fvTokULBg8ezM6dO1FXVycjI4Pnz5/j6+uL\nubk5GRkZUj3nt2/foqGhQYsWLYpMLL/TokUL+vfvz6tXrzh58uQfnpeGhgYzZ87E399fqqfbsGFD\nevfuzeLFi5Xa+vn5ERwcDMDEiRM5e/Ysd+/epU2bNqipqRUa0Sr8M8l1a6PIz3/vekV+PnLd2n96\nv6kZj35NLv8/lQrqNBnrTn3njqhpV2LOjJns2LFDWh8QEIClpSXm5uZ/+niCIAjCf9f169dxdnbG\nysqKpUuXoqGh8bf35+joSOXKlVFXV+fLL7/k0aNHPH/+vIQiFj7k9zeM72w8kMqmg9fKISJBEAQh\nICCA7t27M3bsWOkN1Jo1a+Lt7U2XLl2AD8/J86F10dHRPH36lIiICIyNjVFTU0NDQ4P27dszbdo0\npbZz5syhT58+fPLJJ8WaA0j4OJVVX+FPJZjfqV69utKIU0F4n+fPn3PmzBkmTZqEvb09q1at4sCB\nAygUCipWrMjKlSvZvHmzUumK6tWrS3WMFQoF1apVA+Dt27fMnz+f6OhoEhMTCQ8PZ8OGDaipqVGz\nZk0CAgLQ19fHwsKCGzduMHv2bOrXr4+TkxOHDx/m5MmTvHz5UinJ/PuneMHBwaiqquLu7k5OTg6P\nHj1SKknwe/379+f169dK8fv7+7NixQoyMn6d+K1Tp07k5ORw+PBhhgwZIr0OI5PJ8PLyIiws7O9d\naKFMGNZvyKzmnXCt1xwLLT10skEnu6Ashmu95sxq3gnD+g3/9H5TM4oeFS1TkaFt0IDanVtj2a+H\nVI5l+fLlPH/+HH9//791PoIgCMJ/S1JSEm5ubri5uTF58uQS2Wf79u3Zt28fz549Iysri9jYWCws\nLD74UF8oGQmXHhZ5w/jOxgOpJFx6WIYRCYIgCLdv3+bu3bt069atVPYfHx+Pra0tlStX/mC748eP\nc+3aNYYMGfLe5LJIOn/8yrKvUOwSGRkZGSxcuJBTp06Rnp5O/m9G8clkMlJSUkokIOHjcuDAAXr2\n7ElAQIC0zN3dnYcPC36Bq1WrRmRkJAMGDEBXVxcbGxvs7e3ZsWMHnp6e5Obm0qFDBwByc3PJy8sj\nPz8fhUJBu3bt0NPTIzMzkwcPHpCfn8/169epUaMGd+/exc7Ojp07d7Jt2zbOnz/PmzdvqF+/vlJ8\nCoWCN2/e8OrVK7S1tdHR0aF58+bEx8ezYMEC3rx5Ix2/KCoqKsyePZuJEyfStWtXVFVV+fTTT+nR\nowdLly6VniDKZDJpFHOHDh0YNGgQa9asYcmSJdJN3uPHj4t89VT455DJZMgbNELeoBGA9HdQReUv\nPauT9nHj+WP43QCyrCfPQCajQk1dAG5cv45dvSZs2bKFEydOEB0d/ZePKQiCIPw3nT9/Hk1NTbp2\n7fqnt+3atav0YL5BgwZs374dAE9PT7y9vWndujWqqqrUqVOn0ATNQukI2/7H919h21NEPWZBEIQy\n9OzZM4C/dW9/7tw5LC0tlZaFh4djZmZGRkZGoXW/9+rVKwICAli+fDkqKirvLckxdOhQVFVVpZ/N\nzc3F4LePTFn2FYqdYJ4yZQo//PADffv2pWbNmqJerFAsO3fuRFVVlY4dO1K5cmVq1KiBsbExnp6e\n1KtXDyhIsOXm5uLv709gYCB37txh/fr1LFu2DG1tbTp16gSAvr4+u3fvZvny5Vy4cAG5XE5OTg4K\nhQKFQoGOjg63bt3ixx9/pE2bNqxfv56kpCTy8vJIT0/H0NCQhQsXSrG5uLhw+/ZtfvnlF6ysrAgP\nD6dNmzYsXryYzp07s3LlSjp06MCUKVM+eI7dunVjzpw5bNq0CTc3N6CgDIa1tTXffPMNVapUkY43\nadIkLl68yKRJk4iMjCQyMpJRo0bx5ZdfsmbNGiZMmFAa/xuEUvJ3Est/JC8rhwfbj5CXmYVMRQWt\n6lUZPms4bdu2pV69ejg7OwPg4ODA8OHDSy0OQRAE4eMxePBg0tLScHV1Zc2aNejr6xd727179xZ5\nszxkyBCMjIxYsWIFFSpUYMeOHbi6urJnzx7xxqMgCILwn/PuDezHjx/z6aef/qV9tGzZ8r01mHV1\ndf9wove5c+fSpUsXacLddzmT34uMjBQ1mIUSU+wE8+nTp1m5cqX45ROKTaFQkJ+fj5OTk5QMS01N\n5dWrV7x9+5batQtq1QYEBDBhwgS6dOmCs7MzvXv3JiQkRKn979nY2DB48GBu3bqFpqYmzZs3Z+TI\nkfj7+9O7d2+ePXvGvn37cHNzIz8/n3379rF582alhODGjRsBePPmDc2bNyc9PR0oGJWze/dujI2N\nuXPnDurq6h88T5lMxpw5cxg8eDB9+/ZFQ0ODJk2a0LlzZ5YvXy5NwlahQgVGjRrFwoULiYqKonXr\n1syZM4eRI0fi5eWFs7Mz48aNK9WkpfDPo6KiQpOqhScPrNRAD4Mx/aWfLbT0qF69OleuXCnrEAVB\nEISPhKqqKkFBQQQEBODm5sbq1asxNPzrk7s8e/aM5ORk5syZg5aWFlAwZ0twcDDJycm0b9++pEIX\niuDV24TAqLN/2EYQBEEoO/r6+jRs2JA9e/YoTbj3ex8atPmh0hV2dnZER0fz4sULdHR0imxz8uRJ\nXr16RWxsLFCQ8wBISEjg8OHDxTkN4SNRln2FYmeyKleuLI3EFITiOH36NOrq6lJyGUAul2NhYYGv\nry+xsbFERESgUCjo0qULCQkJ723/Po0bN5YSstra2nTu3Jlt27bx448/0rVrV1RUVKhSpQqffPIJ\nFy9eLHIflSpVYtWqVQwfPlyakEZfXx9/f39OnDjBnj17/vBc7ezsaNq0KREREdKySZMmsWTJEl6+\nfCktGzZsGHFxcdy/f5/AwECePn3K999/j4WFBbq6unz33Xd/eCzh4yPX/ePXpwyrivIpgiAIwt/z\n7oZ12rRp9OzZkwEDBij1j7Kzs8nKypI+eXl5H9xftWrVqFOnDhs2bCAzM5Pc3Fy2bt3Kmzdv/lbi\nWige62Z1cHGUv3e9i6NclMcQBEEoB9OmTWP37t0sWrSIJ0+eAPD06VPCw8PZt28fUFAC9Pffu8Ux\nYMAAatWqxbBhw7h8+TI5OTlkZ2dz9OhRqTRpbGwsu3fvZteuXezatQt7e3scHBzYvHmz0r5EDeaP\nX1n2FYqdYPb09CQ8PJzc3NwSObDw8btx4waff/55kesqV67M0KFDWbRoEVOnTv3D9r/326d9v/3v\nIUOGkJGRwevXr6ldu7ZUa6h27do8flz0RGrnzp2jevXq9OjRAz8/P2n5+PHjqVWrFkOGDJGe+H1I\nYGAgs2fP5vXr10BBcrx9+/asWLFCalOtWjXc3d1ZtmwZ1tbW1KlTh8mTJyOTyRg2bJiod/QfJdet\njeI3de1/T5Gfj1y3dhlGJAiCIHyMfttnGjduHO7u7gwePJjExETy8vJo3rw5JiYm0mfmzJnvrdv4\nTmhoKLdv36Zdu3ZYWVmxadMmlixZUmjeC6F09HcwLPLG0bWTnP4OIskvCIJQHlq3bs3GjRu5efMm\n3bt3x8zMDFdXVzIyMmjZsiUAO3bsUPrebdGiBSkpKchkMs6ePYupqanSZ8GCBQBoaWmxceNGzMzM\n8PHxwdLSkg4dOrB582a6dOkCQI0aNdDT05M+FStWpGLFitSsWVMpzq+//lrpGGZmZkW+QS78u5VV\nX0GmKOYjCw8PD1JSUqhQoQIGBgaoqakhk8lQKBTIZDKlkZv/ZPfu3aN9+/YcPnxYdHxL2bp167h3\n7x7+/v5Frh8+fDiXL19m6tSpdOjQ4YPt7927h7e3N7t37y5yX+7u7kyYMEFKUM+cORMTExN69OgB\nFIwmtrOzw8HBodC2e/bswcfHhxMnTtCyZUsiIyPp2LEjUDDzqqOjI8OHDyc4OFjaJjs7m4iICEaM\nGKG0r759+2Jqaiqdw5UrV7C3t+fHH3+UXh29ffs2lpaW3L59m5iYGLy9vbl16xa6uro0bNiQS5cu\nSfWphf8GhULBtXt3SM14xLXnj7meUfAwpKmuHoZV9ZDr1sawfkNR+14QBEH4qIh+eclJuPTw/yfy\nkeH9ZXOsjMXIZUEQBKF0iO/vf6fS7isUuwZzjRo13ltHTSQ9hKIYGBhw4MCBItd9//33vH79msjI\nSEaOHImNjc0H2/9Zenp6SoXvHz169N5ZXLt168amTZsIDAxk5cqVeHp6cunSJbS1tbG1taVnz56E\nhITw9ddfY2RkBBTUzV26dCn6+vrSU0IoSGzb2Njg5eWFrq4un3/+OW3btiUsLIyxY8cCBeU32rdv\nz6pVq/D29mbMmDEEBASwatUq+vXrx6pVq6RR3cJ/g0wmQ96gEfIGjYCCiS+hdCcRFARBEATh42Hd\nrI4ohyEIgiAIwnuVdl+h2NmLoKCg937mzJlTagEK/17W1tZkZ2dLheWhYNK+xMREgoKCmDp1Kk2b\nNqV9+/aEhoZ+sH1x/HYwvr29PXv37iU7O5u0tDTu3LlD8+bN37vtsmXL2Lp1K5qamrRr105pFPWy\nZctQV1fH3d1dOoaamhoLFizA19eXnJwcqa2hoSE9e/Zk3rx50rLJkycTHBysVGbDz8+PRYsWoaqq\nioeHBxs3biQzM5Nhw4YREREhStH8x6moqIjksiAIgiAIgiAIgiAI/woigyGUquXLl3Pq1Ck6duxI\nt27dWLRoEZs2bcLBwYHGjRsDMHLkSPbu3cvdu3cLtV+8eDG1atUCCkpL2NnZSZ/9+/dz6NAh7Ozs\nSElJYdiwYXh4eAAFo6c7d+5M165dGTp0KNOmTXvvSPurV6+SmZlJWFgYgwcPZsaMGWzfvp3jx48D\nBaP3Fy1axNWrV1m3bp20XdeuXWnYsKFSjWUoKOi/cuVKHj58CICJiQlWVlZKZWQsLS1p1KgRW7du\nxd/fn7y8PFauXImJiQn169eXCv8LgiAIgiAIgiAIgiAIwj9ZsWswA2zfvp09e/bw4MEDsrOzlWow\nHz58uDTjLDGiVozwe+vWrWPJkiUkJCQwdOhQtLS06NixI+PGjSMlJYWKFSuiUCgwMzPjxx9/5Kef\nfkJXVxcoqLHcrl07rl69So0aNaR9+vr6kpWVRUhICABJSUl069aNW7duoampCcDu3buZPn06iYmJ\nODg4cPnyZR48eMDatWuJiYkRSWZBEARB+EiEhoayZMkSgoKCcHJykpbb29vzzTffSHNGPHz4EA8P\nDwwMDJg/fz4ZGRlMnz6da9eu8eDBA+bNmye1fUcul6OpqSk9SJfJZMTHx6OtrQ2AqampUvucnBzy\n8/M5deoUVatWBQr6M/Pnz+fixYuoqalhbm5OaGgoAImJiQQGBnL//n1yc3OpU6cO/fv3x9XVFSgY\nALBo0SKSk5N59eoVdevWZeDAgfTp0+cPr4vol5echEsPCNt+EQCv3iaiXIYgCMI/mLu7O61bt8bb\n27vQ9zgUDFpzcnJiwoQJqKmpMWLECKXSnO/ycerq6gDUr1+f3bt3Y29vz4MHD4iNjVV6g3vfvn34\n+vpiaWkpDZpbtGgRe/bs4fnz56ipqWFsbIyfn59UFvRDxPf3v0tZ9RGKPYJ5zZo1zJo1i6ZNm3L/\n/n3s7e3R19fnxYsX9OrVq1SCE4Sy4ObmRq1atZg5cyaLFy8mLi6OypUrY2pqyvTp04GCm7UNGzaQ\nnZ2Nj4+PtO3nn3+Os7Oz1O4df39/Nm/ezI8//ggU3NyZm5uzatUqqU3Xrl15/fo1x44dIzAwkKdP\nn3LkyBH69u3L2bNn+emnn0r71AVBEARBKGX5+fls2bIFIyMjYmJiCq1/d0N57do1nJ2dsba2ZsmS\nJWhoaKCiooKtrS3BwcHUrl37vW9jrV69mqSkJJKSkrhw4YKUXAak5e8+nTp1wtbWVkou37p1i4ED\nB9K5c2dOnTpFQkKC0iTGn376KSEhIZw5c4bz588zffp0goKCpBJmL1++xMrKim3btnHhwgUCAgKY\nN28e3333XYldQ+HDNh28RmDUOZ69yOLZiywCo86y6eC18g5LEARB+IDffqf/9ns8KSlJehgtk8mQ\nyWTUqVNHaX3Lli3x8vKSft69e7e0LwMDA7Zs2aJ0rNjYWBo3bqx0zJ49e7Jr1y7Onz9PfHw8TZo0\nYeTIkaV81kJZK8s+QrETzDExMcyYMUN6gjJw4EAiIyNxdXUlPT29VIIThLIgk8lYtWoVK1euJDU1\nlYiICIYMGUJgYCDR0dGcO3cOgM8++wxvb29iYmI4e/astH1AQAAxMTFcuXJFWlazZk1GjRrFtGnT\npGVTpkwhKCiIrKwsoKDO7tixYwkODsbS0pJPPvmESZMmUbFiRdzd3ZVKagiCIAiC8O90/PhxMjIy\nmD9/PsnJydy4cUNpvUKh4MyZM7i7u+Pm5sbkyZOldTVr1sTFxQUzM7MP1uYv7guJGRkZHDx4kH79\n+knLQkJCsLOzw9nZGU1NTVRVVTE2NpbWV6tWjTp1Cka6vJuEVkNDQ3qbq3nz5ri4uFCzZk0AzM3N\nsbW15cyZM8WKSfh7Nh28xsYDqYWWbzyQKpLMgiAIH4E/UXQAACcnJw4cOCDNAZWWlkZqaioODg5K\n+/r000+lB9J5eXnIZDL09PRKLnCh3JV1H6HYCeaHDx9Kr9hVqFCB169fAwW/vOJVfqGsvftdvHfv\nHt27dy+0/ttvv6Vr164YGRlx+fJlafmZM2cwNzfHycmJHj16MGjQINLT06lTpw4rVqzA3d0dGxsb\nHBwcmDt3LgsXLmTIkCFkZ2cDMGvWLLS1tXF1dSUvLw+A6tWrM3nyZHx8fJT+YPv6+nLw4EEuXboE\nFNRdbtasGWvWrJHauLu7k5iYyA8//MDUqVM5f/48d+/eZdiwYaxatUo6riAIgiAI/06xsbE4ODhg\nYGCAhYVFoVHMhw4dwtvbm0mTJuHp6fmXjjFmzBisrKzo27fvB0cOb9++nerVq9OuXTtp2dmzZ9HS\n0sLV1ZVWrVrRp08fTp48WWhbCwsLmjdvjoeHB7NmzZLm0vi9zMxMkpOTi/WKrfD3JFx6WOSN4zsb\nD6SScOlhGUYkCIIg/BV/Non8IbVq1cLCwoK9e/cCsGXLFnr27ImGhkahtrt378bCwgIzMzNOnDjB\n4sWLSywOoXyVRx+h2AnmatWq8eLFCwD09PS4evUqAE+fPiU3N7dEgxKEv6tp06YsX74cCwuLQq+T\nWlpasnPnTuLi4nj16hUDBgwAoHfv3tjY2ODn58eCBQs4ePAgurq66OvrExgYCEClSpWIiori/v37\nSn98hw8fzt27d6U/4gA6OjqMHz9eaSTSlClTmDNnjpQ41tTUZMSIESxcuBAXFxc0NTWZNm0acrkc\nuVzOrl27Su0aCYIgCIJQuh4/fsyxY8fo2bMnAD169CAuLk7pAfKpU6eoU6eOUtL3z4iKiuLIkSPE\nx8czaNAg/Pz8pImKf0uhUBAbG8tXX32l1Dd69uwZe/bswcfHh1OnTuHm5sbw4cNJS0tT2j4xMZGk\npCQCAgKYOHGidC/wW3l5eYwbN466desq1ZoWSkfY9pQSaSMIgiCUr6FDh2JpaYmlpSXW1tZ/a18y\nmYy+ffsSExNDXl4eO3bsoG/fvkUmsbt3705iYiInTpzAwMCAUaNG/a1jC/8c5dFHKHaC2dzcXOqs\ndu3alcDAQP73v//h4+ODra1tiQYlCH9X48aN0dfX/2AbhUKBoaEhqampUs2iJUuWcODAAY4fP05k\nZCSenp4EBQUREhLCxYsFRdG7du2Kra0tU6ZM4eHDgic+6urqLFy4EF9fX6WbxuHDh3PhwgUSEhIA\nsLa2xtDQkLVr10ptvL292bZtG+np6Xh6erJp0yYyMzPx8vIiPDy8RK+LIAiCIAhlZ+vWrejq6mJl\nZQVAp06dyMrKUnogPX78ePT09HBzc+Pp06d/+hhWVlZoaGigoaFBly5d6Nmzp1ItxndOnz7N/fv3\nC02+p62tTYcOHbCwsEBVVZWePXuir69fZJJaXV2dnj17YmlpSVxcnNK6nJwcfH19efr0KWFhYaiq\nqv7pcxEEQRCE/6LIyEjOnTvHuXPnpNzB39G2bVuePn1KSEgI9evXf+9bR+/UqFGDKVOmkJKSws2b\nN//28YX/pmInmKdOnUrv3r0B8PDwYNiwYbx8+ZLu3bsza9asUgtQEEpaYmIiTk5OfPHFFyQlJREe\nHs7QoUO5f/8+Ojo6REdHM3ToUExMTOjevTvz588nKCiIIUOGSKP1303W5+HhIe23S5cuNG7cmJCQ\nEGnZuxHJEydOlJ4YTp06lcDAQHJycoCCP+YuLi4sX74cf39/8vPzCQ8Pp1evXly6dInr16+X1aUR\nBEEQBKGE5Ofns23bNp4/f07btm2xsbGhc+fO5OXlKZXJ0NTUJCwsjAYNGuDq6sqjR49KJZ7Nmzfz\nxRdfUKtWLaXlcrm8UFuFQvHBms+5ublKEwlmZWUxcuRIMjIyWL16tdI6ofR49TYpkTaCIAjCx0VF\nRYUvv/yS0NBQnJ2di7XNu/yElpZWaYYmlJHy6CMUO8Gso6NDjRo1CjZSUcHDw4OwsDDGjx8vOpHC\nv4qFhQU7d+7k6NGj9OrVi+PHjzNy5EiprnLbtm1xd3fH09OTuXPncuzYMWrVqoWuri4LFiwAoH79\n+kyfPp0jR45w8OBBad8LFy4kMDCQn3/+WVo2aNAgHjx4INVEtLGxoVGjRmzYsEFq4+PjQ3h4OBUr\nVsTe3p6goCA0NDQYPHgwK1euLKMrIwiCIAhCSTl+/DiPHj0iJiaGXbt2SZ+wsDCSk5OVHiBraGiw\nbNkyjI2NcXFxUSpPkZWVRVZWFgqFgpycHLKysqR5IG7cuMHFixfJzs4mJyeHQ4cOERcXR+fOnZVi\nefr0KYcPH1aa3O8dFxcXvvvuO5KSksjPz2fPnj3cvXtXekPx4MGDXL9+ndzcXLKysoiNjeXChQs4\nODgA8Pr1azw8PMjNzSUiIoKKFSuW+LUUimbdrA4ujoUfELzj4ijHulmdMoxIEARBKEnvq81cnJrN\nAwcOZPXq1XTp0qXI7devX8+zZ88AePToETNmzMDc3Fya2Ff4dyuPPsIHE8zp6enSL256evoHP4Lw\nb2Rvb09iYiL+/v7IZDLmzJkDwIwZM/jxxx/Ztm0bq1evxsvLi/nz5xMcHMy1awWzbfr6+lKvXj0G\nDBjA27dvATAyMqJ///5MmzZNOoaamhqzZs0qNIp59uzZ0ohoAwMD2rZty5o1a9llN7cAACAASURB\nVAgKCiI9PZ0jR44wdOhQoqOjpf0LgiAIgvDvEBMTQ4cOHfjss8+oXr269LGxsaFFixbExMQo1UJW\nVVUlODiY1q1b4+Liwq1btwAwMTHBxMSER48eMXHiRExMTAgNDQUK6idPnDiRVq1a0aZNG8LCwggM\nDOSLL75QimX79u3UrVuXNm3aFIqzU6dO+Pn5MXbsWCwsLFi7di3h4eHUq1cPgJ9//plRo0ZhaWlJ\nu3bt2LdvHxERETRp0gQoSECfO3eOCxcuYGVlhampKaampkyfPr00LqvwO/0dDIu8gXTtJKe/g2E5\nRCQIgiCUFJlMVmhOqXfL/4iOjg7W1tbS5H6/3ZdCoSA+Pp5u3bphamqKi4sLtWrVYtmyZSV7AkK5\nKus+gkzxgUcfcrmckydPUr169SJfn5N2IpMVOdHHP9G9e/do3749hw8fpn79+uUdjvAXmZqakpSU\nxL179/D29i6y1iCAu7s748ePx9jYGIAzZ86wZs0awsLCgIKZ3b///ntCQ0O5f/8+5ubmbNu2jTZt\n2nDp0iXs7e05e/YsixcvJj09HSsrKzZv3kx8fDwqKiqcPXuWtm3b4uPjIyWnnz17hlwu5/DhwzRr\n1gwoeE3W0tISf39/vvrqKxQKBXZ2dnh6euLm5gZAQkICrq6u3LhxAyMjI6pWrcrZs2dxdHTE3d1d\naicIgiAIgvAxEP3ykpNw6eH/T9Yjw/vL5lgZixFogiAIQukQ39//LmXVR1D70Mro6Gh0dHSk/xaE\nf4rfPrG7ffs2dnZ20s/+/v6oqakxc+ZMMjIyGDZsGEZGRkRGRgK/1mBWKBTo6OhINcTr1atHREQE\nLi4uJCcn06xZMyZMmMDAgQPZs2cP5ubm9OrVC5lMRkhICKNGjaJly5Y4OzuzaNEivv76awwMDKhW\nrRpTpkzBx8eH7777DplMhoqKCoGBgYwZMwYnJyfU1NSYOnUqI0eOpH///qiqqmJtbU2dOnXYsWMH\n06ZNY9CgQdy9excvLy8WLlwoEsyCIAiCIAhCkayb1RHlMARBEARBKKSs+ggfHMH8Tm5uLnv27KFN\nmzbUrFmz1IMqTeJJi/BHxowZw/3799myZQsKhYL27dvTuXNn2rRpQ58+fdi+fTvdunXj3Llz6Ovr\n8/z5cxo2bIiRkREJCQnIZDJycnIwMTEhKCiIHj16AAWvoXzxxRcMGDCAIUOGoFAoaNOmDaNHj5Zq\nIu7YsYOgoCBOnDhBjRo1cHJyIjIykkaNGnHgwAFpJHZ5Cg0NZe/evaioqKCiosKMGTO4ePEi0dHR\npKWlcfr0aapWrVreYQqCIAiC8A8n+uWCIAiC8O8jvr+FohRrkj81NTWmTJlCdnZ2accjCOVu7ty5\n3Lx5k5UrV6KiokJUVBTBwcFoa2vj4uLCokWLGDduHEOHDkWhUFC1alWWL19OSkqKNCu8uro6Cxcu\nZOzYsWRlZQFINZ6nT5/O27dvkclkTJ06lZkzZ5Kfnw9Ajx49ePbsGWfOnMHb25uYmBhycnL4+uuv\nCQ8PL7drAgVlPs6fP8+xY8fYsWMHcXFxREVFUbt2bczNzYmKiqJu3brlGqMgCIIgCMJ/TcKlBwwM\n2M/AgP0kXHpY3uEIgiAIgvAPUZZ9hGIlmAE+++wzbt68WZqxCMI/gqamJjExMUyePJnLly/TsGFD\nFixYgJubG5MmTSIlJYUGDRrwyy+/sGrVKgDc3NwwNjZm2LBhvHjxAiiYNKdp06YsX75c2re1tTUt\nWrSQJudxdHRES0uL7du3AwUT/Pj6+hIcHMz48ePJz88nNDQUDw8PNmzYwOvXr8vsOigUClLTfmLn\nxdMEHdvF0N2RzNi/mad5b9l79TypaT9RpUoVatWqhZGRkTQZkCAIgiAI5SstLY3Ro0djY2ODqakp\n7dq1Y+TIkeTk5LB9+3bkcrk0GZ+dnR3Tpk0rNKHwq1evCA4OplOnTrRo0QIbGxucnZ2Jjo6WBp2c\nOXMGuVzOwIEDlbbdtWsX9vb2ZXa+/2WbDl4jMOocz15k8exFFoFRZ9l08Fp5hyUIgiCUMHd3dymP\nIJfLuXDhQpHt1q5dS58+fWjRogUODg7v3V9cXBxyuVwpXyF8XMq6j1DsBPPw4cOZN28e+/btIy0t\njfT0dKWPIHxMDA0NmTdvHv369SMzMxM3NzfkcjmzZ88mOjoaHx8f5s+fj7+/P/fv30cmk7Fx40ay\nsrLw8fGR9rNgwQLmzJnDkydPpGWzZ88mKCiIly9fFjmKeeDAgZw6dYonT57g4ODAvHnzaNCgATY2\nNtII6bJw7d4dJl/cz4b7Fzn/5jEvNEDt80b8nP6UKcO/YfC0cWzft6fM4hEEQRAEoXiGDh2Knp4e\n+/fvJykpiZiYGGxtbXlXGe+TTz4hKSmJpKQkVq1axeHDh1mxYoW0/atXr+jfvz/nz59n3rx5nD17\nlhMnTjB16lRu3Lih1K9RUVEhNTWVo0ePlvVp/udtOniNjQdSCy3feCBVJJkFQRA+Qr+di+p99PT0\n8PT0xMvL64PtYmJikMvlbNu2TcpFCB+P8ugjFDvBPGzYMG7duoWvry8dO3akTZs20sfGxqZUghOE\n8pKYmMiZM2cwNjbG19cXmUxGWFgYmzdv5s2bNwwePJilS5cyYsQIvLy8UCgUNGnShG+++Yb169eT\nnJwMFDxZdHNzY8qUKdK+mzVrRseOHVm4cCEAXbt2RVVVlbi4OAAqVaqEt7c3ixYtYu7cuaSnp3Po\n0CG8vLwICwsrs2uQmvEImYrynwiVCuo0GetOfeeOqGlXYs6MmezYsaPMYhIEQRAE4cMyMjL46aef\n6NevH9ra2kDBzaazszMaGhqF2hsYGGBmZsb169elZdHR0aSnpxMREUHz5s2l7T7//HNmzZqlVG9R\nJpPh7e3N/PnzxQ1qGUq49LDIG8d3Nh5IFeUyBEEQ/oMcHR3p2LEjtWrVem+bW7duceHCBYKDg/nl\nl1+Ij48vwwiF0lZefYRiJ5ijo6Pf+4mKiirxwAShPBkbG3PmzBksLS05ePAg27Zto3r16kRGRjJo\n0CC++eYbrl+/zqeffsqdO3fYtGkTAAEBAejq6uLs7CzdZE2bNo0dO3aQkpIi7T8gIIClS5fy9OlT\naRTzjBkzpJFFI0aMICYmhpo1a9KkSRMmTpyIo6Mjjx8/5vz582VyDVIzHhe5XKYiQ9ugAbU7t8ay\nXw8OHDhQJvEIgiAIgvDHdHV1adKkCZMmTWLnzp3cvHmTD83pnZqaSmJiIi1atJCWHT9+HFtbWylB\n/UdcXV3JysoiNjb2b8cvFE/Y9pQSaSMIgiD898TExGBubo6BgQEODg5s3ry5vEMSSlB59RGKnWBu\n1arVBz+C8DHR1NQkNjaWoKAgpk2bhre3N3fv3qVTp05069YNPz8/oqKi+N///se8efPw8fHh8ePH\nVKhQgXXr1nHnzh1CQkKAghu9adOm4ePjI93gNW7cGGdnZ+bMmQNAz549yc/PZ+/evQDUqlWLvn37\nsmLFCmbMmEFSUhJpaWl4enqWyWR/+fn53HheOMGc9eQZWT9nSD/fuH69UO3lD93ECoIgCIJQ+tau\nXUurVq1Yu3YtTk5O2NjYSHUboWD2d0tLS0xMTHBycqJDhw5Kr9JmZGSgp6entM+2bdtiaWlJixYt\n2LVrl9I6dXV1fH19Wb58OW/evCndkxMEQRAE4S/Lyspi165d9OzZEyjIRRw/fpzHj4seYCYIxVXs\nBPM7T548ITk5mXPnzil9BOFj06RJE5YuXcrMmTMZMWIELi4u5ObmSrUIf/zxRzw9PQkJCWHgwIGM\nGjUKgI4dO9K+fXvGjx8v1SgcNmwYT548UbohmzJlCmvWrCEtLQ2ZTMaUKVOURjH7+vqyYsUKOnfu\njLa2NpMnT2bIkCFs2bJFmkiwrOVl5ZC2cT/XgqK4Pm8tb35+xogRI1i7di12dnY8efKEHj16KJUE\nEQRBEAShbOnq6uLj48P27ds5f/48fn5+hISEsG3bNgDq16/PuXPnSEpKIigoiN27dyuVyNDV1eXh\nQ+VXJ+Pj4zl37hy1atUq8mFyly5dqFevHhEREcWqESn8PV69TUqkjSAIgvDf8u2335KZmYmjoyNQ\nMJi0Ro0abNmypZwjE0pKefURip1g/vnnn3F3d6dt27b069cPd3d36TNgwIASD0wQ/gn69++Pvb09\nP/zwAxUrVmTGjBloaWmxbt06Ro0axZAhQ7h79y5NmjQhJSWF7du3A7B69WqgYJIdADU1NRYtWoSf\nnx9ZWVkA1KlTB09PT2bMmAFAr169ePPmjVRywtDQEGtra9avX8+oUaPYsmULVapUoUOHDmzYsKFU\nz1tFRYUmVfUKLa/UQA+DMf0xnDCIpuMG0HP0UKpVq8aAAQM4duwYly9f5vjx48ycObNU4/ut0NBQ\nunXrRo8ePXBycuLixYtMmDCB9u3b4+TkhJOTE6mp768/JAiCIAgfswoVKtCrVy+aNm1KamqqUvJX\nRUUFJycnHB0dpbeqAGxtbTlx4sSffqA9fvx4oqKixCioMmDdrA4ujvL3rndxlGPdrE4ZRiQIgiD8\nG8TGxpKXl0eXLl2wsbGhbdu2ZGRksHXrVjGXwkeivPoIxU4wz5kzh7y8PHbt2kXFihVZu3YtCxcu\nRF9fn8jIyBIPTBD+KRYvXkxqaiodO3YkIiKCo0eP0rJlS4YPH46XlxdRUVFMnDiRoKAgRo4cybNn\nz9DT0yMoKIj9+/dLs6p37NgRIyMjli5dKu17/Pjx7Ny5k+vXr6OiosKUKVMICAiQRgb5+fmxcOFC\nqbzG8uXLGTZsGKGhoaVeikKuWzjB/HuGRSShy1JSUhLHjh1jx44dxMXFERUVRe3atZHJZNK13blz\nJ3L5+/+4CoIgCMLH5MWLFyxYsIAbN26Qk5NDbm4uBw4c4MaNG1hYWBTZfxgxYoTSW4kDBw6kevXq\neHp6kpKSQnZ2Nvn5+Vy9epVXr16999hmZmbY2tqyatWqUjs/4Vf9HQyLvIF07SSnv4NhOUQkCIIg\nlJXs7GyysrKkT3Z2NgB5eXlkZWWRm5uLQqGQ2gHcvHmTCxcuEBISwq5du6TPli1bePr0KceOHSvP\nUxJKUHn0EYqdYD579izjxo3D0NAQmUxGrVq16NKlC2PHjpVqzQrCx6hixYrExsYyf/58pkyZgru7\nO+np6UycOJHnz59z6tQpRo0aRXh4OF9++SW+vr4AjBw5kkaNGuHi4iL9sV+wYAFz586VRva8e4X1\nXUmJr776iufPn3Po0CEAbGxs0NXVJT4+ni5duhAcHMwXX3xBZmYmp0+fLtXzluvWRvGBJ5iK/Hzk\nurVLNYYPyc/P58mTJ1StWhV1dXUAqlatKs2WK2pBC4IgCP9F6urqPHv2jJEjR9KqVStat25NeHg4\nU6ZMwdHREZlMVqiERYMGDXBycpIegmtra7N582bMzc0ZN24clpaW2NraMn36dEaMGCG9VgsU2pef\nnx+vXr0SZTLKSH8HQyYOakk1nQpU09Fk0uCW9OsoksuCIAgfu0GDBmFiYiJ9nJycAFixYgUmJiZM\nnTqVe/fu0bx5c2ki382bN/P555/Trl07qlevLn0MDQ1xdHQkJiamPE9JKGFl3UeQKYqZhTE1NWXP\nnj3Uq1ePdu3asWjRIkxNTUlLS6Nr165cvHix1IIsSffu3aN9+/YcPnyY+vXrl3c4wr/I+vXrmTlz\nJo6Ojty5c4edO3dy48YNWrduzffff8+gQYMYPHgwCxYskGonJycn06pVK8aNGyeVjfD19eXly5dE\nREQA8Pr1awwMDNi7dy9mZmZs2LCB0NBQjh8/TlhYGBs3biQ9PZ1PPvmE48eP880333Dw4EFevHjB\nmTNnqFq1qlKcFy9epF+/fixevBgHB4e/fL4KhYJr9+6QmvGIa88fcz2jICneVFcPw6p6yHVrY1i/\nYZndQP42ntSMx9x4/pi87ByuhW9FJTcfS0tLXPr0pWXLlvj7+3PhwgUqVKiAtbU1Y8eORUNDo0zi\nFARBEASheES/XBAEQRD+fcT3t1CUYo9gbtiwIXfv3gWgcePGxMXFkZuby7fffku1atVKLUBB+Kdw\nc3PDxsaGp0+fcu/ePUJCQmjatCkzZ85kyJAhREZGEhAQwKxZs/Dy8uLFixe0aNECd3d35s+fz507\ndwCYOnUqcXFxJCcnA6ClpcWkSZOYNGkSAM7Ozjx58oTVq1dz7NgxDh48yNu3bxk7diyNGjVi7969\nrFmzhry8PDIyMpRizMvLIzg4GFtb2789glcmkyFv0Ain5laMb9uTiO4eRHT3YHzbnjg1t0LeoFGZ\njk66du8Oky/uZ8P9i5x/85gXGvBaW516Pv3Q+bIt59/+zOgxY9ixYwdjx47lwIEDbN26lV9++UVK\n5guCIAiCIAiCIAiCIAglq9gJ5l69enHjxg0APD092b59O82aNWPRokXSRGaC8LFbtmwZFy9e5Kuv\nviIgIICUlBS8vLyoUaMGO3fuxNfXlzVr1tCxY0fGjx8PwKJFi9DU1MTFxQUoKOMQEBDAN998IyWB\nPT09uXbtGvHx8aipqeHv709ERARVq1alYsWK+Pj4EB4ezuzZs7l8+TLa2tpUrFix0Css69atw9HR\nsVQe+qioqKCiUuw/GSUuNeMRsiKOL1ORoW3QgNpd2tB1sAsHDhygRo0aAGhoaNC7d28uXbpU1uEK\ngiAIgiAIgiAIgiD8J/xhtmju3Lncvn2bgQMHMmDAAABatWrFt99+y+LFi9m5cyeurq6lHqgg/BNU\nqlSJLVu2sHDhQnx9fenXrx9v3rxh9erVhIWFYWtry8uXL/nss8/Ys2cPR48epXLlyqxcuZLExES2\nbdsGgIeHB+np6ezYsQMoqJc4bPRIho0ZyZyjO4nXecvVn25x7lIKbdrZce3WTU6ePImxsTFVqlTB\n398fHR0d1qxZIyWpHz9+zOHDh6VE9sdW+zA1o/CM9FlPnpH186+juC9d/YH69evz888/AwVlNb77\n7juaNm1aZnEKgiAIQklau3YtHTt2VFq2bt065HI58fHx0rK3b9/SrFkzjhw5gr29Pc2bN8fMzAwL\nCws6derE1KlT+emnn5T2866dqakplpaW9O3bl+PHjyu18ff3p127dpibm2Ntbc3o0aO5f/++tN7D\nwwNTU1Pp06JFC+RyuTSfhFB6Ei49YGDAfgYG7Cfh0sPyDkcQBOGjEhoailwuZ+fOnUrL7e3tiYuL\nk35++PAhXbt2ZcyYMdLcS/Hx8XTt2hUTExO6d+/OyZMnizxGamoqxsbGDB48WFqWnZ3N1KlTcXR0\nxMzMjC+++IJ58+ZJ+34nMjKStm3bYmpqyuDBg0lLS5PWPX78GG9vb+zt7ZHL5UrxvnPnzh0GDRqE\nqakpdnZ2rFmz5s9fJOEfryz7Cn+YYN63bx+dO3fG3d2duLg46Ze6bt26ODo6YmgoJpEQ/luMjIwI\nDg5m7dq1tGjRgjFjxlCnTh1WrFjB4MGDWbFiBYGBgUybNg0PDw/evHlDnz59MDMzw8PDg9evX6Om\npsbixYvx8/Pj7du3XLt3h7OfavIgI509Rw/xqpIqTfp15t7r5+h82ZaUvOfUqFGDcePGMXr0aLZv\n346GhgaqqqrSzeXs2bPx8/NDJpOhUCg+qknu8vPzufG8cII5LyuHtI37uRYUxfV5a7mXloa3tzd+\nfn50796dHj168Msvv+Dt7V0OUQuCIAjC39e6dWvS0tJ48OCBtCwhIYEmTZooTfh74cIFFAoFLVu2\nBAr6BRcuXCAxMZHQ0FAAnJycSElJUdr/7NmzSUpK4uTJk5ibmzN69GhevHghrR8yZAj79+/n/Pnz\nHDx4UHrT6p3IyEiSkpKkz6RJk6hatSpt27YtleshFNh08BqBUed49iKLZy+yCIw6y6aD18o7LEEQ\nhI9Cfn4+W7ZswcjIqMiJ794N5rp27RrOzs5YW1uzZMkSNDQ0SEtLY/To0Xh5eXH+/Hk8PT0ZOXKk\n0sNZgNzcXCZOnIiFhYXS4LC8vDx0dXUJCwvj/PnzbNiwgdOnTzNv3jypTVxcHKtXryY8PJyEhAQa\nN27M8OHDyc/PBwrePra1tSU4OJjatWsXGnyWl5eHl5cXBgYGnD59mtDQUCIiIti3b1+JXUOh/JV1\nX+EPE8xHjhwhLCwMHR0dJk6ciK2tLbNmzZLKZQjCf9HAgQNp1aoVMpmM+Ph4YmJi+PLLL2ndujWR\nkZFMmDCB9evX07JlS6ZMmYJMJmPz5s1kZmbi6+sLQPv27WnWrBmLFy8mNeMRKupqGA/oyZW1u1Dk\n59PQ3opXD3/mbXY2tbu0ocvA/ly4cIFBgwahUCh48eIFgwcPJiwsDIArV67g4+ODvb09Bw4cICAg\ngMOHD5fnZSp1lRroYTCmP4YTBtF03ACM3Hugq6tLdHQ0u3fvZvfu3cybN4+KFSuWd6iCIAiC8JcY\nGBhQs2ZNEhISgIKbwsTEREaPHq2UYE5ISKBZs2Zoa2sX2oe+vj4zZszA1NSUoKCgIo/zrqxUZmam\nNO8KQJMmTdDU1AQK3gySyWTo6em9N95NmzbRq1cvMbluKdp08BobD6QWWr7xQKpIMguCIJSA48eP\nk5GRwfz580lOTi6U/1IoFJw5cwZ3d3fc3NyYPHmytG7Hjh0YGxvTvXt31NTU6N69O5999pn09vI7\n4eHhmJiYYGFhoTQ47F2JTH19fWQyGXXr1qVv376cPXtWahMbG0u/fv0wMjJCU1MTX19f0tLSOH/+\nPAA1a9bExcUFMzOzIstcnjt3jocPHzJ27FgqVKjAZ599hrOzM5s3by6R6yeUv/LoK/xhgllVVZV2\n7doREhLC0aNH+frrrzl+/Djdu3enX79+bNu2jbdv35ZKcILwTxYSEkJycjIuLi6MHDmS27dvs3Tp\nUr799lsMDQ3JycnB2NiYjRs3cvr0aRo2bMj//vc/1qxZw+XLlwEIDg4mODiYczcL/uHXsTJBtYI6\naccSycl4QdOu7bi6aS8At++n0ahRI9atWyeNzO3Tpw/79+/nyZMnHD58mCNHjnDkyBE6derE9OnT\nad++fbldn5KkoqJCk6rvv5l9p6muXrnWiRYEQRCE0mBlZSUlmK9cuULNmjX54osvuHv3Lr/88gtQ\nkGBu3br1B/fTuXNnUlJSyMrKkpa9u6nNzMwkNjaWKlWqoK+vr7TdypUrMTMzo2XLljx+/JgZM2YU\nuf9Lly7xww8/4Ozs/JfPVfiwhEsPi7xhfGfjgVRRLkMQBOFvio2NxcHBAQMDAywsLAqNYj506BDe\n3t5MmjQJT09PpXWpqal8/vnnSss+++wzrl37Nal37do1du7ciZ+fX7HePD516hRGRkZK2//2GJUq\nVaJhw4akpr7/++H3MTZq1EhpINbvYxT+vcqrr/CnMjE1atTA09OTAwcOEB0dTf369ZkxYwY2NjYl\nHtiHTJgwAWNjY6V6b5s2bSrTGARBS0uL2NhYQkJCGDx4MP3796dSpUpER0fj5eXFggULWLhwIRMm\nTGDIkCFkZWUxdepUatSoQd++fVEoFDRp0oRBgwaxZUUkUPCqjfHAXlxZH0fumywU955SKSOTqzMj\nuZeWRmBgICtXruTBgweoqKjQt29fmjVr9p+olyTX/eMEs2ExktCCIAiC8G/TunVrabRyQkICVlZW\nqKmpYWpqyunTp3n58iVXr17F2tr6g/vR09MjPz9fSkoDTJs2DUtLS8zMzIiLi2Pt2rVoaWkpbefp\n6cmFCxc4dOgQKioqSiUyfismJoZWrVrRqFGjv3fCwnuFbU8pkTaCIAhC0R4/fsyxY8fo2bMnAD16\n9FAqFwsFCd86derQrl27Qtu/efOGypUrKy2rXLkyr169An4tjTF58uRC37dFiYqK4vz58/j4+EjL\nXr9+XegYOjo6vH79uljnWNT2v41R+Hcrr77CXx7qp6KiIo0ULOtarzKZjF69einVe+vfv3+ZxiAI\nAMbGxsydO5e9e/eio6PD1KlTsbOzw8XFhXnz5jF58mS2bNmCoaEhM2fORF1dnU2bNnHz5k3Cw8MB\nmDRpEvfOXyLjZsHrqLVMDNGqXYNHV67TxMeFKo4teZb3FiP3HiQnJ6OjoyP9+3v79i1Vq1Zl1apV\nODk5YWtry4gRI5gzZw4ODg7leWlKnFy3Nor/rylVFEV+PnLd2mUYkSAIgiCUDSsrK54+fcqtW7c4\nffo0VlZWQMHE26dPn+bMmTNoaGhgamr6wf08fvwYFRUVqlSpIi2bMWMG586dIz4+Hn19fSIjI9+7\nff369fHz82P//v1kZmYqrXv16hV79+6lX79+f+NMBUEQBKF8bd26FV1dXem7tlOnTmRlZbF3716p\nzfjx49HT08PNzY2nT58qba+lpaU0lwHAixcvpIRuZGQkjRo1ws7O7g9jiYqKIjIykujoaGrX/vVe\nV0tLi5cvXxY6RlFlsopS1PYvX74s9vaCUJQ/lWBOT08nMjISR0dH3N3duX37NpMnTy4023Rp+9gm\nMBP+3QYPHoyZmRnVq1dn7dq1HDp0iFmzZnHz5k2qVKmCqqoqzZs3Z+XKlSQlJWFnZ0eXLl3w9fXl\n2bNn6Orq0ulrV1LCY6Tfa+OBTlzdvI/ct9noO9qQcSuNnOSbxMfHs2jRItLT05kxYwapqaksWbIE\nbW1thg8fjqmp6UeXWH7HsH5DZjXvhGu95lho6aGTDTrZYKGlh2u95sxq3gnD+g3LO0xBEARBKHF1\n6tShUaNGfP/99yQnJ9OqVSvg19IZp0+fpmXLlqiqqn5wP/v27cPExIQKFSoUWlezZk2CgoL49ttv\nSUxMfO8+cnNzUVdXL1RjedeuXWhpaX20/ZB/Cq/eJiXSRhAEQSgsPz+fbdu28fz5c9q2bYuNjQ2d\nO3cmLy9PqUyGpqYmYWFhNGjQAFdXVx49eiStk8vl/PDDD0r7/eGHHzA0JlRuoQAAIABJREFUNATg\n5MmTHD16FCsrK6ysrFi1ahXnzp3D2tpaKTEdEhJCVFQU69evx8DAQGl/crmcK1euSD+/fv2aO3fu\nIJfLi3Wecrmcn376Selh8ZUrV4q9vfDPVl59hT9MMCsUCo4dO8aoUaOws7MjPDycNm3asHPnTrZs\n2UKfPn2oVKlSiQf2ITKZjIMHD9KqVSscHR2ZN28eb968KdMYBOEdmUxGaGgoSUlJuLm5MXDgQH75\n5RfWr1/PuHHjmDlzJiEhIfj4+DBkyBBycnJYtWoVMpkMDw8PAFxdXcl585b7Jy4AUK1pI6rLP+Xm\n7iOoaqhj+GVHLu0/RtWqVenQoQMVK1akUqVK6OjoMGHCBLy8vAgJCeH06dN06NChPC9HqZHJZMgb\nNMKpuRXj2/YkorsHEd09GN+2J07NrZA3aFRodlxBEARB+FhYW1sTFRWFvr4+Ojo6QEG9xPT0dPbv\n31+oPMZvB2P89NNPTJs2jeTkZMaPH//eYzRq9H/s3Xlczdn/wPHXbbMv2ZItMzKulKRC2ZdkKRKF\nYsagIXwtUwbZxhZiLEPKnr2QbNmGGcuIpDLW7FvIMskSui3394ev+5u+ljDqWt7Px+M+Hu7nnM/5\nvM996PE5n3PPfZ/KtG/fnl9//RWA5ORkNm7cqFnldPnyZaZNm0arVq1emsx+seFxTpPc4t+xszDG\nw/H1EwAejkrsLIzzMCIhhPh8HDhwgKSkJMLCwti0aZPmFRwczLFjxzh37pymroGBAXPmzMHc3BwP\nDw+uX78OgIuLCydPniQyMhKVSsXmzZs5c+YMHTp0AGD27Nls27ZN03aXLl2wtLRk48aNmlXOU6dO\nJTw8nBUrVrwy7ZS7uzthYWGcOXOGp0+fMnPmTCpWrIi1tbWmTlpaGmlpaajVatLT00lLSyMzMxOA\nOnXqUK5cOWbMmEFaWhqnT59m7dq1sofCZ0JbY4UcJ5ibNm1Knz59uHv3LuPHj+fAgQOMGTNGq99s\ndOvWjR07dhAdHU1gYCAxMTGMHj1aa/EIUbhwYdauXcuSJUto27YtPXr0wNzcnJ9++olRo0bx888/\ns3HjRsqUKUNAQAAlS5Zk+vTpbN26lYMHD1KjVHlqenXi+JJwMlXpAFTp7MjZ9bu4dOM6KhtTzp5J\n4OipEzRo2gSTr7/C39+fH3/8kYiICNq3b8+RI0eoVavWW+Vx+hz8M02PEEII8bmzt7fn3r17mtXL\n8PxeaGtry99///3SBn+jRo2idu3aWFtb06dPH9RqNREREdSqVeuN1/H29iYuLo7o6GgAIiIiaNGi\nBVZWVvTp0wdbW9uXNvk7duwYFy5cwN3d/QP1VrxJ15bVXvng6NlKSdeW1bQQkRBCfB7CwsJo0aIF\nZmZmlCxZUvNq0KABtWrVIiwsLNuiJl1dXaZPn469vT0eHh5cvHiRihUrMmfOHIKCgrC1tWXhwoUE\nBgZSrlw5AEqUKIGRkZHmVbhwYfLly4eRkREKhYIbN26wdOlS7t27R7t27TT7jjk7O2uu6+zszPff\nf88PP/yAnZ0dFy9eZN68edlis7S0xNLSkqSkJPz8/LC0tCQoKAh4Pn4IDg7m/Pnz1K1blz59+uDl\n5UWbNm3y6JMWuU0bYwWFOodcExMnTqRz585UrVo1VwL4EOLj4+nevTvx8fHo6+u/sW5iYiLNmzdn\nz549VKhQIY8iFF+KBQsWMGfOHAoUKEDXrl0ZOHAgzZs3p02bNuzcuZM6deqwaNEi9u3bR/Xq1alR\nowYPHz7k8uXLXEy6QY8ePSj+dQWKNrfh1IPb3F6xg4IlilKjS1tu/BFD8pmLWHRuy6OEK9zedZje\nvXszZswYxo4dy5YtWzA3N2fhwoXa/hiEEEIIIXIk4/J/59CJW//dpEeBd8ea1DOXlctCCCFyn9y/\nPx15OVbQy6nCqFGjcu3iH5rkZRba5uXlxd69e1Gr1UyePJlGjRqxbNkybGxsWL58Od9++y19+/al\nZ8+eHDx4kPXr11OrVi38/f0ZO3YsqxYspk6dOgS4u5NVJD+VvTqz+z8TsezsRJU2jTgXvotMPR2M\nnRpS4r6K8PBwXF1dmTlzJiYmJuzcuZOMjAz09HL80xZCCCGEEJ8wOwtjSYchhBBCiNfKy7HCJ/n7\n8sjISE0uuCtXrjB16lSaNWv20mYjQuQ1hULB/PnziY2NpXPnznTp0oUSJUrwyy+/MGzYMMaNG8f2\n7dsxMDDg119/xczMjF69euHv78+NGzeoUqUKvXv3JmjGbBQ6OhQsU4JKzepyJmwbmQ9TMXVsyJnQ\nbQDolShCUlISAwYMICMjA6VSSfny5dm+fbuWPwUhhBBCCCGEEEII8aX4JCeYQ0NDNbngevXqhZWV\nFZMnT9Z2WEIAUKRIEdauXUtoaCi1atViwIABdO/enW+++YZLly5RqlQprK2tmTRpEhcuXOCXX36h\nYMGCdOnSBYARI0ZwOvoo989fBUDZuTXX98aQevMuen8/Qi/xb85MXExSUhIdOnRg/fr1GBsb89df\nf9GnTx+Cg4O12X0hhBBCCCGEEEII8QX5JH9Hv2LFCm2HIMQb1apVi/HjxxMUFERaWhqrVq0iODgY\nS0tLZs2aRf/+/enRowdeXl7s2bOHpUuX4ubmxqZNm3B2dqa2R3uOzQ+jybSh5C9elCpOTbi4Jwpb\nn+85E7aNR9duUbd7O3ysWlGrVi0WLlyIu7s7derUwdfXl6tXr2JiYqLtj0EIIYQQWta9e3eOHTum\nSZ9VunRpPD09+e6774DnKebWrFnD+vXruXz5Mvnz56dSpUq4urpqdpNXKpWsXr2a2rVrv9T+jRs3\nmDRpEnFxcajVatq0acOIESPkl4W57NCJmwRvOA5AX1dLSZUhhBBfCCsrK82/09PTATR7kSkUCuLi\n4ujevTsxMTGsXLkSGxsbTX0HBwf69etHhw4dSExMpEWLFhQoUCBb+wsWLMDW1jYPeiJyW16PFd64\ngrlOnTokJycDz1dVPn78OFeDEeJz0rdvX5RKJZaWlgwZMoSUlBQWLVrE0KFD+fnnn9m9ezepqaks\nWLAAFxcX7Ozs6NGjB2lpabRxdSHjWRqJ+48C8I2rA0lHT/Hg6k1MnZuSFHsaw8cZVKpUCScnJ86f\nP0+pUqUYM2YM3bp1k43+hBBCCKHRv39/4uPjiY+PZ9q0acyaNYuoqCgA/Pz8CA4Opl+/fkRFRXHo\n0CFGjhzJH3/8kWO7mZmZ9O3bl3LlyrF//342b97MsWPHmDp1am536Yu2ZtdZ/ENiSH6YRvLDNPxD\njrBm11lthyWEECIPvLifx8fH4+LigrOzs+Z9XFycpl7x4sVfuh8rFAoUCkW2Yzt27MjWpkwufx60\nMVZ44wRzWloaT58+BSAiIoK0tLRcDUaIz4lCoWDhwoXExcXh5ORE165dad68OW3atCE6OpqKFSti\nY2PD6NGjuXbtGmvWrOHJkyf4+PhgVqoctfp05sSSDWSmqdAvVIBvOrXk1PJN6BcsgGm7psStjQTA\nx8eHOXPmMGTIEDZv3sy3337L4sWLNd9mCiGEEEK8YGlpSZUqVTh37hxHjx4lIiKCGTNmZFvFVLNm\nzbdKuXX58mXOnz/P4MGDMTAwwMjIiO+++44NGzagUqlyuytfpDW7zrJ6Z8JLx1fvTJBJZiGE+MKo\n1erXlrm7u5OUlMTWrVvzMCLxMdDWWOGNE8zVq1fHz8+POXPmALB48WLmzp37ypcQ4mXFihUjLCyM\nrVu3UrRoUfz8/Jg2bRqHDh3C2dmZ8PBw3N3d6dOnD+XKlWPkyJEsXLgQg+RUStUwxfCbypzb8BsA\npk5NuH/uCn8nXKaKUxPiDxzi4sWLWFpaUqNGDUqVKoWOjg6RkZF88803bNq0Scu9F0IIIcTH4MUD\nqFqt5ujRo1y6dAkrKyv2799P2bJls/189n3bfSEzM5OnT59y5cqVfx23yO7QiVuvfGB8YfXOBA6d\nuJWHEQkhhNCm/12N/E8FChRg4MCBzJgxQxaffUG0OVZ44wTzpEmTKFy4MDt37gRgz549REZGZntt\n3bqVyMjIXAlOiM+BtbU1Y8eO5e7du4SGhnLgwAFWrFjBmDFjGD16NHv37uXmzZssX74cPz8/ypYt\ny9D+A5lg4cgoPz8ub/oDvaQUDBUGtP7eg3uhvxFg78qA/v01m1v6+voye/ZsOnXqxKxZs+jTpw/z\n58/Xcs+FEEII8TEIDg7G1tYWKysrunXrRrt27bCwsCA5OZkyZcq8d7tff/01JiYmzJgxg2fPnnHj\nxg2WL18OIKn1ckHwhr8+SB0hhBCfP4VCQceOHSlUqBDLli17bb22bdtia2uLra0trq6ueRihyA3a\nHCu8cZO/KlWqEBgYCDzf3GPVqlWUKlUqVwIR4nPWv39//vjjD7KysujZsydxcXH07duXyMhIqlat\nSokSJRg6dCgtW7Zk7dq1NGrUiD937qavlxdX+x3lxh8nWRgSQlbbLMzMzEg8e4EhQ4ZQtWpVRo0a\nhYODAwqFgjZt2rBmzRry58/PX3/9xfnz56lataq2uy+EEEIILfL29qZv374A3L59Gx8fH/z8/DAy\nMuL27dvv3a6uri5BQUFMnjyZZs2aUbx4cTp27Mi0adMwNDT8UOELIYQQ4j3o6OgwdOhQfHx86NSp\n0yvrREZGYmRklMeRic/RG1cw/1NCQoJMLgvxnhQKBYsXL+avv/7C3t6e7t27M2LECP7++2/s7OzY\ntm0bbdu2pX///tSrV4/27dszePBgHjx4gJ+fH7t37+bo0aPo6ekxYcIE/Pz8MDQ0pE+fPkyZMgWF\nQoGvry9Lly7VrJj+/vvvWbBggba7LoQQQoiPiJGREa1atWLXrl00atSI27dvc/To0fdu7+uvv2bh\nwoVERUWxbds28ufPj5GREV999dUHjFrA8x3gP0QdIYQQX45GjRphYWEhqW2/ENocK7z1BPPOnTsZ\nMGAAbdu2xcnJif/85z/s2rUrV4IS4nNUvHhxwsLC2L9/PykpKcyePZsVK1Ywffp0hg8fzqFDhzh9\n+jTr169n8eLFAPTq1YsiRYowceJEBg8ejFqtxs3NjfT0dCIiIvjxxx9Zu3Yt169fp0uXLpw5c4Yf\nfviB06dP4+joSEhICM+ePdNyz4UQQgihTf/MkXz37l127NhB9erVsba2pkOHDvj6+rJnzx5SU1NR\nq9WcPHlSs+L5BZVKRVpamub1YhO/c+fOkZqaSkZGBlFRUcybN48hQ4bkaf++FHYWxng4Kl9b7uGo\nxM7COA8jEkIIoU1v2uTvn2U//fQTYWFhJCcn50VYQou0OVZ4qwnmoUOHMmjQIM6fP0/FihWpUKEC\nCQkJDBw4kJ9++ilXAhPic2Rra8vIkSNRqVRMnz6dlJQUxo0bx+rVqzE3N8fa2pqBAweSnp7Or7/+\nyqZNm4iOjqZHjx48e/aM0NBQdHR08Pf3Z9SoURgaGtK7d2+mTp2KgYEBAwcOZN++fZQpU4a5c+di\nZWVFeHi4trsthBBCCC2aN28eVlZWWFlZ4eLiQunSpfnll18AmDx5Mj/88AOBgYHUr18fe3t7Jk6c\nSIsWLbK10aNHDywtLTUvFxcXAHbt2kXz5s2xsbFhypQp+Pn5acrEh9e1ZbVXPjh6tlLStWU1LUQk\nhBBCW960yd8/y5RKJU5OTqSmpr71+eLTpa2xgkL9pq88gNWrV/PLL7/g7++Po6NjtrIdO3YwcuRI\nfHx88PDwyLUgP6TExESaN2/Onj17qFChgrbDEV8gtVqNq6srKpWKhIQEYmNj6dKlCzVr1mTFihU0\nbtwYPT09VqxYgYWFBQ8ePODKlStERUXh6elJQkICBQoUoHHjxvTs2ZPWrVtTvXp1Tpw4QaFChfj6\n668ZOHAgkyZNYvny5QQFBbF//35td1sIIYQQIhsZl7+/Qydu/XeTHgXeHWtSz1xWLgshhMgbcv/+\nNOT1WOGNm/wBrF+/nh9//PGlyWWAVq1a8ffff7N+/fpPZoJZCG1TKBQsWbIEKysrlEol3t7eLF68\nmNq1a/Pjjz+yaNEiMjMziYyMJCIiAjMzMyZPnsyoUaOoV68e06dPZ8yYMUyePBlPT0+6du1Kjx49\nmDZtGrNmzaJHjx48fPgQXV1dTp48yYULFzh16hQ1atTQdteFEEIIIcQHYGdhLOkwhBBCCPFaeT1W\nyDFFxqVLl2jUqNFryxs1asTFixc/aFBCfO4MDQ0JCwsjLi6O2NhYdu3aRWBgoGaiuXbt2nh7e1O6\ndGn69u3LhAkTSEpKIiAggNmzZ5OYmEj9+vUxNzdn/vz5DB06lOXLl5OUlMSgQYNYtmwZrq6uBAUF\n0bNnT+bPn6/tLgshhBBCCCGEEEKIz1COE8w6OjpkZGS8tjw9PR0dnbfeK1AI8V9169Zl2LBh5M+f\nn6FDh2Jubk69evUoVKgQhw4donbt2gwdOpTp06dTqFAhOnfuTOXKlenbty8jRowAYNKkSfj7+1O4\ncGG6devG9OnTMTExwdHRkW+++YYHDx5QuXJlVq1axZMnT7TcYyGEEEIIIYQQQgjxuclxZrhatWrs\n3LnzteW7du1CqXz9DoVCiNf78ccfqVy5MlZWVnTp0oVp06axZ88evLy8OH78ODt27ODAgQOsXLmS\ngwcPEhkZyYgRI/j99985fPgwlpaWNGvWjFmzZjFs2DCWLFnCnTt38PHxYfHixdjY2DBz5kzs7e0J\nCwvTdneFEEKIL05QUBBKpZKNGzdmO96sWTM2b96seX/r1i3atm3LoEGDUKlU3L59G29vb5o1a4ZS\nqcxW938lJCRgbm7O999/rzmmUqkYM2YMjo6O1K5dm6ZNmxIQEIBKpcp27qlTp+jRowe1a9emTp06\neHt7a8qCg4M1mwO+eCmVSiZOnKipc/jwYdzc3LCxsaFhw4ZMnDjxpWuID+/QiZt8N24H343bwaET\nt7QdjhBCiA+ke/fuKJVKtm/fnu34X3/9hVKppFmzZgAMHz4cc3NzrKyssLa2pm3btoSGhmZrx8LC\nAisrK2xsbOjQoQO7du3SlC9fvhw3Nzdq1apFy5Yt86ZzIs9oY5yQ4wRz9+7dmTt3LiEhIaSnp2uO\nq1Qqli5dyty5c+nWrVuuBinE50qhUBASEsK5c+coWLAg/v7+LFu2jIULF1K3bl0sLS3x8vKiUaNG\nNGzYkO7du6Ovr8+kSZMYPHgwarWa8ePHM3v2bPLnz0/Xrl355ZdfsLa2pmrVqjg6OpKQkED79u0J\nDg7WdneFEEKIL0pWVhbr1q2jevXqr/yi98Xu7WfPnqVz587Y2dkxe/ZsDAwM0NHRoWHDhkyfPp2y\nZcu+dqf3jIwM/Pz8sLGxyVYnMzMTQ0NDgoODiY2NZdWqVRw+fJiAgABNnYsXL/Ldd9/RunVroqKi\nOHToEP3799eU9+3bl/j4eM0rIiIChUJB+/btAXjw4AHe3t64urpy9OhR1q9fT3R0NIGBgR/k8xOv\ntmbXWfxDYkh+mEbywzT8Q46wZtdZbYclhBDiA6lSpQrr1q3Ldmzt2rVUqVIl272+Q4cOxMfHExsb\nS79+/fj555+Jjo7WlPfv35/4+Hiio6Np27YtQ4YM4cqVKwAYGRnxww8/0Ldv3zzpk8g72hon5DjB\n3KZNG3r16sWUKVOoW7cuLi4utG/fnrp16zJ16lS+//572rZtm+uBCvG5KlGiBGvWrOHChQuEh4fz\n6NEjunbtypMnTzh27BhVq1Zl5MiRhIWFkZqaiq+vL99++y0ZGRmsXr0aU1NTOnXqxJQpUxg2bBgL\nFy7k3r17+Pr6smXLFsqWLcvmzZtJSkoiLi5O290VQgghvhgHDhzg/v37TJs2jWPHjnH+/Pls5Wq1\nmujoaLp37063bt0YNWqUpqx06dJ4eHhQu3btN6ajmz9/PpaWltjY2KBWqzXHCxQowJAhQ/jqq69Q\nKBSUK1cOd3d3jhw5oqkTGBhI48aN6dy5M/nz50dXVxdzc/PXXissLAwzMzMsLCwAuHbtGk+fPqVT\np07A84fVJk2acPasTHbmljW7zrJ6Z8JLx1fvTJBJZiGE+Ew4ODhw+vRprl+/DsDjx4/57bffcHV1\nzXav/6e2bdtSvHhxzpw581KZrq4uXbt2JTMzUzMWcXR0xMHBgTJlyuReR0Se0+Y44a2SJw8ZMoR1\n69bRsWNHSpcuTZkyZXBzc2Pt2rX4+PjkaoBCfAns7e3x9fWlePHi9O7dG29vby5fvkyXLl1ISEgg\nLCyMc+fOMXbsWIKDg7l06RKzZs1i+PDhpKamMnr0aBYvXoyuri5ubm7MnDmTVq1aoVKpcHV1Zfv2\n7fTo0UM2+xNCCCHy0Nq1a2nZsiWmpqbY2Ni8tIp59+7deHt7M3LkSH744Yd3bv/s2bNs3LgRX1/f\n1z5w/lNUVBTVq1fXvD9y5AiFChXC09OTunXr4ubmxsGDB195rkqlYsOGDXTp0kVzrFq1alSqVInQ\n0FAyMjK4ceMGf/zxBy1atHjnvoicHTpx65UPjS+s3pkg6TKEEOIzkC9fPpydnVm/fj0AkZGR1KlT\nh9KlS2er9+Len5mZyZYtW3jw4EG2L4pflKtUKlatWoW+vr6kuP2MaXuc8Na781lYWDBy5EgWLlzI\nwoUL8fPzo2bNmrkWmBBfGl9fXypVqkTVqlXp3bs3y5YtY9myZdjb22NhYUGvXr0YNGgQxsbGdOjQ\ngfr161O/fn2mTZtG+fLl6d27N+PHj2fEiBEEBweTkpKCj48P586dQ09Pj5SUFNauXcujR4+03VUh\nhBDis3f79m327dunSSfRrl07Nm/enC0/cVRUFMbGxjRp0uSd23+RGmPUqFEUKlQox/ohISHExsYy\nZMgQzbHk5GS2bt3KkCFDiIqKolu3bvTr10+zYuqfduzYQUZGBk5OTppjBgYG+Pv7ExgYiKWlJc2b\nN8fMzAxXV9d37o/IWfCGvz5IHSGEEB83hUKBu7s7GzZsIDMzk7CwMNzc3F76MnnTpk3Y2tpib2/P\n0qVL8ff3x8bGRlMeHByMra0tTZo04Y8//mDOnDlUrFgxr7sj8oi2xwlvPcEshMhdOjo6LF++nKtX\nr/L333+zfft2hg4dSmJiImfPnsXIyIgJEyawYcMGzpw5Q0hICFOnTmXOnDlcv36dYcOGER4eTnp6\nOi4uLsyePRtPT0+OHz9OmzZtWL58Oc2bN2fVqlXa7qoQQgjx2Vu/fj2GhobUq1cPgFatWpGWlkZk\nZKSmzrBhwzAyMqJbt27cu3fvndpftGgRlStXpnHjxjnWDQkJYdGiRSxbtoyyZctqjhcuXJgWLVpg\nY2ODrq4u7du356uvvuLAgQMvtREWFka7du0oUKCA5lhCQgLe3t4EBARw8uRJDh48yKNHjxg+fPg7\n9UUIIYQQ2VWtWpXy5csTGBhISkoKjRo1eqmOi4sLMTExREdHs2HDBjp06JCt3Nvbm5iYGKKioliz\nZs17faEtxNuSCWYhPiKlSpVizZo1JCUlMWvWLOzs7NDR0aF169ZcunSJxYsXA9CxY0cGDBhAyZIl\n6devH8OHD6dkyZIMHjyYMWPG4OfnR2BgIE+fPuU///kPBgYGPHz4EHNzc4KDg9/qZ7RCCCGEeD9Z\nWVmEh4drHggbNGhA69atNauQXsifPz/BwcFUrFgRT09PkpKS3voaBw8eZO/evdSrV4969eqxePFi\nYmJisLOz4+HDh5p6gYGBhISEsHLlSkxNTbO18aqfyarV6pdyPl+4cIHY2Nhs6TFexPD111/TqFEj\nFAoFJUuWxM3NjT/++OOt+yHeXl9Xyw9SRwghxKfB3d2doKAgXF1dX7nZrzzXi3/S9jhBL9daFkK8\nlwYNGjBkyBBWrFhBt27d2Lx5My1atKBZs2YkJSXRs2dP9u7dS2RkJD179mTJkiUolUoOHTrE4MGD\nMTU15dGjR7Rt25Y5c+bQv39/TE1Nsba2JiwsjPT0dKKjozUrqoQQQgjxYR04cICkpCTWr1+PkZGR\n5viZM2fo3bs3586d0xwzMDBgzpw5/PTTT3h4eLBs2TLNz1fT0tKA5w+Q6enppKWloaenh66uLrNn\nzyY9PV3TztKlSzlx4gQzZsygSJEiAEydOpWdO3eyYsWKV/4k1sPDgxEjRhAfH4+lpSXbtm3j2rVr\nNGzYMFu90NBQatWqRbVq1bIdNzMz49dff+XgwYPY29tz//591q5d+8aNAsX7s7MwxsNR+dr8ih6O\nSuwsjPM4KiGEEB/ai4ljJycnjI2NqVGjxr9q51UyMzPJyMggIyMDtVqNSqVCrVaTL1++97qW0D5t\njxNkBbMQH6Fhw4ZRqVIlSpcuzYQJEwgICODUqVNcu3aN/PnzM2fOHAIDA9mwYQMJCQn4+/szePBg\nChYsiJ+fHyNHjsTPz49ff/0VPT09unXrhlKp5OzZs3Ts2FE2+xNCCCFyUVhYGC1atMDMzIySJUtq\nXg0aNKBWrVqEhYVlW4mkq6vL9OnTsbe3x8PDg4sXLwJgaWmJpaUlSUlJ+Pn5YWlpSVBQEAAlSpTA\nyMhI8ypcuDD58uXDyMgIhULBjRs3WLp0Kffu3aNdu3ZYWVlhZWWFs7Oz5rqtWrXC19cXHx8fbGxs\nWL58OfPnz6d8+fKaOs+ePWPz5s0vrV4GsLOzY/jw4Zqcj05OTuTPn58pU6bk1kf7xevashoeji+v\nPPdspaRry2qvOEMIIcSn5sUYwcDAADs7O4oWLao5/qLsn//OqZ1XmTdvHpaWlowZM4bExERq1qxJ\nrVq1PlAPhLZoc5ygUL/HmvqMjAwuX75MVlYWX331FQYGBrkRW65ITEykefPm7NmzhwoVKmg7HCFe\n686dO1hZWZEvXz6GDRvGzp07MTAwYO/evaSnp7N37166devG/fv3uXTpEvXr12fAgAG4u7tTrVo1\nVq5cSVBQEObm5nTu3Jk6depQoEABqlevzpEjR7h8+TKGhoba7qZ9r9JcAAAgAElEQVQQQgghvlAy\nLn9/h07c+u9GPQq8O9aknrmsXBZCCJE35P798dPGOOGdJ5iPHz/OwIEDefbsGZmZmeTLl49p06Zh\nZ2eXWzF+UPKHID4l+/bto1OnTmRmZrJp0yY6d+6MnZ0dN2/eJCMjg9WrV2NmZsa4ceNo2rQpbm5u\nJCQkEB4ezqJFiwgODqZp06ZcunSJnj17AhAREYGrqyv29vYMGjRIyz0UQgghxJdKxuVCCCHEp0fu\n3+JV3jlFxoQJExg3bhyHDx/myJEjeHl58fPPP+dCaEKIxo0bM2jQIEqXLo23tzdz587l6NGj3L59\nG5VKxcaNG+nfvz/jxo3D1NSURo0aERAQQLdu3UhOTubq1as0bdqUoKAgfHx8iI6OxsDAAH19fdns\nTwghhBBCCCGEEEL8azlOMHt5eXH79m3N+0ePHmFtbQ08z+diY2NDSkpK7kUoxBduxIgRVKpUCbVa\nze7du2ndujVKpZKkpCQmT56Ml5cXRYoUwd3dnalTpxIYGEhiYiITJ07Ez88PPz8/fvnlFywsLDAx\nMcHe3p6tW7eiUCg4cOCAtrsnhBBCCCHewaETN/lu3A6+G7eDQyduaTscIYQQQnxEtDVOyHGCuUmT\nJri5uREWFgaAi4sLbm5uTJs2DX9/f7y9vXF1dc31QIX4Uunq6rJy5Uru379PREQEDRs25Pz589St\nW5fKlSvTt29fVq1axf79+zl9+jQDBgxg+PDhuLi4kC9fPs6cOUP9+vWZP38+vr6+3L17l0ePHlG3\nbl2Cg4O13T0hhBBCvKcXG/dZWVlhbm6Oubm55n3t2rUB6N69OxYWFlhZWWFtbU27du3YvHnzS209\nffoUGxsbHBwcXirbsGEDSqUy2/Vq166t+SXUzJkz6dChA+bm5nz//fe52+kv3JpdZ/EPiSH5YRrJ\nD9PwDznCml1ntR2WEEKI/3HixAn69euHnZ0d1tbWODo64u/vz927d/nhhx8YOHBgtvq7d+/G1taW\nmzdv5ng+wPDhwxk1atQrr52QkEDv3r1p0KABSqWS2NjYV8bXqVMnatWqhYODwyvHBuLTo81xQo4T\nzJ6enoSGhvLbb7/Ro0cP2rZty/Dhw8nIyABg9OjRDBs2LNcDFeJLZmRkxMqVK0lPT2fQoEFMmzaN\n6OhoHj58yN27dzl//jxNmzbFw8ODIUOG8OeffxIVFYW/vz+jR49m+PDhTJs2jebNm/P06VMsLCz4\n888/2b59O3fu3NF294QQQgjxHuLj4zUvFxcXnJ2dNe/j4uI09fr37098fDxHjhyhY8eODB8+nIsX\nL2ZrKzIyEkNDQ+7fv09UVNRL1zIxMcl2vbi4OM3u9CYmJgwaNIjOnTvnuKO9eH9rdp1l9c6El46v\n3pkgk8xCCPEROXjwIJ6enlSpUoVNmzYRGxvLypUrMTQ0JCYmBn9/f2JiYoiIiADgzp07jB49mtGj\nR1OuXLkcz4fnGQVed8/V19fH0dFRs6Dsf+s9evQILy8vWrVqRUxMDOPGjWPs2LEcO3YsFz8Vkdu0\nPU54qxzM5cqVY9GiRbRv355vv/2Wq1evMnz4cPz8/F65ykEI8eE1a9aMAQMGUKxYMaZPn84PP/xA\nmTJluHfvHmPHjmXatGk8fvyYsWPHMnnyZAYNGkTTpk01D4S2trYsWbIEHx8fihYtysWLF2natCkh\nISHa7poQQggh/qW32VdBV1cXNzc3srKyuHDhQraysLAwXFxccHBwIDQ09J3ad3V1pUmTJhQvXlz2\nd8glh07ceuVD4wurdyZIugwhhPhIjBs3DmdnZ3x8fChTpgyAZl+lNm3aUKpUKSZOnMjEiRO5fv06\nI0aMwM7Ojnbt2r3V+S+87p5bpUoV3NzcMDc3f2X5rl27KFiwIL1790ZfXx97e3scHBw0mQvEp+dj\nGCe80yZ/HTp0YN26dRw9ehRPT08uX76cW3EJIV5h9OjRmJiYcPPmTdRqNenp6djY2GBsbMzQoUOZ\nMGECgYGB2Nvbo6enx4oVK/D392f8+PH89NNPTJ06FTc3N86ePYuxsTG3bt1iwYIFZGVlabtrQggh\nhPgX3rRy+MUDqEqlYs2aNRgYGFCjRg1NeUJCAidOnKBdu3a4uLjw+++/8/fff+d6zOLtBW/464PU\nEUIIkbsuX77MtWvXcHJyemO95s2b06ZNG9zd3bl06RLjxo17p/P/jYSEBMzMzLIdMzMz4+xZ+TXM\np+pjGCfkOMF85swZOnbsiJWVFV26dOHBgwf8+uuvfP/99/Tu3ZuFCxfKSgUh8oiuri6rVq3iyZMn\nzJs3j4EDBxIbG0taWhqXLl2iRIkSVKhQgQ4dOjBr1iz8/PwwMzOjTp06HDp0iFq1arFmzRr69+9P\nlSpViImJoWDBguzZs0fbXRNCCCFELgkODsbW1pZatWrx66+/Mn/+fCpUqKApDw0NxcrKiooVK1K3\nbl1Kly5NeHh4tjYSExOxtbXVvCZNmpTX3RBCCCE+esnJycDzNJc5qVu3Lvfv38fBwYEiRYq88/nv\n68mTJxQuXDjbsSJFivD48eNcu6b4/OU4wezn54eNjQ3r16+nVatW/PzzzwA4ODiwYcMGLl26hLu7\ne27HKYT4L2NjY1auXImOjg7Dhw/H19eXfPnykZKSwrBhw1iwYAEnT57k3LlzNG3alClTpjBx4kQC\nAgIYMmQIU6ZMoVevXhw/fpx8+fJRtmxZ2exPCCGE+Ix5e3sTExPD4cOHadSoEYGBgZqyJ0+esGXL\nFpydnTXHnJycWLt2bbY2KlSoQExMjOY1cuTIPItfQF9Xyw9SRwghRO4qUaIEALdv335jvTt37jBx\n4kS8vLwICwvj5MmT73T+v1GoUCEePXqU7dijR49emnQWn46PYZyQ4wTzlStX8PDwoEqVKnTr1o0b\nN25oyooVK8bkyZMZPHhwrgYphMiuRYsWeHt7o6enx8GDBylfvjwWFhaUKlWKOXPm4O7ujre3N2PH\njiUoKIiCBQvSpk0b9u7di5mZGZGRkXh4eGBmZsbhw4f5/fffNbvVCiGEEOLzVLRoUSZOnMi5c+c0\nu8VHRkaSmprK7NmzadCgAQ0aNCAsLIzExET+/PPPd2pfNvjLPXYWxng4Kl9b7uGoxM7COA8jEkII\n8SpfffUVJiYmbN269bV11Go1I0aMoGHDhvj4+ODl5cXQoUNJS0t7q/NfeN/7rlKp5MyZM9mOnTp1\nCqXy9fcZ8XH7GMYJOU4w161bl9GjRxMWFoavry9WVlYv1alfv36uBCeEeL2xY8diYmJCbGwsjRs3\nJiEhgczMTOLj42nVqhUKhYLRo0czcOBAfvrpJ37++WfmzZvHgAED8Pf3Z8CAAVy6dInU1FSsra1Z\nsmSJtrskhBBCiPf0ppR1/ywrVqwYPXr0IDAwkMzMTMLCwmjXrh3btm1j06ZNbNq0iW3btmFvb//S\nKubXycjIIC0tjfT0dLKyslCpVKhUqn/dJ5Fd15bVXvnw6NlKSdeW1bQQkRBCiFcZO3YsW7ZsYebM\nmdy5cweAe/fuMX/+fLZt28aKFSu4fPkyY8eOBZ7/0qho0aIEBAS81fnw/N6ekZGBSqUiLS1N83oh\nLS2NZ8+eAWjqvNh7ycHBgadPn7J48WJUKhVRUVHs3r2bzp07580HJHKFtscJOU4wT5kyBTMzM/bs\n2UOlSpU0iceFENqlp6fHmjVrSE9PJyAgAF9fXzIyMkhNTcXX15eAgADWrVuHg4MDhw8f5vr163h6\nevLbb79hamrK4cOHady4Maamppw/f54FCxaQmZmp7W4JIYQQ4j28aRXT/5Z9++23pKSksGLFCk6d\nOkXv3r0pWbKk5lWqVCl69erF77//zr1791AoFG9sf9SoUVhaWjJ//nyio6OpWbMmrVu3/mB9E/+v\na8tq+PWoQ4mi+ShRND8jv69DFweZXBZCiI+Jvb09q1ev5sKFCzg7O1O7dm08PT25f/8+xsbGzJw5\nk4CAAE1KCl1dXQICAoiIiODgwYNvPL9u3brA83t7REQENWvWxNLSEktLS2rVqsXx48dJTEzUvFco\nFPTo0QNLS0vNr5eKFCnCggUL2LFjB7a2towdO5bx48djaSmplj512hwnKNRf2A59iYmJNG/enD17\n9mTb3ESIT9XOnTvp2rUrJUuWxMbGhkuXLnH37l1sbW05f/48f//9N5MnT+aXX35h69atmJubExQU\nxIgRI1i6dCmenp7cuHEDCwsLJk2alKu71QohhBBCvCDjciGEEOLTI/dv8So5rmB+neTkZDIyMj5k\nLEKI9+Do6Ejfvn1JTU3lzp07JCcno6enx9GjR3FxceHx48fMmDGDx48fExERgbe3N9u3b6d8+fJM\nnjyZIkWK8PXXX5Oeni6b/QkhhBBCCCGEEEKId5LjBPP69euz5XFZsGABtra22NvbY2Njw9SpUzV5\nXIQQ2vHzzz9Tvnx5Ll++TOfOnXnw4AH37t1j3rx5ODk5cfr0aUqWLMnEiRPp06cPkZGRmJqacvHi\nRcaPHw+gyb109epVLfdGCCGEEEIIIYQQQnwq9HKqMGrUKJo2bUq+fPlYt24dc+fOxdvbG0tLS06d\nOsW8efMwMTGhS5cueRGvEILnCf3PJl4l4X4SCfdvcz7lNiWb2XA7dBszZ8+mdds2nD11mpSUFAAK\nFy5MSkoKTZo0ISgoCF9fX7Zv306BAgV49uwZarUatVqNiYkJixYtYsKECVruoRBCCCE+pBMnThAU\nFER8fDwqlYpSpUrRuHFjvLy8KF26NFeuXGHu3LkcPnyY1NRUSpYsSZ06dejTpw8mJibMmTOHuLg4\nli5d+lLb0dHRfPfddxQoUEBzTKlUsmbNmrzs4hfh0ImbBG84DkBfV8tc3xFeCCFE7rKystL8Oz09\nHQB9fX3geZ7luLg4unfvTkxMDCtXrsTGxkZT38HBgX79+tGhQwcSExNp0aIF+/btw8jIiA0bNuDn\n56e5NxcvXhwHBwd8fX0xMDAgISGB6dOnk5CQwL1791i1ahXW1tZ52HORG7Q5TninFBnr1q1jwIAB\neHt7Y29vj5eXF76+voSFheVWfEK8k6CgIJycnGjXrh0uLi4cP36cffv20b59e1xcXPDw8ODatWva\nDvNfO5t4lVHHd7DqxnFin9zmoQEUsjOniHFpypQuTXTsUZ6mPUNfX5+tW7fi4+PDs2fPaN68OQsW\nLMDJyYnz589TokQJJkyYQIECBdDR0eH8+fMsXrxYc2MTQgghxKfv4MGDeHp6UqVKFTZt2kRsbCwr\nV67E0NCQmJgYzp49S8eOHTEwMCA0NJT4+HjCw8OpUaMG+/fvf6tr6OrqEh8fr3nJ5PKHt2bXWfxD\nYkh+mEbywzT8Q46wZtdZbYclhBDiX/jnvdPFxQVnZ2fN+7i4OE294sWLM3Xq1Gzn5rQJb6VKlTRt\nBQUFsXXrVk1aTH19fRwdHTXv39SO+DRoe5zwThPM169fp2HDhtmO1a9fX35SL7QuKyuL2NhY9u3b\nR0REBJs3byYkJISyZcsybtw4Zs6cycaNG3FyciIoKEjb4f5rCfeTUOhk//PVyadP9dFeGHxTAdWT\np+jr6fPs2TPS09P59ddfyZ8/P8OHD2fgwIGMGTMGBwcHHj16hKGhIV5eXgA8e/aMokWLanaXFUII\nIcSnb9y4cTg7O+Pj40OZMmUAKF26NN7e3rRp04bJkydjYWGBv7+/ZrOeYsWK4enpSffu3bUZuviv\nNbvOsnpnwkvHV+9MkElmIYT4TKjV6teWubu7k5SUxNatW9+rbaVSiY2NDWfOnAGgSpUquLm5YW5u\n/l7tiY/LxzBOeKsJ5lOnTvHXX3+RP39+VCpVtrKMjIw3/hEIkRvUajUJ16+w8fhhpuzbhNeWRYzf\nEcq9zGdEnokl4foVihUrRpkyZShdujSPHz8G4NGjR5oHq09Zwv3brzyu0FFg3r8r6YUMuH3nNiYm\nJpQpU4bMzEz09PR4/Pgxd+/eJSYmhgcPHvDgwQPat2/PokWLMDY2pnz58qSkpDB//vz3ju1Vq8gB\nZs6ciaOjI23atGHFihXv3b4QQggh3t7ly5e5du0aTk5Oryx/+vQpMTExry1/W5mZmTRp0oQGDRrQ\np08fEhJefsgR7+fQiVuvfGh8YfXOBA6duJWHEQkhhMgNb1pFXKBAAQYOHMiMGTPe+RfHarWa06dP\nExMTg4WFxb8NU3xkPpZxQo45mAF++OEHzb/j4uKwtLTUvD9z5oxmpYMQeeVFigjNKl4D0KtRmbt7\nDjG632AKf1MJ347d6djWmdGjR9OrVy/y589P4cKFP/mULllZWZxPuQ0G2Y+n3UkGhYJ8pQ2xG9mX\no8Nnc/PmTcqWLYtKpeLJkyd069aNoKAgZs+ezbx582jatCkbN25ET0+PJ0+e8ODBAx4+fEhsbCwX\nLlzA1NT0neKKj4/XrCLX19cnJSUFlUpFeHg4t2/fZufOnQAkJyd/yI9ECCGEEK/x4p5rZGT0yvKH\nDx+SmZn52vK38SL1RtWqVUlNTWXhwoV89913bNmy5bP4Yl/bgjf89VZ1JB+zEEJ8vhQKBR07dmT5\n8uUsW7aM3r1753hOYmIitra2KBQKDA0N6dSpU7b5PfF5+FjGCTlOMO/evTvb+0KFCmV7n5GRQa9e\nvT5sVELk4HUpIqr6dCf1UiKPz19n8vgJ8EzFkiVLWLhwITVr1mTx4sVMmTKFiRMnainy3JOZls7N\nDb+T+TQNhY4OxtVNuRx7nJIlS2JgYICOjg779u2jcuXKLFiwgGLFinH9+nUePHhAkSJFePr0KW5u\nbmzYsIHChQuzYMECAgICXnu9V200eO/keVL/u4pcaViWahVMUCgUhIaGMmPGDM25JUqUyIuPRAgh\nhPjivbjn3r59m6+//vql8qJFi6Krq0tSUtJ7X6NUqVKUKlUKgCJFivDjjz+yc+dO9u/fT6dOnd67\nXSGEEEL8Px0dHYYOHYqPj89b3V8rVKjArl278iAyId4iRUaFChWyvQwNDbOVd+jQARcXl1wLUIhX\neVOKiMKmFSnb2h7bLu3Yvn07KpWKmjVrAtC6dWvi4+PzMtQPTkdHh6rFX15lVLCiEaaDulJteA++\n+elbuv7sS8+ePbl8+TI2NjakpqaSnJyMvb09J0+epFWrVhw7dowJEybw5MkTdHV1sbKyIiMjg8TE\nRJYsWUJaWtpr43jVRoN6NSpz9+97jO43mO/H/sSGbc/zQ127do3IyEg6duyIl5eX5G0XQggh8shX\nX32FiYnJa3M2FihQgDp16hAZGflBryubBX04fV0tP0gdIYQQn75GjRphYWHB3LlztR2K+Eh8LOOE\nd9rk759CQkJISUn5kLEI8VY0KSL+R9qdZNLu3te8P3/uHBUqVODZs2dcuXIFeL6LepUqVfIq1Fyj\nNMz5Z6zVihsxdepUzUNl1apVyZcvHxs3bqRly5YEBATg4OBATEwMhoaGNG7cmCVLltCoUSMMDAwo\nWLAg4eHhr23/TavIK3R2QK9wQSaPn8CGDRtQqVTkz5+f8PBw3N3d8fPz+9efgRBCCCHeztixY9my\nZQszZ87kzp07ANy7d4/58+ezbds2hg8fzsmTJxk1ahSJiYmo1WoePnzImjVrWL58uaadrKwsVCoV\naWlpmpdarebw4cNcvXqVrKwsUlNTmTNnDsnJyS9tDi7ej52FMR6OyteWezgqJT2GEEJ8Bt60v9k/\ny3766SfCwsL+derJtLQ0nj17BqC5v2dlZf2rNkXe+1jGCW+Vg/lVpk2bRoMGDShevPiHjEeI9/a/\nKSIKlSzOwEmzaNasGYMHD0atVlOsWDH8/f21Heq/pjQsi/r6sZcmeF9QZ2WhNCyLgYEBGzduxNLS\nkvPnz6NSqcjIyODcuXPA87yLkZGRBAYGMmLECAoWLEiDBg34888/uXv3LvPnz8fDw+OV18hpFXlh\n04qU+sqUXbt2YWxsjIODAwAtWrRgxIgRH+BTEEIIIcTbsLe3Z/Xq1QQFBeHs7Ex6ejqlS5emadOm\ndOrUiZIlS7J+/Xrmzp1Lly5dSE1NpUSJEtjb22tyNSoUCqKjozW/CnthxowZ3LlzBz8/P+7fv0+B\nAgWoUaMGS5Ys+Vd5nUV2XVtWA3hpEx/PVkq6OFTTRkhCCCE+sDf9+uefZUqlEicnJzZu3PjaOgqF\n4o3tJSYm0qJFC03dHj16ADBlyhTJUvAJ+hjGCQr1m74iAWrWrIlCoXjpmxSVSoW+vr7mP+1ff+Wc\nVPpjkJiYSPPmzdmzZ49sTvgJm7JvE7FPXj3B+YJNISOGNWqfRxHlrX/mPz6bcptz/53s/cbQiGrF\njbLlPwbYuHEj3bt3x8rKitOnT2t2et+8eTP9+vXjxo0bPHv2DGNjY06cOKHZsK9o0aIcPHgQMzOz\nbNfPysrCa8siHr5ho0GA+5v/pJGxKYULF8bExISOHTsSHR3N9OnTWbduXe5/UEIIIYT4aMm4/N0d\nOnHrv5v5KPDuWJN65rJyWQghRN6S+/fHS5vjhBxXMOvo6FCvXj0cHR2zTTKPGjWK/v37y87QQiuU\nhkY5TjBXe0We4s+FQqFAWbEyyoqVATQ/Y9F5zYpmFxcXvv32W5YvX46NjQ2nT5/mt99+o1q1amze\nvBmFQoGfnx9jx46lePHiuLq6cvHiRQDmz5/P7Nmz3yquV60iHzBpAPr6+vj6+hISEkKhQoU+y00W\nhRBCCCFym52FsaTDEEIIIcQraXOckOMEc3h4OIMHDyYuLo6RI0eSP39+AEaPHk2LFi0wNTXN9SCF\n+F9vmyLiS/G6ieV/mjlzJnv37uXIkSMUL16czMxM0tPTSUxMxMPDg3nz5tGwYUMUCgW///47hQoV\n4saNGyxbtozJkydTsGDBbNerWvzlSf4XGw2+YFPISLN7/fz58z9Qb4UQQgghhBBCCCHExyLHWakq\nVaqwfv16FAoFrq6uJCQk5HSKELmuWgUTJtZshWf5mtgUMqKoCoqqnk9oepavycSarahWwUTbYX5U\nDAwM2LJlCzo6Oujr66Ovr09SUhJ2dnaEhoZSsGBBLCws2LNnD3fv3sXFxYUiRYqgp6fH2rVrX2rv\nbTcaFEIIIYQQQgghhBCfr5yXPQL58uVj/Pjx/Oc//6Fnz56EhITkclhCvNmLFBEuNesxrFF7Fjr3\nZqFzb4Y1ao9LzXooK1Z+Y0L7L9XXX3/N0qVLuXv3LtWqVcPAwIC4uDiKFClCRkYGgYGBODk5oVQq\nOXbsGADJyckEBga+1JbSsCzqN+ww+6WtIhdCCCHeRffu3bGwsMDKygorKytatmzJsmXLNOVqtZrV\nq1fj6uqKlZUVdnZ2dO7cmbCwME0dpVJJXFzcS22rVCrGjBmDo6MjtWvXpmnTpgQEBKBSqV6qu3nz\nZpRKJXPnzn2pLDIyEg8PD6ytralRo8ZL5XPmzMHMzEzThwYNGjBmzBjS0tLe92MRr3HoxE2+G7eD\n78bt4NCJW9oORwghxH9dv36dgQMH0qBBA6ysrGjSpAkDBgwgPT1dU0etVuPo6Ii1tTVPnjzJdn50\ndLRm077/1bt3b5RKJREREcDz3MdKpRIrKytq165NnTp1cHV1Zc6cOTx+/DjbuUeOHMHd3R1ra2ua\nNWvGqlWrspU3a9aMzZs3f6iPQXwktDleeKsJ5hdat25NWFgYkZGRZGZm5lZMQrwzHR2dt0oTIaBT\np0507dqVU6dOUaRIEbKysihRogQxMTFYWVmRP39+oqKiSExMxNnZGX19fc6cOUN8fHy2dmQVuRBC\nCPHv9O/fn/j4eOLj45k2bRqzZs0iKioKAD8/P4KDg+nXrx9RUVEcOnSIkSNH8scff+TYbmZmJoaG\nhgQHBxMbG8uqVas4fPgwAQEBL9UNCwtDqVQSHh6u2dPhhWLFitGtWzf8/Pxee6169epp+hAeHs6x\nY8eYN2/eO34S4k3W7DqLf0gMyQ/TSH6Yhn/IEdbsOqvtsIQQQgBeXl4YGRmxY8cO4uPjCQsLo2HD\nhtn2MDt8+DD37t2jRIkSREZGvtSGrq4uGRkZ2b40vnnzJidOnMDIyOilxXM7duwgLi6OQ4cOMXr0\naA4fPkzHjh1JSUkBnk9E9+nThx49ehAbG8vMmTP55Zdf2LlzZ7Z2ZFHe50Xb44UcczD/r4oVKxIa\nGkpqaipFihTJjZiEELksMDCQ/fv3c+vWLXR1dbl58ybffPMNR44cISYmhg4dOnDp0iWuXr2Kjo4O\nKpWK4ODgbHmU33WjQSGEEEK8nqWlJVWqVOHcuXMYGBgQERHBypUrsbGx0dSpWbMmwcHBObZVoEAB\nhgwZonlfrlw53N3dWb16dbZ6Fy9eJC4uji1btuDu7s7+/ftp0qSJprxBgwbA89VVr/PPB2gjIyPq\n16/PuXPncoxRvJ01u86yeufLKQpfHOvaslpehySEEOK/7t+/z5UrVwgMDKRw4cLA83th586ds9UL\nCwvD0dGRcuXKERoaipub20ttubm5sW7dOmrXrg3A+vXradu2LX/++edrr6+rq4uVlRXz5s2jdevW\nLF26lCFDhrBv3z6++uor2rRpAzwfYzg6OrJ69WocHR0/VPfFR+RjGC+810yQrq4uRYsWlW87hPhE\n5cuXj23btpGVlUXp0qXR1dXl6tWrPHr0CKVSya1btzhx4gRXrlyhcePGZGRksHLlSh49evTaNmUV\nuRBCCPFuXkzOqtVqjh49yqVLl7CysmL//v2ULVs22+TyvxUVFUX16tWzHQsLC8Pa2hpTU1NatmxJ\naGjov7rGjRs3+PPPPz9o3F+yQyduvfJh8YXVOxMkXYYQQmiRoaEhVatWZeTIkWzcuJELFy5k++IV\nnqec3LNnD+3ataN9+/acOnWKU6dOvdRWhw4d2L17N48fPyYzM5MNGzbg7u7+VnEUK1YMe3t7Dh8+\nrDn2v79KysrKkj3VPlMfy3jhX88GDRs2jG+//fZDxCKEyOa6DsoAACAASURBVEOmpqYsWrSI27dv\nU7JkSdRqNWXLliUqKoqTJ0/i5ORE+fLlefToEQYGBppckEIIIYT4MIKDg7G1tcXKyopu3brRrl07\nLCwsSE5OpkyZMh/sOiEhIcTGxmZb1ZyWlsamTZto3749AO3bt+fA/7F353E5pf0Dxz93KSJLhUiR\nbbotIUpF9iFjSYXGbrKHsc4w0/AYWxg7NQxmxtRYKlIIZfJYH1SyPb8wljFkCY8SJq337w9P9+Oe\nFqFNvu/Xq9erznXOdb7nfo0517nu63y/x44RHx//Rn1HRUVhY2NDq1at6NKlCxUqVMDV1bXAYv+Q\nrQ86XyD7CCGEKDy+vr7Y2tri6+uLs7MzDg4OrFu3Tt2+c+dOjIyMsLOzw8zMjJYtW2rUU8hiaGiI\nvb09ISEhHD16lGrVqqFUKvMdh7GxsTpFRps2bbh+/TohISGkp6cTHR3NwYMHef78+btfsChxSsp4\n4Z0nmFUqVbZvaIQQ74eBAwfSt29f7t27R5kyZXjw4AGGhoZoa2sTHR3NzZs3uXHjBo0aNSI5OZkV\nK1bIv3chhBCigHh4eBAVFcW5c+c4cuQI165dw9PTEyMjozee6M3N5s2b2bRpE7/88gs1avyv+O7+\n/ftJTk5Wvypra2tL1apVCQwMfKP+W7duTVRUFGfOnOHMmTNYWloycODAHAsKCiGEEKWNgYEBU6dO\nJSgoiDNnzvDFF1/g4+PDzp07UalUBAYG0rNnT/X+Tk5O7N27N8fJXjc3NwICAggMDMz36uUs9+/f\nx8DAAIC6devi7e2Nr68vbdu2ZfXq1fTt25cqVaq828UKkYd3nmD+7rvv8PPzK4hYhBDFYNOmTZiY\nmKhTXDx79oybN2+SmZlJhw4dqFq1Krq6uujq6vLnn38SGRlZ3CELIYQQpY6xsTHdu3cnPDyc9u3b\nEx8fT3R09Dv16ePjw+bNm/n1119p0KCBRltAQAAZGRn06NEDBwcH2rdvT0JCAjt27Mj2Wm1eXv3i\nuUKFCvTv35+bN29y7dq1d4pdwDjX5gWyjxBCiKJRtmxZXFxc+Oijj7h8+TKnTp3i1q1bBAQE4ODg\ngIODA6tWreKvv/5i79692Y5v27Ytz549IzIykl69euX7vE+ePOFf//oXtra26m0dOnRg586dnD59\nGj8/P+Lj4zXaRelRUsYLkjBViA9cuXLlCA8PJz09nYoVK5KRkUHVqlX5448/OHz4MAkJCVy/fp1q\n1aqRkpLC2rVriztkIYQQolR4dXL24cOHHDhwgEaNGtGqVStcXFz44osviIiI4Pnz56hUKv79738z\nbtw4jT5SU1NJSUlR/2StHF6yZAk7d+7Ez88Pc3NzjWOuXbtGTEwMPj4+hISEqH8CAwN59OgRR44c\nAV7ma0xJSSEtLU3jXLlJTk5mx44dlC9fntq1axfER/RBs7esySDH3F+PHuSoxN6yZhFGJIQQ4lVJ\nSUksX76cq1evkpaWRnp6OmFhYVy9ehVra2u2b9+OjY0NBw4cUN9r9+7di6ura45pMhQKBRs2bMDX\n1xc9Pb3Xnj89PZ1z584xceJEKlasiLu7u7rtwoULpKWlkZyczNatWzl+/Djjx4/XOD4tLS3HMYR4\nv5SU8UKZ/O74/Plz9PT0shXxSktL49y5c9jY2BR4cEKIotGwYUPWr1/P6NGj0dXV5cmTJ2hpaVGp\nUiXq16/P9evXqVSpEvHx8QQGBrJ27Vr16zdCCCGEeDvff/89GzZsAKB8+fK0bt2amTNnArBo0SK2\nbt2Kj48P06dPR09Pjzp16tCvXz+NPj777DONv+vVq8emTZv4+eef0dXVxcnJSd1mamrKnj172L59\nO02aNKFjx44axxoZGeHo6Ii/vz+dOnUiODgYT09P4OVDb7NmzVAoFERERGBiYoJCoSAyMhIrKysA\ndHR0sLCwYMOGDejr6xfkR/XByqr6/vfiPYO7KxnQtfArwgshhMidjo4Ojx8/ZuLEiTx8+JAyZcpg\namrK7NmzsbGxYfr06Xh7e2NkZKRx3OjRo+nZs6e62J9CoVC31a9f/7Xn7d69OwqFAm1tbczMzOjY\nsSMjRozQuPd6e3sTExNDRkYGLVq0wM/PL1vfnp6e6vs8vFyBff685PZ/H5WE8YJC9ZqEqklJSUyb\nNo0TJ05QtmxZ3Nzc+PLLL9HR0QFerrZo3749ly5dKpKA31VcXBxdunQhIiICU1PT4g5HiBKlX79+\n7N69G5VKhUKhIC0tjcqVK2NoaEhiYiKpqanqXMyTJ08u7nCFEEII8R6TcXn+nbx4778FehR49G2G\nXVNZuSyEEKJ4yP275CrO8cJrVzCvWbOGuLg4fHx8SEpKYs2aNVy/fp1169ahq6sLIEW/hCgl/Pz8\naNiwIYmJiSQnJ6Ovr4+WlhZGRkakpqZiYmJCbGwsS5YsYdKkSRrftAohhBBCiMJhb1lT0mEIIYQQ\nIk/FOV54bQ7mQ4cOMWfOHDp37oyzszM7duwgMTERDw8Pyc8iRCmjp6fHwYMHSUtLo2zZsiQnJ5OQ\nkMCNGzfQ09Pj1q1baGtr8+DBA44fP17c4QohhBBCCCGEEEKIYvbaCeb//Oc/GkveDQ0N+fnnn0lI\nSGDChAnqoh9CiNKhUaNGrF69mtTUVFQqFWXKlOHJkyekpKSgq6uLmZkZGRkZeHl5FXeoQgghhBAf\nhJMX7zJ87gGGzz3AyYv3ijscIYQQQpQwxT1WeO0Es7GxMTdv3tTYVqlSJX788Ufu37/PtGnT5DV5\nIUqZcePGqQsHpKeno1AoePr0KQYGBjx48AAtLS0OHjzIw4cPiztUIYQQ4oO3bt06lEolwcHBGts7\nd+5Ms2bNsLKywsbGBjc3N44dO5Ztn927d+fY71dffUXTpk2xsrJS/2zbtk1jnwcPHqjfdrSysqJT\np05MmTJFXbhIvLtt4Vfw2hzF46QUHiel4LU5km3hV4o7LCGEKNXyure+et+8d+8ePXv2ZPLkyaSm\nphIfH4+HhwedO3dGqVRmu8dGR0dr3FetrKxo3LixRlHe5ORkvv76a2xsbLCxseGbb74hJSUlxzin\nTJmCUqkkJiZGY/vRo0fp2bMnzZs3p3fv3pw4cUKjPTIyEjc3N1q1akXnzp3ZsmXLW31OomQoCWOF\n104w29rasmfPnmzbDQwM+Pnnn0lMTJQczEKUQgEBARgaGqKrq0t6ejqJiYnEx8ejra1N1apVycjI\nYN26dcUdphBCCPFBy8zMJDAwkEaNGuHv75+tfeHChZw9e5YTJ07QqlUrJk2aRFJSksY+uS0WUSgU\nuLi4cPbsWfXPwIED1e3x8fH069eP+Ph4Nm7cSExMDKGhoXTu3JmDBw8W7IV+oLaFX8lWER5eVomX\nSWYhhCgcr7u3Zt03r1y5wqeffoq9vT2rV69GV1cXLS0t2rVrx7Jly6hRo0a2e6y1tbXGfTUmJoYa\nNWrQp08f9T4LFy7k5s2bhIWFERYWxvXr11m0aFG2OMLDw3ny5Em27bdv32bSpEmMGzeOM2fOMGbM\nGCZOnMidO3eAl0X6xo4dy2effcaZM2dYuXIly5cvJyws7J0+N1E8SspY4bUTzB4eHjg7O+fYVrVq\nVX755Rd5VV6IUqh8+fJERESQmZmJQqFAS0uL1NRUjIyMSEpKQqFQsGzZMjIzM4s7VCGEEOKDdezY\nMRISEli6dCnnzp3j6tWrOe6nq6uLq6srycnJ3Lp1K199q1SqPBeSrFmzhgoVKuDj40P9+vVRKBSU\nL18eJycnpkyZ8lbXI/7n5MV7OT4wZtkadlnSZQghRCF43b1VpVJx+vRphg4dypAhQ5g1a5a6rVq1\nagwaNIiWLVuipfXaKTcOHz7Mw4cPcXV1BeDFixfs2bOHyZMnY2hoiKGhIZMnTyY4OFijDlpCQgLf\nffcd8+fPz9bnrl27aNq0Kb1796ZMmTL07t2bxo0bs2vXLgCOHDlC3bp16dGjBwDNmzfH0dGRrVu3\nvvmHJYpVSRorvPa/dhMTE9q0aZNru7GxsfofghCidLG0tGTJkiUoFAoyMzNJSUnh7t276gfIZ8+e\nERERUdxhCiGEEB+sgIAAunXrRoMGDbC2ts620iprgjg5OZmAgAAqV65M3bp189W3QqEgPDwcW1tb\nHB0d+e677/jrr7/U7UeOHKF79+5oa2sX3AUJtfVB5wtkHyGEEG/mdffW3377DQ8PD7755hvGjBnz\nTufavn07jo6OGBgYAPDHH3+QkpJC06ZN1fs0btyYFy9eaKSvnT9/PkOHDtWomZbl8uXLNGnSRGNb\n48aNuXLlf6tZ/75QLDMzk8uXc5+oFCVTSRorvP7rlNf466+/iIqKKohYhBAl0LRp0+jQoQNGRkbU\nqVOHGjVqYGJiAkDlypX5/PPPUSqVJCYmqo85ffo0rVq1wtnZGWdnZ77//vviCl8IIYQoteLj4zly\n5Ij6tVonJyd2796tscJpzpw52NjY0LJlS3bv3o2vry8VKlTIV/9DhgzhwIEDnD59Gh8fH6Kiopg9\ne7a6PTExEWNj44K9KCGEEKIY5efe+q9//YuaNWvSsWPHdzrX3bt3OXbsGAMGDFBve/78OQD6+vrq\nbRUrVgTg2bNnwMsJ7jt37jB8+PAc+/3rr7/Ux7zaR9bxbdq04fr164SEhJCenk50dDQHDx5Un1uI\nt/HOE8x//vknw4YNK4hYhBAlUGZmJvPnz6dSpUrcunWLP//8k7i4ODIzM0lNTeXGjRs5Plza2NgQ\nHBxMcHAw48ePL4bIhRBCiNJtx44dGBgYYGdnB0D37t1JSUkhNDRUvc+8efOIiori6NGj1K1bl02b\nNuW7/yZNmmBoaAhAgwYN8PT0JCwsjLS0NOBlTZb79+8X4BWJV41zbV4g+wghhMi//NxbZ86cibGx\nMUOGDOHRo0dvfa7AwEDq1auHtbW1elvWl8BZk8EAT58+BV5OOicmJrJgwQJ1aoysN5VeTWlVoUKF\nbPUWkpKS1JPOdevWxdvbG19fX9q2bcvq1avp27cvVapUeetrEcWjJI0V3nmCWaFQSJE/IUoRlUrF\n5ds3Cb5wisVHQhi9ZxPfHQ6mpkV9+G99gpSUFBQKBS9evCAtLU1j9bIQQgghCl9mZiY7d+4kMTGR\n9u3b4+DgwCeffEJGRkaOBYmqVavG4sWL2b9/P9HR0e907qyxf4cOHQgLCyM9Pf2d+hM5s7esySBH\nZa7tgxyV2FvWLMKIhBCidMvvvbVcuXKsX78eMzMzBg8e/FZftqanp7Njxw4+/fRTje1169albNmy\n/Pvf/1Zvi42NpVy5cpibm3PlyhUePnzIsGHDsLOzw97eHoBx48axYsUKAJRKJbGxsRr9xsbGYmFh\nof67Q4cO7Ny5k9OnT+Pn50d8fDy2trZvfB2ieJWksUKZ1+3wySef5DmJnJqammvlaSHE++dK3J/M\nunAARVZBAl0o08ScZxEnadi0CYn3H/D06VOSk5PR1tYmMzOTp0+fkpGRoe5DoVBw9uxZnJycMDY2\nZubMmTRo0KCYrkgIIYQofY4dO8b9+/fZsWOHxptEly5dYtSoUfz+++/ZjjE3N6dPnz6sWbMGX19f\n9fa0tDRSUlLUfysUCnR1dQkNDaV9+/ZUrFiRmzdvsmTJEjp37oyuri4An3/+OW5ubkyaNInp06dj\nbm5OSkoKhw4d4tq1a1LorwAM7PZyMuDvBXwGd1cyoKtFTocIIYR4S29yb9XV1WXt2rXMmDGDQYMG\n8csvv2BmZgagvqeqVCr1PbZMmTIaNQv++c9/8vTpU1xcXDRiKFeuHE5OTqxZs4aPPvoIlUrF6tWr\ncXZ2RldXFysrKw4dOqRxTIcOHVi0aJF6gtjZ2Zkff/yR0NBQunbtyoEDB7h06RLLli1TH3PhwgUa\nNWpEeno6u3bt4vjx4wQGBhbQJymKUkkZK7x2gvn27dv07Nkzx8ThAA8fPiQgIKDAAxNCFI/LCff/\nN7n8X1pldWg4fSjPrt/m397bqKmvz6NHj3j+/Ln6C6aQkBBGjBgBvCwgcPjwYfT09Dhy5AgTJkwg\nLCysyK9FCCGEKK38/f35+OOPady4scZ2BwcHWrRogb+/f46LQDw8POjevTunT59WP4h6enri6emp\n3qds2bKcP3+e7du3M2/ePFJTUzE0NKRbt25MnDhRvZ+xsTE7duzA29ubkSNH8uTJE6pUqYKVldU7\nFz0S/zOwmwXmNSv9t0iPAo++zbBrKiuXhRCioL3pvVVbW5tly5Yxe/ZsBg0axObNm6lfvz7Nm79M\nSaBQKNT32IkTJ2rcQ/39/enRo4dGruUsnp6ezJ8/H0dHRwAcHR3V92ldXd0cU1QaGhqqU2CYmZmx\ndu1alixZgqenJ7Vr18bHx0ddSwnA29ubmJgYMjIyaNGiBX5+ftSvX/9tPzpRzErCWEGhek1+C1dX\nV/r168egQYNybL906RIuLi7vTbXJuLg4unTpQkRERK6T5kJ8yBYfCeHMX/G5tqc+T+bImG+poFee\nu3fvoq2tTe3atUlOTubevXs5HtO5c2eCgoIkp5MQQggh1GRcLoQQQrx/5P4tcvLaFcwtW7bkxo0b\nubaXL18eGxubAg1KCFE8MjMzuZoYD7qa21MePAaFgrLVDNCtoIeyiwM3jpwGUKfGePDgATdv3sTc\n3JxHjx5hZGSEQqHgwoULAKV2cnndunWEhoaipaWFlpYW8+bN4/nz5yxdupS0tDSaNGnCwoULNV6H\nEkIIIYQQQgghhCgtXjvBPGvWrDzb69Spg5+fX4EFJIQoeTJS0rgbdIiM5BQUWlpUMKrCgAED8PPz\nw8DAgDJlymBubo6rqysxMTEcOHCA7du3o62tjZ6enrrYQGlz9uxZjhw5wq5du9DR0SExMZGUlBQ+\n/fRTfvnlF+rUqcOaNWvYtWsX/fr1K+5whRBCCCGEEEIIIQrcayeYhRAfDi0tLRpWMc6WIqO8mTEN\nJg9U/21dwZgZ7Zw4cOAAV69eVW9XKBSkpaUxZMgQhgwZUmRxF4fMzEwePHhAlSpV0NHRAV6u0n78\n+DE6OjrUqVMHgDZt2rBhwwaZYBZCiA+UlZWV+ve0tDQA9X1DoVAQExPD0KFDiYqKYuXKlXzyySfq\n/c+fP8+nn36KiYmJuqDPV199xd69e9V9ZFm1ahUdOnRg7dq1+Pj4MHDgQObMmaNuT0lJoV27diQl\nJXHo0CFMTEyIjo7Gy8uLO3fukJ6eTs2aNRk4cCCDBw9WHxcZGcmyZcu4fv06lStXZuTIkRrtWWbN\nmsWOHTvw8/OTtxsL2MmLd1kf9PKNsHGuzYusGrwQQojikd+xw7lz5yhT5n/TegqFgu3btzN16lTu\n3r0LQHp6OhkZGZQtW1a9T2hoKPv372fv3r3cunWLsmXLYmNjw8yZM6lZU+4x76OSMFaQCWYhhAal\nQfYJ5r+zqGKMQqEgMjKSqlWrqtNkqFQqFi9ezOzZs4si1CKlUqm4EvcnlxPuczkhnquJ8WSkpnHl\n2hXaduyAjY0Ng/q7YWNjQ0ZGBv/+979p2rQpBw4cyDU3tRBCiNLv7Nmz6t9nzZpFRkYGixYtyrZf\n/fr1CQwM1JhgDggIoH79+rx48UK9TaFQ4OLiwvz583M8n0KhwNzcnH379jFz5kzKlSsHwIEDB6hW\nrRpPnz5V71uvXj18fHzUD5PR0dG4u7tjYWGBtbU1cXFxjB07loULF9KjRw/Onz+Pu7s7VatWVRce\nAnj27BmhoaE0atQIf39/mWAuQNvCr2hUhffaHMkgR6W6YrwQQojSJ79jhwkTJjBu3Lhs20NDQ9W/\nr1u3jpMnT+Lr66uxT3p6OrNnz6ZJkyakpaWxYMECxo4dy+7duwvwSkRRKCljBa0iPZsQosRTGtRA\nlZmZa7sqMxOlQQ3g5YrdV29eAF5eXoUaX3G5Evcnsy4cYMudC5z5K54kXXiur0OtqQOo1Lc9Z148\nZNLkyQQHB7NixQoWLVpE//790dfXl/zLQgghgJdfVuama9euxMbGcvv2beDlpO3BgwdxdXXN87ic\n1KxZkxYtWrB//371th07dtC/f3+NvgwNDdWTy5n/vffr6upiYGAAwJEjR6hbty49evQAoHnz5jg6\nOrJ161aN8+3evZuqVavi6elJeHg4iYmJbxSvyNnfHxizbA27zLbwK8UQkRBCiKL2pmOAnI7PqY8x\nY8ZgZWWFrq4uFSpUYNSoUfz+++8kJSW90/lE0SpJYwWZYBZCaLAwrcOCZt0ZXKsZ1hWMqZQKlVJf\npsUYXKsZC5p1x8K0jnp/R0dHjVdlX7x4QWRkZHGEXqguJ9xHoZX9f5kKLQX6Dcyo0aMtPd0HERYW\nRosWLdiyZQuBgYFYW1tTt27dYohYCCFESaNQKHJtK1u2LL1792bHjh3Ay9VHrVu3plq1atn2zeth\nM6utf//+BAQEAHDjxg1u3LhBly5dcjzG2tqaZs2aMWrUKBYsWED9+vXVbZl/+9I5MzOTy5c1H2QC\nAgLo3bs3NjY2VK1alV27duUan8ifkxfv5fjAmGVr2GVOXpQ3pIQQorTLa+zwrpPPrzp16hQ1a9ak\nUqVKBdanKFwlbawgE8xCCA0KhQKlmTnOzeyY2b4PG3uPYmPvUcxs3wfnZnYozcyz3eT8/PyoUqWK\n+u++ffsWddiF7nJC9rQhKQ8ek/IwQf33xUuxmJqa8vjxYwBSU1PZtGkTAwYMKLI4hRBCvJ8UCgVu\nbm4EBQWRkZGBv79/thXH8PJhMiQkBBsbG/VP69atuX//vkZfnTp14vbt21y7do3AwECcnZ3R1dXN\n8dzR0dGcPXuWuXPn4unpyaVLlwBo27Yt169fJyQkhPT0dKKjozl48CDPnz9XH3vhwgUuX75Mnz59\nAHByclJPbIu3tz7ofIHsI4QQovRav359tvHA24iJiWH58uV8++23BRugKFQlbazw1jmYMzIyuHr1\nKiYmJvINhxClmFYOq3b/TqFQcOXKFYyNjQGIi4sjOTkZPT29wg6vSGRmZnI1MR7+9lyekZLG3aBD\nZCSnoNDSooJRFdbNWsCmTZs4fPgwmZmZDBo0CFtb2+IJXAghxHulYcOG1KpVCx8fHxITE2nfvn22\nXIgKhQJnZ+dcczDDy0lobW1tXF1d+fXXXwkPD2fbtm15rnTS0dGhT58+hIaGsnv3bho1aoS5uTne\n3t6sWbMGLy8vPvroI/r27auRemP79u1YWlqqi9s6OTmxfv16IiMj3/pBVwghhBCv5+HhkWMO5jcR\nHR3NhAkTWLBgAR06dCigyMSHKN8TzAsWLMDCwoL+/fuTmZnJsGHDOHPmDHp6evzwww9FPoDMyMhg\n2bJlBAcHk5KSgoODA3PnzlXnjBNCFK3q1auzceNGRo8eDUCvXr2IiIgo5qgKV3kzYxpMHqj+u1Iq\nGBgYMGPGDGbMmFGMkQkhhHhfubm58c033zBhwoQ8X4vNj/79++Po6Ii1tTV16tTRWOWcm/T0dPT1\n9dV/d+jQQeOBc9KkSeovTp89e6aebHZwcFDvo1Ao8Pf3lwnmdzDOtTlem/NOOTbOtXkRRSOEEKI0\nOnbsGNOmTWPRokV8/PHHxR2OeEMlbayQ7xQZBw8e5KOPPgJeFvy4ceMGwcHBDBgwgFWrVhVagLnZ\nsGEDhw4dIjAwkKNHjwLIhI4QxWzUqFE0aNAAgEOHDhVzNAVHS0uLhlWMX7vfRwbG+VrxLYQQ4sOU\nn9zJvXr14qeffmLYsGG57pffnItmZmZs2bIl1wK84eHh/P7776Snp5OSkkJAQAAxMTF069ZNvc+F\nCxdIS0sjOTmZrVu3cvz4ccaPHw9ASEgIWlpa7Nmzh5CQEPXPvHnzOHjwIAkJCTmeV7yevWVNBjkq\nc20f5KjE3rJmEUYkhBCiOORn7PA2wsLCmDx5MsuWLZPJ5fdUSRsr5HsF8+PHj9Wvvx89epTu3buj\nVCopX748/v7+hRZgbgICApg4cSKmpqYAfPnll3Tt2pV79+6pq2ELIYre77//rp5k/eqrr1i8eHEx\nR1QwlAbGnPkrex7mV1nkYxJaCCHEhyuvFclZbbq6utjb22tsf/U4hUJBcHAwoaGhGsfPmDGDgQMH\nZtvfysoq1xgePnzI8uXLefDgAeXKlcPCwoKNGzfSsGFD9T7e3t7ExMSQkZFBixYt8PPzUxcBDAwM\nxM3NTT0ez+Lq6sq6desIDg7G3d39tZ+LyNnAbhYA2Qr4DO6uZEBXi+IISQghRBHLa+zw/fffs2HD\nBo1tq1at0njz6O/jgizfffcdqampTJkyRWPfffv2UaNGjQKIXBSFkjRWUKjy+ZVH+/btWbFiBdbW\n1nTr1o0vvviCbt26cf36dfr3709MTExhx6qWlJRE69atCQ4ORqn832y9tbU1S5cupVOnTrkeGxcX\nR5cuXYiIiMg2GBZCFIyYmBhatWoFFGxl2+J0+fZNZl04gCKXFcqqzEwWNOuO0sy8aAMTQggh3lMy\nLs+fkxfv/bdIjwKPvs2wayqLaYQQQhQfuX+XPCVhrJDvFcxZk8rm5uYkJSXRtm1bAC5fvoy5uXlh\nxZejrMrVFStW1NheqVIlnj17VqSxCCGye/WLn0uXLtGoUaNijKZgWJjWYQHduZxwnyuJ8fye8HI1\n80cGxlhUMUZpUAML0zrFHKUQQgghSht7y5qSDkMIIYQQuSoJY4V8TzDPnDkTExMT7t69y4wZM6hQ\noQIA9+/fx83NrdACzEnWuZ8+faqxPSkpSaMoiRCi6IWFheHi4gKAkZERvXv35vTp0xgZGRVzZO9G\noVCgNDNXr1DOzMwEkJzLQgghhBBCCCGE+KDle4JZR0eHESNGZNs+cuTIAg0oPypVqoSJiQn/93//\np14peevWLZ49e4aFheQjE6I4pKWlMWLECLZs2YK+vj4KhYJ169YRHR1N3759CQ8PR1dXt7jDLDAy\nsSyEEEIIIYQQQggBbzRD8tdffxEdHc2BAwfYt2+fHM4gpwAAIABJREFUxk9Rc3NzY+PGjcTFxfH0\n6VOWLl1Ku3btMDExKfJYhPjQnTt3DjMzMwICArC1taVOnTro6uri4uKCl5cXlStXZuLEiaUmH7MQ\nQghRHIYOHcq6deuAl+mobG1tNd7ou3//Pkqlkrt37wIQFBSEUqnEysoKKysrOnXqhJeXF6mpqQCs\nXbuWxo0bq9u7du2Kj4+Pur+/t1tZWbF8+XJ1+9/7t7e3Z/r06Tx+/LgoPo4PxsmLdxk+9wDD5x7g\n5MV7xR2OEEKIYvL3cUButdB8fX3p378/LVq0oFu3btnav/rqK5o2baoxPli5cqU8r7/HSsJYId8r\nmE+ePMmUKVN48uRJju09evQosKDyY8yYMTx58oR+/fqRmpqKg4MDS5cuLdIYhPjQZWRkMHv2bJYu\nXYqFhQUjR47k4MGD3Lx5k549e1KmzMv/xfz666+0bduW1atXa1SpFUIIIcSbebUSvJaWFt9//z0z\nZ87Mdf/atWsTHh4OvKydMmLECPT19Zk0aRIAdnZ2/PTTTwCcOnWKsWPHUqNGDfr27ZutPSd16tQh\nLCwMgCdPnjBlyhQWLlyoMREt3t628CsaleG9NkcyyFGprhovhBDiw/LqOCA3xsbGjBkzhuvXrxMU\nFJRjHy4uLsyfPx+AP/74g6FDh1KrVq0iT4Er3l1JGSvke4LZy8uLjh07Mm3aNKpXr56v/6gLk5aW\nFjNnzsxzQC2EKDzXrl2jd+/eXL9+nenTp9OuXTvGjBnDjBkzmDNnDmPGjFHvW7FiRfbs2YO9vT0W\nFhZ88sknxRi5EEIIUTp4eHiwfPlyhgwZQq1atV67v1KpxNramkuXLqm3vbpayc7OjgYNGuTanpNX\n2ytXrszHH3+Mv7//m1yGyMXfHxizZG2TSWYhhBA5cXR0BLLXLctN3bp1adWqFVevXi3MsEQhKElj\nhXynyLh16xbjx4/H2Ni42CeXhRDFJzMzk9WrV2Npacn9+/c5dOgQo0aNwt3dne3bt7Nx40YyMzPp\n3LmzxnF16tRhx44dDB8+nP/7v/8rpuiFEEKI0qNJkyZ069YtX6uFVSoVsbGxREVFYWlpma09MzOT\nkydPcvXqVXW7QqHg3Llz2NnZ0aVLF2bPnp1n+ovHjx8THh6OtbX121+UAODkxXs5PjBm2Rp2WdJl\nCCGEeGuvfkF89epVzpw5Q6tWrYoxIvGmStpYId8rmBs3bsydO3eoU6dOYcYjhCjBbt26xcCBAzl/\n/jxt2rQhMDAQHR0d7O3t+fbbb8nMzOThw4e4urqio6OT7fg2bdqwfPlynJycOH36NFWrVi2GqxBC\nCCFKB4VCwdSpU+nRowcXLlygevXq2faJi4vDxsYGhUKBgYEB/fr103jLKCoqChsbG7S0tKhWrRqT\nJ0+mT58+AHTv3p1+/fpRo0YN4uLimDdvHuPHj2f79u3Z+oeXK6Xq1avHggULCvnKS7/1QefztY+9\nZc0iiEYIIURpolKpCAkJISwsjPT0dJKTk+ncuTOdOnUq7tDEGyhpY4V8TzBPmjSJpUuX8vnnn9Oo\nUaNsk0dGRkYFHpwQomRQqVT8/PPPTJkyhczMTObPn6/Opdy/f39sbW3x8PDA1dWVihUr5pm3aejQ\noVy6dAlXV1d+++03dHV1i+oyhBBCiFLHxMSEIUOGsGTJElasWJGt3dTUVJ2DOSetW7fONcdygwYN\nNPpZsGAB7du35/bt25iZmWXrPzU1FV9fX9zc3AgNDcXQ0PBdLk0IIYQQhUChUODs7KzOwZyQkMDc\nuXMZNWoUfn5+xRydeF/lO0WGu7s7sbGxeHh40LFjR9q2bav+cXBwKMwYhRDF6N69e/Ts2ZMZM2ZQ\nuXJlDh8+zNSpU1EoFCxevJjbt2/j4+PDjRs3OHLkCI8fP6ZLly559rlgwQKMjIzw8PCQSrVCCCHE\nOxo3bhw3btzIcyI5NwV5H9bV1WXgwIEkJCRw5syZAuv3QzTOtXmB7COEEEK8joGBAX369CEqKoon\nT54Udzgin0raWCHfK5h/+eWXwoxDCFEC+fv7M2HCBLS1tenYsSM//vgjlStXBmD//v14e3sTGRlJ\nuXLlWLNmDdbW1tSoUYOyZcvm2a+WlhZ+fn44ODiwcuVKpk2bVhSXI4QQQpRK+vr6TJgwAW9v7wLt\nNyufsqGhIfHx8Xz77bc0bdpUvXr579LS0ti+fTtlypTRWP0s3py9ZU0GOSpzza04yFEp6TGEEOID\nl5qaSkpKivpvhUKBrq4uGRkZpKenk56ejkqlIjU1FZVKpX5OV6lUGl8wJyUlERISQs2aNdXP+6Lk\nK2ljhXxPMNva2hZmHEKIEuTRo0eMHz+e48ePk56ejpeXF6NHj1YX+Lx27RrDhw8nKCiIWrVq8eTJ\nE/z8/LCwsGDixIn5Ooe+vj67d+/G3t6ejz76iF69ehXmJQkhhBCl2oABA/Dz89NYeaRQKPIszv26\n9vDwcL799luSk5OpXLkybdu2Vb9Om3X87du3sbKyAkBbW5u6deuyatUq6tatWwBX9WHLqvz+9wfH\nwd2VDOhadFXhhRBClEyfffaZxt/16tVj3759fP/99/j4+AAv79XNmjVDoVBw6dIl9bbg4GBCQ0MB\nKFu2LM2bN2fDhg1FGr94dyVprKBQ5fFe3IULF2jcuDFlypThwoULeXbUrFmzAg+uMMTFxdGlSxci\nIiIwNTUt7nCEKHF2797N2LFjMTIyIi0tjR07dmhUm3/69Cn29vZMmDABDw8PAJYvX87x48c5fPgw\n9+7do1y5cvk+36lTp3BycuLQoUM0bdq0wK9HCCGEECWTjMvz5+TFe/8t5KPAo28z7JrKymUhhBDF\nR+7fJU9JGCvkuYLZzc2NEydOYGRklGfRrle/CRFCvJ8SExOZMmUKERER6OrqYmNjg7e3NxUqVFDv\no1KpcHd3x87OjnHjxgGQnp7OmjVrGDhwIOXLl3+jyWUAOzs7Vq1aRe/evTl9+jTVq1cv0OsSQggh\nhHif2VvWlHQYQgghhMhVSRgr5DnB/Ntvv2FgYKD+XQhROh08eJCRI0dSr149kpOTWbFiBcOGDcu2\n36JFi4iLi2PLli3qV2p37dqFmZkZ0dHRTJgw4a3OP2jQIGJjY3F1dSUiIuK1OZyFEEIIIYQQQggh\nRMmQ5wTzq0vdZdm7EKXPs2fPmDFjBnv27KF+/fokJCRw/PhxlEpltn337duHj48PkZGRGhPAq1at\nYuTIkUybNo3u3bu/dSzz5s2jf//+jBs3jp9++inPnJBCCCGEEB+Kkxfvsj7oZbrCca7Ni32FkhBC\nCCFKhpI0RtB60wMePHjAuXPniIqK0vgRQrxfjh07RvPmzbl9+zZlypShUaNGnDp1KsfJ5atXr/LZ\nZ58REBBArVq11NsjIyO5e/cuaWlpODo6oqen99bxaGlp4evry/nz51m2bNlb9yOEEEK8z6ysrNQ/\nTZs2pWnTpuq/W7ZsCcDQoUNRKpVER0drHNu1a1d27doFvMyPqFQqNfqzsrLSGLe7u7vTqFEj7ty5\no9FP1rHx8fEABAUFafTVqVMnvLy8SE1NBWD//v307t2b1q1bY21tjaurK/v37y+0z+hDsi38Cl6b\no3iclMLjpBS8NkeyLfxKcYclhBCiCFy8eJHx48djb29Pq1atcHR0xMvLi4cPHwJw8+ZNvvjiCxwc\nHLCysuLjjz/G09OTP//8E4C1a9fi7u6eY9/R0dG4urpia2tLq1at6NWrF1u2bCmyaxPvrqSNEfJc\nwfyqhw8fMm3atBwnkyUHsxDvj+TkZGbPns3WrVvp2bMnISEheHt755pn/enTpzg7OzNv3jzatm2r\n0bZy5Uo+//xzgoKCGDVq1DvHVqFCBXbv3o2dnR0WFhY4OTm9c59CCCHE++Ts2bPq32fNmkVGRgaL\nFi3Ktl+VKlVYsmQJgYGB6m0KhSLbG0AHDhzA2Ng42/G3bt0iMjKSjz76iICAAKZOnZpnXLVr1yY8\nPByAy5cvM2LECPT19Zk0aRJWVlb8/PPPVK1aFXg54Txt2jSaN2+OiYlJ/i9eaNgWfiVbVXj4X6X4\nrMrxQgghSp8TJ07g4eHB8OHD+fbbb6levToPHz5kx44dREVFUb9+fQYNGoSjoyPbt2/H1NSUJ0+e\nsHfvXo4ePcrQoUPz7L9evXr4+PhQs+bLFa/R0dG4u7tjYWGBtbV1UVyieAclcYyQ7xXMixYtIiMj\ng5CQEPT09PD19WXFihXUrVuXTZs2FWaMQogCEhUVRcuWLbl27RotWrTg7NmznDx5MtfJZZVKxWef\nfUabNm0YO3asRtvt27cJCwvDxcWFU6dO0aNHjwKJ0dTUVD1hfeHChQLpUwghhHgfqVSqXNvc3Ny4\nf/8+e/fufau+/f39sba2xt3dnZ07d5KRkZHvY5VKJdbW1uoFJjVq1FBPLmdkZKClpUXFihUpX778\nW8UmXlaDz+nBMcvWsMucvHivCCMSQghRlObOnUvv3r2ZPn061atXB6BatWp4eHjQo0cPFi1ahKWl\nJV5eXuqUtpUrV2bw4MGvnVwGMDQ0VE8uZ2ZmAqCrq6uuwyZKrpI6Rsj3BHNkZCQzZszAwsIChUJB\n9erV6dGjB9OnT8fHx6cwYxRCvKPU1FRmz55Nr169GDRoEOfOncPCwoITJ05Qv379XI/z8vLi7t27\neHt7Z1sR5e3tzbBhwzh8+DBdu3alQoUKBRZv69atWbt2LU5OTurXc4UQQogPTV71CPT09Jg0aRIr\nVqwgLS3tjfpNS0tj165dODk50a1bN54/f05ERES+jlWpVMTGxhIVFYWlpaV6+927d7GxscHS0pJ/\n/OMf+Pj4UKVKlTeKS/zP+qDzBbKPEEKI988ff/zBrVu36NWrV47tycnJREVF5dr+JqytrWnWrBmj\nRo1iwYIFec4PiJKhpI4R8p0i4/nz51SrVg2ASpUqkZCQgLm5ORYWFvz73/8utACFEO/mwoULDBs2\njFq1ajF69Gi8vb3ZuHHja9NPhIaG8v333xMVFaVR1A9eFgf88ccfiYyMZOLEiQwbNqzA4/7000+J\njY3FxcWFQ4cOUa5cuQI/hxBCCPG+UigU9O3bF19fX3755ZdcU1X17NlTPVFtZmZGUFAQBw8e5Pnz\n5zg6OlK+fHk+/vhj/P396datW67ni4uLw8bGBoVCgYGBAf369WPMmDHqdhMTE6Kionjx4gW//vor\nEyZMYM+ePTmm5xBCCCFE7h4/fgyQ6z00KSmJjIyMArnHRkdHk5aWxr59+/D09MTc3JxGjRq9c7/i\nw5PvFcx16tTh1q1bANSvX5/du3eTnp7O/v37MTQ0LLQAhRBvJz09nUWLFtGlSxdGjBhBRkYG//zn\nP4mKinrt5PLVq1dxd3cnMDAwx9yJvr6+tG/fHgMDA44fP07Pnj0L5RrmzJmDqakpY8aMyfM1YSGE\nEOJDpKWlxZdffskPP/xAYmJijvuEhoaqi3IHBQUBL9NjdOrUCX19fQCcnJz417/+xe3bt3M9l6mp\nKVFRUURGRhIWFsb06dMpUyb7WpVy5coxatQoqlWrxm+//VYAV/lhGufavED2EUII8f7JmmPL7W3e\nSpUqoa2tzf379wvkfDo6OvTp0wcbGxt2795dIH2KwlNSxwj5nmB2cXHh6tWrAIwZM4agoCAsLS1Z\nuXIlo0ePLrQAhRBv7sqVKzg4OPDbb7/h7e3Nd999h5WVFYcPH6Z27dp5HptV1G/+/Pm0adMmW3tm\nZiarVq1i6tSp7Nmzh86dO1OxYsVCuQ4tLS02b95MbGwsS5YsKZRzCCGEEO+z9u3bY2lpibe3d772\n//PPPzl9+jRHjx7FwcEBBwcHvvrqK1QqlUbBwHeVnp5eoOmzPjT2ljUZ5KjMtX2QoxJ7y5pFGJEQ\nQoiiUrduXerUqZNrnQU9PT1at25NaGhogZ43PT1d/eWzKLlK6hgh3ykyhg8frv7d1taW/fv3c/Hi\nRerUqYNSmfuFCSGKTmZmJmvXrmX+/PnMmTOH//znP0yZMoXNmzfj6OiYr+OHDx9O27ZtsxX1y7Jv\n3z4qVaqEg4MDS5cu5dNPPy3oy9BQvnx5QkJCsLOzw8LCAhcXl0I9nxBCCFFS5PX2zqttM2bMoH//\n/tlSWuXE39+f2rVrs3XrVnXqDJVKxbZt2/D392fSpElvHGdwcDAtW7bE1NSUv/76i82bN5OUlISD\ng8Mb9yX+J6sC/N8L+QzurmRA16KvDi+EEKLozJkzh3HjxlG1alUGDx5M9erVefToETt37sTMzIyv\nvvqKwYMHM2vWLMaNG0etWrV4+vQpoaGhpKWlqdNYZmZmkpqaqjFu0NXV5eDBg5ibm1OvXj0yMjII\nCQkhJiaGr7/+urguWbyBkjhGyPcE89+ZmJjk+Oq8EKJ4/PHHH7i7u5OWlkZISAizZ88G4MyZM/n+\nt+rl5cX9+/fZtm1brvusXLmSKVOm8PTpUw4fPoyfn1+BxJ+XWrVqsWvXLj755BPMzc2xsrIq9HMK\nIYQQxS2vIn+vtimVSnr16kVwcHCex6emphIcHMyECROoWrWqRtvw4cP56aefOHToEI0bN9Y4VqFQ\n5BnLzZs3WbNmDQkJCVSoUAFLS0t+/vnnbOcQb25gNwvMa1b6b7EeBR59m2HXVFYuCyFEademTRu2\nbt3KunXr6N27N2lpaVSrVo1OnTrRr18/jIyM2LFjB97e3gwYMIDnz59jaGhImzZt1DUSFAoFp0+f\nplmzZhp9r1ixgoSEBJYvX86DBw8oV64cFhYWbNy4kYYNGxbH5Yq3UNLGCApVHksjNmzYkOdg8lXv\nS5qMuLg4unTpQkREBKampsUdjhDvTKVSsWnTJjw9PZkxYwZNmzZl5MiRjBs3jm+++QZtbe189RMa\nGsrYsWOJjIzMdUL6/Pnz9OjRgz/++IPAwEC2b9/Onj17CvJy8hQYGMgXX3zB6dOnqVGjRpGdVwgh\nhBAFT8blQgghxPtH7t8iJ3muYN6+fXu+O3pfJpiFKE3u3LnDqFGjePDgAb/99hv+/v6MHj2arVu3\n0rFjx3z38/vvv+Pu7k5wcHCeq51XrVrFhAkT0NXVZceOHfTr168AriL/+vfvz6VLl3B2dubw4cOU\nK1euSM8vhBBCCCGEEEIIITTlOcF86NChoopDCPEGVCoVW7ZsYdq0aUyYMIGhQ4cybNgwKlasSExM\nDNWrV893X0lJSTg7O7NgwYIci/pluX//PsHBwVy7do2nT59y6NAhfvrpp4K4nDcye/ZsLl26xMiR\nI/n111/z/ZaFEEIIIYQQQgghhCh4WsUdgBDizTx48IC+ffuyePFiDhw4QMuWLbG3t8fJyYnQ0NA3\nmlzOKurn4OCgztOUm/Xr1/Ppp59iZGTEvn37aNu2LQYGBu96OW9MoVDw008/cfXqVby8vIr8/EII\nIURRun37NpMmTcLBwQErKys6duzIxIkTSUtLIygoiG7duuV6bGpqKuvWraNXr15YWVnh4ODAsGHD\nCAsLA17Wb5g0aRLt27enZcuW9OrVi8DAwBz7mjVrFkqlkqioqBzb/fz8cHR0VMe4c+fOd794wcmL\ndxk+9wDD5x7g5MV7xR2OEEKIItC5c2d2796d6/bTp0+jVCqxsrLCysqKdu3a8fXXX/PkyRMAgoKC\nNNo7deqEl5cXqampAFy+fJlRo0bh4OCAUqnkzJkzRXp9ouCUpHHCGxX5O3LkCJs3b+batWsANGjQ\ngM8++4wOHToUSnBCCE1BQUFMmDCB4cOH88svvzBnzhyCgoLYtWtXnquPc+Pl5UV8fPxr0+G8ePGC\n9evX889//hOgWNJjvEpPT4+QkBBsbW1RKpX07du32GIRQgghCtPo0aNp164dBw4cQF9fn/j4eA4f\nPkweZVQAyMjIYOzYsTx48IB//OMfWFlZUaZMGSIjIwkMDMTR0ZGnT59iZ2fH7NmzqVatGmfOnGHc\nuHFUqVKFrl27qvt69uwZoaGhNGrUCH9/f2xsbDTO9f3337N7925WrFhBkyZNePLkCY8fPy6Uz+ND\nsi38ikZ1eK/NkQxyVKorxwshhCi9cntTN2u7trY2Z8+eBV5+GT1mzBi8vLxYsmQJALVr1yY8PBx4\nOaE8YsQI9PX1mTRpEjo6Ojg6OjJlyhT69esnbwW/p0raOCHfE8xbtmxh4cKFdOvWjVGjRgFw9uxZ\nxo8fz1dffcXQoUMLLUghPnQJCQl8/vnnnD59mp07d1KjRg06d+5MrVq1iImJwdDQ8I37DA0NZf36\n9URGRlK2bNk89926dStWVlY0atSI58+fEx4ezvr169/2cgpEzZo1CQkJoVu3btStW5eWLVsWazxC\nCCFEQUtISODmzZv4+Pigr68PgLGxMZ9++ulrj927dy/R0dGEhoZSu3Zt9XY7Ozvs7OwAaNasmUZl\n+VatWtGuXTtOnz6tMcG8e/duqlatiqenJyNHjiQxMZEqVaoAL1NtbdiwAW9vb5o0aQJA5cqVqVy5\n8rt/AB+wvz80ZsnaJpPMQgghspiZmdGxY0eOHz+eY7tSqcTa2ppLly4BUL9+ferXr1+UIYoCVhLH\nCflOkbFhwwZmzJjBqlWrGD58OMOHD2fVqlXMmDGDjRs3FmaMQnzQ9u/fj6WlJYaGhpw7d447d+5g\nZ2fH0KFD2bVr11tNLmcV9QsICMizqB+8zPe8atUqpk6dqo7H1tYWIyOjt7qegmRlZcUPP/yAs7Mz\n9+7Ja6NCCCFKFwMDAxo2bMg333yjroPwupXLWY4ePUqzZs00JpdfJzk5mXPnztGoUSON7QEBAfTu\n3RsbGxuqVq3Krl271G3nzp3jxYsXXLp0iS5duuDg4MD06dP5z3/+k+/zCk0nL97L8aExy9awy8X+\nGqwQQoiS488//+TQoUMaXxpnUalUxMbGEhUVhaWlZTFEJwpaSR0n5HuC+cmTJ3Tq1Cnb9g4dOpCU\nlFSgQQkh4OnTp4wZMwYPDw98fX357rvv+PLLL/n666/Zt28fkyZNeqtXWfJb1C9LREQEmZmZ6pVM\nxZ0e4+9cXV0ZO3Ysffr0ITk5ubjDEUIIIQqUr68vtra2+Pr64uzsjIODA+vWrXvtcY8fP8bY2Djf\n58nIyGDGjBmYmJjg7Oys3n7hwgUuX75Mnz59AHByciIgIEDdnpCQAMCJEycIDAxk//79vHjxgi+/\n/DLf5xaa1gedL5B9hBBClE4KhYKMjAxsbGxo3bo1I0aMwN7enq+//lq9T1xcHDY2Ntja2jJ16lT6\n9ev32rpL4v1QUscJ+U6R0bZtW06cOEGdOnU0tp88eRJ7e/sCD0yID9nhw4dxd3enS5cuXLhwgbt3\n76rzDZ85c+atXzvNKurXrl27fN9cVq5cyZQpU1AoFCQnJ3PgwAHWrl37VucvLJ6ensTGxuLu7s62\nbdskh5QQQohSw8DAgKlTpzJ16lRSUlLYt28fs2fPpnr16nne7wwNDfP9dk9aWhpffPEFjx49YuPG\njWhra6vbtm/fjqWlpfoZwMnJSZ1iq3Xr1lSoUAGAsWPHqt+q+vzzz3FxceHFixeUK1fubS9dCCGE\n+CDp6OiQnp6ebXt6ejplypRBpVKhra2da+FdAFNTU3UOZiGKQr5XMNvb27N69Wo8PT0JDAwkMDAQ\nT09PVq9ejYODA/v27VP/CCHezl9//cXkyZMZMmQI3t7ebNq0iZCQENq1a8eECRPYvn37O+U0XLhw\nIfHx8axZsyZf+1+5coXo6GgGDx4MQFhYGK1ataJatWpvHUNhUCgU/Pjjj9y8eZP58+cXdzhCCCFE\noShbtiwuLi589NFHXL58Oc8J5g4dOnDx4kVu3bqVZ58pKSlMnDiRhIQEfvrpJ3WuZ3hZ3G///v1c\nu3YNBwcHHBwcGDZsGAqFAn9/f4Bs6TSAfKfxEDkb59q8QPYRQgjxfqpVqxY3b97U2Pb8+XMePXqE\nmZlZ8QQlSoySOk7I9wrmBQsWABAUFERQUJBG298ndHr06FEAoQnxYTl58iSfffYZ1tbWXLhwgbJl\ny+Lu7s6pU6c4dOjQO+dL2rt3Lz/88ANRUVGvLeqXZfXq1YwdOxY9PT0AAgMDS1R6jFeVK1eO4OBg\n9UpvNze34g5JCCGEeCdJSUls3LgRJycnzM3NUSgUREREcPXqVcaOHcvz589RqVSkpqZqTOrq6OjQ\nq1cvdu3axfjx4/nHP/5B8+bNKVOmDGfOnMHf35/ly5fz/Plzxo0bh66uLhs3bsw2PggJCUFLS4uQ\nkBD1WADg0KFDzJ8/n4SEBGrVqkWHDh3YsGEDjRs3Rltbm++//5527drJ6uW3ZG9Zk0GOylzzKw5y\nVGJvWbOIoxJCCFFUXFxc8PLyol27dlhZWfHs2TOWLFmChYUFjRs3znPlcn6lpKSoxw6pqamkpKSg\no6ODlla+16GKYlJSxwn5nmC+fDn3BNJCiLeXkpLCt99+y88//4y3tzf9+vXj4sWLuLm5YWdnR3R0\ntPr107d15coVRowYQUhICDVr5u9/NI8fP2bbtm3qSrMvXrxg3759LF++/J1iKUw1atQgJCSErl27\nUq9ePaytrYs7JCGEEOKt6ejo8PjxYyZOnMjDhw8pU6YMpqamzJ49G0dHR3bt2sXt27ezFfWZPn06\no0ePZsOGDfz444/MnTuXO3fuoK+vT4MGDRgyZAgA4eHhREVFoaenh52dnfr4Pn368O233xIYGIib\nmxumpqYa/bu6urJu3TqCg4Nxd3fnu+++Y968eXTu3Jly5crh4ODAvHnzCv8DKsWyqr///eFxcHcl\nA7oWfWV4IYQQRad37968ePGCefPmcffuXcqXL0/r1q1Zv369egI4r7eYFApFnu1xcXF8/PHH6n0/\n++wzABYvXqxRh0GUXCVxnKBQ5fMdtrS0NHR0dHJsS0xMpEqVKgUaWGGJi4ujS5cuREREZBssC1HU\nzp49y/Dhw6lXrx4//PAD1atXZ9OmTXh6erKc+XwkAAAgAElEQVR8+XKGDRv2zudISkrC1taWadOm\nMXr06Hwft3jxYi5dusQvv/wCwJ49e1i+fDmHDx9+55gKW3BwMJ9//jmnTp2iVq1axR2OEEIIIXIg\n4/LXO3nx3n8L9Sjw6NsMu6ayclkIIUTxkvt3yVGSxgn5XsHs5ubGypUrMTc319h+8uRJZs6cydGj\nRws6NiFKrbS0NBYvXszatWtZvnw5Q4YM4enTpwwaNIjY2FiOHTuGUql85/NkZmYybNgwOnTo8EaT\ny2lpaXh7e7N37171th07dpTY9Bh/5+zsrK54f/ToUcqXL1/cIQkhhBBCvDF7y5qSDkMIIYQQOSpJ\n44R8J1cxMzPDxcVFnX85PT2dZcuWMWrUKPr06VNoAQpR2sTGxtKmTRuOHz9OTEwMQ4cOJSYmhpYt\nW1KlShVOnTpVIJPL8DJ3+sOHD/Nd1C9LYGAgDRs2pEWLFsDLnEx79uzB1dW1QOIqCjNnzqRx48YM\nHz6czMzM4g5HCCGEEEIIIYQQolTK9wrmNWvWsH37dubNm8exY8eIi4vj/v37bNq0CXt7+8KMUYhS\nISMjg1WrVrFo0SIWLlzImDFjgJf/thYsWIC3t3eBFqbbs2cPGzZsICoqCl1d3Xwfp1KpWLlyJbNn\nz1Zv++2332jcuDEmJiYFFl9hUygUbNy4kc6dOzN37lzmzp1b3CEJIYQQQgghhBBClDpvVB5ywIAB\nDB8+nP379xMbG8vatWv/n737Doviahs4/EMUNGIXTUyMBQs2ELEgwUYoNorYBTWJvQd7jA00aCzB\nDiZqbFHKUgSxGwsqIigmaMRulASNCgo2kGW/P/zY1xVQVIric1/XXq8758w5z+wbnZkzZ54jg8tC\n5MLly5dp374927Zt48SJEwwbNoykpCScnJzYuHEjEREReTq4fP78eQYNGoRCocj1on6Zjh07xr17\n9+jatat62/uUHuN5urq6BAUFsWHDBnx8fAo7HCGEECJfxMbGMnLkSFq3bo2pqSm2trZ4eHhw+/Zt\nAK5du8bEiROxsLDAxMQEKysrpk2bxt9//w3A8uXL+frrr7Nt+9ChQwwYMAAzMzNatmyJs7Mz0dHR\n6vKrV68yduxY2rZtS7NmzejatSv+/v75f9AfiIjYfxnotouBbruIiE0o7HCEEEK8JS8vLwwNDQkO\nDtbYbmlpSePGjbl+/brG9oYNGxIVFQXAjh07aNmyJTdv3lSXp6SkYGlpqV47KdO///5LgwYNsl3X\naebMmZiYmGh8DA0NWb9+fR4dpSgI79o1Qq4HmB8+fMikSZNYv3493333He3bt+ebb77J8pdCCPE/\nKpUKLy8vWrVqhZOTEwcPHqR27dpERETQrFkzatasydGjRzEwMMizPpOTk3F0dMTDw0NjRfjc8vT0\nZNy4cerVaZ8+fcq2bdvo3r17nsVYkKpUqUJISAhjx47lxIkThR2OEEIIkaeOHj2Ks7MzBgYGbNu2\njZMnT7J582YqVKhAVFQU58+fp3v37ujo6ODj40NMTAwBAQE0atQoV2uoJCcnM2DAAPbt28fx48fp\n2rUrQ4YMUd/cpqSkYGZmRkBAAKdOncLNzY0FCxawd+/e/D70Im/rnvN4rI8iMTmVxORUPNafYOue\n84UdlhBCiDeUkZGBv78/DRo0wNfXN0t5mTJlWLRokcY2LS0t9Z87d+5M+/btmTJlinrb7NmzqVWr\nFgMHDtTYz9/fn3r16hEdHc21a9c0ytzd3YmJiVF/Vq5cSfHixenSpUseHKUoCO/iNUKuU2Q4OTmh\no6ODQqGgbt26DBw4kC1btjB79mzCw8NZvHhxfsYpxHvnxo0bDBo0iHv37hEeHk6DBg3IyMhgwYIF\nLF68mF9++QV7e/s87TMjI4P+/fvTvn17Bg8e/Nr7X716lYMHD2o8uTxw4AD16tWjevXqeRhpwTIy\nMmLNmjU4OTlx/PhxWelWCCFEkeHm5oadnR0TJkxQb9PX12fEiBEAfPXVVzRp0gQPDw91ebly5XB2\nds5V+3Z2dhrf+/bty8qVKzlz5gwff/wxRkZGGBkZqctNTU1p06YNkZGRWFtbv82hfdC27jnPlt1x\nWbZnbutrU7+gQxJCCPGWwsPDSUpK4ueff8bOzo6LFy9St25ddfk333zDqlWriImJwcTEJNs2Zs6c\nib29PevWraNy5cocOXKE0NBQjTpKpZKAgADGjx9PYGAgvr6+GoPSL/Lx8cHS0hJ9ff28OVCRr97V\na4Rcz2A2MzNTDy5n6tevH/7+/ly8eDFfghPifaRSqVi/fj3NmjWjffv2HDt2jAYNGnD79m26dOnC\ntm3biIqKyvPBZYA5c+Zw9+5dli5d+kb7Z74iq6enp972vqbHeJG9vT3jxo3D3t6ehw8fFnY4Qggh\nxFu7evUq169f10hr9bzHjx8TFRWVY/mbOH/+PElJSdSrVy/HPk+fPk2DBg3yrM8PTURsQrY3jpm2\n7I57J16FFUII8Xr8/PywsbGhTp06NG/ePMss5qpVqzJw4EB+/PHHHNvQ09NjwYIFLF26FHd3d9zd\n3alSpYpGnQMHDpCcnIyNjQ2Ojo4EBweTlpaWbXu3b9/m999/p0+fPm9/gCLfvcvXCLkeYHZzc0NX\nVzfL9rp166JQKPI0KCHeVzdv3sTBwQFPT0/27dvHtGnTKF68OIcOHcLExISmTZty8OBBPv/88zzv\nOyQkhDVr1qBQKF5rUb9MycnJbNiwgTFjxqi3paenExQU9N6mx3jRxIkTMTY2ZsCAAWRkZBR2OEII\nIcRbSUxMBJ7dkGYnOTkZpVKZY/nrunv3LmPHjmXQoEHZXssolUomT55MtWrVcHR0zJM+P0TegX/k\nSR0hhBDvjlu3bnHo0CEcHByAZxOgQkJCNAZ+tbS0GDJkCDdu3GDnzp05tlW/fn1Kly5NyZIl6dCh\nQ5ZyX19frKys+Oijj7CxseHx48c5pq5SKBRUq1YNc3PztzxCURDe5WuEVw4wKxQKUlNT1d+vXLnC\n06dP1d8fPXqEl5dX/kQnxHvEz88PY2NjjIyMiIqKwtjYGKVSibu7O3369GHt2rXMmzePEiVK5Hnf\ncXFxDB48GIVCwccff/xGbaxbtw4rKyuNG8ZDhw5Rs2ZNatasmUeRFi4tLS28vb3577//mDlzZmGH\nI4QQQryVihUrAs9uWrNTtmxZtLW1NRYDelO3bt1iwIABtGnThvHjx2cpf/r0KePHj+fOnTt4e3uj\nra391n0KIYQQRYVCoaBChQrqdZI6duxIamoqYWFhGvVKly7N6NGj+emnnzTG3p43e/ZsGjZsSNWq\nVbPkbP7nn384evSoOsWVnp4elpaW2S56n5kTulevXnlxiOID98oB5unTp/PgwQP19+7du2tcpD58\n+FAGmMUH7e7du/Tp04eZM2cSEhLC3Llz0dHRISEhAWtraw4ePMjJkyextbXNl/7v37+Po6Mj8+bN\no1WrVm/UhlKpZNmyZbi6umpsVygU9OzZMy/CfGfo6uoSGBjIli1b+O233wo7HCGEEOKN1apVixo1\narB9+/Zsy0uVKkXLli2z3Ly+rvj4eFxcXGjXrh3Tp0/PUp6amsro0aNJSkpi3bp1Gqm2xOsb7mSc\nJ3WEEEK8GzIyMggICODevXu0bdsWCwsLOnXqhFKpzHaxv169elGiRIls71dDQ0M5evQo8+fPZ8GC\nBfj7+xMREaEu9/f3JyMjg++++w4LCwssLCw4dOgQUVFRXL16VaOt8PBwbt++XWTeWP4QvMvXCLlO\nkSGEyCo0NBQjIyOqVatGTEyMeoB3z549mJqa0r59e/bu3Uu1atXypf/MRf0sLS0ZNGjQG7cTEhJC\n1apV1U9T4dmgc1FKj/E8fX19QkJCcHV15fjx44UdjhBCCPHGZs2aRWhoKJ6envz3338A3Llzh9Wr\nV7Njxw6mTp3KmTNnmD59OvHx8ahUKpKTk9m6dSsbN25Ut5ORkUFaWhqpqanqj0ql4vLly/Tr14+u\nXbsyefLkLP0/fPiQwYMHk56ezi+//EKpUqUK7NiLqtZNPqGfrWGO5f1sDWnd5JMCjEgIIcTbCA8P\n5+bNm/j6+rJt2zb1x9vbm9OnT3PhwgWN+tra2kyaNAkvLy9UKpV6e0JCAnPmzGHu3LlUrlwZAwMD\nJk6cyHfffUdKSgrp6ekoFAqGDRtGaGioup/du3dTu3Zt/Pz8NPrx8fHBxsaGChUqFMjvIN7eu3yN\nULxQehXiPXf//n1cXV05ePAgW7ZsoV27dsCznMUzZ85k48aNbNmyhfbt2+drHO7u7iQmJr51HnRP\nT88ss5fDw8OpVq0aBgYGb9X2u6px48b8+uuvdO/enYiIiHzJiy2EEELkN3Nzc7Zs2YKXlxd2dnY8\nffoUfX19OnToQI8ePahUqRIKhYIVK1bQp08fHj58SMWKFTE3N2fo0KHAsxRSkZGRGBkZqdvV0tJi\n8eLF6tlN69evZ/369eryOXPm0LVrV/bs2UNUVBSlSpXSeFDt4ODA7NmzC+pnKHIyV4B/cSEf546G\n9LEunNXhhRBCvJnMnMgNGzbU2G5hYUHTpk3x9fVFS0tLo6xDhw4YGhpy4sQJAFQqFVOmTMHGxgYr\nKyt1PWdnZw4cOICbmxsdO3bkwYMHDBw4UJ1GK9NXX32Fp6cn48ePp0SJEty6dYvDhw+zYcOGfDpq\nkV/e1WsELdXzj0OyYWhoyNGjR6lUqRIAJiYmhISEUL16deDZipNt2rQhLi7nVQzfJfHx8Xz55Zfs\n37+fzz77rLDDEe+hffv2MWjQIDp16sTChQspU6YMADdu3KBv376UKVOGDRs2ZFnJNa+FhIQwatQo\noqKi3jjvMsDJkyfp1q0bV65coXjx/z1zGj16NNWqVWPatGl5Ee4766effmLjxo0cOXJEXukVQggh\nCpBcl79aRGzC/y/Wo8WI7kaYNZaZy0IIIQqXnL/fDe/aNUKuZjCfPXuW8uXLo1KpUKlUnDt3jqSk\nJAD1/wpR1D18+JDJkycTEhLCmjVrNHIqh4aGMnjwYCZMmMDEiRMpVix/s89kLuoXGhr6VoPL8Gz2\n8pgxYzQGlzMyMggMDOTgwYNvGem7z9XVlb/++gsXFxcCAwPz/f87IYQQQojcat3kE0mHIYQQQogs\n3rVrhFwNMGe+Ppdp7Nix+RKMEO+qo0ePMnDgQMzNzYmNjaV8+fIApKWlMXXqVAIDAwkKCsLc3Dzf\nY8mLRf0y/fPPP+zYsYMVK1ZobD927Bj6+vrUq1fvrdp/H2hpabFq1Sqsra35/vvvmTdvXmGHJIQQ\nQgghhBBCCPHeeOUA8759+woiDiHeSU+ePGHmzJls2rSJVatW0a1bN3XZlStX6N27N59++imnTp3K\nkuMoP+TVon6ZVq1ahbOzs3rAPJNCoaBHjx5v3f77QkdHh4CAAFq1akXDhg3p379/YYckhBBCiGxE\nxP6Ld+CfwLNV0t+lmTtCCCGEeD1yXi86XjnALPlUxIcqOjqagQMH0qBBA/7880/09fXVZf7+/owa\nNYrp06czZsyYLAn584u7uztJSUlvvagfwKNHj/jll184duyYxvaMjAwUCgV79+596z7eJ5UrVyY0\nNJT27dtjYGBQILPRhRBCiFe5ceMGCxcu5NSpUzx8+JBy5crRuHFjPD09CQ0Nxdvbmz179mS7b1pa\nGmvXriUsLIx//vmH0qVLU7t2bZydnbG1tSU6OpohQ4Zo7JOamkqdOnUICQnR2D59+nQUCgWbNm2i\nRYsW6u2JiYnMnz+f6OhokpKS0NfXp0ePHlnegMwLW/ec11jQxmP9CfrZGqoXuxFCCCGKiv79+3P6\n9GmNVJbw7Dytq6sLQHp6OkqlUv0doGPHjty4cYPNmzdnafO7774jKSkJb29vPD092b59O/fu3aN4\n8eI0btyYiRMn0qBBg/w9sOfIeb1oeekA8927d9WL++XGnTt3qFy58lsHJURhSktL44cffsDLy4ul\nS5fSp08f9QDykydPGD9+PHv27GHHjh00b968wOLatm0ba9euJSoqCh0dnbdub9OmTbRu3Zo6depo\nbI+MjKRcuXIFemJ5VzRs2JANGzbQo0cPIiIiqFGjRmGHJIQQ4gM3ZMgQ2rRpw65du9DT0+PWrVsc\nPHiQV6zTjVKpZNiwYfz333/MnDkTExMTihcvzokTJ/D398fW1pbmzZsTExOj3kelUvHll1/i4OCg\n0daDBw8ICwujQYMG+Pr6agwwP3z4kDp16jBu3Dg+/fRTLl68yLBhw9DR0eGrr77Ks9/hxZvQTJnb\n5GZUCCFEUTNq1CiGDx+eY7mXlxcRERFs3LhRve3y5ct06dKFK1euULt2bfX2lJQUdu3ahaenJwAO\nDg4MGTIEPT09UlNT8fT0ZPTo0ezfvz//Dug5cl4vel66mlXnzp3x8PDgwoULL20kLi6OuXPn0qVL\nlzwNToiCFhsbi5mZGdHR0Zw+fZq+ffuqB5fPnz9Pq1atuHv3LidPnizQweW4uDiGDBmCQqF460X9\n4Nks5SVLluDq6pql7ENLj/GiTp06MWXKFOzs7EhJSSnscIQQQnzAkpKSuHbtGn369EFPTw+AqlWr\n0rt371c+bN6+fTvR0dF4eXnRqlUrdHR0KFasGGZmZixevDjbfQ4ePMjt27dxcnLS2B4SEkLlypWZ\nNm0ae/bs4d69e+qy6tWrM3ToUD799FMA6tatS5cuXYiMjHybQ9cQEZuQ7U1opi2744iITciz/oQQ\nQoj3gUqlyvLA2cDAAFNTU/z9/TW2h4SEUL58edq1awdA7dq11dcWSqUSLS0tqlatWiBxy3m9aHrp\nAHNISAgPHjygR48eWFtbM2HCBBYvXoy3tzeLFy9m/PjxWFlZ0atXLx49epTlVToh3hdKpZIff/wR\nS0tLRo0axfbt26lWrZq6fNOmTVhYWDBq1Ch8fHwoV65cgcV2//59HBwcmD9//lsv6pdp9+7d6Orq\nqk8umVQqFQqFgp49e+ZJP++rsWPHYmZmhrOzM0qlsrDDEUII8YGqUKECdevW5fvvvyc4OJhLly69\ncuZypsOHD2NkZMTnn3+e6/58fHywtbWlQoUKGtv9/Pyws7OjRYsWVK5cmaCgoBzbyMjIIDIyMk/f\nhPIO/CNP6gghhBDvk9ye81/Uq1cvgoODefr0qXqbn58f3bt310jvGRoaSvPmzWnWrBlHjhxhyZIl\nbx1zbsh5vWh66QBz1apV8fDw4NChQ+oFxY4ePUpQUBARERFoaWkxZMgQDh48iIeHR4E97RAiL124\ncIE2bdqwe/duoqKiGDRokPof3YcPH/L111/j4eHB77//ztChQwss3zI8u0lzcXHBysqKb775Js/a\n9fT0xNXVNcuxREdHU6pUKRo1apRnfb2PtLS0WLFiBSkpKUybNq2wwxFCCPEB27hxI61atWLjxo04\nOjpiYWGBl5fXK/dLTEx8rWvzf//9l/DwcPr06aOx/c8//yQuLk6dNsPe3h4/P78c25k3bx4pKSl5\net0ihBBCfIi8vb1p0aKF+tOyZctc7dexY0cyMjLU6yr98ccfXLp0KctEMjs7O6Kjozly5Ah16tRh\nzJgxeX4M4sPxykX+4NnsiT59+mS54BTifZaRkcHKlStxc3Nj1qxZjBo1imLF/vfMJTY2lt69e9Oq\nVSuio6MpXbp0gcfo5ubGvXv3CAgIyLM2z5w5Q2xsbLZ/n/39/enRo0eBDqK/q3R0dFAoFLRq1YoG\nDRrkaR5JIYQQIrcqVKiAq6srrq6upKamsmPHDmbMmEGVKlVeer6uWLEiCQm5f73U39+f2rVrZ0kB\n5uPjQ5MmTdTrEtjb2+Pt7c2JEyey3OjOmzePI0eOsH79evVrt3lhuJMxHutPvLKOEEIIUZSMGDHi\npTmYc6Krq4ujoyN+fn507twZX19f2rZtm+OD58qVKzNjxgzMzc25dOlSlnWa8pqc14uml85gFqKo\nunbtGlZWVmzZsoVjx44xZswY9eCySqXil19+wdLSkqlTp/Lrr78WyuBycHAw69atQ6FQ5MmifpmW\nLl3KyJEjNVaahf+lx/iQ8y+/qFKlSmzfvp3Jkydz5MiRwg5HCCHEB05XV5du3bpRr1494uLiXjrA\n3K5dO2JjY7l+/for201PT0ehUNC7d2+N7Q8ePGDnzp1cunQJCwsLLCwsGDBgAFpaWvj6+qrrZWRk\nMH36dI4dO8bmzZvz/K3G1k0+oZ+tYY7l/WwNad3kkzztUwghhHif9erVi8jISM6dO8fOnTtfOWE0\nM51GQYx9yHm9aJIBZvFBUalUrFmzhhYtWtCxY0eOHDlCvXr11OXJycn069ePFStWEB4ezoABAwol\nznPnzjFkyBACAgLy9Cbt9u3bKBSKbJ+CxsTEUKxYMYyN5Unh8wwNDdm8eTM9e/bk6tWrhR2OEEKI\nD0hycjKLFy/m4sWLPH36lPT0dHbv3s3Fixdp3ry5enGftLQ0UlNT1Z+MjAy6du1K8+bNGTlyJCdO\nnCA1NRWlUsmJEyeYMGGCRj8HDhwgJSWFbt26aWzftm0bxYoVIzQ0lG3btqk/7u7u7N27l6SkJNLT\n05k4cSJnz55l48aNVKpUKV9+i7429bO9GXXuaCgrzQshhCiS3jQHM/xvsb/Ro0dToUIF2rZtq9Hu\n5s2bSUxMBODmzZu4u7tjamrKJ58UzMCunNeLnlylyBCiKPj3338ZMmQICQkJHDhwgMaNG2uUnzp1\nit69e2NlZcXx48cpVapUocR5//59HB0dWbBgQa5zLOWWt7c3PXr0QF9fP0tZ5uJ+kh4jKxsbG77/\n/nvs7Ow4duwYZcuWLeyQhBBCfABKlChBYmIio0eP5vbt2xQvXpzPPvuMGTNmYGtrS1BQEDdu3MDI\nyEhjvwkTJjBkyBB+/vln1q5di5ubG//88w96enrUqVMHFxcXjfq+vr507tw5S1oLf39/evXqxWef\nfaax3cnJCS8vL4KDg2ncuDE7duxAV1cXS0tLdZ0WLVrw888/5+nv0demPjU/Kfv/C/9oMaK7EWaN\nZYaTEEKIomnVqlVZzqVLliyhXbt2wLO1g152/967d28mT57M6NGjs9Q7fPgwq1at4vHjx1SoUIF2\n7doxZ86cvD+Il5DzetGipXqbRyLvofj4eL788kv279+f5WJZFE0qlYqtW7fi6urK8OHD+f777zVS\nTqhUKlasWMGcOXNYsWIFvXr1KrRYMzIycHBwoEaNGqxYsSJP205NTaVmzZrs3bs3y+C6SqWiXr16\n+Pj4YGpqmqf9FhUqlYqRI0dy/fp1QkJC0NbWLuyQhBBCiPeaXJcLIYQQ7x85f4vsyAxmUaTdvn2b\nESNGcO7cOcLCwrIsXJOUlMQ333zDjRs3iIiIwMDAoJAifWb27Nncv38fT0/PPG87c5GeFweX4dkK\n8enp6TRr1izP+y0qtLS0WLZsGR07dmTKlCksWrSosEMSQgghhBBCCCGEKHSSg1kUWcHBwRgZGVG7\ndm1OnjyZZXD5+PHjmJiYULNmTY4ePVrog8tBQUGsX78ef39/SpQokadtq1QqPD09cXV1zbY8c3E/\nSY/xciVKlMDf35+QkBDWrl1b2OEIIYQQQgghhBBCFLpcDTDv2LGDsWPHMmPGDGJjYzXKEhMT+fLL\nL/MlOCHeRFJSEgMGDGDixIkoFAoWLFhAyZIl1eUZGRksXLgQBwcHli1bhqenJ7q6uoUYMfz1118M\nHTo0zxf1y3To0CFSU1OxtbXNUqZSqfD396dnz5553m9RVLFiRUJDQ5k2bRqHDh0q7HCEEEK8B7y8\nvDA0NCQ4OFhju6WlJSEhIervCQkJdOnShXHjxpGWlsatW7cYMWIElpaWGBoaatTNlJ6ezrJly7C0\ntMTExARra2sOHz6sLt+4cSM9e/akadOm2NjYZNl/06ZN2Nra0qJFC1q2bImzszPHjx/XqHP37l2m\nTJlCq1atMDU1xdHRkf/++w+Aq1evMnbsWNq2bUuzZs3o2rUr/v7+b/V7vUxE7L8MdNvFQLddRMQm\n5Fs/QgghxNvq378/hoaGREdHa2y3trYmKCiI+Ph4DA0NMTEx0fhERUWp9/fy8lLvd//+fZydnXFx\ncSE5OZnIyEiN/Vu1asWwYcO4fv26ep/AwMBsz/8hISEYGhrmeWrO1yHn9KLllQPMwcHBTJw4EZVK\nxd9//03fvn1RKBTqcqVSyT///JOvQQqRW7t378bIyIiyZcvyxx9/8MUXX2iU3759m65duxIcHExU\nVBT29vaFFOn/3Lt3D0dHRxYuXEiLFi3ypQ9PT0++/fZbihXL+lf+r7/+4tGjR/nWd1FUv359fvvt\nN3r37s3ly5cLOxwhhBDvsIyMDPz9/WnQoAG+vr5ZyjPfHjp//jy9e/emdevWLF26FB0dHYoVK0ab\nNm1YtGgRH3/8cbZvGs2aNYtjx46xdu1aYmJi2LJli8ZbWVWrVmXo0KEMHz482/jat2+Pr68vUVFR\nHDt2DCsrK4YPH05aWhrwbA2Hr776Cl1dXXbv3s3JkydZvHgxH330EQApKSmYmZkREBDAqVOncHNz\nY8GCBezdu/etf7sXbd1zHo/1USQmp5KYnIrH+hNs3XM+z/sRQggh8kr58uX58ccfNba9uDjfrl27\niImJUX+evzfPrJeQkICzszOVKlVi3bp16oXntbW11fsdPHiQcuXKMXny5FfG5evri6GhIQEBAWRk\nZOTFob4WOacXPa8cYN6wYQNTp05l+fLlbNy4kYULF/LDDz/k68wEIV5XSkoKw4cPZ+jQofz666+s\nWLGC0qVLa9Q5dOgQzZo1w9jYmIMHD/L5558XUrT/k5GRgYuLC7a2tnz11Vf50selS5eIiIigf//+\n2ZZLeow3Y2VlxcyZM7Gzs+P+/fuFHY4QQoh3VHh4OElJSSxcuJDTp09z8eJFjXKVSkVkZCT9+/fH\nxcWF6dOnq8v09fXp168fzZo1y/Yh8YtdLtAAACAASURBVJUrVwgICGDevHnUqlVLvc+nn36qrmNr\na4u1tTVVqlTJNr7q1atTvnx54Nl1iZaWFpUqVaJ48WdLtQQFBfHgwQNmzZqlrmdgYICenh4ARkZG\n9OvXD319fQBMTU1p06YNkZGRb/R75WTrnvNs2R2XZfuW3XFyQyqEEOKd1atXL27evMn27dvfuI0L\nFy7Qu3dvzMzMWLZsGTo6OtnWK1WqFJ07d85yrfGiy5cvc+rUKRYtWsT9+/c13nwqCHJOL5peOcB8\n7do1OnTooP7eqVMnVqxYgYeHBwEBATIoJQrdoUOHMDY2Ji0tjT///BMrKyuNcqVSyZw5c+jTpw9r\n1qxh3rx5eZ7j+E3NmjWLlJQUfvrpp3zrY+nSpQwZMkQ90+hF/v7+9OjRI9/6L8pGjhyJpaUlffr0\nIT09vbDDEUII8Q7y8/PDxsaGOnXq0Lx58yyzmPft28eIESP4/vvvGTp06Gu1HRkZiZ6eHjt27KBt\n27Z06NCB2bNn8/Dhw9dqJzo6mhYtWmBsbMyGDRtYvXq1ekA7MjKSzz//nMmTJ9OqVSs6derE+vXr\nc2zr8ePHnD59mgYNGrxWDC8TEZuQ7Y1opi274+TVWiGEEO+kUqVKMXbsWH766SeePn362vvHxMTg\n4uKS5SF0dh48eEBoaGiW9ade5Ovri6mpKXXq1MHGxgYfH5/XjutNyTm96HrlAHOpUqVISkrS2PbF\nF1+wZMkS3N3dCQoKyrfghHiZx48f4+rqSr9+/Vi2bBnr1q2jXLlyGnUSEhKwsbHhwIEDnDx5Mtsc\nxIUlMDCQDRs24Ofnl28D3vfu3eO3335j5MiR2ZafO3eOe/fuYWZmli/9fwiWLFlCeno6kyZNKuxQ\nhBBCvGNu3brFoUOHcHBwAMDe3p6QkBB1+gmAY8eO8cknn9C+ffvXbj8pKYkHDx5w5coVdu7ciZ+f\nH3FxccyfP/+12mnevDlRUVGcOHECKysrhg0bxpMnT9R9REZG0rRpU44ePcrChQvx9vYmNDQ0SztK\npZLJkydTrVo1HB0dX/t4cuId+Eee1BFCCCEKmpaWFt27d6d06dJs2LAhSxlAly5daNGiBS1atMDJ\nyUmjzsmTJ9HR0aFLly7Ztq9UKtX7tmzZkujoaEaNGpVjPKmpqWzbtk19beLg4EB4eDi3bt16m8PM\nNTmnF12vHGBu0KBBloU+ANq1a8fixYtZsmSJzGIuwm7fvo2rqyvW1tY4OTkxdOhQrl27hp2dnUa9\n5cuXs27dOgB+/PFHOnXqhL29PaNHjyYlJQWA+Ph4jIyMcHR0xNHRkVmzZqn3t7S05N69e+rvkZGR\nOeYKzCw3MTHh5s2b/Pnnn3Tt2jVLnT179mBqakq7du3Yu3cv1apVe6vfIi/99ddfDBs2LN8W9cv0\nyy+/0LlzZ41XZZ8XEBBA9+7ds33tVuRO8eLF8fPzY+fOnfz888+FHY4QQoh3iEKhoEKFCuoHuR07\ndiQ1NZWwsDB1nSlTplC1alVcXFy4c+fOa7WfmQ7s22+/pXTp0ujr6zN48GD279//RvGWKVOGadOm\nqQeVM/v4+OOP6d+/P8WLF6dx48bY29tn6ePp06eMHz+eO3fu4O3tjba29hvFIIQQQhQ1xYoVY9Kk\nSaxevVpj3EOlUgEQFhZGVFQUUVFRBAYGauz79ddfY2FhgbOzM1evXs3Stra2tnrf2NhYJk2axIAB\nA3JcK2jnzp08fvxYPfmuVatWVK5cWdLgirf2ylGlvn37kpiYmG2ZlZUVCxcufOX0e/F+UqlUjB49\nGjMzM/bu3UtgYCATJkzI9ubn+YcMFhYWhIWFERISQs2aNVm9erW6rEaNGgQHBxMcHIybm1uOfb/s\nocWcOXOwt7fH3d2drVu3UqlSJY3y9PR0pk2bxjfffMOWLVuYOXPmO3WTUxCL+sGz32H58uW4urrm\nWCcz/7J4OxUqVCA0NJQZM2Zw4MCBwg5HCCHEOyAjI4OAgADu3btH27ZtsbCwoFOnTiiVSo00GSVL\nlsTb25vq1avj7OzMzZs3c91HTmko3mbyh1KpJCMjQz14nV0fKpVK4+F0amoqo0ePJikpiXXr1qnz\nM+eV4U7GeVJHCCGEKCxt27alSZMmrFix4rX209bWZv78+XTo0AEXFxfOn885R7G2tjZdu3alZMmS\nhIeHZ1vHz88PpVJJ586dsbCwoG3btiQlJaFQKApksT85pxddrxxgtrKyYurUqTmWd+7cmU2bNqm/\nb9++/bXzvol30/HjxylRogS9e/dWb6tfvz4ff/xxlrqZT97gWQqVzJsOY2PjXN8oPd/G839+Udmy\nZfnjjz/o1atXlrIbN27Qvn17YmJiOHXq1Bu9bpqfCmJRv0yBgYHUrFkTU1PTbMsvXrzIrVu3MDc3\nz9c4PhR169Zl69at9O3bl0uXLhV2OEIIIQpZeHg4N2/exNfXl23btqk/3t7enD59mgsXLqjr6ujo\nsHz5cho3bky/fv24ceOGuiw1NZXU1FRUKhVPnz4lNTUVpVIJQIsWLahXrx7Lli3j8ePH3L17lzVr\n1mBjY6PeX6lUkpqaSnp6OiqVirS0NFJTU9XlW7du5datW6hUKhITE3F3d6dq1ao0adIEACcnJ3XK\nLaVSSVxcHNu3b8fa2hqAhw8fMnjwYNLT0/nll18oVapUnv+WrZt8Qj9bwxzL+9ka0rrJJ3nerxBC\nCPG2nh/bmDx5Mr6+vjlO4nzZ/rNmzcLBwYEBAwbw559/ZltXqVSyY8cO7t27R/369bOUX7p0iVOn\nTrFy5UqNaxN/f3/u3LnDoUOHXvPoXp+c04uu4nnd4IwZMwgJCVHPehDvr4sXL9KoUaNsy65fv66R\nW+/OnTsMGjQoS72AgACNXEHx8fE4OjpSpkwZxo0bpzH7fcCAAeqZxo8ePaJ27drZ9j1u3Lhst4eG\nhjJ48GAmTJjAxIkT38m0DwWxqF8mT09PJk+enGO5QqHAycnpnZrd/b6ztLTEzc0NOzs7IiIiKF++\nfGGHJIQQopD4+vpiZWVFw4YNNbZbWFjQtGlTfH19NWYaa2trs2jRImbMmEG/fv1Yv349BgYGGBs/\nm8WjpaXFtGnTmDZtGqNHj2b06NFoaWnh7e3N7NmzMTc3p0yZMtja2jJhwgR1u6tWrWLlypXqNoyM\njNDS0uLcuXMAnDlzhlWrVvHgwQPKli1LixYtWLt2Lbq6ugBUq1aNn3/+mXnz5rFo0SKqVKnCmDFj\n6NSpE/AsJVlUVBSlSpXSWNPBwcGB2bNn59nv2dfm2Y3yiwsDOXc0pI911ptoIYQQ4l3w/Lne0NCQ\nrl27EhwcnG35q/afPHkyH330EV9//TWrV69GS0sLpVKJiYmJuu6nn37KnDlzaN26tXpbZhs+Pj40\natQoy0S8SpUqYWtri6+vLx06dHir480NOacXTVqql00VfQMmJiaEhIRQvXr1vGw2z8THx/Pll1+y\nf/9+Pvvss8IO5522adMm4uPj+e677zS2x8fHM2LECI3FXVasWMFHH33EN998o97m5eXFX3/9xfLl\nywFIS0vj8ePHlCtXjrNnzzJq1CjCwsIoXbo0lpaWBAYGqgfkTpw4wbp16/D29n5lnGlpaUydOpXA\nwEC2bNnyzs7IDQwM5NtvvyU6OpoqVarka1/Hjx+nX79+XLx4MccBZFNTUxYtWlQgJ5APzbhx44iL\niyMsLIzixfP8OZ4QQghRJLzJdXlEbML/L/6jxYjuRpg1lllOQgghREHKq3E1OacXLTLyIbLw8vIi\nLCyMx48fk5iYyLlz50hOTubRo0ckJiZSpUoV4uPjOX36NE2bNsXBwQGlUqmx2mnfvn05c+YMtWrV\nolu3bnz//fc0b94cHR0d+vfvz+3bt7l37x52dnZ06NBB/dpHamoqLi4uJCUlcffuXRYvXqwxC+dF\nV65coXfv3nz66aecOnWKihUr5vvv8yYyF/XbuXNnvg8uw7PZy2PHjs1xcPnKlSvEx8fTtm3bfI/l\nQ7R48WK6du3K+PHjWbZsWWGHI4QQQhQZrZt8Iq/OCiGEEEWAnNOLlncvh4AoVDExMRw6dIigoCD2\n799PrVq1aNeuHcHBwcydOxdDQ0Pc3d2pUaMGTZs25fLly+jq6nLr1i2ePn0KwOHDh7l48SJubm6E\nhIQwdepU3NzcSExMVOcMnDRpEmXLlsXf3x8dHR31woG6urps3LiRH374gRYtWhAZGUl0dHS2sfr7\n+2NmZkb//v0JCgp6ZweXMxf1W7RoUYEsiHn9+nX27dunMZv8RQEBAXTr1k3SY+ST4sWL4+vry759\n+/Dy8irscIQQQgghhBBCCCHyjQwwCw137tyhfPnylChRAgBvb29iY2OxtrZm6tSpXLlyBX19fXX9\n7du306VLF6pXr65e2Gzu3Lmkp6ezYsUKHB0d2b59O9evXycqKgoHBwfOnDnDokWLcHd3p1KlSkya\nNAmlUsnFixcBKFWqlDpHkFKpzDaPbWJiIj/++CM7duxg7Nixb7Vaen5SKpU4OzvTsWNHBg4cWCB9\nLl++nIEDB1K2bNkc6/j7+9OjR48CiedDVa5cOUJDQ3Fzc2Pfvn2FHY4QQgghhBBCCCFEvpABZqHh\niy++4ObNm9ja2uLm5sbff//NkiVL2Lt3L/PmzcPIyIgaNWqo8y/v3LmTTp06MWnSJFJSUoBni710\n6tSJKVOmEBwcTLt27ahbty62trZs376dxo0bs2jRInVi+WLFitGhQwdu374NPBuU/eGHH4iKiqJV\nq1bUqVMnS5wVK1YkOjq6QGYEv41Zs2bx8OFDFi9eXCD9PXjwgF9//ZWxY8fmWOfvv//mypUrtGvX\nrkBi+pAZGBjg4+ODs7MzFy5cKOxwhBBCfKBiY2MZOXIkrVu3xtTUFFtbWzw8PNTXXteuXWPixIlY\nWFhgYmKClZUV06ZN4++//waePbz++uuvs23b29sbExMTjY+hoSFz587Nl2OJiP2XgW67GOi2i4jY\nhHzpQwghxIfHy8sLQ0ND9QJ8+/fvp2nTpqSnp6vr/P777xgaGrJ161aNfTt06MDmzZsBCAsLo1+/\nfpiamtKoUaMs/cTFxTF48GAsLCwwNDTk5MmTGuWnT59m6NChfPHFFzRv3hwnJ6csE5bu3r3L6NGj\nadasGa1bt2bRokU8v7zaq2IACA4OxsrKiqZNm9KrVy/Onj37Gr/W25PzedEjA8xCw0cffURgYCBz\n5syhYsWKuLq6EhQUlG3d2NhYKlasSJUqVWjZsiVxcXEkJycDoFKpWLBgAba2tri6ur5yFXGVSqWe\nhaytrc22bds4fPgw0dHRREZG5ukxFpTAwEA2bdqEn5+fekZ4flu/fj3t27enZs2aOdYJCAjA0dGx\nwGL60LVv354ffvgBOzs7kpKSCjscIYQQH5ijR4/i7OyMgYEB27Zt4+TJk2zevJkKFSoQFRXF+fPn\n6d69Ozo6Ovj4+BATE0NAQACNGjXi8OHDr2x/+PDhxMTEqD9BQUFoaWnh4OCQ58eydc95PNZHkZic\nSmJyKh7rT7B1z/k870cIIcSHJSMjA39/fxo0aICvry8ArVq14unTp8TExKjrRUREULduXY4fP67e\n9vfff5OQkEDr1q2BZ2+yuri4MG3atGz7KlGiBLa2tnh7ewNkeRv7/v37dOnShbCwMKKjoxk5ciQT\nJkwgNjZWXWfixIkUK1aMw4cP4+fnx969e1mzZo26/FUxREdH4+bmhru7O1FRUdjY2DB06FAePHjw\nOj/bG5PzedGU6wHm//77j4SErE8VEhIS1Plz4VkO3+rVq+dNdKJQFCtWjJYtWzJmzBhmzJjB7t27\ns60XFhbG5cuXsbS0xNramgcPHqjramlpMWXKFHbv3s2UKVNYuXJljv0plUouXLiAgYGBxvYyZcrQ\nrl07zpw5k3cHV0DOnj3LsGHDCAgIKJBF/eDZSXHp0qW4urq+tJ5CoaBnz54FEpN4ZvDgwXTp0oWe\nPXuqc5ULIYQQBcHNzQ07OzsmTJigvibR19dnxIgRdO7cmXnz5tGkSRM8PDzUK8GXK1cOZ2dn+vfv\n/9r9+fr60rBhQ5o0aZKnx7F1z3m27I7Lsn3L7ji5KRVCCPFWwsPDSUpKYuHChZw+fZpLly6hp6dH\nkyZNiIiIUNc7fvw4Y8aM0ZgEFxERQdWqVdXjGRYWFnTu3Fl9Tn2RgYEBPXv2pHHjxtmWt2vXDgcH\nB3WqUCsrK42Zzjdu3CAiIoJJkyahp6dH9erVGTJkCD4+Puo2XhWDv78/NjY2mJubU6JECQYPHoyu\nrm6BpHaU83nRlesB5smTJ3PkyJEs28PDw5kyZUqeBiUKz9WrV7l27Zr6+19//ZXtP0oZGRns2rWL\n7du38/vvv/P777+zcuVKtm/frq6T+YqGi4sLN2/e1Hjyl1n29OlTFi9ezCeffEK9evVITExUz4J+\n8uQJx44do2HDhvlxqPkmKSkJR0dHFi9eXKApPLZv306FChUwNzfPsU58fDznz5/H0tKywOISzyxc\nuBBdXV2+/fbbwg5FCCHEB+Lq1atcv36drl27Zlv++PFjoqKicix/XWlpaQQGBtKnT588aS9TRGxC\ntjejmbbsjpPXa4UQQrwxPz8/bGxsqFOnDs2bN1cP1pqZmakHmO/cuUNCQgJffvkl5cuX59y5c8Cz\nAebM2cv54fbt21y8eBFDQ0MAzp8/T5kyZTQmdjZs2JB//vmHhw8f5qrN8+fPZ0mdYWhoSFxczufa\nvCDn86It1wPMZ8+epVmzZlm2m5qaakzVF++3R48eMXXqVLp06YK9vT1Xr15l9OjRgOarG9HR0Xz8\n8ccaC/41b96cy5cvq/P5PV9/xIgRGrOYJ06ciL29PXZ2dqSmpuLl5QU8+8dz4MCBODg40LNnTzp0\n6JCv/1jntcxF/Tp37syAAQMKtG9PT0++/fbbly54GBAQgL29vaTHKATa2tps3bqVgwcPvnRGvxBC\nCJFXEhMTAahatWq25cnJySiVyhzLX9euXbtIT0/PswHrTN6Bf+RJHSGEEOJFt27d4tChQ+rUTvb2\n9oSEhJCamkrr1q2JjY3l0aNHHD9+nObNm6Otra0x8BwZGZlvYxaPHj1izJgxdOjQATMzM+DZuktl\nypTRqJf5PbcpLh4+fJiljbJly+Z7igw5nxdtxXNb8enTp2RkZGTZnp6ezpMnT/I0KFF4GjVqpPFq\nxfNatmxJy5Yt1X9+sZ62trZ6lvu8efM0ymxsbLCxsQFg06ZNOfZfv379HHM+vw9mzpzJo0ePWLRo\nUYH2e/r0aS5evPjK1BcKhYKpU6cWUFTiRWXLliU0NBRzc3Pq1auHtbV1YYckhBCiCKtYsSLw7Oa5\ndu3aWcrLli2LtrY2N2/ezJP+fH19sbe3p1SpUnnSnhBCCJHfFAoFFSpUUA/gduzYkblz57Jjxw66\ndOlCiRIliIqK4vjx4+o6rVq1IigoCHNzc+7du/fSt4jf1IMHDxg2bBj6+vr8+OOP6u16enqkpKRo\n1M38Xrp06Vy1Xbp06Sxt3L9//6VrOQnxKrmewfz8aprP27ZtG/Xr18/ToIR4HwUEBLB58+YCXdQv\nk6enJ6NHj35pv//++y9nz57FysqqACMTL6pduzZ+fn64uLjk+ytIQgghPmy1atWiRo0aGinMnleq\nVClatmxJWFjYW/d16dIlTp48mefpMQCGOxnnSR0hhBDieRkZGQQEBHDv3j3atm2LhYUFnTp1QqlU\n4uvri46ODs2aNeP48eNZBphPnjxJeHg4BgYGGm9254WkpCS++uorPv74Y5YuXUrx4v+bG1q/fn1S\nUlK4ceOGetvZs2f57LPP0NPTy1X7hoaGnD17Vv1dpVJx7ty5fB/bk/N50ZbrGcyjR49m6NCh3Lhx\nQ/105ujRo+zfv1+d3qCg9O/fn9OnT2v8JVuyZAnt2rUr0DiEyHTmzBmGDx/Orl27CmxRv0w3b94k\nJCQET0/Pl9YLCgqia9eu6OrqFlBkIidt27Zl3rx52NnZERkZqZ5hJoQQQuS1WbNmMXz4cCpXroyz\nszNVqlThzp07BAQEUL16daZOnYqzszPTp09n+PDhfPrpp6SkpBAWFsbTp0/VKb8yMjJIS0tTr6MB\noKOjo07N5ePjQ9OmTfPl5rR1k0/oZ2uYY97GfraGtG7ySZ73K4QQomgLDw/n5s2bKBQKjXRR586d\nY/DgwVy4cIHWrVuzfv160tPT1XmQK1asSLVq1diwYQOdOnXSaDMjI4OnT5+qF3fPPHc+fx+empqq\nPp+mpaWRmppKiRIlKFasGLdv3+brr7+mcePGeHh4UKyY5rzQ6tWrY25uzsKFC/Hw8CApKYk1a9bQ\nu3fvXMfQs2dPBg8ejKOjI6ampmzYsIH09PR8f8NWzudFW65nMFtYWPDzzz9z+/Zt5s+fz/z587l7\n9y6rV68ulIHdUaNGERMTo/7I4LIoLElJSXTr1o2ffvoJU1PTAu9/1apV9O3b95WDlAqFgh49ehRQ\nVOJVvvnmGxwdHenRo4f6xC+EEELkNXNzc7Zs2cKlS5ews7OjWbNmODs7k5SURKtWrahfvz4KhYIn\nT57Qp08fmjVrRrdu3fjrr7/o0KED8GxdjcjISIyMjDA2NlZ/du7cCTxbmDkkJCRfZi9n6mtTn362\nhlm2O3c0pK+NvE0phBDi9fn6+mJlZUXDhg2pVKmS+mNhYUHTpk3x8/PD3NycO3fuqNOFZjIzM+Pu\n3btZ0mMEBwdjbGzM4MGDycjIwMjIiKZNm/Lvv/8CEB8fj7GxMU2bNkVLS4uvvvoKY2NjQkJC1DFd\nunSJ3bt3Y2pqiomJCSYmJvz888/qPhYtWoRKpaJt27b07NkTa2trhgwZkusYTE1NmTVrFjNmzKBF\nixbs3buXn3/+OdcpNt6GnM+LLi3V89MQ3hP9+/fH3NycESNGvPa+8fHxfPnll+zfv5/PPvssH6IT\nHxKlUknXrl2pX78+S5YsKfD+Hz9+TM2aNTl8+PBLZwzdunWL+vXrc/PmTUqWLFmAEYqXUSqVODo6\nUq1aNby9vV+6QKMQQghR1LzJdXlEbML/LwCkxYjuRpg1lplOQgghREHKi3E1OZ8XPblOkZHp1KlT\nXL58GXiWS7QwZmwCbNiwgfXr16Ovr4+9vT3ffPONRsoMIQrCjBkzePLkCQsXLiyU/n/77TeaN2/+\nytdRg4KC6Ny5swwuv2O0tbXZsmUL5ubmLF++nLFjxxZ2SEIIIcQ7rXWTT+T1WSGEEOI9J+fzoifX\nI7IJCQmMGzeOP//8k7JlywKQnJxMkyZNWLZsGZ988vb/YUydOjXbhQQzjRgxgnHjxjFhwgQMDAzQ\n09Pjzz//ZOLEiTx48IDx48e/dQxC5JZCoWDLli1ERUUV+KJ+8CwR/5IlS3I1c1qhUDBy5MgCiEq8\nrjJlyhAaGkrr1q2pV68eHTt2LOyQhBBCCCGEEEIIIXIt1wPM06dPR6lUEhYWhoGBAQCXL19mypQp\nTJ8+nbVr1751MDNnzmTq1Kk5lmfOvmzatKl6m7GxMePGjWPRokUywCwKzJkzZxgxYgS7d+/O8xVj\nc2vv3r0UK1aML7/88qX1bt++TXR0dJbFB8S7o2bNmvj7++Pk5MShQ4do0KBBYYckhBBCCCGEEEII\nkSu5HmCOiopi8+bN6sFlAAMDA2bOnImLi0ueBPPRRx/x0UcfvdG+72EqafGeSkpKwtHRkZ9++olm\nzZoVWhxLlizh22+/fWXe3m3btmFra0upUqUKKDLxJiwsLFi4cCF2dnZERkZSqVKlwg5JCCHEW+rf\nvz+nT5+mePHiaGtrU716dUaMGIGNjQ2WlpbcuXMHbW1tSpQogYGBAa6urupFhAwNDSlZsiRaWlro\n6urSqFEjJk2apF7B/vvvv+ePP/7g6tWrdOvWjblz52r0/Xz7xYsXp1atWowZM4Y2bdqo62zcuJHQ\n0FAuXrxIlSpV2LNnj0Yby5cvx8vLS73qPICLiwsTJkwAIDAwkGnTpqmvMUqWLIm5uTnff//9Kxcf\nflMRsf/iHfgnAMOdjOX1WiGEEEXai2uQPX78mDZt2lChQgX27t2bpf7ff//NqlWriIiIICUlhXLl\nylG3bl169eqFtbU1AHFxcSxatIi4uDju3LnDb7/9VuDpb+V8XvQUy23FypUrZ5vjWFtbm8qVK+dp\nUC+TkpLCgQMHePjwISqVir/++osVK1bQuXPnAotBfLiUSiX9+vWja9eu9O/fv9DiOHfuHKdOnaJf\nv36vrOvv70+PHj0KICrxtgYOHEiPHj3o3r07aWlphR2OEEKIPDBq1ChiYmKIjIykS5cuuLq6cu3a\nNQB++OEHYmJiCA8Pp1GjRgwfPpwHDx6o9123bh0xMTHs27cPPT09jQWuDQ0N+e6777C0tMzxYXNm\n+0ePHsXU1JSxY8eSnJysLq9atSpDhw5l+PDhOcZvZmZGTEyM+pM5uJypRo0a6rJdu3aRmJjIDz/8\n8CY/1Stt3XMej/VRJCankpicisf6E2zdcz5f+hJCCCHeFc+f58PCwqhQoQJJSUkcO3ZMo9758+dx\ncnJCW1ubzZs3c+rUKfbs2cOAAQM0BqNLlCiBra0t3t7eWdovCHI+L5pyPcA8duxY5s2bxz///KPe\n9s8//zB//vwCXZjq6dOneHt7065dO0xNTXF1dcXOzi7Lxa4Q+aGwF/XLtHTpUoYPH/7KRfvu3r3L\n8ePH5QHMe8TDw4Py5cszcuRIeTNDCCGKEG1tbfr27YtSqeTChQsaZbq6uvTq1YtHjx5x/fr1LPvq\n6enh6OhIQkIC9+/fB57NaPriiy/Q09N75flCR0cHJycnHj9+rNG+ra0t1tbWVKlSJcd9X9X28+Xl\nypXDysqKixcvvnSfN7F1z3m27I7Lsn3L7ji5KRVCCPHB8PX1xdHREWtra3x8fDTKPDw8MDY2xsPD\ng88//xwtLS10dHRo06YNCxYs6pT/IgAAIABJREFUUNczMDCgZ8+eNG7cuKDDl/N5EZbrFBmrV6/m\n5s2bWFlZqWcs37lzh5IlS3Lnzh1Wr14NPHvysWPHjvyJFqhYsSK+vr751r4QOSnsRf0y3b17F19f\nX+Lisv6j/KKQkBCsra0pXbp0AUQm8kKxYsXYvHkzX3zxBUuWLMHV1bWwQxJCCPEWMgdg09LS+O23\n3yhRooQ6zUVm2aNHj/D19aVs2bLUrFkzy773798nKCiI6tWrU65cudfu+/Hjx/j5+VGuXDlq1aqV\n6/21tLQ4ffo0ZmZmlC5dGnNzc1xdXXNMf5GYmMiePXto3rx5rvvIjYjYhGxvRjNt2R1HzU/Kyuu1\nQgghirS4uDhiY2P56aef+Pfffxk0aBB3796lUqVKPHnyhOjoaNzd3Qs7zBzJ+bxoy/UAc25nQBb0\n1HohCsK7sKhfptWrV+Po6EjVqlVfWVehUBRqKg/xZvT09AgJCaF169bUr19fZqALIcR7zNvbm3Xr\n1lGiRAlq1KjB8uXL+fzzzwGYNWsWc+bMQUdHh3r16rF69WqN9UiGDBmCtrY2JUuWpEmTJupXWXMr\ns/0HDx5QtmxZNm7c+FoPnTt27EiPHj34+OOPiY+Px93dnZEjR2rMmIqPj6dFixbAs1R2tWvXzpIP\n+m15B/6RqzpyQyqEEKIo8/HxwcTEhOrVq1O9enX09fUJCAhg6NCh3L9/H6VSqTFOcO7cOQYMGABA\namoqu3fv5pNPCu9cKefzoi3XA8xjxozJzziEeGdlLurn6elZqIv6wbPZTytXrszVWwL37t3jyJEj\nWV6bEe+HGjVqEBAQgIODAwcOHKBRo0aFHZIQQog3MGLEiBxzHLu7u2NnZ5fjvmvWrHmra4/M9m/f\nvs2YMWNYs2bNa6X5qlOnjvrPn332GXPnzqVt27bcuHGD6tWrq7dnLg6YlpbGxo0b6dWrF2FhYfm2\n0J8QQgjxoXn06BGhoaEa6WG7du2Kn58fQ4cOpWzZsmhra5OQkKAub9CgAVFRUdy6dYt27dpJCkaR\nr3Kdg1mID5FSqaRv377Y2dnh4uJS2OHg5+eHoaEhxsbGr6wbEhJChw4dKFOmTAFEJvJD69at+emn\nn9SDA0IIIUR2XvUGob6+PvPnz2fnzp1ER0fnWxw6Ojr07duXpKQkTp48mWftDnd69XVPbuoIIYQQ\n7yOVSkVYWBgPHz5k6dKlWFhYYGFhga+vL/Hx8Rw5coRSpUrRvHnzbCejvSsDy3I+L9pkgFmIl5g+\nfTppaWmFvqgfPDspeHp65jonr0KhoEePHvkclchvLi4u9O3bFycnJ1JTUws7HCGEEK8pv27q0tLS\nSE1NJT09nfT0dNLS0khLS8uxfs2aNXFwcGDZsmXqbUqlUt2GSqVSt5lpz549JCYmAnDr1i1mzZpF\n48aN1bOXX/T06VN8fHwoXry4xuznt9W6ySf0szXMsbyfraG8TiuEEKJI8/X1xd7enh07drBt2za2\nbdvGjh07MDc3x8/PD4DvvvuOP/74g2nTpnH9+nWUSiVpaWmcOnUqy8Po1NRUnjx5AvzvmiIjIyNf\nj0HO50VbrlNkCPGh8ff3Z+vWrURFRVG8eOH/VTly5AgPHjzIVT7e5ORkDh48yKZNmwogMpHf5syZ\nQ48ePRgxYgRr166VXPdCCPEeya9/swcNGkRUVJT6e1BQEC1btmTjxo057jNixAg6duxIZGQkrVq1\nYtWqVaxcuVIdp5GREVpaWpw7dw54NsA8e/ZsHj9+TLly5fjiiy+YM2eOxrHduHEDExMTALS1talV\nqxZLlix5rcUEc6OvTX2ALIsDOXc0pI91/TztSwghhHiXaGn9H3t3Hh/T1T9w/DPZBLELtdNSIxWa\njUQVQUUlIQlNLbWkTSKxb1XSqlqqtocixBJrBSGJELGVqnoIkkjb2EJLSyyxBBE0keX3hyfzM2YS\nE52xxPf9euX1Mueec+735umTc++Zc79HwYkTJ5g2bRpVqlRRO/bZZ58xcOBAbty4gVKpJDIykpCQ\nEPr06cPdu3epWLEijRo1Ijg4mJo1awKP9k/o2LGjqu8BAwYAMH36dDw8PAx6LTKel1yK/Jdlrfxz\nkpqaSocOHdi7dy+1a9d+0eGIl1RycjLt27dn165dLzzvcgEvLy86duzIoEGDnlp33bp1rF+/npiY\nmOcQmXgeMjMzef/99/nkk0/U8m49rkmTJjRu3Jjc3FzefPNNZsyYgbm5OSEhIcTGxmJkZISRkRGT\nJ0+mWbNm9O3bl9TUVPbt26fqY9CgQcTFxZGUlERqaipdunThzTffVB338fHBxcWFYcOGcfHiRYyN\njXF2di40JiGEEKIwz3JfHpd85X+bBCkI7N4Mx6ay0kkIIUTJ5enpSa9evfD29n7RoajoY15NxvOS\nR+dlmdHR0Xz44YeUKlVKrTw7O5vt27cb/FsOIZ6X9PR0PD09+f7771+ayeVz587xyy+/6LwiWdJj\nlDwWFhZs3boVR0dHGjdujJubm0Ydc3NzoqOjARgzZgwbNmygefPm7N+/n82bN2Nqasrt27fVXqEu\nX748iYmJ2NnZkZGRwfXr19VW29WrV0/VZ4F//vkHX19fWrRowcOHDxkwYAC//PILbdq0MdDVCyGE\nEI84WdeQ12eFEEK8Fk6dOsXZs2d12oPpVSPjecmjcw7mcePGkZmZqVGemZnJuHHj9BqUKNmUSiUz\nZsxQfV6+fDnBwcEALFiwgDZt2uDh4YGHhwdz5swBoG/fvhw/fhyAixcv4uLiwsGDBzly5Ah2dnZ4\neHjQtWtXfHx8VLkCo6KiVK9xPt7vhx9+yDfffKM1J2LBpn5du3alT58+Bv09FMf8+fP57LPPKFu2\n7FPrZmZmsnfvXrp27focIhPPU506dYiKiiIoKOipde3t7fn777+5ceMGFStWxNTUFICKFStSrVo1\nVb0uXbqoNoLYvXs3nTp1emq+UHNzc1q0aAGAqakpVlZWpKWlPetlCSGEEEIIIYR4zMiRIwkICGD0\n6NE0biypI8TL719v8peeno6FhYU+YhGvCVNTU3788Udu3boFqOcmVCgU+Pj4EB0dTXR0NKNGjVI7\ndvXqVfz8/Bg3bhzvvfceAA4ODkRHR7N161asra0JCwsrst/t27dz5swZjh49qhHb7NmzycnJYebM\nmQa59mdx584d1qxZw5AhQ3SqHxsbS6tWrahUqZKBIxMvQsuWLfntt9+KrJOTk8P+/ftp3Lgx7733\nHlevXsXFxYVJkyap5esEcHJyIj4+nry8PHbs2KGR4/vChQuqL3w8PDxITExUO56RkcG+fftwcnLS\nzwUKIYQQRYhLvkz/STvpP2kncclXXnQ4QgghhEHMnTuX/fv34+Pj86JD0TsZy0ump6bI6Nu3r+rf\nQ4YMUdvsLC8vj3PnzmFvb2+Y6ESJZGJigre3N6tWrWLkyJEaxwtbPZmWlsbYsWMZNWoUzs7OWttl\nZmZSv359rf0UfM7KyiIrK4sKFSpo9OHu7s7AgQNfik39CqxYsQIXF5dCd2x/UkREBB999JGBoxIv\nUmEbRmVlZanSFdnb29OjRw9MTEyIiooiISGBI0eOMHLkSEaPHo2npycARkZG2NnZsW3bNrKysqhV\nq5Zan3Xr1tVIkVEgJyeHUaNG0a9fP8lpL4QQBlCweR7Aw4cPAVRvpCgUCo4dO0bfvn2Jj49n7dq1\navfkH3zwAYMGDcLT01O1mU/p0qXV+l+6dCkODg7ExcURHBzM2bNnycvLo2rVqri4uKju08aNG8e2\nbdtU5wawtbVl+fLlAOzYsYNFixZx+fJlKlSogJeXl85fjBfH+t0papsCTVt1lN4uStWGQUIIIcSr\nJCQkhHnz5mlsrte+fXtu3LiBsbGxqszPz49ly5apPhd1X/Drr79iYmKCsbExderUITAwkE6dOqn6\nHjFihMYbz4WV65uM5SXXU2fRCnaAjo+Pp169epiZmamOmZmZ8cEHH9C9e3fDRShKpN69e9O1a1f8\n/PzUyvPz81m1ahVbt24F4PPPP1etVB4/fjwjRoxQ/WEskJCQgIeHB7dv36ZMmTKqVc+PT8I93u/l\ny5dp06YNSqVSIy4rKyu9Xue/lZuby/z58wkPD9ep/r1799i9ezeLFy82cGTiZVSqVCmtk8FGRka0\naNGCFi1a8Pbbb7N582bVBLNCocDV1ZXBgwczbNiwYp1vwoQJNGjQgH79+uklfiGEEOqSkpJU//7q\nq6/Izc3lu+++06hXsWJFZsyYwaZNm1RlCoVC4wvJnTt3Ur16dbWyixcvEhgYyOTJk3F1dUWhUHDu\n3DlOnDih1penp6cq9djj/vzzTz7//HMWLFiAs7Mz586do1+/flSvXl2vX3g/+UBaoKBMHkyFEEK8\nSvLy8ti0aRNNmjQhPDxcY1+zb7/9Fnd3d7WyQYMGqf5d1H3B4MGDCQgIIDc3l5UrVzJy5Ei2b99O\nvXr1gMIXLBVWri8ylpdsT51gnjx5MgCWlpZ89tlnlClTxuBBiZLPwsICDw8P1qxZg7m5uaq8IJWF\nttdAnJyc2LJlC56enmpt7O3tVROqy5YtY9asWUyaNEltBfPj/ebk5DBs2DC2b9+ukQ7gZRMdHU3N\nmjVV+W6fZseOHbRs2ZIqVaoYODLxqjh//jwKhUK1sv/kyZMaq43t7e0JCAjA1dVV537nzp3LvXv3\nmDZtmj7DFUIIUYii8uN7e3uzefNmtm3bpnUT2KKcPHmSsmXLqq1YatiwIQ0bNtSp/dmzZ6lYsaLq\n7bI333yTli1bkpKSUqw4ihKXfEXrA2mBdbtOU79GedksSAghxCvjwIED3Lp1i6VLl+Lu7s7Zs2dp\n1KiRzu2ftm8OgLGxMb169WL27NmcOXNGNcH8IshYXvLpnIN56NChMrks9Kp///5ERERw//59tfLC\n/lD6+vpibW3N8OHDyc3N1Vqnffv2JCQkaD1W0K+JiQnvv/++Ri7al9HcuXO1phEpTEREBD169DBg\nROJlpu0b5/v37zNu3DhcXV3p2rUr58+f1/raso+PDxUrVtTo58kczGvXriUtLY0lS5bw559/4unp\niYeHBxEREYa7MCGEEEWuKipdujTDhg1jzpw5qldmdWVtbc39+/cZO3Yse/bs4coV7bkQC7s/c3Bw\nIDc3lz179pCXl8eZM2eIj4+nffv2xYqjKIujit57QNc6QgghxMti48aNdOrUiYYNG2Jvb6/x1vLT\nJpCLui8oaJudnU1YWBimpqZqb3DrMjmtbzKWl3w6J5q9desWc+bM4dChQ9y8eZO8vDzVMYVC8dRN\np4R4UoUKFfjwww+JjIxUpVkp6g+dQqHgyy+/ZPTo0Xz55ZdMnz5do05iYiJ169bVKH+83/z8fBIT\nE2natKkersJw4uPjSU1N1XhVpjAPHjxg586dzJ8/38CRiZfVsWPHNMreeecdNmzYoLX+Dz/8UGQ/\ntWvXLvRv++nThX/7LIQQ4vlSKBR0796dNWvWsHr1anx9fbXWK0iBAVCnTh2ioqKoWbMmGzduZPXq\n1cycOZOLFy9Sv359Ro8eTceOHYFH905btmxh165dqr6mTJlC586dqVKlCt988w2ff/452dnZ5Obm\n4u/vT6tWrQx/4UIIIcQrKC0tjf3797N06VIAunbtyqxZsxg7dqwqLe3EiRNVqakUCgWxsbFYWlrq\n1P/ixYtZsWIFpqam1KtXjwULFqjt6fR43wUyMzP1cWniNabzBPOECRM4efIk3t7eWFpaGjw3iyi5\nHv9v59NPPyUsLEzt2NP+25o+fToBAQHMmjWLtm3bqnIw5+fnU758eaZOnarRl0KhUOVgzsnJoXHj\nxvTu3dsAV6c/c+fOZejQoTpvOLhr1y7s7OyoVq2agSMTQgghxMvGyMiIzz//nNGjRxf6NlNsbKxG\nDmaARo0aqe6f0tPTWbx4MSNGjCA2NpZ69eqhUCjw8PDQmoN5//79TJ48mdWrV9OsWTNSU1MZPXo0\n8+bNY/jw4Xq5tgCv5kxbdfSpdYQQQohXQUREBJUqVcLR0RGAzp07M3XqVGJjY1V75UyePFkjB7Ou\nAgMDCQgIKPS4tr71+eaRNjKWl3w6TzAfPnyYpUuXYmtra8h4xGvg8VWWVapU4ddff1V9LmzH8cdX\nWpqamqp2LQcKTYnh6emp+uM8ZMgQg+xmbiipqans3LmTkJAQndtIegwhhBDi9damTRusra0JDg5+\n5j4qV67MsGHDWLNmDWfPnlXlayzsLbP9+/fTsmVLmjVrBjx6+8XNzY3IyEi9TTA7Wdegt4uy0NyN\nvV2UkrNRCCHEKyEvL4/IyEhu375NmzZtVOW5ubmEh4er5jBKGhnLSz6dJ5jLlStHhQoVDBmLEOJ/\nFi5cSN++fXX+/9w///xDbGwss2fPNnBkQgghhHgRikoj9vixsWPH8tFHH1GqVCmd+k1ISODUqVN0\n7NiR6tWrc//+fZYtW0bp0qVV6cSKOreVlRVz5szhxIkTvPPOO1y5coWtW7fqPRVZwc7yTz6Y9ums\npOcHsuu8EEKIV8OBAwe4evUqERERam8VnTp1Cl9fX86cOaNTP7reF7xMZCwv2XSeYPb392fJkiVM\nmzZN51f2hRDFd+/ePUJDQzl8+LDObX788UeaNWvGG2+8YcDIhBBCCPGiFJVC7PFjSqUSNzc3oqOj\ndWpfoUIFjh49SmhoKBkZGZibm9OkSROWLl2quq8oKoVZjx49SEtLY8SIEdy4cQMLCwvatm3LuHHj\ninuJT9WrU2Pq1yj/v02AFAR2b4ZjU1ntJIQQ4tURHh5Ox44dsbKyUitv3bo17777LuHh4TqlpNX1\nvuBlI2N5yaXI1/GrDV9fX3777TdKlSpFw4YNMTExQaFQkJ+fj0KhYNmyZYaOVS9SU1Pp0KEDe/fu\npXbt2i86HCE0hISEsHv3bjZv3qxzm/79+2Nvb8/QoUMNGJkQQgghhP7IfbkQQgjx6pHxW2ij81Lk\nqlWr0qFDB63HXuZvR4R4leTl5fH9998X6wub7OxsYmJi+O677wwYmRBCCCGEEEIIIYQQmnSeYJ4+\nfboh4xBCADt27KBs2bK8//77OrfZu3cvVlZW1KxZ04CRCSGEEEIIIYQQQgihyai4DY4fP8727du5\nd+8e8Chf7MOHD/UemBCvo7lz5zJy5MhivRWwadMmevToYcCohBBCCPGy69u3LyEhIcCjPMzvvvsu\nNjY2qp+CnMzjxo3jq6++Ah69BfX111/j4uKCra0tzs7OzJw5k+zsbLW+Q0NDadOmDTY2Nvj4+HDx\n4kXVsYSEBLy8vGjZsiV2dna4ubkRFhZmsOuMS75M/0k76T9pJ3HJVwx2HiGEEOJFSU5OZtCgQTg5\nOWFnZ4eLiwvTpk3j+vXrjBs3jqZNm2JjY4OdnR3t2rVj2LBhxMXFFdrfiBEjUCqVHDt2TK38l19+\nwdXVlebNm+Pu7s7BgwcNfWmAjOUllc4TzOnp6fTs2ZMePXowevRo0tPTgUcrm2fOnGmwAIV4XSQn\nJ3Py5Ek+/vhjnds8fPiQLVu24OXlZcDIhBBCCPEqePwL6hUrVpCUlKT68fDwUNUpqJebm0ulSpVY\nvHgxiYmJhIWFcfjwYbV7+61bt7JixQqWLFlCXFwcb731FoMGDSIvLw+AN998k4ULF3LkyBESExP5\n5ptvmD59OgkJCXq/vvW7U5i2Kp70jCzSM7KYtuoo63en6P08QgghxIty8OBB+vTpw1tvvcWWLVtI\nTExk7dq1VKpUifj4eBQKBZ6eniQlJZGYmEhkZCS2trYMHDiQH374QaO/3bt3c+fOHY3yixcvMmzY\nMAICAkhMTMTf358hQ4Zw6dIlg16fjOUll84TzN999x0WFhYcOnQIc3NzVXnnzp3573//a5DghHid\nfP/99wwePBgzMzOd2+zbt49GjRpRt25dA0YmhBBCiJKkYI/v0qVLM3LkSBo0aIBCoaBmzZp4e3tz\n9OhRVd2NGzfSs2dPmjRpgrm5OaNGjeLixYskJiYCULlyZWrUeLT7e8Gks5mZGZUqVdJrzOt3p7Bu\n12mN8nW7TsuDqRBCiBJj0qRJuLu7M3r0aKpVqwaApaUlgYGBdOnSBfj/cRygSpUqDBgwgICAAObM\nmcPdu3dVx27dusXMmTOZMmWKxnk2b95M06ZNcXd3x8TEBHd3d6ysrNi8ebPBrk3G8pJN5wnmuLg4\nRo8eTeXKldXK69aty5UrsqRdiH/j2rVrREVFMXDgwGK1i4iI4KOPPjJQVEIIIYR4VT3+8Fkchw4d\nokmTJqrPKSkpvPPOO6rPZcqUoV69epw+rf6AaG9vT7NmzfD19WXq1Km89dZbzxa4FnHJV7Q+kBZY\nt+u0vGIrhBDilXf+/HkuXLiAm5tbsdt26dKFBw8e8Ntvv6nKpkyZQt++faldu7ZG/dOnT6uN7wBW\nVlakpBhmolfG8pJP503+7t27R+nSpTXK79y5g4mJzt0IIbQICQnB29ubqlWr6twmJyeH6OhotVVG\nQgghhBAAfn5+GBsbA2BiYlJkbsYCq1atUr1uW+DevXuUK1dOrV758uVV+7EUSEhI4OHDh2zfvp2g\noCDq16+vNlH9byyO+k2nOk7WNfRyPiGEEOJFKEhFW7169WK3feONNwC4ffs2AHv27OHSpUvMmTNH\na/379+9rjO/lypXjjz/+KPa5dSFjecmn8wrmZs2asWvXLo3ysLAw7O3t9RqUEK+Tf/75h5CQEIYP\nH16sdvv376devXrUr1/fMIEJIYQQ4pUVGhpKfHw88fHxOk8uh4aGsnr1atVDKkDZsmXVXrcFyMjI\nwMLCQqMPU1NTunXrhoODA1u3bv33FyGEEEK8RgoyBqSlpRW77dWrVwGoWLEit2/fZurUqarUGAVv\nNT3+dlPZsmXJyMhQ6yMjI0Nj0lkIXek8wTx69GgWL17M2LFjycnJITQ0lF69erFz505GjBhhyBiF\nKNHWr1/Pu+++i5WVVbHaRURE0KNHDwNFJYQQQojXxcKFC1m1ahVr166lYcOGaseUSiUnTpxQfb53\n7x5///03SqWy0P5ycnK0TkA/qwCv5nqpI4QQQrzMGjRoQL169di2bVuR9R7f1LfA9u3bKV26NO++\n+y4pKSlcv36dfv364ejoiJOTE4AqTzM8Gt9Pnjyp1sfJkydp3Lixnq5GnYzlJV+xVjCHh4ejUCio\nW7cu8fHx1K5dm02bNhV5gymEKFx+fj5z585l5MiRxWqXm5vL5s2bZYJZCCGEEMXyZG7mGTNmEBkZ\nyQ8//KD1rShvb2/Cw8M5deoUDx48YO7cudSpUwc7Ozvg0e70Z86cIScnh6ysLDZu3MixY8fo1KmT\n3mJ2sq5Bb5fCnzd6uyjllVohhBAlwsSJE4mJiWHu3Llcu3YNgBs3brBkyRK2b98OqI/lN2/eZPXq\n1SxZsoQRI0ZgYWGBjY0NP/30E1u2bFH9AHz33Xf4+fkB4OHhwfHjx4mNjSU7O5utW7dy6tQpPD09\nDXJdMpaXfMVKnvz2228zY8YMQ8UixGtn37595ObmFvsh7L///S81a9bU6wY6QgghhCj5FAqFauXT\npUuXWLlyJWZmZnTt2lVVp3bt2sTExADg7u5OWloa/v7+3L17FxsbGxYtWqTq4/r16/znP//h2rVr\nmJub07hxY5YtW0ajRo30GnevTo9WVD25QVCfzkp6fmCY1VZCCCHE89aqVSvWrVtHSEgI7u7uPHz4\nEEtLS5ydnenevTsHDhwgOjqa2NhYjIyMsLCwoFmzZoSEhNCqVSsAzMzMtOZxrly5sioFRp06dViw\nYAEzZswgKCiIunXrsnDhQmrWrGmwa5OxvGRT5Bdji+n8/HyuXr3KjRs3NFY/NGvWTO/BGUJqaiod\nOnRg7969WnfSFOJ5cnd3p2vXrqpvEXU1dOhQatSoQVBQkIEiE0IIIYQwrGe5L49LvvK/jYIUBHZv\nhmNTWe0khBBCPE//dl5NxvKSSecVzKdOnWLkyJH89ddfGscUCgWnTp3SZ1xClHhnzpzh6NGjbNy4\nsVjt8vLyiIyM5OeffzZMYEIIIYQQLykn6xryCq0QQgjxCpOxvGTSeYL566+/platWkybNg1LS0ut\nScWFELqbN28e/v7+lC5duljtDh06RNWqVXn77bcNFJkQQgghhBBCCCGEELrReYL57NmzREZGSs5X\nIfQgPT2ddevWaezaqouIiAg++ugjA0QlhBBCCCGEEEIIIUTxGOlasV69emRkZBgyFiFeG8uWLcPd\n3Z0aNYr3WkhBeowePXoYKDIhhBBCGEpCQgI2NjYaP9bW1iiVShITEwFITk5m0KBBODk5YWdnh4uL\nC9OmTeP69esA/PDDD7i4uODg4ECLFi3o06cPhw8fVp0nKipK6wbCT5bHxcXRv39/WrZsiVKpJC0t\nTa3+/v376devH46OjqrzJCQkaPSbn5+Pi4sLdnZ23L9/Xy+/q8LEJV+m/6Sd9J+0k7jkKwY9lxBC\nCKFvffv2RalUaoynH3zwAZs3byY1NRWlUqlxrxAfH69qHxISomp3584d+vTpwyeffEJGRgZHjhxR\na9+yZUsGDhzIhQsXVG10Hd8NQcbxkkvnCeYJEyYwZ84czpw5Y8h4hCjxHj58SHBwMCNHjix226NH\nj1K+fHmaNGligMiEEEIIYUj29vYkJSWp/Rw5coQmTZrg7OyMnZ0dBw8epE+fPrz11lts2bKFxMRE\n1q5dS6VKlVQPl+3atSM8PJz4+HgOHTpEx44dCQgIIDs7u1jxlClTBk9PT2bOnKn1eEZGBv369WPP\nnj0cPnwYNzc3/Pz8uHr1qlq9w4cPc+PGDSpXrkxsbOyz/XJ0sH53CtNWxZOekUV6RhbTVh1l/e4U\ng51PCCGEMISKFSsyY8YMtTKFQqGWinbnzp1q9wsODg5qdQGuXLlCnz59qFKlCitWrKB8+fIAGBsb\nq9r9/PPPVKhQgbFjx6r11sYEAAAgAElEQVTa6zq+65uM4yWbzikyPv30U3JycujatSsmJiYYGf3/\n3LRCoeC3334zSIBClDQFqWZsbGyK3XbTpk2yelkIIYQoQcaPH09WVhZz5swBYNKkSbi7uzN69GhV\nHUtLSwIDA1Wf69Spo/p3Xl4eCoWCKlWqYGKi8609AM2bN6d58+akpqZqPe7u7q72uVevXixcuJDj\nx4/zxhtvqMrDw8NxcXGhZs2abNiwwSCpvNbvTmHdrtMa5QVlvTo11vs5hRBCCEPw9vZm8+bNbNu2\nDTc3t2fq48yZM/j6+tKpUye++uqrQuuVLl2aLl26qN1X6Dq+65OM4yWfzneh33zzjQHDEOL1kJ+f\nz9y5cwkKCnqmthEREWzbts0AkQkhhBDieQsODubIkSNs2rSJ0qVLc/78eS5cuMCkSZOe2jYhIYHA\nwEAyMzN54403CA0NVVsAYggpKSncunVLbaPh9PR09u7dy7Jly6hVqxbBwcGcOHGCd955R2/njUu+\novWhtMC6XaepX6O87EgvhBDilVC6dGmGDRvGnDlzcHFxwdTUtFjtk5KSWLFiBb6+vvj7+xdZNzMz\nk5iYGOzt7Quto2181ycZx18POk8we3l5GTIOIV4LcXFx3Lx585m+pUxISKB06dI0bdrUAJEJIYQQ\n4nnasWMHoaGhrF69WrUnQ3p6OgDVq1d/ant7e3vi4+O5e/cu8+fPx9/fn9jYWMzNzQFITU1Ve50W\nHqXp0qVvbW7evMmwYcP47LPPqFu3rqo8MjKSKlWq4OjoCICtrS3h4eFMnjz5mc6jzeKop78puTjq\nN3kwFUII8UpQKBR0796dNWvWsHr1anx9fdWOAbi6uqr+XadOHaKiolR1EhMTMTc3x9XVVWv/ubm5\nqnuAe/fuYWlpyYIFC7TWLWx81ycZx18PxXqPLjs7m61bt/Lnn38C0KhRI9zc3DAzMzNIcEKUNHPn\nzmX48OEYGxsXu21ERAQ9evRQy8skhBBCiFdPcnIyQUFBTJ06lebNm6vKK1euDEBaWhpvvvmmTn2V\nK1eOoKAgIiMjOXLkCG3btgWgdu3a7N69W63u5s2b1TYG0lVaWhqffvop77//PqNGjVKV5+fns2nT\nJrUH3K5duzJz5ky++OILypYtW+xzCSGEEK8DIyMjPv/8c0aPHq2WBjM/Px+A2NjYQr8U9vHx4eLF\ni/Tp04eVK1fSoEEDtePGxsaqfRtyc3PZsWMH/fr1U6XrLFDY+C7Es9D5Pbpz587RuXNnvv32W44d\nO0ZiYiJTpkyhc+fOnD9/3pAxClEi/PXXX/z0008MGDCg2G0LHuAk/7IQQgjxaktLS2Pw4MF8+umn\nGm80NWjQgHr16hU7HVZubi55eXlPndAteGgtjtTUVD755BPatm2rkePx8OHDXLhwgY0bN9K6dWta\nt27N999/z/379/Wa0ivAq7le6gghhBAvkzZt2mBtbU1wcHCx2hkbGzN9+nScnZ355JNPSEkpfKM8\nY2Nj3NzcMDc358CBA6ryosZ3fZNx/PWg8wTztGnTaNCgAT///DPh4eFs3LiRffv20aBBA7799ltD\nxihEiRAcHIyPjw/lypUrdtukpCSMjIzUVjkJIYQQ4tXy4MEDAgMDsbGxYejQoVrrTJw4kZiYGObO\nncu1a9cAuHHjBkuWLGH79u0ArF+/nrS0NPLz80lPT2fy5MlUr14da2vrYsWTn59PVlYW2dnZwKO3\nFbOyslQT0X/++Se9e/fGzc1Nbff5Ahs2bMDBwYGdO3eyZcsWtmzZwrZt2/Dy8iI8PLxYsRTFyboG\nvV2UhR7v7aKU12qFEEK8Mh7/wnfs2LGEh4er0mQVp/3EiRPp1q0b/fr14/fff9daNzc3l+3bt3P7\n9m0aN360kd7Txnd9k3H89aBziozExETWr19PhQoVVGUVK1ZkzJgx9O7d2yDBCVFS3L17l5UrV3Ls\n2LFnai/pMYQQQohX365duzh58iTnz5/HxsZG4/iUKVNwc3Nj3bp1hISE4O7uzsOHD7G0tMTZ2Vn1\nJtPx48dZtGgRmZmZlC9fHgcHB5YvX06pUqWAR/kbtd0zPFl+9OhR+vfvrzr2wQcfAPDDDz/g4OBA\naGgo169fZ9WqVaxatUotTicnJ/bu3UtwcDBVqlRRO4+fnx+urq563eyvYHf5JzcJ6tNZSc8PZOd5\nIYQQr47Hx2KlUombmxvR0dFajz+t/dixYylTpgw+Pj4sWbIEhUJBbm6u6j5DoVBQq1Yt1dgNFDm+\nP8t+UbqQcbzkU+Tr+K6cvb09K1asoFmzZmrlv//+Oz4+PiQmJhokQH1LTU2lQ4cO7N27l9q1a7/o\ncMRrYv78+fz3v/9l48aNxW6bn5/P22+/zYYNG7CzszNAdEIIIYQQz9+z3JfHJV/532ZBCgK7N8Ox\nqax4EkIIIZ6nfzOvJuN4yaXzCuZWrVoxZcoU/vOf/6h2lvz777+ZPHky7733nsECFOJVl5uby7x5\n81i7du0ztU9OTiYnJwdbW1s9RyaEEEII8Wpxsq4hr9EKIYQQrygZx0sunSeYv/zySwIDA3FxcVG9\nBnfz5k2srKz48ssvDRagEK+6mJgYLC0tVa+jFFfB5n6SHkMIIYQQQgghhBBCvGx0nmCuXr06kZGR\nxMXF8ccffwDQsGFDWrVqZbDghCgJ5s6dy4gRI56pbX5+Pps2bWL16tV6jkoIIYQQ4tUSl3yZxVGP\nNjEK8GouK6CEEEKIV4iM4yWbUXEqKxQKWrVqRb9+/ejXr59MLgvxFMeOHePcuXN07979mdqfPHmS\n+/fv06JFCz1HJoQQQpQchw4dwtvbGxsbGxwdHZk0aRIAO3bswN3dnRYtWmBvb4+Xlxc7duxQtTt3\n7hze3t60bNkSW1tbOnXqxMKFC9V2d7958yZDhgzB1tYWJycnZs+ejbYtTPLy8ujZsydKpZK0tDS1\nY9HR0XTs2JF3330Xb29vTpw4oXZ89+7duLu7Y2NjQ+fOndm5c6facaVSScuWLbl7966q7OrVqyiV\nSi5fvqwq++WXX3B1daV58+a4u7tz8OBBrb+v06dP07RpU3x8fNTK27dvT7NmzbCxscHBwQFvb28O\nHDigUWfr1q3AoxyMT17v4cOHadGiBcuXL9d67me1fncK01bFk56RRXpGFtNWHWX97hS9nkMIIYQw\nhL59+2JtbY2NjQ329vZ4enqye/duQLexF+Dnn3+md+/e2NraYmtrS+/evfn555816v3111+MGTOG\n1q1bY2NjQ8eOHQkKCuLvv/8GYMGCBVhZWWFjY4ONjQ3t27dn7ty5Wu9t9EnG8ZKvWBPM+/fvx8fH\nh/fff5/3338fHx8f9u/fb6jYhCg2pVLJjBkzVJ+XL19OcHAw8OgPaZs2bfDw8MDDw4M5c+YAj/7Y\nHz9+HICLFy/i4uLCwYMHOXLkCHZ2dnh4eNC1a1d8fHxIT08HYOvWrXTt2hV3d3d69uzJ6dOn0eb7\n779n6NChmJqaPtP1RERESHoMIYQQoghHjhxh+PDh+Pr6cvToUX755Rc++ugjAGxsbFi5ciVHjx4l\nISEBPz8/Ro0apZqUrVatGrNnz+bw4cMcO3aMBQsWEBYWxpYtW1T9jxkzBiMjI3755Rc2btzIjz/+\nSGhoqEYcq1atonTp0hpjdkJCApMmTWLy5MnEx8fTqVMn/P39yczMBODXX39l7NixfPXVVyQlJfHF\nF18wZswYfv/9d7V+jIyMWLRoUaG/h4sXLzJs2DACAgJITEzE39+fIUOGcOnSJbV6OTk5BAUFYW9v\nr/X+4ttvvyUpKYmDBw9iZ2fHsGHDyMjIUKtT2H1JbGwsgwYN4uuvv+azzz4rNNbiWr87RWPXeXi0\nE708nAohhHgVDB48mKSkJI4cOYKrqysjR47kr7/+Ap4+9kZERDB8+HDc3d05cOAABw4cwN3dneHD\nhxMZGamql5KSQvfu3TEzM2PDhg0kJSURGRnJO++8wy+//KKq5+joSFJSEklJScycOZPVq1ezceNG\ng127jOOvB50nmMPCwggMDKRChQr4+vri6+tLhQoVGDRoED/88IMhYxRCZ6ampvz444/cunULUH8A\nUigU+Pj4EB0dTXR0NKNGjVI7dvXqVfz8/Bg3bpxq40oHBweio6PZunUr1tbWhIWFAVCnTh3CwsKI\niYlRPUg96erVq2zbtg0/P79nvp6CCWYhhBBCaDdnzhx69epFp06dMDU1xczMDCsrKwDeeOMNqlat\nCjzadNfIyIhy5cpRpkwZACwsLKhbt67a/YKRkRHVqlUDHk3axsXF8fnnn2NhYUGdOnXw8/Njw4YN\najGcP3+e9evX88UXX2isANq0aROdOnWiVatWmJqa4uvrS6lSpdizZw/waPXy+++/T8uWLQFwdnbG\n1tZW4xyBgYGsW7dOY8K4wObNm2natCnu7u6YmJjg7u6OlZUVmzdvVqu3ZMkSmjdvjr29fZGrlczM\nzPDy8uLBgwdcuHCh0HoFVq5cycSJE1m4cCFubm5Pra+ruOQrWh9KC6zbdZq45Ct6O58QQghhSMbG\nxvTq1Yvc3FzOnDmjdkzb2Hvv3j2mT5+Ov78/vXr1omzZspQtW5ZevXrh5+fH9OnTefDgAQDfffcd\n1tbWTJs2jdq1awNQoUIF+vTpQ9++fVXneXz8t7e3p2HDhhqx6IuM468PnSeYly5dytixY/n+++/p\n378//fv35/vvv2fs2LEsW7bMkDEKoTMTExO8vb1ZtWqV1uOFPUilpaXx2WefMWrUKJydnbW2y8zM\npEKFCsCjFVHlypUDoHnz5ly9elWjjampKcuXL6dSpUrPdC2nT58mPT0dR0fHZ2ovhBBClHT3798n\nOTmZhw8f4uXlhaOjo9qbSQCXL1/GwcEBa2trvv76axYuXEjFihXV+nF3d8fa2hovLy/8/PxUaeBS\nUlIoV64cderUUdW1srLi0qVL3Lt3D3iUGiMoKIgvvvgCCwsLjRhTUlJ455131MqUSiUpKf+/Yicv\nL0/teF5ensbbUe+88w6dOnXiP//5j9bfxenTpzXOY2VlpXaelJQUoqOjGTNmTKH3RAXlDx48YOPG\njVSoUIEGDRporVtg5syZLF++nLVr1z7zpsaFWRz1m17qCCGEEC9SwfianZ1NWFgYpqamKJVKtWPa\nxt6kpCQyMzPp2rWrRp9du3bl7t27/Prrrzx48ID4+Phifcmbl5fH4cOHOXv2LO++++6/vUStZBx/\nfeg8wXznzh2tE29t27bVeG1OiBepd+/exMTEqF49LZCfn8+qVatUKTIez0s4fvx4PvnkEzp16qTW\nJiEhAQ8PD5ydnTl8+DBeXl4a54uIiKBt27Ya5VWqVMHT0/OZryMiIoLu3btjZFSsTDZCCCHEayMj\nI4O8vDy2b9/O9OnTOXDgAK1bt8bf31+Vr7hmzZrEx8dz7Ngx/Pz8GDx4sEaO5JiYGH799VcWL17M\nggULVDkNMzMzVV8oFyj4XHCfsWbNGqpVq0bHjh21xnjv3j2NPsqXL69q365dOw4cOMChQ4fIycnh\nxx9/JCkpSTWBXUChUDBy5Eh++uknjfQZ8GiyXVusBecpSI3x1VdfUbZsWe2/UGDixIk4ODhga2vL\n1q1bWbNmTZH14VHu55YtW9K4ceMi6wkhhBCvq8WLF+Pg4EC7du3Yt28fCxYsoG7dukDRY29Bms7q\n1atr9FnwxtXNmzfJyMggNzdXa70nxcfH4+DgQPPmzRkwYACBgYG4u7vr61LFa0rnmav33ntP60Yh\ncXFxel+pIMS/YWFhgYeHB2vWrFErfzJFRkEaDAAnJye2bNnCP//8o9bG3t6e6Ohofv75Zzw9PZk1\na5ba8cOHDxMZGcmYMWP0fh2SHkMIIYQoWsHDl5eXF2+//TampqYMHDiQnJwckpKS1Oqam5vj6+uL\npaWlKj3F44yNjXn//fdxd3cnKioKeHRP8fjGeoDqc9myZfn7779ZuXIlEyZMKDLGJ/u4c+eOarVz\nixYtmDRpEt999x3vvfce0dHRdOnSResbUDVr1uSTTz5hxowZGnmQy5Ytq7HoIyMjQzXpHBoaSv36\n9bV+Kf64glzRv/zyCw0aNNCab/pJixYtIikpiTFjxpCbm/vU+sUR4NVcL3WEEEKIFykwMJD4+HgO\nHTrE+vXradeunepYUWNv5cqVATS+HAe4du2aqk758uUxNjbW+nb1k1q0aKH68n3UqFGsXr2a69ev\n/8sr1E7G8deHzhPMTk5OzJs3j6CgIDZt2sSmTZsICgpi3rx5tG7dmu3bt6t+hHjR+vfvT0REBPfv\n31crL+x1UF9fX6ytrRk+fHihD0bt27cnISFB9fn06dNMmDCBkJAQVeoMfTl79ixpaWlqk+BCCCGE\nUFeuXDlq1aqlVpafn49CoSh0I7qcnJwiV+Tm5OSoJn8bN27M3bt3uXjxour4iRMnqF27NhYWFiQm\nJpKeno6bmxuOjo50794dePTK6vr164FH6TBOnDihFt+pU6fUVvt6enoSExPDkSNHWLhwIefOnaNF\nixZa4wsICODcuXOq3ecLKJVKTp48qVZ28uRJ1XkOHjzIzz//jKOjI46Ojixfvpz4+HgcHR21vo1o\naWnJ9OnT2bFjh9r9jzZ169YlLCyM48ePM2zYMLKzs4usXxxO1jXo7aIs9HhvFyVO1jX0dj4hhBDi\nRdE29trY2GBhYUFMTIxG/a1bt1KuXDlsbGwoXbo0LVq0IDY29qnnKZgXMTU1xd/fn4YNGzJv3jz9\nXsz/yDj++tB5gnnq1KncuXOHqKgoJkyYwIQJE4iKiuL27dtMmTKFUaNGqX6EeNEqVKjAhx9+qLaj\nalEb2SgUCr788kssLCz48ssvtdZJTExUvcJy+fJlhg4dyqxZs6hXr55+gwciIyPx8vLC2NhY730L\nIYQQJUnv3r2Jiorizz//JCcnh9DQUMzMzLCxsSE6OpoLFy6Ql5dHZmYmwcHBZGRk0Lp1awD++9//\n8vvvv5Odnc3Dhw/Zs2cP27Ztw9XVFXi0qW+rVq2YNWsWmZmZXLx4kdDQUD7++GMAunTpwp49e9iy\nZQtbtmxh6dKlAKxYsYJu3boB8NFHH7F7927i4uLIzs4mNDSUnJwcPvjgA+DR5oMnTpwgNzeXu3fv\n8v3335OWlsaAAQO0Xq+FhQWDBw9m4cKFauUeHh4cP36c2NhYsrOz2bp1K6dOnVKl65o3bx7bt29X\nxdqzZ0+aN2/Oli1bNFJrFKhfvz7dunVj/vz5T/3foUaNGoSFhXHhwgUCAwM13gr7N3p1aqz14bRP\nZyW9OklaDiGEEC+/ouYjHvfk2Fu2bFnGjh3L0qVLCQ8PJzMzk8zMTMLDwwkNDWXs2LGULl0agHHj\nxnH8+HG++uorUlNTyc/PJyMjg/Xr12u84f244cOHq+6ZDEHG8deDia4Vn9xoRIiX0eOrlT799FPC\nwsLUjhW2mqnA9OnTCQgIYNasWbRt21aVgzk/P5/y5cszdepUABYuXEhGRgbffPMN8GhzwYiICL1d\nx6ZNm5g9e7be+hNCCCFKqs8++4x79+7Rv39/srKysLKyYtmyZVhYWPDXX38xf/58bt26RdmyZbG2\ntmblypVUrVoVeJRHefr06Vy6dAkzMzMaNGjArFmz1N4gmj17NhMnTqRNmzaYmZnRo0cP/Pz8gEdp\nN8zNzVV1Hz58iEKhoGrVqpQpUwYAOzs7Jk6cyIQJE7h+/TqNGzdm6dKlqlXUubm5fP3115w/fx6F\nQoGjoyPr169XvRKrTc+ePfnhhx+4c+eOqqxOnTosWLCAGTNmEBQURN26dVm4cCE1a9YE0OjPwsKC\nUqVKPTVXY2BgIJ07d+bIkSO0bNlS4/jj91ZVq1blhx9+wNfXFz8/P0JCQrRufPgsenVqTP0a5f+3\nEZCCwO7NcGwqK56EEEK8Gp42F/G4J8deb29vqlatyrJly5g+fToATZo0Ye7cuWp7pTVu3JiIiAiC\ng4Pp2bMn9+7do3LlyrRq1Qp/f39VHE/GYm9vj4ODA4sWLVL1r28yjpd8inxdv0YpIVJTU+nQoQN7\n9+6ldu3aLzocITScO3cOJycnLl26hImJzt8BCSGEEEK8UuS+XAghhHj1yPgttCnW7NXZs2eJi4vj\n5s2bGsv7JTWGEPoRGRmJp6enTC4LIYQQQgghhBBCiJeezjNYYWFhTJ06lYoVK1KlShXVkvqCjVRk\nglkI/YiIiODbb7990WEIIYQQQgghhBBCCPFUOm/yt2TJEkaPHk1cXBzbtm0jJiaGmJgY1b+FEP/e\n33//zblz52jbtu2LDkUIIYQQJUjfvn2xtrbGxsYGe3t7PD092b17NwDt27dn69athbYLCQlRfb5z\n5w59+vThk08+ISMjg19//RV/f3/ee+897O3t8fLyYs+ePQa5hrjky/SftJP+k3YSl3zFIOcQQggh\nXqTCxt0OHTrQr18/tWwCeXl59OnTh4kTJwKPxvOmTZtqbNZnZWVFfHw8AFFRUXTq1EnjvIWV65OM\n4yWbzhPM//zzj8H/YxPidRcZGUm3bt0wNTV90aEIIYQQooQZPHgwSUlJHDlyBFdXV0aOHMlff/0F\nFL35UMGxK1eu0KdPH6pUqcKKFSsoX748d+7cwdXVldjYWBISEhg0aBCjR48mOTlZr7Gv353CtFXx\npGdkkZ6RxbRVR1m/O0Wv5xBCCCFeBtrG3ZiYGK5evcrKlStV9UJDQ7l16xZBQUGqsnLlyjF79myt\n/b1IMo6XfDpPMLu7u/PTTz8ZMhYhnrsmTZrg4eGh+rl8+TI3btxg4MCBdOvWDVdXV9VuqwDnz5/H\nz88PFxcXvLy8GDFiBDdv3uTIkSMolUr27dunqjtw4ECOHj0KwNq1a/nggw9QKpXcvn270HgiIiLo\n0aOH4S5YCCGEEK89Y2NjevXqRW5uLmfOnNGpzZkzZ/j4449xdHRk/vz5mJmZAdC2bVu6detGxYoV\nAejYsSNKpZLExES9xbt+dwrrdp3WKF+367Q8nAohhCiRnhx3y5Qpw+zZs1mwYAEpKSmcOnWKkJAQ\nZs+eTalSpVTtPv30Uw4cOEBSUtILjF6djOOvB51zMH/xxRcMGjSII0eO0LhxY40NyIYMGaL34IQw\nNHNzc6Kjo9XKvv76a1q3bk3fvn0BVA9eWVlZBAQEMH78eNq1awfA0aNHSU9PR6FQ8MYbb7B48WKc\nnZ2BR98SFnxTaGdnh7Ozs6pPbVJTU0lJSaFDhw76vkwhhBBCCNVrtdnZ2YSFhWFqaopSqXxqu6Sk\nJFasWIGvr6/aF+/aXL9+nbNnzzJy5Ei9xByXfEXrQ2mBdbtOU79GeZysa+jlfEIIIcSLVti426xZ\nM/z8/BgzZgwAgwYNwsrKSq1t9erV6d+/PzNmzGDDhg3PNW5tZBx/fei8gjkiIoKDBw+SmJjIzp07\niY2NJTY2lm3bthEbG2vIGIV4rq5fv0716tVVn99++20AYmJisLGxUU0uA7Ro0YJGjRoBoFQqKVeu\nHIcOHdLos0mTJtSqVavI8166dIkhQ4ZIegwhhBBCGMTixYtxcHCgXbt27Nu3jwULFlC3bt2ntktM\nTMTMzAxXV9ci692/f5+hQ4fi7OyMo6OjfmKO+k0vdYQQQohXRVHjbkBAAKVKlaJs2bL4+flpHFco\nFPj5+XHx4kV27NjxPMItkozjrw+dVzAvXLiQESNG4O/v/1LkbxFCH7KysvDw8ACgTp06LFiwgD59\n+jBy5EjWrl1Lq1at8PLyolq1avzxxx+88847WvspWBEUEBDAvHnzaNWqVbFjadmyJS1btnz2ixFC\nCCGEKEJgYCABAQHFbufj48PFixfp06cPK1eupEGDBhp1MjMzGThwIJaWlsyYMUMf4QohhBCvpaLG\nXSMjIxo1aqSRVeBxZcuWZciQIcyZM4eOHTuqHTMxMSEnJ0ejTU5OTpF9CvE0Oq9gzsrKokuXLjK5\nLEqUUqVKER0dTXR0NAsWLACgdevW7NmzB29vb86dO4enpyfp6ekAaju2amNvbw+gyjv4tPpCCCGE\nEC87Y2Njpk+fjrOzM5988gkpKer5Em/dusWAAQN44403mDdvnl4fUAO8muuljhBCCPGqeNq4C0+f\na/D29sbU1JSwsDC18lq1anHt2jX++ecftfK///5bp7eaikvG8deHzhPMXbp0UdvATIiSrEKFCri5\nuTFz5kysra1JSEigYcOGnDhx4qltAwICWLRo0XOIUgghhBBCd0U9jD58+JCsrCzVT3Z2tka7iRMn\n0q1bN/r168fvv/8OPEot1rdvXxo2bMisWbMwMtL58UInTtY16O1SeJ7o3i5KydsohBCiRClq3H38\neFGMjY35/PPPCQkJUavfvHlz6tevz7Rp08jIyCA3N5f4+HgiIiLw9PTU+7XIOP760Hl5QbVq1QgO\nDiYxMRGlUqmxMkFb7hchXkWHDx+mefPmlC5dmszMTC5cuEDNmjVp27YtS5cuZf/+/bRt2xaA+Ph4\n1a7pBd577z3mzZvH9evXta74l1XNQgghhHgRinoTMSgoiKCgINXnUqVK8dtvv2m0Gzt2LGXKlMHH\nx4clS5Zw+PBh/vjjDy5dusSuXbtU9QIDA5+6IaCuenVqDKCxSVCfzkp6ftBYL+cQQgghXhZFjbv2\n9vYoFAqdsgs4OzujVCo5evSoqszExIQlS5Ywe/Zs3NzcuH//PrVr12b8+PG4uLgY5HpkHH89KPJ1\nnO1q3759kcd/+uknvQRkaKmpqXTo0IG9e/dSu3btFx2OeMFsbW05duyYWtny5cuJiorC2NiY/Px8\nunfvzoABAwA4d+4c06ZN4+LFi5iYmKBUKgkKCuLPP/9kxYoVLF68GHj0/4fBgwezZs0aHBwcWLNm\nDcuXL+fmzZtUqlSJdu3aMWXKlOd9uUIIIYQQL43i3pfHJV/530ZACgK7N8Oxqax4EkIIIZ63Z51X\nk3G8ZNN5grmkkDW4UycAACAASURBVAlmIYQQQgghXjy5LxdCCCFePTJ+C22eKUna/fv3uX//vr5j\nEUIIIYQQQgghhBBCCPEKKdYE87p162jXrh22trbY2trSvn171q9fb6jYhBBCCCGEEEIIIYQQQrzE\ndN7kb9myZSxcuJB+/fphb28PPNrgbMaMGdy7dw9fX1+DBSmEEEIIIYR4dn379qVVq1YEBgaiVCox\nNzdX2yBo4sSJeHh4MG7cOExMTBg8eDBdunRRHc/OzkahUGBqagpA7dq1iYmJYfz48cTFxXH37l3M\nzMxwcHDgiy++oFatWnq/hrjkyyyO+h2AAK/msuu8EEKI5y45OZmQkBCSkpLIzs6matWqtG3bFj8/\nPywtLfnjjz+YP38+R44cISsri9q1a9OjRw/69++vGnejoqJYvHgxu3fv1uj/119/ZdGiRZw4cYKs\nrCzq1q3LoEGD6NixIwCXL1/G1dVVrc3Dhw8pVaoUiYmJauUhISHMmzeP6dOn4+HhoXZszZo1xMTE\ncPbsWapVq6Y1Fn2Tcbxk03mCef369UyYMIHu3burytq0aUP9+vVZuHChTDALIYQQQgjxEnt8QnnF\nihXY2tpqraNQKKhRowZJSUmqch8fH+zs7BgyZIha/U8//ZSJEydibm7O3bt3mThxIuPHj2fNmjV6\njX397hS13eenrTpKbxelamd6IYQQwtAOHjxIYGAg/fv355tvvqFatWpcv36diIgI4uPjefPNN+nV\nqxceHh7ExsZSsWJFjh49yvjx4zl9+jTTp09/6jnu3LmDq6srM2fOpGLFiuzZs4fRo0ezdu1arK2t\nqVmzptr4DNCrVy+aNGmiVpaXl8emTZto0qQJ4eHhGhPM1atXx9/fnz///JOoqKh//8t5ChnHSz6d\nJ5ivXbumWrn8ODs7O65du6bXoIQQQgghhBAvRnH2AG/UqJFaO4VCQfXq1fUaz5MPpQUKyuThVAgh\nxPMwadIk3N3dGT16tKrM0tKSwMBAAAYMGECzZs2YOHGi6nirVq2YNWsW/fr146OPPsLOzq7Ic7Rt\n21btc8eOHVEqlSQmJmJtba1R/8yZMyQlJTFp0iS18gMHDnDr1i2WLl2Ku7s7Z8+eVRuzXVxcALh7\n966OV//sZBx/Peicg7lWrVrs27dPo/znn3+WXSOFEEIIIYR4hRRnEvlpli5diq2tLS1atCAtLY3J\nkyfrre+45CtaH0oLrNt1mrjkK3o7nxBCCKHN+fPnuXDhAm5ublqP//PPP8THx9O1a1eNYy1atOCN\nN97gwIEDxT7v9evXOXv2LEqlUuvxDRs2YGNjw9tvv61WvnHjRjp16kTDhg2xt7cnPDy82OfWBxnH\nXx86TzD7+voya9Ysxo4dy8aNG9m4cSOff/45s2bNkvQYQgghhBBCvEL8/PxwcHDAwcEBJyenf9WX\nv78/x44dY8+ePRgZ
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment