{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<script>\n",
       "code_show=true; \n",
       "function code_toggle() {\n",
       " if (code_show){\n",
       " $('div.input').hide();\n",
       " } else {\n",
       " $('div.input').show();\n",
       " }\n",
       " code_show = !code_show\n",
       "} \n",
       "$( document ).ready(code_toggle);\n",
       "</script>\n",
       "The raw code for this IPython notebook is by default hidden for easier reading.\n",
       "To toggle on/off the raw code, click <a href=\"javascript:code_toggle()\">here</a>."
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import HTML\n",
    "HTML('''<script>\n",
    "code_show=true; \n",
    "function code_toggle() {\n",
    " if (code_show){\n",
    " $('div.input').hide();\n",
    " } else {\n",
    " $('div.input').show();\n",
    " }\n",
    " code_show = !code_show\n",
    "} \n",
    "$( document ).ready(code_toggle);\n",
    "</script>\n",
    "The raw code for this IPython notebook is by default hidden for easier reading.\n",
    "To toggle on/off the raw code, click <a href=\"javascript:code_toggle()\">here</a>.''')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import json\n",
    "import random\n",
    "import datetime\n",
    "import seaborn as sb\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib\n",
    "matplotlib.rcParams['figure.figsize'] = (15.0, 5.0)\n",
    "import numpy as np\n",
    "from collections import Counter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def annotate(x_point,y_point, x_text, y_text, text):\n",
    "    plt.annotate(text, xy=(x_point, y_point), xytext=(x_text, y_text),arrowprops=dict(facecolor='black', shrink=0.05))\n",
    "    \n",
    "def video(fname, mimetype):\n",
    "    from IPython.display import HTML\n",
    "    video_encoded = open(fname, \"rb\").read().encode(\"base64\")\n",
    "    video_tag = '<video loop autoplay alt=\"orderbook video\" src=\"data:video/{0};base64,{1}\" width=100%>'.format(mimetype, video_encoded)\n",
    "    return HTML(data=video_tag)\n",
    "\n",
    "def image(fname, width):\n",
    "    from IPython.display import HTML    \n",
    "    data = '<img src=\"%s\" width=%d%%>' % (fname, width)\n",
    "    return HTML(data=data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# High Frequency Trading in Bitcoin Exchanges\n",
    "\n",
    "Note: This article is the notebook corresponding to my post [High Frequency Trading in Bitcoin Exchanges](https://www.linkedin.com/pulse/high-frequency-trading-bitcoin-exchanges-eduardo-pena-vina) originally published on Linkedin on July 27, 2017.\n",
    "\n",
    "## Introduction\n",
    "\n",
    "In this post I analyze the **presence and activity of high frequency trading** in a Bitcoin exchange. Since to date this markets are *extremely unregulated*, such behaviour takes places with little to no constraint. I show how **over 99%** of orders placed are **not meant to be filled**, but instead to distort the perception of the market. In addition, I try to spot common HFT strategies, such as *Quote Spoofing*, *Layering* and *Momentum ignition*. Given the anonymous nature of these exchanges these last results are to some extent *subjective*.\n",
    "\n",
    "\n",
    "## What is High Frequency Trading?\n",
    "\n",
    "From Wikipedia [1], High-frequency trading (HFT) is a type of algorithmic trading characterized by high speeds, high turnover rates, and high order-to-trade ratios that leverages high-frequency financial data and electronic trading tools."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Methodology\n",
    "\n",
    "This analysis has been carried out with order data from the Websocket stream from **GDAX**, a US based digital asset exchange [2] owned by Coinbase. It is one of the largest markets (over **42 MM USD/day**) [3] and it exposes a high performance socket where all orders are broadcasted. In addition, it offers some interesting features for data analysis:\n",
    "\n",
    "1. Orders are timestamped (as opposed to Bitfinex, for example)\n",
    "2. It has millisecond granularity (again, as opposed to Bitfinex)\n",
    "3. It says whether an order has been matched or cancelled -one could argue that disappearing orders far from the bid/ask spread must have been cancelled (and it's true), but for orders *inside* the spread, this information is necessary.\n",
    "\n",
    "\n",
    "While data has been captured for several days (at the time of this post I'm still capturing data), for the following analysis only data from **July 21, 2017** has been taken. Mind you, there are still **over 2 Million datapoints**.\n",
    "\n",
    "\n",
    "Since the GDAX feed does not explicitly keep information of the current best bid/ask, a little preprocessing is needed. The best bid is the *highest* price for currently open *BUY* orders, while the best ask is the *lowest* price for open *SELL* orders. Although this calculation is not complicated nor particularly slow, it's better to explicitly append the current best bid/ask as additional columns. No further preprocessing has been carried out.\n",
    "\n",
    "## Related work\n",
    "\n",
    "While writing this article, I came across a blog post from Philip Stubbings at *Parasec* [4], who made a **similar analysis in 2014**. While the amount of data differs by orders of magnitude, the findings are the same, especially concerning *flashing orders*. Quoting from his site:\n",
    "\n",
    "> I collected order book event data from the Bitstamp exchange over a **4 month period**, between July and October (2014), resulting in a dataset of **~33 million individual events**; A minuscule dataset in comparison to the throughput on \"conventional\" exchanges, see (Nanex: High Frequency Quote Spam) for example. \n",
    "\n",
    "> While the event dataset consists of ~33 million events, these events can be broken down into individual orders and their types. In total, of the identifiable order types, **there were 14,619,019 individual \"flashed orders\"** (orders added and later deleted without being hit) **representing 93% of all order book activity**, 707,113 \"resting orders\" (orders added and not deleted unless hit) and 455,825 \"marketable orders\" (orders that crossed the book resulting in 1 or more reported trades). \n",
    "\n",
    "As we'll soon see in this report, I recorded **2,169,450** events in less than one day. That means, the number of events per unit of time is ** 8 times bigger than in 2014**. *Flash orders* are still a majority, **representing over 99% of all order book activity**."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analysis\n",
    "\n",
    "### Data exploration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "filename = 'data/2017_07_21_10_52_05.csv.gz'\n",
    "data = pd.read_csv(filename,  parse_dates=['time'], index_col=\"time\")\n",
    "data['time'] = data.index"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First step, load data in memory (2,169,450 trades) corresponding to 723,880 different orders."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loaded 2,169,450 trades\n"
     ]
    }
   ],
   "source": [
    "print \"Loaded {:,} trades\".format(data.shape[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loaded 723,880 orders\n"
     ]
    }
   ],
   "source": [
    "print \"Loaded {:,} orders\".format(data.order_id.nunique())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The provided data feed looks like that:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>client_oid</th>\n",
       "      <th>funds</th>\n",
       "      <th>maker_order_id</th>\n",
       "      <th>order_id</th>\n",
       "      <th>order_type</th>\n",
       "      <th>price</th>\n",
       "      <th>product_id</th>\n",
       "      <th>reason</th>\n",
       "      <th>remaining_size</th>\n",
       "      <th>sequence</th>\n",
       "      <th>side</th>\n",
       "      <th>size</th>\n",
       "      <th>taker_order_id</th>\n",
       "      <th>trade_id</th>\n",
       "      <th>type</th>\n",
       "      <th>bid</th>\n",
       "      <th>ask</th>\n",
       "      <th>time</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</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>2017-07-21 08:52:06.163</th>\n",
       "      <td>150051ad-336a-4429-a1f7-e8e6c07a30fb</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6fdae78f-f00f-4dee-95f2-0ffb6ca2dfb4</td>\n",
       "      <td>limit</td>\n",
       "      <td>2715.35</td>\n",
       "      <td>BTC-USD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3649404788</td>\n",
       "      <td>buy</td>\n",
       "      <td>0.089439</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>received</td>\n",
       "      <td>2715.35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-21 08:52:06.163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-21 08:52:06.163</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6fdae78f-f00f-4dee-95f2-0ffb6ca2dfb4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2715.35</td>\n",
       "      <td>BTC-USD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.089439</td>\n",
       "      <td>3649404789</td>\n",
       "      <td>buy</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>open</td>\n",
       "      <td>2715.35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-21 08:52:06.163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-21 08:52:06.165</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>a7d073fb-c741-4f87-8a43-699462e597a4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2708.71</td>\n",
       "      <td>BTC-USD</td>\n",
       "      <td>canceled</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>3649404790</td>\n",
       "      <td>buy</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>done</td>\n",
       "      <td>2715.35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-21 08:52:06.165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-21 08:52:06.167</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5936f368-9b87-477e-9adc-83f14a525491</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2708.66</td>\n",
       "      <td>BTC-USD</td>\n",
       "      <td>canceled</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>3649404791</td>\n",
       "      <td>buy</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>done</td>\n",
       "      <td>2715.35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-21 08:52:06.167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-21 08:52:06.168</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>71dbb9bf-8a6c-4c0b-8ca2-259d16be43e1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2708.71</td>\n",
       "      <td>BTC-USD</td>\n",
       "      <td>canceled</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>3649404792</td>\n",
       "      <td>buy</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>done</td>\n",
       "      <td>2715.35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2017-07-21 08:52:06.168</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   client_oid  funds  \\\n",
       "time                                                                   \n",
       "2017-07-21 08:52:06.163  150051ad-336a-4429-a1f7-e8e6c07a30fb    NaN   \n",
       "2017-07-21 08:52:06.163                                   NaN    NaN   \n",
       "2017-07-21 08:52:06.165                                   NaN    NaN   \n",
       "2017-07-21 08:52:06.167                                   NaN    NaN   \n",
       "2017-07-21 08:52:06.168                                   NaN    NaN   \n",
       "\n",
       "                        maker_order_id                              order_id  \\\n",
       "time                                                                           \n",
       "2017-07-21 08:52:06.163            NaN  6fdae78f-f00f-4dee-95f2-0ffb6ca2dfb4   \n",
       "2017-07-21 08:52:06.163            NaN  6fdae78f-f00f-4dee-95f2-0ffb6ca2dfb4   \n",
       "2017-07-21 08:52:06.165            NaN  a7d073fb-c741-4f87-8a43-699462e597a4   \n",
       "2017-07-21 08:52:06.167            NaN  5936f368-9b87-477e-9adc-83f14a525491   \n",
       "2017-07-21 08:52:06.168            NaN  71dbb9bf-8a6c-4c0b-8ca2-259d16be43e1   \n",
       "\n",
       "                        order_type    price product_id    reason  \\\n",
       "time                                                               \n",
       "2017-07-21 08:52:06.163      limit  2715.35    BTC-USD       NaN   \n",
       "2017-07-21 08:52:06.163        NaN  2715.35    BTC-USD       NaN   \n",
       "2017-07-21 08:52:06.165        NaN  2708.71    BTC-USD  canceled   \n",
       "2017-07-21 08:52:06.167        NaN  2708.66    BTC-USD  canceled   \n",
       "2017-07-21 08:52:06.168        NaN  2708.71    BTC-USD  canceled   \n",
       "\n",
       "                         remaining_size    sequence side      size  \\\n",
       "time                                                                 \n",
       "2017-07-21 08:52:06.163             NaN  3649404788  buy  0.089439   \n",
       "2017-07-21 08:52:06.163        0.089439  3649404789  buy       NaN   \n",
       "2017-07-21 08:52:06.165        0.200000  3649404790  buy       NaN   \n",
       "2017-07-21 08:52:06.167        0.500000  3649404791  buy       NaN   \n",
       "2017-07-21 08:52:06.168        0.200000  3649404792  buy       NaN   \n",
       "\n",
       "                        taker_order_id  trade_id      type      bid  ask  \\\n",
       "time                                                                       \n",
       "2017-07-21 08:52:06.163            NaN       NaN  received  2715.35  NaN   \n",
       "2017-07-21 08:52:06.163            NaN       NaN      open  2715.35  NaN   \n",
       "2017-07-21 08:52:06.165            NaN       NaN      done  2715.35  NaN   \n",
       "2017-07-21 08:52:06.167            NaN       NaN      done  2715.35  NaN   \n",
       "2017-07-21 08:52:06.168            NaN       NaN      done  2715.35  NaN   \n",
       "\n",
       "                                           time  \n",
       "time                                             \n",
       "2017-07-21 08:52:06.163 2017-07-21 08:52:06.163  \n",
       "2017-07-21 08:52:06.163 2017-07-21 08:52:06.163  \n",
       "2017-07-21 08:52:06.165 2017-07-21 08:52:06.165  \n",
       "2017-07-21 08:52:06.167 2017-07-21 08:52:06.167  \n",
       "2017-07-21 08:52:06.168 2017-07-21 08:52:06.168  "
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are multiple fields and many NaN (Not-a-Number) values. This happens because all sort of orders are mixed, and not every field is relevant to every order. (For details the reader is kindly pointed to the official documentation [7]).\n",
    "We can focus on the most commonly relevant parameters:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "keys = ['price','remaining_size','side','reason','type','order_id']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>price</th>\n",
       "      <th>remaining_size</th>\n",
       "      <th>side</th>\n",
       "      <th>reason</th>\n",
       "      <th>type</th>\n",
       "      <th>order_id</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</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>2017-07-21 08:52:06.163</th>\n",
       "      <td>2715.35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>buy</td>\n",
       "      <td>NaN</td>\n",
       "      <td>received</td>\n",
       "      <td>6fdae78f-f00f-4dee-95f2-0ffb6ca2dfb4</td>\n",
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       "    <tr>\n",
       "      <th>2017-07-21 08:52:06.163</th>\n",
       "      <td>2715.35</td>\n",
       "      <td>0.089439</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>open</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-21 08:52:06.165</th>\n",
       "      <td>2708.71</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>buy</td>\n",
       "      <td>canceled</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-21 08:52:06.167</th>\n",
       "      <td>2708.66</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>buy</td>\n",
       "      <td>canceled</td>\n",
       "      <td>done</td>\n",
       "      <td>5936f368-9b87-477e-9adc-83f14a525491</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-21 08:52:06.168</th>\n",
       "      <td>2708.71</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>buy</td>\n",
       "      <td>canceled</td>\n",
       "      <td>done</td>\n",
       "      <td>71dbb9bf-8a6c-4c0b-8ca2-259d16be43e1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           price  remaining_size side    reason      type  \\\n",
       "time                                                                        \n",
       "2017-07-21 08:52:06.163  2715.35             NaN  buy       NaN  received   \n",
       "2017-07-21 08:52:06.163  2715.35        0.089439  buy       NaN      open   \n",
       "2017-07-21 08:52:06.165  2708.71        0.200000  buy  canceled      done   \n",
       "2017-07-21 08:52:06.167  2708.66        0.500000  buy  canceled      done   \n",
       "2017-07-21 08:52:06.168  2708.71        0.200000  buy  canceled      done   \n",
       "\n",
       "                                                     order_id  \n",
       "time                                                           \n",
       "2017-07-21 08:52:06.163  6fdae78f-f00f-4dee-95f2-0ffb6ca2dfb4  \n",
       "2017-07-21 08:52:06.163  6fdae78f-f00f-4dee-95f2-0ffb6ca2dfb4  \n",
       "2017-07-21 08:52:06.165  a7d073fb-c741-4f87-8a43-699462e597a4  \n",
       "2017-07-21 08:52:06.167  5936f368-9b87-477e-9adc-83f14a525491  \n",
       "2017-07-21 08:52:06.168  71dbb9bf-8a6c-4c0b-8ca2-259d16be43e1  "
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[keys].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now the data is clearer. Each order is defined by its **arrival time** (at the server), its **price**, **amount**, **side** (*buy* or *sell*), **status** and **unique id**. We see that for the first 5 orders, 3 of the are cancellations! (more about that soon)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Granularity of data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's take the time different between arriving orders, and plot as histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dt = data.time.diff().iloc[1:].dt\n",
    "dt = dt.seconds.astype(np.float) + dt.microseconds*1e-6  \n",
    "dt*=1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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CAgIkSUFBQVdFD7D6OoCZGYbh6wgwsTVr1uijjz7SW2+95esoMJlP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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3357daba90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dt.sort_values().diff().hist(bins = np.arange(0,10,0.1)); \n",
    "plt.yscale('log')\n",
    "plt.xlabel(\"Delay (ms)\")\n",
    "plt.ylabel(\"Number of trades\")\n",
    "plt.title(\"Delay between trades (log scale)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We see that a large amount of orders take place simultaneously, and that the smallest *non zero* value of time delay is 1 **ms**. We can directly confirm it with code:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Minimum non zero number of milliseconds:  1.0\n"
     ]
    }
   ],
   "source": [
    "print \"Minimum non zero number of milliseconds: \", dt[dt>0].min()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Analysis of orders by id"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>price</th>\n",
       "      <th>remaining_size</th>\n",
       "      <th>side</th>\n",
       "      <th>reason</th>\n",
       "      <th>type</th>\n",
       "      <th>order_id</th>\n",
       "      <th>order_type</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</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>2017-07-21 08:52:46.605</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>buy</td>\n",
       "      <td>NaN</td>\n",
       "      <td>received</td>\n",
       "      <td>9144b925-ecb6-40fa-880b-2e9f83039812</td>\n",
       "      <td>market</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-21 08:52:46.605</th>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "      <td>buy</td>\n",
       "      <td>filled</td>\n",
       "      <td>done</td>\n",
       "      <td>9144b925-ecb6-40fa-880b-2e9f83039812</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         price  remaining_size side  reason      type  \\\n",
       "time                                                                    \n",
       "2017-07-21 08:52:46.605    NaN             NaN  buy     NaN  received   \n",
       "2017-07-21 08:52:46.605    NaN             0.0  buy  filled      done   \n",
       "\n",
       "                                                     order_id order_type  \n",
       "time                                                                      \n",
       "2017-07-21 08:52:46.605  9144b925-ecb6-40fa-880b-2e9f83039812     market  \n",
       "2017-07-21 08:52:46.605  9144b925-ecb6-40fa-880b-2e9f83039812        NaN  "
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data.order_id=='9144b925-ecb6-40fa-880b-2e9f83039812'][keys+['order_type']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "An interesting observation that will be useful later is that each order_id appear at most three times (99.01%). That means, the order arrives, the order waits (\"open\") and the order is matched or cancelled. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3 716746\n",
      "2 5048\n",
      "1 2086\n"
     ]
    }
   ],
   "source": [
    "for order, freq in Counter(data.groupby('order_id').size()).most_common():\n",
    "    print order, freq"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Analysis of orders by outcome\n",
    "\n",
    "An incoming order has two possible outcomes. Either it is filled (matched with an existing or incoming order) or is is cancelled. During this observation 7,053 orders were filled, while a majority of 714,648 where *Cancelled*. That is a 99.02% of incoming orders were ultimately cancelled!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "reason\n",
       "canceled    714648\n",
       "filled        7053\n",
       "dtype: int64"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.groupby('reason').size()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Grouping orders"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A different exchange, Bitfinex, has been previously analyzed (not shown here for the sake of conciseness). Its data-feed had some major drawbacks that ultimately made me drop it and work with GDAX. Nevertheless, its so called \"Raw Book Order\" feed, showed interesting information. In that exchange traders don't seem to Send/Cancel many orders, but rather Send/Update/Update/Update/.../Update/Cancel. I don't fully understand why, but I guess it could be to bypass API Limits and to optimize execution of orders (by keeping the place in the order book at a given price). \n",
    "\n",
    "In any case, I saw that quickly arriving and cancelling orders (flashing orders) at a given price and similar amount are caused by the same individual. Knowing that, let's find orders at a given price and amount. For example, 0.5BTC@$2707.81"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>price</th>\n",
       "      <th>remaining_size</th>\n",
       "      <th>side</th>\n",
       "      <th>reason</th>\n",
       "      <th>order_id</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</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>2017-07-21 08:58:07.488</th>\n",
       "      <td>2707.81</td>\n",
       "      <td>0.5</td>\n",
       "      <td>buy</td>\n",
       "      <td>canceled</td>\n",
       "      <td>04211005-4140-44c5-98d6-65fcec8eb9e5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-21 08:58:57.500</th>\n",
       "      <td>2707.81</td>\n",
       "      <td>0.5</td>\n",
       "      <td>buy</td>\n",
       "      <td>NaN</td>\n",
       "      <td>17eb23e8-b967-4413-89ed-31ab57f2fc3c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-21 08:58:57.741</th>\n",
       "      <td>2707.81</td>\n",
       "      <td>0.5</td>\n",
       "      <td>buy</td>\n",
       "      <td>canceled</td>\n",
       "      <td>17eb23e8-b967-4413-89ed-31ab57f2fc3c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-21 10:47:39.363</th>\n",
       "      <td>2707.81</td>\n",
       "      <td>0.5</td>\n",
       "      <td>buy</td>\n",
       "      <td>NaN</td>\n",
       "      <td>44c11417-a3a0-4d3c-9672-5b35d59e97e4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-21 10:47:39.882</th>\n",
       "      <td>2707.81</td>\n",
       "      <td>0.5</td>\n",
       "      <td>buy</td>\n",
       "      <td>canceled</td>\n",
       "      <td>44c11417-a3a0-4d3c-9672-5b35d59e97e4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           price  remaining_size side    reason  \\\n",
       "time                                                              \n",
       "2017-07-21 08:58:07.488  2707.81             0.5  buy  canceled   \n",
       "2017-07-21 08:58:57.500  2707.81             0.5  buy       NaN   \n",
       "2017-07-21 08:58:57.741  2707.81             0.5  buy  canceled   \n",
       "2017-07-21 10:47:39.363  2707.81             0.5  buy       NaN   \n",
       "2017-07-21 10:47:39.882  2707.81             0.5  buy  canceled   \n",
       "\n",
       "                                                     order_id  \n",
       "time                                                           \n",
       "2017-07-21 08:58:07.488  04211005-4140-44c5-98d6-65fcec8eb9e5  \n",
       "2017-07-21 08:58:57.500  17eb23e8-b967-4413-89ed-31ab57f2fc3c  \n",
       "2017-07-21 08:58:57.741  17eb23e8-b967-4413-89ed-31ab57f2fc3c  \n",
       "2017-07-21 10:47:39.363  44c11417-a3a0-4d3c-9672-5b35d59e97e4  \n",
       "2017-07-21 10:47:39.882  44c11417-a3a0-4d3c-9672-5b35d59e97e4  "
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w=data[(data.price==2707.81) & (data.remaining_size==0.5)]\n",
    "w[['price','remaining_size','side','reason','order_id']].tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's focus on order 04211005-4140-44c5-98d6-65fcec8eb9e5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>price</th>\n",
       "      <th>remaining_size</th>\n",
       "      <th>side</th>\n",
       "      <th>reason</th>\n",
       "      <th>order_id</th>\n",
       "      <th>type</th>\n",
       "      <th>bid</th>\n",
       "      <th>ask</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</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>2017-07-21 08:58:07.193</th>\n",
       "      <td>2707.81</td>\n",
       "      <td>NaN</td>\n",
       "      <td>buy</td>\n",
       "      <td>NaN</td>\n",
       "      <td>04211005-4140-44c5-98d6-65fcec8eb9e5</td>\n",
       "      <td>received</td>\n",
       "      <td>2713.2</td>\n",
       "      <td>2714.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-21 08:58:07.193</th>\n",
       "      <td>2707.81</td>\n",
       "      <td>0.5</td>\n",
       "      <td>buy</td>\n",
       "      <td>NaN</td>\n",
       "      <td>04211005-4140-44c5-98d6-65fcec8eb9e5</td>\n",
       "      <td>open</td>\n",
       "      <td>2713.2</td>\n",
       "      <td>2714.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-21 08:58:07.488</th>\n",
       "      <td>2707.81</td>\n",
       "      <td>0.5</td>\n",
       "      <td>buy</td>\n",
       "      <td>canceled</td>\n",
       "      <td>04211005-4140-44c5-98d6-65fcec8eb9e5</td>\n",
       "      <td>done</td>\n",
       "      <td>2713.2</td>\n",
       "      <td>2714.51</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           price  remaining_size side    reason  \\\n",
       "time                                                              \n",
       "2017-07-21 08:58:07.193  2707.81             NaN  buy       NaN   \n",
       "2017-07-21 08:58:07.193  2707.81             0.5  buy       NaN   \n",
       "2017-07-21 08:58:07.488  2707.81             0.5  buy  canceled   \n",
       "\n",
       "                                                     order_id      type  \\\n",
       "time                                                                      \n",
       "2017-07-21 08:58:07.193  04211005-4140-44c5-98d6-65fcec8eb9e5  received   \n",
       "2017-07-21 08:58:07.193  04211005-4140-44c5-98d6-65fcec8eb9e5      open   \n",
       "2017-07-21 08:58:07.488  04211005-4140-44c5-98d6-65fcec8eb9e5      done   \n",
       "\n",
       "                            bid      ask  \n",
       "time                                      \n",
       "2017-07-21 08:58:07.193  2713.2  2714.51  \n",
       "2017-07-21 08:58:07.193  2713.2  2714.51  \n",
       "2017-07-21 08:58:07.488  2713.2  2714.51  "
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data.order_id==\"04211005-4140-44c5-98d6-65fcec8eb9e5\"][['price','remaining_size','side','reason','order_id','type', 'bid','ask']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This BUY order was placed **and cancelled 295 ms later** at a level of $2707.81 (when the best ASK price was 2714.51). It seems obvious that this order had no expectation of being filled. \n",
    "Let's see if orders are flashed at higher or lower frequencies than 295 ms."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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qDw8P9e7dWwMHDtQ777yjwYMHS7oZov39/bPt8QQA3JnF\n3M25FwAAALkwbNgwDRgwQG3atMnXfPr06aOIiAgevQAAeUDPHgAAKHAvvfSS3njjjXw/VL1ly5YE\nPQDII3r2AAAAAMAB0bMHAAAAAA6IsAcAAAAADoiwBwAAAAAOiLAHAAAAAA6IsAcAAAAADoiwBwAA\nAAAO6P8BG+wZ1WyJmZIAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3380092cd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "canceled_idx = data.order_id[data.reason==\"canceled\"]\n",
    "d = data[data.order_id.isin(canceled_idx)]\n",
    "g = d.groupby(\"order_id\")\n",
    "dt = g.time.last() - g.time.first()\n",
    "duration = dt.dt.seconds.astype(np.float) + dt.dt.microseconds*1e-6  \n",
    "duration*=1000\n",
    "duration.hist(bins = np.arange(0,300,2));\n",
    "plt.yscale('log')\n",
    "plt.title(\"Number of orders for each lifespan (log scale)\")\n",
    "plt.ylabel(\"Number of orders (log)\")\n",
    "plt.xlabel(\"Time from arrival to cancellation (ms)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Indeed, there are orders flashing at <5 milliseconds! Let's see some of the fastest flashing orders:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "order_id\n",
       "7f043088-f9ad-46f6-bfae-e577db3f7363    3.0\n",
       "7162ca12-94eb-4b50-9249-3562152add62    3.0\n",
       "42af6ed7-aeb1-4cb7-b787-e19c4a54f418    3.0\n",
       "bf51ca32-5b6d-4a7d-ac78-433a1dd1f27e    4.0\n",
       "47a435dc-3627-4d07-b702-cb27e60ec329    4.0\n",
       "Name: time, dtype: float64"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "duration[duration>1].sort_values().head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For example, let's take order_id 7f043088-f9ad-46f6-bfae-e577db3f7363"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>price</th>\n",
       "      <th>remaining_size</th>\n",
       "      <th>side</th>\n",
       "      <th>reason</th>\n",
       "      <th>type</th>\n",
       "      <th>order_id</th>\n",
       "      <th>bid</th>\n",
       "      <th>ask</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>time</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>2017-07-21 12:45:45.516</th>\n",
       "      <td>2769.99</td>\n",
       "      <td>NaN</td>\n",
       "      <td>sell</td>\n",
       "      <td>NaN</td>\n",
       "      <td>received</td>\n",
       "      <td>7f043088-f9ad-46f6-bfae-e577db3f7363</td>\n",
       "      <td>2767.87</td>\n",
       "      <td>2767.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-21 12:45:45.516</th>\n",
       "      <td>2769.99</td>\n",
       "      <td>0.5</td>\n",
       "      <td>sell</td>\n",
       "      <td>NaN</td>\n",
       "      <td>open</td>\n",
       "      <td>7f043088-f9ad-46f6-bfae-e577db3f7363</td>\n",
       "      <td>2767.87</td>\n",
       "      <td>2767.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-07-21 12:45:45.519</th>\n",
       "      <td>2769.99</td>\n",
       "      <td>0.5</td>\n",
       "      <td>sell</td>\n",
       "      <td>canceled</td>\n",
       "      <td>done</td>\n",
       "      <td>7f043088-f9ad-46f6-bfae-e577db3f7363</td>\n",
       "      <td>2767.87</td>\n",
       "      <td>2767.96</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           price  remaining_size  side    reason      type  \\\n",
       "time                                                                         \n",
       "2017-07-21 12:45:45.516  2769.99             NaN  sell       NaN  received   \n",
       "2017-07-21 12:45:45.516  2769.99             0.5  sell       NaN      open   \n",
       "2017-07-21 12:45:45.519  2769.99             0.5  sell  canceled      done   \n",
       "\n",
       "                                                     order_id      bid  \\\n",
       "time                                                                     \n",
       "2017-07-21 12:45:45.516  7f043088-f9ad-46f6-bfae-e577db3f7363  2767.87   \n",
       "2017-07-21 12:45:45.516  7f043088-f9ad-46f6-bfae-e577db3f7363  2767.87   \n",
       "2017-07-21 12:45:45.519  7f043088-f9ad-46f6-bfae-e577db3f7363  2767.87   \n",
       "\n",
       "                             ask  \n",
       "time                              \n",
       "2017-07-21 12:45:45.516  2767.96  \n",
       "2017-07-21 12:45:45.516  2767.96  \n",
       "2017-07-21 12:45:45.519  2767.96  "
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[data.order_id==\"7f043088-f9ad-46f6-bfae-e577db3f7363\"][keys+['bid','ask']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Three milliseconds is an extremely short amount of time considering the GDAX Rate Limits:\n",
    "\n",
    "> ### Rate Limits\n",
    "> 1. We throttle public endpoints by IP: 3 requests per second, up to 6 requests per second in bursts.\n",
    "> 2. We throttle private endpoints by user ID: 5 requests per second, up to 10 requests per second in bursts.\n",
    "> 3. The FIX API throttles each command type (eg.: NewOrderSingle, OrderCancelRequest) to **30 commands per second**.\n",
    "\n",
    "What's **Really interesting** is that these patterns seem to exceed the API Limits (the highest, at 30 command per seconds, means 1 order each 33 ms)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So we can confidently say that **there are bots manipulating the order books**. The next question is, how many? and are they controlled by the same person? Let's find out..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Bots trading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def plotCancelBehaviourForPriceAndSize(price, size, lim=-1):\n",
    "\n",
    "    plt.figure(figsize=(15,5))\n",
    "    #q = data[data.order_id==most_prolific_bots.index[0]]\n",
    "\n",
    "    q = data[((data['size']==size) | (data['remaining_size']==size)) & (data['price']==price)].head(lim)\n",
    "    t=q.time.diff().median()\n",
    "    median_tick_s = t.seconds+t.microseconds*1e-6;\n",
    "    \n",
    "    order_type = q.side.iloc[0]\n",
    "    \n",
    "    d = data.loc[q.index[0]:q.index[-1]]\n",
    "    \n",
    "    d.bid.plot(label=\"bid price\"  )\n",
    "    d.ask.plot(label=\"ask price\")\n",
    "    q[q.reason!=\"canceled\"].price.plot(label=\"%s %.2f BTC @ %.2f\" % (order_type, size, price), style='o');\n",
    "    ylim0 = min(d.bid.min(), q.price.min())\n",
    "    ylim1 = max(d.ask.max(), q.price.max())\n",
    "    plt.vlines(q.index[q.reason==\"canceled\"], ylim0, ylim1, alpha = 0.2);\n",
    "    plt.xlabel(\"Time\")\n",
    "    plt.ylabel(\"Price (USD)\")\n",
    "    plt.title(\"Cancelled orders along time for %.2f BTC @ $%.2f. Median tick: %.1f milliseconds\" % (size, price,median_tick_s*1000))\n",
    "    plt.legend(loc='best', frameon=True)\n",
    "    \n",
    "    plt.ylim(d.bid.min(), d.ask.max())\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's see the cancel behavior for different price levels and amounts. Red points are SELL orders (not always visible), vertical grey lines are cancellations and the blue and green lines are bid and ask price, respectively."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
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PpKQkOnXqlK1ecnIybm5ubN26ldGjR/PKK6/k2Bs4b948QkNDeeKJJ5g/fz5Dhw7NNS6b\nxMRESpYsmaeyAOfPn6dEiRKUKVOGr776iokTJ6LT6fD29iYgIICGDRvi4eGByWTKVtfPz4/169ej\n1+u5cOECzZs3Z968ednuzdu0aRP79+9X7yu0OXToEIqiZDt2jh49SuvWrZk+fTqzZs3K9s+D3Li7\nuzNjxgyGDRvGo48+yvTp05k6dSoABoPBoS13d3cMBkOe2vXy8qJRo0bs2bMHgC1btqjHKkBERASx\nsbF0794dsCbO/v7+HD16lD/++IPWrVvj5eWFu7u7et6wd7tj0svLi+DgYMB6vOV0znLm4MGDNGzY\nkDJlyqDRaJg/f77DfcVffPEFly9fZtq0aXluE+Cjjz4iNjZWvTIgp30/q/T0dNzc3NT3uW2Hhg0b\nUqJECfz8/ChVqhStWrUCoEaNGvlOnnx8fIiLi+OHH34gMTGRfv360bVr11y/F/bt20dISAguLi54\ne3uzdetW6taty549e+jatSuenp7odDqH+4LB+ffS8ePHqVSpkvpPmq5du6rl83LeFkLA7a+1EUL8\np/n5+amX9eTk4sWLvPPOO0RERKDVarlx4wbdunVT53t7e6uvdTodZrOZ+Ph4fHx81Om2H4RJSUlE\nRkYSGhrqMM92iWZWycnJHD582KG8t7c3CQkJJCYmOvx33H559uLi4tQeJwBfX19iY2Md3gNqkmD7\nPBqNRm0ztzjs2wB44YUXsFgsTJ8+nZs3b/L8888zatQotTfGZs2aNWzcuBGj0YjRaMw23xa7/efy\n8fFx+EFm+/y2yxctFgtJSUlqwgY4vM4rLy8v9bVWq8XT0xOwrhOtVovZbCY5OZmdO3eqPbaKopCZ\nmZlru3FxcRQrVszhs9p+MJYsWdJhPToTHR3NkCFDCAoKYvjw4dnmp6enM3fuXJYsWZJtXrFixTCb\nzfTp0weAJ554gnLlynH8+HGnPX3jxo1Tk+9r164xdOhQNBoNbdu2zTXGvBxT9i5dukS1atWIi4vD\n1dVV/WdNSkoKZ8+epUqVKpw4cYLKlSs7rV+uXDkmTpzIqVOnCAsL47XXXqNChQrqPxXWrl3LypUr\nWbVqFaVKlXKou3nzZqeJRMOGDdm7dy9//fUXQ4YM4ZNPPlEvE72dqKgopkyZwvr169XBYkaOHMmO\nHTvw8PBwuJzSYDCo+1ZedOrUic2bN9OwYUNiYmJ4+OGH1XlJSUmkp6c7JH4pKSnqucL+h35O54rc\njkn7c41Wq8ViseQ57qznQ/vELCYmhvnz5xMUFJSnS5xt5s+fz8GDB/n000/x9PTMdd/PysPDQ+2B\nhdy3g/25QKfTqeXyuw7Aei5avHgxK1asYMaMGTRt2pTp06fn+r2Qdd3Zln+787qz76Ws3xn/5rwt\nxINOkkMh7nMNGjQgNjaWU6dOOVzClJmZyQcffMDw4cN56623eOSRR1iyZAk6nY7evXvftl0/Pz/i\n4+PV9waDQf2BVqVKFacjN9ruX7FXunRpHn/8cYf73Gx8fHwc7jOMi4tzuJTLpmTJkg69QwkJCU57\ndmw/FFJSUihWrBgWi4XExMTbxpGVXq9n6NChDB06lAsXLjBkyBAaN26s/lccIDw8nE8++YT169cT\nEBDAwYMH1d4VZ7Hbeshyit2et7e3eu8NWBOqwlC6dGmeeeYZJkyYkOc6JUqUIDExEUVR1B9deem9\nBut2GTx4MN26dctxNNc///yTGzduqIlReno6mZmZxMXF8e677wKQmppK8eLFAeuPRq329hfJlC9f\nnjZt2rBv377bJofNmjXjiy++YMSIEQ4/LMPDw7ly5QpPP/20Q3mDwYC7uzvFihUjMzOTa9eu4efn\nx/Lly9Hr9ZhMJj766CNeffXVbMvas2cPFSpUoHr16oD1ks5nn32W//3vf4B15Nu1a9fy+eefO/0n\nwZ49exg4cKD6PiEhgX379qkx1qpViwYNGnDo0KE8J4dHjx4lICBAHQWyWbNmaLVazp8/T5UqVbh0\n6ZJa1pYY51Xr1q0JCwvjhx9+cEgkwLo/enl5Ob137tixY9nOFVnl9Zj8N/z8/Dh69Kj6PiUlRb0/\n19XVlY0bNzJgwAB27tyZp9FLFy9eTHh4OKtXr1aToNz2fft7lQF1O9j+4ZDf7XAnmjdvTvPmzUlL\nS2POnDm8++679OzZM8fvhazfJTExMbi7u+f5vG7P2XeGTV7O20IIuaxUiPuej48PL774IhMmTFB/\ntBkMBqZNm8bp06fx8PAgNjaWhx9+GJ1Ox8GDB7l06ZJD8uFM48aNiY6OVoew//DDD1myZAn169cn\nOjqa48ePA9Z7+caNG6cOFpBVy5YtOXz4sHp514kTJ3j77bcBa2K7a9cuAC5fvsyRI0ecttGmTRs2\nbNiA2WwmLS2N7777zmlPkbu7O7Vq1WLnzp2A9bI123/Xc4sjq2nTpqmXNwUGBlKyZMls/32Oi4uj\nRIkSlC9fHoPBwMaNG0lLS8u2Htq0acO6devUOjt37lQvg82J7ZKr9PR0kpKS2LZtm9Nyer2etLQ0\np5cr5kVQUBA//vij+gNr165d2X6EZhUQEEDZsmXZunUrYP1BHhMTQ7169W67vPfee4/mzZvn+piP\nJk2acPjwYQ4ePMjBgweZMmWKOpCPj48PLVu2VAf8OH78OFevXqVu3bq3XXZKSgq//PJLnn5Ad+3a\nlczMTGbOnKn2kp07d45x48apPbz2AgICOHv2LK6urkybNo1Ro0bx+uuv8+yzz1KvXj169erF008/\n7XTI/YsXLzJr1iz1B29KSgq7d+/mkUceISoqigULFrB8+XKniWFsbCxxcXE89NBD6jS9Xs+MGTPU\n+wVjY2M5fvx4vob7r1y5MufOnVMvPT916hTJyckEBgbSvn17tmzZQkxMDCaTidWrV+frsmc3Nzee\neOIJVqxY4XBJKUCFChUoW7asmhzGxcUxduxY0tLSaNiwIQcOHMBgMGAwGJwmkHk9JnPj4uKCxWLJ\n9uiR1q1bq/8cUBSFN998Ux1gyMfHh/LlyzN79mymT5+e41UUNn/++SebNm3i448/dugdy23fz6p9\n+/Z8/vnnmM1mbt68me0S3cJy4MABpk+fjsViwdPTk1q1aqHRaHL9XggKCmLLli0YjUbS0tJ47rnn\n+N///kebNm34/vvvMRgMmEwmNmzY4PS8bq9u3bpcuHCBixcvAjjcj52X87YQQnoOhXggjBo1Cl9f\nX1566SXMZjNarZYnn3xSHXDlpZdeYvbs2Xz44Yc8+eSTjBw5kkWLFjlc0pWVh4cHixcvZty4cQBU\nqlSJd955B3d3dxYtWsSMGTNITU3FxcWF0aNH5/glXLp0aWbMmMGIESPIzMzEy8uLyZMnAzBs2DBe\nffVVgoKCqFq1Kk899ZTTNvr160dkZKQ60EZoaKjTe44AwsLCmDx5MkuXLqVVq1bqvSm5xZFV7969\nmTZtGjNmzFB/3GS9j+6JJ57giy++IDg4mDJlyjB58mSOHz/OK6+84tAzNWbMGMLCwggNDUWr1TJ0\n6NDbJlLt2rVjz549hIaGUqlSJdq3b6/+2LdXs2ZNfH19adGiRY6D1uTmkUceYfjw4epopCVKlGD6\n9Om51tFoNCxYsIA333yTDz74AA8PD95///08XVr41VdfUbp0afbt26dOGzBgAH369GH8+PHqqKm5\nmTlzJhMmTCAoKAhvb28WLlyo9iJmNW/ePHXQEUVR6NChg9orkxt3d3fWrFmj3rPo5uaGj48PkydP\ndhhAxaZOnTpcvHiRkydP0qlTJ4fLPBctWkRCQkKOMfbr14+rV6/Svn174uPj6dy5M+3bt6dbt24s\nX76c1NRUdYATsCZ/tsGYbty4gb+/v0PPqbe3N4sXL2bevHmkpqaiKAp9+/blscceIyYmhr59+zos\nW6fTsWrVKgAGDx7M5s2bqVWrFq+99hpDhgzBYrHg6urKvHnzKF68OMWLF2fQoEE8//zzKIrC448/\nrl7mu3PnTnbv3s3s2bNzXb8dO3bk9OnT2RJ1274VFhbGe++9h1arZeDAgXh6etK2bVv1mChZsiSt\nW7fONihNbsek/efOTalSpWjcuDFt27Zl6dKl6vSyZcvy1ltvMWDAAHQ6HXXr1mXgwIEcO3ZMLdOk\nSRM6duxIWFgYixYtYsCAAYwfPz7boDRff/01ycnJ9OjRQ51WoUIFPv3001xjsz9G+vfvT0REBKGh\noeh0OkaMGJHnnuE70bRpU7Zs2UJISAiurq74+/sza9asXL8XOnTowNmzZ3nqqadwc3Oje/fuNGrU\nCEVROHv2LN26dUNRFJo1a6aOZpwTf39/JkyYwMCBA/Hy8nJYh3k5bwshQKPk519mQggh7gn2l22u\nXbuWX375JU/3IomicfjwYcaPH8+4ceMIDg7GxcWF6OhoNm7cyNdff822bdtwcXHJtY1+/fqxZs2a\nuxSxEEKIB5Ekh0II8R9z5swZRowYwcaNG/Hy8mLw4MG0bNmSIUOGFHVoIhcXLlxg2bJlnDhxApPJ\npF4G+/zzz+dr9FMhhBCisEhyKIQQ/0GLFi3iu+++Q6fT0aBBA6ZPn64+lkMIIYQQ4t+Q5FAIIYQQ\nQgghhIxWKoQQQgghhBBCkkMhhBBCCCGEEDxgj7Loue4lqrs/xFPFWwEQEXGOK1cinZYNCLj1oO0j\nR/4gNjaG2rXrqPOqVKlGRMQ5AKpUqUbt2o84baco+fl5Eh+f+7PqHjSnT58CyHF7bd78HWDdplnL\n2dd11k5ObZ8+fQofH3cCAqr+67j+i06fPsW+fT8TEFCRK1ciOX36T0qUuDXoRuPGTQHr8dW4cVOq\nVKnGvn0/ExV1Qy1TpkxZWrVqq67zrMesfVn7OvbzbO8BNZaEhFiuXbsOQIkSJdUytmPbPo7GjZvS\nqVOXAlknRc1+HUZF3XBY7/aiom6o5zzbOgNo1cr6CI6IiHMO5z3bto6KuuGw/suUKetQ3zbdXuXK\ngZQocesZfUeO/AFYt5v9NrCdc+/V8+39Ij/fG862u03W49j+O9Ump+/frO3ExsY4HKc2rVq1Vffn\nrPuZje2YBufn5nt9n5Lv8XtHfreFbf+CW/u6/XnxyJE/sh0b9udmcPx+XL/+S+DWuTGn48qebd+3\nP+/b6tn2+82bv3M479rYzvdwb/42edCPjaz7l/05NzY2BsDhN1fW7+OpUyfl2PYD13OYZjEUdQh3\njV6f/WHMomjItri3aLXy4ON7hWyLe4ucq+4tsj3uHbIt7i2yPQrPA5UcumvcSDM/OMmhEEIIIYQQ\nQuTVA3VZqafOgxRzKnGmBACSNWmku2Y6LZusudVVbfJUUIxatWyyJo04UwJGMnEl94cWCyGEEEII\nIcR/wQOVHHprvYgzJfBljPW+MjyAys7L/s31W28aA3ir0/7mOsQcReuhJcjQtBAjFkIIIYQQDxqd\nTouXlxcuLno0GvDy8gLA3d0dLy8v3N3dcXHJ/We85p+r9l1c9NnqaTRgMmXi4qJ3aDtrXbCWu9cY\njcZ7Mq67RaNB3f62bWtjNGYA4OrqitFozHfbD1Ry2NS7Pj7p3vDPkx2TkhJJSU1xWtbby1t9HR19\nk/T0dPz8/dV5KR7pxJkSyNDkf6ULIYQQQgjhTNmyZQgMrES9eg3w8PDE1dWVPn36AqDXu2AyZaLX\nu+DikvvVa66uroB1MJLMzEyHerZ5TZs2p06demrbNvbJxr0oMfHBHYwGoGLFQHUAIdu2tTGbzQCY\nTCaOHTvCyZMn89X2A5UclnUtRVnXUur7iNhzXLmZh9FKz8dhjE2nQm1/dd4133jiTAmYsRRu0EII\nIYQQ4oHg6upKYGAlXF09MJlS0Wp16HR6NBrrMCEajVb902pzH5RFp7P+zNdqzWg0Zod6Op0evd4F\nrVbn0HbWuuCYNN4r9HotPMC/wXU6E1qtNQm0bdtbrOvF3d2DBg0ac/bs2Xy1/UANSFOQdBrrAWnR\nPLg7phBCCCGEKDguLi7o9a5FHYa4T7i5ud22hzkrSQ7/Jf0/yaEJcxFHIoQQQgghhBB3TpLDf0mv\nsXa3/+V6sWgDEUIIIYQQooDs3r2TpUuXZJv+5puTyMhId5h28OB+Zs4My/cy1qxZyZ9/nvi3IYpC\n9EDdc1hY03NFAAAgAElEQVSQarg/xC/Jh9EiD3AWQgghhBD3t+nTZxdYW/36vVBgbYmCJcnhv+Sl\n88RF0WOxDX0qhBBCCCHEfeDGjetMnjyO6Oib9O79PJ06daF7986sXr2O69ev8fbb0/Dx8aV8+YBs\ndbdu/YHffvuF1NRUoqNv0rPnc3Ts+DS9ez9D8+Yt8PPz48qVSNq0eZJmzR7j7bffJCrqOq6ubrzx\nxnT8/Uswd+5Mrl27islk4sUXh9O4sTw67m6R5PAOaBUNlgd4pCQhhBBCCFF4vv/1CiciErFY/hnj\nQqMBRQGNBs1trl7T/POwQkVRUFDUeg2q+tGjTdVc6165EslHH31KWloqw4cPomPHp9V5K1cuZ9Cg\noTzxRBvefXc2JlP2+hcuRLBixVpSUlJ44YU+tG/fCZPJRPPmj9O8+ePqpajbtm2mRIkShIXNZNeu\nHRw4sA8PDw9KlCjJpEnTSEhIYPTo4axa9VXeV5q4I5Ic3gEtWtK06SiK9B4KIYQQQoj7Q506ddHr\n9fj4+OLl5UViYqI67+LFCOrUqQ9Aw4aNOXTol2z1GzRohF6vp3jx4hQrVozExAQAatd+xKHc2bN/\n0aSJtVcwODgEgHffnc3x40c5ceIYABkZGWRmZuZ71E3x70hyeEes/5E5nnaaR6hTxLEIIYQQQoj7\nydOPBdCjTVXi4+MA6zMHbQ+ztz3IPidubm6ANbkyGo15rge3eh1vvb/1WlFAq7VOsFicX0FnsSgO\n5W2/mbM+M1Gn0zqUtZXp338Q7dqF3jZOUfBktNI7UNFUBoBkc2oRRyKEEEIIIUTBOH36FGazmYSE\neAwGAz4+vuq8wMBK/PXXGQDCw484rX/q1Il/6ieQlpaKr6+v03K1atUmPPwPwDry6erVK6hduw4H\nDuwFID4+zunIqaLwFGrP4dy5czly5Agmk4lhw4axefNm4uPjAUhISKBBgwZMnz6dt956i7Nnz2Iy\nmejZsyc9evQAYNu2bUyePJl169ZRo0aNbO1fv36dESNG0KxZMyZMmFCYH8Wp0mZ//sclLIrcdyiE\nEEIIIe4PFSsGMmPGNK5du8LQoS879CQOGDCYWbOms379l5QvXwGTKTNb/bJlyzN16kSuXo1k6NCX\n0Wqd90cFB4dw+PDvjBw5FJ1OzxtvhOHn5094+B8MHz4Is9nMoEFDC+1ziuwKLTk8dOgQf//9N+vW\nrSM+Pp5nnnmGPXv2qPMnTZpEjx49CA8PR6/X8+WXX5KamkpwcDDPPvsshw8fZt++fdSsWTPHZUye\nPJnHHnssxy7twmZ7jIVZBqURQgghhBD3gaCgdnTp0k197+HhAcCGDT8AULNmLVat+jLXNipUCGDk\nyDEO02z1AaZMCVNfT536Vrb6EydOzXfcomAUWnLYtGlT6tWrB4CPjw8GgwGz2YxOpyMiIoLk5GR1\nfpMmTQCIi4vD19cXrVZL7dq1efTRR+nXr1+Oy1i8eDE//vgjf//9d2F9jFzZksM4UzyKomS7PlsI\nIYQQQggh/isKLTnU6XR4enoCsGHDBlq1aoVOpwNg9erV9O3b16H8K6+8Qnh4OPPmzQPA29v7tsvI\nS5nCpFWsnycqM4Zfrv1OiwrNijQeIYQQQgghilKHDp2LOgRxBwp9tNJdu3axYcMGVqxYAYDRaOTI\nkSOEhYU5lFu0aBFXr15l8ODBbNiwoVASPx8fd/R6nfo+JsYDLy+3HMp6qK89PFxxc3NRy/r4eODv\n70WpGB8qmssQqUSRrkujVKliBR7znboXYypK/v5eQM7rxbbdnZWzn3a7+flZZl7L/Nf4+3vh5eWG\nj4/1OHNzc8HD49YIabZ17eHhqh5TXl5uDmW8vNysx9o/6zzrMWtf1r6O/Tz78rZYkpLAzc1FLZf1\n2LaPw8fH477ZLvbrMOt6t2d/zrOtM1t9sJ47bdvFNt3Wpv36z1rfNj2rrOdbINs2sMVuv1xROPK6\nfp1td5usx7H9Nraffju2fdHZMuz356z7mY1t33H2uf4r+9S9HNuDJj/bwrZ/AU7Pi/avbby83DCZ\n0tHpNGi11j+dToNer1VHB9XpNFgs1uk6Xe5XrOn11vv8TCZNtnp6vRa9Xqsuy9Z21rpZX99L7tW4\n7ga9XovJ5LhP2NiuZNRqNSiKBnf37N/nubZdOCFb7d+/n48//pjly5dTrJj1gPrjjz/Uy0kBzp8/\nD0DVqlWpUKECFStWJCIiwqFMQUlKSs/y3kBqakYOZQ3qa4PBSEZGplo2KclAXFwqSUkGKmjLEOke\nRXKKgejo5AKP+U6UKlXsnoupqMXFWUeWzWm92La7s3L20243P+sy/f29ct0Wt4vrvyguLpXU1Az1\nOMvIyMRgMKrzbevaYDCqx1RqaoZDmdTUDOLiUtV1nvWYtS9rX8d+nn15+/oZGZlquazHtn0cSUn3\n3rH9b9mvw6zr3Z79Oc9+ndn2U1s923qxX2f26z9rfdv0rLKeb4Fs28AWu/1yRcHLz/eGs+1uk/U4\ntt/G9tNvx7YvOluG/f6c0/e5bZ8B5+fme32fku/xe0d+t4Vt/wKcnhftX9ukpmaQnp6J2aygKAoW\ni4LZrGAyWdTHPZjNt6abzbk/Z9tksqh1stYzmSyYTBZ1uq1c1rpZX98rrMnRvRfX3WLbdoDDNgTU\n569bLNb9KD09E70+5/NkVoWWcicnJzN37lyWLl1K8eLF1eknT56kVq1a6vuIiAgWLFgAgMFg4MKF\nCwQEBBRWWAVOq/wzKI1iLuJIhBBCCCGEEOLfK7Sew61btxIfH8+YMbdGKpozZw7R0dEEBgaq04KD\ngzl06BC9e/fGaDQydOhQ/P39Wb9+Pd9//z1nzpxh0qRJVK1alblz5zJz5kz69++Pq6srr7/+OtHR\n0RgMBv7880/efPNNqlWrVlgfySnboDQJGYl3dblCCCGEEEIIUZAKLTns1asXvXr1yjZ96lTHoWk1\nGk22aQA9evRQn3dob8qUKerrNWvWFECkd0b7T+dr+M0TPGcy4KHPfl+FEEIIIYQQ95vu3TuzevU6\ndRDK/Dp06BeuX7/GM890L+DIxL9V6APS3O88FXf1dZIxRZJDIYQQQggh8qB588eLOgSRhSSHd0iD\nhnqeD3Mi7QxGc/aBFoQQQgghhPivSEtLY86cGaSnp5ORkc7YsROoXbsOn3++kr17f0ar1dKixRP0\n7z9IrRMVdYPJk8cxZ85CSpYsCcD169eYOnUiFSsGEhl5mVq1avP66xOZOTMMvd6FpKQEWrRoRUTE\neUaOHMPatavYs+cnNBotw4ePpFGjJnzzzdfs2rUdjUbLE0+0oU+fvjmFLQqIJIcFwEVjXY0ZkhwK\nIYQQQogCsu3KT5xKPIvF/M/AhxoNKApoNOojC3Jim68o1lErbfXq+j1M16odcqyXkBBH+/adaNGi\nFUePHmHt2lXMnDmPr776nE2btqPT6di06Ru1vNFoZMaMaUyYMEVNDG3OnfsfM2fOpXTpMgwZMoC/\n//4fAD4+PkyYMIWtW38AIDLyMnv2/MTSpSu5du0qn3++krJly7Fnz098+OGnALz00mDatg2mbNmy\n+VuJIl8kOSwAekkOhRBCCCHEfcDX14+NGzewfv1XZGZmqvcTtmnzJGPGvEy7dqE89VSoWv7dd2fR\nsmUratSola2tihUDKVPGmszVrv0Ily9fUl/b+9//zlK7dh20Wi0BARWZOHEqP/30I1euRDJq1DAA\n0tJSuXHjmiSHhUySwwKg0+gAOBJ1jEdK1CziaIQQQgghxP2gfcCTdK3agfj4OAD0ehdMpkz0ehdc\nXV1zrevmZn3geUZGBkajMc/1Nm/eRMmSpZg4cSpnz/7F8uUfAfD665O4dOkiu3fvZNSoYSxbtgqA\nUqXKsGPHVp59thcuLi4ObdmeuWd9fas3U693LKfTaR2e1Wcr89hjLRg/fgri7im05xw+SMq6lAJu\nJYlCCCGEEEL8FyUlJVG+fHkADh7ch8lkIiUlhc8++4RKlSozcOAQihXzJS0tFYAhQ16iZcvWrFix\nLFtbV69eISYmBovFwunTf1K58kNOl1mz5sOcPHkck8lEXFwskya9Ts2aDxMefoT09HQUReG9994l\nIyO98D64AKTnsEAU03kBYLTIZaVCCCGEEOK/q02bJ/ngg4Xs3buHLl26sWfPbvbu3U1CQjxDhvTH\nw8OTOnXq4ePjq9bp338Qw4a9QOvWQdSq9bA6PTCwEsuWLeHChQjq1q1HlSpVnS6zXLnyhIR0YOTI\noSiKwrBhIyhbtiw9e/ZhxIghaLVaWrVqg5ubu9P6ouBIclgAbPccGs2ZRRyJEEIIIYQQ/1716jVY\nseJz9f2TT7YDoGPHp7OV3bDhB/X1ihVrs83X612YPPlNh2lTpoSprzt06Ky+7tOnb7bRSLt160G3\nbtmfey4Kj1xWWgBso5VeSorEoliKOBohhBBCCCGEyD9JDguA9p/VmGhMYuelPUUbjBBCCCGEEEWs\nXLnyfPrpmqIOQ+STJIcFQKPR0L7ykwDEpccXcTRCCCGEEEIIkX+SHBaQ5uWaAGCymIs4EiGEEEII\nIYTIP0kOC4hea73v0KSYijgSIYQQQgghhMg/SQ4LiG3E0qi06CKORAghhBBCCCHyT5LDAuKqcwEg\nMvkql5OuFHE0QgghhBBCCJE/8pzDAuKqc6W8V1mupd4g0ZhU1OEIIYQQQogHQPrRcFJ378QcFYWu\nTBm8gtrh3rDRXVn2yJFDGTt2PD///BPFixfn2Wd7qfNMJhPvvDODq1evYDabGTFiDPXrN3Dazptv\nTsbV1VV9BuIXX6zhxx+3odfree21CTz88CMO5bt27Ujp0mXQ6XQYDAY6dXqarl27s3jxQs6ePUNc\nXCzp6emUL18BHx9fZs2aR1xcLO+99y5Xr15Bq9UQEBDI2LETKFasWLZ4LBYLGzdu4OefdwGgKAoN\nGjRi4MAh6PXZ06cPP3yf48ePYTab6dfvBVq3DuKNNyaQkGAdqDI5OYnatesybtwkFiyYy/nzf2My\nmejS5Rk6deoKwO7du5g9ezpLl35GlSrVHNo3m83MmzeLyMjLZGZm0qlTF1q1akt09E3efXc2ZrOZ\n4sX9GDXqVTQaTR63nnOSHBagx8o14Ztzm+VZh0IIIYQQotClHw0nae1q9b35+nX1vVvzx4oqLAB2\n7NiKu7sHH330KRER55k9ezqffLI6W7k//jjEtWtXqFy5CgAREef56acfWb58NefPn+PAgb3ZkkOA\nd99dhKenJwaDgZ49u9C58zOMGvUqAFu3/kBExHlGjhyjlp8xYxrt23fmqadCAfjii9UsWDCHN998\n26FdRVGYPn0KtWo9wsKFS3BxsV4d+N133zJ//jtMmPCGQ/nw8MNERJxn6dLPSExMYODA52ndOoi3\n356jlpk1azqdO3fh5MkT6PV6PvroU9LS0ujZswsdOjzN8eNHOXToIFWrVne6Lg8d+gWDwcCSJZ+Q\nkZFOjx5daNmyNWvXrqJ9+048+mhzvvhiDT//vIugoHa33Ta5keSwAGk01qt0FUUp4kiEEEIIIcT9\nLnX3TqfT03bvwvdfJofR0Td5881JaLVazGYzYWEzKVWqNHPnzuTatauYTCZefHE4jRs3zbWdkJAO\nBAeHAODn50diYmK2MkajkVWrVjBgwGD27v0ZgF9+2U9QUDB6vZ6aNWtRs2atXJeTlJSIr29xdDpd\njmUuXbpISkqymhgC9Or1PBkZGdnKbtu2mYceqkqbNkG89tooMjIyaN78cZKSksjMzCQmJpqSJUup\n5evXb6gmr97exUhPT8dsNqvxXL58kZSUFGrXrvNPeWvvaXx8HD4+Pmi1WmrWrEXDho0ZOXKo0/h9\nfYuTkpKCxWIhLc2Ap6cnWq2WkyePM2TIywA0adKU77/fJMnhvUT7T3IYbYglISOR4m6+RRyREEII\nIYS4X5mjopxON0Xd+Ndt/vrrARo1akLfvi/w999niYmJ4dixcEqUKMmkSdNISEhg9OjhrFr1Va7t\n6PV69RLMr7/+knbtQrOVWbPmM7p2fRZPTy912o0b19FqtYwdOwqz2cTIka9SvXqNbHVff/0VNBoN\nly5dYMyYcbnGcunSRapVq+kwTafT4enpma3sjh3bmDt3IZMmvc6ECW9QvnwFXnppME8//Qx6vZ7z\n5885JIc6nQ4PDw8ANm/+jscee9whUf3666/o3r2XwzLeeGMCJ08eY+rUGQAOn9+ZOnXqUqZMGXr0\neJrU1FRee20iAOnp6bi4uGAyZeLj40tCQlyu7eSFDEhTgFz+eZzFpvNbmfrLbBIzkos4IiGEEEII\ncb/SlSnjdLq+TNl/3Wb9+o3YuXMHH3/8AZmZmdSpU5c//zzB/v17GDlyKG+8MZ6MjAwyMzPz1N43\n33zN2bN/MXDgEIfpkZGXOXv2jNq7aKMoChaLhfnzFzFo0DDmzHG87NPm3XcXsWTJJ6xbt4l169Zy\n6dLFHGPQaMCSh2eRm0wmdDodSUmJeHt7U6FCABqNhlKlSlOtWnV8fHxJS0t1Wnf//j1s3vwdr746\nQZ2WmZnJyZPHaNSoiUPZt9+ew9KlK1mwYE6O7dk7fvwoN29GsW7dJtasWcenn36c5/WfX9JzWIDq\nl6pDbHo8p2P/4nLyVRIyEvB1y36TqxBCCCGEEHfKK6idwz2HNp5Bwf+6zUqVKrN06WccOfI7n366\nlJs3o9DrXejff5DT3r/cbN68iYMH9zN79rvZBnL59dcDREXdYOjQF0hLSyUhIZ61a1fh71+CwMBK\naDQa6tdvwI0b13JdhpeXNw0bNubPP09QqVLlHD/T8uUfZ5v+119nqFXrYfV9QkI8Pj4+REVFUaFC\nAGAdnOb06T+pVOkhTp48QZ069bK189tvv7J69Qrmz1+Mt7e3Ov3YsSMO90teunQRRVGoXPkhypYt\nR/nyFbh48YJ6yWlOTp48TuPGj6LX6ylVqjTFivkQGxuNu7s7GRkZ6HRa4uJi8fPzz7WdvJCewwLk\n5eJJ5yoh1C5hvTbaaDYWcURCCCGEEOJ+5d6wET7P90dfrjxotejLlcfn+f53NFrpgQN7uXgxghYt\nWjFw4BDOnj1D7dp1OHBgL2C9V27p0iW3befq1Sts2vQts2bNw83NLdv8nj2fY9Wqr1i2bCVjx07g\nscda8vzzA2jW7HF+//0QYE2mSpd23jtqoygKZ86cJjCwUo5lAgMrU6pUab755mt12ldffc769V84\nlPPy8iY2NoZSpUpx9ar10XTr13+JTqdDp9Nx4sQxatRwvDw1JSWFDz98n7lz38PHx/GWsjNnTlOt\n2q1BZi5evKCuu/T0dC5fvkS5chVy/XwAAQEVOXPmFACpqSnExETj51eCBg0acejQQcA6aE2DBnc+\nSq30HBYCN60rABmSHAohhBBCiELk3rBRgT66oly5CnzwwXt4eHj8c+/fBAICKhIe/gfDhw/CbDYz\naJDzgVPsbd78HYmJibz++ivqtIULl/DVV2tp2LCR0x44sN5f99tvvzBs2EAAxo6d4LTc66+/glar\nJSMjg8cea0HduvVzjWf69FksWDCXH37YhIeHB9Wq1WD8eMeRRz08PHBxcUVRFKpXr8kbb4yndesg\nOnTozNSpE3jxxZeyPSrip59+JCEhgalTJ6rT3njjLcqWLUtsbAwVKtx6fEerVm3U9Wg0Gunb9wX8\n/PzYvHkT27dv5dy5/zFr1ltUqlSZqVPf4v3359OjR29atWrL778f4qWXBmOxWBgy5CXc3Nx4/vkB\nvPvubHbs2ErJkqVo3Too13WQF5IcFgJXnTU5vJ4ahY+r42Wlfu7FKebq7ayaEEIIIYQQRapq1Wp8\n8MEy9b1tsJWJE6dmK2srl/W5fADDho1g2LAR2ab36/dCtmmNGjVxuC9v8OBhDB48LMcYN23agsmU\n86PjOnTonG2al5c3U6e+lWMdm6FDXyYsbAqTJk1TY7106SKurq5UrZr9c3bp0o0uXbo5bevVV8c7\nvNdoNNmmAXTq1FV93qG90aNfU1+PHz9FfW0wGMjIyMDfvwRhYbMwmW7df2gymXL/gLchyWEh8NC7\nA9aBabLy1HvwTstp6LQ5D7crhBBCCCGEuPtq1XqYMWPG8cknH5KQkIBWq6VSpYfo1q1HUYd2V0hy\nWAjqlXqEDoZg0s2Oz045GXOaaEMsGWYjnlqPIopOCCGEEEIIkZNatR7m7bfnFnUYRUKSw0LgoXen\nY5Wnsk1PzEgi2hBLpuXOunuFEEIIIcT9JzMzE5PJiKurdCKIO5efR47YSHJ4F+n/eQ6iyVI4zyUR\nQgghhBD/XUajkcuXLxEYWAlFsWCxmDGbTSiK9f46RbGof7d7bp/ZbO2MsFjM2eqZzSZMpkx1nq3t\nrHUBh/vZ7h3aXO85vN+ZzSZ1+9u26y0KAOnpBo4dO4LRmL8BMiU5vItsyWFuo5iaLCZupsVQzqtM\nttGQhBBCCCHE/e3GjSiio6M5depP6tatR2BgZbZs+R6AkiVLERMTTcmSpShXrlyu7QQGVgbg8uWL\nXL9+3aFeYGBlqlevwR9/HOLkyRNq2zbNmj2mvq5evUYBf8I75+vrSWxsSlGHUWQiIy9z+fJFAHXb\n2sTHxwHg7V0s34khSHJ4V9mSw60Xd/Finb5Oy3x+ZgN/RIXTq0ZXWgU8fjfDE0IIIYQQ9wCz2UJq\naiqZmSYUBVJTUwHrD/7U1FS8vYuRmZn7bUqKtQOJzEwT6enpDvUUBfR6FzIzTQ5tZ60L1nL3GldX\n13syrrtFUVC3v23b2iQnJwPg6pr92ZJ5ob3z8ERePVauKQDmXC4DOBHzJwA3DTF3JSYhhBBCCCGE\nAEkO76pyXqUBMOZyWanmn02i2P/LRgghhBBCCCEKmSSHd5FOo0Or0WK05JIc/nOfoUV5cG+yFUII\nIYQQQtx9khzeRRqNBhetnsjkazn2DGr/SQ4vJF2WBFEIIYQQQghx10hyeJdp0JJpyeTIzeNO5+s1\n1kFrIpOvsifywN0MTQghhBBCCPEAk+TwLmtcpj4AiRlJTud7u3qpr5OMD+4QvUIIIYQQQoi7S5LD\nu6xuyYeBnO8ptL/cVEEGpRFCCCGEEELcHZIc3mUarPcU5nTPoX1CKMmhEEIIIYQQ4m7RF3UADxqt\nxpqPx6bHkZZpwNPFw2G+fTqYmJHEhcTLTtvxcvGktGfJwgpTCCGEEEII8YCR5PAuc9G6AHDg2m9c\nTIpk0qNjHAvY9SgejjrG4ahjObY15dGxlPcuWyhxCiGEEEIIIR4skhzeZVV8K9G1agd2Xd5LfHpC\ntvkK4O3iRUiltjkOSBOReInziRdINCZRHkkOhRBCCCGEEHeuUJPDuXPncuTIEUwmE8OGDWPz5s3E\nx8cDkJCQQIMGDZg+fTpvvfUWZ8+exWQy0bNnT3r06AHAtm3bmDx5MuvWraNGjRrZ2l++fDnbt29H\no9EwcuRIWrduXZgfp0DotDraVWpD+M0T3EiNyjZfwYJGoyEosFWObey4uJvziRdyvG9RCCGEEEII\nIfKr0JLDQ4cO8ffff7Nu3Tri4+N55pln2LNnjzp/0qRJ9OjRg/DwcPR6PV9++SWpqakEBwfz7LPP\ncvjwYfbt20fNmjWdth8ZGcnWrVv56quvSElJ4bnnnqNly5bodLrC+kgFykXrQqbFhKIoaP558D0A\nyq1Ba3JiK5/TiKdCCCGEEEIIkV+Flhw2bdqUevXqAeDj44PBYMBsNqPT6YiIiCA5OVmd36RJEwDi\n4uLw9fVFq9VSu3ZtHn30Ufr16+e0/d9++40nnngCV1dX/P39qVChAufOncsxmbzXuGj1KCgkZCTi\n516cm2nRWBSFm4YYvF28cq1rSx5NivluhCqEEEIIIYR4ABRacqjT6fD09ARgw4YNtGrVSu3VW716\nNX379nUo/8orrxAeHs68efMA8Pb2zrX9mJgY/P391ff+/v5ER0f/Z5JDD707ALN/f4/RjYYx6/eF\n6ryUzNQ8tfH79SM0KFWnUOITQgghhBBCPFgKfUCaXbt2sWHDBlasWAGA0WjkyJEjhIWFOZRbtGgR\nV69eZfDgwWzYsOG2yWFWebn/zsfHHb3+1mWnMTEeeHm55VD21iMmPDxccXNzUcv6+Hjg7+9FTIy1\njL+/F6VKFctXvM836sLRHSdJNaWR4ZI9Gcytvea6emw6vxVfL+/bLje/cd3v/P2tvbI5rRfbdndW\nzn7a7ebnZ5l5LfNf4+/vhZeXGz4+1uPMzc0FDw9Xdb5tXXt4uKrHlJeXm0MZLy839fiyHXP2x6x9\nWfs69vPsy9tiSUoCNzcXtVzWY9s+Dh8fj/tmu9ivw6zr3Z79Oc+2zmz1wXrutD/v2a8z+/Wftb5t\nelZZz7dAtm1gi/3fnG9F/uR1/Trb7jZZj2P7bWw//XZs+6KzZdjvz1n3MxvbvuPsc/1X9ql7ObYH\nTX62hf3vRGfnRfvXNvbnZlt52z6c9dyY03GVNQbA4bxvq2fb722x2MdpXze/n/tuulfjuhuy7l/2\n51z73zc2uZ0nsyrU5HD//v18/PHHLF++nGLFrBvwjz/+UC8nBTh//jwAVatWpUKFClSsWJGIiAiH\nMs6ULl2aCxcuqO+joqIoXbp0rnWSktKzvDeQmpqRQ1mD+tpgMJKRkamWTUoyEBeXqpaJi0slOjo5\n12Vn5YEPj5ZtxO83wrkSfTPb/NzaM6Vbn5WYlp6Ra7lSpYrlO677XVycNRHPab3Yb9Os5eyn3W5+\n1mX6+3vlui1uF9d/UVxcKqmpGepxlpGRicFgVOfb1rXBYFSPqdTUDIcyqakZ6vFlO+bsj1n7svZ1\n7OfZl7evn5GRqZbLemzbx5GUZLhvtov9Osy63u3Zn/Ps15ltP7XVs60X+3Vmv/6z1rdNzyrr+RbI\ntg1ssf+b863Iu/x8bzjb7jZZj2P7bWw//XZs+6KzZdjvzzl9n9v2GXB+br7X9yn5Hr935Hdb2P9O\ndEEwiDQAACAASURBVHZetH9tY39utpW37aNZz405HVdZYwAczvu2erb93haLfZz2deHe/G3yoB8b\nWfcv+3Ou/e8bm9zOk1lpCzhWVXJyMnPnzmXp0qUUL15cnX7y5Elq1aqlvo+IiGDBggUAGAwGLly4\nQEBAwG3bb968OXv27MFoNBIVFcXNmzepVq1awX+QQmS7tzDJmL+dW6uxbjYZrVQIIYQQQghRUAqt\n53Dr1q3Ex8czZsyth7zPmTOH6OhoAgMD1WnBwcEcOnSI3r17YzQaGTp0KP7+/qxfv57vv/+eM2fO\nMGnSJKpWrcrcuXOZOXMm/fv3p2LFivTs2ZO+ffui0WgICwtDqy20XLdQFHOxXjr7d0JEvurZksMY\nQ1yBxySEEEIIIYR4MBVactirVy969eqVbfrUqVMd3ms0mmzTAHr06KE+79DelClT1Nf9+vXLcTTT\n/wIfN+ultucSLtympCO91nrf5KXkSFKMqXi75j66qRBCCCGEEELczn+rq+0+06BUHTpXCcl3PQ+9\nB76uPgAkZCQWdFhCCCGEEEKIB5Akh0XIXe9OaOUn/1Xdx8o3BSDdfPsbS4UQQgghhBDidiQ5/I9y\n11mHojWYch+pSgghhBBCCCHyotCfcyhuz1PvQVo+kzx3vTsAl5Ov4uXi6bRMnMaThMQ0h2muWlcq\neJdDo9H8u2CFEEIIIYQQ9yVJDu8BdUvW5rcbR/JVx5YQbr2wk60Xduar7tC6/alfqk6+6gghhBBC\nCCHub5Ic3gO6VetEQLHyPORTiXePfJCnOnVK1KJL1fYYTOk5lvH0dCUt7dYDMKNSb3I85hSJGUl3\nHLMQQgghhBDi/iLJ4T3A29WLoIpPYFEsea7jqnPlqUptcy1TqlQxoqOT1ffHo//keMwpzPlYjhBC\nCCGEEOLBIAPS3EM0FO59gDqN9fmIJoupUJcjhBBCCCGE+O+R5PAeUtiDxOi11o7iqynXC3U5Qggh\nhBBCiP8eSQ4fIK46VwD+iDrK5aQrRRyNEEIIIYQQ4l4i9xzeY4bW7U8xV+9CabuyT0X83IoTn5FA\nolEGpRFCCCGEEELcIj2H95j6pepQxbdyobSt1Wj/z96dx0dVn/sD/8yemclMkgmTELKw7xIWQUVk\nu42txa2AGATUWhWp13ptC3r9WVvEYgXrUvRypbjfKlKxrdYLVIWiXAXLKhC2SFiy78lMZiaz//6Y\nnMmZjSQwk5kkn/frxYuZc77nzDPne75n5smZ8xx8L28GAMDtccfkNYiIiIiIqGdictjHCEVp3F4m\nh0RERERE1I7JYR8jk/q63OK0xTkSIiIiIiJKJEwO+xiV1FeUZkfpl3GOhIiIiIiIEgmTwz7min5j\nAABauSbOkRARERERUSJhctjHJMlVUMqU8MAT71CIiIiIiCiBMDnsg6SQwuNlckhERERERO2YHPZB\nUokE5S2VcLid8Q6FiIiIiIgSRKeSQ6/Xi/r6etTX18Pr9cY6JooxmdR3O4sPTv8tzpEQEREREVGi\nkF9s5pEjR7Bhwwbs2bMHKpUKXq8XTqcTU6dOxdKlS5Gfn99dcVIU3TFyHv549B00OUzxDoWIiIiI\niBJExOTwD3/4A7755hv85Cc/wdq1a6HVagEAVqsVX3/9NZ599llcc801ePjhh7stWIqOK9JHAwBc\nHnecIyEiIiIiokQRMTlMTU3Fe++9FzJdo9GgoKAABQUFePvtt2MaHMWGTCqDVCKFy8NrDomIiIiI\nyCdicnj33XfDarXio48+wunTpyGTyTB27FjceOONUCqV/jbUM8klMpQ0n4fD7YRSpoh3OERERERE\nFGcRC9JUVFTgpptuwsGDBzFs2DD069cP27Ztw80334yqqqrujJFiQCH1JYRbij+OcyRERERERJQI\nIp45fPHFF/Hwww/jRz/6UcD0LVu24JlnnsG6detiHhzFzqLRt2Hj0XfQ2NoU71CIiIiIiCgBXPTM\nYXBiCAC33XYbzp07F8uYqBuM7zcWEkjQ6rbHOxQiIiIiIkoAEZNDmUwWcaGUlJSYBEPdRyKRQCVT\nwc7kkIiIiIiIcJGfldrtdpSWload53A4YhYQdR+VTInylko43A4oZcp4h0NERERERHEUMTmsra2N\nWI1UIpHELCDqPmp5EpodJrx/6q+4a0xhvMMhIiIiIqI4ipgc7ty5szvjoDgoHDkXfzi0Ac12U7xD\nISIiIiKiOIt4zaHT6cS2bdv8z3ft2oUHH3wQa9asgdVq7ZbgKLaGpw4BALi97jhHQkRERERE8RYx\nOVy9ejX++c9/AgCqqqqwfPlyzJ49GwqFAs8++2y3BUixI5FIIJPI4PK44h0KERERERHFWcSflR49\nehQffvghAGD79u2YPXs2FixYAABYvHhx90RHMSeTynDWdIFFaYiIiIiI+riIZw61Wq3/8d69e3Ht\ntdf6n8vlEXNK6mEUUl9fbin+OM6REBERERFRPF30msPW1lY0NDTgX//6F6677jr/dIvF0m0BUmwt\nGnUbALAoDRERERFRHxfxFGBhYSFuuOEGuFwuzJs3D0ajEXa7Hf/+7/+OmTNndmeMFEPj0kcDAJy8\n7pCIiIiIqE+LmBz+6Ec/wtSpU9Hc3IwRI0YAAFQqFa6//noUFvKeeL2FTCqDVCJlckhERERE1MdF\n/FkpAGRmZvoTQwETw95HLpGhxdmCamvtJa/D6XGhpPkcK58SEREREfVQEc8cjho1ChKJJGCaTqfD\nLbfcghUrVkClUsU8OOoeSfIk1Fjr8Ntvnscz034FnTK5y+v4S/En+LL8a3wvdwbmDb8pBlESERER\nEVEsRTxzWFRUhGPHjgX8+/vf/46kpCS88MIL3RkjxdjdYxZisD4PHq/nkgvTlLdUAABK2/4nIiIi\nIqKeJeKZQ5lMFjItMzMTy5cvx6JFizq18rVr1+LAgQNwuVx44IEH8Mknn6CxsREA0NTUhAkTJuCp\np57CqlWrcOrUKbhcLtx+++1YsGABzGYzfvnLX8JsNkOj0eD5559HampqwPrXrVuH3bt3QyaTYfny\n5Zg8eXJX3ju1GWUYjtONZ3DWdAGtbvslrUPedksMN39WSkRERETUI13SDQs7c5/DvXv3ori4GJs3\nb0ZjYyPmzp2LXbt2+ec//vjjWLBgAQ4ePAi5XI5NmzbBYrGgoKAA8+fPx9tvv42rrroK9913HzZv\n3oyNGzdixYoV/uWPHz+Or7/+Gps3b4bZbMYDDzyA999//1LeDgFIkvl+Jmy/xORQJvH9McHldUct\nJiIiIiIi6j5dTg73798PtVrdYbspU6YgPz8fAKDX62Gz2eB2uyGTyVBSUgKz2eyfL5zxa2hoQEpK\nCqRSKfbs2YNnnnkGADB79mwsW7YsYP3nzp3D2LFjIZVKkZKSAp1Oh7KyMuTk5HT1LREAldyXHNbZ\nGi5peZnUlxw2tTajpPk8BulzIZVctN4RERERERElkIjJ4aJFi0IK0jQ3N8Pr9WL9+vUdrlgmk0Gj\n0QAAtmzZghkzZvh/qvrOO+9gyZIlAe0ffvhhHDx4EM899xwAoK6uDgaDAQCQnp6OmpqagPYjRozA\nf//3f8Nms8FiseDEiROor69ncniJtApfX310Zitm5lzb5eWVUgUAoNlhwvMH/gt3jS7E1VlXRjVG\nIiIiIiKKnYjJ4SOPPBIyTavVYuTIkZ36Wang888/x5YtW/DGG28AABwOBw4cOICVK1cGtFu3bh3K\ny8tx7733YsuWLQHzvF5vyHqHDRuGwsJC3HPPPcjJycGoUaPCthPT65Mgl7dfS1lXp4ZWG77qql7f\nfnZUrVZCpVL42+r1ahgMWtTV+doYDFoYjbqLvna8dDauf0u7Gm8WvYckRdIlvRetJgkAMNo4HCdq\ni+GUtybkNjEYtAAibxeh38O1E0/raH5XXrOzbXoag0ELrVYFvd43zlQqBdRqpX++sK3VaqV/TGm1\nqoA2Wq3KP76EMSces+K24mXE88TthVhMJkClUvjbBY9tcRx6vbrX9It4GwZvdzHxMU/YZsLygO/Y\nKT7uibeZePsHLy9MDxZ8vAUQ0gdC7Il8vO0tOrt9w/W7IHgci/tYPL0jwr4Y7jXE+3PwfiYQ9p1w\n76un7FOJHFtf05W+EH9PDHdcFD8WiI/NQnthHw4+NkYaV8ExAAg47gvLCfu9EIs4TvGyXX3f3SlR\n4+oOwfuX+Jgr/n4juNhxMljELK+oqAj33HPPRRd+8803L9pm9+7dePXVV/Haa69Bp/N14L59+/w/\nJwWAM2fOAACGDh2K7Oxs5ObmoqSkBBkZGaitrYVOp0N1dTUyMjJC1r9kyRL/GcjCwkJkZ2dfNF6T\nqTXouQ0WS/hr7Ewmm/+xzeaA3e70tzWZbGhosPjbNDRYUFtrvuhrx4PRqOtSXFnaTJjs5kt6L/ZW\nXyGaKf0m4URtMZrMLQm5TRoaLAAQMTZxnwa3E0/raH7waxoM2otuj47i6okaGiywWOz+cWa3O2Gz\nOfzzhW1tszn8Y8pisQe0sVjs/vEljDnxmBW3FS8jniduL17ebnf62wWPbXEcJpOt1/SLeBsGb3cx\n8TFPvM2E/VRYTtgu4m0m3v7BywvTgwUfbwGE9IEQe6Ieb3uLrnxuhOt3QfA4FvexeHpHhH0x3GuI\n9+dIn+fCPgOEPzYn+j7V1c9xip2u9oX4e2K446L4sUB8bBbaC/to8LEx0rgKjgFAwHFfWE7Y74VY\nxHGKlwUS87tJXx8bwfuX+Jgr/n4juNhxMljEi8IsFgsWL16Mzz//HFar1T/darXi888/x+LFiwOm\nBzObzVi7di02bNgQUGX06NGjGDVqlP95SUmJ/9YYNpsNZ8+eRU5ODqZNm4bt27cDAD799FNMnz49\nYP0NDQ24//774fV6UVxcDI/HA6PR2OEbpsjkEhncl1hQxgvfWVuFzPfXCofbGbW4iIiIiIgo9iKe\nOXzooYcwY8YMvPrqq3j00UehUPi+9DudTkydOhWPPfZYwBnAYFu3bkVjY2PAz1PXrFmD2tpa5OXl\n+acVFBRg7969WLhwIRwOB5YuXQqDwYA777wTK1aswKJFi6DX6/3XIq5evRp33XUXcnNzMXr0aMyf\nPx9SqRS//e1vL3tj9HUyqRxOjwsnG4ov2i5Lm4kUlT5gmvCLXuHaw1pbfdj1SCVSDNLnQdmWRBIR\nERERUWK46MWD+fn5WL9+PTweD5qamgAAqampkEo7rkJZWFiIwsLCkOlPPvlkwHOJRBIyDfBd3xiu\n8M0TTzzhf/yLX/wCv/jFLzqMhTonSaaC2+vGy4c3XrRdhroffjP10bDzNArf75+P1BXhSF1R2Dbf\ny52BecNvurxgiYiIiIgoqjpVWUYqlforh1LvNW/4TThSGz6hE3xZvgcmR7jfePtOHaapUnHX6EI0\ntDaGtLC5W7HjwpdodpiiES4REREREUVRl+9zSL1XdnIWspOzLtrmSN1xVFqqQqYL1xwCiHgLC7Oj\nBTsufAm359KuayQiIiIiotjhXcqpS2QSGdxeT8T5wffGFJNLfbcRcV1i0RsiIiIiIoqdDpPD5uZm\nrFmzBsuXLwcA7Ny5Ew0NDTEPjBKTTCqFx+tBqbkcF0xl8Hq9aLabcM5U2vGyEt+J6sbWJhytO46T\nDcVwsqopEREREVFC6DA5/NWvfoWsrCyUlZUB8N3E/rHHHot5YJSYvG1lSZ/d9wes2b8O50ylWLv/\nZdTZ6jtcVjhzWNZSgVePvIWXD2/E1nOfxzReIiIiIiLqnA6Tw4aGBtx1113+W1nccMMNaG1t7WAp\n6q2ytJkBz1ucLWiyN/ufSxD5Z6VSiTRkfmNrU3QDJCIiIiKiS9Kpaw6dTqf/WrK6ujpYrdaYBkWJ\na3DKwIDnnotcfxjOsNTBAc9b3fxDAxERERFRIuiwWumSJUtw2223oba2FsuWLcPRo0cD7jVIfYta\nrg54HlqcJvKZQwBIkicFPG912aMRFhERERERXaYOk8Mf/vCHmDhxIg4dOgSlUolVq1YhIyOjO2Kj\nBKQJSu6a7V27Z2GSLHD5c6YL8Hq9F61ySkREREREsdfhz0q/++47vPvuu/jhD3+I733ve3jxxRdx\n+vTp7oiNEpBOmRzw/OMz2wKuI1S0FZ2JJFmpCXju9LhQ1lIRvQCJiIiIiOiSdJgcPvXUU5g5c6b/\n+fz58/H000/HNChKXJmawLPGSpkSSpmvWNG9VyyBRqEJt5hfQd7MkGlmR0v0AiQiIiIiokvSYXLo\ndrsxefJk//PJkyf7b2dAfY9EIoFKpvQ/d3ic8Hq9yNNlY1JGfofLp6pSQqa5ve6oxkhERERERF3X\n4TWHOp0O7733Hq6++mp4PB7s3r0bWq22O2KjHsDpdkIulUHSucK3YYUWtSEiIiIiou7WYXL4u9/9\nDs8//zw2bdoEAJg4cSJ+97vfxTwwSlzegMdeOD2uyyooU2oqg0qq7LihiEKmwJCUgZBKLj0pJSIi\nIiKidh0mhwaDAatXr+6OWKiHGJk2FEfrTgRMu5xao9vP7wTO7+zycneNLsTVWVdexisTEREREZEg\nYnL4yCOP4KWXXsLMmTPDnhXatWtXLOOiBLZw5DyMTT+OipYqfFm+BwC6dOZw/vCb8WHx3wEAtw2/\nBXa3o0uv39DaiK8qvkGtra5LyxERERERUWQRk8Nf/epXAID33nuv24KhniFVlYLp2VPxdcU+0dTO\nJ4c5yQP8j2fnXtfl16+0VOOrim9Y5ZSIiIiIKIoiJof9+vUDADz33HN46aWXui0g6jn6a9tvayG5\nrB+Wdo1O4bvXYovT0m2vSURERETU23V4zWFOTg62bNmCiRMnQqlsLxqSm5sb08Ao8fUX3fPQi87f\n3uRy00iNQg0JJCg1l1/mmoiIiIiISNBhcrh169aQaRKJBDt27IhJQNRzaBRqKKUKODxOlDSf6/Ry\nyUrfmT+FtMPdLyypRAqlTIH61kY43U4oZIpLWg8REREREbXr8Nv5zp1dryJJfce/5U73VRvtgixt\nJu69YgkG6i797HOaKhVV1hpYXFakylIueT1EREREROQT8SZxLS0tWLt2LZYtW4bXX38dLperO+Oi\nHmJ42tBLWm5SRj7S1WmX/LrDUgcDAGyu1kteBxERERERtYuYHK5cuRIAUFhYiO+++w6vvPJKd8VE\nPYj8En8aernUcjUAJodERERERNES8Zt9eXk5fv/73wMAZsyYgR//+MfdFRP1IDKJLC6vq5YnAQBO\nN37nTxA18iQM0ud16Z6LRERERETkEzE5lMvbZ8lk8UkAKPFpFb4zeJkaY7e+rq6tqM3fS/4RMP2R\nicswPG1It8ZCRERERNQbREwOg8++8GwMhZOhMeKesYuQK7qxfXeYlDEeDrcTDrcDAFBuqcT+6sOo\nttYwOSQiIiIiugQRk8NDhw5h1qxZ/uf19fWYNWsWvF4vJBIJdu3a1Q3hUU8wOXNCt79mklyFWbnT\n/M9PN57B/urDaLI3d3ssRERERES9QcTkcPv27d0ZB9FlSVXpAQCNTA6JiIiIiC5JxOQwOzu7O+Mg\nuiypKt+9Ds+ZSi/artHVDAkk+K7pLIakDIRUErFgLxERERFRnxKf+xAQRZlSpoQEElRZquH2uCGT\nhhZRcrgdeK/ub74ndcBdowtxddaV3RwpEREREVFi4mkT6jX0bRVMXV532PkOtzPguclhjnlMRERE\nREQ9BZND6jXy9LkAAE+E5NALb8Bzj9cT85iIiIiIiHoKJofUa8jarh90R0j6PN7A5NDlccU8JiIi\nIiKinoLJIfUaQnEZ4d6HoQKTw3JLVYwjIiIiIiLqOZgcUq8h/Ez064p9YecH/6z029pjcAZdh0hE\nRERE1FcxOaRe48rMCQAAhyf8mUNv0M9KAcDqssU0JiIiIiKinoLJIfUamRojgMjXEgZfcwgAdrc9\npjEREREREfUUTA6p15BLfbftdLojFZoJTQ5bmRwSEREREQEA5PEOgChaFG3J4bd1xzDXOQcahSZg\nfkNrY8gyJxuK0Ww3AQC0Ci288EICSeyDJSIiIiJKMEwOqddIkqkAABanFe+f+it+csXigPkvHdoQ\nssxHZ7YFPL9Wmo8Ujy52QRIRERERJSgmh9RraBQa/GTsYrxR9G6nCs3cPuJHcHp81UqLG8/gWP1J\n2MHqpURERETUN8U0OVy7di0OHDgAl8uFBx54AJ988gkaG30/7WtqasKECRPw1FNPYdWqVTh16hRc\nLhduv/12LFiwAGazGb/85S9hNpuh0Wjw/PPPIzU11b9ut9uNX//61zh37hycTicWLVqEH/3oR7F8\nO9QD5BvHAghfmTTYzJxr/Y+lkOBY/Ul4JR0vR0RERETUG8UsOdy7dy+Ki4uxefNmNDY2Yu7cudi1\na5d//uOPP44FCxbg4MGDkMvl2LRpEywWCwoKCjB//ny8/fbbuOqqq3Dfffdh8+bN2LhxI1asWOFf\n/ssvv4TNZsO7776L1tZWFBQU4JZbboFUyho7fdmlXi0olcoAAJ4wRWuIiIiIiPqCmCWHU6ZMQX5+\nPgBAr9fDZrPB7XZDJpOhpKQEZrPZP3/y5MkAgIaGBqSkpEAqlWLPnj145plnAACzZ8/GsmXLAtaf\nlpYGk8kEj8cDq9UKrVbLxJD8xWTMzhYcrTve6eVkEl9yaJW0xiQuIiIiIqJEF7PkUCaTQaPxVYvc\nsmULZsyYAZnM9wX8nXfewZIlSwLaP/zwwzh48CCee+45AEBdXR0MBgMAID09HTU1NQHtJ0yYgAED\nBuB73/seWlpa/Ikk9W0SiQRyqRzlLZV49chbnV5O3VbM5rTiPIa6cmIUHRERERFR4op5QZrPP/8c\nW7ZswRtvvAEAcDgcOHDgAFauXBnQbt26dSgvL8e9996LLVu2BMwLd/3Y/v37UVlZic8++wz19fW4\n6667MHPmTCiVyoix6PVJkMtl/ud1dWpotaoIbdX+x2q1EiqVwt9Wr1fDYNCirs7XxmDQwmhMzAqX\niRpXLP3n9Adxvqk8YNq3VcdxpPpEwDTxtvle2jV48/gmyCUyf/8GtxFP62i+WKTpXW3T0xgMWmi1\nKuj1vnGmUimgVrePT2GMqdVK/zbXalUBbbRalX98CWNOPGbFbcXLiOeJ2wuxmEyASqXwtwse2+I4\n9Hp1r+kX8TYM3u5i4mOesM2E5QHfsVN83BNvM/H2D15emB4s+HgLIKQPhNgT+XjbW3R2+4brd0Hw\nOBb3sXh6R4R9MdxriPfn4P1MEOl4Ll4+0fepRI6tr+lKX4i/J4Y7LoofC8THZqG9sA8HHxsjjavg\nGAAEHPeF5YT9XohFHKd42a6+7+6UqHF1h+D9S3zMFX+/EVzsOBkspsnh7t278eqrr+K1116DTufr\nwH379vl/TgoAZ86cAQAMHToU2dnZyM3NRUlJCTIyMlBbWwudTofq6mpkZGQErPvgwYOYOnUq5HI5\nMjMzkZqaiurqauTm5kaMx2RqDXpug8US/iboJlN7tUubzQG73elvazLZ0NBg8bdpaLCgttbc2c3S\nbYxGXULGFWtZshxkpQee/XO3IiQ5DN42Q1IG4mzTeX//BrcRT+tovlhDgwUGg/aifRFp2Z6socEC\ni8XuH2d2uxM2m8M/Xxg/NpvDv80tFntAG4vF7h9fwpgTj1lxW/Ey4nni9uLl7Xanv13w2BbHYTLZ\nek2/iLdh8HYXEx/zxNtM2E+F5YTtIt5m4u0fvLwwPVjw8RZASB8IsSfq8ba36MrnRrh+FwSPY3Ef\ni6d3RNgXw72GeH+O9Hke6XguXj6R96m++jmeiLraF+LvieGOi+LHAvGxWWgv7KPBx8ZI4yo4BgAB\nx31hOWG/F2IRxyleFkjM7yZ9fWwE71/iY674+43gYsfJYDG7SM9sNmPt2rXYsGFDQJXRo0ePYtSo\nUf7nJSUleOGFFwAANpsNZ8+eRU5ODqZNm4bt27cDAD799FNMnz49YP0DBw7EkSNHAAAtLS2orq6G\n0WiM1duhHi5dbeiwjUKqgFfCojRERERE1DfF7Mzh1q1b0djYiEceecQ/bc2aNaitrUVeXp5/WkFB\nAfbu3YuFCxfC4XBg6dKlMBgMuPPOO7FixQosWrQIer3efy3i6tWrcdddd+H666/HV199hTvuuAMe\njwcrVqxAUlJSrN4O9XBGdXqHbRRS33Bw8l6HRERERNQHxSw5LCwsRGFhYcj0J598MuC5RCIJmQYA\nWq0W69evD5n+xBNP+B+vWrUqCpFSX5CWlBrwXKdIDmkjkfgqnZ5VVGA0xnRLXEREREREiYL3fqA+\nQSpp39XHqIfj4YlLQ9pcN+AaAIAb7m6Li4iIiIgoUTA5pD5npHooBiT3D5ku/PTUK+E1h0RERETU\n9zA5JGoja7vmkAVpiIiIiKgvivl9DokSjTdC8ieX+u6BaZW0oqT1AgDAWds+v1Q0rTTM/LLWUgxQ\nZsYgYiIiIiKi2GNySH3G0JTBONN8Fhpp+JvGqmRKwAs0ykzY1vRP38SmMA2bIjyG73rGiZgYlXiJ\niIiIiLoTk0PqM+4Zewe+Pr4HafKUsPPVcjWutI+GRWpDeno/AED/zPZrE6uqq/zTxI8BwOFx4e8l\n22HztMbyLRARERERxQyTQ+oz0pJSMTgp76JtMjwGwAMM0Q4DAIzJG+ufd7ylyD9N/BgA7G4H/l6y\nHR54YhE6EREREVHMsSANURTI2m6V4fYyOSQiIiKinonJIVEUyCS+YjZljko43c44R0NERERE1HVM\nDomiQCKR+B/vKvsqjpEQEREREV0aJodEUTI1eRIAwOK0xjkSIiIiIqKuY3JIFCXZqiwAYFEaIiIi\nIuqRmBwSRYkUvp+WeliUhoiIiIh6ICaHRFEiaUsOG2yNcY6EiIiIiKjrmBwSRYlSogAAnG46E+dI\niIiIiIi6jskhUZTo5ToAgEaujnMkRERERERdx+SQKIpSZDq4PO54h0FERERE1GVMDomiSCqRi0py\n0gAAIABJREFUwuV1xTsMIiIiIqIuY3JIFEUyyGBxWuF0O+MdChERERFRlzA5JIqBL8q/jncIRERE\nRERdwuSQKIquTB4HAGho5e0siIiIiKhnYXJIFEX9FUYAgMVpjXMkRERERERdw+SQKIqSpEkAgBaH\nJc6REBERERF1DZNDoiiSS2RQShU42VgMB4vSEBEREVEPwuSQKMoUUgUA4EsWpSEiIiKiHoTJIVGU\n3TTk+wD401IiIiIi6lmYHBJF2aCUPACA2+uOcyRERERERJ3H5JAoyuQSOQDA5XHFORIiIiIios5j\nckgUZTKpDABw3lQW50iIiIiIiDqPySFRlKnlvttZnDeXwuF2xDkaIiIiIqLOYXJIFGV6pQ5ahQYA\nYHPZ4xwNEREREVHnMDkkioFx6WMAAE4P73VIRERERD0Dk0OiGFDIfPc65M9KiYiIiKinYHJIFANK\nqS85PFx7FG6vJ87REBERERF1jMkhUQwI1xz+79nPUNJ6Ps7REBERERF1jMkhUQxMz56K0YYRAIBW\nD4vSEBEREVHiY3JIFAMahRrTs6cCANxwxzkaIiIiIqKOMTkkihGZxDe8PF5vnCMhIiIiIuoYk0Oi\nGJFJZQCAGmddnCMhIiIiIuoYk0OiGNHI1QCAM/bzcHv501IiIiIiSmxMDoliJE+XAwkkAACnxxXn\naIiIiIiILk4ey5WvXbsWBw4cgMvlwgMPPIBPPvkEjY2NAICmpiZMmDABTz31FFatWoVTp07B5XLh\n9ttvx4IFC2A2m/HLX/4SZrMZGo0Gzz//PFJTU/3r3rVrF15//XX/86KiImzbtg2ZmZmxfEtEnSaR\nSDAhYxwO1RyBi2cOiYiIiCjBxSw53Lt3L4qLi7F582Y0NjZi7ty52LVrl3/+448/jgULFuDgwYOQ\ny+XYtGkTLBYLCgoKMH/+fLz99tu46qqrcN9992Hz5s3YuHEjVqxY4V9+1qxZmDVrFgDg/PnzWLNm\nDRNDSjgKqW+IuTxMDomIiIgoscUsOZwyZQry8/MBAHq9HjabDW63GzKZDCUlJTCbzf75kydPBgA0\nNDQgJSUFUqkUe/bswTPPPAMAmD17NpYtWxbxtV5++WU89NBDsXorRJdMSA5PmUsgbVRjeOpQSCSS\nOEdFRERERBQqZtccymQyaDQaAMCWLVswY8YMyGS+6o3vvPMOlixZEtD+4Ycfxh133IHf/OY3AIC6\nujoYDAYAQHp6OmpqasK+TnV1Nerq6jBmzJhYvRWiS6aR+8bAp9Vf4Q+H/ogKS1WcIyIiIiIiCi+m\n1xwCwOeff44tW7bgjTfeAAA4HA4cOHAAK1euDGi3bt06lJeX495778WWLVsC5nkvcp+4v/3tb7jl\nlls6FYtenwS5XOZ/XlenhlaritBW7X+sViuhUin8bfV6NQwGLerqfG0MBi2MRl2nYuhuiRpXvBgM\nWgCRt4vQ7+Haiad1NF+wUH8jlE7fmcPvWi5AqZWEfe2O4uqJDAYttFoV9HrfOFOpFFCrlf75wrZW\nq5X+MaXVqgLaaLUq//gSxpx4zIrbipcRzxO3F2IxmQCVSuFvFzy2xXHo9epe0y/ibRi83cXExzxh\nmwnLA75jp/i4J95m4u0fvLwwPVjw8RZASB8IsSfy8ba36Oz2DdfvguBxLO5j8fSOCPtiuNcQ78/B\n+5lA2HfCva+esk8lcmx9TVf6Qvw9MdxxUfxYID42C+2FfTj42BhpXAXHACDguC8sJ+z3QiziOMXL\ndvV9d6dEjas7BO9f4mOu+PuN4GLHyWAxTQ53796NV199Fa+99hp0Ol8H7tu3z/9zUgA4c+YMAGDo\n0KHIzs5Gbm4uSkpKkJGRgdraWuh0OlRXVyMjIyPsa+zatQsvvvhip+IxmVqDnttgsdgjtLX5H9ts\nDtjtTn9bk8mGhgaLv01DgwW1teZOxdCdjEZdQsYVTw0NFgCIuF3EfRrcTjyto/lig7wDYU5qwXct\nF9DY1IJaSehrdxRXT9TQYIHFYvePM7vdCZvN4Z8vbGubzeEfUxaLPaCNxWL3jy9hzInHrLiteBnx\nPHF78fJ2u9PfLnhsi+MwmWy9pl/E2zB4u4uJj3nibSbsp8JywnYRbzPx9g9eXpgeLPh4CyCkD4TY\nE/V421t05XMjXL8LgsexuI/F0zsi7IvhXkO8P0f6PBf2GSD0+NoT9il+jieOrvaF+HtiuOOi+LFA\nfGwW2gv7aPCxMdK4Co4BQMBxX1hO2O+FWMRxipcFEvO7SV8fG8H7l/iYK/5+I7jYcTJYzH5Wajab\nsXbtWmzYsCGgyujRo0cxatQo//OSkhK88MILAACbzYazZ88iJycH06ZNw/bt2wEAn376KaZPnx72\ndUpLS9G/f/9YvQ2iqJBIfEPNc5Gz4ERERERE8RSzM4dbt25FY2MjHnnkEf+0NWvWoLa2Fnl5ef5p\nBQUF2Lt3LxYuXAiHw4GlS5fCYDDgzjvvxIoVK7Bo0SLo9Xo899xzAIDVq1fjrrvuQm5uLhobG/1n\nJIkSmbTtfoenG88gOzkLOmVyh8t4vB6caDgNm6s17HwJgOFpQ6FXcgwQERER0eWLWXJYWFiIwsLC\nkOlPPvlkwHOJRBIyDQC0Wi3Wr18fMv2JJ57wP05LS8O2bduiEC1RbKlkvt99/+P8TjS0NuLHY+/o\ncJlTDd9h/bdvXLTNROM43DfuzqjESERERER9W8wL0hARMD51FIxpWXj35BbU2Ro6tYzZ2QIAmJI5\nCUNTBwbM83q92Hz6b7C6Ln69ARERERFRZzE5JOoGSqkC1/SfjI/PbIfZ0bkLqB1u34XEY9NHYkr/\niQHzhOTQ4/VEPVYiIiIi6ptiVpCGiELpVTqYHOaL3p5F4PD4qk0pZYqQeRKJBFKJFG4mh0REREQU\nJTxzSF12vsoMs9WB2iYbpFIJ5DIppFIJnC4PlArf3xtG5KTCoE8KWdbl9uC7smZIpRKU1rQgPSUJ\ncqkEYwYbIJVIOvX6F6rNqKi3hEwfmZuGinoLzleZMSovDUMG6EPa1JldcHu8GNPF9xwteqUOpeZy\nfFN1AHJJ+z03y2xlAABrVXvZ4XPNFwAASmnofeEAX5Ebk8OM/VWHYhjxpSuzlaFJZ4FUVosmnQWe\nbDladW7//ApZLQCg1ehGhawWLpsUTToLWj3tbZp0Fpy2lcBa5UCZrQw1besSiNuKlxHPE7cXYrHJ\nnfB4fYe/Vp3b30YaJo4KWW3CbuOuEm/DVk/gdhdr9bjhSZIH9B8AnLaVAABq2pYT9lehr1s97oDt\nH7y8MF2sTm2GTdY+9luN7f0m7gOXTRryutGgV+kxIm1o1NZHRETUkzE5pC5xuT146q19HbYblZeK\nRxdNCpn+190l2Lb3Qsj0xxZNxMi8tA7X6/F48bt3D8LuCE0KUpOVaGpp/9L437+YCZVSFtDm7X/W\nwwtg+lUeyGXdf+I8Pcn3Hv/nxJ/DN2gOnaRVaMI2TZInoc5WjzePb4pWeNGXBZSiHsgCkKWBCe39\n9i1O+x6ManvcfLqtXfviJtSjtHl3+3ZRBc4PeCxaRjzP/xyiWABgiKZtvtvfphT1IXF8i9P49vjp\nLr7xBCZsw6yg7S6WBQAalKI+YJuVNu9uX0fz6cD9tW2d4u1vClq+fd3tTKgCUNU+YZQwvT6gD9B8\nOvzrRsHKax6DUZMe3ZUSERH1QEwOqUvsztCkTGzKqAwcOVMPs9UZdv7RM+GLsbTYwrcPZml1wu5w\nY2CmDjMnDPBP//CLMwGJodA2ODkUfszZ6nAjWd39yeGcwdcjRzcg5H6HlZUVAICsrAEB03UKLXJ1\n2WHX9eD4n+CCuTw2gUZBZWUFiotPIS3NgMbGBlRWViBZ234Lj7yBgwAAF86fQ97AQejXz4ji4lMw\nm0z+Njq9HsOHj0RW1gBUVlagrq4WjY3t+5C4rXgZ8TzhOQB/LK02KxqbmgAAydpkf5u0NENIHHkD\nB2HcuPHR2CRxJ96GZpMpYLuLmU0mtFhakJU1wL/NAGD48JEAgLq6WvTrZ/Tvr0Jfm02mgO2v0+sD\nlhemi/Xrlw6Ntv12LBfOnwPg6zdxH/TrZwx53ct1uOYoTjYWw+qyAmBySERExOSQusTluvg1bsNz\nUvBdeTMcrvBJZKRr7ZwdrFcgJJED++swa2J70vTltxWwVAUWeglOZMWvbXe4kawOvZYv1nTKZEwb\ncHXI9OPNRQCAMdljO72ugfpcDNTnRi22aDveXISG5grk6PpD2uxE9Tkn1OntyXpedn8AQG1VKfKy\n+2OIZhgamivgqm7/CWK6V4crNCMxJnssjjcXocQlg7S5/Q8J4rbiZcTzhOcA/LGYTE40l/nWo06X\n+dvk6ELjyMvuj+nZ10Rlm8SbeBu6qi0B213MVW2Btd6JdI3Ov80A4AqNLzkscckwRDPMv78Kfe2q\ntgRs/3Rv4PLCdLFMTQrSVBn+57VVpQB8/SbugyGaYSGve7kaWhtxsrEYbu/F/+hFRETUV7AgDXVJ\nR0mcRCKBQi6FI0K74DNmnV2vwGJzAQC06sC/a6TpVCFtW4N+eur2tL92awdnQImo95NJfB+B7jDX\nrhIREfVFferM4YmywHvC1TTJUe8ILVoCAN6m9k1jkWbCqdagrq2tt0kOe5kNNW1t7GU2mLxVYdcT\nTzp9M8ym6N4Hr9ly8UIQUgmglEvR1GLH3qLQbVJZbw273OmyJijkHf+t4kKN795/wWf9DLrQ4jeH\niutQ3dD+ek53ewJ68FQNSqvVIcuUivoUQEC/lpe3TxM/DjdfrLzcBm2TF6n1kfeRSMv2ZOXlNtQ5\n9PC2jTOnOg8WaftZPGFbW6SZKG0bU3UOPSzS9iS+zqHHibbxVV5uCxmz4rbiZcTz6kTthVhsXhmc\nauH1dSFjWxxHaZM87L7cE4m3oUXqDdjuYhap13/M84q2uXAMrWlbTthfhb62SL0B2z94eWG6WLU1\nGS2SwOMtgJA+EI650TzetrSdMTzecBpN9tCfKPdFemsSTKbWTrUtD1OISBBcWEraVoBKLHiZcFo9\nbnjUcrQmh77GaVuJv8BScOEjgVBkCgAsQYWMytsKNLls0pB5iaIr/UGx1dW+EPYvAGELdbUa3SFj\nQ1wsDAgs2BZcrCvSuBIT9n1xITJhOWG/r2iLRRwn0F6ADAgdO4mgq/2RnZyFAcn9YxhR7yHxdqam\nfi9x8y8/incIvd79N43B7iMVOHmhKaavs/TmMbhmbPsg/2xfKTbtKI7paxJR75KcWwZ31rF4h0FE\nRDGWqkrB6mlPxDuMqDl+vAglJd8BAMrKSlFd3f5H0/r6OgBAeno//7TMzP7IyclFWZnv0o0nn3w8\n4rr71JnD6/N1Ac+Di1uIpaUZ/I/Pnz8HS1txBmGeUBwBgK9AwoDoFEiIJl1yEswt0f+LY02jDala\nJQZl6eFye9Dc4oBKKYPd6cbkkUYMzdbj+PnGsMt6PV6UVJqg1yjRP91XLbLV4e7UWUNBkkKGK0dm\nBEybMX4ANElyeL2+M4Q2uwuapNDd+0JpOdweYPDA8EVejh75FoCvTwEE9GtlRYV/mvhxuPlilRUV\n0GpV0KdELngRadmerLIitCCNVlSQZmBbQZrz589hoKgwiklUsEQvFKRp2+bBY9YUpiCNvq0gijBP\nH64gTasFjY2+kpdabbK/jbggjbD8wIGDMC6/lxSkEW1Dk8kUsN3FTCaT/5h30YI0bfur0Ncmkylg\n++vDFKQJ7jOj0QCNpr2PzrcVpNHr9QF9EFCQJgrjZPs3F1Bb0R/3/9sYuDyuy15fb6HTJcFs7tzn\nRmVlZVu/N0OvTwmYZzK1l5TV61OQmhpajbqpKfznRPB6WlpakJycHPIaw4ePRG1tDZqaGpGamhZ2\nfampaTAafZ8XWVmBpXIrKytRW1sDozEjZF6i6Ep/UGx1tS+E/Qto39eFsZKamoYLF86FjI2mpkaY\nTM3IyxsEALhw4Rzy8gbBaMzAgQP/AuAbT+L1XIyw7wvjRLycsN8fOfItLlw451+3QDjeA6FjJxF0\npT/+cf6fMDtaYhxR79GnksPxgwJvCVDicUJhDX+GK8fQnkg2nK2Aw1qHDJXGP2/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XAAAM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\nxYQSxnDIPAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f33471097d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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Ursf1UgV+rxK1WvWsiyA8J8RnQcjp4c9DWna6/HrYX2Mppa6AWmEmL7fRuvNF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\nb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YiIiODOO+9k4cKFDB48mLlz55Kdnc3+/fsZN24cpmlimqbG5DdCyobApWyQa6lJNvTu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\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f332be0f710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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2LXz33VJcXFzlum/btoVbt4xrUQYElKRjx85cuHCeb75ZRHj4QTQaDcWK+eLg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\nP5KSLBeUwm9vAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3329835cd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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hxF0a5X5+MhNCCPG3kP22zbVr13LkyJFcn8MTfw+RkZGMGzeOsWPHEhAQgJOT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3FK6zgGaR3HFkyX9SeKchziPt/Tfp72XXHBtHmV3oipV+QzJL9vXK2xZOjI0KeeeUUhhLgEZZv1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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3355781590>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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48GE4OzvD398fw4cPh1KphImJCZYsWYISJUpg1KhRmDNnDjp16gSJRILKlSuL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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f339a3b5f90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = data.groupby(['price','size'])\n",
    "for (price, size), i  in g.size().sort_values(ascending=False).head(5).iteritems():\n",
    "    plotCancelBehaviourForPriceAndSize(price,size, lim=1000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There is certainly a cadence of placing and cancelling orders."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## HTF Strategies"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Bocconi Students Investment Club (BSIC) [5] describes some strategies which the HFT traders use to distort the perception of the market. For this post I'll focus on Spoofing, Layering and Momentum Ignition.\n",
    "\n",
    "### Spoofing & Layering\n",
    "\n",
    "Quoting from BSIC [5]:\n",
    "\n",
    "> Spoofing is a strategy whereby one places limit orders, and removes them before they are executed. By spoofing limit orders, perpetrators hope to distort other trader’s perceptions of market demand and supply. As an example, a large bid limit order could be placed with the intention of being canceled before it is executed. The spoofer would then seek to benefit from prices rising as the result of false optimism others would see in the market structure."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Detection\n",
    "\n",
    "There is evidence of high frequency spoofing on July 21, 2017 between 09:45:52 and 09:45:56. Let's take a look at the order book. Red points are SELL orders (3 BTC @ $2741.99), vertical grey lines are cancellations and the blue and green lines are bid and ask price, respectively."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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e+/fvp27dusYNz0WKFOGPP/5IdmQ7ERERERERSV2GPcri7gepBgYGUq9ePaNV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\nkiRJkoD/BxYFirSb+sNVAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f335081ebd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "size = 3.00\n",
    "price = 2741.99\n",
    "plt.figure(figsize=(15,5))\n",
    "\n",
    "q = data[((data['size']==size) | (data['remaining_size']==size)) & (data['price']==price)].head(1000)\n",
    "q = q.loc['2017-7-21 9:45:52.000': '2017-7-21 9:45:56.000' ]\n",
    "t=q.time.diff().median()\n",
    "median_tick_s = t.seconds+t.microseconds*1e-6;\n",
    "order_type = q.side.iloc[0]\n",
    "d = data.loc[q.index[0]:q.index[-1]]\n",
    "d.bid.plot(label=\"bid price\" ,alpha = 0.5 )\n",
    "d.ask.plot(label=\"ask price\",alpha = 0.5)\n",
    "q[q.reason!=\"canceled\"].price.plot(label=\"%s %.2f BTC @ %.2f\" % (order_type, size, price), style='o');\n",
    "ylim0 = 2739\n",
    "ylim1 = 2743\n",
    "plt.vlines(q.index[q.reason==\"canceled\"], ylim0, ylim1, alpha = 0.2);\n",
    "plt.xlabel(\"Time\")\n",
    "plt.ylabel(\"Price (USD)\")\n",
    "plt.title(\"Cancelled orders along time for %.2f BTC @ $%.2f. Median tick: %.1f milliseconds\" % (size, price,median_tick_s*1000))\n",
    "plt.legend(loc='best', frameon=True)\n",
    "\n",
    "plt.ylim(ylim0, ylim1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The orders are cancelled around 25 ms after they arrive! They are flashed with a frequency of around 3 Hz. The following animation shows the order book in more or less real time. Notice how a SELL order flashes at level 2741.99 with amount 3 BTC."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "MC4xMDE=\n",
       "\" width=100%>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def plotOrderBookAtTime(t,xmin, xmax, ymax, fname=False, arrowAtPrice=False):\n",
    "    data_past = data[data.index<=t]\n",
    "    q=data_past.groupby('order_id').type.last()==\"open\"\n",
    "    q = data_past[data_past.order_id.isin(q[q].index)]\n",
    "    q = q[q.type==\"received\"]\n",
    "\n",
    "    ask = q[q.side==\"sell\"].groupby('price')['size'].sum().sort_index(ascending=True)\n",
    "    bid = q[q.side==\"buy\"].groupby('price')['size'].sum().sort_index(ascending=False)\n",
    "\n",
    "    plt.bar(bid.index, bid, width = 0.01, color='g')\n",
    "    plt.bar(ask.index, ask, width = 0.01, color='r')\n",
    "    #xmin, xmax = np.percentile(bid.index,80), np.percentile(ask.index,20)\n",
    "    #ymin, ymax = 0, max(bid[bid.index>xmin].max(), ask[ask.index<xmax].max())\n",
    "    plt.xlim(xmin, xmax)\n",
    "    plt.ylim(0, ymax)    \n",
    "    plt.title(\"Order book at time: \"+str(t))\n",
    "    plt.xlabel(\"Price (USD)\")\n",
    "    plt.ylabel(\"Depth (BTC)\")\n",
    "    if arrowAtPrice:\n",
    "        plt.xticks(list(plt.xticks()[0]) + [arrowAtPrice])\n",
    "        plt.annotate('$%.2f' % (arrowAtPrice), xy=(arrowAtPrice, ymax-4), xytext=(arrowAtPrice, ymax-1),arrowprops=dict(facecolor='black', shrink=0.05))\n",
    "    if fname:\n",
    "        plt.savefig(fname)\n",
    "        plt.close()\n",
    "    else:\n",
    "        plt.show()\n",
    "    \n",
    "\n",
    "if False:\n",
    "    dates = data.loc['2017-7-21 9:45:52.000'].index\n",
    "    dates = dates.append(data.loc['2017-7-21 9:45:53.000'].index)\n",
    "    dates = dates.append(data.loc['2017-7-21 9:45:54.000'].index)\n",
    "    dates = dates.append(data.loc['2017-7-21 9:45:55.000'].index)\n",
    "    dates = dates.append(data.loc['2017-7-21 9:45:56.000'].index)    \n",
    "    ts = [t for t in dates]\n",
    "    for i,t in enumerate(ts):\n",
    "        plotOrderBookAtTime(t,2730, 2750, 10, fname = \"img/pic_%05d.png\" % (i), arrowAtPrice=2741.99)\n",
    "        print \"Done %d/%d\" % (i, len(ts))        \n",
    "\n",
    "\n",
    "video(\"videos/animation1.mp4\",\"mp4\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "One interesting thing is that neither the bid or ask price moves."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Also from [5]:\n",
    "> More controversial has been the act of layering which carries many similarities to outright spoofing, but differs in that orders are placed evenly across prices with the goal of reserving an early execution priority at each given price level. If the person has no trade to execute at that price point the orders are simply removed. Despite being more benign in nature, the act of layering also distorts market demand and supply perception."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It seems to be evidence of layering. Let's take a closer look at the minute between July 21, 2017 between 09:41:00 and 9:42:00. Orders seem to push the ASK level downwards, eventually decreasing the BID price. Next, BUY orders are placed at this lowered level, to be sold when the BID price recovers."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
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ysVJakavPxdXGhdlPTUWbklugfGq2ltC/PsXN1pWJrUYbZ7W1pPMpF/ji8DwM\n5P9z6d+gN9dzrhMZc4h32ryJndq20PM+PfQVKoWK1t4PwV2EqVaoaeHZFFu1DanZ15my7yP6NuhF\n+2ptS+J2KrzKOsxD3D9pG8IcaRvCHGkbwpzK2jbKZFipuD9RqRexUVmj0+eRZ8gDIClLw4rT6wst\nvxzwsvcwbusMeXz41+e83Wqk2aSsMMcTT911rP+mXkRv0LPp320m1/rj2n4AcvS5bL3wK8F1n0Sp\nyO/dtVKq8bBzByA2I45MXSYAufr8ZFCTncKUnZ/Q0KUBj/i0NLneobijpOdmkJ6bgU6vw0plddcx\n362N57caE0OA1Wd/NL6+eP0yjdwaFHpeVOolAM6lRN39RU+t5v22E/kn6Sx5hjxWnflRkkMhhBBC\nCGExkhyWUwaDAV8HH5KzNKTm5H9j8WLjAQXK6Q16NpzbQroug/iMxALHZx2cS7eaj/F0nSeMiZkl\n3UzyID9eG5U14Rd28E/SGf5JOmNStp5LbXrU6kKePj/5beUdQBN3fy6kXmZ/7EEupV7lUupVfrm0\n2+z1NpzfirXKivbVAo3JZkm5mhbD8cR/eNyvI9dzTL81qqK2J12XP8FRZMxBk3tr7tGE+q51TMoX\n9rMzJyM3k7XnNgEw9c+Zhf7c8vR57Li8h+qO1WjiLsu3CCGEEEKI+yfJYTmlx3BjuGT+WEQ7tV2B\nHrSbAqu2Qm/Q8/PFXWy58AsAM9tPZcXp9RxNOMHPl3axO3ovSkXRy3jYW9kZXxsMhnsarpmTd2sY\n6M14G7v788e1/cSmxwP5CeTBuCOcT7nAl0fmo1bmN8M6zrV4xKclj/i0pH/DYE6mneD41XMm9R9L\nOGFMlgF+u7oPgB2X91DFyp6naz+Bg7VDkTFWUdvTwLXuHe9v07/bOJl0ms1RP5vsD/RpRd8Gz/De\nnx+RnpvBwbgjJsd3Re/liZqdqeFYDYD6LnXM/uzM6VC9LRP2vk+mLhO9QW/cf+l6NDWdanBJe4Wf\norYD8NVjYXdVtxBCCCGEEIWR5LCcMhgMKFAYExjlHR5YUyqU9Kjdhc412pGr1+FgVYWhzYZwLS2W\nndG/cUV7rcjz9QY919Jjjdtpuek43iHJuklxW2w5+pwCx62UajpVDzLZ17veU8Smx/NnzAFi0+Ox\nVlnT0NV0ttlOtdvSxKGpyb7+DYJZeWYDSZnJPFWnKwqUrDm7kcvaK6TnZrD67MZixexu60qP2l1p\nW7WV2TLf0XsGAAAgAElEQVRpuekAeNl5EJ95q1dWk52CrdqGme2mEpMeh86gMx47p4liw/ktJr2d\nhfXo3olSoeTjdlOISY/jUNxRfr0cAUDYwS8J9GlFA9e6xrJzj+Q/49nE3Z82Pg+jVqpYf34LrjbO\nAHSv9fhdX18IIYQQQjx4JDkspwyY9twVtxfPVm3L7VOj+Dr48EKjfsU691jCSb49vgSASb9/QBN3\nf/o36I27nWux487JK5gcFsbFxhkXG2f83eoXu27Ifx8G+fcx2Tex9Wjy9Hn8FXuY7EKS09vFpMXy\n+7X9JGVpWH5qDaeSzjCkcX9j7+Xt1Ao1ChRMCRyPwWBg4ckVHEk4TuCNhFKhUODr4GNyjp9jdao5\nVCU2I54Tiac4lXyWh71b3NU9Gq+vVFPDsRo1HKvR0LUe51MvsP3iTiJjDxIZe9BY7lTyWeP/1537\nqUA9khwKIYQQQojikOSwHLo5gazixn83X1tac88mjA4YysZ/w7msvcLJpNO89+dH9Kj1OF1rdsZG\nZX3HOnL1ujuWsQSVUkVb39bFKtuvQTARV/5gw/ktHIo/yqnkswxr/hJ1nWuZJOE5edlYq6zyn/lT\nwGvNXkBv0N/x2U1/t/r4u9WnU/Ug8vR5qJRFD+ctjkbuDWjk3oBaTjU4GHfEOJS1b4NnCKr6CH/F\nHeZg3FHO/meGW4B3//iQJh7+GAx6/kk6i5utKz1qF50wqhQqajvXxKqQpPm/NFkpvLvvQwBCWo+l\nuqPvPdyhEEIUpDfomXdsMdfSYvG29+SNgFdL5fl5IYR4UElyWA7dfMbs9j+AylJYrgGgoVs9JrqN\n5vL1K8w8OAeAbRd3svPybzTzaAyAtcqazjXaGZfJKI2lJEqSSqnicb8O1HLy47PDX5Ohy+Tzw9/g\nbe/FuJbDjcNps/NysFHZmJx7tx9KSiIxvF0zj8Y082jM8/59uZoWQ02n6igVSoJ82xDk24ZrabH8\ncmk3B+L+Np6jyU7h96uRJts3h6LeycNeLbBSWfFc/Z7Yqe0KLfNvygXj648OfMGEVqOo6VTjHu9Q\nCCFuydJlcTLpNJD/uys9N6PYjzwIIYS4e5IclkM3l0y4vbdQUcrflPo5VWdu55lExhxkzblN5OTl\ncCj+qPH4nzEHqONck+fq9yrVuEpSXZdazO70IStPbyAy9iBxGfFM+v0D+jcIprlnE7LzcrAuRm9p\nWbBWWVHbueASJb4OPrzUZCB1nGuy4fxWWnkH0KF6W2YemGMs80ydHujRFzj3pixdtvEZx5s/88iY\ngwxu1I82Pi0LJMjXc9NMtr84PI/POs6ocF8aCCHKH/1/lmL+77YQQoiSJclhOWQcVqq4NSFNaQwr\n/S+FQkFb39Y84tOStNwM4/5jiSdZdWYDUamXCDv4JS43Jj6piNRKNS807sfTdZ4wDo1cfXYjP/4b\nTm5eboFnCiuKDtUfJbBqa6yUahQKBR8GTWHN2R9p4/MwzT2b3PH8J2t3JVOXxfWc63x8YDYAy0+t\n4YdTa/mo3RTjN/c6vY715zabnJujzyU7LwdbtU2BeoUQ4m7cvr5s/rb5L7aEEELcP0kOyyFjz6Hi\nVkpYlr0wKqUKZxtH43b7aoH4OVZjS9Qv/JN8hpTs1DKLraS42rrwcbv3iEq9SFKWhojo38lUZNHM\nvVFZh3bPrFVWxtfONo681mzIXZ1rrbLC2caRj9pN4a/Yw/x4fisGDEz6/QOeq9+LZh6NC0xAVMe5\nFlGpF8nUZUpyKIS4b7cv5QO3vjwVQghhGZIclkM3h83kL19Rdj2HRanpVIM3Al7ldPI5vjwyv6zD\nKRGO1g608MxfOuOxGu3LOJryw8nakS5+HWnj8zCTfv8AgHXnfmLduZ9MnkMc3Kgf0dqrRKVe5NL1\naFxtXQA4qzmPtcqaWk4Fh8FaisFg4FzKv9R1rl3iz30KIUrPf3sOZVipEEJYliSH5VB56zksir9b\nfUYHDGXOke/KOhRhYY7WDnzWcQZJmclEpV5k47/hZOoygfxhqG2rtkKbowVg/oll1HWuRaYuy7h+\nZk3HGqiLnagpaFetTYGJbayUalxtXO549u4rv7P+3GaeqNmZZ+r2KP5NCiHKlQI9hzKsVAghLEqS\nw3Lo1lIWSriRFCrLWc/h7Rq61SOk9ViiUi8aF6GX2SorJxuVNb4OPvg6+ODvVp/wCzs4lnjS2CvY\nodqjnE4+x7mUKP5NvWhy7mXtlWJd4+aXI/+mXij0eG2nmkzoOIyifn2dTj4HwD9JZ4pMDg0GA39c\n208Lz6YmMyCmZl/ncPwxOlRrKz2PQpSh/w4jlZ5DIYSwLEkOy6GK1HN4U3VHX6o7+tKmait2XN5D\nkO8jZR2SsDAPO3eGNO5vss9WbcPoh4YCkJuXy/uRs9BkpzCkUX/aVH24WPUaDAZ2XN5DQmaiyf70\n3EyOJBznwvVLjNg8mSpqe7N1pOvyJ1C6U2IXGXOQlWc2sC/mABNajTLu//bYEi5po1ErVbSv1rZY\ncQshSt5/k8H/DjMVQghRsiQ5LIdu9RwqjM8alvZSFvfKRmXNU7W7lnUYohywUlnxwaOTSMxMwtPO\no9jnKRQKutbsVOixuIwEvju+FCu1ijyd+eFlN5PDS9ej+eboQrPlTtxYP+3S9WiT/dFpVwFIyar4\nky0JUZH9dxipwSDDSoUQwpIkOSyHbn4zqlQobs5HU66HlQphjlKhxMves8Tq87b3ZEqbt/D0dCQh\nQWu23IXUy3xyaC5wKwG8k+0Xdxlf//c5p+K4rL2C3qAvMPFOYmYyh+OOor+tx0OpUNDMozFVq3gX\nqOdaWizHEv8xbidkJOJgXYXazjUJuDFhkhAPClnnUAghSpckh+XQzQ+mpj2HkhwKUVy1nf2Y0+kj\ncvW6IstFpV7kq6PfA7A5anuB49fS4zirOW+yz8+xOrZq2wJlZx6YA8BXj4WZ7P/54k72xRwoUP6n\nf7fTyvshHvVtZbJ/8clVpOZcLzReRysHrFXWtPIOwN+tnskxG5UNfo7Vi/27IjEzGRuVtcmzlkKU\nNwUnpJHkUAghLEmSw3Lo9mcOy+tSFkKUdyql6o7PHDZ2b8h7gW+TnKkx7tNj4OsbCeOxxJMcSzxZ\n4LxZ7adhpbQyOcec7BtrQb7cZJDxOUltbhpL/1nNgbjDHIg7XOh5I1v8j8y8LNad3cT1nDTcbF25\nnqNFm5vGz5d28fOlXQXOaeUdwJBG/Y33rTfoydPnFSiXq9cx9c+PcbN1ZfqjIWZjF6KsyVIWQghR\nuiQ5LIdun620okxII0RF5W3vifd/hr5+0uF9fr+6nxx9rsn+8Au/AvD23mnFrj/vRs+Hv2t9HKyr\nGPdXc6jK0YQTJh99z2rOcz7lAvVd6tDIvQEALb2am9T3V+xhEjKTTPZFpVzktOYcB+OOcDDuCG18\nHsbTzp0tF34pMrbkLE2Rx4UoawUnpJFnDoUQwpIkOSyHbv4xzH/mUHoOhShtdmq7QifFebRqa1ad\n+ZE8g2lv3Knks8bXH//1hcmx6LRrAKiUppNKVXOoSjWHqib7nqrdlbScdOwKGbZ60yM+LQvdvyt6\nLzsuRZCao2V/7CGTY43cGhQ73ts52jjSs043XG1cZPipKBMFJ6SRnkMhhLAkSQ7LIeOwUirOUhZC\nPAhcbV0Y0eLlAvszdVl8cXgeV9NiTHr1svKyja9ViuL9ur29d/FuPFajPZ2rt+OM5jwZuswb11TR\nyK0+1iprk7Kp2VpmHfwSTXZKgV5Ik9jT8teKBOjq14kna3fFWmVVaHkhLEHWORRCiNIlyWE5ZBxW\nqriVHspspUKUX3ZqW0IeGVtgf3KWht+u/Im3vWepJFUKhQJ/t/p3LOds48iMoMlFlonWXuWv2MPs\nit4LwK+XI/j1cgR+jtXpXKOdsZynnQe1nf3MVSPEfZF1DoUQonRZNDkMCwvj0KFD6HQ6hg0bxpYt\nW9Bo8p9xSUlJISAggOnTpwP5CdHAgQMJCgpi1Kj8xai3bdvG5MmTWb16NQ0amA6LunLlCj179qRp\n0/yp3V1dXZkzZ44lb6fU3BxGc/tQ0oqyzqEQ4hY3W1eC6z1Z1mHckxqO1ajhWI3e9Z4iWnuVLVG/\n8E/yGS5rr7Dkn1UmZXvXe4p2voHYqm3KKFpRWf13WOm9LDMjhBCi+CyWHEZGRnLu3DlWr16NRqOh\nd+/eREREGI+HhITQt29f4/batWvJzb01+cNff/3Fb7/9RsOGDc1eo3bt2ixbtswi8Zclk55DeeZQ\nCFGGlAolNZ1q8EbAq1y6Hs2VG89QAvxycTeJWcn8eH4rP57fyuM1OtxxhliVQkWQ7yO42rpYOnRR\nCRToOZRhpUIIYVEWSw5bt25N8+b5s+w5OTmRmZlJXl4eKpWKqKgotFqt8XhycjKbN29mwIABxMbG\nAtC4cWMeeeQRXnjhBUuFWG6ZLmWRTynPHAohylhNpxrUdKph3A7ybcOOy3vY9O829AY9O6N/K1Y9\n2y7uoI5zLZ64MemPldKK+i517phYigePocA6h9JzKIQQlmSx5FClUmFvn7+m17p16+jQoQMqVf4f\n/qVLlzJ48GBj2VmzZjFu3DguXrxo3OfgcOeZ8RITExk9ejTx8fEMGjSIXr16lexNlBHjbKXcGkoq\nPYdCiPKoi19HOlUPIlp77Y4f3PUGAz+e38rF65eJSr3IvGOLjcdsVNY0dL3z85I3WSnVPFv/aVxs\nnO81dFEB3D5BmwGDTEgjhBAWZvEJaXbs2MG6detYuHAhADk5ORw6dIhp06YBcODAAVQqFS1btjRJ\nDu/ExcWFMWPG0KtXL7RaLX379iUwMBAvLy+z57i62qNWl/9vpjOsUgGwt7dGlZafINrYqPH0dCzL\nsMrEg3jPonikbZQvVb1di1Wubf3mXL0ey6FrxwFIybrOljM7yM7L4Vjiybu65uGEYzzfvDdd6rTD\n3trOuL8itI2T8WdJytDQvuYjMht1EWLy8pd1UStV5Op1ODvb3dfPtyK0DVE2pG0Icx60tmHR5HDv\n3r3MmzePBQsW4OiY/8YeOHDAOJwUYOfOnZw4cYJ+/fqRnJxMTk4ONWrUIDg4uMi6HRwc6NOnDwBu\nbm40bdqUqKioIpNDjSajBO7K8pK06QBkZ+rI1ekAyM3Rk5CgLcuwSp2np+MDd8+ieKRtVGzWVKGt\ne6Bxu2vVx8jJyy3iDFN6g56lp1ZzMuk0y49uYMWxjXjYugGgUinJy7v/oYfxmYkAeNl54GbrSo/a\nXe67ztt9fvgbAL7avwRPO3cAqlbx5jG/DsYyChT4OVbDqoRnuk3K1OBs44haWfAjgN6gJ1p7FQer\nKrjbuZXodYuSnZdDtPYqdmpbMnVZxv0x6XFA/rOvAMkp6SSo7u3fvvzeEOZI2xDmVNa2UVTCW6zk\n0GAwkJycDOQnYsX5llOr1RIWFsbixYtxcbk18cDx48fx9/c3bk+aNMn4esOGDVy9evWOiSHkT3iz\ne/duQkJCyMjI4PTp09SuXbs4t1PuGWcrVSiMk3bLN8tCiMpKrVQXmqgU5fUWr3DpejQ7Lu/h35QL\nZN9YU1JpUKLX319ymJ2XY3wdn5lIfGYipzXn7qtOc5ysHcjOyyY1R0t8ZiJHC+k9HdH8ZRq5NSjk\n7Py/Dcq7mM06KVPDe39+RH2XOoxtObzA8f2xh1l+ag0ALTyaYKu2LXbdD3k1o7Gb+UnkCnPzOdPl\np9ZwOP6Y+XKK/HI7L+/hWOJJnqzVFQcre5M6hBBC3L8i/xofO3aMb7/9lj///BMbGxsMBgO5ubm0\nbduWoUOHmvQA/ld4eDgajYaxY2+t/TVz5kwSEhLw87vzmlhr167lp59+4tSpU4SEhFC3bl3CwsII\nDQ1lyJAhtGrVio0bN9K/f3/y8vIYOnQo3t7ed3Hr5ZdxtlIUYCg4OY0QQoj8CXJebTrYZF9Jfct7\nIPZvUnOuU93Bl3MpUfdd3+2itVc5mXSaIN9HGOT/HADnUy5wKvmssYxOr2PH5T0AfHNsUZH1tfZ+\niLout74ctVFZ87BXC/5NvYCvQ1UcrKoYjyXc6BE1d08pWSnG14UlqkXZH3vorspD/pIpz9XvRfJt\n13WyduRR30fYc2UfmbpMABq5NeBQ/FHOaM5zRnOe369GGstXc6hKF7+OBHg2K5X1RIUQojJTGMzM\nCz179mz279/PK6+8Qtu2balSJf+PS0ZGBvv27WPhwoUEBgYyevToUg34flSUbuGL1y8z6+Bcuvh1\n5HjiP8RlJNDUvREjWrxc1qGVqsralS/un7QNYU5FaRvpuRnYqW2L7PXL0mXzU9R2Ym8Mrfyvy9or\nJkMwzele8zFi0uNQK9U86vsIXx6ZD8BXj4UVKLvxfDi/Xo7g1aaDqelYvZh3A79cjiAhI7HY5dNy\n07maFmPcVqDAVm3Lu23exNnaKX/kjMFASnYqSoUKZxtHUrO1pOems+nfcHL1+Y9cnNGcN6m3qp2v\n2WuW1JBjUflI2yh5ViolTjYO9Krb457Od7CqgrONUwlHdfcqyt+Uu3VPw0pdXFxYsWJFgf329vZ0\n6dKFLl26sGTJkpKJUJi4veewsGUthBBCVGxVbgyJLIqt2oZ+DZ4xe9xgMPBP8lkyc289T5+dl8PW\nC7+QmnPrw8z2S7uMr6/nFP0hJ0efP6TWy87jrp45HNjw2WKXvSkq9SJ7ruzjeOI/6A0Gmrr7m8w+\nq1AoTNbDdLZxxNnGkREtXgEgT69n7LxfyXa4hFX18xj0Sq6lxd51HEKIkqdQ6SENTiSdvrfzUdDc\nswmupTQjta3KhidqPYaNyrpUrleemU0OX3zxRTIyMti0aRNnz55FpVLRpEkTnnrqKaytrY1lRMm7\nPSH0tvckPiNRpmsXQghhQqFQ0MS94DN+QdXacCT+OBevR9PSuzlbo34xfkC7fTjpuIh3aOzuT0uv\nZsZ9MWn5vZTWpfABqY5zLeo417rn83V5BtKvW+FOEwLyOt2xvJ2dFZmZxZ/4SDw4pG2UrL1Hr+Hs\nlUGrwFzuZfGZLF0WB+L+5mjCiRKPrSi/X9tv8oWcm60rnp5NSzWG8sBscnjt2jUGDx7Mww8/TEBA\nAFqtlm3btjFv3jyWLFmCj49Pacb5QLm1zqGCV5u+QHxGAj725mdhFUIIIW4X4NWMgBtJ34gWr5CW\nm056bga5eblsOL+FhMwkkrM0HEk4zpGE4ybnKlBgb2VXWLXlkq+HA893LXzCnttV1uFh4v5J2yhZ\nB8/Eo8x0pW+DtvdcR5/6PdHc9iyyJaXnZjDnyHek5aaz8KTpqMmGl+qiyCv+pF+WYKu25cXG/Uvl\nSzsoIjn8/PPPGT16dIGZQ9etW8eHH37InDlzLB7cg8pguDlbqRIrpZpqDlXLOCIhhBAVmYNVFePE\nNKMfGgrAP0lnSMxMLlDW087dZBIbIYS4G0qFgsJnNCm+Klb2xRp+X1LebzuRU8lnb4vbwL5rf3Em\n8d9Si6Eo5/b9y4xH3ymVSbeK7DksbEmJ5557jqVLl1o0qAedPGcohBDC0hoXMiRVCCHul1JxaxRc\nReFh5077aqY9ne2rtcXNowqJZdirnJSVzPuRs0jPzWDcnncY89AwajhWw+4ulhm6W2aTQ5XK/LpB\nzs7y/Jsl3T6sVAghhBCFqFifPYV4YCgUigqXHBZGoVCgVqrKdC1VL3tP3nr4dT499DUAs//+FoCH\nPJtRtYo3j/m1x1ZlW6IdSmaTw+zsbKKjows9lpOTU+h+UTKk51AIIYQQQlRESqUCXa4sDVJS6jjX\n4otOH/LDqXUciDsMwN8Jx/k74TjhF3fQwqMJQ5uX3CShZpPDhIQEs7ORStJiWbcvZSGEEMLyTp8+\nxTffzCEhIR693oCzszOvvz6GFi0Cijxv5Mih9OwZTPPmAQwY0Js9e/bf1XV/+ulHevXqXWD/999/\nS0JCPJMmTSlwbMyYEbz++hgaNvQ3W29R55eGQYP6MHfud7i5uVv8WvKRRIjyRVECzxwKU1ZKNS81\nGUC/Bs+QZ8jjsvYqf1zbz9GEExxNPMmWqJ9p7J7/N8FaaUU1h6r3nK+ZTQ537dpl7pCwMOk5FEKI\n0mMwGJg4cRwTJ77Lo4+2A2DPnl2EhLzFhg1bsbW1zLMdSUmJrFixtNDksCizZ39jkXhK0ooV68s6\nBCFEGamIzxxWFDdnkm7i3pAm7g3ZfnEnm6N+ZtvFnWy7uNNYzt3WlYau9VAr1TxRs7PJmrF3YjY5\nzM3NZceOHfTo0QOAiIgI1qxZQ82aNRk1ahT29qU3g9CDRnoOhRCi9KSkpJCUlEiTJrfWs+rY8TEa\nNWpiTAw3bdrA6tU/kJOTQ5MmzZg8+T1sbIqXNP7++x6+++5rcnNzsbOzJyRkCvXrN2T48FdJSIhj\n0KA+LFmyCisr01nocnNzmDp1Mv/8cwJXVzdCQ8Pw9PTiued6MmXKdFq0CGDp0oWsWbMSH5+qPPlk\nT1asWMq6dZuLPD8+Po5PPvmYy5cvATBmzFu0bRtETMw1hg9/hccf78rZs2eYO/c7k3hGjhzKQw89\nzP79fxITc4127TowfnwIKpWKdu1aMWzYG4SHb2b58rV07NiGDRu24uXlzfLli9m06UdUKhVBQe0Y\nOXIcCoXivt5TIUT5pVQq0OslOSwN3Ws9ThWrKiRnaQBIykzmUPxRkrI07Is5AMBvV/8EoHe9p7BX\n5yeXz3g+brZOswt3hIaGsnv3bgBiY2MZP348nTt3xsrKio8//rhk7kgUSnoOhRCi9Li4uNCoUWNG\njx7Oli0buXbtKgBeXt4AHD36NwsWzGPOnHmsW7cZBwcH5s+fV6y6dTodM2ZMY8KEd1m5cgPt23dk\n7tzZAISETMHb24cVK9YXSAwBDh78ixEjRrF27U+4uLiydetPJsejov5lxYqlLF68kq++ms+uXb8W\n6/zQ0GnUr9+AVas28Mkns5k+/T1SU/PXE0tNTaF+/YYFEsObIiP3MWfOPNau/YkjRw6zb99e4zGD\nwcDKlRtMJrQ7evQIW7ZsYsmSFSxbtppjx46we/fO+3pPjdeTGWmEKJcUKJDcsPS0rxbIM3V78Ezd\nHrzS9Hlmtp/K1MAJTGkznuYeTYzlfjy/lR9Or+OH0+uKrM9sz+Hx48dZvz5/WMj27dvp3Lkzffv2\nBeD5558viXsRZshspeVPdk4e2/ZfIisnr6xDAaCWjyOBTXzKOgwhKgWFQsHnn3/N6tU/sHbtKj7+\neAa1atXhtdeG07HjY/zxx288/nhXPDw8AQgO7sPkyRMYOXLsHetWq9Vs2fIranX+n9sWLR4iPHxL\nseJq3vwhfHzy17mtX78B8fFxJsePHv2bhx56GA8PDwCeeqoX33//bZHnZ2ZmcvjwQaZPz/+St3r1\nGrRoEcC+fb8TENASnU5Hhw6dzMbUpcsTxt7UNm0e5fjxY7Rvn1/+0UfbFygfGfkHbdu2w94+f93E\nL7/8DisrK779du49v6dCiPJNqbw1Ck6UvtvXtR3W/EWydNmcTDqFTl+8z7Bmk8MqVW4tgBsZGUm3\nbt1unaQ2e1q5Nm532TyYf7f05P/w1kVEsT6pjIMpQ/lj1ss6inyZ2bqyDqGAxdtPo1Ka7fyv8G6+\n5y90a0jnh6qVcTSisnNwcODVV4fx6qvDSE5OIjx8M1OnTmbx4pVotWns3bubv/6KBECvN6DT5Ra7\n7rVrV7F9+xZycnLIyckp9qiQ2/8OK5VK9HrT2f+02us4OjoZtz09ve54fnp6GgaDgeHDXzEey8zM\npGXL1kD+MlZVqjiYjcnJ6dZSVo6OjiQmJt52zKlA+ZSUFGPyChgTy/t9T4UQ5ZeykixlUVnYqm14\n2LvoydVuV+Qzh1lZWWRkZPDXX38xffp04/709PT7j7QMZKVZl3UIxWbQq8jVuGLI1lHDy/wf6spM\nrVai05WfqZD1BgPPtq+Dq5NNmcZx6EwCx/9NqnQDqpLjLnJ83yacPXwJaN+X6Pg0AH45EC3JobCo\n+Pg4YmJijDOTurm5M3jwS+zatYMLF/7Fw8OD7t2fvqderePHj/LDD0uYP38JVav6cuBAJDNnhpZI\n3FWqVCEzM9O4nZSUWETpfC4urqhUKhYsWFZg7oCYmGt3PD8lJcX4Wqu9XmhCaHo9F+OQVcD4+n7e\nUyFE+aZQKNCXn49v4i6ZTQ779+9P9+7d0el0PPvss3h6epKdnc0bb7xBx44dSzPGEtOn6ktlHcJd\nUVRX0LKBJ66OZZuMlBVPT0cSErRlHUa5U8vHiT4d65Z1GCVCr9ezceN6fvxxPfv27UWr1bJ+/Wba\nt3+EVz7OnzFZhqYIS4uPj2Py5Lf49NO5+Ps3AuDUqZPEx8fSqFETfH2r8+67E3n++RdxdXVl794I\nLl26yODBL92xbo1Gg6urK97ePmRlZbFt21aysjIxGAyo1WoyMzPR6XT3NCKnUaMmLFo0n5SUFOzt\n7dm27c7DVdVqNW3bBrFx43oGDXqBrKwsPvtsJq++OqxY1/ztt9306dOPvLw8IiP3MXr0W0WWDwrq\nwHvvTeJ//xuBvb09ISHjCQ5+jnbtOt7ze3qT/GoQonySYaUVm9m/RsHBwbRt25bU1FQaNGgAgI2N\nDV27dqV///6lFmBJ6tKqRlmHIIQAUlI0fPfdN+zY8TNHjvxt3F+rVm3atg0yLSx/X4SFNW3anAkT\n3uHTTz8iLS0NvV6Pm5s777//ET4+VfHxqcqQIS8zatQwDAY9rq5uvP325GLV3aZNW378cS39+wfj\n4eHJmDFvcfLkcd59dwLvvDMNJycnnnmmG99//wM+Pnf3HHHjxk3p3v1pXnnleby9vXnssSdYs2bF\nHc8bPz6EsLAP2bJlIwBPPNEDb2+fYvUcNmvWnNGjh3PlymXat+9MYOCjRZZv2rQZgwa9wMsvD8LK\nyprAwEfp2rUbCoXint9TIUT5JsNKKzaF4QFK7aUXqmKRnsPK5+DBv1i2bBEREbsL/SD6xBM9WL58\nNd5KyBIAACAASURBVICx59DLxY6Ph7c1KSdtQ5jzoLUNg8FgfIZx377fmT//axYtunOCeC9GjhxK\nz57BdOv2pEXqv1uZ2Tre+Pw3WtR1Z0zfFncs/6C1DVF80jZK1swfDnMmOoXvJ3au8DPvV9a24enp\naPaY2Z5Df3//Aj9QR0dHevXqxdtvv42NzYM51FEIcXd0Oh0rVixjy5ZNREb+SVZWptmyjRo1LsXI\nhKjYNBoNzz//HAsXLsfb24ddu36lSZPmZR2WEOIBdzN9MBhuvRYVh9nk8OTJkwX2JSYmsmzZMj77\n7DNCQkIsGpgQouLLzMwkOLgHf/99uFjl27XrYOGIhKg8XF1dGTp0BGPGjEChUODnV4s33hhT1mEJ\nIR5wSmV+Rqg3GGRZtgrIbHJ4+yK2N3l7ezN+/HgGDRpk0aCEEJWDnZ0dH3/8KWPHjuTUqYJfON2u\nZs1aBAUVXCdNFroWwrzg4OcIDn6uVK41d+53pXIdIUTFprzRXfgAPblWqdzTImkVdZ1DIUTpe+ih\nh1m5cl3BiWb+w9+/UaG/W+RvixBCCFFx3HwsTZazqJjuOjk8ePAgdnZ2lohFCFFJ+fpWo2nTZkWW\n8feX5w2F5e3b9zunT58q6zBECaroE14IUdncGFUqM5ZWUGa7AAcNGlTgF25qaioGg4Gvv/66WJWH\nhYVx6NAhdDodw4YNY8uWLWg0GiB/Id2AgACmT58O5Hc9Dxw4kKCgIEaNGgXAtm3bmDx5MqtXrzYu\np3G7BQsWsH37dhQKBSNHjqyw6y8KUdnN+z97dx4WVfk2cPw7MwiyLwKuWO6WqKhY7ppLu+YKimhm\n5lIumJpbJuaOu5lhmpn2y1QyS1PrVSNJxUhT0dJUUBGVRQYEWQfm/YMYm2BckGEYuD/X1RXnOWfO\nuQ88zsx9ni14DZs3f37fYzp0KNylVIiSlJiYyNSp75KWlsbEie8xdOgwU4ckhBDlTsGYQ+lWap4M\nJocBAQGFymxtbWnUqNFDdSsNDw/n4sWLbNu2DbVaTZ8+fQgNDdXtnz59OgMGDNBt79ixg5ycHN32\nb7/9xuHDh2nUqFGR54+JiWHv3r18/fXXpKWl4efnR4cOHYocKymEMJ29e3ezfPkSsrKydGUqlQo7\nOztSUlKA/PGG7dpJciiMR6vVMmnSOC5cOA/AjBmTiYgIJyhohfSGEUKIElQw5jBPckOzZLBb6blz\n53jmmWf0/mvSpIleYvj554ZbAlq3bs2qVasAcHBwICMjg9zcXACioqJITU2lWbP8KbeTkpLYvXs3\nAwcO1L3+6aefZuHChVSqVKnI8x8/fpyOHTtiaWmJi4sLNWvW5NKlS49w60IIYzt16iSzZk0jOVmt\nV+7nN4RVq9bi4eEBQKNGjQ3+WxeiJKxatZz9+/fqtrOzs4mMPENOTrYJoxKPQxolhCibCjoe5kl2\naJYMNgHevXuXwYMH88Ybb9CuXTtsbGwASE9P5+jRo3z++ee0a9fO4IlVKpXuNSEhIXTq1EnXqrd5\n82b8/f11xy5ZsoSJEydy5coVXZmdnd19A09MTMTFxUW37eLiQkJCgsGWRgBnZxssLKRl0Zzcb5FO\nUbbduHGDyZPHExMTo1f+yiuvsHHjeiwsLGjSpCEjRoygZUsvg39rpUpZ5D6pG8KQ/9aNsLAw1q9f\nq9fFydnZmVWrVlCvXq3SDk+UkLsZ+b2NLC0tHvr9QN43hCFSN0qOtbUlAC4utjg7VDZxNI+votUN\ng8nh2LFj6dSpE8HBwbz33nu6p/o5OTm0bduWqVOn6lr+7ufAgQOEhISwceNGIP9p7YkTJwgMDAQg\nIiIClUpFy5Yt9ZLDR/Uw/ZrV6vRin1+UPjc3exISUk0dhiiGjIwMBg3y5cyZM3rl3t6tWbUqGLU6\nA4AnnmjEl1/u4M6dOwb/1rmavEL7pG4IQ/5bN9LSUhk7djwJCQl6xw0fPpLmzZ+VemTG0jM1AGRn\nax7q7yjvG8IQqRslKyc7/99mQmIamqycBxxdtpXXunG/hPe+gwebNWvG2rVrycvLIzk5GQAnJyeU\nyoeb5DQsLIzg4GA2bNiAvX1+EBEREXpJ5cGDBzl79iw+Pj4kJSWRnZ2Nh4cHvXv3vu+53d3diY6O\n1m3HxcXh7u7+UHEJIYwnLy+PceNGc/Tor3rl9es3YM2aT3FwcNQrr1q1GlWrVivNEEUFMmXKRM6c\nOaVX1qPHC0yZMt1EEQkhRPkm3UrN20MtWKhUKvW6cD6M1NRUgoKC2LRpE05OTrryyMhIGjdurNue\nNm2a7uedO3cSGxv7wMQQoE2bNnz++eeMGzcOtVpNfHw89evXf6QYhRAlb/bsmXz//bd6ZVWrViMo\naCV169Yrxhnlw0UUz2effcp33+3UK6tfvwFLl6566IecQgghHk3BhDQyW6l5Mtpq9nv37kWtVuvN\nerp48WISEhKoXbv2A1+/Y8cOvv/+e/766y+mT59OvXr1CAoKYv78+QwdOhQPDw98fHzw9/dHoVAQ\nGBgoH/ZCmNinn37Cpk0b9Mpsbe2YNWtOsZeqkI8WURxnz55h9erlaDQaXZmtrR0zZ86mevUaJoxM\nlBx5dxCiLFIoC2YrlX+j5shoyaGvry++vr6FymfNmmXwNX379tX9PGDAAL2lLgrMnDlT9/OQIUMY\nMmTIY0YqhCgJ+/b9wLJliwotWfHOO+Px8RlkwshERZOZmcnUqZO4efOGXrm//1BeeaWXiaISQoiK\nQZayMG8PbGpLSUlh8eLFTJ48GYBDhw6RlJRk9MCEEObjzJlTvP/+VNRq/SUrfH0HM2nSVBNFJSqq\n99+fSkTEcb2yDh06M3v2PBNFJIypYHyTEKJsUMqYQ7P2wOTw/fffp3r16ly/fh3In2106lT5sieE\nyBcXd4sJE94mJuaaXnm3bs+zdOlKFI/5zU16pYhHsWXLFrZv36pXVrt2bZYsWaG3Tq8QQgjjKOhW\nKmMOzdMDk8OkpCSGDh2qW8rixRdfJDMz0+iBCSHKvoyMDEaPfpNz587qlbds6U1w8Ab5Mi5KVXR0\nFLNnz9b7jLKysmLy5BnUqycTlpU38rVTiLJJupWat4eawSUnJ0f39D8xMZH0dFkvUIiKTqvVMn78\nGI4cCdMrr1evPh9//CmOjk4GXilEydNoNEyZEqC3xBHAgAEDGTjQz0RRCSFExSNLWZi3Bz7W9/f3\np3///iQkJDB69GgiIyP1JoURQlRMgYHvF1omwN29KkFBK6WVRpS6uXNnc/hwqF5Z69bPMH9+kGkC\nEkKICkq3lIW075ulByaHL730Ei1atOCPP/7A0tKSDz/8UBabF6KC27BhHRs3fqpXZmtry/vvB9Kx\nY6cSvZaMWRAPsm/fD2zZskmvrGrVaixcuBRra2vTBCWEEBWUsmApizwTByKK5YHJ4aVLl/juu++Y\nNGkSANOnT+eNN96gYcOGRg9OCFH2/PjjXpYsWai3ZIVSqWTMmHEMHDi4xK+Xo8nj75hkvbJ0jRZr\nFY892Y0wf3FxccybN5u0tFRdmYWFBePHT6RZMy8TRiaEEBWTrlupPNw1Sw9MDufMmcOECRN02/36\n9WPu3Lls2bLFqIEJIcqeyMjTzJw5FbVafzkbX18/pkyZbpRr3s3UsOh/JwuVTxvckoYeMq6xItNq\ntUyePJ6LF//WK+/ZszdvvTXGRFGJ0iLfO4Uom3QT0siYQ7P0wOQwNzcXb29v3ba3t7d08xKiAoqP\nj2fChLe5du2qXnnXrt1ZunRVibfiPVHNnqu3Unml7RN665hF30zlXHQSKXezS/R6wvwsW7aYH3/c\np1fWokULlixZYaKIhBBC6MYcSr5glh6YHNrb2/PVV1/x7LPPkpeXR1hYGLa2tqURmxCijMjMzGTM\nmDc5ezZSr9zLqyXBwZ/plropSbNe90ajycOykkqv/NDJ65yLTpInkhVIVNRllEolTz5ZR1cWFnaY\n9euD9Y5zcanCihUrcHBwLO0QhQlJ93IhyhbdmEP5mDZLD1zKYuHChZw7d46AgADeffddrly5wsKF\nC0sjNiFEGaDVapkw4W3Cwn7RK69btx5r1qzDycnZKNdVKhSFEsOCcpCxDBXJ999/i49Pb0JCtgOQ\nkpLM7NnTC3VvHjnybTp37myKEIUQQvxDxhyatwe2HLq4uDB//vzSiEUIUQbNnTubb78N0Stzc3Nj\n8eJlNGzYqNTjuTcLmnzoVBQxMTFcuRLNu++O4/jxoyQnJxdqxX7hhZeZOHGyiSIUQghRQLqVmjeD\nyWFAQAArV66kc+fORXbZCA0NNWZcQogy4PPP17Nhg37XPRsbW2bMmE3nzl1NEpO0HFY816/HAJCZ\nmcEXX2wstL9hw0YsW7ZauhcKIUQZIEtZmDeDyeH7778PwFdffVVqwQghyo7/+78fCQpaSGZmpq5M\nqVQyevTbDB481GRxKf/pDC+5YcURG3vd4D57e3s++EDW3xVCiLJCupWaN4PJoaurKwBLlixh5cqV\npRaQEML0zp2LZMaM97h9O1GvvH9/X6ZOfd9EUeWTKbIrlvj4eG7cMJwcNm78NO3adSzFiERZI+3F\nQpQtum6l8jltlh44IU2tWrUICQnh8uXLxMTE6P4TQpRPCQkJTJjwNlevRuuVd+nSlRUr1pi86969\nWdDkQ6ciCA8/QlpamsH9ERHH6dPnZX77LbwUoxJCCGHIveEfJg5EFMsDJ6TZu3dvoTKFQsHBgweN\nEpAQwnSys7MZM+ZNzpw5rVfevHkLgoM3GmXJikclLYcVy/nzfz3wmNOnTzFs2GDGj3+XWbOmlUJU\nQgghDCl4iCsT0pinByaHhw4dKo04hBAmlr9kxRgOHw7VK69Tpy5r1qzDxcXFNIH9h0KSwwolNjb2\ngcdUrVqVl1/uSZ8+/UshIlFWyBdPIcomGXNo3gwmh2lpaaxdu5aoqChat27N66+/joXFA3NJIYSZ\nmjdvNjt36i9Z4erqxqJFy2jUqLGJoiqsYEIayQ0rhuvXrxnc5+rqxssvv8q7775HjRo1SzEqIYQQ\nhsis4ubN4JjDwMBAAHx9fbl06RJr1qwprZiEEKVs06bPWL9+nd6TeGtrG6ZPn8Vzz3UzYWSFqWTM\nYYWh1WqJjS08xt3Z2YVBg/zZu/cgS5euksSwopMZaYQoU3TdSmUpC7NksCkwNjaWpUuXAtCpUyeG\nDRtWWjEJIUrRwYM/sXjxPDIzM3RlCoWCkSNHM2TIMNMFZoCMOaw4rl+P4caNG7ptR0cnnn/+RSZM\nmETDho1MGJkQQghDCp7XyENc82QwOfx3F1KVSlWskwcFBXHixAk0Gg2jRo1iz549qNVqAJKTk/Hy\n8mLu3LlA/hPiQYMG0b59e8aNG0dqaiqTJk0iNTUVGxsbli1bhpOTk+7c169fp2fPnnh6egLg7OzM\n6tWrixWnEBXVn3+eY/r097h9+7Zeeb9+PsyYMdtEUd2fQloOK4wjR8LIzMzE3t6e7t1fZPz4iTRp\n4mnqsIQQQtyHblZxeYhrlgwmh/+drv5Rp68PDw/n4sWLbNu2DbVaTZ8+fQgNDdXtnz59OgMGDNBt\n79ixg5ycHN32F198wTPPPMOIESPYtm0b69evZ8qUKXrXqFOnDlu2bHmkuIQQ+W7fvs2ECWO4ciVK\nr7xz5+dYtWqtyZesMERaDiuOixf/pmfP3owbF4CXV0tThyPKGHkHEKJs0q1zaOI4RPEYTA7/+OMP\nunTpotu+ffs2Xbp0QavVolAo9BK9orRu3ZpmzZoB4ODgQEZGBrm5uahUKqKiokhNTdXtT0pKYvfu\n3QwcOJBbt24BcOzYMRYsWADAc889x+jRox/nPoUQ/5Kdnc3o0cM5ffqUXnnz5l5lZskKQ5S6WdBM\nG4cwjvTMHLI1eSgUCqZOnYmlpaWpQxJlXNl8jCVExaUomDhOPqjNksHkcP/+/Y91YpVKhY2NDQAh\nISF06tRJ1z118+bN+Pv7645dsmQJEydO5MqVK7qyxMRE3dT5VapUIT4+vtA1EhMTGT9+PPHx8fj5\n+dGrV6/HilmIikCr1RIQ8A6//PKzXvmTT9Zl9epgqlSpYqLIHk5Bd5XktCwTRyJKilar5UjkLc5G\n3+b38wm6LsO92j9J7451TRydEEKIRyGzlZo3g8lhzZolM/vbgQMHCAkJYePGjUB+i8WJEyd0s6FG\nRESgUqlo2bKlXnL4b0WtZeTk5MSECRPo1asXqampDBgwgDZt2uDu7m4wFmdnGywsijd+UpiGm5u9\nqUMod2bOnMk332zXK3Nzc+OTTz6mU6dnTRTVw4u7k58U2lhbSv0wQ1qtlosxyWRkavjp+FXOX1OT\nqE7XtQRbqBS0alSViD/jSL6bU6y/sdSLisHynwdEVlaVHvpvLnVDGCJ1o+Q43UgFwNbWqlz8XsvD\nPTwKoy5cGBYWRnBwMBs2bMDePv8XGxERoetOCnDw4EHOnj2Lj48PSUlJZGdn4+Hhgbu7OwkJCdjb\n2xMXF1co6bOzs6Nfv34AuLi44OnpSVRU1H2TQ7U63Qh3KYzFzc2ehIRUU4dRrmzevIkVK1bqPXCp\nXNma996bSatW7c3i952VkQ1AnibXLOKtqDS5eeT+k/FdvJ7M0bO30Grh75hk1Kn6rb5VHKwAaN+0\nOt29PdDk5hHxZxyZWTmP/DeW942K487d/PeCrIesJ1I3hCFSN0pWamomAHfuZJr977W81o37JbxG\nSw5TU1MJCgpi06ZNerOMRkZG0rjxvQW1p02bpvt5586dxMbG0rt3b27dusX+/ft5++23+emnn+jY\nsaPe+cPDw/n555+ZPn066enpnD9/njp16hjrdoQwez//fJBFi+aSkXHvIUnBkhWvvz7chJE9GoUM\ndC+TNLl5hJ+LIzNbQ7w6g4Mnrt/3b+RV35Unq9vTsJYTjZ9w1tuX8k+LkPRIEkII83NvbgB5EzdH\nRksO9+7di1qtJiAgQFe2ePFiEhISqF279gNfP2TIEKZMmYKfnx8ODg4sWbIEgPnz5zN06FC8vb3Z\ntWsXvr6+5ObmMnLkSKpWrWqs2xHCrF24cJ5p0yaRmJigV96v3wBmzgw0TVDFVDD5RFHdzYXxpWfm\nEBOfxlcHLuqVx8SnFTq2pqstLg6VAahT3Z7OXvnDFawqKbGpbHjSI3kAIB5JGZ1ZWYiKSpacMm9G\nSw59fX3x9fUtVD5r1iyDr+nbt6/uZ1tbW9auXVvomJkzZ+p+XrRo0WNGKUT5l5SUxNixo4iO1l+y\nolOnLqxcWXaXrDDon3DlI6f0JCRn8FNEDLl5WkL/iNXbZ21loft/bl4evTvUxdWxMvY2lWhU27mo\n0z1Ywd9YvlgIIYTZ0S1lIW/hZsmoYw6FEKaVk5Pzz5IVf+iVN2vWnODgjWa5TIAulZUPnRJ1Nvo2\nO3+JKrIFMLeI6chfbfcE3Vp54Ghb8nVI/sZCCGG+lLKUhVmT5FCIckqr1TJx4lhCQw/plT/xRB1W\nr/4EV1dXE0X2mKTLYbHcuZtNRrZGt33qYiKnLiaiJX+MX5w6Q7evTnV73ZIhBSpXUuHbtQFKpQJ3\nZ2ssVEqjxSrdSsXDkPohRNmkkKUszJokh0KUU4sXzyMkZJteWZUqrixYEMTTT3uaKKrHd69VST50\nHuR2Sia/nI7lWlwaZy7fvu+xlhZKerT2oEUDN+rWcCilCIumkG6lQghhtqRbqXmT5FCIcuh//9tM\ncPBa8vLydGWVK1fmvfdm0KPHCyaM7PEpZMwhABlZGv6OSS70ZHbn4ShS0vKn+E/LyNHbZ2ddiRYN\n7rUYN/Rwon3T6sYP9hHdm3TIpGEIM2Fmo6aFKPd0s5VKt1KzJMmhEOVMaOghFiyYQ3r6Xb3yESNG\n88YbI0wUVclRVNAnkjmaPF230OPn4th68OJ9j6/haouDrSU2Vhb4PFcfK0sVtdxszWQCInOIUQgh\nRFGkW6l5k+RQiHKkYMmKhAT9JSv69OnPrFlzTBRVySrvS1lcup7ChRi1XllWTi77j19Dk1v4nvt3\nqYfqX+MDFUCLhm64OVkbO1SjkW6lQghhvpSylIVZk+RQiHIiOVnNuHGjiYq6rFfeoUMnVq0ywyUr\nDCkn3Uq1Wi1XbqWSnZMLwO8XEoi8fJv45AyDr6nqYoOHmy0ATetVoZ1nNVRK400MYyrSdVg8FPni\nKUSZJGMOzZskh0KUA/lLVrzJqVMn9cqbNm1GcPBGKleubKLISp45LnNw5dYdDp64zr+GgHI5NqXI\nRNDGyoJ6NR3p7l1Lr9zSQklDD6fyk+TfhwL5YiGEEOZKIWMOzZokh0KYOa1Wy6RJ4zl06IBeee3a\nT7Bq1Vrc3d1NFJmR6JY5KJsfOnl5Wo7/FUdmVv74wF8jbxF9847B49s2qYabU37yXsPVlmeeqloq\ncZZpupbDsvk3FmVLBXheIoRZUcqYQ7MmyaEQZu7TT9eyfftWvTJnZxcWLAjC07OZiaIynrLScph0\nJ5Mvf/obdVqWXvmtpHSysnMLHd+xWXV6ta+jV2ZtpcKmciWjxmmOdEMo5XuFEEKYnYIxh5IbmidJ\nDoUwc4MHv87Ro0fYt28PkL9kxdSpM3j++ZdMHJlxmCJv+OuqmpMX7k3yc/tOJqcuJeq2rSqp9I63\nt6lEz3ZP4mBrCeQvGeFkZ1U6wZYLBa3DQgghzI1uKQvJDs2SJIdCmDk7Ozs+//xLZsyYwv/+t5nh\nw0cyfPhIU4dlNPeWsjDOh05CcgZ7jl4h4ny8brxEtiavyGNrutnyro8XzvaS+JUkma1UPAypHUKU\nTbrPaRlzaJYkORSiHFAqlSxatIwOHTrzyis9TR2OUT3OTJaHTl7nxIWE+x7z19V7y0h4uNthocq/\nYEMPJ9p73lswvlIlJe5O1hVigpjSdi85NG0cQgghHp0sZWHeJDkUohx59dVepg6h9DzCZ07SnUy+\nDYviSOSthzretrIFEwY0p35Nx2IGJx6HAkm4hRDCXN3rVmraOETxSHIohDArBS11kVG3Cf7uLBdi\nkh+YKKbczQbyl4N4u09TPOu43Pd4pVKSE5OSbqVCCGG2pFupeZPkUAhhlu5mavjtr3iA/O6d90no\nKltZgFbLrNe9ZXZQM6CbdEi+V4j7kPohRNkkS1mYN0kOhRBmxc7agiqOlbGqpKK9ZzWeqGbP00/e\nvyVQmBfdU2cTxyGEEOLRyVIW5k1p6gCE6XTo4E18fFypXjMhIZ4hQ3xK7Hx5eXmsX/8Jgwf3x8+v\nHz4+r7F69TI0Gk2JXaMkde78LDdv3nik10yY8DZ79+4GYP78QN3PFVUlCxWfvf8880Y8y0ttnpDE\nsJxSgHyzEA9FJoUSomyRpSzMmySHolS5ubmzZcv2Ejvf99/v5MyZU6xfv5mvvvqGTZu+4q+//mTr\n1i9L7Bqi7FEV0YX0l19+NkEkwmgU0nIohBDmqOCBTZ6MOTRL0q1UFJKZmcmCBXO4ePECGo2Gzp27\nMnZsAN98s53jx48SFLQSyG+1e+21F1m+/CMcHZ1YunQR165dBWDChEm0bduemzdvMHr0cLp168Hf\nf19g5sxABg7swy+/HGfv3t0cPfortra2nD59CgsLFR9+uIi6detx8+YN3nprKsnJKTzzTBsSEuLp\n0qUbL7+sv0zD5cuXqVu3HjY2NgDY2NiyaNEyKleuDED//j2ZNWsuzZt7Fdret28PX3yxEYAmTZow\ndeosLC0tDZaHhYWyfv0nZGRkUqtWLWbPno+TkxPZ2dmsXbuK8PBjaDQ59OrVh6FDhwNw7NgRVq5c\ngoWFBa+8oj+T6Hff7WTbtv+RnZ1NkyZNmTHjA6ysKhMbe53AwJmkpCTTpElTcnPLZitoWZKTk8N7\n701k+vRZ9O7dz9ThiBKgQCHJoRBCmKF7S1mYOBBRLNJyKAr59tsQ0tPv8tVX3/DZZ1+yb99uTp8+\nRdeu3TlxIoKUlGQAIiNPY29vT4MGjZg/P5AGDRry9dc7Wbp0FXPnfqA7LiUlmQYNGrFmzaeFrhUe\nfoQ+fQbw9dc7adHCmx07tgLw8ccrad++PTt2fM+zz7bj999/KzLWNm3a8d13O1m5ciknT/5OVlYW\njo5OWFlVvu893rx5g48/XsWaNevYuvUbMjIyCQn52mB5bOx15s6dTWDgfHbs+I6WLb1ZunQBAF99\ntZno6Gg2b/6aLVu2Exp6kCNHwsjNzWXRorlMmjSN//0vBIVCSW5uLgCnT//Bhg3BrF4dTEjIbuzs\n7Fi/PhiA4OA1eHs/w/bt3zFgwEAiI08X469Ysezbt4fo6CgWLZpHbOx1U4cjSoBCIbOVCiGEOVLK\njNNmTZJDUcigQf4sWrQchUKBg4MDderU48aN6zg7u9C8eQt+/vkgAIcP/0y3bs+TkZHByZO/4+vr\nB0CtWh40b+7F0aO/AqDRaOjUqUuR13ryybo0bvwUAI0aNSIuLn8dutOnT/Hqq68C0KlTF6pUcSvy\n9e3bd2TJklUkJMQxffokXn65K/PnB3Lnzp373uNvv4XTtGkzXF3dUCgUzJ49Dx8fP4Plx48fo0WL\nltStWx+A117rx6+/HiY3N5cjRw7Tt29/LC0tsba25sUXX+GXXw5x/XoM2dnZPPNMGwBefvlV3fWP\nHDlMt249cHXNv6/evfvpukWePv0HXbv2AODppz154okn73sv4l6X0qioy0yZMpG8vDwTRyQel0LB\nY/UrjVens/3QJUJCL5OSllVicQkhhLg/6VZq3ozarTQoKIgTJ06g0WgYNWoUe/bsQa1WA5CcnIyX\nlxdz584F8p8uDBo0iPbt2zNu3DhSU1OZNGkSqamp2NjYsGzZMpycnPTOv2HDBvbv349CoWDs2LF0\n7tzZmLdTYcTEXOOjj1Zw7doVlEol8fFxuu6c3bu/wN69u+ndux9hYb+wePEK7t5NQ6vVMnr0cN05\nMjIyaNmyNQAqlQpbW7sir/XvcqVSRW5u/pf61NQ7ODreW4Dcza3o5BCgdetnad36WXJzc4mMwyp0\ntQAAIABJREFUPM3HH69k2bJFzJmzwOBrUlKSsbOz121bWVndtzwtLZXTp//Az+9el0U7Ozvu3Ekh\nNTWN1auXs27dx0B+F8ennmrCnTsp2Nra6o63t3fQ/ZyamkZY2M/89ls4kP8GqtHkAHDnTgp2dnZF\nvk4UptVqOXnyhG77wIEfWbZsMVOmTDdhVOLxGe5WmpWdy9noJN1kB0l3Mjnwewx3MzUoFAq0Wi2Z\n2bm64+2sK/His7VLIWZhCjIdjRBly72lLEwciCgWoyWH4eHhXLx4kW3btqFWq+nTpw+hoaG6/dOn\nT2fAgAG67R07dpCTk6Pb/uKLL3jmmWcYMWIE27ZtY/369UyZMkW3PyYmhr179/L111+TlpaGn58f\nHTp0QKVSGeuWKozlyxfTqNFTLFy4FJVKxZgx95K+Tp2eY/nyxRw79iuVK1emTp26aDQaVCoVGzZs\n0Y39K/CoM3MWsLW1JT09HUfH/ETt9u3EIo87duwITZs2x87ODpVKhZdXS15/fQTr1q0BQKlUkpd3\n70tiamp+i6KjoxNnz57Rld+9m6brklpUuaurG97ezzBvXlChGFxdXRk0aAjt23fUK79yJZq7d+/q\ntpOT1XqvefHFVxk7NqDQ+eztHUhLSyvydTNnBhb5e6jIwsOPcuHCX3plGzaso337jrRr18FEUYnH\npVRAjiaP05cSOXQyVm/Wu4vXk8nO0W8dtrJUUdXZGgsLFRpN/r/5W0npZOfkka3JRZSe7Jxc0jJy\nCpWrVEocbS1NEJEQojQp/+mXKLOVmiejJYetW7emWbNmADg4OJCRkUFubi4qlYqoqChSU1N1+5OS\nkti9ezcDBw7k1q38boXHjh1jwYL8lp/nnnuO0aNH653/+PHjdOzYEUtLS1xcXKhZsyaXLl2iUaNG\nxrqlCkOtVtOgQSNUKhUREeHExMSQkZEO5LeWPftsW5YtW8yrr74GgIWFBW3btmfXrm/w8xtCZmYm\ny5cv5s03RxU7hqeeasK+ffsYOHAYR46EkZiYUORxISHb+PXXXxg/fhJWVlZkZWURGnoQL69WAFSp\n4sqlSxdp0aIVBw/+RHZ2NgBt27bnk08+4ubNG1SrVp0lSxZSt249XnzxlSLLX365F5988hGxsdep\nWbMWf/55lp9+2k9AwGQ6duzMnj27aNOmHUqlki+++IzGjZ/G2/sZVCoVJ0/+TsuW3vzww25dV4sO\nHTrz/vtTGTz4dZydnQkLC+Xq1Sv4+w/D07Mphw//TIMGDYmMPM316zHF/j1WBPv3/1Bo6RK1OokP\nPpjOrl179VqChflQKhXExKexKuRMkfsdbC15pe0TKBUKVEoFXg1ccbKzws3NnoSEVAAuXFOz+Ks/\n+OuKWlbFKCWa3Dx+OHbV4P5abra0auRe5D7LSko6N6+JTWWZK08Ic6Zbq1beeM2S0d6BVSqVrhUp\nJCSETp066Vr1Nm/ejL+/v+7YJUuWMHHiRK5cuaIrS0xMxMUlf/2yKlWqEB8fr3f+f+8HcHFxISEh\n4b7JobOzDRYW0rL4bwEBY/RaW+fNm8e4ce+wcOFCvvxyI926dWP8+HGsXr2a1q1b0KpVK/r27c2E\nCRMYMKAPbm75X7wXLJjH7NmzGTIkvzW4V69eeHo24Pr1/MlBCo7LyrLVbdvbV8bSUqXb9+/tmTOn\nM2nSJH744Qc6depEixYtcHCw1h1b4KOPVrJkyRKGD/dDoVCQm5tLt27dmDBhAjY2NkyYMI7Zs2ez\nd+93vPDCC9SvXx8nJ2uaNKnPvHlzmTjxbVQqFU2bNmXs2NFYWVkZLJ8/fx4ffDCVnJwcbG1tmTFj\nBm5u9owcOZygoESGDRuIVqvF09OTt98eia2tLfPnz2PhwnlYWlrSt29fbGxscHGxpVmzRrzzzhgm\nThxDXl4eVapUYc6cOXr3fuDAfpo3b0779u2xt6+Mm5s97733Hj169KBHjx7GrRhmoKAuREaeKnL/\nmTOn+eCDqWzZsqU0wxIlZHgvT/6Mug1AdVdb+ndtwL+Xs7NQKQ2ub6d7v/nne8mFmGQuxCQbNV6h\nr7Klijae1XXbmdkaws/e4nrCXa4nRBt8XVVXO15o8+RDXUNRKf8rjJVVpUKfDYY87HGi4pG6UXJy\n/+lPamGhKhe/1/JwD49CoTVyWn/gwAHWrVvHxo0bsbe3Jzs7m379+rF7d/5C3hEREXz33XfMmzeP\nnTt3Ehsby7hx43jhhRcICQnB3t4ejUZDly5d+PXXX3XnDQ4Oxtramtdffx2AyZMn07t3bzp0MNyN\nrOBpsng8f/55lhUrgli/frNRr+PqakdiYn73yhEjhvL668Pp2LGLUa8pzENB61BU1GW6du1Aevrd\nIo+rVKkS8+cHMWzYm6UcoTCVf7ccAsQmpHEnvXAXR2E8KqWCujUcsFDpz3kXn5zB7ZTMIl9zMSaZ\nXb9GM6hbA3q09nio6yTdyWTy2qO0eboqI3s1eeDx/60bQhSQulGytFotby7+mYYeTkwb3NLU4TyW\n8lo37pfwGrXvRlhYGMHBwWzYsAF7+/wgIiIidN1JAQ4ePMjZs2fx8fEhKSmJ7OxsPDw8cHd3JyEh\nAXt7e+Li4nB31++G4u7uTnT0vaePRR0jSp5Go2HTpg307z/QqNf5+ONVgIZ33pnE1atXuHo1mkaN\nnjLqNYX5CQnZZjAxhPzJgVatWkbbtu1p1KhxKUYmyoqabnbUNHUQAgB3J2vcnayL3JeRld81vFjP\nq2VGGiHKFIVCIcsRmTGjLWWRmppKUFAQ69at05tlNDIyksaN731JmzZtGrt27WL79u28/fbbDBgw\ngN69e9O+fXv2798PwE8//UTHjvqTfbRp04bQ0FCys7OJi4sjPj6e+vXrG+t2BPD33+fx9e1NlSpu\nPP/8S0a9lq/vYK5cuYKvb2+mTXuXd9+dirt7VaNeU5ifkyd/f+AxsbHXmTZtkt6EV0KIskVmNxSi\nfFEqFDIhjZkyWsvh3r17UavVBATcm41x8eLFJCQkULv2g6cUHzJkCFOmTMHPzw8HBweWLFkCwPz5\n8xk6dCgeHh74+Pjg7++PQqEgMDAQpVKWbTSmhg0b8803e0rlWq6urmzatKlcNuWLkqFWJ3H6dNHj\nDQtYWFhQrVoNsrOz+PHHfbz6aq9Sik4I8SgUsmi2EOWKQqFAlhw2T0ZLDn19ffH19S1UPmvWLIOv\n6du3r+5nW1tb1q5dW+iYmTNn6n4eMmQIQ4YMecxIhRDmaPv2rbolTiwtLbG0tCIt7d7DhOee68aC\nBUt48sk6ssSNEGWcUlnQcijJoRDlgVIp/57NlTS1CSHMUqVKlkycOIVVq9by668R9Oz5mt5+jUZD\nvXr1JTEUwgw8TrdSGXIoRNmjUCikJ4CZksWEhBBmafjwt/S2a9XSn+Hwxo1YtFqtweUOhBBlh65b\nqQw6FKJcyMrO5VpcGut3n8PR1gp3F2u6eMn0YOZAkkMhRLnQoEFDve0bN24QF3eLatWqG3iFEKKs\nuNdyKMmhEOXJsXNxup9bNnDDwdbShNGIhyHdSoUQ5ULbtu2xtrbRbWdkpBMeftSEEQkhHlZBy+Gj\nNBxKHilE2fVSm8KTT2pyZYYacyDJoRCiXHB3r0qNGjX0yv7++4KJohFCPIqCCWlkjJIQ5cOALvWZ\n5OulV5Yn3cbNgiSHQohyQaFQULNmLb2yGzdiTRSNEOJRKB6rW6mMKxaiTPrPP01pNzQPkhwKIcqN\nGjX0k8PY2OsmikQI8SgKxhxKw6EQ5ZdMOGUeZEIaIUS5UbOm/kxosbHXZcZSIcyAbsyhfHkUotz4\n7yfv//0eQ6fmNYhNvEtGlgbPulW4cFUNCniqtjNnom6jVCqoU82BS7Ep2FlXoopDZa7GpVLT1Zbk\ntCzSszS0aOBGXFI6sYl3aejhhIVKwZ9X1DSq7UQtNzuT3Gt5IsmhEKLcqF+/gd72jRs3iI+Pp2rV\nqiaKSAjxMIrTcqhFEkkhyrL/JoeHTsZy6OTjD/f48qe/De6r7X4vOXSyt+KdPp5UspD1jh+FdCsV\nQpQbbdu2p3Jla912evpdjh+XGUuFKOvuzVYqCZ8Q5UV1V1vcnCpjZ10JJztLrCqpsLZSofpnAipr\nq3tJm7WVCmd7KwAqW+aXW6iUWFtZ/LPfAguVUnesbWUL3c8OtpZYWaqwtrIgISWDhJQMYhPvcuby\nbW7eTi+1+y0vpOVQCFFuVK9egxo1qhMVFaUrkxlLhSj7CmYrLU5yKL3GhSibnOysWDy6nUmu/dWB\nvznwu8w7UBzSciiEKDcUCkWhSWlkxlIhyj6FTEgjhChBCuQ9pbgkORRClCv/Xc4iNlaSQyHKOqVM\nSCOEKEEFPQpkbPKjk+RQCFGu1Kr13+QwxkSRCCEeVkG3Uu2jzUgjhBD3JS2Hj06SQyFEufLkk3X1\ntm/ciCUhIcFE0QghHkZBt1KZkEYIURJkLHLxSXIohChX2rZtj5WVlW47LS2NiIjjJoxICPEgBd1K\ni5MbyndAIcR/yZjD4pPkUAhRrnh41KZ69Rp6ZefP/2WiaIQQD0MpLYdCiJIkYw6LTZJDIUS5olAo\nipiURsYdClGWyWylQoiSpOtRIO8pj0ySQyFEuVOzZk297dhYWetIiLKsOLOVync+IYRBupZD8agk\nORRClDuy1qEQ5kXxT3YYcT6ezGzNI77YCAEJIcyaQrLDYpPkUAhR7jz5ZB297Zs3b6BWJ5koGiHE\ng9hWttD9fPVWqgkjEUKUB7LOYfFZPPiQ4gsKCuLEiRNoNBpGjRrFnj17UKvVACQnJ+Pl5cWcOXP4\n8MMPuXDhAhqNBh8fHwYMGEBCQgLTpk0jMzOTKlWqsHDhQmxtbXXnvn79Oj179sTT0xMAZ2dnVq9e\nbczbEUKYiXbtOmBpaUl2djYAKSkpRET8xvPPv2jiyIQQRVEplQx4rh47fr5MRlauqcMRQpQTMo75\n0RktOQwPD+fixYts27YNtVpNnz59CA0N1e2fPn06AwYM4OTJk1hYWLB161bu3r1L9+7d6devH+vW\nraNbt274+fmxa9cutmzZwujRo/WuUadOHbZs2WKsWxBCmKnatZ+gWrUaXLt2RVf2559nJTkUogyz\ntsr/SpLxEN1K1alZqFOzjB2SEMJMyTqHxWe05LB169Y0a9YMAAcHBzIyMsjNzUWlUhEVFUVqaqpu\nv7e3NwBJSUk4OjqiVCq5evUqvXv3BqBjx44EBAQUSg6FEKIoSqWSGjVq6iWHMimNEGWbtWX+V5Lj\nf8Zx63a6weP+7/cYMrPvtS4q5VugEKKQghmQpenwURktOVSpVNjY2AAQEhJCp06dUKlUAGzevBl/\nf3+948ePH8/JkydZsmQJAA0bNiQ0NBRPT0/CwsK4fft2oWskJiYyfvx44uPj8fPzo1evXsa6HSGE\nmalVS2YsFcKcuDpVBuDM5ducuVz4M/+/vBu7U7mSiq4taz3wWCFExVIwA/KanZFYWBR/ihWVUkHu\nQ86i/ELr2rz4bO1iX6usMOqYQ4ADBw4QEhLCxo0bAcjOzubEiRMEBgbqHbd69WpiY2N58803CQkJ\nYdSoUQQGBuLv70/nzp0LZf5OTk5MmDCBXr16kZqayoABA2jTpg3u7u4GY3F2tsHCQlXi9yiMx83N\n3tQhiDLqQXWjQYN6ettxcTelPlUQ8nc2T66udnw02YG09Oz7Hrf9wN9YVlIxfdgzqJSP1moodUMY\nInWjfGnnVYvTl2+To8krlevdSLzLn9fUDHm1Salcz5iMmhyGhYURHBzMhg0bsLfP/0cXERGh604K\ncPnyZQDq1atHzZo18fDwICoqimbNmrF8+XIAoqKiCA8P1zu3nZ0d/fr1A8DFxQVPT0+ioqLumxyq\n1Ya7qYiyx83NnoQEmbVOFPYwdcPNrYbedkzMdS5disHR0cmYoQkTk/cN82ZrocDWweq+x4zr2xSA\npNtpj3RuqRvCEKkb5Y+7vSWzh7V+7PM8bN0YvugQ2dm5ZlOP7vcwxGhLWaSmphIUFMS6detwcrr3\nZSwyMpLGjRvrtqOionRJYEZGBtHR0dSqVYvt27ezdetWAHbu3EnXrl31zh8eHs7ChQsBSE9P5/z5\n89Spoz99vRCi4mrTph0WFveefyUnqzlxIsKEEQkhhBCiPFIoys/4RqMlh3v37kWtVhMQEMCQIUMY\nMmQIN27cICEhgSpVquiO6969O9WqVWPgwIEMHjyYkSNH4uLiQrdu3dizZw8+Pj7cvHkTHx8fAObP\nn09MTAze3t6kpKTg6+vL0KFDGTlyJFWrVjXW7QghzEydOnWpVk2/9TAyMtJE0QghhBCivFKgKDcr\nKiq05SXNfQjm0tQr8kk3D2HIw9aNnj1f4PjxY7i5uVOjRg369vVhzJixpRChMBV53xCGSN0Qhkjd\nEIY8bN14K+hnnqxuz8wh3qUQ1eO7X7dSo09II4QQpjJ+/Ls4OTnh6dkMa2trU4cjhBBCiHJIoVBQ\nXpoOJTkUQpRbPXq8YOoQhBBCCFHOKRTwkCtelHlGG3MohBBCCCGEEOWdTEgjhBBCCCGEEKJcTUgj\nyaEQQgghhBBCFJO0HAohhBnq0MEbX9/e+Pn1Y+DAvowYMZTff/8NgJMnf8fXt7fRY5g/P5BXX+2O\nn18//Pz6MXSoLz/9tF+3f+zYkfz4494iY4+Pj2Pfvj34+/ug0Wj09k+c+A6ff76+yGv+9dc5Jk58\nh4ED+zBwYF/Gjh3JyZO/P3TMmzZtYP78wIc+vqQcP36MW7duFSovrb+VIX/+eZZ335VZb4UQQuRT\nKJAJaYQQwhx99NE63N3z10Q9c+YUU6e+y1dffVOqMfTvP5Bhw0YAEBV1iREjXsfbuzUuLlUe8Ep4\n8cVX2L17Fzt37sDHZxAAhw+HcvPmDRYvXlHo+EuXLjJ58njee+99Ond+DoATJyKYPXsGs2fPw9v7\nmRK8s5K1bdtXvP76m1SrVs3Uoeh5+mlPli9fY+owhBBClBEKFOVmQhpJDoUQFVazZl7UqlWLc+fO\nYGNjqyvPzMxkwYI5XLx4AY1GQ+fOXRk7NgCA2NjrLFgwh8TEBOztHZgyZQaNGjUmPj6OpUsXce3a\nVQAmTJhE27btHxhD3br1cXBwIC7u1kMlhwqFgnffnUpAwBh69HgRW1tb1qxZwbvvTsXS0rLQ8Zs2\nbeC11/rpEkOAVq1aM2zYm2zYEIy39zN89tk6EhMTuHTpb3r0eJHXXuvL/PlzOHcukurVa1C79hO6\n1xq6z5s3bzB69HC6devB339fYM2aT/n007X8/PMBtFpwd3fngw/m4urqphdfUtJt5s0L5NatG+Tk\n5NCvnw8DB/qzfv0nnDjxG1evRvP22+Pp1u35In8fWVlZrF69jJMnf0epVNK163MMGzaaBQsC8fJq\nRc+evUlKuk2vXi+wYsUaWrduw4UL51mwIJAvvvha71wdOngzYcJkfvjhexITExgxYhS9e/fn5Mnf\n+fTTtbi5uWNhYUHPnr1ZvHge27btIisrk6CgBZw5cwpLS0uGDh3OCy+8THZ2NmvXriI8/BgaTQ69\nevVh6NDhD/z7CiGEMD8KBZSXpkNJDoUQFZpGo6FSJf2k6ttvQ0hPv8tXX31Damoqgwb1oWPHLjRv\n7kVQ0AK6d3+BPn36c/hwKHPnfsCXX25n/vxAPD2bERS0guvXYxg5chhbt36Do6PTfa9/7NgRKlWy\npF69Bg8dc/36Deje/UU+/XQt1apVo0GDhrRp067IY0+dOsnAgf6Fytu378Tq1cvJysrSxbFp01ac\nnJzYuXMHSUm32bZtF3fvpjFixFC8vFoCGLxPgJSUZBo0aMT48ZOIirrMoUMH+PLL7VhYWBAS8jUR\nEcd56aVX9eL44ovPqFGjBsuXf0Rs7HX8/Qfw3HPdeeutMfz4415mzZpL8+ZeBn8X27dvJT4+ji1b\ntpObqyEgYAy1av1IixbeREaepmfP3pw69QdNmjTlzJnTtG7dhtOn/6BVq9ZFnu/69Wts2vQV165d\nYdgwP557rjsAf/99gbfeGkOrVq31uuRu3folGk0OO3Z8T3x8HEOH+tKqVWv27PmO6OhoNm/+mtzc\nXN55ZwT16jWgffuOBu9FCCGEeVIoFJSTIYcy5lAIUXEdO3aEpKTbNG3aXK980CB/Fi1ajkKhwMHB\ngTp16nHjxnWysrL444/f6d49f/3Ejh078+mnm8jIyPhnHJwfALVqedC8uRdHj/5a5HVDQr7Gz68f\nffu+wvvvv8eQIcOKbPW7nxEjRnPs2K/s2LGV8eMnGTwuNfUOzs7OhcqdnV3Izc3l7t00IL+rpJNT\nfiJ7+vRJOnV6DgsLCxwdnWjXrgPAA+9To9HQqVMXAOzt7UlOVvPTT/u4c+cO/fsPLJQYAgQETCEg\nYAoANWvWwsWlCjdv3njo38OxY7/Sq1cfLCwssLKqTM+ePfntt3BatvTm3LlIAM6c+YPevfsRGXn6\nn+1TtGpVdHfaV17pBUDt2k/i4fEEf/55DgArK6siE8rw8KN065ZfH9zdq7Jz515cXd04cuQwffv2\nx9LSEmtra1588RV++eXQQ9+XEEII85G/zmH5yA6l5VAIUaGMGzcKlUpFXp6W6tWrs3TpamxsbPSO\niYm5xkcfreDatSsolUri4+N4+eWepKbeIS8vDzs7OyD/SaGNjQ2JiQlotVpGj77XbTAjI4OWLYtu\nnfr3mEO1Ws3s2dN1XSqVSiV5eXl6x+fm5gKgVKp0ZXZ2drz00qskJMRTtarhMXmOjk4kJiZQs2Yt\nvXK1OgmVSoW9vQMADg4Oun137tzR3SOAvb0D6enp3L2bdt/7VKlU2Nrmv87NzZ0FC5awdesWVqxY\ngpdXCyZPnl4o1r/+Ose6dR8TF3cLpVLJ7duJhe7/fpKT1bp7yL9fR9RqNTVq1CQrK4vU1FQiI88w\ncuQ7/O9/m8nNzeXPP88yY8YHRZ7PwcHxX/dtT2pqKlZWVnq/H/3rJ+v9rgrqUmpqGqtXL2fduo8B\nyMnJ4amnmjz0fQkhhDAfClMHUIIkORRCVCj/npDGkOXLF9Oo0VMsXLgUlUrFmDH5yZCDgyMKhYKU\nlBScnJzQarXExl6nWrXqqFQqNmzYUijRfBBnZ2e6du3OkSNh9Ovng4tLFW7duql3TEzMNaysrHQt\newUsLCywsLj/23ibNu04fPhnmjdvoVd+5MhhmjdvQaVKlQq9xt7egbS0NN12crIaACcnZ4P3WVRr\nX8uW3rRs6U1GRgYff7yS4OA1zJ49T++YDz/8AF9fP3r37odCoaB375fuez//5eJShZSUlH/FmoyL\niwsALVq04vjxo0B+0lavXj1++eVn3N2r6o0x/bfk5GSqVasO5Le6GkoKCzg5OZGSkqzbjo+Pw8HB\nEVdXVwYNGiLdSIUQogJQKMrPhDTSrVQIIf5DrVbToEEjVCoVERHhxMTEkJGRjqWlJa1bt2Hv3t1A\n/lILkydPwMLCgrZt27NrV/7Yu4IJbeLiCi/D8F/Z2dkcO3aEOnXqAvDaa33ZvXsXN27EAnD3bhqf\nfLKa/v0HPjARLMobb7zF/v0/6C2X8ccfJ9i8+XPeemtMka/x9GzKkSOHyc3NJTk5mWPHjgA80n3+\n9ls4y5YtJi8vD2tra+rXb4BCUfjZanJyEo0aNUahULBv3x4yMzPIyMjQXS8tLfW+99euXQd++OE7\ncnNzycjI4LvvvqNt2/xusC1atGL79q14ejYFoEmTZmzb9j+D4w0BDhz4EYArV6KJiYnh6ac973v9\n9u07sX//D2i1Wm7fTmT48MEkJyfTsWNn9uzZRW5uLlqtlk2bNhAefvS+5xJCCGGmFFBeBh1Ky6EQ\nQvzH668P56OPVrBp03o6duzCG2+8xWefraNBg0ZMm/Y+H344i2+/DcHBwYHAwPyWsMmTpxMUtIA9\ne3YB8PzzLxns7hkS8jU//bQPyO8y+swzbRkxIj9Ra9GiFePHv8usWdPIzMxAoVDQrdvzDBnyRrHu\npXr1Gixf/jHr1q3hs8+CUSiUuLq68uGHiwqNtSzQs2cfTp36Ax+f16hWrTqdOj2nS9IM3ed/Ww6b\nN2/BgQM/MmhQXypVssTZ2Zlp02YVutaIEaOZMWMKjo6O9OrVl169+hIUNI+1az+jS5duBAbO4M03\nRxU5qQ5Av36+3LgRy5AhPigUCl555WW6ds2fRKZlS2/mzw9kwICBADRt2ozVq5cxatQ7Bn9fzs7O\nDBvmR2JiPAEBkx/Ycujr60dsbAz9+r1K5cqVeeedAKpVq0bfvj7cvHmTIUN80Gq1NG78ND4+fvc9\nlxBCCPOkLEcT0ii02vJyKw+WkHD/J9CibHFzs5e/mSiS1A1hyOPUjQ4dvNm584cHdjsW5kneN4Qh\nUjeEIQ9bNyZ9fASVUkHQmKJnDi9r3NzsDe6TbqVCCCGEEEIIUUzKcjQjjSSHQgghhBBCCFFsCspL\nZ0wZcyiEEEIAv/76+4MPEkIIIf4jf51DU0dRMqTlUAghhBBCCCGKqTxNSCPJoRBCCCGEEEIUl4Jy\n061UkkMhhBBCCCGEKCaFtBwKIYQQQgghhFBQfloOjTohTVBQECdOnECj0TBq1Cj27NmDWq0GIDk5\nGS8vL+bMmcOHH37IhQsX0Gg0+Pj4MGDAABISEpg2bRqZmZlUqVKFhQsXYmtrq3f+DRs2sH//fhQK\nBWPHjqVz587GvB0hhBBCCCGE0KNQQPlIDY2YHIaHh3Px4kW2bduGWq2mT58+hIaG6vZPnz6dAQMG\ncPLkSSwsLNi6dSt3796le/fu9OvXj3Xr1tGtWzf8/PzYtWsXW7ZsYfTo0brXx8TEsHfvXr7++mvS\n0tLw8/OjQ4cOqFQqY92SEEIIIYQQQugpT91KjZYctm7dmmbNmgHg4OBARkYGubm5qFQqoqKiSE1N\n1e339vYGICkpCUdHR5RKJVevXqV3794AdOzYkYCAAL3k8Pjx43Ts2BFLS0tcXFyoWbM/vizLAAAQ\nvklEQVQmly5dolGjRsa6JSGEEEIIIYTQo9VqScvIIWB12CO/1qOqPe/6NEehUBghskdntORQpVJh\nY2MDQEhICJ06ddK16m3evBl/f3+948ePH8/JkydZsmQJAA0bNiQ0NBRPT0/CwsK4ffu23vGJiYm4\nuLjotl1cXEhISJDkUAghhBBCCFFq0rM0AGRp8nCxt3ro1yXdyeJcdBLZOXlYWZaN3o9GHXMIcODA\nAUJCQti4cSMA2dnZnDhxgsDAQL3jVq9eTWxsLG+++SYhISGMGjWKwMBA/P396dy58wMHeT7MIFA3\nN/ti34cwDfmbCUOkbghDpG4IQ6RuCEOkbghDHqZufDnnpVKIpHQYNTkMCwsjODiYDRs2YG+f/4uN\niIjQdScFuHz5MgD16tWjZs2aeHh4EBUVRbNmzVi+fDkAUVFRhIeH653b3d2d6Oho3XZcXBzu7u7G\nvB0hhBBCCCGEKLeMtpRFamoqQUFBrFu3DicnJ115ZGQkjRs31m1HRUXpksCMjAyio6OpVasW27dv\nZ+vWrQDs3LmTrl276p2/TZs2hIaGkp2dTVxcHPHx8dSvX99YtyOEEEIIIYQQ5ZrRWg737t2LWq0m\nICBAV7Z48WISEhKoXbu2rqx79+6Eh4czcOBAsrOzGTlyJC4uLnTr1o3x48fz7bff4uHhwYQJEwCY\nP38+Q4cOxcPDAx8fH/z9/VEoFAQGBqJUyrKNQgghhBBCCFEcCm15WbFRCCGEEEIIIUSxSVObEEII\nIYQQQghJDoUQQgghhBBCSHIoTCg5OdnUIYgySuqGMETqhjBE6oa4H6kfwhCpG/pUgf9dcFAII4uJ\niWHZsmV8//33ZGdnU61aNaytrU0dligDpG4IQ6RuCEOkboj7kfohDJG6UTRpORSlKjU1lblz5/LU\nU08xfPhwzpw5o1vrUlRsUjeEIVI3hCFSN8T9pKam8uGHH0r9EIVI3TBMkkNRKuLi4gCIj49HqVQy\naNAgWrduTUpKCm5ubrrjZPLciicnJwfIX/PU0tJS6obQuXLlCunp6SQmJsr7htATExNDZmam1A1R\npNOnT5OSksLNmzepVKmS1A+hc+DAAc6fP09cXJx85zBAlrIQRnX+/Hnmz59PlSpVsLW1Zd68eQwf\nPhxPT08OHjyIvb09DRo0oG7dugwfPtzU4YpSdPPmTRYuXEjPnj3p0aMHAH5+fnh7e3Pw4EHs7Oyk\nblRQf//9N3PnzsXe3p6srCw2bNjAiBEjaNy4MaGhoVI3KrCzZ8+ycuVKrKysyM3NJTg4mOHDh/P0\n00/z888/S90QHDt2jAkTJrBgwQK6d+/OkCFD8PLy4tChQ1I/KrDff/+drVu3otVqee+996hWrRqD\nBw+mVatW8p3jP2TMoTAarVbLihUr6NGjBwEBAezZs4dLly4xa9YssrOzsbGxYfny5Tg6OnL06FEs\nLS154oknTB22KCVnz57lwIEDuLi44OTkhIuLCy+88AI5OTnY2tpK3ajAVqxYQdeuXZk8eTL79u0j\nOjqaBQsWcPfuXezs7KRuVFDZ2dnMmTOHl19+mUmTJrF7925sbGx45513yMzMlPcNAeQ/eLxw4QIO\nDg5Ur14df39/ee+o4P744w9GjBiBn58fEydOxM7ODoCXXnqJrKwsee/4D+lWKkpcXl4eWq0WhUKB\njY0NlpaWAMyePZvw8HAiIyM5duwYlStXBqB58+Y4OTnptkX5lZeXp/s5Ojqa9u3bo1arOX36NAB2\ndnb8+uuvUjcqoIL3jaysLCwtLalZsyYAI0aM4Nq1awAcOXJE6kYFVPC+oVar8fLyonv37uTl5eHo\n6Ej16tVRqVRERkbqPmukblQsBfWjoCNcbm4uzs7OAISHh6NSqYiIiMDGxgaQ+lGRFNSN6tWr4+vr\nS6VKlQDYvHkzYWFh5OXlcebMGaysrACpGwUkORQlSqvVolQqUSgUaDQaqlSpQkZGBnfu3MHJyen/\n27vfmKrqB47jb+AKGn9F4DJKIxQm0OUCt9SJsACzGEbRhJw9YM620gdmGpvMavqgtnRp5qgWWw0k\npwTLZWJlsMmw/43UptMUVApNJiT/0gvc+3tg3h+uDiGpFy+f1yMVuPse9r7n+L3ne87h0Ucf5ZNP\nPmHJkiVUVFTQ0tLCwYMHaWpqcu24xTNda+OawsJCnn/+eWJjY2lubnZNEAsLC9m+fTunT59WG+PE\n0P2Gn58fxcXFzJ49G4Bjx44RFhYGwFNPPaU2xpmh+42wsDCKiooICAhg06ZNnDt3jp07d7J27Vpy\nc3OprKzUMWWcGdqHl5cXcPWxBPn5+cydO5ezZ8/y6aefYrVaqaio0L5jHBnaRmRkJFlZWVRXV7Ns\n2TLOnDlDbW0tL7/8MtnZ2Wzfvl37jiG0rFT+s+bmZrZs2UJmZqZr5/zmm28SHBzMxIkT+eGHH4iK\nisJsNpOUlMTrr79Obm4usbGx1NXV0dDQwJo1a7BYLG7eErnZ/qmNt956C6fTybRp0wAIDQ3lyJEj\ndHV1YbFYMJvNmEwmGhsbOXDgAC+++KLa8EBGbTgcDu677z7X99XV1TFr1iyio6MJDw9nwoQJasPD\nGbUBuNqw2WwUFhaSmZlJaWkpGRkZWCwW9u/fr2OKhzPqY3BwkKlTp/LLL7/Q29tLeHg4ZWVlNDY2\nsmbNGiIiIqivr1cfHuyf2ti6dSsmk4n4+Hh6e3uJiopi9erVzJ8/n/LyctLS0rBYLHz55Zdq4y8m\ndw9A7nxfffUVVVVVZGRkMH/+fACefvppwsPDSUxM5Pvvv+fHH3/E39+fmJgYHnvsMc6cOUN+fj4L\nFy50neYXz2PUxpQpU1zfYzabsdls/Pzzz3z++ed0dnayePFifHx81IYHG0kb/f39nDx5kmeffZb2\n9nb27t1LXl4egYGBasODjaQNh8NBT08PAQEBLFy4kKamJoqKisjJyVEbHu7f+rDb7dTU1GAymViw\nYAF2u50TJ05QWFhIf3+/+vBgRm0MXX1iMplwOBx4e3uTlZXF4cOHKSoqIjc3V238RctKZVR++ukn\nuru76enpweFwsHLlSrZu3crAwAAAU6ZMca3/f+KJJ+jt7eWNN96goqKCuro616e/eiN6nn9r49q1\nIIODg66fmTdvHt999x1btmzh/Pnz+Pn5qQ0PdKNtXLp0ifb2dmpra1m7di2dnZ2EhISoDQ800jac\nTieXLl1iz549fPDBB1RWVrJnzx6Sk5MBHVM81Uj7AIiOjiYnJ4fy8nJWrlxJWFiY69oz9eF5/q2N\n0NBQ4OpxJSAggJMnT1JdXU1lZSW1tbWkpqYCamMoLSuVG1ZdXc2GDRuwWq3ExMQQGRlJZmYmjY2N\nnD59mtmzZ//tOpHU1FTsdjsXL15k1apVREdHu3cj5JYYaRteXl6uPux2O2+//TZ2u52NGzfyyCOP\nuJaDiOcYTRtOp5Ndu3Zht9spKSlhwYIFasMD3UgbXl5eTJw4EafTSWtrKxcuXKCkpIS4uDh3b4bc\nIjfSB1y9vsxqtbr+npiYOK7vPOnJRnNc6ejooKmpid9++41169YRGxvr5q0YezQ5lBG79gZraWmh\ntbWVoKAgJk+e7Lqr4MyZM9m0aRPZ2dkEBwcDVz/5r6qqIiUlhYSEBGbNmuX6mniO0bZRU1NDSkoK\ncXFx5OfnExQU5M7NkFtgtG18/PHHJCcnk5aWRkFBgdrwQKNpo7Ozk5qaGh5++GEefPBB0tPTdUzx\nUKPpo6uri127dmG1Wl0/7+Pj487NkFtgNG388ccfVFdXk5WVxZw5c8jMzNS+w4CWlYqha8tChz5+\nAK6emg8PD6evr4+jR4+6/n369OlkZ2dTVlYGQH19PcHBwURFRV33enLnu1ltREREAP9f9iF3vpvV\nRlhYGN7e3vrE34PcjDYmT55MZGTkda8nnuFm9BEUFOT6P4dWGXiOm9FGSEiI9h0j5OXUb0gMGF24\n/eGHH5KQkEB3dzeHDx8mLCyMtLQ0pk6dClxdwjF9+nTy8vJYtmyZdtAeSG2IEbUhRtSGDEd9iBG1\ncXvpbqXyN9988w0fffQR99xzD9nZ2SQlJfHaa6/x5JNPMnPmTAYGBujq6sLLy4vdu3cTHBxMRkYG\nHR0dlJaWkpmZyapVq5gxY4a7N0VuMrUhRtSGGFEbMhz1IUbUhnvozKFcp7W1leLiYlasWMHly5dp\namoiPT2dBx54AF9fX5xOJ+Xl5Xz22Wf4+/uTnJyMw+EgKyuLuLg4mpubiY+Pd/dmyC2gNsSI2hAj\nakOGoz7EiNpwH505FAYHBykrK2PGjBm0tbXx0EMPkZGRgd1up729nfLychITE/H19cXLy4vo6GgW\nLVrEokWLAHjvvfdwOBz4+fnpjehh1IYYURtiRG3IcNSHGFEbY4PuVjrOtbW1UVJSgtPpZNKkSWze\nvJlz586RmpqK2Wzm0KFD/P7777S3t2Oz2YCrzxBKSEhwvYbVanVdAC6eQ22IEbUhRtSGDEd9iBG1\nMXZocjjOXbhwgYaGBjZv3ozFYqG9vZ3jx48zODjIu+++y8DAAHl5eZw4cQKLxUJHRwdffPEFCQkJ\nf3t2jHgWtSFG1IYYURsyHPUhRtTG2KFlpePcpEmTuPfeezl27Bjx8fEsXbqU48ePk5OTQ0FBATEx\nMZw6dYru7m6Cg4NxOp2uxw/ork+eTW2IEbUhRtSGDEd9iBG1MXZoij3ORURE4HA4OHv2LJcvX+bu\nu+8mKSmJHTt24HQ6OXToEPv378fb2xu73U5ISAjp6enuHrbcBmpDjKgNMaI2ZDjqQ4yojbFDy0rH\nOW9vb/z9/WlsbMRsNhMeHk5ycjLvv/8+JpOJgwcPcv78eYqLiwkMDHT3cOU2UhtiRG2IEbUhw1Ef\nYkRtjB1aVirYbDa+/vpr9u3bR2BgIH19fVitVp555hmuXLmCn5+fu4cobqI2xIjaECNqQ4ajPsSI\n2hgb9JxDAaCnp4fdu3dz4MABenp6WLx4MY8//ri7hyVjgNoQI2pDjKgNGY76ECNqw/00OZTrnDp1\nimnTpjFhwgR3D0XGGLUhRtSGGFEbMhz1IUbUhvtocigiIiIiIiK6W6mIiIiIiIhocigiIiIiIiJo\ncigiIiIiIiJocigiIiIiIiJocigiIiIiIiKAyd0DEBERuVNt3LiRI0eOcOXKFY4ePUpKSgoAc+bM\nISIigoKCAjePUEREZOT0KAsREZH/6Ndff2XJkiU0NDS4eygiIiKjpjOHIiIiN9m2bdsYGBjghRde\nICUlheXLl1NfX09/fz/PPfccVVVVtLS0sH79eubNm0dbWxsbNmzgzz//pK+vj9WrVzN37lx3b4aI\niIwzuuZQRETkFurr6+P+++9n586d3HXXXdTX11NWVsaKFSvYsWMHAOvXr2fp0qVUVFTwzjvv8NJL\nLzEwMODmkYuIyHijM4ciIiK3mM1mA8BsNpOamgpAZGQk3d3dAHz77bf09vZSWloKgMlk4uLFi5jN\nZvcMWERExiVNDkVERG4xHx+ff/zzNb6+vmzbto3Q0NDbOSwREZHraFmpiIiIm9lsNvbt2wdAR0cH\nr776qptHJCIi45HOHIqIiLjZunXreOWVV9i7dy92u53ly5e7e0giIjIO6VEWIiIiIiIiomWlIiIi\nIiIiosmhiIiIiIiIoMmhiIiIiIiIoMmhiIiIiIiIoMmhiIiIiIiIoMmhiIiIiIiIoMmhiIiIiIiI\noMmhiIiIiIiIAP8Dbr3lP0YP/7gAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f335752da90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "q = data.loc['2017-7-21 9:41:00.000': '2017-7-21 9:42:01.000' ]\n",
    "\n",
    "ymin, ymax = 2739, 2743\n",
    "\n",
    "q.bid.plot(label=\"bid price\")\n",
    "q.ask.plot(label=\"ask price\")\n",
    "\n",
    "plt.xlabel(\"Time\")\n",
    "plt.ylabel(\"Price (USD)\")\n",
    "plt.legend(loc='best', frameon=True)\n",
    "\n",
    "plt.ylim(ymin, ymax)\n",
    "\n",
    "plt.annotate('Start Layering', xy=('2017-7-21 9:41:08.000', 2742), xytext=('2017-7-21 9:41:12.000', 2742.5),arrowprops=dict(facecolor='black', shrink=0.05))\n",
    "plt.annotate('Layering Succeeded!', xy=('2017-7-21 9:41:17.600', 2741.25), xytext=('2017-7-21 9:41:05.000', 2740),arrowprops=dict(facecolor='black', shrink=0.05))\n",
    "\n",
    "plt.annotate('Place BUY Orders at low price', xy=('2017-7-21 9:41:18.400', 2740.15), xytext=('2017-7-21 9:41:19.000', 2739.2),arrowprops=dict(facecolor='black', shrink=0.05))\n",
    "plt.annotate('Sell at higher price', xy=('2017-7-21 9:41:27.000', 2740.5), xytext=('2017-7-21 9:41:29.000', 2741.15),arrowprops=dict(facecolor='black', shrink=0.05))\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Momentum ignition\n",
    "\n",
    "Still quoting [5]\n",
    "\n",
    "> Momentum ignition is a strategy in which a trader aims to cause a sharp movement in the price of a stock by using a series of trades, which indicate patterns for high frequency traders, with the motive of attracting other algorithm traders to also trade that stock. The instigator of the whole process knows that after the somewhat “artificially created” rapid price movement, the price reverts to normal and thus the trader profits by taking a position early on and eventually trading out before it fizzles out.\n",
    "\n",
    ">To detect momentum ignition, it is important to focus on the following three main characteristics as shown in the chart below:\n",
    "\n",
    ">1.          Stable prices and a spike in volume\n",
    ">2.          A large price movement compared to the intraday volatility\n",
    ">3.          Reversion to the starting price under a lower volume"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following picture from zerohedge and Credit Suisse AES Analysis illustrates this behavior."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<img src=\"img/momentum.png\" width=70%>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "image(\"img/momentum.png\", 70)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This behaviour takes place on July 21, 2017 between 12:00:20 and 12:50:01"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ApvYYdeZ6koOSmNRpHJMTJtEruDvHtCfI0B6lpO4s3QK7omyjt48RBEEQBEcSYfI63Ehh\n8svUtVRJpQz0H0H3sChHl3PDWrNmFceOHb2o3WDQs2fPTk6fPsWoUTejVLaPnqWr4aJS0K9rMFmn\nKkjL1aKrMdKjU+Blg1CoRzC9gruRU3mKLG02R7XH6eofj7uq9SejqTfX89Hh/1JtquGhrpOvaebW\n5hLiHsSQsIHIZTKyK06QWpbGqeoCorwj8FS1jVEIFQYd2wp38+2x79lxZg8ldaUEuQUyJmokDyZO\nZnBYf0Lcg5DL5HioPOgX2ovT1QUcrTjOsYrjdAvsiqvS1dGHIQiCIAhtigiT1+FGCZNmq4XlOT8g\n2eQ83e8B1DdQUHE2q1f/yPHj2U0us9lsZGXdmNdRqlUNPZRH83Wk52rRVhvoeYVA6aHyYEBoHyqN\nVRytaOiRC/MMJdg9sNXqttqs/DdjMQU1ZxgTdROjIoe12mf/L4VcQYJfJ/qE9KCsvrxh6GtRChbJ\nSox3ZItcv3m9zDYLR8oy+DFnLd+fWMPJylysko3+ob2Z3HkiE+JuI843usnJdtQKFX1DelJlrCZL\nm82hsnQS/OLwcfF2wJEIgiAIQtskwuR1uFHC5Ppjv5GjzyTE1plbOvd1dDk3tJUrV5CTc/Ky6xQW\nFrBly2ZGjboZPz//VqrM8dQqBf27BHMsv5L0XC2aSj294oMuGygVcgXJgUn4uviQrj3Kb2cPYZMk\nOvnGtMoQzx9z1nKw9AjdA7sytcvdTjGs1EPlQb+QXnTwDCW36jSZ2mMcLD1MoFsAIe5Bji4PgKLa\nEjae3sY3R1fwW+khyvVaYn2iGBczhuld76N3SDJ+rr5X/PeUy+R0D0xErVCTpsnit9JDhHmEtNow\nY0EQBEFo65ozTIr7TLZTszd9QrWykKmRjzCkU+sPwRPOu//+u9m6dfMll3t6ejF8+AimT5/B6NE3\nt2JlzqPeYOGDFUfILa5mQGIIj9zeFaXiytdDFlSfYUHmN2gNOrr6J/CnxPvxVLfcEM+9xQdYkv09\noR4hvNjnKdyccIilwWJk/ektbCvYhQ0bLjZv3JSueLi44OnqiotCjUquRCVXoVKoUMmVqO2vVf+z\nTIVarsKGDYvNcu5hxWKzYLZZsEiWi9ubaKs0VnGmthgAL5Un/Tv0ZnCHfoR6hFzXsR7RZPJV1ndY\nbBYmdhrH6IjhThHuBUEQBMGZNed9JsXYx3aorFpHleIMCqMPg+MSHF3ODc9sNl9yWVxcJz7/fCHJ\nyb1asSLn4+6q5IXJPflgRRopR0up05t5YmI33Fwu/ysq0jucl/s9y+Kjy8jUZvOvAx/xSLdpxPhE\nNnuNuZWnWXb8R9yVbjze/U9OGSQByivMaI5FY8izoog8hsGjGoO5lkqbDfSOqUkuk9MtoCuDw/rR\nLaBrsw2/7RnUjRd6P8H89K9YlfMLZfXlTE6Y6JTDewVBEAShPRJhsh1anbUbmUyii2d3cZbeCZhM\nlw6ThYUFaLUVrViN83JzUfKXyT35z0+ZpOdqeXfpIZ67twe+npcfiuGhcmdm8p/YlP8ra/M28cGh\n/zAu5mYGduiLr4tPs9RWYdDxRcZiJCQe6TaNIPeAZtlvczpRWMm6/fmk52oBCA8KYVxCf6JCvThV\nUk1ecTV5JToKy6uxYkEmt4HcipurjA5BroT4uxDkrybAV41CJWG2mjHbGh5y5CjlCpRyZaOHSq5E\nKVNevOx/2tRyVYsFvEjvcF7q9zTz075kT3EK5Xotj3ab1qK3aREEQRAEoYEY5trOSJLEc5vexqyo\n5pXeLxPuf+Ncf+esxo27mYMHf6Nz5y6MGnULK1cuQ6PR2Jffccd4Fi361oEVOherzcY3G0+wM62Y\nAG9Xnr+vB2GBVzd0NbviJF9mLaXWXIcMGbE+0fQOSaZXUDI+Ln9sSIfJauL91M8orC3m3oQJjAwf\n8of20xJskkR6jpZ1+/PJKaoCICHch3GDoi55/06zxUpBWS15xdWcKq4mr6SaMl3jLstAH1diw7yJ\nDfMhtoM3UaGeqJTO3dtnsBj5+ugy0suzCHEP5onkh50y9AuCIAiCozXnMFcRJtuZgwUn+TLnCzyM\nEcy97WlHlyMADz10PwMGDOKRR2bi4uLCM888zrJlS+3Lvby8WLVqHcnJPRxYpXORJIm1+/JZtTMP\nD1clT9+dTELE1c10W2uqI7UsjUNlaeRWnkZCQoaMTr4x9AnpQc+g7nipPa+6jkVZSzhUls6QsP7c\n39k5JtyxWG38dqyU9fsLKCqvA6Bnp0BuGxhJfPi1zwhcqzc3hMvfezCLq6gzWOzLlQoZ0R28iQ/3\nIT7cl04dffB0UzXb8TQXm2Rjde46thbsxEPlzp+7P0Qn3xhHlyUIgiAITqXNhMm5c+eSmpqKxWJh\n5syZrF27Fp1OB0BlZSU9e/Zk9OjRLFy40L5NVlYW69evx2az8dJLL2G1WgkKCuK9995DrVY32v/b\nb79NWloaMpmMV155heTk5CvW1N7D5D+3fUUxRxntN4m7eg1ydDlCEzIzM5gwYSw1Ned/FidPnson\nn8x3YFXOaU9GCV+tz0Ymg8fuTKJfl2ubsbPSWMXhsgwOlaWTV3UaABkyOvt1ondwMj2Cul12wp4N\np7fyc95G4nyieabXn1HKHXtlgNFsZVdaMRt/K0BbbUQukzEgMYTbBkYSHnR1AflqSJKEplJPXnE1\nucXV5BRVUVBaw4V/LToGetjDZXy4DwE+rk4RtAH2FKew7Pgq5MiY2uUeBnTo4+iSBEEQBMFptIkw\nuX//fhYuXMgXX3yBTqdj0qRJbN++3b589uzZ3H///Y0CYH5+Pu+++y6fffYZs2fPZvjw4dx22228\n//77hIaGMnXqVPu6v/32GwsXLuTzzz8nNzeXV155heXLl1+xrvYcJg1mI3/Z/g+wyfm/Ua/jqlJf\neSPBIWbMmMbatWvs7wMDg9i8eQcdO4Y7sCrnlHWqgk9XZWAwWZk8qhNj+kX8odCiM1RyuCyd1LJ0\nTlcXAA0TwzQEyx70DEpqdJ1dmiaL/2Z8jZ+LLy/3e+aqezNbQq3ezLbUM2xJPUOt3oxaKWd4jzDG\n9I8g0MetVWrQGy3klVRzsrCSk2eqyC2uwmS22Zf7ebk0CpfhQZ7I5df+/yRJEnqjlTqD+dzDQp3e\njNUq4eWuwttDjbeHGi93FQr5pWf8za44yYLMb9Fb9IyNGsXtsWOQy648Q7AgCIIgtHdtIkxarVaM\nRiPu7u5YrVYGDx7M3r17USgU5OXl8f777zNv3rxG27z44ovMmDGDxMRERo0axYYNG1Cr1Rw+fJhF\nixbxySef2Nf96KOPCAsL49577wVg7NixrFy5Ek/Py3/ha89h8oe0XWzT/kyYrTuv3jzd0eUIl7F9\n+zamTbsPk+n8fU8feWQm77zzngOrcl4FpTV8+H0albUmbu4bzpRR8X8oqPxOq6/gsCaD1NI0CmrO\nAKCQKejiH0/v4GSC3AL5NG0BkiTxQp+niPAKa65DuSYV1QY2HShkx5FijGYrHq5KRvcJZ1SfcLzd\nHXuyyGK1UVhWy8kzVZw80xAwq+vO/zy7qhV06uhDfLgP0R28sVqlhnCoPxcQDWbqDRZqDWbq9Bbq\nDefbr+avkgzwcFPhcy5cenuo8XZX4+3REDh9PNSYldWsPrOCCmMFvYKTebDrZNQK5xueKwiCIAit\nqU3cGkShUODu3nCWf+XKlQwfPhyFomECh8WLFzNt2rRG65eWllJeXk5iYiIAer3ePqw1ICCg0YQl\nAOXl5SQlJdnf+/v7o9Forhgm27OUs6mggrHxzjNBiNC0kSNHMXjwULZv32Zv27RpA7Nnv4a3d/PM\nQNqeRIZ48dqDfflgRRpbDp5BV2PksTsSUav+2KQwAW7+3Bw5gpsjR1Cu13KoLJ1DpWlkabPJ0mbb\n13u02/RWD5L1BgtpOeUcPF5Geq4Wq03Cz8uFScNiGN4zDFe1c0zCrVTIiengTUwHb8b0i0CSJMoq\n9ZwsbAiXOUVVZJ6qIPPUlWcrVipkeLg2hMDQAHc8XVV4uCpxd1Xh4abEw1WFQiGjps5EdZ2ZqnoT\n1XUND12N0X7daNM774m602EOk05BaTX/GP1kM/4rCIIgtF9Gi5n3dn+FpNLj4+6KQqZAIVc0PMvk\nKOQKlDIF8gvalHJlwzKZwr6+u8qdPsE9xMm866S36Pklew9ZZXnA9fUFzpv8YvMURSvcGmTLli2s\nXLmSRYsWAWAymUhNTWXOnDmN1lu9ejXjx49vch9X03l6tR2szZnEnckpTSm1ymLUxgBu7ZPsNNcu\nCZf26KMz2LHjV/vPbmFhPl999TlvvfWWgytzTkFBXvz7uRG8/eVvpB7XUG/M4LUZA/D2uL4euiC8\n6BoZzQOMp6SmjH2FqaQWZzAwvDdjugxupuovr6rWSErWWfamF5N2UoPF2vAzERXqxcQRcYzoHYFK\n6fxDNIODvemWEGJ/X1Vr5NjpCk4VVeGiVuLlrsLTXYWnuxovdzWebg3vXVSK6/qdZbZYqawxUVlr\noLLG2PCoPfeoMVJRE0KuYQ3l6gJ8/dxQKZ0jkAuCIDiz//z6MyW2k2CEs8br21dWZRZ/HfoESnEf\n4GtWUFnEhpwdbM/bj0W69O3mHKVF/6Lu2rWL+fPns2DBAry8GkLcgQMHmpwoZ/v27XzwwQf29+7u\n7hgMBlxdXSktLSU4uPHEG8HBwZSXl9vfl5WVERQUdMWa2usw1692b0Amg0TvZMrLax1djnAVbrnl\nTvr06cfBg7/Z21au/JHHH3/uosmmhPNmTerGonXHSDlaygsf7uCF+3oQ5Ns81w0qcWNY0FCGBQ0F\nWvb3ha7GyKETGlKPl3G8sNI+tDMy2JM+nYPo0znYfkuUSt1let6cXFyIJ3EhTY8YkcwWaqosNNe/\nsq+rEl9XJQRdPKnSaxsPoJPnsDvrGN3CopvpEwVBENons9XCjqIdSAo5voVjOVtqoWOwOw/f3plg\nP1eskhWLzYpVsmK74LVVsmG1WRqez7XvKtrH4ZIsPtn9NQ90uUd0eFwFq81KWnkWO87sIafyFAA2\noysKXRx3Jw/F39t57qXcYmGypqaGuXPn8tVXX+Hre36q+oyMDLp06XLR+oWFhYSGhtrfDx48mI0b\nNzJhwgQ2bdrEsGHDGq0/ZMgQPvnkE6ZMmUJWVhbBwcE37BBXSZI4XpeJJJczsbsY4tpWyGQyJk68\nq1GYzM4+ysKF/+WJJ2Y5sDLnplLKeezORPy9XVi/v4B/Lj7Is/f2IKaDt6NLu6LySj2pJzSkHteQ\nW1RlH6QSF+ZNn87B9O4cRHAzBWOhsQ4eoehMOWSdzRdhUhAE4QpWZezGpqoj0NyZ16YNY/m2HH49\nXMTcbzN44JYEhnbvcNWhsLNfJz46PJ99JQfwdfHhjtgxLVx921VlrGFP8X52F6VQZaoGwMUYQnV+\nGGHqWJ65K5lAJ/ue0GJhct26deh0Op577jl727vvvotGoyEyMrLRujqdzt5z+bunn36al19+meXL\nlxMWFsbEiRMBeP7553nnnXfo3bs3SUlJTJkyBZlMxhtvvNFSh+L09p46ik1Vi48xhmBv5/9CLZz3\n8MOPsWTJNxw7lmVvW7NmFTNnPon8MjNV3ujkMhn3juxEgLcrSzaf4N2lh3hyYjeS4wIdXdpFzlbU\nk3q8jIPHNeSfbeiDk8kgIcKXPp2D6J0QhL+3q4OrbP/i/SM5ehbyq844uhRBEASnZrVZ2V26G0kh\n475ut6JWKZh+a2e6Rvnx5fpsvlyXzbF8HdPHdMbN5cpRwlXpwhM9ZvB/Bz9l/ekt+Lp4M7TjwFY4\nkrZBkiTyqvLZcWYPRzSZWCUrrgoXevv3I+ugF5Xlavp2CeaRcV1xUTvfMOEWvc+kM2qPw1zf3LKA\nMvkJxgXdx+3d+zq6HOEavfvuP/m//3u3Udu8efO5776pl9hCuNDhExo+X5OFxSox/dYERvTs6LBa\nJEmistZEYVkNuUXVHDqhsU8Oo5DL6BrlR+/OQfSOD7ruaz2Fa1NaVcU/Uv+Ju6kD74193tHlCIIg\nOK01mXvZWLYaH2Mcb982s9Gy8ko989dkkVdcTbCfG09M6EZU6NXNR1JWr+H/Uj+jzlzPzOSH6B6Y\n2BLltxluIS7oAAAgAElEQVQmq4kDpYfZcWYvRbUlAHTwCGF4x8HIK8P5dkMuJouNScNjuWNQVLMO\nD24TtwZxVu0tTNYa9by88x9gVfPBza+jFhNLtDm1tTXcdNMQ8vNP29uGD7+JlSt/clxRbUxuURUf\nrUynVm/mzsHRTBwW0+LXZFisNs5W1FNYWktBWQ2FZbUUlNZSqz9/cbxSIadbjD99OgfRMz4QD1cx\nk50jPbXhDZDb+HSMmORKEAShKZIk8fymf2FS6ni00xP0joq5aB2L1caqXXms31+AUiHj3ps6cXOf\n8Kv6u3u6uoCPDn2OBDzb68/E+ES1wFE4N029lp1Fe9lXchC9RY9cJqdHYBLDwwcT5x3Dql2nWLc/\nH1e1gsfuTKRX/JXnhLlWbeLWIELr+DlrHyisRCq6iiDZRnl6ejFmzFi++GK+vW3//j1s3bqZ0aNv\ncWBlbUdcRx9end6HD1ak8fPe0xwr0BHi54aXe8O9B73cVecearzcGp6vZahIvcHcEBbLaiksraWw\nrJai8lr7rKu/C/RxJSHCl8hgTyJCPOkS6XdVQ4CE1uEhBVCnPENJVQUdfPwdXY4gCILT2XQ8FbNK\nh5cxsskgCQ0nSu8d2YmukX58sfYo3205ybHTOmbc3hVPt8ufNI32juSRbtP4PONr/pP+JX/p8xQh\n7s0flpxRuV7LihM/cVR7HAkJL5Unt0WPZkjYAPxcfak3WPjkxwzSc7UE+7nx9N3JdAy8eEI5ZyN6\nJtu4Fzf+G72qjCc7P01SxwhHlyP8QWfPljB69DA0mjJ72+2338mXXy5xYFVtT3Wdic9WZXDiTNUV\n11Wr5Hi5qc+HTHeVPXh6uKmoqDZQWNYQHMurDI22VSrkdAzyIDLYk8gQLyKCPQkP8sTdVQRHZ/be\nr8s5LaVyZ+h9jE0UlwQIgiBcSJIk/rLpPYyqcqZGPsqQTglX3Kay1sgXPx/lWL4OPy8XZo5PIiHC\n94rb7SlOYWn2DwS4+vOXPk/h49I+b933u+Las8w78gVVphpifaIY3nEwPYO7o5I3fG8o0dbxyQ8Z\nnK2oJynGn8cnJLXoaCbRMykAkKMpQa8qQ20IFkGyjQsN7cDNN4/hu+++tbft2LGdtLTD9OjRy4GV\ntS3eHmpefqA3BpOVmnoTNfVmqs8919ifL3itN1FUXofZcumTTF7uKpKi/YgI8WrocQz2JDTAHYWY\nIKnNifbtyGldKjkVhYAIk4IgCBfalZeBUVWOm6HjVQVJAF9PF/4yuSe/7M9n9a485i49zIRhMdw+\nMAq5/NLDXoeEDaDSWM26U5v5T/oinus1E1dl+5yMLr+6kE+PLKTOUs898eO5KWJoo+XpuVo+X5OF\n3mhhbP9I7h4Z26a+Y4gw2Yb9fGwXAD38ezq4EqE5/PnPT/LLL2uorm6YCrq2toYvvpjPvHmfO7iy\ntkUmk+HmosTNRUmw35XXlyQJo9lK9QUhs7bejI+nmohgT3w81OKeWO1EUkg023VQUn/W0aUIgiA4\nnZ9ztoAKxsWOvqbt5HIZdw6OpnOEL5+vyWLVzjyy83U8dmcivp4ul9xuXPTNVBqq2FvyGwsyv+WJ\n5IdRyJ1vttLrcVKXx/z0LzFaTUzrci+DwvrZl0mSxIaUAlZuz0WhkPPYHYkM6hZ6mb05p7YTe4VG\nrDYrufosJKuSid0HObocoRkkJXVjxIhRjdq2bt1MQUG+gyq6MchkMlzVSoJ93YgL86Fnp0CGJneg\ne2wAvp4uIki2I51DwpCsSmps5Y4uRRAEwan8lp9NveosakMIN3VO+kP7SIjw5c0Z/enZKZBj+Trm\nLPqNzDztJdeXyWRM6TyJbgFdOFZxgiXZK2lPV99labP5NG0BZpuFGd0eaBQkjWYr//35KN9vz8XX\ny4XZ03q3ySAJIky2Wdtz0pFUegJsMfh6OP/FucLVeeihGbi4nD+Lp9WW8+mnHzmwIkFoPxQKOS4W\nPyyqGmqNhitvIAiCcINYdXwTALdE3HRdJ1E93VQ8fXd37r85nnqjhfdXpPH9rzlYrLYm11fIFczo\nNo0o7whSzqbyc97GP/zZzuRQWTqfp38NwMzkh+gdnGxfpq0y8K9vD5FytJS4jt78/aG+xHRou/eJ\nF2GyjdqenwLAiMgBDq5EaE7Dh49k8ODGY+m3bNlIZaXOQRUJQvvipwxCJoOMotOOLkUQBMEppBXl\nUq08g9IQwK1J13/plEwm45a+Ebw6vS/Bfm6sTyng7W9SKdHWNbm+i0LNE8kPE+QWwMb8bew8s/e6\na3CkfcUHWJS5BJVcyVM9HiEpoIt92YnCSt76+gD5pTUMS+7AS/f3xucyQ4HbAhEm26DK+lq0stPI\njJ7clNDN0eUIzWzy5AcanRUsLCzks88+dmBFgtB+hHuFAZBdLoaPC4IgAHx/tKE3cGSHEc068UtU\nqBdv/KkfQ7qHcvpsDW9+eYBfDxc1OZTVS+3JUz0exUvlyYoTP3FEk9lsdbSmXwt3823297gr3Xim\n15+J94sDoN5g4Ycdubz33WFq9RYeuCWBP93WBZWy7Uextn8EN6DVWbuRyW3EuiWhUIj/wvZm0qS7\n6devf6O2det+wWg0OqgiQWg/ugRFAnCmptjBlQiCIDhe9tlCKuSnkRt8GZ/c/8obXCM3FyWP3J7I\nkxO7oVLK+WbjcT5amU5VnemidYPcA3iix8OoFCq+ylpKbuXpZq+npUiSxPpTW1l5cg3eai+e6/04\nUd4RWKw2tqae4W+f7+OXffl4e6j5y+QejO4T3m7mZBBJpA1K0x5BkmBC4hBHlyK0AJlMxsSJ9zRq\nO3EimwUL5juoIkFoP5I7RiNJMirMZVdeWRAEoZ1blrkBmQwGBw1r0Q6Kvl2C+ccjA0iK9iM9V8vf\nF6Zw5OTFk6FFeUfwaLfpWCUb89O/5GxdaYvV1FwkSWJV7i+sPbURf1c/nu/9BB08Qkg9XsbrC1JY\nsvkEFquNu4bH8vafB9I12t/RJTcrESbbmKySfEzqCtyMHYgLbpuzPglX9tBDM0hKajyEec2a1dhs\nTV/ALgjC1fF0dUVh8sKkqMRqszq6HEEQBIc5pT1LmSwHmdGLu3u1/J0B/LxceH5yT+4fHY/eaOXj\nH9JZvCEbo6nx7+KkgM5M7XIP9RY9844spNJY1eK1/VE2ycay4z+ytWAnIe7BvND7Cap1Kt5ZcohP\nV2VSXmVgVO+O/GvmIO4YHI2Lqn3d+gREmGxzfjm+G4A+Qb0dXInQklQqFbfddkejtsOHU1mx4jsH\nVSQI7YeXLBAUVnI0JY4uRRAEwWGWpK1HJpPo5zcYtbJ1bj0vl8m4pV8Ef/9TXyKCPdl+pJg5X/5G\nXnF1o/UGdejLnbG3ojNW8lnaIvQW55uB22qz8vXRZewuTiHcM4xpsQ/y3fpC3v4mlZwzVfROCOKt\nRwcwbUxnvD3Uji63xYgw2YaYLGbyTceQLCrGdxezuLZ3Tz75DFFRMY3avv9+mYOqEYT2o4N7w6iO\nzJLTDq1DEATBUYoqyym2HQeTO5P7DGv1zw8P8uS1B/sydkAkZTo9b3+Typo9p7BeMALr1qhRDO04\nkKLaEj5P/wqdobLV67wUs9XMF5mLOVh6hCjPSDpWjeadr7I4eFxDbJg3f3ugN7Pu6k6ov7ujS21x\nIky2IWuz9oPSRAdZZzxdXR1djtDCPD09GTv2tkZt+/fvZfPm9nEPJkFwlDj/cABOVZ5xcCWCIAiO\n8e2R9cjkNnp4DcRV5ZheM5VSzn03deLF+3vh46lm9a5T/GvJIcp09UDDHBKTEybSIzCJk5V5vLl/\nLqtyfqHOXO+Qen9nsBj5LP1LMsqPESgPJ39fIttTNfh7u/D4hCRend6HhAhfh9bYmhRz5syZ4+gi\nWlN9/cWzR7UVi9JWYlbUMSX+Hjr43jg/pDeypKRu/PDDCurqGu7NZLPZqK+vZ9Kke66wpSAIl+Km\ndGX32d2YjXJu6TTQ0eUIgiC0Kk1tJT8VrAKzC38Z/GCrDXG9lCBfN4Ymd0BbZSAzr4JdGSX4uKuJ\nDPFELpPTKziZADd/8qsLOVpxnN3FKciQEeHVEYW8da9BrDfXMy9tIblVp1DUhFKeloSLQs3dI+J4\n5PZEIkO82sQsrR4ezXdvS9Ez2UacKDtDvaoUtSGIXlHRji5HaCUhIaHcfPOYRm07d27n8OFUB1Uk\nCG1fRz8/MLtSL9M6uhRBEIRW982hDSC30dW9Hx6uzRcqroeHq4rHJ3Tjz3cmIpfJ+HJ9Np+tyqSm\n3oRcJmdQh768MfCvTOp0OzJgde463tw/lz3FKa02mVq1qYZ/pXzK6eoCLOVhGE70ZGz/GP71+CDG\n9ItoF/eM/CNEz2QbsfDAz1RJpfT3HUFyx5grbyC0G9HRsfz44/f2+0yazWYMBiO3336ngysThLZJ\nJpPx68k0zGod/QP74eEiLhsQBOHGoKuv5YdTK8Gq4oWBD+KqVjm6pEbCgz0ZkBhMQWktGacq2Jd5\nlvAgD4L93FHIFcT6RDM0bCAymYwTulzSNJkcKsvA18WbEPegZu8VlCSJotoSVmVtZ+mxH6mTKrGU\nRtDbYzRP35VMvy4hqJVtb4bW5uyZFGGyDTCYjazI/QHJquCZAdMcPhxBaF2BgUGkp6dx/Hi2ve3s\n2RLuuGMCvr5+DqxMENquw4V5VHEWP8KJDezg6HIEQRBaxYLffqbcVkgnVV9GJvRwdDlNcndVMbhb\nKC4qBWm5WvZmnqWq1oi/tyve7irUChVd/OMZ2KEvRquR7IqTpJalcaziJMHuQfi7Xt93I6vNSm7l\nKTae2sk3WT/wa9EOigwFWLHgU5fIM4OncEvfSNxdnSuIXwsRJq9DWwyTqzL2cNqYTRiJ3NxZ3BLk\nRhQQEMhPP/2IxWIBQK/XYzZbuOWWWx1cmSC0TWcqdBQYT6A0+dAvsoujyxEEQWhxtUY9y04uR7Ip\neK7/Q7i7OMcQ16bIZDLiw33pERfIicJKMk9VsP1wEQeyy6ipN+HlriLY25vugYn0Du5BtamabN1J\n9pccpKC6kDDPULzVXlf9eUariSztMTbl/8q3R1eyu2Q/hbWFmKwWpKpQYhW9mZZ4L1P6DcHPq+2P\nZmnOMNmiXVxz584lNTUVi8XCzJkzWbt2LTqdDoDKykp69uzJW2+9xb59+/jXv/6FQqHg/vvv5957\n7+Wtt97ixIkTQMMXZ29vbxYtWmTfd0pKCs8++yzx8fEAJCQk8Prrr7fk4ThMSukBUMGdnYc7uhTB\nQYYMGcaQIcPYunWzvW3z5g3odK/h5+fvwMoEoW1KColiVxUU1591dCmCIAitYumhLaA0EyX1IdDr\n6oOWI0WFejHn4f4cySnnwLFS0nO1rNlzmjV7TtMx0IN+XYLp1zWYx7o/yKmqfFbnriNTm02W9jj9\nQ3tze8wYAtya7qmsMdWSUX6M9PJMjlWcxGJrOGEvmVyw6iLwtUUyKqEHw4Z1bNO9kC2txcLk/v37\nOXnyJMuXL0en0zFp0iS2b99uXz579mzuvfdeLBYLb7zxBosXL8bHx8fefmEwnDdvHnFxcRd9Rv/+\n/fn4449b6hCcwrGzBehVZagNwfSIjHJ0OYIDTZnyAL/+uhXbuXswFRWdYd68j3j99TcdXJkgtD1d\nOnREOqagylru6FIEQRBanMFsJL3mNySZgul929aoJpVS3hAauwRjMFlIy9FyILuM9Fwtq3efYvXu\nU4QHedKvazD3d36Q8sgCfspdT8rZVFJLjzA8fDC3Ro/CU+VBWb2G9PKjpGuyyKvKR0ICQNJ7YtEF\nI6sKoXdEPDcNDSc+3KfJazC/+eYrpk//Uyv/KzivFguT/fr1Izk5GQBvb2/0ej1WqxWFQkFeXh41\nNTUkJyeTlpZGVFQUoaENN5H+8MMPG+2nqqqKffv28dRTT7VUqU7tp2M7AOgb1NfBlQiONn78JBYs\n+JyUlH32tg0bfuGvf52Nq7jvqCBcE5VCicrii1ldgd5sxE3lvMO9BEEQrteyw78iKY10tCYT5td2\nby/nqlYyIDGEAYkh6I2Wcz2WZWSe0rJqZx6rduYRGeJJ384T6R9Vxs7SX9lWuIu9xQfwdfXhbF3p\nuT3JUBkCqC8LwKoLJsgtkBG9whjSvQPe7pe+76ZOV8E777yFJEk8+ODDrXPQTq7F5rBVKBS4u7sD\nsHLlSoYPH45C0TDb0eLFi5k2bRoARUVFqFQqnn32WaZMmcLatWsb7WfFihXcddddTZ4ZyMnJ4fHH\nH+f+++9nz549LXUoDlNvMlJoyQazmonJgxxdjuBgMpmMiRPvbtR28uQJvvjiPw6qSBDaNj9FEDKZ\nRFZJgaNLcSq7d+/gT3+aygMP3MMTTzxCXl4ONpuNJ598lAMHUi653axZf2bjxnWtWOn10WjKmD79\nPkeXIQgtzmy1cFC3D8kq54GebatX8nLcXJQMSgrlmXuS+fDpoTxye1eS4wIo0tTx487TfPd9PcoT\nN5GoHoocOeX1WvxskdgKktEfuonajH708O7PCxOH8PbMgdw2IOqyQRJg3bqfKS/XMHfu2+zb1/6y\nxx/R4tOCbtmyhZUrV9qvdzSZTKSmpvL7vD+SJFFSUsLSpUsxGAzcddddDBkyBD+/hvHNa9euZfny\n5RftNzo6mlmzZnHbbbdRWFjIgw8+yKZNm1CrL/9DEBTUNsaIAyzctQcUZqJUvYgOD3R0OYITePHF\nZ1m+/FuOHDlib1u//mfeeONV+8kaQRCuTlxgBJrKbE5VF3NbkJjcDKC0tJS3336T7777jk6dOrFk\nyRI++OBdli1bxnvvvcvDDz/M+vXrmxwNoVYr8fJybTN/Z4OCvNiwYb2jyxCEFvffneuQVHrCpCT6\nJcY6upwWExXhz8RRCdTWm9ifWcKutGLSTmjIP+sJDAUZ1EhyAn1cuefmaG7pH0mAj9s1fcaJE0cB\nKCsr5ZVXXmTjxo107NixBY6m7WjRMLlr1y7mz5/PggUL8Dp3oe+BAwfsw18BAgIC6N69O25ubri5\nuREfH09hYSF+fn6cPn0aPz+/Jv9ohYSEMG7cOAAiIyMJDAyktLSUiIiIy9ak0dQ04xG2rB35e0EF\nt8UPbVN1Cy1rzJhxjcLkwYMH+eST+TzwwIMOrEoQ2p4orzD2V8KJstPid+w5VVUG/v73/4ePTwga\nTQ2xsV05efJ9NJoaPDwC6NIliS+//IZ77ply0bYmk4WaGkOT/5ZffbWAjRvXYbVaiY6O4fXX38LL\ny4uFCz+nvFxDTs4JbrllLBMm3M3/+39vkJGRRkxMLAkJXaio0PLqq3MoKyvl3//+FwUF+QA8++xf\nGDRoyEWfdc89dzJp0j1s3bqZsrKzTJhwN4899gQlJcU8/vgMRo++hRMnjvPqq3OYMmUSO3akIEkS\n8+Z9wM6d21EolIwfP5GpUx9EkiS++moBmzatx2QyMWzYSJ5++vmLTt6tW/cze/fuQqVSk5Z2mMjI\nKB5++DH+859PKCo6w6OPPs6ECXdhs9n44ov/sGPHNgCSkrrzwgsvs379Wvbv38vcuR8AYLVaGT9+\nDJ99thA3N7erOm5BaIrVZuXXgl+RFDLuTRpzw/yu6xHjT48Yf2r1Zg6d0HDweBlKuZxhPTqQHBeA\nQi7HZrJc87/H4cNp9tdZWVlMmTKVZct+vGJnlrNpzpN+LTbMtaamhrlz5/L555/j63t+bHZGRgZd\nupyfhr1Xr15kZ2djNBoxmUzk5+cTHh7e5LoXWrNmDQsXLgRAo9Gg1WoJCQlpqcNpdVkl+RhUGlwM\noXTvePmALNxYnnjiaWJiGp9Z/OGHFUiS5KCKBKFtSg6LQZKgwlTm6FKchp+fPwMHDra/379/D4mJ\n3ezvR4y4iW3btlzTPrOzj/HDDytYsGAxy5atwmQy8cMP50cc7du3h/fe+5j77pvK2rWrKS/XsHLl\nz7z88musW/ezfb1//nMO8fEJLFv2I//+90e89dbfqaqqbPIzMzMz+OKLr/nmmxX8+OP3nDzZMDt8\nVVUl8fGdmTfvv43W37RpPUePZvHddz+ycOFiVq5cztGjmWzcuI5t2zbzxReLWb58NcXFZ1i9emWT\nn5mSsp+HH36MZctWkZ9/mqVLF/Ppp1/wt7+9ztdfN3xf2bZtMykpe1m48Fu++WYFtbU1LF++hBEj\nbuLw4YMYDAYA0tIOExgYRFRU9DUdtyD8r58y92JV1eJv6UTnDjfePXU93VQM7xHGC/f15Jl7kukV\nH4RC/sfiT2WlrtE9vwF2797JX//6XHOU2ma1WJhct24dOp2O5557junTpzN9+nSKi4vRaDQEBATY\n13NxcWHmzJlMnTqVqVOnMmPGDPz9G251oNFo7K9/9/zzz2MwGBg1ahQHDhxg6tSpPPnkk8yZM6fN\nnRW4nDXZDRPv9A8WE+8IjXl4eHDrreMate3fv7dNXaskCM7A18MduckTg0JnnyVZOO/gwd9YseI7\nnn76BXtbYmI3jh7NvKaTV126dOXHH3/Bw8MTuVxO9+49KC4uarTP3086p6Ud4aabRqNUKgkN7WDv\ngdPr9Rw6dJDJk6cCEB4eQY8ePdm7d3eTnzl27O0oFAr8/Pzp0aMnmZnpAFgsFoYPH3nR+vv27bF/\nroeHJ0uWrKRr1yT27NnF7bePx9PTE6VSyR13TGTHjl+b/Mzo6BgiI6NQq9WEh0fQv/9AFAoFcXGd\nKC/XnPuc3Ywdewdubm4oFArGjbuTAwdSCAgIJCGhCwcO7Adg585fuemmm6/5uAXhQlablR0lO5Ek\nGZO7jXV0OW3e+vVr0ekqLmpfseI7PvnkAwdU5BxabJjr5MmTmTx58kXtTd0LcvTo0YwePfqi9hkz\nZlzU9sEH5/+z5s+ff51VOqd6k4EzlmywuTCh+0BHlyM4oVmznuPHH7+nrKxhVjKLxcKSJd8wduzt\nDq5MENoWL1kA1Yp8TleUERsY6uhynMbOndv58MP3mDv3g0YjIfz8/LFYLNTUVOPt7XNV+zIYDHz8\n8f9x+HAqADU11QwaNNS+3Nvb2/66pqYaL6/z74OCgikrK6WurhZJknj88fPfC/R6Pb1792vyMy/c\np5eXNzU11UDD5IAeHp4XrV9VVYmn5/lhX25uDddR1dbW8N1337JmzSqgYfipr2/T96xzd/ewv5bL\nFbi5uZ97LbefrNDpKu2X/fxe2+9fTkeOHM3u3TsZNmwku3bt4MMPP7vm4xaEC23IPohFVYWPMYbu\n4WKU2/U6cuRwk+1Wq5VPPvmAhITOF53svxG0+AQ8wrX7KXMvKCyEy7vh5tJ+eluF5hMcHMwtt4xl\nyZKv7W27dm3n4MEU+vYd4MDKBKFtCXELpdqaT0bJKREmzzlwIIWPPvo3778/j+jomOve34oVSzlz\nppCFC7/F3d2dzz//1N5T9788PDzQ6/X291ptw31AfX39UCgULFjwjX2m+Mu5cBhodXVVo3DZFB8f\nXyorz29TUaHFxcWFwMAghg4dzt13X3xy/I/w9/enurrqgjqr8PdvGK01cuQovvnmS7Kzj+Lt7U1E\nRCQWi+WajlsQLrStcCeSEu7qMsbRpbQL2dnHLrmssrKS119/hZiYOBISOrdiVY7XYsNchT/ugOYg\nkgQTu45wdCmCE3viiVn4+JzvGaivr2fBgi8cWJEgtD2xfg1n6/MqCh1ciXMwGAy8884/+Oc/32sy\nSFZW6lAqlY168a5Ep9MRGRmNu7s7Z8+WsH//HvT6+ibX7do1iR07tmGz2SgtPcv+/XsBUCqVDBo0\nhNWrf7DX+fbbb1JaerbJ/WzduhmbzUZFhZb09DSSk3tdtsahQ4ezZctGTCYTer2eJ598lLy8XIYO\nHcGGDevs1zKuXv0D69evvey+Lmfw4GFs3Lgeg8GAxWLhl19+sg/lDQoKJiysI19/vYhRo275Q8ct\nCL87W61rmHvDGES/mDhHl9PmVVVVcuLE8cuuc/p0Hs899yS1tbWtVJVzED2TTiaj+BRGVTluhg50\nDbuxpxoWLi8hoTM33TSa1at/tLf9+utmTp3Ku2iCHkEQmpYcFsPGcig1lF555RvArl3bqazU8Y9/\nvNaofd68/+LvH0BWViZduyYhv8QEFp999rF9shmA8eMnMXHi3bz66kvcf/9dxMV14umnX+CVV/7K\nihVLL9p+4sS7OXLkEJMnTyQ2No7Ro8fYh6i++OJs5s59m7VrVwMwZsxthIQ03ZscExPLY489xNmz\nxdxzz2RiY+MoKSm+5HGPHj2G3NwcpkyZhFrtwu23T6B79x5IksSpU7nMmPEAAB07hvO3v118uc7V\nuumm0eTmnuSRR6YhSRK9e/dtNDPuyJGjmDfvQ2bNOj+hx7UctyD8btvJhiGZMR6dHFxJ+7B+/S/2\nkRKXc/DgAR5/fAbffruiFapyDjLpBpsC0tmnRP7ntq8o5igjfMZzX5+hV95AuKHt27eHyZMn2c+a\nAzz00Azee+9DB1YlCG2HzWbj6c1/R4aSebfOcXQ5Tm/OnFdJTEzivvumtthnSJKETCYD4NNPP8Jq\ntfDMM3+56u3vuedOXn/9LXr06NlSJQqC03t102dUKk/zSNzj9I4SJ5iv19/+9iKLFv23yWUymYw+\nffoRH59Ap07x3HzzrXTtmtjKFV6bNnFrEOHa1ZkMFFtPgNmV8cn9HV2O0AYMGjSEoUOHN2rbvHkD\nFRUXzzYmCMLF5HI5rjZ/JFU9unrnPtnoaEVFZ0hPP8Kdd05qsc/YvXsHjz76ICaTifr6evbt201S\nUvKVNxQEwc5stVApOwMmd3pERDu6nHYhO/so0DCJV0xMrP2EFzScAHvhhZf46KPPePrp550+SDY3\nESadyOqM3aCwEKlMxFUlJt75/+zdd1QUVxvA4d8WQECqgCiKFZWgiF0sKJbExK5gwZIYE1tsKcaY\nT2MldmONGjVGNNiNxp7YsWAXUKMCKiqC9CZ12f3+IK5uAAEFFvA+53iOc2fmzjugLHfm3vcV8mfg\nwBKyDqgAACAASURBVMEaU86ePn3KihXizaQg5FcFXSsA/EIfaDmSkkupVDJ37iwmT56qznRaFJyd\n21Cvnj2DBrkzbJgHzZq1xNU1e7Z3QRByd+HhPyBTYCm1feOaisJLSqUSG5sqfP/9dI4cOcnZs5ep\nWrWaxjGXLvlqKTrtE2smS5ArUVdRyaHney55HywI/+rWrSfNm7dUJ6oAOHLkIJMmfSey/wlCPtga\n2RCa5M+9qEe0txNvwXIilUpZuTLnKV6FSSaTMWnS92/Vx65d+wspGkEonS4+DgCgodW79YasqEil\nUlat0vz5V7u2HY8ePVRvBwUFFnNUJYd4XFFC+D0JJl0nGoO0ytSrVFnb4QiliEQioXdvN4224OBA\n1q0rm3VYBaGwvVcx6wnz06QwLUciCILw9p6k3kellOIqHo4Vmdq17TS2g4ICecfS0KiJwWQJsf/e\nGQBaWou1kkLBDRnyCQ0aaH5oHDiwl8zMTC1FJAilh4NNVVRKKbGZOdc+FArf7Nk/cPZs1ufe8eN/\n8fx5Vip9T88Z/Pbb+jzP37BhLfPmzc5x34QJo7l7984bn/+23Ny64+d3o0j6FoS8hMREoNBNQD+j\nIqaGYnZSUalfv4HG9sOH9wkJeaidYLRMDCZLgKS0FMIyAyG9HN0aNNN2OEIpJJfL6datp0abn98N\nvL03aykiQSg99OQ66GSYkCFPIEOh0HY474Rp02apk4dt2LCW58+fF1rfy5atpm7deoXWnyCUJieD\nskqC1Dayy+NI4W28/34XjVrfqamp/PXXYS1GpD1iMFkC/BHgAzIF1XQdKKejo+1whFJq5MgvqFVL\nszDx7t073tlpF4JQECYyCyRSJbfDH2k7lFItLS2Vzp3bkpaWVa5oy5bf6NXrQ/X+pUsXsm3bFsaO\nHcHRo4f48ceZPHoUwrhxI9Vv8xITE/jmm/H06dOVr74aS3JyzgPNjIx0pk//Hnf3HowY8QmRkRGA\n5ptBL69f6datM599NpQ9e3bi5tY9z/NfSExMpEOH1sTGxqrbli1bzOrVK1AqlaxduwoPj754ePTF\n03MGKSkpGudfu3aF/v175bi9YcNaFi2ay7ffTqRnzw+YPXsa5875MHz4EHr2/IBz53wASE9PZ+nS\nhQwY0Ac3t+54ef1agO+G8C66E3sXgLY1RGmcomRuXoGaNTVreOY1I6KsEoPJEuBa1FVUKugtEu8I\nb8HAwID33/9Io+3SJV8OHz6opYgEofSobFAJgNvPQrQcSemmp1eOOnXqcefOPwD4+9/AyqoiYWFP\nAfDzu06TJi+Xc3z//XQAVqxYq64LeemSLz/8MJsdO/YRGxvDmTOncrzWlSuXGD16HDt3/ompqRkH\nD/6psf/+/WC8vb347betrFq1jhMn/i7Q+UZGRjRu3ITz533UbT4+p+jQoTMnTvzNxYvn2bBhC5s3\n7yApKZHt238v0Nfq/PmzTJnyA15e2zl58ji+vufZsGEzQ4d+yu+/bwLA29uLBw8e4OW1jc2bd3Dq\n1HH1QFMQ/is1I41EaRiStPI4VLbRdjhlXu3adTS2AwPfzSQ8YjCpZdceB5KuG4tBmg121pW0HY5Q\nyo0b9yWVKr38d6RQKPD29tJiRIJQOthZ2AIQEh+q5UhKv8aNm3Lzpj9KpZLw8DBat25LQIAfz58n\nER0dnS1xxX85O7fG2NgEuVxOzZq1sr0xfMHRsRHW/35u2tnVISLimcZ+P7/rNGrUBAsLC/T09Oja\ntUeBzgdo376jem3n3bt3kMvl1K1bjwsXztKlSzf09fWRyWR89FF3Ll++mL8v0L/q13fEzMwcExNT\nKlSwoGXLVgDUrFmbqKis9bvnzp2hTx83dHV10dfXp0uXrpw+faJA1xHeHWeCb4IsE2ud6hp1EIWi\nYWen+bPs/v0gkpOTtRSN9ojBpJYdvJf1hLFVJZF4R3h7FhYWdOr0gUabj8+ZAv+SIwjvmoY2NQCI\nSs8+oBAKplGjJty8GUBwcCDVq9ekfn1H/P39CAjwx8mpcZ6/5BoYGKr/LpXKck0kZmj46nFSlEql\nxv7ExASMjIzV25aWVgU6H8DFpT3Xr18hLS0NH59TuLp2AiA2Ng4jIyP1cUZGxsTGxrz2vv7r1dJN\nUqlUXb9TKpWpY0lMTGL58iXq6bQ7d24jNTW1QNcR3h1Xnt4CoLG1g5YjeTe0b98BmUym3o6IeMbp\n0ye1GJF2iMGkFiWmPidcGQjp+iLxjlBoRo8eh4mJqXo7JSWZDRvWajEiQSj5LIyMkKQbkiKNFeuM\n31L9+o4EBt7Fz+86DRo0xN7egdu3b+Lvf4MmTYrvs87Q0FBjHWN0dFSB+zA2NsHe3oGrVy+rp7gC\nmJubk5AQrz4uPj4ec/MKGufKZDKNAWpiYmKBr29hYcFXX03G23s33t672bnzT2bNmlvgfoR3Q1jG\nA1SZctrZ1dd2KO8ER0cnbG2rabRdvXpZS9FojxhMatGegLMgy6S6ngO6crm2wxHKiNq17ejQoZNG\n24kTx9/pgrqCkB+GVAB5Oo9jCz7oEF7S1dWlcmUb/vrrCA0aNMTAwACpVMqlS740bZp9Fo5MJiMp\nqeADrbzY2ztw/foV4uLiSE9P5/DhA2/UT/v2Hdm//w8yMjKws8taI9WqVVuOHj1MamoqCoWCgwf3\n4ezcWuO8ChUsiI6OIjY2hszMTP7+u+CZHtu2bacu86RSqfjtt/X4+p5/o/sQyrZ7z0JR6jynvKIS\nhnp62g7nnSCVSnOsN/muEYNJLVGpVFyPuYpKJaGPg0i8IxSuTz/9HH39l1Oo4uJiWbNmpRYjEoSS\nz6pcRQACwh5oOZLSr3Hjpjx4EKz+Rcve3oG4uFhsbKpkO7ZDh86MGjWc48f/zrbvbbz3Xn26dOnG\np58OYsKEUbRu7fJG68hcXFw5f/6seoorgKtrR5ydWzN8+GCGDu2PlVVF3NwGaJxXpUpVPvqoB8OG\nDWLMmM80Eg/lV58+/ahYsRJDhvTDw6MvISEPcXQUWTqF7E7dzyoJUte0Th5HCoUpexKee+/c7BaJ\n6h2748jIwn/6+SYuh9zlt+ANGKRWYeFH47UdjlAGDRrUj7//PqLetrauxPHjZ7G0tNRiVIJQcu25\ncYHjMX9QV6cF49v21XY4QiFQqVTqAeT582dZt+5nNm701nJUglD4Jh39iWSdML6q/zW1rCpqO5x3\nxu7dOxg9+jP1tq6uLidOnKNOnbpajCpvlpZGeR+UT+LNpJYcCsxKvNOmcgstRyKUVR4egzUWhoeH\nh7Fq1TItRiQIJVuDStUBCE8J124gQqGIjY2la9dOhIeHoVKpOHHibxwcHLUdliAUuqS0ZJ7LniFL\nMxEDyWLWqdP7mJmZqbfT09M5fvwvLUZU/MRgUgviU54ToQqGdAM+rN9E2+EIZdRHH3WnRQtnjbYj\nRw6+k2mrBSE/alpWRKXQIVEZre1QhEJgZmbGiBGjmTBhNAMH9iEhIYHhw0doOyxBKHQnA/2RSJVU\n1q2h7VDeOSYmptSqpblu8t69u1qKRjuKNOvLggULuHr1KgqFgpEjR3LgwAFiY2MBiIuLw8nJidmz\nZ3PhwgXmzZuHTCZj4MCBuLu7s2LFCvbv30/FillPWHr06IG7u7tG/+vXr+fIkSNIJBLGjh1Lu3bt\nivJ2Cs2egDMgy6SmvL5IvCMUGYlEQp8+7pw/f1bddv9+MGvXruLLLydpMTJBKJlkUil6mWak6UaQ\nkJKM8SvrjsuSO3duU6/ee9oOo1j06uVGr15u2g5DEIrU9We3QQLNbUQWV22oXduOK1cuqbeDgu5p\nMZriV2QjGV9fXwIDA9m+fTuxsbH07t2bU6dOqfdPmTIFd3d3FAoF06dPx8vLCxMTE3U7wNChQxk8\neHCO/T9+/JhDhw6xbds2kpKS8PDwoE2bNhrT+koilUrFjdhrqGQS+jQUiXeEojVo0FC8vDbi739D\n3XbgwJ+MH/9Vif+/IgjaUEHHkjBJBP5PH9CmVtmq1fbs2TNmz/6BI0cO8eOPC+jXb6C2QxIE4S2p\nVCoiFCGoJDq0qf1uPCQqaV5keX4hODiYpKQkypcvr6WIileRTXNt1qwZy5Zlrc8yNjYmJSVFXXj4\n/v37JCYm4ujoyK1bt6hWrRrW1tbo6+uzdOnSfPV/8eJF2rZti66uLubm5tjY2BAUFFRUt1NoLj26\ni0InnvIZVajxnwLKglDYZDIZ3bv31GgLCPBj8+bftBOQIJRwVY1tALgb9UjLkRSezMxMli1bTNeu\nndixYysJCfGsXr1CowajIAilU8DTB6h0UjBR2ojZblrSoUNn5K987aOiIjlxonCzU5dkRTaYlMlk\nGBhkTRHatWsXLi4u6jchXl5e6jeOoaGh6OjoMGHCBAYMGMCBAy/rQB05coRhw4YxcuRIHj9+rNF/\nVFQU5ubm6m1zc3MiIyOL6nYKzeF/E++0tWmp5UiEd8Xnn4/ONp9/z56d71zqakHIj3qWWQWonyQ+\n1XIkhePEiWP06vURnp4zefQoRN1+69ZN5s/31GJkgiAUhjMP/ACwN6+n5UjeXe+950C1atU12m7c\nuKadYLQgX48wVCoVMTExQNagrSB1mo4dO8auXbv49ddfgawsR1evXmXGjBnqvsPCwvD29iY1NZU+\nffrQunVr2rVrR8uWLWnWrBkHDx5kzpw5rF279rUx5kdhpsItqOikBCIJRpJuwJB2LuiIJ0hCsTCi\nT59eLFy4UN1y+fJFfHz+pm9fUf5AEF7lauzApmAJ8ZlRWv28eFtPnjzhu+++Y+/evTx//jzbfgMD\nA9LTk0v1PQqCAA+Tg1HJwK15a/H/WYscHN4jOPjlDMlHjx68M9+P145m/P39Wbt2LRcuXEBPTw+V\nSkVGRgbOzs6MGDECR8fXp9j28fFhzZo1rF+/HiOjrC/o5cuXNc6rUKECDRo0QF9fH319fezs7Hj8\n+LHGMR06dGDRokUafVtZWfHgwcvC0s+ePcPKKu9po9qsM7n6/F6QKqlVrgFxsWJ6kVB8hg//gi1b\nficsLOttS2ZmJmvWrMPF5X0tRyYIJY88w5hUnVjCnsUhl5autcUKhYLly5ewZcsmnjx5nOMxLVo4\n8+WXk+jQoVOJqb0sCELBxSQnkiyLRCfNHAP0xP9nLapaVTOT7q1b/xARkVCgF3DFqVjqTC5btox5\n8+bRu3dvfHx8uHDhAr6+vvj4+NCrVy/mzZvH8uXLc+04MTGRBQsWsHbtWkxNTdXtAQEB1Kv38lV8\no0aNuHPnDmlpaaSnpxMSEkKVKlWYM2cOV65cAeDSpUvY2WlO02vZsiWnTp0iPT2dZ8+eERERQe3a\ntd/4C1HUnsRFcvP5JVQKXfo37KjtcIR3jLm5OZ07f6DRdvbsGXx9z2spIkEouYylFkikSu49e6Lt\nUArk6NHD9OjRhXnz5uQ4kLS1rcbUqTPYu/cQHTp00kKEgiAUphP3biCRqLA1qKXtUN55Tk6NNbYf\nPXrInTv/aCma4pXrm0lTU1O8vb2ztRsYGNCpUyc6derEpk2bcu340KFDxMbGMnHiRHXb/PnziYyM\nxNbWVt2mp6fHyJEj8fDwQCKR8Omnn2Jubo67uzvTp09HLpcjkUiYM2cOAJ6engwdOpSqVavSr18/\nBg8ejEQiYcaMGUilJbds5trLO0GWiZNuOyqbmeZ9giAUsjFjxrN//151eZ7U1BR+/XUdLVu20nJk\nglCyVDKoRGxGMLfCQ3ivUjVth5OnkJAQPD2nc+TIIVJTU7PtNzQsT7du3Zk6dZa63JYgCKWff+Q/\nIAPnKq+fKSgUvY4dO1OhggXR0VEAZGRkcOzYUezty36GXYnqNYsNk5OT2bdvH/fu3UMmk+Hg4EDX\nrl3R1dUtzhgLlTamAJwMvMGux97IUs1Z9P43ItuWoDWjRn3Gnj071NsmJqYcPPg3derU1WJUglCy\nHL19nT/Dt1JN4sS3rh7aDidXGRkZLF48n23btvD0ac4Jg5ydW/P119/h4lI66jALgpA/mcpMxh+b\nDioJyzvNRCYruS9U3hXdur3PpUu+6u2BAwezbNnPWowod8UyzfXp06d069aNa9euUbt2bSwsLDh8\n+DDdu3cnPDy80AIo69IUGfxx/09UKnCv3VMMJAWt+uyzz9F/pRB7fHwca9as0mJEglDyNLSpCUBU\nWoSWI8ndgQP76Nq1M0uWLMhxIFm9ek1mzJjDH38cFANJQSiDrjwKAnk65lQVA8kS4r9L8oKCArUU\nSfHKdWTz008/MX78eHr16qXRvmvXLn788cfXrpcUXvr10kEydZKwyKhH2zr22g5HeMc1bdqCtm3b\n8ddfh9Vtx44dJSIiIl8JrAThXWBtYgLp+jyXRms7lGzu3w9mzpwZ/PXXYdLT07PtNzIyonv3Xkyd\nOhMLC4tij08QhOJx/lFWSZD6FuJ3y5LCzk5zlldQUCAJCfEYG5toKaLi8do3k/8dSAK4ubnx8OHD\nooypyCSnF28G1cexEdxM9kWVocvoFn2K9dqCkJvBg4dqFNcNDw9j1aqlWoxIEEoeA5U5yNMIi4/R\ndigApKWlMWfODHr2/JADB/blOJBs27YdW7bsYOnSVWIgKQhlXEhyMCqlhA52DbUdivCvjh3f11gK\nGBsbw7Fjf2kxouKR62BSJss9HbqJSekcYU86OofE9KRiu97aKztBqqSxkQuVTEXSHaFk+OCDj2jR\nwlmj7ejRwznWohOEd5WVXlaiGr+nD/I4sujt2bOLrl07sXz5Ep49y77MpFat2syZM59du/7E2bm1\nFiIUBKE4hSfEkqEbi16GJZbGxtoOR/hXnTp1qVatukabv/8N7QRTjHIdTKalpfH48eMc/+T0RLQ0\niEyOYcPNLWQqM4v8WsfuXSNWFoI8tQKftBClQISSQyKR4ObWX6Pt/v1g1qxZqaWIBKHkqW5aBYDg\n6JxrNRaHu3fv8PHHAxk3biT+/n7Z9puYmDB06DAOHz7OiBGjS2w9M0EQCteJwOsA1BAlQUoUiUSS\nbaprYOA9LUVTfHJdMxkZGcnHH3+c477S+oHV3MaJS6E3+CPoIG51ehTZddIy0vnzwQFUcgn96vRG\n/pq3vIKgDQMGDGLTpg3cuHFd3Xbw4H4mTPhaYwqsILyrHKyrcyoOwpLDiv3aKSkpzJ/vyc6d24iM\nzJ4ESCKR0K6dK99+O4WmTVsUe3yCIGjXreg7IIc21cUU15KmVi3NmvfBwYEolcoSXb7wbeX6W+OJ\nEyeKM45i8UWLj3l0NIyTT85S1ciGFpWaFMl11l8+QKZOElYZ9rSuXadIriEIb0Mmk9GtWy+NweTN\nm/5s3vwbw4Z9psXIBKFkqFOxEqpbchKUUcV63R07trJ69Upu3QrIOa46dRk+fCSffDK81D7YFQTh\nzWVkKoiTPIF0A5yqVtd2OMJ/NG7cVGM7JCSEgAB/GjZ00lJERS/XYXJGRgaHD7/M+Hjq1CnGjBnD\n/PnzSU5OLpbgCpu+TjlGNhiKvrwc3nd3E5JQ+NOXQmKecTv5EmToMbpl30LvXxAKy4gRo6n9n4cd\ne/bs5DWlZwXhnSGXydBTmKLQSSQ5Pa3Ir3fr1k2GDOnPxIlf5DiQNDMz59NPP+fw4eMMG/aZGEgK\nwjvqwoN/QKbAUmpbpt92lVaurh2xtKyo3s7MzOTUqbL3gu5Vuf4r9PT05OTJkwCEh4fzzTff4Orq\nio6ODvPmzSu2AAublYElwxw8yFRm8kuAV6En5Fl7NSvpTlPjdlQ0EYuihZKrXLlyfPhhV422y5cv\nsn//Xi1FJAgli5ncEokEAp4+LLJrPH/+nKlTJ+Pm1oOjRw+jUCg09kulUjp27MyOHX8wb95ijIzE\n54ogvMsuPsl62NTQ6j0tRyLkxMDAgFq1NNeyBgbe1VI0xSPXwWRAQAALFiwA4MiRI7i6uuLu7s5X\nX31FcHBwsQVYFBwq1KNbzQ+IS4tn/c3NhZaQ5687V4iXPUKeasGQ5q6F0qcgFKWxYydQubKNelup\nVLJt2+9ajEgQSo4q5SsDcCcipND7VqlUbNmyiY8+6sgvv6wmOjr7dFp7+/dYvHg53t67aNiwUaHH\nIAhC6fMk9T4qpZSOdcR6yZLKzs5OYzsoKFBLkRSPXAeThoaG6r/7+vrSqlUr9XZZSNDxQTVXnCwb\nEBT3gN1BB966v5SMNPaHHESlkjCgbi+RdEcoFczMzOnc+QONtrNnz3DunI+WIhKEkqOuVTUAHic+\nLfC5Xl4bc93n738DDw83vvlmAv/8czvb/goVLBgxYjSHDh1n0KChYkqrIAgAhMREoNBNwCC9IsYG\n+toOR8hF3br2GtvBwUHExpaMmsVF4bVrJlNTU4mJieHSpUu0adNG3V4W6tFJJBKG2PejsqE1p5+c\n40LYlbfqb/2l/Sh1nlNR8R7OtUTSHaH0+OKLCZibV1Bvp6am8ttvG7QYkSCUDI421VCpJMRkZM+o\n+jr79+9jxoz/sWfPLo32xMQEJk/+Cje3nhw//jdKpVJjv1wu5/33P2TXrj+ZM2e+xkNdQRCEk0HX\nAKhlbJfHkYI2de7chXLlyqm34+Pj+Pvvo1qMqGjlOpjs378/Xbp0oUePHvTp0wdLS0vS0tIYPXo0\n7dq1K84Yi0w5uR4jGnyMvlyfbXf3vHFCngfR4dxJufJv0p3ehRylIBSt6tVr0KFDJ422U6eOc/fu\nP1qKSBBKBqNy+sjSy5Mmi833cojnz5+zZMl8kpKSWL16OWlpaahUKjZuXM+HH3Zk48b1xMXFZjvP\nwaE+S5euYvPmbTg41C/sWxEEoQy4E5tVs7BdzbKbGbQsqF69BtWr19BoCwjw11I0RS/XwWSvXr3Y\nvn07v/76K1OnTgVAT0+Pzp07M27cuGILsKhZGlTQSMiTkJ5Y4D5+ubYDpEqam7hiJZLuCKXQ8OEj\nMDB4+RYkPj6e1atXaTEiQSgZjCQWIMskODI8X8fPnDmVW7duAuDnd4OvvhpH//69+e67r7l3L3sS\nBktLK8aMGc/Bg8fo12+gmNIqCEKOUjLSSJSGIUkzwr6STd4nCFojkUioVeu/6ybvaSmaovfanMIV\nK1akTh3NKZv9+/cv0oCK0pgFJ7h5Pzpbu0OFuvSo1SUrIU/AZhRKRQ5n5+zIP5dIkD1BJ9WSwc3a\nF2K0glB8mjRphotLe/V2hQoWyOVi3a8gWBtYA3Az/EGex/r4nGH37h0abTt3buPUqRPZSu7o6Ojw\n4Ydd2bPnADNmzMHAwKDwghYEoczxCboJskysdaqJh06lQJ06dTW2g4ODyMwsnISfJU2umXTq1auX\n7R+rkZERPXr0YNKkSejp6RV5cIUtNCKRJTv8cKptwYCOtbEye/nh3dm2PY8TQ7kW4c/uwP30r5v3\ndNWUjFQOPjqESibBo15vZDJR70covQYP/phbt27SqdP7fPHFeGxtq2k7JEHQutrmVbkbcYEHcaGv\nPS4jI4N582aTmJj37BZHx4aMGTOePn3cCytMQRDKuCthtwBoUslBy5EI+dG0aXON7UePQrh+/RpN\nmzbTUkRFJ9fB5K1bt7K1RUVFsXnzZpYsWcKUKVOKNLCisPSr9qzacYMbQVHcfBDNB81t6epcjXK6\nciQSCYPt+xH+PIIzoReoalSFVpVf/w3/5eJ+lDrJWCvq07xm7WK6C0EoGp07f0CbNi7iDYkgvKJB\n5RocjICI1NdPc1248EcuX7742mMqVrSmf38PJk2aUiofyAqCoD1hGQ9QSeW41BZrqkuDtm3bUbGi\nNc+eZX12KJVKzpw5WSYHk7m+SpPJZNn+VKxYkW+++YaAgIDijLHQ1KhswrcejRjV0wFjQ10OXgjh\n+1988b0VjkqlQk+my0jHjzGQ67P97h4exD/Kta/gqKfcTb0K6eUY7SyS7giln0QiEQNJQfiPKmbm\nkFGO5+Se1v3mTX+2bPF6bT/W1pXYtetPpk6dIQaSgiAUyN1nT1DqPKe8ohKG4udHqVCuXDlq1343\n6k2+0bzM0lxnUiKR0Ny+Ip6ft6RH6+okpSj4Zf9t5v1+jZDwRCz0K/Bp/UFkqpSsC/AiPi37lCWV\nSsW6azuRSJW0NOuApZGRFu5EEARBKGoSiQR9pRkqnRSikhKy7VepVMya9QNRUZGv7Sc8PIw//tj1\n2mMEQRBycvr+DQDqmorSc6VJ7dqa36+ymoSnwIPJK1euoK9f+gul6unI6NW2Jp6ft6BJHUsCn8Qz\n67fLeB25Q5Vy1elZ60Pi0xNYfzN7Qp7D/1wkUR6KbooVHk1dtHQHgiAIQnGw0KsIgF/o/Wz7Vq9e\nwalTJ/LVz7ZtWwgJCSnU2ARBKPsCE7LeaLWvJUqClCZ169bT2L5/P5ioqCgtRVN0cn3F6OHhkS0B\nT3x8PCqVip9//jlfnS9YsICrV6+iUCgYOXIkBw4cIDY2q75WXFwcTk5OzJ49mwsXLjBv3jxkMhkD\nBw7E3d2dxMREvv32WxITE1EqlcyePZtatWqp+37y5Andu3enfv2sueNmZmYsX768wF8AS1N9vujT\ngFsPY9h6LJBTN55y6Z8IerWtRWOrhlyL8GNn4J8MrNsHgOfpqRx+fASVTMIghz4i6Y4gCEIZV93Y\nhscJNwiMfkRHXv4y9/jxIzZs+CXf/cTFxTNz5lR+/XVzUYQpCEIZlJSWzHPZM+RpJtSyqqjtcIQC\n+OCDD5k16wdSU1MASEhI4O+/DzNw4BAtR1a4ch1MTpw4MVuboaEhdevWzdc0V19fXwIDA9m+fTux\nsbH07t2bU6dOqfdPmTIFd3d3FAoF06dPx8vLCxMTE3X7xo0bady4MZ9//jmnTp1i+fLlLFu2TOMa\nNWrUYPPmwvlQdqhuzoxhzTh5LZS9Zx/gfSyQylbVsagTxtlQX2zL29DapgW/XNyHUieZypmONK1e\ns1CuLQiCIJRc9tbV8EmAp8/DNNpnzJiKoaEhTZs2p3x5I8qXL4+hYXmMjLL+Xr68EUZGRlSqAUVZ\nYAAAIABJREFUZEO1arZYWFhhamqqpbsQBKE0Ohnoj0SqxEZP/M5Z2lStakvNmrW4ffumuu3mzdKZ\nd+Z1XpvNddiwYa89eePGjbke06xZMxwdHQEwNjYmJSWFzMxMZDIZ9+/fJzExEUdHR/z8/KhWrRrW\n1lm1vJYuXQrAyJEj1W9Gzc3NiYuLK/jdFZBcJqVzs6q0eK8ie84E4+MXBnH1MHSMY/u9vaSmqwhM\nu4ZEUY4xbUTSHUEQhHeBvXUVVP/IiM/UnJ60YcPrk+4IgiC8revht0EKzSqLLK6lkZ2dncZgMjCw\n7CXhyXUw+fz5cwYNGsSwYcNo1aqVOstjcnIy58+fZ+PGjbRq1SrXjmUymfqcXbt24eLigkyWVQTd\ny8uLwYMHAxAaGoqOjg4TJkzg2bNnDB48mG7dumlku9u0aRPdunXLdo2oqCjGjx9PREQEHh4e9OjR\nI88btrTMO1mOpSVMql6B3o/jWPuHP/fuOaJb9wp7HuxBIoWONh9St4Z1nv0IQlmRkZHB4sWL2bhx\nI6dPn8ba2hqlUsngwYMZO3Zsrj8LYmJi8PT05ObNrB+kcrmcjz/+mH79+gFQt25ddX9vKioqCj8/\nPzp27Jhtn5+fH3p6etSrVy+HM7VvyJAhuLm50bNnT22H8loff/wx3377LUlJSUydOpW///5b2yEV\nO91MU9J1YjAy0aWcrsimKAhC0VOpVEQoQ0CpQ6+WzdHTKb0JMN9VDRo4sG/fH0DWyzGpVJWvsUhp\nkuu/yrFjx+Li4sKaNWv49ttv0dHRAbJ+qXR2dmby5MnqN4+vc+zYMXbt2sWvv/4KQHp6OlevXmXG\njBlA1n+UsLAwvL29SU1NpU+fPrRu3RozMzMAFi5ciK6uLu7umsWdTU1NmTBhAj169CAxMRF3d3da\ntmyJlZXVa+OJjMy7oPQLJuVkTBrghO+tSmz1TyHT+ha6Kdb0dGhRoH4EobT75pvx2NtnFUqOjk5C\nJkv8t/1/TJw4Bm/vXejplct23vTpP1CxYiW8vHYglUp5/PgRo0YNw9LShvr1HbP19yaOHTvFlSuX\ncHRsnm3f779vw9HRiQoVbN64/6KUnq4gMTG1xP88WbRoJQBPnlwhM1NZ4uMtCiZSC6Ik0ZwOuE1j\nW1FXWBCEoucXeh+VPAWT9BokxKVoOxzhDbi4dGLkyFicnBrRsWNnTE3NSsRnaGEOaF/7iMPR0ZGf\nf/4ZpVKpnmZqamqKVJq/pDM+Pj6sWbOG9evXY/Rv+YzLly9rDEIrVKhAgwYN0NfXR19fHzs7Ox4/\nfoyZmRnLli1Tv9n4r/Lly9O3b18ga6Rfv3597t+/n+dgsqAkEgnO9a1pWNuDg/7XaNOoHrJ83r8g\nlBWffPIZ9es7snHjOo32qlVtcXBowP79e3FzG5DtvODgYFxdO6l/ZlStasumTdvVD4sALlw4x759\ne4iOjmLAgMEMHJg1a2Hnzm3s27cbpVKJrW01Jk+ehpmZGZ6eMzA2NubKlUt07tyFrVs3k5mZSUpK\nMjNnzlX3u3fvLo4cOcjZs2eIjY2hf/9B/Pbbev766zDp6em0bdueceO+RCaTMXbsCBo0aMiZMyf5\n7rtp/PnnH1hYWHLzpj8PHgTTvXtvKle2YefOrSQnJzN79jz14BqyihH37v0h8+cvpV49ewB27PDm\n1q0AZs6cm+u9vBAW9pQBA3pz+vTFbNuHDu3n/HkfdHR08fO7jq1tNYYN+5zVq1cQGvqEzz4bRc+e\nfVCpVLne36siIyOYM2c60dFRpKen07Hj+4wc+QUbNqwlPDyM+Pg4goODsLKy4scfF2FmZo6bW3em\nTZut0Y9CoeDLL7+gVau2DBw4GB+fU6xbt5qUlFSqVKnC9OmeZWp9YJXylYhKvcvtiBAxmBQEoVj4\nPPADwN68rpYjEd6Uk1NjnJwaazuMIpWvUZFUKsXc3Pzf17P5G0glJiayYMEC1q5dq/ELRUBAgMaU\ns0aNGnHnzh3S0tJIT08nJCSEKlWqcOXKFfz9/fH09Mzxmr6+vsydm/WLY3JyMnfu3KFGjRr5iu1N\nGJTTwb15CyqZmRTZNQShpHrxFjEn7dq5cuLEsRz3OTu3ZtGieWzevJF79+6gVCqxsLDQGOCEh4fx\n669bmD9/CevWrUahUHDzZgBbt25mxYq1eHvvpmJFa9auXak+58qVy/zyyyYGD/6EPn360b59R42B\nJECvXm7Y2zswZsx4BgwYzNGjhzhx4m/WrfNi+/a9PH36hL17X9b9u3v3Dps376BBg4YAXLx4ngUL\nlrJ8+Rq8vb2Ii4vFy2s77dt3ZNeubRrXkkqltG3ryrlzZ9RtZ86cokOHznneS35cvOjLsGGfs23b\nH4SEPMTb24tVq9bx3XfT2LRpA0Ce9/fCjh1badiwEVu27MTLaztPn4aqU5WfPn2SiRMnsXv3ASpX\ntmHz5o25xrR06UKqVrVl4MDBhIY+Yfbs6cyY4cnOnfto3Lgpixb9WKB7LOnsLGwBuBtbNuuECYJQ\n8jxICkKlgg52jbQdiiDkqshesR06dIjY2FgmTpzIkCFDGDJkCE+fPiUyMpIKFSqoj9PT02PkyJF4\neHjg4eHBp59+irm5OVu3biUsLIyPP/6YIUOGMHbsWAA8PT15/PgxTZs2JT4+nv79+zN06FBGjBhB\nxYoiZbIgFLf33qvP7ds3UalU2faNHj2OESPGcPHiBUaM+ISePbvw22/rUSqV6mPef/9DAOzs6pKe\nnkZcXBwXLpylffsOmJmZA9CtWy8uXfJVn9O0aTONddX5ce6cD1279qB8+fLI5XK6devF6dMn1fud\nnVtrPLhq2rQF+vr61KhRC6VSSevWbQGoVat2jnWiXF07cvbsaSCr9FFQ0D1atmyd573kR/XqNbC1\nrYauri5VqlSlefOWyGSyf2OJzNf9vWBmZsalS774+d1AR0eHmTN/xMLCAoDGjZtQuXLWlGAXlw4E\nBPjnGM8ff+ziyZPHfPXVZAAuXrxAo0aNqVkz641dz559OXv2DJmZmQW6z5LMuUY9pKmmxMgecOze\nNW2HIwhCGReTnEiKTiQ6aRWweWUmiyCUNEW2krd///70798/W/u0adOytXXs2DFb8ozFixfn2O//\n/vc/9d/nzZv3llEKgvC2zMzMUSgUJCYmYGys+eZeKpXSo0dvevToTUpKCufPn+WnnxZgampGr15Z\n09QNDQ0B1G8rlcpM4uJisbCwVPdjZGRMXFysxnZBJSUlsnXrFv78M2shfGZmJqamLz+gjY01+3yR\nQEwikSCVStHXN1DfU06DJCenxkRGRhIeHs6VKxdxdm6Dnp5enveSHwYGhuq/S6UyjVheDMzzur8X\n+vXzIDNTyZIl84iKiqRPn358+umIf78GL79/RkZGJCZmX9cRExPNmjUraNPGRV0mKikpET+/63h4\n9FUfV758eRIS4tWD6NJOT0fOALu+/B7yK3sf7qOFbT2MyhloOyxBEIqAzwN/QuMjtBpDSHwYEgnY\nGoiSIELJludgMj4+njVr1hAZGcmiRYs4ceIETk5OmJuXjV8QBEEoGsnJyVy/flX9Rk9fX5+OHTtz\n+/ZN7t8Peu255uYViI+PV28nJMS99aDEwsKSNm1c6Ns3+0OuwiCTyWjbtj3nzp3h0qULdOuWlaE1\nP/fyYlCoUqmQSCQkJiYU+Pr5vT+5XM6QIZ8wZMgnPHoUwjffjMfRMWtq76slmLIeDmQftOvq6rJh\nw+9MmDCK06dP0q6dKxYWljRt2pw5cxYUOO7SpLVdXc6EOPFEfp0VF7bzvevry2cJglD6+IXeZ9uD\nLdoOQ6111YbaDkEQXivPaa5Tp06lUqVKPHnyBMjKxjp58uQiD0wQhNIhLi4WuVxO+fKamcEkEglz\n587k0KH96raYmGiuXLmIk1OT1/bp7NyaM2dOEh+fNbjZt28Pzs5tcjxWLpeTlJRzZrRX97Vp044j\nRw6RmpoKwN69uzl8+ED+bjKfXF07cu6cD//8c5sWLVrl+15eJDYLDs4aZB85crDA187v/S1Y4Mnl\ny1nTbG1sqvy77CCrpq+//w2ePQsH4OTJ4zRsmH2dTvnyRlhbW/P999NZsmQesbGxNG/ujJ/fDUJD\nsz4nbt++ydKliwp8D6XB2Na9kaQaE6r6hzPBOU8DFgSh9Npx+zAAVTOb0Ei3s1b/dDJ1p0VNuyK7\n11OnjvPJJx54ePRl9Ojh3L8fhFKpZMyYz7h8+WKu540dO4KePbvg4dGXgQP7MHiwOzt2bM31+AkT\nRnP37p2iuAWtmD37B86ePZP3ge+IPN9MxsTEMHToUHVdsS5duvD7778XeWCCIJQMMTHRjB07Qr09\nbtxIZDIZy5atxtLSilu3bmJv75AtUZa+vj5Ll65mzZoVeHlllQaSy3Xo27cfHTp0eu0133uvPoMG\nfcwXX3yOUqnEzq4OX389JcdjmzdvybZtv/PZZ0NZv16ziLyLiys//7yMp09DGTv2Sx48CObTTwcB\nWQOp777LPu3+bTRu3JSZM/9Hy5at0NXVzfe96OmVY/jwkXz99TgsLCxxcyv421MXl/b5ur9evfqy\ncOGP/PTTQlQqFa1bu9C0aXP8/W/QrFkLliyZT2DgPSpWtGbixEm5Xq9hw0Z06vQBixfPZc6cBUye\n/D++/34SCkUGBgYGjB//dYHvoTQw0i9H35q92Rm6iZ1Bf9Ckah0MdbOXxREEofQJCHtInCwEWaoZ\nk7q4l+ns/eHh4SxaNJf16zdjbV2JHTu2MnfuLNat82LKlB9eW/YLYMyY8XzwwUcAREdHMWrUp9ja\nVqNly+x1p5ctW12k91Lcpk2bpe0QShSJKqesGa8YNGgQv/32G8OHD8fLy4uoqChGjhzJ7t27iyvG\nQlUSarsIQlkyY8b/eO89B/r189B2KMJb2LBhLZGREYU+wC6rZv+1mXB5ANVkDfi23RBthyMIQiGY\n+vfPxMoe4mraC7fG2QdFZUlUVBQPHgTRrFlLAO7fD2L06OEcPZqVSO6HH6bg6Ngwx7JfY8eOoHv3\nXurBJMDPPy8jMzOTceO+ws2tO1279uCvvw7z008/M3bs50ybNpuGDZ04fPgAmzZlPWB2cHBg8uRp\n6Orq5qu8VFjYU0aN+pSOHTtz795dVq78BX//GyxfvoTExARMTEyZPn0OxsYm9OzZhd27D6jLcC1b\nthhdXV1GjRqb7zJhCoWCFSuWkJ6ejkqlYvjwUXTo0Enj/q9du8LKlT+RmpqKoWF5vv56MvXqvfdv\nWa+zGBoa4ud3A7lcxqxZ86hZs1aRfD8LqjDrTOb5yGXw4MG4ubkRFBTEqFGj6NmzJ8OHDy+0AARB\nKL1CQ5/g73+D7t17azsUQShW49u4IUkrz0NFAL4Pb2s7HEEQ3tLt8BBipA+RpZrSu2FLbYdT5Cws\nLNQDSYVCwaFDB2jTpp16/+vKfuVEoVCgo6Or3o6IiGDr1j1YW1ur28LCnrJq1TJWrlzL1q27SUlJ\nZdeubQUqLxUfH4edXV1WrvyF5OTnTJ78FSNHjmH79r24uw/ghx+mYGRkROPGTTh/3kd9no9PVrmu\ngpQJW7VqGePGfcWWLTuZN28JZ85oZkhPTk7mhx++Y+LESXh772bQoKHMmDFVnRjP1/ccvXu7s23b\nHho1asrOnblPBS7N8hxMfvjhh6xdu5Zp06bh7u7OH3/8wUcffZTXaYIglHFKpZK5c2cxefJU9PX1\ntR2OIBQrEwN9uttmJVnyvruLlIw0LUckCMLb2BZwGIkE2lRsh0xWdqe3/teOHVvp0eMD/PyuM3r0\neHX768p+/Vdo6BNOnjyOi0t7dVvr1tnzHFy65EuDBo5YWFgikUiYPn0O/fp5FKi8lEKhUF/Hz+86\nVlZW6kFx585dCA19THh4OO3bd1Sva7x79w5yuZy6desVqEyYmZkZR44cJCTkIVWr2jJjhqdGLLdv\n38TS0gpHRycA2rfvSHx8HGFhTwGoXr0m9erZA1C3bl11ToKyJs81k0FBQezbt4+vv85a/zJlyhSG\nDRtGnTp1ijw4QRBKLqlUysqVv2g7DKGQDB8+UtshlDofODTkwpNrROr8w2rfPXzVdqC2QxIE4Q3c\nffaYKOl9ZKkm9GlX9t9Kvqpfv4G4uw/g2LGjjB79KVu27EBPr9xry34B/PzzcjZt2oBKpaJ8eSPG\njp3Ie+/VV+83Msp+Tnx8nEayvhf1ogtSXkomk2FoWB6AxMQkQkOfaJyno6NLXFwsLi7tWbnyJ9LS\n0vDxOYWrayf1tfJbJmzKlB/YtGkDEyeOQU9Pj5Ejv1D3A1kJCP9bqqx8eSNiY7PKf72IE7LKemVm\nKimL8hxMzpw5kwkTJqi3+/bty+zZs9m8eXORBiYIgiAIJd341v2YdnYhQarrXH3chCZVxYNWQSht\nvAMOIZFCaysX5P/WPC7rHj58QGRkBM2atUAikdC5cxd++mkhjx6FYGdXN8/zX03Ak18mJqbcvPky\nC/bz50mkpaW9cXkpCwsLqlWrwYYNOY9J7O0duHr1Mj4+p5g6dda/5+S/TJi5eQW+/PJbvvzyWy5d\n8uV//5ukztT+Yv+rpb9UKhWJifGYm5vz6NHDAt1LaZbne/zMzEyaNm2q3m7atGm+XnkLgiAUxKup\nto8f/4vnz5MA8PScwW+/rddmaNlERkYwZEg/bYchlADm5Q3pUqkbEgl43d5BWmaGtkMSBKEAAiOf\nEikJRppmTB8nZ22HU2zi4mKZM2c6UVGRQFZpKIVCQeXKNur9OZX9ehvOzq3x9/cjLOwpKpWKhQvn\ncuDAvjcuL+XgUJ/o6Chu3boJ8O/ay2nqcUr79h3Zv/8PMjIysLPLetCX3zJaCoWCsWNHEBUVBUDd\nuvWQyeQamevt7R2IiYlWD5CPHTuKpaUVlSpVftMvUamU55tJIyMjvL29adGiBUqlEh8fHwwNDYsj\nNkEQ3iGvptresGEtDRo01JgiUpJYWlqxefMObYchlBDdGzbl4uEbxOrd45cLexnXxl3bIQmCkE+/\n+x1EIoWWFdqiK8/z1+Iyw8mpMUOHfsrEiWNQKpXo6Ogyc6an+nM3t7Jfb8PKqiLffvs/xo8fjUwm\nxd7egf79B6Gnp/dG5aX09MoxZ858li5dQHJyMnK5Dp9/PgqJJKt2souLK0uWzGfw4E/U5+S3jJZc\nLqd7915MnDgayKqd/eWXkyhX7mWpFH19fWbNmsuSJQtITU3B1NSMmTN/VF//XZFnaZCYmBgWL16M\nv3/WqLtRo0ZMnDgRc3Pz151WYonSIIJQvNLSUunWrTMHDvyNnl45tmz5jV27trN3b1Zh6KVLF2Jt\nXYmzZ8/QvXsvrl69zKFD+7GxqcL338/gwIG9GBsbExLykPv3g6levQZz5szHwEDzodaGDWuJj48j\nMjKSoKBATE1NmDt3CRYWFoSHh7NgwRzCwp4il8vx8BjKhx92yxarm1t3evd24/jxv4mICKdnz758\n/vnobOnI//e/GQwY0JvTpy+iUqlYufInzpw5hUwmp0ePXnh4DEWlUuWafvxVWenDfdDR0cXP7zq2\nttUYNuxzVq9eQWjoEz77bBQ9e/ZBqVSybt1qTp8+AYCDQwO++moyhw8fwNf3PAsW/ARkzSbp0eN9\nfv55A/r6+ixaNI9Hj0IAmDDha5ydWxf691iAZ/EJzLqwCJVOGqPsR+FYuYa2QxIEIQ/BUWEs9luK\nNL08SzpPeacGk3kRZb/KtmItDWJubo6npyf79+9n//79zJo1q9QOJAVBKH56euWoU6ced+78A2RN\npbGyqqjOdubnd50mTZqrj//+++kArFixloYNszKkXbrkyw8/zGbHjn3ExsZw5sypHK918uRxJkz4\nmh079mJmZs7Bg/sAWLDAk0aNmrB16x4WLlzGsmWL1Nf/r5s3A1i3bhObN+9gz56dBAbeAzTTkb/q\nr78Oc/v2LbZu3cOGDV7s2rWd27dv5pl+/FUXL/oybNjnbNv2ByEhD/H29mLVqnV89900Nm3aAMCJ\nE39z8eJ5NmzYwubNO0hKSmT79t9p186V69evqKfs+Pldx8LCkmrVquPpOQM7uzps27aHRYuWMXv2\nD8THx73+Gya8kYomxnS0+giJRMXGgG0oMhXaDkkQhDz87ncQiURFC/M2YiD5ClH2SyiIXAeTEydO\nBKBdu3a0b98+2x9BEIT8aty4KTdv+qNUKgkPD6N167YEBPjx/HkS0dHR1K5t99rznZ1bY2xsglwu\np2bNWkRGRuR4XMOGjbC2roREIsHOLisNt0Kh4MqVi/TunTX10Nq6Eo0aNeXq1cs59tGlS1dkMhlm\nZuY0bOikXgvxajryV124cA5X147I5XIMDcvz+++7sLd3yDP9+KuqV6+BrW01dHV1qVKlKs2bt0Qm\nk1GrVm31epYLF87SpUs39PX1kclkfPRRdy5fvkiFChbUqVOPy5d9AThz5iSurp1ISUnh2rUr9O+f\n9VS5SpWqNGzoxPnzZ1/7tRbeXO9GLTBOq0W6TizrLu3XdjiCILzGg+hwwglEklae/k3aajucEkOU\n/RIKKtfHMFOnTgXA29u72IIRBKFsatSoCTt3biM4OJDq1WtSv74jJ08ex9jYBCenxnmuL3h1SmtW\neu3stacgK5X4y+OkKJVK4uPj/k1d/nKfkdHL1N3/9WpacCMjYxITEwDNdOSv+m+q8xcfvnmlH3/d\n/enrG2jcA0BsbBxGRi+vY2RkTGxsDIC6nlbbtu3x8TnN0qU/8/x5EiqVilGjPlWfk5KSQuPGzXKM\nQXh7EomEcS3743lpMQHKi9x51oR6FW21HZYgCDn43e8QEomKZmatxFvJV4iyX0JB5fq/x8LCAoCF\nCxeydOnSYgtIEISyp359R378cSZ+ftdp0KAh9vYOrFq1DGNjY5o0KdrBjYmJKVKplISEBPVAMSEh\nPtfp+q9OA01IiNcYXObWf1zcy3NiYqLR09MrUPrx/DA3Nych4WUK8vj4eMzNKwDQvn0HNm/eyJ07\ntzE2NqZqVVsUCgUymYz16zdjYGBQKDEIeatsZkpb8/fxSdzPLze2srDzN8ik70apAUEoLUJinvFU\neRdphiED2rbXdjiCUKrluWaySpUq7Nq1i+DgYB4/fqz+IwiCkF+6urpUrmzDX38doUGDhhgYGCCV\nSrl0yZemTZtnO14mk5GUVDjJsuRyOc2bt2Tfvj1A1lqQGzeu53hdgOPH/0apVBITE42/vx+Ojo1e\n23+bNi4cO3aU9PR0UlJSGDPmM+7fD853+vH8atWqLUePHiY1NRWFQsHBg/vUyXQsLa2oXNmGTZt+\npUOHzur7dnZuzd69uwFITU3lxx9n8uxZ+BvHIORP/6ZtMEytRppONBsvH9Z2OIIg/MeWG4eRSFU0\nNm2Fno54K6lNJaX819ixIzh69JC2wyiV8vwfdOhQ9i+sRCLh+PHjRRKQIAhlU+PGTfn9903q9ZH2\n9g5cuHAWG5sq2Y7t0KEzo0YNZ/LkqYVy7W++mcL8+Z4cPrwfHR0dvvtuKhUrWud4bI0aNfn8848J\nD3+Km1t/ataslWuyHoCOHd8nODiIAQN6o6urR9euPWnQoCEqlSpf6cfzy9W1I8HBgQwfPhiVSkXj\nxk1xcxug3t++fQdWrlzK2LETNe57wYIfOXBgLwDvv/9hrvctFB6JRMIXLfoz/8pSrieeJSiqMbUt\n3q26Y4JQUj2JjSRUeQeJwgCPtu20HY4glHp5lgYpa0RpEEEQcuPm1p1p02ars8gKwtvw8j3BxeQj\n6GdYMb/zl2K6qyCUAHNPbuKJ6haNynXks1YfaDucUm/nzm3s27cbpVKJrW01Jk+ehpmZGZ6eM7C2\nrkRAgB+PHz+ialVb5s1bolGnEbLeTNrYVOGTTz4jKCiQxYvnEh8fj66uHqNHj8PJqVG+yosNGDAY\nyEog1Lv3h8yfv5R69ewB2LHDm1u3Apg5c26u8Y4dO4Lu3Xvh6OikLv0FEBb2VL2d31Je+S0Npk3F\nUhokKSmJBQsWMGrUKDZs2IBCIdKcC4IgCEJ+DWreHv3UKqToRPD7tWPaDkcQ3nlP46N5nPkPpBvg\n0cRV2+GUejdvBrB162ZWrFiLt/duKla0Zu3aler9J08eY9asuWzfvpe4uDjOnMk5ozlkDQJnzPie\nPn364e29m+++m8qMGf8jMzOzQOXFpFIpbdu6cu7cGXXbmTOn6NChc57x5kd+SnkVpDRYWZDrYHLG\njBkA9O/fn6CgIFauLNgXWxAEQRDeZTKplNFN+6NS6HAx9hQhMc+0HZIgvNO8rh1CIlXiWL4FBnq6\n2g6n1Ltw4Szt23fAzCwroV23br24dMlXvd/ZuY26rFetWrVeu2Y/LOwp0dHRdOqU9ba4Xr33sLa2\n5p9/bhe4vJira0fOnj0NQFxcHEFB92jZsnWe8eZHfkp5FaQ0WFmQ65rJ0NBQFi1aBICLiwuffPJJ\ngTtfsGABV69eRaFQMHLkSA4cOKBOxx8XF4eTkxOzZ8/mwoULzJs3D5lMxsCBA3F3dycxMZGvv/6a\nxMREDAwMWLx4Maamphr9r1+/niNHjiCRSBg7dizt2om574IgvLldu0RtQKFw1bKqSBPDdlxLO8bP\nV7yZ13linqVwBEEofOEJMTzOvAUKfQa36qDtcMqEuLhYLCws1dtGRsbExb0su2VomL+yXgCxsbGU\nL2+k8fPxRQmsgpYXc3JqTGRkJOHh4Vy5chFn5zbo6enlGW9+5KeUV0FKg5UFuQ4m5a/U3HmTOb6+\nvr4EBgayfft2YmNj6d27N6dOnVLvnzJlCu7u7igUCqZPn46XlxcmJibq9k2bNtG8eXM+++wztm/f\nzrp165g0aZL6/MePH3Po0CG2bdtGUlISHh4etGnTpkTNRxYEQRCET1p24taRWyTph7HtxgkGNuqo\n7ZAE4Z3jde0wSJU0MGyOYTk9bYdTJpibVyA+/mXJqoSEOPVbv4L3ZU5iYjwqlUo9OHxYQIl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I0cOVJHjx6V3W5XZGSk63Vdu3bVqVOnNGzYMI0aNUpjx451NYV2u10RERHn1X344YdVVFSkvn37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\nAAAAXFpleqKysjI98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Eg9+eSTl10qW1bmkM1mNSgpaqqBf/q4wuc/fWmwQUkAAKicy30v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\n7f8BCYu70m5A3h0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f33444afad0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,10))\n",
    "plt.subplot(211)\n",
    "t0 = '2017-7-21 12:00:20.000'\n",
    "t1 = '2017-7-21 12:50:01.000' \n",
    "\n",
    "q = data.loc[t0:t1].groupby(pd.TimeGrouper(freq='60S'))\n",
    "bids = q.bid.last()\n",
    "asks = q.ask.last()\n",
    "vol = data[data.type=='match'].loc[t0:t1].groupby(pd.TimeGrouper(freq='60S'))['size'].sum()\n",
    "\n",
    "bids.plot()\n",
    "asks.plot()\n",
    "plt.ylabel(\"Price (USD)\")\n",
    "annotate('2017-7-21 12:09:20.000', 2772.0, '2017-7-21 12:12:20.000', 2760.6, \"1) Short term volume spike\\n     with no price move\")\n",
    "annotate('2017-7-21 12:24:03.000', 2762.5, '2017-7-21 12:27:20.000', 2765.6, \"2) Large price move\\n     with high volume\")\n",
    "annotate('2017-7-21 12:47:03.000', 2768.0, '2017-7-21 12:42:20.000', 2760.0, \"3) Price reversion\\n     on low volume\")\n",
    "\n",
    "\n",
    "plt.subplot(212)\n",
    "vol.plot(kind='bar')\n",
    "plt.ylabel(\"Volume traded (BTC)\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Taking a look at the timeframe between July 21, 2007 between 08:53:28 and 08:53:43 there seems to be a mix between momentum ignition and layering (see previous section). Note the spike in volume at 08:53:31."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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c9URGRp4an5dAQkICffr0pVWr1hqfJyIicp6U+IkYBs5qOMfR6STxfMYYnv13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\nAAAAFkfwA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KYpl8sV9XkXXXSR/vWvf/nPffjhh/Xhhx8muHUAAHSMET8AADpQUFCgHj16\n6LrrrpPH44n4vMsvv1xvvvmmJk2aJJvNpsGDB6tPnz4nsKUAAITGdg4AAAAAYHFM9QQAAAAAiyP4\nAQAAAIDFEfwAAAAAwOIIfgAAAABgcQQ/AAAAALA4gh8AAAAAWBzBDwAAAAAsjuAHAAAAABb3/wFp\nuolIIveYZQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3347111390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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0Ua2nP69YsYKHH36YyZMnx3i65Pvb3/7Gww8/zLXXXpt47IUXXmDGjBlce+21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\nQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f3353e03590>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,10))\n",
    "    \n",
    "t0 = '2017-7-21 8:53:28.000'\n",
    "t1 = '2017-7-21 8:53:43.000' \n",
    "\n",
    "q = data.loc[t0:t1]\n",
    "bids = q.bid\n",
    "asks = q.ask\n",
    "#w = data.loc[t0:t1].groupby([pd.TimeGrouper(freq='5S'),'side'])\n",
    "\n",
    "asks.plot(linestyle='-', marker='X', ms=3, c='r', linewidth=1)\n",
    "bids.plot(linestyle='-', marker='X', ms=3, c='g', linewidth=1)\n",
    "\n",
    "\n",
    "plt.yticks(list(plt.yticks()[0]) + [2713.64, 2713.28 ])\n",
    "\n",
    "annotate('2017-07-21 08:53:30.763',2717.80, '2017-07-21 08:53:31.000',2719,'BUY wall pushed down')\n",
    "annotate('2017-07-21 08:53:30.763',2713.64, '2017-07-21 08:53:29.173',2710,'SELL 2.8BTC@2713.28')\n",
    "annotate('2017-07-21 08:53:33.763',2717.00, '2017-07-21 08:53:36.000',2718,'Layering')\n",
    "annotate('2017-07-21 08:53:37.500',2712.80, '2017-07-21 08:53:34.000',2711,'Layering Succedded!')\n",
    "annotate('2017-07-21 08:53:40.800',2712.10, '2017-07-21 08:53:41.500',2712.5,'Lucky market maker')\n",
    "annotate('2017-07-21 08:53:43.000',2709.60, '2017-07-21 08:53:41.000',2708.5,'Low ASK price')\n",
    "\n",
    "\n",
    "plt.figure(figsize=(15,4))\n",
    "vol = data[data.type=='match'].loc[t0:t1].groupby(pd.TimeGrouper(freq='1S'))['size'].sum()\n",
    "vol.plot(kind='bar')\n",
    "plt.title(\"MATCHED VOLUME\")\n",
    "plt.tight_layout()\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If we look 5 minutes into the future, until 08:58:00, we see that the price recovers to previous levels."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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66aer2LwAMAxwKXMgIiIiUpNWrXqP7du38eab8+nYsRM9evRk4MB7ueyyy2u6\naSJSCzW8YSiLBXzL2yIiIiISUF9++Tlffvk5AGfOnOHzz9P5/PN03njjdbp2vZoePXoyePB9nHtu\n4DN4i0jd0PACuACNwKkGnIiIiFTWO+8sdtacc5WXd5ItWzaxZcsmXn/9Nbp1u4beveNJSvoLERHN\na6ClIlJbeE1iUhv5WPnAPY3AiYiISC3Rs2c8t9/en7PPPtvjMTk52axd+yHJyU/Qq1d3/va3P7Nw\n4XxOnz4dxJaKSG3RAEfgLAEZgZs4MRmAJ55I9vu1RUREpH764x9v4Y9/vAW7PZc335zP5s0b+fTT\n7eTkZLs9PiPjCCtXvsvKle8ydeoLxMbGcfPNf+Smm/o5i76LSP1W9wK4amZmMg0DwyzyoRBB5Sxf\nngoogBMREZHKCw+P4IEHRvDAAyM4cuQwCxfOY+vWzezcmc7JkyfcnnPgwI8cOPAjb7+9iA4dLqdH\njzhuv70/PXvGK5OlSD1W9wK46tIUShEREanFzj77HEaNehyA7777lsWL32Tbti3s2vUlZ86ccXvO\nt9/u4dtv97Bw4Tw6duxEXFxPBg5MUiZLkXqo4QVwKiMgIiIidcTvfteB8eMnYJomaWlbWbFiGdu2\nbeWbb752e3xBQQFffLGTL77YyRtvzOWqq7oSF9dLmSxF6pGGF8BZDI3AiYiISJ1iGAZxcb2Ii+tF\nUVERH364mg8+WE1a2lZ+/HG/23Py8k6ydetmtm7dzJw5s+jWrTu9eyeQlPQXmjePDPITiIi/1MkA\nzqzOCjaLBYoUwImIiEjdZLFYuPnmW7j55lvIz89n6dK3+fjjj9i+PY0jRw67PefYsRzWrfuIdes+\n4tVXXyE2tgfXXns9AwYMpHHjxkF+AhGpjjoXwBlUc1Gu6sCJiIhIPREaGsqf/pTEn/6UhN2ey6JF\nC9i0aSM7dmwnO/uo23MyMzNYuXIFK1eu4OWXXyI2tgd/+MPN/PGPtyqTpUgdUOcCuGozlMRERERE\n6p/w8AiGDh3O0KHDycg4woIFb1Qik+VbdOhwGbGxPbn99v706qVMliK1VQMM4AJTRmDixGRAZQRE\nRESk5rVufXa5TJZpaVvZtetL8vPz3Z7z7bff8O233/Dmm45Mlj16xJGYeC9XXNExmE0XES8aXABn\nBqiMgOrAiYiISG3kmsly+/ZtvPvuMtLSHJksTTefiVwzWc6bN5errrqaHj16MnjwfbRpc14NPIGI\nuGpwAZzHNT23AAAgAElEQVQjiYnKCIiIiEjDYhgGPXr0pEePnhQVFbFmzfu8//5/2b59G/v3/+D2\nnLy8PGcmy9dff41u3brTq1c8gwffp0yWIjWkTgZw7r4t8pnqwImIiEgDZ7FYuOmmftx0Uz+XTJZr\n2b59m0+ZLGfOnK5MliI1pM4FcNXOQhmgKZQiIiIidVHZTJZvvbWQjRs3VCKT5Ytcc40jk2W/frcp\nk6VIgNW5AK7aNAInIiIi4lZ4eARDhgxjyJBhzkyW27ZtYefOdE6cOO72nAMHfuLAgZ94553F/O53\nl9GjRxy33daf3r0TlMlSJAAaXABnOXSQlt07VXiM2aQJvx7IqNR1VQdORERE6hPXTJbff/8dixe/\nybZtWyrMZPndd9/w3Xff8Oab8+nYsROxsXEMHKhMlnVJVExEQK+flZlb6nWrtjGY0dEYv2bx64GM\ngN+/UgyDrIxjHndHndMCMywM4+RJsg5nV+rSPj2nh1mDDS6AA7xPwszLIyomgtN33In9tTeC0CIR\nERGR2qt9+9/x5JNPY5omO3ZsZ/nypWzbtsWnTJbz58+lS5euxMX1YvDg+4iOvqwGnkAqI1Djpibl\nAxcD4OdDpfbVlnFb0zQrDLQMwLDbyz1XlI/Xr+g5TXDMHHTz/5dhVisjSGDYbHaP+2JmlHRO5rBc\nj8d54tq5xZ3m2gGuHXli1OOc/OdYn647cWIyULvKCERHh1fYl+Jf6u/gUn8Hl/o7uNTfwaX+rpqi\noiI++ugD3n9/FWlpnjNZumrevDlxcXF07x7Hn//8f8pkGQSV/f0O1AhYZYOymgpQaiJ4NCkdl5Rq\ngwK4Ei2vuhzLLz87X2dl5pb7ha3MCNzVVzumBtSmqZT6Bym41N/Bpf4OLvV3cKm/g0v9XX35+fks\nW/aOM5Pl4cP/83pOTExrrrkmlmuvvZ577vmTMlkGSGV/vyNv7MPx516goGs3v7WhqkFh2emWgVY2\nPqgKA/8Fnwa4DeAa5BRKgKOf7ym3rfiXJOqcFmQdskFIg+0eEREREZ+FhoYycOC9DBx4L8eP21m0\naAGbNm3g008rzmS5atV7rFr1Hi+//CKxsXHceOPN3HKLMlnWKBPH1D0/CnYgVlXu4oPKio4OJ8tP\nXwhFR4e73V5nI5TqjL55pUyVIiIiIlXSrFm4SybLDBYudGSyTE//zGMmy4MHD3Dw4AFnJsvY2B7c\ndlt/4uP7+JzJMjf3GBERzf35KA2Tafo9gBP/8imAS0lJIT09nYKCAoYOHcqqVavIznZkWsnJyaFL\nly5MmDCBw4cPM3z4cGJjYxk9enSpa3z//ffceeedfPDBB5x33nn+fxJ/8rBgUERERER817p1ax59\n1PGZsDiTZXr6dtLT071msly0aAEdO15JbGxPEhMH0bHjlR7vY5omd999OyNGPMRtt/UPyLM0GArg\naj2vAVxaWhp79+5lyZIlZGdn079/f9avX+/cP2bMGAYMGADA2LFjiYuLo6jM6JVpmkyePJnzzz/f\nv60PFAVwIiIiIn5VnMkyKqoZq1evZfnyVNLStrJnT0WZLD/niy8+Z968uVx1VVfi4nqSlHQf553X\nttSxGzeuZ9euLxk79jHOOiuUm2/uF6zHqn9MEyyWmm6FVMBrANe9e3c6dXLUTYuIiCAvL4/CwkKs\nViv79+/Hbrc790+bNo01a9awd+/eUtdYunQpcXFxbNiwIQCPEABVCOBqU/ISERERkdrKMAyuuaYH\n11zTo1Qmy+3bt/HDD+4zWZ46lce2bVvYtm0Lr7/+Gldf3Z1eveIZPPg+IiNbsHLlCgoLC8nMzOSf\n/3yYRo1Cue66G4L8ZPWDYZqYtSaRv7jjNYCzWq2EhYUBkJqaSkJCgnNh6fz580lKSnIe26xZs3Ln\nZ2dns2LFCv7zn//4HMC1aBFGSEjFi1c9LerzC4uF6Khm8Ntz12UB7ScpR/0dXOrv4FJ/B5f6O7jU\n38Hl2t9JSYkkJSWSn5/PokWL+OCDD9i8eTO//PKL23OPHTvGxx+v5eOP1/LaazPo1asXu3btcu7P\nyDjCY4+NZN68efTt2zfgz1IXVOr322rQslUz0P8TVRbo9xOfk5isXbuW1NRU5s6dCzjSxaanp5Oc\nnFzhec8//zwPPfQQIZXI6JidfdLrMYFM9xtVXHW9WaHP50ycmAyoDlxDpv4OLvV3cKm/g0v9HVzq\n7+CqqL/79buLfv3ucmay3LhxAzt2eM5kmZGRwbJly8ptP3ToEPfd939Mnz6b2Ngefm1/XVPZ3+8W\nZwrJzT5Jof6fqBJ/vp94CgR9muC6adMmZs6cyezZswkPd1xox44dzqmTFdm2bRspKSncc889fP31\n14wYMYKcnJxKNL0mGBiVrOCwfHkqy5enBqg9IiIiIg1HcSbLhQuXsHHjdkaP/hfx8X1o2rT8bC9P\nDh48wIMPPsDnn6cHsKX1kFmkJCa1nNcAzm63k5KSwqxZs4iMjHRu37VrFx06dPB6g48//pi3336b\nt99+myuuuIJXXnml1HVqI1NJTERERERqheJMlkuXrmTNmvUMHz6Sq6/uTmhoqNdzf/ppP8OHD+Hr\nr3d5PVZ+oyyUtZ7XeY2rV68mOzubkSNHOrdNnjwZm81WKqtkRkYGo0aNwmazkZeXx+7duxk/fjyX\nXHJJYFoeSBaLAjgRERGRWubSS9szfvzTmKbJjh3beemlKaxb91GF5+zbt5cHHvg7r78+n/btfxek\nltZhCuBqPa8BXGJiIomJieW2jxs3rtTr1q1bs2DBggqv5W1/ZcTMiAACVNBbhbxFREREaq3iTJZN\nmviWcO67775hyJD/44033uSCCy4McOvqOAVwtZ6KPLijKZQiIiIitVpOTjaffrrNp2NbtWpFQUGB\nM+mcVEB14Go931NDNiQGqgMnIiIiUostWDCPzMxMwBGgtWoVRVRUNNHR0URFxRAdHc3ZZ59Dp05d\nuPDCi2jatGkNt7iO0AhcrVfnArjMYbn0XHQ1825+i0tbtA/MTSwWKpmEUkRERESCqH379rz00it0\n6tSFiy66WAGav5gmquNdu9W5AA7AYlgoNH2v0VZpVVgDN3FiMlC76sCJiIiI1Fd/+MMfa7oJ9VMd\nHIErzo0BAcqPUcvUyQDu++zvSFgcG5BrZw7LrdIauOIacArgRERERKSuMoqKMOvAEJxr0NbQ1MkA\nLvCUxEREREREGiCTWj0C15ADt2IK4NwwLRYMTC2DExEREZEGpuanUFYnSKtvAZ45vnxEUicDOH/P\nbf1D6rU8G/88XVt3c2xQHTgRERGRei3qnBZQWJJTISuz5PNlVEwElvE10apa4P+A/3Z2/Ln2DsQ1\naCryAJxlCSW/6IzztSXjCC07dyAqpn5F8CIiIiLiYIaFYeAlRjE8/FS0rz791GJtmp1X002oMXVy\nBM7fQq2hnCnML7XNwDEF2DWIc/1mpizVgRMRERGpO4wTJwAvlaMq2tkQ1trUcBDnbdZdRdMlayob\nZXR0ODab3W/XckcBHLD5l41s/mUjUPov2/V3tjLBnIiIiIhUTsx09x/Gi54Kzv1dP+eVmj5plHw+\ndBcw1Pa09f4MKGqb2t73gaIAzgPXL1XKjiK7+8Jl4sRkQGUERERERKqs7IiPSc2tRavlUwil4dIa\nODeyMnOdP+AI2Ip/PFm+PNVZC05EREREqqDsB66aXINW3B6RWkYBHLDrL987/xwzI6LU8HjZYK4o\nrClYrUFvo4iIiEh99vqZ2xlwpgOZw12mxXkKoII1OmY03Gl6UntpCiVgGL7FsQUdO3H8369Q0KlL\ngFskIiIi0rCYgFEmMuvTti/fZX/LhF7PMvPL6Xx39BuOnznOWcZZpP95N2c3PSeobVQwJ7WBRuAA\ni48BHBYLmBpLFxEREfE/95+xDAyKzCIMDPIL87mi1ZUUUuj2WJGGQAEcYPmt2nzPc3sz5ppxnr9d\nUYFvERERkYAwTbPczEjDMLAYFkcAZxhc1fpqJsWnENUkutxonUhDoSmUgOW3ODbUGkqhWcE3OhbD\n4wic6sCJiIiIVJdR5pXhHIEDsBpWiswiTNN0fLEu0gBpBI6SKZSNrI0qDuA0AiciIiISECblR+CA\nkhE4HKNxFX5WE2kAFMBREsCFWhthmhUEaIbnNXATJyY7a8GJiIiISCWZJkaZUTXDMMAwMH9bH2cp\nHoHD1BRKabAUwFGShTLUEkphhQGcAUXuAzjVgRMRERGpOk9p4iwYjvVxhoHFMCgyCys4WqT+UwAH\nXDjbkYJ26d63mbrzBc8HKguliIiISEA4kpi4WQNnlF8DV7xPpCFSAFcZhoFR0QidiIiIiFRR+S/J\nnUlMcF0DV+QckRNpiHzKQpmSkkJ6ejoFBQUMHTqUVatWkZ2dDUBOTg5dunRhwoQJHD58mOHDhxMb\nG8vo0aMBsNvt/POf/8Rut1NUVMSECRO4+OKLA/dEARIzIwJuBj6/mcw4FXEUERER8Sd3hbyhJIkJ\nuGSh1BRKacC8BnBpaWns3buXJUuWkJ2dTf/+/Vm/fr1z/5gxYxgwYAAAY8eOJS4ujiKXTI3/+c9/\n6Nq1K/fffz/r16/n5ZdfZurUqf5/kmoorvs2+6tX+fHY/hpujYiIiEhD5D6JibOQt2FguARzmkIp\nDZXXAK579+506tQJgIiICPLy8igsLMRqtbJ//37sdrtz/7Rp01izZg179+51nj906FDn/4wtW7Yk\nJycnEM/hF9VJTas6cCIiIiJVZ7rJM1A8bbI4aHP8ufC3KZTBbqFI7eA1gLNarYSFhQGQmppKQkIC\nVqsVgPnz55OUlOQ8tlmzZuXOb9SokfPP8+bN45ZbbvHaqBYtwggJsXpvvZ81D29K6Ekr0dHh5fZ9\nM/wbLpt+GWavj8DN/trK3bNI4Ki/g0v9HVzq7+BSfweX+ju43PV3aGgIZ4WU/hy25sAHAIzZNMq5\n7b/73wMgqlU4rcL09+YL/X4HV6D726c1cABr164lNTWVuXPnApCfn096ejrJyck+nT9lyhRCQ0Od\n0y0rkp190tdm+dXJE2c4cfIUNpu93L6j2ScAyMk+wRk3+ydOTAbgiSeSA9fASoqODnf7LBIY6u/g\nUn8Hl/o7uNTfwaX+Di5P/X06v4ACinz+u/j11+MUnQj1d/PqHf1+B5c/+9tTIOhTFspNmzYxc+ZM\nZs+eTXi440I7duxwTp30ZurUqRw9epRnnnnGx+bWDKth9T6F0kMZAdWBExEREamG39a5+Upr4KSh\n8hrA2e12UlJSmDVrFpGRkc7tu3btokOHDl5v8Nlnn/HVV1/xzDPPYLHU7qoFVosvAZzKCIiIiIgE\n0x2X3Emvc+NLbWs/t10NtUakZnmdQrl69Wqys7MZOXKkc9vkyZOx2Wycf/75zm0ZGRmMGjUKm81G\nXl4eu3fvZvz48bz11lscPnyYv/zlLwA0b96cV155JQCPUn0Ww0JhUcUBnKFC3iIiIiJ+Z1JSyDtz\nWC4xMyK4unV3Lm91Bfb8XNV9E/mN1wAuMTGRxMTEctvHjRtX6nXr1q1ZsGBBueNeeOGFajQvuBy1\nRdwHcM5h+iKNwImIiIj4naMQnPtd+v5cxKl2z2kMMkcA5+UdQu8gIiIiIn7nrTi3geGs3Quw72+H\nAt0kkVrJ5yyUDYFPa+CK3L+5qA6ciIiISNW5TqF03Vq8ryxNqZSGSgGcC4sPWSgj/jyw5IVhkJVx\nLMCtEhEREWkATPA0h9LERJW7RRwUwLmwGBaPa+CKub51mKZJVEwEWK2MHP4QULvqwImIiIjUFY4R\nON+pjIA0VArgXFgryEJZ/KVP8QC+QUkwZxYW8u+XXwQgSwGciIiISOWZ5YMy87fcA6bpZnqlRuSk\ngVISExe+FPLOynQsnjVxH8yJiIiISOVpmqSIbzQC58KxBs57mYDiIC4qJsJLviQRERER8YW7KZSm\nSxKTsvs0hVIaKo3AubBaPNeBcycrM5eszFxy//Mma5o0oV3b872fJCIiIiLlVZDExB0FcNJQKYBz\nUdEUygrfJAwDQ0NxIiIiIlVmYnqcQWmapsoGiPxGAZwLq2H1mMSkQoZBnz7XqhaciIiIiB8VJzGB\n8l+mK6CThkoBnIsK68BV9CZhGGBqCE5ERESkqtwX8i7ZJyIOCuBcWC0V1IGrKEAzDPZ9/x0TJyYH\noFUiIiIiDYP7AM74bXql4cOxIvWfAjgXVsNKUVVG0gw4cuQwy5en+r9RIiIiIg2Au1E25xY3n880\nhVIaKgVwLiqsA+dtCqWIiIiIVJm3RCUacRNxUADnwjAsVUtiggp5i4iIiASKu9E5BXTSUCmAc3Hd\n27345ujXxMyIKLfPaxmBALZLREREpL5zl8TENXArl4VSn76kgVIA5w8K4ERERESqxahgCqWpbN8i\nTgrg/MA0DHr26Kk6cCIiIiJVZEK5iZKl6sCVzUKpHATSQCmAc7Fp4KdcGtmezGG5lTxTdeBERERE\nqkN14ER8owDORZUnQhoGP+7/QXXgRERERKrKNCvMCqc1cCIOCuDK8PQNj7ckJrbMDNWBExEREaki\nk/Kft4o/l7lbA6cplNJQKYBzUeU3AiUxEREREammiqdJKmATcQjx5aCUlBTS09MpKChg6NChrFq1\niuzsbABycnLo0qULEyZM4PDhwwwfPpzY2FhGjx4NgN1u59FHH8VutxMWFsYLL7xAZGRk4J6oJugN\nRURERKRaHDMofV8Dp6/PpaHyGsClpaWxd+9elixZQnZ2Nv3792f9+vXO/WPGjGHAgAEAjB07lri4\nOIqKipz7582bxzXXXMPf//53lixZwuzZs3nsscf8/yR+UqVFshqBExEREam2ij5RlVsDpy/QpYHy\nOoWye/fuTJ06FYCIiAjy8vIoLCwEYP/+/djtdjp16gTAtGnTuPjii0udv23bNm644QYA+vbty7Zt\n2/z6AP5U4ZtGRW8SCuBEREREqsXEcxITZaEUKeF1BM5qtRIWFgZAamoqCQkJWK1WAObPn09SUpLz\n2GbNmpU7Pysri5YtWwLQqlUrMjMz/dLwQKlSoUjD4Oqu3Uhf8b7/GyQiIiINWsz0iJpuQnC0BM7A\nK9MjyBzuKOm0O+srdmd95TwkZkZEqT9XvvSTSN3n0xo4gLVr15KamsrcuXMByM/PJz09neTkZJ9v\n5mtw1KJFGCEhVp+v6y/ZlmZYrRaio8PL7Tse4ghO3e2jfz/HvhiXN1hPz1p2JC/A9ePctlcCRv0d\nXOrv4FJ/B5f6O7hqfX83pKk+pu9/H7X+762WUD8FV6D726cAbtOmTcycOZM5c+YQHu5o0I4dO5xT\nJysSExODzWYjPDycjIwMYmJivJ6TnX3Sl2b53dGc4xQWFmGz2cvt+zX3OIDbfVGUfl81oVyglpWZ\nW+5Y1+OK9/tTdHS42/ZKYKi/g0v9HVzq7+BSfwdXnejvBjaD0Ne/j1r/91YL1Inf73rEn/3tKRD0\nGsDZ7XZSUlJ44403SmWP3LVrFx06dPB64169evHBBx8wbNgw1qxZQ3x8fCWaHXxVnWNdfJZB+S/J\nTCAqJqJckFYqkBMRERFx46P0TjyZUMCK+9Jquil+4esHXE2PFHHPawC3evVqsrOzGTlypHPb5MmT\nsdlsnH/++c5tGRkZjBo1CpvNRl5eHrt372b8+PEMHjyYxx57jEGDBhEREcGUKVMC8yR+UJnMR66y\nMnO5+uqOHDh0sFwwVhzQFQdxxVwDPnAf4ImIiIiYmMq4KCJOXgO4xMREEhMTy20fN25cqdetW7dm\nwYIFbq8xY8aMKjYv+KqUxOQ37dqeT3r6bufrqJgITNyPygGY4REY9txSAV5Vg7iomAjndUoJclDo\nGqRCYKaGioiINCSmaarmmYg4eS0j0KD4+dut4uDFdPkpdbuTJ8qNxFWXQemAMSomolxQFWg1fX8R\nEZH6xFTsJiIuFMAFWFZmrvMHSgdyWYezMZs0cRvcVYW7QFGBnIiISB2nETgRcaEArgxPSUy8zT1P\nT99davqkO67BXHFA9+uBDApi4zj23gfVmm7463c/YUZGOq5hGOWCuGC97bsLVIN5fxERkfrGNLUG\nTkRKKIBzUVPfbpkWCxQVVe8iRWZJSYKMY45Aqm1bj9M3A+3YkuUUtTmvxu4vIiJSX5hGzX1GEZHa\nRwFcGQdyfyJmRgQxMyo33W/ixGQmTkyu2k39EcCZpuM6rg4eJCszl9zX55N/y+1BTyhy9PM9ZGXm\ncuqv93P82SlKaCIiIlIFRjUSrIlI/aMAzkV1vt1avjyV5ctTq3ayX0bgiipIwmJU//qV5doWw8AI\n9v1FRETqCZUREBFXCuBqA8NPI3CGh79Oi8WxPxjc3McM5v1FRETqGUdJIgVwIuKgAM6NJiFNyBxW\nerpfQN84LdUfITPMIkxP384ZBphBGgErDtRcAzZ/jDCKiIg0VKanFGsi0hApgHPhy/SE6hT69shi\nwahugOVuDZzL9YM2AlYcqLk+j2FxJFkRERGRStMInIi4UgBXC/gnC2UFa+CMIK6B++0+pRZcB/P+\nIiIi9YzWwImIq5CabkBd4W3ygrcacBWy+GGEqsIROKMGRuDKTKHUGjgREZGqMTUCJyIlNALnovjN\nsaI3yYDMQg/0CJzFErwskJ7WwAVrDZ6IiEg9Yxr6ElRESiiAc6MqQdrEidWoA+evLJQeRuDMGphC\nWWpEUWUEREREqkxTKEXElQI4F9VJYlIr6sB5Gjk0gjeF0ZmMxeV+KiMgIiJSdaamUIqICwVwPgpI\n9sli/phiaJqOtW7uGEbwskA6R+BcnscPZRJEREREREQBXKUFYg2c6Yc1ahXWgbNYIFgVZNwlMUEB\nnIiISFVpCqWIuFIA56LGpif4Y4TKxHMWyhpZA+c6AqcplCIiIlVlYmoKpYg4qYyAG3kFecTMiAAg\nc1huqX0BmUrpjyQmFWShbH7XrQBExTieKSsz1+1xfuGcqlkmC2VBQeDuKSIiIiLSQCiAc1Gdb7eq\nVQfOHyNkFdWBoyS9iUlJIFeWr4Gdp/PLtcd5c0NlBERERKrINH1LtCYiDYOmUPooIPXfftNo6duE\njxhKVEyE4+ecFpW/SEV14CgZDzM8/AAl9/chQPN0neJrRfz9L87rhE1+hrCXnndeu+VVl1fy4URE\nRBou09AUShEpoRG4CpSdPgmeA7mJE5MBeOKJ5Crdq9TbcmFhuSDK6+hYBSNwWZm5RMVEeAxBXQMv\nKD1K5+m+7q5llPmz6dIe132WX34u9XwBndIpIiJS16mMgIi4UADnojrTE4prwFU1gHMdIXP9b/E+\nd6Nip++4E/trbzheVFQHDs9BUtnAzjWYK75v2XOPT0ohZN9ejj/3gsfrlLSp5Fplr++6XURERNwz\nHRGciAigAK7SAjGVsjhAchcElQ14XDV6dxmN3l1Wapu7gMuXe5e9f/F93Y60OSbje7yOp3tUNAoo\nIiIi7ploBE5ESvgUwKWkpJCenk5BQQFDhw5l1apVZGdnA5CTk0OXLl2YMGECc+bM4YMPPsAwDEaM\nGEGfPn3Yu3cvTz/9NABWq5UJEybQtm3bwD1RNdT0m2PZIKhVu9aQl+f2WE+BXXUCJJ8DLdP0XHPO\nh+sDWL/7loi/DSZ7845KX0dERKRBMbUGTkRKeA3g0tLS2Lt3L0uWLCE7O5v+/fuzfv165/4xY8Yw\nYMAADh06xOrVq1m8eDHHjx9n0KBB9O7dm2nTpjFkyBDi4+NZuXIls2fPdgZ0dUlx+YCAlBHw4NcD\nGW63B3okKyszl8bz5hLy1Rccf+Hl8ge4GYGrNIsfSieIiIg0CJpCKSIlvAZw3bt3p1OnTgBERESQ\nl5dHYWEhVquV/fv3Y7fb6dSpE6mpqcTHxxMaGkrLli1p06YN+/btIzIykpycHAByc3Np0aIKGRal\nlKAk/bBaobDQ/T6/BHBBLC4uIiJSh2kKpYi48hrAWa1WwsLCAEhNTSUhIQGr1QrA/PnzSUpKAiAr\nK4uWLVs6z2vZsiU2m42HHnqIu+++m+nTp1NUVERqamognsMvqpPEpFp14Goh02rF8BRgmVQ7gDMN\ni+fri4iIiJP5WwgnIgKVSGKydu1aUlNTmTt3LgD5+fmkp6eTnJzs9vjiqYYvvvgiDz/8MLfddhsL\nFy5k+vTpjBkzpsJ7tWgRRkiI1dem+c2ZxvZSr6Ojw51/toc0AyAqqhlNzmoS1HZVh+szVErzMDjL\nQmN35zcNhbBGhFX12gC54WBUo321VH17ntpO/R1c6u/gUn8HV23ub6vFIDQ0pFa3sbLq07PUBerv\n4Ap0f/sUwG3atImZM2cyZ84cwsMdDdqxY4dzaiVATEwMP/74o/N1RkYGMTEx7Ny5k1GjRgHQs2dP\nxo0b5/V+2dknK/UQ/nL0xIlSrzMzc52jcr8eOw6ALctOk5CCcudOnJgMVL2MQCBER4djs9m9H+hG\noxP5hJ44hd3N+U3sp7DkneFEFa8NYMk+SWRhEUercY3apjr9LZWn/g4u9Xdwqb+Dq7b3d0FhEWfO\nFNbqNlZGbe/v+kb9HVz+7G9PgaD7ys8u7HY7KSkpzJo1i8jISOf2Xbt20aFDB+frHj16sH79evLz\n88nIyCAzM5NLLrmEdu3a8dVXXznPadeuXXWfpUYUlw/wlMRk+fJUZy24esFqBdPTFEolMREREQkW\n01AWShEp4XUEbvXq1WRnZzNy5EjntsmTJ2Oz2Tj//POd284991zuuecekpKSMAyD5ORkLBYLjz32\nGMnJycyZM4fQ0FAmTJgQmCcJAJMG/IZpsUChAjgREZEaZ1Zvnb6I1C9eA7jExEQSExPLbXc3FXLw\n4MEMHjy41LaLL76YBQsWVKOJQeTDm2MgCnnXRqbVihHQLJQK4ERERHzRMD55iIivvE6hlAbKUlEZ\ngSJHAFat6yuAExER8YWJqRE4EXFSAOei7HTJs1+N9HBkA1DBGjjDDyNwKiMgIiLiuwa7pENEyvG5\njAV8wXwAAB5DSURBVEBD50xi4mEiQ32rA4fFCGwhb8PwnCRFREREnBrK8g0R8Y1G4MQ9L2vgTH+s\ngfOQ0VNERERKOKZQ6iObiDjo3cBF2ekJ/3vgaPmDPAQdEycmO2vB1QemxeolC2U1b2AxtAZORETE\nBybV/2dXROoPBXB+ojpwlWSxQJFG4ERERLwyFcKJSAkFcC7KZng6d2ZLYmZElNrWYOahWywVr4Gr\n7j8kykIpIiLiExPVgROREgrgfNXQ1msFuA6cslCKiIj4xtQkShFxoQCukswGEsiZFqvnETJ/TaFU\nFkoRERGfaARORIopgHPhrsZK5rDcGmhJLWAxoCjAZQQ0AiciIuJVQ/nyWER8ozpwflLf6sBF9rsB\ngKgYxxrArMySQDbspSlw1lmEvZhC1uHsKl0/ql1rDJfrl+V6PxERkYbMNDQCJyIlFMC58OW9scEk\nMaFktr1J6UDLAMjP90tPuOvysverDAV+IiJS3xim6XaWkIg0TArgvCgyi7AYFq+B28SJyQA88URy\noJsUNMVLpgP1T4a7Hq3O/Sob+CnYExGRuqAhfXksIt4pgPOiOIAr5mkeenENuPoSwGVl5hIVExGw\nfzLcBU/VuV9lAz9vwZ6COxERqS0cX6hqBE5EHBTAuXD35ljUgDMlBjuIqer9Khv4+RLsVXUKZ1SV\nznJPQaSIiBTTGjgRKaYAzouyAZymMdQ+lQl0vAV7Rpn/Vpa//nnVCKGIiBTTJw8RcaUAzotC00Mq\nfamTKgp8qjtl1MA//8h6GyH0FNxlZeYSdU4LzLCmGCdPVDlDaE0JH3IfoWvXYBw/7na/glYRaahM\nTI3AiYiTAjgX7qZQmr+NwKkES/1X3QAhOjqcLJu9WtfwZYTQW+ZOiz23Wpk8XQUzaGr07jKPgaun\n5/HnlNVgqivBaNk+99bfdeW5ROoaxxo4le4VEQcFcF74OoWyvtWBk5pRlRFCd0GdP76n9VcQ6I6v\nH/S9ZUKti99H17UyGYaHP5el77hEAmdo76Pw83LenLGczGH6okSkoVMA58Ld9AR/JzGJmeHbB7c7\nLrmT1258w+P+q+Zfzi/Hf/ZTq6ROSHazra5+ap7u5v+D8cFvRp3jrt8CqbJ/J8Fun0hDU1ff80XE\nrxTAeVFYdgTOzZtnzIyIkjdVPw0JvLtvGe/uW+afi0n9VReHoERERESkyhTAeVF2BO6y/1zo/kB9\nkBapWGW/Odb/Uw615Rv3ihYoioiISNAogHORsLhHuW1XvHFxwO7nbh67r1MsvV0HHEk1bNVMqiG+\nU38Hl/o7MC6a3YbGIY1Y1X8NF0Ve4tyu/g4u9Xdwqb9FpC7xKYBLSUkhPT2dgoIChg4dyqpVq8jO\ndqQoz8nJoUuXLkyYMIE5c+bwwQcfYBgGI0aMoE+fPgBMmjSJzz77jNDQUKZMmULbtm0D90TVcOTE\n4aqf7DKF0p8LjLVYWUSCyTAMTKXdFRERqbW8BnBpaWns3buXJUuWkJ2dTf/+/Vm/fr1z/5gxYxgw\nYACHDh1i9erVLF68mOPHjzNo0CB69+7N5s2bOXToEMuWLeOTTz5hy5YtDBw4MJDPVGUWw1Kpum+u\nwdXVV3cElI1SROo2A8MxdVw1p0RERGolrwFc9+7d6dSpEwARERHk5eVRWFiI1Wpl//792O12OnXq\nRGpqKvHx8YSGhtKyZUvatGnDvn37+Pjjj7n11lsB6Nu3b2CfpppCraG0ahzFr6eyODAko0baoBE3\nEalpRVrYJiIiUmt5DeCsVithYWEApKamkpCQgNVqBWD+/PkkJSUBkJWVRcuWLZ3ntWzZEpvNxi+/\n/MLXX3/NkiVLaNy4MU8++SRt2rQJxLNUW3WCNo28iUh9UDyF0lAWGRERkVrJ5yQma9euJTU1lblz\n5wKQn59Peno6ycnJbo8vXkNhmibNmzdn3rx5rFixgsmTJ/Pyyy9XeK8WLcIICbH62jSpQHR0eE03\noUFRfweX+tv/LIZBIUVEtQonukXp/lV/B5f6O7jU38Gl/g4u9XdwBbq/fQrgNm3axMyZM5kzZw7h\n4Y4G7dixwzm1EiAmJoYff/zR+TojI4OYmBiioqLo3r07APHx8cyaNcvr/bKzT1bqIWqDiROTAXji\nieQabEVpyqoVXOrv4FJ/B4gJRUUmv/56nPCCkv5VfweX+ju41N/Bpf4OLvV3cPmzvz0FghZvJ9rt\ndlJSUpg1axaRkZHO7bt27aJDhw7O1z169GD9+vXk5+eTkZFBZmYml1xyCQkJCWzatAmA3bv/f3t3\nHlV1nf9x/HXZzAUFVHABrZnUpiHGJcvcl5MpOpk2iaNYc5rm2Jg6zvHgwRoN0akRbaoZrVxmtFzG\nkkk8J7exUdxXVCqFEFwQTUBFBRHZPr8//PE9OZkiXr6XK8/HX3K5Fz/fl2+/9775fr6fzzd66KEf\n2UfNza1eHa/Vq+NdPQwAuCcOx41FTBwsYgIAQI10xytw69atU15eniZOnGg9NmvWLOXm5qpVq1bW\nYy1atNDw4cMVGRkph8OhmJgYeXh4aMCAAZo+fbpGjBghLy8vzZgxo3qOBABwzxxyyKice+AAAKih\n7tjARUREKCIi4gePT5069QePjR49WqNHj77pMU9PT8XGxt7DEAEAdmEfOAAAarY7TqEEANQuTKEE\nAKDmooEDAHyPQ4Z94AAAqLEqvY0Abo994ADcDxz/38BxDxwAADUTV+AAABZrFUoaOAAAaiQaOCeZ\nOTPG2gsOANyVQyxiAgBATUYD5yTsAwfgfuBw/P8UShYxAQCgRqKBAwBYKqZOMoUSAICaiQYOAAAA\nANwEDRwAwGJdgWMKJQAANRINHADAUtG4MYUSAICaiX3gnIR94ADcD2jcAACo2bgCBwCwWFMnmUIJ\nAECNRAPnJDNnsg8cAPfHFTgAAGo2GjgnYR84APcF7oEDAKBGo4EDAPwADRwAADUTDRwAwELbBgBA\nzUYDBwCwsA8cAAA1Gw0cAMDCPnAAANRs7APnJOwDB+B+QOMGAEDNxhU4AIDFugJHHwcAQI1EA+ck\nM2eyDxwA98cVOAAAajYaOCdhHzgA9xMaOQAAaiYaOACAJf3SMUlSu38+qMAPGrp4NAAA4H9VahGT\nuLg4JSUlqbS0VGPGjNEXX3yhvLw8SdKlS5fUvn17zZgxQ4sWLdKGDRvkcDg0btw49erVy/oZaWlp\nGjZsmDZs2KDg4ODqORoAAAAAuI/dsYHbs2ePjh07pk8//VR5eXkaOnSoEhMTre9PmTJFL7zwgk6f\nPq1169Zp5cqVKigo0MiRI9W9e3d5enrKGKNZs2apVatW1XksAAAAAHBfu2MD17lzZ4WFhUmSGjZs\nqGvXrqmsrEyenp46fvy48vPzFRYWpvj4ePXo0UM+Pj4KCAhQy5YtlZ6ernbt2unf//63nnrqKW3d\nurXaDwgAUHU5Y6+4eggAAOA27tjAeXp6ql69epKk+Ph49ezZU56enpKkTz75RJGRkZKk8+fPKyAg\nwHpdQECAcnNzFRgYqDVr1mjx4sWVbuD8/evJy8vzrg/GlTIzT7l6CLfUtKmvq4dQq5C3vcjbXuRt\nL/K2F3nbi7ztRd72qu68K72R95dffqn4+Hj985//lCQVFxcrKSlJMTExt3y+MUaSNGfOHP3hD3+Q\nl1fl9wzPyyus9HPx45o29VVubr6rh1FrkLe9yNte5G0v8rYXeduLvO1F3vZyZt4/1ghWqqvavn27\nPvroIy1atEi+vjd+0P79+62plZIUGBioEydOWF9nZ2crMDBQu3fv1rFjN1Y1S09P17hx47RkyRL5\n+flV+WAAAAAAoDa64zYC+fn5iouL0/z5829qur7++ms98sgj1tddunRRYmKiiouLlZ2drZycHD38\n8MPavHmzPvvsM3322Wf6+c9/rrlz59K8AQAAAEAV3PEK3Lp165SXl6eJEydaj82aNUu5ubk3rSrZ\nokULDR8+XJGRkXI4HIqJiZGHB9vMAQAAAICzOEzFzWo1CPN0nYM5z/Yib3uRt73I217kbS/ythd5\n24u87WXHPXBcIgMAAAAAN0EDBwAAAABuggYOAAAAANwEDRwAAAAAuAkaOAAAAABwEzRwAAAAAOAm\nauQ2AgAAAACAH+IKHAAAAAC4CRo4AAAAAHATNHAAAAAA4CZo4AAAAADATdDAAQAAAICboIEDAAAA\nADdBA+fmTpw4oatXr7p6GLUGeduLvO1F3vYib3uRt73I215ZWVmuHkKt4uq8aeDcVFZWlt544w29\n8847un79uquHc98jb3uRt73I217kbS/ythd52+vMmTOaMmWK4uLiaJhtUFPy9nLZ34wqW7VqlZYu\nXaqIiAiNGjXK1cO575G3vcjbXuRtL/K2F3nbi7zttXDhQq1bt06jRo3Sr371K1cP5763aNEirV27\ntkbkzRU4N7J9+3ZdvHhR3t7eCg4Otk6Oe/fu1fnz51VWViZJMsa4cpj3jbNnz0qS6tSpo+bNm5N3\nNaO+7UV924v6thf1bS/q2165ubmSJA8PD9WvX99qJpKTk1VQUGA9j7yd48CBAyopKZExRr6+vjUi\nb4fhX7fGS0pK0tKlS+Xj46Po6GgFBARo3LhxateunU6dOqXLly/Lz89P7dq10yuvvOLq4bq9o0eP\navbs2apfv758fX319ttva9KkSQoJCVFWVhZ5Oxn1bS/q217Ut72ob3tR3/b66quvNG/ePNWpU0dt\n27bVuHHjFBERoX79+unkyZPKyclRgwYNFB4erv79+7t6uG7v0KFDWrx4sRo0aKDXX39dDRo00HPP\nPafBgwfr+PHjLs3bMyYmJsbWvxF3ZcuWLYqKitLIkSM1YcIE1a1bV5Lk7++v+Ph4DR48WFFRUWrU\nqJH27dununXrKiQkxMWjdm+xsbEaNGiQ/vjHP2r16tW6cOGChgwZomXLlpG3k1Hf9qO+7UN924/6\ntg/1ba/i4mJNnTpVw4YNU2RkpBISEuTp6anevXvrb3/7m1566SVNnDhR+fn5OnLkiIKCgtS4cWNX\nD9stGWO0evVqvfXWW/r1r3+tsWPHysfHR5LUuHFjzZ8/Xy+++KJL86aBq2GMMXI4HCorK5OHh4fy\n8vLk7e2t9u3bq0WLFlq5cqWMMWrfvr0ee+wx/eIXv5CPj48CAwO1e/duhYWFKSgoyNWH4XbKy8sl\nSTk5OUpJSVHfvn0VEBAgh8Oh06dPa/DgwQoJCVHXrl3l7e1N3veI+rYX9W2v8vJyORwO6tsm1Le9\nOH/bzxij9PR0nTlzRs8//7wCAgKUmZkpY4yeeeYZhYSEqFu3bvLy8lLz5s31xRdfqHfv3mrYsKGr\nh+52Kj6HHz9+XL6+vgoPD5evr68SEhJUr149dezYUT/72c/Uvn17+fj4uCxvFjGpYQoLC1W/fn15\nenpKkjp06KDMzEx9/PHH+vDDD9WsWTMlJyfr4sWLmj9/vvbu3auwsDAdPHhQx44d0wMPPODiI3Av\nOTk5CgwMlIfHjdtBg4KCNHHiROs/YVpamurVqydJevLJJ7V//36FhoYqKSmJvKugIm/q2x4ZGRkK\nDg5WnTp1JFHf1e1/86a+q1dBQYEaNGjA+dsmFXlz/rbHgQMH5Ofnp4cfflgOh0M//elPNXbsWPn7\n+0uSzp07Z/25b9++OnjwoDp27Khvv/1WhYWFrhy6W/p+3pL09NNP68SJE/rggw907tw5NWzYUHv3\n7pXD4dBbb72lpKQkl+ZNA1dDfPPNN/rkk0/k4eGhIUOGqEuXLnrnnXfUv39/derUSSdOnFBQUJBG\njhwp6UZhJScnKyMjQytXrtSFCxcUFRWltm3buvhI3EN5ebmWLFmi+Ph4rVu3TpI0a9Ys9enTR088\n8YT1vIsXL2ro0KHW14cOHdKKFSvI+y79WN4DBw6kvqtBamqqPvjgAzVs2FBTpkxRnTp1NHv2bPXq\n1Yv6rga3yjsuLk4DBgygvqtBRd4+Pj4aM2aM2rRpozlz5qhnz57UdzW4Vd7Ud/VJTU3Vhx9+qK+/\n/lrvvfeeJGnevHnq0aOHwsLCJEmlpaW6ePGi2rdvb71ux44d+uijj3Tt2jVFRUUpODjYJeN3N7fK\ne+7cuRo0aJC6d++u1atX69lnn9Uvf/lLFRYW6oUXXlBycrKSkpK0cOFCXb161TV5G7hcRkaGiYyM\nNBs2bDCLFy820dHRxhhjzp07Zz0nJyfHFBUVmbKyMmOMMX//+9/N2rVrjTHGXL582f5B3wfi4uJM\nx44dzccff2yMuTlvY4w5f/68ee2114wxxmRnZ5ulS5caY4y5cuWKvQO9T/xv3t999531PerbeebN\nm2eGDh1qEhISbnqc+q4elcmb+nae0tJS88orr5iVK1eanTt3muPHjxtjqO/qUpm8qW/nKC8vN3/+\n85/Niy++aLZt22bi4uKsHLOysm56blpampk4caIx5kb+n3/+uTHmh/8P8ONul3dmZqb1vJMnT5rr\n169bX8+ZM8fs37/flJeX3/Q5xm5sI+BCW7Zs0cWLF5WamqrQ0FA988wzGjhwoMrKylRcXGzNFS8p\nKVHTpk119OhR7dixQ8uXL9fmzZvVpk0bSWKOcyVt2bJFOTk51tcPPvigZs2apSVLlujSpUsKCgqS\nMUYlJSWSpKtXr+rSpUtKSEjQlClTlJ2dbS0hizu7U97NmjVTeXm5SktLqW8n2Lx5s4qLiyVJoaGh\nGjJkiCRp165dKigoUEBAgCRZz6G+783d5E1937stW7YoOztbV65cUfPmzRUREaGuXbuqoKBAV69e\ntRYPoL6do7J58/nEOTZv3qzr16+rT58+WrBggXr06KHHHnvMur+zZcuWkmRtx1BaWqrS0lKtWbNG\nUVFROnPmjCRxj2El3SnvisV2jDFq3bq1Dh06pPT0dK1YsUJ79uxRUFCQHA6HmjVr5rJjYAqlCyQm\nJmrlypVq2bKlunfvrr59+6pTp07Kzc1VdHS0jDGaNWuWOnfurAEDBsjb21vSjTekbdu2qbCwUO+/\n/z6rOVVSRd7BwcF6/PHHrce3b9+uqKgoDRs2TO+++67Gjh2roKAgK2/pxl4r+/btU2xsrHUCxe3d\nbd4V969Q31VTkXeLFi3Uo0cPvfTSS5owYYIWLFig5ORklZWVyd/fX6GhoRo1apS1kpZEfVdFVfOm\nvqvm++eTLl26SJKOHDmi//znP9q+fbvOnDmjoKAgde7cWcOGDaO+79Hd5s3nk3vz/c+DTzzxhJ56\n6inre+np6WrQoIGkG7cheHh4WPcfXrp0Sd988438/f01c+ZMpktW0t3m7XA4JEmnT5/WmjVrVFpa\nqnfffbdm5O2ya3+1UFlZmVm1apXp2rWr2bFjxw++n5eXZ06cOGGMMSYhIcG88cYbJjU11Vy5csUs\nW7bMGGNMSUmJnUN2a3fKe+HChcYYY1JSUkyHDh3Mb37zG1NcXGy+++478+mnn5qysjKTkpJi97Dd\nVlXzPnv2rFm+fLkxhvq+G7fLe82aNSYyMtJs3brVGGNMYmKimTx5sjly5IjJz883K1eupL7v0r3k\nzfn77t0u73/84x+mW7duZvfu3cYYY9auXWumTp1qUlNTqe8qqmrefD6pmtvlXVpaaoy58V756quv\nmqKiIut758+fN5s2bTIFBQUmOTnZ1jG7s6rmnZuba02r/P7jNQFTKKuZ+f990iu6+aCgIA0ePNi6\n7LpixQqlpqaqrKxMfn5+atGihSSpW7dukm5MP/D19bVWGqr47QturbJ5S9LBgwc1ZswYxcXFqV+/\nfiotLZW3t7eaNWum+vXry8PDQ4888ojLjsUdOCPv5s2by8/PTxL1fSd3ynv58uVKS0vTs88+q8mT\nJ1sLOoSFhcnHx0eNGjVSgwYNrJX7qO/bc1benL8rpzJ5Hzt2TC+//LIaNWqkzMxMSbJ+i+7r60t9\n3wVn5M3nk8qr7PtlxfPq1q2rNm3a6Pjx4zf9DA8PD9WvX99a0AS35oy8Kx6XZK0uXFMwhbKaFRUV\nqW7dutY0sS5duujUqVOaM2eOiouL1bp1a+3cuVMBAQGaMWOG/vKXvyg6Olo7d+7UqVOnrMIKDw+X\nJOtyLm6tMnlv27ZNwcHBGjp0qA4fPqzx48frgQce0JAhQ3To0CF16NBBgwYNcvGRuAdn5U19V05l\nzydNmjRRbGysEhMT1bt3b23btk1ZWVnWByzqu3KclTf1XTmVPZ+EhoZq9uzZevvttxUWFqajR4/q\nxIkT1vsl9V05zsqb+q6cyp5PKqZF+vr66vLlyzp9+rTatWsnDw8PNWnSRH379nXxkbgHZ+Xdp08f\nFx/JrdHAVZM9e/Zo6dKlatKkiZ588kmFh4dr6tSpevXVV/X4448rKytLYWFhCg8P1+XLlxUeHq7x\n48fLy8tL0dHRKiws1PTp060rcri9u8n7ypUrCg8P17Bhw/T0009bP+Nf//qXtWcQbo+87XW355NB\ngwbptdde01dffaXPP/9cxcXFmjZtmktvuHYn5G2vqrxfRkREaNy4cfryyy+Vnp6u6dOnc59bJZG3\nvapyPklLS1Pbtm0VHByss2fPuvoQ3EqtydsF0zbveykpKSYyMtIkJiaa9evXm2nTppmioiJz+vRp\nY8yNeeI5OTmmuLjYes20adPMgQMHjDHGFBYWumTc7qoqecfGxppdu3YZY4y19DEqh7ztVZW833zz\nTXPgwAFTWlpq8vLyXDV0t0Te9qpK3jExMdb9WLg75G2vqr5fbt++3VVDdmu1KW+uwDlJWVmZFi5c\nqLZt2+rAgQPq16+fevXqpZMnT2rTpk3y8fG56bdVTZs21Z49e1RSUqKUlBR9++231qpNFfNt8ePu\nNe8jR45ozJgxkmRdXsePI2973WveqampGjt2rDw9Pa37C/HjyNte95p3SkqKfv/737vwCNwLedvL\nme+XuLPamrdnTExMjKsH4e7Onj2rKVOmyBij+vXra968eSooKNCxY8f03nvvycPDQykpKbp06ZI1\nr1a6sfv7xo0bVV5erpiYGDVp0sTFR+IeyNte5G0v8rYXeduLvO1F3vYib3vV5ry5AucE165dU0lJ\niSp64eTkZIWEhMjX11eTJk3SwIED9d///lfr169Xhw4d5OnpqX379um5555Tz549b9q3BndG3vYi\nb3uRt73I217kbS/ythd526s2581cJieoW7euWrdurZSUFEnS7373O+3cuVMrVqzQQw89JEl69NFH\nrSV369ata02zceficRXythd524u87UXe9iJve5G3vcjbXrU5bxo4JwgMDFR5ebkyMzNVVFSkBx98\nUP3791dGRobef/995eXlaePGjTp9+rQkyd/fX71793btoN0YeduLvO1F3vYib3uRt73I217kba/a\nnDf3wDlBxaaKO3bsUFBQkJo2baq2bdtq3759CgoK0q5du3ThwgX96U9/UuPGjV09XLdH3vYib3uR\nt73I217kbS/ythd526s25809cE7SqVMn7d69W+vXr5evr6+uXr2q0NBQRUdH6/r16+x35WTkbS/y\nthd524u87UXe9iJve5G3vWpr3g5jjHH1IO4XBQUFSkhI0NatW1VQUKARI0ZoyJAhrh7WfYu87UXe\n9iJve5G3vcjbXuRtL/K2V23MmwauGmRkZKhVq1by9vZ29VBqBfK2F3nbi7ztRd72Im97kbe9yNte\ntSlvGjgAAAAAcBOsQgkAAAAAboIGDgAAAADcBA0cAAAAALgJGjgAAAAAcBM0cAAAAADgJmjgAAC1\nypo1a5Sbm6sJEya4eigAANw1thEAANQaZWVlCg8P18aNG109FAAAqsTL1QMAAMAur7/+us6cOaOX\nX35Z6enp2rZtm6Kjo+Xv76+MjAylp6dr0qRJ2rx5s9LS0tSxY0dNnz5dkvTXv/5VBw8eVFFRkTp3\n7qzJkyfL4XC4+IgAALUNUygBALXG+PHjFRAQoNjY2JseP3/+vBYsWKBx48YpNjZWb775platWqXV\nq1frypUrWr9+vbKzs7Vs2TLFx8crMzNTW7ZscdFRAABqM67AAQBqvY4dO0qSmjVrpp/85Cdq2LCh\nJMnPz0/5+fnau3evDh8+rNGjR0uS8vPzlZWV5bLxAgBqLxo4AECt5+Xldcs/S5IxRj4+Pho+fLh+\n+9vf2j00AABuwhRKAECt4eHhodLS0rt+XadOnbRp0ybrtXPnztXJkyedPDoAAO6MK3AAgFojMDBQ\nTZo00fPPP6/y8vJKv65///46fPiwRowYIU9PTz366KMKCQmpxpECAHBrbCMAAAAAAG6CKZQAAAAA\n4CZo4AAAAADATdDAAQAAAICboIEDAAAAADdBAwcAAAAAboIGDgAAAADcBA0cAAAAALgJGjgAAAAA\ncBP/B0rzWI5LwiWCAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f332be0e250>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plt.figure(figsize=(15,10))\n",
    "    \n",
    "t0 = '2017-7-21 8:53:28.000'\n",
    "tmp = '2017-7-21 8:53:43.000' \n",
    "t1 = '2017-7-21 8:58:00.000' \n",
    "\n",
    "q = data.loc[t0:t1]\n",
    "bids = q.bid\n",
    "asks = q.ask\n",
    "#w = data.loc[t0:t1].groupby([pd.TimeGrouper(freq='5S'),'side'])\n",
    "\n",
    "asks.plot(linestyle='-', marker='X', ms=3, c='r', linewidth=1)\n",
    "bids.plot(linestyle='-', marker='X', ms=3, c='g', linewidth=1)\n",
    "plt.vlines(tmp,2704,2718, linestyles='--')\n",
    "annotate(tmp,2716.5,'2017-7-21 8:53:55.000', 2717.5, tmp)\n",
    "annotate('2017-7-21 8:57:7.000',2713.5,'2017-7-21 8:55:55.000', 2716, \"Back to previous level\")\n",
    "\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusion\n",
    "\n",
    "According to an interview carried out by The Atlantic [6] to Michael Kearns of the University of Pennsylvania and Andrew Lo at MIT, this behaviour also happens in traditional trading, and its causes are still matter of dispute. Relevant extract:\n",
    "> [...] why would a firm engage in this behavior? Lo and Kearns offered a few theories of their own about what could be happening.\n",
    "\n",
    "> To be honest, we can't come up with a good reason,\" Kearns said. What's particularly difficult to explain is how diverse and prevalent the patterns are. If algorithmic traders are simply testing new bots out -- which isn't a bad explanation -- it doesn't seem plausible that they'd do it so often. Alternatively, one could imagine the patterns are generated by some set of systemic information processing mistakes, but then it might be difficult to explain the variety of the patterns. \n",
    "\n",
    "> \"It's possible that the observed patterns are not malicious, in error, or for testing, but for information-gathering,\" Kearns observed. \"One could easily imagine a HFT shop wanting to regularly examine (e.g.) the latency they experienced from the different exchanges under different conditions, including conditions involving high order volume, rapid changes in prices and volumes, etc. And one might want such information not just when getting started, but on a regular basis, since latency and other exchange properties might well be expected to change over time, exhibit seasonality of various kind, etc. The super-HFT groups might even make co-location decisions based on such benchmarks.\" \n",
    "\n",
    "## References\n",
    "[1]https://en.wikipedia.org/wiki/Bitfinex\n",
    "\n",
    "[2] https://www.gdax.com/\n",
    "\n",
    "[3] Source: https://coinmarketcap.com\n",
    "\n",
    "[4] http://parasec.net/blog/order-book-visualisation/\n",
    "\n",
    "[5]  http://www.bsic.it/marketmanipulation/\n",
    "\n",
    "[6] https://www.theatlantic.com/technology/archive/2010/08/explaining-bizarre-robot-stock-trader-behavior/61028/\n",
    "\n",
    "[7] https://docs.gdax.com/"
   ]
  }
 ],
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