{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Project 5: Capstone Project\n", "### Learning to Trade Using Q-Learning\n", "Uirá Caiado. Aug 10, 2016\n", "\n", "\n", "#### Abstract\n", "\n", "*In this project, I will present an adaptive learning model to trade a single stock under the reinforcement learning framework. This area of machine learning consists in training an agent by reward and punishment without needing to specify the expected action. The agent learns from its experience and develops a strategy that maximizes its profits. The simulation results show initial success in bringing learning techniques to build algorithmic trading strategies.*" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 1. Introduction\n", "\n", "In this section, I will provide a high-level overview of the project, define the problem addressed and the metric used to measure the performance of the model created.\n", "\n", "### 1.1. Project Overview\n", "```\n", "Udacity:\n", "\n", "In this section, look to provide a high-level overview of the project in layman’s terms. Questions to ask yourself when writing this section:\n", "- Has an overview of the project been provided, such as the problem domain, project origin, and related datasets or input data?\n", "- Has enough background information been given so that an uninformed reader would understand the problem domain and following problem statement?\n", "```\n", "Nowadays, algo trading represents almost half of all cash equity trading in western Europe. In advanced markets, it already [accounts](http://en.resenhadabolsa.com.br/portfolio-category/the-distributionintermediation-industry-in-brazil-challenges-and-trends/) for over 40%-50% of total volume. In Brazil its market share is not as large – currently about 10% – but is expected to rise in the years ahead as markets and players go digital.\n", "\n", "As automated strategies are becoming increasingly popular, building an intelligent system that can trade many times a day and adapts itself to the market conditions and still consistently makes money is a subject of keen interest of any market participant.\n", "\n", "Given that it is hard to produce such strategy, in this project I will try to build an algorithm that just does better than a random agent, but learns by itself how to trade. To do so, I will feed my agent with four days of information about every trade and change in the [top of the order book](https://goo.gl/k1dDYZ) in the [PETR4](https://pt.wikipedia.org/wiki/Petrobras) - one of the most liquidity assets in Brazilian Stock Market - in a Reinforcement Learning Framework. Later on, I will test what it has learned in a newest dataset.\n", "\n", "The dataset used in this project is also known as [level I order book data](https://www.thebalance.com/order-book-level-2-market-data-and-depth-of-market-1031118) and includes all trades and changes in the prices and total quantities at best Bid (those who wants to buy the stock) and Offer side (those who intends to sell the stock)." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "### 1.2. Problem Statement\n", "```\n", "Udacity:\n", "\n", "In this section, you will want to clearly define the problem that you are trying to solve, including the strategy (outline of tasks) you will use to achieve the desired solution. You should also thoroughly discuss what the intended solution will be for this problem. Questions to ask yourself when writing this section:\n", "- Is the problem statement clearly defined? Will the reader understand what you are expecting to solve?\n", "- Have you thoroughly discussed how you will attempt to solve the problem?\n", "- Is an anticipated solution clearly defined? Will the reader understand what results you are looking for?\n", "```\n", "[Algo trading](http://goo.gl/b9jAqE) strategies usually are programs that follow a predefined set of instructions to place its orders. \n", "\n", "The primary challenge to this approach is building these rules in a way that it can consistently generate profit without being too sensitive to market conditions. Thus, the goal of this project is to develop an adaptive learning model that can learn by itself those rules and trade a particular asset using reinforcement learning framework under an environment that replays historical high-frequency data.\n", "\n", "As \\cite{chan2001electronic} described, reinforcement learning can be considered as a model-free approximation of dynamic programming. The knowledge of the underlying processes is not assumed but learned from experience. The agent can access some information about the environment state as the order flow imbalance, the sizes of the best bid and offer and so on. At each time step $t$, It should generate some valid action, as buy stocks or insert a limit order at the Ask side. The agent also should receive a reward or a penalty at each time step if it is already carrying a position from previous rounds or if it has made a trade (the cost of the operations are computed as a penalty). Based on the rewards and penalties it gets, the agent should learn an optimal policy for trade this particular stock, maximizing the profit it receives from its actions and resulting positions.\n", "\n", "```\n", "Udacity Reviewer:\n", "\n", "This is really quite close! I'm marking as not meeting specifications because you should fully outline your solution here. You've outlined your strategy regarding reinforcement learning, but you should also address things like data preprocessing, choosing your state space etc. Basically, this section should serve as an outline for your entire solution. Just add a paragraph or two to fully outline your proposed methodology and you're good to go.\n", "```\n", "\n", "This project starts with an overview of the dataset and shows how the environment states will be represented in Section 2. The same section also dives in the reinforcement learning framework and defines the benchmark used at the end of the project. Section 3 discretizes the environment states by transforming its variables and clustering them into six groups. Also describes the implementation of the model and the environments, as well as and the process of improvement made upon the algorithm used. Section 4 presents the final model and compares statistically its performance to the benchmark chosen. Section 5 concludes the project with some closing remarks and possible improvements.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "### 1.3. Metrics\n", "```\n", "Udacity:\n", "\n", "In this section, you will need to clearly define the metrics or calculations you will use to measure performance of a model or result in your project. These calculations and metrics should be justified based on the characteristics of the problem and problem domain. Questions to ask yourself when writing this section:\n", "- Are the metrics you’ve chosen to measure the performance of your models clearly discussed and defined?\n", "- Have you provided reasonable justification for the metrics chosen based on the problem and solution?\n", "```\n", "\n", "```\n", "Udacity Reviewer:\n", "\n", "The section on metrics should address any statistics or metrics that you'll be using in your report. What you've written in your benchmark section is roughly what we're looking for for the metrics section and vice versa. I'd recommend changing the subtitles to clarify this. If it's more logical to introduce the benchmark before explaining your metrics, you could combine the 'Benchmark' and 'Metrics' subsections into a single 'Benchmark and Metrics' section. \n", "```\n", "\n", "Different metrics are used to support the decisions made throughout the project. We use the mean [Silhouette Coefficient](http://scikit-learn.org/stable/modules/clustering.html#silhouette-coefficient) of all samples to justify the clustering method chosen to reduce the state space representation of the environment. As exposed in the scikit-learn documentation, this coefficient is composed by the mean intra-cluster distance ($a$) and the mean nearest-cluster distance ($b$) for each sample. The score for a single cluster is given by $s = \\frac{b-a}{\\max{a, \\, b}}$.This scores are so average down to all samples and varying between $1$ (the best one) and $-1$ (the worst value).\n", "\n", "Then, we use [sharpe ratio](https://en.wikipedia.org/wiki/Sharpe_ratio) to help us understanding the performance impact of different values to the model parameters. The Sharpe is measure upon the first difference ($\\Delta r$) of the accumulated PnL curve of the model. So, the first difference is defined as $\\Delta r = PnL_t - PnL_{t-1}$.\n", "\n", "Finally, as we shall justify latter, the performance of my agent will be compared to the performance of a random agent. These performances will be measured primarily of Reais made (the Brazilian currency) by the agents. To compared the final PnL of both agents in the simulations, we will perform a one-sided [Welch's unequal variances t-test](https://goo.gl/Je2ZLP) for the null hypothesis that the learning agent has the expected PnL greater than the random agent. As the implementation of the [t-test in the scipy](https://goo.gl/gs222c) assumes a two-sided t-test, to perform the one-sided test, we will divide the p-value by $2$ to compare to a critical value of $0.05$ and requires that the t-value is greater than zero. In the next section, I will detail the behavior of learning agent." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 2. Analysis\n", "\n", "In this section, I will explore the data set that will be used in the simulation, define and justify the inputs employed in the state representation of the algorithm, explain the reinforcement learning techniques used and provide a benchmark.\n", "\n", "### 2.1. Data Exploration\n", "```\n", "Udacity:\n", "\n", "In this section, you will be expected to analyze the data you are using for the problem. This data can either be in the form of a dataset (or datasets), input data (or input files), or even an environment. The type of data should be thoroughly described and, if possible, have basic statistics and information presented (such as discussion of input features or defining characteristics about the input or environment). Any abnormalities or interesting qualities about the data that may need to be addressed have been identified (such as features that need to be transformed or the possibility of outliers). Questions to ask yourself when writing this section:\n", "- If a dataset is present for this problem, have you thoroughly discussed certain features about the dataset? Has a data sample been provided to the reader?\n", "- If a dataset is present for this problem, are statistics about the dataset calculated and reported? Have any relevant results from this calculation been discussed?\n", "- If a dataset is **not** present for this problem, has discussion been made about the input space or input data for your problem?\n", "- Are there any abnormalities or characteristics about the input space or dataset that need to be addressed? (categorical variables, missing values, outliers, etc.)\n", "```\n", "The dataset used is composed by level I order book data from PETR4, a stock traded at BMFBovespa Stock Exchange. Includes 45 trading sessions from 07/25/2016 to 09/26/2016. I will use one day to create the scalers of the features used, that I shall explain. Then, I will use four days to train and test the model, and after each training session, I will validate the policy found in an unseen dataset from the subsequent day. The data was collected from Bloomberg. \n", "\n", "In the figure below can be observed how the market behaved on the days that the out-of-sample will be performed. In this charts are plotted the number of cents that an investment of the same amount of money in PETR4 and BOVA11 would have varied on these market sessions. BOVA11 is an [ETF](https://en.wikipedia.org/wiki/Exchange-traded_fund) that can be used as a proxy to the [Bovespa Index](https://goo.gl/TsuUVH), the Brazilian Stock Exchange Index. As can seem, PETR4 was relatively more volatile than the rest of the market." ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [], "source": [ "import zipfile\n", "s_fname = \"data/data_0725_0926.zip\"\n", "s_fname2 = \"data/bova11_2.zip\"\n", "archive = zipfile.ZipFile(s_fname, 'r')\n", "archive2 = zipfile.ZipFile(s_fname2, 'r')\n", "l_fnames = archive.infolist()" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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/JDoAAAAwJFS3JDoSejGH40iyAwaSvlNS6P85Lipa5407pk/vBQDo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JWfzRSZTDg2fft3rN/+cUTtViipdm5i02606+6e+4tRKC4TRHE1YvN1tDfupdcKxI75ze84TRrE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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import qtrader.eda as eda; reload(eda);\n", "df_last_pnl = eda.plot_cents_changed(archive, archive2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "*Let's start by looking at the size of the files that can be used in the simulation:*" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "20160725.csv:\t110,756 rows\t4.42 MB\n", "20160726.csv:\t100,109 rows\t3.98 MB\n", "20160727.csv:\t123,175 rows\t4.93 MB\n", "20160728.csv:\t109,655 rows\t4.37 MB\n", "20160729.csv:\t135,111 rows\t5.40 MB\n", "20160801.csv:\t109,710 rows\t4.37 MB\n", "20160802.csv:\t108,053 rows\t4.30 MB\n", "20160803.csv:\t137,039 rows\t5.49 MB\n", "20160804.csv:\t139,118 rows\t5.56 MB\n", "20160805.csv:\t112,852 rows\t4.51 MB\n", "20160808.csv:\t89,730 rows\t3.55 MB\n", "20160809.csv:\t83,826 rows\t3.33 MB\n", "20160810.csv:\t105,758 rows\t4.21 MB\n", "20160811.csv:\t144,728 rows\t5.81 MB\n", "20160812.csv:\t147,086 rows\t5.90 MB\n", "20160815.csv:\t108,633 rows\t4.33 MB\n", "20160816.csv:\t108,795 rows\t4.33 MB\n", "20160817.csv:\t118,980 rows\t4.75 MB\n", "20160818.csv:\t84,489 rows\t3.36 MB\n", "20160819.csv:\t98,329 rows\t4.00 MB\n", "20160822.csv:\t98,594 rows\t4.02 MB\n", "20160823.csv:\t90,752 rows\t3.69 MB\n", "20160824.csv:\t87,930 rows\t3.56 MB\n", "20160825.csv:\t95,929 rows\t3.89 MB\n", "20160826.csv:\t152,547 rows\t6.24 MB\n", "20160829.csv:\t98,630 rows\t4.02 MB\n", "20160830.csv:\t122,067 rows\t4.98 MB\n", "20160831.csv:\t155,391 rows\t6.37 MB\n", "20160901.csv:\t150,122 rows\t6.15 MB\n", "20160902.csv:\t147,257 rows\t6.04 MB\n", "20160905.csv:\t70,243 rows\t2.86 MB\n", "20160906.csv:\t109,355 rows\t4.46 MB\n", "20160908.csv:\t140,519 rows\t5.77 MB\n", "20160909.csv:\t142,940 rows\t5.86 MB\n", "20160912.csv:\t171,462 rows\t7.02 MB\n", "20160913.csv:\t224,427 rows\t9.25 MB\n", "20160914.csv:\t172,215 rows\t7.05 MB\n", "20160915.csv:\t139,648 rows\t5.72 MB\n", "20160916.csv:\t119,952 rows\t4.90 MB\n", "20160919.csv:\t126,815 rows\t5.18 MB\n", "20160920.csv:\t149,962 rows\t6.15 MB\n", "20160921.csv:\t163,128 rows\t6.70 MB\n", "20160922.csv:\t163,957 rows\t6.74 MB\n", "20160923.csv:\t159,513 rows\t6.56 MB\n", "20160926.csv:\t101,986 rows\t4.15 MB\n", "==========================================\n", "TOTAL\t\t45 files\t228.26 MB\n", "\t\t5,631,273 rows\n", "CPU times: user 18.7 s, sys: 161 ms, total: 18.9 s\n", "Wall time: 18.9 s\n" ] } ], "source": [ "def foo():\n", " f_total = 0.\n", " f_tot_rows = 0.\n", " for i, x in enumerate(archive.infolist()):\n", " f_total += x.file_size/ 1024.**2\n", " for num_rows, row in enumerate(archive.open(x)):\n", " f_tot_rows += 1\n", " print \"{}:\\t{:,.0f} rows\\t{:0.2f} MB\".format(x.filename, num_rows + 1, x.file_size/ 1024.**2)\n", " print '=' * 42\n", " print \"TOTAL\\t\\t{} files\\t{:0.2f} MB\".format(i+1,f_total)\n", " print \"\\t\\t{:0,.0f} rows\".format(f_tot_rows)\n", "\n", "%time foo()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "There are 45 files, each one has 110,000 rows on average, resulting in 5,631,273 rows at total and almost 230 MB of information. Now, let's look at the structure of one of them:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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DateTypePriceSize
02016-07-25 10:02:00TRADE11.985800
12016-07-25 10:02:00BID11.976100
22016-07-25 10:02:00ASK11.9851800
32016-07-25 10:02:00ASK11.9856800
42016-07-25 10:02:00ASK11.9856900
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" ], "text/plain": [ " Date Type Price Size\n", "0 2016-07-25 10:02:00 TRADE 11.98 5800\n", "1 2016-07-25 10:02:00 BID 11.97 6100\n", "2 2016-07-25 10:02:00 ASK 11.98 51800\n", "3 2016-07-25 10:02:00 ASK 11.98 56800\n", "4 2016-07-25 10:02:00 ASK 11.98 56900" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import pandas as pd\n", "df = pd.read_csv(archive.open(l_fnames[0]), index_col=0, parse_dates=['Date'])\n", "df.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Each file is composed of four different fields. The column $Date$ is the timestamp of the row and has a precision of seconds. $Type$ is the kind of information that the row encompasses. The type \"TRADE\" relates to an actual trade that has happened. \"BID\" is related to changes in the best Bid level and \"ASK,\" to the best Offer level. $Price$ is the current best bid or ask and $Size$ is the cumulated quantity on that price and side.\n", "\n", "All this data will be used to create the environment where my agent will operate. This environment is an order book, where the agent will be able to insert limit orders and execute trades at the best prices. The order book is represented by two binary trees, one for the Bid and other for the Ask side. As can be seen in the table below, the nodes of these trees are sorted by price (price level) in ascending order on the Bid side and descending order on the ask side. At each price level, there are other binary trees sorted by order of arrival. The first order to arrive is the first order filled when coming in a trade." ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 13.8 s, sys: 45.4 ms, total: 13.9 s\n", "Wall time: 13.9 s\n" ] } ], "source": [ "import qtrader.simulator as simulator\n", "import qtrader.environment as environment\n", "e = environment.Environment()\n", "sim = simulator.Simulator(e)\n", "%time sim.run(n_trials=1)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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qBidBidAskqAsk
061,40012.0212.0313,800
147,10012.0112.0478,700
251,70012.0012.0520,400
337,90011.9912.0623,100
497,00011.9812.0727,900
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" ], "text/plain": [ " qBid Bid Ask qAsk\n", "0 61,400 12.02 12.03 13,800\n", "1 47,100 12.01 12.04 78,700\n", "2 51,700 12.00 12.05 20,400\n", "3 37,900 11.99 12.06 23,100\n", "4 97,000 11.98 12.07 27,900" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "sim.env.get_order_book()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The environment will answer with the agent's current position and Profit and Loss (PnL) every time the agent executes a trade or has an order filled. The cost of the trade will be accounted as a penalty.\n", "\n", "The agent also will be able to sense the state of the environment and include it in its own state representation. So, this intern state will be represented by a set of variables about the current situation os the market and the state of the agent, given by:\n", "\n", "- $qOFI$ : integer. The net order flow at the bid and ask in the last 10 seconds\n", "- $book\\_ratio$ : float. The Bid size over the Ask size\n", "- $position$: integer. The current position of my agent. The maximum is $100$\n", "- $OrderBid$: boolean. If the agent has order at the bid side\n", "- $OrderAsk$: boolean. If the agent has order at the ask side" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "\n", "```\n", "Udacity:\n", "\n", "Exploratory Visualization:\n", "\n", "In this section, you will need to provide some form of visualization that summarizes or extracts a relevant characteristic or feature about the data. The visualization should adequately support the data being used. Discuss why this visualization was chosen and how it is relevant. Questions to ask yourself when writing this section:\n", "- Have you visualized a relevant characteristic or feature about the dataset or input data?\n", "- Is the visualization thoroughly analyzed and discussed?\n", "- If a plot is provided, are the axes, title, and datum clearly defined?\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Regarding the measure of the Order Flow Imbalance (OFI), there are many ways to measure it. \\cite{cont2014price} argued the *order flow imbalance* is a measure of supply/demand imbalance and defines it as a sum of individual event contribution $e_n$ over time intervals $\\left[ t_{k-1}, \\; t_k \\right]$, such that:\n", "\n", "$$OFI_k = \\sum^{N(t_k)}_{n=N(t_{k-1})+1} e_n$$\n", "\n", "Where $N(t_k)$ and $N(t_{k-1}) + 1$ are index of the first and last event in the interval. The $e_n$ was defined by the authors as a measure of the contribution of the $n$-th event to the size of the bid and ask queues:\n", "\n", "$$e_n = \\mathbb{1}_{P_{n}^{B} \\geq P_{n-1}^{B}} q^{B}_{n} - \\mathbb{1}_{P_{n}^{B} \\leq P_{n-1}^{B}} q^{B}_{n-1} - \\mathbb{1}_{P_{n}^{A} \\leq P_{n-1}^{A}} q^{A}_{n} + \\mathbb{1}_{P_{n}^{A} \\geq P_{n-1}^{A}} q^{A}_{n-1}$$\n", "\n", "Where $q^{B}_{n}$ and $q^{A}_{n}$ are linked to the cumulated quantities at the best bid and ask in the time $n$. The subscript $n-1$ is related to the last observation. $\\mathbb{1}$ is an [indicator](https://en.wikipedia.org/wiki/Indicator_function) function. In the figure below is ploted the 10-second log-return of PETR4 against the contemporaneous OFI. [Log-return](https://quantivity.wordpress.com/2011/02/21/why-log-returns/) is defined as $\\ln{r_t} = \\ln{\\frac{P_t}{P_{t-1}}}$, where $P_t$ is the current price of PETR4 and $P_{t-1}$ is the previous one." ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 2.48 s, sys: 16 ms, total: 2.49 s\n", "Wall time: 2.59 s\n" ] } ], "source": [ "import qtrader.eda as eda; reload(eda);\n", "s_fname = \"data/petr4_0725_0818_2.zip\"\n", "%time eda.test_ofi_indicator(s_fname, f_min_time=20.)" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "(-400000, 400000)" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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RVlaGn/70p7BarRg+fDhuueUWrFmzpt22a9aswaxZs1BaWgqDwYAFCxZAkiSs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\nlsX2vrcqgpYdTUXKQcvubbv6gnt4m5bFtqM72Rk5jt/h5kMdJYcRWw+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0e5BIJBLJ/Kn6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\nUy5JEurr61FSUqKX2e125Ofno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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import pandas as pd\n", "df = pd.read_csv('data/ofi_petr.txt', sep='\\t')\n", "df.drop('TIME', axis=1, inplace=True)\n", "df.dropna(inplace=True)\n", "ax = sns.lmplot(x=\"OFI\", y=\"LOG_RET\", data=df, markers=[\"x\"], palette=\"Set2\", size=4, aspect=2.)\n", "ax.ax.set_title(u'Relation between the Log-return and the $OFI$\\n', fontsize=15);\n", "ax.ax.set_ylim([-0.004, 0.005])\n", "ax.ax.set_xlim([-400000, 400000])" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "As described by \\cite{cont2014price} in a similar test, the figure suggests that order flow imbalance is a stronger driver of high-frequency price changes and this variable will be used to describe the current state of the order book." ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "### 2.2. Algorithms and Techniques\n", "```\n", "Udacity:\n", "\n", "In this section, you will need to discuss the algorithms and techniques you intend to use for solving the problem. You should justify the use of each one based on the characteristics of the problem and the problem domain. Questions to ask yourself when writing this section:\n", "- Are the algorithms you will use, including any default variables/parameters in the project clearly defined?\n", "- Are the techniques to be used thoroughly discussed and justified?\n", "- Is it made clear how the input data or datasets will be handled by the algorithms and techniques chosen?\n", "```\n", "Based on \\cite{cont2014price}, the algo trading might be conveniently modeled in the framework of reinforcement learning. As suggested by \\cite{du1algorithm}, this framework adjusts the parameters of an agent to maximize the expected payoff or reward generated due to its actions. Therefore, the agent learns a policy that tells him the actions it must perform to achieve its best performance. This optimal policy is exactly what we hope to find when we are building an automated trading strategy.\n", "\n", "According to \\cite{chan2001electronic}, Markov decision processes (MDPs) are the most common model when implementing reinforcement learning. The MDP model of the environment consists, among other things, of a discrete set of states $S$ and a discrete set of actions taken from $A$. In this project, depending on the position of the learner(long or short), at each time step $t$ it will be allowed to choose an action $a_t$ from different subsets from the action space $A$ , that consists of six possibles actions:\n", "\n", "$$a_{t} \\in \\left (None,\\, buy,\\, sell,\\, best\\_bid,\\, best\\_ask,\\, best\\_both \\right)$$\n", "\n", "Where $None$ indicates that the agent shouldn't have any order in the market. $Buy$ and $Sell$ means that the agent should execute a market order to buy or sell $100$ stocks (the size of an order will always be a hundred shares). This kind of action will be allowed based on a [trailing stop](https://goo.gl/SVmVzJ) of 4 cents. $best\\_bid$ and $best\\_ask$ indicate that the agent should keep order at best price just in the mentioned side and $best\\_both$, it should have ordered at best price in both sides." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "So, at each discrete time step $t$, the agent senses the current state $s_t$ and choose to take an action $a_t$. The environment responds by providing the agent a reward $r_t=r(s_t, a_t)$ and by producing the succeeding state $s_{t+1}=\\delta(s_t, a_t)$. The functions $r$ and $\\delta$ only depend on the current state and action (it is [memoryless](https://en.wikipedia.org/wiki/Markov_process)), are part of the environment and are not necessarily known to the agent.\n", "\n", "The task of the agent is to learn a policy $\\pi$ that maps each state to an action ($\\pi: S \\rightarrow A$), selecting its next action $a_t$ based solely on the current observed state $s_t$, that is $\\pi(s_t)=a_t$. The optimal policy, or control strategy, is the one that produces the greatest possible cumulative reward over time. So, stating that:\n", "\n", "$$V^{\\pi}(s_t)= r_t + \\gamma r_{t+1} + \\gamma^2 r_{t+1} + ... = \\sum_{i=0}^{\\infty} \\gamma^{i} r_{t+i}$$\n", "\n", "Where $V^{\\pi}(s_t)$ is also called the discounted cumulative reward and it represents the cumulative value achieved by following an policy $\\pi$ from an initial state $s_t$ and $\\gamma \\in [0, 1]$ is a constant that determines the relative value of delayed versus immediate rewards. It is one of the\n", "\n", "If we set $\\gamma=0$, only immediate rewards is considered. As $\\gamma \\rightarrow 1$, future rewards are given greater emphasis relative to immediate reward. The optimal policy $\\pi^{*}$ that will maximizes $V^{\\pi}(s_t)$ for all states $s$ can be written as:\n", "\n", "$$\\pi^{*} = \\underset{\\pi}{\\arg \\max} \\, V^{\\pi} (s)\\,\\,\\,\\,\\,, \\,\\, \\forall s$$\n", "\n", "However, learning $\\pi^{*}: S \\rightarrow A$ directly is difficult because the available training data does not provide training examples of the form $(s, a)$. Instead, as \\cite{Mitchell} explained, the only available information is the sequence of immediate rewards $r(s_i, a_i)$ for $i=1,\\, 2,\\, 3,\\,...$\n", "\n", "So, as we are trying to maximize the cumulative rewards $V^{*}(s_t)$ for all states $s$, the agent should prefer $s_1$ over $s_2$ wherever $V^{*}(s_1) > V^{*}(s_2)$. Given that the agent must choose among actions and not states, and it isn't able to perfectly predict the immediate reward and immediate successor for every possible state-action transition, we also must learn $V^{*}$ indirectly.\n", "\n", "To solve that, we define a function $Q(s, \\, a)$ such that its value is the maximum discounted cumulative reward that can be achieved starting from state $s$ and applying action $a$ as the first action. So, we can write:\n", "\n", "$$Q(s, \\, a) = r(s, a) + \\gamma V^{*}(\\delta(s, a))$$\n", "\n", "As $\\delta(s, a)$ is the state resulting from applying action $a$ to state $s$ (the successor) chosen by following the optimal policy, $V^{*}$ is the cumulative value of the immediate successor state discounted by a factor $\\gamma$. Thus, what we are trying to achieve is\n", "\n", "$$\\pi^{*}(s) = \\underset{a}{\\arg \\max} Q(s, \\, a)$$\n", "\n", "It implies that the optimal policy can be obtained even if the agent just uses the current action $a$ and state $s$ and chooses the action that maximizes $Q(s,\\, a)$. Also, it is important to notice that the function above implies that the agent can select optimal actions even when it has no knowledge of the functions $r$ and $\\delta$.\n", "\n", "Lastly, according to \\cite{Mitchell}, there are some conditions to ensure that the reinforcement learning converges toward an optimal policy. On a deterministic MDP, the agent must select actions in a way that it visits every possible state-action pair infinitely often. This requirement can be a problem in the environment that the agent will operate.\n", "\n", "As the most inputs suggested in the last subsection was defined in an infinite space, in section 3 I will discretize those numbers before use them to train my agent, keeping the state space representation manageable, hopefully. We also will see how \\cite{Mitchell} defined a reliable way to estimate training values for $Q$, given only a sequence of immediate rewards $r$." ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "### 2.3. Benchmark\n", "```\n", "Udacity:\n", "\n", "In this section, you will need to provide a clearly defined benchmark result or threshold for comparing across performances obtained by your solution. The reasoning behind the benchmark (in the case where it is not an established result) should be discussed. Questions to ask yourself when writing this section:\n", "- Has some result or value been provided that acts as a benchmark for measuring performance?\n", "- Is it clear how this result or value was obtained (whether by data or by hypothesis)?\n", "```\n", "\n", "In 1988, the Wall Street Journal created a [Dartboard Contest](http://www.automaticfinances.com/monkey-stock-picking/), where Journal staffers threw darts at a stock table to select their assets, while investment experts picked their own stocks. After six months, they compared the results of the two methods. After adjusting the results to risk level, they found out that the pros barely have beaten the random pickers.\n", "\n", "Given that, the benchmark used to measure the performance of the learner will be the amount of money made, in Reais, by a random agent. So, my goal will be to outperform this agent, that should just produce some random action from a set of allowed actions taken from $A$ at each time step $t$.\n", "\n", "Just like my learner, the set of action can change over time depending on the open position, that is limited to $100$ stocks at most, on any side. When it reaches its limit, it will be allowed just to perform actions that decrease its position. So, for instance, if it already [long](https://goo.gl/GgXJgR) in $100$ shares, the possible moves would be $\\left (None,\\, sell,\\, best\\_ask \\right)$. If it is [short](https://goo.gl/XFR7q3), it just can perform $\\left (None,\\, buy,\\, best\\_bid\\right)$.\n", "\n", "The performance will be measured primarily in the money made by the agents (that will be optimized by the learner). First, I will analyze if the learning agent was able to improve its performance on the same dataset after different trials. Later on, I will use the policy learned to simulate the learning agent behavior in a different dataset and then I will compare the final Profit and Loss of both agents. All data analyzed will be obtained by simulation.\n", "\n", "As the last reference, in the final section, we will compare the total return of the learner to a strategy of buy-and-hold in BOVA11 and in the stock traded to check if we are consistently beating the market and not just being profitable, as the Udacity reviewer noticed." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 3. Methodology\n", "\n", "In this section, I will discretize the input space and implement an agent to learn the Q function.\n", "\n", "### 3.1 Data Preprocessing\n", "```\n", "Udacity:\n", "\n", "In this section, all of your preprocessing steps will need to be clearly documented, if any were necessary. From the previous section, any of the abnormalities or characteristics that you identified about the dataset will be addressed and corrected here. Questions to ask yourself when writing this section:\n", "- If the algorithms chosen require preprocessing steps like feature selection or feature transformations, have they been properly documented?\n", "- Based on the **Data Exploration** section, if there were abnormalities or characteristics that needed to be addressed, have they been properly corrected?\n", "- If no preprocessing is needed, has it been made clear why?\n", "```" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "As mentioned before, I will implement a Markov decision processes (MDP) that requires, among other things, of a discrete set of states $S$. Apart from the input variables $position$, $OrderBid$, $OrderAsk$, the other variables are defined in an infinite domain. I am going to discretize those inputs, so my learning agent can use them in the representation of their intern state. In the Figure bellow, we can see the distribution of those variables. The data was produced using the first day of the dataset." ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import pandas as pd\n", "df = pd.read_csv('data/ofi_petr.txt', sep='\\t')\n", "df.drop(['TIME', 'DELTA_MID'], axis=1, inplace=True)\n", "df.dropna(inplace=True)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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uWZYO9R/WscSYDvUfZok4AADrAAETAJRpxsqpMB/81HIHU8G2NWPlqv76ANaX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\nLXPjL3VYUVFBNpstuEsdygj1l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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Produce a scatter matrix for each pair of features in the data\n", "pd.scatter_matrix(df.ix[:, ['OFI', 'BOOK_RATIO']],\n", " alpha = 0.3, figsize = (14,8), diagonal = 'kde');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "```\n", "Udacity Reviewer:\n", "\n", "Please be sure to specify how you are doing this (I'd recommend giving the formula).\n", "```\n", "The scale of the variables is very different, and, in the case of the $BOOK\\_RATIO$, it presents a logarithmic distribution. I will apply a logarithm transformation on this variable and rescale both to lie between a given minimum and maximum value of each feature using the function [MinMaxScaler](http://scikit-learn.org/stable/modules/preprocessing.html) from scikit-learn. So, both variable will be scaled to lie between $0$ and $1$ by applying the formula $z_{i} =\\frac{x_i - \\min{X}}{\\max{X} - \\min{X}}$. Where $z$ is the transformed variable, $x_i$ is the variable to be transformed and $X$ is a vector with all $x$ that will be transformed. The result of the transformation can be seen in the figure below." ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "collapsed": false }, "outputs": [], "source": [ "import sklearn.preprocessing as preprocessing\n", "import numpy as np" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "collapsed": false }, "outputs": [], "source": [ "scaler_ofi = preprocessing.MinMaxScaler().fit(pd.DataFrame(df.OFI))\n", "scaler_bookratio = preprocessing.MinMaxScaler().fit(pd.DataFrame(np.log(df.BOOK_RATIO)))\n", "d_transformed = {}\n", "d_transformed['OFI'] = scaler_ofi.transform(pd.DataFrame(df.OFI)).T[0]\n", "d_transformed['BOOK_RATIO'] = scaler_bookratio.transform(pd.DataFrame(np.log(df.BOOK_RATIO))).T[0]" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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ex2h3H3wbLrz49KWKQ4FqBEm54U12myUe22ECjsNU8BxUudQMFTftulIYUbU0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DtiJpl0ugBdJxpuJh9lvMZIyGO2K5n9Vku+lzutxu3S4hhNiIbDbL1wffYjYeAeATLb3UWGVM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\naGvkWEs9x1oaOj621lPn7X73reSYuC6Fnjx3mmb1iIj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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "df_transformed = pd.DataFrame(d_transformed)\n", "pd.scatter_matrix(df_transformed.ix[:, ['OFI', 'BOOK_RATIO']],\n", " alpha = 0.3, figsize = (14,8), diagonal = 'kde');" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "As mentioned before, in an MDP environment the agent must visit every possible state-action pair infinitely often. If I just bucketize the variables and combine them, I will end up with a huge number of states to explore. So, to reduce the state space, I am going to group those variables using K-Means and Gaussian Mixture Model (GMM) clustering algorithm. Then I will quantify the \"goodness\" of the clustering results by calculating each data point's [silhouette coefficient](https://goo.gl/FUVD50). The silhouette coefficient for a data point measures how similar it is to its assigned cluster from -1 (dissimilar) to 1 (similar). In the figure below, I am going to calculate the mean silhouette coefficient to K-Means and GMM using a different number of clusters. Also, I will test different covariance structures to GMM." ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "K-Means took 4.59 seconds to run over all complexity space\n", "GMM took 16.85 seconds on average to run over all complexity space\n" ] } ], "source": [ "from sklearn import metrics\n", "from sklearn.cluster import KMeans\n", "from sklearn.mixture import GMM\n", "import time\n", "\n", "\n", "reduced_data = df_transformed.ix[:, ['OFI', 'BOOK_RATIO']]\n", "reduced_data.columns = ['Dimension 1', 'Dimension 2']\n", "range_n_clusters = [2, 3, 4, 5, 6, 8, 10]\n", "\n", "f_st = time.time()\n", "d_score = {}\n", "d_model = {}\n", "s_key = \"Kmeans\"\n", "d_score[s_key] = {}\n", "d_model[s_key] = {}\n", "for n_clusters in range_n_clusters:\n", " # TODO: Apply your clustering algorithm of choice to the reduced data \n", " clusterer = KMeans(n_clusters=n_clusters, random_state=10)\n", " preds = clusterer.fit_predict(reduced_data)\n", " d_model[s_key][n_clusters] = clusterer\n", " d_score[s_key][n_clusters] = metrics.silhouette_score(reduced_data, preds)\n", "print \"K-Means took {:0.2f} seconds to run over all complexity space\".format(time.time() - f_st)\n", "\n", "f_avg = 0\n", "\n", "for covar_type in ['spherical', 'diag', 'tied', 'full']:\n", " f_st = time.time()\n", " s_key = \"GMM_{}\".format(covar_type)\n", " d_score[s_key] = {}\n", " d_model[s_key] = {}\n", " for n_clusters in range_n_clusters:\n", " \n", " # TODO: Apply your clustering algorithm of choice to the reduced data \n", " clusterer = GMM(n_components=n_clusters,\n", " covariance_type=covar_type,\n", " random_state=10)\n", " clusterer.fit(reduced_data)\n", " preds = clusterer.predict(reduced_data)\n", " d_model[s_key][n_clusters] = clusterer\n", " d_score[s_key][n_clusters] = metrics.silhouette_score(reduced_data, preds)\n", " f_avg += time.time() - f_st\n", " \n", "print \"GMM took {:0.2f} seconds on average to run over all complexity space\".format(f_avg / 4.)" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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EeOjlFRi4nPtgUyKr2jtjp7Eu0z5TpkwhJCSEESNGmMqqV6/OxIkT8fHxwcrK\nylTeunVrVq1aRWBgoKls165deHt7k5iYaHbcoKAgtm/fztWrV6lUqZKpPCoqilatWhEfH1/qPn79\n9df8/PPPFBYW0q9fP7Nt/fr1o3HjxowcORKAzz//nMjISDIyMqhVqxbjx48nKOj6N+xpaWkMHz6c\nAwcO4Ovry/Dhw3njjTeIjY2levXqpe5PRSdB9H1iYaPBvZcfKcsOU/twG4wWhVyueRQL+3NEHp9C\nxycnUMlVAmkhhBDiZvIKDIzfs4rcgvwH2q69xorpTbuVOpBOTU1l//79jB49usTtr7zyitnrjh07\nMnr0aCZOnIilpSUAa9asITQ0lIULF5rVtbOzIzg4mKioKPr37w9AYmIiFy5cICwsrNRB9Pbt2/nu\nu+9YvHgx9evXZ/78+Zw4cYLg4OBidVeuXMmqVav47bffqFy5Mt988w3Dhg3jjz/+QFEUxo8fT2Fh\nIdu3byc1NZURI0agKEqp+vEokXSO+8jCVoNHLz+sKjtS92A7Kl/QAqBxTGDdielcvCLL3wkhhBAV\n3fnz51EUBW9v79vWVRSFOnXq4OXlxbZt2wAwGAxs2bKF0NBQVFUttk94eDirV682vY6MjCQ0NLRM\ngevGjRtNudrW1ta8+eabWFuXfJHQrVs31q1bR5UqVVAUhc6dO5OWlkZiYiKqqrJ9+3YGDBiAk5MT\nNWvW5MUXXyx1Px4lMhN9n1nYWeHRy4+UXw6j++tZjBaFJFc/ibXLKTae/oyn9SOpXcOzvLsphBBC\nPHTsNNZMb9rtoU/nKApmCwsLTWV79+5lwIABKIqC0WikevXqREdHm4Lkbt26sWrVKtq0acPWrVsJ\nCAjAzc2txOMHBwczfvx4Tp8+ja+vL1FRUUybNo0jR46Uuo+XL1/G19fX9Fqj0eDl5VVi3ZycHKZN\nm8bvv/9OZmamqc8Gg4H09HTy8/PN0jb8/f1L3Y9HiQTRD4CFvRXuL/iR+ssR6u3rxFFlLSnVTmPj\nFs/v57/i2rV38KtTpby7KYQQQjx07DTW1HJ+uCebfHx8ADh16pQpbzkoKIhDhw4BEBERYVpKrkjX\nrl2ZNWsWOTk5REZGEh4eftPjazQaunTpwurVqwkLC0Ov1+Pn51emIDo/P98syAdKnPUGmDx5MvHx\n8fz888/UqFGD8+fP8+yzz5rtc2OO9+OYygGSzvHAWDpY497bDys3R+rvC8UtqSYAdh7H2Z00l12H\nL970wyxLXmCUAAAgAElEQVSEEEKIh5ezszMtW7Zk0aJFJW7/d/AK4OHhQVBQEOvWrWPPnj20bdv2\nlm2Eh4cTHR3N2rVrCQsLK3MfK1euzKVLl0yvDQYD58+fL7Hu4cOHCQ8Pp0aNGgBmwbqrqyuWlpZc\nvHjRrP7jSILoB8jSwRqP3v5YuTjRYE9XXK8+AYB9pb85kv5fYnefxWiUQFoIIYSoaD788EMOHTrE\ne++9ZwowMzIy+PXXX/nyyy9p1KhRsX26devG3LlzadWqFba2trc8fkBAAACrVq265az1zQQHB7N9\n+3YOHTqEXq9nzpw5N5288/Ly4vDhw+Tn53PgwAHWrl0LQFJSEhYWFgQFBbF48WKys7M5c+YMv/32\nW5n78yiQIPoBs3S0xqO3H9bOjvjtDsc55XpOkUPlQyRc+4nIbacoKDSWcy+FEEIIURa1atVi+fLl\n2Nra0rdvXxo1akRoaCgbNmzggw8+4IsvvgDMUx/atWtHZmamWVB8q9SIbt264eHhYZohLovOnTvz\n6quv8tZbbxESEoKNjY1ZYH9ju6NGjeLkyZM0a9aMmTNnMmHCBNq3b8+QIUOIi4tj+vTpZGZm0qpV\nKz744APefPNNACwsHq+wUlElh+Ceyc3NJS4uDh8fHzw8PG5ZtzBTT8rSQ+hzMjn01Eqy3C8DkH0p\nCKdr4XRrWwdb60c/Zb1ozOrVq4e9vX15d6fCkHErOxmzOyPjVnYyZndGxq3synPMCgoK0Giuxyk7\nd+5k4MCBHDx40FT2MEtJSSEhIeGux+3xumR4iFg62+De2x8be2cCdj6HY3plAByr7SXTei3L1h8j\nK8dQzr0UQgghhDD3wQcfMGjQILKyssjKymLx4sW0bNmyQgTQ95IE0eVI42KLe29/rO2cCfjzORwy\nr89eO3nt5Jr9JpauO0ZKel4591IIIYQQD7OYmBgCAgJo2LBhif8NHDjwnrY3evRoXF1dad++Pc8+\n+ywajYapU6fe0zYqgsfrkuEhpHG1xaO3HylLDxOwozsHn/6NXKc0nGtsJ9Oo4Zf1hTzXtg7VKzuW\nd1eFEEII8RDq0KED3bp1e2Dtubi48NVXXz2w9h5WMhP9ENC42eHR2x9bK1cCdnTHLtsFAOeaW7B0\n28VvG05w6nx6OfdSCPG40RdmcSZrI9mW8bIEpxBC/MsjEUQnJibyxhtv0Lx5c9q2bcvnn39+232S\nkpIIDAw0W/xcr9czbdo0nnnmGZo1a8bAgQNL/Uz6u6Vxt8Ojtx92lm4E7OiBbY4zAC4+m7D22Mfq\nzSc5fOLqA+mLEOLxlmW4xL6kBaw+9RaH05dwyW45u5K/JCdffgcJIUSRRyKIHjp0KFWrViU2NpbF\nixcTExPD4sWLb7nP1KlTiyXAf/bZZ+zfv59ly5axbds2qlWrxtChQ+9jz81pPOxx7+2PvYU7AX92\nxybvegqHq+8GbD0PEfPnWXYeTJQZISHEPaeqKldy4/j94qdEnXmX+PRoClW9afuVawdZd2YEx1Oj\nMKrFHxwhhBCPmwofRB8+fJgTJ07w/vvv4+DggLe3N6+99hrLli276T5bt27l9OnThISEmJU7OTkx\nZswYqlSpgq2tLa+++irnzp3j6tUHN/ti5WmP+wt+OKgeBOzojvW160uvuPquw87jKDsOJLJp5zl5\nKIsQ4p4wqoWczfyDmHPjiD0/kYvZewAVBUtqOgfTqvIEXA3NAIUCVc9fVxez8dwHpF1LKOeeCyFE\n+arwNxYePXoULy8vHB3/ufGufv36nDlzhtzc3GLr/+n1eqZMmcL06dOJiIgw2/buu++avU5MTMTG\nxgYXF5f79wZKYFXJAfcX/FB/OfJ/NxsuJ98mD9fakaiqJYdOQO61fEKDfbHSVPjrICFEOTAU5nA6\nI5YTaWvJLUg2lVtZOFDbtT11XEOxt/IgNzeXSoZ8Amp04XD6YtL0Z0i9dooNZ8egcw+ngUdPNBY2\n5fhOhBCifFT4IDo9PR1nZ2ezMldXVwDS0tKKBdFz5swhMDCQZs2aFQuib5SRkcH06dMZOHAg1tbW\nZeqTXq8nNze3TPsU42iBQ3ht1FUqAX8+z8GWKyiwvoZbndWkHn+ek+dq82t0HKFPe2NjbXl3bZWj\nvLw8s/+L0pFxKzsZs+tyC5I5nbWBczlbKVCvmcrtLSvh69QRb4dgNBa2kA+5+bmm8bIprMLTlSZw\nOmsDxzNXUKgaiEtdydnMHTR0608l2wbl9ZYeOvJZuzMybmUnY3Zn9Hr97SuVQoUPooFS5wifPHmS\n5cuXExkZect6V65cYfDgwTRo0OCOcqIvXbrEpUuXyrxfSaz8NXgcqETAn89xsOUKCq0MuNddSerx\n7lxO9uWX9cfxrwm21jd/TGhFkJCQUN5dqJBk3MrucR2zaxaJpFntJltzHJR/fmfaFnrhZmiGQ2Ed\n9BkWxHOmxP3/GTcfaigDuGITTa7mDLkFV/jz6qc45ftRSd8OS+zu/5upIB7Xz9rdknEru9KO2Q8/\n/MDWrVt57rnnCAsLu2Xdd999l/DwcNq1a8fUqVOpXbs2L7744j3o7aOjwgfR7u7upKebL/+Wnp6O\noii4u7ublU+ePJmhQ4cWK7/RuXPn6N+/P23btuWDDz645TPsb6ZatWqm2fB7oaBmDharLfDf+RyH\nW0RQqMnHQxdBclxPcjNrcuS8hi7B3ri72N6zNh+UvLw8EhIS8PHxwc5O/viWloxb2T2OY6aqRi7l\n7ed01npSDTeuNKRQ3a4pvk4dcbepfctj3GzcVPUpLub+yZH0nzAYs8iyOoLe5ix+ri/hZf/UHf3u\nfFQ8jp+1e+FRGLdz586xcOFCdu7cSWZmJs7Ozvj7+zN48GC0Wi0AgYGBVK9evcQJvU8//ZSlS5fy\n3Xff0aRJE+bNm8f8+fP56KOPCA8PN6ublpZGhw4d0Gq1LFiw4LZjlpmZSXR0NDNnziQ4OPi278XK\nyopq1aqZHo3t6elJvXr1yjAaD6/09PR7MtlZ4YNoPz8/Ll26RHp6uilwPXToEE8++aTZByoxMZG9\ne/dy8uRJZs2aBVx/5ryFhQWxsbGsWLGCtLQ0Bg4cSK9evXjrrbfuuE82Njb39hn2vvbY9rJB+VXB\nb2c3DrdYidGygEr1VnD1aC9ysp5g1ZazPNe2Nl5VnO5duw+QnZ3dvR2zx4SMW9k9DmOWb8zjTMYW\njqdFkZOfZCrXKLb4urajrltnHK0ql+mYJY1bXYf21HRvzl9XvichcysGYxb7U+dxSb+TJlUGl7mN\nR83j8Fm7HyrquMXFxdGvXz9eeuklVq5ciYeHB4mJiSxYsIDXXnuNJUuW4O/vD4DBYODYsWMEBgaa\n9jcajWzevBkXFxdsbW2xt7fH2toaT09PNmzYUGwWOCIiwhT3lGbM0tLSUBSFunXrlmp8FUXB2toa\ne3t7LCwssLKyqpDnpST3Kv2lwgfR9erVw9/fny+++IIxY8aQlJTE4sWLTY+47NSpE9OnT6dx48Zs\n2bLFbN8ZM2ZQrVo1Bg8eDMAXX3xBw4YN7yqAvl+svZxx71kfflPx2xXG4earUS0NVG6wnCtHeqHP\nrs5vMSfo0tqX2t5u5d1dIUQ5yM1PIT59HSfTN5JvzDGV22s8qOvWBV+XtlhbOtzTNm0snXiq2lB8\nnFuzJ2k+OflJXMo5wLozI/H37E1dt85YKBX3vg1R/lR9Lmrq5QfapuJeFcWmbAHjlClTCAkJYcSI\nEaay6tWrM3HiRHx8fLCysjKVt27dmlWrVpkF0bt27cLb25vExESz4wYFBbF9+3auXr1KpUqVTOVR\nUVG0atWqVM+zSEhIMKVvdOvWjSFDhnD27FkMBgNffPEFcD2wDwgIYMmSJTRt2rRM7/1xVeGDaICZ\nM2cyYcIEWrVqhaOjI3369KFPnz4AnD17ltzcXBRFoUqVKmb72dnZ4eDgYErvWLFiBZaWlmzYsAFF\nUVBVFUVRmDJlSrGvUcqD9RMuuPVogPobNNjThb+bRWK0uEYVv+Vc/bs317Iqs2bLKdo296ah9vGe\nARLicZJ27QzH0tZwLnMHKv+s4exu+yRatzBqODXHQrm/v+6rOgQQ6vMFf6f8yrHUNRSqeg5c/YGz\nmdtpVvVN3Gxr3df2xaNJ1edSsHAs6O/yZv2ysrFHM/CTUgfSqamp7N+/n9GjR5e4/ZVXXjF73bFj\nR0aPHs3EiROxtLx+kblmzRpCQ0NZuHChWV07OzuCg4OJioqif//+wPVv1y9cuEBYWFipgmgfHx/W\nr19Pu3btWL16NT4+PowbN65U703c3CMRRFepUoX58+eXuC0uLu6m+82YMcPs9dGjR+9pv+4Hmxou\nuHevDyug/t7OHA1aS6FFLpX9fiXlaB9yMtzZtPMcOXn5tGhY/bHOSxTiUaaqRi7l/MWxtDVcyf37\nhi0KXo5BaN3CqGSne6C/AzQWNjSs9DLeTk+zJ+lbUq+dIk1/mg1nx6J164qf5wuyHJ54JJ0/fx5F\nUfD29r5tXUVRqFOnDl5eXmzbto02bdpgMBjYsmUL77//PgsWLCi2T3h4OLNnzzYF0ZGRkYSGht7R\nz7c8sO3eeSSC6MeNTU1X3J+vBytUdPs7EtdkPQVkU6nBL2iOvURGqjM7D14iOzef9k/VxMJCAmkh\nHhUFRj0Jmds4nhZJluGfr30tFRt8XUKo69YFJ+tq5dhDcLOtRXvvacSnredw8s8UqHqOpa3mfPZO\nmlZ5naoODcu1f6LiUP5vRvhhT+coCmYLC//5Jmjv3r0MGDAARVEwGo1Ur16d6OhoUxDbrVs3Vq1a\nRZs2bdi6dSsBAQG4uZWcjhkcHMz48eM5ffo0vr6+REVFMW3aNI4cOXIX71LcLQmiKygbHzfcnqsH\nK0H9y8ixxtEYjJm4637G+mQ/rl6x50h8Mrl5+XR5xhcrjeQkClGRXStIJz59PSfTN6AvzDKV21q6\nUsctlNquHbCxfHhuLLZQLNG6d+EJp2bsTfqOSzl/kZN/hS0XpuLj3JrGlV7FRuN8+wOJx55iY49S\nzbe8u3FLPj4+AJw6dcqUtxwUFMShQ4eA6zcBzpkzx2yfrl27MmvWLHJycoiMjLxl2qhGo6FLly6s\nXr2asLAw9Ho9fn5+9zSIvvECQJSOPO6uArP1dcetWz2qJNaj7sF2AOiN6TjX+ZknvAoAOH0hg982\nnCDvWkF5dlUIcYcy9OfZdfkbVp9+i79TlpsCaFebmjSvOpQw329o4NH9oQqgb+RgVYnWXuNoUW04\nNpbXn/6akLmNqIThnMnYKl8ti0eCs7MzLVu2ZNGiRSVuLylA9fDwICgoiHXr1rFnzx7atm17yzbC\nw8OJjo5m7dq1t13j+WZuTP+wtrY2W6Xi7Nmzd3TMx5kE0RWc7ZPuuIXrqHbBn9qHQgDIK0zGrtb/\nqON7/fReuprDL+uPkZl9b57QI4S4v1RV5XLOQbacn8q6hJGcydiMUb1+IVzNoTEhT0ykY83PqOXy\nDJYWVrc5WvlTFIWazk/TudaX1HJpA4ChMItdl+ew9cI0sg1JtzmCEA+/Dz/8kEOHDvHee+9x8eJF\n4PrTj3/99Ve+/PJLGjVqVGyfbt26MXfuXFq1aoWt7a2f9RAQEADAqlWr7nixgxsvWn18fDh48CBJ\nSUlkZWWxaNEiNBpJUCgLCaIfAbZ1PHAN0+J1tiG+R64voJ5TkISF12IC6l//oUzNuMbPa49xNe0B\n3+EshCi1QmM+pzM2sz5hFFsuTOVy7kEALBQrfF3aEerz/3jmifFUdfCvkDcN21g60bzqENrUmISj\nVVUALuceZF3CSI6lrsaoytfJouKqVasWy5cvx9bWlr59+9KoUSNCQ0PZsGEDH3zwgWkpuRt/dtu1\na0dmZqZZUHyrn+1u3brh4eFBjRo17qiPNx67Z8+eNGjQgE6dOtGzZ0/CwsLMAnlFUUz1K+LvmwdB\nUeW7tHsmNzeXuLg4fHx88PDweODt5x1PJn3NMc49uYcz9XcA4Gz9BO45b7FjXyYANlaWhLetTY2q\nD8dXv0VjVvREJFE6Mm5l9zCPmb4wi5PpG4hPW8e1wgxTuY2lE7VdO1HHtSO2Gpdy6dv9GrcCo56/\nU5ZzLHW1aVk+N5taNK36Bu62T96zdsrDw/xZe5jJuJWdjNmdSUlJISEh4a7HTebtHyF2Wk8waiEK\njJYFnNXuJtNwAQvH+bR/+h1idySjzy9kRcwJQlv7UremPJRFiPKUaUjkRGokZzK3UqgaTOXO1l5o\n3bpS0zn4kV0S7vpyeH2p6fQ0u5PmkXrtJGn6M8ScHUddty74e/ZGY3Hrr7eFEKI8SRD9iLGrVwnV\nqFJzrYrRopDzdfaRrj+Lhe1curR9l/VbL5FfYCTy/x7K0kgnD2UR4kFSVZWreUc5lrqGxJz9wD9f\nBlax90fr1pVqDo1QlMcj287VtibtvadyMj2aQ1d/okDVczwtkgvZuwiq8jrVHIrnkQohzMXExDBh\nwoSbpl0EBQUVe4iLuHsSRD+C7BtUBlWl1jowWhZy0fcAqddOodjO4flnR7Am9gJ51wqI3XWO7FwD\nTzf2knwnIe4zo1rAuaw/OZ66hjT9GVO5BZZ4O7dC69blsX2qn4ViSV23zng5NmVf0kISc/aRk3+V\nrRemUdOpFY0r9y+3dBYhKoIOHTrQrVu38u7GY0eC6EeUvV8VMKo8GQ1GiwIu+Rwh5doJjiuz6dVp\nJKs2niUj28Duw5fJycunfYuaWFo8HjNfQjxIhsIcTqVv5ET6WvIKUk3l1hYOPOn6LHXdOmGncS/H\nHj48HKwqEew1hvNZf7L/yn+5VpjB2aztXMo5QOPKr+Lj/Ixc8AshHhoSRD/C7AOqohpV6sSA0aKQ\nJO84ruYd5bAyi16hI1m96SxXUnP5+2QKuXkFdH3GFysreSiLEPdCtiGJE2lRnM6IpUD9Z3lJR6sq\naN26UsslRHJ+S6AoCt7OLanqEMCBq//jdMYmDMZsdl3+moTMbQRVeR0n66rl3U0hhJAg+lHn0Kga\nGFW0m1RUi0KuPHGCpNxD/KXMpGfH94jcksC5S1mcuZjBrxtO8Hy72tjZPvzrzgrxsErOO86x1DVc\nzN6NekO+cyW7emjdulLdsQkWilys3o61pSPNqr6Jj3Mwey5/S1b+JZJyD7M+YSR+Hi+gde+KhSJ/\nwoQQ5Ud+Az0GHAKrg6qi29wRo4WR5OonuZTzF3uvzqJb23eJ2XGBY2dSuZycw9J1x+jevi4uTo/m\nigBC3A9GtZCL2bs5lrqGlGvxpnIFC2o4tUDr1hUPu9rl2MOKq7J9Azr5fM7fqSuIS1lJoZrPweQf\nOZu1naZV3pRxFUKUGwmiHxMOTbxQjSr1tnbib4soUque4UL2biyUr+nYahgOdlbsO5pEWqaepeuO\n8Xz7OlR2lzUnhbiVfGMepzNiOZEWRU7+VVO5lYUdvi7tqesWioNVpXLs4aPB0sKaAM8X8XZqyZ7L\n80i5Fk+6/iwbz42njltn/D17Y2VhV97dFEI8ZiSIfow4Nn0CjNBge2eONFtDWuVznMvagYViReug\nITjYW7Ft7wVy8vJZtv4Y4W1q413Nuby7LcRDJyc/mfi0tZzK2Ei+Mc9Ubq+phNatM74ubbGylIvQ\ne83Vxpt23lM4lR7DweSfKDDmcSItigtZuwiqMpjqjoHl3UUhxGNEgujHjGPzJ1CNKg3+7MqRZqtJ\nr3SBhMytWCgamtZ/HQc7K6L/SMCQbyRiYzydgmuh9ZGVA4QASL12imOpazif9ScqRlO5u21tdG5h\nPOHUXPKd7zMLxZI6bp2uL4d3ZQEXs/eSW5DMtosz8HZ6msDK/bHVuJZ3N4V4pPTr14/GjRszcuTI\ne3K8CRMmkJ+fzyeffPJQ9ausZE2zx5BTixq4NH8Sv91hOKdUA+B0xib2X1mErpY7z7erg5XGgkKj\nStTW0+yPSyrnHgtRflTVyMXsPWw6N5ENZ8dyLuuP/wugFZ5wbE67GlPo4D0db+eWEkA/QPZWHrSq\nPpqnq7+HreX1oPlc1h+sPTOc0xmbUVX1NkcQ4t47e/Ys48aNo3Xr1jRq1IjWrVszbNgw4uLiTHV0\nOh3t2rUrcf+pU6ei0+nYs2cPALNnz0an0xEREVGsbmpqKk2bNmXq1Kn3583cR1OmTLnrAPphIEH0\nY8qxZQ1cmj2J/65uOKVVASA+fT0Hri7Bu5oTL3TSYm97/YuKLbvP8/u+C/JHSTxWCox64tOiWXtm\nOL9f/JSredf/CGoUG+q4htKl1ixaeY2ikr1O1i4uJ4qiUMPpKTrX+oonXToAYDDmsPvyN2y+MJks\nw6Vy7qF4nMTFxdGjRw8qV65MREQEBw4cYOnSpXh6etKnTx8OHz5sqqvX69m/f7/Z/kajkZiYGFxc\n/nmwkKIoeHp6smbNmmLtrVu3zqyuePAkneMxpSgKjk97oxpV/Hc+x6GWK8h2ucrxtDWmm3heDNWx\nYmM86Vl69hy5/lCWDi3loSzi0ZZXkEZ82npOpm/AYMw2ldtp3Kjr2pknXdtjbelYjj0U/2Zt6UDT\nqq9T0zmYvUnfkmm4yJXcv1mX8B4NPHpSzz1clsOrwPSGAlIzrj3QNt1dbLGxLttnZsqUKYSEhDBi\nxAhTWfXq1Zk4cSI+Pj5YWf2zfGzr1q1ZtWoVgYH/5PHv2rULb29vEhMTzY4bFBTE9u3buXr1KpUq\n/XOjclRUFK1atSI+Pp7SSElJYdKkSezZs4fCwkICAgKYPHkyNWrUYNy4cSiKgp2dHStXrsTGxoZ3\n3nmHPn36mPbPz89n0qRJREZGYmtrywcffEDnzp0BSExMZMqUKfz111+oqkpISAgTJ07EwcGB3bt3\n88YbbzB8+HBmz57NwoULWbp0KQaDgS+++AKAVatWMXfuXK5cuYJWq2XSpEnodDoAFi9ezI8//khy\ncjLVq1dn+PDhdOjQobSn5b6S3yqPMUVRcAquCYUqAX8+z4GWy8l1TuFoynIsFSsaePTgxVAdEZvi\nSUrJ5eipFHLy8gkLeRJreSiLeMSkXzvLsbQ1nMvcjpFCU7mrjQ86tzBqOLfAUpE11B9mle3r0bHm\nZxxNXUFcSgRGNZ/DyT9zLvMPmlV9Ew+7OuXdRVFGekMBC5YfRm8ovH3le8jG2pJBPfxLHUinpqay\nf/9+Ro8eXeL2V155xex1x44dGT16NBMnTsTS8vrf0zVr1hAaGsrChQvN6trZ2REcHExUVBT9+/cH\nrgetFy5cICwsrNRB9MyZM3F1dWX79u0UFhYyY8YMPvvsM2bNmgVAdHQ048aNY9y4cWzZsoV33nmH\nwMBAtFotAGvXrmXGjBlMmDCB2bNnM3nyZDp16oSFhQVDhgwhKCiImTNnkp2dzXvvvcd//vMfPv74\nYwAKCgo4d+4cO3bswNramqVLl5r6deTIET766CPmz59PYGAg8+bNY8iQIWzatIl9+/bx5Zdfsnz5\ncmrXrs3KlSsZNWoUW7Zswc3NrVTv+36SKcXHnKIoOIX44OL/JA3/fB67rOsfysPJSzmWuhp7Oyt6\nddRSs/r1VTrOJmbya/RxcvPyy7PbQtwTqqpyKecvNp//mPVnR5GQudUUQFd3CKRNjUl0rPkpPi6t\nJYCuICwtrPD37E1Hn8/wtL3+xz/DcI6Ycx+wL+m/ZqupCHGvnD9//vrTNr29b1tXURTq1KmDl5cX\n27ZtA8BgMLBlyxZCQ0NLTJ0MDw9n9erVpteRkZGEhoaWKZUsMzMTKysrrKyssLW1ZfLkyaYAGq7P\nmvfs2RONRkP79u2pV68eW7ZsMW0PDAykZcuWaDQaOnXqRGZmJqmpqRw6dIiTJ08yatQorK2tcXd3\n5+233zbrb0FBAX379sXa2rpYv1atWkXLli1p2rQplpaWDBw4kFGjRqHX6wkKCuKPP/6gdu3r68F3\n7twZvV5f6guH+01mogWKouDcphYYVRr+2Z0DT//GNYcMDlxdgoViRV23UJ5rV5sNf5wl7nQKSSm5\n1x/K0qEurvJQFlEBFRoNJGT+zvG0SDINF0zllooVPs4haN264GzjVY49FHfLxaYG7bw/5mR6DIeS\nfyTfmEd8+jouZu+mSZXBeDk2Ke8uilKwsdYwqIf/Q5/OURTMFhb+M2O+d+9eBgwYgKIoGI1Gqlev\nTnR0tClI7tatG6tWraJNmzZs3bqVgICAm86uBgcHM378eE6fPo2vry9RUVFMmzaNI0eOlLqPgwYN\n4q233mLbtm20atWK0NBQnnrqKdP2WrVqmdWvXr06V65cMb1+4oknTP+2sbn+t99gMHDhwgUKCgpo\n3ry5abuqqhiNRtLS0syOV5Lz589Ts2ZN02tbW1tTmkhBQQGzZ88mOjqatLQ0VFVFURQMBkOp3/f9\nJEG0AP4vkG7nez2Q3nE9kNbbZ7H/yn+xUDTUdu1Ap1Y+ONpbsefIZdKz9CxdG8fz7etQxcOhvLsv\nRKkUkMvxjJUkJMaiL8wwldtYulDHtRO1XTtgq5EbdR4VimJBHbeOeDkGsf/Kf7mQvZvcghR+v/gJ\nNZxaEFj5New05f+VsLg1G2sN1So93Pch+Pj4AHDq1ClT3nJQUBCHDh0CICIigjlz5pjt07VrV2bN\nmkVOTg6RkZGEh4ff9PgajYYuXbqwevVqwsLC0Ov1+Pn5lSmI9vPzIzY2lu3bt7N582beeecdevXq\nZUpBufECADAFrEVuNuttY2ODg4MD+/btu2X7RWkr/1Z0kVGSOXPmEB0dzbx589DpdBiNRurXr3/L\ndh6kRyKdIzExkTfeeIPmzZvTtm1bPv/889vuk5SURGBgoNmH2mAwMHHiRJ555hlatGjBu+++S3p6\n+v3s+kNFURScOzyJW506NNzRHeu867+09iZ9x5mMLSiKQnCTJwhpWgOA3GsFLFt/nLOJGbc6rBAP\nhVNZ60lw+IbjmRGmANrFugbNqr5FuO83+Hn2lAD6EWVv5UErr/dpVX2UKWg+n/Una8+M4FT6Jll5\nSFS0tLYAACAASURBVNw1Z2dnWrZsyaJFi0rc/u8AFcDDw4OgoCDWrVvHnj17aNu27S3bCA8PJzo6\nmrVr1xIWFlbmPmZkZGBlZUWbNm34+OOP+eabb/jll19M28+dO2dWPzExkSpVqtz2uN7e3uTm5nLx\n4kVTWU5OTqnjpxo1anDmzBnTa4PBwH//+1/S09M5fPgw7dq1M91kWJaLhgfhkQiihw4dStWqVYmN\njWXx4sXExMSwePHiW+4zdepUNBrzifj/9//+H3FxcSxbtsz0lcu4cePuY88fPoqi4PJsbdz/P3vn\nHR9Fnf7x92xJsrvp2fRCIJRUCFXAgPSqYPfQU8/u73eed4ciKoKnqD+9szdOD0/OO05FAemKVAHp\nNUAgBEjvu9lN2b4zvz8WNkZqIJDCvF+vvJbd2Zl95mF29jPfeb6fp0t3ev18K2qbFpDYUf4xBbVb\nAOiTGsnEoV1QKgScLpHFa/LIOWFo3cBlZM5DQe1mDpm+RBJcAERqe3JD3AzGJb5Fl6ARKBVn1unJ\ndDziAq5jfOI7dA0eA4BTbGBnxd9ZV/QXah0lF1hbRub8vPDCCxw4cICnnnrKKyjNZjPffPMN77zz\nDpmZmWesM3nyZObMmUNWVhZ+fn7n3X7Pnj0BTw3x+Uatz8VvfvMbPv30UxwOB06nk3379jUpoygp\nKWHp0qW4XC5+/PFHjh49el5hf/ris1u3bmRmZvLqq69SU1NDbW0ts2bNYvr06RcV16233sqOHTvY\nuHEjLpeLefPm8e9//5uAgABiY2M5cuQINpuNvLw85s6dS2BgIBUVbaN/RbsX0dnZ2eTm5jJt2jR0\nOh0JCQk88MADLFiw4JzrbNy4kRMnTjBs2DDva263m4ULF/L73/+eyMhIAgMD+dOf/sSGDRuoqqq6\nCnvSdhAEgaCx3Qjr1J1eW29FbdcgIbGt7H2K67YD0KNzKLeM6oaPWoEoSazadJLdh8pbOXIZmTMx\nWPPYUf4xAErRnxsiZzM8fibRukzZ3/kaxEepo1/kI4yMn02gj6fuvcp6mO/zp3HIsBC3JE+alrk0\nOnfuzMKFC/Hz8+Puu+8mMzOT8ePHs3r1ambMmOG1c/vleWfkyJHU1tY2EcXnOy9NnjyZsLAw4uPj\nmx3fu+++y4YNGxg4cCBZWVls27atyZ37G264gb179zJw4EBmzZrFiy++SFJS0jlj+uVrb7/9NqIo\nMnLkSMaOHYskSfzf//3fRcWVnJzMm2++ycsvv0z//v3ZsGEDc+bMQalU8vjjj+N2uxk0aBDPP/88\nf/zjH7n55pt55ZVXWL9+faufwwWpnd/H+vrrr/nnP//JDz/84H3twIED3HXXXezevRutVtvk/Xa7\nnYkTJ/Laa6+xePFiYmNjeeKJJzh58iQTJkxgw4YNTW5f9O7dm3feeaeJ4D4XFouFnJwcEhMTCQsL\na7F9bC0kUcK0MpfqksPsH7wQl48dBUquj53mnZRTabSweM0xGk65dfRNjWRov7iLPrBP5ywlJeWM\n/yuZcyPn7eKwOA2sLngOm7sGpeBDTMPd9O4xXM5ZM+jIx5pbdJJj/I7DxkWIkucuRZBPPP2jHkOv\n6XHJ2+3IObuSyHlrPi2Vs+eee66Jb3NHx2AwkJ+ff9l5a/cTC00mE4GBgU1eCw72tICtqak5Izkf\nfvghffr0YcCAAU3aaJ6u3fl195/AwMAms0svBrvdjsViadY6bRWfYXGErHZ6GrIMWoxb7WBLyZsM\nCP8TEX4Z+PvB5OGdWPFTIeZ6B7sPV2CutzK8fyxKxYWFtNVqbfIoc3HIebswLtHOz5VvYHN7vr+p\n/vdhq9PLOWsmHf1Y66KdSLi6N/uNn2N05GJ2FLGmcCaJ/iNICboDtULT7G129JxdKeS8NZ+WypnL\n5cLlcnUY7XIh7HZ7i2yn3Yto4KInheTl5bFw4UKWL19+2ds6H2VlZZSVdaB2s/ESIbUxZGybzIFB\n3yGqnGyvfJcY2x1o3Z56qrQ4iewCqLNCXmEt1YZa0hJApby4Een8/PwruAMdFzlvZ0dCotx3KfVq\nz2SVUMf12Mr0gJyzS6Wj5y2UW1Cp9lPtux5RsJNfv5bi2h2E28fg7760Ji0dPWdXCjlvzefrr7/m\n448/Pudd4OTkZJ599tlzrm8ymXC5XOTk5FypEDsk7V5Eh4aGnjED1GQyIQgCoaGhTV5/6aWXeOKJ\nJ854/fR2Tq+r0TSOPJjN5rO+/3xER0d7R8M7ClKyiOWHADK2i2RftwRR5aJcu4hB4dMI9fX8wKSk\niPy4tZjC8npMDXC0zI8JQxLQ+p37MLNareTn55OYmNgk7zLnR87b+ck1L6G+1vNjEK3pT7+4h7HZ\n7HLOLoFr61hLxeYeT3bNfyiz7sSlqKNMs5BoTT8yQu7FT3lx5/VrK2cth5y35nM6Z3fddZe3m+Gl\n8N5777VcUO0Ak8nUIoOd7V5Ep6enU1ZWhslk8grXAwcOkJSU1ORLWFpayq5du8jLy/N26LFYLCgU\nCtatW8e3335LYGAghw4dIjo6GoDc3FycTicZGRnNisnX17dD1nNpb0lDuUSBuNPNwQHLcCvtbK9+\ni2FxswjTeLoJ3TK6O2t+LuDQcQPVJhtL1hdw6+huhASef9axRqPpkDm70sh5O5Oium0cqV0EQIhv\nZ66PexKVwg9B8MyjlnN2aVwredOi5YaAZyip38muirlYXUbKrLuoth+mV/hvSQoa6T2WLsS1krOW\nRs5b85Fz1jxaqmSo3btzpKSkkJGRwVtvvUV9fT3Hjx9n3rx53H333QCMGzeOPXv2EB0dzYYNG/ju\nu+9YsmQJS5YsYcSIEUyZMoW5c+eiUCi48847mTNnDuXl5dTU1PD2228zZsyYZo9Ed1QEpYKQSSlE\n+2eStmsCgqjAKVrZWPwKNTbPbXOlQsGY6xO5LsNzIWKut/PVqiOUVze0Zugy1wg1tpNsK/N4v/sp\ng8iKfQaV4vwXcDIyZyPWvz8TEt+hW/BYQMApWthV8anHDs8u2+HJyMh0ABENntsQFRUVZGVlcf/9\n93PLLbcwZcoUAAoKCrBYLAiCQGRkZJM/jUaDTqfziuQnn3ySzMxMJk+ezOjRowkICGD27NmtuWtt\nDkGlIOTmFKL9+pCyezyIAg6xgQ3FszHZPUbtgiBwfZ9YRlyXAIDV5uKbH45yskRuyiJz5bC6athU\n8gZuyY5CUJMV+ww6tb61w5Jpx6iVWvpGPsyohNkE+XgsxaqsOXxf8DQHq7/BLcp2eDIy1zLtvpwD\nIDIykk8//fSsy85XJP9rD0O1Ws3MmTOZOXNmi8bX0RBUCkJvSYFFEtIeNzl9f8DurmND0cuMSHjJ\n672amRyB1k/Fqk0ncbpElqzNY8z1iaQmtX/7P5m2hVt0sLnkb1hcnqY/AyIfR6/p3spRyXQU9Joe\njEl8gyPGpRwyfIsouThoWEBh3Rb6Rz5OuDa5tUOUkZFpBTrESLTM1UdQKwm5JZU4ZX967B0NEtjc\nZtYXvkSdo7HpSvfEUG4d3R1ftRJRkvh+80l2HiyT2+zKtBiSJLGz4hMMtmMApITeTGLQ0FaOSqaj\noRTUpIXdxrjENwnXpAJQ6yhhbdFMdlX8A4dbLlmTkbnWkEW0zCWj8FEScmsa8dJ1dDvgaQ1qddew\nvuglGpyNXR7jowK4c3wPdBo1AJt2l7BhZ5EspGVahCPGpeTX/gRAjK4vPfVTWjkimY5MoE8sI+Jf\npH/k46gVOgDyTKtZlf9nb0dXGZn2wMyZM89re3c+HA4HycnJ7Ny5s4Wjal/IIlrmslD4KAm9PZVO\nzsF0zb4BAIurmvVFL2FxGrzvCw/RMmVCMqFBnklee3MqWfHTCdxusVXilukYlNTvYn/1fACCfBIY\nFPPHi3ZOkJG5VARBQVLwSCZ0fof4gEGApyZ/c+mbbC75G1aXsZUjlGktCgoKeO655xg6dCiZmZkM\nHTqUJ598sklpaXJyMiNHjjzr+q+88koTcfrBBx+QnJzcpDncaYxGI/379+eVV165qNhEUWTevHne\n57Nnz+b1119vxt7J/Br510bmslH4qAi9PY1E2xC6HMoCoN5Zwfqil7G5Gj28A/19uWtcMtHhntGb\n3PwaVmwqxOWWR6Rlmo/JXsDW0vcACV9lAEPipl9SdzmZc2MwWdl5qJIKkyTfOToLGlUI18dMZUjs\ns2hVnrkexfU7WF/+PCbVHiRJHiS4lsjJyeG2224jIiKCxYsXs2/fPr766iv0ej1TpkwhOzvb+167\n3c6ePXuarC+KIj/++GOTzsmCIKDX61m2bNkZn7dq1aozuiyfj0OHDjF37txL2DOZcyGLaJkWQeHr\nEdJdGm4gMcczMlPnLGV90cvYXbXe92n8VNw+pjtJ8R5P79IqC/tOwtF8E9U1VkRR/qGWuTA2l5lN\nJW/gkmwoUHJ9zDT81RGtHVaHwOF0c/BYNV+tzOFfSw6x+3A1R4ph/c5SXPKdo7MS69+X8Z3foXvw\neEDAJVmp8lvN5spXMduLWjs8mavE7NmzGTZsGH/+858JC/NcVMXExDBr1iymTp2KWq32vnfo0KEs\nWbKkyfrbt28nISEBf3//Jq/369ePAwcOUFVV1eT1FStWkJWVdVGxHThwgClTpmAwGOjVqxc7duzg\nueee46mnnvK+Z+XKldx888307t2b0aNHs2DBAu8yq9XK1KlT6d+/P2PGjGHdunUXl5QOTodw55Bp\nGyj8VITekU7S1xJirovC7jsxO4pYXzybEfEv4qP0nBjUKiU3DUti7bYCso9V02Dz/EBDKSqlgvBQ\nDRGhWiLDdESGaQkN9kOpkK/3ZDy4JSdbSt/y1t33i3qUCG1KK0fVvpEkifLqBrKPVXP0pBGn60yx\nnFtgprbhKDcNSyJA59MKUbZt1AoNfSIfpFPgELaVfUyds5gaRx4/5E8jJewWUkNvRalQX3hDMmcg\n2l24DC3THONiUYVpUPhevEQyGo3s2bOHZ5555qzL77vvvibPx44dyzPPPMOsWbNQKpUALFu2jPHj\nx/PZZ581ea9Go2HIkCGsWLHC25WwtLSU4uJibrrpJo4dO3bB+Hr27Mns2bN566232Lx5M0CTEpHs\n7GxmzJjBxx9/zMCBA9mzZw+PPPII3bt3JzMzkzlz5pCbm8vKlSvx9fVl1qxZ52wxfi0hi2iZFkXh\npyLsznSkr0XEPDfFXfdgsuezoegVhsfPQq30dFRSKARGDeqE1k/BnpxKnC7P+i63SFlVA2VVDYBH\nJCkVAvoQDZFhOiLCtESGadEHa1AqZWF9rSFJErsr5lJl9dQX9gi5kS5BI1o5qvaL1eYk54SR7GNV\nGEy2JstCAv3I6KYnNsKP1ZvzMNRBeXUD/12Rw03DkoiJ8D/HVq9twjTduCHyJbYe/4Ia358RcXLI\n8C1FdVvpF/mYfMHXTES7i8pPdiLZ3Vf1cwVfJRGP9b9oIV1UVIQgCCQkJFx424JAt27diI2N5aef\nfmL48OE4HA42bNjAtGnTzlpyMWnSJD744AOviF6+fDnjx49vMSG7ePFiRowYwaBBnjvJffv2Zfz4\n8SxZsoTMzEzWrFnDPffcQ3h4OACPPPII33//fYt8dntGFtEyLY5Coybszp50/xpEhZvSLvsx2o+z\nseQ1boib4a1bFQSB3sl6fMVKEjp3o65BosLYQKXBQoXBQoPV08jALUpUnHrN+xkKAX2whsgw7Slh\nrUMfokElC+sOTW7NSk6YPbcRo3WZ9Ar/bStH1P6QJImC0loO5lVzvNCE+xclVCqVgh6dQkjvricm\n3B9BELBYLKQlQIOkZ/fhahqsThb8cJSR1yWQ0T28Ffek7aIQVIQ6B9Gr0wQO1n5BpeUQtY4S1hXN\nIiloFL3Cf4uPUtfaYcq0IKfFrNvdKPZ37drFgw8+iCAIiKJITEwMP/zwg3d+weTJk1myZAnDhw9n\n48aN9OzZk5CQkLNuf8iQITz//POcOHGCLl26sGLFCl599VUOHjzYIvEXFhaydetW1qxZA3jOE5Ik\nMWTIEADKy8uJi4vzvj8xMbFFPre9I4tomSuCUqsm7M4Mkr8GSeGmLPEg1dajbCp+g6Fxz6FS+Hrf\nKwgC/ho1EWFakhKCva/XWxxUGi1eUV1haKDe4hHWoih5lhktcOpOlkIQCAv284rqiDAt4SEa1Crl\nVd13mStDWcNe9lX9C/DYjA2K/hMKQf6/vVhq6+0cyjNwKK+a2gZHk2VReh3p3fT0SAzF1+fMnAqC\nQP/UCGIigvh+s6d50o9bC6g0WhjWP16+K3QO/NVRDI97kZO1G9hX+S8cYgPHzWsoqd9N38gHifO/\nTr4lfgEUvioiHuvf5ss5TovK48ePe0drT9cyg2ek98MPP2yyzo033sj7779PQ0MDy5cvZ9KkSeeO\nR6Vi4sSJLF26lJtuugm73U56enqLiWg/Pz+mTJnCCy+8cNblDocDl8vlfS5PNPYgi2iZK4ZS53NK\nSEuIShcV8UeotB5ic8nfGBL7DErF+esq/bU++Gt96BLXKKwtVicVXmHtGbU+LQhESaKqxkpVjZVD\neR57PUGA0KBfjlhrCQ/R4qOWxVd7otZews+l7yAh4aPwZ0jsdHkk7yJwu0WOF5nIPlZNQWltk2V+\nvkpSuoSR3k1PeIj2orbXrVMIIYF+LFmXh7nezv6jVVSbrNx0QxJajVzvezYEQaBL0HBidL3ZUzmP\nwrot2Nw1bCl9i1j/fvSNeBitWu7iej4Uvip8YgJaO4zzEhgYyODBg/n8888ZOHDgGct/OUJ9mrCw\nMPr168eqVavYuXMnb7zxxnk/Y9KkSUyfPh2lUslNN93UYrEDxMfHnyHIKyoqCA8PR6FQEBERQXl5\nYyO1Y8eOyReAyCJa5gqj9PdBf1cGKV+JiAqRqthcyi372VL6NtfHPnXhDfwKrUZN59ggOsc22vpY\nbS4qjQ1UGBpHrc31dgAkyWPTZTBZOXy80bc6NOjUiPWpCYzhodqzjsDJtD52dx0/lbyOU7QioOT6\n2KcI8Ilu7bDaNAaTlYPHqjl83IDV7mqyLCE6gIxu4SQlBF+w/Ely2FBu/C/RdRZIjAetFn2Ihrtv\nTGHlxhMUlNVSUlHP/BU5TBqeRGSYfGFzLvxUwQyO+ROJ9UPZVfEPLK5qSup3UWE5RE/9FLoGj5Hv\nrLRzXnjhBe6++26eeuoppk6dSmxsLGazmdWrV/Puu++eVVxPnjyZt956i6ysLPz8/M67/Z49ewKw\nZMkSPv/882bH5+vrS319PZWVlWdY491xxx38+9//ZvHixdx4443k5eXx2GOP8fzzzzNu3DiGDh3K\n119/zdixY1EoFGdMfrxWkUW0zBVH6e9L+F29SPtK4qBiMdXRxylt2M3W0vfIDH7ssrev8VPRKSaI\nTjGNJwWb3UWl0dIorI0NmGrt3uVGsw2j2caRE41NEUICfYkI1XlHrSPCtPj5yF+R1kSUXGwpfZt6\np2cEpG/kg0Rq01s5qraJw+kmN7+G7GNVpybmNuKvVZPWVU96Vz1BAb7n2MKZiDtXojiyjXBA+joP\nMes2hIwhaHxV3DKqG5t2F7P7cAV1DQ6+WnWEMYMTSekij6qejxj/PozXvk129dccq1mJS7Syp/Kf\nFNRuon/U4wT7XnhimkzbpHPnzixcuJCPPvqIu+++G7PZjFarJS0tjRkzZjBhwgSAJiO4I0eO5MUX\nX2xSynG+Ed7Jkyezfv164uPjmx3foEGDiI2NZfTo0Wc0WenSpQtvvfUW7733Hi+99BIRERE8/PDD\njBs3DoCnn36aGTNmMG7cOIKDg3n++efZsGFDs2PoaAiSXNjSYlgsFnJyckhMTPR6RMo04q61UfX1\nPg50X4gxKh+AWO1ANJVDSU1JQ6u9uFvKl4rd4T5VY93gLQkxmm3nXScowJfIUG2TOmtNM+rkrhSn\nj7WUlJQrnrfWZFfFXPJMPwDQLXgsfSMfvuRtdcScSZJEWXUDB89iTacQBJISgknvqqdTTCAKRfNu\nvUq2BlyfTQdH0++IENUF5Yh7ECI7AZBzwsDqn/Nxn2qa1DctkiF94pr9eR2Jiz3WDNY8dlb8HZO9\nAAABJSmhk0kLu+2C5W4dkY74Hb3SyDm7NAwGA/n5+Zedt9ZXAzLXDMpAP/R3ZpKxQGK/8htM4UWU\nWLYR4NtAinTlbZ98fZTERwUQH9VYW+dwuqk6PWJt9NRZG802Tl9amuvsmOvs5BbUeNcJ9Pdp4mMd\nEaZF6yfXg7Y0x2p+8AroSG0GvSN+17oBtSGsNieHjxs4mFd9hjVdaJAf6d30pHYJu6w6ZXHfOq+A\nLknKIqbmOIKxDKn8BK4vX0HRaziKQTeT0iWM0CBPnXS9xcnuQxVU11iZOLQLfm3ggrMtE6bpyphO\nr3PUuJyDhgW4JSeHjYsoqttK/6jHiNCmtXaIMjIy50E+w8lcVVRBfoTf0ZueC0T2p32DWV9CnTqb\nPcZPGaz9A0rh6opRH7WS2MgAYiMbhbXT6aaqxnpKWHtqrQ0mq1dY19Y7qK13kFfY2NI8QHdaWDeO\nWuvkiVaXTEVDNnsq/wlAgDqa62OmohCu7dOV15ruWDV5RaYm3T1VKgU9EkPI6BZOdLjusif8SA4b\n4l6P1ZUY2wNDbAYRw2/DN/dnxK1LwWlH3LcOMXcXyqF3EJE8kHtuTGX5huOUVNZTUFrL/BU5TB7e\nFX2I3Ir9fCgEFSlhNxMXMJBdFZ9SYcmmzlnGuqK/0CVoJJnhv/U2qpKRORc//vgjM2fOPOd3v1+/\nfnId8xXg2v5VkmkVVMF+RNzRh57fSOzPWEBtaBkllq38VFxPVszT3oYsrYVarSQmwr9JMwmnS6S6\n5nR9teex2tTYpryuwUFdg4PjRY3CWqdRN4rqUE8piL9WLc9ovgB1jjK2lL6FhIhaoT3lxHHtiojT\n1nQH86qpa6Y13aUiHtgINk9dtdhnDJhdoFSi7DsWRff+uDcuQDq2Cyy1uL//DOHgJrQjfsvtY7qz\nYWcR+49WYa6z8+XKHMYP6UzXhLN738o0EuATxbC4meTX/sTeynk4xHpOmNdSWr+LPhEPEh8wSD53\nyJyT0aNHM3ny5NYO45pDFtEyrYIqREPk7X3puUDkcOoyjJH5VFiyWVs0ixvinkejCm3tEJugVimI\nDvcnOrxRzLncIgaT1ethXWmwUF1j9TavaLA6OVFs5kSx2buO1k/lHamODNMSEaolQOcj/ziewuFu\n4KeS13GIDQgIDI6ZSqBvbGuHddVxuUVOnMeaLrVLGOndwq/IKK/kciDu9pTRCDHdkKK7gvmId7kQ\nEIrqxscRCw7hXjcfTJVIxbm4/vMSij6jGXHdjYSHalm3vRCnS2Tp+uMM7BXNoF4x8nF+AQRBoHPQ\nDUTrMtlb+S8K6jZhc5v5uewdYmp/om/kQ+jUcoMbGZm2giyiZVoNVaiGoIlppC6EvNR1lHc6hMle\nwI8FM7ghbgZBvnEX3kgrolIqTolhHeD5YXO7RQxmm1dUVxgsVNVYvJOuLDYX+SW15Jc0CiONr8rr\nYR0RpiMyVEug/7UnrEXJzc+l71DnKAWgd8TviNb1auWori7VNVYO5lWTcxZruk7RgaR315MUf2Fr\nustBPLgZLJ7j091vHF8W7KXBUUuMI7HJBBxFpzSEe19C3PU94o6V4HZ6/n1kO+nDfkPomO4s33Ac\ni83Ftv1lVBmtjB/SWfZovwj8VEEMinmSxIah7Kr4lAZnFaUNu6k8eYie4VPoGjxWtsOTkWkDyCJa\nplVRhmmoyfCj+/5R+Fr9KUjejsVVzdrCFxgSO51w7ZWfcNiSKJUKIkI9I8x087zmFkWMZptXVFca\nGqisseI65aRgtbsoKK1tMuLo66NsIqojwrQEB/h2aGG9v+rflFv2A9AlaCTdgse3ckRXB4fTzdF8\nIwePVZ9hTReg8yGtaxhpXfUE+V+8Nd2lIrldiLu+B0CI6MRalZIdpYUAHDu0hnHxaYyOTcZH6fnp\nEFRqlANvQpE8EPeGL5FOHoD6GtzL5xCVmM7dQ+9k2W4TFQYLx4tMfLkih0kjuhISeH4/XBkP0bpM\nxie+TXb1AnJrluOSbOyp/Jz82k0MiHqcYN9OrR2ijMw1jSyiZVodR7AS3dguJK4CX5s/x3quw0ED\n64tnMyj6SeIDzjSob08oFQrCQzydEtO6el4TRckjrI2NpSCVRovXoszucFNYVkdhWZ13O75qJeGn\nGsQEB6hosElNJpe1Z46b1nK0ZgUA4ZoU+kY+1KEvGCRJoqyqgYN5Z7GmUwgkxQeT3k1Pp+jmW9Nd\nVlw5W6HO450uDJjI5orj3mUO0c3SggNsKs/jtsRM+oV38v4fCcHhKCf/AenEPtzrv4Q6I1L+QTRF\nR7i973jWBaaTc7IGg9nGf1fkMHFoFxJjg84ag0xTVAo/ekfcR6fA69lZ/gk19pMYbXn8kD+d5NBJ\npIXdhkpx5S+wZGRkzkQW0TJtAnXnYILGdIUfwMem43D/VYhKJ1tK36ZPxAN0D+lYo5IKhYA+RIM+\nRENqksdTXJIkamptv+i82ECl0YrD6WkXa3e6KS6vo7i8UVjvPXGEsGCNd1vhIRr0IVq0fqp2I0Ir\nLYfZXfEPAHTqCLJinr7qLi1XC4vNSc5xAwePVWMwn2lNl9FNT0pSWKtYJkqiG/eOlZ4nYTEcCYvA\nUO6phe6jCsPsB8frDdTYLcw9+jPrSnO5s0sfOgfqAU89r5DUGyEhFXH7csTdq8HtQrFjGSODthHe\n7U42nXRjd7hZvPYYWX3i6JcW2W6O09Ym1C+J0Z3+j9yaFWRXf41bcpBjXOy1w5ObEMnIXH1kES3T\nZtD2jMLd4ITN0GvLrRwctAyn2sKeyn9icVbTK/weBOHK1YK2NoIgEBqkITRI4+36JkkSpjq7V1Sf\n9rO2OzzC2i1KngYyRkuTbWn8VOiDG0W1PkRDWLAfalXbqqOsd1SwpfRNRNyoBD+Gxj6LryqwHLA0\nkgAAIABJREFUtcNqUURRorCsluxj1Rz/lTWdWqWge2IoGd30LWJNdzlIubvAXAWAcsBENpWfBECn\n8qG3OpS07qnkWo18e3Iv1bZ6TtRV8/r+1VwXkcgtiZmE+HrqpQW1L8qs21CkDsa9bj5S0REEcxW9\ndn1EWKdhrLKnYnOIbNpdTKXRwpjBndrccdlWUQhKkkMnEed/HTsrPqXCcoB6Zznri16ic+BwMiPu\nxVcZcOENycjItAiyiJZpU/gPjENscMBe6P3THWQPWYbVx8iRmqVYXUYGRP9vhx2lPBuCIBAS6EdI\noB89OnscSyRJoqLKzP5DeWgDwjHVu6iusWKqa2wSY7W5KCqvo+gXo9bgaW1+WlSfFtlBrVRr7RSt\nbCp5A7u7DhAYFPMngnyb38q2rVJbb+dgXjWH8gxnWNNFh+tI76qnR+fQNjHRTpJE3Ns95TQER1KX\nmM7+XUsBGBCWgLJOgSAI9NbHkx4aw/rSXFYUHsTmdrK9Mp891UWMjUtlbFxKY710aDTK255COroD\n98YFYDETV7CBO32yWRF2Cwa7iqMnjdSYbUwankTgVaj57ij4+0QyLO4FCmo3sbdqHnZ3HSdr11Pa\nsIc+EQ+QEDBYHuGXkbkKdAgRXVpayksvvcS+ffvQ6XRMmDCBp59++qzv/fDDD1m0aBEmk4nY2Fge\nfvhhr7diTU0Nr732Gj///DMul4uUlBSeeeYZUlNTr+buXNMIgkDgiC6IFicchcx1t3F4+CrMvsUU\n1G3G5jZzfcxT+Ch1rR1qqyEIAoH+PugDBVJSwr2OCU6XiNFspcpopbrG42NdVWPFamt0eaiptVNT\na+fYLzowqlUKb0nIL0eur2R7c1Fys7X0PcyOIgB6hd9DrH/fK/Z5V4vzW9OpSE0KI72rvs01IJHy\n9oLR44qiHDCen6vyEU9dkQ3UJ2KoK/K+V61QMiYuhYERnVlWcIBN5cdxim6WF2azpfw4N3fuxYDw\nRBSC4CnxSL4OoXMG4taliPvWEuQwcHvZPNaGTiCPGCqNFuavyOGmG5KIi5JHUS8WQRBIDBrqscOr\n+hf5tT9hd5vZWvYu+bUb6Rf5iGyHdxUZMWIEjz32GHfddZf3tXnz5jF37lzmz59Pp07yJNCOSIcQ\n0U888QQZGRmsW7cOg8HAI488gl6v53e/+12T9/3rX/9i6dKlfP755yQkJLB69Wr+/Oc/06NHD5KT\nk/nLX/5CfX09q1atQqPR8OGHH/Loo4+yadMm+ar+KiIoBIIndMdodUIhZKyZRO6o9VT65lBhyWZd\n0YsMjX0OrTqstUNtU6hVv7Tca6TB6vSI6hqPqK6usWIwNfpZO10i5dUNlFc3dYbw16pP1VprvaPW\noUF+KFvAXi27+ktKG3YDkBh4A8khky57m61JdY2Vg8eqOHzCiO3X1nQxgWR009PlClvTXSqSJOHe\ncWoUOiAUqcd1bN7rqY3uHhRBhJ8/hrOsF+jjxz3dBnBDTDe+ObGHI6YKahwWPj+6lfWn6qWTAj0i\nTvDVohz2G2+Jh0/ZccYZl7LLrw/btP2x2lx8uzqXYQPi6dUjXD7fNgNfVSADo/9AYuBQdlZ8SoOz\nkrKGvaw6+Wcy9FPoFjJOtsNrBb777jvmzJnDF198IQvoDky7F9HZ2dnk5ubyxRdfoNPp0Ol0PPDA\nA3zxxRdniOiUlBTefPNN7wE9duxYAgICyMvLIzk5mcOHD/PQQw8RGOipyZw8eTKffvoplZWVREZG\nXu1du6YRVApCbk7B8FU2VDaQvHoUfuOCKVRvxWQvYE3haS/pjnP7/0qh06jRaYLoFNPohiCKEqY6\nm1dUe/4smOsbyw7qLU7qLc4mntYKQSAkyO8Xo9YawkOa14nxpHkjOcYlAIT5dad/5GPtUjQ5nG6O\nnjSSfaz6jAuQ09Z06V31bb5MQco/CJUeGztF//Ecraum+lS3wqFRXS+4fpwuhD+lj+CAsYRvT+yh\n0lZPfp2Bv+7/kf7hnbg1MZNQP8+FnRCRgPKu6UiHtuDetJD+tj3o3dX84D8KJz6s215IpdHCiOsS\n2uQFR1smSteL8Ylvc7B6AUdrluOS7OytmkdB3Sb6Rz5OiF9ia4d4zbB+/XpeffVV/vGPf9CjRw8A\n7r33XgYPHszhw4fZvHkzcXFxvP/++/z3v//lu+++w9/fn9mzZ5OVlQXAkSNHeP311zl06BBqtZqJ\nEyfy7LPPolR6LojmzZvH/Pnzqa6uJiQkhKlTp3LjjTcC8Nxzz6HT6VCpVCxevBiFQsFDDz3Eww8/\nDMCiRYv45JNPqKysJCQkhHvvvZcHHnigFTLV/rksEe1yuVCpWleHHz58mNjYWPz9GzvJpaamcvLk\nSSwWS5PmAAMGDPD+2263880336BUKhk0aBAAw4cPZ8WKFYwcORKdTsfixYtJSUmRBXQrofBVEXpb\nGob/HsBttpG4qj/am8I4IizH4jKwpnAmQ2KnE9HOvKTbAgpF4yTGHomNr9sdbgwm66lRa8/odbXJ\n6p3IKEoSBpNnJPvoycb1fNXKXziEnJ7IqDmjFXW1NZedFX8HQKsKY0jsNJSK9lPjftqaLvtYNbn5\nZ1rTdT1lTZdwla3pLhVJkhC3L/c80QahSMtiU+42AHQqXzL18Tht9gtuRxAEeoXFkRYSzYayYywv\nyMbqdrKzqoB9hmJGxyYzNj4VP6UaQVAgpA9BSOqNe/MiOh/8iTvNi1gRMA6TMtjjXGKyctOwJPy1\nPldy9zscKoUvmRH30ikwix3lf6fGfgKj7TirC6aTHHoTaWF3tEs7PIe7wduE6WoR4BNzSWWDu3bt\n4plnnuG9994jMzOzybJvvvmG999/nzfeeIO7776bBx98kD/+8Y9Mnz6dl19+mb/+9a9kZWVhs9l4\n+OGHuf/++/nss88oLy/nf//3f/nss8949NFH2bVrF++88w4LFy4kJiaGTz75hBkzZnD99dcTEhIC\nwIoVK3j22WeZNm0aS5YsYebMmdx888243W5mz57NN998Q9euXTl06BAPPfQQgwYNIjk5uUVydy3R\nbAUsiiIffvghixcvxmAwcODAAaxWK6+//jozZszAx+fqnvRMJpN35Pg0wcHBgKfG+Zci+jQzZ87k\n22+/JTY2lo8++oiwME9ZwLRp03jssccYMmQIgiAQExPD3Llzr/xOyJwTpb8PoXd4hLRocRK5oiua\nm+9jn+s/OMUGNhTPZlD0H4gPGNTaoXYIfH2UxET4ExPReFEqSRL1FmejqD5VFlJjtnnrZu1ONyWV\n9ZRU1jfZXqC/j0dUB2sIDLFyzPVXRMmFUvBlSOx0/FTBV3X/LpXT1nTZx6ox/sqaLizIj/RWtKa7\nHKTio0hlHi9oRb8x1Iou9hmLARgc2Rm1QomzGdtTKZSMik1mYEQiSwuy+aksD6foZmXRIbZUnOCW\nxF5cF9HZUy+t8Uc1+j7E9OsJXTefO6sW8YNuJAU+nSiramD+8sNMGt6V6HD/C3+wTBNC/DozutNr\n5NasPGWHZyfHuISium30i3yUKF3P1g7xonG4G1h24vc4xYYLv7kFUSt03NTlo2YJ6ZycHN588036\n9+/P4MGDz1jeu3dv0tM9VoQDBgxgw4YN3HzzzQAMHTqUJUs8d+jWr18PwCOPPAJAbGwsDz74IJ98\n8gmPPvoo/fr1Y8uWLfj7+2OxWBg8eDCffPIJx44d8w4WxsXFeed7TZgwgeeff578/HxCQkKQJAk/\nP0/Do7S0NLZt23YpKZLhEkT0Bx98wKJFi7j//vt59913AbBYLOzbt4/33nuPadOmtXiQF0KSmtdw\nYvbs2cycOZPly5fz2GOP8cUXX3hrogVBYOPGjfj7+/PFF1/w4IMPsnLlSjSai58IZLfbsVgsF36j\nDFartcnjWfEF7Y1J1C/OBadI4LIw+k36H/a4/oFbcrCl9B3SgyvoEjDmKkXd+lxU3loQpQBRoT5E\nhfoAnrIQtyhhqrVjMNsxmm0YzDaMZjsN1saa4Np6B7X1Dk6UVKJPm49aZwbAVjSZLaUuwoKKCA32\nJSzID63flb2r1dyciZJEcUUDR07WkF9Sxy/72qiUAl0TgkjpHExEqMZTjiI6sViaIzlbH+XWpSgA\nyU+HvesANhYf9V4Y9QuOxWKxXNKxpgBujknjupB4lhQf5GhtJWaHlXm521hbfISb4zPo4n9qTkNQ\nNEz+M6rDm5m4cyU73Bns0vShweri61U5DO0bTfIpZ5r2wtX+fp6LBL+R6KN6cqDmX1Tasql3VrCh\neDbx2izSgqfgo2xbFyhny5tTtEIzf+NbBEnCarXiusg7SpIksXz5cp544gk++ugjvvjiC26//Xbv\nclEU0ev1Xm2gUCiaPAdwOBxYLBZOnDiBwWCgV69eTbbv4+ODxWLB5XLx7rvvsnbtWmpqahBFEUEQ\nqKur8y6Pioo6Q4eYzWZSU1OZMGEC48ePp2/fvgwaNIhJkyYRFHRtNT+y2y98h+1iaPav1pIlS5gz\nZw6pqam89957AISFhfHOO+9w3333XXURHRoaislkavKayWTyeO6GnvvE6+Pjw6233sqKFSv49ttv\neeqpp1i0aBFfffWVt3zjf/7nf5g3bx5btmxh1KhRFx1TWVkZZWVll7ZD1yj5+fkXfI9Pmoqw/Q4E\np4jvMhVxA+6iOHghboWFg6b5FFceQ+8YjkDbv43eUlxM3q4GQWoI0kMXPThd0GCHBpvnr94moY5f\ngVpXCUBt4RDqSztThRkwe7ehVoLOz/Pnf+pR6wvKFi6LuFDObA6J8hooN4H9V5o4UANRIRAeJKFS\nmjFWmjFWtmh4Vw1tbTldS3IBqIhKo+LYcX6yeWp0ohUaDCeLm0wovNRjbagUTGdfNVsdVZglB0UW\nEx8c3UQXZQDXqcMJOF3Oo4xA1edOkk/8jN70I2t0w3ChZsOuck4cPUmnBA2KdlY731a+n4FMQKHq\nTJXPGtwKC0WWzZQ27EZvH0WAK7XNnTN/nbd4HsWpMF7VGNRiKHlHCy76/U6nk9tvv52MjAweffRR\n/vrXv6JUKr0lEhaLBaPRSE5ODgAGgwGr1ep9XlhYiCRJ5OTkYDKZiIuL4/XXXz/jc3JycliwYAGb\nNm1i2rRpJCQkIIoi9957L4WFhQQHB2MymXC5XN5tn+b08ttuu42srCx27drF0qVL+eyzz3j55ZcJ\nD5fdXJpLs0W00Wg8q+Vbp06dMJvNZ1njypKenk5ZWRkmk8lbxnHgwAGSkpLOGD1+/PHHGTJkCPfc\nc4/3NYVCgUqlwu12I0kSLlfjKJooijidzR9Zio6O9sYic36sViv5+fkkJiZe1Gi/I8KIdXU+Sgd0\nORBNl5tfYEf9ezS4KjD57EAXLJAZ+kiH95Jubt5akyPmReTWesRaEH2IDplEjcKOwWSntt7B6TEm\npxtMDZ6/0whAoL+asGBfQoP8CAvyPAbqLn4i42nOlzO3W+RkaR1HTpoormh629jPR0n3xCCSO4cQ\nGtj+6knPhXLVTwBIPhrCht1Gtb2OumOe/6dRndJICY0DWuZYSwVGSSJbqk7yQ+kRLG4nJ9x1FIoN\nDIvsysiobvgpT31ne/UloCSX2zf/wEqxP7XKQArrNLiPNTBqRAqagLY1eno22ub3MxWHeyyHTF9S\nZNmMW7BS4bcM0S+fXiH3o1W1voBqm3m7ONRqNbGxsaSkpJCSkkJtbS0ffvgh8+fPJyoqCq1Wi16v\nJyXFM4cnLCyMsrIy7/OamhoEQSAlJYXq6mq+/fbbJnkwm82o1Wq0Wi2VlZWMGjWKsWPHYrVaWbt2\nLQAJCQmkpKQQHByMw+Hwbvs0CQkJJCcnU19fT0pKCsOGDQPg0UcfpbCwkKFDh16lbLU+JpOpRQY7\nmy2iY2JiyMnJISUlpUkZxc8//9wqVzEpKSlkZGTw1ltvMX36dCoqKpg3bx4PPfQQAOPGjeO1116j\nT58+9O3bl7lz59KnTx+6d+/Oxo0b2bp1K4888gj+/v4MGDCAOXPm8MYbb+Dv788///lP1Go1/fv3\nb1ZMvr6+Z63Fljk3Go3monKm7aVF7VZQu/YEYq0d1ff1jLzjZTZX/Q2jLY8Sy3ac1JMVM+2a8JK+\n2Ly1FoW1W8it9dT5hfolMSJ+apOJTU6XG4PJ5nUH+bW3tQSY6x2Y6x2cKG5sHHPa2/q0Q0hzvK1/\nmbOLsaZLig9uEVu/toRUWYir8BAAyswR+ISEsSPnMOCZUHhdTBJqRdNJoS1xrI3TZZAV253lhdls\nLD2GSxJZU57LDkMhNyf2YlBkZxSCArpl4tclnd/sWMPKw6UUq2IocehYvOowN/XUEtG7f7twdGlr\n308tWq4P+CPlDSPYVfEJ9c4KqmzZrC+fQYb+LrqHTGgTdnhtLW8XgyAI+Pj4eOOeOnUqR48e5emn\nn+a///0vCoXCK4LBI7oVCoX3ua+v57yo1WoZOXIkoaGhfPDBBzz99NNYrVaeffZZkpKSmDVrFvHx\n8Rw/fhyFQkFpaSnLli0jICAAk8mEVqtFpVIhiuIZOfT19WXDhg188MEHzJkzh86dO1NSUkJVVRVd\nu3Ztdzm/HFqq1KrZInrSpEn8/ve/56GHHkKSJFavXs3Bgwf58ssvW80i5b333mPmzJlkZWXh7+/P\nlClTmDJlCgAFBQXeuqCHHnoIl8vFo48+Sn19PXFxcbz66qveQvx3332X119/ncmTJ+N0OunevTtz\n58695mqF2jq6PjG4Gxw0bCvGVdmAdVkJw2+ZydbK9ylt2E2l5RBrC2dxQ9zzspd0K2K0HWd7+UcA\naFQhDIl95gxnALVKSZReR5T+6nlbO5xu8nKrOHgOa7r0rnrSuoa1eWu6y8HrC63yQdFnFLUOK/sM\nngmFg05NKLxS+Kt9+U1SP26I7sa3J/ZysKaUWqeNL45t9/pLdw+ORFCq8B80jltTqvnp+63ss0dT\nK/jz9QEno3K/IGXMGITQ6CsWZ0cmSpfBuMS3OGT4liPGpbglO/uqvqCgdjMDoh4nxK9za4fY7vj1\nRZ0gCLz55pvccccdPPfcc8266FOpVHz88ce88sorDBkyBJ1Ox6hRo5g+fTrguas+depUBg0aRFJS\nEvfddx/79u3jlVdeOWcZ6+nPnzhxInl5edx///3U1dWh1+u54447GDFixCXu+bWNIDVzVp4kSXzw\nwQfMnz/fW76h1+t54IEHeOCBB1AoOtaITXOwWCzk5OSQmJjodfyQOT+nc5aSktKsq2BJkjD/kIc1\nuwIAvx56Am/syp7KzzhuXgN4LNQ6qpf0pebtamF1GVld8CxWVw1KQc3IhNmE+iVd1jbP5m1dVWOh\ntt5x3vVOe1uHBKipq6vFUCfgcjee9hQKga4JwaR3bT/WdJeDZCjF9cWLgISi7xiUQ+/k+6LDLM7f\nB8BLfScSpW0cOLjSx9pBYynfnthDmbXRj7xPWDy3du5NuKaxdCN7617WHXXgPjVS2te2l8GpYagG\nTkRQt60Lnrb+/fwlNbZ8dlb8HaPN49IioKBHyETS9XdddTu89pS3toKcs0vDYDCQn59/2Xlr9ki0\nIAg8+eST/OEPf8BoNOLr69vEo1lG5mogCAJBY7oiWpzYjxuxHa1GoVPTd/gjaNV6squ/+oWX9DQi\ntGmtHfI1g0u0s6nkr1hdntbi10X9/rIFNDTT27rGit15pre1B4+ADgv2I6NbOCldQtG0M2u6y8G9\nYyUggVKFos8YRElic3keAN0CI5oI6KtBemgMKSFR/FSWx7KCAzS4HOwxFHHAWMKI2B5MiE9Ho1KT\nMag3+s4mlq45SoNbyW6/3lQfKWBs7stoh92BIinzwh8mcwYhfomMSniVY6bvya76Epdk50jNMorq\nt9Mv8lGidb0uvBEZmWuUZovogQMHsm3bNgRBkEdbZVoVQSEQclMPDAsO4iytw7KnDKXOh7SBt6FR\nhbKz/O+nvKRfYWDUH0gIPNO3U6ZlkSSJHeVzvKNaaWG3kRB4/RX9zIvxtq6qsVJlaKDeYqdLfDC9\nU6KI0uvaRV1tSyKZKpGO7gBAkT4EwT+YIzXlVNk8/t5Doy/cofBKoBQUDI/pzoDwRFYUZbO+NBeX\nJLK6OIetFSeZ3Kkn10d1IToqmHtu7c2yNUcoq3FQ4NOJBe4gJi7/D2GdfkI5fApCUOtPkGtvKAQl\nPUImEuc/gF0V/6CsYS8Nzko2Fr9Cp8Ah9A6/Hz+VXNYoI/Nrml17kZiYyPbt269ELDIyzUZQKwm9\nNRVVmOd2TN2mAiwHyukSNJwhsc+iEnwRJRc/l73LUeOKVo6243PYuIjCui0AxPlfR3rYna0ShyAI\nBOh86BIXzICMaCYO7cKdY5MYlCwwrF8M0eH+15yABnDv/B4kERRKFP3GAbDp1Ci0TuVDb33rlj7p\n1D7c2aUvf+kzkZ6hsQDUOW38J28Hr+79niOmcvy1PtwxMZ30rnoATMpgvgm8hRPFJlz/moV7+3Ik\nV/vy624r6NThDI19jsHRf8JX6RHNBbWbWJn/Z06aNza7J4OMTEen2SPRWVlZPPvss6SmppKQkIBa\n3fQ26NSpU1ssOBmZi0GhURN6RxrV8w8g1tkxr85DoVUT07U3IxJeYmPx/2F3m9lbNQ+Ly0Bm+G8R\nhGu3dv9KUVy3nezqrwAI9k1kYPQTcp7bEFKdEemw5wJHSBmEEBhGrcPKXkMRAAOv8ITC5hCpDeT3\naTdwuKaMb07sodRiprjBxDvZ6+gVFsdtnTMZPbgTEWFaNuwoxKHwZbn/eAZad9Lv5+8QD29FOeJu\nFJ3kMq7mIggCCYHXE6nryb6qf3PSvB6Hu47t5R+SX/sT/SMfxd8nsrXDlJFpEzT7F27RokUIgkBO\nTg4//PADy5cv9/6tWCGP9Mm0DsoAX0LvSEPwU4EENcuO4iiuJdQvidEJrxKg9sziP1qzjK1l7+MW\n5ZGqlqTGdpKtZR8A4KcMOuXE4dfKUcn8EnHXDyC6QRBQ9h8PwNaKk94OhUOiWqeU43ykhkTzQp/x\n3N21P/4qzyS3/YZiXtq9koUn99K9azC3jemBxk8FgsA27QC+9x+Nw2TAvegdXCv+jlRf08p70T7x\nVQZwXdT/Mjz+Re/5s8JygFX5U8kxLkGU3K0coYxM69Pskeh169ZdiThkZC4bdZiW0FtTMSw4CC4R\n4+LDhE3JwF8fyaiEV/ip5HUMtmMU1m3B5jKRFXtteElfaWwuE5tK3sAt2VEIKrJip6FTy3WpbQmp\nwYyY7WmuInTvjxAS2WRCYdfAcKKv8oTCi0UpKLghuhv9wzuxsvAQ60qP4pZEfiw5wtaKk0xK7Mlv\nJiSzYsMJKo0W8nySqAkOZWLtSoJyd+E6mY1i0GQUmSMQlFe2tXxHJFKbztjEv3HYsJAc41LckoP9\nVf/x2uG1xKRhGZn2ivIvf/nLX5q7Ul1dHd9//z1r1qxhx44dVFdXExcXd0Zpx7WG0+mkurqa4OBg\n2WrmIjmds/Dw8BY5fpSBvqgjdNiOVIFLxHbciKa7HrVGR6fALMyOQuocpTS4qiit302sfz/Uyvb3\nf9XSebtU3KKTjcWvUevweAwPiPpfYv37tlo850J0uKldcwLN3lqchw3YjxmwF5hwltfjMloRLU4k\nlxtBqQCl0OHqpcXty5FOtfhWTXgUQRvIEVMFa0uPAjA5sRdxupCzrttWjjW1QklqSDT9wztRY7dQ\nbq3FIbrJNpZyuLaU4WmJqF0+GExWrIKGo9o0IpyVBDlrkAoOIebtRdDHIQRe+QnxbSVnLYVCUBGp\nyyAuoD81tpNYXUZsbhMnzGtxihbCNckohMu/QOloebsayDm7NKxWKyaT6bLz1uyj/tChQzz44INe\nk25RFDEYDISHh/Pll18SGxt7ycHIyLQEfkmhBI3rhnnVMcQ6B8ZvDxI2pScqjS/XxzzN7orPOG7+\nEbOjiB8LZ3BD3PME+ya0dtjtDkmS2FnxCQabR5ylhE6mc9ANrRzVmbhqrNR8l4Or2oICkOocOOrO\n7S0tqBUoA31RBPiiDPRF+etHfx8EdduoHb4YJFs94v71AAhdeyPoPefo0xMKtSof+urbz/EfoQng\nf1KHctRUwYITuyluMFFqMfPhkY2kh8aQGZDI/uxqbKKSJYE3kqU4Qq+qDQiGEtwL3kBMHYxyyO0I\n2sDW3pV2R7BvJ0YmzCbPtJoDVf/FJdk4WrOcorrt9I96hGhd79YOUUbmqtJsEf23v/2NESNG8Oyz\nz3o7+RmNRl599VXeeOMN3n///RYPUkamuWjTIxEbnNT9lI/LYMW48DBhd6WjUCvpF/kIWnUY2dVf\nYXUZWFs4kyGxz8he0s3kSM1S8ms3AhCj60uGfkorR3QmtmMGTCtzkRye+k2bXkFgdBiC1Y271o67\nzo5kbdruW3KKuAxWMJy7LaxCo0JxNoF96lGh80FoI01bxL1rwWkHQDlgIgC1Dltjh8KItjOhsDn0\nCI5kRu9x/Fxxgu/yD1DntHGwppTDQhmDUrtRm6vE4XSzyZ1MddckhhUtQGWvQzr8M67j+1BcfwuK\njBsQruEGYZeCQlDSPWQ8sf792V0xl9KG3VhcVWwsfo1OAVn0jvidbIcnc83QbBF94MABPvroI3S6\nxlrS0NBQZs2axcSJE1s0OBmZy0E3IBZ3gwPL7lKcZXXULD1CyM0pCEoFaWG/9JK2yF7SzaSkfjf7\nq+YDEOQTz6CYP6IQ2o4Qk0SJui0FNGzzCEUE8BscS6mPgcjU+CblVpLTjbvOjrvWgbvOdurR7hXZ\nYp0dySk22b5odSFaXbgqmrYN9yJ4JrsqAnxRBvicVWgLfqorXjYi2a0eEQ0IiekIkYkAbK08gVvy\n7FNWG5xQeLEoBAVZUV3pq+/EqqJDrC05gksS2WLNJTBWS+eqBGwNIjlGNca4h5ig3of/kQ1gtyCu\nm490aAuKEb9FEZXY2rvS7tCp9QyJnU5R/Tb2VHyGzW2moG4zZQ37yIy4j86BwzpcWZRrPSpSAAAg\nAElEQVSMzK9ptoj29fU96xfDx8cHl8t1ljVkZFoHQRAIHN4Z0eLEllOF/UQN5tV5BI3rhiAIdAka\njkYVwpb/Z++9w+Oorz3uz8xs31Vb9S7bslXci9wLtgFTjGkGAgSIw6XcF0LIEyC8EKcREu69hISS\ndvMmBELJtR3AxpS44o57t9xUrV52V23r7Mz7x8qyZclYsiVLsufzPH6s3fntzJl5ppw5v3O+p/xV\nZNXH1srf4pEdZNnn97Xp/RqXr5RtFb8DVIxSGDOSf4ReNPe1WW0o7gDOlcfwl7gAEC16IhdkE4zW\nQ76jw3hBL6GzW9DZO8+NV1UV1Su3OdWh/8842kpT6HvOltBVCY1r9HFeHRideI5zfZaz3eqAi4ZL\nezFR9q8Hnzt0HFqj0KqqsrnyTEFhknXgRw3NOj13DBrDjIRMPiray576UzSKbg7EHmOQmIq+yUS1\n08v/mUYw//rxxO/5P6grQ60uJvjhy6ijZiFOux3BpBUadwdBEEgLm0KCZST7at+jsGEtfqWZHVV/\noKRxExPiHyHMkNjXZmpo9BrddqJzc3N57bXXeO655zAYDAD4fD5effVVsrKyetxADY1LQRAEIm8c\nisMdwF/iwnOoBtFqIHxmBgCJ1jHMSfs5G8t+jTfYwN7ad3DLdYyJfVDTOO4En9zIpvL/Qla9iEhM\nS3qmX2nG+iubcK04SrAxlL6gTwoj6tZsJJsRt9t9UesUBAHBrEc069HH2zodoyoqSov/HEf7tJMd\ncrgV9znutKwQdHgIOs6fNiKYdJ3nZbc63KLNeN60ETXgQ9mzOrSelGGIyUMBON5QQ01rh8L+KGt3\nKcSabTyWO4PjrmqWFO7hVIuTwphSonV2YpwxuL0yy/YEmZ33n4xwH0DZthz8XpQDX6Gc2B3Klc6d\nqkVQu4lBsjEx4XEywmews+rPNAUqqXYf5MviHzI8+i6y7bf0SOGhhkZ/o9tn9XPPPceDDz7IJ598\nQlpaqBiltLQUQRD461//2uMGamhcKoIkEnVbNo5/HiJQ3UzL9jIkix7rhFCBld00hGvTXmZD2cs0\nBSo55vwMt+xgcsL3kESt2vk0QTXA5opXaQnUADA+/hHiLLl9bNUZ3PuraFhbAMFQSNgyLpHwawaF\nFDd6GUEU2iLI50MNBAk2d3S0ldOR7UYfaqC99q7qlZG9MnLN+dNGRGvn6SKU70Nw+xEAaeKZ2ZWN\nlSeAUEHhuD7uUNhbDIuM54Wx89hWXcQnxfupj3LgM/hIrEkERWTt9lPUDhvGNQ+8BJuXhlqhe5oI\nrnob4fBmpDnfbivA1Og6cZbh3JDxKkccH5Ff/wlBNcCBug8obdpCXvzjRJuvrJc2DY1uO9FZWVms\nXr2aFStWUFpais/nY8GCBcyfP5+YmJjesFFD45IRDTqi7syl/oMDBF1eGtcXIVoNmHNCesY2Q3st\n6VNN2/DKDcxIfk7TkiaUArC7+q/UevIByIq6mSGRc/vYqhBqIEjD2kI8B6uBkLpGxPWZmHPj+tiy\n9gh6CV2UGV1U56kvqqqi+oLniWa3/t3kB+WsvBEVlGY/SrOfAE3nrNEI3AsEkVa7kcIOolh1hDc2\nMs5gZVBSIoLTjxIeuj6uNERBZFrCEMbHpPFl2RFWl+VToi8luSoJg2zgwPFa6lwebpm9CPOIGQTX\nvQ/OKtTyE8jv/Rxx3LWIkxcgGLSmQd1BEg2MjPkWaWHT2FH1J+q9x3H5SlhT+gJDo25kZMy3+lX6\nl4bGpXBRd06DwcCCBQsIDw9JBFVXV2M2axeFRv9Gshqw3zWC+vf3o7gDuD4/jmjWYcwI6eMadeHM\nTv0p2yp/R3nzLmo9R1hbupiZKS9g1V/dL4gnXF9Q2BAqUEu0jmF07AN9bFEIucGLc3l+W4GfFGki\n6rYc9LED78VHEAQEkw7RpEMf17n9qqqitAQ6Othnfz43bQSJoNNL0OkFYCat0m5Ffuq27Alt2yh1\niGaflvhT9AqoKgMVk07PbRmjmZ4whI+L9rFHKiWpJhGrx0pFTTN/X3GQO+cOI/7bP0XZswpl+2cg\n+1F2r0I5thNp1j0IQ8drKR7dJMKYyrVpL3HStZr9de8jKx6OOz+nrGkHE+IfIck2rq9N1NC4ZLrd\nbOXYsWMsXLiQ9PR0hg4N5dgtWbKEH/7wh0ybNu2qjkZrzVa6z+UWihdNOozpkXjyW5uxnHBgyIhE\nsoWm4UVBR2rYFHxyAw5fIb5gI6eatpFgHYVJF9nr9nWVy3ncKlv2s721pXe4IZlZKS+iE8+ftnC5\n8BU5cSw9jNIQyn82Ztqx3zkcXUTnkcMroSmBIAiIBgkpzIg+xoIhORzjoCjM2bFYRidgm5iCdUIC\nhqP/wBA4hj7chyFvArooM4JFT02gBVEBnXqOQxhUUdwBgk4vgapm/KUN+E7U4zlUg/9ALebqIHq7\nBVNsWN/seA9g0RkYH5tGdlQc+cIpGn1ezD4zQVnl4MlaMEH6mAmI2ZNQG+rAWQV+L+qJXagVBQiJ\ngxDMnefEn8uVcK71BIIgEG3OJCN8Js2Bapr8FQQUNyVNm2n0lxNrzkEnnrletePWfbRjdnH0VLOV\nbjvRzz33HBMnTuSee+5pKyzMzc2lpaWFZcuWcdttt120MQMdzYnuPn1xA5BsBvRJYXhauxr6Tjow\nDY1GNIe2LwgiidZxiIKOGvchZMVDSeMmos1Dsen7R4rA5Tpujb5yNpT9kqAawCBamZ36Uyx6e69t\nryuoqkrz16do+PIkyCGZtrAZ6YRfOwTxG5qgXC0PG/X4dsj/Ckloxnj9AkxjcjANsXMqSeV19rM5\nuZFB07PInDAU4xA7hpRw9HE2pAgTokkHohDKzT4r+CzKEDjuRK53Y0gKQzQO3PQPu8nKtIQhWOwi\nh1vKMLSYEFSRsvIW9teWM2xwCpYR0xDi0lArC0PqJg21obbpQRkhcTDCBXS1r5ZzravoJQvp4dOI\nMKZT685HVr00+E9R2LAOoy6cSGMGgiBox+0i0I7ZxdFnHQsPHjzIn//853YbNRqNPPHEE0ydqmns\nagwMjGmRRN6chWvFURR3AMfSQ0TfNxrJFnoxFASB4dF3YNHZ2VH1JwKKhw1lLzMp4UnSw6f1sfWX\nB1+wiY3lrxBQ3AiITEv6YZ/LVSleGdfnx/AVOAEQzDqibs7COKjzltVXG6qiENzxeeiDPQEh88yU\n+ZkOhXrGJWWgl3TnTXtR1dbIdKMPd5mT5q2lSH7wHqvDV+QkbHo6lrGJ/aahTHcRBYEp8YMZOzeV\nFUcOU3zAg07W464QeOvTXYybEM11g0aiS8tB2fkFyq4vISijbF+Jkv810ux7EQeP7uvdGHCkhk0i\n3jKC/bXvU9CwGr/Swo6qP1LcsJG8hMeQGPhyixpXF90uWzcajTgcHbVWKysrkaT+02xBQ+NCmLNi\nCL92CADBBh+OZYdRfO21zgdFXMPMlP8XnWBCUWW2Vf6Oo45P+8Lcy4qiymyt+C3NgSoAxsV9l3jr\nyD61KVDTQt0/9rU50PoEGzEPjNEc6LNQT+wOpSEAUt5Nbd34mvxe9tadAmBy3CAM0jfHTwRBQLIa\nMCSGYRgeQ80kE4aRoSJc1R+kcV0hde/tw195bjHjwMIk6bl75BjuvzkXKSw0q2F2m9m/1cVLW/7N\ngcZaxCm3onvgZwhpOaEfNdYRXP4m8oq3UBvr+9D6gYlBspKX8ChzU39BuCGkgFLjOcwXxT/keOOn\nqAQvsAYNjf5Dt9M5ysrKePvtt7Hb7fj9fmpra9m+fTu/+MUvmDt3LjNnzuwlU/s/WjpH9+nrqShD\nYhioKv6yRhR3gEBFE+bs2HYRtjBDAgnWMZQ370RWfVS59+NX3CRYRvVZsVFvH7c9NW9T2rQVgMzI\neYyMubvHt9Ed3IdrcH6Sj9paNGceFU/UghwkS9f3va/Ptd5GVVWCX/wF3I0QHoN07QNtTvTGyhMc\nclYC8MDQSYR3Q3EiEAhQ66gjccIQbFlxBKqbUVoCKC0BPAeqUTwBDMnhCLqBq6sebjKRNyyR6qYm\nXC4/kiJhcJnZ0nCCI95yUmNSiRg1G8GehFpRAAEvOKtCKR6CgJAwqF378Cv9XOsJrPpYBkfMRRQk\n6jxHUZCp8x3Bpd9FpWcXNZ5DuLxFtMh1BBQvoqBDJ5i0As9z0M61i6PP0jmeffZZFi9ezPe//30U\nRUFVVXQ6HfPnz+e55567aEM0NPoK27Q0gi1+PAeq8Z9qwPXZMSJvyW7nSNtNg0Na0uW/oslfwXHn\nZ3hkB5MTnkQSDX1ofc9z0rWKE64vAYi3jGRc3Hf6zBY1qNC4vgj33pADiCQQce0QLKMS+sym/opa\nuB/qQm3OpbwbEVqjzaqqtqVyDAmPIdl68QWyhsQwYr49Bve+Spo2laD6g7j3VuI9Xkf47MGYsmMG\nrJMjSSJ3zMzmQEIta78uQVRFkquTqPXV80vnl0xPHMKCQaMIGzQSZdvyUDt12Y+y5SOU/K1Is+9H\nPB2t1ugSkqhnRMxdpIZNYWf1n6jzHEMR/DQESmgIlHQYrxOM2AwJ2PQJhBkSsOkTsRkSCNMnYNZF\naQ2yNC473XaizWYzr776Kj/+8Y8pKytDkiRSU1Ox2bpWtayh0d8QBIGI6zJR3AF8Jx14j9fTuLaQ\n8GsHt3MI2rSky16h3nu8VUva1aolfWWc/9UtB9ldHWqaZNMnMDXpB33WaSzY5MO54iiBilDKgBRu\nJOrWHPQJV8ax7klUVUXZ8Vnogy0KIfdMfcqJhhqqPaFj2BMdCgVRwDouCdOwaBrXFeE9VofSEsC1\n8hiGg9VEXDfkvFrYA4FRw2KJiTSzYv1J3F6ZGFc0Rr+RLWohO2tLuCltOHNmLEQ3fBrBte+hVpwE\nRxXBf/0GJWsi0sy74Qp7se5tIowpzE39BYX1Wyio3IU5MohHqaPJX0lAOdNpVFZ9uHwluHwdHWxJ\nMGDTx7c51TZDYpuzbdbZEQUt3VSj5+n201GWZXQ6HZGRkURGRrJ161YKCwuZPn06ERFaUYDGwEQQ\nBaLmZ+FYdhh/WSPufZWIVj1hU9PajTNKYcxO/QnbKl+nvHkntZ581pQuZlbKiwNeS7rJX8mWit+g\noqAXLcxMfh6j1DeSZr5SF65Pj7VpHhszIomcn9WmoKLRHrU0H7WqCABx/DwE3ZnjtLE1Cm2W9IyP\nSev09xeDZDMStSAbb5GTxtUFBBu8+Etc1L69B9vkVGwTUwZsikdSnI375+eyYv1JquvdhLltGMpT\nKU+o4KOifWysPMnCQWMZfdezkP81wU1LwdOMemwHctEBxAk3gRTb17sxoBAEkUTLeFx+CznROVgs\nFlRVxa800+yvoilQRZO/kmZ/Fc2B0Gd/8ExOflD10+A/RYP/VId1i4Iu5GB3EsG26GM0B1vjoumy\nE+10Onn00Ud55JFHuP766wH40Y9+xPLlywGIjo5myZIlJCdrrVI1BiaCXiLq9lzqPzyAXOemeUsp\nktWAZXT71AGdaGRa0g/ZU/M2J13/ptFfxprSF5iV/CKRpvQ+sv7S8Adb2FT+X/iVFgQEpiY9Tbjx\n8l/LqqrSsqucpg3FbRJrtimp2KamDVgliMuBsmNl6A9zGOLIGW3fNwfOKiiMv3BB4cVgGhSFcdFY\nmreX0by9DIIqzVtK8RypJeK6IRjT+4++encIsxq458Zs1mwr4UhBPcaAkUHl6ZTFVVBHM3/K38Sw\niDjuGjyO1CG/RNnyMcqBjeD3Im39iKHWaAS7BQYP7+tdGbAIgoBRCsNoDiPaPLTDcn+wuVV/utWx\nbnWymwJV+IINbeMUVabRX06jvxxaztkGEjZ9XKcRbKs+ts9m4jQGBl0+O15//XWCwSBZWVkAHD16\nlOXLl/PrX/+aa665hpdeeok//OEPvPzyy71m7PmoqKjg5z//Ofv27cNqtXLTTTfxzDPPdDr2rbfe\n4qOPPsLlcpGcnMx//Md/cOutt7YtX7t2Lb/5zW8oLy8nIyODH/3oR5p031WEaNJhXzg81B680UfD\n6pOIFj2modHtxwkS4+MexqKL5kDdB3hkJ2tPLWZ68nPEW0b0kfUXh6IG2Vb5u9ADBhgT+xCJ1rGX\n3w6/TMMXJ/AeDykeCEaJyJuGYcqMvsAvr26UsuOoZccBEMdfj6A/0whnW3URshpSneiJVI7zIegl\nwqanY86JpWF1Af5TDQSdHhxLDmHKiSX8mkFt8pEDCZ0kMm9aBnF2Cxt2nQJFJLUqheY4F+XWGo43\n1PCrvV8yNX4It85YSNjw6Shr30OtKcHcUg/Lf4s8YjrS9DsRzAO3UU1/xSDZsEs27KYhHZYFgu6Q\ngx2oanWsWx1sfxXeoLNtnEqQpkAlTYFKKs9Zh4CIRR/b6lwnEHZWBNuqj0MStZmxq50uO9EbNmzg\nT3/6E+npoUjbmjVryMzM5Pbbbwfg+9//PosWLeodKy/Ak08+yciRI1m3bh319fU88sgjxMTE8J3v\nfKfduHfeeYcVK1bw9ttvk5aWxqpVq/jBD35AVlYW2dnZ5Ofn88ILL/Daa6+Rl5fHypUrefPNN5k0\naZIm33cVIYUZsS8cTt2HB1A9Ms5Pj2K/awTG1PbpSoIgkBt9O2adnR1VfwxpSZ/6JZMSnyQ9fHof\nWd999te+R2XLPgAGR8xlWNRNl92GQL0b5yf5BB0eAHSxFqJuzRnQubWXi7ZcaKMFcdQ1bd+HCgoL\nABgcdmkFhV1FF23Bfs8IPEdqafqqCMUdwJtfi6/QQdiMDCyjEwbcjIIgCIzLjScmyszKDQV4fUFs\nNZHkxdk5aCvAS4At1QXsqivhptThzL3neYJ718G25UhBP+qhzcgn94Yc6RHTteK3y4ReshAlDSLK\nNKjDMlnx0uzvxMEOVOGRz8gWqii0BKppCVSDe/85axGw6GJa00POpImEIthx/aKrq0bv02Unur6+\nnmHDhrV93rt3b7sIbVpaGvX1l18z8+DBgxw/fpx3330Xq9WK1Wpl0aJFvPvuux2c6JycHF599dW2\nF4F58+YRFhbGyZMnyc7O5t1332XBggVMmxZqpnHHHXdwxx13XO5d0ugH6KIt2O8YjmPJQdSAgvPj\nI0TfO6rT5hSDImZh1kWyufxVZNXLtsrX8cgOsqJu6fdKBYUN6zjmDKUCxJpzGB//8GW32XOsjoYv\nToS65AHm3Fgirs9E+IbugxohlKpi1JLDAIhj5yIYz7x0nGispdrTCMCMxN6LQp+LIAhYhsdhGhxF\n08YS3AeqUH1BGtcU4DlcTcR1mejjB15xaFpiOPffnMvy9Sepc3porFEY688hOLiZHa5CfEGZj4v3\ns7HyJPOTc7FM+BY5zqOIx3eAt4XgmncRDm1GmvtthLiey03X6D460USkKb3T9DtZ8dESqGlLEWn2\nV7bmY1fhlus408pTxS3X4pZrqeZgh/WYddFnRbAT2qmKnN3qXGNg02Un2mQyEQgEMBgMBINB9u3b\nx5133tm2PBAIoNNd/tyhI0eOkJyc3E4dJDc3l6KiItxudzu95okTJ7b97fP5WLp0KZIktb0M7Nmz\nhwULFvDggw9y5MgRMjMz+clPfkJubu7l2yGNfoMhKYzIBdk4P85H9QVxLDtM9H2j0EV0vAEmWEcz\nN+0XbCj7Fd6gi321/8AdqGNM3EP9tmilxp3Prqr/BUKardOSfogkXL7pSVVRadpYTMvOUBoJokD4\n7EGhTnj9/OWjv9AWhdYbEcfObbdsU+UJIFRQOKEHCwq7imjWEzEvE/OIOBpWnUSucxOobKbuH/uw\njkvCNj0N0TCw8k0jwozce2M2/95SzPESJw6XF/NhE49MnMX6piOcbKyl3tfCO4U7SRDNmCfOZ+jo\nawiuew/qK1CrCpE/eAlx9GzEqbchGLV+Av0NnWgkwphKhDG1w7KgEgg52K0R7OZAJU2tEWx3oAa1\nzcEGj1yPR66nxnO4w3pMUlRbBPtsJztMn4Be0s6JgUSX72ApKSns37+fvLw8NmzYgMfjIS8vr215\nfn4+8fHxvWLkN+FyuQgPD2/3XWRkaNrS6XR22vRk8eLFLFu2jOTkZH7/+99jt9sBqKqq4uOPP+bN\nN98kLS2NV199lccff5zVq1djNHZ9asbn8+F2uy88UAOPx9Pu/35Hggnz7DQ8a0tQmv3ULzmI9Y4s\nRHPHS8dIPNPjfszXtb+hWa7kuOsLmnx1jIt+FEno2XzQSz1ubrmWzdX/g0IQSTCRZ38axa/H7b88\n563iDuBeVUSwvBkAwarHMm8QQqKt186Ffn+udZf6CvQFewEIDp9BQBGh9b7TIvvZ3VpQON6eguzz\nI+O/qM1c8nGL0mFZmIX/QA3eHZUgK7TsrsB9tBbzjBR0gyMH3EvT7LwEIsN07DhUi8cns3lzJTNH\nZzN1UDory4/g8LupUjz89uhX5EWncdP8J4k6tgNx1+cIsh9l3zqCx3YSnHIbauYEGGD731sMhGtU\nRxRRYhRRphw4K56iqDJuuY4WuZoWuabd/265tl0nRm/QidfjpNaT32H9BjEcqy4Oqy6+9V/r3/p4\nDGLHmdCBcMz6Iz6fr0fWI6iqql54GPztb3/j73//O3PmzGH16tWMHTuWt956Cwg5n08//TRjx47l\nRz/6UY8Y1lX+/Oc/s3r1apYtW9b2XWlpKfPmzWPNmjXnVQvx+/2sXLmSV155hXfffZfs7GxGjRrF\no48+ypNPPgmA2+1m4sSJ/O///m+Xigvdbjf5+R0vCo2Bj7U0QMTJUEtwf7hA/VgjqtT5gy+Ihwrz\nMrxSKMJqCqaQ5FmIRP+YwlPwccr8Hn6pFlRI9N6JLdix8r230DcEsR/yI7Xew3yRIs4RBhSD5kh0\nh9T81UTVnkQRJY5O/Day4UzA4EDAwdeBWgAWmjKw95P8TMmrEH48gLlOafvOGy3SMExP0DzwcoXr\nm1TyT0GwdXcSImFQosoRxcneQD2B1sikDoEx+mjGB/WkFm4jsq6wbR3NEUmUZ87AZ7X3xS5oXAZU\nFGShEb/oJCA4CYhn/RNcqELXWp2LqgmDYkevRKFXI0P/K1EYlChEzAho99DukpOTc0kdprsciV60\naBE1NTVs3LiRvLw8fvKTn7Qt+/Of/0xDQwOPPfbYRRtysdjtdlwuV7vvXC4XgiC0RZg7w2AwcMcd\nd/DZZ5+xbNkyfvzjHxMTE9MuLcRisRAZGUltbW23bEpMTGyLhmt8Mx6Ph+LiYjIyMjCb+3ERWQ54\nbGX499VgaFRJLTJguWkIwnkc6RxlBLsdf6TKswevVEZN5BImxz6DRdczShMXe9xUVWFn3Rv4vaFz\nOifyboaG39wjNl142yr+Q3V495ZBq9NhGBNH+JRk4i5DsdmAOde6gqsG3aZQ0aCaO52ho8e3LVJV\nlU+OrIUApFujmJY95pI21ePHbSwEilx4NpahNvsx1SuYdvoxTkjEOCYOQRpYzvSIHB9fbjmFq8lP\nlQtU0cL149IYVlnMUaOX3a5yZFR2BeooMJiZP3sh45ob0W35F0JjLbaGCobtXYoycjbK+BtA3z9e\nePqCK+oa7SKqquAJOs6JYJ/5W1EDbWMVwYtXqsArVXRYj04wt0Wvbfp4LGdFsY1i+ICb7eltXC4X\nlZXn6rF0ny470YIg8Pzzz/P88893WPbII4/wwgsv9Enf9hEjRlBZWYnL5WpzXA8cOMCQIUM6XISP\nP/44M2bM4P7772/7ThTFtlzuzMxMjh492raspaWlTQqvOxiNxkt6s7kaMZvN/f6Yma8disun4s2v\nRS5tJLCxjIibhp3n5mRhpvU59ta8zQnXv2mWK9hS+xIzk18gypTRczZ187jtr32fKm8oBSAjfBaj\n4hdelpurGgjSsOok3iMh513QS0TcOBRz1uVvUDMQzrULIW9ej6qqIEoYJ9+McNb+nGioocYbSpOZ\nlTSsx/a1R4/bcAthQ+Np3naKll3lIKv4vq4geMJJ+HWZHZRw+jMWi4X754fx+aYiisoaqHZ4+Gxz\nJVlJEvfn5nGDMoolhbs53lCD0+/hH0W72Boew113PEXasV0oOz5HCAaQ9q9FKtyLNOsehMxxV7XT\ncyVco93Bio0YOtYtqKqCR3Z2yMFubv0sq2dSEmTVQ0OgmIZAMZyT2aETTO10sM9WFDFJUVfludZT\n6S/Sz372s59d6krCwsL6TAIuNjaWTZs2cezYMSZOnMipU6f45S9/yUMPPcTIkSO54YYbyM3NJTEx\nkcrKSt555x0mTZqE3W7nq6++4i9/+QtPP/00ycnJWK1W3nrrLUaOHElcXByvvfYaLpeLZ555pksn\nWSAQoK6ujsjIyKvqBnApnD5msbGxffIS1h0EQcA0xE6gsomgy4tc60YNKBgzos4zXiTROhadYKDa\nfRBZ8VLStBm7KROb4dLqBy7muBU3bGRf7bsARJuGMT3ph4hi7xd2yU4PjqWH8JeEmh9IdjP2ezpK\nBvY2A+lc+ybUxnqU1e+AqiIMn4GUM7nd8k+K91PudmGS9Dw0bDI68dIiu7113ARJxJgRiWloNIFa\nN0qTD8Uj4zlUQ7DRiz45HHGAKLToJJGsDDuqCuU1zQRkhWoX2Mx6slPimBI3iBRrFMXNDtyyH6fP\nzeaaYupjkhiSdzPGZge4asDvQT2+C7WqCCFxMIKpYw7slcyVco32FIIgoJcs2PRx2E2DSbCOIi18\nKpmR15Njv53MyOuI0Y/EVx9GUlQ2VmM0kqBHVn0oqty2HgUZb9BFo7+MOs9Rypt3UdT4FcecKznq\nWEFp4xaq3QdweAtpDtQQUDwIiOhF0xXrYHs8Hlwu1yWfawOrNPo8vP766yxevJjp06djs9m49957\nuffeewEoKSlpK/J7+OGHkWWZRx99lObmZlJSUnj55ZfbVDvmzJnD888/z+LFi3E4HIwaNYq//OUv\niJf4ENK4chAkkchbc3D830ECVc207CxHtOqx5aV0Pl4QyIm+DbPOzvaqPyArHq+oaFUAACAASURB\nVDaWvczExCfICJ/R6W96gzrPcXZU/wkAiy6a6cnPIIm93/zCW+DA9dkxVF8o5880LJqIG4cOOFWG\n/oSy60tQgiCISHk3tlvWHPCxp64UgMlxGRh7oUNhT6OPtRJ970g8B6tp3FCM6g050t6TDsJnZWAe\nGT8gHuSiKDBtXDKxdjNfbi5CDqp8tasCV7PMrLwUxsakMsKexPqK43xWeghvMMDXNcXsqTvF9WNm\nMy93GsLGJdDkQC0+hPzuTxDzbkLMu7FdG3cNDQg9W8y6KKKNRmpkhZzIM7m9qqriCza2dnFsH8Fu\n8lcRUM60bQyqPhr8pTT4SztsQxT02PTxZ5RETuthGxKx6KL7rfLU5aTLhYUaF+Z0YWFGRgbR0VqX\nta5w+phdanL/5SboDoS6GjpDU0IRNw3DMjzuG39T1bKfzRW/QVZCvxkd+22yoxZclIPQnePWEqhj\ndcnzeIMNSIKRa9Ne6rQBQU+iKirNW0tp3hZSiECAsJkZWPOS+8whGqjn2tmozS7kvz0PQRkhZwq6\nGx5ut3xN+VGWFu4B4MdjbyTV1vksSXe4nMct6A7QtKEIz6Gatu/0yeFEXDekU432/kpphYOVXxXi\nbU1nTU0IY/6swZhNIWe40e/l05IDbKoqaJNFizJYuDM1h7EFh1D3rAq9KAFExCLNuR8xY2B1Qr0Y\nroRr9HJzMcfMF2xqay5zdrOZ5kAVvmBTl9YhImE1xHfQwLbpB0a79Pr6eoqLiy9fYaGGhsYZJIse\n+13DqX//AEqLn4YvT4Tagw86v9OSYB3N3NSft2lJ7699D3egnrG9qCUtK142l/833mAolWJy4vd6\n3YFWPAFcK4/hKw4V/IoWPZG3ZGFM04ptLxVl978hKANChyi0qqpsrjwJwKCw6B5xoC83kkVP5I3D\nMI+Ip3H1SeR6D4HyRure3Yd1QhK2KWmIhv4f/YqJNDFuCJQ4LJTXuDlV1cT7K/NZMCeTOLuFcIOJ\n+4dOZFbSUJYW7uGoqxqn383/V7CbQWHR3Hf790na8TnqqaPQUEvw49+hZI5HuuYehDBNxUPj0jBK\nYRjNYUSbO6oy+YMtbTnXoSYzlW2fTz9HABSCNPkraPJXQEv7dQhIWPWxnWphW/Vxl7UfQW9zSU60\nLMt90mBFQ6M/oIswYV84nPp/HkD1BXEtz8d+z0gMiWHn/U2UaRDXpf+KDWUv0+gv54TrCzyyg8mJ\n3+vxNrGqqvB15Vs4fUUAjIz5Fqlhk3p0G+cSqG7GuTyfYEOo4EWfGEbUrdlIYVev4kBPoXqaUA5s\nAEAYOg4hOqnd8oLGWipPdyhMuHwdCnsDY2oEMQ+NpWVXOU1bT4W0pXeU4z1aR/jcwZgy+/9Mn14n\ncPOMdHYdqWdPfg2NLX7++flR5k3LIGtQyBFOsUbx9Ig5HHCUs6xwDzXeZoqa6nm5qZ684ZO5e1ge\n5m0rwN2AenI3cskhxMm3II69FmEApOpoDDwMkhW7NAS7aUiHZQHF0xaxPpMeEnKyPbKzbZxKMOR4\nB6o6rENAwKKPaWuRfnYE26aPvyxphj1Jt69CRVF46623+Pjjj6mvr+fAgQN4PB5eeeUVXnzxRQyG\ngXUANDQuBX2clajbc3EsPRRqD/6v1q6G9vNPD1n1scxNe4lN5f9FnecYZc3b+aqsgRnJz2GUzu+A\nd5dD9csoa94OQFrYNHLtvdvC3n2wmobVJyEYmp62jE0kfPagASdZ1l9R9qwBOdQwRZrYUZZwU1Uo\nCm2SdEyI7djOeKAhSCK2SamYsmJpXFuAr9BJsNGH8+N8jJl2IuYORgrvH9rr50MUBa6ZmEas3cKa\nbSXIQYXPNhZS43AzbWwyoiggCAKjo1MYHpXIV5UnWFlyEE8wwM66UvaJEjfN+RZzy44j7v8KAj6U\nTctQDm9Fmns/YkpWX++ixlWEXjQTZRrU6WymrHhpDlR3mibiluvbxqmotARqaQnUUu0+cM5aBCw6\ne2vkOrFDy/SeDjT1BN12ot98800++ugjHnroIX73u98BoZycffv28frrr/Pss8/2uJEaGv0ZY2oE\nkfOzcK04iuKRcSw9TPT9o5Bs57/gjVIY16Qs5uvKNylr3k6d5yhrSxczK+VFrPrYS7aptHErh+uX\nAmA3DWFiwn/2Wi6yKis0ri3EfaA16qATibg+84I54hpdR/W6UfatA0AYNAohrr0cVkvAx67aUGHQ\npLhBA6KgsKvoIk1E3ZGL90Q9jWsLUZr9+E46qC1xYZuWhnVcUr9/URueGYM9wsSnXxXQ7A6w81AV\ntU43N80cjKm1yFYnSlybnM3kuAxWlBxkY+VJAkqQ5VUn2GCxcO8N32X43vVQVQiOCoJL/wclZwrS\njIUI1oEjCahxZaITTUQa04k0dnyBlxUfLYGacyLYoYJHd6DurHbpKm65HrdcTw0d26WbdVFnpYck\ntksX0Yt9oyve7Tvt8uXL+eMf/0hubi6vv/46ANHR0fz2t7/lwQcf1JxojasS87AYlGuH0Li6gGCj\nL+RI3zsK0XT+S0wnGpma9AP21vydE64vafSXs7rkRWalXJqWtMNbwPaq34fs0kUxI/m5XnuDDzZ6\ncS4/SqAqpEssRZiIui0bfZztAr/U6A7K/nXgDxWkipM6RqG/rilCVkMdbAZ6KkdnCIKAeVgMxoxI\nmjeX0rKnAjWg0PRVMZ7DNURcl4khObyvzfxGEmNt3D8/l0/Xn6SitoXi8kY++CyfW2dnEh15xgGw\n6U3cl5nHrMShLCvcwxFXFS6/hz/WFpGeNZbvZo4hetcq8Daj5m9DLtyHOPV2xFHXIGhKUhr9EJ1o\nJMKYSoQxtcOyoBKgRa5pF8E+7WS3BGpQOdPd1CM78cidt0s3SRFnFTgmtotgG6TeK0ruthPtcDjI\nzc3t8H16ejoNDQ2d/EJD4+rAOiYRpSVA89ZS5Do3zo+PYF84HOEbtG5FQWJc3Hex6GLYX/ce3qCT\ntad+wvSkZ0iwjuq2DR7Zwaby/yKo+pEEPdOTnsOs651CJF+xC+fKo6iekB6pcXAUkTdnfeOLg0b3\nUf3eUCoHIKTmICa2z1VUVZVNVaHuhRkDtKCwq4gGHeFzBmMeHkfD6pMEKpuRa93Uf3AA86h4wmdm\nIJr7b9GS1axn4bws1m8v5eCJOlyNPj78PJ8bZwxmSGr7wttkayRPjZjNIWcFSwv3Uu1ppKTFyU+B\nqVPns7CyBEP+NvB5UNZ/gHJ4M9KcbyMmDu6bndPQuAgkUU+4IZlwQ8emdooq0xKobRfBPu1st/ir\nUTjTLt0bbMDraaDOc6zDeoxSWLsIts2QAIGeeenu9tMuKSmpTU7lbHW8rVu3Eht76dPQGhoDGdvU\nVJQWP+79VfjLGnF+dpyoBdkI39DWOqQlfStmvZ0dlb9HVjxsKPsVkxL+HzIiZnZ527LiY1P5f7cV\neExMeIJoc89HJVVVpWV7GU2bSzg9C2ebnoZtcuqA0PMdaCgHN0BrB8LOotAFjXVUukMBjCsxCt0Z\n+ngb0feNxn2giqaNxai+IJ4D1fhOOgiblYF5eFy/PRd1ksi1U9KJs1tYv+MU/oDC8nUnmTomiUmj\nEtvZLQgCI+3J5EYmsqHyBJ+WHsQt+9naWMMOm5W7Zt3F1MPbEOrKoKaU4D9/jTpyBuL0OxBM2myQ\nxsBGFHShqLIhkcRzgsmKGsQdqGvvYLf93b5dui/YhC/YRL33RNt3xmA8aSy6ZBu77UQvWLCAJ554\ngocffhhVVVm1ahWHDh3iww8/ZNGiSzdIQ2MgIwgC4dcOQXEH8J6ox3einsbVBYRfP+SCD/WM8BmY\npEg2V/wPsuLh66o38cgOsu23XvC3qqqys+pPOLyhiGRu9J2kh0/rsf06jeKTcX1+HN9JBwCCSUfk\n/KxvlPbTuHhU2Y+yaxUAQlImQieFZO0LCju2Dr5SEUQB65hETEOjaVxfhDe/FsUdoOGLE3gO1RB+\n3RD00f1Ta1gQBEZnxxEdaebTDQV4vDJb91VQ6/Qwb1oGhnNmryRRZE5yFhPjMlhZepANFSeQVYUP\nW+r5InMEj6TnkH5wM/g9KAc3opzcE8qVzp2KIGgpHhpXHqIgYTPEYzPEk2Ad3W6Zqiq4ZQfN/soO\nKSLNgSqCqr/H7Oi2E/3YY4/h9/t54403CAQCPPXUU8TExPD4449rTrSGBqGHe+T8LBzLDuE/1Yj7\nQBWiTU/YtAsrJiRYRzI39RetWtJO9te9j1uuZ2zcd75RS/qI42NKmjYDkGKbxMjou3tsf04TqG0J\nydc5vQDo4q1ELchBF9m/FRIGMsqhzdAaZRYn3tzhZaol4Gd3a4fCibEZmKT+m8rQW0hWA1Hzs/CN\njKdh9UmCTi/+Uw3U/X0vtokp2CanfGNKVV+SkhDG/TfnsGJ9ATUONydKnDgbvSyYnUlkJ7KQNr2R\nbw2Z0JovvZdDzgpcsp//ESB7/By+U1OOrWAfeJoJrvo7wsFNSHO/jRDbMRdVQ+NKRRBErPoYrPoY\n4hnZbpmqqniDTqrqSnGUB8+zhq7T7VdUWZZ56qmn+Prrr9myZQu7du1i8+bNPPTQQ1RWVl6yQRoa\nVwKCTiTq9lx0rV3WmreeomVv166PKFMG16W/3JYjdsL1JVsrXkNWfJ2OL2vazsG6DwGINKYzOfHJ\nHo8+efJrqX9/f5sDbR4RR8y9ozQHuhdRg3KoxTdAXBpCJx3rttcUEWjtbDczsWPjhKsJY3oksd8Z\nh21aGkgCKCrNX5+i9u29eIucF15BHxFuM3LPjVlkt2pH1zk9vL/yCCUVjef9TaIlgu+NuIbvDb+G\nRHMot/NowMPzUXY+n3A9wah4ANTKAuT3XyL41T9RfZ7e3xkNjX5OqF26nXB9z7xYdvtJO2HChDZD\noqOjsdlCeVder5fbb7+9R4zS0LgSEI067AuHI0WEIkqNawrwHKvr0m9Pa0nHmLMBKGvewVenXurQ\nkrXBX8rXlW8CYJQimJH8I3Rizzm2alChYV0hrpXHUAMKSAIR12cSccPQfhvdu1JQ87+GplDajDRp\nfocodKigMJTKkWGzX9EFhV1F0ImETU0jdtE4DOmhQr1ggxfnssM4Vxwl2Nz5i2hfo9dJ3DhjEDPH\npyAI4PMH+WjNcXYfrmpXe3QuI+xJLB5/E98aMgGrLtSj4XNknhs8nCO5U1B1BlAVlL1rkN/5Mcqx\nHd+4Pg0Nje7R5XSObdu2sW3bNmRZ5rXXXuuwvLS0FFmWe9Q4DY2BjmQzYF84gvoP9qN4ZFyfHUM0\n67rUAtsohTE7ZTHbKt8IaUl7j7Gm9MfMSnkRERuy0MKOur8gqz5EQceM5Gd7RGP6NMFmP84VRwmU\nhyJiYpiRqFuzv7Ejo0bPoCpBgjs/D32ITkIYMqbDmMKmOipOFxQmXh0FhV1FF2XGftdwvEfraFxf\niNISwHusDl+Rk7Dp6VjGJn5jsW9fIAgCE0YkEBNl5rONhfj8QTbsKqPG4eHaKenodZ3HvCRBZHbS\nMCbGZvBZ6UHWVx7Hh8ofLGZSRk3j0Zpy7GXHoaWB4Of/G0rxmHM/gj3hMu+hhsaVR5edaIPBQHFx\nMcFgkJUrV3ZYbrFYeOaZZ3rUOA2NKwGd3UzUncNx/N/BUFfDj/OJvndkl7SUJdHA1KQfsK/mHY67\nvqDJX8GakhfJi36KStPHeIOhTlB58Y8TY+657mX+sgacK46itIQqnA3pkUTNz0K0XH05t32BenwX\nuGqAUHfCztJzNlWGotDGK6RDYU8jCALmnFiMg6Jo2lyCe28lqj9I47pC3IerQ9rS/fCFMCM5gvtu\nzmHF+pPUu7zkF9bjaPCwYHYmYdbzdwS26g3cPWQ8MxOH8q+ivRxwlFMmCvwkIYWZkTHcXnIUfZMD\n9VQ+8j9+ijhhXijPXt//usBpaAwUuuxEjx8/nvHjx3P33XezZMmS3rRJQ+OKw5AYRtStOTg+OoLq\nD+JYdpjo+0Z3KadYFCTGxi3Coo9hX+0/8AZdbKr5BbRmU2Tbb2VQxKwesVNVVdy7K2j8qqhNvs46\nKYWw6en9LnJ3paKqCsEdn4U+RMYhDJvQYUxLwM+u1oLCSVdpQWFXEU06Iq4d0qYtLVe3IFe3UP/e\nfixjEwmbkY5o7F/a5lHhJu69KYcvNhVRcMpFdb2b91ce4ZZrhpAc/82Of4IlnCeGz+KIs5KlhXuo\ncDew0WRi29CRPNDgZGzxEYSgjLLjc5Sj25GuuRexk5kODQ2NC9PtnGijsfO31qamJhYsWHDJBmlo\nXKkYB0UReWOo+EtpCeBYeohgS9ekdgRBINu+gMmJTyFyJhc53jSGUTH39oh9ij+Ia+UxGteHHGjB\nIBF1Ww7hMzM0B/oyohbsg/oKAKS8mxDEjrnnZxcUaqkcXcOQGEbMt8cQPncwgiF0TN17K6n96248\n+bX9LlfYoJdYMHsIU0YnAeD2yixddZwDx2q79PvcqER+PO5G7svMw6YzEhAl/hYVwy9zJ1J9um18\nYz3BFW8hf/IGakPX1quhoXGGLr9+nzp1ipKSEvbt28eWLVs63HAKCwspLi7uafs0NK4ozLlxBN0B\nmtYXEXR5cX50BPs9IxENXSvSywifgVmK5OvKP4DPyrjox79R+q6ryA4PzuX5yHVuAHQxFqJuzUFn\nN1/glxo9iaqqBLe3psuF2RFyJnc65nRBYbrNTpqtdzpSXokIooB1XBKmYdE0rivCe6wOpSWAa+Ux\nDAeribhuCLqo/nPOC4LAlDFJxNrNfLGpiICssObrEmocbmZPTEWSvjkOJgkisxKHkhebzuelh1lX\ncYxqo4mXUocwOSKau8pOYPQ0oxYdQC7NR5x0M+L4eQg6bWZDQ6MrdNmJ3rt3L7/+9a+RZZmHH364\n0zG33nprjxmmoXGlYpuQjNLip2VHOYGqZpzL87HfkYtwgQfiaeKtI7k28VXyj+ajFy/9ge89Xofr\nixOo/lBk05QTS8T1mV127DV6DrXkMNSE0jTECTcgSB1v0e0KCq+SDoU9jWQzErUgG2+Rk8bVBQQb\nvPhLXNS+vQfb5FRsE1MQzlPI1xdkpkVx700mVqw/iavJx4HjtdS7PMy/ZgjWLrQ5t+gMLBw8lpmJ\nmfyraC/76sv4OiKKPbZx3FVbyeTyAoRgAGXrJyj525Bm34eYPvwy7JmGxsCmy070ggULuOWWWxg1\nahRffvllh+Vmsxm7XYuIaGh0hbCZGSgtATyHa/AXu3B9cYLIm4d1uVWxIAgIXFqKhaqoNG0uoWV7\nWegLUSD8mkFYxiX225bJVzKqqqJ8/WnogyUCccT0Tsdtqgp1pTRKOvK0gsJLwjQoCuOisTRvL6N5\nexkEVZq3lOI5UkvEdUMwpl9YRedyERNl5r6bc/hsYyElFY2U1zTz/sojLJidSUKM9cIrAOLMYfxn\n7kyOuapZUribshYX7yeksjYiiu9WFJPkrAFnNcGPfosybALSrHsQNOlEDY3z0q1XbUEQ2LZtG8nJ\nySQnJxMfH9/2t+ZAa2h0HUEQiJiXiXFw6AHlza+laX3RZcvLDLpDOdmnHWjRqif6nhFYxydpDnQf\noZYdQ60MOcjihOsRdB2VGNyyn121JUBrh0Jt2v2SEfQSYdPTif3OWAypEQAEnR4cSw7hXHmsy3UL\nlwOTUcftc4cyYURInq7ZHeD/vjzKkYL6bq0nKzKeF8fewANDJxKmN1FltvGrwcP5x6BcvMbQ7JZ6\nfBfy339McPcq1KAmX6uh0Rndnq+yWq288cYbzJ49m3HjxgHg8Xj46U9/it/ff242Ghr9HUESibwl\nG32rzFbL7gpadpT3+nb9lU3UvbsXf2koJcCQEk7Mg2MxpET0+rY1zo9yWpHDZEUc2bnaSruCQi2V\no0fRRVuw3zOCiJuGtUk5evNrqf3rblr2VfabwkNRFJg5PoWbZgxCkgSCQZUvNxexYecpFKXrNoqC\nyPSETF6acAvzUnLRiRLboxNYnDOBrfFpIXGegA9l4xLkD15CKT/Ra/ukoTFQ6bYT/cYbb/Cvf/2L\nBx54oO07t9vNvn37eP3113vUOA2NKx3RIGG/MxeptYCvaWMx7kPVvbItVVVp2VdJ/YcHUJpCL7zW\n8UnY7x6BZDu//qxG76NUFqCW5gMgjrsOwdBR+lBVVTa1RqrTbHbSw7TZv55GEAQsw+OI/e44LKNC\n0V7VF6RxdQH17x8gUN3cxxaeIXtwNN+6MbtNO3r3kWo+XnMCj697UWOzTs8dg8bws/HzGRediken\n54PUTP47ZwLlYa2pHHXlBJf8F/K//4bqbvrmFWpoXEV024levnw5f/zjH/nud7/bNu0bHR3Nb3/7\nW5YvX97jBmpoXOmIZj3Rdw1HbHVkG748gbfA0aPbUANBGr48QePqAgiqCHqRyPlZhM8Z3OWCRo3e\nQ9neGoU2mBFHz+l0TFFTPeVuF6BFoXsb0awnYl4m0feNQhdjASBQ2UTdP/bRuK4Qxd8/0hvio63c\nf3MOyfGhxk0llY18sDKfWqe72+uKNdt4LHcGPxw5l1RrFKes4bwybAwfpmfhbU0tUo9sRf77iwT3\nf4WqKD26LxoaA5FuPz0dDge5ubkdvk9PT6ehoaFHjNLQuNqQwk3YFw5HMEqggnPFUfwVjT2ybtnl\npe6DA3gOtXbAizIT/e3RmHN6rkW4xsWj1pSiFh0AQBwzG8Fk6XTcaVk7o6hjolZQeFkwJIcT8+AY\nwq7JQNCLoIbSrmr/ugfPsbp+keJhMetZeP0wRmeFrueGZh///PwoJ0qcF7W+YZHxvDB2Hg8OnUSY\nwcyW2GR+NnwiX0cnhgb43Cjr3iP4z1+hVhf30F5oaAxMuu1EJyUlkZ8fmnY8+waydetWYmP75qFc\nUVHBY489xqRJk5gzZw6vvvrqece+9dZbzJkzh3HjxnHLLbecN3q+Zs0asrOz2blzZ2+ZraHRDn2s\nFfsduaATQVZw/OsIgfruR5TOxlvooO4f+5BrWgAwDo0m5oHR6LtYza/R+wR3fB76Q2dAHHtdp2Pc\nsp+drQWFeXHpWkHhZUSQRGx5KcR+dxzGzFAKjdLsx7XiKM6PjiC7vH1sIUiiyNzJ6Vw3JR1RFAjI\nCp9+VcCWveUX5eiLgsi0hCG8NOEWbkwdjtdg4r1BObyWNY4KS6iGQ60uRv7gZYLr3kf1tvT0Lmlo\nDAi63et0wYIFPPHEEzz88MOoqsqqVas4dOgQH374IYsWLeoNGy/Ik08+yciRI1m3bh319fU88sgj\nxMTE8J3vfKfduHfeeYcVK1bw9ttvk5aWxqpVq/jBD35AVlYW2dnZbeM8Hg+vvPIKFkvnESENjd7C\nkBJB1PwsnMvzUb0yjqWHibl/FFLYmU6hFS0u3j+xA50/QJaa3el6VFWledspmreENIcRIGxGBtaJ\nyZr6Rj9Cra9APbEbAHHULARL5y2dt9cUawWFfYwUbsJ+ey7ek/U0ri0k2OjDV+iktnQPYVNSseYl\n93lq1MhhsURHmvn0qwJaPAG2H6ik1uHmxhmDMV6E7rtJp+e2jNFMTxjCx0X72AW8kjOemTXl3FJR\nhDEoo+xfj3J8F9LMuxBypmj3F42rim5f8Y899hi33XYbb7zxBoFAgKeeeoqPPvqIxx9/nMcff7w3\nbPxGDh48yPHjx3n22WexWq2kpaWxaNEilixZ0mFsTk4Or776Kunp6QiCwLx58wgLC+PkyZPtxr35\n5ptMnTqVqChNH1Pj8mMaGk3E9SFHSWny4Vh2GMUbysEsaKzlN/tWkVSwD11dARtrCjr8XvHKOD86\n0uZAi2Yd9rtGYJuUoj3g+hnBnV8AKkg6xPHzOh0TKigM3aPSbFFkhEVfRgs1zsWUGU3MonFYJ6aA\nKICs0LSphLp39uI71fcpjUlxNu67OadNO7qwrIEPP8/H2XDxEfMYk41Hcqbz7KhrSQ2L4av4VH4x\nfBK77HGhAZ4mgv/+G8Gl/41a1/sKQxoa/YVuR6IFQeCpp57ie9/7Hg6HA6PRiM1m6w3busSRI0dI\nTk5uZ0Nubi5FRUW43e520eSJEye2/e3z+Vi6dCmSJDFlypS2748dO8aKFStYuXIlmzdvvjw7oaFx\nDpZRCQRbAjRvLkGuc+P46AhV19r504kt3F50hJm1oQfVSk8L1QkZxJvDAQhUN+NcfpRg6wNTn2gj\nakEOUrjxvNvS6BtUVy3q0e0AiMOnI9g6b+xRrBUU9jtEg0T4rAzMubE0rC4gUN6IXO/B8c+DmEfE\noZsY36f2hVkN3H1DFmu3lXC4oB5Hg5cPPsvnppmDGXQJUpaZEXE8P2Ye22uK+KR4P38fPIJtMQ7u\nLj1OvNeNWn4C+b2fI467DnHyLZ2qzGhoXEl024m+UI5wXl7eRRtzMbhcLsLDw9t9FxkZehg5nc5O\nUzIWL17MsmXLSE5O5ve//z3R0WciOz/72c94+umn29ahodFX2CanoLT4ce+tJFDeSN2KavKiTrU5\n0ADzywvY9u+/EXvr9/EerqFhdQHIoap5y+iEkPpGP2pfrHEGZdcXoCogSogTbjjvuLMLCvNiMy6T\ndRpdQR9rJfrekXgOVtO4oRjVK+M5VINwoh7LIBE1u+8KD3WSyPXTMoiNtrBh5yl8gSAfrz3B9HHJ\n5I1IuOhZKVEQmBI/mLExqaw6lc+q8nx+bYtkTnUpN1QWY1AUlN3/Rjm2I9TxcOh4bQZM44ql2070\nAw88gCAI7YoVzr5AThcdXk66Wzjx0ksvsXjxYlauXMljjz3Gu+++S3Z2NkuWLEFVVRYuXHhJ9vh8\nPtzuSysIu1rweDzt/tdoj25yAq7aOiLLAmQ5zYx02fn/2Tvv8DjqO/+/Zmb7rnrvsiXLlgvuBbCN\nbTAYYzrE50AIxIEAIeRyJMflfuFSOJLnkpALhJAeSkKSo5gAxgYMNi7ghnuRZcvqlqy6K2n77sz8\n/hh5JWHLkmx1z+t59Ozud7/f2c+OZmff+5lPUUVQo+Jxh4NE+93MKz1K29WWfgAAIABJREFU9Z/W\nYnS2hx9JAtarsjEWJuAL+kHvgQQMs2PN7cRw5BMEQBk3C5/RBuc4Z/jkUCShcHp8BmowhDcYGlRT\nh9V+G67kR+PIKMT/6SlCx5pRAzKxx2Tamo+hLMlFSrAOmWkTcqKIsuawYXs1/qDMtr2nqG1oY9Gs\ndIwX+QP7muR8Zsams/bUUT4QRT6LT+GOqhNc5moEtxP53d+iZE5Ann8HxCT3uD39WOs7+j67MAKB\nQL9sp88iet26dV0eK4pCaWkpf//733nkkUf6xai+EB8fj8vl6jLmcrkQBOG8rchNJhO33XYb7777\nLq+//joPP/wwzz77LH/84x8v2qba2lpqa2svejuXEuXl5UNtwrBDVVX2hJo4kN7EPS2J5LTZCKoF\neNQANePzCEomUvevx+CdFxHQYYtA8xQTYeqhqH6I38HwZDgca+kl20hUZFQEjkeNJdiN8+FIyEmw\nPaEwtU0dEifFGYbDfhv2pIPJaiKmOITRq6LW+2j7vyLcWQbcYwyo0tB5ZKfmqhyuBI8fTla1UtfQ\nyqRssJgu3qZZ2MkyZ7NdrOf3+Zcx2dXIHZXHSQz6EauPwf/9mIas6dRnzUCVepYd+rHWdy65faaq\nCKqCKIcRlBCiEkaUw5FbofNjJYwoh7QxRUaUw4SNFsiZddFm9FlEjx079qyx/Px8CgsL+c53vsM/\n/vGPizaqL0yePJna2lpcLlckBOPgwYPk5eVhtXb99f/ggw+yYMEC7rrrrsiYKIoYDAa2bNmCy+Xi\nvvvui3i2W1tbefjhh7n55pv53ve+12ub0tLS9HCQXuLz+SgvLyc3N/es/9eljKKqvFF5gL2NTUgo\nJEofIzEXmQT8yhSShBTqfE6U8E2EtQa9GIVqYgogYfaNoF8+PYthc6x5WzF8egwANW86eTMvP+c0\nVVVZW7QJQpBhjWFh4fQhuSw+bPbbCMJ7mZemrSVEV8gIskpUZZjoZhHrwkyMY4buu2HyJIWPd9dw\nsroVtx8OlEssvTyTjOSLL3lZCCxUVfY1V/POqSM8FRXHdafLueZ0JQZVIaVyD8nOcuQr70DNmXTO\nbejHWt8ZlvtMliEc7PQXQuh0/8y4IIc6xkLtY52e7zxf6Ly2fZ1wEXXavY5EGoZCRHdHeno6xcXF\n/bW5XlNYWMiUKVN4+umnefzxx6mrq+PFF19k9erVACxbtowf//jHzJgxg5kzZ/LHP/6RGTNmUFBQ\nwObNm9m+fTv3338/U6dO7ZJgCLBy5Ur+8z//86zxnjCbzXp5vD5itVr1fdZOSJF5oXg7exq16hpf\nOl1JjrseRfoQl+F2lIABeUcdCYAAqIBiOkKCvBvhKIhmEK9aqcchdsNQH2vynnUoYS0kw3TFTQjd\n2FLW1kiNT2u4c1VGAXb70Nb2Hur9NtKoyDWSceV4gp/UECh1orqDeNeVYs6PJ+bqsUjRQ5N0d9OS\ncew+fJpte0/hD8qs3VLBotlZTJuQ3C/njAX28cxJz+OD6iI+MJrYlZDKFyqOM6HNidDWhOG93yHk\nTUda9C8I0eeuNKMfa32nN/tMVRRNhIYC7bdB1M7i9KzxYETcRsZCQQh3nhfqOi8chParZ8MKyQAG\nExiM2q09sV8222cRXVZWdtaY3+/n7bffHrKScM888wxPPPEE8+fPx+FwsGrVKlatWgVARUVFJD55\n9erVhMNhHnjgAdxuN5mZmTz11FORqh0pKV0zqiVJIi4ujqioc9du1dHpb/xyiN8e3UqR6zQAN3rc\nzKopBUDKGUP8otk0/+MwijeEAGCWiL4+n+ca6lh50EGmz42y70NQFcRFq3QhPcxQ/W6UA5sAEPKm\nIyRmdjt3a61WvtAkSszREwpHJGK0mbjbJuI/odWWVtxBAiXNNFS4cFyZjX1G+qDXlhYEgTlT0kiM\ns7J+SxmBkMymXVXUN3u5el4Ohn6wxywZuDFnCvNT8/hn+X6eM9uY4azntqoTxIaCqCf3Ea44gjh3\nBeLMaxF6EeIxmlFVpZOQDZ5HyAY6CVntT/R5yWxqQKreQVjt8ACroeDZ4lYeHu3quyAIYDS3C1wT\nGE0I7bfamPkcY8b2++au4+23XcfMYDAiiF3rpIebmqAfQmD6fORef/31Z30xq6qK0Wjk+9///kUb\ndCGkpKTw+9///pzPdY4hFEWRhx56iIceeqhX2/3oo4/6xT4dnd7gDvn51ZHNlLc1AbBEMnHt8b3a\nk9GJSMsfQLDaib99Es1vFeETQiTeOAFHWhx3JC/kVwE3jxzfR5bXjbJ/Iygy4pK7EAS9OsdwQdm3\nUfP2AOKcG7qd5wuH2N1QDsDspFyseofCEYsgCFgLEjHnxuLeVolnbw1qSKHt43J8R+qJWZqPKSO6\n5w31M2MzY1l1QyFvbyqhucXPkZImmlx+blqch8Nm6pfXiDPbuG/8FSxKL+DVk3t5MiaB5TVlLKqr\nRgoHUT5Zg1L0KdKSuxGzzt04aihRVVUTnuFANx7Zz48FuoQrdBWygW49vMgXniwsAWeyv/q3Foxw\nfnHarWjtPGbuOtZ57ZlxURrRzp4+i+iXX375rDGLxUJWVpbenERH5wJpDnh45tAmTp+5fB+Tym07\n12sncIMJw01fR7BqtdCNqQ4cd0+k+tgxkmO0+s/5MUnMzZ7Ms8Ajx/eT421DObgZVVGQrvmSLqSH\nAWrAp10lAIScSYipud3O3VVfHkkoXJCWNxjm6QwwoslA9JKxWCcl07KhhFCtm3CDl6a/HcR6WQrR\nC3MRrYP7Yyk+xsKq5RNYv7WM0uoWTjd6eGVtETcuziM9qf/6P4yJSuTfpy7ls8ZK1tii2ZmQxsrK\nYvLcLdB8Gvn1n6NMmAuzVvRqe6qqaiEDESEbOFvctt92G5Zw1lig01gnr3A/S9N+wdDhkVUlI/6w\ngtkRhWS2RDy3Z4nW8wjZs0WwGSTDiBa3g0WfRfSZ0IdwOExdXR2CIJCamooo6l/SOjoXwmlvC788\nvAlnQAs7uiYtn1v2fgxuJwDS0i8jJGV1WXOuk9stuVM52FzNcwXT+EbJQbLdLaiHtyIrMtLSexH0\nz+iQohz8GNr/x+Lc7sWCqqpsOX0CgEx7LLkOvUPhaMKY4iDhi1PxHjxN25Zy1ICM72AdgZJmoq7K\nxTqpf2KTe4vZZODmJfl8ur+GnQdr8fhCvPZeMVfPy2HyuP6JGwXtnDU7KYep8Rl8eOoYv7HHMLWh\nmluqS4gKh1CP7cRw8gBZsZlIVZ92hCZ04/lFVfrNtn4jEnfbjWiNjJkjIrirkDWfw5vbdS0GYxen\niNfr5URREYWFhZj1OPJBp88iOhAI8KMf/Yi1a9cSDGoFaC0WC3feeSePP/44kiT1sAUdHZ0zlLU1\n8qvDm/GEtUv8t+ROZWnJQdRTxwEQZ16LOGFur7ZllgzcnT+XXx7eyLPjpvKdsmOkuOpRj36KrChI\n131FF9JDhBoKoOz5AAAhowAxY1y3cyvczVR7tLKdC1PH6d6gUYggCtinpWEZl0DrpjL8RQ0o3hAt\n60/gO1xP9NI8jAmDJ4gEQeDK6RkkxVl5/5NyQmGFDz4tp77Zy1WzM5H68bxhkgwsz57MFSlj+WfF\nQZ6MTeTGU6Vc2XAKMeQnrqEEGvrZ/yuI3YcWGE0gdeeRPVd87efFsbHbuFud0U+fRfT//M//sGPH\nDh577DHy8/NRFIXjx4/z8ssvExcX1+t4Yx2dS50i52l+c3QLASWMgMBd+bO50tmAvF+LxReyChHn\n396nbRbGpbIgNZ+tp0v46ZgJ/OiUBXt9JeqxHciqgrRstX6iHwKUw1vB1waAOLf7WGjo6FBoEiXm\nJOcMuG06Q4dkNxG3YjyBKSm0bChBdvoJVrXQ+OI+HHMycczLRDAO3ue1IDeeuBgLb28socUdZP+x\nehqdXlYsysNm6d9Qk1izjXsL5lGRVsCr8XvYXnuS5TVlRIeCBEWRoCi1/4mE2m+7Pu4YC531nPZY\nkYwoBgOiZMQgihhECaOg3RpEEYPQfiuKGCP3JQyC+Ln7Uqc5AgZBwSAHMagyRjmAIeiLbMcgSBi7\nWSsKgv6jeJTRZxG9YcMG/vznPzNuXIcnZf78+cydO5fHHntMF9E6Or1gT0Mlfyr+FFlVMAgiqydc\nyXRZJvxhe85BdALSDQ9ckOC9fcw0DjfX4Ax6+WnuBL5vNCOeOoFavEvzSF//1Us+G34wUcMhlM/e\nB0BIHYOQPbHbub5wiN31WofC2Uk5WA39k+ClM7wx58SSdO8M3Luqce+oAlnFvaMKX1ED0UvzsIwZ\nvHyjpDgbX7xhIu9uOUllbRvVdW5eWVvEzUvySY7vf+94TlQ8377sGvamj+etxIM0+twoAsj9Fa6h\nKlrM9DBAgHOI63OJ+t6LfTUs0xB24W6qxO6xRsaNn1/7ue0Z27cn6vkyF0Wfv0ndbjd5eWcnuhQW\nFlJfr3dI09Hpic21J/h7yW5UtBCMhycuZLzJTvhvT2pZ2pIRw41fR7BeWGlFq8HEXeNm89yRzTQp\nYV6dciWrRANqVRHqic+QVRlp+dd0IT1IqEc/jcS3i3NuOK8naldDOQFFK0O1IDV/UOzTGR4IBpGo\nK7KxFibRsuEkwQoXcosf5+tHsIxPJHrJGCSHeVBssVoM3HZNAVv2VLP3aB1tniD/WHeMa6/MZcKY\n7jsBXyiCIDAzKZtCeyJF7fG9VquVsKoQVhTCitx+XyakKMhn7rffhhWFsKrdhjrNPTMeUpQuc85s\nL/S5tR3jXV8zrCiEVBnlIpp7gBaiElJkQsgXVZHjnJTXXdAyEaGLKD9LfEfGz/aun8/r3tkzbxDb\nt9uLtQZBHFHe+j5/i2ZmZrJ9+3auvPLKLuPbt28nLS2t3wzT0RltqKrKuqrDvF1xCACHwcw3Ji8i\nxx6LvOZ/oa0ZAGnpPQjJ2Rf1WlPiM5iXnMuO+nK2NVYyY+EdjN+2BrXiCGrJPuS1v0G64UEEvXTa\ngKIqMvLu9dqDxEyEsVO7n6uqbK3VQjky7bHkRukJhZcihjgr8XdOwn+skdZNpSieEP7iRgJlTqLm\n52CbnoYgDrzIEEWBRbOzSI63suHTCsKywrotpdQ3e5k/PQNxgG0QBAGjIGEUJWB4nKcUVT2nuA5/\nTqR3L+TPXisrSpcfCL1Z1/mHgXqR0eMKKkFFjlQDGg5Ewml64Zk/e875RH3HuOLx0R9HcJ9F9N13\n383Xv/51brrpJgoKCgAoLi7mnXfe4dFHH+0Hk3R0Rh+KqvJa6R421mgJg/FmG/86eQkptmjkzf+H\nWqW1gRanX4NY2LcOmd3xhbEzOeo8TWvIz1/K9/H95V/D+N4fUMsOoZYeQF77PNKKh3UhPYCox3ZB\nayMAUg9e6Ap3M1UezWO9IDV/RHljdPoXQRCwFiZhHhNH27YKvPtqUYMyrRtL8R6p02pLpw1OE7CJ\neYnEx1h5e1MJbm+Izw6fptHpZfmCsVjMl9bVLFEQMEkGhlOQVZvHzZGiIvIKxmGymM/pXQ/1wdv+\nec9/dz8UursSEO6HMJywqhCWFWDgmsMkCGZut+Ze9Hb6/AlYuXIlJpOJv/71r6xfv55AIEBubi6P\nP/54pEugjo5OB7Ki8OLxHexqb56RZovhm5MXE2e2oRzbibJ3AwBC5njEhXf22+vajWZW5c/md0Vb\ncQa8vFl9hFUrHkZ+97eopQdQyw4hv/0c0k1f1zLQdfoVVVGQd7+rPYhLRRg387zzzyQUGkWJucm5\nA2ydzkhAtBiIuSYvUls6XOchXOeh6a8HsE1PI2pBDuIgCNnURDt3rZjIOx+fpKbeTfmpVv62roib\nF+eTEGsd8NfX6R5J0OKq7QYTNtPQ/y9UVW0Pt+k+lGakheGcjwv69N16663ceuut/W2Ljs6oIyCH\n+X3RVg47awEYE5XANyYtwm40o9ZXIm94SZsYFa+FV/Rz5YwZiVnMSMxib2MVm2tPMDMxm4IVDyGv\n+x1qyT7UiiPIb/0K6aZHtNqlOv2GWrIXmrX27dKc5ectL+jXEwp1zoMpLYrEu6fh3V9L29YK1KCM\nd18t/uONRC8ei2VC4oBfubBbjdx5bQEbd1Vy6HgjrtYAf19XxLL5Y8jP1hut6WgIgtAeYjG8w3Cc\nTieumguLI+/MBYnoI0eOcOLECQKBszNeV65cedFG6eiMBjyhAM8d2Uxpm3Y5f2JcGg8WLsAsGVB9\nbYTf+bXWOEAyYLjxYQTbwFyeXZU3i2JXHZ5wkJdP7OS/ZizHtPxryOv/gHpiD2plEfI/n0W65VFd\nSPcTqqoi72r3QkcnIoyfc975ekKhTk8IooB9RjqWggRaN5bhL25E8YRwrS3GdKiOmKV5GOIG1hMp\nSSJLL88lOd7Gpp1VBEMKb286yeXT0pl3WZoegqQzLDlXGI5q8uPqh233WUQ/++yzPP/88+d8ThAE\nXUTr6ADOgJdnD2+ixtsCaN7FewvmYRAlLdns3d9DaxMA0jX3IKTkDpgt0SYrK/Nm8ufi7TT63bxV\ncYAvjJ2JtPwB5Pf+hFq8C7W6GPnNXyLd8k0Ek2XAbLlUUMsOQkMVAOLs63ushHImlCPDFssYPaFQ\n5zxIDjNxN03AX+akdcNJ5BY/wQoXDS/sxTEvC8ecTATDwJYtmzo+mYRYK2s/PonXH2b7/hoamr0s\nmz8G0yDWtdbRGWr6/El75ZVX+P73v8+BAwc4duxYl7+ioqKBsFFHZ0RR52vlZwc2RAT0orQCvjL+\nivbLW6BsW4NapX1WxGlLECdeMeA2zUnKZUp8OgAbTxVT2tqIIEpa85UJ8wBQT51AXvO/qAHfgNsz\nmlFVFWVnuxfaHtvj/7eirZnK9hJ4C9L0hEKd3mEZE0fSfdNxXJ4FoqDVlv6kkoYX9xGo6A8f2/nJ\nTInirhUTSWnvrFhS6eLv64pwtfoH/LV1dIYLfRbRoVCIlStXYjbrl311dD5PpbuZnx3YQFPAA8CN\n2VP4l7yZiO3CSCnehbKnvfFGRgHiwi8Mil2CIHBX/hwskhEVePn4DkKKrAnp676C0C701NqTmpD2\newfFrtGIWlmEeroUAHHWdT1WP9ETCnUuFMEoETU/h6R7p2PKigFAdvpofvUwzrXFyJ7ggL5+lN3E\nF5ZNoHCsVju6yeXnlXeLqKhpGdDX1dEZLvRZRF9xxRUcO3ZsIGzR0RnRFLvqePrgh7SFAghoscgr\ncqZEPItqQxXyBy9qkx1xSDcMbsOTOLONO8dOB6DW18q7lYcBEEQR6dp7ESYv0Ow8XYq85heofs+g\n2TaaUM7EQlujEKcsPO9cfzgUqdoyKykHm55QqHMBGBJsxK+cTMzyAkSb9qPNX9RAw5/24NlfizqA\n1QmMBpFl88ewcFYmggCBoMyaD0/w2ZHTA/q6OjrDgV59g+/evTtyf8WKFfzgBz/g5ptvJisrC/Fz\nGefz58/vXwt1dEYA+xur+MOxTwirCpIgct/4y5mdlBN5XvW7Cb/dkUgo3fgwgj1m0O28MiWP3Q0V\nHHPV8X7VUWYkZpHtiEcQRKRrvoQiiigHN6PWlRN+42kMt/0bgtUx6HaOVJRTJ1CriwEQZyztMVFz\nV0MFAflMQuHZnWB1dHqLIAjYJiVjGRtH25YKvAdPowZkWjecxHe4npileRhTBuazLAgCsyalkhRn\nZe3mUgJBmS2fVdPQ7OWay3MxDnCMto7OUNErEf2lL30JQRC6/Ko8ePDgWfMEQdDjonUuObadPslf\nT+xCRcUsGnhw4gImxnV071QVBXndHzqablx9N2LqmCGxVRAEvjRuLj/as46AEual4zv4z2nLkEQR\nQRARl9wNooSyfyPUVxJ+/ecYbn9swCqHjDYiXmizDXHq4h7nnwnlSLfFMDYqcSBN07lEEK1GYq7L\nxzo5mZYPSgg3egnVttH4l/3YZ6TjmJ+NaBqYK2A56THcdUMhb20qocnlp6i0meYWPzctzifKrl9l\n0Rl99OqT9NFHHw20HTo6I5L3q46ypnw/AHaDiW9MWsSY6K5iSPlEa7cNIE5djDhpaK/WJFoc3Dpm\nKv84uYdqj4v3qo9yQ/ZkQBPZ4qJVIIgo+z6ExmpNSN/xGIItekjtHu6odeWo5VqIjDjtagTz+cuN\naQmFWqt3vUOhTn9jyogm8Z5pePbW4P6kEjWk4NlTg6+4keglY7EUJAzIMRcbbWHV8kLe21ZGSaWL\nuiYvr6w9yopFeWSm6D/GdUYXvRLRGRkZA22Hjs6IQlVV3ijbz4ZT2pWXOJONRycvJv1zIRpK8W6U\nz94DQEgfh3jV8CgBeVVaAZ81VFLS2sC7lYeZnpBJuj0WaBfSV63UPNJ73oemU4Rf+xmGO749JCEo\nI4VIXWijGXH61T3O39YpoXBeytBcmdAZ3QiSiGN2JtbxibR8VEqgpBnFHcT19jHMY+OIvjoPQ2z/\nl7Q0GSVuXJTHzoO1fLq/Bq8/zOvvH2fx3Cymjk/u99fT0RkqeiWi+xLnvG3btgs2RkdnJCCrCn85\nvpPt9WUApFij+dfJi4m32LvMUxurkT94QXtgj0Va8eCgJhKeD1EQuGfcXJ7ct56QIvPS8R38+7Rr\nkQQtdlEQBMQFd2hCevc6aK7tENKO2CG2fvihNp5CLdkHaFcbeooj98shdp5JKEzM1hMKdQYUKdpC\n/K0T8Zc00fpRKXJrgECpk4bKvURdnoV9dgaC1L9xy4IgMG9qOklxNtZvKyUYUvhoRyX1zV6WzMlG\n6ufX09EZCnr1jb5y5Ur9UqOODhCUw/zh2CccbD4FQI4jnm9MWkTU5xqUqH7P5xIJHxp2XtwUWzQ3\n5kxhTdl+yt3NfHSqmGszCyPPC4KAeOWtIIooO9eC8zTh136qCemo+CG0fPgR8UJLRsQZS3ucv7u+\nU0Jhmt6hUGdwsOQnYMqOxb29Cs9npyCs0La1At/ReqKX5mPO6v9zVF52LKuWa3HSrtYAh4430uTy\nc+OiPOzW4dEWWkfnQumViP7GN74x0Hbo6Ax7fOEgzx3ZTElrAwATYlN4qHAhls/VAVYVBXn9H6BF\nmyct/iJi2vCsvHBNxgT2NlRS7m7m7YqDTE3IIMXaEfssCALSFbdoHuntb4GrvsMjHa131gNQnXWo\nx7UKRuKUBb36saQnFOoMFaJJIvqqXKwTk2jZcJLQqVbCTT6a/3EI6+Rkoq8aEymT118kxFr54g2F\nrNtSSvmpVmrq3byy9ig3Lc4nNdHe8wZ0dIYpvRLRzz77LI8++igAv/jFL7qdJwgC3/rWt/rHMh2d\nYURL0MezhzdR7dE6gc1IzOIr46/AKJ7d4lbZ/s+OBLPLruqxVvBQIgki9xTM46l97xFSZF4+vpPH\nLrsm0hwmMm/ejZpH+pM3oaWhwyMdkzRElg8f5N3rQVVBlBBnLetxfqW7mQo9oVBniDEm2UlYNQXf\noTpaN5ej+sP4DtfjL2nWRPaUlH49Ni0mA7csGccn+06x+/Bp3N4Q/7f+GEuvyGFinv5DUmdk0isR\nvW7duoiIXrt2bbfzdBGtMxpp8Ll55vBGGvxuABam5rMqfxaicHZMn3JiD8qudQAIaXmIi1YNpqkX\nRIY9luVZk3in8hAlrQ1srj3B4vSCs+ZJc27QPNJbX4fWpg6PdOylmyiktjahFm0HQJh4Za/CXLbW\ndu5QqCcU6gwdgiBguywVc34CbZvL8B2uR/WHaXm/BO+Z2tJJ/ecpFkWBBTMzSYq38cEn5YRlhfe2\nlVPf7GPhzMx+ex0dncGiVyL6vffei9zfuHHjgBlzodTU1PDDH/6Q/fv3Y7fbWb58Od/+9rfPOfe5\n555jzZo1uFwuMjIy+OpXv8rNN98MQCAQ4Oc//zkffPABPp+PKVOm8B//8R+MGzduMN+OzjCi2uPk\nmUObaA35AVieNYmbci47p4dGbTyF/P6ftQf2GKQVDw2bRMKeWJY1kX1NVVR7XLxZtp8p8ekkWs5O\njpNmLdM80ptfhbbmDiEdlzIEVg89ymfvgSKDICDN7tkL7Zc7OhTOTMzGbtQTCnWGHslmJPb6AqyT\nU2jdUEK4yUfoVCuNL+/HPisdx+XZiKazr7pdKBPGxBMfbeGtTSW0eYLsPVpHo9PLktlpPS/W0RlG\n9Dk9NhwOd3n86aef8u6779LS0tJvRvWVRx55hNTUVDZu3MiLL77Ihg0bePHFF8+a99JLL/H222/z\nwgsvsGfPHh555BG++93vRtqY//SnP2Xv3r28+uqrbNmyhbS0NB555JFBfjc6w4WSlnp+fuDDiID+\nwtgZ3Jw79dwC2u8l/M7zEAqAKGkCegRVsTCIEveMm4eIQEAJa81jumnZK824loiH3e0k/NpPUZtr\nB8/YYYLqdqEc3gqAMH5urzzynzVU4o90KNQTCnWGF+asGBK/PJ2ohTlgEEFR8ew6ReMLe/GXNPXr\nayUn2LhrRSGZ7V0UK2vbeOOjMlweFVnR24XrjAx6LaKdTid33nlnF0/0448/zle+8hUee+wxli9f\nzqlTpwbEyPNx6NAhjh8/zne+8x3sdjvZ2dncd999vPrqq2fNLSws5Oc//zk5OTkIgsB1111HVFQU\nJSXa5dXo6Ggef/xxUlJSsFgsfPnLX6ayspKGhobBfls6Q8zBplP88vAmfHIIURC4b/zlXJ0x4Zxz\nVVVBfu8P4KoD2hMJ00eeQMqJiufaLK06R5HrNJ/WlXY7V5p+NeKSu7QHnhbCr/0MtalmMMwcNih7\nPwA5DAhIc5b3as3W2hMApNliyIvW40B1hh+CJOKYm0XSfTMwj40DQG4N4HyziOY3jyK3+vvttWwW\nI7dfW8C0CdoP0DZPiANl8Kc3j/HK2qNs+LScg8UNnG70EJaVfntdHZ3+otfXmp955hlkWWb8+PEA\nHDt2jLfeeouf/OQnLFq0iCeffJLnn3+ep556asCMPRdHjx4lIyMDh6Pj0vPEiRMpKyvD6/Vis9ki\n43PmzIncDwQCvPbaa0iSxOWXXw7AN7/5zS7brqmpwWw2ExMzvErSJv9FAAAgAElEQVST6Qws2+tK\nefn4ThRUjKLE1wrnMyW++4ZDyva3UcsOASBMXoh42VWDZWq/syJ7Cvsbqznta+W10r1MjEsjzmw7\n51xp6mIEUUL+8C/gbW0P7XgMIXH0xzaqvjaUAx8DIOTPQEhI73FNpbuZ8khCYZ6eUKgzrDHEWoi7\nbSL+E1ptacUdJFDSTEOFC8eV2dhnpPdLbWlJFFkyN5vkeBsf7ahAVlQURaWuyUtdk5dDJxoBrbZ9\nQpyF5Hg7KQk2UhJsJMbZMBr0etM6Q0evRfTmzZv57W9/S05ODgAffvgh+fn53HrrrYAmQO+7776B\nsfI8uFwuoqO7tiOOjdUuozudzi4i+gxPPPEEr7/+OhkZGfz6178mIeHsUl0tLS38+Mc/ZvXq1ZhM\nfYtbDAQCeL3ePq25VPH5fF1uh5qP60p4q1qrrGGVjHw1fx5jLXHd/j+FsoMYdmrJtkpyDvK8mwkO\nwv9+IPfbF7Kn8qvirfjkEH8p3sHqvLndC768WQihMNLmvyP42gi99jPCKx6BhOHX5bQ/95m4+z2k\ncBCA4NQlvfqff1xdDIBRELksKnXEnCOG22d0JDCq9lmmDceqQvy7agkerEcNKbR9XI7nUB3WRVkY\nUs/fWKi3jM2wEX9NFoeLKzFa4nC5wzQ4/bi9IQAUVaWh2UdDs48j2sVjBAHios0kxVlIjLWSFGch\nIdZySQnrUXWsDSKBQKBfttNrEd3U1ERBQUfG/r59+7jiiisij7Ozs2lq6t+Yqd7SXexmdzz55JM8\n8cQTrF27lq997Wu8/PLLTJjQcam+vr6e+++/n0mTJl1QTHRtbS21tZdejOjFUF5ePqSvr6oqu0ON\n7A9rnkKbILHcmEGgqp4i6s+5xux1kr/vDQBCJhsnxiwkfLxk0GyGgdtvkwxxHA47OdJymrWHd5Fv\niD7P7Bhixy8mq3gTgt+D8M9fUjblRnxRw7P83cXuMzEcoPDAJgBa43Mob3BDQ9F514RUhV2+CgBy\nRQeVJ05elA1DwVB/Rkcio2qfJYBhlpnY4iCmVhWlyYfnjeN40iVa84yoxv65spIQJQAuouMgOw5C\nYWjzgdvffusDv6arUVVobgnQ3BKgmI68LJsZoqzgsICj/dYgje4rP6PqWBtB9FpEWywWQqEQJpMJ\nWZbZv38/t99+e+T5UCiEwTD4lQji4+NxuVxdxlwuF4IgEB/ffbkpk8nEbbfdxrvvvsvrr7/O9773\nPQAqKyu59957WbJkCf/v//2/C7rkmpaWFvGG65wfn89HeXk5ubm5WK3WIbFBUVVeq9zP/kZNQCea\n7Tw47goSzOcp7RTwYXjzDQQ5hCqKCNc/wLjUsYNk8cDvt7HyOH52dCNNQS875SYWTZhGlNHc/YLC\nQuTMLKSNL2MIB8g/8i7yDQ+jJuf0u20XSn/tM3Hv+0iy5oW2LbiNwtSey9TtbKwgVKHFdC7Ln8pY\nx8hpVDMcPqMjjdG8z9RZKsGjjfi310BQxl4j43AKWK7MwFgQf1FhSr3db4GgTIPTR4PTT6PLT4PT\nT6s7GHneG9D+6jqtiY0ykhhnISnWSmKchcQ4C2Zj/1UcGSpG87E2kLhcrn5xdvZa9WZmZnLgwAFm\nz57N5s2b8fl8zJ49O/J8UVERKSmDX+Zq8uTJ1NbW4nK5IsL14MGD5OXlnXVAPfjggyxYsIC77ror\nMiaKYkT8O51OVq9ezZ133slDDz10wTaZzeZzhpHodI/Vah2SfRZSZP507FP2NVUBkGWP49HJi4g2\ndX8yUlUFecOfUFs0D7W0aBWmsZMHxd7PM1D7zQZ8efzl/OLQR3jkIG/VHOGBwvnnX3TZAhSLFXnd\n7xGCPgzvPo90278Ou26NF7PP1FCA8KHNAAhZE7COndSrdTuaKwFIs0YzKSlzRMZDD9VndCQzWveZ\nfY4deVIarZvK8Bc1oPrC+D6sQC52EbM0D0PCxb3nnvabzQZxsVEUdPr96g+GaWj2RmKp65u8ODsl\nQbragrjagpRUtkbGYqPMpCTYSE7Q4qyT421YzCOjLOnnGa3H2kDRX+EvvT5aVqxYwWOPPcaSJUvY\nsGEDS5YsISlJu1x7+vRpfvKTn3DVVYOfUFVYWMiUKVN4+umnefzxx6mrq+PFF19k9erVACxbtowf\n//jHzJgxg5kzZ/LHP/6RGTNmUFBQwObNm9m+fTv3338/AE8//TRTp069KAGtM3LwhUP85ugWils0\nf0VBTDIPT1yI1XD+GHhlx1rU0gMACJPmI162aKBNHRLGx6awMDWfLadL2NNYyb7GKqYnZp13jVgw\nCwQBed3vIehDXvO/cMs3ETNGR6115eBmaG+6I85d0as1VW4n5W1aqNv8NL1Doc7oQLKbiFsxnsCU\nFFo2lCA7/QSrWmh4cR+OuZk45mYiDKKn12IykJUaTVZqR+hZMCRT36wJ6romD/VNXppb/ZyJAHW1\nBXC1BSgud0bWxDjMJLcnLibH20hJsGO1jExhrTPw9PrIuO+++6ivr2fLli3Mnj2b//qv/4o897vf\n/Y6Wlha+9rWvDYiRPfHMM8/wxBNPMH/+fBwOB6tWrWLVKq2ObUVFRSSBZ/Xq1YTDYR544AHcbjeZ\nmZk89dRTkaoda9asQZIkPvjgAwRBQFVVBEHgySef5KabbhqS96YzMLQG/fzqyMdUtldLmJaQyVcn\nXHnONt6dUU7uR9nxNgBCSi7SkrtGtSi6bcx0DjXX4Ax6+VvJbgpikrGfL6wDEMfNhBUPIq/9LQT9\nyG/+UhPSmWd3QRxJqOEQymfvA1o3SiFzfK/WbT2txckbBJHL9Q6FOqMMc04sSffOwL2rGveOKpBV\n3Nur8B1tIHppHpYxcUNmm8kokZkSRWZKVGQsFJKpd54R1tpfc4svIqxb3AFa3AFOVHQI62i7qUNY\nJ9hJibdhsxoH++3oDEMEta9ZeeegpqaGpKQkjMZL+6Dyer0UFRUxRvQQN23BqBZX/cWZfVZYWDho\nl6Ka/B6eObyROl8bAFemjOWucXOQztHGuzNq82nCf38Kgj6wRWH44hO9avM8EAzmfjvcXMOvjnwM\nwOXJY7h3/OW9WqeUHkRe+7xWS9lgQrrlUcSsc9faHgwudp/JBzahbHwFQHsvYy7rcU1ADvPvO9/E\nL4eYm5zLV8Zf0eOa4cZQfEZHOpfqPgs7fbRsOEmwoiNPyTI+keglY5Ac5//xDUO330JhLca6PhIK\n4qHJ5Uc5jzxy2IykJNi7eK0dtsHvQHqpHmsXS1NTE+Xl5Re93/rlGkV6es81Ui8lpM/WIdcUIV19\nN4LlPMlpOoNOjcfFM4c34Qpq8VDXZhZyW+60Hn/wqAEf4Xee0wS0KCHd8NCQCejBZnJ8Opcnj2F7\nfRnb68uYlZTD5PieP/Pi2MvgpkeQ334OwkHkfz4LNz2CmDNxEKzuX1Q5jLJ7vfYgORshd0qv1n3W\nUIFf1koJ6B0KdUY7hjgr8XdOwn+skdZNpSieEP7iRgJlTqLm52CbnoYgDj/nktEgkZ7kID2po1xf\nWFZodPoiYSB1TV4aXT6U9m6Kbm8It9fFyaqOHwx2q7HdW20jJV4T2A6bUXeojWL0QJ8BQj2+m3Dt\nSaTrvjKk3jedDkpbG/nVkY/xttf3vX3MdK7NLOxxnaoqyO//GZpPAyBetXLEhyb0lTvHzuCIs5bW\nkJ+/ntjF92fegNXQ85UnMXcy3Pwo8lu/0oT0W+1COndoEjEvFPXYDmjTQn+kOTf0+kvxTChHqjWa\n/OjhWfJPR6c/EQQBa2ES5jFxtG2rwLuvFjUo07qxFO+ROmKW5mNKi+p5Q0OMQRJJTbSTmtjhCJNl\nhUaXL5K4WNfkodHpi7Qp9/hClFa3UFrdqdyexdBFVKck2Iiym3RhPcCoqgphBVVWUcOK9icr2lhY\nQW7rnzr9uogeANScyXDkY2hrRn79adRZ1yFecQuCpO/uoeJwcw2/K9pKUJEREfhSwVyuSOldSTpl\n1zrUk/sAECZegTh18UCaOiyxG818MX82vy3aijPoZU3ZPu4aN6fnhaB5nm/9puaJDgc1z/SKhzVP\n9QhAVRTkXeu0B/HpCPnTe7Wuyu2krD2hcIGeUKhziSFaDMRck4d1UjItG0oI13kI13lo+usBbNPT\niFqQgzjCKmFIkkhKgp2UhE7CWlFodvnb46s9WiJjsxdZ1oS11x+m/FQr5ac6qoJYzZqw1hIXteTF\naMfoEtaqooLcIV7VsCZmI2OR8XZhe545hNXI3LPXaOvOWiOfP1I56BBgjuWi3+fIOoJHCPLM65HG\nFCJveAkCXpTP3kOpPIph2Vd71R5Yp3/ZVV/OC8e3o6gqBkHkgcL5TE3oXWtqpfQgyqdvASAk52gh\nOqPoRNcXpidmMTMxmz2NlWw5XcKspBzGx/aurKWYNQFu/Vfkfz4DoQDyO7+GFQ8h5k0bYKsvHvX4\nbnC1lzOcsxyhh9j5M2zrlFA4T08o1LlEMaVFkXj3NLz7a2nbWoEalPHuq8V/vJHoxWOxTEgc0edU\nSRRJireRFG9j8rhEABRFpbnFT12TR/NatwvrcFirFe8LhKmoaaWipkNYm01Sl8TF5AQbsVHmC943\nqnIeQdpFgHaaI/ckdNWz13QSwJ3HUC463W5EoIvoAUIcNxMhbSzye39GrSqC+krCf/tvxIV3Il62\naESfNEYSm2qK+b+Te1ABi2Tk65OuoiAmuVdrVedp5PV/AFSwRiHd9HWEHsrfjXb+JW8Wx1x1eMIB\nXj6xk/+asRxzL6+wiJkFHUI66Ede+xtY/oBWzWOYoqqdvNAxSQjjZ59/QTtBOcyO+nIAZiRm4+ih\noomOzmhGEAXsM9KxFCTQurEMf3EjiieEa20xpkN1Wm3puNHTKEQUBRJiLMTbTRSmx6DKCnJQpqXF\nT3OzF5fTh8vlo7U1gBpWkADJF0ZyBXCfdOJVoVJVMYkiDrOE3WTAahSxSBJGgS5iVw6GSfYFaN11\niDZZ1by58sgWsYJRBElEMIgI7bcYhMj9M+MYOs8RtMeS2GUeknDONS3eVnCdvmhbdRE9gAiOOKTb\nv4Wy90OUT9ZAOIiy8RXUskNIS7+MYI8ZahNHLaqqsrbyEGsrDwMQbbTw6OTFZDl6V25JDfoJv/28\nlkgoiEg3fO2SSSQ8H9EmC/+SN5M/FX9Ko9/NW+UH+EJe70WwmDEObvsW8ppfanWk3/2dJqQLZg2g\n1ReOevIANJ0C2r3QPZRAPMNnjZUdCYVpekKhjg6A5DATd9ME/GVOWjecRG7xE6xw0fDCXhzzshCn\n9N85NuKJ/ZzXtSMuVj23N7Y3Htt2r2z321agGw0b3f6X3at3IYM7FHmkAIFzzDIAKqHuXrJvCLSL\nVvHcorWTKO0qdIXu13S3rsscTSQjCoPiZBSbguDqeV5P6CJ6gBEEEWnmtYjZhYTX/wGaalDLDhL+\n6w+Qlt43YuJCRxKKqvCPk3vYXHsCgESLnX+dvIQka++SWVRVbU8krAFAXPgFPTm0E7OTctjdUMHB\n5lNsrClmZlI2eX1ImhPT8uD2f9MasQS8WmMWRUacMHcAre47qqqi7FyrPYiKRyjsXWk/gC3tx16K\nNZpxekKhjk4XLGPiMN83HffOatw7q7Xa0p9UIh6pwxEv43fXEhals8TuuUVrV7F7Ruj2j6IcAkQB\nJAFFEJAFCKsqQUUlDCgCyGjjsqCJalkQUAQwWw3Y7GZsDhOOKDN2hxnReLZg7VHsDsPqKcMZXUQP\nEkJSFoYvfg9l6xso+z8CbxvyW8+iTl2MuOAOBP1yb78QVmReKN7OZ41am+UMWyzfnLKYmPO08f48\nyu71qCV7ARAmzEOcfvWA2DpSEQSBL+bP5sSeenxyiJeP7+R7M67vsVFNZ8TUMQi3P0b4jac1If3e\nH0FRECf2XqgONGrFEdT6CgDEWct6nRhc7emUUJiap4du6eicA8EoETU/B2thklZbuqoFxRUg2gWB\n0tpzelwHBVHoVmx2CFKhU5jBueYI3azrPjwhMuccIlZVVVrdwUji4pkmMf5AuOvEQFD7a3JjkESS\n4q2RrovJcRYSYi1IYu9yOnR6hy6iBxHBYEJavAphzBTk918AbwvKgU0oVUUYrn8AIbl3F3h0zo1f\nDvG7o1s52h7nlBedxNcnXoXd2Ps4ZqXsEMonb2oPkrORlt6ji6BzEGe2cefYGbx8Yienfa2srTzE\nrbl9SxIUUnIw3Pkdwq8/DX635v1XZcRJ8wfI6t7TxQtti0ac3HubttaeBNo7FKboCYU6OufDkGAj\nfuVkfEcbaN1SjuIJIhhERKPUC0EqfC4u9txit1dzziNihxpBEIiJMhMTZaYgVwt5UVWVNk+Qqlon\nRSeqUSUHTS4/Xr8mrMOyQm2Dh9oGD9AAgCQKJMZZuzSJSYi1YpB0YX2h6CJ6CBBzJyN86QfIH76E\nenI/tHfCE6+4BXHmdQj6L8U+4w4FeO7IxxEP4JT4dB6YMB9TH8oKqq66jkRCiwPDjXoi4fm4ImUs\nuxsqKHKd5oOqImYkZJPTx7hxISkLw53f1oS0rw35gxc1j/SUhQNjdC9RTx1HrdGqa4gzr+v1cRCU\nw+ysLwNgRmIWDuPFl1DS0RntCIKAbVIyjHHo3fd6iSAIRDvMjMmIxt8qUFiYjdVqxe0NaTWsmzua\nxHh8Wly1rKgRL/YZRFEgMdYaEdUpCXYS43Rh3Vt0ET1ECLYopBu/jnp4K/LH/9CSDre9gVp+GGnZ\naj2JrQ80Bzw8e2gTtT6tXNC85FzuGTevT5etIomEAS8IgpZIGJ0wUCaPCgRB4O5xc/jRnnUElDAv\nn9jBd6ddh6EPYR0AQmJmu0f65+BtRf7wZVRFRhrCetwRL7TFjnjZVb1et6exEp/eoVBHR2cIEASB\nKLuJKLuJvOzYyLjbG4yEgZxpEuP2aucpRVEjJfgOa6kciIJAQqylXVhrXuukOCtGQ9/O7ZcCuoge\nQgRBQJiyECGzAHn9H1HrylGriwn/5QdIV9+NOL53zSwuZU57W/jl4U04A9ov66szxnPHmBmIfQjB\nUFVV84C2V2EQF9yJmN1zJ0MdSLQ4uHXMNP5x8jOqPS7erz7KDdm9a4ndGSEhvUNIe1pQNr4CioI0\nBPHoSm0pamURAOL0axBMvfcmb6nVvNcp1ijG9bKUoo6Ojs5A4rCZcNhMjM3sENZeX4i6Zi/1Z2pZ\nN3lp9WjdfBVVpcHpo8Hp40iJdnVXECA+xtrR1jzBRlKcDZPx0hbWuogeANZUHSShNY5MeyyZ9jhS\nbFFI52nQIMSlIq38D5Qd76DsXhepWKCUHUJa/EUE8+ipn9mflLc18avDH+MOaykot+ROZVnmxD7H\nMCufvYd64jMAhAlzEWcs7XdbRzNXpY3js4YKSlobeLfyCNMSssiwx/a88HMI8WkY7vx3TUi7nSgf\n/x1UGWnGtQNgdfcou97V7pisiNN6L+JPeVyUtjUCmhdaj6XX0dEZrtisRsZkxDAmo6PUrs8f6pK4\nWN/kpcWtfb+qKjS5fDS5fBw92RRZEx9j0YR1fIfX+lIS1rqIHgDK3M181lYbeWwUJdJsMWS1i+pM\neyyZjjhsneIsBcmAdOWtCDmTkN//E7Q2oRZtJ3zqBNKy1Vp9XZ0IRc7T/KZoCwE5jIDAXfmzL6ge\nr1J+GGXbGu1BUhbSNXoiYV8RBYF7Cuby5N71hBSZl4/v4N+nXXveH47dIcSldHik25pRNr8Ksow0\n+/oBsPxs1IYq1NIDAIjTFiNYeh+XubVTh0I9oVBHR2ekYbUYyUmPISe9Q1j7A+FOoSCa19rV1lE7\npbnFT3OLn6LS5shYXLRZ67zYqbW52TQ65ebofFdDTIYtBo/fGWm2EFJkKt3NVLqbu8xLMNsj3upM\nh3abmDEOw93fR974N9RjO6C1Efm1n6LOuQFx7opel9kazexpqOTPxZ8SVhUMgsjqCVcwI7HvlU1U\nV4NWoxgVLHYMNz6slxq8QFKs0dyUcxlvlO2j3N3Mh6eOcV3mxAvalhCb3FG1o7URZdsboCpIc27o\nZ6vPRj7jhTaYEKf3/opE54TC6XpCoY6OzijBYjaQnRZNdlp0ZCwQ1IT1mcTFuiYvzlZ/5HlnawBn\na4Disg7NExNlbk9ctJEcr3msreaRr2dG/jsYhvxLznTi4+NpCniodjup8rio9jip9rho9Lsj85oC\nHpoCHg40n4qMmSUDGbZYMvMvY2pcEuP2bEAM+lF2rkWtOIK07KsIcSlD8baGBVtqT/C3kt2oaPvq\n4YkLmRCb2uftqKEA4Xd+3ZFIuPwBhBi9KcbFcE3GePY0VlLe1sQ7FYeYFp9Jii2654XnQIhJ6vBI\ntzRoZQcVBWnejf1sdQdqcy3q8T0AiJddhWDrXXMe0BIKvWE9oVBHR2f0YzYZyEqNJiu14/weDMld\nhHV9k4fmVj9qe9OblrYALW0Bjpc7I2tiHKazPNZWi3Gw385FoYvoAUIQBBItDhItDqYlZkXGfeEQ\npzwuqjzOiLA+5XERUmQAAnKY0rZGStsa2QLEjZ/BPWVHGed2oZ4uw/+XH1A/ZxlRU68mzmK/ZEIP\nVFVlfdUR3qo4CIDDYOYbkxeRG9X3ChqRRMLGagDE+bcj5kzqT3MvSURB5Mvj5vLf+97TwjpO7OSx\ny67pU5JnZ4TohA4h7apH2f6W1tnw8psH5LiXd60DVJAMiDOv69Parae12tDJ1igK9IRCHR2dSwyT\nUSIzJYrMlA7nQygk0+D0aU1imrzUNXtpcvk6hLU7SIs7yImKDmEdZTdFBPWZGGu7dfgKa11EDzJW\ng5H8mCTyO3k9FVWh3ueOiOpqj5Nqtwtn0IvTbOHZ8dO5+nQlN9aUYpBDpG9/hwNF23kz7zLiY5Mj\nISFZjjjSbDF96hw3ElBUlddK97KxphiAeLONb05eQuoFejmVPR+gHt8NgFAwu8+CSad70u2x3JA9\nmbcrDlLS2sDm2uMsTh9/wdsTouLbkw1/Bs46rfScIiNeeVu/CmnV1YB6bCcA4qQrERy9T4ys8bg4\n2ao1M9ATCnV0dHQ0jEaJ9GQH6cmOyFgorNDo7JS82OyhyelHaVfWbZ4gbZ4gJ6tckTUOmzGSuHim\nOojDNjx6OOgiehggCiKptmhSbdHMSsqJjLtDgQ6vdcpY/pKSw/VHd5Di9zLV1UjuwW38JbeQjTEd\n3lgRgVRb9Fmx1n1pez2ckBWFl07sYGd9OQBpthi+OXkxceYLK8SvVBxF2fa69iAxA+nae3XR088s\ny5zIvsYqqjxO3iw7wJT4DBItjp4XdoPgiO2o2tFci7J7vdaQZcEd/fa/Uz57D1QFBBFxVt+SGM8k\nFEqCyOXJekKhjo6OTncYDSJpSQ7Skjq+E8KyQqPTF6lhXd/spcHpQ1E0Ye32hnB7WyitbomssVuN\nJHcKA0lJsOOwGQf9+1wX0cMYh9HM+NgUxse2x0CPv5zwvFvxbPobtqLtxISCPHLiAJ+k5vJaeg5h\nUUJBpcbbQo23hV0NFZFtRRktnTzW2m2qNbpPDUkGm6Ac5vfHtnGouQaAMVEJPDJpEY4LTP5TWxqQ\n1/1Oq9VjtmkdCfVEwn5HEkXuKZjLT/a9T0AJ89cTu/jm5MUXdXIT7DEdyYZNp1D2vK95pK9aedEn\nTbWtGeXoJ9rrFM5DiEns9dqgHGbHmYTChEyi+lBTWkdHR0cHDJJIaqKd1EQ7oF2ll2WFRpevU/Ki\nh0anD7ldWHt8IcqqWyjrJKytFkOXcnspCTai7KYBFda6iB5hGMxWYpatRhk3E3nDS+Br48rT5Vwe\nDFC54DZKjeb2eGsXdd5WFNovkYT8FLlOU+Q63bEtQSTNFkOmQyu7l9Vefs8+DISlJxTk10c/5mSr\nVnd3YlwaDxYuwHyB1Um0RMLnwe8B2hMJY/XY1YEi2xHPdVkTWV91hCLXaT6pK2V+at5FbVOwRWO4\n49uE33gaGqtR9n2oCenFX7yok6Sy5wOQw4CANGd5n9bubayKJBQuTNPLUOro6Oj0B5IktgthO2fa\nd8mKQrPLHxHV9c1eGpp9hGUFAJ8/TPmpVspPtUa2YzEbSInvaBCTnGAnxtF/oSC6iB6hiHnTEFLH\nIG94EbXsEGJzLblrf8fY+bdpXdYEkZAiU+NpaY+17oi3PvOlH1YVqjxOqjzOLtuOM9kiYSBnhHWS\n1YF4AXV/LwRXwMszhzdR49V+Yc5OyuHegnl9bid9BlVVkT98GRqqABCvvBUxd3K/2atzbm7Insz+\nxipqfa28VrqXSXFpFxyGcwbBFqUJ6TW/gPpKlAObtNCOq+9CuIDjU/W2ohzaom27YBZCXN8qvZwJ\n5Ui2OPSEQh0dHZ0BRBJFkuJtJMXbmDxOu2KoKCrNLf6IqNbirL2Ew5qw9gfCVNS2UlHbIazNJomM\nRCNZ8Rdvky6iRzCCPQbp5kdRDmxC2fIayCGUza+ilh1Guu4rGB2x5ETFkxPVcaSoqooz4I14q6vd\nmsBu8LvbfdZoCY3N3kgYBYBJlMjo3Cym/dZi6N+s2XpfG788tJGmgAeARWnjWJk364IrPAAo+zZE\nksaEcTMRB6lxx6WOUZS4p2AePz3wAX45xCslu/j6xKsu+tKaYHVguP0x5DX/i1pXjnJoM6oqtzfK\n6ZuQVvZugLDW6ravXugaj4uS9oTC+Wl6QqGOjo7OYCOKAolxVhLjrJypsaUoKs5Wf0RQ1zV5aGj2\nEgxpwjoQlKlvlsmKv/hz9qgQ0TU1Nfzwhz9k//792O12li9fzre//e1zzn3uuedYs2YNLpeLjIwM\nvvrVr3LzzTcDEAwG+e///m82b95MMBhkzpw5/PCHPyQ2tu8tjAcLQRCQpi1BzJpAeP0foKEKtfIo\n4b98H+maexDHzTxrfrzFTrzFztSEzMi4X9ZK73UIa630XkAJAxBUZMramihra+qyvUSLI+KtPhMW\nkmC+sNJ7le5mnj38MW0hrWj7iuwprMiefHGX6iuLULa0J02zgc4AACAASURBVBImpCNde58udgaR\nsdGJLMkYz0enijnUXMPuhgrmJOde9HYFix3ptn9DfvOXqKdLUQ9vQ1YUpKX3IvQyz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Ovd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\nmrS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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import pandas as pd\n", "ax = pd.DataFrame(d_score).plot()\n", "ax.set_xlabel(\"Number of Clusters\")\n", "ax.set_ylabel(\"Silhouette Score\\n\")\n", "ax.set_title(\"Performance vs Complexity\\n\", fontsize = 16);\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The maximum score has happened using 2 clusters.However, I believe that the market can't be simplified that much. So, I will use the K-means with six centroids to group the variables. In the figure below we can see how the algorithm classified the data. Also, in the following table, the centroid was put in their original scales." ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "collapsed": true }, "outputs": [], "source": [ "# get centers\n", "sample_preds = []\n", "centers = d_model[\"Kmeans\"][6].cluster_centers_\n", "preds = d_model[\"Kmeans\"][6].fit_predict(reduced_data)" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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IUSKRiCEhIXLTr127JkokEtHCwkJ8+fKlbLp0nVtbW4uxsbFyv5Gu87Zt24rjxo0T8/Pz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p3jVNifnDm+nXcXTZHrf3Yheidzp4+VSyetq4fXIJ9ppFxPpKK8VLpMUSNnRaRn3lFYjwLi1Kj0\nzGdPjToVE8GSVeMpswrBdlQKZVYhvPvlq5yKUexkCwi0dLS1tfmPz/tE+heTlyn+POZllhLpX8zU\nke8LdZP/UgQ5+VoIcvItF0Fit2XyT71uu4L8GONySmE/LZu26hw5WUT3TloN6h32onqPRZ2MlpFw\nzypUZvOm9ZyNP82pmDhu3bqFfZfOMvsqeZTL4f07uHcvGVePUSirqKKursnF+HA62PbgxuVYhTL0\ntftd1UYigT5x/BhCjkaSl19A8rUEigpzcfUYRcdubuRlpfLg7k3UNLQ5E7kXUXEhboNfpaN9b9rb\ndOPi2XCuXowGxJGuwMBAlJWVqaiowNt7FePGObJ9+1LGju3DjBn9iI3dSmTkh8TH/8ycOQPx8fEh\nOjqa1NRUqioryEy/jdfo2aioqlJVVcmV8ycZPm6ejAx8p259SE2+iqgwE5feztLj6dChPSOG9ueb\nLz/g3t3blIiKaNuhC7dvXqSVaRu0dfTR1jEg5Wosn/7fYryGDJKTfn9SQl5CfT28Wpm24VrSaSza\ndqQgL4u2JuDk2Eu6vq7P3a3kmzxSu4qWjvz9lJtRilFlbxx7utR1C9WJSCTif5vexnOarnRuLR01\nrHqqcyD4BEP6vfqP+vw3J//UZ+Y/FUnrhQsn8jgfnocpbixb9K3QeqEF0dRy8kLES0BAQKCJqT89\nUI276RWs3qqL58iVT/3VU1tbmwE+K1m9VZf0zEoA0jMrGzy+ISiKnuTlPKSwuAoN077otxvM/SJz\n5r+9gqiT0dJxVh3a8aj4EaUlxcSdPEDHLs4MHjmD0ZP/y80rsaCkJJMGWJifRWTIelq3tUVNXVPO\njoK8LExNjHjrnWXY9RyGU9/heHi9hlPf4dLtu/UeibGhHh27OGNq3l6arghQUV7Gmci9gLima8OG\nDSgri7/mwsNPk5rag/DwdB48EAtbKCsrs2LFGDQ1z3D27FCiouJQVlZm/fr10i/Y/NwMEuOO/WV/\nNgOG+So8h64eo4k4ES23XEtLiz6uLigpKePUd7hcpOvonnU4drehv4ebdPu5s2fw6UdLmTt7Rp3X\n935aRr01Z6JHBUDdaYqKaK7UqOZOYRQQeJnR0tJiuu88pk1cxHTfeUKk619Ooxyvixcvsm7dOg4e\nPEhVlfzDec6cOU1mmICAgEBLpb70wAcPK8gq92Dx8mO49muYSlwft8EsXn6ME6lv8MuBQZxIfaPe\n8SKRiED/Nfzy3X8J9F/z1Fqa7UE7se5WM1d5WSkp1xMZ5DNNJo3NvvdoVnz5Ix+v+IpPP1vFd78E\n4D50Gjo6BniPXyCz7ehJb1NWnEdXW2MeXA0hL/UYbfUy2bR2FeVFD+RsKC8rJXy/H4E7D3HlZnq9\nToWWYXvOxRyWE6S4eSVOKhk/YcIErKyspOsyMvIpKxvC+fPTiYw8J13u4NAZY+NblJfbExd3EwBr\na2vGjxdL1ldVVpAQc4Tka+eeqjyorKJYKNjaqh3mbWykNV1q6pp07OJMRXkZDs4DsetopXBcfdQn\nQlKQl4WyikqdaYp10VypUc2ZwiggICDQkmiwnHxISAjvvfceenp6FBcXs2nTJjZs2CDTI+Ts2bPN\nYmRaWhqfffYZ58+fR0dHBx8fH9577z2F26akpPDpp5+SlJSEkZERM2bMYObMmc1il4CAwL+DxjY/\nHjt+Dr+uCvpLAl6W7aFGrPx6S6NfYhsqES/T86uPGumZx/jly6B6e4bdT8uQkXC/lBiJs5u3zDaS\n5sEDvOegqaXLuWOBeI1bSMJfQhGK6DdkMu30M/lm1acyy+dMG8OadVvo6uyDgZEpVy5Ek3LtHF5j\nxc5bTERwnTLxBXlZGJu2oZVpG25ejiMuO03aG+xu6hXpduPGjZMZ5+s7gqio3wCYMGGBdHl2dg4i\nkTHwEGtrU5nxQUFBAFSUlxIbtZ921vb1yue3b9da4XmYMnkiJ//7GR5eE0lKEPfZ0tY1wMNrIlfi\nD/Af39cVjquPKZMnyvTwqs3ZqGBGDuvDrBlTG32febgNwtmxL4G7/iA5TtzH6/vlz9fHS6zudlmh\n8yWouwkICPybaHDEa926dXz00UfExsYSFRWFgYEBc+fOfSGqRIsXL6Z169YcP36czZs3c+zYMTZv\n3iy3XVlZGXPnzmXw4MHExcWxZs0agoODSU1NbXYbBQQE/plI1AkHWvuxePQJBlr78cuXXsTGHK9z\nzItID1REnaIe04uJCvmkzuf1k9GTJyM7T0bALiVG4uoxWuG2tTEwMlUo7NDb2RF1NTWSrydw4kgA\nd25dZNSkt6Tz1CdTfy4mhMrKCu6lXsHA2IyqyioO/rmGgrwsMh7UPOsdHR1lxqmrq7Nx49ts3Pg2\n6urq0uXr1h0lP9+Tbt0OM3r0QIXjtbT1MLOwIiP9DiePBSm0Ky5qH2mZIoXnWNJv60r8ARlRjivx\nBxoVkXoSSzMtwvb5UVhLhORC9E4+eHc2C+c/e0qTlpYWs6ctZPmSb5g9beFz368vg7qboKgoICDw\nMtDgiNfdu3eZNGkSAMbGxvz+++9Mnz6d5cuX8/333zebgUlJSdy4cYOtW7eio6ODjo4Os2bNYuvW\nrXKRrMOHD6Onp8esWeKHuIODAwcOHGg22wQEBP7ZPE/z4z5ug+nh2I+9uzaQE5tCKzMbFi+vP1LW\nWNuejMLV9PySry+T9PxSFDV7MnryZGPiJyNgtZ2t+poYF+Rm0k5B/6ntQTux6zkMfUMTEs4cxanv\ncJn1Epn4sIN/4OI+StpsOTZyL6WiYnq7j5Q2CY6L2o+ShhbBW74h7f4N6RxGRkZPPYd5efkEB4vQ\n1z/Pe+91QUNDQ+H4iooyXPuPJnTfRhycBhIR4i9tVFyQl0V0+E4cnDwxNDZn02Z/NDQ0uJ+WQVtL\nc14ZO4o9+w5yPy2Dvk52POYeWfeSaGtpxrKfVjzT/RB1MpqN/vux7jYIT29d4qMPkXn/Ou59e+D3\njHM+DZFIRFDwZtIzxVEw3wkNj4JJUhgD/FfTY7gKRmaa5GWWcvFo1QtRd3tRTaGf5xwJCAj8O2iw\n46Wvr092djbm5uaA+NfDNWvWMHHiRNauXcvChQt5/Phxkxt45coV2rRpg66urnRZ165dSU1NRSQS\nyagPnjt3Djs7O/7v//6PY8eOYWpqyoIFCxg9enST2yUgIPDP51kdGQkNTQ9sLHWlE+aKLPDtU0/P\nr1jFPb8kEZmN/uJaLwdHT6KOBUpT+J6MatV2thwcPYk6uh1jszbSFLruTp6oqWty9uRuPghYI7e/\n2qmNtecuLyvlUmJNKp7bwFcJCfbDuFVr7t2+Sut2toyZ8l/pPHk5D1FRVcPVzRv9sSZs/OEd8rLT\nxevy8jAxURyJA6iurmb69J9JS3Nl6dL7zJw5TWZ9Xl6e9G81NQ30DU1QUVWhg60Dlu06yqQM6uga\n0N6mG3eSLxF3KRZXz4not+vG/fxsJs9cQgc7R7r2HExGfjaplyOYM20MA/q712lbfdQWQpHgNkhc\nj3Yheuczzfk0msJxaY4UxoZQuym0BHFTaAjwX42zY98mseFFOXcCAgItmwY7Xh4eHixdupSPPvqI\nTp06AWBqaoqfnx+zZs0iPz+/WQzMz89HX19fZpmhoSEg/mKs7Xg9fPiQs2fP8uWXX/Lpp59y+PBh\nli1bhp2dHV26dGkW+wQEBP655GQmY/EMjkxzUl8U7qM1V0i59xibdhpy457W82tAf3dcejsREPgn\nD9KS6NnZlPOndmDjMEQuquXg6El0+E4G+Uwj/f4tqqur6NjFWRqFijwaSFFhDv1duyh8qW1rac79\nv+aTzJ2X85CU64nSSFJhfjYxEbsxNDajmmo6O/Slay8P6Ry10x8ltLHqwpULpwBITEzEzq5uyebF\ni9cQG6vHF18U8+ab0+TWJyYmSv9u3caG/NxM2nYQf4+oqWtKo3T5uZlEhQYSeXQ76fduMX76+1KV\nRX1DE7wnLCYixB87e+dajaJ30q1rF2kkrK2lOf/xfa1BDsCTQii1se42SC7i1tB566IpHRdJCuOL\npCGKis9r04ty7gQEBFo+DXa8lixZwqJFi/D392flypXS5V26dGHbtm0sXbqUigrFKl7PS0MjaY8f\nP8bBwQEfHx+gpjj68OHDjXK8ysrKEIlEz2SrwN+DJF9fyNtvWbzs103PqD3pmRUKpeEfZFSiZ9Tu\nhT0rRCIRh/ZvJf70QRza3qGk1BgtTdky3YWTlPnkl1I2fC7vePkf1mfukilkZ2dzaP9WcrNSMDa1\nYdRYWcnyKZNrIiklJSXs2LmHUqMKEqJ3M3CkWARCmgq4fxMoKTFs3DzpGH1DE7xGzyJk5xoWzp+r\n8PyMGzOSdz78BkePSdKImYqqmowTJZnn4I6fqSgvR1NTRybqpkgApL11V+nfe/fu5bXXFMuor1ix\nhX377uDnN4ZXXx0IwObNh3FwsKJ3b3vpeAntrLsSFbod71fny80VFbod98ETaWXWRux0HtmOkrIy\nGpra0uifs5s3SQmRUmdNTdeSWQs+xMn9VWlkbPyUxXTrZMEH779T70v67TsPMLbppnBdXs5D4pJi\ncR1YE3F7/a1PmD7JG3e3vtLtGvO52xq4vl7HZcv2dUz3nadw/cvAvbRkOrvWrah4PSb5uT/DL/Ic\nvezPTAHFCNet5VJWVtak8zXY8TIyMmL79u08evRIbp2trS27du2S+YWwqTA2NpaLpuXn56OkpCSj\nqAjiCFxBQYHMsjZt2pCdrVhyty7S09NJT09/NoMF/lZu3779d5sg8Ay8rNetY+c+rN8TwCevywsD\nbNynwZBX+nD16tVmt+PKpXhSk9Yzb1wpMzzUSM804Jdt2Qxw0aFPTx3pdpZmqmjp2/D5uhzmji3D\n0lyVtIxKNuzTwKb7DEIO7pTOY+GhRnpmBL9+FYB193l0dVDcGLePiyN9XBw5fyGJ0HB/ujiNwMDI\nFKNWrcnOvI/PBMXRAg+vyWzYuIXRo0YoXD+wXzdCw/2xd/ZGSVm5TmXE/sN8iY3aR8qNRHr0Hix1\nvhSJeth1dUVHz5Dionx27drFqlWrZCTlAX79dQ8bNoSxefNihg7tI13+/fchrFgxmt697UlNTSU4\nOBgAbR19bl2Jx8zSisijgbh41NScRYVup5frUFqZtQFqUh9rR+1OHttBdXU1eTni75TO3fqS8SCF\nQSNrlAz1DU3wGreAsIN/8Pqbn+Dj5UKvnt0Vng9V5ccKa+rKy0q5eSUer3E1io36hiY4ekxiw1Z/\ntLU00NSU7Z3WkM/dtZsX6OtRt+Ny5tCFF/IZeGaqNMjLLKlDUbEEqjSe2/6/4xy9rM9MgfoRrptA\ngx0vCbVrrWqjrKyMs7Pzcxv0JA4ODqSnp5Ofny9NMbx48SK2trZyvwra2toSGBgos+zBgwf079+/\nUfu0sLCQ7kugZVBSUsLt27exsrISUjpaEC3hulWWr+SbzV8wzacQSzNV0jIr8Q/RZ+Coj+WU85oD\nkUhEWPDiv5y/WqmFc81YvSGTHp21pJGvBxmV9O47glFjZ3Bw3xZyY1IxNrVm0YczePz4MRu/Hy03\nzyevV/HN5q34jJpY7zWwt7dn3NjRLFn2EdmFqhi2ao1lu45197UyMiUvTwl7e/t659uxcw+Py3Lq\nVUbMy05nkPc0ThwJYMzktwHFoh5q6hr09RxH+MHNVFRUMHfuXEJDQ6VNlIODI/j44z9wcTHn0KFz\nHDx4lupqqKio5uHDIlxc7KmurmbevHnSDI4OHXvg7vUad1Iu4enmjb/fR3Tq6sqNS3GMnfKO1OlS\nlPqob2jC4JEzCDv4B+OmvEuJ6BFRodvp0LGHwmN19RjNrWvniDx9mXFjRyu8Hh06dOCdD7+hm8tY\nmXq4ysoKXPsrrme2d/bmQtJVZk6fAjTuc9fFrid5mcfqlILvYuchvcYikYhd+wLIyL6LuUl7Jo5r\nvJx9U9Ohw7ss/34qg2bIr7twpJJVS5Y8t42NOUfPS0t4ZgrII1y3lkt+fn6TBqx1mpYAACAASURB\nVGMa7Xi9aOzt7enevTvfffcdy5YtIyMjg82bN0ubNY8YMYJVq1bh5OTEmDFjWLt2Lb///jszZ87k\n2LFjXL58mdWrVzdqnxoaGjK1YwItBy0tLeHatUBe5uvmOcgH176DZNQJ3/q46dQJn8a+4I1M9ylE\nocDHGCP2hhXgO0qswLf9qCGLly9AS0uLGbPfldk20H+NzDyikmr2hReQk1+FgYYSB/duZsacJfXa\noq2tzdqfvxMrIPYdTsKZo/X22+rQoU2911VbW5uF8+eirq4mrfl6kvxcsRx9zPFg9AxNObDjZwYM\n85UTAJEIc2hp66OmrklFeSnh4eEsWrSIX3/9lfPnr/POO3fIy9tPaCiEhsrux87uFywtLVm0aBHh\n4eEA6OobM3X+SjS1dLl6MZriR4UYGplSVJCDRbuO6Bm0IuHMUUSPCsjNTmfgiP8oPE4X91HsC/wJ\nm8698Bo9i1NhO7Gzd5bWgknQNzRB9KiAHr2HsGffQebOlvcWtLW16etox94DG3D3miyNrJ04vBVz\nCyuF51Df0ISse0ly16Ihn7vpvvNYsuoInvJlcCSFVvH98tfR0tKSEZfo7KFFXuZ1PvrhSJOJSzyr\nYqC2tjbTRi1TqKg4ffQHtGrV6rlta+g5akpe5memQN0I163l0dTpoS+94wXw008/8fHHH+Ph4YGu\nri6+vr74+voCcOfOHWl+tpmZGevWreOLL75g7dq1WFhY8Ntvv9GuXbu/03wBAYEWTnOpEzaE+gU+\n1MjJryI9s5JtRwzr7RFWe57YC8VExRczdYwRFmZqpGdW8PP234i1d6yzybIEbW1tXHvZsnfXL7j0\nH8u5mMMyUR4Jt6+c4IOfVjToGOtrBnzyWBBeo2dLa6jiTx1kt/9q7Lr2hsdw/NAWWrftSMaDFGmK\nn1Gr1vj7LYfHj/Hz8+PmzZvMnPkmTk4F9O79ax3HVcjw4cOlTpeSkhJ9BozlbHQIysrKqGtqExW6\nnYdpt+ntPoprF6KJOhaIq8do9A1NOH5oS71Ru9ZtrOnYxZlTYTsxs7SWqfmSUJCXhbauAfqGJjy4\nl6RwLpFIRNz5ZLwnLJYu0zc0YYzvu4Qd/APLdh3lHLqCvCw5Wf/S0lK2Bq4nJz+tXkemIVLwzS0u\n8byKgc2tqPh3y+ULCAi0HJQeN4cGfAtFJBJx9epVrKysmuRXMIEXh+Ta2dvbN/mvSYr6JQlfpE1D\nc163fwqB/msYaO2nWODjYQVfbm5N/0HjZO5LRffs3l0bGGjth4GeCr8GZLN0rnx/rdVbdVm8/Fi9\n97dIJGLBfz+jq8tokhIiSbt3ExVlFdwGT8DAyJTCvyTT504fS38PtwYfZ9TJaNasC6Krs490nrhT\nBxAVFtCzjxcdbB2k24buXY+SsjKu/cegqqpGxGF/Rr0m6xifiznM9nWfAuKvODU1NcaPH8+4ceNw\ndHTEyMiIvLw8EhMT2bt3L8HBwdL0QiUlZex7uDFx1vKaiNKRbWhq6tJ34DjCD21GQ0Nbpr4t4cxR\nqbLjkxTkZZF8PUHqaEWE+KOsrIznXxEySbTu5uU4bDo7Ym3XCxuTAoURrw2btnC/yLxB+5FwIXqn\nTH+vsIgjbDv4DX3G6WBkpkVeZgkXj1bV68iUlJQQuOsPhRGnTf5rKbMKUZhql5dZisZt72dWDhSJ\nRCxZNV7GqZMQ6V/M98uDX5rncX3nqKkQnpktE+G6tVxycnK4fft2k127FhHxEhD4u6irX9IAn5VP\njQwIPB8tyeFtTlvHjp/Dr6uC/pKPl2V7qBHf/XpQZl913bOuQ5az7YghbY3vM3WM4ubCDelNJpEz\nl0iqO/UdTkV5KUkJkeTnPKS1Efj99G2jj7+3syPqasEkX0+Q1i15DvNFTV2TiBB/LNt15PFjsZqh\nqpo6+XlZHN71GxVV5Yyd/F+5+ZzdvLmbcpmLZ49TmJ9FRUUFQUFBBAUF1WuHgZEZ9j3cmTjr/6TL\n9A1NGDP5v0SE+KOlrUsH2+507CJb01xbYv9JEk4fwcOrJprn1G8E+7d/S0HeMPJzM7h5JR7X/qNx\n6jucwvxsToUFMfi/CoqSkO2BJm+7KXdvnpOR9pc4wbWd8p3HfmTE6zWOW0OiU/VJwadn3sG2HuXA\n5Lg7Ctc1hBchB99U/B1y+QICAi2LRjte+fn5rF+/nps3b1JaWiq3fuvWrU1imIDA3019/ZJWb/2E\nHo79XlpHoKXTkhze5rZVW1ubAT4rWb31E/E+zFTrTC2s/55dheuQj9jqtwDfUTXRs9q1Xq0MVUgv\nv1GvI6noxb92X6uiexHP9LnYHrQTu57DFEZynN28iTwaiIqKqoxiYFzUftIfJNeZ4jdy4mKUlJRQ\n19DkTOReiovq7jepraNPK7O2dOrWBw8vxTL0zm7eJMaGcTflslyzaInEfkSIP079RkijdudiDmPb\nxUkm/c/AyJQRw4ZQnH6K8+dTGDulprZO39AEnwmL+X3zFtzd5J2g2j3QnqQgLwvfCT6oqWfw4F4S\nbS3NWFYr0gViR6aXt+Kv/md1ZCzMOpCXeblOcQkLsw6Nmq82zenUCQgICLxoGu14ffDBByQkJODk\n5ISJieIvOwGBfwL7gjcydUQ+CkUNGhAZEHg2WpLD+6Js7eM2mB6O/WQEPhYvl4+qPe2ePZF6iwHD\n3yI9cyMWZmoKa71+9D/MR/89wdLp1Qodydov/uVlpaRe2k916QOUNdvQqq0bNn/VEolEIrYH7Wxw\nI9/6IjmaWrqUlRYzcqJsXZPXmNkEbfy8ToGPElERuvrGKCsr8/YnW4g5vovH1dXkZD0gMz2V1m06\n0rqNDe2su9KpmysP7t7g1LEddSs1GpqQeiMR7/ELpM7fqbCd2HR2pIOtAx1sHdDRNeTB1RDOPEhH\nz8QOD6+JCmquMrG1aUd5eQW6lopVd7s6+7B5SwAL5s+VWV5fPZykrq6+89wcjszk8TNZsupAPeIS\nsxo9p4TmdOoEBAQEXjTKT99Elvj4eIKDg/Hz8+P777+X+ycg8E8hJzNZYV0NgIWZKjmZKS/Yon8H\nNc6DPBKH92XhRdoqEfhYvOQHfKe9qfDluiH37MTJ89l2xBBRSTVR8cUsnWsmHWNhpsY3S3SxMMzB\nUF9Fumzp9GL2+r/Olo3f8crYUaRejiA9NZ78pLdZ8doh1r93mRWvHaLo8pt0aGNA1MloFvz3M3Et\nUrvB3C8yZ/7bK4g6GV3n8bW1NKcwX3HPxTORezAyseBU2J8knDlKRXlNtsXQ0bOJDt+pcFzC6SNY\n2/Wkuqqa65dOo61rQPXjKtrbdGPBMj9mLP6a4a+8TtdeHlRXV5NyPRH7Xh512pGfm4ldN1epY6Zv\naMIgn2mkXE+U2vTg1mkmTXwFE7P2iIoL5ZwugJjwP+nQvh2RJ8/UK8hx4uQZueXa2trMmTaGC9E7\npXYW5mdzIXqnTEphXYgdGcUqXc/qyEjEJSL9i8nLFJ+HvMxSIv2Ln1tcYvL4mVw8Kt9HD8ROne+E\nZ3fqBAQEBF40jXa8dHR0aN26dXPYIiDwUtHKzJb0zAqF69IyKmllZvOCLfp30JIc3pfN1obcs5LU\nxbe/Lq271usvmXoJopJqOrQu5UzYKj5Y3JdenQ2ouPcdX79ZJeO0rVneirDgRXz3w4/0dJ8o46D0\ndJ/IRv/9dUrzTpk8kdTLEXLL7yRfIjc7HQdHTzy8XpMqA95JvvTXMbelqrqKiBB/qSNSkJdFRIg/\n7W26kXrjPMZmllRXVcHjx5SIinl4Xz498VJiJM5u3jg4enIu5rBCG8/GHKK7k6fccmc3b+JPHeTY\n3rWoPBbx1f9+o0e/V7Hq2IODf66RcZAiQvzp5jSIbX8epby8rE4nryAvi+qqSoXrBvR3x++nFbTV\ny6DoXgSm6ndx69uGqNh9+G38Cb+NP/Lld8vY5L9W7nxPHj+T84cVz/s8joyH2yC+Xx6Mxm1vkg/a\noHHbm++XB+Peb+AzzSehOZ06AQEBgReNyooVK1Y0ZkBpaSk3btygZ8+ezWTS30dFRQXZ2dkYGhoK\nqjMtDMm1MzU1RU1N8YtwY7G1687GP3bi3lP+RdZvtz7T5//YZPv6t6LouiUn38REPQ49HfmC+rSM\nSjIrhtK9Z5/n3rdIJGJXkB+RYYEkJ9+kY6cejb6eL8rWhtLQe7ZtO2tSkm8wtPd9hfPo6agQGVeM\naw9tYi8Us+tIAa95GzJ5lBEu3ZTY4B/KF28aKjxuh47qHD+VipntWFRUZLPZtfXNuXMjDifHXnLj\n1NTUaGWozeGDe9DWN0dDU5uczPucjz3C6Elvo6EpfiZraGpjbdeTxDNHaduhM0UFuVRWluPi7sO1\npNMkX0vgWtJpXNxHcvViDCgr0d1pIHZdXTAxa0vKtQQ6dHTAwMhMOidA8rUE7Lq6oKKqirKyColn\njtLKtA0amtoU5mdzZI8fDo6eGJtYytmuoanN2ZgQVDW0cRk4hTZWDsRG7iMvOx0Xj1Gk3rxA8rUE\nigpzcXH3wdjEEm19cx5lX+fypUt06uYqN+epsD8ZPtgVl97Ocusk58vJsReqquWEJ2zEzDUVS8dH\nlGheJzLqOGbdClBvd5utfwRhqNmG9u2speO0lE3YE3iMVu2U0dJRJS+zlLjdZUwd+T421nYK99cQ\n1NTUcOzpwgC3oTj2dGmy52P7dtYM6fcqV2MecTdRGcOK3rw3/6vnsrWl0hzfdQLNj3DdWi4lJSXk\n5+c32bV7JnGNgIAA9uzZQ4cOHVBWlg2afffdd89tlIDAy0BjRA0Emo76VPwCjhqyePlcBaMaR1MJ\nYjS1rc+rjtiYe9bcshPpmccVRuzSMipoZagik44owcJMjf7O2vVE+tToZVdBStJ+rB3GcCkxUkaI\n4kGa4v5UII7kuPR2IiDwT+6kJBAbG4uH9wKF2zq7eZOUEElGWiplpcV07OIsVQWMi9pPXNR+qh9X\nMXTMXBkbzC2t6O02Uk6BUFvXQFor1sHWAct2HUlKEI9TUlKmuvoxhsbmcnaUl5USf+ogAHp6RiTG\nheHqMYpBPtM4tPMX9A1byci7l5eVknDmKBkPUijITaOb02AZQY6CvCwSTh9BpVrErBlT6zxXQJ39\ns8a9Yc+BjdcZ/p+OeE5TkVMrdOszAC11PZKunSU5Lk2mr9WzNipubgTFQAEBgX8CjY54rVu3DiMj\nI9TV1RGJRBQXF8v8e/XVV5vJ1OZHiHi1XJrr16S27axx6ufLkRhlIhMNyawYyvT5P2L1L/yltTlQ\ndN3U1NRQ1bQmcFc0NhYi9HSUSc+sxC9YH8+RK5/73ItEInZtmsXS6cXSiI2ejgruPSsI3BWNUz/f\nBt9DTWlrbMxxdm2axRiXUwxxuoeJehwb/vgTVU1r2v4VrWgIdd2zZuZtZCJ8w3ymsGXbHsXRsaAc\npo8zZl94AWMGG8hFtpLvlmFiqFpHpK+C/KIqLtx4zK3kdBycPLHr6oKOriEx4bswMVLHa/DAOu1X\nU1Pj0aNiTkRfpOKxNl16KO4FpqGpTeSRAMpKShjkPU0mquTafzT371ynnU03rl6IxsFxgNSGlOuJ\nVFdXY25pxdlTB3mYlsKd5EuUl5Vw9WI0Xbr3k/bVkjhrWQ/v4DVqFmejD2FtV5PtcSf5Ehfjw+nV\nZyi9XL0wMDLjcmIkmlq6GBqbYW5pzfn4MNpZd5XZ3sFxAA5OnrS37UHytQTa23Qj/UEyydcSSDhz\nBDMTQ95ZPANb2/rTmf2D1mPSOxktHfn71aytDhdOPqR9JwMMLKq5GvOIznbd8A9az+HwYFJSU5g1\ndT7Dh4yRRqdOxUTwv01vY9I7GUvHRzxSuyoXMXtRiEQi/IPWExK2i1vJN+nSyaFJn+3NPX9zIURO\nWibCdWu5NHXES2igXAuhgXLLRWhO2DKp77qVlJSIVfwyxSp+TdUbq76GxOmZlZxIfaPRapXPa2tu\nbi5LFrjT3jSPK7dKKSmrRktDma4dNbmbZcz3ftEYGSmux4K6I2WS5VcuRvHw/nk+nKuKTTsN0jMr\n2HbEEFOrV8m6vUcmOrZujxqFRVUsmVbF7mMFLJ4qL/4gKqmuswnzRz+mo6GqxOE4A8bO2SgnLhFz\nbDO///QZe/YdVKh4KBKJmLf4I5Q0WpFy/TzDxs5RKECRn5vJzStxXLkQzYxFX8k5S/k5D1FSUlbY\nV+vgn2uw7+HGneRL9HYfWdMk+fA2HhXlY2bZAVeP0bWaJwfQ02UIj4ryuJt8CfchE9HU0iUqNBCv\n0fI1UccPbaH/0EmoqWuyY+NKJs35mPKy0jr7fEWE+EvVDwvzsjDXfCCnZqiIL79bhu2ouusIj267\nxfCpHQGI+l2dx9q59BiuIm2afP5wJdNGLcPDbdBL1aj4VEwEASHfytj6tAbPL9P8zYnwXdcyEa5b\ny6WpGyg3OuIFcPfuXQICAti9ezfh4eGkpqbStm1bdHXlH9gtCSHi1XIRfk1qmdR33dTU1Ojesw+u\nbiPo3rNPk13XyLBAhjjdU7hOT0ccJXJ1G9GoOZ/V1sLCQj777DOmTJlMXGI6kfHFXEku4+btcq4k\nlxEZX8z5y9msXfsLRUWPcHFxQUNDQ2aOuiJll65msumXN1ApCaejxUMm+2gQfLQAVRXoYquJe88K\njkWmMOfd/YTHqUujY3MW/8pg73kciKziUEgkA1005SJbampK5BVU8ltgDj07a6Gno0JaRjlf+GUw\nwFmXOa+1wscdThwPo7CsNXpGbaRj9Y3b8O1XKzC28kTfvBtZhcps27qZVobadOjQnk8++5LbaYV0\ndxpIN8cBxJwIxqaTo9y5Ox2xG2s7R5ISInh4P5lLCZE49hlGl+79xNG147vxGj1Lpo5LgrGJJWej\nD+E9foFM7Vjn7n25k5zEkJEz0NbRr1nu0JfEM0e5l3oZXT1jblyJ58LZcAZ5T1U8v2kbrl06g5a2\nPgV5maTcSCTr4R16uQ5VuH0r0zZcSzqNRduOaGjpkPfwKgMHuD/1/rmVfJNHalcVRrxyM0oozC2j\nfScDHt4p5tbVNIbPM5Vuq6WjhnUvDQ4En2BIv1cJCt5cZ/RMEjFz7OnyVJueF5FIxP82vY3nNF0Z\nW616qkttfZ5nQXPP39wI33UtE+G6tVyaOuLVaFXDmJgYRo4cybZt27h9+zapqals3LgRb29vrl27\n9twGCQgICDQnL4taZVhYGA4ODnz11VcUFcnXiNWmqKiYr776CgcHB8LDw6XLa/cRq60uOKBnJjcT\nfuTzReosm2fOQFddgo8WMMBFh71hhWzZk0NJaTVTR+Rz9FCAnEy9lpYWM2a/y7v/t5kftuQptOlq\nchnenrp88vNDvvwtg0/XZLBicWu8PfWldnz9ZhUq2Rtk5N8NjEypUlJXqHh479494hKT8Ro1C31D\nE9Q1NLGzdyEixJ+CvCygRhlQR9+IszGHmPrGSkZPfpsRr77BxbPHuZN8CX1DE2ztnWQiZeVlpVyJ\nPszFI0EkhAfTf+hkhcfVf+hkkhIi5ZY79RuBtq4hg0fNYOCI/1BdWVmvFLzoUQGnI4JRVVVD39CU\n+3dv1NsfTPRIrCJZkJdFG0v5SKIi6pNajz54FxcvscN79I90BrymeN+SpsnpmXcU9soCcX+v9MwX\n06g4KHgzPYbLp7BCja0v8/wCAgIC9dFocY2ff/6ZOXPm8Oabb6KiIn54VVRU8P3337N69Wo2btzY\n5EYKCAi8OJ5X4OFl50WIdzyNgIAAZsyYQVWV+KVZTU2NCRMmMG7cOBwdHTEyMiIvL4/ExET27t3L\nrl27qKio4N69ewwfPpwtW7bwn//8R2HDZIkgxv+WWUiXWZipsXSuGas3ZDLvNWNCTxXx+a8Z6Osq\no2F6o047XfoOZPc2Iz76MZ2Fvq2wNFcnLaOcdX/mcjaphOrHj/Fw1uF04iM+f8sCLU353/LemlTG\nZzv309n5NUDsWFRVyjsLarqWvDZ1AcNfXSyzXCJ0EX/qIGn3bmLT2Qn7Hu7EnTrAmMlvS7fTNzTB\nfchEjvivJv/aBcoKssjJfEArszY8uJlEZdJZFvcYirmdCRmF2fxxKpTS7r1pY9ddOkd5WSkPrpwl\n+2oCF8tKUVZSobKogLz8TAwMTKjIzeZS1EGqRY8w1W8lnf9J8nMzSbt7k74Dx9HeRtwUWlVVrc5G\nzwV5WWjrGgA1TZAbgkRqPcB/9V9pc5rkZoiI2nsHh37mFBdWcHpnKbbtumFkVqZwDknT5JelUXFz\nNHh+kfMLCAgI1EejHa/r16+zdetWqdMF4peGN998kyFDhjSpcQICAi8GhbVAfTSeWe3vZeZFqVXW\n5cCGhYUxffp0qqurARgyZAgbNmxg/frj3LghwsVFFV1dXcrKyigoUEVNrSs3btxg7ty5hIeHU1VV\nxYwZM2jdurW4j1gf2dSHfeEF9fbnOhH3iMoq+GqJBav8Mrh/6yhfff4WejrKco72vuCNfDAbDPXN\n2RtWQE5+IUXFVairKrH+i7ZYmKmRnlnBxesl3E0vl6ubE5VUExlfRM7tI1wHbLqPIf7UQdrbdpPZ\nrryslIwHKVi076rQMVFT18Rt8AT2BPyPwvxsks9GYtOuE1eiD2PnMgg1dU1uXznLg6hDuBu1oY2q\nAU6OfdlwZCePXPrD1Yt84OErnc9c34QPPHxZeWIrl9LvUC16RJGoCNG9FJTKyqiqruJG2iHcbR2x\nNmmHk1Nf/ojZjZOGEdMte2GuL3befj6wnWK3wbS3d5Yex62zEaScj6FTVycs2tpK99neuiuJMXvw\n9Jknd3wJp4/Qo/fgBjdBro2H2yCcHfsSuOsPkuPuYGLUhoHdqsm5m45GqVitMHDXH+RlhtTrVE0e\nP5Mlqw7gKV+CRlJoFd8vb5pGxaWlpYSFhREfH8+VK1coKSlBS0uLrl274uLigomhZbM6gC+Lgykg\nIPDvpNGOl46ODiUlJairq8ssr6ysRElJqckMExAQeDHUllb37aNGeqY62/bnMcBFhz49dVg6vZjV\nWz+hh2O/f0zkq4/bYHo49hMLYsSKBTEWL2+6yF5dcvVOA5Yxe+5iqdO1YMECfvnlF5SVlYmLKyEs\nbDKrV59GV/c4paXGFBerMHeuAVZWVoSGhrJo0SL8/Pyoqqpi1qxZfPrRYtIzK2Qcnpz8qnql3u+m\nldPeUvz87tVFk5jzBcwcHP6XEyXraNd27HxHGdWIarwhKy//3QdtWOWXQY/OWtKoV+yFYqLii5k6\nxgjfUcqkZx7iq427ycvsgOdwXxm7JM2Lb107V29UyFi/FVaicj4fsVDq/PxxMJAcA33079/jY685\n0uXBCaG80rU/O6PDmO8+AVF5KUcvnyJPVICRtgGtDUwwqIbXLXuhp6nLrnNHiH2shLaOAa30jJjl\n9qp0rl3njgKwdPgcqT3m+iZ8OfpNPt7/E8fPR2PT053qy4ksdhyB+cRBUttU/4qq3bl2kp4dTAnb\n+BnVKpqYm7alSlOD/OIsLMz0sG6Vz0eLVzzTPailpcXk8TNlZODfXVgzV0OcKi0tLbnoWV5mKReP\nVjVJo+LCwkK+/vpr1q9fT3a24qbRACYmJrTrpM/in7ujrSt7HzeFA/iiHEwBAQEBRTRaXOP8+fNE\nRETg7OyMjo4OABkZGaxYsQJTU1NGjRrVHHa+EARxjZaLULj6bNQpre6kQ+DBfJy6aqGmqoSNhYgj\nMcpN3gz477xuzSXeUZ9c/dx3dnHhsrhp8ZAhQwgMDJT2Qtyy5TQlJdepqDBAWbkKW9v7LFtmyCef\nTEdJSQklJSV8fHyIjo4mNTWVwsJCOnXpRfLtLBlJ+KdJve8+VsA7M02pqHjMocgiPl7Yuk5Z/bt3\nbss0iN51NF+hvDyAbTt1jp4qonsnLUQl1ew6UsDSuWYyc3v3V+fCpQz0278i01xZ0ry4lWlbYqP2\nyUi2Szh1bAc25fBh/ynoaoifz7oa2ji1tiP2XDgrRi6SWe5i1Z09iWFMdvZm/8UILt6/zvBu7vS3\n642Wugb7zoexaNBU/M/sI+rmWSY6j2BUj0EkZ99jydDZMnO5Wvfg1K0E0guysTVrj1ot27tZdKQi\nP4fsGxcZ1aUfdmZW0nEe7bsTEXuYC9dOYlupgm2ZMekZ9+mqb469tglj23anuCSbiTMnMHbc6Ge+\nB58mA6+mpoahZhsOBJ/AwKJa3DQ5o4QzwaVMG7VM2oi4qRsVSyTbf177Pxa+8RbHjh1DJBI9dczD\ne3kcD7qDaVtt2tnpN1mDZ0DxuWjC+Zsb4buuZSJct5bL395A+cMPP2TmzJl4enqiry8uoi4sLMTC\nwoJNmzY9t0ECAgIvDkU1QhKmjjFib1gBvqOMsDBTJSe2btlqgRrqOqelZdVcuJwOiF/+NmzYINOA\nvqqqlDfe0GLGjK7o6+tjbGwsl0WgrKzM+vXr6dy5MxUVFWzevJndO/1ZvfULadqkaw8dvt+cy+r3\n5Zv9/uSfxbSxRmhpKhN4MK/ulMQR+ezdtUGuHq6+aJqluTphMQ8Z6KrLibhHdc794RxtXv/2c3p7\nvSuVa8/PSpVGumw6OxIR4o+zmzfKKqrE7Pqd0uyHlD2u4tURNc2UJRGs2NQLvOM1Q+G+XnEcyk/h\nWykqLcbL3g19LT0ADlw4Tj8bR9af3IGSkjL/5/0GAHsSw5jU21vhXPP6T+To5VP8ER1MX5ueOLUX\np0ua65tQWV3FitGL+Sl8C7cy7/KoTISRtgEjHPozx3E4353cimsXVyKux/L+MNmoXF+bnoRu2E0v\nF6dniirV1UTZcxoyjZNrpyRej0mGKg1WLVki1zqlqRoVSyTbS5UesnXjBaqrxJ1rGlrP+KiwlF+W\nxJEW3wrvET7SqFxT8GR6Zu0G0gICAgLNSaMdLwsLC0JCQoiKiuLu3buUlZVhbW2Np6enXPqhgIDA\ny42iGiEJFmZq5OSLRRBepNpfS6eucxoW84jcAvH5nDBhAlZWVnLbqKtrbPvB8AAAIABJREFUYG1d\nf6Naa2trxo8fT1BQENnZ2RQWV7F4+TGZtMmhE9qy7H9v8vY0fSzN1XnwsJzfgnIY6anPABfxC3r9\nKYliR/vJerhWhipyqY0S0jIqGOAidrpOxD3Cd5Rix8vSXBUvjy7o6mXw4F4SbS3N2Bngx7sffktP\n94lSMY3wHb9gU6HE1wP+I3VUNpzaRUfTdtiZW3Em5QLjnYaRVZSLub5ixT4LA1OKSosZYOeMm20v\n/ogOplc7e25m3kVFWYX2xm1ws+0l3T5PVFDnXBIHa+HAKfwaEcDNjLsUl4tQVVZBR12bhLuXUVJS\nxrOTS00a5F9OmqWGMSdvnmW5z3yZ+RYOnMLaE9sZ2d2T4IA/mTpXsQNZHw1R6ZM4UhKnStJTqLkc\nDYkzaGxbzFdzz/NYnFkrrWd88t43MTFhx46z9O/vy6pVq6T1jNXV1ezZcYT5s99pclubysEUEBAQ\naAyNdrwAVFRUGDTo5W4yKCAg8HTE0urH6nyRbmUofqF7UWp//wTqOqfxSTUpVuPGjVM4Nj8/h4UL\nf+Ly5bu0bWvBW28No0+fHnLbjRs3jqCgIPG88fGMHDlSrumzhoYmn659m45t86mufoyaqhK27cU/\njqVnVnDhWkk9TlSNo127Hi697Dq/7jjOFwr6SwccyGPxVBNpjVd9c5tb2uE7rcbJEIlE2JhoEbH5\nSwzadca6lwe2VSp8MqomwmWub8Jyn/l8cWgtD/IzeXeouBbnYUEWGYXZ6GnqytRwjXDoT4GoCC97\nN66k3WJYt/4sHDiFLw79RnFZMeOdhnEoKVLG0TLSNiCjMFuh8/WwIBsjbbHy4HinYYReiWa2+3gy\nCrP58+xhkh5cw7lDdw4lRUr3v3DgFH4+vpW84iIWDZoif9L+mism+Txlms/mWNSn0qetp8qRiIPS\nui/fCY2L6ohEIpm6sYaODwrejJ17NavmnJU6XbXrGZ8kNPQMP/xgwKhRt1mwYLRcPeO4V8bw9f8+\nZ/a0hUJUSkBAoEXToD5etdUKPTw86v0nICDQchg7fg7bjhgqXBdwII8+PXVYvVW3SdX+/unUdU6v\n3KrpZeXoKN8QWFlZjfXrAxCJRMyfP4SSkmK8vSP56adguW1rj798+bJCOzwHefPzpgu07/EhepaT\nseq5lE3HBjLno3z2hRfy9RIL/tidq3BswFFDxk2ocbS1tLTwnfYm7374C6N9f2H1Vl3SMisBSMso\nZ/WGTDxddaVO19ghBg2e+3RUNKvnf8xYlV6s81nCex36Er1hFW94TFQ4fq7HREx0a6JpZvqt+C0y\nkM0xu3Gz7cVs9/HS6NZvkYGUV1agraHBooDP+erw7+QU5+PQphPm+iboqGuz9fReNkUHsycxDM9O\nLgQnhCrc7+7EUEY49AegtYEplx7cYE9iGPpaerh3dEJTTVNu/wl3L/OaszelFaX1RtIe5D/EtG1r\nheufhlilr0Ru+a0LORzeepMBs5SxHZVCmVUI7375KqdiIho076mYCJasGk+ZVUijx99LSyZq7x1y\n0sV2DRkypE6nq6SkhLff9ic3tybFU1lZmV9//VX67vGoSMTeiLWNsl9AQEDgZaRBEa8JEyZI/540\naZKgXigg8A9BkbR6WmYla3dUU63uTmzagCZV+2tpNLanmWT7XJEFH625wsJJyliaqZKWUUnClRrH\ny8hIPg3PwqKMqVM/Z/bskQBMnDiMPn3W8O23Jfj43MbOzkrh+JIS+ZduCRKHqTYlJSXs3bWBwFMp\nKBlW8c3ms0z3KZSR1e8zZLk4dVHBcUsiYH8G/saNffFk3Itnzf+ZyPTw0tZSJjuvkm/WZTB9nDEW\nZmqkZZSz9k8YM6XGiReJRIRu2M3r3V+RjtXT1EVPTQtzfRM5JcIRDv1pbWBKZXVNHzAddW101LVZ\nOLAmoiRJ4/vswC/oa+qQU6zBD5M+kKYAbo7Zw8aTOymtLGeC83Dp8qD4Q7TSMWDtie284jgUCwNT\naS1WP5teaKlpAJBekEU/WyfcbHuxLiqIqupqPhq5QG7/a09sZ5b7eLJK8+uNpF16cIu2Rd3k1jUE\nRSp9ZSWVXD2bzbg37KXLatd92Xf2r3fOhtaN1cXduw8I35EKKK5nrM38+T+RkSHvTD1Zz3jqwF2m\nn+5JwI6n719AQEDgZaVBjteCBTVfKG++qSDHREBAoMWiSFp9+bf/XmdLQl2S8HX1NHtSlj/l3mM+\n/bUMU4tOZKUn0bOLBin3xE1s8/LyMDGRfQkPCPhQ5v+qqqp07KhGQsIkfvjhd9aurWksnJeXJ/27\nsdfpSWdM4ohJrr2rV0diw76o97i1tLSYOHk+V6968qgwg1/+XFWrJ1oF2/bnMXmkEd07af7V/6uK\nVoYqGLcZg2u/mjT13dt3MrZDf6mDdSMjlcxHuRho6hF+9TTXM1IZ7zRMpmbKzswKVWVxCmxMciJh\n16L5dvxShcf6xoBJrD62ie8mLJMuM9c3Ya7HRH4K38rnY9+SWS5JDcwoyCEo/hD38h7Sv2NvZrmP\nlzpdAJtOBTPYvg/m+iZydWK1Ge80jJ1nD+M6tD8bTgezfPgbcttsPLWLmW7jCD8US+6MXIyNjRty\nGaUoaqJ8ct9dPEa3V7h9j+Eq7Ny7DZdeNRkq2dnZLF/5Nll59zE1aku3Lj0bXDemCNGjUh4VlAN1\n1zMCHDkSQ3h4FJMm/Qc/P/n1tesZS4srSYrJpMdwo6fuX0BAQOBlpUGphrXJzMxk6dKaL7kff/yR\n3r17M2nSJO7du9ekxgkICLwYJC/ji5f8gO+0N//1TpdIJCIq5GOWTi+W1ilZmKmxdHoxUSGfyEWZ\nam9voKdC4ME8QiKLGOxSTlXJFT6cq0r3TjXnNDExUWb81aspLFjwE1evyipHamoCqHH3rqx9tcd3\n6/ZskRIJta/92PFziAv7osHHDeDSZyCz39nHdzu7Mvm9R3zp95A5E4xx7aGNlqYyvqOMWDzVBE8X\nPSzadJIZm3X/IQ/yM6RpgstGzOP9YXOwNDLjYNIJFg6cIo0SSRyj2NQLZBblEpOcSMT1WFysuteZ\nxtfawBTrVm1kliXcvcznh9bS0ay9NMWwpKJMun6isze2pu14x2smU/uMJr0gk8KSIkBcT/bNkfX4\ndB9A4t2rlFSUPVWQ42LWLT5c+RETls3ik4NreFiQJTPXEPt+9LXpxZy+r7Ly/Y/rvVYikYhNa9ez\ncNIc5k2Yzqa16ykpKcHDbRDfLw9G47Y3yQdtKE2zUNggGMDITJOM7Jobym/DD8z7v4H0mlDAa8vN\n6DWhgND4jSScSK9zfHrmnXrtLC4sl/5dVz2jSCRi0aL/sWrVYgwM6nY2a49PScpt0P4FBAQEXlYa\n7XitXLmSsjLxl9TFixfZuHEjH3zwAfb29nz77bdNbqCAgIDAi6ZGEl4eidS6BJFIxCcfzmTqiHxi\nLxTza0A2A111WTzVhIGuuhhoFbAjJB+X7jW9Affu3Ssz59Kle/Dze5MlS3bLLC/9KztR9YnchNrj\nXVxcnuUQFdKY45YQH3uCTT+MYcnEywT9T5fl81uzcVcusReKZbZ7srYLQN/UiFO3EuQcrLeHTMfa\npK2MQyRhrscElJWUOHrlFMt95tPGsDUZhYob8qYXZNHGsKZ2SlReyv4LxzHTM2Z4Nw+5eiwQKyFW\n/qUI4dS+G7PcxxOTfJ5N0cGcTrmAobY+ju27Mt5pGEcunZQKctS1/679e6GlpcXAoYMRaVRyOuWC\ndK63hkynr424Z1lrA1PyH+YonAfEtXCfT38Pp3RTPu49i0X2r3LzwFmWTHiD01HRUpW+5Uu+YbCH\nj8K6L4DcjFLMTcTRsOzsbI7GbWTSEnupo2ZkpsXUZT1Iv13ExWh55ys3oxQLsw512gmgqqQp/VtR\nPSPA66//SOfOnZg+3afeuWqPv3+rsEH7FxAQEHhZabTjFRcXx8qVKwE4fPgwXl5eTJgwgaVLl3Lu\n3LkmN1BAQEDgRZOTmVy/1HqmODIVG3OcX1cNxVT9JAZ6KkTFF7N0rplMtOj/5puTX1iFu5M2JkZ/\nNSLetYvbt29L59TUVKVNm28YMKCdzL6ysqqAAuzta9LcUlNTCQ4WC26YmJjg5eXVVIfd4OOWUFpa\nypljK+UjZHPNCD/9iJLSatIzK+sUaFFSUqqzb9ak3t4cuXRSbnlrA1Myi3JZ6OkLwPBuHnUKYmw9\nvRen9jV1TgcuRGCsY8hyn/lykbQzKRcoqSgjvSCLO9kPpGO01DR4xdGL2e7j6WfTCzO9VtJxeaIC\nhnfzYMfZEIX735saxbsfi9McT0dFU14okgpwvOLoJZO+mF6QhWHrVgrnEYlEHFkXzNt9ZB3UuR4T\nySp6wFdfvc/vm36WRiQnj5/JxaNVCudKCq1i4ripAHz+zfsMm2alcDufGXaEBqRQXio7T1JoFb4T\nZikcI6G8vCbipaie8dChU0RFxbBt2zK5dU9Se3x5aVWD9i8gICDwstJox6uiogIDA7Gk7pkzZxgw\nYAAAOjo6T+1ILyAgINASEEvCVyhcJ5Far51e2N5Cna17c+tsGvzWNBOOnCxi3mviF+uKigrmzp1L\ndbU4sjJ+fBfU1S8ye3aNgmxq6j0uXzaja9cNvP++WOGvurqaefPmUVEhtm3evHloaGjQVDTkuEHs\nCOwM8mPT2iUYaNyjpLRabvuZrxiz5EdTTqS+weLlx2RquyQUZNbdg0vi2DxJekEWD2sJVWira9LX\npidrT2yXRp4eFmTx5SE/BjyhUph474qMoycqL2VPYhibooPR1dBm//nj7Ek8RlG54u+y2sqGEnl5\nbXVNch4V8GtEgHT/GYXZ/HzcH/X2BmhpaUlFRL4evaROJ3HTmd18/O1KxfvdvpNXrAfILItLS+Tr\n+ysZ/KUWU360pNouVKr6J6n7+n/2zjusqftt4x9ARtgbAoIMFyoynCDuvepArXtbbbV22Nr+amtt\nq/a1dletihu3glg3iqLiHrhxoYgoewQhgKz3jzSRmARBsYqez3Vxac78fs8h4Ty5n+d+Dgfnkpki\nk00zU/I5HJzL8J7TFQFwuuSBxpRESztDjM31OBJ2T+P+mii7vmw9IkBubi4ffvgLc+dOwdJS/ful\nLGX3lyRTofO/zUilUlYEL2LOL1+wInhRueY7AgIC/z2VDrycnJyIiori7Nmz3Lx5U2Ehf+nSJays\n1H9bJyAgIFCdKNdm/9+UubJpeX06mnHmslSjWuRor8eBk1qM7meJk1i2TUREBJMnT6akpIQhQ7rS\nrl0TmjX7iEmT/mTy5D/o0mUJNjZ3Wbq0ExYW5pSUlDB58mQiIiIAcHZ25ssvv6yS+UqlUjYE/0Vi\nwnUWbiotd95yla9L3eUs/zafPh3NWLA2TSW10MFOlwYNG5dbM2hTs/w0QXnfrLLsiI+i95gBSvuV\nTQlccGgtS49spoNHC07fvUimNJt5e4NIkqSiq1NDEbCdj7+qZEHftWEA1xJvo6tdgweZSfy4ZwlJ\nklSkj/NZcyKMT7f8H8Vl3BRDo8PxcarPrB0LsDa2YGiL3oqUxOOxF5jQehBG+rJ5y01ENAWJ3+74\nCy0nI1b/GcTaZatVHpZTE5KUAlTp43x25m+l48e2SimCbUcYE7xzHouX/87hE3vxcu2C9q3OxO50\nQz+uO7/OCKGVXzvFcazMHMtJSZRibKZH/kOxxv010aBBA8X/n65nnDDhNxo08GD48G7PPM7T+w/u\nP7ZC539beZEWAAICAv8NlW6gPHHiRCZOnEhJSQkjRozAxsYGiUTC5MmTGT58+MsYo4CAgMB/ijqb\nfbnVujxlLj0lFnELWRBlKNKmdi39cpsGt+k2lXMpurzTO5K/l4VRUlLC4sWLuXXrFkFBQaxY8Rmh\noRFs23aN4mJtRo+uy8cfB2JkZMTdu3eZMGGCIujS0dFhxYoVmJqavvBcn3Zv3B2Zxxc/Z/PRCHMc\n7JTnXVpaqlD5QDm1cP6yFBrXEyls5csqZJroP3Qg34/8jI9aqDYXXndqB9LHebR080JsZkNSdiph\ncUfRrWnKuahTPCi4xtQOTzzU5SmBf0Sspr7YjZjEO2TkShgfMAATA2Pm7FlMbr5U0Wz55J2LjG0V\nyNFbZ7mQsJ1byXHkFxZw8PpJWtX25WFWCn8eDEZHW4cp7Ycx0q8vydlpBB3dxL20hzwqyMVY35Av\nuk0gO+8RG07vpKWbF/18ZKmfiZI0bFzskUqlHN4bwb0iK4Ulvoe4NnuvHCVTKiG3QIqugS7janbD\nzsia5Htp/DTxa7qM749fm1bAvwHqvScq347YffiOMVF7Tb266XD20Bo6DXYnM+UqF/cVM6zHdAL8\nVRXHmV/8xJTvuzL080Yq6/YGx9KmvyvWmT0q7SBYtu4wLCyMQYMGATIHzT17LmJgoI+Dw5N0weJi\nWf3j7t1JODiMoW3bWmzYMEuxvxx/f/9KjeNt4kVbAAgICPw3aJWWlqr/erMckpOTyc3Nxc1N9ke1\ntLSUnTt30rt37yof4H+JVColJiYGFxcXQb2rZsjvnYeHB4aGhs/eQeC14HW/bwqr9RSZ1XrZflYb\ngv+inetiRaAlzSvhr+BUvnjPTuU489cYM2XGfsW+69atY9SoURQXyxQUXV1dAgMD6du3Lz4+PlhY\nWJCZmUl0dDRhYWGEhIQo0gt1dHRYs2YNQ4cqBytSqZTN6//m9PFd6Opq49uiB4OGvP/MvmML53b+\nN5AqM+/8Eqb+mE9D727YOdRRzPvpOZclMaWQyNM5DOlloXbOms7/2cBJWGFMoG8XTAyM2XpuD6fu\nXkaS94jWtZuQkJWM9LGUR4V5iO3s+aDZIHZdPoy3U31O3rmoZDf/c/gKbE2sGOnXR7Es5Hw4Ld28\nyC98zN4rRzE3NMHezJZrD28RdvEAGbmq6YxyDGroM6H1QKa0H46JgZFi+Q+7FvFZl3FKNVqAom+X\nSFefOfuW8M4nwzi2IZx+rm1UxuPr3BDp43yWRW1RCiDlLL28jelLZiMSiUhLS2PWux8zo9skAP66\ntJTGX2tOIdu18ibmNgbkZD3G2FyP/BRz/pwVptQ/Tf6+W7ZqIeHnltFjVG0s7QzJSJayNzgWx9om\n8MiGX2eEVPqBPT8/H3uxPZIsCbq6uty8eRMXFxdKS0s5d+684vdezk8//UNo6Gz69PmW//2vJ2Kx\nGGdnJ+7evavo42VtbU1CQgLFxcVsDFlFYso9xLa1GDJgzFsVUGj6zFwRvIgCl91qU0czU/LRj+su\nWPC/Ql73v3UCmklPTycuLq7K7l2lFS8AOzvlBwstLa1qH3QJCAgIPM3TPa/kKXnpKbGYWDizcocJ\nX42T1dAYirRp18KY+ctSGNbbAgc7XRWVTM6wYcOws7Nj7Nix3L9/n8LCQjZu3MjGjRvLHY+TkxMr\nV66kY8eOSstPHT/IplUfYW2cxjdjZQ2LE1OW89PXwXQL/EVt3zEo62KoHEiJDLT5frIekXfrKM2/\nrMr3NGJbXdKzitXOWSqVErp+C6kJSdjUtCdw2CBEIhGh67fwnm9/TEUmBB3dTE6BlHGtAhnp14/k\n7DQ2nd1DP59OOJrbEXI+nJRH6ZiKTLAwNMPR3I4xrQIVypGRniHOlmI+LBPElG1kbCYyYXL7oey6\nHMnMf35H+jhf7TzKkl9UwF+H1hISHc5vA/9H6zpNAZgQMJC9V44q1C05sr5du3mUL8XHoT47/trA\nVx0nqB2Ph7g2+65GaTQX6VOrNSHrNjN8/Cj2hu2iZS0vft2/kqHNe2Gra0dmSozah+zzkQ/JkTzG\nv6cTFrYiMlPyOLwtjjnzv2L2zN9Utp/6wefU3luX72d/ioFJCcZmurQNdOXOCZ3nrqfKycnBSqyP\nJOtJPWN4eDja2to0bdpEZXtLy7MAmJnZ0aJFc0B9PeOZc8dZt/snGnfVwb25iMyUq3w6Z4dGRe9t\nIjHlHu7NNbcQiD0tWPALCLwOVLrG68qVKwwcOBBvb288PDxUfgQEBATeROS1Te1cFzOldyRd6i6n\nsKiAT3+WOfcBOIv1KdSqxZrITizY0b5cY4lOnTpx5coVPvvsM4wMy/8OzNramv/9739cuXJFJeiS\nSqUc2P4VYvN0vppkp+Qu+O3EUiJ3fq2xwL6yLoblmW88SCrkcnwdft7gS0lpN25ejScvL48TR44x\nf9I3NLpnxmCjVjS6Z8ZPE7/mxJFjitql0tJSamjr8FX3iUqufVM7jODorbMcvnkGA119JHk5bD23\nT+FkWNZxUK+GLoM0BDH9fTpz6OYpjt0+z7c7FiiCLl1dXYYMGcKmTZu4efMmqamp3Lx5k02bNjFk\nyBB0dWXX5mFWCkOWfcrUjXPYFn0AM0NTtcYfdqbWXH0YS1FJMbGp8Yxr1k/teOSNlY8lXCjXXCQ1\nIQmQ1Xh19PDj/XZDOXLrLBdibrN3ieqDdEFeETfOpvPux42Uar/6TvTgRuIRjb8H7dp0Zszgj6hp\n3RATamOSVPF6rqeJOn6ID7/rxeRfvbESy8ZQtp6xLFu2RDJmzAJOnJC9PnNGlzFjFrB2bbhKPePU\nqVMVqXRP17Wt2z3/rTeRENvWKreFgGDBLyDwelBpxWvmzJkYGBgwdepUQS4VEBB4KyjrYFi2tunb\niaXMW2VM+I1AHp1KwMrWjU9mja+wSmBqasr8+fN5p2dHVv79KRZGacQ/fExWdjHJmfq08O9J3/6D\n6NSpk0b3wu0hy7EyTKBPR/UOcSO6SwjbukxJuZIjC6T2a6xLe7pGq0/gOBbO3aiSmgiwLEwfm8ee\nDHDqIEuru5fG/02YQWpmGt+0e0+xnZ2pNe959mPpslCcW3qQnJjG8dgLBPp2UTnm+firaGlp07Zu\nM0Wq3t+HN3A9KZaWbl4sPLSOQN8u2JvZ8CArqdxGyo+LCpm6aQ4l//bo6tixI8uWLcPFxYX09Azm\nz9/KjRtZGBmJ8PcXs3r1aubOncv48eOJiIigpLSUbRf208nDj6CjmwAtlfMkSdJo6eZNP59OfLJ5\nbrlB1ZmM6/Qc3JfkxDS12yX9WyMGyjVeg5p2Z1DT7px+GM3O30PwHWKMhZ2IjOQ8Nv9xhXc/Vq3X\nAmg/RMyGrStV0s2ijh9SqEi9WskUsov79nEu2ktJRZJKpc9M8ZPXGfWZImuLMHFOU/5vQhQlxaVK\n9Yyurq6yOSZlIZFoUbduKXXrLgTg4UMp3333E7dvK9cz7t4fSuOuOmrn1rirjtq5vU0MDhzNtLk7\naKuatcrl8GJ+nSFY8AsIvA5UWvG6c+cOQUFBjB07lsGDB6v8CAgICLxplNdYeGSPbPT09Jgy7bdy\nHfzKo3W7bixcdY6m7b+hbecxjH1/LqfO3ydo+Wp69uxZrmV8ekosRcVoVK4c7HRVlCs5FXFvfJoi\nvSb877ccHibLlK+HKUXMW2VI6p3aTPYZpKRYTfLqj1mJSG0j5D61WlNSWsL2e7JUwaeDD+njfE7e\nucjUDiOUjjmr94ecvHMRD3FtrI0tCb92jBXHQjh0/ZRGh8SbyXGcjbuiCLref/99wsPDcXFx4dix\ni3h5DScmJglvbytAyhdfaNGq1RwMDAwJDw9n0iRZbVVxSTHf71rIGP9AdLS0VeZV1m7ex8lD43iS\nJGlYWFvy7uihbL+n2qsM4J/4owQOk5lS9B86UGW75g4+/M/pGyLnFnEjzBntW53R1TYqxx5eRGKK\nskpW1pChPBWpom55G0NWKQVHnv52vP9/zdDWkQWpERER1KtXT6Eydu3agCVLBvF//9eZd9+1Rl8/\nikOHvlYKutasWUPHjh1JTLmncW4WtgYqc3vbqGgLAQEBgVdLpRUvR0dHnsOPQ0BAQOCVIpVK2R6y\nnPSUWKxs3ZWMMp5F+bVNNUg/pT6wqQxP15NVFCtbdyQ5aHRUfJBUqNFdsCLujXLk7oeju2VhbmrI\n6m0ZnLyshXuD3jjW9KGrjo3ac8gbIT9dD2Vnak126g26jO/Pwpk/k5ytrPzsuxqlVgUDWerg/L3L\nyHksxc/Nh26NWqOrrUvQ0S183fN9le2/CvuVrLxsQKZ0LViwAG1t2feOM2fup6SkLiNGtGHAgHYA\ndOr0OxERM/j00wWsX/8JCxcu5NatW0RERPAwK4UFh9Yyxr8/W87uYaRfX5Ikqaw/vZP29VooDDcG\nNOnOvL1BfPeO6j3ddHYXfu+0xtDQkC7j+7N0WSh9arVWqHrb7x2l64RAxfUvb7v3p00n4d59Uu8n\nYVHDhcyUPLUBirp0s63b1z1TRRocOLrCbnnq6owCejtjZqXPkhlnSU/Me+56Rlkq3dUKz+1tJMC/\nPU18WrJh60piT8uUyV9nqFcm32aDEgGBV0mlFa9PP/2UH3/8kZycnJcxHgEBAYEq5+n6rHaui1kw\npxOnjh+s0P4VbSz8KugTOI50aU3W/pOpdv3avWZqlSs5Lfw7MGXGfiLvTtRYl1Y21VJsq4vIQJtJ\nQ6xZNdcKvaILpD5IrnQj5CRJGjY1Zal0jrb2rDgWorRenQomx97MBktjM34K/Bx/d29WHgvB3daJ\ntJwMZu9aRJIk9d9zyBopX064CchqupYtW6YIugDS07VJTPyNsLAn/aJsbGoAuqSkyAJZbW1tgoKC\nFDVf607vwMLIjFsp91hxLIQTdy6io61DfbG74hiSvEdYGZvz58FgEsuM58+DwdzPSsatjmxbr6Y+\nOLWsz8KYUH44u5JocRrTl8ymZWtl63S/Nq2YvmQ2V2pJ2Jh7jCu1JLQd0ZPDwbsU9XOf1BpJeFCC\n2mt2ObyYIQOU082S0+KfqSI9rWKVRR6cySlbZ1SQV8SxnfHsW3ub7IwCPlvkj5uHLebmqr3ZyqKp\nnnFw4Ggu7StWu4+6ub2tiEQixo74gBnT5jF2xAcqAZXQ60tA4NVSacVr4cKFJCQksG3bNiwsLNDS\nUs5zj4qKqrLBCQgI/De8iBr0uqOpPuvzkbnMXzOTxj5+z5xrebUMiuGEAAAgAElEQVRN6/aZM2WG\n5sDmZWNoaEinPnPZtOpj5i5OZkx/mavhw+RCgsL06D5gzjPn9yy1TZP7IcCIHtn8suEmydqNMDEw\nZt/VKDKlEkXPqixpttpGyP/EH2XKJ1+x4JO5fNxsGOfjr7Iocr3CHr6GtraKCiYnUZJKRo6EvMIC\nJafAd5v14NjtaGbvWkzuYynveHXEw8GdRwWy+zZgwABcXFyUjvXll17888/vzJoVqFiWmloMFCMW\nPwm2XV1dCQwMZOPGjWTkSth+IQJPx7oKQ4/k7DQlZW/z2d2IzWzJyntE0JHNpOZkUEOnBoOadmN8\nwEBmzV3Ark1hJMUmMLnFu3Rv8Z5MxTp5lAuNzit6eD19n4aPHyVz11y5lm2/ruHLDk9+91ysHBld\nMI5Vs5fRZYITFnYiMlPyubSvWG26mZ21M5kpN8pVkSrjlievM3JsnE7M2TQCejsrnBX3rI5lwW9B\ndGjXlQMHDnDmzBmuXr1KXl4eIpGIhg0b0qxZM431jPJUunXB82ncVQcLW4Ny5yagitDrS0Dg1VPp\nwKtDB/W2xAICAtWTpxvoJqbsZ8GcjbTp8YNGG/LqRHlBw/BuWRqNJ8pSmZS8V0EL/w409jnF5vWL\n+GHFbnR1tfBt0YPps8vv41VRyku1dLCtQU1nM5YeCVX045Knwq08FsLDgnTEtnaKIKpsKt2ebTvp\nU0tWE+Xr3FCpsfDjwscsObGFmV1VUwe3Re9nlH9fVh4LUfTE6u/TmRN3LjLAtws/719JXmE+/u7e\nrDm5XbFf3759VY41eHBHBg9+oqxcuBDDpUs1cXNbwPffD1Datm/fvooUuS3n9jLAt5tinVzZS5Kk\nsvjIRkwNjJVMQTad3QPIUijP37vGtICRsnXiNLae20dxaQnG+obYGJqxa/EmvJv5qr13J44cI3xZ\nKAY5Woxpqjqf5g4+2Ol/xYzpP9OmXxucHNzVppsBDOgzjGlzQ+k+UXXdqbBsFs8Zw4atKyuc4mdo\naEhgh6ks3Pg570574nJsYSti6OeN+Cd4Me3adKZnz5707NlT5XjPoqKpdALqqYh6+TYblAgI/BdU\nOvCaMmXKyxiHgIDAK6Aq1KDXnaqqz5IFN36yhsqnZA2Vp8z4b5TBiiiSIpGIUeOmMWrctCo/f3nu\nhw+Si7C0ccVUdJsPWjxp6ixXov44tZ5PF8xid+gODiXcwKaWPdO/kjUGPhFxFDvTJ+l5cnt4OZ/u\n/5XFl0Lp56LcgNjHuQHn42Mw0NVn3emduFo7YSoyIezCAc7HX8XXyYObyfdYFLmes/euKo7n4+Oj\ncY5ffrmU+PgCTpy4i6urEX/99S6urk5K2zy9f+5jqeL/DyWpHLp+EiM9Q2yMLZncfpjStZjaYQRz\ndi/GxMBYZd3k9sP482AwQ5r3IjvvEZvO7uGX7+fx9Y+zlM4nlUoJXxbK8Hrd+XHPEkb6qQZeALWs\nHGlp2QR3q8YMHzFK45wBpDmP2bH8Bs07O3L7UgZpiVKS7+VgYWILVN4tL/7BXbqMcFF7rqp4uJen\n0glUHqHXl4DAq+e5GiifOHGC7du38/DhQ9asWUNJSQl79+6lR48eVT0+AQGBl0hVqEGvO5W1TC+P\n5zXAeBFeB0WyvFTLtXtMsalpwmAP9UYYgz26sDt0B8PHqwYAZW3SnyZJkoa3sRuPih/z6+VNOD02\nw9HcHh9nD6Ljrykpaz/uXoKNiSU/BX6mWBZ/eAPFJSUY6z950LSwUG+5D2BsrIedXSF16uhy5UoO\nK1YcxMennqKu6+n9tbS0lFIow6L3Y25kSkFRAQOadFV7jrGtAllwcC0rjoUoUjHlZhxlTUimdhjB\n/x1cpkjDkxO6fgvuNexZdTyUOra1NKZiJknScDS3JzUhSclIwcrcASglOe0+FOtjYWFBhxFWJN3T\nJzI0ji5D3dU2Xa5Mit+LPtwLxg8vD8GgREDg1VNpc43du3czYcIEsrKyiI6WFSMnJSUxc+ZMtmzZ\nUuUDFBAQeHlUtoFudeR5LNNfF542tYAniuSR3TOfu2msVCplQ/BfLPjlYzYE//XM4zxJtTRWNIt+\nmFLE90t18OvyDZKUjAo1An4adTbpckKjwxnYtDuTfQZRnJHHlPbD6dowgOj4GD5oN1RxPhMDY1ys\nHfm86zilZbYmVvzQ5yPMRCaKY2ZmqjcgAfj669H89ttkwsPn4etrz5Ilgxk16jelbcrunyRJpVuj\n1iRKUlkUuR4/N2+8HOsTff+axmthJjIhv0hm9f0oP4elRzZxPv6q4jqVNSEZ3bQPIes2K+3/4G48\nN5Lv8kG7oQxo0o2Q8+Ear52PkweS4iwlI4XSuvuJvLoMHddobFtf4uilDSTGPeL2pQy1TZev3j9I\nXl4eAf7t+XVGCPpx3Ynd6YZ+nOYGyy/SyFcwfngxpFIpK4IXMeeXL1gRvEjlfS0YlAgIvHoqHXgt\nXryY+fPns3jxYoWxhoODA3/88QcrVqyo8gEKCAi8PF5nt76qQl3QkJhSxPw1xq9FfVZ5lNc/TK5I\nVpbndXh82v1w/82xdOz3J02bt5UpV+X0rJK7Fz6Nwib98jaSsmXOf8nZaYpARq4GNbauTXJ2mlqL\n+Wctq2Pnolgu/7KwLFKplIIC5X5c7dvXBHTYu7cOt28/+fKh7P6lpfDRxh/4df8qrIwsqC92R1tb\nGzdrJ7XX4nz8VZZFbWF61wmMbRVIm7rNiM9MZNnRLWw+u4e4tAdKCpq9qY1KwJqUnKSYl6GeAS3d\nvFgUuV5xvqQyQeDO+8dILI5W6dHVd6IHMWfTMDLVI/Bjd46E3SOgt7PKeAE6j6jJmg1BgEztHRw4\nWmG4sWHrSrUB+/M+3Fe0p5iAeioStAq9vgQEXj2VDrzi4+Pp0kX2wV/W0dDPz4+EBPU2tgICAq8n\n1VkNqgwVsUx/HalqRfJFFTR5quWUab8xcPAkDAwMgPKVq7KNgNUht0lfFLONFcdCOB57gTGtAvFx\nbqDYZkCTbqw8G6bWYv5Zy7xr1lcsDwsLU9ouIuI0DRsuwcfnR5KSkhXLXV1tgHQyMxtz5sx1tfs3\nqdUA0KafTycKigqYEfYbp+9eRq+GLvP2LmNb9AFFg+Wnm0Gfj7/K7suHmd5lHIuGzaJt3WasO70D\ne7Mn81AXsDrYOSjN1de5IWNaBXI89gIrjoXwe8Qaenq25YzkBjXqGeDdXX01QUBvZ84ceACA2MW4\nnKbLhoTsWE1eXl6F1ajnfbivjG398/AsNag6U5mgtTLqpYCAQNVT6cDLwsKC9PR0leV3797FyMio\nSgYlICDw31Cd1aDKUjZoGDLiw2oxtxdRJNWlE74MBQ2UlSu5+pKcncbSy9uUGgFrQiQS0bZbR3p6\ntqWfTyeF0iUnOy8HG28XYrLiVNQkC0Ozcpe1rtMUSyOZkrR161bi4uIU2+3bd464uA+5ebMb167d\nViy/eTMJsMXI6CaNG7sCsr9xISGyXmPmhqY0q9WYgqICgo5u5kbSXfp4daCBgzt9vTvx66Av8Xf3\nJuioLJVwy7k9CqVKHoSVTZe0M7VmRo9JRMdfUwRr6gJWsWtNlbnKDUm6N2qDnqMJt2vnM33JbPSM\ntcrp0SUiJ+sxANYORuWkBubh7F3Kh7P6ELR1VoXVqOd5uE9MuffMnmLPy5uewljZoPVZvb4EBARe\nHpUOvPz9/fnqq6+4desWAFlZWURFRfHxxx/Tvv3r/e2xgICAKtVVDXobeF5FUlM64bVLR15aTZ+6\nBr/qGgFr4lmq2bSZXzBz6TwWHF6vtK5rwwCVWqeyywx09RnWvDcAhYWFjB8/npKSEgACA1thajqL\nzp1X0r79k3EeP54CGOLnd5aGDT0oKSlhwoQJFBbKgmAXKwfScjP4KfBzVo7+kQltBnH45hmFogVy\nJ8OR7L58hH0xUYrl6lIj5QT6dmHL2T0aA9byrtGO+Cj+DF7C8PGjEIlEz6i1ysPYXA8Ad09L9gbf\nVrvdsZ3xtOnrgshWQst+Jmq30aRGVfbh/kVqw8rjbUhhfJlBq4CAQNVS6cDriy++ID8/n969e1NQ\nUICfnx/jx4/HwcGBL7/88mWMUUBA4CVTHdWgt4HnUSTLSydMSrhYYQWtsgYc8KTB7yezvlAEAJqQ\nSqWsXbaa32bNY+2y1WhpaZWrmq1fsYY/P/iBdrWbsShyPUkSWU1Ydt4jYpLu8N2OBUrLbiXHMWvH\nXyRnpzGl/XDs/w18IiIimDx5MiUlJbRo0ZhPP63LhQsZ9O8/n08+WUBg4DwOHXIgIGAu69e/T0lJ\nCZMnTyYiIgIAUwNjWtduykcdRymCqej4GCa2eVftPMcHDEBXV1cxJ3WpkXLsTK25o52mMWCtjLJY\nXq3VsZ3xNOvkCEBMZCk6RWbsWH6DjGSZPX5mSh47lt/Ao5kNegY65GQ9fukP9i/L+OFlpzC+Drys\noFVAQKDqqbSdvKmpKWvXruX69evcuXMHAwMDXF1dcXV1fRnjExAQEHirqWz/sPJaBHw5rgYLN5Uy\nW40j/rp95kyZIVPQXraFfWT4Qf5ZsJ6RXr2wM3Un+V4aP038mi7j+zN9yWxC1m1W6vmVm5vL2u/+\nZkbXiQD41/ZVNFq+mHCDuna1GB8wSLHMwtCMuf2nMWfXIn7atwxX65oMbNKdhZFrKSktZfHixdy6\ndYugoCC+/XYkQ4a0ZtGiPTx4UIyRkSF//WXMiBHfEB8fz5AhgxVBl7aWFv19OjO2VaDSfMoLpuzN\nbLA2sGDx4Y1823uKIg1S3faJklQMzY3KDVj92rTCu5mvyjUSiURIpVJC128hNSEJm5r2DOj0MVuD\n/1DYwGckSzkSdo9GfnbkSh5zbFMRI3t/SWlpKau3/x9b/rqGS31zjM316DqsNnoGsoDF2FyPzJS8\nl2pDLq8Nq6htfUV5G3pXVbbXmoCAwKvjufp4AdSvX5/69es/e0MBAQEBgRdCU/8wdY2Vy2sY7e6s\nR7FubeavSZIFVbY1SEwpYu1ec4WCVtmm2k8/7AcOG1TuQ/Kh8AhCflqlCKJApvS859mPpctC8W7m\nq9Lz66sPP2O835Ngp2yj5TUnwujaMECl+TLAhx1GEH7tOBcSYmgork0rd1+iYs9TWlpKREQE9erV\nIzAwkL59+/LBB52wsLAgMzOT6Ohohg8fTkhIiCK9EKCvd2fScrJUgqZnBVMBtZtgamDE7F2LGNbi\nHULOh/NBu6Eq226L3o+9t4PGa6eY/7/KYllOHDlG+LJQ+tRqrQhmtx8J590Rn3En7jqxp+9hbeFI\nu4YlJN+5T8otfeZOm4aVlRUATXxa8vGX4/HuIlEJsJp2dGDPmlv0neihMpaqfLAP8G9PE5+WbNi6\nktjTsj5ev854sT5eb0PvqpcVtAoICFQ9lQ68zp49y48//khsbKyKBS9ATExMlQxMQEBAQEAzmlSp\nIr0mJKYUamwY3dinLX0HjNeooFWmqfaVC5f557d19HNto6Jc+bVppbK/VCplxY8LmRYwUu2c+tRq\nTci6zUpBhVQq5e7V29jVG6J2n6KS4nJT964+vMX0LrIeXwkZSQxt3psfdi/iYVYKhYWFbNy4kY0b\nN6rdX3EcEys+7DCCnAIpyZJUlSCra8MAVh0P1RhMjWkViEhXH//avny9/XfMRSbM2xvEKL++2JvZ\nkChJZfWJbZQUF5N0PZdPxk/G0d4RexfHZway8msUviyU9zz7Kc39Pc9+LA3exvQls1WC5ZiYGKVl\nIpGIgX2GszD4c96dphxg6YtqUJxjyqHVj/DurvtSH+zltWFVxduiBr2MoFVAQKDqqXTg9c033+Dk\n5ERg4LOdqgQEBAReFHWqzpv02fM88ytPlZq36iwrd5jw1bh8lf3k6YSaFDSgXMVMbFuD9FN3FGO4\nvu8MU5s9CYieVq6enkfo+i04i2zLDZQOJdxQvJarOH5iT42KUg1tHY3rkiRp6OrUUKyzN7Ohj3dH\nOtRvSeDiqSRkJZElzVY7FgBLIzNcLB3xsHfH26k+HuLabD27T5E2KEfeU+v7nQt5r/Ug7M1sSJKk\nEhq9X6kfmUhXn+ldxnE89gLdGrVWpEbeTI7j/baDWRa1FYtHBgxr0Bk7U+tnBrJlr2ufWq3VrlMX\nzKpDKpUScvBPmnSyZcfyGwT0dsbCVkRmSh7hwXF8OOxX/Jq3VjzYW5qJ8XbTJvL4Hm7cvsaQAS/+\nkC+VStkYsorEFFngUBXHfJvUoKoOWgUEBKoenVmzZs2qzA6//PILYWFheHt74+HhofJTnSksLCQt\nLQ1zc3MMDQ1f9XAEKoH83tnY2KCrq/6hUeD141n37dTxg2xdMYZ3mkXR0fc+1nqnWbZyMzUMXKnp\nVP3rSg8f3M1P3/ZBJy8CscktWtS5wOo1W545v60bF/NOsyhMjFRNA9wd8rj4IICT59NxE0sxMdIm\nMaWIxSGmtO35Ay6udcodU2zsLaz1Tqs99sPkIlIKO+Pp1YKNq9bRWd8TY33Vz8qaIhsOx5+nsa+3\n0vKIf/ZhkWuApZGp2v0SJalk2Zdy9eIV9oTs4HRYJFObDaGOnQsbTu+kmYunyj6RN09xPekuzV0b\nq6xbczIMV+uaWBtbYKxvSHxGIpZGplgamXMzOY7143+miXNDXK2dsDIyx9lSTANxbXo1bo+xvhE7\npyyma8MAou6cJ1mSRgs3L5rUasjt5Dh2XjpEPXtXjA2MSJKksv70TlIfZYCWFquPbwMtbQY27YaT\npVhpTMb6hpy4E01zF088xG6IzWwpBRrXrE9sajxTO45UXBtjfUOa2Hmwee82WnRro/GzLeKffbQ0\nUZ/6b6xvyOn0GPzaBSiWqXvfBW8MwrppLI7uprg2sODi0SRiTqciSS/At6OYvAfWNG/ij49XM7Sp\nwYEza7BtfhcHnxxydGNYs3Ij5gaOOD/n+zLq+CF+XvER1k1jq+yYcpydXOno15+Y4znER2tjXtiU\nzyb9iNsz3gsvA6lUSvDGIHYf2Mrt2FvUr9uoUn+zhL911RPhvlVf8vLyyMrKqrJ7V2nFy8fHh/j4\neNzd3V/45AICVYFUKmXLxsXE3jzPlbq+DBry/hv1LebbSmVrjaobhw/tZs+m9/h+shliWzsSUwpZ\n+08mbZoVcWR3+fN7liplYqTDuM/3V9iQoyx9AsexcO7Gf6+7MmUNONIfpGBnrv7LtqeVKzk2Ne1x\nzzfQWOO08mwYZpZmDHDvQPbdYrp69QKeKEqLItcT6NsFO1NrkiSpbD63hzZ1mpGRK2H2rkWMCxiI\n+F+1aXlUCC3dvPBz9+H3iNV81X2iUkpgI4e6ZEmz6eThTycPZQfBREkqR2+dRb+GHnam1rhaOWJi\nYMSmM7sxE5mgraNDZl4OiyI3EJeegKGeIbWsHJg/8AtEuvqUlsKj/BxWH99GSnY69uY22Bhb0q1R\nayTSR1gYminOFRodzphWgey9clSjzfyzVCubmvYk39Os+tm4PGnELJVKWbMhiOu3LlK/jhejhr6H\nSCRSMqHQM9ChVS9npePEXryn2F9uzy5HZs8O64Ln08SnZaXfly/jmE/zOqhBUccPsW73TzTuqoN7\ncxGZKVf5dM4OhvWYToC/0L5DQOBtoNKKV8uWLZk+fTpJSUkkJCRw48YNrl+/rvipzoYbguJV/ZAr\nIv1anOCdgHTsDM6+UYrIm0553wKWp+q4iaXsPa6Np1eL/2qoVYpUKmX1XwOY+7GJYn4mRjq08jVi\nw84sAjuVEnFKR+P8KqJK+TRphadXC5r7d8PTq0WFv6nT1dWlhoErG7YeK1cxu3HjBqbpWmqVqyRJ\nGrnOuiqKV+36dQnesJbm4oZsiz6As6UYY31DkrPT+CMymEKdIqb7j1aoQq3rNFXsKzazpZFjXQ7d\nOM2JO9EsOxdGfPpDbjy8w4k7F6hv70bqowwO3TjFritH6NTAj6sPb7H13D5uJN4hLTcLdxsnzETG\nbDm3jw71W7D57B783H1Uxr/0yCaGt+yDrk4NkiRpSPJykD7O50zcZXycPAj07YKPU33upidga2JF\nUxdPCooK2H0pEm1tbSKuH+dx0WMeZqcysc0gOtb3w9LIlPWnd3LwxgnGtAokIzeLNSfC8HPzxslS\nrDLfsqhTrZ6+rivWraKJnWogvP7WPiZ89SG6urocOLiHj78dSnLBOUR2WZjVe8C64E2YGzjy+HEh\nOboxiIxUf08ykvOxKGqKj1czhTKmbjszcQkxx3Pw8WqmdpyaeBnHfN2QSqX8vOIj2o4wVsxTZKSL\ni5ceO0Ii6ejXv0LvUUE5qZ4I96368soVr+XLlxMdHU10dLTKOi0tLfr27fvCgxIQqAhvuiLytlPR\nWqPqyPaQ5Ux+V0vtuuHvWBB5Oof0Us3zq6gq9bxUxML+nUH9+OWDb5VqvOT8E3+U6TNmK16XdT7U\ncTThdMINenq25XjsBR5kJRGfl4JbEw/6iZ48XKtzCpQ7FyZJ0qjVy5u2XTvw48gv+GvIN0gf57Pv\nahSGeiIC3JtwIf46WlpauNs4oa+ji0ENPRYcWkdhcRENHepwJu4yd9Mf8P3OhUxoPUihlG06u5uc\nglxiEm/j69yQ0OhwejRqy5FbZ+jcoBU3ku/iX9v33wbJI5i96298nT3o59OJ5Ow0lhzZRC/P9nT0\n8CM5O42Q8+G0dPPC17khH7QbytyIIP7v3BrcS20Uphua5ivnadXqaRT9vRSuhtYkZ6ex/d5RRX+v\nA4f2snDj57zzgYuiditqRzweTa1Zt3s+sz8J5uvfnm1C8TLs2d8Gy/eK9BN71YqcgIDAy6fSgdfW\nrVuZN28eXbt2xcDA4GWMSUCgQlTGfU2g+mFl605iyn6N7nxlm/1WN8oPKnWJf1iIs5fm+T1prDxT\noy38i1KeAYd8DPW7NmNxZCj9XNqofdgHNTbnxWlsLT7IAa0YjOqK8Kjpx9fDBrF43p/YGVXMKVAe\n2IWs28x7AYM4H3+Vk3cuKtIQk7PTuJ/5kOy8XOIzHuLpWJeejdsp1oWcD6ehmxf+7j4sPbKJk3cu\nkimVYKRniL2pLSYGxgSf/IeD10/RsX5Ldl85TGFxEQObdic77xF7rxxVWNdPaD2Q47EXqGXliJ2p\nNTN7TWZR5HpFcPZBu6EsilyPh7g2Il19xjXrx3lxKvdPXlcEXfL5Bh3dhLOlo6IXWbdGrRHp6qsE\nsup4Vn+v5aGzlNwKLWxF9B5Xjx3Lb9C8S022795EYIep/DLrK8wdi7EWi6jtZcX1SJRMKF6GPfvb\nYPn+NgSXAgICz0a7sjsYGhrSs2dPIegSeOWkp8SqfSiHfxWRlOqriAjIVJ21e83Vrlu3z5y+A15M\n1XmVyILKQrXrHiYXcvuB8TPn18K/A1Nm7Cfy7kQW7GhP5N2JTJmxn+Z+/12tSCNvT6b+PoMrtSRs\nzD3GlVoSpi+ZTcvWspqpsjbnciXHztSayT6DKH7wiElfTGX4+FGIRCJZnVJ2muLYZeu6kiSpACRn\np7H08jZFYPfgbjyRN86w9tQOxGa2mIpMFOeY2mEkWdJsxOa2fNhhhNL5P2g3lKjb55m+dT6T2w+j\nn08nvJ3qk56bSbt6zRjbKpAvu03gcfFjQqP3k/oonTZ1miLS1cfO1JpMqUQxzqdfAwT6dmHvlaNq\nX9uZWiNJyaDt8J7M2bdEMefjt8+TJX2Ev7s3Y1sF4u/uTdDRzfwQuVQpkC0PeX+vT2Z9obiuIFNb\n2gxS7yQZ0NuZ2xfTOX/pOCEH/+SdDxzpM6EeDZrbcHJ7BgM6fUQrv3aK7QcHjubSvmK1x7ocXsyQ\nAZW3Z38Zx3zdkAWXeWrXvSnBpYCAwLOpdI2XlpYWFy9exMdHNS++uiPUeFUvKuq+JvD6Ul7ee0Vr\njV4UqVTK1o2LOXxgA7Gxt6hdt/FLz8F3r+NJ0PJNBHgXqaybvTiTAWP+pnadZ7vE6urqPlcdV1Ug\nv3disZgmLZrh1y6Axr7eSmPYtHo9bahbIedDeZ2Sh4UrOy9FcuJONAVFhfT2as/8o6tIsStEWkuP\nCV99iKu7GyeOHON0WCR9GrYn0LeLooZKR1sbsZkt5+OvciHhOp90GqX2/LUsHYi4fpIRLfsgfZzP\nzkuRfNBuqJKjYOs6TTkdd4nJ7Yfjal0TkKX9peVk4SF2U/tavu+JO9H4ODdQeS2vf8uWZNPOoAGn\n465w+OZpYtPi+brnB0rnb+HqxbWsOAr1IXLXAWJvx1LHo16l7/PuA1tx8MlRu05kpEt0ZBKJD1Lp\n85FYqf6ofnMz9oQdVao/0tXVxdzAkR0hkZiJSxAZ1SAzJZ/ToQUM7zn9uZwCX8YxXzfq1WlI8KqN\nuHjpqaw7va2Azyb9KNR4vcEI9636UtU1XpVWvM6cOUNQUBABAQEMGjSIwYMHK/0ICPxXvMmKiICM\nl63qnDp+kIVzO9POdTFTekfSznUxC+Z04tTxg1VyfE1cvnCS5LQc5i5OVihfD5If88UvOfQcFkSb\ndt1e6vn/K1ITksrt2ZWakKR4bWhoSM0Wdfnt0Gol1WfR0Q20H9iNz374SqHiyJW0z1uPVlGyTt65\nSEauhJN3LuLpWFfj+e3NbCgoKiA5O419V6M0OgqO8e9P5I3Titeh0eF0a9Ra42uQBWNlnQvLvv4n\n/iiBwwaRmpBELStH+vl0orC4kLGtAtWev59rG1IP3GCwUSsa3TPjp4lfc+LIMbXbaqJ8tSWPpNgC\nuo0Tq10vrz8qS4B/e36dEYJ+XHdid7qhH9edX2eEKCljleVlHPN1Qt5P7HBwLpkpsh57mSn5HA7O\nfeP6iQkICGim0jVeZmZmtGvX7iUMRTMPHz7ku+++48KFCxgZGdGjRw8+++yzcvdJTk6me/fujB07\nlilTppS7rUD1pGydy7BuWTjY1uBhShHrqrDOReDV86xao+flVZmzyM/762c65OXbEHZAQnpWMVbm\nOpiZO9CsebsqP+erorI25wmnbjKj60TFMjtTa2Z0ncjSk5bLNaUAACAASURBVNvIG5OnuB/lNQwO\n9O3C7wdWU9vWmWuJsRoNKxIlqbhbO7Pp7B6M9Q3LDRAzpRLupiUwf99yxGbW7L1yFF9nD1YcC6Gv\ndyelWi14YhEvN/w4evssDcW1WRi9mV7vD0YkEmFqY8GaiDDyCx9z8cENPuygxtUCWYBYVFKsGEt5\nDao1MThwNNPmqjfO2L82jjrO3tg5lajdV1P90YvYs2tqlPw6WL6/TAL829PEp6WiCbXYtha/znjx\nJtECAgLVh0oHXj/++OPLGEe5TJkyBU9PTw4ePEh6ejoTJkzA2tqa0aNHa9xn9uzZ1KhR6ekJVDPk\n7mubN/xN7M7zuNf1ZcoMoY+XwLN5VeYsZc8rMtBmSC8LxbrElEdvlClM/6EDmT/pG97z7KeyTm4Y\nIXc8PLw3gske/dUep0+t1nz14Wc413TGpqY9SXEP6Gimvpeknak16dIsJjccyoAm3VgWtYWpaoKa\nbdH7qWXtSDOXRqw7vbPcAO3QjVOkPsrg296TFQYdy4+FcC3xNnam1jiY2yp6iy2PCqGla2NiEm8T\ndfsc7zbtoXA8DL1zmNLSUk4cOUb8iev0aygzJTE4oVfu+RMyklhxLERhuPGsvl5PI1db1gXPp3FX\nHSxsDchIzuPI5lQ+HPYrcfG3yUzZ/Z+YW7ztvaze9OBSQECgfCoUmWzdupUBAwYAsGnTJo3baWlp\nMWjQoKoZ2b9cvnyZmzdvsmbNGoyMjDAyMmLMmDGsWbNGY+B1+PBh7ty5858rcwKvBpFIxMDBk4iJ\nicHDw0MIugQqRFXb1UulUraHLCc9JRYrW3f6DlDfsPhNtsl/mmfZnF84c17heHivyKpc1cnwXDGD\n67Ui+V4a+45tp1NAA42BSqf6/op1AbV9WRS5nv4+nbE3s+FuWgK/7F+Js4WY/MICrIzMmdF9EkFH\nN/NFtwkqxws9H04d21pK6+xMrfmq+0S+37mQ5McZ7LsaRVFJMTW0dTCyNeWWtYS0C5f5uouyeve+\ndyA//7oKY2MTJnk9CTIHNOmm0cFx6ZFNNHdpTHfPNiRnp7HymKwxdKpOVsVvBMpqy43jsVCsz8Lv\npmFlZYVUGqBREStrJf+i/BeNkgUEBAReZyoUeH3//feKwOvbb7/VuN3LCLyuXbuGo6MjxsZPPqgb\nNGjA3bt3kUqlKiYYBQUF/PDDD8ydO5dt27ZV6VgEBATeHKrSrv7U8YMc2f2NzNq9hS6JKftZMGcj\nbXr8QAv/Di/tvNUBTTbnpaWlSmrYs/pYOZrL0hLtTK2Z1ekDfju0WiktUc6Wc3uZ0Fr2d0j6OJ97\n6YnoaOvw18G1ZOU9wtrEgm96vq8IApdFbaV7o9Z0buDPosj1Ckv6JEkqIefDySnIZWKbd9XO7b3W\ng1gWvwfHNp6kJiRhU9Oe8f16MWvaDCa0VF+zZattSldX5TRJQz0DvJ08mL1rERNaD1KyvX/HqwMn\n7lwgr7BAUcf258Fg6niob7ZcHnK1RSqVEhMTowhy1ClimSn5XNpXXKX1R0IvKwEBgbedCgVely5d\nUvz/+vXrL20w6sjKysLU1FRpmbm5zFAhMzNTJfBasGABvr6+NG/e/LkDr4KCAqRS6fMNWOCVkJeX\np/SvQPXgVd63zt2HsPzX9XwxWvXcwXtMGT9taIU+B6RSKZE7Z/x7HOVasXmrvqZ2vR1KD65Vdd5X\nTWXvXf+hAxX/Ly0tZeOqdUp1WuX17ZLXTMkx1DOghbMns/YsZFKrQdibypofBx3dTK/G7RHp6qv0\n9opLf8Dq49v4tveTml87U2tm9JjEDzsXMqJlH8a0CmTL2T1cSLiOq5Uj41sP4pNNc8s16Ii/docm\nLZsx8sPxXD53kT8/moNpBtg1VL9PUUmJ2uMlZ6czomUfjsdeUPTxkjdYdjC3VeodNqhJN47l3uPP\noMUkpCRR09aeYf0HKn7PpFIp67dtVbsO1N87X+8WeNQLZkvYWm4cj8fO2pnZnwxXmJlUBfcfxlKv\nnF5WN47HVovf/VeJ8LeueiLct+pLQUFBlR7vuYqgUlNTuXfvHrq6uri5uWFiYlKlg3qa0tLSCm13\n+/ZtQkJC2Llz5wudLzExkcTExBc6hsCrIS4u7lUPQeA5eFX3zaHeKL5euISalmkUFZdSQ0eLBxnW\n1PMdVeExRezbxMge2airFRvRPZvlS+bRsauyYuJQbxTfLw1ifJ8CHOxq8DC5iGXb9XHzrPh5Xxfi\n4uLIz8/nSPghHqVJMLE2o02X9s/s9Xj76k26uzyxzC/bt6us6hQavR8/N28VA4tOHv7Ept4n/Oox\nopOuU2iohY+5Gw7mtkgf53PyzkWlIC46PoZJbdU7705oPYhPN/8fZoYm+Ll5M6fvJ2TnPSLo6CYe\nFeSWW39V09AG30Qbfpr0DemSDH7oPIVt0Qc07lNDW0ftukyphFpWjtSyclTZ5+leYfZmNmzbuxiH\nKe9gWL8uiWmZ7J45jcBmbQAIOXMEm07NVNb5enopHVfd71oz74By178QxfpkpuRpqCXLg2J9YmJi\nqvacbyjV7XNCQIZw3wQqFXg9fPiQb775hhMnTlBSInNA0tHRoWPHjsycORNra/Xf8L0IlpaWZGUp\n57JnZWWhpaWFpaWl0vLvvvuOKVOmqCyvLGKxWKGqCVQP8vLyiIuLw8XFRagRqEa86vuWk51MwnV9\n+nQ0RWyrS2JKIat26ePk7ISHx7P7aAEcOSDV2Mjbwa4Gujp5Ksfy8PAgr9dAdm5fTcbxu1jauDL5\nf6Oq1e+u/N6lJaZwfON++rm2wc5FliK37e8Q2o/sRfOAlhr3r92wLsmJygGIr3NDPMS12XJ2D3e0\n09AzNmCYZ3u1wUiSJA1bEyv6+XRiJPD3ha1ICgrYem4fDuZ2KvbwmVJJucpVpwb+5D3OR7+GPhtO\n78TC0IxHebn8FPg5y6K2MqPHJJX9VkSF8GHHEVgYmvJxc1kKYF5hQbnqXWpOJkGnQ/i6k3KaZHmp\nlomSVCV7+oeSVIxb1MfQWmbMYmhtQa3BXfgn5BClJcU49m1LXNQ58iU5GJgZ49KvHTt3H6d/7z6I\nRKJX9r6rVetTZvw6nPZqPEEu7i1i7rRp1eo98Cp41Z+ZAs+HcN+qL1lZWVUqxlQ48MrJyWH48OHY\n2Njw+++/U7t2bYqKirh06RKrV69m2LBhhISEKNViVQWNGjUiMTGRrKwsRTB06dIl3N3dlX55Hz58\nyNmzZ7l9+zZ//vknIEu30NbW5uDBg4SGhlb4nPr6+kID5WqKSCQS7l015FXcN6lUyumIOfxvTD6g\nizSvhMjTOZjoSli79GM8vU5W6Esce4d6JKYc0lizZe9QV+3cDA0NGTX206qYyisjPz+f4xv3KxlF\n2JlaM8mrP/MWrqJxU2+N13Dw6GFqHQ9FuvrkG5fy+5K/n9SBWam6Ij6dftjfrR1heWe5cuICN5Lv\nKNLy5DyrhszC0Iwejdpw4s5F2tZtw+oTYWhpaeNobkdtGyfm7FrMuIBA7M1sFO6FdW1rYWH4JBX+\n3abdFSmBmtS7jJIc4q2KmHkkiPe9+iI2syFRkkp8xgPupt3n086qRhYrj4fySafRitdLruzAekob\nle3M23pxZdsB0rbtp07nVhhaWyBNy+RqaDgWLo5s2bmdSaPGPrnW//H7ztDQkBG9vlBbSzay95dY\nWVn9Z2Op7gh/66onwn2rflR1emiFA6/Vq1dTs2ZNVq5ciY7Ok+LYunXr8s477zBmzBiWLVvGxx9/\nXKUD9PDwwNPTk19++YUvvviC5ORkVq1axbhx4wDo1q0bc+fOxcfHh8jISKV9f/zxR8RiMePHC410\nBQQElClr637qYi5HzuQy/B0LhfL167cB9B6yQMUc42n6BI5j4dyN//YDU2bdPnOmzHhzP3+OhB+i\nn6tqAAAwsnFPBowawcwv/0e7VgEq65/leCj/Yk3dNiHnw1XSD+1Mrbl/8z5aE1tzZ9F2lSCrIjVk\nIl19TsSeB0Cvhi4uVjUBeLdZTzKl2fwVEcz9rESczMUKpassZVMC5erd3itHeZCVRGJWCtp2ZlzX\nzcGxZxsuRp1jSsxKLI3NyM3O5kfvoaTnZikFa8nZaWw6uxsdLS1EuvokZafy95UdXLPOo6G+nso8\n9IyNKC0pxWtIryfX2doCryG9uLhhJ7GPjdTfyP8QoZeVgIDA24x2RTeMjIxkypQpSkGXHD09PaZN\nm8b+/furdHBy/vjjD5KTkwkICGDUqFH069ePIUOGAHDv3j2kUilaWlrY2dkp/YhEIoyMjIRv0QQE\nBFRIT4lFbCtTuo6cyeXz8bYK1Upsq8vsD/U4snvmM7/tetLI25jElCIAElOKmL/G+I1v5P0oTXP6\nntjUBlMHMb+HrtV4Df3atGL6ktlcqSVhY+4xrtSSMH3JbFq29le7zQ9nV7LvahRjWgXi49xA6VgP\nJamcvH2F+ycvot+8Nn+e3qy0Xl5DNmvXQpIkqQAkZ6exKHK9IohLkqTh5+6Ln5s38RmJdGv0xPzD\nwtCUmb0nE1C7CRPbvqsSdIFqSqBIV1/Ww6swm5RWYkont8V9VHdu7j5Cve5t0XKyxHF8d9w+6Mvq\n2wfwdW7ImFaBHI+9wIpjIRyPvUCK/mNu+5rw/u1VzCqOpHhyGwprqK97vrH3KJ6BXdSuq93Zn1On\nTvLVvNksW7eG/Px8tduBTA1evHoFX82bzeLVK6r8G1+5u+KMafMYO+KDN/o9IiAgIFCWCited+/e\npV69ehrXe3l58eDBgyoZ1NPY2dmxdOlStevKK8R9Fc2eBQQEqgdyW/fI0zkMf8dC7TYVbaQsb+Qd\ntnUZ6afuYGXrxpQZ6vt4vUmYWJdfl1RqZYRps7qs3rxBKcWtLCKR6JmNgOXbyBsyP220AbA0Zhe6\n9RzwGtKLKyHhXLWQ8t2p1Uz06IG9qSydb3vCKVJ7uDJrexDNbeopOQfCE+XrpwPLydMuVnueW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ODrDr4YLHlVXStVyZ8YmwsLFWWfCi39MhyDx7Sfq114RwuPj2R+7Vm3LBrmF64KVNsbjz63k4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\nfO48UlNTNbpWR+87Xd4rQ9PR+64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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Display the results of the clustering from implementation\n", "import qtrader.eda as eda; reload(eda);\n", "eda.cluster_results(reduced_data, preds, centers)" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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BOOK RATIOOFI
CLUSTER
00.89-173662.94
10.91281563.51
20.76116727.32
30.85-16602.29
47.9123334.13
50.0934240.00
\n", "
" ], "text/plain": [ " BOOK RATIO OFI\n", "CLUSTER \n", "0 0.89 -173662.94\n", "1 0.91 281563.51\n", "2 0.76 116727.32\n", "3 0.85 -16602.29\n", "4 7.91 23334.13\n", "5 0.09 34240.00" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# recovering data\n", "log_centers = centers.copy()\n", "df_aux = pd.DataFrame([np.exp(scaler_bookratio.inverse_transform(log_centers.T[0].reshape(1, -1))[0]),\n", " scaler_ofi.inverse_transform(log_centers.T[1].reshape(1, -1))[0]]).T\n", "df_aux.columns = df_transformed.columns\n", "df_aux.index.name = 'CLUSTER'\n", "df_aux.columns = ['BOOK RATIO', 'OFI']\n", "df_aux.round(2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Curiously, the algorithm gave more emphasis on the $BOOK\\_RATIO$ when its value was very large (the bid size almost eight times greater than the ask size) or tiny (when the bid size was one tenth of the ask size). The other cluster seems mostly dominated by the $OFI$. In the next subsection, I will discuss how I have implemented the Q-learning, how I intend to perform the simulations and make some tests. *Lastly, let's serialize the objects used in clusterization to be used later. *" ] }, { "cell_type": "code", "execution_count": 51, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Done !\n" ] } ], "source": [ "import pickle\n", "pickle.dump(d_model[\"Kmeans\"][6] ,open('data/kmeans_2.dat', 'w'))\n", "pickle.dump(scaler_ofi, open('data/scale_ofi_2.dat', 'w'))\n", "pickle.dump(scaler_bookratio, open('data/scale_bookratio_2.dat', 'w'))\n", "print 'Done !'" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "### 3.2. Implementation\n", "\n", "```\n", "Udacity:\n", "\n", "In this section, the process for which metrics, algorithms, and techniques that you implemented for the given data will need to be clearly documented. It should be abundantly clear how the implementation was carried out, and discussion should be made regarding any complications that occurred during this process. Questions to ask yourself when writing this section:\n", "- Is it made clear how the algorithms and techniques were implemented with the given datasets or input data?\n", "- Were there any complications with the original metrics or techniques that required changing prior to acquiring a solution?\n", "- Was there any part of the coding process (e.g., writing complicated functions) that should be documented?\n", "```\n", "\n", "As we have seen, learning the Q function corresponds to learning the optimal policy. According to \\cite{Mohri_2012}, the optimal state-action value function $Q^{*}$ is defined for all $(s, \\, a) \\in S \\times A$ as the expected return for taking the action $a \\in A$ at the state $s \\in S$, following the optimal policy. So, it can be written as \\cite{Mitchell} suggested:\n", "\n", "$$V^{*}(s) = \\underset{a'}{\\arg \\max} \\, Q(s, \\, a')$$\n", "\n", "Using this relationship, we can write a recursive definition of Q function, such that:\n", "\n", "$$Q(s, \\, a) = r(s, a) + \\gamma \\, \\underset{a'}{\\max} \\, Q(\\delta(s,\\, a), \\, a')$$\n", "\n", "The recursive nature of the function above implies that our agent doesn't know the actual $Q$ function. It just can estimate $Q$, that we will refer as $\\hat{Q}$. It will represents is hypothesis $\\hat{Q}$ as a large table that attributes each pair $(s\\, , \\, a)$ to a value for $\\hat{Q}(s,\\, a)$ - the current hypothesis about the actual but unknown value $Q(s, \\, a)$. I will initialize this table with zeros, but it could be filled with random numbers, according to \\cite{Mitchell}. Still according to him, the agent repeatedly should observe its current state $s$ and do the following:\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "###### Algorithm 1: Update Q-table\n", "- Observe the current state $s$ and the allowed actions $A^{*}$:\n", " - Choose some action $a \\, \\in \\, A^{*}$ and execute it\n", " - Receive the immediate reward $r = r(s, a)$\n", " - if there is no entry $(s, \\, a)$\n", " - initialize the table entry $\\hat{Q}(s, \\, a)$ to zero\n", " - Observe the new state $s' = \\delta(s, \\,a)$. \n", " - Updates the table entry for $\\hat{Q}(s, \\, a)$ following:\n", " - $\\hat{Q}(s, \\, a) \\leftarrow r + \\gamma \\underset{a'}{\\max} \\hat{Q}(s', \\, a')$\n", "- $s \\leftarrow s'$\n", "\n", "The main issue in the strategy presented in Algorithm 1 is that the agent could overcommit to actions that presented positive $\\hat{Q}$ values early in the simulation, failing to explore other actions that could present even higher values. \\cite{Mitchell} proposed to use a probabilistic approach to select actions, assigning higher probabilities to action with high $\\hat{Q}$ values, but given to every action at least a nonzero probability. So, I will implement the following relation:\n", "\n", "$$P(a_i\\, | \\,s ) = \\frac{k ^{\\hat{Q}(s, a_i)}}{\\sum_j k^{\\hat{Q}(s, a_j)}}$$\n", "\n", "Where $P(a_i\\, | \\,s )$ is the probability of selecting the action $a_i$ given the state $s$. The constant $k$ is positive and determines how strongly the selection favors action with high $\\hat{Q}$ values.\n", "\n", "Ideally, to optimize the policy found, the agent should iterate over the same dataset repeatedly until it is not able to improve its PnL. Later on, the policy learned will be tested against the same dataset to check its consistency. Lastly, this policy will be tested on the subsequent day of the training session. So, before perform the out-of-sample test, we will use the following procedure:\n", " \n", "###### Algorithm 2: Train-Test Q-Learning Trader\n", "- **for** each trial in total iterations desired **do**:\n", " - **for** each observation in the session **do**:\n", " - Update the table $\\hat{Q}$\n", " - Save the table $\\hat{Q}$ indexed by the trial ID\n", "- **for** each trial in total iterations made **do**:\n", " - Load the table $\\hat{Q}$ related to the current trial\n", " - **for** each observation in the session **do**:\n", " - Observe the current state $s$ and the allowed actions $A^{*}$:\n", " - **if** $s \\, \\notin \\, \\hat{Q}$: Close out open positions or do nothing\n", " - **else**: Choose the optimal action $a \\, \\in \\, A^{*}$ and execute it" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Each training session will include data from the largest part of a trading session, starting at 10:30 and closing at 16:30. Also, the agent will be allowed to hold a position of just 100 shares at maximum (long or short). When the training session is over, all positions from the learner will be closed out so the agent always will start a new session without carrying positions.\n", "\n", "The agent will be allowed to take action every $2$ seconds and, due to this delay, every time it decides to insert limit orders, it will place it 1 cent worst than the best price. So, if the best bid is $12.00$ and the best ask is $12.02$, if the agent chooses the action $BEST\\_BOTH$, it should include a buy order at $11.99$ and a sell order at $12.03$. It will be allowed to cancel these orders after 2 seconds. However, if these orders are filled in the mean time, the environment will inform the agent so it can update its current position. Even though, it just will take new actions after passed those 2 seconds.\n", "\n", "```\n", "Udacity Reviewer:\n", "\n", "Please be sure to note any complications that occurred during the coding process. Otherwise, this section is simply excellent\n", "```\n", "One of the biggest complication of the approach proposed in this project was to find out a reasonable representation of the environment state that wasn't too big to visit each state-action pair sufficiently often but was still useful in the learning process. In the next subsection, I will try different configurations of $k$ and $\\gamma$ to try to improve the performance of the learning agent over the same trial.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "### 3.3. Refinement\n", "```\n", "Udacity:\n", "\n", "In this section, you will need to discuss the process of improvement you made upon the algorithms and techniques you used in your implementation. For example, adjusting parameters for certain models to acquire improved solutions would fall under the refinement category. Your initial and final solutions should be reported, as well as any significant intermediate results as necessary. Questions to ask yourself when writing this section:\n", "- Has an initial solution been found and clearly reported?\n", "- Is the process of improvement clearly documented, such as what techniques were used?\n", "- Are intermediate and final solutions clearly reported as the process is improved?\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As mentioned before, we should iterate over the same dataset and check the policy learned on the same observations until convergence. Given the time required to perform each train-test iteration, \"until convergence\" will be 10 repetitions. We are going to train the model on the dataset from 08/15/2016. After each iteration, we will check how the agent would perform using the policy it has just learned. The agent in the first training session will use $\\gamma=0.7$ and $k=0.3$. In the figure below are the results of the first round of iterations:" ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 38.7 s, sys: 200 ms, total: 38.9 s\n", "Wall time: 39.1 s\n" ] } ], "source": [ "# analyze the logs from the in-sample tests\n", "import qtrader.eda as eda;reload(eda);\n", "s_fname = 'log/train_test/sim_Fri_Oct__7_002946_2016.log' # 15 old\n", "# s_fname = 'log/train_test/sim_Wed_Oct__5_110344_2016.log' # 15\n", "# s_fname = 'log/train_test/sim_Thu_Oct__6_165539_2016.log' # 25\n", "# s_fname = 'log/train_test/sim_Thu_Oct__6_175507_2016.log' # 35\n", "# s_fname = 'log/train_test/sim_Thu_Oct__6_183555_2016.log' # 5\n", "%time d_rtn_train_1 = eda.simple_counts(s_fname, 'LearningAgent_k')" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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7d+fhhx9m4cKFlJSUGNz+5MmThIWF0alTJ9544w2dV2w3btxAoVBw4sQJg9sq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\niObNm3Ps2DEcHR0BUCgUaDQ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zw86u9hNX1TaffcmX4Z/fKzcXF/xc/ExangaRT2wsbeRK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+LatqDC44WV120EhJaXo5yvBzQjbkQ7/DriVSvTck/QJTCMEF8Deq1OGqQt5G3Xt4vy241mr/2v\neX4VFZTpdPhqdFgP/txgAwJACavqE3wicRzdj21GO3B0i0ZCcYSpwsJpY3GD28vMZeRWmvAvLcCv\nouUX79px4nx1GHSOfSlpyDfffMPSpUtZsGAB3bp148MPP2Tq1Kl89dVX+Pn58fDDD/PHP/6RCRMm\nsG3bNpKTkxk2bBizZ8/m0KFDXHnllcyYMcMpZXGF8vO/xHYtLWbSKftZVv3Cot1RpHo1lUfg/FyK\nqyzHmb+xtCSX+vXrx913301RURFXXHEF999/vxNL5Fyl5WZ8z1+AL5RT67NbMvI2jhbn8++DW9Cg\nkNShC6ZSx2aCrfzqrZoGBKBJvBzCojEFFaB2vARNrV/H1MORVTcXzCYqt2/AVGEhJyC4agS6nkNQ\njcVoLhmIYi4Fc6nUSW6Ue8EwnNX2nMmk27kiQg7WDENe7hdA0hU3tlXRRDvQ7Vxh1YSDAOfnotEq\nGi6LjndjqeT65q7rm9c1IiwWC/Pnz+ebb77Bz8+Pe+65h2nTprUq5qDCXH6O6ISvVot18/sN7+hr\ngOBwMJkwhsRQ8fv5+Lr4NpSpwsKT2z/GWNGMNv3BDOe86MEM/HU+PD/seqdctJcvX86MGTO48sor\nAXjkkUf4/vvv+eyzzxg3bhwlJSVERETQsWNHJk2aRMeOHYmIiECj0aDVavH39ycoyHOHHjxTVkpk\nmZEb63nYTBvi+KzBruBQHoHTcumrfdm8MNw5eQQty6Xw8HCMRiM6nc6jcynbVMyS1G/oGtiBJwZe\nY/tx4ufc46w7touS8qofN4ZFdkOjaOgVEsXfLp0MgNFoJJXmNyJUYzHqoW22Ze24u1H6XAGmBn5A\nqZ64zmKidM93PN3/Ckw6HyjNq/oPYP93dY+TOqnNHT+X3+C24WcueKbmqttcXBrRXmQZAuhkKqVP\nrUEVqidMdTe5vrnv+uZ1jYgXX3yRAwcOsHLlSjIzM/m///s/YmNjGTeu5SPfhFqqbtlpzXVbpkr8\nANSifCjKQzP8OpffdWiP0tLSWLhwIS+++KJtXXl5OSdOnKBDhw7ccsstzJ49m1dffZUxY8Zw8803\nExgYiNELukQA5JmKefDwLjpY6un/GewZjYj2oqW55A0+zfyVCtXKsZJ88srOEWUIwlJZwYpDW+32\n6xJYNeqJWlJA5c+foJ5ORxsQim/UgGa9jlpZgfWnj+H8OO7aGx9B061v4wfpzz8kWVYK9XRx8Dbt\nuU4qLDcBEOzjR3G5faOw2Mf+4VdDRPPmRBIXt8cGX8mdx1PpZCq1W680VW8Ih3jj9c2rGhEmk4l1\n69axfPlyEhISSEhI4L777mPVqlWtakREmqsqXe2ZWiMwJVyK7lr3d3sw6Hx5ftj1TXZnSj+eTlx8\nHH56vwb3a0rtOHFhUU5rXVdUVPD000/XGbqsOvmfffZZ7rrrLjZu3MjGjRt57733WLZsGQMHun+U\nl+Y4cvo4CfU0IFQUlC7NnP3cxZqTR+D8XBqe2N9peQQty6VXX32V4GDPH7qypKImh06UnCHKEERp\nhcVun+GR3Rgd0wsA685vUPf/CIAmP5POhQUw5LJGX0NVVSrffwn1/AyzRHVtugEBKLWGjTVUVvDs\nvp/Iu2Yqmthe9e4vdZL7FJ/vjhsXFE5H/2C+zqwZz19vrRlVxzrsOpBGhGjC6l5DmNRzOGeyjtut\n1/3xFRS/ADeVyp5c39x3ffOqRsTBgweprKxk0KBBtnVJSUksXbq0kaMaVhLUgaCSAi49c5pdYVGE\n+4XatmlHec5tXoPOl/hGftE2Go0YtTl0C2jdU/614zjzf4z4+Hiys7Pp0qWLbd3s2bO59tprSUxM\n5F//+hdz5sxh+vTpTJ8+nWnTprFp0yYGDhzoFXd+jGdO1Vn3cu8hPDHyVpTgcDeUqH5N5RE4P5cM\nWp+md3ZAS3Lphx9+YOLEiU4th6udOFfAsKg4SivsG6e3XJKE7/kH9dVzZ+22BRZl2T3IqOZnUrl9\nQ9Wdg9IiQEEzYFRNAwLQDhzTrPIoMd2pGty6agQWg6Llkq59UQLqH5JQ6iT3OV12ji6lxSRZFU53\nqvmiNKFrf67ZXdXoVMM6oh8pz0KIxlWgIb1jN+6I6cn6gWPg6//atin+ntWdT65v7uFVjYi8vDxC\nQ0PR6WqKHR4ejtls5uzZs4SFNX9yk1y9AT/fmgr23vRU9LF9sFav8JC+fu3BtGnTmD9/Pl27dmXQ\noEGsWbOGr7/+mlmzZhEaGspXX32FRqNh6tSpZGVlcejQISZNmgSAXq8nIyODgoICOnTo4OYzqd/g\nY/vslot8fInuMcSjGhDtRUtyafz48QAYDAZOnDjh0blULbO0EABjec2diCmXDCGoVp1FWT1da4ry\nUA1dodxMxcr5dTZXnq558F97y/+hNHN2ayUiFt29C1GLqp5/UDrENNiA8AbtuU664+he4s9U9fku\ntljY4Ff1ReeKgDCU83e2NIEyEZho2oddeuJ3fqCHW/r+hvLzjQjpxuQa3nh986pGhMlkwtfX/teo\n6mWLxVLfIfXK8gvg9V59eeH4Qds6n4pyqH4mwteAUs/oKKJlJk6cSEFBAa+88goFBQX07NmTZcuW\n0blz1a30JUuW8PzzzzNp0iQCAwO5/fbbmTx5MkajkdGjR7NixQpOnDjB2rVr3XwmdZUYi+l1tuaB\n1r2DRpMTHsOtl8iwv67QklyaNGkSqamp3HjjjSxYsIC0tDSPzKXaqrsx1R5pZ1D4BV1Pyuz7JwP4\nvPtXKuqsrUvTfxSa2J4OlUkJDm83DeP2XCdF13q2L3j///i/K6dQdskAwrLSqJ7RQ9P/SvcUTniV\ns3q93XDB2gl/wnp0J9qRN7mxVO2XN17fvKoRodfr6zQWqperZ/xrjq9j4qjQaO36+apaHeXnitAC\nqq+h0QfoTCaT3b8t1R7jjB8/niuvvJL09HS7OFOmTGHKlCl2+1a/xz169KgzrrHRaMRkMjF8+HBu\nueUWDIbGP5PGOOv9qc93+zfxh/N/l+sNJF46mURAtZRjtDQ9UoQnfXaeFsdZuVR97BVXXMF3331n\nt78jLjwnV+RTtYxzBeQWn+WT9JqJ4DTllRitNeXWlZ1r1hzV5fe8BIoGJS+jamI4rQ9qZNd653Lw\npM/fWXEutjrpQp13fUtF4m+wFJ2pur5ptJR17tPgXB6e9NlJnLaLU59CH19i9H41eR6bWPUfNGsu\nGE87R0+Kc80119CzZ886Mbzt+qao3jD95nm7du3izjvvZO/evWg0GgB++eUXpk+fzq5du5o83mg0\nkpqaygemdApUMw+b9HT/dUOd/UyBERwZMqWeCKK9SExMbHWfyNTUVHrsfB//80Mqpg68gfKQGGcV\nUXgJZ+XSB6Z0zqj1j3wUqOj4vaE7OouR4DPpKNZKYtOq+rcXRvYgt+sQotO3E3Km6uHHMv8wLH7B\nnI4bTlmgjBDmDVxRJ1Xb+5s/0jF9G1End1HuYyD18rtbWVrhyZxZJ12p70ikpuUPIQvv1lQuedWd\niMTERHQ6Hbt372bIkCEA7Nixg379+jkcK1Cnp+vIa6nUW9Hu/Mpumz4wmMTExAaPNZlMpKenExcX\n59AdEInj/jgA6enpLY7VmB7DRoHWsW5wnvxetZc4ripL9bIz3RDVnY9zjqJe8PDuQ32uItIvEO0n\n/0RT68FogMB+l6Hp0h9L1q+2dbqRN6KNH4ij0z950ud2scQB19VJ1froStEYqrr+6gLk+tZe44Dz\nc+nKvoNbfKwnv1fujuNJZakvTnOvb17ViPDz8+P6669n3rx5PP/88+Tk5LBixQoWLlzocKypvS/D\n39+fytCImoepz/MZfh36ZrTiDQZDq1r7Eqft47hMVFf8WzHJiye+V+0tjieVpT4D0DDmy7e4xBDA\nywlJcL4h0S2wA121Gqw7PsN6QQMCwK9rb1Q/A3mR3YnI/tW2TmlFGT3tvWrPcVxBN3UBalkple+9\nAIBPXgbq4V8AUEwlzSq7J75XEqfxOK7gaefY3uJ4UllaEserGhEAycnJPPPMM0ydOpWgoCD+/Oc/\nM3bsWIfjXBJUdYu/zggjvn4y8oBwmPbKW9xdBOHlxhfmo7FWcklpMeGWMs6cn+Dt/oSRVLz7AhSe\nf4BfUdBOmIF1z3cosT1ROsSA0UhpaCwVV09FH9IBJcjzRg0SbaNwzF2EdOiIAlg790LNPIy6f3PN\nDpXNefReCAjzlVEqReO8rhHh5+fHCy+8wAsvvNDiGJdGdCOgeuZOf/tJOrSTH0bROXfsX9F+WfuM\nRBsWjtK5t7uLIrycUlHz5a5rabGtERGh0VBR3YAANIOuRtNjMJoedbsZqD2S0LjgLonwHoGh0TUL\nIVGQedhuu3bsnW1cIuGtJnWWH1RF47yuEeEMIyNregortWbsVPpcgaaZ46YLAWBNuBxNePsY9lK4\nl5J3wvZ319ISdnWIRq/RUflDzXB92hv+jCa+vzuKJ7yQ4hdA7ZFTNMOuQ5N4udvKI7xLhN4zZqQW\nnkvj7gK4m+Lrh/bGR1B6DUN76QR3F0cIIYg1Vc0PYa4sR/31R9t6JURGWhIOuOABfU1Pmb9GCOE8\nF+WdiAtpuvVFI89BCCE8hP/5fuux2gu6VoZF17O3EA0wXDDYQ2Tn+vcTQogWuOjvRAghhKdQouMA\nCFe0BOj0TO1S8+OGdvLDKIpU2aL5NANG1fw9eCyKxrEhqIUQojFyJ0K0WnJyMuvXr0dRFC6cu1BR\nFN5++22GDRvW7Hjbtm1j6tSppKSkOLuowsO5KpdWrVrl7KI6XeXwCShF2ag56QQBf7/sRtRTR6is\n3sEv0I2l8y5SJ1VRfP3QPfxm1d8XdG0SQrSt9nh9k0aEaLU5c+bw+OOPA/D555+zfPly5s+fT8+e\nPTEYDISEhDQRwd6QIUP48ccfm95RtDuuyKVvvvmGnJycpnd2M7VzIpjOVi2cOwu5GaiZh2zbFf+W\nz0NysZE6qYY0HoTwDLXrpfXr17NixQree+892xwf3nh98+h74/feey8fffSR3brCwkIefPBBhgwZ\nwtixY/nkk0/cVDpRLTAwkPDwcMLDwwkKCkKr1RIcHEyHDh0IDw9Hp3OsrarT6QiXEY8uSq7IpQ4d\nvGjOBF8/258Va/6K9eAvNdsMcieiuaROEkJ4mtr1UmBgIIqi2Ookb72+eWQjQlVV/vrXv/LTTz/V\n2TZ79mxKS0t5//33mT59OnPnzmXfvn1uKKVoruTkZJKTk7n++usZMWIEGRkZHD16lHvvvZchQ4Yw\nYMAA7rjjDo4dOwZU3aJLSEgAIC8vz9bavuaaaxgwYADTp0+nuLjYnack3KQluTRkyBAAsrKySEhI\n8OhcUmo1IgAwFlX9GxCCUj23jWg1qZOEEJ7GG69vHtedKScnh7/85S9kZmYSHGw/EdzJkyf5/vvv\n+e6774iJiaF79+7s3r2bNWvWtGryOU+nmo2oBacb3K6UlWEozkHJMWD182twv6bUjqN2ikPRO2/S\nqk8++YTFixcTHh5Oly5dGDduHCNHjuSZZ56hpKSEZ555hkWLFrF48eKqslxwC37p0qW88sorWK1W\n/vSnP/HWW2/x8MMPO618F4Om8gicn0uY48DJk5+161y68LkHswkA7W+muKEwDZM6ycPzSIiLjFzf\nqrR1veRxjYgDBw7QqVMnXn31VW688Ua7bXv27KFTp07ExMTY1iUlJbFs2bK2LmabUc1GKpbPBrOx\nwX10QE+A3dQ8hNkCteNU6P3R3bvQaRft/v37M2pU1UghJpOJ22+/nd///vf4nf8fefLkySxfvrzB\n4x966CH69esHwMSJE+Xuk4Oak0fg/FxSD2xAve9Fp375a8+5pER2qX9DaGTbFqQRUidV8eQ8EuJi\nIte3Gm1dL3lcI2L06NGMHj263m15eXlERUXZrQsPD+f06cZbn8L9YmNjbX8bDAZuu+021q9fz/79\n+zl27BgHDhwgIqL+ibQURaFbt2625cDAQCoqKlxeZuGZ2nUuBdff714Jkv74zn97QA8AACAASURB\nVNau80gI4ZW8rV5q80aE2Wxu8EnyyMhI21Pq9TGZTPj42E++5OvrS3l5ucNlMBobb7E2xmQy2f3r\n8ji3z0MpbPjpe7PZTFZ2Np1iYtDrW95vunYc3+iulFcCDr5PZrPZNnRZ9XlVVFSg1Wpt77nJZOKO\nO+4gLCyMUaNGcc0113D8+HFWrlyJ0WikrKzM7vjqGNXHl5eXU1lZ2ezP0FmfV328KpeayCNwfi5F\nJwzA0II8qo7hrFwCbH+3NJcufI+dnU9msxmTyYQy8SF0n75q/9qKrtH3UOqkxmNIndR8bZ5LEscj\n4tTHq3LJy65v1d9bL6xTvO361uaNiD179nDXXXfVO+zc66+/ztVXX93gsXq9vk6DwWKx2G7zNFd2\ndjbZ2dkOHVOf9PT0VsdwWpzgaNJKrVDayoqkOs6xlpUpOzvb9hlVn1dhYSGKopCamgrArl27yMnJ\nYcGCBbY82L9/PxaLhdTUVDIyMlBV1Xa8qqocPXqUwsJCoOqOVGlpqS1ecznr86pNcqnxOOlZOZDV\nsuHnnJlLAJmZmU7JJVfkEdTkktZiou8F21IPHqr3mAu11zySOqn52mWdJHHaLE5t7TKXPOT6lp+f\nD9ifkzde39q8ETF8+HAOHjzYomOjo6PJy8uzW5efn09kpGP9hWNiYggNDW1RGaCqhZaenk5cXFyj\nd04uxjhHjhyx3S2qjhMaGoqiKCQmJgJVrWOLxUJWVhZ9+vTh559/ZuPGjQQGBpKYmEhpaSmKohAX\nF2f7vHv06GF7FiYyMpKMjAxbPEfOC5xb2UouuS6OM3MJoHPnzkDLc+nCc6pedhZbLqlW+LlmvTWu\nf5Pl86TPzdPiSJ3kGE/67CSOY3FAcslb4hw4cADALoY3Xt887pmIxgwcOJCsrCxycnKIjo4GICUl\nhUGDBjkUR6/X4++EJ+oNBoPEuYBer7cldXWc6rGPq2NedtllzJgxgxdffBGz2Uzv3r2ZP38+c+bM\n4dy5c7Y7S9X/YymKYlcmHx8fNBqNw2VsTaXREMkl18VxZi4B+Pn5OSWXnPXeXKh2LtW+3+r723tQ\nDM17PU/43DwtjtRJLeMJn53EcSyOs0kuuS5O9Q8btWN44/XNqxoRXbp0YeTIkfzlL39hzpw57N27\nl88//9ytU34Le5MnT2b8+PF2t8/qG3535syZzJw5s86xAFFRUaSmpmI0GomMjCQlJcUuqWfNmuWi\n0gtP4qxcSklJITU1lU6dOtW5reupuaS58hasm9eixPdHMchM1a0hdZIQwtNMmjSJnj172q3zxuub\nRzci6ntu4sUXX2Tu3LnceuutREZG8vzzz9uGsxJCiPZAmzQOTedeEBrt7qIIIYQQ9fLoRsSmTZvq\nrOvQoYNtkg0hhGivlOg4dxdBCCGEaJDG3QUQQgghhBBCeBdpRAghhBBCCCEcIo0IIYQQQgghhEOk\nESGEEEIIIYRwiDQihBBCCCGEEA7xuEZESUkJc+bMYcSIEVx++eUkJydTUlJi215YWMiDDz7IkCFD\nGDt2LJ988okbSyuEEEIIIcTFx+MaEU8//TSHDx/m3//+N2+99RZpaWnMnTvXtn327NmUlpby/vvv\nM336dObOncu+ffvcWGIhhBBCCCEuLh41T4TJZOKbb77hnXfeITExEYAnn3ySP/zhD1gsFk6fPs33\n33/Pd999R0xMDN27d2f37t2sWbOm3pn+hBBCCCGEEM7nUXciNBoN//rXv0hISLCtU1WVyspKjEYj\ne/fupVOnTsTExNi2JyUlsXv3bncUVwghhBBCiIuSR92J0Ov1jBw50m7d22+/Te/evQkNDSUvL4+o\nqCi77eHh4Zw+fbotiymEEEIIIcRFrc0bEWazmZycnHq3RUZGYjAYbMurVq3iq6++Yvny5UBVdycf\nHx+7Y3x9fSkvL3ddgYUQQgghhBB22rwRsWfPHu666y4URamz7fXXX+fqq68GYPXq1Tz33HPMmTOH\nyy+/HKi6U3Fhg8FiseDn59es17ZarQCcO3euNaeA2WwGqkaKMplMEseL4lSrzoWWklzynjiuKkv1\nsifkkie93xLHsTjVPCGPwLPfK4nTeJxqkkueH8eTylJfnOZe3xRVVdUWv6qLLF++nJdeeonZs2dz\n991329Z/9tlnvPLKK2zatMm27sMPP+TNN99kw4YNTcY9c+YM6enpLiix8DZxcXGEh4e3+HjJJVFN\nckk4g+SRcBbJJeEsTeWSRz0TAbB+/XoWLVrEnDlzuPPOO+22DRw4kKysLHJycoiOjgYgJSWFQYMG\nNSt2SEgIcXFx6PV6NBqPeqZctBGr1YrZbCYkJKRVcSSXhOSScAbJI+EskkvCWZqbSx51J6KoqIjR\no0czfvx4HnvsMbtt4eHhKIrC/fffj9lsZs6cOezdu5fnnnuOVatW0a9fPzeVWgghhBBCiIuLRzUi\nvvjiizqNB1VVURSFTZs20alTJwoKCpg7dy4//fQTkZGRPPLII1x33XVuKrEQQgghhBAXH49qRAgh\nhBBCCCE8n3R2E0IIIYQQQjhEGhFCCCGEEEIIh0gjQgghhBBCCOEQaUQIIYQQQgghHCKNCCGEEEII\nIYRDpBEhhBBCCCGEcIg0IoQQQgghhBAOkUaEEEIIIYQQwiHSiBBCCCGEEEI4RBoRQgghhBBCCIdI\nI0IIIYQQQgjhEGlECCGEEEIIIRwijQghhBBCCCGEQ6QRIYQQQgghhHCINCKEEEIIIYQQDpFGhBBC\nCCGEEMIh0ogQQgghhBBCOEQaEUIIIYQQQgiHSCPCi2zatIlRo0YxePBgtmzZ0ui+69evZ8yYMQ1u\nT05OJjk5udmv/eWXXzJ+/HgGDx7MvffeS1ZWVrOPFZ7FXXmUkJBAYmIiCQkJdv99/PHHDpVfeA53\n1kmvvfYao0aNYvjw4TzyyCMUFBQ0+1jhWdyZR8uXL+fqq69m+PDhPPnkkxiNxmYfK9zPnblTbcmS\nJfUet2jRIi6//HIuvfRSXnrpJYfjegNpRHiR1157jSuvvJINGzYwbNiwJvdXFMUpr7tz504ef/xx\n7rvvPtavX4+Pjw+PPvqoU2KLtueuPNqyZQs//vgjW7ZsYcuWLdx3333ExsZy9dVXOyW+aHvuyqV3\n332XDz/8kL///e+sWbOG3NxcnnrqKafEFm3PnXn0xhtv8Nhjj/HOO++Qk5PDY4895pTYom24K3eq\nffbZZ7z++ut11r/11lt88cUXLF68mNdee41PP/2UFStWOPW1PYE0IrxISUkJQ4YMoWPHjvj6+rbZ\n665YsYLrr7+eKVOmEBcXx9y5c8nLy6OwsLDNyiCcx115FB4ebvvPaDSycuVKnnvuOQIDA9usDMK5\n3JVLmzdv5tprr2Xo0KH06NGD++67j61bt7bZ6wvnclcerV69mnvuuYfrrruO7t27s3DhQr7//nvS\n09PbrAyiddyVO5WVlcybN4+5c+fStWvXOttXrlzJQw89xODBgxk+fDiPP/44q1atarPytRVpRHiJ\nMWPGkJWVRXJysu2X29OnT/PnP/+ZSy+9lMsuu4wFCxZQXl5e7/E7duxg8uTJDBo0iIcffhiTyWTb\ndurUKRISEti+fXu9x27bto1rrrnGtty5c2c2bdpEaGioE89QtAV35lFtr776KpdffjmXXXaZc05M\ntDl35lJoaCg//PADOTk5lJWV8dlnn9G3b1/nn6RwOXfm0cmTJxkwYIBtOTIykg4dOrB7924nnqFw\nFXfmjtFo5MiRI6xdu5ZBgwbZbcvNzSU7O5uhQ4fa1iUlJZGVlUV+fn5rT9ujSCPCS3zwwQdER0cz\nd+5c1q1bR3l5OVOnTsVsNrN69Wr++c9/8sMPP9Tb766goIDp06czcuRIPvroI3r06MGXX35p2x4T\nE8OWLVsYPHhwnWNLSkooKiqioqKCe++9l5EjRzJjxgxycnJcer7CNdyVR7VlZWXx+eefM3PmTKef\nn2g77sylmTNnotFoGDVqFElJSezcuZNFixa57FyF67gzj8LDw+2uZUajkaKiIs6ePev8ExVO587c\nCQoKYs2aNfTq1avOtry8PBRFISoqyrYuIiICVVU5ffq0E87cc0gjwkuEhYWh0WgIDAwkLCyMzZs3\nk5uby6JFi+jRoweXXnopTz/9NGvWrLFrTQNs2LCB8PBwHnvsMeLi4pg1axb9+/e3bddoNISHh6PT\n6eq8bvVDZs899xw33HAD//rXv7BYLEyfPt21Jyxcwl15VNu6devo37+/3bHC+7gzlzIzM/H392fp\n0qWsWrWK6OhonnzySZeer3ANd+bRddddx7Jly0hLS8NsNrNw4UKABn+5Fp7FE65n9al+rdrdq6r/\ntlgsLTlVjyWNCC917Ngx4uPj7fqTDx48mMrKSk6cOGG3b1paGr1797Zb19wvcFqtFoApU6YwceJE\n+vXrx6JFizh8+LDc8m0H2iqPavv666+ZNGlSywosPFZb5tLs2bOZNm2abVSWf/zjH/z000/s3bu3\ndSch3K4t82jmzJn069ePCRMmMGzYMPR6PYmJiQQEBLTuJIRbuON6Vh+9Xg/YNxiq/zYYDE55DU8h\njQgvVZ2ktVmtVlRVxWq1Nnm8j49Ps14nLCwMnU5HfHy8bV1oaCihoaFkZ2c3v8DCI7VVHlU7ffo0\naWlpMiJTO9RWuVRQUEB2drbdF4COHTsSFhYmQ0+3A21ZJ/n5+fHKK6+wfft2tm7dypw5czh16hSd\nO3d2qMzCM7T19awh0dHRAHbPP1R3cYqMjHTKa3gKaUR4qfj4eI4fP05xcbFt3a5du9DpdHVGCujZ\nsye//vorqqra1h04cKBZr6PVaunXrx8HDx60rSsoKODs2bPExsa28iyEu7VVHlXbs2cPMTExdOzY\nsXUFFx6nrXIpJCQEX19f0tLSbOsKCgooLCyUL3/tQFvWSS+99BIfffQRgYGBBAQEsHfvXs6dO9fk\nc13CM7X19awhUVFRxMTEkJKSYlu3Y8cOYmJiiIiIcMpreAppRHipESNG0KVLF5544gkOHz7Mzz//\nzIIFC5g4cWKdITN/97vfUVZWxnPPPcfx48f597//zc6dO23brVYr+fn5DfYDnTZtGitXruTLL78k\nLS2NJ598kj59+tiNaiG8U1vmEcCRI0fo3r27y85HuE9b5ZJWq+XGG2/kxRdfZMeOHRw+fJgnnniC\nwYMH069fP5efp3CttqyToqKieOONN9i3bx/79+/niSee4Pe//z3BwcEuPUfhGm19PWvMbbfdxqJF\ni9i2bRu//PILL7/8MlOnTm3V+XkiaUR4kdqTpGg0GpYsWQLArbfeyuOPP87YsWN55pln6hwXHBzM\nv//9b/bu3csNN9zA1q1bueGGG2zbs7Oz+c1vftPgMw7jx48nOTmZv/3tb9x8880AvPHGG848NdGG\n3JVHUHV7Vy7Q7Ye7cunJJ5/kmmuu4fHHH+euu+4iJCSk3gmfhHdwVx7deeedjBkzhvvvv58//vGP\njBkzhieeeMLJZydcyZ3Xs8bcd999XHfddTz44IM88sgjTJ48uV02IhS19r0cD2GxWHjhhRf4/PPP\n8fX15aabbuKRRx4BqkbleOqpp9i9ezexsbEkJyczYsQIN5dYCCGEEEKIi4dH3olYsGABW7du5a23\n3mLRokWsXbuWtWvXAjBjxgyioqL44IMPmDRpErNmzWp34+4KIYQQQgjhyTzuTkRRUREjRozgP//5\nj222vzfffJP09HQmTpzIjBkz2Lp1q+0p/GnTppGUlMSsWbPcWWwhhBBCCCEuGo7PouFiKSkpBAUF\n2U0Xfv/99wOwdOlS+vbtazeMV1JSksxXIIQQQgghRBvyuO5MJ0+eJDY2lo8++ohrr72WsWPHsnjx\nYlRVJS8vz24acag7bb0QQgghhBDCtTzuToTRaCQ9PZ21a9eycOFC8vLyePrppzEYDJhMJrtpxKFq\nKvH2No24EEIIIYQQnszjGhFarZbS0lJefvll24RUp06dYs2aNYwcOZLCwkK7/S0WC35+fs2KXVFR\nQVFREXq9Ho3G427CiDZgtVoxm82EhISg07U8/SWXhOSScAbJI+EskkvCWZqbSx7XiIiKikKv19vN\naBsfH09OTg7R0dEcOXLEbv/8/PxmTyNeVFREenq6M4srvFRcXBzh4eEtPl5ySVSTXBLOIHkknEVy\nSThLU7nkcY2IgQMHYjabOXHiBN26dQMgLS2N2NhYBg4cyNKlS7FYLLZuTSkpKXYPYTem+oHsiIiI\nOrMXOsJsNpOdnU1MTIzdQ94Sx/PjQNUkMq2JB5JL3hTHVWWpXvaEXPKk91viOBYHpE6SOJJLF1sc\nTypLfXGae33zuEZEfHw8o0aNYvbs2cybN4+8vDzefPNNZs6cybBhw4iJiWH27NnMmDGDb7/9ln37\n9rFw4cJmxa6+LRcYGNiqVrrRaCQ7O5vQ0FD8/f0ljhfFgapKtrW3aCWXvCeOq8pSvewJueRJ77fE\ncSwOSJ0kcSSXLrY4nlSW+uI09/rmkZ3dFi1aRLdu3bjjjjtITk7mzjvv5I477rBNaZ6Xl8dNN93E\np59+yhtvvGHX9UkIIYQQQgjhWh53JwKqWr8LFy6s9w5Dly5dWLlypRtKJYQQQgghhAAPvRMhhBBC\nCCGE8FzSiBBCCCGEEEI4RBoRQgghhBBCCIdII0IIIYQQQgjhEGlECCGEEEIIIRwijQghhBBCCCGE\nQzyyEbFx40YSEhJITEy0/fvnP/8ZgMzMTKZNm8bgwYOZMGECW7ZscXNphTfoduBLfJY+RPnqZ91d\nFCGEEEIIr+eR80QcPXqUMWPGsGDBAlRVBWqmYZ8xYwaJiYl88MEHbNy4kVmzZrFhwwaZcE407NxZ\nQvKPu7sUQgghhBDthkc2ItLS0ujZsycdOnSwW79161YyMzN5//330ev1PPDAA2zdupV169Yxa9Ys\nN5XWvZKTk1m/fn292xRF4e2332bYsGEtip2RkUFGRgYjR45sTRHdTinOd3cRvILkkmgvqnNZURTb\nD1HVWpvLOTk5FBYWcvXVVzujqKIRUieJ9sSV9dLJkyfJy8tr83z22EbEiBEj6qzfu3cvffv2td2V\nAEhKSmL37t1tWTyPMmfOHGbOnMnhw4c5duwYq1ev5oMPPrAlaEhISItjJycn85vf/MbrK1ntj+/b\n/lbiB7ixJJ5Nckm0F3PmzOHxxx8H4PPPP2f58uXMnz+fnj17YjAYWpXLS5cuZezYsdKIaANSJ4n2\npHa9tH79elasWMF7772HwWAAWpfP8+bN46qrrpJGBMDx48f53//+x5IlS7Barfz2t7/loYceIi8v\nj6ioKLt9w8PDycnJcVNJ3S8wMBCNRkNISIjt7wvv4LTUhS1lb2LNSKXy+3fR9B2Bcva0bb32sklw\n6JAbS+a5JJdEexEYGEhgYCAAQUFBaLVagoOD6dChA/7+/q2KLbncdqROEu1J7XopMDAQRVGcUie5\nk8c1IrKysigrK0Ov1/PPf/6TzMxMnnvuOcrKyjCZTPj6+trt7+vri8Viceg1zGYzRqOxWfuaKsvJ\nLSuxP77MTG6lCe2ZbPSl+gaObEY5GogT5ReEQevT7DgmkwmA8vJyVFWtc25r167lv//9L0VFRfTt\n25cnnniC7t27A/Dzzz/zyiuvcOLECSIjI7n22muJi4tj7ty57Ny5k127drF161aWLFnicHmq/22p\n1sTx+eDvAFg3r7WtKx33RyrN5laV6ULNzaX68ghcm0uO5hG0z1xyVT62Nt6FHKmXLtTW/881lM/V\nXJHXXSojHM5nqHpfq78w1j6v5uZyVFQU06ZNY/LkycyePZvDhw9z5MgRduzY4VAu1+aqHALPvr5J\nneS5cerTmjoJ2vYcm6qTwPm53fFccYtjlJeXA3XPydF66be//S2LFy9m9+7d7Nmzx+F8rtbS65vH\nNSI6derEL7/8QnBwMAAJCQlYrVb+8pe/cOONN1JcbP+hWSwW/Pz8HHqN7OxssrOzm9zPolayxnQM\nC9b6d0jPcOh1G3RBHF80/N5wCb6K1qEw+fn5WCwWUlNTbeu2b9/Of//7X+6//36io6P54YcfuPfe\ne3n55Zfx9fXlscce4/rrr+fBBx8kNTWVpUuXkpCQwOTJkzl06BB9+vRh0qRJdjGbfVrp6Q4f44w4\nirWS/hess+gDSTMp4KQyVWtOLjWZR+CSXGppHkH7zCV35WNzNbdeakxbnGOz8tkWyHl53dJ8zs7O\ntl2wq8/L0Vx+7rnnCAkJYcqUKaSlpbUql+1OywW55MnXN6mTPD9Obc6ok8D15+hQnQROy+0vDmW2\nKp/B/pxaWi/dfffdnD592in1kqOflcc1IgBbA6Ja9+7dMZvNREREkJaWZrctPz+fyMhIh+LHxMQQ\nGhra5H6mynK0+05AZTMT00m0Wi29evdu9i82JpOJ9PR0IiIi8PX1JTEx0bZt4cKF/OlPf+Lmm28G\nYPTo0dx6660cO3aMMWPGYDKZSExMZOTIkSQlJREeHs6AAQOIiIggKCiIrl27kpSU5FD5q8sTFxdn\n6+vXEs2OU1aK9stlKEW5UFmBUl73bsORwTcTFx8POLeybU4ueUseQfvMJVflY/WyszS3XmpO2Vqq\nOXG8KZ8Bjhw5go9P1THV5+VILo8cOZLBgweTkJCAVqtFq9USExPjcC7XVvt9hravk8A9n6PUSa6N\nA+7JpYa01XvlrjpJo9G0qE4COHDgAIDdObWkXoqLiyMvL4+AgIAW5XO1ll7fPK4R8eOPP/LYY4+x\nefNm2wPUBw4cICwsjKFDh/LWW29hsVhs3ZpSUlIYOnSoQ6+h1+ub1QfNH3hh+PWcNtrf/Sgzl5F+\nPJ24+Dj89I7dBWlOnI7+wRh0vg0f2AAfHx8URbE7t/T0dF5++WVeeeUV27ry8nKys7Pp3Lkzt9xy\nC/PmzWPp0qVceeWVtgrW398fjUaDj49Pi/vrGQwGp/T1aypO5a8/YM1peAhXVedLpa+hVZVYQ5qT\nSw3lEbg2l1qaR9A+c6mt8rGlmlsvNaYtzrGxfK7miryOC4tqUT7r9XoURQFqzsuRXB4zZgw333wz\nUVFRtq4drcnl2txVJ4F7rm9SJ7k2jrM5o04C179XzamTwPm5PTyxP+FBLXsYuvqHjdrn1JJ6KSIi\ngry8vFbnczVHPyuPa0QMHjwYg8FgG5UhIyODl156ifvvv59hw4YRExPD7NmzmTFjBt9++y379u1j\n4cKFLiuPQedLfHCE3Tqj0YhRm0O3gNY9EOOsOI2pqKjg6aefrjNsWPXDPc8++yx33XUXGzdu5Ouv\nv2bdunWEhYUxevRol5THmdSKcijKQ01rZHQuRYN1kPtHUakvj0BySXinhvK5mivyuqVfPuvjSC5v\n3LiR9957j2XLljFw4ECnlcETyPVNtBdN1Ung/NxuyR2IxrSkXnr11Vfr9N5pSx43Y3VAQADLly/n\n7Nmz3HzzzTz11FPcdttt3HPPPWg0GpYsWUJeXh433XQTn376KW+88YZMNNeI+Ph4srOz6dKli+2/\nN954g71795Kbm8uzzz5LfHw806dPZ9WqVfTu3ZsffvgBwPbrnSdSy81UrHiSirefRs2u6uKmGfpb\ndA8uQTvlCXQzXkX38JvoHlqCNelaN5e2fWivuSQuPo7k8rp16xg6dCibNm0CJJc9idRJoj1pSb1U\nnc/u4nF3IqDqGYjly5fXu61Lly6sXLmyjUvkvaZNm8b8+fPp2rUrgwYNYs2aNXz99dfMmjWL0NBQ\nvvrqKzQaDVOnTuX48eNkZGQwZcoUoOq21okTJygoKHDasHrOouZmwLmzduuU+AEoOh+Uzr1qrXT8\ngSdRv/aaS+Li40guZ2VlcejQISZNmgRUdfHIyMiQXPYAUidVyag8h7HgJEkduri7KKIVWlIvjR8/\nHnBfPntkI0I4z8SJEykoKOCVV16hoKCAnj17smzZMjp37gzAkiVLeP7555k0aRIBAQGMHTvWdrG8\n5ZZbeOqpp0hLS2Pt2rWNvUybU4/utP2tve4BlMiuKB3kjpQrtddcEhcfR3I5MDCQ22+/ncmTJ2M0\nGhk9ejQrVqzgxIkTkstuJnUSFFpMfGk+BcdPsSF9PzcZ4txdJNFCLamXqkdjuvHGG1mwYEGb57M0\nItqRSZMmcdttt9VZP3XqVKZOnVrvMQMGDODdd98Fqvr51R4abNy4cYwbN841hW0F9WwO1p3f2JaV\nnkkoGrnj4EwXSy6J9m/y5MmMHz++zrCHzc3lCw0fPpypU6d69QRR3shb6qRyayXfZB7ET6vjqk69\n0Li421SWqcil8YVrTJo0iZ49e9ZZ72i9VD3Yw9VXX83EiROdX9AmSCNCeB0176TdsjQghBBCeILN\n2Uf4+MQeoGo0qj5hMS59va156S6NL0RjPO7BaiGaopbW/PKive6PbiyJEEIIUeNocZ7t7/yycy59\nrVOlhewvOm1b/nN/GXVKtC1pRAivox74qeoPv0A0vYc1vrMQQgjRBlRV5VRpoW159dHtVKqumwDt\n73s32v4eGNaJIJ+Wz30gREt4dCPigQceIDk52bacmZnJtGnTGDx4MBMmTGDLli1uLJ1wB1VVUXNP\nVC34SoUphBDC/VRVZfXR7eSYSuzW7zmT2eSxeaZznDUbbcvnys18kfErHxzfxQfHd7E5+wiqqtod\nY6oop7TCYlseE123f70Qruaxz0R8/vnnbN68mcmTJ9vWzZw5k4SEBD744AM2btzIrFmz2LBhg8wT\ncTGxlNn+VKK7ubEgQgghLnY78zNIPXuaQ0W55Jjqzph8tCiPIRFdGzx+V8Ep3j6+nUCdnmeGTiDQ\nR88XGfvZlHXIbr/VR7fTNyyGmX1HoVU0dl2lumgC6BoQ5ryTEqKZPLIRUVRUxEsvvcSAAQNs67Zu\n3crJkydZu3Yter2eBx54gK1bt7Ju3TpmzZrlxtKKNmWqqTg1iZe5sSBCmtGY4gAAIABJREFUCCEu\nZkUWE2+mbsGK2uA+GRfMZ1RbvrWMD49XNRbOVZjZmZ+BVtHYGhA+5wcNKbdWAvDr2Wx252dyrtzM\nvrOnbHGu8I1q9bkI0RIe2Yh48cUXuf7668nNzbWt27t3L3379kWv19vWJSUlsXv3bncUUbiJaqz1\nS48hyH0FEUIIcdEyVVhYcnCrrQER6ReIXqtjXOdEiixlfHB8FwA5pmKM57sd6bU6tIqGsopyMkrP\nkl1ptIu5+uh2u+VxsYl09A9m+aGfbOuWHfzRbh8FCFR8nH16QjSLxzUitm7dSkpKCp9++inz5s2z\nrc/LyyMqyr61HR4eTk5OTlsXUbiJWlFO5Xsv2JYVQ6AbSyOEEOJitSHrICdLq+4yaBUN85N+h67W\ncOMKsO74LorLy3hk6zrb+slxg/gsY5/t7kJjruh4CeH6AAw6H17/9Yd69/HV6NC6eC4KIRriUY0I\ni8XC/PnzmTdvHr6+vnbbTCZTnXW+vr5YLBYuZsnJyaxfv77ebYqi8PbbbzNsWPNHMEpNTeUPf/hD\nnYmZ3E0tN1Pxr0dqVigaCAp3X4HaoYsll0T7V53LiqLUeSC1Jbm8bds2pk6dSkpKirOLKhrhqXVS\nmVrB//KO2ZZvih9k14AASAzrCMfrHrs+vXm9J+KDwonwq/qhrH+HWP526WSe+KXue5EQHAUX99cg\nr+GqemnVqlXOLmqzeVQj4rXXXqNfv35cccUVdbbp9XqKiuxnZrRYLPj5OT5Cj9lsts3y1xImk8nu\nX3fGefTRR7nnnns4efIkhw4d4t1332X16tW27cHBwc0+V5PJRK9evfjkk09c+/4Yi9F+vRwUhcpr\n7gH/4CbjKEcPoKs1EkX5HfMpt5SDpbz15WkFyaWGy9MmudRGMeqL4+x8ak0ueVIeeUKcRx99lJkz\nZwLw5Zdf8vbbb/PMM8/QuXNnDAaDQ7kMkJCQwDfffOP282oOqZMaLk9r6qSM0rNsP5NBb/9wfrTU\ndLW+rdtgLg3rWidmB0XPwwmjyC2rGq1pc24amUb77zA6FDro/SmttB9pCaB/SEe7mNoLvnTGB3Tg\n0ohu9NCHkpuZJbnkBXFq10uffvopq1at4r///a/te2xL6qVPPvmE4uJit13fPKoR8cUXX3DmzBkG\nDx4MQHl51RfEr776iunTp3P06FG7/fPz84mMjHT4dbKzs8nOzm51edPT01sdw1lxQkJCKCsro7Ky\n0q6Ll6PdvbRaLcXFxRQX1x1lwlENnVfH4z8TlVP1E0321q8406lfk3E6Ht9LdWe2Xy+bSmVGNtD8\nz7DYamHt4e300YUSqHFe/1HJpYa1RS61dQxnxrmQM3LJ087RE+KUlJRgtVoJDg625WNru8F6wnk1\nROqkhrW0TlJVlXfLjlOilvPjBbcX1JxCUvMa/uJX3en2OjpiNERQeb4x4K/UdEPaZz3LVmoaJv10\nYUSeKSe1wP6OSYjiQ5Fa9b1oWGUIwXlGcql6bckl74pTVlaGoigUFRXZfiBvTb3krnPyqEbEqlWr\nqKiosC2/9NJLAPzlL3/h1KlTLFu2DIvFYuvWlJKSwtChQx1+nZiYGEJDQ1tcTpPJRHp6OnFxcRgM\nBo+JExERga+vL4mJibZt1c+VHDx4kDNnzrBixQosFgsvv/wye/bsoaKigj59+vD0008THR3Nhg0b\nWLBgATt37iQrK4sJEyawaNEi/vGPf5Cbm8ull17KggULCApq+KHmRs9LtaLb+Z5tsWNoIFG1yttQ\nnMDsHVWHh8fSa2CSw+/PKwd/IM9aRrmvhhE4rxuU5JIbc8nBc3L2e1y97CytySVPzSNPiHPkyBF8\nfKp+OKiO40gux8XFsWPHDh544AG2bNnC9u3befjhhx3O5YbOC5z7BVDqJOfXSSdLCyk5eLhO2fy1\nPlzWd2CrzisuLo5efr3ZuvMT27Z7BlyJUs9zDn8oieSX/BMkdehMQkh0nTggueQtcQ4cOABgF6Ol\n9dLq1avR6/XcfPPNLa6XWnp986hGRExMjN1yQEAAAF26dCE2NpaYmBhmz57NjBkz+Pbbb9m3bx8L\nFy50+HX0ej3+/v7N2lc1G1ELTtutU8rKMBTn4F9sQG9p+YRnDcVROnRE0TevfLX5+PigKIrduel0\nOj755BMWL15MeHg4vXr1Yty4cYwcOZK//vWvlJSU8Mwzz/D666+zaNGiqtc/H6M6sf/zn//wj3/8\nA6vVyp/+9CfeeecdHn744SbLYzAY7MqiVlZQ8e7zcK6gpnz5J9E18VkYDAa0ZSWogCa4Q7M/u2qF\nFhN51qr5JU6bSsDgvEZEc3OpvjwC1+ZSS/MIPD+XWsIZMZwZ50KO1EsNaatzbCifq7kir/0C41qU\nz3q93vaFrPq8HMnlxYsX4+fnh6Iodl8YWprLtbXmi0xDPPn65q110tbMvfWWaXyXPk77f/bZpAks\nP/QTA8M72777XGiAf1cGRNc/54S7c6kxbVEvNVUngfNz26CJa/F5Vf+wUfucWlovAbYuUa2tlxz9\nrDyqEdEYjUbD4sWLefLJJ7npppvo2rUrb7zxhksnmlPNRiqWzwaz/a1KHdATYDc0Pb5CwxqMo/dH\nd+/CFle2F+rfvz+jRo0Cqlqbt99+O7///e9tSTd58mSWL1/e4PEPPfQQ/fpVdTmaOHEi+/bta94L\nF+dT8dHbNcOylhTU2UVN349aVoriV3+laduv+EzVHwF1fxUxV1awLPV/GCvKuTfhCtvDaNW+yzla\n55i21FAegYtzycl5BG7MJeExGsvnaq7I64r2Ui96CLdc37y0TtqZn1FnXc+gSC6LinfGKQAQ7R/M\nk4N/67R4F5Pm1Eng/NxWD2xAve9Fr8tnZ/LoRsQLL7xgt9ylSxdWrlzpptJ4r9jYWNvfBoOB2267\njfXr17N//36OHTvGgQMHiIiIqPdYRVHo1q1mZujAwEC7LmeN0RzYgpqT3uR+6qnDKN0HN7yD2QRF\neVXliYits3lX/kn2n63qt7np1CFu7V7T3elESQGbc9Nsy0MiukBps4ov6uGuXBLC2SSX2wdXf47l\n1krMlXU/2xm9RuDvxC+PQoD31Use3YhwN+X8ryYX3iIzl5VxPD2d+Lg49C0YHaqpOK255Vuf2kPj\nGo1GbrrpJsLDwxkzZgwTJkzg2LFjvPXWWw0eX33brdqFQ5M1RHOqatZNQiLR9DjfSFA0aHoPp2L9\nP+H8SBXqqaOoUd3qBqiwVh2Sm25bpUTH1dkto1b3qG+zDnF9twH46arK/PzuL23b7uk+nP6hndp8\nyNGG8ghcm0vOziNwXy4Jz9FYPldzRV77dWpZd6aGXOy57I7rmzfVSaqqsvbYTr7PrnkWIi6wAydL\nCxnpIzNEe5Lm1Eng/NyOG3Qpvl6Sz64ijYgmKHp/lJhL7NapRiOmAhNqdByaVvTzc1YcR2zbto38\n/Hy++OILW1+6//3vf05PtOD84yj5mQBoeg9HO2Ky3Xbt9TOpfOd5AKwpX2FN+apODJ2iEBF/Gbpj\nW6tWKApKZBfb9krVSrGljPRz9t2kNp46iE6j4ewFtzYTg6NbfV4tVV8egeSS8E4N5XM1V+S1s798\n1nax5rJc3xr2xclf+TbrkN26W7sPJULjx5FDhxo4SrhLU3USOD+30Tv/OZTavKFekkbERSY0NBSj\n0cjXX39Nv379+Omnn1izZg2BgfXP/tyiZC0tIiS/ZiIeTZ/L6+yi6XgJav8rse7b3GAYRVXpVN2A\nAIjojOKjB8BSWcFfd35Bbtm5Osd9mlG3D+AAXVidyYBE67RJLgnRBiSX24fmfo6njcVszzuBqqps\nz0snXGOkoyGEbGMR2cZi/vi/NXVi+2l1xPgHo1qk25poG95QL0kj4iIzaNAgZsyYwbPPPovZbKZ3\n797MmzePOXPmkJeXV2f/+oaZa0zlzm/w+eE9wqpXhEajhDXw8HtwrX59YR3t7lZYd29CzbQfUk93\n06O2vzPOna3TgPDX+WKsqH/qzu66+ie0Ey3n6lwSoq00lsu5ubl19pdc9kzNrZMW7v6Ks7l5qMCH\nx/fgVxwCQHreCYrL7SfZGtmxO/3DOtE1sAMGnS9GaUSINuIN9ZI0ItqRSZMmcdttt9mtu/DhdICZ\nM2faZk2sNnnyZIxGI4mJiaSkpABVD/hc+PzArFmzGi2Deni73bKmW58G91UCw2r+9g9C07PmgWg1\nO82+EWEIRDHUjHW87+wp29939ryUzgGhdAkMY8aP79b7WkGK8yaYuxh4Qi4J4QyTJ09m/Pjxdvnn\nSC4DREVFkZqaitFoJDIykpSUFLthECWXXc9ZddKa7zbwryM/4RceylVvPm23X9ykq+yWf9OxB3f0\nGCaNRuF0kyZNomfPnnbrWlIvpaSkkJqaSqdOdZ/3bIt6SRoRwqlUc1nN374GlN7DG945uNZ8DSEX\nzDwe2MF+OahmObP0LF+ePGBbvjwqHq1G02i59DS+XQghRPtWqaosO/KTbfmZpN8Rpg9g15mT/JB1\nhArVyqDwWGL8Q1BQGBzRpZFoQgiPbERkZGTwzDPPsHPnTsLCwrjjjju49957AcjMzOSpp55i9+7d\nxMbGkpyczIgRI9xcYmFzfk6IvNgBhF47Dd9GZkpUOvVA6XMFFOejHXat3TZNwqVUHNuD5cxp9P4B\n6C6baNu25fQxu31rNyB6hURxuMj+Nl9icDRKhfySJIQQF6vcsnOsMNl3kY00BKFVNFwWFe/UOR+E\nuFh4XCNCVVUeeOABBg4cyMcff0x6ejqPPvooHTt25He/+x0zZswgMTGRDz74gI0bNzJr1iw2bNjg\n0knnRPOouRlw/jkFi18QaBt/kFnRaNCNv6f+bf5BVF73Jw6nppKYmIjv+a4D5dZKUmpN/HNv7yvs\njru9+zB+ykmjX4dOBProyTOdo5s+mOOH3TvhnHBMubU1UwEJIUSN9JIzvPDrRrt1XQM7oFXkDrUQ\nreFxjYj8/Hz69OnDvHnz8Pf3p2vXrlx++eWkpKQQHh5OZmYm77//Pnq9ngceeICtW7eybt066ZPq\nASpWP1vzt4/zh/TLKi1iwa4NVKpV80fc3n0ow6Pi7PbpFBDCzZcMsS13DgjDaGx8FktRV27ZOT47\nvo1Cs4lwvwBiA0KZ2LV/m/QNTj17mn/s/xaA27sNpuF7WUII0bhTpYW8sLvuEOI3xg1yyeup5wqp\n/OY/4OOH9rf3oOh8mzym0XhmI5VfrwBVRTtuGopfgHMKKoQTeFwzPDIykpdfftn20FpKSgo7duxg\n+PDh7Nmzh759+6LX6237JyUlsXv3bncVVzSgwtf54yevPZZia0AABPm0fLIY0bg3j25lX0EWJ0vP\nsvtMJp9n7OdIcd0Rl5ytrLLc1oAAeOfELpe/phBtQVVVVGNJ1TCMqkpA4SmUg1uxHq87JLVwnl/P\nZtv+DlJ8uCIijtGdetE71DXzBlm3fY6avh/1yA4qXpvR6mE3rQe2oh7dhZq2G+uvW+y2qYW5KCdT\nUSrLW/UaQrSUx92JqG3MmDFkZ2dz1VVXMW7cOJ5//nmiouxnigwPDycnJ8dNJRQAakU5XPBgc4WP\n8xsRJeVldsuBPvoG9hQNeevQT+zIy2BgeCwPJIxs8M5Cvrm0zrozZecgxDUztVpVlWKLqc7zLEK0\nB6pqpXLt31CzjkJkF7R+QXQ/PziEJTAChkxxcwnbr0JLzZ3oW/zi6Netr93IWs6iVlZQ+c1/UVO3\n2m84mwMdWt7dWs1Jt/1t3bwWzaAxKFodamEuFf+Zg05V6Q9Unruacl9/MHRu8WsJ4SiPbkS89tpr\n5OfnM3/+fJ5//nlMJpPdlOBQNUW4xVL/3AANMZvNreriYjKZ7P69qOOYStCtfQHlgjkbKnz9nVoe\nc2UFmaWFdtt1lWqzPkdnvT/18aZcKik380tuOgA7809yqjCfDnr7W+NGo5Hvzdn1HA35pSXNPldH\nzqtStfKPg5vJNBbWu32Z8RCkHOL2boMZHtGtWa/f0rI4EsfZ+dSaXGoXdUl7jlOUi0/W+eey8k66\ntAuAN9VJroxTWmHhjLmUTaeqZpfu7BeCVtE4rTxlOSfR7vgEpazqBxclP7Pe/ctOHkb1qztPUZPn\nVXIGpeA02szD1P6ppyx1O+olA1Eyj6CrdZdDu2cTZic3SCWXXBfHk8pSX5zmxlNUL5h686uvvuLx\nxx/n5ptvpri4mL///e+2be+88w7vvvsuH3/8cZNxjEZjnXF0Rf2i07cRmnsYpVZ2VPgaONXjSip8\n/FAVDRW+/kSf2E50Rkqd4/f+Zjo4sf/8/vKz/FRu/yv1VEMP9ErLZqFOTExs1a9R3phL+dYyPiw7\nYVuepO9KR639HaMiq4X3yo7Xe3x/XRiX+0ZRplZgqdWtDECvaFv8WaRXnONry6mmdwRu0HflnFp3\nsqeOWgP+int+E7kYc0k0k2oloDCLwKJsojN21LuLMTCCo0OmSB45gaqqnFMr2Fdxlv0VZ+22xWsD\nuUYf67TX6nRkMxHZv9a7rULni+78xKd5sQPI7u7YCJI+ZefovX01mgvq2Wq/Xj6N4DPpdDn8nd36\n4tAupA+YILkknKapXPK4OxFnzpxh165djB071rauR48elJeXExkZSVpamt3++fn5REZGXhimUTEx\nMYSGhra4jCaTifT0dOLi4jAYWt5tx2PjdIomeHPdhoGvuYSeu9bZlq09hqIG2SeXNaob50bfDdm5\nTj2vA3kWON8lP9YQwvhOCfQPjXE4DkB6enqLy3Qhb8qlX4tOw9GaRsTZYB1XdUkgt+wcob4G9Fod\nu3JPwMn6X8MnOABTSBArj9f9MqRB4YGel9M7OMqh8zJXVrBs92fNPs+PzBn1rg/1MTC3/zX1jrbi\nqve4etlZWpNLHluXXCRxKlUrJ0rP0tk/FF9NTWNas+dbtPs+rTfWui496V+YT3pELM2ryZrHm+qk\n5tifn0ne6Rwu696nyTirj6ewo6D+Cuzarv2oyDnrlPPKOHqIMGPVj1pqcDhqx+5VGzVarIlXoEZ1\nw7r+ZTS56YSrJkITE+uN09D7oxzbY9eAUH30UGFBOf+bb+LJrWgyD9q2n43sgXbcNNDqwEPqJPC8\nXPKkOJ5UlvriNPf65nGNiMzMTB588EF++OEH2/MP+/btIzw8nKSkJJYvX47FYrF1a0pJSWHo0KEO\nvYZer3dKn0iDwdCu4ig56YTmHCJo99qadb2GoQSEYN21sc7+mqN1v0z6DB2PITQcsnOdel7nrP/P\n3nmHyXFVaf9XVR2me3LWRI000kgjjbI0kpwkBzkHsFivwWQWA8YkA17bfLABvPbasGZZjGENi8Ek\n4wA2loVzlGVZVg6jkSZpcs6du+p+f1RPd1eHCdJIGtn9Pk8/T1e6dav69r33nHvO++qJY+Vpudy+\nbNMJlzPdOFvakl9TeenoMcO+N3sa8KDxbk8TALcv28SQ0N+zBHx/9TWoQuOJxj0c6G9nd38ru/tj\nL9lrCH5+7G3W580hOymFDdlzJvVc+7tCqx4bCyq4Ye5KPJqfdscQ9+9/cdLPPehzoZkVUsdJ6J8p\n/7N4mI62NNOe8YNSzpONe3ihtYZz88v5ZMXa4H5/TxPxlvpr0rJ4Lb+EcmvGtBoRZ0ufNBm0OQb5\n1XF9nFkmLyR7nHIO9LfFNSC+XnURs61p1HQNnFR9hBAoz/2cqjCxU6XqfJS1V0ed688tQnQ3IXud\nWMe5X2R9hBD4974Q3DZ96vu62Krbgf+XtwMYDAhhstBSuYnKlOnnsXs/taWZWs5MqsuJlDPjjIgl\nS5ZQVVXFXXfdxZ133klrays//OEP+dKXvsSaNWsoKCjgjjvu4JZbbuGVV17hwIED3HvvvWe62mc9\n1H2vYnrl95RG7FfOux4pPRf5vOsRrUfB70O01sY0KgBIyZz0PdscgyQpZrInQVk36NXj8zJOAevT\nBwEvtdXSNNIXtX/MgAC4b19o0m43Wci16YNSWgwWrIsKF1CZoScLPtW4hw6XLjK4vVs3CrIUK5Ph\nzmp29Ae/3zB3JYosY5ctZFjj/85zUrP5YuX5ABwd6uZXtboCrdPvJT3RPhI4hRjwOmnwj+AZaGOR\nUkSGVR9sX2jVQz+2ddUz5HWSnZRCv3uUL9TrzIF7M/N4rHQ+5/R0UN3XSW1aJovTyvnInHLyrCm0\n1TedqUea0djVE1p5PDbSS3Fm/KiDVwK5DwD5tjS6An0SwIKMfNzTkcPkGkEOMyAApLzYeVqSxaYb\nkL1taA37o49LJogRTS6aD0NPyBiSsnQTU8TTtEgQjCRwBjHjjAhZlvnZz37G97//fW688UZsNhuf\n/OQn+fjHPw7AQw89xF133cXmzZspLS3lwQcfTAjNjUFoqNufQTu6EymnCMlqR66+Cikte9zLtM4m\ntFd+H/tgahYAksmCVFaln2+2QAwjQqo6D6mwHFzuqGORaHUM8IPdW7GZzPzHmuuwjcOlrQlBV0AJ\nezIGRwJGjPrc/KUpRIP8yflr+e2xHeNe4/CHyArSIibmdpOZK0sWk2rRzYS3uxqCRsQYej0OJsMR\nMuTRB/aylCyD8nimxU6aOYnhCEYuCYlz8ucGJ295tpD37d3uJq4rWzaJuyaQwNTh9vu47/AruFU/\nNLST1nKA/6i+DrNszAU6ONCBJASfrw9Rt3Yk2RkxW3m+sIznC8sAuExWmJeqT4onlxH0AURYWp0I\nrOnUDHTS4RwixWxlRU4JZllBE4LDg50ArMwu4dxZ5fzPodcASDVbkacrP89lJBAhIw+puCL2udaQ\nN1d9+idRh01A9rzzkaRB1DBSCdEZWp2VZoVUtCWTGSw28EYYQwmq8wTOIGacEQG6VsRPfhL9pwMo\nKSnh0UcfPc01OjsgHd2J9s4zAIj+jkCXK6Fc8olxrwunkAuH6TP3IMnRybJS+GpDRh7mz/zHlOv6\nclstAnD6fRwd6mZZdvwpZ5/HgSvAgz07JWvK9/qg4/BAZ/B7vi2Vc/Ln8ueGXfpkKA4unjU/+D18\n9acsJYsvLDo/aEAAMb3/3e5RijEuib7RcYw+j4PcpFQaR3oBqAtoT6RbjecqssydKy6jc2gAZ3Mn\n8xcuQLaYkSWZZHPI4LSHGZ/PtRxKGBEJnBQ0IWh1DDDLloZFMQ6Pna5hw39m2Oemz+1glj3EvFPk\nHGF1Xxfr+jpI9Ye4+9/JiQ5YMs88maYZhQP9bWxpPhjcfuz4Xg4Md3E4TPfhI94VbCquNDhJVuaW\nGvokr6pOW52EayT43X/dN0iaU4kUb4VgnNXUMeQ37cRU9yax06dBudg4dku5JYi2o8aTTOYJ75NA\nAqcKM9KISGDqSO8+hulI9OqAGJqEQFiAOlUoJlrmbaC09mWk/DKkjDhLx1kFyMsvQrhGUS799AnV\n1xM2GB8f7afdOcRQhIfFpEG+UHm8OTRAzE4Zf1UlASPaHYP85ug7we1PVaxDkqS4cdpjuKIwlAi4\nJreMrS2HGPK6+UTF2iha2OQYq0jv9bdQbC1lrJSW0QF+X7cz7v0yLdExmFnWZJJSJGqkLsyygt0S\n7XGzR9zbq/qjJn8JJDBZPHN8P1tbDnH+rHlsKlrI210NSJLEBbPmMeiJprr8l13P8o9zVwW3P9Vw\nmEK3UWOlLi2LvhgTSku8yWcCAPz00OtR+8INCIDm0QGeatwbDCcDqEjPQwlbefBq02dEhK9EiJSM\n+AYEIEX85qZP/QBkvV7qS48iWo5g8oettCaHJTCbLSjnfwQpzxhgrFz1BUTjAUR/O9ouPW9Cm111\nok+TQAInjcRo+36Aa4TZMQwIAOEcjrk/HNqOADtOWg6D+RUULF2DLYbnbAySJKFc+LGJyxUCTYio\npWRNaOzqDcW6hnubIpEjW+l1eQCwKiZyEuFMk4YmBA8ceAV/gOVjQXo+5Wm6YegZZxWiSLYbWI6S\nzRa+s+IKPKqfXFtK1PkWJbRaZVVMwbKb1dBkqtMV3Q5zklKwyAopZisbC+dHHZ8MIo2ILtcIJVPI\ny0kggTFoQrC1RafsfLOzjjc764LHtrYcimnoAjzWoDPZSUKQ79YNDb8lCZPXDRn5NK+6CIaiBVEt\niZWIk0Z4ThfAdbOXkm6xGVSixYQuk8lDDPWGNiYai5LC+kqrHSlMcE7KyEO0hJKjSc/F/Nl7Jry/\nlJyOVHUeAPLaq8HjwmeyQYKO9X0LVdPoco1QYE+LKw57JpEwIt4HkMZbbXAOjXutuuv54HcRyH8g\nqxAp6cSy/F1+Lw/XbQevh78ebkND8J0VVxgme9s6G2Jem6SYSA3Edw573Xg0P72aJ3j8ypKqGfkn\nmqkY8roMOQVzwnJjcpNS6AkIBH5+4bkU2NM5PtpPnmKjrymagSktxirAGCxyqBu5sqQqGFrgEH6E\nELj9vmBOSzi+sngDs+zpU3+wMMiSxLeWXsIP9+tGdHfCiEjgBBG5EhqJgYDysV0yIWQpGGI5hiva\nG1ECE1Ztwz9irtKT/5c5h9ld+zYjPg+DXhcZFhsVqbmkOhJhKLGgCi0oijmGZMmEI4Y+TDiuLl3C\nFSWLAd3RVZGex9Ghbj67YP201U006XkuzpQczOPk8QFIpZVIpYsQg90oa68yHszIM56bNXV+Lslq\n1/MuTkIMLoGZj7807ePFthouLlzADeWrJr7gNCNhRLwfMNwb/5hzBHXbX5DXXq0nZoVBDPWgvfF4\ncFtdfRX0jkaWMGns7m3mFzVvhXYE+vzX2o9yZWkVb3XW0+YY4GB/e8zrr5+zgg0Fukf60WM7eKsz\npAlikmQuK47m2v4gotc9isvvw6+ppFtsZMXwiLn8Pv77wCvB7XxbKhcXLghuf2bBen55ZBvnzSpn\nda7OLlKUnIHT6WRIiv37xMPq3FKebNyDANbllVEz2MGRwS4cwsd39j0XNdkaQ0Ycz+5UUZ6Wg0mS\n8QuNNscgS7IKAYJhTYNeF83qKAx1YXVbSTZZKEvNThikH0BIR7Yc83GIAAAgAElEQVTjb9yLcvEn\nkMImckIIRo4fYuFQH8dSM1EDSf55tlSWZxcz6tOdGZqqkjuiUVRaQs1oDz2uEQ4PdiILjSs7moLl\n2dJygt9n2dO4c8XlhnokxLziY1tnA7+ve9ewL0OyjGtELMos4JrZSwz7bl28kW7XCMXJJ65zEAkx\nogvYuVLzmMgElMxWTJtvi3lMrroA31AfIx0tpGXnYKm+ctrqmMD7Cy+26f3Ey+21XDN7KbaIeZxf\n02hXncjD3RRJ2Qaykalg0Otit6+Pmub9CEWixJzKZEqaFiPixz/+MV//+teno6gETgBSgLpTmCyY\nv/BfiO5mGOpGfeERALR3tyCl5yAFPGNj0A5tC36XV26C3BLoPbGBTROCx+qjBepAT6Le3dtCi8Oo\nIFqelkv9cGgVZYwyFKKpXNMttsSkDz3ZMDJWeHFmAQtTckkNEyd6u6s+yJgkIXH7sk2khLF4lKfl\nck/1h6alTmkWG/+2+mqEEGRY7cGwj1YtvoeswJZG0jQlBMqSTHFKJk0jfWxpOciWFj08LtWcxIfL\nloWYqOpCHDgfLV/NxsI4rCoJvK8gnCMoW37Bgr4OTK4hBOB/9iHMH/8XhHME0V6HdmQHBcfe41ZA\nA76+ciOaLPO9lVca2JfGJv8L0vJYMauMmoFODg92kun1GO4p5UyGmyyBWHiiYXfUvhXmbNrCclKu\nLq3i2bAw2OUxiDmsimn6VyUDK6p+88lRSUtJdrT1H6a5pobKykqkU6A7k8DZj8iw45bRfioy8g37\nHm3cyX5PBxzTaYHvXH4ZZamxc0cHPU529DRRkZbHnDBHR7/bwb8dCESl9OhO6WzJymZb2YR1nBYj\n4re//e20GhFdXV3cfffd7Nixg6SkJK644gpuu+02LBYLra2tfPe732Xv3r0UFRVx5513cu65U5OU\nfz9BqH6U97bqG0nJSJYkpOIKtIhkMjEYHfIkukN5CfIFN8BJ8Gh3u0aCWg6RGPV7GPWHBtksq51Z\ntjRuml/Nd3Y+E9yfExZDGvknmJ36wWVlGvQ4g2FJzx4/EHX80EAHhwIJh5XHhlEUhY6wMLaPlq82\nGBCnAuG/3dLs4qBeRDi+WHk+JlnGq6pUpOdFHT8ZLM0qjNLBGPG541LZvtxeGzQidve2sLu3mevL\nlsdc1UlgZkAM9SBcDuRZZVO6Tju6E7n1CAY2/Z4WtIZ9qE//T9T5MnBubztv5hVH0bdGIiXA0T/L\nFcr/US7/JyT79At/fRCxJnc2Hy1ZzpEjR7i2eDENjgGunb00GFo2hqVZRae8LsLvC9Kr+qdpFTWB\nBMbDYEQ7b3EMRBkRDaPGca9+uCeuEfHI0XeoGewkSTFx39rrsSom3KrPEPUxVUyLESFiCKacDL76\n1a+SkZHBH/7wBwYHB7nrrrtQFIVvf/vb3HLLLVRWVvLkk0/y0ksvceutt7J169YPpFaE1lGP+qew\nZKwwVhApjHYQQAx1I0ZCwl5a3W5Eoy6AI81bMWUvv1f18/fWwwx4nJhlhdyk6ITbSCQpJm4sX836\n/LnBfd9beSWPHtvBurw5hgTsqsxCbqk4l8NN9ZQWFbMyjC/7g4SD/e1BvvPJoGbYmMC5Jnc2G04w\naflEsSK7mFJ7Js1O48rTipySU3bPS4sXUWBPx+n3ogkRxQSVKVn40qILeGeghVfaa+l2jeDwebCb\nLPxt11ZUSeJRv5evVV0Ys3yt9SimZx9ikd8H6TfDvKWn7FkSiAGfB//v/h28LqSPfRcpP7bAV0w4\nBmPujmVAjOHizmb6FqyZsOji5Aw+53Sxoi4kJibNTbSNk4FHM3pfx8amC/Pnc1XAY+8eDIVIXl1a\nRab11E/q1VdDWkq+k1yJSCCByWAsjHIMjzfsYdTnQUJiSVYhJSmZjIZpOgH8uWE3a/PmkGK2IoRg\nW1c9hwc6ybelUhPQUnGrfl5rP8rFRQv4913P0ecxMsoBXFu2FLomJuaZFiNiOsNMGhoa2L9/P9u2\nbSMrS/c+f/WrX+W+++7j/PPPp7W1lccffxyr1crNN9/M9u3beeKJJ7j11lunrQ5nC9Qn/8uwrVVf\nHdpINS7jiqPv4T/6XsxypKKpTzLf7Tkel1WpIjWXoyOhlY/cpBRW5pRy/ZzlUecWJWdwx/LLousk\nScxPzcVv6qUyqzgqDvCDgCGva9IGhEmSmSUlkZySEhRts5ksXF16+un/JEniC/PX8519z522e5pl\nhZU5ITrEc2eV0+d2IBB43B6664+Tm5TCmtzZvNKuK9u2OYeYXb+Xuw7r8de/do5AHCNC1O5Aco1g\nAsSrv0OzfwExjcyRCYQghIZoPQqOIcjWDU+pry3oBVbf24rpqi9OvrwJGOqGzBYeWLCS9SODXHZc\nZ8xJM1n43IJzJi67fg8rDm837JNOw4T2/YpwqlaAtXllMc+bl57LvLRcRnweLilaeBpqBuJgKN8v\nsRKRwOlApBEhEDwXYJDb0nKQInvsfJ/HG3bxqYp1/F/tdnb2HI95zrs9TSzIyDcYEFmShfOLKnCh\nUpVZQO10GhF33nln3GNerzfusakiNzeXX/7yl0EDYgwjIyPs27ePxYsXY7WGFqZXrVrF3r17I4v5\nYCCsgWmyCW3xBcFtyWpHWnwe4tBbsa4MnbegGnn5JVO+dXeY6E44Mi12vjj/HPbUHGTxgkoyU9Ni\nnpfA+HD5vdy+4y/B7dkpWdwwdyUA9++PpvP9+sINDB9vp3J+JfYZEF9rN1n4aNJc/ujWmbi+uXTq\nbexkoEhyMMHMKZz0BBwd4Yrngx4nc17/c3D7M42HOTrUTWlyZlS+hvCEQvWk0X7Ux+7Bn5IDK//h\nVD7G+wJiqBfRfgw0FZCQyqqQko2sXEJoutEAiJYjqH//FQBmoHjWQpTRaIrUSd1bCERdgC3MnoXi\nHiIpEOqpAf9XtZ6U0kV8v2Idkqbif+hr4PNgcQ4jv/kEqqyAyYy8dCMAyvP/x/yBPkyHrPgQ0Gck\nIZDP23xC9fwgY9Tnpnawm6XZRTzZuCe4f35aHlWZhbhihNkqksy3An3K6ciVE8IoB+ePIbCZQALT\njUiWski0hSmd51iT6Q0YBO90N7EiuyTKgLCbLDgDKxetjkHu2fu84XiqbGFj/jzsdjvOSbJ+TdqI\nqK6uPqFjU0Vqaqohx0EIwe9+9zvWr19PT08PeXnGWOrs7Gy6uk5sgDlbIYRANBpj4x1p+STJRt5x\n5ZJPIqrOB48T/DEMPVsKUlHFCXXCAzGWv6yyic9XnoskSdgkE9aE6NcJo3nUGAp0x/LLguFedyy/\nlNfaj7Iip5Sd3U0U2NMptKUxzNRYlU41UmUzD6z60IwwasaQarYiISEQdMbwUP9o/0vkJaXwr6uv\nNmhl4HVHnZvAJKCp+H//73ofFICUX4bpY/8vuC00FfWP/4Hoju0xy+o8YtjWju7C7/ohymWfRZog\nV0oc3QkBKuN+eyr3L1yKDJSbk/hG9XV8KdxYVEwo19yC+tQD+n32vRq6504970wGbADR3R/yBTeg\nrLp03PokEI3H6nfxbgxv6ecWnjPu2HRaiTacRqfZySZWJ5DARNCExoF+nQzEqpiozi3jYH87m4oX\nYlVMHOrX8yD9qorN4ePC8qXce/jl4PVHh7oN5dlNZh5Y/xHqh3u4b9+LMe+ZKk094mPSs7wPf/jD\nUy58OnDfffdRU1PDE088wa9//WssFiM3s8VimdaVkLMBoukA6tM/MexTTdGJs5IsIxWWT/v9/Zoa\ns9P/VMU6ytNyJ23BJhAf4YmD/7HmOkO+yJzUHOYs0JkVxlhJEu98cpAlmXRLEoNeF1taDnJFxPFb\na/ewNzOXzkUXUBRODRkwIlTZhBKI2Zbyy05Ppc9mOIYMBgTohA5C05ACTg/RdCiuARELEgLRcgSt\nZjtK9VXjnqtufTj4vU3W0GQZDbhx2aYoymvAQPs6HrSKtSgmBbweRN0uSEpGXrh20s+QQAixxpI7\nll16WvIcJoLWcgRx/BCivc64XxlfIyKBmYuMrqPIWi9i9aVIkoTQNBAa0gxxeh4f6eeZ4/sY9XuD\nauvr8ubwsXnGHK3zZs0DQoxx+bZUbl+2KWggNEUkXI+lLpen6aGAdcPRZDsZ0tTb9ZTf2l//+lfu\nuecehoeHAxUTSJJ0Sjiv77//fh599FF+/OMfM2/ePKxWK0NDRvE0r9dLUtLUmGc8Hs9JTbrGlldj\nLbOejnJMbz5JpA/meMECDjbuZmHGLJZmFp7S+rSELaHNTs6k2TGAVTZRZk3D6XSe8fdzqsqJhVPV\nlt5sPwaAjIRVndhImGnvaiaVE1lGiT2DzP5OrmyPFj1cODJAxcgAO9sbyAyLtTZ5nEjAcM5cklOS\nMQ924Vt1JXSOI/Q4RZxMW5pJ73vsekn1Ib3wf9EHhYarvxvsaeDzYA44RITVjuSJ/fxfW7mR61vr\nKHaOUOx2YvX78A324ZngfZmECPaVvkBISorJSoZkjv2uFZuB/99/1ZeROuuRAvoAPsVMfXo5xRWL\nsNkC3uiNN4Es45PkSQt/nY190qkoJxYpy83z1pNvCoVTnKm2LXU2Ynr6gaj9niUXgSTNqP/adJQT\nC2dTW5oMPF3NlNa+DLXgf+tx/Fd9GeWFX4I1Gf8Nd4LZOnEh01Sf8DJ29bWwrbcJIQRNjn7DeUmK\niatmLYz7O4SXk6SEZoato0ZCiauKFgXLqM4qMRgRiiSxKqOI+W7blJ9tykbET3/6Ux555BEqK0+t\n8Nf3v/99HnvsMe6//34uuUSPfczPz6euzugR6O3tJTc3d0pld3R00NHRcdJ1bGpqOukyTqSc+W4P\nY4upruQc3l12Nc9623D1N7O9X6dtvdBSwHzTieUjTFSf42pIkK5aTac6KR0zMk3HjDRhZ+r9nOpy\nwnEq2lKjf4Q6r87VbJMUao8ciXPV+OVMV33eL+WMlbFWpJLV1kjpiDFkbCSjiNTBNmRgZ+026vv6\nqTJnYnENsrBXV/FWFTNHitdBMdNqQMD0tKWZ9L6zO2sw9TbHPNa2601cKbmk9R9njJyzP6uM7I7D\nUefWpOnib4+X6pS836x5jzl+H/vba/nbnr9zrjmfXCWJjK5actoP0j+rEln1kd1+yOBskQMT1mRN\nHtfplTtnHdnth3Cm5tE87IfkOfonDDPpPUfibBrfvGHsBNmSlSuSiqG9n5r2/qhzT/c7n//eY8EJ\nkgB8lmR6i5fRm7ngjNTndJUTjrOpLU0IIZi39ynDLtOWB/UvPg8t777GaFZpjAtPTX1UoTEgvHgb\nG/iTqw4/0Qb1XCWVBaZ06mqPTqouaphRHs5ydr4ln4weFzUBHbAh1RiP+WlTCZXbnibJOUB72zn0\npOTqIXvJE+usTNmIyM3NPeUGxE9/+lMee+wxHnjgATZt2hTcv2zZMh5++GG8Xm8wrGnXrl2sXr16\nSuUXFBSQkXHiKpYul4umpibKyspC3qjTWI7pkDUYk2u22XjcGz1Qv+7t5NolU1tej1WfZscAu/tb\nKU3OpMUxgEdT6XF7IJDTvWphVVTuw5l+P+OVA9Pb2U5nW9LMCr+qe4dGb2gAXZxVSGXZxP+3mfzO\nz3Q5scowvReiiHQpCh3Xf5uS9Fy0X34LGUGhy8Gr3i7+wSJh3vnH4LmqYg6WM1budOFk2tK0vG9V\nxXfsPdoHR8lbds7E5TiGAAExFIG9TYdJrt8WfU0AZYefj9qXdtXn4JffDG7/smIFZUN9vJVrXFkd\nNel9/2zHIOuaDyLlO1nSVocUMPRsjj4kLZo6qyY9i+rMYi6YNZ8ie3rU8SAC41syEPnP+6D1Saf6\nv9vlHoFDumNwc/lKKtPzo845I33JQCdmp94Pi5xi/JtvRwJygZQZ1LdFlgMf3LY0Lkb6kA+8jjLS\nHfeU0rxsxPzJzW2n47kerXuX3UPGPMYsi53S5EwyLDauLKycUKcmVl1sextxqaHx7YK8uXy4xEg7\nPV9TOXLMRa/HwSfnrqG88zimACV7YcPbADhTcqibBHHIlI2I1atX84Mf/ICNGzcaWJLWrJmYU3sy\nqK+v56GHHuILX/gCK1asoLe3N3isurqagoIC7rjjDm655RZeeeUVDhw4wL333jule1it1mlJ9rTZ\nbKe1HKH6Uf/+K0RfSHm3bU4VCE/UuRqCY65+FmcWYJpEQ4xXn0cPvUSve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PN26PySqXm5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\nHye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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import qtrader.eda as eda; reload(eda);\n", "eda.plot_train_test_sim(d_rtn_train_1)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The curve Train in the charts is the PnL obtained during the training session when the agent was allowed to explore new actions randomly. The test is the PnL obtained using strictly the policy learned. \n", "\n", "Although the agent was able to profit at the end of every single round, \"Convergence\" is something that I can not claim. For instance, the PnL was worst in the first round than in the first one. I believe this stability of the results is difficult to obtain in day-trading. For example, even if the agent think that it should buy before the market goes up, it doesn't depending on its will if its order is filled.\n", "\n", "We will target on improving the final PnL of the agent. However, less variability of the results is desired, especially at the beginning of the day, when the strategy didn't make any money yet. So, we also will look at the [sharpe ratio](https://en.wikipedia.org/wiki/Sharpe_ratio) of the first difference of the cumulated PnL produced by each configuration.\n", "\n", "First, we are going to iterate through some values for $k$ and look at its performance in the training phase at the first hours of the training session. We also will use just 5 iterations here to speed up the tests." ] }, { "cell_type": "code", "execution_count": 43, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 42 s, sys: 140 ms, total: 42.1 s\n", "Wall time: 43.1 s\n" ] } ], "source": [ "# improving K\n", "import qtrader.eda as eda;reload(eda);\n", "s_fname = 'log/train_test/sim_Thu_Oct__6_133518_2016.log'\n", "%time d_rtn_k = eda.count_by_k_gamma(s_fname, 'LearningAgent_k', 'k')" ] }, { "cell_type": "code", "execution_count": 79, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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juRt3aue//vorhg8fbkj7Pvvss9BoNDhz5ozdvz+2c/s48ty7o9Zo583F67ll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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "\n", "f, na_ax = plt.subplots(1, 4, sharex=True, sharey=True)\n", "for ax1, s_key in zip(na_ax.ravel(), ['0.3', '0.8', '1.3', '2.0']):\n", " df_aux = pd.Series(d_rtn_k[s_key][5])\n", " df_filter = pd.Series([x.hour for x in df_aux.index])\n", " df_aux = df_aux[((df_filter < 15)).values]\n", " df_aux.reset_index(drop=True, inplace=True)\n", " df_aux.plot(legend=False, ax=ax1)\n", " df_first_diff = df_aux - df_aux.shift()\n", " df_first_diff = df_first_diff[df_first_diff != 0]\n", " f_sharpe = df_first_diff.mean()/df_first_diff.std()\n", " ax1.set_title('$k = {}$ | $sharpe = {:0.2f}$'.format(s_key, f_sharpe), fontsize=10)\n", " ax1.xaxis.set_ticklabels([])\n", " ax1.set_ylabel('PnL', fontsize=8)\n", " ax1.set_xlabel('Time', fontsize=8)\n", "f.tight_layout()\n", "s_title = 'Cumulative PnL Changing K\\n'\n", "f.suptitle(s_title, fontsize=16, y=1.03);" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "When the agent was set to use $k=0.8$ and $k=2.0$, it achieved very similar results and Sharpe ratios. As the variable $k$ control the likelihood of the agent try new actions based on the Q value already observed, I will prefer the smallest value because it improves the chance of the agent to explore. Now, let's perform the same analysis varying only the $\\gamma$:" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 41.4 s, sys: 140 ms, total: 41.5 s\n", "Wall time: 42.8 s\n" ] } ], "source": [ "# improving Gamma\n", "import qtrader.eda as eda;reload(eda);\n", "s_fname = 'log/train_test/sim_Thu_Oct__6_154516_2016.log'\n", "%time d_rtn_gammas = eda.count_by_k_gamma(s_fname, 'LearningAgent_k', 'gamma')" ] }, { "cell_type": "code", "execution_count": 76, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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2j2/v3r2Ijo62+X5bU1PP8bRp0/DEE0+YNX9WVVXhvffew6xZswAA3bp1w08/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\npbRACnQohWnfDi8tKdDpvNOFwhToFGiZTgc6FB6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diueeey7q2F27dmHFihUZnb+hoQGV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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "\n", "f, na_ax = plt.subplots(1, 4, sharex=True, sharey=True)\n", "for ax1, s_key in zip(na_ax.ravel(), ['0.3', '0.5', '0.7', '0.9']):\n", " df_aux = pd.Series(d_rtn_gammas[s_key][5])\n", " df_filter = pd.Series([x.hour for x in df_aux.index])\n", " df_aux = df_aux[((df_filter < 15)).values]\n", " df_aux.reset_index(drop=True, inplace=True)\n", " df_aux.plot(legend=False, ax=ax1)\n", " df_first_diff = df_aux - df_aux.shift()\n", " f_sharpe = df_first_diff.mean()/df_first_diff.std()\n", " ax1.set_title('$\\gamma = {}$ | $sharpe = {:0.2f}$'.format(s_key, f_sharpe), fontsize=10)\n", " ax1.xaxis.set_ticklabels([])\n", " ax1.set_ylabel('PnL', fontsize=8)\n", " ax1.set_xlabel('Time Step', fontsize=8)\n", "f.tight_layout()\n", "s_title = 'Cumulative PnL Changing Gamma\\n'\n", "f.suptitle(s_title, fontsize=16, y=1.03);" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As explained before, as $\\gamma$ approaches one, future rewards are given greater emphasis about the immediate reward. When it is zero, only immediate rewards is considered. Despite the fact that the best parameter was $\\gamma = 0.9$, I am not comfortable in giving so little attention to immediate rewards. It sounds dangerous when we talk about stock markets. So, I will choose to use $\\gamma = 0.5$ arbitrarily in the next tests. *In the figure below, the agent is trained using $\\gamma=0.5$ and $k=0.8$. [the next chart is not used in the final version]*" ] }, { "cell_type": "code", "execution_count": 29, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 40.8 s, sys: 331 ms, total: 41.1 s\n", "Wall time: 41.6 s\n" ] } ], "source": [ "# analyze the logs from the in-sample tests\n", "import qtrader.eda as eda;reload(eda);\n", "# s_fname = 'log/train_test/sim_Fri_Oct__7_002946_2016.log' # 15 old\n", "s_fname = 'log/train_test/sim_Wed_Oct__5_110344_2016.log' # 15\n", "# s_fname = 'log/train_test/sim_Thu_Oct__6_165539_2016.log' # 25\n", "# s_fname = 'log/train_test/sim_Thu_Oct__6_175507_2016.log' # 35\n", "# s_fname = 'log/train_test/sim_Thu_Oct__6_183555_2016.log' # 5\n", "%time d_rtn_train_2 = eda.simple_counts(s_fname, 'LearningAgent_k')" ] }, { "cell_type": "code", "execution_count": 163, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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MoijEx8ebla1cuZJvvvmGs2fPWlytLyxufXx8rP6AzmOP4x4QEGDTcklJSSiKYvW4Qm4y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\n5OTkjKntoqIiMjNjw2qSxeVy0dTUREVFBSbT6MW1T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BwaLdIxCi/UD3bzTnugv6TrjCyQ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\niIiIiIgU+39nM8oZxzYlbAAAAABJRU5ErkJggg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import qtrader.eda as eda; reload(eda);\n", "eda.plot_train_test_sim(d_rtn)" ] }, { "cell_type": "code", "execution_count": 103, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 1.91 s, sys: 13.9 ms, total: 1.92 s\n", "Wall time: 1.96 s\n" ] } ], "source": [ "# analyze the logs from the out-of-sample tests\n", "import qtrader.eda as eda;reload(eda);\n", "s_fname = 'log/train_test/sim_Fri_Oct__7_003943_2016.log' # idx = 15 old\n", "%time d_rtn_test_1 = eda.simple_counts(s_fname, 'LearningAgent_k')" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 1.8 s, sys: 9.08 ms, total: 1.81 s\n", "Wall time: 1.82 s\n" ] } ], "source": [ "# analyze the logs from the out-of-sample tests\n", "import qtrader.eda as eda;reload(eda);\n", "s_fname = 'log/train_test/sim_Wed_Oct__5_111812_2016.log' # idx = 15\n", "%time d_rtn_test_2 = eda.simple_counts(s_fname, 'LearningAgent_k')" ] }, { "cell_type": "code", "execution_count": 105, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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gc0OHDmXy5MkYDAaLy8k6nY5XXnmFf/3rXyiKQmhoKCkpKURGRhIXF1fkMnFlKzxTp6oq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\n8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AChLcRk9kCrsjxzWpxPSkREROMZA1uZatcx9dayIWUIqbE7LUi5xf6gVxP9W9prKUJ3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\nTicyMjJ6vTahA9uJE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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# compare the old with the data using the new configuration\n", "import pandas as pd\n", "df_plot = pd.DataFrame(d_rtn_test_1['pnl']['test']).mean(axis=1).fillna(method='ffill')\n", "ax1 = df_plot.plot(legend=True, label='old')\n", "df_plot = pd.DataFrame(d_rtn_test_2['pnl']['test']).mean(axis=1).fillna(method='ffill')\n", "df_plot.plot(legend=True, label='new', ax=ax1)\n", "ax1.set_title('Cumulative PnL Produced by New\\nand Old Configurations')\n", "ax1.set_xlabel('Time')\n", "ax1.set_ylabel('PnL');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In the figure above, an agent was trained using $\\gamma=0.5$ and $k=0.8$ and its performance in out-of-sample test is compared to the previous implementation. In this case, the dataset from 07/16/2016 was used. the current configuration improved the performance of the model. We will discuss the final results in the next section." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 4. Results\n", "\n", "In this section, I will evaluate the final model, test its robustness and compare its performance to the benchmark established earlier.\n", "\n", "### 4.1. Model Evaluation and Validation\n", "```\n", "Udacity:\n", "\n", "In this section, the final model and any supporting qualities should be evaluated in detail. It should be clear how the final model was derived and why this model was chosen. In addition, some type of analysis should be used to validate the robustness of this model and its solution, such as manipulating the input data or environment to see how the model’s solution is affected (this is called sensitivity analysis). Questions to ask yourself when writing this section:\n", "- Is the final model reasonable and aligning with solution expectations? Are the final parameters of the model appropriate?\n", "- Has the final model been tested with various inputs to evaluate whether the model generalizes well to unseen data?\n", "- Is the model robust enough for the problem? Do small perturbations (changes) in training data or the input space greatly affect the results?\n", "- Can results found from the model be trusted?\n", "```" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "One of the last questions that remain is if the model can make money in different scenarios. To test the robustness of the final model, I am going to use the same framework in very spaced days.\n", "\n", "As each round of training and testing sessions takes 20-30 minutes to complete, I will check its performance just on three different days. I have already used the file of index 15 in the last tests. Now, I am going to use the files with index 5, 25 and 35 to train new models, and use the files with index 6, 26 and 36 to perform out-of-sample tests. In the Figure below we can see how the model performed in different unseen datasets." ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 5.83 s, sys: 35 ms, total: 5.86 s\n", "Wall time: 5.94 s\n" ] } ], "source": [ "# analyze the logs from the out-of-sample tests\n", "import qtrader.eda as eda;reload(eda);\n", "l_fname = ['log/train_test/sim_Thu_Oct__6_171842_2016.log', # idx = 25\n", " 'log/train_test/sim_Thu_Oct__6_181611_2016.log', # idx = 35\n", " 'log/train_test/sim_Thu_Oct__6_184852_2016.log'] # idx = 5\n", "def foo(l_fname):\n", " d_learning_k = {}\n", " for idx, s_fname in zip([25, 35, 5], l_fname):\n", " d_learning_k[idx] = eda.simple_counts(s_fname, 'LearningAgent_k')\n", " return d_learning_k\n", "\n", "%time d_learning_k = foo(l_fname)" ] }, { "cell_type": "code", "execution_count": 84, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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YTCZUVVVBpVIxlRdRO7FYLNDr9YiMjBQX8/EV1mmi9sc6TdR5eFOfAzZosOnV\nqxeWLFmCe+65B1OmTIFarXbYr1arERMT06xzVVVV4dKlS21QSiJqSkpKSrPranOxThP5D+s0UefR\nnPoccEHDvn378Oyzz2Lr1q3iNolEAolEgiFDhmDbtm0Ox584cQLDhg1r1rlVKhUAIDY2FmFhYb4r\nNBF5VFNTg7KyMrH++RLrNFH7Y50m6jy8qc8BFzSkp6ejpqYGr7/+Oh577DFotVqsW7cOGRkZmDNn\nDtavX4/PP/8cWVlZ2Lt3L3bt2oXPPvusWee2dXWGhYX5vHWEiBoUaTX4peg8jGYz5AYz+kPZJkMN\nWKeJ/KOsrIx1mqiTaG59DrgBg2FhYVi/fj2OHz+O8ePHY/r06YiIiMBf/vIXREdH4+2338bHH3+M\njIwMvPLKK3j99dcxYMAAfxebiOz858JBbM8/i1+KcnCsssDfxSEiIqJWCrieBgAYMGAAPvroI7f7\nMjIy8NVXX7VziYjIGyW6agBAiFyJaHmIn0tDRERErRVwPQ1E1PFVG/QAgBuTB2F+3zF+Lg0RERG1\nFoMGIvIpvdkEvcUEAAhXBPu5NEREROQLDBqIyKc0Bp34d4QyyI8lISIiIl9h0EBEPqUx1ol/RygY\nNBAREXUGDBqIyGdK66rx1smfxMfsaSAiIuocGDQQkddMFjOu1FTAIggO27/POw292TqfQSaRsqeB\niIiok2DQQERe+yTnAF46shVbrp5y2F5lbJjPcF//0VDKAjKrMxEREXmJQQMReW1PcS4A4JvLxx22\n60xGAMDQ6GRc271fu5eLiIiI2gabAYmo1c6oi1Cmq0Wd2QAACJIp/FwiIiIi8iUGDUTkFZPF7PC4\n1qjHmhM7HLYFyxk0EBERdSYcnkREXqk26h0el+trXY4JZk8DERFRp8KggYi8Yr94GwCU6VyDhiD2\nNBAREXUqDBqIyCv2i7cBwKnKApdjOKeBiIioc2HQQERece5p2F10weUYzmkgIiLqXBg0EJFXqo26\nJo/hnAYiIqLOhUEDEXnF1tMQoQhCmFzl9hgOTyIiIupcGDQQkVdsPQ1RqhCsGHGL22PCFe6DCSIi\nIuqYGDQQkVc0xoaehtigMPxx2E1ICY9BhCIIfcJjcHOPNCSGRPq5lERERORLXNyNiLxiG54UrgwC\nAPSLiMOK4e57HIiIiKhzYE8DETXb4bIrKNBWAbD2NBAREVHXwKCBiJqlSFuFd07vFh9HKhk0EBER\ndRUMGohoZtwOAAAgAElEQVSoWexXfg6SKTAqtpcfS0NERETtiUEDETWLwWIS/35m1FREqUL8WBoi\nIiJqTwEZNBQUFODRRx/F2LFjMXHiRKxYsQI1NTUAgL179+Luu+/GqFGjMH36dGzatMnPpSXqGvTm\nhqBBJWUOBSIioq4kIIOGRYsWITIyEjt37sQXX3yB8+fP49VXX0VpaSkWL16Me++9F3v37sXKlSux\nevVqnDp1yt9FJuo0jpXn4ZvLx2G0mB22G8wNj5UyBg1ERERdScAFDdXV1RgyZAieeuopBAUFISEh\nATNnzsSBAwewadMm9OnTBzNnzoRSqcT48eORmZmJDRs2+LvYRJ2CyWLG/8v+BZuvnMS2q9kO+/T1\nw5OkkEAuCbivDiIiImpDAffLHx4ejpdeegnR0dHitsLCQiQkJODUqVO45pprHI4fPHgwTpw40d7F\nJOqUqo168e8DpZcd9tmGJyllckgkknYtFxEREflXwAUNzk6cOIFPPvkEixYtglqtRkREhMP+yMhI\nVFZW+ql0RJ1Ldf1qz/YEQcCH5/bh2yvW4FzFoUlEXZbJadgiEXUdAf3rf+jQISxevBh/+MMfMH78\neLz33nsQBKHV59Xr9dBqtT4oIVHnUlpdJf4tCAK0Wi1KdTX4tThX3K6QSL2qP3q9vumDWol1mqjt\nbco7hV9KLuDe7kPQ1qu0sE4TtQ9vfqMDNmjYsWMH/vjHP+Lpp59GVlYWAKBbt25Qq9UOx6nVasTE\nxHh17sLCQhQWFvqsrESdxVlTQ9Cg1+tx+vRp5JqqHY7RGazbAwnrNFHb26E9DwDYXHQGdwantOm1\nWKeJAk9ABg2HDx/GihUrsHbtWowfP17cnp6ejo0bNzoce+LECQwbNsyr8ycmJiIqKsonZSXqTAqK\nzgH5RQAAmUKOtLQ0XCo4Ddj9dlukEqSlpTX7nGq1us1//FmnidqWIAjA4bPtdj3WaaL24c1vdMAF\nDWazGatXrxaHJNnLysrCunXr8PnnnyMrKwt79+7Frl278Nlnn3l1DZVKhZAQLkxFXVu5rhafXzyM\nmvrJzxJIcLaquGG/QYtNhadRrq9xeJ7BYvaq/tTV1fmmwI1gnSZqW7VGQ7tej3WaqH148xsdcEHD\nkSNHkJubixdffBEvvPACJBIJBEGARCLB1q1b8fbbb+PFF1/E888/j+TkZLz++usYMGCAv4tN1OH8\nXHgOh8uuNnrMjgLXlkWTYGmrIhFRgKo2tn3wT0SBLeCChoyMjEbHSycmJuKrr75qxxIRdU4VuloA\nQKhciZigMFypqRD3KaUyGJglhYjqaQyumdWIqGsJ+JSrRNQ2NPXpVftGxOL2XukO+/4y7k5/FImI\nApAgCDivKfF3MYjIzxg0EHVR1fUthxGKYEQoHBMoKmVyl/UYQuRKAMD0XkPap4BEFBC2XM3GN5e5\niCpRVxdww5O6ujJdDXYV5WB8fB90D4n0d3GoE9PUT4COUAYhXOmadT1MrhJXgZZAgmdHTcPl6goM\n7ta9XctJRP51Ws3Up0TEoCHgrDmxA2W6GvxadAFvcIgItRGzxYJaU33QoAhy6WkAgFCFEuV667yH\ncIUKkcpgDI1JbtdyEpH/2eYzJIdE4X+GXI/80hLUFZX5uVRE1N4YNASYMp01vWW1se1X0aWuqaSu\nGu+c3iU+DlcGQSlz/SoIlavEvyPc9EQQUddgm/80NCYZkcpgmILCcAkMGoi6GgYNHZBZsOBw2VUY\nzCZkxPV2GXtO5IkgCHjn9C7k1TasrJ4QHO5wzLj4FABAmKIhaAh30xNBRJ2fyWKG1mRdo8FdjyQR\ndR282+yADpddxXtnfgUAqA1aTOPEVGomrckoBgwxqlDc3nsIeoVFAwCeHjkVJysKMLF7fwCOQUNo\n/SRoIupa7Hu93c19IqKug0FDADHUTzptSmFtlfh3kba6rYpDnZD9Ak1z+mdgSHTDHIXk0Cgkh0aJ\nj1OjuuOngnMAAF0zP5tE1LkUaTXi3+xpIOramHI1gNjGjTbFNoEVAPRmY1sVhzoh+wWaIhTBjR47\nNDoJPUO7AQDGJ/Rp03IRUfswmE04UZGPI2VXUV6/wKMngiDgbyd/Eh9zbhNR18aehgBS7bTiplmw\nQCZxjetq68eXAkAdgwbygn1g2tQNgFQixVNDb0C5vhY96oMHIurYvrh4FD8XWnsQg2QK/HX8XZBI\nJG6PvVJTCQsEAIBcIkW80/wnIupa2NMQQJwzJnkarlRjdxyHjZA3qu2ChnC7OQueBMuVDBiIOhFb\nwAAAOrNRnOTszrGKPPHv18bOctuIRURdB78BAojzUCNPAQGHJ1FL2YYnhciVkEtlfi4NEflbY8Ni\nbUkT+oTHIFTBZAhEXR2DhgCitzgGCe56GnQmI67UVIqP60wMGqj5bDcInNBIRIDjPCdnhVpr0o2k\nkCiPxxBR18E5DQFE7xQkOAcRALDx0tFGn0OdU6Vei4/P70eVoSH70dXaSkxI6Iu5A8ZA2sxhA1qj\ndShCaDOGJhFR52IRLC7bPPU0GC1mlNZZFxtNDIlo03IRUcfAoCGAuAQNbgKCnwvPOx5jMcEiWJp9\n00gd057iXJysLHC7fVBkAsY1M7uRbeJ8iFzh0/IRUeB79/SvLtucE3DYFNdpINRPgk4MiWzTchFR\nx8CgIYA49yy4CxoiFEEuLUN6swnBXHyrU1PrtQCAYJkCvcOjcUZdLO4rqtN4epoL26THYBmDBqKu\notqgQ6G2CkfKr7rsO1x2FTUmPVQyOfqFxyFfq8bY+BSH9YCSGDQQERg0BBTnIMHgZniSyU33cp3Z\nyKChk7MFikmhUZjeayjOqH9o0XlsPQ38vBB1DQW1VXjxyBaY3fx2AMB5TQnOa0octuXXqsVV4FUy\nObqpQtq8nEQU+DimJYA4T3x2DiJMFrPYUjzMbiXfdSd3euxips6h2m4Cs/P6Cp5uBtyxTZxnTwNR\n13Cuqtjjd4RUIkGoXAm50/DWnYXnsfVqNgAgMTjC4zoORNS1sKchgDinWDVazA6P7ddxsF9kJ1+r\nxsZLRzFv4Li2LSD5jS3DSYQyyCXzUXMCxoJaNTRGHepsw5PY00DUJdh6KVUyOf4n/Xr0CouGwind\n8r8vHMRPBeccttkWdesbEds+BSWigMegIYA4D0cyuAQNDTeHyaGOKfAuaMrarmDkd7Yf/nBFEFQy\nx2p7rqoEn+ceRmJIJM5VlYitiiFyJW7pMRghciVePfYDdHZregRzIjRRh2AWLNCbTQhpYaBva1SI\nVAajX0Sc22PcpWAeGBmPkbG9MDY+pUXXJaLOh0FDgFDrtThR4Zgdx7mnoVxXK/7tHDQEyfhP2RnV\nmQz4y/Ht4lC1CGWQy1CBcn0tfsg/4/b5FkFARlwvh4AB4PAkoo5AEAS8fuwHXKmpxPLhN6NXWLTX\n52jO2izOQx4B4IGB4xETFOr19Yio8+KchgDx9eXjLtuMZseg4VRlIQBrC7JL0MCW407pREUBrtY2\nLOZnS32YYDc8zVk3VYjYKlmmq0Gh1jW7EnsaiAJfrUmPi9XlMAsWfHT+vy06hzi0sZGgIdxp3yOD\nJwdUwHC1phK/FOa4NKQRUfti83SAOFnhmoPfeXhSdn3QcE23RMicJq4FseW4U7JfzG3+oPEYUD+8\n4IkhmThYegUGswmbrpxweM7UnunI1ZRib8lFaAw65NeqXc7b0qEORNR+7FdrLnIT/HsiCAIuVZej\nyqhDhd7aQx3upjfBxrmnITUywcuStq0Xj2wBYA2ibut5jZ9LQ9R1MWgIED3Duok9CTbG+jkOdSYj\njlXkobz+y7+3my5qpdPENuoc7IcWjItvWMAtWhWKm3ukAQAUUhm+tFspPEIZJN4gaIw6lOlqHM4p\nlUgQGxTW1kUnolayX5PHuRGpMYfLruLdM7sdtjXW0xCldEyp6jxvyp9sGd8AYNPlEwwaiPwocL4Z\n7OzatQvLly/HuHHj8Je//MVh3969e/Hmm28iNzcXSUlJWLBgAaZPn+6nkvpOqFzlss3WFftJzn4c\nKL0sbo9WuXYbmyzNT7tJHYd91iRPnPdFKBoyLNUY9ag1NWTdmpkyDH0j4hCpDG6D0hKRL2mcMqNd\n0JS6DCVyFiJX4tfiCw7bFFIZ0qOTPD6nmyoE03qm40RlAa5L7B9QKVYr9Q1z+QRB8GNJiCjggob3\n3nsPX3zxBVJSUlz2lZaWYvHixXj66acxbdo0HDp0CI888gj69u2La67p2K0P9mM1e4RGIa9WjTPq\nYqw68DXK7CZAA0CUynrDNzqutxhMuFsIjjq+arusSZ4474tQNqzlIEBAaZ21p2Fy9/64la10RB2G\nfU8DALx2zLtFHTOTBuHG5FSEypVNznvLShmKrJShXpexrVXoteLftjSwROQfATcROigoCBs2bECv\nXr1c9m3atAl9+vTBzJkzoVQqMX78eGRmZmLDhg1+KKlv2YYipUV1R7DMOt68XF/rEjAADT0Nc/qN\nFrd503VNHYdab53T0FjQ4L6noaEnwbYKNOcxEAU+i2DB+aoSnKwowKXq8lada0JCX8QEhXboRBmV\ndkEDwN4GIn8KuJ6G+++/3+O+U6dOufQoDB48GFu2bGnrYrVYncmA9ef24Vh5npj5ZnC37pjdd5TD\ncbabfqVU1mTXsO0mMVShFHsbGDR0Pqcri5CvtU5ibmx4UrSqYTyyXCKFUiZ3m/mEGZOIAt/nuUew\nveCsw7a4oDDc138MTELj3/PZlYXYUb9IW3xwOHo4ZdnriJyDBq3JgFCF63BeImp7ARc0NEatVqN7\n9+4O2yIjI1FZWenhGf733dVTOFaeBwAo1FaJ/78+cSDi7NJm2oYnKWVySBoJAKKUwQ6Zk2wToA1m\nDk/qbP5bclH8u2dYN4/HhSmC8NuB45BdWShOlo4PDkeIXAGt3SRCWw8WEQWmSr3WJWAAgFFxvZDW\nrbubZzgaEBmPcr0WFbpaZPUeGlBzE1qqwuAYNNSY9AwaiPykQwUNgG+6JvV6PbRabdMH+kBedYXb\n7UWaSoQKDRmP9PU3dxKLAInF8TVOSeiP25LScLjiKvqGxTiU3XaswWxqt9dE7aOw1hpkyiVSpIfG\nN/rvOzy8O4aHW28qbMddnzAAm/OzxWOkFotfPiN6vb7pg3xwDX7+qSMTBAGvnWyYszAmphdu6D4Q\nCqkU3ZQhzf58P5CSIf7dVnWiPet0mbbaYXtlTTXChQ5360IUsLypzx2q5nXr1g1qtWPOebVajZiY\nGK/OU1hYiMLCwqYP9AGD3v2X9plLuTDIS8XHtTrr2PWaKg1MgmMmpLqKKlyoPodIAOWlebAf5aox\nWN8PrUGH06dP+7Ts5F9F9T1Tg2WROHvG/YrPjak0OvbAlRUU4XRxjYejO7b2rNNEbUErmBxa1QWN\nFuV1VwEARf4qlB/Z6nRJneNv/tmLF1ArC5yF54i6kg4VNKSnp2Pjxo0O206cOIFhw4Z5dZ7ExERE\nRbXPWM+Tl/XIKat22R6ZEIu0+L7iY8nxK4DRiPiYWBgtZpwrbVjIp19yT6TFuE4MB4DLBcDxwkoI\nUinS0tJ8/wLIL/aXX4HuknWYWlpyb6TFpnh9Dk3ZZey5XCI+HpDSF33DvAuwfUGtVrf5DX171mmi\ntnBOUwqcb0iV2i+pJ9Jie/uxRJ61V52OjIyE9sh5h+1xyYlI65bcptcm6kq8qc8dKmjIysrCunXr\n8PnnnyMrKwt79+7Frl278Nlnn3l1HpVKhZCQkKYP9IFQlWM+/GCZAnVmI3SwOJTBWD/BLUSpcki/\nCgCxYREey2s7v9FibrfXRG1vz9lL4t99uyW06N82PNjxOd1Cw/3yGamrq2v6oFZqzzpN1BYqKh3T\nqzb2ve9v7VWnBaUMRqee933lV9AvOgEJwRFtXgairsCb+hxwQcPQodbJWyaTdWLvDz/8AIlEgmPH\njiE6Ohpvv/02XnzxRTz//PNITk7G66+/jgEDBvi51J5Z4PiFF64MQl2dUcy/b2PLfqSQuv6T2KfP\ndKaonwhtEiywCBZIJQGXRZdawD5wTAlvWe+A86quzJ5EFLiK6zQOj5taxK0rqNS73sycrSrG0we/\nxTuT7vVDiYi6toALGo4fP97o/oyMDHz11VftVJrWM5odew0iFEEoqat2WLRHEAS77EkywGkBm8bS\nbSrtbgz1ZjOC5QwaOgPb52FK4sAWn0PlFICGuVl1nIjajyAIOFx2FaW6GkglEkQpg3Gw9DJuSE5F\njdFxMmIo66vDavbOLIIAaSfIDkXUkQRc0NAeNudnY5IiDX0iYtv8WvYtxsNjekAK65ecxtAQNNhP\nfFZIZZA5fRE2drNnn6O/QKtGv4i4VpeZ/M9ksX4mFNKWB4FKp54G58dE1L5Oq4vw7pndLtsv1VQg\nqX4dHwBI75aIWDdrrXQ1WpNB/FsukTr8VurNJvaeErWzLtksfUZTgleOfd+m1xAEAaV1NQ5fevMG\njEN4fa+BfU+Dwa43QimViSs+28gauXHsEx4DW4iRqynzQckpENgWcZJLZU0c6VkQgwSigGJbq8dZ\nlaEOtfW/FWPieuOx9Os7xRoLrVFt0uF4eb74OC4ozGF/nd1vKxG1jy59V2G0mMU5Ab726YWD2FnY\nkPVhUGQCQhVKRNSPU62262kwWhoWZlNK5Yh1+nJsTLBcicSQSBRoq3CpurzpJ1CHYBTnuPiup4GI\n/MsWGKikcgTLFVAbGsbsa+uH4nDhMquPLx7GVaM186BMIkWkKhiFdvM+tGYDosHeGKL21CV7Gmzy\natpuJWn7gAFomLBsm5+gt5igr1/FWW+3mrNCKkOMl93StuNrGhn/SR2LbXiSXNLyoFYlZdc9USCp\nNVqDhnBlEB5Pv15sRAIaJv2GyrlyO+A4NClUrkSI0/tSVtc515whCmRdOmgocspW4SvuVq1W2oIG\nux8JWwYl+3LEBoUhSObdzV6wzPplqq1fVZo6NosgiGN3W9MTppK1TS8aEbWM2JsgVyI5NAr39h8t\n7jPX13lOgHYV4iZo+MfpXfji4hE/lYioa+rSQYPO3DY32QandRaAhrHp4XaZkGyTofNqrSteyiVS\nJASHAwBGxVoXc7un36gmrxdSPxlMyzGenYLZbrKfvBXDk1ozH4KIfM82PMk2BMldZrwQBXsanIUq\nlGLjmL3v8077oTREXVeXHvRcZzI1fVALOK/BANhSqTquuWCbDJ1fHzQkhkSKk55/N2g8bu+VjkS7\njBqe2FpgtCY9irQaRKtCOJ69AzPZBZ2tvfFXSeXQW0y4s8+I1haLiFqp1tjQ0wA49jzbcHiSK2tP\nA4dbEvlbl76zrDO3Tcu8c75twHVOA9DQ01Cqs47N7B7SsMKlXCpDUmhUs67XEDQY8cyhbxGlDMYz\no6a5dOf6it5sgtZkQDdVYK5W2tHZp+lVtHKxvqdHTcWVmkoMi05ubbGIqJXEnob67+ZIZTBUMrnD\nvLa4oHC/lC2QRSiCEMxgisjvunTQoGujOQDuehpsQYNKJhdbf6uN1olvtkxK7lqdmsM5OFAb6rCr\nMAe39BzcovM1xiJY8NKRLSipq8bKEbeiV1i0z6/R1dkmQQOt72mIDQrzKhsXEbWdhqDBOjxJKZPj\n0cHX4URlAQAgJSzGofGIrOsUXZ80CAVadaPH1ZkMOKsuxqCo7s1ev0Gt1yJIrvB6HiFRV9W1g4Y2\nmtPgrqdBaXfzF64Mgl5XA41BB0EQxCCjsZWfG+OuBebLS0chlUjQKywag6ISWnRed9T6OhTXWdPg\nfXHxCJYMucFn5yYrh54Gzksg6hRqjDpx3lmYXVrVgVEJGOjD7+jOZsWIWxAbFAa1QevxmE/O78cv\nRTkAgGu6JeLx9OubPG9BrRrPH96CaFUIXhg9HbJW9uoSdQVdupbUtWPQoJA2xGe2HgWNUQetyShm\nyglvcU+D+1aSzy8ewZoTO1BSf5PvC/ZpXY1uJnxT65l8NBGaiALDwdLLeGrfl+JjXzbkdHa2Bjel\n1H0bpyAIYsAAAKcqC5t13i8uHoUAAeX6WpQyfStRs3TpO5ITFQXYW5zr8/NW6l1bRKLtxv/bMihV\nG/TiECWg5T0NzsOT7FunBQi4oClt0Xnd0dgtSucmsyz5gH0w1pp1GogoMHxz+bj4d2JwBJKakeCC\nrGzBgqeegJamGrefR2KfsY6IPOvSQQMAvH9uHwpqGx8r6a3K+m7UhOBwzEwZjjn9MjAytqe439bT\ncKW2wuEm3D6zkjdiVKFioDAzZbjLKsL5Pnx9Grv5GgIYNbQFE4cnEXUqan1D49CDqddCIpH4sTQd\ni6I+82CUyv3vY4W+tkXnNQoN37NMV07UPF0+aAB8v8ibrachOTQKt/YcjClJAx0mtNqCBr3ZhB/y\nzzRsb2FPQ6hChaeG3oDH06fglh5pLvvzfBk02AU5HJ7UNowWDk8i6iz0ZhP0Fmur9n39R6NnWDc/\nl6jjkEukYg9DbFAY7u470uWYj87/t8nz5FSV4qtLx8SUt4Bj40wdF0YlapYuPRG6gW9bfWxBg6eU\npAMi44Gr1r+PV+QDsHa9tjR7EgD0CY8V/57TbzT+dXaP+NiXcxo0dsOp7AMI8h2TYL9OA4MGoo7M\nsTe55d/xXZHzekM3JqeiylDnsKjb5ZoKj883CxasPfkzTquLAADFdRosTJsEwDFLnXP69TqTARZB\nEBfhIyIr3pHAt12TZosFVQbrjXU3pfugIa1bd8Q7pcFMDIkQF3ZrrYy43nhk8GRMSOgLACjX16LG\nTRrYlqg2NLTUVBv1sDiNBc2vVeMf2b/go/P/hcHcNovndXb2PQ0cnkTUsdk3tIS3sDe5q1K6+f4b\nHJXY7OefqCgQAwYAOFx2Vfzb6KGnQWcy4k8HNmHF/q/F33IismLQAGurgq9U6LXiSP+YoFCPx/WL\niHN4nNzMhdyaQyqRYHhMD/S3u8bKA984dMd6yyIIMAsWaO2yJwkQUO2UKeq7KydxtDwPu4su4GDZ\nlRZfzx9yqkrx4bl9+LXogl/LYeJEaKJOo9oH89a6KueeBsDa6JYR26vR51nqs3Tk1VS63S8IAmrt\nfsvsJ1NnqwtRY9JDbzHhp4JzLSk2UafVZYcnrRh+C/58dBsA3/Y0FNvNj0gI9rxIj3OLky+DBhv7\niWN6swkF2qoWLcZmESz489HvccVNN7DGoEOksuE6ZbqG1HXFPp4r0tbePv0Lqo16/Fqci7So7ohu\nJOjzRo1RhwOll2EwW4MBuVQKqUQCqUTqdoFB++529jQQdVzHyvPwj9O7xMctnbfWVbnraQCAzORB\njTZKGS1mqGRynKxfNM9ZlaEOOruecPvhSRa7tIC+bFAk6gy6bNAggQRxQWEo1dW4pGw7Vp6Hkrpq\nZCYP8nrBF/v5A3GNrMTrPLa1RxsEDfY38wBQUNuyoOFyTYXbgAGwfvn2RMPEvkq77txyXcuyWvhD\nrVHv0GtSadC2Omio0NXi2ysncKjsaosXEuScBqKO6/9l/yL+rZLKoXLTck6eeVqboanGlJeObEGp\nrsYhALDnnBzEvvGm1tgQKDDZB5GjLvsN1k0VLK6kbN/TUGPUiV/0oQqVOC+guWyrJXdThbjtWrVx\nbnHqEer7jBpRTkHD+nN7MSqul9et15JGJorbp2A1WczQ2AUN9r0Ogc45La0vsmn8WHAGv9qtAyKF\nBAJcU9XKJFKXd1gikWBCQl/2NBB1EpzP4L1wDxORnb8Xh8X0wLHyPPFxcSPJPwxmk8v3vf09gP0c\nlCom+yBy0CWDhlk9hyBCGSyupGzfNWn/ZZNdWeh10FCut94oN9bLALiObW2LrBqhctcv3GPleciI\n6+3VeRqbC2Hfs1Jl0DncDl+sLsdZdXGHWP00X+sUNPhgtfCDpY7d508MycS5qhJ8e+WEw/Y/j5nh\n0itERJ0LMyd5z1Og5Rw0BMsUzT7nJzkHXJ5v3xNs3+Nc3sI1IIg6qy459qFPWAyAhpWU7Ycn1dh9\nYTivtNwctpaJpm4CU8JjxGOuTxrYJov9SCQSPDXkBofApyVrNthyjLuz5eopMfd1pZsv2I4ykcy5\nRckXY1njg8LFv/uEx6B/RJzbMc1hTOtH1Ok4Z5YLljf/xpaswj0EWq3pgd1XctFlHqPe3NAwZp8i\nt1xXA8HDECeirqhL9jTY2IIC+wVf1HbDa0JbEDTYMmU01aoULFfgpdFZqDHqPa7n4AsDoxIwMCoB\nhdoqXKwux5arpzA6rrdXE6/tv1DduVxTgcHdElHkpkvYuQU/UNnn7AZ8MzzJNnRrVGwvPFy/Cqy7\nz4W382aIKPDZj40HfL0aUNfQnOFJQS2YJ1LuNHRWb2n4vrcfcmuwmFFt1HMCO1G9Dne3UlBQgIUL\nF2Ls2LHIzMzEG2+80eJz2Vox7L8kbAuztYQgCKiuP1dzvmQUUlmbBgz27OdMvHJ0m1cZo9ytt3Bf\n/zHi37b3L7/Wmt4uQhEkrtxZUleNnwrOwmQxo0irweYrJ7D1anaz3ucTFfn47spJlPpwcTpPnCe8\n+WJ4UnX92NiE4HCxJ4k/PkRdg8ZHa+N0Zc3paUgO7eZ1IpFLTok99Ha/cdVOazPYhhwTUQfsaXj0\n0UcxZMgQ7NixA+Xl5Xj44YcRGxuLBx54wOtz2Vp9tSYDTBYz5FKZwxCbxobluFNnNsJU3yXt6cvO\nX8Yn9MGuohwA1taTkrpqpITHNOu57t6H2KBQSCGBBYLYu2Ib+tQjNArJIQ1f4v++cAhGiwX/Lbko\nHnOpuhyLBk/yeM0yXQ3WndoJwLpq9vLhtzSrrM1VrNVAZzahV1g3SCQSh1WYgdYPTzJazOKwN/tA\ngeOaibqGf53Z4+8idHiNBQ1j4lJwtqoYDwwch2hVCLIrC5Ftt5CbN+yDBudgr0xXiz7hsS06L1Fn\n06F6Gk6cOIFz585h6dKlCA0NRa9evTB//nx89tlnLTqf/c1ctTguv6GVwdjEsBxn9mMhA61FuV9E\nHDOhY5IAACAASURBVJ4dNU18rPEiK4S7ngaLIIhj8W1fsrZJ5IkhkS4L2/2YfwZF2oZ1G0p1jfce\n2K/xcLG6vNll9eSsuhjfXDqOHflncaIiH08f+hYvH92KH/PPAHCd7N2anoYaox6v1K8BAjhOenf+\nEWR2JKLORxAEl3Vqbut5jZ9K03E1Ng/kwdQJeHXMHYgPDodcKsPDaRObPF+ih7WTbEGDwWxyWL8B\n6Fipw4naWofqacjOzkZycjLCwhoyEw0ePBgXL16EVqtFSIh3Q33sW32rjTp0U4W0qqfBvoUiEFf+\ntE/B6k3XucHN+5ASHo0IZRA0Rp0YgNiGPIUrg1xa1I0Ws9gLAzQ9Z8A5qDFbLJC1cM2CWqMBfzv5\nk3j9ILtMGzmaUtyENBid5jTkVJW26FqAdaKd/YTzuOCGz2uQXIGs3kPwzeUTSAyJxG8Hjm3xdYgo\nMOnsep0zYnshM3kQ+kXE+blUHUtaZAJ6N7GukH0CEU8Lwdm7s+8IsQcbAELkCmhNRujNJgiC4PZ3\nscppuBJRV9ahgga1Wo2ICMeWgqgo6zCYyspKr4MG+3RuGoMOgiA4LE5m8LKnwX5CdajC+0nUbS1I\npoBcIoVJsHjV02CbCB2hCMLCtEkIlisQpmgIDDRGHUwWszgvIFimcFnEyDlIaGpOhfOXd7VRh6gW\nzv8o19c4BCz26fVs74NzT0O5vhY5VSXoHxnv9fWK7XpU5vTLcFlQb1qvIZjWa4jX5yWijsH++3Vs\nfB8GDC0wNSnNq6yCMolUHDLrSXxQOMYn9MXe+vVzopQh0JqqYIEAk2ARh9raq+bcFCJRhwoaAPgk\n/Zler4dWq4Xc1HCu0poqlMqDHSbEHim/ireOb8fv+o1tVoab6rqGyb0WgxFaS8snVbeVcIUKlYY6\nVNRVQ6ttXvlq64dsKSRSJCmsw460Wi1CpNYW+yqdFhXVDTfKMrOAujrH1hnnBc10ZiNqamsh9fCj\nUKF1nHz25YUjqDU1BGUxqlBMSx7crOE9pdVVHvep9VpotVqHFUFtzpYXIknR+Hob7hTW9zIMiojH\nmKgezX6fOyu9Xt/0QT64Rld/nylwlFQ39DQqLeh0n81ArdMKqazREQImgwFKoeE3J0zW0LinrqlG\naU3Db0W8Kgwl+hqodbWd7t+PyJ439blDBQ3R0dFQqx1TeKrVakgkEkRHN96Naa+wsBCFhYUQBAEq\nSKGHBXvzzsNQXOFybHZVMbaePIi+8nA3Z3J02dhQtovnciAPwFSatkDpTFkBPqmsQrQkCCnyxm+M\nS/TWOQWC0YTTp0+L2w0G6419pa4GJ8+dEbeXFhbhdEnjGScEACdOn4JS4v6mP09f4vD4v+WXXY4p\nLi9DP3k4JJAgQqJAmNT9+NezJs9BQ5WhDtnZ2dDorXMsUmRhuGKugQXApeICnK5sfIhavrkWZ0xV\nkNUnVAyWyJFrsmaRkmsNDu8XtR1bnSYKBLmmhjlbxZeuolbasgm6XVlL6rTU0nijYm7OBdSYGn6n\n62obgoFTZ88gz9IwPDm0/qu/rEbD73Gieh0qaEhPT0dhYSHUarU4LOn48ePo168fgoObP4cgMTFR\nfP61eQJ2FJ/HFXMNpvROA3Jdb04jE2KRFt/0ytDFxTlAXjEkANLTBrfJgm2ttTtHjdIqHUot1v8A\nYNXAmxCrCvX4nP25NUClBuEhoUhLTRO3FxbJcTy/EjrBgqSUXsCZiwCAAb37oF94LHDobKNlqY0L\nw7C4FPGxIAjYWXIBhXUalBmNgNPoMAmAfmGxuFBTBgHAGXMVzpitAUGITIFnh97qtuehoOgckO/+\nR9sMAX0HDYDyfClQW4foiCgYdFIU1GmgjAhDWp80t88DrEOa3j2yyeP+Ad17Ii2hn8f9XYVarW7z\nG3r7Ok3kb+UlucDVAgDA8LRrOl3Cg0Ct06rjV1Bn9DwHYfCgVCg0pTiUa20I6xUTj6ul1t+tnn1T\nkF92GSgpRrhchb6xibhYdB4GGZCW5vl3gKij86Y+d6igIS0tDUOGDMFf/vIXLFu2DMXFxXj//ffx\n4IMPenUelUolzn8YEN0dO4rPQwCgsbgfZ69QKpo1X0KQWYMEpUyO0FDPN+H+1C0oDKgqdtimlZgb\nfX1mibX1JlihdDguJtTa+2KBgBo0tMhHh0UgJCQEcUFhKNV57nHYcOUopvQcBHn9D+pZdTG+zjvp\n8fiU8BgsHX4z/vjfjS6T07RmI2okZiSHuPYI6WBx2WbPKJfAXD98SqVUIkoIQUGdBlqLsdH35dOc\ng42eNz4s0ut5Np2R81C1tmBfp4n8zfadEyxTIDKs6V7qjiZg63QT7XQRoWEYExaBc7VlMFosmJDY\nD7/WBw1SpRzF9Wsy9Ajrhuj63xKtyQBVcBAX4aROy5v63OFqwVtvvYXi4mJMnDgRv/3tbzFz5kzM\nmTOnxecLs1v1ucLDgmM1xubl7LdNnFZJAzcWc5cKVu8mpaq7/c6vy/5cJXYLsAXXZydaPPg6l3NN\nSRzg8LjILi3hpfrUqhIAPUO7YVBkAq5LHIBeYdHoFxGHO/uMAOB5pW53GZlOVxaJaVU90Rh04orQ\nColUfF2NZZgqqK3Cz4XnGj1voKXdJaL2UVKfUjq6kR5can9yiRRSiQTzBo7Dg6kTEGSX0lVnMolZ\n75JDo8REHwKsabSJqIP1NABAQkIC3n33XZ+dL9RumXpP+Zibmz3BNgFL2YJl7duLu8XFmgoabGtY\nhNm9V9ZzNQwJs89JbsutnRQaiRuSB2F7vnWY0gMDx6FvRCx+LjwvHpurKRNXq87XWr+wu4dE4k8j\nb/NYHrmH1KvON/mCIOBfZ38VHyulMhgsrhmxNAadOAFeIZVBVR/05NWqsac4F3qzCYMi45Fkt+ro\n0fI8j+Wz4UJuRF2T/c0ntZ+m0qQ4DxlW2c2DK9FVi8k2eoRGOWRA1JoMiFQGXhp1ovbW4XoafM3+\nRrhC7z5oaG6eZoOHFvlAEu6m9dvdOgz2bOkDnZ9r35KeqykDYO0lUMnsW28aWv/jgsLFXgibT3IO\niGnu8u1WlG6MxUMGLed0eXqzSQx4AODx9OsxsXs/XJc4AH8df1fD6zPWiUGDXCpDpN3r+uDcPvz7\nwkG8fvwHh0XuTqtdx/85/6iwp4Goc7EIAg6UXMLuohy3GdcA65o0trTLTX2XkW95m10xWN7wW22/\nNk9yaBRCZI5BAxExaHAY6uIpaDhanocirecMPDa2FnulLHAnvXnb02C2WMTWF+fnhilU4hDSkvq5\nC0EyhUMa1czkQZDAmiI1JTwaYQoV4oMdx/ieq7JmSqqsHx4WG9R4Niezhx8Gjd0EuBqjDmpDw3Cz\nxYMnY0BkPOYOGIt7+49GsFwp/ttXGXTiOg4KqRTDYnq4nFtrMjp8Ptz1Stm3KsokUodF5Iio4ztU\ndgXvnd2Dj87vx+ar7udfFWk14loB7GnwP+c1g+wF2wUGORrr75AUEiSGRCLY7t6gqcVIibqKLh80\nyKUy8UvFtnx8bFAYeoV1czjuWHl+k+cShycFcE+Dt3Maqh1WuXZ8rkwixeTEAWLgIIEEk53mLPQI\n7YaXR8/A6pFTIZfKIJVI/z97dx7fVn3mi/9ztFuW5H2PYyd2NmchCQESllAgLGVJKTRAO8PtJVBy\nmXbKi8lt2v7aodMWLu0MLZcumQZelHJnJpMMky7pBi1tSsuSsoSAg53V2Rzvi7xol875/SHp+Bzp\nyJYcWYvzef8lnXMkfe3kWOc53+f7PPjKypvwjTW3ysecczkhSZL8h9maYM1ClChpL2z+1ZlD6POM\noWN0AP97/8/wtXd/nXDsym3K9CSDTo/KAjsuLp8bd3x0xiVR59Aa60TjQZ0g5GT1LCKavuMjfYrH\n2l3jO13D8mPONGSW1u2kR5Zdi0sqGvDg4ivj9ul1OrmTdHRNY5XVAaNOL6fZAoCHMw1EAPJwTcNM\nsBnMqgtni96Azy+9BsdG+7Cj/TUAwHhw6oVQ8kLoHF7ToJWXOVkzHGV6j0PjtZ9qvgT3NF0sP9dp\nVJgotagXA1oMRlgMRsyzl+Hk2CA63U74xZB8dy42hSlWZYEdvYqF10pPH9qHAr0xrpmcVlqWw1SA\nbs8oRgMeuSN0tDSiVnAVDRR8oaAcZNRZi+W1GE32CvwB4fUbygCCiPKXKEnyjZGzioDgnNuJkCgi\nem9AJ+gwHvDh5c5wTf9Cg5l58BkXHzbMtZXigcVXJHxFgcEEvyIFeVFRFQD1zSt3iDMNRACDBgDh\nxdCDitQTs94Au8mC1eVzUWMtQrd7BK4kKihFL75zOWiwGky4o3ElDgycwanxcDO7yWYalCk/9gQL\ne7UChWTUWotwcmwQve5RVc7oVDMN9zStQY/7j5rlXAcSlHjVnGmIBAbDPrf8VWOMNJvTOj4606Cc\nZbi1YTk6RvtRVeDA6vJ63FK/DD2eUVxft3jSn4GIct+fu49j94l35FQV5cyrLxTE372+C0B4LddV\n1c1oc/bIf4PmFBZztjHDtDJX9QkKZ0RZ9UaMYOJ77uLyegDhG0gGQYegJHKmgSgid69uM8gWc5Gq\nTC+K5r27kpppyP30JAC4sb4FN9a34Bvv/gbn3E7VAt9Y6pkGc8LjpiMaHHhDAVXOqHJaWEu5xYbH\nLtmo2nZybADfOvg7zeMteoNmRato0KBcqxCtzFRojP9Zo8HCqGLBdYm5AJ+Yv1p+vrFxxaRjJ6L8\n8ftz7QhK4pQV9CQAf+45rtq2piI+xZFmVmrLoMOUZVcFCGi0l8nPrQYTRgNermkgisjtq9sMib1A\nVM4URKsrJVOnWe5nkMMLoZWiC7a9kwQNgdBEidJ0B0PR37MvFIQnNHEnZ6r0JC211sS5w2Vm7YXV\nRZGSsW7FF0I0PUmvcYfw0FAXQpKIAc/EbIay7CwRzR5BMaQ5c/nZlqthN5rlmdp+zxj+0HVEdcwT\nl36MPRqyYFX5HLzWcwIAsKK0DldVN0/5GuWC5wpLoeoGU0EkaGD1JKIwBg0I554qKYOG6D5XEn80\nvKHc79OgFK3uM1nJ1aA0ETQk6o8wXdHfk08MpjTToMWsN6DEZMWwomKSUafH8tJaXFOzUPM1WusW\not2ptYKBs65hVU6zAMCuMSNBRPkpIIbw+87DGA144A0G4so7NzsqsKKsDgAwz1EOIFySWxk0rKuc\nx4AhS+6ctwomnR6LiqqwMpJmNBWr4iZVjbVItS/6XeThmgYiAAwaAAA2ozo9SdlnIdrgZaqZBk8w\nIKcwlZry4wvDpLjTn0gg0ilZJwjTXruQiCXSWEeUJNX0f8EUaxoS+d8XbcBX3t4rP9+6/Dr5i12L\nVtBQarYCAJaV1uLi8rkIiCFcXjUfPz35HnyKxnACgHVV8/MmQKQJ51xO7D39Aa6uWYCWkppsD4dy\nyL6uo/jF6fcT7tcqoeowWmDRG+GNXFhezLSkrLEaTLi7aU1Kr1GuO4n9940GFFzTQBTGKx5MPtNg\ni+wbC3jx3OHXcXH5XM07GP3eiWo+sX0IcpU5clf96EgfXAEfCo3hKlLKnz8QU1UonZT9LJQN9KaT\nngTE93fQqpikpDWbEP230wkCHlwyUaJvVZJ3rSg7Jkuxi/VU6x8xFvDi4GAndlz1qRkcFeWTHvcI\n9px8D0D4O8BhtEAAUFdYgtGAB6Ik4Zra+FlLQRBw1/zV+F1nOxrspQxE84wyBS22R0/0ppBfccOI\n6ELGoAHqrtCAunqPsmTeW/2n8Vb/ac0LjbbhHvlxlTU/ggaH6mc7hdPjw3i77xQ+u/Rq+YtPLkUq\npD9oUHaO/tmp8N09vaBLW4CiVQFJqSgmqLAbLVNWbqLcNOAbRx2qkjp2qkWtdGH6+akP5McbG1Zg\nQwoV0K6obsIV1U0zMSyaYdfULsTJI2+i1lqEBlupal/0uyjAoIEIAIMGABMpSFGLiicuPpaV1sKo\n06v+aIiSpOp67A0G8LNTBwGE/8gUm6wzPOL0uK52EV45dxgAMOb34c3eDgDAs4dfx1PrPgFgIj0p\n3esZAO0F42Vma9rKFE6VOhTuaC3IPR2q8mSGiOIFRe2Gf1OJPZfpwvPB4Dm4gj6cdQ3J25JZQEuz\nw6UVjSgz21BVYI/77omucZvu3xei2eaC7wgNxKcnzVOUXLMZzbiotE613xWzvkHZ46HcXJg3FyGl\nlkKURRbsKRcQK9c4zGR6klkXn4a0efHlaf+cRHSCDmur5kUeC1gXeUz5J5CgS3is2G7irIqSfQEx\nhFCWLsrOjg/jh22v4idH92PAG/47vmn+6pzutUPpJQgCmosqNNNZjZF1fEHONBAB4EwDAKC6wAGr\nwQhPMIj7F18et+C30V6GdwbOyM9HA17VHxivorLCpxetnfkBp1H0y7HHPSpvU6boRKsnzUjQEPPF\nfMvcZZhnT7xwORkLHJU4NtqXdFWj/7lwLe6efzH0gsBFzXks2S/1Eb86NWnU741LT6TMcQV8+Nq7\nv4ZZr8fXVt8y5TnY6x6FXwyh3laiuX9f11EcdvZo7tNyamwwblttTAUdunBFZxoCEoMGIoBBA4Bw\nc5d/uvhW+EMhVBTE1/SPzXMc9XtRpyiQ5Ff0MtC6e57LoiXlejwj8jZV0BC5GJuZ9CT1f79EHadT\n8ZklV+D1nhMpVTCZTolXyi1TfalLkoQXju7H/r5Tqu3h9Q28SMyWv/ScwFjAi7EA0DrUNel5O+L3\n4P8cfBn+UBBfuOh6zI+pjHbO5cSuE++c95jqC7UDErrwTKxpYHoSEcCgQaZc8BxrQVElLqlowNv9\npwHEL6T0KWYa8m1aO7oYWdngzKq4iI7+sczETMNUC5eTUWQqwM1zl533+1B+mepLvdczhjf7TsZt\nH1VU7aL0+8Wp9/FazwlsWXIlmosq4/YrZ2mnCvze7T8jH//P7/8eNVaHvK/WWiTPBusQTjdJ1tGR\nPvnxldVNU1ZdowtH9GYZF0ITheXXFW6WCIKA+xatwzv9pyEBeO7IG7AaTFhWWgsg3JwsKt+CBovG\neJUBgjzTMBPVk2I6TGv1TSBKxlRf6okaGI4l0el9ugJiCP5QKK7QwoXkN2c/BAD8ywev4FNNlwAA\n6m0lcbMEgHrGVsu7ihRRCRK63BOzo8rHC4oq8Q8rrkt6jFv+slN+fElFQ9Kvo9nPKC+EZtBABDBo\nSJpe0KHCYkNfpKbz7zrbJ4KGUP4GDVo9EfyaC6HTn55kiqmelI6ZBrowBadYCO0KaC949oRmZiH0\nkNeFx977LdxBPz4xf3VK5TtnCymmm/LOE28DAAQI+Oaa21BRYFPN0o4FEs/6jPg9ODHaLz+/MlLe\n1B8K4a3+U6pj711w6bTHzE7OpKRMT5IkKW2V/YjyFasnpeD+xVfIj0cVKUrRoEGAAEOauybPNLNG\n0KDsfBy9GDPMQHqSTtDJ1ZuMOj1KzPlRqpZyTyDBTEJUoipJHkVaXjq9P3QOrqAfEoC3YtZRXCgS\nNdwLzxI4AYTXh0WN+hP3zzgwcAbREOSba27DvQsuw70LLsOnF16mOq7YVICK8yidzL9BpBTtTyRB\nghgTBBNdiPLrCjfLGu1luGHOEgDqsqvRoMGsN+TdnQitmYZu94jcoXkmS64CwOeXXYNPzFuFL6y4\nntWLaNqUMw39njG81nNCdRHqShA0uGcoaDjncsqPnXm2bqJtuBv/efxttA8nX4VIizJQ+8ziK+Te\nL8BEgKBcT9DtHsXZ8WF0uUbQq6jmBgDv9p8FEF6kXKkICgw6vWoN1nSKKSwqmujLM1N/5yg/KQuA\ncF0DEdOTUmaL9HQYD/rk6cromoZ8S00CgEQxzo/a/oIvrrxB/kM5EzMNAFBtdaBasaCRaDoCoXDQ\nMOAdx9cP/AYBMYSFRZXYumIDgMlmGmYmPanTNSw/HvF78O2Dv0PH2ACAcB8YbyiIdVXzcOOclhn5\n/OkKiiF8/9CfIELCX3pO4PuX3wX9NFMTXcGJGyvRbusmnR5+MYTRgBfv9p9RzdgeGenFY+/9Vn7+\nUMt6rCybA1ES5dSklWVz4j7HbiyQg7/prIv69MK12HPyPVxcnnzFNbowKIPIgBiCBay0R/nvfFLt\nONOQosJITXdRkuTpd+VMQ74Z8rk1t0cvcKKdMI15lnZFF5aAFD4Hz44Py4Hu0ZE+dEcWyCovYD8x\nbxWaHeHqOp7QzMw09MTcKY+eTwBwcmwQ3e4R/PTkwRn57PMxGvBCjCQChSQxrlJcKpSBWnQxePSi\n/p3+03jm8GuTvv7oSC+AcApZdExllvg1B8q1UNNZF1VmKcSDS65MqUwzXRiUN8umWjdFlA9e7mzD\ntr/+LKV+Nkr5d5WbZTZFDwNX0IcCg1FeOBxbDSgfXFndhDd6OzT39bpH0eMJX/zM1EwDUTocHxtE\np2s4Lg3pxGg/aqxF8gVsTYED189ZgjPjQwBmpiO0PxRMOhgJSSL0ORSQx64rGA14UZxEnv/RkT60\nDXdDwkTet0dVxjn8d9NutGDA61JVO7qiqgk3z12KncffxofD3fL2schYlP+mhYb4RnzK2QWWS6V0\nMjI9iWaZ6M2qp1r/iB1XfSrl1+ffVW6WFSq6x34weA6ry+vzeqahyVGBbRddj2fbX8ewXz3r8B/H\n35YfM9eXct0r546oavcDE2U83ZHqSdbI+VsQuYiNTU86NtKHt/tP45a5yybt3TKZ0RTuzo8HfNP+\nnJkQO7OgtTj53479FUecvfj7pR9BldUBXyiIHxz6k6r0dKzoxb4j5mctNhXg1oZlKDUXoqrArgoa\nor9HZWCnbDwZFduvgShdlKXGGTQQ5WjQ0Nraiq1bt6K0tBS7du1S7Tt8+DAef/xxtLe3o6ysDPfc\ncw/uu+++jI1Neadrd8e7+Pnp91FqCt+Jy9eFvE2OCnzrstvx0tkP8bNT78vbj0TSA4DwxQ1RTpMk\nOTiIivZnGI+kJxVGLjqjF5/KGQFREvHDD1+FJxRAv3ccDy+7ZlrDGFNcaN+/6HJIkfvvzx95M+7Y\nUb83p4KG2CAhvpFlEK/1nAAAfO/DP+Gu+avR6RqWAwarwQSDoFMFTnpBB1PkpkORIn3o0ooG3Lfo\ncugiubV2o/r3MOYP/5spU8u0el5cX7cENqMFJp2efRYorWLXNBBd6HLuKveXv/wlvvvd72LBggUY\nHVXnBft8PmzZsgV33303nn32WXR0dGDz5s2or6/Hhg0bMjI+m1E9Pe4LBdEdSeHJx/QkpdhKMha9\nUe7A2q1IJyDKRXqdLi49yR/5oh+OrN2JltSMVg0bD/jwtXd+BSCcKhQNItqGuzEe8MWd78lQXjDP\ns5fJJUDPjA3hD11HYo71AChJ+TNmSuwsSWwQ4VSsgRrwjmN7259V+7dddD1qrEV4qvUPOOwM33So\nKrDLi+6urG7G8dF+6AQBt85dLgcMQPwiZnmmIaBMT4oPGiwGI66pXZj0z0iULHWjU65poPwW2ztn\nOnLuKtfv9+O//uu/sHv3brz2mnqh3L59+xAMBvHQQw9BEAS0tLRg06ZN2L17d9aCBiWtqfN8srq8\nHi93tsnPCw0mOWi4fs6F15yK8ovW+oSAGIIkSXLQUByZFYwuqJUAed1OrF7PKGzGipTHobzQVubY\n39V0Me5quhjjAS+27v9p3LHZJkoSfq6YaQTig4ipysdGg7LNiy7H/r6TECUJq8vq5f0N9lJ87eJb\nNF9rjkmBHAt4cXykTxUI5vvfWMovXNNAs0k6/g/nXNBw5513JtzX1taGRYsWqUpFtbS04MUXX8zE\n0AAAOkGAXtAhpFFJId+/0BrtZWhylOPE6AAseqN8wbCoqAqrFF/8RLnIHfQj9kaKPxTEeMAnVz4p\njVzUriybgzsaV2Ig0uE9qss9guOR8p7R9RBKoiSh0zWMQa8LrqAPi4ur8d8d78l9TUrNVpRGAhKT\nTg+LRh8Uq8EMHQSIkFJa/zDTtKppRIOtfV1HcGioG4eGuyZ9j+jPW2QqSLmcrFZ657988AqWldQC\nCM/ksiADZZK6ehKDBspvvgQNN1ORc0HDZJxOJxwO9ULH4uJijIykljrj8/ngdmuXGk2GDoDWnw+T\nJJzX++aCxfZKnBgdkGcYAGBlcQ08nvxqUEW5w+fLzHqYcb83Lmjw+H3oHh2SnxdAJ5+jV5U1xr3H\ngM+Fxw/9HgAw5nHBbVafz/956gDeGjwjPy8xFWBYcfe9Y2yii6zdYE7498BmNGM04MWQezxn/mac\nGJ5Yw1RktGAk4MXZ8SGcHOrFrhPvJvUe5/OzzDMXo7bAgX6vC4CEQCTQiwYqBXpjzvyuLnSZOKfP\n93s6HYL+iVmucY876+MhOh8jPpfqefT/cyrnc8aDhr1792Lbtm2q2YJoo4knnngCt99++6Sv18rJ\nSrVJRXd3N7q7u6c+MPEgNDeP9A+i3dk+/ffNAYOBobhtzu5+tPczaKDcNuJxy/X8owacwzg0dkx+\nPnimC0HdQOxLZW5p4k7MqbNnoO92qva3edR32qMBgynS8sYPEYHIHcnCkID2du2/B8ZgeJydA31o\nH8vu34xR0Y8xKYD3I+d+iWDCItixH170e8fx0pH3AAACgMkyYlcYShL+vMm6BdWQIhldu7wdGFf8\nexhD0nm/P+WP8/6eTgO/Ynaho/MMTD3aqYxE+WBIVAcHh9o+TLnkd8aDho0bN2Ljxo3Tem1JSQlO\nnz6t2jY8PIzi4uKU3qempibl1yhdfjaIV/tOxG2fP2culpTWTft9c8FgXwdwtl+1bcn8ZjQU5s5i\nTcovTqczI1/+LikYFzQU2ApRVFQBnDkHAFi1eOmkpZG9oQBwMHxuV9RUY0n5RDUeSZLge++Y5uvq\nbSWwGkxodU78nAsr6rCkbonm8RXHhjE42ged1YwlC7WPyYROtxPPtv9J9VubV1yJ1eUN2H+sHxKA\ng8FwMNFkK8d8exl+161ezP3R2iVYUzoHJSbrtLuMallyyoO3B8/Kz/9m4aVoKCxN2/vT9GXiyKgI\nDQAAIABJREFUnD7f7+l0kCQJxvdOIiCFUFheiiU1i7I6HqLzcdo1BBw+JT9vWNAMu9Gc0vmcV+lJ\ny5cvx65duyCKInSRBUqtra1YsWJFSu9jNpthtU7dsCiRO5pWw2IyY0FRBZ5pf02u0FJSaDuv980F\nVkt8c6RKezGslvz+uSh7MpXapgwYTDo9/GIIogD4BFHeVmJ3JHo5AMCsXKtk0KnOZ08wIKfMxCq2\nFKLa6lAFDY3FFQn/HhRbCoFRwC0Gsvo3o2PwZNzswZqqRjQVVwHH4revr2nGysq5+O4Hf5DXiZQX\n2jGnJPUF41NZWFIjBw3X1i7Ckoo5af8Mmp5MnNPn+z2dLkXmAgx4x+GWgjkxHqJp88XMlJn0sBZY\nUzqfczZo0EpDWr9+PWw2G7Zv344HHngAR44cwZ49e/Dkk09mdGwWgxF3zFsJINwkyh9JUdDqVppv\nlM1souzTKDtJlE3z7OU4MtILvxiSew3YjVN3C9YLOhgEHYKSGLcQOlweNaxAb1T1eLAbLZhTqL4r\nGvtcKVpeNNvVkzpd4fSr6gIHtiy5EoVGs9w3osRklRs+CghXV9MLOjQ5KlBqKUSfZwwA4DDOTJ+J\ny6vmQZIk+MUgrqxunpHPIJpKkSkcNIxMUTmMKNf5Yxpwjvm9qCqY/EZarJwLGm666SZ0d3cjFApB\nFEWsWLECgiDgpZdeQk1NDXbs2IFHH30UzzzzDMrLy7F161asX78+a+O16o0YQfiPSb5XTwIAg06d\n32bRG/K2aR1dmEpMVvnCNxw0hPM47aapgwYAMOn1CAZFjT+wE/mglQV2nB6fWP9TaDChThEkGAQd\nKiP9GbQ4IgHMWMAHURKhSzGvNF3ORYKGubZS1MYGPbZiDA+Fg4YmR4WqCd1tc5fjpycPoqLAhsXF\nVTMyNoNOj6trF8zIexMlK9qQMNsBPtH5iq2edNblRHNRZUrvkXNXgy+99NKk+5ubm7Fz584MjWZq\ni4qr5eZuWt1K840h5uLFkcTdWaJcUldYDJM+PGMWEEPyl32yM2YmnQFuBOALhSBKEjpGBxCSRLQO\nTSyCji396Q75UWGxyWlRtYVFky4wiwYwEiSMB/xxjc0ywRXwo9sd/ts1xxY/K9JSXCP/zJdXzVft\nu7SyEZdWNs74GImyzREJljnTQPlizO9Fr2cUJeZCuScRoBE0jMcXvplKzgUN+eb2xovg9LvRYCub\nJTMN6oshu2lmUg+IZsqcwmJ5lsAbCshBQ7IBcHRmzS8G8WZvB/7fsb/GHbO4qAonRicKBqworYNO\n0KHRXoajI32YZy+f9DOUYxkLeLMSNBx29kCKrGhYUlwdt/8jtQtQW1gEAQIWpng3imi2KDGHvwOd\nfg9Cogi9LjuzgkTJGPF78JW398qN3L6w4no0F4XXnPnE+JmGVDFoOE8FBiMeasleelS6xaYncaaB\n8k1dYbGcdhNtTgYkt6YBCC+YBsKpTf9x/O24/SvL5uCG+iXodo9gJODBFVVN8kX3/1hwGQ4OdmJd\n1bxJP0MZJIz6vagrnOTgGXJ0pA9AeAZmjkZ1NJ2gw2KNYILoQlJrDc/ChSQRXe4R1NtYSZBy16mx\nQVXn5+OjfXLQ4AqoS646fan3HWHQQCqxC6GzcQeU6HxUFNjkRbpKDfbkynWadJGZhlAQFr0BruBE\ng6d/uewO2I1mCIKALS1XaXy2HdfPmbqEqjIYVy6wTidJktDnGZMXbFdYbChUpGiNRtItKix26NJY\nKpVoNlEGCWddwwwaKKdFC39EKdfijMbsGw/4ICboO5YIgwZSiZ1pSPbuLFGuKDUXwqhXB7/3L7oc\nq8rqk3p9dD2EXwzCYbSogoZ0BdE2oxkCBEiQZmyB5b6uo9jdMdHJ2ajT4xtrbkWpOTytIS8QZ3U0\nooSKTQWwG80YC/jQ6RqWt0eb0hLlkpGY7xNloDAWs0+EFDf7MJW0JOe9+uqr6XgbygFMT6J8Zzda\nUKA3qratLJuT9Be8WZ5pCEHZleGj9UvTNUToBB1skYv12Ls/50uSJBwd6VMFDEB4UfiJ0Ylu2OPR\nUrScTSRKSBAElFlsAACnz4OAGMK3D/4OX33nl3AF/FO8miizYm9Cac00WA3GuG3JSkvQ8Nxzz6Xj\nbSgHxKYn8YKC8o1OEOS76VGplA2OHntkpBe9kcpoFr0hrUEDoCi7muaZhvcGz+I7H7wiP7+lfpn8\nWPlZ0ZkGG2caiCZVpKig9FbfKXSMDWDAO44DA2eyPDIitdj0JOXzaABRZy2J25astKQnaTVio/zE\nmQaaDZRl5lKllZL3sYaLYE5zvxKHyYJzbmDY70aXa0ROfTDrDWgpqYFRF99oMRkditmEcosNG+Ys\nxr7uo3AH/fJdJVES4QpG05N4jhNNZqJXgwdHRnrl7cEEHeKJMu3U2CD6PGPodo+otg/73Hir7xSA\niVmFusJiHBsNF8L4zdlDqNVZsRDJ3TxKy7cg8/pmj7g+DZxpoDywtrwBv+4/ijvnrQKAuJmGVFxf\ntxhOnxsHBs/K22Zixm1OYQnanT047OzF1w/8OmYMS/CJ+aum9b5DkYoY5ZZCfHPNrdAJOjiMlnDQ\nELmrNB7wIXqrhzMNRJObmGnwoss1cVE2nmI+ONFMODk2gG8d/J3mPk8ogOeOvKHaVltYBIOgQ1AS\ncXSkD4OCGQsLGpP6rKSDhu9+97sJ93V2dib7NpTjYvs0cKaB8sEVFfPwkflL5UZM5zMrUGopxJaW\nq/D/ju7H670d0As6zLOXpWuosiuq5+P359o193WM9WtuT8aQzwUg3OU52mnaYbKgxzMqT1U/0/66\nfDzPcaLJRYMGnxhU3cmNTQUhyoYjzl7Vc6NOjzsaV+KXZ1rhDqrX3dgMZiwvqYU4X8IbvR3hlNVA\nCMlK+pvVZErcuOyOO+5I+gMpt1kNRpSYrRj2uVFd4Eh7SgbRTHHENCKssNjQ7x3HFTHdjJP1N82X\n4orqJpSZC1FstqZjiCo11iI0OSrkJnFGnR7rKufhzz3HcXJsEKIkyhf9qYj2pihRjDmagjQa8MIV\n8KNjbCKFqV6jRwMRTVDOuCtTktK9HoloOjojfYlqrEXYuvw6mPUGmPQGrK9phicYUB1bYDDCoNPj\nmtqFuKZ2Id7qO4WfH31X6201JX1F+LnPfS7pN6X8pRN0+MrKm3BibAALHBVMPaO89Q/Lr8OHw91Y\nUzF3Wq/X63RoclSkeVRqV1U3yUFDQAyh2uoAAIiShB9++Cr+ftk1Kb1fUAxhJNJ/QZmiFb3oGfN7\ncWj4HEKRC5+Hl13DYgdEUyiKuSERle7KZ0TTEW1mWl9Yovp7btDpYTdNvjYu0f/tRFK+jfzyyy/j\nmWeewcjIiGoB9B/+8IdU34pylN1kwcqyOdkeBtF5KbUU4qqa5mwPY1IXl8/FT47uBwC0FFejTHGh\nf2i4O+X3+2DonLxWoarALm93KGYaoo3vzHqD3MmaiBJLdGE14vfg1Ngg6gqLp124gOh8RJt4AuGZ\nhlSlum415aDhu9/9Lv7xH/8RtbW1qb6UiIgUTHoD/teSq/CXnuO4a/5q+ELq3FJRkpLu1jzgHceO\n9tcAhEvELlYEBNEvhoAYQp9nHEC4IgxnEomm5jBaIACIrRPZ7x3HEwdfxuVV8/HphWuzMTS6wHlD\nATllrmgas8YzPtMwZ84cXHnllam+jIiINKwqr8eq8nC36qCoDhr8oSAsBmPca0KSCAGCKqBQLoZb\nVT5XdedTWVb1rf5T4W0pflkQXaj0unAzxrEE1ZLe6O3AHY0rmepHGadMkZtOtcsCvTGuauZkUg4a\n1q9fj3//93/H2rVroddPfCnNmzcv1bciIiIFg06PzYvW4cdH3gQQvoukDBpEScL3D+1Dm7NH3nbX\n/NW4rm6xXGoVAO5dcKnqfbW+TFg1iSh5RaaChEEDALQ5uzHodeH13hNYVVaPT8xfncHR0YVqzD/x\nf3I6PXcEQQinsibZbi3loOGFF16AIAj48Y9/rPpQrmkgIjp/hYaJvgneUFC1r8vtVAUMAPBfHQfg\nF0P41ZlWAEBNgQP62H4rxvhZhUJj4op4RKTmMBUAkQWnWvo94/hl5Bz8/bnDuGFOC/sc0YxTlv2d\nbqPOj9UtQ2/nuaSOTTpoGBsbw9NPP42GhgasWbMGn/nMZyYtw0pERKmzKMoce0PqcnmdCS5afn7q\nffmxVnlYrYuX2FJ8RJRYiSKdz260xPVoiHbYjXL63QwaaMapg4bpNeos0EiBTSTpRKZ/+qd/gtVq\nxX333Yeenh784Ac/mNbgiIgoMbN+4g+4NxRAl2sEL3YcwOs9J+TSerGUOanOSMlVJa3KLtP9giG6\nENUWFsuPSzQC89gGWyMa5yFROkmShP888Q4AyL0ZZlrSn9DV1YXvfOc7AIArr7wSn/70p2dsUERE\nFyrlXR9vKIjdJ15DV6QLrc0Qf6H/8LJrsKCoEp97fTcA4MrqJs33vbl+KV7qbIMoSSi3FOKm+qUz\nMHqi2WmuogmiqGjwFhWbEj7Kxm80w7rdIxAjrQ8s+uRnC85H0kGDwTBxqE6XepdSIiKamjI96cWO\nAxjwjsvPx4PhRW9XVTfDFfTBojdicXE1dIKA/2/lTTg22oerqrV7U3ys8SJ8rPGimR080SxVb5sI\nGubby3HO5Zx07ShnGmimDfsnil/cMndZRj4z6aAhtp4363sTEaWfMj1JGTAoNdhK4xrXNdhL0WAv\nndGxEV2oCgwmfKzhIhwd6cWtDcuxv+8k/DElkpUYNNBMU1ZOurh8bkY+M+mg4cCBA6r+DE6nU/X8\ntddeS+/IiIguQMl0lp2jyK8mosy4ee5S3IxwWp/VYIJ/ksDgT93HUG8rTZguSHS+oougdRBgNWSm\nMFHSQcPLL788k+MgIqIE6gtLcNY1DCDcX6GOQQNRVhUazJpFB5T+8/jbuKJqPjMzLnBazTjTIdrY\nzWY0p/29E0k6aKirq5vJccicTieeeOIJvP766wgGg7jkkkvwla98BdXV1QCAw4cP4/HHH0d7ezvK\nyspwzz334L777svI2IiIMmFd1Xzs7+3AhrrFqLDYcVVNE06ODcIV8KPRXpqRKhlElFiiPicLHJVy\n+dWgJKLT5YTNaNasuESzT0AM4b873sOo34Ob5y7DgHccPz7yBix6I7ZddAMqCmxp+6xos8FMlvbN\nuW+eL33pSwiFQvj1r38NQRCwbds2fPnLX8bzzz8Pn8+HLVu24O6778azzz6Ljo4ObN68GfX19diw\nYUO2h05ElBafXnAZPtm0BmZFcNDkqMjiiIhISauSGRC+gPvc0qvxgw9fBQA89t5vAQBfXnkjGu1l\nGRsfZcehoS78qfsoACAghaAXdPCLIfjFEN4f6sSGusVp+ZyQKOLN3g4A02/qNh05VwappqYGX/zi\nF1FUVASHw4F77rkHBw4cAADs27cPwWAQDz30ECwWC1paWrBp0ybs3r07y6MmIkofQRBUAQMR5ZZL\nKhvkx8WKxm8mnV4zfXDPyfcw7HPLJTJpdlKW2nX6PKrma2NpLMP71/5T8uNMzjTkXNDwta99Dc3N\nE1VBurq6UFERvsPW1taGRYsWqfIDW1pa0NramvFxEhER0YVpVVk9/rb5UjzUsh6VBXZ5u1GnVwUR\nUUdH+vClt36Onxx9M5PDpAxzh/zyY58YVAURo4H0BQ0nRwfkxx+pWZi2951KzgUNSp2dnfje976H\nv/u7vwMQXu/gcDhUxxQXF2NkZCQbwyMiIqILkCAIuKqmGSvL5qhmBQ06PXSCDvWKZnBKf+07laER\nUjZ4ggH5sSvgUwUK6Wz4d3QkvG5meWkt5jvK0/a+U8n4/PfevXuxbds21WyBJEkQBAFPPPEEbr/9\ndgDAiRMn8MADD+COO+7AHXfcoTo2VqqVCXw+H9xu99QHEtF58/l8Ux+Uhs/gOU2UGTyn1QyS4hok\nJMLtduPvFlyOLx/8tebx+fJzUerGvBP/tq6gX7XP6XOn5d/+rcEz6PGMAgCqTLbzfs9UzueMBw0b\nN27Exo0bJz3mgw8+wIMPPoj7778fn/nMZ+TtJSUlOH36tOrY4eFhFBenVn6wu7sb3d3dKb2GiHIX\nz2mi2SWfzmm3b6IJ48jQENrH2ic9vr198v2Uv3p9gwn3DXvGz/vf3in68LKvS35uGfagfTRz/59y\nbqXdqVOnsGXLFnzpS1+SZx2ili9fjl27dkEUReh04cyq1tZWrFixIqXPqKmpSTnQIKLpcTqdM/7l\nz3OaKHN4TqsdPhvAkb5wmnRNZRWWVEdyzN89onn8osWLM1ZXnzLrL8ecwOiY5j4vQli8ePG0+3a8\nP3wO/9Xxtvy8yGjBdcsuntZ7KaVyPudc0PCNb3wDd911V1zAAADr16+HzWbD9u3b8cADD+DIkSPY\ns2cPnnzyyZQ+w2w2w2plzWSiTPB4Jm+AlA48p4kyh+e0mtVsUT2eatxGi5nV0WYpP0IJ94UkCT49\nUGpJ7f/1kM+FHvcoOtzDqu1LSqrTco6kcj7n1P/anp4evPnmm3jnnXfw/PPPQxAEeb3Dc889hzVr\n1mDHjh149NFH8cwzz6C8vBxbt27F+vXrsz10IiIiugDphYmaMkbdxGXV5kXr8OMj8dWSfKEgg4ZZ\nyq1YCK2l0+VEqaUw6feTJAnfPPBbuGPWRwCARa/dYHAm5dT/2urq6inzvZqbm7Fz584MjYiIiIgo\nMR0m0k30itSTyyrnYcTvxZ6T76mOPzBwBgIErK9pnnaqCuUmj8bFPRAOLEORDuEryuqSfr9hn1sz\nYACAAoNxWmM8HzldcpWIiIgolynXJ0hQV3i8umZB3PH/eeId7DzxNt4ZODPjY6PMkSRJLrl6U32L\nvH1ZSQ1qrOF2Ad1uZ0rv2elKfLzVkPmZBgYNRERERNOkU6QnxXZ8NusNuLK6SfN17w92zui4KLOc\nfg98YhAAUF3gwOeWXo21lfPwNwsuRbnFBgAY9LmSfr+QKOKHba8m3F+gz/xMQ06lJxERERHlE+VM\nQ2zQAABmnfallgCmJs0m5xSzAnMKS1BvK8Hy0nAqUpk5vI5h0Jt80HBybGDS/UxPIiIiIsojUwYN\nCRY9s+zq7PFq9zF8/8M/AQj/u1ZH0pGiyiKLn0f8HgRE7QpL/Z4xPN36R7zZ2xE5dvIO0qYEwehM\nYtBARERENE0Xl8+VH68qr4/bb06QRsKQYfb447mJnhyNtjIYdXrV/uhMgwRg14l3NN/j6UP70Obs\nwU+O7gcAjAYmL4UqIj5AnWlMTyIiIiKaphKzFd9YcysghR/HMui078+6Q5OX56T8MeIPX+AbdXrc\nv/jyuP0VBXb58Ws9J3B7w0Wwmyb6ewTFEPq9E53FQ5KIUY2ZhpbiarQ5ewAAlRZ73P6ZxqCBiIiI\n6DxUFTgS7tMlmFNwBXwzNRzKoIAYgicSAN45b5W86Fmp1lqEFaV1+GDoHADgnYHTuKZ2kby/2z2q\nOn484MNoID5ouLpmARYVV6PQYEJtYVE6f4ykMD2JiIiIaIYkWrvgSlB/n/LLmGJGwGG0aB4jCAI+\nu/RqVEVmHE6PDan2D8VUVRrxe9DnGYt7H7vJgpvqW3BVTfP5DntaONNARERENEMSBg2caZgVlDMC\nDpN20BA1p7AEvZ6xuP4LQz636vnj772k+fpslFlV4kwDERER0QxRllZdXV6PjzdeBAAJO/1SfhlN\nYqYhqq6wGABw1jWMf3jzv/HoO7/EybGBuJkGpeWltQDCXaWVayOygTMNRERERDOkRlF+c23lPPkC\nMSiJECVR1RyO8s9vzh6SH08109DsqJAfu4J+uIJ+vNHTIa+JiPXg4iuxsmwOTo8PwWGyxFVlyjT+\nTyUiIiKaIc1Flfh440W4pX4ZVpTWqerr+0LaNfspvX55uhVf/OvPcHJ08oZpqXIF/Dg5NggAsOiN\nsEyRPrSwqBL3L7oct8xdhtJIpa3xoC8uPQkIL3q+uGIu9Dod5jvKNRdYZxpnGoiIiIhm0E31S+XH\nygtLXyiQlc6+F5pfnWkFAPyw7VU8ufbOlF8fFEP4ydH9kCQJ9y++HO5gAL89+yGKTQXyMZvmr4Iw\nRcM+QRBwaWUjAODs+DCGfG64An559ukjNQuwtmoe9IIOcyKpTLmEQQMRERFRhig7RPtCwSyO5MIz\nNs3F5/u6juLt/tMAgI+MLsSfu4/hrcjzqAVFlSm9Z6HBFBmTF05fuM9DucWGefbyaY0xE5ieRERE\nRJQhqqBBZNAw0wJicilgkiShxz0KURJV27vdI/jvk+/Jzz3BQFzAAAAlpvjGfpMpNJoBAF3uEUiR\n7s6lkc7RuYpBAxEREVGGcKYhszzB5Dpvv3LuML727q/w78feUm0/ONipeu4Kxs9W2I0WmPSpJe8U\nGsxx20o1OornEgYNRERERBli1jFoyCRPaKK0rWGSSlXR2YTXezvUr48JOoYjqURK07nYLzSa4raV\nMGggIiIiIoAzDZmmvOg36JK77A0pUpR8MeVQO8b6446/tnZRyuOyxcw0lJisKFIsrM5FDBqIiIiI\nMsSsrJ7ENQ0zThk06IXk+hw4FbMJ3pjA7thIn+p5rbUIa6vmpTwum1EdNHzzktumrL6UbQwaiIiI\niDLErJ+4cG0dPJfFkVwYlI3TjAlmGmJTkHo9o/Jjb8xMgzKIWFZSg88uvXpa45rvKEeTowJmvQGf\nmLcq643bksGSq0REREQZouwAfWDwLJw+N4pzPJc9n3mCE2sa9AnWNAxH+iREPX1oH/71yk9CJwgJ\nU8jm28vx98uumfa4jDo9tl10/bRfnw2caSAiIiLKkl7PGIBwyU8/1ziknXKmQZ9gpqHfOx63bTzS\n0yF2piGqpaQmDaPLL5xpICIiIsoSf2Rdw/NH38S7/Wfw8LJrsLC4Ksujmj3cipmGYKRnwxu9HQiI\nIVRa7PjpqYM4Mz4U97rRgAcOkyVuTUPUrXOXzcyAcxhnGoiIiIgy6K75q+XHYwEfulxO/LXvFIKS\niB+1/yWLI5t9et0T6xMCooiz48N44eh+7Dz+Nr734T7NgAEARv1eABMzDesqJxY7f2LeqpxftDwT\nci5oOHfuHD772c/isssuw9q1a/Hggw/i1KlT8v7Dhw/j3nvvxZo1a3DjjTfi+eefz95giYiIiFL0\nkZqF8uMXju7H1w/8Rn7uUtwZp/N3zuWUHwfEIE6PD8rPRUlSHWtRVLaKBg3RkqullkI8svxafKzh\nommVWJ0Nci496bOf/SxWrVqFV199FaIo4qtf/SoeeeQR/OxnP4PP58OWLVtw991349lnn0VHRwc2\nb96M+vp6bNiwIdtDJyIiIpqSXqeDWWfQLLl64d2/np5hnxvfbf0DxgM+fHrhWoiShH87th+eoPp3\nKmEiMAiIIgKRFCUt9y1cix2HX4MoSRgJeCBJEryR97PojVhcXI3FxdUz8wPlgZwKGgKBAO69917c\ncMMNsFgsAIBbb70VDz/8MABg3759CAaDeOihhyAIAlpaWrBp0ybs3r2bQQMRERHljQKDET6/Vr48\nw4ZkfDjcjb7IIvJXu49BB8Ad1F60HBWSRAx6XXHb/+fCtVhVXg+L3giH0QKn34MBzzj+te3PECNB\nh0WfU5fMWZFTvwGj0Yg777xTft7d3Y2dO3fi5ptvBgC0tbVh0aJFqjyylpYWvPjiixkfKxEREdF0\nWQ0mOP2euO0MGZKjrDTlCvjkGYUGWykurWxUHXt8pB/vDZ4FADnQUCqz2OTUJIcpHDT8uee46pgC\ngymdw89LORU0KC1fvhzBYBDXX389vv71rwMAnE4nHA6H6rji4mKMjIyk9N4+nw9utzttYyWixHw+\nX0Y+g+c0UWbwnE4PKSafPkoQMOt/9nTw+Lzy4zG/FyFJBAA0Wktweclc1bEmUZCDhm53/DWjVdTJ\nv3OLoH1pXKIzzcp/l1TO54wHDXv37sW2bdtUswWSJEEQBDzxxBO4/fbbAQCtra3o7e3Ft7/9bWze\nvBn/8R//IR8bK9UV7N3d3eju7j6Pn4KIcgnPaaLZ5UI4p7sVXYeVJAlob2/P8GjyT1dgYkHziN8j\nzzR4hkfQPq7+/fUGJ2YXlOlJhYIBDXobejtOozeyLeCLn/0BgKGT5zAidKVp9Pkp40HDxo0bsXHj\nxqSOraqqwpe//GVcddVVaGtrQ0lJCU6fPq06Znh4GMXFxSmNoaamJuXXENH0OJ3OGf/y5zlNlDk8\np9NjyTEn2kd747brBAFLlizJwojyy8lzbUDPAAAgpFjs3FRbjyXlDapjxZEe4HiX6tibahbjxtrF\nce/7/ikPTg7GN3tb1tKStrHnklTO55xKTzp58iTuu+8+/OIXv0BRURGAiVkEg8GA5cuXY9euXRBF\nEbpIV7/W1lasWLEipc8xm82wWtmynSgTPB7tuzbpxHOaKHN4TqfHXc1r8JuzhwAAb/dP3BAVBGHW\n/+xpoddrbi63FcX9/upRFndcaaFd8/dst6i3mXR6fLxx5az9N0nlfM6pPg0NDQ2w2+147LHHMDY2\nhvHxcXznO99BQ0MDmpqasH79ethsNmzfvh1erxfvv/8+9uzZg0996lPZHjoRERFR0moLi/DA4iuw\nsmyOajsXQicnUelUh8kSt63aWoRGuzpwsBvjjwOAAkWvhjXlc/H05Ztwbd2F2ZchVk4FDTqdDs88\n8wxcLhfWr1+PDRs2YGhoCD/60Y9gMBhgMpmwY8cOvPHGG7j00kvxyCOPYOvWrVi/fn22h05ERESU\nMmtMVZ5QggXSpBaU4oMGq8GISotd83hlF24AcCQKGgxGxWMTdEJOXSpnVU6lJwHhPMbt27cn3N/c\n3IydO3dmcEREREREM0N5ZxsI9xIIiiEYdNrpNxQWjMw02AxmfKr5EgDAPEcZLAaj5vFNjgrVc7vJ\nrHmcsrSqPsVCO7NdzgUNRERERBeKMkth3DZfKMigYQoBMVxitcpqx8UVc6c4OqzYVCCwCJrtAAAg\nAElEQVT3xkg002BRBHE6Bg0qnHMhIiIiyhKHqQCPLL9WlXM/Hpz5Xhj5LrqmwSAkH1zdv+hyAECt\ntUgVHCSSakn/2Y5BAxEREVEWLS6uxuaF6+TnZ8aHszia/BBNTzLqkr+UXVhchcfWbMSXVt6YMCBQ\nzi6YdEzIUWLQQERERJRllQV2eVH0ybGBLI8m90XTk1JN46oosMGsTxwMtBRXo9hUAIvegGtrF57X\nGGcbhlBEREREWSYIAhptpWhz9uAsZxqmFK2eZEzz2g+T3oBvrrkNIUlSVVIizjQQERER5YTKgnC5\n0EGvK8sjyX3ymoYZWDBu0hsYMGhg0EBERESUA0ojlZSGfW6EJDHLo8lt0fQkI/soZAx/00REREQ5\noNxsAwCIkDDi82R5NLltYiE0S9NmCoMGIiIiohxQarHKj39/rj2LI8l9M5meRNoYNBARERHlgAqL\nTX78x66jWRxJ7ptYCM1L2Uxh9SQiIiKiHGAzWlBnLcY5txNAOAXnQryTLkoidIIOoiSi3zOOTlf4\n92HS62HSGTAe8MEf4kxDpjFoICIiIsoRN9QvwfNH3gQAeENB2C6wi+I9J9/Dn7uPQScIcAcDUx7P\nNQ2Zw6CBiIiIKEdY9BOlPr2hAGxGcxZHk3m/60x+LYdFb8SS4uoZHA0pMWggIiIiyhEWRbdib2jq\nO+2zSaIysw22UtTbSvBazwkAQE2BA4+suA4FeiNMk3R3pvTib5qIiIgoR6hmGoLBLI4k88YDPs3t\nTY4K2BUzLsVmK4pMBZkaFkUwaCAiIiLKEbHpSReSUb9Xc3uZpVA1A8N1DNnBoIGIiIgoRygvjn2h\nC2umYSygHTSUmq3QKzo/C5kaEKkwaCAiIiLKEcqZBs8snmkIiSJ6PaMoMJhQYg43tesYHdA8tsRs\nBaRMjo60MGggIiIiyhEmvQECwtfIszU9SZRE/J+DL8n9F/7Hgssw7HPjl2daNY8vNRfCoyi/WmIu\nzMg4SY1BAxEREVGO0AkCzHoDvKEgPEF/toczI/oUDdsA4MPhbgz5XJrH1hQ4YDda4DBacHH5XHS5\nR3Bbw7JMDZUUGDQQERER5RCTLhw0/OrMIdw4p2XWlRU9pwgYgPBahugi6DmFxXioZT1G/J5wsGCy\nQCeEVzE8uOTKjI+VJsyu/4VEREREec4vTiyAPusaRpOjIoujSb9O17Dq+ajfi9HIIujV5XNRbrGh\n3GLLxtBoErqpDyEiIiKiTLlr/sXy43yroOQLBfFU6x/w1bf34uDAWc1jYmca+r3jCIghAIDDaJnx\nMdL05HTQ8MILL2Dx4sXo6uqStx0+fBj33nsv1qxZgxtvvBHPP/98FkdIRERElF5Liqvlx75QEP2e\nMZwdH57kFbmj3dmDw85e9HvHEy5s7owJGpSdoB0mBg25KmfTk/r6+vD8889DECaq8fp8PmzZsgV3\n3303nn32WXR0dGDz5s2or6/Hhg0bsjhaIiIiovQwK9Yw/Kj9L/Ljr62+BbWFRdkYUtKUi7edPo/m\n/sHIoucFjkocG+1T7edMQ+7K2ZmGxx9/HJ/85CdV2/bt24dgMIiHHnoIFosFLS0t2LRpE3bv3p2l\nURIRERGllznBwufXeo9neCSp84dC8mOfGJ9adVYxy7CkpDpuv50zDTkrJ4OGV199FUePHsXmzZsh\nSRPdPNra2rBo0SLV7ENLSwtaW7Wnv4iIiIjyjUGn19xeoGj8lqu84kQ/hYAYktcqRH0weA4AYBB0\nuLK6CcWmAnlffWEJSiON3ij35Fx6ks/nw2OPPYZvfOMbMBrVJ4fT6YTD4VBtKy4uxsjISCaHSERE\nRJRxljwIGvwxC7dH/V6UWSaasX0w1AkAWFpaiyJTAR67ZKPco6HCYoNOyMn72YQsBA179+7Ftm3b\nVLMFkiRBEAQ88cQTOHnyJFasWIF169Zpvl458xClfK9k+Hw+uN3u1AZORNPi8/ky8hk8p4kyg+d0\n9hwd7sVfe0/i2uoFWFlSl+3haBr3eVXPe0eHUSCGr9NCkoh+zzgAoMFSJP8b2yOXo16P+rU081I5\nnzMeNGzcuBEbN27U3NfR0YF//ud/xi9+8QvN/SUlJTh9+rRq2/DwMIqLi1MaQ3d3N7q7u1N6DRHl\nLp7TRLMLz2ltHzjD1SRf6HgbxoIRuelZLun196ueP33kz/ioeQ7q9YUYFwMQEb756+ofQvtwezaG\nSNOUU+lJv/nNbzA+Po6NGzeqZhQ+/vGP48EHH8Ty5cuxa9cuiKIInS48fdXa2ooVK1ak9Dk1NTUp\nBxpEND1Op3PGv/x5ThNlDs/pDHn3yKS7dXVlWFJUlaHBJO/dky5gSJ023lUg4oamJegYHwSOdAAA\nls1bgEZbaTaGSAqpnM85FTTcd9992LRpk2rb1VdfjWeffRZNTU0wGo2w2WzYvn07HnjgARw5cgR7\n9uzBk08+mdLnmM1mWK1caEOUCR5PfMm9dOM5TZQ5PKdzwziCOfk7CkUmP+xGC8YiXZ7PeUdhtVrR\nO3xGPq62qBRWLnrOulTO55wKGgoLC1FYWKjaJggCysvL5e07duzAo48+imeeeQbl5eXYunUr1q9f\nn43hEhEREWVF7ILjXBHtYN1gK8Gy0jrsOvEOBrzj2PKXnfIxekEHh6JqEuWHnAoatLS3q/Pdmpub\nsXPnzgRHExEREc0uRp0+rnSpL0eDBn+kN4NZb0R9oXaK2Xx7eU6ux6DJsa4VERERUY5ZXDyxXqHC\nYovbr9U4LRdEgxmT3oAiU3z6UVWBHZ9bdnWmh0VpwKCBiIiIKMdsXnQ5bqlfhq+u+iiMGs3ecjE9\nyRsKYNgXLqNq1unh0OjuvK5qfl70m6B4OZ+eRERERHShKTIVYGNjuDqkVtDgi0lXmmlnx4fhCfqh\nEwQYdHo02EpVfbL2nvoAvz57SH5u1hth1sdfZtqN8YEE5QcGDUREREQ5LNszDe3DPfi/h/6o2va/\nllyFVeX18nNlwAAAc20lmu9lN5rTP0DKCKYnEREREeUwk9ZMQwaDho6xgaS2RRl1elxcPldzn1bK\nEuUHBg1EREREOcygNdOQwYXQo35v3LYxxbaQJKr2LSupVaUuKdkMnGnIVwwaiIiIiHKY1uX3+c40\nDHld6HGPJnVstEmb0qhi23jAp9qnnE1YX92s2lfE/gx5i2saiIiIiHLYUKQiEQCUmKwY9rvPa03D\niN+Drx/4DXyhAL6x5jZUFtgnPV5rpkG5LXa/Mp3qzvmrMN9RDk8wgOaiCpg0FkdTfuC/HBEREVEO\nG/COy48b7KUYHnTDP83qSZIk4TsfvAJvKAAAODbSN3XQoDHTEJ19ECUJHw53J3ytRW/Euqr50xor\n5RamJxERERHlsDpFZ+VqqwPA9NOT2pzd6PWMyc+NOj1EScQHg+fwVt8pdIzGL3AeC3jito0GvBAl\nCS+dbcPPTh1U7dOq9kT5jzMNRERERDnsnqY1+Ldjf8WaigZ4guEZgul2hO6OWcfgF0PY33cKLxzd\nL2/7piJlKSCG4I58ppIoSXAHfXit57hqu1lvwEdqF05rbJTbGDQQERER5bBqqwNfuOh6AMAfzh0G\nEL6YFyUJugRVihJxxSxa9oeC+N25dtW29wc7cf2cJQC0F0FHHRruxqDPBQC4cU4Lbq5fCglAgYEd\nn2cjpicRERER5Qlll+XplF11Bf2q534xNGk6kXKR89YVG/DFi26Qnz9/5E0AgEHQ4aP1S2ExGBkw\nzGKcaSAiIiLKEyadImgIBWHRp3aR7o4NGkJBGAT1PeSgou+CcqbBYbRAa2JjaUkNg4ULAIMGIiIi\nojyhnGnwhVKvoBSXniQG42YaxhKUU3WYLJAkKe49Pzp3acrjoPzDoIGIiIgoT6hmGtKUnhTbcVpZ\nYjU602AQdCjQGyFBHTR8smkN5tnLUx4H5R8GDURERER5Qj3TcP5Bgy8URDCm58PJsQHsOfkedIKA\nl862AQDsRgsEQYAQ05+6yVGR8hgoPzFoICIiIsoT0w0aDjt78Meuo6pGcUB4tsITE0gMeF34Xae6\nopLDZNF836opGsPR7MGggYiIiChPxKYntQ6dw69Ot+JjjRehpaQm4et+cmQ/hv3uuO0HBs7GbSs2\nFcAvhlSLpq9J0HvBpOel5IWC/9JEREREecKsn1h/4AsF8dyRNwAATx/ahx1XfSrh67QChlgfb7wI\nN9WHFzWfGhvEEwdflvetq5ovP15ZNgcHBzuxqKgq5fFT/mLQQERERJQnTNPo0+DXSGNyGC2qBc8A\n4FUcV2stSvh+9y64FMtL67CyrC6pz6fZgc3diIiIiPKESVHpyJvkmobY4AAIL2yOtaykduJz9AY0\nRxY5/03zJarjbEYLrqxugk3jPWj24kwDERERUZ7QCToYdXoExBAGva6kXqPstRA16Jt47YOLr0RF\ngQ1zbaWqYz679Gp0uZyY72BJVcrBoOHaa69FX18f9Ho9JEmCIAi44oorsH37dgDA4cOH8fjjj6O9\nvR1lZWW45557cN9992V51ERERESZYdIZEBBD6PWMJnW81kzDbQ3L8WLHAegFHVaX10PQaPVsNZjQ\nXFR53uOl2SHnggYA+MlPfoI1a9bEbff5fNiyZQvuvvtuPPvss+jo6MDmzZtRX1+PDRs2ZGGkRERE\nRJll1uvhCgLd7pGEx/S4R7HrxDtYVzVPs3P01TULUGgwoclRoRkwEMXKyTUNWi3KAWDfvn0IBoN4\n6KGHYLFY0NLSgk2bNmH37t0ZHiERERFRdpj1RgDAkE9dEUnZpO2Hba+i3dmDHx95E0M+dRqTThBg\n1Omxrmo+KtlngZKUk0HDCy+8gOuvvx6rV6/G5z//eQwNDQEA2trasGjRIlVE3NLSgtbW1mwNlYiI\niCijrAaj5nZvKIgB7zgefedX6POMydvPuZwAgDJzIW6pX4avrvpoRsZJs0vOBQ1Lly7FihUrsHfv\nXvz2t7/FyMgIHn74YQCA0+mEw+FQHV9cXIyRkcTTc0RERESzidVg0tzuDQXwavexuLUOHwydAwC0\nlNRgY+MK1BUWz/gYafbJ+JqGvXv3Ytu2barZguiC5yeeeALf//735e0FBQV49NFHceutt+Ls2bPy\nsbFSzcXz+Xxwu6duckJE58/n82XkM3hOE2UGz+nsswh6ze1O1xicnsQVlSqMVv5eSSWV8znjQcPG\njRuxcePGpI+fM2cOJElCX18fSkpKcPr0adX+4eFhFBenFjF3d3eju7s7pdcQUe7iOU00u/CcnpzX\nP665/ciJ4+gLDid8XUH/ONoH22dqWDTL5VT1pK6uLjzzzDP4yle+AqMxnK93/PhxCIKA+vp6LF++\nHLt27YIoitDpwplVra2tWLFiRUqfU1NTk3KgQUTT43Q6Z/zLn+c0UebwnM6+zm4dWrvig4Pq+jk4\n0DUKuIG51hKccU8cc1vdUqypXpDJYVIeSOV8zqmgoaysDH/84x9hMBiwdetWjI6O4lvf+hauvfZa\nVFZWYv369bDZbNi+fTseeOABHDlyBHv27MGTTz6Z0ueYzWZYrdYZ+imISMnj8cz4Z/CcJsocntPZ\nV2y1aW7/aecHGIg0fFtYUqUKGppKqvg7pTipnM85tRDabDbjueeew8mTJ7F+/XrcdtttmDt3Lr79\n7W8DAEwmE3bs2IE33ngDl156KR555BFs3boV69evz/LIiYiIiDLDZjDLj0vNVhSbCgBADhgAoKrA\nIZdT1Qs61NtKMjtImnVyaqYBABYsWIDnnnsu4f7m5mbs3LkzgyMiIiIiyh0G3cQ930ZbGQJSCM6h\niTvGS4qrcUlFAxYUVeC9gU4sLKqAzWjWeiuipOVc0EBEREREidXbSiAAkADcWN+CDwbPoXWoCwAg\nAPj8so9AJ+hQYChCzdyibA6VZhEGDURERER5pNRciH9Yfh0kAI32MnS7J/pVCRCgE3Iq+5xmCQYN\nRERERHlmYXGV/LjUXCg/FhHfz4ooHRiKEhEREeWxMkvh1AcRnScGDURERER5rMTEUqo08xg0EBER\nEeUxvaKa0sXlc7M4EprNuKaBiIiIKM99YcUGHBzsxA1zWrI9FJqlGDQQERER5bnmoko0F1Vmexg0\nizE9iYiIiIiIJsWggYiIiIiIJsWggYiIiIiIJsWggYiIiIiIJsWggYiIiIiIJsWggYiIiIiIJsWg\ngYiIiIiIJsWggYiIiIiIJsWggYiIiIiIJsWggYiIiIiIJsWggYiIiIiIJsWggYiIiIiIJsWggYiI\niIiIJsWggYiIiIiIJsWggYiIiIiIJsWggYiIiIiIJpWTQcOLL76I6667DitXrsQ999yD9vZ2ed/h\nw4dx7733Ys2aNbjxxhvx/PPPZ3GkRERERESzX84FDX/605/w/e9/H08//TT279+Pa665Bv/6r/8K\nAPD5fNiyZQvWrVuH1157DU899RR27NiBV155JcujJiIiIiKavQzZHkCsH//4x9i8eTOWLVsGANiy\nZYu8b9++fQgGg3jooYcgCAJaWlqwadMm7N69Gxs2bMjWkImIiIiIZrWcmmkQRREHDx6ETqfDnXfe\niUsuuQT3338/zp49CwBoa2vDokWLIAiC/JqWlha0trZma8hERERERLNeTgUNQ0ND8Pv9+MUvfoGn\nnnoKr7zyCsxmMx5++GEAgNPphMPhUL2muLgYIyMj2RguEREREdEFIePpSXv37sW2bdtUswWSJEEQ\nBDzyyCMAgL/927/F3LlzAQBf+MIXcPPNN+P06dPysbGU7zUZURQBAOPj4+f1MxBR8qLnW/T8Syee\n00SZx3OaaPZI5XzOeNCwceNGbNy4UXOfKIp4+umnYbfb5W11dXWQJAn9/f0oKSmRg4eo4eFhFBcX\nJ/XZPp8PADAwMICBgYFp/gRENB0+nw82my3t7wnwnCbKBp7TRLNHMudzTi2E1ul0aGxsRHt7u7yw\nubOzE4IgoK6uDsuXL8euXbsgiiJ0unBmVWtrK1asWJHU+xcVFaGxsRFms1l+PRHNLFEU4fP5UFRU\nlPb35jlNlHk8p4lmj1TO55wKGgDgnnvuwQ9/+ENcc801aGxsxFNPPYW1a9eipqYGZWVlsNls2L59\nOx544AEcOXIEe/bswZNPPpnUexsMBpSVlc3wT0BEsdJ9NzKK5zRRdvCcJpo9kj2fBUlrkUCW/eAH\nP8CuXf9/e/cfE3X9xwH8CaJiGdn1i7x0Fiu5O+6OOIyElgubP7ayZZrK+kFjgn9cNapRNqTMjbac\n55wokwwZUHx3Ekm6BHRRaS1Ix7i6aMrNll53uIxLfqw7tdf3D8Z9vwh84Erug/B8bGxw7w/4HON5\n7nWfz70//0FPTw9SU1OxZcsWaDQaAEB7ezsKCgrw448/4rbbbkNOTg7WrFmjcmIiIiIioolrXA4N\nREREREQ0fvCCQSIiIiIiUjSph4Zjx44hLS0Nr7322pDrJSUlSEhIQHV1teLP8fv9yM/Px6JFi5Ca\nmorc3NwB9444d+4c1q9fj5SUFCxevBg2m+0fZWpubsbatWthsVjw2GOPobi4eNifEwgEUFBQgEWL\nFmHhwoV45ZVX4PP5guu//fYbcnJykJKSgvT0dMX3hShlOnz4MFasWIEHHngg+HOG27YrXJn6iQhW\nrlyJ559/fthjwpGpubkZ8fHxMJvNMJvNMJlMMJvNqK+vVy0T0LfN2htvvAGLxYKUlBQUFBQgEAiM\neaaxxE6z0+w0Oz0UdpqdVsrETo/OpB0a9u7di8LCQsybN2/I9aysLLS0tAy6mdxQtm7divb2duzf\nvx91dXUIBALIz88PrlutVsydOxeNjY0oLS1FXV0dKisrQ8rk8XiQk5ODlStXorm5GTabDaWlpTh4\n8OCQmWw2G9ra2mC321FfXw8RwcaNGwdkio2NxRdffIGysjIcOXIEZWVlIWVyOp3YuHEj8vLy0NLS\ngj179uDTTz/FRx99pFqm/1dZWRm8m/hwwpVJq9WitbUVra2tcDgcaG1txdKlS1XN9NZbb8Hv96Ox\nsRGfffYZ3G73sE+Q1yrTWGKn2elwZmKnxx47zU6HMxM7PQoySVVUVEhXV5e8+eab8uqrrw5aLy4u\nFhGRRx55RPbv3z9g7bvvvhOTySR///23XLp0SZKSkuTrr78Orp86dUp0Op1cuHBBWlpaxGAwSHd3\nd3C9srJSHn/88ZAyORwOKSwsHPDYSy+9JJs2bRIRke+//15MJpMEAgG5fPmyJCcnS2NjY/BYl8sl\n8fHxcv78eXE4HGIwGKSrqyu4XlVVJcuXLw8pU3t7uxw9enTAY1arVdVM/To6OiQ1NVV27Nghzz33\nXPBxNTI1NTVJenr6kDnVyuR2uyUhIUEuXLgQ1kxjiZ1mp9lpdrofO92HnR5dJnZ6dMbdlqvh8uyz\nzyqub9iwYdi1lJQUtLa2AgB++eUX9Pb2Qq/XB9fvu+8+REVFwel04tdff8XcuXNx4403Btf1ej1c\nLhf8fj+mT58+qkxGoxFGo3HAY16vF/PnzwcAJCcnBzOdOXMG3d3d0Ol0wWPvvfdeREdHw+l0oqOj\nA1qtdsAWW3q9HmfOnEFvby9uuOGGUWWKi4tDXFwcgL59fpuamnDy5Els3bpVtUz93nvvPaxbtw5a\nrRYnTpwIPq5Wpu7ublitVpw4cQLTp0/Hiy++iMzMTNUynTx5ErNnz8aBAwewb98+REZGYsWKFcjN\nzUVkZOSYZRpL7DQ7zU6z0/3Y6T7sNDt9LTs9aS9Pulb6rxe7+vRoTEwMOjs74fP5Bq3dfPPNEJEB\n15qFqqKiAmfPnsW6deuGzXT1jTqUMvXfVbuzszPkLLW1tTAajbBarcjNzUVaWpqqmY4dO4affvoJ\n2dnZiseFK9PMmTMxf/58ZGZm4vjx4ygsLERRURFqampUy+T1eoMfDQ0N2LlzJ6qrq4c8HR/uvye1\nsdPs9EjY6esLO81Oj4SdHh0ODdeIhHHn2srKSuzcuRPFxcXB+1eEmula5n3yySfxww8/4IMPPsCu\nXbtgt9tVyxQIBLBlyxZs2rQJ06ZNG9X3jHUmvV6P8vJyJCcnIyoqCmlpaVi7du2QT0bhyiQiuHLl\nCvLy8jBjxgyYTCasXr0ahw8fVi3TeMNOs9PDYaevT+w0Oz0cdnp0ODT8S7fccgsADHo14s8//8St\nt94KjUYzaIrz+XyIjIwMfm8otm/fjpKSEpSXlyMxMXHIY/qfoIbKpNFooNFoBq35fD5EREQoPrkp\niYyMRFJSEjIyMlBRUaFapt27d0Ov1+Phhx8GoFwSNX5P/bRaLc6fP69apttvvx3R0dGIivrfFYpa\nrRa///67apnGC3a6DzsdGnZ6/GKn+7DToWGnB5u072m4VubNm4eZM2fC6XTijjvuAAC0tbVBRGAw\nGBATEwO3242uri7cdNNNAACHw4H7779/1BN2v3379uHzzz+H3W5HbGzssMfNmTMHMTExcDqduOuu\nuwAAp06dwqVLl2A0GtHR0QGPxwOfzxc8PeVwOBAXF4cZM2aMOk9JSQlOnz4dvDYSACIiIjB16lTV\nMh08eBAXL17EQw89BKDvFY1AIICFCxfiwIEDuPPOO8Oeqa6uDp2dnQNOUbtcLsyZM0e131NcXBx6\nenpw7tw53H333QAAt9uN2bNnq5ZpvGCn2emRsNPXF3aanR4JOz06PNPwL02ZMgWrVq1CcXExOjo6\n8Mcff2D79u1YtmwZZs2aBaPRCJ1Oh23btqGnpwculwvl5eXIyMgI6d85e/Zs8FSn0hMR0PdqwjPP\nPIPi4mJ4v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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "\n", "f, na_ax = plt.subplots(1, 3, sharey=True)\n", "for ax1, idx in zip(na_ax.ravel(), [5, 25, 35]):\n", " df_plot = pd.DataFrame(d_learning_k[idx]['pnl']['test']).mean(axis=1)\n", " df_plot.fillna(method='ffill').plot(legend=False, ax=ax1)\n", " ax1.set_title('idx: {}'.format(idx + 1), fontsize=10)\n", " ax1.set_ylabel('PnL', fontsize=8)\n", " ax1.set_xlabel('Time', fontsize=8)\n", "f.tight_layout()\n", "s_title = 'Cumulative PnL in Diferent Days\\n'\n", "f.suptitle(s_title, fontsize=16, y=1.03);" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "The model was able to make money in two different days after being trained in the previous session to each day. The performance of the third day was pretty bad. However, even wasting a lot of money at the beginning of the day, the agent was able to recover the most of its loss at the end of the session.\n", "\n", "Looking at just to this data, the performance of the model looks very unstable and a little disapointing. In the next subsection, we will see why it is not that bad." ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "### 4.2. Justification\n", "```\n", "Udacity:\n", "\n", "In this section, your model’s final solution and its results should be compared to the benchmark you established earlier in the project using some type of statistical analysis. You should also justify whether these results and the solution are significant enough to have solved the problem posed in the project. Questions to ask yourself when writing this section:\n", "- Are the final results found stronger than the benchmark result reported earlier?\n", "- Have you thoroughly analyzed and discussed the final solution?\n", "- Is the final solution significant enough to have solved the problem?\n", "```\n" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "Lastly, I am going to compare the final model with the performance of a random agent. We are going to compare the performance of those agents in an out-of-sample test.\n", "\n", "As the learning agent follows strictly the policy learned, I will simulate the operations of this agent on the datasets tested just once. Even though I had run more trials, the return would be the same. However, I will simulate the operations of the random agent $20$ times at each dataset. As this agent can take any action at each run, the performance can be very good or very bad. So, I will compare the performance of the learning agent to the average performance of the random agent.\n", "\n", "In the figure below we can see how much money each one has made in the first dataset used in this project, from 08/16/2016. The learning agent was trained using data from 08/15/2016, the previous day." ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 36 s, sys: 135 ms, total: 36.1 s\n", "Wall time: 36.2 s\n" ] } ], "source": [ "# analyze the logs from the out-of-sample random agent\n", "import qtrader.eda as eda;reload(eda);\n", "s_fname = 'log/train_test/sim_Wed_Oct__5_111907_2016.log' # idx = 15\n", "%time d_rtn_test_1r = eda.simple_counts(s_fname, 'BasicAgent')" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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NJTY2ltDQULPF6hWREVvRYGzZsoVNmzYxZ84cAN588026du1ao0BaG21YIisr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\n8WvunkYIA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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import pandas as pd\n", "import scipy\n", "ax1 = pd.DataFrame(d_rtn_test_2['pnl']['test']).mean(axis=1).fillna(method='ffill').plot(legend=True, label='LearningAgent_k')\n", "pd.DataFrame(d_rtn_test_1r['pnl']['test']).mean(axis=1).fillna(method='ffill').plot(legend=True, label='RandomAgent', ax=ax1)\n", "ax1.set_title('Cumulative PnL Comparision\\n')\n", "ax1.set_xlabel('Time')\n", "ax1.set_ylabel('PnL');\n", "#performs t-test\n", "a = [float(pd.DataFrame(d_rtn_test_2['pnl']['test']).iloc[-1].values)] * 2\n", "b = list(pd.DataFrame(d_rtn_test_1r['pnl']['test']).fillna(method='ffill').iloc[-1].values)\n", "tval, p_value = scipy.stats.ttest_ind(a, b, equal_var=False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "A Welch's unequal variances t-test was conducted to compare if the PnL of the learner was greater than the PnL of a random agent. There was a significant difference between the performances (t-value $\\approx 7.93$; p-value $< 0.000$). These results suggest that learning agent really outperformed the random agent, the chosen benchmark. Finally, I am going to perform the same test using the datasets used in the previous subsection." ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "t-value = 7.928302, p-value = 0.00000019\n" ] } ], "source": [ "print \"t-value = {:0.6f}, p-value = {:0.8f}\".format(tval, p_value)" ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "collapsed": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 1min 52s, sys: 433 ms, total: 1min 52s\n", "Wall time: 1min 52s\n" ] } ], "source": [ "# analyze the logs from the out-of-sample tests\n", "import qtrader.eda as eda;reload(eda);\n", "l_fname = ['log/train_test/sim_Thu_Oct__6_172024_2016.log', # idx = 25\n", " 'log/train_test/sim_Thu_Oct__6_181735_2016.log', # idx = 35\n", " 'log/train_test/sim_Thu_Oct__6_184957_2016.log'] # idx = 5\n", "def foo(l_fname):\n", " d_basic = {}\n", " for idx, s_fname in zip([25, 35, 5], l_fname):\n", " d_basic[idx] = eda.simple_counts(s_fname, 'BasicAgent')\n", " return d_basic\n", "\n", "%time d_basic = foo(l_fname)" ] }, { "cell_type": "code", "execution_count": 26, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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ttym+Wfp1b5vOyLrSpUsTEBBAmzZtiI6O5sCBAxgaGjJ79mz69euXrrh79+7N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jeBjg4YtpsIWsPh0+ePo8o/huXeWChHRPU4TI/hoFWqcI9Td4ExCaJ1QbiLPrDgJFi1RCQRlNIJ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\nzUPDhg3x+eef44svvsAff/yB9evXS+ccO3YMr732mjSo92Hy8/ORlJSEx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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import scipy.stats\n", "\n", "f, na_ax = plt.subplots(1, 3, sharey=True)\n", "l_stattest = []\n", "for ax1, idx in zip(na_ax.ravel(), [5, 25, 35]):\n", " # plot results\n", " df_learning_agent = pd.DataFrame(d_learning_k[idx]['pnl']['test']).mean(axis=1)\n", " df_learning_agent.fillna(method='ffill').plot(legend=True, label='LearningAgent_k', ax=ax1)\n", " df_random_agent = pd.DataFrame(d_basic[idx]['pnl']['test']).mean(axis=1)\n", " df_random_agent.fillna(method='ffill').plot(legend=True, label='RandomAgent', ax=ax1)\n", " #performs t-test\n", " a = [float(pd.DataFrame(d_learning_k[idx]['pnl']['test']).iloc[-1].values)] * 2\n", " b = list(pd.DataFrame(d_basic[idx]['pnl']['test']).iloc[-1].values)\n", " tval, p_value = scipy.stats.ttest_ind(a, b, equal_var=False)\n", " l_stattest.append({'key': idx+1,'tval': tval, 'p_value': p_value/2})\n", " # set axis\n", " ax1.set_title('idx: ${}$ | p-value : ${:.3f}$'.format(idx+1, p_value/2.), fontsize=10)\n", " ax1.set_ylabel('PnL', fontsize=8)\n", " ax1.set_xlabel('Time', fontsize=8)\n", "f.tight_layout()\n", "s_title = 'Cumulative PnL Comparision in Diferent Days\\n'\n", "f.suptitle(s_title, fontsize=16, y=1.03);" ] }, { "cell_type": "code", "execution_count": 27, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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keyp_valuetval
060.0000055.972489
1260.4324720.172402
2360.4698780.076584
\n", "
" ], "text/plain": [ " key p_value tval\n", "0 6 0.000005 5.972489\n", "1 26 0.432472 0.172402\n", "2 36 0.469878 0.076584" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pd.DataFrame(l_stattest)" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "In the dataset with index 26 and 36, the random agent outperformed the learning agent most the time, but at the end of these days, the learning agent was able to catch up the random agent performance.\n", "On this days, the t-test also rejected that the PnL of the learner was greater than the PnL from the random agent. In the dataset with index 6, the learning agent outperformed the random agent by a large margin, also confirmed by the t-test (t-value $\\approx 5.97$; p-value $< 0.000$). Curiously, in the worst day of the test, the random agent also performed poorly, suggesting that it wasn't a problem of my agent, but something that has happened on the market.\n", "\n", "I believe these results are encoraging because they suggested that using the same learning framework on different days we can successfully find practical solutions that adapt well to new circumstances." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## 5. Conclusion\n", "\n", "In this section, I will discuss the final result of the model, summarize the entire problem solution and suggest some improvements that could be made.\n", "\n", "### 5.1. Final Remarks\n", "\n", "```\n", "Udacity:\n", "\n", "Free-Form Visualization:\n", "\n", "In this section, you will need to provide some form of visualization that emphasizes an important quality about the project. It is much more free-form, but should reasonably support a significant result or characteristic about the problem that you want to discuss. Questions to ask yourself when writing this section:\n", "- Have you visualized a relevant or important quality about the problem, dataset, input data, or results?\n", "- Is the visualization thoroughly analyzed and discussed?\n", "- If a plot is provided, are the axes, title, and datum clearly defined?\n", "```\n", "\n", "In this project, We have proposed the use of the reinforcement learning framework to build an agent that learns how to trade according to the market states and its own conditions. After that the agent's policy was optimized to the previous sessions to the days it would have traded (in the out-of-sample tests), the agent would have been able to generate the result exposed in the figure below." ] }, { "cell_type": "code", "execution_count": 109, "metadata": { "collapsed": false }, "outputs": [ { "data": { "image/png": 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lZWWYPXs2unfvDm9vb7zzzjv4+++/2Xz5EIDg4GBMmzYNsbGxGDt2LFavXo3g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Npeh9UZ09Hi6IWZ1yM2hMjscPQhSm+EcQiFItQ4/N6g+wZhsU03x6LJLhfIeGj+VXjiyAea7Zdk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\nEiyiG7ymLnRst8tUYE/o2hvo2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"text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# group all data generated previously\n", "df_aux = pd.concat([pd.DataFrame(d_learning_k[5]['pnl']['test']),\n", " pd.DataFrame(d_rtn_test_2['pnl']['test']),\n", " pd.DataFrame(d_learning_k[25]['pnl']['test']),\n", " pd.DataFrame(d_learning_k[35]['pnl']['test'])])\n", "d_data = df_aux.to_dict()\n", "df_plot = eda.make_df(d_data).reset_index(drop=True)[1]\n", "\n", "df_aux = pd.concat([pd.DataFrame(d_basic[5]['pnl']['test']).mean(axis=1),\n", " pd.DataFrame(d_rtn_test_1r['pnl']['test']).mean(axis=1),\n", " pd.DataFrame(d_basic[25]['pnl']['test']).mean(axis=1),\n", " pd.DataFrame(d_basic[35]['pnl']['test']).mean(axis=1)])\n", "d_data = pd.DataFrame(df_aux).to_dict()\n", "df_plot2 = eda.make_df(d_data).reset_index(drop=True)[0]\n", "ax1 = df_plot.plot(legend=True, label='LearningAgent_k')\n", "df_plot2.plot(legend=True, label='RandomAgent')\n", "ax1.set_title('Cumulated PnL from Simulations\\n', fontsize=16)\n", "ax1.set_ylabel('PnL')\n", "ax1.set_xlabel('Time Step');" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "The chart above shows the accumulated return in four different days generated by the learning agent and by the random agent. Although the learning agent has not made money all the time, it still beat the performance of the random agent on the period of the tests. It also would have beaten a buy-and-hold strategy in BOVA11 and PETR4. Both would have lost money in the period, R\\$ $-14,00$ and R\\$ $-8,00$, respectively." ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "BOVA11 -14.0\n", "PETR4 -8.0\n", "dtype: float64" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "((df_last_pnl)*100).sum()" ] }, { "cell_type": "markdown", "metadata": { "collapsed": true }, "source": [ "```\n", "Udacity:\n", "\n", "Reflection:\n", "\n", "In this section, you will summarize the entire end-to-end problem solution and discuss one or two particular aspects of the project you found interesting or difficult. You are expected to reflect on the project as a whole to show that you have a firm understanding of the entire process employed in your work. Questions to ask yourself when writing this section:\n", "- Have you thoroughly summarized the entire process you used for this project?\n", "- Were there any interesting aspects of the project?\n", "- Were there any difficult aspects of the project?\n", "- Does the final model and solution fit your expectations for the problem, and should it be used in a general setting to solve these types of problems?\n", "```" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To find the optimal policy we have used Q-Learning, a model-free approach to reinforcement learning. We trained the agent by simulating several runs on the same dataset, allowing the agent to explore the results of different actions on the same environment. So, we have back-tested the policy learned on the same dataset and found out that the policy learned not always converge to a better one. We noticed that this non-convergence could be related to the nature of our problem.\n", "\n", "So, we refined the model testing different configurations of the model parameters and compare the PnL of the new policy to the old one backtesting them against a different dataset. Finally, after we selected the best parameters, we trained the model in different days and tested against the subsequent sessions. \n", "\n", "We compared these results to the returns of a random agent and concluded that our model was significantly better during the period of the tests.\n", "\n", "One of the most interesting parts of this project was to define the state representation of the environment. I find out that when we increase the state space too much, it becomes very hard the agent learns an acceptable policy in the number of the trials we have used. The number of trials used was mostly determined by the time it took to run (several minutes)\n", "\n", "It was interesting to see that, even clustering the variables using k-means, the agent was still capable of using the resulting clusters to learn something useful from the environment. \n", "\n", "Building the environment was the most difficult and challenging part of the entire project. Not just find an adequate structure for build the order book wasn't trivial, but make the environment operates it correctly was difficult. It has to manage different orders from various agents and ensure that each agent can place, cancel or fill orders (or have orders been filled) in the right sequence.\n", "\n", "Overall, I believe that the simulation results have shown initial success in bringing reinforcement learning techniques to build algorithmic trading strategies. Develop a strategy that doesn't perform any [arbitrage](https://en.wikipedia.org/wiki/Arbitrage) and still never lose money is something very unlikely to happen. This agent was able to mimic the performance of an average random agent sometimes and outperforms it other times. In the long run, It would be good enough." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### 5.2. Improvement\n", "```\n", "Udacity:\n", "\n", "In this section, you will need to provide discussion as to how one aspect of the implementation you designed could be improved. As an example, consider ways your implementation can be made more general, and what would need to be modified. You do not need to make this improvement, but the potential solutions resulting from these changes are considered and compared/contrasted to your current solution. Questions to ask yourself when writing this section:\n", "- Are there further improvements that could be made on the algorithms or techniques you used in this project?\n", "- Were there algorithms or techniques you researched that you did not know how to implement, but would consider using if you knew how?\n", "- If you used your final solution as the new benchmark, do you think an even better solution exists?\n", "```\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Many areas could be explored to improve the current model and refine the test results. I wasn't able to achieve a stable solution using Q-Learning, and I believe that it is most due to the non-deterministic nature of the problem. So, we could test [Recurrent Reinforcement Learning](https://goo.gl/4U4ntD), for instance, which \\cite{du1algorithm} argued that it could outperform Q-learning in the sense of stability and computational convenience.\n", "\n", "Also, I believe that different state representations should be tested much deeper. The state observed by the agent is one of the most relevant aspects of reinforcement learning problems and probably there are better representations that the one used in this project to the given task.\n", "\n", "Another future extension to that project also could include a more realistic environment, where other agents respond to the actions of the learning agent, and lastly, we could test other reward functions to the problem posed. Would be interesting to include some future information in the response of the environment to the actions of the agent, for example, to see how it would affect the policies learned." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "*Style notebook and change matplotlib defaults*" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\n", "\n", "\n", "\n" ], "text/plain": [ "" ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#loading style sheet\n", "from IPython.core.display import HTML\n", "HTML( open('ipython_style.css').read())" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "collapsed": false }, "outputs": [], "source": [ "#changing matplotlib defaults\n", "%matplotlib inline\n", "import seaborn as sns\n", "sns.set_palette(\"deep\", desat=.6)\n", "sns.set_context(rc={\"figure.figsize\": (8, 4)})\n", "sns.set_style(\"whitegrid\")\n", "sns.set_palette(sns.color_palette(\"Set2\", 10))" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] } ], "metadata": { "anaconda-cloud": {}, "kernelspec": { "display_name": "Python [conda env:python2]", "language": "python", "name": "conda-env-python2-py" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.12" } }, "nbformat": 4, "nbformat_minor": 0 }