Bandit-tutorial.ipynb

bandit-tutorial.ipynb

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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/kiwamizamurai/ad94f49d9a85969f0ecaa8cc2bf1925c/bandit-tutorial.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eTP8zIRlWFdM",
        "colab_type": "text"
      },
      "source": [
        "## Preface\n",
        "\n",
        "強化学習に入門するとMDPに出会いました。\n",
        "\n",
        "そして完全にoverwhelmed状態になったのでレベルを落としBandit Algorithmから始めます。\n",
        "\n",
        "この記事は強化学習の知識ゼロの僕によるBanditを実装と、MDPの入り口に触れるためのメモです。\n",
        "\n",
        "\n",
        "### Keywords\n",
        "\n",
        "- Exploration / Exploitation\n",
        "- MAB (Murti-Armed-Bandit)\n",
        "- Advertising Technology\n",
        "- A / B Test\n",
        "- Bayesian A / B Test\n",
        "- $\\epsilon$ - Greedy\n",
        "- UCB (Upper Confidence Bound)\n",
        "- Thompson Sampling\n",
        "- MDP (Markov decision process)\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zoep6P4-X4Ha",
        "colab_type": "text"
      },
      "source": [
        "## Exploration / Exploitation\n",
        "\n",
        "- Exploration is 探索\n",
        "- Exploitation is 活用\n",
        "\n",
        "この考え方は日常的にも多く存在します。たとえば僕を例にして説明します。\n",
        "\n",
        "ラーメンが好きで毎回行きつけのラーメン屋さんにいくんですよね。もちろん、毎回いっているということはそこが美味しいって経験からわかっているので通っているんです。これがExploitationです。\n",
        "\n",
        "しかし、同じラーメン屋さんにばかり通っていると仮に近くにもっと美味しいラーメン屋さんやつけ麺屋さんができてもその存在を知り得ないですよね。なのでたまには自分の知らないお店に期待していきたくなりますよね。で僕ももちろん3回に1回くらいの割合で新しいお店を体験します。これがExplorationです。\n",
        "\n",
        "ただ、新しいお店だと「美味しい！」時と「普通かなー」な時と「んー」な時がありますよね。これらを報酬といいます。もちろん報酬の高い、つまり「美味しい！」を選択できるようなExplorationができれば理想ですね。\n",
        "\n",
        "これらを考慮すると、ベストな選択としては行きつけでExploitationしつつも期待度の高いお店にExplorationしたいですよね。\n",
        "\n",
        "> けどどんな割合でこれを実行すればいいんやー、、、、、\n",
        "\n",
        "そこでBandit Algorithmの登場です。"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1DsTbCXfZg7T",
        "colab_type": "text"
      },
      "source": [
        "## Murti-Armed-Bandit\n",
        "\n",
        "上記のように複数の選択肢に対してExploration / Exploitationを考える問題を多腕バンディット問題といいます。\n",
        "\n",
        "簡単にまとめてみますと\n",
        "\n",
        "> バンディットアルゴリズム問題とは\n",
        "\n",
        "- 期待値がわからないK個の選択肢が存在する\n",
        "- N回の試行全てにおいて最善の選択肢を選び続けトータルの報酬を最大化したい\n",
        "\n",
        "という感じです。（お気づきの方もいるかもしれませんが状態$S$を考えません。）\n",
        "\n",
        "\n",
        "具体的にどんな例がMABに応用できるかといいますと\n",
        "\n",
        "- 広告, A/B test\n",
        "\n",
        "です。いったんBanditからは離れてこれについてちょっと深入りしていきます。"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "saTiTB34dDsz",
        "colab_type": "text"
      },
      "source": [
        "## Advertising Technology\n",
        "\n",
        "> 広告 $\\times$ テクノロジー\n",
        "\n",
        "目的は、広告に関わる全住民つまり、広告主側と媒体側（広告主，メディア，消費者）をwin-winの関係にすることです。\n",
        "\n",
        "そのなかでもReal time bidding（RTB）がキーワードになります。それを説明する前に次の用語を簡単に\n",
        "\n",
        "- DSP (Demand-Side Platform)\n",
        "\n",
        "広告主側の広告効果を最適化するため、ユーザーに適した単価の安い配信先を探す\n",
        "\n",
        "- SSP (Supply Side Platform)\n",
        "\n",
        "媒体側の広告収益を最適化するため、より高額な広告に入札する\n",
        "\n",
        "つまり、DSPが「この広告貼ってー」とお願いし、SSPが「ええよー」と返します。\n",
        "\n",
        "しかし、一対一関係ではないので「俺の広告も貼ってくれー」といろんな人がお願いします。\n",
        "\n",
        "（SSPも複数あります。サイトA、サイトB的な感じです）\n",
        "\n",
        "そんなマーケットのことをRTBといいます。\n",
        "\n",
        "複数のDSPが各々資金を持ってSSPに交渉し、最も価格の高いDSPをSSPが決定します。\n",
        "\n",
        "ただ値段の妥当性がわからないですよね。そこで次の用語が登場します。\n",
        "\n",
        "- CPM：Cost Per Mile．1000PVあたりの単価．\n",
        "- CPC：Cost Per Click．1クリックあたりの単価．\n",
        "- CPI：Cost Per Install．1インストールあたりの単価．\n",
        "- LTV：Life Time Value．1ユーザがもたらす収益．\n",
        "- CTR：Click Through Rate．クリック率．\n",
        "- CVR：ConVersion Rate．コンバージョン率\n",
        "\n",
        "これらの指標をもちいてDSPの値段が決定されたりします。これ以上話すとやばいので気になる方は次や参考文献からどうぞ。\n",
        "\n",
        "- https://speakerdeck.com/kaky0922/treasure-data-tech-talk-20160425\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AZNQ6zVHhzXS",
        "colab_type": "text"
      },
      "source": [
        "## Bayesian A/B Test\n",
        "\n",
        "A/BテストとはAとBどっちがいいの？\n",
        "\n",
        "を統計学的仮説検定を元に検証する試験のことです。\n",
        "\n",
        "Bayesian A/Bテストとは\n",
        "\n",
        "A/Bテストをベイズでやろう！！のことです。\n",
        "\n",
        "たとえば商品Aの購入率が$p$、商品Bの購入率が$q$としたとき\n",
        "\n",
        "分布に有意差あんの？をベイズで解決します。\n",
        "\n",
        "- http://tdual.hatenablog.com/entry/2018/04/21/004620"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Pk4-Rk-qjRWF",
        "colab_type": "text"
      },
      "source": [
        "## あらためて　Bandit\n",
        "\n",
        "これらを踏まえてBanditをおさらいすると\n",
        "\n",
        "バンディットアルゴリズムはアームを選択した結果得られる報酬を逐次的に反映し、次のアームの選択に活かすことからA/Bテストに比べて機会損失の低減が見込めます。\n",
        "\n",
        "加えてですねえ、A/Bテストは事前分布の問題もあるのでねえ、、\n",
        "\n",
        "\n",
        "では次のセクションで最適化に移るためにBandit Algorithmを定式化します。\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0NyclHqptdto",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        },
        "outputId": "9e42bd88-6ff5-4291-eef4-d316e8aa2427"
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "from collections import Counter\n",
        "sns.set()\n",
        "\n",
        "plt.rcParams[\"figure.figsize\"] = (18, 9)\n",
        "plt.rcParams[\"font.size\"] = 18\n",
        "\n",
        "from tqdm import tqdm_notebook as tqdm\n",
        "!jupyter nbextension enable --py --sys-prefix widgetsnbextension"
      ],
      "execution_count": 109,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Enabling notebook extension jupyter-js-widgets/extension...\n",
            "      - Validating: \u001b[32mOK\u001b[0m\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kAVuqdeSnD4l",
        "colab_type": "text"
      },
      "source": [
        "## A Bernoulli multi-armed bandit\n",
        "\n",
        "$$ \\langle \\mathcal{A}, \\mathcal{R} \\rangle  $$\n",
        "\n",
        "where\n",
        "\n",
        "- $K$ arms with reward probabilities, $\\{ \\theta_1, \\cdots, \\theta_K \\}$\n",
        "- At each time step $t$, take an action $a$ on one arm and receive a reward $r$\n",
        "- $\\mathcal{A}$ is a set of actions.\n",
        "\n",
        "The value of action $a$ is the expected reward\n",
        "\n",
        "$$\n",
        "\\mathcal{Q} (a) = \\mathbb{E} [r|a] = \\theta\n",
        "$$\n",
        "\n",
        "- $\\mathcal{R}$ is a reward function. In the case of Bernoulli bandit, we observe a reward $r$.\n",
        "\n",
        "At the time step $t$\n",
        "\n",
        "$$ r_t = \\mathcal{R} (a_t) $$\n",
        "\n",
        "may return reward 1 with a probability $\\mathcal{Q}(a_t)$ or 0 otherwise\n",
        "\n",
        "It is a simplified version of Markov decision process, as there is no state $\\mathcal{S}$."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mvJ0dVMGnAjF",
        "colab_type": "text"
      },
      "source": [
        "## Objective of Bandit\n",
        "\n",
        "Objective funciton is cumulative reward (Optimization is Maximization)\n",
        "\n",
        "$$  objective = \\sum_{i=1}^{T} r_t   $$\n",
        "\n",
        "\n",
        "If we know the optimal action with the best reward, then the goal is same as to minimize the potential regret or loss by not picking the optimal action.\n",
        "\n",
        "The optimal reward probability $\\theta^*$ of the optimal action $a^*$ is:\n",
        "\n",
        "$$\n",
        "\\theta^* = \\mathcal{Q}(a^*) = \\max_{a \\in  \\mathcal{A}}  \\mathcal{Q}(a)  =  \\max_{1 \\leq i \\leq K} \\theta_i\n",
        "$$\n",
        "\n",
        "Our loss function is the total regret we might have by not selecting the optimal action up to the time step $T$:\n",
        "\n",
        "$$\n",
        "\\mathcal{L}_T = \\mathbb{E} \\left[  \\sum_{t=1}^{T} \\left(  \\theta^* - \\mathcal{Q}(a_t)  \\right)  \\right]\n",
        "$$"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ugAKG6q9P2jm",
        "colab_type": "text"
      },
      "source": [
        "## Opimization Algorithms\n",
        "\n",
        "ではBandit Algorithmの最適化アルゴリズムを見ていきます。\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mguEabPVkFYm",
        "colab_type": "text"
      },
      "source": [
        "\n",
        "### $\\epsilon$ - Greedy\n",
        "\n",
        "- パラメータ$\\epsilon \\in (0,1)$を設定 (small)\n",
        "- $\\epsilon$の確率でExploration\n",
        "   - ランダムでArmを選択\n",
        "- $1-\\epsilon$の確率でExploitation\n",
        "   - 経験を元に、最大の行動価値を持つArmを選択\n",
        "\n",
        "\n",
        "経験を元に算出される行動価値は次で定義されます\n",
        "\n",
        "$$\n",
        "\\hat{\\mathcal{Q}}_t (a)  = \\frac{1}{N_t(a)} \\sum_{\\tau=1}^{t}  r_\\tau  \\mathbb{1} [a_\\tau = a]\n",
        "$$\n",
        "\n",
        "ここで\n",
        "\n",
        "$$\n",
        "N_t(a) = \\sum_{\\tau=1}^{t} \\mathbb{1} [a_\\tau=a]\n",
        "$$\n",
        "\n",
        "はaction=$a$が選択された総数です\n",
        "\n",
        "したがってExploitationは次のように定式化されます\n",
        "\n",
        "$$  \\hat{a}_t^* = \\arg \\max_{a\\in \\mathcal{A}} \\hat{\\mathcal{Q}_t} (a)   $$"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vX_QPFDpV8z_",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "class BernoulliArm():\n",
        "    def __init__(self, p):\n",
        "        self.p = p\n",
        " \n",
        "    def get_reward(self):\n",
        "        if np.random.random() > self.p:\n",
        "            return 0.0\n",
        "        else:\n",
        "            return 1.0"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Oq4LRg4GwlS_",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "probs = [0.054,  0.069,  0.080,  0.097,  0.112, 0.119,  0.121,  0.144,  0.155,  0.274]\n",
        "n_arms = len(probs)\n",
        "\n",
        "Trials = 10000   # 試行回数\n",
        " \n",
        "arms = pd.Series(map(lambda x: BernoulliArm(x), probs))"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0Jq1A0J6WE1Z",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "class EpsilonGreedy():\n",
        "  def __init__(self, epsilon):\n",
        "    self.epsilon = epsilon        # Parameter epsilon (small)\n",
        "    self.counts = []              # LIST arm count \n",
        "    self.rewards = []             # LIST rewards\n",
        "    self.expectations = []        # LIST expectation\n",
        " \n",
        "  def initialize(self, n_arms):\n",
        "    self.counts = np.zeros(n_arms)\n",
        "    self.rewards = np.zeros(n_arms)\n",
        "    self.expectations = np.zeros(n_arms)\n",
        "\n",
        "  def select_arm(self):\n",
        "    # Exploitation\n",
        "    if np.random.random() > self.epsilon:  \n",
        "        return np.argmax(self.expectations)\n",
        "    # Exploration\n",
        "    else:\n",
        "        return np.random.randint(0, len(self.rewards))\n",
        "\n",
        "  def update(self, chosen_arm, reward):\n",
        "    self.counts[chosen_arm] += 1\n",
        "    self.rewards[chosen_arm] += reward\n",
        "    sum_select_arm = self.counts[chosen_arm]\n",
        "    sum_reward = self.rewards[chosen_arm]\n",
        "    expectation = float(sum_reward/sum_select_arm)\n",
        "    self.expectations[chosen_arm] = expectation"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DTWGAivUySVe",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def demonstrate(algo, arms, Trials):\n",
        "  chosen_arms = np.zeros(Trials)\n",
        "  cumulative_rewards = np.zeros(Trials)\n",
        "  algo.initialize(len(arms))\n",
        "  # Trial Loop\n",
        "  for t in tqdm(range(Trials)):\n",
        "      chosen_arm = algo.select_arm()\n",
        "      chosen_arms[t] = chosen_arm\n",
        "      reward = arms[chosen_arm].get_reward()\n",
        "      if t == 0:\n",
        "          cumulative_rewards[t] = reward\n",
        "      else:\n",
        "          cumulative_rewards[t] = cumulative_rewards[t-1] + reward\n",
        "      algo.update(chosen_arm, reward)\n",
        "  return [chosen_arms, cumulative_rewards]"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "roITpqGgWE31",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 120,
          "referenced_widgets": [
            "8a4b93bd85e34c68bdfbaf636eb1b252",
            "fa1b4d97992642949eb56c8a8faf2c38",
            "c372e6f1e1a34013b231c39ad528c19d",
            "6d1208f275ce473fa79e291221199687",
            "d105398c9c1c4f18b11c95e5682df66f",
            "066b52de38554d0faf2ccb2e569d41e6",
            "3d31eef9777b4af4a8fa99e16d84e166",
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        },
        "outputId": "b489957b-5ac0-4875-d9b9-7df5afe10f74"
      },
      "source": [
        "%%time\n",
        "\n",
        "epsilon = 0.2  # Parameter\n",
        "EG = EpsilonGreedy(epsilon)\n",
        "result = demonstrate(EG, arms, Trials)\n",
        "\n",
        "print(result[0].shape, result[1].shape)"
      ],
      "execution_count": 176,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "8a4b93bd85e34c68bdfbaf636eb1b252",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0, max=10000), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "(10000,) (10000,)\n",
            "CPU times: user 314 ms, sys: 9.32 ms, total: 323 ms\n",
            "Wall time: 324 ms\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QgmcuQ_qWE6g",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 186
        },
        "outputId": "67edbc2a-b225-4942-a1ce-d0b7baac567c"
      },
      "source": [
        "df_EG = pd.DataFrame({\"arms\": result[0], \"rewards\": result[1]})\n",
        "best_arms_list = (result[0]==np.argmax(probs)).astype(int)\n",
        "df_EG[\"best_arm_rate\"] = best_arms_list.cumsum() / Trials\n",
        "df_EG.T"
      ],
      "execution_count": 177,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<div>\n",
              "<style scoped>\n",
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              "      <th></th>\n",
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              "      <th>20</th>\n",
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              "      <th>22</th>\n",
              "      <th>23</th>\n",
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              "      <th>39</th>\n",
              "      <th>...</th>\n",
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              "      <th>9962</th>\n",
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              "      <th>9970</th>\n",
              "      <th>9971</th>\n",
              "      <th>9972</th>\n",
              "      <th>9973</th>\n",
              "      <th>9974</th>\n",
              "      <th>9975</th>\n",
              "      <th>9976</th>\n",
              "      <th>9977</th>\n",
              "      <th>9978</th>\n",
              "      <th>9979</th>\n",
              "      <th>9980</th>\n",
              "      <th>9981</th>\n",
              "      <th>9982</th>\n",
              "      <th>9983</th>\n",
              "      <th>9984</th>\n",
              "      <th>9985</th>\n",
              "      <th>9986</th>\n",
              "      <th>9987</th>\n",
              "      <th>9988</th>\n",
              "      <th>9989</th>\n",
              "      <th>9990</th>\n",
              "      <th>9991</th>\n",
              "      <th>9992</th>\n",
              "      <th>9993</th>\n",
              "      <th>9994</th>\n",
              "      <th>9995</th>\n",
              "      <th>9996</th>\n",
              "      <th>9997</th>\n",
              "      <th>9998</th>\n",
              "      <th>9999</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>arms</th>\n",
              "      <td>8.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>7.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>7.0000</td>\n",
              "      <td>8.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>5.0000</td>\n",
              "      <td>7.0000</td>\n",
              "      <td>7.0000</td>\n",
              "      <td>2.0000</td>\n",
              "      <td>7.0000</td>\n",
              "      <td>7.0000</td>\n",
              "      <td>7.0000</td>\n",
              "      <td>7.0000</td>\n",
              "      <td>7.0000</td>\n",
              "      <td>...</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>4.0000</td>\n",
              "      <td>9.000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>3.0000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>9.000</td>\n",
              "      <td>0.000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>8.0000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>9.000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>1.0000</td>\n",
              "      <td>9.0000</td>\n",
              "      <td>9.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>rewards</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0000</td>\n",
              "      <td>7.0000</td>\n",
              "      <td>7.0000</td>\n",
              "      <td>7.0000</td>\n",
              "      <td>7.0000</td>\n",
              "      <td>7.0000</td>\n",
              "      <td>7.0000</td>\n",
              "      <td>7.0000</td>\n",
              "      <td>8.0000</td>\n",
              "      <td>8.0000</td>\n",
              "      <td>8.0000</td>\n",
              "      <td>8.0000</td>\n",
              "      <td>8.0000</td>\n",
              "      <td>8.0000</td>\n",
              "      <td>8.0000</td>\n",
              "      <td>...</td>\n",
              "      <td>2367.0000</td>\n",
              "      <td>2367.0000</td>\n",
              "      <td>2367.0000</td>\n",
              "      <td>2367.0000</td>\n",
              "      <td>2367.0000</td>\n",
              "      <td>2368.000</td>\n",
              "      <td>2369.0000</td>\n",
              "      <td>2369.0000</td>\n",
              "      <td>2369.0000</td>\n",
              "      <td>2369.0000</td>\n",
              "      <td>2370.0000</td>\n",
              "      <td>2370.0000</td>\n",
              "      <td>2370.0000</td>\n",
              "      <td>2371.0000</td>\n",
              "      <td>2371.0000</td>\n",
              "      <td>2372.0000</td>\n",
              "      <td>2372.000</td>\n",
              "      <td>2372.000</td>\n",
              "      <td>2373.0000</td>\n",
              "      <td>2374.0000</td>\n",
              "      <td>2374.0000</td>\n",
              "      <td>2375.0000</td>\n",
              "      <td>2375.0000</td>\n",
              "      <td>2375.0000</td>\n",
              "      <td>2375.0000</td>\n",
              "      <td>2375.0000</td>\n",
              "      <td>2376.0000</td>\n",
              "      <td>2376.0000</td>\n",
              "      <td>2376.000</td>\n",
              "      <td>2376.0000</td>\n",
              "      <td>2376.0000</td>\n",
              "      <td>2376.0000</td>\n",
              "      <td>2377.0000</td>\n",
              "      <td>2377.0000</td>\n",
              "      <td>2377.0000</td>\n",
              "      <td>2377.0000</td>\n",
              "      <td>2377.0000</td>\n",
              "      <td>2377.0000</td>\n",
              "      <td>2377.0000</td>\n",
              "      <td>2377.000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>best_arm_rate</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>0.0001</td>\n",
              "      <td>...</td>\n",
              "      <td>0.7826</td>\n",
              "      <td>0.7827</td>\n",
              "      <td>0.7828</td>\n",
              "      <td>0.7829</td>\n",
              "      <td>0.7829</td>\n",
              "      <td>0.783</td>\n",
              "      <td>0.7831</td>\n",
              "      <td>0.7832</td>\n",
              "      <td>0.7832</td>\n",
              "      <td>0.7833</td>\n",
              "      <td>0.7834</td>\n",
              "      <td>0.7835</td>\n",
              "      <td>0.7836</td>\n",
              "      <td>0.7837</td>\n",
              "      <td>0.7838</td>\n",
              "      <td>0.7839</td>\n",
              "      <td>0.784</td>\n",
              "      <td>0.784</td>\n",
              "      <td>0.7841</td>\n",
              "      <td>0.7842</td>\n",
              "      <td>0.7843</td>\n",
              "      <td>0.7844</td>\n",
              "      <td>0.7845</td>\n",
              "      <td>0.7846</td>\n",
              "      <td>0.7846</td>\n",
              "      <td>0.7847</td>\n",
              "      <td>0.7848</td>\n",
              "      <td>0.7849</td>\n",
              "      <td>0.785</td>\n",
              "      <td>0.7851</td>\n",
              "      <td>0.7852</td>\n",
              "      <td>0.7853</td>\n",
              "      <td>0.7854</td>\n",
              "      <td>0.7855</td>\n",
              "      <td>0.7856</td>\n",
              "      <td>0.7857</td>\n",
              "      <td>0.7858</td>\n",
              "      <td>0.7858</td>\n",
              "      <td>0.7859</td>\n",
              "      <td>0.786</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3 rows × 10000 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "               0     1     2     ...       9997       9998      9999\n",
              "arms            8.0   0.0   0.0  ...     1.0000     9.0000     9.000\n",
              "rewards         0.0   0.0   1.0  ...  2377.0000  2377.0000  2377.000\n",
              "best_arm_rate   0.0   0.0   0.0  ...     0.7858     0.7859     0.786\n",
              "\n",
              "[3 rows x 10000 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 177
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2ITV0sUmWE80",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 573
        },
        "outputId": "e647968d-bfbd-4fa8-eb32-229fb8440283"
      },
      "source": [
        "plt.subplot(212)\n",
        "plt.plot(df_EG['rewards'])\n",
        "plt.title(EG.__class__.__name__ + ' {}'.format(epsilon))\n",
        "\n",
        "plt.subplot(222)\n",
        "sns.countplot(df_EG['arms'])\n",
        "plt.title('Each Counter')\n",
        "\n",
        "plt.subplot(221)\n",
        "plt.plot(df_EG['best_arm_rate'])\n",
        "plt.title('Best Arm Rate')\n",
        "\n",
        "print(Counter(df_EG['arms']))\n",
        "\n",
        "df_EG_small = df_EG"
      ],
      "execution_count": 178,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Counter({9.0: 7860, 7.0: 487, 2.0: 222, 5.0: 216, 1.0: 212, 0.0: 208, 3.0: 206, 4.0: 199, 8.0: 198, 6.0: 192})\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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pV97bqi83HFWPjq0154lBenhsd8IHNFi+vr4aPHiwkpOTJZ1/gkV2draCg4Mr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\n0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            "text/plain": [
              "<Figure size 1296x648 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FKc7DxUOBcQu",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 658,
          "referenced_widgets": [
            "7cdccb56924b40a8a77e6f3fff4cbfa2",
            "abf0678f6ee345ab873549e61e92acaa",
            "d9c1800b66124001939c2ec9dfe6de17",
            "2fa20262224246d5bef57c85648b7204",
            "b85e884508a64653a772a4d864b31197",
            "d02d1f5beafd46a0b6b0ea6f4e7a5e64",
            "da576e10c0f5479caadd191c9f787764",
            "ee0d693670494805acb8d9cecf7e48ee"
          ]
        },
        "outputId": "9e75930e-6049-4001-9b5c-be55c7f3a519"
      },
      "source": [
        "# パラメータを変更してシミュレーションする\n",
        "%%time\n",
        "\n",
        "epsilon = 0.85  # Parameter\n",
        "EG = EpsilonGreedy(epsilon)\n",
        "result = demonstrate(EG, arms, Trials)\n",
        "\n",
        "df_EG = pd.DataFrame({\"arms\": result[0], \"rewards\": result[1]})\n",
        "best_arms_list = (result[0]==np.argmax(probs)).astype(int)\n",
        "df_EG[\"best_arm_rate\"] = best_arms_list.cumsum() / Trials\n",
        "\n",
        "plt.subplot(212)\n",
        "plt.plot(df_EG['rewards'])\n",
        "plt.title(EG.__class__.__name__ + ' {}'.format(epsilon))\n",
        "\n",
        "plt.subplot(222)\n",
        "sns.countplot(df_EG['arms'])\n",
        "plt.title('Each Counter')\n",
        "\n",
        "plt.subplot(221)\n",
        "plt.plot(df_EG['best_arm_rate'])\n",
        "plt.title('Best Arm Rate')\n",
        "\n",
        "print(Counter(df_EG['arms']))\n",
        "\n",
        "df_EG_big = df_EG"
      ],
      "execution_count": 179,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "7cdccb56924b40a8a77e6f3fff4cbfa2",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0, max=10000), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "Counter({9.0: 2336, 2.0: 925, 6.0: 871, 0.0: 870, 8.0: 858, 7.0: 840, 4.0: 839, 1.0: 821, 5.0: 820, 3.0: 820})\n",
            "CPU times: user 355 ms, sys: 3.83 ms, total: 359 ms\n",
            "Wall time: 375 ms\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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hYbJYLux8WywWhYaGKisrq1YBcTWrVq3Stm3bFBISoieffFJxcXH1jQIALldR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\n",
            "text/plain": [
              "<Figure size 1296x648 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KJws01mxMBi5",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# small epsilon\n",
        "df_EG_small = df_EG_small.rename(columns={'arms': 'sArms', 'rewards': 'sRewards', 'best_arm_rate': 'sBAR'})\n",
        "# big epsilon\n",
        "df_EG_big = df_EG_big.rename(columns={'arms': 'bArms', 'rewards': 'bRewards', 'best_arm_rate': 'bBAR'})\n",
        "\n",
        "df_compare = pd.concat((df_EG_small, df_EG_big), axis=1)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3VURk44QCCki",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 573
        },
        "outputId": "99d6bfde-5d77-4140-8e83-1e3562a75e1d"
      },
      "source": [
        "f, axes = plt.subplots(1, 2, sharex=False)\n",
        "\n",
        "df_compare[['sRewards', 'bRewards']].plot(ax=axes[0])\n",
        "df_compare[['sBAR', 'bBAR']].plot(ax=axes[1])\n",
        "\n",
        "axes[0].set_title('Cumulative Rewards')\n",
        "axes[1].set_title('Best Arm Rate')"
      ],
      "execution_count": 197,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Best Arm Rate')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 197
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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GTfj++xn4+ZWlceMmmM1m9uzZyZ49u3j66WEAfP75J7Rs2ZqPPvoMBwcH+vbt\nRWZmhuUYJUvm7T9JgwaBzJw5l717d7Fu3RrmzPmeqVO/y583LyIieXY2NpWP5uwBYOzAJlQt72nj\niiSvCnsv8neurq7cf/8D/PHHVvr0CWPt2jUYjdk89VRfIGc9iPT0dF58cRSuriWAm/cyIiJS/Fy7\n24WDA7weFoK/j/tdHceQz3XJ36xe/RMA586d5cSJCOrXb3jdNm3bPkSTJs354YfvAWjVqjXLli22\nXPKQmZnJiRPHAShf3h+DwcDatatp3LgpoaFN+fnnVTg5OVG+fM7t11JTU/H398fBwYFdu/4kKurc\nTesLDm7M9u3bSEpKBGDVqhWW16Kjo3B396B9+46MGPEyERHHMJlM9z4oIiKSZ5v3R/HuzF0AvNg7\nUOGD3JW89CMmk4n9+/dQuXIVANas+YmPPhrP4sUrWbx4JcuWraFevfps2nT9nbL+2cuIiEjxci18\ncHU28NaTjanoe3fhAxTjGRCFgdFo5Omnw7h69Sqvvfbmdes/XDN8+AsMHtyfJ54YQKdOXbh0KZkR\nI3JmNJhMJh555DFq1cq5rrJx4yaEhx/A19cXyPnGIjAwyHKsZ599gc8/H8d3300nIKAeNWrUuml9\nNWvW4sknn+bZZwfj5uZOixb/+5Zm3749LFgwF0dHR0wmE6+99m8MBuVVIiLWEpt0hVlrIzA4ODCy\ndyCBNfTNstydW/Uj19aAyM7Oonr1GgwcOJTDhw+RkpJC48ZNch2nfftOrF79E506dbnuHH/vZa71\nKCIiUvQd/CuBKUsP4uHmnOdbbd6Kg9lsNudTbVaVkHAZk+l/pV+4cIby5avasKLiycnJQHb2zWc+\naNzzj5+fJ/HxqbYuw25ovK1HY33nDkRe5MvF4QC8ERZMnSq3v9OFweCAj49HQZcm/6B+5PbyY0z0\nc8R6NNbWpfG2Ho31nYs4m8TnCw5QwdeNl/sE4eXuctt9btePaAaEiIhIIXI5PYtJ/w0fBj0ckKfw\nQURERCQ/HT+XzBeLw/HzLsGrfYPzbfFrBRAiIiKFRGLKVd6asQMzOeFDq0B/W5ckIiIidubQqQQm\nLzlImVL5Gz6AAggREZFCYemWk6z64wwAD4VWUvggIiIiVvfHoRi+W32Uir4evNo3iFJ5uOziThSr\nAMJsNuPg4GDrMuxGEV0+RESkUDGbzfy44QS/7D1PCRdHBnauS9OAcrYuS+6B+pH/Ua8gIlJ0bD90\ngf+sPkadyt680CsQtxL5HxcUmwDCycmFtLQU3N1L6UPfCsxmM2lpKTg55W8iJiJib+b/Eskve8/j\n61WCt58KzfdvGsS61I/8jxrzHXAAACAASURBVHoFEZGiY8eRWL5ddYS6VbwZ8WggJV0LJiooNgFE\n6dJ+JCXFc/lysq1LKVYMBgMm043vguHk5ELp0n5WrkhEpPg4G5vKht3ncHN14uNnmuOo2x0XeepH\nclOvICJS+EWcTeK71UeoXdmbl/s0wtnJscDOVWwCCEdHJ3x9db1sftPtakRECkZSagbvztwFwOgn\nQhQ+FBPqR0REpCg5cT7nbhe+XiV5oVfDAg0fANTtiIiIWFm20cRn8/YB8HTnulQqe/P7ZYuIiIgU\nhJPRl5iw4ADe7i682jcoX+92cTPFZgaEiIhIUXAg8iKTlx7EaDLTpG5ZHmhUwdYliYiIiJ05fDqR\nKUsPUsrdmTeeCMHbw9Uq51UAISIiYiXhJxP4cnE4jgYH+neozYPBFW1dkoiIiNiZE+eT+XLRAXy8\nSvJa3yCrhQ+gAEJERMQqIs9f4otFBwB4PSyYWpW8bVyRiIiI2Ju45HS+WnKQMqVK8NaTja1y2cXf\nKYAQEREpYHFJV/hozh6cHA0817OBwgcRERGxusvpWXy56ABms5mXHmtk9fABFECIiIgUqKTUDMbP\n3w/AK30aUbdqaRtXJCIiIvYmMeUqn83bR0LKVUY9HkT5Mm42qUMBhIiISAHZdjCGWWuPkW00065x\nJYUPIiIiYnUpVzKZsPAAKVcyGfV4EHWq2K4fUQAhIiJSAP44FMN3q48C8Hq/YIUPIiIiYnWpVzL5\n7Md9xCVd4eU+tg0fQAGEiIhIvjt8OpEZq45icHDgo2eaU9a7pK1LEhERETtzPu4yXy4O51JaJi8+\n1oiAQvBliAIIERGRfBRxNonP/7vmw4uPBSp8EBEREas7cjqRr5cdwtnZwOv9gqlZycvWJQEKIERE\nRPLN7mNxfL38EADvDWpK5bIeNq5IRERE7M3R04l8uTgcX68SjHg00GYLTt6IAggREZF8sPd4vCV8\neOXxRgofRERExOrOxqYyedlBynqX5LWwYEq5udi6pFwUQIiIiNyjnUdjmbbiMADvDAilun8pG1ck\nIiIi9mbHkVj+s+Yo7iWceLlPo0IXPoACCBERkXuy/8RFpq04jIMDfDCkGf4+7rYuSUREROzMnoh4\nvl15hPsqlmJY13qUKVXC1iXdkAIIERGRu7TlQDTf/3wMgFcfD1L4ICIiIla370Q801Ycopq/Jy8/\n1oiSroX31/zCW5mIiEghFhl1yRI+vD+4KRX9tOaDiIiIWNfJ6EtMW3GYymU9eKVPUKEOH0ABhIiI\nyB0xm82s+fMMSzb/BcDLfRopfBARERGrOx93mUmLw/H2cOGlPo1wK1H4f70v/BWKiIgUIr/ti7KE\nD2MHNqFqeU8bVyQiIiL2Ji7pCp/O2wfAS48VzgUnb0QBhIiISB6dOJ/MD+uPU9LVkU+eaYFnEfmw\nFxERkeIj9UomExcewGw28+aTjYvUGlQKIERERPJg59FYZqw6CsD/DWqm8EFERESsLi7pCp/N28+l\ntExe7Vv0FsBWACEiInIb2w9f4NuVRwB46bFAfLwK562tREREpPhKSctkwsIDXM3M5vWwYGpW9LJ1\nSXdMAYSIiMgtHD2daAkfPhzarMh90yAiIiJFX3pGNhMW7CcpNYPX+hbN8AHAYOsCRERECqvL6Vl8\nuSQcyFlwUuGDiIiIWFu20cTU5Yc4H5/G8480pGalohk+gGZAiIiI3NDJ6Et8tTiczCwTTz9cV3e7\nEBEREavLyjYyZdkhDp1KZGDnugTW8LF1SfdEAYSIiMjfXLyUzqTF4ZyPTwPg0X/dxwOBFWxclYiI\niNibbKOJr5Yc5NCpRJ5oX5vWjYp+P6IAQkRE5G9mrjnG+fg0mtcvR+9/1aBMKS04WdScOnWK0aNH\nk5ycjLe3N+PGjaNatWq5tnn99deJiIiwPI6IiGDKlCm0a9fOytWKiIhcz2w288O6CA6dSuSpjnVo\nE1zR1iXlCwUQIiJi98xmM6diUtlyIJqjZ5Jo2aA8g7vWs3VZcpfGjh1LWFgYPXr0YMWKFYwZM4bZ\ns2fn2ubTTz+1/P3YsWMMGDCABx54wNqlioiI3NCSzX+xNTyGbvdXKzbhA2gRShERsXNXM7MZ891O\nPpi9my0Hoint6UqftjVtXZbcpYSEBI4cOULXrl0B6Nq1K0eOHCExMfGm+yxevJhu3brh4uJirTJF\nRERuasPuc6z58wz/CqpAzweq27qcfKUZECIiYrdOxaTw/qzdAFT3L0X/DrWpVt4TBwcHG1cmdysm\nJoZy5crh6OgIgKOjI2XLliUmJoYyZcpct31mZiYrV67k+++/t3KlIiIi1/ttXxTzNp4guJYvT3ao\nU+x6EgUQIiJilw5EXuTLxTm32Ozesho9WlUvdh/ycnsbN26kQoUKBAQE3NX+Pj4e+VyR3Iyfn+5E\nYy0aa+vSeFtPYR/rjTvPMHtdBKEB5XhzYFOcnYrfBQsKIERExO6ci7tsCR9G9Q2ifrXrvxmXosnf\n35/Y2FiMRiOOjo4YjUbi4uLw9/e/4fZLlizh0UcfvevzJSRcxmQy3/X+kjd+fp7Ex6faugy7oLG2\nLo239RT2sd55NJZvVhymfrXSDO0SQHJSmq1LuisGg8Mtw/niF6mIiIjcwh+HYhj7n50AvPlkY4UP\nxYyPjw8BAQGsWrUKgFWrVhEQEHDDyy8uXLjAnj176Natm7XLFBERsdgTEc+3K49Qs5IXIx4NLJYz\nH64pvu9MRETkH3Yfi2PGqqMADO4SQM2KXjauSArCu+++y5w5c+jYsSNz5szhvffeA2Do0KEcPHjQ\nst2yZct48MEH8fLS/wMREbGN8JMJTFtxiCrlPBnZOxAXZ0dbl1SgdAmGiIjYhaTUDKatOAzAJ880\np2xpNxtXJAWlRo0aLFq06Lrnv/3221yPn332WWuVJCIicp0DkReZsuwgFX3dGfV4I9xKONu6pAKn\nAEJERIo1o8nE9J+OsOtYHABPtK+t8EFERERs6tCphJzwwc+DUY8H2UX4AAogRESkmPvP6qPsOhZH\nWe+S9HuoFoE1fGxdkoiIiNixMxdSmbL0EP4+7ox6PAiPkvYRPoACCBERKcYORF5k++FY/H3c+GBI\nM91mU0RERGwqLukKXyw+gHtJJ17u08iuwgdQACEiIsVU6pVMy602/92/scIHERERsanTF1KYsOAA\nRpOZf/cPwdvD1dYlWZ0CCBERKZYW/BoJQL+HatndtwsiIiJSuERGXWLiwv24uTozqm8Q5cvY53pU\nCiBERKTYCT95kT8OXaCSnwftQyvbuhwRERGxYyfOJzNh4QG83F149fEgfL1L2rokm1EAISIixYbR\nZGLJb3+xdudZAIb3qG/jikRERMSexSSkMWlxOF7uLrzeL5gypUrYuiSbUgAhIiLFxvc/H2PbwQsA\nvBEWTAVfdxtXJCIiIvYq4dJVxs/fj6PBgVceD7L78AEUQIiISDGReiWTbQcv4FOqBJ8Mb46jwWDr\nkkRERMROJaVmMGHhfq5mGnkjLJiydnzZxd8pgBARkWJh4X8XnRzQuY7CBxEREbGZUzEpTF1+iJQr\nmbzUuxFVynnauqRCQwGEiIgUeacvpLDt0AWqlPOgQXUfW5cjIiIidiribBITFx3AvYQzr/ULpkYF\nL1uXVKgogBARkSIt7WoWH8/ZC8CQLvVsXI2IiIjYq5NRl/hiUTg+pUrwelgIXu4uti6p0NEcVRER\nKbKMJhNvf7uDrGwTnZtXoVJZD1uXJCIiInbofPxlJiw8QCn3nJkPCh9u7LYBRFJSEkOHDqVjx450\n69aNF154gcTERAD2799P9+7d6dixI4MGDSIhIcGy392+JiIikhdms5nP5u3nUlomHZpU5rE2NW1d\nkoiIiNihi5fSmbjwAC7OBl7rF4y3h6utSyq0bhtAODg4MGTIENatW8fKlSupXLky48ePx2Qy8dpr\nrzFmzBjWrVtHaGgo48ePB7jr10RERPJq/i+RHD+XTL1qpXm8rcIHERERsb60q1lMXHiAq5lGXn6s\nEb5eutvFrdw2gPD29qZZs2aWx0FBQURHR3Po0CFcXV0JDQ0FoG/fvqxduxbgrl8TERHJi0uXM9iw\n+xy+XiV46bFGODg42LokERERsTPZRhNTlh4kLimdkY821N0u8uCO1oAwmUzMmzePtm3bEhMTQ4UK\nFSyvlSlTBpPJRHJy8l2/JiIicjsJl67y8uRtAAzrVh8nRy1nJCIiItaVlW1i2orDHDubzKCHA6hT\npbStSyoS7uguGO+//z5ubm7079+fDRs2FFRNeeLjo4XGrMXPT0metWisrUvjbT35NdYmk5nR0/8E\nYEiPBrQIrpQvxxURERHJK5PJzDc/HWbv8Xj6tatFiwblbV1SkZHnAGLcuHGcOXOGadOmYTAY8Pf3\nJzo62vJ6YmIiBoMBb2/vu37tTiQkXMZkMt/RPnLn/Pw8iY9PtXUZdkFjbV0ab+vJz7HeeiCauMQr\nNA0oy/0BZfVv+DcGg4PCeRERkQJmNJmYueaYJXxo36SyrUsqUvI0b3XChAkcOnSIKVOm4OKSczuR\nBg0acPXqVXbv3g3A/Pnz6dSp0z29JiIicjN7IuKY+fMxDA4ODO5Sz9bliIiIiJ0xm838uOEEfxy6\nQNf7qyp8uAu3nQFx4sQJvvnmG6pVq0bfvn0BqFSpElOmTOHTTz9l7NixZGRkULFiRT777DMADAbD\nXb0mIiJyI1Hxl5my7BAAo/oG4eykdR9ERETEun7ecZZN+6Lo3LwKvVrXsHU5RZKD2Wwuktcx6BIM\n69A0devRWFuXxtt67nWsk1Iz+GD2bpJSM3gjLFiLPN2ELsGwDfUj1qGf2dajsbYujbf13OtYbw2P\nZuaaYzQNKMuw7vUx6A5cN3S7fuSOFqEUERGxpqNnkvhs3j4Awh6qpfBBRERErG5PRDyzfo6gfrXS\nDOlaT+HDPVAAISIihdKByIt8uTgcgOcfaUDjOmVtXJGIiIjYm593nGHxppNUKefJc4801O2/75EC\nCBERKVQysows2hTJr3ujAHiup8IHERERsb61O86yaNNJGtfxY0iXeri6ONq6pCJPAYSIiBQaRpOJ\nf3+zneTLmXh7uPBm/8b4epe0dVkiIiJiZ7YciGbhpkia1C3LMz205kN+UQAhIiKFQmaWkdH/DR+6\ntKhKr9b34aAPexEREbGy38NjmPXzMRpUL6M1H/KZAggREbG5bKOJ+b9GKnwQERERm1q/8yzzf42k\nXrXSPN+roW79nc8UQIiIiE3FJl3h7W93YDSZKeXmrPBBREREbGLVH6dZuuUvQmr7MaxbPVycteZD\nflMAISIiNpNtNPHOjJzwoWer6rQOqqDwQURERKzKZDazbMtfrN5+hub1yjGoS4DudlFAFECIiIjN\nbNx9nmyjme4tq9G9VXVblyMiIiJ26Fr40KJ+OZ5+WOFDQVIAISIiNrH3eDwLN0XiXsKJbi2r2boc\nERERsUMbd59j9fYz/CuoAk91rKOZmAVMAYSIiFhdZNQlJi89iLOTgaHd6uNo0DcNIiIiYl0r/zjN\nsi1/EVzLl/4dait8sAIFECIiYlVZ2Ua+WhIOwDtPhVKprIeNKxIRERF7s2HXOZZt+Ytm9coxuEuA\nvgyxEgUQIiJiNUaTic8XHCD1ShZd76+m8EFERESsbvexOOb9coKQ2n4M6arwwZoUQIiIiFWkZ2Tz\n4qTfyTaaaHBfGXq1vs/WJYmIiIidORWTwrerjlCzohfPdK+n8MHKFECIiEiBMpnMLNl8krU7zmI0\nmenSoqrCBxEREbG6i5fSmbQ4HC93F154tCHOTo62LsnuKIAQEZECNX9DBKu3n6Fs6ZL0aFmdFg3K\n27okERERsTOxiVf49Md9ZGYbebVfMKXcXGxdkl1SACEiIgUm6mIa89ZHUKaUKx8Pa67VpUVERMTq\nLl3OYNy8fVy5ms2rfYOp6Otu65LslgIIEREpMPM3Hgfg2R4NFD6IiIiI1SWmXOWz+fu5dDmDUX2D\nqO5fytYl2TUFECIiUiAO/ZXA4dNJtAysQI2KXrYuR0REROzM5fQsPl+QEz68O7QFZT112YWtaclP\nERHJdxt2n2PCwgMAPPNIQxtXIyIiIvYmPSObSYvDiU9O58XegdS/z8fWJQmaASEiIvnst31RzNt4\nAldnR155vBGlS5UgPj7L1mWJiIiInbiYnM6Xi8O5kHiFZ7rXp06V0rYuSf5LAYSIiOSb+OR0Zq+L\nAOD1sGBdZykiIiJWlXIlk/EL9nP5ShYv9g6kgWY+FCoKIEREJF9kG018sSjnsot3n25ClXKeNq5I\nRERE7El6RjZfLgonKTWD1/oGU7OS1qAqbBRAiIjIPTsbm8pXSw6SkHKV9qGVFT6IiIiIVWVmGflq\nSThnY1N5tmcDhQ+FlAIIERG5J1EX03hv5i7MQIv65enbrqatSxIRERE7cuVqNl8tCef4uWSGdK1H\nSG0/W5ckN6EAQkRE7smUpQcxA0+0r027xpVsXY6IiIjYkZy7XRwgMiqFIV3r0aJBeVuXJLegAEJE\nRO7Kob8SmLzsIJlZJh4MqajwQQqNU6dOMXr0aJKTk/H29mbcuHFUq1btuu3WrFnD1KlTMZvNODg4\nMHPmTHx9fa1fsIiI3JVso4nJSw9y4vwlhnWvT7N65WxdktyGAggREbljkVGXmLAwZ8HJHq2q06VF\nVRtXJPI/Y8eOJSwsjB49erBixQrGjBnD7Nmzc21z8OBBJk+ezKxZs/Dz8yM1NRUXFxcbVSwiInfK\nbDYzZ/1xjp5J4umH6yp8KCIMti5ARESKnqnLDwHw/CMN6dGqOk6O+jiRwiEhIYEjR47QtWtXALp2\n7cqRI0dITEzMtd3333/PoEGD8PPLuU7Y09MTV1dXq9crIiJ3Z93Oc2w5EE2XFlV5ILCCrcuRPFLH\nKCIid2ThpkiSUjN4MLgijetokScpXGJiYihXrhyOjo4AODo6UrZsWWJiYnJtd/LkSc6dO8cTTzzB\nI488wtdff43ZbLZFySIicod2Ho1l0aZIQuv48Ujr+2xdjtwBXYIhIiJ5tmH3OdbuOEtJV0f6tqtl\n63JE7prRaCQiIoKZM2eSmZnJkCFDqFChAj179ryj4/j4eBRQhfJPfn66va+1aKytS+N9Z46eSuS7\n1UcJqF6GNwY2pYRL3n+l1VjbngIIERHJk6TUDOZtPIGTowNjBzbB2UmT6KTw8ff3JzY2FqPRiKOj\nI0ajkbi4OPz9/XNtV6FCBTp16oSLiwsuLi60a9eO8PDwOw4gEhIuYzJp5kRB8/PzJD4+1dZl2AWN\ntXVpvO9MXHI6H8zaTWlPV4Z3r0/qpXTyOnoaa+swGBxuGc6rexQRkTyZvfYYAG88EULZ0m42rkbk\nxnx8fAgICGDVqlUArFq1ioCAAMqUKZNru65du/L7779jNpvJysrizz//pG7durYoWURE8uBSWiYT\nFuzHbDbz0mON8CjpbOuS5C4ogBARkdvaH3mRAycTqFnRixoVvGxdjsgtvfvuu8yZM4eOHTsyZ84c\n3nvvPQCGDh3KwYMHAejSpQs+Pj48/PDD9OzZk5o1a9K7d29bli0iIjdx5Wo2Xyw8QHJqBiN7B1K+\njL4IKaoczEV0xSVNebQOTVWyHo21dWm88+7ipXRen7odgA+HNsPfx/2O9tdYW8ftpjxKwVA/Yh36\nOWI9Gmvr0njf3pWrWUxYeIAzF1J5oVdDGtX0vavjaKytQ5dgiIjIPfl6Wc4tN0f0anjH4YOIiIjI\n3UrPyGbiopzw4dmeDe46fJDCQwGEiIjc1MJNkZy+kEpIbT+Ca+uWmyIiImIdWdkmvloSzqnoVIb3\naECI+pBiQQGEiIjc0InzyazdcRaDgwPPdK9v63JERETETphMZr756TDHziYzuEsAjesofCgudBtO\nERG5zo4jsXzz02EgZ90H3XJTRERErMFsNjN343H2Ho+nb7tatGhQ3tYlST5SACEiIhZZ2SbW7zrL\nks1/AfBKn0aU00rTIiIiYiWr/jjNpr1RdGpWhQ5NKtu6HMlnCiBERASAq5nZTFhwgMioSwC83i+Y\nulVL27gqERERsRfbDsawbOspmtcvR+82NWxdjhQABRAiIgLAjFVHiYy6RJWyHrweFoJbCX1EiIiI\niHUcPpXI9z8fI6BqaQY9HIDBwcHWJUkBUHcpIiLsj7zI3uPx1KhYireeDLV1OSIiImJHwk8mMGXZ\nQcr7uPH8Iw1wctTaU8WVAggRETt3+kIKkxaHAzCwc4CNqxERERF7cuhUApOXHqSCrxujHg/CrYSz\nrUuSAqQAQkTEjiWlZvB/3+8Gcu524e/jbuOKRERExF7sj7zI1OWH8Pdx49W+wXiUVPhQ3CmAEBGx\nU5fTs/hk7h4AnmhfW+GDiIiIWM2fRy7w3aqjVPR155W+QQof7IQCCBERO3Q5PYux/9lJUmoGzeuV\no13jSrYuSUREROzEtoMxfLf6KLUrezPy0UAtfG1H9C8tImJnjCYTH87eTVJqBl3vr0av1vfZuiQR\nERGxEzuOxPKf1UcJqFqalx4LxNnJ0dYliRUpgBARsSNxyelMWLCfuKR0QuuWVfggIiIiVrPzaCzT\nVx6mVmVvRvZW+GCPFECIiNiRr5aEE5eUTsemlenzYE1blyMiIiJ24tCpBGasOkKNil682DsQV2eF\nD/ZIAYSIiB3Iyjbx7crDRMWn0Sa4Io+3rWXrkkRERMROHD6VyKTF4ZQr7caLvQMp6apfQ+2V/uVF\nRIq5k1GXGPfjXrKNZpoGlCXsIYUPIiIiYh0RZ5OYtCSc8mXceT0sGPcSutuFPVMAISJSjP155AKz\nfo4g22hmcJcAWjb0t3VJIiIiYiciziYxcdEBfL1K8Fo/3WpTFECIiBRbO4/GMv2nIwAM7VaPFvXL\n27giERERsRd/Hr7ArHUR+JQqwat9g/F0c7F1SVIIKIAQESlmzGYzG3afZ/4vJwAYN7wFft4lbVyV\niIiI2Iuffj/F8t9PUa28Jy/0akhpT1dblySFhAIIEZFiZsGvkazfdQ43VyfeGRCq8EFERESsZt3O\nsyz//RQtG5Rn4MN1cTQYbF2SFCIKIEREipF9x+NZv+scri6OfP58S1xddIsrERERsY4dR2JZ8Gsk\noXX8FD7IDSmAEBEpJraGRzNzzTEAxgwIVfggIiIiVnP4VCLfrT5C7UpeDO1WX+GD3JACCBGRYuCX\nPeeZu+E4Lk4Gxj7dBH8fd1uXJCIiInZi7Y6zLNwUib+PGy88Goizk8IHuTEFECIiRdjhU4ls3H2O\nAycTABjdP0Thg4iIiFjNb/uiWLgpkqCavgzpWg+3EvoVU25O/ztERIqo7Ycv8O3KnNtsVvLz4LV+\nQbrFlYiIiFjNpn1R/LAugvrVSvNszwaa+SC3pQBCRKQIysg0WsKH9wc3xd/XHYODg42rEhEREXux\n7WAMP6yLILCGD88/0lDhg+SJAggRkSJo/Px9APTvUJuKfh42rkZERETsye/hMcxcc5SAqqV5/hHN\nfJC8UwAhIlLErNt5lpPRKVT396RtSCVblyMiIiJ2ZP2uc8z/5QT1qpVmxKOBODvprluSdwogRESK\nCLPZzOx1EWzeH42Lk4FX+wbbuiQRERGxI9sPXWD+Lyf+e9lFA4UPcscUQIiIFAFZ2UYmLQ7n8Okk\nSrk58/ZToZR01Y9wERERsY4T55OZ+fNR6lbx5oVeDXFy1GUXcufUvYqIFHJbDkQza+0xzGbwdHPm\no2EtdIsrERERsZqLyelMXnqQMqVK8NwjCh/k7qmDFREpxLYciOb7n48B0LddLR4KraS7XYiIiIjV\nXE7P4svF4RiNZl7sHYhHSWdblyRFmAIIEZFCav+Ji5bw4ZtX/6XrLEVERMSqrlzNZuLCA8QmpfPy\nY4H4+7jbuiQp4hRAiIgUQjuPxjJtxWEA3nqyscIHERERsar0jGw+X7CP0xdSef6RhgRUK2PrkqQY\nUAAhIlLI/LY/itlrIwB4b1BTKpf1sHFFIiIiYk/SM7KZsGA/Zy5c5vlHGhJS28/WJUkxoQBCRKQQ\nSUnLtIQPX4xoRSl3FxtXJCIiIvbk4qWcBSfPx6XxbM8GCh8kXymAEBEpRH7ceByA5x9poPBBRERE\nrComIY1xc/eSkW3ihV4NCarla+uSpJhRACEiUkgcOZ3IzqNx1K9WmsZ1ytq6HBEREbEjFxKv8OmP\n+wB456lQKvhqwUnJfwogREQKgdXbT7Nk818A9H2otm2LEREREbsSm3SFT+bswWSGN8KCFT5IgVEA\nISJiYws3RbJ2x1lcnR0Z9XgQFfWhLyIiIlaSciWTiQsPYDLD62HBVPTT4tdScBRAiIjY0Jz1Efy6\nNwqA8c/fj3sJZxtXJCIiIvbicnoWn/64j6TUDF7vF0wlhQ9SwBRAiIhYmdls5kxsKvN/ieT4uWRc\nnR35ZHgLhQ8iIiJiNddmPsQlpTOyd0NqVPSydUliBxRAiIhYkclk5pMf9xJ5/hIA/j5ujHo8CC/d\n8UJERESsJDHlKuN+3Evy5Uye69mABtV9/p+9+w6sqj78//+8O5sMkhBm2IQVAoh7oqIVjIshUlv1\no611D5QOxW+1tbgntdo6sCqIgliWW1FAFCSEEMJKAoGETLLHXef3R1pafyrKyD25974ef8E5F/Li\ncO69577u+7zfZkeSMKECQkQkQIr31/PAKxvwGwb9e8Qx/exB9E2LMzuWiIiIhJHqulb+8toGmtu8\n3DF1FIN6xZsdScKICggRkQDweP385Z/f4DcMsk/py4Unp2OxWMyOJSIiImGkrsnNY2/m0Nzm4/ap\no+jfXbddSGCpgBAR6WAer59XVhbg9vqZfEZ/zj+hj9mRREREJMy0ur08sXAT1XWtKh/ENCogREQ6\nkGEYPPT6N+wqrSch1sW543qZHUkkLBQVFTFr1ixqa2uJj49nzpw5pKenf+sxTz/9NK+//jopKSkA\njB49mtmzZ5uQVkSkb6AhBQAAIABJREFUY3l9fv76zhb2lDdw06UjdduFmEYFhIhIB/r70q3sKq1n\nYM8u3H3FaKy67UIkIGbPns306dPJzs5myZIl3HvvvcybN+87j7vooou4++67TUgoIhIYhmEwb+U2\nNhdWc+V5gxk1oKvZkSSMWc0OICISqjZsq2Ttlv2kJkRy57QslQ8iAVJdXU1+fj4TJ04EYOLEieTn\n51NTU2NyMhGRwFuxbg9fbC7jwpPTOWNUD7PjSJj7SQXEnDlzOOussxg8eDDbt28/uP2ss87ivPPO\nIzs7m+zsbD7//POD+3JycrjwwguZMGECV199NdXV1T9pn4hIsKusbeGVlQU8u3gzToeV26eOwmFX\n3ysSKGVlZaSmpmKz2QCw2WykpKRQVlb2nccuW7aMSZMmcfXVV7Nx48ZARxUR6VBfF1Tw1qe7OH5o\nKtmn9DU7jshPuwVj/PjxXHnllVxxxRXf2ffUU08xaNCgb23z+/3MnDmTBx98kLFjxzJ37lweeeQR\nHnzwwUPuExEJdnsrG7n3H18BkBDr4rYpmSTHR5qcSkS+z7Rp0/j1r3+Nw+Fg9erV/OY3v2H58uUk\nJCT85L8jKSmmAxPK/0pOjjU7QtjQsQ6sjjrea3JLef7dLWSkJ3LXlcfhdNg65OcEE53b5vtJBcTY\nsWMP6y/Ny8vD5XId/HPTpk1j/PjxPPjgg4fcJyISzMoPNDP7xfbyYca5gzh1ZHeNfBAxQVpaGuXl\n5fh8Pmw2Gz6fj4qKCtLS0r71uOTk5IO/Pvnkk0lLS2PHjh2MGzfuJ/+s6upG/H7jmGWX75ecHEtl\nZYPZMcKCjnVgddTx/mjDXl7/cDv90uK48eLh1NU2H/OfEWx0bgeG1Wo5ZDl/1JNQ3nnnnRiGwZgx\nY7j99tuJi4ujrKyM7t27H3xMYmIifr+f2traQ+6Lj//ps7HqG4fAUVMYODrWgXWsjrffb/DJhhKe\nWbgJw4D/d92JjB6cckz+7lChc1sCKSkpiYyMDJYuXUp2djZLly4lIyODxMTEbz2uvLyc1NRUALZu\n3cq+ffvo21dDlEUkuK1ct4c3P9nJ8H6J/Oai4UQ4te6AdB5HdTa+9tprpKWl4Xa7+dOf/sQf//hH\nHnnkkWOV7ZD0jUNgqCkMHB3rwDpWx9vr8/PQGxvZubcOu83Cby4aTq/ESP1f/g+d24HxY984hJv7\n7ruPWbNmMXfuXOLi4pgzZw4A1157LTfffDMjRozgscceY8uWLVitVhwOBw899NC3RkWIiASb978u\n4c1PdnLckBSunTQUu00jMaVzOaoC4j9DGZ1OJ9OnT+f6668/uL20tPTg42pqarBarcTHxx9yn4hI\nsHnzk53s3FtHv+5xzLw8C5furxTpFPr378/ChQu/s/2FF144+Ov/lBIiIqHgPyMfxgxKVvkgndYR\nn5XNzc00NLR/o2UYBsuXLycjIwOA4cOH09rayvr16wGYP38+55133o/uExEJJnvKG/hw/V6iI+zc\nPV3lg4iIiJjjg3+PfBg7JIVfZQ9T+SCd1k8aAfHAAw/w/vvvU1VVxVVXXUV8fDzPPfccN910Ez6f\nD7/fT//+/Zk9ezYAVquVhx56iNmzZ9PW1kaPHj14+OGHf3SfiEiwKCqr5/5X2ovUW6dk4rCrfBAR\nEZHA+2jDXt74aAdjBiVznUY+SCdnMQwjKCdS0BwQgaF7twNHxzqwjuZ4/+9SmzddOoKsgbpn/FB0\nbgeG5oAwh65HAkOvI4GjYx1YR3u8N+2s4qm3c8ns35UbLhmOzary4Yfo3A6MDl8FQ0QknKzaVMrL\nKwoAuO7CoSofRERExBS7Sut4bskWeqfE8qsLh6l8kKCgAkJE5CfwGwavvreNz3JKiXDauOWykQzu\nnWB2LBEREQlDO/fW8cTCTcRFO7hl8khcTt0KKsFBBYSIyI9obvXwuxfWUd/kJibSwV2XZ9EzRUPd\npfMwDAN/XQXoFgwRkZD3RW4ZL63YSmJsBDOnZREf4zI7kshPpgJCRORHPDI/h/omNxec2IeJJ6br\nWwbpVHxVu2leNBt7l2S48Tmz44iISAdau2U/L63YytA+Cfzm4hFEuvRxToKLzlgRkUNYtamU4v0N\nDOubyKWn9zc7jsh3tH78NwAcw88xOYmIiHSkD9aX8MaHOxjUsws3XDKCCKc+yknw0VkrIvIDqupa\neHlFARYLXDdpqNlxRA4yDAPvts9pW78Io7kW+6BTcI6YYHYsERHpIKs2lfLGhzvIGtiV6y8arqU2\nJWipgBAR+R5VdS3c9de1ANw5dRSxUU6TE4mAv6UeX9k22tYtwGioAsAxdDyu46eYnExERDrK6s1l\nvLKigOH9Evl19jCVDxLUVECIiHyP1z/YAcD/TcwgIz3R5DQS7gzDT9vnr+Ap+OzfWyw4sybhGH4O\n1sg4U7OJiEjHyd1VxUvLCxjSJ4EbLx6Bw655qCS4qYAQEfkfbW4fi1YVkrOzipH9kzhpeJrZkSTM\nGV43zUvux19dgiU6AdeJl2PrNghrVLzZ0UREpAPlFVbzzKI8eqZEc+MlI3A6VD5I8FMBISLyb1W1\nLfy/l7+mqdVLWlIUl48faHYkCWOGYeAt/oa2Nf/EaDqAvf8JRJx5HRarht6KiIS6r7aW8/el+aQl\nRXPntCytdiEhQ2eyiAhQVt3E719YB8D5x/dm8pkDTE4k4c69fhHujf8CwHXCVJwjzzc5kYiIBMJ/\nVrsY0KMLt0weSXSEw+xIIseMCggRCXsr1+3hzU92Au1zPui2CzGLYRj4a0po/WIe/vKdWCK7ED31\nL1ickWZHExGRAPhow16tdiEhTQWEiIStusY2nluyhW0ltVgscM8vxpLeTRP6SWAZnlb8deW4N7yD\nd28e+DwAWJN6EXnOTSofRETCxOrNZbz2wXZGDVD5IKFLBYSIhK0nFuayu7yB44emMuXMASTEusyO\nJGHGU/g1rR8+e/D3lthkHINPxZY2GFu3QVgsFhPTiYhIoHxdUMGLy7cyND1B5YOENBUQIhJ2Wtq8\nPPraBnaXNzCsbyK/unCY2ZEkDHkKVtG66kUAnMddir3PaGyJPUxOJSIigZazo4rn393CgB5duPGS\nETjsKh8kdKmAEJGw4fX5WfjJLj5YXwJA1y4RKh8k4Ax3M61rXse7/QsAoi69H1tSL5NTiYiIGbYU\nVvPckjx6pcRwy2WZRDj18UxCm85wEQkLhmHw13fy2Lijii4xTn55wTAy+yaYHUvCTNs3S3CvXwyA\nJTKOqOw/YI1LMTmViIiYYWtxDU8v2kxCrItbp2QSFaGPZhL6dJaLSMhraHbz13fyKNhTS5/UWGbN\nGE3P7vFUVjaYHU3ChL++ktbP/o6vbBs4Iog49RfY+x6Hxaa3YRGRcJS7q5q5izeT1jWaWy8bSVyU\n0+xIIgGhKx8RCWll1U08Mj+HAw1t9E2L4/c/H4PVqon9JDDcBZ/h3rQCo24/ANau6USeexPWmCST\nk4mIiFlyd1XzzKLNdEuM4oFfn4yn1W12JJGAUQEhIiGrze3j/lfW0+r2MfGkPlxyWn+zI0kY8exY\nQ9uqlwBwDD0Le7/jsHfPMDmViIiYacO2CuYuzqNHcjQzLx9FfKyLShUQEkZUQIhISGpp8/LMos20\nun1ced5gzhil1QUkMAyfB++ur2j99AUAoqfOwdol1eRUIiJiti3FNfzt3Xz6dY/jzmlZuJw2syOJ\nBJwKCBEJOX7D4PE3N7FzXx19usVyWmZ3syNJGPBVFePO+wjvjtVg+AGIuvD3Kh9ERKR9wsm3cklN\njOSWyZkqHyRsqYAQkZDiNwz+NG89RWUNDOubyB1TR5kdSUKYYRh4tn6CJ/9j/DV72zc6InEOPRPH\n8HOwRmulFRGRcJdfXMNTb+WSnBDJzGlZxEQ6zI4kYhoVECISMvyGwYP/3EBRWQOjByVzw8XDzY4k\nIcwwDJoXzcZfvQesNmy9RuIak401uS8Wi9XseCIi0glsL6nl6bc3Hywf4qK12oWENxUQIhIS2tw+\nnluSx6599aR3i+WGi4djsWi1C+kYhqeVlvefwl+9B2tyX6Im/RaLXReVIiLyX9tLanli4SYSYl3c\nOXWUygcRVECISAgwDIM//3MDJRWN9EmN5Xc/H6PyQTqE4ffS8v4z+PbkAGBNHUDUpFlYrHo7FRGR\n/9peUsvjCzfRJcrJzMuz6BLjMjuSSKegKyYRCWotbV5e+Fc+JRWNDEtP4I5pWWZHkhDm/uZf+Pbk\nYEsbgmP4OTj6jjE7koiIdDJbimp48q1c4mOc3H3FaBJiVT6I/IcKCBEJWvtrmrn3H+vw+gz694jj\nxktHmh1JQpDh9+HZ/gX+8p14tn2OJTKOyIl3a5SNiIh8x5aiGp5YuIluiVHceXkWXXTbhci3qIAQ\nkaC18JOdeH0Gl589kHPG9jI7joQYf9MB3JuW48n74OA2a0IPXCfPUPkgIiLfsaW4hqffziUtKZq7\npmu1C5HvowJCRILO7v0NzHtvG0Vl9Yzsn6TyQY4pw+/Fvf4d3DlL2zfYnThHno9zdDYWq1a3EBGR\n79peUsuTC3PplhjJndNGqXwQ+QEqIEQkqKxct4c3P9kJwJmje3Dxqf1MTiShwt9Sj6fgM9zrF4Fh\nYImIxXX8FOyDTtGIBxER+UG79zfw1Fu5JHWJ4M7Ls4iL0m0XIj9EBYSIBI1tew4cLB9+N2MMA3p2\nMTmRhALD56Xti1fwbPv84DZn1iScYy9R8SAiIoe0tbiGp97eTHSknTumZKp8EPkRKiBEJCiUVjXx\nyPz2pQ/v/7/j6dE12uREEux8FYV4dq7FuycXo74cW7dBOIaehb3/8SoeRETkR+XuquKZRZtJSYji\n9imZJMZFmB1JpNNTASEind68lQV8mlMKwC/PH6LyQY6Yv7mOtjX/xLdvK0ZbIwCWqHgcGWcSceov\nTE4nIiLBYmtxDc8s2kyPrjHcNiWTOK12IfKTqIAQkU6ttKqJT3NKcTls/P7nY+iZEmN2JAlChs9L\ny/KH8ZVtA8DaNR3H8LNx9D8Ba3w3k9OJiEgw2VfZyDOL80hNiOIOTTgpclhUQIhIp1Vd18o9f18H\nwD2/GEt3jXyQI9S2bgG+sm3YumfgHH4u9vQssyOJiEgQ2lfZyMNvbMTpsHLr5EyVDyKHSQWEiHRK\ndU1unli4CQP4v4kZKh/kiPibDuDZ8hGevA+wxHYl8oK7NL+DiIgckT3lDTy6IAer1cIdU0eR1EVz\nPogcLhUQItLp7Kts5N5/fIUBnJaZxknD08yOJEHGMAx8Jbm0rHz84LbIs29Q+SAiIkekeH89D72+\nkUiXnZmXZ9EtMcrsSCJBSQWEiHQqXp+fP//zGwzg19nDGJeRanYkCTL+lnraPn8Fb/EGAJzjpuDM\nPF/lg4iIHJGisnoenZ9DdISDu6/IomuXSLMjiQQtFRAi0mnU1LfywLz1tLR5ufT0fiof5LD4m+to\n+2Ie3pJN4PNi6ZJK1AV3YY1JMjuaiIgEqe0ltTyxcBMxkQ7uulzlg8jRUgEhIp3G3HfyqG10M+mk\ndC44Md3sOBIkDMPAW/g1rZ+/BO4WLF264Rx2Ns7hZ5sdTUREgljOjirmvrOZpC6RzJw2isQ4zfkg\ncrRUQIhIp/DeV3soLK3n5BHduPi0fmbHkSDhb6yhZfnD+GvLwGbHdeJ0nCPONTuWiIgEuR17a3lu\nSR49kmO4fUomsVFOsyOJhAQVECJiKr9h8FlOKQs+3gnAjHMGm5xIgoFhGLg3vot7wztgGNj7HUfE\n6ddgcejbKREROTpFZfU8tmAT8TEubpus8kHkWFIBISKmqalv5bE3N1Fa1QTA3dOzcDltJqeSYND2\n5Xw8m9/DEhmH68TpOAacYHYkEREJAfuqmnhi4SZioxzcNT2LuGiVDyLHkgoIETGFYRj87d0tlFY1\nMaBHF26+bCQxkQ6zY0kQcBd81l4+xCQRPe0hLFaVViIicvR27avjiYWbsNms3DYlU3M+iHQAq9kB\nRCT8VNe1MvvFr9ixt44xg5P53c/HqHyQH2W4W2j5+DnaVr0EQNSFv1P5ID+oqKiIqVOnMmHCBKZO\nnUpxcfEPPrawsJDMzEzmzJkTuIAi0qlsL6llzusbiXTZ+d2M0aQlRZsdSSQkaQSEiARMZW0Liz8v\n5Mst5QAM7hXPr7OHmZxKgoG3dCst7z8F7hZwRRN92QNYoxPMjiWd2OzZs5k+fTrZ2dksWbKEe++9\nl3nz5n3ncT6fj9mzZ3P22Vo1RSRc7a9p5um3c0nqEsFdl2eREOsyO5JIyFIBISIB4fH6mP3iV7S6\nfaQlRXHp6f3JGtgVi8VidjTp5HzlO2lZ2v7NtHPMxTizLsBi1duX/LDq6mry8/N56aX20TITJ07k\n/vvvp6amhsTExG899vnnn+eMM86gubmZ5uZmM+KKiIn21zTz6PwcrFYLt00eqfJBpIPpCk5EAuKd\nz4todfu46NS+XHhyX7PjSJBo++Zd3OsXARB5/u3Ye400OZEEg7KyMlJTU7HZ2m/RsdlspKSkUFZW\n9q0CoqCggC+++IJ58+Yxd+5cs+KKiEn2VjbyyPwc/H6D26ZkkpIQZXYkkZCnAkJEOlxJRSMr1u2h\nS4yTiSemmx1HOjl/Sz2erZ/i2f4FRn0FAJGTfos9TUu0yrHj8Xi45557ePDBBw8WFUciKSnmGKaS\nQ0lOjjU7QtgIh2O9dnMZj76+gegIOw/ccAq9Us37N4fD8e4sdKzNpwJCRDpMYWk9i1btIr/4ABYL\nXDtxKFarbrmQ72d43bg3vIN70/L2Dc4oHCPPwzVqIpYIfciTny4tLY3y8nJ8Ph82mw2fz0dFRQVp\naWkHH1NZWcmePXu47rrrAKivr8cwDBobG7n//vt/8s+qrm7E7zeO+b9Bvi05OZbKygazY4SFcDjW\neUXVPLkwlz7dYvnNRcOJsGLavzkcjndnoWMdGFar5ZDlvAoIEekQbW4fD8xbD0CvlBh+nT1MM0rL\n9/KWbMaduwLfvvz2DY4IIk65Env/47XKhRyRpKQkMjIyWLp0KdnZ2SxdupSMjIxv3X7RvXt31q1b\nd/D3Tz/9NM3Nzdx9991mRBaRANm4o5K5i/NIS4rm9imjiIrQxyGRQNIzTkSOOb/f4A9//xKAyWf2\n5/zj+5icSDor3/4dtKx4FABbr5E4+h2HfcCJWGx6e5Kjc9999zFr1izmzp1LXFzcwSU2r732Wm6+\n+WZGjBhhckIRCbT1BRX87d0t9EqJ4dbJmSofREygZ52IHHOPLsihur6NE4d1U/kg38vwuvHsWEPb\nugUARE35M7b47ianklDSv39/Fi5c+J3tL7zwwvc+/qabburoSCJioq8LKvjbki30TYvllsmZxEQ6\nzI4kEpZUQIjIMeE3DD78uoQN2yvZsbeO3qkxXHNBhtmxpBPx11fQtuEdfHvzMFrqD26POPM6lQ8i\nItJh1m7Zz9+X5jOgRxdunZxJpEsfgUTMomefiBw1wzB4fEEOW4oPADBqQFeuv2iYJpyUgzw71tD6\nyfMAWFMHYO93HLau6dh6DscanWByOhERCVWrN5fx4rKtDOoVz82XjVT5IGIyPQNF5Kg9uziPLcUH\n6NE1mj9eMw6LRcWDtPPu3ULxq3/F39IIVjuR596EvXem2bFERCQMrM3bz0vLCxjSJ4EbLxmh8kGk\nE9CzUESOiGEYrPxqD2s272dfVRM9k6O55xfHqXyQg/wNVbQsfxgAZ9YknFmTsNidJqcSEZFwsC6/\nnL8vy2dgz3huunQEEU597BHpDPRMFJEj8tGGvSz8ZBcRThsnDEvlF+cNwWG3mh1LTOarLMZb+BXe\nsm0YzbUA9LhqDvWOVJOTiYhIuPhqaznP/2sL/bt34bbJmbicWtJZpLNQASEihy2/uIbXP9yBw27l\nyZtPVfEgALR98y7u9YsAsETFY+3aB9uQ03B1HwCVDSanExGRcPDN9kqefzef/j26cMfUUbgcKh9E\nOhMVECJyWOqa3Dy2YBMAf7hyrMoHwfC00rz4j/hrS8EZSdTPZmJL6Wd2LBERCTNfbS3n+XfzSU+L\nbR/5oPJBpNNRASEih2XeygL8hsHtUzPplRJjdhwxma9mLy3LH8ForsU+8CRcJ0zDGhlndiwREQkz\nmwuref7dfAb0iOMWLbUp0mnpmSkiP0l9k5u3PtvFxh1VdO8azbD0RLMjiYkMTyvN79yP/8A+AOwD\nTiDyzOtMTiUiIuFoe0ktcxfn0TM5WuWDSCenZ6eIHJJhGCz5ooh3VxcDMKBnF3594TCtdhGm/M21\n+Pbm4c77AP+Bfdh6jcA1Ohtb6gCzo4mISBgq2H2AJ9/OJSHWxa1TVD6IdHZ6horID2p1e3lswSZ2\n7qvDYbdyzQUZjMvQagbhyGhrom39YjxbPjy4zd53LJHn3GhiKhERCWe79tXx5Nu5JMa6uGPqKOJj\nXGZHEpEfoQJCRL5X7q5qnnorF79hMLhXPHdMG4Xdpgknw407dwWeHV/ir94NgCUiFtfJP8fWfYjm\nehAREdOUVTfxxMJNxEU5uHNaFgmxKh9EgoEKCBH5Fq/Pz8srCliTtx+AK84ZxPgxPU1OJYFk+L34\nq/bg3rQcb9F6sNiwDzoZe+9R2NPHYLGqiBIREfNU1Lbw2IIcbFYLd6h8EAkqKiBE5KA95Q3c99LX\nAHTvGs3tUzJJjIswOZUEkuF107L8EXz7twNgTx9DxNnXY7Hq7UJERMxXU9/KY/NzaHX7uH3qKFLi\nI82OJCKHQVeUIkJji4dla4t576sSACae1IeLT+2niSbDjL+xmubFf8RoqcOaOoCIk2dg65pudiwR\nEREAKmtb+Mtr39DU6mHmtCz6pulWQJFgowJCJIx5fX7W5u3nva9LKK1qwma18Ovs4YwZnGx2NAkg\no7URz/YvaPtyAWDgHH0hrrGXmB1LRETkoN37G3jszRx8PoO7p49W+SASpFRAiISpAw1t/OnV9dTU\ntwFw1ugezDh3sMmpJNA8Retp/eCZ9t84Ioi6YCa2lP7mhhIREfkfJRWNPDJ/IxFOG7dfMYq0pGiz\nI4nIEVIBIRKGGls8/O6FL2lz+zhuSAq/PH+I1s0OM4bfR/OSP+GvLAQg4rSrsfXOxBrVxeRkIiIi\n/1VV18Ljb+bgdNiYOX205nwQCXL6xCESZjZsq+DZxXkAjB/TkyvOGWRyIgk0z/bVtG1YjNFQha3b\nICLO+hXWmCSzY4mIiHxLSUUjTyzcRJvHz2+vUPkgEgpUQIiEkaq6loPlw88nDOaMUd1NTiSB5C3Z\nTNuXC/Af2AtWG87RF+Icc7EmGxURkU5nT3kDjy7IwWq1cPf0LHqmxJgdSUSOARUQImHiQEMbd/11\nLQB3T89icO8EkxNJIPiqimlbvxijoRL/gVIAHCMm4Dp+CharzeR0IiIi31VR28JjC3KwWS3MvDxL\ncz6IhBAVECJh4tX3tgEw+cz+Kh/CgL++As+Otbg3LAbA2jUdx5DTcY48H2t8N5PTiYiIfL+9le23\nXfj8BndfMVrlg0iIUQEhEgZ27K0lZ2cVGX0SOP/4PmbHkQ7kry3DW5JL25fzwTDAFU3k6f+HPT3L\n7GgiIiKHVFXbwqMLcgC4c5pGPoiEIhUQIiHOMAyefzcfgKvOH2JyGukoht9P85L78VcWtW+w2Yk4\n41rs/cZpjgcREen0SioaefzNHDweP7+dMZoeyZrzQSQUqYAQCXGvvreN6vpWzhzdg66aPTokGX4/\nrZ8+j7+yCGtyX1xZF2LrPVJzPIiISFAoKqvnyYWbsNms3DU9S+WDSAhTASESonx+P3MX57FxRxUu\nh43pZw80O5J0AE/BKlq/fAPcLVgiYom66B4sFqvZsURERH6StXn7eXllAdERdu6YOoruXXXbhUgo\nUwEhEqJe+2AHG3dU0S0xilkzRmOz6kNpKPHX7ad11cv4ygoAC66TrsCRcabKBxERCQp+w+CdzwtZ\numY3A3t24TcXDadLjMvsWCLSwVRAiIQYr8/PGx/t4NON++iWGMUD1x6PVXMAhAx3wWe4v34bo6Ue\nAFvaYCIn3IrFqdtrREQkOBiGwfyPdvDh+r2cPKIbvzhvCHabCnSRcKACQiSE7K9p5nfPfwlAXLST\n+646TuVDiDD8Ptq+XIAn731wROIcNRFb70zs3XRrjYiIBA+/YfDSsq2sztvPOWN7MW38AE2WLBJG\nVECIhAjDMHhm0WYApp41gPFjeurbhBBhGAYtyx7CV7YNHBFET5uDNTLO7FgiIiKHbcnnRazO28+k\nk9K56NS+Kh9EwsyPfjqZM2cOZ511FoMHD2b79u0HtxcVFTF16lQmTJjA1KlTKS4uPup9InLk/rpk\nC6VVTZw4rBsTxvVW+RACDE8bnm2f0zR/Jr6ybdh6DCXml3NVPoiISFBam7eff60p5pSRaSofRMLU\nj35CGT9+PK+99ho9evT41vbZs2czffp03nvvPaZPn86999571PtE5MjMe28b6wsqGNCjC1dfMMTs\nOHKUjLYm2nKW0bTgblo/+wdGQxX2QacSef4dmmRSRESC0rY9B3hpxVaG9I7nygmDVT6IhKkfvZId\nO3YsaWlp39pWXV1Nfn4+EydOBGDixInk5+dTU1NzxPtE5Mh8snEfn27cR2yUgzumjdJqF0HO8LTR\n+MZM3F8txGipwz7gBKKnPUzkGddgsdrMjiciInLYCkvrefKtXLp2ieQ3F4/QKE2RMHZEc0CUlZWR\nmpqKzdZ+MWyz2UhJSaGsrAzDMI5oX2Ji4jH6J4mEj6Vrilm0qhC7zcLsXx6Hy6EPqMHMnf8xbV+8\nChg4Bp+K69SrsKhQEhGRIFaw+wBPvpVLTKSDmZdnERPpMDuSiJgoaCehTEqKMTtC2EhOjjU7Qtg4\nnGNdXFbPolWFALz2x/OJitAb+uHqLOe2v62F/Qv+RFvJVqyRsXQ971qiM04KqeGpneVYi4hI4Oze\n38CTb+WSGOe+/SQ1AAAgAElEQVTizmlZJMS6zI4kIiY7ogIiLS2N8vJyfD4fNpsNn89HRUUFaWlp\nGIZxRPsOV3V1I36/cSTx5TAkJ8dSWdlgdoywcLjH+onXNwBw31XH0dTQSlNDa0dFC0md5dz2tzbQ\n8u6f8deWYU3pR9T5d9DiiqalqtHsaMdMZznWoc5qtaicF5FOo+JAM08s3ERMpJ2Zl2cRH6PyQUR+\nwhwQ3ycpKYmMjAyWLl0KwNKlS8nIyCAxMfGI94nIT2MYBh+uL2FXaT2njkyjd6q+WQ5W/sZqmhf+\nHn9tGY6MM4m+6F4srmizY4mIiByVuiY3j8zPwevzc+uUUSofROQgi2EYhxxG8MADD/D+++9TVVVF\nQkIC8fHxLFu2jF27djFr1izq6+uJi4tjzpw59OvXD+CI9x0OjYAIDH1zGTg/dqxXby5jxbo9VNa2\n4PH6AXjiplOIi3YGKmJIMfvc9jcdoOn1O8Dw4zphKs6R55uWpaOZfazDhUZAmEPXI4Gh15HAOdpj\nXX6gmUfn51Df7Oauy0fTr7uWjj4UnduBo2MdGD92PfKjBURnpTf8wNATNXAOday/yC3jxeVbAThp\neDfSkqI4fVQPTeR0FMw8tz0Fq2hd9SIAzrGX4Bp9oSk5AkWvI4GhAsIcuh4JDL2OBM7RHOv9Nc08\n9Po3eH0G1180nIw+Ccc4XejRuR04OtaB8WPXI0E7CaVIuFi5bg9vfrITgD9dezxpSRqiH6z8tftp\ny/kX3u2rAYg8/3bsvUaanEpEROTo7dxbx5NvbcJqtXDX9Cx6JqsQFZHvUgEh0ontKq3jzU92Eumy\n8cerjyepS4TZkeQIuQs+o23VSwBYu6YTcfIMbKkDTE4lIiJy9EqrmnjyrU1ERzq4bXImqYlRZkcS\nkU5KBYRIJ5W7q4onFuYCcOe0LJUPQchwt9D62T/wlRZgtLWvahEx/noc/Y83OZmIiMixUVXbwsPz\nN2KzWbl96ihS4iPNjiQinZgKCJFOaNnaYt7+rBCAO6eNom+aJnAKNr7ynTSvfBzamrClDcGW2h/H\n0PFYY7Tqj4iIhIYDDW08siAHj8fPrBmjVT6IyI9SASHSiVTUtvDkwk2UVTfjdFi5c2oWA3p2MTuW\nHAZ/0wHcm9/Dk7sSLFZcJ12Bc/g5ZscSERE5puqb3Dy6IIe6Jjd3TBmlOR9E5CdRASHSSWzeVcXv\nnlsLwLiMFH55/hAinHqKBgPD78Wz+X3cBZ9h1JW3b7RYiJ78Z6zx3cwNJyIicoy1ur08sXATVbUt\n3DI5U1+WiMhPpk83Ip2AYRg8vSAHgFsuG0nmgK4mJ5KfymhrountezEaqwFwZJyBvc9obL2GY7FY\nTU4nIiJybDW3enl0QQ67yxu46ZKRWmpTRA6LCggRkxmGwesf7qCsuomzx/ZU+RAkDL8Pd84y3OsX\nAWDvN46I067C4tT9ryIiEprqmtw8Oj+Hsuomrs8ezqiBumYRkcOjAkLEZB9/s4+PNuzF6bBxyWn9\nzI4jP8IwDLy7N9K29nWMhioAIs+/HXuvkSYnE5H/KCoqYtasWdTW1hIfH8+cOXNIT0//1mPefvtt\nXn75ZaxWK36/n8mTJ3PllVeaE1gkCNQ1tvHQGxuprmvlpktHMLK/ygcROXwqIERMNG9lAZ/mlGK1\nWJj/wM+oPdBkdiT5Ab7KItyb38dbkgtt7f9P9j5ZRJx+DZYITbwl0pnMnj2b6dOnk52dzZIlS7j3\n3nuZN2/etx4zYcIELrnkEiwWC42NjUyaNIlx48YxZMgQk1KLdF7tt11sorq+ldumZDK4t267EJEj\nowJCxCSLVxXyaU4pMZEOZl0xGodd8wV0Nv7WBjx5H+KrLMJXkguAJSoex9hLcA4/G4szyuSEIvL/\nV11dTX5+Pi+99BIAEydO5P7776empobExP8ugxsT89/isLW1FY/Hg8ViCXhekc6uuq6VJ99qX6Hr\n1skqH0Tk6KiAEDHBzr11/GtNMVEuO/f/3/F0iXaaHUn+zVe1G9/+7fjrK/DsWNM+2sFqx5o6ANfx\nU7ClDtSHFJFOrKysjNTUVGw2GwA2m42UlBTKysq+VUAAfPTRRzz22GPs2bOHO+64g8GDB5sRWaTT\nam718MTCTdQ0tN92Maxv4o//IRGRQ1ABIRJAhmHwdUEFzy3ZAsDvrxyj8qETMNzNeLavwZP/Ef7a\nsoPbLVHxOEZNxDXuMhPTiUhHGT9+POPHj6e0tJQbbriB0047jX79Dm8unqQk3YIVKMnJsWZHCBvJ\nybE0t3p4bOEmyg80c9+1J5I5MNnsWCFL53bg6FibTwWESAAtWlXIsrW7Afh19jDSkqJNTiTe0q20\nLHsIDANsThzDz8Ex5HSssclYHC6z44nIYUpLS6O8vByfz4fNZsPn81FRUUFaWtoP/pnu3bszYsQI\nPv3008MuIKqrG/H7jaONLT8iOTmWysoGs2OEheTkWHaXHODxhTkU7qvn6gsy6B4foePfQXRuB46O\ndWBYrZZDlvMqIEQCZPf+Bpat3Y3NauHRG08mLkojH8zir6+krngVjasXYzQdAMAx7GxcJ07DYtXL\nokgwS0pKIiMjg6VLl5Kdnc3SpUvJyMj4zu0Xu3bton///gDU1NSwbt06zj33XDMii3QqbR4fT72d\nS3FZA9dfNJyxQ1LMjiQiIURX2iIBUFhazwPz1gPw2xljVD6YwPB58FUW4SlYhXf7F/xnvRH7gBOJ\nOOkKrWQhEkLuu+8+Zs2axdy5c4mLi2POnDkAXHvttdx8882MGDGCBQsWsHr1aux2O4ZhMGPGDE45\n5RSTk4uYq6nVw6PPr2V7SS3XXThU5YOIHHMWwzCCctyghjwGhoYqHb39Nc3c8/d1+PwGN1w8gjGD\nv/8eSh3rY8/wefDkf4x3Ty6+/dvA5wXAEptM6qTraYzoicWuMqij6dwOjB8b8igdQ9cjgaHXkY5X\nVdvCQ29spKa+lasvyOCk4T9825IcOzq3A0fHOjB0C4aIiVravPz+hS8xDJhy5oAfLB/k2PPX7ad5\nxeMY9eXgjMLWbTD2XiOw9x2DNTaZqORYmvQmJCIiQn2zm4fnb6S51csff3US3eMjzI4kIiFKBYRI\nB2hu9ZKzs5I3P96JYcDlZw/knLG9zI4VFvxNB3B/swTP1k8BcGScgevkGZrbQURE5Hu4PT6efiuX\n2kY3d03PInNgsr4lFpEOoytykWPI7zd4fOEmthTVHNx23vG9VT4EiL+xhqYFs8DnxhIZR8SZ12Hv\nOdzsWCIiIp2Sx+vn2cV5FJbW85uLh9O/exezI4lIiFMBIXKMlFQ0cv8rX+P1GaQlRXHOcb04bkgK\n0REOs6OFBU/xN7R++Cz4fbhOnI5j+DlYLBazY4mIiHRK7eXDZjYXVnPleYMZM1gTTopIx1MBIXIM\ntHl8/PnVDXh9Bpee3o+fndBHH34DqOW9J/Hu3giA65QrcQ49y+REIiIinZfX114+5O6q5soJgzlj\nVA+zI4lImFABIXIMzFtZQJvHx9SzBjBhXG+z44SVlk9ewLt7I5bYZKIumIk1Tt/giIiI/BC/3+Af\ny7aSu6uan587iDOyVD6ISOCogBA5Sqs3l7F2Szkp8ZGce5zmeggEw+/HW7wBz/Yv8O3ZhDWpD1EX\n/QGLTbe7iIiI/BC/YfDyygLW5Zdz6en9OHN0T7MjiUiYUQEhchS2l9Tyj2VbAbhl8kjddhEAvuo9\ntCx7GKO1fYZuS1Q8UZNmqXwQERH5EYtXFfJFbhmTTkrnghPTzY4jImFIBYTIESqpaOQvr30DwOxf\nHkdaUrTJiUKXYRj4q3fj2bEWz+b3AHAMPQvn6AuxRMRisdpMTigiItK5rdpUyrK1uzktM42LTu1r\ndhwRCVMqIESOwLK1xbz9WSEAM84dRJ9useYGClH+hkra1i/Gu/NLMPztG+0uIs+9GXvPYeaGExER\nCQKGYbBs7W4WrypkWN9EZpw7WCM2RcQ0KiBEDtOufXW8/VkhsVEOfv/zMaQkRJkdKeQYhh9v0QZa\nP3kefB6sqQOw9xmNvdtArF37YLE7zY4oIiISFBZ/XsjSNbsZl5HCVT/LwG6zmh1JRMKYCgiRn2jH\n3lq+yq/g42/2AjBzWpbKhw5g+L20fvYi3h1rAHCddhXOIaebnEpERCS4GIbBki+KWLpmN6dlducX\n52nkg4iYTwWEyE9gGAbPLtpMfbOHhFgXk8/sT8+UGLNjhRz31k9p+3I+eFqxJvQgcsItWlZTRETk\nMP2nfHh3dTEnj+jGlRNUPohI56ACQuQneO2D7dQ3e7j09H6aNbqDtHz6D7zbPwdXNK5TrsSRcaYu\nlkRERI7AynV7DpYPV/0sA6veT0Wkk1ABIXII/n9P3PTxN/uIctk5M6uH2ZFCjuH30fb5K3i3f441\nqQ9RF9+DxaqXJhERkSPxac4+Fn666+CcDyofRKQz0VW+yA/Yua+OP7+6AYDk+Ah+9/OxREU4TE4V\nWgyvm+alf8FfUYg1uR+RE25W+SAiInKE1ubt59WV2xjZP4lrLhiq8kFEOh1d6Yv8gDc/3gnAz88d\nxOlZPfQmfowZhkHzsofwVxRi651J5IRbdcuFiIjIEVq1qZRXVhQwsGcXrr9oOA67VrsQkc5HBYTI\n/3B7fOTsrOKrrRXs3FfHcUNSOHN0T7NjhRzD76f53T/hr9iFrddIos67zexIIiIiQWvZ2mLe/qyQ\nQb3iuW1KJi6HzexIIiLfSwWEyL998HUJ8z/agfHv3/dOjeGqnw0xNVOoMVobaV7xKP7KIgDsA04k\n4sxrTU4lIiISvN75vJB3VxczLiOFay4YqpEPItKpqYAQAbbuPsAbH+0AYOJJ6ZyWmUZCrAubVW/i\nR8vfXIen4DN8FYX49uQAYE8fg633SByDT9NtFyIiIkfog/UlvLu6mBOHdeOaCzKwWvWeKiKdmwoI\nCXsVB5p5+I2NAMy6YjSDesWbnCg0tG14B0/BKoymmvYNFhu2tME4hp+Do+9Yc8OJiIgEuZwdVcz/\ncAejByVzzUStdiEiwUEFhIS1jdsreXllAQC3T81U+XCUDK8bX2kB7vyP8O3ZhCUyDkfGmdh6DMXR\n7ziz44mIiISE3F1VPPduHn26xXLtJK12ISLBQwWEhK0P1pfwxoc7sFosXD5+IMP7JpkdKagZbU00\nvnIj/HsWDXufLCLOvA6LM9LcYCIiIiHkP6td9EiO4ZbLRmrCSREJKiogJOz4DYNX39vGZzmlWC0W\nnrrlFKIiHGbHClqeHWto+2YJRl05AI6h43FmTcQanWByMhERkdCyYVsFr6woYFjfRG64eAQup8oH\nEQkuKiAkrHi8Pp5ZlMfmwmqS4lzcfFmmyocjZBgGbesW4MldCYBjyBlYu/bGOfQsk5OJiIiEnvzi\nGp5bsoV+3eO44ZIRGvkgIkFJBYSEjZ176/jzPzcA7Uts3vOLsVrl4ggZhkHrh8/iLVoPNgfR0x7S\niAcREZEOsqe8gWcWbaZbUhS3TclU+SAiQUsFhIS8VreXjzbs5e3PCgE4b1xvLjm9n8qHI+RvrKb1\n47/h278da3JforLvwaJjKSIi0iH21zTz6IIcIl12bpuskZsiEtxUQEhIq2ts4+6/rcXt8RMb5eDm\nS0fSv0cXs2MFLX9jNU0L7gafF/vAk4g4/RqVDyIiIh2ksLSeZxdvxjBg5uVZJMZFmB1JROSoqICQ\nkPb3ZVtxe/z87IQ+XHJaP6xWLVN1pAzDoHnJA+Dz4jppBs7hZ5sdSUREJGTlFVbzzKLNREc6uHPa\nKLolRpkdSUTkqKmAkJD19me72FJUwwnDUrnsjP5mxwla3r1bcOcsxVdZBJ5WnJk/U/kgIiLSgb7c\nsp9/LNtKj67R3D51FHHRTrMjiYgcEyogJCQtWlXIsrW7sQAXndrP7DhByVe+E19lMW1r/gmArccw\nbN2H4Mz8mcnJREREQtfqzWX8Y9lWBvbswk2XjiQmUnM+iEjoUAEhIefd1UUsXVOM3Wbl6VtO1RrZ\nh8nw+2lZ/jC+0q0Ht0X+bCb2nsNMTCUiIhL6Nu6o5OUVBWT0SeCWy0bi1GoXIhJiVEBIyKhvcvPS\n8q1s2lVNQqyL314xWuXDYfLXldO84jGM+nKsCT1xnfJzbAk9sETEmB1NREQkpK0vqOBv726hV0oM\nN14yQuWDiAQVw9OGtyQXo3wbXHj9Dz5OBYSEhD3lDTy2IIf6Zg+Z/ZO47sJhRLp0eh+Otm/exb1+\nEQDOURNxHncpFosm7RQREeloqzaV8up720hPi+W2yaN0DSMinZ5hGBhNB/Dt24KvohBv8TcYLXU4\nktMP+ef06iZBr6XNywPz1uP1GWSf0pfsU/qaHSno+Kr3tJcPdhdRk2ZhS9YxFBERCYTPc0t5eUUB\ng3vFc9OlI4iK0OW5iHRORlsT3t05+A/sw1O8AaOuvH2H3YktdSDOkdfg6Dn0kH+HXuEk6D39di5e\nn8GUMwdw3vG9zY4TVAxPG+7clbg3LAYgKvsP2JJ6mZxKREQkPOTuquLlFQUMTW+f88Fh120XItK5\n+OsrcOeuxLs7B6Op5t9bLVhT++PMOAtban+sKf0Pjpy2WA89gloFhAS11ZvLKNhTy+Be8UwYpw/O\nh8PweWlZ+Ti+sgJwRRNx4nSVDyIiIgGye38Df33nv3M+qHwQEbMZhoHRUIlv/w68+/LxVexsH+Vg\ns7eviDf4VGw9hmJL7Y/FemRVggoICVqfbNzHq+9tA+C6C4dpvoLD4G86QMuKx/DXlGBPH0PkuTeZ\nHUlERCRsbC+p5em3c4mOtHPLZZlEOHVJLiLmMAwDX/lOPFs/wVda8N9RDq5obF3TsQ0+HUf/cVhj\nux6Tn6dXOwlKX20tP1g+/PHqcSTEukxOFDz89RU0zb8LAPugU4k84xqTE4mIiISPvMJqnlm8mfho\nF7dPG6VrGBEJOH9LPb7SAvw1JXh3b8RfsxccEdh7DMM2cgK21IFYk9OxWKzH/GergJCgs2tfHc8t\n2QLAn687gW6JUSYnCh7+lnqalz0MgOuEqThHnm9yIhERkfCxq7SOZxZtJjkhkjunZdEl2ml2JBEJ\nE0ZbE77KIjw7v8RbtB48rYAFa1JvXCfPwDHwZCzOyA7PoQJCgsqGbZU8u3gzAHdMHaXy4TD4W+pp\nfud+jIZKHMPPVfkgIiISQLv3N/DEm5voEuNU+SAiHc7wtOE/sBdvSV77KIeq4vYddhf29CwcQ87A\nljoAiy2wlYAKCAkaG7ZV8OziPABum5LJsL6JJicKDoa3DXfeB7i/egsAZ+bPcB0/xeRUIiIi4WPH\n3loef3MTURF27lD5ICIdxPD78Ffvwbs3D/emFeBuBsCa1Afn6Gys8WnY+4zC4ogwLaMKCAkKeUXV\nPLs4Dwtw+7RRDEtX+XAoht+Lb29e+xCrnV8e3B5xxrU4Bp1sYjIREZHwkrOzirmL80iMc3HH1FEk\nx3f8EGcRCR+G4cdfUYg7/2O8uzeCuwUAW49hODLOwNY1HWtcsskp/0sFhHR6u/c38NiCTQD8SXM+\nfC/D3YJn1zr8dfvx7d+Ov6Lw4D5b6kDsA0/EMehkLHZNdCUiIhIIhmGwdE0x764upmdKDLdOztTI\nBxE5aobhx2iowlu8Ae/eLfj2bwevu30SyT5Z2HuNwJrUC2tCz065SqAKCOm0fH4/Ly4rYO2W/QD8\n/soxKh/+fwy/F+/2NbSuevG/G52RWFP64Rh0Cva+Y7FGxpkXUEREJEyt/GoPiz8vYvSgZK7+WQZR\nEbrsFpEj42+sxrd3C76avXh3b8RoqATAmtATx4ATsCb1xjHgRCyuaJOT/ji9EkqntK+ykScW5lJd\n34rdZuHuK0bTv3sXs2N1KobPQ8vSh/CV7wAg4qxfm35Pl4iIiMDqzWUs/GQX4zJSuO7CYVg74beQ\nItK5GV43nh1r8OR/hL+6pH2jzYGtazr2Eedi6zkMW3x3c0MeARUQ0uksWlXI0jXFAAxLT+DWKZnY\nrMd+DdpgZRgGntyVtH2zBDyt2NIGE3Ha1Vi7pJodTUREJOyt3lzGP5ZtZWDPLlxzQYbKBxH5yfz1\nFXhLt+It/gZfSR4YPqxJvXFmTcLe/3is8d2wWIP7I3xwp5eQs2FbJUvXFBMX5eBX2cPJ6JNgdqRO\nw99YTdvXi/Dt2YTR1ojFFYPz+Kk4Mk7H4tStKSIiImb7IreMF5dvJaNPArdcNhKH3WZ2JBHp5Hw1\nJbjXv4OvfAdGSz0Alqh4HBmnY+89CluvEZ1yLocjpQJCOg3DMHj1vQKsFgsPXX8STofetP/D31xL\n0+t3AO3L6DiGn41zxAQsTs2kLSLyfYqKipg1axa1tbXEx8czZ84c0tPTv/WYZ599luXLl2O1WnE4\nHNx2222ceuqp5gSWoLd6cxkv/bt8uPnSkbqOEZHv5W+px7c3D++eXHyVhRj1Fe0TSPYdgy2xN7a0\nQVi79sFiCc0R4CogpNPYuKOK+mYP5x/fW2/a/8NbkkvLx38DwHncpbiyJpmcSESk85s9ezbTp08n\nOzubJUuWcO+99zJv3rxvPWbkyJFcffXVREZGUlBQwIwZM/jiiy+IiNBcOnJ48oqqeXlFAYN7x3Pz\npSNxOXUdIyLt/C31eIvW46+vxFdWgL+yqH2HKxpb6kBsQ07HMeBErDGJ5gYNEBUQ0il8mrOPeSu3\nATDxpHRzw3Qi7rwPaFvzGgCuEy/HOWKCyYlERDq/6upq8vPzeemllwCYOHEi999/PzU1NSQm/vcC\n739HOwwePBjDMKitraVbt24BzyzBa3NhNXMX55GWFM1NKh9EhPa5HDy7vsK3bwu+sm1g+MFmxxrf\nHefoC7H3HtU+ysEafq8XKiDEdHvKG5i3chtWi4Xf/nw0kS6dlt49ObStnY+/bj9YLERdej+2xJ5m\nxxIRCQplZWWkpqZis7Vf2NlsNlJSUigrK/tWAfG/3nnnHXr37q3yQQ7L2i37+cfSraR1jeK2KZm6\nhhEJQ4bPi7+uDKOxBl/ZNrx7cvEf2AuANbEXjhETcAw4AVvXPiYn7Rz0Kimm+s9M0QD3/GIsfbrF\nmpzIfK1rXseT9z4AjhETcGVNwhIRY3IqEZHQ9dVXX/Hkk0/y4osvHvafTUrS63OgJCd3rmuE977c\nzQv/ymdE/6784epxREU4zI50zHS2Yx3qdLwD51gda19LI83bv6K5aBNN+WvaRzgAWKy4egwkevQv\niBo4BmdSj2Py80KJCggxzf+WDzPOHRTW5YPh99GQt4rGT+dj1JVjiYonatIsrF30TZyIyOFKS0uj\nvLwcn8+HzWbD5/NRUVFBWlradx67ceNGZs6cydy5c+nXr99h/6zq6kb8fuNYxJZDSE6OpbKywewY\nB63LL+f5f21heL9Ebrx4GE0NrTQ1tJod65jobMc61Ol4B87RHmt/Yw2egs/wle/Ety8fMMARgWPI\n6Vi79sGa0ANbfBqWiBg8QJ0fCMP/W6vVcshyXgWEmOKl5Vv5PLcMgMdvPJkuMS6TE5nHV1tK8+I/\n0uhpBSzYB55ExClXYnFoEjQRkSORlJRERkYGS5cuJTs7m6VLl5KRkfGd2y9yc3O57bbbeOqppxg2\nbJhJaSXY/Kd8GNijCzdcNEJLbYqEqP+vvTuPj6o89D/+OefMTDYIISFAEvY97JuAC1oBEVdQqyi3\n1rZqF1u9rbWW3nurttZraf15bW+ltba1t63iUne0FHFDZZF9h7CEEMieELJP5pzz/P6Il9ZbiyyZ\nmSzf9+vl6xXmJDNfHoeZJ995znOM7+NXF+GV7sMvP0Bk7xrwmrHTsgiOnkVwyDTszIEd9moV0aIC\nQmJu/e4y3ttaTHpqArdfPbbTlg8mXE/ztr/SvOV18Fy6jL0QM/qKTrMDrohINN13330sXLiQxYsX\nk5qayqJFiwC49dZbueOOOxgzZgw/+MEPaGpq4p577jn+cz/5yU8YPnx4vGJLG7er4Ci/WbqToX3S\n+Na147ThpEgHYbwIfkUBXtkB/GMleOX5+BWHwHgt3+AECfSfQMJZ12B36xXfsO2cCgiJqSMV9Sx+\naTsACxdMpEdaUpwTxYdfU0b98/dApAkroQuhKVfSc8Y1WoInItJKBg8ezHPPPfcPtz/++OPHv37+\n+edjGUnauYMlNfziha30Sk/mjmvGqHwQacdMcyNuwSbcIzswTfX4pfsw4bqWgwkp2F16EBxzEXa3\n3gSyR2B17YFl61fn1qBRlJipb4pwz2/WAnDndeM6ZflgjE947bNEti4DIDTlWhLGXxbnVCIiInIi\nRyrqefiZLaQkBvnWteM61IaTIp2BMT4N+Vto2rYW78gO/KNHwBisxK5YKd1xckYSGDARp/dQ7C4Z\n8Y7boamAkJioqW/m3x9fgwGuOGcAowd1rn/Yxovg7l1N8/bl+FWHsRK7kjjrNgLZufGOJiIiIidw\npLyOh57ejGNbfHv+eDK6aY8mkfbARMJ4xbtxCzbjHlhHXbgObAcnawShfuNw+ozG6T0cy9YeDrGk\nAkKirrCsjoee3kR9k8vV5w/i8nMGxDtSzBhjCL/3eyJ73jt+eZ7A4KkkXvhlLFtLN0VERNqy8upG\nHnp6M74x3L1gIr3Sk+MdSUROwLjNuIVbiex5D+/ILvCaW/ZvGDCR7qOm0pieixXqfKuw2xIVEBJV\nx+rC/PjJDTSGPa67cAhzpvaLd6SYCa99lubty8FzsVJ7kjD+cgKDp2IFO+emmyIiIu1JWXUjDz+z\nGdfz+d7nJpHdIyXekUTkE/iNNXjFu/HKDrR86Beux0rpTnD4eQT6jsHJGYUVCNE1sytN2m8t7lRA\nSNRsO1DJfz27BYDPzR7GjIl94pwoNvzaCsJrnsbNXw9YJEy9juDYObpEj4iISDtRUd3If/5xA67r\n881rx6l8EGlDjO/jlezBPbgJr3Ar/rFSwAAWTr+xhHI/c7x0kLZHBYRExVMr8lix/jAAt1yeyzmj\ns+KcKKeb7qMAACAASURBVDb82nLql3wHADtzEMlXLNSLn4iISDtS3xThv57bguv6LPyXifTp2SXe\nkUQ6PWMM/tEi3Px1RHa/i6k/CnYAp+cgQkPOxskegZM5ACuglcZtnQoIaXWvrylgxfrDJCUEuPuG\nCfTv3TXekWLCqyyk4fnvA5Bw3k2ERl4Y50QiIiJyKsLNHv/17BbKqxv59vzxKh9E4shvrMEr3Utk\n90q80n0QrgcsnJyRBKdeR6DfeO3n0A6pgJBWtXxdIX9+Zz+ObfHQbeeQlNDxn2LG+Lh5H9D07m8B\nSJh2g8oHERGRdiYc8Xj0xW3kF9dw27zRDO/XPd6RRDod01RHZP9a3P1r8Ur2AgaCiQQGTMLJGkYg\nOxc7tWe8Y8oZ6Pi/HUrMbDtQydNv7gXg/lumdujywbhh3MJtuHtX4R7ZCZEmAJKu+B6BrOFxTici\nIiKnIuJ6LH5xO9vzq7hpznAmDdcvOCKxYiJhIvtWt5QORbsBg9WtF6Hxl7ZcKjNzkDZx70A67m+I\nEjN1jRGWrzvE0lUFADxw61R6d8DLVBm3GffAupbiYf+a47dbXTMJjr6IwJCzcbpnxzGhiIiInKqm\nZpdHX9zOjo/KhwvG58Q7kkiH59eW4xXvwT2yE7dgMzQ3YKX2JDhmNoEBE3F6D8OyrHjHlChQASFn\nZPX2Eh5fuhOAhKDD3QsmkJXRMXeKbnzjv/EKtwHgZI0gOOxcnH7jsJNS45xMRERETofr+Sx+cTs7\nVT6IRIUxBlNThnf0MN6RXfi15ZhwPX7pPgCshC4EckYSHDWTQHZunNNKLJxxATFjxgxCoRAJCS3L\nYu666y6mT5/O5s2bueeeewiHw+Tk5PDTn/6UjIwMgBMek/ajui58vHz42rzRTBjag4DT8S416Rbt\nonnLX/AKt2F3zyb5yn/HSuiYJYuIiEhn4fk+v3yp5bSLL14ygunjtIpR5EwZ4+NXFuIe3oZfWYhX\ndgBTW95y0Algp2VjBRMJjrmY4NBzsDP66lL1nUyrrID4+c9/zrBhw47/2fd9vvOd7/Dggw8yefJk\nFi9ezEMPPcSDDz54wmPSfuQX13D//6wH4MtXjuSsER3vXEm3cBtNq/6EOVYKgN1jAMmXf1e77YqI\niLRznu/zm6W72LS3ghtmDVX5IHIG/LrKllOU89fjVxRgmmoBsFK6Y6f2JDDuUpyMvtgZ/XR5eonO\nKRjbt28nISGByZMnA3D99dczc+ZMHnzwwRMek/Zh/5FjPPT0ZgBumzeayR2sfDBuM5GdbxJe8wwA\ngWHnkTDhCuxuveKcTERERM5UU7PLr1/ZyeZ9FVxzwSAumtw33pFE2g3ju5iaCvz6KiJ5H+AV78bU\nVQJgpfZq2TQyaziBvmOwu2iFu/yjVikg7rrrLowxTJo0iTvvvJPi4mKys//WJKenp+P7PtXV1Sc8\nlpaW1hpxJIqOlNfxwB83APDFS0d0qPLBuM34NeU0vPRDcMNgB0i57j91qR8REZEO4n/3fNiRX8WC\nWUOZpfJB5ISM24x/rBT3wId4pfvwKgqguaHlYCBEoN947JEzCOSMxO4xQBtHyqc64wLiySefJCsr\ni+bmZh544AF++MMfctFFF7VGthPKyOgS9ceQFpmZXY9//eOnNgKw6BvnMXJgx2k1m8sLOfz7b4Pv\nAdBl1HR6XPpV7FBiTHP8/VhL9Gm8Y0djLSLx5vuGx17eoT0fRD6FCdcfP6XCLdgMvgtY2JkDCfQf\nTyA7Fys5DSdzIFaifieTU3PGBURWVhYAoVCIBQsW8LWvfY3Pf/7zFBUVHf+eqqoqbNsmLS2NrKys\nf3rsVFRW1uH75kzjy6fIzOxKeXktvjH8/vXd5B2qZsLQHmR2CVFeXhvveGcscmAdzVtexy/PByA0\ncS5O76FYfUZTeSwCRGKW5X/HWmJD4x07GuvYsG1L5bzIP+F6Pr9ZupMNeeVcP2OIygeR/8NvrMEt\n2IRXuA334EYwPgQTCQ4/D6fXEJzsXJ1SIa3ijAqIhoYGPM+ja9euGGN4/fXXyc3NZfTo0TQ1NbF+\n/XomT57M008/zZw5cwBOeEzapqKKehY9tZHahgi9uifxxUs7xiVyInveo+nd3wIQGHQWwZEzdPkf\nERGRDsb3DY+9soMNe8q56vxBzJ7SL96RRNoEEwnjlR8gsuNN3ENbwWuGhBSCI84nMPTclhUOTlS2\nDJRO7IyeUZWVldx+++14nofv+wwePJh7770X27b5yU9+wr333vuxS20CJzwmbY/vGx7443oawx5X\nnjuAuecNbPfndvl1VTS99Su8kjxwAqRc8yPstN7xjiUiIiKtzBjDkjf3smFPOfNnDOFilQ/SSRlj\nMHUV+EeP4BXn4RbvwS/b33IwlExg0GRCo2ZiZw7UZTElqixjTLs8j0GnYESfbwz//vhaSqsauGhy\nX26YNTTekc6I31CNu/9DwqufAlpWPYQmXIGT0TYmI1qmHlsa79jRWMeGTsGID81HYuN0Xkc83+d3\nr+1i9Y5SZp/Vl+tntu95TKzoNTu2oj3efk0Zkf0f4h74EL/yUMuNloOdnkOg3zisrj0IDprSKS4z\nr+d2bHzafERrauQTGWN4cnkepVUNjBmUwfyZQ+Id6bSZ5kaa3vs97v61LTdYNkkX30Gg3/j4BhMR\nEZGo8I3hd6/tZvWOUuZM6cdnLxwc70giMWF8H694N5Fd7+CV7sPUVwFgp2WTcPYN2GlZOFkjsAKh\nOCeVzkoFhHyix17ZwYe7ykhJDHD7NWOw2+lpF25JHo1/eRgiTdjdcwiNuRin7xjslO7xjiYiIiJR\n4PuGP/x1N6t3lHDV9IFcce7AeEcSiRpjDKa2nMi+NXhFu/BK9oLvYiV2xckegd1jJsFBZ+my8tJm\nqICQjzHG8NrqguPlw//cN4ea6oZ4xzplxvg0vf1r3H1rAAgMm07SZ26OcyoRERGJpnCzx69f3cGm\nvRVcfk5/lQ/S4Ri3Ga88H+/QFtySPPyjR6C5EQA7oy+BIdMI5IwkMHASViAhzmlF/pEKCPmYVz84\nyEvv5xNwbB64dRoJQSfekU6aMYbmLa/h7nkfv6YMjI+d0Y/Ez9yKk9E33vFEREQkihrDLj9dsomC\nklqunzmU2WfpvV86BhMJ41cXEcn7gMjud8GLtOzjkDmA4JCzsbtn42SNwEnvE++oIp9KBYQc9/bG\nw8fLh8V3nk/AaR874Pq15TStfALvyM6WGyyHwOCp2N2zCY27DMtuH38PEREROT0R1+MXL2yjsKyO\nb1w9hgnDMuMdSeS0GN/FKzuAX1GAd2QnXnUR5ljpR0etlhUO/cbh5IzETkqNa1aR06ECQgBYsmIv\nb6wvBOC7/zKhzZcPfmMN7t5VuAWb8Yp3A2D3GEBw2LkEh53XKXbyFRERkZY9Hx57ZSe7Co5y82W5\nKh+kXfKbaonseItI3nuY2goArC4ZOJkDsQdOxs7o3/J1qp7f0r6pgBD+Z9lu3t1chAX81+3nkZrS\ntnfF9atLqH/ph9DcsjdFYNBZBIedi9NnNJatp7SIiEhnYYzhj8v3sDGvnBtmDuXcMVnxjiTyqYwX\nwS3YjH+0iLKmCuoP7cbUlgPgZA0nOPlqnN5Dsbr0wGqnG8GL/DP6ba2Te3fzEd7dXERyQoD/941z\n2/SeD8Z3cfM30PTO4+C5hKZcS3D4dC0/ExER6YR8Y1iyYi/vbi7ikmn9uEh7PkgbZoyPd2gLkbwP\n8EryMI01ALjJqTg9h2APn04gZyROryFxTioSXSogOinP91m29hDPv3sAC/jhzVPadPkA0PTOb3H3\nrQYgcdZtBAdNiXMiERERiQffGJ54bRcfbC9h9ll9+ewFg+MdSeQTeeX5NG9bjpu/DjwXElIIZI0g\nOGI6TvZIemZlUF5eG++YIjGjAqITen9rMX9cvoeI6xMM2PzwS1NIT02Md6x/ykSaaN60FHffaqyE\nLiRfdY+uZSwiItJJGWN45s19fLC9hCvPHcDc8wZqmbq0Gcb4mJpyIgfWEdn9bsupFU6A4NDzcLJH\nEBg4GcvRr2DSeenZ38nsO3yM372+Cwu4fuZQLhiXTUKo7a18ML4Pvotxw9Qv+Q5EmiCQQPJV92rz\nHRERkU7stdUFvLG+kFmT+qh8kDbDb6zBK9xGeP0LmLpKAJzewwiMmklg6Dk6ZVjkIyogOpGI6/Pg\nkxsA+I+bJjMwq22+ELpFu2lc9jC4zcdvC464gIRp1+vqFiIiIp2UMYZXPzjIS+/nM21UL66fNVTl\ng8SF31CNV5yHf/QI/rFS/Joy/IqDYHzs7jmEzl6A02cUTveceEcVaXNUQHQiz761D2NaVj60xfLB\nuGEa3/gFXuE2AAJDzsZOz8HulkVw4KQ4pxMREZF4evn9fF754CBTR/biS5fmYqt8kBgyzQ24+Rto\n3vwa/rGS47dbKd2xu/UmOPoiAn3H4uTkYllt+3L2IvGkAqKTeGfzEd7ceJjsHinMboO7RHtVh2lc\nugjTVEtgyNkkTJuPnZwW71giIiISZ8YYnnh1B698cJBzx/TmS5fmauWDxIRXcZBI3ircQ5tb9nIw\nBju9D6FJ8wj0HYud0RfLCcY7pki7ogKiE9h1sIo/LNtDKGjztbmj4h3nY0xzA+EPnyey800AgmPn\nkDjt+jinEhERkbbA/2jDyTfWFzJ9bBY3Xjxc5YNEld9Ui7t3Ne7BjXjFuwFwckbhDJyMkzUcp88Y\nLFsrHEROlwqIDs4Yw2Ov7gTgOzdMICezS5wTtTBNdUTyPiC8ZknLDU6IpItuI9BvfHyDiYiISJvg\nG8NTb+Tx1sYjXDF9EHPP6a/TLiQqjOfiFm7BzfsA9/AOcMNYXTMJTb6a0MgZWIltY/4s0hGogOjg\nXlh5gJr6Zq4+fxCDs7vFOw5+XSVNbz9+vFEGSPzMLQSGTMOy9XQUERGRFn9+Zz9vbTzCnCn9uHXu\naCoq6uIdSToIYwx+ZQH+sTK8ol24+esxTbVYSakEh0wlOHIGdkY/7eUgEgX6ja8DW7b2EK+tLsCx\nLeZM7RfXLF75QSI73ySS937L+XOZAwkOmUYw90KsQCiu2URERKTt8I1hyRt7eXPjYWZMzOHaCwfr\ntAs5Y35DNd6RnUT2rcGvKMA0Hms54IQI9BtLYMg0An3Hal4qEmUqIDog3zf8afke3tlcBMDCf5lI\nwIlfg+s3HKPhxfsAWjbuGTuH4LDz4pZHRERE2iZjDE+vaCkfLprcl/kzhqh8kNNifB+vbB/u3lW4\n+RswTbUAWF0zcbJH4OSMxOk5CLtLD13mXSSGVEB0MMfqm/nur1bRHPFJDDk8+JWz6ZYSnybXGEPz\nuudp3rwUgMTZdxAcMDEuWURERKRtM8bw1Bt/Kx+un6nyQU6NaW7EqyjAK8kjsvtdTF0l2A6B/hNw\neg/FzuiH03u4NpEUiSMVEB2E7xteWHmAZWsP4RvDvPMGctk5/XHi8ALrVRTgHt6Ou3cV/tEjACRe\ndLvKBxEREflExhiee2c/b248zOyztPJBTp7fWIO79wPcgs14pfvA9wCwM/oSmnglwUFnYYWS45xS\nRP6XCogO4jev7WTNjlJCQZsvXJLLtJG9Y/r4xnfxivbQvH053qEtLTc6QZys4STNuRMrmBDTPCIi\nItJ+vPhey4conxmfrfJBPpVff5TI3lW4+z/ErzrUsr9Y9z4ER88mkDUcu+cg7KTUeMcUkU+gAqID\nKDvawJodpaSmhFj01bNJCDoxfXyvspCmN3+JX92y54TVrReJ534eJydXuweLiIjICf31w0MsXVXA\n9LFZfO7i4Sof5BP5tRV4RbuI7FuDV7QLjI+dOZDQ+MsJDDoLJyO+G66LyMlRAdHONUc87v+f9QB8\n89qxMS8fIvs/pOnNxQA4OaNIvOBm7C7pMc0gIiIi7dObGw7zzFv7mDQ8k8/PGY6t8kEA43t4pfvw\nCrfhlefjVxdj6qsAsBK6tGxoPvx87LTYrvgVkTOnAqKde2HlAeqbXGaf1ZcBvWO71Cy84SWaN7yE\nldiVpNl34PQeGtPHFxERkfbr3c1HePKNPCYM7cFXrhwVl32rpO3wq4txi/fgFe3CK96DaagGy/ro\nqhW52F17EBg4Gbt7jjaRFGnHVEC0Y4fL61i+rpCM1ASunxm7X/6bd79LePUSiDRBMImU+T/GSkiJ\n2eOLiIhI+7ZifSFPrdjLyAHd+erc0XG9XLjEj2luIJK3CvfAh3glewGDlZSK03sYgf7jCQyYpEtk\ninQwKiDaqf1HjvHAHzcA8OUrR8Xscb3KQsIrnwDLJjRpHqFRs1Q+iIiIyEn7YFsxT63Yy4ShPfja\nPJUPnY1xm/GK9xDZsxL30FZww9jdswlNmvu3FQ46FUekw1IB0Q49/+5+XltdAMA3rh7D0D5pMXlc\n99BmGpc9AkDy3P/A6TkoJo8rIiIiHcPbGw/zp+V5WvnQyfh1VXile/FK9xHJ+wCaGyCUTHDoOQSG\nTMPpPUylg0gnoQKinTlWF+a11QWEgja3zRvD2MEZUX9M01RHeO2zRPasBCBx9h0qH0REpM3Kz89n\n4cKFVFdXk5aWxqJFixgwYMDHvuf999/n4YcfJi8vjxtvvJHvfve78QnbibyxvpAlK/YybnAGX503\nmmBA5UNHZZrqcIv3ENnzHn75AUxjTcsBJ4DTezjB3M8Q6DcOKxCKb1ARiTkVEO2IMYbf/2U3AN9d\nMJGBWdHfdLKpcBd1zzwI4XrszEEkTr8Jp0f/qD+uiIjI6br33ntZsGABc+fO5eWXX+aee+7hD3/4\nw8e+p2/fvjzwwAMsW7aM5ubmOCXtPD7cVcoSnXbRIRljIFyPW5KHd3gHXtk+/IpDtOzn0A2n7zjs\ntN4EsoZjZ/RT6SDSyamAaEf+Z9ketuyvZFifblEvH4wxNL3x39Qe3AhAaNylJEy9LqqPKSIicqYq\nKyvZuXMnTzzxBACXX345999/P1VVVaSn/+0y0f37t5TpK1asUAERZdvzK/nN0p0M7dONr84dpfKh\nAzC+j191iMjOt3HzN2DCdS0H7AB25gBC4y/FyR6JkzUMywnGN6yItCkqINqJ597Zx8otRfTolsh3\nFkyI6mOZSJjGN/4b7/B2gulZhC65Gzule1QfU0REpDUUFxfTq1cvHMcBwHEcevbsSXFx8ccKiNaS\nkdGl1e+zI8k7dJTFL26nT8+u/OAr59A1+fQ//c7M7NqKyeREPmmsjRehMX8bNRv/SsO+jWB8LCdI\n8rDJJGQPJZTZj8T+o7C1wuGU6bkdOxrr+FMB0Q6s213GX9YconvXBP7j85Ojdp1sv+EY7t5VhNc+\nA4DdczA5N/2QymORqDyeiIhIe1dZWYfvm3jHaJN2Hazi5y9so2tSkDuuGUNTfZim+vBp3VdmZlfK\ny2tbOaF8kr8fa2N8vOI83APrcA9txtRVtmweOWomdvccAv3HYyenEQEiQP3RMHB6/487Kz23Y0dj\nHRu2bZ2wnFcB0cY1Nbv88qXtAPzolqkkJUTnf1nzrncIv/f7439OmHY9obFzsEOJtLyliIiItH1Z\nWVmUlpbieR6O4+B5HmVlZWRlZcU7Wqey59BRfvb8VjLTkrjzuvGkdUmIdyQ5Scb38I+V4B7c1LKJ\nZHUR2AGc7BEEp84n0G8sVjAx3jFFpJ1SAdGGGWNY/GJL+XDjxcNbvXwwxie89lm8wq34R4sASDjn\ncwSGTMVO1PIkERFpfzIyMsjNzWXp0qXMnTuXpUuXkpubG5XTL+STHS6r4+fPbyMjNZG7rp9AtxQt\nyW8P/Opiwuuep6BkD35jy6fEduZAEs77PMHBU7ESUuKcUEQ6AhUQbdiytYfYnl9Fr/RkPjM+u1Xv\n2/gujUt/gleSh5XUjcCw6SRMuhK7a2arPo6IiEis3XfffSxcuJDFixeTmprKokWLALj11lu54447\nGDNmDOvXr+fOO++krq4OYwyvvfYaDzzwANOnT49z+vYtv7iG/3p2CwlBmzuvG6/yoQ0zxmBqynCL\ndxPZ8SZ+5SEIJpIyeAJuzxE43XNweg2Jd0wR6WBUQLRR+48c47l39gNwz02TsSyr1e7br62g8Y1f\n4FccxO6eQ/I192NFaV8JERGRWBs8eDDPPffcP9z++OOPH/968uTJrFy5MpaxOrxdBUf52Z+3kJwQ\n4O4FE8nopmX6bYWJhPEqDuJXF+OV5OEfLcKvOgy+C4Cd0ZfQpHkER1xArwH9dJ68iESNCog2qKii\nngf+uAGA7980udVOvXCP7KRp5ROY2nIAAoOnkjTza61y3yIiItJ57f6ofMjslsS3r9eeD22B8V28\nsnwiW5fhFm4Dr+Vys1ZiV+yMfgRHXojdPQe7ew5Or8FYlj6MEpHoUwHRxuw8WMVDT28G4KY5wxmY\nlXrG92maG2h693e4+esBCAw7j+Dw6QSyhp/xfYuIiEjnll9cwyN/3kL3roncdYP2fIgn4zbjFm4l\nsusd/MpCTOMxCCYRHDINp9847LQs7G69tfJVROJGBUQbUlrVcLx8uPmyXM4dc2Y7dptwPeEP/0xk\n19stNySkkPLZH2GndD/TqCIiIiIcKa/jZ89tITU5xMIFKh/iwSs/iFu4Fb/iIF7JXkxTLVZyGk52\nLoG+o3H6jsVOOvMPtEREWoMKiDbilQ/yeem9fAC+cfUYJg47/c0gjTG4ez+g6f0/ghvGSk4jNP5y\ngsPP02WTREREpFUcLKnhp0s2E3AsvnXdOLrptIuYMJEwbsEmvOLduIe2YuqrALBS0ltKhyFTCfQZ\ngxVQGSQibY8KiDZg9Y4SXnovn8SQw1euHMW4IT3O6P7C7/2eyO53AQhNnEvC5KtaI6aIiIgIAGXV\njTzybMuGk9/9lwn06JYU70gdmjE+XuF2IvtW4RVux4TrwHYI9BuHM+ZigsPOxUrsEu+YIiKfSgVE\nnO0uOMrjr+7EAh78ytlntHTRNDdQ//R3W5bepaSTMv/Har9FRESkVR2rC/PQkk14vuG788epfIgS\n4/t4R7YT2b8Wr3AbprEGElII9B5GMPdCnD4jsWxN5UWkfdGrVhwdrQ3zkyWbAPiPmyafUfngle2n\n4ZX/BN8jMHgaiRd8SeWDiIiItKrGsMsjz22lpqGZu2+YSFZGSrwjdSimuRH38Dbc/I14xbsxDdUQ\nSMDJziU4cBKBIdOwnGC8Y4qInDYVEHH07Nv7ALhh5tDTvtqFMT6RrX8lvPYZAEJTPkvC+MtbLaOI\niIgItKx8eOTPWyksq+P2a8YwKFsbG54p43t4ZfvxCjbj15ThHtracrnMUBKBnFEEBkwkMGASVlD7\na4hIx6ACIk6WrT3E2p2lDOubxkVn9T2t+4jsX0t49ZKWdtwOkHzVvTgZp3dfIiIiIv/MsfpmHnpm\nM+VHG/nG1WPOeL+qzsoYg2msadlAct8a3MPbwYuA7WB17UFg0FkEh5+H03sYlu3EO66ISKtTAREH\nOw5W8ezb+0hKaNl08lQZY4jsWEF41ZMAhCZfRWjsJTrlQkRERFpdWXUjDy3ZRE1DM3d8diwjB6TH\nO1K749cfpXnLX3ALNmJqKwGDldiV4LBzcbKGE+g7FitBp7OISMenAiLGnlqRx4r1hwH40S3T6N71\n1JbUNW/5C807VmDqKgFImf9j7G69Wz2niIiIyLG6MA8/s5mGJpc7rxvPsL5p8Y7UbvjHSnALt7dc\nMrNoFxhDYMAE7MFTcfqOxckcqA+PRKTTUQERI1v3V/Dy+wfJL67Btizuun78qZcPO948vtdDoP8E\nEs6+ATu1ZzTiioiISCdXUd3I/3t2C9V1Ye66fgJDcrrFO1KbZowBL4JXno+bv57IjjfB+FipPQmO\nvohg7gU4adnxjikiElcqIKLM9w2PvriNTXsrAPjM+GxumDWUYODkz+szvkd41ZNEdr6FlZxG8rx7\nsLto+aOIiIhEx6HSWh56ejO+b/j2/PEqHz6BX1eJX3EIt3g3Xtl+/KojEGlsOWhZBAZNITTxSuy0\nbCzLim9YEZE2QgVEFBljeOL1XWzaW8Gwvml88dIR9OqefEr34VUX0fjKg5imWqyUdJKvugc7Wcsf\nRUREJDqKK+v56ZJNhIIOd84fT04P7U0ALfM6v2w/kfwNeIVb8Y8eaTngBLC75xAcejZWSnfslHQC\n/cZhJXaJb2ARkTZIBUSUrN9dxrqP/uvWJcS35487tVUPXoTwmmeI7FgBQGDQFBIvvFXXfhYREZGo\nyS+u4RcvbMOxLe5eMOGUPzjpiNySvbgHN+Dmb8DUlgMWTk4uoaHn4PQcjNNzkPZyEBE5SSogouCD\nbcX89rVdAPTv3ZW7b5hwSuWDX3+Uhpfux9RXYWcOJOGszxLoc+pXyxARERE5WfnFNfx0ySaSEwN8\n67rxnbZ88CoKcA9twT9Wgl92AP9YCVgWTvZIAuMvI9B/AnayTkkRETkdKiBa2a6DVcfLhx9/ZRo9\nT/HNO7zueZo3vQpAaNI8EibNa/WMIiIiIn+vuLKeh5/ZTJekIN/73KRT3ii7vTLGQKQJ/1gJkb2r\n8I7swD9aBNByOkXXTBJGzWo5vUKXyRQROWMqIFrRyi1F/P4vuwH4zvXjT6l8cAs207T6KUxNGVZK\nOokzvkIga3i0ooqIiIgAUFPfzCPPbcGxLe66YUKHLx+M7+MV7SKy62284j2YptqWA5bz0akV5xEc\ndq5WOYiIRIEKiFayeW/F8fLh7hsmMKJ/95P6OeOGaXr7cdz89QAEBk8l8fwvYQU79pu/iIiIxF9d\nY4SHn9nMsbpm7l4wkZ5pSfGOFBUmEsY/ehi3aA+RPSsxx0qwErrg9B2Dnd4XOyUNJzsXO+Xk5m8i\nInJ6VEC0gh35Vfz8+a0APHTbOaSnJp7Uz7lFu2j8y/8DzyUw6KyW4iHUMd/4RUREpG0pr27kkee2\nUF7dyO3XjGVQdmq8I7Uqv7Gm5aoV+9fi7v8QjA+A3aM/ofO/SHDQFM27RERiTAXEGVqzo4Rfv7oT\nuwVmPwAAFGVJREFUgK9fNfqky4emlU8Q2f0uAIkzv0Zw8NSoZRQRERH5e0UV9Tz4pw34xvCta8eR\nOyA93pFahXGbiexdRSTvffzSfS032gGCI2fgZA3H6TkIu0tGfEOKiHRiKiDOQEFJ7fHy4YFbp5KV\n8embE3mVhwivehKveA9Wai+SLrwVp9eQaEcVERERAeBQaS0/f34rAcdm4ecmtuurXRhj8MvzcQu3\nEdm7ClNbBsZgdc0kNGkeTtYInB79tdJBRKSNUAFxmnxjeOjpTQB8/6bJn1o+mEgT4Q0vEdm6DAC7\nxwCSr7oHy7KjnlVEREQEYPO+Ch59YRvJiQG+Pb/9XmrTNNUR3vQq7r7VmMYaAOxeQwgOnoKTM5JA\ndm6cE4qIyCdRAXEaCkpq+cHv1wFw9fmDGJj1z8+Z9KqLiGxdRmTvGvCasZK6kXTpt3Ey+sUqroiI\niAjrd5fxy5e3069nV+747Nh2d7UL43v45fk073jzoz0dPAIDJuH0G0ugzxjsLh3jNBIRkY5MBcQp\nqqlv5oE/bgBg3vSBXHp2/0/8vuZd7xDZ8x5+2X4ArG69CA49l4SJV8Ysq4iIiAjAroKj/PrVnQzK\nSuWb140jJTEY70gnzTTVcXTlX6hf/5eW1Q5OkODw8wiOmqkPdERE2hkVEKfgaG2Y7/16Na7n8+Ur\nRzJtZO9/+B63aBeR3Stx960GIDBgEsHRs7QUUEREROJi874KfvXydjLTEvnXa9tH+WCaG4jseqdl\nM8nqYjAGp+9YAgMnERw4GSvh0/fdEhGRtkcFxElavq6Qp9/cC8DMSX0+Vj74DdWEVz2FV5KHaagG\nwM4cROL5X1AzLyIiInFhjOH1NQU8/+4B+mR24dvXj6dLUtstH0y4nkjeB3ile3EPb4fmxpZ9HcbM\nIXPi+dSGsuIdUUREzpAKiJPw9Jt7Wb6uEICbL8vl3DEtb4DGbabprV/hHtwIgJWcRnDsJYTGzsFO\n7ha3vCIiIiIvrDzAa6sLmJLbky9dmkso6MQ70j8wzY34R48Q2beGyO6VH+2XlUqgz2hCYy4+fqWw\nxMyu1JbXxjmtiIicKRUQn6KgpJbl6wpJSQzwo1un0S0ldPxY+MM/4x7ciNWtF4nn/AtOnzFYlhXH\ntCIiIiLw6qqDvLa6gPPHZfP5OcOx28D8xBiDqS3HP3oEr6IAv/LQ8Q9xsB0CAycTGnsJTuaAuOYU\nEZHoUQHxKX772k4AvnPDhOPlg19XSdPKJ/AOb8dKSafL/EXxjCgiIiJy3GurD/LiygNMye3J5y+O\nT/lgjMHUlOGVH8CvLsE9tBn/6BHw3OPfYyV2JThqFk7WMJzsXOzErjHPKSIisaUC4gS2HajkcHk9\n54/Lpl+vrvgN1TS9+1u8wm0A2D0GkDTza3FOKSIiItLi7U1HeP7dA0wd2YtbLx+JbceufDDGtKxq\nyF+Pe3BjS+HwEbvXEIIjZ2J3ScfO6I/TcyBWoH1dBlRERM6cCohP4BvD2h2l/Oaj1Q+f/cxgjO/T\n+NpP8I8W4fQeRsLU646flygiIiISbxv2lPGn5XsYOziDWy7PjUn5YHwfN38d3pFduEU7MTVlYFnY\nmQNJOPsGnOxcrOQ07KTUqGcREZG2TwXEJ/jr2kM8985+HNvi1itHkuxW07BscUv50HcsyZfcGe+I\nIiIiIse9s/kIf/prHgOzUvnq3FE4th3VxzNNdbiHttC8YwV+eT4EE3F6DiYw7lIC/cZhp3SP6uOL\niEj7pALi/ygoqeW5d/YTcGz++45zsfLeon7JEgCCI84nYfoX4htQRERE5O+8tfEwf1qex+iB6dx2\n1WgSQ9GZ3vnHSnEPb8M9sA6vZB8YDys5jYTzPk9wxAVYdtu7yoaIiLQtKiD+zr4jx/jPP27Awuff\nLgwRefHfW5YSYpEw/SZCuZ+Jd0QRERGR49bvLuPJN/IYNziDr189hoBz5isfjDH41UX4lYfwq0vw\na0rxyvMxx0oBsLr2IDhqJoEBE3F6DcFyNJ0UEZGTo3cMoKqmib9+WMiK9YeYnrCba1LWY200GCBh\n2nxCYy+Jd0QRERGRj9meX8ljr+xgUHYqX507+ozKBxNpIrL7XbziPLyjh4+XDQBWlwzsbr1xhp9P\ncMBErG69ddlxERE5LZ2+gCiqqOee335ID6uau7qvpo9VBpZNaNylhMZdipWQEu+IIiIiIh+zfncZ\nj72yg6yMZL517TgSQqd++oOJhHELNuIV7cIt2IJpPIaVko6d0ZfAyBk4WSOwu/XGCupqFSIi0jo6\ndQFRUHyMZ556hW902cbgYBkAgUFTSJzxVawob94kIiIicqqMMSxdXcCLKw8wMCuVf712LMmJwVP6\neb/iIOE1T+OV7gPfg1AyTu+hhMZfTqD30CimFxGRzq7TFhAHNqwhed3v+FrXZgACQ84mNO5SnIy+\ncU4mIiIi8o+MMTz5Rh5vbTzCWSN68oVLRpCUcOKpnPE9/PJ8TFMtXtVhInnvY46VYiWlEhx9EYGc\nUTg5I7WBpIiIxESnKyCqa5tYvfQVzqt9HWwo6zOTgTPmYSd2jXc0ERERkU9kjOHF9w7w1sYjzD6r\nL/NnDPnEfRiMMZhjJXgVB/GK9xDZvxaaG48ftzMHEjp7AYEh07CTUmP5VxAREek8BYQxPjXvLcHZ\n/QbnfXRb6aSvMWTS1LjmEhEREfk0f/2wkKWrCjh3TG+u+z/lg19/lMiut/HKD+JXHMQ01rQcsAME\nBk4m0H8cdmpP7NReWIld4vQ3EBER6QQFhPFdwqueonnvGuxIAwD7e89m7Iw5DOmSHud0IiIiIie2\nansxz769j8kjevLFS3OxLQsTrsc9uJHI3lV4xXlgvJYrVfQZg9NzIE6vodipPbFCSfGOLyIiclyH\nLiCMF6Fx2SN4R3ZwzE9he/Mw7LPmc/HZg+MdTURERORTbT9Qye9e283Ivl350gRD8+qn8Ip34x8t\nAt/DSkknOGY2wRHTcdKy4x1XRETkhDpsAeEe3ETD27/GijSS7/bgkZpLuOzsAVyj8kFERETaOGMM\nG3ce5qXlG7g2/TDnNO8g8tdGsCyc7FyCo2cTHDARu9cn7wUhIiLSFnW4AsK4zdTs24y9cjEWsKJx\nFFu6TOcLl/Tj/HH6ZEBERETaJr+uEq9sP351CTXb3mVYuJK7UwADTmYuwZEzCPQZhRVKjndUERGR\n09KhCoi62joanr6bJNOy18PP6y/jwovO477RWXFOJiIiIvJxLVesKCVy4EPcwq34ZQfA+ACUu+kU\nJp3N9CkjSOwzHCu1l1Y6iIhIu9fuC4hws8e63WVEDm1mwpFnSbIMu+zhJJ11Nf82dpjerEVERKRN\nMMbHHCvFPbQVr2w/XvkBTG0FAHbPQQRHXsh2hvHUB2UMHtyfr8wbTcCx45xaRESk9cStgMjPz2fh\nwoVUV1eTlpbGokWLGDBgwCndx/Z9Zbzy0gpmJW1jXLAYLCgbMo8pM+ZFJ7SIiIi0eSczx/A8jx/9\n6Ee89957WJbFl7/8Za699tpWzWHcZtyDG/CPFuHXV+Ed2oppqgXASknHTu9DYMwcnJxcnO45rN9d\nxq9e3sHIAX1VPoiISIcUtwLi3nvvZcGCBcydO5eXX36Ze+65hz/84Q8n/fOvLV/H5P2PcXtqpOWG\n7n1JPP8LDO6lTSZFREQ6s5OZY7z66qscOnSI5cuXU11dzbx58zj77LPp06fPaT+u8SL4FQV4lYW4\nBZvwyvZDuB4AKzkNp9cQnL5jCOSMwkrt+bFVmtsOVPLYKzsYlJPKbVepfBARkY4pLgVEZWUlO3fu\n5IknngDg8ssv5/7776eqqor09PSTuo/PVD6Da0VoGnoR6ePOx0nvG83IIiIi0g6c7Bzj9ddf59pr\nr8W2bdLT05k1axbLli3jlltuOaXH85vqCO94G694d0vh0NzYcqBLD/ysMbj9p+BmDqMh7GNMy74P\nfq3B1BzDGEM44nOg6BivrS4gp0cK3/zsWBJD7f4MWRERkU8Ul3e44uJievXqheM4ADiOQ8+ePSku\nLj7pAgIgNOOrdB0yLVoxRUREpJ052TlGcXEx2dl/uzpWVlYWJSUlp/x4DS/eh3esnArTjXyvHzub\nenHETaO0qhscsmBjNfDhp95Pbv/ufP2q0SQnBk85g4iISHvRbiv2Xtd9j4Se/eMdo1PIzOwa7wid\nhsY6tjTesaOxlo5qd2gch7P7UZ+cjePYDE4OMiLgkJQQICnBwbYsHMciKSFIMGBjWWBZFo5lYdkt\nX/dKTyYzLUkbZ38KvY7EjsY6tjTesaOxjr+4FBBZWVmUlpbieR6O4+B5HmVlZWRlnfzlMuucDGrK\na6OYUqDlH2m5xjkmNNaxpfGOHY11bNi2RUZGl3jHiLuTnWNkZWVRVFTE2LFjgX9cEXGyJl9zIxN9\nc2ahXY+Kirozu48OTq8jsaOxji2Nd+xorGPj0+YjcdnhKCMjg9zcXJYuXQrA0qVLyc3NPaXTL0RE\nRET+r5OdY8yZM4fnnnsO3/epqqpixYoVXHzxxfGILCIi0mnE7RSM++67j4ULF7J48WJSU1NZtGhR\nvKKIiIhIB/LP5hi33nord9xxB2PGjGHu3Lls2bKF2bNnA/D1r3+dvn21obWIiEg0WcaYM1w3GB+V\nlXX4Z7rkUT6VlirFjsY6tjTesaOxjg2dghEfmo/Ehl5HYkdjHVsa79jRWMdGmzwFQ0REREREREQ6\nFxUQIiIiIiIiIhJ1KiBEREREREREJOpUQIiIiIiIiIhI1KmAEBEREREREZGoUwEhIiIiIiIiIlGn\nAkJEREREREREok4FhIiIiIiIiIhEnQoIEREREREREYk6FRAiIiIiIiIiEnUqIEREREREREQk6lRA\niIiIiIiIiEjUqYAQERERERERkahTASEiIiIiIiIiUacCQkRERERERESiTgWEiIiIiIiIiERdIN4B\nTpdtW/GO0GlorGNHYx1bGu/Y0VhHn8Y4PjTusaOxjh2NdWxpvGNHYx19nzbGljHGxCiLiIiIiIiI\niHRSOgVDRERERERERKJOBYSIiIiIiIiIRJ0KCBERERERERGJOhUQIiIiIiIiIhJ1KiBERERERERE\nJOpUQIiIiIiIiIhI1KmAEBEREREREZGoUwEhIiIiIiIiIlGnAkJEREREREREoq5dFRD5+fnMnz+f\niy++mPnz53Pw4MF4R2pXjh49yq233srFF1/MFVdcwTe+8Q2qqqoA2Lx5M1deeSUXX3wxX/rSl6is\nrDz+c6d7TFr84he/YPjw4eTl5QEa62gIh8Pce++9zJ49myuuuILvf//7wIlfM073mMDbb7/NvHnz\nmDt3LldeeSXLly8HNN7Seeg5e2Y0H4kPzUeiT/OR2NJ8pJ0y7ciNN95oXnrpJWOMMS+99JK58cYb\n45yofTl69KhZs2bN8T//+Mc/Nt/73veM53lm1qxZZt26dcYYYx599FGzcOFCY4w57WPSYvv27ebm\nm282F154odmzZ4/GOkruv/9+88ADDxjf940xxpSXlxtjTvyacbrHOjvf983kyZPNnj17jDHG7Nq1\ny4wfP954nqfxlk5Dz9kzo/lI7Gk+Ehuaj8SO5iPtV7spICoqKsykSZOM67rGGGNc1zWTJk0ylZWV\ncU7Wfi1btszcdNNNZsuWLeayyy47fntlZaUZP368Mcac9jExJhwOm+uuu84UFhYef8PXWLe+uro6\nM2nSJFNXV/ex20/0mnG6x6TlDX/KlClm/fr1xhhjPvzwQzN79myNt3Qaes62Ps1HokvzkdjQfCS2\nNB9pvwLxXoFxsoqLi+nVqxeO4wDgOA49e/akuLiY9PT0OKdrf3zfZ8mSJcyYMYPi4mKys7OPH0tP\nT8f3faqrq0/7WFpaWkz/Pm3Rz372M6688kr69Olz/DaNdesrLCwkLS2NX/ziF6xdu5aUlBT+9V//\nlcTExH/6mmGMOa1jeq0By7J45JFHuO2220hOTqa+vp5f//rXJ3yN1nhLR6L5SOvSfCT6NB+JDc1H\nYkvzkfarXe0BIa3n/vvvJzk5mc997nPxjtIhbdq0ie3bt7NgwYJ4R+nwPM+jsLCQkSNH8sILL3DX\nXXdx++2309DQEO9oHZLrujz22GMsXryYt99+m1/+8pd885vf1HiLyGnRfCS6NB+JHc1HYkvzkfar\n3ayAyMrKorS0FM/zcBwHz/MoKysjKysr3tHanUWLFlFQUMCvfvUrbNsmKyuLoqKi48erqqqwbZu0\ntLTTPtbZrVu3jv379zNz5kwASkpKuPnmm7nxxhs11q0sKyuLQCDA5ZdfDsC4cePo3r07iYmJ//Q1\nwxhzWscEdu3aRVlZGZMmTQJg0qRJJCUlkZCQoPGWTkHzkdaj+Uj0aT4SO5qPxJbmI+1Xu1kBkZGR\nQW5uLkuXLgVg6dKl5ObmaknMKXr44YfZvn07jz76KKFQCIDRo0fT1NTE+vXrAXj66aeZM2fOGR3r\n7L785S/z/vvv89Zbb/HWW2/Ru3dvfvvb33LLLbdorFtZeno6U6dO5YMPPgBadjCurKxkwIAB//Q1\n40SvJ3qtObHevXtTUlLCgQMHANi/fz+VlZX0799f4y2dgp6zrUPzkdjQfCR2NB+JLc1H2i/LGGPi\nHeJk7d+/n4ULF1JTU0NqaiqLFi1i0KBB8Y7Vbuzdu5fLL7+cAQMGkJiYCECfPn149NFH2bhxI/fe\ney/hcJicnBx++tOf0qNHD4DTPiZ/M2PGDH71q18xbNgwjXUUFBYW8m//9m9UV1cTCAT45je/yQUX\nXHDC14zTPSbwyiuv8Pjjj2NZFgB33HEHs2bN0nhLp6Hn7JnRfCR+NB+JLs1HYkvzkfapXRUQIiIi\nIiIiItI+tZtTMERERERERESk/VIBISIiIiIiIiJRpwJCRERERERERKJOBYSIiIiIiIiIRJ0KCBER\nERERERGJOhUQIiIiIiIiIhJ1KiBEREREREREJOpUQIiIiIiIiIhI1P1/9dwQDdXAnHQAAAAASUVO\nRK5CYII=\n",
            "text/plain": [
              "<Figure size 1296x648 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qgK2kJPdPxor",
        "colab_type": "text"
      },
      "source": [
        "### Boltzmann exploration (Softmax)\n",
        "\n",
        "- パラメータ$\\epsilon \\in (0,1)$を設定 (small)\n",
        "- パラメータ$w \\in (0,1)$を設定 (small)\n",
        "- $\\epsilon$の確率でExploration\n",
        "   - 各Armの行動価値をSoftmaxで重み付けし選択\n",
        "- $1-\\epsilon$の確率でExploitation\n",
        "   - 経験を元に、最大の行動価値を持つArmを選択\n",
        "\n",
        "\n",
        "$\\epsilon$-GreedyではExplorationにおいて全アームを等確率で扱っていた\n",
        "\n",
        "Boltzmann Exploration Algorithmでは行動価値の高いArmを高い確率で低いものは低い確率で、のように重み付する\n",
        "\n",
        "具体的にはaction=$a$の確率を重み$w$を加えて次のように定式化する\n",
        "\n",
        "$$ p_a = \\frac{ \\exp( \\frac{ \\hat{\\mathcal{Q}}_t (a_i)  }{w}) }{\\sum_{j}  \\exp( \\frac{ \\hat{\\mathcal{Q}}_t (a_j)  }{w}) }  $$\n",
        "\n",
        "したがってExploitationは次のように定式化されます\n",
        "\n",
        "$$  \\hat{a}_t^* = \\arg \\max_{a\\in \\mathcal{A}} p_a  $$"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BoXKj2eQCCmk",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "class BoltzmannSoftmax():\n",
        "  def __init__(self, epsilon, weight):\n",
        "    self.epsilon = epsilon        # Parameter epsilon (small)\n",
        "    self.weight = weight          # Weight for softmax\n",
        "    self.counts = []              # LIST arm count \n",
        "    self.rewards = []             # LIST rewards\n",
        "    self.expectations = []        # LIST expectation\n",
        " \n",
        "  def initialize(self, n_arms):\n",
        "    self.counts = np.zeros(n_arms)\n",
        "    self.rewards = np.zeros(n_arms)\n",
        "    self.expectations = np.zeros(n_arms)\n",
        "\n",
        "  def softmax(self, x):\n",
        "      e_x = np.exp(x - np.max(x))\n",
        "      return e_x / e_x.sum()\n",
        "\n",
        "  def select_arm(self):\n",
        "    # Exploitation\n",
        "    if np.random.random() > self.epsilon:  \n",
        "      return np.argmax(self.expectations)\n",
        "    # Exploration\n",
        "    else:\n",
        "      Boltzmann_prob = self.softmax(self.expectations/self.weight)\n",
        "      return np.random.choice(len(Boltzmann_prob), p=Boltzmann_prob)\n",
        "\n",
        "  def update(self, chosen_arm, reward):\n",
        "    self.counts[chosen_arm] += 1\n",
        "    self.rewards[chosen_arm] += reward\n",
        "    sum_select_arm = self.counts[chosen_arm]\n",
        "    sum_reward = self.rewards[chosen_arm]\n",
        "    expectation = float(sum_reward/sum_select_arm)\n",
        "    self.expectations[chosen_arm] = expectation"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_-oRxjKZPX9-",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 120,
          "referenced_widgets": [
            "5d050630dd144d56bed349a7bc28b208",
            "81e99ce8e85b4d6c8b22b0185bc6c33c",
            "fb7f1addd8c44a188e97870906195642",
            "97b8c945d8334fdeababef91254edb5e",
            "1c5d2d7b310a4d1f8bd66895bb9d587b",
            "70cefdf2377f4483afdc3381339e8b87",
            "8ca5ae2b77ac4ede87a6c7f268ca0c84",
            "60ebc453e5b64ddd88551063cc2db6d5"
          ]
        },
        "outputId": "b1c63242-54d8-4d0b-d5d6-0fa8eaf6a215"
      },
      "source": [
        "%%time\n",
        "\n",
        "epsilon = 0.2  # Parameter\n",
        "weight = 0.05   # Parameter\n",
        "BS = BoltzmannSoftmax(epsilon, weight)\n",
        "result = demonstrate(BS, arms, Trials)\n",
        "\n",
        "print(result[0].shape, result[1].shape)"
      ],
      "execution_count": 255,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "5d050630dd144d56bed349a7bc28b208",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(IntProgress(value=0, max=10000), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "(10000,) (10000,)\n",
            "CPU times: user 629 ms, sys: 84.7 ms, total: 714 ms\n",
            "Wall time: 613 ms\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mDZqHVcnPYAp",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df_BS = pd.DataFrame({\"arms\": result[0], \"rewards\": result[1]})\n",
        "best_arms_list_BS = (result[0]==np.argmax(probs)).astype(int)\n",
        "df_BS[\"best_arm_rate\"] = best_arms_list_BS.cumsum() / Trials"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sTwCgFrRPYDL",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 573
        },
        "outputId": "0f39dd17-9fdb-4f5e-b464-321852045e2e"
      },
      "source": [
        "plt.subplot(212)\n",
        "plt.plot(df_BS['rewards'])\n",
        "plt.title(BS.__class__.__name__ + ' {}'.format(weight))\n",
        "\n",
        "plt.subplot(222)\n",
        "sns.countplot(df_BS['arms'])\n",
        "plt.title('Each Counter')\n",
        "\n",
        "plt.subplot(221)\n",
        "plt.plot(df_BS['best_arm_rate'])\n",
        "plt.title('Best Arm Rate')\n",
        "\n",
        "print(Counter(df_BS['arms']))"
      ],
      "execution_count": 257,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Counter({9.0: 9292, 8.0: 334, 6.0: 112, 0.0: 77, 5.0: 53, 7.0: 53, 3.0: 45, 2.0: 17, 4.0: 15, 1.0: 2})\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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HAgIAgMtwvqZOH39xSpt35ajiXK0GR3XRvIWDNaBHF1dHAwAAaNUoIAAAaIKyqhp9vOek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\npHcAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 1296x648 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ctgRh9kJVEL9",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# Boltzmann softmax\n",
        "df_BS = df_BS.rename(columns={'arms': 'bArms', 'rewards': 'bRewards', 'best_arm_rate': 'bBAR'})\n",
        "\n",
        "df_compare_bs = pd.concat((df_EG_small, df_BS), axis=1)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XVg39fccPYFN",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 573
        },
        "outputId": "c1de2d2f-a4ab-4fcb-bc50-aa6b002647ad"
      },
      "source": [
        "f, axes = plt.subplots(1, 2, sharex=False)\n",
        "\n",
        "df_compare_bs[['sRewards', 'bRewards']].plot(ax=axes[0])\n",
        "df_compare_bs[['sBAR', 'bBAR']].plot(ax=axes[1])\n",
        "\n",
        "axes[0].set_title('Cumulative Rewards')\n",
        "axes[1].set_title('Best Arm Rate')"
      ],
      "execution_count": 259,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'Best Arm Rate')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 259
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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w1I/4h/4d8R+NtX9pvP1HY+0fl+pHCmwA4fUa+sL3E42z/2is/Uvj7T8aayms1I/4j8bZ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\n",
            "text/plain": [
              "<Figure size 1296x648 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Z0s8keAqbuA3",
        "colab_type": "text"
      },
      "source": [
        "SoftmaxはGreedyの改良版とも言えるはずだが精度は悪い\n",
        "\n",
        "これはおそらく両方のアルゴリズムが初期動作に依存し、かつSoftmaxはその依存度が相対的に高いことが原因かと考えられる\n",
        "\n",
        "たとえば初めの方の試行においてたまたま確率の低いArmを引くことによって、本来それよりもArmがあるにもかかわらずSOftmaxでどんどんそのArmの確率が高まってしまうからだ"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hpByM2pPg63v",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "7be91e51-a3a3-4f29-859c-a23dd79b6faf"
      },
      "source": [
        "result[0]==9"
      ],
      "execution_count": 260,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([False, False, False, ...,  True,  True, False])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 260
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_pXDTONCd0K9",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "percentages = np.zeros((Trials, n_arms))\n",
        "\n",
        "for j in range(n_arms):\n",
        "  before = (result[0]==j).astype(int)\n",
        "  culcul = before.cumsum() / Trials\n",
        "  percentages[:, j] = culcul"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "synLyekegZOi",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 660
        },
        "outputId": "69e9dd29-0546-40c7-871b-784f21a84d6a"
      },
      "source": [
        "tmp = pd.DataFrame(percentages, columns=['P: ' + i for i in list(map(str, probs))])\n",
        "\n",
        "t = 300\n",
        "\n",
        "f, axes = plt.subplots(1, 3, sharex=False)\n",
        "tmp.iloc[:t, :].plot(ax=axes[0])\n",
        "tmp.iloc[:2*t, :].plot(ax=axes[1])\n",
        "tmp.plot(ax=axes[2])\n",
        "\n",
        "axes[0].set_title('Until Time={}'.format(t))\n",
        "axes[1].set_title('Until Time={}'.format(2*t))\n",
        "axes[2].set_title('Cumulative Arm Rate')\n",
        "\n",
        "plt.tight_layout()"
      ],
      "execution_count": 283,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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n5yaXy+Dn5yV1GZJgTjk/9tn5uVp/Adfrs6vmlKtlVH252v8HDcFjVDseo9rxGNWstoxy\nisE9QRBdLpBcrb8A++wq2GdyRswp18A+Oz9X6y/gmn12Na6YUfXF41M7HqPa8RjVjseo4fhYLhER\nERERERERURPFwT0iIiIiIiIiIqImyikey62KxWLGzZs5MJtNUpdic3q9HIIgNNr+3NxU8PMLhELh\ntP+5EBE1KmfOKIA5RUTU1Dl7TtXHvWYaM4qIGoPTfsPcvJkDDw81vLyCIZPJpC7Hptzc5DCbG+ek\nSRRFFBXdws2bOWjePKRR9klE5OycOaMA5hQRUVPn7DlVH/eSacwoImosTvtYrtlsgpdXM5cPo3sl\nk8ng5dWMV+2IiGyIGWU7zCkiIttjTtkGM4qIGovTDu4BYBjZCI8jEZHt8bvVdngsiYhsj9+ttsHj\nSESNwakH94iIiIiIiIiIiJyZ086552hGjkyASqWCUqmCIFjw9NPjEBcXX+t6hw8fwurVb8NisSAi\nIgopKXPh7a2u1M5gyMOCBXOQlZUFd3d3TJ/+v+jc+T4AwIsvToBOp4OXlxcAYNSoJ/DII49WWP/j\njz/Exx9/iE8++Qzh4e1t0GMiImoqbJlRHh4eldoxo4iI6F5ImVPPP5+M7Oxs5hQROTQO7jWihQuX\nIjy8PS5cOIeJE8chNrYXfH19q21fXFyMZcsW4d131yAsrBWWLFmAzZs3IDn5uUpt339/FaKjY7Bi\nxbs4deokFiyYjc2bv7DeBv6Pf0xDnz79qtzP+fPn8OuvZxAczEleiYhcla0y6plnkiu1ZUYREdG9\nYk4REVWPj+VKoGPHSKjVamRlXa+x3dGjRxAZGYWwsFYAgKSkEdi//9sq2x44sA9JSSMBANHR3aBU\nKnHu3NlaazGZTFi+fCmmTZtZz14QEZEzYkYREZEjY04REVXmEnfu/XA6C4d/ybLLtvt2DUGfLvW7\nSnP8eDpMJhNCQ1shNzcH06ZNxbp1myq10+myodX+d9tabTD0el2ldgUF+RBFscKVqztto6I6AwBW\nr34bH3ywCu3bd8Tzz09GYGAQAOCjj97HoEFDEBLSol59ICIi22BGMaOIiBwZc4o5RUSOzyUG9xzF\nrFkzoFK5w8vLC4sWLYVGo4FGo6kyjGxp9uz50GqDYbFYsGHDWsyZ8xree+9fOHPmF5w//xuef36y\nXfdPRESOjxlFRESOTKqcmjdvAQICgphTROTQXGJwr0+X+l8Rsoc780TUlVYbjBMn0q2fdbpsBAVp\nK7Xz8bl9lSk/P996xenPbbXaYACAQqHA448/ibVr10AQBJw4cRyXL2dg1KjbE8Lm5Ojx8suTkZIy\nF/ff37thnSQionphRjGjiIgcGXMqGGazwJwiIofGOfccWO/eD+C3387i6tVMAEBq6nYMGBBXZduH\nH45Dauo2AMCpUydRVlaGiIgomM1mGAx51nbffrsH4eHtIJfL8dRTY7Fjx25s25aGbdvSEBgYhOXL\nVzKMiIioVswoIiJyZLbKqbw85hQROT6XuHPPkdU0T4Ra7YXp01Mwffo/IAgCOnSIwNSp06pcb+LE\nFzF//hzs3j0c7u7umD17PuRyOcrKyvDqq/+A2VwOURTRvHkQXn99caP2kYiImqaGZlROTg5eemky\nM4qIiOyqMc6lXnllCsrLmVNE5NhkoiiKUhdxr/LyjBCEit3Izr6C4ODWElVkX25ucpjNQqPuU+rj\nGRioQU5OoWT7lwL77Bpcqc9yuQwBAd5SlyGJu3NK6u9Ue2NOuQZX67Or9RdwvT67ak652rlUfdki\n05z9eLrad0VD8BjVjseoZrVlFB/LJSIiIiIiIiIiaqI4uEdERERERERERNREcXCPiIiIiIiIiIio\nieLgHhERERERERERURPFwT0iIiIiIiIiIqImioN7RERERERERERETZSb1AUQEZH9FRlOI+9KKgBR\nshpUHn4I6J8i2f6JiIiqYxFEbL6YjSkBHaQuhYiIqJLThkI8FOBd7XIO7jWSkSMToFKpoFSqIAgW\nPP30OMTFxde63uHDh7B69duwWCyIiIhCSspceHurK7UzGPKwYMEcZGVlwd3dHdOn/y86d74PACAI\nAv71rw+wf/+3UKmU0GqD8eabbwMAzpw5jZUrl6O0tARKpQqvvpqCiIhI23aeiCRXmHMMCpUPvPy7\nSlaDm9JTsn1TzWyZUR4eHpXaMaOIyNH9lm/EjZIyqcugakidU2vWvMecIiLJ6EtM+Pa6AQ91CKm2\nDQf3GtHChUsRHt4eFy6cw8SJ4xAb2wu+vr7Vti8uLsayZYvw7rtrEBbWCkuWLMDmzRuQnPxcpbbv\nv78K0dExWLHiXZw6dRILFszG5s1fQCaT4fPPNyEz8wo+/fRzuLm5wWDIAwCIoohZs6Zj3rxF6Nat\nu3W9DRs+h0wms9txIKLGZSrRw1R8A74tB6FZUG/J6pDL+b3iyGyVUc88k1ypLTOKiBzdUX0BmikV\nUpdBNZAqpz77jDlFRNIpFwRsuZgFlaLmWfVcYnCv/MIPKD9/yC7bVkb0h7Jjn3qt07FjJNRqNbKy\nrtcYSEePHkFkZBTCwloBAJKSRmDhwnlVDu4dOLAPW7emAQCio7tBqVTi3LmziIrqjM8+24h3310D\nN7fbv25//wAAQH5+PozGQnTr1t26nl6vx/nz5xAZGVWvPhE5s/IyAwyZaRAFs823nXdJgfJyi823\n+2cWcxEAObz8uth1P1LKyMjAzJkzkZ+fD19fXyxduhRt2rSp0MZisWDhwoX4/vvvIZPJMGHCBIwa\nNQoAsH37dqxbtw5yuRyCIGDUqFH4+9//DgBYuXIlNm3ahKCgIABA9+7dMXfuXJvV7mwZVdVJEzOK\niByZvsSES4UlSGoTJHUpDsnVc2rz5g1YtYo5RUTS+DozB1klJiRHhdXYrk4v1MjIyMDo0aMRHx+P\n0aNH4/Lly5XaWCwWvP7664iLi8PAgQOxdetW67LDhw/jsccew3333YelS5dWWnfXrl1ISEjAsGHD\nkJCQgNzc3LqU1WQdP54Ok8mE0NBWyM3NwdixY6psp9NlQ6v9722XWm0w9HpdpXYFBfkQRbFCuN1p\nazQacetWAf79731ITn4azz33DL7//jsAgJ+fH3x8fK2fDx8+hOLiIuh0WbbrLJETMOb8jLKiq5Ar\n3G3+R+HmYZft/vmP0t0fvi0ehkLpJfWhtJu5c+dizJgx2LNnD8aMGYM5c+ZUapOWlobMzEzs3bsX\nW7ZswcqVK3Ht2jUAQHx8PL766ivs2LEDmzdvxtq1a3Hu3DnruklJSdixYwd27Nhh04E9R8SMIiJX\nc0xfAIUM6BqgkboUqoPGzqmCAuYUEUnjjKEQP+fcQv9gP7RrVvMUR3W6c+/OSVNiYiJ27NiBOXPm\n4JNPPqnQ5s8nTfn5+UhKSsIDDzyA0NBQhIWFYdGiRdi9ezdMJlOF9U6fPo1Vq1Zh/fr1CAwMRGFh\nIVQqVT27XDNlxz71viJkD7NmzYBK5Q4vLy8sWrQUGo0GGo0G69Ztsts+BcECk8kEURSwZs16XLt2\nFS+8MB7h4e3RsmUoFi9+C6tXv4O1a9egU6cuaNs2HAoFH0kgukMULCi6eRpqn0g0bzvS5tsPDNQg\nJ6fQ5tt1JXl5eTh79izWrl0LABg2bBgWLFgAg8EAf39/a7tdu3Zh1KhRkMvl8Pf3R1xcHHbv3o3x\n48fD2/u/k9OWlpaivLy80R6pYUYxo4hIOiaLgON5t3CfnwZqN36/VIU5xZwiosZnLDdjx5UctFS7\nY2DLgFrb1zq4Z4uTptatWwMA9u3bV2lwb926dXj22WcRGBgIANBonPeK2Z15IupKqw3GiRPp1s86\nXTaCgrSV2vn43L7KdOdxtD+3bdbMB56eagwaNBQAEBoaho4dI3Dhwjm0bBmKiIhIvP32agBAeXk5\nEhIGoU2b8Ab3kcjZlNy6AMFcDC//aKlLoWpkZWVBq9Va/zGtUCgQFBSErKysCjmVlZWFFi1aWD+H\nhIQgOzvb+nn//v1Yvnw5MjMz8corryAiIsK6bOfOnTh8+DACAwMxefJkxMTENELPGhcziohc0SlD\nIcosAnoH+UhdCtVCqpxSq5lTRNS4RFHEjis5KLUIGBmuhaIOc5fXOrhnq5Om6ly8eBGhoaH461//\niuLiYgwcOBDPP/98ve6YCKjidcB6vRxubnV66rjRKBT1q6lPnz5YsWIZbty4hlatWmHHji8QFzcQ\nACptZ8CAgfjqqy/w7LPjcfLkCZhMJnTu3BlyuRyDBsUjPf1HJCWNgMFgwMWLv6NDhw5wc5MjLy8X\nAQHNAdweaO3evQfatGldqRa5XI7AQGkHXqXevxTYZ+n9cfUMlO7NENauG2Qy+3ynOFqfXdVf/vIX\n/OUvf8GNGzcwadIk9O/fH+Hh4XjiiScwceJEKJVK/PDDD3jhhRewa9cu+Pn51Xnbd+eUM2fUnW38\neVv2ziiAOSUVV+uzq/UXcO4+i6KI9PPXEKrxRI+2gXwJgpPp3fsBrFixDFevZiIsrBVSU7djwIC4\nKts+/HAcUlO3YezY8Th16iTKysoQEXF73ryBA+Nx7NgRJCY+hps3Dfjjj9+tg4x/zqkNG9YiJqY7\nQkNrnheLiKg2vxiM+PWmEfGhAdB6utdpHclfqGGxWHD+/HmsXbsWJpMJ48ePR4sWLZCUlFTnbeTl\nGSEIYoWfCYIAs1mwdbn3xGKpXFNubg6mTZta5e3k7u6emD49Ba+8MgWCIKBDhwhMmfIKACA7W1dh\nveeem4T58+dg1640uLu7Y9as1yEIt49DcvIkLF78OrZs2fx/k8hPQmhoa5jNArZv34Zvv90NQRAQ\nGRmFmTNnV3ncBEGQ9NFBV3x0kX2WnqW8EAW559BM+z/IzS2yyz4crc/2JJfLqrwYc69CQkKg0+lg\nsVigUChgsVig1+sREhJSqd2NGzfQtWtXAJUvSt3RokULdOnSBd999x3Cw8Otd5YDtwe0QkJC8Pvv\nv+P++++vc41355QzZ5TZLODmzTy89NLkRssogDklBVfrs6v1F3D+PmcaS3D1VgkSWwchN9dot5wi\n+6kpp9RqL0yfnoLp0/9hzampU6dVud7EiS9i/vw52L17ONzd3TF79nzI5bcvUj3//IuYP38etm37\nDDKZDM89NwmtW7cBAOzY8UWFnHrttcpz/hIR1Ud+WTm+uqJHmJcH+gXX/WYCmSiKYk0N8vLyEB8f\nj2PHjllPmnr16oW9e/dWuHNvwoQJeOyxxzB48GAAwPz589GiRQuMHz/e2mblypUoLi7GjBkzrD97\n7rnnMGTIEOtg3po1a5CVlVXlZOjV11h5cC87+wqCg6u+ut/UubnJG/2kUOrj6ez/uKwK+yy9W7of\nkH9jP0KiJkHpUfs8Bw3haH22J3ueND311FMYOXKkdW7Ybdu2YcOGDRXafPHFF9i5cyfWrFljnRt2\n48aNCAsLw8WLF9GuXTsAgMFgwJNPPonZs2ejb9++0Ol00GpvP8bz22+/YezYsfj6668rDPrV5u6c\nkvo71d6YU67B1frsav0FnL/PWy9l4+zNIszs1hbuCrnLDu652rlUfdki05z9eDr7d4Ut8BjVjscI\nEEQR6y5cR6axFC92boXmHv99H0VtGVXrnXsBAQGIiorC119/jcTERHz99deIioqqMLAHAIMHD8bW\nrVsxaNAg5OfnY9++fdi4cWOtxQ8bNgwHDx5EYmIizGYzjh49ivj4+FrXIyKyJ1EUYcw7BZVXqN0G\n9sh25s2bh5kzZ2L16tVo1qyZ9c3sycnJmDJlCrp06YLExEScOnUKgwYNAgBMmjQJYWG3H53ZsmUL\nfvjhB7i5uUEURfztb39D3759AQDLly/Hr7/+CrlcDqVSiWXLltVrYI+IiBxPUbkFvxiM6BnYDO4K\nx5omgYiIXNMxfQH+uFWCpNZBFQb26qJOj+Xe60lTeno6Xn75ZRiNRoiiiJ07d2LRokXo168fHnnk\nEZw5cwZDhw6FXC5H3759MXKk7d9ISURUH6bi6zCX5cI/aJjUpVAdtGvXDlu3bq308zVr1lj/rlAo\n8Prrr1e5fkpKSrXbvpN5RETkPP6TWwCLKKIXX6RBREQOILfUhN3XctHRR42egc3qvX6dBvfu9aQp\nNjYWhw4dqnKZXC7Ha6+9htdee60upRARNYqivJOQyZVQ+3WWuhQiIiKyIUEUcSynAG01nnWeqJyI\niMheygUBn13MhkImw/A22qH/xzcAACAASURBVAa94In3oBMR3UUQylF081eofaMgV/Af/URERM7k\n94Ji3Cwzozfv2iMiIomJoogdV/S4UVyGx8O18FE17L23HNwjIrpLSf45iEIZvPy7SV0KERER2dhR\nfT40SgU6+breyzOIiMixpOfewvHcQgxo4Y/Ie8glDu4REd3FmHcSCpUv3L2d961mRERErshQVo4L\nBcWIDfSBQl7/x56IiIhsJbfUhK8zc9CumScGtPCvfYUaNOx+P6q3kSMToFKpoFSqIAgWPP30OMTF\n1f5W4MOHD2H16rdhsVgQERGFlJS58PZWV2pnMORhwYI5yMrKgru7O6ZP/1907nwfAODMmdN4++23\nUF5eDrPZjJEjH0dSEl9aQlQVc1k+yowZ8Al+sEFzHRA1RbbMKA8Pj0rtmFFE5Ch+0hdABuD+BkxW\nTtKRNqd+wT//+SZziohsyiKK2HZJB4VMhpFtgyG/x3NPDu41ooULlyI8vD0uXDiHiRPHITa2F3x9\nfattX1xcjGXLFuHdd9cgLKwVlixZgM2bNyA5+blKbd9/fxWio2OwYsW7OHXqJBYsmI3Nm7+ATCbD\nW2+9geTk59GnTz/k5eXiiSeGo3//h+HvH2DP7hI1SUWGUwAAr4BoiSshaly2yqhnnkmu1JYZRUSO\noFwQkJ57C5G+XvBRKaUuh+pJqpxaunQxxo9nThGRbR24YUBmUSlGhwc3eJ69P+NjuRLo2DESarUa\nWVnXa2x39OgRREZGISysFQAgKWkE9u//tsq2Bw7ss15Bio7uBqVSiXPnzgIAZDKgqMgI4HbIqdVe\n8PDwtFV3iJyGKIowGk7B3bst3FTV/2ORyJkxo4jIWZ0xGFFstqB3EDO+KWv8nJIxp4jIpq4ZS/Hd\nDQNiAjSIDtDYZJsucefesaz/4Mesn+2y7QdCeqJXSI96rXP8eDpMJhNCQ1shNzcH06ZNxbp1myq1\n0+myodWGWD9rtcHQ63WV2hUU5EMUxQpXru60jYrqjJSUuZg58xW8//4qFBbewuzZC6BWV360l8jV\nlRkvw2LKh2/Iw1KXQi6EGcWMIqLGcUxfgOYeSoQ348BMfbh6Ts2aNQ+vvvoSc4qIbKJcELA1Ixsa\npRuGtQq02XZdYnDPUcyaNQMqlTu8vLywaNFSaDQaaDSaKsPIljZt2oAXXpiKv/xlIDIzL2Pq1BfQ\nsWMkgoOD7bpfoqbGmHcKMoU7PH0jpS6FqNExo4jImd0oKkVmUSkeCWt+z/MakTSkyqlPP/2EOUVE\nNrPnWh5ySsvxTMcW8HRT2Gy7LjG41yukR72vCNnDnXki6kqrDcaJE+nWzzpdNoKCtJXa+fjcvsqU\nn59vveJ0p21+fj4OHTqAuXMXAgBatWqD8PD2OHv2DAOJ6E8ESxlK8s/Cyz8acjnn4aHGw4xiRhGR\n/R3LKYBSLkP35nyRRn25ek4dPHgAc+YsAMCcIqJ7c6GgCEd0+egd5IMOPl423Tbn3HNgvXs/gN9+\nO4urVzMBAKmp2zFgQFyVbR9+OA6pqdsAAKdOnURZWRkiIqKg0WigVKpw8uRxAEBeXi7++OM82rRp\n2zidIGoiim/+ClE080UaRHXEjCKipqLEbMHJvEJE+2tsepcEOTZb5ZRKpWROEdE9KzZb8EWGDkEe\nKgwJa27z7bvEnXuOrKZ5ItRqL0yfnoLp0/8BQRDQoUMEpk6dVuV6Eye+iPnz52D37uFwd3fH7Nnz\nIZffHrudP/8NvPPOP2GxCBAEC5599jmEh7drvE4SNQFGw0m4eTSHSt1S6lKIHEZDMyonJwcvvTSZ\nGUVEDuFEXiHKBRG9gnykLoVsrDHOpRYuXMKcIqJ7IooivsjQwWi24O8dWkApt/19djJRFEWbb7WR\n5eUZIQgVu5GdfQXBwa0lqsi+3NzkMJuFRt2n1MczMFCDnJxCyfYvBfa58ZSX5iLrt9XwbRGHZtr/\nadR9u9LvWS6XISDAW+oyJHF3Tkn9nWpvzCnX4Gp9drX+As7RZ1EU8f/OXIGHQoHnO4XV2NZVc8rV\nzqXqyxaZ5uzH0xm+K+yNx6h2znyMjurz8dWVHAwODUD/EP8GbaO2jOJjuUTk8oryTgKQwcu/q9Sl\nEBERkQ1dKixBTmk579ojIiJJ5Jaa8M3VXHRopka/YD+77YeDe0Tk0kRRQJHhF3g26wCF0vWu1hMR\nETmzY/oCeCrk6OLPjCciosZlEURsvaSDQibDY221kNnxbe0c3CMil1Z66yIsZiO8ArpJXQoRERHZ\n0C2TGWdvGhEb6GOX+Y2IiIhq8u8sA64WlSKxdRB8VPZ95QVTjohcmtFwEnI3NTybdZC6FCIiIrKh\nn3MKIAK4P7CZ1KUQEZGLyTSW4LsbBnQP0CA6QGP3/XFwj4hclsVcjJKC8/Dy6wKZXCF1OURERGQj\nFkHEzzkF6OCjRoCHSupyiIjIhZSaLdhyKRs+KjcMaxXYKPvk4B4Ruaxiw2lAFPhILhERkZP5Ld+I\nW+UW9OaLNIiIqJF9nZmD/DIzRocHw8OtcW4i4eAeEbkso+EUlJ4hUHlqpS6FiIiIbOiovgC+Kjd0\n9PGSuhQiInIhv9404nheIR4K8UdrjWej7de+M/qR1ciRCVCpVFAqVRAEC55+ehzi4uJrXe/w4UNY\nvfptWCwWREREISVlLry91ZXaGQx5WLBgDrKysuDu7o7p0/8XnTvfBwA4c+Y0Vq5cjtLSEiiVKrz6\nagoiIiJRXl6O5OSnrdsoLS1FVtZ1pKXtRbNmvMpJzs1UnI3ykmz4hQ6WuhQiydkyozw8PCq1Y0YR\nUWPSl5hwqbAE8aEBkNvxzYTUeKTNqV+wYsU/mVNEVKsCUzm+yNChhdodA1r4N+q+ObjXiBYuXIrw\n8Pa4cOEcJk4ch9jYXvD19a22fXFxMZYtW4R3312DsLBWWLJkATZv3oDk5OcqtX3//VWIjo7BihXv\n4tSpk1iwYDY2b/4CADBr1nTMm7cI3bp1ty7bsOFzKJVKrFu3ybqNzz/fhPT0nxhG5BKMhpOATAG1\nXxepSyFyCLbKqGeeSa7UlhlFRI3pmL4ACpkMPZrzRRrORKqceu21VzF3LnOKiGomiCK2Z+hhFkU8\n0S4YCnnjXlxyicG9W0d+QMHhQ3bZtk/f/mj2P33qtU7HjpFQq9XIyrpeYyAdPXoEkZFRCAtrBQBI\nShqBhQvnVTm4d+DAPmzdmgYAiI7uBqVSiXPnziI4uAWMxkJ069bdukyv1+P8+XOIjIyqsI2dO9Pw\n7LOVw47I2YiCBcWG01D7REDh1ni3ShNVxdkyqqqTJmYUETUWk0XA8bxb6OLnDW+lS5zq2J2r51Rh\nIXOKiGr3oy4ff9wqRmLrIDSX4EVOnHNPAsePp8NkMiE0tBVyc3MwduyYKtvpdNnQakOsn7XaYOj1\nukrtCgryIYpihXC709bPzw8+Pr74/vvvANy+Nb24uAg6XVaFbZw7dxZ5ebno06e/DXpI5NhKbl2A\nYCnhizSIqsCMIqKm7JShEGUWAb34Ig2n1dg55evLnCKiml0zluKbq7mI8FHj/kBp7hp3ictZzf6n\nT72vCNnDrFkzoFK5w8vLC4sWLYVGo4FGo6lwO7c9LF78Flavfgdr165Bp05d0LZtOBSKim9s+frr\nrxAfPwRubi7xnwS5OGPeSSiUGnhowqUuhYgZxYwiIhsRRRFH9QUI8VShlXfledWoYVw9p5Ys+SdW\nrnybOUVEVTJZBHyekQ2N0g2PhwdDJtFcr/z2aUR35omoK602GCdOpFs/63TZCAqq/FZPH5/bV5ny\n8/OtV5z+3DYiIhJvv70aAFBeXo6EhEFo0+a/gxplZWXYt28PVq9eU/9OETUx5vJClN76A820/wOZ\njDcvE93BjCKipu5qUSmyisuQ1DpIspMrsh+pcioyMoo5RUTVSsvMQW5pOcZFtISnm6L2FeyEZ7YO\nrHfvB/Dbb2dx9WomACA1dTsGDIirsu3DD8chNXUbAODUqZMoKytDRMTteSDy8nKt7TZsWIuYmO4I\nDQ2z/uzgwQMICwurV1gSNVXFhl8AiPDy5yO5RPeCGUVEjuaovgDucjmiAzRSl0IOgDlFRPYkiiK+\nvZ6H/+TewoMhfmjXTC1pPRzck1hN80So1V6YPj0F06f/A6NHJ8FoNOLJJ5+qcr2JE1/EiRPH8cQT\nw7F8+RLMnj0fcvntX++OHV/gyScfw+jRSbhyJQOvvTanwn527foKjzzyqJ16SOQ4RFGEMe8k3L3C\noPQIkLocIofX0IzKyWFGEVHjMpabcdpgRExzDdwVPMVxFY1xLvXll9uZU0RUyVF9AQ7cMKCjjxpx\nLaU/t5SJoihKXcS9ysszQhAqdiM7+wqCg1tLVJF9ubnJYTYLjbpPqY9nYKAGOTmFku1fCuyz7ZUV\nXYXuwlr4t0qAd0CM3fZTH670e5bLZQgI8Ja6DEncnVNSf6faG3PKNbhan12tv0DT6vPBLAP2XMvD\n1PtaQevp3qBtuGpOudq5VH3ZItOc/Xg2pe8KqfAY1a4pHSNdSRlW/XoV7Zt54qkOLSBvhKkgasso\nXtYiIpdhzDsFmVwJtW8nqUshIiIiGxFEET/pC9BW49nggT0iIqK6sAgitl3SwV0hx4i22kYZ2KsL\nDu4RkUsQhHIU3zwDtW8nyBX8hz8REZGzuFBQjJsmM3oH+UhdChERObmD2QZcLy5DUutAeCsd5x21\nHNwjIpdQkv8bRMEEL/9oqUshIiIiGzqmz4dGqUAnX9d7pJaIiBrPidxb2H/dgK7+3rjP37Fe3sTB\nPSJyCca8k3BT+cHd23nnOyEiInI1hrJyXCgoRs9AHyjkjvFoFBEROZ+Lt4qxLUOHAA8lHm0dJHU5\nlXBwj4icnrnsJsqMl+EVEA2Zg8yJQERERPfuJ30BZAB6BjaTuhQiInJSxnIztlzMRnMPFSZ1agW1\nm0Lqkirh4B4ROT2j4RQA8JFcIiIiJ1IuCEjPvYUoPy/4qJRSl0NERE5IEEVsz9Ch1CLgyXbBcFc4\n5jCa48z+5+RGjkyASqWCUqmCIFjw9NPjEBcXX+t6hw8fwurVb8NisSAiIgopKXPh7a2u1G7Tpg1I\nS/sS165dxZIly9GnT79alwmCgNmzZ+DSpYtQqdzh5+eHV19NQcuWobbrOJHERFFEkeEUPDRt4abi\nRNtEVbFlRnl4eFRqx4wiIns4YzCi2GxBryBfqUshO5MypzZu/ASpqV8wp4hc1A/Z+ThfUIyEVoEI\nVjvuixkdc8jRSS1cuBTr12/G7NnzsXjxfOTn59fYvri4GMuWLcLSpSuwZUsq1Go1Nm/eUGXbmJju\neOutdxAdHVOvZUOGDMPGjduwfv1m9Ov3IJYtW9SwzhE5qDLjZVhMBfDyr/zfPxH9FzOKiJqaY/oC\nNPdQop3GU+pSqBFIl1M9mFNELuqasRR7rueik6+Xw7+RnYN7EujYMRJqtRpZWddrbHf06BFERkYh\nLKwVACApaQT27/+2yrZRUZ2rvUpU3TK5XI6+fR+EXH77P4POnbsiOzurPl0hcnjGvJOQKdzh6Rsh\ndSlETQIzioiaghtFpcgsKkWvQB/Op+tiGjunOnViThG5IrMgYFuGDho3NzzWVuvwWeMSj+WeP52N\nc79k22XbkV2DEdEluF7rHD+eDpPJhNDQVsjNzcG0aVOxbt2mSu10umxotSHWz1ptMPR63T3XXJ0v\nvvgcffv2t9v2iRqbYClFSf5v8AqIhlzOuXjIMTGj6oYZRUR/diynAEq5DN2b80Ua9sacqhvmFJFz\n+fcNA/SlJozt2MIhX6BxN5cY3HMUs2bNgErlDi8vLyxatBQajQYajabKMGpsGzeux+XLGXjnnfel\nLoXIZopv/gpRNMPLv5vUpRA5PGYUETUVJWYLTuYVItpfA88mcMJFtsGcIqLGcr2oFIeybqJH82bo\n6OMldTl14hKDexFd6n9FyB4WLlyK8PD2dW6v1QbjxIl062edLhtBQVqb17Vt22f49ts9eOed96qc\nYJaoqTLmnYTSIxAqdQupSyGqFjOqZswoIrrbibxClAsiejn4/EfOgjlVM+YUkXMxCyK2ZejgrVRg\naFhzqcupM86558B6934Av/12FlevZgIAUlO3Y8CAOJvuIzV1O7766kusWPEumjXjP5DIeZSX5sBU\nfB1e/tEOPz8CUVPEjCIiKYiiiKP6fIR5eaClFwdSqHrMKSJqiANZBuhKTEhqo21Sd4dzcE9iubk5\nGDt2TJXL1GovTJ+egunT/4HRo5NgNBrx5JNPVbnepk2fYPjwofj119NYvHgehg8fiqIiY43LiouL\n8M9/LkFJSQleemkSxo4dg+Tkp+3faaJGYMw7BUAGL/+uUpdC1GQ1NKNycphRRGQflwpLkFta7vBv\nLaTG0RjnUp9+up45ReQibhSV4mCWATEBGkT6No3Hce+QiaIoSl3EvcrLM0IQKnYjO/sKgoNbS1SR\nfbm5yWE2C426T6mPZ2CgBjk5hZLtXwrsc8OJooDrZ/4f3L1aIDD8CRtUZj+u9HuWy2UICPCWugxJ\n3J1TUn+n2htzyjW4Wp9drb+AY/Z54x9ZyCgsxozotlDKbXufgqvmlKudS9WXLTLN2Y+nI35XOBoe\no9pJfYzMgoj3zmbCaLZg6n2tHe4lGrVlFO/cIyKnU3rrDwhmI1+kQURE5EQKTGb8dtOI2OY+Nh/Y\nIyIi13Ywy4CsEhOSWgc53MBeXTAVicjpGA2nIHdTw9Ong9SlEBERkY38nFMAEcD9gXwkl4iIbCer\nuAwHsgyI9tcgyq9p3sHNwT0icioWczFKCs7Dy68LZLKmd8WFiIiIKrMIIn7OKUBHHzX8PZRSl0NE\nRE7CLAjYcjEbaoUCCa0DpS6nwTi4R0ROpchwGhAFeAXwkVwiIiJncTbfiMJyC3oF+UpdChEROZED\nN25CX2rCiLbaJvk47h0c3CMip1JkOAmVZwhUnlqpSyEiIiIbOaYvgJ/KDR191FKXQkRETuLPb8eN\naGJvx70bB/eIyGmYirNQXqLjXXtERERORF9iwqXCEtwf5AO5TCZ1OURE5ATMgojtGTp4KRV4pFXT\nfRz3Dg7uEZHTMBpOATIF1H73SV0KERER2cgxfQEUMhl6NG8mdSlEROQkDmXffjtuYhN9O+7d3KQu\nwFWMHJkAlUoFpVIFQbDg6afHIS4uvtb1Dh8+hNWr34bFYkFERBRSUubC27vy4wibNm1AWtqXuHbt\nKpYsWY4+ffrVadmZM6excuVylJaWQKlU4dVXUxAREWmbThM1IlEwo9hwGmqfSCjcPKUuh6hJsWVG\neXh4VGrHjCKihjJZBBzPu4Uuft7wVvLUxVVJmVMbN36C1NQvmFNETiS7uAwHbhjQ1d8bnZro23Hv\nxjv3GtHChUuxfv1mzJ49H4sXz0d+fn6N7YuLi7Fs2SIsXboCW7akQq1WY/PmDVW2jYnpjrfeegfR\n0TF1XiaKImbNmo7nn5+M9es/w+TJL2PBgtkQRbHhnSSSQHH+OeRkbIVgKYFXQLTU5RA1ScwoInJE\npwyFKLMI6BXkI3UpJDHpcqoHc4rIiVjE24/jeigUSGgVJHU5NuMSl78yzv6EjDNH7bLttvf1RttO\n99drnY4dI6FWq5GVdR2+vtW/8evo0SOIjIxCWFgrAEBS0ggsXDgPycnPVWobFdW52u1Utyw/Px9G\nYyG6desOAIiO7ga9Xo/z588hMjKq7h0ikpAoWmC4uhOiUA537zbw0IRLXRJRvThbRj3zTHKltswo\nImoIURRxVF+AEE8VWnlXvtuKGoer51SnTp1hNguVfs6cImqaDmffxPXiMjzZLhheyqb/OO4dvHNP\nAsePp8NkMiE0tBVyc3MwduyYKtvpdNnQakOsn7XaYOj1OpvV4efnBx8fX3z//XcAbt+2XlxcBJ0u\ny2b7ILK3koI/IJiLENBmOLQd/g6ZjF9rRPeCGUVEjuJqUSmyisvQK8gXMr5Ig/4Pc4qIGkpfYsL+\n6wZ09vPCfU7yOO4dLnHnXttO99f7ipA9zJo1AyqVO7y8vLBo0VJoNBpoNBqsW7dJspoWL34Lq1e/\ng7Vr16BTpy5o2zYcCoXzjF6T8ysynITczQuezTpIXQpRgzCjqseMInJtR/UFcFfIER2gkboUl8ac\nqh5ziqjpEEQRX2TooJTL8GjrIKe7aFSnwb2MjAzMnDkT+fn58PX1xdKlS9GmTZsKbSwWCxYuXIjv\nv/8eMpkMEyZMwKhRowAAhw8fxvLly3HhwgU89dRTmDFjRqV9XLp0CcOHD8eYMWOqXO4MFi5civDw\n9nVur9UG48SJdOtnnS4bQUFam9YUERGJt99eDQAoLy9HQsIgtGnDxxqpabCUF6Gk4Hdognrxjj2i\ne8SMIiJHYiw347TBiPsDm8FdwYwn5hQR3ZsjunxkFpXi8XAtNE74gqY6JeXcuXMxZswY7NmzB2PG\njMGcOXMqtUlLS0NmZib27t2LLVu2YOXKlbh27RoAICwsDIsWLcK4ceOq3L7FYsHcuXMRFxd3D11x\nPr17P4DffjuLq1czAQCpqdsxYIBtj1FeXq717xs2rEVMTHeEhobZdB9E9lJ08xcAArz9u0ldCpHL\nYUYRkb0Yy81Y9WsmLKKIXkHVz6lGVBPmFBHdkVdqwrfX8xDp44Vof+e8G7zWwb28vDycPXsWw4YN\nAwAMGzYMZ8+ehcFgqNBu165dGDVqFORyOfz9/REXF4fdu3cDAFq3bo2oqCi4uVU9Ovrhhx/ioYce\nqnQ3oCuoaZ4ItdoL06enYPr0f2D06CQYjUY8+eRTVa63adMnGD58KH799TQWL56H4cOHoqjIWOuy\nHTu+wJNPPobRo5Nw5UoGXnut8sAtkSMSRRFFeaegUreE0jNQ6nKInFJDMyonhxlFRA33U04BbpVb\n0DvIB0GeKqnLkUxGRgZGjx6N+Ph4jB49GpcvX67UJi8vDxMmTEBCQgKGDBmCefPmwWw2N36xEmmM\nc6lPP13PnCJqwgRRxPbLeihkMiS2cb7Hce+QibW8q/vMmTOYMWMGdu7caf3Z0KFD8eabb6Jz5/++\nVSghIQGLFi1C165dAQBr1qyBTqfDrFmzrG1WrlyJ4uLiCo/dnjt3DgsWLMAnn3yC1atXV1peF3l5\nRghCxW5kZ19BcHDrem2nqXBzk1f5xiZ7kvp4BgZqkJNTKNn+pcA+16ys+AZ05z+CX9gj0DTvYefK\n7MeVfs9yuQwBAc41cW1d3Z1TUn+n2htzyjW4Wp9drb+ANH22iCLePHUZWk8Vnolo2aj7drSc+vvf\n/44RI0YgMTERO3bswPbt2/HJJ59UaLNo0SK4ublhxowZKC8vx5gxY/DMM89g6NChdd6Pq51L1Zct\nMs3Zj6crfj/WF49R7ex1jI7o8vF1Zg5GtAlCj0Afm2+/sdSWUZI+aFxeXo7Zs2fjjTfeuKeJR6vq\noF4vh5ub887P0dh9k8vlCAyU9vZVqfcvBfa5epm//QqZ3A2t2/eCQulp56rsyxV/z0RERFU5l1+E\nW+VmJLZ27bvy7zw9tXbtWgC3n55asGABDAYD/P39re1kMhmKioogCAJMJhPKy8uh1dp2XjkioqZK\nV1KG3VdzEeGjRvfmzaQux65qHdwLCQmBTqeDxWKBQqGAxWKBXq9HSEhIpXY3btyw3rmXlZWFFi1a\n1LjtnJwcZGZmYsKECQCAW7duQRRFGI1GLFiwoM6dqOpqkyAIjX7XQGOR4o4IQRAkvdLgilc62Ofq\niYIZuTdOwNMnEoZ8M4Cme5xc6ffsaHdEEBGR4zmmz4evyg0Rvl5SlyKprKwsaLVa6w0QCoUCQUFB\nyMrKqjC498ILL2Dy5Mno27cvSkpK8Ne//hU9etTviQZXvFGivu71WDjCjRL25uz9swUeo9rZ8hiZ\nBRHvH7kGD6UCE2LboZm70mbbdkS1Du4FBAQgKioKX3/9NRITE/H1118jKiqqQqgAwODBg7F161YM\nGjQI+fn52LdvHzZu3Fjjtlu0aIFjx45ZP1f12C4R0d2KC85BtJTyRRpEREROJKfEhD9ulWBQywDI\nnXROJFvbvXs3IiIisH79ehQVFSE5ORm7d+/G4MGD67wNV7tRor5scWOF1DdK2JsrXaxuKB6j2tn6\nGH17PQ+Zt0rw1/YhKLtVihyU2mzbUqjtRok6XYKYN28ePv30U8THx+PTTz/F66+/DgBITk7G6dOn\nAQCJiYkIDQ3FoEGD8Pjjj2PSpEkIC7v9pqD09HT0798fa9euxWeffYb+/fvj+++/v9e+EZGLKso7\nCYXSB+6atlKXQkRERDbyU04BFDKgR6BzPzpVF39+egpAtU9Pffrpp3j00Uchl8uh0WgwYMCACjdP\nEBG5osuFJfjuhgExARp09nONJ4fqNOdeu3btsHXr1ko/X7NmjfXvCoXCOuh3t9jYWBw6dKjW/Uye\nPLku5RCRCzObClBaeAnNgvs57ZuOiIiIXI3JIuA/ubfQ2c8bGqWk04I7hLo+PRUaGopDhw6ha9eu\nMJlM+PHHHzFw4ECJqiYikl6ZRcDWjGz4uSvxaOsgqctpNJxIgYialCLDLwDAR3LJKiMjA6NHj0Z8\nfDxGjx6Ny5cvV2pjsVjw+uuvIy4uDgMHDqxwwWr79u1ISEhAYmIiEhISKryJsKb1iIjIdn4xFKLU\nIqB3kK/UpTiMujw9lZKSgv/85z9ISEhAUlIS2rRpg8cff1zKsomIJLXrag7yy8wY2VYLd4XrDHnx\nslgjGTkyASqVCkqlCoJgwdNPj0NcXHyt6x0+fAirV78Ni8WCiIgopKTMhbe3ulK7TZs2IC3tS1y7\ndhVLlixHnz79ANye32H27Bm4dOkiVCp3+Pn54dVXU9CyZSgAYNWq/4eDB/+NrKwb+OSTzxAe3t62\nHSeyIVEUUWQ4BXfv1nBz95O6HHIQc+fOxZgxY5CYmIgdO3Zgzpw5FQboACAtLQ2ZmZnYu3cv8vPz\nkZSUhAceeAChoaGIYuhjNgAAIABJREFUj4/HY489BplMBqPRiISEBNx///2IjIyscT1nYsuM8vDw\nqNSOGUVENRFFEUf1BQj2VKG1d+XvEFdVl6enWrVqZX2jrjOTMqdmzpyOixf/YE4RNQFnbxrxc84t\n9A/2QxuNp9TlNCrXGcZ0AAsXLsX69Zsxe/Z8LF48H/n5+TW2Ly4uxrJli7B06Qps2ZIKtVqNzZs3\nVNk2JqY73nrrHURHx1RaNmTIMGzcuA3r129Gv34PYtmyRdZl/fo9hFWrPkRwcEil9YgcTVlRJsxl\nBnjxrj36P3l5eTh79iyGDRsGABg2bBjOnj0Lg8FQod2uXbswatQoyOVy+Pv7Iy4uDrt37wYAeHt7\nWx/xLi0tRXl5ufVzTes5G2YUEUnlWlEZbhSXoVeQD6fcoGpJlVNDhyYwp4iagGKzBamX9QhRuyOu\nZYDU5TQ63rkngY4dI6FWq5GVdR2+vtU/enD06BFERkYhLKwVACApaQQWLpyH5OTnKrWNiupc5Tbk\ncjn69n3Q+rlz5674/PPN1s/R0RwkoaajKO8UZHIV1L5RUpdCDiIrKwtarRYKhQLA7flfg4KCkJWV\nVWFeoqysLLRo0cL6OSQkBNnZ2dbP+/fvx/Lly5GZmYlXXnkFERERdVqvru5+s5VeL4ebm2NdX1Mo\nbtfUqVMneHmpoddnoXlz/2rb//zzj4iKikLbtm0AACNGjML8+XOsGfXn/nXp0gUAIJPJoFDI/rRM\njoceetjaLjo6Glu3brYu79Gje6X6qiOXyxEYqKlHj21P6v1LwdX67Gr9BRqnz2k38uDhJkdcRAt4\nuCnsvj9q2u71XOqZZ5Irta3pXKp//wetb8vluRSR4/rqih7FFgueadsSbnLXu1DkEoN7posGlP1u\nqL1hA7h38IeqXfUnP1U5fjwdJpMJoaGtkJubg2nTpmLduk2V2ul02dBq/3sVSKsNhl6v+//s3Xlg\nVOW9P/73rMmsSWYyM1lZAgIRCFgX4CpdlK0SDCKUq9WrtaW9Xq7e4q1K/bYIrbSF32298qt4v5fW\nWlxajShIRKp0E9qCGwlgBCskbElmJjOZSWbLzJxzvn9Q08YEkskyZ5b36y+SOWfm/UzCfHKe8yzD\nyvvyyy/iuus+O6znIJKDKEQR8n0AfcE0KFVaueNQhrnhhhtwww03oKWlBatXr8ZnP/tZVFRUjNjz\nezwBiKLU87Uoij0XCqlSowThQqb3338X3d1RFBeXoa3NedEa1dLSCru9uKcdhYV2OJ1OxOMi1Gpl\nz/f/kSRJEASp38cA4MUXX8C1136238c/yXcxoijC7e4aVFtHg81mkvX15ZBtbc629gLJaXMwJuCd\nlg5cZTOjqyMEOd9hpVLR52YMpU6d+gSvpYjo0z7oCOCIN4AbSiwo1ufIHUcWWdG5lyq+852HoNXm\nwGAwYOPGTTCZTDCZTP0Wo9Hw3HO/RHNzE7Zs+Z+kvB7RSAr5GiGJMRgtM+SOQimkuLgYTqcTgiBA\npVJBEAS4XC4UFxf3Oa6lpQVVVVUA+o7I+0RJSQmmT5+OP/zhD6ioqBj0eZmANYqI5PBeeyfikoRZ\n9jy5o1CKY50iov4EYxem45boc/D54sRuFmSSrOjc005I/I7QaHj00U0JLbLqcBTh8OF3e752Ottg\ntzuG9NovvfRrvPnmb7Bly5P9LiJLlOqCnnqoc6zQGsrljkIpxGq1orKyEnV1daipqUFdXR0qKyt7\nTckFgEWLFqG2thYLFiyAz+fDvn378NxzzwEATp48iQkTJgAAvF4vDh06hAULFgx43khhjWKNIspW\noiThbbcf4006OHTZOdIiHbBOsU4RpbLdZ1yICALuHl8KVRZOx/1Eai34Q73Mnj0HH37YiLNnzwAA\ndu7cgeuvn5fw8+zcuQOvvvoKHnvsCZjNvCtK6SfW7UV38AwMlhlcaJv6WL9+PZ599lksXLgQzz77\nLDZs2AAAWLVqFY4ePQoAqKmpQVlZGRYsWIAvfelLWL16NcrLL3QUv/DCC1i8eDFqampw11134fbb\nb8d111034HnZjjWKiIbr484QvN0xjtqjUTFSdeqVV15inSJKUQ2eLhzxBvCFEmvWTsf9hEKSJGng\nw1Lbp9cyAoC2ttMoKhorU6K+li9fgs2bH+tzt+lS60QAwP79f8DWrVsgiiIuu2wy/s//WQ+TydBn\nHaTnn9+O2tpfw+frgF6vh1abg2effREKhQILF34eRUXFMBgurCGi0WiwbdsvAQD//d//H/74x9/D\n6/UgLy8fZnMenn32xT455H4/uc5NdrhYm30tv0On808omfZNqDWZtZh5Nv2cs3kto0/XKbk/Uz9t\nJGuUTqdDR4cHa9bcm7QaBcj/nmbT/+VPZFubs629wOi3eftfW3A+GMEDVeNTYvHzbK1T2XYtpdPp\n+pyX6ddSoy0bPx8TxfdoYIm+R53ROB4/dhqFuVp8fUpZxo/aG6hGsXMvDV1sofLRJPf7mY0fhmzz\nBZIkouWDLdDo7LBPuE2mZKMnm37O2XrRBKR+595IY53KDtnW5mxrLzC6be7ojuG/jjTj8yUWzC+1\njsprJCpb61S2XUslaiRqWqa/n9n4+ZgovkcDS+Q9kiQJ2//aglNdYdw7dQwKczN/w8WBahSn5RJR\nSot0NUGIdcJomSl3FCIiIhohb7v9AICrC80yJyEionTzvqcLJ/whLCi1ZkXH3mCwc4+IUlrQUw+l\nSgdd3iS5oxAREdEIiIsi3nV3ojLfgPwcjdxxiIgojfi6Y6g748Y4kw5zHPlyx0kZ7NwjopQlxsMI\n+Y9DXzANCmVWbO5NRESU8Y51BBCMC9xIg4iIEiJKEmqbnJAkCcvHOaDkZos92LlHRCkr2HEMkAQY\nrZySS0RElCkOufyw5mgwwayXOwoREaWRvzh9aOoKo3qMDZZcjvz+R+zcI6KUFfQ2QJPrgEZXJHcU\nIiIiGgGtoW6cDkQwy57HERdERDRo7nAUvznnwZQ8A67keq19sHOPiFJSNOxCNNQCg3UmFPzjn4iI\nKCMccvmgUSp4YUZERIMmShJeanJCo1Rg6Tg7rw/7wc49IkpJQU89oFDCYJkudxQiIiIaAZG4gHpP\nF6osJujUKrnjEBFRmvhDawfOBiO4aawdZi3XYu8PO/eSZPnyJbjttltw55234o47voR9+34zqPMO\nHHgLt912C1auXIp1676NSCTS73HPP/8Mbr11GebOvRp/+tP+fo95/fU6XHfdVf0+/tRT/4vrrrsK\np059PPhGEY0SSRIQ7DgCnXkSVGqux0M02lijiCgZDnu6EBUlzOZGGpQg1imi7HU+GMHvznsw3WJE\nlcUod5yUxc69JHr00U345S9/he9+93v4wQ++B5/Pd8njQ6EQNm/eiE2bHsMLL+yEXq/Hr371TL/H\nXnHFZ/Bf/7UFM2Zc0e/jLpcTu3a9jKlT+46COnHiOD744BiKiooTbxTRKAj7/woxHuJGGkRJxBpF\nRKNJkiQcdPlRZshBqSFX7jiUhliniLJPXBRR2+SEUaPC0rGcjnspWTGe8eTJj/DxxydG5bknTpyM\nCRMmJXTOpElToNfr0dp6Hvn5+Rc97uDBP2PKlEqUl48BACxdegsefXQ9Vq36Rp9jKyunXvI1N2/e\niHvvvR9PPrml1/ej0Sh+8pNNWL9+I+69t+/zEskh6K2HUm1Ernmi3FGIRl2m1aivfGVVn2NZo4io\nqSsMdySK5eMdckehBLFOsU4RyeW3571whaO487ISLucwAI7ck8H777+LaDSKsrIxaG934667buv3\nOKezDQ7H3+8AORxFcLmcCb/eK6+8hPHjJ2Dq1Gl9HvvZz/4HCxZ8EcXFJQk/L9FoEGIBhP1/hcEy\nHQoFP6KIko01iohGw0GXHzqVEtM5pYqGKdl1aseOWtYpIhmcDUTwVlsHriw0Y3K+Qe44KS8rRu5N\nmDAp4TtCo+E733kIWm0ODAYDNm7cBJPJBJPJhKeffn7UXrOl5Tx2796JJ5/8WZ/Hjh07ghMnPsQ9\n99w7aq9PlKig9ygAiVNyKWuwRrFGEWW6zmgcjb4ArnXkQ6Pkjbt0k+116tVXX8HWraxTRMkUiQv4\n9clWmLVqLC4vlDtOWsiKzr1U8eijm1BRMfhphg5HEQ4ffrfna6ezDXZ7YlMZjh07ivZ2N7785RUA\nAK/Xgx/96Pv4xjdWo6OjA83NTVix4iYAgNvtwv3334uHH34E11wzO6HXIRoJkiQh6K2HVl8KTa5N\n7jhEWYU1iohGyztuP0QJuMbGjTRo6OSqU2436xRRsr12th2+aByrppQhl9NxB4Wdeyls9uw5eOyx\nzTh79gzKy8dg584duP76eQk9x4IFi7BgwaKer//937+OW2+9A9deOxcAcMcdd/U8tnz5Emze/FhC\nRZNoJIU6zyEWccNSvljuKEQ0ANYoIhoMQZTwjtuPSXl6WHO1csehLDJSderGG29EPC4CYJ0iSoYT\nviDea+/E54sLMM6kkztO2uC4eJldap0Ivd6ABx98GA8++E2sXLkUgUAAt956R7/nPf/8dtx88434\n4IOj+MEP1uPmm29EMBhIShuIRorn/DtQKNTQF1x6UWMiSo6h1ii3mzWKiC740BdEZ0zALDtH7dHI\n47UUUWYJxwW80uyEQ6fF9SUWueOkFYUkSZLcIYbL4wlAFHs3o63tNIqKxsqUaHSp1cqeu0fJIvf7\nabOZ4HZ3yfb6csi2NotiDK0fPIYc02UoHHez3HGSJpt+zkqlAlZrdi6k/uk6Jfdn6mhjncoO2dbm\nbGsvMDJt/vmJc/BEYvhW1TgoFYoRSjY6srVOZdu1VKJGoqZl+vuZjZ+PieJ7NDCbzYSth/6KBk8X\n7rm8HKWGXLkjpZSBahRH7hFRSgj7TkCIR2C0zpA7ChEREY0AVziKk51hXGPLS/mOPSIikte7rR04\n7OnC50ss7NgbAq65R0QpIeithza3ADnG8XJHISIiomEKxQXUnmqDSgFcZTPLHYeIiFKYrzuGZxrP\nosyQg88XczruUHDkHhHJLh71I9J1CtaSK6HgnX0iIqK098Y5D86HujHDaoJRw/EERETUP0GU8OKp\nNgiShJUVRVAreT04FOzcIyLZBb0NAABrydUyJyEiIqLhiggC6j2duDzfgGXjHHLHISKiFPaHVi+a\nAxHcOrWcu6oPAzv3iEhWkiQh6GlAjnEccvQcgk1ERJTuDrd3ISpK+HyxhWvtERHRRZ0PRvD7Vi9m\nWky4tswqd5y0xs49IpJVd/AM4tEOGK0z5Y5CREREwyRJEg65/SjV56DMyAXRiYiof3FRRG2TE0a1\nCkvG2uSOk/a4AEaSLF++BFqtFhqNFqIo4M47v4p58xYOeN6BA29h69bHIQgCJk+uxMMPPwKjUd/n\nuOeffwa7d7+Cc+fO4kc/+gmuvXZuz2P//u9fh9PphMFgAACsWPHPWLz4pl65tNocAMA999yLWbPm\njESTiQYl6KmHQqmFLr9S7ihEWWska1Rubt+LedYoouzRHIjAFY7ilnF2uaNQBpGzTt1zzyq0tbWx\nThGNsD1n2+EKR3HnZSXQqVVyx0l77NxLokcf3YSKion46KPj+Nd//SquumoW8vPzL3p8KBTC5s0b\n8cQT21BePgY/+tH38atfPYNVq77R59grrvgMPve5L+CHP/xev8/1zW9+q1eR6i8XUbKJQjdCvkbo\nC6ZBqdTIHYcoq41UjfrKV1b1OZY1iih7HHT5kKtSYrrFJHcUyjCsU0SZo7EjgIMuP66x5WFyvkHu\nOBmB03JlMGnSFOj1erS2nr/kcQcP/hlTplSivHwMAGDp0lvw29++2e+xlZVTUVpaNuJZiUZTyNcI\nSYzBaOGUXKJUwRpFREPVFYvjg44Ariw0Q6viZQaNDtYpovQWjAl4pdmFYn0OlozhdNyRkhUj9wKe\nBgS99aPy3AbLTBitMxI65/3330U0GkVZ2Ri0t7vxrW/9B55++vk+xzmdbXA4inu+djiK4HI5h5Rz\n69bH8X//708xceIk3HPPvbDZ/j5VYsOG7wKQMH36THzjG6thMvFOKyVH0FMPdY4VWgP/mKLsxRrF\nGkWUKd5xd0KUgFn2PLmj0AhinWKdIhpJu8+4EBEE3D2+FColN10aKVnRuZcqvvOdh6DV5sBgMGDj\nxk0wmUwwmUz9FqOR9N3vfg8ORxEEQcAzz/wC69Z9G08++XMAwBNPbIPDUYRoNIotW36Mxx7bjHXr\nvj+qeYgAIBbxoDt4FvklN0DBnfSIZMcaRUTDIUgS3nH5MdGsR2GuVu44lIHkqlPr138fVquddYpo\nBBzzduGIN4B5pVYU63PkjpNRsqJzz2idkfAdodGQ6HoMDkcRDh9+t+drp7MNdrsj4dd1OIoAACqV\nCl/60q34xS+2QRRFKJXKnse0Wi1uvnkF1q69P+HnJxqKoLcBgAJ6S5XcUYhkxRrFGkWUCU74gvDH\n4tzxMAOxThUhHhdZp4iGKRCLY9dpN0r0OfhcUYHccTIOF8NIYbNnz8GHHzbi7NkzAICdO3fg+uvn\nJfQc8XgcXq+n5+s33/wNKiomQKlUIhwOIxAIAAAkScK+fb/BxImTRq4BRBchSSKC3gbkmidAreHU\nBaJ0xBpFRP/ooMuPPI2aC6NTyhipOuXxsE4RDZckSdjR5EREELB8vIPTcUdBVozcS2WXWidCrzfg\nwQcfxoMPfhOiKOKyyybjP/7jW/2e9/zz21Fb+2v4fB34wQ/WQ6vNwbPPvgilUoUHHvgm4vEYJElC\nYaEdGzb8AADg9Xrwne88CFEUIQgixo0bj//8z7XJazxlrUjXKQixLhSULpQ7ChFdwlBrlNvtxpo1\n97JGEWWJ9kgUH3eGMK/UChWX2qAkSsa11H/+532IxViniIbjbbcfJ/wh3FheiCJOxx0VCkmSJLlD\nDJfHE4Ao9m5GW9tpFBWNlSnR6FKrlYjHxaS+ptzvp81mgtvdJdvryyGT29ze9BIiXU0onbYGCuXf\n7zFkcpsvJpvarFQqYLUa5Y4hi0/XKbk/U0cb61R2yLY2Z1t7gcG3+bUzbvzF5cNDM8bDpEnfsQPZ\nWqey7VoqUSNR0zL9/czGz8dEZfN75O2OYcux0xhjzMVXJpVedL31bH6PBmOgGsVpuUSUVEI8jJD/\nBPSW6b069oiIiCj9RAUR77V3YmqBMa079oiIaOSJkoSXm5xQQIFl4xzcSHEUsXOPiJIq1HEMkAQY\nLfIvzExERETDc8TbhYggYrY9X+4oRESUYt52+3GqK4wbxxQiP0cjd5yMxs49IkqqoKceGl0RtPpi\nuaMQERHRMB1y+WHXaTHOmCt3FCIiSiGeSBSvn23HZWY9rio0yx0n47Fzj4iSJhp2Ihpu5ag9IiKi\nDHAuEMH5UDdm2/M41YqIiHqIkoQXTzmhVCiwbLydNSIJ2LlHREkT9NQDCiX0lulyRyEiIqJhOuj2\nQatUYKbVJHcUIiJKIQfaOnA2GEHNWBvytJyOmwzs3COipJBEAcGOo9DlTYZKrZc7DhEREQ1DKC7g\niCeAK6xm5KpUcschIqIU4Qx3483zXkwtMGCGhTd/koWde0SUFOHOv0KMhzgll4iIKAO8196JuCRh\nlj1P7ihERJQiBEnCjiYnclQK3DSW03GTifvVJ8ny5Uug1Wqh0WghigLuvPOrmDdv4YDnHTjwFrZu\nfRyCIGDy5Eo8/PAjMBp7j3oSRRHf/e5DOHXqJLTaHBQUFOCBBx5GaWkZWltb8O1vf6vn2ECgC8Fg\nEK+//rtez/HUU/+Lp576X2zf/mtUVEwcmUYT/YOgpx4qtRG5Zv5+EaWakaxRubm9F9VnjSLKPKIk\n4ZDLj3HGXBTpc+SOQ1lAzjr18MPfgiRdOJZ1iujS9rd24FywG/88oQgmDbubkonvdhI9+ugmVFRM\nxEcfHce//utXcdVVs5Cfn3/R40OhEDZv3ognntiG8vIx+NGPvo9f/eoZrFr1jT7HfvGL1finf5oL\npVKJHTtewObNG/H440+iuLgETz/9fM9xjz/+YwhCvNe5J04cxwcfHENREXcvpdEhxAIId/4VJvsc\nKBQcMEyUikaqRn3lK6v6HMsaRZRZPu4Mwdsdw/xSq9xRKIvIVaeeeebXiMdFAKxTRJfSFurGb1u8\nmFZgRBWn4yZdVnTuvd/eiffaO0flua8sNOMzCW7rPGnSFOj1erS2nr9kQTp48M+YMqUS5eVjAABL\nl96CRx9d36dzT6lU4rrrPtfz9dSpVXjxxV/1eb5YLIY333wdP/7xT3u+F41G8ZOfbML69Rtx7719\nOw2JRkLQewSABKN1ptxRiFJOptWoT180sUYRZZ5DLj8MahWmFhjkjkJJwDp1AesU0cXFRBG/PtWG\nXJUSN421yR0nK3EIjQzef/9dRKNRlJWNQXu7G3fddVu/xzmdbXA4/n4HyOEogsvlHPD5X375RVx3\n3Wf7fP/AgT+isNCOyZOn9HzvZz/7HyxY8EUUF5cMoSVEA5MkCUFvA7SGMmhyC+WOQ0QDYI0iokvp\n6I7huC+Iq21mqJW8lKDkY50iSj37znvgCkexosIBI6fjyiIr3vXPDOGO0Gj4znceglabA4PBgI0b\nN8FkMsFkMvWakjRczz33SzQ3N2HLlv/p89hrr72KxYtv6vn62LEjOHHiQ9xzz70j9vpEnxYNtSAW\nccNSXi13FKKUxBp1AWsUUXp4x+0HAFxt40Ya2YJ16gLWKaL+neoM4UCbD9fY8jApjyO65ZIVnXup\n4pN1IgbL4SjC4cPv9nztdLbBbndc9PiXXvo13nzzN9iy5ck+C8W63S7U17+P7373ez3fO3z4fTQ3\nN2HFipt6jrn//nvx8MOP4JprZg86J9GlBL31UCjU0BdMlTsKEV0CaxQRDSQuinjH3Ykp+QYU5Gjk\njkNZhnWKKPWE4wJqTzlRkKPBF8s5S0tOHEufwmbPnoMPP2zE2bNnAAA7d+7A9dfP6/fYnTt34NVX\nX8Fjjz0Bs7nvndTXX6/DnDnXIS/v7+tS3HHHXdi1ay9eemk3XnppN2w2O37yk/+fxYhGjCjGEOw4\nBl1+JZQq7qZHlElYo4iyzwcdQQTjAmbZOWqPUh/rFNHoe+2MG12xOP65ogg5KnYvyWlQ735TUxNW\nrlyJhQsXYuXKlWhubu5zjCAI2LBhA+bNm4f58+ejtra257EDBw5g2bJlmDZtGjZt2tTrvCeeeAKL\nFy/GkiVLsGzZMuzfv394LUozl1onQq834MEHH8aDD34TK1cuRSAQwK233tHnvFAoiB//+EcIh8NY\ns2Y17rrrNqxadWev59qzp67XMHKiZAj7jkMSurmRBlGaGmqNcrtZo4gy0UGXD5YcDSaa9XJHIQLA\naykiOX3YEcD7ni58trgAZcbcgU+gUaWQJEka6KB/+Zd/wS233IKamhrs2rULO3bswPbt23sds3Pn\nTuzevRvbtm2Dz+fD0qVL8fzzz6OsrAynT59GKBTC3r17EY1G8dBDD/Wct3//flx11VXQ6XQ4fvw4\nbr/9dhw4cKDPUOhL8XgCEMXezWhrO42iorGDfo50olYre7ZjTxa530+bzQS3u0u215dDJrTZ9fEz\niHV3oOTye6FQKAY8PhPanKhsarNSqYDVapQ7hiw+Xafk/kwdbaxT2SHb2pxt7QV6t7kt1I0tH5zB\nF8sLMbeoQOZkoyNb61S2XUslaiRqWqa/n9n4+ZioTHuPQnEB/330NIwaFf7t8jFQKwe+1htIpr1H\nI22gGjXgyD2Px4PGxkZUV19YDL+6uhqNjY3wer29jtuzZw9WrFgBpVIJi8WCefPmYe/evQCAsWPH\norKyEmp13yX+5s6dC51OBwCYPHkyJEmCz+cbfAuJKCXFo35EuppgsFQNqmOPiIiIUtMnHXtqhQJX\npsDGCkREJB9JkvBKsxMhQcDyiqIR6dij4Ruwc6+1tRUOhwMqlQoAoFKpYLfb0dra2ue4kpK/bwFe\nXFyMtra2hMLs3LkTY8aMQVFRUULnEVHqCXobAABGC6fkEhERpbM/Oy/ceL95nB16tUrmNEREJKd6\nTxc+6AhifqkVJXquq54qUma33LfffhuPP/44nnrqqYTP7W9oosulhEqlyNgRQ2p18harlCQJSqUS\nNpspaa/ZH7lfXw7p2mZJEtF2/AhMlokoLitP6Nx0bfNwZGOb6cJna6bWqGQbxAojRDRE4biABm8X\nrraZcQVH7WUV1qmRwRpFmaQzGsfuM26MMeZm7BIN6WrAzr3i4mI4nU4IggCVSgVBEOByuVBcXNzn\nuJaWFlRVVQHoO5LvUg4fPowHHngAW7duRUVFRcKN6G+dCKVSDb/fB4PBnHFFKZlrGUmShGCwE0ql\nWtb579k4/z6d2xzpakY07IXJ/tmE2pDObR6qbGpztq5l1B+1WotgsDMja1SyfVKn1Gqt3FGIMtJ7\n7Z2IiRJm2fMHPpgyBuvUyGCNokzyyXRcQZKwfLwDSn42pJQBO/esVisqKytRV1eHmpoa1NXVobKy\nEhaLpddxixYtQm1tLRYsWACfz4d9+/bhueeeGzDAkSNHsGbNGmzZsgVTp04deks+paDAho4ONwKB\nzFu/T6lUQhSTt1C5Wq1FQYEtaa9H6S/orYdCmQNdfqXcUYhSUibXKIB1iihTiJKEQy4/xhhzOfUq\ny2R6nUrEcGsaaxRlivfbO3HCH8Li8kIU5rLDOtUMalru+vXrsXbtWmzduhVmsxmbNm0CAKxatQr3\n3Xcfpk+fjpqaGjQ0NGDBggUAgNWrV6O8/MJ0vHfffRf3338/AoEAJEnCa6+9ho0bN2Lu3LnYsGED\nIpEI1q1b1/N6mzdvxuTJk4fVMJVKjcLC4oEPTEPZNNKH0o8odCPk+xD6gulQKjVyxyFKSZlcowDW\nKaJMcby9C57uGG4otQx8MGWUTK9TiWBNIwK8kRjqzrZjnDEXcxwcyZ2KBtW5N2HCBNTW1vb5/rZt\n23r+rVKpsGHwZH1cAAAgAElEQVTDhn7Pv+qqq/DWW2/1+9iOHTsGE4GI0kTI1whJjMFonSF3FCIi\nIhqG359xQ69WYVoBl1QgIspWoiShtqkNCgDLK4o4HTdFJW9XBiLKCkFPPdQ5Vmj1ZXJHISIioiHy\ndcfQ4PTj6kIz1EpeMhARZav9bR04HYjgprE2WHI4MytVsVIT0YiJRTzoDp6F0TqTiy8TERGlKUmS\n8MfWDgDANfY8mdMQEZFczgUiePO8B9MKjJhhMckdhy6BnXtENGKC3noAChgsVXJHISIioiHa1+LF\nIbcf02xmFHCUBhFRVoqJImqbnDCq1bh5nJ2DN1IcO/eIaERIkoig9whyzROh0vCuDhERUTqKiSIO\nuXyw5Ghwx/QxcschIiKZ/Pa8F+5IFMvG26FTq+SOQwNg5x4RjYhI1ykIsS4YrTPljkJERERDdMwb\nQCguYuk4OwpytXLHISIiGZwJhLG/rQNX28yYlGeQOw4NAjv3iGhEBD31UKp00JknyR2FiIiIhuig\ny4/CXA0mmHRyRyEiIhlEBREvNTmRp1Xji+WFcsehQWLnHhENmxAPI+Q/Ab1lOhRKDtkmIiJKR+eD\nEZwNRjDLlse1lYiIstTrZ9vRHolh2XgHclW8tksX7NwjomELdRwFJAFGC6fkEhERpatDLj80SgU+\nU2iWOwoREcnghC+IQ24/rnPkY6JZL3ccSgA794ho2AKeBmh0RdDqi+SOQkREREMQjgto8HZhhsXE\nhdOJiLJQKC7g5WYnHDot5pdZ5Y5DCVLLHYCI0ls07EQs3IqCskVyR6Es1tTUhLVr18Ln8yE/Px+b\nNm3CuHHjeh0jCAIeffRR7N+/HwqFAl//+texYsUKAMATTzyBPXv2QKlUQqPRYM2aNZg7dy4AYO3a\ntfjzn/+MgoICAMCiRYtwzz33JLV9RESj7bCnCzFRwix7ntxRiIgoySRJwstNToTiAu6cVAqNkuPA\n0g0794hoWIKeekChgr5gmtxRKIs98sgjuO2221BTU4Ndu3Zh3bp12L59e69jdu/ejTNnzuCNN96A\nz+fD0qVLMWfOHJSVlaGqqgp33303dDodjh8/jttvvx0HDhxAbm4uAODrX/86br/9djmaRkQ06iRJ\nwkGXD+WGXJQacuWOQ0RESXbY04VGXxCLygpRos+ROw4NAbtjiWjIJFFAsOModHmToFJzTQaSh8fj\nQWNjI6qrqwEA1dXVaGxshNfr7XXcnj17sGLFCiiVSlgsFsybNw979+4FAMydOxc63YWdISdPngxJ\nkuDz+ZLbECIimZzqCqM9EsNsjtojIso6/mgMdWfcGGvMxXVF+XLHoSFi5x4RDVm48yOI8RA30iBZ\ntba2wuFwQPW33bxUKhXsdjtaW1v7HFdSUtLzdXFxMdra2vo8386dOzFmzBgUFf19Dclf/OIXWLJk\nCf7t3/4NJ0+eHKWWEBHJ46DLD71aiWkWo9xRiIgoiS5Mx3VBkCQsH++Akjulpy1OyyWiIQt46qFS\nG5FrniB3FKIR8fbbb+Pxxx/HU0891fO9NWvWwGazQalUYufOnfja176Gffv29XQmDobVmn0XzDab\nSe4IScc2Z75MbG9HJIoPfQHMH29HiaPvyL1MbDMREV3wF5cff+0M4aaxNlhztXLHoWFg5x4RDYkQ\nCyDS+THM9jlQKDgImORTXFwMp9MJQRCgUqkgCAJcLheKi4v7HNfS0oKqqioAfUfyHT58GA888AC2\nbt2KioqKnu87HI6efy9duhQ//OEP0dbWhtLS0kFn9HgCEEVpqE1MOzabCW53l9wxkoptznyZ2t59\n5z2QJGCaQdenfZna5otRKhVZeTOGiLKTKxzF3rPtmJynxywbl2VId7wiJ6IhCXqPAJBgsHJKLsnL\narWisrISdXV1AIC6ujpUVlbCYrH0Om7RokWora2FKIrwer3Yt28fFi5cCAA4cuQI1qxZgy1btmDq\n1Km9znM6nT3/3r9/P5RKZa8OPyKidCWIEt5x+3FZnp4jNoiIsoggSXipqQ1alQLLxjug4HTctMeR\ne0SUMEmSEPDWQ2sogya3UO44RFi/fj3Wrl2LrVu3wmw2Y9OmTQCAVatW4b777sP06dNRU1ODhoYG\nLFiwAACwevVqlJeXAwA2bNiASCSCdevW9Tzn5s2bMXnyZDz00EPweDxQKBQwGo148sknoVazfBJR\n+mv0BdAVE3AzN9IgIsoqvzvvxblgN26dUASThn/XZgL+FIkoYdHQecQj7bCUV8sdhQgAMGHCBNTW\n1vb5/rZt23r+rVKpsGHDhn7P37Fjx0Wf++mnnx52PiKiVHTI5Ue+Vo1JeQa5oxARUZKc7Azh961e\nXGE1YbqF66pmCk7LJaKEBT0NUCjU0BdMHfhgIiIiSjmucBSnusKYZc/j7ohERFkiEhfwUpMT1hwN\nasba5Y5DI4ide0SUEFGMIdhxDLr8y6FU5cgdh4iIiIbgkMsHlUKBKwvNckchIqIkkCQJO0+70BWN\n40sVRdCq2B2USfjTJKKEhH3HIYndMFpnyB2FiIiIhqBbEPG+pwvTC4wwcq0lIqKscMQbwBFvANeX\nWlBuzJU7Do0wdu4RUUICnnqotPnIMY6TOwoRERENQYOnC92CiFncSIOIKCt0RuN49bQL5YZcfK7Y\nInccGgXs3COiQYtHfegONMFomcHt0omIiNKQJEk46PKhWKfFGI7cICLKeKIk4eVmJ+KShBUVDqh4\nHZeR2LlHRIMW9DQAAAyckktERJSWzgQiaAtHMcuezxt1RERZ4C9OHz7yh7CorBCFuVq549AoYece\nEQ2KJEkIeBuQYxwPtTZf7jhEREQ0BIdcfuSolJhhNckdhYiIRpkrHMVvznkwOU+P2VyKIaOxc4+I\nBqU7cBpC1AejdabcUYiIiGgIArE4jnYE8BmrCTncJZGIKKMJkoSXmtqgUSpw8zgHR2tnOFZ1IhqU\ngKceCmUOdPlT5I5CREREQ/BeeycEScIsO0fgExFlut+d9+JcsBtLx9lh1nJn9EzHzj0iGpAodCPs\na4ShYCqUSo3ccYiIiChBoiThkMuPCpMOdh3XXCIiymRnAxH8odWLz1hNmG7hMgzZgJ17RDSgUMcH\nkKQ4DJySS0RElJY+8gfhi8Yxi2suERFltJgo4qWmNpi1alSPsckdh5KEnXtENKCAtx7qnEJo9aVy\nRyEiIqIhOOTyw6RR4fJ8o9xRiIhoFL15zgN3JIZl4+zIVavkjkNJws49IrqkWKQd0eA5GK0zuQgr\nERFRGvJGYvjIH8LVtjyolKzlRESZ6iN/EH9y+nCNLQ+X5RnkjkNJxM49IrqkoLcBgAIGS5XcUYiI\niGgI3nb7oQBwtY1TcomIMlU4LmBHkxOFuVp8sbxQ7jiUZOzcI6KLkiQRQe8R5JonQqXhNB4iIqJ0\nExNFvNvuR2WBAXncLZGIKGPVnXEjGBOwssKBHBW7erINf+JEdFGRzpMQYl0wciMNIiKitHTMG0Ao\nLmKWPV/uKERENEqO+wI47OnC50osKDHkyh2HZMDOPSK6qIC3Hkq1HjrzJLmjEBER0RAcdPlRmKvB\nBJNO7ihERDQKwnEBrzS7UKTT4gvFFrnjkEzYuUdE/RLiIYT9H8FQMB0KJXdZIiIiSjfngxGcDUYw\ny5bHTbGIiDLUa3+bjnvLeAfU3DQpa7Fzj4j6Feo4BkgCDJYZckchIiKiITjk8kOjVOAzhWa5oxAR\n0Sg47gvifU8XPldsQSmn42Y1du4RUb8CnnpodMXQ6ovkjkJEREQJCscFNHi7MMNigk7NEfhERJkm\nFBews9kJh06LL5QUyB2HZMbOPSLqIxpqQyzcBqOVo/aIiIjS0fvtnYiJEmbZ8+SOQkREI0ySJOxs\ndiEQ/2Q6Lrt2sh1/A4ioj6C3AVCooC+YLncUIiIiSpAkSTjk9qPckMtpWkREGeiIN4BjHQHML7Wi\njJ/zBHbuEdGnSKKAoPcI9HmToVJzZz0iIqJ0c7IrjPZIDLM5ao+IKON0RuN49bQL5YZcXFfE6bh0\nATv3iKiXcOdHEIUwN9IgIiJKQ4HYhYs+vVqJaRaj3HFoGJqamrBy5UosXLgQK1euRHNzc7/H7dmz\nB0uWLEF1dTWWLFmC9vb25AYloqSRJAmvNDsREyUsH++Aijuh09+o5Q5ARKkl4KmHSmNCrnmC3FGI\niIgoQS83u9AeieHzxQXQcA2mtPbII4/gtttuQ01NDXbt2oV169Zh+/btvY45evQofvrTn+KXv/wl\nbDYburq6oNVqZUpMRKPtkNuPE/4QFpcXwqbj/3X6O1Z8IuohxLoQ6fwYBksVFAp+PBAREaWTju4Y\nTviC+IzVhBtKrXLHoWHweDxobGxEdXU1AKC6uhqNjY3wer29jnv66adx9913w2azAQBMJhNycnKS\nnpeIRp8nEsXrZ9txmVmPf3Lkyx2HUgyv3omoR9B7BIAEg2Wm3FGIiIgoQW+7/ACAeaVWTtVKc62t\nrXA4HFCpVAAAlUoFu92O1tbWXsedPHkSZ8+exZe//GXcfPPN2Lp1KyRJkiMyEY0iUZJQ2+SESqHA\nsvEOKPgZT5/CablEBODC+g0BTwNyDOXQ5PJuPxERUTqJiyLeae9EZb4B+TkaueNQkgiCgBMnTuAX\nv/gFotEovva1r6GkpARLly4d9HNYrVybcSA2m0nuCCmP79HAhvMe7fm4DWcCEXx1xlhMLM3cTTT4\nezR07NwjIgBANHQe8e52mB1L5I5CRERECTrWEUAoLmAWd8jNCMXFxXA6nRAEASqVCoIgwOVyobi4\nuNdxJSUlWLRoEbRaLbRaLW644QYcOXIkoc49jycAUeRov4ux2Uxwu7vkjpHS+B4NbDjv0blABLs+\nasG0AiMqNJqMfa/5e3RpSqXikjdjOC2XiAAAQU89FEoN9PmXyx2FiIiIEnTQ5Yc1R4MJZr3cUWgE\nWK1WVFZWoq6uDgBQV1eHyspKWCyWXsdVV1fjwIEDkCQJsVgMBw8exJQpU+SITESjICqIeLGpDSaN\nGjePs3M6Ll0UO/eICKIYQ7DjGPT5lVCquAgzERFROmkNdeNMIIJZ9jwoeeGXMdavX49nn30WCxcu\nxLPPPosNGzYAAFatWoWjR48CABYvXgyr1Yobb7wRS5cuxcSJE7F8+XI5YxPRCHrlbzugL69wQKdW\nyR2HUhin5RIRwr4PIYlRbqRBRESUhg65fNAoFbiy0Cx3FBpBEyZMQG1tbZ/vb9u2reffSqUS3/72\nt/Htb387mdGIKAmOervQ4O3C9SUWjsqmAXHkHhEh4KmHSpuPHONYuaMQERFRAiJxAfWeLlRZTBzV\nQUSUIbpicew67UKpPgdfKLYMfAJlPXbuEWW5eLcP3YFmGC0zuIYDERFRmjns6UJUlDCbG2kQEWUE\nSZKwo8mJqCBhRUURVEpeo9HA2LlHlOWC3gYAgME6Q+YkRERElAhJknDQ5UeZIQelhly54xAR0Qh4\n292Jj/whLCovhF2nlTsOpQl27hFlMUmSEPA2INc0HmptvtxxiIiIKAFNXWG4I1HMsrOGExFlAm93\nDK+fdWOiWYc5HJFNCWDnHlEW6w40Q4j6uJEGERFRGjro8kOnUqLKYpQ7ChERDZMoSXi5yQkFFFg2\nzsElkygh7NwjymIBTz0Uqhzo8qfIHYWIiIgS0BmNo9EXwJWFZmiU/JOeiCjdHXL5caorjMVjCpGf\no5E7DqWZQf0l0NTUhJUrV2LhwoVYuXIlmpub+xwjCAI2bNiAefPmYf78+b22bT9w4ACWLVuGadOm\nYdOmTYM+j4hGjyhEEPZ9CEP+NCiVLB5ERETp5B23H6IEzOK0LSKitNceiWLvuXZMytPjykKz3HEo\nDakHc9AjjzyC2267DTU1Ndi1axfWrVuH7du39zpm9+7dOHPmDN544w34fD4sXboUc+bMQVlZGcrL\ny7Fx40bs3bsX0Wh00OcR0egJdTRCkuLcSIOIiCjNCKKEd9x+XGbWw5rLxdaJiNKZIEl48VQb1AoF\nbh5n53RcGpIBR+55PB40NjaiuroaAFBdXY3GxkZ4vd5ex+3ZswcrVqyAUqmExWLBvHnzsHfvXgDA\n2LFjUVlZCbW6b1/ipc4jotET8NZDnVsIrb5U7ihERESUgA99QXTGBMzmqD0iorT3pzYfzgW7cdNY\nO/K0nFFFQzPgyL3W1lY4HA6oVCoAgEqlgt1uR2trKywWS6/jSkpKer4uLi5GW1vbgAGGet4/slqz\nbxFhm80kd4SkY5tHTiTowpngOZROWgy7PbWGffPnTEREdGmH3D7ka9WYnG+QOwoREQ2DKxzFvvMe\nXJ5v4OZINCyDmpab6jyeAERRkjtG0thsJrjdXXLHSCq2eWT5zv8JgALQTk6p95U/58ymVCqy8mYM\nEdFIcoWjONkZxoJSK5ScukVElLY+2R1Xo1SghtNxaZgGnJZbXFwMp9MJQRAAXNgAw+Vyobi4uM9x\nLS0tPV+3traiqKhowABDPY+IhkaSRAS9R6AzXwaVhh0tRERE6eRttx8qBXClLbVG3hMRUWL+7PTh\nTDCC6jE2mDQZMe6KZDRg557VakVlZSXq6uoAAHV1daisrOw1JRcAFi1ahNraWoiiCK/Xi3379mHh\nwoUDBhjqeUQ0NJHOjyHEAzBYZ8odhYiIiBIQFUS8396JqQVGXggSEaWx9kgUb5zzYEq+ATOtXKKH\nhm9QfxWsX78ea9euxdatW2E2m7Fp0yYAwKpVq3Dfffdh+vTpqKmpQUNDAxYsWAAAWL16NcrLywEA\n7777Lu6//34EAgFIkoTXXnsNGzduxNy5cy95HhGNvIC3AUq1HjrzZXJHISIiogQ0eLsQEUTMtufL\nHYWIiIZIlCTsaHJCrVRg6VhOx6WRMajOvQkTJqC2trbP97dt29bzb5VKhQ0bNvR7/lVXXYW33nqr\n38cudR4RjSwhHkLYfwKmwquhUKrkjkNERESDJEkSDrr8KNJpMdaYK3ccIiIaooMuP04HIlg+3gGz\nlqOwaWQMOC2XiDJHyHsUkEROySUiIkozZ4MRtIa6Mcuex1EeRERpyhOJ4jfn2jE5T48rOB2XRhA7\n94iySMDbAK2uGFqdQ+4oRERElIBDLj9ylErMtHIjDSKidCRIEl441QaVQoGl3B2XRhg794iyRDTU\nhli4jaP2iIiI0kwwJuCIN4ArCk3IUfHPdyKidLS/tQPngt1YOtaOPK1G7jiUYfjXAVGWCHjrAYUK\n+oJpckchIiKiBLzX7ocgSZhlz5M7ChERDcHZzhB+2+LBdIsRVZyOS6OAqzcSZQFJjCPkPQp93mSo\n1Dq54xAREdEgiZKEQ24/xpt0cOhy5I5DREQJiosinmo4B51KhZqxdrnjUIbiyD2iLBD2fwRRCHNK\nLhERUZr5qz+Eju44R+0REaWpN897ca4rjJvH26FXq+SOQxmKnXtEWSDgrYdKY0KuqULuKERERJSA\nQy4/TBoVLs83yh2FiIgSdDYQwYG2Dswtt6KSn+M0iti5R5Th4rEuRDpPwmCpgkLB//JERETpoqM7\nhhP+IK4qzINayV0ViYjSSVwUsaPJCbNGjeVTyuSOQxmOV/pEGS7kPQJAgsHCKblERETp5G2XHwBw\ntc0scxIiIkrU71s64IpEsXScHXoNp+PS6GLnHlEGkyQJAU89cgzl0ORa5Y5DREREgxQXRbzT3onK\nfAPyczRyxyEiogS0BCP4Y6sXn7GaMDnfIHccygLs3CPKYNHQOcS7PdxIg4iIKM0c6wggFBe4kQYR\nUZoRRAk7mpwwaFRYPMYmdxzKEuzcI8pgAU8DFEoN9PmXyx2FiIiIEnDQ5Yc1R4MJZr3cUYiIKAF/\nbPOiNRxFzVg7dNwdl5KEnXtEGUoUogh1HIM+/3IoVTlyxyEiIqJBagl140wggln2PCgV3EiDiChd\ntIW68fsWL6osRlxewN1xKXnYuUeUocL+45DEKAyWGXJHISIiogQccvmgUSpwZSE30iAiSheCdGE6\nbq5KhSVj7HLHoSzDzj2iDBXw1EOtLUCOcazcUYiIiGiQQnEBh9u7UGUxcToXEVEaOdDWgfOhbtw0\n1gYDd8elJGPnHlEGind3oDvQDIN1BhSczkNERJQWQnEBjx4+hbgkYTY30iAiShuucBS/Pe/F1AID\npnE6LsmAnXtEGSjgbQAATsklIiJKI++1dwIA5pVaUWrIlTkNERENhihJeLnJCY1SgZvG2jm4gmTB\nzj2iDCNJEoLeBuSaKqDW8q4/ERFROhAlCYdcfow15uL6EovccYiIaJD+4vThTDCC6jE2mDRqueNQ\nlmLnHlGG6Q40Q4j6YbDMlDsKUdI0NTVh5cqVWLhwIVauXInm5uY+xwiCgA0bNmDevHmYP38+amtr\nex574oknsHjxYixZsgTLli3D/v37ex4Lh8P45je/ifnz52PRokX4/e9/n4wmEVGW+bgzBG93DLPt\n+XJHISKiQfJEonjjvAdT8gyYaTXJHYeyGLuViTJMwFMPhSoHuvzJckchSppHHnkEt912G2pqarBr\n1y6sW7cO27dv73XM7t27cebMGbzxxhvw+XxYunQp5syZg7KyMlRVVeHuu++GTqfD8ePHcfvtt+PA\ngQPIzc3Fz3/+cxiNRrz55ptobm7Gl7/8ZbzxxhswGAwytZaIMtEhlx8GtQpTC/jZQkSUDkRJwsvN\nLqgUCtSM43RckhdH7hFlEFGIIOz7EIaCaVAqNXLHIUoKj8eDxsZGVFdXAwCqq6vR2NgIr9fb67g9\ne/ZgxYoVUCqVsFgsmDdvHvbu3QsAmDt3LnQ6HQBg8uTJkCQJPp8PAPD6669j5cqVAIBx48Zh2rRp\neOutt5LVPCLKAh3dMRz3BXG1zQy1kn+eExGlgz85fWjqCuPG8kLkaTluiuTFvx6IMkio4wNIUpxT\ncimrtLa2wuFwQKVSAQBUKhXsdjtaW1v7HFdSUtLzdXFxMdra2vo8386dOzFmzBgUFRUBAFpaWlBa\nWjrgeUREQ/WO2w8AuNrGtXKJiNKBM9yNN895UJlvwJWFZrnjEHFaLlEmCXjqocm1QasvGfhgIurj\n7bffxuOPP46nnnpqRJ/XajWO6POlA5st+9adYZsz32i0Ny6KeK+hCVX2PEwqS72NNLLtZ0xENBBB\nkrCjyQmtSoGlnI5LKYKde0QZIhZxIxo6j/yS+SwwlFWKi4vhdDohCAJUKhUEQYDL5UJxcXGf41pa\nWlBVVQWg70i+w4cP44EHHsDWrVtRUVHR8/2SkhKcP38eFoul57xZs2YllNHjCUAUpaE2Me3YbCa4\n3V1yx0gqtjnzjVZ7Gzxd6IrGcUW+IeXez2z7GSuViqy8GUNEiXmrtQPngt24dUIRd8ellMFpuUQZ\nIuBpAKCAwTJd7ihESWW1WlFZWYm6ujoAQF1dHSorK3s64z6xaNEi1NbWQhRFeL1e7Nu3DwsXLgQA\nHDlyBGvWrMGWLVswderUPue98MILAIDm5mYcPXoUc+fOTULLiCgbHHL5YMnRYKJZL3cUIiIawPlg\nBL9r8WC6xYjpFo5sptTBbmaiDCBJIoLeI9DlXQaVhnecKfusX78ea9euxdatW2E2m7Fp0yYAwKpV\nq3Dfffdh+vTpqKmpQUNDAxYsWAAAWL16NcrLywEAGzZsQCQSwbp163qec/PmzZg8eTK++tWvYu3a\ntZg/fz6USiW+973vwWjk/zMiGr62UDeaAxF8sbwQSo66JyJKaTFRxIunnDCoVbhpjF3uOES9sHOP\nKANEOj+GGA9wIw3KWhMmTEBtbW2f72/btq3n3yqVChs2bOj3/B07dlz0ufV6PbZs2TL8kEREn3LI\n5YdaoeBi7EREaeC3571wR6L4yqQSGDQqueMQ9cJpuUQZIOCph1Kthy7vMrmjEBER0SBEBAGHPZ2o\nshqhV/MikYgolZ0JhLG/rQNX28y4LM8gdxyiPti5R5TmhHgI4c6PYCiYDoWCFwdERETpoN7Thago\nYbYtX+4oRER0CVFBRO0pJ/K0atxYbpM7DlG/2LlHlOaC3qOAJMJg5ZRcIiKidCBJEg66/CjV56DM\nmCt3HCIiuoS959rh6Y5h2XgHclTsQqHUxN9MojQX9NZDqy+BVueQOwoRERENQnMgAlc4itn2PLmj\nEBHRJXzsD+Ggy4859jzuak4pjZ17RGksGmpFLOyEwTJD7ihEREQ0SAddPuhUSky3mOSOQkREF9Et\niHi52YnCXA0WlRfKHYfokti5R5TGAt4GQKGCoWCa3FGIiIhoELpicXzQEcCVhWZoOb2LiChl7T3b\nDn80jlvGOaBR8vOaUht/Q4nSlCTGEfIehT5vCpRqndxxiIiIaBDecXdClIBrOCWXiChlnewM4ZDb\nj2sd+Rhr4rUWpT527hGlqbD/I4hCGAYrp+QSERGlA0GS8I7Lj8vMehTmauWOQ0RE/egWRLzc5IQ1\nR4N5pVa54xANCjv3iNJUwFsPlcaMXFOF3FGIiIhoAKIk4dXTLvhjccziqD0iopS191w7fNE4bhnv\n4PIJlDb4m0qUhuLRTkQ6T8JgqYJCwf/GREREqe5YRwDvuDth1qgwOd8gdxwiIurHyc4QDrn8+CdH\nPsZxOi6lEfYKEKWhoPcIAAkG60y5oxAREdEgHHL5YdKo8J9V46BSKOSOQ0REnxKJC9jxt+m48zkd\nl9IMO/eI0owkSQh6G5BjGANNjkXuOERERDQAZ7gbTV1hXOso4I6LREQp6rW/7Y67nNNxKQ3xN5Yo\nzUSD5xDv9nDUHhERUZo45PJDrVDgykKz3FGIiKgfJ3xBvNfeic8WF3B3XEpL7NwjSjMBbz0USg30\n+ZfLHYWIiIgG0C2IONzehekWIwwaldxxiIjoU8JxAa80u2DXaXFDCWdGUXpi5x5RGhGFKEI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gAgIqIRufhHsDoa4fDO0TsKjTgcS+PgUBpL6r2od9r0jkNEZAqDhTJ+O5DCsoAXSxrYjks0Fizu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\nRiURpenVpHTlP5enBTSjUk2m6ei6p1qZZaC7/ExUmk2q2Jpc+TWlogxA0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            "text/plain": [
              "<Figure size 1296x648 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UFlrENY8WAYK",
        "colab_type": "text"
      },
      "source": [
        "## References\n",
        "\n",
        "- https://accel-brain.com/semantics-of-natural-language-processing-driven-by-bayesian-information-search-by-deep-reinforcement-learning/verstarkungslernalgorithmus-als-funktionale-erweiterung-des-banditenalgorithmus/\n",
        "- https://ferret-plus.com/11986\n",
        "- https://www.cs.princeton.edu/courses/archive/fall16/cos402/lectures/402-lec22.pdf\n",
        "- https://lilianweng.github.io/lil-log/2018/01/23/the-multi-armed-bandit-problem-and-its-solutions.html\n",
        "- https://www.smartbowwow.com/2018/08/python.html\n",
        "- https://www.smartbowwow.com/2018/08/python.html\n",
        "- https://haltaro.github.io/2017/08/08/introduction-to-ad-tech\n",
        "- https://github.com/brianfarris/RLtalk/blob/master/RLtalk.ipynb\n",
        "- https://blog.albert2005.co.jp/2017/01/23/%E3%83%90%E3%83%B3%E3%83%87%E3%82%A3%E3%83%83%E3%83%88%E3%82%A2%E3%83%AB%E3%82%B4%E3%83%AA%E3%82%BA%E3%83%A0%E3%80%80%E5%9F%BA%E6%9C%AC%E7%B7%A8/\n",
        "- https://www.cs.princeton.edu/courses/archive/fall16/cos402/lectures/402-lec22.pdf"
      ]
    }
  ]
}

長くなったのでここでいったん切ります

次回のGistでは

• UDB
• Thompson Sampling

そしてできればシンプルなMDPまで実装しようと思います

最後のSoftmaxとの比較間違って認識してますね

オレンジがBanditなので少し良くなってます