diff --git a/src/2024-spring-lab3-ai-transpiler-ja.ipynb b/src/2024-spring-lab3-ai-transpiler-ja.ipynb
index c5c50e7..581856d 100644
--- a/src/2024-spring-lab3-ai-transpiler-ja.ipynb
+++ b/src/2024-spring-lab3-ai-transpiler-ja.ipynb
@@ -13,19 +13,17 @@
    "id": "f67ec71c-206b-45fc-a6f2-ec58b4891d4c",
    "metadata": {},
    "source": [
-    "# Lab 3: What's Next - AIを活用した Qiskit Transpiler Service を使ってみる"
+    "# AIを活用した Qiskit Transpiler Service を使ってみる(2024年 Lab3)"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "8979f3ca-d980-49c5-bda4-d7f59ed033f6",
+   "id": "5ce55c7a-ee15-4cab-8947-3efc03340706",
    "metadata": {},
    "source": [
-    "# Table of Contents\n",
-    "\n",
-    "* [Introduction to AI-Powered Transpiler Passes](Introduction-to-AI-Powered-Transpiler-Passes)\n",
-    "    * [Exercise 1](#exercise1)\n",
-    "    * [Exercise 2](#exercise2)"
+    "```{important}\n",
+    "このLabはIBM Quantum Premium Planユーザーのみ実行可能です。（Quantum Challenge中はイベント用に権限が付与されます）\n",
+    "```"
    ]
   },
   {
@@ -33,22 +31,12 @@
    "id": "bf00347e-9ffd-4f4d-9270-21eb512f8f96",
    "metadata": {},
    "source": [
-    "# Imports"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "3c4bb49c-26f3-4b0a-b8fa-e25f2882a688",
-   "metadata": {
-    "id": "5a76cfa8-9f5d-4716-a007-c13bcb54b82b"
-   },
-   "source": [
-    "いつものように、オプションのインストールから始めます。QiskitのインストールとAPIトークンのセルは、以前の Lab で保存していない場合のみ実行する必要があります。"
+    "## Setup"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "abb25eb9-4327-4ae0-9db4-745b87194a3d",
    "metadata": {
     "scrolled": true
@@ -57,32 +45,30 @@
    "source": [
     "### Install Qiskit and relevant packages, if needed\n",
     "### IMPORTANT: Make sure you are using python 3.10 or 3.11 for compatibility of the required packages\n",
-    "%pip install qiskit[visualization]==1.0.2\n",
-    "%pip install qiskit-ibm-runtime\n",
-    "%pip install qiskit-aer\n",
-    "%pip install graphviz\n",
-    "%pip install qiskit-transpiler-service\n",
-    "%pip install git+https://github.com/qiskit-community/Quantum-Challenge-Grader.git -U"
+    "# %pip install qiskit[visualization]==1.0.2\n",
+    "# %pip install qiskit-ibm-runtime\n",
+    "# %pip install qiskit-aer\n",
+    "# %pip install graphviz\n",
+    "# %pip install qiskit-transpiler-service\n",
+    "# %pip install git+https://github.com/qiskit-community/Quantum-Challenge-Grader.git -U"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "id": "ef1f5086",
    "metadata": {},
    "outputs": [],
    "source": [
-    "### Save API Token, if needed\n",
-    "\n",
-    "%set_env QXToken=deleteThisAndPasteYourTokenHere\n",
+    "# Load your API token in .env\n",
     "\n",
-    "# Make sure there is no space between the equal sign\n",
-    "# and the beginning of your token"
+    "%load_ext dotenv\n",
+    "%dotenv"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "id": "1aff5103-c92a-45b0-93bb-f5b034de45c4",
    "metadata": {},
    "outputs": [],
@@ -90,6 +76,7 @@
     "# Imports\n",
     "\n",
     "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
     "from qiskit.circuit.library import EfficientSU2\n",
     "from qiskit.transpiler.preset_passmanagers import generate_preset_pass_manager\n",
     "from qiskit_ibm_runtime import QiskitRuntimeService\n",
@@ -97,30 +84,23 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "08927292-6f1a-4490-901a-fdcdc3b411f8",
+   "cell_type": "markdown",
+   "id": "545418e9-a530-4e11-a323-d01177dd1da0",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "# Import for grader\n",
-    "from qc_grader.challenges.iqc_2024 import grade_lab3_ait_ex1, grade_lab3_ait_ex2"
+    "## はじめに\n",
+    "\n",
+    "Lab 3 へようこそ！ 本日は、Qiskit スタック用に開発されているエキサイティングな新機能の一部を、特別にご紹介します。この教育的な Challenge は notebook が分かれていて、それぞれがユニークで画期的なイノベーションを紹介し、これらの新機能を探索しテストを促します。複雑な量子回路を簡素化する Circuit Knitting Toolboxのようなツールを探求し、Qiskit Serverless で量子コンピューティングと古典コンピューティングのシームレスな統合をセットアップするワークフローを体験し、AI-Powered Transpiler Passes と コード生成と回路最適化のための Qiskit Code Assistant のような AI 搭載ツールを活用するチャンスがあります。これらのイノベーションが量子開発にどのような革命をもたらすのか、ぜひご覧ください！"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "545418e9-a530-4e11-a323-d01177dd1da0",
+   "id": "382aa58f-1688-4eca-a6a3-3647d9589bec",
    "metadata": {},
    "source": [
-    "## はじめに\n",
-    "\n",
-    "Lab 3 へようこそ！ 本日は、Qiskit スタック用に開発されているエキサイティングな新機能の一部を、特別にご紹介します。この教育的な Challenge は notebook が分かれていて、それぞれがユニークで画期的なイノベーションを紹介し、これらの新機能を探索しテストを促します。複雑な量子回路を簡素化する Circuit Knitting Toolboxのようなツールを探求し、Qiskit Serverless で量子コンピューティングと古典コンピューティングのシームレスな統合をセットアップするワークフローを体験し、AI-Powered Transpiler Passes と コード生成と回路最適化のための Qiskit Code Assistant のような AI 搭載ツールを活用するチャンスがあります。これらのイノベーションが量子開発にどのような革命をもたらすのか、ぜひご覧ください！\n",
-    "\n",
-    "<div class=\"alert alert-block alert-danger\">\n",
-    "    \n",
+    "```{warning}\n",
     "これらの機能は **ベータ版およびリリースプレビュー版** であるため、バグに遭遇する可能性が高いことにご注意ください。量子開発の限界に挑戦してください！\n",
-    "\n",
-    "</div>"
+    "```"
    ]
   },
   {
@@ -128,44 +108,39 @@
    "id": "430cc7b6-46f2-4077-9746-edbb079ff0db",
    "metadata": {},
    "source": [
-    "# Qiskit Transpiler service を使った AI 搭載 transpiler passes の紹介\n",
-    "\n",
+    "## Qiskit Transpiler service を使った AI 搭載 transpiler passes の紹介\n",
     "\n",
-    "このハンズオン演習では、Qiskit の AI 搭載 transpiler passes の最先端機能を探求する機会を提供します。Qiskit Transpiler Service の最近のベータ版リリースにより、 AI と IBM Cloud&reg; リソースを活用して量子回路をより効率的に最適化できるようになりました。\n",
     "\n",
-    "特定の量子デバイスの制約や特性に合わせて抽象的な量子回路をトランスパイルすることは、量子コンピューティングのワークフローにおいて非常に重要なステップです。Lab 2 で学んだように、このプロセスは従来、ヒューリスティックなアルゴリズムに依存していましたが、新しいAIを搭載したtranspiler passes は、実用的なアプリケーションに十分な速度でありながら、より効率的で高品質なトランスパイルの可能性を提供します。今回のチャレンジでは、Qiskit Transpiler Service のベータ版へのアクセス権を提供し、実験していただきます。\n",
-    "\n",
-    "**このツールの詳細については、 [ブログ](https://www.ibm.com/quantum/blog/ai-transpiler-passes) と [arxiv論文](https://arxiv.org/abs/2405.13196) をご覧ください。** ツールのドキュメントは [IBM Quantum Platform docs](https://docs.quantum.ibm.com/transpile/qiskit-transpiler-service) にあります。\n",
+    "このLabでは、Qiskit の AI 搭載 transpiler passes の最先端機能を探求します。最新の Qiskit Transpiler Serviceのベータ版リリースにより、 AI と IBM Cloud&reg; リソースを活用して量子回路をより効率的に最適化できるようになりました。\n",
     "\n",
-    "この Exercise では、このベータ・リリース・プレビューで、 AI 搭載 transpiler passes を実験し、従来の手法と比較し、量子コンピューティング・ワークフローをどのように強化できるかを理解します。さあ、量子回路最適化の未来に飛び込んでみましょう！"
+    "特定の量子デバイスの制約や特性に合わせて抽象化された量子回路をトランスパイルすることは、量子コンピューティングのワークフローにおいて非常に重要なステップです。Lab 2 で学んだように、このプロセスは従来、ヒューリスティックなアルゴリズムに依存していましたが、新しいAIを搭載したtranspiler passes は、実用的なアプリケーション向けに十分な速度でありながら、より効率的で高品質なトランスパイルの可能性を提供します。"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "75b7f2b4-31e5-4ebc-82fd-330f0bcdd807",
+   "id": "0142dcdd-e84e-4317-968e-8079889e8012",
    "metadata": {},
    "source": [
-    "## Step 1: 回路の作成\n",
+    "今回のチャレンジでは、Qiskit Transpiler Service のベータ版へのアクセス権を提供し、実験していただきます。\n",
     "\n",
-    "Qiskit の circuit library を使って量子回路を作成します。このステップでは、量子回路の構造とゲートを定義します。これは、その後のトランスパイルと最適化のタスクの基礎となります。ここでは、元の [論文](https://arxiv.org/abs/2405.13196) で示された回路と非常によく似た回路を使用します。"
+    "**このツールの詳細については、 [ブログ](https://www.ibm.com/quantum/blog/ai-transpiler-passes) と [arxiv論文](https://arxiv.org/abs/2405.13196) をご覧ください。** ツールのドキュメントは [IBM Quantum Platform docs](https://docs.quantum.ibm.com/transpile/qiskit-transpiler-service) にあります。\n",
+    "\n",
+    "この Exercise では、このベータ・リリース・プレビューで、 AI 搭載 transpiler passes を実験し、従来の手法と比較し、量子コンピューティング・ワークフローをどのように強化できるかを理解します。さあ、量子回路最適化の未来に飛び込んでみましょう！"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "da050482-4412-41e2-9548-9e84a45749c3",
+   "id": "75b7f2b4-31e5-4ebc-82fd-330f0bcdd807",
    "metadata": {},
    "source": [
-    "<div class=\"alert alert-block alert-info\">\n",
-    "\n",
-    "**重要:** qiskit-transpiler-service パッケージがインストールされ、IBM Quantum Platform を使用するようにトークンが設定されていることを確認してください。この方法については、 [こちら](https://docs.quantum.ibm.com/start/setup-channel#set-up-to-use-ibm-quantum-platfor) のドキュメントリンクを参照してください。\n",
-    "\n",
+    "### Step 1: 回路の作成\n",
     "\n",
-    "</div>"
+    "Qiskit の circuit library を使って量子回路を作成します。このステップでは、量子回路の構造とゲートを定義します。これは、その後のトランスパイルと最適化のタスクの基礎となります。ここでは、元の [論文](https://arxiv.org/abs/2405.13196) で示された回路と非常によく似た回路を使用します。"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "id": "392639ca-7190-4c32-b531-b41960e7ea91",
    "metadata": {
     "scrolled": true
@@ -177,12 +152,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "id": "8502685d-24fd-4a0b-b993-45b185b72a07",
    "metadata": {
     "scrolled": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Original circuit -> Depth: 63, CNOTs: 61\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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9ngEAAACcr0um/GVmZmrixImaNWtWu8UUzvrd/7teo67oJ7td8pTXa/iQKC39r/F+iylJiuwTqid/Pl2zrxvWbjEFAAAAoOt02Vl4WlraBcWX52UpOmm6muurZI8eIMf41C7KLPikJA3Sx/+4TX9/Za+q65q08W9zNXRQlOn9lOdlyeGapZbGBjXs2aTosdf3qt8zAAAAYDZLL2skxrRONZOkA8Pma5hzhOx2u/bvLtGIq87G9AZRkaG697bRXbLtT37P5/6Opdna596lkYlnYwAAAABcGEsLqrCQs/ftJCWPOvN60pSuKSx6q09+z+f+jiUpaeoYizICAAAAeobgeQ4VAAAAAHQzFFQAAAAA0EmWTvnztkjuGv8xiTGtU9ZwafHZAAAAAB2ztKBy1/B8pIt1oua0Gk8bpm+XzwYAAADoWNA8vKgyf6V8RpMiE1zyVlcodsZCq1MKauVHT+or33tDew/WqqauSTv21ejvD8/skuXW+WwAAACAtgXPhC2bTUbtMYWER6r/lLlWZxP0bru/UG9tPqJDFSd1722jtX7TEd2x5LUO27W0+PT0S7v15sbDgXfGZwMAAAC0qUsKqsLCQuXk5OiKK65QcXFxQG1CHYM0cMZC1e98V02VpV2RVo+x50Ct9h2sO/N/Z1y0JGn3gVrtO1jrt+1Pf/ehvvaTt3XH4tdVtLUyoP74bAAAAIC22Xw+n8/sja5atUqLFi3S448/rpSUFE2dOvW8n+fm5srj8ajOEa8tyYv9bmvS5hVy1JX5jVnvHqLUxIqLzru7OFYfoec2JWjRnVfLGRet1JShWr/piA5X1Ojo7nzFRp9ut+3ru4bq44OxsqlFt04s08hB9W3GmfXZAAAAAN2N0+lURkZGQLFdUlBlZ2fLMAwZhqGxY8dq3rx5bcYVV5mz8MGSZUXKWTqtk9l2Py0tPl395TXavqdKkrT8wal64JENcl01QB+tvk02m63dtidPGfrRbzZp845jWv+nL7YbZ9ZnAwAAAPRkXTLlLzMzUxMnTtS9997bbjGFzgsJsempn9+gMSNiFBFu16HKBo0dEaMnfz7dbzElSVGRocpZOk3J4wZdomwBAACAnqvLVvlLS0u7oPjyvCxFJ02XfD7JZpNjfGoXZdYzTB4/WNuev13vfdQ61TH7/skKDTW/Pi7Py5LDNUstp0/q5J7N6jvmWj4bAAAA4P9n6bLpiTGt08Yk6cCw+RrmHCG73a79u0s04qqzMWhbaGiIpqfEdcm2P/lszv1cpC9on3uXRiaejQEAAAB6M0sLqrCQs/fgJCWPOvN60pTRFmWET3zy2Zz7uUhS0tQxFmUEAAAABJ/geQ4VAAAAAHQzFFQAAAAA0EmWTvnztkjuGv8xiTGt088Q3AL5LCU+TwAAAPQslhZU7hqedXSpGUaLPtx5XMerG03dbiCfpcTnCQAAgJ7F0oLqXJX5K+UzmhSZ4JK3ukKxMxZanVKPU/j+IX331+/rYEWDDKNFJaW1ejH3Rg0dFGV6X3yeAAAA6A2CZ/KVzSaj9phCwiPVf8pcq7PpcU41GvrWL97Vrv01qj9p6Jv/OVYbth3Vgofe7LBtbX2THnxkg54vLA28Qz5PAAAA9AJdUlAVFhYqJydHEyZMUFFRUUBtQh2DNHDGQtXvfFdNlaVdkVav9q/3D2n/ofoz/3fGRUuS9hyoVcNJr9+23/z5u1r+9Hb9T9a78hyuC6g/Pk8AAAD0Bjafz+cze6OrVq3SokWLtGzZMl1//fWaPn36eT/Pzc2Vx+NRnSNeW5IX+93WpM0r5Kgr8xuz3j1EqYkVF513T7bvaF+t23qF7rtrgpxx0UpNGar1m46o4mi1Th1Yo1B7+1+DV4ov187yAQqzN+u/r92j6D7GZ2IC+SylwD5PAAAAwEpOp1MZGRkBxXZJQZWdnS3DMDR+/HjV1tbq7rvvbjOuuMqcRSmWLCtSztJpncy2d2jyNst1xwsqKa2VJC1/cKoeeGSD/uOG4Xr5tzf5bXuq0dCKZ7Zry65j+sfyG9uMCeSzlFiUAgAAAD1Ll0z5y8zM1MSJE3XNNde0W0zh0goPs+uZX6XKlThQgwZEqLrutGZNidOzv57RYdvIPqH6wTcmKn5odNcnCgAAAHQjXbbKX1pa2gXFl+dlyeGapZbTp2QLDZNjfGoXZdZ7TR4/WB/940vaW1anvpGh+vl3kruknzOfZWODmk/WKDRmMJ8nAAAAeiRLl01PjGmdAiZJB4bN1zDnCNntdu3fXaIRV52NgXlsNptGXdHP9O2291lK0j73Lo1MPBsHAAAA9BSWFlRhIWfvp0lKHnXm9aQpoy3KCJ3V3mcpSUlTx1iQEQAAAND1guc5VAAAAADQzVBQAQAAAEAnWTrlz9siuWv8xyTGtE4nQ88TyOcv8R0AAABA8LK0oHLXmPMcKnSt8qMnVfDWAZUerlNLi08hITZTthvI5y/xHQAAAEDwsrSgOldl/kr5jCZFJrjkra5Q7IyFVqcEST/7/Rb9cfUuHao8qVC7TSlfWat//u4mDYmNNLUfPn8AAAB0R10ykaqwsFA5OTmaM2eOli9fHlgjm01G7TGFhEeq/5S5XZEWLtDeslr9Lm+nDlWelCR9+yvjtGXXcX39px1fVtpcfEwLHnpTz6zbHVhnfP4AAADohrrkClVJSYnS09MVFhamhISEwBJxDJJjwkzVbMyXPSpGkQkTuiI1XID/e9GtiuOnzvzfGRctSdrtqe2w7ZJHNuitzUf0zpYjuv3zCeobFeY3ns8fAAAA3ZHN5/P5zN5odna2DMOQYRi67777FBsbe97Pc3Nz5fF4VOeI15bkxX63NWnzCjnqyvzGrHcPUWpixUXnjfNtOTBAb7rjlL5gvJxx0UpNGaqn1+3Rsy9u1j3X7vXbdt3Hw7XnaIz6hnv1tRvcsrdxLTSQz18K7DsAAAAAmMXpdCojIyOg2C4pqCSpoKBALpdL8fHx7cYUV5mzKMWSZUXKWTqtE1nCn7qGJk2a96L2ltVJkpY/OFU/eGyT0u8ap4eXTPHb9nRTs/75dpn++W6ZHv/x59qMCeTzl1iUAgAAAMGryxajTktL81tMIfg5+obr7w/P0tQJlyl+aF+davTqG3eM1q/vn9xh24hwu770+QT1jfQ/1Q8AAADozoJmlb/yvCw5XLPka2mWfD45xqdanRIkpSQNUtGzt+p0U7PCQkNMWzL90z75/FtOn1Td1tfV75qb+Q4AAAAg6FlaUCXGtE7nkqQDw+ZrmHOE7Ha79u8u0YirzsbAehHhdtO32d7nL31B+9y7NDLxbBwAAAAQjCwtqMJCzt4bk5Q86szrSVNGW5QRLqX2Pn9JSpo6xoKMAAAAgAvTZfdQAQAAAEBPR0EFAAAAAJ1k6ZQ/b4vkrvEfkxjTOjUMkAL7zkh8bwAAAHBpWFpQuWvMeQ4VgovP59O/3z+kl948oJLSap1uajZtUYtAvjMS3xsAAABcGkGzbHpl/kr5jCZFJrjkra5Q7IyFVqeETmhubtGt6YV6a/MR1Z/0KsQmTblrrQr/8B+6bGCkqX3xnQEAAIDVumRSVGFhoXJycjR27FitWbMmsEY2m4zaYwoJj1T/KXO7Ii1cAqv/vV+vf3BY9Se9kqT77krSVneVlizb0GHbJ18o0c3/84qefKEksM74zgAAAMBiXXKFqqSkROnp6aqvr1dDQ0NgiTgGyTFhpmo25sseFaPIhAldkRq6WN4r+9V4uvnM/51x0ZKknfurO2yb8/R27dhXrbIjDfra7R0vnc93BgAAAFaz+Xw+n9kbzc7OlmEYGjWq9dlCd95553k/z83NlcfjUZ0jXluSF/vd1qTNK+SoK/Mbs949RKmJFReXNEyx3j1EHx4YpPQFSXLGRSs1ZaieXrdHzxd8oHkppX7bvvjRFfIc7ytnbL2+NLHtzzyQ74wU2PcGAAAAaIvT6VRGRkZAsV1SUElSQUGBXC6X4uPj240prjJnUYoly4qUs3RaJ7KE2SqOn9K1C1/S/kP1kqT0BUl6tmCPnvzZ5zR3ptNvW8No0Td+9rb++JPPKTS07dmogXxnJBalAAAAwKXRZQtLp6Wl+S2m0DMNiY3Umkdv1MwpcRo7sr+KPq7Uyoeu7bCYkqTQ0BAN6BfRbjEFAAAABJugWeWvPC9L0UnT1dxQLXvf/nKMT7U6JXTS1aNj9foTc7q8n/K8LDlcs9Ry+pQadn+g6LHX870BAADAJWVpQZUY0zo1S5IODJuvYc4Rstvt2r+7RCOuOhsDfKK974x0o/a5d2lk4tk4AAAAoKtZWlCFhZy9zyUpedSZ15OmdLzCG3qn9r4zkpQ0dYwFGQEAAKA342YVAAAAAOgkS69QeVskd43/mMSY1qsSQGfxPQMAAEBXsbSgcteYs2w64A/fMwAAAHSVoFnlD71bXUOTcp7erhdf9ygmOlxL7hkvR99wq9MCAAAA/Aqagqoyf6V8RpMiE1zyVlcodsZCq1PCJVJVe1qpXy3Q9j1V8vmkn/1+i54vLNX6P6VpQL8IU/viewYAAAAzdcldI4WFhcrJydGUKVP09NNPB9bIZpNRe0wh4ZHqP2VuV6SFIPXT336obbtbi6n0BUny+aRtu6v0099+2GHb+371nqbetVZ/fH5XYJ3xPQMAAICJuuQKVUlJidLT09XQ0KADBw4ElohjkBwTZqpmY77sUTGKTJjQFakhCG3bXXXm38646DP/3r6nqq3wM2rrm/R8YamOHDul0NAQfeOOjpdN53sGAAAAM9l8Pp/P7I1mZ2fLMAyFhoZqxIgRmjdv3nk/z83NlcfjUZ0jXluSF/vd1qTNK+SoK/Mbs949RKmJFRedN6zxz23DtKuiv9IXJOmeW0Zp/aYj8pTX61+vvav/GH+o3XY+n/TiR1eovCZKE4ad0OeuqmwzzqzvGQAAAHoHp9OpjIyMgGK7pKCSpIKCArlcLsXHx7cbU1xlzuprS5YVKWfptE5kiWBQeqhOM7/2skoP1yt9QZIee7ZYCZdH640n5yhhmMNvW5/Pp4zs9/XYQ9e1G2PW9wwAAAD4tC5blCItLe2C4svzstQveY68Jw7LHtVPjvGpXZQZgk3CMIde+d1NeujRjdqwtVJfmnmFfn3/5A6LKUmy2WwKtQd2K2B5XpYcrlnytTTr1L6PFDniar5nAAAAuChBs8rfgOnzFTF4hGyjktV4sMTqdHCJjR7RX2tyv9ClfZz5jtntciRNV+PBABeyAAAAANphaUGVGNM61arVqHN+Mvq8GOBinP2ejfrUT8acFwMAAABcKEsLqrAQ7ltB1+N7BgAAgK7SJc+hAgAAAIDewNIrVN4WyV3jPyYxpvUKA3Ap8d0EAABAICwtqNw1LGeN4MR3EwAAAIEImlX+gAu1Y2+V/t9vNmvDtqM61disX6anaGBMhNVpAQAAoBcJmoKqMn+lfEaTIhNc8lZXKHbGQqtTQhDbvOOYvpRRqIMVDZKk3/9jl979qELvPXOLoqPCTO2L7yYAAADaY+odIIWFhcrJydG4ceO0fft2rVu3Ti+88EJgjW02GbXHFBIeqf5T5pqZFnqgHz626Uwxlb4gSZJUvLdKK/9a7Lfd6aZm3fiNlzX6ln/oyTUBPu+M7yYAAADaYeoVqpKSEqWnpysqKkqSZLfbZbfbPxOXm5srj8ejOke8lLy4NRHHIDkmzFTNxnzZo2IUmTBBkvTooyvkqCvz2+969xAtKX/OzLeCILdl20hJkUpfkKR7bhklZ1y0POX1evJvb+jojqfbbXe0LkJvfDBSLb4Q/fKxl1X89uNtxpn13QQAAED343Q6lZGREVCszefz+czqODs7W4ZhKCUlRQ0NDQoLC1NTU5PuuOOONuOLq8y58X/JsiLlLJ3WyazRHX3xO/9SwdutxczyB6fqgUc2yG636ZElU3T/3ePbbef1tujLD7ym9z6u0G++f63uvPnKNuPM+m4CAACgZzP1ClVmZqYKCgo0btw4xcfHm7lp4DwPL5ms4r1VKj1cL095vSTp6sSBWvSfY/y2CwsL0drHvqAly4raLaYAAACAQJm+KEVaWtoFtynPy1K/ibNlNFTr9KESRY64Wo7xqWanhh5k3JUDtP5Pafrp7z7Uzn1V+tE3JyrzXpci+5j7lS7Py5LDNUu+lmY1VZQqfLCT7yYAAADOCIpV/gZMn6+IwSNks9ula25S48FdVqeEbuCKuGg99fPpXdrHed/NpOl8NwEAAHAeSwuqxJjW+1CkUZ/6yZjzYoBLje8mAAAAAmFpQRUWwk39CE58NwEAABAIU59DBQAAAAC9iaVXqLwtkrvGf0xiTOvVAiDY8X0GAADofSwtqNw1POsHPQffZwAAgN4nKFb5k6TK/JXyGU2KTHDJW12h2BkLrU4JPdDTL+3W75/bqT1ltTp89KRWPnStLhsYaXo/fJ8BAAB6h6ApqGSzyag9ppDwSPWfMtfqbNAD/S5vp37w2CZV1zVJkvJe2a+d+2q06W9zFdbBPLxTjYZONzWrf7+IwDrj+wwAANArmHo3R2FhoXJycjRu3Dht375dq1ev1vbt2wNqG+oYpIEzFqp+57tqqiw1My1AkvTH50vOFFPpC5IkSbv2Vyvv1X1+23kO1yn5Ky9qwh0v6Nn8PQH1xfcZAACgd7D5fD6fWRtbtWqVFi1apCeeeEI33HCDoqOjVV9fr/Hjx58Xl5ubK4/HozpHvLYkL/a7zUmbV8hRV+Y3Zr17iFITKy46f/Rsf3pvlKpPRih9QZLuuWWU1m86Ik95vd5750197qrKdtvtKI/Rq8XDJUlj46p0c9LhNuPM+j4DAADAWk6nUxkZGQHFmlpQZWdnyzAMpaSkqKGh4UxBdfvtt7cZX1xlzk38S5YVKWfptE5mjd4i9asFemvzEUnS8gen6oFHNqi/I1z//N1sTXMNabfd6aZm3fPD9Xr/40r9+w83a3RC/zbjzPo+AwAAoPsw9R6qzMxMFRQUaNy4cYqPjzdz08BFe/R703THA4Xaf7BenvJ6RUeFafZ1w/wWU5IUEW5X3rJZWrKsqN1iCgAAAL2T6YtSpKWlXXCb8rws9Zs4W0ZDtYzqCoUPdsoxPtXs1NDLTRobqw+enasVz2zX/kN1em7ZTN18w3DT+ynPy5LDNUu+lmY1HtihPvFj+T4DAAD0UEGxyt+A6fMVMXiEbHa7JKnx4C6LM0JPNWhAH/0yPaVL+zj3++xIms73GQAAoAeztKBKjGm9p0Qa9amfjDkvBugO+D4DAAD0PpYWVGEh3KCPnoPvMwAAQO9j6nOoAAAAAKA3sfQKlbdFctf4j0mMaf3LP9ATsQ8AAAB0b5YWVO4antuD3o19AAAAoHsLilX+JKkyf6V8RpMiE1zyVlcodsZCq1MC5PW2KP3X72v9pnIdPnZKu/bX6E9Z0zUkNtL0vtgHAAAAup/gmUhks8moPaaQ8Ej1nzLX6mwASdI3f/6OnnihRDv316imrkn/fOeg5nz7Vfl8vg7b7jlQo92eDubznYt9AAAAoNsxtaAqLCxUTk6Oxo0bp+3bt+vtt9/W2rVrA2ob6hikgTMWqn7nu2qqLDUzLaBTmrzNevvDIzKaW4un9AVJkqSS0hq982GF37br3vRo2sJ1uvbudVr7emlA/bEPAAAAdD82XyB/ag/QqlWrtGjRIj3xxBO64YYbNGLECBUWFmru3PP/2p6bmyuPx6M6R7y2JC/2u81Jm1fIUVfmN2a9e4hSE/2f4AIX6rQRoqffH6V7vzxRzrhopaYM1fpNR+Qpr9Oej1/V6KG17bZ9b+9l2rB/sCRp6ohKXXfl0TbjzNoHAAAAYB6n06mMjIyAYk0tqLKzs2UYhlJSUtTQ0KCSkhLdeOONmjx5cpvxxVXm3JC/ZFmRcpZO62TWQPsmz1+rTcXHJEnLH5yqBx7ZIGdcX3343G0aGBPRbrtTjYa+88v3tGHbUW3821xFRbZ9u6JZ+wAAAACsYeqiFJmZmSooKNC4ceMUHx9v5qYBS/zuR9drfubr2n+oTp7yel0+OEqL7x7vt5iSpMg+oXoqa7qWLCtqt5gCAABA92f6mV5aWtoFtynPy1K/ibNlNFSrqWK/+sSPlWN8qtmpARcsJWmQPnruNv31n3tVVdukjX+9VZcP7mt6P+V5WXK4ZsnXbOjk3g8VdeU17AMAAADdgKV/Ok+MaZ3OdGDYfA1zjpDdbpck7XPv0sjEszGAlfpGhekbd4zpkm23vQ+ksg8AAAB0E5YWVGEhrfeGJCWPOu/1pKldc/IKBBv2AQAAgO4teJ5DBQAAAADdDAUVAAAAAHSSpVP+vC2Su8Z/TGJM67QoAK3YbwAAAIKHpQWVu4Zn8KDnqq49rcbTzaZvl/0GAAAgeATNA3Iq81fKZzQpMsElb3WFYmcstDoloFMqjp/S/O+9rt0H6lRdd1o791Xrbw/P1NBBUab3xX4DAABgreCZFGSzyag9ppDwSPWfMtfqbIBOu31xod7YeEQHKxp0722j9eamI7p98WsdtvP5fPrby3v11ubywDtjvwEAALCUqQVVYWGhcnJyNG7cOG3fvl1FRUVavXp1QG1DHYM0cMZC1e98V02VpWamBVwy+w7WaveB2jP/d8ZFS5L2HKjV3rLa9ppJkrIe36J7frRet93/mt77qCKg/thvAAAArGXz+Xw+sza2atUqLVq0SE888YRuuOEGDRw4UK+88oruvffe8+Jyc3Pl8XhU54jXluTFfrc5afMKOerK/Masdw9RamJgJ6BAVzpWH6HnNiVo0Z1XyxkXrdSUoVq/6YgOVdTq6O51GhR9ut22r+8aqo8Pxsomn77oOqBRg+vbjDNrvwEAAEDbnE6nMjIyAoo1taDKzs6WYRhKSUlRQ0ODhg4dqoqKCt12221txhdXmXNz/ZJlRcpZOq2TWQPm8fl8uvrLa7Rtd5UkafmDU/XAIxs0ftQAfbz6NoWE2Npte/KUoR88tkmbdxzVW//3Rdlsbceatd8AAADg4pm6KEVmZqYKCgo0btw4xcfHm7lpoFuw2Wx68mc36J4fvqX9h+p0qLJBY0bE6Mmf3eC3mJKkqMhQPZo5TUuWFbVbTAEAACC4mL7KX1pa2gW3Kc/LUr+Js2U0VKuxbIeirrxGjvGpZqcGXBKTxw/W1tW3650tR+TzSb/OmKywLngoVHlelhyuWfK1NKvx4C71GTaa/QYAAOASs3TZ9MSY1qlJB4bN1zDnCNntdkk3aZ97l0Ymno0BupuwsBDNnHJ5l2y77f1mOvsNAACABSwtqMJCWu/zSEoedd7rSVPHWJQREPzYbwAAAIJH8DyHCgAAAAC6GQoqAAAAAOgkS6f8eVskd43/mMSY1ilOADonkP1MYl8DAADoDEsLKncNz9MBPtHc3KItu47rRE37D//tjED2M4l9DQAAoDMsLajOVZm/Uj6jSZEJLnmrKxQ7Y6HVKQGXzJsfHNa3f/W+Dh6pl9do0a79NXox90YNHRRlel/sawAAAOYJngk+NpuM2mMKCY9U/ylzrc4GuGRONzXrmz9/Vzv3VavupKFv/udYbdh2VAseerPDtnUNTfpezgd6obA08A7Z1wAAAExjakFVWFionJwcjRs3Ttu3b5fb7dYzzzwTUNtQxyANnLFQ9TvfVVNlqZlpAUGt8P3D2n+o7sz/nXHRkqQ9B2pVf9Lrt+3/ZL2rZf+3TYt+/o5Kz9mGP+xrAAAA5rH5fD6fWRtbtWqVFi1apCeeeEI33HCDjhw5osbGRn3xi188Ly43N1cej0d1jnhtSV7sd5uTNq+Qo67Mb8x69xClJlZcdP6AFfYf66uXPr5C9901Qc64aKWmDNX6TUdUcbRaJw+sUZi9/V30leLLtbN8gMLszfqva/fI0cf4TEwg+5kU2L4GAADQGzidTmVkZAQUa2pBlZ2dLcMwlJKSooaGBjU2NurEiRO677772owvrjJnUYoly4qUs3RaJ7MGrOX1tmjCHS+opLR1Kb7lD07VA49s0E3XDdMrv7/Zb9tTjYaW/3mbPio5rtU5N7YZE8h+JrEoBQAAQGeYuihFZmamCgoKNG7cOMXHx5u5aaDHCgsL0TO/mq6v//QdHa48qara05oxeaj+mj2zw7aRfUL1o0WTtGRZ0SXIFAAAAJ9m+ip/aWlpF9ymPC9L/SbOltFQraajHvUZNlqO8almpwYErcnjB+ujf9ymPQdqFdUnVFn3JXdJP+V5WXK4ZsnX0qz6He8oeuz17GsAAAAXwdJl0xNjWqcZHRg2X8OcI2S32yVJ+9y7NDLxbAzQG9hsNl3lNP8L/8l+Jn16X5vOvgYAAHCRLC2owkJa79lISh513utJU8dYlBHQ83yyn0nsawAAAGYLnudQAQAAAEA3Q0EFAAAAAJ1k6ZQ/b4vkrvEfkxjTOmUJwKUTyL4psX8CAABYWlC5a8x5DhXQW1UcP6V/vlMmT3m9Wlp8CgmxmbLdQPZNif0TAADA0oLqXJX5K+UzmhSZ4JK3ukKxMxZanRIQ1H75x4/0++d26mDFSYXabUqZv1b//O1NGhIbaWo/7JsAAADtM3WyTmFhoXJycjRu3Dht375dTz31lIqLiwNrbLPJqD2mkPBI9Z8y18y0gB5n/8E6/eZvO3Sw4qQk6dtfGactO4/raz/p+LLSxyXHteChN/TMut2Bdca+CQAA0C5Tr1CVlJQoPT1dUVFRkqQhQ4aovr4+sEQcg+SYMFM1G/Nlj4pRZMIEM1MDepSn1+3WkWOnzvzfGRctSdrt6fjGp/uzi/TmpiN6Z0uFbvt8gqKjwvzGs28CAAC0z+bz+XxmbSw7O1uGYSglJUUNDQ2Ki4tTWVmZ5s2bd15cbm6uPB6P6hzx2pK82O82J21eIUddmd+Y9e4hSk2suOj8ge7io7IBeqMkTukLxssZF63UlKF6et0ePfviZt1z7V6/bfO3DtfuyhhFhXv19Rt2yx7y2SEgkH1TCmz/BAAA6G6cTqcyMjICijW1oJKkgoICuVwuxcfHdxhbXGXOohRLlhUpZ+m0C8gS6N7qGpo0ad6L2ltWJ0la/uBUfT93o+77ylgt72BfON3UrHVvHtC/3j+oP/zkc23GBLJvSixKAQAAYPqCx2lpaQEVUwA6z9E3XH9/eJamTrhM8UP76mSjV1+7PVEPL5nSYduIcLu+PHtEh1P9AAAA0LGgWOWvPC9L/SbOltFQrZN7Nyt67PVyjE+1Oi0gqKUkDVLRs7fqVKOh8LAQ2e1d80Co8rwsOVyz5Gs21LDrffUdcy37JwAAwP/P0oIqMaZ1ytCBYfM1zDlCdrtd0k3a596lkYlnYwC0L7KP+bvxJ/um9On9M5X9EwAA4ByWFlRhIa33XyQljzrv9aSpYyzKCIB0dt+U2D8BAAD86Zo5QgAAAADQC1BQAQAAAEAnWTrlz9siuTt4DmliTOv0IwDBLZD9WWKfBgAAPYulBZW7xpznUAEIjM/n0xsby/XSGx7t2Fet003Nigi3m7LtQPZniX0aAAD0LEGxbLokVeavlM9oUmSCS97qCsXOWGh1SkCP0tLi0233F+qNjeWqa/AqJESactdLKvzDzbpsYKSpfbE/AwCA3sLUiTeFhYXKycnRuHHjtH37dq1Zs0ZFRUWBNbbZZNQeU0h4pPpPmWtmWgAkvfBaqf5ddEh1DV5J0n3zk7TVfUL3P7yhw7b/96Jb//GtV/TkCyWBdcb+DAAAeglTr1CVlJQoPT1dUVFRkqTS0lLFxsYGlohjkBwTZqpmY77sUTGKTJhgZmpAr/f3f+7TqcbmM/93xkVLkkpKqzts+8ift6l4b7VKD9fra7eP7jCe/RkAAPQWNp/P5zNrY9nZ2TIMQykpKWpoaFBERIROnDihu++++7y43NxceTwe1TnitSV5sd9tTtq8Qo66Mr8x691DlJpYcdH5Az3ZevdgfXjgMqUvSJIzLlqpKUP19Lo9Wp3/ge6cXOq37dqP4nXgRF85+nj139ftbTMmkP1ZCmyfBgAAsJLT6VRGRkZAsaYWVJJUUFAgl8ul+Pj4DmOLq8xZlGLJsiLlLJ12AVkCvU/F8VO6duFL2n+oXpKUviBJz+bv0eM/vl53fGGE37Zeb4v2HqzV757bqdzMa9uMCWR/lliUAgAA9CymL16clpYWUDEF4NIaEhupNY/eqJmT4zRmRIze/6hCK743tcNiSpLCwkI0ZkR/2UNslyBTAACA7iMoVvkrz8tSv4mzZTRU69S+Leo75lo5xqdanRbQ41w9OlavPzmny/spz8uSwzVLvpZmGdUVCo0ZzD4NAAB6JEsLqsSY1uk/B4bN1zDnCNntdkk3aZ97l0Ymno0BEPw+2Z+lT+/TYp8GAAA9lqUFVVhI670UScmjzns9aeoYizIC0Fmf7M8S+zQAAOg9TL+HCgAAAAB6C0uvUHlbJHeN/5jEmNa/fAPoeRgDAABAd2dpQeWuMWfZdADdE2MAAADo7oJilT8Awav+pFeP/mW7Pth2VEerG1XX0CRH33Cr0wIAAAgKQVNQVeavlM9oUmSCS97qCsXOWGh1SkCvV117WjPufVlbd5/QJ48Av/6efK3/U5oG9IswtS/GAAAA0B2ZemdCYWGhcnJyNG7cOG3fvl0ffPCBli9fHlhjm01G7TGFhEeq/5S5ZqYFoJOyHv9IH7vPFlPpC5K0bXeVfvrbDztse3/2+5q24CU98XxJYJ0xBgAAgG7I1CtUJSUlSk9PV1RUlCRp0qRJqqioCCwRxyA5JsxUzcZ82aNiFJkwwczUAHTCRyXHz/u/My5akrRtd5XfdvUnvXruX/tVfvSUQkJs+vodozvsizEAAAB0Rzaf75O/PV+87OxsGYahlJQUNTQ06LLLLtO4ceMUGxt7Xlxubq48Ho/qHPHakrzY7zYnbV4hR12Z35j17iFKTQyscAMQuFe2D9POI/2VviBJzrhopaYM1dPr9ujVwnc1Z8Khdtv5fNKLH12hwzVRmjDshKZfVdlmnFljAAAAgJmcTqcyMjICijW1oJKkgoICuVwuxcfHdxhbXGXOCl9LlhUpZ+m0C8gSQCBKD9Vp5tdeVunhekmtU/7Wvu7Ra0/crCvjY/y29fl8yvj1+3rs+9e1G2PWGAAAAGAV0xelSEtLu+A25XlZ6jdxtoyGarWcqlVozGA5xqeanRqAC5QwzKGXfztbmSs2quJ4o/aV1apg1Rc6LKYkyWazKTQ0sNs0y/Oy5HDNkq/ZUO2Hr6jfNTczBgAAgG4hKFb5GzB9viIGj5DNbpckNR7cZXFGAD4xduQAvbRydpf2ce4Y4BifyhgAAAC6DUsLqsSY1uk80qhP/WTMeTEAeibGAAAA0N1ZWlCFhXBvBNCbMQYAAIDuztTnUAEAAABAb2LpFSpvi+Su8R+TGNP6V2wAkBg3AABAcLG0oHLXsGQygAvDuAEAAIJJUKzyB6BnKdlfrR/9ZrPe/7hSp5ualXVfigbGRFidFgAAgOmCpqCqzF8pn9GkyASXvNUVip2x0OqUAHTCxyXHdct3/62yIw2SpN/m7dLbH1bovWduUXRUmKl9MW4AAACrmXqXQWFhoXJycjRu3Dht375deXl5WrNmTWCNbTYZtccUEh6p/lPmmpkWgEvooUc3nSmm0hckSZK276nSY88W+23X5G3W7EWvaMytq/XkmpLAOmPcAAAAFjP1ClVJSYnS09MVFRUlSTp9+rS8Xu9n4nJzc+XxeFTniJeSF7cm4hgkx4SZqtmYL3tUjCITJkiSHn10hRx1ZX77Xe8eoiXlz5n5VgB00pZtIyRFKX1Bku65ZZSccdHylNfryb+/oWM7n2633bH6CL22YaRafCH65WMvq/jtx9uMM2vcAAAAaI/T6VRGRkZAsTafz+czq+Ps7GwZhqGUlBQ1NDSopaVFzc3NuvPOO9uML64y5+byJcuKlLN0WiezBmCmW+77l/Lfai1mlj84VQ88skF2u/S/6ZO19Kuudtt5vS26Y8lreu/jCj2Wea3uSruyzTizxg0AAAAzmHqFKjMzUwUFBRo3bpzi4+PN3DSAbuLhJZO1fU+VSg/Xy1NeL0lyXRWr73xlnN92YWEhemnlF7RkWVG7xRQAAECwMX1RirS0tAtuU56XpX4TZ8toqFb99jfV75qb5RifanZqAC6BsSMHaP2f0vST336oHXur9NC9Lv3gG1crKtLc4aY8L0sO1yz5WppVv+MdRY+9nnEDAABcckGxyt+A6fMVMXiEbHa7Yq65SY0Hd1mdEoCLcEVctP6UNb1L+zh33HAkTWfcAAAAlrC0oEqMab3XQRr1qZ+MOS8GAD7BuAEAAIKJpQVVWAg3jgO4MIwbAAAgmJj6HCoAAAAA6E0svULlbZHcNf5jEmNa/yINAJ3FWAMAALqKpQWVu4bnyQDoeow1AACgqwTFKn+SVJm/Uj6jSZEJLnmrKxQ7Y6HVKQG4hP768l6t+vsO7TlQq8OVJ7Xy+9fqsoGRpvfDWAMAAMwUNAWVbDYZtccUEh6p/lPmWp0NgEvoj8+XKHPFB6qqbZIk5b26Xzv312jj325VeJjdb9vG04ZON7UoxhEeWGeMNQAAwESm3jFQWFionJwcjRs3Ttu3b9fLL7+sp59+OqC2oY5BGjhjoep3vqumylIz0wIQ5B5/bueZYip9QZIkaef+av3t5b1+2x080qDkO9dqwu0v6Nn8PQH1xVgDAADMZOoVqpKSEqWnpysqKkqSdNlll+nDDz/8TFxubq48Ho/qHPFS8mJJ0sDpX5EkRV6RdF7so4+ukKOuzG+/691DtKT8OTPeAgAL7POMkhSh9AVJuueWUXLGRctTXq/H/rhGH6+vaLfdrvJ+2rEvXpL0y8de1ObXD7cZZ9ZYAwAAegen06mMjIyAYm0+n89nVsfZ2dkyDEMpKSlqaGhQQkKC9uzZo3nz5rUZX1xlzo3iS5YVKWfptE5mDcBqM75aoPWbj0iSlj84VQ88skExjnDlr/yCbrhmaLvtTjc16+4frFfR1gq98vubNW5k24OFWWMNAADAp5k65S8zM1MTJ07UuHHjdPvtt+uaa65pt5gCgE88mjlNI4ZHS5I85fXqG2nXjdMu1/WThvhtFxFu13OPzNKXvzCi3WIKAACgK5m+KEVaWtoFtynPy1K/ibNlNFTr5N7Nih57vRzjU81ODUCQmjgmVhv+cquWP71NpYfq9feHZylterxsNpup/ZTnZSk6abqaG6rVVOlR5IirGWsAAMBFCYpV/gZMn6+IwSNks9sVc81Najy4y+qUAFxilw2M1K/vn9KlfZw71khirAEAABfN0oIqMab1vgVp1Kd+Mua8GAC4GIw1AACgq1haUIWFcBM4gK7HWAMAALqKqYtSAAAAAEBvYukVKm+L5K7xH5MY0/rXZQC4lBifAABAICwtqNw1PBsGQHBifAIAAIEIilX+JKkyf6V8RpMiE1zyVlcodsZCq1MCEMQMo0WLHy7S6x+U6/DRkyoprdFTP5+uIbGRpvfF+AQAANoTPJNVbDYZtccUEh6p/lPmWp0NgCD3rax39fjqEu3YV63quia9/PZBzfn2q2pp8XXYdv/BOu07WBt4Z4xPAACgHaYWVIWFhcrJydHMmTO1du1arVu3Ti+88EJAbUMdgzRwxkLV73xXTZWlZqYFoIfxelv05qZyeY0WSVL6giRJUklpjd7aXO637T/fLtPUBS9pyl0v6cXXSgPqj/EJAAC0x+bz+Tr+c26AVq1apUWLFunxxx/X8OHDFRYWJkmaM2fOeXG5ubnyeDyqc8RrS/Jiv9uctHmFHHVlfmPWu4coNbHi4pIH0G00GSH68/tX6t4vT5IzLlqpKUO1ftMRecrrtfvjVzRmaPtXn97fd5mK9g2WJE1OOKobRlW2GWfW+AQAALofp9OpjIyMgGJNLaiys7NlGIYMw9CcOXN05MgRNTU16Y477mgzvrjKnJu+lywrUs7SaZ3MGkB3NOWutdq4/ZgkafmDU/XAIxt0xdC++vC5Lym2f592251qNPTtX76nDdsqtfGvc9U3KqzNOLPGJwAA0LOZuihFZmamCgoK5HK5FB8fb+amAeA8v/3h9Zr/vde171CdPOX1uvyySH33rnF+iylJiuwTqj9lTdeSZUXtFlMAAACBMn2Vv7S0tAtuU56XpZgpt8pbdUSnD5UocsTVcoxPNTs1AD1IStIgbfnHbfpL/h6dqDmtomdvVfzQaNP7Kc/LUnTSdDU3VKu5oUbhg52MTwAA4AxLl01PjGmdMnNg2HwNc46Q3X61pJu0z71LIxPPxgBAW6KjwvQ/88Z2ybY/Oz7ZJYnxCQAAnMfSgiospPX+g6TkUee9njR1jEUZAUArxicAABCI4HkOFQAAAAB0MxRUAAAAANBJlk7587ZI7hr/MYkxrVNvACDYMaYBAND7WFpQuWt4zguAS6+mrkmnm5pN3y5jGgAAvY+lBdW5KvNXymc0KTLBJW91hWJnLLQ6JQA9zNETpzQ/8w25PbWqqj2tHfuq9bfsmRo6KMr0vhjTAADoHYJn4onNJqP2mELCI9V/ylyrswHQA92+5DW9tqFcZUcadO9to/XmxiO6ffFrHbbz+Xz6x7/26Z0PjwTeGWMaAAC9gqlXqAoLC7V161atW7dO999/v7xer8aMGaPx48d3nIhjkBwTZqpmY77sUTGKTJhgZmoAejnP4Tq5S8/e4OSMa30I8O4DNdrtqdFVzvYfKvWrP36knz/+kaIjw/TSYzfq+muGdtgfYxoAAL2Dzefz+cza2KpVq7Ro0SI9/vjjGj58uK6++mrV19d/pqDKzc2Vx+NRnSNeW5IX+93mpM0r5Kgr8xuz3j1EqYkVF50/gJ7rREO48jaO0DfvvFrOuGilpgzV+k1HdKiiRpXufF3mON1u2zdKhuqjsljZ5FPahDJdNaSuzTizxjQAAGAtp9OpjIyMgGJNLaiys7NlGIYMw9CcOXNUVVWl+vp63X777W3GF1eZcwP3kmVFylk6rZNZA+gNfD6frv7yGm3bXSVJWv7gVD3wyAYlXdlfW5+/XSEhtnbbnjxl6Pu5G7V5xzG9/ecvymZrO9asMQ0AAHQfpk75y8zMVEFBgVwul+Lj483cNABcFJvNpid/doPu+eFb2newTocqG5To7KfHf3y932JKkqIiQ5X70LVasqyo3WIKAAD0Tqav8peWlnbBbcrzshQz5VY1151Q07EyhQ92yjE+1ezUAPRyk8cP1tbVt2v95nL5fNKvMyYrrAseClWel6XopOlqbqiW90S5+sSPZUwDAKCHsnTZ9MSY1ukvB4bN1zDnCNntdknSPvcujUw8GwMAZgkLC9GN04Z1ybYZ0wAA6H0sLajCQlrvJUhKHnXe60lTx1iUEQB0HmMaAAC9T/A8hwoAAAAAuhkKKgAAAADoJEun/HlbJHeN/5jEmNZpNADQ0wQyBkqMgwAABDNLCyp3Dc9sARD8mptbtNV9QlW17T/8tzMCGQMlxkEAAIKZpQXVuSrzV8pnNCkywSVvdYViZyy0OiUA0Nsflut/fv6eDlY2qMnbop37avRi7o0aOijK9L4YBwEA6H6CZxKJzSaj9phCwiPVf8pcq7MBADV5m/X1n7yjHfuqVVvv1Te/PEYbth3VXQ+92WHb+pNeff/RjXrxtdLAO2QcBACg2zH1ClVhYaG2bt2qdevW6f7779fAgQN14sQJzZ3b8YlBqGOQHBNmqmZjvuxRMYpMmGBmagBwwd74oFz7D9Wf+b8zLlqStMdTo9r6JvWLDm+37bey3tVfCvYqtn+EXKMHauTwfh32xzgIAED3Y/P5fD6zNrZq1SotWrRIjz/+uIYPH64bb7xRhYWFnymocnNz5fF4VOeI15bkxX63OWnzCjnqyvzGrHcPUWpixUXnDwDn8hzvqxc/ukL33TVBzrhopaYM1fpNR1RxtFr1nhcVEdrSbttXiy/XjvIBCrM3655pe9Uv0vuZmEDGQCmwcRAAAJjH6XQqIyMjoFhTC6rs7GwZhiHDMDRnzhwVFhbqxhtv1OTJk9uML64yZ1GKJcuKlLN0WiezBoC2eb0tmnDHCyopbV2Kb/mDU/XAIxv0hWmX619/+A+/bU81Gnr4T1v1cckJvfDojW3GBDIGSixKAQBAMDN1yl9mZqYKCgrkcrkUHx/fbiEFAN1BWFiInvnVdH39p+/oUOVJVdWe1vRrhuqv2TM7bBvZJ1Q/+dY1WrKs6BJkCgAArGL6Kn9paWkX3KY8L0sxU26Vt+qImir2q0/8WDnGp5qdGgBcsMnjB+ujf9wmd2mNoiJDlXVfcpf0U56Xpeik6WpuqNbpI/sUdeU1jIMAAHQDli6bnhjTOpXlwLD5GuYcIbv9aknSPvcujUw8GwMAVrLZbBo9or/p2/1kDJTOHQftkhgHAQDoLiwtqMJCWu8LSEoedd7rSVPHWJQRAFw6n4yBEuMgAADdVfA8hwoAAAAAuhkKKgAAAADoJEun/HlbJHeN/5jEmNZpMQCAwMZNibETAIBLxdKCyl1jznOoACDYHD1xSq++d0hl5fVqafEpJMRmynYDGTclxk4AAC4VSwuqc1Xmr5TPaFJkgkve6grFzlhodUoA0CnZT32sVX/fqbIjDQq12zR5/lq9/NubNCQ20tR+GDcBALCeqRNCCgsLlZOTo5kzZ2rt2rUqKirS6tWrA2tss8moPaaQ8Ej1nzLXzLQA4JLxHK5T7rPFKjvSIEn69lfG6cOdx3Xvj9/qsO323Sd09/ff1DPrdgfWGeMmAACWM/UKVUlJidLT0xURESFJuuKKK7Rjx47AEnEMkmPCTNVszJc9KkaRCRPMTA0ALoln1u1R+dFTZ/7vjIuWJO321HbYNv3XRXpjY7ne3HREc2c61S863G884yYAANaz+Xw+n1kby87OlmEYMgxDc+bMkdfrVUVFhW677bbz4nJzc+XxeFTniNeW5MV+tzlp8wo56sr8xqx3D1FqYsVF5w8AF+vjsgF6vSRO6QvGyxkXrdSUoXp63R795cXN+q9r9/ptm791uHZXxigq3Kuv3bBboSGfHZ4DGTelwMZOAADQNqfTqYyMjIBiTS2oJKmgoEAul0vx8fEdxhZXmbMoxZJlRcpZOu0CsgSArlF/0quJ/7lGe8vqJEnLH5yqhx7dqG/NG6Pch6712/Z0U7PWvuFR4fsH9YefTm8zJpBxU2JRCgAALhXTF9VNS0sLqJgCgJ4oOipMf394lqaMv0zxQ6J0stGrr37pKi1/cGqHbSPC7Zp300hF9/U/1Q8AAASPoFjlrzwvSzFTbpVRe0ynSrcq6spr5BifanVaANApKUmDtOGvt6r+pFd9wu0KDe2aB0KV52UpOmm6mhuq5a2uUJ9hoxk7AQC4xCwtqBJjWqelHBg2X8OcI2S32yV9XvvcuzQy8WwMAHRH0VFhpm/zk3FT+vTYKcZOAAAsYGlBFRbSOsc/KXnUea8nTR1jUUYAENw+GTclxk4AAIJB18xDAQAAAIBegIIKAAAAADrJ0il/3hbJXeM/JjGmdYoLAKBzAhlrJcZbAAA6w9KCyl1jznOoAKC78/l8envzEb34hkfFe6vU5G1WeJjdlG0HMtZKjLcAAHRGUCybLkmV+SvlM5oUmeCSt7pCsTMWWp0SAFwSLS0+fXnJa3rtg8OqrfcqJESaPP8lFf7hZl02MNLUvhhrAQAwl6mTOwoLC5WTk6OZM2dq7dq1crvdeuaZZwJrbLPJqD2mkPBI9Z8y18y0ACCovfTmAb363kHV1nslSffNT9JW9wllZBd12PYv+XuU9p1X9eQLJYF1xlgLAICpTL1CVVJSovT0dEVEREiSDhw4oAEDAps/EuoYJMeEmarZmC97VIwiEyaYmRoABK2/FuzVycbmM/93xkVLkkpKO77x6eE/bdW23VXaV1anr90+usN4xloAAMxl8/l8PrM2lp2dLcMwZBiG5syZo927d+vEiRO67777zovLzc2Vx+NRnSNeW5IX+93mpM0r5Kgr8xuz3j1EqYkVF50/AFjhrd2DtdlzmdIXJMkZF63UlKF6et0erc7/QHdOLvXbdu1H8fKc6Kt+fbz67+v2thkTyFgrBTbeAgDQGzidTmVkZAQUa2pBJUkFBQVyuVyKj4/vMLa4ypxFKZYsK1LO0mkXkCUABI/K46c0beFL2n+oXpKUviBJf8nfrd/+8DrdefOVftt6vS1ye2r0h9U7lfvQdW3GBDLWSixKAQBAZ5i+QG5aWlpAxRQAoNXg2Ei9sOJGzUgZqtEJMXp3yxEtWzylw2JKksLCQpQ0aoDsdtY7BwDACkGxyl95XpZiptwqb9URNR31qM+w0XKMT7U6LQC4ZCaOidUbT6V1eT/leVmKTpqu5oZqnTpQrOix1zPeAgBwESwtqBJjWqeYHBg2X8OcI2S3Xy1J2ufepZGJZ2MAAJ33yVgrnTve2iXNZbwFAOAiWVpQhYW0ztdPSh513utJU8dYlBEA9DyfjLUS4y0AAGZj0j0AAAAAdJKlV6i8LZK7g8esJMa0/nUVAHDpMD4DABAYSwsqd405y6YDAMzF+AwAQGCCYpU/AMCFazjp1cq/7dB7H1XoeHWj6k96FR0VZnVaAAD0KkFTUFXmr5TPaFJkgkve6grFzlhodUoAELRq65uU+tUCbd19Qi0tra9dd/c6vflUmgbGRJjaF+MzAADtM3X2e2FhoXJycjRz5kytXbtWTz31lIqLiwNrbLPJqD2mkPBI9Z8y18y0AKDH+eUfP9JHJWeLqfQFSdq2u0o/WbW5w7YPPLJB1y58SU88XxJYZ4zPAAC0y9QrVCUlJUpPT1dEROtfR4cMGaL6+vrAEnEMkmPCTNVszJc9KkaRCRPMTA0AepQPdxw/7//OuGhJ0vY9VX7bnTxlKO+VfTpUeVKS9PU7RnfYF+MzAADts/l8Pp9ZG8vOzpZhGDIMQ3PmzJFhGCorK9O8efPOi8vNzZXH41GdI15bkhf73eakzSvkqCvzG7PePUSpiRUXnT8AdBevbL9cO48MUPqCJDnjopWaMlRPr9ujV/79ntJcB9tt5/NJL350hQ5XRyppWLVmtDN2mjU+AwDQHTmdTmVkZAQUa2pBJUkFBQVyuVyKj4/vMLa4ypxVpJYsK1LO0mkXkCUAdG+ew3Wace/LKj3cOgsgfUGS1rxWqtf++B+6yhnjt63P51P6/76vlT+4rt0Ys8ZnAAB6OtMXpUhLS7vgNuV5WYqZcquM2mNqcG9Q9Njr5RifanZqANBjOC936OXfztb3cjaq4sQp7TlQo/zfzO6wmJIkm82msAAfIFWel6XopOlqbqhWY9lO9R1zLeMzAADnCIpV/gZMn6+IwSNks9vV7+rPq/HgLqtTAoCgN3bkAK37zewu7ePc8VlT5zI+AwDwKZYWVIkxrVNGpFGf+smY82IAAJcW4zMAAIGxtKAKC2H+PQAEI8ZnAAACY+pzqAAAAACgN7H0CpW3RXLX+I9JjGn9SykAILgxpgMAeiNLCyp3DcvyAkBPwZgOAOiNgmKVPwDApbHnQI3+3282650tFfIaLfrZt5M1MCbC6rQAAOi2gqagqsxfKZ/RpMgEl7zVFYqdsdDqlACgR9m++4TS7vuXDpQ3SJJ+87edWr/piN59+oty9A03tS/GdABAb2HqTPbCwkLl5ORo5syZWrt2rdasWaOioqLAGttsMmqPKSQ8Uv2nzDUzLQCApIdyN50pptIXJEmStu+pUu5fiv22a/I2a863XtXYuav15AslgXXGmA4A6CVMvUJVUlKi9PR0RUS0Th8pLS1VbGzsZ+Jyc3Pl8XhU54iXkhe3JuIYJMeEmarZmC97VIwiEyZIkh59dIUcdWV++13vHqIl5c+Z+VYAoMfZ9NEISVFKX5Cke24ZJWdctDzl9fpT3ps6UfJMu+2O10foXx+MUHOLXb9Y+U8Vv/N4m3FmjekAAFjN6XQqIyMjoFibz+fzmdVxdna2DMOQYRiaM2eOKisrdeLECd19991txhdXmXMD85JlRcpZOq2TWQNA73Drd/+ldetbi5nlD07VA49sUEiIlHVfsn7w9YnttvN6W3THkkK993Glch6cqntuvarNOLPGdAAAuhNTr1BlZmaqoKBALpdL8fHxZm4aAHCRshdP1rbdVSo9XC9Peb0kacJVA5VxV5LfdmFhIXpp5WwtWVbUbjEFAEBvZfqiFGlpaRfcpjwvSzFTbpVRU6mTezar75hr5RifanZqANCrjR05QG8+NUc/XvWhivec0IP/PUE/+sZE9Y0KM7Wf8rwsRSdNV3NDtXxGk0JjBjOmAwB6rKBY5W/A9PmKGDxCNrtd/SZ+QY0Hd1mdEgD0SM7LHfrzL7u2uDl3TJfEmA4A6NEsLagSY1rn00ujPvWTMefFAACCH2M6AKA3srSgCgvh5mQA6CkY0wEAvZGpz6ECAAAAgN7E0itU3hbJXeM/JjGm9a+eAICeh+MAAKC7s7SgctfwzBIA6M04DgAAurugWOUPABC8nnt1nx776w7t9tSo/OgpPfbQNF02MNLqtAAACApBU1BV5q+Uz2hSZIJL3uoKxc5YaHVKANDr/elFtx5c/oFO1JyWJP39lX3asa9aG/92q8LD7H7bNnmbdbqpWY6+4QH1xXEAANAdmTorvbCwUDk5OZo5c6bWrl2rDz74QMuXLw+ssc0mo/aYQsIj1X/KXDPTAgB00m//vvNMMZW+IEmStHN/tZ4t2Ou33eHKBl0z70Ul3faCnlm3O7DOOA4AALohU69QlZSUKD09XREREZKkSZMmqaKi4jNxubm58ng8qnPES8mLWxNxDJJjwkzVbMyXPSpGkQkTJEmPPrpCjroyv/2udw/RkvLnzHwrAABJe0tHSYpQ+oIk3XPLKDnjouUpr9fKP67Rtrc+O75/ouSIQ8V7r5Ak/WrlS9ryxqE248w6DgAAYCan06mMjIyAYm0+n89nVsfZ2dkyDEOGYWjOnDlqbGzUuHHjFBsb22Z8cZU5NyMvWVaknKXTOpk1AKA9M+8t0JubjkiSlj84VQ88skH9osP0Uu4XlDo5rt12p5uadfcP1uv9jyv08qrZmpDYtccBAACsYuoVqszMTBUUFMjlcik+Pt7MTQMALLDie9N0++JC7T9UL095vaL6hGrW5DhNTxnqt11EuF3PPTJLS5YVtVtMAQDQE5i+KEVaWtoFtynPy1LMlFtl1B5Tc/0JhcYMlmN8qtmpAQAu0MQxsSr6y6165M/btO9Qnf7yq1TNneWUzWYztZ/yvCxFJ01Xc0O1GkqK1O+amzkOAAC6haBY5W/A9PmKGDxCNnvrilGNB3dZnBEA4BODYyP18JIpXdrHuceB/lPnchwAAHQblhZUiTGtc+OlUZ/6yZjzYgAAPRPHAQBAd2dpQRUWwo3GANCbcRwAAHR3pj6HCgAAAAB6E0uvUHlbJHeN/5jEmNa/YAIAIHHsAAAEF0sLKncNzx8BAFwYjh0AgGASFKv8SVJl/kr5jCZFJrjkra5Q7IyFVqcEAOiE5uYWPfDIByosOqRDlSdVUlqjp34+XUNiI03vi2MHAMBqwTMhwmaTUXtMIeGR6j9lrtXZAAA66Tu/fE+/e26nivdWq7quSS+/fVBzvv2qWlp8Hbb1HK7T/oN1gXfGsQMAYDFTC6rCwkLl5ORo5syZWrt2rfLy8rRmzZqA2oY6BmngjIWq3/mumipLzUwLAHCJGEaLXvugXE3eFklS+oIkSVJJabXWbyz32/bf7x3UlAUvacpda7XmtdKA+uPYAQCwms3n83X8J8MArVq1SosWLdLjjz+u4cOHq6amRiEhIVq48PwpGLm5ufJ4PKpzxGtL8mK/25y0eYUcdWV+Y9a7hyg1seKi8wcAXBxvs03/994o3fvlSXLGRSs1ZajWbzoiT3m9Sra8qnGXt7+axPv7Bqlo3xBJUorzqD53VWWbcWYdOwAAaI/T6VRGRkZAsaYWVNnZ2TIMQ4ZhaM6cOfJ4PGpubtadd97ZZnxxlTk3Fi9ZVqScpdM6mTUAwExT73pJH2w/Kkla/uBUPfDIBsUP7avNf5+rywa2fx/VqUZD3/rFe9qwrVIb/zZX0VFhbcaZdewAAMAMpi5KkZmZqYKCArlcLsXHx2vy5Mlmbh4A0A389kfX6StLX9e+Q3XylNcrblCkvj1vrN9iSpIi+4Tq/34xXUuWFbVbTAEAEGxMX+UvLS3tgtuU52UpZsqtMmoqVbf1dfW75mY5xqeanRoA4BJIHjdIW/5xm55Zt0fHqhv1/l9ukfNyh+n9lOdlKTppupobqnXqQLGix17PsQMAcMlZumx6YkzrtIwDw+ZrmHOE7Ha7pC9on3uXRiaejQEAdC/RUWH61p1ju2TbbR875nLsAABYwtKCKiykdY57UvKo815PmjrGoowAAMGOYwcAIJgEz3OoAAAAAKCboaACAAAAgE6ydMqft0Vyt/9IEkmt8+DDKPsAABeB4w0AoKtYWlC5a3iWCADgrPqTXjV5m03fLscbAEBXsbSgOldl/kr5jCZFJrjkra5Q7IyFVqcEALhEjlU16q7MN7SrtEZVtae1Y1+N/vrrGRo6KMr0vjjeAADMFDyTG2w2GbXHFBIeqf5T5lqdDQDgEvryktf076LDKjvSoHtvG603PijXbfcXdtjO5/NpzWulevfDI4F3xvEGAGAiU69QFRYWauvWrVq3bp3uv/9+hYWF6dixY7rnnns6TsQxSI4JM1WzMV/2qBhFJkwwMzUAQJA6eKRBJZ6zNzg546IlSbsP1Kpkf7VGj+jfbtvsp7bqp7/7UH37hGlN7uc1PTmuw/443gAAzGTz+Xw+sza2atUqLVq0SI8//riGDx+uyy+/XK+++qp+9KMfnReXm5srj8ejOke8tiQv9rvNSZtXyFFX5jdmvXuIUhMrLjp/AMClV9UQrr9vGqFvzrtazrhopaYM1fpNR3ToSI2OuAs0pF9ju23fLBmiLWWDJPk0Z/xBjR5a22acWccbAEDv4HQ6lZGREVCsqQVVdna2DMOQYRiaM2eO7Ha79uzZo3nz5rUZX1xlzk3CS5YVKWfptE5mDQCwks/n08Qvr9HW3VWSpOUPTtUDj2zQ2JH9te3522S3tz87/eQpQw89ulGbdhzVu0/fIpvN1macWccbAAA+zdR7qDIzMzVx4kTde++9mjx5sq655pp2iykAACTJZrPpiZ/doNEJMQoPC9HBigYlOvvpdz+6zm8xJUlRkaF67PvXapprcLvFFAAAXcn0Vf7S0tIuuE15XpZiptwqo6ZSDbs3Knrs9XKMTzU7NQBAkJo8frC2PX+73th4WC0+n359f4rCw+ym91Oel6V+yXPkPX5QTZUeRY64muMNAOCiWLpsemJM6xSLA8Pma5hzhOx2u6QvaJ97l0Ymno0BAPR8YWEhmn3d8C7Z9mePN8mSxPEGAHDRLC2owkJa56snJY867/WkqWMsyggA0BNxvAEAdJXgeQ4VAAAAAHQzFFQAAAAA0EmWTvnztkjuGv8xiTGtUzUAALhUAjk+SRyjAAAWF1TuGp4LAgDovJYWn7bvqVJ17WlTtxvI8UniGAUAsLigOldl/kr5jCZFJrjkra5Q7IyFVqcEAAhi739coW/89F0dqmzQ6aZm7dxfozWP3qihg6JM74tjFACgPcEzUcFmk1F7TCHhkeo/Za7V2QAAgpjX26Kv/r+3VLy3StV1TfrGl8eoaOtRzc98o8O2J08Z+uFjm/Tia6WBd8gxCgDQDlOvUBUWFmrr1q165ZVX9M1vflMRERHyer26/fbbO07EMUiOCTNVszFf9qgYRSZMMDM1AEAP8tbmcu0/VH/m/864aEnS3gN1qq49rf79Itpt+61fvqunX9qj2P4RmpA4UFfG9+uwP45RAID22Hw+n8+sja1atUqLFi3Sww8/rKFDh2ro0KGSpDlz5pwXl5ubK4/HozpHvLYkL/a7zUmbV8hRV+Y3Zr17iFITKy4ueQBAt3HgeJTWfOTUfXdNkDMuWqkpQ7V+0xEdOVqtBs+Lightabftq8WXa0f5AIXZm7Vw6l71j/J+JiaQ45MU2DEKAND9OJ1OZWRkBBRrakGVnZ0twzBkGIZcLpdCQ0PV1NSkO+64o8344ipzFqVYsqxIOUundTJrAEB34/W2yPXlF7Rrf+tSfMsfnKoHHtmgWVPi9NoTc/y2PdVo6NdPfqyt7uNakzu7zZhAjk8Si1IAAEye8peZmamCggK5XC7Fx8ebuWkAAM4ICwvR07+crq//5B0drDypEzWNumHSEP0te2aHbSP7hOpn30nWkmVFlyBTAEBPZ/oqf2lpaRfcpjwvSwOun6fGQ7vUVOlR5Iir5RifanZqAIAeZPL4wfpo9W3aua9aUX1C9YvvpnRJP+V5WeqXPEfeE4fVXF+l8MFOjlEAgDMsXTY9MaZ1usSBYfM1zDlCdvtoSdI+9y6NTDwbAwBAW2w2m8Zdaf6cu0+OT9K5x6hkSRyjAADns7SgCgtpnXuelDzqvNeTpo6xKCMAAM4enySOUQAA/4LnOVQAAAAA0M1QUAEAAABAJ1k65c/bIrlr/MckxrROvQAAIJgFckyTOK4BQE9jaUHlrjHnOVQAAATqeHWj/v3+IZUdqVdLi08hITZTthvIMU3iuAYAPY2lBdW5KvNXymc0KTLBJW91hWJnLLQ6JQBAD5Pz9DblPlusA+UNCrPbNHn+Wr3825s0JDbS1H44pgFA72HqpIPCwkLl5ORo9uzZWr16tVavXq3t27cH1thmk1F7TCHhkeo/Za6ZaQEAoINHGrT8z9t0oLxBkvStr4zThzuP694fv9Vh2537qvRfP1qvZ/P3BNYZxzQA6DVMvUJVUlKi9PR0NTY2qra2VrNmzVJ9fX1giTgGyTFhpmo25sseFaPIhAlmpgYA6OWeyd+tw0dPnfm/My5akuT21HbY9rv/+75e21Cu1zccVtr0ePXvF+E3nmMaAPQeNp/P5zNrY9nZ2TIMQ4ZhyOVyqW/fvqqvr9ftt99+Xlxubq48Ho/qHPHakrzY7zYnbV4hR12Z35j17iFKTay46PwBAD3Xx2UD9HpJnNIXjJczLlqpKUP19Lo9+suazfqv6/b6bZu/dbh2V8YoKtyrr12/W6H2zx46AzmmSYEd1wAA1nI6ncrIyAgo1tSCSpIKCgrkcrkUHx/fYWxxlTmLUixZVqScpdMuIEsAQG9Tf9KrSf+5RnvK6iRJyx+cqswVH+ibXx6tVT+83m/b003Ner6wVG98cEh//On0NmMCOaZJLEoBAD2N6Qu3pqWlBVRMAQBwKUVHhelvD8/S5PGDNHxIXzWc8uqeW0cpN/PaDttGhNt115wr5egbfgkyBQB0J0Gxyl95XpYGXD9PjYd2qbmhRuGDnXKMT7U6LQBAD5OSNEgf/HWu6hqaFBFuV3iYvUv6Kc/LUr/kOfIePyjviXL1iR/LcQ0AeihLC6rEmNapDweGzdcw5wjZ7aMlSfvcuzQy8WwMAABm6oorTZ8c06Rzj2vJkjiuAUBPZmlBFRbSOo88KXnUea8nTR1jUUYAAHTOJ8c0ieMaAPQmpt9DBQAAAAC9BQUVAAAAAHSSpVP+vC2Su8Z/TGJM6zQKAAB6mkCOgxLHQgAIZpYWVO4ac55DBQBAV/H5fHr/40qtec2jHXur1ORtNm11wECOgxLHQgAIZkGxbLokVeavlM9oUmSCS97qCsXOWGh1SgCAXs7n8+nOB9/Qv4oOqaauSSEh0uT5L6nwDzfrsoGRpvbFcRAAuidTJxAUFhYqJydHs2fP1urVq/X2229r7dq1gTW22WTUHlNIeKT6T5lrZloAAHTKy2+X6eV3ylRT1yRJum9+kra6T+i7vy7qsO3fXt6rL973Lz25piSwzjgOAkC3ZGpBVVJSovT0dM2YMUO1tbW65pprAm4b6hikgTMWqn7nu2qqLDUzLQAAOuUv+XvUcMo4839nXLQkyV3a8Y1Pv37qYxW8VaZlT20NqC+OgwDQPdl8Pp/PrI1lZ2fLMAwZhiGXy6Vdu3bpxhtv1OTJk8+Ly83NlcfjUZ0jXluSF/vd5qTNK+SoK/Mbs949RKmJFRedPwAA53pn92Bt9Fym9AVJcsZFKzVlqJ5et0f/yN+or0ze77ft2o/iVXo8Wv0im/TV6/a2GRPIcVAK7FgIADCP0+lURkZGQLGmFlSSVFBQIJfLpfj4+A5ji6vMWZRiybIi5SyddgFZAgDQsaMnTmnqgpe0/1C9JCl9QZKeWbdbjz10rRZ+cZTftl5vi3bur9YTL+zSYw9d12ZMIMdBiUUpACCYmb4Ia1paWkDFFAAAwe6ygZF6YcWNSk0eqkRnP73z4RH9+v7JHRZTkhQWFiJX4kCF2lnvHAB6sqBY5a88L0sDrp+nxkO75D1Rrj7xY+UYn2p1WgAAaOKYWL35p7Qu76c8L0v9kufIe/ygTh/Zp6grr+FYCADdgKUFVWJM6zSGA8Pma5hzhOz20ZKkfe5dGpl4NgYAgJ7ok+OgdO6xMFkSx0IA6C4sLajCQlrnhCclnz91ImnqGIsyAgDg0vnkOChxLASA7oqJ3QAAAADQSZZeofK2SO4OHuWRGNP6FzwAAMCxEwCCjaUFlbvGnGXTAQDoLTh2AkBwCYpV/gAA6ElOnjL0u+d26O0PK3SsqlH1J72KjgqzOi0AQBcImoKqMn+lfEaTIhNc8lZXKHbGQqtTAgDggtU1NGnGvS/rY/dxNTe3vnbd3ev05lNpGhgTYWpfHDsBwHqmzrAuLCxUTk6OZs+erdWrV6uoqEirV68OrLHNJqP2mELCI9V/ylwz0wIA4JL53yc+1oc7zxZT6QuStG13lf7fyk0dts3M+UDX3b1Of3x+V2CdcewEAMuZeoWqpKRE6enpamxsVG1tra644grt2LEjsEQcg+SYMFM1G/Nlj4pRZMIEM1MDAOCS2FR87Lz/O+OiJUnb91b7bdd42tBf/7lXBytOqrmlRd+4o+Nl0zl2AoD1bD6fz2fWxrKzs2UYhgzDkMvl0pAhQ1RRUaHbbrvtvLjc3Fx5PB7VOeK1JXmx321O2rxCjroyvzHr3UOUmlhx0fkDAHCxXi2+XDvKByh9QZKccdFKTRmqp9ft0T///Z6+6DrYbjufT3rxoyt0uDpS4y6v0czRR9qMM+vYCQBon9PpVEZGRkCxphZUklRQUCCXy6X4+PgOY4urzFmpaMmyIuUsnXYBWQIA0DUOlNcr9asFKj1cL6l1yt+a10r16u9v1tiR/f229fl8+u7/vqff/OD6dmPMOnYCAMxh+qIUaWlpZm8SAIBu44q4aBWsmq3vrdioiuOn5C6t1trcL3RYTEmSzWZTeJi965MEAJgmKFb5K8/L0oDr56nx0C6dPrJPUVdeI8f4VKvTAgCgU8ZdOUD5v5ndpX2U52WpX/IceY8flLe6Qn2GjebYCQAWsLSgSoxpnZZwYNh8DXOOkN0+WpK0z71LIxPPxgAAgFafPXYmS+LYCQBWsbSgCgtpneOdlDzqvNeTpna8shEAAL0Rx04ACC6mPocKAAAAAHoTS69QeVskd43/mMSY1r/GAQCAzuF4CwBdx9KCyl3D0q8AAHQ1jrcA0HWCYpU/AAB6u/0H6/Sj32zS25sr1Nzs00+/fY0G9IuwOi0AQAeCpqCqzF8pn9GkyASXvNUVip2x0OqUAAC4JHbsrdKcb/9LnvLWhwE/9tcdemNjud59+oty9A03tS+OtwBgLlNnSxcWFionJ0ezZ8/W6tWr5Xa79cwzzwTW2GaTUXtMIeGR6j9lrplpAQAQ1B56dOOZYip9QZIkafueKq14Zrvfdl5vi75437807kvP68kXSgLrjOMtAJjK1CtUJSUlSk9PV2Njo2pra3XgwAENGPDZCdm5ubnyeDyqc8RLyYtbE3EMkmPCTNVszJc9KkaRCRMkSY8+ukKOujK//a53D9GS8ufMfCsAAFwyG7eMkBSl9AVJuueWUXLGRctTXq//e269qt1/abfdiYZwvbphpIwWu37x2D9V/M7jbcaZdbwFgN7C6XQqIyMjoFibz+fzmdVxdna2DMOQYRhyuVw6deqUTpw4ofvuu6/N+OIqc26SXbKsSDlLp3UyawAArDU3/d966c0DkqTlD07VA49skM0m/fzb1+hHiya1284wWnT74kK9+1GlHlkyRV+9LbHNOLOOtwCAzzL1ClVmZqYKCgrkcrkUHx9v5qYBAOixshdP1lb3CZUerj8z9W/CVQOUsTDJb7vQ0BC9tHK2liwrareYAgB0LdMXpUhLS7vgNuV5WRpw/Tw1Htolb3WF+gwbLcf4VLNTAwAgKI0Z0V9vPDlHP161Wdt2n9DihUn68f9MMn1BivK8LPVLniPv8YM6daBY0WOv53gLABcpKFb5GzB9viIGj1Cf4aMlSY0Hd1mcEQAAl1bCMIee/tWMLu3jk+OtbVSy+k+dy/EWAExgaUGVGNM6Z1sa9amfjDkvBgAAdB7HWwDoOpYWVGEh3AALAEBX43gLAF3H1OdQAQAAAEBvYukVKm+L5K7xH5MY0/qXNQAAcOlwjAaAwFhaULlreC4GAADBiGM0AAQmKFb5AwAAF+6FwlI9+pftKimtUcXxU3r0e9N02cBIq9MCgF4laAqqyvyV8hlNikxwyVtdodgZC61OCQCAoPWX/D26/+EiHa8+LUn668v7tH1PtT74662KCLf7bev1tui0t1nRUWEB9cUxGgDaZ+rM58LCQuXk5Gj27NlavXq1nnrqKRUXFwfW2GaTUXtMIeGR6j9lrplpAQDQ4zz21+IzxVT6giRJ0s791Xq2YK/fdhXHTir5Ky8q6UvP65l1uwPrjGM0ALTL1CtUJSUlSk9PV2Njo2prazVkyBDV19d/Ji43N1cej0d1jngpeXFrIo5BckyYqZqN+bJHxSgyYYIk6dFHV8hRV+a33/XuIVpS/pyZbwUAgKC2Z98oSRFKX5Cke24ZJWdctDzl9Vr5xIva/vaRdtu5KxzatvsKSdIvH3tJW9441GacWcdoAOiOnE6nMjIyAoq1+Xw+n1kdZ2dnyzAMGYYhl8uloUOHqqysTPPmzWszvrjKnBtelywrUs7SaZ3MGgCA7mfW117WGxvLJUnLH5yqBx7ZIEffMK159PP6/NRh7bY73dSshd9/U+9/XKn838zWxDGxbcaZdYwGgJ7O1CtUmZmZKigokMvlUnx8vCTp2muvNbMLAAAgacX3puq2+wu1/1C9POX1iuxj14yUoZo15XK/7SLC7frH8s9rybKidospAEDgTF+UIi0t7YLblOdlacD189R4aJdOHShW9Njr5RifanZqAAD0GFePjtX7f7lVy/60VfsP1+nPv0jVHTcmyGazmdpPeV6W+iXPkffEYTUeKFbfMddyjAaAcwTFKn8Dps9XxOAR6jN8tPpPnavGg7usTgkAgKA3JDZSjzw4tUv7+OQYbRuVLE25hWM0AHyKpQVVYkzr/Gtp1Kd+Mua8GAAAcGlxjAaAwFhaUIWFcDMrAADBiGM0AATG1OdQAQAAAEBvYukVKm+L5K7xH5MY0/pXMgAAENw4rgPojSwtqNw1POMCAICeguM6gN4oKFb5k6TK/JXyGU2KTHDJW12h2BkLrU4JAIAepbm5RZkrNuqVdw/qcOVJuT21evJnn9OQ2EjT++K4DqC3CJ6L7jabjNpjCgmPVP8pc63OBgCAHifj10Va+fcdKt5braq6JhW8Vab/+Naramnxddj24JEGlR6qC7wzjusAeglTC6rCwkLl5ORo9uzZWr16tdasWaOioqKA2oY6BmngjIWq3/mumipLzUwLAIBer7m5Rf8qOqSmphZJUvqCJElSSWm1Xt9w2G/b1zcc1uS71mryXS/phcLSgPrjuA6gt7D5fL6O/ywVoFWrVmnRokV6+OGHNXToUNXU1Cg5OVnTp08/Ly43N1cej0d1jnhtSV7sd5uTNq+Qo67Mb8x69xClJlZcdP4AAPRURrNNf3pvlO798iQ546KVmjJU6zcdkae8Xju3vKrxl7e/mkTR/kF6f+8QSVKy86imX1XZZpxZx3UAsJrT6VRGRkZAsaYWVNnZ2TIMQ4ZhyOVyKTw8XCdOnNDdd9/dZnxxlTk3ry5ZVqScpdM6mTUAAL3DtAUvacO2o5Kk5Q9O1QOPbNDwwVHalPclv/dRnWo09D+/eFcbtlbqg7/OVb/o8DbjzDquA0B3YuqiFJmZmSooKJDL5VJ8fLyZmwYAABdp1Q+v051LX9f+Q3XylNdraGykFs0b0+GiFJF9QvXnX6RqybKidospAOitTF/lLy0t7YLblOdlacD189R4aJcay3aq75hr5RifanZqAAD0asnjBmnLc1/Sn9fu1tHq03rvmVs0YrjD9H7K87LUL3mOvMcPymc0KTRmMMd1AD2WpcumJ8a0Xvo/MGy+hjlHyG4fLWmu9rl3aWTi2RgAAGAOR99w3XdXUpds+7PH9WRJ4rgOoEeztKAKC2mdR52UPOq815OmjrEoIwAA0Fkc1wH0RsHzHCoAAAAA6GYoqAAAAACgkyyd8udtkdztP/ZCUutc6zDKPgAAeiTOBQB0d5YWVO4anlcBAEB3cPKUoSZvs+nb5VwAQHdnaUF1rsr8lfIZTYpMcMlbXaHYGQutTgkAgF7vRM1pLXjoDe3YV62qmtPaua9Gz/56hoYOijK9L84FAHRHwXMB3WaTUXtMIeGR6j9lrtXZAAAASV9e8ppeefeQDpQ36Ku3jdbrH5TrSxmFHbbz+Xxa96ZH731UEXhnnAsA6IZMLagKCwuVk5Oj2bNna/Xq1frggw+0fPnygNqGOgZp4IyFqt/5rpoqS81MCwAAdMLhygbt2l995v/OuGhJ0p6yWu3cV912o//fI3/epv988A3d8t1/a/2m8oD641wAQHdk8/l8PrM2tmrVKi1atEgPP/ywhg4dqrvvvluvvPKKbrnllvPicnNz5fF4VOeI15bkxX63OWnzCjnqyvzGrHcPUWriBfwFDAAAdKjqZLjyNo7QN+ZdLWdctFJThmr9piM6eKRWR0ryNTSmsd22b5YM0ZayQZJ8ujnpoMbG1bYZZ9a5AACYyel0KiMjI6BYUwuq7OxsGYYhwzDkcrk0aNAgjRs3TrGxsW3GF1eZcyPqkmVFylk6rZNZAwCAtvh8Pk38zzXa6q6SJC1/cKoeeGSDxo7or20v3Ca7vf2JLidPGcp89ANtKj6m9565RTabrc04s84FAMAqpi5KkZmZqYKCArlcLsXHx5u5aQAAcInZbDY98dMbdPcP3tL+Q3U6eKReV13RT7/5wbV+iylJiooM1crvX6cly4raLaYAoCcwfZW/tLS0C25TnpelAdfPU+OhXfIZTQqNGSzH+FSzUwMAABdo8vjB2vb87XptwyF5DZ/+9/7Jigi3m95PeV6W+iXPkffEYTXsek/9rrmZcwEA3YKly6YnxrRexj8wbL6GOUfIbh8tSdrn3qWRiWdjAACAdcLCQnTzDV0z8+Sz5wLJkm7hXABAt2FpQRUW0jonOil51HmvJ00dY1FGAADgUuJcAEB3FzzPoQIAAACAboaCCgAAAAA6ydIpf94WyV3jPyYxpnU6AAAAQCDnDhLnDwAuHUsLKncNz54AAKAnamnxacfeKlXXNZm63UDOHSTOHwBcOpYWVOeqzF8pn9GkyASXvNUVip2x0OqUAABAJ2zcXqmv/eQdHaxoUOPpZu3aX6MXVnxeQwdFmd4X5w8ArBY8F8NtNhm1xxQSHqn+U+ZanQ0AAOgEw2jRPT98S9t2V6mqtknf+PIYvf9xpeZ/740O255qNPTjVZu19g1P4B1y/gDAYqZeoSosLNTWrVv1yiuv6Jvf/Kaam5sVHh6u2267reNEHIPkmDBTNRvzZY+KUWTCBDNTAwAAl8DbHx7R/kN1Z/7vjIuWJO0pq1VV7WkN6BfRbtvv/PI9/WntbsX2j9C4kf11lbPjB1Bx/gDAajafz+cza2OrVq3SokWL9PDDD2vo0KEKDQ1VSEiIFi48//J7bm6uPB6P6hzx2pK82O82J21eIUddmd+Y9e4hSk2suOj8AQDAxTlwIkovfnSFvjPfJWdctFJThmr9piM6crRG9aVr1Cespd22rxZfrh3lAxQa0qyFU/dpQN/P3n8VyLmDFNj5AwC0x+l0KiMjI6BYUwuq7OxsGYYhwzDkcrnU3Nys5uZm3XnnnW3GF1eZsyjFkmVFylk6rZNZAwAAsxhGiybc8YJ27W9dim/5g1P1wCMbNGPyUL3xZJrftqcaDf3vkx/r45LjWvvY7DZjAjl3kFiUAsClY+qUv8zMTBUUFMjlcik+Pt7MTQMAgG4gNDRET/9yuu79yTs6VNGg4zWNuvbqwfpb9swO20b2CdXPv5OsJcuKLkGmAGAO01f5S0vz/9entpTnZWnA9fPUeGiXGkqK1O+am+UYn2p2agAA4BKYPH6wtq6+TTv2VqtPhF2//G5Kl/RTnpelfslz5D1xWKc82xQ99nrOHwBccpYum54Y03pJ/sCw+RrmHCG7fbSkudrn3qWRiWdjAABA92Kz2ZQ0yvw5d5+cO0jnnj8kS7qF8wcAlrC0oAoLaZ3fnJQ86rzXk6aOsSgjAAAQzD45d5A4fwAQHILnOVQAAAAA0M1QUAEAAABAJ1k65c/bIrlr/MckxrRe3gcAAOiMQM43JM45AHSOpQWVu8ac51ABAIDur6r2tAqLDulQZYN8Pp9sNpsp2w3kfEPinANA51haUJ2rMn+lfEaTIhNc8lZXKHbGQqtTAgAAl8hjfylWzjPb5ClvUJjdpslfWauC396kIbGRpvbD+QYAs5l6YbuwsFA5OTmaPXu2Vq9erZdffllPP/10YI1tNhm1xxQSHqn+U+aamRYAAAhihysb9PD/bZWnvEGS9K2vjNPmncf11f/3Vodt3aU1+u8fvaVn8/cE1hnnGwBMZuoVqpKSEqWnp6uxsVG1tbVyOp368MMPA0vEMUiOCTNVszFf9qgYRSZMMDM1AAAQpJ4t2KtDlSfP/N8ZFy1J2u3p+Man7/zqPRUWHdZrGw5pzvR4DegX4Tee8w0AZrP5fD6fWRvLzs6WYRgyDEMul0tOp1N79uzRvHnzzovLzc2Vx+NRnSNeW5IX+93mpM0r5Kgr8xuz3j1EqYkVF50/AAC49LYd6q/Xdl6u7y4YL2dctFJThurpdXv0zJrN+u/r9vptm791mHZX9ldkmFdfu2G3wuyfPa0J5HxDCuycA0Dv4HQ6lZGREVCsqQWVJBUUFMjlcik+Pr7D2OIqcxalWLKsSDlLp11AlgAAIFg0nPRq4n+u0Z6yOknS8genKnPFB/rabYn6/Y9v8Nv2dFOz8l7Zp/WbyvXkz6e3GRPI+YbEohQAOsf0xUHT0tICKqYAAAAkqW9UmP728CxNHj9Iw4ZEqeGUVwvmXKmV37+uw7YR4Xbdc+tVinGEX4JMAeCzgmKVv/K8LA24fp4aD+3SqQPFih57vRzjU61OCwAAXCIpSYP0wV/nqqauSX0i7IoIt5veR3lelvpNnC2joVqnD5WoT/xYhcYMVkvTKUWPZqYLgM6xtKBKjGm9vH5g2HwNc46Q3T5a0lztc+/SyMSzMQAAoHfoiitNnz3fsEu6SZJ0urFRx49W6PJ4zjkAdI6lBVVYSOtc5aTkUee9njR1jEUZAQCAnqa9841WfaQ45yXPCUDPYfo9VAAAAADQW1BQAQAAAEAnWTrlz9siuTt4Zl9iTOulegAAgEslkHMUifMUABYXVO4ac55DBQAAeqcPtlVqzese7dxXLa+3RWEmVTeBnKNInKcACJJl0yWpMn+lfEaTIhNc8lZXKHbGQqtTAgAAQcrn8+muzDf16nsHVVXbpJAQafL8tfr3H27WZQMjTe2LcxQA/phaUBUWFmrr1q3atGmT/uM//kP9+/eX1+vV7bff3nFjm01G7TGFhEeq/5S5ZqYFAAB6mH+9f0j5b5Wp/qRXknTf/CQ99myxvvvr9/X3h2f5bfvcq/v0TP4e3TYrQffelthxZ5yjAPDD1Fm/JSUlSk9P13XXXacBAwbIbrerT58+AbUNdQzSwBkLVb/zXTVVlpqZFgAA6GGeeWn3mWJKkpxx0ZKkkv0d3/j0v098rPz1Zcp+6uOA+uIcBYA/Np/P5zNrY9nZ2TIMQ8OHD1ddXZ2cTqeampp0xx13nBeXm5srj8ejOke8tiQv9rvNSZtXyFFX5jdmvXuIUhMrLjp/AADQPbyzZ7A2ll6m9AVJcsZFKzVlqJ5et0fPrduo+VP2+2279qN4lR6PlqOPV/dev6fNmEDOUaTAzlMAdD9Op1MZGRkBxZpaUElSQUGBXC6X4uPjO4wtrjJnUYoly4qUs3TaBWQJAAC6s2NVjZqyYK32H6yXJKUvSNLTL+3Wiu9N1X/P9T+Nz+ttUfHeKj31Yokee+i6NmMCOUeRWJQCQBc8hyotLS2gYgoAAKCzBg3oo+eX36jpyUN11RX99PbmI/rFfdd0WExJUlhYiCaOiVWonfXOAVy8oFjlrzwvS9FJ0+WtrpBRdUSRI66WY3yq1WkBAIAgNmlsrNb/Ka1L+yjPy1K/ibNlNFTr9KEShQ2KVz/XLJ06uFPRo5kdA8DigioxpvVS+YFh8zXMOUJ2u12StM+9SyMTz8YAAABcSm2fo9wkSTrd2KjjR+N0eTznKQAsLqjCQlrnHScljzrv9aSpYyzKCAAAoP1zlFZ9pDjnJc8JQHBi8jAAAAAAdJKlV6i8LZK7g8dFJMa0/pUIAAAgmHFeA/ROlhZU7hpzlk0HAACwGuc1QO8UFKv8AQAAXAqNpw09/o9denPTER09cUr1J72KjgqzOi0A3VjQFFSV+SvlM5oUmeCSt7pCsTMWWp0SAADoQepPejXz3gJtKTmh5mafJOm6u9fpjSfnKLZ/H1P74rwG6D1MncVbWFionJwc3XXXXXrmmWe0evVqbd++PbDGNpuM2mMKCY9U/ylzzUwLAABA2U9t1aYdx88UU+kLkrRtd5V+tHJzh21/kLtJN9yzTk88XxJYZ5zXAL2GqQVVSUmJ0tPTdd1112nAgAFKSUkJuG2oY5AGzlio+p3vqqmy1My0AAAA9MG2yvP+74yLliTt2Fflt12Tt1l/yd+jdz+q1B9W7wqoL85rgN7D5vP5fGZtLDs7W4ZhaPjw4aqrq1NiYqLq6+t1++23nxeXm5srj8ejOke8tiQv9rvNSZtXyFFX5jdmvXuIUhMrLjp/AADQc/2r+HIVlw9Q+oIkOeOilZoyVE+v26OX//Webrn6YLvtfD7pxY+u0KHqKI2Nq9bnxxxpM86s8xoA1nM6ncrIyAgo1tSCSpIKCgrkcrkUHx/fYWxxlTmr4SxZVqScpdMuIEsAANDbHCivV+pXC1R6uF5S65S/Fwr365Xf3aykUf5PNnw+n+771Xta9cPr240x67wGQPdi+qIUaWlpZm8SAADgol0RF62CVbO1NOcDVRw7pV37qrXm0Rs7LKYkyWazKSLcfgmyBNDdBMUqf+V5WYpOmq7m+io1n6xV+GCnHONTrU4LAAD0MOOuHKCCVTd1aR/leVnqN3G2jIZqnT5UoohhiYoYPEJGQ5X0OWbUAD2NpQVVYkzrpe8Dw+ZrmHOE7PbWv/zsc+/SyMSzMQAAAMGu7fOa1uLtdGOjjh/tw3kN0ANZWlCFhbTOI05KHnXe60lTx1iUEQAAQOe0d17Tqo8U57zkOQHoeqYumw4AAAAAvYmlV6i8LZK7xn9MYkzrX3wAAAB6Gs6FgO7P0oLKXcPyogAAoPfiXAjo/oJilT8AAIBg5Tlcp//3m816c9MRNTf79NNvX6MB/SKsTgtAkAiagqoyf6V8RpMiE1zyVlcodsZCq1MCAAC9nLu0Rjf9zytnHgb82F936I2N5Xrnz19Uv+hwU/viXAjonkydkVtYWKicnBzdddddeuaZZ/T2229r7dq1gTW22WTUHlNIeKT6T5lrZloAAACdkvnoxjPFVPqCJEnS9j1VWvHMdr/tDKNFt37330r60vN68oWSwDrjXAjolkwtqEpKSpSenq7rrrtOAwYM0DXXXBNw21DHIA2csVD1O99VU2WpmWkBAAB0SvnRk2f+7YyLliT5fNKm4mN+2+07WKfXPzisHfuq9Y9/7w+oL86FgO7J5vP5fGZtLDs7W4ZhaPjw4aqrq1NdXZ1uvPFGTZ78/7V37/FRlmf+x7+TydkMARKBCJMJSIfDQASCgFgJ2hZro+JhF4tQt7bdtd21yU8qZXtw291sDykSTJGubrVVqG3TRS2QWKupNSoaBETQABmOQwgh4ZDTBHJ4MvP7I6+i2GQyhCeZIfm8/yLDdT33xevFH9eV+577ufaCuIKCAnk8HjXZ7NqZ8VDAZ07fsVq2psqAMaXukcp01lxy/QAAAB+3cZddh04OUfYSl+67bbxKt5+Qp7pJW99+XXOvPtltns8nbdqdqprGWM0dV6upY+q7jDOrFwJgLofDoZycnKBiTR2oJKm4uFjp6emy2+09xpbXmXOzzbKVZcpfPuciqgQAAOhZxeF6ff4bf9aR415lL3Hp58+Va+r4YXprXXDfoeqpRzGrFwIQOqZfSpGVlXXROdWFuUpwzVN7fY06ms4o1j5JtimZZpcGAABwUSaMHaq/Pv0Fff/xHfrAfUbfXDxZP/zXGaZfSFFdmKsh0xbIaK5Xa1WFYh1TZI25Qn75pRv4pTEQzsLilr9h8xYrZsRYWaxWSVLLsX0hrggAAKBT2mibfvOT+X26xgW90IybJUm+tha11/OVBiDchXSgciZ2bmNL4z/xNxMviAEAABiIuu+FJClWkoNeCAhzIR2ooiI4EwwAAAYveiHg8mfqtekAAAAAMJiEdIeq3Se5GwLHOBM7f3sDAAAA+icg3IR0oHI3cFUoAADAxaB/AsJLWNzyBwAAMJBsft2jR5/9UPsO16v2TIse+/YcJQ+LDXVZAPpA2AxUtUVr5DfaFJeWrvb6GiXNXxrqkgAAAC7a7/90UN/8yTs6Vd8qSXqu+KA+2H9G7/52oWKirQFzDcOntnaf4uOCa9Hon4DQM/V0bUlJifLz83Xvvfdq/fr1Kisr04YNG4JLtlhkNJ5SRHSchs5aaGZZAAAA/Wb1+vLzw1T2Epckae+hBq3bvD9gXu3ps5r5xY2adMcGrdsUOPY8+icg5EzdoaqoqFB2draeeOIJDRs2TKmpqdqzZ8/fxRUUFMjj8ajJZpcyHuosxJYs29Qb1bCtSNb4RMWlTZUkPfbYatmaKgOuW+oeqWXVfzDznwIAANArBw5fLSlW2Utcuu+28XKkJMhT7dXjT2/S3i3/231ebYJ2uR2SpB+v2aT3X6/qMs6s/glA9xwOh3JycoKKtfj9fr9ZC+fl5ckwDI0ZM0ZNTU2aMWOGampqdOedd3YZX15nzpcql60sU/7yOb2sGgAAwDw3fe0l/fXdaknSqodn61uPblVCfKQ25H9GN88d021ea1uHlvz76yrbXas/FnxWM11XdhlnVv8EwBym7lCtWLFCxcXFSk9Pl91uN/PRAAAAl4XVy2frzv9XosNVXnmqvYqNtuqGGaO04LrRAfNioq3akP8ZLVtZ1u0wBSD8mH4pRVZW1kXnVBfmKsE1T0bjKbWdPKr4q2fINiXT7NIAAAD63DUTkvTOb25X3tO7dPi4V7/OvUH/uGCsLBaLaWtUF+ZqyLQFMprr1VpVoSsmXS9fi1eWqBglTODUDtCfwuKWv2HzFitmxFhZrJ0337Qc2xfiigAAAHpvZFKc8r/dd4PNBb3TjJslSb62FrXX1/TZmgC6FtKBypnYecZXGv+Jv5l4QQwAAAA6OROlwkWf7J0kKVaS43wMgP4R0oEqKoIvTAIAAFwM+icgvJj6HioAAAAAGExCukPV7pPcDYFjnImdv4kBAABA79BzAX0npAOVu4H3KAAAAPQ1ei6g74TFLX+SVFu0Rn6jTXFp6Wqvr1HS/KWhLgkAAKBf+Hx+fadgm/701jEdq2nW/qONeuqHN2hkUpzpa9FzAeYKn41di0VG4ylFRMdp6KyFoa4GAACg3zz0szIVPLdHH+yvU11jm4pKK3XLN/4sn8/fY+7x2mZ5jjcFvxg9F2AqUweqkpIS5efn695779X69evldru1fv36oHIjbckaPn+pvHu3qK32iJllAQAAhC2fz6+Xt1Spta1DkpS9xCVJqjjSoFffqQqY+8aOal27eJNmLt6k5189HNR69FyAuSx+v7/nX30Eae3atXrggQf0xBNPKC0tTbGxsWppadGtt956QVxBQYE8Ho+abHbtzHgo4DOn71gtW1NlwJhS90hlOnmRHQAAuPwYPoue2TJe9//DdDlSEpQ5c5RKt5+Qp9qr8h2vKH1Mfbe57x5O0paDoyRJM1JPddsPmdVzAYOFw+FQTk5OULGmDlR5eXkyDENjxoxRU1OThg8frjNnzujBBx/sMr68zpwvSC5bWab85X33NnIAAIC+dN3STSrbfVKStOrh2frWo1s1ekS83v3t7bpqxBXd5p1rMfT13C0q212rd3+7UIm26C7jzOq5APw9Uy+lWLFihYqLi5Weni673W7mowEAAAasNd+Zqy9++zUdOtYkT7VXI4bH6mt3TQg4TElSXGyknv1RppatLOt2mALQt0y/5S8rK+uic6oLc5Xgmqf2+hp1NNcrdvQE2aZkml0aAABAWJrpStbOP9yhX73oVs3pFm1Zd5vGpw4xdY3qwlwNmbZARnO9WqsqFJk4QvHjpstorlPCBE76AL0V0mvTnYmd28tHRy/WaMdYWa1WSdIh9z6Nc34UAwAAMNDZrohWztIpffJsZ6L01LKP91s3S5JaW1p0+mSsrrLTcwG9FdKBKiqi86yuK2P8BZ+7Zk8MUUUAAAADT1SEdMsn+q1OsVKKo9/rAQaS8HkPFQAAAABcZhioAAAAAKCXQnrkr90nuRsCxzgTO7epAQAA0H/o04DghHSgcjfwTgQAAIBLca7FULvhM/259GlAcEI6UH1cbdEa+Y02xaWlq72+Rknzl4a6JAAAgLBV19iqpd95XeUH63WmoVV7DtbruZ/O16jkeNPXok8Duhc+m7QWi4zGU4qIjtPQWQtDXQ0AAEBYW/Twa3rpzWPyHPfq/juceu3dat2RUxJU7p/erFTZ7trgF6NPA7pl6g5VSUmJdu/ere3bt+uWW25Re3u7Zs+eLZfL1XMhtmTZpt6ohm1FssYnKi5tqpmlAQAADBgnTp3VnoP15392pCRIkvYfbdCeg3WafHX35/BWr/9Q3y3Yrvi4SG1YdZNunHVVj+vRpwHds/j9fr9ZD1u7dq0eeOABPfHEE0pLS5PFYlFycrJmz559QVxBQYE8Ho+abHbtzHgo4DOn71gtW1NlwJhS90hlOmsuuX4AAIDLQf3ZKP1+2zj986Jr5EhJUObMUSrdfkLHTjSquqJYKYnnus0tdY/Ue0eTJfm1YHKVXFd1ffOEWX0acDlyOBzKyckJKtbUgSovL0+GYWjMmDFqampSRkaGKisrtWjRoi7jy+vM+bLjspVlyl8+p5dVAwAAXF78fr+m/eMftdt9RpK06uHZ+tajWzUxLVEfvHCXIiO7/1bH2XOGvr36XW378KTe+c3tioiwdBlnVp8GDHSmHvlbsWKFiouLlZ6eLrvdLkm67rrrzFwCAABg0LNYLHrqh9dr6XdKdbjKq8oTXo2321Tw73MCDlOSFB8Xqce/O1fLVpZ1O0wBCJ7pt/xlZWVddE51Ya4SXPNkNJ1Wy7F9Sph0vWxTMs0uDQAAYMC4dsoIffDCXXr17eNq7+jQj7NnKi7W3NauujBXQ6YtkNFcr9aqCkUljVZMynj52s4pYQKngwApxNemOxM7t4qPjl6s0Y6xslqtkqRD7n0a5/woBgAAAH8vOsqqrEx7nzzbmSg9tezjPdrNkqTWlhadPlmjq+z0aYAU4oEqKqLz3K0rY/wFn7tmTwxRRQAAAJA6+7RbPtGjdYqVUhz9Xg8QrsLnPVQAAAAAcJlhoAIAAACAXgrpkb92n+Tu+tUH5zkTO7ecAQAAEL6C6eskejsMPCEdqNwNvN8AAACgP/n9fu073KCGpjZTnxtMXyfR22HgCelA9XG1RWvkN9oUl5au9voaJc1fGuqSAAAABpQde07pK//xho7VnNW5VkP7jjTo+fzPaFRyvOlr0dthsAifDVeLRUbjKUVEx2norIWhrgYAAGBA6ejw6UvffV273XU609Cqf757ot5+v1ZfXP7XHnNbWg395/+8p82ve4JfkN4Og4SpO1QlJSXavXu3tm/frltuuUUJCQlKSUnRnDk9v/gt0pYs29Qb1bCtSNb4RMWlTTWzNAAAgEHtnV21OlzlPf+zIyVBknSgslGn61uUNDS229xv/uQdPfWCW8MTY/TO+kQ504b2uB69HQYLi9/v95v1sLVr1+qBBx7QE088obS0NO3fv18ZGRmaN2/eBXEFBQXyeDxqstm1M+OhgM+cvmO1bE2VAWNK3SOV6ay55PoBAAAGqmN18XrhPYf+7d6pcqQkKHPmKJVuP6ETtQ1qOvJHxUV3dJv7yp6rVH58mKwRPi2ZdVBJCX///atg+jopuN4OCDWHw6GcnJygYk0dqPLy8mQYhsaMGaOmpiaNHTtWZ86c0Ze+9KUu48vrzLmUYtnKMuUv73kXDAAAYLAyDJ+m3v2C9h3uvIpv1cOz9a1Ht+qGGSP1xjO3Bsw912Lox0+9r/f3ndbmx2/uMiaYvk7iUgoMPKYe+VuxYoWKi4uVnp4uu91u5qMBAABwCSIjI7TuR/P0lf94S8dqmnW6/pxmT71Sv//ZjT3mxsVGKvfBmVq2sqwfKgUuL6bf8peVlXXROdWFuUpwzZPRUKvW6oO6YuJ1sk3JNLs0AACAQe3aKSO0a8OdKj9Qp9gYq36Ufa3pa1QX5mrItAUymuvVWlWheOcsRQ1LUXtdtRImcKIIA09Ir013JnZu+x4dvVijHWNltVolSYfc+zTO+VEMAAAAzBERYdFU53DTn9t1X9d5PLC1pUWnT0pX2entMPCEdKCKiug8Q+vKGH/B567ZE0NUEQAAAHqju76uU6yU4uj3moD+ED7voQIAAACAywwDFQAAAAD0UkiP/LX7JHdD4BhnYucWMgAAAAaWYHpBiX4Q4S2kA5W7wZz3UAEAAKDvNDS16a/vVquqtll+v18Wi8WU5wbTC0r0gwhvIR2oPq62aI38Rpvi0tLVXl+jpPlLQ10SAADAoPeL3+/Rymc+kKfaq0irRdcu3qjitTdrZFKcqevQC+JyZermaUlJifLz83Xvvfdq/fr1evfdd7Vq1argki0WGY2nFBEdp6GzFppZFgAAAHrhxKmz+snTu3TkuFd+v/SNeyZrx57Tuv+RN3rMPVTZqK888oaeKzoQ3GL0grhMmTpQVVRUKDs7W3PnztWwYcM0ffp0OZ3OoHIjbckaPn+pvHu3qK32iJllAQAAoBd+/6dDOlZz9vzPjpQESVLFkZ6/+PT1/96iX2/crxWPbdOZhtYe4+kFcbmy+P1+v1kPy8vLk2EYGjNmjJqamnTNNddo8uTJSkpKuiCuoKBAHo9HTTa7dmY8FPCZ03eslq2pMmBMqXukMp01l1w/AAAAPvJhVaJK9o7WN5dMkSMlQZkzR2nd5gNa/+J7+vLcwDtPxbtHy107VHFR7frqp/cryvr3LWcwvaAUXD8ImMnhcCgnJyeoWFMHKkkqLi5Wenq67HZ7j7HldeZcSrFsZZnyl8+5iCoBAADQk7PnDF3zjy/qwNFGSdKqh2fr26u36v6FTv3yhzcEzG1t69BvXzqoN3dU61e5mV3GBNMLSlxKgfBm+gWUWVlZQQ1TAAAACG/xcZH6Xd58zZycrNEj4uU9267Fn79aa783t8fcmGir7r/DqaFDYvqhUiB0wuKWv+rCXCW45sloOi35OhSZOEK2KV3/JgMAAAD9Z6brSm37/ULVNbYqLsaq2Bjz28fqwlwNmbZARnO9WqsqFJk4QjEjx8ovvxImcAoJ4S2kA5UzsXML9+joxRrtGCur1SpJOuTep3HOj2IAAAAQWsP6YKep617wZklSa0uLTp+s0VV2+kGEt5AOVFERnedhXRnjL/jcNXtiiCoCAABAf+muF+wUK6U4+r0m4GKZ/h0qAAAAABgsGKgAAAAAoJdCeuSv3Se5e3gvnDOxczsYAAAACKZ/lOgh0X9COlC5G8x5DxUAAADCy3t7TunFvxzRvsP1am/3Kcqk6SaY/lGih0T/CYtr0yWptmiN/Eab4tLS1V5fo6T5S0NdEgAAAC6S3+/Xfd8r1UtvVOpMY5siIqRrF2/UK09+XiOS4kxdi/4R4cDUgaqkpES7d+/W9u3bdcsttyg6OlrR0dG68847e062WGQ0nlJEdJyGzlpoZlkAAADoJ3/Zelwb/+pRU7MhSXpwsUs/f65cD/7kHf3h0ZsC5r7wlyN6duN+LbzRoa/c6ex5MfpHhAFTT5ZWVFQoOztbc+fO1bBhw9Ta2qrm5uagciNtyRo+f6m8e7eorfaImWUBAACgn6zbtP/8MCVJjpQESZL7SM9ffPrvJ9/XpteP6idP75Lf7+8xnv4R4cDiD+Z/a5Dy8vJkGIbGjBmjpqYmjRo1Sh0dHbrnnnsuiCsoKJDH41GTza6dGQ8FfOb0Hatla6oMGFPqHqlMZ80l1w8AAIBLs+XAlXr3yAhlL3HJkZKgzJmjtG7zAf1h8zYtnnU4YO7G9+06fCpBQ+La9ZXrD3QZE0z/KAXXQwLdcTgcysnJCSrW1IFKkoqLi5Weni673d5jbHmdOZdSLFtZpvzlcy6iSgAAAPSFU3Utmr1kkw4da5IkZS9x6dlN+/Xosln62t0TAua2t/v0wf4zemajWz//ztwuY4LpHyUupUD/Mf0yyaysrKCGKQAAAAw8ycNitWHVTbphxkiNT7WpdHu1/vMb03scpiQpKipCMyYnKzKS+85x+QiLW/6qC3OV4Jono6FWZw++pyEzPi/blMxQlwUAAIBemD4pWW88c2ufrlFdmKsh0xbIaK5Xa1WFYlKuVqQtWX75lTCBk0voPyEdqJyJnduxR0cv1mjHWFmtVkn/qEPufRrn/CgGAAAAkLrrH2+WJLW2tOj0yRpdZaeHRP8J6UAVFdF5ttWVMf6Cz12zJ4aoIgAAAISz7vrHTrFSiqPfa8LgxgFVAAAAAOilkO5Qtfskdw+vJHAmdv4mAgAAAOgNek70pZAOVO4Gc65NBwAAALpDz4m+FBa3/AEAAGBwa23r0FPPV+i1d4/rZN05NZ9t1xXxUaEuC+hR2AxUtUVr5DfaFJeWrvb6GiXNXxrqkgAAANAPzp4zNP+rxdq597SMDr8k6bovbdZfn/6CkobGmroWPSfMZupJ0ZKSEuXn5+vee+/V+vXr9dJLL2ndunXBJVssMhpPKSI6TkNnLTSzLAAAAISxR5/dre3lp84PU9lLXPpgf52+t2ZHj7mPPL5DN/xTkZ56viK4xeg5YTJTB6qKigplZ2dr7ty5GjZsmK688kodPXo0qNxIW7KGz18q794taqs9YmZZAAAACGNbdtbK7//oZ0dKgiSp/EBdwLz2dp/Wbdqvt3bW6MkN+4Jai54TZrP4/R//73tp8vLyZBiGxowZo6amJs2dO1cHDhzQokWLLogrKCiQx+NRk82unRkPBXzm9B2rZWuqDBhT6h6pTGfNJdcPAACA/vfKnqtUfnyYspe45EhJUObMUVq3+YCKXnlHC68J3Ae+uDNVVfXxmjiyQZ+dXN1ljFk9JwYPh8OhnJycoGJNHagkqbi4WOnp6bLb7T3GlteZc+PKspVlyl8+5yKqBAAAQLioPOHVvC8X68hxr6TOI3/Pv3pYL/1igdKdSQFzfT6/Hvzx21r7vbmyWCxdxpjVcwJdMf1SiqysLLMfCQAAgAHMPipBRY9/Tsvzt6nm9DntOVinDfmf6XGYkqSICItiY6zdDlNAXwuLW/6qC3OV4Jono+GkWo67lTDpetmmZIa6LAAAAPQT1/jheukXN/fpGtWFuRoybYGM5noZ9TWKGp6iyMQR8rWdk27gtBN6J6QDlTOxc3v16OjFGu0YK6vVKkk65N6ncc6PYgAAAIDe6q7nlKTWlhadPllDz4leC+lAFRXReVbVlTH+gs9dsyeGqCIAAAAMNN31nJ1ipRRHv9eEgcPUa9MBAAAAYDAJ6Q5Vu09yNwSOcSZ2/lYBAAAA6C/0qQhWSAcqdwNXWAIAACD80KciWGFxyx8AAABwsSpPePUfa9/TX7ZWye+X/uPr0zVsSEyoy8IgEzYDVW3RGvmNNsWlpau9vkZJ85eGuiQAAACEqYOVDfrcv7ysw1WdLwN+7DflKik7ri3rbtWQhGhT16JPRSCmnvosKSlRfn6+UlNTVV5ers2bN+uFF14ILtlikdF4ShHRcRo6a6GZZQEAAGCAWZG/7fwwlb3EJUn68ECdVj37QcC8jg6f7vp/JZpy5/N6+oWK4BajT0UApu5QVVRUKDs7WzExMfJ6vbJarRfc8x+wEFuybFNvVMO2IlnjExWXNtXM0gAAADCAVJ08d/7PjpSE83/evud0wLwjx716taxK3rOG/vDnQ/rqXRN6XIs+FYFY/H6/36yH5eXlyTAMGYahSZMmKS4uTm1tbbr77rsviCsoKJDH41GTza6dGQ8FfOb0Hatla6oMGFPqHqlMZ80l1w8AAIDLw6ZdY3TwZKKyl7h0323jVbr9hDzVTSrbUqrrx9d2m+fzSZt2p+pEQ6yuu/qkrhlT12WcWX0qLk8Oh0M5OTlBxZo6UElScXGx0tPTZbfbe4wtrzPn9pRlK8uUv3zORVQJAACAy1nF4Xp9/ht/1pHjXmUvcennz5XLdfVQbVl3mxJtPX+Hqqf+0aw+FQOf6ZdSZGVlXXROdWGuElzz5G9vVcuxfYobe41sUzLNLg0AAAADxISxQ/XaU1/Q9x/frt3uM/rXRRP1Xw9mBDVMXYzqwlwNmbZARnO9jPoaRcTZNCT9Jp07tle6gV/oI0xu+Rs2b7FiRoyVxWrVkOkL1HJsX6hLAgAAQJgbO8am5356Y5+u8fE+9W98bS2KGpbSp+vi8hHSgcqZ2LlVKo3/xN9MvCAGAAAA6E/d96mSFCvJQZ8KSSEeqKIiOHcKAACA8EOfimCZ+h4qAAAAABhMQrpD1e6T3A2BY5yJnb8hAAAAAMIZve3gFNKByt3AdZQAAAAYGOhtB6ewuOUPAAAA6A9/erNSP3tmt/YeqtepuhblL5+j5GGxoS4Ll7GwGahqi9bIb7QpLi1d7fU1Spq/NNQlAQAAYADZ8Mph/euPtuhkXaskaX3RQe1yn9HW525XbEzgtrijw6e2dp/iYoNrn+ltBw9TT3CWlJQoPz9fqampKi8v14YNG/Thhx8Gl2yxyGg8pYjoOA2dtdDMsgAAAAA9+uwH54ep7CUuSdKeg/V6duP+gHmn61s084sbNWnh83p2kzu4xehtBw1Td6gqKiqUnZ2tmJgYeb1ezZw5U16v9+/iCgoK5PF41GSzSxkPdRZiS5Zt6o1q2FYka3yi4tKmSpIee2y1bE2VAdctdY/Usuo/mPlPAQAAwACz/9DVkmKVvcSl+24bL0dKgjzVXq39dZEqyn7Zbd7hU1fo/Yo0SdJP1mzWrteruowzq7dF6DkcDuXk5AQVa/H7/X6zFs7Ly5NhGDIMQ5MmTdLQoUPl9Xp11113dRlfXmfOF/eWrSxT/vI5vawaAAAAg8FnvvaSXnu3WpK06uHZ+tajW3VFXKR+/7MbdWtmard5be0dunfF63pnV41eWP1ZzU4f0WWcWb0tLi+m7lCtWLFCxcXFSk9Pl91uN/PRAAAAwCXJXz5bd/6/Eh2u8spT7VVMVIQ+PX2kvnBD4L41OsqqDfmf0bKVZd0OUxi8TL+UIisr66JzqgtzleCaJ/n9ajt5VNEjHLJNyTS7NAAAAAxi10xI0tvrb9NPn96lw1VN+uUPb9C9XxiniAiLaWtUF+ZqyLQFMprrZdTXKHLoCMWMGCujuU4JEzhRNRCFxS1/w+YtVsyIsbJYrZKklmP7QlwRAAAABqJRyfF6bMV1ffb8T/a1kuRra5GlnqvZB6qQDlTOxM5zpNL4T/zNxAtiAAAAgHDnTJQKF32yr5WkWEmO8zEYWEI6UEVF8KU8AAAADAz0toOTqe+hAgAAAIDBJKQ7VO0+yd0QOMaZ2DntAwAAAAMN/fDlL6QDlbuBu/oBAAAweNEPX/7C4pY/SaotWiO/0aa4tHS119coaf7SUJcEAACAQc7n8+uRx3eo6I2jqjzRrANHG/XLH96gkUlxpq9FP3x5Cp/NQ4tFRuMpRUTHaeishaGuBgAAANDDq7Yqf/2H2u2uU11jmzaXVuqWb/xZPp+/x9wTp86q8oQ3+MXohy9Lpg5UJSUlys/PV2pqqsrLy/Xmm29q48aNQeVG2pI1fP5SefduUVvtETPLAgAAAC6a3+/XS28eU0trhyQpe4lLklRxpEF/fvtYwNy336/RzC9u1MwvbtSGVw4FtR798OXJ4vf7ex6vg7R27Vo98MADevLJJzVz5kxNmTJFJSUlWrjwwgm7oKBAHo9HTTa7dmY8FPCZ03eslq2pMmBMqXukMp01l1w/AAAA8DcdPunXb39K9989XY6UBGXOHKXS7Sfkqfbqw+2v6hp7Xbe52w4n6a2DoyRJ0+2nNH9C172qWf0wzOVwOJSTkxNUrKkDVV5engzDkGEYmjRpkg4ePKjPfvazuvbaa7uML68z50t4y1aWKX/5nF5WDQAAAHTtuqWbVLb7pCRp1cOz9a1Ht+qqK+O19bnbNWbUFd3mnWsx9MB/vaWy3Se19be3a9iQmC7jzOqHETqmXkqxYsUKFRcXKz09XXa73cxHAwAAAP3u8e/O1T3LX9OhY03yVHt15fBYfXnhpwIOU5IUFxupdT+er2Ury7odpjAwmH7LX1ZW1kXnVBfmKsE1T/72VrWeOKRY+yTZpmSaXRoAAABwUTImJ+u9wjv01AsVqj1zTm/+OksTxg41dY3qwlwNmbZARnO9jPoaRSWPkTXmCvnlV8IETmGFu5Bem+5M7NzCPDp6sUY7xspqtUqSDrn3aZzzoxgAAAAgVIYkRGvZfVP75NnOROmpZRf2wpLU2tKi0ydrdJWdfjjchXSgioroPA/qyhh/weeu2RNDVBEAAADQf6IipFs+0Qt3ipVSHP1eDy5e+LyHCgAAAAAuMwxUAAAAANBLIT3y1+6T3A2BY5yJnVuhAAAAAOihw01IByp3A/fuAwAAYGBqbeuQYfhMfy49dHgJ6UD1cbVFa+Q32hSXlq72+holzV8a6pIAAACAi9bQ1KYvffd1fbC/TqfrW7X3UIPW/yRTo5LjTV+LHjr0wmcj0GKR0XhKEdFxGjprYairAQAAAHpl0cN/0ebSSh057tX9dzpVsvW4FmaXyO/395j76jtV2vZhbfCL0UOHnKkDVUlJifLz85Wamqry8nKVlZVpw4YNQeVG2pI1fP5SefduUVvtETPLAgAAAPpF7elzKj9Yf/5nR0qCJOlAZaP2fOzzrvz8uXItzHlVn//6K3pta1VQ69FDh57FH8yoHKS1a9fqgQce0JNPPqmZM2fKbrfr5Zdf1le+8pUL4goKCuTxeNRks2tnxkMBnzl9x2rZmioDxpS6RyrTWXPJ9QMAAACXouFclH737jj986Jr5EhJUObMUSrdfkLHTjTq+L5iXTX0XLe5pe6Reu9osiS/PjvpuKaOru8yzqweGt1zOBzKyckJKtbUgSovL0+GYcgwDE2aNEljxoxRTU2N7rzzzi7jy+vM+ULdspVlyl8+p5dVAwAAAObw+/2avuiP2lVxRpK06uHZ+tajW+VMS9SHz9+lqABX7509Z2h5/lZtKz+lst/crogIS5dxZvXQMIepl1KsWLFCxcXFSk9Pl91uN/PRAAAAQNizWCz65Q+u19LvlOpwlVdHT3h19RibVi+fFXCYkqT4uEit/d71WrayrNthCuHH9Fv+srKyLjqnujBXCa558ncYOndkt+KvniHblEyzSwMAAAD63LVTRuiDF+7Sy1uOqa2tQz/+5kzFx5nbdlcX5mrItAUymutl1NcoNtUlX4tXlqgYJUzg5FZ/Cum16c7Ezu3Io6MXa7RjrKxWq6TP6JB7n8Y5P4oBAAAALifRUVbdPt/RJ892JkpPLft4/9yptaVFp0/W6Co7PXR/CulAFRXRebbTlTH+gs9dsyeGqCIAAAAgvEVFSLd8on/uFCul9M0Qh+6Fz3uoAAAAAOAyw0AFAAAAAL0U0iN/7T7J3RA4xpnYua0JAAAA4OIF03NL9N29FdKByt3AHfoAAACA1PkOq/2eRjV620x9bjA9t0Tf3VshHag+rrZojfxGm+LS0tVeX6Ok+UtDXRIAAADQL3ZVnNY/fe8NVdU2q7nF0N7DDXo+/zMalRxv+lr03eYKn009i0VG4ylFRMdp6KyFoa4GAAAA6BcdHT7d+++va5f7jE7Vt+qf756ot9+v1ReX/7XH3Na2Dv33kzu1+XVP8AvSd5vK1IGqpKRE+fn5Sk1NVXl5udxut9avXx9UbqQtWcPnL5V37xa11R4xsywAAAAgbG394KSOVDWd/9mRkiBJ2n+0USfPnAuYm/PTd/TI2vf05Ufe1N5D9UGtR99tLovf7/eb9bC1a9fqgQce0JNPPqmZM2eqqalJLS0tuvXWWy+IKygokMfjUZPNrp0ZDwV85vQdq2VrqgwYU+oeqUxnzSXXDwAAAPS3qvo4Pb8jTf9271Q5UhKUOXOUSref0ImTDWo8/EfFR3d0m/vqnqv04fFhiozo0OJZh5Sc8Pffvwqm55aC67sHC4fDoZycnKBiTR2o8vLyZBiGDMPQpEmTZBiGzpw5owcffLDL+PI6cy6lWLayTPnL5/SyagAAACB0DMOn9Ltf0N7DnVfxrXp4tr716FZ9evpIvfnsrQFzz7UY+tH/vq+dFadUvPbzXcYE03NLXErRW6ZeSrFixQoVFxcrPT1ddrvdzEcDAAAAA1JkZISe/dE83f/ImzpWe1an6s7pWleyfpd3Y4+5cbGR+u/smVq2sqwfKkVXTL/lLysr66JzqgtzleCaJ397q1prjyh29ATZpmSaXRoAAAAQlq6dMkK7n79LH+w/o5hoq36cc63pa1QX5mrItAUymutl1NfIEhmt+HHTZTTXKWECp716K6TXpjsTO7cWj45erNGOsbJarZKkQ+59Guf8KAYAAAAY6CIiLLpmQpLpz+2u55ak1pYWnT4Zq6vs9N29FdKBKiqi85ymK2P8BZ+7Zk8MUUUAAADAwNJdz90pVkpx9HtNA0n4vIcKAAAAAC4zDFQAAAAA0EshPfLX7pPcDYFjnImd25QAAAAA+kcwfbpEry6FeKByN5jzHioAAABgMGr0tql0e7WqT56V3++XxWIx5bnB9OkSvboU4oHq42qL1shvtCkuLV3t9TVKmr801CUBAAAAYeuXz1foJ0+9ryPHvYq0WnTt4k0qXrtAI5PiTF2HPj0wUzfoSkpKlJ+fr9TUVJWXl+tXv/qVysvLg0u2WGQ0nlJEdJyGzlpoZlkAAADAgFJ7+pxyn9ypw1Ve+f3SN+6ZrB17Tumfvl/aY+6RqiZ99Qdv6HcvHQxuMfr0gEzdoaqoqFB2drZiYmLk9Xo1cuRIeb3e4AqxJcs29UY1bCuSNT5RcWlTzSwNAAAAGDAKXz6kyhPN5392pCRIkvZ7Gns8+vf13C3689tVevmtKn3uutFKHhYbcC369MAsfr/fb9bD8vLyZBiGDMPQpEmTZLfbVVlZqUWLFl0QV1BQII/HoyabXTszHgr4zOk7VsvWVBkwptQ9UpnOmkuuHwAAALgclB9P1Kt7rtI3l0yVIyVBmTNHad3mA1r34nu6f+6BgLnFu0fLXTtUsVHt+ur1BxQd6fu7mGD6dCm4Xv1y5HA4lJOTE1SsqQOVJBUXFys9PV12u73H2PI6cy6lWLayTPnL51xElQAAAMDl6+w5Q9P+8UXtP9ooSVr18Gwtz9+q+277lH6dOy9gbmtbh9Zv3q+33q/RM7mZXcYE06dLXEoh9cF7qLKysoIapgAAAAD0TnxcpH6bd6MyJifpqhHx8p5t0z03j9MTj1zfY25MtFVfu3uihg+J6YdKB76wuOWvujBXCa558vs61FxRpoRJ18s2petpGQAAAIA005Ws7b+/Q6fqWhQfG6n4OPNb++rCXA2ZtkBGc72M+hpFxF6hmJTx8rWdU8IETohJIR6onImd24RHRy/WaMdYWa1WSTfpkHufxjk/igEAAADQtZ4uleiNrvv0Tq0tLTp9skZX2enVpRAPVFERnWcuXRnjL/jcNXtiiCoCAAAA0F2f3ilWSnH0e03hyvTvUAEAAADAYMFABQAAAAC9FNIjf+0+yd0QOMaZ2LnlCAAAACB8BdPbSwOvvw/pQOVuMOc9VAAAAACC8/6+03rxNY8qjtSrvd2nKJOmm2B6e2ng9fdhcW26JNUWrZHfaFNcWrra62uUNH9pqEsCAAAABgy/36/7H3lTRaVHdbqhVRER0rX3btQrT3xeI5LiTF1rMPX2pm62lZSUKD8/X6mpqSovL9eLL76osrKy4JItFhmNpxQRHaehsxaaWRYAAAAw6L2x/YRefO2ITje0SpIeXOzSroozevDHb/eYu+mvHt2R86p+9aI7uMUGUW9v6g5VRUWFsrOzFRMTI6/XqyNHjigpKSm4QmzJsk29UQ3bimSNT1Rc2lQzSwMAAAAGtWc371ejt/38z46UBElShaexx9z/emKnduw9rfIDdbr/jk/JYrEEjB9Mvb3F7/f7zXpYXl6eDMOQYRiaNGmSrrjiCp05c0Zf+tKXLogrKCiQx+NRk82unRkPBXzm9B2rZWuqDBhT6h6pTGfNJdcPAAAADFRvH7xSWw+PUPYSlxwpCcqcOUrrNh9Q4eZtunfW4YC5G3fZdeikTYmxbfrKpw90GRNMby8F19+HmsPhUE5OTlCxpg5UklRcXKz09HTZ7fYeY8vrzLmUYtnKMuUvn3MRVQIAAACDy+n6Fs26d5MOHWuSJGUvcemZjW79NGemvnHP5IC57e0+vV9xWus279ea78ztMiaY3l4aeJdSmH5hYVZWVlDDFAAAAID+kzQ0Vv/36E369PSRutpuU+m2aj3yL9N6HKYkKSoqQtdOuVJRkQPovnOThMUtf9WFuUpwzZPfaNPZAzt0xcTrZJuSGeqyAAAAgAFlxuRkvfnsrX26RnVhroZMWyCjuV5GfY1iRjsVNSxF7XXVSpgw8E6VhXSgciZ2bvkdHb1Yox1jZbVaJX1Oh9z7NM75UQwAAACA8NZ1b9+ptaVFp09KV9kHXn8f0oEqKqLz/KQrY/wFn7tmTwxRRQAAAAB6o7vevlOslOLo95r6A4cgAQAAAKCXQrpD1e6T3A2BY5yJndMuAAAAgIFlIMwDIR2o3A3mXJsOAAAA4PIzEOaBsLjlDwAAAEB4amvv0DN/3K9Xy6pUc/qcms+264r4qFCXFTbCZqCqLVojv9GmuLR0tdfXKGn+0lCXBAAAAAxq51oM3fjVl/Te3tNqN3yySLruS5v116e/oKShsaaudbnOA6aeRiwpKVF+fr5SU1NVXl6ud999V6tWrQou2WKR0XhKEdFxGjproZllAQAAAOiF1b/5UNvKT6rd8EmSvrnEpQ/21+m7P9/eY+5//s97yry/SE89XxHcYpfpPGDqDlVFRYWys7MVExMjr9erGTNmqKamJrhCbMmyTb1RDduKZI1PVFzaVDNLAwAAAHCR3th+Qj7fRz87UhIkSeUH6gPmdXT49Os/7pen2qvmc4a+dveEHte6XOcBi9/v95v1sLy8PBmGIcMwNGnSJKWkpGjy5MlKSkq6IK6goEAej0dNNrt2ZjwU8JnTd6yWrakyYEype6QyncENbgAAAACC8+qeFH14fLiyl7jkSElQ5sxRWrf5gDb/+R3dMS1wj/7izlRV1cdrwshGfW7y8S5jzJoHzOZwOJSTkxNUrKkDlSQVFxcrPT1ddru9x9jyOnNu9Vi2skz5y+dcRJUAAAAAenLsRLNu+HKRjhz3SpKyl7i04dXD2vzzz2nG5OSAuT6fX//2oy36xfevl8Vi6TLGrHkglEy/lCIrK8vsRwIAAAAIgTGjrlDR45/T8vxtOnHqrD48cEb/9+hNPQ5TkhQRYVFcbGS3w9RAERa3/FUX5irBNU9+X4c6mk4rMnGEbFMyQ10WAAAAMOi5xg/XS7+4uU/XqC7M1ZBpC2Q018uor5ElMloxI8fKL790Q3ifRAvpQOVM7NzCOzp6sUY7xspqtUqSDrn3aZzzoxgAAAAAA09384Aktba06PTJmrCfB0I6UEVFdJ6HdGWMv+Bz1+yJIaoIAAAAQH/pbh7oFCulOPq9potl6nuoAAAAAGAwCekOVbtPcjcEjnEmdk6uAAAAABBuM0RIByp3w+V/TSIAAACA/hNuM0RY3PIHAAAAYOCoqmnWD37xnl59p0oWi0WP/Ms0DR0SE+qy+kTYDFS1RWvkN9oUl5au9voaJc1fGuqSAAAAAFykw8ca9dl/eVmHjjVJkvLXfahX36nSW8/eqiEJ0aauFQ4zhKknC0tKSpSfn6/U1FSVl5ersLBQL774YnDJFouMxlOKiI7T0FkLzSwLAAAAQD9ZsXrb+WEqe4lLkvTB/jr97NcfBMzr6PDpH5b9Rel3v6CnX6gIbrEwmCFM3aGqqKhQdna2YmJi5PV61draqvb29uAKsSXLNvVGNWwrkjU+UXFpU80sDQAAAEA/qKo9e/7PjpSE839+b++pgHlHq5v16jtVamxu1+9fPqSv3jWhx7XCYYaw+P1+v1kPy8vLk2EYMgxDkyZNUkREhDo6OnTPPfdcEFdQUCCPx6Mmm107Mx4K+MzpO1bL1lQZMKbUPVKZzppLrh8AAADApdm0a4wOnkxU9hKX7rttvEq3n5Cn2qu333pdN3yqtts8n0/atDtVJxriNGdcrabZ67qMM2uGCMThcCgnJyeoWFMHKkkqLi5Wenq67HZ7j7Hldebc0LFsZZnyl8+5iCoBAAAA9AX3kQbd/PWXdeS4V9lLXPr5c+WaPG6o3lp3q4YFcTFFT729WTOEWUy/lCIrK+uic6oLc5Xgmie/0aam3a9pyIzPyzYl0+zSAAAAAPQxZ1qi/vLLW/T9x3do177T+pd/mKD/fjAjqGHqYlQX5mrItAUymutl1NcockiSIm3J8ssv3dB/my1hccvfsHmLFTNirCxWq4ZM+5xaju0LdUkAAAAAemmcfYh+m3djn67x8Rnib3xtLWqv79+vAoV0oHImdm7HSeM/8TcTL4gBAAAAACnQDCFJsZIc/TpDhHSgiorov7ONAAAAAC5/4TZDmPoeKgAAAAAYTEK6Q9Xuk9wNgWOciZ1TKAAAAAD0Rl/OHSEdqNwN4XXlIQAAAICBpy/njrC45Q8AAADA4PbK28eU96vd2nOwXqfqWpS/fI6Sh8WGuqwehc1AVVu0Rn6jTXFp6Wqvr1HS/KWhLgkAAABAP/jjX47ogdwtqj3TIklaX3RQu9xntPW52xUbE3hk8fn8ajd8iom2Boz7G7PnDlO/nVRSUqL8/HylpqaqvLxcL730ktatWxdcssUio/GUIqLjNHTWQjPLAgAAABDGfvbMB+eHqewlLknSnoP1+vUf3QHz6hpbde3ijZpw+//p2U2BY88zee4wdYeqoqJC2dnZiomJkdfr1ZVXXqn33nvv7+IKCgrk8XjUZLNLGQ91FmJLlm3qjWrYViRrfKLi0qZKkh57bLVsTZUB1y11j9Sy6j+Y+U8BAAAA0E/cB66WFKvsJS7dd9t4OVIS5Kn26he/Ltb+rU91m3f41BV6b2+aJOnHa4q06/VjXcZd7NzhcDiUk5MTVO0Wv9/vD/Lf2aO8vDwZhiHDMDRp0iSNHz9eBw4c0KJFi7qML68z58thy1aWKX/5nF5WDQAAACCUPvO1l/Tau9WSpFUPz9a3Ht2q+NhIPffT+brjJke3eW3tHVr87ddVtrtGf3j0Jl0/fVSXcWbNHV0xdYdqxYoVKi4uVnp6uux2uyRpxowZZi4BAAAAYIBZ/e05uiPnVR2u8spT7VV0VITmThuh2+enBsyLjrLq+dWf0bKVZd0OU33N9EspsrKyLjqnujBXCa558hvtat7/rhImXS/blEyzSwMAAAAQhtKdw7Vl3W366dO7dPhYo/7n+9frvtvGKyLCYtoa1YW5GjJtgYzmerXVHFZMytWKTBwhX9s5JUzo/Wm3sLjlb9i8xYoZMVYWq1VDpn1WLcf2hbokAAAAAP0o5cp4Ffz7dX32/I/PHH/ja2tRe33NJT03pAOVM7HzrKI0/hN/M/GCGAAAAADoLWeiVLjokzOHJMVKcpyP6Y2QDlRREb374hcAAAAABKsv5w5T30MFAAAAAINJSHeo2n2SuyFwjDOxc6IEAAAAgN7oy7kjpAOVu6Hv7oMHAAAAAKlv546wuOVPkmqL1shvtCkuLV3t9TVKmr801CUBAAAACFN+v18//MVObXzdo8oTXh2sbNL//uDTGpkUFzDP7LkjbAYqWSwyGk8pIjpOQ2ctDCrF5/PL7WmQYfj6uDgAAAAA4WTF6m16/Hd7dK61Q5K06fWjqjzxZ2373e2yWgOc3evF3BGIqd9OKikpUX5+vqZOnaqysjJt3rxZL7zwQlC5kbZkDZ+/VN69W9RWeySonK/+4E1lfHGjNrx6RD6f/xIqBwAAAHC58Pv92lx69Pwwlb3EJUnad6ReL2+pCpjbm7kj4PMu+QkfU1FRoezsbLW2tqqtrU1Wq1XWj704628KCgrk8XjUZLNLGQ9JkobP+6IkKS7VdUHsY4+tlq2pssv1Xtk2VmfPxctob1XOQw8ryspQBQAAAAx0Pr9UdfxTkqKVvcSl+24bL0dKgjzVXq1a84z+8se6C+Ivdu5wOBzKyckJqhaL3+83bQrJy8uTYRiaMmWKGhsbNXToULW1tenuu+/uMr687tK+HFZUelS/KNyr+TNH6dtfueYSqwcAAABwubhu6WaV7a6VJK16eLa+9ehWpSTHqey525WaknBB7KXOHYGYukO1YsUKFRcXKz09XXa73cxHd+nWzFTdmpna5+sAAAAACC+Pf/c63bP8NR061iRPtVfJQ2O09NbxfzdM9TXTL6XIysq66JzqwlzZ0m+Sr6VZLcf2KW7sNbJNyTS7NAAAAAADRMbkZO34/R166oV9qj55Tq//6gtyjR/ebXx1Ya6GTFsgo7lebTWHFTl0pIak36Rzx/YqYcKcXtdh6pG/i/W3F2wdPXRAox1jz3/f6pB7n8Y5J0rixb4AAAAALk27TyrZeeHMIUmtLS06fbJGV9kdvZ47QjpQAQAAAMDljL0fAAAAAOglBioAAAAA6CUGKgAAAADoJQYqAAAAAOglBioAAAAA6CUGKgAAAADoJQYqAAAAAOglBioAAAAA6CUGKgAAAADoJQYqAAAAAOglBioAAAAA6CUGKgAAAADopf8PpDA1jWp0VsMAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 1081.24x1026.74 with 1 Axes>"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "circuit = EfficientSU2(NUM_QUBITS, su2_gates=\"rz\", entanglement=\"circular\", reps=1).decompose()\n",
     "\n",
@@ -195,9 +189,13 @@
    "id": "46eec6f3-d4d5-40fd-97fa-d7fca0fa8344",
    "metadata": {},
    "source": [
-    "## Step 2: 回路のトランスパイルと最適化\n",
+    "### Step 2: 回路のトランスパイルと最適化\n",
+    "\n",
+    "このステップでは、Qiskit Transpiler Service を使って回路をトランスパイルし、最適化します。このプロセスを2回実行します。最初はAIなしで、次にAIを使用した transpiler passes を使用します。\n",
+    "\n",
+    "Qiskit Transpiler Service は、クラウド上でヒューリスティックなトランスパイラー機能とAIによるトランスパイラー機能の両方を提供します。IBM Quantum™ のクラウドリソースと高度な AI 搭載 transpiler passes の恩恵を受けるために、実行中のトランスパイル・タスクを活用することができます。 \n",
     "\n",
-    "このステップでは、Qiskit Transpiler Service を使って回路をトランスパイルし、最適化します。このプロセスを2回実行します。最初はAIなしで、次にAIを使用した transpiler passes を使用します。このセクションでは Qiskit Transpiler Service を使用します。Qiskit Transpiler Service は、クラウド上でヒューリスティックなトランスパイラー機能とAIによるトランスパイラー機能の両方を提供します。IBM Quantum™ のクラウドリソースと高度な AI 搭載 transpiler passes の恩恵を受けるために、実行中のトランスパイル・タスクを活用することができます。 **詳細については、 [こちら](https://docs.quantum.ibm.com/transpile/qiskit-transpiler-service) の Qiskit Transpiler Serviceのドキュメントを参照してください。** \n"
+    "**詳細については、 [こちら](https://docs.quantum.ibm.com/transpile/qiskit-transpiler-service) の Qiskit Transpiler Serviceのドキュメントを参照してください。** \n"
    ]
   },
   {
@@ -205,7 +203,7 @@
    "id": "cd951713-03e5-4f81-8ff3-c3e60c3d3772",
    "metadata": {},
    "source": [
-    "#### Qiskit Transpiler Service - AI なし\n",
+    "#### Exercise 1: Qiskit Transpiler Service - AI なし\n",
     "\n",
     "AIなし：Qiskit Transpiler Service で利用可能な従来のヒューリスティック手法を使って回路をトランスパイルします。"
    ]
@@ -215,60 +213,84 @@
    "id": "c665e734-ebb8-4f66-95d9-6e752d9c7370",
    "metadata": {},
    "source": [
-    "<a id=\"exercise1\"></a>\n",
-    "<div class=\"alert alert-block alert-success\">\n",
-    "    \n",
-    "<b> Exercise 1:</b> \n",
-    "\n",
+    "```{admonition}Exercise\n",
     "Qiskit Transpiler Service をセットアップして、クラウド上に回路をトランスパイルしましょう。Qiskit Transpiler Service の最新版がインストールされ、設定されていることを確認してください。この演習では `ibm_brisbane` バックエンドを使用します。バックエンドを設定し、 **AI フラグをオンにせず、** optimization level  `3` で transpiler を構成します。\n",
-    "</div>"
+    "```"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "c00dae26-e073-45d0-ba88-4d24db222cc8",
+   "execution_count": 6,
+   "id": "85c73031-c3fe-41a5-b754-c5a85d4b626e",
    "metadata": {},
    "outputs": [],
    "source": [
-    "transpiler_ai_false = TranspilerService( \n",
-    "    # Add your code here\n",
-    ")"
+    "backend_name = 'ibm_brisbane'\n",
+    "optimization_level = 3"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "47949823-1053-43d7-8139-57784c763034",
+   "execution_count": 7,
+   "id": "c00dae26-e073-45d0-ba88-4d24db222cc8",
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Submit your answer using following code\n",
-    "\n",
-    "grade_lab3_ait_ex1(transpiler_ai_false)\n",
-    "# Expected result type: TranspilerService"
+    "transpiler_ai_false = TranspilerService( # Add your code here\n",
+    "    backend_name=backend_name,\n",
+    "    ai=False,\n",
+    "    optimization_level=optimization_level\n",
+    ")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "id": "4b63cdca-a872-406f-bab0-08965eaacbd0",
    "metadata": {
     "scrolled": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO:qiskit_transpiler_service.transpiler_service:Requesting transpile to the service\n",
+      "INFO:qiskit_transpiler_service.transpiler_service:Qiskit transpiler service returned a result\n"
+     ]
+    }
+   ],
    "source": [
     "circuit_ai_false = transpiler_ai_false.run(circuit)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "id": "358aa7f2-3b15-47eb-a869-185751aa44de",
    "metadata": {
     "scrolled": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Transpiled without AI -> Depth: 1339, CNOTs: 343\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 22612.3x2130.41 with 1 Axes>"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "print(f\"Transpiled without AI -> Depth: {circuit_ai_false.depth()}, CNOTs: {circuit_ai_false.num_nonlocal_gates()}\")\n",
     "circuit_ai_false.draw(fold=-1, output=\"mpl\", scale=0.2)"
@@ -279,7 +301,7 @@
    "id": "fda47e18-4953-4d48-a726-260925dffa97",
    "metadata": {},
    "source": [
-    "#### Qiskit Transpiler Service - AI搭載\n",
+    "#### Exercise 2: Qiskit Transpiler Service - AI搭載\n",
     "AIを搭載した transpiler passes を有効にして、回路の最適化をどのように改善できる可能性があるかを確認します。"
    ]
   },
@@ -288,79 +310,102 @@
    "id": "41e2ff99-2cd5-4079-8c0c-9fd973f29d99",
    "metadata": {},
    "source": [
-    "<a id=\"exercise2\"></a>\n",
-    "<div class=\"alert alert-block alert-success\">\n",
-    "    \n",
-    "<b> Exercise 2:</b> \n",
-    "\n",
+    "```{admonition}Exercise\n",
     "それでは AI フラグを `on` にして Qiskit Transpiler サービスを使用してみましょう。環境が Qiskit Transpiler Service の最新バージョンでセットアップされていることを確認してください。引き続き `ibm_brisbane` バックエンドを使用します。トランスパイラーを optimization level `3` で設定し、AI フラグを有効にして. AI による高度な最適化を活用します。このセットアップでは、AI を活用してゲート数と回路深度を最適化することで、量子回路のトランスパイルを試みます。\n",
-    "</div>"
+    "```"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 10,
    "id": "6cedf51d-4391-4ef7-8c8a-8f14fdb72e45",
    "metadata": {
     "scrolled": true
    },
    "outputs": [],
    "source": [
-    "transpiler_ai_true = TranspilerService(\n",
-    "    # Add your code here\n",
+    "transpiler_ai_true = TranspilerService( # Add your code here\n",
+    "    backend_name=backend_name,\n",
+    "    ai=True,\n",
+    "    optimization_level=optimization_level\n",
     ")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "0a9b1623-b617-415d-b112-6d209eae4574",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Submit your answer using following code\n",
-    "\n",
-    "grade_lab3_ait_ex2(transpiler_ai_true)\n",
-    "# Expected result type: TranspilerService"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "id": "4c14843e-e056-4580-820e-1dbd75ea3152",
    "metadata": {
     "scrolled": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO:qiskit_transpiler_service.transpiler_service:Requesting transpile to the service\n",
+      "INFO:qiskit_transpiler_service.transpiler_service:Qiskit transpiler service returned a result\n"
+     ]
+    }
+   ],
    "source": [
     "circuit_ai_true = transpiler_ai_true.run(circuit)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "id": "e04470d2-d901-4757-bbdc-bce4703b1406",
    "metadata": {
     "scrolled": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Transpiled with AI -> Depth: 277, CNOTs: 64\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 4853.29x2130.41 with 1 Axes>"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "print(f\"Transpiled with AI -> Depth: {circuit_ai_true.depth()}, CNOTs: {circuit_ai_true.num_nonlocal_gates()}\")\n",
     "circuit_ai_true.draw(fold=-1, output=\"mpl\", scale=0.2)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "60861d05-3290-45d5-9d45-6330f38383d5",
+   "metadata": {},
+   "source": [
+    "```{note}\n",
+    "ヒューリスティックにトランスパイルをした場合の量子回路の深さは1300程度であるのに対して、AIトランスパイルの場合は270程度に抑えられていて、効果的にトランスパイル出来ていることが確認できます。\n",
+    "```"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "91e2aa6f-fa83-4496-b709-b5a9b9893b49",
    "metadata": {},
    "source": [
-    "## Step 3: グラフのプロット\n",
+    "### Step 3: 結果の可視化\n",
     "トランスパイルと最適化の結果を可視化します。グラフをプロットして、 AI を使用してトランスパイルした回路と AI を使用しない回路の性能指標（深さ、ゲート数など）を比較します。これにより、 AI 搭載 transpiler passes が量子回路に与える影響を理解することができます。"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "id": "03164f5b",
    "metadata": {},
    "outputs": [],
@@ -373,12 +418,39 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 14,
    "id": "42d031ed-ba31-4b6e-8bc4-bdb2257898fd",
    "metadata": {
     "scrolled": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "INFO:qiskit_transpiler_service.transpiler_service:Requesting transpile to the service\n",
+      "INFO:qiskit_transpiler_service.transpiler_service:Qiskit transpiler service returned a result\n",
+      "INFO:qiskit_transpiler_service.transpiler_service:Requesting transpile to the service\n",
+      "INFO:qiskit_transpiler_service.transpiler_service:Qiskit transpiler service returned a result\n",
+      "INFO:qiskit_transpiler_service.transpiler_service:Requesting transpile to the service\n",
+      "INFO:qiskit_transpiler_service.transpiler_service:Qiskit transpiler service returned a result\n",
+      "INFO:qiskit_transpiler_service.transpiler_service:Requesting transpile to the service\n",
+      "INFO:qiskit_transpiler_service.transpiler_service:Qiskit transpiler service returned a result\n",
+      "INFO:qiskit_transpiler_service.transpiler_service:Requesting transpile to the service\n",
+      "INFO:qiskit_transpiler_service.transpiler_service:Qiskit transpiler service returned a result\n",
+      "INFO:qiskit_transpiler_service.transpiler_service:Requesting transpile to the service\n",
+      "INFO:qiskit_transpiler_service.transpiler_service:Qiskit transpiler service returned a result\n",
+      "INFO:qiskit_transpiler_service.transpiler_service:Requesting transpile to the service\n",
+      "INFO:qiskit_transpiler_service.transpiler_service:Qiskit transpiler service returned a result\n",
+      "INFO:qiskit_transpiler_service.transpiler_service:Requesting transpile to the service\n",
+      "INFO:qiskit_transpiler_service.transpiler_service:Qiskit transpiler service returned a result\n",
+      "INFO:qiskit_transpiler_service.transpiler_service:Requesting transpile to the service\n",
+      "INFO:qiskit_transpiler_service.transpiler_service:Qiskit transpiler service returned a result\n",
+      "INFO:qiskit_transpiler_service.transpiler_service:Requesting transpile to the service\n",
+      "INFO:qiskit_transpiler_service.transpiler_service:Qiskit transpiler service returned a result\n"
+     ]
+    }
+   ],
    "source": [
     "# Run and compile results\n",
     "num_qubits = [11, 21, 41, 61, 81]\n",
@@ -403,7 +475,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 15,
    "id": "20505da5-f19d-490b-a3ae-2d00450b2a07",
    "metadata": {
     "scrolled": true
@@ -412,16 +484,16 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.legend.Legend at 0x16895a0d0>"
+       "<matplotlib.legend.Legend at 0x7f53ddee9250>"
       ]
      },
-     "execution_count": 27,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -439,27 +511,6 @@
     "plt.legend([\"Qiskit Transpiler Service with AI\", \"Qiskit Transpiler Service without AI\", \"Qiskit SDK\"])"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "5cce599f-0073-498d-82b4-a27fc2078ab1",
-   "metadata": {},
-   "source": [
-    "<a id=\"exercise5\"></a>\n",
-    "<div class=\"alert alert-block alert-warning\">\n",
-    "    \n",
-    "<b> ボーナス Exercise! </b> \n",
-    "\n",
-    "AIトランスパイラーで何ができるかを体験したところで、 Qiskit Transpiler Service を使用して、 様々な高い深さ (Depth) および高い幅 (Width) の回路を試してみてください！\n",
-    "\n",
-    "また、Lab 2 で学んだ「従来の」Qiskit passes のドロップイン置き換えとして機能する AI 搭載 transpiler passes を、いくつかの transpiling タスクで確認することもできます。これについては [こちら](https://docs.quantum.ibm.com/transpile/ai-transpiler-passes) をご覧ください。\n",
-    "\n",
-    "結果を投稿し、ゲートの深さと CNOT 数の最もよく改善されたものを Discord で披露してください！\n",
-    "\n",
-    "あなたの発見を自由に紹介し、コミュニティと成果を議論してください！\n",
-    "\n",
-    "</div>"
-   ]
-  },
   {
    "cell_type": "markdown",
    "id": "b05aaa22-2e3b-433d-81cd-a583ba5598c4",
@@ -473,7 +524,7 @@
    "id": "2dfa65c3-755d-4272-924f-7154c162b054",
    "metadata": {},
    "source": [
-    "# 追加情報\n",
+    "## 追加情報\n",
     "\n",
     "**Created by:** Vishal Sharathchandra Bajpe, David Kremer\n",
     "\n",
@@ -481,13 +532,21 @@
     "\n",
     "**Version:** 1.0.0"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1e8b3fb2-4b77-413f-b949-bd206600d297",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "iqc2024",
    "language": "python",
-   "name": "python3"
+   "name": "iqc2024"
   },
   "language_info": {
    "codemirror_mode": {
@@ -499,7 +558,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.0"
+   "version": "3.11.2"
   }
  },
  "nbformat": 4,
diff --git a/src/2024-spring-lab3-circuit-knitting-ja.ipynb b/src/2024-spring-lab3-circuit-knitting-ja.ipynb
index c6a5991..f1724eb 100644
--- a/src/2024-spring-lab3-circuit-knitting-ja.ipynb
+++ b/src/2024-spring-lab3-circuit-knitting-ja.ipynb
@@ -1196,7 +1196,7 @@
    "id": "cde8d325-98bb-4d8b-9015-832420d6c9cf",
    "metadata": {},
    "source": [
-    "# 結果の可視化"
+    "## 結果の可視化"
    ]
   },
   {
@@ -1286,7 +1286,7 @@
     "tags": []
    },
    "source": [
-    "# 追加情報\n",
+    "## 追加情報\n",
     "\n",
     "**Created by:** Kifumi Numata\n",
     "\n",
diff --git a/src/_toc.yml b/src/_toc.yml
index 28954f4..2408b00 100644
--- a/src/_toc.yml
+++ b/src/_toc.yml
@@ -14,6 +14,8 @@ parts:
     title: Dynamic Circuits入門 (2023春 Lab1)
   - file: 2024-spring-lab2-transpilation-ja
     title: Transpiler入門(2024春 Lab2)
+  - file: 2024-spring-lab3-ai-transpiler-ja
+    title: Transpiler powere by AI(2024春 Lab3)
   - file: 2024-spring-lab3-circuit-knitting-ja
     title: Circuit Knittingの紹介(2024春 Lab3)