diff --git a/1_Basics_IV.ipynb b/1_Basics_IV.ipynb
index 8b6bf946..9db1210b 100644
--- a/1_Basics_IV.ipynb
+++ b/1_Basics_IV.ipynb
@@ -36,14 +36,18 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "heading_collapsed": true
+   },
    "source": [
     "## フローチャート"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "hidden": true
+   },
    "source": [
     "本題に入る前に，まずフローチャートについて説明する。フローチャートを使うと，より直観的に制御フローを理解することができるだろう。フローチャートとは，コードの実行やプログラムの処理の流れ（順番）を示す図である。非常に簡単で，見れば直ぐに理解できる便利なツールである。次のコードを考えてみよう。"
    ]
@@ -51,7 +55,9 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "metadata": {},
+   "metadata": {
+    "hidden": true
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -69,14 +75,14 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "hidden": true
+   },
    "source": [
     "このコード・セルを実行すると上から順に次のように実行される。\n",
-    "> `#1`の行：`10`を変数`x`に割り当てる。\n",
-    "\n",
-    "> `#2`の行：`#1`が終わった後に，`5`を変数`y`に割り当てる。\n",
-    "\n",
-    "> `#3`の行：`#2`が終わった後に，`x+y`の計算結果を`print()`関数を使い表示する。\n",
+    "* `#1`の行：`10`を変数`x`に割り当てる。\n",
+    "* `#2`の行：`#1`が終わった後に，`5`を変数`y`に割り当てる。\n",
+    "* `#3`の行：`#2`が終わった後に，`x+y`の計算結果を`print()`関数を使い表示する。\n",
     "\n",
     "この流れをフローチャートに表してみよう。"
    ]
@@ -85,6 +91,7 @@
    "cell_type": "code",
    "execution_count": 32,
    "metadata": {
+    "hidden": true,
     "tags": [
      "hide-input"
     ]
@@ -1732,11 +1739,13 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "hidden": true
+   },
    "source": [
-    "一番最初と最後の横長丸枠は，プログラムの始まり（`START`）と終わり（`END`）を表す。長方形枠はコードの処理，そして，矢印はプログラムの実行の順番（フロー）を意味する。単純な例なので，上から下に一直線の実行フローとなっている。より複雑なコードの場合，矢印が横向きや上向きになったりもし，枠も様々な形を使い実行フローを表現することになる。以下では，枠は次の３種類だけを使い制御フローをシンプルな形で表すことにする。\n",
-    "* 横長丸枠（端子）：プログラムの始まりと終わり\n",
-    "* 長方形枠（処理）：コードの処理\n",
+    "一番最初と最後の楕円は，プログラムの始まり（`START`）と終わり（`END`）を表す。長方形はコードの処理，そして，矢印はプログラムの実行の順番（フロー）を意味する。単純な例なので，上から下に一直線の実行フローとなっている。より複雑なコードの場合，矢印が横向きや上向きになったりもし，枠も様々な形を使い実行フローを表現することになる。以下では，枠は次の３種類だけを使い制御フローをシンプルな形で表すことにする。\n",
+    "* 楕円（端子）：プログラムの始まりと終わり\n",
+    "* 長方形（処理）：コードの処理\n",
     "* 菱形（判断）：条件分岐\n",
     "\n",
     "また，矢印に`True`や`False`等を付け加えて条件分岐を表現することになる。"
@@ -1744,28 +1753,37 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "heading_collapsed": true
+   },
    "source": [
     "## `if`文"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "heading_collapsed": true,
+    "hidden": true
+   },
    "source": [
     "### 説明と簡単な例"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "hidden": true
+   },
    "source": [
     "`if`文を使うと，指定した条件によって処理を複数パターンに分けることができる。条件をブール型（真偽）（`True`又は`False`）で判断しコードを実行することになる。次の構文となる。"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "hidden": true
+   },
    "source": [
     "```\n",
     "if ＜条件１＞:\n",
@@ -1799,7 +1817,9 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "metadata": {},
+   "metadata": {
+    "hidden": true
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -1821,7 +1841,9 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "hidden": true
+   },
    "source": [
     "＜コードのの説明＞\n",
     "* `#1`：`10`を`x`に割り当てる。\n",
@@ -1836,8 +1858,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 78,
+   "execution_count": 142,
    "metadata": {
+    "hidden": true,
     "tags": [
      "hide-input"
     ]
@@ -1845,17 +1868,17 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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+       "Q 1113 2006 1113 1675 \n",
+       "L 1113 63 \n",
+       "L 563 63 \n",
+       "L 563 3250 \n",
+       "L 1081 3250 \n",
+       "L 1056 2303 \n",
+       "L 1069 2303 \n",
+       "Q 1422 3341 2097 3341 \n",
+       "Q 2206 3341 2309 3316 \n",
+       "z\n",
+       "\" transform=\"scale(0.015625)\"/>\n",
+       "      <path id=\"IPAexGothic-75\" d=\"M 3284 63 \n",
+       "L 2772 63 \n",
+       "L 2772 644 \n",
+       "Q 2300 0 1625 0 \n",
+       "Q 1072 0 763 375 \n",
+       "Q 519 678 519 1241 \n",
+       "L 519 3250 \n",
+       "L 1069 3250 \n",
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+       "L 2734 3250 \n",
+       "L 3284 3250 \n",
+       "L 3284 63 \n",
+       "z\n",
+       "\" transform=\"scale(0.015625)\"/>\n",
+       "     </defs>\n",
+       "     <use xlink:href=\"#IPAexGothic-54\"/>\n",
+       "     <use xlink:href=\"#IPAexGothic-72\" x=\"59.912109\"/>\n",
+       "     <use xlink:href=\"#IPAexGothic-75\" x=\"96.923828\"/>\n",
+       "     <use xlink:href=\"#IPAexGothic-65\" x=\"157.324219\"/>\n",
+       "    </g>\n",
+       "   </g>\n",
        "   <g id=\"text_5\">\n",
        "    <!-- x = 10 ? -->\n",
-       "    <g transform=\"translate(62.818125 172.424141) scale(0.125 -0.125)\">\n",
+       "    <g transform=\"translate(62.818125 171.884141) scale(0.125 -0.125)\">\n",
        "     <defs>\n",
        "      <path id=\"IPAexGothic-3f\" d=\"M 225 3425 \n",
        "Q 503 4725 1763 4725 \n",
@@ -3566,7 +3589,7 @@
        "   </g>\n",
        "   <g id=\"text_6\">\n",
        "    <!-- 「条件はTrueです。」 -->\n",
-       "    <g transform=\"translate(23.101328 248.418672) scale(0.125 -0.125)\">\n",
+       "    <g transform=\"translate(215.701328 171.884141) scale(0.125 -0.125)\">\n",
        "     <defs>\n",
        "      <path id=\"IPAexGothic-300c\" d=\"M 4134 5300 \n",
        "L 5875 5300 \n",
@@ -3809,157 +3832,44 @@
        "     <use xlink:href=\"#IPAexGothic-3002\" x=\"814.208984\"/>\n",
        "     <use xlink:href=\"#IPAexGothic-300d\" x=\"914.208984\"/>\n",
        "    </g>\n",
-       "    <!-- の表示 -->\n",
-       "    <g transform=\"translate(67.74 262.029609) scale(0.125 -0.125)\">\n",
+       "   </g>\n",
+       "   <g id=\"text_7\">\n",
+       "    <!-- END -->\n",
+       "    <g transform=\"translate(265.890781 234.884141) scale(0.125 -0.125)\">\n",
        "     <defs>\n",
-       "      <path id=\"IPAexGothic-306e\" d=\"M 3119 469 \n",
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-       "L 3119 469 \n",
+       "      <path id=\"IPAexGothic-45\" d=\"M 3547 63 \n",
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        "z\n",
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-       "z\n",
-       "\" transform=\"scale(0.015625)\"/>\n",
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-       "Q 3850 575 3209 2350 \n",
-       "z\n",
-       "\" transform=\"scale(0.015625)\"/>\n",
-       "      <path id=\"IPAexGothic-793a\" d=\"M 3488 2822 \n",
-       "L 3488 153 \n",
-       "Q 3488 -144 3334 -247 \n",
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-       "z\n",
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-       "L 403 616 \n",
-       "z\n",
-       "\" transform=\"scale(0.015625)\"/>\n",
-       "     </defs>\n",
-       "     <use xlink:href=\"#IPAexGothic-306e\"/>\n",
-       "     <use xlink:href=\"#IPAexGothic-8868\" x=\"100\"/>\n",
-       "     <use xlink:href=\"#IPAexGothic-793a\" x=\"200\"/>\n",
-       "    </g>\n",
-       "   </g>\n",
-       "   <g id=\"text_7\">\n",
-       "    <!-- END -->\n",
-       "    <g transform=\"translate(73.290781 323.624141) scale(0.125 -0.125)\">\n",
-       "     <defs>\n",
-       "      <path id=\"IPAexGothic-45\" d=\"M 3547 63 \n",
-       "L 609 63 \n",
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-       "L 3547 556 \n",
-       "L 3547 63 \n",
-       "z\n",
-       "\" transform=\"scale(0.015625)\"/>\n",
-       "      <path id=\"IPAexGothic-4e\" d=\"M 4244 63 \n",
-       "L 3731 63 \n",
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-       "L 609 63 \n",
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-       "Q 3694 1897 3694 2469 \n",
-       "L 3694 4634 \n",
-       "L 4244 4634 \n",
-       "L 4244 63 \n",
+       "\" transform=\"scale(0.015625)\"/>\n",
+       "      <path id=\"IPAexGothic-4e\" d=\"M 4244 63 \n",
+       "L 3731 63 \n",
+       "L 1697 3150 \n",
+       "Q 1466 3500 1141 4097 \n",
+       "L 1116 4097 \n",
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+       "L 1159 63 \n",
+       "L 609 63 \n",
+       "L 609 4634 \n",
+       "L 1366 4634 \n",
+       "L 3113 1978 \n",
+       "Q 3453 1447 3713 966 \n",
+       "L 3738 966 \n",
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+       "L 3694 4634 \n",
+       "L 4244 4634 \n",
+       "L 4244 63 \n",
        "z\n",
        "\" transform=\"scale(0.015625)\"/>\n",
        "      <path id=\"IPAexGothic-44\" d=\"M 609 4634 \n",
@@ -3987,7 +3897,7 @@
        "   </g>\n",
        "   <g id=\"text_8\">\n",
        "    <!-- 「条件はFalseです。」 -->\n",
-       "    <g transform=\"translate(213.950352 165.618672) scale(0.125 -0.125)\">\n",
+       "    <g transform=\"translate(21.350352 249.284141) scale(0.125 -0.125)\">\n",
        "     <use xlink:href=\"#IPAexGothic-300c\"/>\n",
        "     <use xlink:href=\"#IPAexGothic-6761\" x=\"100\"/>\n",
        "     <use xlink:href=\"#IPAexGothic-4ef6\" x=\"200\"/>\n",
@@ -4002,16 +3912,10 @@
        "     <use xlink:href=\"#IPAexGothic-3002\" x=\"842.236328\"/>\n",
        "     <use xlink:href=\"#IPAexGothic-300d\" x=\"942.236328\"/>\n",
        "    </g>\n",
-       "    <!-- の表示 -->\n",
-       "    <g transform=\"translate(260.34 179.229609) scale(0.125 -0.125)\">\n",
-       "     <use xlink:href=\"#IPAexGothic-306e\"/>\n",
-       "     <use xlink:href=\"#IPAexGothic-8868\" x=\"100\"/>\n",
-       "     <use xlink:href=\"#IPAexGothic-793a\" x=\"200\"/>\n",
-       "    </g>\n",
        "   </g>\n",
        "   <g id=\"text_9\">\n",
        "    <!-- END -->\n",
-       "    <g transform=\"translate(265.890781 240.824141) scale(0.125 -0.125)\">\n",
+       "    <g transform=\"translate(73.290781 312.284141) scale(0.125 -0.125)\">\n",
        "     <use xlink:href=\"#IPAexGothic-45\"/>\n",
        "     <use xlink:href=\"#IPAexGothic-4e\" x=\"59.521484\"/>\n",
        "     <use xlink:href=\"#IPAexGothic-44\" x=\"135.498047\"/>\n",
@@ -4020,14 +3924,14 @@
        "  </g>\n",
        " </g>\n",
        " <defs>\n",
-       "  <clipPath id=\"p2391ac10b9\">\n",
-       "   <rect x=\"3.6\" y=\"3.6\" width=\"358.38\" height=\"350.46\"/>\n",
+       "  <clipPath id=\"p6ac39a6ef4\">\n",
+       "   <rect x=\"3.6\" y=\"3.6\" width=\"358.38\" height=\"338.58\"/>\n",
        "  </clipPath>\n",
        " </defs>\n",
        "</svg>\n"
       ],
       "text/plain": [
-       "<schemdraw.backends.mpl.Figure object at 0x124454390>"
+       "<schemdraw.backends.mpl.Figure object at 0x12546cf10>"
       ]
      },
      "metadata": {},
@@ -4038,25 +3942,30 @@
     "with schemdraw.Drawing() as sd:\n",
     "    flow.Start(w=2, h=1).label('START')\n",
     "    flow.Arrow().down(sd.unit/4)\n",
+    "    \n",
     "    b = flow.Box(w=2, h=1).label('x = 10')\n",
     "    flow.Arrow().down(sd.unit/4)\n",
-    "    d = flow.Decision(w=3, h=1.3, S='True', E='False').label('x = 10 ?').drop('S')\n",
-    "    flow.Arrow().down(sd.unit/3)\n",
-    "    b = flow.Box(w=3.7, h=1.3).label('「条件はTrueです。」\\nの表示')\n",
+    "    \n",
+    "    d = flow.Decision(w=3, h=1.3, S='False', E='True').label('x = 10 ?').drop('S')\n",
+    "    \n",
+    "    flow.Arrow().right().at(d.E).length(2)\n",
+    "    b = flow.Box(w=3.7, h=1).label('「条件はTrueです。」').drop('S')\n",
     "    flow.Arrow().down(sd.unit/4)\n",
     "    flow.Start(w=2, h=1).label('END')\n",
     "    \n",
-    "    flow.Arrow().right().at(d.E).length(2)\n",
-    "    b = flow.Box(w=3.7, h=1.3).label('「条件はFalseです。」\\nの表示').drop('S')\n",
+    "    flow.Arrow().down(sd.unit/3).at(d.S)\n",
+    "    b = flow.Box(w=3.7, h=1).label('「条件はFalseです。」')\n",
     "    flow.Arrow().down(sd.unit/4)\n",
     "    flow.Start(w=2, h=1).label('END')"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "hidden": true
+   },
    "source": [
-    "菱形枠中の`？`は「判断」を意味するが，上のコードの`#2`に対応している。`x=10`は`True`なので，菱形枠から下に移動して`条件はTrueです。`が表示されることになる。\n",
+    "菱形枠中の`？`は「判断」を意味するが，上のコードの`#2`に対応している。`x=10`は`True`なので，菱形枠から右に移動して`条件はTrueです。`が表示されることになる。\n",
     "\n",
     "次の例は上の例と似ているが少しだけ異なる。"
    ]
@@ -4064,7 +3973,9 @@
   {
    "cell_type": "code",
    "execution_count": 81,
-   "metadata": {},
+   "metadata": {
+    "hidden": true
+   },
    "outputs": [],
    "source": [
     "x = 20                        #1\n",
@@ -4078,7 +3989,9 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "hidden": true
+   },
    "source": [
     "＜コードの文の説明＞\n",
     "* 上の`if`文と異なるのは`#5`だけである。`pass`は「何もしない」という意味。\n",
@@ -4092,8 +4005,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 96,
+   "execution_count": 150,
    "metadata": {
+    "hidden": true,
     "tags": [
      "hide-input"
     ]
@@ -4101,17 +4015,17 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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-       "z\n",
-       "\" transform=\"scale(0.015625)\"/>\n",
-       "     </defs>\n",
-       "     <use xlink:href=\"#IPAexGothic-306e\"/>\n",
-       "     <use xlink:href=\"#IPAexGothic-8868\" x=\"100\"/>\n",
-       "     <use xlink:href=\"#IPAexGothic-793a\" x=\"200\"/>\n",
-       "    </g>\n",
-       "   </g>\n",
-       "   <g id=\"text_7\">\n",
-       "    <!-- END -->\n",
-       "    <g transform=\"translate(70.230781 323.624141) scale(0.125 -0.125)\">\n",
+       "   </g>\n",
+       "   <g id=\"text_7\">\n",
+       "    <!-- END -->\n",
+       "    <g transform=\"translate(233.760781 231.734141) scale(0.125 -0.125)\">\n",
        "     <defs>\n",
        "      <path id=\"IPAexGothic-45\" d=\"M 3547 63 \n",
        "L 609 63 \n",
@@ -6221,7 +6022,7 @@
        "   </g>\n",
        "   <g id=\"text_8\">\n",
        "    <!-- END -->\n",
-       "    <g transform=\"translate(232.230781 172.424141) scale(0.125 -0.125)\">\n",
+       "    <g transform=\"translate(59.160781 246.134141) scale(0.125 -0.125)\">\n",
        "     <use xlink:href=\"#IPAexGothic-45\"/>\n",
        "     <use xlink:href=\"#IPAexGothic-4e\" x=\"59.521484\"/>\n",
        "     <use xlink:href=\"#IPAexGothic-44\" x=\"135.498047\"/>\n",
@@ -6230,14 +6031,14 @@
        "  </g>\n",
        " </g>\n",
        " <defs>\n",
-       "  <clipPath id=\"p8cd2627a87\">\n",
-       "   <rect x=\"3.6\" y=\"3.6\" width=\"291.06\" height=\"350.46\"/>\n",
+       "  <clipPath id=\"p21ac84025e\">\n",
+       "   <rect x=\"3.6\" y=\"3.6\" width=\"324.72\" height=\"269.28\"/>\n",
        "  </clipPath>\n",
        " </defs>\n",
        "</svg>\n"
       ],
       "text/plain": [
-       "<schemdraw.backends.mpl.Figure object at 0x124e09590>"
+       "<schemdraw.backends.mpl.Figure object at 0x12555fe50>"
       ]
      },
      "metadata": {},
@@ -6248,25 +6049,19 @@
     "with schemdraw.Drawing() as sd:\n",
     "    flow.Start(w=2, h=1).label('START')\n",
     "    flow.Arrow().down(sd.unit/4)\n",
+    "    \n",
     "    b = flow.Box(w=2, h=1).label('x = 10')\n",
     "    flow.Arrow().down(sd.unit/4)\n",
-    "    d = flow.Decision(w=3, h=1.3, S='True', E='False').label('x = 10 ?').drop('S')\n",
-    "    flow.Arrow().down(sd.unit/3)\n",
-    "    flow.Box(w=3.7, h=1.3).label('「条件はTrueです。」\\nの表示')\n",
+    "    \n",
+    "    d = flow.Decision(w=3, h=1.3, S='False', E='True').label('x = 10 ?').drop('S')\n",
+    "    flow.Arrow().right().at(d.E).length(1.5)\n",
+    "    flow.Box(w=3.7, h=1).label('「条件はTrueです。」').drop('S')\n",
     "    flow.Arrow().down(sd.unit/4)\n",
     "    flow.Start(w=2, h=1).label('END')\n",
+    "#     flow.Start(w=2, h=1).anchor('W').label('END')\n",
     "    \n",
-    "    flow.Arrow().right().at(d.E).length(2)\n",
-    "    flow.Start(w=2, h=1).anchor('W').label('END')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "heading_collapsed": true
-   },
-   "source": [
-    "### 複数条件"
+    "    flow.Arrow().down(sd.unit/3).at(d.S)\n",
+    "    flow.Start(w=2, h=1).label('END')"
    ]
   },
   {
@@ -6275,56 +6070,17 @@
     "hidden": true
    },
    "source": [
-    "次に，複数の条件がある例を考える。`change_in_gdp`をGDPの変化だとしよう。次の表示がされる`if`文を作成する。\n",
-    "\n",
-    "1. `change_in_gdp`の値が正の場合，`GDPは増加しています。`を表示する。\n",
-    "1. `change_in_gdp`の値が負の場合，`GDPは減少しています。`を表示する。\n",
-    "1. `change_in_gdp`の値が`0`の場合，`GDPは変化していません。`を表示する。"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {
-    "hidden": true
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "GDPは増加しています。\n"
-     ]
-    }
-   ],
-   "source": [
-    "change_in_gdp = 200  #1\n",
-    "\n",
-    "if change_in_gdp > 0:\n",
-    "    print('GDPは増加しています。')\n",
-    "\n",
-    "elif change_in_gdp < 0:\n",
-    "    print('GDPは減少しています。')\n",
-    "\n",
-    "else:\n",
-    "    print('GDPは変化していません。')"
+    "`False`と判断されると，直ぐに`END`となっている。"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {
+    "heading_collapsed": true,
     "hidden": true
    },
    "source": [
-    "＜`if`文の説明＞\n",
-    "* `if`が１つ目の条件, `elif`が２つ目の条件, `else`が３つ目の条件を指定している。\n",
-    "* `if`, `elif`, `else` で始まる行の最後は`:`となる。\n",
-    "* `print` で始まる行には4つの半角スペースのインデントが入る\n",
-    "* `else`の行に`change_in_gdp==0`は不要（残りの可能性は`change_in_gdp==0`しかないため）\n",
-    "* `elif`は`else if`の省略形であり，２つ目の条件を定義する。\n",
-    "* `elif`は`if`と`else`の間に複数入れることが可能である。\n",
-    "\n",
-    "コードを実行すると，`#1`で`200`が`change_in_gdp`割り当てられているので`GDPは増加しています。`が表示されることになる。"
+    "### 複数条件"
    ]
   },
   {
@@ -6333,340 +6089,8888 @@
     "hidden": true
    },
    "source": [
-    "このコードを次のように入れ子の`if`文として書くことも可能である。"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {
-    "hidden": true
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "GDPは増加しています。\n"
-     ]
-    }
-   ],
-   "source": [
-    "change_in_gdp = 200\n",
-    "\n",
-    "if change_in_gdp > 0:               #1\n",
-    "    print('GDPは増加しています。')\n",
+    "次に，複数の条件がある例を考える。`change_in_gdp`をGDPの変化だとしよう。次の表示がされる`if`文を作成する。\n",
     "\n",
-    "else:                               #2\n",
-    "    if change_in_gdp < 0:           #3\n",
-    "        print('GDPは減少しています。')\n",
+    "1. `change_in_gdp`の値が正の場合，`GDPは増加しています。`を表示する。\n",
+    "1. `change_in_gdp`の値が負の場合，`GDPは減少しています。`を表示する。\n",
+    "1. `change_in_gdp`の値が`0`の場合，`GDPは変化していません。`を表示する。\n",
     "\n",
-    "    else:                           #4\n",
-    "        print('GDPは変化していません。')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "hidden": true
-   },
-   "source": [
-    "＜`if`文の説明＞\n",
-    "* `#1`と`#2`を使って`0`で条件分岐させている。\n",
-    "    * `#1`：`change_in_gdp`が正であれば`GDPは増加しています。`が表示される。\n",
-    "    * `#2`：`change_in_gdp`が非正の場合は次の条件分岐に進む。\n",
-    "* `#3`と`#4`を使って，`0`で条件分岐させている。\n",
-    "    * `#3`：`change_in_gdp`が負であれば`GDPは減少しています。`が表示される。\n",
-    "    * `#4`：`change_in_gdp`が`0`であれば`GDPは変化していません。`が表示される。\n",
-    "    \n",
-    "このコードを見ると，複数条件の場合に使う`elif`は`else if`の略だと気づくとはずだ。またコードを読んで感じることは，入れ子にすると可読性が落ちることである。複数条件の場合は，可能な限り`elif`を使うようにしよう。"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "heading_collapsed": true
-   },
-   "source": [
-    "### 関数化"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "hidden": true
-   },
-   "source": [
-    "`if`文は関数の中で使うことも可能である。GDPに関する例を使って考えてみよう。"
+    "`change_in_gdp`の値が`200`として，フローチャートで表すと次のようになる。"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {
-    "hidden": true
-   },
-   "outputs": [],
-   "source": [
-    "def gdp_change(change_in_gdp):\n",
-    "    \n",
-    "    if change_in_gdp > 0:\n",
-    "        print('GDPは増加しています。')\n",
-    "\n",
-    "    elif change_in_gdp < 0:\n",
-    "        print('GDPは減少しています。')\n",
-    "\n",
-    "    else:\n",
-    "        print('GDPは変化していません。')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
+   "execution_count": 138,
    "metadata": {
-    "hidden": true
-   },
-   "source": [
-    "＜関数の説明＞\n",
-    "* 引数が`change_in_gdp`\n",
-    "* `return`がないので返り値はなく，単に`print()`関数で表示をするだけとなる。\n",
-    "* `if`，`elif`，`else`の行は4つの半角スペースのインデントが入っている。\n",
-    "* `print`の行は8つの半角スペースのインデントが入っている。"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {
-    "hidden": true
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "GDPは増加しています。\n"
-     ]
-    }
-   ],
-   "source": [
-    "gdp_change(200)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {
-    "hidden": true
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "GDPは減少しています。\n"
-     ]
-    }
-   ],
-   "source": [
-    "gdp_change(-200)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {
-    "hidden": true
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "GDPは変化していません。\n"
-     ]
-    }
-   ],
-   "source": [
-    "gdp_change(0)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "heading_collapsed": true
-   },
-   "source": [
-    "### 直接真偽値を使う"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "hidden": true
-   },
-   "source": [
-    "`if`文を実行する上で，条件が真偽値`True`又は`False`を返すかで制御フローが分岐することが分かったと思う。ここで真偽値が重要な役割を果たしているが，`bool()`関数を使って真偽値をできることを思い出そう。空の文字列`''`や`0`などは「空」・「無」なので`False`となるが，それら以外は`True`となる。次の例はこの特性を使った例となる。"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {
-    "hidden": true
-   },
-   "outputs": [],
-   "source": [
-    "def truth_value(x):\n",
-    "\n",
-    "    if x:   # この行に着目\n",
-    "        print('真偽値はTrueです。')\n",
-    "\n",
-    "    else:\n",
-    "        print('真偽値はFalseです。')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "hidden": true
-   },
-   "source": [
-    "このコードで着目してほしいのは`if x:`の行である。引数`x`自体が条件文になっている。もし引数に文字列`abc`が使われると，`if 'abc':`となり，エラーが発生するのではと思うかも知れないが，そうならない。実は`if`文の場合，下の左と右のコードは同じなのである。\n",
-    "```\n",
-    "if x:　→　if bool(x):\n",
-    "```\n",
-    "この解釈はどの`if`文でも成立するので覚えておこう。"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {
-    "hidden": true
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "真偽値はTrueです。\n"
-     ]
-    }
-   ],
-   "source": [
-    "truth_value('経済学')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {
-    "hidden": true
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "真偽値はTrueです。\n"
-     ]
-    }
-   ],
-   "source": [
-    "truth_value('0')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {
-    "hidden": true
+    "hidden": true,
+    "tags": [
+     "hide-input"
+    ]
    },
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "真偽値はFalseです。\n"
-     ]
+     "data": {
+      "image/png": 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+       "    <!-- END -->\n",
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+       "  </g>\n",
+       " </g>\n",
+       " <defs>\n",
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+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "with schemdraw.Drawing() as sd:\n",
+    "    flow.Start(w=2, h=1).label('START')\n",
+    "    flow.Arrow().down(sd.unit/4)\n",
+    "    b = flow.Box(w=4, h=1).label('change_in_gdp = 200')\n",
+    "    flow.Arrow().down(sd.unit/4)\n",
+    "    d = flow.Decision(w=5, h=1.3, S='False', E='True'\n",
+    "                     ).label('change_in_gdp > 0 ?').drop('S')\n",
+    "    \n",
+    "    flow.Arrow().right().at(d.E).length(1.5)\n",
+    "    b = flow.Box(w=4., h=1.).label('「GDPは増加しています」').drop('S')\n",
+    "    flow.Arrow().down(sd.unit/5)\n",
+    "    flow.Start(w=2, h=1).label('END')\n",
+    "    \n",
+    "    flow.Arrow().down(sd.unit/2).at(d.S)\n",
+    "    d = flow.Decision(w=5, h=1.3, S='False', E='True'\n",
+    "                 ).label('change_in_gdp < 0 ?').drop('S')\n",
+    "\n",
+    "    flow.Arrow().right().at(d.E).length(1.5)\n",
+    "    b = flow.Box(w=4., h=1.).label('「GDPは減少しています」').drop('S')\n",
+    "    flow.Arrow().down(sd.unit/5)\n",
+    "    flow.Start(w=2, h=1).label('END')\n",
+    "\n",
+    "    flow.Arrow().down(sd.unit/3).at(d.S)\n",
+    "    b = flow.Box(w=4.5, h=1.).label('「GDPは変化していません」').drop('S')\n",
+    "    flow.Arrow().down(sd.unit/4)\n",
+    "    flow.Start(w=2, h=1).label('END')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "hidden": true
+   },
+   "source": [
+    "このフローチャートをコードに落とし込むと次のようになる。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "hidden": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "GDPは増加しています。\n"
+     ]
+    }
+   ],
+   "source": [
+    "change_in_gdp = 200  #1\n",
+    "\n",
+    "if change_in_gdp > 0:\n",
+    "    print('GDPは増加しています。')\n",
+    "\n",
+    "elif change_in_gdp < 0:\n",
+    "    print('GDPは減少しています。')\n",
+    "\n",
+    "else:\n",
+    "    print('GDPは変化していません。')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "hidden": true
+   },
+   "source": [
+    "＜`if`文の説明＞\n",
+    "* `if`が１つ目の条件, `elif`が２つ目の条件, `else`が３つ目の条件を指定している。\n",
+    "* `if`, `elif`, `else` で始まる行の最後は`:`となる。\n",
+    "* `print` で始まる行には4つの半角スペースのインデントが入る\n",
+    "* `else`の行に`change_in_gdp==0`は不要（残りの可能性は`change_in_gdp==0`しかないため）\n",
+    "* `elif`は`else if`の省略形であり，２つ目の条件を定義する。\n",
+    "* `elif`は`if`と`else`の間に複数入れることが可能である。\n",
+    "\n",
+    "コードを実行すると，`#1`で`200`が`change_in_gdp`割り当てられているので`GDPは増加しています。`が表示されることになる。"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "hidden": true
+   },
+   "source": [
+    "このコードを次のように入れ子の`if`文として書くことも可能である。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "hidden": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "GDPは増加しています。\n"
+     ]
+    }
+   ],
+   "source": [
+    "change_in_gdp = 200\n",
+    "\n",
+    "if change_in_gdp > 0:               #1\n",
+    "    print('GDPは増加しています。')\n",
+    "\n",
+    "else:                               #2\n",
+    "    if change_in_gdp < 0:           #3\n",
+    "        print('GDPは減少しています。')\n",
+    "\n",
+    "    else:                           #4\n",
+    "        print('GDPは変化していません。')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "hidden": true
+   },
+   "source": [
+    "＜`if`文の説明＞\n",
+    "* `#1`と`#2`を使って`0`で条件分岐させている。\n",
+    "    * `#1`：`change_in_gdp`が正であれば`GDPは増加しています。`が表示される。\n",
+    "    * `#2`：`change_in_gdp`が非正の場合は次の条件分岐に進む。\n",
+    "* `#3`と`#4`を使って，`0`で条件分岐させている。\n",
+    "    * `#3`：`change_in_gdp`が負であれば`GDPは減少しています。`が表示される。\n",
+    "    * `#4`：`change_in_gdp`が`0`であれば`GDPは変化していません。`が表示される。\n",
+    "    \n",
+    "このコードを見ると，複数条件の場合に使う`elif`は`else if`の略だと気づくはずだ。またコードを読んで感じることは，入れ子にすると可読性が落ちることが分かる。複数条件の場合は，`elif`を使うようにしよう！"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "heading_collapsed": true,
+    "hidden": true
+   },
+   "source": [
+    "### 関数化"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "hidden": true
+   },
+   "source": [
+    "`if`文は関数の中で使うことも可能である。GDPに関する例を使って考えてみよう。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "hidden": true
+   },
+   "outputs": [],
+   "source": [
+    "def gdp_change(change_in_gdp):\n",
+    "    \n",
+    "    if change_in_gdp > 0:\n",
+    "        print('GDPは増加しています。')\n",
+    "\n",
+    "    elif change_in_gdp < 0:\n",
+    "        print('GDPは減少しています。')\n",
+    "\n",
+    "    else:\n",
+    "        print('GDPは変化していません。')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "hidden": true
+   },
+   "source": [
+    "＜関数の説明＞\n",
+    "* 引数が`change_in_gdp`\n",
+    "* `return`がないので返り値はなく，単に`print()`関数で表示をするだけとなる。\n",
+    "* `if`，`elif`，`else`の行は4つの半角スペースのインデントが入っている。\n",
+    "* `print`の行は8つの半角スペースのインデントが入っている。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "hidden": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "GDPは増加しています。\n"
+     ]
+    }
+   ],
+   "source": [
+    "gdp_change(200)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "hidden": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "GDPは減少しています。\n"
+     ]
+    }
+   ],
+   "source": [
+    "gdp_change(-200)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "hidden": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "GDPは変化していません。\n"
+     ]
+    }
+   ],
+   "source": [
+    "gdp_change(0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "heading_collapsed": true,
+    "hidden": true
+   },
+   "source": [
+    "### 直接真偽値を使う"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "hidden": true
+   },
+   "source": [
+    "`if`文を実行する上で，条件が真偽値`True`又は`False`を返すかで制御フローが分岐することが分かったと思う。ここで真偽値が重要な役割を果たしているが，`bool()`関数を使って真偽値をできることを思い出そう。空の文字列`''`や`0`などは「空」・「無」なので`False`となるが，それら以外は`True`となる。次の例はこの特性を使った例となる。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "hidden": true
+   },
+   "outputs": [],
+   "source": [
+    "def truth_value(x):\n",
+    "\n",
+    "    if x:   # この行に着目\n",
+    "        print('真偽値はTrueです。')\n",
+    "\n",
+    "    else:\n",
+    "        print('真偽値はFalseです。')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "hidden": true
+   },
+   "source": [
+    "このコードで着目してほしいのは`if x:`の行である。引数`x`自体が条件文になっている。もし引数に文字列`abc`が使われると，`if 'abc':`となり，エラーが発生するのではと思うかも知れないが，そうならない。実は`if`文の場合，下の左と右のコードは同じなのである。\n",
+    "```\n",
+    "if x:　→　if bool(x):\n",
+    "```\n",
+    "この解釈はどの`if`文でも成立するので覚えておこう。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "hidden": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "真偽値はTrueです。\n"
+     ]
+    }
+   ],
+   "source": [
+    "truth_value('経済学')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "hidden": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "真偽値はTrueです。\n"
+     ]
+    }
+   ],
+   "source": [
+    "truth_value('0')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "hidden": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "真偽値はFalseです。\n"
+     ]
+    }
+   ],
+   "source": [
+    "truth_value(0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "hidden": true
+   },
+   "source": [
+    "真偽値を使ったもう１つの例を紹介しよう。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "hidden": true
+   },
+   "outputs": [],
+   "source": [
+    "def my_wallet(money_in_my_wallet):\n",
+    "    \n",
+    "    if money_in_my_wallet:   #1\n",
+    "        print('なに買おうかな😄')\n",
+    "    \n",
+    "    else:\n",
+    "        print('一文なしだよ😅')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "hidden": true
+   },
+   "source": [
+    "実行してみよう。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "hidden": true
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "一文なしだよ😅\n"
+     ]
+    }
+   ],
+   "source": [
+    "my_wallet(0)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "hidden": true
+   },
+   "source": [
+    "＜`#1`の`if money_in_my_wallet:`について＞\n",
+    "* `if money_in_my_wallet != 0`と同じである。だが`if money_in_my_wallet:`の方がより簡単で`Python`的（Pythonic）だと言える。\n",
+    "* `if money_in_my_wallet:`は「もしお財布にお金があれば」と読めるため，より直感的でもある。"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "heading_collapsed": true,
+    "hidden": true
+   },
+   "source": [
+    "### 数値を返す例"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "hidden": true
+   },
+   "source": [
+    "今までの例では`print()`関数を使ったが，もちろん数値を返す`if`文を書くことも可能であり，むしろそれが一般的だろう。次の関数を考えてみよう。\n",
+    "\n",
+    "$$\n",
+    "y = \\left|x\\right|\n",
+    "$$\n",
+    "\n",
+    "まず，フローチャートを考えてみる。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 204,
+   "metadata": {
+    "hidden": true,
+    "tags": [
+     "hide-input"
+    ]
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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GjeHk5IRmzZqVm6NARET07lhEtExUVBQcHR0RGRmJli1bSh2HiIjotXjXDBEREUmGRYSIiIgkwyJCREREkmERISIiIsmwiBAREZFkWESIiIhIMiwiREREJBkWESIiIpIMiwgRERFJhkWEiIiIJMMiQkRERJJhESEiIiLJsIgQERGRZFhEiIiISDIsIkRERCQZFhEiIiKSDIsIERERSYZFhIiIiCTDIkJERESSYREhIiIiybCIEBERkWRYRIiIiEgyLCJEREQkGZkQQkgdgt7NgAED8OeffwIAcnJy8ODBA1hZWUFPTw/jx4/H2LFjJU5IRERUMD2pA9C7a968ORQKRZ5lDx48AAC0a9dOikhERERq4RERLXD16lU0adIk33ILCwvExcVBR4dn4IiISDPxL5QWsLe3R926dfMt9/b2ZgkhIiKNxr9SWkAmk8HHxyff8oKWERERaRIWES3x39JhYGAADw8PidIQERGph0VES7i6usLExCT3azc3NxgbG0uYiIiI6M1YRLSEvr4+unXrlvt1jx49JExDRESkHhYRLfJq+WARISKisoC372qRpKQkWFhYoGnTpvjrr7+kjkNERPRGHNBMi1SvXh3t2rVD586dpY5CRESkFhYRLePj48MiQkREZYYkp2Zu3ryJ58+fl/Zuy4X4+HiYm5tzILMSUrlyZTRo0EDqGEREWqPUj4jcvHkTDRs2LO3dEhWbGzdusIwQERWTUi8iL4+EbNmyBfb29qW9e6K3Fh0dDX9/fx7NIyIqRpJdI2Jvb4+WLVtKtXsiIiLSALyQgIiIiCTDIkJERESSYRF5C0+ePClweWpqKh49elTKaYCQkBDcvHmz1PdLRET0rlhEiig9PR2WlpY4c+ZMvudCQ0Px/vvvv9V2N27ciEuXLr3VunPnzkVERMRrX3P69Gn4+/sX+FxiYiISExMLfO7AgQM4efJkkTNlZmZCJpPh8OHDeZanp6cXeVtERKS9ytWAZhs3bsT169fx3XffvfU2fv/9dxgYGKB58+Z4+vRpnufu3LkDGxubPMt1dXVRuXLl124zNTUVn332GdatW6dWkXn27BlUKlXu10qlEunp6Xn2a2hoCENDw9yvExMTcerUqQK3t3DhQgQHB+PevXv5nvvpp58AAAcPHiw0z4MHD/D5559j+fLlsLKyKvR1CQkJaNSoEVavXo2+ffsW+rrCpKamIiEhAfHx8UhNTc0zyd+r7t69i7S0NDx58gSPHz9GQkICHj58iNjYWPTu3Zvz8BARaZByVUS2bdsGY2PjAp9LTU1Feno6VCoVVCoVqlSpUuBr9+/fD29vb1y7dg0tWrQocFvVqlXL/e/69evj1q1b+V5z//59VK5cGXp6etiyZQv09fVRt25d7Nu3D1evXoWRkRG++OKLArf//vvvo0KFCqhSpQqAfwrQggULsGrVKgDA33//jc8++wzVq1fHzp07cfz48df+f4mJiUG9evUKfK569eoF5n/Ve++9h5s3b2LIkCE4dOhQoa+bP38+9PT04OHhke+5tLQ03Lt3D/fu3cPdu3dz/zs2Nhbx8fGIj49HWlpa7utr1aqF2NjYAvfj5uaGhIQE1KhRI/dx8+ZN/PXXXzAzM2MRISLSIOWqiPz555+YO3du7tcvT1ckJCTkO2Xw008/Yfz48XmWKZVKKBQKbNiwAc2bN8d/B6Vt3bo1hg0bhpEjR742x4sXL1C7du18y93d3WFhYQFbW1t07dr1tdv48ccfc1/j7OyMCRMmwNfXFzKZDMOHD3/tuv/18OFD1K1bt8DnzMzMcP78+deur6+vj5UrV8LFxQU7d+5E7969873m0qVL+PnnnxEYGJhboF4KDw+Hp6cngH9GLrWzs4OtrS1sbW3RrVs3hIWFYefOnRg8eDD8/PzQtm3bPGXvv65evZrnaNDvv/8OT09PfPvtt5g+ffpr3wsREZWuMlNEnjx5gnr16qFRo0b4888/8yxv3749MjIy8Oeff6JGjRoFrn/v3j08efIETk5Oucvq1auHgIAA1KxZE1ZWVqhUqRJkMhl0dHQKPBoSFhaGhISEPNsAADs7O9y7dw9ZWVn466+/MG7cOACAq6trgac09PX1kZycjKysLGzevBmbNm3CyZMnX/vH9VV79uzB9evX4eDgAOCfoytffvklZsyYgRo1amDTpk0wMDDAtm3b1Nre48eP0b59+wKfMzQ0RGZm5hu30aFDB3h6eiIkJKTAIvLNN9+gQ4cO+PTTT/M91759exw6dAiNGjVCrVq1cperVCr4+/vj4sWL+Ouvv9C4cWO13s+rJeTs2bPo3bs3lixZgo8//lit9YmIqBSJUhYZGSkAiMjIyCKvO3fuXAFA7N+/XwghREZGhujQoYMwNTUV0dHRr133wIEDQiaTifT09LfKLYQQzs7OAoB49OiRWLdunfD29hZCCGFtbS2OHTuW57Xr168XHTt2fO32EhMTRe3atUX//v2Fubm5qF69uggMDMzzmszMTHHz5s3XbsfR0VEEBwfnW75o0aLcDKGhocLa2rrA9evWrSvmzZsnrl27Jnbt2pXnuenTpwsLC4vX7v+lp0+f5v53RkaGACAOHTqU+/WjR4/U2s5L48aNE/Xq1RNJSUlFWu+lP//8U1hYWIjQ0NC3Wv+/3uV7l4iIClam7poZN24cLCwsMGvWLKhUKgwaNAjnz5/H7t270ahRo9euGxMTA0tLSxgZGb3Vvg8ePIi4uLjcr7OyspCampr7ddeuXXMvEDU0NMQnn3zyxm2OHj0aDx48wHvvvYdDhw5hzpw5GDNmDC5evIhLly5h3LhxsLKyQrdu3ZCTk5Nn3fr166N69eqoXr06Ll68iGHDhuV+vXDhwiK9N2NjYyiVSnz11Vc4cuRInudUKtUbJ9Br27YtZDIZqlatCplMBplMlvv/2cPDI/fr9957DzKZDG3btn1jpujoaCxZsgQbNmyAmZlZkd4PABw5cgRdu3aFnZ0d5s+fD1NTU1SsWBH29vaYOnUqh2knItIQZebUDPDPH8ypU6di7Nix6NKlC06cOIHg4GA4Ozu/cd3k5GRYWFi81X5fvHiB0aNH4+uvv8aoUaMKfM3BgwfRqVOn3K83bNiADRs2FLrNJUuWICQkBFu2bMGAAQMAAE2bNsWiRYvg5uaG1NRU9OzZE7/88gu6d+8OPb28H9XVq1dzr1F59RoRAPle+yZVq1ZFWFgYbty4gc2bN+d5Li0trdALfF8KCwvDixcv1NrXDz/8UOjdO69as2YN7O3t4eLiotZ2XxUcHAx/f3/o6+vD1tYWffr0Qf369SGTyXD+/Hl8++232LNnD/78809UqlSpyNsnIqLiU6aKCACMHDkSs2fPxrFjx7B06VJ88MEHaq334sULGBkZ4f79+3jy5AmaNm2q9j5TU1NhZ2eH7t27v23sPI4dO4YJEyZg9erVuSXk2LFjGD9+PG7fvo0WLVogPDy8wCMB2dnZ8PHxybPs1q1bWLhwITZu3Ji77P3330fNmjXVylO/fn1s3LgR3333Xb7rVOLi4t64HVNTU7X2A0DtP/zR0dFo0qSJ2tt9aeHChZg8eTJ8fX2xfPlyWFpa5nm+YcOG6Ny5M+rVq4cNGzYUemcSERGVjjJXRBYvXozk5GQAgImJidrrGRoaQqVS4YcffoCuri5++OEHDB8+HF999dUb/+CZmppix44duH//fqGv6d69O3R1dXO/zsnJKfQUhL6+PmbOnImhQ4cCAL799lvMnz8fM2fORPfu3XHixIlCT0fo6urmu+iyoIsw33vvPVy4cOG17+slFxcX/Prrrxg8eHC+56KiouDm5vba9TMyMvD48WO19vXs2TO1XvfixQu1j7K89Ouvv2Ly5Mn4/vvv8dVXXxX6uho1asDOzg5Xrlwp0vaJiKj4lalrRF7+oZk8eTKaNm2KWbNmqf3HytjYGPfv38f69esxevRoyGQybN26FdHR0Wqt/6bTHfv370dqamruY8WKFYW+1tnZOfc20l9//RULFizA8ePHMWnSJJiZmaFixYqFrqujo4O+ffsiJycHly9fLvDRvn17dOzYUa33BQDDhw9HZmZmviMfZ8+exe3bt9GlS5fXrr9r1y7Url1brceiRYvUytS0aVP8/vvvRRqJ1c/PDwcPHsRXX32FP//8Ey1atEClSpXg6uqKs2fP5r4uMzMT9+7dU/uIERERlZwyU0SOHj2KoUOHYuDAgfjuu+8wc+ZM3L17N3cQrzcxNTXFgwcP4OzsDBsbGwD/FIJp06bh+PHjuaOVPnv2DLGxsfjf//6HjIwMtfN9/PHHaN68ee7jm2++UWu9jRs34qOPPkLr1q0BABMmTMg3LHpBFAoFTp48iczMzDyPgICA3Itqrays1D4F9d8LUp89e4aPP/4YtWrVKvB23FfJ5XIIIdR6zJw5U608n3zyCZ4/f45hw4ap/Tno6urmlqYPP/wQvr6+uHPnDvr06YMuXbogMjISQghMmDAB2dnZGDRokFrbJSKiklMmTs1cunQJvr6+cHFxwbp16yCTyfDBBx+gWbNmmDdvHoYNG/baowgAUKdOHQBAr169cpetXbsWAwYMQOfOnQtc58SJE3B1dX1jvrt376r/Zv6jZs2aOHjwIA4fPowWLVrk3nmSkZGB5ORkPHjwAE5OTgUekfHy8sKECRPyLHv1SEy/fv3Qr1+/Imf63//+B39/f9y4cQMHDhyAvr5+0d/YO2rcuDHWrVuH4cOH4+TJk/Dz80P79u1Rv359NG7cOM9YIQWRyWR4+PAh9PT0MHLkSFy5cgX+/v6oWrUqLl++jG3btuUWUiIiklBp3y9c1LEYYmJihJWVlWjatKlISUnJ89yOHTsEADF//vw3bicuLk5YWlqKo0eP5nvu1q1bYvfu3WLz5s0iKChIhIeHi4iICPHs2bM8r/v7779zxxH55ZdfBAC1HgWN8fHS48ePhVwuF5UrVy5wXX19ffHw4cN86/Xq1Uvo6ekJAwODPA8A4ty5c7l5Q0JCxPnz58XMmTNF/fr1X/v/KD09XXz44YdCT09P1KpVK9/YKIV5Ob6Kuo82bdqotV0hhLh+/br49NNPxXvvvZe7/r59+9643p9//ilatmyZZ782NjZi7NixIjY2Vu39v4rjiBARFT+NPyJSu3btQi8S9fX1zTfMemFq1KiBhw8fFvhc/fr1Ub9+/SJna9++PXbt2vXG173uolpTU1P89ttvEEIgMTERz58/h56eHipXrozKlSu/9mjE/Pnz8x0RqVq1au5/K5VKjBs3DikpKdDR0cGIESNem9PIyAitWrVC8+bN8dlnn6l9h0tISIhao68C/1xsXNDMxYVp2LAhVq5ciZUrV+LevXuIiYmBra3tG9dr27YtIiMjkZqaipSUFFStWvWNtyETEVHpkwl1/5IXk6ioKDg6OiIyMhItW7YszV1rlZiYGBgbG7/VYF/0dvi9S0RU/DT+iAgV7OU1L0RERGVZmblrhoiIiLQPiwgRERFJptSLyMtRUZ88eVLauyYiIiINU+pF5OW8JP+d04SIiIjKH56aISIiIsmwiPxr7969Bc6DEhUVhbVr16q1DSEElEplcUcrsuzsbNy/fx/dunVTe5K5sur333/Ht99+qxH/34mIqOh4+y6A06dPY/DgwTh06FC+57Zt24YrV67A2toaqamp+Z5v2bJl7q204eHhGDlyZKFDvt+/fx+jR49Gp06d0LNnT9StW7dIOdPT0wsdyl4IgXv37sHS0hJeXl4YOHAgTE1N8dVXX2H16tVF2k9Z0qZNG0ybNg2PHj3C0qVLpY5DRERFVO6PiKSlpaFv376YP39+gYNUHT9+HB07dsTIkSPh6+ub73H06FG19/Xs2TPUrVsXS5YsQb169eDs7Ixt27apvb6TkxMWLlxY4HM5OTmoW7cuTp8+jRkzZmDChAmYPn06KleurPbosyUpNTUVs2bNgo+PD2rUqAGZTIYhQ4YU+nqlUomAgADY2trCwMAAtra2CAgIyHfkQ19fHyEhIdi4cSNCQ0NL+F0QEVFxK/dFZOHChTAzM8Pw4cPzPZeQkIBz587Bw8MD586dw/nz5wEA9+7dw6NHj/Do0SO0atUKMplMrSHOGzdujJ9++gl37tzB77//DgsLC7WLSFJSEqKjo9G4ceMCn69QoQKAfwpJ586dMXr0aFSpUgU//fQTZDKZWvsoSUlJSZg9ezYiIyPh5OT0xtePHj0aU6ZMgaurK5YvXw5XV1dMmTIFY8aMyfdac3NzTJ06FZMmTUJ2dnZJxCciohJSrk/NKJVKLFu2DAsXLoSurm6+53fu3AlLS0s0a9YMwD/DqtesWTPPqKZPnz59q3136NABHTp0gEqlUuv1ERERAP6Z3wYAMjMzkZ2dDWNjY+jo6EClUkFPTw+3b99GWFgYKlas+No5bkpbjRo1cP/+fVhZWSEnJye3OBXkf//7H1asWIExY8ZgyZIlAICPP/4YlStXRmBgIEaOHImmTZvmWeeLL77A7NmzsW/fPvTu3bsk3woRERWjcn1E5Pfff8fTp0/h4+NT4PObNm1C7dq1c78+c+YMnj59iubNm6N58+aYOXOmWvvJzMzEvXv3cO7cOezbtw8rV67EpEmT0L9/f7i7uxc6qd+rLl68iDp16uTe/rxt2zaYmJhAV1cX+vr60NXVRU5ODkaNGoWhQ4di165dSEtLUytfaTAwMICVlZVar1UoFBBCYNy4cXmWjxs3DkIIKBSKfOsYGxvDw8NDrUkIiYhIc5TrInL27FnUr18f5ubm+Z67ePEiTp8+nWdZWFgYxo4di2XLlsHT0xN//PGHWvtZvnw5bGxs0Lp1a/Tr1w8rVqxAXFwc4uLi8PvvvyMqKuqN24iOjsb777+f+3X//v1x9+5dREdH4+LFi7h58yYqVaqE4OBgJCQk4M8//0SNGjXUyqdpzp8/DwsLi3wX89atWxfm5uaIjIwscL127drh7NmzpRGRiIiKSbk+NfPw4UNYWloW+FxAQAAMDQ1zv758+TKio6MRHh6OmjVr4siRI2jQoIFa+/H390erVq1Qv3591KxZEzKZDEePHkWPHj2wceNG9OzZ843buHfvHlq0aJH7taGhIaytrfO8Rl9fX+1TPZosLi6u0KMnVlZWePDgQYHP1ahRA/Hx8SUZjYiIilm5LiIZGRkwNjbOtzw6OhqhoaH48ssvc++KWbRoEfT09LB//34MHz4cFy5cQI8ePdTaj4WFBSwsLHK/vnDhAnx9fbFkyRIMHDhQrW0kJCTkOU1UEH19feTk5Ki1vbeRnZ2N27dvq/XaihUrvvUMwenp6ahcuXKBzxkaGhY6NoqxsbFGnY4iIqI3K9dFxMLCosBD+TY2Nli4cCFMTExw9OhRREZGYvPmzdi4cSO+/fZbnD59Gr///jt+/PHHIt8ae+3aNXTr1g1TpkzB0KFD1V4vLS0t91bcwu6CKeki8uDBA9jb26v12o4dO+L48eNvtZ+KFSsiKyurwOcyMzNhZGRU4HPx8fF5Ch8REWm+cl1E6tWrh7t370KlUkFH5/8vlzEyMsKYMWOwYcMGAP9M0Ddy5EgMGDAAnp6e8PDwQK1atVC/fn3cunVL7f3dvXsXHh4eePLkCb799lvMmTMHu3btgoeHxxvX1dPTQ4UKFTBy5Eh4e3vnns7JycnBkydPULVqVVSoUKFEb1+1sLDA/v371Xrty4tq30bNmjVx8eLFAp978OBBnlNUr7p9+zbq1av31vslIqLSV66LiKenJ4YNG4Y//vgDLi4uhb6uS5cu6NKlC4B/JuvT19fHxx9/XKR9xcbGonPnztDT08OOHTvg5uYGFxcXbN++Xa0iYmJigqtXr2L79u2YP38+0tPTMWrUKPz222948eIF9PT0IITAqVOn0KtXL1SvXr1I+dRhZGQET0/PYt/ufzk6OuLgwYP4+++/81yw+vfffyMxMRGOjo4Frrd37158+umnJZ6PiIiKT7m+a8bCwgKdO3fGli1b1F5n+fLlSExMxLBhwwAAlStXxsCBAwsch+Sl+/fvo3PnzqhRowYiIyPh4+MDY2NjNGrUqMBh4wtiZmaG5cuXY+jQoTA1NcUPP/yAqKgoXL9+HS9evMCNGzdQu3ZtHDlyBFZWVhgxYkSeizo3bNgAmUyGSpUqqf1epeLn5weZTIbFixfnWb548WLIZDL4+fnlWyciIgJ3795F3759SyklEREVh3J9RAQA5s+fD2dnZ4wfPx6NGjV67WvDw8MxceJEHDx4EPr6+gD+KTOvKzL37t2Dm5sbrKysEBYWlqcIWFpa4sSJE3j27BkqVqyIJ0+e4Pbt22jdunWeU0UAUL9+fRw/fhyDBg3KXZaVlYVnz57BwsICjx8/RkJCAn799VfUqVMHn3/+Ofr375/vFuOCLs4tLcuWLcPTp09z7+y5dOkS5s6dCwDo2bNn7u3JzZo1w6effoqlS5fi+fPncHZ2xh9//IH169djxIgReW5jfunrr7/GiBEjijx/DxERSavcF5FWrVphxIgRGDFiBA4fPlzoiJ9r1qzB6NGjsWzZMjg7O+d5buXKlahQoQIiIiJyC8pLQ4cOhbm5eb4SAgCffvopQkNDUaVKlTzLHz16lO/Uiq2tLSpUqJA7ouj48eMRHR0NR0fH3AtUe/ToAW9vb1SoUAF//PEHkpOTc9f39fXFX3/9hYcPHxbh/07x+uGHH3Dv3r3cry9cuIALFy4AAGrVqpWnYCxbtgx16tTBmjVrsGXLFtSqVQvz5s3DxIkT82131apViI2N5VwzRERlkShlkZGRAoCIjIws7V0XKjs7W3Tt2lUMHTo0z/L169eLNm3aiPT0dNGuXTuxefPmAtf/7LPPRIsWLcT7778vVqxYkee5xMRE8eTJk9fuPy4uTty4cUM8ePBAZGZmFviahIQEER0dXWD2+/fvi2fPnr12Hzdu3BDvv/++uHPnzmtfV9YcPnxYmJmZicuXL5f4vjTxe5eIqKyTCVG6U7NGRUXB0dERkZGRBc52q6nEa26bpfKhrH7vEhFpsnJ9sWpRsIQQEREVPxYRIiIikgyLCBEREUmGRYSIiIgkI9ntu9HR0VLtWus9efIE1apVkzqG1uH3LBFR8Sv1IvJyVlV/f//S3jVRsShsZmAiIiq6Ur99FwBu3ryJ58+fl/Zuy4Xo6Gj4+/tjy5Ytas+US+qrXLkyGjRoIHUMIiKtIcmpGf4iL3n29vYc64KIiDQeL1YlIiIiybCIEBERkWRYRIiIiEgyLCJEREQkGRYRIiIikgyLCBEREUmGRYSIiIgkwyJCREREkmERISIiIsmwiBAREZFkWESIiIhIMiwiREREJBkWESIiIpIMiwgRERFJhkWEiIiIJMMiQkRERJJhESEiIiLJsIgQERGRZFhEiIiISDIsIkRERCQZFhEiIiKSjJ7UAejd7dq1C0+ePAEA3L17FwCwe/duXLp0Cfb29mjTpo2E6YiIiAonE0IIqUPQuxk2bBjWr19f4HObNm3CoEGDSjkRERGRenhqRgv4+PgUuFxHRwdeXl6lnIaIiEh9LCJawMPDA/r6+vmWt2/fHmZmZhIkIiIiUg+LiBaoVKkS3Nzc8i0v7EgJERGRpmAR0RIFlY4ePXpIkISIiEh9vFhVS9y7dw82Nja5X9erVw+3bt2CTCaTLhQREdEb8IiIlrC2tsb777+f+7WPjw9LCBERaTwWES3y6ukZXh9CRERlAYuIFnlZPkxMTODi4iJxGiIiojfjyKpapFWrVjA3N0fHjh0LvJ2XiIhI07CIaBEdHR14e3ujc+fOUkchIiJSC0/NaJGbN29CpVIhKSkJjx8/ljoOERHRG/H23TIuJiYG27Ztg0KhQGRkJIyMjJCVlQUdHR14eHhALpejV69eqFKlitRRiYiI8uERkTIoPj4egYGBcHZ2hrW1NWbMmAEbGxsEBwcjKSkJcXFxWLJkCVJTUzF48GBYWFjA19cXQUFBSEtLkzo+ERFRLh4RKSMeP36M7du3IygoCMePH4euri66desGuVyOnj17onLlygWuFxsbi+DgYAQFBeHs2bOoWLEievbsCT8/P3h6esLQ0LCU3wkREdH/YxHRYCkpKdi5cyeCgoJw6NAhqFQquLu7w8/PD76+vjA1NS3S9u7cuYOgoCAoFApcunQJJiYm8PX1hVwuh7u7OypUqFBC74SIiKhgLCIaJi0tDXv37oVCoUBYWBhevHgBFxcXyOVy9OnTBxYWFsWyn+joaAQFBeG3337DjRs3YGZmhj59+kAul8PV1RW6urrFsh8iotKSlZWFK1eu4Pr164iNjUVycjIyMjKgLX/mdHR0YGxsDHNzc1hbW8Pe3h4NGjSAjk7ZvsqCRUQDZGZm4sCBA1AoFNizZw/S09PRunVryOVy9OvXD7Vq1SqxfQshcPHiRSgUCgQFBeHu3buwtLRE//794efnh7Zt25b5b3Ii0l5Xr17F9u3bER4ejnPnzuHFixcAgCpVqsDMzAxGRkZa8ztMqVQiLS0NCQkJyMzMBPDP+3RxcYGXlxd8fX1haWkpccqiYxGRSHZ2Ng4fPoygoCCEhobi2bNnaNasGfz8/ODn54d69eqVeiYhBM6ePQuFQoFt27YhLi4OderUgZ+fH+RyOVq0aMH5a4hIcllZWdi6dSuWL1+OqKgoVK5cGR4eHujUqRNatWoFe3t7rb5TUAiBhIQEXL58GWfOnMHRo0fx+++/Q6VSwcvLC2PGjEGXLl3KzO9rFpFSpFQqcfLkSSgUCmzfvh2PHz+GnZ0d5HI5/Pz8YG9vL3XEXCqVCqdOnYJCoci9G8fW1hZyuRxyuRxNmjSROiJpuJs3b+L58+dSx6B/Va5cGQ0aNJA6xjtRKpVYt24dZs+ejbi4OHh5eeHjjz9G9+7dYWBgIHU8SSUnJ2Pbtm1YuXIl/vrrL7Rq1QoLFiwoGwNcCipRSqVS/PHHH2L06NHC0tJSABA2NjZi8uTJ4sKFC0KlUkkd8Y2ys7NFeHi4GDp0qKhSpYoAIBwcHMTcuXPFzZs3pY5HGujGjRsCAB8a9rhx44bU3xpvLSoqSrRo0UIAEAMGDBDR0dFSR9JIKpVKHDx4ULRp00YAEP379xcJCQlSx3otHhEpAUIIREVFISgoCEFBQYiJiUHNmjXRv39/yOVytG7duswcMvuvrKwsHDx4EAqFArt27UJaWhocHR0hl8vRv39/1KlTR+qIkrl79y7q1q2r1mtnzpyJWbNmlWwgCUVFRcHR0RFbtmzRqCN95VV0dDT8/f0RGRmJli1bSh2nSIQQ+P777zFt2jQ0btwYq1atQps2baSOpfGEENi6dSvGjx8PmUyGTZs2wdPTU+pYBZO0BmmZy5cvi+nTpwtbW1sBQFSvXl189tln4sSJE0KpVEodr9ilpaWJ4OBg0adPH2FgYCAAiPbt24ulS5eKhw8fSh2v1L148UJER0fnebi7u4uaNWvmW/7o0SOp45aoyMhIAUBERkZKHYVE2f080tLSRN++fQUAMWnSJJGVlSV1pDInPj5edO/eXchkMhEQEKCRR+FZRN7RjRs3xLfffiscHBwEAFG1alUxbNgwER4eLrKzs6WOV2pSUlLE5s2bhbe3t6hQoYLQ0dERbm5uYtWqVSIpKUnqeJLp1auXsLa2ljpGqSurf/i0VVn8PJ4+fSqcnZ1FxYoVRWhoqNRxyjSlUimmTZsmAIgxY8ZoXBnRjnuaSllMTAx++OEHODk5oWHDhggICECzZs2we/duxMfHY+3atejatSv09MrP5MYmJibw9/fH3r17ER8fj1WrVkFHRwcjR46EpaUlvLy8sGnTJqSkpEgdVSPcvXsXMpkMO3fuxJ49e1CvXj2MHTsWANCpUyc0b9483zoFLc/KysL06dNhY2MDIyMjNG7cGN9//33uLYxEZVFqaio8PT1x5coVHD16FL1795Y6Upmmo6ODuXPnYsWKFQgMDMTYsWM1amyV8vOX8h3Fx8cjODgYCoUCp0+fhqGhIby9vTF58mR4eXmhYsWKUkfUGKamphg+fDiGDx+OhIQEbN++HQqFAoMHD4aBgQG6d+8OuVyOHj16wNjYWOq4krp27Rp27tyJVatW4f333y/SuiqVCr1798aNGzfw3XffoVGjRoiMjMTUqVMRERGBkJCQEkpNVHKUSiXkcjkuX76MY8eOwcnJSepIWmPEiBEAgJEjR8LKygqTJk2SONE/WEReo7D5XbZs2fLa+V3o/1lYWGDUqFEYNWpUnnlv5HI5570BsHLlSpw6dQpWVlZFXjc4OBhHjhzBrVu3ci8SbtmyJWrUqAEfHx+cP3+ev8SpzPnmm2+wf/9+hIWF8fu3BIwYMQKxsbGYMmUKmjVrphEXsPLUzH+kpKRg48aN8PLygqWlJT777DPo6upi1apViI+Px549ezBw4ECWkLdQu3ZtfPnll4iIiMDt27cxffp0XL16Fb6+vrCwsMCQIUNw4MABZGdnSx211HTs2PGtSggA7N27F9nZ2ahXrx709PRyHy8PY0dFRRVjUqKSd/ToUXz33XeYN28eunXrJnUcrTVnzhx4enrio48+QmJiotRxeEQEKHx+lyVLlhTr/C70/+rVq4cpU6ZgypQpeea92bhxY7ma96Zp06ZvvW5CQgKsrKxw4MCBAp+vUaPGW2+bqLSlp6dj+PDh6NSpEyZOnCh1HK2mo6ODDRs2oEmTJhg9ejSCgoIkzVNui0hh87sEBASU+PwulJe9vT1mzZqFmTNn5pn3ZtWqVVo/701BJUtXVxcqlSrf8mfPnuX52szMDAkJCahXrx6vUaIyb8GCBXj48CEOHTqkdT/nmsjc3ByLFi3CoEGDMHLkSElHYC1Xn3Z2djb279+PIUOGwMLCAr6+vrh27RqmT5+O27dvIyIiAuPHj2cJkYhMJkPz5s0REBCAO3fu4MyZM5DL5QgJCYGzszPq1q2LiRMnIioqSqOu+C5uNWvWxIMHD6BUKnOXHT58GBcuXMjzuh49eiAnJwcLFy7Mszw7OxuDBg3CnTt3SiUv0btKTEzEDz/8gLFjx8LW1lbqOOXGwIED0aZNG0yaNEnS36laX0SUSiWOHTuGESNGoEaNGvDy8sKZM2cwfvx4XL16FX/99RemTJkiySRzVDiZTIY2bdpg0aJFiI2NxYkTJ+Dt7Y3169fD0dERDRs2xIwZM3DlyhWpoxa7vn37Ijk5GePHj0dkZCTWrVuHIUOGoHHjxnleJ5fL0bVrV8yZMwfjx4/HH3/8gUOHDsHDwwOnT5+GqampRO+AqGiWLFkCHR0djbmLo7yQyWT49ttvce7cORw+fFi6IBKPY1IitGF+FypYWZv3prABzf7++28BQCxatKjA9QICAkSNGjWEoaGh6Nixo4iIiBADBw4UzZo1y/O6rKwsMWfOHNGgQQNRoUIFYWlpKT755BORmJhY/G+mCMriAFraTJM/j4yMDGFmZibGjh0rdZRySaVSiebNm4sePXpIlkFr5poRWjy/CxWM895orpdzzZTFuU20kSZ/HiEhIejXrx+io6PRqFEjqeOUSytWrMDnn3+OBw8ewNLSstT3X+ZPzVy5cgUzZsxAw4YN4eTkhPXr18Pb2xsnTpxAbGwsFi1ahDZt2rCEaCEDAwP4+Phg69atSExMRHBwMGxsbDB9+nRYW1vD2dkZgYGBiI+PlzoqERUiODgYLVu2ZAmRUP/+/aGjo4PQ0FBJ9l8mi8jNmzcxd+5cNG3aFA4ODli2bBlcXV0RHh6Ohw8f4ueff4arqyuvvP4PpVKJgIAA2NrawsDAALa2tggICMhzUWRZVbFiRfTt2xchISFITEzE5s2bUa1aNXz11VewsrKCu7s7Vq9ejcePH0sdlcoAbf5Z0SQ5OTkIDw9Hr169JM2xYcMGyGSyQh+LFy8GgNyvFQpFgduZNWsWbGxs8iyzsbHJs61KlSqhYcOGGDJkCP74448SfmfqMTU1RYcOHRAWFibJ/svMX2rO7/LuRo8ejSlTpsDV1RXLly+Hq6srpkyZgjFjxrx2PSEE1qxZg5YtW6Jy5cqoVasW5HI5/v7771JKXjSc94be1dv+rFDRXLp0CSkpKXBzc5M6CgAgNDQU0dHR+R6DBw/OfU3NmjUxatQoPHjwQO3turu7527r+PHjmDVrFtLS0uDi4oIvvvhCI+4CdHd3x++//17g0AElTrKrU9Tw8OFDsXTpUtG+fXsBQBgaGoo+ffqI4OBgkZaWJnW8MuXSpUtCJpOJMWPG5Fk+ZswYIZPJxKVLlwpdd+bMmUJPT0/MnDlTREREiL179woHBwfx3nvviYcPH5Z09GITHx8vli9fLlxcXAQAYWBgIHr37i0UCoVITU2VOp5W0eSLI9/kXX5WNJWmfh4rVqwQurq6Ij09XdIc69evFwDEhQsXXvs6AGLx4sXC3NxcdOnSJd+NDzNnzsx3cbq1tbXo1atXgdvbvXt37u9WqR08eFAAENevXy/1fWvcEZHHjx9j1apVcHd3h5WVFb766iuYmppiy5YtSExMREhICPr27VvmBnB68uQJqlWrhnbt2uVbbm9vDxsbGzx8+LDE9q9QKCCEwLhx4/IsHzduHIQQhR5qfPz4MebPn4+ZM2di1qxZaN26Nby9vRESEoJHjx7ht99+K7HMxe3lvDcnT55ETEwMvvvuO8TFxUEul8Pc3BwDBgzAzp07kZmZKXVUjZOUlIRFixbh1q1bUkcpcW/7s0L/XO8RFhaGjIwMtV4fHR0NW1tbGBkZlXCy4lOlShUEBgbi8OHDCAwMfKdt+fj4YOTIkViwYAGSk5OLKeHbcXBwAABcvXq11PetEUWkPMzvUq1aNUyYMAFnzpzJHZI7MzMTPXv2RGJiIg4cOFDgkNwqlQpJSUlqPV53quH8+fOwsLBA3bp18yyvW7cuzM3NERkZWeB6GRkZmDRpEkaNGpVneZUqVXKfL4s4703RpKam4ssvv0SDBg1gb2+PiRMn4uTJk8jJyZE6WrF7258VAvbt2wdvb29Ur14dvXr1wpo1a177D6x79+7l+/9cFrwc7Xny5MmIjo5+p235+fkhMzMTR44cKaZ0b8fS0hKGhoa4d+9e6e+81I/B/Cs1NVUoFArRu3dvoa+vLwAIFxcXsXz5chEfHy9VrBKVmpoqLCwsRJs2bYRSqRR9+/YVhoaG4tSpU4Wu83K8CXUeHTt2LHQ7Dg4OomXLlgU+16JFC+Hg4KD2+1CpVMLf318YGhqKGzduqL1eWXD16lUxc+ZM0bBhQwFAmJmZiU8//VQcPXpU5OTkSB1PMoV9H5qamoqBAwcKhUIhnj59mvt6TT0VoI7i/FnRFKX1eQwePLjA75NWrVqJ2bNni6ioqDynM9q3by8GDx5copnU8fLUjK6ubr6Hl5dX7usAiPXr1wshhEhOThZWVlbC0dFRvHjxQghR9FMzQggRFxcnAIiFCxcW99sqsjp16oipU6eW+n5L/crOx48fY/To0di1a1e5m9/F2NgYU6dOxdixY9GlSxecOHECwcHBcHZ2LnQdS0tLHDp0SK3tV6tWrdDn0tPTCz2iZGhomG8ek8IolUoMHjwYO3bswNatW9GgQQO11isr3jTvTe/evfHxxx+Xu9vB4+LiClyenJyMrVu3YuvWrdDT04OLiwt8fHzK9EjFxfWzoone9V/vb/L8+fMCl587dw7nzp3DzJkzUatWLfTo0QM+Pj54/vw5jI2NSzRTUQQFBcHOzi7PssK+F6pVq4Z169bB09MTs2fPxty5c99qn+LfC1U1YXLPSpUqIT09vdT3W+pF5OnTpzh58iTS09NhamqKjh07vtNU6GXNyJEjMXv2bBw7dgxLly7FBx988NrXGxoaokuXLu+834oVKyIrK6vA5zIzM9U+Rzt58mSEh4fj9OnTaN68+Tvn0lQymQxNmjRBx44d8fDhQ8TGxiI+Ph4rVqzAihUrpI6nkXJychAREQETExPcv38fwD/XQJU1xfWzoklefg7+/v4luh91Cvr9+/dx4sQJmJiYICMjQ6NKff369XOvlVBH165d8fnnn2PBggXo27fvW+3z5XVX1tbWb7V+cZLJZJLcNVPqRaR+/fqIiYnBqVOnoFAosH79enz//fewtbWFXC6HXC5HkyZNSjtWqVm8eHHuRUkmJiZvfL1SqcSjR4/U2ra+vn6h84vUrFkTFy9eLPC5Bw8eoEWLFm/cflZWFpYvX44VK1ZobQlRKpU4efIkFAoFtm/fjsePH8POzg7Tp0+Hn58fDAwM8PTpU6ljlrq4uDj4+PgU+FytWrXg4+MDHx8fdO7cGYaGhoiKisJPP/302qN0mqo4flY0zcvPYcuWLbC3ty+x/cybNw87duzIt1xPTw+urq653yf169cHAJw4caLMXmf20sKFC3Ho0CGMGDEC3bp1K/L6CoUCBgYG8PDwKIF0RZORkSFJ0ZZk0A0dHR24urrC1dUVS5cuxdGjRxEUFITAwEDMnTsXDg4OkMvl8PPz06qZGH/99VdMnjwZkydPxr59+zBr1iwMGDAA+vr6ha4TGxur9sVcHTt2xPHjxwt8ztHREQcPHsTff/+dZ3t///03EhMT4ejo+MbtP3r0CPr6+vnu/CnrVCoVzpw5A4VCgeDgYMTHx8PGxgaffPIJ/Pz80KxZM436V5sU/ltwW7dunXt4Xdv+/xTHz4qmsre3L9Eh3l89jWFqagovLy/4+PigW7duuRe4v8rU1LTMDzJoZGSELVu2oF27dkhISCjSutu3b8eqVavwzTffqPUP05KWlJQEMzOzUt+v5KN/6enpoWvXrujatSt+/vnn3LlD5s+fj+nTp2vN3CFHjx7F0KFDMXDgQHz33XdwcnJC3759sWrVKnzxxReFrldc14j4+fkhICAAixcvxpIlS3KXL168GDKZDH5+fm/cfq1atbTmaIAoZG6il0flODdRXnp6eujVqxd8fHzg7e0tyXwUpaU4flbKq/r162PixIno0aMH2rVr98YBJmvXro2zZ8+WUro3u3v3LgwNDfMtr1KlSoF3Nb7k5OSE6dOnY9asWQWeYklNTcW1a9cA/HMdzfXr17F9+3bs3LkTn3/+OaZNm1Z8b+ItpaSk4NmzZ9Jcq1nql8eqKS0tTQQHB4s+ffoIQ0NDAUC0b99eLF26tEwNoiWEEBcvXhQmJibC3d099+pqlUolmjVrJiwtLUttcLYRI0YIAGLo0KFizZo1YujQoQKAGDFihFrr79ixQ9jZ2YkdO3aUcNKSc/nyZTF9+nRha2srAIjq1auLzz77TJw4cUIolUqp42mNsnzXjBDv/rOiaTT18/jxxx+FkZGR5HekvbxrprDHwIEDhRB575r5r+zsbNG6desC75p5dVtGRkbC1tZWDBo0SBw7dqxk31gRnD59WrLvEY0tIq9KSUkRmzdvFj169BAVKlQQOjo6ws3NTaxatUokJSVJHe+1YmJihJWVlWjatKlISUnJ89yOHTsEADF//vxSyZKdnS3mzZsn6tatKypUqCDq1q0r5s2bJ7Kzs9Va/+UPa2E/iJrqxo0b4ttvvxVNmjQRAETVqlXFsGHDRHh4uNrvnYpGU//wqetdf1Y0jaZ+HseOHRMAyuRotdpm6dKlQl9fX2RmZpb6vmVCaMAg90WQnJyM0NBQKBQKHD16FDo6OvDw8IBcLkevXr0KPA9J5U9MTAy2bdsGhUKByMhIGBsbo3fv3vDz80PXrl1hYGAgdUStpsnTzpdHmvp5pKWloVq1avjxxx8xevRoqeOUa3369EFCQgJOnTpV6vvWiJFVi8LU1BTDhw/HoUOHEBcXhyVLliA1NRWDBw+GhYUFfH19ERQUhLS0NKmjUimLj49HYGAgnJ2dYW1tjRkzZsDGxgbBwcFITEzEli1b4OPjwxJCpCGMjY3h4uKCffv2SR2lXMvKysKhQ4fg6ekpyf7LXBF51atzh8TGxnLukHLo5dxEbm5uqFmzptbMTURUXvTp0wdHjhxRe5gCKn779+/H8+fP3ziuVUkp00XkVbVq1eLcIeVEQXMT6enpYfXq1VozNxFRedG/f3/o6Ohg48aNUkcpt9asWQNHR0c0btxYkv1rTRF5Vb169TBlyhRcvHgRV69exfjx43HmzBl0794dNWrUwIgRI3Ds2DEolUqpo5Ka0tLSEBQUBF9fX5ibm2PIkCFITU3FkiVLEBcXh4MHD2L48OGFDuhGRJqpevXq8PPzQ2BgIP+hKIFr165h3759+PzzzyXLoJVF5FUv5w6Jjo7GhQsX8Mknn+DgwYNwc3NDrVq1MHbsWJw+fVqSYW3p9TIzM7Fz587cU21yuRxxcXEICAhAbGwsTp48iVGjRsHCwkLqqET0DiZOnIiYmBisX79e6ijlzpw5c2BlZYUPP/xQsgxaX0RekslkaN68OebPn487d+7gzJkzkMvlCAkJgbOzM+rWrYuJEyciKioKZexGIq2SnZ2N/fv3Y8iQIbkXH1+7dg3Tp0/H7du3ERERgfHjx2v9BIlE5YmDgwM+/PBDfPPNN2V6UsGyJiIiAr/99htmzZol6UX8Ze723eKmUqly570JDg5GUlJSuZn3RlMUNr/Ly2H+S3JuDCoZmnq7aHlVFj6P2NhY2Nvb46OPPsLPP/8sdRyt9+LFC7Rq1Qp6eno4e/aspLP/lpsjIoV5Oe/Nzz//jIcPHyI8PByurq4IDAyEg4MDmjZtinnz5uXOkEjFQ6VS4fTp0xgzZgxq1aoFNzc3HDx4EJ988gkuXLiA6OhozJo1iyWEqJyoXbs2AgIC8MsvvyAsLEzqOFpvxowZuHr1KtasWSNpCQGguUO8Sy0zM1Ps3r1bfPjhh8LY2FgAEI6OjuL7778X9+7dkzpemaRSqcT58+fF119/LerUqSMAiJo1a4px48aJM2fOCJVKJXVEKiaaOpJneVVWPg+VSiW8vLyEqampuH37ttRxtFZoaKgAIBYuXCh1FCFEGRxZVQrp6ekICwuDQqHAvn37kJmZifbt20Mul6Nfv35aPQFYcbhy5QoUCgUUCgVu3bqF6tWro1+/fpDL5ejQoQN0dMr9gTmtUxZOBZQnZenzSE5ORps2baCrq4tTp06hevXqUkfSKhEREXBzc4OXlxe2bdumEZN78i+AGipWrIi+ffsiJCQECQkJ2Lx5M0xNTfHVV1/BysoK7u7uWL16dZmfzro43bx5E3PnzoWDgwMcHBywbNkyuLq6Ijw8HA8fPsTPP/8MV1dXlhAiysPU1BRhYWF48uQJPDw8kJSUJHUkrXH+/Hl4enqiRYsW2Lhxo0aUEIBFpMhMTEzg7++PPXv2ID4+HqtWrYKOjg5GjhwJS0tLeHl5YdOmTUhJSZE6aqmLiYnBDz/8ACcnJzRs2BABAQFo3rw5du/ejfj4eKxduxZdu3Z949TgRFS+NWjQAEeOHEFcXBw6dOiAO3fuSB2pzAsPD0fnzp3RqFEj7Nu3T6NGm2YReQec94bzuxBRyXBwcMCpU6egVCrRqlUrXsD6llQqFQICAuDl5YWOHTvi0KFDGjc5LItIMSlP895wfhciKg0NGjRAREQE2rZtC29vb4waNapcHm1+W7du3YK7uzumTp2KyZMnY9euXahUqZLUsfJhESkB2jjvDed3ISIpmJqaYu/evVi2bBk2bdoEOzs7rFq1qkz9/ixtycnJmDRpEpo0aYK7d+/i8OHDmDdvnvS36RaCd82UoujoaAQFBUGhUOD69eswMzNDnz59IJfL4erqqnHfJGlpadi7dy8UCgXCwsLw4sULuLi4QC6Xo0+fPhxanQr18i6NLVu2cCwYDRAdHQ1/f/8ycdfM68TGxmLKlCnYunUr6tSpg9GjR2Pw4MF47733pI6mEa5du4YVK1Zg7dq1UKlUmDBhAiZNmqTxR6dZRCQghMDFixdzS8ndu3dhaWmJ/v37w8/PD23btpXsbpLMzEwcOHAACoUCe/bsQXp6Olq3bp17qzKHVid13Lx5Ew0bNpQ6Bv3HjRs30KBBA6ljvLPLly/j+++/h0KhgEqlgru7O7y9vdGpUyc0btxY4/5RV1IyMjIQGRmJI0eOYPfu3YiKioKZmRlGjBiBsWPHwtzcXOqIamERkZgQAmfPnoVCocC2bdsQFxeHOnXqwM/PD3K5HC1atCjxW6yys7Nx+PBhBAUFITQ0FM+ePUOzZs3g5+cHPz8/1KtXr0T3T9rp5s2beP78udQx6F+VK1fWihLyqqSkJGzbtg07duzAyZMnkZ2dDSMjI9jZ2aFOnTqoXr06jIyMtGKYACEEVCoVUlNTkZiYiDt37uD27dtQKpWoUqUKunXrhn79+qFHjx4wNDSUOm6RsIhokNKc94bzuxCRNklPT8fZs2cRFRWF69ev4/79+3j8+DEyMjK0ZiJTXV1dVKxYEebm5rC2tkbjxo3h5OSEZs2alemjQCwiGionJwdHjx5FUFAQtm/fjpSUFDg4OOQWBVtb2yJvU6VS4cyZM7lFJz4+HjY2NrnbbNasmcYMcENEROUDi0gZkJWVhYMHD0KhUGDXrl1IS0uDo6Mj5HI5+vfvjzp16hS6rhACUVFRCAoKQlBQEGJiYlCzZk30798fcrkcrVu3ZvkgIiLJsIiUMerOe8P5XYiIqCxgESnDnj17ht27dyMoKAjh4eFQKpVwdXVFfHw8rl27hqpVq+KDDz6An58f3NzcOLQ6ERFpHBYRLZGcnIzQ0FBs3rwZJ0+exMqVK/HRRx9xaHUiItJoLCJapixN901ERMQLBYiIiEgyLCJEREQkGRYRIiIikgyLCBEREUmGRYSIiIgkwyJC78TGxga9e/eWOgYREZVRLCLl0IYNGyCTyQp9LFu2TOqIRERUTnCozXIsNDQUjRo1yrf85TDxREREJY1FpByzsbEpsIgQERGVFp6aoUIdPnwYzs7OMDY2hrW1NSZMmIDMzMzXrpOZmYkvv/wSVlZWqFixItq3b4/9+/fneU1KSgq++OIL1KxZE8bGxmjRogXWrl0LlUpVkm+HiIg0EI+IUIHCwsLQs2dPfPTRR1iyZAkuXLiAMWPGQKlUYtGiRYWuFxAQgN9++w3r16+Hubk5fvvtN3z22We4ePEiqlSpgvT0dHTq1AkymQw///wzateujRMnTmD06NGIjo7GDz/8UIrvkoiIpMYiUo45OTnlW+bt7Y1du3bB0tIS48aNyy0GTk5OuHDhAoKDg19bRF7OcePp6QkAaNmyJebMmQMjIyMAQGBgIB48eIBbt27BxMQEAODo6Ah9fX2MGzcOX3/9NSwsLIr7rRIRkYZiESnHgoKCYGdnl2fZy3LQsmXLfJPmNW7cGL/88strtzlgwAD4+/vj448/xhdffIHmzZvnlhAA2Lt3L5KSkmBqappvXaVSiYsXL6Jr165v+5aIiKiMYREpx+rXrw8HB4cCn0tMTERAQAAOHz6Me/fuISMjA0ql8o3b/PDDD1GjRg0EBATA0dERLVq0QGBgINq1awcASEhIgJOTE9atW1fg+tbW1m//hoiIqMxhEaF8hBBwc3NDTEwMJk2ahPbt26NatWrYu3cvZsyY8cb1O3fujM6dO+Pu3bsYM2YMPDw8cP36dVhZWcHMzAyxsbFo0qQJZDJZKbwbIiLSZLxrhvJ59OgRrly5grFjx2LatGno3LkzmjdvjgcPHgDAa4+MPHnyJPfuFxsbG2zatAlpaWk4ffo0AKBHjx548OABNm7cmGe9p0+fQi6XIykpqYTeFRERaSIeEaF8zM3N0bBhQ4SEhKBjx44wNjZGcHAwTp06BQBITk7Ge++9l289IQS6d+8OY2NjTJgwATVr1kRISAh0dXXRtGlTAMDYsWMRHByMTz/9FDExMfD09ER8fDxmzJgBIyOj3GtUiIiofOARESrQnj17YG1tjQ8++AC9e/eGSqXCiRMnYGBgkHt0479kMhkUCgWsrKwwePBgtG3bFmFhYdi+fXvuwGmVKlXCyZMnMXr0aKxduxYdOnTA6NGj0bVrVxw5cgT6+vql+TaJiEhiMiGEkDoEFZ+oqCg4Ojrm3kZLRESkyXhEhIiIiCTDIkJERESSYREhIiIiybCIEBERkWRYRIiIiEgyLCJEREQkGRYRIiIikgyLCBEREUmGRYSIiIgkwyJCREREkmERISIiIsmwiBAREZFkWESIiIhIMiwiREREJBkWESIiIpIMiwgRERFJRk/qAPTudu3ahSdPngAA7t69CwDYvXs3Ll26BHt7e7Rp00bCdERERIWTCSGE1CHo3QwbNgzr168v8LlNmzZh0KBBpZyIiIhIPTw1owV8fHwKXK6jowMvL69STkNERKQ+FhEt4OHhAX19/XzL27dvDzMzMwkSERERqYdFRAtUqlQJbm5u+ZYXdqSEiIhIU7CIaImCSkePHj0kSEJERKQ+XqyqJe7duwcbG5vcr+vVq4dbt25BJpNJF4qIiOgNeERES1hbW+P999/P/drHx4clhIiINB6LiBZ59fQMrw8hIqKygEVEi7wsHyYmJnBxcZE4DRER0ZtxZFUt0qpVK5ibm6Njx44F3s5LRESkaVhEtIiOjg68vb3RuXNnqaMQERGphadmtMjNmzehUqmQlJSEx48fSx2HiIjojXj7bhkXExODbdu2QaFQIDIyEkZGRsjKyoKOjg48PDwgl8vRq1cvVKlSReqoRERE+fCISBkUHx+PwMBAODs7w9raGjNmzICNjQ2Cg4ORlJSEuLg4LFmyBKmpqRg8eDAsLCzg6+uLoKAgpKWlSR2fiIgoF4+IlBGPHz/G9u3bERQUhOPHj0NXVxfdunWDXC5Hz549Ubly5QLXi42NRXBwMIKCgnD27FlUrFgRPXv2hJ+fHzw9PWFoaFjK74SIiOj/sYhosJSUFOzcuRNBQUE4dOgQVCoV3N3d4efnB19fX5iamhZpe3fu3EFQUBAUCgUuXboEExMT+Pr6Qi6Xw93dHRUqVCihd0JERFQwFhENk5aWhr1790KhUCAsLAwvXryAi4sL5HI5+vTpAwsLi2LZT3R0NIKCgvDbb7/hxo0bMDMzQ58+fSCXy+Hq6gpdXd1i2Q8RUWnJysrClStXcP36dcTGxiI5ORkZGRnQlj9zOjo6MDY2hrm5OaytrWFvb48GDRpAR6dsX2XBIqIBMjMzceDAASgUCuzZswfp6elo3bo15HI5+vXrh1q1apXYvoUQuHjxIhQKBYKCgnD37l1YWlqif//+8PPzQ9u2bcv8NzkRaa+rV69i+/btCA8Px7lz5/DixQsAQJUqVWBmZgYjIyOt+R2mVCqRlpaGhIQEZGZmAvjnfbq4uMDLywu+vr6wtLSUOGXRsYhIJDs7G4cPH0ZQUBBCQ0Px7NkzNGvWDH5+fvDz80O9evVKPZMQAmfPnoVCocC2bdsQFxeHOnXqwM/PD3K5HC1atOD8NUQkuaysLGzduhXLly9HVFQUKleuDA8PD3Tq1AmtWrWCvb29Vt8pKIRAQkICLl++jDNnzuDo0aP4/fffoVKp4OXlhTFjxqBLly5l5vc1i0gpUiqVOHnyJBQKBbZv347Hjx/Dzs4Ocrkcfn5+sLe3lzpiLpVKhVOnTkGhUOTejWNrawu5XA65XI4mTZpIHZE03M2bN/H8+XOpY9C/KleujAYNGkgd450olUqsW7cOs2fPRlxcHLy8vPDxxx+je/fuMDAwkDqepJKTk7Ft2zasXLkSf/31F1q1aoUFCxaUjQEuBZUopVIp/vjjDzF69GhhaWkpAAgbGxsxefJkceHCBaFSqaSO+EbZ2dkiPDxcDB06VFSpUkUAEA4ODmLu3Lni5s2bUscjDXTjxg0BgA8Ne9y4cUPqb423FhUVJVq0aCEAiAEDBojo6GipI2kklUolDh48KNq0aSMAiP79+4uEhASpY70Wj4iUACEEoqKiEBQUhKCgIMTExKBmzZro378/5HI5WrduXWYOmf1XVlYWDh48CIVCgV27diEtLQ2Ojo6Qy+Xo378/6tSpI3VEydy9exd169ZV67UzZ87ErFmzSjaQhKKiouDo6IgtW7Zo1JG+8io6Ohr+/v6IjIxEy5YtpY5TJEIIfP/995g2bRoaN26MVatWoU2bNlLH0nhCCGzduhXjx4+HTCbDpk2b4OnpKXWsgklag7TM5cuXxfTp04Wtra0AIKpXry4+++wzceLECaFUKqWOV+zS0tJEcHCw6NOnjzAwMBAARPv27cXSpUvFw4cPpY5X6l68eCGio6PzPNzd3UXNmjXzLX/06JHUcUtUZGSkACAiIyOljkKi7H4eaWlpom/fvgKAmDRpksjKypI6UpkTHx8vunfvLmQymQgICNDIo/AsIu/oxo0b4ttvvxUODg4CgKhataoYNmyYCA8PF9nZ2VLHKzUpKSli8+bNwtvbW1SoUEHo6OgINzc3sWrVKpGUlCR1PMn06tVLWFtbSx2j1JXVP3zaqix+Hk+fPhXOzs6iYsWKIjQ0VOo4ZZpSqRTTpk0TAMSYMWM0roxoxz1NpSwmJgY//PADnJyc0LBhQwQEBKBZs2bYvXs34uPjsXbtWnTt2hV6euVncmMTExP4+/tj7969iI+Px6pVq6Cjo4ORI0fC0tISXl5e2LRpE1JSUqSOqhHu3r0LmUyGnTt3Ys+ePahXrx7Gjh0LAOjUqROaN2+eb52ClmdlZWH69OmwsbGBkZERGjdujO+//z73Fkaisig1NRWenp64cuUKjh49it69e0sdqUzT0dHB3LlzsWLFCgQGBmLs2LEaNbZK+flL+Y7i4+MRHBwMhUKB06dPw9DQEN7e3pg8eTK8vLxQsWJFqSNqDFNTUwwfPhzDhw9HQkICtm/fDoVCgcGDB8PAwADdu3eHXC5Hjx49YGxsLHVcSV27dg07d+7EqlWr8P777xdpXZVKhd69e+PGjRv47rvv0KhRI0RGRmLq1KmIiIhASEhICaUmKjlKpRJyuRyXL1/GsWPH4OTkJHUkrTFixAgAwMiRI2FlZYVJkyZJnOgfLCKvUdj8Llu2bHnt/C70/ywsLDBq1CiMGjUqz7w3crmc894AWLlyJU6dOgUrK6sirxscHIwjR47g1q1buRcJt2zZEjVq1ICPjw/Onz/PX+JU5nzzzTfYv38/wsLC+P1bAkaMGIHY2FhMmTIFzZo104gLWHlq5j9SUlKwceNGeHl5wdLSEp999hl0dXWxatUqxMfHY8+ePRg4cCBLyFuoXbs2vvzyS0REROD27duYPn06rl69Cl9fX1hYWGDIkCE4cOAAsrOzpY5aajp27PhWJQQA9u7di+zsbNSrVw96enq5j5eHsaOioooxKVHJO3r0KL777jvMmzcP3bp1kzqO1pozZw48PT3x0UcfITExUeo4PCICFD6/y5IlS4p1fhf6f/Xq1cOUKVMwZcqUPPPebNy4sVzNe9O0adO3XjchIQFWVlY4cOBAgc/XqFHjrbdNVNrS09MxfPhwdOrUCRMnTpQ6jlbT0dHBhg0b0KRJE4wePRpBQUGS5im3RaSw+V0CAgJKfH4Xysve3h6zZs3CzJkz88x7s2rVKq2f96agkqWrqwuVSpVv+bNnz/J8bWZmhoSEBNSrV4/XKFGZt2DBAjx8+BCHDh3Sup9zTWRubo5FixZh0KBBGDlypKQjsJarTzs7Oxv79+/HkCFDYGFhAV9fX1y7dg3Tp0/H7du3ERERgfHjx7OESEQmk6F58+YICAjAnTt3cObMGcjlcoSEhMDZ2Rl169bFxIkTERUVpVFXfBe3mjVr4sGDB1AqlbnLDh8+jAsXLuR5XY8ePZCTk4OFCxfmWZ6dnY1Bgwbhzp07pZKX6F0lJibihx9+wNixY2Frayt1nHJj4MCBaNOmDSZNmiTp71StLyJKpRLHjh3DiBEjUKNGDXh5eeHMmTMYP348rl69ir/++gtTpkyRZJI5KpxMJkObNm2waNEixMbG4sSJE/D29sb69evh6OiIhg0bYsaMGbhy5YrUUYtd3759kZycjPHjxyMyMhLr1q3DkCFD0Lhx4zyvk8vl6Nq1K+bMmYPx48fjjz/+wKFDh+Dh4YHTp0/D1NRUondAVDRLliyBjo6OxtzFUV7IZDJ8++23OHfuHA4fPixdEInHMSkR2jC/CxWsrM17U9iAZn///bcAIBYtWlTgegEBAaJGjRrC0NBQdOzYUURERIiBAweKZs2a5XldVlaWmDNnjmjQoIGoUKGCsLS0FJ988olITEws/jdTBGVxAC1tpsmfR0ZGhjAzMxNjx46VOkq5pFKpRPPmzUWPHj0ky6A1c80ILZ7fhQrGeW8018u5Zsri3CbaSJM/j5CQEPTr1w/R0dFo1KiR1HHKpRUrVuDzzz/HgwcPYGlpWer7L/OnZq5cuYIZM2agYcOGcHJywvr16+Ht7Y0TJ04gNjYWixYtQps2bVhCtJCBgQF8fHywdetWJCYmIjg4GDY2Npg+fTqsra3h7OyMwMBAxMfHSx2ViAoRHByMli1bsoRIqH///tDR0UFoaKgk+y+TReTmzZuYO3cumjZtCgcHByxbtgyurq4IDw/Hw4cP8fPPP8PV1ZVXXv+HUqlEQEAAbG1tYWBgAFtbWwQEBOS5KLKsqlixIvr27YuQkBAkJiZi8+bNqFatGr766itYWVnB3d0dq1evxuPHj6WOSkT/ysnJQXh4OHr16iVpjg0bNkAmkxX6WLx4MQDkfq1QKArczqxZs2BjY5NnmY2NTZ5tVapUCQ0bNsSQIUPwxx9/lPA7U4+pqSk6dOiAsLAwSfZfZv5Sc36Xdzd69GhMmTIFrq6uWL58OVxdXTFlyhSMGTPmtesJIbBmzRq0bNkSlStXRq1atSCXy/H333+XUvKi4bw3RGXDpUuXkJKSAjc3N6mjAABCQ0MRHR2d7zF48ODc19SsWROjRo3CgwcP1N6uu7t77raOHz+OWbNmIS0tDS4uLvjiiy804i5Ad3d3/P777wUOHVDiJLs6RQ0PHz4US5cuFe3btxcAhKGhoejTp48IDg4WaWlpUscrFampqcVyEealS5eETCYTY8aMybN8zJgxQiaTiUuXLhW67syZM4Wenp6YOXOmiIiIEHv37hUODg7ivffeEw8fPnznbKUlPj5eLF++XLi4uAgAwsDAQPTu3VsoFAqRmpoqdTytoskXR75JcnKyqFq1qmjbtm2+5Y0aNRLW1tYiLi5OonRvR1M/jxUrVghdXV2Rnp4uaY7169cLAOLChQuvfR0AsXjxYmFubi66dOmS78aHmTNn5rs43draWvTq1avA7e3evTv3d6vUDh48KACI69evl/q+Na6IJCUliZUrVwo3Nzeho6MjKlSoIHr06CG2bNkinj17JnW8t/a2v9xe3l3h7OwsVq1aJZ4+ffpW+586daoAIO7cuZNn+Z07dwQAMXXq1ALXS0pKEvr6+uLbb7/Ns/zatWsCgPjpp5/eKo/UYmJixI8//ihat24tAIiKFSsKuVwuQkNDRUZGhtTxNM6jR4/ETz/9pHYp1tQ/fOqaO3euACD2798vhPjnzo4OHToIU1NTER0dLXG6oiutz2Pbtm1i3759aheLsWPHCjs7uxLNpI6iFJH169eLoKAgAUAsWbIkz/NFLSJCCPHFF18IQ0ND8fjx47dMXzzi4uIEABEaGlrq+9aIUzPlYX6XatWqYcKECThz5kzukNyZmZno2bMnEhMTceDAgQKH5K5RowYWL16MjIwMfPrpp7C0tMSAAQMQHh5epGs7zp8/DwsLC9StWzfP8rp168Lc3ByRkZEFrpeRkYFJkyZh1KhReZZXqVIl9/myiPPeFE1qaiq+/PJLNGjQAPb29pg4cSJOnjyJnJwcqaOViHHjxsHCwgKzZs2CSqXCoEGDcP78eezevZsXVb7Gvn374O3tjerVq6NXr15Ys2YNHj58WOjr7927l+93UlnwcrTnyZMnIzo6+p225efnh8zMTBw5cqSY0r0dS0tLGBoa4t69e6W/81KvPv9KTU0VCoVC9O7dW+jr6wsAwsXFRSxfvlzEx8dLFatEpaamCgsLC9GmTRuhVCpF3759haGhoTh16pRa61+5ckVMnDhRWFlZCQCiZs2aYuLEieLq1atvXNfBwUG0bNmywOdatGghHBwc1H4fKpVK+Pv7C0NDQ3Hjxg211ysLrl69KmbOnCkaNmwoAAgzMzPx6aefiqNHj4qcnByp40nm5ZG5/z5MTU3FwIEDhUKhyHO0rqwfERFCiCVLlggAonPnzkJHR0ds375d6khvrbQ+j8GDBxf4fdKqVSsxe/ZsERUVled0Rvv27cXgwYNLNJM6Xh4R0dXVzffw8vLKfR3+PSIixD9Hs62srISjo6N48eKFEOLtjoi8PBKxcOHC4n5bRVanTp1Cj46XpFK/svPx48cYPXo0du3aVe7mdzE2NsbUqVMxduxYdOnSBSdOnEBwcDCcnZ3VWr9x48ZYsGAB5s+fjyNHjmDz5s1Yvnw5Fi5ciFatWmH8+PEYMGBAgeump6cXekTJ0NAw3zwmhVEqlRg8eDB27NiBrVu3okGDBmqtV1a8ad6b3r174+OPPy53t4PHxcUVuDw5ORlbt27F1q1boaenBxcXF/j4+GjFSMUjR47E7NmzcezYMSxduhQffPCB1JHe2bv+6/1Nnj9/XuDyc+fO4dy5c5g5cyZq1aqFHj16wMfHB8+fP4exsXGJZiqKoKAg2NnZ5VlW2O/NatWqYd26dfD09MTs2bMxd+7ct9qn+PdCVU2Y3LNSpUpIT08v9f2WehF5+vQpTp48ifT0dJiamqJjx47vNBV6WVMcv9x0dHTg4eEBDw8PjBgxAh999BHOnTuHlStXFlpEKlasiKysrAKfy8zMhJGRkVr7njx5MsLDw3H69Gk0b968yNnLCplMhiZNmqBjx454+PAhYmNjER8fjxUrVmDFihVSx9NIOTk5iIiIgImJCe7fvw8AePLkicSp3t7ixYuRnJwM4J87scqyl5+Dv79/ie5HnYJ+//59nDhxAiYmJsjIyNCoUl+/fn04ODio/fquXbvi888/x4IFC9C3b9+32uetW7cAANbW1m+1fnGSyWSS3DVT6kWkfv36iImJwalTp6BQKLB+/Xp8//33sLW1hVwuh1wuR5MmTUo7Vqkpjl9ucXFx2Lp1KzZv3oz//e9/qFq1KkaMGIFPPvmk0HVq1qyJixcvFvjcgwcP0KJFizfuNysrC8uXL8eKFSu0toQolUqcPHkSCoUC27dvx+PHj2FnZ4fp06fDz88PBgYGePr0qdQxS11cXBx8fHwKfK5WrVrw8fGBj48POnfuDENDQ0RFReGnn35CtWrVSjlp8fj1118xefJkTJ48Gfv27cOsWbMwYMAA6OvrSx3trbz8HLZs2QJ7e/sS28+8efOwY8eOfMv19PTg6uqa+31Sv359AMCJEyfK7HVmLy1cuBCHDh3CiBEj0K1btyKvr1AoYGBgAA8PjxJIVzQZGRlq/6O0WJX6yaD/eDl3yLBhw8rE3CHvYuvWrUImk4nJkyeLpk2bChsbG5GVlaXWuqmpqWLz5s3Cw8ND6OjoCF1dXeHp6SkUCoXIzMx84/pTpkx5q7tmXhUbGyuqVKmiddeFcG6iN/vvNSKtW7cWc+bMKfT/T1m+RuTIkSNCX19f+Pv7C5VKJUJCQgQAERgYKHW0tybFNSKmpqbC399fBAUFFXq3X/fu3V97/URpKepdM/917tw5oaenJ6ytrYt0jUhISIjQ1dUVs2fPfrvgxczExESSa1UkLyKvyszMFLt37xYffvihMDY2FgCEo6Oj+P7778W9e/ekjvdO3vaX27Nnz8SgQYNy/380btxYLFiwoMjjGPz111+vHUfk4sWLRX5PZZlKpRLnz58XX3/9tahTp07uxb/jxo0TZ86cYfn4j9jYWNGrVy+xZs0atcaOKatF5OLFi8LExES4u7vnXoCoUqlEs2bNhKWlZZkdv6i0Po85c+aIiRMnipMnT4rs7Ow3vv7TTz8VzZs3L9FM6nhZREJDQ0V0dHS+x8vft4UVESGEmDVrlgBQYBFxd3fP3dbZs2fF5s2bRe/evQUA8fnnn2vEhfBPnz4VAMSvv/5a6vvWqCLyqrS0NBEcHCz69OkjDA0NBQDRvn17sXTp0jI1iJYQ7/bL7e+//xampqZi1KhR4uzZs++UY8SIEQKAGDp0qFizZo0YOnSoACBGjBih1vo7duwQdnZ2YseOHe+UQ0qXL18W06dPF7a2tgKAqF69uvjss8/EiRMnhFKplDqe1iiLRSQmJkZYWVmJpk2bipSUlDzP7dixQwAQ8+fPlyjdu9HUz+PHH38URkZGkv8hfllECnsMHDhQCPH6IpKdnS1at25dYBF5dVtGRkbC1tZWDBo0SBw7dqxk31gRnD59WrLvEY0tIq9KSUkRmzdvFj169BAVKlQQOjo6ws3NTaxatUokJSVJHe+13vWX24sXL9Q+ffMm2dnZYt68eaJu3bqiQoUKom7dumLevHlq/ctFiP//YS3sB1FT3bhxQ3z77beiSZMmAoCoWrWqGDZsmAgPD1f7vVPRaOofvvJKUz+PY8eOCQCvHdmZSsfSpUuFvr6+Wqf6i5tMCA0Y5L4IkpOTERoaCoVCgaNHj+beQSKXy9GrV6/cgbaofIuJicG2bdugUCgQGRkJY2Nj9O7dG35+fujatSsMDAykjqjVNHna+fJIUz+PtLQ0VKtWDT/++CNGjx4tdZxyrU+fPkhISMCpU6dKfd8aMbJqUZiammL48OE4dOgQ4uLisGTJEqSmpmLw4MGwsLCAr68vgoKCkJaWJnVUKmXx8fEIDAyEs7MzrK2tMWPGDNjY2CA4OBiJiYnYsmULfHx8WEKINISxsTFcXFywb98+qaOUa1lZWTh06BA8PT0l2X+ZKyKvsrCwwKhRo3Dy5EnExsbiu+++Q1xcHORyOczNzTFgwADs3LkTmZmZUkelEvL48WOsWrUKbm5uqFmzJr766iuYmppiy5YtSExMREhICPr27YuKFStKHZWICtCnTx8cOXIEjx49kjpKubV//348f/5cskH7ynQReVWtWrU4d0g5UdDcRHp6eli9erXWzE1EVF70798fOjo62Lhxo9RRyq01a9bA0dERjRs3lmT/WlNEXlWvXj1MmTIFFy9exNWrVzF+/HicOXMG3bt3R40aNTBixAgcO3asSJPGkbTS0tIQFBQEX19fmJubY8iQIUhNTcWSJUsQFxeHgwcPYvjw4TA1NZU6KhEVQfXq1eHn54fAwED+Q1EC165dw759+/D5559LlkEri8irXs4dEh0djQsXLuCTTz7BwYMH4ebmhlq1amHs2LE4ffq0JMPa0utlZmZi586duafa5HI54uLiEBAQgNjYWJw8eRKjRo2ChYWF1FGJ6B1MnDgRMTExWL9+vdRRyp05c+bAysoKH374oWQZtL6IvCSTydC8eXPMnz8fd+7cwZkzZyCXyxESEgJnZ2fUrVsXEydORFRUFMrYjURaJTs7G/v378eQIUNyLz6+du0apk+fjtu3byMiIgLjx4/X+gkSicoTBwcHfPjhh/jmm2/UnoCT3l1ERAR+++03zJo1S9KL+Mvc7bvFTaVS5c57ExwcjKSkpHIz742mKGx+F7lcDj8/vxKdG4NKhqbeLlpelYXPIzY2Fvb29vjoo4/w888/Sx1H67148QKtWrWCnp4ezp49K+nsv+XmiEhhdHR04Orqip9//hkPHz5EeHg4XF1dERgYCAcHBzRt2hTz5s3LnSGRiodKpcLp06cxZswY1KpVC25ubjh48CA++eQTXLhwAdHR0Zg1axZLCFE5Ubt2bQQEBOCXX35BWFiY1HG03owZM3D16lWsWbNG0hICQPpJ7zSVNs97IxXO71J+aOpInuVVWfk8VCqV8PLyEqampuL27dtSx9FaoaGhAoAkE9wVpNyfmlFHeno6wsLCoFAosG/fPmRmZqJ9+/aQy+Xo168fLC0tpY6o0a5cuQKFQgGFQoFbt26hevXq6NevH+RyOTp06AAdnXJ/YE7rlIVTAeVJWfo8kpOT0aZNG+jq6uLUqVOoXr261JG0SkREBNzc3ODl5YVt27ZBJpNJHYmnZtRRsWJF9O3bFyEhIUhISMDmzZthamqKr776ClZWVnB3d8fq1avx+PFjqaNqjJs3b2Lu3LlwcHCAg4MDli1bBldXV4SHh+Phw4f4+eef4erqyhJCRHmYmpoiLCwMT548gYeHB5KSkqSOpDXOnz8PT09PtGjRAhs3btSIEgKwiBSZiYkJ/P39sWfPHsTHx2PVqlXQ0dHByJEjYWlpCS8vL2zatAkpKSlSRy11MTEx+OGHH+Dk5ISGDRsiICAAzZs3x+7duxEfH4+1a9eia9eu0NPTkzoqEWmwBg0a4MiRI4iLi0OHDh1w584dqSOVeeHh4ejcuTMaNWqEffv2adRo0ywi74Dz3nB+FyIqGQ4ODjh16hSUSiVatWrFC1jfkkqlQkBAALy8vNCxY0ccOnRI4yaHZREpJuVp3hvO70JEpaFBgwaIiIhA27Zt4e3tjVGjRpXLo81v69atW3B3d8fUqVMxefJk7Nq1C5UqVZI6Vj4sIiVAG+e94fwuRCQFU1NT7N27F8uWLcOmTZtgZ2eHVatWlanfn6UtOTkZkyZNQpMmTXD37l0cPnwY8+bNk/423ULwrplSFB0djaCgICgUCly/fh1mZmbo06cP5HI5XF1dNe6bJC0tDXv37oVCoUBYWBhevHgBFxcXyOVy9OnTh0OrU6Fe3qWxZcsWjgWjAaKjo+Hv718m7pp5ndjYWEyZMgVbt25FnTp1MHr0aAwePBjvvfee1NE0wrVr17BixQqsXbsWKpUKEyZMwKRJkzT+6DSLiASEELh48WJuKbl79y4sLS3Rv39/+Pn5oW3btpLdTZKZmYkDBw5AoVBgz549SE9PR+vWrXNvVebQ6qSOmzdvomHDhlLHoP+4ceMGGjRoIHWMd3b58mV8//33UCgUUKlUcHd3h7e3Nzp16oTGjRtr3D/qSkpGRgYiIyNx5MgR7N69G1FRUTAzM8OIESMwduxYmJubSx1RLSwiEhNC4OzZs1AoFNi2bRvi4uJQp04d+Pn5QS6Xo0WLFiV+i1V2djYOHz6MoKAghIaG4tmzZ2jWrBn8/Pzg5+eHevXqlej+STvdvHkTz58/lzoG/aty5cpaUUJelZSUhG3btmHHjh04efIksrOzYWRkBDs7O9SpUwfVq1eHkZGRVgwTIISASqVCamoqEhMTcefOHdy+fRtKpRJVqlRBt27d0K9fP/To0QOGhoZSxy0SFhENUprz3nB+FyLSJunp6Th79iyioqJw/fp13L9/H48fP0ZGRobWTGSqq6uLihUrwtzcHNbW1mjcuDGcnJzQrFmzMn0UiEVEQ+Xk5ODo0aMICgrC9u3bkZKSAgcHh9yiYGtrW+RtqlQqnDlzJrfoxMfHw8bGJnebzZo105gBboiIqHxgESkDsrKycPDgQSgUCuzatQtpaWlwdHSEXC5H//79UadOnULXFUIgKioKQUFBCAoKQkxMDGrWrIn+/ftDLpejdevWLB9ERCQZFpEyRt15bzi/CxERlQUsImXYs2fPsHv3bgQFBSE8PBxKpRKurq6Ij4/HtWvXULVqVXzwwQfw8/ODm5sbh1YnIiKNwyKiJZKTkxEaGorNmzfj5MmTWLlyJT766CMOrU5ERBqNRUTLlKXpvomIiHihABEREUmGRYSIiIgkwyJCREREkmERISIiIsmwiBAREZFkWETondjY2KB3795SxyAiojKKRaQc2rBhA2QyWaGPZcuWSR2RiIjKCQ61WY6FhoaiUaNG+Za/HCaeiIiopLGIlGM2NjYFFhEiIqLSwlMzVKjDhw/D2dkZxsbGsLa2xoQJE5CZmfnadTIzM/Hll1/CysoKFStWRPv27bF///48r0lJScEXX3yBmjVrwtjYGC1atMDatWuhUqlK8u0QEZEG4hERKlBYWBh69uyJjz76CEuWLMGFCxcwZswYKJVKLFq0qND1AgIC8Ntvv2H9+vUwNzfHb7/9hs8++wwXL15ElSpVkJ6ejk6dOkEmk+Hnn39G7dq1ceLECYwePRrR0dH44YcfSvFdEhGR1FhEyjEnJ6d8y7y9vbFr1y5YWlpi3LhxucXAyckJFy5cQHBw8GuLyMs5bjw9PQEALVu2xJw5c2BkZAQACAwMxIMHD3Dr1i2YmJgAABwdHaGvr49x48bh66+/hoWFRXG/VSIi0lAsIuVYUFAQ7Ozs8ix7WQ5atmyZb9K8xo0b45dffnntNgcMGAB/f398/PHH+OKLL9C8efPcEgIAe/fuRVJSEkxNTfOtq1QqcfHiRXTt2vVt3xIREZUxLCLlWP369eHg4FDgc4mJiQgICMDhw4dx7949ZGRkQKlUvnGbH374IWrUqIGAgAA4OjqiRYsWCAwMRLt27QAACQkJcHJywrp16wpc39ra+u3fEBERlTksIpSPEAJubm6IiYnBpEmT0L59e1SrVg179+7FjBkz3rh+586d0blzZ9y9exdjxoyBh4cHrl+/DisrK5iZmSE2NhZNmjSBTCYrhXdDRESajHfNUD6PHj3ClStXMHbsWEybNg2dO3dG8+bN8eDBAwB47ZGRJ0+e5N79YmNjg02bNiEtLQ2nT58GAPTo0QMPHjzAxo0b86z39OlTyOVyJCUlldC7IiIiTcQjIpSPubk5GjZsiJCQEHTs2BHGxsYIDg7GqVOnAADJycl477338q0nhED37t1hbGyMCRMmoGbNmggJCYGuri6aNm0KABg7diyCg4Px6aefIiYmBp6enoiPj8eMGTNgZGSUe40KERGVDzwiQgXas2cPrK2t8cEHH6B3795QqVQ4ceIEDAwMco9u/JdMJoNCoYCVlRUGDx6Mtm3bIiwsDNu3b88dOK1SpUo4efIkRo8ejbVr16JDhw4YPXo0unbtiiNHjkBfX7803yYREUlMJoQQUoeg4hMVFQVHR8fc22iJiIg0GY+IEBERkWRYRIiIiEgyLCJEREQ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+       "\" transform=\"scale(0.015625)\"/>\n",
+       "      <path id=\"IPAexGothic-73\" d=\"M 2234 2547 \n",
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+       "z\n",
+       "\" transform=\"scale(0.015625)\"/>\n",
+       "      <path id=\"IPAexGothic-65\" d=\"M 863 1594 \n",
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+       "z\n",
+       "\" transform=\"scale(0.015625)\"/>\n",
+       "     </defs>\n",
+       "     <use xlink:href=\"#IPAexGothic-46\"/>\n",
+       "     <use xlink:href=\"#IPAexGothic-61\" x=\"57.177734\"/>\n",
+       "     <use xlink:href=\"#IPAexGothic-6c\" x=\"112.158203\"/>\n",
+       "     <use xlink:href=\"#IPAexGothic-73\" x=\"139.160156\"/>\n",
+       "     <use xlink:href=\"#IPAexGothic-65\" x=\"185.351562\"/>\n",
+       "    </g>\n",
+       "   </g>\n",
+       "   <g id=\"text_4\">\n",
+       "    <!-- True -->\n",
+       "    <g transform=\"translate(151.83 163.135) scale(0.125 -0.125)\">\n",
+       "     <defs>\n",
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+       "z\n",
+       "\" transform=\"scale(0.015625)\"/>\n",
+       "      <path id=\"IPAexGothic-75\" d=\"M 3284 63 \n",
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+       "L 3284 63 \n",
+       "z\n",
+       "\" transform=\"scale(0.015625)\"/>\n",
+       "     </defs>\n",
+       "     <use xlink:href=\"#IPAexGothic-54\"/>\n",
+       "     <use xlink:href=\"#IPAexGothic-72\" x=\"59.912109\"/>\n",
+       "     <use xlink:href=\"#IPAexGothic-75\" x=\"96.923828\"/>\n",
+       "     <use xlink:href=\"#IPAexGothic-65\" x=\"157.324219\"/>\n",
+       "    </g>\n",
+       "   </g>\n",
+       "   <g id=\"text_5\">\n",
+       "    <!-- $x=0$ ? -->\n",
+       "    <g transform=\"translate(63.65 173.684141) scale(0.125 -0.125)\">\n",
+       "     <defs>\n",
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+       "\" transform=\"scale(0.015625)\"/>\n",
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+       "L 1978 63 \n",
+       "z\n",
+       "\" transform=\"scale(0.015625)\"/>\n",
+       "     </defs>\n",
+       "     <use xlink:href=\"#DejaVuSans-Oblique-78\" transform=\"translate(0 0.78125)\"/>\n",
+       "     <use xlink:href=\"#DejaVuSans-3d\" transform=\"translate(78.662109 0.78125)\"/>\n",
+       "     <use xlink:href=\"#DejaVuSans-30\" transform=\"translate(181.933594 0.78125)\"/>\n",
+       "     <use xlink:href=\"#IPAexGothic-20\" transform=\"translate(245.556641 0.78125)\"/>\n",
+       "     <use xlink:href=\"#IPAexGothic-3f\" transform=\"translate(272.558594 0.78125)\"/>\n",
+       "    </g>\n",
+       "   </g>\n",
+       "   <g id=\"text_6\">\n",
+       "    <!-- $0$ -->\n",
+       "    <g transform=\"translate(233.15 173.684141) scale(0.125 -0.125)\">\n",
+       "     <use xlink:href=\"#DejaVuSans-30\" transform=\"translate(0 0.78125)\"/>\n",
+       "    </g>\n",
+       "   </g>\n",
+       "   <g id=\"text_7\">\n",
+       "    <!-- END -->\n",
+       "    <g transform=\"translate(322.950781 173.684141) scale(0.125 -0.125)\">\n",
+       "     <defs>\n",
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+       "z\n",
+       "\" transform=\"scale(0.015625)\"/>\n",
+       "     </defs>\n",
+       "     <use xlink:href=\"#IPAexGothic-45\"/>\n",
+       "     <use xlink:href=\"#IPAexGothic-4e\" x=\"59.521484\"/>\n",
+       "     <use xlink:href=\"#IPAexGothic-44\" x=\"135.498047\"/>\n",
+       "    </g>\n",
+       "   </g>\n",
+       "   <g id=\"text_8\">\n",
+       "    <!-- False -->\n",
+       "    <g transform=\"translate(88.83 285.033281) scale(0.125 -0.125)\">\n",
+       "     <use xlink:href=\"#IPAexGothic-46\"/>\n",
+       "     <use xlink:href=\"#IPAexGothic-61\" x=\"57.177734\"/>\n",
+       "     <use xlink:href=\"#IPAexGothic-6c\" x=\"112.158203\"/>\n",
+       "     <use xlink:href=\"#IPAexGothic-73\" x=\"139.160156\"/>\n",
+       "     <use xlink:href=\"#IPAexGothic-65\" x=\"185.351562\"/>\n",
+       "    </g>\n",
+       "   </g>\n",
+       "   <g id=\"text_9\">\n",
+       "    <!-- True -->\n",
+       "    <g transform=\"translate(151.83 242.335) scale(0.125 -0.125)\">\n",
+       "     <use xlink:href=\"#IPAexGothic-54\"/>\n",
+       "     <use xlink:href=\"#IPAexGothic-72\" x=\"59.912109\"/>\n",
+       "     <use xlink:href=\"#IPAexGothic-75\" x=\"96.923828\"/>\n",
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+       "    </g>\n",
+       "   </g>\n",
+       "   <g id=\"text_10\">\n",
+       "    <!-- $x&gt;0$ ? -->\n",
+       "    <g transform=\"translate(63.65 252.884141) scale(0.125 -0.125)\">\n",
+       "     <defs>\n",
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+       "z\n",
+       "\" transform=\"scale(0.015625)\"/>\n",
+       "     </defs>\n",
+       "     <use xlink:href=\"#DejaVuSans-Oblique-78\" transform=\"translate(0 0.78125)\"/>\n",
+       "     <use xlink:href=\"#DejaVuSans-3e\" transform=\"translate(78.662109 0.78125)\"/>\n",
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+       "     <use xlink:href=\"#IPAexGothic-3f\" transform=\"translate(272.558594 0.78125)\"/>\n",
+       "    </g>\n",
+       "   </g>\n",
+       "   <g id=\"text_11\">\n",
+       "    <!-- $x$ -->\n",
+       "    <g transform=\"translate(233.4 252.884141) scale(0.125 -0.125)\">\n",
+       "     <use xlink:href=\"#DejaVuSans-Oblique-78\" transform=\"translate(0 0.3125)\"/>\n",
+       "    </g>\n",
+       "   </g>\n",
+       "   <g id=\"text_12\">\n",
+       "    <!-- END -->\n",
+       "    <g transform=\"translate(322.950781 252.884141) scale(0.125 -0.125)\">\n",
+       "     <use xlink:href=\"#IPAexGothic-45\"/>\n",
+       "     <use xlink:href=\"#IPAexGothic-4e\" x=\"59.521484\"/>\n",
+       "     <use xlink:href=\"#IPAexGothic-44\" x=\"135.498047\"/>\n",
+       "    </g>\n",
+       "   </g>\n",
+       "   <g id=\"text_13\">\n",
+       "    <!-- $-x$ -->\n",
+       "    <g transform=\"translate(75.2125 326.684141) scale(0.125 -0.125)\">\n",
+       "     <use xlink:href=\"#DejaVuSans-2212\" transform=\"translate(0 0.3125)\"/>\n",
+       "     <use xlink:href=\"#DejaVuSans-Oblique-78\" transform=\"translate(83.789062 0.3125)\"/>\n",
+       "    </g>\n",
+       "   </g>\n",
+       "   <g id=\"text_14\">\n",
+       "    <!-- END -->\n",
+       "    <g transform=\"translate(70.950781 387.884141) scale(0.125 -0.125)\">\n",
+       "     <use xlink:href=\"#IPAexGothic-45\"/>\n",
+       "     <use xlink:href=\"#IPAexGothic-4e\" x=\"59.521484\"/>\n",
+       "     <use xlink:href=\"#IPAexGothic-44\" x=\"135.498047\"/>\n",
+       "    </g>\n",
+       "   </g>\n",
+       "  </g>\n",
+       " </g>\n",
+       " <defs>\n",
+       "  <clipPath id=\"p202866707b\">\n",
+       "   <rect x=\"3.6\" y=\"3.6\" width=\"386.1\" height=\"417.78\"/>\n",
+       "  </clipPath>\n",
+       " </defs>\n",
+       "</svg>\n"
+      ],
+      "text/plain": [
+       "<schemdraw.backends.mpl.Figure object at 0x125d08850>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "with schemdraw.Drawing() as sd:\n",
+    "    flow.Start(w=2, h=1).label('START')\n",
+    "    flow.Arrow().down(sd.unit/4)\n",
+    "    \n",
+    "    flow.Box(w=3.5, h=1).label(r'$x$'+' に値を割り当てる\\n（例えば，'+r'$-10$）')\n",
+    "    flow.Arrow().down(sd.unit/4)\n",
+    "    \n",
+    "    d = flow.Decision(w=3.5, h=1.2, S='False', E='True'\n",
+    "                     ).label(r'$x=0$ ?')\n",
+    "    \n",
+    "    flow.Arrow().right().at(d.E).length(1.5)\n",
+    "    flow.Box(w=2., h=0.9).label(r'$0$')\n",
+    "    flow.Arrow().right(sd.unit/4)\n",
+    "    flow.Start(w=2, h=1).label('END').anchor('W')\n",
+    "    \n",
+    "    flow.Arrow().down().at(d.S).length(1.)\n",
+    "    d = flow.Decision(w=3.5, h=1.2, S='False', E='True'\n",
+    "                     ).label(r'$x>0$ ?')\n",
+    "    \n",
+    "    flow.Arrow().right().at(d.E).length(1.5)\n",
+    "    flow.Box(w=2., h=0.9).label(r'$x$')\n",
+    "    flow.Arrow().right(sd.unit/4)\n",
+    "    flow.Start(w=2, h=1).label('END').anchor('W')\n",
+    "    \n",
+    "    flow.Arrow().down(sd.unit/3).at(d.S)\n",
+    "    flow.Box(w=2, h=0.9).label(r'$-x$').drop('S')\n",
+    "    flow.Arrow().down(sd.unit/4)\n",
+    "    flow.Start(w=2, h=1).label('END')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "hidden": true
+   },
+   "source": [
+    "ここでは，まず $x=0$ が`True`か`False`かを判断し，次に $x>0$ が`True`か`False`かを判定している。しかし，図から分かるように，この２つの判断は，非常に似ており，次のように１つにまとめることができる。"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 206,
+   "metadata": {
+    "hidden": true,
+    "tags": [
+     "hide-input"
+    ]
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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    ],
    "source": [
-    "truth_value(0)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "hidden": true
-   },
-   "source": [
-    "真偽値を使ったもう１つの例を紹介しよう。"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {
-    "hidden": true
-   },
-   "outputs": [],
-   "source": [
-    "def my_wallet(money_in_my_wallet):\n",
+    "with schemdraw.Drawing() as sd:\n",
+    "    flow.Start(w=2, h=1).label('START')\n",
+    "    flow.Arrow().down(sd.unit/4)\n",
     "    \n",
-    "    if money_in_my_wallet:   #1\n",
-    "        print('なに買おうかな😄')\n",
+    "    flow.Box(w=3.5, h=1).label(r'$x$'+' に値を割り当てる\\n（例えば，'+r'$-10$）')\n",
+    "    flow.Arrow().down(sd.unit/4)\n",
     "    \n",
-    "    else:\n",
-    "        print('一文なしだよ😅')"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "hidden": true
-   },
-   "source": [
-    "実行してみよう。"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "metadata": {
-    "hidden": true
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "一文なしだよ😅\n"
-     ]
-    }
-   ],
-   "source": [
-    "my_wallet(0)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "hidden": true
-   },
-   "source": [
-    "＜`#1`の`if money_in_my_wallet:`について＞\n",
-    "* `if money_in_my_wallet != 0`と同じである。だが`if money_in_my_wallet:`の方がより簡単で`Python`的（Pythonic）だと言える。\n",
-    "* `if money_in_my_wallet:`は「もしお財布にお金があれば」と読めるため，より直感的でもある。"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "heading_collapsed": true
-   },
-   "source": [
-    "### 数値を返す例"
+    "    d = flow.Decision(w=3.5, h=1.2, S='False', E='True'\n",
+    "                     ).label(r'$x\\geq 0$ ?').drop('S')\n",
+    "    \n",
+    "    flow.Arrow().right().at(d.E).length(1.5)\n",
+    "    b = flow.Box(w=2., h=0.9).label(r'$x$').drop('S')\n",
+    "    flow.Arrow().down(sd.unit/5)\n",
+    "    flow.Start(w=2, h=1).label('END')\n",
+    "    \n",
+    "    flow.Arrow().down(sd.unit/3).at(d.S)\n",
+    "    b = flow.Box(w=2, h=0.9).label(r'$-x$').drop('S')\n",
+    "    flow.Arrow().down(sd.unit/4)\n",
+    "    flow.Start(w=2, h=1).label('END')"
    ]
   },
   {
@@ -6675,11 +14979,7 @@
     "hidden": true
    },
    "source": [
-    "今までの例では`print()`関数を使ったが，もちろん数値を返す`if`文を書くことも可能であり，むしろそれが一般的だろう。次の関数を`if`文で表してみよう。\n",
-    "\n",
-    "$$\n",
-    "y = \\left|x\\right|\n",
-    "$$"
+    "このフローチャートに従って，`if`文を使いコードを書いてみよう。"
    ]
   },
   {
@@ -6722,7 +15022,9 @@
     "* (`#1`) `x`が非負であれば，`x`が`y`に割り当てられる。\n",
     "* (`#2`) `x`が負であれば，`-x`が`y`に割り当てられる。\n",
     "\n",
-    "`#0`で`-10`が`x`に割り当てられているので，`#3`の`y`には`10`が割り当てられている。従って，`y`を実行すると`10`が表示されることになる。この`if`文を関数にまとめてみよう。"
+    "`#0`で`-10`が`x`に割り当てられているので，`#3`の`y`には`10`が割り当てられている。従って，`y`を実行すると`10`が表示されることになる。\n",
+    "\n",
+    "次に，この`if`文を関数にまとめてみよう。"
    ]
   },
   {
@@ -6750,7 +15052,7 @@
     "hidden": true
    },
    "source": [
-    "主な違い：\n",
+    "上の`if`文との主な違い：\n",
     "* `x`を引数に使う。\n",
     "* 関数の戻り値を設定するために`return y`が追加されている。\n",
     "\n",
@@ -6849,12 +15151,12 @@
     "\\end{cases}\n",
     "$$\n",
     "\n",
-    "次のコードで$\\rho=-\\infty$以外のケースを関数で表している。"
+    "次のコードでは，$\\rho=-\\infty$以外のケースを関数で表している。"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 207,
    "metadata": {
     "hidden": true
    },