Received: from malur.postgresql.org ([217.196.149.56]) by arkaria.postgresql.org with esmtps (TLS1.2:ECDHE_RSA_AES_256_CBC_SHA1:256) (Exim 4.89) (envelope-from ) id 1hkRMV-0003Du-M5 for pgsql-docs@arkaria.postgresql.org; Mon, 08 Jul 2019 10:59:12 +0000 Received: from localhost ([127.0.0.1] helo=malur.postgresql.org) by malur.postgresql.org with esmtp (Exim 4.89) (envelope-from ) id 1hkRMU-00086v-Gv for pgsql-docs@arkaria.postgresql.org; Mon, 08 Jul 2019 10:59:10 +0000 Received: from magus.postgresql.org ([2a02:c0:301:0:ffff::29]) by malur.postgresql.org with esmtps (TLS1.2:ECDHE_RSA_AES_256_CBC_SHA1:256) (Exim 4.89) (envelope-from ) id 1hkRMU-00086o-6M for pgsql-docs@lists.postgresql.org; Mon, 08 Jul 2019 10:59:10 +0000 Received: from mout.kundenserver.de ([217.72.192.74]) by magus.postgresql.org with esmtps (TLS1.2:ECDHE_RSA_AES_256_CBC_SHA1:256) (Exim 4.89) (envelope-from ) id 1hkRMQ-0007NA-RG for pgsql-docs@lists.postgresql.org; Mon, 08 Jul 2019 10:59:09 +0000 Received: from [192.168.178.43] ([77.190.96.197]) by mrelayeu.kundenserver.de (mreue108 [212.227.15.145]) with ESMTPSA (Nemesis) id 1M2fHt-1hmvfL1pYF-0047tG for ; Mon, 08 Jul 2019 12:59:04 +0200 From: =?UTF-8?Q?J=c3=bcrgen_Purtz?= Subject: Make 'Genetic Algorithm' a real figure To: Pg Docs Message-ID: Date: Mon, 8 Jul 2019 12:59:04 +0200 User-Agent: Mozilla/5.0 (X11; Linux x86_64; rv:60.0) Gecko/20100101 Thunderbird/60.7.2 MIME-Version: 1.0 Content-Type: multipart/mixed; boundary="------------34744F87CEF46F1D136BBE74" Content-Language: en-US X-Provags-ID: V03:K1:59MKxBPOEn71QM3AjTDQPtH6TObRfCVrXf7efBCyglT26mK97AF VlYqZlMySkO+6uXYCfsGD1bTiDfeaO6107tRMXY26zy/n1r2GvyxV4Q5dF7Hzt6bpbFQpeO su2LJvktVoWT0Bcqy6FCvqU1hej9PJoIQxhaRZtgHCNwtzeq9RdEX6DUGjllEgffiz+eYEb 1nqlP8htlCtuVzAfiQVBg== X-Spam-Flag: NO X-UI-Out-Filterresults: notjunk:1;V03:K0:0ybpqGutn+0=:/TsShZdveiOS/wJVeF4ug0 PrMiVH1LqlTr7h5fN+eDRdVRKOJ0pfIiciV4uls9fv2f1dmBLTQ+VvEccd+8GS1smmlQ1FElG +1/QXdfTDpWMlwbCFncatvp+HivXLpUo/900Dybr3r2lS2CBEoZHRZIzaQHpzKWWfbcLBlqtU vqqzvlk/hnOswqtJahU+qcQMrJVJVNKLMxra7Y7lModxrXno6PfYc0z5cPesz6NewFOlUqu3R UXF2McrZ7TZTfFLWq2elcSiSiJg3sFTZ2UDIandSLvkY/31nJf1Z3kZUYmCfVlYBIX0POhkRK wnkDwlOSqu4Vrj6VhvRkCqDhq5LKTmH+EcCJFw7GJxqo4tY3WbaIkAwPVWoSOUjeMfpgSONrj Aq2oWyeiohHTIigANF4FysGS+HYCQmAjFCHTFk/zxV+AyQnLldVXufj7nolbcc62w1ORdJMQ/ mzdU+kLyd/pk0j9A5sU1E9GLm0DWwVSbCOZZVcF72LAAb2XIOIvy+v5H8v6xCH+tsYS0d+qqg 5Le8Bk2x72xQOgxPdOz+yqVW1mHgkJldj+OIa+Y5MYw/TNiodzLOVryQcNgRsMTsD5xt/x3Bx k4UW70TNv5g2ZTPdsQYHH2kSblYzhNwDUkw1Id9q/15dxifYU4h6CS10F4v3NzN/c+Bz5kaMi MTLI6WKNWuP8Lhx+GPxgUip31WQQ2EnxPxBGCvdIk4Lw2HjG2n+7RCWDZIUp/s34Ur50AL+i1 f1o/BCkgEmuFhMCfeDZSIo5QOfjswHhZ645Vkw== List-Id: List-Help: List-Subscribe: List-Post: List-Owner: List-Archive: Precedence: bulk This is a multi-part message in MIME format. --------------34744F87CEF46F1D136BBE74 Content-Type: text/plain; charset=utf-8; format=flowed Content-Transfer-Encoding: 8bit Currently the 'figure' of a genetic algorithm is created with some kind of 'ascii art'. The patch makes it a real figure. Kind regards Jürgen Purtz --------------34744F87CEF46F1D136BBE74 Content-Type: image/png; name="Screenshot from 2019-07-08 12-52-59.png" Content-Transfer-Encoding: base64 Content-Disposition: attachment; filename="Screenshot from 2019-07-08 12-52-59.png" iVBORw0KGgoAAAANSUhEUgAABJMAAANlCAYAAADIH7gOAAAABHNCSVQICAgIfAhkiAAAABl0 RVh0U29mdHdhcmUAZ25vbWUtc2NyZWVuc2hvdO8Dvz4AACAASURBVHic7N1fTBt33j/6Nz+t NLPS2Y73orWfi419sY1dqYm96ka4SiPYtBXeNBJ+kkq4zQWkvcCJjoTTG5wjHYVeHEEuTsye i8AjnRbvRdastK15pLS4arp2lVbQH30E264EoY+EiXSE6blgOHuBufqeCxvwn7H9HXsMJHm/ JKQWxt+/n/nOzCfjmQ4hhAAREREREREREZGE/3HUDSAiIiIiIiIioicHk0lERERERERERCSN ySQiIiIiIiIiIpJmIpmUR2bAgY6ODrgi8+1rUVvpiHd3QA1MQy/+ZmXMhw7bAFKH2IpcZhJj 4ylkD6HM+YgLHY4wntQZO46OImasViterOpbbrIbHR0dBj82DJQVLr+u5DKTCAd8cNlUdHSo sLl8CEbimNfrfmxfZd/asR8eZ2b6exzWjad3fqqPQ0aOc/+Pc9sqWbamHdIx9rDHVl+aRjTU DY/DBrWjA6pqg8sXwMDYNJYMA7S5c8HjeNx8kuL42SC3NpKx1taiPJbiA/C7CutAh20AGWub d+w0uya1+/zZirY8C2Tj/Tgee4y1lmc5rGO5EflkUj6FyZlNAMD6dByZfEv1HhuqwwWvxwHb IdaZS43j5si0tcmkNpRJxo4iZqxWK16s7ZsTfbEkksnSn2lE/CWbSK0reSyNd8Pzh2uY1n0I j8WRTMYxFvIgG7+KVz1BxFcat6ayb8/aPvOk9fdJa6/VjnP/j3Pb2uWw+nx4Y5vH0mQAnt+9 g/ElFd2RMcSTScQnxxD2A/Nj7+B3gUnkqj7W3LngcTxuPotxTGQoG0c4PI18YBKZxUUszo/B 3/hTz6TDOX9urS30BGo6z3K4x3Ijv5DdUJ+JI7WtoavHg/kvpjGZGUd3QG2+5mPCNTCDpYGj bgU9SZ7mmLG2bzb4AkEEPbW3kFlX8pkIgje+htqbwNJMCI69PwRDCIcDCPiuIhwag28pCl+d 1jzN80ZEZEZ+PoLgtS+AvgRWpkNwlf5xIIzo2BLi01Wnn02fC3L9JTrGckvI7rowEA7BX+9E imriGketaPbYetjHckNCyoaY6lEE7P1idi0hejUIrTcptgy23FlOiKFer3BqioCiCbuzU/SN psu2ldlmIz0q+jqdQlMgFMUuvD1DIrG8U1bX3JBTwD4oErMH29oH03u1iLXkkOhxa0JRFKG5 e8RQck5MdEEoPYn9upZHvQJav5itKDOZjh3Ub/eK3or2VZZvr1F+pbkhpwBQ/uMcEnMm+m2m zL3+zC4mxGBXvf4U56XHK+zFeXF29onYXK2eGHzWwjmdnZsS/Z1OoSmK0JxdYjC5JoTYEYtT /aLTWRhzZ+egSKwZjIV9UCSSw6LXaxcKCv3ti83VnJOyPvR1CbddK3xOc4uu/glROQSVMVOj NOn4kBl3+bhsXF69eDHqm8zcVtqY6BKAV4wu1xsjmXVlSyR6FAGlR0xtGJeyFusUCjTRP1t/ PyntW6P90EijcZCNH9m5NDPnjfYts/2trlupuR81vW6sJcVwb/FzgFA0p/D2jIr0ltyaZrzu S7anTt1Sf5fut9xxyHD8LThONHM8aefcmDkGWHUMLt3vd5J9QoNbDC1WjZSY6lIEvDGxZnI+ ZI+xMuuD2f1Uds2pVlxXtV6RkDvEF8mfC1aqOrZI7GOVjnJNbH6s5c9LZvuMYnCjENO9CbFT WV4ra2C9dhqUa/XxzczaeBjnjoYsOg6YHbu681rnHMTM+X6p2X6tal9wDh3sCa1fj1VrZX+S mReZNleuSTL7n9nzZ2uPeaL6cxZfTwpxOGtde84VjM9Ta17XSF53Wbqm1NTssfXwj+VG5JJJ GxOiqzjRO2JHJPs0AaWnquE7i6OiU4HQvP0ilkyLufSsSE4Ni/7BxP7OKbPNVnpQOAHh7BkW ifScSCdjos+tCGg9YmrtoL65IaeAognN3Scm0stiY2NNLK8VGrU12y+cUISzNyaS6TmRTo6K XrdT2DWJZJKiCbu3X0zNrYmtrQ0xN9Er7NBEb/Kgw3vlu/v2yo+JPoPyq2xtiNlBp4DWJxJr a2JtbU1sbGyZ6reZMgv9cQqnu1MMTiTFbDopJvq9Qqnoz9682DsHxUQyLebSSRHrdQtF8Yrh xfqLj/VzahdOd5cYmkqK9GxCjPbYBRSv6B/sEe6uITGVTIvZxKjosUMonTFRmq8oLK6K0Nz9 IrG4JXZ2tsRyol+4FUV0xupmNsTW7KjoH54QieSsSM8V6uhzK0LpnCg7uMgkk2TjQ3bcZeNS qrw68VLZN5m5NVJIJrnF8NyW2No6+NnZKduo8bqyMyv6NQilZ6r2PrUWE96Kkx8jZX2rMwZG pGJcMn5k51J6LZLZt0z2d28/tDs7xdDUrJibmxVTQ11CQ/l+1Py6sSxGvRCKt7/wubk5MZuc EqODw2J2q3576637cu1pUHfDv8v3W/Y4VMWC40TTx5M2zY3Z47pVx+DyNW1ODDkh7P1pURad yzHhhSJ6amWsLTjGSq0PJvdT2TWnys6s6Gu0rhqRPBc0Uj4PjfcxI0e5JjY91kL+vMRUMqml NbD++BqfU1t7fJNdGw/r3LGalccBc2NXb17rnYPIrkWVdrY2xFqiT9jhFIOza2JtbUPs7QpW XI8ZaX5/ajwvsm1uJplk5vzZ6mNe9SC24XpSHM5aZ925QuPz1FrXNXLXXVauKXU0e2w9gmO5 Ealk0lrMKwCn2LtW25ntF3Yoomui9MRrQ0x0KQLOQZGuebyS2WZNxDoh4B4WZf94uDFV0vGC QtA6xdBcZWHFMryj5RO7OCzckEgmwS2GF6vLU3qTxbqL/99ZsegsjwovGlwkCCEWh90CWr9I N9lv+TIPxmiwbMAXxbC7tD/FDKV7SJQP5bKIdSpC663Xn/bMaVl7t6ZEj4KqOrameoSCThFb a9TfnWKGuV80uHml2vKocCvl8dA4mSQbH/LjLheX8uXVipfyvsnMrbFCMgnVPyVjIrWubEyJ LtT/Fy6xkxS9Suk4GKuct1pjYNCbpsfBKH7k5tLcWiSzb8n3d69uTfSVnchsidl+e8l+1MK6 sZUQPVBET50jV6M1rXrdl2xPo7obtk223/LHIfn+y853C8eTtsyN2WOAdcfgyv2+8P+9ojS0 F4cKJ+T1zttbO8bWYLA+mNlPZcusUmdd3dnZKfspJXcuWKtZpcn8xjFm5CjXxBqdajzWQv68 xFQyqZU1sEE7q8utoenjm+zaeHjnjlUsOw7UUHPsjOdV5hykpbUoPSjsNeattesxE2T2p4bz It/mppJJQvb82epjnrF2XE8asnits+5codF5avV1jbnrLgvXlDqaPrYewbHciMQDuFcwPfkP wB3CQPFpbGogjKBzF1/HSx76lc8gNb8LdyiM7lpfuZPaZh6ZJcAdHCh//okjiIFuBZuZ+fIH jWl+BHwVhRXL8IaCKHtciy+EoLtxjwtlllUOl0PBbi5XeMNEsXxPKFj+3URPECGvRPlGzPbb DK0bwbIB98DvKe/PTGYX7uAA/GVD6UEg6MH2fAZLNdvdjjmtaK/NA48D0LpDKP+1CzbkkK38 KqjiR6CsIyr8gW5om/PI1HtQcz6L1FgI3R4HbKoKVe1Ax0s38Wg3i5WsiSeTycaH2XGXiMum 59GwHxJzW5cT/VNppNMHP3OTe888klxXTGnTWwFkx8FM/DSaS9nt2rluKN0IBUofJWlDd6hk P2ol3mwe+Ny7yERDiEzOILOSMzd7NdZ9qfY0qrvR32XrafU4ZER2vluJizbNjfnjetmGlh2D PQMRdOVTGN97hkA+hfHpddhDYZSFuxmNjrGAdceXUlaXqccR/OUv8cv9nwAm94+vFq7ZrcTY Ua2JrY51s+cltbSyBpotF7D2+Ca7Nh72uWMpq44DQBNjVzmvJs7FZNYiWVZcj9Usu8n9SWJe 2nZOZIbVx7x21l31+UNa66w4V2h0nlrVN7PXXRauKTW14XrosI7lRY2TSUuTmHwEuANBuHQd uq5D1z0IBZzAd3FM702WrkPfBRwuR+2yTG1TeVZng8OhAnq2fMdSbbBVrl17ZTgq63GgXtUH ZaooL1JF4Rf5wqK1V76tuo1Vv5Jltt9mqGrF2wUq+5ODvgs8uv27qle5v3TzH4W/N2y3lXNa 2d7i1lUTrULd60P5htUxYbPBBh252h1BKtyNP46twBWexMz8EpaWlrE8NwwvgLyZ83LZ+DA7 7g3jsoV5rNcPqZ3GiA0efze6uw9+/D5Hocmy64rNAYcG6Nk68Z/LIrcL2BwOSJ7GmCM1Dibj p9Fcym7XznXD5qjaj1Sb42A/ainefBhLzWKkO49UNIQ/vPRvsDl8CI1nqt84YcRw3ZdtT6O6 G/xdtp5Wj0NGZOe7pbhox9yYPwa07RjsCCISVPH1ZBwrAPSZScxsujEQ7m5+/Wh0jLXy+LKv hTJrrau2IMbn5jA3N4fEYEXGU3bNltJCjB3JmmjB/DV1XlJHS2ugyXKtPr7Jro2Hfe5YxqLj gOmxq7d+Shw4Gq5FJlhxPWZccAv7U6N5aeM5kRlWH/PaWXf5hw9vrbPiXKHReWpV98xfd1m3 ptTQyrH1yI/lBQ3e5pZHZnIG6wDwp1fx6z9V/n0d8fgSomO+QqAowEo2B6DGgmdqG71iGx25 XB6wuRq/drFYRk7XgbKtdeiVxTbDZoNqdflW9LtZxbrd4TRmwgaNV23l//pr8Nm2z6kZeg65 PFC6MudzOeiwwVGzonnEZ9bhDs8gHinJhy81cb+LbHy0Mu416m1HeXXntikm1hXVj6BfwV8z 00jpAwgZzF82NY0laAiU/7OOdaTGwcL4aaptbdi39Bz0yv1IL9mPWo03VwDReABRAPpKBqnJ KMI3ghhwZJEymuhGzLSnUd31/h6UrKcdxyHZ+W41Lto0N5bFaUvHYBsCkRCcr05icj4Ez2QK +c4xhNu0fBS0Y31oocy9dXV+pmJdtcHjL/xTpWO+9GTZxJoty+oY2+9CO9ZEC+ZP6rxERXWJ eflko9XnAPssjl/ZtfEoz4sBa44DVoxd287FZOu1evxbHBOJeWmuzS3uf6WOwTVdc3Uf1lpn UdsbnafWKN/6NbJZLR5bj8OxHI3uTMpnEJ9Zh9I5hGS6/Osq6XQSQ17g0XQc8wCgdiPoV/Bo ehKZWhEntY0f3T7g0Uy8/Faz3AymM7uwd/sbT7TqR7dPwVKq4l+5chmkmsi4GZUf8AEr0zPl t4OtzGD6HxIft6lAvvIOhNb6bVimrOK8ZDPzgMcDT+WPq84dH4c1p2bsZjA9UzrzOlLTKWzb /ej21PhMvnDAsFWsPiupFB6ZrV82PloZd8N65cuTiheZuW2GmXUFNgSjA3DufoFIeKb6X62z cYRHvsOuM4SIye+oSO8zMuNgZfyYYWLfMr1G7GYQT5X+W4eOTDxzsB9ZGL82TzdC4yMIaNtY mc82194m22NUd92/y9bT4nGopeOEhWuuNXNj8TGg1WOwP4Kwdx3xSAjjXwPdkYGG9bd0jDWx PkjX09KaU1xXt/8TkbDEbe2m1mzzGu2DprRjTbRifZc4L3G4HEBuBWXfJNFNfA3O6nOKPVYf 32TXxsM+d6yj6eOAFWPXrnOxhvW2afwtjKfqeWm+zbL7n9z58+HEruXXk4e01tVktu2NzlOr ym/TGtmslo+tx+RYXu+BSoXX6CqiZ8r4QWcbE11CgX3/4VRlbxtIzIp0o7e51dim7Enus+n6 T3K3Dxq+yrXwpgi76InNiY0dIXY20mK0yykUReIB3AZlJvuUsocHH7xJZkLMzlW/Sabew80K 42oXvRNpMbe4KBaXN8SOiX6bKVO2PzuLo6JTKzzdvjAvaTGbnBKxoT7RNZSuX3fb57TwBp6q t3XNDQkn7GJwruLzxaf7D07MivTcrJga7Kx6ur9I9wsNiuhN7M3U3kPZ+kVybUcIsSWWE4PC a9eEAkX0JA5mtOoB3FVlyceH7LhbPY+14qXu29xqzK2RwgO4vWLU4NUGZtcVIXbEYqxLaICw d/aL0amkmJ1NiqnRfuHVIKB4xbDEO0ur+lZjDIw0Hgf5+JGdS+m1SHLfMtPfsv1oqrgfDVXv R02vG2sTorerTwxPJEQyPSfm0kkxMegVGuyiv/jURLNrmnR7GtUt0zbJfsseh4y0epxo+njS prlp9bje7DG41gsTCusMBLQ+qRcztHaMlV8f5PdT+TJr9EgsxnqEHRCau0cMjk6IRDIpksmE mBgdFF3Og9cNm1+zq5XNg0SMGTm6NbG1sZY+L1kcFm5oonM4Lda2dsTW8qwY7XEXXo9d+QDu VtbAeu00LNf645vs2nhY545VLDsOtD52+3U1OBeTHXtDhg/gtuZ6rFoL+5PEvMi2uerYILn/ yZ4/W33MM2L99eThrHWWnStInKcaXtc0fd1lYk0xuDasZMWx9bCP5UbqJJO2RKJXqf+Gk62E 6NUgtP7ZkovjhBjq8Qq7phReD+jsFH2xdNlJs8w2G+lR0dfpFJoCAcUu3D1DIrFc3rn6i9eO WEsOiR53YQfQnJ2if2JWxLqsSSbtld+1V767Swwl0oWn7/dVnrZWWhOJwU7h1JTCG66cQ/v1 yfTbTJlmFqmd5aQY7tsrQxGa3Sk6ewZFLN346e7tnVOTyST7oEjOTYg+r71wYmL3ir7YXPmF 22xhJy9bGDfSYnjvwLHXvnRMdDVKJhmVZSI+ZMbd+nk0jhejCy+Zua1UO5nU3LoihBAb6ZgY 3G9H4e1wirtfcv8w6lvt/dBIw3GQjB+rk0mFqmXWDfn+HuxHsfr7kWhy3diaE7H+HuF12ott 1oTT2yuGksslc25uTZNuT6O6pdom22+545Cx1o8TTR1P2jg3rRzXmz0G13z75saE6ILBcaWm Fo+xkuuDqXVJuszathanxHBfl3DbtUJyTdGE09sj+kcTYrHw+sOm1+xS5W9zk9vHKh3lmtjK WEufl4gdsZwYFJ3Oipg2eptbK2tgg3Yalmvx8c3M2ngY545VrDwOtDh2+3U1OAdpRzKp0PxW r8cMNLs/Sc6LTJurjw1y+5+Z82drj3lG2nA9eQhrnZXnCo3OUw2va5q+7jKxphheG5ay5ti6 v+khHcuNdAghhNm7magGfRpB1wByIyuYj7iOujXPpPmIC69OBzCXm4T/qBtTifFhIR2pAR+C 0zaEUxmMd7f1yQlE9CQwscbm4gG4ruYwsryEaKNb74lacKzPS4iILMK17tnU4AHcVJOewfjI EmwBHzw2FfncPOIjI/hPNYjkgOuoW0dHjfHRZjYE4imM5/y4FgzAkckgKvtKWiJ68jW5xuor S1jJZjAW/QJqTwIDTCQRERERNYXJpGapKpCdxsjACHKb24DmhKd7AMnpMQR5kwQxPg6BB+GU jvBRN4OIDl9Ta6yOmfDvcPVrBfbOQcTjocN8NxIRERHRU4VfcyMiIiIiIiIiImn/46gbQERE RERERERETw4mk4iIiIiIiIiISBqTSUREREREREREJO2ZSCblMpMYG08h28Y65iMudDjCmG9j HaVq9WllzIcO2wBSh9QOao3VcWMm1mtte9ixfNQq9xkzY9i+/U1HvLsDamAaepN1HcUawXXp sFXHydHLIxN2wRaYRq74m8Na5w7jWC9T37O2htZ3dDG6Mu6HzTeGlUOul4iI6FnxbCSTUuO4 OTJ9aCeYh6FWn1SHC16PA3xh2LPJTKw/jfuFFcyMy2Hub2brOoo1gjFFWJlENK5iYKR9b0qr FWeHHX+M9+PNEx5BMDeGyHSu8cZERERk2i+OugFkLdfADJYGjroVRM+Gw9zfrKqLawS1Tx6Z 8TEs+aKY9h91W+iZpwYQDtnQPRbHSigKz1G3h4iI6CnT8M6kVEhFh2+84l/ecpjs7oAanEZ+ 71fZGUSDPjhsKjo6OqDaXPAFxpApua85vzKNSKC4jWqDyx/C+HzFjc8S5VSp85n5iAu/u/0I 2P4z/tDRgY6ODnS4Ivu3n+cyYwj5XbCpHVBVB3yBCKZX8lVV5FemEQn64Cq23eHyIzSWqbpt W1+aRri7WJ7Dh2DFNvmVaURC3fA4bFA7OqDaPOgemETlMDTbJ6Ovk8i2vdTebfrTM1EEfY5C Wx0+hMbnyz63v13qYBwd4cz+360cX0vi5yjjtI5cZrw4TqrhOMvsh41ivZTMto1iWXqsatRf L26smAPptcvkuJSq2t+aios8sjMRBDw2qKoKmyeAyMxKVfvM1GVmjdibi5n9GGww3zX2U9mx y8+EYOvwILJUOQ45xLuN5uyAmbbKrD1myqvXHqM4ll3r5dsgFydm+56aj2OguPbYXN0Iz2QB 5LEUH4DfVajL5Q9jOisxIPkMJqc34QsF4TJsV/11bn/c6uz7teLs/24QfzJrSqN1qXLbVtdQ 62PEuJ3Pcoz6Q0E4/jGJSX7nkIiIyHqigdk+RcAbE2tlv90QE10QSm9C7AghhFgWo14Ixdsv JpJpMTc3J2aTU2J0cFjMbhU+sbM4KjoVCHvnYGGbdFLEet1CUbxieHGnWG7jcqo1+MzWhpgd dApofSKxtibW1tbExkahsK30oHACwtkzLBLpOZFOxkSfWxHQesRUSYf32q55+0UsmRZz6VmR nBoW/YOJ/XGZG3IKKE7hdHeKwYmkmE0nxUS/VyjQRG/yoPFbs6Oif3hCJJKzIj2XFrOJUdHn VoTSOVEyxs33aXnUK6D1i1kTbTcyN+QUgCI0d79ILG6JnZ0tsZzoF25FEZ2x5fLtFE1o7j4x kV4WGxtrYnnN+vG1Jn6OMk7rjLNiF3ZnpxiamhVzc7NiaqhLaCgfZ6n9sE5cVKmzrWwsy41V vX4bx41VcyC3dlXsM2bGsPKzTcbF1my/cEIRzt6YSKbnRDo5KnrdTmHXIJSehNhqpi4Ta8Te XNi9/WJqbk1sbW2IuYleYa8x3zX3U+k658SQE8LenxZlUbIcE14oomdqo+ZYybZVdu2RLa9R ewzXP6m13kSfJOPEXN/twunuEkNTSZGeTYjRHruA4hX9gz3C3TUkppKFdvfYIZTOmFgWDaT7 hR1OMbRoNE6N1zmpfb9WnNWJP9m1qt58VrFgDbU6Row88zG6Myv6NQj38GLlX4iIiKhF1iST thKiB4roSdQ6qdkQUz2KgHtIzJVfPYhYpyK03uJJRsNyDEh8ZnHYLaD1i3TZb9dErBMC7mFR doqxMSW6FAj74N6FzoaY6FIEnIMiXef6uJB8cYrBso0WxbAbQulNirqX1sujwq24xf65TtN9 qrxok2u7fH92Cr+394vZnfLthuYqK7ByfC2Kn6OM0xoK46eJvrILgi0x228vG2fZxEituDBS a1u5WJYcq7r9Noob6+agqWSSMDeG5YmoZuKiuJ94R8svghaHhRt1kkmWrRF7c1Gy/pS0q3S+ ZdYS2ToL/98rSsN+cahwYV7v2liurbJrj2x5jdpjFMc1VK71ZvvUME7M9r1iP9+aEj0KquZ5 a6pHKOgUsbVG3fMKKD0iUTEccuuc/JpSK86Mfy9frtn5bG0NraHpGDHGGC22s2eq7jGJiIiI zLPmAdw2D3zuXWSiIUQmZ5BZyZXf1pyfx0xmF+7gAPxq6R88CAQ92J7PYEmmnGbqriU/j8wS 4A4OwFf6e0cQA90KNjPzha9a5DNIze/CHQqjWzUs6YDWjWDZRh74PQp2c7mDW8HzWaTGQuj2 OAq3+qsd6HjpJh7tZrGSzbfWp6o+mmi7EcWPQNmEqfAHuqFtziNT+noUzY+Ar6ICK8fXqvg5 yjitR+lGKFD6OGQbukMG43yYGsWy7FjVrcM4bo5kDqzQTJuK+4k3FCx/nocvhKDb4rrq0fwI lO+ocDlK57vFtaSCZyCCrnwK43sPxs2nMD69DnsojLJdoam2Sq49suUhj3xeh64Xf/IVI20U x4DcWm+yTw3jxHTfK/ZzmwceB6B1h1D+axdsyCHb4DnGuWwOUB1wGMVIo3XOijXFiNlya82n WVadD5S1q/QXlXFary3Pcow64HAo2M2uoEH4EhERkUkWvc3Nh7HULEa680hFQ/jDS/8Gm8OH 0HimcPDWc9B3gUe3f1d4rkDJz0s3/1H4u0w5zdRdi65D3wUcrsorFxscDhXQs4U27W8n8V4a Va14Q5IKqACQL17o6UiFu/HHsRW4wpOYmV/C0tIylueG4QVwcI3SZJ9q9rHJd+rYbLBVnn/a bLBBR6707FU12M7K8bUsfo4yTuuwOarGT7U5qsf5MDWKZemxqleHUdwc0RxYook27cW/ozL+ Hai/21rcf1VF+VRUzneLa0klRxCRoIqvJ+NYAaDPTGJm042BcDcaXsZLt7XB2iNb3nwUnl/+ Gr/+dfHHFsJM2eYGcSy91pvsU6M4aaLvRrk7W1WHVKj7x7Ha8vk8oNaYwUbrnBVrihGz5RrO ZxMsOx84KK9ujNRty7Mdo3tbHvk/OBARET1lJN7mpqL6EJyvPtFwBRCNBxAFoK9kkJqMInwj iAFHFqmgDTYFcIfTmAkbXIyotoOHddYrJ1Tjn6yb+Yyt0KaVrA6UvcBYRy6XB2yuwgnM/na5 iu2aMY/4zDrc4RnEIyX/JrdkcJLTTJ8qtdp2PYdcHig9g8znctBhg6NRE6wcX5uF8XOUcVqL noNeOc565ThL7oeHxcyctKvchnNwBGNmNi6K/c3pOlB2yaRDr9x1Wq2rFZaugwBgQyASgvPV SUzOh+CZTCHfOYawr/EnGxctufbI8kUwMxcqiSSbxFuhTKz1MmTjxOq+m26mDdB14z42WueO w5pyqCyOkaOu/9jGaB56freQzLS0XCIiImp4Z5LD5QByKyi741mv//Ubm6cbofERBLRtrMxn AbUbQb+CbGYe8HjgqfxxOQz/NbqqHAlGn1FtKpCv+Bcr1Y9uH/BoJl5+i3tuBtOZXdi7/YUT zGLbH01PItPqGV6+cCFrq8jErKRSeGRFuT3kXgAAIABJREFUnyq12vbdDKZnSu9z0JGaTmHb 7kd3o6spK8e3TfFzlHFaZjeDeKr032J1ZOKZsnGW3Q+l4qKJbas/3NxYtatcozloZu0CWhyX Bm2qrsyPbp+CpVTFHUW5DFImvuLY9BohS3ItMRV//gjC3nXEIyGMfw10RwasuaiXXXuky3PB 5/fDv//jaXxR2uRaX7sNknFidd9N8vg8UHazyGYN/thonTOx79eKM+NjfZvWqjrtkGJ1jBx1 /cc2RrNYyQKay2NJGpyIiIgONLwzyRcKwn17EtGRDKajfthyGUxGRsovKLKTCA5k4AkF4fe4 4EAOS9MjSG3bEQx4AKgIjY9gsvsmuv1ZRCNB+Bwq8noWK5kUZhBGZrxbohwDEp9xeTzQdjOY nMzA5rdBVR3weFwYGBvE+B9uIxgAxiIBOPJLmIxG8YXag6no3tctHIW2+28i6M9jJBqCzwHo 2Qxm5n0YmQzJn/iofgS7FVydHMFMcBJBVx4r01GExrNQLOlT9e3lLbVdUTEfDSKsjyDkA7Lx EUT+mkdnLIpAw7NvK8fXYU38HGac5uIIdo8hH55BKtIg86aomI8ECuPsAbLTI4j8VS8bZ6n9 sE5cGE2XXAzVIjknplk01ybGTHZcGoZ8M+sXXBgYCWH8j1EMjHsQD/th0zMYD42VvWK8mbpa m99KcmuJuTo9GAh3YeTa13ik9WE8aNV9A7JrTxvJrvXSZOPkaPtu6+6GB2PILOURdlXU1HCd k19TasVZrd+3Z61qcR+zPEZMelZiNLeE+awCf9R/UG5mALY/TKM7oWMm1PbVgIiI6OnV+Bnd O2I5MSg6nZpQoAjN3SWGEmkRK3ub25yI9fcIr9MuNAUCiiac3l4xlFwue8vIznJSDPd1Cqem FF47b3eKzp5BEUsXXwUtWU4Zqc+sicTgXr0QcA6JueJfNtKjoq/TWfysXbh7hkRiubq2ncWE GOrxCvte252doi+WLn8LjH1wv9w9yT5FoLPkjVIbaTHc4xaaAqHs1ZeOiS4oomfvFTgt9Kny rUkybTey15/k3ITo89qFokAodq/oi82Vfa5Wvw+6a834CmFB/BxmnC6PCi8gvA1ef3QwzrG6 4yy1Hwoh6sV6NeNtpWNZZqwa9LtW26xZK+TGrHqfkR/D8jesNbF+Fdu5lhwSPe5iO52don9i ttDOmm9zs26NMDXfDfdT+XVJCCHExoToAoRzqHaUljLTVpm1x0x5ZtpTbEDjtd5UG+TipLW+ z4khp8F8zA0JJ+xisOE0rYmYVxH2/nRZzMuvc7JrSq19tPa+K1Nuo3XJqL8traGWx0i1Zz1G txK9QlF6xFRp5bP9QqvoIxEREZnXIYQQR5XIouNrPuLCq9MBzOUm4T/qxjyB9HgAjoiKeHYG Vj++huhpkYsH4Lqaw8jyEqKNH0RET4DcdACesA3x7DQsu9mMqCk5xLtdiLpmkI0H2n9HIhER 0TPGore5EdGBPOZTS/CER5hIIjKgryxhPjWOcPQLqD1RDDCR9NRwBMcQdsxgLJ496qbQs25p HGPzPkRHmEgiIiJqB4m3uRGROSoC0zkEjroZRMeSjpnw73D1awX2zkHE4yE+GPdpovowMj2J 8fkcdLT37XFE9WRzDoSn4wi7jrolRERETyd+zY2IiIiIiIiIiKTxa25ERERERERERCSNySQi IiIiIiIiIpLGZBIREREREREREUljMomIiIiIiIiIiKQxmURERERERERERNKYTCIiIiIiIiIi ImlMJhERERERERERkTQmk4iIiIiIiIiISBqTSUREREREREREJI3JJCIiIiIiIiIiksZkEhER ERERERERSWMyiYiIiIiIiIiIpDGZRERERERERERE0phMIiIiIiIiIiIiaUwmERERERERERGR NCaTiIiIiIiIiIhIGpNJREREREREREQkjckkIiIiIiIiIiKSxmQSERERERERERFJa5hMWoq6 0NHRUfPHEc7sbzsTUou/92FspZ3NPiSpEGw1++5BtKKP+lIckaAPLpuKjg4VNpcfoegMVvKS 9enzmIyEEPC7YFMP6gpM65Z0R1+KIxI4aJ9qc8Dl8SMQCmM8lSvbNr80jbFoFNHoGKaXZDvQ PsetPdbKIzsdQcDjgLofX36MZw+p9lwG8UgI3T4XbGphH1ZtDnj8AQxE48jkjtd4N4qF9q1D WYz7y9cAo/KP0zpo1JajGz8iIiIiInpa/OKoG/C00DNh+AP/gUe7AKBAUYDt9e/w19v/jtR8 DPOpCDxqg0KyMxj/01/xqA3ty89H4O/+U7F9Bbvbm1jf3sT6o++wZAshEnAcbL8Ux83bXwAA ujwDCPkclUUequPWHktlJxEa+BO+K8aO3emAqrrgaBQvVlQ9M4BA6M9lcQEUYuPRd1/g0Xdf IAMfsmO+9jdG0pHFQnYG8e9Kf/EI8fgSosdobGQ81fsSEREREREdClPJJGffFCYHSi88VKiu gwspf3QGswMAYIPHZUXzjgsvhmYnEbKV/Eq1weXa+58ljIWLiSSlE6NLGUQ9wFLUD//tf2D7 6ygG4kHMh12VBZez+REcGoXL74MjE8G//4dVaSUdM2OTxYSBHT2jk4gGXLDldeRWljAzE8f8 ISQuqIaVJawUkznOoQyy4/5DqTY/H0Hg3/9cTF4qcHaFEY0E4XOpyOdyyK5kkJqewZN2c0q7 1qGV6Tj+UfG7R9NxzI+N43BmzLynd00mIiIiIqIjJRpYHHYKAAKA8I4u19022acUt/WKg013 xPLUoOhyakJRFGH39orh2UUx1bO3baeIrQkhxIaY6ELxd11iamvv86W/79n/fVld6Vkx2usV dgUC7mGxWPzk1mJCDPd2CrddEQogFLtbdPaNiuTaTqNuF8z2Ca3YnokNIcROjc+txURncYzQ OSHWSn7v3fu9d1TUH73KIr37496T2Gr8gbqWxai32A77oEjXr1nEOrFfd/mPJvpnC1vVH39z cymEEDvLSTHc1yXcdq0wV5pduDt7RWxuRaI9xzB2hBBbi1NiqLdTOLVCfYrmFJ29Q2Jqca+B OyLRqxj3zTkk5urNUnJI9HZ5hdOuCUWBABShOb2iqz8m0hsyrdsQE10Hddv7kqLmxyq6LDs2 VePc5xV2TRFQ7MLbOyrSW2bLbSI2S3a62jEmM6eLYthdrEvpEf299mIddjGYrtNv0+vg3lg0 ip0aY1wRy+VtaWL85ubERH+xHVXztiOSvaX1p4v1K0Kxe0VfbE5siR2xWNbvPjGx2Op6RkRE RERER81UMsnZNyVmZ2cPftJpsVxyXWB0EbU21VNMyJT+2IVdQ8VFVLMJAU1oWskFefEiamt2 ULiVvc8pQiteQAIQ0DpFbFHiAnI/mYTiBTsEFE24u/rFxFxJx5dHD5JGnbGDZFLp75VekZTP Q1icTNoquWhVhL2zXwzHEmJ2bllsVbXJ7AWn0fibm8vyuSr/6Zr4n21MJrUvdjZm+4XTsM0Q gFP0JzdEK8mkuSHnfjzanfZCAmH/s4Mi3aiJW1OiZ/8z3rJERt2PmRibg3FW9hNeSkkftd7E fgJLrtzmk0n1Y0wi+zY3tD+fSm9CbMz2C/teIq4/XZZva20dlI2dyrqMY7m1ZJIm7Pbq+DyY t9JkktG2mujs6azut71fzJpYC4mIiIiI6Pgx9Ta39b9exR//+MeDnz8EMTZf5wP5DMaiX2Ab AOBEX2IZWztbWJzwofjLGsx852ob22oAsfQaNrY2sDw9AFd+HtG9r505+5BY06HndOjLMXRp ALa/QzQyjVyjokvs7j1TZncbj77+M6696kc4U3wwtssPn73496U4xjM55PM5pMZLvhazqyNn zXO0m2BDKBqGWwGAXWx+92fcvvEO/vjqS/i1zQFfaAwHz992ITIvsDXVs//prqkNCCEghI54 oLJsg/Ev+3uDuSydK2joGp7F2tYOdrY2sDgbQ8jzosn2HIPYyWcwMvBnrAMA3OhPrmFH7GAt 2Q83AGAdfw6PIJNXEZrJQ8z2QSt+1D26XOhbtv5Xp1yhcaSXtyDyOnLZHHL5LcwNeQt/XI9j bKZBsGVXkN2Lac0Hn2vvDzri3RUPm7cNIAWUz5WpsdmF6o9hcSeP/EYSfcV9ZTsVR0Y3U67Z 2CxqGGONYyYTny7Op4JAKABHdwiB4qRtzkwiU+8Z5WbWQenYqayk0X4INLNv67YQpuaWsZwe LcwFSuatcltHGMnlNSxO9BTjeRvffbEEz/AsltfmMNql7A0YpusOGBERERERHXemkkmmraSQ 2Sz+d1cU4yEPbKoNvvA4Im6rKlHQOx5HpNsFh80Bj88D28o0UuvFP+dXMDkQQHd3NwLhaWSL 1zC78zOYb3Q94woiOjWLxbUt7AiBnY05TPQ6i398hHg0jiwAqN0YGSteQO3+A3/6w7/hl7/8 N/zRsmcetU7tHsf8fALDfV1wayV/2N3EP/56E3/0h+tfENdkMP5mPl46V50jiI8F4LIV3jTn C0QQ7jZVmkltip2lGaSKca90RTEWdEGFCldwDNGu4jabKcwsNd9yh78bjuwMxiJhDISCCAYH MDa/d4W/i+xStvnCa2l6bOwIjoThUwE4uhH0FZMKewlWq/ZXmXY3E2P5DOIzexPajVDABqjd CAX2syuIp+ok78ysg03HTov7oSENwbFJDPg98HSHMbCX3TRMjGsIjY0h6HHBFwxh/0l69hDG RgLwuPwYCO0VsI3sMXtDIBERERERmWPqAdze0WUsRT3yH9Bz2LvmUBwuHDy62wGHC7DmtWUe +H0Vl005fb9ebP4DX29WfgbArg5dB1DvRUaeEMq66/AjHB/B9K+v4msAu0vzWAHgAuAamMGS bQTRsRlkVnLIqw74gwGoqT/hP9cBaC642pkXkWDzhTA2HcIY8tBXlpBJTWJs5M/4bhvA+jTi 85Po7jZbqsH4m1EyV5rLY3A3RTu1KXZK4l51OSriXgO+3gZQLKMpWcQDflz9wqhxBfl8g4t1 lwcuBYW7dbZXsJQFul0AYMNARiCUzyDi+QP+Y73kM02PjQOe/VfTqVD3bwTKI59vpVxJLcZY PjOJvVwSfN1w5VawkgNsfh+Uv36NXWxjJp6CHgwZJ3DMrINNx06L+6EhF3yeg3mzqQqAXezP W8W2HldxW5uK/U1dPuz9Wi27AYzJJCIiIiKiJ1l770yyOfYvrnZz2ZKvv+Swkq3e/OBao/Ri JWu4bV0O2369Wl8SO4VnQ1X8ZDDQzIVp6VVU2cVR4e6B6fkV5HQdem4FqagHuWKnFX8AfrW8 nEbX+zJtkSsjj1w2V3L5psLm8SMYiWMsZN/fRtetu8CTnsuSudrOrqDyz5bX14gVsVMS9/ls rizuc9m97zXZYGv2jezz4xgpJpKUzmHMbexACIGdkq/LNWQLIOgv3iGE7zA+kkJpfkJV1eov DLZrv2rn/lpRvvkY05GKpw6+jfbdTbz60kt46aWX8OqNr7H/7ddUHDO1vvtoZh1sd+wcIaaP iIiIiIieHu1NJnkC6N7LVXw9juj0CvR8DkuTEcSr7kqyweHYuxReQiqTA5BHNj6G6fXKbRvV G0Sg+G207ZkRRDMHl2R5fQWpyTACkVSDi5scJgM+BCOTSM1nkdN15FZSGBsYwdfFLRR/YP/r HPmlaUymlpDV8wDyyC1NIxyM4rtdAHBiIBo8uEicDkD95S/xy192wD+eLakzj7yuQ9d16CUX pvu/K0n21C7DiI6ZARdcviDCY3HMZOaxtLSEzHQUI/u3XJTcWYBCMmEv1ZCdXzF5IWhiLj2h /bnCdyMYiKawoueR17NYSk0iXnw4S/32HLPY8R2Usfv1GKIzK9DzOlZmohjbCx5nAEETN/mV 0Q/utLH5AvA5VAA5pOKZ+o8iK+PAwEgYe9+yWv9zEL5AFPFUITbmUxksVd79Ysl+ZcBkuaZj UzLGDOkpxGckRnU3g3itbJKZdbDdsYNW920iIiIiIiLA1NvcvKXv2TbQ7FuMJtYK2+6UvCEJ gFA0peRNULXeyFX++u89G7P9ZW9vUjR74bXk+29kSla+8byyBDFR881H1W+u2prqqfmWpK7R xbK6dhI9+2+q6ix9jdZaTHTWfIsTBJQekdhpUEatvnTVKRcQWk+i/NXwy7GDN9Ht/8iPv5m5 lHrTVoP2HK/YMfdGrtK3Brob7GOFAUuKvv39xy68Pb2ix2sXinLQRudQvXfBHVhL9NUc+4NY 7xfpJsbGeJwrXie/3MSYNxGbzb7NbWvqYD/T+pKi8r2KO+mDuFM6J8RajfrNrIPNvc3NOJYN /97Uvm00b8ZzKXYSB28KLHm75cZU18GYT0m8QY+IiIiIiI6t9t6ZhMKzhOanBtHl1KBAgd3d i+HkzMGziBQbbMVbdtTAOFITffDaFQAKbK4AhpMpjNV7rVUNjkC8+MDpTrjtCrC9CR02ON2d 6B0cxWTU3+C9Xw4ExqYw3N8Dr9sOTSm0SXN60dMfw+xSBhFfyZ08ngD6urxwahoUAIrmhLdn ELH0ClJRn6l3jFnPgdB4EhPD/ejt9MJpL7QRiga7uwv9o7NYmgmVP47GE0Z8qh+dTm3/LgYz zMylLTCJpaVk4eHg9r3xs8Pd2Yvg3nNgGrTneMVOoYylxSkM9XbCqRVarGhOeHuHMLW4hHiw he8p2YKYzEygv9MJBZtYmV+C7osiFQ/Jf82tyBWaxtLKLCYGe9HptqPQVKXQ1q5eDI4mMLcy ie6SfrU6NkZMldtEbErFWJUcpuOZ4lfZNAQHAlXPRFK7wwg6C/+9+90kZrLGJZlZB9saO0DL +zYREREREVGHEEK0tQZ9CZkVG/x+V/FiMI9sKoLAH/8DjwAonRNYmQ8f8oOXiYgOEddBIiIi IiJ6iph6m1tTsnEMvPonrCsa7DYVyOvY3C4+tlbrxMjkAC+giOjpxnWQiIiIiIieIm3/mhsc AYR6u+C2Abq+ic08YHd60TNY+KpY1He0XwAjImo7roNERERERPQUaf/X3IiIiIiIiIiI6KnR /juTiIiIiIiIiIjoqcFkEhERERERERERSWMyiYiIiIiIiIiIpDGZRERERERERERE0phMIiIi IiIiIiIiaUwmERERERERERGRNCaTiIiIiIiIiIhIGpNJREREREREREQkjckkIiIiIiIiIiKS xmQSERERERERERFJYzKJiIiIiIiIiIikMZlERERERERERETSmEwiIiIiIiIiIiJpTCYRERER EREREZE0JpOIiIiIiIiIiEgak0lERERERERERCTtF/X++K9//euw2kFERERERESSfvWrXx11 E4joGcY7k4iIiIiIiIiISBqTSUREREREREREJI3JJCIiIiIiIiIiksZkEhERERERERERSWMy iYiIiIiIiIiIpDGZRERERERERERE0phMIiIiIiIiIiIiaUwmERERERERERGRNCaTiIiIiIiI iIhIGpNJREREREREREQkjckkIiIiIiIiIiKSxmQSERERERERERFJYzKJiIiIiIiIiIikMZlE RERERERERETSmEwiIiIiIiIiIiJpTCYREREREREREZE0JpOIiIiIiIiIiEgak0lERERERERE RCSNySQiIiIiIiIiIpLGZBIREREREREREUljMomIiIiIiIiIiKQxmURERERERERERNKYTCIi IiIiIiIiImlMJhERERERERERkTQmk4iIiIiIiIiISBqTSUREREREREREJI3JJCIiIiIiIiIi ksZkEhERERERERERSWMyiYiIiIiIiIiIpDGZRERERERERERE0phMIiIiIiIiIiIiaUwmERER ERERERGRNCaTiIiIiIiIiIhIGpNJREREREREREQkjckkIiIiIiIiIiKSxmQSERERERERERFJ YzKJiIiIiIiIiIikMZlERERERERERETSmEwiIiIiIiIiIiJpTCYREREREREREZE0JpOIiIiI iIiIiEgak0lERERERERERCSNySQiIiIiIiIiIpLGZBIREREREREREUljMomIiIiIiIiIiKQx mURERERERERERNKYTCIiIiIiIiIiImlMJhERERERERERkTQmk4iIiIiIiIiISNovjroBRMfZ W2+9ddRNIHpmvfzyy7h9+/ZRN4OIiIiIiCowmURUx8OHD3Hq1ClomnbUTSF6pvz4448QQhx1 M4iIiIiIyACTSUQNjI2N4dy5c0fdDKJnyoULF466CUREREREVAOfmURERERERERERNKYTCIi IiIiIiIiImlMJhERERERERERkTQmk4iIiIiIiIiISBqTSUREREREREREJI3JJCIiIiIiIiIi ksZkEhERERERERERSWMyiYiI6NjSsbmZb7jNesNtiIiIiIisw2QSERHRYVj9CO+cfwW/fe45 PP/bV3D27FmcPfsKXn75FVyI3MNqZT4o/wPuXnoXoz8c/EFfuIc79xagl234Mx5cu4Tw/c1D 6MTxYDwOwOrd8/jt+btYPZJW1aLj4Z1LOHv2PC5cOI+z54fxZWXDnwC1xvy4aXc7j2PsPSlz Q0RETxcmk4iIiA7DyfeR+PskLr4AnLiewLfffotvv/0v/POzD6Ddv4YL174suRjU8WXkXfzt tXGMv2nb/+32wl2M3l3AdnnBeP/jG8Ctd3DneGVR2sZ4HIAXTr2Ny2+fwgtH0qoaVmOIjOq4 8pe/4/PPP8fE+ydhU4+6UebVGvPjpt3tPI6x96TMDRERPV2YTCIiIjpKzst47w0NPz/4Cxb2 frcaw8hnp/DBeyflyrC9iQ+u7CJ262/P9N0JtnPXcfv6Odgab3p41jfxM+w4YQcAFaevvI8z T2Ayieo7lrFHRETURkwmERERHbVdAFD2//eHe/exeuoNnCm5Mv3h7iW8e2cVu6t3cOnsWZw9 fxUfrR/8/eS5M9AefIIHjbJJ+gLuXj2L3/72Zbxy9jyu3vkIkVeew/Mvn8WFW3vprHXcH76E 8+fP48L5Ql13FwoFr945i+eeew7PPf8O7j28g0uv/AbPP/8bnL16r+IrPpJlLNzFO2d/g+ef ew7Pnf8Im8hj9V4El86fx4ULF3D+7FlciPxt/2uAtcZh/d5VnH/lN3ju+Xdw36AdZ8+ex4Xz 53H2QhgfLRwMknx/jNQve/3eVZyPfobt3W8Qff1s4Stuho+3qt9nU2N+6xLOn90r5wLCd77E eunfa8wJAKzfH95vw4Xz53Epcg8/6I1iz8T4Vs117TqNNRcbzZRlxEzsVc3Zy7/B8795GRdu PcRm/gd89M4r+M3zz+M3Z8P4W1kb68+RbJuIiIja7RdH3QAiIqJnmf7DXcQebOPE5Ss4V/gN fvzxMdQTJ2Ev2e709U/xF5zF7+9dwaffXoezsqATp/AC7uObn4C3z9SsDfevvYNbj6/gq39+ iNNqHqt3L+H1n4AzsU/x+ft2ADq+DL+Faz/fxDd/vwInAP3LMF679B60bz7FlQ++xf93Kozf XH6Aj+5fxuS3P+GF1bu49HoEt/72FhJv28yVce8ixj/7CRM/3cJbtwAgj4VPFnBq/Ct8eFoF sIl7l87inVtO/NftM7XHwTmFv78Qxm/e3S7r75fht3Bt9Tq++uo6Tqp77bgEfPV3vH8SOCnV H+OxbFS288pBm8a+TeBizSio32e5Nla3J//DHVx4awIL19+EU20wJ9o93Li2gDe++TuuOwHk f8Ct1yN48PMVfFAz9kyOb+Vc67XrPG047E3GRhNjbsRM7JXP2RVMff8T1IUoLrx1Fe+sXsSV m1/hp4nHuHvpddwYuYiLUxehNtpvDDpkrs9ERETW4Z1JREREh+zx3Xf2H8D9+rUHOHHzE3w1 fg6Fbz/9jM11QNM0c4VqGmzYrv/2t81PcPfBNt64cQOnVQBQcfK9G3ijtKrNzxD7ZBtvXLu8 f2Fqe/N9vKE8wN1PSu+DsePi+2/jpKrCdvoy3j4F/Ljwk/kyrl/BaZsK25kP8enUZdhhw1sT n+LmaXV/m7cun8bjbx6af7jx5meIfbKJ166/i5PqXjuu4/IL32P07kLFxnX603LZjcj2ud6Y f1LVHvX0e7h5463CHDSak583sZn/Gaur+t6HcWNqHJdP1Gm22fGtnGvTdVoYG5aWVY8db1+/ CKeqwn7uPbxx4mc8tl/B+6dtUG2ncfntU8j/sFCoU3q/ISIiOnq8M4mIiOiQnbiewLcf1Hoe Uh7bu7tQTD9XR4WCXexu5wHU+PDqAlZ37bjsLLntQ7XjxAsKNsu2yWN15ALOjx5stq2eADY3 ARTbrZzAyf2Lfg2aDcjv5lsoQ4XdXmz34/uIXruHhc3d4gcfYxcvmn/AsFF/cQInncDPqz9g E2cO7v6q159Wy5Yh0+e6Y/6jQXtsePOD9wv/udBgTk5ewc3L93D18ou4//s3cPntK3j/3Yv7 SaKWx8Boru1N1GlVbFhdVi3KieLzsgBAhV1TcOLkwWO6Nc0GmN1viIiIjgEmk4iIiI4VFZqm YDe/a/JzeexCgaJZ8XRnOy6P/x01vu1zoKQqpeqP5ssAAGzew3uXotBvfIWvPjgNFYD+t0t4 caRxq1tWtz9tZKbPLbWx/pxcnPwv/PTBQ3x272N8dOcqJkbPIPbV53jfqhxGVWjazdVpZWwc ZpxV9ttg4g72dsn9hoiI6Ijxa25ERETHyguw24Ht7UZP0s6j7L6Z7W3osOOEvU4y6eQZnFQ2 8Xi9pOz8Jh7/vFu1zU/r5fWv3ovg1peS74prpYzVh1jYPomLF08fXIPXzatVjINBO8r6i8dY XQdeOHna3J1D7SzbdJ9l26Nj4d49PNxE4znRf8CXP+iwnTyHKx9O4e///BTvad/g7n2jr1cV x7zVMTBVJ6yNDSvGvF75zbBi37O6TURERDUwmURERHSs2HDmtRPIP3588NWzIk3TgPwmtgGs 3nkdr98pueh+/CMeq6dw5sU6RdsuHt/aAAAgAElEQVQv4r03NDyIxfBDHii80epjLORLbpWw v4Ubl+14uL8NgPV7uDW6ihMnJV983koZJ07jRWUVDx6sFi6K8+v45JOFsuv8uuNg0I5v7v5l /y1d+pd38cnPv8cH11u89cPKsiX63Ex78gsxRO78AFVD4zl5fA/RyF8qnhek4eSJwleyDMe8 1TFoUGcVK2OjyTGXLr8ZTe43bW0TERFRDR1CCFHrj//6178Osy1Ex85zzz2Hzz77DOfOnTvq phA9Uy5cuAAA+Pzzz4+4JRZa/QjvhO9i4fufsP3Cizh54hxufjqOi0bXiKt3cPb1Bdz4MYGy l4npX2L40g082H0BqnIaNxPjuFi8/eOHW6/g0uMP8f3URdRN1+gLuHsjgjsPtqGdOIEz19+D ducafrz+z+Lb3IDC68lvYPTBJhS7AsCJt2/GcP2cDfr9CC7d+gTf/wSc+P1ljCVuIn/rHYx8 9j0e40X8/t0xfH77TaiyZZx6Ea/dSGDy7b2681j9WwThkc/wWDmBE/aTOGNfxcT9Tbx46jLG Pr+NN/PV43DqwVVcvfOg2K7XcGMyUfyqVKEdd77RoWrAdt6J927H8P6ZwijJ98dI/bLX75W0 6dSLOHH5Nj7/wCjJUr/P//v/uov/6/+QH/O99uRxGu+Pj+HK/kOIas8J9AV8FB3FvdU8VBXI b+dhf+Mmxj98s3CHUc3YMzG+lXPdqE6T41QrNi4aFiZRltGkG4yDUexdXq2MqytYvRbG3Yc/ Ydt+Cm/cmMKH6iiujj7Aj5sKXjx1GeOf38Y5tc4c1VJnXaCn269+9aujbgIRPcOYTCKq41lM JuUXPkL0Vgwf//gCLt+4if/tzE/4P0fv4i8/nsREyauJN7+8g1uxj7GgvoHrN8dwBfdKPncZ /8snf8H/c+IEFOzi8TcPsPniWzhjB7C9iu3Ln+LT0w/K6hn7YO/iIY+H4Zdx6ecP8c9Pr+xf UFS262D7Gn8/9QkujPyMkycO7rjYXv0G3zw+hdj3n+PKzyXbv3Vy/xEWu6s/QvvwW4xXTfk6 7p5/C6sf/tPgbxbb/BLDkY+xbbdjdzOP126O4/3TVjwH58nxVCaTTNHxMPI6oiem9p/nUn/z +7j6+l2cSXyO642eb6PryNtsJWU+RPi372J3/CdMXXy24oyI6EnGZBIRHSUmk4jqeBaTSQCA ++/g+dFz+P7b63ACyN9/B7+PLmBbu4LPvvoQe3kN/d5VRF+YwuSblZ97DZ9EFnB5/H04sY67 53+Phx/8v0hcBLBwC5HV6xi/Yq+qp1DofYQv3cI3P2q4/v3fcd1Zu1112/1wGJHtDzG+d3Gs 38fV165h++Y3+HQvI2ZQnn5/GB/bb6P65oHDSiZt4t6l1/HgvW8wddEGrN/F+bdW8eH34zj3 DF3nM5kEIL+Ke9ciWLg8hfG6txms4u6lKNavTeD2m41vR3gYOYu7r32KRPHukM37V3E2omDi +0m8KfktNiIiOnpMJhHRUeIzk4hIgoozNxO4oXyMdyNfovFjQE/jg/H3jRM+Zz4sJJJq2Pzs E+CDKdw49SM++viH5pt87vZBIgnruPdeBA/PTGDiimGrAACrd67i45NGiSTgh3sj+NvjTTyM hRGO3MGXlQ+z2ZNv8eGnm/dxb+EU3nqjeFXvfAPnlPu495CPVH3mqCdxZepTjLymNdjwBbz7 8adSiSQAOPHGa9i9+w4uXLqECxfO4tJdDR9+Ps5EEhERERFJ+8VRN4CInhDaKXyQmMCPZ9/D ex99g0/fr52Uad46Prmv4crUaZzKn8PIyMd4eLP1O3JW715FdP0i/vLVxerncDz+CDfeeQgF wO7jTbx20biM01dG8PZHC1i9MVnnzqRNfHTpZcROfY5/3j4DYB333nkLtxYMEkGqHZenvq1+ /fPjVTxW7Dh4IZeGk/ZtLDzehsF7tempp8LWMMljk9jmgPPibXxaI86JiIiIiGQwmURE8uwX MZFYwOuX3sWt01/hhtXl//AxHp68gusqgIvv4Y0b1/DxgzGca+E5LvmFW7g6uov3PhuD4fNL T7yPWKLwNbf1v93BgmKwjTQ7rkx8jjPqXobIiSuJf+JKK0USEREREREdM0wmEZEp6pkP8Zex H/H61Ws4+V4eqPEGZ/PyePjxA2xubyMSuVf4zQt5PPj4PvSLb9d/O1Ut+kNEr34MbeQrfCjx AGvn2x8YfzXPBNV5Bqf3/6+JO5NOnMSJ3QfYzKN4I9I2Vjc1nDjR6KtO9GTTsbmpwm6vF6c6 1jdVOOtuQ0RERETUfnxmEhGZ5rzyMabe+AGR0QXsWlVo/gHubV9HYmoc4+OFn8TUdZx4eBef rNf+2PpHVzG8YPSXTdy/cRX3T8Uw9X7J661+uItb9+s89enLCML3jZ5PpEJRi89DWv0b7hkl iABsLvwN91f3/la4M+m///u/q3/+aZBIAgD7G7h86kd89qDYxvUHeLj7Bq48S0/fPu5WP8I7 51/Bb597Ds//9hWcPXsWZ8++gpf/f/buLqbNLM/3/S8vJbt2ithqqeJJl2LfVDwzKvDWKGWN RuC+ICCNwCdJA5pp8FSPgGkd43OOZFBLgZGOgIstYEsbmC2NibQFzNHIQZoOuRmTi4bkxlRJ W66eLdmlUbczasku1Uhm39hD97Q9SsK54CW82PBAHAzm+5GQ2l6P1/N/1uPQ4ldrraf2jlqC YSV3fTWi/k9VP5ks+VqSlI8r1NalsfjbD2ZjYU2GY/v2J1vTSl+b/JFSG3ZVn+LjICVDjfq0 MaRk0U9VSlbRyTbV1zeqpaVR9Y0PtXzUBnP5ZT1svKNPP76ultlzel/f4zWUuv/l9r7Pcxa/ x6c1tgCA6sXMJAB75OOzGpxLqJDOaGTytv7a/VJ/G4oppkGFLCMKeKySrPJML2g02aZYic+N DzTLpoyWJ0f0JF3Q2lxQs7Zx9brNB4//rxv6z/9rTqsZj2Ipn7wOScorFkvKrK811hfUf+qr 0/+c3zo+mNT2PJ1cPKUbriJ12+fUt5iTpWFRwc7FtxeYSarga997/K7+lI4q11VsZGzytLsU nvKr21RQ03hHkWMyWhkb1GSdU95RV5F2IxzqnR9XMtgn/4pNhUxOHfNTF+pJbmees1cLL1wK fnpX0cCCvhzYCitTYXXe7VNL7oa+nm82OJsuq+Vgl540PNWLXTtg52IhjYV9ave5d/XjVO9c v2J3OzXpfKEBZ7H+qkvxcZBu1HWoXXXlmxhZDskpBcey6v36hQKOvOLhsApH/bs1N2vihU3m O3dVNBM/D97jNZS6/+X2vs9zFr/HpzW2AIDqRZgEYA+zq1fTT3s1vfNOs6Y9gSJHOhV49s0h n5Mkm5oH5tU8MG/gPP+XgnuPkLt3QV/2vn2n8//Y3/9uB+v+tljeU/L4ozl7n+pF72FH2OR7 +i/vvkeSzauJBXZIPncc7eppGtTS0mPF1KxmI59JTmlkqU5D4waTIWuzBnwjujv8RD0LJ1z+ WQWsnoAmSm6EXyGpjNZkk90mSWa5fIf+sgDO5vcYAACDWOYGAEC5FCTJ+C7u8XBEybomuXel QvFQm7omkyokJ9VWX6/6xm7N7lrq6fS4ZVlZ1MpR61OyMYW66/Xpp7W6U9+o7slZBe9c18e1 9WoZ3p5DklLkYZsaGxvV0rh5rlBss+PkZL2uX7+u6x93KhydVNudW/r441uq7w7vW5ZjsI9Y SJ31t/Tx9eu63jirjPJKhoNqa2xUS0uLGuvr1RJ8srNMsNQ4pMLdarxzS9c/7lSkSB319Y1q aWxUfYtfs7G3g2T8eoo5vO9UuFuNg0vKFVY1eLd+c4lb8ZWwe+9LY4uC4aQOHlp6TCUpFXm4 M24tjY1qC4YVz+767HCbGuu3x7VF/sllpQz0bXiMjryGw++tkfMc9u/g8Ovf72Tfs5P0Vcxx vscHxqX2lj6+VauW4agy+bhmO+/o1scf61a9X0/21Hj498VoTQAAHAczkwAAKINsPKSplZzs 7T5tTzbwTH+j5+a3a532vs4qkUjLbHfKtqsfV+CpHqten4d9evpl4OCm8PY63VBEqy+ljmL7 bm31Henr1HDap+ffjMplzisZatPdl5J76qme9dokZbXsb1Xf2pBWX/jkkJRd9quhrUeW1afy DXypf6vz61b7imYj7Xr05UvdSIbUdjeo4SetWuiwHq+PsFfTSy8183JYrcOSlFdsMaa66e0N 8jMKt9Wrc9ihX0y4S4+DY14vbvh1qyu353qX/a3qSwb0/HlATvN2HW3S8xfqdUpOQ9dTfCyP 6tvhe1vT+JcLKj2vsNh96VJLuiDn/vOVGlNLWP19MTWtvlDAISkf1/DdoFbWfHJZD9aaj0+q pXVGsUCzHOby3POjr+Hwe2vkXpS8/9nDrr/YmJ/we1bU4X0Vc5zv8d5x8Wn+65cyxwbV0tqt zqRXvqHnejmTVqjtrvpHvPLOe2U+6vtS5IKOd80AABTHzCQAAE4oHerc2YD7bt+K7EOLej7t 0U58ZDZrz7Y5e16vKZOSLJZjPqnPYpFVOWUyh0yHyCwqtJJTU3+/Nh9kaJazp19Nu0+VWdLU Yk5Nfe07f0xam3vVZFpRaHH3PBSbvL0dcprNsrra1VEnJWIvj99HwCeX1Syre1RP59tlk1Wt M081tPOkRZta211Kr0aPvyFxZklTixk1BLrkNG/XEVD7ja81Ftq/k88h1/POfR9VZ7H70rd3 T7SjxnQto0x+Tcnk1swTs0v989Nqt2/2v79Ws6tHQ/2tm32V5Z4buAbD9/aY90I6/PqLKuP3 rKx9HcamjoBXDrNZNk+PmuxrStt86nVZZba61N5Rp3w8tnlOw/cUAIDyYmYSAAAnZN+9Afex 5ZUrFGQ69ubqZplUUCGXl1Tiw8mYkgWb2h27pmqYbbLfMCmz55i8kiMtahx7e1jObJcyGWl7 nonJLufOH+oWWaxSvpB/hz7Mstm26k5HNNgXViyz9VzIXFoF3dbuOUeGFLte2eV0SGvJuDJy v539ddj1vGvfJ6nzuPfF6dNQe1jd7bcV+bxJ7R0+9XZ5N8OjWKJIrVY1D2zt3xQr1z0/4hok Y/f2uPdCOvz6SynX96zcfZVism/tvSVJZtksJtmdb7fptlis0nH/DQIAUGaESQAAVIRZFotJ hXzhmJ/LqyCTTJZyPOLPpvbpFyqxQuetXac6uCPU8fuQJGXC6mkbVLb/uZ4PuGSWlH3Sptsj R1f9zg69nrPg8DH1PvqFXg5EtRSe0+xkt2bG3Jp6/kzGtvwuxz0/wnHu7bHPYyt9/cVyk3J+ z07zO7v/30uRwXn7m8PgPQUAoIxY5gYAQEXckM0m5XJH7aSd37u5cS6nrGyy2w4Jk5xuOU0Z pVO7+s5nlF4rHDjmZWrv+ZPhoIaXj6qpDH0ko4rlnPJ6XW//bj40V8sX2ah6bx17rldpJVPS DafL+Myh9913Oe5LNq7leFZWp0e+0Xm9+OapeiyrCkWSJWrNKhYOK5ox0He5ruHY99aIrft/ 2PUXU87vWVmu65D+T6Ic97TcNQEALgTCJAAAKsIqd4Nd+XR67/Igbe2jlM8oJyk5eVd3J3f9 oZxOKG2uk/v2IV3bvOppsmhlakrxvLT5FKo5xfK7pjfYWtXfblN05xhJqbCGx5KyO0ttRr3/ PO/Qh92l26akVla2ngSWT2lxMbbnb/NDx6FIHauhxztP1souh7S49rkGAu84XaOcfRe7L3NT Wtm9RuqoMU2HNRh8vG+PHouc9htFa83HphScjMtsMdB3ua7BwL01ouj9P+z6iynn9+yE12W4 /5M44T19rzUBAC6ESxsbGxulGtfX10+zFuDMuX79upaWluTxeI4+GEDZtLS0SJKePXtW4UqK SM6q0x9S7OuXyt24Lafdo6Gn0/Ia/Ft8b1+Tqr8bU39iQXseJpZd1sO2fq0UbshscmloYVre rSkw8eE7akuP6ut5rw49ZTamUH9Qkys5Wex2uQM9skz2KRH4ZutpbtLmI8X7NbaSkclmkuRQ x9CUAh6rspGg2oYX9fVLyf55u8YXhpQf7tTI0tdK67Y+7xrXs4lmmY32UXdbDf0LetSxfe68 kk+C8o8sKW2yy25zym1LaiaS0e26do0/m1Bz/uA41K10q3tyZauuBvU/Wtha3rRZx+RqVmaL lMs71DMxpV735igZv55iDu87Fd5VU91t2dsn9GygRNC0577ckKvdJ0u4X+FCndzt03o26j70 vigb0+zgmMLJvMxmKZ/Ly9Y0pOnR5q1ZUntrzcul3ulx+XY2FSrDPT/yGuoOvbf/7/9d0H// L0bOU+Tfgemo69/vZN8zb9HODPRV7AtU5DqKfY/bk/vH36dkn1+h6EvlbHVq6p/XqHlM3WMr SmRMul3XrulnE/KYD/m+lHLI7xicHzU1NZUuAcAFRpgEHIIwCaiMMx0mlVVW0eBdDdrnd/Zg OfzwiLrvhuReeKbAUfvqZrPKW627+ozK/2mXCtMvNe8tx35LAIBKIkwCUEkscwMAoGKs8owv KJAY1GBk/2K3/ZIK9czpxvj80UGSpOhIq7qfvO0zE5nTilrV1UCQBAAAgHfD09wAAKgks1O+ +adqPXKv3Bvqmnsqq8HldPamBhUmO9Xy2Lq1N4pbo8/G1XyS5XgAAADALoRJAABUnNlASGQ1 HCRJksM7oafed6kJAAAAKI5lbgAAAAAAADCMMAkAAAAAAACGESYBAAAAAADAMMIkAAAAAAAA GEaYBAAAAAAAAMMIkwAAAAAAAGAYYRIAAAAAAAAMI0wCAAAAAACAYVcrXQBw1g0NDclisVS6 DBzT69ev9erVK5lMpkqXghP45ptvVFtbW+kyAAAAABRBmAQcYmhoqNIl4IQSiYQikYh++tOf 6oMPPqh0OTimhoYG2e32SpcBAAAAoIhLGxsbG6Ua19fXT7MWACibx48fy+/3K5PJ6MMPP6x0 OQAAAGVVU1NT6RIAXGDsmQQAAAAAAADDCJMAAAAAAABgGGESAAAAAAAADCNMAgAAAAAAgGGE SQAAAAAAADCMMAkAAAAAAACGESYBAAAAAADAMMIkAAAAAAAAGEaYBAAAAAAAAMMIkwAAAAAA AGAYYRIAAAAAAAAMI0wCAAAAAACAYYRJAAAAAAAAMOxqpQsAgHeVSqX07bff7nkvmUxKkr76 6iuZTKY9bbW1tbJaradWHwAAAABUk0sbGxsbpRrX19dPsxYAOJFwOKy+vj7Dx6fTacIkAABw rtXU1FS6BAAXGDOTAJx7ra2tho67fPmy/vRP/5QgCQAAAADeAXsmATj3rFarfvSjH+ny5cN/ pb1580Z/8Rd/cUpVAQAAAEB1IkwCUBXu3bunN2/eHHrMtWvX5PV6T6kiAAAAAKhOhEkAqoLX 69W1a9dKtl+9elX3798/xYoAAAAAoDoRJgGoGvfv39fVq8W3gnv16hWzkgAAAACgDAiTAFQN r9erV69eFW376KOPCJMAAAAAoAwIkwBUDa/Xq9/7vd878P7ly5f1xRdfVKAiAAAAAKg+hEkA qsoPf/jDA091e/PmjXw+X4UqAgAAAIDqQpgEoKr4fL4DT3W7efOmXC5XhSoCAAAAgOpCmASg qrhcLt28eXPn9eXLl/XgwYMKVgQAAAAA1YUwCUDVefDgwc5SN5a4AQAAAEB5ESYBqDqBQGBn qdsf/uEfssQNAAAAAMqIMAlA1XE4HPr93/99SdJf/uVfVrgaAAAAAKgulzY2NjZKNa6vr59m LcCZ09raWukScELfffedfv3rX8vtdstsNle6HJxAbW2tJiYmKl0GAABnUk1NTaVLAHCBXa10 AcBZFo1GVVdXJ4vFUulScEzf+973lMlkZDKZdEhmjjMqkUhw3wAAAIAzijAJOML4+Lg8Hk+l y8AJRKNR7t051dLSUukSAAAAAJTAnkkAqhZBEgAAAACUH2ESAAAAAAAADCNMAgAAAAAAgGGE SQAAAAAAADCMMAkAAAAAAACGESYBAAAAAADAMMIkAAAAAAAAGEaYBAAAAAAAAMMIkwAAAAAA AGAYYRIAAAAAAAAMI0wCAAAAAACAYYRJAAAAAAAAMIwwCQAAAAAAAIYRJgEAAAAAAMAwwiQA AAAAAAAYRpgEAAAAAAAAwwiTAAAAAAAAYBhhEgAAAAAAAAwjTAKA05BPKRZLFW/LxBVL5k+3 HgAAAAA4IcIkAIbkY7MKttTq+q1GdU8u62U0JH9Lra7falN4V0aSWZ6Uv6VWd9qCmo3l933u b/X/1NerrbNTnZ1tqr91XZ82dqqzs1OdLXfUMps6cJ7M2woU9X+qj9vCu947WNfutqLty37d qW/bPOfWT8udW7r+cYtmU/uO9/vl3/rpbqxXMHrEuPj98vs71dLYpofLuyrJxxXqHlHSYpOU Uqixdm9fNpsyk90ajmbf4Q4BAAAAwOm4tLGxsVGqcX19/TRrAc6c69eva2lpSR6Pp9KlnA2R Tn085tHXXwbkkJSPdOrzwZhyFp+Wno/KZd48LBvu1uCNeT1q3v+5Bi0GY2qf7pVDKYUaP1d0 4H9rwSspNqxgMqBpn+3AeTY7jcjfNqzVhEWBr18o4Chd16F1Rx8qmBvVtNe80293Q59yQ6t6 6nOU7C8beag524QG3AbGJRrU510ZjSQW1GGVkpONCprn9Szg0GaY1Krk6Dea3v21yoTV1hbX 0PMJuc3HuitVqaWlRZL07NmzClcCAMDZVFNTU+kSAFxgzEwC8A7Mcg8tqN80p67gso6eV+PS wHRv8cDHPboZJJWQWVqUBubVX5fQ7Fz85CV7Jt4GSUop3BNU1D2jGV/RqiRJycluzTlLBElF mJ11sueTSqQlKa5wuCB3w2b/8fCInqQzik755Q9OamcCk61BraYlhWMnvTAAAAAAOB2ESQDe jaVOAwszcq/0qGe2xJ5A7yylxYhFviaX2gMerS3OKVqGLYaSoW4Npryan/LqQIyVnlX/1jK4 wcXjXVcmuqKEza0mp6RsUom0TU77ZpvLN6IOu02e/kd6ND2g5p0T22Rz5BRPvK8xBAAAAIDy uFrpAgBUAZtXMwsx3W3r0rDrufrL3X98TlGnTwGzJG+Pmvr7NLcyLo/35OvB8rFhdY8V1LM0 Lo+1yAH2Xk0tbC5bSz2ZVMx0RIeZJxoJJmVRTrm8UzNPh+QxS8rllJVJpiNLNctkMimXKZzk cgAAAADg1BAmASgLs3tUj8cTutvdJ2dPXrpRrp7zis6tKJPLKRgMb75zI6+VuYiy3g4Vy4GO lI1qsHtOlpHnGnUdHUg5OgaKL83bzdahkekiezaZzLKqoEJe0lGnKhRksR2VWgEAAABAZbHM DUDZOHxzmm+KKzgWU9nm1+RXFM4FtDA/renpzZ+F+YDs0ZAOW32Wmu3Ww6L7D2UU6e9WpG5K 873Ot2/HQxqOHLLr03JQ/sgJ1tZZnbLbMsqsbb9hlsmcV16Skk8Ujm33mdFaxiTH7dL7RgEA AADAWcDMJACG5OOzGpxLqJDOaGTytv7a/VJ/G4oppkGFLCMKeKySrPJML2g02aZYic+NDzTL poyWJ0f0JF3Q2lxQs7Zx9W49wmzP8f91Q//5f81pNeNRLOWT1yFJecViSZn1tcb6gvpPfXX6 n/NbxweTsmydNxdP6YarSN32OfUt5mRpWFSwc/HtBWaSKvja9x6/qz+lo8p1HTEuQZMC4737 nsZWp/amvKbiWQ04rZJs8rS7FJ7yq9tUUNN4x3ZHWsl41M6j3AAAAACccZc2NjY2SjWur6+f Zi3AmXP9+nUtLS3J4/EcfTBQSiYif19UvrmJ4vszKa/4ZJfGbFNaOOSpchdJS0uLJOnZs2cV rgQAgLOppqam0iUAuMBY5gYA75vNq0czTUqvJou3Z6JKOMc1T5AEAAAA4BxgmRsAnAZbs3ze E7QBAAAAwBnDzCQAAAAAAAAYRpgEAAAAAAAAwwiTAAAAAAAAYBhhEgAAAAAAAAwjTAIAAAAA AIBhhEkAAAAAAAAwjDAJAAAAAAAAhhEmAQAAAAAAwDDCJAAAAAAAABhGmAQAAAAAAADDCJMA AAAAAABgGGESAAAAAAAADCNMAgAAAAAAgGGESQAAAAAAADCMMAkAAAAAAACGESYBAAAAAADA MMIkAAAAAAAAGEaYBAAAAAAAAMOuVroA4KxrbW2tdAnAhdTQ0FDpEgAAAAAUQZgEHGJoaKjS JeCEEomEIpGIfvrTn+qDDz6odDk4AbvdXukSAAAAABRxaWNjY6NU4/r6+mnWAgBl8/jxY/n9 fmUyGX344YeVLgcAAKCsampqKl0CgAuMPZMAAAAAAABgGGESAAAAAAAADCNMAgAAAAAAgGGE SQAAAAAAADCMMAkAAAAAAACGESYBAAAAAADAMMIkAAAAAAAAGEaYBAAAAAAAAMMIkwAAAAAA AGAYYRIAAAAAAAAMI0wCAAAAAACAYYRJAAAAAAAAMIwwCQAAAAAAAIZdrXQBAPCuUqmUvv32 2z3vJZNJSdJXX30lk8m0p622tlZWq/XU6gMAAACAanJpY2Njo1Tj+vr6adYCACcSDofV19dn +Ph0Ok2YBAAAzrWamppKlwDgAmNmEoBzr7W11dBxly9f1p/92Z8RJAEAAADAO2DPJADnntVq VVdXly5fPvxX2ps3b3Tv3r1TqgoAAAAAqhNhEoCq4PV69ebNm0OPuXbtmrxe7ylVBAAAAADV iTAJQFXwer366KOPSrZfvXpV9+/fP8WKAAAAAKA6ESYBqBr37t3T1avFt4J79eoVs5IAAAAA oAwIkwBUDa/Xq1evXhVtu3nzJmESAAAAAJQBYRKAquH1enXz5s0D71++fFkPHjyoQEUAAAAA UH0IkwBUlQcPHhx4qtubN2/k8/kqVBEAAAAAVBfCJABVxefzHXiq2yeffCKXy1WhigAAAACg uhAmAagqLpdLn3zyyc7rK6oCfzEAACAASURBVFeu6N69exWsCAAAAACqC2ESgKpz7949Xbly RZL0+vVrlrgBAAAAQBkRJgGoOoFAQK9fv5YkffbZZyxxAwAAAIAyIkwCUHUcDoc+++wzSdIX X3xR4WoAAAAAoLpc2tjY2CjVuL6+fpq1AGdOa2trpUvACX333Xf69a9/LbfbLbPZXOlycAK1 tbWamJiodBkAAJxJNTU1lS4BwAV2tdIFAGdZNBpVXV2dLBZLpUvBMX3ve99TJpORyWTSIZk5 zqhEIsF9AwAAAM4owiTgCOPj4/J4PJUuAycQjUa5d+dUS0tLpUsAAAAAUAJ7JgGoWgRJAAAA AFB+hEkAAAAAAAAwjDAJAAAAAAAAhhEmAQAAAAAAwDDCJAAAAAAAABhGmAQAAAAAAADDCJMA AAAAAABgGGESAAAAAAAADCNMAgAAAAAAgGGESQAAAAAAADCMMAkAAAAAAACGESYBAAAAAADA MMIkAAAAAAAAGEaYBAAAAAAAAMMIkwAAAAAAAGAYYRIAAAAAAAAMI0wCAAAAAACAYYRJAAAA AAAAMIwwCQCqUT6lWCxVvC0TVyyZP916AAAAAFSNq5UuAEDlxcNBDY4tyjb+rea979JTSqHG ViVHv9G05/ifzsdmNTg8pbnEDbW3OmXabkjHlOt5rnnH4tv2/nZ9tPhY39ntMqmg9OqKMrdb 5bZJyiWVa3+qx84lDY6F9Djh1MzqU/kcm91llic1PDWnmLlJgaFx+RQuet5CMiHL6Jea9kiZ 6KQGp2Iy3bBJymhtTarrm9Zos22zzyPajyMbm1TPWEK3b5uUXnNrdL5XzpJjlFM6WVDd0Iwm ts+VjyvUPSXL6Izcxe6JzabMcLeGfTMa9ViPXR8AAACAi40wCYBcvhH1LC5qqcJ1mN29mg6s KDzm0cijgBzbDdFhPcyb97YPNGgxbdZPp3vlUEqhxs8VHVjQgldSbFjBpFlWT0DTuahWB2Ma 7BpW3fNRucySrXlA42sJDd6YVq9bkoqfNxt5qDmzpHxUw90RuZ+/UMCx3datrkROarYd3X5M sdmQ8u1fasJnUz6fl/mIMcpHg/q8Kyh3YkEdVikZCirimdczp7nEGWzyjno11zam2PMJuUsd BgAAAABFsMwNOKdSkYfq7vQr+DCo7k6/ZuN5KR/XbNsdfXyrXt3huKSMlodbVHunTbPxrzXb 3anu4EMF/Z3q9IdVfKVTXvHZbjV++qmCUUmKK9zdqE9rg4pp83WpfuLhET1JZxSd8ssfnNRy 5pBaDcqGu+XPj2qieX/i4dLAdO/bwGk396imfdshjlnuoQX1m+bUFVxW1uB5k5PdmnNOaMAt STkVCjkl028/bfXO6HFge77QUe0HZZYfqnPXmIS3BjH55KFmVnNKhgflD84qqaOTHrOzTvZ8 Uom0JMUVDhfkbtgcmVL3RLYGtZqWFI4ZHBAAAAAA2MLMJOA8Ss2qbzCn/q8fqdksKfZQd7qH 5f7FhHrnRrXyeUgNDS5JktvtVIN7RL2uNUXaRzXvdUrKKxqs1+Biq5769i9zMsvVO6KOcKuS kiSXfCMdmm1N7rTbSvTj8o2oYzamZP+jt0uqDqnVVer60rPq74xuLjdLJ2UZecfxstRpYGFG ifoe9cyu6mlv0Qhqz3kL6Ywatpf8mZvUPzSntrY6Rd2t8rZ75fU2bS6pM9K+X2pW3X1p9Xy9 OZMoH3uo+s5hOb+ckLtjQn0ri5rxTOnRgXtTXCa6ooTNrSGnpGxSibRN7fbNtqL3RJJkk82R UziRkjwlxgMAAAAAiiBMAs6h7OqSYvm8FgeDW0vTcrJZLEpnJZe1SYGmQQ0uJtU7YNFSxCTf 9GYoYcuMye8vyGyWcvGcUpa0pOPumXPjWP0cXmuJU9h7NbWwtYRreVJz5djWx+bVzEJMd9u6 NOx6rv4jzpt6MqnYzqZNZrkCT/UvXUlFV1YUWRxT52BQrvFnetrrNNC+V3Z1STF7k2a2rstc 55FrbViRpOQumbDtk3mikWBSFuWUyzs183RIHrOkXE5ZmWQ6ckKTWSaTSblMweAJAQAAAGAT YRJwXtm8Gpreta9QPq/NFVFmeQLtynfPKuZ1aMXWoXmzlI/0qzNk19MvJ+QyS8nJmDpzh52g +FK04/dzWK1HMzcPKGDs0KP7co/q8XhCd7v75OzJSzdKH+voGNi1hC6rZLIgp9MpT4dTno6A hp50qm5kVrHeCbmPbH8PbB0a2T2m20xmWVVQIa+jx7hQkMVmOuIgAAAAANiLPZOAc8ja0Cp3 ekWr2/vfZJ+ouy2k7YVocvnksywq6I/K7duMMvK5nHIWmyxmScorlcwc7HiHRTesBaUzm3sA ZRMxpbeypcP7Mctkzm/GUMknCsfyR9d6yhy+Oc03xRUci+nIOTnLQfkjeUkxTfonFdudr5nN Mt1wbOVRR7XvtTkmUcW2tljKJ6KKW5rkLb3FknFWp+y2jDJrO4UcuCebMlrLmOS4ffwNwgEA AABcbMxMAs4jR6/mZ5IK9nUrdtui/JrUND6ut1mEU75ep6bCTWrfetPaPqTRxaC62uJy283K JaW1xJRC3ik1JEc0l8wrPfdQT5wT6nBa1dTfo7nhHvljt+W0mWQrRDU5uazpQOl+Am6bPO0u haf86jYV1DTeYaDWt/LxWQ3OJVRIZzQSlHpGAtr95Po97ZO3NT7QLJsyWp4c0ZN0QWtzQc3a xtW79XiybDSkkVBMMQ0qZBlRwGOVZJVnekGjyTbFip43Kcv2CdNR5bo2x9PrntNYV7fsdouU zyi9ZtPoo56tmUFHtRe5f9NJBfv8WrWblUvnNfB4Wm7z5mblM7Gc4ulBBRXQuM+1Z4LR3lpN Coz37nsaW53am/Kaimc14LRKKnJPNjvSSsajdh7lBgAAAOCYLm1sbGyUalxfXz/NWoAz5/r1 61paWpLH4zn6YOCsyETk74vKNzexJ4x7K6/4ZJfGbFNa8J3NzbdbWlokSc+ePatwJQAAnE01 NTWVLgHABcYyNwCoNjavHs00Kb1aYjFhJqqEc1zzZzRIAgAAAHC2scwNAKqRrVk+7wnaAAAA AOAIzEwCAAAAAACAYYRJAAAAAAAAMIwwCQAAAAAAAIYRJgEAAAAAAMAwwiQAAAAAAAAYRpgE AAAAAAAAwwiTAAAAAAAAYBhhEgAAAAAAAAwjTAIAAAAAAIBhhEkAAAAAAAAwjDAJAAAAAAAA hhEmAQAAAAAAwDDCJAAAAAAAABhGmAQAAAAAAADDCJMAAAAAAABgGGESAAAAAAAADCNMAgAA AAAAgGGESQAAAAAAADDsaqULAM661tbWSpcAXEgNDQ2VLgEAAABAEYRJwCGGhoYqXQJOKJFI KBKJ6Kc//ak++OCDSpeDE7Db7ZUuAQAAAEARlzY2NjZKNa6vr59mLQBQNo8fP5bf71cmk9GH H35Y6XIAAADKqqamptIlALjA2DMJAAAAAAAAhhEmAQAAAAAAwDDCJAAAAAAAABhGmAQAAAAA AADDCJMAAAAAAABgGGESAAAAAAAADCNMAgAAAAAAgGGESQAAAAAAADCMMAkAAAAAAACGESYB AAAAAADAMMIkAAAAAAAAGEaYBAAAAAAAAMMIkwAAAAAAAGDY1UoXAADvKpVK6dtvv93zXjKZ lCR99dVXMplMe9pqa2tltVpPrT4AAAAAqCaXNjY2Nko1rq+vn2YtAHAi4XBYfX19ho9Pp9OE SQAA4FyrqampdAkALjCWuQE491pbW3Xt2rUjj7t06ZJ+9KMfESQBAAAAwDsgTAJw7lmtVt2/ f1+XLx/+K21jY0P37t07paoAAAAAoDoRJgGoCl6vV2/evDn0mGvXrsnr9Z5SRQAAAABQnQiT AFQFr9erjz76qGT71atXdf/+/VOsCAAAAACqE2ESgKpx7949Xb1a/CGVr169YlYSAAAAAJQB YRKAquHz+fTq1auibTdv3iRMAgAAAIAyIEwCUDU8Ho9u3rx54P3Lly/rwYMHFagIAAAAAKoP YRKAqvLgwYMDT3V78+aNfD5fhSoCAAAAgOpCmASgqvh8vgNPdfvkk0/kcrkqVBEAAAAAVBfC JABVxeVy6ZNPPtl5feXKFd27d6+CFQEAAABAdSFMAlB1fvzjH+vKlSuSpNevXysQCFS4IgAA AACoHoRJAKpOV1eXXr9+LUn67LPP5HA4KlwRAAAAAFQPwiQAVcfhcOizzz6TJH3xxRcVrgYA AAAAqsvVShcAAOWwuroqSYpGo5Kk3/3ud5Kkn//858rlcrJaraqrq9P169fZjBsAAAAA3gFh EoBzYX9YtP/1bnV1dfre976nTCaj//iP/1AoFFIul9tzzHa4ZLFYVFdXR9gEAAAAAAZd2tjY 2CjVuL6+fpq1ALjAjhsW7Q+Bdr/eFo/H9wRD8XhcuVxOiURCuVzuwOvdCJsAAMBZVlNTU+kS AFxghEkATsX7CIvKjbAJAACcF4RJACqJMAlAWZyHsOhdETYBAICzgjAJQCURJgEw5CKERe+K sAkAAJwWwiQAlUSYBEASYdFpIGwCAADlQpgEoJIIk4ALgrDo7CNsAgAARhEmAagkwiSgShAW VT/CJgAAsI0wCUAlESYB5wRhEY5C2AQAwMVBmASgkgiTgDOCsAjvG2ETAADVgzAJQCURJgGn hLAIZx1hEwAA5wdhEoBKIkwCyoSwCNWOsAkAgLODMAlAJREmAQYRFgGHI2wCAOD0ECYBqCTC JGALYRHwfhE2AQBQPoRJACqJMAkXBmERcLYRNgEAYBxhEoBKIkxC1SAsAqobYRMAAG8RJgGo JMIknBuERQAOQ9gEALhICJMAVBJhEs4MwiIA7xNhEwCgmhAmAagkwiScGsIiAGcZYRMA4Dwh TAJQSYRJKBvCIgDVjLAJAHCWECYBqCTCJBhGWAQApRE2AQBOE2ESgEoiTMIOwqLzLxOd1OBU TKYbNkkZra1JdX3TGm1O62F9UC/tdplUUHp1RZnbrXLbJOWSyrU/1bNeh6SsYrMjCq3mZTJJ KuSUs3g1NOKTyyrlY7MaHJ7SXOKG2ludMimndLKguqEZTTTbjtfeP6S/dr/UfxsL6XHCqZnV p/I5tq5jeVLDU3OKmZsUGBpXr9u8tzaLWeZ8Tuk16XZ7QEM+t4p/63Z/RlIup7W8RQ2+IQW8 DulAvQXlkikVPKOaG/XIqn3X3N+ujxYf67tDxvGpa2Vfn5sKyYQso19q3Hzccw5pfKBZtiPu TTYa0qDhsUQlEDYBAMqJMAlAJREmXSCERVUuH5W/dliu5y8U2AoSspFudSWH9Gwgr8lgTO3T vXIopVDj54oO/G8teCXFhhVMBjTtsyj28K78uRE9f9S8E85knnSrZcqu+eejcpklRTr18ZhH X38ZkENSPhrU510ZjSQW1GE9QXukU58PxpSz+LS0fQ5J2XC3Bm/M61GzJOUVfXhXwX215ePD aumTpr8c1cE/r/PFryfSrbuhBj1/1iubDtaj7BO13R7R7WffaMK99aGdYxq0eOQ42g72KSkb eag524QG3Mc9Z0COUtey794YG0ucVYRNAIDjIEwCUElXK10AyuekYVFDQwNhUVXIqVDIKZnO So7Ne2j1zuhxfjNRGJgu8Qeme1TTbkmpWT2cM6n36+Y9s3xsHUPyTd3VyGK/nvoOfjfMzjrZ 81El0toMi47ZLpnlHlpQ3WybuoINWn3UfHCWUSqs4TmTAvtqM7v6NT2elr1Yt6mwHhb5jM07 ohlTTpaigyEpt6as8irkizW6jh7HIpKT3Yp45zXgPMk5tXMtR98bA2OJM2s7BPJ4PEXbi4VN 2WxWoVCIsAkAAACnijDpnMlms5qZmZFEWIR9zE3qH5pTW1udou5Wedu98nqbNpdgGZBPrCph dmrUsb/FLqczr1A0IfkO/pGbia4oYXNrqERQclS7JMlSp4GFGSXqe9Qzu6qnvXuLyCdWlbA4 5TxQm1UuT/Hvc+nPOOTZP0Mn/UQj/ri0llA0lpbFO65A8b/njUvPqr8zKpOkQjqjBu/Jz3ms e3PEWOL8et9hU19f33u/BgAAAFQHwqRzJpFIaGxs7MD7DodDdrtdXq9XdXV1unXrlhwO/oi8 WMxyBZ7qX7qSiq6sKLI4ps7BoFzjz/S097AkZxfT0YdIkjJPNBJMyqKccnmnZp4OyWM+Rnsx Nq9mFmK629alYddz9e9vL+wrITKssUhayaTkm5/f2SPoROwdGnkUkENJhToHpf52GRyxQ/rs 1dTC5jK21JNJxfaP7XHPafTeSEePJapSqbBp+z88bIdK0WhU2Wx25z9ERCIRSSJMAgAAgGGE SeeMx+PR6upq0X014vH4gVlK2yHT9s/2a8KmapRVMlmQ0+mUp8MpT0dAQ086VTcyq1jvhEqs wNphrmtQXS6sZEry7PlqpJVMmuUK1L19y9ahkem3+wEdcFR7qRrco3o8ntDd7j45e/LSjV21 5cNK7KrN5h3VtHdZ3bdGlCkU6avk9WSVShZkc9p0MN9yqidwQ58HQ2p6MfDugdIWR8fAIWNx 9DmPdW+2P1NiLFF9jrPE2W63q6GhYc//H2z/AAAAAEYRJp1DJ1nqkEqlFIlEDix1IGyqJjFN +lfU+2xCOw/sMptluuEwliM4fJromVNwKqr2ac+uDavHFDb1a779dJZHOnxzmo/dVdtYTt7H b2sb7QkpOLas9kfN2lm5ly+o1DZDxa8nr2SoS53xfj1/1FwkTJLMngH1FFo0FunRvLeM17wc lL8wrkfeg2c98pwnvDdFxxLnznHDou2foaGhA7/fAQAAgHIgTKpChE0XlVNe95zGurplt1uk fEbpNZtGH/XsmhWT0fLkiJ6kC1qbC2rWtvtR8Wa5J5Y0PTui/u6wLBazlM8pZ27S/FPf5tPC 4rManEuokM5oJGhSYLxXu580f6z2ydv6a/dL/W0oppgGFbKMKOCxSrLKM72g0WSbYjufNMsz 8VyPZkc02L0oi8WsfD6n3FpelqERtRedVLH/eqR8LqfcjR4tTG9uTL2nnoc3NDTRIaec8gVc +nywS8H0kAYbkhrfVfP4QLNsh4zj3jFIvt3oOx1Vruvk5zzq3mSjIY0YGkucNYRFAAAAOG8u bWxsbJRqXF9fP81acEYc5/HUhE0AcLiThkXFfr8CALCtpqam0iUAuMAIk3Bs7xo2RaNRDQ4O 8ocRgKpAWAQAqATCJACVRJiEsmNmE4BqcpKw6N/+7d/0wQcf6K/+6q8IiwAA7wVhEoBKIkzC qQqFQhocHNT9+/f1J3/yJ4RNACrufcws+slPfqJUKqWf//znp3AFAICLiDAJQCWxATdO1d// /d9Lkn7xi1/s/O/92CAcQDmxwTUAAABQXsxMwqlJpVKqq6vbeb26urrz5LnjYBkdgN3O4p5F zEwCALxvzEwCUEnMTMKpWVpa2vnfV65cUTgcPlGYtP0Zj8dTtJ2ZTUB1YWYRAAAAcLYwMwmn 5o//+I/1y1/+Uttfue9///v65S9/eep1MLMJOFvO4syid8XMJADA+8bMJACVRJiEUxGPx9XQ 0HDg/cePH8vr9VagotIIm4Dyqsaw6CiESQCA940wCUAlscwNpyIcDuvKlSt6/fr1zntXr15V JBI5c2ESy+iA42EZGgAAAHCxMDMJp+IP/uAP9K//+q8H3q+pqdF3331XgYreH2Y2odpcxJlF 74qZSQCA942ZSQAqiZlJeO/i8XjRIEnaDCzP4uykd8HMJpw3zCwCAAAAcByESXjvwuGwLl++ rDdv3hxou3z5ctWFSUchbMJpIywCAAAAUE4sc8N79/3vf1+/+c1vSrZ/9NFH+ud//mdZrdZT rOr8Yhkd9mMZ2tnDMjcAwPvGMjcAlcTMJLxXkUjk0CBJkn7zm99oaWlJPp/vlKo635jZdPEw swgAAADAWUKYhPcqEono6tWrevXqVcljrly5on/8x38kTCoTwqbzh7AIAAAAwHnCMje8Vzdv 3tRvf/tbQ8em02mWup0BLKMrP5ahXTwscwMAvG8scwNQScxMwnsTj8f1R3/0R3ve+/d//3f9 0z/9k+rq6mSxWPa0JRKJkrNpcHqY2XR8zCwCAAAAcJEwMwmn6le/+pXcbrcikYh+8IMfVLoc vAfVOLOJmUU4LmYmAQDeN2YmAagkZiYBKKvzOLOJmUUAAAAAYBxhEoBTVYmwibAIAAAAAMqH MAnAmVLOsKkYwiIAAAAAeDeESQDOFaNh09/93d/pZz/7mf7mb/5Gn376KWERAAAAAJQJYRKA qrIdNn377bf62c9+ph/96Ef68MMPK1wVAAAAAFSPy5UuAAAAAAAAAOcHYRIAAAAAAAAMI0wC AAAAAACAYYRJAAAAAAAAMIwwCQAAAAAAAIYRJgEAAAAAAMAwwiQAAAAAAAAYRpgEAAAAAAAA wwiTAJxQVtHJNtXXN6qlpVH1jQ+1nC19dDzUpvraW7r+aVCx0ysSAAAAAFBmVytdAIBzKjml 4FhWvV+/UMCRVzwcVsFc+nBX4KmWbrTp9uDplQgAAAAAKD/CJAAnk8poTTbZbZJklsvXW+mK AAAAAACngDAJwLGlwt3qnlxRriAN3q3XmKlBI89G5Vgc1OBsXHmzWflcTmZ3v6bHO+Q8ZMZS KvJQ/ZMx5c1mKZ+X2dWrkRGfXFZJSinysF+TsazMKignp3wTUwq4rad1qQAAAACAfQiTAByb wzevFzf8utWV0/iXC/JKkrIKL8ZUN/1coy6zpIzCbfXqHHboFxPu4h1lw+rvi6lp9YUCDkn5 uIbvBrWy5pPLmtWyv1V9a0NafeGTQ1J22a+Gth5ZVp/K5zitqwUAAAAA7EaYBKBMrGqdeap2 2/Y0JJta210KhqJKyi1nsY+sZZTJrymZzEoOq2R2qX9+Wjm7pMySphZzanrcru3cyNrcqybT XYUWk/INvO0xlUrp22+/3dN1MpmUJH311VcymUx72mpra2W1MrsJAAAAAE6CMAlA+aQjGuwL K5YpbL7OpVXQbeVKHe/0aag9rO7224p83qT2Dp96u7yby+JiMSULeSVHWtQ49vYjObNdymSk XfHU6uqq+vr6ip7ihz/84cEy0+kTXR4AAAAAgDAJQLlkwuppG1S2/7meD7hklpR90qbbI4d9 yCbvo1/o5UBUS+E5zU52a2bMrannz9S71d4+/UKlVslta21t1bVr1/Tb3/720OMuXbqkP//z P2dWEgAAAAC8g8uVLgBAlUhGFcs55fVuBkmSpMIRn8nGtRzPyur0yDc6rxffPFWPZVWhSFJy uuU0ZfQyld17mnBQw8t737Narbp//74uXz78V9rGxobu3bt3vOsCAAAAAOxBmASgPOwu3TYl tbKSVF6S8iktLsYOz5PSYQ0GHyu5502LnPYbkq1V/e02RaemFM9vNaXCGh5Lyu48OLPI6/Xq zZs3h5Z47do1eb3e41wVAAAAAGAflrkBOLZUuFvdkyvKFaTB+kaF2if0bKBHj2bi8o/cVe2s XXabU26bXcosyt8o/Z/3X+r/+x8xFdbi8jdKo0+n5bV3KOAck78xIrNZyufysrXPabpjMyxq frSk+Yf96quvl8lmkuRQx8xj9RZ5kpvX69VHH32k3/zmN0Vrvnr1qu7fv/8eRwUAAAAALoZL GxsbG6Ua19fXT7MWXAC/+tWv5Ha7FYlE9IMf/KDS5aDK+P1+/cM//INevXpVtP3x48fMTMKp +MlPfqJUKqWf//znlS4FAFClampqKl0CgAuMZW4AqobP5ysZJN28eZMgCQAAAADKgDAJQNXw eDy6efPmgfcvX76sBw8eVKAiAAAAAKg+hEkAqsqDBw8OPNXtzZs38vl8FaoIAAAAAKoLYRKA quLz+Q481e2TTz6Ry+WqUEUAAAAAUF0IkwBUFZfLpU8++WTn9ZUrV3Tv3r0KVgQAAAAA1YUw CUDV+fGPf6wrV65Ikl6/fq1AIFDhigAAAACgehAmAag6XV1dev36tSTps88+k8PhqHBFAAAA AFA9CJMAVB2Hw6HPPvtMkvTFF19UuBoAAAAAqC5XK10AcJa1trZWugSc0O9+9ztJ0uLiopaW lipcDU6itrZWExMTlS4DAAAAwD6EScAhotGourq6WCZ1DmWzWS0uLqqpqanSpeAEwuGwNjY2 Kl0GAAAAgCIIk4Aj+Hw+eTyeSpeBE/D5fHK5XJUuAycQjUYrXQIAAACAEtgzCUDVIkgCAAAA gPIjTAIAAAAAAIBhhEkAAAAAAAAwjDAJAAAAAAAAhhEmAQAAAAAAwDDCJAAAAAAAABhGmAQA AAAAAADDCJMAAAAAAABgGGESAAAAAAAADCNMAgAAAAAAgGGESQAAAAAAADCMMAkAAAAAAACG ESYBAAAAAADAMMIkAAAAAAAAGEaYBAAAAAAAAMMIkwAAAAAAAGAYYRIAAAAAAAAMI0wCAAAA AACAYYRJwFmWTykWSxVvy8QVS+ZPtx5UN75vAAAAAAwgTAJOST42q2BLra7falS33y+/v1Mt jW16uJzZOiKmh3e6Fdn5QFyh7hElLTZJKYUaaxWM7urQZlNmslvD0ewp1tytzsZGtQ1HlS15 zOZPd2P9rnqzis0G1d3tlz/ol7+7U22dfk1GUnobT+w6xr95TGcwrPjWibLR0OZ5rtfqYexg qBEfrtf1j++oLRhWvETtLfX1O7XvaZ9c1stoSP6WWl2/1abwrjwlszwpf0ut7rQFNbvnvHlF /Z/q47awNu9gTA/r69XW2anOzjbV37quTxs71dnZqc6WO2qZTR04Z8bgdR+vLikZ7lZLm18P Z2MHr7Xod08n+r6lIsMKdreo5eGy3t+3EAAAAMBZc2ljY2OjVOP6+vpp1oIL4Fe/+pXcbrci kYh+8IMfVLqcI12/fl1LS/8/e3cT01aa53v8VyladncqsTcdTyaKvUkstQLW1aSs0Si4FglR a7CVpIANtiolg0oyqmRr7AAAIABJREFUlloyqFrA3WBWwAbYXGADrBw2kJWNdCtUbUxaGrl6 Y6dnuly9sUuzcO7G7hqpjZQKd8FLeLHh8BIczPcjRQ3nOec5//PSJfHT8zwnIY/Hczodxjv1 2xGPvn8ZlkNSORnRp/6CopkFdVhT6r87Jc+f5+WTlB2/r4h5Xsthhzb+uPcqO/xKkztLKcTU 1pbW4LdjcptPp8TDalZxUW23o7q9/Epj7ir7SCrG+zVnG1Ofu6xU/wOFSlF9O/NQ1q3S40E9 mGrWt8vdsqnKPotBtU7YNf/tsFxmSfGg7g6k9No+qO+XA7Jp+2QKeQeUKLXo+atJbZW1r67s uO7dW1L7y5fqc+5vL8c79elASiVLQImtc0oqxoIauDavmYc77ksxrlDbkFYzFoW//05hR1rj kZTaJ7vlUE5T9z9Vsu//acEnKTWkSDasyYBtzzmNXfeR6lJW4/c6VZj+s8Zc1Z/j7nfvBO9b Oa7O2zEFflyQ7xTfwdbWVknS8vLy6XV6hr766ivlcjl98803tS4FAFCnrly5UusSAFxgjEwC asjsbJK9nFUmv7clrVhsTe7mjWgmHYtqMV9QciKkUGRc2wNKbM3ymhKKpaqcoFzWqU9MKr1W UWWtHdBxdjyoOeeY+tyScjH1z5kUHnwXlkiSzRfVdK9bFr3bp3vvPh2DCmhO0aV3416c4UE1 Z0Y0smM0TnpuSc5wy0ZfByiXCiqbbbJV3dEs9+CCek1z8kcOHm1TSCxJffPqbcpodi4tyaW+ ye7tMG0X9/BGkLSX4es2XpdUVqFslu2QYGf3u3eC981sksW0phIz4AAAAIALgzAJqKFCckUZ m1stTklya+zlxqgkFbPK5G1y2jf2cwWi6rDb5Omd0cxknx5u5xI22RwlpTOV1rkpaLbtpj7t 3/rLP6dYZ6Nu3bq1/1/jPfVXC6QkKb+oaCikYNs93WoeUck3rPDewVr5WfV2bkzrGlh6V085 s6qMxSnnvpTFIc9Dl8xb+5idatq3j11OZ1npZGZ7i/maV4NdFi0NxZSTpMKi5vJ+dTlNlWsv LCoaiSgS6lRrcEWu0VFVynW2WZrUtzAt90qXumarrB+knJbiFgVaXGoPe/R6aU7JY4QpR7lu Y3VJ0pqhc+969078vpEkAQAAABdJQ60LAC6cwqKikawsKqlUdmr6+aA8W6NItv53raSiTDId Om3ILJPJpFKhUoBgU2B6WW7z1qQvhwILrxQ4Ts32DkVnwnIoq6nOAam3Xc59+3RrYmFjClVu cVypKtlOVYb3N8vVO6iWTwc0kWxX18qKnOEZWUsrlXe3dSg6uTVF74VCzW0KWlY177NW3l+S bD5NL6T0oM2vIde36t3bnp5T0hlQ2CzJ16WW3h7NrYzKc5x5Xke5T4fVJUnFnPIlu9zXKrRV e/dKJ3nfHHLaCkr/KAXcVQ8EAAAAUEcIk4CztjPcqMZkllVrG1PJDvsDf21NFlvlRMLscOvd sjk5xTq9GqqweLXMNrXPv3y3BlJVTnWFr+nTyJRavuvbHyhtcnT0bV+fualZTaWYsjnJs+ui i8pl12Rz2g7YJ69s1ixXuGn3Caw+DYZH9GCgTfnmQT1zSjpoZNX2cR75mgqKxDOS7+B1sMzu YT0bzehBsEfOrrK0Hc6UlZxbUaFUUiQS29hyrayVubiKvg4dEFHtP8dRr/vAuqRcvF8DIwmV +p6pYlZW7d070fvmVFfUowehVoW6BzUa9hzpHgAAAAA4f5jmBnyIrE7ZbQUVXm9tMMtk3lz/ KLuo2HYgVNDrgkmO25XnbRVSi4pvf859Y2TS3/72t/3/XhkJkjYr8fSpa21KI/FDvt/1IqJQ vCw5AhrrWtPcRHLHWj9lZaf8ahtPb1xTxX2kQnxEMVOvou374wlnV1R+i0Pt4YeH5h/v5JXN S3aX3dDejsCc5lvSioyk3k0eK68oVgprYX5Sk5Mb/xbmw7Inp7R00Oyzyic48nVXrUuSwzem hURUlvERHfZ4djnR+5bVXDSplpllzRAkAQAAABcCI5OAM1JOz2pgLqO1fEHRiEnh0e4DvsDW pPaWsibSRfU5rZJs8rS7FJsIKWhaU8tox1anWil41F6xo4JWRgY03uSUb9hVof2INfdf0+BY h5xyKhB26dMBvyL5QQ00ZzW6fV3Zd4tg55Mq+SXJLPdYQpOzUfUGY7JYpHKppNK1Li1Mbi08 vXcfs1QuqWRu0fzzwMYXzdKzGphLKVUe0KxjVN3uhxpb3vyMWW5R/eOrKhXKGu9f1PBYh+y7 7ndWFpVVyudVcE9qpsux+9rGb+t/u3/U/5lKKaUBTVmiCnuskqzyTC5oONu2MfCpnNJscEir BY9SuYB8DkkqK5XKyqzvNdITkWVyUJZ4VIv5Nb2ei2jWNqruzeez95yjfQ8Pve5ickrRw+ra yeqQ3ZJX/rW0lewc/u6d5H3LKVuwyXP7WK8YAAAAgHPoo/X19fVqjT///PNZ1oIL4IcffpDb 7VY8Htdnn31W63IOdfXqVSUSCXk8B0+Jei8KcYV6kgrMjclTcbhHWelxv0ZsE1oIHDhpDhdK Wv13e2RbeKm+avMQKzn2+/ZCoVvT8nz/XIFTHJbU2toqSVpeXj69Ts/QV199pVwup2+++abW pQAA6tSVK1dqXQKAC4xpbsCHyubTzHSL8qvZyu2FpDLOUc0TJGEXixyWkvKlIx523PetWNJr WWQ5xtrjAAAAAM4nwiTgQ2Z7qICvyvCSzTb+hsduDvmHwypPhdQ/u3stpkMd8X3LxYcUGVjR 7dFBtfAiAgAAABcGayYBQJ2xesKaOYOZmQ7fsCZ97/88AAAAAD4sjEwCAAAAAACAYYRJAAAA AAAAMIwwCQAAAAAAAIYRJgEAAAAAAMAwwiQAAAAAAAAYRpgEAAAAAAAAwwiTAAAAAAAAYBhh EgAAAAAAAAwjTAIAAAAAAIBhhEkAAAAAAAAwjDAJAAAAAAAAhhEmAQAAAAAAwDDCJAAAAAAA ABhGmAQAAAAAAADDCJMAAAAAAABgGGESAAAAAAAADCNMAgAAAAAAgGENtS4A+NB5vd5alwBc SM3NzbUuAQAAAEAFhEnAAQYHB2tdAo4pk8koHo/r66+/1q9+9atal4NjsNvttS4BAAAAQAWE ScABCJPOr2fPnikej+uPf/yjfv3rX9e6HAAAAACoG6yZBAAAAAAAAMMIkwAAAAAAAGAYYRIA AAAAAAAMI0wCAAAAAACAYYRJAAAAAAAAMIwwCQAAAAAAAIYRJgEAAAAAAMAwwiQAAAAAAAAY RpgEAAAAAAAAwwiTAAAAAAAAYBhhEgAAAAAAAAwjTAIAAAAAAIBhhEkAAAAAAAAwrKHWBQDA SeVyOf3000+7tmWzWUnSn/70J5lMpl1tjY2NslqtZ1YfAAAAANQTwiQA597q6qp6enoqtn3+ +ee7fr9y5Yr+8pe/nEVZAAAAAFCXmOYG4Nzzer26fPnyoft99NFH8nq9jEoCAAAAgBMgTAJw 7lmtVj1+/FiXLh38n7T19XU9evTojKoCAAAAgPpEmASgLvh8Pr19+/bAfS5fviyfz3dGFQEA AABAfSJMAlAXfD6fPvnkk6rtDQ0Nevz48RlWBAAAAAD1iTAJQN149OiRGhoqf1fgzZs3CgQC Z1wRAAAAANQfwiQAdSMQCOjNmzcV265fvy6Px3PGFQEAAABA/SFMAlA3PB6Prl+/vm/7pUuX 9OTJkxpUBAAAAAD1hzAJQF158uTJvq+6vX37liluAAAAAHBKCJMA1JVAILDvq243btyQy+Wq UUUAAAAAUF8IkwDUFZfLpRs3bmz//vHHH+vp06c1rAgAAAAA6gthEoC68/TpU3388ceSpF9+ +UV+v7/GFQEAAABA/SBMAlB3/H6/fvnlF0nSnTt35HA4alwRAAAAANQPwiQAdcfhcOjOnTuS pC+++KLG1QAAAABAfWmodQHAh8zr9da6BBzTP/7xD0nS0tKSEolEjavBcTQ2NmpsbKzWZQAA AADYgzAJOEAymZTf72ea1DlULBaVSCTU0tJS61JwDLFYTOvr67UuAwAAAEAFhEnAIQKBgDwe T63LwDEEAgG5XK5al4FjSCaTtS4BAAAAQBWsmQSgbhEkAQAAAMDpI0wCAAAAAACAYYRJAAAA AAAAMIwwCQAAAAAAAIYRJgEAAAAAAMAwwiQAAAAAAAAYRpgEAAAAAAAAwwiTAAAAAAAAYBhh EgAAAAAAAAwjTAIAAAAAAIBhhEkAAAAAAAAwjDAJAAAAAAAAhhEmAQAAAAAAwDDCJAAAAAAA ABhGmAQAAAAAAADDCJMAAAAAAABgGGESAAAAAAAADCNMAgAAAAAAgGGEScBFUs4plcpVbiuk lcqWz7YenB6eLQAAAIAzQpgEnCPl1KwirY26evO+gqGQQqFOtd5vU/+LwuYeKfXfDSq+72dJ 5bSmglFlLTZJOU3db1QkuaNzm02F8aCGksX3Vn8xObVR/9VG9af2hxvpoXu6+tu7aovElJZU TI4reP+Wrt5qVWgqpY3KikpOhdTaeFdtkVmlyyn137unts5OdXa26d7Nq7p1v1OdnZ3qbL2r 1tmtgKWsZOiWftsW08bdOvy4Xfd7/MXmcUWlZiMKBkMKhUIKBTvVGYkpXXx3jaHWRl292abY jmyn8GJcodZG3W2LaHbPtWdjQbW2hdQ/u3GNR3vOOtazzcWHFAm2qrX/hd7fEwcAAABQjwiT gHPE7O7WZLhJJnuHojMzmplZ0PNhuxJdES0ekghkpyKKe6IKOM1V9rDJN+xTZmBEFXKeU2H1 hDUZduu2XXo2tKTCzsZiXFMrJVlsHg1OBuSSZPX0aTTglMnVpdGwW9aNXuQJj6rL7VbPZLdc ZpNs7i5NLCxoYWFCgdsmufsWtLCwoIVhn5zmzestriiWtciWnNVSTpIOP27X/e57KJvKSvV7 FUp5NTE/o5mZGc3ML2iyeUVB75DS5a1rbJLdktaAf2ObJNke9mk04Ja7Z1Ld7p3PIKv4VFpN 0RmNdW9c41Gf83GercM3rMnpsCzP5rTKoCUAAAAAR0CYBJxzZmeT7OWsMvmD9korFluTu9mx 8VssqsV8QcmJkEKRcW0PeLE1y2tKKJaq0k25rNPIHZzhQTVnRjSyI7VKzy3JGW6R5ci9udQ3 2S1HpSb3sCYDNklSIbEk9c2rtymj2bm04eN2ycXUP2dS9+DDzWBrg61jUAHNKbq0lfSY5R5c UK9pTv7IYSN/yiqUzbJVy4G2eqz6nE/wbM0mWUxrKhEmAQAAADgCwiTgnCskV5SxudXilCS3 xl7Oy6c9PxezyuRtcto3jnEFouqw2+TpndHMZJ8ebucmNtkcJaUzldbeKWi27aY+7d9KI3KK dTbq1q1b+/813lN/tUBKkvmaV4NdFi0NxZSTpMKi5vJ+dTlNJ74fleW0FLco0OJSe9ij10tz Sh4jQClnVpUxO9W0L4Gyy+ksK53MvNtkaVLfwrTcK13qmq2ylpEkac3Quas+5xM/W5IkAAAA AEfTUOsCABxDYVHRSFYWlVQqOzX9fFCerZEtO0e4bP28VlJRJpkOGf0imWUymVQqVAo4bApM L8ttdm/+7lBg4ZUCx7oAs1y9g2r5dEATyXZ1razIGZ6RtbRyrN4OlZ5T0hlQ2CzJ16WW3h7N rYzK4zv0hux3lLzL5tP0QkoP2vwacn2r3kr7FHPKl+xyX6vQZuQ5n+jZOuS0FZT+UQq4qx4I AAAAALsQJgHnka1D0clw5SlalZjMsmpNa2XtDpsqWVuTxVY5MTE73HJt/5ZTrNOroUoLLJlt ap9/qbGDAgqrT4PhET0YaFO+eVDPnJIqjGYyWcxS8bVK0o6pZSWVZFGFiWgVlJWcW1GhVFIk EtvYcq2slbm4ir6OXdPVDmNualZTKaZsTvLsuvl5ZbNmucJN+49xD+vZaEYPgj1ydpWlHaFR Lt6vgZGESn3P5KtUiJHnfKJn61RX1KMHoVaFugc1GvYc6X4AAAAAuJgIk4CLwOqU3VZQ4bU2 ExmzTObN9Y+yi4qVfAq4zZIKel0wyXG7ckxTSC0qZfHJ5zTrZCOTNji7ovKvPJMr/LBqDmJ1 t6jpx0Ulsl0Kby4wXc4mlJBb7UZOUl5RrBTWwnzgXfiUtujugykt5TrUbTiRk+QIaKxrTpGJ pNon3wUvhfiIYqZezbdXjmIcgTnNpx6obaQk37Md231jWmh2q/PTEcX9C+o4TpJzomeb1Vw0 qZaZPx8c/AEAAADADqyZBJwj5fSsInMZreUXFY3MHuGra01qbylrdev79bLJ0+5SdiKk4FBC umbeOoFWCh61uytFOwWtjAxoKJY9Yf0ppeYGNJsqS9aHGlueV8AhKbeo/vFVlQpJjfcvavss ji7NTLgUD97T/dZWtbW1qm2ooJ7RvaOKCnoxHtVifk2ZuchG/+WUZoNDWs2llNpeKqisVCor s77XSE9Ei9kKx+2qd/N+j79QQWa5xxKabFpSbzCkSCSiSCiogZUWzT/vk8ssFZNTGphKKTU1 oKnk1v22yjO5oOFK99XqkN2SV/713vtk9Dmf5NnmlC3Y5Lp9UP8AAAAAsNtH6+vr69Uaf/75 57OsBRfADz/8ILfbrXg8rs8++6zW5Rzq6tWrSiQS8ng8tS7l5ApxhXqSCsyNyVNxBExZ6XG/ RmwTWggcZbgOTiat/rs9si28VJ/zmF0c+9m+UOjWtDzfP1fgA5vf1traKklaXl6ucSXH89VX XymXy+mbb76pdSkAgDp15cqVWpcA4AJjZBJwUdh8mpluUX61ysiiQlIZ56jmCZLOmEUOS0n5 0gm6OO6zLZb0WhZZjrEOOQAAAICLizAJuEhsDxXwVRn+stlGrnDWHPIPh1WeCql/Nqni4QdU dsRnm4sPKTKwotujg2rhoQMAAAA4AhbgBoAas3rCmjnjmZQO37AmfWd7TgAAAAD1gZFJAAAA AAAAMIwwCQBQd4qpmMZjqeNPGwQAAABQFWESAKDulFJTGplK6STrmgMAAACojDAJAAAAAAAA hhEmAQDqSnqqTf7xrNay42q7d0/37gc1m5Oy4/d09epVXf1tp2KpKXXeu6nfXr2qq/dn9X/H W3Xv1m919d6UcpKkpIbu39Wt3/5WbYs7J8vlFO9v0/3799V6f6PvqRST6QAAAHCxECYBAOqK K/xcz/qcMjn79PzlS738bl7dDsnZ91J/X/LLspbSbMyiwcSP+vHbHjWZpf/Vt7xxzHYvHg1/ N6N2286ei3oR8qrnx3bNf/edlr97qcSgSVNtXYrlzvwyAQAAgJohTAIAXDA2+cIBuaxmWd3D ej7fLtvhB0mFhCaWSmrpaZdjc5P1YbdaTCuaWsq+x3oBAACAD0tDrQsAAOBMmexy2rd+Mctm Mxs7LptSdq2sbLRV90febS6Z7VKhIMl5yoUCAAAAHybCJADAxWMwP1rbt8Wm9snvNOY+5XoA AACAc4RpbgCAOldW2cBeZpNJKhdU2j6ssDHgaIvTLaepoB9zuxfczsYiGnrBItwAAAC4OAiT AAB1x2KxbAdD2fEHejB++JpGNqdLlnxKqc0AKRdfUmbXDl71ttuUnJhQeiudysU0NJKV3Wk9 5SsAAAAAPlyESQCAumP19qrLsqTgvfsKxt0aDDhVjEd0fyCh0tqqBu7dV2ixsPsgz6AmA2VN 3Lur+22dmlprUYttTamoV21TaUlWPZxJaL45o55793S/9b7u96zIM/1M3Y6KZQAAAAB1iTWT AAD1x/pQY9+92r3NN6nvfJMHHGSTb/I77dolENDuIxzyjT2X79QKBQAAAM4fRiYBAAAAAADA MMIkAAAAAAAAGEaYBAAAAAAAAMMIkwAAAAAAAGAYC3ADh/B6vbUuAbiQmpuba10CAAAAgAoI k4ADDA4O1roEHFMmk1E8HtfXX3+tX/3qV7UuB8dgt9trXQIAAACACgiTgAMQJp1fz549Uzwe 1x//+Ef9+te/rnU5AAAAAFA3WDMJAAAAAAAAhhEmAQAAAAAAwDDCJAAAAAAAABhGmAQAAAAA AADDCJMAAAAAAABgGGESAAAAAAAADCNMAgAAAAAAgGGESQAAAAAAADCMMAkAAAAAAACGESYB AAAAAADAMMIkAAAAAAAAGEaYBAAAAAAAAMMIkwAAAAAAAGBYQ60LAICTyuVy+umnn3Zty2az kqQ//elPMplMu9oaGxtltVrPrD4AAAAAqCeESQDOvdXVVfX09FRs+/zzz3f9fuXKFf3lL385 i7IAAAAAoC4xzQ3AuRcIBHT58uVD9/voo4/k9XoZlQQAAAAAJ0CYBKAuPH78WJcuHfyftPX1 dT169OiMKgIAAACA+kSYBKAu+Hw+vX379sB9Ll++LJ/Pd0YVAQAAAEB9IkwCUBd8Pp8++eST qu0NDQ16/PjxGVYEAAAAAPWJMAlA3Xj06JEaGip/V+DNmzcKBAJnXBEAAAAA1B/CJAB1IxwO 682bNxXbrl+/Lo/Hc8YVAQAAAED9IUwCUDdcLpeuX7++b/ulS5f05MmTGlQEAAAAAPWHMAlA XXny5Mm+r7q9ffuWKW4AAAAAcEoIkwDUlUAgsO+rbjdu3JDL5apRRQAAAABQXwiTANQVl8ul GzdubP/+8ccf6+nTpzWsCAAAAADqC2ESgLrzhz/8YfvnX375RX6/v4bVAAAAAEB9IUwCUHe8 Xu/2z3fu3JHD4ahhNQAAAABQXwiTANQdh8OhO3fuSJK++OKLGlcDAAAAAPWlodYFAB+ynSNc cL784x//kCQtLS0pkUjUuBocR2Njo8bGxmpdBgAAAIA9CJOAAySTSfn9fqZJnUPFYlGJREIt LS21LgXHEIvFtL6+XusyAAAAAFRAmAQcIhAIyOPx1LoMHEM4HCYIPKeSyWStSwAAAABQBWsm AahbBEkAAAAAcPoIkwAAAAAAAGAYYRIAAAAAAAAMI0wCAAAAAACAYYRJAAAAAAAAMIwwCQAA AAAAAIYRJgEAAAAAAMAwwiQAAAAAAAAYRpgEAAAAAAAAwwiTAAAAAAAAYBhhEgAAAAAAAAwj TAIAAAAAAIBhhEkAAAAAAAAwjDAJAAAAAAAAhhEmAQAAAAAAwDDCJAAAAAAAABhGmAQAAAAA AADDCJMAAAAAAABgGGEScBbKOaVSuffTdyGtVLb8fvpG7R307tTy2X+odQEAAAB47wiTgBMo p2YVaW3U1Zv3FQyFFAp1qvV+m/pfFHbslNZUMKqsxSYpp6n7jYokj3O2gpJTQd29eU/j2R2b bTYVxoMaShZPdjGHnT05rmBbp0KhiEKhTrW1dWpo8zr334eNf8H79xRJ7mkff6HCnr4PO35D UanZiILBkEKRkELBTrV1hjQez6mslPrv3VNbZ6c6O9t07+ZV3brfqc7OTnW23lXrbK5KDTv6 DG302RmJKb15K4vJKYVaG3X1ZptiO3KTwotxhVobdbctotnU7tAkGwuqtS2k/tmUihWvbe87 klL/3aDi+37W4e/Oe3j2p/JOV6grFx9SJNiq1v4Xer9vKgAAAID3raHWBQDnmdndrcnwimIj HkVnwnJIKicj+tQfkTuzoA6rlJ2KKO6Z17LTbKDHohY7vcoMvtSwa3dLOjaubFOLXMruOcYm 37BPc20jSn07JreR0xxVOamhYFzub79T2LFZaTwof6YkPbRVvA8b+/RrzrznPvU9lG1P94cd L5WV6vcqVIrq2/mHsm62F+JBPZhaUcDnls3dpfBktxzKaer+p0r2LWjBJyk1pEjWXKGGKn0u BtXqzWr+22G5PGFNlpJaHUhpwD+kpm+H5TJLtod9Gn2d0cC1SXW7d15JVvGptJqm/6yxredn 4B2p5vB35yjPvvq7tdPpvNP763L4hjXZElfn7TmtDj+U7328pwAAAADOBCOTgFNmdjbJXs4q k5ektGKxNbmbN+KRdCyqxXxByYmQQpFxvdg7ROcArsCYuj3XZKrUaGuW15RQLFXl4HJZJ5t0 VNLaWknZ/LsxJVbftJ6FnVWPyI4HNeccU5+76i4H2nV8Lqb+OZPCg+9CH0my+aKa7nXLIpf6 Jru3Q6hd3MOaDOyNr9712b23z45BBTSn6NLWtZrlHlxQr2lO/shho2rKKpTNsh0SlOx+R6ox +O4c9uxPwbHe6Up1mU2ymNZUYgYcAAAAcK4RJgGnrJBcUcbmVotTUjGrTN4mp32jzRWIqsNu k6d3RjOTfXpYIeM4HptsjpLSmUpr2BQ023ZTn/Zv/VWfU6yzUbdu3dr/r/Ge+iuFEuYW9Q46 FG9r0t3WkIZm40oVJOve0CQ/q97OjellA0vHWCOqyvHlzKoyFqec+9IihzwPXTrOIJdyZlUZ s1NN+/q0y+ksK53MvNtkaVLfwrTcK13qmj3outYMnXvXOyK3xl7Oy6c9Pxt+dw569qfjeO90 tbpIkgAAAIDzjmluwGkoLCoaycqikkplp6afD8pjllQqqSiTTAemHTnFOr0a2lx7Z630WuXU LcUkyWxT+/xLjR06uscsk8mkUqFSmGFTYHpZbvNWJw4FFl4pcKQLNMsVfq6/+bNKrqwovjSi zoGIXKPLet69Y3SSvVsTCxtTo3KL40pVHEZ1gJMef1RH6d/m0/RCSg/a/BpyfaveSvsUc8qX 7HJfq9BW7R2RtCsN2/p5zci7s3FA9Wd/gnfrRO90tbocctoKSv8oBY45Yg0AAABA7REmAafB 1qHoZHj/NCuTWVataa0sVR8+szPcMbauTUVra7LYKqcjZodb77rbHTDs3rFawFBUNrsmp9Mp T4dTno6wBhc71RSdVap7TJVyAUdHX+VpZwbtPN7c1KymUkzZnOTZ1WlRueyabE7bkUcnVe8z r2zWLFe4af8x7mE9G83oQbBHzq6ytCM0ysX7NTCSUKnvmXyV1kGq9o5UY+jd2VT12Z/g3TrR O12tLqe6oh6ngScQAAAgAElEQVQ9CLUq1D2o0bBHBywZBQAAAOADxTQ34H2yOmW3FVR4vbXB LJN5c/2i7KJilQKdYynodcEkx+3K8+YKqUXFtz/VvhEw/O1vf9v/71W1kSopjYfGtatcs1mm aw5VGoSz7UVEoXj1a8zNBitPq9t7vCOgsa41zU0kd6xZVFZ2yq+28fTxJk5V7FMqxEcUM/Uq 2l455nAE5jTfklZkJLVrUpvDN6aFRFSW8RHFT+NzZYbfnYOf/ak7UV1ZzUWTaplZ1gxBEgAA AHBuMTIJOIFyelYDcxmt5QuKRkwKj3bv+aJWk9pbyppIF9XntEqyydPuUmwipKBpTS2jHcbP lZrVQCyhVDmvzEhEpfZeDfscW4VopeBRe8XPeRW0MjKg8SanfEce7rTFKZ97TiP+oOx2i1Qu KP/apuGZro2vfe26D1lZtg7LJ1XyV28vpXO65jr8eMks91hCk7NR9QZjslikcqmk0rUuLUzu XEC7oBfjUS3m1/R6LqJZ26i6N+/JrnOM39Zo38M9fZqlckklc4vmnwfkMkvF5JSiUymlNKAp S1Rhj1WSVZ7JBQ1n27QvB7M6ZLfklX8tbRV1+DtSjcF358Bnf3Sn9k5XrCunbMEmz+1TKRUA AABAjXy0vr6+Xq3x559/PstacAH88MMPcrvdisfj+uyzz2pdzqGuXr2qRCIhj8dz/E4KcYV6 kgrMjcnzXoZilJUe92vENqGFwEkmluHk0uq/2yPbwkv1Vf/QnXGHvjs1evbHruuFQrem5fn+ uQKH/H+htbVVkrS8vHxaVZ+pr776SrlcTt98802tSwEA1KkrV67UugQAFxjT3ID3zebTzHSL 8qvZ99N/IamMc1TzBEkfAIsclpLypVPq7rB3p1bP/rh1FUt6LYsspzOICgAAAECNECYBZ8H2 UAHfaQxVqd43f59/CBzyD4dVngqpf3b3WkzHdtC7U8tnf8S6cvEhRQZWdHt0UC28rAAAAMC5 xppJAHCKrJ6wZk4wK7JeOXzDmvTVugoAAAAAp4GRSQAAAAAAADCMMAkAAAAAAACGESYBAAAA AADAMMIkAAAAAAAAGEaYBAAAAAAAAMMIkwAAAAAAAGAYYRIAAAAAAAAMI0wCAAAAAACAYYRJ AAAAAAAAMIwwCQAAAAAAAIYRJgEAAAAAAMAwwiQAAAAAAAAYRpgEAAAAAAAAwwiTAAAAAAAA YBhhEgAAAAAAAAwjTAIAAAAAAIBhhEkAAAAAAAAwrKHWBQAfOq/XW+sSgAupubm51iUAAAAA qIAwCTjA4OBgrUvAMWUyGcXjcX399df61a9+VetycAx2u73WJQAAAACogDAJOABh0vn17Nkz xeNx/fGPf9Svf/3rWpcDAAAAAHWDNZMAAAAAAABgGGESAAAAAAAADCNMAgAAAAAAgGGESQAA AAAAADCMMAkAAAAAAACGESYBAAAAAADAMMIkAAAAAAAAGEaYBAAAAAAAAMMIkwAAAAAAAGAY YRIAAAAAAAAMI0wCAAAAAACAYYRJAAAAAAAAMIwwCQAAAAAAAIY11LoAADipXC6nn376ade2 bDYrSfrTn/4kk8m0q62xsVFWq/XM6gMAAACAekKYBODcW11dVU9PT8W2zz//fNfvV65c0X// 93+fRVkAAAAAUJeY5gbg3AsEArp8+fKh+126dEler/cMKgIAAACA+kWYBKAuPH78WJcuHfyf tLdv3+rRo0dnVBEAAAAA1CfCJAB1wefz6e3btwfuc/nyZfl8vjOqCAAAAADqE2ESgLrg8/n0 ySefVG1vaGjQ48ePz7AiAAAAAKhPhEkA6sajR4/U0FD5uwJv3rxRIBA444oAAAAAoP4QJgGo G+FwWG/evKnYdv36dXk8njOuCAAAAADqD2ESgLrhcrl0/fr1fdsvXbqkJ0+e1KAiAAAAAKg/ hEkA6sqTJ0/2fdXt7du3THEDAAAAgFNCmASgrgQCgX1fdbtx44ZcLleNKgIAAACA+kKYBKCu uFwu3bhxY/v3jz/+WE+fPq1hRQAAAABQXwiTANSdP/zhD9s///LLL/L7/TWsBgAAAADqC2ES gLrj9Xq3f75z544cDkcNqwEAAACA+kKYBKDuOBwO3blzR5L0xRdf1LgaAAAAAKgvDbUuAPiQ 7RzhgvPlH//4hyRpaWlJiUSixtXgOBobGzU2NlbrMgAAAADsQZgEHCCZTMrv9zNN6hwqFotK JBJqaWmpdSk4hlgspvX19VqXAQAAAKACwiTgEIFAQB6Pp9Zl4BjC4TBB4DmVTCZrXQIAAACA KlgzCUDdIkgCAAAAgNNHmAQAAAAAAADDCJMAAAAAAABgGGESAAAAAAAADCNMAgAAAAAAgGGE SQAAAAAAADCMMAkAAAAAAACGESYBAAAAAADAMMIkAAAAAAAAGEaYBAAAAAAAAMMIkwAAAAAA AGAYYRIAAAAAAAAMI0wCAAAAAACAYYRJAAAAAAAAMIwwCQAAAAAAAIYRJgEAAAAAAMAwwiQA AAAAAAAYRpgEAAAAAAAAwwiTAKDelXNKpXKV2wpppbLls60HAAAAwLnWUOsCANRGOhbRwMiS bKM/ad53kp5ymrrvVXb4lSY9Rz+6nJrVwNCE5jLX1O51yrTVkE+p1PWt5h1L79p72/XJ0jP9 t90uk9aUX11R4bZXbpukUlal9ud65kxoYGRKzzJOTa8+V8Cx0V3hxbiGJuaUMrcoPDiqgGIV z7uWzcgy/FKTHqmQHNfAREqmazZJBb1+LTX1TGr4oW2jz0Paj6KYGlfXSEa3b5uUf+3W8Hy3 nFXvUUn57JqaBqc19tAmKaX+u1Py/Hlevl0/SyqnNRWckGV4Wu5Kz8pmU2EoqKHAtIY91iPX DQAAAODiIUwCLihXIKqupSUlalyH2d2tyfCKYiMeRWfCcmw1JIfUXzbvbu9r1lLerK8nu+VQ TlP3P1Wyb0ELPkmpIUWyZlk9YU2WklodSGnAP6Smb4flMku2h30afZ3RwLVJdbslqfJ5i/F+ zZkllZMaCsbl/vY7hR1bbUH5MyXpoe3w9iNKzU6p3P5SYwGbyuWyzIfco3Iyok/9EbkzC+o4 IAPKTkUU98xr2WmusodNvmGf5tpGlPp2TO5quwEAAADAJqa5AedILt6vYGdIkf6Igp0hzabL Ujmt2ba7+u3NewrG0pIKejHUqsa7bZpNf6/ZYKeCkX5FQp3qDMVUeUZTWenZoO7fuqVIUpLS igXv61ZjRClt/F6tn3QsqsV8QcmJkEKRcb0oHFCrQcVYUKHysMYe7k02XOqb7H4XOO3kHtZk YCvEMcs9uKBe05z8kRcqGjxvdjyoOeeY+tySVNLaWknZ/Lujrb5pPQtvjRc6rH2/wot+de64 J7HNm5hd7Nf0aknZ2IBCkVlldXiiY3Y2yV7OKpM/aK+0YrE1uZs37li1ZyVbs7ymhGKpQ08L AAAAAIxMAs6N3Kx6Bkrq/X5GD82SUv26GxyS+89j6p4b1sqnU2pudkmS3G6nmt1RdbteK94+ rHmfU1JZycg9DSx59TywdyiLWa7uqDpiXmUlSS4Foh2a9Wa3221V+nEFouqYTSnbO/Nu6tQB tbqqXV9+Vr2dyY3pZvmsLNET3i9Lk/oWppW516Wu2VU9764YQe0671q+oOatKX/mFvUOzqmt rUlJt1e+dp98vpaNKXVG2vfKzSrYk1fX9xsjicqpft3rHJLz5ZjcHWPqWVnStGdCM/ueTWWF 5IoyNrcGnZLk1tjL+c2WHT8Xs8rkbWq3b/xa8VlJkmyyOUqKZXKSp8p9AgAAAIBNhEnAOVFc TShVLmtpILI5Na0km8WifFFyWVsUbhnQwFJW3X0WJeImBSY3QglbYUSh0JrMZqmULilnyUs6 6to4147Uz8G1VjmFvVsTC5tTuF6Ma+40lu+x+TS9kNKDNr+GXN+q95Dz5hbHldpetMksV/i5 /ubPKrmyovjSiDoHInKNLut5t9NA+27F1YRS9hZNb16Xuckj1+shxbOSu2rCtkdhUdFIVhaV VCo7Nf18UJ6tQUy75sVt/u9aSUWZZDp0oJNZJpNJpcKawUIAAAAAXGSEScB5YvNpcHLHukLl 8mZwYJYn3K5ycFYpn0Mrtg7Nm6VyvFedU3Y9fzkml1nKjqfUWTroBJWnoh29n4NqPZz5YZ/C xnY9vC/3sJ6NZvQg2CNnV1m6Vn1fR0ffjil0RWWza3I6nfJ0OOXpCGtwsVNN0VmlusfkPrT9 PbB1KLrznh7GZJZVa1or6/B7v7Ymi810yE4AAAAAwJpJwLlhbfbKnV/R6tY6N8VFBdumtDUR Ta6AApYlRUJJuQMbUUa5VFLJYpPFLEll5bKF/R1vs+iadU35wsYaQMVMSvnNbOngfswymcsb MVR2UbFU+fBaz5gjMKf5lrQiIykdOvbmRUSheFlSSuOhcaV25mtms0zXHJt51GHtu23ck6RS m0sslTNJpS0t8lVfYunkrE7ZbQUVXm8XuO9ZbSjodcEkx+2jLxwOAAAA4OJhZBJwXji6NT+d VaQnqNRti8qvpZbRUb3LIpwKdDs1EWtR++ZGa/ughpci8rel5babVcpKrzMTmvJNqDkb1Vy2 rPxcvxadY+pwWtXS26W5oS6FUrfltJlkW0tqfPyFJsPV+wm7bfK0uxSbCCloWlPLaIeBWt8p p2c1MJfRWr6gaETqioa18wv1u9rHb2u076FsKujFeFSL+TW9noto1jaq7s3PkBWTU4pOpZTS gKYsUYU9VklWeSYXNJxtU6riebOybJ0wn1TJv3E/fe45jfiDststUrmg/Gubhme6NkcGHdZe 4flNZhXpCWnVblYpX1bfs0m5zRuLlU+nSkrnBxRRWKMB166BRLtrNSk82m3wq2tNam8payJd VJ/TKqnCs9o4gVYKHrXzKTcAAAAABny0vr6+Xq3x559/PstacAH88MMPcrvdisfj+uyzz2pd zqGuXr2qRCIhj8dz+M7Ah6gQV6gnqcDc2K6Q7p2y0uN+jdgmtBD4cBbfbm1tlSQtLy/XuJLj +eqrr5TL5fTNN9/UuhQAQJ26cuVKrUsAcIExzQ0A6pnNp5npFuVXq0wyLCSVcY5q/gMKkgAA AAB82JjmBgD1zvZQAd8x2gAAAACgAkYmAQAAAAAAwDDCJAAAAAAAABhGmAQAAAAAAADDCJMA AAAAAABgGGESAAAAAAAADCNMAgAAAAAAgGGESQAAAAAAADCMMAkAAAAAAACGESYBAAAAAADA MMIkAAAAAAAAGEaYBAAAAAAAAMMIkwAAAAAAAGAYYRIAAAAAAAAMI0wCAAAAAACAYYRJAAAA AAAAMIwwCQAAAAAAAIYRJgEAAAAAAMAwwiQAAAAAAAAY1lDrAoAPndfrrXUJwIXU3Nxc6xIA AAAAVECYBBxgcHCw1iV8UF69eqW//vWv6ujoqHUpuADsdnutSwAAAABQAWEScADCpN3Gxsb0 8uVL7gsAAAAAXGCsmQQAAAAAAADDCJMAAAAAAABgGGESAAAAAAAADCNMAgAAAAAAgGGESQAA AAAAADCMMAkAAAAAAACGESYBAAAAAADAMMIkAAAAAAAAGEaYBAAAAAAAAMMIkwAAAAAAAGAY YRIAAAAAAAAMI0wCAAAAAACAYYRJAAAAAAAAMKyh1gUAAHCexWIx5fP5XdtevXqlUqmkkZGR ffsPDg6eVWkAAADAe0GYBADACaTTaU1PT1ds2xsmeb3esygJAAAAeK+Y5gYAwAkEAoH3si8A AADwoSJMAgDgBFwul27cuHHofpcvX5bP5zuDigAAAID3izAJAIATevr0qT7++OOq7Q0NDXr8 +PEZVgQAAAC8P4RJAACckN/v1y+//FK1/c2bN4xKAgAAQN1gAW4AFU1NTSmRSOzals/n9fe/ /73iIsJ79wUuEofDod/97nf661//qvX19X3tn3zyCWESAAAA6gZhEoCK7Ha7kslkxba923// +9+fRUnAB+3LL7/UwMDAvu2XLl3SF198UYOKAAAAgPeDaW4AKvL5fPqnf/onQ/s+efLkPVcD fPgqjdiTpLdv3/IVNwAAANQVwiQAVX3++ee6dOng/0z85je/4Q9lQBtT3f7t3/5NH3300a7t 169fl8vlqlFVAAAAwOkjTAJQVSAQ0Nu3b6u2X7p0SY8ePTrDioAP29OnT3etmXTp0iVG7gEA AKDuECYBqMrlcumf//mfq7a/ffuWMAnYYe9UN6a4AQAAoB4RJgE40OPHj/Xxxx9XbLt8+TJf qAJ2sFqt+v3vf789PfR3v/sdU9wAAABQdwiTABwoHA7rl19+2be9oaFBjx8/rkFFwIftyZMn 29NDv/zyyxpXAwAAAJw+wiQAB3I4HPrd7363b/ubN2+YvgNU4PV69Zvf/Gb7ZwAAAKDeNNS6 AAAfvi+//FIDAwO7tl2/fl0ej6dGFQEfhnQ6rZ9++knpdFqSlM/nlc/n9cknn0jaGNlnt9tl t9slbaxDZrFY1NzcXLOaAQAAgJMiTAJwKK/XuytM4gtVuKiKxaJevnypeDyu1dVV5XK57bad odG//Mu/6Oeff9b6+rpyuZySyaTy+fz2vlarVV6vVx6PR62trbJarWd+LQAAAMBxESYBOJTD 4dCdO3f0n//5n1pfX+cLVbhwnj17png8rng8LmkjOPJ6vfL5fFVH6BWLxYohUTqdViwW0+rq qmKxmCTJ4/EoEAjI7/e/v4sAAAAATslH6+vr69Uaf/7557OsBRfADz/8ILfbrXg8rs8++6zW 5eAIYrGYenp6JEk3btzQf/3Xf9W4IuD9SyaTGh0dVTKZVFNTkwKBgLxerxwOx6n0n8vllEgk lEwmlUgk5HA4NDIywlcSAQCHunLlSq1LAHCBsQA3AEN2LiT89OnTGlYCvH/pdFper1der1fF YlGJREIvX75UOBw+tSBJ2hj1Fw6HtbCwoEQioZs3b8rv98vr9SqZTJ7aeQAAAIDTxDS3OlAs FvXq1atal2HI1pohmUxGly6RZZ43//qv/6r/+I//kNPp1Orqaq3L+WDcvHnzVAMG1NbAwICm pqZkt9s1PT19rCmd6XRaf//734+00LbH45HH41EymdTAwMD2mkqxWIw1lQAAAPBBYZpbHUgm k3x+GqihwcFBDQ4O1roMnFCxWJTP51M6ndbo6KjC4fCh+28txr31FbedC3LvZLVa1dTUJLvd bnjR7VgspoGBATkcDk1NTcnlch372gAA9YdpbgBqiZFJdWR0dFRNTU21LgN17H/+53+0srLC l9x2IMitD+l0WoFAQMViUaurq1WDm2KxqIWFBSWTyV2LcTc3N2+PQmpqapLFYpEklUolZTIZ SRvrI20tvi1JLpdLgUBAra2tFUe2BQIBNTU1qaenRz6fT7FYrOpi3wAAAMBZIkyqI01NTfyh gffu3//932tdAnCq4vG4wuGwbt68qXg8XnXK4sjIiKanp1UsFtXc3KzR0VFDi3HvXUw7l8tp dXVV8Xhc/f39GhkZUU9Pj3p6evaNVnK5XEokEtvrKB132h0AAABwmli0BgBwYcViMfn9ft27 d2/7a2p7PXv2TE1NTRoZGVFra6symYyWl5ePvRi3w+FQIBDQwsKC8vm8enp6tqexjYyM7Nvf arVqeXlZfr9/O3QCAAAAaokwCQBwIcXjcfX09Mjv92thYWHfqKCtEUihUEiNjY3KZDKamZk5 1cXWrVarBgcHtbq6qtbWVo2MjKi5uVnpdHrfvjMzM5qenlYsFtueKgcAAADUAmESAODCSafT CofD8nq9mpmZqdju8XiUy+WUSCS0sLDwXr/Y53A4/n97dwjcxpn3cfyXmZupSSOh18gS6QVl l9wYZUVuLqS7qCmpFuVCLKG0JF6UFEkhSZA3JBekDUmDdk2aObJr5HvJ2ihT8qjIQesp8Yv8 glQ+KyvZjm1ZlvT9zATkWY32MUhn/Ovz/z16+fKlsizT4eGhPM9Tmqalz/m+f3RCadRzAAAA 4CoQJgEAFkpRFPJ9XysrKwrDsPQ8jmN5nqebN28qy7Ir7aIbdCTdvn1bruuOPIH08uVLOY4j 3/dHnmACAAAAJo0wCQCwUDzPU1EUiqKoNNp2lg6lSTtLR1IURVpZWVG73VZRFFe+RwAAACw2 wiQAwMJ49OiR8jwfGRSd1qF01U7qSKpWqwrDUMYYbncDAADAlSNMAgAsBGOMwjBUEASybXvo 2WkdStNyUkeSbdvqdrtK05T+JAAAAFwpwiQAwELodDqqVCqlsbHTOpSm7aSOJN/3ZVmWut3u lHYHAACARUSYBACYe2maKooidbvd0via7/tjO5Sui+MdSZ8bnE6K43gKOwMAAMAiIkwCAMy9 brerWq1W6heK4/goaJpG2fZZDTqS8jxXp9MZetZoNOQ4joIgmNLuAAAAsGgIkwAAc23QKTRq FCwIAjmOo0ajMYWdfRnbttVsNhWGYekGtyAIZIwpFXUDAAAAk0CYBACYa71eT5ZlyfO80rox ZqZO9ARBoMPDw1K3U6PRkOu617LzCQAAAPOHMAkAMNc2NzflOM7QWlEUCoJAzWZzJk4lDdTr dbXbbYVhKGPM0DPP85TneenUEgAAAHDZCJMAAHMrTdOj29qOS5LkKFCaNa1WS0VRKEmSofVB YPb5OgAAAHDZCJMAAHMrjmNVKhXZtj20nqapLMu61qXb41SrVbmuqyiKhtbr9bosy1KaplPa GQAAABYFYRIAYG5tbW3Jdd3S+qjRt1kybqTNcRxtbm5OaVcAAABYFIRJAIC5ZIxRnuelTqRx o2+zZNxIm+/7KoqC00kAAACYKMIkAMBc6vf7kqRarTa0nmXZyNG3WTIYaYvjeGh98DMNfnYA AABgEgiTgLGMNv5+Ww8n/j/4J/mePaUb9/W3lTt69mES3w9cf6NOJlmWNaXd/Okg16u1b/XN N2s67z99x3G0v78/8hlhEgAAACaJMAmYOYXe/nBHj/PTP5n3numD9Q/N7vkL4PyyLBv7rFKp XOFORliy9eDne7p1ga+oVqva3d0trU89KAMAAMDc+8u0NwBcV3nvid7297T/fE1rv9zSveAn 3V0e8cGDAx0sLWlp0u85B9t/Klu/avtyvg6YOaNCo99//710WulLmfiRnvT2Vaktab9/ICd4 oQf2kvKNH3T/2Xst3/tZt/qxtnf2VGm/1ru2rSUd6EPvodZefVT9Vk21Wwc6uNAuVCrglj79 zHl+hrQZAAAAOCfCJGAM23+i719t68OPL/Vi7O+de3r13W09tza1+3RVklHvB1ePt0f8iri0 rHuvt/R09TzvAfCliqIYeUrHGHOxLzav1Frf14//eam7S5K2H+lv9x9r9X+fym6/UTdfUetj TdGbTVXNhv7uPFf6z9e62/+X1h5/VPs/7/R9VSri+/qXvjr3Nk66jW7c+BsAAABwGQiTgAtZ lh9uanVpkBDV5b/Z1eXfETUcUv3f/kcdbH+jnjQ2pAIW3c7Ozthnn5dyf4kiS7R9cKBf1h/q 011q+1quVNQvJLsqSV/plrOqqiTV/6q63uvjgVRsx9qpeVqtfvqe6qoj6xLODaZpOnTSqtFo cJsbAAAAJoowCbigpfrqsU6iLz+ZdDbHQ6pCb39wtRNs6WfKkIDpWPYUvGirPvj7wYGOz7ou Lf33xNFX5z98dC6jRt8AAACAy0QBNzDWkr5a+rPT5MNb9UYFRJL2tt8q/jB49in0+e2338p/ dscFSWd7D4Avc1IR9UVuO6s6rlb775Xt/blQvNX97zZ02oWJ1VVPVv+9tv/MeortTOPPTp1u MMr2ef/TSSeyAAAAgMtAmASMtazGPVsfnq/p/uNE+p9RFdt7et9Z1+Peab9GXvQ953Ow/UoP H4baPujrl85DPY4v2BUDzJCJ3XZWf6DX4V8Vt+7r4aOHWvsx0z+6bd2StPfrM4Xb+5+K9T/s 6ddnobb3c/WevNWHW//Uy58r2vjuO91fW9OTVKrtb+v541jn+Zc5qTE+AAAA4DSMuQEnuPXg nf794KRPLMt/99uFO5JOf89xVX3/Zkvfn+GTS6sP9GL1gfTiApsDZtikbjtb9p7qjTdi/e5P enf3p/8u/PROx/8q/7X+ffw/GE8vtI2RodFl3FYHAAAAnISTSQCAuTTvt50ZY0aGSRe+rQ4A AAA4BWESAGCufX6zWaPRGDn+Nmu2trbGjrNdeJQPAAAAOAFhEgBgLg2Cls/Ltl3XVVEUpZBp lhhjZIyR5w3P2g1+JjqTAAAAMEmESQCAuVSv12VZluI4Hlq3bVuVSqW0PkuSJJFUHuWL41iV SkW2bU9jWwAAAFgQhEkAgLnleZ62trZK667ranNzcwo7uhxpmsp1XVWr1aH1zc1Nua47pV0B AABgURAmAQDm1mCk7fNTSJ7nHY2KzZqiKJQkSenGtnGjbwAAAMBlI0wCAMwt27ZVq9VK/Uie 56lWq6ndbk9pZ+e3vr6uSqWiZrM5tD5u9A0AAAC4bIRJAIC55jjOyJG2IAiUpulMFXEbYxRF kdrtdmnELYqikaNvAAAAwGUjTAIAzDXf92WMUa/XK61blqVutzulnX25TqejWq2mVqs1tJ6m qfI8Z8QNAAAAV4IwCQAw1xqNhlzXHRkadbtdpWlaCpquozRNFUWRgiAonT7qdruyLEu+709p dwAAAFgkhEkAgLnX7XZljFGn0xlaHwRNQRAoz/Mp7e50RVEcnaT6PDDq9XpK03SmTlgBAABg thEmAQDmXr1eV7PZVBiGKopi6FkYhlpZWZHv+6Vn10FRFPI8T4eHh0cl28d1u105jlO63Q0A AACYFMIkAMBCCIJAh4eHCsNwaL1arSqKoqPQ5roJgkDGGCVJUhpv29jYkDGGU0kAAAC4UoRJ AICFUK/X1W631el0FMdx6VmSJMrzvFRuPU2tVku9Xk/dble2bQ89y/Nc3W5XrVar9AwAAACY JMIkAIgJ2VMAAAOhSURBVMDCCIJAruuq3W6XOpJs21YYhur1enIcZ6ojb0VRHAVJYRiWepIG p6hWVlYUBMGUdgkAAIBFRZgEAFgoJ3Uk+b6vLMtkjFGj0ZhKKbcxRp7nKY5jRVE0NkgadCh9 PvoGAAAATBphEgBgoZzWkWTbtrIs082bN49CnauSpqkajYaKolCSJCP3d1KHEgAAAHAVCJMA AAvntI6kwfM7d+6o2WzKdV2laTqx/eR5Ltd15bqubt++rSzLRvYgndShBAAAAFwVwiQAwEI6 rSOpWq3qzZs3SpJERVEchT3GmEvbgzFGrVZLjuPIGKMwDLW5uVk6cVQUhZrN5tgOJQAAAOAq ESYBABbWWTqSGo2Gtra2FIahjDGyLEuWZWl9fV1Zln3xO/M8V6fTkeM4sixLcRwrDEPt7u6O DIkGHUppmo7sUAIAAACu2l+mvQFcnt3dXd24cWPa2wCAmTLoSGo2m/I8TxsbGyO7inzfl+/7 iuNYcRyr1+tpY2ND1WpVlmWpUqnIsixJn8bkKpXKUTjV7/fV7/e1s7OjoihUqVTkuq5arZZc 1x3bfZTnuTzP082bN5UkCaNtAAAAuBZuHB4eHo57+Mcff1zlXnBOaZrKdd1pbwNYWEEQcD37 HCiKQq1WS0mSKAgCtVqtUwuu8zxXkiRHfUr7+/va2dkZ+kytVlOtVpMkWZYlz/PUaDRO3UsY hup0OrIsi7JtAEDJ119/Pe0tAFhghEkAABzT6XS0sbGhGzduqNVqXXlQGEWROp3OUZ/S06dP r/T9AIDZQJgEYJroTAIA4JggCJRlmb799tujk0FRFE38vXEcy7Isra2t6c6dO9rZ2SFIAgAA wLXEySQAAMYwxmh9fV1Jkqher8t1XXmeJ8dxLuX78zxXFEXKskx5nstxHAVBcOoYHAAAnEwC ME2ESQAAnCJNU/V6PWVZpn6/r2q1Ksdx5HmearXamcOlLMu0v7+vOI6VJMlQGbfv+4RIAIAz I0wCME2ESQAAfIFB6XYcx6Wy7cHNbsf1+30ZY4bWarXa0SknAiQAwHkQJgGYJsIkAADOyRij fr8v6dOpI+nTTWyDkKlWq6ler0v6dJNbpVIZWgMA4LwIkwBME2ESAAAAAMwYwiQA08RtbgAA AAAAADgzwiQAAAAAAACcGWESAAAAAAAAzowwCQAAAAAAAGdGmAQAAAAAAIAzI0wCAAAAAADA mREmAQAAAAAA4MwIkwAAAAAAAHBm/w8ceta5gZD1fgAAAABJRU5ErkJggg== --------------34744F87CEF46F1D136BBE74 Content-Type: text/x-patch; name="genetic-algorithm.patch" Content-Transfer-Encoding: 8bit Content-Disposition: attachment; filename="genetic-algorithm.patch" diff --git a/doc/src/sgml/geqo.sgml b/doc/src/sgml/geqo.sgml index 5120dfbb42..5a52fb46db 100644 --- a/doc/src/sgml/geqo.sgml +++ b/doc/src/sgml/geqo.sgml @@ -84,7 +84,8 @@ Through simulation of the evolutionary operations recombination, mutation, and selection new generations of search points are found - that show a higher average fitness than their ancestors. + that show a higher average fitness than their ancestors. + illustrates in which order and how long the three steps are processed. @@ -94,48 +95,13 @@ non-random (better than random). -
- Structured Diagram of a Genetic Algorithm - - - - - - P(t) - generation of ancestors at a time t - - - - P''(t) - generation of descendants at a time t - - - - - - -+=========================================+ -|>>>>>>>>>>> Algorithm GA <<<<<<<<<<<<<<| -+=========================================+ -| INITIALIZE t := 0 | -+=========================================+ -| INITIALIZE P(t) | -+=========================================+ -| evaluate FITNESS of P(t) | -+=========================================+ -| while not STOPPING CRITERION do | -| +-------------------------------------+ -| | P'(t) := RECOMBINATION{P(t)} | -| +-------------------------------------+ -| | P''(t) := MUTATION{P'(t)} | -| +-------------------------------------+ -| | P(t+1) := SELECTION{P''(t) + P(t)} | -| +-------------------------------------+ -| | evaluate FITNESS of P''(t) | -| +-------------------------------------+ -| | t := t + 1 | -+===+=====================================+ - +
+ Structure of a Genetic Algorithm + + + + +
diff --git a/doc/src/sgml/images/Makefile b/doc/src/sgml/images/Makefile index 1e7993020b..f9e356348b 100644 --- a/doc/src/sgml/images/Makefile +++ b/doc/src/sgml/images/Makefile @@ -3,6 +3,7 @@ # see README in this directory about image handling ALL_IMAGES = \ + genetic-algorithm.svg \ gin.svg \ pagelayout.svg diff --git a/doc/src/sgml/images/genetic-algorithm.gv b/doc/src/sgml/images/genetic-algorithm.gv index e69de29bb2..170cc9ee28 100644 --- a/doc/src/sgml/images/genetic-algorithm.gv +++ b/doc/src/sgml/images/genetic-algorithm.gv @@ -0,0 +1,44 @@ +digraph { + layout=dot; + splines=ortho; + nodesep=0.3; + ranksep=0.3; + node [shape=box; width=2.2; fontsize=8]; + pad="1.0, 0.5"; + bgcolor=grey95; + + // title + // label="Structure of a Genetic Algorithm" fontsize=26; + + + // nodes + a1[label="INITIALIZE t := 0"]; + a2[label="INITIALIZE P(t)"]; + a3[label="evaluate FITNESS of P(t)"]; + a4[shape="diamond", label="STOPPING CRITERION"; width=4]; + + // connect 'end' node with 'a9' node (bottom of figure) + { + rank=same; + a9[label="t := t + 1"]; + // end-symbol similar to UML notation + end[shape=doublecircle; label="end"; width=0.5]; + } + + a5[label="P'(t) := RECOMBINATION{P(t)}"]; + a6[label="P''(t) := MUTATION{P'(t)}"]; + a7[label="P(t+1) := SELECTION{P''(t) + P(t)}"]; + a8[label="evaluate FITNESS of P''(t)"]; + + // edges + a1 -> a2 -> a3 -> a4; + a4 -> a5[xlabel="false "; fontsize=10]; + a4 -> end[xlabel="true "; fontsize=10]; + a5 -> a6 -> a7 -> a8 -> a9; + a4 -> a9 [dir=back]; // forces 'true'-edge to right side of figure + + // explain the notation + expl [shape=plaintext; fontsize=10; width=3.2; + label="P(t) generation of ancestors at a time t\nP''(t) generation of descendants at a time t"]; + +} diff --git a/doc/src/sgml/images/genetic-algorithm.svg b/doc/src/sgml/images/genetic-algorithm.svg index e69de29bb2..2db8bef230 100644 --- a/doc/src/sgml/images/genetic-algorithm.svg +++ b/doc/src/sgml/images/genetic-algorithm.svg @@ -0,0 +1,139 @@ + + + + + +%3 + + + +a1 + +INITIALIZE t := 0 + + + +a2 + +INITIALIZE P(t) + + + +a1->a2 + + + + + +a3 + +evaluate FITNESS of P(t) + + + +a2->a3 + + + + + +a4 + +STOPPING CRITERION + + + +a3->a4 + + + + + +a9 + +t := t + 1 + + + +a4->a9 + + + + + +end + + +end + + + +a4->end + + +true   + + + +a5 + +P'(t) := RECOMBINATION{P(t)} + + + +a4->a5 + + +false    + + + +a6 + +P''(t) := MUTATION{P'(t)} + + + +a5->a6 + + + + + +a7 + +P(t+1) := SELECTION{P''(t) + P(t)} + + + +a6->a7 + + + + + +a8 + +evaluate FITNESS of P''(t) + + + +a7->a8 + + + + + +a8->a9 + + + + + +expl +P(t) generation of ancestors at a time t +P''(t) generation of descendants at a time t + + + --------------34744F87CEF46F1D136BBE74--