From owner-chemistry@ccl.net Tue Jun 28 08:30:00 2016 From: "teja reddy reddyteja80%gmail.com" To: CCL Subject: CCL: correct transition state or not Message-Id: <-52254-160628072752-27327-Y3+LkutTprQ10dlPkngi1Q|server.ccl.net> X-Original-From: teja reddy Content-Type: multipart/related; boundary=001a113d6a0a1ede02053654edd6 Date: Tue, 28 Jun 2016 16:57:46 +0530 MIME-Version: 1.0 Sent to CCL by: teja reddy [reddyteja80~~gmail.com] --001a113d6a0a1ede02053654edd6 Content-Type: multipart/alternative; boundary=001a113d6a0a1eddff053654edd5 --001a113d6a0a1eddff053654edd5 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: quoted-printable Dear friends, =E2=80=8BI have optimized TBP transition state which is showi= ng -216cm-1 negative frequency but is showing only 9 points on the curve like shown below. can anyone help me is it a correct transition state [image: Inline images 1] --001a113d6a0a1eddff053654edd5 Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable
De= ar friends, =E2=80=8BI have optimized TBP transition state which is showing= -216cm-1 negative frequency but is showing only 9 points on the curve like= shown below. can anyone help me is it a correct transition state
3D"Inline<= i>


=C2=A0=C2=A0=C2= =A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=
--001a113d6a0a1eddff053654edd5-- --001a113d6a0a1ede02053654edd6 Content-Type: image/png; name="image.png" Content-Disposition: inline; filename="image.png" Content-Transfer-Encoding: base64 Content-ID: X-Attachment-Id: ii_15596c33e3e5b53d iVBORw0KGgoAAAANSUhEUgAAAdUAAAGyCAYAAACySF4VAAAAAXNSR0IArs4c6QAAAARnQU1BAACx jwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAEqjSURBVHhe7d1fjCvXfSf4Xwf75HnoBhYIECBY KLw3Itx6URi7MMLuyFcO2G377guxIgbjxU64mpXTlDdXnIEZXGr3ruHRrKiE2R2qF1a3o4lA5CG7 Czog8nCd6SZiXwVeDEA5DLAD0WjlNqOHAAECzA5vJnEsS/Ld8zvnFOucYhVZRRbJIvn9GGWxi2TV YZGXX54/VWfvsUAAAACwsJ/R/wUAAIAFIVQBAAASglAFAABISGif6t7enr41HbpkAQAAlKmhOisw 3eBFsAIAAPhCNax2GhaaMnj5v2JBsAIAwK6b6FPlaDQX9ujRI/nfs7Mz+sY3viH/63JjOGpzMQAA bC7+ro+ypA2X6U//9E/1X5P4viTKHWug0l//9V/TX/7lX8r/Mq6dustMH7xNz3/60/Rpd3n+bfpA 3yV97xWx/hX6nv7T9j16hZ/zSvC9H7z9vHju8/S2ucEp2/veK5+m560HC/x4c/tTyzMLl9d9ri67 sUy+jA/o7eeNx/iPjeTfjvl6+T7f6wcAWBLzuz9oSaMf/OAH9Mx/+V8FBiuv4/v4MYuKFao/+7M/ Sz//8z8v/xsLB+oXv0Nf+qMf0g9/qJY3n3xIf6HuVIHSJSrIv8M8RU+9/82A4Pge/U7jPX2bzd7e c/kCvfdQ7d31vW6HCvnnxK2o5YnjKaq6r/3NAnVeMsJa/tj4Ij38qndsfvjbRN8NTHNvO39UJWp8 LSh8p0H4AsBu+uVf/mX6d//P9yeC1Q1Uvo8fs6hYofrlL3/Z+m80IqS+1qAn3/w2vfCEXiU899pr xBFG9AS98G0RFK/l5V/TPPkk0Xe+60uE73WpUygYARhhe79wk57qdL1gE7e6nQLJTI1Rnrk8lxdl fZ/+Qr4M99j8kF5TB0N54gV6wfw7wBMvfJUK732H/IcDAACC+YM16UBlE6HKLcrmsrAPvkvfec8N rBi4+dXXDHrzK1+lJxu/Y4ShCKVvvk/Vr0QIQHN7T3yevvRUh7ruhmQw53XILxnv66kv0ef5B8a8 x2YWX1O7am7mWupL1KH3qPFFsT6kKR0AYJuZwZp0oDIrVP1t4qPRSC6u3//937f+G9lTN+kX9E3V /8lf9vM0Qz5H+YIRhhxKpAMqlifo8196it5X1UWj6XdZdJDx6+7m6YfffkGUQDOOTRwfvP1NL5wt Ijy/qGq/sin5j6r0/kt8rJ+j1374pqgl6yZkq2oMAOtgDuyZtsDmmNr8u7+/P16Yf6BSZO+5/afc bPlt8WXPX+4zPPeaHT7ac18RIfFNVeP83u+I8Pjq5GMC+bb3xOe/xG3JYjsf0F+8/xTdjJNsVk0w ymAmHWQi4OxmZ8E4NrN54fzFxpP0ZsDxoQ/+gt4XR3f8G+GJF+irhffI14UMAClgVmSmLZAcs8nX bApOSuQ+1evra2ugEv8dyRO/QE+O+xATwE23on763e+9Td98v0pfmbfCNd7OHLVdEVTfdgcV/dDt G45APO+3q+/TN90qur8ZeiZjwFOc/QIAwEQfqr+PNQkzQ9U9N/Xy8pKOjo7o61//uvwv/+0/ZzXY cyQql6KGFfP0lIA+VeUJeuGrT1LjpQbRlz4frZbKJrbHTcCiXHG3syAeYPRk42u66ZtfC48G9p1m I2rCb8c6WAb5I8ZsIhc/PsaDsAAAdlPYoKSkg3VmqJpNvjdu3JDr+L9xmoJlk++bRC+Nm0xfover v22NBo7lua9Q9akCfXXuDSjcBPyU+N+X4nfKLkD/yHBPh+Fmadnv6R4bsXyN6PNzh+Bz9Jq5PXkq k1ur5T5pDFQCgMUE9fuaSxp95jOfmQhUlxus/JhF7T0OabDnA8N3cU2Ug5ObfMvlsr5X1WDN9e7j AQAAdtXMUI0KoQoAALtuaqjGhVAFAIBdFhqqAAAAEE/kU2oAAABgOoQqAABAQhCqAAAACUGoAgAA JAShCgAAkBCEKgAAQEIQqgAAAAnZG41GOE8VAAAgAaipAgAAJAShCgAAkBCEKgAAQEIQqgAAAAkR odqlysEBHYyXIzob6nvlfebfAAAAEEbXVB2q90c0Go2oXyeqnZxRvBxF+AIAAEw0/2bKVSr1OnSB gAQAAIglXp/q8IyOjKbiSpdXci21SC3qUS0n1suVQzo78j8OAABgu02E6vCsQS2nQMcZvWJMhGeu Rodt1Uw86tdpUOQm3zw1R20quU3Izbx46CnVDtvqcWLhVQAAANtOh6quZYpaZa52SO3LMk1k6vAh DUR03nYDMlOmaqlHV9f6b9ONLDmtIh2hkxUAAHbIxECl0ahJC1csReBeim2d0wmafwEAYGdE71PN 3KRDatF9NyCHZ9RoGTXXAJnyJfXrDg0eosYKAADbL8ZApTw1ZT+qHoCU61Ch79Zq83S7ZAxU6lbG g5S4OblanmhMBgAA2DqYpQYAACAhMWqqAAAAMA1CFQAAICEIVQAAgIQgVAEAABKCUAUAAEgIQhUA ACAhCFUAAICEIFQBAAASglAFAABICEIVAAAgIQhVAACAhCBUAQAAErL3L+tNXFAfAAAgAQhVAAAA 7d7dl+nRo0f6r/j2Hgv6NgAAwM569fU3Fg9VzKcKAAC7bn9/P5FQxUAlAACAhCBUAQAAEoJQBQAA SAhCFQAAIKJKpaJvBUOoAgAAROAG6rRgRagCAADM4A/SsGBFqAIAAExhBmiz2dS3goMVoQoAABCB G6hmsPohVGHNulQ5OKCDqEulq5+3WsM387oMeXpzqFeG6VbsMs9Y1vSSNkasY58yQWX31k1f8tNe bNhnLP8mbdgh2hj+IA0LVoQqAEAKvftKLiBY9Y/QYkv/7fPuK5QT908NZIgtLECD1iNUYc3y1ByN aGQs/dc+q+/7LL3Wt+8bNfP6vni6FffXfEV8La3OZ1/r2+UPWOZ8SbAFSu2Az0T/NfHJV9595dT4 vA7pzXyRvDgtUdt8Xruk1/Pzfm3javXbAqEKAJAmmZfoW+Mflu/Rn7vh2D2lV97Vtz/7GvVHTfGT 1JBvGoH8Lr1yin6FdUCowkbzaqD24vVTquYyr7WsRUV+jPuAFPVNzexrC+l8DT4Gk/2PYcfK2y7X hALuHy+qlm9ux1+kafdNSODYz37/lfmObbTjsSrd++6H+LP02rdeooz+yyICuevWXNEEshYIVdhQ /rC0tYriS2/Gt7r8op3WN5W2QR+tou81TTsGoqaSi9O3xtvKeTWhKfJ3vObJ1n27PN73/mt0Z8p3 +uLHfvH33xJ4bKMdj8QN36RfG+/4KfpFmZ5D+vP35ApxbAv0hcBEhTRAqMJG6laMviXZFKZ/nRv9 UfxFWemqPluvu0n3QzWJTsdfXGbfVJ/GLW/vdujfLpiqPNgkuJajlynhMe6PtV7TffF1r1jHoNTW 5eelLV6REt63ZrxmUaMJ3ZbRTzeW+QIVvFQdl0dUpcbb+GzhC8E1Kam78LGP/v7r2z5zH9ug47EA Gf7+z0TuFfGTSCm13Sbea3p/nLO/OOXYQhKur6/nXhCqsIHsGlG/azSFcfOX8cVn16RM5gAps28q Q18YJ8a79P61vrliPICl+5J+VeI1/cb4Jbl9bL5jYDX1iddm9K11JtKJB4CZr3nKtvJN4weJyzxG LXIPsdk8WZhalVr02C/2/i90bAOPR/Lc0EcL7uZBqMLmGf65+PrTgn6152+Pa2r03p9HakY0awq5 BNv8Zo7+NQMhDvMY6NMozNdg1nbenfXLYNbxDJD5QmFcw1PBZQRR6TfIzazp5jz2ib7/AeY4HvOy R/96NXVu4bBr2TfoSfeAz/OaYGUQqrCz1CAXo5lvWy3jS9jfBGw0/ZZuz65e7cyxjyVDL3W9pvtW 0RwIlaFffErfTKBbApYHoQqbJ/OL5H6/BAaG8QUfWtMYvkm/NX6Qfb6fd55sipnHwOpPDVhm1YZn Hc9AdhNwcTxiqEQzM3XRY5/E+z/NXMcjKXm6Mz4GLfoto0M8f9uN23fplV8L6YsXxzbv1vzjDNSC xCBUYQPlyft+8Y0U5S8VY0joZK1J95tdvz9uHhUPsvoXvUE0aWYcg4mRq3wYvFNIZo8A9h3P8bbU KSVhI2zNJuAx61iGWPjYL/L+RzHf8UiKeVzf7fxb77Xl7xgDubjJ33dKD792c5DTXK8dFoVQhY2U b3rNZOoLRv86N75UuAY3OdBDnWpy8FvveYHAoeQ+P+EmyZmjf3mZs0ZhHQPrNZh9kyX6jQgdnOZp Mt62ZpxSYg3yUSJ9kZt9nnMe+/nf/2jmOh5JMZvWraZeu3lYFEydcx3w2rkvH4Oc1gOhChvKf6qM TQ4AMb5VrC9JqUDfMk492UzqGIQ1mapBUr6r7oThUbNzHA+vSZJFaPqVuNyLHvt4739scx6PZNij oO0rI+mR06FDkFVz+nh0M6zc3mg0eqxvAwD4cJOnW0PjL2x/SPMIXl3D5L7dra8ezToesKn29/fp 1dffoHt3X6Z+v6/XxoeaKgBMYVx0IEjMUb+bb8bxgJ2HUAXYeeY1bs1rBvN6o59zYhCSqKW6o3Y+ O/2yhJtl3uMBgFAFAB4AMx5xpAdyyUAxB+Z8ll4bp6Z70QYvYKZflnDTxD0eAB6EKgAQX37Pug6u iS/VN+qGXyWp1N6+gTGLHA/YaRioBAAAOw8DlQAAAFIGoQoAAJAQhCoAAEBCEKoAAAAJQagCAAAk BKN/V+T0bHzKOAAArNmdsn395KRG/643VLsVOhjPo+S/juaQzo5yVOupv5x6ny7L9olhw7Mjyl1V I1xvlE9Wb1C2f0nuJuRz3Y2TQ3XjPs/k8+bFoXrv7ov6L+Wdd96lz30u+GLoq4Ry2FCOSTgmNpTD tmnlePX1t5YWqutr/h2e0VFxIMJMT05cH1Dx6ExEqdKtiEA9dCdfbtNhLUfuDFndirrCiReK03Ur vimlRJjnaofe5MjtQ6qdePt2TTwPAABgirWF6vCiQ71SdVwDzJSrVOp16IKTTQRuoyVqj+PLgKnp jtwKab7pBrGjVkzBNdJGtm5P4cRXSzFrxTey5PSu6Fr/yQKfBwAAMEWKBirdoKzToytOtusr6jkF Ol6wyZXD+aRToPPyTb0imAx4JytKoEV83qLS0FzCUA4byjEJx8SGcthQDs/aQjVzXCCn1aAzt811 eEGdHtHg4ZCGDwdy1YVu5uXFbfqNbkhnJx0qnJfDL/TNTdCyGZmoPn5chOcBAAAEWNlAJXNg0HjQ kTlQySlRiVo0KPTpnE7kY3n2ftnky+GXE0HnGzA0baAS33citqQGN80YcGRs//gi+vM47GfhZmrG A5WefeZpeZuZv6i4c92F9QrWK1ivYL2C9coi69kyByql6JQaNdr3qiqClETYNrLUv/Rqizw4qZG1 RwCHh6o9ctgUNIqYqe23qdApxnreNBy6Zqhi9O90KIctLeVgOCY2lMO2aeXYztG/frL516Esd2wG DByKJ0PlSz2yVy5tUQvm02ZGIcE4JNXifCPm8wAAADzrC1Vu+j2okNtV2j2teaOBM8dUcFrUcDtc h2o0cGHhkUsK13DNfYudi9ppctsHAIDdtL5QzTfVual6IFJxUKf+uBmXa5rq3FQ5UClXo8N2hAsw yIFHRliGyJQvrX0fyPNlF7/AQ1xpaC5hKIcN5ZiEY2JDOWwohweXKVyiWX2qAACwervRpwoAALDh EKprxCPV0gDlsKEck3BMbCiHDeXwIFQBAAASglAFAABICEJ1jTBizoZy2NJSDoZjYkM5bCiHB6EK AACQEIRqAuS5rgHLTHv/QC0AALAVEKoJ8C5raC+hdJi+8+AB0eO/W3u4YuSeDeWYhGNiQzlsKIcH obpqHJ4iSPfoMd269Tna2/uUClY3XAEAYGMhVNeAg/TBg3fGiwzWlOMyugsAAARDqK6SrqWGWlNt ddaIuVX9CMAIQltaysFwTGwohw3l8CBUYS57Ivx5AQAAD0J1lXRN9PHjH8n+VHfhv6VZNdkUeSzK yYsbrtMWAIBdsd5QlXOquqeg+KdsG9LZkXd6ypE7t6pBzotamTXRG+tS5eCIzE2oOVXd7Zv32fud vD8ZKkj3vEBdo1kj5kJ/BAhuuE5bgoLWvzCMILSlpRwMx8SGcthQDs/6QpXnPpXzmKrTT+T8pkdn ItKUbiVHtcO2Pj1Fza3q5me3osIuV+upFTN0K0Vq6duSCPNc7ZDa7ukv7UOqnXj7JnLG5VJLgnOt ipCRNVIdJJL7N9+XWuoHwDw/AoKC1r9wsN66dWsibM0lLgyuAoBVW1uoDi861CtVx2GVKVep1OvQ BSebCNxGSwTbHXfS8jw1Rbi5c5jnmyrs+nVHrZiCa6SNbJ2smfPyTfH8ptiqdiNLTu+KrvWfRId0 c5kTlosQ4UVOZMthof/eZRysDx48mAhbcwkKWv/iWtXgKgAAU4r6VG9Q1unRFSfb9RX1nAIdLxps IpxPOgU6L9/UK4LJgHeyogTsmq6iVYAXtsf/J8Ji3TZl5F5Q0PoXf7jOAyMZJ+GY2FAOG8rhWVuo Zo4L5LQaXl/l8II6IswGD4c0fDiQqy50My8vkbpOLUM6O+lQ4bxModnMTdCyGZmobj1uQA2jXzX+ vmFd3HANYtZozQUAICl7o9FItkIuGzfDun2gTr1Pl9zuywOVirq30ylRiVo0KPTpnE7kY0tt3eTL 4ZcTAdm3+zblNq+qNHLbhQ1834nYktyPHKjUoKzv+WPm9sm3r5B9Mw7cWbiZmp2etejZZ56Wtxn/ ouIvdA4As3Pd/KWVlvWbUk6Xu54HVbm4Lzjs8UHBuomvl2G9gvUK1ivmevbq62/RnbLVKUj7+/ti /Rt07+7L1O/39dr4Vhaqs/Go2xxdVUWQkgjbRpb6l17tkQcnNbI6jLXwUFXbChrHNA50n6Dtu6bd Nw2Hrhmq9+6+KG+73LBaN/7w+T90plWVc1Y5VoXLwYOmgqzy/UrL8WBpem9QDg/KYYtajmWGanr6 VGXzr0NZ7ticGDgUV4bKl+bo3baoBasRvcHBOCTd4gwgcXgGLfwDw78AALjWF6ryHFXv3NTuac0b DZw5poLToobb4TpUo4ELC49cUriGa50X2z0VtVq1/cn7KlRMcN+w2aIGLS8AsHvWF6r5pjo3VQ8G Kg7q1B8343JNU52bKgcL5Wp02A7pDzXJgUf+i0hMypQvrX0fyPNl1fan3bet0tBswza1HEFBy0vc oPWfV5uW48HwGbGhHDaUw5OiPtXtsyl9qtNsQhk3SXiwPpbn07r8V64CgOTsRp8qwA4wa7LmAgDb AaEKcsRcGqAcNrfJOLx2uzp4b2wohw3l8EQLVdlXqfsYA5fkLzgPsEu4qdc/aYF52cY0BSwAhAsP VTNITzp6ZbjOCQIWYBEcpO7iZzYVmwGLkAVIl5BQ7VLFCtICnY/P+QxazsUjPJ2T2SNwIT3CRszx FzZ/ia8KRhDawsphBqw/ZJcF740N5bChHJ4pzb9GkBpXNgpmXmzBDlgAWK6wgF1myAJAsJBQzVNz ZpCG4YA1plXbAXb/srcArJoZsP6QBYDlizZQCaaym8K9ZVNg5J5tm8qRVMDivbGhHDaUwxM9VM2B S0dnxGOR+ELzB5gXbSvxFy9/EcP2CAvYeUIWAIJFC1W+Tm+uRsFzd9+nMwz3BdgoZsD6QxYA5hch VId01uA5T9UsL/26o1YL+Waf6oMW1WqnGO27wTByz7aL5QgLWDdk8d7YUA4byuGJEKrXdCWqqE79 POCi8hkqV+3rJwLAZjMD1h+yfv5JAAB23cIDlYaYiBRgq4UFLAcpTwLgLghWgEiheoOyDlGvliP/ mCSeezRX42psVjxqDnJOVfcUFP8FI4Z0duTed0BHAf22cu7TSAOlulTxXelJzZvqbt9/FajZ+94m /hFz/IXJX6CrhhGEtrSUg7llMQN2HfDe2FAOWxrKESFUvSbeVvFAhWivRjkRNvK2UKrOcU4rjyaW c5Wq00/kHKZ6VDHrVnJUO2zr01PU3KpufspRx8b+Z+lWisS9wmMizHO1Q2q7p7+0D6l2Em3fAAAA YaI1/+abMlwme09LMpjGc4vHMLzoUK9UHffTZspVKvU6dMHJJgK30XKofsfdcJ6axn7yTTeIvUFT YbhG2sjW7bLL12NcoOJGlpzeFV3z7Rn7BgAlaBIAt2kYYFfF6FNV4aJqb+6S5JWTuJm5R1ecbNdX 1HMKdDzfJZ08IiBPOgU6L9/UK4LJgHebsJPa9wbByD0byjEprCz+SQDcpuFlhSveGxvKYUtDORYe qDSvzHGBnFbD68scXlCnRzR4OBwPfrrQzby8xG9+HdLZSYcK51OaprkJWjYjE9X145LZ9+ZaV38q bJdlhytAWu2JGudjfXs6DiD3AhBOnfqXZboWwVOkNo0itI2OBzUJTr1Pl9zuywOVirq30ylRiVo0 KPTpnE7kY0tt3ewq9y0Csn9pndYjt3lVDdw/33citiT3IwcqNSjre/6Ysf3jC1XOWftmHLizcI2e nZ616Nlnnpa3Gf+icgPM7Fw3f2mtYz2XiefxdK1qvwzrlW1c7war+9la1X4Z1itY73n19bfoTtnu 0Nzf3xfr36B7d1+mfr+v18YXLVTN8GNWqJaonr1D5cC0ioNH3OboqirCjMT+Glm5D3erPDipkdVh rIWHqtpW0DimcaD7jLd/8zTSvqPg0DVD9d7dF+Vtlxuq68YfPvdDt84ymeVYJ5RjUlJlccN13s8Y 3hsbymGLWo5lhmqE5l8RUKu4opJs/nUoyx2b5sChuZhT0fHCg6xU+YODcUjj020X3jcAhOEw5YXD 1Q1YgG0SIVSXdEUleY6qd25q97TmjQbOHFPBaVHD7XAdqhG5hYRGD3EN1zovtnsqarV6+0veNwAg XGF7LTxQae4rKuWb6txUPRioOKhTf9yMyzVNdX6oHCyUq9FhO6Q/1MT9nxMXkZiUKV9a+z6Q58u6 259z3xvMbS7hL7d5m+WSkIbmI4ZyTFpWWeKGK94bG8phS0M5IoTq8q6oxOE2bqKdmBTdPoUnYCyS er55R6ZMl4Gn+fC27GC09u27L8q+ASA5qLnCtogQqku6ohIAgA/CFTZdtObfJVxRCdKDR8ylAcph S0s52KrLEhaueG9sKIctDeWI0ae67CsqAQDYUHOFTRMhVPnCCds/U8uu4y8s/vICSCM3XG/duoVw hVSLUVOFbYWRezaUY1JaypKWmis+IzaUwxMhVN3Rvye+OUcBANYjLeEK4BchVNXFH0SsUi2nz+uc WGafG7rNgo/J7OsCA8BiEK6QNmj+TYA9eMtbNgV/GfEX07phBKEtLeVgaT8mqw5XfEZsKIcnQqgG jfr1LxgFDADrh5orrFuEUFWjf3dpTlEA2GxB4bq396nxArAsizf/yuvtHmEQEywMIwhtaSkH29Rj 4oXrp+jBg3fGy6LBis+IDeXwTAlVVUM9OCgST/zGlygMGozDF5xXFysEAADYbckMVHIKhJnRNhM3 jfEveQAAWNyUUHUHKKlr/pba/sFJxjIxw0xEck5Vt9brPy1nSGdHXo046IpOcl7USJ29XOu2m6jV nKru9o37rDIZy9GZKNF2wsg9G8oxadOPyePHP6Jbtz43XsTPSXXHnPAZsaEcnmRqqvPgvlg5j6kK Zjm/qRFc3UqOaodtHdxqflM3P7sVFXTuLDmzdCuqCXtMBGeudignA5Dbbx9S7UTvW04eoNeP759z InYASA0OVm9Rg5gAkhY5VAcPk62nDS861CtVx/OYZspVKvU6dMG7EYHbaDlUv+OeqKNqze5sOPmm Crt+3VErpuAaaSNbt2fYkcFpnAZ0I0tO74qu9Z9+3fstcgrHmN4OYIsgWGEZ1ldTncCXQ+zRFSfb 9RX1kuinFeF80inQefmmXhFMBnzYROsy4EtUtWcx3wpufypG7tlQjknbekzmDVZ8RmwohydCqC7n 2r+Z4wI5rYa3zeEFdXqqRjx8OJCrLnQzLy/xz5Md0tlJhwrnU/p7RWAeyWZkonrI47qnfOcdXNwC YEuhxgpJ2huNRo/17RA8yMfXJzmBJyufflUlboZ1+0Cdep8uuebHg4KKestOSWylRYNCn87pRD6W B0fJJl8Ov5wIyP7luLmYyW1eVWkUMEs633citiT3I19Dg7K+54+FbD90vcZhPws3U7PTsxY9+8zT 8jbjX1RuTdHsXDd/aS17Pe//wYMH8vYq94v1CtYraVm/7n+PWK8sez179fW36E7ZHiuzv78v1r9B 9+6+TP1+X6+Nb2WhOhuP9s3RVVUEKYmwbWSpb4wq5sFJjawOYy08VNW2gsYxjQPdJ2j7vK5I7cDQ joJD1wzVe3dflLdd7j/idTG/RPwfunVAOWxpKQfbhWMS598jPiO2TSvHMkM1QvPviq79K5t/Hcpy x+aMgUOzZah8aZaPTwty5EjjoEDlENYtzoYu3bcGSwHANuNA5WAFWMT6BirJ80G9c1O573I8Gjhz TAWnRQ23w3WoRgMXErrCBNdwrfNiu6eiVmtvf3jWoNYWX9Ri3bVkgDRCsMKiIoaqfSGGyWWO+VTz TXVuqt5GcVCn/riZlWua6txUuf1cjQ7bIf2hJjnwaHZZMuVLa98H8nxZc/tdOuU+3eqcF7XYMGlo tmEohy0t5WC7dEyiBCs+IzaUwxOhT5Urldy3WKJSqxXSt5pEn+r24cDm5meWtj5V1FQBpsO/ke21 5j5V7lvk/96Wfavy4kIl70pHslhh53gCAGwoNAXDPCL3qZZuB9VD83SHr2q00KAiWDX/L3AeMZcG KIctLeVgu3pMwoIVnxEbyuGJPVDpBl8JYvCQ3Gs2ZG4e6lsAANsHNVaII3Kotu6r4T8yRHs1OtWj gfi6uAAA2wzBClFFCNU83ZYdp/fpjE9xyd+W/ajupOXFgUNO6TYGKW0wjNyzoRyTcEzsYMXxsKEc nkg11XyzT/VBizrqL2r26+TND1Og8zmvOAQAsElQY4VZIjb/qisUja9GlCnTpXu1onknKN8i8lzX gCWN+AuBvxgAYD4IVpgm9kAlmKROL5pcNgVG7tlQjkk4JjaeiCINwYr3xZaGcoSEKl9EP7j2FbzM cUUlAIANhhorBEFNFQBgTghW8AsJ1YCZadSllKjtXy8XXKJwk2Hkng3lmIRjYjPLsc5gxftiS0M5 UFPdIfwPH4OUAACWB6EKALAgNAODa72hKudUDRvsZE83d+TOrWqQ86JWogyR4oFXR2RuQs2p6m7f vk9NIRdy3xbCyD0byjEJx8QWVI51BCveF1sayrG+UOXgkvOYqn5ZOb/p0dn4msLdSo5qh95sODy3 qpufPBUdB16u1lMrZuhWivaUdSLMc7VDr3+4fUi1E3ffIoDl/K3GfTmMbgaA2VBjhbWF6vCiQ71S dTwxeKZcpVKvQxecbCJwGy2H6nfc4U9q4JR74aZ8UwVen2fImYFrpI1sXU1R58o3xfONwVU3suS4 M+0MH9KAHMq6c9nJyzIO6OGG11bRnwqwGgjW3ZaiPtUblHV6dMXJdn1FPadAx4teqkmE80mnQOfl m3pFMBnw7pywmTJVSz3qyHTnTTSoZYT/NsLIPRvKMQnHxDarHKsKVrwvtjSUIyRUAy7+UOQG1BYV /evlEr95NHNcIKfV8PorhxfU6fGsckNRWRzIVRe6mZeXSF2nliGdnXSocD7lMoq67zRXI6obj+Oa cPUqJ/ebu6rSCNc2BoCYUGPdTXuj0eixvm3gUPX1Q07F569OP1eVm2HdPlCn3lfXEeaBSjKseWVJ bKVFg0KfzulEPrbU1k2+HH45EZD9S6vGKLcZEnp834nYkrpeMb+eBmV9zx+zts8DpHJ0VdX7lmWk wNfHoTsLN1Oz07MWPfvM0/I2419UbpOs2blu/tJKcv2tW7fkpdWWtX0X1itYr2A9yX97ZtfLqvbL sF4x17NXX3+L7pStTkHa398X69+ge3dfpn6/r9fGFxKq62CEGYkga2Spb1ysnwcnNbI6jLXwUFXb ChrHNA50n/H2b57Swf3b1jaD9h0Fh64Zqvfuvihvu1bZzzltX/zh83/o1gHlsKWlHAzHxBa3HMv6 t473xRa1HMsM1fT0qcrmXz1AyBw4NBc1qw4HmlraohbsyJHGwcE4JN3irJqeBw/1SODtsMrwBoBJ /O+P/x3C9gvvUzVOb4mHa4kR+ljlOare47qnNW80cOaYCk6LGm6H61CNBi4sPHJJ4Rqu1Q/cPRW1 WrV92dfrjkJmCe8bAHYTgnU3TKmpdujkQA8UijBKyD139ODgRE9mPkO+qc5N1fsoDurUHze5ck1T nZsqtynPGw3pDzXJgUezAz1TvrT2fSDPl9Xb57li5bmp+r6o+95gaWi2YSiHLS3lYDgmtnnLkXSw 4n2xpaEc4X2qcvCOqD3y7VKJSq3W1IFLpXabqMiDm7iZdbtDKCoO5TT0qaL5FyBd8G9yvdbTp8o1 NrdP8jafTDOLO7MNAjVN8I8XIH2SrrFCekQbqCSvQOQO+gleAs5qgQ3BI+bSAOWwpaUcDMfElkQ5 kghWvC+2NJQjPaN/AQB2DGqs2wehCgAAkBCEKmDkng/KMQnHxJZkORapreJ9saWhHAjVLYZBSgCb Ac3A2yNCqKqL68e/oP3ukOezBiwAAFEhWLdD5Jpqq+iGRfwZabZd0GhoXjYFRu7ZUI5JOCa2ZZUj brDifbGloRxzNP8a07/NfSlDAAAI4gbr3t6nxgtsjgih6l7UQSxt+woU1KtRTgfs0XhiVAAAWMxj evDgnfGCYN0c8Wqq5kUgfAHbc6/Ti87XVIgzSAkj92woxyQcExvKYUM5PPFCVc4so5t+3cnF/VpF BCsAAOykCKGqRv8GBqlTp75bczVrr637GMwEADCnx49/RLdufW688N+wGeYYqFSithuil2Wyrp3P zcP+ftdpzJrvxKhinpfVvS+4z1bOixqpVsw/DI7I3ISaU9Xdvn3f9HJtH4zcs6Eck3BMbKsoBwep u4SNCMb7YktDOSKHaqnt1kiblMi183lqOTmPqdqunN/UGE3creSodtjW+1Rzq7r56c7dmqvJielm 6lZ4SjqDCM1c7dD7ccDzp57ofc8o1yaI058KAOmHc1g3R4RQVaN/I89CIwczzQ7e4UWHeqXqeJq4 TLlKpV6HLji9RLA1Wg7V77hbscuQb7qB56gVU3CNtJGti/q1wV/GG1lyeld0LW5OLRcAAMAU8fpU Iyzzj1G6QVmnR1ecbNdX1HMKdLzovKwinE86BTov39QrgskgdbKiBEGMcm0pjNyzoRyTcExs6yhH UG0V74stDeWYo091Or7yUpRzVjPHBXJaDa8vc3hBnR7R4OGQhg8HctWFbuadL6yHdHbSocK5r9/X xE29Ytu5GlFdP25auQAA1gnNwOm3NxqNHuvbIbimWqQWj/T1D0ziUBKJ1HPvc/+Wg5nsJmBuhnX7 QJ16ny65fZUHBLkjip2SeFaLBoU+ndOJfCz348omX7ldEZD9y3GzLJPbvKrSKKBtmu87EVuS+5Gv oUFZ3/PH/NsPKZfalofDfhZupmanZy169pmn5W3Gv6jcvk+zc938pTXv+lu3bll9qklvn2G9gvUK 1iurWs/fHQ8ePJC32ar2yzZ9PXv19bfoTtkeVLu/vy/Wv0H37r5M/X5fr40vcqiKlAzsV1VhyYN+ dIjKQOKHxx3QxKN9c3RVFfshsY1G1gpxHpzUyNrBFh6qaltB45jGge4TtH3FKFe8FyRD1wzVe3df lLddbqgmaZ5t8ofP/6FbB5TDlpZyMBwT27rLYf4gx/HwRC3HrFB99OiRXhtf5ObfsObPzM1DfUtx m25jk82sDmW5Y9MYODSfDJUv9cheubRFbdORI3qDApWDM7TYZrkAAFKAA5WDFdInQqjyQB11GcKJ fk1uNuVmUj3IZ9zEGzroxyDPBfXOAe2e1rxRt5ljKjgtargdm2I/PBq4sPDIJYXLaZ1/2j0VtVq9 /WnlAgBICQ5W7uqBdIkQqqLWd14X9Txz+je9yP5TolLV7GstUdvf9xok31TngOptFQd16o/bV7mm qc5Ndfdz2A7pDzVxyEe4WEOmfGnt+0Cel6q3P7Vc2ykNzTYM5bClpRwMx8SWpvcmDfC+eCL0qbr0 gCX9l8JNqhHCbkdxKK+yT3UZfbQAkG74dx9fKvpU3QsweP2UvCBQAQDWCf2r6RIhVNXFHzBf6vbi EXNpgHLY0lIOhmNiQzlsKIcnRk0VAADSCLXV9Igx+vfEnskFAABSA8GaDhFC9Zqu5EUUelTL6dGy E8v2T4+WdosMVsDIPRvKMQnHxIZy2FAOD5p/ExD8Q2P2JQwBAJKE2ur6RQjVoFG//iXuJQm3S/Ax UafSAACsEoJ1vVBTBYzc80E5JuGY2NJejlUHK94XT/RQlVcr0k2bR2fEY5b4IvQH8edkAwAA2ErR QpWvh6svSTjpPp1hWPBaLTJICQC2E5qB1yNCqA7prMEXJ1SzvPTrfBVgJd/sU33QolrtFKN/NxhG 7tlQjkk4JrZNKceqghXviydCqKpTapz6ecAlCTNUrtrXTwQAANhVCw9Umnv+VCanWXNPQfGf68qT g7v3BV8mUU7hFqlPly+1eBRy8YqA+6xyHUxOeQcAsCHQDLxaEUI1fD7VWPOn+vHAJznlmjr9RE63 pgdAsW4lR7XDtj49RU0D5+5fDpASYSf3HUG34p9dxzN5nwjZYotKbX1qTLtErWJ6L26RRH8qRu7Z UI5JOCa2TSvHsoMV74snQqh6Tbw8n6oMsl6Nckao2fOpRjO86FiTf2fKVSr1OnTBqSoClyclr99x z35V58q605rmm24Qe/27YTj4G9k6BTVSB943fEgDseb2eNe3xV8DehhYywUAAPBEa/7NN2VtcTKY StQ2wm4xXCPu0dW1uHl9RT2nQMeLTisnwvmkU6Dz8k29whB2n9y3WfM2ygUAsKHQDLwaMfpUg66s NP+VlDLHBXJaDa8vc3hBHVHxHYgqodtPe6Gbeefr1xzS2UmHCudBtejw++S+D28a6zN081CVa1th 5J4N5ZiEY2Lb1HIsK1jxvnj2RDg+1reXatz/Kjj1Pl1yuy8PCCrqHk2nJOq9LRoU+nROJ/Kx3K8p a8GiVnmUEyHYtydFl9u8qtIooKrM952ILcn9yMFIDcrq58+6z79N7sNtZHWZDRz2s/CPD3Z61qJn n3la3mb85rv9oWY/gPmhiLL+1q1b4z7VRbaD9QrWK1ivbON68zuDrWq/LA3r2auvv0V3ynbb6/7+ vlj/Bt27+zI9evRIr40vYqjySNwchY8L4mbgRa//q/ZxVRVBSiJsG1nqX3o1yaBgCw/V8PI69TYV OsWQ+8T2b5769m2UK+YL5NA1Q/Xe3Rflbdeig4wWfT4A7KZd/+5YZqhGav5VI3G5JrlEsvnXoSx3 Zt7IktO7ovm7MTNUvjSbqbk/WF284rKcn3KfiNGJffN5urpcW8r8RbdOKIctLeVgOCa2TS8HB2qS zcB4XzwRQrVL92UL7e0ps9XMUUuV54J6p6p0T2veaODMMRWcFjXcDtehGg1cWHjkUgSZm3RILbo/ Lth98dch3VzBrgEAViXpYAUl8kCl0vgck4Tkm+rcVD0QqTioU3/cvso1TXVuqhyolKvRYdvuTw3E fa8LT5iep6Y8N1UPkpLnrO721HYAABBNhD5VHshTpFapHTggCMIts08V/akAkIRd/C5Zc59qnm7z vs3TXwAAYCugGThZMfpUe1TL6SbRiSW9l/EDAABYlch9qrC9MHLPhnJMwjGxbVs5Fq2t4n3xRGr+ DR/16y4YyAMAsMnQDJwM1FQ3EAYpAQCkU0io8ojfiNfb9Z1vCpvHfwmvdUE5bGkpB8MxsW1rOeat reJ98USvqcpzQMMm+t5twYO3Zl8XGAAgbdAMvBg0/yYguJ9ZnZ8KALBpEKzzQ6gCRu75oByTcExs KIcN5fAgVDcMBikBwCqgtjofhCoAAARCsMaHUAWM3PNBOSbhmNhQDhvK4UGoAgBAKNRW45kaquPp z3jJ1agXdP3forww8HzkOa7utvznug7p7Mjbz1HAuTzDsyM6iHYyLVVCTwcKvy/69lcD/akAsA4I 1ujWV1Pl816LA6r31ekncm7VozMRpUq3kqPaYVufnqLmVnXzrVtRQZur9dSKGbqVIoVFf9B9cbe/ 6TByz4ZyTMIxsaEcNpTDExKqUa73ay7xr/07vOhQr1QdTzyeKVep1OvQBaeqCNxGy6H6HXerqjzu dK75ptpvv+6oFVNwbbORrZM9c54Sdl+c7QMA7ALUVqNJUZ/qDco6Pbq6Fjevr6jnFOhYB+7cRDif dAp0Xr6pVxim3QcAABMQrLOtLVQzxwVyzInPhxfU6RENHg5p+HAgV13oZlhe4ndtDunspEOF8zJN ZvO0+3YPRu7ZUI5JOCY2lMOGcnj2RqPRY317qbip1e2jdOp9uuR2Xx6o5A50ckpUohYNCn06pxP5 2FJbN/ly/2tOhGD/ctxczOQ2r6o0ctuFDXzfidiS3I8cjNSgrH7+tPtM07bPOOxn4WZkdnrWomef eVreZvzmuwOPzH4A80Nhrr9169Z4kFKUx2O9gvUK1itYryy6nr+PHjx4sPL9uhZZz159/S26U7Y7 /vb398X6N+je3Zfp0aNHem18KwvV2Xi0b46uqiJISYRtI0v9S68myYOHGlkdxlp46KltBY0zcupt KnSKIfdF3X40HLpmqN67+6K87YozmjfOYwEAlm2Tv5OWGarp6VOVzb8OZW+I2zey5PSuiLtX55Oh 8qU5kKotasGOHGl8Wc5Puc9XVd0R5i+6dUI5bGkpB8MxsaEcdv8qjodnfaHqm4e1e1rzRgNnjqng tKjhdrjq0cCFhUcuAQAALE9IqKpJyt1BQrOXOSYpzzfVual6G8VBnfrjZlauaapzU+X2czU6bE/2 eU7gvtctnDAdTb8AkEZmbRWUkD5VDtXwCyZMKlF7jnNVtx3/IOAmZrZInypCFQDSbG/vU/oWB+2P 9K30WkOf6vIv/gAAAJuPA/XBg3fGixmwuyg9A5UAAAA2XMRQtS9uP7lsXz/mLsHIPRvKMQnHxIZy pFMajkekUFUXt+eLM8CqoT8VANKM+1Bv3frceNmEPtVlihCqXbovRyzdlv2sbU7Wkjd7jAxaJ0t8 eikAAOwe7kvlMN31QGWR+1RLt4OGIuXpDs/kstCFGmDd/JfwWheUw5aWcjAcExvKYUM5PLEHKt3I ihAdPCT3OviZm4f61u4K7meefV1gAADYLpFDtXVfDUWSIdqr0akemdRVbcM7bfIUI7UsCv2pAACb JUKo5um27Di9T2d82cD8bdmP2iqq2lhx4JBTuo3zVDcYRjLaUI5JOCY2lMOGcngi1VTzzT7VBy3q qL+o2a+TI2+zAp3POYsLAADANonY/KtmfRnP4pIp06XbzGlMzwYAALDLIoSqurh+BVd32FoYuWdD OSbhmNhQDhvK4Yk8UCmUnBnmiNxZ2iAZGKQEALB5poSqO/2bmq3GHZg0seRq1FNPiE/Oqepuy3+p Q/vSiEcBqT08O6KDSFVofi1hwR9wn/yh4O0btXQAAIhi8ZoqcwoUe/5wDq7igOp91Tcr51Y9Ohuf /6oujehduYnnVnXDrVtRYZerRYvzbiV8GrvJ+0TIyvlbdZ9xv06D4nbXxDFyz4ZyTMIxsaEcNpTD MyVU3enf1KUIS27IBC1zDFYaXnSoV6qOJx7PlKtU6nXogsNLBG6j5VD9jjuqWJXFHWScb6r99vlq TjNwbbaRrQdetzjovuFZg1pOnca7zhxTwenRFS4ZBQAAMyRTU03EDcq64XV9Rb15ar9+IpxPOgU6 L9/UKwwh92XKl74fCdd0NXf7NgAA7JIIoWrXEpOSOS6Q02p4zarDC+qI8Bo8HNLw4UCuutDNvPP1 aw7p7KRDhfOgWvS0+2yy5irqsoGXPl6SVQ9Swsg9G8oxCcfEhnLYUA7P3mg0eqxvT8d9oBODkhyq 9y/HTbjTcFOr2wfq1PvqnFceqFTUPZoOTy3XokGhT+d0Ih/LTc4yzOW+RQj69iW3eVWlUUDi830n Ykvq3FoejNSgrH7+tPsssnzc7xv8GjnsZ+FmanZ61qJnn3la3mb85rvhafYDTFvvwnoF6xWsV7Be wXolbD179fW36E7Z7hTc398X69+ge3dfpkePHum18UULVTP8AozDbyE82jdHV1WxLRL7a2SpbzTD 8uCkRlaHsRYeqmpbQeOYnHqbCp1iyH3e9tWPAIr8oyEIh64Zqvfuvihvu8JqpDidBgBgeZYZqhGa f0VANVSgTgxWkpOrErUa3qjducnmX4eyPDHrjSw5C00np64A5ZWVB1txrZqvCpWfcl9ygbpJzF90 64Ry2NJSDoZjYkM5bCiHJ0KoqoE6XIubqBDmm2oE7jwBKM9R9c5N7Z7WvNHAcsRtixpuh+tQjQYu LDxyKQJRrnUGKmqpAACba32jf2UgD6ioByIVB3Xqj1Oba5rq3FQ5UEmeNxoh5LjvdeIiEvGoqex6 VMt5g6R4Cbr4BAAAgClCn6rXPznRd+r2tToiEHFh/QkcxtzEzKL2qaKmCgCwXGvuUxW1xqruO/Vf qlAPXipVEagAAADRmn/zTXm5vsnrF6kBPouP/AUAANh80ftUzTlUx8tujI5dlXU1/WLkng3lmIRj YkM5bCiHJyRU+YIImJ0FAAAgjvWN/gUAANgyCFWYuITXuqActrSUg+GY2FAOG8rhQagmwBoRbSxx 4FQaAIDNNzVUJ06hCV0Wu+DCprMHb3kLAADsFtRUASP3fFCOSTgmNpTDhnJ4pobqxAX0Q5cm4VRV AADYdaipAgAAJAShmgLrHqSEkXs2lGMSjokN5bChHB6EKgAAQEJCQjVPzdEKrukr51QNG0HMs+N4 I4yDpl7jycQPIl32ia8QdUTBs7dN3ie3Oy5X2PMAAABs66up8tynxYG8ID8PdpJzqx6diShVupUc 1Q7beiCUmlvVzc9uRQVejueji6BbKZKaT2fSxH1ykvJDaruDsNqHVDvxyrWNMHLPhnJMwjGxoRw2 lMOztlAdXnSoV6qOL8ifKVep1OvQBaeXCNxGy6H6HbeqbNec8003iCfnzfHjWmcjWyd75jwl8D6e kccczXwjS07viq71nwAAAGFS1Kd6g7JOj644va6vqOcU6HjRGXBEOJ90CnRevqlXGKbdZ5Dh72RF 6ZYDV1ICANgeawvVzHGBnFbD668cXlCnRzR4OKThw4FcdaGbeXmJP2POkM5OOlQ4D5pAfdp9GjdP yyZmovq0x20BjNyzoRyTcExsKIcN5fDsjUajx/r2UnFTq9sH6tT7dMntvjxQqah7NJ0SlahFg0Kf zulEPpYvPiGbfDngciIE+/b8rXKbV1UaBYyo4vtOxJbkfuRgpAZl9fOn3TchZN+Mw34WbqZmp2ct evaZp+Vtxm8+11LZgwcP5H+Z+aEw+wewXsF6BesVrFewXomynr36+lt0p2x3Cu7v74v1b9C9uy/T o0eP9Nr4Vhaqs/Fo3xxdVUWQkgjbRpb6l14NkQcnNbI6jLXwUFXbChrH5NTbVOgUQ+6zt+8K2ncU HLpmqN67+6K87XJDFc2/AACrs8xQTU+fqmz+dSjLnZcLDw7KUPlSj96VS1vUgh050viynJ9yX1Bo Dkm3Ridqb+9T4v/598z6f9OYv+jWCeWwpaUcDMfEhnLYUA7P+kJVnqPqnZvaPa15o4Ezx1RwWtRw O1yHajRwYeGRS7Nx7dc6Z7Z7Kmq1ye6bA/XBg3fGiwpYAADYdOsL1XxTnZuqByIVB3Xqj5txuaap zk2VA5VyNTpsh/R5muTgosWmocuUL61yHchzaSPsGwAAdl6K+lS3T1ifqltTdd269Tl6/PhH+i8A AFim3ehT3SEcoByk7oJABQDYDgjVNeEgdRcAANgOCNU1wog5G8phS0s5GI6JDeWwoRwehCoAAEBC EKoAAAAJQaiukf/SWeuCcthQjkk4JjaUw4ZyeBCqCZDnswYsAACwWxCqCfAueWgvAACwWxCqa4QR czaUw5aWcjAcExvKYUM5PAhVAACAhCBUAQAAEoJQXSOMmLOhHLa0lIPhmNhQDhvK4UGoAgAAJGS9 oSrnVHVPQfFP2TaksyPv9JQjd25Vg5z7tBJlorcuVQ6OKGATwrz3AQAA2NYXqjz3qZyrVJ1+Iucw PToTUap0KzmqHbb16SlqblU3P7sVFbS5Wk+tmKFbKVJL3/ab974kYMScDeWwpaUcDMfEhnLYUA7P 2kJ1eNGhXqk6nvw7U65SqdehC05VEbiNlkP1O+6k5XlqinB15zDPN90gdtSKKbg228jWyZ45T5n3 PgAAgCAp6lO9QVmnR1fX4ub1FfWcAh3rwJ2bCOeTToHOyzf1CsO89wEAAIRYW6hmjgvktBpef+Xw gjo9osHDIQ0fDuSqC93My0ukrlPLkM5OOlQ4L9NkNs97X7IwYs6GctjSUg6GY2JDOWwoh2dvNBo9 1reXiptT3T5Qp96nS2735YFKRd1r6ZSoRC0aFPp0TifysaW2bvIVNcejnAi6/uW4uZjJbV5VaeS2 Cxv4vhOxJbkfOeCoQVn9/Hnv8+Own8W9XOHpWYuefeZpeZuZb77ZD4D1CtYrWK9gvYL1yiLr2auv v0V3ynbn3v7+vlj/Bt27+zI9evRIr41vZaE6G4/2zdFVVQQpibBtZKl/6dUWeXBSI6vDWAsPVbWt oHFMTr1NhU5xjvvsfcfFoXrv7ov6LwAAWJdlhmp6+lRl869D2Rvi9o0sOb0r4u7V+WSofOld2J5H D5fIkSONL8v5Oe+bP1DDmL+k1gnlsKEck3BMbCiHDeXwrC9U5Tmq3rmp3dOaNxo4c0wFp0UNt8N1 qEYDFxYeuQQAALA86wvVfFOdm6oHIhUHdeqPm3G5pqnOTZUDlXI1OmwH92tauO914iISAAAAq5Gi PtXthj5VAIB02JGBStuNQxUAANIBoQoAALAk2zf6FwAAYMOhprpGUS4eAQAA0fHpkPNA8+8W4FCd 9QGY9Rhsw4Zt2JLYBtuUsmIbNmwjOjT/AgAApAxCFQAAICEIVQAAgIQgVFNu3v4BE7ZhwzZs2IYN 27Bt0zZWAaEKAACQEITqhkvLrzeUw4ZyTMIxsaEctjR9VheBUAUAAEgIQnWN8AvRhnLY0vTLHcfE hnLYUA4PQhUAACAhCFUAAICEIFQBAAASglBdtm5FXo/SXSpdvd4v6uPmFXX7wzM6ivK4ecV+nV2q HBzR2VD/mZTI5RjS2ZH3uKOkCzLX+7KE42EYnh3RwbQ3ZtmfVW1mOZb9WdVmlmNsSZ9VbXY5lvxZ 1eK9L0s4HlHf9xV9Tv0Qqksl/pEVW1Rqj2QH+qhdolaxItb6RX3cvGKUI1ejQ/dx/ToNikn+o4j/ OruVIiU/vXv0cnQrOaodttXjRm06rOUS/Mc55/vSPqRaLsnPh9KtqC+fXK2n1wSJ/x7GFbkcS/2s Ri2HZzmf1ejlWO5nNWo5lv1Zjfq+L/9zGgahukzDhzSgEt3O67/zt8VfA3ro/wBEfdy8Im5/eNag llOnO+7jMsdUcHp0da3/XlTM18m/iBvZunhMwiK/L2fUaDlUHx+QPDXFP9Cm++eiYn0+HMre0H8n /fnQ8k31BdSvO3pNgJjv4TyilGPpn1Uh0vHQlvZZFaK9L0v+rArRPx/L+6xGft9X8DkNg1Bdpusr 6jlZcj9fJG5lgz4AUR83r4jbz5QvaXRZpoz+WzyRrqL9SI8mzusUXxInnQKdl2/qFQmK9b4U6Ng7 IMmKWo5MmaqlHnUu1DeC/GIpVam8rHJNE+c9XKKlf1bjWOZnNaplf1ajWvJnNfL7vsbPKUJ1iYYP B0SHN40PQIZuHhINfD+Xoj5uXvNuX/6DMH/tLSh6OYZ0dtKhwrn5jyc5sd4X4UI3e/GSZHNanPeF awnVq5xqfruq0ijJKkgM836Wli3pz2p0y/2sRrXsz2ocq/yshr3v6/ycIlQhWLdCuRpRvd+kVX9P Dc9OqFM4X09NzK9Xo6vbqtlrGf120agBKPfdcty+L76wVtM/tBHwWVV27bO6xvd9GoTqEmXUTyPx MXMNSf2Asv8FRn3cvOJuX47uKw7Eh/Uy0S+LaOUY0kWnJ74f1C/dgwMe/NGjWi650Yyx3her/8Zu 2lpU5PeleyoHoIx/8Oeb1C61qLH6b8zYn6VlW9ZnNZrlf1ajWvZnNbIVfVZnve/r/JwiVJfpRpac 3hV5zfjc/m904ruiPm5eMbbPH1b1628JX1KRypGh8qX+lSuXNpXIEeUZ0WVSBZr7fUlYxHLIpizr C2KNYnyWlm2pn9VIVvBZjWrZn9WIVvFZjfS+r/FzilBdpsxNOhS/Xe+7bR/d++KvQ5r4sRT1cfOK uv1xc8qSvqSW/Tqjivy+8MhC41f2UI2wLCQ1GiRiOTLHBfEF0aFxpSPpcsSRlvdw2Z/VTbPsz2pE S/+sRn3f1/g5RaguVZ6a8vwoPXhAnjel2//Fh+1o3Ncw5XGJiFaO7n0+y041X6nmLLUk15QV9Xgs W9RycE1Ene8nHyf+NR+2k/wSj1iOTJku5fl++nGJl2OGlX5Wp1jpZ3WKlX5Wp1jpZ3WKFX5Wp77v Kfmc7o1Go8f6NgAAwE7a39+nV19/g+7dfZkePXqk18aHmioAAEBCEKoAAAAJQagCAAAkBKEKAACQ EIQqAABAQhCqAAAACUGoAgAAJAShCgAAkBCEKixJlyrm1U7ikldHUc+fPYXVgvuaKrlty4uA622F Lkdn67/Gb+CxX+YxjqBbsY/TOssSyn+MVnDMYv07gVVAqMIWyFNTX9Q8+QuZL2PbJWrrbXoLX4xd 6NUol4ZgnbDMYzxdl+cILfLl6dTF6s3jJWeISeXxYus7ZrA+CFWAVFDXKpVEsJ6i1qGIGqrMUxmo 5jVkObC8HyInqaqxwi5DqMIKqQmM3aY7/zJuvuImrVyNevpPeVFseWfI8ysVXzNbxP1IXhOdtYwf FNKEF9QcuWiNiaer0jctgU2f/gu6h7wOsUw0C04re+ixj3EcrLLFeS/8xHMbMlFF5b4acFH2PN12 f4d0LrxjH+l4CfOW3S30xPN5PlWT/5gl8LkUy/hxoe+VFvU4QKIQqrA+pbZqytM1tFbxiOR3D890 0a+PA6bUFo8Zz3rskev5+c3bek2IsP3ILy79Reg+xq39tIr2F5RBTZCsvj5VGfpU58Iu2nR7faW/ IL15Hyf3NSL1MlpUPJj2OkbUl4UyX2+Eskc89ixa2XxC34sAwwvq6MQo3Q4uQ76p9ju6LBNnbtQy zVN293F8PLzne03S+iVFF+tzGfB+Tnmv5npvIBEIVVgP/rJwv6zzt1WQiUjpjCdinEE8P+S73jZt P8OHNJB/i4eNv7S9frDgMOnSaU1HX72vy5Ch8rn+cpu76VZ8keovQa9W5u3LfL35pg5C8TpqcmfB Zc6Uq77jmmTZg7YVVDbDou/5TFHLNF/Z3cfZzz8f16DzTf2DLIqpxyLq+xnGK9/0zw0sA0IVdpec yFhR8y5GaBqTkx0z38TLXGvQX4TG92AIri34m+VUzcSsbXj7EuutmlqGjgvy21Fs6v7sMrsSKbsW tq15y5aEqGVatOzjH2P+56dE0p8biAWhCjtM1Qi8Zjsz7JbZ9+Qb/Ws04bWKwfsdT7asl5xbEzHI Jj/jMZN9fJCIcTP9ciXxfkb53ECyEKqw88b9cryME1YE7KpO1bD6xlrUmOjwMk8l8S9N8dNADYBR X5hmYMdojkyjzDF5FavgnzjydBsOjFW9VyuR1Ps563MDy4BQBTDlm+MBIdS7omt1yxPWF7joSfhG gIxHsob2OxqjSDlMuqekKiD8JTrlyzLJsk8p24U3umjBL+4Mlas6RlqNgME1Xbqvq25O4ZgyUcu0 aNlDn5+QqO9nmCmvz/rc6LWQLIQqpN7g4ZL++RunHHhhYg7yCPpizdMdHbp84QH1PPFldaJPbXDq dGeuJDECpNch9V0YtC+xt7MT/aUrilgtU2Z8Ko75JcpfoP7mwvhlDz/2wWXrVnJeIMx3IGziR45q POhRLWeOWjVGyIpyn8vRQlHLtGjZzeefTI7YXVTk99PmvVfBr2/ic6NuQsIQqpBOmTKNM0Z8MSzl l7X4wvZOZ9C/4PUXI48KNUdemjLlS9/z9Jex+HLv61M75mLUMGon6vXKfemmYbeMqlmQazF6YJHR fCyPlXwdbkDYIpU94rGf3NaBvlADN1maF2pYjGyel/vhYFX7sd4n45hHLdOiZefnqxYNt0wJBSqL 8X7yY4PeK/n6Zn1uYCn2RqPRY30bAABgJ+3v79Orr79B9+6+TI8ePdJrlUqlQs1mU//lCVqPmioA AMAMHKAm/98uhCoAAEAEbpCGBSpDqAIAAExhNvGagRrUJIxQBQAAmMEfoEGByhCqAAAAEbhBGhao DKEKAAAQ0bRAZQhVAACAhCBUAQAAEoJQBQAASAhCFQAAICF7/7LexGUKAQAAEoBr/wIAACQEzb8A AAAJQagCAAAkBKEKAACQEIQqAABAQhCqAAAACUGoAgAAJAShCgAAYPirv/orfSs+hCoAAEBCcPEH AADYSH/8x3+sbyXjV37lV+R/uab6cz/3c/J2XAhVAADYSByqn/nMZ/Rfk9pv/y/00U8+pI8++kgu H3/8CZ38xpv6XtsPfvCDREIVzb8AALB1/u9/8z/Tf/vPivSrJ1+mUvnL4r//hP5J6b+m/+3r/1Q/ YjkQqgAAsFX+r7f+JxGo/5g++UTUTj/6kD75+Cf0k7//j3J5/vl/SK9Wi/qRyUOoAgDAVvnJT0SI ymbfn9DzX25Q4R//JhX/u2/Sj//uP9Lf/+j/o+//v3+jH5k8hCoAAGyVjz76mD7+mJdP6Kc//Sn9 4R/+IT3z6Z+hD0Wo/vjvHsn+1WVBqAIAwFb5Z5V/TV+t/C79D+Vv0R/8wR/Qb9b+Gyr96j+iD3/8 NzJUP/nkE/3I5CFUAQBg67z11lv0e7/3e/R//KtfpRde+Bz95MO/pQ9/9Lf0td8c0DvvvKMflTyE KgAAbKXf/de/Tr/6T5+ljz/8O/r4x/+JKv/re/T9739f37scCFUAANhKP/MzIuL2iB4/fkwff/xT vXa5EKoAALCl9uijD/9WLh+LZRUQqgAAsJX++5ebdOfrPfofv/Hv6Z//1gf0J3/yJ/qe5UGoAgDA Vvo3//uv0+v/4r+g11/+z+lfnfwDunXrlr4nWX/2Z38mF4ZQBQCArcTnqX74o7+hH//ob+nDv/9P eu1yIVQBAGArfSRC9ccffkI/+ein9NEne2rg0hL80i/9klwYQhUAALbSr7/yLfrGt/4Dvfq7P6bG //mf0Xe/+119z+LMJl80/wIAwE5ot9v0ne98h7rdrl6zXAhVAACAmMwmX/M2JikHAICNxJOUJ2nW JOVuEy8HaNhthCoAAIABoQoAAJAC6FMFAABIyN4H7RdRUwUAAFgY0f8Pv2raZV7mqO4AAAAASUVO RK5CYII= --001a113d6a0a1ede02053654edd6-- From owner-chemistry@ccl.net Tue Jun 28 09:50:01 2016 From: "Partha Sengupta anapspsmo##gmail.com" To: CCL Subject: CCL: NBO Message-Id: <-52255-160628091107-3534-S5DP2V3Cp4c5An05uBXT6g~~server.ccl.net> X-Original-From: Partha Sengupta Content-Type: multipart/alternative; boundary=001a1137c5163070e60536565ecb Date: Tue, 28 Jun 2016 18:40:58 +0530 MIME-Version: 1.0 Sent to CCL by: Partha Sengupta [anapspsmo- -gmail.com] --001a1137c5163070e60536565ecb Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: quoted-printable I have five structures. Will you help me doing the NBO of those species? PSSengupta On Sun, Jun 26, 2016 at 10:44 PM, Wojciech Kolodziejczyk dziecial],[ icnanotox.org wrote: > What is your problem? > 26 cze 2016 11:43 "Partha Sengupta anapspsmo]=3D[gmail.com" < > owner-chemistry_-_ccl.net> napisa=C5=82(a): > >> Friends, Is there any one who can help me doing some NBO analysis with >> NBO 6 package. >> Partha >> >> -- >> >> >> *Dr. Partha Sarathi SenguptaAssociate ProfessorVivekananda Mahavidyalaya= , >> Burdwan* >> > --=20 *Dr. Partha Sarathi SenguptaAssociate ProfessorVivekananda Mahavidyalaya, Burdwan* --001a1137c5163070e60536565ecb Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable
I have five structures. Will you help me doing the NB= O of those species?
PSSengupta

On Sun, Jun 26, 2016 at 10:44 PM, Wojciech = Kolodziejczyk dziecial],[icnanotox.org= <owner-chemistry~~ccl.net> wrote:

What is your problem?

26 cze 2016 11:43 "Partha Sengupta anapspsm= o]=3D[gmail.com" &l= t;owner-chem= istry_-_ccl.net> napisa=C5=82(a):
Friends, Is there any one who ca= n help me doing some NBO analysis with NBO 6 package.
Partha

--
Dr. Partha Sarathi Sengupta
Associate Prof= essor
Vivekananda Mahavidyalaya, Burdwan



--
Dr. Partha Sarathi Sengupta
Associate Professor
Vivekana= nda Mahavidyalaya, Burdwan
--001a1137c5163070e60536565ecb-- From owner-chemistry@ccl.net Tue Jun 28 11:12:01 2016 From: "Tobias Kraemer t.kraemer~!~hw.ac.uk" To: CCL Subject: CCL: correct transition state or not Message-Id: <-52256-160628110106-17563-GCUTlXm1ZnD3BSNkVcy55A{}server.ccl.net> X-Original-From: "Tobias Kraemer" Date: Tue, 28 Jun 2016 11:01:05 -0400 Sent to CCL by: "Tobias Kraemer" [t.kraemer:_:hw.ac.uk] Dear Teja, At first glance this looks like a reasonable IRC, quite flat around the TS (not sure what the outlier means). A reasonable thing to do next is to optimize the last point of the IRC (1.8 on the X-coordinate) and see where this leads you. Of course you should also run the IRC job for the other direction (reverse or forward, whichever way you look at this) and do the same thing here, optimize the last point on the trajectory. Inspection of these optimized structures help you to confirm if the TS is reasonable and the one you were looking for. I often look the at the animation of the imaginary mode itself, this tells me already if this TS corresponds to the desired reaction coordinate. You can also do a quick version of the above protocol, displace the TS geometry by a small increment in both directions of the TS along the imaginary mode (use GaussView to do this), and optimize these new (initial) geometries to their nearest minima. In the end, it is a combination of visual inspection of the TS as well as the ground state geometries which will reveal if this is the right TS for the reaction. Hope this helps Tobi Dr. Tobias Kraemer MRSC Research Associate Institute of Chemical Sciences School of Engineering & Physical Sciences Heriot-Watt University Edinburgh EH14 4AS United Kingdom email: t.kraemer[-]hw.ac.uk phone: +44 (0)131 451 3259 > "teja reddy reddyteja80%gmail.com" wrote: > > Sent to CCL by: teja reddy [reddyteja80~~gmail.com] > --001a113d6a0a1ede02053654edd6 > Content-Type: multipart/alternative; boundary=001a113d6a0a1eddff053654edd5 > > --001a113d6a0a1eddff053654edd5 > Content-Type: text/plain; charset=UTF-8 > Content-Transfer-Encoding: quoted-printable > > Dear friends, =E2=80=8BI have optimized TBP transition state which is showi= > ng > -216cm-1 negative frequency but is showing only 9 points on the curve like > shown below. can anyone help me is it a correct transition state > [image: Inline images 1] > > --001a113d6a0a1eddff053654edd5 > Content-Type: text/html; charset=UTF-8 > Content-Transfer-Encoding: quoted-printable > >
De= > ar friends, =E2=80=8BI have optimized TBP transition state which is showing= > -216cm-1 negative frequency but is showing only 9 points on the curve like= > shown below. can anyone help me is it a correct transition state
class=3D"gmail_default" style=3D"color:rgb(0,0,0)"> ht=3D"434" alt=3D"Inline images 1" src=3D"cid:ii_15596c33e3e5b53d"> <= > i>
>
e">
ir=3D"ltr">
nt color=3D"#000000">
mily:courier new,monospace">=C2=A0=C2=A0=C2= > =A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 = >
>
> > --001a113d6a0a1eddff053654edd5-- > --001a113d6a0a1ede02053654edd6 > Content-Type: image/png; name="image.png" > Content-Disposition: inline; filename="image.png" > Content-Transfer-Encoding: base64 > Content-ID: > X-Attachment-Id: ii_15596c33e3e5b53d > > iVBORw0KGgoAAAANSUhEUgAAAdUAAAGyCAYAAACySF4VAAAAAXNSR0IArs4c6QAAAARnQU1BAAC x > jwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAEqjSURBVHhe7d1fjCvXfSf4Xwf75HnoBhYIECB Y > KLw3Itx6URi7MMLuyFcO2G377guxIgbjxU64mpXTlDdXnIEZXGr3ruHRrKiE2R2qF1a3o4lA5CG 7 > Czog8nCd6SZiXwVeDEA5DLAD0WjlNqOHAAECzA5vJnEsS/Ld8zvnFOucYhVZRRbJIvn9GGWxi2T V > YZGXX54/VWfvsUAAAACwsJ/R/wUAAIAFIVQBAAASglAFAABISGif6t7enr41HbpkAQAAlKmhOis w > 3eBFsAIAAPhCNax2GhaaMnj5v2JBsAIAwK6b6FPlaDQX9ujRI/nfs7Mz+sY3viH/63JjOGpzMQA A > bC7+ro+ypA2X6U//9E/1X5P4viTKHWug0l//9V/TX/7lX8r/Mq6dustMH7xNz3/60/Rpd3n+bfp A > 3yV97xWx/hX6nv7T9j16hZ/zSvC9H7z9vHju8/S2ucEp2/veK5+m560HC/x4c/tTyzMLl9d9ri6 7 > sUy+jA/o7eeNx/iPjeTfjvl6+T7f6wcAWBLzuz9oSaMf/OAH9Mx/+V8FBiuv4/v4MYuKFao/+7M / > Sz//8z8v/xsLB+oXv0Nf+qMf0g9/qJY3n3xIf6HuVIHSJSrIv8M8RU+9/82A4Pge/U7jPX2bzd7 e > c/kCvfdQ7d31vW6HCvnnxK2o5YnjKaq6r/3NAnVeMsJa/tj4Ij38qndsfvjbRN8NTHNvO39UJWp 8 > LSh8p0H4AsBu+uVf/mX6d//P9yeC1Q1Uvo8fs6hYofrlL3/Z+m80IqS+1qAn3/w2vfCEXiU899p r > xBFG9AS98G0RFK/l5V/TPPkk0Xe+60uE73WpUygYARhhe79wk57qdL1gE7e6nQLJTI1Rnrk8lxd l > fZ/+Qr4M99j8kF5TB0N54gV6wfw7wBMvfJUK732H/IcDAACC+YM16UBlE6HKLcrmsrAPvkvfec8 N > rBi4+dXXDHrzK1+lJxu/Y4ShCKVvvk/Vr0QIQHN7T3yevvRUh7ruhmQw53XILxnv66kv0ef5B8a 8 > x2YWX1O7am7mWupL1KH3qPFFsT6kKR0AYJuZwZp0oDIrVP1t4qPRSC6u3//937f+G9lTN+kX9E3 V > /8lf9vM0Qz5H+YIRhhxKpAMqlifo8196it5X1UWj6XdZdJDx6+7m6YfffkGUQDOOTRwfvP1NL5w t > Ijy/qGq/sin5j6r0/kt8rJ+j1374pqgl6yZkq2oMAOtgDuyZtsDmmNr8u7+/P16Yf6BSZO+5/af c > bPlt8WXPX+4zPPeaHT7ac18RIfFNVeP83u+I8Pjq5GMC+bb3xOe/xG3JYjsf0F+8/xTdjJNsVk0 w > ymAmHWQi4OxmZ8E4NrN54fzFxpP0ZsDxoQ/+gt4XR3f8G+GJF+irhffI14UMAClgVmSmLZAcs8n X > bApOSuQ+1evra2ugEv8dyRO/QE+O+xATwE23on763e+9Td98v0pfmbfCNd7OHLVdEVTfdgcV/dD t > G45APO+3q+/TN90qur8ZeiZjwFOc/QIAwEQfqr+PNQkzQ9U9N/Xy8pKOjo7o61//uvwv/+0/ZzX Y > cyQql6KGFfP0lIA+VeUJeuGrT1LjpQbRlz4frZbKJrbHTcCiXHG3syAeYPRk42u66ZtfC48G9p1 m > I2rCb8c6WAb5I8ZsIhc/PsaDsAAAdlPYoKSkg3VmqJpNvjdu3JDr+L9xmoJlk++bRC+Nm0xfove r > v22NBo7lua9Q9akCfXXuDSjcBPyU+N+X4nfKLkD/yHBPh+Fmadnv6R4bsXyN6PNzh+Bz9Jq5PXk q > k1ur5T5pDFQCgMUE9fuaSxp95jOfmQhUlxus/JhF7T0OabDnA8N3cU2Ug5ObfMvlsr5X1WDN9e7 j > AQAAdtXMUI0KoQoAALtuaqjGhVAFAIBdFhqqAAAAEE/kU2oAAABgOoQqAABAQhCqAAAACUGoAgA A > JAShCgAAkBCEKgAAQEIQqgAAAAnZG41GOE8VAAAgAaipAgAAJAShCgAAkBCEKgAAQEIQqgAAAAk R > odqlysEBHYyXIzob6nvlfebfAAAAEEbXVB2q90c0Go2oXyeqnZxRvBxF+AIAAEw0/2bKVSr1OnS B > gAQAAIglXp/q8IyOjKbiSpdXci21SC3qUS0n1suVQzo78j8OAABgu02E6vCsQS2nQMcZvWJMhGe u > Rodt1Uw86tdpUOQm3zw1R20quU3Izbx46CnVDtvqcWLhVQAAANtOh6quZYpaZa52SO3LMk1k6vA h > DUR03nYDMlOmaqlHV9f6b9ONLDmtIh2hkxUAAHbIxECl0ahJC1csReBeim2d0wmafwEAYGdE71P N > 3KRDatF9NyCHZ9RoGTXXAJnyJfXrDg0eosYKAADbL8ZApTw1ZT+qHoCU61Ch79Zq83S7ZAxU6lb G > g5S4OblanmhMBgAA2DqYpQYAACAhMWqqAAAAMA1CFQAAICEIVQAAgIQgVAEAABKCUAUAAEgIQhU A > ACAhCFUAAICEIFQBAAASglAFAABICEIVAAAgIQhVAACAhCBUAQAAErL3L+tNXFAfAAAgAQhVAAA A > 7d7dl+nRo0f6r/j2Hgv6NgAAwM569fU3Fg9VzKcKAAC7bn9/P5FQxUAlAACAhCBUAQAAEoJQBQA A > SAhCFQAAIKJKpaJvBUOoAgAAROAG6rRgRagCAADM4A/SsGBFqAIAAExhBmiz2dS3goMVoQoAABC B > G6hmsPohVGHNulQ5OKCDqEulq5+3WsM387oMeXpzqFeG6VbsMs9Y1vSSNkasY58yQWX31k1f8tN e > bNhnLP8mbdgh2hj+IA0LVoQqAEAKvftKLiBY9Y/QYkv/7fPuK5QT908NZIgtLECD1iNUYc3y1By N > aGQs/dc+q+/7LL3Wt+8bNfP6vni6FffXfEV8La3OZ1/r2+UPWOZ8SbAFSu2Az0T/NfHJV9595dT 4 > vA7pzXyRvDgtUdt8Xruk1/Pzfm3javXbAqEKAJAmmZfoW+Mflu/Rn7vh2D2lV97Vtz/7GvVHTfG T > 1JBvGoH8Lr1yin6FdUCowkbzaqD24vVTquYyr7WsRUV+jPuAFPVNzexrC+l8DT4Gk/2PYcfK2y7 X > hALuHy+qlm9ux1+kafdNSODYz37/lfmObbTjsSrd++6H+LP02rdeooz+yyICuevWXNEEshYIVdh Q > /rC0tYriS2/Gt7r8op3WN5W2QR+tou81TTsGoqaSi9O3xtvKeTWhKfJ3vObJ1n27PN73/mt0Z8p 3 > +uLHfvH33xJ4bKMdj8QN36RfG+/4KfpFmZ5D+vP35ApxbAv0hcBEhTRAqMJG6laMviXZFKZ/nRv 9 > UfxFWemqPluvu0n3QzWJTsdfXGbfVJ/GLW/vdujfLpiqPNgkuJajlynhMe6PtV7TffF1r1jHoNT W > 5eelLV6REt63ZrxmUaMJ3ZbRTzeW+QIVvFQdl0dUpcbb+GzhC8E1Kam78LGP/v7r2z5zH9ug47E A > Gf7+z0TuFfGTSCm13Sbea3p/nLO/OOXYQhKur6/nXhCqsIHsGlG/azSFcfOX8cVn16RM5gAps28 q > Q18YJ8a79P61vrliPICl+5J+VeI1/cb4Jbl9bL5jYDX1iddm9K11JtKJB4CZr3nKtvJN4weJyzx G > LXIPsdk8WZhalVr02C/2/i90bAOPR/Lc0EcL7uZBqMLmGf65+PrTgn6152+Pa2r03p9HakY0awq 5 > BNv8Zo7+NQMhDvMY6NMozNdg1nbenfXLYNbxDJD5QmFcw1PBZQRR6TfIzazp5jz2ib7/AeY4HvO y > R/96NXVu4bBr2TfoSfeAz/OaYGUQqrCz1CAXo5lvWy3jS9jfBGw0/ZZuz65e7cyxjyVDL3W9pvt W > 0RwIlaFffErfTKBbApYHoQqbJ/OL5H6/BAaG8QUfWtMYvkm/NX6Qfb6fd55sipnHwOpPDVhm1YZ n > Hc9AdhNwcTxiqEQzM3XRY5/E+z/NXMcjKXm6Mz4GLfoto0M8f9uN23fplV8L6YsXxzbv1vzjDNS C > xCBUYQPlyft+8Y0U5S8VY0joZK1J95tdvz9uHhUPsvoXvUE0aWYcg4mRq3wYvFNIZo8A9h3P8bb U > KSVhI2zNJuAx61iGWPjYL/L+RzHf8UiKeVzf7fxb77Xl7xgDubjJ33dKD792c5DTXK8dFoVQhY2 U > b3rNZOoLRv86N75UuAY3OdBDnWpy8FvveYHAoeQ+P+EmyZmjf3mZs0ZhHQPrNZh9kyX6jQgdnOZ p > Mt62ZpxSYg3yUSJ9kZt9nnMe+/nf/2jmOh5JMZvWraZeu3lYFEydcx3w2rkvH4Oc1gOhChvKf6q M > TQ4AMb5VrC9JqUDfMk492UzqGIQ1mapBUr6r7oThUbNzHA+vSZJFaPqVuNyLHvt4739scx6PZNi j > oO0rI+mR06FDkFVz+nh0M6zc3mg0eqxvAwD4cJOnW0PjL2x/SPMIXl3D5L7dra8ezToesKn29/f p > 1dffoHt3X6Z+v6/XxoeaKgBMYVx0IEjMUb+bb8bxgJ2HUAXYeeY1bs1rBvN6o59zYhCSqKW6o3Y + > O/2yhJtl3uMBgFAFAB4AMx5xpAdyyUAxB+Z8ll4bp6Z70QYvYKZflnDTxD0eAB6EKgAQX37Pug6 u > iS/VN+qGXyWp1N6+gTGLHA/YaRioBAAAOw8DlQAAAFIGoQoAAJAQhCoAAEBCEKoAAAAJQagCAAA k > BKN/V+T0bHzKOAAArNmdsn395KRG/643VLsVOhjPo+S/juaQzo5yVOupv5x6ny7L9olhw7Mjyl1 V > I1xvlE9Wb1C2f0nuJuRz3Y2TQ3XjPs/k8+bFoXrv7ov6L+Wdd96lz30u+GLoq4Ry2FCOSTgmNpT D > tmnlePX1t5YWqutr/h2e0VFxIMJMT05cH1Dx6ExEqdKtiEA9dCdfbtNhLUfuDFndirrCiReK03U r > vimlRJjnaofe5MjtQ6qdePt2TTwPAABgirWF6vCiQ71SdVwDzJSrVOp16IKTTQRuoyVqj+PLgKn p > jtwKab7pBrGjVkzBNdJGtm5P4cRXSzFrxTey5PSu6Fr/yQKfBwAAMEWKBirdoKzToytOtusr6jk F > Ol6wyZXD+aRToPPyTb0imAx4JytKoEV83qLS0FzCUA4byjEJx8SGcthQDs/aQjVzXCCn1aAzt81 1 > eEGdHtHg4ZCGDwdy1YVu5uXFbfqNbkhnJx0qnJfDL/TNTdCyGZmoPn5chOcBAAAEWNlAJXNg0Hj Q > kTlQySlRiVo0KPTpnE7kY3n2ftnky+GXE0HnGzA0baAS33citqQGN80YcGRs//gi+vM47GfhZmr G > A5WefeZpeZuZv6i4c92F9QrWK1ivYL2C9coi69kyByql6JQaNdr3qiqClETYNrLUv/Rqizw4qZG 1 > RwCHh6o9ctgUNIqYqe23qdApxnreNBy6Zqhi9O90KIctLeVgOCY2lMO2aeXYztG/frL516Esd2w G > DByKJ0PlSz2yVy5tUQvm02ZGIcE4JNXifCPm8wAAADzrC1Vu+j2okNtV2j2teaOBM8dUcFrUcDt c > h2o0cGHhkUsK13DNfYudi9ppctsHAIDdtL5QzTfVual6IFJxUKf+uBmXa5rq3FQ5UClXo8N2hAs w > yIFHRliGyJQvrX0fyPNlF7/AQ1xpaC5hKIcN5ZiEY2JDOWwohweXKVyiWX2qAACwervRpwoAALD h > EKprxCPV0gDlsKEck3BMbCiHDeXwIFQBAAASglAFAABICEJ1jTBizoZy2NJSDoZjYkM5bCiHB6E K > AACQEIRqAuS5rgHLTHv/QC0AALAVEKoJ8C5raC+hdJi+8+AB0eO/W3u4YuSeDeWYhGNiQzlsKIc H > obpqHJ4iSPfoMd269Tna2/uUClY3XAEAYGMhVNeAg/TBg3fGiwzWlOMyugsAAARDqK6SrqWGWlN t > ddaIuVX9CMAIQltaysFwTGwohw3l8CBUYS57Ivx5AQAAD0J1lXRN9PHjH8n+VHfhv6VZNdkUeSz K > yYsbrtMWAIBdsd5QlXOquqeg+KdsG9LZkXd6ypE7t6pBzotamTXRG+tS5eCIzE2oOVXd7Zv32fu d > vD8ZKkj3vEBdo1kj5kJ/BAhuuE5bgoLWvzCMILSlpRwMx8SGcthQDs/6QpXnPpXzmKrTT+T8pkd n > ItKUbiVHtcO2Pj1Fza3q5me3osIuV+upFTN0K0Vq6duSCPNc7ZDa7ukv7UOqnXj7JnLG5VJLgnO t > ipCRNVIdJJL7N9+XWuoHwDw/AoKC1r9wsN66dWsibM0lLgyuAoBVW1uoDi861CtVx2GVKVep1Ov Q > BSebCNxGSwTbHXfS8jw1Rbi5c5jnmyrs+nVHrZiCa6SNbJ2smfPyTfH8ptiqdiNLTu+KrvWfRId 0 > c5kTlosQ4UVOZMthof/eZRysDx48mAhbcwkKWv/iWtXgKgAAU4r6VG9Q1unRFSfb9RX1nAIdLxp s > IpxPOgU6L9/UK4LJgHeyogTsmq6iVYAXtsf/J8Ji3TZl5F5Q0PoXf7jOAyMZJ+GY2FAOG8rhWVu o > Zo4L5LQaXl/l8II6IswGD4c0fDiQqy50My8vkbpOLUM6O+lQ4bxModnMTdCyGZmobj1uQA2jXzX + > vmFd3HANYtZozQUAICl7o9FItkIuGzfDun2gTr1Pl9zuywOVirq30ylRiVo0KPTpnE7kY0tt3eT L > 4ZcTAdm3+zblNq+qNHLbhQ1834nYktyPHKjUoKzv+WPm9sm3r5B9Mw7cWbiZmp2etejZZ56Wtxn / > ouIvdA4As3Pd/KWVlvWbUk6Xu54HVbm4Lzjs8UHBuomvl2G9gvUK1ivmevbq62/RnbLVKUj7+/t i > /Rt07+7L1O/39dr4Vhaqs/Go2xxdVUWQkgjbRpb6l17tkQcnNbI6jLXwUFXbChrHNA50n6Dtu6b d > Nw2Hrhmq9+6+KG+73LBaN/7w+T90plWVc1Y5VoXLwYOmgqzy/UrL8WBpem9QDg/KYYtajmWGanr 6 > VGXzr0NZ7ticGDgUV4bKl+bo3baoBasRvcHBOCTd4gwgcXgGLfwDw78AALjWF6ryHFXv3NTuac0 b > DZw5poLToobb4TpUo4ELC49cUriGa50X2z0VtVq1/cn7KlRMcN+w2aIGLS8AsHvWF6r5pjo3VQ8 G > Kg7q1B8343JNU52bKgcL5Wp02A7pDzXJgUf+i0hMypQvrX0fyPNl1fan3bet0tBswza1HEFBy0v c > oPWfV5uW48HwGbGhHDaUw5OiPtXtsyl9qtNsQhk3SXiwPpbn07r8V64CgOTsRp8qwA4wa7LmAgD b > AaEKcsRcGqAcNrfJOLx2uzp4b2wohw3l8EQLVdlXqfsYA5fkLzgPsEu4qdc/aYF52cY0BSwAhAs P > VTNITzp6ZbjOCQIWYBEcpO7iZzYVmwGLkAVIl5BQ7VLFCtICnY/P+QxazsUjPJ2T2SNwIT3CRsz x > FzZ/ia8KRhDawsphBqw/ZJcF740N5bChHJ4pzb9GkBpXNgpmXmzBDlgAWK6wgF1myAJAsJBQzVN z > ZpCG4YA1plXbAXb/srcArJoZsP6QBYDlizZQCaaym8K9ZVNg5J5tm8qRVMDivbGhHDaUwxM9VM2 B > S0dnxGOR+ELzB5gXbSvxFy9/EcP2CAvYeUIWAIJFC1W+Tm+uRsFzd9+nMwz3BdgoZsD6QxYA5hc h > VId01uA5T9UsL/26o1YL+Waf6oMW1WqnGO27wTByz7aL5QgLWDdk8d7YUA4byuGJEKrXdCWqqE7 9 > POCi8hkqV+3rJwLAZjMD1h+yfv5JAAB23cIDlYaYiBRgq4UFLAcpTwLgLghWgEiheoOyDlGvliP / > mCSeezRX42psVjxqDnJOVfcUFP8FI4Z0duTed0BHAf22cu7TSAOlulTxXelJzZvqbt9/FajZ+94 m > /hFz/IXJX6CrhhGEtrSUg7llMQN2HfDe2FAOWxrKESFUvSbeVvFAhWivRjkRNvK2UKrOcU4rjya W > c5Wq00/kHKZ6VDHrVnJUO2zr01PU3KpufspRx8b+Z+lWisS9wmMizHO1Q2q7p7+0D6l2Em3fAAA A > YaI1/+abMlwme09LMpjGc4vHMLzoUK9UHffTZspVKvU6dMHJJgK30XKofsfdcJ6axn7yTTeIvUF T > YbhG2sjW7bLL12NcoOJGlpzeFV3z7Rn7BgAlaBIAt2kYYFfF6FNV4aJqb+6S5JWTuJm5R1ecbNd X > 1HMKdDzfJZ08IiBPOgU6L9/UK4LJgHebsJPa9wbByD0byjEprCz+SQDcpuFlhSveGxvKYUtDORY e > qDSvzHGBnFbD68scXlCnRzR4OBwPfrrQzby8xG9+HdLZSYcK51OaprkJWjYjE9X145LZ9+ZaV38 q > bJdlhytAWu2JGudjfXs6DiD3AhBOnfqXZboWwVOkNo0itI2OBzUJTr1Pl9zuywOVirq30ylRiVo 0 > KPTpnE7kY0tt3ewq9y0Csn9pndYjt3lVDdw/33citiT3IwcqNSjre/6Ysf3jC1XOWftmHLizcI2 e > nZ616Nlnnpa3Gf+icgPM7Fw3f2mtYz2XiefxdK1qvwzrlW1c7war+9la1X4Z1itY73n19bfoTtn u > 0Nzf3xfr36B7d1+mfr+v18YXLVTN8GNWqJaonr1D5cC0ioNH3OboqirCjMT+Glm5D3erPDipkdV h > rIWHqtpW0DimcaD7jLd/8zTSvqPg0DVD9d7dF+Vtlxuq68YfPvdDt84ymeVYJ5RjUlJlccN13s8 Y > 3hsbymGLWo5lhmqE5l8RUKu4opJs/nUoyx2b5sChuZhT0fHCg6xU+YODcUjj020X3jcAhOEw5YX D > 1Q1YgG0SIVSXdEUleY6qd25q97TmjQbOHFPBaVHD7XAdqhG5hYRGD3EN1zovtnsqarV6+0veNwA g > XGF7LTxQae4rKuWb6txUPRioOKhTf9yMyzVNdX6oHCyUq9FhO6Q/1MT9nxMXkZiUKV9a+z6Q58u 6 > 259z3xvMbS7hL7d5m+WSkIbmI4ZyTFpWWeKGK94bG8phS0M5IoTq8q6oxOE2bqKdmBTdPoUnYCy S > er55R6ZMl4Gn+fC27GC09u27L8q+ASA5qLnCtogQqku6ohIAgA/CFTZdtObfJVxRCdKDR8ylAcp h > S0s52KrLEhaueG9sKIctDeWI0ae67CsqAQDYUHOFTRMhVPnCCds/U8uu4y8s/vICSCM3XG/duoV w > hVSLUVOFbYWRezaUY1JaypKWmis+IzaUwxMhVN3Rvye+OUcBANYjLeEK4BchVNXFH0SsUi2nz+u c > WGafG7rNgo/J7OsCA8BiEK6QNmj+TYA9eMtbNgV/GfEX07phBKEtLeVgaT8mqw5XfEZsKIcnQqg G > jfr1LxgFDADrh5orrFuEUFWjf3dpTlEA2GxB4bq396nxArAsizf/yuvtHmEQEywMIwhtaSkH29R j > 4oXrp+jBg3fGy6LBis+IDeXwTAlVVUM9OCgST/zGlygMGozDF5xXFysEAADYbckMVHIKhJnRNhM 3 > jfEveQAAWNyUUHUHKKlr/pba/sFJxjIxw0xEck5Vt9brPy1nSGdHXo046IpOcl7USJ29XOu2m6j V > nKru9o37rDIZy9GZKNF2wsg9G8oxadOPyePHP6Jbtz43XsTPSXXHnPAZsaEcnmRqqvPgvlg5j6k K > Zjm/qRFc3UqOaodtHdxqflM3P7sVFXTuLDmzdCuqCXtMBGeudignA5Dbbx9S7UTvW04eoNeP759 z > InYASA0OVm9Rg5gAkhY5VAcPk62nDS861CtVx/OYZspVKvU6dMG7EYHbaDlUv+OeqKNqze5sOPm m > Crt+3VErpuAaaSNbt2fYkcFpnAZ0I0tO74qu9Z9+3fstcgrHmN4OYIsgWGEZ1ldTncCXQ+zRFSf b > 9RX1kuinFeF80inQefmmXhFMBnzYROsy4EtUtWcx3wpufypG7tlQjknbekzmDVZ8RmwohydCqC7 n > 2r+Z4wI5rYa3zeEFdXqqRjx8OJCrLnQzLy/xz5Md0tlJhwrnU/p7RWAeyWZkonrI47qnfOcdXNw C > YEuhxgpJ2huNRo/17RA8yMfXJzmBJyufflUlboZ1+0Cdep8uuebHg4KKestOSWylRYNCn87pRD6 W > B0fJJl8Ov5wIyP7luLmYyW1eVWkUMEs633citiT3I19Dg7K+54+FbD90vcZhPws3U7PTsxY9+8z T > 8jbjX1RuTdHsXDd/aS17Pe//wYMH8vYq94v1CtYraVm/7n+PWK8sez179fW36E7ZHiuzv78v1r9 B > 9+6+TP1+X6+Nb2WhOhuP9s3RVVUEKYmwbWSpb4wq5sFJjawOYy08VNW2gsYxjQPdJ2j7vK5I7cD Q > joJD1wzVe3dflLdd7j/idTG/RPwfunVAOWxpKQfbhWMS598jPiO2TSvHMkM1QvPviq79K5t/Hcp y > x+aMgUOzZah8aZaPTwty5EjjoEDlENYtzoYu3bcGSwHANuNA5WAFWMT6BirJ80G9c1O573I8Gjh z > TAWnRQ23w3WoRgMXErrCBNdwrfNiu6eiVmtvf3jWoNYWX9Ri3bVkgDRCsMKiIoaqfSGGyWWO+VT z > TXVuqt5GcVCn/riZlWua6txUuf1cjQ7bIf2hJjnwaHZZMuVLa98H8nxZc/tdOuU+3eqcF7XYMGl o > tmEohy0t5WC7dEyiBCs+IzaUwxOhT5Urldy3WKJSqxXSt5pEn+r24cDm5meWtj5V1FQBpsO/ke2 1 > 5j5V7lvk/96Wfavy4kIl70pHslhh53gCAGwoNAXDPCL3qZZuB9VD83SHr2q00KAiWDX/L3AeMZc G > KIctLeVgu3pMwoIVnxEbyuGJPVDpBl8JYvCQ3Gs2ZG4e6lsAANsHNVaII3Kotu6r4T8yRHs1OtW j > gfi6uAAA2wzBClFFCNU83ZYdp/fpjE9xyd+W/ajupOXFgUNO6TYGKW0wjNyzoRyTcEzsYMXxsKE c > nkg11XyzT/VBizrqL2r26+TND1Og8zmvOAQAsElQY4VZIjb/qisUja9GlCnTpXu1onknKN8i8lz X > gCWN+AuBvxgAYD4IVpgm9kAlmKROL5pcNgVG7tlQjkk4JjaeiCINwYr3xZaGcoSEKl9EP7j2Fbz M > cUUlAIANhhorBEFNFQBgTghW8AsJ1YCZadSllKjtXy8XXKJwk2Hkng3lmIRjYjPLsc5gxftiS0M 5 > UFPdIfwPH4OUAACWB6EKALAgNAODa72hKudUDRvsZE83d+TOrWqQ86JWogyR4oFXR2RuQs2p6m7 f > vk9NIRdy3xbCyD0byjEJx8QWVI51BCveF1sayrG+UOXgkvOYqn5ZOb/p0dn4msLdSo5qh95sODy 3 > qpufPBUdB16u1lMrZuhWivaUdSLMc7VDr3+4fUi1E3ffIoDl/K3GfTmMbgaA2VBjhbWF6vCiQ71 S > dTwxeKZcpVKvQxecbCJwGy2H6nfc4U9q4JR74aZ8UwVen2fImYFrpI1sXU1R58o3xfONwVU3suS 4 > M+0MH9KAHMq6c9nJyzIO6OGG11bRnwqwGgjW3ZaiPtUblHV6dMXJdn1FPadAx4teqkmE80mnQOf l > m3pFMBnw7pywmTJVSz3qyHTnTTSoZYT/NsLIPRvKMQnHxDarHKsKVrwvtjSUIyRUAy7+UOQG1BY V > /evlEr95NHNcIKfV8PorhxfU6fGsckNRWRzIVRe6mZeXSF2nliGdnXSocD7lMoq67zRXI6obj+O a > cPUqJ/ebu6rSCNc2BoCYUGPdTXuj0eixvm3gUPX1Q07F569OP1eVm2HdPlCn3lfXEeaBSjKseWV J > bKVFg0KfzulEPrbU1k2+HH45EZD9S6vGKLcZEnp834nYkrpeMb+eBmV9zx+zts8DpHJ0VdX7lmW k > wNfHoTsLN1Oz07MWPfvM0/I2419UbpOs2blu/tJKcv2tW7fkpdWWtX0X1itYr2A9yX97ZtfLqvb L > sF4x17NXX3+L7pStTkHa398X69+ge3dfpn6/r9fGFxKq62CEGYkga2Spb1ysnwcnNbI6jLXwUFX b > ChrHNA50n/H2b57Swf3b1jaD9h0Fh64Zqvfuvihvu1bZzzltX/zh83/o1gHlsKWlHAzHxBa3HMv 6 > t473xRa1HMsM1fT0qcrmXz1AyBw4NBc1qw4HmlraohbsyJHGwcE4JN3irJqeBw/1SODtsMrwBoB J > /O+P/x3C9gvvUzVOb4mHa4kR+ljlOare47qnNW80cOaYCk6LGm6H61CNBi4sPHJJ4Rqu1Q/cPRW 1 > WrV92dfrjkJmCe8bAHYTgnU3TKmpdujkQA8UijBKyD139ODgRE9mPkO+qc5N1fsoDurUHze5ck1 T > nZsqtynPGw3pDzXJgUezAz1TvrT2fSDPl9Xb57li5bmp+r6o+95gaWi2YSiHLS3lYDgmtnnLkXS w > 4n2xpaEc4X2qcvCOqD3y7VKJSq3W1IFLpXabqMiDm7iZdbtDKCoO5TT0qaL5FyBd8G9yvdbTp8o 1 > NrdP8jafTDOLO7MNAjVN8I8XIH2SrrFCekQbqCSvQOQO+gleAs5qgQ3BI+bSAOWwpaUcDMfElkQ 5 > kghWvC+2NJQjPaN/AQB2DGqs2wehCgAAkBCEKmDkng/KMQnHxJZkORapreJ9saWhHAjVLYZBSgC b > Ac3A2yNCqKqL68e/oP3ukOezBiwAAFEhWLdD5Jpqq+iGRfwZabZd0GhoXjYFRu7ZUI5JOCa2ZZU j > brDifbGloRxzNP8a07/NfSlDAAAI4gbr3t6nxgtsjgih6l7UQSxt+woU1KtRTgfs0XhiVAAAWMx j > evDgnfGCYN0c8Wqq5kUgfAHbc6/Ti87XVIgzSAkj92woxyQcExvKYUM5PPFCVc4so5t+3cnF/Vp F > BCsAAOykCKGqRv8GBqlTp75bczVrr637GMwEADCnx49/RLdufW688N+wGeYYqFSithuil2Wyrp3 P > zcP+ftdpzJrvxKhinpfVvS+4z1bOixqpVsw/DI7I3ISaU9Xdvn3f9HJtH4zcs6Eck3BMbKsoBwe p > u4SNCMb7YktDOSKHaqnt1kiblMi183lqOTmPqdqunN/UGE3creSodtjW+1Rzq7r56c7dmqvJiel m > 6lZ4SjqDCM1c7dD7ccDzp57ofc8o1yaI058KAOmHc1g3R4RQVaN/I89CIwczzQ7e4UWHeqXqeJq 4 > TLlKpV6HLji9RLA1Wg7V77hbscuQb7qB56gVU3CNtJGti/q1wV/GG1lyeld0LW5OLRcAAMAU8fp U > Iyzzj1G6QVmnR1ecbNdX1HMKdLzovKwinE86BTov39QrgskgdbKiBEGMcm0pjNyzoRyTcExs6yh H > UG0V74stDeWYo091Or7yUpRzVjPHBXJaDa8vc3hBnR7R4OGQhg8HctWFbuadL6yHdHbSocK5r9/ X > xE29Ytu5GlFdP25auQAA1gnNwOm3NxqNHuvbIbimWqQWj/T1D0ziUBKJ1HPvc/+Wg5nsJmBuhnX 7 > QJ16ny65fZUHBLkjip2SeFaLBoU+ndOJfCz348omX7ldEZD9y3GzLJPbvKrSKKBtmu87EVuS+5G v > oUFZ3/PH/NsPKZfalofDfhZupmanZy169pmn5W3Gv6jcvk+zc938pTXv+lu3bll9qklvn2G9gvU K > 1iurWs/fHQ8ePJC32ar2yzZ9PXv19bfoTtkeVLu/vy/Wv0H37r5M/X5fr40vcqiKlAzsV1VhyYN + > dIjKQOKHxx3QxKN9c3RVFfshsY1G1gpxHpzUyNrBFh6qaltB45jGge4TtH3FKFe8FyRD1wzVe3d f > lLddbqgmaZ5t8ofP/6FbB5TDlpZyMBwT27rLYf4gx/HwRC3HrFB99OiRXhtf5ObfsObPzM1DfUt x > m25jk82sDmW5Y9MYODSfDJUv9cheubRFbdORI3qDApWDM7TYZrkAAFKAA5WDFdInQqjyQB11GcK J > fk1uNuVmUj3IZ9zEGzroxyDPBfXOAe2e1rxRt5ljKjgtargdm2I/PBq4sPDIJYXLaZ1/2j0VtVq 9 > /WnlAgBICQ5W7uqBdIkQqqLWd14X9Txz+je9yP5TolLV7GstUdvf9xok31TngOptFQd16o/bV7m m > qc5Ndfdz2A7pDzVxyEe4WEOmfGnt+0Cel6q3P7Vc2ykNzTYM5bClpRwMx8SWpvcmDfC+eCL0qbr 0 > gCX9l8JNqhHCbkdxKK+yT3UZfbQAkG74dx9fKvpU3QsweP2UvCBQAQDWCf2r6RIhVNXFHzBf6vb i > EXNpgHLY0lIOhmNiQzlsKIcnRk0VAADSCLXV9Igx+vfEnskFAABSA8GaDhFC9Zqu5EUUelTL6dG y > E8v2T4+WdosMVsDIPRvKMQnHxIZy2FAOD5p/ExD8Q2P2JQwBAJKE2ur6RQjVoFG//iXuJQm3S/A x > UafSAACsEoJ1vVBTBYzc80E5JuGY2NJejlUHK94XT/RQlVcr0k2bR2fEY5b4IvQH8edkAwAA2Er R > QpWvh6svSTjpPp1hWPBaLTJICQC2E5qB1yNCqA7prMEXJ1SzvPTrfBVgJd/sU33QolrtFKN/Nxh G > 7tlQjkk4JrZNKceqghXviydCqKpTapz6ecAlCTNUrtrXTwQAANhVCw9Umnv+VCanWXNPQfGf68q T > g7v3BV8mUU7hFqlPly+1eBRy8YqA+6xyHUxOeQcAsCHQDLxaEUI1fD7VWPOn+vHAJznlmjr9RE6 3 > pgdAsW4lR7XDtj49RU0D5+5fDpASYSf3HUG34p9dxzN5nwjZYotKbX1qTLtErWJ6L26RRH8qRu7 Z > UI5JOCa2TSvHsoMV74snQqh6Tbw8n6oMsl6Nckao2fOpRjO86FiTf2fKVSr1OnTBqSoClyclr99 x > z35V58q605rmm24Qe/27YTj4G9k6BTVSB943fEgDseb2eNe3xV8DehhYywUAAPBEa/7NN2VtcTK Y > StQ2wm4xXCPu0dW1uHl9RT2nQMeLTisnwvmkU6Dz8k29whB2n9y3WfM2ygUAsKHQDLwaMfpUg66 s > NP+VlDLHBXJaDa8vc3hBHVHxHYgqodtPe6Gbeefr1xzS2UmHCudBtejw++S+D28a6zN081CVa1t h > 5J4N5ZiEY2Lb1HIsK1jxvnj2RDg+1reXatz/Kjj1Pl1yuy8PCCrqHk2nJOq9LRoU+nROJ/Kx3K8 p > a8GiVnmUEyHYtydFl9u8qtIooKrM952ILcn9yMFIDcrq58+6z79N7sNtZHWZDRz2s/CPD3Z61qJ n > n3la3mb85rv9oWY/gPmhiLL+1q1b4z7VRbaD9QrWK1ivbON68zuDrWq/LA3r2auvv0V3ynbb6/7 + > vlj/Bt27+zI9evRIr40vYqjySNwchY8L4mbgRa//q/ZxVRVBSiJsG1nqX3o1yaBgCw/V8PI69TY V > OsWQ+8T2b5769m2UK+YL5NA1Q/Xe3Rflbdeig4wWfT4A7KZd/+5YZqhGav5VI3G5JrlEsvnXoSx 3 > Zt7IktO7ovm7MTNUvjSbqbk/WF284rKcn3KfiNGJffN5urpcW8r8RbdOKIctLeVgOCa2TS8HB2q S > zcB4XzwRQrVL92UL7e0ps9XMUUuV54J6p6p0T2veaODMMRWcFjXcDtehGg1cWHjkUgSZm3RILbo / > Lth98dch3VzBrgEAViXpYAUl8kCl0vgck4Tkm+rcVD0QqTioU3/cvso1TXVuqhyolKvRYdvuTw3 E > fa8LT5iep6Y8N1UPkpLnrO721HYAABBNhD5VHshTpFapHTggCMIts08V/akAkIRd/C5Zc59qnm7 z > vs3TXwAAYCugGThZMfpUe1TL6SbRiSW9l/EDAABYlch9qrC9MHLPhnJMwjGxbVs5Fq2t4n3xRGr + > DR/16y4YyAMAsMnQDJwM1FQ3EAYpAQCkU0io8ojfiNfb9Z1vCpvHfwmvdUE5bGkpB8MxsW1rOea t > reJ98USvqcpzQMMm+t5twYO3Zl8XGAAgbdAMvBg0/yYguJ9ZnZ8KALBpEKzzQ6gCRu75oByTcEx s > KIcN5fAgVDcMBikBwCqgtjofhCoAAARCsMaHUAWM3PNBOSbhmNhQDhvK4UGoAgBAKNRW45kaquP p > z3jJ1agXdP3forww8HzkOa7utvznug7p7Mjbz1HAuTzDsyM6iHYyLVVCTwcKvy/69lcD/akAsA4 I > 1ujWV1Pl816LA6r31ekncm7VozMRpUq3kqPaYVufnqLmVnXzrVtRQZur9dSKGbqVIoVFf9B9cbe / > 6TByz4ZyTMIxsaEcNpTDExKqUa73ay7xr/07vOhQr1QdTzyeKVep1OvQBaeqCNxGy6H6HXerqjz u > dK75ptpvv+6oFVNwbbORrZM9c54Sdl+c7QMA7ALUVqNJUZ/qDco6Pbq6Fjevr6jnFOhYB+7cRDi f > dAp0Xr6pVxim3QcAABMQrLOtLVQzxwVyzInPhxfU6RENHg5p+HAgV13oZlhe4ndtDunspEOF8zJ N > ZvO0+3YPRu7ZUI5JOCY2lMOGcnj2RqPRY317qbip1e2jdOp9uuR2Xx6o5A50ckpUohYNCn06pxP 5 > 2FJbN/ly/2tOhGD/ctxczOQ2r6o0ctuFDXzfidiS3I8cjNSgrH7+tPtM07bPOOxn4WZkdnrWome f > eVreZvzmuwOPzH4A80Nhrr9169Z4kFKUx2O9gvUK1itYryy6nr+PHjx4sPL9uhZZz159/S26U7Y 7 > /vb398X6N+je3Zfp0aNHem18KwvV2Xi0b46uqiJISYRtI0v9S68myYOHGlkdxlp46KltBY0zcup t > KnSKIfdF3X40HLpmqN67+6K87YozmjfOYwEAlm2Tv5OWGarp6VOVzb8OZW+I2zey5PSuiLtX55O h > 8qU5kKotasGOHGl8Wc5Puc9XVd0R5i+6dUI5bGkpB8MxsaEcdv8qjodnfaHqm4e1e1rzRgNnjqn g > tKjhdrjq0cCFhUcuAQAALE9IqKpJyt1BQrOXOSYpzzfVual6G8VBnfrjZlauaapzU+X2czU6bE/ 2 > eU7gvtctnDAdTb8AkEZmbRWUkD5VDtXwCyZMKlF7jnNVtx3/IOAmZrZInypCFQDSbG/vU/oWB+2 P > 9K30WkOf6vIv/gAAAJuPA/XBg3fGixmwuyg9A5UAAAA2XMRQtS9uP7lsXz/mLsHIPRvKMQnHxIZ y > pFMajkekUFUXt+eLM8CqoT8VANKM+1Bv3frceNmEPtVlihCqXbovRyzdlv2sbU7Wkjd7jAxaJ0t 8 > eikAAOwe7kvlMN31QGWR+1RLt4OGIuXpDs/kstCFGmDd/JfwWheUw5aWcjAcExvKYUM5PLEHKt3 I > ihAdPCT3OviZm4f61u4K7meefV1gAADYLpFDtXVfDUWSIdqr0akemdRVbcM7bfIUI7UsCv2pAAC b > JUKo5um27Di9T2d82cD8bdmP2iqq2lhx4JBTuo3zVDcYRjLaUI5JOCY2lMOGcngi1VTzzT7VBy3 q > qL+o2a+TI2+zAp3POYsLAADANonY/KtmfRnP4pIp06XbzGlMzwYAALDLIoSqurh+BVd32FoYuWd D > OSbhmNhQDhvK4Yk8UCmUnBnmiNxZ2iAZGKQEALB5poSqO/2bmq3GHZg0seRq1FNPiE/Oqepuy3+ p > Q/vSiEcBqT08O6KDSFVofi1hwR9wn/yh4O0btXQAAIhi8ZoqcwoUe/5wDq7igOp91Tcr51Y9Ohu f > /6oujehduYnnVnXDrVtRYZerRYvzbiV8GrvJ+0TIyvlbdZ9xv06D4nbXxDFyz4ZyTMIxsaEcNpT D > MyVU3enf1KUIS27IBC1zDFYaXnSoV6qOJx7PlKtU6nXogsNLBG6j5VD9jjuqWJXFHWScb6r99vl q > TjNwbbaRrQdetzjovuFZg1pOnca7zhxTwenRFS4ZBQAAMyRTU03EDcq64XV9Rb15ar9+IpxPOgU 6 > L9/UKwwh92XKl74fCdd0NXf7NgAA7JIIoWrXEpOSOS6Q02p4zarDC+qI8Bo8HNLw4UCuutDNvPP 1 > aw7p7KRDhfOgWvS0+2yy5irqsoGXPl6SVQ9Swsg9G8oxCcfEhnLYUA7P3mg0eqxvT8d9oBODkhy q > 9y/HTbjTcFOr2wfq1PvqnFceqFTUPZoOTy3XokGhT+d0Ih/LTc4yzOW+RQj69iW3eVWlUUDi830 n > Ykvq3FoejNSgrH7+tPsssnzc7xv8GjnsZ+FmanZ61qJnn3la3mb85rvhafYDTFvvwnoF6xWsV7B e > wXolbD179fW36E7Z7hTc398X69+ge3dfpkePHum18UULVTP8AozDbyE82jdHV1WxLRL7a2SpbzT D > 8uCkRlaHsRYeqmpbQeOYnHqbCp1iyH3e9tWPAIr8oyEIh64Zqvfuvihvu8JqpDidBgBgeZYZqhG a > f0VANVSgTgxWkpOrErUa3qjducnmX4eyPDHrjSw5C00np64A5ZWVB1txrZqvCpWfcl9ygbpJzF9 0 > 64Ry2NJSDoZjYkM5bCiHJ0KoqoE6XIubqBDmm2oE7jwBKM9R9c5N7Z7WvNHAcsRtixpuh+tQjQY u > LDxyKQJRrnUGKmqpAACba32jf2UgD6ioByIVB3Xqj1Oba5rq3FQ5UEmeNxoh5LjvdeIiEvGoqex 6 > VMt5g6R4Cbr4BAAAgClCn6rXPznRd+r2tToiEHFh/QkcxtzEzKL2qaKmCgCwXGvuUxW1xqruO/V f > qlAPXipVEagAAADRmn/zTXm5vsnrF6kBPouP/AUAANh80ftUzTlUx8tujI5dlXU1/WLkng3lmIR j > YkM5bCiHJyRU+YIImJ0FAAAgjvWN/gUAANgyCFWYuITXuqActrSUg+GY2FAOG8rhQagmwBoRbSx x > 4FQaAIDNNzVUJ06hCV0Wu+DCprMHb3kLAADsFtRUASP3fFCOSTgmNpTDhnJ4pobqxAX0Q5cm4VR V > AADYdaipAgAAJAShmgLrHqSEkXs2lGMSjokN5bChHB6EKgAAQEJCQjVPzdEKrukr51QNG0HMs+N 4 > I4yDpl7jycQPIl32ia8QdUTBs7dN3ie3Oy5X2PMAAABs66up8tynxYG8ID8PdpJzqx6diShVupU c > 1Q7beiCUmlvVzc9uRQVejueji6BbKZKaT2fSxH1ykvJDaruDsNqHVDvxyrWNMHLPhnJMwjGxoRw 2 > lMOztlAdXnSoV6qOL8ifKVep1OvQBaeXCNxGy6H6HbeqbNec8003iCfnzfHjWmcjWyd75jwl8D6 e > kccczXwjS07viq71nwAAAGFS1Kd6g7JOj644va6vqOcU6HjRGXBEOJ90CnRevqlXGKbdZ5Dh72R F > 6ZYDV1ICANgeawvVzHGBnFbD668cXlCnRzR4OKThw4FcdaGbeXmJP2POkM5OOlQ4D5pAfdp9Gjd P > yyZmovq0x20BjNyzoRyTcExsKIcN5fDsjUajx/r2UnFTq9sH6tT7dMntvjxQqah7NJ0SlahFg0K f > zulEPpYvPiGbfDngciIE+/b8rXKbV1UaBYyo4vtOxJbkfuRgpAZl9fOn3TchZN+Mw34WbqZmp2c t > evaZp+Vtxm8+11LZgwcP5H+Z+aEw+wewXsF6BesVrFewXomynr36+lt0p2x3Cu7v74v1b9C9uy/ T > o0eP9Nr4Vhaqs/Fo3xxdVUWQkgjbRpb6l14NkQcnNbI6jLXwUFXbChrH5NTbVOgUQ+6zt+8K2nc U > HLpmqN67+6K87XJDFc2/AACrs8xQTU+fqmz+dSjLnZcLDw7KUPlSj96VS1vUgh050viynJ9yX1B o > Dkm3Ridqb+9T4v/598z6f9OYv+jWCeWwpaUcDMfEhnLYUA7P+kJVnqPqnZvaPa15o4Ezx1RwWtR w > O1yHajRwYeGRS7Nx7dc6Z7Z7Kmq1ye6bA/XBg3fGiwpYAADYdOsL1XxTnZuqByIVB3Xqj5txuaa p > zk2VA5VyNTpsh/R5muTgosWmocuUL61yHchzaSPsGwAAdl6K+lS3T1ifqltTdd269Tl6/PhH+i8 A > AFim3ehT3SEcoByk7oJABQDYDgjVNeEgdRcAANgOCNU1wog5G8phS0s5GI6JDeWwoRwehCoAAEB C > EKoAAAAJQaiukf/SWeuCcthQjkk4JjaUw4ZyeBCqCZDnswYsAACwWxCqCfAueWgvAACwWxCqa4Q R > czaUw5aWcjAcExvKYUM5PAhVAACAhCBUAQAAEoJQXSOMmLOhHLa0lIPhmNhQDhvK4UGoAgAAJGS 9 > oSrnVHVPQfFP2TaksyPv9JQjd25Vg5z7tBJlorcuVQ6OKGATwrz3AQAA2NYXqjz3qZyrVJ1+Iuc w > PToTUap0KzmqHbb16SlqblU3P7sVFbS5Wk+tmKFbKVJL3/ab974kYMScDeWwpaUcDMfEhnLYUA7 P > 2kJ1eNGhXqk6nvw7U65SqdehC05VEbiNlkP1O+6k5XlqinB15zDPN90gdtSKKbg228jWyZ45T5n 3 > PgAAgCAp6lO9QVmnR1fX4ub1FfWcAh3rwJ2bCOeTToHOyzf1CsO89wEAAIRYW6hmjgvktBpef+X w > gjo9osHDIQ0fDuSqC93My0ukrlPLkM5OOlQ4L9NkNs97X7IwYs6GctjSUg6GY2JDOWwoh2dvNBo 9 > 1reXiptT3T5Qp96nS2735YFKRd1r6ZSoRC0aFPp0TifysaW2bvIVNcejnAi6/uW4uZjJbV5VaeS 2 > Cxv4vhOxJbkfOeCoQVn9/Hnv8+Own8W9XOHpWYuefeZpeZuZb77ZD4D1CtYrWK9gvYL1yiLr2au v > v0V3ynbn3v7+vlj/Bt27+zI9evRIr41vZaE6G4/2zdFVVQQpibBtZKl/6dUWeXBSI6vDWAsPVbW t > oHFMTr1NhU5xjvvsfcfFoXrv7ov6LwAAWJdlhmp6+lRl869D2Rvi9o0sOb0r4u7V+WSofOld2J5 H > D5fIkSONL8v5Oe+bP1DDmL+k1gnlsKEck3BMbCiHDeXwrC9U5Tmq3rmp3dOaNxo4c0wFp0UNt8N 1 > qEYDFxYeuQQAALA86wvVfFOdm6oHIhUHdeqPm3G5pqnOTZUDlXI1OmwH92tauO914iISAAAAq5G i > PtXthj5VAIB02JGBStuNQxUAANIBoQoAALAk2zf6FwAAYMOhprpGUS4eAQAA0fHpkPNA8+8W4FC d > 9QGY9Rhsw4Zt2JLYBtuUsmIbNmwjOjT/AgAApAxCFQAAICEIVQAAgIQgVFNu3v4BE7ZhwzZs2IY N > 27Bt0zZWAaEKAACQEITqhkvLrzeUw4ZyTMIxsaEctjR9VheBUAUAAEgIQnWN8AvRhnLY0vTLHcf E > hnLYUA4PQhUAACAhCFUAAICEIFQBAAASglBdtm5FXo/SXSpdvd4v6uPmFXX7wzM6ivK4ecV+nV2 q > HBzR2VD/mZTI5RjS2ZH3uKOkCzLX+7KE42EYnh3RwbQ3ZtmfVW1mOZb9WdVmlmNsSZ9VbXY5lvx Z > 1eK9L0s4HlHf9xV9Tv0Qqksl/pEVW1Rqj2QH+qhdolaxItb6RX3cvGKUI1ejQ/dx/ToNikn+o4j / > OruVIiU/vXv0cnQrOaodttXjRm06rOUS/Mc55/vSPqRaLsnPh9KtqC+fXK2n1wSJ/x7GFbkcS/2 s > Ri2HZzmf1ejlWO5nNWo5lv1Zjfq+L/9zGgahukzDhzSgEt3O67/zt8VfA3ro/wBEfdy8Im5/eNa g > llOnO+7jMsdUcHp0da3/XlTM18m/iBvZunhMwiK/L2fUaDlUHx+QPDXFP9Cm++eiYn0+HMre0H8 n > /fnQ8k31BdSvO3pNgJjv4TyilGPpn1Uh0vHQlvZZFaK9L0v+rArRPx/L+6xGft9X8DkNg1Bdpus r > 6jlZcj9fJG5lgz4AUR83r4jbz5QvaXRZpoz+WzyRrqL9SI8mzusUXxInnQKdl2/qFQmK9b4U6Ng 7 > IMmKWo5MmaqlHnUu1DeC/GIpVam8rHJNE+c9XKKlf1bjWOZnNaplf1ajWvJnNfL7vsbPKUJ1iYY P > B0SHN40PQIZuHhINfD+Xoj5uXvNuX/6DMH/tLSh6OYZ0dtKhwrn5jyc5sd4X4UI3e/GSZHNanPe F > awnVq5xqfruq0ijJKkgM836Wli3pz2p0y/2sRrXsz2ocq/yshr3v6/ycIlQhWLdCuRpRvd+kVX9 P > Dc9OqFM4X09NzK9Xo6vbqtlrGf120agBKPfdcty+L76wVtM/tBHwWVV27bO6xvd9GoTqEmXUTyP x > MXMNSf2Asv8FRn3cvOJuX47uKw7Eh/Uy0S+LaOUY0kWnJ74f1C/dgwMe/NGjWi650Yyx3her/8Z u > 2lpU5PeleyoHoIx/8Oeb1C61qLH6b8zYn6VlW9ZnNZrlf1ajWvZnNbIVfVZnve/r/JwiVJfpRpa c > 3hV5zfjc/m904ruiPm5eMbbPH1b1628JX1KRypGh8qX+lSuXNpXIEeUZ0WVSBZr7fUlYxHLIpiz r > C2KNYnyWlm2pn9VIVvBZjWrZn9WIVvFZjfS+r/FzilBdpsxNOhS/Xe+7bR/d++KvQ5r4sRT1cfO K > uv1xc8qSvqSW/Tqjivy+8MhC41f2UI2wLCQ1GiRiOTLHBfEF0aFxpSPpcsSRlvdw2Z/VTbPsz2p E > S/+sRn3f1/g5RaguVZ6a8vwoPXhAnjel2//Fh+1o3Ncw5XGJiFaO7n0+y041X6nmLLUk15QV9Xg s > W9RycE1Ene8nHyf+NR+2k/wSj1iOTJku5fl++nGJl2OGlX5Wp1jpZ3WKlX5Wp1jpZ3WKFX5Wp77 v > Kfmc7o1Go8f6NgAAwE7a39+nV19/g+7dfZkePXqk18aHmioAAEBCEKoAAAAJQagCAAAkBKEKAAC Q > EIQqAABAQhCqAAAACUGoAgAAJAShCgAAkBCEKixJlyrm1U7ikldHUc+fPYXVgvuaKrlty4uA622 F > Lkdn67/Gb+CxX+YxjqBbsY/TOssSyn+MVnDMYv07gVVAqMIWyFNTX9Q8+QuZL2PbJWrrbXoLX4x d > 6NUol4ZgnbDMYzxdl+cILfLl6dTF6s3jJWeISeXxYus7ZrA+CFWAVFDXKpVEsJ6i1qGIGqrMUxm o > 5jVkObC8HyInqaqxwi5DqMIKqQmM3aY7/zJuvuImrVyNevpPeVFseWfI8ysVXzNbxP1IXhOdtYw f > FNKEF9QcuWiNiaer0jctgU2f/gu6h7wOsUw0C04re+ixj3EcrLLFeS/8xHMbMlFF5b4acFH2PN1 2 > f4d0LrxjH+l4CfOW3S30xPN5PlWT/5gl8LkUy/hxoe+VFvU4QKIQqrA+pbZqytM1tFbxiOR3D89 0 > 0a+PA6bUFo8Zz3rskev5+c3bek2IsP3ILy79Reg+xq39tIr2F5RBTZCsvj5VGfpU58Iu2nR7faW / > IL15Hyf3NSL1MlpUPJj2OkbUl4UyX2+Eskc89ixa2XxC34sAwwvq6MQo3Q4uQ76p9ju6LBNnbtQ y > zVN293F8PLzne03S+iVFF+tzGfB+Tnmv5npvIBEIVVgP/rJwv6zzt1WQiUjpjCdinEE8P+S73jZ t > P8OHNJB/i4eNv7S9frDgMOnSaU1HX72vy5Ch8rn+cpu76VZ8keovQa9W5u3LfL35pg5C8Tpqcmf B > Zc6Uq77jmmTZg7YVVDbDou/5TFHLNF/Z3cfZzz8f16DzTf2DLIqpxyLq+xnGK9/0zw0sA0IVdpe c > yFhR8y5GaBqTkx0z38TLXGvQX4TG92AIri34m+VUzcSsbXj7EuutmlqGjgvy21Fs6v7sMrsSKbs W > tq15y5aEqGVatOzjH2P+56dE0p8biAWhCjtM1Qi8Zjsz7JbZ9+Qb/Ws04bWKwfsdT7asl5xbEzH I > Jj/jMZN9fJCIcTP9ciXxfkb53ECyEKqw88b9cryME1YE7KpO1bD6xlrUmOjwMk8l8S9N8dNADYB R > X5hmYMdojkyjzDF5FavgnzjydBsOjFW9VyuR1Ps563MDy4BQBTDlm+MBIdS7omt1yxPWF7joSfh G > gIxHsob2OxqjSDlMuqekKiD8JTrlyzLJsk8p24U3umjBL+4Mlas6RlqNgME1Xbqvq25O4ZgyUcu 0 > aNlDn5+QqO9nmCmvz/rc6LWQLIQqpN7g4ZL++RunHHhhYg7yCPpizdMdHbp84QH1PPFldaJPbXD q > dGeuJDECpNch9V0YtC+xt7MT/aUrilgtU2Z8Ko75JcpfoP7mwvhlDz/2wWXrVnJeIMx3IGziR45 q > POhRLWeOWjVGyIpyn8vRQlHLtGjZzeefTI7YXVTk99PmvVfBr2/ic6NuQsIQqpBOmTKNM0Z8MSz l > l7X4wvZOZ9C/4PUXI48KNUdemjLlS9/z9Jex+HLv61M75mLUMGon6vXKfemmYbeMqlmQazF6YJH R > fCyPlXwdbkDYIpU94rGf3NaBvlADN1maF2pYjGyel/vhYFX7sd4n45hHLdOiZefnqxYNt0wJBSq L > 8X7yY4PeK/n6Zn1uYCn2RqPRY30bAABgJ+3v79Orr79B9+6+TI8ePdJrlUqlQs1mU//lCVqPmio A > AMAMHKAm/98uhCoAAEAEbpCGBSpDqAIAAExhNvGagRrUJIxQBQAAmMEfoEGByhCqAAAAEbhBGha o > DKEKAAAQ0bRAZQhVAACAhCBUAQAAEoJQBQAASAhCFQAAICF7/7LexGUKAQAAEoBr/wIAACQEzb8 A > AAAJQagCAAAkBKEKAACQEIQqAABAQhCqAAAACUGoAgAAJAShCgAAYPirv/orfSs+hCoAAEBCcPE H > AADYSH/8x3+sbyXjV37lV+R/uab6cz/3c/J2XAhVAADYSByqn/nMZ/Rfk9pv/y/00U8+pI8++kg u > H3/8CZ38xpv6XtsPfvCDREIVzb8AALB1/u9/8z/Tf/vPivSrJ1+mUvnL4r//hP5J6b+m/+3r/1Q / > YjkQqgAAsFX+r7f+JxGo/5g++UTUTj/6kD75+Cf0k7//j3J5/vl/SK9Wi/qRyUOoAgDAVvnJT0S I > ymbfn9DzX25Q4R//JhX/u2/Sj//uP9Lf/+j/o+//v3+jH5k8hCoAAGyVjz76mD7+mJdP6Kc//Sn 9 > 4R/+IT3z6Z+hD0Wo/vjvHsn+1WVBqAIAwFb5Z5V/TV+t/C79D+Vv0R/8wR/Qb9b+Gyr96j+iD3/ 8 > NzJUP/nkE/3I5CFUAQBg67z11lv0e7/3e/R//KtfpRde+Bz95MO/pQ9/9Lf0td8c0DvvvKMflTy E > KgAAbKXf/de/Tr/6T5+ljz/8O/r4x/+JKv/re/T9739f37scCFUAANhKP/MzIuL2iB4/fkwff/x T > vXa5EKoAALCl9uijD/9WLh+LZRUQqgAAsJX++5ebdOfrPfofv/Hv6Z//1gf0J3/yJ/qe5UGoAgD A > Vvo3//uv0+v/4r+g11/+z+lfnfwDunXrlr4nWX/2Z38mF4ZQBQCArcTnqX74o7+hH//ob+nDv/9 P > eu1yIVQBAGArfSRC9ccffkI/+ein9NEne2rg0hL80i/9klwYQhUAALbSr7/yLfrGt/4Dvfq7P6b G > //mf0Xe/+119z+LMJl80/wIAwE5ot9v0ne98h7rdrl6zXAhVAACAmMwmX/M2JikHAICNxJOUJ2n W > JOVuEy8HaNhthCoAAIABoQoAAJAC6FMFAABIyN4H7RdRUwUAAFgY0f8Pv2raZV7mqO4AAAAASUV O > RK5CYII= > --001a113d6a0a1ede02053654edd6-- > > From owner-chemistry@ccl.net Tue Jun 28 14:26:01 2016 From: "teja reddy reddyteja80]=[gmail.com" To: CCL Subject: CCL: correct transition state or not Message-Id: <-52257-160628130953-31559-xMFnDSYB5PWkSHn8UzDnNw()server.ccl.net> X-Original-From: teja reddy Content-Type: multipart/alternative; boundary=001a113deff4117613053659b409 Date: Tue, 28 Jun 2016 22:39:44 +0530 MIME-Version: 1.0 Sent to CCL by: teja reddy [reddyteja80!A!gmail.com] --001a113deff4117613053659b409 Content-Type: text/plain; charset=UTF-8 thank you Dear Dr. Tobias Kraemer , I have tried both forward and reverse and optimized the last point geometry on IRC, in each case it is optimized as product intermediate. can any one suggest regarding this Correct transition state characterization. On 28 June 2016 at 20:31, Tobias Kraemer t.kraemer~!~hw.ac.uk < owner-chemistry/a\ccl.net> wrote: > > Sent to CCL by: "Tobias Kraemer" [t.kraemer:_:hw.ac.uk] > Dear Teja, > > > At first glance this looks like a reasonable IRC, quite flat around the TS > (not sure what the outlier means). A reasonable thing to do next is to > optimize the last point of the IRC (1.8 on the X-coordinate) and see where > this leads you. Of course you should also run the IRC job for the other > direction (reverse or forward, whichever way you look at this) and do the > same thing here, optimize the last point on the trajectory. Inspection of > these optimized structures help you to confirm if the TS is reasonable and > the one you were looking for. I often look the at the animation of the > imaginary mode itself, this tells me already if this TS corresponds to the > desired reaction coordinate. You can also do a quick version of the above > protocol, displace the TS geometry by a small increment in both directions > of the TS along the imaginary mode (use GaussView to do this), and optimize > these new (initial) geometries to their nearest minima. In the end, it is a > combination of visual inspection of the TS as well as the ground state > geometries which will reveal if this is the right TS for the reaction. > > Hope this helps > > > Tobi > > > > Dr. Tobias Kraemer MRSC > Research Associate > Institute of Chemical Sciences > School of Engineering & Physical Sciences > Heriot-Watt University > Edinburgh EH14 4AS > United Kingdom > email: t.kraemer a hw.ac.uk > phone: +44 (0)131 451 3259 > > > "teja reddy reddyteja80%gmail.com" wrote: > > > > Sent to CCL by: teja reddy [reddyteja80~~gmail.com] > > --001a113d6a0a1ede02053654edd6 > > Content-Type: multipart/alternative; > boundary=001a113d6a0a1eddff053654edd5 > > > > --001a113d6a0a1eddff053654edd5 > > Content-Type: text/plain; charset=UTF-8 > > Content-Transfer-Encoding: quoted-printable > > > > Dear friends, =E2=80=8BI have optimized TBP transition state which is > showi= > > ng > > -216cm-1 negative frequency but is showing only 9 points on the curve > like > > shown below. can anyone help me is it a correct transition state > > [image: Inline images 1] > > > > --001a113d6a0a1eddff053654edd5 > > Content-Type: text/html; charset=UTF-8 > > Content-Transfer-Encoding: quoted-printable > > > >
style=3D"color:rgb(0,0,0)">De= > > ar friends, =E2=80=8BI have optimized TBP transition state which is > showing= > > -216cm-1 negative frequency but is showing only 9 points on the curve > like= > > shown below. can anyone help me is it a correct transition state
> > class=3D"gmail_default" style=3D"color:rgb(0,0,0)"> heig= > > ht=3D"434" alt=3D"Inline images 1" src=3D"cid:ii_15596c33e3e5b53d"> > <= > > i>
>
> >
smartmail=3D"gmail_signatur= > > e">
d= > > ir=3D"ltr">
> > nt color=3D"#000000">
fa= > > mily:courier new,monospace"> color=3D"#000000">=C2=A0=C2=A0=C2= > > > =A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 > = > >
> >
> > > > --001a113d6a0a1eddff053654edd5-- > > --001a113d6a0a1ede02053654edd6 > > Content-Type: image/png; name="image.png" > > Content-Disposition: inline; filename="image.png" > > Content-Transfer-Encoding: base64 > > Content-ID: > > X-Attachment-Id: ii_15596c33e3e5b53d > > > > > iVBORw0KGgoAAAANSUhEUgAAAdUAAAGyCAYAAACySF4VAAAAAXNSR0IArs4c6QAAAARnQU1BAAC > x > > > jwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAEqjSURBVHhe7d1fjCvXfSf4Xwf75HnoBhYIECB > Y > > > KLw3Itx6URi7MMLuyFcO2G377guxIgbjxU64mpXTlDdXnIEZXGr3ruHRrKiE2R2qF1a3o4lA5CG > 7 > > > Czog8nCd6SZiXwVeDEA5DLAD0WjlNqOHAAECzA5vJnEsS/Ld8zvnFOucYhVZRRbJIvn9GGWxi2T > V > > > YZGXX54/VWfvsUAAAACwsJ/R/wUAAIAFIVQBAAASglAFAABISGif6t7enr41HbpkAQAAlKmhOis > w > > > 3eBFsAIAAPhCNax2GhaaMnj5v2JBsAIAwK6b6FPlaDQX9ujRI/nfs7Mz+sY3viH/63JjOGpzMQA > A > > > bC7+ro+ypA2X6U//9E/1X5P4viTKHWug0l//9V/TX/7lX8r/Mq6dustMH7xNz3/60/Rpd3n+bfp > A > > > 3yV97xWx/hX6nv7T9j16hZ/zSvC9H7z9vHju8/S2ucEp2/veK5+m560HC/x4c/tTyzMLl9d9ri6 > 7 > > > sUy+jA/o7eeNx/iPjeTfjvl6+T7f6wcAWBLzuz9oSaMf/OAH9Mx/+V8FBiuv4/v4MYuKFao/+7M > / > > > Sz//8z8v/xsLB+oXv0Nf+qMf0g9/qJY3n3xIf6HuVIHSJSrIv8M8RU+9/82A4Pge/U7jPX2bzd7 > e > > > c/kCvfdQ7d31vW6HCvnnxK2o5YnjKaq6r/3NAnVeMsJa/tj4Ij38qndsfvjbRN8NTHNvO39UJWp > 8 > > > LSh8p0H4AsBu+uVf/mX6d//P9yeC1Q1Uvo8fs6hYofrlL3/Z+m80IqS+1qAn3/w2vfCEXiU899p > r > > > xBFG9AS98G0RFK/l5V/TPPkk0Xe+60uE73WpUygYARhhe79wk57qdL1gE7e6nQLJTI1Rnrk8lxd > l > > > fZ/+Qr4M99j8kF5TB0N54gV6wfw7wBMvfJUK732H/IcDAACC+YM16UBlE6HKLcrmsrAPvkvfec8 > N > > > rBi4+dXXDHrzK1+lJxu/Y4ShCKVvvk/Vr0QIQHN7T3yevvRUh7ruhmQw53XILxnv66kv0ef5B8a > 8 > > > x2YWX1O7am7mWupL1KH3qPFFsT6kKR0AYJuZwZp0oDIrVP1t4qPRSC6u3//937f+G9lTN+kX9E3 > V > > > /8lf9vM0Qz5H+YIRhhxKpAMqlifo8196it5X1UWj6XdZdJDx6+7m6YfffkGUQDOOTRwfvP1NL5w > t > > > Ijy/qGq/sin5j6r0/kt8rJ+j1374pqgl6yZkq2oMAOtgDuyZtsDmmNr8u7+/P16Yf6BSZO+5/af > c > > > bPlt8WXPX+4zPPeaHT7ac18RIfFNVeP83u+I8Pjq5GMC+bb3xOe/xG3JYjsf0F+8/xTdjJNsVk0 > w > > > ymAmHWQi4OxmZ8E4NrN54fzFxpP0ZsDxoQ/+gt4XR3f8G+GJF+irhffI14UMAClgVmSmLZAcs8n > X > > > bApOSuQ+1evra2ugEv8dyRO/QE+O+xATwE23on763e+9Td98v0pfmbfCNd7OHLVdEVTfdgcV/dD > t > > > G45APO+3q+/TN90qur8ZeiZjwFOc/QIAwEQfqr+PNQkzQ9U9N/Xy8pKOjo7o61//uvwv/+0/ZzX > Y > > > cyQql6KGFfP0lIA+VeUJeuGrT1LjpQbRlz4frZbKJrbHTcCiXHG3syAeYPRk42u66ZtfC48G9p1 > m > > > I2rCb8c6WAb5I8ZsIhc/PsaDsAAAdlPYoKSkg3VmqJpNvjdu3JDr+L9xmoJlk++bRC+Nm0xfove > r > > > v22NBo7lua9Q9akCfXXuDSjcBPyU+N+X4nfKLkD/yHBPh+Fmadnv6R4bsXyN6PNzh+Bz9Jq5PXk > q > > > k1ur5T5pDFQCgMUE9fuaSxp95jOfmQhUlxus/JhF7T0OabDnA8N3cU2Ug5ObfMvlsr5X1WDN9e7 > j > > > AQAAdtXMUI0KoQoAALtuaqjGhVAFAIBdFhqqAAAAEE/kU2oAAABgOoQqAABAQhCqAAAACUGoAgA > A > > > JAShCgAAkBCEKgAAQEIQqgAAAAnZG41GOE8VAAAgAaipAgAAJAShCgAAkBCEKgAAQEIQqgAAAAk > R > > > odqlysEBHYyXIzob6nvlfebfAAAAEEbXVB2q90c0Go2oXyeqnZxRvBxF+AIAAEw0/2bKVSr1OnS > B > > > gAQAAIglXp/q8IyOjKbiSpdXci21SC3qUS0n1suVQzo78j8OAABgu02E6vCsQS2nQMcZvWJMhGe > u > > > Rodt1Uw86tdpUOQm3zw1R20quU3Izbx46CnVDtvqcWLhVQAAANtOh6quZYpaZa52SO3LMk1k6vA > h > > > DUR03nYDMlOmaqlHV9f6b9ONLDmtIh2hkxUAAHbIxECl0ahJC1csReBeim2d0wmafwEAYGdE71P > N > > > 3KRDatF9NyCHZ9RoGTXXAJnyJfXrDg0eosYKAADbL8ZApTw1ZT+qHoCU61Ch79Zq83S7ZAxU6lb > G > > > g5S4OblanmhMBgAA2DqYpQYAACAhMWqqAAAAMA1CFQAAICEIVQAAgIQgVAEAABKCUAUAAEgIQhU > A > > > ACAhCFUAAICEIFQBAAASglAFAABICEIVAAAgIQhVAACAhCBUAQAAErL3L+tNXFAfAAAgAQhVAAA > A > > > 7d7dl+nRo0f6r/j2Hgv6NgAAwM569fU3Fg9VzKcKAAC7bn9/P5FQxUAlAACAhCBUAQAAEoJQBQA > A > > > SAhCFQAAIKJKpaJvBUOoAgAAROAG6rRgRagCAADM4A/SsGBFqAIAAExhBmiz2dS3goMVoQoAABC > B > > > G6hmsPohVGHNulQ5OKCDqEulq5+3WsM387oMeXpzqFeG6VbsMs9Y1vSSNkasY58yQWX31k1f8tN > e > > > bNhnLP8mbdgh2hj+IA0LVoQqAEAKvftKLiBY9Y/QYkv/7fPuK5QT908NZIgtLECD1iNUYc3y1By > N > > > aGQs/dc+q+/7LL3Wt+8bNfP6vni6FffXfEV8La3OZ1/r2+UPWOZ8SbAFSu2Az0T/NfHJV9595dT > 4 > > > vA7pzXyRvDgtUdt8Xruk1/Pzfm3javXbAqEKAJAmmZfoW+Mflu/Rn7vh2D2lV97Vtz/7GvVHTfG > T > > > 1JBvGoH8Lr1yin6FdUCowkbzaqD24vVTquYyr7WsRUV+jPuAFPVNzexrC+l8DT4Gk/2PYcfK2y7 > X > > > hALuHy+qlm9ux1+kafdNSODYz37/lfmObbTjsSrd++6H+LP02rdeooz+yyICuevWXNEEshYIVdh > Q > > > /rC0tYriS2/Gt7r8op3WN5W2QR+tou81TTsGoqaSi9O3xtvKeTWhKfJ3vObJ1n27PN73/mt0Z8p > 3 > > > +uLHfvH33xJ4bKMdj8QN36RfG+/4KfpFmZ5D+vP35ApxbAv0hcBEhTRAqMJG6laMviXZFKZ/nRv > 9 > > > UfxFWemqPluvu0n3QzWJTsdfXGbfVJ/GLW/vdujfLpiqPNgkuJajlynhMe6PtV7TffF1r1jHoNT > W > > > 5eelLV6REt63ZrxmUaMJ3ZbRTzeW+QIVvFQdl0dUpcbb+GzhC8E1Kam78LGP/v7r2z5zH9ug47E > A > > > Gf7+z0TuFfGTSCm13Sbea3p/nLO/OOXYQhKur6/nXhCqsIHsGlG/azSFcfOX8cVn16RM5gAps28 > q > > > Q18YJ8a79P61vrliPICl+5J+VeI1/cb4Jbl9bL5jYDX1iddm9K11JtKJB4CZr3nKtvJN4weJyzx > G > > > LXIPsdk8WZhalVr02C/2/i90bAOPR/Lc0EcL7uZBqMLmGf65+PrTgn6152+Pa2r03p9HakY0awq > 5 > > > BNv8Zo7+NQMhDvMY6NMozNdg1nbenfXLYNbxDJD5QmFcw1PBZQRR6TfIzazp5jz2ib7/AeY4HvO > y > > > R/96NXVu4bBr2TfoSfeAz/OaYGUQqrCz1CAXo5lvWy3jS9jfBGw0/ZZuz65e7cyxjyVDL3W9pvt > W > > > 0RwIlaFffErfTKBbApYHoQqbJ/OL5H6/BAaG8QUfWtMYvkm/NX6Qfb6fd55sipnHwOpPDVhm1YZ > n > > > Hc9AdhNwcTxiqEQzM3XRY5/E+z/NXMcjKXm6Mz4GLfoto0M8f9uN23fplV8L6YsXxzbv1vzjDNS > C > > > xCBUYQPlyft+8Y0U5S8VY0joZK1J95tdvz9uHhUPsvoXvUE0aWYcg4mRq3wYvFNIZo8A9h3P8bb > U > > > KSVhI2zNJuAx61iGWPjYL/L+RzHf8UiKeVzf7fxb77Xl7xgDubjJ33dKD792c5DTXK8dFoVQhY2 > U > > > b3rNZOoLRv86N75UuAY3OdBDnWpy8FvveYHAoeQ+P+EmyZmjf3mZs0ZhHQPrNZh9kyX6jQgdnOZ > p > > > Mt62ZpxSYg3yUSJ9kZt9nnMe+/nf/2jmOh5JMZvWraZeu3lYFEydcx3w2rkvH4Oc1gOhChvKf6q > M > > > TQ4AMb5VrC9JqUDfMk492UzqGIQ1mapBUr6r7oThUbNzHA+vSZJFaPqVuNyLHvt4739scx6PZNi > j > > > oO0rI+mR06FDkFVz+nh0M6zc3mg0eqxvAwD4cJOnW0PjL2x/SPMIXl3D5L7dra8ezToesKn29/f > p > > > 1dffoHt3X6Z+v6/XxoeaKgBMYVx0IEjMUb+bb8bxgJ2HUAXYeeY1bs1rBvN6o59zYhCSqKW6o3Y > + > > > O/2yhJtl3uMBgFAFAB4AMx5xpAdyyUAxB+Z8ll4bp6Z70QYvYKZflnDTxD0eAB6EKgAQX37Pug6 > u > > > iS/VN+qGXyWp1N6+gTGLHA/YaRioBAAAOw8DlQAAAFIGoQoAAJAQhCoAAEBCEKoAAAAJQagCAAA > k > > > BKN/V+T0bHzKOAAArNmdsn395KRG/643VLsVOhjPo+S/juaQzo5yVOupv5x6ny7L9olhw7Mjyl1 > V > > > I1xvlE9Wb1C2f0nuJuRz3Y2TQ3XjPs/k8+bFoXrv7ov6L+Wdd96lz30u+GLoq4Ry2FCOSTgmNpT > D > > > tmnlePX1t5YWqutr/h2e0VFxIMJMT05cH1Dx6ExEqdKtiEA9dCdfbtNhLUfuDFndirrCiReK03U > r > > > vimlRJjnaofe5MjtQ6qdePt2TTwPAABgirWF6vCiQ71SdVwDzJSrVOp16IKTTQRuoyVqj+PLgKn > p > > > jtwKab7pBrGjVkzBNdJGtm5P4cRXSzFrxTey5PSu6Fr/yQKfBwAAMEWKBirdoKzToytOtusr6jk > F > > > Ol6wyZXD+aRToPPyTb0imAx4JytKoEV83qLS0FzCUA4byjEJx8SGcthQDs/aQjVzXCCn1aAzt81 > 1 > > > eEGdHtHg4ZCGDwdy1YVu5uXFbfqNbkhnJx0qnJfDL/TNTdCyGZmoPn5chOcBAAAEWNlAJXNg0Hj > Q > > > kTlQySlRiVo0KPTpnE7kY3n2ftnky+GXE0HnGzA0baAS33citqQGN80YcGRs//gi+vM47GfhZmr > G > > > A5WefeZpeZuZv6i4c92F9QrWK1ivYL2C9coi69kyByql6JQaNdr3qiqClETYNrLUv/Rqizw4qZG > 1 > > > RwCHh6o9ctgUNIqYqe23qdApxnreNBy6Zqhi9O90KIctLeVgOCY2lMO2aeXYztG/frL516Esd2w > G > > > DByKJ0PlSz2yVy5tUQvm02ZGIcE4JNXifCPm8wAAADzrC1Vu+j2okNtV2j2teaOBM8dUcFrUcDt > c > > > h2o0cGHhkUsK13DNfYudi9ppctsHAIDdtL5QzTfVual6IFJxUKf+uBmXa5rq3FQ5UClXo8N2hAs > w > > > yIFHRliGyJQvrX0fyPNlF7/AQ1xpaC5hKIcN5ZiEY2JDOWwohweXKVyiWX2qAACwervRpwoAALD > h > > > EKprxCPV0gDlsKEck3BMbCiHDeXwIFQBAAASglAFAABICEJ1jTBizoZy2NJSDoZjYkM5bCiHB6E > K > > > AACQEIRqAuS5rgHLTHv/QC0AALAVEKoJ8C5raC+hdJi+8+AB0eO/W3u4YuSeDeWYhGNiQzlsKIc > H > > > obpqHJ4iSPfoMd269Tna2/uUClY3XAEAYGMhVNeAg/TBg3fGiwzWlOMyugsAAARDqK6SrqWGWlN > t > > > ddaIuVX9CMAIQltaysFwTGwohw3l8CBUYS57Ivx5AQAAD0J1lXRN9PHjH8n+VHfhv6VZNdkUeSz > K > > > yYsbrtMWAIBdsd5QlXOquqeg+KdsG9LZkXd6ypE7t6pBzotamTXRG+tS5eCIzE2oOVXd7Zv32fu > d > > > vD8ZKkj3vEBdo1kj5kJ/BAhuuE5bgoLWvzCMILSlpRwMx8SGcthQDs/6QpXnPpXzmKrTT+T8pkd > n > > > ItKUbiVHtcO2Pj1Fza3q5me3osIuV+upFTN0K0Vq6duSCPNc7ZDa7ukv7UOqnXj7JnLG5VJLgnO > t > > > ipCRNVIdJJL7N9+XWuoHwDw/AoKC1r9wsN66dWsibM0lLgyuAoBVW1uoDi861CtVx2GVKVep1Ov > Q > > > BSebCNxGSwTbHXfS8jw1Rbi5c5jnmyrs+nVHrZiCa6SNbJ2smfPyTfH8ptiqdiNLTu+KrvWfRId > 0 > > > c5kTlosQ4UVOZMthof/eZRysDx48mAhbcwkKWv/iWtXgKgAAU4r6VG9Q1unRFSfb9RX1nAIdLxp > s > > > IpxPOgU6L9/UK4LJgHeyogTsmq6iVYAXtsf/J8Ji3TZl5F5Q0PoXf7jOAyMZJ+GY2FAOG8rhWVu > o > > > Zo4L5LQaXl/l8II6IswGD4c0fDiQqy50My8vkbpOLUM6O+lQ4bxModnMTdCyGZmobj1uQA2jXzX > + > > > vmFd3HANYtZozQUAICl7o9FItkIuGzfDun2gTr1Pl9zuywOVirq30ylRiVo0KPTpnE7kY0tt3eT > L > > > 4ZcTAdm3+zblNq+qNHLbhQ1834nYktyPHKjUoKzv+WPm9sm3r5B9Mw7cWbiZmp2etejZZ56Wtxn > / > > > ouIvdA4As3Pd/KWVlvWbUk6Xu54HVbm4Lzjs8UHBuomvl2G9gvUK1ivmevbq62/RnbLVKUj7+/t > i > > > /Rt07+7L1O/39dr4Vhaqs/Go2xxdVUWQkgjbRpb6l17tkQcnNbI6jLXwUFXbChrHNA50n6Dtu6b > d > > > Nw2Hrhmq9+6+KG+73LBaN/7w+T90plWVc1Y5VoXLwYOmgqzy/UrL8WBpem9QDg/KYYtajmWGanr > 6 > > > VGXzr0NZ7ticGDgUV4bKl+bo3baoBasRvcHBOCTd4gwgcXgGLfwDw78AALjWF6ryHFXv3NTuac0 > b > > > DZw5poLToobb4TpUo4ELC49cUriGa50X2z0VtVq1/cn7KlRMcN+w2aIGLS8AsHvWF6r5pjo3VQ8 > G > > > Kg7q1B8343JNU52bKgcL5Wp02A7pDzXJgUf+i0hMypQvrX0fyPNl1fan3bet0tBswza1HEFBy0v > c > > > oPWfV5uW48HwGbGhHDaUw5OiPtXtsyl9qtNsQhk3SXiwPpbn07r8V64CgOTsRp8qwA4wa7LmAgD > b > > > AaEKcsRcGqAcNrfJOLx2uzp4b2wohw3l8EQLVdlXqfsYA5fkLzgPsEu4qdc/aYF52cY0BSwAhAs > P > > > VTNITzp6ZbjOCQIWYBEcpO7iZzYVmwGLkAVIl5BQ7VLFCtICnY/P+QxazsUjPJ2T2SNwIT3CRsz > x > > > FzZ/ia8KRhDawsphBqw/ZJcF740N5bChHJ4pzb9GkBpXNgpmXmzBDlgAWK6wgF1myAJAsJBQzVN > z > > > ZpCG4YA1plXbAXb/srcArJoZsP6QBYDlizZQCaaym8K9ZVNg5J5tm8qRVMDivbGhHDaUwxM9VM2 > B > > > S0dnxGOR+ELzB5gXbSvxFy9/EcP2CAvYeUIWAIJFC1W+Tm+uRsFzd9+nMwz3BdgoZsD6QxYA5hc > h > > > VId01uA5T9UsL/26o1YL+Waf6oMW1WqnGO27wTByz7aL5QgLWDdk8d7YUA4byuGJEKrXdCWqqE7 > 9 > > > POCi8hkqV+3rJwLAZjMD1h+yfv5JAAB23cIDlYaYiBRgq4UFLAcpTwLgLghWgEiheoOyDlGvliP > / > > > mCSeezRX42psVjxqDnJOVfcUFP8FI4Z0duTed0BHAf22cu7TSAOlulTxXelJzZvqbt9/FajZ+94 > m > > > /hFz/IXJX6CrhhGEtrSUg7llMQN2HfDe2FAOWxrKESFUvSbeVvFAhWivRjkRNvK2UKrOcU4rjya > W > > > c5Wq00/kHKZ6VDHrVnJUO2zr01PU3KpufspRx8b+Z+lWisS9wmMizHO1Q2q7p7+0D6l2Em3fAAA > A > > > YaI1/+abMlwme09LMpjGc4vHMLzoUK9UHffTZspVKvU6dMHJJgK30XKofsfdcJ6axn7yTTeIvUF > T > > > YbhG2sjW7bLL12NcoOJGlpzeFV3z7Rn7BgAlaBIAt2kYYFfF6FNV4aJqb+6S5JWTuJm5R1ecbNd > X > > > 1HMKdDzfJZ08IiBPOgU6L9/UK4LJgHebsJPa9wbByD0byjEprCz+SQDcpuFlhSveGxvKYUtDORY > e > > > qDSvzHGBnFbD68scXlCnRzR4OBwPfrrQzby8xG9+HdLZSYcK51OaprkJWjYjE9X145LZ9+ZaV38 > q > > > bJdlhytAWu2JGudjfXs6DiD3AhBOnfqXZboWwVOkNo0itI2OBzUJTr1Pl9zuywOVirq30ylRiVo > 0 > > > KPTpnE7kY0tt3ewq9y0Csn9pndYjt3lVDdw/33citiT3IwcqNSjre/6Ysf3jC1XOWftmHLizcI2 > e > > > nZ616Nlnnpa3Gf+icgPM7Fw3f2mtYz2XiefxdK1qvwzrlW1c7war+9la1X4Z1itY73n19bfoTtn > u > > > 0Nzf3xfr36B7d1+mfr+v18YXLVTN8GNWqJaonr1D5cC0ioNH3OboqirCjMT+Glm5D3erPDipkdV > h > > > rIWHqtpW0DimcaD7jLd/8zTSvqPg0DVD9d7dF+Vtlxuq68YfPvdDt84ymeVYJ5RjUlJlccN13s8 > Y > > > 3hsbymGLWo5lhmqE5l8RUKu4opJs/nUoyx2b5sChuZhT0fHCg6xU+YODcUjj020X3jcAhOEw5YX > D > > > 1Q1YgG0SIVSXdEUleY6qd25q97TmjQbOHFPBaVHD7XAdqhG5hYRGD3EN1zovtnsqarV6+0veNwA > g > > > XGF7LTxQae4rKuWb6txUPRioOKhTf9yMyzVNdX6oHCyUq9FhO6Q/1MT9nxMXkZiUKV9a+z6Q58u > 6 > > > 259z3xvMbS7hL7d5m+WSkIbmI4ZyTFpWWeKGK94bG8phS0M5IoTq8q6oxOE2bqKdmBTdPoUnYCy > S > > > er55R6ZMl4Gn+fC27GC09u27L8q+ASA5qLnCtogQqku6ohIAgA/CFTZdtObfJVxRCdKDR8ylAcp > h > > > S0s52KrLEhaueG9sKIctDeWI0ae67CsqAQDYUHOFTRMhVPnCCds/U8uu4y8s/vICSCM3XG/duoV > w > > > hVSLUVOFbYWRezaUY1JaypKWmis+IzaUwxMhVN3Rvye+OUcBANYjLeEK4BchVNXFH0SsUi2nz+u > c > > > WGafG7rNgo/J7OsCA8BiEK6QNmj+TYA9eMtbNgV/GfEX07phBKEtLeVgaT8mqw5XfEZsKIcnQqg > G > > > jfr1LxgFDADrh5orrFuEUFWjf3dpTlEA2GxB4bq396nxArAsizf/yuvtHmEQEywMIwhtaSkH29R > j > > > 4oXrp+jBg3fGy6LBis+IDeXwTAlVVUM9OCgST/zGlygMGozDF5xXFysEAADYbckMVHIKhJnRNhM > 3 > > > jfEveQAAWNyUUHUHKKlr/pba/sFJxjIxw0xEck5Vt9brPy1nSGdHXo046IpOcl7USJ29XOu2m6j > V > > > nKru9o37rDIZy9GZKNF2wsg9G8oxadOPyePHP6Jbtz43XsTPSXXHnPAZsaEcnmRqqvPgvlg5j6k > K > > > Zjm/qRFc3UqOaodtHdxqflM3P7sVFXTuLDmzdCuqCXtMBGeudignA5Dbbx9S7UTvW04eoNeP759 > z > > > InYASA0OVm9Rg5gAkhY5VAcPk62nDS861CtVx/OYZspVKvU6dMG7EYHbaDlUv+OeqKNqze5sOPm > m > > > Crt+3VErpuAaaSNbt2fYkcFpnAZ0I0tO74qu9Z9+3fstcgrHmN4OYIsgWGEZ1ldTncCXQ+zRFSf > b > > > 9RX1kuinFeF80inQefmmXhFMBnzYROsy4EtUtWcx3wpufypG7tlQjknbekzmDVZ8RmwohydCqC7 > n > > > 2r+Z4wI5rYa3zeEFdXqqRjx8OJCrLnQzLy/xz5Md0tlJhwrnU/p7RWAeyWZkonrI47qnfOcdXNw > C > > > YEuhxgpJ2huNRo/17RA8yMfXJzmBJyufflUlboZ1+0Cdep8uuebHg4KKestOSWylRYNCn87pRD6 > W > > > B0fJJl8Ov5wIyP7luLmYyW1eVWkUMEs633citiT3I19Dg7K+54+FbD90vcZhPws3U7PTsxY9+8z > T > > > 8jbjX1RuTdHsXDd/aS17Pe//wYMH8vYq94v1CtYraVm/7n+PWK8sez179fW36E7ZHiuzv78v1r9 > B > > > 9+6+TP1+X6+Nb2WhOhuP9s3RVVUEKYmwbWSpb4wq5sFJjawOYy08VNW2gsYxjQPdJ2j7vK5I7cD > Q > > > joJD1wzVe3dflLdd7j/idTG/RPwfunVAOWxpKQfbhWMS598jPiO2TSvHMkM1QvPviq79K5t/Hcp > y > > > x+aMgUOzZah8aZaPTwty5EjjoEDlENYtzoYu3bcGSwHANuNA5WAFWMT6BirJ80G9c1O573I8Gjh > z > > > TAWnRQ23w3WoRgMXErrCBNdwrfNiu6eiVmtvf3jWoNYWX9Ri3bVkgDRCsMKiIoaqfSGGyWWO+VT > z > > > TXVuqt5GcVCn/riZlWua6txUuf1cjQ7bIf2hJjnwaHZZMuVLa98H8nxZc/tdOuU+3eqcF7XYMGl > o > > > tmEohy0t5WC7dEyiBCs+IzaUwxOhT5Urldy3WKJSqxXSt5pEn+r24cDm5meWtj5V1FQBpsO/ke2 > 1 > > > 5j5V7lvk/96Wfavy4kIl70pHslhh53gCAGwoNAXDPCL3qZZuB9VD83SHr2q00KAiWDX/L3AeMZc > G > > > KIctLeVgu3pMwoIVnxEbyuGJPVDpBl8JYvCQ3Gs2ZG4e6lsAANsHNVaII3Kotu6r4T8yRHs1OtW > j > > > gfi6uAAA2wzBClFFCNU83ZYdp/fpjE9xyd+W/ajupOXFgUNO6TYGKW0wjNyzoRyTcEzsYMXxsKE > c > > > nkg11XyzT/VBizrqL2r26+TND1Og8zmvOAQAsElQY4VZIjb/qisUja9GlCnTpXu1onknKN8i8lz > X > > > gCWN+AuBvxgAYD4IVpgm9kAlmKROL5pcNgVG7tlQjkk4JjaeiCINwYr3xZaGcoSEKl9EP7j2Fbz > M > > > cUUlAIANhhorBEFNFQBgTghW8AsJ1YCZadSllKjtXy8XXKJwk2Hkng3lmIRjYjPLsc5gxftiS0M > 5 > > > UFPdIfwPH4OUAACWB6EKALAgNAODa72hKudUDRvsZE83d+TOrWqQ86JWogyR4oFXR2RuQs2p6m7 > f > > > vk9NIRdy3xbCyD0byjEJx8QWVI51BCveF1sayrG+UOXgkvOYqn5ZOb/p0dn4msLdSo5qh95sODy > 3 > > > qpufPBUdB16u1lMrZuhWivaUdSLMc7VDr3+4fUi1E3ffIoDl/K3GfTmMbgaA2VBjhbWF6vCiQ71 > S > > > dTwxeKZcpVKvQxecbCJwGy2H6nfc4U9q4JR74aZ8UwVen2fImYFrpI1sXU1R58o3xfONwVU3suS > 4 > > > M+0MH9KAHMq6c9nJyzIO6OGG11bRnwqwGgjW3ZaiPtUblHV6dMXJdn1FPadAx4teqkmE80mnQOf > l > > > m3pFMBnw7pywmTJVSz3qyHTnTTSoZYT/NsLIPRvKMQnHxDarHKsKVrwvtjSUIyRUAy7+UOQG1BY > V > > > /evlEr95NHNcIKfV8PorhxfU6fGsckNRWRzIVRe6mZeXSF2nliGdnXSocD7lMoq67zRXI6obj+O > a > > > cPUqJ/ebu6rSCNc2BoCYUGPdTXuj0eixvm3gUPX1Q07F569OP1eVm2HdPlCn3lfXEeaBSjKseWV > J > > > bKVFg0KfzulEPrbU1k2+HH45EZD9S6vGKLcZEnp834nYkrpeMb+eBmV9zx+zts8DpHJ0VdX7lmW > k > > > wNfHoTsLN1Oz07MWPfvM0/I2419UbpOs2blu/tJKcv2tW7fkpdWWtX0X1itYr2A9yX97ZtfLqvb > L > > > sF4x17NXX3+L7pStTkHa398X69+ge3dfpn6/r9fGFxKq62CEGYkga2Spb1ysnwcnNbI6jLXwUFX > b > > > ChrHNA50n/H2b57Swf3b1jaD9h0Fh64Zqvfuvihvu1bZzzltX/zh83/o1gHlsKWlHAzHxBa3HMv > 6 > > > t473xRa1HMsM1fT0qcrmXz1AyBw4NBc1qw4HmlraohbsyJHGwcE4JN3irJqeBw/1SODtsMrwBoB > J > > > /O+P/x3C9gvvUzVOb4mHa4kR+ljlOare47qnNW80cOaYCk6LGm6H61CNBi4sPHJJ4Rqu1Q/cPRW > 1 > > > WrV92dfrjkJmCe8bAHYTgnU3TKmpdujkQA8UijBKyD139ODgRE9mPkO+qc5N1fsoDurUHze5ck1 > T > > > nZsqtynPGw3pDzXJgUezAz1TvrT2fSDPl9Xb57li5bmp+r6o+95gaWi2YSiHLS3lYDgmtnnLkXS > w > > > 4n2xpaEc4X2qcvCOqD3y7VKJSq3W1IFLpXabqMiDm7iZdbtDKCoO5TT0qaL5FyBd8G9yvdbTp8o > 1 > > > NrdP8jafTDOLO7MNAjVN8I8XIH2SrrFCekQbqCSvQOQO+gleAs5qgQ3BI+bSAOWwpaUcDMfElkQ > 5 > > > kghWvC+2NJQjPaN/AQB2DGqs2wehCgAAkBCEKmDkng/KMQnHxJZkORapreJ9saWhHAjVLYZBSgC > b > > > Ac3A2yNCqKqL68e/oP3ukOezBiwAAFEhWLdD5Jpqq+iGRfwZabZd0GhoXjYFRu7ZUI5JOCa2ZZU > j > > > brDifbGloRxzNP8a07/NfSlDAAAI4gbr3t6nxgtsjgih6l7UQSxt+woU1KtRTgfs0XhiVAAAWMx > j > > > evDgnfGCYN0c8Wqq5kUgfAHbc6/Ti87XVIgzSAkj92woxyQcExvKYUM5PPFCVc4so5t+3cnF/Vp > F > > > BCsAAOykCKGqRv8GBqlTp75bczVrr637GMwEADCnx49/RLdufW688N+wGeYYqFSithuil2Wyrp3 > P > > > zcP+ftdpzJrvxKhinpfVvS+4z1bOixqpVsw/DI7I3ISaU9Xdvn3f9HJtH4zcs6Eck3BMbKsoBwe > p > > > u4SNCMb7YktDOSKHaqnt1kiblMi183lqOTmPqdqunN/UGE3creSodtjW+1Rzq7r56c7dmqvJiel > m > > > 6lZ4SjqDCM1c7dD7ccDzp57ofc8o1yaI058KAOmHc1g3R4RQVaN/I89CIwczzQ7e4UWHeqXqeJq > 4 > > > TLlKpV6HLji9RLA1Wg7V77hbscuQb7qB56gVU3CNtJGti/q1wV/GG1lyeld0LW5OLRcAAMAU8fp > U > > > Iyzzj1G6QVmnR1ecbNdX1HMKdLzovKwinE86BTov39QrgskgdbKiBEGMcm0pjNyzoRyTcExs6yh > H > > > UG0V74stDeWYo091Or7yUpRzVjPHBXJaDa8vc3hBnR7R4OGQhg8HctWFbuadL6yHdHbSocK5r9/ > X > > > xE29Ytu5GlFdP25auQAA1gnNwOm3NxqNHuvbIbimWqQWj/T1D0ziUBKJ1HPvc/+Wg5nsJmBuhnX > 7 > > > QJ16ny65fZUHBLkjip2SeFaLBoU+ndOJfCz348omX7ldEZD9y3GzLJPbvKrSKKBtmu87EVuS+5G > v > > > oUFZ3/PH/NsPKZfalofDfhZupmanZy169pmn5W3Gv6jcvk+zc938pTXv+lu3bll9qklvn2G9gvU > K > > > 1iurWs/fHQ8ePJC32ar2yzZ9PXv19bfoTtkeVLu/vy/Wv0H37r5M/X5fr40vcqiKlAzsV1VhyYN > + > > > dIjKQOKHxx3QxKN9c3RVFfshsY1G1gpxHpzUyNrBFh6qaltB45jGge4TtH3FKFe8FyRD1wzVe3d > f > > > lLddbqgmaZ5t8ofP/6FbB5TDlpZyMBwT27rLYf4gx/HwRC3HrFB99OiRXhtf5ObfsObPzM1DfUt > x > > > m25jk82sDmW5Y9MYODSfDJUv9cheubRFbdORI3qDApWDM7TYZrkAAFKAA5WDFdInQqjyQB11GcK > J > > > fk1uNuVmUj3IZ9zEGzroxyDPBfXOAe2e1rxRt5ljKjgtargdm2I/PBq4sPDIJYXLaZ1/2j0VtVq > 9 > > > /WnlAgBICQ5W7uqBdIkQqqLWd14X9Txz+je9yP5TolLV7GstUdvf9xok31TngOptFQd16o/bV7m > m > > > qc5Ndfdz2A7pDzVxyEe4WEOmfGnt+0Cel6q3P7Vc2ykNzTYM5bClpRwMx8SWpvcmDfC+eCL0qbr > 0 > > > gCX9l8JNqhHCbkdxKK+yT3UZfbQAkG74dx9fKvpU3QsweP2UvCBQAQDWCf2r6RIhVNXFHzBf6vb > i > > > EXNpgHLY0lIOhmNiQzlsKIcnRk0VAADSCLXV9Igx+vfEnskFAABSA8GaDhFC9Zqu5EUUelTL6dG > y > > > E8v2T4+WdosMVsDIPRvKMQnHxIZy2FAOD5p/ExD8Q2P2JQwBAJKE2ur6RQjVoFG//iXuJQm3S/A > x > > > UafSAACsEoJ1vVBTBYzc80E5JuGY2NJejlUHK94XT/RQlVcr0k2bR2fEY5b4IvQH8edkAwAA2Er > R > > > QpWvh6svSTjpPp1hWPBaLTJICQC2E5qB1yNCqA7prMEXJ1SzvPTrfBVgJd/sU33QolrtFKN/Nxh > G > > > 7tlQjkk4JrZNKceqghXviydCqKpTapz6ecAlCTNUrtrXTwQAANhVCw9Umnv+VCanWXNPQfGf68q > T > > > g7v3BV8mUU7hFqlPly+1eBRy8YqA+6xyHUxOeQcAsCHQDLxaEUI1fD7VWPOn+vHAJznlmjr9RE6 > 3 > > > pgdAsW4lR7XDtj49RU0D5+5fDpASYSf3HUG34p9dxzN5nwjZYotKbX1qTLtErWJ6L26RRH8qRu7 > Z > > > UI5JOCa2TSvHsoMV74snQqh6Tbw8n6oMsl6Nckao2fOpRjO86FiTf2fKVSr1OnTBqSoClyclr99 > x > > > z35V58q605rmm24Qe/27YTj4G9k6BTVSB943fEgDseb2eNe3xV8DehhYywUAAPBEa/7NN2VtcTK > Y > > > StQ2wm4xXCPu0dW1uHl9RT2nQMeLTisnwvmkU6Dz8k29whB2n9y3WfM2ygUAsKHQDLwaMfpUg66 > s > > > NP+VlDLHBXJaDa8vc3hBHVHxHYgqodtPe6Gbeefr1xzS2UmHCudBtejw++S+D28a6zN081CVa1t > h > > > 5J4N5ZiEY2Lb1HIsK1jxvnj2RDg+1reXatz/Kjj1Pl1yuy8PCCrqHk2nJOq9LRoU+nROJ/Kx3K8 > p > > > a8GiVnmUEyHYtydFl9u8qtIooKrM952ILcn9yMFIDcrq58+6z79N7sNtZHWZDRz2s/CPD3Z61qJ > n > > > n3la3mb85rv9oWY/gPmhiLL+1q1b4z7VRbaD9QrWK1ivbON68zuDrWq/LA3r2auvv0V3ynbb6/7 > + > > > vlj/Bt27+zI9evRIr40vYqjySNwchY8L4mbgRa//q/ZxVRVBSiJsG1nqX3o1yaBgCw/V8PI69TY > V > > > OsWQ+8T2b5769m2UK+YL5NA1Q/Xe3Rflbdeig4wWfT4A7KZd/+5YZqhGav5VI3G5JrlEsvnXoSx > 3 > > > Zt7IktO7ovm7MTNUvjSbqbk/WF284rKcn3KfiNGJffN5urpcW8r8RbdOKIctLeVgOCa2TS8HB2q > S > > > zcB4XzwRQrVL92UL7e0ps9XMUUuV54J6p6p0T2veaODMMRWcFjXcDtehGg1cWHjkUgSZm3RILbo > / > > > Lth98dch3VzBrgEAViXpYAUl8kCl0vgck4Tkm+rcVD0QqTioU3/cvso1TXVuqhyolKvRYdvuTw3 > E > > > fa8LT5iep6Y8N1UPkpLnrO721HYAABBNhD5VHshTpFapHTggCMIts08V/akAkIRd/C5Zc59qnm7 > z > > > vs3TXwAAYCugGThZMfpUe1TL6SbRiSW9l/EDAABYlch9qrC9MHLPhnJMwjGxbVs5Fq2t4n3xRGr > + > > > DR/16y4YyAMAsMnQDJwM1FQ3EAYpAQCkU0io8ojfiNfb9Z1vCpvHfwmvdUE5bGkpB8MxsW1rOea > t > > > reJ98USvqcpzQMMm+t5twYO3Zl8XGAAgbdAMvBg0/yYguJ9ZnZ8KALBpEKzzQ6gCRu75oByTcEx > s > > > KIcN5fAgVDcMBikBwCqgtjofhCoAAARCsMaHUAWM3PNBOSbhmNhQDhvK4UGoAgBAKNRW45kaquP > p > > > z3jJ1agXdP3forww8HzkOa7utvznug7p7Mjbz1HAuTzDsyM6iHYyLVVCTwcKvy/69lcD/akAsA4 > I > > > 1ujWV1Pl816LA6r31ekncm7VozMRpUq3kqPaYVufnqLmVnXzrVtRQZur9dSKGbqVIoVFf9B9cbe > / > > > 6TByz4ZyTMIxsaEcNpTDExKqUa73ay7xr/07vOhQr1QdTzyeKVep1OvQBaeqCNxGy6H6HXerqjz > u > > > dK75ptpvv+6oFVNwbbORrZM9c54Sdl+c7QMA7ALUVqNJUZ/qDco6Pbq6Fjevr6jnFOhYB+7cRDi > f > > > dAp0Xr6pVxim3QcAABMQrLOtLVQzxwVyzInPhxfU6RENHg5p+HAgV13oZlhe4ndtDunspEOF8zJ > N > > > ZvO0+3YPRu7ZUI5JOCY2lMOGcnj2RqPRY317qbip1e2jdOp9uuR2Xx6o5A50ckpUohYNCn06pxP > 5 > > > 2FJbN/ly/2tOhGD/ctxczOQ2r6o0ctuFDXzfidiS3I8cjNSgrH7+tPtM07bPOOxn4WZkdnrWome > f > > > eVreZvzmuwOPzH4A80Nhrr9169Z4kFKUx2O9gvUK1itYryy6nr+PHjx4sPL9uhZZz159/S26U7Y > 7 > > > /vb398X6N+je3Zfp0aNHem18KwvV2Xi0b46uqiJISYRtI0v9S68myYOHGlkdxlp46KltBY0zcup > t > > > KnSKIfdF3X40HLpmqN67+6K87YozmjfOYwEAlm2Tv5OWGarp6VOVzb8OZW+I2zey5PSuiLtX55O > h > > > 8qU5kKotasGOHGl8Wc5Puc9XVd0R5i+6dUI5bGkpB8MxsaEcdv8qjodnfaHqm4e1e1rzRgNnjqn > g > > > tKjhdrjq0cCFhUcuAQAALE9IqKpJyt1BQrOXOSYpzzfVual6G8VBnfrjZlauaapzU+X2czU6bE/ > 2 > > > eU7gvtctnDAdTb8AkEZmbRWUkD5VDtXwCyZMKlF7jnNVtx3/IOAmZrZInypCFQDSbG/vU/oWB+2 > P > > > 9K30WkOf6vIv/gAAAJuPA/XBg3fGixmwuyg9A5UAAAA2XMRQtS9uP7lsXz/mLsHIPRvKMQnHxIZ > y > > > pFMajkekUFUXt+eLM8CqoT8VANKM+1Bv3frceNmEPtVlihCqXbovRyzdlv2sbU7Wkjd7jAxaJ0t > 8 > > > eikAAOwe7kvlMN31QGWR+1RLt4OGIuXpDs/kstCFGmDd/JfwWheUw5aWcjAcExvKYUM5PLEHKt3 > I > > > ihAdPCT3OviZm4f61u4K7meefV1gAADYLpFDtXVfDUWSIdqr0akemdRVbcM7bfIUI7UsCv2pAAC > b > > > JUKo5um27Di9T2d82cD8bdmP2iqq2lhx4JBTuo3zVDcYRjLaUI5JOCY2lMOGcngi1VTzzT7VBy3 > q > > > qL+o2a+TI2+zAp3POYsLAADANonY/KtmfRnP4pIp06XbzGlMzwYAALDLIoSqurh+BVd32FoYuWd > D > > > OSbhmNhQDhvK4Yk8UCmUnBnmiNxZ2iAZGKQEALB5poSqO/2bmq3GHZg0seRq1FNPiE/Oqepuy3+ > p > > > Q/vSiEcBqT08O6KDSFVofi1hwR9wn/yh4O0btXQAAIhi8ZoqcwoUe/5wDq7igOp91Tcr51Y9Ohu > f > > > /6oujehduYnnVnXDrVtRYZerRYvzbiV8GrvJ+0TIyvlbdZ9xv06D4nbXxDFyz4ZyTMIxsaEcNpT > D > > > MyVU3enf1KUIS27IBC1zDFYaXnSoV6qOJx7PlKtU6nXogsNLBG6j5VD9jjuqWJXFHWScb6r99vl > q > > > TjNwbbaRrQdetzjovuFZg1pOnca7zhxTwenRFS4ZBQAAMyRTU03EDcq64XV9Rb15ar9+IpxPOgU > 6 > > > L9/UKwwh92XKl74fCdd0NXf7NgAA7JIIoWrXEpOSOS6Q02p4zarDC+qI8Bo8HNLw4UCuutDNvPP > 1 > > > aw7p7KRDhfOgWvS0+2yy5irqsoGXPl6SVQ9Swsg9G8oxCcfEhnLYUA7P3mg0eqxvT8d9oBODkhy > q > > > 9y/HTbjTcFOr2wfq1PvqnFceqFTUPZoOTy3XokGhT+d0Ih/LTc4yzOW+RQj69iW3eVWlUUDi830 > n > > > Ykvq3FoejNSgrH7+tPsssnzc7xv8GjnsZ+FmanZ61qJnn3la3mb85rvhafYDTFvvwnoF6xWsV7B > e > > > wXolbD179fW36E7Z7hTc398X69+ge3dfpkePHum18UULVTP8AozDbyE82jdHV1WxLRL7a2SpbzT > D > > > 8uCkRlaHsRYeqmpbQeOYnHqbCp1iyH3e9tWPAIr8oyEIh64Zqvfuvihvu8JqpDidBgBgeZYZqhG > a > > > f0VANVSgTgxWkpOrErUa3qjducnmX4eyPDHrjSw5C00np64A5ZWVB1txrZqvCpWfcl9ygbpJzF9 > 0 > > > 64Ry2NJSDoZjYkM5bCiHJ0KoqoE6XIubqBDmm2oE7jwBKM9R9c5N7Z7WvNHAcsRtixpuh+tQjQY > u > > > LDxyKQJRrnUGKmqpAACba32jf2UgD6ioByIVB3Xqj1Oba5rq3FQ5UEmeNxoh5LjvdeIiEvGoqex > 6 > > > VMt5g6R4Cbr4BAAAgClCn6rXPznRd+r2tToiEHFh/QkcxtzEzKL2qaKmCgCwXGvuUxW1xqruO/V > f > > > qlAPXipVEagAAADRmn/zTXm5vsnrF6kBPouP/AUAANh80ftUzTlUx8tujI5dlXU1/WLkng3lmIR > j > > > YkM5bCiHJyRU+YIImJ0FAAAgjvWN/gUAANgyCFWYuITXuqActrSUg+GY2FAOG8rhQagmwBoRbSx > x > > > 4FQaAIDNNzVUJ06hCV0Wu+DCprMHb3kLAADsFtRUASP3fFCOSTgmNpTDhnJ4pobqxAX0Q5cm4VR > V > > > AADYdaipAgAAJAShmgLrHqSEkXs2lGMSjokN5bChHB6EKgAAQEJCQjVPzdEKrukr51QNG0HMs+N > 4 > > > I4yDpl7jycQPIl32ia8QdUTBs7dN3ie3Oy5X2PMAAABs66up8tynxYG8ID8PdpJzqx6diShVupU > c > > > 1Q7beiCUmlvVzc9uRQVejueji6BbKZKaT2fSxH1ykvJDaruDsNqHVDvxyrWNMHLPhnJMwjGxoRw > 2 > > > lMOztlAdXnSoV6qOL8ifKVep1OvQBaeXCNxGy6H6HbeqbNec8003iCfnzfHjWmcjWyd75jwl8D6 > e > > > kccczXwjS07viq71nwAAAGFS1Kd6g7JOj644va6vqOcU6HjRGXBEOJ90CnRevqlXGKbdZ5Dh72R > F > > > 6ZYDV1ICANgeawvVzHGBnFbD668cXlCnRzR4OKThw4FcdaGbeXmJP2POkM5OOlQ4D5pAfdp9Gjd > P > > > yyZmovq0x20BjNyzoRyTcExsKIcN5fDsjUajx/r2UnFTq9sH6tT7dMntvjxQqah7NJ0SlahFg0K > f > > > zulEPpYvPiGbfDngciIE+/b8rXKbV1UaBYyo4vtOxJbkfuRgpAZl9fOn3TchZN+Mw34WbqZmp2c > t > > > evaZp+Vtxm8+11LZgwcP5H+Z+aEw+wewXsF6BesVrFewXomynr36+lt0p2x3Cu7v74v1b9C9uy/ > T > > > o0eP9Nr4Vhaqs/Fo3xxdVUWQkgjbRpb6l14NkQcnNbI6jLXwUFXbChrH5NTbVOgUQ+6zt+8K2nc > U > > > HLpmqN67+6K87XJDFc2/AACrs8xQTU+fqmz+dSjLnZcLDw7KUPlSj96VS1vUgh050viynJ9yX1B > o > > > Dkm3Ridqb+9T4v/598z6f9OYv+jWCeWwpaUcDMfEhnLYUA7P+kJVnqPqnZvaPa15o4Ezx1RwWtR > w > > > O1yHajRwYeGRS7Nx7dc6Z7Z7Kmq1ye6bA/XBg3fGiwpYAADYdOsL1XxTnZuqByIVB3Xqj5txuaa > p > > > zk2VA5VyNTpsh/R5muTgosWmocuUL61yHchzaSPsGwAAdl6K+lS3T1ifqltTdd269Tl6/PhH+i8 > A > > > AFim3ehT3SEcoByk7oJABQDYDgjVNeEgdRcAANgOCNU1wog5G8phS0s5GI6JDeWwoRwehCoAAEB > C > > > EKoAAAAJQaiukf/SWeuCcthQjkk4JjaUw4ZyeBCqCZDnswYsAACwWxCqCfAueWgvAACwWxCqa4Q > R > > > czaUw5aWcjAcExvKYUM5PAhVAACAhCBUAQAAEoJQXSOMmLOhHLa0lIPhmNhQDhvK4UGoAgAAJGS > 9 > > > oSrnVHVPQfFP2TaksyPv9JQjd25Vg5z7tBJlorcuVQ6OKGATwrz3AQAA2NYXqjz3qZyrVJ1+Iuc > w > > > PToTUap0KzmqHbb16SlqblU3P7sVFbS5Wk+tmKFbKVJL3/ab974kYMScDeWwpaUcDMfEhnLYUA7 > P > > > 2kJ1eNGhXqk6nvw7U65SqdehC05VEbiNlkP1O+6k5XlqinB15zDPN90gdtSKKbg228jWyZ45T5n > 3 > > > PgAAgCAp6lO9QVmnR1fX4ub1FfWcAh3rwJ2bCOeTToHOyzf1CsO89wEAAIRYW6hmjgvktBpef+X > w > > > gjo9osHDIQ0fDuSqC93My0ukrlPLkM5OOlQ4L9NkNs97X7IwYs6GctjSUg6GY2JDOWwoh2dvNBo > 9 > > > 1reXiptT3T5Qp96nS2735YFKRd1r6ZSoRC0aFPp0TifysaW2bvIVNcejnAi6/uW4uZjJbV5VaeS > 2 > > > Cxv4vhOxJbkfOeCoQVn9/Hnv8+Own8W9XOHpWYuefeZpeZuZb77ZD4D1CtYrWK9gvYL1yiLr2au > v > > > v0V3ynbn3v7+vlj/Bt27+zI9evRIr41vZaE6G4/2zdFVVQQpibBtZKl/6dUWeXBSI6vDWAsPVbW > t > > > oHFMTr1NhU5xjvvsfcfFoXrv7ov6LwAAWJdlhmp6+lRl869D2Rvi9o0sOb0r4u7V+WSofOld2J5 > H > > > D5fIkSONL8v5Oe+bP1DDmL+k1gnlsKEck3BMbCiHDeXwrC9U5Tmq3rmp3dOaNxo4c0wFp0UNt8N > 1 > > > qEYDFxYeuQQAALA86wvVfFOdm6oHIhUHdeqPm3G5pqnOTZUDlXI1OmwH92tauO914iISAAAAq5G > i > > > PtXthj5VAIB02JGBStuNQxUAANIBoQoAALAk2zf6FwAAYMOhprpGUS4eAQAA0fHpkPNA8+8W4FC > d > > > 9QGY9Rhsw4Zt2JLYBtuUsmIbNmwjOjT/AgAApAxCFQAAICEIVQAAgIQgVFNu3v4BE7ZhwzZs2IY > N > > > 27Bt0zZWAaEKAACQEITqhkvLrzeUw4ZyTMIxsaEctjR9VheBUAUAAEgIQnWN8AvRhnLY0vTLHcf > E > > > hnLYUA4PQhUAACAhCFUAAICEIFQBAAASglBdtm5FXo/SXSpdvd4v6uPmFXX7wzM6ivK4ecV+nV2 > q > > > HBzR2VD/mZTI5RjS2ZH3uKOkCzLX+7KE42EYnh3RwbQ3ZtmfVW1mOZb9WdVmlmNsSZ9VbXY5lvx > Z > > > 1eK9L0s4HlHf9xV9Tv0Qqksl/pEVW1Rqj2QH+qhdolaxItb6RX3cvGKUI1ejQ/dx/ToNikn+o4j > / > > > OruVIiU/vXv0cnQrOaodttXjRm06rOUS/Mc55/vSPqRaLsnPh9KtqC+fXK2n1wSJ/x7GFbkcS/2 > s > > > Ri2HZzmf1ejlWO5nNWo5lv1Zjfq+L/9zGgahukzDhzSgEt3O67/zt8VfA3ro/wBEfdy8Im5/eNa > g > > > llOnO+7jMsdUcHp0da3/XlTM18m/iBvZunhMwiK/L2fUaDlUHx+QPDXFP9Cm++eiYn0+HMre0H8 > n > > > /fnQ8k31BdSvO3pNgJjv4TyilGPpn1Uh0vHQlvZZFaK9L0v+rArRPx/L+6xGft9X8DkNg1Bdpus > r > > > 6jlZcj9fJG5lgz4AUR83r4jbz5QvaXRZpoz+WzyRrqL9SI8mzusUXxInnQKdl2/qFQmK9b4U6Ng > 7 > > > IMmKWo5MmaqlHnUu1DeC/GIpVam8rHJNE+c9XKKlf1bjWOZnNaplf1ajWvJnNfL7vsbPKUJ1iYY > P > > > B0SHN40PQIZuHhINfD+Xoj5uXvNuX/6DMH/tLSh6OYZ0dtKhwrn5jyc5sd4X4UI3e/GSZHNanPe > F > > > awnVq5xqfruq0ijJKkgM836Wli3pz2p0y/2sRrXsz2ocq/yshr3v6/ycIlQhWLdCuRpRvd+kVX9 > P > > > Dc9OqFM4X09NzK9Xo6vbqtlrGf120agBKPfdcty+L76wVtM/tBHwWVV27bO6xvd9GoTqEmXUTyP > x > > > MXMNSf2Asv8FRn3cvOJuX47uKw7Eh/Uy0S+LaOUY0kWnJ74f1C/dgwMe/NGjWi650Yyx3her/8Z > u > > > 2lpU5PeleyoHoIx/8Oeb1C61qLH6b8zYn6VlW9ZnNZrlf1ajWvZnNbIVfVZnve/r/JwiVJfpRpa > c > > > 3hV5zfjc/m904ruiPm5eMbbPH1b1628JX1KRypGh8qX+lSuXNpXIEeUZ0WVSBZr7fUlYxHLIpiz > r > > > C2KNYnyWlm2pn9VIVvBZjWrZn9WIVvFZjfS+r/FzilBdpsxNOhS/Xe+7bR/d++KvQ5r4sRT1cfO > K > > > uv1xc8qSvqSW/Tqjivy+8MhC41f2UI2wLCQ1GiRiOTLHBfEF0aFxpSPpcsSRlvdw2Z/VTbPsz2p > E > > > S/+sRn3f1/g5RaguVZ6a8vwoPXhAnjel2//Fh+1o3Ncw5XGJiFaO7n0+y041X6nmLLUk15QV9Xg > s > > > W9RycE1Ene8nHyf+NR+2k/wSj1iOTJku5fl++nGJl2OGlX5Wp1jpZ3WKlX5Wp1jpZ3WKFX5Wp77 > v > > > Kfmc7o1Go8f6NgAAwE7a39+nV19/g+7dfZkePXqk18aHmioAAEBCEKoAAAAJQagCAAAkBKEKAAC > Q > > > EIQqAABAQhCqAAAACUGoAgAAJAShCgAAkBCEKixJlyrm1U7ikldHUc+fPYXVgvuaKrlty4uA622 > F > > > Lkdn67/Gb+CxX+YxjqBbsY/TOssSyn+MVnDMYv07gVVAqMIWyFNTX9Q8+QuZL2PbJWrrbXoLX4x > d > > > 6NUol4ZgnbDMYzxdl+cILfLl6dTF6s3jJWeISeXxYus7ZrA+CFWAVFDXKpVEsJ6i1qGIGqrMUxm > o > > > 5jVkObC8HyInqaqxwi5DqMIKqQmM3aY7/zJuvuImrVyNevpPeVFseWfI8ysVXzNbxP1IXhOdtYw > f > > > FNKEF9QcuWiNiaer0jctgU2f/gu6h7wOsUw0C04re+ixj3EcrLLFeS/8xHMbMlFF5b4acFH2PN1 > 2 > > > f4d0LrxjH+l4CfOW3S30xPN5PlWT/5gl8LkUy/hxoe+VFvU4QKIQqrA+pbZqytM1tFbxiOR3D89 > 0 > > > 0a+PA6bUFo8Zz3rskev5+c3bek2IsP3ILy79Reg+xq39tIr2F5RBTZCsvj5VGfpU58Iu2nR7faW > / > > > IL15Hyf3NSL1MlpUPJj2OkbUl4UyX2+Eskc89ixa2XxC34sAwwvq6MQo3Q4uQ76p9ju6LBNnbtQ > y > > > zVN293F8PLzne03S+iVFF+tzGfB+Tnmv5npvIBEIVVgP/rJwv6zzt1WQiUjpjCdinEE8P+S73jZ > t > > > P8OHNJB/i4eNv7S9frDgMOnSaU1HX72vy5Ch8rn+cpu76VZ8keovQa9W5u3LfL35pg5C8Tpqcmf > B > > > Zc6Uq77jmmTZg7YVVDbDou/5TFHLNF/Z3cfZzz8f16DzTf2DLIqpxyLq+xnGK9/0zw0sA0IVdpe > c > > > yFhR8y5GaBqTkx0z38TLXGvQX4TG92AIri34m+VUzcSsbXj7EuutmlqGjgvy21Fs6v7sMrsSKbs > W > > > tq15y5aEqGVatOzjH2P+56dE0p8biAWhCjtM1Qi8Zjsz7JbZ9+Qb/Ws04bWKwfsdT7asl5xbEzH > I > > > Jj/jMZN9fJCIcTP9ciXxfkb53ECyEKqw88b9cryME1YE7KpO1bD6xlrUmOjwMk8l8S9N8dNADYB > R > > > X5hmYMdojkyjzDF5FavgnzjydBsOjFW9VyuR1Ps563MDy4BQBTDlm+MBIdS7omt1yxPWF7joSfh > G > > > gIxHsob2OxqjSDlMuqekKiD8JTrlyzLJsk8p24U3umjBL+4Mlas6RlqNgME1Xbqvq25O4ZgyUcu > 0 > > > aNlDn5+QqO9nmCmvz/rc6LWQLIQqpN7g4ZL++RunHHhhYg7yCPpizdMdHbp84QH1PPFldaJPbXD > q > > > dGeuJDECpNch9V0YtC+xt7MT/aUrilgtU2Z8Ko75JcpfoP7mwvhlDz/2wWXrVnJeIMx3IGziR45 > q > > > POhRLWeOWjVGyIpyn8vRQlHLtGjZzeefTI7YXVTk99PmvVfBr2/ic6NuQsIQqpBOmTKNM0Z8MSz > l > > > l7X4wvZOZ9C/4PUXI48KNUdemjLlS9/z9Jex+HLv61M75mLUMGon6vXKfemmYbeMqlmQazF6YJH > R > > > fCyPlXwdbkDYIpU94rGf3NaBvlADN1maF2pYjGyel/vhYFX7sd4n45hHLdOiZefnqxYNt0wJBSq > L > > > 8X7yY4PeK/n6Zn1uYCn2RqPRY30bAABgJ+3v79Orr79B9+6+TI8ePdJrlUqlQs1mU//lCVqPmio > A > > > AMAMHKAm/98uhCoAAEAEbpCGBSpDqAIAAExhNvGagRrUJIxQBQAAmMEfoEGByhCqAAAAEbhBGha > o > > > DKEKAAAQ0bRAZQhVAACAhCBUAQAAEoJQBQAASAhCFQAAICF7/7LexGUKAQAAEoBr/wIAACQEzb8 > A > > > AAAJQagCAAAkBKEKAACQEIQqAABAQhCqAAAACUGoAgAAJAShCgAAYPirv/orfSs+hCoAAEBCcPE > H > > > AADYSH/8x3+sbyXjV37lV+R/uab6cz/3c/J2XAhVAADYSByqn/nMZ/Rfk9pv/y/00U8+pI8++kg > u > > > H3/8CZ38xpv6XtsPfvCDREIVzb8AALB1/u9/8z/Tf/vPivSrJ1+mUvnL4r//hP5J6b+m/+3r/1Q > / > > > YjkQqgAAsFX+r7f+JxGo/5g++UTUTj/6kD75+Cf0k7//j3J5/vl/SK9Wi/qRyUOoAgDAVvnJT0S > I > > > ymbfn9DzX25Q4R//JhX/u2/Sj//uP9Lf/+j/o+//v3+jH5k8hCoAAGyVjz76mD7+mJdP6Kc//Sn > 9 > > > 4R/+IT3z6Z+hD0Wo/vjvHsn+1WVBqAIAwFb5Z5V/TV+t/C79D+Vv0R/8wR/Qb9b+Gyr96j+iD3/ > 8 > > > NzJUP/nkE/3I5CFUAQBg67z11lv0e7/3e/R//KtfpRde+Bz95MO/pQ9/9Lf0td8c0DvvvKMflTy > E > > > KgAAbKXf/de/Tr/6T5+ljz/8O/r4x/+JKv/re/T9739f37scCFUAANhKP/MzIuL2iB4/fkwff/x > T > > > vXa5EKoAALCl9uijD/9WLh+LZRUQqgAAsJX++5ebdOfrPfofv/Hv6Z//1gf0J3/yJ/qe5UGoAgD > A > > > Vvo3//uv0+v/4r+g11/+z+lfnfwDunXrlr4nWX/2Z38mF4ZQBQCArcTnqX74o7+hH//ob+nDv/9 > P > > > eu1yIVQBAGArfSRC9ccffkI/+ein9NEne2rg0hL80i/9klwYQhUAALbSr7/yLfrGt/4Dvfq7P6b > G > > > //mf0Xe/+119z+LMJl80/wIAwE5ot9v0ne98h7rdrl6zXAhVAACAmMwmX/M2JikHAICNxJOUJ2n > W > > > JOVuEy8HaNhthCoAAIABoQoAAJAC6FMFAABIyN4H7RdRUwUAAFgY0f8Pv2raZV7mqO4AAAAASUV > O > > RK5CYII= > > --001a113d6a0a1ede02053654edd6--> > > -- *A GENTLE WORD, A KIND LOOK, A GOOD-NATURED SMILE CAN WORK WONDERS AND ACCOMPLISH* --------------------------- * Venkata Pera Reddy B.* * Research scholar* * Dept. of Chemistry* * National Institute of Technology* * Durgapur**-713209,W.B, India* --001a113deff4117613053659b409 Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable
th= ank you Dear=C2=A0 =C2=A0Dr. Tobias Kraemer ,
I have tried both forward and reverse and o= ptimized the last point geometry on IRC, in each case it is optimized as pr= oduct intermediate. can any one suggest regarding this Correct transition s= tate characterization.

On 28 June 2016 at 20:31, Tobias Kraemer t.kraemer~!~<= a href=3D"http://hw.ac.uk">hw.ac.uk <owner-chemistry/a\ccl.net= > wrote:

Sent to CCL by: "Tobias=C2=A0 Kraemer" [t.kraemer:_:hw.ac.uk]
Dear Teja,


At first glance this looks like a reasonable IRC, quite flat around the TS<= br> (not sure what the outlier means). A reasonable thing to do next is to
optimize the last point of the IRC (1.8 on the X-coordinate) and see where<= br> this leads you. Of course you should also run the IRC job for the other
direction (reverse or forward, whichever way you look at this) and do the same thing here, optimize the last point on the trajectory. Inspection of these optimized structures help you to confirm if the TS is reasonable and<= br> the one you were looking for. I often look the at the animation of the
imaginary mode itself, this tells me already if this TS corresponds to the<= br> desired reaction coordinate. You can also do a quick version of the above protocol, displace the TS geometry by a small increment in both directions<= br> of the TS along the imaginary mode (use GaussView to do this), and optimize=
these new (initial) geometries to their nearest minima. In the end, it is a=
combination of visual inspection of the TS as well as the ground state
geometries which will reveal if this is the right TS for the reaction.

Hope this helps


Tobi



Dr. Tobias Kraemer MRSC
Research Associate
Institute of Chemical Sciences
School of Engineering & Physical Sciences
Heriot-Watt University
Edinburgh EH14 4AS
United Kingdom
email: t.kraemer a hw.ac.uk
phone: +44 (0)131 451 3259

> "teja reddy reddyteja80%gmail.com"=C2=A0 wrote:
>
> Sent to CCL by: teja reddy [reddyteja80~~gmail.com]
> --001a113d6a0a1ede02053654edd6
> Content-Type: multipart/alternative;
boundary=3D001a113d6a0a1eddff053654edd5
>
> --001a113d6a0a1eddff053654edd5
> Content-Type: text/plain; charset=3DUTF-8
> Content-Transfer-Encoding: quoted-printable
>
> Dear friends, =3DE2=3D80=3D8BI have optimized TBP transition state whi= ch is
showi=3D
> ng
> -216cm-1 negative frequency but is showing only 9 points on the = curve
like
> shown below. can anyone help me is it a correct transition state
> [image: Inline images 1]
>
> --001a113d6a0a1eddff053654edd5
> Content-Type: text/html; charset=3DUTF-8
> Content-Transfer-Encoding: quoted-printable
>
> <div dir=3D3D"ltr"><div class=3D3D"gmail_defau= lt"
style=3D3D"color:rgb(0,0,0)">De=3D
> ar friends, =3DE2=3D80=3D8BI have optimized TBP transition state which= is
showing=3D
>=C2=A0 -216cm-1 negative frequency but is showing only 9 points o= n the curve
like=3D
>=C2=A0 shown below. can anyone help me is it a correct transition state= </div>
<div=3D
>=C2=A0 class=3D3D"gmail_default" style=3D3D"color:rgb(0,= 0,0)"><img width=3D3D"469"
heig=3D
> ht=3D3D"434" alt=3D3D"Inline images 1" src=3D3D&qu= ot;cid:ii_15596c33e3e5b53d"><b>
</b><=3D
> i></i><u></u><sub></sub><sup>&l= t;/sup><strike></strike><br clear=3D3D"all">=
</div=3D
> ><b></b><br><div class=3D3D"gmail_signatu= re" data-
smartmail=3D3D"gmail_signatur=3D
> e"><div dir=3D3D"ltr"><div><div dir= =3D3D"ltr"><div><div dir=3D3D"ltr"><d= iv><div
d=3D
> ir=3D3D"ltr"><div><span style=3D3D"font-fam= ily:courier new,monospace"><b><i>
<fo=3D
> nt color=3D3D"#000000"><br></font></i>&= lt;/b></span></div><span style=3D3D"font-
fa=3D
> mily:courier new,monospace"><b><i><font
color=3D3D"#000000">=3DC2=3DA0=3DC2=3DA0=3DC2=3D
>
=3DA0=3DC2=3DA0=3DC2=3DA0=3DC2=3DA0=3DC2=3DA0=3DC2=3DA0=3DC2=3DA0=3DC2=3DA0= =3DC2=3DA0=3DC2=3DA0=3DC2=3DA0=3DC2=3DA0=3DC2=3DA0
=3D
>=C2=A0 </font></i></b></span></div></d= iv></div></div></div></div></div></div&= gt;
> </div>
>
> --001a113d6a0a1eddff053654edd5--
> --001a113d6a0a1ede02053654edd6
> Content-Type: image/png; name=3D"image.png"
> Content-Disposition: inline; filename=3D"image.png"
> Content-Transfer-Encoding: base64
> Content-ID: <ii_15596c33e3e5b53d>
> X-Attachment-Id: ii_15596c33e3e5b53d
>
>
iVBORw0KGgoAAAANSUhEUgAAAdUAAAGyCAYAAACySF4VAAAAAXNSR0IArs4c6QAAAARnQU1BAAC=
x
>
jwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAEqjSURBVHhe7d1fjCvXfSf4Xwf75HnoBhYIECB=
Y
>
KLw3Itx6URi7MMLuyFcO2G377guxIgbjxU64mpXTlDdXnIEZXGr3ruHRrKiE2R2qF1a3o4lA5CG=
7
>
Czog8nCd6SZiXwVeDEA5DLAD0WjlNqOHAAECzA5vJnEsS/Ld8zvnFOucYhVZRRbJIvn9GGWxi2T=
V
>
YZGXX54/VWfvsUAAAACwsJ/R/wUAAIAFIVQBAAASglAFAABISGif6t7enr41HbpkAQAAlKmhOis=
w
>
3eBFsAIAAPhCNax2GhaaMnj5v2JBsAIAwK6b6FPlaDQX9ujRI/nfs7Mz+sY3viH/63JjOGpzMQA=
A
>
bC7+ro+ypA2X6U//9E/1X5P4viTKHWug0l//9V/TX/7lX8r/Mq6dustMH7xNz3/60/Rpd3n+bfp=
A
>
3yV97xWx/hX6nv7T9j16hZ/zSvC9H7z9vHju8/S2ucEp2/veK5+m560HC/x4c/tTyzMLl9d9ri6=
7
>
sUy+jA/o7eeNx/iPjeTfjvl6+T7f6wcAWBLzuz9oSaMf/OAH9Mx/+V8FBiuv4/v4MYuKFao/+7M=
/
>
Sz//8z8v/xsLB+oXv0Nf+qMf0g9/qJY3n3xIf6HuVIHSJSrIv8M8RU+9/82A4Pge/U7jPX2bzd7=
e
>
c/kCvfdQ7d31vW6HCvnnxK2o5YnjKaq6r/3NAnVeMsJa/tj4Ij38qndsfvjbRN8NTHNvO39UJWp=
8
>
LSh8p0H4AsBu+uVf/mX6d//P9yeC1Q1Uvo8fs6hYofrlL3/Z+m80IqS+1qAn3/w2vfCEXiU899p=
r
>
xBFG9AS98G0RFK/l5V/TPPkk0Xe+60uE73WpUygYARhhe79wk57qdL1gE7e6nQLJTI1Rnrk8lxd=
l
>
fZ/+Qr4M99j8kF5TB0N54gV6wfw7wBMvfJUK732H/IcDAACC+YM16UBlE6HKLcrmsrAPvkvfec8=
N
>
rBi4+dXXDHrzK1+lJxu/Y4ShCKVvvk/Vr0QIQHN7T3yevvRUh7ruhmQw53XILxnv66kv0ef5B8a=
8
>
x2YWX1O7am7mWupL1KH3qPFFsT6kKR0AYJuZwZp0oDIrVP1t4qPRSC6u3//937f+G9lTN+kX9E3=
V
>
/8lf9vM0Qz5H+YIRhhxKpAMqlifo8196it5X1UWj6XdZdJDx6+7m6YfffkGUQDOOTRwfvP1NL5w=
t
>
Ijy/qGq/sin5j6r0/kt8rJ+j1374pqgl6yZkq2oMAOtgDuyZtsDmmNr8u7+/P16Yf6BSZO+5/af=
c
>
bPlt8WXPX+4zPPeaHT7ac18RIfFNVeP83u+I8Pjq5GMC+bb3xOe/xG3JYjsf0F+8/xTdjJNsVk0=
w
>
ymAmHWQi4OxmZ8E4NrN54fzFxpP0ZsDxoQ/+gt4XR3f8G+GJF+irhffI14UMAClgVmSmLZAcs8n=
X
>
bApOSuQ+1evra2ugEv8dyRO/QE+O+xATwE23on763e+9Td98v0pfmbfCNd7OHLVdEVTfdgcV/dD=
t
>
G45APO+3q+/TN90qur8ZeiZjwFOc/QIAwEQfqr+PNQkzQ9U9N/Xy8pKOjo7o61//uvwv/+0/ZzX=
Y
>
cyQql6KGFfP0lIA+VeUJeuGrT1LjpQbRlz4frZbKJrbHTcCiXHG3syAeYPRk42u66ZtfC48G9p1=
m
>
I2rCb8c6WAb5I8ZsIhc/PsaDsAAAdlPYoKSkg3VmqJpNvjdu3JDr+L9xmoJlk++bRC+Nm0xfove=
r
>
v22NBo7lua9Q9akCfXXuDSjcBPyU+N+X4nfKLkD/yHBPh+Fmadnv6R4bsXyN6PNzh+Bz9Jq5PXk=
q
>
k1ur5T5pDFQCgMUE9fuaSxp95jOfmQhUlxus/JhF7T0OabDnA8N3cU2Ug5ObfMvlsr5X1WDN9e7=
j
>
AQAAdtXMUI0KoQoAALtuaqjGhVAFAIBdFhqqAAAAEE/kU2oAAABgOoQqAABAQhCqAAAACUGoAgA=
A
>
JAShCgAAkBCEKgAAQEIQqgAAAAnZG41GOE8VAAAgAaipAgAAJAShCgAAkBCEKgAAQEIQqgAAAAk=
R
>
odqlysEBHYyXIzob6nvlfebfAAAAEEbXVB2q90c0Go2oXyeqnZxRvBxF+AIAAEw0/2bKVSr1OnS=
B
>
gAQAAIglXp/q8IyOjKbiSpdXci21SC3qUS0n1suVQzo78j8OAABgu02E6vCsQS2nQMcZvWJMhGe=
u
>
Rodt1Uw86tdpUOQm3zw1R20quU3Izbx46CnVDtvqcWLhVQAAANtOh6quZYpaZa52SO3LMk1k6vA=
h
>
DUR03nYDMlOmaqlHV9f6b9ONLDmtIh2hkxUAAHbIxECl0ahJC1csReBeim2d0wmafwEAYGdE71P=
N
>
3KRDatF9NyCHZ9RoGTXXAJnyJfXrDg0eosYKAADbL8ZApTw1ZT+qHoCU61Ch79Zq83S7ZAxU6lb=
G
>
g5S4OblanmhMBgAA2DqYpQYAACAhMWqqAAAAMA1CFQAAICEIVQAAgIQgVAEAABKCUAUAAEgIQhU=
A
>
ACAhCFUAAICEIFQBAAASglAFAABICEIVAAAgIQhVAACAhCBUAQAAErL3L+tNXFAfAAAgAQhVAAA=
A
>
7d7dl+nRo0f6r/j2Hgv6NgAAwM569fU3Fg9VzKcKAAC7bn9/P5FQxUAlAACAhCBUAQAAEoJQBQA=
A
>
SAhCFQAAIKJKpaJvBUOoAgAAROAG6rRgRagCAADM4A/SsGBFqAIAAExhBmiz2dS3goMVoQoAABC=
B
>
G6hmsPohVGHNulQ5OKCDqEulq5+3WsM387oMeXpzqFeG6VbsMs9Y1vSSNkasY58yQWX31k1f8tN=
e
>
bNhnLP8mbdgh2hj+IA0LVoQqAEAKvftKLiBY9Y/QYkv/7fPuK5QT908NZIgtLECD1iNUYc3y1By=
N
>
aGQs/dc+q+/7LL3Wt+8bNfP6vni6FffXfEV8La3OZ1/r2+UPWOZ8SbAFSu2Az0T/NfHJV9595dT=
4
>
vA7pzXyRvDgtUdt8Xruk1/Pzfm3javXbAqEKAJAmmZfoW+Mflu/Rn7vh2D2lV97Vtz/7GvVHTfG=
T
>
1JBvGoH8Lr1yin6FdUCowkbzaqD24vVTquYyr7WsRUV+jPuAFPVNzexrC+l8DT4Gk/2PYcfK2y7=
X
>
hALuHy+qlm9ux1+kafdNSODYz37/lfmObbTjsSrd++6H+LP02rdeooz+yyICuevWXNEEshYIVdh=
Q
>
/rC0tYriS2/Gt7r8op3WN5W2QR+tou81TTsGoqaSi9O3xtvKeTWhKfJ3vObJ1n27PN73/mt0Z8p=
3
>
+uLHfvH33xJ4bKMdj8QN36RfG+/4KfpFmZ5D+vP35ApxbAv0hcBEhTRAqMJG6laMviXZFKZ/nRv=
9
>
UfxFWemqPluvu0n3QzWJTsdfXGbfVJ/GLW/vdujfLpiqPNgkuJajlynhMe6PtV7TffF1r1jHoNT=
W
>
5eelLV6REt63ZrxmUaMJ3ZbRTzeW+QIVvFQdl0dUpcbb+GzhC8E1Kam78LGP/v7r2z5zH9ug47E=
A
>
Gf7+z0TuFfGTSCm13Sbea3p/nLO/OOXYQhKur6/nXhCqsIHsGlG/azSFcfOX8cVn16RM5gAps28=
q
>
Q18YJ8a79P61vrliPICl+5J+VeI1/cb4Jbl9bL5jYDX1iddm9K11JtKJB4CZr3nKtvJN4weJyzx=
G
>
LXIPsdk8WZhalVr02C/2/i90bAOPR/Lc0EcL7uZBqMLmGf65+PrTgn6152+Pa2r03p9HakY0awq=
5
>
BNv8Zo7+NQMhDvMY6NMozNdg1nbenfXLYNbxDJD5QmFcw1PBZQRR6TfIzazp5jz2ib7/AeY4HvO=
y
>
R/96NXVu4bBr2TfoSfeAz/OaYGUQqrCz1CAXo5lvWy3jS9jfBGw0/ZZuz65e7cyxjyVDL3W9pvt=
W
>
0RwIlaFffErfTKBbApYHoQqbJ/OL5H6/BAaG8QUfWtMYvkm/NX6Qfb6fd55sipnHwOpPDVhm1YZ=
n
>
Hc9AdhNwcTxiqEQzM3XRY5/E+z/NXMcjKXm6Mz4GLfoto0M8f9uN23fplV8L6YsXxzbv1vzjDNS=
C
>
xCBUYQPlyft+8Y0U5S8VY0joZK1J95tdvz9uHhUPsvoXvUE0aWYcg4mRq3wYvFNIZo8A9h3P8bb=
U
>
KSVhI2zNJuAx61iGWPjYL/L+RzHf8UiKeVzf7fxb77Xl7xgDubjJ33dKD792c5DTXK8dFoVQhY2=
U
>
b3rNZOoLRv86N75UuAY3OdBDnWpy8FvveYHAoeQ+P+EmyZmjf3mZs0ZhHQPrNZh9kyX6jQgdnOZ=
p
>
Mt62ZpxSYg3yUSJ9kZt9nnMe+/nf/2jmOh5JMZvWraZeu3lYFEydcx3w2rkvH4Oc1gOhChvKf6q=
M
>
TQ4AMb5VrC9JqUDfMk492UzqGIQ1mapBUr6r7oThUbNzHA+vSZJFaPqVuNyLHvt4739scx6PZNi=
j
>
oO0rI+mR06FDkFVz+nh0M6zc3mg0eqxvAwD4cJOnW0PjL2x/SPMIXl3D5L7dra8ezToesKn29/f=
p
>
1dffoHt3X6Z+v6/XxoeaKgBMYVx0IEjMUb+bb8bxgJ2HUAXYeeY1bs1rBvN6o59zYhCSqKW6o3Y=
+
>
O/2yhJtl3uMBgFAFAB4AMx5xpAdyyUAxB+Z8ll4bp6Z70QYvYKZflnDTxD0eAB6EKgAQX37Pug6=
u
>
iS/VN+qGXyWp1N6+gTGLHA/YaRioBAAAOw8DlQAAAFIGoQoAAJAQhCoAAEBCEKoAAAAJQagCAAA=
k
>
BKN/V+T0bHzKOAAArNmdsn395KRG/643VLsVOhjPo+S/juaQzo5yVOupv5x6ny7L9olhw7Mjyl1=
V
>
I1xvlE9Wb1C2f0nuJuRz3Y2TQ3XjPs/k8+bFoXrv7ov6L+Wdd96lz30u+GLoq4Ry2FCOSTgmNpT=
D
>
tmnlePX1t5YWqutr/h2e0VFxIMJMT05cH1Dx6ExEqdKtiEA9dCdfbtNhLUfuDFndirrCiReK03U=
r
>
vimlRJjnaofe5MjtQ6qdePt2TTwPAABgirWF6vCiQ71SdVwDzJSrVOp16IKTTQRuoyVqj+PLgKn=
p
>
jtwKab7pBrGjVkzBNdJGtm5P4cRXSzFrxTey5PSu6Fr/yQKfBwAAMEWKBirdoKzToytOtusr6jk=
F
>
Ol6wyZXD+aRToPPyTb0imAx4JytKoEV83qLS0FzCUA4byjEJx8SGcthQDs/aQjVzXCCn1aAzt81=
1
>
eEGdHtHg4ZCGDwdy1YVu5uXFbfqNbkhnJx0qnJfDL/TNTdCyGZmoPn5chOcBAAAEWNlAJXNg0Hj=
Q
>
kTlQySlRiVo0KPTpnE7kY3n2ftnky+GXE0HnGzA0baAS33citqQGN80YcGRs//gi+vM47GfhZmr=
G
>
A5WefeZpeZuZv6i4c92F9QrWK1ivYL2C9coi69kyByql6JQaNdr3qiqClETYNrLUv/Rqizw4qZG=
1
>
RwCHh6o9ctgUNIqYqe23qdApxnreNBy6Zqhi9O90KIctLeVgOCY2lMO2aeXYztG/frL516Esd2w=
G
>
DByKJ0PlSz2yVy5tUQvm02ZGIcE4JNXifCPm8wAAADzrC1Vu+j2okNtV2j2teaOBM8dUcFrUcDt=
c
>
h2o0cGHhkUsK13DNfYudi9ppctsHAIDdtL5QzTfVual6IFJxUKf+uBmXa5rq3FQ5UClXo8N2hAs=
w
>
yIFHRliGyJQvrX0fyPNlF7/AQ1xpaC5hKIcN5ZiEY2JDOWwohweXKVyiWX2qAACwervRpwoAALD=
h
>
EKprxCPV0gDlsKEck3BMbCiHDeXwIFQBAAASglAFAABICEJ1jTBizoZy2NJSDoZjYkM5bCiHB6E=
K
>
AACQEIRqAuS5rgHLTHv/QC0AALAVEKoJ8C5raC+hdJi+8+AB0eO/W3u4YuSeDeWYhGNiQzlsKIc=
H
>
obpqHJ4iSPfoMd269Tna2/uUClY3XAEAYGMhVNeAg/TBg3fGiwzWlOMyugsAAARDqK6SrqWGWlN=
t
>
ddaIuVX9CMAIQltaysFwTGwohw3l8CBUYS57Ivx5AQAAD0J1lXRN9PHjH8n+VHfhv6VZNdkUeSz=
K
>
yYsbrtMWAIBdsd5QlXOquqeg+KdsG9LZkXd6ypE7t6pBzotamTXRG+tS5eCIzE2oOVXd7Zv32fu=
d
>
vD8ZKkj3vEBdo1kj5kJ/BAhuuE5bgoLWvzCMILSlpRwMx8SGcthQDs/6QpXnPpXzmKrTT+T8pkd=
n
>
ItKUbiVHtcO2Pj1Fza3q5me3osIuV+upFTN0K0Vq6duSCPNc7ZDa7ukv7UOqnXj7JnLG5VJLgnO=
t
>
ipCRNVIdJJL7N9+XWuoHwDw/AoKC1r9wsN66dWsibM0lLgyuAoBVW1uoDi861CtVx2GVKVep1Ov=
Q
>
BSebCNxGSwTbHXfS8jw1Rbi5c5jnmyrs+nVHrZiCa6SNbJ2smfPyTfH8ptiqdiNLTu+KrvWfRId=
0
>
c5kTlosQ4UVOZMthof/eZRysDx48mAhbcwkKWv/iWtXgKgAAU4r6VG9Q1unRFSfb9RX1nAIdLxp=
s
>
IpxPOgU6L9/UK4LJgHeyogTsmq6iVYAXtsf/J8Ji3TZl5F5Q0PoXf7jOAyMZJ+GY2FAOG8rhWVu=
o
>
Zo4L5LQaXl/l8II6IswGD4c0fDiQqy50My8vkbpOLUM6O+lQ4bxModnMTdCyGZmobj1uQA2jXzX=
+
>
vmFd3HANYtZozQUAICl7o9FItkIuGzfDun2gTr1Pl9zuywOVirq30ylRiVo0KPTpnE7kY0tt3eT=
L
>
4ZcTAdm3+zblNq+qNHLbhQ1834nYktyPHKjUoKzv+WPm9sm3r5B9Mw7cWbiZmp2etejZZ56Wtxn=
/
>
ouIvdA4As3Pd/KWVlvWbUk6Xu54HVbm4Lzjs8UHBuomvl2G9gvUK1ivmevbq62/RnbLVKUj7+/t=
i
>
/Rt07+7L1O/39dr4Vhaqs/Go2xxdVUWQkgjbRpb6l17tkQcnNbI6jLXwUFXbChrHNA50n6Dtu6b=
d
>
Nw2Hrhmq9+6+KG+73LBaN/7w+T90plWVc1Y5VoXLwYOmgqzy/UrL8WBpem9QDg/KYYtajmWGanr=
6
>
VGXzr0NZ7ticGDgUV4bKl+bo3baoBasRvcHBOCTd4gwgcXgGLfwDw78AALjWF6ryHFXv3NTuac0=
b
>
DZw5poLToobb4TpUo4ELC49cUriGa50X2z0VtVq1/cn7KlRMcN+w2aIGLS8AsHvWF6r5pjo3VQ8=
G
>
Kg7q1B8343JNU52bKgcL5Wp02A7pDzXJgUf+i0hMypQvrX0fyPNl1fan3bet0tBswza1HEFBy0v=
c
>
oPWfV5uW48HwGbGhHDaUw5OiPtXtsyl9qtNsQhk3SXiwPpbn07r8V64CgOTsRp8qwA4wa7LmAgD=
b
>
AaEKcsRcGqAcNrfJOLx2uzp4b2wohw3l8EQLVdlXqfsYA5fkLzgPsEu4qdc/aYF52cY0BSwAhAs=
P
>
VTNITzp6ZbjOCQIWYBEcpO7iZzYVmwGLkAVIl5BQ7VLFCtICnY/P+QxazsUjPJ2T2SNwIT3CRsz=
x
>
FzZ/ia8KRhDawsphBqw/ZJcF740N5bChHJ4pzb9GkBpXNgpmXmzBDlgAWK6wgF1myAJAsJBQzVN=
z
>
ZpCG4YA1plXbAXb/srcArJoZsP6QBYDlizZQCaaym8K9ZVNg5J5tm8qRVMDivbGhHDaUwxM9VM2=
B
>
S0dnxGOR+ELzB5gXbSvxFy9/EcP2CAvYeUIWAIJFC1W+Tm+uRsFzd9+nMwz3BdgoZsD6QxYA5hc=
h
>
VId01uA5T9UsL/26o1YL+Waf6oMW1WqnGO27wTByz7aL5QgLWDdk8d7YUA4byuGJEKrXdCWqqE7=
9
>
POCi8hkqV+3rJwLAZjMD1h+yfv5JAAB23cIDlYaYiBRgq4UFLAcpTwLgLghWgEiheoOyDlGvliP=
/
>
mCSeezRX42psVjxqDnJOVfcUFP8FI4Z0duTed0BHAf22cu7TSAOlulTxXelJzZvqbt9/FajZ+94=
m
>
/hFz/IXJX6CrhhGEtrSUg7llMQN2HfDe2FAOWxrKESFUvSbeVvFAhWivRjkRNvK2UKrOcU4rjya=
W
>
c5Wq00/kHKZ6VDHrVnJUO2zr01PU3KpufspRx8b+Z+lWisS9wmMizHO1Q2q7p7+0D6l2Em3fAAA=
A
>
YaI1/+abMlwme09LMpjGc4vHMLzoUK9UHffTZspVKvU6dMHJJgK30XKofsfdcJ6axn7yTTeIvUF=
T
>
YbhG2sjW7bLL12NcoOJGlpzeFV3z7Rn7BgAlaBIAt2kYYFfF6FNV4aJqb+6S5JWTuJm5R1ecbNd=
X
>
1HMKdDzfJZ08IiBPOgU6L9/UK4LJgHebsJPa9wbByD0byjEprCz+SQDcpuFlhSveGxvKYUtDORY=
e
>
qDSvzHGBnFbD68scXlCnRzR4OBwPfrrQzby8xG9+HdLZSYcK51OaprkJWjYjE9X145LZ9+ZaV38=
q
>
bJdlhytAWu2JGudjfXs6DiD3AhBOnfqXZboWwVOkNo0itI2OBzUJTr1Pl9zuywOVirq30ylRiVo=
0
>
KPTpnE7kY0tt3ewq9y0Csn9pndYjt3lVDdw/33citiT3IwcqNSjre/6Ysf3jC1XOWftmHLizcI2=
e
>
nZ616Nlnnpa3Gf+icgPM7Fw3f2mtYz2XiefxdK1qvwzrlW1c7war+9la1X4Z1itY73n19bfoTtn=
u
>
0Nzf3xfr36B7d1+mfr+v18YXLVTN8GNWqJaonr1D5cC0ioNH3OboqirCjMT+Glm5D3erPDipkdV=
h
>
rIWHqtpW0DimcaD7jLd/8zTSvqPg0DVD9d7dF+Vtlxuq68YfPvdDt84ymeVYJ5RjUlJlccN13s8=
Y
>
3hsbymGLWo5lhmqE5l8RUKu4opJs/nUoyx2b5sChuZhT0fHCg6xU+YODcUjj020X3jcAhOEw5YX=
D
>
1Q1YgG0SIVSXdEUleY6qd25q97TmjQbOHFPBaVHD7XAdqhG5hYRGD3EN1zovtnsqarV6+0veNwA=
g
>
XGF7LTxQae4rKuWb6txUPRioOKhTf9yMyzVNdX6oHCyUq9FhO6Q/1MT9nxMXkZiUKV9a+z6Q58u=
6
>
259z3xvMbS7hL7d5m+WSkIbmI4ZyTFpWWeKGK94bG8phS0M5IoTq8q6oxOE2bqKdmBTdPoUnYCy=
S
>
er55R6ZMl4Gn+fC27GC09u27L8q+ASA5qLnCtogQqku6ohIAgA/CFTZdtObfJVxRCdKDR8ylAcp=
h
>
S0s52KrLEhaueG9sKIctDeWI0ae67CsqAQDYUHOFTRMhVPnCCds/U8uu4y8s/vICSCM3XG/duoV=
w
>
hVSLUVOFbYWRezaUY1JaypKWmis+IzaUwxMhVN3Rvye+OUcBANYjLeEK4BchVNXFH0SsUi2nz+u=
c
>
WGafG7rNgo/J7OsCA8BiEK6QNmj+TYA9eMtbNgV/GfEX07phBKEtLeVgaT8mqw5XfEZsKIcnQqg=
G
>
jfr1LxgFDADrh5orrFuEUFWjf3dpTlEA2GxB4bq396nxArAsizf/yuvtHmEQEywMIwhtaSkH29R=
j
>
4oXrp+jBg3fGy6LBis+IDeXwTAlVVUM9OCgST/zGlygMGozDF5xXFysEAADYbckMVHIKhJnRNhM=
3
>
jfEveQAAWNyUUHUHKKlr/pba/sFJxjIxw0xEck5Vt9brPy1nSGdHXo046IpOcl7USJ29XOu2m6j=
V
>
nKru9o37rDIZy9GZKNF2wsg9G8oxadOPyePHP6Jbtz43XsTPSXXHnPAZsaEcnmRqqvPgvlg5j6k=
K
>
Zjm/qRFc3UqOaodtHdxqflM3P7sVFXTuLDmzdCuqCXtMBGeudignA5Dbbx9S7UTvW04eoNeP759=
z
>
InYASA0OVm9Rg5gAkhY5VAcPk62nDS861CtVx/OYZspVKvU6dMG7EYHbaDlUv+OeqKNqze5sOPm=
m
>
Crt+3VErpuAaaSNbt2fYkcFpnAZ0I0tO74qu9Z9+3fstcgrHmN4OYIsgWGEZ1ldTncCXQ+zRFSf=
b
>
9RX1kuinFeF80inQefmmXhFMBnzYROsy4EtUtWcx3wpufypG7tlQjknbekzmDVZ8RmwohydCqC7=
n
>
2r+Z4wI5rYa3zeEFdXqqRjx8OJCrLnQzLy/xz5Md0tlJhwrnU/p7RWAeyWZkonrI47qnfOcdXNw=
C
>
YEuhxgpJ2huNRo/17RA8yMfXJzmBJyufflUlboZ1+0Cdep8uuebHg4KKestOSWylRYNCn87pRD6=
W
>
B0fJJl8Ov5wIyP7luLmYyW1eVWkUMEs633citiT3I19Dg7K+54+FbD90vcZhPws3U7PTsxY9+8z=
T
>
8jbjX1RuTdHsXDd/aS17Pe//wYMH8vYq94v1CtYraVm/7n+PWK8sez179fW36E7ZHiuzv78v1r9=
B
>
9+6+TP1+X6+Nb2WhOhuP9s3RVVUEKYmwbWSpb4wq5sFJjawOYy08VNW2gsYxjQPdJ2j7vK5I7cD=
Q
>
joJD1wzVe3dflLdd7j/idTG/RPwfunVAOWxpKQfbhWMS598jPiO2TSvHMkM1QvPviq79K5t/Hcp=
y
>
x+aMgUOzZah8aZaPTwty5EjjoEDlENYtzoYu3bcGSwHANuNA5WAFWMT6BirJ80G9c1O573I8Gjh=
z
>
TAWnRQ23w3WoRgMXErrCBNdwrfNiu6eiVmtvf3jWoNYWX9Ri3bVkgDRCsMKiIoaqfSGGyWWO+VT=
z
>
TXVuqt5GcVCn/riZlWua6txUuf1cjQ7bIf2hJjnwaHZZMuVLa98H8nxZc/tdOuU+3eqcF7XYMGl=
o
>
tmEohy0t5WC7dEyiBCs+IzaUwxOhT5Urldy3WKJSqxXSt5pEn+r24cDm5meWtj5V1FQBpsO/ke2=
1
>
5j5V7lvk/96Wfavy4kIl70pHslhh53gCAGwoNAXDPCL3qZZuB9VD83SHr2q00KAiWDX/L3AeMZc=
G
>
KIctLeVgu3pMwoIVnxEbyuGJPVDpBl8JYvCQ3Gs2ZG4e6lsAANsHNVaII3Kotu6r4T8yRHs1OtW=
j
>
gfi6uAAA2wzBClFFCNU83ZYdp/fpjE9xyd+W/ajupOXFgUNO6TYGKW0wjNyzoRyTcEzsYMXxsKE=
c
>
nkg11XyzT/VBizrqL2r26+TND1Og8zmvOAQAsElQY4VZIjb/qisUja9GlCnTpXu1onknKN8i8lz=
X
>
gCWN+AuBvxgAYD4IVpgm9kAlmKROL5pcNgVG7tlQjkk4JjaeiCINwYr3xZaGcoSEKl9EP7j2Fbz=
M
>
cUUlAIANhhorBEFNFQBgTghW8AsJ1YCZadSllKjtXy8XXKJwk2Hkng3lmIRjYjPLsc5gxftiS0M=
5
>
UFPdIfwPH4OUAACWB6EKALAgNAODa72hKudUDRvsZE83d+TOrWqQ86JWogyR4oFXR2RuQs2p6m7=
f
>
vk9NIRdy3xbCyD0byjEJx8QWVI51BCveF1sayrG+UOXgkvOYqn5ZOb/p0dn4msLdSo5qh95sODy=
3
>
qpufPBUdB16u1lMrZuhWivaUdSLMc7VDr3+4fUi1E3ffIoDl/K3GfTmMbgaA2VBjhbWF6vCiQ71=
S
>
dTwxeKZcpVKvQxecbCJwGy2H6nfc4U9q4JR74aZ8UwVen2fImYFrpI1sXU1R58o3xfONwVU3suS=
4
>
M+0MH9KAHMq6c9nJyzIO6OGG11bRnwqwGgjW3ZaiPtUblHV6dMXJdn1FPadAx4teqkmE80mnQOf=
l
>
m3pFMBnw7pywmTJVSz3qyHTnTTSoZYT/NsLIPRvKMQnHxDarHKsKVrwvtjSUIyRUAy7+UOQG1BY=
V
>
/evlEr95NHNcIKfV8PorhxfU6fGsckNRWRzIVRe6mZeXSF2nliGdnXSocD7lMoq67zRXI6obj+O=
a
>
cPUqJ/ebu6rSCNc2BoCYUGPdTXuj0eixvm3gUPX1Q07F569OP1eVm2HdPlCn3lfXEeaBSjKseWV=
J
>
bKVFg0KfzulEPrbU1k2+HH45EZD9S6vGKLcZEnp834nYkrpeMb+eBmV9zx+zts8DpHJ0VdX7lmW=
k
>
wNfHoTsLN1Oz07MWPfvM0/I2419UbpOs2blu/tJKcv2tW7fkpdWWtX0X1itYr2A9yX97ZtfLqvb=
L
>
sF4x17NXX3+L7pStTkHa398X69+ge3dfpn6/r9fGFxKq62CEGYkga2Spb1ysnwcnNbI6jLXwUFX=
b
>
ChrHNA50n/H2b57Swf3b1jaD9h0Fh64Zqvfuvihvu1bZzzltX/zh83/o1gHlsKWlHAzHxBa3HMv=
6
>
t473xRa1HMsM1fT0qcrmXz1AyBw4NBc1qw4HmlraohbsyJHGwcE4JN3irJqeBw/1SODtsMrwBoB=
J
>
/O+P/x3C9gvvUzVOb4mHa4kR+ljlOare47qnNW80cOaYCk6LGm6H61CNBi4sPHJJ4Rqu1Q/cPRW=
1
>
WrV92dfrjkJmCe8bAHYTgnU3TKmpdujkQA8UijBKyD139ODgRE9mPkO+qc5N1fsoDurUHze5ck1=
T
>
nZsqtynPGw3pDzXJgUezAz1TvrT2fSDPl9Xb57li5bmp+r6o+95gaWi2YSiHLS3lYDgmtnnLkXS=
w
>
4n2xpaEc4X2qcvCOqD3y7VKJSq3W1IFLpXabqMiDm7iZdbtDKCoO5TT0qaL5FyBd8G9yvdbTp8o=
1
>
NrdP8jafTDOLO7MNAjVN8I8XIH2SrrFCekQbqCSvQOQO+gleAs5qgQ3BI+bSAOWwpaUcDMfElkQ=
5
>
kghWvC+2NJQjPaN/AQB2DGqs2wehCgAAkBCEKmDkng/KMQnHxJZkORapreJ9saWhHAjVLYZBSgC=
b
>
Ac3A2yNCqKqL68e/oP3ukOezBiwAAFEhWLdD5Jpqq+iGRfwZabZd0GhoXjYFRu7ZUI5JOCa2ZZU=
j
>
brDifbGloRxzNP8a07/NfSlDAAAI4gbr3t6nxgtsjgih6l7UQSxt+woU1KtRTgfs0XhiVAAAWMx=
j
>
evDgnfGCYN0c8Wqq5kUgfAHbc6/Ti87XVIgzSAkj92woxyQcExvKYUM5PPFCVc4so5t+3cnF/Vp=
F
>
BCsAAOykCKGqRv8GBqlTp75bczVrr637GMwEADCnx49/RLdufW688N+wGeYYqFSithuil2Wyrp3=
P
>
zcP+ftdpzJrvxKhinpfVvS+4z1bOixqpVsw/DI7I3ISaU9Xdvn3f9HJtH4zcs6Eck3BMbKsoBwe=
p
>
u4SNCMb7YktDOSKHaqnt1kiblMi183lqOTmPqdqunN/UGE3creSodtjW+1Rzq7r56c7dmqvJiel=
m
>
6lZ4SjqDCM1c7dD7ccDzp57ofc8o1yaI058KAOmHc1g3R4RQVaN/I89CIwczzQ7e4UWHeqXqeJq=
4
>
TLlKpV6HLji9RLA1Wg7V77hbscuQb7qB56gVU3CNtJGti/q1wV/GG1lyeld0LW5OLRcAAMAU8fp=
U
>
Iyzzj1G6QVmnR1ecbNdX1HMKdLzovKwinE86BTov39QrgskgdbKiBEGMcm0pjNyzoRyTcExs6yh=
H
>
UG0V74stDeWYo091Or7yUpRzVjPHBXJaDa8vc3hBnR7R4OGQhg8HctWFbuadL6yHdHbSocK5r9/=
X
>
xE29Ytu5GlFdP25auQAA1gnNwOm3NxqNHuvbIbimWqQWj/T1D0ziUBKJ1HPvc/+Wg5nsJmBuhnX=
7
>
QJ16ny65fZUHBLkjip2SeFaLBoU+ndOJfCz348omX7ldEZD9y3GzLJPbvKrSKKBtmu87EVuS+5G=
v
>
oUFZ3/PH/NsPKZfalofDfhZupmanZy169pmn5W3Gv6jcvk+zc938pTXv+lu3bll9qklvn2G9gvU=
K
>
1iurWs/fHQ8ePJC32ar2yzZ9PXv19bfoTtkeVLu/vy/Wv0H37r5M/X5fr40vcqiKlAzsV1VhyYN=
+
>
dIjKQOKHxx3QxKN9c3RVFfshsY1G1gpxHpzUyNrBFh6qaltB45jGge4TtH3FKFe8FyRD1wzVe3d=
f
>
lLddbqgmaZ5t8ofP/6FbB5TDlpZyMBwT27rLYf4gx/HwRC3HrFB99OiRXhtf5ObfsObPzM1DfUt=
x
>
m25jk82sDmW5Y9MYODSfDJUv9cheubRFbdORI3qDApWDM7TYZrkAAFKAA5WDFdInQqjyQB11GcK=
J
>
fk1uNuVmUj3IZ9zEGzroxyDPBfXOAe2e1rxRt5ljKjgtargdm2I/PBq4sPDIJYXLaZ1/2j0VtVq=
9
>
/WnlAgBICQ5W7uqBdIkQqqLWd14X9Txz+je9yP5TolLV7GstUdvf9xok31TngOptFQd16o/bV7m=
m
>
qc5Ndfdz2A7pDzVxyEe4WEOmfGnt+0Cel6q3P7Vc2ykNzTYM5bClpRwMx8SWpvcmDfC+eCL0qbr=
0
>
gCX9l8JNqhHCbkdxKK+yT3UZfbQAkG74dx9fKvpU3QsweP2UvCBQAQDWCf2r6RIhVNXFHzBf6vb=
i
>
EXNpgHLY0lIOhmNiQzlsKIcnRk0VAADSCLXV9Igx+vfEnskFAABSA8GaDhFC9Zqu5EUUelTL6dG=
y
>
E8v2T4+WdosMVsDIPRvKMQnHxIZy2FAOD5p/ExD8Q2P2JQwBAJKE2ur6RQjVoFG//iXuJQm3S/A=
x
>
UafSAACsEoJ1vVBTBYzc80E5JuGY2NJejlUHK94XT/RQlVcr0k2bR2fEY5b4IvQH8edkAwAA2Er=
R
>
QpWvh6svSTjpPp1hWPBaLTJICQC2E5qB1yNCqA7prMEXJ1SzvPTrfBVgJd/sU33QolrtFKN/Nxh=
G
>
7tlQjkk4JrZNKceqghXviydCqKpTapz6ecAlCTNUrtrXTwQAANhVCw9Umnv+VCanWXNPQfGf68q=
T
>
g7v3BV8mUU7hFqlPly+1eBRy8YqA+6xyHUxOeQcAsCHQDLxaEUI1fD7VWPOn+vHAJznlmjr9RE6=
3
>
pgdAsW4lR7XDtj49RU0D5+5fDpASYSf3HUG34p9dxzN5nwjZYotKbX1qTLtErWJ6L26RRH8qRu7=
Z
>
UI5JOCa2TSvHsoMV74snQqh6Tbw8n6oMsl6Nckao2fOpRjO86FiTf2fKVSr1OnTBqSoClyclr99=
x
>
z35V58q605rmm24Qe/27YTj4G9k6BTVSB943fEgDseb2eNe3xV8DehhYywUAAPBEa/7NN2VtcTK=
Y
>
StQ2wm4xXCPu0dW1uHl9RT2nQMeLTisnwvmkU6Dz8k29whB2n9y3WfM2ygUAsKHQDLwaMfpUg66=
s
>
NP+VlDLHBXJaDa8vc3hBHVHxHYgqodtPe6Gbeefr1xzS2UmHCudBtejw++S+D28a6zN081CVa1t=
h
>
5J4N5ZiEY2Lb1HIsK1jxvnj2RDg+1reXatz/Kjj1Pl1yuy8PCCrqHk2nJOq9LRoU+nROJ/Kx3K8=
p
>
a8GiVnmUEyHYtydFl9u8qtIooKrM952ILcn9yMFIDcrq58+6z79N7sNtZHWZDRz2s/CPD3Z61qJ=
n
>
n3la3mb85rv9oWY/gPmhiLL+1q1b4z7VRbaD9QrWK1ivbON68zuDrWq/LA3r2auvv0V3ynbb6/7=
+
>
vlj/Bt27+zI9evRIr40vYqjySNwchY8L4mbgRa//q/ZxVRVBSiJsG1nqX3o1yaBgCw/V8PI69TY=
V
>
OsWQ+8T2b5769m2UK+YL5NA1Q/Xe3Rflbdeig4wWfT4A7KZd/+5YZqhGav5VI3G5JrlEsvnXoSx=
3
>
Zt7IktO7ovm7MTNUvjSbqbk/WF284rKcn3KfiNGJffN5urpcW8r8RbdOKIctLeVgOCa2TS8HB2q=
S
>
zcB4XzwRQrVL92UL7e0ps9XMUUuV54J6p6p0T2veaODMMRWcFjXcDtehGg1cWHjkUgSZm3RILbo=
/
>
Lth98dch3VzBrgEAViXpYAUl8kCl0vgck4Tkm+rcVD0QqTioU3/cvso1TXVuqhyolKvRYdvuTw3=
E
>
fa8LT5iep6Y8N1UPkpLnrO721HYAABBNhD5VHshTpFapHTggCMIts08V/akAkIRd/C5Zc59qnm7=
z
>
vs3TXwAAYCugGThZMfpUe1TL6SbRiSW9l/EDAABYlch9qrC9MHLPhnJMwjGxbVs5Fq2t4n3xRGr=
+
>
DR/16y4YyAMAsMnQDJwM1FQ3EAYpAQCkU0io8ojfiNfb9Z1vCpvHfwmvdUE5bGkpB8MxsW1rOea=
t
>
reJ98USvqcpzQMMm+t5twYO3Zl8XGAAgbdAMvBg0/yYguJ9ZnZ8KALBpEKzzQ6gCRu75oByTcEx=
s
>
KIcN5fAgVDcMBikBwCqgtjofhCoAAARCsMaHUAWM3PNBOSbhmNhQDhvK4UGoAgBAKNRW45kaquP=
p
>
z3jJ1agXdP3forww8HzkOa7utvznug7p7Mjbz1HAuTzDsyM6iHYyLVVCTwcKvy/69lcD/akAsA4=
I
>
1ujWV1Pl816LA6r31ekncm7VozMRpUq3kqPaYVufnqLmVnXzrVtRQZur9dSKGbqVIoVFf9B9cbe=
/
>
6TByz4ZyTMIxsaEcNpTDExKqUa73ay7xr/07vOhQr1QdTzyeKVep1OvQBaeqCNxGy6H6HXerqjz=
u
>
dK75ptpvv+6oFVNwbbORrZM9c54Sdl+c7QMA7ALUVqNJUZ/qDco6Pbq6Fjevr6jnFOhYB+7cRDi=
f
>
dAp0Xr6pVxim3QcAABMQrLOtLVQzxwVyzInPhxfU6RENHg5p+HAgV13oZlhe4ndtDunspEOF8zJ=
N
>
ZvO0+3YPRu7ZUI5JOCY2lMOGcnj2RqPRY317qbip1e2jdOp9uuR2Xx6o5A50ckpUohYNCn06pxP=
5
>
2FJbN/ly/2tOhGD/ctxczOQ2r6o0ctuFDXzfidiS3I8cjNSgrH7+tPtM07bPOOxn4WZkdnrWome=
f
>
eVreZvzmuwOPzH4A80Nhrr9169Z4kFKUx2O9gvUK1itYryy6nr+PHjx4sPL9uhZZz159/S26U7Y=
7
>
/vb398X6N+je3Zfp0aNHem18KwvV2Xi0b46uqiJISYRtI0v9S68myYOHGlkdxlp46KltBY0zcup=
t
>
KnSKIfdF3X40HLpmqN67+6K87YozmjfOYwEAlm2Tv5OWGarp6VOVzb8OZW+I2zey5PSuiLtX55O=
h
>
8qU5kKotasGOHGl8Wc5Puc9XVd0R5i+6dUI5bGkpB8MxsaEcdv8qjodnfaHqm4e1e1rzRgNnjqn=
g
>
tKjhdrjq0cCFhUcuAQAALE9IqKpJyt1BQrOXOSYpzzfVual6G8VBnfrjZlauaapzU+X2czU6bE/=
2
>
eU7gvtctnDAdTb8AkEZmbRWUkD5VDtXwCyZMKlF7jnNVtx3/IOAmZrZInypCFQDSbG/vU/oWB+2=
P
>
9K30WkOf6vIv/gAAAJuPA/XBg3fGixmwuyg9A5UAAAA2XMRQtS9uP7lsXz/mLsHIPRvKMQnHxIZ=
y
>
pFMajkekUFUXt+eLM8CqoT8VANKM+1Bv3frceNmEPtVlihCqXbovRyzdlv2sbU7Wkjd7jAxaJ0t=
8
>
eikAAOwe7kvlMN31QGWR+1RLt4OGIuXpDs/kstCFGmDd/JfwWheUw5aWcjAcExvKYUM5PLEHKt3=
I
>
ihAdPCT3OviZm4f61u4K7meefV1gAADYLpFDtXVfDUWSIdqr0akemdRVbcM7bfIUI7UsCv2pAAC=
b
>
JUKo5um27Di9T2d82cD8bdmP2iqq2lhx4JBTuo3zVDcYRjLaUI5JOCY2lMOGcngi1VTzzT7VBy3=
q
>
qL+o2a+TI2+zAp3POYsLAADANonY/KtmfRnP4pIp06XbzGlMzwYAALDLIoSqurh+BVd32FoYuWd=
D
>
OSbhmNhQDhvK4Yk8UCmUnBnmiNxZ2iAZGKQEALB5poSqO/2bmq3GHZg0seRq1FNPiE/Oqepuy3+=
p
>
Q/vSiEcBqT08O6KDSFVofi1hwR9wn/yh4O0btXQAAIhi8ZoqcwoUe/5wDq7igOp91Tcr51Y9Ohu=
f
>
/6oujehduYnnVnXDrVtRYZerRYvzbiV8GrvJ+0TIyvlbdZ9xv06D4nbXxDFyz4ZyTMIxsaEcNpT=
D
>
MyVU3enf1KUIS27IBC1zDFYaXnSoV6qOJx7PlKtU6nXogsNLBG6j5VD9jjuqWJXFHWScb6r99vl=
q
>
TjNwbbaRrQdetzjovuFZg1pOnca7zhxTwenRFS4ZBQAAMyRTU03EDcq64XV9Rb15ar9+IpxPOgU=
6
>
L9/UKwwh92XKl74fCdd0NXf7NgAA7JIIoWrXEpOSOS6Q02p4zarDC+qI8Bo8HNLw4UCuutDNvPP=
1
>
aw7p7KRDhfOgWvS0+2yy5irqsoGXPl6SVQ9Swsg9G8oxCcfEhnLYUA7P3mg0eqxvT8d9oBODkhy=
q
>
9y/HTbjTcFOr2wfq1PvqnFceqFTUPZoOTy3XokGhT+d0Ih/LTc4yzOW+RQj69iW3eVWlUUDi830=
n
>
Ykvq3FoejNSgrH7+tPsssnzc7xv8GjnsZ+FmanZ61qJnn3la3mb85rvhafYDTFvvwnoF6xWsV7B=
e
>
wXolbD179fW36E7Z7hTc398X69+ge3dfpkePHum18UULVTP8AozDbyE82jdHV1WxLRL7a2SpbzT=
D
>
8uCkRlaHsRYeqmpbQeOYnHqbCp1iyH3e9tWPAIr8oyEIh64Zqvfuvihvu8JqpDidBgBgeZYZqhG=
a
>
f0VANVSgTgxWkpOrErUa3qjducnmX4eyPDHrjSw5C00np64A5ZWVB1txrZqvCpWfcl9ygbpJzF9=
0
>
64Ry2NJSDoZjYkM5bCiHJ0KoqoE6XIubqBDmm2oE7jwBKM9R9c5N7Z7WvNHAcsRtixpuh+tQjQY=
u
>
LDxyKQJRrnUGKmqpAACba32jf2UgD6ioByIVB3Xqj1Oba5rq3FQ5UEmeNxoh5LjvdeIiEvGoqex=
6
>
VMt5g6R4Cbr4BAAAgClCn6rXPznRd+r2tToiEHFh/QkcxtzEzKL2qaKmCgCwXGvuUxW1xqruO/V=
f
>
qlAPXipVEagAAADRmn/zTXm5vsnrF6kBPouP/AUAANh80ftUzTlUx8tujI5dlXU1/WLkng3lmIR=
j
>
YkM5bCiHJyRU+YIImJ0FAAAgjvWN/gUAANgyCFWYuITXuqActrSUg+GY2FAOG8rhQagmwBoRbSx=
x
>
4FQaAIDNNzVUJ06hCV0Wu+DCprMHb3kLAADsFtRUASP3fFCOSTgmNpTDhnJ4pobqxAX0Q5cm4VR=
V
>
AADYdaipAgAAJAShmgLrHqSEkXs2lGMSjokN5bChHB6EKgAAQEJCQjVPzdEKrukr51QNG0HMs+N=
4
>
I4yDpl7jycQPIl32ia8QdUTBs7dN3ie3Oy5X2PMAAABs66up8tynxYG8ID8PdpJzqx6diShVupU=
c
>
1Q7beiCUmlvVzc9uRQVejueji6BbKZKaT2fSxH1ykvJDaruDsNqHVDvxyrWNMHLPhnJMwjGxoRw=
2
>
lMOztlAdXnSoV6qOL8ifKVep1OvQBaeXCNxGy6H6HbeqbNec8003iCfnzfHjWmcjWyd75jwl8D6=
e
>
kccczXwjS07viq71nwAAAGFS1Kd6g7JOj644va6vqOcU6HjRGXBEOJ90CnRevqlXGKbdZ5Dh72R=
F
>
6ZYDV1ICANgeawvVzHGBnFbD668cXlCnRzR4OKThw4FcdaGbeXmJP2POkM5OOlQ4D5pAfdp9Gjd=
P
>
yyZmovq0x20BjNyzoRyTcExsKIcN5fDsjUajx/r2UnFTq9sH6tT7dMntvjxQqah7NJ0SlahFg0K=
f
>
zulEPpYvPiGbfDngciIE+/b8rXKbV1UaBYyo4vtOxJbkfuRgpAZl9fOn3TchZN+Mw34WbqZmp2c=
t
>
evaZp+Vtxm8+11LZgwcP5H+Z+aEw+wewXsF6BesVrFewXomynr36+lt0p2x3Cu7v74v1b9C9uy/=
T
>
o0eP9Nr4Vhaqs/Fo3xxdVUWQkgjbRpb6l14NkQcnNbI6jLXwUFXbChrH5NTbVOgUQ+6zt+8K2nc=
U
>
HLpmqN67+6K87XJDFc2/AACrs8xQTU+fqmz+dSjLnZcLDw7KUPlSj96VS1vUgh050viynJ9yX1B=
o
>
Dkm3Ridqb+9T4v/598z6f9OYv+jWCeWwpaUcDMfEhnLYUA7P+kJVnqPqnZvaPa15o4Ezx1RwWtR=
w
>
O1yHajRwYeGRS7Nx7dc6Z7Z7Kmq1ye6bA/XBg3fGiwpYAADYdOsL1XxTnZuqByIVB3Xqj5txuaa=
p
>
zk2VA5VyNTpsh/R5muTgosWmocuUL61yHchzaSPsGwAAdl6K+lS3T1ifqltTdd269Tl6/PhH+i8=
A
>
AFim3ehT3SEcoByk7oJABQDYDgjVNeEgdRcAANgOCNU1wog5G8phS0s5GI6JDeWwoRwehCoAAEB=
C
>
EKoAAAAJQaiukf/SWeuCcthQjkk4JjaUw4ZyeBCqCZDnswYsAACwWxCqCfAueWgvAACwWxCqa4Q=
R
>
czaUw5aWcjAcExvKYUM5PAhVAACAhCBUAQAAEoJQXSOMmLOhHLa0lIPhmNhQDhvK4UGoAgAAJGS=
9
>
oSrnVHVPQfFP2TaksyPv9JQjd25Vg5z7tBJlorcuVQ6OKGATwrz3AQAA2NYXqjz3qZyrVJ1+Iuc=
w
>
PToTUap0KzmqHbb16SlqblU3P7sVFbS5Wk+tmKFbKVJL3/ab974kYMScDeWwpaUcDMfEhnLYUA7=
P
>
2kJ1eNGhXqk6nvw7U65SqdehC05VEbiNlkP1O+6k5XlqinB15zDPN90gdtSKKbg228jWyZ45T5n=
3
>
PgAAgCAp6lO9QVmnR1fX4ub1FfWcAh3rwJ2bCOeTToHOyzf1CsO89wEAAIRYW6hmjgvktBpef+X=
w
>
gjo9osHDIQ0fDuSqC93My0ukrlPLkM5OOlQ4L9NkNs97X7IwYs6GctjSUg6GY2JDOWwoh2dvNBo=
9
>
1reXiptT3T5Qp96nS2735YFKRd1r6ZSoRC0aFPp0TifysaW2bvIVNcejnAi6/uW4uZjJbV5VaeS=
2
>
Cxv4vhOxJbkfOeCoQVn9/Hnv8+Own8W9XOHpWYuefeZpeZuZb77ZD4D1CtYrWK9gvYL1yiLr2au=
v
>
v0V3ynbn3v7+vlj/Bt27+zI9evRIr41vZaE6G4/2zdFVVQQpibBtZKl/6dUWeXBSI6vDWAsPVbW=
t
>
oHFMTr1NhU5xjvvsfcfFoXrv7ov6LwAAWJdlhmp6+lRl869D2Rvi9o0sOb0r4u7V+WSofOld2J5=
H
>
D5fIkSONL8v5Oe+bP1DDmL+k1gnlsKEck3BMbCiHDeXwrC9U5Tmq3rmp3dOaNxo4c0wFp0UNt8N=
1
>
qEYDFxYeuQQAALA86wvVfFOdm6oHIhUHdeqPm3G5pqnOTZUDlXI1OmwH92tauO914iISAAAAq5G=
i
>
PtXthj5VAIB02JGBStuNQxUAANIBoQoAALAk2zf6FwAAYMOhprpGUS4eAQAA0fHpkPNA8+8W4FC=
d
>
9QGY9Rhsw4Zt2JLYBtuUsmIbNmwjOjT/AgAApAxCFQAAICEIVQAAgIQgVFNu3v4BE7ZhwzZs2IY=
N
>
27Bt0zZWAaEKAACQEITqhkvLrzeUw4ZyTMIxsaEctjR9VheBUAUAAEgIQnWN8AvRhnLY0vTLHcf=
E
>
hnLYUA4PQhUAACAhCFUAAICEIFQBAAASglBdtm5FXo/SXSpdvd4v6uPmFXX7wzM6ivK4ecV+nV2=
q
>
HBzR2VD/mZTI5RjS2ZH3uKOkCzLX+7KE42EYnh3RwbQ3ZtmfVW1mOZb9WdVmlmNsSZ9VbXY5lvx=
Z
>
1eK9L0s4HlHf9xV9Tv0Qqksl/pEVW1Rqj2QH+qhdolaxItb6RX3cvGKUI1ejQ/dx/ToNikn+o4j=
/
>
OruVIiU/vXv0cnQrOaodttXjRm06rOUS/Mc55/vSPqRaLsnPh9KtqC+fXK2n1wSJ/x7GFbkcS/2=
s
>
Ri2HZzmf1ejlWO5nNWo5lv1Zjfq+L/9zGgahukzDhzSgEt3O67/zt8VfA3ro/wBEfdy8Im5/eNa=
g
>
llOnO+7jMsdUcHp0da3/XlTM18m/iBvZunhMwiK/L2fUaDlUHx+QPDXFP9Cm++eiYn0+HMre0H8=
n
>
/fnQ8k31BdSvO3pNgJjv4TyilGPpn1Uh0vHQlvZZFaK9L0v+rArRPx/L+6xGft9X8DkNg1Bdpus=
r
>
6jlZcj9fJG5lgz4AUR83r4jbz5QvaXRZpoz+WzyRrqL9SI8mzusUXxInnQKdl2/qFQmK9b4U6Ng=
7
>
IMmKWo5MmaqlHnUu1DeC/GIpVam8rHJNE+c9XKKlf1bjWOZnNaplf1ajWvJnNfL7vsbPKUJ1iYY=
P
>
B0SHN40PQIZuHhINfD+Xoj5uXvNuX/6DMH/tLSh6OYZ0dtKhwrn5jyc5sd4X4UI3e/GSZHNanPe=
F
>
awnVq5xqfruq0ijJKkgM836Wli3pz2p0y/2sRrXsz2ocq/yshr3v6/ycIlQhWLdCuRpRvd+kVX9=
P
>
Dc9OqFM4X09NzK9Xo6vbqtlrGf120agBKPfdcty+L76wVtM/tBHwWVV27bO6xvd9GoTqEmXUTyP=
x
>
MXMNSf2Asv8FRn3cvOJuX47uKw7Eh/Uy0S+LaOUY0kWnJ74f1C/dgwMe/NGjWi650Yyx3her/8Z=
u
>
2lpU5PeleyoHoIx/8Oeb1C61qLH6b8zYn6VlW9ZnNZrlf1ajWvZnNbIVfVZnve/r/JwiVJfpRpa=
c
>
3hV5zfjc/m904ruiPm5eMbbPH1b1628JX1KRypGh8qX+lSuXNpXIEeUZ0WVSBZr7fUlYxHLIpiz=
r
>
C2KNYnyWlm2pn9VIVvBZjWrZn9WIVvFZjfS+r/FzilBdpsxNOhS/Xe+7bR/d++KvQ5r4sRT1cfO=
K
>
uv1xc8qSvqSW/Tqjivy+8MhC41f2UI2wLCQ1GiRiOTLHBfEF0aFxpSPpcsSRlvdw2Z/VTbPsz2p=
E
>
S/+sRn3f1/g5RaguVZ6a8vwoPXhAnjel2//Fh+1o3Ncw5XGJiFaO7n0+y041X6nmLLUk15QV9Xg=
s
>
W9RycE1Ene8nHyf+NR+2k/wSj1iOTJku5fl++nGJl2OGlX5Wp1jpZ3WKlX5Wp1jpZ3WKFX5Wp77=
v
>
Kfmc7o1Go8f6NgAAwE7a39+nV19/g+7dfZkePXqk18aHmioAAEBCEKoAAAAJQagCAAAkBKEKAAC=
Q
>
EIQqAABAQhCqAAAACUGoAgAAJAShCgAAkBCEKixJlyrm1U7ikldHUc+fPYXVgvuaKrlty4uA622=
F
>
Lkdn67/Gb+CxX+YxjqBbsY/TOssSyn+MVnDMYv07gVVAqMIWyFNTX9Q8+QuZL2PbJWrrbXoLX4x=
d
>
6NUol4ZgnbDMYzxdl+cILfLl6dTF6s3jJWeISeXxYus7ZrA+CFWAVFDXKpVEsJ6i1qGIGqrMUxm=
o
>
5jVkObC8HyInqaqxwi5DqMIKqQmM3aY7/zJuvuImrVyNevpPeVFseWfI8ysVXzNbxP1IXhOdtYw=
f
>
FNKEF9QcuWiNiaer0jctgU2f/gu6h7wOsUw0C04re+ixj3EcrLLFeS/8xHMbMlFF5b4acFH2PN1=
2
>
f4d0LrxjH+l4CfOW3S30xPN5PlWT/5gl8LkUy/hxoe+VFvU4QKIQqrA+pbZqytM1tFbxiOR3D89=
0
>
0a+PA6bUFo8Zz3rskev5+c3bek2IsP3ILy79Reg+xq39tIr2F5RBTZCsvj5VGfpU58Iu2nR7faW=
/
>
IL15Hyf3NSL1MlpUPJj2OkbUl4UyX2+Eskc89ixa2XxC34sAwwvq6MQo3Q4uQ76p9ju6LBNnbtQ=
y
>
zVN293F8PLzne03S+iVFF+tzGfB+Tnmv5npvIBEIVVgP/rJwv6zzt1WQiUjpjCdinEE8P+S73jZ=
t
>
P8OHNJB/i4eNv7S9frDgMOnSaU1HX72vy5Ch8rn+cpu76VZ8keovQa9W5u3LfL35pg5C8Tpqcmf=
B
>
Zc6Uq77jmmTZg7YVVDbDou/5TFHLNF/Z3cfZzz8f16DzTf2DLIqpxyLq+xnGK9/0zw0sA0IVdpe=
c
>
yFhR8y5GaBqTkx0z38TLXGvQX4TG92AIri34m+VUzcSsbXj7EuutmlqGjgvy21Fs6v7sMrsSKbs=
W
>
tq15y5aEqGVatOzjH2P+56dE0p8biAWhCjtM1Qi8Zjsz7JbZ9+Qb/Ws04bWKwfsdT7asl5xbEzH=
I
>
Jj/jMZN9fJCIcTP9ciXxfkb53ECyEKqw88b9cryME1YE7KpO1bD6xlrUmOjwMk8l8S9N8dNADYB=
R
>
X5hmYMdojkyjzDF5FavgnzjydBsOjFW9VyuR1Ps563MDy4BQBTDlm+MBIdS7omt1yxPWF7joSfh=
G
>
gIxHsob2OxqjSDlMuqekKiD8JTrlyzLJsk8p24U3umjBL+4Mlas6RlqNgME1Xbqvq25O4ZgyUcu=
0
>
aNlDn5+QqO9nmCmvz/rc6LWQLIQqpN7g4ZL++RunHHhhYg7yCPpizdMdHbp84QH1PPFldaJPbXD=
q
>
dGeuJDECpNch9V0YtC+xt7MT/aUrilgtU2Z8Ko75JcpfoP7mwvhlDz/2wWXrVnJeIMx3IGziR45=
q
>
POhRLWeOWjVGyIpyn8vRQlHLtGjZzeefTI7YXVTk99PmvVfBr2/ic6NuQsIQqpBOmTKNM0Z8MSz=
l
>
l7X4wvZOZ9C/4PUXI48KNUdemjLlS9/z9Jex+HLv61M75mLUMGon6vXKfemmYbeMqlmQazF6YJH=
R
>
fCyPlXwdbkDYIpU94rGf3NaBvlADN1maF2pYjGyel/vhYFX7sd4n45hHLdOiZefnqxYNt0wJBSq=
L
>
8X7yY4PeK/n6Zn1uYCn2RqPRY30bAABgJ+3v79Orr79B9+6+TI8ePdJrlUqlQs1mU//lCVqPmio=
A
>
AMAMHKAm/98uhCoAAEAEbpCGBSpDqAIAAExhNvGagRrUJIxQBQAAmMEfoEGByhCqAAAAEbhBGha=
o
>
DKEKAAAQ0bRAZQhVAACAhCBUAQAAEoJQBQAASAhCFQAAICF7/7LexGUKAQAAEoBr/wIAACQEzb8=
A
>
AAAJQagCAAAkBKEKAACQEIQqAABAQhCqAAAACUGoAgAAJAShCgAAYPirv/orfSs+hCoAAEBCcPE=
H
>
AADYSH/8x3+sbyXjV37lV+R/uab6cz/3c/J2XAhVAADYSByqn/nMZ/Rfk9pv/y/00U8+pI8++kg=
u
>
H3/8CZ38xpv6XtsPfvCDREIVzb8AALB1/u9/8z/Tf/vPivSrJ1+mUvnL4r//hP5J6b+m/+3r/1Q=
/
>
YjkQqgAAsFX+r7f+JxGo/5g++UTUTj/6kD75+Cf0k7//j3J5/vl/SK9Wi/qRyUOoAgDAVvnJT0S=
I
>
ymbfn9DzX25Q4R//JhX/u2/Sj//uP9Lf/+j/o+//v3+jH5k8hCoAAGyVjz76mD7+mJdP6Kc//Sn=
9
>
4R/+IT3z6Z+hD0Wo/vjvHsn+1WVBqAIAwFb5Z5V/TV+t/C79D+Vv0R/8wR/Qb9b+Gyr96j+iD3/=
8
>
NzJUP/nkE/3I5CFUAQBg67z11lv0e7/3e/R//KtfpRde+Bz95MO/pQ9/9Lf0td8c0DvvvKMflTy=
E
>
KgAAbKXf/de/Tr/6T5+ljz/8O/r4x/+JKv/re/T9739f37scCFUAANhKP/MzIuL2iB4/fkwff/x=
T
>
vXa5EKoAALCl9uijD/9WLh+LZRUQqgAAsJX++5ebdOfrPfofv/Hv6Z//1gf0J3/yJ/qe5UGoAgD=
A
>
Vvo3//uv0+v/4r+g11/+z+lfnfwDunXrlr4nWX/2Z38mF4ZQBQCArcTnqX74o7+hH//ob+nDv/9=
P
>
eu1yIVQBAGArfSRC9ccffkI/+ein9NEne2rg0hL80i/9klwYQhUAALbSr7/yLfrGt/4Dvfq7P6b=
G
>
//mf0Xe/+119z+LMJl80/wIAwE5ot9v0ne98h7rdrl6zXAhVAACAmMwmX/M2JikHAICNxJOUJ2n=
W
>
JOVuEy8HaNhthCoAAIABoQoAAJAC6FMFAABIyN4H7RdRUwUAAFgY0f8Pv2raZV7mqO4AAAAASUV=
O
> RK5CYII=3D
> --001a113d6a0a1ede02053654edd6--
>
>



-=3D This is automatically added to each message by the mailing script =3D-=
E-mail to subscribers: CHEMISTRY/a\ccl.n= et or use:
=C2=A0 =C2=A0 =C2=A0 http://www.ccl.net/cgi-bin/ccl/s= end_ccl_message

E-mail to administrators: CHEM= ISTRY-REQUEST/a\ccl.net or use
=C2=A0 =C2=A0 =C2=A0 http://www.ccl.net/cgi-bin/ccl/s= end_ccl_message

Subscribe/Unsubscribe:
=C2=A0 =C2=A0 =C2=A0 http://www.ccl.net/chemistry/sub_un= sub.shtml

Before posting, check wait time at: http://www.ccl.net

Job: http://www.ccl.net/jobs
Conferences: http://server.ccl.net/chemist= ry/announcements/conferences/

Search Messages: http://www.ccl.net/chemistry/sear= chccl/index.shtml
=C2=A0 =C2=A0 =C2=A0 http://www.ccl.net/spammers.txt

RTFI: http://www.ccl.net/chemistry/aboutccl/instr= uctions/





--
A GENTLE WORD, A KIND LOOK, A GOOD-NATURED SM= ILE CAN WORK WONDERS AND ACCOMPLISH
=C2=A0 =C2=A0 =C2=A0 =C2=A0 =C2=A0 =C2=A0 =C2=A0--------------------= -------
=C2=A0 =C2=A0 =C2=A0 =C2=A0 =C2=A0 =C2=A0 =C2=A0 =C2= =A0=C2=A0Venkata Pera Reddy B.
<= span style=3D"font-family:courier new,monospace">=C2=A0 =C2=A0 =C2=A0=C2=A0 =C2=A0 =C2=A0= =C2=A0 =C2=A0 =C2=A0Research scholar
= =C2=A0 =C2=A0 =C2=A0 =C2=A0 =C2=A0 =C2=A0 =C2= =A0 =C2=A0 Dept. of Chemistry
=C2=A0 = =C2=A0 =C2=A0 =C2=A0 =C2=A0 =C2=A0 =C2=A0 =C2=A0 National Institute of Tech= nology
= =C2=A0 = =C2=A0 =C2=A0 =C2=A0 =C2=A0 =C2=A0 =C2=A0 =C2=A0 Durgapur-= 713209,W.B, India
<= /div>
--001a113deff4117613053659b409-- From owner-chemistry@ccl.net Tue Jun 28 17:04:00 2016 From: "Tandon Swetanshu tandons-,-tcd.ie" To: CCL Subject: CCL: Coupling constant (Jab) - Why more unpaired electrons means a smaller coupling? Message-Id: <-52258-160628155323-8859-6sf86EDJXnJ6JI0ARq/now{=}server.ccl.net> X-Original-From: Tandon Swetanshu Content-Type: multipart/alternative; boundary=94eb2c12483cfdaf8605365bfc6f Date: Tue, 28 Jun 2016 20:53:17 +0100 MIME-Version: 1.0 Sent to CCL by: Tandon Swetanshu [tandons::tcd.ie] --94eb2c12483cfdaf8605365bfc6f Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: quoted-printable Hi Henrique, Thanks a lot for the insight. I have a small doubt. Before obtaining the susceptibility curve, we need to obtain the coupling constant. So can't we just compare the calculated coupling constants with the experimental ones? Thanks again, Swetanshu. On 26 June 2016 at 22:05, Henrique C. S. Junior henriquecsj(~)gmail.com < owner-chemistry=-=ccl.net> wrote: > Hi, Swetanshu, > It is not an easy task to decide what configuration is correct to describ= e > the magnetic couplings in a polynuclear system. The best approach is to > compare the various solutions with an experimental magnetic susceptibilit= y > curve using a statistical fit software (like origin). > > > > ---------- > *Henrique C. S. Junior* > Qu=C3=ADmico Industrial - UFRRJ > Mestrando em Qu=C3=ADmica Inorg=C3=A2nica - UFRRJ > Centro de Processamento de Dados - PMP > > > ------------------------------ > From: owner-chemistry=C3=8Cl.net > To: henriquecsjgmail.com > Subject: CCL: Coupling constant (Jab) - Why more unpaired electrons means > a smaller coupling? > Date: Fri, 24 Jun 2016 11:45:36 +0100 > > Hi All, > > I have a question somewhat related to this topic. When working out the J > values in a system with more than 3 metal atoms, there are many different > solutions. Each solutions is obtained by choosing a different set of > equations. From the above discussion it seems to me that the large > differeence in the solutions are due to the large number of unpaired > electrons and the reduction in the spacing between levels at higher energ= y. > Due to this, depending upon the states under consideration the J values > obtained would differ (please correct me if I am wrong). But how does one > decide as to which set of solution is appropriate. > > Thanks, > Swetanshu. > > On 12 June 2016 at 00:27, James Buchwald buchwja/rpi.edu < > owner-chemistry,ccl.net> wrote: > > Hi Henrique, > > The diminishing Jab that you're predicting assumes that (E[HS] - E[BS]) > does not grow as quickly as the spin term in the denominator. Depending = on > the system, this is not necessarily the case, and the energy spacing can > grow faster. > > The reason that the equations appear to cause this is that the > Heisenberg-Dirac-van Vleck Hamiltonian (which the three equations were > derived from) has a "spin ladder" of solutions ranging from the low-spin = to > the high-spin states. If your low-spin state is a singlet, you'll also > have triplets, pentets, and so on until you reach the high-spin state. > Similarly, if you start from a doublet, you'll have intermediate quartets= , > etc. > > As you introduce more and more unpaired electrons, the spin of the > high-spin state increases - but all of the intermediate states between th= e > high-spin and low-spin limits still exist. You can work out the splittin= g > between these individual states in terms of J, and what ends up happening > is that the states spread out. The denominator essentially corrects for > that spacing, rather than saying anything about the strength of the > magnetic coupling. > > Best, > James > > On 06/11/2016 05:54 PM, Henrique C. S. Junior henriquecsj-x-gmail.com > wrote: > > I hope this is not a "homework" question, but I'm having a bad time tryin= g > to figure this out. > Available literature proposes 3 equations to calculate the coupling > constant during a Broken-Symmetry approach: > > J(1) =3D -(E[HS]-E[BS])/Smax**2 > J(2) =3D -(E[HS]-E[BS])/(Smax*(Smax+1)) > J(3) =3D -(E[HS]-E[BS])/(HS-BS) > > I'm intrigued by the fact that, from the equations, the more the system > have unpaired electrons, the minor will be Jab. Why does this happen? > Doesn't more unpaired electrons increase magnetic momenta (and an increas= e > in magnetic coupling)? > > -- > *Henrique C. S. Junior* > Qu=C3=ADmico Industrial - UFRRJ > Mestrando em Qu=C3=ADmica Inorg=C3=A2nica - UFRRJ > Centro de Processamento de Dados - PMP > > > -- > James R. Buchwald > Doctoral Candidate, Theoretical Chemistry > Dinolfo Laboratory > Dept. of Chemistry and Chemical Biology > Rensselaer Polytechnic Institutehttp://www.rpi.edu/~buchwj > > > --94eb2c12483cfdaf8605365bfc6f Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable
Hi Henrique,

Thanks a lot for = the insight. I have a small doubt. Before obtaining the susceptibility curv= e, we need to obtain the coupling constant. So can't we just compare th= e calculated coupling constants with the experimental ones?

T= hanks again,
Swetanshu.

On 26 June 2016 at 22:05, Henrique C. S. Junior he= nriquecsj(~)gmail.com &l= t;owner-chemis= try=-=ccl.net> wrote:
Hi, S= wetanshu,
It is not an easy task to d= ecide what configuration is correct to describe the magnetic couplings in a= polynuclear system. The best approach is to compare the various solutions = with an experimental magnetic susceptibility curve using a statistical fit = software (like origin).



-= ---------
Henri= que C. S. Junior
Qu=C3=ADmico Industrial - UFRRJ
Mestrando em Qu=C3=ADmica Inorg=C3= =A2nica - UFRRJ
Centro de Processamento de Dados - PMP



= > From: owner-chemistry=C3=8Cl.net
To: henriquecsjgmail.com
Subject: CCL: Coupling c= onstant (Jab) - Why more unpaired electrons means a smaller coupling?
Da= te: Fri, 24 Jun 2016 11:45:36 +0100

Hi All,
I have a question somewhat related to this topic. When working = out the J values in a system with more than 3 metal atoms, there are many d= ifferent solutions.=C2=A0 Each solutions is obtained by choosing a differen= t set of equations. From the above discussion it seems to me that the large= differeence in the solutions are due to the large number of unpaired elect= rons and the reduction in the spacing between levels at higher energy. Due = to this, depending upon the states under consideration the J values obtaine= d would differ (please correct me if I am wrong). But how does one decide a= s to which set of solution is appropriate.

Th= anks,
Swetanshu.

On 12 June 2016 at 00:27, Jam= es Buchwald buchwja/rpi.edu <owner-chemistry,ccl.net> wrote:
=20 =20 =20
Hi Henrique,

The diminishing Jab that you're predicting assumes that (E[HS] - E[BS]) does not grow as quickly as the spin term in the denominator.=C2=A0 Depending on the system, this is not necessarily the case, and the energy spacing can grow faster.

The reason that the equations appear to cause this is that the Heisenberg-Dirac-van Vleck Hamiltonian (which the three equations were derived from) has a "spin ladder" of solutions ranging f= rom the low-spin to the high-spin states.=C2=A0 If your low-spin state is a singlet, you'll also have triplets, pentets, and so on until you reach the high-spin state.=C2=A0 Similarly, if you start from a doublet= , you'll have intermediate quartets, etc.

As you introduce more and more unpaired electrons, the spin of the high-spin state increases - but all of the intermediate states between the high-spin and low-spin limits still exist.=C2=A0 You can wo= rk out the splitting between these individual states in terms of J, and what ends up happening is that the states spread out.=C2=A0 The denominator essentially corrects for that spacing, rather than saying anything about the strength of the magnetic coupling.

Best,
James

On 06/11/2016 05:54 PM, Henrique C. S. Junior h= enriquecsj-x-gmail.com wrote:
I hope this is not a "homework" question, but I'm= having a bad time trying to figure this out.
Available literature proposes 3 equations to calculate the coupling constant during a Broken-Symmetry approach:

J(1) =3D -(E[HS]-E[BS])/Smax**2
J(2) =3D -(E[HS]-E[BS])/(Smax*(Smax+1))
J(3) =3D -(E[HS]-E[BS])/(<S**2>HS-<S**2>BS)

I'm intrigued by the fact that, from the equations, the more the system have unpaired electrons, the minor will be Jab. Why does this happen? Doesn't more unpaired electrons increase magnetic momenta (and an increase in magnetic coupling)?

--
<= font face=3D"monospace, monospace">Henrique C. S= . Junior
Qu=C3=ADmico Industrial - UFRRJ
<= font face=3D"monospace, monospace">Mestrando em Qu=C3=ADmica Inorg=C3=A2nica - UFRRJ
Centro de Processamento de Dados - PMP

--=20
James R. Buchwald
Doctoral Candidate, Theoretical Chemistry
Dinolfo Laboratory
Dept. of Chemistry and Chemical Biology
Rensselaer Polytechnic Institute
http://www.rpi.edu=
/~buchwj


--94eb2c12483cfdaf8605365bfc6f-- From owner-chemistry@ccl.net Tue Jun 28 17:39:00 2016 From: "Dr. Robert Molt r.molt.chemical.physics(a)gmail.com" To: CCL Subject: CCL: correct transition state or not Message-Id: <-52259-160628160404-9500-IjGPtZdnRh5hn9Pq31LHhA(~)server.ccl.net> X-Original-From: "Dr. Robert Molt" Content-Type: multipart/alternative; boundary="------------1EAAEFE951C29BA91A07A9DF" Date: Tue, 28 Jun 2016 21:03:51 +0100 MIME-Version: 1.0 Sent to CCL by: "Dr. Robert Molt" [r.molt.chemical.physics . gmail.com] This is a multi-part message in MIME format. --------------1EAAEFE951C29BA91A07A9DF Content-Type: text/plain; charset=utf-8; format=flowed Content-Transfer-Encoding: 7bit Constraints on the structure to ''keep it on course'' during the TS search can be very helpful. Constraint the critical distance/angle during the search, take that result, re-optimize without constraint. Calculating force constants frequently can help On 28/06/2016 18:09, teja reddy reddyteja80]=[gmail.com wrote: > thank you Dear Dr. Tobias Kraemer , > I have tried both forward and reverse and optimized the last point > geometry on IRC, in each case it is optimized as product intermediate. > can any one suggest regarding this Correct transition state > characterization. > > On 28 June 2016 at 20:31, Tobias Kraemer t.kraemer~!~hw.ac.uk > > wrote: > > > Sent to CCL by: "Tobias Kraemer" [t.kraemer:_:hw.ac.uk > ] > Dear Teja, > > > At first glance this looks like a reasonable IRC, quite flat > around the TS > (not sure what the outlier means). A reasonable thing to do next is to > optimize the last point of the IRC (1.8 on the X-coordinate) and > see where > this leads you. Of course you should also run the IRC job for the > other > direction (reverse or forward, whichever way you look at this) and > do the > same thing here, optimize the last point on the trajectory. > Inspection of > these optimized structures help you to confirm if the TS is > reasonable and > the one you were looking for. I often look the at the animation of the > imaginary mode itself, this tells me already if this TS > corresponds to the > desired reaction coordinate. You can also do a quick version of > the above > protocol, displace the TS geometry by a small increment in both > directions > of the TS along the imaginary mode (use GaussView to do this), and > optimize > these new (initial) geometries to their nearest minima. In the > end, it is a > combination of visual inspection of the TS as well as the ground state > geometries which will reveal if this is the right TS for the reaction. > > Hope this helps > > > Tobi > > > > Dr. Tobias Kraemer MRSC > Research Associate > Institute of Chemical Sciences > School of Engineering & Physical Sciences > Heriot-Watt University > Edinburgh EH14 4AS > United Kingdom > email: t.kraemer a hw.ac.uk > phone: +44 (0)131 451 3259 > > > "teja reddy reddyteja80%gmail.com " wrote: > > > > Sent to CCL by: teja reddy [reddyteja80~~gmail.com > ] > > --001a113d6a0a1ede02053654edd6 > > Content-Type: multipart/alternative; > boundary=001a113d6a0a1eddff053654edd5 > > > > --001a113d6a0a1eddff053654edd5 > > Content-Type: text/plain; charset=UTF-8 > > Content-Transfer-Encoding: quoted-printable > > > > Dear friends, =E2=80=8BI have optimized TBP transition state > which is > showi= > > ng > > -216cm-1 negative frequency but is showing only 9 points on the curve > like > > shown below. can anyone help me is it a correct transition state > > [image: Inline images 1] > > > > --001a113d6a0a1eddff053654edd5 > > Content-Type: text/html; charset=UTF-8 > > Content-Transfer-Encoding: quoted-printable > > > >
style=3D"color:rgb(0,0,0)">De= > > ar friends, =E2=80=8BI have optimized TBP transition state which is > showing= > > -216cm-1 negative frequency but is showing only 9 points on the curve > like= > > shown below. can anyone help me is it a correct transition > state
> > class=3D"gmail_default" style=3D"color:rgb(0,0,0)"> width=3D"469" > heig= > > ht=3D"434" alt=3D"Inline images 1" > src=3D"cid:ii_15596c33e3e5b53d"> > <= > > i>
clear=3D"all"> >
> >
smartmail=3D"gmail_signatur= > > e">
dir=3D"ltr">
d= > > ir=3D"ltr">
new,monospace"> > > nt color=3D"#000000">
style=3D"font- > fa= > > mily:courier new,monospace"> color=3D"#000000">=C2=A0=C2=A0=C2= > > > =A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 > = > > >
> >
> > > > --001a113d6a0a1eddff053654edd5-- > > --001a113d6a0a1ede02053654edd6 > > Content-Type: image/png; name="image.png" > > Content-Disposition: inline; filename="image.png" > > Content-Transfer-Encoding: base64 > > Content-ID: > > X-Attachment-Id: ii_15596c33e3e5b53d > > > > > iVBORw0KGgoAAAANSUhEUgAAAdUAAAGyCAYAAACySF4VAAAAAXNSR0IArs4c6QAAAARnQU1BAAC > x > > > jwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAEqjSURBVHhe7d1fjCvXfSf4Xwf75HnoBhYIECB > Y > > > KLw3Itx6URi7MMLuyFcO2G377guxIgbjxU64mpXTlDdXnIEZXGr3ruHRrKiE2R2qF1a3o4lA5CG > 7 > > > Czog8nCd6SZiXwVeDEA5DLAD0WjlNqOHAAECzA5vJnEsS/Ld8zvnFOucYhVZRRbJIvn9GGWxi2T > V > > > YZGXX54/VWfvsUAAAACwsJ/R/wUAAIAFIVQBAAASglAFAABISGif6t7enr41HbpkAQAAlKmhOis > w > > > 3eBFsAIAAPhCNax2GhaaMnj5v2JBsAIAwK6b6FPlaDQX9ujRI/nfs7Mz+sY3viH/63JjOGpzMQA > A > > > bC7+ro+ypA2X6U//9E/1X5P4viTKHWug0l//9V/TX/7lX8r/Mq6dustMH7xNz3/60/Rpd3n+bfp > A > > > 3yV97xWx/hX6nv7T9j16hZ/zSvC9H7z9vHju8/S2ucEp2/veK5+m560HC/x4c/tTyzMLl9d9ri6 > 7 > > > sUy+jA/o7eeNx/iPjeTfjvl6+T7f6wcAWBLzuz9oSaMf/OAH9Mx/+V8FBiuv4/v4MYuKFao/+7M > / > > > Sz//8z8v/xsLB+oXv0Nf+qMf0g9/qJY3n3xIf6HuVIHSJSrIv8M8RU+9/82A4Pge/U7jPX2bzd7 > e > > > c/kCvfdQ7d31vW6HCvnnxK2o5YnjKaq6r/3NAnVeMsJa/tj4Ij38qndsfvjbRN8NTHNvO39UJWp > 8 > > > LSh8p0H4AsBu+uVf/mX6d//P9yeC1Q1Uvo8fs6hYofrlL3/Z+m80IqS+1qAn3/w2vfCEXiU899p > r > > > xBFG9AS98G0RFK/l5V/TPPkk0Xe+60uE73WpUygYARhhe79wk57qdL1gE7e6nQLJTI1Rnrk8lxd > l > > > fZ/+Qr4M99j8kF5TB0N54gV6wfw7wBMvfJUK732H/IcDAACC+YM16UBlE6HKLcrmsrAPvkvfec8 > N > > > rBi4+dXXDHrzK1+lJxu/Y4ShCKVvvk/Vr0QIQHN7T3yevvRUh7ruhmQw53XILxnv66kv0ef5B8a > 8 > > > x2YWX1O7am7mWupL1KH3qPFFsT6kKR0AYJuZwZp0oDIrVP1t4qPRSC6u3//937f+G9lTN+kX9E3 > V > > > /8lf9vM0Qz5H+YIRhhxKpAMqlifo8196it5X1UWj6XdZdJDx6+7m6YfffkGUQDOOTRwfvP1NL5w > t > > > Ijy/qGq/sin5j6r0/kt8rJ+j1374pqgl6yZkq2oMAOtgDuyZtsDmmNr8u7+/P16Yf6BSZO+5/af > c > > > bPlt8WXPX+4zPPeaHT7ac18RIfFNVeP83u+I8Pjq5GMC+bb3xOe/xG3JYjsf0F+8/xTdjJNsVk0 > w > > > ymAmHWQi4OxmZ8E4NrN54fzFxpP0ZsDxoQ/+gt4XR3f8G+GJF+irhffI14UMAClgVmSmLZAcs8n > X > > > bApOSuQ+1evra2ugEv8dyRO/QE+O+xATwE23on763e+9Td98v0pfmbfCNd7OHLVdEVTfdgcV/dD > t > > > G45APO+3q+/TN90qur8ZeiZjwFOc/QIAwEQfqr+PNQkzQ9U9N/Xy8pKOjo7o61//uvwv/+0/ZzX > Y > > > cyQql6KGFfP0lIA+VeUJeuGrT1LjpQbRlz4frZbKJrbHTcCiXHG3syAeYPRk42u66ZtfC48G9p1 > m > > > I2rCb8c6WAb5I8ZsIhc/PsaDsAAAdlPYoKSkg3VmqJpNvjdu3JDr+L9xmoJlk++bRC+Nm0xfove > r > > > v22NBo7lua9Q9akCfXXuDSjcBPyU+N+X4nfKLkD/yHBPh+Fmadnv6R4bsXyN6PNzh+Bz9Jq5PXk > q > > > k1ur5T5pDFQCgMUE9fuaSxp95jOfmQhUlxus/JhF7T0OabDnA8N3cU2Ug5ObfMvlsr5X1WDN9e7 > j > > > AQAAdtXMUI0KoQoAALtuaqjGhVAFAIBdFhqqAAAAEE/kU2oAAABgOoQqAABAQhCqAAAACUGoAgA > A > > > JAShCgAAkBCEKgAAQEIQqgAAAAnZG41GOE8VAAAgAaipAgAAJAShCgAAkBCEKgAAQEIQqgAAAAk > R > > > odqlysEBHYyXIzob6nvlfebfAAAAEEbXVB2q90c0Go2oXyeqnZxRvBxF+AIAAEw0/2bKVSr1OnS > B > > > gAQAAIglXp/q8IyOjKbiSpdXci21SC3qUS0n1suVQzo78j8OAABgu02E6vCsQS2nQMcZvWJMhGe > u > > > Rodt1Uw86tdpUOQm3zw1R20quU3Izbx46CnVDtvqcWLhVQAAANtOh6quZYpaZa52SO3LMk1k6vA > h > > > DUR03nYDMlOmaqlHV9f6b9ONLDmtIh2hkxUAAHbIxECl0ahJC1csReBeim2d0wmafwEAYGdE71P > N > > > 3KRDatF9NyCHZ9RoGTXXAJnyJfXrDg0eosYKAADbL8ZApTw1ZT+qHoCU61Ch79Zq83S7ZAxU6lb > G > > > g5S4OblanmhMBgAA2DqYpQYAACAhMWqqAAAAMA1CFQAAICEIVQAAgIQgVAEAABKCUAUAAEgIQhU > A > > > ACAhCFUAAICEIFQBAAASglAFAABICEIVAAAgIQhVAACAhCBUAQAAErL3L+tNXFAfAAAgAQhVAAA > A > > > 7d7dl+nRo0f6r/j2Hgv6NgAAwM569fU3Fg9VzKcKAAC7bn9/P5FQxUAlAACAhCBUAQAAEoJQBQA > A > > > SAhCFQAAIKJKpaJvBUOoAgAAROAG6rRgRagCAADM4A/SsGBFqAIAAExhBmiz2dS3goMVoQoAABC > B > > > G6hmsPohVGHNulQ5OKCDqEulq5+3WsM387oMeXpzqFeG6VbsMs9Y1vSSNkasY58yQWX31k1f8tN > e > > > bNhnLP8mbdgh2hj+IA0LVoQqAEAKvftKLiBY9Y/QYkv/7fPuK5QT908NZIgtLECD1iNUYc3y1By > N > > > aGQs/dc+q+/7LL3Wt+8bNfP6vni6FffXfEV8La3OZ1/r2+UPWOZ8SbAFSu2Az0T/NfHJV9595dT > 4 > > > vA7pzXyRvDgtUdt8Xruk1/Pzfm3javXbAqEKAJAmmZfoW+Mflu/Rn7vh2D2lV97Vtz/7GvVHTfG > T > > > 1JBvGoH8Lr1yin6FdUCowkbzaqD24vVTquYyr7WsRUV+jPuAFPVNzexrC+l8DT4Gk/2PYcfK2y7 > X > > > hALuHy+qlm9ux1+kafdNSODYz37/lfmObbTjsSrd++6H+LP02rdeooz+yyICuevWXNEEshYIVdh > Q > > > /rC0tYriS2/Gt7r8op3WN5W2QR+tou81TTsGoqaSi9O3xtvKeTWhKfJ3vObJ1n27PN73/mt0Z8p > 3 > > > +uLHfvH33xJ4bKMdj8QN36RfG+/4KfpFmZ5D+vP35ApxbAv0hcBEhTRAqMJG6laMviXZFKZ/nRv > 9 > > > UfxFWemqPluvu0n3QzWJTsdfXGbfVJ/GLW/vdujfLpiqPNgkuJajlynhMe6PtV7TffF1r1jHoNT > W > > > 5eelLV6REt63ZrxmUaMJ3ZbRTzeW+QIVvFQdl0dUpcbb+GzhC8E1Kam78LGP/v7r2z5zH9ug47E > A > > > Gf7+z0TuFfGTSCm13Sbea3p/nLO/OOXYQhKur6/nXhCqsIHsGlG/azSFcfOX8cVn16RM5gAps28 > q > > > Q18YJ8a79P61vrliPICl+5J+VeI1/cb4Jbl9bL5jYDX1iddm9K11JtKJB4CZr3nKtvJN4weJyzx > G > > > LXIPsdk8WZhalVr02C/2/i90bAOPR/Lc0EcL7uZBqMLmGf65+PrTgn6152+Pa2r03p9HakY0awq > 5 > > > BNv8Zo7+NQMhDvMY6NMozNdg1nbenfXLYNbxDJD5QmFcw1PBZQRR6TfIzazp5jz2ib7/AeY4HvO > y > > > R/96NXVu4bBr2TfoSfeAz/OaYGUQqrCz1CAXo5lvWy3jS9jfBGw0/ZZuz65e7cyxjyVDL3W9pvt > W > > > 0RwIlaFffErfTKBbApYHoQqbJ/OL5H6/BAaG8QUfWtMYvkm/NX6Qfb6fd55sipnHwOpPDVhm1YZ > n > > > Hc9AdhNwcTxiqEQzM3XRY5/E+z/NXMcjKXm6Mz4GLfoto0M8f9uN23fplV8L6YsXxzbv1vzjDNS > C > > > xCBUYQPlyft+8Y0U5S8VY0joZK1J95tdvz9uHhUPsvoXvUE0aWYcg4mRq3wYvFNIZo8A9h3P8bb > U > > > KSVhI2zNJuAx61iGWPjYL/L+RzHf8UiKeVzf7fxb77Xl7xgDubjJ33dKD792c5DTXK8dFoVQhY2 > U > > > b3rNZOoLRv86N75UuAY3OdBDnWpy8FvveYHAoeQ+P+EmyZmjf3mZs0ZhHQPrNZh9kyX6jQgdnOZ > p > > > Mt62ZpxSYg3yUSJ9kZt9nnMe+/nf/2jmOh5JMZvWraZeu3lYFEydcx3w2rkvH4Oc1gOhChvKf6q > M > > > TQ4AMb5VrC9JqUDfMk492UzqGIQ1mapBUr6r7oThUbNzHA+vSZJFaPqVuNyLHvt4739scx6PZNi > j > > > oO0rI+mR06FDkFVz+nh0M6zc3mg0eqxvAwD4cJOnW0PjL2x/SPMIXl3D5L7dra8ezToesKn29/f > p > > > 1dffoHt3X6Z+v6/XxoeaKgBMYVx0IEjMUb+bb8bxgJ2HUAXYeeY1bs1rBvN6o59zYhCSqKW6o3Y > + > > > O/2yhJtl3uMBgFAFAB4AMx5xpAdyyUAxB+Z8ll4bp6Z70QYvYKZflnDTxD0eAB6EKgAQX37Pug6 > u > > > iS/VN+qGXyWp1N6+gTGLHA/YaRioBAAAOw8DlQAAAFIGoQoAAJAQhCoAAEBCEKoAAAAJQagCAAA > k > > > BKN/V+T0bHzKOAAArNmdsn395KRG/643VLsVOhjPo+S/juaQzo5yVOupv5x6ny7L9olhw7Mjyl1 > V > > > I1xvlE9Wb1C2f0nuJuRz3Y2TQ3XjPs/k8+bFoXrv7ov6L+Wdd96lz30u+GLoq4Ry2FCOSTgmNpT > D > > > tmnlePX1t5YWqutr/h2e0VFxIMJMT05cH1Dx6ExEqdKtiEA9dCdfbtNhLUfuDFndirrCiReK03U > r > > > vimlRJjnaofe5MjtQ6qdePt2TTwPAABgirWF6vCiQ71SdVwDzJSrVOp16IKTTQRuoyVqj+PLgKn > p > > > jtwKab7pBrGjVkzBNdJGtm5P4cRXSzFrxTey5PSu6Fr/yQKfBwAAMEWKBirdoKzToytOtusr6jk > F > > > Ol6wyZXD+aRToPPyTb0imAx4JytKoEV83qLS0FzCUA4byjEJx8SGcthQDs/aQjVzXCCn1aAzt81 > 1 > > > eEGdHtHg4ZCGDwdy1YVu5uXFbfqNbkhnJx0qnJfDL/TNTdCyGZmoPn5chOcBAAAEWNlAJXNg0Hj > Q > > > kTlQySlRiVo0KPTpnE7kY3n2ftnky+GXE0HnGzA0baAS33citqQGN80YcGRs//gi+vM47GfhZmr > G > > > A5WefeZpeZuZv6i4c92F9QrWK1ivYL2C9coi69kyByql6JQaNdr3qiqClETYNrLUv/Rqizw4qZG > 1 > > > RwCHh6o9ctgUNIqYqe23qdApxnreNBy6Zqhi9O90KIctLeVgOCY2lMO2aeXYztG/frL516Esd2w > G > > > DByKJ0PlSz2yVy5tUQvm02ZGIcE4JNXifCPm8wAAADzrC1Vu+j2okNtV2j2teaOBM8dUcFrUcDt > c > > > h2o0cGHhkUsK13DNfYudi9ppctsHAIDdtL5QzTfVual6IFJxUKf+uBmXa5rq3FQ5UClXo8N2hAs > w > > > yIFHRliGyJQvrX0fyPNlF7/AQ1xpaC5hKIcN5ZiEY2JDOWwohweXKVyiWX2qAACwervRpwoAALD > h > > > EKprxCPV0gDlsKEck3BMbCiHDeXwIFQBAAASglAFAABICEJ1jTBizoZy2NJSDoZjYkM5bCiHB6E > K > > > AACQEIRqAuS5rgHLTHv/QC0AALAVEKoJ8C5raC+hdJi+8+AB0eO/W3u4YuSeDeWYhGNiQzlsKIc > H > > > obpqHJ4iSPfoMd269Tna2/uUClY3XAEAYGMhVNeAg/TBg3fGiwzWlOMyugsAAARDqK6SrqWGWlN > t > > > ddaIuVX9CMAIQltaysFwTGwohw3l8CBUYS57Ivx5AQAAD0J1lXRN9PHjH8n+VHfhv6VZNdkUeSz > K > > > yYsbrtMWAIBdsd5QlXOquqeg+KdsG9LZkXd6ypE7t6pBzotamTXRG+tS5eCIzE2oOVXd7Zv32fu > d > > > vD8ZKkj3vEBdo1kj5kJ/BAhuuE5bgoLWvzCMILSlpRwMx8SGcthQDs/6QpXnPpXzmKrTT+T8pkd > n > > > ItKUbiVHtcO2Pj1Fza3q5me3osIuV+upFTN0K0Vq6duSCPNc7ZDa7ukv7UOqnXj7JnLG5VJLgnO > t > > > ipCRNVIdJJL7N9+XWuoHwDw/AoKC1r9wsN66dWsibM0lLgyuAoBVW1uoDi861CtVx2GVKVep1Ov > Q > > > BSebCNxGSwTbHXfS8jw1Rbi5c5jnmyrs+nVHrZiCa6SNbJ2smfPyTfH8ptiqdiNLTu+KrvWfRId > 0 > > > c5kTlosQ4UVOZMthof/eZRysDx48mAhbcwkKWv/iWtXgKgAAU4r6VG9Q1unRFSfb9RX1nAIdLxp > s > > > IpxPOgU6L9/UK4LJgHeyogTsmq6iVYAXtsf/J8Ji3TZl5F5Q0PoXf7jOAyMZJ+GY2FAOG8rhWVu > o > > > Zo4L5LQaXl/l8II6IswGD4c0fDiQqy50My8vkbpOLUM6O+lQ4bxModnMTdCyGZmobj1uQA2jXzX > + > > > vmFd3HANYtZozQUAICl7o9FItkIuGzfDun2gTr1Pl9zuywOVirq30ylRiVo0KPTpnE7kY0tt3eT > L > > > 4ZcTAdm3+zblNq+qNHLbhQ1834nYktyPHKjUoKzv+WPm9sm3r5B9Mw7cWbiZmp2etejZZ56Wtxn > / > > > ouIvdA4As3Pd/KWVlvWbUk6Xu54HVbm4Lzjs8UHBuomvl2G9gvUK1ivmevbq62/RnbLVKUj7+/t > i > > > /Rt07+7L1O/39dr4Vhaqs/Go2xxdVUWQkgjbRpb6l17tkQcnNbI6jLXwUFXbChrHNA50n6Dtu6b > d > > > Nw2Hrhmq9+6+KG+73LBaN/7w+T90plWVc1Y5VoXLwYOmgqzy/UrL8WBpem9QDg/KYYtajmWGanr > 6 > > > VGXzr0NZ7ticGDgUV4bKl+bo3baoBasRvcHBOCTd4gwgcXgGLfwDw78AALjWF6ryHFXv3NTuac0 > b > > > DZw5poLToobb4TpUo4ELC49cUriGa50X2z0VtVq1/cn7KlRMcN+w2aIGLS8AsHvWF6r5pjo3VQ8 > G > > > Kg7q1B8343JNU52bKgcL5Wp02A7pDzXJgUf+i0hMypQvrX0fyPNl1fan3bet0tBswza1HEFBy0v > c > > > oPWfV5uW48HwGbGhHDaUw5OiPtXtsyl9qtNsQhk3SXiwPpbn07r8V64CgOTsRp8qwA4wa7LmAgD > b > > > AaEKcsRcGqAcNrfJOLx2uzp4b2wohw3l8EQLVdlXqfsYA5fkLzgPsEu4qdc/aYF52cY0BSwAhAs > P > > > VTNITzp6ZbjOCQIWYBEcpO7iZzYVmwGLkAVIl5BQ7VLFCtICnY/P+QxazsUjPJ2T2SNwIT3CRsz > x > > > FzZ/ia8KRhDawsphBqw/ZJcF740N5bChHJ4pzb9GkBpXNgpmXmzBDlgAWK6wgF1myAJAsJBQzVN > z > > > ZpCG4YA1plXbAXb/srcArJoZsP6QBYDlizZQCaaym8K9ZVNg5J5tm8qRVMDivbGhHDaUwxM9VM2 > B > > > S0dnxGOR+ELzB5gXbSvxFy9/EcP2CAvYeUIWAIJFC1W+Tm+uRsFzd9+nMwz3BdgoZsD6QxYA5hc > h > > > VId01uA5T9UsL/26o1YL+Waf6oMW1WqnGO27wTByz7aL5QgLWDdk8d7YUA4byuGJEKrXdCWqqE7 > 9 > > > POCi8hkqV+3rJwLAZjMD1h+yfv5JAAB23cIDlYaYiBRgq4UFLAcpTwLgLghWgEiheoOyDlGvliP > / > > > mCSeezRX42psVjxqDnJOVfcUFP8FI4Z0duTed0BHAf22cu7TSAOlulTxXelJzZvqbt9/FajZ+94 > m > > > /hFz/IXJX6CrhhGEtrSUg7llMQN2HfDe2FAOWxrKESFUvSbeVvFAhWivRjkRNvK2UKrOcU4rjya > W > > > c5Wq00/kHKZ6VDHrVnJUO2zr01PU3KpufspRx8b+Z+lWisS9wmMizHO1Q2q7p7+0D6l2Em3fAAA > A > > > YaI1/+abMlwme09LMpjGc4vHMLzoUK9UHffTZspVKvU6dMHJJgK30XKofsfdcJ6axn7yTTeIvUF > T > > > YbhG2sjW7bLL12NcoOJGlpzeFV3z7Rn7BgAlaBIAt2kYYFfF6FNV4aJqb+6S5JWTuJm5R1ecbNd > X > > > 1HMKdDzfJZ08IiBPOgU6L9/UK4LJgHebsJPa9wbByD0byjEprCz+SQDcpuFlhSveGxvKYUtDORY > e > > > qDSvzHGBnFbD68scXlCnRzR4OBwPfrrQzby8xG9+HdLZSYcK51OaprkJWjYjE9X145LZ9+ZaV38 > q > > > bJdlhytAWu2JGudjfXs6DiD3AhBOnfqXZboWwVOkNo0itI2OBzUJTr1Pl9zuywOVirq30ylRiVo > 0 > > > KPTpnE7kY0tt3ewq9y0Csn9pndYjt3lVDdw/33citiT3IwcqNSjre/6Ysf3jC1XOWftmHLizcI2 > e > > > nZ616Nlnnpa3Gf+icgPM7Fw3f2mtYz2XiefxdK1qvwzrlW1c7war+9la1X4Z1itY73n19bfoTtn > u > > > 0Nzf3xfr36B7d1+mfr+v18YXLVTN8GNWqJaonr1D5cC0ioNH3OboqirCjMT+Glm5D3erPDipkdV > h > > > rIWHqtpW0DimcaD7jLd/8zTSvqPg0DVD9d7dF+Vtlxuq68YfPvdDt84ymeVYJ5RjUlJlccN13s8 > Y > > > 3hsbymGLWo5lhmqE5l8RUKu4opJs/nUoyx2b5sChuZhT0fHCg6xU+YODcUjj020X3jcAhOEw5YX > D > > > 1Q1YgG0SIVSXdEUleY6qd25q97TmjQbOHFPBaVHD7XAdqhG5hYRGD3EN1zovtnsqarV6+0veNwA > g > > > XGF7LTxQae4rKuWb6txUPRioOKhTf9yMyzVNdX6oHCyUq9FhO6Q/1MT9nxMXkZiUKV9a+z6Q58u > 6 > > > 259z3xvMbS7hL7d5m+WSkIbmI4ZyTFpWWeKGK94bG8phS0M5IoTq8q6oxOE2bqKdmBTdPoUnYCy > S > > > er55R6ZMl4Gn+fC27GC09u27L8q+ASA5qLnCtogQqku6ohIAgA/CFTZdtObfJVxRCdKDR8ylAcp > h > > > S0s52KrLEhaueG9sKIctDeWI0ae67CsqAQDYUHOFTRMhVPnCCds/U8uu4y8s/vICSCM3XG/duoV > w > > > hVSLUVOFbYWRezaUY1JaypKWmis+IzaUwxMhVN3Rvye+OUcBANYjLeEK4BchVNXFH0SsUi2nz+u > c > > > WGafG7rNgo/J7OsCA8BiEK6QNmj+TYA9eMtbNgV/GfEX07phBKEtLeVgaT8mqw5XfEZsKIcnQqg > G > > > jfr1LxgFDADrh5orrFuEUFWjf3dpTlEA2GxB4bq396nxArAsizf/yuvtHmEQEywMIwhtaSkH29R > j > > > 4oXrp+jBg3fGy6LBis+IDeXwTAlVVUM9OCgST/zGlygMGozDF5xXFysEAADYbckMVHIKhJnRNhM > 3 > > > jfEveQAAWNyUUHUHKKlr/pba/sFJxjIxw0xEck5Vt9brPy1nSGdHXo046IpOcl7USJ29XOu2m6j > V > > > nKru9o37rDIZy9GZKNF2wsg9G8oxadOPyePHP6Jbtz43XsTPSXXHnPAZsaEcnmRqqvPgvlg5j6k > K > > > Zjm/qRFc3UqOaodtHdxqflM3P7sVFXTuLDmzdCuqCXtMBGeudignA5Dbbx9S7UTvW04eoNeP759 > z > > > InYASA0OVm9Rg5gAkhY5VAcPk62nDS861CtVx/OYZspVKvU6dMG7EYHbaDlUv+OeqKNqze5sOPm > m > > > Crt+3VErpuAaaSNbt2fYkcFpnAZ0I0tO74qu9Z9+3fstcgrHmN4OYIsgWGEZ1ldTncCXQ+zRFSf > b > > > 9RX1kuinFeF80inQefmmXhFMBnzYROsy4EtUtWcx3wpufypG7tlQjknbekzmDVZ8RmwohydCqC7 > n > > > 2r+Z4wI5rYa3zeEFdXqqRjx8OJCrLnQzLy/xz5Md0tlJhwrnU/p7RWAeyWZkonrI47qnfOcdXNw > C > > > YEuhxgpJ2huNRo/17RA8yMfXJzmBJyufflUlboZ1+0Cdep8uuebHg4KKestOSWylRYNCn87pRD6 > W > > > B0fJJl8Ov5wIyP7luLmYyW1eVWkUMEs633citiT3I19Dg7K+54+FbD90vcZhPws3U7PTsxY9+8z > T > > > 8jbjX1RuTdHsXDd/aS17Pe//wYMH8vYq94v1CtYraVm/7n+PWK8sez179fW36E7ZHiuzv78v1r9 > B > > > 9+6+TP1+X6+Nb2WhOhuP9s3RVVUEKYmwbWSpb4wq5sFJjawOYy08VNW2gsYxjQPdJ2j7vK5I7cD > Q > > > joJD1wzVe3dflLdd7j/idTG/RPwfunVAOWxpKQfbhWMS598jPiO2TSvHMkM1QvPviq79K5t/Hcp > y > > > x+aMgUOzZah8aZaPTwty5EjjoEDlENYtzoYu3bcGSwHANuNA5WAFWMT6BirJ80G9c1O573I8Gjh > z > > > TAWnRQ23w3WoRgMXErrCBNdwrfNiu6eiVmtvf3jWoNYWX9Ri3bVkgDRCsMKiIoaqfSGGyWWO+VT > z > > > TXVuqt5GcVCn/riZlWua6txUuf1cjQ7bIf2hJjnwaHZZMuVLa98H8nxZc/tdOuU+3eqcF7XYMGl > o > > > tmEohy0t5WC7dEyiBCs+IzaUwxOhT5Urldy3WKJSqxXSt5pEn+r24cDm5meWtj5V1FQBpsO/ke2 > 1 > > > 5j5V7lvk/96Wfavy4kIl70pHslhh53gCAGwoNAXDPCL3qZZuB9VD83SHr2q00KAiWDX/L3AeMZc > G > > > KIctLeVgu3pMwoIVnxEbyuGJPVDpBl8JYvCQ3Gs2ZG4e6lsAANsHNVaII3Kotu6r4T8yRHs1OtW > j > > > gfi6uAAA2wzBClFFCNU83ZYdp/fpjE9xyd+W/ajupOXFgUNO6TYGKW0wjNyzoRyTcEzsYMXxsKE > c > > > nkg11XyzT/VBizrqL2r26+TND1Og8zmvOAQAsElQY4VZIjb/qisUja9GlCnTpXu1onknKN8i8lz > X > > > gCWN+AuBvxgAYD4IVpgm9kAlmKROL5pcNgVG7tlQjkk4JjaeiCINwYr3xZaGcoSEKl9EP7j2Fbz > M > > > cUUlAIANhhorBEFNFQBgTghW8AsJ1YCZadSllKjtXy8XXKJwk2Hkng3lmIRjYjPLsc5gxftiS0M > 5 > > > UFPdIfwPH4OUAACWB6EKALAgNAODa72hKudUDRvsZE83d+TOrWqQ86JWogyR4oFXR2RuQs2p6m7 > f > > > vk9NIRdy3xbCyD0byjEJx8QWVI51BCveF1sayrG+UOXgkvOYqn5ZOb/p0dn4msLdSo5qh95sODy > 3 > > > qpufPBUdB16u1lMrZuhWivaUdSLMc7VDr3+4fUi1E3ffIoDl/K3GfTmMbgaA2VBjhbWF6vCiQ71 > S > > > dTwxeKZcpVKvQxecbCJwGy2H6nfc4U9q4JR74aZ8UwVen2fImYFrpI1sXU1R58o3xfONwVU3suS > 4 > > > M+0MH9KAHMq6c9nJyzIO6OGG11bRnwqwGgjW3ZaiPtUblHV6dMXJdn1FPadAx4teqkmE80mnQOf > l > > > m3pFMBnw7pywmTJVSz3qyHTnTTSoZYT/NsLIPRvKMQnHxDarHKsKVrwvtjSUIyRUAy7+UOQG1BY > V > > > /evlEr95NHNcIKfV8PorhxfU6fGsckNRWRzIVRe6mZeXSF2nliGdnXSocD7lMoq67zRXI6obj+O > a > > > cPUqJ/ebu6rSCNc2BoCYUGPdTXuj0eixvm3gUPX1Q07F569OP1eVm2HdPlCn3lfXEeaBSjKseWV > J > > > bKVFg0KfzulEPrbU1k2+HH45EZD9S6vGKLcZEnp834nYkrpeMb+eBmV9zx+zts8DpHJ0VdX7lmW > k > > > wNfHoTsLN1Oz07MWPfvM0/I2419UbpOs2blu/tJKcv2tW7fkpdWWtX0X1itYr2A9yX97ZtfLqvb > L > > > sF4x17NXX3+L7pStTkHa398X69+ge3dfpn6/r9fGFxKq62CEGYkga2Spb1ysnwcnNbI6jLXwUFX > b > > > ChrHNA50n/H2b57Swf3b1jaD9h0Fh64Zqvfuvihvu1bZzzltX/zh83/o1gHlsKWlHAzHxBa3HMv > 6 > > > t473xRa1HMsM1fT0qcrmXz1AyBw4NBc1qw4HmlraohbsyJHGwcE4JN3irJqeBw/1SODtsMrwBoB > J > > > /O+P/x3C9gvvUzVOb4mHa4kR+ljlOare47qnNW80cOaYCk6LGm6H61CNBi4sPHJJ4Rqu1Q/cPRW > 1 > > > WrV92dfrjkJmCe8bAHYTgnU3TKmpdujkQA8UijBKyD139ODgRE9mPkO+qc5N1fsoDurUHze5ck1 > T > > > nZsqtynPGw3pDzXJgUezAz1TvrT2fSDPl9Xb57li5bmp+r6o+95gaWi2YSiHLS3lYDgmtnnLkXS > w > > > 4n2xpaEc4X2qcvCOqD3y7VKJSq3W1IFLpXabqMiDm7iZdbtDKCoO5TT0qaL5FyBd8G9yvdbTp8o > 1 > > > NrdP8jafTDOLO7MNAjVN8I8XIH2SrrFCekQbqCSvQOQO+gleAs5qgQ3BI+bSAOWwpaUcDMfElkQ > 5 > > > kghWvC+2NJQjPaN/AQB2DGqs2wehCgAAkBCEKmDkng/KMQnHxJZkORapreJ9saWhHAjVLYZBSgC > b > > > Ac3A2yNCqKqL68e/oP3ukOezBiwAAFEhWLdD5Jpqq+iGRfwZabZd0GhoXjYFRu7ZUI5JOCa2ZZU > j > > > brDifbGloRxzNP8a07/NfSlDAAAI4gbr3t6nxgtsjgih6l7UQSxt+woU1KtRTgfs0XhiVAAAWMx > j > > > evDgnfGCYN0c8Wqq5kUgfAHbc6/Ti87XVIgzSAkj92woxyQcExvKYUM5PPFCVc4so5t+3cnF/Vp > F > > > BCsAAOykCKGqRv8GBqlTp75bczVrr637GMwEADCnx49/RLdufW688N+wGeYYqFSithuil2Wyrp3 > P > > > zcP+ftdpzJrvxKhinpfVvS+4z1bOixqpVsw/DI7I3ISaU9Xdvn3f9HJtH4zcs6Eck3BMbKsoBwe > p > > > u4SNCMb7YktDOSKHaqnt1kiblMi183lqOTmPqdqunN/UGE3creSodtjW+1Rzq7r56c7dmqvJiel > m > > > 6lZ4SjqDCM1c7dD7ccDzp57ofc8o1yaI058KAOmHc1g3R4RQVaN/I89CIwczzQ7e4UWHeqXqeJq > 4 > > > TLlKpV6HLji9RLA1Wg7V77hbscuQb7qB56gVU3CNtJGti/q1wV/GG1lyeld0LW5OLRcAAMAU8fp > U > > > Iyzzj1G6QVmnR1ecbNdX1HMKdLzovKwinE86BTov39QrgskgdbKiBEGMcm0pjNyzoRyTcExs6yh > H > > > UG0V74stDeWYo091Or7yUpRzVjPHBXJaDa8vc3hBnR7R4OGQhg8HctWFbuadL6yHdHbSocK5r9/ > X > > > xE29Ytu5GlFdP25auQAA1gnNwOm3NxqNHuvbIbimWqQWj/T1D0ziUBKJ1HPvc/+Wg5nsJmBuhnX > 7 > > > QJ16ny65fZUHBLkjip2SeFaLBoU+ndOJfCz348omX7ldEZD9y3GzLJPbvKrSKKBtmu87EVuS+5G > v > > > oUFZ3/PH/NsPKZfalofDfhZupmanZy169pmn5W3Gv6jcvk+zc938pTXv+lu3bll9qklvn2G9gvU > K > > > 1iurWs/fHQ8ePJC32ar2yzZ9PXv19bfoTtkeVLu/vy/Wv0H37r5M/X5fr40vcqiKlAzsV1VhyYN > + > > > dIjKQOKHxx3QxKN9c3RVFfshsY1G1gpxHpzUyNrBFh6qaltB45jGge4TtH3FKFe8FyRD1wzVe3d > f > > > lLddbqgmaZ5t8ofP/6FbB5TDlpZyMBwT27rLYf4gx/HwRC3HrFB99OiRXhtf5ObfsObPzM1DfUt > x > > > m25jk82sDmW5Y9MYODSfDJUv9cheubRFbdORI3qDApWDM7TYZrkAAFKAA5WDFdInQqjyQB11GcK > J > > > fk1uNuVmUj3IZ9zEGzroxyDPBfXOAe2e1rxRt5ljKjgtargdm2I/PBq4sPDIJYXLaZ1/2j0VtVq > 9 > > > /WnlAgBICQ5W7uqBdIkQqqLWd14X9Txz+je9yP5TolLV7GstUdvf9xok31TngOptFQd16o/bV7m > m > > > qc5Ndfdz2A7pDzVxyEe4WEOmfGnt+0Cel6q3P7Vc2ykNzTYM5bClpRwMx8SWpvcmDfC+eCL0qbr > 0 > > > gCX9l8JNqhHCbkdxKK+yT3UZfbQAkG74dx9fKvpU3QsweP2UvCBQAQDWCf2r6RIhVNXFHzBf6vb > i > > > EXNpgHLY0lIOhmNiQzlsKIcnRk0VAADSCLXV9Igx+vfEnskFAABSA8GaDhFC9Zqu5EUUelTL6dG > y > > > E8v2T4+WdosMVsDIPRvKMQnHxIZy2FAOD5p/ExD8Q2P2JQwBAJKE2ur6RQjVoFG//iXuJQm3S/A > x > > > UafSAACsEoJ1vVBTBYzc80E5JuGY2NJejlUHK94XT/RQlVcr0k2bR2fEY5b4IvQH8edkAwAA2Er > R > > > QpWvh6svSTjpPp1hWPBaLTJICQC2E5qB1yNCqA7prMEXJ1SzvPTrfBVgJd/sU33QolrtFKN/Nxh > G > > > 7tlQjkk4JrZNKceqghXviydCqKpTapz6ecAlCTNUrtrXTwQAANhVCw9Umnv+VCanWXNPQfGf68q > T > > > g7v3BV8mUU7hFqlPly+1eBRy8YqA+6xyHUxOeQcAsCHQDLxaEUI1fD7VWPOn+vHAJznlmjr9RE6 > 3 > > > pgdAsW4lR7XDtj49RU0D5+5fDpASYSf3HUG34p9dxzN5nwjZYotKbX1qTLtErWJ6L26RRH8qRu7 > Z > > > UI5JOCa2TSvHsoMV74snQqh6Tbw8n6oMsl6Nckao2fOpRjO86FiTf2fKVSr1OnTBqSoClyclr99 > x > > > z35V58q605rmm24Qe/27YTj4G9k6BTVSB943fEgDseb2eNe3xV8DehhYywUAAPBEa/7NN2VtcTK > Y > > > StQ2wm4xXCPu0dW1uHl9RT2nQMeLTisnwvmkU6Dz8k29whB2n9y3WfM2ygUAsKHQDLwaMfpUg66 > s > > > NP+VlDLHBXJaDa8vc3hBHVHxHYgqodtPe6Gbeefr1xzS2UmHCudBtejw++S+D28a6zN081CVa1t > h > > > 5J4N5ZiEY2Lb1HIsK1jxvnj2RDg+1reXatz/Kjj1Pl1yuy8PCCrqHk2nJOq9LRoU+nROJ/Kx3K8 > p > > > a8GiVnmUEyHYtydFl9u8qtIooKrM952ILcn9yMFIDcrq58+6z79N7sNtZHWZDRz2s/CPD3Z61qJ > n > > > n3la3mb85rv9oWY/gPmhiLL+1q1b4z7VRbaD9QrWK1ivbON68zuDrWq/LA3r2auvv0V3ynbb6/7 > + > > > vlj/Bt27+zI9evRIr40vYqjySNwchY8L4mbgRa//q/ZxVRVBSiJsG1nqX3o1yaBgCw/V8PI69TY > V > > > OsWQ+8T2b5769m2UK+YL5NA1Q/Xe3Rflbdeig4wWfT4A7KZd/+5YZqhGav5VI3G5JrlEsvnXoSx > 3 > > > Zt7IktO7ovm7MTNUvjSbqbk/WF284rKcn3KfiNGJffN5urpcW8r8RbdOKIctLeVgOCa2TS8HB2q > S > > > zcB4XzwRQrVL92UL7e0ps9XMUUuV54J6p6p0T2veaODMMRWcFjXcDtehGg1cWHjkUgSZm3RILbo > / > > > Lth98dch3VzBrgEAViXpYAUl8kCl0vgck4Tkm+rcVD0QqTioU3/cvso1TXVuqhyolKvRYdvuTw3 > E > > > fa8LT5iep6Y8N1UPkpLnrO721HYAABBNhD5VHshTpFapHTggCMIts08V/akAkIRd/C5Zc59qnm7 > z > > > vs3TXwAAYCugGThZMfpUe1TL6SbRiSW9l/EDAABYlch9qrC9MHLPhnJMwjGxbVs5Fq2t4n3xRGr > + > > > DR/16y4YyAMAsMnQDJwM1FQ3EAYpAQCkU0io8ojfiNfb9Z1vCpvHfwmvdUE5bGkpB8MxsW1rOea > t > > > reJ98USvqcpzQMMm+t5twYO3Zl8XGAAgbdAMvBg0/yYguJ9ZnZ8KALBpEKzzQ6gCRu75oByTcEx > s > > > KIcN5fAgVDcMBikBwCqgtjofhCoAAARCsMaHUAWM3PNBOSbhmNhQDhvK4UGoAgBAKNRW45kaquP > p > > > z3jJ1agXdP3forww8HzkOa7utvznug7p7Mjbz1HAuTzDsyM6iHYyLVVCTwcKvy/69lcD/akAsA4 > I > > > 1ujWV1Pl816LA6r31ekncm7VozMRpUq3kqPaYVufnqLmVnXzrVtRQZur9dSKGbqVIoVFf9B9cbe > / > > > 6TByz4ZyTMIxsaEcNpTDExKqUa73ay7xr/07vOhQr1QdTzyeKVep1OvQBaeqCNxGy6H6HXerqjz > u > > > dK75ptpvv+6oFVNwbbORrZM9c54Sdl+c7QMA7ALUVqNJUZ/qDco6Pbq6Fjevr6jnFOhYB+7cRDi > f > > > dAp0Xr6pVxim3QcAABMQrLOtLVQzxwVyzInPhxfU6RENHg5p+HAgV13oZlhe4ndtDunspEOF8zJ > N > > > ZvO0+3YPRu7ZUI5JOCY2lMOGcnj2RqPRY317qbip1e2jdOp9uuR2Xx6o5A50ckpUohYNCn06pxP > 5 > > > 2FJbN/ly/2tOhGD/ctxczOQ2r6o0ctuFDXzfidiS3I8cjNSgrH7+tPtM07bPOOxn4WZkdnrWome > f > > > eVreZvzmuwOPzH4A80Nhrr9169Z4kFKUx2O9gvUK1itYryy6nr+PHjx4sPL9uhZZz159/S26U7Y > 7 > > > /vb398X6N+je3Zfp0aNHem18KwvV2Xi0b46uqiJISYRtI0v9S68myYOHGlkdxlp46KltBY0zcup > t > > > KnSKIfdF3X40HLpmqN67+6K87YozmjfOYwEAlm2Tv5OWGarp6VOVzb8OZW+I2zey5PSuiLtX55O > h > > > 8qU5kKotasGOHGl8Wc5Puc9XVd0R5i+6dUI5bGkpB8MxsaEcdv8qjodnfaHqm4e1e1rzRgNnjqn > g > > > tKjhdrjq0cCFhUcuAQAALE9IqKpJyt1BQrOXOSYpzzfVual6G8VBnfrjZlauaapzU+X2czU6bE/ > 2 > > > eU7gvtctnDAdTb8AkEZmbRWUkD5VDtXwCyZMKlF7jnNVtx3/IOAmZrZInypCFQDSbG/vU/oWB+2 > P > > > 9K30WkOf6vIv/gAAAJuPA/XBg3fGixmwuyg9A5UAAAA2XMRQtS9uP7lsXz/mLsHIPRvKMQnHxIZ > y > > > pFMajkekUFUXt+eLM8CqoT8VANKM+1Bv3frceNmEPtVlihCqXbovRyzdlv2sbU7Wkjd7jAxaJ0t > 8 > > > eikAAOwe7kvlMN31QGWR+1RLt4OGIuXpDs/kstCFGmDd/JfwWheUw5aWcjAcExvKYUM5PLEHKt3 > I > > > ihAdPCT3OviZm4f61u4K7meefV1gAADYLpFDtXVfDUWSIdqr0akemdRVbcM7bfIUI7UsCv2pAAC > b > > > JUKo5um27Di9T2d82cD8bdmP2iqq2lhx4JBTuo3zVDcYRjLaUI5JOCY2lMOGcngi1VTzzT7VBy3 > q > > > qL+o2a+TI2+zAp3POYsLAADANonY/KtmfRnP4pIp06XbzGlMzwYAALDLIoSqurh+BVd32FoYuWd > D > > > OSbhmNhQDhvK4Yk8UCmUnBnmiNxZ2iAZGKQEALB5poSqO/2bmq3GHZg0seRq1FNPiE/Oqepuy3+ > p > > > Q/vSiEcBqT08O6KDSFVofi1hwR9wn/yh4O0btXQAAIhi8ZoqcwoUe/5wDq7igOp91Tcr51Y9Ohu > f > > > /6oujehduYnnVnXDrVtRYZerRYvzbiV8GrvJ+0TIyvlbdZ9xv06D4nbXxDFyz4ZyTMIxsaEcNpT > D > > > MyVU3enf1KUIS27IBC1zDFYaXnSoV6qOJx7PlKtU6nXogsNLBG6j5VD9jjuqWJXFHWScb6r99vl > q > > > TjNwbbaRrQdetzjovuFZg1pOnca7zhxTwenRFS4ZBQAAMyRTU03EDcq64XV9Rb15ar9+IpxPOgU > 6 > > > L9/UKwwh92XKl74fCdd0NXf7NgAA7JIIoWrXEpOSOS6Q02p4zarDC+qI8Bo8HNLw4UCuutDNvPP > 1 > > > aw7p7KRDhfOgWvS0+2yy5irqsoGXPl6SVQ9Swsg9G8oxCcfEhnLYUA7P3mg0eqxvT8d9oBODkhy > q > > > 9y/HTbjTcFOr2wfq1PvqnFceqFTUPZoOTy3XokGhT+d0Ih/LTc4yzOW+RQj69iW3eVWlUUDi830 > n > > > Ykvq3FoejNSgrH7+tPsssnzc7xv8GjnsZ+FmanZ61qJnn3la3mb85rvhafYDTFvvwnoF6xWsV7B > e > > > wXolbD179fW36E7Z7hTc398X69+ge3dfpkePHum18UULVTP8AozDbyE82jdHV1WxLRL7a2SpbzT > D > > > 8uCkRlaHsRYeqmpbQeOYnHqbCp1iyH3e9tWPAIr8oyEIh64Zqvfuvihvu8JqpDidBgBgeZYZqhG > a > > > f0VANVSgTgxWkpOrErUa3qjducnmX4eyPDHrjSw5C00np64A5ZWVB1txrZqvCpWfcl9ygbpJzF9 > 0 > > > 64Ry2NJSDoZjYkM5bCiHJ0KoqoE6XIubqBDmm2oE7jwBKM9R9c5N7Z7WvNHAcsRtixpuh+tQjQY > u > > > LDxyKQJRrnUGKmqpAACba32jf2UgD6ioByIVB3Xqj1Oba5rq3FQ5UEmeNxoh5LjvdeIiEvGoqex > 6 > > > VMt5g6R4Cbr4BAAAgClCn6rXPznRd+r2tToiEHFh/QkcxtzEzKL2qaKmCgCwXGvuUxW1xqruO/V > f > > > qlAPXipVEagAAADRmn/zTXm5vsnrF6kBPouP/AUAANh80ftUzTlUx8tujI5dlXU1/WLkng3lmIR > j > > > YkM5bCiHJyRU+YIImJ0FAAAgjvWN/gUAANgyCFWYuITXuqActrSUg+GY2FAOG8rhQagmwBoRbSx > x > > > 4FQaAIDNNzVUJ06hCV0Wu+DCprMHb3kLAADsFtRUASP3fFCOSTgmNpTDhnJ4pobqxAX0Q5cm4VR > V > > > AADYdaipAgAAJAShmgLrHqSEkXs2lGMSjokN5bChHB6EKgAAQEJCQjVPzdEKrukr51QNG0HMs+N > 4 > > > I4yDpl7jycQPIl32ia8QdUTBs7dN3ie3Oy5X2PMAAABs66up8tynxYG8ID8PdpJzqx6diShVupU > c > > > 1Q7beiCUmlvVzc9uRQVejueji6BbKZKaT2fSxH1ykvJDaruDsNqHVDvxyrWNMHLPhnJMwjGxoRw > 2 > > > lMOztlAdXnSoV6qOL8ifKVep1OvQBaeXCNxGy6H6HbeqbNec8003iCfnzfHjWmcjWyd75jwl8D6 > e > > > kccczXwjS07viq71nwAAAGFS1Kd6g7JOj644va6vqOcU6HjRGXBEOJ90CnRevqlXGKbdZ5Dh72R > F > > > 6ZYDV1ICANgeawvVzHGBnFbD668cXlCnRzR4OKThw4FcdaGbeXmJP2POkM5OOlQ4D5pAfdp9Gjd > P > > > yyZmovq0x20BjNyzoRyTcExsKIcN5fDsjUajx/r2UnFTq9sH6tT7dMntvjxQqah7NJ0SlahFg0K > f > > > zulEPpYvPiGbfDngciIE+/b8rXKbV1UaBYyo4vtOxJbkfuRgpAZl9fOn3TchZN+Mw34WbqZmp2c > t > > > evaZp+Vtxm8+11LZgwcP5H+Z+aEw+wewXsF6BesVrFewXomynr36+lt0p2x3Cu7v74v1b9C9uy/ > T > > > o0eP9Nr4Vhaqs/Fo3xxdVUWQkgjbRpb6l14NkQcnNbI6jLXwUFXbChrH5NTbVOgUQ+6zt+8K2nc > U > > > HLpmqN67+6K87XJDFc2/AACrs8xQTU+fqmz+dSjLnZcLDw7KUPlSj96VS1vUgh050viynJ9yX1B > o > > > Dkm3Ridqb+9T4v/598z6f9OYv+jWCeWwpaUcDMfEhnLYUA7P+kJVnqPqnZvaPa15o4Ezx1RwWtR > w > > > O1yHajRwYeGRS7Nx7dc6Z7Z7Kmq1ye6bA/XBg3fGiwpYAADYdOsL1XxTnZuqByIVB3Xqj5txuaa > p > > > zk2VA5VyNTpsh/R5muTgosWmocuUL61yHchzaSPsGwAAdl6K+lS3T1ifqltTdd269Tl6/PhH+i8 > A > > > AFim3ehT3SEcoByk7oJABQDYDgjVNeEgdRcAANgOCNU1wog5G8phS0s5GI6JDeWwoRwehCoAAEB > C > > > EKoAAAAJQaiukf/SWeuCcthQjkk4JjaUw4ZyeBCqCZDnswYsAACwWxCqCfAueWgvAACwWxCqa4Q > R > > > czaUw5aWcjAcExvKYUM5PAhVAACAhCBUAQAAEoJQXSOMmLOhHLa0lIPhmNhQDhvK4UGoAgAAJGS > 9 > > > oSrnVHVPQfFP2TaksyPv9JQjd25Vg5z7tBJlorcuVQ6OKGATwrz3AQAA2NYXqjz3qZyrVJ1+Iuc > w > > > PToTUap0KzmqHbb16SlqblU3P7sVFbS5Wk+tmKFbKVJL3/ab974kYMScDeWwpaUcDMfEhnLYUA7 > P > > > 2kJ1eNGhXqk6nvw7U65SqdehC05VEbiNlkP1O+6k5XlqinB15zDPN90gdtSKKbg228jWyZ45T5n > 3 > > > PgAAgCAp6lO9QVmnR1fX4ub1FfWcAh3rwJ2bCOeTToHOyzf1CsO89wEAAIRYW6hmjgvktBpef+X > w > > > gjo9osHDIQ0fDuSqC93My0ukrlPLkM5OOlQ4L9NkNs97X7IwYs6GctjSUg6GY2JDOWwoh2dvNBo > 9 > > > 1reXiptT3T5Qp96nS2735YFKRd1r6ZSoRC0aFPp0TifysaW2bvIVNcejnAi6/uW4uZjJbV5VaeS > 2 > > > Cxv4vhOxJbkfOeCoQVn9/Hnv8+Own8W9XOHpWYuefeZpeZuZb77ZD4D1CtYrWK9gvYL1yiLr2au > v > > > v0V3ynbn3v7+vlj/Bt27+zI9evRIr41vZaE6G4/2zdFVVQQpibBtZKl/6dUWeXBSI6vDWAsPVbW > t > > > oHFMTr1NhU5xjvvsfcfFoXrv7ov6LwAAWJdlhmp6+lRl869D2Rvi9o0sOb0r4u7V+WSofOld2J5 > H > > > D5fIkSONL8v5Oe+bP1DDmL+k1gnlsKEck3BMbCiHDeXwrC9U5Tmq3rmp3dOaNxo4c0wFp0UNt8N > 1 > > > qEYDFxYeuQQAALA86wvVfFOdm6oHIhUHdeqPm3G5pqnOTZUDlXI1OmwH92tauO914iISAAAAq5G > i > > > PtXthj5VAIB02JGBStuNQxUAANIBoQoAALAk2zf6FwAAYMOhprpGUS4eAQAA0fHpkPNA8+8W4FC > d > > > 9QGY9Rhsw4Zt2JLYBtuUsmIbNmwjOjT/AgAApAxCFQAAICEIVQAAgIQgVFNu3v4BE7ZhwzZs2IY > N > > > 27Bt0zZWAaEKAACQEITqhkvLrzeUw4ZyTMIxsaEctjR9VheBUAUAAEgIQnWN8AvRhnLY0vTLHcf > E > > > hnLYUA4PQhUAACAhCFUAAICEIFQBAAASglBdtm5FXo/SXSpdvd4v6uPmFXX7wzM6ivK4ecV+nV2 > q > > > HBzR2VD/mZTI5RjS2ZH3uKOkCzLX+7KE42EYnh3RwbQ3ZtmfVW1mOZb9WdVmlmNsSZ9VbXY5lvx > Z > > > 1eK9L0s4HlHf9xV9Tv0Qqksl/pEVW1Rqj2QH+qhdolaxItb6RX3cvGKUI1ejQ/dx/ToNikn+o4j > / > > > OruVIiU/vXv0cnQrOaodttXjRm06rOUS/Mc55/vSPqRaLsnPh9KtqC+fXK2n1wSJ/x7GFbkcS/2 > s > > > Ri2HZzmf1ejlWO5nNWo5lv1Zjfq+L/9zGgahukzDhzSgEt3O67/zt8VfA3ro/wBEfdy8Im5/eNa > g > > > llOnO+7jMsdUcHp0da3/XlTM18m/iBvZunhMwiK/L2fUaDlUHx+QPDXFP9Cm++eiYn0+HMre0H8 > n > > > /fnQ8k31BdSvO3pNgJjv4TyilGPpn1Uh0vHQlvZZFaK9L0v+rArRPx/L+6xGft9X8DkNg1Bdpus > r > > > 6jlZcj9fJG5lgz4AUR83r4jbz5QvaXRZpoz+WzyRrqL9SI8mzusUXxInnQKdl2/qFQmK9b4U6Ng > 7 > > > IMmKWo5MmaqlHnUu1DeC/GIpVam8rHJNE+c9XKKlf1bjWOZnNaplf1ajWvJnNfL7vsbPKUJ1iYY > P > > > B0SHN40PQIZuHhINfD+Xoj5uXvNuX/6DMH/tLSh6OYZ0dtKhwrn5jyc5sd4X4UI3e/GSZHNanPe > F > > > awnVq5xqfruq0ijJKkgM836Wli3pz2p0y/2sRrXsz2ocq/yshr3v6/ycIlQhWLdCuRpRvd+kVX9 > P > > > Dc9OqFM4X09NzK9Xo6vbqtlrGf120agBKPfdcty+L76wVtM/tBHwWVV27bO6xvd9GoTqEmXUTyP > x > > > MXMNSf2Asv8FRn3cvOJuX47uKw7Eh/Uy0S+LaOUY0kWnJ74f1C/dgwMe/NGjWi650Yyx3her/8Z > u > > > 2lpU5PeleyoHoIx/8Oeb1C61qLH6b8zYn6VlW9ZnNZrlf1ajWvZnNbIVfVZnve/r/JwiVJfpRpa > c > > > 3hV5zfjc/m904ruiPm5eMbbPH1b1628JX1KRypGh8qX+lSuXNpXIEeUZ0WVSBZr7fUlYxHLIpiz > r > > > C2KNYnyWlm2pn9VIVvBZjWrZn9WIVvFZjfS+r/FzilBdpsxNOhS/Xe+7bR/d++KvQ5r4sRT1cfO > K > > > uv1xc8qSvqSW/Tqjivy+8MhC41f2UI2wLCQ1GiRiOTLHBfEF0aFxpSPpcsSRlvdw2Z/VTbPsz2p > E > > > S/+sRn3f1/g5RaguVZ6a8vwoPXhAnjel2//Fh+1o3Ncw5XGJiFaO7n0+y041X6nmLLUk15QV9Xg > s > > > W9RycE1Ene8nHyf+NR+2k/wSj1iOTJku5fl++nGJl2OGlX5Wp1jpZ3WKlX5Wp1jpZ3WKFX5Wp77 > v > > > Kfmc7o1Go8f6NgAAwE7a39+nV19/g+7dfZkePXqk18aHmioAAEBCEKoAAAAJQagCAAAkBKEKAAC > Q > > > EIQqAABAQhCqAAAACUGoAgAAJAShCgAAkBCEKixJlyrm1U7ikldHUc+fPYXVgvuaKrlty4uA622 > F > > > Lkdn67/Gb+CxX+YxjqBbsY/TOssSyn+MVnDMYv07gVVAqMIWyFNTX9Q8+QuZL2PbJWrrbXoLX4x > d > > > 6NUol4ZgnbDMYzxdl+cILfLl6dTF6s3jJWeISeXxYus7ZrA+CFWAVFDXKpVEsJ6i1qGIGqrMUxm > o > > > 5jVkObC8HyInqaqxwi5DqMIKqQmM3aY7/zJuvuImrVyNevpPeVFseWfI8ysVXzNbxP1IXhOdtYw > f > > > FNKEF9QcuWiNiaer0jctgU2f/gu6h7wOsUw0C04re+ixj3EcrLLFeS/8xHMbMlFF5b4acFH2PN1 > 2 > > > f4d0LrxjH+l4CfOW3S30xPN5PlWT/5gl8LkUy/hxoe+VFvU4QKIQqrA+pbZqytM1tFbxiOR3D89 > 0 > > > 0a+PA6bUFo8Zz3rskev5+c3bek2IsP3ILy79Reg+xq39tIr2F5RBTZCsvj5VGfpU58Iu2nR7faW > / > > > IL15Hyf3NSL1MlpUPJj2OkbUl4UyX2+Eskc89ixa2XxC34sAwwvq6MQo3Q4uQ76p9ju6LBNnbtQ > y > > > zVN293F8PLzne03S+iVFF+tzGfB+Tnmv5npvIBEIVVgP/rJwv6zzt1WQiUjpjCdinEE8P+S73jZ > t > > > P8OHNJB/i4eNv7S9frDgMOnSaU1HX72vy5Ch8rn+cpu76VZ8keovQa9W5u3LfL35pg5C8Tpqcmf > B > > > Zc6Uq77jmmTZg7YVVDbDou/5TFHLNF/Z3cfZzz8f16DzTf2DLIqpxyLq+xnGK9/0zw0sA0IVdpe > c > > > yFhR8y5GaBqTkx0z38TLXGvQX4TG92AIri34m+VUzcSsbXj7EuutmlqGjgvy21Fs6v7sMrsSKbs > W > > > tq15y5aEqGVatOzjH2P+56dE0p8biAWhCjtM1Qi8Zjsz7JbZ9+Qb/Ws04bWKwfsdT7asl5xbEzH > I > > > Jj/jMZN9fJCIcTP9ciXxfkb53ECyEKqw88b9cryME1YE7KpO1bD6xlrUmOjwMk8l8S9N8dNADYB > R > > > X5hmYMdojkyjzDF5FavgnzjydBsOjFW9VyuR1Ps563MDy4BQBTDlm+MBIdS7omt1yxPWF7joSfh > G > > > gIxHsob2OxqjSDlMuqekKiD8JTrlyzLJsk8p24U3umjBL+4Mlas6RlqNgME1Xbqvq25O4ZgyUcu > 0 > > > aNlDn5+QqO9nmCmvz/rc6LWQLIQqpN7g4ZL++RunHHhhYg7yCPpizdMdHbp84QH1PPFldaJPbXD > q > > > dGeuJDECpNch9V0YtC+xt7MT/aUrilgtU2Z8Ko75JcpfoP7mwvhlDz/2wWXrVnJeIMx3IGziR45 > q > > > POhRLWeOWjVGyIpyn8vRQlHLtGjZzeefTI7YXVTk99PmvVfBr2/ic6NuQsIQqpBOmTKNM0Z8MSz > l > > > l7X4wvZOZ9C/4PUXI48KNUdemjLlS9/z9Jex+HLv61M75mLUMGon6vXKfemmYbeMqlmQazF6YJH > R > > > fCyPlXwdbkDYIpU94rGf3NaBvlADN1maF2pYjGyel/vhYFX7sd4n45hHLdOiZefnqxYNt0wJBSq > L > > > 8X7yY4PeK/n6Zn1uYCn2RqPRY30bAABgJ+3v79Orr79B9+6+TI8ePdJrlUqlQs1mU//lCVqPmio > A > > > AMAMHKAm/98uhCoAAEAEbpCGBSpDqAIAAExhNvGagRrUJIxQBQAAmMEfoEGByhCqAAAAEbhBGha > o > > > DKEKAAAQ0bRAZQhVAACAhCBUAQAAEoJQBQAASAhCFQAAICF7/7LexGUKAQAAEoBr/wIAACQEzb8 > A > > > AAAJQagCAAAkBKEKAACQEIQqAABAQhCqAAAACUGoAgAAJAShCgAAYPirv/orfSs+hCoAAEBCcPE > H > > > AADYSH/8x3+sbyXjV37lV+R/uab6cz/3c/J2XAhVAADYSByqn/nMZ/Rfk9pv/y/00U8+pI8++kg > u > > > H3/8CZ38xpv6XtsPfvCDREIVzb8AALB1/u9/8z/Tf/vPivSrJ1+mUvnL4r//hP5J6b+m/+3r/1Q > / > > > YjkQqgAAsFX+r7f+JxGo/5g++UTUTj/6kD75+Cf0k7//j3J5/vl/SK9Wi/qRyUOoAgDAVvnJT0S > I > > > ymbfn9DzX25Q4R//JhX/u2/Sj//uP9Lf/+j/o+//v3+jH5k8hCoAAGyVjz76mD7+mJdP6Kc//Sn > 9 > > > 4R/+IT3z6Z+hD0Wo/vjvHsn+1WVBqAIAwFb5Z5V/TV+t/C79D+Vv0R/8wR/Qb9b+Gyr96j+iD3/ > 8 > > > NzJUP/nkE/3I5CFUAQBg67z11lv0e7/3e/R//KtfpRde+Bz95MO/pQ9/9Lf0td8c0DvvvKMflTy > E > > > KgAAbKXf/de/Tr/6T5+ljz/8O/r4x/+JKv/re/T9739f37scCFUAANhKP/MzIuL2iB4/fkwff/x > T > > > vXa5EKoAALCl9uijD/9WLh+LZRUQqgAAsJX++5ebdOfrPfofv/Hv6Z//1gf0J3/yJ/qe5UGoAgD > A > > > Vvo3//uv0+v/4r+g11/+z+lfnfwDunXrlr4nWX/2Z38mF4ZQBQCArcTnqX74o7+hH//ob+nDv/9 > P > > > eu1yIVQBAGArfSRC9ccffkI/+ein9NEne2rg0hL80i/9klwYQhUAALbSr7/yLfrGt/4Dvfq7P6b > G > > > //mf0Xe/+119z+LMJl80/wIAwE5ot9v0ne98h7rdrl6zXAhVAACAmMwmX/M2JikHAICNxJOUJ2n > W > > > JOVuEy8HaNhthCoAAIABoQoAAJAC6FMFAABIyN4H7RdRUwUAAFgY0f8Pv2raZV7mqO4AAAAASUV > O > > RK5CYII= > > --001a113d6a0a1ede02053654edd6-- > > > > > > > > -= This is automatically added to each message by the mailing > script =- > E-mail to subscribers: CHEMISTRY_._ccl.net > or use:> > E-mail to administrators: CHEMISTRY-REQUEST_._ccl.net > or use> Conferences: > http://server.ccl.net/chemistry/announcements/conferences/> > > > > > -- > *A GENTLE WORD, A KIND LOOK, A GOOD-NATURED SMILE CAN WORK WONDERS AND > ACCOMPLISH* > --------------------------- > *Venkata Pera Reddy B.* > */Research scholar > /* > */ Dept. of Chemistry > /* > */ National Institute of Technology/* > */ Durgapur/**/-713209,W.B, India/* --------------1EAAEFE951C29BA91A07A9DF Content-Type: text/html; charset=utf-8 Content-Transfer-Encoding: 8bit

Constraints on the structure to ''keep it on course'' during the TS search can be very helpful. Constraint the critical distance/angle during the search, take that result, re-optimize without constraint. Calculating force constants frequently can help


On 28/06/2016 18:09, teja reddy reddyteja80]=[gmail.com wrote:
thank you Dear   Dr. Tobias Kraemer ,
I have tried both forward and reverse and optimized the last point geometry on IRC, in each case it is optimized as product intermediate. can any one suggest regarding this Correct transition state characterization.

On 28 June 2016 at 20:31, Tobias Kraemer t.kraemer~!~hw.ac.uk <owner-chemistry_._ccl.net> wrote:

Sent to CCL by: "Tobias  Kraemer" [t.kraemer:_:hw.ac.uk]
Dear Teja,


At first glance this looks like a reasonable IRC, quite flat around the TS
(not sure what the outlier means). A reasonable thing to do next is to
optimize the last point of the IRC (1.8 on the X-coordinate) and see where
this leads you. Of course you should also run the IRC job for the other
direction (reverse or forward, whichever way you look at this) and do the
same thing here, optimize the last point on the trajectory. Inspection of
these optimized structures help you to confirm if the TS is reasonable and
the one you were looking for. I often look the at the animation of the
imaginary mode itself, this tells me already if this TS corresponds to the
desired reaction coordinate. You can also do a quick version of the above
protocol, displace the TS geometry by a small increment in both directions
of the TS along the imaginary mode (use GaussView to do this), and optimize
these new (initial) geometries to their nearest minima. In the end, it is a
combination of visual inspection of the TS as well as the ground state
geometries which will reveal if this is the right TS for the reaction.

Hope this helps


Tobi



Dr. Tobias Kraemer MRSC
Research Associate
Institute of Chemical Sciences
School of Engineering & Physical Sciences
Heriot-Watt University
Edinburgh EH14 4AS
United Kingdom
email: t.kraemer a hw.ac.uk
phone: +44 (0)131 451 3259

> "teja reddy reddyteja80%gmail.com"  wrote:
>
> Sent to CCL by: teja reddy [reddyteja80~~gmail.com]
> --001a113d6a0a1ede02053654edd6
> Content-Type: multipart/alternative;
boundary=001a113d6a0a1eddff053654edd5
>
> --001a113d6a0a1eddff053654edd5
> Content-Type: text/plain; charset=UTF-8
> Content-Transfer-Encoding: quoted-printable
>
> Dear friends, =E2=80=8BI have optimized TBP transition state which is
showi=
> ng
> -216cm-1 negative frequency but is showing only 9 points on the curve
like
> shown below. can anyone help me is it a correct transition state
> [image: Inline images 1]
>
> --001a113d6a0a1eddff053654edd5
> Content-Type: text/html; charset=UTF-8
> Content-Transfer-Encoding: quoted-printable
>
> <div dir=3D"ltr"><div class=3D"gmail_default"
style=3D"color:rgb(0,0,0)">De=
> ar friends, =E2=80=8BI have optimized TBP transition state which is
showing=
>  -216cm-1 negative frequency but is showing only 9 points on the curve
like=
>  shown below. can anyone help me is it a correct transition state</div>
<div=
>  class=3D"gmail_default" style=3D"color:rgb(0,0,0)"><img width=3D"469"
heig=
> ht=3D"434" alt=3D"Inline images 1" src=3D"cid:ii_15596c33e3e5b53d"><b>
</b><=
> i></i><u></u><sub></sub><sup></sup><strike></strike><br clear=3D"all">
</div=
> ><b></b><br><div class=3D"gmail_signature" data-
smartmail=3D"gmail_signatur=
> e"><div dir=3D"ltr"><div><div dir=3D"ltr"><div><div dir=3D"ltr"><div><div
d=
> ir=3D"ltr"><div><span style=3D"font-family:courier new,monospace"><b><i>
<fo=
> nt color=3D"#000000"><br></font></i></b></span></div><span style=3D"font-
fa=
> mily:courier new,monospace"><b><i><font
color=3D"#000000">=C2=A0=C2=A0=C2=
>
=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0
=
>  </font></i></b></span></div></div></div></div></div></div></div></div>
> </div>
>
> --001a113d6a0a1eddff053654edd5--
> --001a113d6a0a1ede02053654edd6
> Content-Type: image/png; name="image.png"
> Content-Disposition: inline; filename="image.png"
> Content-Transfer-Encoding: base64
> Content-ID: <ii_15596c33e3e5b53d>
> X-Attachment-Id: ii_15596c33e3e5b53d
>
>
iVBORw0KGgoAAAANSUhEUgAAAdUAAAGyCAYAAACySF4VAAAAAXNSR0IArs4c6QAAAARnQU1BAAC
x
>
jwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAEqjSURBVHhe7d1fjCvXfSf4Xwf75HnoBhYIECB
Y
>
KLw3Itx6URi7MMLuyFcO2G377guxIgbjxU64mpXTlDdXnIEZXGr3ruHRrKiE2R2qF1a3o4lA5CG
7
>
Czog8nCd6SZiXwVeDEA5DLAD0WjlNqOHAAECzA5vJnEsS/Ld8zvnFOucYhVZRRbJIvn9GGWxi2T
V
>
YZGXX54/VWfvsUAAAACwsJ/R/wUAAIAFIVQBAAASglAFAABISGif6t7enr41HbpkAQAAlKmhOis
w
>
3eBFsAIAAPhCNax2GhaaMnj5v2JBsAIAwK6b6FPlaDQX9ujRI/nfs7Mz+sY3viH/63JjOGpzMQA
A
>
bC7+ro+ypA2X6U//9E/1X5P4viTKHWug0l//9V/TX/7lX8r/Mq6dustMH7xNz3/60/Rpd3n+bfp
A
>
3yV97xWx/hX6nv7T9j16hZ/zSvC9H7z9vHju8/S2ucEp2/veK5+m560HC/x4c/tTyzMLl9d9ri6
7
>
sUy+jA/o7eeNx/iPjeTfjvl6+T7f6wcAWBLzuz9oSaMf/OAH9Mx/+V8FBiuv4/v4MYuKFao/+7M
/
>
Sz//8z8v/xsLB+oXv0Nf+qMf0g9/qJY3n3xIf6HuVIHSJSrIv8M8RU+9/82A4Pge/U7jPX2bzd7
e
>
c/kCvfdQ7d31vW6HCvnnxK2o5YnjKaq6r/3NAnVeMsJa/tj4Ij38qndsfvjbRN8NTHNvO39UJWp
8
>
LSh8p0H4AsBu+uVf/mX6d//P9yeC1Q1Uvo8fs6hYofrlL3/Z+m80IqS+1qAn3/w2vfCEXiU899p
r
>
xBFG9AS98G0RFK/l5V/TPPkk0Xe+60uE73WpUygYARhhe79wk57qdL1gE7e6nQLJTI1Rnrk8lxd
l
>
fZ/+Qr4M99j8kF5TB0N54gV6wfw7wBMvfJUK732H/IcDAACC+YM16UBlE6HKLcrmsrAPvkvfec8
N
>
rBi4+dXXDHrzK1+lJxu/Y4ShCKVvvk/Vr0QIQHN7T3yevvRUh7ruhmQw53XILxnv66kv0ef5B8a
8
>
x2YWX1O7am7mWupL1KH3qPFFsT6kKR0AYJuZwZp0oDIrVP1t4qPRSC6u3//937f+G9lTN+kX9E3
V
>
/8lf9vM0Qz5H+YIRhhxKpAMqlifo8196it5X1UWj6XdZdJDx6+7m6YfffkGUQDOOTRwfvP1NL5w
t
>
Ijy/qGq/sin5j6r0/kt8rJ+j1374pqgl6yZkq2oMAOtgDuyZtsDmmNr8u7+/P16Yf6BSZO+5/af
c
>
bPlt8WXPX+4zPPeaHT7ac18RIfFNVeP83u+I8Pjq5GMC+bb3xOe/xG3JYjsf0F+8/xTdjJNsVk0
w
>
ymAmHWQi4OxmZ8E4NrN54fzFxpP0ZsDxoQ/+gt4XR3f8G+GJF+irhffI14UMAClgVmSmLZAcs8n
X
>
bApOSuQ+1evra2ugEv8dyRO/QE+O+xATwE23on763e+9Td98v0pfmbfCNd7OHLVdEVTfdgcV/dD
t
>
G45APO+3q+/TN90qur8ZeiZjwFOc/QIAwEQfqr+PNQkzQ9U9N/Xy8pKOjo7o61//uvwv/+0/ZzX
Y
>
cyQql6KGFfP0lIA+VeUJeuGrT1LjpQbRlz4frZbKJrbHTcCiXHG3syAeYPRk42u66ZtfC48G9p1
m
>
I2rCb8c6WAb5I8ZsIhc/PsaDsAAAdlPYoKSkg3VmqJpNvjdu3JDr+L9xmoJlk++bRC+Nm0xfove
r
>
v22NBo7lua9Q9akCfXXuDSjcBPyU+N+X4nfKLkD/yHBPh+Fmadnv6R4bsXyN6PNzh+Bz9Jq5PXk
q
>
k1ur5T5pDFQCgMUE9fuaSxp95jOfmQhUlxus/JhF7T0OabDnA8N3cU2Ug5ObfMvlsr5X1WDN9e7
j
>
AQAAdtXMUI0KoQoAALtuaqjGhVAFAIBdFhqqAAAAEE/kU2oAAABgOoQqAABAQhCqAAAACUGoAgA
A
>
JAShCgAAkBCEKgAAQEIQqgAAAAnZG41GOE8VAAAgAaipAgAAJAShCgAAkBCEKgAAQEIQqgAAAAk
R
>
odqlysEBHYyXIzob6nvlfebfAAAAEEbXVB2q90c0Go2oXyeqnZxRvBxF+AIAAEw0/2bKVSr1OnS
B
>
gAQAAIglXp/q8IyOjKbiSpdXci21SC3qUS0n1suVQzo78j8OAABgu02E6vCsQS2nQMcZvWJMhGe
u
>
Rodt1Uw86tdpUOQm3zw1R20quU3Izbx46CnVDtvqcWLhVQAAANtOh6quZYpaZa52SO3LMk1k6vA
h
>
DUR03nYDMlOmaqlHV9f6b9ONLDmtIh2hkxUAAHbIxECl0ahJC1csReBeim2d0wmafwEAYGdE71P
N
>
3KRDatF9NyCHZ9RoGTXXAJnyJfXrDg0eosYKAADbL8ZApTw1ZT+qHoCU61Ch79Zq83S7ZAxU6lb
G
>
g5S4OblanmhMBgAA2DqYpQYAACAhMWqqAAAAMA1CFQAAICEIVQAAgIQgVAEAABKCUAUAAEgIQhU
A
>
ACAhCFUAAICEIFQBAAASglAFAABICEIVAAAgIQhVAACAhCBUAQAAErL3L+tNXFAfAAAgAQhVAAA
A
>
7d7dl+nRo0f6r/j2Hgv6NgAAwM569fU3Fg9VzKcKAAC7bn9/P5FQxUAlAACAhCBUAQAAEoJQBQA
A
>
SAhCFQAAIKJKpaJvBUOoAgAAROAG6rRgRagCAADM4A/SsGBFqAIAAExhBmiz2dS3goMVoQoAABC
B
>
G6hmsPohVGHNulQ5OKCDqEulq5+3WsM387oMeXpzqFeG6VbsMs9Y1vSSNkasY58yQWX31k1f8tN
e
>
bNhnLP8mbdgh2hj+IA0LVoQqAEAKvftKLiBY9Y/QYkv/7fPuK5QT908NZIgtLECD1iNUYc3y1By
N
>
aGQs/dc+q+/7LL3Wt+8bNfP6vni6FffXfEV8La3OZ1/r2+UPWOZ8SbAFSu2Az0T/NfHJV9595dT
4
>
vA7pzXyRvDgtUdt8Xruk1/Pzfm3javXbAqEKAJAmmZfoW+Mflu/Rn7vh2D2lV97Vtz/7GvVHTfG
T
>
1JBvGoH8Lr1yin6FdUCowkbzaqD24vVTquYyr7WsRUV+jPuAFPVNzexrC+l8DT4Gk/2PYcfK2y7
X
>
hALuHy+qlm9ux1+kafdNSODYz37/lfmObbTjsSrd++6H+LP02rdeooz+yyICuevWXNEEshYIVdh
Q
>
/rC0tYriS2/Gt7r8op3WN5W2QR+tou81TTsGoqaSi9O3xtvKeTWhKfJ3vObJ1n27PN73/mt0Z8p
3
>
+uLHfvH33xJ4bKMdj8QN36RfG+/4KfpFmZ5D+vP35ApxbAv0hcBEhTRAqMJG6laMviXZFKZ/nRv
9
>
UfxFWemqPluvu0n3QzWJTsdfXGbfVJ/GLW/vdujfLpiqPNgkuJajlynhMe6PtV7TffF1r1jHoNT
W
>
5eelLV6REt63ZrxmUaMJ3ZbRTzeW+QIVvFQdl0dUpcbb+GzhC8E1Kam78LGP/v7r2z5zH9ug47E
A
>
Gf7+z0TuFfGTSCm13Sbea3p/nLO/OOXYQhKur6/nXhCqsIHsGlG/azSFcfOX8cVn16RM5gAps28
q
>
Q18YJ8a79P61vrliPICl+5J+VeI1/cb4Jbl9bL5jYDX1iddm9K11JtKJB4CZr3nKtvJN4weJyzx
G
>
LXIPsdk8WZhalVr02C/2/i90bAOPR/Lc0EcL7uZBqMLmGf65+PrTgn6152+Pa2r03p9HakY0awq
5
>
BNv8Zo7+NQMhDvMY6NMozNdg1nbenfXLYNbxDJD5QmFcw1PBZQRR6TfIzazp5jz2ib7/AeY4HvO
y
>
R/96NXVu4bBr2TfoSfeAz/OaYGUQqrCz1CAXo5lvWy3jS9jfBGw0/ZZuz65e7cyxjyVDL3W9pvt
W
>
0RwIlaFffErfTKBbApYHoQqbJ/OL5H6/BAaG8QUfWtMYvkm/NX6Qfb6fd55sipnHwOpPDVhm1YZ
n
>
Hc9AdhNwcTxiqEQzM3XRY5/E+z/NXMcjKXm6Mz4GLfoto0M8f9uN23fplV8L6YsXxzbv1vzjDNS
C
>
xCBUYQPlyft+8Y0U5S8VY0joZK1J95tdvz9uHhUPsvoXvUE0aWYcg4mRq3wYvFNIZo8A9h3P8bb
U
>
KSVhI2zNJuAx61iGWPjYL/L+RzHf8UiKeVzf7fxb77Xl7xgDubjJ33dKD792c5DTXK8dFoVQhY2
U
>
b3rNZOoLRv86N75UuAY3OdBDnWpy8FvveYHAoeQ+P+EmyZmjf3mZs0ZhHQPrNZh9kyX6jQgdnOZ
p
>
Mt62ZpxSYg3yUSJ9kZt9nnMe+/nf/2jmOh5JMZvWraZeu3lYFEydcx3w2rkvH4Oc1gOhChvKf6q
M
>
TQ4AMb5VrC9JqUDfMk492UzqGIQ1mapBUr6r7oThUbNzHA+vSZJFaPqVuNyLHvt4739scx6PZNi
j
>
oO0rI+mR06FDkFVz+nh0M6zc3mg0eqxvAwD4cJOnW0PjL2x/SPMIXl3D5L7dra8ezToesKn29/f
p
>
1dffoHt3X6Z+v6/XxoeaKgBMYVx0IEjMUb+bb8bxgJ2HUAXYeeY1bs1rBvN6o59zYhCSqKW6o3Y
+
>
O/2yhJtl3uMBgFAFAB4AMx5xpAdyyUAxB+Z8ll4bp6Z70QYvYKZflnDTxD0eAB6EKgAQX37Pug6
u
>
iS/VN+qGXyWp1N6+gTGLHA/YaRioBAAAOw8DlQAAAFIGoQoAAJAQhCoAAEBCEKoAAAAJQagCAAA
k
>
BKN/V+T0bHzKOAAArNmdsn395KRG/643VLsVOhjPo+S/juaQzo5yVOupv5x6ny7L9olhw7Mjyl1
V
>
I1xvlE9Wb1C2f0nuJuRz3Y2TQ3XjPs/k8+bFoXrv7ov6L+Wdd96lz30u+GLoq4Ry2FCOSTgmNpT
D
>
tmnlePX1t5YWqutr/h2e0VFxIMJMT05cH1Dx6ExEqdKtiEA9dCdfbtNhLUfuDFndirrCiReK03U
r
>
vimlRJjnaofe5MjtQ6qdePt2TTwPAABgirWF6vCiQ71SdVwDzJSrVOp16IKTTQRuoyVqj+PLgKn
p
>
jtwKab7pBrGjVkzBNdJGtm5P4cRXSzFrxTey5PSu6Fr/yQKfBwAAMEWKBirdoKzToytOtusr6jk
F
>
Ol6wyZXD+aRToPPyTb0imAx4JytKoEV83qLS0FzCUA4byjEJx8SGcthQDs/aQjVzXCCn1aAzt81
1
>
eEGdHtHg4ZCGDwdy1YVu5uXFbfqNbkhnJx0qnJfDL/TNTdCyGZmoPn5chOcBAAAEWNlAJXNg0Hj
Q
>
kTlQySlRiVo0KPTpnE7kY3n2ftnky+GXE0HnGzA0baAS33citqQGN80YcGRs//gi+vM47GfhZmr
G
>
A5WefeZpeZuZv6i4c92F9QrWK1ivYL2C9coi69kyByql6JQaNdr3qiqClETYNrLUv/Rqizw4qZG
1
>
RwCHh6o9ctgUNIqYqe23qdApxnreNBy6Zqhi9O90KIctLeVgOCY2lMO2aeXYztG/frL516Esd2w
G
>
DByKJ0PlSz2yVy5tUQvm02ZGIcE4JNXifCPm8wAAADzrC1Vu+j2okNtV2j2teaOBM8dUcFrUcDt
c
>
h2o0cGHhkUsK13DNfYudi9ppctsHAIDdtL5QzTfVual6IFJxUKf+uBmXa5rq3FQ5UClXo8N2hAs
w
>
yIFHRliGyJQvrX0fyPNlF7/AQ1xpaC5hKIcN5ZiEY2JDOWwohweXKVyiWX2qAACwervRpwoAALD
h
>
EKprxCPV0gDlsKEck3BMbCiHDeXwIFQBAAASglAFAABICEJ1jTBizoZy2NJSDoZjYkM5bCiHB6E
K
>
AACQEIRqAuS5rgHLTHv/QC0AALAVEKoJ8C5raC+hdJi+8+AB0eO/W3u4YuSeDeWYhGNiQzlsKIc
H
>
obpqHJ4iSPfoMd269Tna2/uUClY3XAEAYGMhVNeAg/TBg3fGiwzWlOMyugsAAARDqK6SrqWGWlN
t
>
ddaIuVX9CMAIQltaysFwTGwohw3l8CBUYS57Ivx5AQAAD0J1lXRN9PHjH8n+VHfhv6VZNdkUeSz
K
>
yYsbrtMWAIBdsd5QlXOquqeg+KdsG9LZkXd6ypE7t6pBzotamTXRG+tS5eCIzE2oOVXd7Zv32fu
d
>
vD8ZKkj3vEBdo1kj5kJ/BAhuuE5bgoLWvzCMILSlpRwMx8SGcthQDs/6QpXnPpXzmKrTT+T8pkd
n
>
ItKUbiVHtcO2Pj1Fza3q5me3osIuV+upFTN0K0Vq6duSCPNc7ZDa7ukv7UOqnXj7JnLG5VJLgnO
t
>
ipCRNVIdJJL7N9+XWuoHwDw/AoKC1r9wsN66dWsibM0lLgyuAoBVW1uoDi861CtVx2GVKVep1Ov
Q
>
BSebCNxGSwTbHXfS8jw1Rbi5c5jnmyrs+nVHrZiCa6SNbJ2smfPyTfH8ptiqdiNLTu+KrvWfRId
0
>
c5kTlosQ4UVOZMthof/eZRysDx48mAhbcwkKWv/iWtXgKgAAU4r6VG9Q1unRFSfb9RX1nAIdLxp
s
>
IpxPOgU6L9/UK4LJgHeyogTsmq6iVYAXtsf/J8Ji3TZl5F5Q0PoXf7jOAyMZJ+GY2FAOG8rhWVu
o
>
Zo4L5LQaXl/l8II6IswGD4c0fDiQqy50My8vkbpOLUM6O+lQ4bxModnMTdCyGZmobj1uQA2jXzX
+
>
vmFd3HANYtZozQUAICl7o9FItkIuGzfDun2gTr1Pl9zuywOVirq30ylRiVo0KPTpnE7kY0tt3eT
L
>
4ZcTAdm3+zblNq+qNHLbhQ1834nYktyPHKjUoKzv+WPm9sm3r5B9Mw7cWbiZmp2etejZZ56Wtxn
/
>
ouIvdA4As3Pd/KWVlvWbUk6Xu54HVbm4Lzjs8UHBuomvl2G9gvUK1ivmevbq62/RnbLVKUj7+/t
i
>
/Rt07+7L1O/39dr4Vhaqs/Go2xxdVUWQkgjbRpb6l17tkQcnNbI6jLXwUFXbChrHNA50n6Dtu6b
d
>
Nw2Hrhmq9+6+KG+73LBaN/7w+T90plWVc1Y5VoXLwYOmgqzy/UrL8WBpem9QDg/KYYtajmWGanr
6
>
VGXzr0NZ7ticGDgUV4bKl+bo3baoBasRvcHBOCTd4gwgcXgGLfwDw78AALjWF6ryHFXv3NTuac0
b
>
DZw5poLToobb4TpUo4ELC49cUriGa50X2z0VtVq1/cn7KlRMcN+w2aIGLS8AsHvWF6r5pjo3VQ8
G
>
Kg7q1B8343JNU52bKgcL5Wp02A7pDzXJgUf+i0hMypQvrX0fyPNl1fan3bet0tBswza1HEFBy0v
c
>
oPWfV5uW48HwGbGhHDaUw5OiPtXtsyl9qtNsQhk3SXiwPpbn07r8V64CgOTsRp8qwA4wa7LmAgD
b
>
AaEKcsRcGqAcNrfJOLx2uzp4b2wohw3l8EQLVdlXqfsYA5fkLzgPsEu4qdc/aYF52cY0BSwAhAs
P
>
VTNITzp6ZbjOCQIWYBEcpO7iZzYVmwGLkAVIl5BQ7VLFCtICnY/P+QxazsUjPJ2T2SNwIT3CRsz
x
>
FzZ/ia8KRhDawsphBqw/ZJcF740N5bChHJ4pzb9GkBpXNgpmXmzBDlgAWK6wgF1myAJAsJBQzVN
z
>
ZpCG4YA1plXbAXb/srcArJoZsP6QBYDlizZQCaaym8K9ZVNg5J5tm8qRVMDivbGhHDaUwxM9VM2
B
>
S0dnxGOR+ELzB5gXbSvxFy9/EcP2CAvYeUIWAIJFC1W+Tm+uRsFzd9+nMwz3BdgoZsD6QxYA5hc
h
>
VId01uA5T9UsL/26o1YL+Waf6oMW1WqnGO27wTByz7aL5QgLWDdk8d7YUA4byuGJEKrXdCWqqE7
9
>
POCi8hkqV+3rJwLAZjMD1h+yfv5JAAB23cIDlYaYiBRgq4UFLAcpTwLgLghWgEiheoOyDlGvliP
/
>
mCSeezRX42psVjxqDnJOVfcUFP8FI4Z0duTed0BHAf22cu7TSAOlulTxXelJzZvqbt9/FajZ+94
m
>
/hFz/IXJX6CrhhGEtrSUg7llMQN2HfDe2FAOWxrKESFUvSbeVvFAhWivRjkRNvK2UKrOcU4rjya
W
>
c5Wq00/kHKZ6VDHrVnJUO2zr01PU3KpufspRx8b+Z+lWisS9wmMizHO1Q2q7p7+0D6l2Em3fAAA
A
>
YaI1/+abMlwme09LMpjGc4vHMLzoUK9UHffTZspVKvU6dMHJJgK30XKofsfdcJ6axn7yTTeIvUF
T
>
YbhG2sjW7bLL12NcoOJGlpzeFV3z7Rn7BgAlaBIAt2kYYFfF6FNV4aJqb+6S5JWTuJm5R1ecbNd
X
>
1HMKdDzfJZ08IiBPOgU6L9/UK4LJgHebsJPa9wbByD0byjEprCz+SQDcpuFlhSveGxvKYUtDORY
e
>
qDSvzHGBnFbD68scXlCnRzR4OBwPfrrQzby8xG9+HdLZSYcK51OaprkJWjYjE9X145LZ9+ZaV38
q
>
bJdlhytAWu2JGudjfXs6DiD3AhBOnfqXZboWwVOkNo0itI2OBzUJTr1Pl9zuywOVirq30ylRiVo
0
>
KPTpnE7kY0tt3ewq9y0Csn9pndYjt3lVDdw/33citiT3IwcqNSjre/6Ysf3jC1XOWftmHLizcI2
e
>
nZ616Nlnnpa3Gf+icgPM7Fw3f2mtYz2XiefxdK1qvwzrlW1c7war+9la1X4Z1itY73n19bfoTtn
u
>
0Nzf3xfr36B7d1+mfr+v18YXLVTN8GNWqJaonr1D5cC0ioNH3OboqirCjMT+Glm5D3erPDipkdV
h
>
rIWHqtpW0DimcaD7jLd/8zTSvqPg0DVD9d7dF+Vtlxuq68YfPvdDt84ymeVYJ5RjUlJlccN13s8
Y
>
3hsbymGLWo5lhmqE5l8RUKu4opJs/nUoyx2b5sChuZhT0fHCg6xU+YODcUjj020X3jcAhOEw5YX
D
>
1Q1YgG0SIVSXdEUleY6qd25q97TmjQbOHFPBaVHD7XAdqhG5hYRGD3EN1zovtnsqarV6+0veNwA
g
>
XGF7LTxQae4rKuWb6txUPRioOKhTf9yMyzVNdX6oHCyUq9FhO6Q/1MT9nxMXkZiUKV9a+z6Q58u
6
>
259z3xvMbS7hL7d5m+WSkIbmI4ZyTFpWWeKGK94bG8phS0M5IoTq8q6oxOE2bqKdmBTdPoUnYCy
S
>
er55R6ZMl4Gn+fC27GC09u27L8q+ASA5qLnCtogQqku6ohIAgA/CFTZdtObfJVxRCdKDR8ylAcp
h
>
S0s52KrLEhaueG9sKIctDeWI0ae67CsqAQDYUHOFTRMhVPnCCds/U8uu4y8s/vICSCM3XG/duoV
w
>
hVSLUVOFbYWRezaUY1JaypKWmis+IzaUwxMhVN3Rvye+OUcBANYjLeEK4BchVNXFH0SsUi2nz+u
c
>
WGafG7rNgo/J7OsCA8BiEK6QNmj+TYA9eMtbNgV/GfEX07phBKEtLeVgaT8mqw5XfEZsKIcnQqg
G
>
jfr1LxgFDADrh5orrFuEUFWjf3dpTlEA2GxB4bq396nxArAsizf/yuvtHmEQEywMIwhtaSkH29R
j
>
4oXrp+jBg3fGy6LBis+IDeXwTAlVVUM9OCgST/zGlygMGozDF5xXFysEAADYbckMVHIKhJnRNhM
3
>
jfEveQAAWNyUUHUHKKlr/pba/sFJxjIxw0xEck5Vt9brPy1nSGdHXo046IpOcl7USJ29XOu2m6j
V
>
nKru9o37rDIZy9GZKNF2wsg9G8oxadOPyePHP6Jbtz43XsTPSXXHnPAZsaEcnmRqqvPgvlg5j6k
K
>
Zjm/qRFc3UqOaodtHdxqflM3P7sVFXTuLDmzdCuqCXtMBGeudignA5Dbbx9S7UTvW04eoNeP759
z
>
InYASA0OVm9Rg5gAkhY5VAcPk62nDS861CtVx/OYZspVKvU6dMG7EYHbaDlUv+OeqKNqze5sOPm
m
>
Crt+3VErpuAaaSNbt2fYkcFpnAZ0I0tO74qu9Z9+3fstcgrHmN4OYIsgWGEZ1ldTncCXQ+zRFSf
b
>
9RX1kuinFeF80inQefmmXhFMBnzYROsy4EtUtWcx3wpufypG7tlQjknbekzmDVZ8RmwohydCqC7
n
>
2r+Z4wI5rYa3zeEFdXqqRjx8OJCrLnQzLy/xz5Md0tlJhwrnU/p7RWAeyWZkonrI47qnfOcdXNw
C
>
YEuhxgpJ2huNRo/17RA8yMfXJzmBJyufflUlboZ1+0Cdep8uuebHg4KKestOSWylRYNCn87pRD6
W
>
B0fJJl8Ov5wIyP7luLmYyW1eVWkUMEs633citiT3I19Dg7K+54+FbD90vcZhPws3U7PTsxY9+8z
T
>
8jbjX1RuTdHsXDd/aS17Pe//wYMH8vYq94v1CtYraVm/7n+PWK8sez179fW36E7ZHiuzv78v1r9
B
>
9+6+TP1+X6+Nb2WhOhuP9s3RVVUEKYmwbWSpb4wq5sFJjawOYy08VNW2gsYxjQPdJ2j7vK5I7cD
Q
>
joJD1wzVe3dflLdd7j/idTG/RPwfunVAOWxpKQfbhWMS598jPiO2TSvHMkM1QvPviq79K5t/Hcp
y
>
x+aMgUOzZah8aZaPTwty5EjjoEDlENYtzoYu3bcGSwHANuNA5WAFWMT6BirJ80G9c1O573I8Gjh
z
>
TAWnRQ23w3WoRgMXErrCBNdwrfNiu6eiVmtvf3jWoNYWX9Ri3bVkgDRCsMKiIoaqfSGGyWWO+VT
z
>
TXVuqt5GcVCn/riZlWua6txUuf1cjQ7bIf2hJjnwaHZZMuVLa98H8nxZc/tdOuU+3eqcF7XYMGl
o
>
tmEohy0t5WC7dEyiBCs+IzaUwxOhT5Urldy3WKJSqxXSt5pEn+r24cDm5meWtj5V1FQBpsO/ke2
1
>
5j5V7lvk/96Wfavy4kIl70pHslhh53gCAGwoNAXDPCL3qZZuB9VD83SHr2q00KAiWDX/L3AeMZc
G
>
KIctLeVgu3pMwoIVnxEbyuGJPVDpBl8JYvCQ3Gs2ZG4e6lsAANsHNVaII3Kotu6r4T8yRHs1OtW
j
>
gfi6uAAA2wzBClFFCNU83ZYdp/fpjE9xyd+W/ajupOXFgUNO6TYGKW0wjNyzoRyTcEzsYMXxsKE
c
>
nkg11XyzT/VBizrqL2r26+TND1Og8zmvOAQAsElQY4VZIjb/qisUja9GlCnTpXu1onknKN8i8lz
X
>
gCWN+AuBvxgAYD4IVpgm9kAlmKROL5pcNgVG7tlQjkk4JjaeiCINwYr3xZaGcoSEKl9EP7j2Fbz
M
>
cUUlAIANhhorBEFNFQBgTghW8AsJ1YCZadSllKjtXy8XXKJwk2Hkng3lmIRjYjPLsc5gxftiS0M
5
>
UFPdIfwPH4OUAACWB6EKALAgNAODa72hKudUDRvsZE83d+TOrWqQ86JWogyR4oFXR2RuQs2p6m7
f
>
vk9NIRdy3xbCyD0byjEJx8QWVI51BCveF1sayrG+UOXgkvOYqn5ZOb/p0dn4msLdSo5qh95sODy
3
>
qpufPBUdB16u1lMrZuhWivaUdSLMc7VDr3+4fUi1E3ffIoDl/K3GfTmMbgaA2VBjhbWF6vCiQ71
S
>
dTwxeKZcpVKvQxecbCJwGy2H6nfc4U9q4JR74aZ8UwVen2fImYFrpI1sXU1R58o3xfONwVU3suS
4
>
M+0MH9KAHMq6c9nJyzIO6OGG11bRnwqwGgjW3ZaiPtUblHV6dMXJdn1FPadAx4teqkmE80mnQOf
l
>
m3pFMBnw7pywmTJVSz3qyHTnTTSoZYT/NsLIPRvKMQnHxDarHKsKVrwvtjSUIyRUAy7+UOQG1BY
V
>
/evlEr95NHNcIKfV8PorhxfU6fGsckNRWRzIVRe6mZeXSF2nliGdnXSocD7lMoq67zRXI6obj+O
a
>
cPUqJ/ebu6rSCNc2BoCYUGPdTXuj0eixvm3gUPX1Q07F569OP1eVm2HdPlCn3lfXEeaBSjKseWV
J
>
bKVFg0KfzulEPrbU1k2+HH45EZD9S6vGKLcZEnp834nYkrpeMb+eBmV9zx+zts8DpHJ0VdX7lmW
k
>
wNfHoTsLN1Oz07MWPfvM0/I2419UbpOs2blu/tJKcv2tW7fkpdWWtX0X1itYr2A9yX97ZtfLqvb
L
>
sF4x17NXX3+L7pStTkHa398X69+ge3dfpn6/r9fGFxKq62CEGYkga2Spb1ysnwcnNbI6jLXwUFX
b
>
ChrHNA50n/H2b57Swf3b1jaD9h0Fh64Zqvfuvihvu1bZzzltX/zh83/o1gHlsKWlHAzHxBa3HMv
6
>
t473xRa1HMsM1fT0qcrmXz1AyBw4NBc1qw4HmlraohbsyJHGwcE4JN3irJqeBw/1SODtsMrwBoB
J
>
/O+P/x3C9gvvUzVOb4mHa4kR+ljlOare47qnNW80cOaYCk6LGm6H61CNBi4sPHJJ4Rqu1Q/cPRW
1
>
WrV92dfrjkJmCe8bAHYTgnU3TKmpdujkQA8UijBKyD139ODgRE9mPkO+qc5N1fsoDurUHze5ck1
T
>
nZsqtynPGw3pDzXJgUezAz1TvrT2fSDPl9Xb57li5bmp+r6o+95gaWi2YSiHLS3lYDgmtnnLkXS
w
>
4n2xpaEc4X2qcvCOqD3y7VKJSq3W1IFLpXabqMiDm7iZdbtDKCoO5TT0qaL5FyBd8G9yvdbTp8o
1
>
NrdP8jafTDOLO7MNAjVN8I8XIH2SrrFCekQbqCSvQOQO+gleAs5qgQ3BI+bSAOWwpaUcDMfElkQ
5
>
kghWvC+2NJQjPaN/AQB2DGqs2wehCgAAkBCEKmDkng/KMQnHxJZkORapreJ9saWhHAjVLYZBSgC
b
>
Ac3A2yNCqKqL68e/oP3ukOezBiwAAFEhWLdD5Jpqq+iGRfwZabZd0GhoXjYFRu7ZUI5JOCa2ZZU
j
>
brDifbGloRxzNP8a07/NfSlDAAAI4gbr3t6nxgtsjgih6l7UQSxt+woU1KtRTgfs0XhiVAAAWMx
j
>
evDgnfGCYN0c8Wqq5kUgfAHbc6/Ti87XVIgzSAkj92woxyQcExvKYUM5PPFCVc4so5t+3cnF/Vp
F
>
BCsAAOykCKGqRv8GBqlTp75bczVrr637GMwEADCnx49/RLdufW688N+wGeYYqFSithuil2Wyrp3
P
>
zcP+ftdpzJrvxKhinpfVvS+4z1bOixqpVsw/DI7I3ISaU9Xdvn3f9HJtH4zcs6Eck3BMbKsoBwe
p
>
u4SNCMb7YktDOSKHaqnt1kiblMi183lqOTmPqdqunN/UGE3creSodtjW+1Rzq7r56c7dmqvJiel
m
>
6lZ4SjqDCM1c7dD7ccDzp57ofc8o1yaI058KAOmHc1g3R4RQVaN/I89CIwczzQ7e4UWHeqXqeJq
4
>
TLlKpV6HLji9RLA1Wg7V77hbscuQb7qB56gVU3CNtJGti/q1wV/GG1lyeld0LW5OLRcAAMAU8fp
U
>
Iyzzj1G6QVmnR1ecbNdX1HMKdLzovKwinE86BTov39QrgskgdbKiBEGMcm0pjNyzoRyTcExs6yh
H
>
UG0V74stDeWYo091Or7yUpRzVjPHBXJaDa8vc3hBnR7R4OGQhg8HctWFbuadL6yHdHbSocK5r9/
X
>
xE29Ytu5GlFdP25auQAA1gnNwOm3NxqNHuvbIbimWqQWj/T1D0ziUBKJ1HPvc/+Wg5nsJmBuhnX
7
>
QJ16ny65fZUHBLkjip2SeFaLBoU+ndOJfCz348omX7ldEZD9y3GzLJPbvKrSKKBtmu87EVuS+5G
v
>
oUFZ3/PH/NsPKZfalofDfhZupmanZy169pmn5W3Gv6jcvk+zc938pTXv+lu3bll9qklvn2G9gvU
K
>
1iurWs/fHQ8ePJC32ar2yzZ9PXv19bfoTtkeVLu/vy/Wv0H37r5M/X5fr40vcqiKlAzsV1VhyYN
+
>
dIjKQOKHxx3QxKN9c3RVFfshsY1G1gpxHpzUyNrBFh6qaltB45jGge4TtH3FKFe8FyRD1wzVe3d
f
>
lLddbqgmaZ5t8ofP/6FbB5TDlpZyMBwT27rLYf4gx/HwRC3HrFB99OiRXhtf5ObfsObPzM1DfUt
x
>
m25jk82sDmW5Y9MYODSfDJUv9cheubRFbdORI3qDApWDM7TYZrkAAFKAA5WDFdInQqjyQB11GcK
J
>
fk1uNuVmUj3IZ9zEGzroxyDPBfXOAe2e1rxRt5ljKjgtargdm2I/PBq4sPDIJYXLaZ1/2j0VtVq
9
>
/WnlAgBICQ5W7uqBdIkQqqLWd14X9Txz+je9yP5TolLV7GstUdvf9xok31TngOptFQd16o/bV7m
m
>
qc5Ndfdz2A7pDzVxyEe4WEOmfGnt+0Cel6q3P7Vc2ykNzTYM5bClpRwMx8SWpvcmDfC+eCL0qbr
0
>
gCX9l8JNqhHCbkdxKK+yT3UZfbQAkG74dx9fKvpU3QsweP2UvCBQAQDWCf2r6RIhVNXFHzBf6vb
i
>
EXNpgHLY0lIOhmNiQzlsKIcnRk0VAADSCLXV9Igx+vfEnskFAABSA8GaDhFC9Zqu5EUUelTL6dG
y
>
E8v2T4+WdosMVsDIPRvKMQnHxIZy2FAOD5p/ExD8Q2P2JQwBAJKE2ur6RQjVoFG//iXuJQm3S/A
x
>
UafSAACsEoJ1vVBTBYzc80E5JuGY2NJejlUHK94XT/RQlVcr0k2bR2fEY5b4IvQH8edkAwAA2Er
R
>
QpWvh6svSTjpPp1hWPBaLTJICQC2E5qB1yNCqA7prMEXJ1SzvPTrfBVgJd/sU33QolrtFKN/Nxh
G
>
7tlQjkk4JrZNKceqghXviydCqKpTapz6ecAlCTNUrtrXTwQAANhVCw9Umnv+VCanWXNPQfGf68q
T
>
g7v3BV8mUU7hFqlPly+1eBRy8YqA+6xyHUxOeQcAsCHQDLxaEUI1fD7VWPOn+vHAJznlmjr9RE6
3
>
pgdAsW4lR7XDtj49RU0D5+5fDpASYSf3HUG34p9dxzN5nwjZYotKbX1qTLtErWJ6L26RRH8qRu7
Z
>
UI5JOCa2TSvHsoMV74snQqh6Tbw8n6oMsl6Nckao2fOpRjO86FiTf2fKVSr1OnTBqSoClyclr99
x
>
z35V58q605rmm24Qe/27YTj4G9k6BTVSB943fEgDseb2eNe3xV8DehhYywUAAPBEa/7NN2VtcTK
Y
>
StQ2wm4xXCPu0dW1uHl9RT2nQMeLTisnwvmkU6Dz8k29whB2n9y3WfM2ygUAsKHQDLwaMfpUg66
s
>
NP+VlDLHBXJaDa8vc3hBHVHxHYgqodtPe6Gbeefr1xzS2UmHCudBtejw++S+D28a6zN081CVa1t
h
>
5J4N5ZiEY2Lb1HIsK1jxvnj2RDg+1reXatz/Kjj1Pl1yuy8PCCrqHk2nJOq9LRoU+nROJ/Kx3K8
p
>
a8GiVnmUEyHYtydFl9u8qtIooKrM952ILcn9yMFIDcrq58+6z79N7sNtZHWZDRz2s/CPD3Z61qJ
n
>
n3la3mb85rv9oWY/gPmhiLL+1q1b4z7VRbaD9QrWK1ivbON68zuDrWq/LA3r2auvv0V3ynbb6/7
+
>
vlj/Bt27+zI9evRIr40vYqjySNwchY8L4mbgRa//q/ZxVRVBSiJsG1nqX3o1yaBgCw/V8PI69TY
V
>
OsWQ+8T2b5769m2UK+YL5NA1Q/Xe3Rflbdeig4wWfT4A7KZd/+5YZqhGav5VI3G5JrlEsvnXoSx
3
>
Zt7IktO7ovm7MTNUvjSbqbk/WF284rKcn3KfiNGJffN5urpcW8r8RbdOKIctLeVgOCa2TS8HB2q
S
>
zcB4XzwRQrVL92UL7e0ps9XMUUuV54J6p6p0T2veaODMMRWcFjXcDtehGg1cWHjkUgSZm3RILbo
/
>
Lth98dch3VzBrgEAViXpYAUl8kCl0vgck4Tkm+rcVD0QqTioU3/cvso1TXVuqhyolKvRYdvuTw3
E
>
fa8LT5iep6Y8N1UPkpLnrO721HYAABBNhD5VHshTpFapHTggCMIts08V/akAkIRd/C5Zc59qnm7
z
>
vs3TXwAAYCugGThZMfpUe1TL6SbRiSW9l/EDAABYlch9qrC9MHLPhnJMwjGxbVs5Fq2t4n3xRGr
+
>
DR/16y4YyAMAsMnQDJwM1FQ3EAYpAQCkU0io8ojfiNfb9Z1vCpvHfwmvdUE5bGkpB8MxsW1rOea
t
>
reJ98USvqcpzQMMm+t5twYO3Zl8XGAAgbdAMvBg0/yYguJ9ZnZ8KALBpEKzzQ6gCRu75oByTcEx
s
>
KIcN5fAgVDcMBikBwCqgtjofhCoAAARCsMaHUAWM3PNBOSbhmNhQDhvK4UGoAgBAKNRW45kaquP
p
>
z3jJ1agXdP3forww8HzkOa7utvznug7p7Mjbz1HAuTzDsyM6iHYyLVVCTwcKvy/69lcD/akAsA4
I
>
1ujWV1Pl816LA6r31ekncm7VozMRpUq3kqPaYVufnqLmVnXzrVtRQZur9dSKGbqVIoVFf9B9cbe
/
>
6TByz4ZyTMIxsaEcNpTDExKqUa73ay7xr/07vOhQr1QdTzyeKVep1OvQBaeqCNxGy6H6HXerqjz
u
>
dK75ptpvv+6oFVNwbbORrZM9c54Sdl+c7QMA7ALUVqNJUZ/qDco6Pbq6Fjevr6jnFOhYB+7cRDi
f
>
dAp0Xr6pVxim3QcAABMQrLOtLVQzxwVyzInPhxfU6RENHg5p+HAgV13oZlhe4ndtDunspEOF8zJ
N
>
ZvO0+3YPRu7ZUI5JOCY2lMOGcnj2RqPRY317qbip1e2jdOp9uuR2Xx6o5A50ckpUohYNCn06pxP
5
>
2FJbN/ly/2tOhGD/ctxczOQ2r6o0ctuFDXzfidiS3I8cjNSgrH7+tPtM07bPOOxn4WZkdnrWome
f
>
eVreZvzmuwOPzH4A80Nhrr9169Z4kFKUx2O9gvUK1itYryy6nr+PHjx4sPL9uhZZz159/S26U7Y
7
>
/vb398X6N+je3Zfp0aNHem18KwvV2Xi0b46uqiJISYRtI0v9S68myYOHGlkdxlp46KltBY0zcup
t
>
KnSKIfdF3X40HLpmqN67+6K87YozmjfOYwEAlm2Tv5OWGarp6VOVzb8OZW+I2zey5PSuiLtX55O
h
>
8qU5kKotasGOHGl8Wc5Puc9XVd0R5i+6dUI5bGkpB8MxsaEcdv8qjodnfaHqm4e1e1rzRgNnjqn
g
>
tKjhdrjq0cCFhUcuAQAALE9IqKpJyt1BQrOXOSYpzzfVual6G8VBnfrjZlauaapzU+X2czU6bE/
2
>
eU7gvtctnDAdTb8AkEZmbRWUkD5VDtXwCyZMKlF7jnNVtx3/IOAmZrZInypCFQDSbG/vU/oWB+2
P
>
9K30WkOf6vIv/gAAAJuPA/XBg3fGixmwuyg9A5UAAAA2XMRQtS9uP7lsXz/mLsHIPRvKMQnHxIZ
y
>
pFMajkekUFUXt+eLM8CqoT8VANKM+1Bv3frceNmEPtVlihCqXbovRyzdlv2sbU7Wkjd7jAxaJ0t
8
>
eikAAOwe7kvlMN31QGWR+1RLt4OGIuXpDs/kstCFGmDd/JfwWheUw5aWcjAcExvKYUM5PLEHKt3
I
>
ihAdPCT3OviZm4f61u4K7meefV1gAADYLpFDtXVfDUWSIdqr0akemdRVbcM7bfIUI7UsCv2pAAC
b
>
JUKo5um27Di9T2d82cD8bdmP2iqq2lhx4JBTuo3zVDcYRjLaUI5JOCY2lMOGcngi1VTzzT7VBy3
q
>
qL+o2a+TI2+zAp3POYsLAADANonY/KtmfRnP4pIp06XbzGlMzwYAALDLIoSqurh+BVd32FoYuWd
D
>
OSbhmNhQDhvK4Yk8UCmUnBnmiNxZ2iAZGKQEALB5poSqO/2bmq3GHZg0seRq1FNPiE/Oqepuy3+
p
>
Q/vSiEcBqT08O6KDSFVofi1hwR9wn/yh4O0btXQAAIhi8ZoqcwoUe/5wDq7igOp91Tcr51Y9Ohu
f
>
/6oujehduYnnVnXDrVtRYZerRYvzbiV8GrvJ+0TIyvlbdZ9xv06D4nbXxDFyz4ZyTMIxsaEcNpT
D
>
MyVU3enf1KUIS27IBC1zDFYaXnSoV6qOJx7PlKtU6nXogsNLBG6j5VD9jjuqWJXFHWScb6r99vl
q
>
TjNwbbaRrQdetzjovuFZg1pOnca7zhxTwenRFS4ZBQAAMyRTU03EDcq64XV9Rb15ar9+IpxPOgU
6
>
L9/UKwwh92XKl74fCdd0NXf7NgAA7JIIoWrXEpOSOS6Q02p4zarDC+qI8Bo8HNLw4UCuutDNvPP
1
>
aw7p7KRDhfOgWvS0+2yy5irqsoGXPl6SVQ9Swsg9G8oxCcfEhnLYUA7P3mg0eqxvT8d9oBODkhy
q
>
9y/HTbjTcFOr2wfq1PvqnFceqFTUPZoOTy3XokGhT+d0Ih/LTc4yzOW+RQj69iW3eVWlUUDi830
n
>
Ykvq3FoejNSgrH7+tPsssnzc7xv8GjnsZ+FmanZ61qJnn3la3mb85rvhafYDTFvvwnoF6xWsV7B
e
>
wXolbD179fW36E7Z7hTc398X69+ge3dfpkePHum18UULVTP8AozDbyE82jdHV1WxLRL7a2SpbzT
D
>
8uCkRlaHsRYeqmpbQeOYnHqbCp1iyH3e9tWPAIr8oyEIh64Zqvfuvihvu8JqpDidBgBgeZYZqhG
a
>
f0VANVSgTgxWkpOrErUa3qjducnmX4eyPDHrjSw5C00np64A5ZWVB1txrZqvCpWfcl9ygbpJzF9
0
>
64Ry2NJSDoZjYkM5bCiHJ0KoqoE6XIubqBDmm2oE7jwBKM9R9c5N7Z7WvNHAcsRtixpuh+tQjQY
u
>
LDxyKQJRrnUGKmqpAACba32jf2UgD6ioByIVB3Xqj1Oba5rq3FQ5UEmeNxoh5LjvdeIiEvGoqex
6
>
VMt5g6R4Cbr4BAAAgClCn6rXPznRd+r2tToiEHFh/QkcxtzEzKL2qaKmCgCwXGvuUxW1xqruO/V
f
>
qlAPXipVEagAAADRmn/zTXm5vsnrF6kBPouP/AUAANh80ftUzTlUx8tujI5dlXU1/WLkng3lmIR
j
>
YkM5bCiHJyRU+YIImJ0FAAAgjvWN/gUAANgyCFWYuITXuqActrSUg+GY2FAOG8rhQagmwBoRbSx
x
>
4FQaAIDNNzVUJ06hCV0Wu+DCprMHb3kLAADsFtRUASP3fFCOSTgmNpTDhnJ4pobqxAX0Q5cm4VR
V
>
AADYdaipAgAAJAShmgLrHqSEkXs2lGMSjokN5bChHB6EKgAAQEJCQjVPzdEKrukr51QNG0HMs+N
4
>
I4yDpl7jycQPIl32ia8QdUTBs7dN3ie3Oy5X2PMAAABs66up8tynxYG8ID8PdpJzqx6diShVupU
c
>
1Q7beiCUmlvVzc9uRQVejueji6BbKZKaT2fSxH1ykvJDaruDsNqHVDvxyrWNMHLPhnJMwjGxoRw
2
>
lMOztlAdXnSoV6qOL8ifKVep1OvQBaeXCNxGy6H6HbeqbNec8003iCfnzfHjWmcjWyd75jwl8D6
e
>
kccczXwjS07viq71nwAAAGFS1Kd6g7JOj644va6vqOcU6HjRGXBEOJ90CnRevqlXGKbdZ5Dh72R
F
>
6ZYDV1ICANgeawvVzHGBnFbD668cXlCnRzR4OKThw4FcdaGbeXmJP2POkM5OOlQ4D5pAfdp9Gjd
P
>
yyZmovq0x20BjNyzoRyTcExsKIcN5fDsjUajx/r2UnFTq9sH6tT7dMntvjxQqah7NJ0SlahFg0K
f
>
zulEPpYvPiGbfDngciIE+/b8rXKbV1UaBYyo4vtOxJbkfuRgpAZl9fOn3TchZN+Mw34WbqZmp2c
t
>
evaZp+Vtxm8+11LZgwcP5H+Z+aEw+wewXsF6BesVrFewXomynr36+lt0p2x3Cu7v74v1b9C9uy/
T
>
o0eP9Nr4Vhaqs/Fo3xxdVUWQkgjbRpb6l14NkQcnNbI6jLXwUFXbChrH5NTbVOgUQ+6zt+8K2nc
U
>
HLpmqN67+6K87XJDFc2/AACrs8xQTU+fqmz+dSjLnZcLDw7KUPlSj96VS1vUgh050viynJ9yX1B
o
>
Dkm3Ridqb+9T4v/598z6f9OYv+jWCeWwpaUcDMfEhnLYUA7P+kJVnqPqnZvaPa15o4Ezx1RwWtR
w
>
O1yHajRwYeGRS7Nx7dc6Z7Z7Kmq1ye6bA/XBg3fGiwpYAADYdOsL1XxTnZuqByIVB3Xqj5txuaa
p
>
zk2VA5VyNTpsh/R5muTgosWmocuUL61yHchzaSPsGwAAdl6K+lS3T1ifqltTdd269Tl6/PhH+i8
A
>
AFim3ehT3SEcoByk7oJABQDYDgjVNeEgdRcAANgOCNU1wog5G8phS0s5GI6JDeWwoRwehCoAAEB
C
>
EKoAAAAJQaiukf/SWeuCcthQjkk4JjaUw4ZyeBCqCZDnswYsAACwWxCqCfAueWgvAACwWxCqa4Q
R
>
czaUw5aWcjAcExvKYUM5PAhVAACAhCBUAQAAEoJQXSOMmLOhHLa0lIPhmNhQDhvK4UGoAgAAJGS
9
>
oSrnVHVPQfFP2TaksyPv9JQjd25Vg5z7tBJlorcuVQ6OKGATwrz3AQAA2NYXqjz3qZyrVJ1+Iuc
w
>
PToTUap0KzmqHbb16SlqblU3P7sVFbS5Wk+tmKFbKVJL3/ab974kYMScDeWwpaUcDMfEhnLYUA7
P
>
2kJ1eNGhXqk6nvw7U65SqdehC05VEbiNlkP1O+6k5XlqinB15zDPN90gdtSKKbg228jWyZ45T5n
3
>
PgAAgCAp6lO9QVmnR1fX4ub1FfWcAh3rwJ2bCOeTToHOyzf1CsO89wEAAIRYW6hmjgvktBpef+X
w
>
gjo9osHDIQ0fDuSqC93My0ukrlPLkM5OOlQ4L9NkNs97X7IwYs6GctjSUg6GY2JDOWwoh2dvNBo
9
>
1reXiptT3T5Qp96nS2735YFKRd1r6ZSoRC0aFPp0TifysaW2bvIVNcejnAi6/uW4uZjJbV5VaeS
2
>
Cxv4vhOxJbkfOeCoQVn9/Hnv8+Own8W9XOHpWYuefeZpeZuZb77ZD4D1CtYrWK9gvYL1yiLr2au
v
>
v0V3ynbn3v7+vlj/Bt27+zI9evRIr41vZaE6G4/2zdFVVQQpibBtZKl/6dUWeXBSI6vDWAsPVbW
t
>
oHFMTr1NhU5xjvvsfcfFoXrv7ov6LwAAWJdlhmp6+lRl869D2Rvi9o0sOb0r4u7V+WSofOld2J5
H
>
D5fIkSONL8v5Oe+bP1DDmL+k1gnlsKEck3BMbCiHDeXwrC9U5Tmq3rmp3dOaNxo4c0wFp0UNt8N
1
>
qEYDFxYeuQQAALA86wvVfFOdm6oHIhUHdeqPm3G5pqnOTZUDlXI1OmwH92tauO914iISAAAAq5G
i
>
PtXthj5VAIB02JGBStuNQxUAANIBoQoAALAk2zf6FwAAYMOhprpGUS4eAQAA0fHpkPNA8+8W4FC
d
>
9QGY9Rhsw4Zt2JLYBtuUsmIbNmwjOjT/AgAApAxCFQAAICEIVQAAgIQgVFNu3v4BE7ZhwzZs2IY
N
>
27Bt0zZWAaEKAACQEITqhkvLrzeUw4ZyTMIxsaEctjR9VheBUAUAAEgIQnWN8AvRhnLY0vTLHcf
E
>
hnLYUA4PQhUAACAhCFUAAICEIFQBAAASglBdtm5FXo/SXSpdvd4v6uPmFXX7wzM6ivK4ecV+nV2
q
>
HBzR2VD/mZTI5RjS2ZH3uKOkCzLX+7KE42EYnh3RwbQ3ZtmfVW1mOZb9WdVmlmNsSZ9VbXY5lvx
Z
>
1eK9L0s4HlHf9xV9Tv0Qqksl/pEVW1Rqj2QH+qhdolaxItb6RX3cvGKUI1ejQ/dx/ToNikn+o4j
/
>
OruVIiU/vXv0cnQrOaodttXjRm06rOUS/Mc55/vSPqRaLsnPh9KtqC+fXK2n1wSJ/x7GFbkcS/2
s
>
Ri2HZzmf1ejlWO5nNWo5lv1Zjfq+L/9zGgahukzDhzSgEt3O67/zt8VfA3ro/wBEfdy8Im5/eNa
g
>
llOnO+7jMsdUcHp0da3/XlTM18m/iBvZunhMwiK/L2fUaDlUHx+QPDXFP9Cm++eiYn0+HMre0H8
n
>
/fnQ8k31BdSvO3pNgJjv4TyilGPpn1Uh0vHQlvZZFaK9L0v+rArRPx/L+6xGft9X8DkNg1Bdpus
r
>
6jlZcj9fJG5lgz4AUR83r4jbz5QvaXRZpoz+WzyRrqL9SI8mzusUXxInnQKdl2/qFQmK9b4U6Ng
7
>
IMmKWo5MmaqlHnUu1DeC/GIpVam8rHJNE+c9XKKlf1bjWOZnNaplf1ajWvJnNfL7vsbPKUJ1iYY
P
>
B0SHN40PQIZuHhINfD+Xoj5uXvNuX/6DMH/tLSh6OYZ0dtKhwrn5jyc5sd4X4UI3e/GSZHNanPe
F
>
awnVq5xqfruq0ijJKkgM836Wli3pz2p0y/2sRrXsz2ocq/yshr3v6/ycIlQhWLdCuRpRvd+kVX9
P
>
Dc9OqFM4X09NzK9Xo6vbqtlrGf120agBKPfdcty+L76wVtM/tBHwWVV27bO6xvd9GoTqEmXUTyP
x
>
MXMNSf2Asv8FRn3cvOJuX47uKw7Eh/Uy0S+LaOUY0kWnJ74f1C/dgwMe/NGjWi650Yyx3her/8Z
u
>
2lpU5PeleyoHoIx/8Oeb1C61qLH6b8zYn6VlW9ZnNZrlf1ajWvZnNbIVfVZnve/r/JwiVJfpRpa
c
>
3hV5zfjc/m904ruiPm5eMbbPH1b1628JX1KRypGh8qX+lSuXNpXIEeUZ0WVSBZr7fUlYxHLIpiz
r
>
C2KNYnyWlm2pn9VIVvBZjWrZn9WIVvFZjfS+r/FzilBdpsxNOhS/Xe+7bR/d++KvQ5r4sRT1cfO
K
>
uv1xc8qSvqSW/Tqjivy+8MhC41f2UI2wLCQ1GiRiOTLHBfEF0aFxpSPpcsSRlvdw2Z/VTbPsz2p
E
>
S/+sRn3f1/g5RaguVZ6a8vwoPXhAnjel2//Fh+1o3Ncw5XGJiFaO7n0+y041X6nmLLUk15QV9Xg
s
>
W9RycE1Ene8nHyf+NR+2k/wSj1iOTJku5fl++nGJl2OGlX5Wp1jpZ3WKlX5Wp1jpZ3WKFX5Wp77
v
>
Kfmc7o1Go8f6NgAAwE7a39+nV19/g+7dfZkePXqk18aHmioAAEBCEKoAAAAJQagCAAAkBKEKAAC
Q
>
EIQqAABAQhCqAAAACUGoAgAAJAShCgAAkBCEKixJlyrm1U7ikldHUc+fPYXVgvuaKrlty4uA622
F
>
Lkdn67/Gb+CxX+YxjqBbsY/TOssSyn+MVnDMYv07gVVAqMIWyFNTX9Q8+QuZL2PbJWrrbXoLX4x
d
>
6NUol4ZgnbDMYzxdl+cILfLl6dTF6s3jJWeISeXxYus7ZrA+CFWAVFDXKpVEsJ6i1qGIGqrMUxm
o
>
5jVkObC8HyInqaqxwi5DqMIKqQmM3aY7/zJuvuImrVyNevpPeVFseWfI8ysVXzNbxP1IXhOdtYw
f
>
FNKEF9QcuWiNiaer0jctgU2f/gu6h7wOsUw0C04re+ixj3EcrLLFeS/8xHMbMlFF5b4acFH2PN1
2
>
f4d0LrxjH+l4CfOW3S30xPN5PlWT/5gl8LkUy/hxoe+VFvU4QKIQqrA+pbZqytM1tFbxiOR3D89
0
>
0a+PA6bUFo8Zz3rskev5+c3bek2IsP3ILy79Reg+xq39tIr2F5RBTZCsvj5VGfpU58Iu2nR7faW
/
>
IL15Hyf3NSL1MlpUPJj2OkbUl4UyX2+Eskc89ixa2XxC34sAwwvq6MQo3Q4uQ76p9ju6LBNnbtQ
y
>
zVN293F8PLzne03S+iVFF+tzGfB+Tnmv5npvIBEIVVgP/rJwv6zzt1WQiUjpjCdinEE8P+S73jZ
t
>
P8OHNJB/i4eNv7S9frDgMOnSaU1HX72vy5Ch8rn+cpu76VZ8keovQa9W5u3LfL35pg5C8Tpqcmf
B
>
Zc6Uq77jmmTZg7YVVDbDou/5TFHLNF/Z3cfZzz8f16DzTf2DLIqpxyLq+xnGK9/0zw0sA0IVdpe
c
>
yFhR8y5GaBqTkx0z38TLXGvQX4TG92AIri34m+VUzcSsbXj7EuutmlqGjgvy21Fs6v7sMrsSKbs
W
>
tq15y5aEqGVatOzjH2P+56dE0p8biAWhCjtM1Qi8Zjsz7JbZ9+Qb/Ws04bWKwfsdT7asl5xbEzH
I
>
Jj/jMZN9fJCIcTP9ciXxfkb53ECyEKqw88b9cryME1YE7KpO1bD6xlrUmOjwMk8l8S9N8dNADYB
R
>
X5hmYMdojkyjzDF5FavgnzjydBsOjFW9VyuR1Ps563MDy4BQBTDlm+MBIdS7omt1yxPWF7joSfh
G
>
gIxHsob2OxqjSDlMuqekKiD8JTrlyzLJsk8p24U3umjBL+4Mlas6RlqNgME1Xbqvq25O4ZgyUcu
0
>
aNlDn5+QqO9nmCmvz/rc6LWQLIQqpN7g4ZL++RunHHhhYg7yCPpizdMdHbp84QH1PPFldaJPbXD
q
>
dGeuJDECpNch9V0YtC+xt7MT/aUrilgtU2Z8Ko75JcpfoP7mwvhlDz/2wWXrVnJeIMx3IGziR45
q
>
POhRLWeOWjVGyIpyn8vRQlHLtGjZzeefTI7YXVTk99PmvVfBr2/ic6NuQsIQqpBOmTKNM0Z8MSz
l
>
l7X4wvZOZ9C/4PUXI48KNUdemjLlS9/z9Jex+HLv61M75mLUMGon6vXKfemmYbeMqlmQazF6YJH
R
>
fCyPlXwdbkDYIpU94rGf3NaBvlADN1maF2pYjGyel/vhYFX7sd4n45hHLdOiZefnqxYNt0wJBSq
L
>
8X7yY4PeK/n6Zn1uYCn2RqPRY30bAABgJ+3v79Orr79B9+6+TI8ePdJrlUqlQs1mU//lCVqPmio
A
>
AMAMHKAm/98uhCoAAEAEbpCGBSpDqAIAAExhNvGagRrUJIxQBQAAmMEfoEGByhCqAAAAEbhBGha
o
>
DKEKAAAQ0bRAZQhVAACAhCBUAQAAEoJQBQAASAhCFQAAICF7/7LexGUKAQAAEoBr/wIAACQEzb8
A
>
AAAJQagCAAAkBKEKAACQEIQqAABAQhCqAAAACUGoAgAAJAShCgAAYPirv/orfSs+hCoAAEBCcPE
H
>
AADYSH/8x3+sbyXjV37lV+R/uab6cz/3c/J2XAhVAADYSByqn/nMZ/Rfk9pv/y/00U8+pI8++kg
u
>
H3/8CZ38xpv6XtsPfvCDREIVzb8AALB1/u9/8z/Tf/vPivSrJ1+mUvnL4r//hP5J6b+m/+3r/1Q
/
>
YjkQqgAAsFX+r7f+JxGo/5g++UTUTj/6kD75+Cf0k7//j3J5/vl/SK9Wi/qRyUOoAgDAVvnJT0S
I
>
ymbfn9DzX25Q4R//JhX/u2/Sj//uP9Lf/+j/o+//v3+jH5k8hCoAAGyVjz76mD7+mJdP6Kc//Sn
9
>
4R/+IT3z6Z+hD0Wo/vjvHsn+1WVBqAIAwFb5Z5V/TV+t/C79D+Vv0R/8wR/Qb9b+Gyr96j+iD3/
8
>
NzJUP/nkE/3I5CFUAQBg67z11lv0e7/3e/R//KtfpRde+Bz95MO/pQ9/9Lf0td8c0DvvvKMflTy
E
>
KgAAbKXf/de/Tr/6T5+ljz/8O/r4x/+JKv/re/T9739f37scCFUAANhKP/MzIuL2iB4/fkwff/x
T
>
vXa5EKoAALCl9uijD/9WLh+LZRUQqgAAsJX++5ebdOfrPfofv/Hv6Z//1gf0J3/yJ/qe5UGoAgD
A
>
Vvo3//uv0+v/4r+g11/+z+lfnfwDunXrlr4nWX/2Z38mF4ZQBQCArcTnqX74o7+hH//ob+nDv/9
P
>
eu1yIVQBAGArfSRC9ccffkI/+ein9NEne2rg0hL80i/9klwYQhUAALbSr7/yLfrGt/4Dvfq7P6b
G
>
//mf0Xe/+119z+LMJl80/wIAwE5ot9v0ne98h7rdrl6zXAhVAACAmMwmX/M2JikHAICNxJOUJ2n
W
>
JOVuEy8HaNhthCoAAIABoQoAAJAC6FMFAABIyN4H7RdRUwUAAFgY0f8Pv2raZV7mqO4AAAAASUV
O
> RK5CYII=
> --001a113d6a0a1ede02053654edd6--
>
>



E-mail to subscribers: CHEMISTRY_._ccl.net or use:
      http://www.ccl.net/cgi-bin/ccl/send_ccl_message

E-mail to administrators: CHEMISTRY-REQUEST_._ccl.net or use
      http://www.ccl.net/cgi-bin/ccl/send_ccl_message

Subscribe/Unsubscribe:
      http://www.ccl.net/chemistry/sub_unsub.shtml

Before posting, check wait time at: http://www.ccl.net

Job: http://www.ccl.net/jobs
Conferences: http://server.ccl.net/chemistry/announcements/conferences/

Search Messages: http://www.ccl.net/chemistry/searchccl/index.shtml
      http://www.ccl.net/spammers.txt

RTFI: http://www.ccl.net/chemistry/aboutccl/instructions/





--
A GENTLE WORD, A KIND LOOK, A GOOD-NATURED SMILE CAN WORK WONDERS AND ACCOMPLISH
             ---------------------------
                Venkata Pera Reddy B.
                Research scholar
                Dept. of Chemistry
                National Institute of Technology
                Durgapur-713209,W.B, India

--------------1EAAEFE951C29BA91A07A9DF--