{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":87793,"databundleVersionId":11228175,"sourceType":"competition"},{"sourceId":238135,"sourceType":"modelInstanceVersion","isSourceIdPinned":true,"modelInstanceId":203383,"modelId":225112}],"dockerImageVersionId":30918,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"## RNA Structural Intelligence (RSI) - Version 0.1\n\n### Changelog & Overview\n\n**Version 0.1** represents the **first structured attempt** at modeling RNA **secondary structures** using **relational intelligence** principles. This approach treats RNA **not just as a sequence**, but as a **dynamic, interconnected system**, allowing us to:\n\n- Construct **graph-based representations** of RNA structures.\n- Identify **secondary structure elements** (stems, loops, bulges, etc.).\n- **Visualize 3D relationships** between nucleotides.\n- Lay the foundation for **tertiary interactions and stacking analysis**.\n\nAt its core, this isn’t just about **RNA structure prediction**—it’s about applying **relational intelligence** to complex, **biological networks**.\n\n### Roadmap: Next Steps & Open Challenges\n\n1. **Refine Secondary Structure Detection**\n   - Improve loop/bulge identification (account for non-canonical pairings).\n   - Validate against known RNA structural datasets (benchmarking).\n2. **Tertiary Structure Integration**\n   - Identify **coaxial stacking** & tertiary interactions.\n   - Explore the impact of **RNA folding pathways** (not just static states).\n3. **Dynamic Representation & Folding Simulation**\n   - Move beyond static graphs → explore **dynamic modeling** of RNA folding.\n   - Consider **energy landscapes** and how relational intelligence can **predict transitions**.\n4. **Collaboration & Expert Input**\n   - Seeking **bioinformatics specialists** who understand **RNA structure & folding dynamics**.\n   - Open to collaborating with **graph AI researchers** to refine relational intelligence applications.\n\n### Call for Collaboration\n\nThis is **not** a product, nor is it about financial gain. The goal is to **validate a thesis**—that relational intelligence can **provide new insights** into biological systems. If this **resonates with you**, particularly if you have a **bioinformatics background**, let’s talk. The ideal collaborator is someone who:\n\n- Understands RNA structure **(secondary & tertiary interactions)**.\n- Can challenge & refine the framework through **biological expertise**.\n- Wants to explore **graph-based reasoning** in biology.\n\nThis is an **open invitation** to explore something potentially significant. If that excites you, let’s **build & iterate together**.\n\n---\n\n![image.png](attachment:4a30c82e-34d9-4fdd-a84c-5f635290c295.png)\n![image.png](attachment:6c05554d-1a39-4063-83a9-62fc100c2a55.png)","metadata":{},"attachments":{"4a30c82e-34d9-4fdd-a84c-5f635290c295.png":{"image/png":"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"},"6c05554d-1a39-4063-83a9-62fc100c2a55.png":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAo4AAAF+CAYAAAAMdJtkAAAMPGlDQ1BJQ0MgUHJvZmlsZQAASImVVwdYU8kWnluSkEBoAQSkhN4EkRpASggt9I4gKiEJEEqMgaBiRxYVXLuogA1dFVHsNDtiZxHsfbGgoqyLBbvyJgV03Ve+d/LNvX/+OfOfM+fOLQOA2gmOSJSLqgOQJywQxwb708clp9BJvQCFPwRYARMON1/EjI4OB9CGzn+3d9ehJ7Qr9lKtf/b/V9Pg8fO5ACDREKfz8rl5EB8EAK/misQFABClvNnUApEUwwa0xDBBiBdKcaYcV0txuhzvlfnEx7IgbgNASYXDEWcCoNoJeXohNxNqqPZD7CjkCYQAqNEh9snLm8yDOA1ia+gjgliqz0j/QSfzb5rpw5ocTuYwls9FZkoBgnxRLmf6/1mO/215uZKhGJawqWSJQ2Klc4Z1u5kzOUyKVSDuE6ZHRkGsCfEHAU/mDzFKyZKEJMj9UQNuPgvWDOhA7MjjBIRBbABxkDA3MlzBp2cIgtgQwxWCThMUsOMh1oV4IT8/ME7hs0k8OVYRC23IELOYCv4cRyyLK411X5KTwFTov87isxX6mGpRVnwSxBSIzQsFiZEQq0LskJ8TF6bwGVuUxYoc8hFLYqX5m0McyxcG+8v1scIMcVCswr8sL39ovtimLAE7UoH3F2TFh8jrg7VxObL84VywTr6QmTCkw88fFz40Fx4/IFA+d+wZX5gQp9D5ICrwj5WPxSmi3GiFP27Kzw2W8qYQu+QXxinG4okFcEHK9fEMUUF0vDxPvCibExotzwdfBsIBCwQAOpDAlg4mg2wg6Ohr7IP/5D1BgAPEIBPwgb2CGRqRJOsRwmMcKAJ/QsQH+cPj/GW9fFAI+a/DrPxoDzJkvYWyETngCcR5IAzkwv8S2SjhcLRE8Bgygn9E58DGhfnmwibt//f8EPudYUImXMFIhiLS1YY8iYHEAGIIMYhog+vjPrgXHg6PfrA54QzcY2ge3/0JTwhdhIeEa4Ruwq1JgmLxT1lGgG6oH6SoRfqPtcAtoaYr7o97Q3WojOvg+sAed4FxmLgvjOwKWZYib2lV6D9p/20GP1wNhR/ZkYySR5D9yNY/j1S1VXUdVpHW+sf6yHNNH643a7jn5/isH6rPg+ewnz2xhdgB7Cx2EjuPHcEaAR07jjVh7dhRKR5eXY9lq2soWqwsnxyoI/hHvKErK61kvmOdY6/jF3lfAX+a9BkNWJNF08WCzKwCOhO+Efh0tpDrMIru5OjkCoD0/SJ/fL2Jkb03EJ3279z8PwDwPj44OHj4Oxd6HIB97vD2b/7OWTPgq0MZgHPNXIm4UM7h0gMBPiXU4J2mB4yAGbCG83ECbsAL+IFAEAqiQDxIBhNh9llwnYvBVDATzAOloBwsA6tBJdgItoAdYDfYDxrBEXASnAEXQSe4Bu7A1dMDXoB+8A58RhCEhFARGqKHGCMWiB3ihDAQHyQQCUdikWQkDclEhIgEmYnMR8qRFUglshmpRfYhzchJ5DzShdxCHiC9yGvkE4qhKqgWaohaoqNRBspEw9B4dAKaiU5Bi9ASdAm6Fq1Bd6EN6En0InoN7UZfoAMYwJQxHcwEs8cYGAuLwlKwDEyMzcbKsAqsBqvHWuB1voJ1Y33YR5yI03A6bg9XcAiegHPxKfhsfDFeie/AG/A2/Ar+AO/HvxGoBAOCHcGTwCaMI2QSphJKCRWEbYRDhNPwXuohvCMSiTpEK6I7vBeTidnEGcTFxPXEPcQTxC7iI+IAiUTSI9mRvElRJA6pgFRKWkfaRTpOukzqIX1QUlYyVnJSClJKURIqFStVKO1UOqZ0Wemp0meyOtmC7EmOIvPI08lLyVvJLeRL5B7yZ4oGxYriTYmnZFPmUdZS6imnKXcpb5SVlU2VPZRjlAXKc5XXKu9VPqf8QPmjiqaKrQpLJVVForJEZbvKCZVbKm+oVKol1Y+aQi2gLqHWUk9R71M/qNJUHVTZqjzVOapVqg2ql1VfqpHVLNSYahPVitQq1A6oXVLrUyerW6qz1Dnqs9Wr1JvVb6gPaNA0xmhEaeRpLNbYqXFe45kmSdNSM1CTp1miuUXzlOYjGkYzo7FoXNp82lbaaVqPFlHLSoutla1VrrVbq0OrX1tT20U7UXuadpX2Ue1uHUzHUoetk6uzVGe/znWdTyMMRzBH8EcsGlE/4vKI97ojdf10+bplunt0r+l+0qPrBerl6C3Xa9S7p4/r2+rH6E/V36B/Wr9vpNZIr5HckWUj94+8bYAa2BrEGsww2GLQbjBgaGQYbCgyXGd4yrDPSMfIzyjbaJXRMaNeY5qxj7HAeJXxcePndG06k55LX0tvo/ebGJiEmEhMNpt0mHw2tTJNMC023WN6z4xixjDLMFtl1mrWb25sHmE+07zO/LYF2YJhkWWxxuKsxXtLK8skywWWjZbPrHSt2FZFVnVWd62p1r7WU6xrrK/aEG0YNjk26206bVFbV9ss2yrbS3aonZudwG69XdcowiiPUcJRNaNu2KvYM+0L7evsHzjoOIQ7FDs0OrwcbT46ZfTy0WdHf3N0dcx13Op4Z4zmmNAxxWNaxrx2snXiOlU5XXWmOgc5z3Fucn7lYufCd9ngctOV5hrhusC11fWrm7ub2K3erdfd3D3Nvdr9BkOLEc1YzDjnQfDw95jjccTjo6ebZ4Hnfs+/vOy9crx2ej0bazWWP3br2Efept4c783e3T50nzSfTT7dvia+HN8a34d+Zn48v21+T5k2zGzmLuZLf0d/sf8h//csT9Ys1okALCA4oCygI1AzMCGwMvB+kGlQZlBdUH+wa/CM4BMhhJCwkOUhN9iGbC67lt0f6h46K7QtTCUsLqwy7GG4bbg4vCUCjQiNWBlxN9IiUhjZGAWi2FEro+5FW0VPiT4cQ4yJjqmKeRI7JnZm7Nk4WtykuJ1x7+L945fG30mwTpAktCaqJaYm1ia+TwpIWpHUPW70uFnjLibrJwuSm1JIKYkp21IGxgeOXz2+J9U1tTT1+gSrCdMmnJ+oPzF34tFJapM4kw6kEdKS0namfeFEcWo4A+ns9Or0fi6Lu4b7gufHW8Xr5XvzV/CfZnhnrMh4lumduTKzN8s3qyKrT8ASVApeZYdkb8x+nxOVsz1nMDcpd0+eUl5aXrNQU5gjbJtsNHna5C6RnahU1D3Fc8rqKf3iMPG2fCR/Qn5TgRb8kG+XWEt+kTwo9CmsKvwwNXHqgWka04TT2qfbTl80/WlRUNFvM/AZ3BmtM01mzpv5YBZz1ubZyOz02a1zzOaUzOmZGzx3xzzKvJx5vxc7Fq8ofjs/aX5LiWHJ3JJHvwT/UleqWiouvbHAa8HGhfhCwcKORc6L1i36VsYru1DuWF5R/mUxd/GFX8f8uvbXwSUZSzqWui3dsIy4TLjs+nLf5TtWaKwoWvFoZcTKhlX0VWWr3q6etPp8hUvFxjWUNZI13WvD1zatM1+3bN2XyqzKa1X+VXuqDaoXVb9fz1t/eYPfhvqNhhvLN37aJNh0c3Pw5oYay5qKLcQthVuebE3cevY3xm+12/S3lW/7ul24vXtH7I62Wvfa2p0GO5fWoXWSut5dqbs6dwfsbqq3r9+8R2dP+V6wV7L3+b60fdf3h+1vPcA4UH/Q4mD1IdqhsgakYXpDf2NWY3dTclNXc2hza4tXy6HDDoe3HzE5UnVU++jSY5RjJccGjxcdHzghOtF3MvPko9ZJrXdOjTt1tS2mreN02OlzZ4LOnDrLPHv8nPe5I+c9zzdfYFxovOh2saHdtf3Q766/H+pw62i45H6pqdOjs6VrbNexy76XT14JuHLmKvvqxWuR17quJ1y/eSP1RvdN3s1nt3JvvbpdePvznbl3CXfL7qnfq7hvcL/mD5s/9nS7dR99EPCg/WHcwzuPuI9ePM5//KWn5An1ScVT46e1z5yeHekN6u18Pv55zwvRi899pX9q/Fn90vrlwb/8/mrvH9ff80r8avD14jd6b7a/dXnbOhA9cP9d3rvP78s+6H3Y8ZHx8eynpE9PP0/9Qvqy9qvN15ZvYd/uDuYNDoo4Yo7sUwCDDc3IAOD1dgCoyQDQ4P6MMl6+/5MZIt+zyhD4T1i+R5SZGwD18Ps9pg9+3dwAYO9WuP2C+mqpAERTAYj3AKiz83Ab2qvJ9pVSI8J9wCb21/S8dPBvTL7n/CHvn89AquoCfj7/C1ZVfFQWOTtCAAAAVmVYSWZNTQAqAAAACAABh2kABAAAAAEAAAAaAAAAAAADkoYABwAAABIAAABEoAIABAAAAAEAAAKOoAMABAAAAAEAAAF+AAAAAEFTQ0lJAAAAU2NyZWVuc2hvdPbJCf8AAAHWaVRYdFhNTDpjb20uYWRvYmUueG1wAAAAAAA8eDp4bXBtZXRhIHhtbG5zOng9ImFkb2JlOm5zOm1ldGEvIiB4OnhtcHRrPSJYTVAgQ29yZSA2LjAuMCI+CiAgIDxyZGY6UkRGIHhtbG5zOnJkZj0iaHR0cDovL3d3dy53My5vcmcvMTk5OS8wMi8yMi1yZGYtc3ludGF4LW5zIyI+CiAgICAgIDxyZGY6RGVzY3JpcHRpb24gcmRmOmFib3V0PSIiCiAgICAgICAgICAgIHhtbG5zOmV4aWY9Imh0dHA6Ly9ucy5hZG9iZS5jb20vZXhpZi8xLjAvIj4KICAgICAgICAgPGV4aWY6UGl4ZWxZRGltZW5zaW9uPjM4MjwvZXhpZjpQaXhlbFlEaW1lbnNpb24+CiAgICAgICAgIDxleGlmOlBpeGVsWERpbWVuc2lvbj42NTQ8L2V4aWY6UGl4ZWxYRGltZW5zaW9uPgogICAgICAgICA8ZXhpZjpVc2VyQ29tbWVudD5TY3JlZW5zaG90PC9leGlmOlVzZXJDb21tZW50PgogICAgICA8L3JkZjpEZXNjcmlwdGlvbj4KICAgPC9yZGY6UkRGPgo8L3g6eG1wbWV0YT4KRuVm3gAAQABJREFUeAHsvWmQJMl1JvbyzrqPvq/p6eme7uprZsATBLk0I0SCEMBjQNvFYGC4TLvGNe4PrWklcsEBKaMZCBACubuitGtcSistDxAYQCIxJECIEMEhl6BAgMAAM9NXdU8PevrurqquuyrvTL3PI1+mZ1REZmRWZmVm9fPuTI/wKzy+8Er/4r3nz0MlDqRBEVAEFAFFQBFQBBQBRUARaIBAuEG+ZisCioAioAgoAoqAIqAIKAIGASWOOhAUAUVAEVAEFAFFQBFQBAIhoMQxEExaSBFQBBQBRUARUAQUAUVAiaOOAUVAEVAEFAFFQBFQBBSBQAgocQwEkxZSBBQBRUARUAQUAUVAEVDiqGNAEVAEFAFFQBFQBBQBRSAQAkocA8GkhRQBRUARUAQUAUVAEVAElDjqGFAEFAFFQBFQBBQBRUARCISAEsdAMGkhRUARUAQUAUVAEVAEFAEljjoGFAFFQBFQBBQBRUARUAQCIaDEMRBMWkgRUAQUAUVAEVAEFAFFQImjjgFFQBFQBBQBRUARUAQUgUAIKHEMBJMWUgQUAUVAEVAEFAFFQBFQ4qhjQBFQBBQBRUARUAQUAUUgEAJKHAPBpIUUAUVAEVAEFAFFQBFQBJQ46hhQBBQBRUARUAQUAUVAEQiEgBLHQDBpIUVAEVAEFAFFQBFQBBQBJY46BhQBRUARUAQUAUVAEVAEAiGgxDEQTFpIEVAEFAFFQBFQBBQBRUCJo44BRUARUAQUAUVAEVAEFIFACChxDASTFlIEFAFFQBFQBBQBRUARUOKoY0ARUAQUAUVAEVAEFAFFIBACShwDwaSFFAFFQBFQBBQBRUARUASUOOoYUAQUAUVAEVAEFAFFQBEIhIASx0AwaSFFQBFQBBQBRUARUAQUASWOOgYUAUVAEVAEFAFFQBFQBAIhEA1USgs9NAik/+R5c6/Rk2cIHw2KgCKgCCgCioAioAgIAqESBznR+OFBQAgi7jj1+c82vPHY1OkaIpn8ufc0rKMFFAFFQBFQBBQBRWB7IaDEcXs9z7p3k790nkAYc9MX6pYLmgkyCQKpksmgiGk5RUARUAQUAUWgvxFQ4tjfzy9Q79tNGN0XVQLpRkTPFQFFQBFQBBSB7YmAEsft+Vwrd7X6sV9pm4Sx0qjPAQjk8Ed+3SdXkxUBRUARUAQUAUWg3xHQVdX9/gTr9H8rSSO6ARU4rqlBEVAEFAFFQBFQBLYnAkoct+dzNQSuXbaMzUCk5LEZtLSsIqAIKAKKgCLQXwgoceyv5xWot1staXR3SsmjGxE9VwQUAUVAEVAEtgcCauO4PZ5j5S66TRorHeEDXTRjo6HHioAioAgoAopA/yOgxLH/n6G5g06vnN4MTCPPfVRd9mwGQK2rCCgCioAioAj0CAJKHHvkQWymGyCNKx//1c000fG6Sh47DrFeQBFQBBQBRUAR6DgCShw7DnHnL7Dw/nd1/iJtuMLEH36+Da1oE4qAIqAIKAKKgCLQLQR0r+puId+m69pbB7apyY41g762Y6vC6TvnafrOOdPP6bvnTTy1r7qv9tT+szS1v3resRvShhUBRUARUAQUgYcMAZU49vkD7xdpo8DcrNRRSCIIIo5bCU9/r7Ov9tPf92wr1bWOIqAIKAKKgCKgCJQRUOLYQ0MhmytSOlugaCREkXCIotGwif26CAle6vOf9cvuyfSBdz0TSOoIkvjCS59pmSz63TxIpBJIP3Q0XRFQBBQBRUARqI+AEsf6+Gxp7moqRytruQ3XjDCRjDGJDIecWEjlOu/Skr9ycUP5Xk+oJ3XsFGF0Y6IE0o2InisCioAioAgoAo0RUOLYGKMtK+FHHL06UDj/MkU+/mEKMZlkRkkhJpclPozGYhTCJxqlULg3/bv7rbAGafzEFz7idbsdS/vwT39M7SE7hq42rAgoAoqAIrDdEOhNZrHdUA54P4VCKWBJLvbZPzBlS6USlQpFKmRylF1NUW41TdmFFcrMLlD6/jxl5hb4fIlyS8tUWFujYjpDxXw++HU6UNJrQU83SCNuDUQV19agCCgCioAioAgoAo0RUIljY4y2rMTSapbW041JnUgb7Y4Vi0weiwVWacfs5DrHLKVkCWWIVeChSPkTjlAoHqMwSys7HWypYy+QN5U8dvqJa/uKgCKgCCgC2wEBlTj20FPMFwNKHMvSRrvrLHck5oFNBK7B0spirkCFdI7yaxnKraxT9sESSyofUGZmnrLzi0ZamV9dpcJ6iorZLJWYoLYjiNSxF0gj7qdX+tEObLUNRUARUAQUAUWgUwioxLFTyLbQ7oPlDGV5VXXD8N63bygCaSNIXTSwxHFDE4ETqnaVvGBHpJUt2FX+7rtP9ZyaWCWPgYeBFlQEFAFFQBF4CBFQ4thDD31mIUWB7By9iGMBKu4SRSJBVdWdunFnoY5Rf/OinXA0wvpwVoW7VOD/OjZN2R883qlObKpdJY+bgk8rKwKKgCKgCGxjBFRVva0ebnPK6s7curNYp5jNGxU4FutUVeC8WIdV4L8Uu0jfHc1SqpiibClDhVIAKWtnOuvZqqqtPWHRREVAEVAEFAFFgJQ49tAgCCRt9Okv7BXNahef/N5ILtEfjcwyacyxbLREmWKO1gsZWims0WJ+mZYKy3y8Sqv8AalMF9OUL+WNLeZW9x/kUYMioAgoAoqAIqAI1CKgxLEWDz3rMAJfOpj2vQK4b6FUZLJYNKQyXcwyiVxnQrlSJpYrhlSuF9e3hFS+8K3P+PZVMxQBRUARUAQUgYcRASWOPfLUC0FXVPv0F+ux2brQJzd4MhbZrL/tXXQ1PEVr+48Grxig5KdH5wKU8i8CqSpIZbaYZ+LoTSrXimuGVLZDBf7CS8/7d0ZzFAFFQBFQBBSBhxCBzjvsewhB7cotM6mCX8bNhgj7chz8fz9PR9jsMHKHl9swUZudOEU75i/wvtkRcx7ixS6thEsj2VaqBapjSCWrv/E/R2IzmTF1zeY6bJWBLRv5myLc/whFzbFZIV7nCnAOPrX/TJ0SmqUIKAKKgCKgCDw8CLTGAB4efLbsToublDg6HW0DcyzfcYQXQxeYf4Ek7l6cNqTxWmzKnIskcmnPwcD4nIut0bWx9viADHzRckFRgedYmmrbVUIF3siu8oWXVF3dLN5aXhFQBBQBRWD7IqASxx55tiA3vRiyOSL2pGPCkRy70OHz5M3XjUxv7P4tI4G0++0njfzc7iW7WM8cG1JJDqGFGtwJVcnoN27+Pf39d79JZ/c9xeQ5TFHeEzzMboYi/NGgCCgCioAioAg8bAioxLFHnng6tU4rS3OUWlumfD5H2EKwmWB2jmmHrtq6KKSO7N/bSB4lGSQS6Qg5JpGZLLYuDFdiqLYRbGlkN6WNpjOb+IIK/HPf+j1aWcvR4kqG5hbTNDOfopt35+nipcu0wGnLnJfKsDSTnbdv1lZ1E13VqoqAIqAIKAKKQMcRUIljxyEOfoECE8ZMao0yc3cIx5FonGKxOEV5V5ZYPMm7tERMHGPppM0R2yGtBOHzkhYKSSwcPUWR1y9WbsaQSiaQsfKCnFjUkcAVi2w/yOmQRiKg3XMDqXI9iFX7T1J3bfYiTc++QlO7nizfBxPmTIrNKUOUZsLI1LqSLgcRlkzGeB9wkVJCQhnlc9hZ2s9OymusCCgCioAioAj0AwJKHHvkKUWZGI7v2FfTm3w+S7lMmorsIBtxLpum5YUHtCOfKdMvkJAqEXGkfU5aTUMNTrCSGgtfNhOEYKKNtVSRhgbCTKpKlEyEqeqCR0gjE8h4fDOX2/K60/dfrSGORTYADdfBDD45CzAS9SGVIJAglvjgGUIFHsX2jQLRlt+hXlARUAQUAUVAEWiMgBLHxhhtSYmih9gwyhJHfEwYrnajMPUmCl+F9K/IpJJJWFk9nM9j20EER7JXJZVCMB2S4pRxvkE2QWIaBZE2ggvZJNFdD3kgjQiQQsIFD9S9tauX2UYQOnAOxXLfcRxucbU26nY6fPnC8/T0mfdXLuNIhFvb3tGQSn5GufxGcwSxnzTSSiaTIrGU9EoH9EARUAQUAUVAEegCAkocuwC61yWb2jXmmQ9Q6OMf5mbgWobJV9GROsaiDpFxOChbPTIpA2mrfgpMV6BgrUolQTFBTkBC0V4jDgli2Ig8ckMmCMGsIY3oHF8kMpAwZWyy2C8kEh0vspQ2Fkmae2jnF1bX4+NHKvF8vFTgulinnU9B21IEFAFFQBHwQ0CJox8yPZweOfMU1docggxWg0P+QA691c8OkWRSiSq8CAcLcUxamVQi2ZFWOgTTIX5VsllgjimkEGUDBRBYLigksjQ4ZqrlsiW223R6b5NIZELVG2LbQHe6qdjlrzyvDBoaaU3i2GrXxWVTPRW4F6lUu8pWEdd6ioAioAgoAm4ElDi6EenSuZequm5XWOpIRuroKKbrlnVlOqSwTCpddnogkGjRUYFD+mWTSjQEIodFIXDT46ibsahGCKHrUtVTriPkNpxMVMiikMZqwepRxGKnkEaCQIpUsttkMpfL8OIlR2pa7XF3j4LaVWLhjqjA1a6yu89Mr64IKAKKQL8hoMSxR55Ys/6/a6SOTPYcKePmb0aki1CBu4PhlGW7yljIIZUoU+LFO7YKvCrx5EaMWLO2pehggiWWzgVERY9zHCO2pZBSU4iixEjfmTxI99dumiLSnpTvdFxiVXW9xTGdvn6z7RtSyQ/DTwUOVbcs1EGs/iqbRVjLKwKKgCLwcCCgxLFHnnMB+t8mQ+kUu4epuMjxYHpNtteouEMIHbtKr7IVFTjU0uUPVmyXbFbM3YyODVfV0EwURRYJwki8FkikkEIkva6FtLn0LZO1vsp7V6+XKJ6I0PAY3AF1HgtIYsPGNtSvd/2TrnaV/fOstKeKgCKgCHQbASWO3X4Cm7h+9NkPEn3hM4akhbpIYuAInF1Nlu0ia+0qoW6GnaIJTCaTB3Y7QkgmlMW8QzCRB0lnlFdhl0qQPIbNQvEIS74k+JFIboZGxmL0yK7j9Ma9S7S+WqQkr+qGBr5TBBIO2iPlhUjSv+0aB7WrFPdCkFxiBbiqwLfriND7UgQUgYcdASWOPTICHDVw853J//SzRJ//g6YqYrW1l7PvphqxCoM02lsTWlk1h/EdYxQbGqxJwwnU3EZCCckkVoKXpZRGAglVN/NOqKjzTCrZtSXFk0wsS45kcc/ISZrPTNNc6jKNTIRodbFIafYjCanlerZIg8MO+WwniSwW80yO9E8Hz86owI2/SpzVBmBeIZR8rHaVtfjomSKgCCgC/YiAzn498tREstNsdyB1zDNxDKqcdZyEN3uVxuXLbhl9C8L9TmLHhGe+UVZDD26ElbUSS5DKHDsSx78w21VG42xbmWdpZSlHBZZ03ll/2ezIAgDSqRCdOXqa9g9O0V9feaGi8oZUEuts/KSWnp2qk1hgEWsMbFlDXQQMqcTza+CvEtJm2FVCMI3dddS1UF1YNVMRUAQUga4ioMSxq/A7F29V2ihdX/oX/wNN/Md/J6d1Y6yW3uwuMV4XcIiZk2Mthq4UHTy4t3LczAFIZTxRpcX2whkQEyzsLjAxAYbhUIFeu3OeUuOrlM9lWSrI3oaYNIKMZDMheB6i9Yyjxh4aqSWozfQJO/lg+0cNrSPQrF0lFbOUSA4oqWwdcq2pCCgCikBbEFDi2BYYN9dI0654XJdLHzlCuX/965T4zf/RlVN72o6tBWtbrD3z41IDbNfYriALZ9AeSCTsGaMxh8TF4k58b+02DY3GDWk00sZoyaivoxyHIywt5AU42TSLK5mPQuVdYgfqMSankHwFcS0EH47YR1xDZxAQ6bv4q4RNaSyUodK6cz2owB0JZXUluG7Z2Jlnoa0qAoqAIuBGQImjG5EunMtEuZlLR86+iQrPfYIiZd+OXm3B3myrw5mT/4i+OnilI5cFaUSA5FFIJM4de0ZeaMOqbYgii7zYBmWRHo2VzAIarL6GCjyTKtAAm12WWBzJGnAmjkwoLbtKkEssPDo8eZyy2RRLLxMs4cwy+Wz/rjHou4aNCOQyKRoYTlAOz4WDUYH72FXK1owglnjealfpYKbfioAioAi0CwElju1CchPtbFZVjX2To1jlyzvK0Kf/ggq/+q9I9pa2u9XOBTF2u17HmNeX/9vfoCd++E105MVfpGuz2Fu7M8EQhIEqKV7jldVDvCgG6aFwiVJreT6OUJEFklhtjQUzWGQD1fXQaNSUQ88c5+dchv8qZLFOmOvj+NDIYzR797pZuANRZTi8ymQ1bSSPUbZ3BJEEqdwuLno686RaazUai1IBC6eqj9i3oUYqcLe/SrWr9IVSMxQBRUAR8EQgxJNi+T3eM18TtwCBTLZA88u8FUuAMD37Ck3ff5Wm9jxBU7vYjyOHG6+fo0eOnq2p7Uceawp18ATSzztjT9LYWIjuZF6h337xubZfbTIxZVZUB2n4wNhjXCxJt5eqBBaSK5BLCThHgHpbVOJS5nee+XMpRjN3rtHA0Iixc4TaGhLITDrNMZ5hiN5Yu0an9jzJJDLCKvAk214iHnDIfaUVPQiKQDGfMkXD0YGgVVoqh7FgJJUsYYbqGyQT9rGQ1HdBWN/SPWglRUARUAQ6jYASx04jHKD9VKZAiyu1xPGF839YqXll5lVfiR14fy6boRMHv4eO736iUufpM+/3lTxWCnXowKjMIf3ksLxMNDpK9Mk2Sx2F5NnEz307KGOrsHEOUogAYog8aQdpovrGsZRFuSO7TtGzj3/SkGDcy+3r07TnwFH64vTzKGrCly84x2b9Nz8Tx+k54iK95dDbTIxnFWHp5E89/o9ZZR43viCjbCsJUgmSqdJKQbM2DpfSlMnBxdJGV061JTt3JqRS3AsZv6NMLtVfZecw15YVAUWgNxFQ4tgDz2U9naelVdadcgBhFBISpGtCHOMs2XIHEJ7/+vmX6eyqs2jEnd/u88LRUxT56L/d0CzI44s3mruvDY24EpqRNqKqEMRdgydpdv0SHdt7mq7eu1BpFcQA/h9BHqUs0kAu/9HRZ+j7Rz9Ap86EzPP5wku/x6rTONtGOjaWlUYCHOB5wSUS4rcc/HH6qePvpgzb8MF3ZYh15CCQiWRSVeAWllgYs7yaYSkvs/YeDH52lZLeg13WLikCioAi0DICShxbhq59Fb/5xrfo0//wn32livWuhK3vCvk8S2O8V/liJfWbv71K73q9QBPJsXpNbSoPjsjNTjZ1WvmFz76zTm5zWSB39aSN0pqQQTlHnForsMTPccuDcyGIop5eWSpUCCSI5L9868eNeQAIPSSK6XUmMYMOUQ/aD1zHL/zk6fcY04NjEyeN2huriHOZNNtgFmpU4FjJDVIpKnDYVcIRubFv9Wt8G6SHCmxPWkr05X0KecQYw0Id9Ve5DQak3oIi8JAjoMSxywPgE1/4CL106xuUEx1qk/0BuYBD7KgPcdw3coTurlwzrZ79+n36b24NUzK2UTrZ5GUrxYMQRincrDRV6m029iN3efb/yBzNEEeQRtlxBtfD40Da8nKK4rGEOcbkb+pksywRdNKkb3INL6IqZRrFkBD/0lt/07MYnnOebSmxIMe2q8QuNlCHhyCpZKmzWwW+HUhlIT1PkeSkJy79nogxpXaV/f4Utf+KwMOFgBLHLj5vkMZpdli9yhKVPKsvWwnwdQc1JwiDOzy68yS9MXfJnWwkaMe+8rJJD118xXMF9oZKnGC2N+Q4dPZJipRtGL3K1Uv7+U+/I5CksF4byIMKWSSEjcr65cOX44lDTxpJrxA/xAiY0FfXl2gg4ahHcY6QZ1u7Uqkq4bXLmwKb/KpHHv2aNi8PPAYgpQS5xCp7OECHChzHRlKJRTq8stxIKctxP6wCr/hwjAz73f62TceYE5tKkEu1q9y2j1pvTBHoKwSUOHbpcQlpxOU3RxxZ4sT2cm7JUrFMRLHHs1eA+lVWZSO/cP5lKp17xatoQxW0ZyWfREgd//Rbn65ZiOJTdEuSQdRenznP5NshhrKYZn5hhiYnqo7LhaiCqOdzvHNMOGZc+6CTkE4isNCvIqnEOUgl8kBwhZgivVFohTzWa9NIKqH65h1v6qnAQTDFtVCvqMDhO3OAPU0VQp1dUV0Pv17MExW4kVYywRR/lZLei33WPikCisD2QECJYxeeo00acfllljgK0Wu2O5AoIUTgx9EKaM+PNEoxN3mU9E7Hv/GX8Ot4oS2Sx6B9FeLnVR7qZ0hzZMHMytochWmIBniLO5BBkTY60sUCb19YZBvHeNNSz2akk+0mj173jTSQSkgs/VTgIJPYlxsS7W64Fspl1ynB9qjFUPvMK/yw2C7pII9wH+SlAtd9wLfLU9b7UAS6h4ASxy3G3k0acfmlwoqRGrbSFajyQHoikdZ8uXeTPN6Yr/pUbObem11RLW3Xk/qBqD2YK9CNpb8zqt1BVlELYbRJJ4g6nJtHoo7j8Jq8spobaaiL60HaKO3Y/cCxO13yJd4q8ijXc8e2XWWRbxrkErFbBe62q2yna6FcZoUJEI/tiEoc3c+n1XOMOy9Sqf4qW0VU6ykCDxcCShy38Hl7kUZcfqmwzMSxtY7Alg0LI7AzSquhW+SxVd+ONllr5p7rEUe0s7g8a5obH91lSJ+0bRO81FqW4knehYa3MRQVtK2qlrJu6SLO0W+3r0iUR7ot2ZTrIu42ebT74j4WFbjbrrKdroV6wYej+7638/ka/w3gRWBiYod5sREVuPqr3M5PXe9NEWgOASWOzeHVcmk/0ogGN0UceYVvOArn0a0TR/Shn8hjqxJH3KdfENI4OrLD2DuC0An5Qx0hhPky3qUSq099bBu9roFtEJO8LaK041XGL62XyaNfn/1U4LK7jtu1kN/uOhHK0Opa7/pw9Lv/fk2fu3edhkYmPH1miv2kLNRBjB12JL1f71n7rQgoAs0hoMSxObxaKl2PNKLBxTx7yG4x5IxrGDiOdhbBBLFt9LtUt8gjbB5bVVv73Uu9dLfkUUgjJI0SYAKABUd2WRwX2SYwEo9VyKWURyxEsx45FGlpPSIpLn3sa/cjebSxsY+9VOBwMZTLZWpWgUPyNTYySOvZIvuvHDYvRzLO7fb0uH0IyK5I7sV2ja6gdpWNENJ8RWD7IKDEscPPEu52QBzrhc0Qxyyvlo3FE8bOURbYNFoU49eXbpKTX/8LkMetWzAjBG41tWRc19ikEfgAS6y0FhIopDCXyVBiwMFb0lBGSB5iSCJF9WyXsXFHuqiupY6feyHk4xpwFI6tJLdz2OBaKLtG7Ka0xq4yxoSysvq7j1wL9fpzw2YCd65fooNHTre9qxi/kFCKeyEs0gHZVBV426HWBhWBjiOgxLHDEDeSNhbYRcpKYa3lXtjE0c9vYzONd0vqiD4GkTwK4WvmnrzKChnL5tMUj/qv2BUCKW0UWCoWYYfgbkJpn0sf7TTUl3NpS2Lpi9STdHcMSeR//tD/407etueQ+kaK6xSKV3c8ErvKfnQt1OsPCq6PZu9epwOHp7a0q/i7qBBKPla7yi2FXy+mCDSNQGtLcZu+zMNZAdJGfDoaeFENVlVjhxgvZ9/NXnv6/qs1/h2brb+Z8r/8E7/ZkDz6SeWavS4mK0jwGu0LDultmlWlWNQCf5lZln7Fk1X7RyGDIH0iZYywLSPIINIkoN9y7r4HaQN1wty+EEhJlzbQh+nZV8zzwf7fS0slOnTI8T8pZbZTjF1xEixdZEgqIQpfk/wxweUT3FaBQ/WdSa3R8sIDdje0/XfXqQC0iQOsmk8ktn71OsY9b2NAOXaL5Q5iP2nbVUJaib8NdS3kRkvPFYGtQUAljh3EuZG0EZfOlXK0Vki13ItsmiVmvH8xHFNvZmW13YHfeebP7dMtPwY5+rNzn/Lcu1ukc5vplKh8m1nVjeuCOBYLvIo9VN1u0O6PTR6lf8iXRTRIc5NGKecVo66bRHqZE4BEjjob3Hg107dpmdQy+9KMt8WH4wYVOEszt8vuOu16wCtLc8bGdHzHvnY12dF21K6yo/Bq44qALwIqcfSFZvMZnZY2gshQWeDULtKIu8buLt20pcOONvu/70m6k3mFIAG9MvNqhUTuGjxJ85npph8OyCKC3BfI6bXZixXbxEYNQsJRKMBReNUNj1siCFIIsmeTSSMZKS94lzzbBjLIddGG7KN99d6FitRR6oI0gjzaYTsQySj7b8zm8rwPu31nrR07viUjVWmlqxm3CtxIK3MPmEhluCRLt7gTCX5B68XddVy30vKpkTgODLVcf6srFouORB8vzbw0bcPl8Xdj21Xqlo0bINIERaAlBJQ4tgRb40ovfOszjQtxCdg49lqA+lYIVrf6ZojP8pM0debJShe+cfVlurX+KquonqqrYhaSOLXnCV+1OySaCCBxTbnAZLKOnWaibOgPIijBLRm0yaOUwUSGdLfnJKShH25ppE06oaaW66HvU2+t4oL23URxO0gh4/E4ZdlrwFaEeipwt2shUYHbpLKbu+u0C58May+Gx3a0q7mut4O/F4dUbuwK/rbUrnIjLpqiCARBQFXVQVBqocyHfvdnA9VKF9OULrY2OWIVZCGfZ8LRBpGMq7eiznUlb/npzZtVO752kqFf+Ow7K/eCCQYTSaNQKDj7gjPVNMQR5YXMSf3gbVV3lxHS6KXqdvdJyvzTH/g4FWeeoB96S5guni/RqTPe/Qd+Y2OhDcTS3W4vnsOHYyqTp3iid6Vgtl1lt3bXadezu3XtAu0/fLLi2qtd7fZbO152lWxWaf7m1a6y356m9rcTCKjEsQOoBpU24tJF/td6KImmuvUmfGr2gtQRXcPiDyGMbqmaT9cbJkMVbwchfXaa1zFMA5ztHdn5N7vryayX2FGyo4cWwoi25NirDUlDOZFSFpm4IjgkNMTSx+pCGykvsUgl76bP0dNvecpgA9IIgojgXizjPq9HMuUaPRMzxrwtUs90x6sjUIHH4wPm45UvKnDE2K4S0srM3B129VTgW4P/1cgGFXg0mthy8oaXUAT1k8m/yawCx8drsQ4wwt8uVOCy+htkEhoI3bIR6Gh4GBBQ4tiBp/zCS893oNWNTZofe29B08bCLaTICt4WqvZ0Fb+V1A0Jn7EpdYgMVlvDHEzqCGHEjbuP/cAQEoh8tAN1tJBJh0T61SSjqoc5Aci0l1TWjyCKZFLIuP8Vup+DxSvR6Ej3O7KJHtSowF3tBFGBw64S5DKW4DiEeIAxibla2vxpnm05I0xYNTRGAH+balfZGCctsX0RUOLY5WcrTrtb6UaJ34rZE0/HQjdd89g3JZLGbpMd8EZIFewgJBExPhIkXc7rxUIgMSHB/tFNGkU9bbdvt2dLFeGip7Jiio+EQLqxc2Mq5ex2u3mMlyKguZ0lYOJWCBJLd3CrwCGplN11SsAGkkomk9hdJ8JEEm2BVDqLgJqX0pqFMUxSNWwOgSqp3NiOrQJPrS3S0PAIJROQLqtroY1oaUovI6DEsZefTp2+wW/jrYUrdUpszyw3AWrnXYKYicTPq90Sq06hqnaHUJhVW8wq7R177HYwmbhJn50v7bnLIB11hVhiZTUCJJN+QVT7Bx9x+gkJI0ghzr2wEwIpkki/drc6HRKwBK9achTwW3317l+vngrcy7WQqMChDjcrwCGhLO+qI3E9FXjO7EClxLGTT95Wgd++dYv2HDhK0ZQzwoU82v4q1a6yk09D294MAkocN4NeG+q2MjFCSokfGiNb8iAybehWzzUhpAdxJ4OQNM9rGMA35ghhzKaL7FPTIXVoRwijEEI5RwuSj2PJx7FXEJIpK6vl3Kss0oQM4hh4gTTaaSJdtFXcKCsBdcS5uOAueVsWY4xHeK/wLbtg/1zIkSoGdy0EaSIcodurwN2uhbAD1RCTTQ2dRwDSdNi42iYHNqn06gF+I9Su0gsZTesGAkocu4G6dc1WiCOq3176LrFH6p5fPGDdalsOQYAuni/yKmJ/qVtbLuTTSKjOciSYiOV4a5lwhA3ny6prkEUEL3IoaZAkekkRpa5NZp12nd1lguAghFFIok28bRW3fbuoMzrqSCxxLHWkLbtsx47NwhjW27f6B9KxjvV+wzV2lQF318nxdoPZTIoWH8x4qsBtktP7CPR2D1uxJ8VvQT27ygj/5kRZmCASyyj//ug+4L09Dvq5d0ocu/z0WMnZVA8e2XGCkqmz9NLlV5g3squSXa/xHngbVaFNNdoHhSEBEzID0thJSZgtGRRobGfrkuaOIXkMs2ekpXle1BGPMhl07B6dH/2q+x3UE9KIY5BGL/IoZVAfUkaUQww7SJBJIc/A4tYNf5c8uIaQRJC/Ed76WfADoYS7HgTkiTTSJJS/hDBuJYGMx9j5N/twjHCsoX0I+KnA4Ypn76HH+UI81lj6aFaDs6SyngocBDUSg33l1q8Cbx8iW98SMIXEt11BSKWXUzdbBW5eOsNMMJlUSnq7+qDtPFwI6K9ynzxvbDV35fbLdOPBZe7xZRrcX6IjkbfTXCFKt+cvseNexy0MSIUQjj65tUDdFHIjhYXMyHk7Y+DnJnK84SDLGjfaN9rXxTPCbjRjk3HCDjdXb52nBJNHUTHbhNQ+RhtSBsfu52d+8LkdvwAsxEZRCKFfWaSLHaQc22WlHZFQ2nmCuVxDSKek22U3ewyH2rk0E8fNNqT1GyKQZ7tILLYRqaIs2nFXFNdCRd60AOTSkEqWUvaaayF3v3vtHHaosXj7iGO9+6unAgd5hKWTqMARq11lPTQ1TxBQ4ihIdCmGtrlRgJTx6r1z/GNT6+g7M3iBVtdu0OhkxOw8AjISZtKDGE6lQSIRI9jqTielv747QU7qIQAiVxP4QXktjLHLYDtAIX3DQyE6e+wsk/3ztLJUqOCf5mczNOyoslHXJpBSt54No20b6SUBhGR2aalKDsVW0e4njm080Q7KgZxLeZFQoqwQRRwjSF27jJPTvu9iIWeoevta1Jb8EMgx+UvwiuxGoZ4KvJdcCzW6j27np9bXaHLX3m53w/iqRCfqqcCFVEJKqf4qu/7IeqYDShx75lFs7IgtZXTvRQ2ScX3uKku0WE3Ex3AaDbIDSRm2boWaFKRRCKOQSbnKdpJMuomN3GM7Y0Pw/YV+NQQQ17104zwvlIH7HucZ4HnhGYA0iroZsUMWJXZ6LM/Mq//jN1dM8uIhx78hSJwtHRQyJ6TSfS6kz24baTADQB2v8lJHruOHt6i5/fLtazY6xsrhcFj9CjbCqR35IH1w67OZIFLKoK6FsMsOHKHbq8Db5VpoM/exFXWxSCkWH9yKS23qGvi9qkcqdcvGTcHb15WVOHbx8dXbp9pPymh3l81V6PCOU3SDVdVCNkBEMAdMRKdoea1EC0sXKxJJKYM28KMA4iLHTr06zMiU7M5XIyICYtOozKZ77uOKR9p1CKCcVVXPkRjvDZStrrAW0ghSL+ppHLt3izn79fuVxo7ezdCxZbdoep5G//Tt/ByJ9j39LOXLpXGeeN8HjVQQmAguQv4qjXoc2GVEAinF0I6QSruc5CMWNbfky7XtMkGOjQ9HvpFovP2OroNc/2Er45C3zmHtZ1cpOIsKHDH6InaV21EFLmYB/e6f1JBK2MPmN9roi/2kkVbyfCQ77Ei6PHeN+xcBJY5dfnZYdIF/WCEd4sUVj+0+XbFldEsZvboK0ggyIqRQ4uXSZSoMsR3k5BmaXXeI5doqVu9WJZHs5s2EWNl2Dz8GIDEIkEj2WxCJWLv7DdwSCX4+YOquAMzcpFGKOOkROvbIKTY1uMDSYJQFaXdKFPgcz0ueWeTSEv0Uf44twV+kLJqvT+bNM/zCZyibY9tI7h7+oAt8jvTBn36Wos9+ULpTiUHoEITgOWe130ISJRVlvYigpHlhL+2LJFLaahRD2hjjG3BT5Ub1NL81BLBDTyLZvf3Aa1TgrltwyGSWF+vkynaVWU/XQiCn2F0HdprYAUfsNV3Ndf00qFlA1zu6iQ40Y1dpq8B1H/BNgL7FVR8a4pi/dJ7wkZD6/Gfl0MSxqdMUPXmmkpb8ufdUjjt1YAgjT49YdBFinebB0SN09e4rrDbixwLdqCEPXAozKB/Dxg7/EOxVviAesjDDZFpfQhqRZEgGxyCFUGkL4UR9kBznU608P1+kv/9akcaYNIyw/Rts4IQMVEv1xhH6JerWdvcR6mWetzjUJ3F+SGDBDLAdGg7RgTFIiKu2kHgGYzdW6MdfXqhIFfG4zTNHjN2BoO9GMGPCuw8inBNSiuKhFz5DBf6UWCJpE0gbH5A6t59H1HUHEERZuQ2SKGNB2hKiKUTSri+SSKQhX+wo7TL2cbGQpfjgAGXKBNvO0+P2I5BhG8fxnfvb33AbWhRSaYwWgrgWSqfZdi/Pfzf+u+t0k1S2wyygDbB2rQmQSoR6KnBnkY74rdR9wLv2sOpcOMQExHmSdQr1a1b6T54nN0Fs5V5AKkEkbWJZr50XvvUZCrJfda6Uo7VCypA+rJiWxS9GCll+LA5ZZFUm/NpxMOdMIPEHaFRMvPoUgbU8FE9slIiZTP4SkjgOFTZLtDIxlkiytEzUpSgHcmNL0H7nmT+X6iYW8gB3LhKEQMh5J2IvMrKZ63zyxV80q5+baSMH1zDRKNvd+WPs1Z7gbpy2s0QZBB/SR0h2J++s0j//mweGD8ofIWghpI3Ol9OiUWPzZe2/VJDJo+MHvS5pJJrykoACIJM4Lzz3CYqceapC3trx7OoRwUbPzS8/l12nRCxMxdDWrDz1BPEhSYRZwJ3rl+jgkdPb6o69dteBZBUk2barlF11JO60a6H52Vtslz7EL5ET2wrvrbgZzE9qV7kVSDe+xrYkju0ijG74miGQH/rdn3VX33CeLqZp98QRujYDiRTP7AGCIZVl1XYxXzB+1By1JlMPsA8mHZBK4lDeCYRs2qQQhGZHgkkkq7QRkCckB/HJR87QL731N01evS9In1Z4FS+kVpBIgVSK9KlevaB5IBcIItlyzjb3PT37Cv32i8811Qh21ojFE4a4AysE/JA1CjbmKCvEcQeTxn/6lQdVaSIymRna5BBJFWkjTiRwoeHoCO0cHHcIYZkYSrbEQhjtc/pVhzxKmpeKGXlBJJFByqAtkVDi2P0c5fkiDwH5vHyIJ3jGO+EsAHJy9LsTCEAFfP/263Tg8FQnmu/ZNsWuUlwLgWhmWFpZb3edcDi6aRX47evTtGvfYfJaRNSzYPVBx8R+EtJKzHeIS0V2e8Tauxi/8GtoLwLbijiufuxXKDd9ob0IebQWhEA2kjpO7T9D3/ju16jU4piGpKCQz1eklOgmVN/pdbbHSzJ1BIE0jNJJB4msEkienHl/ZdAfLKKZXZ9mCWZ19S/a+tD3fox+8JgjnXJP9sj3CyACUEWCTIJEQqqF0Ewbdtt+Uim7jN9xvbrNSh2zmFSKcRoYdFZFi12i37XtdDd5HL2xTD//1wvOgpiyJBGPCkGIoyGMcoIMKYBjDvuHdrKPw6RRZScSIbZxZPtJlkK63z+8yCMkj/Enn3Ia4m8/8igFGuVLOcRByaRdxz7GMxsfYR+BuSKP7d5feWr3vR+P11YXKLW6TDv3Hu7H7nekzyCRhliyA/R8Lse/syypbIMKHL/ZcLT+yNGzHem3NlqLwNy96zQ0MsGfMfPzaRbrlB2gi2shtausxSzo2bYhjltFGm1gR577aF31tZ/U8ejuKbp89zzlQixZ4beiVgJsRMx+p0240XBU4MwQmYRAVRqNsmQS5MQRoBH/RtLBidN0d+UC/fKb/4T27snRa68laGJHvEIEm5UmggjcZEnkaFm9LdLJVolks1j5kccXzv8hffnC84GaA8XOpTPsXidZo8oPVNlVCO50/tlfPagQQdgwIrgli8a2EWRSCCOeU/l4IBKn/SO7TT0Qw3XeI3tkiF0xZdj0gEkkAtIL3HY8Zp+zOUN58ayorU3hNn0Ba9t+EediF+m+BPIQZPW2PR4ipRRdfi1Pu/eOtPzC4bSu340QWFmaM6rb8R37GhXVfEZASGWBfyyFXBrXQj4qcNhoyu462Gpw9u71h066262B4+yGdLyhlBiaI9uuEgIW3bKx/lPbFsSxG6RRYK1HHj/xhY/Q9J3qghxIGc/ffJkHpSNmXC+uU5YNuVsJ9YijqJyDtIuyWCyDD0gk7Onesf9j9D2Hj9Njj8XZHpLdokRWjZ+3SCRG05fjrNLO0IlTIbp9J0qHD8eatvsTggFppJDKZglpkHtDmXrSsl/47DsDNQNccM9YrRlEPe3XqCGNL8472RYRrJBH5ngmGYth+MA+ttucHBiliWSZiZczQBTtUOD3gwpJLOeJNBIvCDCNnf/R99DaOz9YMS0AmbbD1J4naGrXk3ZSXTxrCjZ5gjEh5DFUWKVcqXZlLCSZ9iKbJpvX4j4IqM2dDzAtJosKHDFsKcWuEi/5/OZnWh0cHuXfkjj/psZYqo6V4LplY4tw+1aDCca9m1c2bbvrZ1cpqnHfDmzzjL4njt0kjTI2/MgjSCPII8Lje0/RZT63F1esFdcoZ35QpKXgMX6UECLsfqIdwbbb+5dv/bghDLZt2uBglkklX5MX6WAfYeQ9cqhIX/nLGH3f97M0ju3/hoZLlGfiCUkX1ooHtQkSIon7EKInRNImFK3ep7Tprh9U6ggVUzaT44VErTukHnx9mf7F3y3UdAGSwxSvIEZI8nEax2CLCLak0UlxiCTPPUcnDpVTaiMhj0IQcY5jiaX03Noiu+1J0Hpxhc4N5eiFdz0iWTUxXiqwdeJiftqkwz7z+O4nzPG+5FkaST9Zl8zJc5VFOEHV2Etzi7ScGqsQWrtT7RgPdnsP+/Hdm1dpx54DanO3BQMBJB1bO8bZbZCtAnfbVYproXAILoYGGkrMtqDrfXeJ1Noyra0sdNQEA+QRP9MirQTJhM9Kx2QIx86LQt+BF6DDfU0ce4E0CsZ+5BG2jv/3P3yqImWU8ohXWbKSL6+WttODHAchju79lhu1C/L4jieepafPvL9SVCb/W0wUf+gtYbMiF5kiHQIp27cvR+dfzdHpMyFKrUd4cUORJiejrPrOMNks8Ipw+C+MUZ4JpXHHwKuLw0yU6rnFQLtiJymdETIp5+2Ig0gdvaS7zUh1RdJY41pHOm/Eis4PTA155F+kSnkuY4rxD9EBtm1MxpK0xu6U4jAA53bgv1HIIpp1E0WcIyysr9NafoXybCJhAjeaZGnHeSaPf/wzh4z5wvEDpzesOH9k8hRvbVmk+YxDIJ3KZBb6/MzZ95mXjGYJnYwr9zOFpCAWylApMmxeIvxsZOV6KomUp9FaDHXe/sMna15oW2tJazVCQGzuBoZ4BZgriAo8x3aV+M2U2L0K/GHZXccFT9Oniw/uGpI+NuGY9DTdQJsqGDLJP9BR/u0WYgk+GTX7gjvEs02X2tJm+pY49hJplCfmJo9pNqi+cOcV+l//8uNSpCZeYeJYaJE4QgWCt1f3auxsPs0LJTKV68RjCSYYwdyaQKKEldQyKVcaKR9gkl7iHUxOnwkb4ghyJ9IkFEE9BNtuDT+I5sPSSryBxaE/5XuG9DKdWmcp3qAhkJBSYhcCjoy0Euqb1VXnOmjTbhsk9uChkKdECmWbCY2kjo4klu1JmWS5ia570YvXdYU0euWZNMMIq2+mttraLXUEyds7WPtDmM9Duou3XrhoclTQ7mstpJdoPu1sVYi8aClm6uC4ABLJffjy1ABNP/Wjxtfkg8wl8yOHfAm2RFrSJBZJJF448Jz87BpRHmMGwU0YTSJ/ZdKrNDwQM6pqSZPYb1xKvsbNIbBdXfE0h8LWlcaK6j0Hjm74HQnSg3oq8BCv9oaUMsE22FB9b5VroSD97laZmTvXeHHmDvIi6d3qk9d1RRW+uniPxnfsNdo8zJOQZkaZcIriyatuN9P6jjjCiffKx3+1m5jVvbaQx8XFRRofHzdl3baO0sAyE0fxzyhpQeNUeo3VwjmzqAIkMldWXW+oj3m6ykuYYMQq+9K6SaXtt7HeJC0kTqSOG67JCaKWRB7K+bUnP4hweh6DkTLb/WSNoTnvEMEkZNfuQf4hZCLBhnk5lojmc7ySnNU36+uOih4kBVQTDsr9yAj6IAHExS7XyDWPIUwlxw7VbRYQhDg+/fkbFcfe0gd3bKusTR4TuQqfxC8Hn4A0HuAFMSI9FBW0LICRdJBHBNgwpnNpur02Rxvad4o439w2K88MgfzfPvQ2WiirpfGDNsnumuBAHsdBgrx4SNkg40TKynNp5MMRbeLFBMF+acG55OH54rje+ET5hz1ksyl6cP827Tt07GGHouP330mS7thTVnfXwYv6VrgW6jhom7hAP0nS640NWx0uWzfK4p1u2ln2FXHsddKIcQ41Q/y/e45Gvv/NNcPeizwuFVaMJKumYIMTSBTX11cMkTJFA8zpIIu+xJIbGWCHtB9553/YsBAC7WMCvnWjyLZsGx1fuydqe0Wt6Vv5C6QAamcELHAIql5cXCwQbCvhlRLifdiS4F5w/5BaQm1TKrEKgKWqWXbQvbDI7i5uhmltLUaPPBrdQCycHmwksX7kEUQIu774SXelPb/YS9pYUT+7K4EpIpRfMWvKcd6B4V1GRY0iIIkgjrLNINIkYFEMVNc59hEK0iihLnksF/rSsSSde3NVognCCJX8YHGK0rHpQATSTR7l+n4xxoatji7mU0bSTOFEIOJXjyAiD0EJpIOD+xuueLAv9OQub0fy7vJ63joCkKQvzc/S7v1HWm+khZq2Cty2q+zl3XVauM2aKv3mm3Sz9pj4nd5qO8u+Io69qJ62R2yeyUs0HjdJE3/4eTvLHLvJ41Jh2UiWNhT0SFhNLRkCUyGAZZ5hSxM9qlWTUN6HZII4Dg+M0U+efk+NfWO1snMkUiGvdKiPcYm3sB0kgkgc3ZO2PZmjPQS35Mgk8lc9UoAyIq3EHw4W7ESYMUFaid0FYFeZTsfp3Dmi3XvyNDoepnv3kkbFDbWOu19u8mhLE/Fcw1G23eR67mCXc+cFkTbW1AF5tHQTIHvrbHZwcGQXxcJJQxZtlzs1dfkEq6URsqU03VuvkkYnlb9d5LSSbh381gcPE3YXgqQxkTtBxaErlVyx68Q9J3NTlEs6uw/tSJwkW73tRR7t515p0OMgzH23fTg2GgPShLTv9fIiee5nLnUf1rhX7MAeBvx70e2RmBHl2Nm+I7WsrgLv5u46mx0P/eabFH+H0GaNjO3c7K171sf8mGfb2SxziJ28EA6SSwhiNmNn2TfEsZeljZAyIsC2RMLAu54x2xTKucQ2eVzMl0UikukTLy7PbpQY1iGCXs0YqSOYhYs8In18dFdNFVlVXZMY4AQTtKgRbXWwu6qUA2G8cL5YWXSDiR15MsHbx+42Gp3jhxA/jGYPnRLvsMN/KWtrIZq5n2aiWqLp6TiNT0SM2jqTzZvjKw8u0n/46q+xRA+LeapA5TLsiodtM8O8qMcrCKGy87ykjZJfI02URJ8YC2Zg1yiqaRliopp2n0PSeGtl1pgw+DRZXXTjUeDLJyB13FPJWbv7OJ08HWPJq7O/NhbK3Ji/aPKBk4Qju07T67yVojhG9yKPUlakjPKcJR1xajXPC3HSlM4OVUwKmh0HKI/gbl/aqXd9p+bD8a2ueLbuOQNr2B92ihx04k7kxXyrd9fZ7L10mohttn/u+rDHHJvcxTaqrs3Y3QU3cY4XFyy48tIuiMobUktRgzeys+wb4tipbQQ38SxMVVvK6G7LS+qIMkIegxBHT9KIRpokjqjiruNFGk05/mpEHmUSlvL1YpStt2DCPdE303a96/rlyZu2uBe6cydMs/cTvDo8TddXv01/c+uP6eYiJG0gj7xoJwNJcozJGP9huZk3l3ATTVz37Nfv009eTuOw+VCWPELiKI6+RdJoE0a8B3CXDKnERWDTOJ9edlz8lNvwIqkmTXixJeGUjkLq6BeELIJYe903VvKPhE4aaWQ98mi3bz9vLx+OUhblvCSKku8X2+37lXkY03X7u6176tvN7ZG8mIOM2Cpw27UQ7NVhThRj90Nb6VpoK4hYO0fOVthjbuYl0bazrOwV/msc2glCp9rqtQUxkDJipS12BfALsZNnKLyrajMm5X7kxH9FF++co9vLtyTJM/YljaY0M0ePSd+zIUlksgCyCGNcqKdHhyclZ0P8jWt/Rcf2nKGdQ3s35CEhwS4NRXLjWaCc+PdfYx+IzJ+wlzXqIKAe3mzkHLG0h3SE119jH4K7hd2YpLZ9heAOCCvSsasDLzoZn4jTgUPMwMJxevzQYQpld9HXr36F7VX5+bKv9gKvXDZqarardBTy1a7g3Eg1QSmt5/EB7A6zibB/eAdNDjiLq9AM2gYXhIQRZBEEEluw4hgEMsuSxjts05hn6SoKouwA3xuvaad4KMar9zm93D+0Fed7xY95AVJZq9+41sUdEUqPlR8WEsoBRHBuCdJMXJcXI/EuQ7OL93lyqD4nHBejDwypXErN0cWZl+nsjrdVnrW0ZccyDmDeEI+mKDk4UNMnGS+QIIo9JOpLutS327SPkQ/yODPjjDsWINf0B9fFWEOZRm3Z7fb78fLCfZZ07K3But/vqVf7vzR/d1thbX4/edEi9txO8lyC1csjY5M0yu5vhjlODg4ZDRx+W2A+lE2v09LCDEEauLqyyOdrJt1x2ZY3L+V4UXf/FrXyPBfm7vAK5f1taauV6zdTBwvU1tnn5NhErdavmTaClJ1nTPC37mVu1ag+5hJ84KMZnk8yWdbg9QNxhLQxvwV7UDcCUPIhZQRhhASqXijNzlD8R9/qWeQtj7+Vvnn9m7S4PuuZX580ogpP1tX52rMNr0SQxuHBSRoaaCwWb0QeZRKvN4FDZY1J+W9eLNLrV0tsbxii3XzuNUGjPaSbD++3/e2XioYo4ByTunvC97q/VtKkbdTFtQ7v2k+nHnmCXrr914agZdL8h8IsDc+bN5DhN2wQEHycRwAVdgkuhsok7Ozf36dj8w6Bq/THRc4cqZ/3A8RCmIHYQKUqDjDU8DH+G5mc4dgsjmEimS4waVxlQoeCplPODzBIJMhvMcQrZlzXB5GECirBUs0cs1CTXS4z+iBN0ydrd6ZB0xirkDSCNELauJqdMyQykZ2igaUfo3TiAuEYxBFlpM6V+ZcptbiLdg3v83zupiB/TUzmeVwyrpFEzUuJjAspJ7FfuuTbMZ6rlMexHeQFRdIfBgKJBQRrq4sdn7BsnB/W44cNa7yYw28vSGUiOWhI5eDwONuZ72TysofMzjmcjwBbSizQAqlcWeTP8gI77l5ktSrvqsYSh0J5g4QQv+QGIZX9hvX66hL/VoY76jYIcz6whbufdoW+II69Im0MImW0H0xxbpb8pI5g8E/t/TEjkbHJI1ZNz/NDxsNuGLx5R91qY6P8Nsi2Npj4ZXKvV6EReURdmZBx7DfpHns8RPiA/NkEEOUhCUIbdkCZY8ccIokykDZJOZEQgbC669ltBD0GYcD1EIQ8QNIKies/vPFX/IPFK+UT2FoR7oLQT+cD42J4QcoxkQzzwhz41ASuH/prR9qIHzr3j525S5POb3Hgc7hombDhUBx84xgBhNRuw957mtcD0Rr/uC5llinPkkVIGKMsSTVSR6e6aRqufPLY2hLX4YFnznFxDnkmuyChCBiTuNYkY+EndXRKOmVRHkQSRDE3eJEnAcYiNOcsnOE4mjpBpfgDWkrN0rl7f0Vv3vde0z4w9nruUH8Zp+YsIa33XKUu+irPC2mtSKlRD23YY0nalHEm97ydYkzWRX5gmNA1dBYBxboWX0i9YrzTGEhlcnDEjEGQSkgrQSoHhobNSzrmQKjCV5YWaHnhHi0vzvHLzpIhlRmWWBb4Nw17huOFXiRpqfVl86bzHG8AAEAASURBVBvT6/4bBZG1lXlKsMQWJLtTIc1eSEqMZTv/1nueOPaKtDGolNH98P2kjnDcnMrk6YePvM0QlJnVuzSzfJMdbM+7m9h4zhO2CYZ1bMz2SoFqeoIXwUTYWSwCJv0gxBFlg5BHlEMQUiCTr5Na/Ua65GHSRoAEUoJM4Da5tMuDUFxlySUkmTiW8hJLO83EqIs+2NdEfZDHnzj2s7SSWuEFJ9cqTYIs4YOAGOpZYIlFMsf/ywydXGLVC7LNVznGsZyjIp/CXsRphVgtPUL7eVcYs485PxyYQfBTMi8Q9jaVqIrgPD+iufV5SuUd1otdiEAQkVchm3wNEMko+2qMs9TUlOFzsX1EOaitY6yTh1q7XJlm4yWaOegvlcb94gOiPBk/SeninMFCiCTyQBpj6ROGTEK9/X0nzlJxbY/pm6idgb0QQNicYmV8KeSMUedON6qkMR7w7GVcoByORXKIc5C+BEut7TJIdwfJF6IqRBLl7PaQLi8u7jb68TzNYxq4Y+LW0FkE1tccqZJi3RjnICpwY2vOYxcq8PT6KhPK2YoKPJNa5YtgMwRoW9qrAm/c++ZLQIU8wqQZEtpOBZBT2JmCqLcr9AVxhOSuW6FZKaO7n35Sxzw73EtlWJ3JAQRlx/Ae+pvpP2O3CCzCChqEddQpL4QxztvU2UEmfcRBQrPkEW3ak7DXNTBpQ0r07ZdKRgWMiVomcOS560uerNhGfpLJAQifkE+kuQmg17UlDeWlrtc18WZ7dOw4/ZMf+IUN0mFpQ2KQpkMza3TsgeMwHASuzP8qBJFn6zKBdHCfHBg1C2CSEXk+IIxchJ8LJnbjWsiowMvVuEFjV8mq8jRLpxewI0y5TazABjFEPVwYEkiRPkJdjWMQxkGkgySWA6SOII2whcQx8qcneQV6HeIodTF+QBoRbCk2jh/deZoWctMOBpy/urCTfvDxp8wCFyGLNQSwmGNVFRO0OccHJ9rMf+b3aZS15gOH9npKKVEGAQQUz1LGCMaSkEKnRLBvuw7ak3PE0radHqzV3iuVYjIDFyDtnEx67y57o0fr7C8zzpN2J6VKvXGnne2Flwp8aGTCqMBBvoZGxth+coEGBoeNhE1U4Evz94xdJSRv+D2HZiNfftkOqgLvxJ2JCnli5/5ONF9pE5JaYBNlm/52hdpX+3a12qZ24IIn10Xbxnorppu5RdxHlBfK2AFb69nht198zvhShD9FBNk6sO6uMHYDfIyFL1jFhiDtmJM2faGPjVZbuy+FSdbtFsUuA4fg+KAcFtJgK0FM0KiDT7360i6kS/x3Ualnt1/v2KttaVPq4cVB1CDYjhEBPh+n779KV2Ze3bCvsykA4sbB8DlzxF8gfPzMdyRHWMVSouHoGD8vltiVB4JTBfWculINjUANjjdoNGBIIUqxCG8xAwfyqMHpnJZheyB7xTR8QJp2ncZNkyCklXSkcB7SzD7Z/GMq+YX8gNmLGg7QgwYQZ3HXg2O47bFdFV1c/hx9/bUn6G3f+yZD9EZHq/cKghgq5SjOqqdDX/5TJqHOQiC2EiB64TN8wuOBD/EpHD1FpVNPVspEn/1gxXWPV1/xnFtZjS1jAaQULysyXmRc2teSsnZaLx/jdyWRHOrlLm6bvqVYKjY6UXVxtW1urIduBL/R+JT4dxJYu7U0btdCUIEvL/AiPkMgWYPEpApbNiKO8voFs3Uja+fc28y285ZhxxlPtE8K6NU3kNNsZp3vp73X6Xni6AVGp9NAFhDEmXenr4f9kt0B+0ubPaYt0wc4AUcAOYAqE4QCoVWSiMkdwZ7cTUKdrz879ymaeuuTdUpUs2QyDTJxo+wPlZ2Ho7w9SaNFnCNIm86Z8w3iKUGuJeTTTrfrSnuS7xc7jnBr1QhTu57csMuOPMN9N79Gk9dfNtI3wXeAF3skXRJfDDFnlxeW2GUc4hdlIil+Gd39wY8iVkCLL0m43lnnN2cQPWzwjRHLSl6HKPLxAP8Apjg/yTHMGbNMysy7iiGfTutQUSMdIQ0j9DLBRJtYTQ7SiJXUiCFBBHfdM3KS5jPTTgMe37aPR9y/+HVE/V2DJ+nlpU/T2+hNhoiBLK5+42Uan7nEqnTsulSkBIa0Ma53Ghc8yn+SdGtoig6/zmSWP/LjVWBieSM5RYfe/iYCiUTA8xUXUHjuNkkFEXSPD+dq3t8i4bbHj30s13OnebfWG6kZVvONd1jS0Rt32t1eYOIGmekkAenuHfbO1bFCOWQIZNlo2+oapG0ViZvLAgcv5YZYMpmEayFIKkEqvXbXcVS+w215nukUiKNomqzOtvEQ5BSeQ9xEerOXkN/ezbazbeq3S8rYCJAC/6BI+PKF5+WwbiwEEWQGwb13ct3KdTL5by1waEYCJY3aEzcm9CATLMpggkdwT/JCDmVCl+sgdl9LyAPy5NpBiQPKDSULbP/X+I/76TPvxyUof463Qkxeq0jDTKLHFwhRhRTxUMCiF5CjLC+0gQwxky3yIibeYtHirFBbS0gVyqt5kMBEL8lqZjhtTZVXIabYXhAhjZjJItTWKUgguQwCXjyyRWznaHhnWTKJDOQSTe08SedoviJRdUhwyewog51iEBbL+1qbE9cXytsvJDjHbjSz60Tnvvg7dPbTf2qIn700I8t2v6v7TtHE7OUKNtKsYHU4PV2DLTBD3hFWidMXOI9JZOnpZ2mUCaT9QiHtILbHjYwJOz/IMcYG2oG0G9eRMR10bAW5RqfKgMzgN0TJTKcQrrYLlSgmbg2dRwBSRKipmw14KYcZgZcpgbGVZGIpu+uAVC4+uM8vA0V+ro6UEtLJeGKAX5IHmiJoOX55g6q9kyHLuwINsGukdoeN1LzdV+iT9iBlxGerpIzCG0VS1U2YMKlDIhQ0bKbPmGAxWQcJmJhBGrG7DCZkqYc27Mnfry2Ug/9IqSe72ggRRZv4+AVc4zyIIJsANBtAZuBfMUiQldKog2P2NU4jQw5pBDGCRBKud4pFdgf06ClDnOZTyxQtVfsFySFII6TRlcBEEyposEKTxxkgjKYESCh/SvwBeQSxRIZRhXPCpZmL7GsNNpHcAdTBhwct4oXcJUMaQQzrBZE2ohzGV4l/xNa/e4OJ4/9h7gH3ZocEd3Vidppufu8zdDU8ZbKuxZzYLickEmk4vs7SRmkL59EvsGr7vW+nwvmX7WqG5MlYkIxmxqPUQSzjT8iptIt0tCkBxLLXAibDdr109tq99Vp/QGagAtXQeQRA6kDi2hlAKiGpdPxU7jQ7rxw4PEX7D5+gHbx9H1ZE4yVsaf4+3bl+iW5fv0xz966bxTrY+rDemoU0L+RJBHCLt5n7MZh0QKqpxJGfCqSM2C7Q3jJwMw8rSF1MwAiwk2s2mLpYptqlEFRC6tc9mVgx2cqEW68sVNiYkEH8vIieTSrd7eBa8kEbmMjRDq4LAikEQCZ4d3/27GldYmBLC939CnoOIpRMOGQSdSKson2wvsgkEqvinVawqMUQRh5TkCiOxapv3UYFXR5ryIN6GkSwJpQllUguGuLp2D3GknwBHmfY97vAjl8j7H4I1yywSjmfA/kAkXTIpPFjycdFnIvYsnwREEiQxtTtGXPtLx1MG8K3su9khfBJl/AS8+jLn6VjRUeyiCZACkEgQRC9AqSQwEkCyi/uZqnoRz9Mb3zp25JcIxmsJPJBM+PRrmcfSxtIs8eom1jadbp1DElHgiUkGjqPACRV7SYzne91f14hk2aSzkRuK4JIKYeGJ9g/4j7avf8xOnjkNO05cMRIEfFiBtJ2//brdOvaRcLOQdi9BVv/YYEOfFT6qdXb2X9DTjuwlWH32Ec70dlEW+ur6/Rg9CCl9x6i+8nd7B3dJQbZRNuNqmKRRSuq30bttpKPCRshqORxM1JH6R8mW5ECShqImz0JSzpikDx8UAaTs5A9pEkd5Em6XRfHyMNEjvL2dSUdZdAOziUMDWZpdbXzfyaOilqu6h2DHOGzUlg1BM7YLcK+sWz1ECnBnpFXW7OED46/QSgNSYR0kZkZtjA0No18HpM861IgloMxR60WCyVZEsn/uCzsY6KxCE3ETnIz7H4oykbopTD/APKCnHSZKDLpNOXRHl/LSCchoeRPfm2dUrfum/Spw0+Y+NOjc8a2UQhflompLPyRLiEPKmiJQRARQCBtKaOUlxjlYTcJe8hDv/+ckTx6vVy4xwqevYwjtGUTQGk7SIzxhSDjENeRdmVsSV6Q9tpdBvZcsoiu3W1re7UIQFVYsa2rzdKzNiIA84sc2zhGu2wWEFQ6OcOEEr+NQaWTrUAFaSfIaSsas0bX6/yM2KgHXc4fHB6kPekZmltgf3TLt6nEs/DC5CNGbV187ASFHufFABOHeWWSo3cEsZTPZrqe5wkeC01aCZDOuCfZVtrxqgPNZJCwWamjXEMm2WYmaUzCqAc1NFZi23WRJ1IeuQZie/LGOerLZI7Y3Q7KIOAHaXycmcgmQpB3Eaiog5DHhTQvkHIGgIlB9goh/EBwHHbidGmVxweruJkgsPWOIZMj0RFnNXWBzZq5fo5V23AEDjJpB2MjyflC6LBKWgJsGuUFA1LEOK9kicV50U4uRBPxU2ZMYrU3PrC7ZI5J+fUUpe6wpBEd4s/09VdNc186kKLFXY/zMZNMllLGIhwfO9PwxQXq/4Nr0+aDPgq2EktfEYskMvLxD9P+pVdMlhBIGQ/2WBFSJ23I2JTzZmNpG+NL2pYxJ3nNttmO8lCfwshfQ+cRMCtaVbrbcaBhS9qsjWHHO1W+gJd0cpg34nBcCE0Ys5F60knMQa2ETHq1JZvPINd66ImjgHQwc4sHHpbhx2hi/gbdGTxMxdfYncj0eZpcuM5v6CxhSaUNsQS5zB94lP0F8gqs8gftCKGUuJLG7njc4eK977QubTTEwd1ie85BCIJKHSExbVeQSVom1iDtoqysxAbx8wqQ7NjE0qsM0kQdLoQCMd7YxBYM5zL5+7Xhlw6CAzvFRkFsHRuVA+EzgYlY/PjpDcVBIvEJsxQZLn+wreBKHg6fWWLJ6TFWVw+EhsxiGbgDgnSyJnDBNZaUYBzIKmkve0YskgGRxOKqB5lLZgX2ZMJRJ0P6mF/NMGmc5ab5whLQifJn6O40Y+xc27wIXTnH0k1+jkb97cRCLEUlDvU/fkeh5kbAamqJhTxKbDLKXyCPQzdeNi8MSJJx9jUeN/JckSbE0q6LY790dzm/c7meSBolRnlcX8ao9MWvnXakQ6Wn6tN2IFm/DbFv64TEp/6VH75cEK9OLALpFJKpde7v0EhHbCelz500k1DiKCi7YhDJKM/4+IAI4q0hUiaWIJfJezfZTogd6PIncvSYo+JmQglAQSzxQUD91VdepsVFtrviDwLiP/nOp8zEjMk5KFFzapup1KgF5bxbcasS00b9tSfSRmWRD9IJ4if17EkZkh1ZDCP59dqUCR6qbLhj+Nu/re6sgTy0IR+Z7Ou1J3mwU2xXMHaL5cayVy7wgHARP+tCKAv/jiYwYcuzdDLHq6nzxCuquUvyMgvVNVTb8gHZBSkUwuj1QgEJ5Hi01u4QK6eRll1JUebeDF8jRPvGT5uPu58xVnlj20Ys+snDZzqXhUNeOCcC+cswqRRbYKcu/12xE/MY21aO3r1AcxOP06HURU4r0qPZS0ZK6kUaBQ6QRyyYkWeM9LeUXUDhGM/TlkQjDc8awU4PMo6cWhu/RdIoMdpCf+wXJxlfG2u3JwW+68LlHaTa06K24oUAbEk77afP67oPY1o/SdEdrwYZz1XcXtLJZmwnbekkyGmnbD6VOAb4KwP5QxASiWOQSVFfR2+xRJLLRJlQYoGNSC5RLjZ12pDLZDJNb7wxT/fupZBM353hCb8cMEELeRQiKTGK2MdSp5Mx+oMgffK7VifsM90TaTPkTCZgTMqoBymktId7kHy/+7HTMZFjH9Sf+AlnFxjJQxtiH4ky0j+brErZVuJ6xMduz6yWthPqkEdIHxGMzSMOmKBBVY0AIokFLzgH/cQHbnqw7zQIIMaAxDJOhUyivqivkYfxgHiMx3rmrmPTiDJ3Fy+Yz/6JMw4RdPUVf17YAxwkEfcPsglCmWC7SlF9w1YHpJLprCGW0IbveHCZy4FsQr4JkskLdlhiGWW1t0gtHUklCCd6wrWZPMJ/pB3wTBHwPDFeJMixPGNJb2YcSR2/GG3JdWQMIU3SJc+vfrPpMrGoFKxZ5JovD1vSTvvpa75X27MGnKz3ixS9FcffQW0n7ZXdsPkEoRbJdzufvBLHJtG0SWScpY2ilhYS6W5Odr5JskuGp56apL17B3ibvDRv8FZgdSJsyVgKxAsDbNtCpOEjwT43ZI4nQdaimiCkUmIkmjJOdl99e02S7sk86A2hHnahAcnDxO/Vtl+6XKPIRERW2mMiR8DkDgkm/EOiTRwjiARp/Z0fNOTHJHbwK212PChfgIkTsydPtXWlC5xvJI/CoJCBehwkCZLILEsn4ZoHY2httcQ/xiG6t3LRjM/dmX9S8c2IfDgHd4fU4jrNX5sjswim3L6UucME0qikXelOPpyXOw7Q4XLIHWDbiB1jUNUQRdhSmmXluAckwrayLK1kMWqZJxqJKupcix3lv7M83xfbU7K7ntwf/e98L7xoZ2255odVnrOQRYwfecbok9c4wpjwSnffg9+5XFPGkFwb6fhI243Gq1/7drr6FbTR6OxxP0nBOotEZ1vHyxDchnn5YezslVtrHQum2vFCUU86GSv7leyE7STuWolja8++UstIGllkIiQSGUImK4VcByCREZagyC4gkK5ggoYrE5BJxPgIqUR1IYawJ8MkihhBSKXEkiblJUY6jiWWY5Pg84U2g5Tzqd50skyU7ooyscoE6s73OkdZkEd8MPGDACDNbgN5dtt2HtrELgJw8moHTO6ogxht4mMH095xh/h4SQ/XUo4Jg13HPob0LcgiGeN30a7Ix43U1pA8GpIoTLFcH8RK/D9ip5kQr5i+9MSP0kL2AiVzU2ZsYnzeWHqZHt3l2FQepHfTlUt5I42ERFKkkvnZWbqzcJ6mb5wzrU89ctbVS+9T5/rOz1H8DWebQxBFCca10ZXG2x+CVJZKEaP+hrQyYnZXCtNj+df5OMo2kcd5O0/22frC59ipb4z3xh7kFeYZKqTnKcSr1XkJOP+hpGj/3hS7QVqjPXt4P/CFWqmzmyjKmEBfMYZEcih9bzbGuJSA9mSM2uNV8puNQWbUr2CzqLVWXm1JW8Ot2VqtSPCavUY7y4PMdXK7T0gn4QkDNp+Tuw5Su/xO2hj0NHF07+9sd7wXj21ppByDRMZ/5h/XdFf2J65J5BMQSfuDfJBKBBBKfDDBmkk0xAt0WFLpJoaiRhQiKTHawLHENimUNiRGGSGMtiTUVO7gl5u4uS+FCbRRGdSxJ1uco55MupAUXiw7FEeeBJSRCVquUWBVU72tmtCmTPKoI5Kimz/0PtMsSKAEIZFDA43/5IIskknZEke5iMQuYijJiI3amsmVuOoRB+FCKjPFHL06zItaYtO0f+w0q6IvsbQRri5KtHd/hN6YvUBDxRN0iz5H4YnLRlW9J/EEDefPUm6BjXf52qDSj09+CJczq6grdoomZeOXdBcE1g7wWQnH5xJsPPHy5BeknFtyifaP5K6yjWTEqMHTf/RHtHsfk8k7QxRJTtK1GzGWuIK4580iooFElBKRAj2yb82QykgpRSuLGTpzJs++X9fowVyKFuazNWMSY0gkh379ayZdxqSQURljaEPSZLwGaRcG8+6XoSD1tEzzCMCWtNvuYZrvdf/VaJcEb6vufCscf6fWVmrIaT3pJHavaeR3UkxcBKPGs5iU7EIM4ggbwX4OIJCJM87ezm+8UaoskBFiFvTehFA6qj4mgSxyBKm0iaFRfccciaUQSLQv1xJiKOduImm3JXmQNKEtqSvtyblMWhIHvZ9Wy8lE6qe2a9QPTOqnzoSNFBJtyORr9wfXkHZEVW3nu49RFnUg2cTx5I98j+OA2ioIMiPkUWIru/lDsCBhXHZtN/uSPJTljyGKHBsfkJxkL7QBeYyHovT6vgQNDYdphhe6/NwPvpfSbJY7EpqigYEMJZn4roUv07G9p824wNi4n3mV1hPnKLvKXgfK11u//Hs0FDpF+9iucTh8miWAWGwkudIpiR01Nc6AjY0Pmw2bgFXpdjpenmxS6ZSqfgNvSC4fTPJCHR+SOfm3z5sKIP94bo8eSdD9mUGKJ0fo4qUkG5MkqBQZplB8jG1Aee9vbmf3Xuxrm2dpZJwe3A/R5FiWRpJLdO9Wmm69wfspsrQym15h++c1owL3G6fVngY7EjIqLyqoJWnyNyFjtl6L2DUmat4865XSvM0iID706r14bvYaWt9BoJ9MArZqXMANVJBdaVqxnVx8cLf3VdXJn3tP3/99iOT00UdD7BMQE6Nj2+gmZEFuFNIb4yfPo7CQS8QgkUs3jlFu7jgtzxfYYz3vt2kcQ8sfG2zYHEmSkEDEXgHkEUHIpBBMxDJpCdnC5CUfaUvOg0xsUqdRjAnUvqZdXvpkp7mPUQZtYPK1pThSDvlQVWMRgVe+lEMs/UAsn5F/5tg6ChGy1c9CIpFmp9tt2iTJTq859iOJnA43PSCJRgUM0oiy/DFEsVzPRMizQraUp3Nv3mPGCkjiF7/zGUMWV0rTdPrgDxDc7WR4K8Kr9y7QvpGDdPwApJLTNLPwHWZyGTo054yVWzt5fBV5UQyrrZeX2ASDrzEaOU17WYqJVdYglVVsWHJe1uADGwQQPrP7i3Nqds8R3AQbIZUo4ieB3DE/bbZwLDezIZJtCfHc7DAy5pzJ2MUPLGyoYvFBCkcHaHAkRsdPJw2xLEWHaefeMEsvSzS/UKT79yIEaWVqJU37dy3Q2BAb7rM6fH0lR6+/tsrYrvPOESkm0vXNFuz+eB3L35O8/Mg9yLlXHVWfeqHS/rRO+tBrf2/7u0UsjEl0YHeUTqCyFeNis+Q0iHSypyWOeHD9LnUceNczvuMPhExImJA2iX0rsUzHmZr9SyAH0siRQ1cosmOahsec2RgTbpbJIwKukxxwfPBBHY0PiGWabfAQg1TiGB/pE47rBSFNEktZOUcsk51MyBKjrNgLShmpXy9GmxJQzz6X9EYxCCTIIVZhY9KV6+dyznaDtpTHT4KE60IFLiFy5ikitnU0ZIclbfCfKKQIZXAM3iBqafHzKKQIZfxIJfJMcJG+ikSRM2HviAU0opou16iNygRSVlsnIzG6OuqMLoxNPHfY0iKGbeOXzz9PdxYvVtT3M+u3zUpqjJfs/BLzUl40tAv8tDxCy3F4+JK57uQDjqcvGCI5ytJZ+GAEQbwzdILOHfk5ukxThgACGxA+7P6CfJsUGgzLNqT2zTSSQNpla44/+wc1p/KsZUzYmfZYtdPxQ2uIZYJtinYO0aFHB2lhGdLKEbozO2GklTfvwOl2jo4+BjV5mAoZ3o2H1imXekBQgcfCbEfJ0kqvBTv2texjGesieZRxK+coizT7xadd6tNzrxbpU39QHe92v/SYf0vVJGBLhoEsjOkXLwGd9K0ogKfWljri+NuWTvI2Er0fQB5ldXLv97a2hyJttFO9bBxtaR4majnHpCwSP7RhuEIQ5shlIXk0IVakJw6cNZM8COHca4/T4L7LThYTBJADhFicJzS+NkhkvJyOfkgfilwOxwgoh4BJ6RZ/sIJZVp9iQsOEJRObKVj+Qlp45VWaXHWcouf3v7eSLZO21JcM9znSJQ0xPuiHXF/qNRPj2vig37duOBPi6JDjv9NuR/pop8kxVOD2fZdOsYkC2+kJOZRyIIlwzA3fjutMxgdZsid+HkGMQB4NQQryiuAij7bq2UgZkS9ETjpgx5wnWxeeG83Tn77rkUqu/exh22jGIa8VOsIk8pqcc2nsQ51fT9PhBXbIPYnBWVU9Q1UNdzwINya5L9yfUvEircwT7VtdpFiapfDMoA+/cYWJcoi+ceAZGhoM0YHlV9jdzjTxjqA0zsMY5FE0rLB9RDAkG+S8fC4SSCHfDoamqOeXaZPrQupoiL6rlPtZY5w1Cs74KVlqZIypOOXyMUrxvca4DYwuFjbT4mqChocHWAWepVJ6nckn21QyqRzm/XYhkcysLbIkZYAh45cO3goym2U3SVD38981bOfcalC7fzIOnb8P5wcD9pjN7o8LgvjKy85dv8r+/vGxg00en+Dhjo+EJ/nd6ewTPS+bkO62Nc7zM4XtmIbOItBvC2NgjznGjr87GcwCuA7v2R1i1Sf/EvV+WHj/u3q/k64ewj5z+CO/7kolSmUK9Ox/+vEN6X4JQtJA6MJsrI9H1sobFtyn2L4XRYKIiTY3d8JIKHENkTahP0Jg7T4gHwQShPO3fupLptuQFsrqZSFwoRt/RENDvAvJGhPhlQs0HrpmykaZjOYNQeX9lJms4tiE8aNUHK2upC2OnKHiyBNOns83Jki5NorgWAigVLEnVElrFONN9qVvXKW9Bx839+XVhlzbJhgyYVfaf+/bK4fugypBtMmiu1TteTqXpttrc4aAYQcZ45anHjFsRByt5r/0jh+hc5M3Ks/cyqocyouFvGxgfKzfusfCsoxTpnI9+VlxSAtWV8tKa2nsUxcPlu0P2YyCSWOcSZPxsMMFVtbZqwBXhX9HkGyQwL/b+W46sPSq2b9a2rAxlDSJYdsoZFLS3DEkmmM//CaKPvtBd5bnuTxfiVHIPrYrIR1Bxo67nLzsIN9d1qnJ5hK8QKtY4BthLwvxWJRxYIfpfJ5js4BYHOTRcUFE7IoowzcMfQSce8vvA64hfw+xyDLdubVAu/YdluYrfask8AHI4h/+/kaSaJdp5vh9HyB63wceLgJ5+/o07TlwtPIcmsFLywZHYGVpjn3O5mh8x77glbpYEuNi36HjG1762tmlrRh7fSFxBKhQ+aY+/9l24tvxtvzsMwtN2jYJecPkmWVpFWIhcpIX5GaENAqBhA2bhHTkMk9GjkSRTUZokBdHgBzgOrhG9TrOQhmpJ5PiaFnFyeIQliZ+muK3v2gIYTTFhCDr+NWLlklils+xHR5Cho/R9tpqgYbodTZuu1ohk2H6AoubjlJm37tpJeQQSLmeXB+xTdyq/XAkh7YUUCZnqYu27InVbhuLCPbvL9IBlkIiSF27DI7t60HNjf2z7ZD/6Wcpyn4DvYJIxITgVGMm1EyYEER6Zo5ZVBULJ83+0thTuka6aEp7fDGphL2jcdXjkS1Jf3E8Qed3XqddyVM0n5mW5JpYXhZg1wgbRwSMpVdfu+6UY9II3gi7Sgi7HZW1QyArpLFMLN9xK2nqgNgVCuxC5+QpKl3FXtjOPY8MsvQbojkO+HO5NTRFP3D3cxUiCKnt8u6TND4HNXgZKy5nE0X72DTk8QWVeOGFaXpj7KxZ1GQ/X4/iFaKFchgTYl6xtOSMQ6RJGxKjHRk/0qZNGpEm7SEdAS9fSIN6iHcWMGn44vc6fptLUHRgmKWYTCpz7A+WZZgRtmmOsKeFIntuD5Uy/AygSYjQ/t0MSoF3uornCTtJjI0RSzn576/M0O3+tpswoqsIn/oDfFjrwdLI939w+0sh+0196jyl/vw2Ww0O8x9KHwRoEfBSJ397nejyVo29vpE4AuR+kjqOPPdRY5/pNThWeXnm+/7Pt3llNUyDCgTqpoiwDq7RCokU8uh1QRCEdVZpRzO8ndzIZWMLiXKOxNORQqIMJI+/88yfmyZWb79C44v/F6uhmfyVAySLdqhIFq1EkT6CTOIYhBL3IzWFYCJvdedP0eqO91YkjLak0WrSTLhCCJFuH9vl3Mf25J6Ir9Kt6w8q0hkhCFDLn2aVtE0K3O3IuUzKhV/9VxV1quTZsRBGSROyKMTJTYDmWIW5lF1hG7m42TqwripaGq1IAiWhGsOu8QVLRS3PtlqiemSPNZTL8f6Z+UXHvtGUwnU44BtOwC9ff9WQScdqIkSPLPDLyZHT9IFv3qGzuSFTFtI0PPHisdO+OAGTHG9BCFtRMfVIHzpFI3cvmfTlPSfp7j0m7vtDNMRpIqV0LgB7UR63TGatPxvJMrEh+AGljjUVrRN53jLe8CJh2xtKUfsFw2scob4QR2lT6gaN8eJjPiydBGbYQafINq9wlJxOx2mYtWX37iVohOfcgcE8/eYnk/TiV1gFXn5hCXqdVsqBQH7y31RfWltpo5frgCA8uH+bJUvHermb26JvWyFdaxdQWyEdxYYGaysLvFjvcLu67dlOX/311lto4nl3XUqEitrLtlG6I5OvnG82tiWCmMylfYm92relj+58EMKxyQgld18xblmwKjudclTTsfSJipoa10KIT/8K7b7zP1F8/buG/IHkCSEUsiix5EmM+jiGyhqfYlnCCcIopFHuY3juizRx7j10ePycIY8rlvNtTMAyCWOyxcSLGEGO5RyxfJAv6dIGYqxMm2AMJA1STXywJ/YFXgTjLKRxtjSU+tKmxCiHEPnovzW7npgTjy9H6uZI2kx5lrqB4MB9DfLEFY0sltk5xEvzWZKI7QJBHhGipbLfGnPm8QV1dpnUuXNBGuFwXgKePxx64+XCHTDW5Lmj3PFH32Qkiyfg6FvIaVl1Pg3SyA2YBTrlV4EbbPaVvH6JTqWHzH2hCjw/QjoJW0Vx+g37QzlGH4AH7EBh52hiVl+DNCKEmRgN3b1Iu3c5pPHu8EmaGZ+imbEpus4LcPCpRxpNI234kvEnEnAhjSCC+EhAuowrScOYkTKoL20h311f6tSL7QU7kdggCy2HeZyvUjGUpLGd47xwZ5AX8uRoYKhEH/6lGH31v4A0GvrO5DJPE+P89463N5B6fCD29Rk/9frhlQc7yV/676vjzatMP6c5Dp4diXo/30ev932rpGvtwmEr3AZl0p3bn9rGoa+II1S/ve7X0c+u0QYdxz95ukU3Qzz/lOdld5PmHJO5qJVlkgfxEvLlrgQCaZMGO1/amdgVNQQSEscldggN20jkoc2Vrz5HBVYvIwg5lDbc5BDnKGOXk2PkIYA8Sj2JE2UVN/Jx3eiF36CDo+dohMmhBCFrOId00J54kSbnMjkjTQLyUB8B+ThGGysrzp+HtC1lQB7xgRoc5UQaiXbkg7ZQRvbLvvPz/8asEEa6rBKGFK3y4XnULQ0DQUKQ2JzwF+pMsq9BBJBHTOiIxam37wTvQR7/01snTTvuL7jYwdgQkmjn2yYOr9/8jrm+kSxyITGZBhGU1dWGVJbzoMY+vhgz94r7KrBq1eEkDpGQhS7hKSatvFMM7tUrACv5gFzDsfruxWm6Hj/JW3oSTbAKe3xumnbuCNG+lUu0uMvx54j2QMSvxViaHiDIsw9Q1LMI6uPFRQKkjTLGJA1lMG6EcEo6YklHHsqhfqt9ymR49TZvRYYgKyQ/8stJunCB3TYZYg97Y355K0bZrRDGGTwqYB9wYI2/BRBIXv3NW3GyDJNjkMkysWySVG5n8gibu37ZNxljoV9DJrXK2rDhvun+VrgN2ipn6H1FHDFCsNikl8mjn12jPbqL/CP79Jn320mBjx25RXUialRRiKQQPZR3k0isvpZtDuu1h7ZG2LUPPmjjnSz4Gsq/bsgFCCCI3irbKgo5FFJotylkUNJwDjtHu45fPdRBeUglh658wkgeMbG6g0zUIHRuoogJ2CZ6mIQRJE3qFplhwCRAJnWbEMrEjRjtoY7sRuMmBSCPCCi349//zwSVKMzLQGBsomjmZS6HdPmgHo4RUFbsHnE8Ghtz0lnSiEUyCFgdbd4q5M3CazLnPNg8IoA0Lh5yCGhlBb7JqX7hmT8yuVHyiBKQSO6IHq9c0yaL0gLSLmP7Qe6LyWcx1nsW2WdPOYCwwC9psejgVMDbCQdDIF1udwSLctVKJEQcuJwIsfH5yrRRVYOkJm84NpCj99l+ki8BdTfCI+lpOp87YVwegUguzjvplUbLBzK+ZJy48xudy7jB88fYECkk0t1tCimUNt3nqGNLK91jTer5xSA0smgGZSD1c6+SBoa8MyO/3OA3gQHDWOLnw5vpcByh8QmYxSPP2SEIzzRsPiCS/OzwYYIJYomPkVZiHHqMxe1KHrdq8magH+oA6Vo0VrX/7WUwtko6Csff8DXb6dBXNo42GKsf+5Wec9FTz67R7vuD5Qy71ijQJ1/8xZpVznYZv2P8KGE1JX6wNxNA/ESiCKkSCAICJm7sStMoFNj/3KdOP2aKwT4RZA9zvkijhJxCWphKsVsbJnw4bjagXbRlSx1BHiWkpz7ccOU1ymKSFVKIcxBFUXUffMSxWbQn8nzmFnveH2JJ60SFPNr5aEOCkAAhnyu8UAITvJSXdLl+9jvfoZH/5cM8iTurhUGIMGEj2MdOivMNNTWIo5An2D8uZxcpU8yyOxdnRbOjErZreR/DpvHF7xmn5cMO696ZPEhz6VvehTkVTr/vs9ROxohd8PDwo5R7MO+QQ8kAqWCuYIaoPU458dHlCP367f1S0hAL3oiFVdC8GAZ7U7OUEVjY41DueWXfSRq8falmAYw0JORRXPZIuh3DzhEjBxQRZgC2veS9H3wPrb/jQ/xSxCu6+flhkROeqx0whhBAAtsRMD7kGvYx2sa1Gl0HdbCFpj3WpF/SrpzD9OL+7dfNvrVI8yKNUnZTMZ69acCRYTq/U+U0zsO5Mzb4BRAHHJ58MkSf+C1+obn3vDnHFxbXeYX8yGM1nhdsd15e5buRduvaBdp/+GRHF0F047567Zpz964bl0cDQ64/1F7rKPdnK2wPt9K2NvJrHHoQ54Zdiv/oW6lw6TwV52Yblt2KAkFJI/qyus5uM/g3c8fwHvrGtb9qqntQ7UVYJLBZ4gi7MAkijUSfigWWAPEKTfzzuwZI49FkhH5skkWOHFAfEz+mAbSbKquykc7zs8lH2yB8IIIi9bH7YBry+EIZIYpoCwFxpe79r1J+5DiFknucTJ9vkLYEC+bkg/Nduzkt6RAETNTJ8vHMDG+jd2eZJaFsB7YjQRnmZfggYEKWNiRGOo6BF9pYZlL67ZegUizRsWMOgQQJQBuoP/joPgqdPkuR/+8rFSIIfCCJRAySKBOsSCdBnsx98zWMVIjJFR7hQmbFkKEKP+ODWChG4VKE5T5cqRwglcyzmvG1sTD9yc8cosx4vPJ81/NlsasUdsWpArv/4cBDzzxLO3vm7jWauXeT+10eL7gBDuJ4HGrqB4v3DYs8UiaNIHlQT+ODe8E95vLc76VZHh9OeujEGQov8PljU7Sa2EXhxVl6ENpJ4/k5U97uA44FE7jXSezfber6lTHlMa5YeAacDYF8/CzdnXyS4Jg8wapuPKuLFxwfpSgvLwEyjtxtt3KOMSMB17PP5SUD+fLSgz68/lrJjFukozzGsBwjD/3HGEMd3Ju0Cbs7rLgeHB5vmTRiDOb5OUF9jYBHvXMHT4pp54UHz5Evaq6La+OYv6ofllziR8IZIfzMSmkKZ+/TzI17dPFvv0bvPPnHFF3lTQuWrxhS6fwKOdUdhTmPlewCu/biMuVP7M4fEz6hle9QKbGTP/V/B7i1jgYQ9DX2Tzo2UZWqd/SCD3Hj87O3aWLnATPeeh2GNXZcG+MflkSyc9LA9dUl/h3ktQmDjhapk5j0LXEEKL1CHpshjej3te++RksLczQWHaULM6/QcpoNipzf4oZ/BAUWz3Rir1kQMXwM2eMJHb/5IKklVldVSBr3HaSReKXmD0+O0Jnh8qpYTofUEVJBlHWkjLB9wg40UPk6EqU8qwlBMBFABiGJBMHIZIqVdJPp8SXqa9Sz+4Pj8MxXaSn0OKVpr5koZaL1aGZDkkysmKhl8sZxqTBLw6PjPFHWLjpBeXtSxmSOevakjcn82ONVh+LIR7ndnC51c2N7mTwyOfrqVwzpwSSMD8gU7lEIFTqMCdmRTuLenUkaZSO8r3SmwM63WdSLc2A5zHsrp/IpKoWqpBEPM88qxKtMGuHg21yHCUAie5wihV20a3yMllPzJn3nwElazc7WYOz0wRkbo6ETlCEeA+VQYNYAH46GKKBhBL6eIYxLM4Y0IhX5//zmOO0pxs294f4QIE0298f3LBJBnEeYKIKohObnaDA1R6ETp2li9pJJk9XmINjzO9mmkf1aog4Cypb4ZXJhJxPI1Wq6k+t8oyy6ilg+iafO0uF3vMlIpW///+y9CZxlSV3nG3fLPbOysva9qqu6qe6q7q5m0QFkGFEEBMTnjCIITetnPm/ePGUcUEAUdVQGFxT0M4+ZN883gyCry8hjGXFQxBkWWZruru6u6qqufe1act/zbu/3jbj/m5En7828mZWZVQX5rzo34sR24sSJPPE7/y3Oaz5LfM1z5B/xjZvS7vrVaRDHxwXl+PCwORRfY6Fx2rC5RNsGHG3e0B7ziLG0vOQ1/IdQBYxSJu7XlWeG3Je+lHW/+NZWd0U4fjHEWBlAtzGkTxDnPC8b15Ba41fzIK2dctJTGsy85pG2uGS+PNO/3j1yYot76XOl1iBiviAC1389AUFINUzcCG4lB0m+rABl9vqXPYBMTT0jKcS9VnRFwxigr+iFv8sudrsB9KGB6+KOrtF7fPlE64DTJgFTtkZdbrqtgSODc7PB40JBI33Ol5u04LR6P2vr27e4b577e7nKKOrFWxBXRweATQgCvcNgbOCXXt6gvlwGVskyEmDMv4wlskZHCb9TLPDliT51QOwi0a/t3TWjBwDOmACPgMTW1owHNBjUsN0h90PZCYHFNuXBRaPmJOJyiWKNI2lcRmuTcsk0y6O/7cNfcdkNd3qOQ7ywsvCyEHM/8UJqdePQ8v0CPn7Vrdu43vefdDsob4sy5RAVei6PFmqIcgYObVElNB036iK6BkRmNm+W/8KDrnzpkgdKtjDDdYM0VDMWZM45IAOWOT2j4fy4vz/Sp8py1+RXW/VHYUZz7fiasvvMi7a6Uy94gRvNBw49YH6nrt+tbVnOyIiktXC3y5bWu6ESvhSnnyX6jX0jV/11uXY+1eueJ7+a5wef8GmliQAcubYRXewdok4Yd1p7x4keb0nNPRoRBxQABOFioYPI1LYy/nr62AA0w30Mc1GAAR+FahTRPaARwxdAIuUZO/JaxgKX1MbS2oyvDVAFqLM1pNuw2aXv1VYnIg/ABAh5RgBD7sdzoytgDAAJmBzU879WAXkPP0xDAfzF888nNvhjc8zqo+PIjkx+PlYAGn2KyeYadWOyeW9tFQSsfuWX1+t+JRnQDTEeAL3kuMRtzBe3ugYYeYaoCti55Vs7qdKYS09ecSkPGMN7xPIIr/Std4dPbnWv+N4nNS+4z+hQlPnEewACVGa4gE8Le6FTHI5kauiYy178C5fvuMOVmzZV/zZCzeX9nRiXBEB9Wwmuz/Leya3d+vjYkF8j4aDfDtR//ZKclG9d1rnYp2us6dF7TGvCctNtq+OYHJiV1nnEQAdDmLnc7iT7aOeXr2sftYhiXUfEM/5/BTR64Ki3pbd8rrw0eTHBXQoAIR3ivGqVvhzkASxcUXawEL1l+1Z3/5oOD+QAejGgg/OIZfRcBKcRQIkhDTqR1DdH4MStTULAZlZ/B/O1addrROeRxRYgx+JqFOuEeUAoPaV77g9GJFaG0OrE5eN8i1OOMnF5DGgAG9CQ9Oie/8Jpf5D9X3nEdX3+T2f4MZzL9yCLM+ARsa+cJbkLw9f0/EPbtqMMHMYvPXdt1QAm5GpxHb3LldqP+1M/rxRDP5X9zQGKJ+XcO/nuYZvBc31YOQfgb3qxE9f7Xb5/yG3pPuC3FvRgUe0xVc2P4z9NP8f9709e9RxFdAtnWIlrnk/Jr2PTmeBax3cq8cO9Ai6tLvqPOLjGqMY4l4kq/pR6EHXN+ChZnjKIt8de/aDb/cPPDhUSvzZfLJlnanqrlkYI0OuSjiRgD7KtOOfTVfSFF/BDfwCEpt/YSNXf/fd97gtfgOMx8x2hXQzdZkl3saJeCpqaEqDLVF5UapDxJi3rZMhQuNDQJR56xefcQy9/uKGyVijoS4br+vejz5DEY8/P6Q/xXm9E4fmTdXbYsXZuNOy7FnSjv3Cmto4m7S/WMPJG+/adVH+g97KMuHLSSV5/y9/WSugeJnWYl3tQvmOAIwM18d8+sSK7y+BPshHr6VoPj6/9Z3pnAsdPPfGn7m+enFYMr1WPNBZlthrLNsl9Bp/eBi4VN8Dpv7phJ1WApX+Jcq71QkttvabnTC9LHFoaH/CcildvXut+ctPGGeUN9JEYA78ZheqcAB47OjLas7noOZBWDNBoIIW0OB4DVStvIcrzU/vfbacNhTG4o8LAQFGGBKdcW9e+qqEE6fOBRco0QlyPRT8YYrDbzDTQZp/sfcXDbuRrj7qOc4dnAEm4Yzxns66Or8VWhP+Q6XUntzS789vaPFi0MQMMsrc0tFb+Gfvlaoe0i4NH3dSEXCuJcydYpkW+sS9Va3dL8cfd09f+sytXBnDL9YK7ezgrbvKk26t7vHMi61q1UG9uWePnDsC2wHZbPT2u9NQRz+0q49pFZdB7nQEofW/DD+DOcwZ1Wr7zHtd05ojagyPP30Dos3WdsnAg2RGmFtUDk1i7H7/3QQH7snejlKybnCNxPnkAScAcIYARSgJIjG7IAVwuFkwm+2Eg8mtfKbmXvSLtud1cO9n+S140po8vsSX1EBgDGy/KQnFaHA+5i/+lrWxqzKXmML5Ktn5o33H3h2+e/32YrFfvfGTfW12h/YDefsEgytwJIamYGFff9JXU2tahd5Dec3wYiW2azjR5zk0ju3zw/oZ4h2O8yPu5npeCZB/xTHDXxvt88iqgTI5O/fOrl06Lu7ZBEoFb3x3PSjj+Hh3pd6hJ9GzYXn/QljDnOwo42rgsF4C8EcBofWPXi6t943ZaDWOuYzUxEcGkH1F2Ti+mWmTg0VxgzOJWVsDjQrmVpte4t73F/UZCRJ3sB4DPaC6AZ2UIrQ7cSsTXdk59QClibytnaSZOBcRYvi+kn0a4jlY2GbIwF7WV29XLZ7Xzw51VQwPKJRfjZN3FnifBgAER2jNRY/OnP+T6+8tu/fqUu369pDCMCYY4Pf/HQ56zeWnyMfdHX/zlBXWjUJCYT2CiJb/f6/HBVYQYX5yA48/RgKKFdoF7//GK231u3O0fEjqoQ9sy2iJRIsWyFuc0nMJKOR96tqZi2kKv3N7pBrSFIE69sa42f44U91yr3TPTSIeTKF68a5J4u7Tv4Iw6CwE/lAU4Xn3xg9XxBgDWe948n/k+IuyZ0k/jTmLFj+9Rs+YfUDsH5QvUaL42rZyFcDixqLYQEGkU9/0jHy66//rHk64Jq58KzTc+PWslhpe0PwkwrX6jIeLp1PgF6eLKCbkwvj4Rfbw5q49nulvnW/b9b/6Ae2DftC5to9erV67eOyG5w06TnIIW2Z0rJa8LEgu0trVrnqFyoeekA653KpMT57bZffrIR2d98E9JdSPXIq8X9W6sXgcr6fj3XQWQ8wySsm8ny3XjQuOhY7lopTmw35HA0R5OQVbXduSfChwXy2skRBxtoujFchiT18lrob4+IDPEGjQfePQvOSlt8UW7GAJI+n96+TXKrXTyDVgWtxH6yH3PaviyMfijUgwA40ZqpSPKZk0x8TSABQIgGnczBqWWZsCmtPPVrlE3HbbAx4s2rhOGB3vdxq17/HXtxwCD1bF0wrh+nL6QuC38gEVrz65p7di12ZWGrQ8huJS2J/fRq4+6P3n4Vzzo65086gGg1a0VIqqGO4IOKmoDdm5jaXXsGezbLLHyX3zRvfp0mMOt4sxMyLF0kuA0btXiCi7gMIxgIeX9h060wJal1H19+/Nc97XpPaspB7exeMfdLheJswE0iJj9XtMCfgY2CeFIxsAIcf5cbnq4RnLLQcbZAJ+B9/iZzAUsaS9J9txog7hxnOFOorYA97m7ut97cOeUbGO+8/galGU+AVL/4L0Fd+qkPsBaZr83GCdoPoBIub37nDtzOpRv5NeDxkY4jfGkqDS81FxHmq0HHue6l4I+IvNwEXNZl9PH1PG+J9ynHv+4O3nliGauZjaTW4QEiNsoarLlpHB6o2pDqwDSD2vNn5UWy9bsxAISV2JbxMvnT7h1m7ZpzVx+wxhu/TsaONZ6tnAjofG/+mQ1O7mV4VKBxOoFoshUvuR6B2sDR4rNBR6Lenuz1+xyOD31rz29+ZLcynJh1KWKk+4Xd25yBzraggiG96W4VHyF896s95IEPMYAz8AkICTJJYyGyEetLqAQojxpBmisXUuz9uwaJ7d9zNeLOS8+ofJjiyynBggsfz62v9WN68VpcdzanC+kDu3ZYk958y/ZSF0DIoAcOI/v+8I7fbV1zXe7a2NBf9D0FkmDk2ggMdl+Xj5GMXQASJo+JON+6JtX3cuOzZy7GTkgL8mKu6OpU9bYw76pHr281pWDUQkJRYHIjETSSa5jZc0Vz1CaFb5m+CmpfqG5syaYifU+p8SFzOOSS6CmuTlwg9y+e9wz6+5zux/9pNepRLfR+4dU08bFxB+kbVdogOn6C3/SNb3xoVlzIX6WFgc0JsFk1P26UZ5t8qOAwrQ3zY0kxZAUDuwDp7uWX0lKzkePHy65X/i3RbdlS9ldupStOabWBuCQY77v0ka4kQ2BRm5TBDcSDuRkIYQh1bml5jrS7mLAo/XnqWszOfr+I9yrSwQjMB6bl/LYxFZF3o0+zb8pVcC/N4GcUSG7QI3w51/yHrd/w/01cr57k+Z7P99KI4OU8JK2WN0uPe7lopW4RrLv33XAMTkAK30+qUW5Tw7A56J64DG4x8HKdKaLmLnautG84sgz7h13bHMH2tvVlF6VcC39oTNTPKtcJIBJAKVeijqwfETMkzXLhKgzBvAsyYCgndcKDSRanoFFzsmzNojDdezreL0V9Ytzo4t9IzopgIB6oNQuakDDuEykx2DTyllo4JFz4gFQBG5UDDisfDKM6ycXOcoC/gBZOPImXpQ7m2ftOOjBgulAwlE8IeMYnjHGMkY/+lfn3L5BQTyebYJS4qLDwc7If2STYOC2CqfRihkM4tzihQqYtDKExWyLyxQmwhIrRJdvk5NAkYE7f6KfGDxaGoAHoqwHinIkzvQ0y96YE2nlAJ7uaTkc122O/vHnZwA4nq09P8rbc0s+d8oA2rkz01XtTh126eEnqObSQ0dcdviUj/PTX97tWjZLrC7xOhRzxu160x8QmgPSuYRMXxKx9I4djX1U0N67f6PkThyf0PaZAu96b9g47d6jj5Rzvukb/qHNDbJRMAObhkBj8qrhNjW/Khk6v2fPBfcf3/JfkyVv+Hwx4LHW31OyI3DCePfhZxeydyVx/070s58MUvynutL18a17DsY93H7l/UmRCq2CRxuJEK60WHbm1Rd2Njkx4oYHet36zbsWVnEBpbnGYN+1WRKyBTSx4KKrwHHBQ3ZjFcYni25geG7gyBVqgUe2DINYAFaCSlND7u3b17p7O+ZWQA5f3tGLsgoupzmELAheYVxhAJjiEAH2InDCPdUSXSfvFWBo1tsAIAOQpEMASMTdT/Z8wu8AQpot/LbQIxqsB8YW8mJKAgmuNRcZOIjLWN+wukbkXIuS3CrOoRi80jZtvfPtJbdjp/wMTjzqvvz1PnflpJCGqHvnMR3BmprzNdufdj27LhL1QHJD2zR3kjTjVv6Lz573oJEFTo9WDsabqntks+qlUH0QeliXzrm1TdKjU1xF/fpICNHbatyju9llrBwm3Skh3Pz2u1x5cMADQHPzEgPAJKA0UEQ6nHOoUMAtlI9Wfyhn7ZBIPPNb75sBFGOuImU4Z6zZe3yNxhgyoNhZPuyyF/5MTqlP+rln85C5abq49lETaoZ5Tl6cbrui1AKT1MMABsIIJmxxqeeteQzk+AcvAABAAElEQVSorPVRBLfxbW/VGEh8mhY6Xr8u4/UWfSP6qTwGH1paHGJxTZnkOMdl4jjjWjWEiR94XKjReKX+l/7oN2d8FDZafb5yCwGPjYBGrlfQgKWlyNmIOxQPKgOCrPxd2F+MGqrcOyCSKGV/7sW/4e7e+EDDBjv05zuVbjfDGJ7Dclp/N8LoWOq5sAocl3pE52lvbKLgBkf0Rm6AkuAx+UXbQBM3VOQXN2bmBY3JC9iXM9xGI/Q6w2I+k1uZF8cL340QYLIk8aZfSBX3675CzlmI4wXW2iU0UTbuYbhGTiJtA5Mj61/lRta93oMpA2wG0qhrYIw4XCMMDaCVUGb2F0r80Ed0F9nf2kBgXASwgHEFFAPGj3y45D7y4VDyPkm1Dj8W4vyymPeO9Lqx4mxDg6ZMq5sqTusn7v6+z7g9L/zSdGXFXiNO451wGkWt4iSOFyY9eGyWbiOLWl5bHnZkO90W26XG0JvypmcAtavrYTiJfhFhAxShypo5HeqhljoD55GmYxDjL4UPRnEXjcg/ee9r3Y5vf1L3Lv1NgI86EhzZz6wP51K2EK74y7/jMgeDD0drh7AWOCfd5tLFJx9x3YOfdDs6z3h9XOYpc49baZWY3z5uDEjyoUQ+cxSqN6fJm9r2qhncSNIguzZx5goEkGVexNbcAMkPfbDoPv0p/V1J1QT1lsD18lX8vGCs1gh4XryYUn/pm7b9a+IJzCbGWjYjUl+YnRenpNFplEEMtOuONh+ePRXO/ckCf1730i+6f/WqL1d1m636XGNnZeYLx54X1FnmKtcoaKSNpdoO1vMi9Rj4+Akf2Uxg5/7tS37d7eu6U39YcmHmnyc635rE4t7jagiDnUaswOe639sh73YyjGFbxM7udctq/X0ztl5cBY4r/JcyMp53w6OBc9jIpWPwWMDaTytho25TGmm/VhlcRPxoT9Ydyp+tlT1vWhI81gN+pLN4wcWqinUibiVLmAcf+oHZCneSF2mGUHlY1ULxIkKbLNDsjU36sc0fncFZtIUXABmDM0unvUe/dc597wt69FLuqHIqSZ+PaMM4U/OVbSTf+mRg19qnLiLLdjGCf+PXZoKhJLiKrzOgXX8mpI84kZ97IYczufuFf+1++uGv1BVP0+7apg63prnigFcOeXNy22SE2Dk1pR1CcAulRJ4lZHFCqKT5HFtbWzp59vzLmiSARwOKpqtImSTFhjCUh5tYPv64G916j2s5/5S404gStchHVtqZT37eg8QYjMftAiDjvPSwOIwX/8wVe09UdW8pH89D45zb3AdEMich+7CBKx7Og/oAHEjmLkZh1Xp1AKSvWPmxecLcAzzCgSR859tCgec/v9d9/evr3O47gnia+4/J5owfX2UAIKF6INJn1vipK6K2B0mdOF6jjVpJcB2TZOOTTF/IeT1wbm0sBDQC9vITslxvmbZct3aWMkRsvW/t3VWDHc0YSXI0f8TpxLVVEeNJgcq0LL/HZeGtN6HenfLE0dyq92eC9b6UHVuhtvCJeO3y2eqe6yt02UVfZiVA7kpcIzkAq8AxOSLLfD4k0Dgq8LgQMvC4EFHIQtqPywIa3/6S97q2b74+Tl5UfCEAMl5044uFNoxTSciXvV6WnmkTRIH2Ve45KgKWntuplymQ5erWd7iObWLDiVhgYxBGvBZXCSu4VvmDZHso40TGdeP+1YsnwUa9cgtNpx+4V/mrv0y53XukondsJhfIQEC9dk38KIsnNzwZrOUBlEn6zcxvu/vbj7lMk3alyRRcT2uQz7bKdU5LrvbimOrXriAaf2AH+ADCUrqkDx6MY4zQb8zqnHKTlS0tczq3OqRDdk6ctGK72GO5Zq/jCKewHgEeoVhEzbik0yVZgIsb2AJXOlhrp37sdW7slW/y5ZPiaZ9Y+bF5A2hseep34izPWbQPlRkZlRPjPNbKi9MAQ1i3Q+ihwrmEYzqWu8NN7n+P/yghLxZL15qXpEE/8WNyrq4dboaGSt5XakhNuU2by+7atXDGrxnDMDeIw4W87/6y+7u/DZzRUCZ+GjIyEaNa+GQGBzjmNk63PjvWvV5+Rq/p48Ue9OwiM1KSwNFA45mBnb7c9s6zM0D7jMrznNTjOi4ENHIJ7yqtYlE9zyVvOHsunUc8b2AJXtZmDVltw5TTR3ZJkx33QjAeDFTyoT4+iU6mnjEczNuEW3k7GcashPX3Slyj1oS97bccrHVTt3LahIxjEN0uhF6454fcvk0H3YW+036x9wBpIQ00UBbA+KZ/8hb3moNv9KVzl/6ygVpzF6GfLDdmvYsqHByoJNVLp5wHImqHbeZU239ZNzVlBAoEPnRo6aq2WfTjisgNq2A5iFZ4XYvmVMt219s76dragooAvg/RQ2IrQLZw4xrEbdu2S+evu207N/ht5th+DiLfti5kX2pL95k1fljcWcCtzRpF5k2qVf9X3lEUgEhpqzsBYblxQbzvOWi6ta1b2QJPO+jJa9JAwISzrkFZQDf6prm0rFgzba6nfZ3rbg3i4HtKx93bWz/m7m05qdGWeLPY7rat6Xad4qS0iouYNauOWS3rWWkxSmu7TIhR4yiLVSwvjiRV0xCslQU+UyXtu64FDf27cSdfjhLNlVnAlMYXAvWxyPb14UyK21DW9TNyjeI5htrPuhZxj35MKgCS+x3afLdrHetV/8WR1lyCW53Zf4/L/pt3+GfEM924KbhB4pklD55F65SMXg6/R20H9QnmLQd+USHmNqAmOcetfDI92Xfy4TZywJXMSo2jiW07UwOuafwR17nvB/xcpR5A1gCizU3OOfz2iMr/1rfkM/aq/Fzm8P06bVHdp+8EPsAAietl1CI1UrCDuFXO7bvLuUsXZSw0Ij1hMZDLml979wWXQYBFmFaAbupWDY90Xi6Mad/z2R8gyXvkfGJMDyYMWchWX7o3tIX0GhUeesU/zEi1cexuGXQc8fvjZO9O19OmP4wGqSjRb7l504zSCwWNVAaw6eFoTHgnLS99/fTf+fVgffvmWRcCCGbwM6kPLLiOZe1n79I8LHEhs/JWoHmfFweywF6c+ntrk4smec51xakR/f0KbKb5uwtAc0qbTQSDTJ718t/XrJupkTA2PODvrVl7Mt/qxLaIrC2t7eGjezn6uxLXqNXvVY5jrVFZxjT0G9FzXAzBCevPDbv//tSfaSeQI4tpYlYdAOOP3PuGWS4floLjaBeDawgoyOjlY9wCC61MHJIXUz1uZFzG4lbX65Jp4Z3Y+DI3uv413kBgoL/gzp4puPb2vGtvy7tO+c2bmmr3O0WMjuirW4Yde+5okfuEp1yq6eAMEbe1byEcxfk4P1aWxdw4VpbWaBjXffsvlLz+Igt4rGvGlm4mViSOuPNOgcfz58SdrXCRWOzxw3fyRABVcBx4qRmRf1fhEffWzDssaUa4TYYVzdJ/8xyKGTkzTzIDQq4V4rnD/eVpxhbTlo8IOsWFI5r55EMGvbR0uJXFXLtLy5k14G9s292u++rRqIWZUWseIAlNiAOXY9s96Uae+Z43uA0vfnbNZ8O4x2oHtTiNocXpX5vTiKkBi0liHpvIupE5TXsm1qat5K5INjcsTF7v5T9Ykl4iIKDk9uzNeR+Mu/eEOQByY54cenZZPh7lVP5amEPgAzDQS19Wdv/rf6ZkZBXK29wx7iTjyphamJrqdalCY8Ax2c/4HL3IsydnciOTHMe4fDKeVBFI5ifPk2O6GNBIm0GNCNAWLKqT11mO8//02s8tabNwKgHA/MVm9BHj56t8WOb4UBOIZOchwCgf5VMCn3xtLGSHnaXo7Er7K7yRPmNkmdN7ajkdf98sffyVm+U38gS+g+oW+Dy+Adq/8ZA7uPV51Rbi7a6qiXUigMSbsb1VEB1LT80DSO4/vJRsoaW7Bvh4WTWyqNa5xWpd2vDta6UrltaiPy5l/XBQlxckVqrPfva4e+zRCbd/f8H19w24R7457thRcWzohPbXVRuTchEjkfXomLbSG29xO3eza0Ruhs4bCzdkO3gkF3LjDt0IeHy33KqY0UsMGrmugUaLAyzhRm7bhuEDqWGRN+fNgIfTp0J6DKxeNfVhFQzpyd+LvUUHeMzliv4DIJlv5/hghDMImYEUECorNztFPf9MBUgCBQGNYTb44v6HsmYsQ+hRjNJIhxBpZ4ujrqQdafDH2H5RO83ALYOTsjucV41epN+I4YyBRurbtob9L3+j2/vCB0iaRTw/E1vzgbCr+/FZ4ulZlZRg8za28rd5CACETH9xXCJpxNFGlDORtv1dkGZtUs679XnqXdUtNW0+WUgZm3s2JxHPCzn6jwjGgY+JAP5Cf546GvrQtQaQKv+24yn3gMDk0SPimIuzjaibj5H2jrLnaJ8945+cN6bhegYecxFoLJS0S4y2Gaw+NAo2SN6QZnpY/BcDIund3ep4A2Rjf3Zgl9u77pw3qiENTiTnSWJMC8OHpUN7n8/69OMfSRZp6BwH4GmJhVeSePcv5S4zqObEpJnjspI0MFMy0pHM651ZkngbUNnaKnUVMQMwvEKFKoXegoAk87yIHyy9cOFdLqUIHHWAvN4ttHk70PjYqGvrrOiAL1OHx8dGXNfaTcvUev1mV4Fj/bFZlhy/x/QiW8YdT1LB2V4cFvLF/NSVwzOusH/TfbM4ijMKrNCJBxJgAQGIsdGwU4ldOl4gLe1GQ78Yq5F4YaXNsLhm3AtfBErKuX/ywi6v6yhJrPxtTYkjdd51rN0h8KC6rWOeWzmpl0BrS587eUxGKeJWYqQEt3JtT/CPx0v3rv2tEhGnXXd3pqo7CVeS61sfjFNp5/RnLqLcL8qB82OPBZF0vbKxNTXvcPre1zezNIs8BwDSuI2cQ3skCj3YekROmMM5v/H6zTngcUtPSuItzmpTua1T+lVaSAyRRsUAjRDbtrH4QPyyMMXXwsLawxqFtaistvNjE4HTWNF1ZK0CREI13Ia6M4de67Z9Mzj9Z7/rkZ2H3OWK+6ORkUHpAEqxT2SAy4xhulOPu+yTv61GKx8iCusRwA8CHBrFIJC4lcHqGrJ84laPeUt6kvzfyIBc/jz5Lte3493VORWXs3llIZxlv5+3njOPxJ53XMfi5HUIID59PKS0yNIaB+TPfV7JPfyNlNu1Gw52yr3hTSX3j1917ln7nedKZgramzCibFqg0UiX1y70Gr4ozfIaCTXcgMZ4nOJ4vSYMJBqQtPNa5TF0mtp/n+PduVhJTpKDX+s6S53G3tj23l/qtpPtIar24uoKuKxOT+k8M2/y7LAjYxy/w450K1EngHNZLsux+7is+lWvCfApPdC8Ki/GYKcgjw45PkxNRyLZyVvo3Ou8qr/LuZML1/Abgqyw0RN6lavAcYUnG6BpOYldBm7lnQaMC3Vlco/b5E5XuS5gBBZTFgWzLGWckucmBjSgGYv+kmU57+/T/sDS/YvJFlUDCZwbwBsfnXSXLuSk9dOklx2cLG0fphfjOn3UUa5d3Kh+iby3bdPXr8Q4588LALdIf7JFm8xfv+T/kEcHs9IVkmiXr/Vik3TGArcyI0S3a1fWg5P42nHfknHE0088EUBjDA4pF58bNzKuH4MEQANiaxb+1rbCLK7hj6Q+7KYK8Ahmk83YZol4L2s8t60rVzl3s0sLGMoCOj0s0WUN8Eh5FhUTU9O2BzcVUMn1qyJubkBt+Osrbu1Rplk7Gk3kxQ2WniJW1ubnUVlVcOStr9UExE4y+kbwVtajb3ufkHVw2B1cHHW5CS16UBN+KEVwjzvKj7n9E79XBY2kXy/sdt2p0zM4gaRDBvziOUn6jHlZAZ5xmeScpo7Nb+IxeVApf5Frzv6KO9f97hnqEpSzeUWc4UdFxFxe2XwgneO5Elx865vT40WdB549nQZnkjlz6AE4kNKflUopfiNx8YNrntOnaCfl1umDqntdm/LKSpOY3kkh2CaNHhb7U3sirdYEC7lz/sbjQRwu5EKNYnh267Nn3PGrO/WsNCcMkFa4jovmNvJO130Fs7A5b2PJM5ea67jYDgIMY45l+IRSazx/AKOA5dTomMpkXbP0djta2zW3xl1hQrtNiVMZQKV0LxEd6Jwjya2cHB/179TF9nEl6+WnxnRPy6uHyTVaWuf2sbwc91wuobe+SrfFCIDyV8rx90oMCByAjg5En4CiAIxYYBF1mNsSziFbkInDQYgXEfLsnDAuy/lacciM4PbFCyviSCPi5PcPFMKXtWUoxF8e+VaXL+9vfiPrlZ5bZembymx0TW27vIuIrnUH3Kkzu1xT61bXrJcj1NI05lqbL+kr7YT75teOu+H+Y96lRL+A5vGnBhx7Y/N8+YKMyXQa47Q4DlgckREDBCDkgCp4y8fthzQWSzhKu3fDLQ3gwfLvyj5p0VkhrXIALCE4j2MTAnQCJQZCfEb0A3gEHNYi2jKNDeJ8TNg1KG8fFwBF0j0pbk/Ll9WXRpMAyomT6Fs5d7Zlv7/vWvduTfjwtQ/6DwA4inwI4MSbj4b161s0Pi3ihFzV2Ey4vWO/4vYM/Y4HfVcmdvuqzCdAI3PUXOnMaLtyYnMSQMgcjudlPKdJh5JzutJM3YB6rROn3d7RX/Xz0j6EalXwz0fGQOgqEo/nyCPf1nNQ2v2yoDYijTFMy0gCQP+c55bcJz4W3GDBpSaPA3UJQGRPx3Uklm7rzhbpz6ZkvLfRbdomcyY1WW2VCAe3W020Ky4uBPQxDjaehBav1yKgEbpr47lp0FhpY0g79Cye24hLnJuzlMJ1vNWJ9yWct+bWLumTt7lSqkXbTEqUnelwmZYehW2y8A6gsUn6lBJ4ywvDpHRmh115atCV88MuXZ4Q53JYc493lwCn3pe3MuHTs0n6jctJ46PD1TVmOa+TbBvgf3Nme7In30Xnpuv0XXTLc94qIMEWVjiNLKKMkYn05qo830KRrGtgwdLjc+Ic7eLG9axv8mDC8g9UdnNhgQZEkm5OuoclEjYjGdqlzIte3CJOaptXigZUPnNlq9uyY58HlnfevddNlXa7rdqRZ3KqTZaseffIw2Puy1+64B7++gkdJ93ff+G8e8ubx9w3vi6RrIwbgrix7LlD++8uux/50aCPBvh7wQttJcY1kcUD58juMw5py3Qde3pCzivG/iQuMm+cq8B5HJf+mwEJD1AEQiCLzwUeM0IsGLokwSXQ2e6CsBrX4gPZOfGU2F7Pck950fR2gZXTOclORQMb9vs++JPKD/4cazn65nlx8NHAx0HPuo0uN3rMtRdO6t7C3NzUcsbPUYAgczWzbp+eb+COH728w+vRGUiM56SJSS2PrsRgJ+6fxalfa+6T7g+5ibK4k9h6Z/njvu/2UWP3Q5gR+LPng24jZPqwBhYBgKhBABTvvS846qccluccD39reonguUIW+hNZ6upP2B15pM895zll19183l25IBEamfoZnljnxibb3fa9Agg637xLk04h+1L7Qr6gb2lRP4wnRMgBJ5LxaYTsWRB+9Rsf8e+dxbyf/darFdWLRq671GUQsd/OFMTY7fKB2alJK3+TzQKY8g+baloj/WVxK8tZN5nXnNIXyhpN7FxKXgJS2ohAoDJVHAkcbm1kMCXu5dTkaM2P8JUen8AdDYyD5br2SoDTWn0vyxvGqlV1rZFZpjRenM/0Lk7XZ6X3o1xKq+pGh9NElJQfk3NkFm4WXxYCXu71yBYKWwgoZ+Xnc/KbbLOWlRqLMgsxZHELSTO9RfP5SBoUl7G4haHE9C/pEHo8/+EPS+5/fgk9ITh6WDKzEMIBEljSMGDZXCrJglOidDgdXl+RjIhiP3sG5BBNAg4++F+w/gycI8Dnf079kG+X6rTC1eLWOF/XIZc5Aopj2u0nztsgy/T2VpzSq1CCDGDkRmVtK6CIax38NyYpfu7hTnVflUJxX4h7Eoi0nWaK3RstVXOGD4/AFSMxtqBmS8FGiOfQM/Ixlz73GY0/ACrUsvkECDSLaUtDBNpZOuXTB8p7vDiUcgYc4U62aoxi8TSt2rz1V+jeK8R7MlxMvzx3m/sk2rWqBaJI0hehzaXXvBKVBLk8kooEzyL5jPiIYO4cvLfoHj9cmUdRu8moPc84PZXv1cItYyi54/FTUJMDDmTMgPPnlUkzIcCokXGtmX43Xlzn7n7WmDt+XM9MY13PoGYhVtVx34gzxheGd3kOYzIvPv+Pl664r0+0uPToXS7fcsxnteT3u4mcPkzmePdQcKU2Zoj7G8fN926cdqNxtqt87NHZrbzhQfvLnJ23nClIYy6dPeq27zlQvQwGjv6Qz0p0pptw7qrJVtL5pF6AzfoqwiagKPHGSu+wsxJOuVfiGtXBrkR4DnCCV3UckyOzjOc3ot9Yku7H7aAUfCPDZyJKxqlNC61RvGiyIEO8zG1xjfPjOIsGvulsIaWeAUDijVJch7i1B2A0TiVpbFloaRaSDieLclBc387j8Mv/K+f+/u+CKHD3nkzVfQ4Ab5PctqGzyZc3IJKXZFFff3bOwn33PZPuqaNtcrMiLtCTiAwFEvWuZ7wQbR9+DD+BXDHQawp/4t28cUaTHlCqIRNLk07P+0bCuFfWf5I9FcWVMkCCyDhcK+QBujz46lrnUhKrZPICGBXSXeifuFoCk3Kw4/UaATHWPlfDAKmMMn7FSttX1cUwjjFAWRwecpnOgOrbWkNtv/e09B6xoCaOTmMF99vl64Y8n6Zjn9WNBDEoc4yxA/QhgjYwGDcQRKBhQe0unhZYCeJnA4aZdXfKcld+MStzNt9+h0sPnRQ3OXAE4V6WtAtNrGZB+8x17iiZHl+ba2Qvfcyxv7V9wNh8zWY1ivLDCNkz8txrnfux9kjPuSceFxC3gfela/9YG3Gu/MgLxNOgdG6f3eoOfzs8Y8Aic5TnD4jMy9I6JwOZlqw+nDGUUV5TZtydOTEua/t1buP6cdcvGxs/ig30Je7DXHHeB6bLGJeL3xP9EoEaldqPaz6GDkzAzVb9+YjFNLfCBgpxnxCxw3VcrG47W5ZC4f0Qtzw7bmUt5w0Phtj9h/goDX8DlreUIfp8mYQ19VwGO03aVgu9yrGR2gY7RUlyzBk6+s0FvceaW5aGQ4gYnXfXcq7XiOsZj+W8Rq3nV9A7vFUi+FXgWGt0bsG0kjg16Vpv7luwrzfapRhAEmdxNIMZW7iN82OLM9eMFwM7L2mG20IKiDPQB5hLipipM6mXSPs8LhSsvS5x22iPc9rzq6d+SQMoGnjEwhniHDIQ6U/0Ey/4iJERH0LHxfgwkEfIEgZQEwzQXNBiPJWplvW+HVvKAovNeiGW3JOPB9FOuYyZ9DS3ksXcb1mpcYVb+aqmjyk/kG9fQGBam9By6odwIdcqu6ivf/x0AhZtmsY7t5TbJYYCM1RAIBCR66WNAxkhF9I9qU1z7WNJsM7I9x9hYrmyzeFEXqItrVlcF65Y6akjrnf9frfuZx9yl9bc7w1heFZQ/Ax4TjGo5zx17qMuq23+XP8RcQDDloLUGxfYG7l+wuvlVudcgktIOae0/NWn3UBur+c8+rSxU+pcuL6fo9JPdB6E+twq55F2Dagy3wEt7CSDwYB2lPNk+r+0Q3kfDqmvW2fPKwxY4E6npcKAE/5Dh1KesxhaWsJf9qaWntrhRxSKjNvoGeUkaM4BGv2D41RzZNde+Ws8qyQ9r7ZcrxvEBaTayEuPdmRcjqrLLe459w24c9rnur8MR/f0rL9vmm6Uku8G6jF+cCOLpW/WbMZAI1xIAOXGyR93V5v/vPqMqMTnD/89179mKyuTiGHP/pdori+A4j3uF1BtRtGPfDicEt53f8kb7C0HVxKxbGvbwoDdXAY75WzRjesPpDwxJvAlTxHN8jEsXUonh+nl9I0BMqSDrW3La7SCKHyh4zHjwS3ypEkup6byei8vsv5qtUWMAIvCKjU+AoBGAAkv/ZjrwgsfAEm6LQgWwhkiH7LQrgjAswPwZnHyAQ0cly6l3NhYU/Xc6tYLaQOy9ggBI1jlsl8wbUIGIolbmoVWlzxewICfHqExwCKW00Z9/QEcVYGZ8vfuDbmAzYP3qo64bOVycBF06AEBKzntzcnoA0XtnHaTyIHmAGlCkC8b+6Bf+Fj87J9fBXUmHXV/zDdjxyW6RiTMs0K0HoNFOJDcixGuetg2MKnXSD6wimNS/hkh4pDXg1RIP+K+2McF5ZqmUJoP1yK81Lnf5d7wJpc5eKiqq6piftwZaw7GnmeHjqoR5+tGxG0UaExXOITMIY5LF4PqxISMgiD/t4xrnMoczGvewUmcaL7H6z+250/6etTFZyOHER898dwEJNqWhdwPbTPfaRvwglsTI65DeavvQ/WjPHjYivgQh80H7x1VO0FXUYN+w6ARrve8pBsAGHriZirHveJGetKtACzPnZZouzgNJimXluuWnLiQazv63IaOS77MwX3nXVv+lHt68gcEKkveqv1afpf/cLgRCQ59YXzhRvIxZVTrHQ1ohACNkAFKypq432fcxJ9GDXsQQQMYcQ5voG+pug3HkjZD2zYJlqb1vAzWcKa9VBQb7OSa9V5KtbqpIn8ruPq67nUoJ8eHdL7w+8DbBu/c5aSlHo9G+8oWlkVJMVY5jo2O2BKUMzHRYpoqyP8VjqhXitANbLqoRfQmE1wsCADpuScCKLzwbeG0hdu6yYJLHosz4PJY8XVuhzINKFi5ODTwR9qmjRNuTTf6haGOgTsrH5e1tGQIMPEX1WpI/WEByc7KFoSUBVjCAbPQ6n/og4CSIPoFJAK6eBlDO3YKfJ4LcX4NPJ48KcB4sOxd9nz726Eu9TZoK7mk70fWR0QoYUTVhuLTwuHptoFocH5sPSXECrpZb4u8Xq5ggZj6hkpu6wZrdTqn5n7SAq9FifXSEiOlJkarLnasVrM4iPFe1rbHdfKalKka2KhzIzgDb0s5HHvvqjj2tmeHyx2spyHSjMtIfPvO8IzQT12TeszdqbnlIg6h9Sv4AdTXdpuMU/qe1t/i9EcLZdBhdHASdUxp/vlzq5z4szWuOdnMVRNhc24cRdKZ2+bv0cryLDjsb8BAZ+b8J90Xv72PYh4Y86HwPd/T6048LTSsCswJOJDGzQYEMofe9NPOPfrtsmPuGHebshx27hvVT/Lc0n0I1zEtgxeFfJck6fFHggjbi7MrcZtIuPIZuF4Bkdwc9TnU3nPvOuz/jnvWtAoci6GbOa13QdmdG9wtv6opNzJadnt6znqwDbc3N3I6cKOpro7kO/a4zPApnYVzH0n8xP0FFOYmnjWvbiOgkbKl/j0uDbhojv44E+3fKqeAxre9dWV6A4A8/FjJ/d4fhL+7G73qSji6bm4JXMKUDL7G9dXbohdeSfp8meZ2rSfoCjcGBuGOds8jtbodxiPZR0D0lDZyaJLR0tI81eQVVs9rjgCL72IJR58rqc+AztStRIAcFgLjMsSAkUU2tkQlj8WZ7cQgAEIM+Excmbw/+7q0caZO8rD2DJQQWjzZHufUv+dgusqRJA0ul4mnrS+EH/9oWHFZtOE4GjikjoFG8pKEn0eAAAs7dQi/78VhspFuQCBZr/55WLmBiPYP590FgUaIlo1DSTgmi8eR0by3ZmRv27C/LaLy6Qmf7ENJH0FYXWPcAheSHWeME4kBTbjGNIbwF45+fBnVkX8PN/ADb3Du19/vvvGK3/eOvXkecHyNAO1QAOoBWDHe8bNFP/XOMflsFLHLCMS8SlKTQGVW7ijGx+AiFtxY8/ZkEY3/zNcq8xFQY5xGjGWMM27z2DjoNAYYNIr7YPPagCfnOFMnbBk/7V7y3BPun31/m7aWbJWf0bL7nudpIPTc8M0IARp378ElT5gnPJMPfVA6jpo/MSi0ORRqhfLxvLM5RT76nP5hVQobt/G+B3Qx3Yad+2ydP/bwuCOvnJW7JuEtygxgMKgh4pwpA5D0VtfiSL7hpd/your2a5+uXob7h1O4qeWs3w3GvxdU9/SporsyIW6k4oNuj39+AEny43cHYNLeIz70/ZSbqvV3+25ONh/1oNC4j4Too8ZkXMdS59Pq8KlqPmUBnrcarSRotHvnoxeXYjdKvJdX0tE13EhAYlkfLuVshz5UJEnJqA+4BirM7woon19+x9+MaXIzkBsd5/nql7SxQ7qiyzvzDTdfzdX8mzYCsNBXWscRruOtRiwAcB9jYuFMLtbkl7rumQHYrA66jQb2YuDHGMORm48McFAujsdtFZ941NkRtwc3EpBCGHO+PvXf5GpiTQB5cAvhOAIek4CLRd0WbvIoA7Hwkw4R4qQZojztEe7eHRa/GAT4Qgv4odVwGKQM4eCYQti0IhbjvBTEURLnJZpHl6iM37V8AJVaS9Dbq+JKcSERY1eBpMBkWaAwL7E1ouuCtvTJ6wBcTrXIRYfypzo3uoJETKmOLte1qd0/B9wmmd4qYwzBSWSseU4QgJHn5LnCOrd5wF7URrbLCPMqBm6WT3pXl/x4tkoVYPRcTfAIMPTcSQEJH796woMR6sKNNFG0gcm4bZvLdm0LKcPYMv8N+LS0hP3fyUsPP0HgCet8OOcYL7CAGzBEh5Y488HPiT1hjtmcgntN3OYSjVE+njNWnzyvexmGWp0TtzErrqPOD1e4ivpznSbFEVOThzW2z4vyyePovzbmmjNj7v59xz0oXps6I9FfSvqIu93Z1CvdeMseAcTd/tkwNhw0g39GwCTgDfH244M/7Md+ZKToRdyF7a/2z6Tcd9IDSToGyOSvIiU9tzPXj5KkPBkrCcUCDgGTqbS4i7kACAsSl5NnIBOjRfQbbftI6mCJDRnw9Cc38edmgEa73aUAjyvhTNv6mwwBkfIL5EHkVElxUZu2XU1pro+PDMwSZWO0gkrQctLk+PLrUNbqf0ZKy7joglZF1bVGaJnS/B6ei2y7pDd3WuK5lSS4jreCuDp5z7XE13EZFmNe4PW4poAIA3kG3qjf3zupHURafZ4BjbjdWnHAYflxrcyi9iOP+V1MiCef1MDGu13n5aOu/KOvc8M773Ntpw+7LRR63Zs8gDx/TmJmLZos5l3a3hRbEhZ5ziFbuDk3EED6tev8hnLkUQ63O9/4R+koVgACIBQ6cwYOVSgLMOjWdTBYaZLYNbai9oUb+KEe4A/RrJiOXvRNNbqMpTeqBQEcogsWOJBwIYtwFBXm5eS3LH2ZQkELr986EBCq97TqZbQjAlzOUekGtojDxL2xwNM2ZOMSzsKvPdc4NABJCcDi174KQE+JI1ny6gNwfw/uetzlzvyxwMxotbmyOJmYmwP05iJ0fkrD51xJjuwL7Xt9UfQjPfgzkbfa0KOoAh3aBEym5Q+yuSJGTV7DrstchsDkkxOIwEFXNgqhlpXFhdB5VDN0n+hAsXMRhgpJS9hQK4whc4w5w3hyxNxH0uO8bdukm3hueuzJm3MB0dDpsQeAaBe1kGHlgXJANsw6BzxCD9z1dHWnHriMOzrPyKZIHdAmP7kNd7hib9ldHtstg6W0ay+erBrRGEf2gZ6/VivBi0BL8bQbOKsPh6G73f7WE9UPAsbOA1h/RcT5qA5wj6ETT1864vZuPuju3nKf++wjH/eAk49XQCZlxy7tcy2bT6u8diJau99dHAzgc1xbqpZ0rZ1dz3LFNU+73smQbpzKyuWWPbiZoNFuzsDjG9+0OMvrm+Wv0PpvoYmyYT4XpFLT0dHqRoav62+yXcZcgUuJ0cpyO/6elIrPcutQ2j3HIb5e80XpXitxzr/7uNJq/OaOAOz6dOVltpI9QdybrbO4rWQ/al3LACTcF17mRiwcMbcUkJgEgnZultHUbWvHH1jGl4UzBcCIQYi1T1j4+Idc9jMfrwKZOK9WvPuqFg7We9VZ6z5eLTLw9UddZqzsRo++0XXtf0DcJIlKT0wv2HAUY3BoFW1Bx5EzuowQCz/pF7S2GuPUygHU4IwY4AJ8DgyokkIDjQsFkFaPa3OdIbnsaRewAZzmJM4lDeIrNZfLiPMYAFBGprSoA9Af+tUkbo7noCnOOZbgBYzBhSroEyJy7/ZHazl1AJYgjeiRU9iTPVdOks8druKLdosrNyKn7X2fdq3jARzI64rShK6np5B8DcoHopMOZiWtrP6W03pdClCOTWX9ODLP4HYZUAED2fhy/SQZwCMdYFmQUQu3GafTHn/rWQFSiJ2VmNsASONqATqNK+kLVX5ohzkLON62dUpx4KrzXMePfLhSKBHQX+szHxPxR0mcR7WLF6fnGHmIwB+XQXJBrnaq2wqKE1NKVc41djwqRNPGgZxxeRtbwCUZsqp2GMxU6KGXP1yJBaDNCVxc1AXweYnggW0HSztfrZyDrlPAGTA3kNvjd/ihfG9+t5y5n5KYXnvIp067rg7V7d7nJtru0ZfU/+eGUndovl1xI4X9bvh8zh24P+dB4tePPequjQWwd/KZJ7WrzJPuRXtf6750/BPim2vLTbWHynluvfRdtV/z3s0H3PGLTyie8nHKl3LHXNe2rDt59YjS0259y3Z3ZfS8L0PflptuBdBo9wh4RL/yve8rLdhtj7cglmThViJE2bzemtvX6SNQHHJxxNOlETkhH5Ej8+W1qF4JHcpaY12SBCmdFUdDVHlz1iq2mrbUI3AjoouiVuFGxKhL3efCtp9Y6iaXvL1a4utS58HqdQz8VRMSEfI5PFdXiAvAYaJMilp9uIv9X3nEude/3IPGRDOLOgVQtoqr8dbMO9xrjr7Frb/6iBaW6aYuXQpGDYAwjh07Q2hl4BBBJtYmHQ4jXEcrQz3bJWa65dkxgCBArVECKLUK2FCDeJPiXNMsq4lzpDNwGIPFNZwzDsAk/SLEmXlJW5Bl5F6nUMQwSaIhIVr2qpUGXwCZah+DHSxrvQhcolhE4Byjw/1usP+qGxX4s+3IeGZGAMamp97lWp76Hc9Bh4sO525M3EzbOtAAooUZWGUi4Vh/cIOlvHZM0Nd+h6w0Wkpy3VGa0j0EUSk7ljQL0PCRNdFyh7eiBgTORQYYKWcHY9MkkM2ctoM2AKdWvhZotOtw3+xq1KGPoMuXM140vxD3KKMC1UY8n1hknUwHDEDecbdCxg6gyEdL93rph2kI80Xc9Iy7ew9Jr1HnZYFKdMdKmXUqGMowxkXX5grpHt8egPD3//UH/JgYx9XuGW4uwBk9UID0wJqKOs3pT/vx4bnijJ3nwnghugbkDaf3+LYxPhoVN7Dlyme8a6Wt7Wd9vzuyT7nOHU97gAhoHBrkQ11zWdfgABD+4/k/820Z13DHmr2amyH/XJ/2Swc8qA6gcWfPAddW2u+3MSxrjgNor09cCPengega+Be+jz5hGX5uJdAY3x7gkb4thCYncea9vGBsIf2Jy3rrbO14w5yeLDVp55pJ7cOd86JsKUX6j8C4/I3G+ahcbh3KWn3kvQon1fT/9We+SrfDCJTk6DkNx2OFqdR5X9XIZIUvvaDLGfcR/a/Jra+Uvtx9M+rHQML03GYU0Al/lIBzK0tIWY72977VZd7zS27tB97pAQ+LKvsjLyWxXzQA8ucn3uI5P4AuDBo44ARhFQs3co36xYKO70b2HqaciaMNQLKo00c4kj6/L5yTBlkYzqZ/Yy4iqdQF/nixtELiLQKIEL+446nGJ0Occ1zxcOCqh2cDlzDopqKPFvpM23YY2MRpN2lYZMO51FIst0DsaS59QilmZ8XxA1g2oRcpUJmS37XR8WDteObUpOu9ctGdPHbGXTh9xB178mk3/Nh/cKnD73alvuMCnUFEjkEP1CZAgb7h4KD4fiA2keCCDwFARh4QabHPytM1cQ90NI4piaVaiuyikPfGGoBH6Moz7BQjA5pRzUWBnJi8vmMlDS4rc25SLn4AFlC+Mp5WjvoGKi1u7ZFOOUIjm6/4I71jnzh4IjiQr3y1VAQqz5405k8MCi1PfpM9kQdH8Wf+5cyyVs44kwWnySlivBgXP7TaJq5/MKTn0oGDaI7BU3K5gxsedByt17vVT8+xnOpzuO35mVd9zj13f68HfsbN5RqAR8AgIn6zPu8e/Kz/GODcxoE6HOzow/hA6ElSl4M4hH9I6tDvqczdGh/+VlKe07hrd3jXjoqLvt39uH8+5HMAEKGzmlMZcYZJg6hroPLi4BG/A43lUYc4+ehQDnX/hY+jMwnhK3KpCNWElbKeXkyfFwIe+ftYScOYxdyP1WF95m+arRIR6cISZ5cV9CEL+YklAZHoey63DqXdTxyi38hHu1H0erSk1XC5RqBwA2bVwapaK+pNoNuB62jDUl5zpytu+yktGJP+sPQ4hJto4DBOL8pFTNYQTCWDslv/n1+QN+4jPoWF08DOromgBE8GIGmpCAAJeEwSAJJrj0gVb8MG+Xzeqr1/N8n4Y6cTty2AwWeuBE4e+mjQyKi2lJPBA2T9tjj3EnMYKWWg0OKUYZkEUBJy5DWPQ4s6qUPmigeOzLA4PIip8SWIxbVHX3Xqxcn0N34cnOOKBXE+lBHYA5Bu3Njq1qzd6A7ct9nvCd7Wtc9tH/6oe1Hm19z6ia+E/k/IWGWyKB3WvOZFXlynSXel+QUCjZPaU1xdwzyYm2KhUlgCCRmY1IJPGhwzIziSBijT2h+3KBEVYwVQ2dV91oOSjAD22EhhBvfRgx+lm3oF3MX2dgxtAigyoEQ5DsbbAA9cNvw4QgAezikDIDGAapzywQG5DxHHFtE1RkNv/vmMB4IAQv/c9SECEYcYWwODnBPn4+MjHw5xy0uWy2hPdi9iVh2GjA6nCjJ8KckApnJOe8QZL0+U4VwLKuHZkwKXSoNzmRl+zL3ux7QdoQxguEcO7g1raSNTnbFxIZ04RHkjdvTx413Js3RCA5Clzr0++Rv9p8QlvMd1Z/d7ruEJiac3tN2tjzYZ5bg/r4JFX3joLtdeepbmgziX+WkLasA/2/8ZeKRsDCbhpGJxbWCSfFNJWNvD/OH5Vh4ImYugpXDqvYjLLrhKo8AWQ5Cm5vABtOCLrHCF2GjFu+7RvttYZU9M6vNKHw5ZKZQXp0b0oTitS73QLt4sfU/eU1OrwHGhj+vml+fLy9jEK92b24XryLhM7X+3H54mOb6ekoHAfIRYGi4NVMsAqfir4jRq+zoWTMhC4iy6HhApbkCJdDiR5NmiTNpCCfD4gcIPub2TEo1HZNdnNxrjMmo3P7dpEyCS/mFAIXHZ6XD9EQHKb34DPCRLbgFM+gR4MDA5KUBoYJGldyLiIFo8uryP2n0xatPLtIw3VNfGg4KMCW0CTsFg9J1da6ZULgm0qWftUpd4Mg3upf4MPHlOptpDfM02jDHtHf1VrwdHWXQl8UbQ0ganEofoOXGjmrTrQpPbMPFl19EZOEtY1QY4DEDWoQ6UtEOCv0Fuwi6hEBc4Qq2Bw0aWTrPaH3df++OeEwYYac+f8ttmtsjymvtmBxgcV3vAR78q40y/Y66hgSXSsQY2zhrncEfNPyTAB1AEGYcNgMV83rKl4NiFkfcFH0j2kfT6N9gz8NU8OKRv9Sh+HswZjlpUbuqZnSxQOIs0jt5NT5yhsfMAkzTl/+GbP+FF/q0Tp6uluD9EzoyNuUoqaoz9uEkHG04veQAv9go3N1w0EI+nNRiPN/qSJzWH4Ahi2DJQCNsMAvj6JsOHYU/zfs9xBPgBJovtx9xo+piAo5zf5064tQKblOH6xy8+aZephgYUuQb7YMfAkjzq9k5e8um5JnHXBS4BoeQtlBNp6gPVi9/CkXpGW3GXeYcvt7FJfL0bidcyWkGU3dzaJUPAZukzt+pvMqNdamTsVx73rn1Y1xdC6Hsu1daIC7luQc8hmwtSBOqFN89CWlgtu+gRKBqrZIEtoNOVuYl7odJdAFn8Ql7gLaxI8Yn9vzTjOh0da/z5yMigFpnJGXl2wqJqXJq8kMrlywFIkG+g0comQxZdOGJJoAgnkjwOrKmheBFOtjPXOaLrJHiMywMeOeBCYkTDNcclwoZDRBwQuXtPyus47tgBR0O7zexz2gkl5dZJzawWYYOl9XwGJc/BUnZYwU5xZyjHvRowBDA2V8TPlKMOu9LEhAibcaS/RsSTaYixOQCkOYFROJmcr+2Zdq80+Y1f9oYTxo0CdFgcrh6LMWAi6A+yj7esIaVbCTcM7ijGN76XCg20kRIIziN1dcZN6mY9F1Khr6W/71x+yINWA3Vckzh6dmvWaEtGXbs3v8ePEwCGg+vQR/oVDD3C1dj1hXz0MMlLEkCRfCPuFS8BTxzWHr3a/ShJhx5Iu/f9UX0AmCy/e890CvOJg9tOzmX0u7zz7+nidWPeSIZb4aDe9OC697/5AzPq2XPjPrl/zs1VEvqkftykU4pPR6jUFQD7xOWn3fGrO90XvrHVj7cBN2ucegBMG7uTMr6qRVYPAAno44jBJH3CETyEIQ3PWNPJgz4nrqTnXkoEbWoIdo343ABqzIkEXHIt3ACxa8265q1Wdc4Q3cHbCzjOeTs+M+/1Gxe21eD8rS5Pifm4gYBGnIuzS82kPEl4928SZedSk67RXWomxIFtlseJlSTwBx/fMeNqFTiu5BO4za91K4NHrKiTeo023ADIwIGsL76mLHqkO3fnPNdmPtBobRPGQDFeVIl7a2qVAQhZHuFC9CPnA4/WFwNeLPAQOmprusruyhWBS+k4funvU279+tAPQCZW1fjhizmLGLvwfcNyGIuxba9k33CdH22u4EEd/QB8GsFhTBLgD1c7HJOTXFOD0gDFXMi2FvZNDZUunJMO4pPvquqy1WvKuD21gBh1wI1VDpi67UWqIEWfzmLu+ZEVgEmFcMCF9Jbh6FGODohbih9LnKEXdW9yD6XxyI0FNz3rcqfD+AroQQAiwBEhLnUIIQBnm7iMOYWkYVGMCBei/wBFG1nOr3e80oum77xryp063VHlpPsKlZ9770u7P/q/plOYi/W4ieZ0frr0NLi3uWx5Zek1Nky6Pbi0+H00eugVn3MP7Ou10xmhgX8DemTaePExy3aOjA9cSoB6R0fG+3T8/udc9PqQ9szReYRjSVm2hARAouf41dFpv3uARQOM1LO6cYdI652Qay39nRAfKmtTeRGcQwjw2LMh7V3wAPwog64kYJIyGM3YNXwF/dTiRDZPho9OuJGUb1X/zagmWZ92/vRD1trtE85nKANQyjUvYG7dxFufmpT+IaobDRCi7ExThxdlj4u7zC416ENmUvIoIX3IWgSAQwc/BnC1yi11WrmENXXQI7e2o9e7Ja2GyzUCtf7YG7nWzTKMqdW3WxE8snjU89kY3wPgcS4q6g8Tb/zeEEbiaYgFsrencSMYA2/UNbBowMnyCAGbtM1hiz916lGj4JH67G/NAfcBVz1cg2sCKOFMXroYrsLiTV5MZuxCWmwog09F66cZysT1kvH4XjOeRReuNVkRSTMm+GfED6L3hSiraiyvAZCEMVkfCY0LSfv+ngRABySq3j38Ljd19em4Ws04oIEDqgceyQNAgu4YIw9ySKyQV31UngeVlFMZQIjnWOpeUSTP5tHb05ipMioQAEl0K6eE0kp6EZfly7Igfc9MVnuaD223pqshwMjI+otYNTd6qgqayAdUQZRZP/I5z3Fkr9wXvDA4Q8dfJeLrWCVj1+603KJMcx7B7M9+tsSu3tgqPCcbc9944sfGPk4uN9VhX8eFojhjZ2JrOI3TrndCIUCiSTgMMAKkeWYGmimJvmNGxjK1yD9r5RNSZ1CW0saxRORPemdXWhy9u71IGA6hcQPRd0S9oN47GxGjcZW5NuAQbiShxUk3MImuJGASziQOwuEw0j5gstY1aAMwaXmcj6ROV41qmFfkWftbij9+W3EbGRtoLrALUIJWeocUf9EF/mB1nJFO8UJBHVzIRnepmZQedWvbynIbGYZmuVabmJypp7IKHBc4QW5GcQxj0A27VehWAo8sLvSnUTLwmBRfmzpAktPIsK/rC7pOjV4jLhfADehCC7XAUrwg2wIccsX523Agrjor3gh4NMBoIiu7Bo2xMw1ku818ruWhKhiknAHDUGr6l3QzjiHV4v7eJKqzeoTx/VEWopyFzQJ6ADIDk0EsLnAljt2kLMQxoME9T9xOXD+0NPN36w+c8DqFiAohQIKBjZklp88ADRBl65HnPlYejgeSKpjAtL6qcSjjPN2FxNYjAoz4sJR+pazB0a3E+CqbFXdB6LPYsdff98aWUxqSgrhS2qdb4BKQmUkDWrQ1ofQsAQn0k4N+AxZNfJu8T9QuCtJHyMrJIGJr26ObOIYyEOoZxnlkbDG6wq2TOYynDCAS4jnYbjKcm56jPR/OTV82nxJ4rD+cVA/5lTKIrf9AbncO3Lem+sxstx1AmRnBxACN++cwUEmTAOq5niNlqLO98wxRTxjbMHa8O970Tx/0ImH0Gzd33iOgH1zqMJ88gBNHCEAJ2ANQYhCzqW2XOMx8lNW/YQOQcCAtzsXRkzRxNGASov3i6eCih7gBWOoZETeguLE9GOGI3+nLHvvyQSt2W4W8p+pxHRFTt6ywWHaxg+d9TbbdmEgdEDnXLjVev1HOxleaypLEpdK8uKcp8+9E06erseUaAaxBR7W37WIIpVvAY2u73vi3CBXXv8Slhh9x6Skp2N0kQqexsO11i7p6U5NEBdJtQ/fR+8gUMkj/1jtd6/lTc7Z3OrffdeWv68tyzmI1M3nxU49F1+oTx6gEcUV27NqMeldbD8h58cy056f/1h3LH3T92S0zytoJYul6JBdjnsYlCVmvNX5MTLGS9Of25x7XIujxXLUq59ZHli4ABufCMFUijqGdLW2oe1EGUOjzdG8QcQ5fX4AKvUJrK4DCwK3DDyTjAUjD6GVcxjA41p2Lmv6ZxJQ9kwJn2upN5QnpOw7IIQAFnMBaRDqHL1OYCFzGGgXpjweFarcKEoknmrVz7tXXkcy/KaO/eYl57DqMDXqUOITOFga98U5zEwY0iKSlA6WxOd27w61tF5uQhoTEmJ9sc0cnpmR1yzZ3mrq+T37fbHGu7H7L0pfqndrgumRlvnatFPPFZOcANF69WnYXZQi2YWPo+KZNKXf/obL7wt+Em+aZ2HORyzZPnF+9Sn/DuYWkQ5yTD/m9ffOyptb2kn4s1P2f+pc97rD2p6aEjYsvrJ/f+6V/cPcf0O5BAyf8+HAPmXy/j1uZeqG9dwCQxHnmJfwqzvM+Kmhe8XfYkR10+QPvdOXmTW59+2Z35OqjbkB/fxOl6z4/njOU58inrvsypWyvGxqXrocmAx8Au9cfcGtaN7i+kav+Hnua7nbDE+HvlnbC3A9jxPl4kfdHmHtD49f8nNrYcbcba/sHf7vESaev1IUjOjXco204e31dCtEGoHVCTqfp2/nP/4LmgOa7ppuF9ozqjeGtkn7lGede+rIwPnGfRof7JKZukTFIY+LfuO5Kx+lrk/rZpG1Rl4L48AOsFWWLXZD6S5t8Q06MDetveq0+LOWajxfACpA33tEuOZnczGdQ+fNfgR6sXuI7bgRuJucR0FhPp3EhA20cyMLhb7vWi2fnrbonHwxfKAjIMeOXeStGBWzxJalenLyN47MtNAGTryp/mGyvO+cji/jBoIZr/4/Oh3xtXtumlwhc0brmFy2fqR+81XBAcZ/j1z3Aj51j0JHEWBCr0+C0O4QTk3LcrHT0Ehk7iJD2rE0WPQijFwxgAIPj8nNYS4Td9PxJl9lVUehUHfwyGufJOHGeOzUHV8hfrPJTNlQYJ1biZHF4LFcjP04yAAk4SOmGbStD+gKn0MTQ9BXuISGHSnvO2F2bLimUCEucycHUnTO4lc0tWe1YUnltSyReEHeSnXbgVuJiaHSo36FyMT46qGNIQHNcYx7E1fTxnoOhrnkSgPOI2LoW2TOqlVcv7b7v6RHvNDj2xifjR/9Lnx83XPb44dWEOXTncff+f/MB9z1b/8FzCwE+jA0USMoMUwAAQABJREFUj41xH0m3MbKQPJ4xXEnqUL/Ye4KiM8jKk0gZL+4W2EQf1N4fiPFfvPOnPBCbUTk62bbmbs3RACBJBshn5aKENJx/c1g+nEuMW6CuVLCQNrE37SASN7pr2wFfLynmhttJGxy0Z2Jr2kFfkja4HnT94X+uePDvyrn9TcWW+6TfqmTSkWT/MDYBQN0OND4mo5VlclKOKDtfysnLwojehVMul9GHoz4YyoXxG3Lt08i4FvQh2NQym8tZeQM10sRqmRsZAe/CY5ENsDhkbtE/oJsBHpcKNNrjADym//KjWoAFUnbsteR5Q17WGL8sZoGt1TjtxAYptcoAJu+Uqx6/73k5LYvpWqUWlvbZqdf7CgA+I8AjBCcHYonioH8AyFr99D4WyRP4AwBiTQ0AhPMBCMRVEG6BDKACIrmmjR8hh4HIUBdQwXaFbGWYVqgConKX/iYk5kv1zOTCAw6qAKECGDk3ioGEpfl8OqViAMO5wCGg0HMfK5XnKmvtpyQ65roAHIAiltVQ3C/iBnatHiG+CK1c0hI8J2DZJPF3e3uza+to9i6GCttf706caHOPPTLpjj816K5dPusunT3qhnqPiHdx0vVdu+B32QFYXrsyIm5G3outP/+3ab81Ide0OcVzsGdCepJMbI16BHHKP3GkTc86gOzHv12Rd3O7FUMYjGBwuRMbwnB/JnqOdTYRQdu9E8YHeSbCNvCNiBnCWMb8QIaUADyJ8xwoV5CvV3OWjuj+e/cdcvu0bSAUi5/xywgBDE0H0rtt0j0FC3yfXfMHYIfhDCDQxN7m8ocKXjytvgAGOWgfUXg9MTXtASTbO9IeTFJ+9PKd7urR+71qgXlVsM5gyIV6SlfXhFdPsedl+bdSWMs1D8YmK21BvJgx4cNsuZ2U4/gbsX1TtEsNfW1KS4zM39Yy7FLj25cOelK/kfRVUTWjsALEy2hcjkAXQ+YwtOUm6Dc00l/E1sWuO8UuuDSvqKiR9uqVwXJ6cv+/8+KlemUWk85WgulPfdRz2ZqGBwUcQFDiABnraJ5GY5EQhjTNIwsTZQNrhscDmIjBW73Lehgk7t3J5kNhv2kVZIE30BP3p14bcfqJ3CH3ytKfVpN8+zprRvas/zE4on9YXk9IjAYR9z6LVa5d/skQLVM+7gMLHudwMQOFiHCPBxuUp/823Jwbd9Nc98CNA8Q2SZw5MlZ0LbtkWCJuY6pLW9XpbwvuXpIon0w3ESFljbvly6iDaXwVQaoHWX/C2fSvpRNy0F9Lmy41M5aWzmKmYpyFSHZMKgIs7NYfD2i4brf0Hsf7ZvWb1gBEfNxQLHlfjE9R7mim1rxIwHzKrdu03W3eukYL73rX3LZR1+7Sx2eH7hl3RiXX2jLu+nvFkZy47i6cvSLn6P1u/7PG3E+8dsL1Xp9wTx0Vl0PD8exny//kNVmvV4Ah/YDsnOeKeoSBffLK2S75wQQ0irVcGcuHfjgAxkP7LlNkFpmIud6znFUhkWAfOCQDzFtTg9WxtTEmj/jkoQ9Uxff8jSPK9wZEhSva8aMkNYGNXuyMr/re4SByZg6P5q+5Vx56nTt2+XHdl/4QUqhczJ53XCdJgEHaiInzQYmks/obumPTAe1jfdSfU4Z27+n6CXdp+Alfhb7QhoFlEhGrP+uOze7s375R6dRhpyjnTp0Mz2ODPCjgOWHL1qy7cCF8zNl7grK3EsF1fMOD0+PDB83oyIAc+2+4lbpZsy9T2gAAA7i2ju6a+UuRODo8oI+G5qrY3rv2kSg7lWnxomwMDMv5Ub1jZVTGy1Ps/UbXr7n6h5X3lNxVZaSjHVNKL6LKn3acvBpf6hEY164VA8MVJbMFNg6XoFmgsb1j7QJrrnxx9gVmT+ClJABjI1bTi70mBjHuuN5cWnzRe4TgPLae1xt4hejStWJ1+756l7TFmZc/9LPZ/xEiiV+MX4z7QFmrlyg245SdanA6niQ4i6yNOArPaaEjnH69zyy9Y4NYToyhFiW4j4iuMQgihMxamt1ejOxeOK/VT8snL443v0r7VG+QUYU48XBz+DCzhdm4VIAQyM79yRw/qYlBL1ou26oqEDEfIASkAAA9gARLTN/arCuV2qb/fo37WKuPpOHgGl+FSYrLE4/vjb+T/vYf8qLq7nVbPEfNfJTG7QCSIDhtxDs6iu5rXxE3tFn7cHfIKEc7KLW15t2pU0V39GhOGKnkPvWp9Xp++J7LyCGz7lM3XNKCUhQHGQK4GMGB5Mj0fdG98Xn/7wywA1c1Bj9Wx8LkPVl6rTAeizh/rjbqSSvgPjJW//qTr/RzifZsPjG30DNEZAyhc+o5TLImAsyZ8QvcQgjupM1H8uESwlG8a9tBv4817Vq+r1D5qZUW51ucNjGw2b/lPveSHQ+6n3mw7P63f152f/WX4VnY3wrhjp3aWlFejq5LJRPCAApi73rAKM/NNhIIOTfvF663EfvOYwzSs2G7Jd2y4fBgGNzONULqy0RXL512a3o2zCkOxy/k5NiQ6+ps0/ySkZ2eb0F/n4t1GA4ntaQPymzrbI8Jq8BxmR50stnvFuAY3zcgMq0v5vSQxGTSRWqEEFmVumTZ2HmwqoPUSL0bKvP6l3uRHYrutue1tQfYKe076HePsbRGQ4DOOe0ig17kfIQu38XeCiKcr3Al/zMSMX++7aEGSzu3e49zZ07XLr5Thk6/3vVL3qcjO8nglicsQ6E8ADIGjUCyOJ9Se8XZiIn7R8cRQlQN1w2KgaNPqPwYMDTQGefF8cw+6TZ+v0BYqxBMhVL+SxvgH3rF1ny4yOGcRRvffnMRYCM1NepyMuyAqp/T6v5cYNDKxgCzHgeyrFW7nIv0hUpT4syF63H9HG56GKLKwNImjoKbpBhvbVp945YOp+9w3anTHkCOPe9jXhRd6yMTYGRW1fTZQCNxoyflumdNl1zUSLwJUZ5yBQFJFqW8do/4iz8Xh1esyHxFdxI1GkBkoZB2L//hnNsu8IVeWka6Cjgh3/jMr1f/9g0sAx5Hc3dU94wOV5v+5R1Q731RDyxO1w4xrsGe1nE79UCj1WWMHh78iPubJz9hSTVDuGHcs31kIjLGzY4ByJqVaiQCFI32yKPC0FAp+H7U3w1g04AkQHGvxOinr01/2DGvf/4l73H5y/fO2Jfa/oYAhvhuhXbvCX/35AEmn/s87V/+Fe02tTmUYUOAp+R9jC1MbyaIjIHjQO9lcchzmovLB8bC6Nz47/VnzrrO7nVzgrobvcqF00+6rbvkNso+audp0DsX1/slndLuU5qYMCHL6YW5C8KfJPqU3sF/4nqrwDExIMt1OjZRcIMjkvcsghr52lhEszelSvbSx2pedzk5ijUvWEksfPxDLvuZjwvg4AJlbueqgMh6oGeua1geYuzua9PGNZZu4clL+kRcIBnX0RYMFoa5yMohxjKupJWvx3W0fEJb6irYppq1VnpXa9pxX1JNqkbsmuJR+X2usxpnytlCVi0YReK8OE6R1tcK5G0NX8EGJOD8FTrFXhG1TV7w4mu4ceSH/Z3lIFqcSXZhMYfavnDiJz3W71PQvwS4efapAoxc5iP6AFg1kJcs7zmZcLTF6mmkPerXa8vnwfHS7iv+PgW2rm99tzv99Hm3aau2OCt0VYEi4A+KOY3GYQs54Zd8A5SASAggWItrSR5tbNuGwZNApQwZAJgY5gAsJ+VKBa4cKHhz739ybXnJszWeiL+b5bidrAE3DXppLyaem3FT7RnbeVxurjgGNIA5wON8oJF2bHw+8PW3ea5hvbabJ7e50cx5AeRpDlm9spZuINDO64WNlnvoOf/e62V+6IO4aku5D30wgEJUCOAi2t+MuUrC3ZKpFxiQpA+U+4EfLLu/+9uwuxT6yZcuBRdN9fq4XOkxcLyd1ryFgrqFjh8Gbr1XLrotO4TwF0EAwJQM6CSX8ds3jozJC0Vzx7wgFOObFC/qlCZUglaBY2JAluu0r3/Y9Q0OadFq0QtnYcj/8vkT0lnaphfC0pj6L9c93pbtitsI5bWi4WgWTkI9Ku6V77SKY/B6ZeZLtxd6rXL94jj0yWJyIfS+4u9K1/GBahXE1HANTFx9//1l7wScAhZPgjvr057xR9wv5t5RbWshka092lpPuntwGOEuQsnrwE6Dj4mBDFxFXNOAxzCksT7UuyYib8o36X6aXzpbdEI9uEzoi41LBxKxKiJsAxuAD4CdAV/KA17oI2DPQF9OiuYYs8QEeOOY72OfMpBNIbiHVW6lMvWydd5yu/4UCw1Ev1UAG7fLdTjUDtdMNTe58Xt/y50duNelS8fcpm17/VyOmllU1IAkTsTPn3fu+XIqDhkQJW5gK5lm58atbHv6NyV9OCldSgFCOT2H0JLi/gBg/N35v71KmK9wvOcSa/tG5vnxltkH3l1XbE/1Wvfw7s+/TXtXiw1Xg6YmxIlpadbwB64g/h3ZISZJMQiM48lyyXNE3oi76xEGO29/yXt9NkYlH/lwvZK102Nw+aafdh508vfHtH9AjuABmUND2t5xb3hOg4O121nq1Bg4LjcYW6q+w33GAG2xoK6RfiAK54MM9ZMbIT7wSpJwwEUsqb1sc7t0ngt6Z7bUbBajm3xR79Aa+Y1/MtVsejWx0RGYyrMf5aj/csDK8cLpIw5ACJsbtjyTA/cZTETvOylq+FbaOSbq1m0fhdtoFCDF3Cu6gUY4j4DIxVAMpnBLE+9Ks1a7WCyUzDWP1YOLyCJgIicWAa7JYXEra6H16XTrA+6DXb9ryQ2HGMi0iotEO1hCe1CoONsJQojhIVyYAA4oZ3qP5n6HfMpZWc5jojz1Mnd1+GSAoIlrrRwgA8vj9vasF03DaYy5VeTDneEpE8KNAjSaWJt24OAB+ABk/uAWFJfAJ6TPgR51aQ8aqYcXBQ8aFfcueUiELAxn8/7S1+LanepwsMb2YJTraKpwPd8dcTDRK9478quey2c7bRx5olwFRckLAZYMMJFHHA5iTAb+cCL+sleEfbBxJA5ZXc6tHPU57JxyiK354C0c+G0Z/tzl2tokdpd9N9bgTQK8zS1NegZ6ELqZgpyC5mVphfhbAnLN47wbklNxtm5klx1cMjGHGlXLR+RdEGikr3BNCa3f9M2I/sZ9Jv1dL3+vt3A2q2or66/N+PtZFOYRrnIQJ3PExHl7KbjjwWL7ZQd+0h+AyFrlLf3kM/KaoDJGlk6dGDRyL/39OLsPOqVveBADk1CLNA7eBUbESTNi2AGd/u9RTKV2/WkdPZryuwitXVt2W7bJ8OmZ0LbVWYnQqwLMI/1ZiX40co2wm0ukftJIpQWWQUUEf5Y3SgvZpcZfS39r6cxsbiN5qxzHG30aDdZHTI242gj0z9c4k8JvSVYJEfHwdYH7HR50c0uLGxsZlGLsJm8gk07Lj5s4Y6u0BCNQ4TbSEsC+KTetM9do6zcqvk5epxGuI0uKt2wWVwZ9xDdO/o0XTyXbSp6zcKDPVE/P0crvnXzEsUtNo7RtXcYDxmT5eNESb8mDKUGdKmhMljeuoqXDvQSIGpV/7qdce+6v7dSHAMOYq2hxK2T57CMNqIS8/psAY1zWynk9vJRENLbFll1egx5AgxLUVl6ukJornDO7VhyCD6ma8kBHobWjtHpcx/yaHS47cF4FBJvWhviMerRZaccDSIFHxN/llqCUOCkDvKnWze5Y8x9W9RRNzAzIAOTZufUVoEdaHJJn+o1WLg4NfMVgy+p/7asl9/wX1P4Aosyu7sdd+cwn/b7StMm4A4gAL4B4nglpnjusQWQc0xkZC22XgZxYYqmhJ11q8Jx/FlmB6Yy428atZP4A6OA6l3b+iDP1FwA0ept2T/SD+IVzM9PtHm2sOP/40293JwTk+NCgn+GjvugBr5WPQ/QdeyeP+vJxOuCPNholAKJdN66DXuP+DfdXkxbDcaxWViT+G0UiwcclRDrPBAJs5nIaW5t8IXnJf43jeDsZxsD0AdQtp+HqxbNPLZkUodZDA/yiddGq/bLxKjA2pgeuL9MuufjKl2uviavAsdZILkNavyyqJ/Rib5SCvpD8vwlE9l654Dq61srZp0Cmtv/BypEdJpo1YbPSc0KJ2BTSFyoGb7Q/35HlKsARQMA458zkcAE3C+cxfeIJvVRrL5YLaMqxK81O7WF95sr0B0Yj9U3PsZGyVsZE2bY4WLqFgEe4mbUsraljC0490GjtWDiZlxhZQ8SOKRCcRc+djBYoK2sh1zDwOPnDr3PX92TcnU3/3bJrhgA/FugYFJIGZw5L5cK1EzOssONy1iDAJTchPyYANdUDvHgiZF1VyJzBmpo43MisDH8o5+My1PF1QXcUV3q85pY5qSSQxzEHI9O3Ef9QHqKJqWybIHlOi7tc0GhzB5yuu7V3uZPtv+XLDAsswjE0kBeDohhEko5eY1KnsVZ5A17GfbR2KMt1yIfs2v5EP5SXtytPd7Z83K3p/6xlzQo9eNTzsu0Ek88JCUEYO0JdTwfhYNf3ub72H1R74lDr45sPb8LxiWa/kw77CfPhbfdlfZ/VgSjh9774Nnf84pMVgxW9f3WdRj7eAYtmjR0DxzgeXWZWNC4XcxrjgosFjoBBdCEbISzkcZfj53w8kRupvIAyBhxvJ8MYpIYbtuxqaD4sYCiqRflQuXz+uNu2a381bTkjZhATtntsk7EkH2KzuZ2rwHE5n0LUdu/QpF7ujQNHq8rEQbS9fc8BSxJ4lMhGx1wK6fbShGvJF1FaPsdyza3LNsGrnbudIlXgiO+rwqKAo93ujVhf04YBMeLP9IV50t99j2uNLCnJq0WLAY7WTsxZiOOWP5fBDNzObd4Fj5WeGSJxNFG058ySLSQW36uB0Dic2YrEcT/72y5z7wMue/GjrrPvMx67AZTms5SmHQAIC7A5iR5r2uZaJs5L1w4DgLR8xWkrT4XG7bI6JRVoxhchQFErLNikxFZf+ruD8+KhkUAwYmgPXHxBasNTVa6QoAegApHa0EUiWm0nWLlxgCM6mJ4UlNW+P8M/Co4yfeN+qEIZ/XJ9I9Zuzsv4dU1Pr/6Ic6GsDHAQ0+Kc3wASYA6QZECJdAigZ4CP8zidc6O4jKVZm+TV4mZSzsoYmITTBxno5Lxn5GM+renibCB5vbDbdZZOzfoYoIJ5YPDxra/3bdiP6VYi0UH0PdBfEKd7TIYfKbdh/VgAlQv48AY8nr52JHA99U5li8hGKQaAVqdRS2z0HbmU6TRafQsbAY4YyDz2WBh36sVdr/U3b20nw5UCjoCxng2bBfqDWkqyH7fKea21ean7hvrauFzsrLRbooyb1LtgSO/Ydr3PtD7KDdeUVEnMtc8qcFzqJ12nvesDE+KeBA5EnSI1k+GEXbl4ckFfHLEYnJcmftkQh8dicLiV6BZhrGPhdx23sgIcAxAXR+wGVQDmElujn5V09WMAKn6R2yRoxK+jlb0R4GhtxCH9wura9CTrgcfdm7L6gAk14QBhvMK9eBU1JcNFs/xsFlE154HjaIDSdBrRi8SJLQxJGw/60f9//rYbv+OQBzxY5AMuAGToJeIQu6cn5y2lAX6AQ8TQUBIIsnhDBiCNgwU3Uo/Gg0dfIP7BnYX2iU+SZySyDgPePMpDXKpzgKTApY+Trfw4Tjucl7xlNVIDjXFqq1tbuuTbWgjT2kTUXrSu+4b4+IELWpYY3YMVuaPB0tq4jb5Q4qcWIEwU8acGDjlJgk/S4msgGt6+cxqoWF7yWl+VWPvgwaA7aW3SlrnxIh4TLrpw73UjrrroA34rG/3w5gM8q8nKu+H9X/5Vd+LS495Z95nepzVPp+8x7metuM0/8hZSD+D4zpcGQ5ha7dYCjgYU6xnD0c6UHMFDTU3h78KfNPCznODROI63i2EMIt7hgV63fvOuBkZucUVuFve1PKWNMLKdeofrA1j4ISNZiuN9qL8DXPvIN8QqrcQIoGO1GFqMYQxcRhTS61lhe91Kuc8olQPXkq/yIXmJLRZwUB5EPDlelpEYHG4l7TbqR2ox93qz6izuyczurYmrY/H1pLjMSDQZO4AQDCVcXkAGqogbWCIO8NrQnXHXBsQNq+j4jUm0ezZzj9s4IR0vCkVkCu+0EbfTSDpWlRCiqEe+Pc35jC2z35d7v3vL1Fvcs3LTfuQQUc+83nSvAIXcq/WFkHuynWLCFcPvtA5jqA+QZGGd2i1Oy+sfdOsPHoqL+zigL9uaEdjDP5lEtJVwTECyqeL/zoAhFXz5aJHnvL8MJ+u0v1ZKu7W4sVMegNJWlcTNK0lKkxoTeMTyVw8M0FgFeHS54gBbD9il9EYFGBpgNNBIexb3rwHevAA8tbU2dSmASWX0uW2upxzOCwJ/GX3pW71qnyoR02uMgTAcELiNAHh//3JDs/7Su9x1925fywAcJwbi0PO752AwHKnFNTSOIXW75OMxSdSBa2jtEQIaa7VFG9Ye7QAWQ59Cu5bHHtK2j3TyeliO7+ic3Y9kueS5tU16eI+xF/g0t9bK0/+2tmm/lXx4Y9Q4JDWhN975r9z/PfL77uSVJ8R5RIQ3rWPJg/K6lrP+Oq3lxgBjzJ3EmOZHD77RN2DjO93adMz+1gghM4KzMKSGXwAjYHEhgNFE1bRgeo5xWtz+jcZxPYM6we2wzrCXNuvichLX6O5cvh1pavUdZlWz1v5i5UU3/XfSqvf4hD6+JT3RF8RSrZu1+rCaVhmBK33jAgoLH2q+agb7rrmNW/esyFjG3Eq4lEm/bCkZ5/DiNd0hvsY91/J2NNqpcByLFRGfOfRdqoE2DiTW05ABxnDW2G8jnMekS57GWl5YKRalt+bD7jL4bOxZgAV4WNBKfhcZRHwxVzHuhS187i6Bxt963wwwQjlEmrXEmXEbpuNIGuAJDiR/dQCsWgTwhI49s9Ft2y6RdO8Zz63EAhsnzFA2la/JefSZ9sPftl6lBvR4q1rciliIqLokUTX5tcrYG5k8Hw9dVGG1AAcg2yoH2zNBT+DCTkn8jtg79NuuF4utSTMAaWCEME4nblzDJNjzBSs/tepbGkUAa+g5dgpYAi7tunEbMaCzdOuPncf1LG+uflk9wnrtx23G5a190pJlADW4XhnQDjufeeKj7tTVJ92unrvcGflmxdrbTzTV8wBS4N2DLC2+/pxnriIxtxGQaDqQ1gfSHnrOe9yOtvurnF3y4nG1PtK/Rx8puV96m9WeOzTQOHep2bkL0YecXbvxFDiOeBeBkbHSotnGezldciUcf2MYs1L6jXZnfl9seTwoluvzFevnWCur4ZKMwGJAIxcG/QPOVooAhfNxK72Yp6I75L/Gxa28nY12vPgFueoSk3EgFwMYrStbpUNYDzxebTngOZB3FR9zJ90DVmVZQriGf5R5v/u11z7idp/7qMtrqwnEtOZWZ66Les6jwE+L9rI2LiucRfw9+jyrLMDoXvugy4jLyIJv+nAskLZYGtCjiueqWd1KmASIiKwRa7M3tPkEjOtZ/MC2a/pbE1e3vNftXXPOjUj3UV49/TUKRcW040tWO8vUAnpCDSoZhNbEiBvos/JJIMl0A2uo8EwuJkkR7vPxyjnW2HntOQ3ZOFQ5VBW0CfjORkxTyvrdU556l+uSziNkIARuo4mU4RDirw8uIGMPF9IoFiNb3fj5UDdQAIdWxtdTe/bs/n/23gNckuyq8zxpnvemvLdd3dXVLU2DBhAIpAEkkGHYGWQagfiAhYXZGcwsTtMwGkkIIQ0a7O4OO8MikAe+AUkgaRYkhHBCQrQr013mlX3VVfW8N2n2/G7kyXczKtJnvqrqzvO9fBFxzbk3bkZG/ONY2lgd+8SHdAuwh6MNCgM262/ltrW5+vPb4BLsRdVZ/3Bbjq2O82NudkwdgKaru1fteo/J8e2PyJlbT8iZG0/KpanzKh0OQCFXAfcT56SkXzBB0IN3ClI5aht94saR5OSA5dSaSvH1Sz649bgGrn9Q3vLS7ysYk3Ht/H0wTzn0ohfHNb1jxmkMgpLi/6uRMvpccKLhuir4rWoDd9/0L1a/U5X7FkaINUYQcS/QyvKCDG8NXbwNnDhCo7YaIn3UO4UOlaQvLS1pFJfgXhPFrwUco1alwWW5e3qDud4Zdia2jlKDB7aChU47AMt1Vff4anCklQDUltNOZd9hMfCI2tpoz94gzE745m71jdi+930iJx56RFnp5+nHJfvUE7KmH4tvWWrsAFapai8Hakzyknrtm9xDaenAQ84Bxh7U/gPfHpz+OQCYkCZ2q2rZt/Pz27APMESt7QMtHGIGBoJbH+UGHtkeGrns2pIeEQcWZ8+j5aLxzLLMXa9nxQZOXe3AoBapglptfkzaaCDK4QGm4Ijnq38fwHTFQUywU44cvw28ZsVuazaN4Ru2zd3xU/UpxHpAtsZuDVRtnVEbUULU2Br74NDU0AAmW3sDeWxNJQ1fQu4cV9tE4+O3p97KrT/H7BvYZB96QHlA/piuwPsXHtt4Gy+a+m38epuXxy6/W2pMGllfmyt8cUb0QQ1hcfigTqbd6ZuPy/WVp+TZm086Rxr9BvLjsZPW8E28MOwfPSZHtpxwL9sv3/GtBffHxdlzMj3RowAzKUPDSVlabJOhkQ59kGs6RzUBsPPzGX/PW6Qg7aBf16h9P1SP8USSGmW7bfXVbB/OWaQQOaR3IDrAfzX8mt0WgQ6RTZqpUkdN3a6+CJtNWY3ckmgrrYIP34c2e44viPFqtW9kcbCxwUD7XqBStkPMP6wGB1Q6p52JcacSd57gd8BphzdnVSjd1UtcDDzapK9ctr3mbAPQGDzoGQGpoPB508Z4FlA99scfdoUGEllfKHP4Ack+8LDETjwc9NcybkB8LFqY/0DnYcyDMv+wXEDyEdhAIlk0gETMPwOPpBQssFNU3pABLLZ+X8CVgUfbOqClgaohyvj9Li6o5B8jzWyndMdWXJ0Ttqg4CdAIudNE3AfaVKKeRF/qQpQ/ZgeHamJK0p42bJHEcgW6so1ldv0MNLqDIv9YY2zu3Nz1nGxtOGYf3qj5p3oD7+P8mnr8kGgBJpEEAupo44MyA4+E7GHfwKaxCPPk2L5P9mlv/HxgdjUkXTZ+bP1+8ILoy8d4u0I9Q3884x/U3f6/XL31gKcRcSTNq9TKbEu7f94P+nmRO0e/n7Wx69mObWvlly6lZOu2dSfZnJ5KyVNPrMvBAzPqHLnq7o83bnZIp3oaDwwlXGghC8F2/MHg11Orw4vNo9TW4juG2+DwV6/kEXvJEw+hjUAqq/F074EMaUgDkT43kwIJt3cBNnOwHG++A153yjmKtoDjJnwZrSGCFahEDc5bfTGnnajYlY1y2nH2SHf5F1UOPBpQ4zRQLe0/oA/uBgDKMGgstkzJN70lqMpt7cE+dm5JDuxTr/K2vmJd8+XFHujw0jCOBbaKppY2oAjIIw81xD4EcIoi62tg0doYAOXYeADq+vqCl7dUulOBmIJPDVdBwOlOlUwaAQLdwueGRKaYQB8dMQUAIh7VIzKuaLGwieuip4FqOqvG96msOqrZIEW2TjXqJhA08M/P9qkZmPmQzA4+6mwYCYoNseaAF1NbE/fRB3gGEC31nJkQBL03VKlhsAQPyACf2TkaP+ro4wcMNxBFnU+0s37wg5fNO6gL5mHXj41tPMJzs3K7Ru241JaoFIOjO0s1ydcVOw9rEJ4f5fv28S2TVafLZXHZvddaB2t4+D61Ye1YlekZzaKjAMvX5nzt1wzLX/3VoL6IqEe9qsRjKtpEou3ua951scGxur0oVbVxqPfeCXCEsK3DMeZeoLD0uRlzXl5a0DSDlV1vjRp/fXVBOnq6RcPulqRy96OSnVuVla0AUpJaiVA6HcRrewEQb9CmCpfQy5xJK9MqgQ2CowfejqsqrcSOqB6nnUCNGvF0vwvXHPBYSXYZQGS9oJEb+nt+JST+qmJN7CG+a1dKAzArANKwiMUe4FFs/bYOJJzOyqAHCA3YGTi0Lbz8/TA49Mfy27HPb9X4mnSTcso4BoSttyUlneiQ9uSiZFfV6UdBenvcVNUb3PN2jwDD0OXFsQONNM/VTcd36vmp9J2xRjXv9OJVByoZH0Drq543Rgn2nNQ8wk7X5s4W6rrxScnuffQ2tadvp0g7ky6yb8DPvk/KjMzu7uplDR7uBRqnPgB0wbjwsO+zGKiycfILkuNhY9nWn0cxnn659bNxbUu5z8vaRW2RxHCfQRLj949qy9i0CVOwxoFk1OYXblPsOJgnoKpDeBzAf1Q1uqzZvFpP/PzbM/Jt34LEmnkSYkq3SLr1DcUkgoHNtYLJnH0lx5WCPv+ltNgca/W0fvP3BvcYVLNd3ffGs67Z3s6owqFmqsKjvsfu7m5ZXFqW9s7SL/kt4Bi1eg0u44fbovpWwKSVUkSNEQ746zvtWApHP9MOsSu7Ee3kntrhB3t9s21ub3Ja86kEQNpMBlS6NDWF3ZuVFN/yAMBuCvVRIwgVb0c7ngEbTl728LVtsXHsAcyDtl+lTMmFHMoKdSCmI17QBpCoLgUYQ93zh750Dl7wTSc21OPwbNPzcbz1JQZEmCDFnT6o4/o7D19Hdoy9ZCwWfR+gTVa9pIc0cE62o0dfjPS2PHdFkgpSXVxKncfV+f2yu++iA4+megZgmrTVAUcbLH82wY6tia0HcRL7+x/KgxvWNgygTLpn64+ED5ACUOzXawkpIXVmdxcGjaEpFPA3YBUFnvx5MJ457IT52bHNL0p1Thsbi3Y2npUZDwtJZMdRW18aRn/m5s81qg9ljMvcrK3NoVj7SsrhaXOG75x+H9euxeU1r8vIn35Cf+CqPr6NHIBUQMmzSD8OCGeDLDi0BUAGQFL3I6SVpSSONlYt2WW41xihmr1XhCTrpKgt8iyy86lnuxmq8Mj5ZTSCRLK8XWUrHE/k6jW2cFlTDc5oysFa6Ob4mOap3nLXR9Gv5dw2q0+U0w72Son/8THp+WyQwk5vm7mbJzfRADBV80a+WecSNc4HXhWcwwd+L6r29rIoNbZ5Ndrb/+29ai9JxFIKgHS92zQnXgTxEIbs4RpuYg/fEQ3HM7rwp+Hq/LFJ5XxJoVUCmiiHDBwakLI25bbwh5D8tWWWXBJfw2q8gzju+lDGk5uHM6Q3WLdlk2+rrrVZ7CWVsuqtHUV2Ljjy9PQGQCAMAJk/NJM9ID1rZ9TZrEMBrI6vgb9l5nwBiKYd7alfbDsoHS95F0VlyQdc1ti+L45NbY3EkbA7fIef+VTGAabvekPpFw/4mPra5x2+DpiDkQEvuyasrbWxemvvb23e1idcR3kxPoSJ4QV0cGRHvhttOW9z8rG+NPDnQblJcP3yPKM6dmxM4/uqbw6u0WpZ8uJh0kqu1bC0MkNcUSSVFUgrTcJZbg6ARl+j0eyczOXmU2k9YZlmJp5raoi8zciBHT5fXiZiqXmJteubSBlqAccyC9SI6qWVlMwurNXEivRLI9t2NfXtpqaJPU86Zd74rQooUs7xwd7GTULsbqZ6CwVU8tRH1hW8mQcgU4/c8Z1cCryS87aFuYk89WRGnng8COqNFCBMBhLxZGyUVDE8hn9M+qrlVU35ptK0UsRD0B6A/r71oWz0lJ4vwKwMGSi0MDzhPuZEA0ADSFr7Mmzz1fGlaU3DpakKc0G6AYWAx4xKa+K6YyDROqym1C5SvWrZxjWpdDgOo7XztwZUbX7UAfwsrBDHHxy/4R7oa+saPkgdc3jnIR3j9+7ZFqi3cyDS+o0v7pORtjHJPvTWokG24VuO+C4C1WvQ0gddBpLIfX31ikolNWIJXthWbt8xPQFz8xoGyDy8OTZe4fY2Zhhshudq7aIAYrhtsWN4+JRaveo8qvsGNKWSEvWch41Vbk4+r2r3bU2i+vnzYD5+JplKpIRRPG8ry4FK4jmSASoAmYEKnLZhaSX2ti4lY/hHEGLs204DWsKpdUPN75rDqJeIRk+u2Tmwo+ZLnuoO1Z6k866KUa2CspaquvjaNKymHq/qWjLHNGziLwBGqUPHJH5Ws7HoE7cYHglulNgMAQ68G6cDlSxSACCD+6TtI21hn/rmER7KYQIMnngoXFr82H9I+g/14j2qrAFR5aS4pXr6Y9u+PZgBAa5Ms7ysTp5zbExyGMXTgCLhekwyxxapI/1MxWs8aG/1tKFfMYqtq1GZUjIeSHectFEB45o+MNs1NzXfuTtl3ZJ9Ia7XDKARYnszdlRtGcfKAmCbG/1Oafaak4tLcnpxWS4sBl7dlENIiCA3bm7/M1MzQaGcddvXbBty9cd7FmRne6/cePwjkn248CIBqPlgC8Cyb/Apl+Yvx0zic6ck0/+ADGvBsC7RTPa4AtDgGuT74fsyEBV2ejHvadqYhJK2egYOQDIG4xtQQl1OW46NJ78pyNq4g4h/xoeqjb4RDUNFjMd5uGvNqzt7ek1iiQHnEW9qYqqDtsGcvOaRuzZnGyOykVdIe8j/Trxqt2trbvPlZfB3/pvIIRU6Y+O8Z6/Ief25YKJSiZlKmL871gsrFkvII1+V1aw0t/8u8vdHvc7NtjKdy3pgoNLdCz1p5Xt+Jav3qA34gSlAe8eGRsJiZDL+RnijyNkJGXaMjm17yIVIsuNmbJvt7QyIxvmpnGdzo88tpqYL6aw6AVZwObckjo1e/Qh+c4vrsricSx8SUV+q6F4R35c6h7u5bvEfviCdv/I2valu2N9VM9/goe2BydxTvEBaqQyjJJWU1U0f+nTdLJrNwM97WutYBh4GY09K55l3Oza+RK4SvgYgDVRybPvW3y8rxj+2MuvSD1off8vXv5bWtG6JDXtHfQ6oTZmqkPXrTpPGU0OqGG/U3jYHf2zj+dTCgvzhjUk5r2DRACJ1Pki0trb1Lyvr47c/1Nsp37VtRNoP/8ltoIp84NnpU4oIz0kiJ610fBWwE0g8ao42Ltu1Xa9xh8XC/hADEjj0dWojaQSQMgK8zqkEEjtKH/DRxgdstOeaAIz6ANXKfbBF37D00sazbRjUGbizuc1NnpSd++4vcFYI9zFexbY+zzBI9/vAF/LPwa8P7xtfK0fj8FM/aUd3dvvQQ1nVfmzYVnJfPHb/svzsz2g0AUUoLgSbxvUl7NzZ6dPyhet/Lhcnzrj7ZT0zP7DlATm69aF8ysZ6eIX78kzesedowbUQblPPMfaNzc6BHTW/mJrfrKCB0ftTOWoBx3Ir1IB61NSoq2uhy+efkr2HTtTStdWnghWYnb4pyXf+B+m5fqWC1tU34UaJRMVXgwdllAZqcAOQheASj8fS40WpqUv3qKyWB1H4IV1Zz9tbVWM3c3vv6JLEycekQ3NLQ+WATDQHTU2dyyQDaAPEGYAzfmwhk1Caapvy9lWT5t3OnZiL5LSG+Op9wJYigGN3nzq/kDEn+HJNhWyc4D8fPyCfvvEP8qc3p+VQT6cDjVZvfP1jf7/UNRMGkUcOvkK+ce93y0u2xGV5/Km8/SgpCl22GZ9xaH8itV8GY2Oh0kJvdkAkABJpGGDIB4LWsVg5AHNAJY6EDKIfBB9iTHaMPS77Fp5yZclPfNht+Tc5fEz61GksrlL4OeJMar+wGUe+ccQOvHHyMTIpHh6uN66dL5v6zUAm/UsBQ+MftTUwGlVXrswHkD54ROp4Ub8qX+JYixq7lj7hOft2jRYp48krX5SPawrH8TmuJ+Kb6u9HfztIvlyWHd3isENB3saSygrJz/ldYZeizbifXb/ybNlroSiDCipQhUNmFlFBl4Y0iaUXNMlBedDIYC3g2JAlL82kVuB4L9l9lF6Bu7d26tZVSZ49K/2/+ct3ZJJOMqk3ymDL3RLAAaQEVEKm+ta9nLrXnHbSb313PpC2a9qkf8Ue7pUMhyF5RyJd8Q2pEp54BZvUkfaALQN4lfSPagOPsOTPygCWqI3xcMa+MLY4nQeExYAaIC1N8G9VXRtl9PtbTfTlQSovEwQCd+kN1SPcwOt/PH/JgcWO9SNyn8ZUe3Kt0FAV3nwYmw/7kM3F6oLS4v+39w3LN3enpVu65GXbBtw6AmRx7rG1KN47uoY1w1lnNHlRPdLV7lLXK7P3tU6l3bur0KzCQBKAJywRtDq2O/7698QHiOlDD0haU16S83z25W+U4b/6iH7/KiTVVIAjU2fyE6OdZTWikGNLacmxD/Q4BihSFg4ttLw4J4vz0zK6fR/NKibmDiE5hC/S8oWrTzlA6zOZXD8uA/sK18avr3SfMQzsWp+f/veF6QhZp+HhIMLC/gOBGpuUgs0k7mf2cuzbNaKO/vhTH3BZdghv09bekW/HfG67N6rU3r9PuhdtxPh64Qf3RHaLhxj6sVe8q241NtfC8tJcU3Npb0YO7PD3jZSzU3+r2fiGuUC4jX/cAo7+ajRpf3JOgwUT7K1KqvRNt0q2rebeCvAj7ekbkvZ3q7r6vKro7iIKAEGhmofpcfO8+f0/qh4FJzSXqca+1FzmqHzYkhItHk9uun1MsWVbW12Urg6Ne1iBwXUxHlHl3V96NKq4QHoY2aBMoS+JpClACPKBqQFHV1HmX/AdBqAu06nOQfHgKT2d3S896xfk1PheeWDnZQd82rYelrf/0+ccaDQQCHvjwb5fznFOuKnfOUcbRB+/bfh4V3tCfmjrRqy29lhStvUMOUGP2VYyx75MYItpIHpjhMr23Hn2xKVdJcQ3d/6MAB4BODjOoGJGskgmGgNXBiDZtv3x78r2v/uoBlrXOJllLEkARPM77pfBm6fdWl555A2y80tqx6m4fXnPA9J3/XR+wgDIxVd/jwy99MX5slI7tThDoPKHUPsn5s+7fZNus762nibdtZcT11D/mcqfFJHVUCXgsRp+flucY2oFmUfvW5Jf/60NaRag8dc++1bHnpfk9RUNb6Mq60rJvVrrRZ3PCc6+XvO3SSsVWJK+UaGlY10veMTbOaGxPJspDbw6drtZRKXrUnO77Jpk9UcUS5ZONWj8E29TsoPWtjkrsLSccjZO1XInNuGKGsX3DegrYouasgKz0xPS068ZFyYmJf7s000Zo1amPPh5q0ZdQyBYS+koR0/IwA/9hHT39itAVJs5vTEincZoe352WhbmJmVOVfDzc1OytrIoa5rxgrhjGfUez6t8fFRR5QR5OK1qdCmN/lKWMPIG3Kocq2zbahpkY6v6QH72ti48nONIITziIR0u86oLdts0bZ/fln0+8DU+MfU+hCpZwnwbnrjeTbkrNuMkjNsH5+Tpq3tlqGtafvHsk87xxfrwIITYAgytPCgNysNldmxb6++cdXJfAaDxh0f1Ie41SmmDtey69GmmGjv/G7P90t8xq2YWgQrazv/izF4Z7FRDxArInef6tKDa7p/+hMSGjkp7/7a8/R6AEVU0auLc6Urmo++XLZ/7fbn45euy3LVFRjW+JcCQDzStuZ7X+rZI29yEWxfKWJ/OxQl23X7PlZOSOHZcspMTstg5Kn1rGiNTBwBQDp78S+n+8l/I1C1y8qoKd/t2B2bD1zTXOdf44vyUgpruiiJbABg7z/ySuza5PpN67qwna8gn3XdIMktTrozy9YVJd22560tNBDLLQR19+bSN/5E65BDKTYFRxzZ3fqX+hc+Btt/yypg8+URWbty4vSdq7OmpYM2oZY3DLyHWC1V3qXprF96inn7fr3Wo8ER/sxqKygeNtDWHQ+oqJYCguzfafVEnhyc390I+xOlFrc2Xjv0k68e974tjn5XD2x6U0Z7tlQ5V0G5uZkJzaQ/rWGXeZAp6VX6AsIiMMf2Dm5uvm5BpGphB162y76Alcaz8O6255c3pZf3B2W2xcjaIj2enbjU1XlTls3l+tixwPnr0VffGSVbgEFMsdiVp04pl2sGLj5RfDfXmS+u1r0/MYjEc61nwYlLHKJ6og3s1HmJYshPV1i8zyZBfRigeoxTx7XK5qEE+ivEdQKHecJnlmkbVXUwNbOppwM3etg65rEDfeBzEznEhAKtW5ipz/wCFnekjspIMPKhtXL+N7cP/7bsGnPwly4NViTKIfl16DezsH75tnZAcDsUubkjKcvczAE+1tHLsZ4uGArr4nv9XJYUfdRJGQMq5xDE5nD6jD2qVwu0PVM8aa13kyIYamjqI9mH1dL5OpYwz0xkZvBXwoq3Rqe98lwyq9BFHGwgJqNljAh7np8/Itl2H5Pr1ZL7c+toWwEgu8FKE6p7v3yS6fluuM6Ow3auVI51M7Xp90bWzdlFSR+rCamtrb1vWZP+B4KiYJ/aDD+JZXfl37ts0wjkMGikjHBpalIbed2CcI6ST6ZQKb/TCSWrWJ17Aa5U88rzYte+YsW74dnFhWkhn6McLbfggEQyrdWBsSRwjFrHRRYvqGGM352p4r6q0KK2Bqrt7B6vp1mpbxQqgehgazQX1/VdvlvTjX5H49K0qOGxuU+wa41vLvy1j68MNEruhDpWWdKpTBtdR/+Co9A9tddLKrp5e9xZu0srlxXmZm7klrMnC/IyTVq4sL7gUjymVHEKE5eBN3ydsuSiLkkC2JWOyltI81U14Q0/3H5HkxF/7Uym6j20iwI2Z84hG+mOStaKdtMLaoMJGgsGxSRzpF9dsMCwHH2waOXYDeEzXOwZkPRWEAaI/IMEf30AjXeAzp6ntcIqZXk/JrkS7XFIxEvcPJEHU273kQFfQhpNKxVW6PHlI9vUvykhHm8zog5J2tDdC0vhT2/vdGrgyrTyn+bYVT8lIDgCmVHK9ovecIU09ttZ9UBIqMYOQHEI2fwAj53B5bp+TPgLI/XpbN1cY+sd3xncXlqBN/u8/LjvHPu9AIiAG0DcTH5XRWCBJvLw4IgOpCRnvPSaDOMxM3grsFnU7oY4x3csqgfR+u6jxDTimBrY4dbVJ01iby53HZDg7Idue+QvpfckJ2fvIDgcMOzs1U8/lrHzlH7PS25eWZ07NSEf3FleHCh1gZg47nFr7mcekbeKLobPcOGRtEBx0dgYINzNwSOJrGy8ftGS97IOtK31mBl4j3WtnBdDO+tOn2NptjBZISU1a6peXkjwGc9BrTwXJfFg3Wyufx/XrzNMvKb6PPaOfUCAKNNI7o9eqkxDy1tUEQjrJvRCJYwAg0/LFi5+TI9tPVCV5xF4bUIdpU7NoYXayYul2o+aAlLNd79NmRlMJ35bEsZJVqrPN9QnNMlED8fZB6rzhLbtr6N3qUm4FitmQpn/+J+86e0fOpVle1FHrhJkEN8lMNh1sFcysrqy4+GIKR1Qy2a6AFHtKBacdulVA2aZqzqWltgKP0kR2WYhE1az0XGFHmahzCZeZk4uVm1TRtlZebIvEMQzKwm2tfi3ZLVeXjmi6wEsOPCBtMpDFvg8awzw43qMSYJM+cgyQhMYzanCmxDiQDyg5NtDElgf9vxjqkZd1FaqhgNEXOg/L4bVzt52PSR5NElZKsmhtGNepXBUk2da3DaXeJ5M88uKx87f/feRvDgB5OnOfPNj2jJMoAmhMWmigcGbrhm0j0sj5bRtOMiurCoxH75cd82c0JFpGeroUPOAk86zaHgY4Lj+lKGezC+eWZFpfpI7cf8i1AzjO62dWwWPP+hPy8PAfStfKWJ6H7Zjtoh3b1r/GirWxtmz99pgI7B+8LGy3f82jNUse8bj+/fcHCQL8scL74XUOH4fb2zEJBnzASHkYNGZUTO48prVuTe8rZD0Kv5Aav0ZveVFGfQ1Q/8lvfa/cv1WDX1ZAmyENLNCAVTCnRjRZW5lXCb/eGxKV2TcyZgs4NmLly/CoFTjWYpRdZiqtam8FigFHmtxt4NGp4N6hr/B3AVkYDWwqM/o0sS1qcMsLDqAEWA4N9MmCIkdy0DbLaacW8MgDGVBjnsy2rD6os7Lw1ldVA8wAbb5kz9qTf9pSCobBFeO84+IV5wgDsIvqb6F42J5TVbXfxgAjY+2Mt8l1tU/0ya//+v52+da+LidpBGfqdJ1QNKsMfZ4nVZ3/QI9+byMHZHVyTDrUyWrP0Ege6MYGDzsnlzDw9sdlH2ADUDbwaKDT1sCOaQt4XH/P70pGvaQh9e8qIMAKYBAParbX+47JvpUzzmHGAKK1sTqO+V58XoTqGRxSJjnAiNmbk5wdDUDk5MgxGVI19nPv+1SBOrrYy7tdc3ZOXEvz8YPOm/xG16vVPvGk2y84mYgD6++vSbgZ10qUett3NqJP2KO6mMra+FuGqQ/8npWU3uIcQ2Dx8xpQPOwkg0qaTxgwwjEMGm2UtH5R2G6vq0S9GscY61/PFvU1kk7m8KoTb5J/9fD3u7mU4kkEjq7ufunqUff7JhCAttmhfqKm3RZP6UuVfgdlMnv5fVvA0V+NJuxj33VzarkmzsQYhAZUtdiixq8AoRXmVTWwdeeBSOZ3C3i8m0Bj5EKFCpFWpvVDiI25ad2q1XVnpzrnZFR9qjfHGKBSpZRJgmGrTR0OPkgrAZs8SGohe5BX25cHdxSApDwMfIy3DxytLLw1u8ZwOcfwfvvY5bz3tA/yfCAX7gsYOtjdKRdVQmNEX/qw3atmCVfUNtLKaPM9I11yuCOQUp5bXZMjun9jMTB12NoX4S1hjHPbYU2PONQVeF+jusY7GrL1oSyuXsO2VrluTs06OBvY/BGX0rePNCC0vKxSp49dlsxEh4YBCTytJl76Rg2P9YR0d6tUW6MchKWC8AcYmuTR96SmDpOAzg6g8e1EP0L2QITtMUlluCWSx/GBhx2AnJ4Yl+ERfQGIjeY9waOuNTunMC+cgiDCE6Fy7uyKRUooWYs2DclUDEAWk06a1JYxAIo+WXihMKD02/j7pCuESFMalaqUuhV9lHWqYMrSlkYBRdoZFQON1CN15GLNqClLMoxEjUGTt2b/+HW7v0Ve/8gPal744mroZksDNyPUT9RyEr8xHeuu6t7bAo5RK9nAsnqAI284SGpKXcwNnOoLjlUxaYK/EHcaPG6meto/70bsI9FtU49QP6hsOacd5GGmBrcQQ6YGL2c8H/VAb8R5GA/AEo4LnSk1AitCgDbEY9nOgSItRMgG88sXrrl6VNFX1H70mDwkpzJP5iWAxQAk0keGIO0gY/HxsTbH9N2jDjbqJyk/sqXPtT+/uq4AMhDn0R9C4ria3Csdqcv5cYOagO/ppUACeWh4w5u3GECyflFbA5lsifFIGKLxpf2y6xOfF7mhLxkH75PV2DaZm8/K1pkzDhialDEKOAL40goQLWYjgNDI2iNRROI41nZMDqyf0SgAeNVqRh8toz0AE/tbA6D0t77sG3jsarvsbNpMysQ1ljz5SwFQVmcVmTnvbGdXOw+50EVcH5CfT9wV5P6tKtAmeD0gsqcnCFPEPkToo2KOMa5B7p+tp5X54NHKbOuDyUoBpPWN2vpSTEwMzNazGO/3fPanXJzGKF6UpdSeFhU1L5B3kgCx73jZb+kU1DFqeKtqSzR0lkebIQ3cjFA/3im53ah7dLhN1HHLOSZqVRpYltIb1PJqbVljCDSKVKZZ9mENPM17khX2ozx5cRwpRvFXvPKOOczw8Er+i3vE0ztiAVMatqZbxRNp9Tw2mp+Py8REXEZGO6OddjRVSNhpZ0XDU1TitCOd253TRaUOMzanSrfYRLmMLypJhaLAXVZf9KStx2WmMWeaMP//88p15/hCOY4w0ITccBLDWUU1W7rvk8X1SQWoRySd0FgpHuEwwwc6rKkDbZ9j5mNzgu93DnXKsMZnJBLStCKxIQW059dSMpJURwFtD3BsywYg2AAnfGx/i9pgQprLQxZj90l7dlqBV1AGeGE9KiFr59YvNaX3tJj0fPQJid9U0AD/aQ1JM3dDetbmHTt4M2r6wP1aHoTiYU4AZDyrOy+fls6lILwOZfaxNpfU6aVXw+9cfNEb5OD1zzueyRBIbNc50A9im1Uv7dTNW3nwGP/Cn6s9pDqobB9VILFdrl1T7/mFJ6XnnP4mcwAbjlAAAEAASURBVM4rWQ2dw5iLyUPqXHRR+QTXB9fIszf3qvOPxofVNcOJyJyhCM8DWZgi23fOL9o/q6kdZ1cHJNEzrC8fQ26/LROE9HEd9Z/PjzKud0L2ZPpuzzCGwxqfmzcDBzbC9dgnypnNxii2pY8BRkCj8acMUOk7ySFt/PTJjxRj5crxqG6mY0zJwb1KN2+99zy46xGZvHFV7bkXVX2OeU1gCEs8WmJE2guE17Vhu80O9RM10XU9rzZ9w8pyn6iCcj+dKnq0mm7aCmA/hrSlRc1ZgcAer/ybbkJtC51BfXOmEck1ylA/suFdXMjNeF2ljj4hmfBz8J56OnjgWBvU1rwoIWXHRAPHMEwJCIFB6s1tu1RipV6NSOL5/gD/kzeuyfil03J17JRcm+mWa0NvVk/wwH4prfpdl23Cyd1slDq3SbJTBDwADkbrChjNM7G7K1GgdgzAUCBtJO90FKFmhu/E8jNuu3tP0gET2jIOmWR8wu7Rxrf5WD0e1KilYwkFDFropI3aKKvpDvlA1oetA086huOXOyf2+UwtLzlVq69GDaumHcOIf5y3nbtJKzOfvynxW4Fzj5uH/oungzUB9CUAYPpk6rxy2qmTkQSikobaLwbqa8pMWogEcXHX/e4YSePuxTNOsrhn/iknXQRs0gYyqSLjTL3sjRvlqhYPBxlPfPzDrg+S7n2DT8nW8V923+ly5wFnc4jdIR/U0Kik+di5Ht162aVkxAyCtbK1Yw1MfW1tXZgdB5YVBGo+cNT6ZhLAvltrlW4imaT/1fl9TjJpkkomSSggvLuLEb85fnv+x6SRbG2/WH+/3KSM4bJ5fQfxJY9khSlHBPAOYsvmVNflOjSx/jMKcsnTvFPvNdxfSDOJuRjSxiCzTWcTR1cpuP7+N1tI1K3RE1bX1WSgSmpJHKtcsGqbr6U0vEUNWWMYZ2Fu2klfeJi2qPErsLQ468LVVPJjRfKY0u+x2UHCUU3H3/afKwq50/gVaSzHNn24r6pFPbEhi9GWrdFhfIq1d17casvHd4akGAkAAfIJMURg3s7uHol17ZBM/1FJTv2ds6nEAD6tdlQ8ANIqiQNIoprCvgnJFgTIrZgUZcVygNi6kRUmrr9TwABqUAMKxtOkbpdmV+Tv5xfyoM3qo7bTC0EYGhsD6aOBOWtvdba18hNdbXnVNGX0o80IUkT9+8z8ihzKqa7Pje+Qkf5gTrThY+3pe3Nxl4YtWZZrcwdd6B3OcSpzQHqTgbSSYzs/2mP3mF2ZEsLOJNdn8hKyvLTyY9doFkGanzoz70AsQNZsEG0L+GNeBgJpY5/2+QmXqxpJI2VQQkNLsU8Yn9nkqHQt33LfM0HA91z6vHRefNo53KAWx37U2RJrH/gTZLx94Ya+uCel45Gvkbax35CMShAJiRNbnXbn3x3fyFnOPh+kgWiZkDqyJuHrgGOkkNTZmsHT9gGDSBjhw9rhiAT4bEvPOCkl/Qm+Dn/ajU3v03LaZ2V8sl8DiN+Q1c6HnCQwWIWN/yYptBKTOJrUEPBo0ki2Vm/tbRtVR1t+y0a8EP7Z+V9135edm9XZ1v0O9fdoJij8Hqv6HRqjBm412qMc2/qw04b09g/pi+mCTN68qg48y+4+06xn8WaE+olapnh2VcOIten1pzfrKqgFHKtYrFqaclOtFTjOTN2QvsEtVX+ptczzhdgHx5junj7nnFHJ+cdPaNgGjfXYDACZB4yM8TyhtKqqyRhTaQxH/8FV7KFVammIXclYgMpEz27J7PkuVYOlVHqjzhuaTQLJhgsBknu+AUKQ6jtAqVsAJvtOQqmVWh0QYCoHMB1IIrtCWtWstMFzulNFOTnNAA9JAwtIhyD/wfkz5y86YBYwLv/fAOFhlbgBJDkmQPiMzpX9dpVCEsORfQKFm+r6BzUzDM4wU9puGNW01huxC2g8s5oRoN+RwQU5e22HDPcF4JF1sfZse9vnFQynZWffqqxoH0CLgUaADUA5O3BY0m1DLu4jsR85Z7KgOACk7W0N1j6rDjnj0RLXWFadpxIbtmWWCYatnoaOGwDHK13HJDs0Kh26HnPb73cZZJhzz2oAtO08bTuUmRA+qKv1NFTV/ZQsaD/aO6mlfk1IOC8tBHEiie84qraWenXo96xS8z0z0jn7RQfk+P6h9v6RABzrISDaQCTnyfqUItbE1iPczlTWVg8vRmSNIevLPLAX3d17yV2vSD4BlJ1daVnqe4VTTZsk8doVkVvqZ7l1W+mXNAOQtmU8eHDsg07U3lFSR9ob/c3ND8iFiZMB0FfLCiwywuvCb42wp6iqIUAjNnfVghgbsxFbTfAqLz3wrY4V9xMX/7Zv0EkeiQGJ6VgzwOPSwqyedzBeI86jEh6sf2p1XpIdvZU0L2jTco4pWI7GHxCKZH6xUF1X6SjN9uKqdB7P13aNWN/Uh9/vlid26onIOHRRa4dkI/uAxq5QSr7pLVFNnhdlxHBcWtUs1ar+udNEZo/43CmnCoyaCzAR8GGgkQPb55HtoID+yyqQmFjfJZnevbIz+w8KRAlpUxoo8JAHTH7kxk35xHMqsfKa+yAtal7hskMKeM4/d9oVE9NRcYrGecTBIABV8CP8zjcOHZKu9Lhrl5+/x8yyxiBpo294Tkgh9+xtK3Cc2ampObtUesz5mCc6W0ALAJKsKJABZ2+4/O7qLz+T34/aySTU+SdR3ObY74Mksvva6byK2cAlamjU1fzOUG1HEW2RDHbkPLCdtDGXq35Ng6JDcU3Dls2qPeb3dUhm/4vz6mPjZ98rWyij6QTxMIdYA78c1bO1RyIrM+fcepVaK8fI+0f/KOcZ44vKOzN5TjIPvVVB5UP5nqY+BgQS2FyvFNm9N+721ayvwHQk36nIDgDS8oob36imP/LRV+eLuUZGOu7XoPSA8Q0CJPLbCaca9GM8brTevL1wVhnmeev6JTWb2S5Tt57T+SZkeOtuBZDlzZwqnXWzQ/1EzQMb9K6OpKxnqrNvhFcLOEataAPL6gGOl88/5ey6GjidFitvBZqRTD799OOSfeoJb5SN3eczSNw4y409wjysZ+tLYWiSjlIPqY0RK9vDMzY+H+QlL5cmzj2M+xXo6/N2ect3upiVBA+emU7J3sv/znnuAjB5APofkCYSCwfKAtgpb34yAE3wgix8DvsW6NsHcJRHkfVna2pZ9unL9h2aUtC10WO8qftSe2Rbz3N5VjjF5Kbkyp5RKeIRl6M736Rg529nDsjX9o9JlxoBjnYOOqDoNzDgAni8Mr9f9vRdjARFSBuzX9pQ7/o8bD+rkttM27AdVrRd0/dyYjgCFp0EUUEhxD4BwIuF5zEVuIvxqDEcV3T+eFrjOAOtKyDvOJqW9gcTMjb0Eo1NebHoubsOuX9Imi2mo1/OPmsFATLn5gKJ9GBszJUBIi28EQXFQKXxiKqnDt6p4+90PO2f/Y7smK39pgxQAiKRJAIuSwFK2vt9wzz/+OnfF+wFixFAEsqo1B5v6lpDcBXjX2/5gS0PyE+/4r15NuHA38RXns1pA/sGRhsyf4QYO/YcbQiv/MTL7KTXFvQ+oFqatu4yLW+vbgHH29ekoSWzC2uypCkHa6EWcKxl1Srv01rfyteqlpZptXNLdFYHAkqNYw+4Bx4MHuyl2m5GnZNiXv5EYIOmYAMAiTQHg3+3h9pbS5jtH9yakj+bCGwCmZsBRNfFO6YOotzaBCWF/wnLs5zcIuOzqof0aIc67vzI1kBix9hdmhFiWb2wmQPHjpQx/J9VgHNfZ2AQyPEzK8HxOZXEHVYAZVt/Hkgdn7122LF5eF/h2IAWk0RemtknvT0xGWm7mAdAq++/KPKcGs+VoUyyPx/XMaqpLx2MqqfMpI8GDik7Fw9C87Cf046y69qKBgJPnzmpR4FjDvVr6qzQ+w2ck7Y/2iMzww+7foTNEfV+xpHFgbjcvmNWwb9wzEaAJlLbMMEbcGhg0KSW1i4s4bRy2qeO/5wCyA2po9XZ1pccUgYQtDKO+a1BZMoxtbTtG2gMWhT+p9//8clv13VSr3idR1g9ba2pW1laVRtzYrmWV+9bv83a+lJHwuSQHcsPi0dYMUyd5mcmXPgeAGSthMr4jgT+Vk/8RX1prMTGP3xu1csowxxax01ZAcTjdzq2VVNO7C5h2lrf5n4RrG8b9n8NHIYH1t0CGjmt1M5HVVX6SfdwN3vGDvVmxvnEJ2BkHCM6jwBqPoWPra6YJBLP7Gz2igOXvvoa0OhY80/Rog8aHXgEBfKnn6H0HjmzckXu6wgko4BI5gFopP5ITvJmc2FLHmsDjD6wOXl1rys3Kdi+/fpo0RiHAATKVs7OyXRqrwzLWZ9d5H4sraFPcgHBoxoQGLwceDRgOHjzdAAMlVGbOsWm9z7gTEoAg/C4/lzGZaJJa0YZJI0GOG8M3CeDq/8kia0qEdM1ial9G97T0ITaFnZcPytdmr4QgHwoccGVF/t3fnKvemVfygNo+rF25l092n4xsqutpduqqhuyMneA+tsDrfCEAkD5tM4tCM9jqmVXmftnkQ18EGhlNNko1wshR9Rnxj4kpC2/Ov+ADM19zHmOE+CddUNyenlxQb6uZ+Pl4FIqIVeWki64uQ8kkZTr7UGzlWgKSJ23X2fjscWZLVGl44bfv9b9MzeelGNbAnOi5aVFdbwrBIbYYRL1gQgPUzevqCPrjKqyd6hZzoaNbqVjLy/NakaazTXncfaNmm2qvb22cVvAsdJvt8Z2eLu16O5bAbKYkAKvRc1ZgbQGte5Sz96cuVhTBjH128ZDrinDlGS6tus1LhSKSYwMTPmdcKxxeG3jGexX5/fDtwpsGF12DW3h18GL40M9QX5fs3kMt8kzZkdtM7Mamues2i4e3nndVW3pvibqeufmtpLYK53py/kuJPVQLVZJMhADUDm++7w8cWmvbi8H4EZBI5QYOayxdC5I7G+nZHgiGLckU62MaX70RpEFAocfqQrlou4otl/Zc796VZ+SfVQoATQBP4T9IXD46JWnpeNrg7rpzj0ytHRZ1i6sSMfBzgBA9iZcaJxDI5cdCFzpPCi962NBh9B/2uhZuVKuj8n1A7Kt86KMuskoEE3tl/7MBX2Il1nwEF8OndRTbRvZ2vchgEz97PnqR53k0FctGwuTKF69nNGXsXhewshvid8VBFCMzz8hw/N/4PhbX7a7lj+u842pSj6XFUi9XLgOdivo71Zv7870lXxweekJHLk+tZiVL613qbkHL1JqE5uzswhLJX0QCWjEaQ27wjtBACzuZcXsGSnfuvOgxn1ccOprvudq7R/XNS4s4X82kzATUNWIfg+1jVr9lVrbOC/YXnjB1UJcrG3qPdmi5qxAWp8oBD5tUXNWgIcCWZOaSTzY7iRo5NyQOvqUf3j7hRXuG7i07TW9uV9L3+5YZwDx/OKqy2HNMZ99GrfxqfQOPSgckMPzmgLSIcQt4+6Bbi0MhJI9BrJjQCOqa7ytixEgiA8qVM4bSaSdP1viDT51SbPCnFP9ZUhFfbHjsPCBLuW2xcaJKjepY1SdX8ZPHBtGpIs4vQAOIWJEsk+MR5xprBwJZY863FzecUASW4I4msOrSHbV9rFz0Z0v5wwBeAifg3dz58oFDfquaFuJXN3FiHUZaRsrqEaSGQUasRnlU44AjZBJva09phT8PqJ+I1YOaITsmH1+VwcSH3ZxIYldieQYwv7SvnPDcajtKee8cAzqSp9zoJHrqH9gA5VcWnmNvErTSD7WvyIvGToo2+Jr6pwUqLNN4ugG0X9tK/dpakP11leACRFI/07R+tqSeqqXl8rhAAiA7NIoHc9deVZQbwM6KyFiRG62A2FSTVriiOBrpBZwrHHhKum2qLaNKY3jWAtlNLiYvZHV0r/Vp/QKZFSqYWEgSrds1dayAgRxthA1tfSvpQ9SFJOW1NK/1j6kfGsm8RAOf3arNBKwSDn2jtDFlTV5MB5I9cwj/KyG5AFIHlRQyWP4sKpjOxUkdowccH3pZ7zZN55/MpWRo6gRR67JWX2AU87HyIEU1KQKGIrR/sHL8uLhT0lmbCnfxFjsXz0nfKB9uv2rUQ3GPaq6yybQoDq+rJ86KfPbgiDiNgTgB6/rHfOBU41JHanv7dF1y5Gd+/JZTdSshHoaAMW5z85mnIqW8m5VQUM7uy+6rQFMd+D/03UzMiBmx/4WMMmHNIV+sG+/jb+P1Bt+2FBCYcevYr8P/zeD41j3lx51fQ2Q2ndsLwgcA5rZ8qEcYt+un/bhA7I6OebKub72dnzS7XeOHpDXJE/LD6sZ7pv715y3NaF6hpLHZDD3We98RnYOPpBXbyeXjuUl747JJv5zoK4KaSC2jgQQj6koD7tFHGlKEeBybXWpqESzVN966hIqIa4VmzBuCzjWs/pF+rr81NPLMqeOMZkapS4tYFNkcRtUjGcsuZBb1JwV4CGyirvrJhJSE6QlRuGsNFbe6C1OCM0Gj+E5XyWOpJ4qOamxd9yt17I9tClXOOgQ4WF1PnBaUluWHABcnRjTe5Paw+nHgBFb11PbfsdwXE4vp+WY2j2ua2YJHGkCvqpa7X11ABzMOSToVvS/r4pkGk8celNYKCovm/iIJCY2wBpOLUgB7RPFvJzUEQkjHwAhntWW2zrMy88YY0KiPccv6/mqTd/W/a75hf7XStfuNgeOsFc06uoMFpbrHQJQG9izNgYO85LInASPevpZX2sf3pLbGsleUSDqdYCX2VCG2/P7MEcXr0v+N1NNrvdic7ZrZG1qrOCFhHI+Vk6cyvu7E/LtHf8kh7YfV/vXMy5cz62l03kwuaVbzQZU+nhsx4tk7dZ9ei1kBY/nzSQyU7WrY0w1ZPaP23YdcpmtxtVjmhSGUVSpRDOqbz1lBDaP68tnrdQy8qp15SL6ARgXltZr9qI2lthLLGJsq7GiWtScFUir6m6z7UqacyZ3J9c2tf1ZVKNyDODvFG2mI42Bx84z79600+VBbGkKUWtjMmYSvfMK2l1mGG2jwYLknAIopI2ooAGIZxUMjqXjauMXSBa1mSMHIumhzOMTmoFn9033gD+1qAHSFYD95dQe+ZrsE7KiCAsbN+i05mU+oin2ioEJ18j7dzz7FYdlrYg5P712UE60B5IrVNg7r592gI82gEfUyTvmTzuga8GxqcuoNDSszZ/fdkz6bhAzMJhf+P3F1Kz0D5OptndmNWSTrlXi1kW3pofmP+HWDfDi07bOSyoNVDs/tVdEKjg1nxFsGomneGl+vwtNRHvGRBKpiZQcAMrkgKbPi334jy8dyPcjNibrSrnZ0Yb7RB3bdzGhUngAo5G/b2VsAY2pL/+irOW+U7+u3v3PrGxwcC8n+s9p1DQw/eW0QpDVJ/Q46dYIm7vJVb57PWcNpXRgz3HZsyMuX7nxjOZwf0CePa0mXIV+KhvMm7C3qhljhturD1fDVLB/HN2+r8D+cXB0u/5uuvIzrVaime9Yxw5ZanrUGWc9W7vcsBWOp44vwO+6vJqSeQWN4RuL36bcPp6oc9M3nCQMj60WNW8FCLgKcPRDLDRvtBce50bEcGzkqqGmqyScSL1jFpPaEPz7kzem8+zdA1SPAH+1EP2j+r59pwbjyxEQ55TaKT6gkh3aWx/6WegdK+P4xM5DTiJk/Q2FXp/fLtv7ngOBSkf/bhlVB4i4uhpnMzj9qNrSeWEH4YiwW8MmbXxhn+wdvKiOBTFZvD4oyaWj0vbxDzrWnDJzg+z0OX5aU/s9+I9/78oWs6Oy8spXS+eFMXXcyMpWl8lFZKztmFzueUi+fvJjDmg420QNpeNLH9mvh7LqNND1Og1h5C1wPlbnoW3OmQUPYmw4d/ddcsAO6R5gDYkj58S8kPzdWNkvs3MZBY1j0qsONUbWHo/rwHnGagq3vkc2vIvFhyzstXG09NUf2jiI2Dv1dEYe3Pe0hF94sK1EcmpSy8ze10pcQ09ZAHJnqqD8ALN+2+mlefmD+WX1NM/KoZx3PtcYZMsZPqaOF5sPLW4AKsp8wt6xTUFt8Hwle9HGWvrtGrX/yuNvlNcce6ML/L1jT2CLWy9v4kFO3xqX3n5SpG5zpmgTz13S7HAjm2rjmF5fcvngJVF8vcuda+2QsxznJtZ/+fEz8n//7v9o4giVs0bKODGzIjPza3WBRi6qKc2JyQXVAo2Vr3+tLVdXVjbdrqTWud6L/VIatuVOpg4Lr5mpsU3iApBsBpnksRxvHqJ89nd2uk+59tXWu2e1AjgDjaZqZkwe3Ba/0R7mHKNGpM4+ICD47Oh/Tp7VeG9IKztXJxUQaey9kfvVWURVtxp+CGscgNWFyZ36nStikpTs6j2vtltqRxzXGIXPnJHZL/y1A1TK0hFb26eA/RM50MgxquXZv78gNzS9HU4ngDlo/9opeenwkzL78jeqCj3tUvFd6TvhwrakzmjuaR2e9J2rmlfet+FaVQkroV0gJJD0NZ54Xi8qaJ7detAFDLdIGME6aF7ujj3aa2O2OLMAEgGNRhwDsgBSi20HpW3r4QBQqX/jwZFLTjoLiLQQPCYRNNAI+Ioi6q0tvBkbySZ8GA97RvbpzzFe/mz5QPNPB2CdfbNl5Nq363/v0FMSe/JdVDvQu7AQrBGgEWJsPthLum2u3Ek/BwNAVdBWweIrVbPrpNu5JbNr3TEs8o/2j2o+9DABFPkAGiEkkc0GjTYHNH9d3Y3zdkZI4ds/zk7fVCegBT232iSaNs9qt51q77xWo++FjXVPqao//ukvyJ/o5x8VOL786/+ZnUN+S/0H/uAzsrCwJN/0Df9M3vyvXyk7t2/J1zdyh5vKIukEVcpYD/lSxq07D9TDqtW3ihUgHE9C06e1qPErkI/hmAu30fgR6ucIgORBis2Xgcn6uQYcDDyGpThR/C/qCwxEnmlwjR1HtbUy7j2lKJwZhgc3sRp9cjhMyw04Wh3Hxp+t1RvQJN8zNDOjTiGa1hCPW14QCMVyNHlBwQcqx6BNsi0wwMdRasv0JQWhytCbe8BbJZI7d0nP+DWbQn7rwufoEWBQXQWVr+ZcVqeJIQWiwxdUFd2WEHWalv2Pf1R1rQmXbzqt0saEOrwAaH3q0Mw4RoFN40Y96um28fOuemaPel/LgvRIcIzUEa9qwOSN2DYZ7T2gebmPS2bqpKawPCdXEq+Vfek/dX1jMc10rOq/nvULkp7UOauD45cvHpOX7b/gAOWW7JgsLWbkS20/K11r/yjHuv/C9QOQecviwOCN1f15YGrSPgAUEse+TMCPvNsAqtHERUn1HdZsRhkZVYAnufWH+dCwAlo3SmD/a4CRa779zGOyFY9sBYNkSErod9nRu7FOuW5FNwnSK3pjFW0YrvCuK7/KwKMvebRryW/H/maE6CFMDoG/G0lm/0j8R7SL0LqqjmuJ/1jrvEg1mKwhW4w/XuVXid/rDu2//OsfcWDw6KG9smN7oaEDUshfePf/I6/4hkfkp/7td8tffuEr8t7f3HjbauSUUUvfmlmuGzS2pIyN/Faq45XVp/TdJBGrbvZ3d+sgRubGg/luna0fzocHKs40jSIDj5Xyu6AOLmPLBPXeAG6V9vXbhUGjX2f7ADaL0XhSbRfDY7r6APtZl9u2TuqmoAPQQyy/rOZeRhLmJFHaGiCZUVU2vzEATurgfXK544gC0UC9zXZMJXOsOKARYGae4GxJ98cLSNoZMKI2Zp5Z2aIq63FNL4jKGsmhU1V7szMNJuXYRVZLhOPpGr+QA3Ib1wN2ldvlpsRmLziVbefymAYMT8ih+J+5NUCFmx044nKXI4FjHbq6kvKNL3p2Y01UqHhj9YC8OPke9Vj/cwUM3IOCGdq6cYSKG4901hUyaR9tWHe/LesP4QFNnamQXWHEP3tJSp58LB9mx/rDyySfto1gkS/inGumIteXgcftyWiBTKCqrnnUqjo2M0wO9o+YShHqh/SFN8fHijrQVDXpMo35TaU0mH29EVtuA47jz91yauAf+PF3yef++h/LTGNzq/t6u1XS+IiTKO7aVihJ/OAfflq+6kXH5H/7vu90bf7Tz/2Qzv8rMq/Sx0YRamlSCNarlubLw8YOz16kjMWCizZq3i0+hStg8bXq/fEUcm0d2QogP8Eh414iHqiNdqYx8Ig0pxLyARtgripKaIaTrkFfo1q2O+Md70k4qSLhefwx2aceIrRKKRqKXXRSRjx/8RwGgFy5knJb9ttU2pe88IwLuwMfTm1q9IjsX1fP2xzj2a1HHbgEUM7ofjKZzD3c9GrSyfCb5b65rvFtd84/KbuX1HklBrhIKchMaTrBwwomN2zRAJBILC1GYxhg5oaN3KDCjus8mEuYOB/AC8AKoGwEWLTwNVbGltiGRvQ11fP40n4VBx5xzj7Uo1oGPM9oWHAj1pU+RqbmtmPqfLU05T6otHbh7ej4Yy6EDudhKm1rw3m4sgOvs6KiW1NRF20QVVHmusbWEdvIH+pNSxR4zFkbbIq6el1TTjbz2YxEs6u338V/7NFUnpM3rlQV/zFqecuVZTOaLUZjTtZLBcARVe/rf/Ax+finviD9CtKuXS8dg6jewWvtP35jQnbu2PiBweeZs5fl5S99JM9y1/YRtw8QbgThLX1zarluj+mWlLER30Z9PMgzSpytFjVnBVQ4ow/EMk+I5gzdMK6osc0mrB6mgMe1Y++UzN7vUrUeitXyBF6JwCwFHfP1OcCY6BrRsJm1q9WIuZfnqSOxD3g8tZTesH1UiVkxAsTwwe4P4GG2e2FgQn+g0PDE2TxopAwHmLaxZ9mVwVtnFSCSik69bjsfdA/vWEy99HdprmhNRcjDHGAZy4nrYhqTbt/qKdk2f0rtIVdlWeNZrulLOZ/di0/ruQS2lgClcgASkFqOAGdxzYjjclZHNOZFwc7bgJ8dW3MkiuPX0k4ySx3t/mni26U3fcsBSGtn9pYcI1GEcJgxsnXnGD5hcGntbIvzlgFczoP+4blRhpTT7B2tbyO2bnW5ACKIpT+kY9t1uC+pYuMQma0jxc0MzYPncUdH7c4joWlHHpLK0AJ/Y/+4fY9K5PW5RPxH7B9NwBHZucZC7BtXiO1aJ+WBI5K59/zmB+R1r/oG+bOPvk/+yzt/XN78Xa+sk33juxsQ3Ompqpk7YLKvb8PI9NpzamSihJSyHkItfVNjMjbCltFFk9c7V0vKWM83Un/fVlae+tewFAckjmsqBbqXCTW2HxPSbMNqPadjO75GnRhHJNG7XWJqDM+nUiBZMKYCRfI40x9e9QJG420Pa6SLhp0oM+ca106P+zS3bRhoGA+2gA7IVJ127ApL/CMIuBEcsEMEFx5YV1tGJSSIfbkQPajAMxmtPHJCaxRAKqiMx9ul4/iLVOLW4TJCzYzer8BUpYMKdj/X9zqnnktniKu7mleDAyx5iUypLt0AYyBtzD8W3dhR/wBf/rmxJrYufp2VRfFw4FpV/PCh3b6h064Z0k6Okd6yv9Sx25Xb1kA5hbSzMeBj4NLqpqeyzhHGXoTi8087Xv4/N36EVBwv8HJA1OfD/lBXX7ioomOuOa43M6GgE042pWjs1qmmgUfntNJE4AgoxKTHl2ia/eMOBZCEiyMDzfJiY734UgqIY/HKXmBLrX3c1NFffvy0vmEsy1e/6H6n3v1SznP5g+ps0kh1b6nJVFL3zLnLrpnv9DK/sOjK7ju88SZ2PSdp7OutzSuqUWppJoaUEUNYEqUTWb5Fd3YFUHklW+kGm/YltLWpz53/BGjaSJvLuB4J5LEtD+cfcvH2fuFjQBIVs4HJYlsHEhUoxruGNed0l+sfdfZ+zLyo+nJlFqCZB7mpqN0DXR/q3fqbAWTwsfRzUfyoJ/6ggceoNqXKMp7klFSBZq9o9otsr/ao/eKzQdgdjt0HxxjdBzCOTJ2T7JGHVEKZlINr5xVA6sPyyIsdwMwANhWV4rQTSHUycq17jzyT3a1jpRRE4sVtNpfRM+XcAFU+aMMmMcrGkDYOnOk2TKh7LWWfD/poj/QWdfjSYtKN074UOOkYD6SRtOMDyLS5WD2pEPv7AyBvZdnpU7e1o86kkGGzCua03HnAut+2DbenQZdKhIsSANGr5DqDuMai6J93Bs5jVmdpCO0Y8NgMes3R16v9YX1Cp1LzIvB3l8ZSjCIA5PCW3TKybbfLPNMo+8cArKYLwGrU+JWUJd/7Gx90NoFfpYBx57ZR+YnHfu22fl9+4rSTQN5WsckFSBsBsb29XZGSxDkFvkZnzl0SnGhqkTg+99xNWVCVR1yReZu+dfBF1mIPB0BZ0JRDCf0hcSG06O5YgYw+ifhOW9ScFcioQ0M88fzyWMcG0n8I40ize291HtmvO/Fm+bXPvvW2RUfFXKmaGUATZXtnTC+luK5vV/FZfaVbHuSmvubhznGX97Ll0swpYHlWg38TbgYCwBi5fT0GzMS/caukvzRjVQVby1PtSxwVRbs2gEBRMMjZmIc1GWWQPO5eDNIE0hBgSVvbun5ajne1aLmTWmp4H3HHzDEmf7f19XJo9UmXbpB+u5evyuSIpoq7GXe2kifkLKyVAJDBXqZDvcc1gjfrj7PMUOy8rHQdlNmljAwnL+vxRUXbhdJKWxPWYXL9gIwM3m4LiR1kivSNnhTTQKDj6WKfBGsLQLTYkWS5mUuMSn/2lnOm8SEZ/QF9a8kHc1EDFGBe+6DEVMJpV4fNLTi74D9zsLGtvk1D5aQWCdqt36V+p1ZOj7QGOk+GznlIQ9gsawKLoqSnglf/OeV3RHmXIqSOX/Sw42bctlGBLy8tyODIzlJTq6tuZXlJPeJLi1SD/Ne9LoA49o+dCjQJ1+dLKauZRGpdA3+rM45GpqqbEj2jR96G2vehBw7LyzWEDRI6QOQPf9//Iu/42f/VDfCHH/+cczqpe7Q6GCAZ/dGffq985rNf1DfZlDyjwLBD9RkH9u50c3Z2maqqZu4AzHe+73flO77tZe640mHXNbbR5OyKpLJqMK5vpHj0rWvk+CWVGK5oyqDFuSkXd2ltbUXr1vTi5ycYeA6Gx0DKSLqi3v4RfbOoTXwf5tk6bswKoIaIqUSss4ocpI0Z+YXBJbU6L3EN91AK4NzrK7Fla0xtoKo7i9Ge7XLq5uMys1S73XUgIeMBntB7kNrs5SwCLJvKQiYhuxLrMuyBuOpmudHapEA4zqSXZ2SnBi4O00DnBkDArNXmAfhgn48zd9W4iTLuIYAco8H0lPCByBjD/npMJbIe/mIfcMe2c3HCba2ecqSPg6mg3NqxvdIdlOeGchvKL6u39cMLn5e+tcCGH16qtZbH+18hu9QGcCgzJ8kt2rArmD/3eK7lmZ7D0tOHeltL9LxAlIm1KUmkpjSEDp7fQaxIwH1GkdGaxr5M9e2TxPqsk272Jmckszzl1sPWiUmxn1qYVPC7AaJs7fy5sz/YOStj0/ukv2MmkDZqMHYkp0gmu2LKPzd2MhEs4D+l/qNwra6uimy9/m7nmNSuzkr++OExbGyTnibX4auhf7Qf28zAIYmvbQSzD/NqUynvCl7xLJRPOQDOJM5XABqtqz6R5VrKoefIeROapxbBjvEPb796/zfJbjUPGBgqdMANt6vneE5tGHsHhvU7LyGdzQ2Q1HSiPf1DzsRiemLcScTbVaBV7f01oba+62qWEa9gzHLnFvv+H/vF7HV1gsGuMYqQQD5z9lLR+qg+zSxD4ohqGpU1qmlTWQMsf/7dvy39PT0yt7io0tMt8t9/7a0VSRyrTRWYUvsDbBCQKOIZzT5SrKTmV3M2M9yFlEgvFNcfUa1vCM1cxxcy7+tXzqkEeHveMPmFvBaNPneATSw1r0KjjQwmjR7jbuOH/SNZaXybyGJz/OOnf18+c/IjxarLlnPP4YGRSAQPUjoMdxxzMSAtVRveqHilNpJQP27tGdKbWiAZC/NGZWnqTqsDPJJdBUeQ1Ni8pD827jyn8bAuRqips4k+BxRNcui3BfhFldPGpJHUWzu2ULE+hPXZq97XVo9zDXaSycMr0vFgvODhHNOsMSaNgychh5C8UuZAvB53rqj0UAUQgFEklWndZ0umHb43PovJHS4UC315gdUioKlTWTtJLsxDxBionk2dzbEv+aO5zY01HxxccpLIlZd82HFKjn/IhRGyPsaPDDh+me37w6OWN5V6eH6o2cNl9F1W7/fxkNSRdYA432qoXFaZRsd0fN9rPqwSx7mmagmvaf7qXfvU3KJKAl8AOpcWZmVgZFtVmc/aYquyqC8zfsrDKofPN4/9yaf+Kkv8w7erdBHHGOIhYu84p+CMWIjQf/nFH1OQti/f6W7dAVQy916Vmn61huaphBqRKtDGmVe1NDf2nr5BzZ+qb6ZZRfjqcg+5TBp6d0JFiuqat4gENkMahLqRb0s2l9Y2egUIg5TQtW9l54len3pL8Ubs0pfodKy5Hon1zrOZ/QGSFi8vapwf+eiro4orKkuhKtX7SFT2DFRs09MZmUmdcVk4iInXKNqp4UK6cgHzDaBEgYxVBRIdCoh8MpCz9DtjmvtZX7g1pmMx8JhJ9jvnH7+/gUDKsHnEttGAnt/O37c+bOd33C/EZ4QIz2Nqbmtj/ZAUcv9uyyVY73rdulxc3in7Oq9pmsMTsn/HhqQYlTGA2LbGw7acM8DSD8czF1Op4Op5vf/wPMil0FO9YUyBLt8UCqz1nl0aHPx6INHU0mJhgfxUhMW+D7LITPU+6q7Ftr97owOzCUW0Nmf7Xvw5A059MOnX2b5970gkS4X/Oa/xCX2qFTjC47cXEvJcKpDOWfpBn3ejwCO/oR96+CfdM7pZ/gjcI2cmnnNOsv45VLNPVpvZqZvaJSYDw1vLBhDnhT67PieJDg3Z1QByuaq//Q0/6VghdUTNS0geJHZf9eJjTc2+0oD518wCKSNqad4U6yVuNji/VJL7OPDiU4mlAstAchl49pnEkrkQrT6udxPsK1vSynq/nY3+vKnxbbdA48aaNHpvdXlOurs61I6qSj1uoydyh/mZF3YUgKxH6khQ4jaViJVSU/Fg3Z5ck38zXP+9jWX0QaMtK6pRZ39nBd4WQMIcCGTtk0kdrYxYjoTlMcrqPS/TNmyHt20BehCq5r171bmlypzUJpGEhwFPygCV8OZF/0LioNwXu0QTSRxelfYHgnNIb1MJul7XEE4whOIxAOUDt7Dk1a+jL/XYBaKWNj48gzgGuK6upNWEJu72EVVSxsd934ou4zid6TaQXqq0Unmyzzi+RJKxVo79rILXhxS8PulyUQMYd/VepMqNx9Y8uNm/NLPPhVEiNeJgPMhOQ7lPgFFyVvvnbvt+O/anl+dlSm35zipIPkzGIb0ca/WZ86WOUcCR8RoBHv+vN/ypC8aNtrARkjnmFSYETGnFDIMjO8JVVR8DICdvXBVU14OjO4viBZctRlXVkuypeoyoDg44Er/RlzpGNXy+lAEYSRW4qDYpjSDACACwHqNVfx7wAlyuqx2lqcGJ7ZQm9y+SBpWW4RGMYW1LDe6vXOl9+55aTkql16ne2rWVeQ2loiIV9fxtUbACgMirl7MFAcZrlTquaYrCtk4Fjg4ylF7hn+9fqflBbZxRUUfZNlo9asyww4TVOdAUUm2vvv+iyHNqcJcjnGNwjCkHGq29bZEc7pg/o97Qx/Ihe6yukq2BUF8aSXge1nW870HnjDM5fEx2vVRzOQPUVE3tE8B5aioj+wYvuWIfPJlql/On3EBdWJIXltjZWoYllQyA6hu192xsvwOtThWesyGkfDK9R7Z1jucAZUwll/tk7f5f1H4J6Xz2FyLNCJgb5zEgY/oMy8j44oHArEDnfXZNY0qun5IdPRfzINGdqP6L+l6dd7WmLPTXgfbnJm7kr0EcYmoFjvDypY4cN5p+7BXvEqIf1KpGrnQ+aL26uvulq0c97hpExH1cUB+MXrVDRlJ6mxYzm4vdmHM8q3dYBxxhQgzHZuZ2rneijejfSLU0Usapm1fVaHWwKjuDes8DYIn6m7djA5YmrQRwOkCpAJNtSw0erHYQDmlStu06ePsPqt4vpNW/cAXSyxr6RCUodeZCLWT6/Ds6c+uJSA/rUmeK5Gl9TaVgFebPJZRJuVh4pcYrBxr9vg5MaEEYONDGl06uffaGZCM8rNfjqqKOdeQlgWE1sj+Wv28A0MpMkmjHlW4DIPqUzh/HERyPkMop0DmgQP2bhyXZW9oDlvNHYkcfvJ4hA41m58k6dK8XSvIcWNRg4r59KLyQRhaT6MLb1hubU1FPab00nGRSBg7KhfMrsuXwQTk1/+1OCPG1GfXkV/DrSyspMDU4vJgrzqHXFvY78IiTDfXMmdzb4ZcDbBtRw9PPzBNsTv41YFJH5lePxJFz/oxafX1xpfT3QLta6JXH3yj/8sHvUcfb+tXI5cYHmO7Yc7ThzyKzf1yYm5ahLTsKcElmbU4yChqTbY1ZP2fjiG1jMygI7ZOVPnVYwZGFAN2kBTSHlmaMGcWTB9nc4ppGTNe7QQPIpFeNkjI2YEqOBReOk1YqsDQ1OBVR9pX1hBlq1Hw3gw83gskb11qgcTMWW8dIyKrL3tHR1bi36U2a+qYNQzzIgQGVbK1WBx7d71u9IpPtQbiaSib8aM+y1GrrGKWiLjWmAZCoNtQRzgUni9VfLnSOMbtGfAq9iD/O05m81BaKJ4qvlYX7Wnk1W/JjYxpEgHEAIOBx7t/9kuxqf2+B1BCePjjyxzDwRJlJDq0tquLe3rhKDAvB4/JyRl/0C8PcECMyLKH0xym1j/TvfM87nLMW0u6Rk290zXHQWes6oPm21c5Sz89Xgweqb5W3OvGqwkoVDU5nRuWZ5x6Sr9v1OfUaD+YII87Hvmu2vlkCUtTY4OECh5lxlYQt8QUpwb5WMuBYTFUNX2wUq43tSJ+ffsV73bQQMiCYaYQaOeo8sTUkM0wtjjFR/KLKAqHWFa3asH+MpRfU7ry7YWA18eEP/M7bogZvRNmv/9ePyejIoAubc/HKuPzNF59yGSUImbNZRKrA6bnVjTe0OgbmC5l47rJ0aJyqAY2ndLfFAuTHzpywgero7Na4T33u092rhu0qFm/XsiCMRxBmaEU9x5YWZ2VxflpDRyy7UENpjWaP/SXhiO6286v2qwu+ryuyZQeSgA0v1Gr5tNpXvgLxrNruajirSsJMVM71+dUS0EgoH8LzHN72oPztuT/X31r5J6oLxYPkSH/jldJT6201heepFjQyHzsHQAYqSTu2Ouz4HLDyQvOgos4mg3BlgJmV1cCeD1Usx4TZAcA5VW1uG3XuDuip40x24lZBW+sb1ccvQyLGvS+p9wnGgrJHHpDut3yfxOb/Sa7e0pzCHRcdaFI5hAuJM9w969pxTnaubO2TWJ927XqS03nv8u54EL6INtYvNnxIT3w6z4Py3uSspHoPaSif6XyoHTdYBf/WDv6w9GvUCIjrLHntj2RWDkpvQqVOy9OykDgsXfE5BelJzY2tIYaSWq5qZKSKqypcYW7ra1gpL8iunvNyanxYr9VFLVfvcT35lDr0zMf3S3u/JrNYnXYvBIQnWlGP3bYtR6RtMfA0Z53g1af2d8uYXuki1wMcz6t1WamwPJzvUM+WqsNd/dJrf5eujhZmJ9XGtM89Q62skduVpXllp/a/DVRTh+fH/aGnb8iZtGH/uDA/I0NDQyrRLx/6J8yr2HFeVV2sQT3lL/qm79XA4T/mAozXw6eWvo1USzP+3SplrGVtivWJsq9Ew2CPtHvJvhLQeOv6JY2+v6tpRs7F1vGFXJ5dm3VA4DYbmxfyopQ5d9TW//nTP+ekTqWack0jEarlJagayWM1KuqS81UAZNI2v51zEPnNz0r2RirSGQawBwEGixFtADu+hJK2lIf7UeYyzWh9MekloJysMeZR7cb90KfdxpxL3IH+c+A3d8D5+baK5rFsbf0664fq2oJ4Wzurg5+ptF1cR6eKPu+aRa2l9betOcTYMdvuLz3qH1a0z3zs3FjjIMRQTG6u7NIMcxoO7/pxmU7fJ//yyH+VxPA+6Vi5pqBSQao6wbgQQzoKxxB81jQawIQ6cizrNVwrmcSx1v5R/cyu0eqapUY2/qQdxvmV3NSbRSsLUzI9dUu6FUxG2j/WMJHE25Rq6Fe2C97ZH/zD/ykjwwMqcWx38RQJ2N1s4o1ofnHd5ZZ2dhV1Dni3SxnrPL2C7rypICnCm4zg2LwVdeuHLR+ccrJ6NyAw+orm0CSQNga5SCuRXAI8Uxq/C4qpJMGpPQpG2JwDHgI3xy8GsRo7GuNFtjkzv7dHYd1jmg84nmw5xlTzTSJ5PLrzQfni2F+4bvHFo5JKENDaXtkCbhkXvJe4fzmRWBWDlJI82n0SaRCSxuEa8w2Hp8P8AU5hwOOCR2uyiaVLQ5JQe6wwIfHjs6YYIwwCrS311GGb2LcaBP+mjnKAIlsj9pFc8oHQmtLXb4cZAGTS3PRb3y3xrYHULtuxzUkdLeg152Uf+gAEu+LBeQx3zzlgibRtNnYgkBzmJJLWhyDe1F+e2ye9bUFwbdYICePE/IB6NI+po8p+cbw0MDiBt+kLmEulAg9sxg0TgDy1603hYmkb/6OCMtTg7dkNCSfHJgm1howHMa/gZYU5qJq9fUFGetfkvu1X5fi2x2UudlgdNmPKb1bbof7WFLvJrRogXF8g1RuGz0rnLg3sOC0DmsJvhWcEiL/w0rZhS259iWOphgRfr+TZEwaN3L8W5iabG/h7ZiIH3kq8FZU6uRrqujo17J8+B/GJmLxxWbUBqvFQ7WM91DSJI5ld3vObH5T5+SUZv3HLzfFX3/kTzsaxngmX6otael4/jSKkjGm9oQRqae9O1KgBnkd8ouwr7WbMaTpQmotf2Wz7SnJ7brbT0vPoq6z5VHjJIshsNhGdg7Vmxi+QjuUcZioJxVNuqUpJHrd2D8hq8lg+yHQ5XtXUAyCRoDmApABn7dg7Xfe1t/6kxM6euk1yaLwBd1AxABnUBv9pa+3YJ+ZjO2kGKyBehkEzSHNTr32TJN/0ltt6tZ95rMCJ5bYGWmDxFa3Ona8CvrTGdCS+pUnyrN62SCp3dF9UFfBBVzQ4FJerV1JOMrnec1Bf0rMFzjJRfJa++kPGrmBbSuIIH5x6orzDC5iUOLDvlrBCFtcREJtQ5xmAJM+BFLaPDnCL3FAhw4q+BOXJA5Fu1zvOt9Edkzha+CK/LrxfKjQPNo2k/8SD2idC2yyqWrdZkTcAps22b/TPx/bTqzMSayMbU1xfPHDqvaIvTZomUx1oOjprE6w0DTjapNkSmPsHfuxdruhj/z24Yfj19e6vqj3GrDq/NCImI3MJFveqBtbcogvbegjW+/3Q39088AhXWxe8wNlGhRmqN34lqgD4tmI1NuJbq47H2uqihrpLvuBjOFa3aoWtw+CRe9pIx/0ynTot6yvqUd1Zv1dkFHj0bRrxkl1azBQAlcJZ1n6EGrbjJcGzwLikf14DLpOTWoFesdiMpeqMT3hLOJ2r41l5uLPQGSfcjmMcY4jEHb/vhCTeEZ1FjXaVgEfaQYAyYisuLGScpzK2n8S2BCT6ntdB643/ALGZjKZ5VGw10jbmAPeagsfE3Pk8MHP8FZyZN3aUito4lgKO1ia8jQKm4TZ2bJ7h2elz0paMq1o6yDRDvQOV8ZzOWtfXMg/hMLOcc5hRbBlQfscKdOuByM8oeP771Q4Fofo9dJQW5BQDjr4jjDeK2yW+ItSswN8A0/mZSRndvs+Nsxn/wDIdCfVbCCVkYC5Tt57Tayshw1t3F43/WGyOmwIcGfyDf/AZee9vfVAe/8vfKzaXqstRSyNlXFppTExG3ggI5A3waJQtQNUn9QLtUMy+MqHfBaCzEvtKkxAPNSCw6gv0a6jrtInh2NXVJelsyxGpnoUMg0d4oX4ja0xCs7c427d6BtC+Bh6xZxxSZz/LCmNsDfTU6tlrfPwtUigkjXiVh9Mz5sGjJzX0+7JfC3ikX1Tgb8p9WltflfgvvE+SJ16cn1/UPOlTDXj0x2BNo6RlSCUB1BZ+B7CVl9xpH1Tho8kxmUgdcAAUngbs2KaO/5wL9O2P5e9XAxzNm5v+FhDc5xW1z4sGIYHyEmWdE8R5QasrapurYY7a2zbUs8x7XWMLhtMSug72T9n4WPLT+jLzt4vqTJWzrUCCSfY1F2bI+njbMHgsBRrpNvHcJenXLCzNDPzNOM0CpvAO0/raknR2tBe9JwOWZzXDD/EfiRJTqW16U4AjEsb3/sYH5af+7Xc720aOf+KxX3Xn9N9+9a3hc6vpeHJqVm7dUhU4uaD14qk3IDYIfFYNSGtB3zWdQKtTVSsAsLT4lVFpHAGXqxocGWeYVvzKqpa2YY1jmSVZT8cbFiusYRO7Rxn5GWZ4CGb1Gk9qOrwo8FHtKfIQ/YlDx2Tg5l+U7MoDHjIQULJxicooiRihYvzMOj54hJWpncNsawGQSO8g48mxBf8GiNz8/h+Vbd/yHUEj77+FTqLIn2st4DGvxvaCopszjb/O7EeBNoudyFyo7+2Jy8CL3qj7J1StnZWv/bpoKVw1wBHePjGXct99eO7WnnJCMCm0VTDW5sL2+PEgAciZuEY9WVqsyGnGVNXMD65ZFRwRASSexDb/9pdVA47FVNP+ebK/GYG/SUe8mVrMRCwlS0tLmtWueHg0np3z6k2Ov0L/4GhFwLZpwPENP/CY2jZOyNFDe52NY7/GcmxEzmukjH6qwHKAgrzQhKApFhDblzK21Jvhn9K9cWwBvgf1bZHrgXRO/BgsMDpn4adxxN6y0jere2MF7vws+R3FUvMSax+485N5ns0AAHn6+lfkws2Tt6mUTJVNfupKiEDHx7Y9VGDfVQsIqmQs2pCiLrWzcq9eA4/0BdwZ0OPYJ8BjJTmr/T7shwEkzjXtj/5raXtwT0UqRB/s1rNugKar8/tdij+bo4E0A2KWkpB6wJgr90Dn4pGflVNXT8ievRv63KuXM/rgjxVIdOsBjoxt80Iayffhp1ukHlpoU0eg9bF826AUZxmVLDqVdFLBYwBsfVW2tVtWp8pyANKAox/HEf7EKSZ8XCKZVM32xloAGF/z4KPywNYX2zBFt2aetnXngaJt6q24OnZSdu67f1OfPb59Y7n5m/0j6zmybU9J+8emAEebIA4yz5y77KSOBACvJ/B3LWppBx4UQCCh8gGFzQ8AsbQwK32Ksrt6BvQLbQEKW5t7ZWsBvonVWCyvN9eBe8EoY19Jf1SBxfjcK2tyJ+bZUlM3d9VJU9ahkQ4I4wGQhD5z8iMlBwUkQmGgGNWJkDPx+aclPncqbzcX1a6SMsAiVA1gBJBBSPVSH36/JD/xYXdcTroYBoKuU5l/rs9Rjfn4wMPOCcZyB8fbduSlij5ALMUuHKqnVFu/zldH++X+PoDNzzozO5uRbR1j0rb1iAvwTVtigrJmzPfk0xnZvUeDPmvZ7GwQZJ669r9XZ5+c2tjnX8u+qbLD/DBDMHtL+BrYxLk0o44YbaoVtDIb1/qwFS9dIdlmIGwg/fA9UcAxz0uFBTt698lD+75G79/tLguM1ZXb8ntaUftsANP40hU5uvWhfJdKfjv5xiV2AGWEh9ux53CJVo2t4mU+kV2q2lkx0L7e1MnENP91dM7upgLHRi1Do2My8iViy4jdXFdPn3PUCDtsoBKCfElVC1A06httDB97S6zXvCB4qSCUkAav1ptVWqWWJq0EdLbSOJb/vlpq6vJrVE+L61fOVRST1FSrvlq11nGT44GXbvu1TxZlYSAxo/mdM30bD9yiHaqo8AEkoXmKRXOrFjw6aeUbvlfGBx52kjkflPvTYy2hsD2m3wbANhh7Uq79zYcKpId+m2L7PpCqBJDRnmw0U3sKHUwBiTZH+/4pMzqQ+LDwHdLfgKjV1buFJw5Ao8mLBazs3FIudalCAABAAElEQVQp9T/QOD3JnOg43D4PHjk3/ZhU0meGNHJFQd2nhl/vF+f3SRUILWuIuKmJcRktIS0r9tLFvZ8wVziLlCJ7GbMxS7X165qdkcYfy/ZxVuzp6pD1zO1qfGtTasucp2+NR9o/3tXAESkjWV/IodkoYjEW59TlvgJPIgAFwAEPYAMU/BxNGF6Jw0aj5t3iU7gC/NA3I8C3L7UmP3iUfSXmELzlNjvMUOEK3D1HLTV187+LWtVclUrOmn8G1Y3gzzv99OOSfeoJiZ16QjJniofuQSNKzMbwsx+giHQRCofZYZz56TMuu1Qxpwibi22LnQlAe/zkk646HOC7WB8DTn59GFwhnUxoPuvUrtc7cG7zACQCGDkGKM7rJ6ymhu+pp7NyPPuY3Hgu7by5AY/Mr14QyTzNFtM8xsPnkdVsPAm1QYxyYPFV1gY06R+5JjnHKp9/1D7PhZvXzufAztZ8EwBjKQn9+uqqS+VZSfxHY1qp7STt70Tgb0kvq815VgUftcds5Pln9o840Jg5310JHHGaWlxubExGLiiTMtrJ2wVQ69apP1UNDqAwYNmSVNW6mpX3A6jcuHZBsGlsZuqmSmbED8tJLPWpFUguS9tXPh+l1qvqTd3d8qau5HKpqQ3X+/il07L7wPGa+hvQqKlzhZ0MvJjqtMJuZZsVmzvSSMhU2uwDEFP3PSyLC1npV3VtGCTSJkysLaB8cMuJvJo63Cbq2M7XJH1+GwAkKn9Tv/qgyG9n+z6AsjK2AKhM/wMKFm+X5hpotPa2TiZxpNykjswxcfKxfBxJ6gw8sg+FVc9BaXX/zfkHu1u8whH4ZBQ44hjj2x76XM2bnDUyYi7hNfFtZe1crX14yz0ZoHbm1tNyI3NT/ufJj4abFBzjaANwbNeMLrVQJQASjUEpc6paxi3Xh5i6y+vqrKiCjXoJ/DSj0lySfWD/eNcBx0arpVmwaqSM9S6w9fclVQYoqMOOAmedzQyIbXN6vmxRLaE+3sywBrWuHd8914IvtSbcEx6y0PNBat1SU9d6dVTWz+x4G2EfZcCiEarsqNkboGokgCwGFEqVM7dKztFf22L8os7Tysqtp9mO0r6Yyt9AU2bvax3bsG2orWkYpJabr9WfUtvHvUNPyfCVdzt1MBANYMe4PoAEsBnIta2bUIX//D5O9S4XHHCMazaycsAUj/F2DZDupKs6D9r7dqB+cPMwaI6aHiGt3vf//bSaHWkkAgWuURJP68fLQ0bTTZp5mpVXuw1norH+8N/swN/unDSPeLJrxKbRkK3ZP941wLEW55dyK9EMKWO5MSutb0mqKl2pwnbPtwDfwUvFvWtfyQ0qKUsaVqMVKL/wSm3cES++q8uLTcto0biZFnIy4FJYWttRMfBUCrhVMr6/tpW0LzV7v7+/7/ehHKoE1AYtC//7/YuNUdgjcJyhbPjKY5KePKsOIAecPWZYqofEcHffRVX1B8ZY2ByOL+3Px44M8w0f+/wAkVPpvTKQvaAvxxoyL8cz3Cd8bOCTraPBQzI/p3EtQ0Hjw/38Yz8OKvFP0xjIqp1lm6Y+jiJylENRIX2i2pcqiwKPgK1mZqSJmk9qfUU62mJNS8ZwVwDHRqcKZCHthkBQy0aIaqO+nGaW+ZKqsOMOEkuTVHFuLxRP4BdagO9iUmvKobtBat1SUzfzLhDw5mUJO9pGS9gBHlcvZ+WBB81qu/HnArCDwtKyekaKkjhVCqLC40atbRT/cL9KjsudO7aHrH014/nnGXx/GeURHb/RnyNjxOeekCNL7xECdgPGcGj5x1vfJo9s+VRe+rh/8HK+G0ASOjRyOZ/tphQAhC9pFY18x5il5bQstR2S/syFSAcY68PW+JitIzFAiVVZyTXkg0bjaSF7Muoz0d7ZcZvanMD6cQW3jQrRFgaPzc5IY+dZsNXg6o5i0WC5oG0NB3cUODZDLY2UcUGjoTfjRlvD+jatSzWSqjhB0htg59C0k6mAsZkbNDPOVgXTuKuamNTa0jgSv5LHdFrNIVC7oBInOH69aRxLnXRmbU4yenNKttVmH1SKd6suWAEyWnT19rtQPM1ck2oATLXzgPdmqK+rnRdr29M3dJutNKAMqlUyGPQO/hvYs61fZ/u2Pr6HtNWFt2E+4eNwe/8YW8dwOkmke3hrxzW3NISk0Q/U7UsBL0zu03A1G+DS5+2rliknfqM5xtgYqKMrJRfwXJ2cLa+5nWex6zQKNPpjgQ3S6+kAPKoE0sjlgO+4HVBafS1bHzw2OyNN1PwwH1pRp6pmBRu/I8CxGWppFu9elzJGXQC1lgEsS2VaMU9gUjbd7ZlWEPWTV3PbroMNeyusdV3vpX6+1NqctwCWdss0qXWtWZdaaurNuRoqDcXTiNnYw7kRvJrNg7kS8DoscTMQVgnowzFm+56jRV+si4GUes+NuRcDidRBlcyfdta+GD/aGDnHncufcNmHzM4R0AigM4BIW3NaMYcXJI1WHy7L8/baULaqkrywY4zxYDu5fkCBJeGMxiJV2UgcJ3a+M78OnCdrEvWdlAONNkd8DNx9S1+skTA6aaTOs02BY6PJwGOzM9JEzTuWXqg6fmMUn2Jlmw4cFzWvNKppxMaNIt4kFufVEFRBEAFyW1R6BaJUoK5MA6KZgbAByzsdYobvlrA7m+2RVnoFnx+1/ssFwBKHHW6s/jVQKutSen1JHwzF86A+P1bpzp/FzfExGRje0jTpQbEzLAVuivW5U+UGKvzxowCG1dO+t7dyb/Uo/sarnm0xkOuP5+/bWOFzizouJuGNyiTjSwt9BxXG88Ee4Xf2DV5y0zAwSZmjoQflUPzPnFp778BFvZfgUV2oKjUnmKBD6f9+msrY5Q85kDk9lZWhYbXdO/dx6epSBx8Fl4tdB+SDjwcxR7+4Ul7zYWCRexu2j1m1g2yWRu7ffMPbZKuMymZqynD46kiqr3i89jA8pb8ZXTZdxMYhuBKj4Zo/Pb/q3nRKNKu6CvsBwAX2P8368que1D3eIawCRRWK2hMVqG9f2UwVKEvYAo137kIq9nLBjLCthLo6NBtENubyoLayLrklacq/KDu8pgx0DzMFXEGVSuloe+7ZeenvnajooR4F3uDRLGI8X4Jo45tdpB3740eV+fW2Xy7bjQ8U6RO2a7R6y7NtWwAnaRRxsFldSavntnpvd94eCgYs0JYstMs0KSbjuVSL/RpGZv52tTZAcSZ7v/RPfcLZShIcfFzjMhcjyzYTricET1qDk2fU6xqtW7nA3+H+lR6TL3vf8FH5D6/69Uq71N2OF/q4AuJYsqtuXsUYNB04NkstDaggLqOl4Sp2gq3yxq9As1WgzBh1ArEaR7bt0htE834AjV+dFwZHfn/dbWl9GVxWm6gg3FDUy8ULyXmrWd+8pcQbHNnRrCEq4gto2a15kasBZxUxbmCjMOCCNWVG/txZ16nJNRka3VnROVUKzGyserdIEednJdJ5ySSVjGHnVGx+lIedoIqBR0AhRDYYVMhQGDi6wty//7+9LwGSpDrPfHVXdVff10wPzAzMAAMDCEnYcoRgLQiHkWwFlry6FtDaDh0hr+VA2rVYSdZqbYyFLMIrEZZWrI6wHEJY8notLZZAbITBEcgb1grZ3DMMM8BcPTM90z093V1dd/X+38v6q19lZ1ZlVmVWZVW/B1N5vSv/zM788j++n+szd+PqKj0LBveIofJhcfQCiMaPSzCJABsUri8oWtoKGIaKGYqCLolDYcqpnnq0Okr9grWjq7mcOJ25AKUhaQ2l8rC+orJlByDB34gzbkbZo3TlapXp9z7+K39Wlx/eVScuK8fCJYH4ET/9zn0Fjn4Ev0CGWsvo8k7qcPVGJlBospyk8INf1/DYhHY96PC1czpcMzO13cdFhLSV5nugH4K3nMqtlXrw8V1ZWhCT23a10tyXNgzGGLR4NQj6VTVt7fRrBlIMtnjOnGqwXBmz9JW0G9vcr109r/ar46nr6B/bKHxOZpO1cbT+lz8AkCoxefDz9QdpC+DOnEZQAj4bsKd2sDr5dpE88/f0MVkUx5b3iN1j9YE04I2cHXhNHF/ZLU3eDEpDOQKApCxYh99hckTtctM6A8cjmRGxnjskjpTWxR7Q/eB/+teomAEkAmOicLchyp4wZbjxgpJHHZ8Dby6d2i/uuvk+9ZBv66XsgggnxnyNB/AFOELLuHAh57lZGlqOxfkTYnB4VAMK3247fzu2MoFiROxHgcmTHZiRFlKbQKVYAvfTrt+d+nHRKI1jLwRv+X1xVJJqv8dy278ZyLhtb1cfAAjFCQWLXR9mUGWuZw46cgK6uA+/zpv7V5dWY2GfHcC2qq/2p67baR5RBwEyA8VXJFk4CL2HiEoHATWNylq2Qr6HlPklT4ExZKtGxhiATvhBwoSN9gB+p4gfcmZbRMydJL/68pK4JH3UFjSi/tGl3cQn+Zo0T/P4RxbPyFXWNh4uGvfMXuIvbFRQ76FMijK+EfE3+WECOMJ0DVqeEAFX8E7aZbpp1K/5mDkjDQfLmOt5uQ2MlIiURDnkr5XOU+AIe/5KJi8yuYrnaBccfnjZ9Covo5c3Rz/3xQTfCHSCCRQUMxJs0joHbcQoNZTf/pX9LON2zw1uBO2kwGs2vtXHxVa/B44deU7s3HNNM9F17TgDGbuAjFYn5gYENRrDqp+Dzx0Ul++/vO5dhXoorMEztux/rfq1r936EbtxrAA2nwNGa3YeqLt+/hmxff7PbCfHGj6ZDYbM1/BBZEBpbgSQiLAJ5Kg2B8agrtRc0lLmuB47LBZy0yKzvCZ2jpwVr+WvIXB5tKFpnPtYKRDTRnYNm7IQBiTQZ5iseV8j7SPA41+dDxs++wjtrhbp94h3DYFJN3mrub26ND+zkJrQb61jsbAmYtC+RnoEOMIsfWFlTUQIsZeKefpjDIksXdhEkiJ76EaKxhL0pQGeObpYpFVySraptYzqrdjf6/xxMD51ke2JWplArXzrWqWYsR1YH6hJoNs+d3ggS40lBW018q/sp3vArB2rXYwtsAJwA+2al6AU75UzJ4/QO+ty8tsMbwJYdkDNLG6n9cztvN5mbSnPB2kGmaaIA2q4jtXYrHlkcMgmZKu66j41Wwz2S+7FlZeNdz5p7mxLhQItcxnpm5gnE3g4tyDBpBqxjb5VPknuC/tfWkuKVPm4OJSviCuSG1pQAEhZqkrHRuARbR/KkBKCMIta5POFWCYkB241EFA97nQd91iI0KwaePPV9/7IafOW6oXXc8TfSFyVicGW2jtt1LbGEWbp5UxB5PKGqdFqYFwI+gQhISKaKkZqbIr6gUmSBIslhFuifvClEo4QmXCVrJqBhNYyWkm1v/aBg3P5/IJoNx8vAEWZ/uHeYu5CgAtoK3EfOvGv7C/Jen827ZqpvZ9RfY/9eA+ARHhodKLjlDz1knW+BQBjDshw3tq6JvpsF0AysJo7uSjikZWa3yjvtx65+V60R2mm4TNqtf7rZp4AjEPkLmg299vNFeAxevJvakEr0A42ApAAcJnYpWTC3uBhhHaSvuZIY0eAyQ50VUEjpFBJDhIzQ30ua4zLROOI2N5OPpFIgwj/SGS2WVxbFudz2ZoQs+GLRZJApAoSJYAk8HiY/B/3RsnwbGG9Rp0jNBbM1uYCLCIzysgsbQ0AsLmhsl0s5OV7R9Vc3rL/feIdV79fqeXtKvgby6GBTWDY21FIu0sCMhwDWujZq1SBeNAjfLxMDrUJSki+trokVlZXRXpwkC54lJjeUwIANZ5IERs9+ST0eBaUFkTd103Yh8tvgm8AR/zrF2L0btwUfpupO3FOUltJTvGVdeNewJjy45aW+JANCoepKotep+SBtstLjaEqm1bWL5DrE0Dozt0zdc3dALO6hrTRTltzX422G2kO1WM8H16iT3XdbgyQhMdP/lAebgQecaxYWDf4FGmdicRXV3NiYJAItmE7NhfWNCIIBmwZYYPn0Y7fEX6Wi4sVCR7j8ZDUSl7InxcjycPmnuX2S+Qmd3kiLIEig0euaAaPfBzBNZbgkeyjMF2vk2uONF2T56ObgsCYOLlVmYtfWkc8myPra74Sf/O5tAQc/YqWxqQ4H7HKy4gHPaK0JHKnh32EzOA5+uJA5gtaJS0SAUq6wJEI+cURDNbAki9v8JfQDAaF4BvgQWqryEwhlzQ3CTZt/CvduFwE/0o4m2GWNMN5eiB2mxrG2Wzd13J7D3TqWdNt9wD3ktzcwglo2dzKnz2cxhER1aqWEHPkou7nfU6WKnhzUt9tHTdytJsL+jAH15j7jR/8TJ32EfO00kBK8/YYgcSlI/JUFosTYjq5uPm0CDSGiJxaBYxqJfalVPeZ1w+cnRKH88+IicpOMT1wsubXyKAQarD5zA4xkz5ZaypVY7Qf2kUOnGF1GdphHcuvrUbE6dJm3slyucr3SEotSzBcG2ljRQ282dhrrPmldSzkMyIZJ9aK0Gawap5Du9uugKNfnIw4CQAIREy7zZAgX+zQJBGwjMWiMpgC3wVgg4cyNUYmShGK1IAl1s0+De0KUbdvTQJBAo1OzoBBBeeGtiNGB5iIRBN9+QGzMH9MpIfHe8Zk6uS6uqkjP2KhtSb/SnaFgI8tsu6gtJvG0W4uoOS5sHjWEVm1XR9B2g9Ag2I2o3ZqjlY+oypwUtfNc2p0jOs6qcN1vV6awWKjuaCuqglGXRQVVEIDiRJeflECSWgareh6sG9wkMzXq1kykQ+JCHJfk/9iZfiqWlvZUYMfEHxb8Ttyk7nlRZElrACwdyBbFlemjGQEz535dQKLT0vAyEAQbaQZu0RmbMK1L1NADMzWamHAyfvswCOAYIliNJB72wllD8Amil1dX7SO5awo0rWJxf3LGMNycgwcvTJL88DqkrWMI2MznoM6BpaUWEj6SSD7SZHC7ssy6ispw++jpLkEKHYbuKOeg153JwEm+B6f2tY3IMQKVOD1yNyFfoEKd5JvvXY/mKlbP3tnLQ1N9YaPrds0jnaj8N9Luz7Adv1vtf3wqS6TZWF4bNr1qTO4cqKRbATaXA9sauB0Hm7mwHV5yYE1vI0pwBcyvPK8aTbGZjazIs4vlsX0m/6D3IF2KNteus1YafLbTOtopuDh7gAWUbB8mfwsx8oXiwtLFXHZjlNyHwfR4DgiqqXfo2JJl/uIxoepeoze6n+BECRlD6FN0IQ1ouwxiL+jtnjGD+AYC+VFtkgZdzrgytfU67NQrIilVe9TBeKS8Ff06OQ237KDGOZE46sEY0YozJ7ib2pFAkv6mqgQkIyB/6mSJ26nCpnCKSKcfCpRkK8ZvpUaWNbE1vYKTEUg+E4k0233FZQO8AGCYpfpBqAC/pXQVqnchUwzBN+6Rrmhu32emZVFqW3s9jyCPD7uAfxLWEySP2Jx7fPZjFgrGanSsB+lkX8lrCRlSq/Wr4VJqZ2AMScyYMBi199geowopQ6KgaGxTS9aOy0c98XLZmNgnqiLetzGydyd1kGfmOvwcL0WjdvzuFzPiXaX58ltkCkIBdvcX2XoWvJnvJaHkXNgreXK2ROiNDAg92E8aC7Dy8+IbbXajVea8URya7OmkLexNKKsT4rT8T3i0IltFDUfE5fHj3NTaa6ukGbu0dV18XZKbagWmLK3RYuWJmsAxVg8If0ei8RTGWtA2SP9DZvwSarjtruO8bL5VRFNTbTblaP2thpHP83SOEmkC4SJZ6SFLz5HZ+ZRJbzsZd5HigiHj2UusyrICC6/VgfTQzJqqlyuSFO4GhHu0fB92Q0yNkD7FvRr30nhq6DC0FoZ/pU8h0agguv4vQx6NLXf5+93/7gH5MdFlWYIHKZQpMBKgo+LVTLTjYzPSGCKj9lOaBb8Pmer/gFQVFOpVR0n+7gfBjXmNlBcZFaWhB39F9qjMJgyA0ocs9qH/ebCoMu83+9tdVx13c24ajte56W5n5deeFkUK5eIq6/Z0ElFXviMNFsDrCEKeyz0mrnZpm07zSNrHDc1aLIDmkb4Pi5FCUCe3SYqE6copSGyWBn+jSojz2M5IX6aa+wnCAwDraIVZQ9HZMcSVp+PxkS91jiWijmRSkRJ9htybyKStg5bjpLJlUQmW/Q88wtmylpGZAXphQcfa5FYysn0OK/KZUECy7D0r4zQx8va6qL0gyhQKH6cvk4AkADCdeCOITa4JfTCB0PdRe7ABmvGzfcbD62CiizlZzWDCtTzkxgdD0rQHPWThphlG5Ql7gFoq2011vSiQkE0eGaFTK10PQAs+8UVQp4c/QCoQYtmB064XrOl2o9VX7iXARzB6mAlc9ay8ThWGjvsQ99W/XM7LLkvLP0ozcZvZ0x1zuo6g2b0DaC/Y8e6GBwoiIsuidbkAbN2Yu0VYXj8CTFYpHUQVFOxCrSRB+inmeYRQJC1jNym0RJ1ETBDznBi/aJ58dwyIcZkRBzLv12cD78oXp94pdbfLYQZf0rgsVGBBQDaR5iuKxGKulbMw3hWhgAGOlgioXWiRCyQCd0S0nk+kzqNIwCOH6kCMWsEQkDLuNU0TdAgwL9SftHgK4W2c9ks0RWkpa9lmtInFsnXBmbwfg/cQWQozLR2X/ie391bqEPcVwCXfgVt9ENUb6/fDqCQwQsLjBNWRWoryQwOYInAHSv/SnyY9FoaR4AiABM7zaGVLKz2AeigqAAQ76V5IgKf3bXPqkltH4MkFTiZwRq2UdQ6xp76X3O7+qOtb2GO6rlxT+p4dnW4rtules6vHF4T6YEz4tzibiIfN8DhS499W1wz8kgNJIJepzCwXwyvvyhimVdq+63GXaPgl4Fq8AsfZ42jW+DI7bGUbbFiTFFun13bISaSJ+V7GiDTidZR9kVv7hplD1kFYJXEPWUm/kZdtXitcQxV1kS+FLL8AFLH9WpdwlM/zdKYKByRM8tkEugRLaNXwkU/dRokwoaxaErEqkncQ9EysbyX5P2bSsXFGjkWw8dtZfmCGBkdFQXyq0xS5h1k3CkT6IxSpG6vRoTjHlilewBcjbp4LwG+z6w0JxgNoAIaKhVYuiFGh9M7GA906Z4EYBZj31irWeAe4PvAfFx1hWD/SuxDgaYTRdVYGxrwzmpN5CQsfgDE7Pz4LKrb7mJQpQJIaIoG0iPyHQW/R7vCbVWgxHUZmGGefJyPWS25XjOAadW20T4A62YF58HzbVbXyXH1HKam1sTiQkKCRvZZVUEjorEXKWBlT+hHMl817j5oHe24Is2gUZ0PuBeZWkfd72gd3w+mW3s5fkJcNHWpKCy+KrtwonVERfg94h5CFDW0jxGi7Fkn17VIvDOaPzlZ/FCcRjzeuXiBqJ+cjKqWcXr2kto56hVDAmyexFaBIr2i1Qs/NEYJ2GlfmIBloWg83OMxyrRTXCOzCt2cRAmAtkhlBNAPTWWQA3dgCkJWmKntu3oW+BpXrHd/GVRYed2ooALAco3MdyhGZKBxrxXpGlbogYi/6SCBit69Iu5njhcUPsBbKfysaQQspcaSrj9cIXAfcCpP+FdiHcAVc+g21RSATztZaRgEshzTpMEFFVxqYKTp8wlACcATQFYFTdyX1T4+pi65nl8gzu+x1P55HR8kk9Nsiyd/xgPfoejmjewzAIl7Jo7J6qopukhR0JWJy0ScTNpWxcrf8Ug5RMDRqrazfYSz6J6uah8JbyPKmkEj9/CmZK6pryPXBe1OiKwBoOyhXqXmkY/5vcT7NUqIofr95/dwsv/o0orhN+P1aFtZy+iVLPGwJw+mWndgryelQq3ghR8Kk++Z5LCku58iwvNZup5kqgKYTFB9AEqQo3crcAdAY+ncaQka8dLRJXgS2AQqTB+uMFOnBo0XAvtXSrBpQ4yur7M/1xj8bMWiP5HVuAca+lcqrhC57Nom/8pOpvIE6GJTKCQNINeOGRv36yC5DK3Sfe6EnoeBZ7vj+nOXbGg9GZyax8F+zJ3Pw3y81e18PitGJ2dlc+TJjv/zj2TqQdYoYskFIJLzYqfIHF0izscCHV8OXyomo69xNblUQSYf+FWrL2A+2GAJwChNfNWpSD9JrFsoa51qHXk4kINHyccQ4BEf3c0oe7hdu0solVSc0G5/Ttp7rk/VWkYnYvemDgPLMGXMkYXun0RqI+8mNAiICAcxOnx187kLMrMOgGUsRrQCZP6GOdwvLQLuBWSFmZjZIcfw5qx1L52WAJup7QJjACLttFVwvWD+Sr/us07Lo1vjwU2FicY7PQfWVDZyhWCqKSuNtZ9pHL0AQI3oeexkzeOqWkOso9iBNuPoxi/quW2z0dp6jYGh2bzPY2GJuavztu7J+V4EhODe5I/G9aVna405CIaXOAAt4gtz+8Su0YrMP419DBoBMBGBHad811w2aR1twB7XV5fsD1kDjXTQKhui2obX7ah5+Lh5iYhqGaBC82tG2WNu2+o2AmPysFh2UC/jKXDUWsZWL70/7fhhj97xocW+lTxahYDlAPKFSmf6nMhkzlOABflnkEmKsn1SBG1KlMgUTop3MuFEaw8Fbt9oiX4AGkfHpzvmsNtoPvpYaxLAdRwZHmwYTe2ltsrtfdbaWfVuq3hiwDYKuJtnxa4Qcg4mjbXqCtEJjTUAUSt0PmOkLUMAp9vgPQZqAGNYR7ECg3ZaPrUNrxu9tP7LoLb1Hty1zGdXRTK1ceHDy883DHyBFvGXd/9YAsgSmZ2PLu0iM/Zr0t8RIx9f2S1yif1if/pRORGz1tEJ8GNSbz6Tmmmad2DZBIDuIncxqzSEahfqOvwbw6SogfYRpusisavgowluZX6VAml6w7HqjefXIKZ+PQGO0CxBzQ8BaV9Gk4QDvFkDlqEoOcYn6N9Q3WylxjJMX3/0JVnMLYsy+XEUKEd4HICSfC2TA4NSgwlgaQ7cWVqYI7Lo0ZqJs65jvdEzEigVMmQFadEuVD1Lvs+caKs4+MPgSDP8Mlhb1WvRwH5cZGgdkfFE4IOvR8omVwjTvO001qxdZY21NIc7+IAF+DJr20xDWm7CHSO7tiz9eFlzZgf2zB0wUOP6VgCQtXxoa3Uc+6wAp3ksN9tmrSLGUOfI6276tKqLdwUnMsBxelXQBw4CNja0hlbtGBCy7yPXuXjoNWp7TOQHLhUnVveJPeFH5CH6jiUlBteyXjJg5OAZaY7mqgCK3L4JaOQmbpZITRitolr8rTJlD1Ig8z3lpr9mdYG9UvQ+Lq7zSTVr4c3xtoEjtIxwih2mdIF+CMab09S9tCIBfuHjW4nzXyZSI7KrWILygxOgDJOaPEL+KvncCu2nlEzk22HQE5TEAGUQQOJ12AXMwLKV+eg2nZdAuZTb9EHh9SycaqvsooEZWIIU2wApnX2Iei2PRv3hHAsUuMI+p43q9soxJxrrdhgBOMLXCqyZZYT3mErPA7AHcIXC4NDcRt22q8MAjudgB9j4ONdX+25lXQWK3F6dI9a9GAsUUecXTtVpw8vDe4TIvcrDOlrWzNn0TnltaaeYzr4sLoocFheyFZFKhWugkc3P3CnA4h5qA8zGgJGPWS59AI0wU4OORy3YjiaIy5niDKB9lIFmpjpqfbfr65UixTDQmP4pNC2n1DJwVLWMblX7ljPRO3tKAqxF4EkniE4IJZ+bF+X1kBibuphwJH0eVgqiFhFOoBJgU2oQSHVfQNJ4ithE4E6/v/BZTr20xN84edXRw65xFgU/z4nvM/6IMY9l1laZidE5GjhMwWL9kG0lHk9KrZhZDv28zR8Wdnpv6V9L/JUqIwDuCxTcPxdfTNHg9IwplVJidTUsVlbCtiAQyg8zPQ8DLTuwZyd7MyDDNgrAHPp88fkKpcMLW2ofjZre/NrR9Lg9n2azGZvYLpAVTCqRmlV2cHz36DGqRYEz5O84mDaQ0QNP/Vvx4df/r5qPIvstOgGLAJtkHPOtwK0H5mlzMVP27Nl+tblKy9uJWJgo/coi3mHgGJo7mzE+p1xMHVpGEMwOWuT5dNGNrtpnEmAfVyfuCvLBTn/1IUrlCD5BmCiRyhFgEznCK/RXXiH/Srz4uxUR3meXx/XpZFYWRJJcGCId5AdzPckmDQAqcK+p/JW4p1o1gzYZzvfDnHnLyd+Y75PpgQH4wwLmfdwLTj4s8MEEeh4rGQP8uSUjVwGkug7xqWDSSpzm+lZ1vNjnFYiEvCG7yfw/itDRR0hL6D2i+fsTc2IfZX2xwGgNRSG1lFzDIYB0SgSObuWHNk0KHyt2BabsX5x5i3jPGz5gS+Rv19Zqf6i8KsqhARpzM2C1qu/VPlfAEYKB83AiNUhfAPZkqV5NTvfTOxLAC23x7GlJ8O3FTcwvfGTdkfRC9AeHP8gi0q7RLvi7AVjGyNeLFtpNwodbJbt6Vpqpu6lx9OG06rpkbZVVthW8BDtJM1M3MZsNaDXmjh6gtG77bWro3W4ksLiYlx8RefpwHUpX5AcGPiyKCDigpdRS07PG7F8JQNcOgDTPsRFw8wo8WoFUdVyvxpEfai89IAbKcyJ04UhTP0ezLJptn8+uiEWihHJb6BVCigpq5RA0on83wLFA9xBiBaBhbFS+8u6HJbgG48ToxGzLoE9qOMsZEYrVxyY0GturY45N1eByA3DUvoxeib5/+gEBKUCjlwTfdqZJsjjJghd+pMphmSC2frGeI9M3pXckJxf8QaUGKA9tZlUDyxZvM/ytx4jDqZ9BI0TDZlArMeEFKF+C9EJg/0rUwz4UAItO+1fyRxnucV6Xk9E/LUlgfJwN4AOb2s8dPSiGRifkftZYQ1PNgVtD1CS0TqTsqwQwyYWgmR+32X+RwSfM1mwO3zQJ2sHtVJBnVa/ZPvTD4JHrYlyvACP3ib+LAQqMXD/yBDF5eM8RM5Yaagk4yvk1xnR8Cq6X4B5BaQYaL5m6Sj43JrftIiXcvDh9/JCY3rGnJcVHMb8q4wjIkt/xEp0eJ40NqWzgRwBevzItYSYslox1Vcs4ZpMjteOz1gMGRgK4PxbOnOw4wbcKLEE1RJ9d5IRs+OLBUJADiKQHGMjRCUoKslEJENSmUgMimyMnZfJlKpHDcog4MJs98AMj7A5OBNHUMUpxuZULXoD4p95rqjwAIKX5k8ygnaCZ4bFByVMsrDWkSOK6eulOAiqYG5mYERnKogQffqu/hEYfFrhvUKw+LBgIYonobwZzvN9uxl6APKsxsI/BY7vglOeOoBCAxuwaRf0OEL2bhwEhwCrj9Bx3pXUEuPIJNOKc1wlDOfmQu3z6WhaRJJtP0HmcoVzpo3SvubXiIvg0ly/QR4tj/V9t7HZXopFwiDQ3dJHl2Jtt8/l8XkyM7KSXMOVjrAJLcPuVia8IIFOXrSsBaD2CSvAtX/Zqmh26TIkBI5VjLAEzN7LuEMlsNZUjbBjIN4rCpm+kc9yqgTuIll8nmiZd7CUAcCAphmyocRhYQltlTuOnEqObzaD2IxpHkPoP6R918V4CDObQM17kr7wMjryyGB3d/G50+mHB19/Kv/LMmbjYtZsSNMiPtObaOQZ5mJ8VCMR+J4WBItflfr0Ap9wnwGJi5gpRPn+IvuspJZ+HyC1JQZWESnmopku/kQo00VBUNCrQNr7j6vfXVUFShRnSOOI9Cj//UQowclpKZOkLhbsTuNj0zZAgm/1G2SwYvFxLpJ3Ey5aBJbSV0FpqYLkhuX5bA2g8c/IV+mqaMF6ePXSC/MDn/I1I5YhC30ay8At/vUJZdeKgGKIUa/RggH8lAnfwEEIqxxJl3emHSF3jrDd+oUVeJ01tNKX9mDek4n6NgWUj/spWaGbAStBvlDzupduZFldeM0Uv9VcJOO51PaCT67970AjcOnxoVWzfXhLLFPEN0/f27eQqQuZvfGCYPywY5JnBn+sJdqIBgcdIlNLwIUOZB+AR2kZQ9kRJB5wiq1GWnlVOi48KR1JEEE+joX2znc5dN99neQzWr+0X7xVLRGc0P/eqGJ++qKnpGuMBrEZJCdKN0hQ4NpuU1FjWYsEbA0sASnAdaWDZTKrBPw6C74H0sGv1evDPzPBdM172BskyA0tmpZH+lfRAjEYjpKhcF7nVRTJ5k1mc/C5B+8KBO/Q5KDUJvcZvKs3UlBdZF38lwP6V6qe5OiIH7kBjpabxw4cNLD4wjaEPTYyuSs3bdfztJpJJAnPn5bPOqVlZnYVdG3aBwLNmP1kwUW/31IYfYqmUF8loXiwuFIgPd1kMD1Vq/pXoH2bw06diYnwiTvdBwpGplOdlpa1kQIqlVybr3KmXRRpUOlXwGCNteTvFyDADmh4hxigBRXZ5qXF3rGrE0sfAYysOR3Vid978OXXTch3aRsSSQPs4PrWd7rtBy3rYWSkXyO0qLYpdMjy0DRxtz6x6QAWWqUQ9sCQMKTWT0FhKzSV9TTCwxDZ8L3UJngTg1Autx8jYdPAm14EZ8QOfh0qmx3lVLvHCD4XIdEF6yfVyTuSIHD1CIBM+lVF6gOLehvxaSeVYN5BPG/EoeYVqM7VP0nXeLQNL2WIjm5skWYZfMUjAYd7iwB0AShRoulBi5PPL/JWGlt3HN6ccsT9/EBAKihmYrq0AV7OzZkAGMAZORbs+uN5GukR8UpBmTeKHEQksEQeIerjW+BeN5sQrh9fEtpkluY25WF3/Rh+vVppLr0zWAI2sJSRVYe0Z2ExmdsfVDDMpAstNtY6sZvQRSoBiBykG7cot+98n9k29zu5w3X4QqYO15hyBx6HRSVvKHuSnhn+jzItd10NnNkIE1HwUaXsnYQUs2RyugWV7sm21NUAjgJEmfW9VguD7ImBJsFG+6ClPeIzAJAJ3ABSwL0wBO/hmskrl2PqozlrCTF3OnReJ9Nb8KHAmpe7WgpmqGSUP7iOpsSRtpeRJpaUMFiN3C5m9gsAlfCUBKOBf1whYdPdsgzE6NI7gghw2fSw3A4Pm2dtpH831sM1aPxXYYX0DWNa3Uus5vf4wg8+dDIvdl9Trvd3Ms34WG1sDP7tNbhQobWB87RW5DpAF/1x8QLst50q7xWT0tU3N5pYXLU3WwA9kGCJllNEE627L3UvNfQjZNz6CPIumAr9GOxO1qWrdJq4fPlbsKHtiobzIFmFxaE+DWzeoi41AA8dm54EbokQ3ITSTrLEEsDRM4vgqq94xzTrSxx1JAA/P5fML0h/DUQNdybUE8MDAPwDLGPnMIIE9HkxwrI+RQzhuaTwscL/DFO7WRNVsQrm1JQlke5n0u9k59sPxE6++IGZ3XenKPKmeN0Al7jOmmYGbBZ6WEQKU2C+zO1nwF6p9bLX1U8cPN2SPaATqzLICKESBZs+uqOAN6yeOVcRVV4el5tEJeLTrF/vN13/pfEmkyRTO138tmxBj41Fx5nRC7L6UNNctEExH5x4S8ZM/3DQN+IsjCrkV8Lips+oOO/CIw60CR6QxfCjTPCc86JnCBBqtZAQTtVNto9W5wXS9snRuE2VPOb8kIolRqyYd2Rc6eWp+fXYbOVb0YWFgCVU5FKtYamDZ2oUGVyN8L7ZffLnlH0hrvepWbiWAlzqiFUEzZOQIz0onafQDjVKEfC3lhxTd6wjccWuiDFXWRLHc//yNbuUetPpwoh8Zn/KNkkdqK8kMbkWMDlnAv44DN7z+eAmarHk++HCGW4CX1hanAJKBIgAkm7pVYMlz5KVaj/e5WeL6w7dycLAozs5nxSiZ2PHsQcEzxYpmyKp/1jqaj/kKHg1MXqPfkcTf9pZk89Rq24/lhPhprrnG0Y74u13QyBPh5BoIRIW7BLYTUfrgiNr7QHJbv5bRB/7yB+LuT33Ir/672i9U0zHy17ILdmJzNwNLDtrBUkeEb1w65moEbYDVV9VGTb3mtwTYf8mg7yAPqGqOcB5XAkt6UobCRSInLpIPnEFZUchlRTxpfD3DFG4VEY7rLIpkMk8ZpMfcp14GTwJx8l/0k5Knzr/SdPq4x/BP9a9ElVaAhanrQG/ipZ1dXSZtHTEOODAROjFjN9I4sjAAFMH3qBYGhljyunq81XU2j+P6T88YbBPlSr1vp3r9mb8UWK1cdYPA2OxfGx3YTWbq17CrrkCzWSI3Hfb7rjvY4sbs8LhopHl0260T0EgqKbIOGf+p/XsFGtEnKHuQXKNG2TPe/edz6HW//P71J3/4AKVb0lGU6oXHugos2bdSJUc31+/HbTwkccPixnXysOxHGfTTObGJSgbu4OVPmuRoLCEALBPJBAFK0mQifLxHI8L76Vo1OheYsODrGMQANQAL3Gdu8kM3OtcgHePnIehTulEAElHMgTRW4FGta7Rq/mtuw0CSl817MD4gpMaa/Grj2ZfE+qt/LdLlU9IVQsJf+gFBOLJ8lctwy4H7zWb/QB6rFlzDOxosock8s3phw+eREC1ArVv/RqfaRgNEw2fT8DVs1aexwSnVHQJlj6gUKDPPpIgnuqhxxKxWVjMaONZdHmOjGTk6gCU0k3JJD3Gss9ayHzSWeDHNE6v9xExzXikL8eldAZQANAlqiSeNPKeJ1IiAw3UmV5KmqHXSWpbyGZFZzlL1kNQ0I4hHAkrytQxqRLh6bv28juuYWTkfyFOEVrwRMTp/vDAxNpZwswAvHUqQ/SsBEFR6HjcXAKCMTc5u2ql1VTM192UFGtGG67oBfdyGx2SNqJsoa77+8h5I/5KIzv9QRNfOcpfk/gAoB/cxsowQaoS/I9LFsjULoBJoEsDSLeCDJlPVPGKkVooTbSP6xTsS80TxGzRiDFD2ZFfmxcL8qaaUPajvV4nOzkyKfvVx9Eto3C8DS2O7nmoI+wAoe5kc/dzpowJpt6Aq16W/JQBNSoTM2/HExrWOEZdjcrDeARsvfWgrS8U8PfgpjWMxQ9pK0ixUzeB4iMKfWKdy9Pd+AXdjkbTDvVj448XgSt18BlJbSfeZGriDyHBEg0PDoxJjd8O/UqXn2Tx7+z0AZarJ+cXn18VFO+3peex7MkAh92UGe+Z2DPqwv1ldta0KSHmu6nGn6wvpd4uJpXvpY8IAWEb6QQMcyj7o1SnTv8osduSjTc8PPEMALIsFCtghwm/iD5eaSdQ3gCV9zDLApCMGGCX/yyrSBHjMEg/myQtLtXZO5/s1ImB3WtYJOIISB5Q75qwwTvtwUw/P6eFh+sin5AxQ6jSi7HHTr9u6fR0c41YYnayPjy7c7AwsjUjw4GgsF8+ekF/+QTSFdfI6bZWx1ktZUUBmHNI8tlrY9wnAkggsZUR4qQR/ODLlRMIymALaJGgtt2oqx1Zla9UOkdUXXbLf6lBf75Nm0GrgDvwsUXDvobgJ3JANWvyBqwBAg5mep8XuHDVTgZzaQN3fTLuo1lX7sFq36stqn1Vb8z67CGu1ngEeKWmCEsF9ZGGnULkb4VNogEp6xOAlin9UsF+mNJSaSvqhLYBIfFxlykSi7jA9oVMTNY/5S9tvEr/9bz6BzY6UAjiBAbDjaXnPg7IHZXz64prGthMT6Wk6nk4IqFtjqMBSai7JDI4/FBm4Q5pMP6mGwNUIX5ExF3kzuyUnPa43EpC8YAWiyOD0ON50W9eLfLmTFgGaBNC/AADg4Z7NZkWSsnNISgslcAcggM1XdR3pDSkB0MPM7LhUy0i5H/jjBYDS0FwW60AlqnLgRrvpQp2mh1OmZ7sKQMelkVYQwA2FTcjchpfcj2rGxjHu0w1wRDu1PoNGdR/qOCnhlWdF8uDnm1YFeAzjI7Nq/m3agCrgXQUTNcqGGRzvS+xBikLDf/J8doW4D4sb/o84rBSn9DvQLqK8be87yV1kydMoe2U6lquxcElk80jfuBHtbUfZY9mBRzs1cPRIkJ3uBn8UVhyW7HPZKrDETQgTkZeUE52WjR7PnQRg/kiE86Ic3jBTu+vBm9oMLEMhkASXxerKBTJLxol+Iif9ygxtUtwyItybGfRWL35T8vSWNJzNFveY1FjSM65dYnQ/6HmcnYVBDm6XhcYK2DHo4/6t6vCxRku0Q2Egamw1/8X4u0afk+ARAI5LktwPkAFGLQweF8uXWhJ+q3XbWed5sDbSiuwbfouXT18rhzGbovGuREG2l04V8DeGYsObPhaZsic9PNqR+Wjg2Kkr3uFxGFgy1ZATDksm+NZajA5frC4PBzM1XqhBJ/1mDSU4LGEKX8us0gM0IonS85R+a2CQogyRK7yaeYcjHbssXt+GR4Ql+PQ6+eLy7WQC0jHuMfwtqP6VUFwxMbbqXxkOR8XSuTkxOjlbi6r18jQAtuzAIY9jV4eBoQr0zHW5DvfVaIm2qpbTvG3V9gfPf1vuPjT/rDh8+gXpq7gtWhQfThtuBVZtkEIwRf67ZaLEg+ZxfMAI3rOqa/ZrtKrjdF9u3ydFZcgAiE7bIAZgeHzaCARz2qiNejIQp5wh4GgtEygAFuePk596SgbRtDFU06YaODYVUX9WMAPLXAE33RyF+U/Jl1GrGsv+lFZ/nxXM1KtZ0jr2eBCUYZosEKg0zOGEAMjHCflcY9IfLUk5YMnLo2+AJTQeyCiESEtdOiMBqa2s+leCugouF2vE7ZgeHpMTYGJs3HNeBu4A5J04tk6ZY+C/V19wDKbpRiCTASRashmbe3ECILk9axrN29zXwbPPiIefe1C8evZF3iWXuWxFJFNGcEwz8Cgb0N8p3lGIdRkfGBBjKWuwVDdIixutgEYMdfLoQbFj174WR3XfrFhYE8lEXJTX7amL0Cs+KLNrGV8p9DRwdH/9tkQL+FUCPLKmEiZwfOFpcvT+uvwympqyxYTirQfF9IpE+KUfpSjIEvFXIvPJyoULMloX5+DXS98v+cA8tbK0ICa37fJrCN2vAwkgkDBBHyWpgWFDW6n4V6I5NJjQjKPwPdZKVifZQYOfRgCQj/HSrDHk/Q26rzuE+igMJO0Ao1GL8gqQ/zREgAhpFLfgEaHR46kNAKn6NfIYrSxbBY2Gdu+EmJ69pJVhW2oTCZXE2toa3WsUnt+kwHq4tHBGTM5cTAoB7/keNXBscgH0YWsJWAHLEgHNMuUO7wcOS+uz7r+9vWKm9lvyeLlLE6XFSx9jG/6V0CLFW0rl6Mf8kQZ04cxJnTveD+G66NMpiMD9JbXipKk0tONFCt3YyLgCLssoaSrD5G7RLHAHwA9FNR/LHU1+VMCnrqOZU/DI9bCE9vKvX75rk4bRahoAj7G4ARxxHODx5kRJ7I1t7ON2rG2EgGrr1Wqz5Mdn9ovkdk6XpaFLRWnHe1ybp7l/ADMEYHVS279eXBHrkcFN/o08J/MS9yUoe9JETeRl9D/AvwaOZmnrbU8kAGDJgTqcdaefyNE9EVIAOukXM7XforR66UuwWeUXxPheReu6OZdjR54TO/dc46aJruuDBMBEgdLOCxpgUn68UOAOm8GdEqMzmHNyalzXrHVEWxxDYU2isVX/y+1Q94GnPlHzX6yvtXkL7wPWOKpHbxvMbgKPNbCIiip4rDacHWkdPAI0Fvbdo07B9TrMwdDkpQaba/9cd27RAP6N68VlEUnU8+paVK3bhfsJc0UgmFeUPYOpmAaOdVLu042502cFcpKjXP/6feLWt97Y9TOVFEPkAE34Upq/mWoI5nCtsezM5dlKZmq/JcrAEkEV8OTKZsmJnTRIyN8LkzhnQ0HADvKMexW4A0qeiZkdHXPQ91uOvdy/l/Q8VnIwtJSgsSKNJWktkWmnVM0PDc3f2lpM7NwdlQTpTvwrAQDhF2n2ecTYDC6t5sHHARrhy2gHCM1tG9VTwWMdaOROAB5pvcrvLfe2onks7Hi7KM3exr22vOw0FVapmBOpRFQUK439G+1OiCl7JrfvavtZMTqU0MDRTtD9sh+g8YN33iuuuGynPKWfPX1A7Nu7S9z9yQ8FNmMQHhwAkFbk6Gwi75fr083z0GbqzknfSpuEF+EoaU5ylCc8NZCmlyJl3SHYiY8pp8BSU/J07ho2G6mb9DyYG+4xmE8rxDjwr0+tGVlphipy2o1cLey0jKxZtDrvLzxugEYcAyAkDFtnhrZq0wg4oj6brguULeaqQcMntK4f+rvA30wr4NErwIj5QPt36vihjgbGiHJWFEnOyObVavGKsmfbxIAGjq1ehF5p99l7vy5WMhnxxXs+Jqf80uGj4uN/eL9c/8b9nwoseGwkXxVYSs0l/UGxOVwDy0aSqz+mzdT18ujmFr/0EbiDSF3kBc/ns1JTSYkiSGtJvm+kwQSwBOUQE6NrSp5uXrXNY/utddw8orM90q2C0B2A5fmlkji/UBSpFKWvGzJSOULrODmdIoqrGCV+SEjtJZurzdpHM2iUKQFNwS9WszL7OFrVwT4AyF1Rg7LnFua5loiRDjoEjzBHV4avkkN4oWGUHVV/AMA6TvxNzBfZYtjxB6U6X3Xd8Mc1KHuQOpOfI2qdRuu41tNjKQ0cGwmpH4594GOfEztmpsTdn/pQ7XRYC4kdvQoeaydjsQJgaUWObqR1xBcjnkJbu+ABAuC4Huku6ffWvgrOzl596QNYUmZe0vKUJBUPyNGhnR8iOhip0fGYBsbZDHUtloDxYu5stC2PbbcE8AMwNNP1qPvTxK2Ij5fXXslLM/XEGKW2I3JuuFqMjIbEWjYhxsaj4ss/vYfM0wdI67cR0MKaRF7azaPZcbSzA5dvSlBqSRpyT2Rd7I3KpKZ1mseVmV8UV01fQ8EuV7cc8GI3b/N+mH3hfjKYNiiYzMe93m7Vv7HRPFql7BlIRsVIOq6BYyPh9sOxh3/8pPjs578uHvnun9dpFxk8vuXGN4i7PnpHP5yq43NgYOmGHN1x5z1SEWZqlFA01SMz1tO0kgCbn6a27yRzYVHmsQUxeowAJkjRk6kU5QzP04WGtiI4EeFW59Iv+5iep1PAwq3czBpEtDebpVFHLQMDBXHfE/9ZHDn9ImmpjPS38jgAJD1QQ5RfOpel9H7RsIgnw4TxNoCl2o/K56jub7ReIV5WcwpCgCl8UKkuHXfe/Dmxb+p1jbry5Fintcrwb4yGSAMb9ZZWpxXKHvg3phLks/1HVDyRpu4kkBK4gvwZ506dE1/4yoPi2qsuI/BopEcaSg+SCXtNPPviEfEbAQiW6aTw8KxDovgYPeTwLxGPSMdjRIul6R++quCIHI9F5DGZVJ5U9NBTAnT2Q4lHKiJboJynBCZ06WUJkDZo9YIYGQNxf1yatBHtGY2nCDSmZU5bznaCjDtFMn/n1pYpeIfMbcuLMsp1vVLN50wvaGjjmXOwl6XSzbmDSmd5cV4MDnVGI+X2XBOU4Q9AEVpDrKNAG4l9AIxYx/75+XUxPW2s/+H37xJzywfpfoKbBP0jjZv8V10nHEdBFyE6RtYeeq6Q16OolIjiSt5TIOSXT09w84swaQztgKUxm41fK9CIo5g7ulyngdnc+tNX/0HsnblaTA5u2+jAh7WlxTNidHzGh56tuwyHITTy+SQXFS9LnJ4RA+kRce7UayTLiuQibdb/MGkbwyT71kJ0mvWuj3dNAk89fVBcf109m700U98rxAfJbP0Hv3e7uOPdt8j5PUWBMlfs3dm1uQZ1YAkUJbC0niH7UfYqOTrMaaFQ72eKsb46W2svNC5F4nNsVPCix0sC/6wKB+6Uinn6kKDIzdyaDNCBb2WZXv7xJPk0kcYSLy+YG1Utj1V/W30f5IMsRTBpBjUdpMr/CLCoZqVh7SPX+b8vPS1OLr1IHxl0Zek7E35uZrMzNI1sZi4WQiJO21xIP0kIDx/dFTJ/kz96qYQN4zC+4qng/sKqvM+wpP/sQKPREPPA/QiXjRJ9NBlQBllr9t3sn9YRz84EfRh0tNAHX6FCmlwfvvFxr267+DJJ2QNNKpIJMBA3nyOuO96NKJrH0SydHt9+zwc+I6OmP/H7t4uhdH0E1gPf+r7Av9kZQ+uYpuPfvP/Tm+r1uAi6Pn0ASzxY5ZK+iLEeJHJ0babu+i3i6QT8puRhYCl17hSxK9VGdAZwFcZ7JEaA/ntsfAAAH2VJREFUFBoltxHhngohgJ112qTplwg4GOaSqatEgTJ6Hls08k6bwaM6PoNIdR/WrdrgzimXoAEFmNwwg1comQTyVUuoIoElwUlCl6p/pewTQJQKg0c/Tdb4GEDp5AdBOb/kmr9RTtLlTzPKHvZvRLcaOLoUbtCrAzgeOnJMXL5np/jSn95Z59eIua+sromHH31SDA0NiJtueKMGjV24oACUTDXE0eCdJEfX0dRduOg+Dnnu9FExNDrRtVzjEliSVgQvdGgkJL8gBVrADQJQAMsitEIUGa5GhPsokkB03W16nlaFAI0jCjSOSCV4/+OfrnXFwG/n+FUEII181LyPK2GbC7RUToq5D1XbaHyUEKDElwppLaXZu6qphOYS950BMg3z+aXT+8VdN9/nZFjXdeC/Ojg02rG/NRnEGCbOznC9Esj1xB02YJ/pNGXnMYNj9m9EV9pU7VCgvVANVDso3/vGn0jKHfA3mqOmoYW8vWqq7oVz6sc5SlM4+VUahZfGFiw4dhyWXpCjI01dKFLu2IOvH69f0M4JPnUFollJJLsTIS/9ZE2+spGqWU0So1MQA1728LGMRci0WDDSO0KOGfKz9jN/czevFYJjls8v0EdisafM+2yihuwOnnm2TkvIQJASkcj9qLN32/667DFsyga3ozRvo1K1WAXHNAKNaCa1jNA7ykdl/fMSx3FvhShgR95rpBJ9+dQz4p9eeETs3/Z6HJb3F/wx4evrhBhdNrL5ya6tUprBWZuj3u8OrcP/mLSsG5Z/7wdResQzZGr7LrE4f5y0wETXpFD2xGMbk9AaR0Vo/bQKzeIH7vycmDtzVnzzS58mX8ZdAv6P8Gk0m7D76bz7/VxUYCk1l/R1jwcnNJbYbkY1pM3U/XeHdCNvrldSxMseWqQ8kaALMoMDZIVJa1ki30r4WpUJoaQGBum+RkrHFO1DcMbGC8yrefjVD85n6dyc9B3zaww/+/3d7/267H40uk8slQ5uGmpb+kpx8oKheQSARCYZFNY64vKq+al5PwNQ1FXBpKppxDG3RfpPkgZy77ZrpNYR9xf+MTE6lijYx0FgTj9cEMl95uQrHc0NHwuXRDZPQYwxJrR0K5HW66uUPYlEXPI3cm8aOLIk+nQJAvDH/+kpcfObryfgeGCTBrJPT3vLnpYVsGRzOIDlenFF5Iqia9qpLXthfDxxmJcuLJ4V07OX+DhKd7rGCx6m8HXSViLfLoBYCeouRIEmkyKZHJAfTAAB8LEMYuBO0Ol57K7sD57/tnjshe9uOhzOXC6KyZdkthgcJNGLS6b2S9O1lW+jeZ9Zw6gO0C5wRF/y44M0jP/jfY+qXVuu8/1VphSOuM+gZYOhHfyVUeKxRNrQKHGjhimiGRl5ADxHJ7Zb9uXHTvg3hmLDXftYYsqenbv3iumJjbzcGjj6cbUD1ucXvvygAJ8jax4DNj09nQ5KABqcyjppdKqaSo4M1+ToHbwIHg/VlRRoHp9Dq91ZBe7AFQ5BO2pEeDcDdwBkzp462lFNVavyVNuxtlHdZ7UObSTKm664Tjzy7F9LQMlaRoBEAMdkakNLrAJJdd0L0Mjzg8zfdu3t4jev+S3e1dKSgSVy0OPDJZ5IduyjG+cQ66B/o52AMI80KTzHRkdqVbSPY00U/bkCou9/fPJfJMk3zNW6bG0JgMICXkLED21ZoLFE1h0Glhy0o4GlpbgCsROmWwSkbMXSiIeUQnEMLRJpjyAj+BaDaqhI25LzksBlLl8kmhPSLFHgTrv+b3byhxZ0MD0caHoe89yhbXRSpOmZniUwYx84FRZTA1eKPBGBL2QPSNoeAMgKPXBUc7TaLwNML0Ej+ofMH33mQXHrlbe1pYVuRmWlnovX6+BXXecgIK87d9EfZDk8XE9BZPP6cNGrrhp4Cdz2rlvErVuM5DvwFyWgE8RzyiBGt54g+1GyphIvDgTtSB9LWtelOxKIJwaIKiVry9XYnVl1f1QASxVchilTkuouFooWDP+3ck6srSzJCZeqZkpssP9bpM1UjsNj0wL0PKnBkbaATPclWj8D+Cqy7yOirKFBRAEgHCNN5OhYRJqw94zD/9Gg8anvAcGAmzPDmOu0so1r9tBPvyxue9NHe1LmSfIrzObyohZH2YoQPGgDn2Pmb+TuNHBkSfTpcnbbVI3wu09PUZ9WByUgI8LpQWJoLKG7rC9WwDJIHJb1s+2fLRlIQn5awobku3/O1NszqQOWpqB0mCnxD35t+WxGrJUMYIl9MeRxJtNlgkyXoBhyErgzSBQny+fPiPGpi7w9iQD1BsAoPyZJAX5eHBTh5StJ01oWx4QBKiMpyi6jPDbADXlk/nlfzgAk4mnK4Y7gpNHJ2Z4DjyX6EIzGvE0z2IqgkxbIVQPHViSp22gJaAlYSsAJsMSLBQCTg3bYHC7NXpa96p3NJCApecgPKzW44cDerI0+3lgCRgQ3BUeYqIa4Ffu/IbAim7kgAyvgCoII8QRl2wGwjBGwRGAFrk+v0vPw+TpdQgtJYpBlIX9ADFaupOCtAyI9EhbJ4hUiEzais/H3DtBozkPtdBwn9SB7gMbF+RNifPqingGP8FvGs3Q9AAwCsECZiwaOZonobS0BLQHfJMDA0hhAUT1URwSg7CY5um8n7nPHceKoy1IOal06JwH2fzNreYeqU2BgicCKIkW+L5PWEpHg8yePiLGJKVEolsl3jAIOSAUHEBWkiPBD8896IkhJuzN2SIyQZ7U0Y5MrDJbwe7x05kpx/Pxmih9PBlY6gVwBGnsJPJaKWXKpSIogeP8ktMZRuZv0qpaAlkDgJCCBZe1BVQ8sVaohRM4aATvOOSwDd7IeTgip2UowVesSGAkwsOQc4SkiBEcBPQ959VEGkiGifiGDKtG8ILdzqbiKRCjkVxmVEbyggylToFo3IsKZj9FLYcKMnYySm8vL7xEXv+65joBGnr8KHhvlY+b63V7ifsjlC+Qr2l3dnpV/I2TT3Vl1++ro8bUE+lACiKQH2fvc6XNiaJBSS974hk2pJ3vxtBG4E6GfSBVYphL2wFJqLulz3Q05ei/KhOcci1NwTH6NN/UywBJANg5oHWd3GTQ2mCrxm4swBXNwgYWyQLyCMH1LYEkfBsUCgKVB9B8jcBmmSPDMWsaTjCg8rt9LBNJELqFnUxeU4xvg8ThpIC/uGjeiExkjb3covHE/OGnjRx0r/0aMo4GjH9LWfWoJdEkCyBiEVJMoaUovicxB933lO+L66/bJyPp+jq43A0vzJWCqIWTXYWDJfpbYbpZ1x9xfkLY5mwp8o3g9SPPTc9mQAABMenhcgFwZfo92peZbGSINJFWKxA0gwS9tcFjChw+mcESEs39lLJ6QH0wJ8qtErrp2I8Lt5teL+yF7w+fxeGCz+eBvuEKpE6NEbt/tYuXfiDnxPdjt+enxtQS0BDyQwMOPPilmt0+KL97zsVpqSWgfsf+zn/+6eOpfD4q7P/UhD0bqvS6Yashu5gwsmcOSKYd6hcMSlDylEtF36Mhqu0scmP1Mz4PcwAAzrRSriHDVvxI+lhReIfkUS0XSRtMfQLlcog8LZNkRMutOvoBMKWG5b6t8cEDew+PT4vzCKfI17VwWGKfXuFIuSD/vIIAzK/9GnEcQ5uZUnrqeloCWQBMJvHT4mJidmaqBRlSHthH/bn/3r4r3fvC/iOtfb2gfm3S15Q4zsLQjR2etJANLjgYPCrDUlDy9dcv6Sc/DEeEskSiRnKOw9ROgEsE5WMZilEmKgCXAJLSYCdJ0wcVDLSH8cfRRkR9XhLLhbxo0eqRiPivCLX5MeHmJ7PwbMcbmOGsvR9Z9aQloCXRUAgCFyE0OLaO5IHPQTTe8Qfo+mo/p7eYSQOAOTDfwrRxIRsVIOi7GhhJieiwlZsZTYpr+TY4mxSjtGxqMyTpJqisjS5t333YNpuRpuyPdQUckADN1bm2VwFrng5oksCQfSfjGihCRpMfTZApPi8TAOKEC4qasFvIShqKSACYF6ZB/JYAmrzO45CW36ZUlwGMiNUjcmvOBmnKpmCcPg+7r9Oz8GyGs7s8uUJdMT0ZLoLclAB/Gg4ePig9+7HNSy3jTm99YC45B0MzPnj4gbn/XW3v7JAM6e6YaakSObuaw9JIcHZQ8mZXzAZWOnpaVBKZ37AkkKThrGEGijQLtEworHhks1pYELGXVqqIyRME866A+qBbuj7eDsgR4h68pwCPcB4JQCuSzOjS2retTsfNvxMQ0cOz65dET0BLwVgJ3ffQOcfMN10u/xq/+1d/J4Bge4dZbbpSAkrf1snMSYGBpjFgfEY59MmCnRFodet9y0A6bw52QoyMIAtogXXpHAuzfmM0sB4q8HRldGlHybAKCjCirFm0VNOJqrENjSUt5uFpXajOxR/5fbdiFS2cQs88HAjwibSjfE10QRd2Qdv6NqBSiL4aNz4K6ZnpDS0BLoNclgChr+D1C27id0k/+Avk66tKbElCBpeFXaXBYIlc4gCVA49zRA+KiS/b35glu0VnDVG2m5+m2KA6efUbc//infZkGAKNEkdQ7AChDEJjCQxQFTjvIVIv91eHbAJZffe+PHJ8Dm6y7qXnM51aIVisvhkYmHc/bj4rQMMP9xq5ojaOdZPR+LYE+kMAQUfIgMEYIDRh7/XKq5OhWHJYHXn5NLK0WxX7yvVQDeDiop9fPv1/nDw2TE3qeTp7/vqnX+TacNH8rCkbWXoaIWghlnY6BGF3+Yp1U8HIfA0s6AqVlM2AJrambAsAI8LhygfhvuwTcMisXxPBod0EjZBaPNQ5/aXzUjdR1XS0BLQEtAS2BrkgAL9J/feYl8cg//D8ZlDNMwTkI3kGwDjQH2yYGZPDO+HBC7h9MxQQCd+DHxP5rXZm4HlRKAKAls7zUlUAZu0twy/732R3ydT+AJWCjAShpndjQsY6AHrmvCho5cEcqMAlFGkE7tJfW8e+y6f2u5YnrALM6/B67UaL4e4wYEfDdGJ/HTMQ2u9LwMSw1cFSlode1BLQEtAR6VAKXX7ZLnDx1znL2AJbQWMJvCRHhAJaICFeBJdbNwBIR4RpYWorU852g51klbVdQyjuufn9QplI3DwksASRh1gbIpHUDWBoAkyu/46p/JxAZXKFUjmXKulMpZWg9Q6CHuCvLeUrrWLQElgCPZUrfCb/TTha4LEC7GgQ+zUaBMZCJNlV38s7QY2kJaAloCfgkgeF0Shw6cqyl3gEsG70sYBYsUd5k1QQO38qgcFi2dNIBa4QgjbmFgyJNZtKgBEhA6/jYC98NmKQaTwcgEmbqUDghKNaMuCvTdQ3MqRwr5WxNW4m2ccq4MzQ8IhYXzsisO50i1M/nVmUaybrJdmEDH4qNngWYkgaOXbgwekgtAS0BLQGvJQCeThQEQs1SIJSXhYFlK+ToTiLCvZxrL/c1uX1XoOh5oHXsNeCI63/rNXfY3gbmVI6EDgmwbVTPUbo/mMrHJ2dIA0wm63JOmr5BjA7HymgsIZBxRwbykF+mVxrCCmkco7HkxkS6tNbMvxHT0sCxSxdHD6sloCWgJeC1BC7fs1OcPL3gOXBsNk+mGnICLJlqyEsOy2bz65XjrN0KEj1Pr2kdMd92gntqwJJuGvApnjt9VOa3RtodEKDnCiUJLOPkB3ju7Bl5axkZeOLEblAWiQSBPwKUIOQ3Mvg48wgs5NfE4HD3A2Oa+TfihDVwlJdd/2gJaAloCfS+BHZQnvJDLx8NHO1SPbBU1DtVkSPy20yO7obDsvev3MYZDI/NSHqe1ODwxs4uru2bubZntI4wUXvtmzk+fZFYnD8hwSNcCAAGUWAGHzXlugaARNpGw0fyAkLCyb2jTNsF0iYaQS8xApbhKrBklwQO7PFKe9nO7dLMTI2+NXBsR8K6rZaAloCWQIAkAHP10BCZ1HqsMLA0pm0NLEttkKP3kjiCRs8D7V0zQvCgyPeum+/zfCoAigCP504fk0sGe1YDoa7UGlM6Q6vCwLJI2WGymQticCAJ67cM1AnCh4IT/0aclyYAt7q6ep+WgJaAloCWQE9IQL546YeBpUqO3qsclgAYToBKJy/QFx7/RMNsMp2ci9VYd978ubZM1FZ9qvsQ9QzNI0BkI/Cotum1dVB0gW2hWdHAsZmE9HEtAS0BLQEtgZ6VgAosZfYdyrIDnj8AzCADS3AJwuQJepiglKCCR/g1em2itpI5g8fJbbs8C4qxGqdb+8D9CrquZsWZ12azXvRxLQEtAS0BLYHASeCBb32fUk4eDdy8OjkhRISbOSzN5OhWHJbw9eomhyXoeVaXFy25BjspP3UsmILdZmRR2/ux7odfo908oWk0fB6PSwofu3q9ut+JfyPOTQPHXr3Cet5aAloCWgIkgZ89fVB84csPWspieTUjHvjWDwRylutiLQGmGmpGjj5KJjwATs660wlydKbnsZ55d/YGCTwCNPrh19hIsgCPo5OzZLbuL/Do1L8Rsmmuk2wkQX1MS0BLQEtAS6CrEgDx9z8++S/iphuulxHVJ8+cJS3jMbGyslYjBP/YZzLim1/6dFfn2auDM7C0oxqCKdwvcnSm5wE5dCJZT2TdTXkCrHXbbO23T2Mj+QI8Do9Piwvnz4gxU2R1o3ZBPoZ0h06L9nF0KildT0tAS0BLIKASuO4t/17OLE0gEpHVO2amxCxR81yxdydxOmJpkIMHdPp9PS32o0TWHeaw5Kw7TsjR4Vc3f/KImN21L3By6hZ47CZoVC9CoZAVmZWlvgCPTv0bcf4aOKp3gV7XEtAS0BLoQQn82nv/o/jjT304cPyNPSjKjk/ZCliaydGXz8/L9Hfwewxa6TR4DApo5OsAsnbQ6wQpiInn5mY5MZIUTrLGoE9tqnYjWV1XS0BLQEsggBLYTtpFmKx16T0JMIelYQq35rAcHpgRBUqFF0vEJFF6kMjRYbY+ePYZ8fBzD/pK19OpyGm3dxD4FyvrZUoVOd+z4BH+jU5BI+SjNY5u7xJdX0tAS0BLQEtASyAgEpAUQ1VydJXDEuZwJ6ZwL0/DawCJ4JfLp6/tCNVOu3JYuXCOEsVUehI8xuMRMTHcnL+RZaSBI0tCL7UEtAS0BHpcAnOnz4qnKMr6iZ/8XCxTJPWpU+ekr+P1110pPvLb7+zxs9PTRwT9L1zn3NcRgTsAkN0iR//B89+WF+2xF77r6OJBq4iCNIft5Jt2NJgPlaB1ROk1s7Ub/0acnwaOkIIuWgJaAoGTwMc/8yVJI/MNHQ3s6No8+D8fEw/81d/JugiGQWDMcHqQAGRGPPzjJ8Wtb71R3PXROxz1pSsFTwL4KPi19/0n8ch3/5wCnqY8maAKLKXmUgngYd9LTwaqdgKN5MEzz9Z12asgse4klI1eBI9u/Btxqho4Khdcr2oJaAkERwIAO5/9/NfF3Z/8kAQ9PDPe/we/d7u449238O4tvQRP49ve93Fxx7veaqlZhKbqv977NfHI9/7blpZTr588CN3nSIt896c+1JFTAbAE1VClgohw0lxWgaVhEidtJu3TZbMEghzMZJ4t/Btnxt35Rzsn7jGPpre1BLQEtAR8lAA0ZLMzk+KBv/x+bRRoXUB2festNzoCjZ+99+sC/2C67ecCuayuZi1BI86bkqeIuTPn+lkEW+Lcbn3rDeSKcEBqkDtxwsxhaSZHnx5LSbCxbWJAIOtON8jRO3H+rY4BUzXSRSJtZNCLG/5GPhcNHFkSeqkloCUQOAl85HfeKQEPNGbQqn3wznvF8OCg+MTv3950rvD1e/ixJ+W/J4ggu58Lmy7NABmAUmpoSdt4vQvfuH6WVS+fG64z/ibUj6lung8Dy1QiInMcDw/GxBhl2GFgOU2aLBVYIg9ykuoi606/F4DHYj5H0fDZQJ9qigJj3BZtqnYrMV1fS0BLoKMSAEdhOj0gx5yjrCh/8417HPl4ffBjn5NtYExDFpW/+eY9ruYNTSXyPH/PZTtXg3hYGWZM/IOWFmU5k5FaSKxDQwuwPVSVI/bp0rsSwN8EACS08r1c2I+STeCIAndDjt4L535+4ZQYHBoVnAUoaHN269+I+Wsex6BdRT0fLQEtgToJ3Pq2GyUgwk4EyrB2ra6SaQPaRvxDfZj2AKigsWTgBC0cwOTtDXwkr3/9PhmRbOo6sJuImkb0NM4XZWhwQFx+2S6xj4Jk+LwDO3k9MVcSANk7fFahRXby9+Cq8w5WdsJhCTAJgMlZd8zk6B2cbktDISXh4tkTFGk9I5CqMEjFTX5qdd4aOKrS0OtaAloCgZPATTe8QQK/2971q47NrQ986+9kXbxYDff974uDlL9ZpTK57yvfEUNDAzWtDcDk/6Z/v/vbvynbAmxh7F4qOF9tku6lK9baXHEfAzyqoBEfRp/9/Ndkesl+oV5iYGlIabNJVQbsVDksGVgGiRydr+4owOP8CTE6ORso8Aj/RrgbuC3ax9GtxHR9LQEtgY5KYJmCPlB+gbRpTgr8/KBt/AgBQBRo3FCe+MlTcokfNfAGfoCojwhu5Hhm4HXfX3xHAknUx0sZQTnv+cBnBMyEMGOjjS5aAt2SgPoRhDngQ+d2iqp/8G9/3LHgmW6dO48LYInAHfhYplMxAT5C+FTCxxKBO/CxHCdiawTvDNJx+FjGCCx12scyHI6I8emLxNK5OeLULPL0u75MxFqDgFrj2PVLpyegJaAl0EgCpwjYocxuM3z3GtXFMQA+lC/8xYMEGneJ9FCKfCRT5K94TO7nn2/c/ynJi3fflx8SP3v6RekHyDQnAIqIQkZ7lO/87WPiob/9P7IO+jtEfcGH0ktOPZ6XXmoJtCoBfPSAqxPBM73u/9iqDLgdNGkR+olUgz8ALtVixWG5TjuhsWTfS7V+u+sAj9A4QvMIEBkEs3U8Wi8Tp+eogaNTSel6WgJaAl2RAHwRUVSznN1EYG4G4INZe3UlK05SMM2ppw0aGgS6qAX9wRQNDSWCRxg0os4KkWajsG/g40/+XLyRXspqHYzlZE6yI/2jJeCRBIxI+Z+QZvxKSfLO9yh3D/CIvwG3WWa4/VZZmoGl+bztOCzZ57IVDkuARYDGIIDHVv0bIScNHM13i97WEtASCJQEZrdPStBmfkFaTRKaFta6qMe/Q1lV4NOovkwB/J74iTVND2snkX0F5eYb3yj9LKFlvOnNbxQI2NnqGh1Vvnq9sxJAsJcQ35ea9JvffL1AIBfuVbh1PETacWjY2UWjszPrn9EALGHWtisMLBERDk0lR4Y3I0dn8Aiz9fj0xSIcth/Dbmwv9rfq34ixNXD04groPrQEtAR8k8BNN7yRNINvbNo/NIfQtNxNQQPmguhilEMvH5UBMgCN8GlEEAFM4FjHy5fBIEzVKEOUsg+F6yGtHwDoVym135fu+XjNH1JW0j9aAh2QALTc0JCj4APmcfLdxQcT7n0U0DH9ySc/XNOWy536x3MJMLCM2aAoM7DkoB0sw+F41Wx9vGvgsVX/RghS8zh6fjvpDrUEtASCKAEEtsBnES9baA4BBjn6FAEvKJySDxqdhx99Um5vgEiDSxIm74//4f2SW9ItN2QQ5aLn1HsSgLnanLca+1C0+0RvXE8jIrws8rmcCMcSotMclq3wN7JkI39EhTf0UktAS0BLoF8l8O7fuFncRCZnQQQ9b7nhevEbCnkyzOE/fuKfRTwWF9fu30ug8Sdk9lsTaPPY4/8sPvnH/11cQVpLNpc//OOfiMmJkZqGsl9lps8rmBJgTTgyIhn3tKEdx3586OCexccPloVCUVL0BPNMtu6swqSyjEbCIpGI03MnIpIyOjwqo7+HBowI8FQiKo/FKPoZdUMURY4CbWY7Bf6Nw4Pxlqh4MK7WOLYjfd1WS0BLoC8lwFQ7MtCANDkwZfM+nDDMgV/80zv1C7kvr37vnBQ05ep9CBcMNlsj8Gs7uWFgHyKt2Q2jd85Oz7SRBCQpuokcnc3h0F42KnECqRNEU9Rq0cCxVcnpdloCWgJbSgIwBZ48vSDP2cyht6UEoU82MBLAPcmm6Y9/5v4aQ8BHfucdtf0AjvDN1W4VgblsHZlII3J08FmC97LVYuPW2Wp3up2WgJaAlkB/SgAvaH5J9+cZ6rPqNQnw/QizNLhIv/eNP7HUgiPHuy69IQG4GrBLTDszlll3qhyWxGjZTleb2nYnDnzTNPQOLQEtAS0BLQEtAS2BViSAQK7f/a3f3AQaoZHUZOCtSLQ7bUAX9l4K4sN1C3LRwDHIV0fPTUtAS0BLQEtAS6CJBNKUbhB517kAeCBFJiKvEdSF/Ou6BF8CcIGRrA933hto8Kh9HIN/L+kZagloCWgJaAloCdhKAH6MAIoIgEHGpIcfo6xGFMD1kd95pw6KsZVacA989t6vi4NE+/XN+z/tidna6zPVwNFrier+tAS0BLQEtAS0BDosAQTA/PyZA5JGClRTYARgH8gOT0UP54EEggweNXD04ALrLrQEtAS0BLQEtAS0BLQEvJQAEhUsr6xtiohHMNTcqXPiE79/e1c0ktrH0currPvSEtAS0BLQEtAS0BLQEvBAAl+852My2xVnr+Iur7/uSkoxebZrgTRa48hXQi+1BLQEtAS0BLQEtAS0BHpEAuDuXF7NiG9+6dMdnbHWOHZU3HowLQEtAS0BLQEtAS0BLYHWJICIedZA3vrWG8TPicKHt1vr0X0rTQDuXma6hZaAloCWgJaAloCWgJaA7xIAUFSDnJD+FP6NoO0Bfyei5ztd/j/7gCIcZdubEgAAAABJRU5ErkJggg=="}}},{"cell_type":"markdown","source":"# **RNA 3D Folding: A Relational Intelligence Approach**\nCallum Maystone / SlappAI - 04/02/2025\n\n## **Introduction**\nRNA folding is a fundamental process in molecular biology that determines the structure and function of RNA molecules. Traditional approaches to RNA structure prediction have relied heavily on sequence-based algorithms, thermodynamic modeling, and computational folding simulations. While these methods have advanced significantly, they often struggle with capturing the true **relational complexity** of RNA structures—particularly **how interactions between nucleotides shape 3D conformations over time**.\n\nIn this work, we propose a **relational intelligence-based approach** to RNA folding, leveraging **graph theory** and **network-based modeling** to structure RNA sequences dynamically. Rather than treating RNA as a linear sequence with static base-pairing rules, we model RNA as a **relational graph**, where:\n- **Nucleotides** = **Nodes** in a graph\n- **Bonds & interactions** = **Edges** connecting nodes\n- **Structural properties** = **Graph attributes**\n\nThis approach enables us to capture emergent properties of RNA folding by analyzing **how relational interactions evolve and self-organize**, rather than just predicting the lowest-energy conformation.\n\n---\n\n## **The Challenge**\nThe Kaggle RNA 3D Structure Prediction Challenge aims to improve **structural accuracy** in RNA modeling. Current methodologies focus on **sequence-based** and **thermodynamic** simulations, which often:\n1. **Fail to capture higher-order interactions**, such as multi-loop junctions, coaxial stacking, and dynamic flexibility.\n2. **Struggle with computational complexity**, requiring extensive energy-based minimization and brute-force calculations.\n3. **Lack a relational framework** to understand how RNA structures emerge through **self-organizing interactions** rather than isolated sequence constraints.\n\nBy leveraging **relational intelligence**, we aim to **augment** existing approaches with a more holistic, graph-based perspective that naturally captures the **hierarchical**, **spatial**, and **dynamic** aspects of RNA folding.\n\n---\n\n## **Our Approach: Relational Graph Modeling**\nWe structure RNA sequences as **multi-layered graphs**, where relationships between nucleotides define the emergent structure:\n\n1. **Graph Representation of RNA**\n   - **Nodes**: Represent individual nucleotides, enriched with attributes such as type (A, U, G, C), position, and chemical properties.\n   - **Edges**: Capture interactions, including:\n     - **Backbone connections** (sequential nucleotide links)\n     - **Base-pairing** (Watson-Crick & non-canonical pairs)\n     - **Coaxial stacking** (stacking of helices into stable structures)\n     - **Flexibility zones** (bulges, loops, and junctions)\n\n2. **Dynamic Classification of Secondary Structures**\n   - **Hairpins**: Terminal loops forming at the end of a stem\n   - **Bulges**: Single-stranded nucleotides disrupting a helix\n   - **Internal Loops**: Unpaired regions between paired stems\n   - **Multi-loops**: Junctions where multiple helices converge\n   - **Dynamic Flex Points**: Unstable or flexible regions influencing stacking & folding\n\n3. **Interactive 3D Visualization & Analysis**\n   - Using **Plotly 3D Graphs**, we generate **explorable RNA structures** to analyze and validate our relational model.\n   - This visualization allows us to **observe emergent patterns**, such as coaxial stacking, hierarchical folding, and spatial constraints in real time.\n\n---\n\n## **Why This Matters**\nThis approach has the potential to redefine how we understand RNA structure formation:\n✅ **Captures emergent complexity** rather than just minimizing energy states.\n✅ **Models RNA folding as a dynamic network**, revealing self-organizing principles.\n✅ **Allows for real-time visualization**, enabling better interpretability.\n✅ **Provides a flexible framework** that can integrate with machine learning models for predictive analysis.\n\nOur hypothesis is simple: **RNA is inherently relational**. By modeling it as a **relational intelligence system**, we can extract key structural insights that traditional methods may overlook.\n\nThis notebook is designed as an **open collaboration**—we welcome insights from computational biologists, RNA experts, and graph theorists to refine and validate this approach. 🚀\n\n","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19"}},{"cell_type":"markdown","source":"Below is a **high-level end-to-end pipeline** for **RNA modeling with relational intelligence**, showing **where we are now** and **where we can enhance** as we progress. This pipeline focuses on **utilizing relational graphs**—not brute-force or purely energy-based methods—and is designed to be **modular** so each step can be tested, validated, and refined independently.\n\n---\n\n## **1. Data Ingestion & Initial Graph Construction**\n**Goal:** Load raw RNA sequence data and 3D coordinates, build a preliminary graph.\n\n1. **Load `train_sequences.csv`:**  \n   - Extract `target_id` and the corresponding `sequence`.\n   - Keep associated metadata (e.g., `description`, `temporal_cutoff`).\n\n2. **Load `train_labels.csv`:**  \n   - Filter rows by `target_id`.\n   - Map each nucleotide (by `resid`) to its **(x, y, z)** coordinate.\n\n3. **Build Graph (T0):**  \n   - **Nodes:** each nucleotide (`resname`, `position`, etc.).  \n   - **Edges:** \n     - **Phosphodiester bonds** (sequential backbone).  \n     - **Base-pairing** (A-U, G-C, G-U wobble).  \n   - **Store** node attributes (`x, y, z`, `resname`), edge attributes (`interaction`, `weight`, etc.).\n\n**Validation Checkpoints:**  \n- Print **node count** = length of the sequence.  \n- Print **edge count** = backbone edges + any base-pair edges.  \n- Inspect random node to confirm coordinates are loaded.\n\n---\n\n## **2. Secondary Structure Extraction (T1)**\n**Goal:** Identify and classify key secondary structure features (stems, loops, bulges).\n\n1. **Detect Stems (base-pair continuity):**  \n   - Identify **continuous** base-pairs forming stable helices.\n   - Mark these edges as **`type=\"stem\"`**.\n\n2. **Mark Unpaired Nucleotides:**  \n   - Any node **not** in a stem is **unpaired**.\n\n3. **Classify Loops & Bulges:**\n   - **Hairpins**: Single loop at the end of a stem.  \n   - **Bulges**: Unpaired nucleotides within a stem but not symmetrically matched.  \n   - **Internal Loops**: Unpaired regions in a stem, but on both sides.  \n   - **Multi-loops**: Junctions with 3+ stems converging.\n\n4. **Create T1 Graph (Filtered):**  \n   - Keep edges for **backbone** and **stems** only.  \n   - Mark nodes with classification: **stem** or **loop** or **bulge**, etc.\n\n**Validation Checkpoints:**  \n- Are the **stem segments** correct (consecutive base pairs)?  \n- Do the **loop/bulge counts** match expectations?  \n- Flatten to a **2D representation** (like a dot-bracket) to confirm correctness.\n\n---\n\n## **3. Visualization & Inspection (2D & 3D)**\n**Goal:** Confirm we’re capturing structure accurately before adding complexity.\n\n1. **2D Flattened Plot (for debugging):**  \n   - Place nucleotides on a line (index-based).  \n   - Draw arcs for base pairs.  \n   - Color nucleotides by secondary structure classification.\n\n2. **3D Spatial Plot (Plotly):**  \n   - Use **(x, y, z)** from `train_labels.csv`.  \n   - Only display **stem + backbone** edges, color-coded.  \n   - Color nodes by **nucleotide type** or **secondary structure**.\n\n**Validation Checkpoints:**  \n- Do we see **helical patterns** in 3D space?  \n- Are loops/unpaired nucleotides visually separate?  \n- If it’s messy, check if base pairs are **over-detected** or coordinates are incomplete.\n\n---\n\n## **4. Relational Intelligence Layer (T2)**\n**Goal:** Add logic for **dynamic folding** and **spatial constraints**. We move from a static map to a **self-organizing graph**.\n\n1. **Introduce Stack/Coaxial Interactions:**  \n   - Identify stacked bases in stems (like a short-range alignment).  \n   - Mark these interactions with `type=\"stacking\"`.\n\n2. **Define Rigid vs. Flexible Regions:**  \n   - **Stems** = rigid.  \n   - **Loops, bulges** = flexible.  \n   - This helps when we model **movement** or **folding** over time.\n\n3. **Temporal or Iterative Updates:**  \n   - We can simulate **folding** by applying **forces** (like a force-directed model) and letting the graph find a stable state.\n   - Or we keep it purely as a **static** representation but highlight how **loops** might be free to shift.\n\n**Validation Checkpoints:**  \n- Are stacked regions aligning in 3D?  \n- Do rigid/flexible definitions match known RNA physics?\n\n---\n\n## **5. Tertiary Structure & Advanced Features (T3)**\n**Goal:** Incorporate **long-range** or **pseudoknot** interactions, handle **multi-domain** RNAs.\n\n1. **Detect Pseudoknots & Non-Canonical Interactions:**\n   - Not purely nested base pairs, might require separate logic.\n\n2. **Incorporate Experimental Data / Additional Constraints:**\n   - If we have known **covalent modifications** or **binding sites**, attach them as additional nodes/edges.\n\n3. **Multi-Domain Handling:**\n   - Some RNAs have **multiple separate folded regions**—we track each domain’s structure and how they connect.\n\n**Validation Checkpoints:**  \n- Are pseudoknot edges conflicting with the existing structure?  \n- Do we have **loop entanglements**?\n\n---\n\n## **6. Final Output & Applications**\n**Goal:** Provide a **fully relational** model of the RNA that can be used for:\n\n1. **3D Visualization & Folding Simulations**  \n2. **Structure Prediction** → Compare to known structures for **TM-score** or RMSD.  \n3. **Mutation Impact Analysis** → If we tweak a base, how does it shift the graph?\n\n---\n\n## **Enhancements & Gaps**\n1. **Refine Feature Extraction** → We might need better logic for **hairpins vs. bulges**.  \n2. **Incorporate Stacking Energetics** → Evaluate energies to rank possible stems.  \n3. **Dynamic Movement** → Possibly integrate **force-directed** or **energy-based** simulations with the graph.  \n4. **Validation Tools** → Cross-reference with known RNA structures (e.g., RCSB PDB) to ensure predicted structure is realistic.  \n5. **Scalability** → Large RNAs might be complex, so a hierarchical approach (domain by domain) may be necessary.\n\n---\n\n### **In Summary**\n**We ingest data** → **Build a raw relational graph** → **Filter for secondary structure** → **Flatten & visualize** to confirm correctness → **Add advanced relational intelligence** (stacking, dynamic folding, tertiary constraints) → **Output a final stable structure** or a **model** that captures the RNA’s relational logic in 3D.\n\nThat’s your **relational intelligence pipeline** for RNA. The focus is on **incremental refinement**: we **validate** at each step rather than jumping to a complex 3D model that might be wrong or unmanageable.\n\n**Any part** that’s not working as expected, we **debug** with more logging, flattening, or partial displays. Once stable for one RNA, we **scale** to more sequences.","metadata":{}},{"cell_type":"code","source":"!pip install ace_tools_open","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-04T01:36:45.574685Z","iopub.execute_input":"2025-03-04T01:36:45.575111Z","iopub.status.idle":"2025-03-04T01:36:50.918996Z","shell.execute_reply.started":"2025-03-04T01:36:45.575084Z","shell.execute_reply":"2025-03-04T01:36:50.917444Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"# Re-load the files after execution state reset\nimport pandas as pd\n\n# Define file paths\nsequences_path = \"/kaggle/input/stanford-rna-3d-folding/train_sequences.csv\"\nlabels_path = \"/kaggle/input/stanford-rna-3d-folding/train_labels.csv\"\n\n# Load the datasets\ndf_sequences = pd.read_csv(sequences_path)\ndf_labels = pd.read_csv(labels_path)\n\n# Display basic dataset info\nsummary = {\n    \"Sequences Shape\": df_sequences.shape,\n    \"Labels Shape\": df_labels.shape,\n    \"Sequences Columns\": df_sequences.columns.tolist(),\n    \"Labels Columns\": df_labels.columns.tolist(),\n}\n\nimport ace_tools_open as tools\n\n# Show first few rows of each dataset\ntools.display_dataframe_to_user(name=\"RNA Sequences Sample\", dataframe=df_sequences.head())\ntools.display_dataframe_to_user(name=\"RNA Labels Sample\", dataframe=df_labels.head())\n\n# Return summary\nsummary","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-04T01:36:50.920928Z","iopub.execute_input":"2025-03-04T01:36:50.921363Z","iopub.status.idle":"2025-03-04T01:36:51.213180Z","shell.execute_reply.started":"2025-03-04T01:36:50.921314Z","shell.execute_reply":"2025-03-04T01:36:51.212070Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"import networkx as nx\nimport pandas as pd\nimport plotly.graph_objs as go\n\n# Load RNA datasets (processing only the first sequence for now)\ndf_sequences = pd.read_csv(sequences_path)\ndf_labels = pd.read_csv(labels_path)\n\n# Select first RNA target for processing\nrna_target = df_sequences.iloc[0]['target_id']\nrna_sequence = df_sequences.iloc[0]['sequence']\n\nprint(f\"Processing RNA Target: {rna_target}\")\n\n# Create a directed graph to capture RNA structure\nG = nx.DiGraph()\n\n# Define base-pairing rules\npairings = {'A': {'U'}, 'U': {'A', 'G'}, 'G': {'C', 'U'}, 'C': {'G'}}\n\n# Add nucleotides as nodes with sequence positions\nfor i, nucleotide in enumerate(rna_sequence):\n    G.add_node(i, resname=nucleotide, position=i, target_id=rna_target)\n\n# Add sequential phosphodiester bonds (5' to 3' direction)\nfor i in range(len(rna_sequence) - 1):\n    G.add_edge(i, i + 1, interaction=\"phosphodiester\", weight=1.0, direction=\"5to3\")\n\n# Identify base-pairing interactions\nfor i in range(len(rna_sequence)):\n    for j in range(i + 3, len(rna_sequence)):  # Enforce minimum loop size\n        if rna_sequence[j] in pairings.get(rna_sequence[i], {}):\n            G.add_edge(i, j, interaction=\"base-pair\", weight=2.0)\n\n# Process RNA structural data (3D coordinates)\ndf_labels_filtered = df_labels[df_labels['ID'].str.startswith(rna_target)]\nfor _, row in df_labels_filtered.iterrows():\n    res_id = int(row[\"resid\"]) - 1  # Convert 1-based to 0-based index\n    if res_id in G.nodes:\n        G.nodes[res_id][\"x\"] = row[\"x_1\"]\n        G.nodes[res_id][\"y\"] = row[\"y_1\"]\n        G.nodes[res_id][\"z\"] = row[\"z_1\"]\n\nprint(f\"RNA Graph Created with {len(G.nodes)} nodes and {len(G.edges)} edges.\")\n\n# Visualization function for 3D RNA structure\ndef clean_rna_3d_visualization(G, target_id):\n    \"\"\"Enhanced 3D Visualization of RNA Structure with Clear Coloring & Depth Effects\"\"\"\n    \n    # Extract node positions\n    node_positions = {\n        n: (d.get('x', 0), d.get('y', 0), d.get('z', 0)) \n        for n, d in G.nodes(data=True)\n    }\n    \n    # Define color coding\n    nucleotide_colors = {'A': 'red', 'U': 'blue', 'G': 'green', 'C': 'orange'}\n    edge_colors = {'phosphodiester': 'gray', 'base-pair': 'blue', 'stacking': 'red'}\n    \n    # Prepare edge traces\n    edge_traces = []\n    for u, v, d in G.edges(data=True):\n        x0, y0, z0 = node_positions[u]\n        x1, y1, z1 = node_positions[v]\n        \n        color = edge_colors.get(d.get('interaction', 'phosphodiester'), 'gray')\n        \n        edge_traces.append(go.Scatter3d(\n            x=[x0, x1, None], \n            y=[y0, y1, None], \n            z=[z0, z1, None],\n            mode='lines',\n            line=dict(color=color, width=0.1),\n            hoverinfo='none'\n        ))\n    \n    # Prepare node traces\n    node_x, node_y, node_z, node_colors, labels = [], [], [], [], []\n    for n, (x, y, z) in node_positions.items():\n        nucleotide = G.nodes[n]['resname']\n        node_x.append(x)\n        node_y.append(y)\n        node_z.append(z)\n        node_colors.append(nucleotide_colors.get(nucleotide, 'lightblue'))\n        labels.append(f\"{nucleotide} ({n})\")\n    \n    node_trace = go.Scatter3d(\n        x=node_x, y=node_y, z=node_z,\n        mode='markers',\n        marker=dict(size=30, color=node_colors, opacity=0.8),\n        text=labels,\n        hoverinfo='text'\n    )\n    \n    # Create 3D figure\n    fig = go.Figure(data=edge_traces + [node_trace])\n    fig.update_layout(\n        title=f'3D RNA Visualization: {target_id}',\n        showlegend=False,\n        scene=dict(\n            xaxis_title='X Axis',\n            yaxis_title='Y Axis',\n            zaxis_title='Z Axis',\n            xaxis=dict(showbackground=True, gridcolor=\"rgb(200, 200, 200)\"),\n            yaxis=dict(showbackground=True, gridcolor=\"rgb(200, 200, 200)\"),\n            zaxis=dict(showbackground=True, gridcolor=\"rgb(200, 200, 200)\"),\n        ),\n        margin=dict(l=0, r=0, b=0, t=40),\n    )\n    \n    fig.show()\n\n# Run the visualization with the cleaned-up function\nclean_rna_3d_visualization(G, rna_target)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-04T01:37:12.466555Z","iopub.execute_input":"2025-03-04T01:37:12.466904Z","iopub.status.idle":"2025-03-04T01:37:12.896610Z","shell.execute_reply.started":"2025-03-04T01:37:12.466878Z","shell.execute_reply":"2025-03-04T01:37:12.895380Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"import pandas as pd\nimport ace_tools_open as tools  # or just display with print if needed\n\n# -- STEP 1: Load & Inspect Data --\n\n# Paths to CSV files\n\n# Load data\ndf_sequences = pd.read_csv(sequences_path)\ndf_labels = pd.read_csv(labels_path)\n\n# Debug checks\nprint(\"Sequences Shape:\", df_sequences.shape)\nprint(\"Labels Shape:\", df_labels.shape)\n\n# Display sample data\ntools.display_dataframe_to_user(name=\"Sequences Sample\", dataframe=df_sequences.head())\ntools.display_dataframe_to_user(name=\"Labels Sample\", dataframe=df_labels.head())\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-04T01:36:51.634316Z","iopub.execute_input":"2025-03-04T01:36:51.634798Z","iopub.status.idle":"2025-03-04T01:36:51.918602Z","shell.execute_reply.started":"2025-03-04T01:36:51.634754Z","shell.execute_reply":"2025-03-04T01:36:51.916799Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"import networkx as nx\n\ndef build_rna_graph(target_id, df_sequences, df_labels):\n    \"\"\"\n    Build a directed RNA graph for a single target_id:\n    - Nodes = nucleotides\n    - Edges = phosphodiester bonds + base-pairing\n    - Node attributes = x, y, z for 3D coords (if available)\n    \"\"\"\n\n    # Extract the row for this target_id\n    seq_row = df_sequences[df_sequences[\"target_id\"] == target_id].iloc[0]\n    rna_sequence = seq_row[\"sequence\"]\n\n    G = nx.DiGraph()\n    \n    # Define base-pairing rules (Watson-Crick + Wobble)\n    pairings = {'A': {'U'}, 'U': {'A', 'G'}, 'G': {'C', 'U'}, 'C': {'G'}}\n\n    # Add nucleotides as nodes\n    for i, nucleotide in enumerate(rna_sequence):\n        G.add_node(i, resname=nucleotide, position=i, target_id=target_id)\n\n    # Phosphodiester bonds\n    for i in range(len(rna_sequence) - 1):\n        G.add_edge(i, i+1, interaction=\"phosphodiester\", type=\"backbone\")\n\n    # Base-pair interactions\n    for i in range(len(rna_sequence)):\n        for j in range(i+3, len(rna_sequence)):  # minimum loop size\n            if rna_sequence[j] in pairings.get(rna_sequence[i], {}):\n                G.add_edge(i, j, interaction=\"base-pair\", type=\"stem\")\n\n    # Attach 3D coords from df_labels\n    label_rows = df_labels[df_labels[\"ID\"].str.startswith(target_id)]\n    for _, row in label_rows.iterrows():\n        resid = int(row[\"resid\"]) - 1  # convert 1-based to 0-based\n        if resid in G.nodes:\n            G.nodes[resid][\"x\"] = row[\"x_1\"]\n            G.nodes[resid][\"y\"] = row[\"y_1\"]\n            G.nodes[resid][\"z\"] = row[\"z_1\"]\n\n    print(f\"Built graph for {target_id} with {len(G.nodes)} nodes and {len(G.edges)} edges.\")\n    return G\n\n# Example usage\ntarget_id = df_sequences.iloc[0][\"target_id\"]  # take the first target\nG = build_rna_graph(target_id, df_sequences, df_labels)\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-04T01:36:51.920199Z","iopub.execute_input":"2025-03-04T01:36:51.920874Z","iopub.status.idle":"2025-03-04T01:36:51.982401Z","shell.execute_reply.started":"2025-03-04T01:36:51.920837Z","shell.execute_reply":"2025-03-04T01:36:51.980243Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"def extract_secondary_structure(G):\n    \"\"\"\n    Identify stems, loops, bulges, hairpins, etc.\n    Return a dictionary of classified features.\n    \"\"\"\n\n    # 1. Identify base-pair edges\n    stems = [(u,v) for u,v,d in G.edges(data=True) if d.get(\"type\") == \"stem\"]\n\n    # 2. Track which nodes are in stems vs. not\n    stem_nodes = set()\n    for u,v in stems:\n        stem_nodes.add(u)\n        stem_nodes.add(v)\n    unpaired_nodes = set(G.nodes) - stem_nodes\n\n    # 3. Simple logic for bulges, hairpins, loops\n    #    (Can refine as needed)\n    hairpins, bulges, internal_loops, multi_loops = [], [], [], []\n\n    # hairpin: single unpaired node flanked by stems on both sides\n    for n in sorted(unpaired_nodes):\n        left_is_stem = (n-1 in stem_nodes)\n        right_is_stem = (n+1 in stem_nodes)\n        if left_is_stem and right_is_stem:\n            hairpins.append(n)\n        elif left_is_stem or right_is_stem:\n            bulges.append(n)\n        else:\n            internal_loops.append(n)\n\n    # multi-loops: nodes in stems that connect 3+ other stem nodes\n    # Build adjacency for stem nodes only\n    adjacency = {}\n    for u,v in stems:\n        adjacency.setdefault(u, set()).add(v)\n        adjacency.setdefault(v, set()).add(u)\n\n    for node, neighbors in adjacency.items():\n        if len(neighbors) > 2:\n            multi_loops.append(node)\n\n    structure_features = {\n        \"stems\": stems,\n        \"hairpins\": hairpins,\n        \"bulges\": bulges,\n        \"internal_loops\": internal_loops,\n        \"multi_loops\": multi_loops\n    }\n\n    return structure_features\n\nstructure_features = extract_secondary_structure(G)\nprint(\"Secondary Structure:\", structure_features)\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-04T01:36:51.983692Z","iopub.execute_input":"2025-03-04T01:36:51.984015Z","iopub.status.idle":"2025-03-04T01:36:51.994833Z","shell.execute_reply.started":"2025-03-04T01:36:51.983989Z","shell.execute_reply":"2025-03-04T01:36:51.993368Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"def flatten_rna_2d(rna_sequence, structure_features):\n    \"\"\"\n    Creates a simplistic 'dot-bracket' style or arc representation for debugging.\n    \"\"\"\n\n    # Initialize with dots\n    flattened = [\".\" for _ in range(len(rna_sequence))]\n    \n    # Mark stems (base pairs) as parentheses\n    # We only do this if they form a neat i-j pairing\n    for u,v in structure_features[\"stems\"]:\n        if u < v:\n            flattened[u] = \"(\"\n            flattened[v] = \")\"\n\n    # Mark hairpins (H), bulges (B), loops (L)\n    for h in structure_features[\"hairpins\"]:\n        flattened[h] = \"H\"\n    for b in structure_features[\"bulges\"]:\n        flattened[b] = \"B\"\n    for l in structure_features[\"internal_loops\"]:\n        flattened[l] = \"L\"\n\n    # multi_loops - just label them as \"M\"\n    for m in structure_features[\"multi_loops\"]:\n        if flattened[m] in [\".\", \"(\", \")\"]:\n            flattened[m] = \"M\"\n\n    flattened_str = \"\".join(flattened)\n    print(\"RNA Sequence:\", rna_sequence)\n    print(\"Flattened 2D:\", flattened_str)\n    return flattened_str\n\nflattened_str = flatten_rna_2d(rna_sequence, structure_features)\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-04T01:36:51.996281Z","iopub.execute_input":"2025-03-04T01:36:51.996858Z","iopub.status.idle":"2025-03-04T01:36:52.028723Z","shell.execute_reply.started":"2025-03-04T01:36:51.996812Z","shell.execute_reply":"2025-03-04T01:36:52.027472Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"import plotly.graph_objects as go\n\ndef visualize_rna_3d(G, structure_features, title=\"RNA 3D Visualization\"):\n    node_positions = {\n        n: (d.get('x',0), d.get('y',0), d.get('z',0))\n        for n,d in G.nodes(data=True)\n    }\n    \n    # color logic\n    color_map = {\"hairpins\":\"red\",\"bulges\":\"orange\",\"internal_loops\":\"green\",\"multi_loops\":\"purple\"}\n    \n    edge_traces = []\n    # Plot only backbone + stems\n    for u,v,d in G.edges(data=True):\n        if d[\"type\"] in [\"backbone\",\"stem\"]:\n            x0,y0,z0 = node_positions[u]\n            x1,y1,z1 = node_positions[v]\n            edge_color = \"gray\" if d[\"type\"]==\"backbone\" else \"blue\"\n            edge_traces.append(go.Scatter3d(\n                x=[x0,x1,None], y=[y0,y1,None], z=[z0,z1,None],\n                mode=\"lines\", line=dict(color=edge_color, width=2)\n            ))\n\n    node_x, node_y, node_z, node_colors, labels = [],[],[],[],[]\n    for n, (x,y,z) in node_positions.items():\n        # define color based on classification\n        c=\"gray\"  # default\n        if n in structure_features[\"hairpins\"]:\n            c=\"red\"\n        elif n in structure_features[\"bulges\"]:\n            c=\"orange\"\n        elif n in structure_features[\"internal_loops\"]:\n            c=\"green\"\n        elif n in structure_features[\"multi_loops\"]:\n            c=\"purple\"\n        elif n in [u for (u,v) in structure_features[\"stems\"]]+[v for (u,v) in structure_features[\"stems\"]]:\n            c=\"blue\"\n        \n        node_x.append(x)\n        node_y.append(y)\n        node_z.append(z)\n        node_colors.append(c)\n        labels.append(f\"{G.nodes[n]['resname']} ({n})\")\n\n    node_trace = go.Scatter3d(\n        x=node_x, y=node_y, z=node_z,\n        mode=\"markers\",\n        marker=dict(size=30, color=node_colors, opacity=0.9),\n        text=labels,\n        hoverinfo=\"text\"\n    )\n    \n    fig = go.Figure(data=edge_traces + [node_trace])\n    fig.update_layout(\n        title=title,\n        scene=dict(\n            xaxis_title=\"X\",yaxis_title=\"Y\",zaxis_title=\"Z\"\n        )\n    )\n    fig.show()\n\n# Example usage\nvisualize_rna_3d(G, structure_features, \"RNA 3D with Labeled Features\")\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-04T01:36:52.031648Z","iopub.execute_input":"2025-03-04T01:36:52.032149Z","iopub.status.idle":"2025-03-04T01:36:52.157857Z","shell.execute_reply.started":"2025-03-04T01:36:52.032086Z","shell.execute_reply":"2025-03-04T01:36:52.156289Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"def detect_coaxial_stacking(G, structure_features, distance_threshold=3.5):\n    \"\"\"\n    Identify coaxial stacking by checking distance between consecutive base-pair planes.\n    \"\"\"\n    # This is more advanced & depends on local geometry (vectors).\n    # For now, just do a simplistic distance check\n    pass\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-04T01:36:52.159868Z","iopub.execute_input":"2025-03-04T01:36:52.160259Z","iopub.status.idle":"2025-03-04T01:36:52.165567Z","shell.execute_reply.started":"2025-03-04T01:36:52.160230Z","shell.execute_reply":"2025-03-04T01:36:52.164096Z"}},"outputs":[],"execution_count":null}]}