PDA

View Full Version : Maximum number of defined neighbours per LTE cell



esoestemp
2015-06-17, 09:59 PM
Hi experts,
I need a help concerning the question in the title - it is about ERAN8.1/SRAN10.
I found in HUAWEI documentation some explanations, but look at them below:

"The eNodeB preferentially selects and delivers neighboring cells whose Cell Measure Priorityis set to HIGH_PRIORITY(High Priority). If the configured number of neighboring cells exceeds the upper limit defined in 3GPP specifications and multiple neighboring cells are configured with the same priority, the eNodeB randomly selects some neighboring cells for delivery"

37825


From this I can understand we can define times more than 3GPP limitations, but the delivered amount to UE is the 3GPP restriction.

What do you think?
Is there any difference between Idle and Connected mode?

http://www.finetopix.com/image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAx8AAAHPCAIAAAC9Z/D0AAAgAElEQVR4nOydd1gUx//439JU5ARFRREFRAEVrFhjQw2oUWxgN8ZYY9TkE1vsDRUVRFEEKRqxIKjYsQIKUYFQrnmXu83EmCca9bHka3nUH/Ds74/dK8AdLMfR1vfrP5a93dnZndnXzLxnFmgEQRAEQRDEeEBNJwBBEARBEIRXoF0hCIIgCIIYE7QrBEEQBEEQYwI0TcfGxkYitYmIiIhFixZNmzatphOCIIhx PHHH6dMmXLw4MGaTgiCIFXF6dOni9nVtGnTunTpAkhtwsXFxcrKqqZTgSCIcWjdujWWaAThMb169Vq/fn0xu5o8ebKbm1tubu59pHaQk5MzdOhQLy vnJycmk4LgiCVJTs7e8aMGY6Ojnl5eTWdFgRBjI9QKKxXr54Ou3J2diZIbaJv3769evWq6VQgCGIc/Pz8HB0dazoVCIJUFWhXdQO0KwThE2hXCMJv0K7qBmhXCMIn0K4QhN gXdUN0K4QhE gXSEIv0G7qhugXSEIn0C7QhB g3ZVN0C7QhA gXaFIPwG7apugHaFIHwC7QpB A3aVd0A7QpB ATaFYLwG7SrugHaFYLwCbQrBOE3aFd1A7QrBOETaFcIwm/QruoGaFcIwifQrhCE3/DKruR5WSJluXspRFlCRTWkxqigXSEIn0C7QpAKIs9JS8sv/xVfWzDMruT3Th3cHx5xKCrqUGT4gZhLuSUvmBLdOLI/LPzgoaioQ5ER4Qeiz2dzSQ2Vn7TWz8vDy29tUj7F7QKUeckxwZuWzQv4skfbhhZdg 7p/J0yPzkmeOOyeQE PZ2szDssuybndvQKYkD6OcLBruR348P37Q8/GBF5KCqKzfcDsck6HkajJrPqrrnqj17FZ5NnX47e8fOShfMWLF4RGHUlR6/TK3JvJkTu2rhy6aL5c fMW/j90hUbgvbHXcwQa 6dMvt8TPjByOiY2MOHY2OiIg Gh4WG7AzaviMoOCwq/mqWrEK7ITUOB7viZYmum0Vafi8h4kB4xKHomNjDsbExMdGHDh4IP3pDRBFCFPcTIvYfOBgZFRN7 HBsbEz0oYMHDhy5Jqz6i6sMlc2YqnIAHWfKOLZr3Q/fThza1aEh1OsenMUpdQnh 8LYOxYbE30o4sDekF1BO4J2hYYfSbrNoRPGGBhmV5JLawOGerU1A4aG/TfdKF5tK7MOLxnr3c0OAMCyff Rs/ekckiMMiOwK3vIroEZ3DJAnhG1fMaXTqbMz3rs0Z31irsxK2eP7ylg9nJbk1IlnVeGpJ8jHOxKcmltwLDeThagornnYL FERmlLtWoySzjYIrcW9cyK/g6L/GbKsxRHRjzbLLrG4fZQTEadFl4Iqd4RabMSdo a4BTAwAAsLBz69nfe/hw7/7d2tkyD3T91n0XnswnhBDZrd2zfHu1MVUfzcrO0alt8/rqPz1nR91TcN0NqXE42BUvSjQ/irT0ysYpPn1dGmhuRZchY5ccyVISQqTJm6f79nXW3KZmnoP9FkXX7mJW6YypIgfQgTR5 6IZo9yZ/DXteyCXy2 ubJzqo1UPmtm2dXZu20x9j y8VyVVvf5WYmRQem5ea/UD5TI3Pq9UYrNCe5lAu5 ucS6PeUcn2gIAgO3Eo3ncL0KZvqUzAADU6x2WU8bRo4YypaPjhttV8 QbmH4OcB0ZlCTOYN/pFgMP6nsMjZpMHQdT5p3b9d3obs2hnue2DM59kDp/U3U5qgvjnY26G9QNAEDg2NHTvbWlqpg4LjyvLgyU8NyqQU2Yst/Bf3NCpnZ/KiVJjV7S3wZAMOqwUL1VeHgk20AQfHVESAghsvSD0xzZgzceHZtXkd2QmoTryGCdLdF8K9LabzyzvmElOmJkFxe2Yf5XzyuUS 9KTWOUjKkCB9ANdS oCwAANBgaxTm1ouMTmzJJazY5XkwIIbLUXT7WbHLb/5Bc1T35lbAr2dUfnUFDE9 Q9BLOkhc9vCF0XJ9WAZWRZcSHbg89lVGx687c3Y156PuHlyG26pdO583pVdVmMiz95cPVrmRXljgx98PKNyZf/27GTGapg8kufdcWAAAaDo/mWhT0/qaqclRPMox0NtFx/1ZtpkRnKgghhMpP/N6NqXl77WNrZfntoKHM02jm cNZ3c2o7LC gvbaFZPk9Nctmbvb1P 4iNlGZe3tzzbJ2iy8KKvAbkhNwtWu6myJ5luRJkSWvFR9K2JL3Ar5zVWuUOH3f41ihIypEgfQSVZoDwAAEIwomfNlpO68ynjtZiRKmG2i4/6scVkMjqjq 1QJu5Jf 6mdaQtvX d6bN6aeixNEmnvITzylaBep013qnyQM3tvTybDhkSWkWGiuHE2AADgUfU90saGs11d/V875m4IRh8Rlr9/lSC/tsyFaRZNYpoMVfSb2osibftI3y0p6t4o c2VHZg21CkxIYRQWeG bPeS6496m1DihNm9x0Rq9cZqGsgtpiew1QWRJExnOzfaL78ur8BuSE3C2a7qaonmWZEm2i4hGHO0xK1Q3N7Qkf3fyMOc3/91nepzgGyVXVWgEGiKjv3ss1Jmm/hkANNlB45V38isjF1dX 5i5vh9UvKWQVYqeW3mF6YVFSCM87M28dhSrKOIkqRGrfDv79rSRtC4ubPXmKURqex1y/Pv3jwXF75t2TcjvXpOP66Vh5KUyGX Azq3adbYqpHA1qFjf//lEZfT0tNvp968npotIyRnfx8TAICGw6JychJ HuNpbyMQ2Dp5jV99KltzcnH8JCZjPXfclaSFL/R2ayEQ2Nh3HDIr6FKxzgNl3qXQxWP7d3Ro1rhRI4Gtg3u/sYtDLzOxf5QsN Pa2aP7t/44faiXX3iWOHnr2I7NbT0Xn9OVfkouvHfjbGzI2oX A3v4RWQJL28L6G5v3ciqSWtP36UxdzkbPVe7kt9gXuMA1mPjRDr30JVMWV7G1dOxe9Z95z wm29oRt6lbZO82jSxsmrS1isg8IqYIrLUsNl929pYCZo5eU1Ym5CjLOueyW/9zLTjWs1KEBFKLsrOklCEEKLIStgyc6CrncCykcDOpa//mhNZqtuj6zcP9D4RZd0hQzO9Cu8flRM92hrAeuj2VDkhhCjvBvViAxY8N1VglFrTeG71zRmVNuWEezcovo3jbkhNwtWu6myJ5l Rll/7iX1b24w/VuJWKNM3d2b/N469TQphRnJibOi67ycP9XD9KiqPEEqWc/tKQnTI iVTvD08p5/UOoaejJScXzF68GDvocOGDx8 fNhQ78HeATtuyQghsstLXC0ae9TxFCZDcC/YcMHDzE29t7yKChMw6o3sF6X7b637Wl0P/CJoY6QJm3WoM0NWLpqK4OTQTWds49vfswQRTWfnFaqS0zceo2LUDrueekhBBC5Z Y2QoAAJymRmdWeRdLpexqRXszx 8vy5TZR6a3VeWtmecP51QPjejYeBtTj0D1mDuVd2aNjz1A08FLQqLCN052NwMAEAzbdUdBSHbUhI72jdmjNNa0DURnlniaA4DNkGWHzl48vsWvJWjRdFx0NiE5B/qaAgCYdZ7o61hP /9WX 7PVJ1ekjC9BZOzk6d7WWnvBebdV6h6EOR39vjZAwDYjVx7 PyVxL0LvZiwmQ5z4/Moeeo2Hxdbc/ZnXddsGdMcAAAcFhzVkX5F u6RbnaqqBsn/3Fu5lonBTOvrVxfrVztSqGq0aDpxOO66mJd2UxlHRzX0U4VsWk3ZJCTQGDdSJ2PdqN/mNmjqZV1Y3VMoGBEZDal52Di5B3 rpoITwBgi4T49LxOjRo5dO0/wMtFoMqBbmtvyvX95sA 3U9E2XfI0EzXdS2VvX UNCs9Nfnk7nm9G5vZj9ySrLIa4eFRbA5ouqy5IEtWNZ7tv01iqou8hEXuJgAAtqP3q94MHHdDahKudlU3SzQvi7S6Mw6ajDuSI1dqdIBSym6tZ/uuVKPx4sT5Xm1VQT6CEbH5RJG 27d984bsppaz1K0c/RmpFKaeiVz Bfu2sp8eeurKXSlFSP4xf1sAMOm6KU1BCCXJuHQieKo9gMB77ZHkLBkp 2Wr711bkjJf2IQY4gDl3WrViZM2jHI0rddywPSlK/43z6 LKrHQRO215SaOKFLWMAEZ0Kj37GXLl8we39ehgWWrrqO D71SLTM6K2NXN1Z0MHP8/rKMECK7vqF/I1UGNBuzl5FX0fEJTUw9d9xlLkR5f5 PAABMe 1ilk2Qnp1tDwAAjosuMWqjjjFQ9yUrUtd7Mnm/8gbT7M/YwcRYNRq85eS5y7dFFCEkN7w/0xVQr8PX4SkSSn7/6LdsK6ORjzpYQRMf6jg MClbQUlvx3zXja0BLIcfzCaEUJlhQy0BAKx8IrIp9jpXsveo4yomDbkRg9lfWdj18Js1e2LPFm4/JOtMPyEkN3wAU4DrtZu297qIUmSfWuLBTGYw67e/jCh8bTjblfqBKqM7XncyIwYxF2XWZWliHkWonLgZrdg76vRN7H05IbLr63ow dxY04IocTAqPzkqZO1YJqObfLky9EBYaEhkspAi TGj3PyicihCiDI7NoCxUugWdI/S/xsdSeV0hwzMdCPfP WdzR6gjW3/nxLzKEKygrupcnZpRUIrNV3drefE7g3o5eluXx8AwLrbjNBb0oruhtQknO2qLpboMn5Uh4u0/PpyFyiXpv4n1BIsv7GiPQAANJ awJ5dPULPvjoJIWVlJCGEiI6x0dmqLjNlxm5VEKXT9 y7U3R8YlNwUr1Jy3/Z6syYYnB4YVfUAbjdanHS9x1NAMBjzU25KimRE5sVy10OiSOKlLXskcGmvWcXDzcHAYCpwK69l /sradzqj46qFJ2tbKDmfpSlNlHv3ZS5a2Zx LTQoqIjk9oYtaFfUao 8G9TAEAWqnGQNXzAEz7sk 0uiZRN nzY3yZO6aOlcqPHSEAKB7eprIrk16qFRk0zQzNIg2SxJnMc911l7o/S35zNduh2/Lr0xJCsg8MZB5brUA8yelZbH9Zd YpUXc9tJ7HdDjKRXlSSmf6CSH50V8ycq7KCaLMCGSUEUp0meqn4nbVYlqCvrpYZzLVMf8eW9icFh2fyPTGOiw4z9wxRSr7uGpNH9BxMHWEp353EB0bzxxbtTqGnt UPjqnO2Rgphv5/kmTty2YPW/e1 P6qycuQ vZZyUkK9SL/VPVucQNTeBHq9mns28nRu/fFx6TcCtPYdBuSE1ScbuqYyXaiEWaEFIbirT8OutKYDVoXeyphITE02fOnD179uyZ0wknD3zrxPxPPTJICFHeYccLHRaoJgurp9m56Fl1sXRGkvxY9oXTZuF5GSGyK0tdANg t6YT4/IJIeKE6XZmrivYiEoOL1udGaMNlxd2BR2AU 1NZYV7NwQAcP7xquaxUcVdsS7IJXFaRcduJnONiszD33Zgu3DbzUuo6jDGysZdac8/kt3aOkTVrwnWw3ak5Byb0MSs6877jFsmfcu4JZhYNWlm16pVy bWrH83HhbB5IfyzqZOAKAVG6Lub2o lY0HvhvUox4AmPYM1ETKqezK8stolXFlhXRnDu61VzV3Vt1q0LIrIj033wEAAFpMTxATWfIP7OOhtWiZJmCRfY6ER8cwPZUlpyeXTj8hJD/Gl nY7RGqSkneIW9mBSLtLtMyqXjcleqB0oHOZArj/JiL6rTxNpOxkrOz2TFqde2YE8YEuNX3Vk8f0HEwmSo wbnkpFdZ5vnILUumj zXqSV77ztvZm6jnt UOjq3O2RgplfZ/ZNeXdeHXXPKaWmyTBNaad5/b/Hp24q0HT5uTs7t2nfo0KFDhw7tXZyd3Hy3MeFaWvPHyhxR5LgbUpNUPO6qjpVoIxZpQkhtKNLqniitubilzlMs4l2ZvoXpvXZackVtV wLx/XnW9p2VUZGEpIdPoQZ5nVbdVOWd2ScbUOvdQfnMkNxFv13ZSgliTPszDutUR2Rw8tWZ8Zow WFXUEH4FR7ixOmMQE8mh4vopkzyHYCckkcUdxazdqV1iis8Lg/W/dafLEvq2rHByuzIkPyUicTVbgYA5UXP99VPbrfdtxC78ZmXXdlEkK03KbRoI1xCQkJCYmJp88knUnat5xqiMQOZh1MT4y66u9qoPAGDmPn1b9OF9Pw1rBgCCfj9f1nokctm4q4bD1XaVs5/ZZNJH3dMrTpjK9Llq25Wqt9ekR9BdisguLWJHj7XmFVL3WSsuZVddgu4Xuz060q zKKv636Db7szyM5qQCtiVus ujOBlnckUxY1lggTc17GtCnUrS1MXq7rULTXjrbru2eXFTBnS1CmESK5un DeCABafjFrXfiJ8KlMe0VV8HT RsfRud0hAzO96u4fyT8yWqC5vpxDPmwoheWw8BJFXCHJuZtydudoduKw5dD96h1kF9k57uoFXHTCcTekJuFsV3W1RBuxSBNCakOR1ohukwklo9oVaevcmf9pD6oo0thoLGf1zGD1CJbbWlXXVHkZSQh1dyfTVVOvx9bELb0aNvePy1fcCfRiusTbLz17fLqducf6VHV3UPkvW50Zow2XF3YFHYBT7Z0fPZwJTSu26LcqmIJtL3JJnFZUe6vZZ1VFR5mxVRWuUaqpYGwqY1cXF7atV6rEK9JDRtiCFt1YSdWIv/6LUuq645TkRugkp3pg2byVfRsXzwHjvgs6k1V8kEOlUvW9D6kaYDlhvU0AAMy UPd4i06wS11o2xVrymZe29KV2h3EbTTrPioz2AaIae QTIows0wBQKtjuaz058f4MN3Q3dVjlPkxPsx4p6ZjrRwqvt5VyW4L5d39U8etTZbpS6Z6vQqtuphtZTktvqxu6fauB1Bs6R0dB5OeX8D8UDVySogidUOXegAAbj/flBOttkdPNgd0/Ebn0bndIQMz3Uj3T5G b/bsA8WX1JacYbq/rf2OCgkhkrNzVUGg7RefL/3SVKSqKmvt 6hZvK/JBJ0RzhXaDalJKr7eVR0r0UYs0oSQGi7ShBDtV1jjYjPXCNGefKDlqZppkw7zVVmgHp11X8fIUPkZSQhRpK1nhhhN2njYWrgtuyojhOTG DH63KhjZ4G2XHF52erMGN1Xq/ FXUEH4FR7q1ekajg0PFv1elVPybSbeVrCMXFaczy1 q40imzeP7T29l1Jz85uBc2nnCrVOBaf 6mbZraIun9HelbVmdfYp9SiYwzK2xs7sblxWp0bt0MndTBv0C/kvv6cyNnnVQ8AwGJQhEqlsoKZkUGLQeo1w9RdTlpdruLTs 0BTDsvOcdchuzKUuaGmPTYrpJr1biwmVcgMx1BXRI9thZfOEtX jV9zppWUe5BpsFoUuba8tpwtStNj2nJYMW8KJ9mHVffUuhLpvAoO47gtpYtpepWlrpqULcytOYK6DiYOhGaictqIe22LUNJiCI9eJgAAKCe174cfb/RfXROd8jATDfS/aOy9vRuaD89LlfzxMpvrekMAGZdV7KxBFT KXUTz3586O0SNYSmU9tOs2SV1rwM1SLsOuG4G1KTcLWrOluieVWkmXSqx7W0ckv9P1Wso1YTX9N3Zdp13S05IUSeHubHiofqrpSfkczxVausQIOBe 4xuSQ9N59d2A5AW664vGx1ZkwxOLywK oAXG41dT kHxtT5jQzNktJCFFkHf/ek mnUwUfckicpvNU5WSEEMXtLWyPn 34mJyqlavK2FVezAgBNPA qONhVGZGT1Hddo2BKDL2qJeht 7h/ PWPXuDtyz7eljfyTHsMWQXFzItesFo1Yps0nNzmXa4WTOn9q5ubu7u7u7uHTt28uzRf/Si8DQZIVpfwoFuqs5URepapu1fzytE1TxRfwkH6ntM2xydmBQf9oO3XcO2vmvPaD5BqbwXNpJp8Tl cyyHIkSZeWhCMwAw6bg4STXFJdjLhLn7JbxZR/oJyQxh1E9TyVF3t7MG35nrMmtc7UoT0dOgz/Lwo8dOnDxxPC7mYOj21bO8rBqwkas6k5kTzs4wUvfjC1WDWTbj2JaaOlxaM31A18Hk15ezDYv6ncd8/c3MJTH3heoXvlnbPt59Oti1YOfYqoJIdfxGqfvoHO6QoZlurPvHdFRZes0LS85VEEp86 AcDwswc50eob0agiIzdkF3dpaNoMuUTXG3hMzBFHnXYpYPUn3MRmv5vNxDX7L7m/ffq7/dxXE3pCbhald1tkTzq0gTQohIfSug6/YSC1KLTqj/111rREMYN9aG3Wxu197NqallS083ZuBL1X8oKTcjCSFaY2G2/sfUFYI8ZZ0ncyXuq4tFcZX/stWZMcUp/4VdYQfgdKvzT8xQf1/HrEV7dydbS7vuXkyHlpVvTB7HxKnHCwCaTTqWTxFFzpW9sz0tAADMPRaU/OZrFWCYXQmPTXFrplozxKKJ25RjpVrIspTtw6wBik0OIJQ4OWiSpzrqDQBA4PbVmnNCipDsyDHtbOtr/tHI3jswTUFkycs9iq1gpY1p981Xz//Up6WlZlP9Ft0XJUm0FsEHaOTgvS1NQUj23t6Wtj0He9iod27QafKuq ISmUyJk7f7ewgAAOq3cnFpaQFg2eGrNcx6e/KULd4OWmtlmQjs 624IiO6038rJWiYQyPNNgtbz28TxER26XtH9Sa7gZtvlb90Nie7kl5e3rcx6MduSrxYVzJTfj0wyqmxiXqbecuhgYeX9W1uorVb2zHRuUR8anIz1RYrx5EHrkbovGdEnrp9uLpruM3UmCwlkV5Z3p1tzJi5TdlzLmqMKqUW9iPCsygdv9HzRJRzh4jijkGZbsz7R2VF NlrP7VWrj5Lii10p0KRdXr7nC872aqyur5AYMl elTg5DXim5/Dzt6TEUKI9NySns21kgdgKmjhMftUiYE/jrshNQ4nu6rTJZpPRVp0YnqnFsXWSDQVOAwLuqMghIjiv/Zo0Uj7f2aC1kPYLzXIb4eMUy/BaOY2KzolTq1hZjYdv44XcchIQgghedE jQCgrdanSgmh7ocOrA8A7ZeXmoBYxstW720oSRnHMNQByrnV7HN/I2iCi2ohsobdFx6 c141Pg7Q0GHE/kyqbJsghMo 8nUHUyiJmY1Tr7H/i9RVFxsfw yKkglz80RSuZKilDKJME8o16WB8tyUs0fCY2 U7DZUCtOS4qIjImNOXEwXqbOUkonyhRKZXEkRQinkMrFQJFMSQmS3I Z0aWzbb 6GHUFBQUE7tgduWffjJE mF0owIjZHKhJJZAolRRFCKRUyiUiqYA4nFMsUFKWQS8ViGUUIUebevJ6tIESecyMhNjLy8OlUkf6OI6Xw9rljMZGRMceSUvO1HjylTJjPnI9QlEImFQuFUqXe9FMykVAslSvUaRNK2MTli6RyJaWUS8ViGYfuK259V3Jhbr5YyixzRykVcrlMKhGLhPl5uTl5QlmZycwXMRuZZIpkcqlIJJUplBR7lfkiOSFEKRMJJTIFpVTIpCKxTKHnnhFCKOnd83GHIqJPJGerir08O/lY1KG4i/dkhBClTMxkgEwiErOPT4nf6HsiyrlDxLBMN/b9o6R3kxOOHDoUe/JShrjcO6wQZiQnxsVEhodHxhw9ee7m/VI/UYhysnPyhGLmpigVMqkoL1dUyss57obUNNz6rup4ieZNkaZk dnZuWyWUkqFTCzMzc6Vsp10wpzcfLFMrmBOJJMIc7NzJZpDKPNTEo9ExSTczFMQQpQyieo8wnyxgmNGEkKU0rzs7JySZVkp07VVK0t1vGzLuQ0cj1EZB9B/q9VQ4jtJcTFHzqTkKQghlFyiyhRhvlCmlSs6bYIQopTm5QolciVFKeVSUX5uTm6 RGcaq45KjAxWB7LkFd0tAJxLBv6q4nZtA05 HnOiuI4MIghSF A6MoggSN2kdtuVklkJQzDqcIleR m5OfYAYO0XWzc R15p0K4QhE gXSEIv6nddkXyj/hZA4DNqH3a89tlN7cPFQA08dl9R/dkAf6BdoUgfALtCkH4TS23K6K4GzHdzRwALF0Gjp85b H8bwJ8utqZgnWPb8JSqnYpsFoF2hWC8Am0KwThN7XdrgghRJGbHLNj5aLZ0yYFTJr zcIV2yLPZX5GYkUIQbtCEH6BdoUg/KYu2BWCdoUg/ALtCkH4DdpV3QDtCkH4BNoVgvAbtKu6AdoVgvAJtCsE4TdoV3UDtCsE4RNoVwjCb q6XVGy zfvlFxyXefGug3f7EqWee1MfGLyPSl BQ/5LKkLdsXDihRBqo0asyulMO101O4NK5YunDd3weKfVm/aERoZfy2L01xASnwzZtvK76aP7u9mawqNvozO17exBPK78eFh4RFRMUfiTsSfSkhIOH3m7NmkpLNnz5xOTDh18njc0cMxURHh w8m3Ktl3w6pkF1R0oykyKC1Py6aP2fO/O W/rz1QOIdSbVqDJWftNbPy8PLb21SfskTK 7HLuzFfn z2877VJk7V0 SEKS64WBXivuJkeERUTGHj8bFxcUxldPBuBuiqn18uVSkvAZrCsQ41IBdSVIOLvV1Zz2KhVu06eXTxcHazZDy5au/ttv1WOY1HC5PAtP/l3YL5J2tgvTqhvYwnyDnkX 8KtPgQj9X02vKbgbFfSm8GTOlkCgLm9Z3/voYN6uzdnctZpxqlq 2iQMiOwK5uVXQOLfUxeemPHqJZgYmPfoiEACL46Iixj50qhyL11TWvhjio6C4IYBge7kiZvmebb31Xz8eBmnkP8vo 5X7VPL5eKtLZSotAb9COsKRAjUc12pcgIn8Z uLq1z/KYNK0eFXnW2e2T3MwAugfd49JikF1c2AZKfmtQ50YNwji/5q0CDqXlMp9zFMdPYj9X7jD/nESpkEmF2RnnNvYWOM4/Vy3f0OYON7uismMCWgKAaafvTmSrP7cpvBLoYwNOS65U3yJheUcnMjlrO/Go5ltF0qsbBgkAbAOOCwmR3z2yZll4ulzfzkPKrRUAACAASURBVAajzDu367vR3ZpDPc9tGZonychnQZBKwXVkUHZliRNTSZn1359T9eliz1p2RVrr0FPoDfoR1hSIcahOu6KECfPaMxVF2 mHs3S0CqRnZ7e1m3BMxOVosuSlTK3TYnqCpMyNGkTHxrfuuiVddWZxwvQWTHqcFl9WqYfk9NfOHqtv1bJP7HCyK/n1lW4AAFa McVrhdyDA5p033m/Oru5ZRnxodtDT2VojE5 a61nPQCATpvuKMvbuTJnvvRdWwAAaDg8ulg2GPUsCFIpuNqV/OYq1 rvUS nIq116C30Bv0IawrEGFSjXcmuLGXdSm bQH5r/Rd9lyVzeqhlyT8w5b/V7LOSMjdqoCT3UtKF6le7JGG6HWtXSzUnlWWl3cmrZXLFza6y9/YxZarh2OLVsCwlbO3uqzXcHZcXNawhAAB4br9blZ4nv7bMhXnMJsXXhWY38lnC1a4UaevcmUrKZlwcp3anMSinIq11GFTosaZAqpTK2JUkJXKZ/4DObZo1tmoksHXo2N9/ecTltPT026k3r6dml1QkSeIMVmWacX2WKUlq1Ar//q4tbQSNmzt7jVkakaoxBNnVH50BAMB jmYYT dG/RegtivnH68WS6/47NIRgwZ7D/fx9fX19RnuPWTE0jNiIk763yjvoV/6 PoMG Kz8FS LCc9OTEmdP33AYN7 ATdEd0KmzfUw8nevq1b79Hfh10XF3OIMi mXDjZVVZIT3YModPcqDu6HZUybqKlaVE/ftWltY1A0MTOqcvwhbGZSiLPv3vzXFz4tmXfjPTqOf24Kmwj50BfU9au0mWS3LupKXcllL6d9R dEEKIIithy8yBrnYCy0YCO5e /mtOaLpC5bd Zhr7rWYliAglF2VnSR7oPYsy71Lo4rH9Ozo0a9yokcDWwb3f2MWhl9loVkouvHfjbGzI2oX A3v4RWQJL28L6G5v3ciqSWtP36UxdzUOrshK2DzD26ONraCRwMaurXtfv2L/RpAScLUr5Z1NnZhS3XTicdauKFlextXTsXvWfec/sJtvaEbepW2TvNo0sbJq0tYrIPCKmCKy1LDZfdvaWAmaOXlNWJuQo2R xrns66tI9VUIBqaovMNyLoG6Cj1FiBFrCiNVFMhnhMF2JTqzxNMcAGyGLDt09uLxLX4tQYum46KzivUD3JAF25BFZReWfW NgDNB28JCQqfONkdzMAAMGwXXfYJ1V29X/tAADAYcF5Tb Tro160diVy/LrxSYJKvNvnNw13ZlNsOPssMRb UqiFKYkhk5vDdCw74/RyZm3tvm6tWrE7tN69FiPhgCmmjyo77UqWcrxYsqFk13JLi1y0py/XmNHj/6 /rOWrNkVc0kVtSlPNVqi5ffjVvi0MYUmbn0HDejpZAUApr33ZFHZURM62jdmj9d4zFEhIcrshLXjPQRQHPs5SVIdO5Myj04IEZ e16lRI4eu/Qd4uaiOadZt7U05IUScvMPf1aL4eaz9DuzTfRb5nT1 9gAAdiPXHj5/JXHvQi9LAADoMDc jyKK9N0j3ews2d85 Y9zM9c rpnX1tsKQgihco/NaAtQz2VyUHzyzeT4kIV9rOq5rrpZy adIrUJznaVvsWDed6a p9g7IrKOjiuo10D9jG0GzLISSCwblRP9Vzajf5hZo mVtaN1eVAMCIym6pI2ddZkZZRIRiYovIOy7EE6i70cULj1RRGqiiQzwsD7UqRut6TebpW3pATQogyY0c3AABoNHjLyXOXb5eaNSw5M4v1L7N B3LLS5by/j4fAQCY9trFmJj07Gx7AABwXHSJKe3qbt22311Ui5TOjXoRJ0xtDsUuQxsqK8y7IVvo1AEPOYd8BOC4UF3j5EUPZ/Yxc50UdD5XQZQ5Z9YMYkuy5dDwbIrTxZQLt6h2ZeahgNagkxbea86rbooREq3MivJvCQC2E2NyKEIIUd4LGSCw//o0M4ygDsVl tyVORdjD4WvG85UW 2 izhx8kRc3Jm7Ml07E1LO0fNjRrn5ReVQhBBldmwAewu7Bd2jCJWfHBWydizjzE2 XBl6ICw0JDJZSOk6C5UZNtQSAMDKJ4Kt6uU3mMg1gI6r2CciN3wAU1XWazdt73URpcg tcTDlH2S9 cQQqh7u3ubgXY8meiEf1uvXZk4nRvRC2e7ytha0q4IIYTkRgxi3MCsy9LEPIpQOXEzWqne79/E3pcTIru rocZAGjP/ONS9omuirT8WsygFHGoHMsrgfoLvZFqCmNVFMhnhoF2lR/jy7SBPFRzVvNjRwgAAAQjYnWGXsrOs5NQAMqf1UHdD 5lCgDQavZZtof4XlAXAAAw7cs qPLry9nyr6UoOjfqRRw/qRmTJDedYez5ceObAFOqDmZThBDqfujAhhZeWzVdTqJjE5hdumpepsqM7b2YKqTF9AQJp4spF84rMijzLoYuDfDu6mRjBiVw/p7Nk8onWnaZqYCsfNV3W3Z17Qi/nWzOKFLWMJWP3YxEVdiGemi4S4m y1I7l3d0bUTH2HvktiaF7VNThQFrB9PpSlL2gYHM26Dj jTVgSWnVY2A7juY6LD86C8tiydbmRHINC3AY0u6Uuuhs kzc 3 U9ezZErJ3Wu38nAyN6If7nYVqLar41p2JTw8UsA hGwVLDo kSkKDgvOM2VWkbqWeebN oezLVoOZZ8QHRUph1rMkBRxqRzLL4F6C702htcUxqookM8MA 1K/aZsPpVZRYm6G9SjHgCY9gwsOSGMgcoM6c32QtuMK28JFWnSt0z7BUysmjSza9WqZXNrthO38bAI1q6u/cT0XTt r2VXujbqRXQygF2RwW1tqq6uW3U6LPrtuqskitQNXcytRzGNIQax6hBalZVmwo2t/wkRp4spF0PWalcIMy4e2blkpLOq99/151vGSXRWxjam2mg2WXcInTpYpNU3Z9R2paqPPHcUt6uSOyvLOzohRJZ5PnLLkukj 3VqySar82b2wZOpngHnH7TrzFJJUgfuQvfgLHWe3d7Qkdmoajrnx/gyCw71CFUNdquXTfMIzKAIIaITAayls5i38ByzukRoCYJoU/G qyYTitlVnB/TFdxp423mQZOcnc10FWlkISesjwkAQH3vSHYeEYeyT4iOipRDLWZIirhUjhxKoL5CT4xRUxivokA LwyNu5JdXe1VHwDAzH36tujD 34a1gwABP1 vqxvhokibQMr8mA9JianzIdNHRDVaNDGuISEhITExNNnks4n387VjN p4y7bfndJVuZGvYiOs 04cFubonNgXHb1pw7MHh5rb4kuLnQ0dZiTpB3lqV4yS7uyUkdLdlybquB0MeXCya6UuVeOJ5aaRqy4E jFtEydllwxTqLV1VLD4VE6Z39Sqga3vapJqmXkJfsuS 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 iQD4vDLYr e3QSR3MG/QLqcAalYqMvV xQ3Eg6PNDfLaOoRNKmi9VEulZVYdxY5 QdN3dSqpArpazzkjK3KgX9QpMpeYMaqUnc 9g1VwYEHwZnlX8csWnpjDKoLWIkyx5aTsAaDv9SA4bp1nuxZQLJ7vKj/Gxaf11QolFceQ313gAANiOj82ljJRo2cXvHJn/WnitTi7tscrbGzux9 G06j6om7Ylh2FL7VzW0YVHvmKbg9sylIQo0oOHCQAA6nntYwdZ1bWozXjtdWlLJ0l2ZSnTR2bSY7tKSVXDl2ZegWyQl7p3X9P zD3ItL9NeoflEEKU6Zu7OkzUjNqo1rn22IgzhRB9cLYr9WTrRuoOKEIIER5lx HUxUkdD 6g tSEuoNF81MuZZ/oqkjLr8UMShGHyrH8Eqiz0BuvpjBWRYF8ZhhqV9Jzc5k X7NmTu1d3dzc3d3d3Tt27OTZo//oReFpetvs0utBYx1VM3Xrtxv69YqgQ8cSz108f ZEVPDaBX5erVsO23ufIoqMPT7sl37Buof/j1v37A3esuzrYX0nx7DPqTpIUbto6NyoD2X6FtVYpSp8TBd5h/3YlLScmVhyL3WHDAj6LDqYnC3Jvbb/m04NrLrNj7mnrirKv5hy4WJXyjubOgOAVfeZ206lS5m5dnmXd0/pYApg6j4nTi2zRki0ImPPl6qOyIYdxyzeHLI/bPf6H1YfZ1aTkV1cyHSmC0arpltSWXv7MQOUJXukSu9cxtE1y6aZte3j3aeDXQt2/rQ6cFR fTnbHK7feczX38xcwnyYTUeSlPfCRjKtbcdvjuVQhCgzD01oBgAmHRcnqe50ZohXveLvDOrudva56bzpDhPV3t7MbnxoKjuZNW3HQEsAwbDgDJQrRB9c7UoTPg1dtmn1S eEszP01MNawiNsV7w6sFU9vmfSS9Wfwqns66xIy63FDEtR ZVj SVQZ6EXGq mMFJFgXxmGBx3lbzcQ72cSUlMu29OK PFIk2LWeHfx7FRqd8J2g asfH4PaYXiRInB03yLLZGksDtqzXnhBRR3An60qmJZkkRM2sn35C0VB0b9X2EU3Z1dX97gan2wS2s2/kf1TndUZI40w4AoPPPpZdtUAeJamjQeUZYagm9LONiuMHJrnJOb57 hTN7FjMra tGJgBg6ew9f 91rS86GifRlPDSlgkdrbT aeE0YutNGcmOHNPOVutj2Y3svTdELfFqof39bAubNoPW35ARXTsHpinKODqRXlnenQ1PNXObsudc1BjV8jQW9iPCsyhC5Knbh6uvr83UmCylvrMQSpy83Z9ZiKt KxeXlhYAlh2 WsMGpCvuBA1z0HpMLWw9v00QE9ml7x3Vm wGbk5O3jSoGQCARQsnNzdHG1MT225TgpLFGMeK6IeDXYlOzfJobglamApaewemyTMPjHJqbKLeat5yaODhZX2ba7ZAo7ZjonOJ NRk9XQLK8eRBzIpDmVfZ 2aoSRlVQhUJVJUTk3PpQTekuso9EatKYxSUdzCBfA LwweGZTdjpjTpbFtv7kbdgQFBQXt2B64Zd2PkzyZQTR9yzIUg5JlpZyPPxIdER4eEXPs7I0smY7XkVKYlhQXHREZc Jiukip akwL18kkckVFEUpZVKRUCSjdG7Ud3KFJC9PJJXJFUqKEEqpkMvE blCPfvLzi9sA5be 3QsYKRu43kGXruecDjqcGKqSG8rRffFcKICcwYpaeaNs8diIg9GxMQlJN TVGmiFXkpZ OiI2OOJ93MYitoSibKF0pkciVFCKWQy8RCkUwuFQrFUpkmtyVCkUypZ2dlWUcnhBB5dvKxqENxF /JCCFKmVgqV1JKuUwiEstVKxRK756POxQRfSI5W17uWYhSePvcsZjIyJhjSan52s0CSiYSiqVyBZNqmUQklCjYw4mYk0rFYuZI8tzUc8eiIyJijl9MF2M7FSkPLn1X8vzs7Nx8kUQmV1KUUiETC3OzcyVK5gFknmfmuRTJ5FKRSCpTKCmKUsikYmG SE4IUcpEQolMQSkVMqlILKM4lf1yKlKdFUIlUlTWYStSAksWekKMXlMYo6JAPh8MsytZ8oruFgDOi88XD25SzRGpIx9W54ji9hYvy5bTT kaalQP7qvXeKkaDFmRQS/VlWgEQfTAdWTQyGDZR5BqwiC7UjLTWASjDpdYt0p6bo49AFj7xXL TnntJ//YFDuLTit1h73nq5Y Vq/xUjUY1a6qK9EIguihhuwKyz6CVBOG9V3lH/GzBgCbUfu0A3dlN7cPFQA08dnN fN5tRfRyVn9RyzasmvLwoG2YDs Vs8CXTn72U8T618j2CgY1a6qK9EIguihhuwKyz6CVBOGfmfwbsR0N3MAsHQZOH7mvIXzvwnw6WpnCtY9vglL4UOhVX8NAaBeu5mHs3Q08xT3YpZMGNROFf5p083Hf3FEVU0TM5ZdVWuiEQTRQ/XbFZZ9BKlODF9NlChyk2N2rFw0e9qkgEnTv1m4YlvkuUw iBUhhBBKeC1qy0/fL16 /WiqjrhwZpfrcZGRUdExMbGxsbEx0YcOHjySXFUflzOWXVVrohEE0UP12xWWfQSpTiphV0g1YtSRQQRBapgaGhlEEKSaQLuqG6BdIQifQLtCEH6DdlU3QLtCED6BdoUg/Abtqm6AdoUgfALtCkH4DdpV3QDtCkH4BNoVgvAbtKu6AdoVgvAJtCsE4TdoV3UDtCsE4RNoVwjCb9Cu6gZoVwjCJ8aNG4d2hSA8RrddtWjRojtSmwgICGjatGlNpwJBEOMwefJkKyurmk4FgiBVQq9evXTY1cCBAy0tLb9EahP29vYWFhY1nQoEQYyDi4uLqalpTacCQZCqAgDmzp1bsu/Kzc2NRmoT3t7egwYNqulUIAhiHKZPn96 ffuaTgWCIFWFiYmJjpFBtKvaBtoVgvAJtCsE4TdoV3UDtCsE4RNoVwjCb9Cu6gZoVwjCJ9CuEITfoF3VDdCuEIRPoF0hCL9Bu6oboF0hCJ9Au0IQfoN2VTdAu0IQPoF2hSD8Bu2qboB2hSB8Au0KQfgN2lXdAO0KQfgE2hWC8Bu0q7oB2hWC8Am0KwThN2hXdQO0KwThE2hXCMJv0K7qBmhXCMIn0K4QhN gXdUN0K4QhE gXSEIv0G7qhtUyK4 PqeEvwmp5x/1/PuZQpgj0vtvBEGqnArZlfGKbMGbf37P/03yLxZ BKliDLKrwuf3ju5a7t/NrrGVlVXjlj2nrQ45lvmisKrT jnD1a7eP4ia7l4fGOp3mnXk9w9a/y18lhY42tGU/beZ48iNN/4tqLI0IwiiD452xaXIfvp9n3dLgZUKm07fp70ueZyid4oLgdMHeg2Z9MOOmKR7/3wouQOCIMalEn1Xr69NbQIANpOSSxVl/RT9J0mR/lfxdH7ucLKroudXFvYZPHfX8QsXT 6Z38sKAOp12yZRNVM/UeHe1oKOYxau3rRu8cRuVgAAJl03/PauqhOPIEgJONkVpyL76trsto1t7VqytB24Jf998cN8oE7M7dSo2fDAO8 xDYwg1UQl7Op91jJHAHBelcO9HVRAwkf4Rv NRbyicLGrT3/Gb4yRqCrWolfXZrcAgF7R/xTRNE3T7 7 5D07/tEn1d4PTwTYAoBg3IWXVZZsBEF0wsWuuBTZT4q93r3W/PZe9xFomv4gO/hVE7AcEizGZhSCVCOVsavfVjgBgMuafK529fGPqJGNTXseQruqMIZEtT8/NcgEmn19i kqLPzn0v7kx9o5/1G8yRUAPEMoHB1EkOqFg11xKbKvU a4eCy7 udbPXXqf78udwOw/DL6TyzkCFKtGNWuit79mRK54tsVV54WvieXdy aPHbCnMCLDz/SNE0XPM3YM741AIB9wIbdwXsOXX30iS56/1da1Ko5yy88/k8Wv2bmhFlbrz4uoGn6w8Mb 1d8GzBu9Ffjpi/ddUGBjS4D7OqDcJ2b7dBwxSe9ezw/ UU9qO97 nllU4cgSMUwbM5giSJb8Mf /uZMSJaN5/g1CbK3RcV2/yjZ1hUAnJdn6e/bQhCkSjCaXRU TQuZ088GAKDrliMrh3fv5zva27UBALiuynpHF74Snvtl//euANB2dkhM7JFTt0W39szt3wQAoPOqnTN6OloBAHQP /OdZPcgQYOemzKeF3z46/xCZwCbcSf/ cy7uypsV 8fhI8fsPjqszLy7UP Whdo9FX8kyL9 yAIUhUYZFclimzR89tBC6eO9e7mwE5kMXGdE/ nZjrgm9tzWwKA25qLZ3ctnjJyYK9 X87cdBYbqwhSHRi37 rvKC8AsBqw8sKjjzRNFz1NHGUJ4LD0PlOeX5z2NgPQGhksenKkLwCYeSy6/O nV/mno J/e/l/95a0BnBcxrS2Pkq3ugNYjb9cgch5PsLdroreyC6F/e r9uYAAM2Hb814qUee3uf83L6Bx4Y8bNUiSLVjiF3pL7If/0kLneZmBgD1PNergt7f3VvSGgCgzZeLQhLSMjOSto9rDQBW3qEPcMogglQ1xo27enlmmDlA9wMPWX1i3WjcJcaNStkV/fLMcHOAjtseaIavCp nbJw6Y/vd10U0TdMfpEEeAKZDEl9U7jrrOhXou/r08k9RRlLYDz5tAADAdsqFZzr8quCvwyNb91if9dbICUUQhAMVt6vyimzRq/SfPU0ABGPPvaBpmi56fKRvPQDz4WfUlee7zJUuANDQ9/jjz3wwAEGqHCPbVZKPhbZdFZC9XQEajDr/iqZpnXaV5GMB0GXPHyVDLovekWv7lvqPGjPeuxmAyaCEFzRNF/yTvPvn5Rp Dr7x5DOJ1TQg7qrodcaqjgBQ/8vEUoFVn0i0X exhxS4piCC1AgVtStORfZd5nJngDY/3H9H03SBYrcHADSfnfZGcxRFcBcAaDzxymc GIAgVU5ttKuPD5OWD3HpMm1v pNPRY9jeqnt6n32MkfQpt3qvM ki9ugL EUPUscZQnQLezP4ptf/7phmM8mtncQQZDqp0J2xbnIvvt1UWtVKEbRP7G9AaDVgnSt3q43ad 2ADDz/twHAxCkyql9dvXfncXOUH/IoYcFNE3TxeyKLnz36vkzDc9fvf9c rcN 87gR/FGV2g09sIrrW3vJQcChv U/PRzyTkEqY1UwK4qUGTf3f/BqcmoRCYW4H3mj20AzL1PPtVI2fvs5Y4ArRZkYEgAglQtlbErpidJu/ oHLtiwrJ6qP ty67e3p7TQt23rbKregPiP/NVAwyzq5cX/Zs1n3zhubpyfS87NH3ogsRHWl2Fhf/eikoi pdtQBDE HC1qwoV2XdZqzw7/uaiTwQ95aVwDrCRc0HVWvL09sDK2/S0e5QpAqphJ29d/NaU0AwG7uHVVJLXryS18A6Lzzd7bkf/p9lweA6cATT5lf3JjWBMBm7C/iB1dCdtx4VkS/SPA2A3BeqVlq H3OKmcAaOEfLXr VJS4IaC7JQC4/JQYv/ew POd3sbFrt4KD/20YOWBlEeM7X58eHpeZ9fpCX r6uW34v2j7Rq5jp41R8W3Xwf4eLZov/hXrGsRpFrhZFdlF9l3v20a2rH7 A3nFO KaLrgWcbuiT1H7PhNE2VFF728tagdmPXcJmbqhIK/fhnVrPXU0xjTjiBVjoFfcb4fF7J6SidmHTvzjv4rdx/L/EsYv2WaqwkAQNvxq8OvEnLt4OqxDgAApu7TNp UvCkqep2 3NMMAMBpcoz8Sc7RDZPdTQEAGvactfnkA6a3quCv41PbsAvk9f/prDR1kQMAWHqtuPY5D2ZxsKuCR3GjbZh8c 0zeFBvry8CNl/5W/0VDSrC1xp04bgs /O1VgSpGcq3q3KL7McHIUOsmHWurJu3aO3x1c nqVJF SM5Ob 7batBCwP3bF/q17P/nBgprneFINVAJfquDKPgv0d//P1fOTP9Pj3/PS9f8Zwxg08vqAd/vfmMzYqmuY4MFr55mHP72pXkmxnCR597jiFIbcawtdpLUvj24W p126m5/zxsozB/aL3/wjv3Ey59 ApThJGkOqi2u0KMQjD4q4QBKmdGMeuEASpraBd1Q3QrhCET6BdIQi/QbuqG6BdIQifQLtCEH6DdlU3QLtCED6BdoUg/Abtqm6AdoUgfALtCkH4DdpV3QDtCkH4BNoVgvAbtKu6AdoVgvAJtCsE4TdoV3UDtCsE4RNoVwjCb9Cu6gZoVwjCJ9CuEITfoF3VDdCuEIRPoF0hCL pvF0VvpacD9u4bOnyzZE3H36ogiQiNNoVgvALtCsE4TeVs6ui13e3 PSeEZp0IfrH3g0ATDot//VN T9DKgzaFYLwCbQrBOE3lbKrt78uaWvecduDTzRNFz45N6e9ue24xH LqiipnzVoVwjCJ9CuEITfVMau3t6eYwfQ9 i/VZY6RAXaFYLwCbQrBOE3lbGrf4/2Bag3IP5FlaUOUYF2hSB8Au0KQfiNYXZV8OR2bOjuDQH2AOD49dbg4OB9J4X/FRW9/ystatWc5Rce/yeLXzNzwqytVx8X0DRN058e34leNzdgzKix034IvkS9KzZ6 OlJxuENC6aM/cpv6g97L9 /uPN/O7PefvzjXHhIcHBwcMiBc398pGn64x/nDoQEBwcHh8aksEct69BF7/5MiVzx7YorTwvfk8u7F00eO2FO4MWHH7VPXPgy58TWRVPHjhodMG/jsZxXhTRd8DglJjSYZe8vvz4toGmafi8/vT84ODg4OCxR9t7gvK4MaFcIwifQrhCE3xhoV8/un4qO3Pm1AwC4zA89dOhQ7Nn05OC5/ZsAAHRetXNGT0crAIDuYX8WFr1K3zCsp39Qsvjh72n7AhwALLzW3/uPsaCCJ5d 9Grl U34DfHDPzLjlvSwAIAGo86/oumiumN3mQAAIABJREFUd4pfxtsAmHmfZnrHCl7l7O5nDtBizm02dF7Pof/f07SQOf1sAAC6bjmycnj3fr6jvV0bAIDrqqx37E/f5Owe4dJjYdxvj18 StvUyxyg3bzLzwoLX4uiJrYAAGi/OvON2gLf3PvJuUHn5beeFtA1AtoVgvAJtCsE4TeVGBks/PtQT4B6A0 pRwaLnhzpCwBmHosu//vpVf7pqPjfXha Tpnr3H7Jr2/ZfV5cmGANAD2Cf/9E0x8fBPezbDI2/nEh 99395c6qOyKpgv DOumZVc0/T57uZOWXZV16KK/o7wAwGrAyguPPtI0XfQ0cZQlgMPS9omqZfpy5oY9Fxo gDeynRfU0AzL0TX9A0XfT88oxmAE2nXnmpvtbHcb7tJ5x9VmMR 2hXCMIn0K4QhN8Y1a7ol2eGmwOwswgZXiSNtjJxmbxiHcvqBYMaA4Dp4Phn9KurU5uATUDya/XeBX EdtXYVeHDA92L21XOKmeNXZV1aJp eWaYOUD3Aw9Zc/so3eoOYDXu0muaLnpyfKgFuKzNV63PVfT2wek9O49kvmB2/vhgR1cAs377/2C6qgqovV 4zb9dg4tNoF0hCJ9Au0IQfmNku0rysQDosucP9fjZ 99WOEHD4ZH3xcWRklcF735d1BrAdZNEEwxVQPZytquyDq1Oi8autA/9Ju3bFtr/K0XR07PjrQFaf5f hqbpD/nru3Vdl1 TS6WiXSEIn0C7QhB U9V29fbO3JYAvSIf6fCYV dHNQRw3Sg2zK7KOjRdtl29vjxeAOC88jf9Iervc1Z3AGgwNPZRwZs7CzsO2PdHDUVcMaBdIQifQLtCEH5T1Xb1UbzRFcB8YORDbTkpfHInSfz2vxtTbQCsxp5XhzeVsqvwHvrtqqxD02XbFRPeBZ23PdCeQ/hBcT5Jru6gKvz7l ENAdotu3Zqktvok09qdpFUtCsE4RNoVwjCbypjV48iegLULkc/Wm0nZFv02f1xIAGvuESd6pfvj00pJxgcIPhQ8j pgA1B8cTqnitD49CHTX2BX9NK4/APQ5olKb/24vsAewnXnrTTmHpsu2K/pV8mQbALAZd yRKqkf5OHT5pzRXmn Tfqi1gD1mtg6zrr2qvz8qFLQrhCET6BdIQi/qYRdfZRscQMAj90KtUu9SPA2Kzni9klxwLshAIBZO9/5a7ZuXjV7iJPTpMTHhTRd DRpsi0AgIPfhuO37t45vH8V6NteyKicyq33/br88 vH5wduOMEV0bAUC3wAw5eVlQ1qHpoie/9AWAzjt/Z83t07PABMB554StM0/UGyo5cZAECroYu2hx8MXj21R ue67Pf0dp8osL6mgE4LcuqmUWutEC7QhA gXaFIPzGMLsqfJH1y6bZfQQAAGDrvThw3/F7f2Qd3TDZ3RQAoGHPWZtPPnin2Ts9cGRrUNFyxI57r1Rrfr76deswW/Yfgr4rLtwL0RoZpOmPisjRzZj/mrSbEp3360pngIYdfBftvfbwg/5Dv5XEb5nmagIA0Hb86vCrhFw7uHqsAwCAqfu0zSclb4rogidXVnxho/plMfL/79qeR1Fj1LHNmie5Cs1D qHbQrBOETaFcIwm8q9RXnilDw6vdfky9cuSN9VlJVit7//duNS9cyH74rKhF3xfz7zR93r165/eBFAU0XvZalZ/71vojrocvlw5P81CvX7sqffdT577fpi7r4xOoJm69W0K4QhE gXSEIv6k2u KGDruqOYqenvb3mHLhRc3GszOgXSEIn0C7QhB U9vsitrTBaC b9LL8vetqiQ8ubZz6aI1YadOB09o321tGYs2VCdoVwjCJ9CuEITf1C67Knp5dVYLAHDbmF9TUlP09PggUyYWy9o7KOdt b oFtCuEIRPoF0hCL pRXb16dHVg1tWr1i fPny5SvW7jhy73nNxDu9VyQFrfp5x7HM5zW6fmhx0K4QhE gXSEIv6lFdoWUAdoVgvAJtCsE4TdoV3UDtCsE4RNoVwjCb9Cu6gZoVwjCJ9CuEITfoF3VDdCuEIRPoF0hCL9Bu6oboF0hCJ9Au0IQfoN2VTdAu0IQPoF2hSD8pkbsquh1duTKn/akPeO45ELha n5kJ 33dK3/4e/0w9vWveL/IPxkljxRFYtaFcIwifQrhCE39SIXb26MLohAPQ5/Ljcj8wUPs8IWzTYFgCgy54/Si9A9eH3E2snupkBQLNZqW9qKJHVANoVgvAJtCsE4Tc1MzL49sGpoMAjv73i5i2FjyJ66rMrmqbpNymzmhnfriqYyCoG7QpB ATaFYLwmzoRd/XyzDDzMuzqQ84q5yqwq1oF2hWC8Am0KwThN3XDrpJ8LMqyq/w1LmhXCILUHdCuEITfGGpXRe/ TIlc8e2KK08L35PLuxdNHjthTuDFhx 19/n0 E70urkBY0aNnfZD8CXqnXqIreB5TkLgwvn7RNqfav7076 xGxYvWDhn vQFG3 5/ /7T58 FRQW0bSWXX16pzi3Y2GA38S52y//pT6X2q7 eys7Ezjf32/8rJ9jMl8Ui0YveiO/FLrsm4ljxvh/u2r/VaJ15qL3f6VFrZqz/MLj/2Txa2ZOmLX16uOCUonkcsFlXUMlQbtCED6BdoUg/MYQuyp8mhYyp58NAEDXLUdWDu/ez3e0t2sDAHBdlfWO2afoVfqGYT39g5LFD39P2xfgAGDhtf7ef0X0 we/rPBrbwoAtl nqDub3kv2 jRrOnyf B1d9CpjfQ8zAADT g2aDY35q5C1K48NsatH9Pb2G ftYg4AndblsYrE2FXT8YGLvZra2NlaAAAAtJmZ Dfb1/X wcHxzs7jQm7/9d9LKnnzMBswdV947nEBTRc Tdszt38TAIDOq3bO6OloBQDQPfj6Ye1Ecrng8q6hkqBdIQifQLtCEH5jcN/V31FeAGA1YOWFRx9pmi56mjjKEsBh6f13NE3Tr1PmOrdf8utbdu8XFyZYA0CP4N8/0TRNv0n52lbbrgoeHhpkDjYBV18zf7McMWwH5hOvt7xq4a9vnpwqNPNE0XPT3tJwBwXJbN6BVjV Awfm/my0KaLniSvLynBQA0mXzxRRFNv89Z38lUMDrhX7YPqejZxWnNABoOO0Q 0TRNFz050hcAzDwWXf7306v801Hxv70sLJXIci643GuoJGhXCMIn0K4QhN8YHHfFRJp3P/CQ7Zb5KN3qDmA17tJrmqZfJI22MnGZvGIdy oFgxoDgOng Gc0TdPvs5c5atvV68vjBQD236lsjDUZj12MjJWKu/r0YFtHAMGEK4zJlI67 iTf3QMABOMvvaJfXpxoDdAr5h/NAN377OVOAOC84rf3zKUMNwfouO3BJ 0LLJnIMi 4/GuoJGhXCMIn0K4QhN8YbldJPhbaslFA9nYFaDDq/Cuafv/bCidoODzyvrg4UvKqgKZp n3OKmdtcXn363f2APW/THjG/F30T0wvALOBv7BLTZW0q4I/9nYFaDjq/CuapnVGtX UbHEDgK57yevbc wA6o8490or8a vTGgMAF6Rj3QdnqFkIsu6YA7XUEnQrhCET6BdIQi/qRK7entnbkuAXpGP9IQblRQX oN4ey9zqD/ogOIjTdOFj0 OaQytv73yvEj7XFp2VVxsdNhV0ePYXgDQbR95fmGMJYDJgONPtROQ WMbAOga oeuw tOZDl2Vd41VBK0KwThE2hXCMJvqsSuPoo3ugKYD4x8qO0rhU/uJInf0rQOu6LpwmfJi9ybOfXy 2bBnIChgyasO/fnhxLnqohdffp9Z2eAJtNu/veOESmHpffU4ec0zWy0mXrjP12HZ6ioXZVzDZUE7QpB ATaFYLwmyqxK/pt ryWANDYJ0yicprCp5eWjAsUfqBpHXZV9DJt5aDhIQ8 ljqN1rkqYFdF/570aQD289P o m3GYtaA0Db/2Vq9OrF2ZENofmsG691Hp6honZVzjVUErQrBOETaFcIwm8MnjP45Je ANB5pypo 9PvuzwATAeeeErTNP1JccC7IQCAWTvf Wu2bl41e4iT06TEx4yZvP31O3sAwfjL7Py6ArK/Zz1oMmD2ig1bt 8M3rMv/NDhkxd /eMNO6r27PgAEwD3wAc6z8XaVf3BB35nzKboxa2lHSw7fJfMfIC58J9TAc0A6g8IkTBzDAsexn5p3WRUzJ/s4V4keJsBOK/8TXv5rZKJLOeCy72GSoJ2hSB8Au0KQfiNQXb1VhK/ZZqrCQBA2/Grw68Scu3g6rEOAACm7tM2n5S8KaILX6QHjmwNKlqO2HHvVRFN058eXQ370dsGAKCh19ydSeQjTdPv8nd/2RRKIRgU NsT8bENk91MAQBaj1q P/kPzbnMOs3Yekr nqbfK86sGe3aEMxdhs1cvHT2iO7dxwemPtMEfRW9FUVMc68PVl0nfL9y2be Xv1nHsj5r4im6aJXOUc3THY3BQBo2HPW5pMP3tE6EinOLf Cy7gGIyzKgHaFIHwC7QpB E3Vfgmn4NXvvyZfuHJH qzsZQne5u/9es7hB// Q0ly7mek3bp6KenU4dBVY53tJ7KrLnDg47MH6ckXLqXkPHqnq7 o6P0/ WlXLt24Cp0aKhtDHKNegF7QpB ATaFYLwm1rwncHCZ5dmt3P9X b7kv94n7lq OI7xlmNs4qp8mtAu0IQPoF2hSD8phbY1bP4IWZg0nHRqQfaMUrv/0ha8dXkg79XTZC4sanya0C7QhA gXaFIPymFthV4YvbG4fZAQCAVWv37r379vXq0r516x6zDgmNFBJe9VT5NaBdIQifQLtCEH5TC yKpmma/vgkOyli2 r/LV7846rNe0 m/fG2roiVhqq8BrQrBOETaFcIwm9qi10hZYN2hSB8Au0KQfgN2lXdAO0KQfgE2hWC8Bu0q7oB2hWC8Am0KwThN2hXdQO0KwThE2hXCMJv0K7qBmhXCMIn0K4QhN gXdUN0K4QhE gXSEIv6kBu/rw953YjevjNGtsltqAlALtCkH4BNoVgvCb6rWrD4r4dRNdTQGgxZzbb3RtQHSDdoUgfALtCkH4TfX3Xf13c0bTYjJVagNSGrQrBOETaFcIwm q367eZy93LCZTpTYgpUG7QhA gXaFIPymBuwqZ5VzcbsquQEpDdoVgvAJtCsE4TeVsqvClzknti6aOnbU6IB5G4/lvCrU t nx3ei180NGDNq7LQfgi9R79Sf3EO7MgS0KwThE2hXCMJvDLarojc5u0e49FgY99vjl4/SNvUyB2g37/KzQpqm6aJX6RuG9fQPShY//D1tX4ADgIXX nv/MYKFdmUIaFcIwifQrhCE3xhqV69TF7Sx6LhR9IGmaZou/Du6rwmAuXfiC5qmX6fMdW6/5Ne37K4vLkywBoAewb9/omm0K8NAu0IQPoF2hSD8xjC7KnpyfKgFuKzN/6Da8PbB6T07j2S KKTpF0mjrUxcJq9Yx7J6waDGAGA6OP4ZTaNdGQbaFYLwCbQrBOE3htnVm7RvWwB0P/CwsPT/3v 2wgkaDo 8Ly6OlLwqoGm0K8NAu0IQPoF2hSD8xjC7en15vADAeeVv70v/7 2duS0BekU 0mFeNI12ZRhoVwjCJ9CuEITfGGZX7 4vdQCAztseaH 95oPifJL8w0fxRlcA84GRDwu0/lf45E6S C1No10ZBtoVgvAJtCsE4TcGRrW/Sp5sAwA24449UjnUB3n4tDln/i2i36bPawkAjX3CJO/Y/xU vbRkXKDwA02jXRkG2hWC8Am0KwThN4bOGfwg2dHLDACg1dBF28MPBq e2qN1z//P3n2HNXX///9/yhCxgCg4KloZljqrgra2rqI460Kl1FWr4KJqWxUpVnGh1oqzaN1aF65SEUE/VkUER4V3VRCFCxDxkvmDwAXkIvkm53r9/kiQQMIKIOTVx 0/c8LJ63BdiXde55Vz1j4qZowxaWKAkzERkYHt6AWrN23wnvuFtfVXF9IVpwqLohZ3JGrleq1AuSu1B0Ad6gqAJ6grAL5pfzVRWUao1yBzUrJ0 unKa2npNnnuXb xVqXbqMOYrfdFAmNMlnF7/49O5kRELRzdNwfGid5UeKBQqOIl/8NQVwA8QV0B8K2Od8IpyXh8O/T6vRfZEvVtMlFCVFhwaMSzbKn6Rqgd1BUAT1BXAHx79/cZBG2grgB4groC4BvqSjegrgB4groC4BvqSjegrgB4groC4BvqSjegrgB4groC4BvqSjegrgB4groC4BvqSjegrgB4groC4BvqSjegrgB4groC4BvqSjegrgB4groC4BvqSjegrgB4groC4BvqSjegrgB4groC4BvqSjegrgB4groC4BvqSjegrgB4groC4BvqSjeMHj16yJAhjT0KAKgfCxYsQF0BcExDXX311VempqYETUn//v1btGjR2KMAgPrRq1cvS0vLxvvkB4CGpaGuBg8ebGFhsQ6aEnt7e3Nz88YeBQDUjy //LJNmzaCIDTehz8ANCCcGdQNWHcFwBOsuwLgG pKN6CuAHiCugLgG pKN6CuAHiCugLgG pKN6CuAHiCugLgG pKN6CuAHiCugLgG pKN6CuAHiCugLgG pKN6CuAHiCugLgG pKN6CuAHiCugLgG pKN6CuAHiCugLgG pKN6CuAHiCugLgG pKN6CuAHiCugLgG pKN6CuAHiCugLgG pKN6CuAHiCugLgG pKN9SqriQ5SU inyTlSCrZnJ34JOZppZsBoMGhrgD4plVdyXPu//Hryml925uZmJiYdXCc4bPj1MNceUOP9b spnUljj80s5sRKRj1mHM8oURlqzw73G98F33lZoMuY9fdyJQ12JgBoDKoKwC 1WHuKv/69NZEZP5VWH7NX08oiLv1rKD24/yvq1FdCTmhiz4d5vHr6eArZ3cuGGBCRM36bo4rnaOSJu1zamXafcIin/Vrlkzta0JEpNfHN7q4oQcPABWgrgD4Voe6Ev zogsR2XjHlFT/ZCVZyr4xow /xjRXbdWkrqQvA9cdiRMr/yWIrs9tR0QDDr8RGGOMFd9b7jQ3ME1a uzUM64WRGQ6OTivwYYNABqhrgD4Vpe6ivayJiK71Y9rWleS5ENjzfQdD6Kuak2bVe0554bqkeU3NxVThfI3Ib Fpav 5iWx6 2JqPeOJJwdBHi3UFcAfKvXuhKKX9464DXPKzRLLk65ut3TbdIUd78rqRLGGJNlRe50sSIi6ujqu91/58FrpbMo0vSIw2s8XCeMmzTje/ QpGJBuTPxq/BD3u4rg9MLngeunj1lzqZr6f/dCtCirkqerPnIYvi RGmlz8g5O6gZGY2 mFPX0QFA7aCuAPhWb3Ulzwrf4f6ZORFRn43HVzn3 2z0eCf7FkRk7/1PMZOLnvx14rfv7Inog7k7jhw9fi4yQ8aYILrrO8Jx2i9hsakJ4XtcOxE177/2fsH/ywrf6fF5ayKint7bZjl2MSEi6rf35X920qvWdSWO3 cyeMm17Cp YyWPf7aj974MzBDqPDwAqBXUFQDf6nfu6vWh/kRkMnhVcJqEMSZkXRjXkqjTsgeKhdO5F50MiFTODObf8rDpujSqSPnP3OAprYjIwT9BypiQcXwgERn08ryaKRU9vngoMDrvPxtXtagrofB5yN4fv xqSETU1nlTZF4l8SSO alri16 /4o1bwaAhoO6AuBb/a67yrs0wpCoX0CqMoMkzzZ1IzKZHKL4VmHFusoNGm iZ fmtUbJZ FQMyLSHxaYzRjLu RsSNR9c3zlp7b O2oxdyXNe/k0Mmjv96M6ExGRxdfB2Rr6Svbq2Fgrh7X/FKlvAoCGhroC4Fs911XQqOaqdSVL2d2HqMW4yyLGmFpdiaO9rMnY cCD2PKepYhkb3f28c7kt6utZG/Ctv 0ssxP/jcy/iNLsbRYdyXkR3p3JyKjkRfUFlZJUw5P7DnpYCIuKArQKFBXAHxrzLoqivDoQDTgQJrmE37qdSV tKILqbL1 bfmV4PQaVrdCUfIvjCuJVHfvS/LP5wf5Tti1Pp7 VhvBdBIUFcAfGvMupLErrMnMhxyIFV1AkqeEREUW8Q01RWTF4tyssvkiMT/lZVY2t1nUBK7zp7emxQsUnlMHBfg6rw8LOu/8psDaIpQVwB8q0tdKWaSVOePqqkrxbIsh7ebi 7O70BEZqP2xpVeL1yeFbJ0st TEqaxrv67tKurvCvTLNu6Bee8naQSPz84c/jCC2kqv1J55s1DQSlY2wbwLqGuAPhWh7oq HtGayJq7xFRujJayDgxkIh6bksovZRVwq 9iPSHnMlS/MSNGa2JzCediI0P3bH1RrYgTQxwMiYiMrAdvWD1pg3ec7 wtv7qguKal7nnnQyIbFZF40ttNauroicHly9cFXArTVG7ktSL83vazzz/ujSlimJ/G9/ Pfvxc9xLzfvGdVTvdl2XRGFtO8A7hboC4JuWd3F cHKHz9c9DImIyLD7tFXbTz189SRw4wx7PSKiD1x89l1LSbm 32dSJyIi/W4zNpyNKxSE/LsrexsQEVm7HUksYYwxee5dv7FWbxdSdRiz9b5IYIIo5g9ft276RETGjnM2nI3/r98LrwZ1JUs7Od6ciIjM7T8dNvST/oNcN4S fnvjm6TfR7ciTbqseIR BXi3UFcAfKvD3JV2ZAVpya8Lyp/sk4kSosKCQyOeZeMEVSVqdmZQXpgac d6aNjfkU/SCrGwCqDJQl0B8O2d1xVoRbt1VwDQNKGuAPiGutINqCsAnqCuAPiGutINqCsAnqCuAPiGutINqCsAnqCuAPiGutINqCsAnqCuAPiGutINqCsAnqCuAPiGutINqCsAnqCuAPiGutINqCsAnqCuAPiGutINqCsAnqCuAPiGutINqCsAnqCuAPhW97qS58dd3rtuxbKVGw78nVrSAEMEhroC4AvqCoBvdasrIf/exlGfzNoVFHz4h09aEOn1WBlV2EAj/W9DXQHwBHUFwLc61VVR1NIPDLtvjpcyxuQZf7l3NbSYfCFTaKCh/qehrgB4groC4Ftd6qrojnt7ooF/ZDbY6KAU6gqAJ6grAL7Vpa4y/xhI1GxwYG6DjQ5Koa4AeIK6AuCbdnUly7hzdNd2X9eORNTlm03 /v57zj4pEATxq/BD3u4rg9MLngeunj1lzqZr6TLGGGPS9IjDazxcJ4ybNON7/5Ck4nJnD6UZkcd8F3496cuJ07/fffXBlW0/bvunSJL8174d/v7 /jsC/kqWMMYkyX8F7PD39/ffdeSWcq9V7VoofnnrgNc8r9AsuTjl6nZPt0lT3P2upEpUX1ieF3Nmk f0SePGu85fdypGJGdMln7ryC5/pd0norJkjDEmfnHxN39/f3//vReei7X XdcF6gqAJ6grAL5pWVfZD84dPrDtm05EZLdg18GDB4/ eTfM3 Pz1kREPb23zXLsYkJE1G/vS7kguus7wnHaL2GxqQnhe1w7ETXvv/Z gaKCZBkhP/R/v/e3 27EpiY/PLnUoTkRtRh3WcSYUJx4wsWcyMDpomJ2TCaK2f6ZIVE79zvKpfOV7Pr/ZYXvcP/MnIioz8bjq5z7fTZ6vJN9CyKy9/6nWPmjhTHbx9g5LDoZnZ6XFr5 gCGR7fyr2XJ5/tNDU9sREXX1eVj4tgIL7y 3adFz5c0sGWsUqCsAnqCuAPhWhzOD8tcHHYmaDTn39sygkHF8IBEZ9PK8mikVPb54KDA6T55/y8Om69KoIuVzcoOntCIiB/8EKWOSeP/PWraeFJguV24tfrCsU2ldMSZ7ubevSl0xJn600lqlrqratfD6UH8iMhm8KjhNwhgTsi6Ma0nUadmDYsYYy7 9sHPz7uueligP5fBAPSJDpwu5jDEh5 osS6I200Pz3h5r snRXaf8md1oK/ZRVwA8QV0B8K1e64rlXXI2JFJ i1AhN2i8iZ6dm9caJZ FQ82ISH9YYDYTXZvemsxdw/LfPluWvKtPWV3JUwP6la rGG bsrqqateM5V0aYUjULyBVWW6SZ5u6EZlMDslnTMg4Pbw52f38uPT6XEJR/MWd244/zFU8WRK/tQ RwWe/JSumqmRJuwd9tOBOI15sAnUFwBPUFQDf6rmugkY1J/p4Z/Lb82fiaC9rMnY 8CC2vGcpIllxlKcVkf36uLLFULKU3TWuq6p2/XYsZXWluuvC8HntVLepEbL dGlFZLX4biFjrOTx2r591jxuzEuloq4AeIK6AuBbQ9dVUYRHB6IBB9I0dIzo8jhjIvt1sdrVVVW7ZlXXVf5VF1Mim1XRlS9RF8f4fEjUYvjRNFlhxKLug/ckN9KKKwXUFQBPUFcAfGvoupLErrMnMhxyIFU1TuQZEUGxRQU3ppsTmUy6/HZ5k1pd7XOovK6q2jWruq4Uy7uo5 Z41e8QliReDnrxdoJK/vqEszGR7Yrr5776aPzZjMa9SCrqCoAnqCsAvtWlrtJ dyRqNuhsztuH1OuKFd2d34GIzEbtjSsu/cGskKWT/Z6UyFN//1SPyGjYvqTSdVrSeL9uZXXFsk5 TkSfHi9Nm4I7CzsSWcy WVjNrlnVdcVEYW7mRGQVRa6VBLXuyb4X5J9UrzhXc9rYiatbboMue6qPrfR4NCXQHwBHUFwLc61JUkbuNHRNRre Lblso972RQ8YybNDHAyZiIyMB29ILVmzZ4z/3C2vqrC lyxuRZQW4WRESdJvqevnkv4vKe7136m6nUlWJlltHnm6OyS/Lj/1w3a0yf94ior1/ki5Q8WVW7ZkLGiYFE1HNbgrLcpAm/9iLSH3ImizHGSuK2DjAgInp/uOeWffv9faY7WDmufVTMVEmT9g40ILJe8U/jXORKBeoKgCeoKwC aVdX8tx/Tqyf 6kpERFZOC3x23P6fvI/f/jSRU5xAAAgAElEQVS6ddMnIjJ2nLPhbHxx2bPv o21olIdxmy9Lyq95qcoatMIC UG04Fewfd3qJwZZEySeGC8pWKrnu3Xh/ NWmVDZPzhaM/d11NLKt91UVzgxhn2ekREH7j47LuWknJ9v8 kTkRE t1mbDgbVygwWUao1yDz0p 0dPrpymtpxeMUsi Mbdfvl dqG9451BUAT1BXAHyr012ca0MmSogKCw6NeJZdMVUE8evoGyHXH6YWCxXWXSk2FybfuxZ6Jz5XxpiQ//zuw1dioaa7rlZJxuPbodfvvciWaNxcdNfz41FHK1k2/06hrgB4groC4Ns7q6ua0VBXjUfIujit19fBuY27nl0BdQXAE9QVAN aWl0l7fyYyGh0UF71z22oIWRc37bMc/Xecxf9p3Tt 3MVF214l1BXADxBXQHwrWnVlZB3bU47Ivpo3ePGihoh6/RQfcVarFZOv8QUVf8T7wTqCoAnqCsAvjWhupKmXdu/0cdr5cqVK1d6/bz1 P2cxlnvJE4M sX7p62nHuY06vVDy0NdAfAEdQXAtyZUV1AF1BUAT1BXAHxDXekG1BUAT1BXAHxDXekG1BUAT1BXAHxDXekG1BUAT1BXAHxDXekG1BUAT1BXAHxDXekG1BUAT1BXAHxrlLoS8h8dWLV8Z3h2DS 5IM9/dnnHT5tvVvb8ktd3j61fc JFSf0NsfaDbFioKwCeoK4A NYodSUKHm9MRJ8eS6/2JjPynMi9nsMsiIg 3pmsfgGqkoQzP0/9yICILOfcLmykQb4DqCsAnqCuAPjWOGcGi LP/eJ3PFpUs26Rp/3uWFldMcZY4a05lvVfV7UcZANDXQHwBHUFwDedWHeVd2mEYRV1VRLjbdMAddWkoK4AeIK6AuCbbtRV0KjmVdXV49V2qCsA0B2oKwC aVtXQvHLWwe85nmFZsnFKVe3e7pNmuLudyVVovocaXrE4TUerhPGTZrxvX9IUvHbU2yynJjzfosW7HmqeqtmaWbUUd8lCxe5z5y5cN2JB5liqVQqkwuMqdSVtDjxr62LXCdO9dhy9dXb13pbVwVFzy/5LZg20WXOT0ce5pZbjS4UvgjZteLbqRMmTJvn/du1FJVXFsSvwg95u68MTi94Hrh69pQ5m66ly9QGWZMDruoY6gh1BcAT1BUA37SpK3lW A73z8yJiPpsPL7Kud9no8c72bcgInvvf4oVzxFEd31HOE77JSw2NSF8j2snoub9194vEJg4/oTXxK76RGTxza23k03iuN2jLNs474ktZoIocq2DARGRvlELy FHXsmVddXL96jPmE cJk52sjMkoh5r/lUmkqKu2rj4Lenfxry9RXMiIqLOsy 8Vs51ieP3u9jYTN5x51VBXlLYhhHmpN9t0V/pMsbkWeE7PT5vTUTU03vbLMcuJkRE/fz/75jqIGtywNUdQx2hrgB4groC4JvWc1evD/UnIpPBq4LTJIwxIevCuJZEnZY9KGaMsfxbHjZdl0YVKZ dGzylFRE5 CdIGWOs8NY3Fqp1JUs9ONSQzF2v5Sv nX9jlgVRx0V3lT vqCvjT5cHp0kZY0LWxYmmRF1WPFLklaKuqJPL7od5csZkGWErHZsTUWu3K7kCY KYtT30Tcefz1TOIQnZV2ZYEhmPOJgiZYwxIeP4QCIy6OV5NVMqenzxUGB0nlxtkNUccLXHUEeoKwCeoK4A Kb1uivFSvN AanKaRnJs03diEwmh QzxnKDxpvo2bl5rVHyWTjUjIj0hwVmM8aY NGKLqp1lX/VxZSo4 LSGlOWTK9fFTGmtu5KGr 5O5HplFBFyaivu5K 2O5ARKYuISKWd2VqK6IBR96UnaATP1ppTUQ2XtFixaE4GxJ13xwvVT3AioOs8oCrP4Y6Ql0B8AR1BcA37esqaFRz1diQpezuQ9Ri3GURY JoL2sydj7wILa8ZykiGWOMiWO8bVTDpThqcUcio5HnsxX/Ft4cGUBkMOSE8lJTFetKlry7D5HxuMsixpjGVe2SuI0fEVGf3Sn5d9zbExmN UukMvj80ClmRNT/QJqm3StUHGRVB1yDY6gj1BUAT1BXAHxrkLoqivDoQDTgQFoly40qhgsrid0ywJCMhgYkShhj8vSzE8zIal5ojqD6Wip1VT5sNNSVkH50ABH13ZOSEzyhJZHe4NNZqgN4 ENnIuqzK1nT7jUPspq6qu4Y6gh1BcAT1BUA3xqkriSx6 yJDIccSFXtFXlGRFBsEWMa6ooxeXaYZzdL6wETv13o7jp86JQ1f70sqfBatakracK2nkStZ/xdUKwIqU7L7r9dfs6Y4kHz6TcKNO1eobZ1Vc0x1BHqCoAnqCsAvjVIXbGiu/M7EJHZqL1xpU0jzwpZOtnvSQljGupKyAtfNdR5R7xE7WVUXqsWdSVknh3VgjouCC9grCjS04qIPvjxYVle5f451pjazrmRr3H3CrWtq2qOoY5QVwA8QV0B8E3r7wxmnBhIRD23lS7alib82otIf8iZLMYYkyYGOBkTERnYjl6wetMG77lfWFt/dSFdUSZFUYs7Epm6XFV v06W8ptjM2o9eK6X76Yt2/x37tl38NjZ4KjkQuVZtezTg/WIuvnFa3wtZV0ZDQtIUJSNkHtz2YctP1wcprgBs/zNOVdLIqPBO IU3zGUpR4d2ar1uCMvlbvLPe9kQGSzKlr18lsVB1nNAVd7DHWEugLgCeoKgG9a1VVRXODGGfZ6REQfuPjsu5aScn2/z6RORET63WZsOBtXKDB57l2/sVZUqsOYrfdFAmNMmnZt7w9O5kRExv09tgWlSBhjxY 3j2xDakyH kVnxJ7ydftIn4jIatzK38KSy17LoMesTedeiBkTJ15aPd7emAztRsxesmzumH79XPxuZ5ct hKKnv4 o5sRmfSZ8t2qFfNG9/98dkBMgcAYE0Qxf/i6ddMnIjJ2nLPhbHwx0zDI2P9Vf8BVHEM9XJQBdQXAE9QVAN8a9k44MlFCVFhwaMSz7KovS1D0ePc37sfiM98kxcU8iAy/eS0k6NyxXd6TbDpOVV51oQYk2fF3w4JDbsWkFWuaLxLEbx6Hh4bcuBefVW roVTVyzFUCnUFwBPUFQDfmsB9BuXZIXNt7X98KK64QfzQ23lJRP1cjbOBNfgxoK4AeIK6AuBbE6ir7MAvDEivu e5eNU1SuLkIK8v3fYnNMwi8frW4MeAugLgCeoKgG9NoK7kuXfWjWhPREQmVt36fTJwYP Pu1pZOcw5 KSeloQ3vAY/BtQVAE9QVwB8awJ1xRhjTJLxKOj3zT4/Llnyg/eG3WfDk4t0JazKNOQxoK4AeIK6AuBbU6krqBrqCoAnqCsAvqGudAPqCoAnqCsAvqGudAPqCoAnqCsAvqGudAPqCoAnqCsAvqGudAPqCoAnqCsAvqGudAPqCoAnqCsAvjVCXZW8jji6bu3Jsmtsqj0AalBXADxBXQHw7d3WVUli4Jqp9vpE1M79TqGmB0Az1BUAT1BXAHx793NXBX/PalMuptQeAHWoKwCeoK4A Pbu60r8aGWXcjGl9gCoQ10B8AR1BcC3RqirGG b8nVV8QFQh7oC4AnqCoBvdaoreV7MmU2e0yeNG 86f92pGJFcZZs0PeLwGg/XCeMmzfjePySp O0t91BX2kBdAfAEdQXAN63rSiiM2T7GzmHRyej0vLTw9QMMiWznX82WM8aYILrrO8Jx2i9hsakJ4XtcOxE177/2foEisFBX2kBdAfAEdQXAN23rKv/2ws7Nu697WsIYY0zvBAPSJDpwu5jLH8Wx42XZdGFSmfmhs8pRUROfgnSBlDXWkHdQXAE9QVAN 0qysh4/Tw5mT38 OS0geK4i/u3Hb8Ya6csdyg8SZ6dm5ea5R8Fg41IyL9YYHZjKGutIO6AuAJ6gqAb9rVVWH4vHZE/QJS5erbxNFe1mTsfOBBbHnPUkQyxlBX2kFdAfAEdQXAN 3qKv qiymRzaposfq2ogiPDkQDDqRpKC/GUFfaQV0B8AR1BcA37eqq MGyTkTUc3O86t1rShIvB70okcSusycyHHIgVaayTZ4RERRbxBjqSjuoKwCeoK4A KblqnZRmJs5EZlPPpVW2lAlL/bNcL UKbCiu/M7EJHZqL1xxcpt8qyQpZP9npQwhrrSDuoKgCeoKwC afudwZK4rQMMiIjeH 65Zd9 f5/pDlaOax8VM8aYNDHAyZiIyMB29ILVmzZ4z/3C2vqrC mKU4VFUYs7ErVyvVag3JXaA6AOdQXAE9QVAN 0v5qoLCPUa5A5KVk6/XTltbR0mzz3rt9Yq9Jt1GHM1vsigTEmy7i9/0cncyKiFo7umwPjRG8qPFAoVPGS/2GoKwCeoK4A FbHO GUZDy HXr93otsifo2mSghKiw4NOJZtlR9I9QO6gqAJ6grAL69 /sMgjZQVwA8QV0B8A11pRtQVwA8QV0B8A11pRtQVwA8QV0B8A11pRtQVwA8QV0B8A11pRtQVwA8QV0B8A11pRtQVwA8QV0B8A11pRtQVwA8QV0B8A11pRtQVwA8QV0B8A11pRtQVwA8QV0B8A11pRtQVwA8QV0B8A11pRtQVwA8QV0B8A11pRtQVwA8QV0B8E1zXdnb2z958uQeNA3/ 9//pk2bNnDgwP/973 NPRYAqKvo6Ojly5fb2Ng8ffq0sccCAPXvxYsXzZo1q1hXkydPNjIyImhK2rdvr6 v39ijAID60aZNG7yjAfjm4 NTrq5GjRrVqVOnG9CUODo6WltbN/YoAKB jB07tk2bNv/3f//X2AMBgAbRrFkzT0/PimcGse6qqcG6KwCeYN0VAN wql03oK4AeIK6AuAb6ko3oK4AeIK6AuAb6ko3oK4AeIK6AuAb6ko3oK4AeIK6AuAb6ko3oK4AeIK6AuAb6ko3oK4AeIK6AuAb6ko3oK4AeIK6AuAb6ko3oK4AeIK6AuAb6ko3oK4AeIK6AuAb6ko3oK4AeIK6AuAb6ko3oK4AeIK6AuBbE6grIf/RgVXLd4Zny2v2fHn s8s7ftp8s7Lnl7y e2z9mhMvSupviLUfZH2rVV1JcpKeRD9JypFUsjk78UnM00o3A0CDq31dSfNepRcLmrZU 46WZCc9jY6Jf13YSB9fAP9BWtSVJPXKHp85w2xbm5qYthu4Jiq//BteknI5YNN3o2zNzdr2nub164nIrGqGIAoeb0xEnx5L1/jJoUqeE7nXc5gFEdHHO5NlattLEs78PPUjAyKynHO7sLq91UYtBtkgalpX4vhDM7sZkYJRjznHE1QjU54d7je i75ys0GXsetuZKr/FgGgodWmrkpe3/5t0bCOzbsse1Bcfku172hZeujPY3o7fLlg9YZ1K2YO6Tlw3uG4ovo6BgConNZzV5KUU1 /T0TUdtrpV2r/Q0ue tqbO5/LrtEYiuLP/eJ3PFpUs26Rp/3uWFldMcZY4a05lvVfV7UcZL2rUV0JOaGLPh3m8evp4Ctndy4YYEJEzfpujiv9i1aatM plWn3CYt81q9ZMrWvCRGRXh/f6OIqdwoA9a mdSXPuXdo/Q8zHFsSUacKdVXtO7ok1s xZeeFf cpP7bET9b3NHz/29DcRvoYA/gPqcOZwcLwuW2JiMjQcf2jCikjZBwbbPttPQeOUt6lEYZV1FVJjLdNA9RVI6tJXUlfBq47EidW/ksQXZ/bjogGHH6j CgtvrfcaW5gmrT02alnXC2IyHRycF6DDRsANKrdmcGC627manVV7Tta/M KLvTepJD8sh 5v8SKzKaG5TMAaFh1qytr 6mj2hMRdZx9Kb1c7GSdHNrV/U7D1FXQqOZV1dXj1Xb/zbqqKOfcUD2y/OZmAWOMMfmbkN/C0lXXXUhi19sTUe8dSTg7CPBu1a6uiiIXdaxYV9W/o4vuuLcnen/ rbcxlRfsYqo2BQYADaBudWU3 GjiA18HAyIyGrTtqbhso3pdSdMjDq/xcJ0wbtKM7/1DksqWZ8pyYs77LVqwR/XHmTQz6qjvkoWL3GfOXLjuxINMsVQqlckFxlTqSlqc NfWRa4Tp3psufrq7YLOt3VVUPT8kt CaRNd5vx05GFuueWcQuGLkF0rvp06YcK0ed6/XUtReWVB/Cr8kLf7yuD0gueBq2dPmbPpWrpMbZBC8ctbB7zmeYVmycUpV7d7uk2a4u53JbX8qtIqjqHWtKirkidrPrIYvi9RWukzcs4OakZGoy/maDUkANBa7eqq N53VupnBtVUeEcLuSFurYmow9TDz8WMsZJnOwaZWEw49rLyzwQAqCd1ratjGYLs1ckpFkREXTxCskojpnxdCaK7viMcp/0SFpuaEL7HtRNR8/5r7xcITBx/wmtiV30isvjm1tsWE8ftHmXZxnlPbDETRJFrHQyIiPSNWlgOP/JKrqyrXr5HfcZ84jRxspOdIRH1WPOvMpEUddXGxW9J/zbm7S2aK9Z7dp594bVyhkYcv9/FxmbyjjuvCvKSwjaMMCf9bov SpcxJs8K3 nxeWsiop7e22Y5djEhIurn/3/HVAcpzwrf4f6ZORFRn43HVzn3 2z0eCf7FkRk7/1Pcc2OodZqXVfi H0ug5dcq o7jiWPf7aj974MzMAiDIB3rCHqSv0dLXtz8ZvOREQtP11 aMfXvR2 PRqPeSuAd6Ee6ooxIT/Su5ceEb03fE 84jtq5eoq/5aHTdelUaVfVckNntKKiBz8E6SMMVZ46xsL1bqSpR4cakjmrteU09n5N2ZZEHVcdFf584q6Mv50eXCalDEmZF2caErUZcUjRV4p6oo6uex mCdnTJYRttKxORG1druSKzAmjlnbQ990/PlM5QeQkH1lhiWR8YiDKVLGGBMyjg8kIoNenlczpaLHFw8FRufJ1QYpvD7Un4hMBq8KTpMwxoSsC Naqnz6VXcMtVbzuhIKn4fs/fHLroZERG2dN0XmVRJP4pifurbo5fuvWPNmAGg4DVBXmt/R0tTz87vpERE16 l9p7JPAwCoZ/VSV4wxafKR8eZERB8uvZkrlK r3KDxJnp2bl5rlHwWDjUjIv1hgdmMMSZ tKKLal3lX3UxJeq4uLTGlCXT61dFjKmtu5LGb 5OZDolVFEy6uuupC 2OxCRqUuIiOVdmdqKaMCRN2UfMuJHK62JyMYrWswYY3mXnA2Jum OLzd7XnGQiqX1/QJSlXNDkmebuhGZTFYuIK3uGGqtFnNX0ryXTyOD9n4/qjMREVl8HZyt4RNV9urYWCuHtf/g29kAjaDe66qyd3Txs8PfDnOeMqQtEZFet4V/vsYyS4B3oL7qijEh79YP9kRE5l8eSpJkltWVONrLmoydDzyILe9ZikjGGGPiGG8b1XApjlrckcho5Hnl9RyEN0cGEBkMOaG81FTFupIl7 5DZDzusogxpnFVuyRu40dE1Gd3Sv4d9/ZERmP EqkcSH7oFDMi6n8gTa5h9woVB6l4VlldyVJ29yFqUTqI6o6h1rRYdyXkR3p3JyKjkRfUFlZJUw5P7DnpYCIuKArQKOq5rip5R5fE7x3VvqvnLZEge3N5aW8DIqIeq 4V1GHgAFAj9VdXjDHJi4CRJkTUrKdX0L4hpXVVFOHRgWiAol00qBgurCR2ywBDMhoakChhjMnTz04wI6t5oTnKV1Krq/Jho6GuhPSjA4io756UnOAJLYn0Bp9WvcSp OEPnYmoz65kmYbdax5kNXVV3THUmlZ3whGyL4xrSdR378vyD dH Y4Ytf5ePk4SADSS qyryt7R0sTdAw31 v/2UvFZJs 5ubxHMyL9z/a/xPwVQAOr17piTJ59bbEtEZGRZUsrZV1JYtfZExkOOZCq o6WZ0QExRYxpqGuGJNnh3l2s7QeMPHbhe6uw4dOWfPXy7JLjte rqQJ23oStZ7xd0GxIqQ6Lbuv8imleNB8 o0CTbtXqG1dVXMMtabdfQYlsevs6b1JwaozdeK4AFfn5WFZuCcGQOOpv7qq9B0tvDn6KVGH RFlJwtLYjf2JGo1DRe8Amhodamr29/aDjqidqpLHLdjmDERUbvSdVdFd d3ICKzUXvjSj8b5FkhSyf7PSlhTENdCXnhq4Y674iv5LRVretKyDw7qgV1XBBewFhRpKcVEX3w48Oyj6ncP8caU9s5N/I17l55VLWsq2qOoda0q6u8K9Ms27oFl82YiZ8fnDl84YU0lWOTZ948FJSCr2gDvEu1rKsoTyuiTkvvV6yrKt/RORdHG5HZ1FCVlCq6u/B9 uDHh/guC0ADq0Nd5QaNs ix8Zl6P8gzL8/rpFJXTJoY4GRMRGRgO3rB6k0bvOd YW391QXlhfCKohZ3JDJ1uar8DJCl/ObYjFoPnuvlu2nLNv de/YdPHY2OCq5UNkI2acH6xF18ytddi5N LUXkf6QM4qzfYq6MhoWkKAYmZB7c9mHLT9cHKa4OIH8zTlXSyKjwTuUVzWXpR4d2ar1uCOl14DJPe9kQGSzKrrc50 FQQoZJwYSUc9tCZoHUd0x1FpN6qroycHlC1cF3EpTzJFJUi/O72k/8/zbRaxFsb Nb/ e/fg57qXmfeM6qne7rkuisLYd4J2qXV0pvrPcbl54uWskV/eOFkQ3F3Qi80lnXpfOa4mfbPi49afbNHxqA0D90qquZJmRJ7avcrFrRtR62OJNAX8lV3yzFj/eMqzn/LKricpz7/qNtaJSHcZsvS8SGGPStGt7f3AyJyIy7u xLShFwhgrfrx9ZBtSYzrULzoj9pSv20f6RERW41b Fpaccn2/z6ROREQGPWZtOvdCzJg48dLq8fbGZGg3YvaSZXPH9Ovn4ndb5bpPQtHT32d0MyKTPlO W7Vi3uj n88OiCkQGGOCKOYPX7du kRExo5zNpxVXBqm4iBj/xe4cYa9HhHRBy466llA1Cv9uMDWfjCoWqjkGrkqlBXcnSTiq tknm9p8OG/pJ/0GuG0Jfv71NRtLvo1upD4hUrmUBAO9KjetK8jJ4z9p5n7xHRGQ60N03ICyNMVbTd7T4 fF5/d7/cNwP2w8cDtgwf8znE9Zey8CiK4CGV4e5q6rJ81NfFZRfCSATJUSFBYdGPMuu jxU0ePd37gfi898kxQX8yAy/Oa1kKBzx3Z5T7LpWG6Ou2qS7Pi7YcEht2LSijXNFwniN4/DQ0Nu3IvPqsNqqMrVyzGoqNmZQXlhasyd66Fhf0c SSvEwiqAJqt2c1d1I81NeHj7xt93H6cV4VMB4B1psLrSljw7ZK6tvYZ1AeKH3s5LInTiFFYDHIN2664AoGl6l3UFAO9ek6ur7MAvDEivu e5eNU1SuLkIK8v3fYn6MZygQY4BtQVAE9QVwB8a3J1Jc 9s25EeyIiMrHq1u TgQP7f9zVysphzsEnWi8Jf9ca4BhQVwA8QV0B8K3J1RVjjDFJxqOg3zf7/LhkyQ/eG3afDU8u0pWwKlO/x4C6AuAJ6gqAb02zrqAi1BUAT1BXAHxDXekG1BUAT1BXAHxDXekG1BUAT1BXAHxDXekG1BUAT1BXAHxDXekG1BUAT1BXAHxDXekG1BUAT1BXAHzjpa4kWcmZDXJLG 2VvI44um7tSZWrh6o/UmOoKwCeoK4A KZNXUnf3DqyzWtKL0tTExMTs/cHzF6z80yMqPRqTiVJQb9t9Bxpa25q3mX4ok0Hrz PXNrD3MTExNS8tYWlpUUbc1MTE1Oz1haWlpZtzM1MTUxMLPqvf1yQcmWf35LRduamJiYmJmYWVh927/ahtW33/s7TvY/ez676vqPy9DPjbMacSq94Ey1J6pU9PnOG2bY2NTFtN3BNVH75S05JUi4HbPpulK25Wdve07x PRGZVePfW9VKEgPXTLXXJ6J27opbWas/UjuoKwCeoK4A Kb13JWQecbJkIjafntbQyxInm3sZuy4N0XGGMsPcbHq7Xn heKezgU3Z7Uhoo93JssYY4L4TVSAq7XNAsXN96QJ23oSkf7QM1mMMSbPjzu9qJcBEb0/9Why5TM 0gR/ByLqt/2FxttDS1JOff0 EVHbaadfqWWa5KmvvbnzuezqDri2Cv6e1aZ8S6k/UnOoKwCeoK4A Kb9mcHC8LltiaibX7ym7Mk NdjK5Wo Y4zlXp6/4nZB6YbydcUYY0L25e9 vKl4Qu75L/SJDJwu5pY X5rg79iMiEwmXsqu5GLnxQ9/7EJERNYr/lG7cbLqWIkMHdc/qtA2QsaxwbYaE7FuxI9WdinfUuqP1BzqCoAnqCsAvtWhru64tyOiHls1ThjlBg7rNDUsnzHGSl49Siq7C4x6XTG56PnjDMVO8i6NMCxfV6wk5idbIqIPfnyoMZ2E3BA3a4d506yIqM300DyNYw2fa20/dVR7IqKOsy ll5vAyjo5tKtWxVM1cYy3TYW6Unuk5lBXADxBXQHw7R3UVXka6kqFhroqnXfquytJ00/IXx12sp50/vVzfwciMhp 4nXFxVeKfdgNPpr4wNfBgIiMBm17qhJq1deVPC/mzCbP6ZPGjXedv 5UjEj1FaTpEYfXeLhOGDdpxvf IUnFbzMSdQUAlUFdAfCtqdeVJGHfiPeIyHzymTcasolJYtf3/XBhRCGTp58aaUxEfbY9Vx9PYfhcu8HHMgTZq5NTLIiIuniEZJXuruq6Egpjto xc1h0Mjo9Ly18/QBDItv5V7PljDEmiO76jnCc9ktYbGpC B7XTkTN 6 9X6AILNQVAFQGdQXAtyZZV80 2RX578PbQYd8Z/QzITJ3mHvgcYHGRVeFdxZ86LApTsIYY6Lrsy2J6IMfHhSrPU1ZV4wJ ZHevfSI6L3he IVl3Cosq7yby/s3Lz7uqeKp8pfHx6oR2TodCGXMZZ/y8Om69KootJDDp7Siogc/BOkjKGuAKByqCsAvjXJuqL3x87/7tthbYjIYMAvsVoS8PwAAB2gSURBVJpXqjPGhMzzE21GHis9FyiOXmVLRK3dQiouviqrK8aYNPnIeHMiog X3swVqqwrIeP08OZk9/Pj0ktpCUXxF3duO/4wV85YbtB4Ez07N681Sj4Lh5oRkf6wwGzGUFcAUDnUFQDftK rooj5HYioxxYNZ IYyz49tPNX1wrUN9T4zKAgur3Elojec/49WeOFFpg0afcnZrYzfLf ouT3/RdmRNTc6Vha bOI5eqKMSHv1g/2RETmXx5KkmRWXleF4fPaEfULSNVwUlIc7WVNxs4HHsSW9yxFJGMMdQUAlUNdAfBN 7oSP/yhMxHZ vyr4Rrp8lf7B9q53ylS31KbdVdF/6zp3YzIcOC2OA2vIY5e1d3W1W//QRW7l/Y1IKLeW8pfJqJCXTHGJC8CRpoQUbOeXkH7hlRWV/lXXUyJbFZFa5g K4rw6EA04ECapuVgDHUFAJVDXQHwTfu6kiXv piIzKaEajj/V3x/2UeO2xI0zDnVblV7Sdy2gYZEzXqv adiqYnCZtl9tiuxwkvkhbi1JqJOSpLr5SryvG5NnXFtsSERlZtrSqpHiKHyzrREQ9N5eLtZLEy0EvSiSx6 yJDIccSFU9EHlGRFBsEWOoKwCoHOoKgG91uM g OHyLkRktSRKbYqq8N4P9vaar09V8PeM1kTUe4fG6yvkXnQyINL/4kLZ1USTD4x8j4hsFl3LUZklkqcddbaeEJiptta9 MH3nYmolcufKhcfLbz9re2gI kVnyyO2zHMmKq6O40ozM2ciMwnn0orHW7Ji30z3C9lCqzo7vwORGQ2am9cacnJs0KWTvZ7UsIY6goAKoe6AuBbXe7iLHtzztWSyKCv1/XMslSSZkb8Ov6DLm6BrzXeGzDnwsjmRNRl5SMN7SVPDehHRNR3T0rZD8ten5nShohMnX55WHqjwPw7S7qYjTifo EFFGuliHqsjX47fZUbNM6ix8Zn6heVl2dentepquIpids6wICI6P3hnlv27ff3me5g5bj2UTFjjEkTA5yMiYgMbEcvWL1pg/fcL6ytv7qgvNthUdTijkStXMsWn6k/UnOoKwCeoK4A FaXumKMFcefmD gNZGBVf xrrNmuY4f2r2N8ftDvz XpL5QSpZx59ivXpNtiIiITAZ6rN976cXbxJKkXNnn952TpWJr2xFLN 8PTlHmkDw7ZK4VERG9/9nXP27avvabT8yIqHkv11W/3VS98Lr09bWd3zlZKPZBbQa5/xIcHXli yoXu2ZErYct3hTwl9rtCosfbxnWc37l80myjFCvQebKXZKl009XXr89GynPves31qp0G3UYs/W SGCMyTJu7//RyZyIqIWjbAuEKp2iOV3NanEqgrAJ6grgD4Vse6YowxJi9IefT3X4EnT5w8G3TjUWphJcu8myx5fuqrgqoHXZLx Hbo9XsvsjXcU1EmSogKCw6NeJat auN9QJ1BcAT1BUA3 qjrqDhoa4AeIK6AuAb6ko3oK4AeIK6AuAb6ko3oK4AeIK6AuAb6ko3oK4AeIK6AuAb6ko3oK4AeIK6AuAb6ko3oK4AeIK6AuAb6ko3oK4AeIK6AuAb6ko3oK4AeIK6AuAb6ko3oK4AeIK6AuAb6ko3oK4AeIK6AuAb6ko3oK4AeIK6AuAb6ko3oK4AeIK6AuAb6ko3oK4AeIK6AuCb5rqytrb 7rvvFkDTsGjRokWLFtnZ2S1atKixxwIA9cDHx6d9 /b4mAXg0vLly5s1a1axrpycnAwMDDpAU2JiYqKnp9fYowCA mFmZtasWbPGHgUANBQi8vT0rDh3hTODTY2zszPODAJwY 7cuTgzCMAxrLvSDVh3BcATrLsC4BvqSjegrgB4groC4BvqSjegrgB4groC4BvqSjegrgB4groC4BvqSjegrgB4groC4BvqSjegrgB4groC4BvqSjegrgB4groC4BvqSjegrgB4groC4BvqSjegrgB4groC4BvqSjegrgB4groC4BvqSjegrgB4groC4BvqSjegrgB4groC4FsTqCsh/9GBVct3hmfLa/Z8ef6zyzt 2nyzsueXvL57bP2aEy9K6m ItR9kfatVXUlykp5EP0nKkVSyOTvxSczTSjcDQIPTtq5khW8SHkfHZWp698pFLx7FJBc00mcUAKjSoq4kqVf2 MwZZtva1MS03cA1UflC c0plwM2fTfK1tysbe9pXr eiMyqZgii4PHGRPTpsXShmmcyeU7kXs9hFkREH 9MlqltL0k48/PUjwyIyHLO7cLq9lYbtRhkg6hpXYnjD83sZkQKRj3mHE9QjUx5drjf C76ys0GXcauu5Gp/lsEgIZW27oSihOD/WYO6f/FV99vPRJ0/436H4 S5zsHG5HFN7fq9ZMPALSj9dyVJOXU1 8TEbWddvqV2v/Qkqe 9ubO57JrNIai HO/ B2PFtWsW RpvztWVleMMVZ4a45l/ddVLQdZ72pUV0JO6KJPh3n8ejr4ytmdCwaYEFGzvpvjSv/KlSbtc2pl2n3CIp/1a5ZM7WtCRKTXxze6uKEHDwAV1KquSpLOePR4z9LZLyKnsokp8dPN/Q2IUFcATUQdzgwWhs9tS0REho7rH1V4QwsZxwbbflvPgaOUd2mEYRV1VRLjbdMAddXIalJX0peB647EiZX/EkTX57YjogGH3yiKsPjecqe5gWnS0mennnG1ICLTycF5DTZsANCo5nVV8nz/l62p5Rf sZX/HVT0yPez3mNHdUBdATQVdasra/upo9oTEXWcfSm9XOxknRza1f1Ow9RV0KjmVdXV49V2/826qijn3FA9svzmZgFjjDH5m5DfwtJV//KVxK63J6LeO5JwdhDg3appXRVErfyIqOXIwy8rf5cW3Fs14NPVEVE/d0VdATQVdasru8FHEx/4OhgQkdGgbU/FZRvV60qaHnF4jYfrhHGTZnzvH5JU/PYUmywn5rzfogV7VH cSTOjjvouWbjIfebMhetOPMgUS6VSmVxgTKWupMWJf21d5DpxqseWq6/eLvJ8W1cFRc8v S2YNtFlzk9HHuaWm1AXCl E7Frx7dQJE6bN8/7tWorKKwviV GHvN1XBqcXPA9cPXvKnE3X0mVqgxSKX9464DXPKzRLLk65ut3TbdIUd78rqeVXmlZxDLWmRV2VPFnzkcXwfYnSSp Rc3ZQMzIafTFHqyEBgNZqVleSuM19iMhm5T/iyp4iiMK/dxzi91hc8mQN6gqgyahrXR3LEGSvTk6xICLq4hGSVRox5etKEN31HeE47Zew2NSE8D2unYia9197v0Bg4vgTXhO76ldYLiCO2z3Kso3znthiJogi1zoYEBHpG7WwHH7klVxZV718j/qM cRp4mQnO0Mi6rHmX XHj6Ku2rj4Lenfxry9RXPFCu7Osy 8Vv7tJ47f72JjM3nHnVcFeUlhG0aYk363RX lyxiTZ4Xv9Pi8NRFRT 9tsxy7mBAR9fP/v2Oqg5Rnhe9w/8yciKjPxuOrnPt9Nnq8k30LIrL3/qe4ZsdQa7WuK3H8PpfBS65V9R3Hksc/29F7XwZmNNJaMoD/rhrVVeEdjw5E9NHqK3/ uuTrsUMGfDZy9vo/E1XOEAo51xY6OO98LmEMdQXQlNRDXTEm5Ed699IjoveG74lXfJelXF3l3/Kw6bo0qkj5g7nBU1oRkYN/gpQxxgpvfWOh qEgSz041JDMXa/lK3/6xiwLoo6L7ip/XlFXxp8uD06TMsaErIsTTYm6rHikyCtFXVEnl90P8 SMyTLCVjo2J6LWbldyBcbEMWt76JuOP5 pTAoh 8oMSyLjEQdTpIwxJmQcH0hEBr08r2ZKRY8vHgqMzpOrDVJ4fag/EZkMXhWcJmGMCVkXxrUk6rTsQXGNjqHWal5XQuHzkL0/ftnVkIiorfOmyLxK4kkc81PXFr18/630j2IAaCg1qavi 0utiIg6j/TccT78YWTQlslWRGTitEv5MSvPvDy33/gDyVLGUFcATUu91BVjTJp8ZLw5EdGHS2/mCuXrKjdovImenZvXGiWfhUPNiEh/WGA2Y4yJH63oovqhkH/VxZSo4 LSGlOWTK9fFTGmtu5KGr 5O5HplFBFyaivu5K 2O5ARKYuISKWd2VqK6IBR96UJYf40UprIrLxihYzxljeJWdDou6b48udUas4SMXS n4Bqcq5IcmzTd2ITCaH5NfoGGqtFnNX0ryXTyOD9n4/qjMREVl8HZytoa9kr46NtXJY 4 2uQcAdVCDuhLSjw9sRmTofCm39KHih6vsiMh49Ol0OZO/OTe937RTacoPQtQVQFNSX3XFmJB36wd7IiLzLw8lSTLL6koc7WVNxs4HHsSW9yxFJGOMMXGMt43qh0Jx1OKOREYjzyuv5yC8OTKAyGDICeWlpirWlSx5dx8i43GXRYwxjavaJXEbPyKiPrtT8u 4tycyGvOXSOVA8kOnmBFR/wNpcg27V6g4SMWzyupKlrK7D1GL0kFUdwy1psW6KyE/0rs7ERmNvKC2sEqacnhiz0kHE3FBUYBGUYO6kiVu70VEbeeGl32WSRP9PyYis6mh/1/q8cn2I/0jnj1Xehrs2ZnIfPIfMc8TUkVa/hkHAPWk/uqKMSZ5ETDShIia9fQK2jektK6KIjw6EA1QtIsGFcOFlcRuGWBIRkMDEiWMMXn62QlmZDUvNEf5Smp1VT5sNNSVkH50ABH13ZOSEzyhJZHe4NOqlzgVP/yhMxH12ZUs07B7zYOspq6qO4Za0 pOOEL2hXEtifrufVn 4fwo3xGj1t/Lx3orgEZSk7mrN0c/IaL3F6ouKCgMn9eOyMDpQsKZz6lS3bc8R14BNKp6rSvG5NnXFtsSERlZtrRS1pUkdp09keGQA6mqvSLPiAiKLWJMQ10xJs8O8 xmaT1g4rcL3V2HD52y5q XZZcmrn1dSRO29SRqPePvgmJFSHVadl9lYajiQfPpNwo07V6htnVVzTHUmnb3GZTErrOn9yYFq87UieMCXJ2Xh2XhdhkAjacm664Uf/cZOp3NKreQoQvR wsjc1OvnTyq6uDGCRZELT7z3n/0j BnBfjbCaBR1aWubn9rO iI2qkucdyOYcZERO1K110V3Z3fgYjMRu2NK20aeVbI0sl T0oY01BXQl74qqHOO IrOW1V67oSMs OakEdF4QXMFYU6WlFRB/8 LAsr3L/HGtMbefcyNe4e VR1bKuqjmGWtOurvKuTLNs6xZcNmMmfn5w5vCFF9JUjk2eefNQUAr 0AV4l2r0ncGSf3 2J2o1JfjtwiuWf3WqGVkt1vD9GKy7AmhK6lBXuUHjLHpsfKbeD/LMy/M6qdQVkyYGOBkTERnYjl6wetMG77lfWFt/dUF5acuiqMUdiUxdriq/XydL c2xGbUePNfLd9OWbf479 w7eOxscFRyobIRsk8P1iPq5le67Fya8GsvIv0hZxRn xR1ZTQsIEExMiH35rIPW364OExxcQL5m3OulkRGg3cor2ouSz06slXrcUdeKneXe97JgMhmVXS579JVGKSQcWIgEfXclqB5ENUdQ63VpK6KnhxcvnBVwK00xRyZJPXi/J72M8 XXomCFcX Nr79e/bj57iXmveN66je7bouicLadoB3qmbXuxLybnrakoHj5ljFm1r26sQ4S6vpF9M1TD2jrgCaEq3qSpYZeWL7Khe7ZkSthy3eFPBXcsXEKn68ZVjP WVXE5Xn3vUba/V2VUCHMVvviwTGmDTt2t4fnMyJiIz7e2wLSpEwxoofbx/ZRn0pgelQv iM2FO bh/pExFZjVv5W1hyyvX9PpM6EREZ9Ji16dwLMWPixEurx9sbk6HdiNlLls0d06 fi99tles CUVPf5/RzYhM kz5btWKeaP7fz47IKZAYIwJopg/fN266RMRGTvO2XA2vphpGGTs/wI3zrDXIyL6wMVn37WUskHod5ux4WxcoVDVMWhVMjWoK1naScXXNsnc/tNhQz/pP8h1Q jrtze Sfp9dCuNSzTeXssCAN6VGt8JR5JydkE/i/eHLvLbuWXZRMfP3Y8803xHHNQVQFNSh7mrqsnzU18VlP8DSyZKiAoLDo14ll31eaiix7u/cT8Wn/kmKS7mQWT4zWshQeeO7fKeZNNxqvKqCzUgyY6/GxYccismrVjTfJEgfvM4PDTkxr34rDqshqpcvRyDipqdGZQXpsbcuR4a9nfkk7RCLKwCaLJqdRdnQfzmScTft 7HZ FbvgA6osHqSlvy7JC5tvY/PlSbThE/9HZeEqETp7Aa4Bi0W3cFAE1TreoKAHROk6ur7MAvDEivu e5eNU1SuLkIK8v3fYn6MZfbg1wDKgrAJ6grgD41uTqSp57Z92I9kREZGLVrd8nAwf2/7irlZXDnINPtF4S/q41wDGgrgB4groC4FuTqyvGGGOSjEdBv2/2 XHJkh 8N w G55cpCthVaZ jwF1BcAT1BUA35pmXUFFqCsAnqCuAPiGutINqCsAnqCuAPiGutINqCsAnqCuAPiGutINqCsAnqCuAPiGutINqCsAnqCuAPiGutINqCsAnqCuAPhWT3UlSHKSnzy4GxH5z/OMYjljjAlFb16/w5uxSLKSMxvkljbaK3kdcXTd2pMqVw9Vf6TGUFcAPEFdAfCtrnUlFDz5Y WXPdqad/l0/HT3RYvmuY3 tI/DiDk GxaOnBuWzxiTvrl5ZNuqr/q2MzMxMWtr16vPW70 6tKulanFJ5ueljAmSbmyz2/JaDtzUxMTExMzC6sPu3f70Nq2e3/n6d5H72fLqhyFPP3MOJsxp9RuHC9JvbLHZ84w29amJqbtBq6Jyi9/ySlJyuWATd NsjU3a9t7mtevJyKzanjU1SlJDFwz1V6fiNq5K25lrf5I7aCuAHiCugLgW53qSvzi6NddiD5w2x j2i2StBCvAUZEn/2RWfqQkHFyiD4ROR58rVpA8rzIdYN6Lb5beuc9acK2nkSkP/RMFmOMyfPjTi/qZUBE7089mlz5jI80wd BiPptf6Hx9tCSlFNfv09E1Hba6VdqmSZ56mtv7nwuuyYHXBsFf89qU76l1B pOdQVAE9QVwB8076u5FlX5nUiaum094V698jTz3/Vue W529rJz9sWiv1umKM5V1dtvzvgtJ/5Z7/Qp/IwOlibukj0gR/x2ZEZDLxUnYlFzsvfvhjFyIisl7xj9qNkxljjBWGz21LRESGjusfVWgbIePYYNtvb2tRPFUTP1rZpXxLqT9Sc6grAJ6grgD4pm1dCXnX53Ugoo98n2pe7iSJ3zX95/vFpf8suO5mrrGumCQ/t/htNuVdGmFYvq5YScxPtkREH/z4UGM6CbkhbtYO86ZZEVGb6aF5mp5TGD7X2n7qqPZERB1nX0ovN4GVdXJoV62Kp2riGG bCnWl9kjNoa4AeIK6AuCblnUlSwkYqE9EvbcnaDwZxxgTxDnZZdmksa5kr8OO/1MuNTTUVem8U99dSZoWX8lfHXaynnT 9XN/ByIyGn5CLd8U 7AbfDTxga DAREZDdr2VCXUqq8reV7MmU2e0yeNG 86f92pGJHqK0jTIw6v8XCdMG7SjO/9Q5LKjhh1BQCVQV0B8E27upKnHRyoR0TtPSKKqnziW5rqSp521MXlQq7q09TqSpKwb8R7RGQcwbTd9AlMSu7/vhwohCJk8/NdKYiPpse67ee4Xhc 0GH8sQZK9OTrEgIuriEZJVuruq60oojNk xs5h0cno9Ly08PUDDIls51/NVnwvUnTXd4TjtF/CYlMTwve4diJq3n/t/QJFYKGuAKAyqCsAvmlXV4Xh89oREdmvj6uw5kqWfuv3dcvmzZo5c bMmbPmLFrz 51Mxt7WlXGvEV8qjBs5qJs56Q0K1FBXzT7ZFfnvw9tBh3xn9DMhMneYe BxgcZFV4V3FnzosEkxCNH12ZZE9MEPD4rVnqasK8aE/EjvXnpE9N7wPfGKc5pV1lX 7YWdm3dfpzz9KX99eKAekaHThVzGWP4tD5uuS6NK zI3eEorInLwV0znoa4AoDKoKwC aVdXyjXq9OHaJxpWXQnZwTMtiYisVz4sTQ9lXfXaci8xOTk5OTkpIe7Bn tGdHbSVFf0/tj53307rA0RGQz4JVbzSnXGmJB5fqLNyGOl02Hi6FW2RNTaLaTi4quyumKMSZOPjDcnIvpw6c1cocq6EjJOD29Odj8/Lj1KoSj 4s5txx/myhnLDRpvomfn5rVGyWfhUDMi0h8WmM0Y6goAKoe6AuCbdnUlfrSiCxFRq2lh Ro2y1/tcyAiA6ey034a110V31uzIKiyM4OC6PYSWyJ6z/n3ZM1ru6RJuz8xs53hu/UXJb/vvzAjouZOx9LKn0UsV1eMCXm3frAnIjL/8lCSJLPyulLM0fULSNVwUlIc7WVNxs4HHsSW9yxFJGMMdQUAlUNdAfBNy1Xt WFu5kREnb9XPw3HmPDmcH8iaj4q6O0kkubvDEry0gvKhUv5dVdF/6zp3YzIcOC2OA1TZOLoVd1tXf32H1Sxe2lfAyLqvSW 3BnLCnXFGJO8CBhpQkTNenoF7RtSWV3lX3UxJbJZFa1h qwowqMD0YADaZVckB51BQCVQV0B8E3bKzIU3f/Bmoio7TfX8tRWRNW4rhQkr27ffKmooYqr2kvitg00JGrWe80/FZfPi8Jm2X22K7HCtFZeiFtrIuq09J5q9anXFWPy7GuLbYmIjCxbWlVSPMUPlnUiop6by8VaSeLloBclkth19kSGQw6kqn6VUZ4RERRbxBjqCgAqh7oC4JvWVxMVcq4t6EJE9NGqqIorzjXV1bWvKqkr2cujM2cHKssn96KTAZH F2WnFKXJB0a R0Q2i67lqPyoPO2os/WEwEy1sit 8H1nImrl8qfKxUcLb39rO hIesUni N2DDOmqu5OI1LM0ZlPPpVW2lAlL/bNcL UKbCiu/M7EJHZqL1xpSUnzwpZOtlPsRYNdQUAlUFdAfCtLnfCKUk46vYBEZkP33g7s9wEzsvf lWoq5wLzs2JqMfW8tdLkLy68mM/q7GllSRPDehHRNR3T0rZ/mSvz0xpQ0SmTr88LL3hTv6dJV3MRpzP0TCq0u8z9lgb/Xb6KjdonEWPjc80XFM 8/K8TlUVT0nc1gEGRETvD/fcsm /v890ByvHtY KGWNMmvj/t3c/oUnGYQDHf1GEDSpnk2q7jO0QZrcoV4LLhfZndEjYSoJgzIphHXbQahFRbiUMujSGx2CMxqBiDbPDECrr0mBEg7r0hxGCUGv0hxAVO2ijUiHYO9z78P0cX/T1eW9f5OX3DDnXKaXUmqYDp/tCV8937Wts7Bwvbjv8luipV2pjR2zxIPrSK/ PugIkoa4A2Za4xTm38HIkeMRqVKvr9x7z9/WHr108e8LZvL6mYVfnpZHpz9l8Pv1xKnLljKtBFdQ2WawF27c1bTYopWoOj6dyhS3Ofmdd4VPm/ecGhifeFnMom5rsKnx/657jvaHByyd3b1BKrd3REbw19efB6 m52E2/c1Pxp0z27vDEi6e3B4NHm1cpVdvaExq6X7Ku8PvM9Vbrqcr/J2WS0YDdWLylqnNeeDC3GIjZT0/6D/1 MqW2HLzxfD6Xz czyfhwr9OolFKGnd0Dd159TZdcqbDWpwLqCpCEugJkW2JdFeV JGcTsXtjo6Njdyfj0 /my52qvmJlv7z/sFDh3fSin8mZePTRs9epMqukM/NvEg8noo9nU5WOrdcAdQVIQl0BsmlTV1hu1BUgCXUFyEZd6QN1BUhCXQGyUVf6QF0BklBXgGzUlT5QV4Ak1BUgG3WlD9QVIAl1BchGXekDdQVIQl0BslFX kBdAZJQV4Bs1JU UFeAJNQVIBt1pQ/UFSAJdQXIRl3pA3UFSEJdAbJRV/pAXQGSUFeAbNSVPlBXgCTUFSBb bqyWCzVGwlluN1u6goQw fzUVeAYGXqyuv1ulwuA1YSh8NhNpurPQUAbdhsNpPJVO0pACyXtra2f sqHA4HscK0t7fb7fZqTwFAGx6Pp6WlJRAIVHsQAMslEon8VVcAAADQCnUFAACgJeoKAABAS9QVAACAln4BFfFmA8xxh0cAAAAASUVORK5CYII=

wolverine
2015-06-17, 10:22 PM
Not sure where Huawei are coming from regarding the intra frequency case.

According to 3GPP 36.113

8.1.2.2 E-UTRAN intra frequency measurements
The UE shall be able to identify new intra-frequency cells and perform RSRP measurements of identified intrafrequency
cells without an explicit intra-frequency neighbour cell list containing physical layer cell identities. During
the RRC_CONNECTED state the UE shall continuously measure identified intra frequency cells and additionally
search for and identify new intra frequency cells.

So according to the above the eNodeB does not need to send any neighbour lists to the UE. As such I don't understand what they are talking about. Unless someone is getting confused with 3G.

esoestemp
2015-06-17, 11:36 PM
Hi wolverine (http://www.finetopix.com/member.php?6992-wolverine),

How about LTE ->UTRAN.
Is that value 32 per UTRAN frequency or the total limitation.

qaqa
2015-08-30, 10:37 AM
@Wolverine,
the measurement is indeed performed by the UE with no control from the eNode. The HO though is a pure eNOdeB process, so what HUawei means with "delivery" is the selection of the target cell for which HO to be performed. If this cell is not defined as a neighbour, i..e, no X2, either S1 based HO will happen or the call will drop.

blame it on the weird chinese --> English translation methodology that Huawei uses to create English documentation :-)

linhhy
2015-08-30, 02:25 PM
@Wolverine,
the measurement is indeed performed by the UE with no control from the eNode.

I think UE performs the measurement based on "RRC connection reconfiguration message" that control from eNodeB.