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FCS 文章精要:北京航空航天大学肖利民教授等——通过模型和量化分析最小化周期性复制系统中的同步成本 |
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论文标题:Minimizing the cost of periodically replicated systems via model and quantitative analysis
期刊:Frontiers of Computer Science
作者:Chenhao ZHANG, Liang WANG, Limin XIAO, Shixuan JIANG, Meng HAN, Jinquan WANG, Bing WEI, Guangjun QIN
出版时间:15 Oct 2024
DOI: 10.1007/s11704-023-2625-8
微信链接:点击此处阅读微信文章
针对多周期性复制中的同步问题,北京航空航天大学大学肖利民教授团队撰写了研究论文:最小化周期性复制系统中的同步成本。
文章信息
标 题:
Minimizing the cost of periodically replicated systems via model and quantitative analysis
引用格式:
Chenhao ZHANG, Liang WANG, Limin XIAO, Shixuan JIANG, Meng HAN, Jinquan WANG, Bing WEI, Guangjun QIN. Minimizing the cost of periodically replicated systems via model and quantitative analysis. Front. Comput. Sci., 2024, 18(5): 185206
阅读原文:
![](/upload/paper/images/2024/7/2024712167113610.png)
文章概述
文章旨在提出面向周期性复制的一致性量化分析模型和同步成本模型,通过定量分析一致性和同步成本之间的权衡找到不同工作负载下成本最优的同步周期,优化周期性复制系统的同步成本。
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KPcEAo5p++r9oWbaSD2qqMq5ESC7lBmqr+BPiJ8WbXrZ5BXvNLOv7KM2YwZdWUqEQDUN4go6Uqr5Zr7OLjbFS3DQWOJ7lJQp+7uZ+HczfXseWnYYpA0xDYSAO/kHiDA4trm324Onuzy1W6/D1jhjxjRrHWw5f8LaOm1AckwScLnnfLNRg0nWcQESHSItPz8AXpv/4xb/bSdTMzixcd94zZlgKAMhEVjm+KKsdKyvMkdywDJVXOe+wClvLgYdzN9Vzh0AmK4zbUrQg0DAEQkQk5uDP/9oaVxJ1R3p3dnXPJYzxjOnEDnjPmAGYPXOe8MeOeMXiVuKEH8qwsOmem8roLZue//rHaIxu0PyIYklzIuCh6rD1jEK6ePN38p37Tq1x54bT3Z+9/Y0IAykJUElZPkyVEII+xq9aGqS0ziWIS0SBpK7qMc9m0pdUwRaDhCGxljdzWWLG4Nu20eNpK5dHZ05ap0Ok9Y/pOX8wdFWOmiZxUjJkEIZk7szZjx5wxe+CXOo0iLChf9dHLjpvrSAkRCLRLSVJsfqkfVYfScTlz6AvTswe/gHVbcY+0RIX6HvLl7rjlUH07AsA07ZHERt5jl61MFEbSVu+kcTZbGqYINAwBkBG80ol1KRh09xhjxo0x6GhwN/PIu7M3s26Z5+0Zs5GTDxASPPIJygiPgeaNeYxIjT8DE5gmyF5YnDe5p3O2a+nM/J/duYCksBs1BtO6k0iILTwsjuI5MXG5K8/ujju7FJWoRL1BBOmFwavx9QhkiWVcW3mPXa7yuMIJmaD4oDhKr1IRUAQEAnl3dpFdeb2eMVsrxpwA4ZgzZm8YQZE19YwZIcLik53M9yMBSQl7m8dFICTZAGHhuuS3SRe54em529t/L2Z8os4mxiEqthsBD+NueYnUf/bRRhQs8sAyjs28xy6UhZ/AhMpH0oZT0jibLQ1TBIqFgL8AcxtkA0uWd2dvYFXyyQprUeaM2Q2C4hOVuDMCdQXzHw9lYqvOsDFm7tAX9nBCEOQmwsF1eBh3Q8cfpOukKy0Pt7of+h1vdnHHkYhkJQpRoZsDSQ4NhZHkcequRyAORnF063Nx++LYzGPsQv785CWVZZN+0nWFIz4ojtKrVASKhwD+ZeMG6C+63OGvbTiBf+0NKG0enb0BxW5cFoxYTOHRTxY5Vxe6+rMzeEsoC5t4pGIlBex1YjEIY9CsnUgLP9ngbh5H4SRd+hRulU/f582+ceiUt+ScfwIRDKl/FkRFbxAhIPvRUXGKqhct13qtqLYbOXa5ymQL52FwB531NVefIlBUBPBIwFY2V7hNN0VYIzt7imI2Jyke9/iPekBSMl1Xgr1NfNt4nGRtA1Fr7f3mW35x9tD9J6ykgBEVHi+JBuJ4GHdTnBx0XeEyLc+35j7waa/S24W6h726HEZUbDeGqNBxvaAbCsVx/VZ0cyyD6hdVL8iGKy6qbR27XAhquCLQYghoZ3dcUMyezBmDmS3cTDOZSZFZ4SbtkxVsxpZo3xWQHNiYn9hVmw2pkQELSSESISWRDkpL8eQPk3H1YQ/b9Vc6Og5JXIQ/DlFB0qg3OpFNKi/yDDptxoP0KU6mo/AkUtqCP4odVzpbeBZhKFOUQ8euKCipjiLQKAQiPstPUhzt7BbUgPecMZhFwf4oeM087eEafGlhrodHfkkymVu86HMzl/zMTBiRQDwnEza3LUza5Tc3HsfT8vBA94FPezMdi2ZDHn9lQVRc+CeBvJXTRMUpql4SrKLaxtiFNymxps92Jslb07QxAq6G5wovAlSusrnCI5fZ3yRslyWByzZuZtibPGyK3GIyNEiJigUiWpeC14/9aFwbuj5ckttipRbEdbgbCiBCWKw74ZOiWJ9WwCzMyUXnzMzjg4GW2ZOgMEksgvx+3VF2Zz5BcUHlOPlLr6tg99waWgsdQURF4lnF1C/vQkvBIdX68bpa3MEWyh9rw9NWq6h6trRhYVFtY+za72/1AJIvz0wf1YYVWuObjwB1YJSEGhEPCyoh6dt0guJs+nHCePkoHx4WZEvqkx9puFva4PZJj4dV9SvG7LesSXDqI0984G32zC63Ms+0fiUqAkFgjcXN/hs+/BVafo0oFYWR3yZJB5LcXA/XF9vu400gzOKELS6tpa099nn6PieBkCTBL0O1LBSHMHKTtIVRnE3G1a/ZuP9279SSjh/XKrXQEZeowALHmbsXWtcQjkBUrIL0eJzLzfOUbp5GxnE/9MJOri/dMh/pl/rkl3phfkoXVUp7UdOpHuv4HETudoEUphMW77IbJZxsk0Qa7nbZgE6QXpQ4rsPdxt9DQ96MSIekLBu9zirTSb24fiUqArF5Y/aBNGBWRUTRtZFSqC3wcn1yc6VqmP/WF0hL5JkzEJyTfctP1W76MWdVCpHu6x9DnXG62raLqAC3oJMwtmFOcVlLWZ6s7XN7PC8ensYdByuXLg93uV1l5PouHQqHLs2a2NLZwigtpIyXfq7L3VIvzE9poWc7ZVmkPUqvMgICBJ6UYUm5Ptzkp3TST+FZSLItZZht6MuTpyF7PIzcFCdlNR5rHxwzI1wfbvLX7DpmYig+qVSiwpCjGQrHzAZdEymZBauTridJqVS1x/LG1vx8Jkfq1/yeMdtPvnF9uYnKxC6vcvHP/HsColLDIcRB1ytELXW0LR9bWOqMxPiQVx5h5cwj3zg2oUtEBWWVaaVf1kfGh/kpPdeDO+ikNCRl2rBwilcZEQECWMqw5FKf/JRO+ik8C0m2pQyzDX1KA13utvm5PdKVsqqDt0cciyZJn2wt8Pv/9LPeDE6JCiGODdPO7DjrmtWgayIls2B1kj4iuXuBn2ZzQECslkTgnDE7q2s8yjiTwso89+MHdouqca9rRoXrBLkl5kG6Wcc1Iu9G5OHCJcu849qCftgZp9w8f+4mGzIvHk5uSFtaiudxUdyUTmVEBAhUKcOSS33yIx13czsyPMzP03I3pZOS69jc0Kc0iHe5XWl5Gp4Whvrwb92SsE7PlidmYrLey8P/3hD/V2IpWnsE+deG1qbYXhXGNaLrxN1hAFEa6HH3Aj+ILB6DOGbdFuSDN5JOXLQy1v4p9LgHZSE3l65w6ATFcRtx3XMHvxhEzLIgKhL3BVjmFNCIfBuRRxA8WeSfxEaaP1m2/CiMpKvOPB5u18nTu3R4OOkjTI+ECBCgSM7dYeYIdCnJji096VJcmJ/0pEQ6SsvdUk/6ZRryQ4+7ZTqKJx1Ictd08Qin5jnrID1KQ36yabCD7Vn1zFxpOntmhSiCIba5m2tHYLo2KC6/PlGKb9O3hRmfkGJWJ3TvFnxu4WRvV2SignITiYjiJl2SMo2PA+FSk6QfVVZ+/MWg3XnTEpUo1ycPHev1zTgjwjxjs4U2R3WOI3mFKB0Pg9sVbtOjMKSxHVHCuY7LbbOtYQEIAEgCk2SAel2UTd8WVpcoAw/yoHxIRjVr07eFSXvQIT2SdTr+Jl+2Rzg2fVtYnb2UHiUqPoBsMWvQTZOuB8mU8C9MftowPthnW8y7UBmPq/7uPz8QlRBAD+3TJskGxZOfSx7H3S4dHh7k9p59IGhn3jISldzaB2sElAdJFtUWTtSbzwZLHKQfoFAYSQ6ULYzHU3rokS65bVKmpfQUTjbIT9IVTvEqQxAgAEmGqBcimspKshGForxI1uWJf8pzxhwIWDxYp5+zR4nKmVFnCOTAsYiWXwK6piR5XCZuPN6LWJZqft6z928MIgE8zh9gUfYFJ+nJOIS7wigNl9Dl/jB35e92/DAEuLIRldzaBsOJrgmCGpEfy7owTsIgSLoKKzEjGy59Cud63E3xJKV9hMsw6Q9KS3EqIyBAwJKMkKTpKlRWko0oEOVFckGe2EgszmuoCwxkF6BE5cwIQt/0ka8ku5B2XltXgjjheMwHsmLZb8dqZu7QFw6EEQIe7w+aqEMdqeB+7qa0PAxu10n6ofL//gTqiNO2JojqWiaikmu7IEB83MnbqDwpv6JI1DvujAqVnWNGbpKkIyXFk0Q83K6Tp+dpXOHcDtdRd0IEXKAnNNeQZM0oszNPvH7qndn+ObDyePvjtBEM1HkdSlTOvO2z279hBj32yesaLLDrX3fcwCNt3x/ly8lEGjCwwi0lD5NumdYWT/ZIN4qc/eWRyvyrXvW3CwCoDygLUbH1d1tYfe3i+6rXjiWTefB47mZJWsJJdQuSrooiDQ6S0n0m1v7L03ANVzjXke4kaaQN9SsCjUcA/y6xkRfWTPivq/J/m9ydReGUqJwhKngUF/bPnuONfU5AaugmuqO7u/uRlStXHqCzq6vrfh7vf4/EtakZt43Rk76sTFv418VLjze5p3P24OcnwsgBJxPSTX4puU2KQxh32/w8ndX93z5CsymbZH2EnzAWwYXzVjEBLuLMsqBkm9ukMJKIg5tL39tSQo5dVOcolbTp2sJstkgPMuzk6cN0eTxPp25FoDgIYN0K1kjg9PfzsH33Bd+zwM2LT3mmqYTs7GlslTIt1gr5W+YDC9cBvLf39vY+2tnZ+fyKFSuOX3XVVS9+4AMf8OjcuXOn9+Uvf7l2fvzjH6/FQednf/Znpzs6OmaXL1/+dHd395eMMVuM45GHT1axoPaAq0AyfH5191/Mvu2S2B8nlCQCg6+LeNDATPHkt0lpt85/4NPebF/XScvuv7Ja8JeFqNjK3qww3PRwkPS9LSP4TT3Mbau0DZcswmw2bPlTWFx9SqdSESg0AiAqaNw4syAsSlSMGcFsCsih5coPr1y58hu9vb1Hb7vtttnPfOYz3hNPPOE99dRTic99+/Z5O3bs8H7lV37l6PLly491d3c/YCMsFWMm/VmeqLMwwzPnnDMzv+PmunUnnCCwtkNtqCqlDvzQpXCejoeRW+rz8AXup+/zZi/fcKKyaNF3Iy4oV6JiaZghQXR9Q9RKHS3HLtQ56mHTTRom00l/UJni6AbZ0bioCBz+6PLBw9tW7PrJXSu2Tu5wfrcjqjkDG7B1eFv3l2A7csIYij/Z1r0Z9p/7cE/onhUxzAaqHt7WvQV5vvCR7uFARXskJypo5DjTEBbZ2e25tnAo7Z8iFzf39fXdMDg4eOS+++5LTErCCM33vvc973d/93dnBwYGnpWzZP6sGh6PRG6b9HHD+Y/fWCMZC4iChYRwHSIoJG1xCJPx0s/T1dwTu7zZXxg+OdvRcSjqZwJONz0lKsn6X6veBGnciyMlgi5sbDZdaUlXxsMv48gfR9rstnUYprWxr0eq8+kPdB/68bbuynMf7D71j7cu+3pae//9t7oe+ckHu08d3tbtHbqjazqtPZl+19uX3T1154rjsH/wQ11Hb/+5xe+WOln7H7lp6R8/96HuE8jz2Tu7Xnzbaxa9M2YeeBTgauxJCIsSFX/fErG4eejcc889/I//+I+5kRROYjDL0t3d/TQfhU5f5Op+KiAfPDzMDf3KOefMzP7WVZUaQWDb1VP7oTgbwbCFQZ+HkxtSnmS7TuKbPheufqWyaNEPY+6wrEQl7KIvjMc1afWj7ceuVr/Asn74Wiv+qSc+L+pdtH/yAysquAHjfPK9K06msYe0f39r11GyB9vII61Nnn7nWxf/x7N3ds8jD9jfennHBI/Pw/3IDUsPU52e/kB35dbXdTwZMx8QtgU3Bj8McRjU4xxt39nxvRz/EQvfhG/7LbfcMsvJRN7u9evXv2TY7Al78wdrWWIdeK250nHO0cobXjM7//d/YJ1doXZURyZ8QoO4oHAez91II/1kp/IPO7/tdS/7VMiryLZ6KlGxoWIPo7HBHttaoW0/drXW5WxQbZ7/UM+jP7lr+fRzdy1/6bltKz6YNlvYgK2f3LXipZ98aIVt2/lUWRzetnzkJ9uWT1ftb+s+mNfjJV7Iw3f1bHruzuUvI8+pO5f/a4JHZLZHP0RQkrwR1Pad3Tuzp418xLLj1a9+9TwezeRNUGAf615wg/dn16pNxjNmi0+g8Eci9oFZi8qSxd+e61hUmf/Ub9YRDz+vapgkFrf16lYAACAASURBVOQnSUSDkxAex91ch9JVDn1heu7ZL0R6zdpRSSUqDmDaPLjtx642v/7Jq48bccK1F9ZMYeu5u1bY3n6x6scNBDmB/eltfUlu8nGzq+pPbesbQp4JSArSc6KShqBQ2du+s3tnv5jM36TaceWVV+JNHS/vNSp4Owj5nHfeeccFURnziUrcWTK6tlWJR0FzF5/3p5VDXwDZt854ENkgSSSD/JSOJMUTMaFwktVZnAOf9uZ+/MVd3uSetH1LiUrdFVWPj0Dbj13aEhSBoiIAopIFQaH6tX1n94wZ9wkBX7C9A68U//Vf/7V39dVXz/3Mz/yM9573vGf2wQcf9NKuW/nWt75VJT+33nqrNzAw4EHC5qWXXorrWnv8hA8O+uWKulsuXVOnnD34hU3eoS/u5UQjU/f9t3vem4dPVsu9btUfOgsSL0KJSjy82kW77ceudrnQWs/yIYCFlWn/ofJat31nJ6LCQTntrhIVeuyDRzMgLm94wxvmli5d6r3mNa/xbrzxxto+KXjdmO+hQu4Pf/jDNZ23ve1tVWICcgI3ZlI46QkgKlgknenhTX5+cP6XLn/cu2TdMe+9v+jN33+751rLEkhkvv4xD69De7+xseL1dp3widVebFiXYYGVqGQIZguZavuxq4WupVZFEQhEoO07OxEVscizjqgQYSGJmRZs8Eabvf3ar/1aBY+K5Pm+972vpoNHSJhNIRtSBhCVzGZUeEvwP+Oww3vVq/7SW9xxpEoyQDZed/60d8WGE96vvdHzPvyOurUtIC14hOT90uVTPinxvGWLn/LX+eB7SXxWimeXxq1EJQ16rZu27ceu1r20WjNFoB6Btu/s7AOAdWtUQEIkmcjTf8kll8hHP5t9MoAbde6HT1yQJ16L3oFdY/29XBZsOOdv8Y9HUwvicihoqxGV6johWs9jwYvHW6I1yEeg7ccubQmKQLsg0Pad3f+SNd76GWEXPXBGJQ/CYiEqqd76YXUpu7OViAqRELomNj+PI7fKhQi0/di1EBINUQRaE4G27+xzxtCXk2sLWU9f6iIQlW3+jErsfVRarKm2GlHhl0cSFRnH/equR6Dtx656ONSnCLQuAm3f2U/fKWgHWP4afBGICpUr1s60LdhUlai04EXNoEptP3ZlgKGaUARKgUDbd3a2AyzfWK3pRAVrRPwZlcjf+ilFi4tfyFYhKrbZE4TZDpuuTa+dw9p+7Grni691by8E2r6z+wtD8fVk/hpw04lKxZj9PlHJ8nX0MrbuViIqwJ9ICEl5TYi8kJTx6j+DQNuPXdoQ7Ai4Oo4rnFuJosP1s3JHyRc6UfSoTHF0kSauPuVTJ3HTqgvIxtP2nR2vJQPbOWPwwUc6mkpU8DbNnDEn5ozB96fa/Wg1osKvp+zT8FMYSa6v7rMItP3YdRYKdXEEXB3HFc7Twu3SQzg/KR0Pi+qmtFwirTy4PRkHvy0N6QXFkY6USdLUbBBJIVmLSO/Qzm6MASEAtux122YTlRGfPO1Nf4lLb6FViYptTOBh3F36i5hDBXTsygHUVjDp6jiucKoz4m0nj7e5KUzKsPygb8uPwihe2pV+yofSBUmeNkhPxvF0oW4lKqEQJVLw9wsBUaE3f5pNVOiNH75uJlHdWiBRuxAVGhvoksHPDx7P3VynndxKVNrpaseoK3UOkpQU/jQHT8/dsEl5RZGyDDZbpCPjKJxLl44rnKeV7iRppI2qP2Oyop39TCMjYrDdB72pRIXt7ULEydoW2iQwT6KCfplZ3wy5HpQXSa4eFMbj4MZB0ve2pdCxqy0ve3ClZcfgfri5X1qyxfEwlxt2eBzZjRrG08s00k+2XRL6rpOnsdnlYdzNy8dtBLqVqATCkyiSPgDI1qk0jaiw9Sn4dk67L6TF9cyTqMC+7JOJ2lCDElFZSTYo20Jmo0SlkJeluYWSHYP7yU3SVlIex93QJT9Jnh5hUc+o6ShPaZenl25eNpeb0sh4ng/pQHI9Hu50g6QoUXHCkypizphJH1/sUNtMolLdkXbemH2pKtQ6ifMkKrwPcndR0aOxpKjla2S5lKg0Eu0S5EUdmCSKHMVNetS5bJJ0uISbDp5P3DDSt0lul7uhy8tJabmOy026ZCOOn+s63URSSDoVo0doZ/exOn1RqxuszRmz83RQ04jKvDHjPmFq943eqBVnRVR4vyXbFEaSwossi1pWlIvORuCnY1cjUC5pHraGKDuO9IdVletzN9JJf5wwyjfMhi1e5gMd10n5kJT2uN/lprSBkggKyUDlaJHa2X2cPGOGgOucMVOng5pCVG4xZswvwzR7AynalWxdrSyJCu9/QAx+OsuAoCx/1DInTZfEft55UZl07CIkVFoRkA0xzG81wgJ5eu6GCvxRT2YyMA3ZJX2ZZ1A4LwvpcSltcX3upjRSn8IXSElOyE9yQYJoAdrZGU40m/FxY/5LM76evN+YB3yispsVq92dWRAV6mckCVPyQ5Kb4ook05avkXVrVF46dhWphRasLLZGaAvjxUa87SQdnp67bfEIs+mQrk3a9HkYd/P0Mpz8UvI0LjelQTx3u/QXhEtCQn6SCxJEC9DOznDy/BmNQ8ZMNZqoXHvxxS/NGnMK11N8yZmVsC2dSlTSX/Y4Yw50ub70h5WGpw3TTROvY1ca9Fo8ra0R2sI4DLZ4HuZy22xwXR5vc5OulNClMOnmdlw6rnCyhfg4J8/T6naREVe41Yg9UDu7wAVv/gDXB375l72nnnqqYeeXe3tPIl+xlb8oXVt60xIV2V+5Py6gUfp1XJuN0I9TZ6kr/UHlJXyCdLKK07ErKyRbzI6rwbrCqfq2eB4GN52Uxiaj6FA6aV+Gu+JJD5J0SFJcmJ/0uJRpeFwz3drZBfqeMZtBGA4vWjT3r9/7XkOIyj8//LD3ijHz2DbfM2ZQFKndvVkSFWDZjL6IPPM8ZRuJkpdMQ36Jj/STnpSkR1LGZ+3XsStrRFvAXlDjC4pD1RFvOwmWqOm5PtmjsCAp7Yf5YYt0SHL7tjAeb3MnSWOzk3WYdnYLovRBwD8577xXvvWtb+VKVr785S97TyxbRrMpuyzFafegRhCVovbPrK591PpBj+tKP8rD46l8XM8WT3pZSh27skSzBWyFNbwk8TwNd3O4EO6KIz3SIUnhkBTGbXA36cowmx9hQSfZcklp06XX6HDt7BbEsUYEsypYM7JxyZJjV1xxxfTOnTu9J554IhPSsm/fPu/jH/+4t3bt2pc+sXTpQf+Rz5S+6WO5GOk2fLP1O+rH1sxCAiltkAwx0ZRoGw62gkg9qqdNl4fxdNzNdbJ269iVNaJqTxEoKALa2R0XxjOmuq0+NoL7OWNu6u7ufmTZsmXPr1ix4vh11133EogGZkPolCQGZITiILE4F4Sno6Njtru7++murq77/8yY/8X/SjIe+Wx0FKXdg9PMqLhumjycu1sV66h15Hpwcz+wkX4K4+HcLeMRJ+OTYq5jV1LkNJ0iUDIEtLMHXDD6WCFeW2ZqWEMyBqKxcuXKA3SCxPBZN5ARioM8nR433E3GmE7YwloU7NmC2RTPmK3MvjrrEUhKVOim6JKUS1Y3TrJXRBm1jhwr1MPm5/WjeFsYj4MbB0nfm0ro2JUKPk2sCJQHAe3sAdcKj2JovQq2tM/q2zueMcNzxkz4j3x0XUrANTgdlZSoBFs9G5vlzfOs1WQuurmTTGYleaowLMLiXTlTOpIuvTjhOnbFQUt1FYESI6CdPeTiYcdaRipALoZDkgRGe8ZsmjMGO896PvmpzrAEJmrvyHYhKrabuC0sr9aAvMLyC4t3lS2KbVdaV7iOXS5kNFwRaDEEtLNHuKCYSfFJBfY5AcmI/agGszOeMdv9Rz143IMbsB7hCDSCqCS9AYeXPp1GI8sVhUxE0XHVOOu66NjlQlrDFYEWQ0A7e4wLenqkrX640H9kg68tbwlLDpIDgkLrUXyiox8cDAPubHzeROVsTsVzZX1zb1YNs64H1onhm1x6KAKKQBsgoEQl5kX2jBmlbwIRYcFusj6JwWZxoyAw8GMWhh7z+LrQG4qZZburtytRyfrm3ox2hDrkUQ/8QdjTjAppnoqAItB4BJSoJMQcrxPT4yD2OAePdBacPpFRgpIM63YkKnnc3JOhX8xU+4wxOitZzGujpVIEMkdAiUpKSP1HO7VZlNN3GDwewlmdXUlpXpPn/9ZP0TBWkhJ8RfDYB+OWLkIPxkljFYGWQaAViQoG+qgnXUh5c5B+0rPJIF1XHMLjnLZ8KcyVB8WXXbbTjEqrX8ss2iJe59+WhSG1oQgoAuVAoFFEBf+CRp9++unHvJwPEAB5hIXJeO6HW57cPtfl4XC74lzhMr3Nhkwr/TYbWYd99rOfxY1itEFNvF2Iio2k2MIaBHshs9HZlEJeFi2UIpAvAo0iKlj85u3Zsyfre+YCe7Ybd1AY4lwnjMu0cfxSlwrrCqd4LqWuzY8weXIbWbtHR/Gkq5pnvq3zjPV2IiqEK5eNwLgseWABbeibdmWpjJZTEVAEoiGQC1EZHBx8/+Dg4NdYEapE5eGHHz6a9U1T2uM3cnnzlnGUlocjjPu5W8aRn+u43JQXpSEJfddJOra0FMbzo7C85bXXXnvKLzNd4o2dnZ0vGmNGKCBD2S5EJUPIWtIU9i7a3ZI100opAopAIAKZExWQlHe+851HHnzwweODg4N/4y96qxKVb37zmwfyvonabtxhYTKe+7kbZSd/kESc7aS6U1ryB0mpG+YPspVV3PXXX489LFBHHCOXXXbZ1OTkpAeZA1lRouID3cYCH+zE97Z0AW0bNwKtevsikClR6e3t/Y3rrrvuCN0QH3744Znzzz//O8aY9+LGVmSi4t94awSD6iDD4cchJde3uSmMp+VhLjfPx1aWoDCXzbThjKhUScr09HTVJGQOZEWJSvuOT6g5ZulAUvraGwatvSLQvghkRlQGBgZuePOb3/zciRMn6u6Djz766Km+vr5/ww21kUQl7AaOeDq4G2Hcz908jsJJ8jiXXVs40ttOmy6FNVsSUQEpIZJCZWJkBf+CsziUqGSBYjlt4Gvj+5WklPPiaakVgawQyISouEgK3bzuvPPOWdyMv/nNb/4PCstLcuIQlAfXi0MUeDrYl36epyuOh3M3peVh3B01nvTyklddddXzr371qz1JUig/hF9++eXPo11k0FCVqGQAYglN4DEPXkXWxz0lvHhaZEUgSwRSE5UwkoKbF972wQ33z//8z+unW+jOlqHkN3a45UlZST0Kh5RxLhtSl/xSn9sjHUgcMk6Gyfi4/jO5ZPeLtSjDw8MVyKADM2vXXHPNcxmQFSUqWfZ4taUIKAKKQMkQmPCnVvEMOMn53QsvvHBGPu6RNzAiKt/5zndkVOZ+fiPnbmTE/S53kJ6Ms/kRRgfPg8IgeTh3kw4Pc7nDdCk+SwlygleTw0gK5Yl2cdVVV51aunTpvyRsX2iTINPbS9avtLiKgCKgCCgCGSGA789g464k5+2XXnrpEdf0P92sIImoHDiQ+0s/gSTAdtNHmOtE2XmaKH5eb5mW4nh4UN62/MgGSbJFksKzlnFJCuUPsvKWt7zlp11dXZgZSdLOkEan/zPq8GpGEVAEFIF2QaDubQ+6Kblko4iKvFnbSACVUepSOJc2HRkm/WHpER+UhqePogtbcexJ+1H8SUkK2QZZeetb33oEr663SwfReioCioAioAg0D4FYJAU3KyIqjzzyCN27cpFxbthcl7tRMPKT5IWVYdIfpEtxQWlIh6RNF2F0kl6ecvfu3d7Y2FjqLG666SYlK83rt5qzIqAIKAJtgcDQhg0bJqOuUaA7GxEVyLwO2w3dlhfd4EmfpNSV4TId6XM9rmNz29JQmJQ8PeKkX+rn7ce127JlS+pslKy0xTihlVQEFAFFoCkIJCIp/M42MzPjfeUrXzn293//93tP33t36FkuDO6+++5H3/Wud73Cr2kSN8jKwMDAXU1pxZqpIqAIKAKKQEsikJqkYJ1CRq+rtiTAZakU1pmAaOB6pjluueWW6XXr1v1JWeqt5VQEFAFFQBEoLgKD69ev/1Hcxz38JqYkpbgXN0nJQFZAOtOSlbvvvlvJSpILoGkUAUVAEVAEagj0rVu3biLta8V44wPfAapZVUfpEcBGbkpWSn8ZtQKKgCKgCJQagUxIii6eLHUbCCx8lmTlvPPOuz8wM41UBBQBRUARUAQYAkpSGBjqdCOQFVnZsWPHy4ODg19z56QxioAioAgoAorAGQQ6BwcH/2X//v18mUlst86ktE9zAlm5+OKLX4iyS3FQQ3rwwQePK1lpn3ajNVUEFAFFIAkCneeff/53Hn300VNBN5SwuDvvvPPFc889994kBdA0pUUg9kaAtnakZKW0118LrggoAopA7ghkQlL0TY7cr1ORM8iarOg3fop8tbVsioAioAg0EAElKQ0Eu8WzyoysYHZPP0jY4q1Fq6cIKAKKQBQEBgcH/+bhhx+esU3FRw3TmZQoSLeNzsj69esPp9l7B+0OjyCVrLRNm9GKKgKKgCJgRwCLF7EuICohsenpugI7tm0emno3YyUrbd6CtPqKgCKgCLQwSan7iB//oJ/DHdQYYCvsiJMf2ZJ2pZ/0yiyzJit9ZQZDy64IKAKKgCIQA4EWJilAIc5NX+qG+W0oyzSuMnA97pb6iJOnLd8yhGVGVrBLsjFGyUoZrrqWURFQBBSBNAjgY3BYU2J7jBM17Ktf/erMmjVrvpmmHDmmlSQgKCupa/NL0mDTkXlIHcRTmM0ehXE9sknpyF82OYTvRaX9FAPSK1kp26XX8ioCioAiEBOBLEhKCRY50o2dbv4uCfRIl5AM85MelzyNLS/SlXoUDhk1jqepuT1jPDprgcVyDGbx3SglK8W6qFoaRUARUAQyRaBNSAow4zf9MAylbpjfZk+mcZWB63G31A+KW5A/CAoPlH4e12R3Jp9mYGRlsMn10ewVAUVAEVAEskIAO8Vix9ioj3ZseiWYSSG46m7cFOiQpAsZ9ySTZIP8kGFhtrwofVAc6dSkJCbSX1MshiMzsoLHScaYoWJUS0uhCCgCioAikBiBwcHB9994441HbOQjahj+xa5Zs+YHJdmAi5ME201fxifG1k9I9lx58XjKi8Js/qA40q9JSUykv6ZYHEeVrKT9VAP2admwYcOkkpXiXFgtiSKgCCgCsRHIiqSUbBEjv9FzN+HHw7g7ajzpkbTZoDguuR7c8iRdrocw6Se9qgQxkWedQjE9fVl8V0rJSjEvrpZKEVAEFIFICASRlMcee8wbGxvzRkdHvS1btnjw82N8fNzbtm2b96Y3vclbvXr1K8aYu4wxZVkTwG/s3E248TDuRnxcv0yD9PKMm69ML8tE9qpSzqBIf51ysTyZfLqBkZVhUb2hnp6eXf39/QdWr1693xizVcSjPe9AHHS6urruN8aMCB31KgKKgCKgCOSBQE9Pz7suv/zyl0E4+FbmJ06c8DZt2lQ99+7d6yF+z549VT8IC+LvueeeKoHZtWtXNR4k5rbbbju+atWqlwYGBm7Io7wZ2+Q3du6mbHiYyx2mS/GQQTZccTw8jg2eb9UtiYn0L0hQrIBUZGX//v3VNvroo496F1544XNENEDSBwYGjt57772zaOPUhnt6eg75OpvWrFnzAto64qCD9r5hw4YX165d+1CxINLSKAKKgCLQWghs7O/v/3ZPT8/8tddeWyUcQ0NDVQlCsnnz5gWzJzSTgvjBwcEqUaEwLkFirrnmmudKQFY4CYDbdtJV57oUxiXFk+Rx5OZx3I147ic3pOuUaWx+yrcqJTGR/jrlYnqqZCXqpxympqaqbRTteuPGjdW2PTIy4l1wwQVov8f6+vo+e9NNN1nXZE1MTHivfe1rD1999dXT09P2rYT+6I/+6BVsiFhMqLRUioAioAgUHwG85YAp7B3GmC18IeGaNWv+z0suueQYCIcchPGP0faIhxMRuGU6GQ+ycvHFF79A/1wLChcRgijFC9MlQuGyJdOTPpeUVupSOJc2HVsYTwPWU1unUhdRHk8n7ZaMNrZv374qGdm5c6eHWRM64B4eHq7G8ZlCxMOPGZLbb799nvRtEkQn7Pj93//9E6tWrfpseeDTkioCioAi0HwEOjFwYjobj2EwII+NjR2Ff2Bg4Bt4zv6xj33sRNgAnEU8biLIs/mQOEsQemNnKW26CKOTqVqdtvRWRcfsCumSHZIUDmkL4/Et4+7t7d1/7rnnzmPmD218+/bt1VkTzJ5gzRTWVIWR6SzaOMgSHnWWaF1Wy7QBrYgioAiUE4GNAwMDP8K/PNsgDOKAqW/MmjTquOSSS6axUJHP6BQI2ig3dujQiaKTO0paqmpUXWnblU6Gy3SUbyvKvtWrV/8FHsnYZjwwW0LkpVFt/L777pvp7e39rjFmUysCrnVSBBQBRSArBEaGhoaO4Nl60IF/mfjH2agD+WGh4vr16w8X/DFQVtdB7eSIQH9//8RDDz00E9Z+8SjIRmTC0iWNx58AkCfs6pxj9dW0IqAIKALlRQADOH9Gn3TAzSsdCMtll102pWSlvG2s2SVfsWLFB2+99daX82qjWdjFRzyVrDS7pWj+ioAiUDgE+vr6dtx1113Hshho87SB1zv9fSoKh6EWqPAIDJ177rnTWBNS9KOnp+e4rlkpfHvSAioCikADEejr7u4+VoYBHDcY7D+hsyoNbB0tklV/f/+j2M+nDMdnPvOZ2f7+/gdaBHqthiKgCCgCqREYveKKK+wbPRRwVMcbSP7r0nErPmaMGdezlBjInWDjXnvT3d39vHzNuIDNu1okLFbHDraxK6kJFAFFQBFoRQQ6Ozs/+YlPfGK2qIO2LNdHP/rRWWPM9gTXAtuYj+pZSgw6E1xvnmQIr9fLtlRUPxa0+zvb8jqoWxFQBBSBtkRgtK+v78lGvm6c9uZwxx13nDTGbGvLq6WVToIAZmN2YCYubdtrVHp8QXzlypVPJ6msplEEFAFFoFUQwEfUDuGRz8033/xiWdan4EaBfVWMMRtb5UJoPfJDYHBwcO+6deteQjvHzb8sB74F5H+4MD9w1LIioAgoAgVGYGjDhg2TYfulFHFQx1s/S5YsmTPGbC4wvlq0AiCAbfI/97nPvVLEdhxUJryGj91xsfi3ADBqERQBRUARaDwC2JIem0uV7cBCSGxrjrLrQsPGt5uS5bj57W9/+4tla+MoL33MU7fVL1mL0+IqAopApghEGr/FVu+1LdbDEiOd6+Bx3O3Sl+H4t4kD0/nGmNRvgmSKqhorDAJ9fX2P4IOZUY6s2zlv19wdpSzQoTb+/ve/X9diFaZFaUEUAUWgkQgM4yYfddCkgVbKoPTQJX2px8O5W+qF+bHmwH97p5HYaV4lQWDlypWxdlmmtihlUDuELulzPR7G3VwnilvXqZSksWkxFQFFIHMERrBhWpSBEjo00EKSOyxtkC6Pi2rPlh+m9XWdSuZto2UM4o2ZOItnqS3y9mlrdzzMpcvDyS5PF9WNGSHMDLXMRdGKKAKKgCIQFYGOjo7ZqG/50KBLMmyQpYGZpNSn8Kj2ZHryK1GJerXbUy/uLrTUHklSO3NJ3o6lDo8jt9SJ4t+9ezf2UvlSe15BrbUioAi0NQLYmhtbdEcZLGngJhmWhvRISn2E43DFIw7P6MPeSFqxYoV+C6WtW3Fo5WMtpqX2SFK2W+knPZI8HmE4bHFcL+wDoLpGJfQaq4IioAi0MAKDAwMDp6JMjfNBlw+yLjfp00At9cLioY9yDQ8Pe1u3bpXJq368/YPt0Fv4+mjVMkBgzZo1/xD19WRqlyStDY8Fcj3uhgr3czdL7mFGc8uWLdV27trWX79plUEjUBOKgCJQTgSwv8QnP/nJVwYHB72xsTHvnnvuqb7yywdSctNAS5LCXZLrcTfp8zDupngut2/fXi0bD4P7lltueXnFihUfLCf6WuoGItDZ39//7ZGRkWo72rlzZ5UgyPYEP7VFkjYdHsb1uJvbkm6entwg5SiffBSr3/ppYCvRrBQBRaBYCICkPPjgg8cxaG/bts3D12RBVKLMrtDg6pJBAzalkToUbpMYvLHx1dTUVC0aG76tXr16f7FQ1dIUFIGNr3/965/HIxa08aivK9cam8Mh23CY32GmFox+iDd86EC7X7t2Ld5qGyoorlosRUARUATyQWDdunV/cvfdd09jIOzr61vwL44GyiJJzPiATOHANP6aNWt+YIzpywchtdpKCMRdUNusdg/yvWnTpmr2WJt16aWXeueee+5T2s5bqTVqXRQBRSAUASIpGA2xsyt2vyzD8e53v7tywQUXHF+2bNlJfLfFGJP2K7qhWKlCSyDQ2dnZeUI+Uilim8djHvxxwLosnCArjz766Kl169ZNKFlpibaolVAEFIEwBDhJwUCNaWZMN5fhGBgYOOrvl9KqsyhYHyEPW5jUUX8wAkNoO2Vo43gshYXj8k03PI5VshJ8kTVWEVAEWgCBc889994777yzboM3rE/BQtWiHyVaUFhdjIm1ChFP3rJspMQWxtMEuXkZuJ60yfWkm6crq3uwp6fneNHbOMqHdViuN3+UrJS1+Wm5FQFFIBICg4OD73/nO995RA7WIAD4uF/Rj7GxMcymbIlU2eYqSRIQVBquy908jYs4xA3nNuHm+XE313OFc51SuPEKu4sAFKXtR+mLjKwMlgJ4LaQioAgoAlEQcJEUDNDYUA3PwvnbNI0euDH40sfXbHnjTY3BwcF/KcmaFNvNXYaRX0pcTgqTbpufLj9PQ2FB+jIuSXqeT+HdAwMDf3bffffN2NpXI8KwPiZoUzfE4w9DkA6VE/1l/fr1P9I3gQrf7LSAioAiEAUBkJQbb7xxwUwKDXqQeJOmmQtq8ZYD3nawHfgXvHbt2mdLtJCQbvokcZngln4KJ0k6pOeS8rKTTiaqRAAAIABJREFUngwnu7ZwGeay4Qqvpffq64VKhqapJW6so29gYOBws2ZV8Do0NnVzHeh/WNge9UA9NmzYMKlkpbGNSHNTBBSBjBHo7e39jWuvvTaQpNDAiHUqIAwgLZiCxqI+rF9pxLFmzZo5OUhjhucjH/nICZ+klGkPCX6jJneYpCtPeuQn6QpHvIzjfrjpJFs2STo2adOvhUliIv01xWI4Rs8777wpLCBHGwd5wCPFoNm8rNr/e97znpM333xzRb55hDJgk7ck+7ooWSlGo9JSKAKKQEIEBgYGbnjzm9/8nBwYgwZezGpgrxJMQYOo3HHHHZhpmYtiA4N/kn+rmI5fsWLF3/b39x/Aa8dXXHHFNM7e3t4jnZ2dnyjRTApdKdzs+RHk53HcbUtviw8Lc8UjnMdxN8871C2JifSHGmi8wmBXV9f9aG/+14i3rF+//rB8y8bWT/BYhvbxscW7wkC60Z7xXS18BPSSSy6ptvHVq1dXrr/++jk8ykl6MLIy3HgoNUdFQBFQBBIikISkyIGSBsCBgYH/dM011zwXRkKSPD7CAI7peEZG8NrxqH+WdY8UedMP8lMcSXnFZbjNjzAe7nIH2Y6aRtpAxjztAv+CBMUMGDrvvPOedj1+pL6B9oq3cqIQd0oDafm690a/jV98/vnnfwf7pHD9uG70zQsvvPA5Y8xIMeHVUikCioAiwBDIkqTQ82/YxFsTV1999TQ9GsLUOU5/Fubo8uXLX165cuXT2JI/6kB78803v9jd3f1eVvxWcPIbN7mjSOjQCRwojcSE61Ac13W5SZdkkB6PI32r5EQFbu63JihuYB8+x4D9Vu69995Zat8kEYa4/v7+CRD3qGQF/SPkMw+dWZAVPL667LLLppSsFLeBackUAUXgDAIjF1100QtRB1EboQgZ8DZhK3JMm9PpD8J4bbg6A0LfD7LZpjCUDyTF31221a4dv8mTO0y6MEA6eXJdaRdxFCbdPJ2M42lIzxZGcTVJ5IQIipQ1xfI4hnp6enZR+yaJME7co5CVhx56aAYzNZQuAIIqWYlD8qkvcRnSdwOy1yhFQBFQBDJAAM/V2SMSm8UR/KNKszAwq4EOZAWLFG2Pi/APc2ho6EgLzqTQNaEbPEkZTn5IqcPjbPE2fRkGv+102ZbpuV5QXFWPiAklIuJC/laVmGW8+OKLX5CLwEEc0O7f8Y53/HT16tV/EdJnOTydUUg+JyY2N+vDeLzkPDo7Oz9pjNG9WJwIaYQioAgkQcAL+HdWGJLCKrYFj4v4Alm4/RmYVl74RySBQeEkJJIIyLS2eG4Xbqkj413+KOlCdSRRcWXWouEjAwMD38A1oEXg69atewntvqen55Ykdc6KrFx++eXPg0zZyoDPaCxfvnzG/xyFTUXDFAFFQBFIhED1+x+WvRNSkxQ8inn961//vDEm8F9YolKf+boxLZBt1W/0cGhCb+5MmXQhyc2iQ2dGKA1JnjbITfokg3Q1LhoC1MZTk/AsyAr6NB5PSbJC3/oq0U7P0dBXLUVAEWg6AoMrVqyoLlLFtLJPVrDCfwhu2yMW27SwLQwDGl5jlgNa02tc3gJEuflDh86gmkpb3M/dsEH2giTp8TyD9CmO66u7AQiArOzYseNlW5+NGibJCpEUpMf2A6ersaMBVdEsFAFFoE0QqPv6K4gJ1qNkQVJs/7raBFOtpiJQaATOO++8++++++7pqMTEpkdkBYvguS3se+Sveys0Blo4RUARKA8CdUQFAxIWzaWdSVGSUp4GoCVtTwT4LIiNiEQJA1mRG9VhJ1x/w7v2BFZrrQgoApkjMIrFelEGpag6eCsh6YK/zGunBhUBRcCJQBZkRY4LEfZ3cZZHIxQBRUARsCGQKVG56aabjuBjhbaM2iQMCx/xfF7P8mHQDguyF3RDkJXf/u3ffkkSjqR+fA4Am9ctyEgDFAFFQBFIiMAm7AqbdFDi6ZSkVK+AEpXyERQilW1JVNBqV61a9XH0X96fk7rx2BivUSccjzSZIqAIKAILENiC1wmTDkqUTknKAlw1QBEoFQKYCc2CrGDdCj6QWKrKa2EVAUWg0AikJipY8Y/p40LXUgunCCgCoQhkRVZ8olLWj3+G4qQKioAi0FgEtt1xxx0naWYkrlSS0tiLpbkpAnkjALKCBfGYGUl64COLEb5DlHdV1L4ioAi0CAI7sEFTkkNJSou0AK2GIiAQwFt7UT6O6Bo3NmzY8KJ+bVmAql5FQBFIjEAiooIPpuHrr4lz1YSKgCJQaASwo3RSsoItD4wxWFiuhyKgCCgC6RDAxkzYoCnJoTMq6bDX1IpAwRFI/K0v/d5Pwa+sFk8RKBMCaYgKyI2SlTJdbS2rIhAZgcQkBeMC1r0ZY7ZFzk0VFQFFQBFwIYDvdMgtsOPOrihZcaGr4YpAKREYevWrX31oamoq7lBQ09cPE5byumuhFYFiIoB1JuPj47UBJopjYmLCQxqcu3fvrn4tdd26dbP6inIxr7GWShGIgUDqr6ZjDNHv/cRAXFUVAUUgGAEQFZANSTzwj+iGG254CYvicPb09Bw3xuDz7V5PT88hpMPZ09PzpdM50M6eunguGG6NVQQKjUBXV9d+6ufU97nEuCBPGju4xCwtZmsLXVktnCKgCJQDAaxRCSAeY/7KfRCQwXLUSEupCCgCGSGAfi9P+lNSk/SnhUuQnbVr1z6UUTnUjCKgCCgCioAioAgoAoqAIqAIKAKKgCKgCCgCioAioAgoAoqAIqAIKAKKgCKgCCgCioAioAgoAoqAIqAIKAKKgCKgCCgCbYGAXLip/oWLWRUTxSTLNtAWA0vUSg6dVqytEle3YqFtIPc2sN0Y0xm1gxZAD4Mvvg8zrqdioG2gIW1gyhiDNzv18BEAScEApGRFMdA20Jg2MFmyj8KBqGCM0EMRUAQag8AeY8yWxmRVjlzo5lSO0mopFYHyI4CbPm7+ZTmUqJTlSmk5WwUBJSriSipREYCoVxHIGYFWISrV3ZBpt1Qmk8AHW3RwN4WpVATaCQElKuJqK1ERgKhXEcgZgVYiKllBxckJd2dlX+0oAmVCQImKuFpKVAQg6lUEckZAicpCgDk54e6FmhqiCLQ+AkpUxDVWoiIAUa8ikDMCrUpUXAQD4XS6oOVppduWloeRm2RQHi4dHk5uSD0UgWYgoERFoM6JCu+g3C2SRPbyjs7dkQ2ooiLQggi0ElHh44Stj8sw6afLy8PJTdKmgzCKJ8nDKA1JruPSgw7X426yo1IRaAQCSlQEypKoiOhUXt7RuTuVUU2sCJQcgVYiKvxS2Pp4kjBKQ9KVB8VLyfXJTTrkh5Rh0g8FCsOrojRWppW2fXQ2Z2gf5evjFfXd2zLMA7bkkaX9dn81V4mKaF3U6RBMnVKoJPZye9yd2GAOCTv7+/sf559BT+l+XGzmlan9gYGBb1gGoaHVq1fvT1nuA5S+r6/vEYHz8MqVK/+Z4tPKVatWfVbYbzdvqxIV23W09fuwMIonye3yMHJD0sl1uZviueTxcCPOdXj33HNPJuell156yrJHRia2UUaH/aGurq5TWdUBtowx2CyUjtG1a9eeyNE+5dMuUomKuNJBRCWw40YcHCg7bss1WFA40pCbJNnhkuIgbQfFI47cUneot7f3lfHxcS+LE7ZEB87U/kUXXXTUsgfHluuuuy6zOlgG7Mzs79271+vu7n7edrHaKEyJysKLzfsluUlybRlGfkhyc31yB8VZdTCbwmZUvKyOsbEx9GE5Y5CVec9hf2jVqlVHs8oEtsQ4N3rFFVdM52ifrlG7SCUq4kpLokIdnqRQr3plp5d+SsPDyU3SpoMwiifJwyiNLYzrSz0ex93QGxoYGMisA8OW6MCZ2sdgYCMqGJyyGiTYNSAct2Rlf3JyUonKmV1eW2HDN9mXqL1wKXWkn3R5OLlJ2nRkmNSleJJh8dBboKNExT6qKFGhZpWbVKIioJVEhUcv6Lh+pC08LIziSbryoXgpuT7cFM/Dk4RlSiSUqNgHNgpVolJtrq0wo4K+RifvgzY36bn6J48Pcrts28JtYdI26chw+KtHKxGV/v7+zP7MwJb4Q5bpjIrFPl2SdpFKVMSVDiIqQrXmrXXkWkg4caA0JFnSOtJB8ZB0cl1yUxyXFMcl4uXBw5SoEIvwpYUE6oyKbEHp/K1AVNIhUJLUSlTE4OB7LURCiUq2bVqJisCzaEQFxSMiQSREFLnqJR1bHA+z6fEwJSpiLGL4E45KVAiJbKQSlWxwzN2KEhUxOChRyb3N+RkoURFIZ0FU+I2fm+fh5CZJetKPcAojSbpcBsWF6fG0SlTEWMTwJxyVqBAS2UglKtng2Egropck9zoWuyY3KFI67A/po59GNpfUeSlRERASUcHNm06hYvWSLr/pkyKPC3NTGi5tNnk8uaVtCoeUcdwmdytREQOdEhXejHJxK1HJBdZcjYpektzrIBLJDYqUDvtKVHJtHpkbV6IiICWiIoJb2qtERQxu3KtEJfe2r0Qld4gzz4B3kVRuB5FIZZMndtjX15MzbxK5GlSiIuBVoqKvJ/NxjmaieDNpyUc/njGjnjHbT1d4h3/urnQu2T+3sueAt2jRNz1jdnrGbORAZORWopIRkA00U9dH0ngcRCKNybq0DvtKVGI2Fs+YTn+MoPFhx5wxeyvdy7+LMWLemMf8cWM4puko6kpUBErtSFQ4BProp26Ywx5XtTVChFNLEZXvPzu+8eDn/tOn5zo6Kidfve7osTe9fu7Y6JXe83fdWne+/Etv9v7ja5/3vv/sNya//8w3xicOje/8/jPjYy/+5jt+0R+gku6FokSFWlZ5pOglyb0OIpHcoEjpsJ/3OJfpWz+WbR4a2lImDo6PPv8779qLxdSvvO6108d/YcTDeCDHCIwb/z7+Je+pH33jQHWMODi+48mD45tOvub8d6QkMUpUxBVve6KS846Nmf6T0Q3fROsN8WJGpNLV9d6JZ8a3PHXwiX0TB8c9foKUcX8U9zNf+UPv+GUXzWAQqyxZ8mN/VoZvJx5SKqNEJQyh4sULOpDc6yASyQ2KlA77ukbF0aY8YzaDWDz5zPjWp370+AE5BiQZI378xx/zjm9YfwpjxGxHx5OeMVs9+/eXHKUySlQEMkpU8t1aWokKG0gbteEbBp9K5+JJ//VSmiWqSj4QBQ1CPA7uoBP5zC9Z8leeMVGmgZWoiEGoBF7WitM5HUQinVGW2mFfiYpoZJ4x22aXLP5po8aIyqJzZuYWLXogImFRoiKulxIVJSpsmCv3ox8QhfnOxd/A4HPk9l/3frgfs7dnZ03IHUQ6iMiQLvzcTfEkEfej/7rLO/aGy2bnFp2DmRY80+4U/Yx7lahwNMrhrusjaTwOIpHGZF1ah30lKn47w7qT2c6lEzPLl80e3v5e79/+36/W9W/q65Cuk/d9m5vCSMLOoc//J++VdWtPzXYsOuYt/NaT7AVKVAQiSlSUqNQNdH7n5M2kFGtU5ozZWVm0aBaEAc+N+SAR5qZ4LoED+bmbwkjyOAxGMyt7Z45f/Jo/5QAKtxIVAUgJvHV9JI7nwIED3r59+2pJHESiFh/XMTEx4eFjn3Q47KciKvhg6/79+ykLL+udaYFPiP3UTQR/HuY6Ox/Gn5iXbnhrlaDY+jDvz9xNulzyeO7mOnBT3FM//FsP5KiyuKNy8jXrtwZUSomKAEeJSkKicuLEieqn2Xfu3FnrwJaPdSV+9EP28el0uHFkvUZlenra27p1q7dnz55aHdCpRBtJTFTwqGfbtm21gTqPRz8YgPDYZXb5slkQBdcgQYMFxZOfJIWT5OHcTfEkXXHf/9H4NoEjeZWoEBLlkbX+EceBm+/g4KA3Ojrqbd++vZrUQSTimK3pggQNDQ15mzZtCrOfmKiABA0PD1fPxx57rJp3lkQF4+fGjRvD7KdqKZ4xg5hFOXnu6lkskKe+S5L6MMmwcBkPv0xLOq64pw4+Po1Fu46KKVERwChRSUhUQCA2b95cPXft2lXtwFkSFXRgso+8cGRNVLZs2VIlEhgo6F8fOpxoI4mJCg2gGOgwqOZBVE6tG/zDU4MDM3wWxTZI8IHE5balcw00pMttURjJp54Z3y2whFeJigWUggdV+1/cH/wBQB+mvoz0WRIVso/xB30twH5iogKChT8bOIlsZUlUMAZhfBsbG/NoHLXYT9U8Znt79x973UWzP3jy6wtICu/fvC+73NS3eTrp5jpBcf/z4OMnsNDfUjklKgIUJSopiAoGB5zUwbIkKjT4wD7N2uRBVDBA5EVUMEhjxiYvovLks+Mj//6trxx2DUBykKDBh6SM5wOM1IHfdfJ00o23jSYnx/maFSUqYhAqgTcuR6nqYyYU7R99GCQ9gEjkbT8xUcGsK8YInHDjsBCJxK8nAxeMEyAsNHNssZ+4iXz/mfHN//6N/+skHrvIvkl+2dcRbgsjfZJSxzU+cD1KWyd/NL5dVFCJigBEiUpCooJOBTKxe/fu2iCTJVGBUdgmEgR/1kQFAw9IEH/G7Xc23kwSz6iQfZoyznJG5cDkeN+Tzz4xWdfhxevHiOODBLn9OlqJB9kjXWmD4klyPQqT8tQF5+E15s0+qEpUeOsqh7vWx9M6spxRsZXFYT8xUbHlYSESiYlKRPuJWsm/To4PV2ctLOMC76O8D5Mb0nVSWtKFn7spnmRQHHSwoHd2Rdez7K1BJSriiitRSUhUbB0sa6Ii88iaqEj78PudkzeTxERF2s+SqNj2RaGBgUs+SHA36djCEMfDuZvSkQyKI53qArqODqz2x+vLSlR46yqHWzblxH4HkUhsTyZ02G87ooJZzCcPPjFBfTBI8j7M3ZTGFoY4Hs7dlI5kUBzpvPyWN8xUFi36of/GoBIVMS4oUQkgKlNTUx5WvIedNGUZl6hgxiHMNuLJfhKiAnIQJQ8a8NCpRBsJJCpR7NOK/qyIChaqUgcPk3yQIDdJpCU3SbLH/dxN8SSD4kgH8qW3/cLM3Dnn/E8lKqJ1lcNL3WOBxBiBxbJhJ9Zo4XAQiQV2KSCqfZq1dNgPJCooW1j5EY+y4Ig7o4KyRbFPdbbYj91Knnz2iT28/wW5eR8mN0mkIzdJssX93E3xJIPiSAePr08OrDo5Z8wuY3TDN3nBlagEEBV0YCz0Cjvp2W1cooIbd5htxJP9JEQFJCVKHjRIoFOJRhJIVKLYp8dXWRCVuSVLPjn97l87Rh08TPr1qQ020OcDR1y3zI+nl3Hcj+ldvBr5G8Z8zxjjWu0voC+EF2XFLFA7H9Q9UksHkUhtlww47AcSFUobVVqIRKEe/VT6uh+Z+oO7nGtSeL+EuyhjBN5anD3nnJlzjXnYhO+10lb9UYlKAFGJ2nFJLy5RoXRRZRKiEtU26fmdlneCQKJC6aLItEQF06KVxR3HsUW1HGxcfkkkgvw8zuWW+XA9GSf9mFUZP+ecF5So8OZVCrezeUed8dAZlfBZJwLZQoQiNxLPmBH8IZj8mwdLN0Zgwe9Mb/fJPzbmH5So1F9yJSoBRCXqlCVNicYlKnGnXJMQFbzCGGfaFTfe+iZiAolKFPt4YwBHBkRlGzZUC1rBL8lBGJFwxfNwH5O6f148TObp8mMHWwyitxgzJjAusldnVIyhe2hq6ZjxSG2XDDjst82MCrapP3rFpbOuPmgL5309TjxPx8cDm9tm1xaGDx8eWbz4uBKV+iFRiUoAUaHOH1XGJSpR7ZJeEqJCaaNKv5PxVhJIVKLahV5aolJZ2vFVbI1v6+CuMD6YcB0+mPBwcvN03E3xJIPiSIfL470r5r5qzP/BAS64W4lKAFHBY9koj1bR9nE4iISzG0W1HzJjE0hUULYodaBH0JYZj8BHP1EfoRMIFvuRu0ilq+vf4jz2Qd909WGE08n7MLl5Ou6meJJBcaRDEvtB4c/Mm4z5UORKt4Fi2xMVfFKcOoiUcWdULJ8nD/y8us6oxOthc91d//KTe+6IRVRoACiK/OnIcGW/MQ/Eq3lTtZWoBBAVLHSPslidbvJxiUpU+zSr67AfOA6hbFHqQIv6LeNcIFFB2aLYp/HXYj9yB/AWnTODmcui9Pe45cBsMYjKB435/ciVbgNFJSoBRIU6TlRp6WCBA0RUu6TX7jMqc4s7jj/zlT8s7SCEQevwbTfOP2nMIyUaW5SoBBAV6ptRpYNIRE0equewn+k4ZBnnAolKaKGFgsV+pO6CrfJxk8fC9bgEoUj6xwZWVj5vjG1X60g4tKKSEhUlKnXDhD/Vydt6IR79YCEtBiHXVvlFGmjCynLDjdfrGhXeworvrusjaTwOIpHGZF1ah/12ISqjGCPC+l/R47/9/+07qmtU6gcFJSpKVOoGuqISFTTbucWLSz+jgkFS3/qpH4RK4KvrI2k8DiKRxmRdWof9diEqw60wo/K1/+ehKSUq9aNC2xMVLICt6+kpPLqYNhi8tItpZ5cv+0HSNSquBW2ucJ9QZP7v7PHvPIwV/XicUpZDH/0YE2mNRZR1GNddd90rlptQ3vaHent7X4lSvig6sGWMGWINeHTDhg1Ho6SNomOxz7IKdoKoJF2j4hoLXOF5jRG799z7lKWNBFe8xWPbnqh0dXWdirLiPYoObIkOPJSl/bVr156w3OS2XHrppZnVAZ1StPnM7OMLrN3d3c8L+5G9x68c+ZU4z5/5ABPFLaeEZRofm9qbAOSX6YL8D+/73BHLNYyMQRMU256orFix4m/7+/sPZHGuXLnyn82ZTynULmVfX98jWdiGDd/+xprxM46+np6ev8sqD9gyxvSxPAb7+/u/nZX9/v7+x40x/EOeLKtg5wu3bv5E0u0LZH+nfszDKYwkj6PxwCZJP4r83+/d9k9KVOqvc7sTFXQGfLmScEgrYYt3sLzt42piwEhbbp5+W30Tqf5z4vFp3bbPmoss3d6nfvT4gSidnXRoIJFSxpOfS0qDMO526fBwl/uDH7n135SouK+vxigCaRB4cnJ8MMqHCHn/pL4tJelQOPm55HHc7dLh4S73VW/5+a8pUalvBXTTqQ9VnyJQUATifucHg4ftpEFCxiHcFUZpuIQu9we5D995y+yXli99VolKQRuXFqslEHjqmfHdQf2Qx8m+zv2kx8Oov7vCKA2XlIaHudzH3/S6l/5XYx5TolLfFJWo1OOhvoIjgK+iPnXwiWlXR7eF80GFx/MBhLtJh4dxG9JN+kESj6wqHR2VW435FyUqBW9kWrxSI/Dks+MjQX3RFsf7NI+XYwCPg1vGczvcLdPZ/Nh6Ad/6udCY/6JEpb4JKlGpx0N9JUBg4tD4TltHt4XRQCIldClMuslOUDyPI/0g+cJt75ytdCx6Ybkx31SiUoJGpkUsNQJPHXxiX1B/5HHUl6WEDoVJN6UPiudxpO+SWFdz7HWvPTn/qlf9pX49eWHTU6KyEBMNKTgCJ37uZy84/sZLp8MW1vKBQrrJLyUfSCgOYdxt8/N00v3sn/5+dbdJ78zbPvgSsb71U/A2psUrNwInzz/3Q8cuvTD0u2C8X0s3+aXk/ZvibGMCj+NpbO7nb33n7OzijhewaZ0SlYVtT4nKQkw0pOAIYPO3uSWL/+nYGy87Zev0MixowKA4kjwtwiic3C7J03H3D/fv9WaXLT112hD6Gg4lKj4QKhSBvBDADR83fhAA3h9dburntniKI8l1aDxAGLldkqfjbvFHBpDs0Uc/9S1DiUo9HuorCQKeMUOVxYuPvPgr11ZcryNGGTCgQ4MMDR48HQ8jt9Tn4dwNknJqzapT/nQuIatEhZBQqQjkiABmMCuLzpnBF4l5v+Ru3te5W+rAT2MFuUmfdHk86VCcS4KkzHZ0VDxj+NuWSlREu1CiIgBRb3kQ8IwZqXR0HMLMyg+e/HrgYEQDhWswkeFyoJHx0k/2Sf7H1z7vzXZ1zsy/6lV/ixkghqoSFQaGOhWBPBHwjNmEBapHbnyb8w9N1L5u6/M8jLulTRoXuMTmldigzjuzRQaHQYkKR+O0W4mKAES95UEA/5g8Y7ZUFi/+j5PrB0/ZvgOEwYMPINxNg4YtTA40pAMpT7LD5Uu/fv1354zZZUFTiYoFFA1SBPJAwDNmo2fMXbOLO156+aqfm7Wta6P+TP2X+jr5IW1hMpx0yB6X3Bbc2OulsmbVDz1jbN/9UqIiGoMSFQGIeouLAIjJvDH75oyZ8v+J0D8Sb76jo+p+4Y53ebZHQTRoyAFDDjY8ng88FE5hLv/EwSemvv/MuG3wIWCVqBASKhWBjBHALOucMXsrxkwuGCMWL/bmujq9qT+4yzr72rAx4pnH93//2XG5ezBHQokKR+O0W4mKAES9xUMAg8+8MY/xgadizH4MSKf/6uyYM2b3vDHjc8Ycm1+6xJv6o9+tG4j4AOQiGjKcExgex91c58mDT5zAa9MHJsf51uI2MJWo2FDRMEUgBQJYs+aPB7U/L3PGHMAfG3+M2IUxomLMy5W+Hm/yr3Y3fIx46uDj008+M741QjWVqAiQlKgIQNRbHASqb/cYs5sIytyZf0mBW/D7pGbfy7/05tojGpr9IElkg6QtHHF0UjwkhXFZ6Vx68umv3X9xROSUqEQEStUUgSgIgIjQGFE5M9u6TawLqzNTJTXLl335p791Q60/8z5O/ZxLike/p3A+BlC8LQ56xy698F8j/ImhcipRISR8qURFAKLeYiDgGdPnGQNmgH9IeNQTSFBkqf31K+Mz6wa9w7/3vmMvbn7rSSxewyJXPqjEcWPBLr7MisdLM2tWnayW7cxi2c0y/wC/EpUAcDRKEYiKAMiIZ8wef4yYxpszQQRF2sWfGs+Yfa/8/CXe83e8a/bI/3Zj5cd//DHPttYt6jiBNTB4k+fI7b/uVXq7T86dc86Md+bP1rDMP8CvREWAo0RFAKLe5iOAfzyeMRP+AHTA3wQpUcH8QQJk52Slc+lB36b3ysjwURD4AOSqAAAgAElEQVQOvLqIE9tX43ViOSBh0Jq+6frKqXVrjlPaypIl3/b/xfFP3UctnxKVqEipniLgQMD/I0OPg7EeJQ4RqLPqE5zqI6O5JYtfRD+fW9Z56thVI6/Q+HB4+3urf1Js698wdrz8tl+YmRlY+Uo1bceio96ZPzBbUc66zKJ5lKgInJSoCEDU21wEQEr8GRQMHHi+zF/tTVQ4vP7nk4wTnjHX+LMtCIP98bmVPQfmOhYdPf6my++bODg+Sue/To4PYwD0yQ4GnZFEBahPpESlHg/1KQKxEPBnUvb7fTrVHxnKGG/feMZgfMC483681uz/GXmssnjRf6cx4vmPvud2Gh+qcnIcf6qguwuzvmkIE5VFN3xjSPhOJSoLMdGQJiLAHvfszrIY/iCCQQj/vpL8y8mqOEpUskJS7bQlAj4pQF/GjEpmfdl/lRlkBWfiGZoMLorOqAgQlagIQNTbPATYojjczDM/2AC3L3Pj0Q0qUYmOlWoqAnUIeMZs9mc9cvnDwf7Q4NFz6tncusJH9yhREVgpURGAqLc5CPiPY/AvCYvi8GGuzA9/ypjWvvAtqzPPK8CgEpUAcDRKEXAh4K9dw/iAcSJoHxKXiUjh3pltD5AHCEMzDiUqAnUlKgIQ9TYeAZ9A0CZucd6giV1Yf80JTe9mseYkbhmUqMRFLBt9vIpqO1zhNt1WCHPV1xVemDp7xtC6FNy30h6u+oKg4I1D2jAu1/HIUQklKgKYViAqrgaHqgbFCShawuuqryu8EJVmq+6zeiTjqm81PIf84uCoRCUOWmd1ce3ounJJ7rOaC12kA0lu0pJ+Ci+q5HWgsvOwoHKTHpekT7bIXyhJj3ywiZtfMKoDvFR2HhZUfqlP/potf72Kx/ILspd1nBIVgWhRiApvYNRoeJgods1Lugiw6fP4WqICO3gdqOw8LKjopMcl6ZMt8hdGitkUmuGgOqCcVHYeFlR+qU/+mi1HnkE2s4xTopIcTbqWJGvXNMRkmD6PDzFViGgqL8kkONjScHuFqCgVAoTBf+TDZziovCRtdSITXHJ9W5pqvL+rLWZYeJ7cTl5uJSoC2aIQFd5YeCPiblH0qlfGSz+3a0tfxDCqA8modeD6tjQyvhB1D5jdoPKStNXJVgeub0tTjWeL5rKaxbGVxRamRMWGSrQwurZShqUmfehxN6WzhVFcESWVV8qwspI+6YX5Sa+p0jKbQuWh8ktJ8S5J+ojnbtKvhvkbwjVjVkWJCl0JXxaZqNgakCj+gkZmS2MLk3aK5KfyShlWRtInvTA/6TVNhsxsUPmlDCsv6UOPuyldLcw7+y+NZnJIJ0+pRCU5unTtpAyzSPrQ425KZwujuCJKKq+UYWUlfehxN6WzhVFc06RjNoXXgcpNMqysUs/pb9KsihIVcQWVqAhACuClTiNlWNFIH3rcTelsYRTXFBkyq0HllTKsrKRPek4//VPDxm+k3ACpRCU5yHQtpQyzSPrQ426bP8xWEeKpDlKGlS1In+LCbDQ0nt4GdKwVoTJLGVZG0ic97uduNBZss+/hI6ik3ACpREWA3OpEpa7RiboX1UtlljKsvEH6FBdmo6Hx/oZNeAa8yZIxlVlKi2pdEOlTIPdzNwYhfCsErzviLaDMNo6ijB1SiYoDmAjBuH50Dbk7LCmlgR532/xhtooQz+vO3WFlI10uKQ3CCnfMnf0oqe2rw1QPlJu7w+pBdaU05Cc7delnz37OI8knM+psRfQoURFAFY2oUIOhBiSKu8BL+hQR5ie9Ikted+4OKzPpcklpEFaow38FEAQBryXbNlaieqDc3B1WD6orpSE/2alLzz5qFuujh3VG4nmUqMTDi2vTNUUYv65cx+W26dvCXOmLFN42OJwyZurlM38kbHsrNQSH05nQ15m3N6gRKFERQBeZqIiiOr2uwcYV7jRUkIiGdL5m15U99nFtld8QHPzvdGBW57EGYaJEJR3Q1K9JprNW3tRUf5LlrYmj5PTYZz64b1L9STqsJQ/2917yMLOS3EqslEpUBFxFIiooGjU2kqK4beOl+pNsuYqzxz6jAZWj+pMMUE0W1YTHP0pUkl0qSkVtgSSFt5uk+pNsufrPnX3sEzTbSfUnmQsO7PFPI74BpERFXEUlKgKQgnip05EsSLGyKQZ/7BNikepPMkQ9WXSDH/8oUUl2mWSqXNuEzKzA/pbFYdaYqdno68dyxeG0cXr8g3tm3ocSFYFw0YgKFS/XRkeZlEC2JA606yO+qRHxGuSKg/+Jdzz+2RWxPGnUlKikQU/TtgUC+N5XE962cWJLYxZeV3YqZRehREVgWVSiIoqp3lZCwDNmq7/LZLM+DFgHJz2D9owBicj7UKKSDcJYXIkdQ2kM29HX1/dIf3//ATq7urru5/HGGDxmtC3czqZEzbGCt9Xw1lwNh56eni8RBpDw83hf37Y4tTk1sOTK1o7F+fOA64sFr1Usli5d+mmOQ39//6MU58sxY0ykN3n8R8T4MzNpKW7WQUpUBKLUuEVwU714BrhFDjpLly59hb394fEGODAw8A2/gQatd2hqpRJkXh2IMdjyunZ3dz/PcVi5cuXTPP50PrimGLgKOyB7Z589R7leqEd1IOb1RL05DsCFx/s3KQxEkQZk/xXl6QTXKW6SLIgKZpj4LJP0o0y2sLhlhT6uUSMIXFjZcEPZjpsNrnVPT8/xt7/97S/ec889Hp179uzxxsfHa+euXbtqcdC54oorpjs6OmbRdvybN9Y+NOq19LD6RY1HebdifOzp6Tm0bNmyk1dfffU0YQC5e/fuGgbAA34eD33g5/cZ3LzxhyFSP4layLR6njHb/T8zrvUpGBe2+OMjFrlWr+9HP/rRWarrzp0763DYu3dvHQ433HDDSwMDA0e7urog6R7iXIPinX1NOe82o0RFNKAiEJVqg0NDQYNZt27dS2NjY0floDM9Pe3xgw9I+/bt89BAMRChweKG1dnZ+cmobFlg0kzvJhqAaCDGYMvrOjk5yWHwDhw4UBePToqBiAZk/4bt7HzNqCz7Cqqrww+j3LihoB40EHMcUG9+ABceD9wwENGADFx9wmOtMitT3gO2EhXrFXAGDmNswA0FfRw3G9kHeDuI4kbbwc0b40x3d/ex/v7+B0pAWPoGBgb+DOW97bbbjmN8nJiYiFJdpw5wBJ533HHHSfQTf8Yh7/bvvNA8Ao+FfaIid43u7O3t/dTy5ctfxvVDP9+/f7+zjlEipqamPLqH4P6D+4cxZiMvD9ysTAvipG5KvxIVAWBTicqKFSs+SA0ODQUNJosDN6xPfOITsxjcVq9e/RdF+7cgrgG8o/h3hBtyFgMQYYgBGR2Zdb5CEBZ/9sI2hTrc398/gfKi3JKMUL3iSgzIwBX4+jNSCzaYw/oUf2DM+wNkWRAVSxPKLahpMyoDAwM3DA0NHcHYkNdx4sQJ7zOf+czs2rVrny3wH5vhvr6+n953330zKG9eB0jLmjVrXjDGSHKQW+NyGfZnL7DPEp8Z7luzZs0Pfu/3fu+E/OOaJSa4f1xyySXTg4OD7+flY98ly/uRtRIVDvxpd9OIyuDg4NduvfXWl/NscGi8Dz300Mz69et/VNRBCJ0BM0Fp/x2FdVR0vgsvvPC5Zg9CbD2IXJS28fzzz38+7b+jMBxAWkBYLIMQrZvJe1MnJSpiEHJ4h9avX3847/GB2gtIsf840VGcpgV3rly5cirtLBLVM0wCb5+sNG1mha0HwcxG7VizZs03v/rVr86E1SGLeBDCyy+/HI/Za7MnbN2Ma++nWllTOpSoCACbRVS2YNouiwYVxQZu0v50nqh+073D+MeY578kjg9mrHp7e480c/0KbeKEdSoM/U7MrDXqpgRMNmzY8CInbaxcO1m58nAqUYmG6vYPfvCDs7z95u3esGHDS/zGFK2YuWttvvLKKxs2VgJjPDI1xmB9V1MOz5ghf3aTb8I4iPU4ebcBbh+zuv5apioOrFxR31ZMip8SFYFcU4hKf3//t/GMuFEHiIC/uFBUv+ne7TfddNOpRuGAfNauXYtFybV/CY1GgP0rQdujY/Siiy5q6GD87ne/u+IvwK6WgREVDBJ5HkpUoqG74+KLL55vFInHjIU/RkRZ4B2tBtlobVm6dOl8I2dUVq9ejb7hWsSaTa0CrLBZV94XsZi6ug6tUePl6Oio569tq5aWERX04TwPJSoC3WYRlQMXXnjhbKP+QW/fjgXkdW9JCBia5t2BQSirtRhhHfixxx4jHJo2GLOt8/kjFpSnuqAtrA5ZxGPQHxzENg3VR5/Vi88Gobz/LSlRidbdduBGMTIykmu7ABHCP2fkc8EFFxz333KKVsLGaG35+Z//+ZPnn3/+XN5/7rBGZXh42EN+TSYqo/6MCp91Hert7X1l48aN1Td38rx3YAYe+WzatKmOqOBy++XK+0vKSlRE32oaUQF5uOCCC+axkC2vRocbMxrb1q1YflBMorJly5bqIIlp7rz+NWH9y9jYWBWLyy67DNO6RSAq/B/bKMp15ZVXzqGcea1TwaMvvBWFwRi4n+4LtVkdRlTy/rekREUMQg7vDlwrtN3rr79+bmhoqPpmH/p02vGC3vLYtm1blbBCwqb/1mDT+oYDh+pjcpQZ4xgI9vve975KFm8/oc7AE2Mx8EXfQz54LF8QolLrn1hjiJcjQCzx9hdwwKxoVi8fgJzgdWYQVhBkjEGwzWdUcH18omJ7EcBx+RIFK1ERsDWNqKBhUOfr7e2dv+aaa+YwMKUZiDAzgX8duAmh44GkwB6OohIV1BmdD50EZQaTx8CR5i0oDO4YyDAAo+Phxgw/jmYPxqcvBG1FXUdUUC6UD+W86KKLKpj2x4CcZiBC+8L1B8YYfDC4Ed6Qp/sCHwhpEFKiUj9I4MadNyb1OZ7xVYlKtdF6XvWVZFwzjBOdnZ01sokwnOj3GFPkiX5FOps3b662AbQDuDGTwklPs/uGDQQQBr6eD20a5f7VX/3Vytq1a+dxwk11RJzEAH7gQzoYHzEm9PX1VcdIYMT/JBWAqOBfBAZt3j+rRIXaA8ZM1Onmm2+u4A8v1YXqCGnDAeMJ6YD4YXzEvQHjA8ZdPrvtICp4RqhExdFY8wpuKlHhjY5uKDQQ4UaFxoMTDYoaF5cUD4nBC40OumhgvOMhnyITFcIBEkweAwcNqiAvVE/84+H1JzcIGemgw2IQgi4GLd7xYL/ZgzEGH38Q4v9cR4moEBYoN8qPgYgGVaoj/mFT3blEnUkHuOGGBGygg0GLHwg73an4QEhEJe9BSGdUoo1mdUSFXzu4Qcb5TQf/runac4mbD7WRMPLf7L7hgKWOqEgcMM6B3FMd8eeE15/cfAwFbsDPdRSIqPA/M3VERZadZocIB8y6UN25BEkjHRAdOT5yuwFEBWNHnofOqAh0C0FUeOMgNxoQMWL+b4AaGSTFQ4JhBx1lISqyDhiIqJ58QOI4gOSRDv+HKG3B3+zBOCpRkWVHvaiOuOHw+pMb+JCOJKrSHtKc7gtKVMSAYPEWYkZFXr88/M3uGxbsERRIVPLAoYxEJQ8clKg4WmQTggtLVLJueGUlKlnj0OzBmBEV/m9pwYxK1vWW9gKISt6POXRGJdpAFzijIq9nFv4G9Q0sIo+zoVqrEhVsrMhnVWutgi24538kAmdUsrj+0kYAUcl71lVnVGqt4YxDiYoAJKUXm5jF2dm0VQdj7EWC3Rv5rpJVaNkHCQtFVOhrrQ34MKESlWidrFX7Bq4/ZvMwVkQhLK1KVHDvAQ4L+oNjC4OiEBXsdaFEJVofzkxLiUpmUFYNoQGj82FHxSiEpVUHY/wjAA5TkrCwf0v4Z0lH02dU2Fs/+noyXZUzUh/91OOR1kdEBf0DZxhhaXWiQjjUCAvb06ju9WS89SNnPfL0O2ZUsOBRX09O2wtipleiEhOwEHUiKtT5wghLqxMVwqFGWDxjNltW9BeBqGz0ywWSledRG5DzzCRD20pUMgTTn0GgfsGli7C0C1EhLMZ/z5jbLX2x6TMqDZx11Uc/os+1M1HBtywwCGd54oZMHY5LF2EpAlHB45ksMYAtbH3N60/uqTuNuc8fhPi/pSIQFdpkSrfQrx8kcD1Brhp9FKFv0OMJar+NkOgX/JFpEYgK2kAj6l7NY+jMq8neSWMeZ42uCESFtvbPe9ZViQq78HC2M1HBDQkDcJbniYAOjbitEn8s6mzkYVkwiG96ZIkBbLkImzfiD0Kzxvwlw6IIRGXMJ1D8kRQrYmZO4IOBvyxHOxOVPK4Rrr/tpl+bdRSZFoGoiCJl4nWRwOnzjfmU3xf5RwmLQFRo1pX/ycoEDGFEiYoApJ2JioAiE6989IMBCQRllzHG9jXSIvxrzKTiwgg6mm0w3vdaY670ByG+IK0IRGWnX64oa4tEdWN5lahEg6tV+4YkKi6CQii1C1GZPl1h3I/6UHHPmCnPGCxcpdmlIhAV+sI6XhTI81CiItBVoiIASenlRCWIoFA2rToYS6JS9/zdM+aATwqqgxJmGDDT08iZJfl6smcMPoSEhXI2QknXKwupRCUaiq3aN4iohBEUQqnViUodQaFKe8bs8/sjvRlVBKKy2y9T3h91VaJCDcGXSlQEICm9ICpRCApl06qDMRGVOoJClfaM2et3eHoEUgSiMu0Zg0Ez70OJSjSEW7VvYH2D9dV9ByytSlSAQW0GRdbdM4ZmOGkbgyIQFfkHSxY7K78SFYGkEhUBSEov1jfE+UfeqoMxBhf6J7QAUs+YbT5RoSnUphIV9moyFgHnfShRiYZwq/aNaLU/q9WqROVsDS0u9nYgHpvjaCpRwSMo/1HUhF+ePIUSFYGuEhUBSIO9bTkYsw2daPV8s4kKvTJNg2KezUCJSjR027JvWKBpV6Iy7P+ZoT1Lmk1U/v/2ri/EjirNHzDYnT+3b/ftTmxDgi0ZNqIgg4IEfDAPBhRB9CVkwYfxYWUYhWllhQwI+jBuHpaQZZARRiQ7ggQZmDyN7ovmMbu+BFmW+DITFmZwJjok2TjGMYm1/m7Xr/3y9XdOnbp9b93qvt+F4vv/nVO/c+rc71bVrcLbC3FpGGeJR/3xQkUh7IWKAqRhcSIX4yKE2fKgx3V6fMZdqPDaM/4BNeqPFyp5CE/ksWFAM5GFCnDApdjyLAbuZRt3oXK0XLNG/a9A7LoXKupA8EJFAdKwOLGLMR5VXx74uE9l3IUK/2HAm3tHOQ28UMlDd2KPDQXPJBcqJ8s1ApeSx12onC37co8an1GIXqgoVL1QUYA0LE7sYize+YNnEoytUBGP627i/hRMLy9U8g6yiT02FDyTXKg8VhYHODbHVqiIe9iauD8Fw++FijoIvFBRgDQsTuxiXD6OGs9JwOWfcRYqvOzDfxeMegp4oZKH8MQeGwqeSS5UcANr//LPP4Zw/7je9VOEwMs++L5s4uOFikLZCxUFSMPiRC/GfHbJL0JYHsdzVLoh/JwLIe6baWjsvVDJA7rxY+Pee+/F39NH/YyMvL3/3uvIk08+eaXJZwwdOXLkagihqcL9+z01uCKE/uWf/w7hn5suVN58881iZmbm10UI5xu87AMUvFBRc2EshcrCwsJHp0+fbuzYu3btWrFly5brat/bIC4///zzXzcGRFEUbVqM+Sbl34fwW/SrSRxefvnl66+E8I44tdzUfPBCJQ/pA03Oic8++6zodrt/Ve/ZyevpaL1m5+bmLl261MzhgbVyaWkJODRxL0YlcuIfgudmZmb+dP78+caWiUOHDl1+IYQXyzWiqcs+wMQLFTUzxlKohBAee/jhh5s58oqiePfdd79ZXFz8D7XvbRAXd+3a9UVTi9C5c+eKubm5P7Rhx9GH8tkE/RtZ7+t2/xf9a+IDvPfu3XvxWgj/Uy5Co35svoTcCxWJRoKfn5//GdYJFBGj/Jw5c6b4wQ9+8OfUs38S3Ry5aWFh4cn9+/d/cfbs2VHCUKAIwJnNxcXFn4x8p2o0wCdZ/2cIzy0sLFz84IMPRooD5tvhw4cv79mz59/EE3L5zKcaPR/Y1QsVBd24CpVw5513vo5fTKM8+DDhXnzxxS937dr1Xy38pcShODg/P3/l1KlTIzv48Cvp+PHj1++4444/4qY0NtwGyoe//TmEt9E/9BP9HdUHZ/Lwi/Hfp6f/pSxS5IvPmoDEC5V6KD+2bdu2KyhYTp48WVy4cGEoUwNF8YkTJ4o9e/Zc6fV6mAOtOIOQgOaHvV7vPNZMXJIYVlGP4gS4Al+cscD9Yok+jMUkHv6GcVrcuXPnWVwGeuWVV64P6/sD3xVYg3GZDfOt0+n8UxECn52CH1N851ATGHiholAeW6FS9uMADj4sFnj3Cirl9Z5dwMTFAsQJNzs7i31s+2ex1+v9bmZm5m+4FIQDZr0LMhYyLGi43tzpdL7s9Xq/4gu/2gSGPKvy6xD+Af1Ef5999tm/DWNBBo7AE7hiccNlR3wp8VcaFsGG8fBCZTDAH5udnf1Np9P5HMcJjm8c5zgbwk0fMzgGaAPFGoMvZFwGxpnFbdu2/XIDFCgarQO4bwL937p169fYn2PHjt2yn/ryCGSJA/xxWQM4ojgBrjjLrRtqk2wcr0vT09M/x/cHTs7iTBC/Q7ivuohBMUIbKNdHrAsoTrAGhxBWn6U0prMpgN0LFTX5xl2osDv4NfMaKuWpqamvULjgCxYTjxt+CctJRj0ovoQwUTFhMXHLBWh1wrGRDUDx+P1lHDBckLGgyH3Frx+JAxZraQcOXIixoJU3xTV1o+hAEPOsSrHylmnkQH9/zAUZ+8OFiPuqv6SAC22gXIiBY7kA4dRt/2yS+oU2UJ/XEeSFyjrAK0NxnBzBcY6zIdww1itXFFfe3I0vc9rKsyZY7/CF3OSv4/XvbTwDjpPHpqam/lXuZ3lmZPXt5ZClHf5hpUCv87qPeC8asGQcszgT1P8OEfvaL2I4J8piZHW+iPVxzVnmMZ5NAZpeqKg51ZZCRXWrfxoWd52zf6/hl7CYgDgFuGorX/LVulOWeqcGkLGQ4Bf/6r7i14/EoSzKVu3lqdsNtRCLsyp4RLU1jtif/kJELPSXVPmrUOIA3NYsxOXfonEqF22N41ekFyoDHAge4giIsyojvV+kXI/4gLcfjwF5L1QU6FzYldpFR6BZBMSD11BErCkwhtUb8URczP1xfLxQGQfq3uaGR6B88Bofqz+yv5HjzG75Q6aJ9/pY4+KFikLFCxUFiIvjQ+C7c9WvlQsEvsyH/hl1/swOe6GSCZS7OQIaAXEJ6MIonn006vx6fyKyFyoKGC9UFCAujhcBccZjqG8yFs9jGOkZmwz0vFDJAMldHIEYAuKMxwfD/DdOeV/KyM/YxPZL6L1QEWCA3RCFCn5lq35niYPElb/ocf9CcsvpwKDtW7nr5Krja7U1Tl15D0kf+5srT6Vc9/024r1CyGvdA9PkLnuhMiK01zPvB4lFTM6Ws7uDtm/lrpOrjq/V1jh0KE5uhnBOYL/uPwvgh8yNlcf1Y0xHeg9MBmZeqCiQJqZQEZN6zeIiMck5cHN8kDPmF9MPGiP7n8ph+aEvdTadYxA51R77fyMEnNotvl15y7K5EDFPqg83QzgGvxsh4L1CTf8V2eqaFyoWKkPQYZwHTSNjOa8sKvPLGKmXfI4P/GN+Mf2gMbJvqRyWH/pSZ9M5BpFT7d0IoX/D6/WVR9yv+eeObI95pI48n5Bd+hylfozUCxUF/oYpVDjRUlTuG/wgk1o2qSNv+dNGmvKBLbYh3oqN+af07ItFB42Tuax+SvuweKudsv+z/NVULkRrigzup9UXnMb9NgScGkaRgtO5I7v5zmo/ofNCJQHOekycD1VUtwF/6Eil3dLRnrLl+CA+tqX6E4uJ6dkXi8ZioLf8LV0dXys+V6fbKf+d08fw7yHgkm70/UTcT9kWbs69GcIp2L5Z+SHTlkdaeKEiB+o7fsMUKqrflaKc1DHeSsIJXUWtWK2T7cKmZe2f8smJZb46vozRdBg5dE4tyzY0D1lvZeGyWrDQLvPKxQf2sshp01NHvVCRAzZEHuM9SDoZF+OtvPDN2axYrZPtwqZl7Z/yyYllvjq+jNF0GDl0Ti3LNjQPWW1rChbakReXl29+/8+eoixy2vJDBl30QkVNgE1ZqHAik5aTU0/mvqzwyFogGCPzUyeptEte+mg+5hfT63jIdXxHEW/l1Dqrj9Bpfak7yNO8kHGGpLwkxDF9DXJZlPR1N1Z+YS0P82Y7vQ8Dyl6oDAhcVZieO1X+sDOGlDrIetP5ZIy2abnKV9olr/NIOeYX08tY8nV8GSPpeuNlrhhvtQGd1IsHtPX1OEOCNeFmCG9+V73y34QFz9Ii9puVM62wmZeWY/1pQO+FigK59YWKnIyq76ao/aUseQRrOaYzG1LxyFV3i+UdRJ/Tdk5e5snxHdSHbVgUOaFnbsU/xcs5Vix05ULUxgKFu+SFCpEYIpXzJDetjpGy5JFPyzFdrG0ZD77uFss7iD6n7Zy8zJPjO6gP27AockLP3KXPwW9DOF1eyjFxLn/QtLFA4a54oUIkSrohChVrklo6tW9rRE5qTbWjlTum07FSZjtSF+Nj+S29laOqrSo7ctKHVOp0m/Cpu+kcOj/bJdV2GV8+/Il9eAq/qKS9xbwXKiMYnDpzMad5zkFNdeyw2mU7Or8lr7fNqraq7OgTfUilTvcZPnU3nUPnZ7uk2l7Ki+WDJPHDpd8HK28LdV6oqEFpfaGi+hsV9YTlxCRFIH00jSY1DIw1TKsqthmjq44JJtZOXT2biMVZdu2rZcYMg1q5pU7yuj3YUnbt3xLZC5UxDoSeL5xDkqJ79NO0TtcZm4qR7Vp8Kpa2WDt19VX5LLtuQ8uMGQa1ckud5HV7sKXs2n/MshcqagA2ZaGi9jG66Awycatiqg6Iqnj2PeZXV1+VD3adU8uWD/MOQpE/tsm2rAKrI/8AAA5DSURBVH7I9phD6jYA74XKGAcpZ06he/TTtE7XGRuLgT3lk7LJnDG/unrmjMXBrm1atnyYdxCK/LFNtmX1Q7bHHFLXYt4LFTU4rS1UOLFyKPYpNlGlnrymxAT6upuOTfWlysZcKT/2XfrSv6rvOoZxWp9qQ/uuV7baoo50vW20LN4LlSEOCOZI7oZmU3NK2shryq5DX3fTsXX6w1iLso/altJX9V3ngmzls3QxXytnHZ3VFnWkdfK12NcLFTU4rS1UVD8rRT1RKZMiAXlNreT00baYXvrBJ7VJ3xgfayemj+VJ6WO56upTbVTZmmyrqi8N2b1QaQhoqxlrvlFHijjymubmlDmsGOqQP7XRL0XZR+0T02u/HDmWq64+p62YT5NtxfrQkN4LFQX0pi1UsJ/WxKaOVOFxi2j5WLpbgiLt0icnHr7aD7LWWTmlj+StnIzXVMdp+zBltCU35Gb7pLH2GBezt1TvhcoYByY2pyw9daSpbls+lk7nSPmkbDKP9oOsdfSX+hgPX2ljrEVz/azYujq0JTfEs33SWE7Gxewt03uhogZkUxcq2Fc5gSWvbQqXvqj9c2KqfKycuW1bflZ7sg3JW75WTh1j+axHh/xyk7l021rWvim79G0R74XKGAcjNV+kTfLorpb1Llh2S5cTR5+c+Jy+MZ/lK9uQvOUr85DXMdQPiyK/3GRe3baWtW/KLn1bwHuhogZhwxcqnMRqv1ZFTk7SVUPG4qN9q9qiP/1ilH4pavXX8rf8pE7yiNdybk7Lb9i6WN9i+mG331A+L1QaAlo2gzlUNY9oJ9XxUk7xbMvKo+Okr8Vrf0vOaQdxlp/UST7mr9vXMdo+KjnWbkw/qn6MKK8XKgrYDV+oqP1x0RFoOwJeqLR9hLx/jsB4EfBCReGPQgWgHPTNMfA50MgcOFfirA7F1op4kB6e/umbY+BzoLk5sPpOs9auDA12DGDgF55vjoHPgebmQPKV9A0e/96UI+AIOAKOgCPgCDgCjoAj4Ag4Ao6AI+AIOAKOgCPgCDgCjoAj4Ag4Ao6AI+AIOAKOgCPgCDgCjoAj4Ag4Ao6AI+AIOAKOgCPgCDgCjoAj4Ag4Ao6AI+AIOAKOgCPgCDgCjoAj4Ag4Ao6AI+AIOAKOgCPgCDgCjoAj4Ag4Ao6AI+AIOAKOgCPgCDgCjoAj4Ag4Ao6AI+AIOAKOgCPgCDgCjoAj4Ag4Ao6AIzCpCOB9LbEXR+HFg/JzIuG7LB1DCHgnUCzvaeW7GEK4FvH/LIQwrfzxkrZYbv1OFLxAMearX+KEfYj5Yt/lJ/XiNfRPftB/7IeV+1IIYVY6l+9RsnyhQ7vyM44xuSA7UPLQxfqsxwTjH/NtakyAObC3+mGNSWrObbQxwbGGY05+xjEmWHvkJzUmddeBUY0J1hP5wdy25hB0+jhJrQNNjgnW9Vif9ZgMc21uw5jUWZtHOSZ4ua/8pMZkmN+Xev7KPjjvCDgCjoAj4Ag4Ao6AI+AIOAKOgCPgCDgCjoAj4Ag4Ao6AI+AIOAKOgCPgCDgCjoAj4Ag4Ao6AI+AIOAKOgCPgCDgCjoAj4Ag4Ao7AcBDAHevWJ6a3fF3nCDgCjoAj4Ag4Ao6AiQD/GgcjiwupM4NKJf0tn5TN8nedI+AIOAKOgCPgCDgCJgIsKkjhJHkzKMMnJ0cst+snEwE83wHPMeCmn2szmaj4XksE9BzRz3aSvs47Ao7AJkGABYWmVbsn/cFTZpyWqXfqCBCBp2ZnZ3/T6XQ+x/zZt2/f5QcffPASt61bt34Nfa/Xw8OhjhoPR2Mep5sXgSPdbvd3U1NT/Tmye/fuy/v377/EbcuWLddvu+2263Nzc5gjeFCkF7ebdy74nk0wAiwoNK2CRPtTZpyWqR8GzckNH+kned2HlE37Qq7rb+WYZN3i7Ozs7w8dOnT55MmTxYULF4rU58yZM8Xy8vL1+fn5K4uLiz+ZZOAmaN+XOp3Onx555JErx48fLz788MPi008/NbdPPvmkeOedd4pnnnnm6+3bt3+5a9cunyMTNFF8VycDAX7palq199qfMuIkb+WBve6m81htyJzaX/dL+mreipU62bbkpY/zEQR6vd6vXn/99eup4sSyXbt2rcAXUc0zK7HxienR65QtsleuHiYCc3NzH6FAiRUnMT2KlnKO+JmVYQ6I53IExowAFmUuzJKv6paMgS9lzVflkXaZQ+rJs38WhU9OPHNJWhUnfa126sbrfBMl41LOgQMHirNnz1r1iKlDkXLixAmOO+5hSX3keOTwOpeOYbua6jjK2k/L9HMaQQCXeh544IG/nz59OrtY+fjjj4uXXnqJWOv3WkVaWpcabVV92J8U1TlkXslrv5hcN6auf6zdlD6nDcvH0qGdunqrbzKH5C1f140ZAQwQB4k0t0uWv6Wz8sEvd5PxOr+UJS9jLD7VNv1TPjEbY51GEEChcvTo0eL++++/ubS0VBw+fPjGq6++Wpw6darAZR5uKEygP3jwYDE9PY3LP8Vdd911tbzZNpJ9Vc25oCkdqKcsqbRJ3vKBXW7SB3wsXvu5LBBAoYKi4+677/529+7d3z799NPFCy+8ULzxxhv9yzy41IMNPs8991zx0EMPFTMzM32+0+l8FUJoU6Ei9mwNa80PqdM8ZG5rkpUKGRPzkfocf7ZZRWN5q9qI2WN6tEMbaGqTfZI846nTMvVOW4IAB4i0iW5ZbdXVaX8t5+5H3bi6/rn9mAg/FCooRvDB/Sm4TwUFyeOPP34DRQk3FCbQ0xf+uNE2o1DB+MQ2Yqzt0Md0jJEUvvKjZdgsnYxxPoLA9PT057wv5f333y+OHTvWL1QeffTRflGCwgQbihQUKyhaeDmo2+2imB12oaLnRkqWe6XnQI5s5UZOGat5K0bqdJ+kzeKlv25b2ygjj/xIOdVGHZvMb/GyTWm32ojpZJzzLUKAg0vaRNdik8TSsz+WjTr4kJdU67UsfSUv2yRPCj/9sXTax+UQgixUzOs8CWVmoUKcrfGETY6V5GWc5GUeydPHyin9JC9jnI8gIAsVFiC5dESFitVTjGvVhz5yDpBHLO0yj9TV5a2cModsh3yVXeaEr7VJHytvqg1to0xq5aOOFL7WRrtFdX7Lx3UtRKDJgbPaytXFoJPxkqe/paMtRXVclZzKNfG2hgoVjpGmwJ86zXNsUnZpo7/Ok+MjY51XCGyAQgVjzE31/hZRz4UqGcHMS8qElEmlnjzjU7K0Wf7aPqgP+smP5Kkj1Ta9f5Zfjg/jSKva0XbGOZ1gBKxJkasDbFW+OXb4WJseFplL+sf6oeNdFgg0UKjo8WLrHDvI9CGlj7Rp3pIZJ/Pk8IyTVMal2pIxm5LfunXr6qWf3DMp9JudnR3FpR+JM8dJU+lDHj5VG31JmRfyoHwqrqo/tLM/sh+0aZrjo2Mgy7hSzNpnGWfllTrmlTHkY32QMc5PMAJyIlXxhCnlBx9OOs3LeIunLhZHO/NrSrvTDAQaKFTYC44TZUlpI9U26kFTG+PoDzmHZ5ymjCXV9omQN1mhkhoza5yhkxvjpW8dXvoyF6nVDm2SMgdprk36xXjZB/LSl22S0iZlyVt26kjhzxhS2pw6ArcgoCeIlm9xVoLlK3WSZ6jUgY9t9JdUx9Im9dQ5TSDQQKGSM64cN1L0WMZxD6SdPrRJKv1yeBkrecaSStvE8C0uVOS4xHg5TvQB1Rv8aLditN2Klz46F2VS2YYVF/OzfGUuxpHm2KSv5GVbzEM7qdYzBna90VdS5tFU+jjvCNyCQN3Jov0pI2mMZ4O0g5KnjdTSa12VzFxODQQaKFTYqhwnycNOmZQx0qZ5S2Yc8jCXptKHfIzGYmP+m1Lf0kKFY0PMq2T40YdUx1p66PQmc6V45pdUt5GKt3ylv+4XZenDtmWuGF8Vx1xVfjI/Y6p00i55xjt1BG5BAJMkZ6JIH4u3dLIh2OlD3qKMoY0yKXNQBo35Sh/nm/vXjx6P2JhZYyJ9yTOfpFXjLmOtdmI6xsXsm17fwkKFYyLHX/MYF/pxjChrX6mnbxVljG5H6q0c0g5eyjoX5SqfnHakD9vVedme9pUyeR0rZZlf8jJW+kNfJTPW6UZA4C/Lnacu/rTzEeiQ+8sJxbSU9QSiXVLtUyUjVvpIPpVX2sjHYml3mkCgwTMq6AXGKjZeVXpplzzzJvZyTZs6vk5syndT2lpYqFg4V41plR05LR+pq8s32U/dluyrtEEfsxED+pDKePI6h/TVNuZlrEUHibHyuG7cCFxc3v7Dvyzv+L+Ly51ihW7Ha9bX+5ETLJaLPqT0owzKj+RTOtpAdYyVV/ozhn7a5nImAjt37vzt22+//U3icSmmCY/RX1pa+msI4Z7MpuRYWeONNFovddImeeljdUX70iemp50014/+m47iXT94Ci3/yZNLG37XT2qcUjaMF+zc5PhZcdrPkmUO8vSzctIHtMpe5WO1Y+lkm5LX7Vuy1uk+aTtkrdNtpuzS1/m2I/D58o6DF5d3XEGhAgq57X32/rUegcVut/vHI0eOXMW7XC5dumQWJlSeO3eu/56fXq93dX5+/mcZexdbpLgwkTIVZcaR0g5KnaTSTh722CdlQwxzx+InSX/P9u3bv3jiiSeuvvXWWwXe45MqVt57773+G7bn5uau+tuTJ2ma+L46AiUCF1/a8YuLP+18fvHFzusOiiMwRAR+tLCw8NHU1NRX+/btu4ynzupty5Yt1+fm5v6wbdu2X47gsehD3BVPNQIEpkMIP+p2u2dvv/32r/bu3Xv5vvvuu6Q3zJFut3t+x44dJ3yOjGAUPKUj4Ag4Ao5AHwFcUsTZOr3hy8o/jgAQ8Dni88ARcAQcAUfAEXAEHAFHwBFwBG5F4P8BllVohH2h7bwAAAAASUVORK5CYII=)
技术步骤
分别构建一致性量化分析模型和同步成本模型,通过定量分析陈旧度和同步成本之间的权衡推导出成本最优的同步周期。基于此,建立一种动态的周期性同步策略,从而使系统适应不同的工作负载并降低同步成本。
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)
实验结果
大量实验结果表明,基于本文提出的动态周期性复制策略,可大幅降低系统的同步成本,并且能够适应不同的工作负载,在更高和更低的工作负载上具有更有的成本表现。
![](/upload/paper/images/2024/7/202471216814700.png)
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Frontiers of Computer Science
Frontiers of Computer Science (FCS)是由教育部主管、高等教育出版社和北京航空航天大学共同主办、SpringerNature 公司海外发行的英文学术期刊。本刊于 2007 年创刊,双月刊,全球发行。主要刊登计算机科学领域具有创新性的综述论文、研究论文等。本刊主编为周志华教授,共同主编为熊璋教授。编委会及青年 AE 团队由国内外知名学者及优秀青年学者组成。本刊被 SCI、Ei、DBLP、INSPEC、SCOPUS 和中国科学引文数据库(CSCD)核心库等收录,为 CCF 推荐期刊;两次入选“中国科技期刊国际影响力提升计划”;入选“第4届中国国际化精品科技期刊”;入选“中国科技期刊卓越行动计划项目”。
《前沿》系列英文学术期刊
由教育部主管、高等教育出版社主办的《前沿》(Frontiers)系列英文学术期刊,于2006年正式创刊,以网络版和印刷版向全球发行。系列期刊包括基础科学、生命科学、工程技术和人文社会科学四个主题,是我国覆盖学科最广泛的英文学术期刊群,其中12种被SCI收录,其他也被A&HCI、Ei、MEDLINE或相应学科国际权威检索系统收录,具有一定的国际学术影响力。系列期刊采用在线优先出版方式,保证文章以最快速度发表。
中国学术前沿期刊网
http://journal.hep.com.cn
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