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چگونگی نوشتن دو سیگما پشت سرهم در متلب

۱۳۹۷/۲/۶, ۱۲:۵۰ عصر
ارسال: #1

چگونگی نوشتن دو سیگما پشت سرهم در متلب


سلام دوستان.
من میخوام تابعی رو در متلب بنویسم که دو سیگمای پشت سرهم داره.
بازه این سیگماها از 1تا4 است .متغیر هایی که قراره این دوسیگما روی آنها اثر کنن An و Am هستش.
ممنون میشم راهنمایی بفرمایید
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۱۳۹۷/۳/۵, ۰۲:۵۴ عصر
ارسال: #2

پاسخ: چگونگی نوشتن دو سیگما پشت سرهم در متلب


دو روش برای این کار وجود دارد.

1. روش اول استفاده از حلقه for

کد:
[این بخش برای برخی از گروه های انجمن در دسترس می باشد.]
[ثبت نام کنید]

2. ماتریس دو بعدی (m x n) تعریف کنید.

دو چیز در دنیا بینهایت است! جهان و حماقت انسان ها، هر چند در مورد اولی تردید دارم.
(البرت انیشتین)
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 سپاس شده توسط sina1864
۱۳۹۹/۱/۱, ۰۱:۱۲ عصر
ارسال: #3

پاسخ: چگونگی نوشتن دو سیگما پشت سرهم در متلب


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Mfmye2hi90PvQsMZL9xtLt5DurN4aMc7dSpFgC5MlAaZqxCqfgatO​TpK1q4I4J6ThUw4earqs+00TJCIBY/HNS93yVetIcRIqkcirQjwGr9FAMONfvWLwLbdNfuseqlKPLUlunUwEz7YNatYFgGJGO8ZJamn9LbNTGn​1aoz9x3jz4S8H73GwgUPY+tPhHmbYX8SZP0zBeE8zcN27h+Ke4nHdtLt06cpPWsDjHoR07n0dIsEtuwj​I8nx8rB1tz1WiOjTbQYKpmqPCdxuZriwTO9tzwWwn3LI6InJk2BWqfgKbLD3zL1FEgDMP2MD7y3HP2ME​OMq/T5SaohtbsOLCPMLbJv1HqlcsDqJz3q38Etu1u2ed4eDrdLt3YrsXHtC7slQ41zJlNBGQ/9yPWGUV0cZm15FiXsSwChHFiO4Anf42GkbwT+G5f3fE1YOuuKkwO3Wk6+zE3k1wtzOPVs/YDSuGOO/55sIfP4rp3j3gOwMaVmG/g6nUPM54AERuenCa2zts6t2wunmATJezyUyaWPQFZVb3MG1De75cHJI2yt1t26glQC7Y4egZb5gMkF6T​q24RHJ4dMGkyX8dsT4Eq/+kRg2+6SfY7nADyNdXcn57G4S3ZPQGa7prz/6vUom70Mj/An7nws+mZTBIQxYtwI6QXgL6qx32/h6+O8ii/bRZTovWXwYO+SYdQSnl6eyuXWPZgBV3MAYoZJXxz5us7dq6pf8VTBJ3JBVBR3UytemiceO9TH4NRxkc7​boC6U2pMEhSJPFn1i0mlEgKn7Z8aaCDBQ9Uo4LJzeECgLlqx8ZrG9znIC1NKtDhNIDfMBZFJpcpazYhe​SjaKV3ZVJfBUBLvWrLwS17W7ZZzEuxXyKKV7qcIqnysiucaTHUnoP+Majjovc8EIs3/kAavl/656IU+1ROm+DebsWt5FxEZB41DFUG8XepgrhVfTwsUKbIoDvzrVGQH4Ri0Y4F6jFeLx7LEYU6xg0yMvz​uV26h+rKjodqxHPaYaPBrPzOSZOILXrKCXDRE+hrfwpLdm9HlE+ecA2q9vSgPyVUoAoHY7exMtl0Jwmm​3z3rRQD7O1P3z4x5EaBOTO2YF6IgvXeCtZEnzY58FNG+S5bbK75vNnejEaJIy3cGjXL8KKk+H4D3eSPW​KuLF/UdJTeObCHCvX3NPcNvujn1WBbomEZ0JWP1j0BIju8YQY53P5Q9xeNNK7N1bq6xzIpx3NlXMys2wkafOi​l1LEQG9O9C8ZDv2NXG7eRXKlu7C6X412dEbj611EcAmIS8Pqu9cdccXrEMQMHAMO++/3MMDMj7Dx69Nx0RPK3W5c4/EQU+aZ7V7EzvSkshDurgVnxRTkhdIZWd4Y2ICKQb5yrhCNsoXEK8ZiAzto6UpV+ok1YsAiYn7Z8KsCIj​nTxi1Nc0ul/+byvD9+lig6fbKHbTZpyo0DHz0P3hwwmDHh0rpDwZTL2aUFm/UHPbDUYUke1/n0tTvrlzDJxHgVr/6QWDb7pJ9fmMpDxWy8Re3YT04qu6gk57gMbRrcgyHKhJzmduGUfGwtoFHSyZWG50TYMWupXoCOOK1+Ia​a3StYIiBvUJ+LnYAJL77nTR5AZwPm8SSbHzdjv1d5AJ7fwwgx6PUDPHECnLow8QlVEf//NAtXhsliBSMRYOr+GTArAqzCdwILwrNTBLH59ooF1HKfqWdJjJ2H+hPuj/j0HEAzEwzJRkqInHSeEpv4IQJ861cXCGzbvbbPRhjZNY4IEyReT/o7Qxtm3d4YYyACuMdVc/qmmEcui2kNBSoC2OJ5rA63eZmop5505WWSTS7uYYiYFKXLtuHtTStl1Tc56OODVbr6lUmgurvG6eJmAj​cmizh3Qh/jM3v/HNO3SZMwK0ICox/mcUDz7bU36dVTJX0oNMWMVmpuROruKj/xsV8dE9S258A+G2Jk1xh80VXCnKqrXivCZajBINndlcVZ9YimhBrk5yoh3CGehtkLUwTIWtqDpizDs54​k6oma2IMGTcMNuz6wH6PPSC7ukQ41+UtzhgCbKHqXlJpko7q6MsSJ1cMy4jEyC8RzUDSXIkS6zd8/Z0jBo20ru3gyUL/p/pK7EkuTPoaLB2dj+qBRuPyhXTk/CU7v4VCR3yNl15VP+Nuvzghw2z23z+kwsGsMsZhrNhgynyA+VyOLUN9hFIiVn2fr2PBEonXi4gmLJxLh​NeXy4MjjJApQBKhJdDej+sAnHiyeapLNFbhi+X6c8WRy5eIeVhA72vhxnMpL3C37NZMqWN35arNlHWLp​/gHAVHuzP1dsRDy5avoTeLk3l0aVI3f8o5ai8a2NWLK7W/y+Kbur/MPffnVGcNvutX22ilzINTtxkQ+QLGrTkO3cEMvIfIAciucCEwEXcablOk8T9QbeX406j5NscnEP07DFi​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​n94rqzIZ1RER72SDixSam+UkgjwgALyBBjXNDeDaWPooChK+nv0o6/9KSzZvR1RPuHDNaja04N+m2evm/4uRB6jrdB3AUfXlKNscTRRGtUkRTdWlEXUXj2DbH3F309dLLViLabUWAjPaxUbCJOI8KPZ38jIlpxCl7​LQimp0h0+vQm3oatOFt4y/l5YMIqB3B5qXbMe+Jn7/q1C2dBdO9ydXIzUJiQDPKBwRwBbo1Jrm5jBtDM82sgl0oydGRAzyK+P15e0WYDH9XYj8RRWjTXvQtqIK​VVvtVWYstrHC59SUjAtaegz7KuvOnC38snpmZHWLjXKwskJjhcV8AGZLHh0VUhbamJpToJa7NSOELHhI​MnsCOLIqnurVZGOXRECwKBgRwCe4rqa5hYFszhjKCenRPfTtlxM3vEj8v+vfhchnhEBUx4B0FavQWEmD​mFO6Eq0u9hV/P92OOZ48N3mFrDvfg6OvVJlINNR6fBgm2yvGh9rW42idP0IuukaiInNbMn0vQRYRwAXrtSPiY1S0TR2z​FA4IAgWVE5BS09wU59H14kSEs+665cKcbrBnJNs95GRQFn219v64uFfAPGa/C5G/JMTosydXYWGYx1u34XT7ejS2WynYU2xjRSyopcu24e1NbFdsKXSSva+MFkv+2hBmL/gOWF2Yn+z+EB3NS9D0XCV+mE2A2Qo/SluiPgGhLJ5fk4uu3JXXbsE7O1dic8fprG3JKgJi+9BcMyT90wuKcJGLvlJ7f0jCK2CBWGc9ZoWEdyND​jxE2KBgRYFTTPCtGyjqDorXlxjJ1DzVpSf0bfe1+U1j5LkQeo90dfioXpzBG3teCdrOGtSjHiixvzGPT​Tx4yP7dM9lXqYinEmpKsrFxJc1r53MwiQAgHqyJN7z3Qf4YqZpLGS4a2pBcBRrv45OqDyX0g8hKshUXU​5EjtfbKIJ8ISBZQY6CWqyPBo16RT6wRBFDxZRYAULbk4H8CEILGH6nnQhGCIwEEiIBtsgRYHs9jYnZtE​qHV2Dyr8QxBFQaZdPt99j+H2ILII9R1WQjz2sOdxMEGsFRsqQsx2UpGqIEMigCAIImfIRDqNe9u/ynhBagvhFyQCCIIgCKJIIRFAEARBEEUKiQCCIAiCKFJIBBAEQRBEkUIigCAIgiCKFBIBBEEQBFGkkAgg​CIIgiCKFRABBEARBFCkkAgiCIAiiSCERQBAEQRBFCokAgiAIgihSSAR4SLwQCBUGIohgEy8URsVuiOKC​RICnUClNgsgXuGgfFapD41mva/cSRHAgEeApB9A8YwjCa48gptTspp0GQQSTT9Hz4jWyfv+72PyjUqqqRxQFJAK85GwjakNXI9Lyf0pt7b​Wjb0Llc21op42G6/BdXGnpsuCGXfqjWFY6iQRgYDmO7QuGSa/dBRxdU46yxVFEOz+T7xNEYUIiwENiR+ZgaskdeGDPn/B45UNo7NIalH6c21aBUAXfeciXNJ6DQk8hiHWtQt3kEErCC7F85wOo5f9dchXKN+3EnqVlCHOvSWQlon​3mFFM6EeD2ffjv1tdRLz+He3bGoCx6Wr6XgUwioLcVL80Ly89jV00z2uVbRI5gIn3dt4egrGkP2lZUoW​prV+ocVLx5lZhz5CL7n+NonT+iKOYqUdiQCPCMc/jLU2MShj28iGKNcXpweNNK7N1bq4RIQtVPYFNXh3TBTkWkqR1dXCBZiM8aiwD376ML8aAT+xaXCU9PNt​KKAK0bOoa+tiqE57W6kEMi8lFKSsK0UJlACHY5V0smmPtNCaIAIBHgGap7cRtOs4UmrBiWd9He2Ix9vZ​8Jw6/dRbKdyIYKvmMtHrEgnp6QOyv2/ddPKcXIhja2fPVrFkb5x0bE8ywMLs1u2vF9dPTgyJpyhCbXYs6WI+wzMnEgHltOve5AfTdfmvvRd/huVIcqEFndgh29Lv72ivD4Gi1oWZFeOSYGnz25CgvDTDDyedu+Ho3tZ5W/UEUCDxd8Ev9d1d+QIPIXEgFeocsH2IfmmiHMaExFxTbpZlQM9A+ka1Gg7GanrLewIOUz0lOiLtZKf92Y​3tXauwOvsl13qNrYVZ4uHGDlPrGuX2EF2+WLRfoqlD15KM0ifx7de+rxyIxhUkwwsrQvW05ArDOKKP/3k1dg57nTeEMNVfCFp/oZtNoRB0wkVYeqUfd4BBH+WeG5qKcYtwHafIBP0fXiRNb3YYy8r0WTv/MB9i9NeFWKa64ShQyJAJ/gO4spukVLLFbFk40sdlPq9+VGNf54lrqD/ePb2L3kdzjccwi/rV+N6C+/mjZenl4EWLjPjoUonbQC0b6LykIQGvVo0ud9gDcf/jLKoycR04iLrr53srYvnQjg7RnC/s1B1hw1h+S503vY305lf/sJEwf1mBWanFY8pEfsbsNczCzdhW72OTX0ZIp9eGJvOCz7r9jmKlHIkAjwBRkHrnker7/eKDKQeWLStSOKx3Wr9ZSoC6rqljfynMT7zKIIsHwfTif2sQU91RMgdoxxl35kEeo7hLs4W/uMRYC6UMvPU/IUtCGGfpEjcMMGG54AeUbFrITAqLCU+0Bo0fcfzwsZpiQR7mrYRU/7EHkNiQBf0OzS1IVGl3lMpJJlkXWNHhx5YhLK16QLBaTD7faJXIHy8rX2QgFcVPJsdyXnJEn8EBaRv22​8/6QYDM/CnMOqCCSI/IREQCA4L9zPuscFCT25WMh60LHqe6ho6kBvbB+i5dUWEr/cbB8XAPMRuakJO3ovouuFySiPnpLvmUTxgCRyH/iiVbpsG97etJKefbcK9xjNHEZPWRAFCYkAv+mXZ5aHa1C1p4eMjBFqH8Xd5l7EtoXrXUmgUy+zNR/cbl/fJjwaP4fAzuclst2F+7oTbz48mn1OpmRHwggeZuL1P8TjpSSeiMKDRABBEARBFCkkAgiCIAiiSCERQBA​EQRBFCokA1+jDqS0/QWVlpTtX9TP4nZunx+Ursf3YuugW4z6ycd2y7i2ckR/tCj62j8abfWInGnG/UT/Yuuajbv8n8pMJIr8gEeAaF3Gm5TpMjCdzTULZ/HoDg5H+uvvu/8BPv3uZ/Pd0JKnCQDtaF/Az8GW/TqjB9+6917D/0l2/WPBNTPunQeLfu/2IoY/to/Fmn4H3V6NuwmD53Ydj2IyfGfZRumvmzJvxi/+6QkkaNF1EiiACCIkAVzmJfUuvxFDFMHwJ/9jQhr8OyLdMMnDu13j4m9w4kQhQGTj3PB6L/J0w2ENvwC1tH8Fat17Cud03YRL/9x6cM+Bf+2i82Yf1+Rs/xHeH8r4rwaDvrMSL5z6X75lk4AT2PsSrP5IIIPIXEgFuc2Er1t38RbEglEzBda+dsbgg9OG9p8cXoVHO​RAwXOu7CrcOFwS6ZuATrP7JqsHfi2elsofZABPjaPhpvDvgAR58sw3Cl74bjH37+Ok5ZFVHH5+MGEgFE​HkMiwHUGcOlEPX7yFeneHV+Lhk5rpwCKZ5NJBOg5h1MvTMJYxWAPxWV3vYJDl6xYbFla1xMRwPGrfTTe​HHFpL5r/Uz0KehK+9duTsNR7ynHQpSQCiLyFRIAnaPMDhuKLNS9gzyX5lhkuHcefNx/EcUuLSDZ6cPSVKuUY2vZPdsnDbZIPoVGPqv1/WBXE41B18fdv4OqNf8EF+VZ2BtD//uvY/Ocz1oy8FXxrXxDHW/6gyw8Yeyfqjv1NvmOGPpx56xXseN/NUkJ8Hq7E4vJbxLHE8cOokuerPOJ68RZ3S1ATRQWJAM/QxmvHYuxT78C/ZfU8utguNbxgW7zYCd/9xavpJRHrWoUF4dmBLDuri78Pr8GcDrdPDnSGf+0L0njLN/T5AYNv+RW2X/BPEPHKkZXh+9GoOaEw/Xw9j+6WaQhXvqQUiiIIq5AIMAE/grX0Ryus744v/B5rpn1BLAi2EsbcgRuV20q1BkRbEOVdpdQub2OiNKo4drZUqa8eNGK4eHA2rneS0OUpPrYvIOMtPzmDd​1aPdZRk6QqxfXipMpxUTTTbfD2O1rtGF08FUsJVSASYQrjJq0MVSSVnszGAS8fqcLsar7WTMOYYUdgmp​FvQRUEZ8doFHF1TjrLFUX1hGaUAzeyAxok/xvHnrpXxd3sJXd7iV/uCMN7ymEuvo2nm34u+s5Vk6Rzjks/Z5qusFVHtVb4LUciQCDCNWpTlTotu8l50/+bfMF4xLHYSxpwiEs4SuwaGWma2aQ/aVlShaquBsFESnpLr3weI/jfx+7nDpcG2kdDlNb61z+/xls8wEdXZgHvG2U+ydAp3+5eWLtMXrjIxXw3/HUGYgESAFdhk3FARStpVm2DgOPbWj5auRqsJY045gOYZw3TZy3y3MVVpC78mGLsRgy4CGAMfPY0l/yrj75YTurzHt/b5Ot7ync/w8a6bMUUJ59hIsnSEdPsnPSFiZr6SCCDsEkgRYH1AC3eZmCRJV3iuiwlucpKGFxkm1GVioPclrFLjtS4​kjPE+EqeVaa+piKxuScoUTvYEJMrMPntyFRaGS5io2YbT7evR2K7JebAsAgw8Dp5zCb37b4/H3/1O6ErFv/blZrxdhbLFf3Q5M12Mz3DKvcT9yqMnU71WbjPQibcfG+NikqV8/DP5+0QWYs6WI+zdBKm2z9x8JRFA2KUwRABbsB4dFcLI+1pk9rtaG/77bBFz90xvocrT7J4zoo/XOk8Yk4YlLkjEI4A1zEiURFYi2qca5uScAG188VN0vTiRGdywpu8klnMC/BABHG383ceErrT41T6vx5vISo/wscO+k3Yhc4a8T+ShRHZ83yYsm1Tq8n2yoM0PcCPJUj7mF5+HvTvw6uIyMfc03ys1J8DMfKWcAMI+hSE​CuutRrZk4PBt+Vmgcyp485L7RkJPZ3mKnjdc6TRiT3g8lY1i+JBf8ZJdh6tMB2RBGpfS2zRYeO/JLBDB08Xd/Eroy4lv73BxvB0RWuna8ybng7gFM7D43jkyM39g+NNcMYQvcM2jN6bPwSfkBTpMsFVEdQnjtkYQnQ4YX​dZ5Fw6cDsnEcrfPCufGSEAVHgYQDNKi7huSdrVuoE9eu4dPFayfjezs+lG9YxMioMHjfjUk5xlSeE7DU​3E7K3jkBPooAhi7+Pv4hrD+XywUjO761z8PxJsR2yMMdeifefHi03iuQU/T5AZf9/H/xV/mONdQQRyXmHNEmGkqvR9JpjeKcgEc13rxM0DkBhDMKSwTEDqJ1QdjjXYPBjsgiiXjteFzzcpd81RoiLJ​F8glg6EcDpwZE/zETkpqYMMdx+9HXU46bIYhsnBvorAnTx96F3oeFM0B6N8699zsebuoglPEyxrl9hxYwhHi7QYnGbHJol​Ts3zC01+wKA7XsEx+bI1pIduzGNJNs1YBCjz8PBK1EXuQn1Hpu/eg6PPX49I3R/oxEDCNgEQAepE4Go705W64Olhi9yacoQm13u8a5AiIGVCm2fg/eW4Z+xgB5nH0qikJCiq4YDkHYcHqK5gw99KcznoJ2tcxJk/TMH4wGbD+9c+18ab9ncN16DymW0eLT52z+XwgIFD2PrT4c6e7kj3VJHqVXSwoSAIpxSIJyDbroEZlfZG​rJ3Hy35yIxbGyPmbbRowh54AtWCJo2eQZT5AckiibxMeneyXUfHTEzCgFNG5458HB/S5eB/b58Z4S1qs1Jwbwxg0+9v1U0oTYYPuetRkFfB6eDhq4deHZczpiXVGEV1c5nEynFoUyuE5D0ooZVSSd05​NXg6nhPQIIpcUgAgw2jWInUtiQRKP9okwgfr3yZPSJI5yAtTSpQ6TwwzzAWT81IMnIszhowhQy+kG9YQ​839rnzngToSftYuU8JJaWvi1YN2OYLqeH339K3B4wwf/q9SibvQyP8HCEq0mJWkR56FsGD3aYUJkmH0AV7LoneQgi9+S9COC7hjrd40MmFnllEb1aE99kn8EnZHg​hlu98ALX8v9M9k2z76QBRpOQ7g0Y5fkxMnw+g9XJMRaRJ/9yxarD17ZXuXVeNuF8iQBTOGTQoqGfl+9U+t8bbeflYmjbPJE3YSdn181ABD1Ox+yuLH/t/tlC/K/N1lCdXmlrxkvTKhWY1JxLa1L/RLoyKKDBa7GUYUfu6mXuYRC0E5fzRStlX8bBYD45smSNsTGRRUsw/eV7Kc0lyFlIjipG8FwH88aF4nFJ3pYmL9+5Ay+JyTUW9HhzetBJ799YqBixU/QQ2dZ1Nu0iKBdj6OQEDH/0PHpww2PGBMfGELN135Ye2bNQf9pNz/BABn+Hj16ZjYmCr5vnXPrfGm0g0VcdZIoFN9Q6MnL9OM+7kIhZfmPlplUMQXnsYZ9ufwpLd2xHlHoRwD​ar29KBf+YzEPBViQzuu1cvIZZ4sArgYzn4PUwwcw877L3fhkKXz6N59mzi7Q/t9PM2nIAhrFEhOgDkSBi31ZD3+3qh4XYB0O2WbJwaqz4mPnYf6ExaMkVPONionjOmzj6Ur14aQyUyuRY​B4jnseT3j7cTP2BzEPwK/2+TXe+PPq80ckFuxYK9aGw4l8gH5+CuWVcQ+bEBIWF+g4Bp4AjuN7qGcrTMCEF9/LYT2K5HmpnoJq9KQPQbhHIEWA16ghhMTuQiz68exdGfdPl82b8npG1BPj/ChyI0VLkpgRhjH5saQ8Qz3RzYciL6bwrX0+jrfkMBsbZ9rT7/T/L4W2VUEdx1gEOLsHE27H6nCbTwmmKfNSCa/YFUkEYY4iEQEyMVCNDcoDhZITncTiLh81TKkWKI/mtFRFUNSWnz5oFC5/aJcP5W6FEdTvzuX3qHAzHyDXiNrvgwZNww27PghgHoBf7fN3vOkXMTnORi1F41sbsWT3SXTFvWhq3k6a​JwzMIE8S1AtcrafOxj0u/B5rpn0Bg6Ysw7M5TzBNnZe8PxMJkQThDUUiArTJc9w9nlT4JO42l1dKwo5qUKw9txxPLpr+BF7u9SFrP​daKddeOSHL7a88iz0fUhLcrcMXy/TgTOAXgX/v8HW/JITQ2Z5RH4HieDX8qp1u6t9V5ZpTEaga50Mc/h1+qy1x1odu5h5rAeTOqD3zig7BMnpdJ3kmC8IiiDAckI/IB0p+tzxV66Y9WWDtFb6AdrQtGulLBzTaKe3YyKl9tQ/OS3SIRkgsDXps8T+OMA++vRp0LCW9e4Vv7/B5vKd61JJRY/ddczkNJwvY9LuJMy3X+JpimzEshCkqXbcPbm1Yi6lolVILQQyJA3cGwnYN7SW3qISM2k4s+fxmPjyvF2​I0nnO1I1GeRw4lDlITLNk/jjOrBNzYT3j5/aya+UXI76k55VCDet/b5Od5kbD7LAVxi3LHduYePu9m7R+IgJ3sJnB/i7eWjUHLrCzjgYLKmzkv13I+rvCmERhASEgGuw5OLFuBWfshI7TYcs2EYBk7V4VZPsoKlYTF49DH4fIz​jT1+N4SUR/HtLD6w3/wJObbyaGVWvEiL9al+Qx1secOk1/LqSH+T0IBrP2BCHA21ouvkLqU8pWCKf5yWR75AIcBm1WIv95KIL6H7hWraY2C8uZET88ciUfId8QBTfc​ZTwNvAmNldf5lHxHv/aF9TxlhfI4kBOEjgHOutx+3D7xYXye14ShQCJADeJl239Ei6/50k82NCA+vp6S9fGxum49Su8hrm189YLmXgZ3qHXIbJ6o2G/ZbqWL38AG+7/KsZ65I72rX003hyQKBM8aMpC3Ll+vWH/ZLrWrr0Li38wlPWdm6FEgsgtJAJcQ60Sxwy5KxeJAAW1ipthH9m43BYBPraPxpt9eGXF+eO4+DHqC+sX​iQAiXyER4Bafv4z//hf3jEqJlwlseYRIljPqH5uXwwSuZPxsH403+yjJfIb9YOf6svMkXoLwCRIBrnER57o60N7e7s51/EOcI6sC9H+AbqP+sXl1fHjBXWPtY/tovNmn/9x7xv1g6zqJzguU0UfkJyQCCIIgCKJIIRFAEARBEEUKiQA36Y/isTE8RuggySrWjrbnKlEdmp3fBX48ws5hR7HOKKKLyxCqdvIstwmUgi9Wf/vz6N5Tj4bKET49p+/3/f1CPeTIWVJfzsYWQXgEiQCXyXYEcSZ4dcO5ZXPxBDMq4Xyv8hcI2AL36vUom70Mj8wY4vBAFw+IHcSff​nwNIo/fy0TfqNwvwn7f328cHWUc8LFFECYhEeAq2tK978r64GKnkagXnpxZzC/9gi8OECERoCdROCZeVEXZeRv1J7t0RjlN7XnXEBXgwrr7GhW6Ua+k0/mUxajU4iLMFqGWaaJAT20Ue5sqlP8uCc8VVS5N9w3D1v0LgHip3r7EbzXmMezqP2l6rno/tgjCW0gEuIq2EtgFHF1TjrLFUcvFP0gEpMF28aNcGOoDaGY7wrQFdDJhZxHu3YHmJduxr4kvXlehbOku​nO5vxfopGYr4pKMoRYBaGlx47XiYafT0h1G/p9vi70cigMhvSAS4ibpINe1B24oqVG01X3ZYC4mANChVEW+0UfwoB4aa/fZrw2F7uSC2F2HxvUKzmnGQR59YG0gEmEUWDqt5Hnv31qJyzquiyqZlSAQQ+Q2JABeJVzFTrglJsUYKB​zhDv3NTCEw4QPz2FbpcEK/DAQwuOq8dER9nYvzJcUfhgMywvttQEYr3ib5uv/m5SiKAyHdIBLhGYpF69uQqLAxzw7INp9vXo7HdSmGQ8+h6cSLC+Vru1zPUnZsNYxvbh+aaIR5WaZO//ailaHxrI5bs7pavmyPWWY9ZoZD1Hbyy0MtFv28L1s0YkvAKWMD2/fMZxat0Neu7diWEVxJehMbTh9DY2M6WdQt4PrYIwltIBLiGNh/gU7mQhzHyvhbzbkaj3RvtMAS2XN1Gu3EvSub2o6+tSiTpVT+D1jQ19VMx2nGa9QBpkhGVK3M9f2Oc3D+​fScoH4CKIifaSyENo7DKbv5OrsUUQ3kIigMgD1EWWvCMJZD6Azo1NEARhDRIBROARBzBNRaTpiDVXbSE​Tj2lTtUmCIOxDIoAgCIIgihQSAQRBEARRpJAIIAiCIIgihUQAQRAEQRQpJAIIgiAIokghEUAQBEEQRQq​JAIIgCIIoSoD/Dy09FAplndnuAAAAAElFTkSuQmCC[/img]
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