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AHCQH4ycc3XcMZ919cC8YSirQUqhXJiRPcOdwThX/p7yCdkJDq0N3Pt6IAGblEvyDL1rQpgsoI15+UB+Q8OlOgwLYQ+JVw9wrv4wJFz31poNYcO4JhhKiAfLAtY5Dsvt4hbdeKeEzrk24Obsfk18Lo8+OAT7ZMGmHluzVW6sy+3ixQkry8Iba5292umDy8CO/ZxRKswuXK0csxJClJB4LZA7/IbOuOZcGT2zwRy5zrMazHdoesGYn9Ag4zMcRfMilrzpR8pzriGoz78SjKESvE/m0tCcXMDSN8RCYPgB5zI/ZFlmWsQiSMTaPT/nzZgBDszDJ3Lhutfd7kLYReIVYFN9MdRVOOcRG6g5DJwtcwL2i5UzsC7ajeDLFziHOYfWRSx5ufCOMQOD9cUqaI5TljS2YGWgeVMGW/VHiixbE1xAbbldPCAwXKycOJiAiGUOEuU4Ifkn5scgHfUL79hC1ZrVgL8QsyeTeP1ucFfOqfdsqhaYQvTQwtkyV+ZIm4XFHHZOw/9qgi+WReyavFyY8twUzsGzXv3ygf1qKrxXS2vlDYsQRCVTbptcQO11xbebFbEQQVaO7bj58b/8SEnf54yA6eVyu3hq8I5ZMBvwF0L8xb/n+BzgMF0iYnrY4J+wQnPGrivOOYSQ+kI+1NfIwj4iapusORYcjgt0lb3oIOpyEXuFz0JdwomgwRuCofj4aKBR2hWxrdsQd0f+jisfXm4Xn4g7XJfJheAlOs5u0MRrcFCaeoqvLlVMxbGvcY0JfUMdZ0PJ7VSZ88KxkmeU+b6gpDvnCfuz85fyIJPbe07w/08N+k8UTfWEEP3417dv39yG8430Ob6HUe3DCQxuBoN7Qn4WoymfUl7JERuUu1oq2d7hCoDbocULnKJ87p4OMH93zCIWlRGMTtLu5uyeOnOYA1HxJ8dofuKthcYpyCBayCz52EGYPECU9NpXMZ+KQuYEX7GrI/KrTOhFrJHuunPn17ECOalAUPoD2bBctpsqSKnn1AzSfe+RPfNqrXHSWNxNSbiCFQIVViK5h8jEvFtuFxk6u77gy32O745WlbAtRbSzQqCl6BSO8TxoM7EYE+ucMFNO6vn8gA0AACAASURBVBw24uzh2gWvDGTYLozZqCKHyAp+zwzCZu1gr3KKtqpsmzLYpbGFmZlMLLKU+RyxdgRpDrydunAVYi7MsmzYOM9T7JJnqHw4xGtfdApOohWoRCwyGaxBmk/G7lXOiMuHDzA26oBcQZxYuv+7isPSXGDOKpsQse4YDyplpjJHpsInXYsjxHSYfcMmYzjhejrVS7UhBt4TDGXusDR2Ym3StDdwv+NPkDcfesfevClDBhul+xY6EE8R+sZOmCO6hoWH6wlWqgkxayRe7TBp4ZqDLoDXHKOZPclELIQMa/OTS6vrEAEi1rtLTWRGJGApoBaxuCP4LcFQ5o4TrgokCDExJF5tMAvhmoPN5pFjNKIkYsfq1Mia2XycQPkZ692lr1mvoyojAUvDP0Qs08BgJyRg0yHhKsREkXjlZ1bCtcAFPrvg4WuE7t+1sGddCcbQC9gS1nsOzZRjS8BScVBqPkVBQcBqjoyLhKsQE0bilZvrmQrX3ME+lYClwd1nejLSvcKsAuZ6Kt0qb87ur9Btlg0z2dfsnwJWdiode1yBQlkRgXEpyDEenyRchZg2Eq+8vHcGeI7CNacgYFVCnA4ncH6D2Bkc8qyruSZNNbBmkU0954KAlZ0aH3d++4g9qITxnSjIMThv1ZxJiOkj8cpHLhZYy/pGxQlYXNqsJk7j89E5XCNfCcMqXD6OlHUeDTSVYRRcprKv2T/t1EeC4cyBPQK8F1YCvLAf2suGgTr7LoSIi8QrF3cJxIIJUAaka3TG4RGOwNWYjiE6hjJmXffEZ0T7whosMJk9QYXCb6Ql2VPhEfukuTWJIEe+l6mMOA6PFrLvQoh4SLxy4Byd/1qKIqcAzsqvcgwHI5+Hp4kcAVbBsp743cqM2ddzC/e++sAzPVGGLTr7gn0yXQWBvUxlxP3Is++z7AsixJyReE1PXpp5O/cH0YTC2aFP/KM1ww5nhY4Sz0PGJhtTzrrmKPsamUKGTVnYOHxEdm0y+6QT4K4JnrKwnTCbfRdC9EfiNR0uKv+fsUszpwAcw0s5hr3ZwXE6SX1WCPfHHqYcQ4Dbqa9PZAoZM0DmO4a6Z+uCQhIonZn8PlnIwipTX89uKtl3IUR3JF7HJ9+MVzK+/ZBj2JlippWlJPaCYAw+ptZhOARjBuNguV1M4soLCJQjZBBlq+qZ1T6JLGyeqVfX6p/Zq0pNCJEj8ToOe5S5SrQOgBzDxtyhk/URU1dG4kZNd3NZq5gPjFUMrEGN1qBi5Eq2Ksh+7sFdBGRPJWJ/sC+UjKtKTQjxnX/rMQyK23w2cyg9TA2e79Vyu1ij3PCStAx1bHaYgxtiZ5BVoMzt2gX3eT8QjKOIa9z0akr2M7dVsFe5rTomGFoqdsj8b7RP/gVK+U9xZdSK+O7rocj3rck2yxNCdEfiNT7PBcGqDOvIYKNzjtAa5ygvZrjxu2j1LZxBC9cuMd7puZtheRqjeM2whicZSEDGe7PcLk4gUljPfsfGmo1KAp7Nw3K7uML8WE18ftxhTqg0WAgRROI1Ds7gPkiwcoEN8Ha5XVzCKXRf5xP9uDs4gw8GN37GzOvsnCdnu5bbxR3hGpmseM1BF3Vnpy4RdDudoJDNBeutxEk74Ffk2frTQqDjwNLnCKCAvxCiFRKv7XEb8BPE6oOixvwgG5tnOF7BMcy/rJbr7fM5aHnTx12ejM2C5lYynLOGfROJyINuELInJXtlTaw8F2yU9soI5NnY7C/7mWfsLe1l+d6VB1slWOPCuM4Y37GeUzM2hM/q5V/fvn1zBvAbwWAYecZkesq/ZGinRUHMnhT+y+ggPheCJk/I1AghZkRBzJ7gi02wPJaCuzqvOBKlwKybG69JhrYrzQntXUKIXsxZvBY7+eVRhZf8SyJ1vsAJyJ3DV6X/Dilsd8U5iA3/RZu9ECIEBO0R7NMRvl4NKGzz6qOvhcCu7BQhgbkx1D72XJgTL4WAvwIYQoio5OKVsWFKFFSqJIbAs2barKGXUnmINnghxCBAwLwq/Ozy/68iF6mZgrrTohCkzWm6h/1j/5KPJYQYm+/iVQghhBBCCCGEYOYXvR0hhBBCCCGEEOxIvAohhBBCCCGEoEfiVQghhBBCCCEEPRKvQgghhBBCCCHokXgVQgghhBBCCEGPxKsQQgghhBBCCHokXoUQQgghhBBC0CPxKoQQQgghhBCCHolXIYQQQgghhBD0SLwKIYQQQgghhKBH4lUIIYQQQgghBD0Sr0IIIYQQQggh6JF4FUIIIYQQQghBj8SrEEIIIYQQQgh6JF6FEEIIIYQQQtAj8SqEEEIIIYQQgh6JVyGEEEIIIYQQ9Ei8CiGEEEIIIYSgR+JVCCGEEEIIIQQ9Eq9CCCGEEEIIIeiReBVCCCGEEEIIQY/EqxBCCCGEEEIIeiRehRBCCCGEEELQI/EqhBBCCCGEEIIeiVchhBBCCCGEEPRIvAohhBBCCCGEoEfiVQghhBBCCCEEPRKvQgghhBBCCCHokXgVQgghhBBCCEGPxKsQQgghhBBCCHokXoUQQgghhBBC0CPxKoQQQgghhBCCHolXIYQQQgghhBD0SLwKIYQQQgghhKBH4lUIIYQQQgghBD0Sr0IIIYQQQggh6JF4FUIIIYQQQghBj8SrEEIIIYQQQgh6JF6FEEIIIYQQQtAj8SqEEEIIIYQQgh6JVyGEEEIIIYQQ9Ei8CiGEEEIIIYSg59+xBrjcLk6zLPt6c3b/xPChl9vFqyzLTrIse7k5u38hGJIQdGid1GP9GcE2Zzdn9w/pRyNyltvFUZZlR0zzqjCmp5uz+68E43HrLmPxK0R88I5fyT7NB/kdoq9f8q9v3761+gfY3C6yLDvF5DsMfOvObYBZlrmB3Q45QWH8TjEu978PAt/6mI/p5uz+NuLvP8XvL+KE/DrSz1/BoSjiFv2mwTjGoPFYbs7urxp8Xorn6fl37t+syn/e5DM1HJfv5zzE2tQJ1onv821i2Iau7zTws04LNu7Y8y17PJ/boW1bG+AQFG2zb+zF8T9ApHR+x0OvibF+z0hrr/huqtbeS2HfHExALreL4nheB75tX9rHBxORBd/iomI8zxhLa9sUeMd9iWK/AuPN7XSZdax5AZtx6fmraHO/9Lua2KfBfMfAHIgyr/vYqDb/dqB5XEtXW9vS9o3lnzflBX5Er7UQ8E8arbHA++61bzf4+dHs2lB+SePMKx7+qmJTKXOIr/Msy35fbhfPMLqtncmaMV1WPIwyr/H1brld7OF8XkV4Se6lfPCM71Uk58r33N1CLz9L7zhGoM1YmjyP0PPMIgnYps+zzFGPz9SE0LuLYTgZ1onv8z1gg+hL13f6A2xyVw1s3EHhGTnb9ojnkyRzgHFfwtY2oTj+rOc7HnpNjPV7oq+9gjBYVQR5y+Tv5U2WZZ+X28Ud9s1YIjof02WFE1mkOFc+LLeLHZ55NGGNMa3xmes4xtc7jGXTQswNsTfGsl8+LgO26KWNXathFXguR333nRwIs6uG7zfz+I6PeMcxnHXfZ105gRVhPvexUW3+bQofL2tra+F3XHWwfbnfsY4konr7xc73zLKsjy0OaacmP8s39j3mbAzbM4hfBr9k1WLdt/JLas+8ugEstwunhj+3EK4+jrEZvyCi2BmM6QVjauqQlznAQ/2fizxgA43Nh7zsSUThSs+zOYbWSXKW24XbKL90tHHu33xZbhe3Yz4f5xS634lxNxWuPorveANnU/R7N5fY/D+0cN58nGNuPfS1fYiw52NqIlx9HMKePPXdx7O/szIvLRycIof4LE95CdpM8GVKuxL6Wb1tgLOFzp44u9Lx/eY4+/pHjDUQ4HCAYNtscXah4Hd0tX0HhbXN8m5yW7wh8IMOIgawolLyS/qs+0q/pFK8YtJ86eH4+jiEIWrt6MEY5k5mH4egTL5IhjCMlBPMKLQLlgmj6yQZcLDeRfj957GyFXVAODz1FK0+3uAdx3SQZwPWnpsDv/cQiD6cA/9nF0fOrVcEoPuI1jKd9/HiuLBe+o7pEE7l1ARs6Lkex/issCEx94fyz+4alAjReQ004N3MAiDRge1zouWPiPPqAEkgJr/DzekHAgH7mm2fHtMv8YrXQsSsaar9sfTVhFaOHibKQ0Mnc18az3ODf3OICfnTuYOeHBNFjqaAnmcFhtdJEmAM6xys/DntGowx2lmdEJj/fzR0+p9L77jJZzhAuZ6qHFqA5/XUMHvfZe1lcOQaH50oCMQmAehdaUz7Bv/mHPag1VxBFL2JcM3nbx35eakpUfXOYtjfKse3c+YVe0NX+9SEDwNVuTBk1ExS8DuaiJay7WuyJx3DzrAEGI5R1pwamn16bL8kdOb1tmYD3uHFPYQOuheaw6wqjHCjmurCwqgy5vmYvAf88TPyRiwhZ/UApc1ZzLO5ubEdoWPipkPm54vnz963dATG7ko51vM0xQTWyagUzmL5CJ65KZzluCgZ6v3QGxqES1VgYg87cBs6m1N6x+XPkPNJ66s5DbOIj4V347WZhWZhVVmxRja+4ZjuCo3HfhoT1shpzZn53LFscwbrqmJc3rNlhYZOl55nc9XxzOJ1z2qeVGvkjXMWu555w7Os8vE6Zc4gXD9XfMu+MN+8gb5Cg5+qs+J50OQ0YlOzQ8yF3uXwA/Nbyx+/9qzdvvP+B9hPXmrszHPB9lX5HasKAXyACov/Rjj//Nyg/P5VzR7p1uCGoEv2JtDYbTQi+yX5PKj0S34Sr8i4VnUevGzisOIXuK91oBHKvkX0sMoh32HjqhwTDNx3o4kIwbpikXw/mxt5Um4iG9qfgFFotZnhIHqZJwNt65MvWEKmsE7GJNS0xm1swbWKz5uXDV0VjHa0LqA+4BiGNog9fn9tVULxHWf+xho7nQFrDubBbU0XzUYNvfK55eZmoOHJYxPHrYFwdWNa1Ykf/P0m378CjnCG33PbZI+DcAoFxt6GbBTGsoZPUXw2ux6N/CjtV8MM4KrHOo2+vhsI109NggwF3/EKP3MdmMd59itmFdC5K32M2e02Nm3n63K78D3vKPO+EDAP2Zkd7Ezl7yr5HUewOSEdkvvSfQJHXxt+/nw8twG7dznWUaEKjhHISrJnN/FLmvhGJb/Et//9wy/5R9kw6pVDm4rb7I66ZFrcJLk5uz9FxCgvRVo1cfSg6EMOuYvQnrQdk9sEb87u3Wd9W1EaFbss5VgOYVSO25TPTZ0JrZMx8UXY91XCtYj7npuz+0vYtechNw+IkZBj+Iz32+n3Y164n/8Rf9TINosfbCoyRB/d3tfFUXTv5ebs/qjwXhoFfBuI6fcYU6tAJ/bxE2RtfBw3zOaEMlvvm9qowpy9jtzAiIUmgdlOn7twdUWT72v6M08qqk7cvP3N2cq2dgXv+aiirP7NAOf+VD7cnE2F33GNfamV7YPfcQq/w8fBmH4H7ORpwAc6J5krSZrDNvVLuvgTdX7JD/GKFxDaOK6x2fVyaDCJj7ChN4ken1Yoejemiz5jwsMJTcq+zYF8P1NNAbqj5xnA+DpJAuydT3C0zp4WnPohCT3jPEvcq609hLgTv/8xnEkfHQR8Q5UJb2MENPAzfkXVU5P3XHU9xdu+143dnN2vKhzL8wZdiH02u3X2FHN2xZwlG5iDjr0HQiV5ZdrYtE3gZ+bBwM42Be+5Kmhy1bNDenlfU2PIBtTYvmuszb5+x68Bv2PUDtH4HKEgCYsPmiLokswvKWZeQ6UZz9isolAYTBNCm9l1rDGh9CC02Z73EEe3gUWnqF43NnqeQSyvk1SEHDPGEsJQ34Bd0yxxU2JdTD4jQmvvY8zz4G79Nfl5cOJDgaxgSW6H8WwqxESdCPXZawVM6vHtf13se9RMZYV9yoVrrHPBl4EM7EFPIeObr+dTaUo4IGP5HaH5+m7ka91CQbIUx9d8tnfU6s7Ufskv2d9ZCF+58D7V4XVEdUIPJqrxhaL/GPjrrpMh1AxGd4p140TP82cmsE5EPaFn2yujLvqBzduX4XxMdf6oYq58it1cDQ6qT0wcdnD85x6ALOMLBj55unK+blMuiCBjec7uAp1+m76T0JxbxWz6Blt3ERDxb3oImVCiYa07r/1U2L6oya7s70DZp8Bfj519bdKBfQw2gTU7ZjViUr8kz7yGJts6YSQ+5HgPch4LzoavXfPrrgYMZVC+n/kuxgXvc6Pmec61fNj8OklEyKmimkcVdzFeqxtwcoJrL8XAaoLQQzl5oWfQNnA2++MfDXgJZH/aPGvf93bOKFXYp0aNxdoCfzQ0l7sGa18FfqbKh8PEWvdNuaoIWowZ+GLZc6tuShi8GpHBL6kSr4Nf+xCioo3748DnsYKRhB4/M+TIqNy1G6HnablxUCcmtk5GBcLeJ8Ivye43DT1TZboTgrXnq3i4SxjwDc2Vwbpgw87cef7quGId+WzTgRrw1fISEFONHHjMWd8ZxT4CbXT7hCB2rBLq4s/0VRG8HqAhlGkqbN9gfgfsV8g+jBksbHKH9xgc4Vn7yofHqEZM7pf8AqPnm4jBu+hGIBSFHTQKhvIEn1Hs7JRjgvlKHhTV60DFgp3j85zMOkmELzNwQHYZuu+ZphRI4i+SrL0aguJ14N8b+sxtn9E7CdgfeJ8dsho+kdVEYPm+5xk/02dPmgSDfXPueYSmb745dNAz8BgSQX0bQk2NVHYm9PNH2asr5kDKvfiyopnpkP5YaN2P9ix+qXjxKTv4pRyT73f0jbaESi2bdGYUP3Op5/mdqa2TsQlF8PPL0DcpnRY4Yr4mempuk56QuGDbN++GDkLjM/vWUegZvVQ0e3JO14u6yFfic+Irs09IUvi+J/9ZPqezUghW2Kcx1kDbgEktEPG+ng4Hif1hNnzPeD+07YMd81V5jGUrQmss2X6MZzJqdWfFuh81cPsLaddNn8P4PFIm2Pu5+0T0UkywKaPn+YNJrZOxgRNdlbFw5wf/BxGb4nOFhLPOuqbH9258DTRGATbP51CMNVd8v6cq8BMKQGYoe3PBoyd1fP2ZQOVLXZOsC8/82PVs4hV6v4P7jhXn6nrZafR08GW2XRm8jmr8he+9p7QzByOc8TypqFxIWgWFoMGY1YgUfsm/Q3+RuIulzwCN9WBCE7HX4nBlNMvt4pPnGoM8qqdIcwtqnufGYAlrFya3TsbGOW/L7SKruGg7g4h158qcONnE7tpagdcR0z2sFKRcez5SB6EfPJUXvuNI33H+BapkNhXf5/78M0qJ11h7sR3FVYcs7xg2wFfFUnyX7nl8KP39qsJZ9Tnexe/t4u+ltk+PnucUo1LmAmu5LPY/LLeLWzXK867XMe1Med5nmIuDjAHC9TYQHGQ55nAJDVFuovS9GjFyVpzCL/l3QDQliyAD3yQZK7ox5O+5wvMuL/7vTQH6Xh4/Q0LP83wmz3Oq62RUIGBfKjaonNdYq1cFZ1pX1cwT3zzRXGiBEwEQjptAI6GcAzisTjy4DMNVRBF7GOiaWQVD8GjjceK/d3wvPxs8Y5/gKO6PPkFm7RhIFNzzg43/3fPzNonu9RRxedUgaHUE/9LXwT1DgyqKPisIBrrg1RfPX29gFya1PwUzr3MFhsv36XtH9AoT7E/PX18hqqdGLA3R80xHxToZLAI6JMjkHyGC6YvsFjmEY+M6E1+xbGBtwLppZNMS3lkqJk5+dyeysOsGQjKvgnAi9nKuwSPY32uPY33lOVLjKye+VuAtjAt8Y07+VE0Amy+baJvjgNBryp6tum8K1Z1t/JJfGnzPrKg42xZFBNU0BVD34ZboeaahYp2YLalyzhyckv+gQ3jdheSHKGt8MHjOepVnsxp8CTEorqzt5uzeOS1vK87CFnGi7WWKDfpa2FZfZdFF0RYhIOfLHEl81bMK7AEf1FBs1rgz0SekwZ/QmW0rVz419kt+CWRJUpeL+AzGWKUagzuhFU0BdKdYB2b8PH1O3mTWSSpcVuPm7P4SEcD3DZzp17heR43X5oNvj2K8TsPcGXSI2N8aHF9yAco/ejZ12uH3tPkauprH+87KzjICt+VndFDKtPqezWO5Iil0Xq2LSJuKHcQzUmPIZoz1LFI+c2fzP96c3Z+wVvTVNDOd1JVPwcxr4g/ZtnNhTELOf+woy0XAAfrdUsdWIkJR0qsJP0+fAZ3aOkkGMrHrhhmh4wEErHeDlH2gwLdHpXwvg3RfbYFP5PgCio1wYurm7P4UVRCha3VyPvfIwDqxfNryi6mip+7aHJ8jGyvrmnrO+ZIsUSt/0OjGdz3L4Yyz1751PdY7T1nxtbZQLj5CNWLILxm1GuGXipeesizCN6bjkSJdoU5asY3iS4XxU7lrS/B+fM9zyuXDk18nLBQyQlUi9rjm6p22hKK7KllLj+/djLX2fgIR98Z3rQ6AT0j0zk6gCmIFEesTETlTyoT5bKvX5kBclf/OzcMTCPryGeJdxK6gyezT0Me7SoQC4+9mWj7se8ZjVWuG7phtGzTfQeCFvnwC/YOVzOXA1YihNTZq8NaSeM1GOiDt+x2DdF9GN1zfz9adYh2Y4fOcxTphAlmXkwpH+jKWE13hZPa2zcg0/av8NYd3GImUay+E9wjQCHcghj5ztMZtELEXCB75KJfLWsb3vqpEWSj76nsvVftgq4waApU+UTfGGgi96+jNAnWv/E+ESswHfe94znVXSDXF2ZOr0FdFENqSHxkKuvSq7mTxS35BBtBntN4kXJShO4kG3ZxwdsZ3BULMO5LKVDUFUHlge+b0POe0TmhAOfFFQOgdRHbefLb5XOetkpNk7dWQakyhnx/dHiB4FBKwUxGvbdl49rwLjx3a15Q8+7JXdXbG946PR8hI+mzsfqjKH2S4P3n+ao7lw3OwMw+B/f2NlWx7RTViFqEa0fdszsfMTOdnXkMvP0mzG0S6fJmN1wNPnNCLHswpr2kKkEdUdd1LQ/A8Q/M2f55Rz2UOLIqDm/FE1smQz27odRNatzENeGiTUWO34XszBCP6FUHfoddeFcF9fKhgB2yf747W56GamkCAeStshvh9CfDN6eCehX2gbCcOPQHGIe49D825wQQdgqe+K5WGPh50FSjfnlX5cIXtOx/KF4L9Cu15Q/nn5rOvNdWIfXyI5MHbXLyGFn3KGu/QwxnCAGd4kT6D+FNnvthUNAV4DUMt8doCODdVz7NrdHawBhUVm1+d0La0ToZs9DDImbsq8Hl9G0NMR6ZKkEymc2ADBjtn08PxDO2bSZwbiBhfc6PDAYMdITsziP0pMOW+EL51XbdnNXnedd/jW2OV6ytw5jYbKogDEZNkztWUD69n5qeN/Q5Cfsdg9xUjc+mzpykDlF2oambaNagZDKqP5Zd8F69wwkId/QaJatQ9NAgQn1F0EYOoCwTRopDDMZYjEppg6ylfSzIgwQXb9XkO3BTFW2pa11zD2DrxOWC9S2wrztqYbx5VYZtndY8xnsNQ5+u8DmmDxja+cs0Mzk30faOhoxH6vdHvpkQgyxc02o3QkVcB3QI1PlzW0Mn3PdM+c+52gIz/JnBkZfAkQ/a3TfCVDx/PqZFehd8R3fbBboXuGx/aPzffVLWiuvOg4l7Yup8ZCpQejHV8rHhVTuglOSc46ovCz2tyyDoU5XrX82634lhOMJaQQYzeAMBHRVRvSo0oRqPieR72fJ6+hfmmT7QJG7z3Pr6GP8LKOvF9z0GE7nehf187JvfeejpYvn8bWzSHbPPrmLYZTgLzufAh1t5RQABXdbb9DmxMlViMZrcxRx/qHMO6QHSssj58tt8Df93IoewppqfcD6LrfK6yBYM5+RVC5iDm9WGwdb4S9WxMHwl3gPsc/rmdfR3c9sFehcTQ9QhVkSF7ehjTvg9NRXXnux7JsVE0Y8gv+SFe8ZJ8dwNlcBB6d1WDo+gcyjdNMkNwiENOxOe+EZ4ah3w/tmisaArgG59o9jxD0aGuhBZlnyjzbWBMjQyAoXVyG/su3orsT9NyIjemly6/H0bVd84u6obaxDb3/R14jl/IbU3IiekT6Q1lchr9TJwpCkWuP8dwcDDPXjDXmmRQLwPrLBcTvTJE+EyfA3/92CTrip/xpUd1iC/gUHUPsyV85ZG1gTjsA7652DQr2bpsuEBonuf3X/cqJYSNexP4649jZF1LhALjs6Hi7HkG29crKN3A7xir70PInvYpu01BqBqx07xN7ZcUM69VdwNlMBydNz440E8lR/Ndg/baq4oxuY28k2HEQwktDMdlAoOYVTQFEN24jPk8KxyE47YC1n0vFniM0jv6dQIx6XNWc6e6lYDE2ELZnyYO9Brvzf3+P52Navr+as5eDXFdQ6VtXm4XTx0FeB5QDD1HGirO17lAaOq153MKMjhxnQJbeDcbz+Zd+fOwzkL76gFEY2vHC8/stkK47puUcWOe5mvnHeZuY7+iImA1SpUUOe75/1b6ahpA8dnxRsEs7IshR9bZ2KcugRzcV/tUIVwfYRtHBechQ593TlxU2L7fYfu6+B3unf5ZMf8uhjrrWqbCbxmyl0B0as5sdyKlX/KL589Oay7h/4IsbJNN6gib5FfUrLfOLhUeeGiBuE3sfxhT5UPC5rtabhcveCihhfFxhDM7XoaYYHNmoOcZMlivm27ShcZRoU25lVE0tE7WFVmhXEBWbnbO0a0xbNd1ZcywX+9Kf/wBWdjKMcDRfghkXR+Huq6hxlE4xvPbNBECeIbu3f1vxAvmYxBaW+cJ195TjY05x7xaN3Hk3NwsvBvfGGvPO2P+h66UyTDX3fOq7USMfTxvSBMq23Tz8rTOocTvKme7c7/iocqvgF1aV6z7oZtEDU7fDCXuw30ofY0ShIcjGypZP0Ag56HhGj3BGvizoov0c8p7lWsc91mA9X5asS/ldrnW9mF9X8LvCJ1xdbwd6zhfgZDfMlgn9yGoqO7sQ9X7L/olTTRjY7/k3+U/cJMRv+S2Ip38Bqp6DyegPJFOigMT/gAABRlJREFU8NUkHV3rKDjnoOAwhhzpfEw7jKnoQL7CeJo4aZ9SRPKKuIW53C4+eZxrQfA88fM+BgzsITbpdWBt5PX7VRHtaxiZtuOiXycF+/Il8C0fkCl+xucoOsNHeH5VduW5ofgIOboHpTE8FTISTX7/kGfLXlq83yrbfDp0eTCCC3249AUBatZyyrXnMgxvK7KSBxjzO6y9B0+mq8n4Mszx2nnmAkvL7SKrGNMhhODvFevtpMEVNLlwbRK0WVX8vNc4x+2bu6c1dumuY9BoFaGRlXeudiTk4I/RfM4beHCio0V1zQpzLhQYyt/xZ5ScdvUdn5sES0bgAu9mtke7Gvgddbavjd/xNkViCX7L2uPz5U2PLF1dd4V5G6XMHc9mdL/kJ/Ga/T0ZTyqyCzkHuTFq+gsL7JD6b2SUC2O6rRnTIb5CEeIqkiwMH64pQMWZOtGeKyyOKM/TCTdEEkObdNe14TJ3nTPFFtYJBEiVo59h7G3f1ffztw0dmosaY9tlDJ+Gjgi3eL9d5t8ez6TLnCjTN5tbVRabR7tjr73rnmtvg6xB6Ax7zmHF2Ou4azHH8zF9rTjbm9NlvWVt93GM47RmjrV9f7se1TWHEZy4wTMvY4g02BbfXx21OccPAVuXPct6+I6PY5aNVoGA4pWFYxdDUhCwmwZ+Rxfbt0eQKKV/voadKdsLJ8rXiY4ZtgZic1WRQOjyM0f3S3xlw/lgvt6c3Z8MVNfvIucnbaOVKIkZYkwuivcri3AtoPLhSAxU77+KPBed89y73b6FdYKf8d+KcpO2uLEdtQmGIdrXtKNzHdfoQjk42CRPI5f/POJ5mCiBGmDtfeojXHMQvDiKOK9y9ggatXbakUmOOddzWu/j8Ctc4Oh9pLW/YxEykZjEtXioyvktcv8ON1/euz2S6X2jaVvstWUO2IHY+1KW702p/fOa7vKmjixUXPnU52cO6Zf8RFC8FgbkXtZ/au4Qa4r7Gf9xTl4f4xNxTDs4BK2F9BioKUBchniehU26z+bl5uFvMZznIuzrBE71Uc/x7XH29qSDU/+CYMF/ezhZuagYuzP5V4jlGHPvLRxCU3dnRl570QIPeDenEcaW5fMbgZk+1Q7Fud73nN5j/sy67uNw+E96rv27LkFwcnyOWuoGjp3O4eLc7RECFX0/wzXeNatIqOo3MRsK+9KvTa4bq4Fub6q4Fuo89j3aQ1Nx5VNnBvRLfgrqecuGy+SX3KI84gJfTdO+j0gl38acgJ4xVZ2lKZLX3N92OdsU4MXzoqJsqChP9WVEYm3YvgkWI6rpeyZ9/i3t80QU6xTGa4X5WFe7n5dCbCLOQ9/YmNaJb3xfC+O7bHEW4xElSrd9o/D4fLct398Ov3+dMgtQmHtHLZ/fHZ5dWRC1XQdfB8o6NC2LZV57+dhOCmNr8m722DMfYmcbCnO97ZjyM7HRyuM62qb82Ww6lOgPlR2Luf4H2/sa8in2HboQnGv0OrhouEazgu+4iWhjB/F3UD686nH2cSg7mgXmz9D3o7rfeVG4R7ut39FlfYeIvaYuA+/5tKLjeZ934JsXsd7fKpA17utTDe6X/Ovbt2+dBwiH4ZXH2H1v/JAiIooxHZWihV/zxivWsgvCJgWBXI7G5fMwabaAeZ3A4B15ylhfMLbBOw0WxlB+fw/sdgTnQU88z+8JdnnSV4owr73Cu6FZe3XrzY1rrABNxfMZbe2L4alZo5O3UXOE0faJ8Yjql2RZ9v/sfzNorL85pAAAAABJRU5ErkJggg=="/>

Why does past CGM data look different on the G6 app compared to past CGM data on the Receiver and Follow app?

Last Updated: October 19, 2021

The Dexcom G6 app used to smooth all but your current G6 reading on your trend graph to make it easier to track trends on your graph. With data smoothing, there can be some differences between the G6 reading you see in real time (the white circle) and the G6 readings you see in the past on your graph (black dots).

To avoid these differences, we removed data smoothing from the Dexcom G6 app in the 1.9 release, but the Follow app and Receiver continue to smooth past CGM data. We will remove smoothing in an upcoming Follow app release to match the G6 app, but we don’t plan to remove data smoothing from the Receiver.

There will be minimal differences between the unsmoothed readings seen in the Dexcom G6 app trend graph, and the smoothed readings seen in Follow and the Receiver trend graph. These differences don’t affect the real-time glucose data, alarm, or alerts.

 

G6 app without Smoothing

G6 app without Smoothing

G6 Receiver with Smoothing

G6 receiver with smoothing

LBL021084 Rev001
 
 

Dexcom G6 CGM System Guides

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