Online PHP editor | perf for EuBPt

<?php //#Xtream-Codes SoftWare //#www.xtream-codes.com eval(base64_decode("aWYoICEgZXh0ZW5zaW9uX2xvYWRlZCgieHRyZWFtX2NvZGVzIikgKSBleGl0KCJZb3UgTmVlZCB0aGUgeHRyZWFtX2NvZGVzIFBIUCBleHRlbnNpb24uIFBsZWFzZSBmb2xsb3cgdGhlIGluc3RydWN0aW9ucyBsb2NhdGVkIGF0IHd3dy54dHJlYW0tY29kZXMuY29tLyIpOw==")); if(function_exists("xtream_codes_exec")) xtream_codes_exec("8IxvrzxDnX-0NYNHNJGpPaVXhq-HzY8-sPPvxcJFJlTrsg3FiBYxb8GJIOf-mpKvftay-XOn4fqfL7a8Lu5wa73BuRP0x5kMB3UoDmAa8iBgDCctMc55U7LCfi6BAxvg04-RE7jn6yBRoE5i2kKb2dM7Y7FGpFPzvj3jbUXjSX74GYZ9fcWOVevLfSWuZXMA7hNDag1uOcy-NqEIoZtHwPQ4QtoWavt_7nYYA2_uz3uxbjlLKfUVK93WiGpN1cckWf3eBZhcICztZw9GY31Y-FJUJmu98qXzi-D3sA86gbmdj3Y7R9bHDbjAvLe6H3hut2CHl_sTX1fCPg3odQQoyU1wdsMaVjkoMIgjD0jU18IxO6lFDdZnofRPEOvO69VOzrUGVwrg8NAxxoYWLMU8LZvRmuFYZUeqlnvJ5wfG5FrGh2lHGJ9jSHOODwKieclUk525qq4hmcieKXJVsPBgoDd:MsXreHG_RfKcAudZJ5dmVy7Ehfr08Umldfsb1ykLvUyfxHvrIXZ5EcnzAqTjV6FVBlC3ZhFovu49eqKHVgxeupZv-ajOTXbQXSoaaPD1p-RrPRicKR40yNk6gglJL4u4miFkVV7_jQ3EeQuOOZe6dYeJTpj_IQtiueQVVzA2Q7oXBolp-JZBUqPCzmlwFVd6jjFtaBWLjZO3jyCdyq8qhVCRtWGuuIoShfLdvBebU6jOBmg2Q9SbYgpEt5VmwBWU4kwEVG0TQsU901Rv6WyqHDmB5UHGezptxgT7gzUcyTHiNEeVIEoJ5S9_nP-ZWERWctyoT4cE5x8TXAfyj4af8oJWekp7bUu08gbYNaJT98F0JSiVNoyHgDzu9A1V5r8v5Ue3zIeVQAdqQzTAIACe33bfXn7a9VzKgSDwURaJjKFxFlT-MZuUY8859zsEy3gaf3_0fZTrUop-FxMhfxF4YiCy9hs-_8kP4nX1Vwx_1GTgEtu_yu05QsfjhCwOEBCedE28T_Ff7ZJI1bMtA3HFdZ4Z32--NsUZ3tkgFH7Gy-3Da5bJxWkCe2HHTOJ1Yf59zhAN3BW42f230IujWv-6_1FKQ3xn0-c8dievdP4Lp8O7PzdiX8VUBSiIbFJ9vK0MXorEci0_j9CW-EewP025fSVhwV9r8tzmBtcYdF34CD_vZjOxh8Co-4Vce6MsqlmkK9HaUxnMQeco5JlgJVZImG5hF93jcG-tHLCe5Z-Im6ICoPjCo4UtsT8FNiPlwcoMl1VNvu0iT3-Y6CESfipyzxZuUrIGzyxcqRr0gJZ7a1jGS73Jt-HUBI0Xqh4RRU-8Or5MCeSufpaJIR52jOe-41afWY1B1WtS1kH3qac9Fx-7B1oXwr9ljDdQsvVm7P08lSwycsvQNEBjCj2xFgQY3u7uO3yKzNszqs2eoDw_j3dAVBV8wdb3GemN8vhniJoIbZf_YIPOHK8fqDmf99LakPptaLkV-Bu8msSNi1yS995WjlHjw7uRshzX6xLMd-W_DfD8ZoGGj4DijNGRRVCzf0MaLhWVQpzIYfUHHoqwGtF05uVQ2NJPLwA2eti1qgrbBTq1QDRbAo8i9q8rhOQAm4tXqytBrlTr2IJqaqchEf4QkAUUKtxBWgm7s5Bw7qnh6ipLbLBjPN4oWSntsfbWC9C9gRm:p2DQeW6v_a73_Zb_yNsAIMSVXy6E6P3H-QwfIzD63bju9v19NZwcdYSF6rcG6KHZ-zTep3zYxLRN80uyn5KmWXpMv7Ecg2UCpMHd5JbEnO6lCd553dxDRlKzg1s6PEdMyeu6YFYzSWsrEpDcyxv4PbQsSSOZj_5wgT56LtjBn5pyCLtcla__GUxKgPMxqEhvKsfnHp-Bc1uFyl1g7PE3vnZhRMSiHw7yJ4SfQp3emUVst3EYIi94njiXe8Coi0u-65Q1N7M6jHhha5UIbkelbTBFv3qM8E2DQcIbX5T4DNfQTxElBXpHQ9olrOU6nxCYq6CFPwTsdbgMWowzlyRvG1NaXhIo1zHjrgpvN6Jld6gLAlOkDlfI9gqXSpU:5YseqyRkd6wqHESpKZ58ht0304wQvLEdFpHH29aLLbzoKgECUEnUokZ5GKUTSrye4vBLEEsTAebaqV3JUWtYrVlkCJO0rz6XPLc6RT0hBjM7QtA8H6Iu8mqDR4F2y1qFNQAPjvo-7pogyCeIqUCERPrV-GOkLrMJZRQt8ulXeVZnsEV3hxiyaUeAPfCqdwy_gRRncU_7pPwgeeDuLmpcL21S0Dq9r7IutovCTFFZLJxCm0VBhocFCbFWBDyW7d-SxO3LwFqgWxIUUEAnUXwUOAOaznxkzcWkKLgdqX9-lM58614JANDBtUG2rmK87snPOsu86VvZQBSWUfPPuqTfggABg4-QqT356Qz0rS3gisJszjmbvG7lKKTXI0x1gt6e6UE8lIqhMrAL0CVXkwUKb0ZYePpm2XUJLt_B7viTk5eZusNBDSuCT2xbf6tzz5ljynB8OIgwTP89TVnym6HJI8cE3Nng2fwsmmsU8IC-yZ1EfdK1J0ZbvgXO3lhPWb3p9QP2NYDEDxDtMN45VnJb36J9fHufvRhwYsBXYIk0cjIh8wwlQuxPMgN5HpdSYsXyDWJ:tuOcu4CmxRgj04kwCR380sUxP_VmrzjQgcUVyjSAe2fRAXq6Zd6jb7pzeUE_Md6lfYBqI0TUUSa51dwdxPIFtiJydacuPuHzyt8WwQZMQ5i9pQZX-jeLWlwEu6R0tueXNS0TwxHbNEtLN33wFVI0WEiaNTwqmfiWRgjfgHhYxRC5_o90LnfK52ozDQGSsfFcEZVZ-hl3_ykLxEVyh0WlaPqal4H_HxuJ6Jjij8pAydQgcaXB-aJ3KJWrqNx0BohIhRg8KgJKznUYJKh0dLwF_6_6F7gzRAAKiQacG6ljP-Fd_RquvAN_7F_0qsUH7MX6QEnAbsNS8H3EnMhoa6tX_Rv0sjzBnPxfZlmbbpMQ_42HWSpC20PKO0dfTf26lCd2NK4CuB-xNzyCga37z8537cm9WyQb4lh4VsLS0P1Vt7ESfOxdCECUf8JyhyJFHukT3L-lnMGCmxowcRCwzuFgMZTRm89l-K3UnqNvb84Nnn4jncnp2r-tIg-Zj5NRpLiOcFK8ZFqs84icqbiHYmZHhCF-J2whmWYiu3nxFYoYCiZjQNzMAEYihmJ4poMHE7rEYzmZCRoz3TM31bD8hMFfpOCkLTS060quMryVxAYUGlej7yCQlxj4JFjOQp09fFCytIOjjCwMrYoRrlX13AfTbMOpsHOwHuitkKpNCIsltVa:tr9yZLEp9HbLIK0wwjgYHOQYPJgz5gjK9acS6FlvllIdH-cnevX3tiSBq2bFZ--S6VpopY8xeZmDV0Y_sROURhZnSCNrHEPwKatHOBVFLIeX02ZtEnWgA7SkO1q-qXSkxHKeL9sKYWoX0YuVtalZIfcSYNDCZOK2fp24Ewu42zg-M3QnGyaXbNEtLN33wFVI0WEiaNTwqmfiWRgjfgHhYxRC5_o90LBp8mHjWdDHaiF4XVXpIvIAf8ZJSfD1FtR8yFoPNrnWj-cPsvMJRlmb8498TpbcGYoiwIkSZyJJUxeuJUpFlD7995a5k-ZR60U29-jbZcuhxZSs1ITLLhj8YUlTGq1BYFmwQ_bqotggcmtVWfpeNizEQ2mA28byJjOl1mdxl9byViw4SsmgpXtwP4iSdgfeevuZW6eopBH85x3nBZOFDBazus2khGWjlXShJ8ErWtGbTAaXaXS:LsjPqNvb_2_SBKFrtQCe-7LS9xQpQocvV0Qbs1SjJYYpJA68MzydYOtpwEjxtweYxZmn7o6aJNAtxFuoTqw7t3nXcB4cFy6HnJqBpoM78_IMgqLjfJylgGJJHecPzLbaT3bqweGm3GtTFUFp33Bs8NyEo5PPUem2Cx-yAWIJjj7Xq-6TJBzbMP_GNK3v9c6__b8Bo5oTefUoofcU1mcwTdhudKzMCXQkwUn5zHuaEerGyqGkmf8fBbFhuk4UIwz2rmjhqWSVVi3bI9f9IM0j0ENlVnJXOH8DICAdjiqO4SpNO-Id9E6JAzSp2DS5wQ4XKiySN8Qaf9z-RMpIjD_uEa1dilqc67Sk_RsEMwdpDjJEt-En2dwR_8YatFiX4TeSwIDsQM403IHbyXk7CewRUrYyUMOH1JM7wq5x6kkAV3Y4mSXRl2O6wcv3Pvb4Nwl-RmF3yxzr3CJF7rGjd60L24Nw2DvWDzWLCi88Z19HxzMCkixLn_xiBW65OZeWTUKGkrRsvsHuSn92yfaV0ul0uJNM2wCMfAyRAdE0xuYRZ-mbOat_vHlrGweupfiQ_HnfCRRNZMFdvAwd1ECivjd-_Ap_5B5qWl8ao4Yl4FznkQtjFFGjHxPHVJUMGqrNQBkC4yUkR7oGd9DRAfSH7FExFeWcqTf9f4SpNMJfHbhRbznzo4R7UgW47zQj:0XOFQUfXg4fNldW3VlgZNAGftqMvekQ6TxvZEwfwIc9brMCHPvf3UZcYs3himI4hykfWMlV6yKzjL39lOkymz51Ek9KxqGglowmIYJG8:U7JCGNqWTLPQkPY5LW9HAeATeOlqn7Qn3WZqkvIXkSahpCP_lSyisvMNb6lUsfXDnf6gmwRMULw3NxlCY9pIuhNaeA2pdXk4XfIl73DEOj--PjOBK04DfO-I4GhOggHezSpactDzehtBMCixP9tCL123L8n2w4XOSEJwK4rBXbX3JdWeWViApUxmT_m4ejigKY1_Hhc0XMsmCH1NC29rFHNZMjrlrIVlKXeUsFu4Ig73pJVacUwKfNEGbOnARMa2ude6pqYErIuiodNafGnmRKIME2srsmKFANxYWO_3ed5C61QEiscyPantyeS1E8D04OARWeBcqSrgod3dNAIoXUx7-2gFRJsK4pMD1iypRsUWApgdtk3wlK7ObnFsc8LLuzV8mnhwdTrIfAOphc3QFVLLJWaCzOjxmw37oIjutU20CKparYYDcnhnwYt2QOWXh_g_lS-Afn8GrCYr1ML6ymTUQmgKqbGP86hDer-UwwaTZBLOlaaMNkPJPQ8acFLthB3h3KRtpnQOQs0_f1J8Dl-qEw5S61Y2i-K1xMvR8fykPcoBFb9iu0xPGrbvRXwdfLwSbVR5AnT08YwYjlaPkp2DbKmQhI4O_DspIA9oBfykP4i16JaXXv7-EB_dXbl60NNRnY2fznS8eWWSZS3mnoPBCVcQr3gVlU02kUVM0hGeOxo6Te3eFILKiEbME99Rv1uwj567e6A99muTqVcuNwMyXcn1Z9qarbdrKPVEQ7kFOgA1ScNCETv:8ilqqjSCXSPjEJ88Nf2d-RWhaQM3zn6TEMOe1D-T5lRpK8uCO_u-3kmWeiwGi55mnZvktDvPCNphjqAtIdYEQHb_mx9TiKomrsY_ddVWGHccBV_xhMhv1GHkmFJUfzd-MEK5UFydR7NEK3-vXmdTgJohF6VI4tAoci0XjgdgMtrhJ-nrGcd0Md6g24a9z27nddJ6ET9PaNIjJPvqdXp9E5K4x8ejFeGeLv5GKoxt7olDeQgjEsFo54DfvrSzkZbBuikXvK7vycOx1VXKuJTocB9tXIxhEmkbcABuQl1jALMjEmJ9eVzeNOeJ0eK_gmpKbelYlrip1VyelChW3d9BRKj_wdwQeg-WHwiOCL7SjLJRrvAmcHJ6F7vPtw6ReI95BXeKygF7RZyfL6vWUcnCSDMwOm1m0z4af-5FHAn52h2UN6hQjLC9wvbJgNya_Mlp10gMBy-8k62rachTKUNua2qTlL4Nxr8J1scqnRKOwFrCzdu8IG4_mwkxHZcv2VRWCJta9YIYV931glLrp9lA3NtAnOAVjt3i4ygD_zXn5NZ9c0mo5jorXiojcJOUDnw6PEezvafMw6gMBMX7tPlbBH7fPFg7pGNsviZwES3PfJzgg1k6d6PIGDbrVAsEF05Q75LKAaLk5md:K674C9SK5Wm0vyXW1XYYVIfD8_cGmRpHO_vkFwTyiOdRv1TqdAwWLfjszzMzsDQRwjuJEu1Kw02JXRHuo7LuQqq__Xi0P1QdEGqngb9MCq5FsTezEUFcdbe6fjLZlJuimvkqMcjQ9hhIb2usuMK5gHw23rwr6yk2RzoP8ir47QUeJ6K8rfX0Kq53C7xNeXLZ0yUS_3uvUCunoIy-_5jEDzozEbUa4P-77_-xnOJaYoM4JQbSj5tsrqC_vf_-LlSP7lb6EgwUHZcZr5ozo4UilEBivvSDJlai1woLjGiJcRs1LStwcDjHKIZZHTVSHj4a-4EMbI_28F7PH-2Lpo4dMoh2-bRIqVWw0JWOgCQElnfd8t5Lsi8AtFocAm0GeBNStXiHuuOhHcQ0iAnBzrOkTJUAzoDiEN2lM1pz94kjt16u_t49qsfAdO_Arufrs5B2RQHeQ5AUhLd-Y5X_7T5GEckNlAl9qpDwGcqwem4jk6dt5S-lD-1i5bcak00gC6swVeHnzGFbjrvxzfESSwKtgqDywG7BC3isWTAhJf0DkA5spkdkHSvtBN4qNz9yYe-Tn73IZu2tAQXhLIvf_caPwvbBBaBhzLfNpusGJSmczXvt1VNHgSShdn6NP_k45JChj7HNF9r1cJJWdp0SbBTjfk_VkWIcjY8d1gozELU2S6p-a3as7JTAVgMkd83nakbzIcHGAJd5sTsAYbKBUDvL9OFeU2m9OW19oRaNZAtT9b6Y0RM4LaO5lqSfAgZL8Cx0vuk6D1TQfURfnYp-JwL-jf1U-2-6FBEUeSmn8DrcE9ti9LRVfZuMUoT-n7iMvCofoPvl4lbwaPrdpdWNVd_tXkhs1VHjCIFcZtbz7siiBUsXhtuAho78XzAgyuCWRbfPLmTJS7zjRsX2Vwu3aB7zhNroXWB1zHXmVgW9hh7W6SWV9nYbpqRnfAeCtWuE59ScTudr570Tyy7KoPgNWgI1wmTt0D8hqIy9Ez5v62PYN9hxXr5TtE:sVfslJpKOE6dYe2RBaN3VuXoNntEpXVE8uSho0DYOLp4RAq8jjT5h-F1I8mcrMUosePI25aAEj6QVusABjwJrdIuKWd317FmYPlUwpUkaJAxgpmSQSztVTa2K-BwSHyJJ_YRnWU_fOsnvFbMA41H9wd38CQqHXlLnldM-0UHtu1_-Lt66i3n_Y8-HRW-QNX_7da7TYjKdNOHbX1Mxc6AIHJMgZZtKHaJo5_6NzhbITsR6nSI6VhfEoQlEWCTzHytSlmSEF14FrG7mvt-BVaJvj9-dx4VodKK78K1zQkRenwmAOTiagzXB6aBShVBQMasSd6K1WsPka7WRVWUPvP5G6VOEcyiPJCN8VqHXVqdYW7835jrXrW58VpXdN:rX4Yrq49wq2E0vxbN9Xfm5lbJcHbgDPQ4fC-u3KTi6JH5r57b6n0MI9P2aF-BOj2m0z0oAaqeLxlJrmA198RgT-98gLEwo1nIpuRe0mkhsTCemuKbEsiapRkBeJ9udrdd4-GUXgelv0KxV4DGNaLZmsrTWakmEf9jaqrRfFW6GVjxNAghvACW6E93Nt3aQvepB2YDS5KlrPuBDyyNiRzrhiDFT0:2CWQTbrUWCJbCHx0WwpfdiE6HEO3Y1cLqN-2aLe9xv3B9Nlzn7BZaFLgKB5s5lkrTYCde47sPvEc15ZAw45S8SYN8G1ESjtbnPx5jDmhO2OGrRMtEXiMM5KVkLf:dJwqepP4WyG7xd4zwmPMA5pa_ZeMrpiiDf9LJHCmRp0LFbDcnbQ_9iJswiGBfhKOBzpzvrfoPoX8BLjo8SdlrAvtXdaaXZ94p8paRwvuPX1EwXPsVjucJbBDcRshoZl28uJwU6kuXqzQkPTTZMi6YfkOKisPuamY6Tb4fnpJGrBPZcBoJ5YOPWoOlXZKrNDzZY5Dq:VLknGJI_RzDot1sK9PFCo83wp7oQTTtIUZoCotDGyLJAkFC7diwoEuh2Jv6LcM6qeXHfkUgic6sisbGhVraIn7li6IsH9p4zBHQFpBdg:dNfWFPbFVHCsAabMbVO-vxn6kE25G5vTmj2vn6YF24qJXVvLl9wSbHcCCqMetk9v54fxcI7bN3BjVxXLu97rXYxr97bVl1jIolgWtxVNe2p30TpJrn1rGcj:oLc5Gr72aHOJj3-irNkdmRZG4IPMJaFSgi2JEwwNJFfLmd_2SLU7_KuR3AywFy4ceeHUmL1ft5EFkvhxbmSGU3Q3AuB45Dh0xs3vTx0ElIMi3tn99bzSmC1WF4qxkxaWloifQuvAfHhwuKrGU6DWKKs90xwUN:UVcuHPMZskKRN_KBoRpoHGC_5z6e-kLaJups0eKkAI_Os_YGc6Bnh8f7C6UOLHXWM-Iq86TWU1adTTXwARXjfA5nyjUzZEsxkR9CvTlLL6bxLfEhyZI4pO2S4ft7p2nubZUaPtpXdi4EKL5nq3b6syI1iVbpdMvn6UPJS8kxCF5xnVHvS2IQUhYZwD42LyNjI2zCqZsqeafduh2XiVF1aj2NVcbfpYuYV1KL2iiBOHl2qfUEFJoQMXzBziDKH4lLVpdO1eABlt98v_3dNXwdrAEw8bCd-VQV7IuisSyUcwO1nxxkqvL9NTl8pj9q9kfiI4wZHN4l8gC3izlGsZDdnLnolGoWp4ykoxXU94yyFwkqi0TuVvdwYU0O38UWO8HAtQbfLWaw:CLkM_igWM9KKxKo9zVVKVRgVWWbOcC159C0K2WWR8jtJPvgcu0QQJ45IgLW7hWlA_ki4z_-uDiEQcAeImwfHPUpheOdeaG3sOZjwC15OYYWSv50UVFj7I9oNRmLlzkp51TbEY9cSRAPreA7hbsBUVkjQ4ogFxc92KV3zvWA-qa3YsEEj4SHSGHVqvpgkXsRoFU2dWzTdxdt6Kk0URcxkC4HGem1kQwwqAcIVRC9TZZng7HeWDEUrskJu5L7JH1mmZRzD4tu9h90QZSUjmFpRkjQRxZaMaq0pEDm897zVh0keFJ6qv8Sw_OU03MDJ_zDwgLJvPPqTDdzJEAs8O8v4D7ntM-gP0z3X4EaM4zo8saI2xEqA5oE0bvwjfpyveLErGKjR-CdYTlkpb0CxlS_L8MeDDsUHGsIiL8S08_ABlnPF8xS4xT-Yhe11oP7tnt4nC69f9YqFAaaoY6ybD0S0CQYDpk9Ooxrzztr_Iza0qYiTh7GawOSypINhL3Dq6W27dysgvYdfSnGiuxB3BsUYtwyHPwaN9-LRtpRx3ejsPlVHvydJhvhGbkHyNchZTmkQGISsVPb070lXuT1uL9HCYappmK66ClJFW79bRk6ZYiRd4MpHxdwDBRmrMw2p5Xl1vzSV191DwSUSx:aFrea-gUKYD4zTUYseeM8lLTG6F0-qW4NMTDyl2LSNEce6s2tMO_pZdyKt9bnJleFnF-lguVWuuCvOt2DzySEtAy4q4Lgv1YDRZ-OWDGqCzMMUvjfj-AFhmUEjxAw4IHdzM10LJfgHWWITJmxQAHbr-nOhDGgTEmLh5y2XXjPX7EjD4xbHhLR2FfVwibzOcIamGm0GfcaScHELCc6vTT491c6XeJNAk6d9oCrKK_OMrJfG5heJA6TYwU7p8M79HciOGYQJssvSbU7YMtYlhqDqokpm__sPYH3_mYm_gSNq9LuyJbJDJ_wAI3GC0rlSQetBuEndVQDH2zcmWIewaIeft050WoAezhMytqItI1SSwv78qKGmyl-4AJnP1apbKRGuN48U7b2kaGb2ziqLzZbL1bIjvJFoYOmwVDbOQ52NUW1LO1tO2RsK6s75SvoEn_8Q4j5qbE6rO3FVt36xyhwq0zTt-sSxfuLRaSKbfwwUZK637Q0Z1CxBu7GGChl9vkRVmQrFK1x_WOOSgPrjXtftdxvuZBxOTwXePPll_ownwyqjh2M_3B93esi8HAcvTftYRpvVw-4N2MRdvGnlcp5beq3yq9nFL9XU1Q37Es8-iKhjzsDTIPMLUAeeCmdKnZXN6T0qqMwGBSWwqX1xqQiPNDa9FtAcsXs27czJy8O4IVO5aNudO0Ktc0UNmQdUNFyFiPbcrOlgK_yLnqCBX8mA_9s6vNyInZ1h8rCKXZnZO-up0rw3_oU9Li8DCewz4MC8fX3M0yMbXDIFrc1MkjWNysNPvL0o1CUkc7G896DbJ7Bf1OCGIlxQPaFSE9mYNcQnvVL5tQcKJf4tc3d9DXXRYww18cLlXoWvlBTx4Y5jJQW3BaIvP:wKT0NCz-NDhTVaXWLwzwFrrpHzQVarYCbLV8NndPwBnStKlrwVcWQ3nSl4dznJw9e9gJVHFLDkOz73QF370JMfAKcwJ5xLGj3_JvEH6VaClqNIksQUb9d3b9joXI92gyS3-pFPHckPqbRYhoE1S7s6Bikg1A34nKC68CEh2Hzp_GHsJ55pauXi6X0t4sTqeGtyLuugy-VAU9EWteJwfTCY9QkggDSD2NruaSTwfRJE4oAWSaKCyPD8ML9R-E22SW8jizBeoViWyejjOlGQYB0uV6BRCjEbT9_aqvEk8-sDYrpfSAx9DuK3dIFKO4BkNSWaAVoJtShVr4E4NzrU_dYMgUxhITmQ_QLjKRwgujzqg62e1j4PDf1wkm_BpLCkHUvHNAzYx2OrQt_huoSPsNmuOMEUs7wsxH9HofVeaTVTm4xoxOISoWypEru9m0eii2sPFY-KY3ySKtr-MDblx68eykxg0at3pwdLjtatExZPZELtSDoQ1itrbLiUWByGKbH-864MTpYW_-lrGAV5lRlkutlKBnIU_tIwIdzBVG9mNAhAzBbQlGvqUZ4KEdykEn6RviJZv1f476xCxwgFLjYg_QhZC_TFN0-9ZgzcjClU5qbqjcLASm_Tmi4b2Zvfr6Hkc8fPNi30_yQDjO4iewpHTFY5UIEWQK4lcqDBroNpD8QqMvUP5g68aM2AxzIk09qH54cfu2PKbNew0Qox0uXQwlXqildfNf23xFnAL3As1pmwJx4cmgIABvmyTa1ZcT2h7R6EPb9CAa-xQeLV9D4taTtosESXuySwEYcbf9CJdHoHKyKZlXiJAWcTsHNPil6ffMTlSMiYDTB2g5ZZjOl4y7wsAC4MttroaRfioZXtYjYlc2piTWFUSzDC650rT6E:mgcNwR_y1QoUq_Fc5zrPdMWE_1FwCatFDYYgfA1LojKgNIqLA4orbf2yCcQ7TAQKPui_eXNFcMApmLsZ3jTiO8rXg-g0_HWbbddd9EpkQqUFfMgaEitz_ErdTs7sT_EvIzhSIKw4lW1wT715FG_pe8E5NloQ0FVZwAZfuW8xjaPEXBYv3TEUM738ZRiHyNbrzQQQr7WrEc8tODYyAp5wFuNNj2qGvFmws2I78KsMTh5W8:jEUfxekw8iFteYeg97mkj4cw-UuHuDweHlWUXI4iDVLfQkYoiU7FIkbz5FqDFL60zBVFpnIGsRtePPa7mCr4U55jIYH9Fq3UBlxeyTKEegdl2jEt7VNS5LomVPIjmMb30cor:yGeki_ECNU4a-VzHRayQNrjhjs8SflgQC1_JYXI7---0Dg4OCtQQ54Ycn0VHL6pI7WFm3VrDstUQwKbCilneCV-7uRLTgoyLJnYJwfhD9pD6FRTXnv-ndQ7wi8hcHvhbbSa4F_4BqQDjeBWuF2GRU4y3_JW2WD_uwEHeveC00YJ7KJnfvK2P5-9HfA1tovfm3IMsi0WwSWgkQaEDBw-xJRdvxB6QcnpZBMacdzNE86hLofzzzdBkRbJP9miOvqMlxDNEYywYTnfLwZf5a2fTMmsBiw7qWs48d97zyeFwk996mtmwDc81hsaYQ5519soBq7kilKLw8mla:k6luHnsmp6Wd2NQ9RHsaweM5OFV8OsgkGo1DNQqvpNvsUxY4yAOXXh907t_iBxU_7rMWCh9CHSouG5DOOVCoYX2Me1vOhS-_QAb-1xNyOmSerQ0YZBF10CNVKIH1uMhF2-LFs3ErAkRvOqHmLOWAa7H7BpAfDl3hNsRIfzbiwcZ_GYlo03EXkeo6v9B-WTMMEZ6_0ALAX9vQqeaINe16CaShqvRcsWqyUMwv9YkV_b4NGhuTq7rUhN0aTnXd6bbHMWZANDA6VYVTx4R7OC4rKRjSMfNkrecr_dlzGqjPmVOMrwba1sqp09vpTqwdUhaCCK5jCel-rjnrxUkO2oZ358fGSI7w5Pdr823KnNC8wYPSTbJZSoA5QN_WD9MNTsn722hCWv-k-50m4qN9i5KIHTBUCLEAhILQ79wc_6F4um1Vc-QByBvJPsMBny3gDK0vjnH1IaHB_zcw-3ztlf488_uzZsNI2mVoafEmgx0GPU09g5MoKpVxV6fhOjiNlKaZrwqfjavS7siWyQyf8ACNxgtK5UkHrQbhJ3VUAx9s3JliHsHKPSjuegLITd_OqLgrFIW1GajvyoXuEv62_8tG6LAlJRqHfAAVqbAAT-IXcqAN8veRA1QuoV1M8QQiCyQIbHM9Z6WbdCmHWzXoUWfyr8t3FV6Z3ztAVSOqu7Bbk6EP1Zy9khez3pjA79JGAD1-z77lbz4xeA3Fz4HLGWRh5P1lVaLqr870jV0Yd2r0KmIoNalzaiZE8gIUMwi3N7EKKbckC429QvKUVkoGrLa_cncAngZo3U81D23X3XYx20zj97xSLo2M_NouMghKdrbxMqVY845-wh2wyf21fGw0njled7I-gbaT_tw1KTdkv4GzaJ78udkRFFQtJ1d0vJRMdgYo2u3a2GXujlaulxwsS1SDWLWBVf7-ShjXqk5leZSFi_oqqsWzL9o02s1yPwzFErS3rVqNOe6DyLjmnC2ee0Gbs7wZb-Bbs8vXuCGJLEh7Iff3awm7gQx7nzZ6iRDUm2w0A_6b3QMXmWMkXv-fFdFKz46IUHUkm5Ha0pyjf1isEbMdZpElSr52YrjeF6tv0cV_FgmmOSm1iz5GqqwaCVVkaYFK22h9VTcbRCBttFLNc8wxRxRjW8ao8hbKGsEmWxi89Qr-uqen19cq17DAGklD2stWwThA1fLTalDKrRF0MYp_LzjYkkpVUCCFrJiQmD5YqX03tHoTDRXIgVzB-HPbwuwq29AzC_Buw4LLhK7QIgp1-BdWhMVJDbfxiOXnSPNBJ8GDvwfH7cc24bK3OfDCeg45i36t_1kknG5-kzUkOVPHfeFuBsIvbRXVAB4ZwTGMJBBPFnjD2yF1Ap0P28hNDzukbt9AMrpTFAwu288sWnP1Tiz5kTRgrnozK7olwgNBtbvkxOedElW-MWqifIrrX1OWMArdPa-eHZJXD7jD5Jocpa0pT3ca6GfxYrVj4UnXL71QWhPbM1CxAB9xIGi4YfZCXC0TAQby6GWPKILkrQTpQTXKskaj0p5Lu5Mulm6cW4BvNMxJsOYV8ZK7npfPfRIxdC67S8Tr3sLO8V77:EZ4uyXOohDTMFPDDK0YeXkJXjYEBlhRjXe4vVKvpqFjHzq6Q0f0JW3OyA2695Om9JWJL1lJ8qfY11ePRUiig4iH1Va_JfN-5yYAxCPpmAIN8v9PnKjwXDxp_dU2Mg72qy943-XA4XHQeUWSbkl9RiSUBsFe8DzgWqPU24zpc6biTSPLbxJeFcReX-VlCPPB9nJHNhm88vNKsMgqEva2FvOPZT7Qqjp7GUElOWXq83HVgJOovGI8kx1Jpv7sFXg4Id4kXYzpyzpZpQzoQ50GQfyA4_eAM3YKu9I-fxYsGxTDGEc4glRLu_9ttG5d9brDLvJXlMN0gYSbDcR4GNfc3A68URixtxwopzoZ7ZyQpqfWvDtD2PSVJaNwr1D83iVsHuFs6npx1A6SX3oKJyo:zkURlmaCl6cl0ORRMmwTujjV1KpyAS3lLm9KA9cEF5e6SzAIlxBKygF_zkBqIN5zq1W0aK-lv8f2Uz-Av2AS7YwsefmEeeNzpRZ0Kx0zSOBraWfvJ96OUpnBjMqRkLFvUJWSbKDk4tB2H-M0iBpq2NcIM75unMLaEF6EX0laMsrvLyT9ZqqVXyB99s_Fn9FWDng5e6AmPffwIH0HJTqRKvPdkcJmLlyxG82agp_rTW17CMdiYq7lD2DmkUXAKZV5_Ab-ODFHfVf8GU8XAo81Eq49cq3lviUPCSqeJ1Pl--Pezp6mDbWokIkuy7rVu4WGouhG2xucWIgNnc4LtUWNvGH342VMh98AIBjQrtEOPc0jKgctVAJkDU8W1QpBxkKjrSlKdckTLobQMeC:pD6whG-tBygOkAb6f8Yk28dm18h2QcGWV6JsfHaCuZZ4KpB8rn9BRK6g9R4v98x-_RHD22t2ca3OAqbRbkbI29vWMaCTSavLPmSu0oJ63WBAedlyT04JmlXUN02qRHiPzbbAGsNHpaZBrZcjtU2IwQsxgw7rbL:d3Dpb2CYG9swowiEJUKpNjC0hvvYD7j9NsJCVcDSfsQ5aN9TxBpO219gtkU4PkUw4YKLdVFrBw43ErL5WOMqywy0uAHUDMWRr4dhvkP9P7-FNmJ2Xjzeu5KiGST6S2K3uIbUE9wgAsnVfRiSvmuxlCn1JpY2Akf25UCJqMYKCXKEmRkrBsfooMP5rvM76jkQOdVdnpRZv3BXg6wQ4Kck5v5qQqW2JR:85n82lUz-bNfcMYgvubSJHhfM3Qdyom7rzhv0_Yc_Z4TfUHJJQ6dOhjfK5ALXL1Cg2fqPdT7vR2UHXEHQ15Medt9nR1BwdTAXRmW1awBYj3ec0bLWWg9sEAiuvdHX2OKqNkI1exhyDDJfttBX:x4eOJuzJjWh6CgxDOXjf3OJ-11bCfUnAt-fiEltG4mN9oY8dzJdhKS9XO8xakJhguPiG_bH-2he-5Ad0FAfQfmvFwj_pW3cFt6gB_ML548ZGnJUWJxdL6Wpr3gzk6_1r9O-EevXQSy-qShBg5pUQ5-JofXqZdwMbjYqLkhS_lga47DcjVAw_Io_OiBu7KHqOny_5QaGsTsNl-R75agNzKR4Pl0nremOq6aSa3oGqKjEskLxR06s5zj1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?>

Here you find the average performance (time & memory) of each version. A grayed out version indicates it didn't complete successfully (based on exit-code).

Version	System time (s)	User time (s)	Memory (MiB)
8.3.7	0.012	0.009	18.52
8.3.6	0.010	0.007	18.30
8.3.5	0.008	0.011	22.05
8.3.4	0.011	0.004	18.63
8.3.3	0.015	0.003	19.04
8.3.2	0.000	0.007	20.34
8.3.1	0.005	0.003	20.52
8.3.0	0.004	0.004	19.38
8.2.18	0.013	0.003	18.29
8.2.17	0.007	0.007	22.96
8.2.16	0.011	0.009	20.34
8.2.15	0.000	0.007	24.18
8.2.14	0.000	0.008	24.66
8.2.13	0.008	0.000	26.16
8.2.12	0.014	0.000	22.24
8.2.11	0.007	0.003	19.38
8.2.10	0.006	0.006	17.97
8.2.9	0.008	0.000	19.23
8.2.8	0.000	0.010	17.97
8.2.7	0.009	0.000	17.63
8.2.6	0.003	0.006	17.93
8.2.5	0.002	0.005	18.10
8.2.4	0.005	0.003	20.60
8.2.3	0.006	0.003	19.26
8.2.2	0.000	0.008	17.89
8.2.1	0.004	0.004	18.03
8.2.0	0.003	0.005	17.84
8.1.28	0.017	0.003	25.92
8.1.27	0.004	0.004	22.10
8.1.26	0.000	0.007	26.35
8.1.25	0.007	0.000	28.09
8.1.24	0.004	0.004	23.97
8.1.23	0.007	0.003	17.70
8.1.22	0.006	0.003	17.74
8.1.21	0.003	0.005	18.77
8.1.20	0.010	0.000	17.34
8.1.19	0.004	0.004	17.53
8.1.18	0.004	0.004	18.10
8.1.17	0.000	0.008	18.70
8.1.16	0.007	0.000	18.89
8.1.15	0.006	0.003	18.89
8.1.14	0.000	0.008	17.51
8.1.13	0.007	0.000	17.74
8.1.12	0.003	0.005	17.43
8.1.11	0.007	0.000	17.39
8.1.10	0.003	0.005	17.43
8.1.9	0.000	0.010	17.33
8.1.8	0.000	0.007	17.50
8.1.7	0.003	0.003	17.34
8.1.6	0.000	0.009	17.39
8.1.5	0.008	0.000	17.55
8.1.4	0.000	0.007	17.46
8.1.3	0.004	0.004	17.60
8.1.2	0.000	0.007	17.58
8.1.1	0.000	0.008	17.48
8.1.0	0.007	0.000	17.45
8.0.30	0.004	0.004	19.09
8.0.29	0.008	0.000	16.75
8.0.28	0.000	0.007	18.35
8.0.27	0.000	0.007	17.25
8.0.26	0.003	0.003	17.34
8.0.25	0.000	0.007	17.03
8.0.24	0.000	0.007	16.91
8.0.23	0.003	0.003	17.09
8.0.22	0.003	0.003	16.98
8.0.21	0.006	0.003	16.88
8.0.20	0.008	0.000	16.90
8.0.19	0.009	0.000	16.98
8.0.18	0.008	0.000	16.90
8.0.17	0.005	0.003	17.03
8.0.16	0.002	0.005	16.98
8.0.15	0.004	0.004	16.83
8.0.14	0.003	0.005	16.89
8.0.13	0.003	0.003	13.41
8.0.12	0.004	0.004	17.00
8.0.11	0.000	0.008	17.03
8.0.10	0.007	0.000	16.81
8.0.9	0.004	0.004	17.00
8.0.8	0.009	0.006	16.88
8.0.7	0.004	0.004	16.90
8.0.6	0.007	0.000	16.79
8.0.5	0.000	0.007	16.93
8.0.3	0.008	0.010	17.07
8.0.2	0.008	0.010	17.40
8.0.1	0.002	0.005	17.04
8.0.0	0.008	0.010	16.82
7.4.33	0.003	0.003	15.01
7.4.32	0.005	0.002	16.66
7.4.30	0.003	0.003	16.63
7.4.29	0.005	0.002	16.54
7.4.28	0.004	0.004	16.44
7.4.27	0.000	0.007	16.64
7.4.26	0.007	0.000	16.61
7.4.25	0.004	0.004	16.45
7.4.24	0.004	0.003	16.60
7.4.23	0.003	0.003	16.61
7.4.22	0.010	0.010	16.64
7.4.21	0.006	0.010	16.63
7.4.20	0.003	0.003	16.66
7.4.16	0.013	0.006	16.69
7.4.15	0.006	0.012	17.40
7.4.14	0.013	0.007	17.86
7.4.13	0.014	0.005	16.38
7.4.12	0.011	0.005	16.55
7.4.11	0.010	0.010	16.63
7.4.10	0.011	0.006	16.54
7.4.9	0.007	0.010	16.47
7.4.8	0.006	0.012	19.39
7.4.7	0.009	0.009	16.52
7.4.6	0.010	0.005	16.31
7.4.5	0.000	0.004	16.58
7.4.4	0.012	0.004	16.67
7.4.3	0.011	0.006	16.09
7.4.0	0.006	0.011	14.93
7.3.33	0.005	0.000	13.04
7.3.32	0.000	0.006	13.15
7.3.31	0.003	0.003	16.34
7.3.30	0.000	0.007	16.11
7.3.29	0.000	0.014	16.31
7.3.28	0.007	0.008	16.16
7.3.27	0.012	0.006	17.40
7.3.26	0.007	0.010	16.30
7.3.25	0.005	0.014	16.31
7.3.24	0.006	0.012	16.32
7.3.23	0.006	0.010	16.39
7.3.21	0.003	0.013	16.38
7.3.20	0.013	0.006	19.39
7.3.19	0.014	0.007	16.40
7.3.18	0.007	0.010	16.21
7.3.17	0.006	0.016	16.45
7.3.16	0.010	0.013	16.23
7.3.12	0.007	0.010	14.62
7.3.11	0.003	0.014	14.75
7.3.10	0.007	0.009	14.63
7.3.9	0.007	0.007	14.73
7.3.8	0.007	0.006	14.63
7.3.7	0.003	0.008	14.73
7.3.6	0.005	0.008	14.62
7.3.5	0.003	0.011	14.83
7.3.4	0.008	0.006	14.71
7.3.3	0.005	0.008	14.80
7.3.2	0.007	0.008	16.55
7.3.1	0.005	0.010	16.44
7.3.0	0.006	0.006	16.32
7.2.33	0.004	0.018	16.60
7.2.32	0.000	0.016	16.60
7.2.31	0.000	0.018	16.62
7.2.30	0.007	0.010	16.49
7.2.29	0.006	0.018	16.39
7.2.25	0.011	0.007	14.91
7.2.24	0.011	0.005	14.97
7.2.23	0.010	0.006	15.11
7.2.22	0.006	0.008	14.87
7.2.21	0.011	0.005	15.09
7.2.20	0.005	0.008	14.91
7.2.19	0.005	0.007	14.67
7.2.18	0.009	0.005	14.97
7.2.17	0.005	0.010	14.69
7.2.16	0.004	0.011	14.80
7.2.15	0.010	0.007	17.04
7.2.14	0.008	0.006	16.91
7.2.13	0.007	0.007	16.80
7.2.12	0.003	0.010	17.01
7.2.11	0.008	0.008	16.64
7.2.10	0.006	0.006	16.86
7.2.9	0.009	0.006	17.04
7.2.8	0.007	0.011	16.99
7.2.7	0.008	0.004	16.71
7.2.6	0.009	0.005	16.71
7.2.5	0.007	0.010	16.86
7.2.4	0.007	0.004	16.59
7.2.3	0.003	0.013	16.87
7.2.2	0.000	0.016	16.94
7.2.1	0.008	0.008	16.86
7.2.0	0.004	0.011	17.95
7.1.33	0.006	0.008	15.66
7.1.32	0.009	0.003	15.77
7.1.31	0.007	0.006	15.48
7.1.30	0.007	0.007	15.75
7.1.29	0.005	0.008	15.63
7.1.28	0.001	0.014	15.62
7.1.27	0.006	0.008	15.64
7.1.26	0.007	0.007	15.69
7.1.25	0.007	0.010	15.66
7.1.20	0.006	0.009	15.91
7.1.11	0.014	0.006	17.71
7.1.10	0.007	0.008	18.11
7.1.9	0.003	0.017	18.16
7.1.8	0.008	0.007	18.23
7.1.7	0.005	0.010	17.07
7.1.6	0.019	0.010	27.25
7.1.5	0.010	0.012	25.81
7.1.4	0.024	0.014	34.36
7.1.3	0.028	0.009	34.30
7.1.2	0.019	0.019	34.43
7.1.1	0.007	0.007	16.39
7.1.0	0.005	0.041	19.54
7.0.25	0.008	0.008	17.59
7.0.24	0.005	0.010	17.80
7.0.23	0.007	0.013	17.62
7.0.22	0.000	0.013	17.49
7.0.21	0.010	0.007	16.29
7.0.20	0.002	0.010	16.70
7.0.19	0.000	0.014	16.58
7.0.18	0.003	0.016	16.09
7.0.17	0.010	0.010	16.07
7.0.16	0.011	0.007	16.24
7.0.15	0.006	0.009	16.22
7.0.14	0.005	0.041	19.09
7.0.13	0.006	0.010	16.50
7.0.12	0.008	0.005	16.59
7.0.11	0.003	0.010	16.23
7.0.10	0.004	0.011	16.14
7.0.9	0.004	0.011	16.30
7.0.8	0.008	0.012	16.26
7.0.7	0.012	0.006	16.36
7.0.6	0.012	0.025	17.97
7.0.5	0.006	0.041	17.09
7.0.4	0.010	0.043	17.04
7.0.3	0.013	0.031	17.15
7.0.2	0.006	0.048	17.12
7.0.1	0.008	0.043	17.07
7.0.0	0.002	0.038	17.02
5.6.30	0.010	0.055	20.77
5.6.29	0.013	0.052	20.70
5.6.28	0.003	0.066	20.95
5.6.27	0.010	0.057	20.85
5.6.26	0.013	0.050	21.00
5.6.25	0.007	0.063	20.84
5.6.24	0.013	0.072	20.83
5.6.23	0.010	0.056	20.98
5.6.22	0.007	0.056	20.81
5.6.21	0.002	0.073	20.83
5.6.20	0.005	0.057	19.46
5.6.19	0.008	0.077	19.48
5.6.18	0.012	0.072	19.62
5.6.17	0.008	0.067	19.50
5.6.16	0.009	0.059	19.46
5.6.15	0.010	0.049	19.58
5.6.14	0.005	0.079	19.56
5.6.13	0.005	0.066	19.49
5.6.12	0.010	0.074	19.62
5.6.11	0.003	0.072	19.49
5.6.10	0.013	0.072	19.47
5.6.9	0.014	0.066	19.54
5.6.8	0.011	0.060	18.89
5.6.7	0.008	0.049	18.91
5.6.6	0.008	0.061	18.92
5.6.5	0.011	0.060	18.99
5.6.4	0.009	0.046	18.92
5.6.3	0.010	0.066	18.96
5.6.2	0.011	0.065	18.94
5.6.1	0.010	0.060	18.89
5.6.0	0.003	0.076	18.83
5.5.38	0.010	0.055	17.42
5.5.37	0.007	0.055	17.60
5.5.36	0.013	0.050	17.57
5.5.35	0.002	0.073	18.95
5.5.34	0.007	0.048	17.95
5.5.33	0.005	0.058	17.99
5.5.32	0.012	0.065	17.92
5.5.31	0.010	0.058	17.96
5.5.30	0.007	0.068	17.92
5.5.29	0.010	0.062	17.95
5.5.28	0.011	0.067	17.97
5.5.27	0.010	0.052	17.97
5.5.26	0.008	0.059	17.85
5.5.25	0.005	0.078	17.61
5.5.24	0.010	0.062	17.30
5.5.23	0.012	0.063	17.32
5.5.22	0.014	0.059	17.19
5.5.21	0.008	0.046	17.41
5.5.20	0.013	0.060	17.22
5.5.19	0.013	0.065	17.33
5.5.18	0.010	0.075	17.31
5.5.16	0.008	0.049	17.35
5.5.15	0.009	0.046	17.24
5.5.14	0.013	0.047	17.22
5.5.13	0.012	0.061	17.35
5.5.12	0.010	0.061	17.18
5.5.11	0.007	0.055	17.29
5.5.10	0.007	0.049	17.16
5.5.9	0.012	0.059	17.19
5.5.8	0.013	0.068	17.18
5.5.7	0.003	0.071	17.10
5.5.6	0.007	0.062	17.19
5.5.5	0.008	0.066	17.22
5.5.4	0.010	0.063	17.20
5.5.3	0.013	0.062	17.14
5.5.2	0.005	0.062	17.15
5.5.1	0.010	0.071	17.09
5.5.0	0.010	0.054	17.19
5.4.45	0.013	0.058	19.29
5.4.44	0.008	0.067	19.19
5.4.43	0.005	0.074	19.29
5.4.42	0.005	0.067	19.32
5.4.41	0.007	0.068	19.19
5.4.40	0.005	0.073	18.96
5.4.39	0.011	0.074	18.89
5.4.38	0.012	0.059	19.02
5.4.37	0.005	0.046	19.04
5.4.36	0.007	0.047	18.95
5.4.35	0.003	0.062	19.05
5.4.34	0.011	0.056	18.93
5.4.32	0.010	0.061	19.16
5.4.31	0.008	0.047	18.96
5.4.30	0.007	0.054	19.03
5.4.29	0.005	0.066	18.98
5.4.28	0.014	0.063	19.00
5.4.27	0.011	0.053	18.82
5.4.26	0.007	0.045	19.03
5.4.25	0.007	0.072	18.97
5.4.24	0.006	0.060	19.13
5.4.23	0.010	0.072	19.01
5.4.22	0.009	0.057	18.91
5.4.21	0.005	0.076	18.99
5.4.20	0.008	0.071	19.08
5.4.19	0.009	0.064	18.98
5.4.18	0.010	0.061	18.96
5.4.17	0.016	0.055	19.04
5.4.16	0.006	0.070	19.03
5.4.15	0.003	0.051	18.93
5.4.14	0.014	0.057	16.37
5.4.13	0.013	0.042	16.40
5.4.12	0.009	0.058	16.40
5.4.11	0.011	0.050	16.58
5.4.10	0.005	0.060	16.38
5.4.9	0.005	0.047	16.40
5.4.8	0.007	0.060	16.30
5.4.7	0.006	0.059	16.32
5.4.6	0.005	0.052	16.35
5.4.5	0.011	0.046	16.42
5.4.4	0.003	0.058	16.41
5.4.3	0.005	0.059	16.41
5.4.2	0.010	0.056	16.28
5.4.1	0.011	0.059	16.39
5.4.0	0.008	0.066	15.82
5.3.29	0.003	0.065	14.65
5.3.28	0.012	0.065	14.66
5.3.27	0.009	0.072	14.60
5.3.26	0.005	0.057	14.68
5.3.25	0.009	0.065	14.51
5.3.24	0.010	0.058	14.67
5.3.23	0.007	0.044	14.58
5.3.22	0.012	0.057	14.49
5.3.21	0.005	0.066	14.54
5.3.20	0.007	0.068	14.57
5.3.19	0.007	0.052	14.65
5.3.18	0.005	0.059	14.50
5.3.17	0.010	0.045	14.54
5.3.16	0.008	0.059	14.41
5.3.15	0.007	0.046	14.56
5.3.14	0.003	0.070	14.69
5.3.13	0.012	0.067	14.54
5.3.12	0.013	0.058	14.62
5.3.11	0.010	0.064	14.54
5.3.10	0.015	0.044	14.09
5.3.9	0.002	0.056	13.94
5.3.8	0.011	0.054	14.09
5.3.7	0.007	0.061	14.05
5.3.6	0.006	0.063	14.03
5.3.5	0.007	0.060	14.03
5.3.4	0.008	0.071	14.04
5.3.3	0.005	0.051	13.95
5.3.2	0.008	0.059	13.59
5.3.1	0.003	0.050	13.57
5.3.0	0.003	0.051	13.62
5.2.17	0.005	0.046	11.16
5.2.16	0.010	0.038	11.25
5.2.15	0.008	0.056	11.11
5.2.14	0.005	0.040	11.14
5.2.13	0.008	0.035	11.25
5.2.12	0.005	0.034	11.17
5.2.11	0.006	0.038	11.15
5.2.10	0.005	0.039	11.20
5.2.9	0.009	0.030	11.17
5.2.8	0.002	0.037	11.07
5.2.7	0.002	0.038	11.15
5.2.6	0.003	0.034	11.14
5.2.5	0.005	0.033	11.15
5.2.4	0.005	0.033	11.07
5.2.3	0.002	0.037	11.08
5.2.2	0.006	0.038	11.02
5.2.1	0.004	0.043	10.95
5.2.0	0.010	0.029	10.82
5.1.6	0.003	0.029	10.07
5.1.5	0.002	0.030	10.11
5.1.4	0.007	0.026	10.13
5.1.3	0.005	0.030	10.53
5.1.2	0.003	0.032	10.34
5.1.1	0.003	0.029	10.11
5.1.0	0.006	0.032	10.18
5.0.5	0.005	0.022	8.91
5.0.4	0.005	0.022	8.89
5.0.3	0.002	0.036	8.71
5.0.2	0.007	0.020	8.77
5.0.1	0.002	0.023	8.65
5.0.0	0.007	0.031	8.61
4.4.9	0.001	0.019	8.11
4.4.8	0.010	0.012	8.11
4.4.7	0.003	0.021	8.11
4.4.6	0.005	0.019	8.11
4.4.5	0.008	0.013	8.11
4.4.4	0.000	0.030	8.11
4.4.3	0.002	0.018	8.11
4.4.2	0.004	0.017	8.11
4.4.1	0.003	0.020	8.11
4.4.0	0.002	0.028	8.11
4.3.11	0.006	0.015	8.11
4.3.10	0.003	0.019	8.11
4.3.9	0.000	0.020	8.11
4.3.8	0.002	0.028	8.11
4.3.7	0.004	0.014	8.11
4.3.6	0.003	0.017	8.11
4.3.5	0.003	0.017	8.11
4.3.4	0.002	0.029	8.11
4.3.3	0.002	0.022	8.11
4.3.2	0.003	0.018	8.11
4.3.1	0.002	0.019	8.11
4.3.0	0.002	0.020	8.11