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

true1

22,1,8,1length20,2 5Takes a text string as input, and reports a new text string containing all but the first character of the input.

pt:_ sem o primeiro caractere ca:_ sense la primera lletra es:todos menos la primera letra de _ All but first of empty word.letterTakes a text string as input, divides it into words treating one or more spaces as a word separator (only spaces count; punctuation is part of the word) and reports a text string containing all but the first word, with one space between words and no spaces at the beginning or end. (Note: consider using SENTENCE➞LIST and processing the resulting list instead of doing recursion on sentences in text string form. List operations are faster.)

pt:_ sem a primeira palavra ca:_ sense la primera paraula es:todas menos la primera palabra de _ All but first of empty sentence.Takes a text string as input, and reports a new text string containing all but the last letter of the input.

pt:_ sem o último caractere ca:_ sense la darrera lletra es:todos menos la última letra de _ reversereverseAll but first of empty word.letterTakes a text string as input, divides it into words treating one or more spaces as a word separator (only spaces count; punctuation is part of the word) and reports a text string containing all but the last word, with one space between words and no spaces at the beginning or end. (Note: consider using SENTENCE->LIST and processing the resulting list instead of doing recursion on sentences in text string form. List operations are faster.)

pt:_ sem a última palavra ca:_ sense la darrera paraula es:todos menos la última palabra de _ reversereverseAll but last of empty sentence.Takes a text string as input, divides it into words treating one or more spaces as a word separator (only spaces count; punctuation is part of the word) and reports a text string containing only the first word, with no spaces before or after it.

pt:a primeira palavra de _ ca:primera paraula de _ es:primera palabra de _ Takes a text string as input, and reports the last character in the string.

pt:o último caractere de _ ca:primera lletra de _ es:última letra de _ length0lengthTakes a text string as input, divides it into words treating one or more spaces as a word separator (only spaces count; punctuation is part of the word) and reports a text string containing only the last word of the input, with no spaces before or after it.

pt:a última palavra de _ ca:darrera paraula de _ es:última palabra de _ lastLast of empty sentence.Takes a text string as input, and reports TRUE if the string has no characters in it of any kind, otherwise false.

pt:a palavra _ está vazia ca:paraula buida? _ es:¿palabra vacía? _ length0Takes a text string as input, and reports TRUE if the input contains no characters other than spaces (therefore, no words when the string is considered as a sentence), otherwise FALSE.

pt:a frase _ está vazia ca:frase buida? _ es:¿oración vacía? _ Like JOIN, takes any number of words (text strings) and reports a sentence with its inputs concatenated, but inserts a blank space between the inputs. Consider using SENTENCE (Lists palette) instead.

de:füge Wörter zusammen _ ca:uneix les paraules _ es:unir las palabras _ fr:fusionne les mots _ pt:uma frase com as palavras _ firstbffirst1list11bf Takes a sentence in list form and reports the sentence as a text string.

de:Liste $arrowRight Satz _ ca:llista $arrowRight frase _ es:lista $arrowRight frase _ fr:liste $arrowRight phrase _ pt:uma frase com as palavras em _ Takes a sentence in text string form and reports the sentence as a list of its words.

de:Satz $arrowRight Liste _ ca:frase $arrowRight llista _ es:frase $arrowRight lista _ fr:phrase $arrowRight liste _ pt:uma lista com as palavras da frase _ report a list in which each item is one letter from the input word

de:Wort $arrowRight Liste _ ca:paraula $arrowRight llista _ es:palabra $arrowRight lista _ fr:mot $arrowRight liste _ pt:uma lista com os caracteres da palavra _ letterjoin all the items of the input list into a single word, and report it

de:Liste $arrowRight Wort _ ca:llista $arrowRight paraula _ es:lista $arrowRight palabra _ fr:liste $arrowRight mot _ pt:uma palavra com os caracteres em _ listlistSENTENCE is the main constructor for sentences, represented as lists of words. It takes zero or more inputs, each of which can be either a list or a text string. If a list, the input is assumed to be a list of words. If a text string, it is converted to a list of words using SENTENCE→LIST. Then all the lists of words are appended to form a new list of words. If the inputs are lists of lists rather than lists of words, SENTENCE, like APPEND, does only one level of flattening, reporting a list of all the items of all the input lists.

ca:frase _ es:oración _

pt:lança o erro _ Takes a (possibly deep) list as input, and reports a human-readable text form of the list (namely, Lisp notation).

ca:notació textual de _ es:imprimible _ ( )Helper function for word/sentence library. Reports its first input, unless that input is empty, in which case it gives its second input as an error message.

es:requerir no vacío _ _ Takes a text string as input, and reports the first character in the string.

pt:a primeira palavra de _ ca:primera lletra de _ es:primera letra de _ 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UoQIFSFCj3v3BknYZkVENyOnG0LhAM98J49KJuTAi/ggaMO+Arb6gdPtIZuBrQPpAGnhYQLTr0uVGo92P/wzlKcQHnvU8l+RtRkp3KOz0bpAAFykvA8itoq+FU0yasw1lwE5bVKuHrFKAABSgwUcB2ACYpBShAAQpQgAK5C9gOwLYexDG8HuqbuVdDyhymcsyKofjSj+G1XZ9vzH34uZ9xZvD14VpRf58k1UdzP5tnUIACBRPgXxoKRsuGCyOQVQA2qyH5/Qi4XBjJTEOy9SjKwfVIvPV4ztWQMincc1bsiJ/3Ubw++PlZhSE6uNUzpr/evac/vXxuYM7AAGK9mTucfahtnZh6NA1oroEybQzqyAgwMBV95DUoUNECDLQVPb3VNDjLAGymIU2rwU+GxtAhAwvDvXjIRKrGAPzAvz76ua9dc927TojWENRNpkUD0DQx9WhfAHZNT0E6sh/xDdW0uDhWClCAAhQ4vECuaUg+WcbcUAjjQacaA7Ceqr/oSLevOQXsGIT6rsnrh/uoQ6Ue+eC+EIhvjQKjXIwUoAAFKEABQyDrNCRJx6O6wN8IHc+HQnvLEe7Nba3GAPyNa7598/0/v2emUemoBrHtY/AsiyC21g/PqWbqkQ/uJSpcL9dgtwq4loaRWM8lV1kC/Ca0suaTo6FA3gUs3iQsv4K26lC1b8JqhDLLgbS3H8ntGVayH+6lNYh3dgGqlSFfpwAFKFBNAtX84TVz7LYDcDUtGo6VAhSgAAUokC8B2wH4U9dWTzWkQ6F/54ZpQzNmuDcokvJOviaF7VCAAhSgQOULZBWAzTSktjZ4HA7oXV0Hvlb91LXdmyFVbzWkb99Q3zUjKP/lkVLdVmO59AJjxm7oYWCw8pcPR0gBClCAApMVsAzAmWlIw2O4WqSxORzGK+YFyzIAG0+xthx5dqRGAA60pK7pUGa0CUiv60iNSXAsiSB2e3Yt8CgKUIACFKhGgZzSkAIBzDOQyj4A53GmjQC87p6f3vWDr337cUCuj0J9wQ/lk5F9RRhK9qeaN0GU7KSwY6UhwF+O0piHKuhF1mlIRjUk2YnLBRALhfAz8wlQZXkHnMeJNQLwS7965JavXHXtuxKkJg3pPwqIqwDcEUGcfxfOo3XZNjXlb+hTfsGynRp2nALFFLD9RSw3YZXnJiy+RRfz147XpgAFKJC3v4SSkgIUoAAFKDC1AuV+I2H7DtjWgzi2rIW6NfdqSJ7LrkvJbg9G773Zket0K0suH3Z95lyMdH2xIddzsznef1I06ULNLZIk7X1SGH8OIVDuvzWcVApQgAJ5EMgqAJtpSMZ/k0mo0eiBZxrbehRl5zoktq3PuRqSZ+X1quRSMHbPzUquBu7zVnY7rzoXo++ubs/13GyO954YVn/8w5+2/ujvbqrpx1hf5jl+1AZc2DPSA8Qy/t3tRU3zhGNFEEpbEnIiij2hbK5b3scwIpf3/LH3FKDAZAQsA7CZhqQlcK8sY54uMDvSh1/k5VnQmQE4h/fgUg/AFy08d9Frf3i1UYPW34/4m/snxu2Fu0OGWBhGbLyalFHAARCtmce2AZ44PCsA0VkdAXgyS5fnUIACFChvgazTkHSB/5XTOEOToLlk3G3WBOYd8MELwLgDju4cbF7YPvs8IN7ZD+w2jzDqBetIz+3PKGFovOaFe/mEYx0BuC/WIJQoYg8DMDKX+UMBClCAAhUkkHUakp7GOlnGmbpAPNyLNWYaUnkFYB3u8y4v+FfQx/uP/tJw/1BDCumnZDh3CaTnJ6G+7IByy5/KFT4fRWytD55L9/1XuUKC5M881gN1awzKGRqk5ihij1TQeuNQKJC9QA7fimXfKI+kQOkIWH4FbdVVbsI6WGjiJqwAXPM1SPEo4m+ZRxpfMSfgXhxB/Fnzg4zx2qGOtfLn6xSgAAUoUJ4CtgNwKQ27cj4wV85ISml9sC8UoAAFSknAdgDuuU1ZpWtah51BeRatVn91cjv+ffj2nHc127nu+527rOby0Wubb3zLLdWuL9Q12C4FKEABClSvgGUADgTgV91IDr+LwdZW+NJpxA5KQ7rVvVmScLYdQs+i1cPPnDQTd478qCC5uZPp27Kay0N/2fDNp2fKga+lsCc2CAxnttMINA4Bw41Agwu17gj2hCdzHZ5DAQpQgALVKWAZgBsb0eiuwcVpCb8TSXghozXSh3Xjm7AqPAC3ynVfdUNZFoH6gDnmRigdboE/D2vqD5qBGgH3WQKO3zEIV+cvEUdNAQpQYDIClgG4OYh2Zxrnp9PYKMs4GTIC4V7cPZ4HXOEBeJbccvOfdi4vjkK91xyzAe2Fa2U/Eo/UAw0eKBcLqE+HgOhkJoHnUIACFKBA9QlYBuDWVpyi6zhekrABwLkAoqEQNplU3RUcgD837YZnjnC0/osOfW4U6v0+uJeocL3sQaIRAl8RmnY3II3pkBcI6Nv6oO6oviVUDiPmprZymCX2kQIHBCrkd9ZiGJYB2GpJVNEmLNkP99IaxDu7ANXKha9TgAIUoAAF3k/AdgAmLwUKKVAhn4MLScS2KUCBMhWwHYDtPIjjxvlJ/Grs1bpysHNKjvRvpn8dHrn+78uhv+wjBShQGAF+KCyMazW2ahmAJ6YhxeNIDA4eSMmx8yjKG+cl8Wv19ZyrIRVjohySnPiP6d+AIuqmHaJ6EYynWzkAvQuIt8AT3IVYBECyGH3lNSlAAQpQoPQFLAPweBpSAptkN07WNTRF+nCfWSCg2gLwTNEyb2L1otmAexjuqwX0zRKEF8D/6dBPCCP+eOkvAfaQAhSgQPkIVNI3EJYB2ExDisfxmNuDawD0h/vw82oNwIqoM8oKTqxeZDzH+fj9S1jXIJoloD0C9f7yWdbsKQUoQAEKTKWAZQA205B0HZ26wFlCgiPch7vyUQ+4HL+Cbhfeqw9VvWgM7i/qQCwN8bgTOBNIvxZG4pWpnMyCX6uSPnoWHIsXoAAFKPD+ApYB2AqwmjdhsXqR1erg6xSgAAUocDgB2wGYtBSgAAUoQAEK5C5gOwBfelvPKgHdVjWk3Ltd3DPu+XJTzCNq/0GSpFhxe8KrU4ACFKBAuQpYBmAzDalJIKaqaE3ISA3sxE5zE9bHbu/eDEi2qiGVG97df9Uw9PzGjfOvvORKMYDYTi9qWh3QXAJqpBcYK7fxsL8UsC3A/QG2CdlA8QSKtXwtA7CZhpRU8YTLhWYA54RCuMesDFStAfjxhx8+4a8uv0aRIbWlIN6UkD5Bg961C4k/Fm8Z8coUoAAFKFAuApYB2ExD8njwQCIBv6YhEArht+YAqzUAb39x27yPL17xgTQc3f0Y+08/XJdGkHjM/GagXBYA+0kBClCAAsURsAzAZhqSpmGNEFgWDuPRzLJ81RqAv7X6K2ff+7N7Z2qQhmRog2noziiS/1WcaeRVKUABClCg3AQsA7DVgLgJy0qIr1OAAhSgAAXeK2A7ABOVAhSgAAUoQIHcBWwHYDsP4ohvWQt167qcqyF5LrsuJR9Ti9EXb3bkPuQDZ8jeuSPTlv8Cg3edMc1OO8a5LV/43+G0p+H+eqneKMLAHwpUhECxdodWBB4HQQELAcsAnFkNCYAjEEBzOIzxIGOnGEO8cx0S29bnXA3Js/J6VTrGg7Ft31XszLCj5Zid9cvvxODdZ8yw087eAHztO90ju3HJ3MDRuwYQ6wUkDdD3NtsANAlAG8SBKlIdgDICj89IYzJ3lBvH+lDbmsKeWOaxdvvG8ylAgQIK8FNKAXEru2nLAGymISVieNKp4Dw9hRejUYRMFgbgfRJGAL7/nvVX/+3nv7LDCdEagrppv5HUDNdcJ+QTwog9DCBt/HsQqEnCPcNIY8o4dm+wdkNZFoH6QGZgruxlyNFRgAIUqD4BywBspiFpTmwRaVwEYCxfxRgq7Q44JTdcfKTb15QCdgxCfddcTgGgFnAtDSOxPmOJuQJwXbQ/jen35r/74T5Kh7Q4CvXezN3m1bc0OWIKUIAClS1gGYDNNKR0Gk8LJ841OCJ9+GU+qiFVWgD++ldv/u69/3pXu6RJG2sQ2z4Gz7IIYuv9wv19XZNe06E+KsH9QRWul51IeZzQTjTSmGqh/m7/sWv98JyqQ58b3VfKMF7Zy4+jowAFSlaAX63vm5oCOlgGYKvFwU1Y+7+CnrAJqxHKLAfS3n4kt2cYyn64l9Yg3tkFqOa/H+ZYK/rSf72AC7f0B88eUoACFHh/AdsBuODAfBMvODEvQAEKUIACUy9gOwD3bK9dpRegGpLi/9ye4Yaj8M7wjbWTYTH2H+cyuHPa3lVdqP+xJEnjd6aTuS7PoQAFKEABCmQjYBmjMtKQhoNBtCWTSBy0C/r3tZslIO/VkBTfZyPDjbPxzvA3c05TymbgE49ZHHx3+Jf/cv9xf3vNV5wpqLv6gd37j5GnQ2kz/r8Pao+5i3ky1+A5FCgHAX7pVA6zxD5aCpTBQrYMwGYaUnwMT7nduEDT0FmpAfjPTr/oiu3/8XKvjuQ7EwNwCjjHCfVhlhu0XPY8gAIUoMABgTIIhMWaLssAPJ6GZBRjcGKJpkGJhmDks+59ykR3Bd0BX3fV6jPX3L3mOAnojiD2kjkpRhqRBvfiKOIbizVRvC4FKEABClSWgGUANtOQJAkbdB3HaxKaoyE8YjJUUgD+4if/cvGGBx/rEJB73Rh7dX9q0KMBuJcnEN/Cp1NV1uLnaChAAQoUU8AyAFt1rlQ3YVn1e+LrEzdhVWxqUK4wPJ4CFKAABQoiYDsAF6RXbJQCFKAABShQ4QK2A7CdB3HcMP9V/GqsM+dqSFM5J5+oWT76jeYvveWWajMfIzmVXeC1KEABClCgAgUsA/CEakhyQwOmDQ9j0LSwU4zh6/NewbPqlilJM5rs3H2ibkXo6w1f3OiX6q6bWNHIaLMRaBwChr2ome6A5hJQI9wpPVltnkcBClCgegQsA7CZhhTuxSOBAM7SBaZH+nBfNQXgr9Vf+/QM2XvrxIpGjVA63AJ/HtbUH3hR45eQPkGD3rULiT9WzxLiSClAAQqUt0CxMqUsA3BmNSRHGq1pwBfpw9rxNKQLnZN6EEf9DXdGyukOeKZUt/oQFY3ghWtlPxLGrvC0H65LI0g8ZtqU95Jk7ylAAQpMpUCxwuBUjvHga1kGYDMNSdPwguREADpOjfThpwASRlPV8BX0de6rnz26dnp4YkUjDxKNEPiK0LS7AWksDd0ZRfK/ijedvDIFKEABCpSLgGUAthpIFW7COmRFIysnvk4BClCgEALVd99YCMXitGk7ABen27xq4QX4a114Y16BAhSoZgHbAbjnNmWVrmkddhA9i1arr5w8A5uGf6jYacfuuXOU84Y+2vRPAx5Hwz122+L5FKAABShAgfcTsAzAGWlIQ0Y1JCHQ39ODmNlo963uzZJkrxqSZ9Hq4VdOmoFNIz9sKOZ0Ha0s6fpY87+8PUu0flLFaHIYB9KtjH41AQ2D+6okaQ1A08TXi9l3XpsCFKAABcpLwDIAm2lIHhceSyZRm9JxQbgXD1RyAG4VdR93w3NxGDFjd/PezWZe1ASF0K52aeotcTiPkeBYEkHs9vKabvaWAhSgAAVKRcAyAJtpSB4PHtizB8fKMuaEQlhTyQE4KHyflqGfXwv1gS5ANcfqg+fjbsSe6AFifiifjEC9v1Qmkv2gAAUoQIHyErAMwGYakizjcU3DfF0gGO7Fg+N5wBX4FXSH8N+QhnY8oK4BlIVpSF0SoAmBv9M1/TEgPSIgrgJwRwTxd8prytlbClCg3AW4RbLcZ3Bf/y0DsNUwK3wTlhSAsiQN9eX+fX/75c+UCvBtZkq5eTEKUGBKBWwH4CntLS9GAQpQgAJlL8CP1vm6A77QuUqHnnMaUsPX7h6Nb1kLdeu6nKsheS67LiW7PRi992ZHritRWXL5sGvh2Ri57fM577iWZ580PO3aH2Hwq0tyP9ddn2h5rAduufZ7ufa5rI7nb1ZZTRc7SwEKFE/A8g44sxqS34+Ay4WRg9KQbDwLOt65Dolt63MdEik6AAAgAElEQVSuhuRZeb0quRSM3XNzznnD7vNWdjtPPBujt13Tniu7Y87Cd+uu/RGGvnzezFzPhVI75n2sR1dEXYsXNc39GOvLbMOP2oALe0aMDV4Z/+62e2zO/czTCYzDeYJkMxSgQMUKWAZgMw0pncAGuBCUgYXhXjxkith5FnTOAXj/u3o5B+CZomUBIFo1aP39iL+539HthbtDhlgYRmzc1g/3UTaPrdiFy4FRgAIUKHcBywA8IQ2pUZYxNxTCpqIE4P0XnZIAfIhbuL13wF/4EYa+ZOsOuM4L93Ig3pm5scuH2lYd6bn9UMdtjeHaPbbcFyj7TwEKUKBSBSwDsJmGlErhGdmFbwgdz4dCe8sRpgyUKb0DnsoAfIgZz8dX0O3C+wUJkj+F9FMynLsE0vOTUF92QLlFh/R8FLG1Pngu3fdf5YrJHDuAxGuVumA5LgpQgAKFFJjKP59ZBmCrgdqphlQpm7D0LPK55ENswgrANV+DFI8i/pbp3AZ4EnAvjiD+rPHIS/PfcznWas74OgUoQAEKTFYgfyHadgCe7BB4HgUoQAEKUKCaBWwH4Auf7FmlabmnIZUDeqNbxO46r0Gvket+WA79rew+5u9TZ2U7cXQUoEC5CFgG4Mw0pLY2eBwO6F1dB56P/KEnuzdLkM4ulwHn0s8GpzR4z9KGdKuoO9qFWncEe8IAnD7AHQVGc2mLx1KAAhSgAAUyBSwDsJmGlFTxhKzgSpHG5nAYr5iNVEMADoq6owTcZwHy7yWkzhSQ1DDiT3ApVbcA78mLNP+ELxI8L5tvAcsAnJmGFIvhaKMD1RaAfaLuWA+UiwXUp/cAmgL3B6KIb8z3ZLA9ClCAAhSoHgHLAGymIUkSNmjAlQKIhUL4mblDtxrugDtE8zk6xAIAL+nAGZLAcR5NvSmzVGH1LJlsRspblGyUeAwFKFDdApYB2IqHm7CshPh61Qjwc0fVTDUHSoF8CNgOwPnoBNugAAUoQAEKVJuA7QBs60Ecw+uhvpl7NaTMSVKOWTHkOvNSjHR9trEQk+c9sVdVxO6fSFJ7ZpGEQlyKbVKAAu8rwK8YuEAqS8AyAGemIQWD8CaTUKPRAyk4th5FObgeibcez7kaUuYUuOes2OH64Eewu+tzswoxNb4T+4befeftOacefaZ7ALHezKdTGc9vTmFPbBAYNq8dBGo0KP4U1F2Zz3ouRN/YJgUoQAEKlK+AZQA205CEjm2ahtm6wOxIH36Rl2dBl0kA/purv3j2fT9/KOmEaA1lFEtoAJrcUJZFoD5gBmY/PGfoSI3pSL7DAFy+vxjF6Xkl3eFV0liKsxp41coXsAzAZhqSJO3N/T1Fk6C5ZNxt1gSuhjtgVdKPmi0FjksBOwahvmsuC6Nc4J8KKCyOQr3X/EDSAs8MAZwpAd0RxF6q/CXEEVKAAhSgwGQELAOwmYaUkPFrt4ZzdYF4uBdrzDu+agjAHz7roiu3v7T9A5ImbaxBbPsYPMsiiK31w3OqDn1uFOr9PriXqHC9XI9kbRr6iQJybx/GfjeZSan2c3jvVO0rgOOfUgH+wk0pd+bFLAOwVc+qbRNWI5RZDqS9/Uhuz7CR/XAvrUG8k7nBViuGr1OAAhSggCFgOwCTkQIUoAAFKECB3AVsB+AlPT2roJdCNaRsqvJmD/R4sGlPTMT+2Sf5dmd/Fo+kAAUoQAEKZCdgGYCbmtCg1UMMv4vB1lb40mnEMtOQzu3u3ixJlVcN6fFgY3Sot++kE9pOgJF+NBtwDqGmuR9jfdnR8qjsBfhHqOyteCQFKFApApYBuCWIYx1pLEjL+C+RQgtktEb6sM7chFXJAfiWG25e9k8/uH3USD9KQ2oBUu9okNRdSLxRKQuA46AABShAgeIIWAZgzIbbvwfLnAKdqRROh4xAuBd3m2k3lRyAJUla0CG1zDbSj1zA0Tp0ByB2RxB7sTjTxataCfBe2kqIr1OAAqUiYBWARWsQ39aBHUkJz7jSOANANBTCJnMAlRyAP3PJJ77w/MbnFhjpR8Z4JaA9jdiTfMBGqSxf9oMCFKBA+QpYBWDLkZXOJizLruZ0ADdh5cTFgylAAQpQIEcB2wE4x+vxcApQgAIUoAAF8pEHbOtBHFvWQt2aezUkz2XXpQY+2oD/G/mho9CzKAmhndW6Ax65/qZCX4vtU4ACFKBA9QhY3gFPTEOKx5EYHDxQ/cfWoyg71yGxbX3O1ZA8K69Xd11aj66RHyqFnipJEumzpr8LRdTVeg+RhuRHbcCFPSM9wHi5QqNKkoy0wopIhZ4dtk8BClCgfAUsA/B4GlIaW2Q3TtI1NEX6cB8A48kXqJYAPFO0HAOIVg1afz/ib+6fcrcX7g4ZYmEYsYfMZWAEYCB9tIy0GkLyt+W7PNhzClCAAhQolIBlADbTkFwyNibT+DKA/nAffl5tAVgRdQ4v3MuBeGfmLmgj2OpIz+3PKFNoTJYfro9EkHgcQHoyk8d0msmo8RwKUIAC5SNgFYDH05AkDS+lgQ8ICY5wH+7KSz3gMvoKul14PyNB8qeQfkqGc5dAen4S6ssOKLf8qSTh81HE1vrgudT473QowRTQHoW6tXyWAntKAQpQgAJTKWAVgC37Uo2bsAJwzdcgxaOIv2UCtQGeBNyLI4g/az4lzBKPB1CAAhSgQBkIFOY7SdsBOCu5wvQ9q0tXx0EEro555igpQIFKErAdgHtuU1bpmtZhB8WzaLUqan3Y03mjrV3Njob20YbLnsCuf1tQZ6c/xrktV78xBGfDwzU13p122+L5FKAABShQiQL2bn4sA7CZhtQkEFNVtCZkpAZ2wghK+3ZB3+reLEk42w6tZ9HqYanGi7EXvtVgpx1R3xZp+MQTGPz5iTmnNk28bvPVr+2I7sYnT5sxv6cPak/mZqoA6vwqRpPDwGDGea7pUKZPPNbOeHguBShAAQpUroBlADbTkBIJPO12ownAOaEQ7jH/zlnJATjUH//UoiMXdQloC/oRf8JcBo1Aoxuei8OIPQIgYfx7B6CMwOObeGzlLh2OrLQE7H0SL62xsDcUqA4BywBspiEZJQiDQbRpGgKhEMZzWys5AMf0upXHNsxqBKTRzB3NzfC0y9DPr4X6QBeg7l8qsg/u8yceWx3LiKOkAAUoQIFcBawC8HgakgysT6dxXjiMR80UpEr/CnrT5v/+4qoVl6cEpFQY6iYfPB+LIvbLVtSckoZ2PKCuAZSFaUhdDoiEjtTC/cf+OteJ4PEUoAAFKFBdAlYB2FKjWjZheVEzXUDviCD2UgaKFICyJA31ZZYotFwqPIACFKAABTIDSL40+BeofEmyHQpQgAIUqAYB+3fAFzpX6dBzTkNq+Nrdo7fP34ytY8/YThnK10Rd03Rj/CL3ZZtrnNMy73Lz1TzboQAFKEABCowLWAbgzGpIAByBAJrDYUTMFuwUY7hjXie2qc/YThnK13x+vuGbu5fVXf6tmVLggYkVjoxrNABNRurRYdKQ8tUNtkMBClCAAlUgYBmAzTSkeBzPuDxYoqfwYjSKUKUG4LPTl3zv2MZZa99b4ch5ogTHkghitx8qDakK1gqHSAEKUIACeRSwDMBmGpIMbNeADwMYy1cxhlK9A26XAg8eusKR8skI1PsPk4aUx2lhUxSgQFYCpbD5pBT6kBUWDyo1AasAPJ6GhDSe1wXOMAYQ6cMv81ENqRQD8EkDi28/ddaCwMQKR144TxAQV/3pm+g7BORmMw0pCoyW2qSyPxSgAAUoUPoCVgHYcgR2qiGV+iYsVjiynH4eQAEKUIACkxSwHYAneV2eRgEKUIACFKhqAdsBuGd77aTSkKzUFf/n9siuI7Cn54Zaq2NzfV2SPSnfgnd1t1T73VzP5fEUoAAFKECBfAhYBuCMNKRh41nQySQSB+2C/n3tZgn2qiEdaiCK77MRh/sIjPZ8Pe9pSpJQ1JYTdqBV1E1XoDQqUEMZz3QWQShtSciJKPaM7/bOBzbboAAFpkiAG6OmCLpMLlOi68EyAJtpSG43fhWP40Oahs5KCcCzhP8yDek3ahHvMQOw8XffODwrANHJAFwmv1zZdrNEfwmz7f6hjqvAIdnh4LkUKCsBywBspiF5m/DEriFcqGlQoiE8PF4PuIzvgGeI5pMckE9MQ9vej/j/7J85RwDuizUIJYrY+DjLalbZWQpQgAIUKHkBqwA8noaUlPCMM4U5moTmaAhGHdy9P93lHYAXCsjHC+jbNchjAun5HqhbY1DO0CA1R/fV++UPBShAgakV4FcbU+tdpKtZBWDLblXKJqwAXPM1SPEo4m9ZDrrsD+Bvd9lPIQdAAQqUvYDtAFz2AhwABShAAQpQoAgCtgOwnQdxxLeshbp1Xc7VkDyXXZeS3R6M3nuzI1czZcnlw66Lz8bIxmsbcj33oOOF0L1fjsIj13/HVjs8mQIUoAAFshaopO/vLAPwhGpIckMDpg0PY9DUslMNKd65Dolt63NOM/KsvF6VXArG7rlZyXrW9h/oPm9lt/OiczD69LXtuZ578PGS5v1qPxRRV+NFTXM/xvoyX/ejNnCIikruQxwrNcPTVoNYfw8Qs9cnnk0BClCAAuUiYBmAzTSk+nqs270bH9QFpkf6cB8D8L4APFO0zAFEqwatvx/xN80474W7Y2JFJT/cRx3iWDEDaErBc0EYsQfKZeGwnxSgAAUoYE/AMgBnVkMCMDMN+CJ9WDuehnShc1IP4qi/4c5IhdwBy164lwPxzn5gtzkdPtS2Hqqi0qGPdZ4ISHOiSKyxN508mwIUoAAFykXAKgCPpyFJGn6jCTRCx6mRPvwUQMIYZLV/Bd0uvJ+WIPlTSD8lw7nLSGVKQn3ZAeWWiRWVfFCumHiskfY0CuU0GVIwjNiD5gebcllA7CcFykWgkv52WC7mFd3PPCwoqwBs6cdNWAc2YR0qlelwFZWqK+3JchnxAApQgAJVJ2A7AFedGAdMAQpQgAIUyIOA7QB8Us/aVULXOvLQl6I08XjgnKEGp7KmVqrtLUoHeFEKUIACFKhKAcsAnJGGNGRUQxIC/T09B9JlFnU/thmSdHa56q1vXbyjLqFfdkRNe+8AYn3NQK1ATe3EtKJyHR/7TQEKUIACpSlgGYDNNCSnE4/rOmpSOi4I92I8XaYSAvB/Prn5C1d9+Ir/kYE5KcRfkKAsBPTeKOJvl+a0sVcUoAAFKFDuApYB2ExDivRhnc+HE2QZc0IhjKfLVEIA9snKx4JSIwCxW0O8T8CzPAV92xDUHeU+wew/BShQAgJ52DFbAqNgF/IsYBWAD6qG5Epjti4QDPdiPF2mEgLwQ7f88023fPOmuZImbUxD75GgL9CAV3ch8UaevdkcBShAgfcVYKyungViFYAtJbgJy5KIB1CgjAT49l9Gk8Wu5lOgCEvfdgDO5/jZFgUokH+BIryv5H8QbJECFShgOwDbeRDHk/N/jTfGNuZcDSmf83B6/TXxc2uv+73irHsmn+2yLQpQgAIUoMD7CVgG4MxqSH4/Ai4XRjLTkN77KEodgGWzMJ4F/eS85/Cm+nTO1ZDyOaWn1f3l7nMbrv+3mVLgh4eoXoQGoGkYe6s/yUaK0gAwks/rsy0KUIACFKhOActIaaYhJZPYKBRMl4GF4V48ZHLZeRZ0qQTgU6Rr7jm2YeY/Tqxe5IPzRAmOJRHEbvfBfZGAaKqoikX8brI6f+s5agpQoEgCB7/pWgbgCWlIflnG3FAImyopABt3wO1S4NZDVS/yQ/lkBOr9xjOd4/AsjyL2cJFmjpelAAUoQIEKErAKwONpSEhjky7w10LH86HQ3nKEKcOhEu6A54/9xUMnB+elJ1Yv8sJ5goC4CsAdEvT5mpCX6lrshsyygxW0FjiUwwjwiwIuDQpQoBACVgHY8pqVtgnrcNWLLCH2H8A362yleBwFKECB6hawHYBLgq/aol5Rx1vUi5fEcmMnKEABCuRDwHYA7rlNWaVr9qoheRatVgdPDuB/h7+n5GNQVm2c07Yz5ULN9yVJSlsdy9cpQAEKUKDEBCZ1HzCpkwo6cMsAnJmG1NYGj8MBvasLqtmr7lvdmyUJtqoheRatHh44KYD/G/luQ0FHu7/xxcGexFUfvnzGsxuec2ZWPeoAFBVKawJSagCxnQCMnCr+UIACFKAABfIuYBmAzTSkRAJPOzz4C5HG5nAYr1RCAP71hmfnZVY9MgNwGjgnCvUeAFrexdkgBShAAQpQIKsnZsyG278Hy4xqSIEAjjPUKiEA/9WHL5/x2IZff2hi1aMmKDMF0oFdSP523wNFeBPM3xQKUIACFMi/gNUd8EHVkBxprBRALBTCz8y7w3L9CvqDR59y8o533plrVD0ScA4KpOeHof7aB88noog9aqZZHSBnMM7/8mOLFKAABapJINcHcVjYVMImrABc8zVI8Sjib1XCUuBHhUqYRY6BAhSodAGrO+BKHz/HR4G8C/ADUN5J2SAFKlLAdgC28yCO+Ja1ULeuy7kakuey61LyhfUY7fueI9+zIlwz9rTM+8+0Itfdnu+22R4FKECBfAjwQ14+FIvfhmUAzkxDCgbhTSahRqMYNbtu51GU8c51SGxbn3M1JM/K61XpglqM9X0/73nDsmtGpGne7xOzRd2cBGqnRbAnnDlNXtRM78fYAIC4+e/TgOYaKNNCUI3UpWTxp5U9oEDlCzAIVf4cV/oILQOwmYYkSfgPXcdRusDsSB9+kY9nQZdyAG4XLUsAHKVD/oOZKxwAajW4g4BYGEVsjbk4/HB9VEBsZwCu9F8Xjo8CFKBA/gQsA7BZDQkC74g0ztQkaC4Zd5s1gSv1DlgRdbP8cK2oQeLpLhx48EgAyhE6pNYIYi+Z07CvbKF8fArSpgHEevI3PVXQEm9jqmCSOUQKUOBQAlYBeDwNSRN4QU7hDF0gHu6Fcfe39yEVlRqA20XLLQCEBDxpjFOC8OoQXYD2TQnpZ8NIbPDCc1k/YmsCcB2XhnwcIHVmPlmLS44CewX4IYMLgQIUOISAVQC2RKuGTVhe1CzSoIcHEOs2QZqBaU4op4ShPmeJxAMoQAEKmAL8QMa1sF/AdgCmJAUoQAEK5EuA0TlfkuXQju0APK/nr1dB1zvKYbDHOFuHfxm4Ju6Sav+pHPpbrX3kW1C1zjzHTYFDC1Tqe0I2AVhubkbtwABGWlvhS6cRy0xDmtf917arIU3VopvjDPQ86Pv8iCLqjmsEGoeAoSagQQPEMDA4Vf3gdSpUYEreJabkIhU6QRwWBUpLwDIAt7biIl2gSdLwoqYhCBmtRmEGcxNWOQbgWaLp0xrEKUD8Lh3uc4wpkRHfFAb2lNb0sDcUoAAFKFCpApYB2KgBnEphecyFXytxnAkZgXAv7jbzgMsxABt3wH4ofx6BuiYA94UapCYV6hO7gV2VOtEcFwUoQAEKlJaAZQAOBPFhaFgqATcBOBdANBTCJnMY5RiAZwrf1YD+yRSk7zuhLTTGEkb8Cdb/La3Fyd5QgAIUqGQBywBsNXhuwrIS4uvVIMC/zFbDLGc7Rq6GbKWq/bjDBmAuoWpfGhw/BShAAQoUUsD2HbCtB3EMr4f6Zu7VkDJBlGNWDLnmXIqRDasa7UJ5v7orpYjf/UCSzk3ZbYvnU4ACFKAABd5PIJsAfFAaUjyOxOAghs1GbT2KcnA9Em89nnM1pMwBuees2OGa82fY/cSnZ9mdau9Xd8X/9aYf+W/69g9rJzxSUmqGp60Gsf4eIGZex3galkDNxGPtdoPnU4ACFKBAFQhYBmAzDckh4ZkUcLquoSnSh/sA6IZPpQXg848/66Q3X/tjkwatvx/xN/evATEDaErBc0EYsQfMdeEF6iUoCwG9N4r421WwXjhEClCAAhTIk4BlADbTkBQFG2JxfAVAf7gPP6/UANy3I9p4yhHHLgXinf3AbtPZqHgESHOiSIyXIdx3B+xZnoK+bQjqjjzNCZuhAAUoQIGSFcjfDinLAGymIekafqwLnCUkOMJ9uCsv9YCL/BX0REbjK+jjW478q+HB3Q0ppJ+S4dwlkJ7vgbp1FMppMqRgGLEHffB8PIrYWi/cR0jQF2jAq7uQeKNQ6yV/012oHpZ+uzQs/TliDylQbQKWAdgKpJI3YQXgmq9BikcRf8t0aAM8CbgXRxB/lnnDVquDr09eoFgfGYp13clL8UwKlKuA7QCcy8D5q52LFo+lAAUoQIFSEShE/LIdgI/tOWOVpqOkqyF9adpn0p+e9vHNHmnallKZTPaDAhSgAAWqWyCbALw3DWnaNCRUFa0JGamBndhpbsI6pvv0zZCks0uZ8csNn02sqvnYd46Wp93hAPQhQFGgNAKOPSGMRku57+wbBShAAQpUpoBlADbTkDwuPGYEYADnhEK4x/z7Z7kE4I+lLvrBvKaOfgF9cxyJbgfcfmMDVRSJhytzajkqClCAAhQoZQHLAGymIYVCeDgYxExNQyAUwm/NQZVLADbugDtk7waj32EkXvFCOccF9dVeoL+UJ4h9owAFKECByhSwDMBmGlI6hRtkGReHw3jUTEEySMolAF+auPCW41uOGNGBWC3iv9gDz/IoYo9U5rRyVBSgAAUoUOoClgHYagDchGUlxNeLKlCIrYtFHRAvTgEKVIqA7QBcKRAcBwUKIcD4XwhVtkmByhCwHYBtPYhjy1qoW3OvhuS57LqU7PZg9N6bHblOg7Lk8mHXwrMxctvnG3I9V5590nDzPz4XU6Rp/7z/Udi5NsHjKUABClCAAnsFsgnA49WQADgCATSHw4iYfraKMXSuQ2Lb+pyrIXlWXq9KLgVj99ys5DqP7vNWdjtPPBujt13Tnuu5jjkL32388fODs0Xd6QnUTotgTzizDS9qpvdjbABA3Pz3JqBBA8QwMJhxrGiGJziAWB+AdK794PHZCfDuMzsnHmUKcMVwLUytgGUAzkxDGovjYj2FF6NRhKo5ALeLlo8DOEqH/AezbGEAqNXgDgJiYRSx8YINLXAd64C8oB6xdW/vD8wB1Pk1JBtkYE4I8Sendsp5NQpQgAIUKAUBywBspiElBH7j1PERAGN5K8ZQpnfAiqg7yQ/Xihoknu4CVHMiA1CO0CG1RhB7KWNy3X64lkWQWJf57GgvnIsAsTuj5GEprAf2gQIUoAAFpkjAMgBnpCF9XzhxrtGvSB9+mZdqSGUagNtFi1GOUUjA3rtXCcKrQ3QB2jclpJ8NI7HBC89l/Yg94hfKjbqGHU6o65NQ5qYhdTmQboKQPiVp0sYw1OenaK55GQpQgAIUKCEBywBs1dfq3IRV/8+mixc1izTo4QHEus1/M+oEO6GcEob6XIafFICyJA315cw6w1a+fJ0CFKAABSpTwHYArkwWjooCFKBAlQhw71nRJtp2AO65TVmla5qtakieRatVMdeHPTtvynlXs5Wcw9kcaz7+j7pbqvuh1bEl9zp/MUpuStghClSEAN9bbExj/vCyCcBmGtJoMIi2ZBKJg3ZB3+reLEmwVQ3Js2j1sHSsD2O9N+Wcm2ulKMnNQ97j30gHRN1sF2rdE1KH5OlQ2nQ4xlgVyUqSr1OAAhSgQD4FLAOwmYbkFFibTGKFpqGzHAPwdFF3pID7LAHH78wgXA+01MD1QQmuFxmA87ms2BYFKEABClgJWAbgjGpIawNBXKxpUKIhGCX8dKPx7jK5A/aKumM8UC4WUJ8OAXtrAHcAyhhcF0mAFkZivRUWX6dA5Qvk7+u1yrc6/AipWM2zn/3YLQOwmYYkATfpOo7XJDRHQxivIlQuAXiWaD5bh7xAQN+Whu4wUoc0xF6T4D5DA1z9iD+RPRuPpAAFKECBQgpUw4cYywBsBVyOm7AOlTpkNU6+TgEKUIACFMingO0AnM/OsC0KUIACFKBAtQjYDsB2HsTxzvyNiIw9UVdo7DrXnJGT/c8lFKn+p4W+FtsvL4Fq+JqrvGaEvaVA9QhkE4AzqyHJDQ2YNjx8oLKPnWpI78zbiH71yZyrIeU6PTXOY3Yu8j03OlvULZxYxSgI1GhQ/CmIRD/GenNtm8dTgAJVKMBPblU46fkfsmUANtOQwr14IBDAebrA9Egf7jO7Uk4BuF20XDKxipERgNNQAhqwOAr17vwTs0UKUIACFKDAewUsA7CZhiQEfqPr6EgDvkgf1o6nIV3o3Cwh9wdx1N9wZ2Sq74AVUTfvUFWMmuGaZ9AMIPE6FwkFKEABClBgKgQsA7CZhqQ58BNJQwA6To30wfhbasLoYJndARv9PqiKURixlwPwfCK8r4avNlXoe5Oo+UMBmwL8JtQmIE+nQBEFLAOwVd/KdRMWU5GsZpavU4ACFKBAIQVsB+BCdo5tU4ACFKAABSpVwHYAPr+nfZWuS7aqIeUT98e+NUOz3Sc+pUjK/+SzXbZFAQpQgALFEKjcP7RkE4DNNKTdRjUkIdDf04OYOQ3nd7dvhiTZqoaUzym93ffLHUe7Tlg9Xap9YRDY3QzUCdTU9mOsL5/XYVsUoAAFKEABOwKWATgjDemhGTPQlNJxgZGSVMoBeOA3e7738XOXB12aeosKOCQoCwG9N4r423aweC4FKEABCkyNQOXe9x7wswzAGdWQHvb5cKIsY04oBGPH8N6fvN0B50nbvANul7yKG7EnxgCngGd5Cvq2Iag7pmbpTLxKngZXnM7zqhSgAAUoUAABywCcWQ0JwHG6QDDciwfNPOC8BeA8Dc4IwJGtwz9Yef5HjtM1/TFA3ylBX6ABr+5C4o08XYbNZC3ADx9ZU/FACpSgAH+DCzcplgHY6tI5b8IyEmBtX/XwveImLKsZ4+sUoAAFKFAKAgUMhaUwPPaBAhSgAAXyI8B74fw4HmjFdgC28yCO+Ja1ULeuy7kakuey61LyMbUYffFmhx0Q2Tt3pHnVSwlFqmGVJDuQPJcCFKAABXIWyCYAj1dD8vsRcLkwkpmGZOdRlPHOdUhsW59zNSTPyutV6RgPxqNqTjwAAA/XSURBVLZ9V8l5xBknOFqO2dl45bY9s0X9iROrJBmHeVEzvR9jAwDi5mmNQKMLte4I9oTtXJvnFkKAn9ALoco2KVBeAuXzPmAZgM00pPoaPDo0hg4ZWBjuxUPmhFRCAG4X3uUTqyQFgFoN7iAgFkb3PSd6708zME3AfZaA43cMwuX1a8neUoACFCiuwMEfDiwD8IQ0pFZZxtxQCJsqKQAron7uoaokBaAcoUNqjSD2kjneeqDFA+ViAfXpEBAt7mTy6hQ4tED53ANwBilQvQKWAdhMQ0ol8QPZhW8IHc+HQnvLEaYMtgq5A/7HiVWSdIguQPumhPSzYSQ2eOG5rB+xNa1wzdUhLxDQt/UVLa+4AAuW79gFQGWTFKBAtQpk85ZqGYCt8CptE9ahqiQZXzs7oZwShvqclQdfpwAFKECBUhfIJjwWfgy2A3Dhu8grUIACFKAABSpPwHYA/nZP6ypNR1GrIV3S9KOxea5LNtW6Gn77/lNUGp96Km8ZcUQUoAAFKLBXIIcwk00AHk9DMjZkORzQu7qgmtQ3dk/fLEkoajWk5Y23DBxf+9FvtEu190b3pQwljXShIWDYfGQmlwYFKEABClCglAQsA3BmGtLwGK4WaWwOh/FKqQVg/+BptyxqP0FOQ7pPgy67Bf48rKk/MDeLZYWewyeXrNorxYOqYYyl6M4+UYAC4wJ8G9pHYRmAM9OQAgEcb5xUigF43x1wy2tpSP83gFi3F66V/Ug8klMA5i8IBShQXAG+MxfXn1efUgHLAJxZDUkDrhRALBTCzwBoRk9L5Sto7+Bpt3yg/YR6CXgT0F+CwFeEpt0dQtLi78JT6s2LUYACFKAABbK7A7ZyKq9NWFaj4esUoAAFqlGAXz2Ysz6VEpZ3wNW4FDlmClCAAhQolMBUhrhCjSE/7doOwLYexNG+Aerg4zlXQ7Iaurtx6WD9rPuGPY5pd1kdW/qvc7GW/hyxh/sEuFa5EiiQi0A2AXg8DSkYhDeZhBqNYtS8iK1HUc54AonhDTlXQ7IaoHPakq6GIx/smi7q/kwDxDAwaJ7TASgqlFYV6tAQMGTVFl+nAAUoMCkBfh6ZFFs1nWQZgM00pHQCm2QZ83SB2ZE+/CIvz4IucACeIZqvcUBeUI/Yurf3lxQMwHW8DrkugdgbDMDVtNQ5VgpQgAKlJWAZgM00JF3HHyUJZ2kSNJeMu82awKV8B6yIugv9cC2LILHO3LUdBLxJuM6VIaIhqJtLazom2xt+1J6sHM+jAAUoUCwBywBspiHJArdqGs7VBeLhXhj1cfemIZVqAK6fdf+ODrf/BV3DDifU9Ukoc9OQumSIJJA6CZB2R6FuKRY8r0sBClSfAD8qV9+cv9+ILQOwFVeZbMKSAlCWpKG+3A/sthoTXy9fAb7Ble/clW7PuapKd27Ku2e2A3B5D7+Ce8/3jAqeXA6NAhSoBAHbAbjnNmWVrmm2qiF5Fq1WRa0PezpvVOygOhraR5s+94e0ItXdYacdnksBClCAAhQotEBOAbi1Fb50GrGD0pBudduuhuRZtHpYqvFi7IVvNdgZsKhvizR/7r/jraL2BBdq3RHsCWe0J4JQ2nqhGv9mVEziDwUoQAEKUKBoAlkH4NZWdGgagpDRGunD+K7i7hIMwEFRO1/AfZaA43cZQVgOAk0JeM7vR+zBoonzwhSgAAUoUNoCU/QnvKwDcMNMNClxnAkZgXAv7h7PAy7BAOwTtQs9UC4WUJ8OAVFzpgNwngqIQBjxx0t79tk7ClCAAhSodIGsA3BHBxRVxQoA0VAIm0yYUrwD7hBNF+mQFwjo29LQHRKEF4i9Ciin65AaIog9WukTy/FRoOACU3SXUPBx8AIUKJJA1gH4cP0r9U1YXtQs0qCHjRrBRTLmZSlAAQpQgALvEbAdgGlKAQpQgAIUoEDuArYDsK0HcWxZC3XrupyrIXkuuy4luz0YvfdmR65DVpZcPlz71X/aWeOoN57mxR8KUIACFKBAUQRyCsBGGlI8jsTgIIbN3tp6FGXnOiS2rc+5GpJn5fWq5FIwds/NOecNu89b2V1/3T+9HBD1nxOANogDYwEgN8MzfQCxXvNRm8Y4G4CmQxxblAk73EX557iSmg52hgKlLcA3jJKYn6wD8IwZaEkBp+samiJ9uA+AboygHANw7Zf/32/bnN5vOiGfEEbsYQBpYyzN8LRJSNc7IVpDUM2NZlIzXHMnHlus2ePvTbHked2pE+AqnzprXqmYAlkHYGMXdCyOrwDoD/fh5+UcgI074Fmi/krAtTSMxPrMCfBBOSsF7BiE+q757wGg9lDHFnPieG0KUIACFChvgawDcCAAvybhYiHBEe7DXXmpB1ykr6DdX/jJ9tl109/WNek1HeqjEtwfVOF6WUFyLgQulDRpYw1i28fgWRZBbL1fuL9vHstiDuW94Nl7ClCAAqUikHUAPlyHK2ATluyHe2kN4p1dgGqOsxHKLAfS3n4kt5fKZLEfFKAABShQOQK2A3ApUfAvR6U0G+wLBShAAQq8n4DtAPyrnsZVug5b1ZCymSJ/zSVDxzb8LOJx1D2QzfHVfAw/iFTz7HPsFKBAvgQK/V6adQDe/yjK1oSM1MBO7DQ3Yf2qu3EzJJydrwEfrh2vZ/mOY6b9v9eOdgau0QARgmr0IVno67J9ClCAAhQolEChQ1yh+p2fdnMOwADOCYVwj5knW4wAnALOikN9ahgYzA8DW6EABShAAQrkLmDnI0TWAdjoVjCImZqGQCiE35rdnMoAPK/pn19VRN2lAbgvZEWj3BcKz6AABShAgdIRyCkABwL4RDgMo5JQqlgBeJbw3qFBfi2KPaHSYWRPKEABCuRfwM7dVf57wxbzLZBTAD7UxbkJK99TwvYoQAEKUKAaBGwH4GpA4hgpkL0A71myt+KRFKhuAdsB2NaDOIbXQ30z92pImVOmHLNiaNold0XcUvmnJ5XyW3cp961kfoWJVDJTwY5QoBwEcg3AjkAAzeEwIubgbBVjGFyPxFuP51wNKRPWPWfFjvrld742Xd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