{"id":64,"date":"2026-10-18T05:01:12","date_gmt":"2026-10-18T05:01:12","guid":{"rendered":"https:\/\/risksacademy.com\/risk-science\/departments\/decision-behaviour-communication\/"},"modified":"2026-10-18T05:01:12","modified_gmt":"2026-10-18T05:01:12","slug":"decision-behaviour-communication","status":"publish","type":"page","link":"https:\/\/risksacademy.com\/risk-science\/departments\/decision-behaviour-communication\/","title":{"rendered":"Department of Decision, Behaviour and Communication"},"content":{"rendered":"\n<!-- Risk Academy page \u00b7 https:\/\/risksacademy.com\/risk-science\/departments\/decision-behaviour-communication\/ \u00b7 generated by integrations\/wordpress\/academy\/build.mjs, never edit this file --><script type=\"text\/x-nexus\" class=\"_iub_cs_skip\" id=\"nxe-ast-engine\" 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f\/U7braBTvyk0x7RJQ94LVHBMeFRdszHd2D83tFHcGOSLvPSDN8lloZ1w\/RH2xPjAmNMB9KjAmNsZ4wTyqk8KkFO26cut+eGBUabS3PmeztawTbs5ymkRhGH3stk7p2gt38L9ju9jpT\/aYNm9sL9HN5bjC\/fhrBDksm1yXuKihQ2AtS+X\/ArbuZX+QYvlstMM2Z6XKb\/Ys3xBNwBdxWv\/n1kVTD5GsCcYfLk9+Pk+J153VGmFmf5cbN8m2mydV055lWhIgzG6DN9kVzqgeSTRwdHBUTFhfWPfcmQ7q+ivzs6MYiOtzpHP5iSX1c1gvpG4Qh13t\/PVaveXJOK4ukAB4HnO7EfgW3mRaOyfsv2OF3DTCaugz3dWpzoHVeHSdvINXICmTkk+TdtMp05DUgF4zm66SV2N0YC7gLFusv4OUKGJmFmsyz\/VlhYWHpfQPZhSSRaI8JjbSH2CPtfTLtSU3s3jSrM9sZbG8RcFqvXfN6nx1mH3pIWFRIWEzHsPCEyIiEyHgzwnQ123ud6Y6EGLP1LNNZkGpk9ksx12jh+sjQyMgoc8EBM5HLuynYWkKcWbwwO7MjY+Mj8vrao+LCzZQj4AyYAc\/hM8yKl5HquOFDOueZaF5rTv5YorN\/YqbLkRAbGhdm5gKGWe+Ki4y93iSe7Tezgpj02NRb9h9hD7FHm\/t\/vM3jpgAapqRkZ3rdrjvIIDwmJCwuJCLKkkFMQmREaFxsYRlE3CyDfoVkEB4XG3tDCLERkYWEEGXm9WarfXhsfF5zf3RsnNmI\/u8LITI2MtiR5Uw3fA3dZtXBZGE+nSeX2JjIW+QSGxne+xa5xBTIpUmeYrTzGSl\/IZTwsJDIsI5hMQlRYQnhcaExNwkl5q+FEhYfE35DKHExEeGFVcOSSURURFzezw9iIyPCw\/8rMok339b+pUziI6IsmHdLtLzuRdIMo7Dm\/CsO+WbXkmy6NsMXkmpVAsxOa+OpbCMPkGX7zGwiIxDI8ifUqXPD6YRm+9P9oenevoXG\/HXMJdXpGx4aVsefnWmmJnWiQqN7mhOHphve3n6rfpNpBDK85kE3a9LReqllZUl3YH2Ln8k0Ak7Ty4Zej6Nmo7fX7U6yMiarlFPwk5+Ct+6pRn4recCe6fUH7F4LQtkzXZ7sgPmTDJc7Lw77Ayb8c\/ntfV1+V7LbqGvvYAR8OSEN0wKGz57h9XizfWbc9noMe1q2L5Bh+Oz5UjIDpcXCmWnYO3Vobe+XYeTFJKuD3PCZqMTvN\/zWWJorEDB8Nf325OxAwBJHXkP6jdpKHkrKD2QdXZlGw5RAttN9Hbf8j6GlglKpFZ9uY1n3jiydPuMfsg0163cpfTzefm4jteCnHHnRwe1KMQ+r2V9htOt6f72kf0P3\/xlk+M\/re6oRcLrcdQa6UnP\/XVXPMMxEJ9Xbz2Mimzrm2ntmZrpC83m5TA3vdnPUvCmEFPKb3W+2nCwT+PsCLsMfmg8q\/aEFou0W1j00O8sElB3z4vgNo7GMJcvw2S2AYV2ZzspuvfD5FxX3Fkv9e7r8vw53FzKJdjfmy\/O0fzVl3vrySgiWfVhzF3Dy581b6Dc8wbfajN1r3ri9fr89zZWe7TPM2GcutKF5VJk5\/5JN3Si5W7cj1MtqspqnXlVT1SK1QK1Xm9VedUwNVwdUWdyHhuiCifgBLWg1\/UQxVJI2ojvqoz62IRezURllMAfDqTt34bHUjJ6k12k9racO1I\/60mt0HkWoFo3HAhzFY5RFjWkJLaUXqCu1pcZUnR6g8vQb3sMUeLEVh\/EZvsAbiKRYCiYfDaQP6AVqSPHUkFpTVzpDH\/N+mauv6Azbbr1PN7al2Y7qifppvUFf0E1sO22LbO\/ZWgU1COpqU7ZTer4ubzuqf9T79RV9SLOtkm2\/DrENsn2lG+rV4pEwKSpXmSVahshCKSsn2CYNxCtTpJ9AxvBQvpePUQOuxt3oLXTBA7ikzqqSaII1qE9tqT7NpvlUiUtwFD\/JT\/FA7sOH6SydoBFEtBav4xxq0++YiwkqRw1So9RwNV29pl5W76spyqeGqzfUr6oUiqARpuJn2CiHvqJfqQMNRS6CURoPojSaozRKoz1q0kXqySw1+VV6hZaQ4qUUSxfxEDWmmnQez+M1eLARLWkMLaE6dBjF6SLOoRZFUCiZMtX0NoYgF8PxKWrSbyhHL5OXn+P1NIArcmmeRB\/QPTyfVtG9\/DMPkNJ6jX5Or9RdbffZAvoP8eu7bRm2922dbM1sYUGf2HrYytnusk3TmXqHnqtH6zf1ZJ2qo\/UjOqD9uoluoD8Qp4RKlBSXP7iGDJDycpXvlyYyUj6R98QuuzmFL9NndI5q8RwqQh6EoQiqoQYcSMcqNCU\/TaGi3JNb8wjexZP4EU7gBL5GSbSJNlAbOoCFeA1z8RreQB+kq+lqhJqgximPqqsylVu9olaoD9R6dV59re7Fo\/gB4dSKXqFVNJkc1ANNcZ8l3waojoeQi1l4g5rzbzSTS\/D9\/BPdxefJxr9QC4qiXViBDdiF6YjFQVSlBtSMKtI27McOHMFpbMEGHEAx+hDpGIvJeBftqBb9ggeoPZ2gOfwYr6R0bsRhHMl9eQmH8hn6gdK4oihdSV+VhvpJfVBCdR+9V9eytbZp24u28bazerf+SK\/RE3Rvnai76Va6pr4k5+WSPKqvaugXxCdtpa5UlFKi5Bz\/ymf4BFeQ7jJcekuCtJZzPIzrcRBrnk8\/ojdCEIRwjMFAPI0JOILWdIR+Jy9P4VxewsmcwmmcxsW4F02jKhRNXWkg\/YJlWI49cFB52oOVaq1arGaqUaqBylZ+NUTNVW+q3eo9tUJ9o0ogA9PwEHWkETSLkug8xqC2JeUemIo+eB7303A6TuP4IteURlyRH2PwLNpMg2kkRVNN6kjXMBqd0Bxv4iQGkJ+KURQdxcf4AtuQhufRBdOxAyWoCz1FRL+iGJWgXvQ91eA43sAX6ST9RF15Lh\/iQTJQislFTpBRPJbf4gelp6yW81JNp+gNOsj2g96vG9qO6\/G6jX5Md9FNdT0drKvr0vqaXJILQrqsbY3+UB6XBlJHSktRucbn+Qz\/xKf4HHeWKTJBsqWcbOSm\/AiHcRDfSwNREVVQF5k4imu4ivI0iHZQNx7Cq7iIpHIEK7bxNbqPq\/Br9Ag9TFexAVVpO45hFj5DDLWjUvQl3lcL1Eb1qkpXk9V76mW1Tx1QO9RudVwdUcURghHYgghqTH5KpSpUlHYjHKUxHDl4H99jFmrQL9SUH5Cx8oYE8yCy83nqQPPocdqLb\/\/0tSG0AWvxCF7GSZSkKuSgCPodxWg5duJ5dMYMrMBq3E\/lqCl1o6pUjnpRNl2lSM7gH7itDOevqQePYpbh0klv01skXHt1kK6hw3UP\/Yt8K1ekvp6uz+oxeoUuaRuhm+siuqiuoivraB2t7bqk1vqa\/C5VdWlbRdsZGSStpJaUlWJy1ZLyKf6Rf+RiEizl5Dzv4AXs4cHcmJfTLsSiAtpjEg5gJH1CG+kYHSfNz\/AznMgVOZy\/pd1UhpvwLGpNuyiYtmAL3sBiLMBczMQsBNNoSqcKdA1dVJZKV9VVGVVZrVIb1BA1Sm1Vd+GSKgFGCHpjBKZgB37FMGpKv+F7OFAaQwFajPfRiVpRdV7NI2S7vMF7yUGr6AHuTp\/gKGLoEmZhNt5FNophCg4jG6XpQTqNmfgeW9EQSUjCJEzAVnyL46hOxekhGk01eCz3423cQk5wmrzB1yiXP+WBEqZ36sO6o+15W3tba1sJ21YdobfLctktNu3ST+oJuoZtqq6plT4vF+SKkC6pS+sSuphm\/axOtFWzPaPL6sd0kn5Y75J75Spf5F\/4JJ+wPn9wVakrX\/MansKn6WkqR8+hIjpiCd7GOXSiPfQt3cdtuSX34O6cyFWZ+TCtoJLsJz\/lUg\/6AsuwDIuxxJLybMzDbkyi3hROFUkoVD2o6qlBqrlKVU1UjGqkFqpFarYilEA1NEQiUtENK7AbVegatiAYHpTHGJSju6gifU576DP6jXvKO8z8BNWjJ6kEL6ZU+hnZOAYvnsdFtEMxrMJauLEe76MveuI59MSX+A7j0AFH8I7lq6tRBHWgavwRF5EeslZCpKNEyxjWPIxP8hGZo+NtS2xpNmXbqqfpejpSz5VnZK0ckjK6g47VW\/Uw\/bD26V16oZ6gX9KJuqJmzdqhp+k021lbb1uibZ9uYWtjG6znSGsxpXyKj\/Mx\/oF\/YZJz\/D0HmLkH7cNYPIB6mIa3sA4f4TS60UjaTt9QGS7DJbk0H6A9FMRvU3l+nnrQLqpLH+N1vI4leAOvYR7mYwMUVaI2VI8eoDNYgVbqmPpWrVZ91XfqI+VUs9Rzqq8aozapw+qgsqMowtAFz2II3scmNEFJlMT7WI4ZeJRWUjmezMEcx5qP0EuURCm0Cj3pE+pKf2A5OqMn+uNF9EExpCEYc\/AYIlEMBvYg6E\/sUoTO4lUk4yPsxn30KD1BL5GDv+PZ8qlslor6AznLHbguz+XHpKGuaWtoq2s7orfqvvp7OSE9xC5D5XXZL\/dopRP0S3qjjrctsHWx\/ajX6SRdXNt1B71Bt7QdtVUPmmbLtW23UdA1m7b9LuOlvlzgU3yCT7FNSslP\/CWv51E8gfZhAGrgObyJg1YE+RgXEEMraQldJB+X5e00h8bQCJpIn9I31JniqAntwpdYg7dxHm9gNhZiPX6Hj54hG23BJmzFu5iCY2qK+l2F4V6MVUWQpe7CKfW5Oq5+UjvVQVUDoaiHomiICZiMFNhRB+NxD32KA2hBmyiat\/BILs5b\/rT3BXSaHmOmlShNNakCrUQWEnE3it30aQInmuAFHEUc5VIQ\/YZvsA6jsBfNyKDttJC7yBUJ0tX0LvmOe7GLn+JveYWs0Q5bmO2YPqnP6RnaoVvJHF7CteUlWS7zpauubdtle9WWbDugF+gndIjeKqQX6HjbQludIEfQXNubNgmqHfR40DjbLH2\/XiJPSLiESIw0k4eEZR1H87fUjt5ELh5BFKZgOTZjG75FL\/LRNAriX+ke\/oR20tv0B93DE6kv1afydArf4QCuoAodxlc4iCP4GXNRnHJpPB3HYrRGbYyEC\/vVb+oTFYqxppdUL6oP1Sr1trKhMuJRH6tUaZRDGJqgLR6HH06cUZfVD6hI95KQn9ZTHP\/O73A3vkAfUXkezuPYSVswGptQhtwoni\/b5zENj6I2MjEVyzATR7EOAbyFstSI9uIjvIgZ2I+utIke5yIyV4ZJSf2QjpShbPACPsz1pZbeqYvaftVz9VW9XD+jRZeW4vwMX+aHZIi00d1t\/Wy\/6j16h35Gt9W75Rl5WO\/XyTanbaqtZtDntpW2L222oLpBU2zTdVv9qyyU3tJb+ktr+ZHHcgQz76AX6Uu0xMN4CM0wBltRjeKpE7WmLuSld+k01ea7+G6+l+P4An1Kzel3\/IBD2I\/PUYtGkEGlqCa1plJUFMOg6GF6DtkYj9\/U50rBreaqSPjwBRagEX5WVXFAtUVr1EGXP63+kHoQxfGglROanwo4pA6p46oRpmMBHqQF1JcdfIUPcwJX4Qd5On\/Pr1EVWowk7MR0FENVvAs\/5mIpVmEIvLiKndiMb\/EtVmMfTqMYrcdXWIHx2IvB1Jr38rf8LV\/hDjJIeslrvJKPcHHZIcP1ML1Cf6db6hV6hA7Sj4qfL9N0Ps6hslnW6rK23bqsLqXv0l9LJ\/HJCTkl5XWOrm5rYvvVlh40NKhc0GTbJzpDV9In5Bl5QiLkHikqO3gG53AL9tA3GIJQPIyH8SwWQxOoLNUiG9WgDNpMe+kwraP+NI8a8738Hj1JNvoJx3AQ+9GS6lEXmkCPUAmahjhUQXW8hyxk4QFofKhGqWw1VkWrTaoEemElZqAuDqkOuA8tkAo\/MnEPiuBBRCMGD6Om5VuBbaoCZqMXBuIK6pFB5yied7LB9fheNmgpDSShreiFMpbHKIkG6IGFWIRPUZSWYheqUntaQp3IRU2pIoWQieJL0VEcRwLtoxm8lMfwMj7JzWSibOVDvIdbS6KupDP1KT1WK91SB+nWMol\/IBu\/xeVltITrTbqtXiFpUly+5G85SAKyTmza0Gt0A9uztlm287YJtrtsnfU2eU06SQ05x6nilkgR2cGruAXvoZ\/RAsEIRghiMBQvoD9m40OUphb0OHmpPz1HE+kXWkptKIqq0F10Db\/hBI7iDF6kAfQAxVIKJZODdmMovlZ2xOMbFY0KuKCeVn1UquqgPlIdcByj8DrewwAQWloeIxzNYCANKaiJ9qiHIiiOtuiCXrimpmE9ytFLqEENaQyV52+oJv9Oj7Cf36T21JxGwo\/u+R4jFK9gIcpTHLWidvQg9aY3qSq34zSuyDW5NJ+mFTSGVtEomkoZtJtcPIl\/4D\/4O9ZSTFbwNP6WF4gZ0UbohfpRPV8uiEvWcSVeTA34Z46UIvqCrJUWcpCTeSgf5xT5RXrrFL1IB9mCbQ5bQ9tcW8A2Un8jkyRDKst2zuW3eBq\/wMt4Brv5GxpA91MaYhGCEEQjA4noiYnYg8bU3cobXqMB1JkG0POUbumEorvoLI7jKO6iRIqj+6gOdaMu1JmG0iOUjqPqkjqprqjz6pgarJ5VnVRL1UENVstVQ7yBNViAXPRFK5SEB2MwFlmYgqHIQQ46ogHaYpF6GG+rn9VY1KAo6khHQBRFC+hhHsn7aSjV4jX0DM3Oj3zF8QCaoDG8WISHKJNOUwU+SHE8g6vIQHlXPpQx8j1v5CEczS14Dj\/Nw3koCbfgqjyE+\/B43s4j+RVeysEyQ+rp53UbfVJcMlNaSk9eQt\/TCu4q1eVV6SzBksOVeQi3kt8kSJ+XHnqZrm3bpnfqIJuyPa+L6lSJl1IyjTtyF+7F6dyWK3MRXknRFEM\/4RkMQBjqIBFt8ARmYwqq0mEwjaYl1JYiqTJVoJpUjoqR0B\/4FSfwA07ifhpFp2klLaReNJ78dBBPoSzOqbfVFDVDnVPfq3Gqu0pUHVRL1UVNV6+qj1Q\/vIerWI8FiIAfHZGJeZiO4RiAqZiCjsiCwnz1mbqmRiGa3qPptJrqURg1o9V0gmpzYypJnakvvrqOKqIQgnAkIxunEU7L6BSt4++5grSWYXJQZssMcUhxGSqdJEwO81juwSeoDo9nyCkuLlWF5Cy\/zot5Md8nq6Su3izF9B+yg7\/jJF5FLhrKP\/MOPsRf8HDWfJWcfJ9sktlyUTz6JT1bT9Ir9XJdX1+UVXKEF\/AE9vFhmkuTKYtaUjU6g6+xDc+gLprjUYQjEo+iDZKRjPFYh2\/wBcZRT6pLMdSGQqgy3U8l6W4qQhdwBj\/hMurR29SHz9Ia+oAu00t0Hh\/iQWxSi9RLaooapT5S76lM1V09oZJUkgqosWqrqoVdai6u4gccwBPwYyz6YjIeR1VMghtjMQddcUh9qIajMoE+oSt0mkZSCN1PDupGw2g+VaQ2qIuyCGAL6qL9n9a3EwPRDk9hASrSIGrLE3gtX+a64pFLvJ17yFF+h7WEiV0+4dacxMN5JH\/KB7mIlJXq0kMeEUOu8Exezkc4VRZIKz1a3uG7+S2aSMk0i4bxPbKcp3CAj9B2SuSi0lnelAd1op6on9FrdY4ery\/LQnlc4iWdK\/AReoPSqBU9Rq0omGrRD0hBPKIQhUhEIBJRaIhu6Iqn8QrewT7sRylqS49TB+pMXSiFUqkpNSFNl\/A7StNyqs2juAtX50nUlqpTFZqOy6oM1qmF6mU1Vg1Wg9QLyq+eVF3U4ypTTVHrVAX48DkeQF+cxTZ40QJdkYIS+F09ifaog1kYhnTMVWXxHN7Fc3SFPqIAVaHadA71qSU5aTgVpcdRBCPQj86gH6YgAXMxEh3xLj7GkzSPHuVxfJkPcCr35808jYfxCF7JH\/IWPsbNeQyP47f5Ky4rpeVLvsoNxJDF0lPqyDu8lwfINRkqRSSdv6OF1IfaUkt6lVqzi10czgvoMxrGW7m9zJTzckW+E6d+Vb+st0q2FJWdXFG680UrPodRBSpJoCaUTJ8hCbGIRSp6oCU6IgoxeAxJeAqzsRzz8ClqUSPqTO2pA3WhptSQalEFupvuoQRy00gS3s7R\/DhXZg+1Ik2LkIp7wJipXlJj1TOqn3pWBZRT9VRPql7qGfW2Wqk6QlMDKkvncQhFaTp6IAllcF6VQntURleEoisWqFnquGqFfniA5tMOSqXy9AMuoB3VIaH9uAc\/qs\/VGjxBh7ETwzEQKViP4ViOJrSTnuYPeAt\/wR25Kw\/nsTydx\/MWXsmr+DB34znckX9im9wl5QRyjk9xUekuL8sSCZFyki0zpYg0569pBXWhetSculA8TSXiUP6NBlM2HaWRXE2GyX7ZKJNlmuyRd6SXlJNXuQnvYIMPUSeqSuH0O05gPSrSQxRJUxCHenDCjRQ0QhwS0BCZ6Gsh+VWw0d1UlJKsTxvKoB7UkR6lFlSZIiiFRtMpeoPTeBQfpRSyUVHahF5ohV44qJaphWq2WqZWq6eUS6WqnsqpstQMdUptUen4EW2oIbWlDrQD7RGBGjip9qpq+FFVRE+0xDn1qqqLHIzFQvyBnpRKmRRMlektVKIwWo3KeEtVQC2MxBYUofN4G1PxOdbiLBTVopM0hDuwi1\/ibbyTf+Iz\/Anv4Z38AU\/iybyWl\/DT\/CF\/wW2kpOzkfbyXz3CUfC7rpJo8IvXlLmnKv5GbOlIJeoCiqBNVoj1UlCfTKKpH26gaz+Q6skAmS7z0lIqynz\/g9\/lZNrgab6RsiqYaZObPhzEPlelBSqBX0AAJSEA84lEX9RCPJnDhSczFGuxDe2pIuXQvdbFQhI\/SqBN1orbkpIk0mvrQXHqIr1IsE88hH3WlL7EQc5GD4bhmIY178LMapzJVb2WooWqomqn2q4GojGGIogaUTJ3obtqDCoiGHXbsUFfVQ\/DDjWX4VU1XjbEIa7AdW1GWHqOmVI\/OIQcVyUY5+Fz9oEZjMvpiA8rRt5iB9fgWJagUraFfqS5H80f8IbOYkqwkZeQhOcpf8jbez4fYrLJHyzo+zh\/wB1xCykqwRMhCOShKl5UQeUsGSH8O5n7UiB6ka6hOIRRMu2gh9ScPJdM6qsQH2SndpL9c5nk8m9PZfDNwhIpzR86h89iLN7EeI7ADo3ASXWg\/GqK+Jed6eAQt0QLN8QQG4VWswW6UoZpU\/88MPIZq01j6jjKoAzWiwfQVBfFe2kJ7qTyDe\/MUfoInkpfG0VRqSCfxI4KoP55DY0zAXRiiAsqrctUitUqdViEYgp7wYyW6UEeqQ2VpFK6oy6ocdqmvVCRaojs2YyAexqeqHQbAQA4+wXIcRGWy0X20A3FwIQk71CX1JrbjAu6lw3gan6ASbaXTNJfq8kUuLw4pLR7pIqvlLRkvZeQ7PsuX+ASf4wYSJ\/2kh3wsMfIWVxKSXzhYessq+UyCdH2ZJd9JCcng2VSXFJ1FOSpN1SmRfNSUnqOHKJX20VD+nZPkF87kepzG9\/AWmkEB+pUSeRidwzgMQ1\/0gBOZ8OA5nEQjPIIGaIB6qItmSEY6pmG6VWHbC6IG1IE6UldqTR56n9IpiR6nqRTO31E0j+JFPIs\/4Om8iDdwNpdhG2+g43SCNtFoepta0z4k0SYQRquhaoxaqK6pGAxBEUqiLERQafoCtWkzzuEguuMzdVJtVeVxPwZjPPbAhU\/UHPWzikAyVuKUhR1PoSgVp3M4jRD0wVvqd2XDMyhKS+DBeCzEp7iPllJrPsIjZalMl0yJlsGSKouklGzmj3i75RtGykGZJcflPdkvHeUz\/om\/5tPcUAIyQ0bJOnlEYiRdLvLd3IkcdB5foyz9AKbGFEadqSU1orUUx0\/xKk7i+3k\/DSEXxVAsNaNLVIk70fvojXboYOHitmiPTngCuWiExyxJm++STWTkw0jMwDvYiQuIoGR6gVyUSWZV2UsGueg52kJbqT0f5UelvnzCZ3kjL+cgnkhjaSKtojPUmeP4BF2g\/rSKptDr+FUtUS+r7ao8ZuMampGX5lB76kap1JzOYT4aYASCUQRmdKyMTEzH63gLl9RU5cc45GIXsvArjuErCJUiG\/2IT1AW9bBYCeZiDtYgE09gCnaiDa2jRD7NafKhdNXnpJe0Fshl\/pzX8mZeyW\/zXq4rM2Wy\/CwOfUZi5R6pIuWkmtwvbWWmOOUKb+QV\/CvfIy\/x61SHfsL3+AQXcBpFqR01pWgq+ye23WVVHhZTOjWgSlSDylEVGkLfUWdStBnT8SQS0QqtLO\/QAi3RDo3RFI9Zkn4EbZCBgZjw587fwwlcQhA9SRNpEy2i7TSDRtAk+ohsfI6OUmuezheZ5DJf5ae5AZ+mD2gffU\/FuAcP5i\/5C17K8ZzA7ThALyEHjN3KgU\/xCy4jjFZTES5C32AvzqE05aA3flH3IBjr1DsKMPAtOuCEmqwOqvvxKYi+x26cxM+4gIPYh834BE\/gbfWG2qeiUA0V0RB34xl8gc70B83jByVbnpUdMlobeqdMlS5ykb\/h3fwpv8Jz2Hw3FyK15QWpLfu5sjSRYdJHXpTB4pcq8gb34DP0JL\/BL\/H31IiIvsVJfIiP8TsqUjiF0CVcwYM0kGbTOupItchOpeguKkuTaBnVpi+tWJyJ9miDNmiNVmiNlmiGZpaczX8bwolBeN7Sji\/xC6pTU+pDi+ldOktlmflTWkv76V6uxpO4D6fyJN7Cy\/lJTuBNtJHOUoD38xnuIgPkblnJc3jen0g\/mYlXUhmagXpoYFYxqAK1oKn0G2Wy+Ub2MxBdQAdMQx98q0IwX21R7bASa8CYqirjDazDZ6hIF\/E1TmM3vsH7mIJJiMJ89aYqjdp4R21RpeCFHz3xB7ZRH97Iv3O8PC\/HpYXeqBvrMvoH6SHX+Gfexa\/xWB7Fk3gK53BfHstHOVXeke9kmbSTovItd+IlvJnG0BCqxT\/RG3T3n6szV7kWxxFDlag+VaA9VmdEFk2lJhRKNakq3U01yEc9qCYdwSK8iFHohY5ob8k6T6tbo43lR9qjHQJYg3esNwwPUAQl0XM0lQ7SFQrinhzgXDbrctX4EZ7Fy\/kgf8ZpHMeJfJK201m6j0dxdRkqM6SLVJYrvIT787s8iitzOf6DhpL5Nv91\/I6+NISmUiyzLJXzuI\/mII6uYhkOYCyqY5maZWXimhZjk3KgMw7DzO6L0kmMx1fYjdP4HWfRDq+riliDcZiLVKShBr7EJazHfoyguryF75XHZbYo\/Y6228rYftMt9P36NYmWB+UDnsKDuR8H2Mdefp1D5CnpY1bZuD4X4af5LT5LvakzJdMDFEa16SQ+xT5swyocB9F9VIvOYg\/2I5x6UD2qTpWtGH43BehTmk+H4ELKn9boxGiMwtMIwImxWILZ6Iwu6Ime6IZUTMOP2IRfUYZepnX0Bj3ASdyKP+EveCG\/yN24Ec\/kn7icVJGKco9c4FIymmtzVR7GM3kjr+fS0kraSDV5WGrLQ\/ImN+Pq3IbL80VaTM2pPI2l1XSE9lIfHiANdAP9FS6DqR59gCfoPCagPJapl9UWNQ2aVuIb9bYajWsIoSpUhk5hCn6xkGgxWo3P1c9qIY5gCdIwGdsxGb0xFG8hiBZRU97BV7irHBBYvSrFbFO0X5fRe2SDDBKvvM\/LOcBPsY\/3cEkZJO\/JQzKa7+WKXJZn0SBKpTTaRo15C4GOYgfewztYjaU4BkVMdvoaa7ANReg++h2V6VesxDAsRhTVINBc+PE+VmAlXsN6rMV8fIai9AW6oxfS4UYfPIWBeAUfgCiNVtL3FMkGr+fKcoHD5XGxSSan8QxuJXskTq+TZTJTLstoyZLq8jl\/x0FygRNlvmySbTJNEqWZfMhTOJYjeSanc3neRs\/SWfqdynNZzuGA\/CiNdapuTnZ6mCKpLjWxujMSYfbIHFEbcflP\/PaK+kl9jaoUS5XpMi6jMTYgHKdVLfymXlEROIDJeA65mIG5eBn7UJwW0Id0hupza\/6FB8tpSdOT9DH9rS5lG69r69ekvyyWaHHIm7yIB\/FqLitzZKTcLSlci+\/hu\/h70tyEl1Mxns0f8GYqRT\/iU2zHBryDZfgM+7ACb+BVzMJreBOv40U8g2z4rLq626qau7Hgz2zfrBLtwOfYg4PoSO+jG3oiC9noj\/4YhjfxMcpTZ1pIX1IJ7sHr+TsuIfWkuzwhx3k5z+cHJVOeklZSRlqKXZpIZ7nCl7m83C9PSD+ZIU\/JEOllZayn+C1uxy24CS\/kmdyRHXyKsvkpbsQvcrKE64n6cf2F3EsXUJQ60lms\/RNPnMHLuAtj1PeqFbrjNzVONcAF1LKq2\/PRBNvUFLVIzVAb1UeqB4biNyxFc5TA\/SiF+biEbvQ+7aLO\/Cmv5ll8iUdLKT1Un9MHdFnbZl1Nz5F7RMtVPsun+RTXk0QJlWO8hN1MXJfr8WdUk6fy05zJw\/kueZu3UQs6gy\/wMVZhOXZjJl7GVEzGBEzCNMzBSORiCAYgG08hgCEYhiF4FlOsiLIFx\/AHqtIlfIwn0Adu9LVq+BOxCkfxM3pQV9pMn1AQV+Y1\/DOXFC0H+Ai\/z0f5A04XswvnAZnIw\/gwH+feskVOyzpZJy9LtuUx6oiWIzyLx\/FA9nMWd+UtfID381QewYM4g2dxN+mun9Hj9FHJkIoUS3G0D1txEn6cw0acUy+pF9X9KILR6jsVRPfRwxRMIbQSh9W9OAmm0\/gM23EJFzAGP6mX1GQ1Q0VgMUrQFPqVLtFgnsJneBvP4xZyl87UJWx1bO1tsJXXrcUmf3BtCZMy0lDaShk5xoO4KZ+lHbSfzlJr7s9F5SRP5Ff4Q95HjSmJLmIPPoDZgfIN1mCWJeVxGINRGI6N+AyfYTJyMBQDMRgvYAKmYTE24xAOQFFtSqLP4cUz6GPVL4ZjOjbgHqpLdclJfWgBXSYvT+KN\/DHv5M8tZL+GlVSW1rJcaspivltay3bexT+zIUtluLwki2WLzJTnpKt4JFW80klaSSOpKHfLWq4oJeRLdkgVKS\/vi1\/X0Ye0XS+UjvIDVmMCXJiKcWiL5zET92GTGqGOqlHqpFqKeCpO+7ARJelpvKg+RSg9TA0pjmLpPCZik5qoJqnJaoqaql5WvXAF6yiCB3Muz+cSUln+4GQprqvq7vo3uSIfSa54ZKSMkSHypUyTrqLkaT5LK2kjHaG7OYKv8sf8I5cQhzws6\/gIvU0Zljc29eBHvImVeNWS83hMsDpStmMZJuFpjMXTmIhZWITF2IDNuITaVI8eooZUkq7hEBZiDkZhMMZhNx6kPVhEb9B0Wko76DcK5Wd5ML\/Hh\/hHvsbH+DJXknnCeqx8xc\/KMjnD3\/BXfJFLS6g8J5X0Xjkgl2WdrJU\/ZLq8KGtkv8yTDvKY9JVhEistpJu8Lm7t1w3187qRLqaXSTdZhxcwH0MRg8FIwutYiOX4Wr2g5qsr6jFUpNp0DX6Y9a2JahBq0wOkaTVi4MSXaqKariZbcp6qXlGvqJlqq1qLXOrBM7mYKGkh7WQvR0gX6SbPS0NhOcJP8xT+iKvLKd7GvflXmkqLaR+V42acxYP5fkmXWHFKmmh5iNfTHupFNlIUTMVoH9ZhOWZjGiZhJuZhHl7Ci1iOiRiC0XgVG3ACFWk0hVA56kqPWh0W86x+vss4gWNYjxnYjtKUTF+hP+2iQ2R2xVXiOtz2z\/g1ld\/i\/XyRH5BHpYjWeptMkKflJB\/mE1xLKkgVaS8+GSXD5Cu5Xz+oSR+Q32SbHJZV0ltWyGZZKUqvkAlyRDL1x7qbvixF9GTt0jX0RXlbnsSz6Gbl+d8oD3wYhUmYp15Qf6j3cQ7VqQx9hPFYrEarMao43sQZjMZBtVXNVS+rV9UKtUHtUBvVVjVfvaxmqLmqKa5iM2XyEYZUkzPWm7iX+UP+kF\/lqTyM23N3TuIUHs4zmPlFeo2OUDP281Ir1ncXQwZLqDwu87gK\/04zqT2l0ljy00OUQC2oK5lVtyl4xer5mYOJeBZD8TwW4ws0pZ60hurwz7SSHqKpNI0m0iQaRD5qSKD9+Bgf4xJ60liqRH+gJS2m1bSXZlMNLsUenscX+QpXlh7ypmj9smyVhZIqDeURGSx2aS85MlkWyjSpqmfqJrqk7qGH6CB9QM7ITJkuc+Q7eUzfpYvp3+RhnaLj9C\/yjRySCP2wflMOyGypiSo4qvaob9RKdVnVQSvUxSz1omqKdahEZt1tA+7BKDVabVWvqyuqGfaocWqv+kYpaFxR9+MJzMMZfAMHVqh1apF6HL9gDK2jklyT4zmLR\/EMHsOreSbP5X7cj+dxV+7BNbkdb6BldJIG8Hk2ZLzsklTt0UX0cmkqH\/JYriarWHETbsvteC\/dz3dzSd5KPWgxXsZMCw+PxnA8h2FYg\/toNn1IqVyBa\/DHtI7epmsUytvoEp2k92kEvUijKJp60AAaSl7yUoL5hpuaUhc6RJepNS\/iPfwzl5Z0uUdfkRfksKyXmfKq7JdpMkXS5U3ZIofkMV1XL9WDLI\/wlO6kr8lD+rzYdAXdWr+ol+r7dAVt1\/V0bV1FbxPWx+W47JQfZaKc4ZVqkpqtFqiRapgaoZ5XS9VGNUwdVOMwDh+hGA6ocWqE2qEOqklqtJphvS\/YqE6pIkjFp7iC5kS0kS7QNDqK7iAcV+tVFNahPC2jP+gDWkvER2k\/zaei3JT782SexEncn5dSbxpNR+hJHss\/8zGZq3fq9\/Up\/aF+RNfWa+VZyZX9vIj38gF2svlG0kcNqBYdxkLMxAzMx1grDxmDGbiX9lJZLs0\/Ehh8H1fl03Qfu7kKv0Mf02H6mLbRAhpPz9IUGk\/P03MUSfdSOepCO6kiP2\/5hmrSUJ6WJ2Wo7JREfUpOyin5SC7JKzJN3pKquqaO1jG6rX5Ut9d1dA8dr7vobP2WrmArbWtqa2+7oNN1N52ju2mbfldmyEvyusyVqdY7y0ryhgxW5meIGqKGWn+fVsPUMPW8OqK+UCPVKDVWzVEvqLFqnJqnFqqxar2qhGa4po6o5mAaTkvoI3qXfqOiXJ0uYww+V2+qL9RVdQDbMQM\/oDO1pVJUlcpQZZpBZ+kKKT5GSbyfJtIFeppz5EUJ0k10qq5jO6FjbId1pq6t50otOcgTuCRr3kMvURyF0L20E+uwEosxEy9hEiZiJbbgQ\/yBFBpDz9KzVJzd\/IqFC2P5KW7DsXyAivND\/BntpeO0lQ7RAVpJo2k09aVMqkxpdC+n8ZdcQ9rIszJDekmK7JYGmrVTT9cVdSUdroN1L91X23UVPUJ315V1LR2tH9A1tV1X0269WE\/Xg\/RYPUw79eM6WD+gv5OrskkWyR7ZLjvktOyTnyVdfyq5KlcNsj65lryftaQ8TM1UM9Vm9Z6aoeojFDPUWrVV7VXF8Ri2Yimqoh+ewXu4gIE0jo5QHf6FxtPXaI9TqhauqvfVNnVJpWA5NuEYVmALgugthFAb8tAs6zcpHegd8vIg+Ul+ksF6pN6nF2tly9JXpJew9OV7GTyE2lEPS4unkeKLNJTiqDI1oAN4BSvwAYpQfapPVSiSUmg8xfIr\/DWv4Kk8jcdye67PnbkGV+RqrLkyN+Xe3IdHcGs+SqtoGk2l5ZRLV+hVPsp\/cBNZLZ+JIcvldflOInWy9uhVeotO1I20R3+u69vuth3V63Q\/3UzH6Tq6trbrCrq0vluX10E6SrfR0CflspyRj2STfCzbZb8ck13yqbTTH2iXXiG5\/x9TXxlm1bU0vbureu09JMgQNLi7B7cAQYMESHAJ7u4a3N3dCSS4u7u7u0OQ4C4fc+797vM++zkzZ37Mj6np092ru6qWdJOu0u2\/SEfgPFiGyDAZL+NltsyRGTJfNsk1+VdEz0kUHaKzdZAu1+RIgSOqGINM\/JUTOJ3L8En\/0lQ6QTNqUo2ju+WUPJW4OkE97NUZ+rtu106I2PMJMiAm67KSPbNIroEb6da6kW6lUzfDDrMVSzM+N2IJuqMrOqEXJuAf\/MXJjMMOod3RBV0YYnJe02yohNKog+G4jIQcxB+5m+t5gJ3Ym525lptp9o4JLa6ltNrWw9rbHf7BLNyDHZiBZojO8mzC\/XSW0fp87S+a2VvL4Iq6OW6t6+02uWMutV\/Lz+MX98W\/5Lq7Ru5XV8TlcTlcJpfL5XVN3Sw32pVx2V1Gl8D57pU9tON2yU7YQdtr262de+96ObrvrKt0lS7\/RbpHKH\/0lQEyUAbLcBkvM2W+\/C1vZIfslWNyRV5JFo2YRR\/SJNiAUSG2zFYc5DemVoGTkQbrdIsmw06dqD\/rC3kmZ+SdrNPftYdGQ1RExwuNjp\/QEcvY1A7ZY6vtBro+rp57a\/Mtmc1nHSancR8CfsIlHIbyH7zHO6Skx5koha7YrvN0ux7Ta\/pGI5hBHqIiKVrhDIzjeYBTOYSjuYC7ufrr+Xk+1SJbE7tgh+wf62PveIotmJTHsAL5MQlPkJ11OJcbKZbVCtti+9H1cOX9zn4Mf7vb46a7sS6LH+YvdgNdI\/ebK+rKuIquvKvlmrsF7rjb5qq6X1xFV8blc8ndN+6zPbfHdtPO21G7YkPdY1fEdbSOjED5Pzh3k4gc0kv6yUAZFMJ5k7yTpbJWNsk22SX75Z0U0Vq6UbdrOJrhDtqxKb+gIMK5ma3tPY8wPqeHNGjDsFtbae8QC1f1mjTV8riJxFS+Qi7W5WjmZgYbZKfsib2wzVbK3nEbB\/F3NuVyDmAJpmN+luMNtEBpzEbzECvIIT3W6CJdpIf1kt7XAAXQED8gF8oiD1rjIA7iPGawM4dxMBdzJFcxszW3BbbYptlwW2udLIVtYQI+xN\/4A5XQB3OxDqSyGAfxH95kP4vsrrscfmR\/hTvhovgpfPXPu\/luvGvr6rqK7ldXxTV2bVx3N8WtcrPcWNfe9XDdXFNX1mVwcV1SF8fBPbFr9srmuNR+e9fbtvAJ1kpn6RxC+j8ZumsomofIdPlbAn0uV2SXHJDDckLOyTOprj10u9aAcTrS8glpH5iZr\/EeD9jWplhBO8F72IdeaIY6SA4gNvbpJ1miC7CPha2uZbR6Vsy2sIwVsybWzxJZXFvCVlzLGfyNXdmCw9mOPbieCZkLcRALeZAKkfEoxEfeqAd1s67Xw3pB7yqRCuUxHrPxLWfiAgZiO3owgps4ixt4l9\/aIuthI2y69bdB1ssGW3u7wG6MzDVYgbroggU4BWUCJmZ5duM21rK+FsMNcrddHX+J\/9FPFFzyt\/qj\/Rb+HtfM1XItXSfX3nV0A90Mt86ddBfcaXfBrXWT3QjXzpVzzV1dl8fFcjFcPXfabXXV3D7LaMs5FwNDGHf9b0R3DfUbA2SY7Je7Ulhz6y15JffkmtyS+xJoH92n9TEdJRmDpbiLn9nIulpKmxOR9ayDfWsjI5i6aIrI2K4X9Y6W1WeySb9DC077mvn2uHYuvytvDa2albQqdouL2IylmCSkR0jBTFzGGHaWy\/kBv6MmsuJntEdZvNVbekwP6yZdrWt0r57Se\/pJw5EdPXEUH9GaAzmKA3kArZjNallL2225XHZ3x7pbZStmVSyJpQgpteaxA19jIMZjPrbjHr5lYXZhL95gIttuYe6EG+o\/9yMF1YNBQapgpV\/Ir+jP8C+7pq6Ra+r6u\/nuk8vqh\/tHXQY\/jt\/dH+Cn89+7+y6a39Jv4B9zm91kN87dcNX8De6NNbJbnMhs3I7\/j3IX+U8G6RmK55Xyj\/yo+bWQFtUi+o0+lxfyVmLrEs2LrUjD4uzCspzK9bzM3nbczrOj1bBtVsm28jUc+uslNfTWVJpU38ptLccwm2Tj3BvX04mbahOsotW3+jaNWZmM3\/ALwDAWYWfWZcTUZjXLcxgTcw024E\/0Qm4A53VraJ68U0\/pK42C5MiDeliGRDzHxxxjP1tKG8uT7GeH7KzFdZnceVtt3a2CpbTotpTl+BMnMgG34BJeQxiZJTiYI3iMZgVtmj2yLm6+f8vPHJQNOgXL\/Vl+JT+Lv96NdwNce9fG9XKz3Un32cXxi\/i3\/XG+F2zwh\/sd\/Jeugf\/RzxG0DZ76M\/2I3xvmD\/cj+0VdL3PWhIMILkQEuhGZo1Po63\/e9ZABMknOywdJp+W0rlZX1cjaVUfrBI0Jj0XYmPX4I4fRrJFttb+siYU7ujjudxvPlZyDVVoH3fBEV2l9FNBDuhBnmdBddU3cF6OL7MTttTjWlHH5LQN+xkuAb3AXr5GUL\/EJnTiLMXkHmzADUzEONeDhgO7Qw3pbidhoia4Yjv04ixgczenMaSPtpL2yHdbVsttme2MPbZI1su\/sIPdxHguwPP\/iVP7KEWzKpuzDjbzKxNbQhtopu28J3WCXxX\/jovmffD\/Y5k\/3O\/nR\/Edup1voxrlxbqo75Ar42f1Z\/vdBxqBJcDxIE1Y+LHFY7DAN1vq7\/fAgctjmsCnBo2B78F3Qz7\/ontsM+9bucBb\/RTN80ghcI56O\/\/3eKYTzNsmlcTWX+lpHK2hxLaQFtI0+1u8QHTHRH0XYn09ZxWZaSztmaV0Wl8zlc5\/tiK2x2HYf77UlCn6tW4t1kn6nizRCkxXDfbBYroCL7RK4W1bBrjEXjR\/wBi\/wAvF5Fx5z8CFe4AAc16IdxmAgFmM+VqA+Pul+vasvNRVaYTe+ZxvG5U4uYn5Wplobu23fuoc2xprZKttmz77m5Sj2idu4nlM5mWbh9p4nuJs3eZ3hVskW20cr6ka5E66ff8Rf7A\/yXVAm+C2oHtz0p\/oN\/Qx+mP+PO+o2uC3uuIvhD\/OjBwmDK8GUoHxQJpjpxwpmB0XDSob1C5YEErYnWB5MD74LW+svcD85c\/FdYjvNwozMyJyL7niknf6Hc8cQ1h2lg\/STBXJZRMtpR22jXTSn9tMW2kiva238hqT8kQt5lIdZwnYZ3SjXzHVweV0Bd9UiWVX2YM0QFvkRF1c0KqLoj5jCN6xvLy2le29nbYeVtMx2lD0YlaTPTHyIa3iEUkzEaXyNoaiGX1AB9dADe7ABtVEcR\/WZesiGKXiB1XzNrLadzkZZOlvEDFbTLllKd8D62BrbbAttmTW00vacsGM8zbj2i02y9tbSxtg+u2ivLLlb5pL6K\/wjfqpgQuCHZQ67ExwMngSlwxoFkYK7\/nF\/vl\/HT+F\/cuddZL+GP83\/LVgcHAgyhhUJ2viV\/Gj+fhceHAwSBgv8F+5nf6p7ar1d8qCTn8jlsvi2md0Zi\/cxPnROTYmP2jGEbMTzH6QjtMftpI+Mlb3yvSbTQdpb2+g47RfaSS3AI\/jMw\/68xZm23Uq6Wq6ja+pGuyE2xiYbXE9bxu5czzw8hwZ4iBZopNO0Dn5mFftssdx37rx1szT2jD1D3VsTPsNVgHU5gFk5iOuYhC9RHj+jJGpiOnphOFpBcF0DpMZUjGd5G2jzbKdVt6RW3Q5ZuJWzfJbDNtggW2InLJUr5Kq7+O6gFXDLLIfVtMtWzA10vdxqt8LF9sv69f29fpRgaZAoLH9Y8bANQbKwnMELP1+QJWgbJAxbG+QNix32IigdnPR7+iv8h26tG+xv8u\/4afwr\/kk\/Iq4mWjP3o3\/FT+x3cCncdtvEVCxgdy2t22fvmYpRuQf9kRH18FC\/6BOdoe2lnbQPPf8f7bbSTjpKDxksG8Tp7zpdl+k2XaypEYtTOYkLmdDaW1c7bllcO7fUZfN7uibuG3fPzXAj3WLX0qVzZWxeRMfARszDIsinF\/QOuvM9r9lnO2D37Kgls7u8y58Zid25jAPYhktYmj24md3osTYaoD46YDTyIw2S4YZ+j7R4jtNsx79Zx\/pYJatp9a2hnbbe9oVxLYWNso32r\/3mkvvV\/XZ+Dj+GP9xdsv6hLmeI\/7e\/2V\/jB0HsYFCQOtgQ\/BCMClYE\/YLqwbRgQ1Ag6OCf8GsHi4IPQYOwDGFRgk1+Ur+Vm+iiuHJWwbYZ3CoXyd11W9xTK2epLbOFu9WugutsJViLGTgJBTiHNzgqYi6Guigd2g5HxzQdrG31gXaQttL2vwhHvNr\/F+cJsleeSDwtrn30D32i+\/WGDkI3juAsxrETHGTZ3BRX321ydfyp\/l+ul5vjTrl7br6fxO\/lvnFqVVmEXfgaO3FXxyr4hWvsnLW1G3bW2ltpy28L2I5hVsAK2AJWZ2UO5Rnu5+98hS2YjDFohG7Ih3B80ttaGC+RlGc4yGpabKtgySy11bANtsLq21kuYnFrbfdstMvkP\/aLBN8GFf0S\/ktXz51xKf2T\/hs\/dfBLECWoFAwLJvvz\/CERasPgun\/MZ\/DCnxm88ev64\/07QcawZGESqXTYxSCH\/6t95jUe5mBWCH1Cs1k5e2yT7AO34xkSch9jWiYbzfqIhhKIhObYghNYjIPoiSY4pBv1Jz2sc1S0oi7SttJa2v0P63YhlDvJH6EZ6EY5I1F0oj7Q777W+CcaEydQhD9xBfdwiqVxUd33bpLr5T\/3t\/tX\/Nh+dr+tG+CK+TndLLvLDPwH89AUUZgdLfQQlrG+dbZTlsbq2CHrZE95jeNss9Wx8nacnXmYt3mIB1iWJ3ACW1AZJbEFr7EMo\/E9DiIP37Edv7H8ljbkNRDXxtkGG2G5bTA\/srqtsdxug6vqN\/Z7+\/H8HP5B98zR3+TuuxOupe8Faf0brqJ\/251x5fzdfscgV1jZYJU\/0e8U9AyrGNbVP+6e+rXCXKRXkW5HOhak97faI\/7ILTiMDViL88jJNbzKEYzOZiGVyq\/oiLFogg\/aV+frZY2LIeiJcMSDIRH2aBuNpdM0qr6WrurQXlqHngikI2K5jbSVTtJPBst4mSP75ZlU1JeaBMVCJ4ZiyIvzOI7TbG6JrLidtIauqB8juOUP9sv751w6d85uuKr+SbfTXjElx+GDTsHfqKBzkIetuYur+InNbKkVsw620SZYY3vPu4xp1SyV7eYiLuZEXsdu7MEmlEVv7EELOIxHM97kR9JmcxznczNvsrkttR1WysbyHQdaJEttDULuBZncVUvlmrixLtxdt\/O2xEq5e26dK+c+2lvrFor4qUGCsFFhxcPKB0P8VsGUsJvBKv8395P\/Y1A7rH3Y7rAX\/mZLbOsJ7kAeFEcU\/ILh6MLcvIOtqI8L2ken6G3tjKI4pL3+w17WrAjDTp2tN7SP\/qzf631Jrtclrg7Vf\/Q\/UdwmhO1\/ojkC72Gh6cZJuSMlNSGm4yNa4lfEYixWD7GfHqANYdHcP66vf8jv4M93H9wi5\/nNXW4bZdFdAbfaUll6VsEtHanzdZfWRWJW4k80HmcJe8QsNtEmhfLcSaayfjbR8ttLFmBUvsFo7MMsdERjpEYW\/IhtKM3XfMZC9r2941su4nweY4QepbFNoNhoy2mnuIrb+I7lrIF1tBG239bYMittkWyoHbaIujDH4OL6T\/2zwdCweWGtwoYEt\/3hfhN\/V5A47Jn\/zE\/jDroGQY6wA8E0\/zc3xIrbGG5FHzSE4bpu0GSYjH2YjDrYrRU1lS7SriiA8zotpHpqrl30kQ7UpppT92oNra+\/aWb9IlMlh1bXOto+FMURWWOajJD\/VMWuMkRmyEq5Kum0v2ZHYs5nS8bmPcxkKqtkH9iTSe2aLXYZ\/bNutf\/WrXSR3UBXzF\/jiltS1uChkBI5EXfgb2zQ3VoIo7EJT\/EQEafcmqzEZVzNyRzFIcxnJ2yDNbEkNpw\/civ+wVKUR1GEIxdKYCmyczo38h4v0rMP\/Dc0hdvN24zYIk7gbAYmdppzOYgjeIOveJ0nuJ1qDSzcuttu1rcqVtj62O92wfq4Kn54sCXIFMQK4gdz\/DEuk3\/EHxiM9O+4TlbElffb+e39yf5+953zLBYHIx1e6ZZQf3tSY6MVKuGB1tZPklrn6AadqE21rWbSHRJTY+qfOk\/jaiLtoBk0vUZUwCS6UNZLeo2hg2Wc\/CkbZLZMkTHSPZSl+8hUWSUn5YWk0Rd6FYP4gYVsKo9jF1dZYvfA2lg6O2Pb3V7X1310P7sTFs0l9LP5ydwha2Q7mJQ\/MTdyYDOmIyYa6j6tgo0owLbsyxK8hhM4hRsYxMM8zYv8mxs4m\/UZlQdh7IIsSIxY+AU3kYENuI1mB7iODZmPGfgDB\/Mmm9hsK2oNWIlrmdii2iOu50B2DPFVBnEMk1gpq2MJ7A1nMZK943VWMroyrqPb6tL6zf3Ffh\/\/livuattOq+guuU7uW5fV5ll2V8v1cVn86H5dV9YWMBLz4GSIuVBO02pdXaIX9F9tqRcljlbV9Oo0hpbVdvpG5ohoPO2tBfS0JNLEekqyRzhrSU8Rra5l9ZLsFWpavS1rZaqMkZ6hKjhVzsozSaJ5dKkORjr+xQjPkZj2Gz0Td9Kldd0tsqvtxjpz1V1fm2wL3BN3y8X20\/kv3GqbaOH2MzOFOP+vNWIfsA1pOJB7uIwFeRpFUBsT8Rzh\/IbxmJe38RYxeRUn8Qdq43f0RTZsx2skZ4vQ7rYsP2AVuuAIcnMPS9qvdoYlGJ19vsZ5NYtuRxnBG5rEE1zNDmzI7dzOVvaatXmKR2mWzV5aLqcui+virrlp7ppb68q6uC69vedKO2Mzra3d5wCbZ1stcL+6I26iu2SJbSlP4YUmxUNtqYX1ucTTH7Sw\/iuL5K3E1ScSwbAfpQ30mnSX3fJFymobfSl3JbXeln2yRJZIf3kuTyW\/7hdPX4rTlxJVnV6QbbJCFstNialVdGGIFRMJXeHYjrApls9+tx02xe1yWdwXy+ISuzF20t5wqVV3A9x718gv6U91a90qt99q2BkOiNhtY6I+1Cq4jMacwsZMztGIg3eaHuvRDRdwBB0xG\/twGZsQlcPQD8\/wCinRFVPwAZF5H0+xEx1QGu2hXMDbXM+knItnKMq9rG31LK994hGOZGd25R+cwBscz6Zcxp+4hfEsn5WyTVbTfbY\/7ITFc+XdA8vmlrjfXTU7xfUsbCktsf1h21nW6lp322XhzncpXBbXworwEz7jIbLjiLbWTPpA1spfMl8mSGy9KXvkrKTR8hpZ18sQuSRRdLt8lMdyQsprQf0gMXSB9JODElej6ia5IAm0slbXVlpTC2gZrajnJLku1RfaBfk5i314jKPtvR21FjbVorh3dssyuhmumIvj\/rICVsSS2nUbYD3cB1fTj3CUm+WX9NP5210Bl8uVs9jMivzYpbuQkm8gnI3OSIan+j2+CWXgrGiO6WiHRdiLsziK3UjJODyIjGiAymiEeqiA1siFIjiHMxiKcRiLntiGcA5nTfvLulgmS2fJ7Tj\/5jHeYRSrb+G2itlZkQd5kWJxbZfNcgndEYMVt\/NWy55aPTfMTbS7\/IP\/cDfDLJFt4beW056xqm22kRbbvbN3lsmycB1jsjkOa0MN18\/yUi7LMvlDNspkmSmTxKnpNqkr0yW+VtAnMk4GSDQtqOtkpRyQ0rJM3khUXSKb5aXE1dLaN7Sh764DQ5zsq1oWe9CDBey0NbXq9rfBnbe9dtbW2yNbb91stnlukg2y85zLJ6xnkVxdN8\/19Rv7F11\/18HFdrndTptkv1hGW8zDyIr4KIdj6IYqiIEH6qMD5qI3eqAF2iI\/+mAkOmIxIjxT7qIPeqMGcoaYfRmRCVlDW5P8KILSqIFWWIVr6M4qNsWyWqL\/PUmthi22Lfa3Nbbv7RDLMx7LcDXn2COr6ta5p9bX5rCqJbH0BhfdLbaTLMgS9CyzFTBndfnxa08fw4pYNEthzayYM5fZzrI8VyEBFmsfza7nZasskqFST1pKaxkne+WwdJGpsl1OyytJq8tkqlySrHpVzkg+6S0H5b18lDGSRKtqB52j0\/W07tGzelZn6k49qFc1H1LzBWPZQ+a3eNbGPpi60s65yzbJUthlLmFl1mV3nmPEzuJ3d8k1d+fcePejm2U7rKLFtSscztxsyLG8hkLYp1kxAK2RHrf1vRZGC6zAagxCU\/yNLmiMjdiBnbiCzdiGJaiC+miGeiiNzMiMLCGcC6IEKqAVRuA1ZrIav7PalvH\/4JzNytoWq2XHbLa1s8+cwJZ8izvIzhbsYT+6SK6xjeELzmMmW2t7bIa94GRG4Uve5L88ygXswC08yNOcwkQ22lK62i6By2m1eAR5QKzV4vpatsok6RfSBxaWkvK7jJKCskCayUlJpwX1gTSSO5JU\/5RfpLgckDXyIoJDLr\/qj1pKl+ppXaR39YO2Cu3xO+M18qI79iIfH\/MFa9oCi+Hu21H71p21CXaSGZjNwlxaF89959a5u26+S+p2WTeraYWsg51nTxZjTG5Bf+TCj2iBGLimkXFXL2gJZEPCr68Z6I0d2I+5COdozEATjMVojMF1fEI0bsYZdENX1ENmZENW5AwpUquiBYbjIOLzAFvYUuv5P4wT\/5935S2dJbIfbB7781tLaw0YcBzH2Lduq93kFXRhWctuuS25PeUj3MUM1mQiDuZpXIexCbPxCQfbMjtpYyyWa2A7WZATkRDztYnm1S+yQVbJHBkhQ+V3qSJlpbFUk5WyTc7IFzkinaW\/nJMX0k5ShE4hmySi61glF2SN1NUqWlYL6x6tjxm4GXLpq8y9KM5VzG\/tra8lco1cBIf9DfuzFsdwFidaNtfX7Xaz3HWXwT22mXafNViFVRmViZmc8ZiWMbkcLVAc5VEWaXFJf0VdpMI\/+kFLITNKYCpWYj+UH3AEI9AfrUL5dxIeYx2eYgoqITtyIQ9yIS9qohbaYBjW4FsuYh7baK2tnCW2+tbCyltdm20Z\/k9sRzy\/2wSL7JrZapZgT8TmYca3AhaXjnu4kHPYhW1ZhqVwAKm5H0tRFI1wAfPwGckZy1rbzNAmcyIr8jiaIzl2aw+NpC\/lrByWCdJPJspv8p1UkJZSWPrKNbkpj6Sg7pCfZaFsl3XSXtJKdkko6SSQhdpVh2hsra8tNYEO03V6WSOjJ7agNKcyPX3ra7EcXHa3yvJYPCtpnutqORjdHlkDF8GjnuDyuCGW1i4wN6PyFd7iFSJ8T6qxIUswHl\/iDh7jGZogwGu9oDf1hj7XF0okRR\/sRC38hXWIzs\/4jA0YioPIyuhMyjTciokogAIoiKIojobog79xHgnYkqltk7WwslbCZthMe2Kv7LPttrHWy9L\/F+NCVtd6mrifXCcX3\/WxWVyJdfiLu5iP9ZCBMfgMF3EAu3Aa0TEGyXFbd+tJpGMSPEd9PmQ2a2DtbDSnoS\/y4IGO155aUm\/Ic1ksW0Oet52lpYR\/zQ4lpae0kd9kmxyRl5JJF0kXKS1FZYAMl+bSVKrLenmrX9RHI+2phfBMx2g7LYnvOYYdeYIPuZs3WMneWxnXzu2111bFqdts5\/kKl9jSttpst8E2h2bts\/gDb+MCTiGM4YzF8mzJySzPuqzL2qzAuqzIk2iF6LikV\/SuvtPyqIH+6IdVeI45+AfpWZ3JuRob8RCNmZPvsQr90BBD0Am\/oTl6YAH+RSJ253J2\/VoRrttHO2bRXRYX252zqVb9f7kjnfWyFxbfpbEM1tmK23TbYm1tEfthHZLxKbJgChojMlIgIaIiA4phlZ7QqdpUW6EOTuhS1OQgzuYLvuJxpuYPGK0l9Bf19YqsljeyXobKUPlT5skw+UHiSiSpKJ1kokyWVvKHqObQh7JURsmfEkvfhPbaHyWxztNzmh7ZcELDsQEL9Yj2RzTm5z0+ZDTLaH\/aTsvuBrtf3TLX09V0t+0l8\/I6ujCJfe\/q2QQq3+MajmIP3uJHlmITluBPnMeh3MgvvMpDvM4wu8tRLM4OiI8INvI\/WggD4bgI75CW+ZiMlTmA2fk93yIbHX9mbn7CeczCEfzI1WiDaTiDlFzApcxgZ0POMddssG23VdbaqvwP44yW37raNfvBzXBfrJrNZQ824a7QdvAXVkVX1EIYPFzXzvqLVteumk7HaG3MRnK8kxgorEu0Ce4gDqNzLtezD\/cjHKO1iL6WU7JDZktnGSwzQlOgP2SitJCM8sGLJ42kgOSXsXJQoKcktxbWlbJZXklsnSpLRLQQXup5jYUx2It28LgYsxHhcvcEf7AIn3CSwRV156yybbdhdsLKuQc23WrZWJ7BWl5gFp7EWqzFKizGdOzCKdRnOX7PSQyzRTzPAhbfjjOytbS5doStQnP\/6AASIg7q4wTuYAcu4goOoDKH8yIL8GfWYhzWYAcmYi1WYBaW5WucxFRcg882vMla9ta+dWtsslW3X0Ma2v88SSy1Zf963p5u+d1Ut8RVcHPsHptbfd7CQazAY1xGA9zSdRobxTAKzzQWUiKpltdPekd3hzSs52WEVkFrLMcuFGQBpudcvNDmmkuT6Ud5K0dkgfSVOlJHCkk8SSIFJYvEl389kVoyTqbIcKkhDeSopNBjElOTKXW0xNR6mhTDMBBTsBNCJUL7\/Odoid8xDbnYmmf5lKntFefxTxa2i7bPDXK53ECjPcEj7MUaLMAojMU0DMVCLMQ6HMZdFOVE3mR37qBvmew9+9tl+2z97BOTsiMyoQvy4ZP6yICayInKiMV4X6M\/DyO40Gs59Ovpsy+rsCm7sRKT8SM+4wKOIgmzciRz226baJ2sjmWxcItvxS1RqIsuZfXsJ6tif1luN8rl8BP7G90418Kpa2Dn2ZIv0BFZEQuvtSYaYRnm4g80wBotoIHm1Z91jxTSLnpJsmjCkNtQJUTMwY8gM9brXM2pxTW2\/isPZJlsl7WyXZbLDKkvaaWh5JQX3nMvlzSQRJJLhstBSatRNJ6m1\/6aUR9JfZ2q5\/QvTY+BUCZldZZjWa6N6ON4CCexAutxH+8Qg4lZgmOY0fZYAtfR3rAJb+MwtmALFmMhpqA\/ukTs7rAMB3ECkVmay3iBjTiBu\/iQl9jWLto1G27fWm2eQS\/Mx1X0QFIkwWRcQ0JeQT524WN0ZIuQhrM9Z7I3u7IRizEKryI24zAZe3IPI7RnFSyWxbKEFsUiWE2jrGRIoVHIxlpd+8PuWWf3oz\/HL+0n8RP4a11Od9p8a8O7mIdJqIOfsBerkIXCtFimFzUOEiCWfpQEelKHaiTdIF0khkbVNzoaQ9AaGzSbltGtoYnPBpkqw6Wt5JNysko+yTPZLE0klcSTl95V75mXWybIS7km86SfzJFDkl1ra29dpLkUyIFDmhjlUQY5cQ\/LeJq7I7yN2Z5DGcWuE\/aJMewMC\/AyX\/Msq1K5EWuwEYND2WIK5qINemFYqKoFrMj3SMjarMGcXM5tbMzzLGl97YyNtqI2kGFMzUtYhcLojiT4A4dwCzVZgpm5DQX5G0eyNydzCUczD6OzAMN5EK9QlmU5P+SkFt0SWGrLZPktlnW1E3bNetkY62TTbK11t3GW2XV3cf2kQbRgv1\/CP+3Gu1fWzQrYdObhA9RANcxADn5ENjzRMETHKnyLPHo2tE1PgMn6q1bW7pJAR+kdvax\/a1t98vVU11UGy2QZJ60ll2SQNFJa6ssMmS3X5IZ0lmoSRa57L7wBMlfmSl0pL\/EkqfwoY+WTdNPtelzfyBotqA\/lkiRWoC3OoDabcRwvkZbS8tsHO2kHrJLdJdmV0XgSf2IWZmEJFqEL\/sRszEAN1EE9tEUrdMRU\/IN1uICXiMYGTMDGvM8mNsK223pbayntPk+yPx+HeISNECAnCqMLovIczsNjSbZnLc5nBB9sFWczL+NyGSIxDROxFSNZJ2trUa2dTbciZpbCatpV8907kxAXea+NsV2W0g108fx0wURf\/NGulvtgXa2IpbHrHM3fqcyBI\/idb7AMxfAnVmIPcmKdtsESDEcKhCGDbpYFUlU6y2S5LHH1ivSU0pJDOkomySW\/SB75RpJKYqkpJaW91JadclsmSHk57j3yvpcSMlASymsvkwySJeJrcm2v+TWdNpAGslm66U0tqA30rm7DU4zlHb7lIeaz45bf7bTfbRq78RIWoy9GYCIGYQbmhXZ\/MzAJbfANN2IykjAfl6IvVmACluEAziADf2J5wgZbDBfF\/WUfLZt7bs2tA6tyamgrHA\/RUBhLsQJ9Ql4WZzGaTdmAA7iR0\/kDH2AlniEXc7MXB\/ENO1gWS2jJra4lMLGWtsyG2Ei7bt+6lG6PLbezlsKF+9P80\/5SP5YfMR0\/aZUth51jWXZmXD7EERTDbmRkXV5Ga2TnOQxBCgzC\/K95MD8+al0drEU1vg5WT49LHflZUkm4hEsgX7zX3hfvnffce+Jd96JIYkktsaWEpJFhskgaygdvn8ev3Uc3ySsXvSjiS1U5K2\/kvdySXRJZH0s1VXRAZhTR1FiGsZzL1pzDA4xiVWyaORvNgtyBEeiDZhiNDhiHiZiGKRiOIRiPGriPBNyHCuzHh+iFgViCzdiKeOzGtdxEWgprZTHca8vptrotLrarY7PMrAwnISNihxj6BVADt\/Av3iMLO\/HXr3V+MSvwIxZjI54jGX9gMd5hhKb9Ht\/Qt0JW1MSiWSYrbD\/bENtr7+yjnbSnttm19T\/51\/3Ffkp\/i3trw+wFR7M6U\/MKlmMd\/sQL9AxtVQtyHdIyjPvRG10Rlf+gEK5qOJ5rSW2om3SuTtWimljHS2NpJEUkoVSR3BJNIslT7653xbvqnfPeeZEkTEpIH8kur73d3huvnsyUPHLWyyR1Zba8krtyTubLHEmMvnpU++IRMrA9jutq5ORAbuJpnmVSi2MH2JdZuBj90RjN0Aa90R8jMAIjQyiXxSgsQjSOYlru4osINSuPYAHGYAn24F\/kYSsOZ2xrZyvte4vslrjRod1oRGc4gztQDamRBmlQLeSmvB3RKEzN3SzCkozPpzgEx1XYjgTswdX8l2u4iBN4jY9Y3KpaRH+f1FJadmtlA2x4hEbRVfZX+FOCkcEhP7O\/0OV1fW2slbFo1o9xOY\/N+RdL8zIeYDRnMEKdcQCLsQepmYKHkAL1kRezdIxmxBlNgcd6QtNoV+kjF6SVFJV60keSSxbJJXHko3fRO+Sd8E55570HXh4Jl73eIe+hl0HqiC87vezyjfwsi6WmLJdHEk2jIRFmYidSsjH\/oDIS3yE5u3A0D\/MFj7E+1zARB6IdaqEYSqA1+qI\/+oRqXgf0xnjEYRs+Yl36ttGK23H2YV5uw+yQU+FVFOcK3uErTucrXrTxrp57YT\/YXe5mO15CM9RAXlRGZ\/yKCdiBdIzQ7UxjXf7Am3gR8jq8gSNIyDYcw4HMz4aswMr8k2rRLYaVsHLWzX6zvOYsl+2zIq6K\/9yfEyCY4Jf0p7v+7i8XyQ2zVyGm003msRdswsJ0zMQxPML+7MCkLMGyIbXQHvyJooiKL9oSpRAXs7WUhusa2S7PZZNUC52uS0hlaSYtJbJkkECueYe9Xd4mb7d31tvp7fQCKSSVJIqs9G57aaSx\/CqfvcoyRM7KQJ2gVXEZFbmEyziI5ZiW53ENufgHl4T+tkW8g\/kYCY81kQe\/ohN6YCYWoDhyoydm4z5acArDbYDFdpUtiz3nQqbhdCzDBjxEL\/7NwkzGZaxgEtIltXJJnHPTvtalcP6FwaiA37AZxkOhencV0VmYXZmWVxFxy8BpbMZ8nMO\/qMfC\/Jn\/4CWSsw5r8CkT2hn6lsJy2z6+Yll7aOVdK392cDIoEGzzG\/il\/Gr+HfeLe2TFrYuNtWohJ\/rPXM8mzMW1vPO1I8rMDCzKRTiHiM7mPtbiNs6jPcogBYjB2lDz6B1RnSFjZJz8Lr2kqRSXXFJPSslHL6s0kxLy0FvqbfSWeU+9bBJLbnoXvEVemPzrpZWYssf77JWRkXJBftEz2hxfUI5FWYUZGZnbsQBn8Bjf8xGuhxz5UpKMxfnIidLoi8a4ipfoikyoj\/44gD7MaDGtvh2ysnaZNUK\/NQ8LsBUH8Q65+R7pCNtn+dw3LpVr4G7bedtkdWwni3MtWoY+txeQi0\/4kUtZmxFsnx94DvuxE\/cxAG\/xGhmYmIX5EDtwCzHYlCs5jnM5jX+HHPC2MbmZG+0euMp+seBj0CvIHrz0UwSz\/Oj+AtfURXV77Z6ts9+tnPl2k8PYj8f5F5\/gEAZjBHpjEqZjJfqiAJojDsqiBwrhtA7WxppEX0t5\/Vemy0AZKwuktaSUttJdUspQqSMLQz8v9hZ6a7zr3i5vubfIm+tN98Z7Q73R3jpvnudLcUkuA+Wq\/K1lQrf4xOde7MZcNMc5gHfxCKm5MqRuPsTvmJh3UR5pUQoNsQjfMgVHIy1G4yzWcT978gnfsTe\/4w1cxirMxzpsxGYcxSlcRQlmsD3Wxp7a326g+82ttOi2iV34BkOxCmUYoXRpxLUsZGL1mIYvEZt3cQp7sT\/Ua0YLzQFP4G+swEf8wmKsxPb8gfU4jDXZhZtYx+7Ydy66\/5f\/we8ReGG9g7VBomC\/P9z\/xd\/gsrpF1th+MM8uM71tZ3f+zSXswsHMzBPogYGIuB9gFI5oenyHq7pPt+t4\/aw7dLn21fw6VOPrWYmuS6SRlJdGMlFaSVPZJgslg8SUI14gu7y53t\/eZG+qN8Eb6U3whnnjvEFef6+nN9Tb7R32ZsphGS3ltJqu1H+1ik7R1Liqq1GH49mAffiRv9s8PsIiTEJDFEFSZMZPmIDluIl6aIJNuIM9\/I2VeYsHWJMpmZ23sQ4rsBKbcQzncAKXkJxRraKNs9LuopvlvnPHrIFFtsU8idO4iBnsEKEGYBQrYEvYjZl5D2dwCsdwFkuwGicxD6dwDc+xFcMQ4YTyHFEZ4RsXn\/HYhX+StsK6uab+Yb9RsDyIElY6LEfY0CBLkCSY78f3p7iEro2lsb38mR15n8Msp6m1YUleRrTQbCsXPukp3aPbdJXO0tYh5ktC\/Veey135Ry7KI6mtFfS97Jb+0l76ykapK8flrSySaZJGikpfaSWRZaY30VvuTfLWev94V7253gxvpDfY6+t18zp4SbUMquheuSrhmgw1kZoNOBydMQXxuINmh7mQ9RiLl3AEkTgQ1fED0n\/t6SMzNn\/DXPjcFTHlw1nE4mLmsbPsxgsh1tYqrMNRVGFdvgpNPU\/QtzWW2E1yH11HJ+43+5dVmIjNGM9gfa2i5bZTLMc2LMCLeBbaut7AklDFnY5RmIRD2IFRWImLmIpTeIF4\/I6RWILteIeFDC6eX9Y\/6S745YIaQYXgqv+7D\/+4W+aSufwuputjl\/kLC3Ejw62ALWI0vsV29EM9pEV7lMAveKSF8COSIhkES3Whjtbu2lBvyoCQ0\/Ag6SMbZZCMkSlyRW5IEm2spfWSbJBt0kjiyivvurfcO+lRHnn7va3eBg9y1VvtzfOmeH289RLBrXqgTzQVduM8irEHn+IdhvEmC9lJu2wbrYe94GAWZmbeQj+URzga4wvGIzvqYxaOIxlHMB2jcyU\/sTNTsT6rMjY3YxPOoBrj2DYW4gck42XutGXWyj5ZSpfV9bAwW8JyvMsBdt7WWwYraC+5lA14KITyv\/iIO9iGAZiB8WiPVTiGUZiNLtiFG3iNFEzLsizPbezEscxls+yNvbCuLrv\/yj31cwT1ghv+Ur+Mf9wVdw1sHVeGJihXUJCtuZ8bmJ2O59AJuzATPi+iKSqgPbKEvMMGaSG9JAdkvXyRL7JDuskCWSSTpJ38JmUlv9SUJXJDjsk7+UFvyGTpJk0lhySRe15Meesd95Z4V7xwcXLFu+zt8eZ4k7zX3gr5W77Tc9pP+6rDTQzhFT5muHWzVRbVZXG53TA7z1qsyDfYFJoXNcc3GIOYyIMBqMWzTGerOY5p+SuvcyfL8i7TWylewC5cQANu51q+pmdXGJ\/rmcOWU6ywZbAydpKbOZ2neMjyuY52hm84lX\/wDsrxG87AZuzDFZzDKtRGHYzCajRDfYzHKKzHEdxEGLOwCmfwOH+0s3bOjllk18P1dNvdBtfGLxLsDuoEz\/yO\/ueI7ZqltilsztR8gvm4gUwcwQfMzHRcg8g8gJOYhgnohPTwUU9ba7iO1TZ6TP\/SwVpVAz0oOTWH5g35aPeR3ySfpJHyMlXuSVpdKyUliSSVLJJAwkXkhveXd9SLIbklrzzxtnk7vDXeS6+OJpFPXgbpIzMko27QlojFPbzLUtbBVto0a2tPbYO9ZzN+CNXmyWiNHIiBtCCyozPScRIPM9yOsTBPMoYd5kE+ZG6rxoc4ilgRXTLz2jBbaBvsB5vINCzBGrzHNpbUCls5e8t+1sQtdJetrt3nTOZmJX7EfETcezMd47Ees9ENzVATQ1EXwzEHi7EDl\/EG4czMiYxtG22sbbTSbofb7tf1t\/o\/BQ\/8036y4I8gUVDLP+F8N8zSWiqbZnUtgvXrsz\/m4V\/05DqeY0v2QRG0wQTUxlZtF\/Lo76cVtJm+0HAEuKu9tKhm17gaS+\/Kn9JfxslgaSffSzb5UZZKYt0ulSS7iNzxdnpHveveB8\/JOe+Nd8Rb6y3wNntrPZNSUkOXyXApIHGlhHyQxdofcZmJH5nPXvIHu8+j9r17bd9aX6bnrlAPVDfk4PdZv+hPaIJheI8mX\/8vB\/kbJzClFbOF1tVy2zzewkV8yxY8zqx23F7aIitksziNuVj465mutv1qze25nbTI7qJTv70ba2dDzi7RuBoJuRsbMQbtsRBzMRO7MRHV0Rc9MQ3rcQGvEZNVuZwn2NYiuxHurRvuM\/g3GBfkCKYHT4Nfwm4G7YKcwUw\/zK\/njtpT+9l96+rbXNbjKexHccyF8lc2YVp+zyIIUARLtaSO0HZ6Xu\/qMV2g5zUK2iMvNmotLaLf6ks5Ibtls0yRhlJBGkoiiSz1ZY\/slf2yVLpLVrnnFZFv5Lb3jcSUdV6iUAZJIMe9HNJdIhwXxuo++UVySgU9q9u0MgrxHM+xA7+xfLbZLlg7S2ETuJ6D+DA0N2qLNXin0VATPTEJ9\/EN67A+R3IHz3E6tzOGTec3\/J7\/ABxAZ93tuHWwx\/wrpG+vxgtsyq2cZsussOvlOrmPboW7Yp85iGHMzczMwcpMzofYhd9RFqVD7gIDkR9jMAyzsAXXEcbq7M\/MtsRq2EHr6Gr6BYIXQcewo8HqYGDwTZA8eOxXDWb7mfyVrr6b5pa5oW63+dYjNENMyDVIiSm4C8dkbI+4CMNZra+dNAeSYI3+gC36DZKgAcYjFR5oRJxn1qyaUUUj60BpK12knuSRJPLFKyN5Ja0kkGiSWCpLQ6kpKeSTd9677JWS\/pJf8ssFL7aUkV4sy6yoqi0lgVySxxIJm1CA3VmVU5jfWtlYK2c1rYjFtORf82k+PkYn1MRviIkkaA\/ha9zHOXxBVKZiRd7lCE7kUy5gJlZjTpZjXU5lVitt77iTc7ifffkXt\/Eyy9pe22rb3XV3z51xdN1tDyszEQuzIj06HscC1EFt9Eaf0L0ZbfEzxmAkZmEjHiEnezKGVbAYboab5va4in6z4HOwIWgRxAsKB5v8OH5S\/6R\/27\/kd\/bT+HH8T267+8HttOx2nou4iUk5ERnwM9ZiDCbhvG7QnbpJz+lT7YdmGIzmKIm+mI4GyIJN2kWT6GFZIftkvbyRXTJKRkpDWSWVJL689V56n7zP3mPvgvfEKyP55aWXXEQue5EkmyyQgWJSQcpIeubHNu2rF8XkkszQokjMVuzIMrzJKPar1bUy1ssm2VqLZo+4ht25BIuxE5sRE+Ad5GVDTuEB1mUxjmK4redSruJxnmIj9uJg9uBrxrNvrYA9YmJLale5gjv4nn\/ZS2vlirgT7p1L5Qq4M9bfHrEfC4dOpPdCN0rNQcR9pRHbuoTIhD4YgpGYgYvIx+V8wKNWzS13P\/kH\/b3+Jr9\/0DT4x28QXPUj+4\/c3y6Xa+r2uex+Tv+pK+kiudKuoRti3WwWHa\/hA66iFKIhPY7rXr2j9\/Q7JEJB9ERbTMBSTMR8jEdpHNOMml0b6WRtpaX1quyVcdJNhsgROSierpb6UlkSSCR553ny1DvlnfAoiaWclJbXXmqpLMtkoeSUn6WX1MUdbapJNbOkklNfu\/Km2g3nETADq3ERH\/BHa21i73mLt+mZb415BJcxHL8iJZajIMdxKWezCityJl+zpFW1ppzEjbzFI\/zMbWzGZYxld6l2jiv5J8ezW+h+j5w2z\/rZI8vuVltT22xzbKnNstg2g\/H+X0vnGF5n\/3TtmVkzv53abqq7dlOnqZHaNlPbdlMztVObqW3bdpvaxvvf+32OfM6HXMfOtWfWrLVO3auhGldja0zdibc4hSU+wmZBDEF3PERcnaj57IGldY1dFM90zwg\/\/yhL\/LZ6gj1BnnOeYn53PKc9eT073Cs7bfFcFhfHHbRqVtp62GutYr90pLZUp0NwAPFQCU2RHF4OZgfkRA9swFx0xmt5JZWxWubJFrkhKVEFDREVCyRY3vNH3sjduAkX4xZcjbNzDM7OjbgoF+P4\/JbO+Sbny\/SXEnNmrsVDuDLn5cpcm3fLPDnHXTkH7+Z\/nEleyDaE6VGtYwGW1b7pRf2tj\/W+XtQnelI7ayLdB2gdXQLGMSTRxDpAG+lAvaxX9bMms7V6GbV1l0boeV3tbQDQY1pT92oN62OROlh7apju0jDNZc8tkxthj\/S6xrAxds+e2k2barnsqubUXlpRr2I\/VmMsvIlsb1t1bZzAD+wG6TWNZpUtv1vv8npeeSb6ffNr4XfNc9SFuEWujuePa+fJ53nvirtvtspym5j4SFantavmtp+aRvdinq9XN7tXicVkQDNqb9zERSxBLuTCb6mCL5IAw3EDzTAX7\/EEnXxUibryg3fxU77O6ziYA7kbF+G+vIOHcBuOz7HYn5\/QBdpKR+kgxeSz9JmS8Dl6Qq8oq\/zlThyV23JiGSzREYaW+kfX2EG7aEdst0W1QFulfXSsztbHekEz62vU1Jy6DpVRBYk1rWbQt2ii5\/WM9tBp+gynUUgbaQftqen0OWLqZ5TShZrU8lk8m65pNJ0u0rr2n+vsMrny1l2v6hA7b\/3snh212zbYnHkV0xJ6BB1RGg1wAlG1M4C63r40HaiZtKTGs4uW1M10JTwHPIF+tf1i+o33vHQx3Gur6hK4rS65N\/Xj3rn8bpXtt4RuuWW2LPpGu9sojaHjNYPewmCMRG80wwFE0QBNqt5JPQu6YR\/qYSa+ehkl2KoJtKgO05p6BcE4IJ2kjuSXz7yVB3EdnsfnfPzRLdyFc3IeHsGVOC1\/oT20gZZROK2j1bSVntNPOkU3uTrn5Ojcgc9zL0mGDHpDi9oKu2rmwu2TVtNC2lJ76Qz1s1SW3OqrR1f4prti+Cpr8BnncBildIUm1\/Oa27ZqIc2KtdiA+PoNT\/APffEFg\/SgrtNhGqpptJOWsAfWzP22ajZAi+k33Wml3F4r7H5YPZutrbWSRtNZgC7CdCTwcX6Lwh\/j8BFldLnO1FC9q+3sjfV3t1xDz3lPsF87v9GeOJ4gd87yWahttkA7YwVcU\/fUhto6rWTprYqm0WPa2r7pVH2lRzWrLoKo12EwBx\/RQa\/7Un8rcQKJ9SVKoTh2IIq21hwW3UbrD4TiqlySnVJJIvkuH+QO3IEf8lc+wnd5BVflTFyGG3F\/bsI5+QmdpwO0hhbQVNpLN+gdTaeVXI5DOJRHcA\/J\/r9dd4A+05Z23KaZv2XVIjoG9XWxprR3msQWq+kfNNL2ml9jawiS4gde4zAy6modpe+wQ3\/qJo2tfeGPVdiGCKxHDF2LUYitmbSOttPh+gkNNZ4ts3YWxzprfr2iCe2ABbi0roHL74raVE2ka7EZC1EJydAS1fFFeuGTtMcaeImDLzWl1bPYjlwWd9KV8hz2nPec8Dz1VPWIRz0hro4bZRVth97VLnbN4tpLzafvNJqeRZCu0SArYJ31vObVt7iBpziAe\/iNSnoZW8A6G5\/xGqMRhAbeFiedode0pX3SNhqBduiKLngkNSWdHOdrfJP\/8CnOIv5ylZtwHm7O7TkmZ+DYfJPuUyx+SftoPoXRNBpDI2kExZJrXEDOckJ+zkdlLu4gu77RSuq9ScZGOkCvaT9bZ0HWVatqBD4jtSbRFvoODvXwADuwAGm1g95CPh2qMTUMA1EDN2Ua1mEDqiEMQ1EdTzEcQ7EUSXST7tWX+lknq79+xQj1ZnVqWFqX3yV0IyyeVdCEml3Xa229iMVojua4JJ8kA3riEnLqcE1gXWyXxXGTXag76mJ5knn8PAk8pT0fPOM92T1JPRHujuX18i20s07WcnbA+3+GdcimB\/SKZrCuGktNC2gZ7YbL+IG8ml9ZU+txBOgtVNCFvrf1JaxAcQ3XUpbDbussHacf0QH\/ZKvUkTQSR07wGw6QbNJEkstNXufzmqfg3\/SYftMLekr\/KCbvoLW0lVbRbJpIk2iDTJOpUlnq8WTuImUQgP\/wRBbJQ+mKejiE9gaXws02fzug9XUr6qMLSmsfPQ+HEGzEfQzHKy9HCwn1CkIwH0lwS7phGrogKeKBUAj\/YRX+obPe0\/R2S4dqW22ppxGo13SzntfY1snmWT4Xxy2wohZsO7SVBdla9fLfNqMDLkkqlMZUbMdLFPYpzVftj322bK6xC3dNXQ93yi3x1PD0cY+sqHvjxrlv9txGG1t7jao79SdWYSkeoowO0H8apll1IyaiB4phIFYimVbTeBqo6TWrLtUS+gZN9aRW0ReoqAe1qJ3Xn5ju3X+RDZuksRT00Rhv8SeOL62kjcSTexxTDnJnjs8ZOBf\/pOQMfkSbaD1do8d0gRbQAppDT7AfhySaVOIATiRt5DW\/57ZyTKJiAgprfkvj\/N1qK2OFLa1F6Hsk1\/hIpf7aAXekDXqgHwYhBEOwFv1RFF6i9Fp5IN7MXbjskb3ySnJiC+JpET2jCeyHdtJQLaDhKKe39Kdv\/sthA22bpXb7XEOXzj2wATbdUvuc7M+wHrl8DKSGOIxiOkLPambrYUNtk620A3bT0rs7NtHV9gR7prm7tl5LWHS30R1yfd1bq2SLdIK+wm7Mxiak1KSaxP7pUm2uwT7luR0S+vxuz0HaTCfqKF2l2TWh9tYgO6t1dbkGmsdC9B0a47ucki8yQTpLiIyWwqJSUipIGbnIWzmUS3FNLs81uAkHczx+REfoPF2nZ3SAVtJu2kEx+SONxRTskke8nhNxM57H4ZxHTkl51EZc\/axPrL57YIMsh+3QHNZZP2M+Psp5fMJsvJff0gXzMBOd0AGpUQRe7ut+6SYjpI9sl4eSGz2xyqf470BG3avXNEhz63dv76S21tH\/22ZqWEPbpDEsukVYsDvqsrnYLtDdt8Z2TlPpSpRDaZTHUUmC3cip0\/SNxjU1s1xW1IbZXBtm\/7nxrrCnuutrOzW97tQxvjTzXSvkzlkNK2nHtL56WY1v0EKDLZ\/V1QvYgJIoh2KIghiYhZNohnBc87WDz9EXekAb2WNraWVsmW3UHxiLzNpMd+ClhEoZSS3xheQlf+SrnFm+8X6e5NtWsrLwF0rDX+k1XaWf5Pg73aV1dIQi6RKtpMlYAIc00oOTcEOOIYJzXj8YXmCmLrHxLq+75SNydNFbmIklOI2\/cg\/RNADtMQq5sFjC5LksFa+yNVoGylBpLGGyRI5JDXTBEPTDJKxFbG2j53SNltO4ug0zkFab60SN0L+6XGvpCd1ueV0b182FuLbuiS20GDZJi+oN1EQwvI3rzyUEz+FVjlZpK58rO8A62SdN5Ia4Le6qS+Zu2Cs9gRhaXU9rZ61rU6yxBdttHavvURwhWI9yukhraRdtrEn1otd1Ig+lJjIhCqbhK0rrbA3XZ9pLD2tX+2JFLL31tjiWRbvrUktr+bQdbkonySIqXnbxRV7In\/grJ5SEco3v8HiuyvFZGHybnlECTse36CDtoyd0hpbRfkqBEBRBd2nLSXkW\/+GHchGJtZp6e7Me2j97ZIttiMUxjw3VNUgCPxySKkivF7AI93AE+THK55bJjkeyWpr4crgP5Jf8FUVyZENnnEZs7aDBWkJzayTG\/O\/3GqMDbiKeZtVDGlcD9Jpus+buqqvrRrhZLo67YPMsg43yUcELwutp2CGp0ByiQzW7JtcC2k4n6XQt7eNZtHRFXQObrtn0B3oiAuOQVAvrdU2qUXSA5tUlaIGUGIaNyKkJdB3uIglO4iQEM2WPXJcvkhKheISe2kI3qvd9NtHqWW8drLP0lR7UGO6bttYPKIZfskcaSAb5wVf5CC\/+33ffAl7IM3g4D+JuXJfTcgKOpIJclP9RNn5KxyiSbtFWukX3qByaA2glQzgpd+PcclAaYBi2IYs+0FIW6NUu9avmtLR2WUkHoSwOSwEk0J84jOt4gVVIp498ik9zRMFqqSlfBTgjZ8UP\/ZBIf8PbEpRTr+EmNmEZJmAiyiEQndEWS\/EeZ5BJV2hF+2HzXEmX2yVwpd1re24z7bhG037ojP6YixdySmrhuy+xeRa7cRCl9IQWtYn23uq5CS6D1dSYeg5XsBZ\/pCYaI72+QQXsQXOtpOPxWjKgN7qjNmJgnk9BCkBljJJoqIZRmI5T8NNm2k6LaTuN1I6WyIbpeTTSn7rYMrmtVtI66wTExjypLf\/JJz7DO3gFz+K+3IarclPOxTnYq+P\/oZSchItxEU7MN+gs\/aVTdIqe0gZqjry4LhEyk1NwDf7DxaWO7JComIQAna8pra\/520ktrx59jrMoh3GYKENRTvtoK92tr3SuLkYeJMZ\/SIoTEizXRZAF0ZEPjXALSfUxvuIwwjAExdEai1EQmZEB6TEJj7EHE3EJC7WRnbfKrpxr46q6L9bKWlkCe6lX9AV6wNv0\/VueS4QURDUfCfMkmukzfai\/tKjttAYuh6vksrqB5myWZtOpeghV8FMIMZEKFxFFq2h6HQmHh3JULkiYzJTl0krmy0HZJy8lIaqjP+KhFjbgOXrpbwRpJ62h0LEordP\/t0E698PyWXltheiYJ0XEyQM+yNP5G8\/xJSUKcX7Oxdm5AGfltJyRi3B7DuVc\/Ipi8G+KxsLH6Qq1R3zclUJSi7NyBc7DsWW21EUE9sHLeb6vfvZeE9kpHayv8Efq4LYcldmooPkto8W2OvobWX09uQWlnDSV1fJCvshXSYr8aIMhWIEviKbvsdqXx1Q8lw8iiI4UqIFe6I0mMH2sBSy6O+SKutRuhx20o5bdSutfLEU19MR0VEAlLJHj4o9AXx4qo07QXxpsU+2ofbaRttLeWTdrqMG6A1kRjtKaT1dgm9SWMInj86eFIrlGoBxq46FUw3PpjNSYLLVkuZyXAXJGPsk1aePzWUXRCbod4TiFdWiDR9iDClpbS9t\/VklbIDYWSmX5xyd4OZ\/g+HKMn\/Mc7s0LeApP4Ox8j97QIXpCcTiA\/fkzvaGE\/JUu0nt6Sr2QH2ukkHgppi05iGfxACHslKVyS55hjobofF2sMzVEc2lZeGk0r6U\/\/DWpHVaPddeBiIVY6Cp7JYOPV1sVwxGAob7W\/e8wVY2vzxFX12M36uKuvJIv8lPiIBWAmN60m6a2btbchbpIi+miuIXWz8QK6HK9r08xUb9qH52J1zJHHsko\/EIu7aNtdZqe1exWwOrbLY1qpW2grkBsnIchB6YgjkagAkZIA\/kuCXBMXkl89IGfDkS1\/32nlMJilEU+DJAyckuWSwwMRC3kQl4cRZCe1+h6BxPRD\/mQDTnwVPL6Zqb1uCZzZKCUFchtPsqXOJLjSGKJ5Ct8njfxGK7BfhxBe+go3aVftIVm0kHaSpfoHMXgmpwYvySHeCnzf\/gor+YgHsfpxdv1tUh64wo+Yp7207m6RmvqINTGLkmJiWip7zWNTdT9WIau+CIFZasUx0iMxhgMwEi0QgtMxTM89\/UeVtWkPhLKdbkod+SxvJJn8sD3xKciprbXClbXZls3G2o37Y0ts9saz8bZRw3TO7re0lki7YVImSEJMQ5\/4dGCWk6L6CCN0PT6E5V1vibQWWiAy9JBrkkgnqIxRklVqSHzZZWkQR+0RSdsgZf6fRmRGIBwxMAyqSnt5Z+kxWtJhjLYg48I0fdawLqr6E4M9LXZpIeXblxZLkhWiSJ\/OJKjyQt+xtc4kdznHTyYV\/N2HsQF+QWdomN0kPaTh6twJB2hUJpMMyiMDtFdIjyXyRIhF6S95JE3PJincEE+7Gv6yoD4KK6ttJXW14raRv+gPtrKR4mqOe2dBuodmJ7FJNTCXkkh8dAV7VED3TEEzdABY\/D+f9tIfe2qAzWafsc7iZCDclauyGW5Js\/ku8RDCWzBD+T30aK62VbL5V7bJhtrh+2tRdh2+89lc3fN35LrKETKZHkp\/XAPpl8QX+Npau2CkmiIUBREVJRFWvSSfvJF2iImKkpmCZZlUg3xsVoipSpuopqqltCbyI37MkGmSi6ZK919rKEcGIJeWI0CulAj9ZB+wl+00CdayvbpEN2Cr7JKOkoNiSq7OYYMkXgSycllMwdyYm7EhbgJZ+DPdJUO0Ty6Qv+oMqfiq7SMplJ\/Gkgz6DDFR0zckdmYhhF4Jt4u8p\/cg2vyba4hifEehbSw9vH5xQdpMs2F9BIbpfQnLiNY62mg3kOf\/82gY6SoVEJnFEdb9EB3TPHNzD11qI7QMP2OsXgrC2WZbJE9sk8eyj1fxjkrpuMLArW7prdZ5v+\/+czLythm9+yFZXUxXCPX1XV2by3cHmiAdsIPGS0p0RV\/8RqrsBEjcVUWSWdpLpmkhsSQw5xIREiKy0JJI2e5jZyQMGklX6Qm2qMnxiKRbsBL\/EEw6mGXxJF9khz5ERV\/JBFy4SCCtLz+QDptptOULbHr46K6pvZQO2kZfJVwiS13eQ1\/4njyjn\/yNm7DmfkjfaAoHJ+JL9Aimk+b6Cxdohj8ga7RBhpDnWkCjafh0lVy4QWu4jZaoBrWSXVZxUU5kgdKG6TXRD46xFuEam89iavSQHqiH97hNbJ4CfCaVnegFc5ILDHckgUYjwnYgEh8RZDvptpCK2t3HJexMk5myRJZLqslOQYiAfJiOaLoAvUzs1F22\/bbWWtklS3IutkRG2+v7Yb9s4GusDtv6eybFtQVOCvhksyX+06FlJgt2f43Zy2RndJexsgSKSBdJIFUlBN8gxfxcfame7ZLYhAmSA5clbSYj+fiVQiGYaUsESf7ZY2UxWkc92XGLuMZ2qASNqOu+ltVN9E9dTPcc2tuU3QIkuCqjBKS\/TyRr\/NXTiQ\/OYyLcUIWfk+H6T7toAO0g2bRZPpEF2kKzaUJNJUGUltqQemkhFyXlXiMaBpb42lMlJA1fIj\/8AE5gjJ6HTm0iMbX+viM72ISBc1wDRW1uubT5tpfi+oTbIQ\/KktM+SaG61IGRzEPN\/AB0bSO5tBlqIhl0kO6SKickRvyRJLCSwYrjFN4oNPtoaV3HhfL1bAEvsRUPstl1ayC9bX29sD6uRD31SKstp3Uh5iGD7JKBsta6SyDZIaMg6AULnpvwrJGsuOwJJb+skHmyR9ezW+4nLSUQRJLVss+GSOr5J5Ml\/YoiujIjunymnPKIsmKN5IYfhiDORiKC9ITcXW4RtgDG+dmOLiMFtMSax9clOpCElVW8yiuKWklhvzja7zAd+MO4A+0iY7SYTpEB2gJzaQhNJh60nDqRiHUjBpTHnkg4zADt1BNQzSzNsBM8ZdHXIRDZT6eIgy58RG11R+rpIa0lVJIo7m1kAbofnxBGf2CbliOYoiNUZJB8ksxbMIG3MINHMVnxNK42hLLpb20lHbSSdrJBFkno2WNPJSSeIpV2su+W0bncY2dd7v\/rsVtlUXYRKtheayy7bYMztwHa2SHlXU8DLfll\/hjrqTGKB\/J3LsHTUIYwlEbhP7SWhZIdGyU8rKEu\/BljiqHOav0l27ymx9xfdkuSTBIHEJlrCSTZzxX0mGirJIn0g6xsV+uyi+pj9k6yTq6KS6ha2zv9DS64YcskZTyjq9yOA\/gY3ySt\/I0bucjzY\/mMpyIj9A6OkGOk\/E5WkILaTiNpB7UhfpQJ5pG06U1fvlU53Y6TrPrGHyVsvKJ63ELHiVXJA6Ko7LO0XAckTu8WUajhl7DTBzFKPTEUoyBH6LBS2NuhGC0kt5yUn7KYXH4Kf9hO35jNKZLVakp9aS+NJL20l9GyDZJgmVooQ0sk2vg7tpFO2R\/9Lt+U2dTrKRL6EZbaQuwzvbOgpxz222eRvpazULwXMYjH46gsmbSjbiDSdpcF6IgNss22SYpwPiCrlghAbKOh\/NwXstfOKMkkvmcWarIXXkuCX0UyJoyQ35xUgmRzVJSdos3s9lUPBiD3Opvayy\/U9fLfquXLf1BekgOSS9H2MvwacsdeDCP4r6cnKtxI67FyTiS1tA+mk07aC9dpj20iYbSABpPG2gTjaEtVESS4D4eo6hW0lQ6A4vQB+vlF1eSO1yTC0ltmYERmlX\/Sjo5yW\/kHgI1AtnQVPZLfvnBHqkg+eQRD5NQqSKfeZO0F3+JK9F9ZNZLvr\/by70tKRWlm\/SRUJkty+WzRGCTJrU71smVda1tgs31fZq\/609NZytstE21ZpbKCli45XPx3EBbqpU1mc\/XURaBGArTYD2gC\/SFXtbMOhbRkAZ70MHnbe+KKrguE2SMvOKqPIin8HyO4DZ8kDtLXOkvveQDT+I1\/I97SX35yV5y9hCfGrdeCkP1mza38TbbSthhjadt8UTWSXNJIvf5CC\/l77yRq3NuHsijOYijc0vOwk9pB+2mjbSKFtF0mkqTaQyNplBaTdvoEC2njfSKp0ppDMVv1NI22l1\/IQCDZaikls+yVo4xiwejMQiT5TAHS0lsQjQtBJFkEguTpBTeSAUZIANkjNSSW9JMSiMCldAKibFChkgNSS8ZJYfkl+bST4bLIlkqx+SrdEcFTW6Pfe1Vb62oxbao9lu\/6w\/9o7D8FsPiWg5LZ0Wsm22zlm6LFbDXOk+3aBwdgJ54hyIaVzvpBz2jCfUi1uARyuo0Ta09kAUj5A+L7OGHnFU6\/5\/2kIK78CneyVM4o6zh6vKAG\/M5\/spD5Scv5u\/sJ\/6yRYBD6KWP9aJGtZfaUklr4J3MlkqSUu7xRl7Ns3kcR3JvDubsvlxsHCZOwI\/pDCk\/oyP0hFZQGE2kqTSBFtJBOkkLKIzG0XUOkdy4j2V4jslaRcuoNw98QYZLJzyQIGnGC9ir+seUqZxUoiAS+5EN7\/i3nEYUjacVUEWKojnGoyGW47SEIhJ\/EUvHYBm8XMaaEiK1fbzQQTJH9sp+eS4VMA6xda0Ot27utKvu5lh0g\/3VH\/pT\/yhbHBtpjS2zlbWWNteKuN0ulxtnNey1btOouhphCNT+OkoP6mtta8N1qA70NdmP1wM+qmMlqS99ZIz845Ucykv4Bb\/gYZyB43EKnsTLuDqf5uscwK34GDeV8pJGhnISOSJ5sRC7UVh7awddqo30LnLgqI9O7c3XX+H1vIRH8wDuyAe5IdfkZFyb8\/i00OicnIX\/URwWvkIbaCHNodW0nBbQLJpG42gkbea4slq2SWtsQgiiagvtoWdRBFdkMbJhjYyWKfyGZ\/AwLiMBiI4JuC0HuYp0RBxfsvgV1kov5NHp2kmj6B9ZhDp6XevpYC2ubTERv2SHPJW42Cbb5aTckpdSAtvQSd\/rDCvlwt0x1859tua2yCrZH\/3r+xEzi221rLJ1sf3WyhXzRPWUdjPthx7QMgp9B9GbelaHaohe0WHWw+pYIj2K6\/gkM6W7HJE3skp6yl3exjVlnY+0Op6HcW9Ox\/E5mJU\/UDqOy4l5OZeWy9JabvNtDpH3kgKV4e06CdJvWInXMk6KiZ\/s4I8s4m2f6sFTuBN39GVhy3IBjsnFOB\/\/oQd0h47TPjpMW2gXHaRdtInW0FKaTzNpEo2m4ZRFLnA8OS2\/ZaikR1PsQQZtpVORH42RE6tltnhkAbfgEA6QDJgjMdFF9nFuvMYjjNfZmk0HYgSWwGlhbaRrUULr63c9q\/u0mp7AJhxEXF\/qsBuCURwx4BCMHriK3prUjtlIl989ckPceNfffbRkZqbmzGPOoltKC7QFVtP9crk9kZ5Unv7uqCW0GdpYW2kRva0FNZl+R7ge1do2VVNqGzyWNbJMkuGfdJRUkkve8B0u5yO4L5VUUkrW8ETuylV4IdfgmPyK7lI\/TiifuZU84wXspJA0k98yDZ\/wAseQGV+kvzziMG7P83gst+fyHJXzcVVuy\/M4lKv73kg\/KStnYuFP9I6e0m26TGfoIG2mtT73RjhtpKU0k0ZQaskqHzmbNBfDF3TUPvoPXkLgOfRCFqyRYrJVwqW4tOdV3EQKSDXpKHElGoLVm3QsZakthZ5EbB2vK3SGfkQL3aQf9Lre0KYaX8OxHZNwD6U1nTbQ3PoX8zASlfWN\/tCYlsAm2Utb6a67SHfSsQu3JBbNYlgsi2FRLbX1tfwunueRZ5DfKb\/8fq89b90vK2jvNdg++tQ57xb7BxfVz6pYVPO2c9+ULoiNE\/BDciktH7iF9Jcmklfu8mvuwwt4LYfzBo7gvlyPMzFzGe7MI\/g1n+VmvIx3cWvpLVnQCrPRB9tQGfekrtzj\/lyQk\/I\/+k5XqBLn4ybclbtwD58rJgUn5p9k\/Ive0TO6TZfoFO2lq\/SbftFFWkuz6BCF016K4qPbTZJmUgGXfFzLwZrRfup9dIDDYTkmPSWeJJf+\/IwXc0\/ew5O5uYzCdFWrbNntiD5BLV2hN\/SvrtO5ekPP6htdo\/01UB9hAoZhOlJodW2ipbWAptAXMJ2jkyzUhbj\/XD7XxO10g91lN8fVdZlddYtt8S2hJbHklsGu2BY317PJb6NfBr+xfqmiHPP77VnlblhN8945MupiFMcpxNFgnaAB9llZy+IZwhGM\/XJWyshWWSmTpbEk8l2p88k7XsmXuLF85a1cg\/NwMn5EzbgcP+TG4t3MSvJmvsFh8ldKIhWK4K9Ml9pygYdxHc7FhTk\/76DkHMiZOS2n5tScmBP73F5+\/Je+0lt6TFfoFl2mT\/SCXtBJWkkn6SLdpIsUTmnlh4zCIGkrU8TbC9VC\/a2k9bVaOgvpsEGKSBS5xtd4Fi\/h6jKUz\/ALXiOzkFn36mt9py91mmawJpbCpmhbbarpdYmO0nZaV+PofoSjO3Yhti8Jch9zcBgXQXpY19oSd8vl8sTzvHaNXCFXz92zI3bf3ltZK2gpLKMFWA0z98y996SLUjDKfk9Xv4FR+vvd9pTz3LIctlyHq3dbrovvUg8NINpdH2sbX\/N4As2GxxIftyUFNkhXWS7LZI48kxLSXOrLW37L\/Xk4j+NHVIyfUmauyJ85p8yQEFnMQRzBOWWKRMNp2SqdJJV84cVcgjOy94L9mFaTH2fmlL7nG5tjcAyOyuC\/9J0+0UMC\/6Z3dIvAwlH4Ma2ji3SbdtJ1WknzJRl+SE20wyTxw2HU0gOayQ7rTo2qkxEfl2SoZJGX\/IoHs7eHNExC+StX8CXRd2pKC7HROlCXaz09jl3IqKW0rXbREK2m7bSMvvP5le9gCsqjGjqgDAaitG7TIt4kvRvnLrnBbpbL5LZYZxtiXe2ATbU8lsGKWjWbYDmcefz8PFHWezJ7kvr9FyWTX4SLtKp2XhtqQW2mi1AMLXBMMqAB7qK5btf22lqj60QEefnnMkZaSR1JKUukjIyQFVJFLvIvPsGNOC1H55c0lv\/QHsrAB\/kM+0sXOc1xeDDHkXCZKPskk0STKzyeK7HwZlpHx2g\/zaOddJ+acXpOxjE4M2dgPxaOxrE4Jv8l8nVSPSfHUfkbnabrdJ2Yb1Ik7aH6uCAp4acPoPgoa9BBr6nHrus47aK9tbD2xjMJlWB566Ma95GoqCWL+IwAF9FT\/WybVtXzyKOrsBqzsAqJNJ3W097aUpPoX+zFBEyD95aQAL\/kn2TCJWzWZ7resrpl7oALd\/cth4vh+eb6uL1WzQKtijW2rlbXdtoXy+gye3L5vfU8cFfcUk+YX6Cnjttn29XbUvIIM3EczVAEYbguUTEOZ3ECybAXd5EJO6QNYuKznJdW4m19ecaQUtJEYsobHsF5eDYbF+Z13Ig\/0wnKxNN4H0fwbH5Po\/gS3+S3fI238jIuwn\/oOG2k6RRO42kMjaEImkU7aTsto8V0jHbQUlpMm+gQHaERNJPC6Dj9x8yJ2cPGr+ktCSfjl\/SYSqMIhqGYptfKKIsX8KYl7mkHLasVtZom0Hfoi5uyQkrJOZ7CUcTbk9VfTvEbnippkEXz6AlEYCkqIhix9CsCtJk20laaXX\/gEIYgE7ycgH1yTm7ITwlCUY1r3SzSqrgprol7YyOtgfP3dPMk86RzHS2f5bFSttbm2mPzkuZKeAL8kvpl9MR1WTw5\/eJ68rq8NlWT6TWMRF3UQHFkRmXERie5JWUwFZvlmuTED5km7yQr5spKqSmZxV8u83oO4308g9fxLi7NJTkhB\/MhLso5+BUdoCJcgjNzA\/5FzKk5iBtwKQ7iVHyTTtIpmkgDqRd1o57UnhpRLapNragdNaYQaknNqDk1oT40iqpQFwqhwRRGS+gredMT0TgGR+FMHEkfaD72ILte0y1aTJd6FWStr9PUm4ZtqN68j0fHoyyOSD0xWcB3+Z6sk0CkRS5ZyDklI16iMfKgAgQL8QMvcRP70Uiz61Lcxih0xTtJjK2yXA7LDUmOCWivuzWbnbIsLsTtshRWxVq5DJ49Lpkns5tgQVbIytgVK+\/yuuVutevsGeyp4MnuZthN18qzyrPVnbMn2kTLaFu9gVz4Kz9ksSyRWdJSHkoJHJfq8lguSS2JkGTwx05fn3uQZJAnfIxX8QFuyiW4GQdwYe7Nz7g6F+Bv5PUsf6LzdIWSc3xe75t8r9JWWkmTaCh1pi7Uk7pQC2pBNagOVaXqVInKUBkqTsWoMJWhkhRIVSiQylI1KkutaTZtoIs0iUbQHJpPu+gQvaDEehoBGqbrNKVW0v6YhyhaQFuqn97GEaTEekzEKOTFImkgrzmCK8p26QV\/XYbmsov9JSFKSm5skJcyABcwFicQpJl0BXJiNxogJ7bJMtkse+ScvJEBgN7S\/2y+xXWNXHZXzbyUiTu2x9V1r7yqus223bbZhttha+p+utWeZH7tPXlcFIvU8zbZ9fc8dLldgG3UPdpar2Ab2uC4XJcaeCGdpaNckN7S0acmFZMgWSDdZbqEyyoZKP0khXzij7yfJ\/AUzs5pOQMP4U\/ch8vzR8rB92gxzaN1tIDm0mJa7NPb\/n9CexTNpHW0iObQJppKHWg6taa2VJHKUzUqT8FUjIpSEQqkApSHclEOyknZKC+VpYpUjbJTaapELWgg7aR72ldjqr9W1pu6TTPpXsTVyppIV\/tyMMdliRRCIWTCdekmMWQ795DKCIO\/BuoQTJTN\/IJHSHMfsZnREB9kGK5iKpagMKKjFRQjJQNyoQIG4Dd6YrNWtQa21xK5NG6theo+7NFZVtnVdM1sqL2wmi6u62jDbZUVcb\/dFk9Dv7ueTi6mNdVBtsO8iZ+3FqlttIgeR0J9iyC8kddSH5ngVYRSSSJ5wNEkSFKLySP+wQ\/5Igf9n\/6ZWjrKJG7CRbgid+YArsKLeD0P5TxePwVV5s\/0kRLwcVpB82g0zaCBNJTm0RZaQ0fpBh2lcTSDztJw2knhFEJHKZQmUneqQ6WpGpWjMlSMgig35aCslJUyUyZKR\/9RCkpJ\/pSaqlB1e6UzNJN6M1bdNZ9OwTeoPsRpqM7FOtTELekuDSWTQM7ybk4jYyUunqONBusWXJBK8oAPSCA+ywbZIxulEGrhp9RCTtySqTJbvETRWyik83WzXsQM\/aT5LNA+2nH7pd11JjZrDjtok22sZjV\/t8LdtYTutWVx59x4z0HPAE89z1jX2yZrQR1h3V16z1W7oDn0IVZjPu7hFkagIVoCeC67paZckTKSQBLLbX7GXnXNm9cZ73Pcr+RTfIVbcWlOy125LU\/mqTyL3\/FvPs4hPIuncXWOwek4F5+iWzSLltAaOkf36QGdpmf0hCZTBO2jo9SXttJ6+kGvaCuNpjoURm1oAIVQX2pChX3vEe+zzk7ZKAulpf8oDflTEkpGCS1SR2shPaZrdZiq9vK6NnypwB+Yg8Zogo3SHnmhqCKJ5CXXk+nyXcaioBbQ5Hocl+QtP+QL8kCaSVfpLjvlk3j1aG\/m7pFX6cJZ\/EQ93acT9JR20hX6SQfZDCtkj9V7XR2gjS22bdceWtPiuWFumZvjSrluLo8np19Kv21e2pfL73LbE7xSc5k8Jd1\/lkIXozvy+Lowd2IvLmMSimK+vJXt0k6qyWSBzwmXRr7yD97Gm3kE9+e6XJ3zcRf25lJHcy8ey7tZZBcX5SJcn7PzGB7J7Tg1K8+k3bSH9tA52k8v6Ru9plA6QzfoFC2mDRRGa+kFnaPR1JjW0iSaRCt9LtwpVJQGUzsqT8UpP+WjAMpK6SgNpSB\/SkzrdIjW0TraVxf5OrZyazB6YiIeYQyGowLy4qqEIA4SY5GIfOCTPi18Ag4hpZJ2wmtpJwc5qXSXuJJagqWKtJb9MlOqyDepghk4g4YYqIe0ii7XTNbYytsky2aPNdAuaWwNRErNoH8R22rbD\/Nzs9wcd99tdTk8PT1j\/MSvpqejO2yJ7JduwwU9ZEdcdJfCRulB1EMQGP2QGkl8Cfj16I8cmCbTZLaMl5IyTk7KaCktPziePOaJvIvv8EwO5ViSVry914vZ26VRgbtwb+7CGdn4Ct2mQ3SdrtJD+kGX6QPF5r9UnN\/RHxpOV3yelxn0lrbRAXpAO6g7baaNdJB20BlaQU2pCnWjydSKptJgakPlqBblpgy+T3RqSkrNLIqt0I6aVT9jgT7WLnobKdEHIzEWDTDIS++SungtKbFWnnANSY9xMkxqYiFuIZUeRjSMl7NcVD7ydX7LfpJS0klCSSWN5KYUw0mM0dEaqls1RDtquDbz+hNti623a3oTK1EEA7EGIRrX7mqkftFAm2QxXAGX03PPc99zwNPYE+pOWlc7oWvxF2INrIad0sSq+hzVURzXBPBHVBBSoAC8t+tweSjzpJEckqoS3UcBfsyR\/Iv9pLhM4aOcUEbJPd7Ni3kzh\/A6XsSLuQI7Lsv12MNZOQGfpNJcjBNzTK7I5TgJt+PPNIfmEvghnaPbFIff0RHqRGPoIp2nPbSbelId6klVff0mM2kDDaCyNJ+aUB2qRKUpM6WmVNTN8lsZW6FncAU99ZQ20uNIjdLojn4oidxogyYYiJMyWcZKBfnHB+WBTJZdUgy78dJ3wXggneUk15ZASSPRJYVUkqwyXK5KKx+pINjK2nmdomNUrY4VsCHm7w64WW6xXdEN+CcFcQTptKNm18t4gxo6SVNaOlff4\/wCPCs9jzz73BXrYNu1iCbUfniCfvoMn3xkqbKIjyuSBneEsF0WylQ5IgclCQr5+nhDpa6ESwN5wLkko7SU+pJURvM1jiVjpIg85xO8jefxcW7DBTg+F+bhHOzLwyfm5pyJl3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auto;padding:0 16px;font-family:ui-sans-serif,system-ui,-apple-system,\"Segoe UI\",sans-serif;line-height:1.55;overflow-wrap:break-word}#nxe-n23frerh.nxe :where(*,*::before,*::after){box-sizing:inherit}#nxe-n23frerh.nxe :where(section,header,footer,nav,aside){display:block;margin:0 0 32px}#nxe-n23frerh.nxe :where(h1,h2,h3,h4){line-height:1.2;margin:24px 0 12px;font-weight:600}#nxe-n23frerh.nxe :where(p,ul,ol,dl,table,figure,details){margin:0 0 16px}#nxe-n23frerh.nxe :where(ul,ol){padding-left:20px}#nxe-n23frerh.nxe a{color:inherit;text-decoration:underline;text-underline-offset:2px}#nxe-n23frerh.nxe table{border-collapse:collapse;width:100%;display:block;overflow-x:auto}#nxe-n23frerh.nxe :where(th,td){padding:6px 8px;text-align:left;vertical-align:top;border-bottom:1px solid;border-color:inherit}#nxe-n23frerh.nxe svg{display:none}#nxe-n23frerh.nxe svg.nx-i{display:inline-block;width:18px;height:18px;vertical-align:-3px}#nxe-n23frerh.nxe :where([role=\"tablist\"],[role=\"toolbar\"],[hidden],button,.nx-theme-toggle,.nx-live-slot){display:none}#nxe-n23frerh.nxe img{max-width:100%;height:auto}<\/style><svg class=\"nx-defs\" aria-hidden=\"true\" focusable=\"false\" width=\"0\" height=\"0\"><defs><linearGradient id=\"nx-gi\" x1=\"0\" y1=\"0\" x2=\"1\" y2=\"1\"><stop offset=\"0\" class=\"nx-gi-a\"\/><stop offset=\"0.55\" class=\"nx-gi-b\"\/><stop offset=\"1\" class=\"nx-gi-c\"\/><\/linearGradient><\/defs><\/svg><section class=\"nx-hero nx-fh\" data-layout=\"faculty\" data-ground=\"none\" data-ah=\"department\" data-ah-len=\"long\" aria-labelledby=\"nx-ast-title\"><div class=\"nx-container\"><div class=\"nx-fh-grid\"><div class=\"nx-hero-text nx-ah-text\"><p class=\"nx-ah-kicker\"><span>Risk Academy, a Nexortium programme<\/span><span>Faculty of Risk Science and Methods<\/span><\/p><p class=\"nx-ah-accent\"><svg class=\"nx-ah-motif\" data-motif=\"bands\" viewBox=\"0 0 44 16\" aria-hidden=\"true\" focusable=\"false\"><path data-k=\"b\" d=\"M1 5C12 3 30 2 43 1M1 11C12 13 30 14 43 15\"\/><path d=\"M1 8C12 8 30 8 43 8\"\/><\/svg><span>Uncertainty and decision analysis, scenarios and stress tests, communication, perception and behaviour<\/span><\/p><h1 id=\"nx-ast-title\" class=\"nx-hero-title nx-ah-title\">Department of Decision, Behaviour and Communication<\/h1><p class=\"nx-tagline nx-ah-lede\">A probability only matters once someone decides on it and someone else understands it.<\/p><div class=\"nx-actions\"><a class=\"nx-btn\" data-variant=\"primary\" href=\"#nx-sec-maps\">Open the twin builder <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a class=\"nx-btn\" data-variant=\"secondary\" href=\"#nx-sec-disciplines\">See the disciplines<\/a><\/div><p class=\"nx-fh-links\"><a class=\"nx-link\" href=\"https:\/\/risksacademy.com\/risk-science\/\">Back to Faculty of Risk Science and Methods<\/a><\/p><\/div><div class=\"nx-fh-con\"><p class=\"nx-fh-con-h\"><span class=\"nx-tw-path\"><span>risksacademy.com<\/span><span>risk-science<\/span><strong>department<\/strong><\/span><\/p><div class=\"nx-fh-con-b\"><figure class=\"nx-ra-sig\" data-motif=\"bands\" data-scope=\"department\"><svg class=\"nx-ra-sig-svg\" viewBox=\"0 0 480 300\" role=\"img\" aria-label=\"Department of Decision, Behaviour and Communication: 1 department and 5 disciplines, drawn as uncertainty bands. 2 disciplines with open courses; primary courses 2 open, 2 in preparation and 2 approved for authoring. 01 Department of Decision, Behaviour and Communication: Uncertainty and decision making (1 open, 1 in preparation, 1 approved); Scenario analysis and stress testing (1 open, 0 in preparation, 0 approved); Risk communication and risk literacy (0 open, 1 in preparation, 0 approved); Risk perception and behavioural science (0 open, 0 in preparation, 1 approved); Expert judgement and elicitation (0 open, 0 in preparation, 0 approved).\" focusable=\"false\" data-nx-z=\"lZPNTsQgFIVfhdz9tPwNnSaFtRu33SNUaazVUBLr2xuKjq1WqSsScjjfuQdoXnRwyAx6miSM88nr0+QAWQm3DCPR0kpAqZrQzWGrCjOgWQLDgN4k0JoCiqKTHo179hKeemuHDhRuyrivmh2QTSBSsYIdYC26DI7kcYyIojoyWtRlcDSP4+JIj1zkimSfqB2Px+SxOHDyzWAK2gdQ+I9q7vRo6fXWWXXDBV6CM9pyGoP7zoSfZ9ZPIC6vvQ1OAr0szbmuf3BBAuHRYaehYY1Mt1uqxvTeDN1Wej8AMl9PwEReBchLYMU5616Tf7vXZO2en56wy3V8wheb3Pjb0kldp5Af34HUvKWY\/xpZp8gRH\/PSM0uBoVTv\"><title>Department of Decision, Behaviour and Communication: 1 department and 5 disciplines, drawn as uncertainty bands. 2 disciplines with open courses; primary courses 2 open, 2 in preparation and 2 approved for authoring. 01 Department of Decision, Behaviour and Communication: Uncertainty and decision making (1 open, 1 in preparation, 1 approved); Scenario analysis and stress testing (1 open, 0 in preparation, 0 approved); Risk communication and risk literacy (0 open, 1 in preparation, 0 approved); Risk perception and behavioural science (0 open, 0 in preparation, 1 approved); Expert judgement and elicitation (0 open, 0 in preparation, 0 approved).<\/title><\/svg><figcaption class=\"nx-ra-sig-cap\"><span><span class=\"nx-ra-sig-t\">Decision, Behaviour and Communication: its disciplines and courses.<\/span> Drawn as uncertainty bands.<\/span><ul class=\"nx-ra-key\"><li data-k=\"live\">Open, 2<\/li><li data-k=\"prep\">In preparation, 2<\/li><li data-k=\"appr\">Approved for authoring, 2<\/li><\/ul><span class=\"nx-ra-sig-src\">From the Academy atlas and the curriculum: primary courses only; numbers mark departments.<\/span><\/figcaption><\/figure><\/div><a class=\"nx-fh-go\" href=\"#nx-sec-maps\"><span class=\"nx-fh-go-k\">Twin builder and simulator<\/span><span class=\"nx-fh-go-t\">The central Apennines: L'Aquila, Amatrice and Norcia<\/span><span class=\"nx-fh-go-m\">4 twin generators, 8 layers, 4 instruments<\/span><\/a><\/div><\/div><dl class=\"nx-ah-figs\" data-n=\"3\"><div><dt>disciplines<\/dt><dd>5<\/dd><\/div><div><dt>courses open now, 2 in preparation<\/dt><dd>2<\/dd><\/div><div><dt>reference earthquakes, M6.2 to M6.6<\/dt><dd>3<\/dd><\/div><\/dl><p class=\"nx-ah-fignote\">Twin figures for the central Apennines: L'Aquila, Amatrice and Norcia, counted from its layers at their stated dates.<\/p><\/div><\/section><section id=\"nx-sec-maps\" class=\"nx-as\" data-as=\"maps\" aria-labelledby=\"nx-sec-maps-h\"><div class=\"nx-container\"><div class=\"nx-as-head\"><h2 id=\"nx-sec-maps-h\" class=\"nx-as-title\">Twin builder and simulator.<\/h2><p class=\"nx-as-lede\">For Department of Decision, Behaviour and Communication: the faculty's twin of L'Aquila on the planet map, the globe and in 3D. Pick a generator, switch layers, run the instruments; every layer prints its provider and date.<\/p><\/div><div class=\"nx-as-body\"><div class=\"nx-ra-map nx-tw\" data-ra-map=\"risk-science\" data-ra-map-od=\"J\/suhpDmyEM6vt\/FeKzBtfv97U9AlgeKOZNVS1zHFVo=\" data-ra-map-state=\"idle\" data-ra-map-mode=\"learn\" data-ra-view=\"map\" data-tw-pip=\"twin\"><div class=\"nx-tw-head nx-ra-map-bar\" role=\"toolbar\" aria-label=\"Twin builder controls\"><p class=\"nx-tw-path\"><span>risk-science<\/span><span>l'aquila<\/span><strong>twin builder<\/strong><\/p><div class=\"nx-ra-tb-search\" data-tw-search=\"true\"><\/div><span class=\"nx-ra-map-seg\" role=\"group\" aria-label=\"View\"><button type=\"button\" class=\"nx-ra-map-btn\" data-ra-map-act=\"view-map\" aria-pressed=\"true\">Planet map<\/button><button type=\"button\" class=\"nx-ra-map-btn\" data-ra-map-act=\"view-globe\" aria-pressed=\"false\">Globe<\/button><button type=\"button\" class=\"nx-ra-map-btn\" data-ra-map-act=\"view-twin\" aria-pressed=\"false\">3D twin<\/button><\/span><span class=\"nx-ra-map-seg\" role=\"group\" aria-label=\"Extent\"><button type=\"button\" class=\"nx-ra-map-btn\" data-ra-map-act=\"anchor\" aria-pressed=\"true\" disabled>L'Aquila<\/button><button type=\"button\" class=\"nx-ra-map-btn\" data-ra-map-act=\"world\" aria-pressed=\"false\" disabled>World<\/button><\/span><span class=\"nx-ra-map-seg\" role=\"group\" aria-label=\"Mode\"><button type=\"button\" class=\"nx-ra-map-btn\" data-ra-map-act=\"learn\" aria-pressed=\"true\" disabled>Learn<\/button><button type=\"button\" class=\"nx-ra-map-btn\" data-ra-map-act=\"expert\" aria-pressed=\"false\" disabled>Expert<\/button><\/span><span class=\"nx-tw-more\"><button type=\"button\" class=\"nx-ra-map-btn\" data-ra-map-act=\"share\" disabled>Share and cite<\/button><button type=\"button\" class=\"nx-ra-map-btn\" data-ra-map-act=\"tools\" disabled>Expert tools<\/button><\/span><\/div><div class=\"nx-tw-gens nx-ra-tb-gens\" role=\"group\" aria-label=\"Twin generators\"><button type=\"button\" class=\"nx-ra-tb-gen\" data-ra-gen=\"shake\" aria-pressed=\"false\"><span class=\"nx-ra-tb-gk\">Field<\/span><span class=\"nx-ra-tb-gt\">Event shaking field<\/span><span class=\"nx-ra-tb-gp\">ShakeMap intensity of the 2009 and 2016 main shocks.<\/span><\/button><button type=\"button\" class=\"nx-ra-tb-gen\" data-ra-gen=\"sample\" aria-pressed=\"false\"><span class=\"nx-ra-tb-gk\">Sampling<\/span><span class=\"nx-ra-tb-gt\">Hazard sampling field<\/span><span class=\"nx-ra-tb-gp\">A density field of the live USGS catalogue in view: where events sample the hazard this week.<\/span><\/button><button type=\"button\" class=\"nx-ra-tb-gen\" data-ra-gen=\"lead\" aria-pressed=\"false\"><span class=\"nx-ra-tb-gk\">Rings<\/span><span class=\"nx-ra-tb-gt\">Warning lead-time rings<\/span><span class=\"nx-ra-tb-gp\">Lead time an alert leaves around each reference event.<\/span><\/button><button type=\"button\" class=\"nx-ra-tb-gen\" data-ra-gen=\"exp\" aria-pressed=\"false\"><span class=\"nx-ra-tb-gk\">Exposure<\/span><span class=\"nx-ra-tb-gt\">Exposure under the events<\/span><span class=\"nx-ra-tb-gp\">GPW population density under the reference events.<\/span><\/button><\/div><div class=\"nx-tw-body\"><div class=\"nx-ra-map-views\"><div class=\"nx-ra-map-stage\"><div class=\"nx-ra-map-idle\"><button type=\"button\" class=\"nx-btn\" data-variant=\"secondary\" data-ra-map-act=\"load\">Load the map<\/button><\/div><\/div><div class=\"nx-ra-map-twin\"><div class=\"nx-ah\" data-ah=\"twin\"><div class=\"nx-ast\" data-ast=\"twin\" data-ast-state=\"flat\" data-ast-faculty=\"risk-science\" data-ast-mode=\"metres\" data-ast-od=\"KwWwtf3193b19APMOHPUbXw4RChtn3Zh8FJe1r+skOI=\" data-ast-data=\"ocHQ7mLOaEtl4b+N+wMxxmuM4FHvHPjlBnmWBZzsKAk=\" data-ast-exag=\"1.5\"><div class=\"nx-ast-stage\" tabindex=\"0\" role=\"region\" aria-label=\"Digital twin of The central Apennines: L'Aquila, Amatrice and Norcia\" aria-describedby=\"nx-ast-twin-help\"><figure class=\"nx-ra-sig nx-ast-flat\" data-scope=\"twin\" id=\"nx-ast-fig\"><svg class=\"nx-ra-sig-svg nx-ast-svg\" viewBox=\"0 0 1200 1133\" role=\"img\" aria-label=\"The central Apennines: L'Aquila, Amatrice and Norcia: a flat plan of the faculty twin. Terrain 24 to 2,805 m; 3 reference earthquakes, M6.2 to M6.6; Earthquakes M4.5 and above, past week (live): live, loads in the twin; USGS ShakeMap intensity contours: live, loads in the twin. Contours every 500 metres from the elevation grid; reference earthquakes as marks.\" focusable=\"false\" 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\"><title>The central Apennines: L'Aquila, Amatrice and Norcia: a flat plan of the faculty twin. Terrain 24 to 2,805 m; 3 reference earthquakes, M6.2 to M6.6; Earthquakes M4.5 and above, past week (live): live, loads in the twin; USGS ShakeMap intensity contours: live, loads in the twin. Contours every 500 metres from the elevation grid; reference earthquakes as marks.<\/title><\/svg><figcaption class=\"nx-ra-sig-cap\"><span><span class=\"nx-ra-sig-t\">The central Apennines: L'Aquila, Amatrice and Norcia, Italy.<\/span> Flat plan of the same data: relief, the three reference epicentres with magnitude and depth, and the numbers below; the sampler's figure shows one precomputed field with its parameters. The 3D twin opens on devices with WebGL once its data and library have been checked.<\/span><ul class=\"nx-ra-key nx-ast-key\"><li data-k=\"terrain\">Terrain 24 to 2,805 m<\/li><li data-k=\"event\">3 reference earthquakes, M6.2 to M6.6<\/li><li data-k=\"live-quakes-live\">Earthquakes M4.5 and above, past week (live): live, loads in the twin<\/li><li data-k=\"live-shakemap\">USGS ShakeMap intensity contours: live, loads in the twin<\/li><\/ul><span class=\"nx-ra-sig-src\">Credits and dates per layer are listed under the stage. Relief in the twin is exaggerated \u00d71.5 for legibility.<\/span><\/figcaption><\/figure><p class=\"nx-ast-help\" id=\"nx-ast-twin-help\">Drag to move, right drag or Shift with a drag to turn and tilt, Ctrl with the wheel to zoom. Keyboard: arrows move, Shift with arrows turn and tilt, + and - zoom, 0 resets, V steps through the views, Escape clears.<\/p><\/div><div class=\"nx-ast-bar nx-ah-hud\" role=\"toolbar\" aria-label=\"Twin controls\"><button type=\"button\" class=\"nx-ast-btn\" data-ast-act=\"open\" data-variant=\"primary\">Open the 3D twin<\/button><span class=\"nx-ah-status\" data-live=\"true\"><span class=\"nx-ah-dot\" aria-hidden=\"true\"><\/span>2 live layers, checked 17 Oct 2026<\/span><button type=\"button\" class=\"nx-ast-btn\" data-ast-act=\"reset\" disabled>Reset view<\/button><span class=\"nx-ast-group\" aria-label=\"View\" data-ast-views=\"true\" data-ast-default=\"a-instrument\"><button type=\"button\" class=\"nx-ast-btn\" data-ast-act=\"style\" data-ast-style=\"a-instrument\" aria-pressed=\"true\" disabled>Drawing<\/button><button type=\"button\" class=\"nx-ast-btn\" data-ast-act=\"style\" data-ast-style=\"b-daylight\" aria-pressed=\"false\" disabled>Photo<\/button><button type=\"button\" class=\"nx-ast-btn\" data-ast-act=\"style\" data-ast-style=\"c-holograph\" aria-pressed=\"false\" disabled>Holograph<\/button><\/span><details class=\"nx-ah-menu\" data-k=\"places\"><summary><span>Places<\/span><span class=\"nx-ah-n\">4<\/span><\/summary><div class=\"nx-ah-pop\"><span class=\"nx-ast-group\" aria-label=\"Views\"><button type=\"button\" class=\"nx-ast-btn\" data-ast-act=\"view\" data-ast-view=\"laquila\" disabled>L'Aquila 2009<\/button><button type=\"button\" class=\"nx-ast-btn\" data-ast-act=\"view\" data-ast-view=\"amatrice\" disabled>Amatrice and Norcia 2016<\/button><button type=\"button\" class=\"nx-ast-btn\" data-ast-act=\"view\" data-ast-view=\"gran-sasso\" disabled>Gran Sasso<\/button><button type=\"button\" class=\"nx-ast-btn\" data-ast-act=\"view\" data-ast-view=\"whole\" disabled>The whole box<\/button><\/span><\/div><\/details><details class=\"nx-ah-menu\" data-k=\"layers\"><summary><span>Layers<\/span><span class=\"nx-ah-n\">4<\/span><\/summary><div class=\"nx-ah-pop\"><span class=\"nx-ast-group\" aria-label=\"Layers\"><button type=\"button\" class=\"nx-ast-btn\" data-ast-act=\"overlay\" aria-pressed=\"false\" hidden disabled>Analysis overlay<\/button><button type=\"button\" class=\"nx-ast-btn\" data-ast-act=\"layer\" data-ast-layer=\"terrain\" data-ast-delivery=\"inline\" aria-pressed=\"true\" disabled><span class=\"nx-ah-sw\" data-f=\"terrain\" aria-hidden=\"true\"><\/span><span>Terrain<\/span><\/button><button type=\"button\" class=\"nx-ast-btn\" data-ast-act=\"layer\" data-ast-layer=\"events\" data-ast-delivery=\"inline\" aria-pressed=\"true\" disabled><span class=\"nx-ah-sw\" data-f=\"points\" aria-hidden=\"true\"><\/span><span>Reference earthquakes<\/span><\/button><button type=\"button\" class=\"nx-ast-btn\" data-ast-act=\"layer\" data-ast-layer=\"quakes-live\" data-ast-delivery=\"browser-direct\" aria-pressed=\"false\" disabled><span class=\"nx-ah-sw\" data-f=\"live\" aria-hidden=\"true\"><\/span><span>Earthquakes M4.5 and above<\/span><span class=\"nx-ah-tag\">Live<\/span><\/button><button type=\"button\" class=\"nx-ast-btn\" data-ast-act=\"layer\" data-ast-layer=\"shakemap\" data-ast-delivery=\"browser-direct\" aria-pressed=\"false\" disabled><span class=\"nx-ah-sw\" data-f=\"live\" aria-hidden=\"true\"><\/span><span>USGS ShakeMap intensity contours<\/span><span class=\"nx-ah-tag\">Live<\/span><\/button><\/span><\/div><\/details><span class=\"nx-ast-group nx-ah-time\" aria-label=\"Time\"><button type=\"button\" class=\"nx-ast-btn\" data-ast-act=\"replay\" disabled>Replay the events<\/button><\/span><button type=\"button\" class=\"nx-ast-btn nx-ah-tomap\" data-ast-act=\"to-map\" aria-controls=\"nx-sec-maps\"><span class=\"nx-ah-pin\" aria-hidden=\"true\"><\/span>Open in the map<\/button><details class=\"nx-ast-cred nx-ah-info\"><summary aria-label=\"Credits and data dates, The central Apennines: L'Aquila, Amatrice and Norcia\"><span class=\"nx-ah-i\" aria-hidden=\"true\">i<\/span><span class=\"nx-ah-it\">Credits<\/span><\/summary><div class=\"nx-ah-pop\"><ul class=\"nx-ast-credits\"><li data-ast-layer=\"terrain\"><strong>Terrain<\/strong> Surface height in whole metres on the plan's grid of cells about 455 by 605 metres; the box rises from 24 m in the Tiber valley to 2,805 m on the Gran Sasso. <span class=\"nx-ast-cr\">Copernicus DEM GLO-30 (c) DLR e.V. 2010-2014 and (c) Airbus Defence and Space GmbH 2014-2018 provided under COPERNICUS by the European Union and ESA. read 2026-10-17.<\/span> <span class=\"nx-ast-est\">Estimate: A digital surface model: trees and roofs are in the heights. Relief exaggeration is printed on the stage.<\/span><\/li><li data-ast-layer=\"events\"><strong>Reference earthquakes<\/strong> The three reference main shocks (L'Aquila 2009, Amatrice 2016, Norcia 2016): origin, magnitude, depth, time and review status from the USGS detail record, the hypocentre drawn below the ground. <span class=\"nx-ast-cr\">U.S. Geological Survey Earthquake Hazards Program. read 2026-10-17.<\/span> <span class=\"nx-ast-est\">Estimate: Reported solutions as reviewed by the USGS; magnitudes and depths carry the USGS stated uncertainties, which the event page links rather than restates.<\/span><\/li><li data-ast-layer=\"quakes-live\"><strong>Earthquakes M4.5 and above, past week (live)<\/strong> Reviewed and automatic seismic solutions of the past week inside the box, with magnitude and depth, read from the world feed and filtered to the box in your browser; the distribution fitter reads the same world feed for its sample. <span class=\"nx-ast-cr\">U.S. Geological Survey; reported detections, automatic solutions preliminary; never a warning. Live: this page requests earthquake.usgs.gov when the layer is opened; the data date is read from metadata.generated and printed with it.<\/span> <span class=\"nx-ast-est\">Estimate: Reported detections; automatic solutions are preliminary; never a warning.<\/span><\/li><li data-ast-layer=\"shakemap\"><strong>USGS ShakeMap intensity contours<\/strong> The ShakeMap MMI contours of each reference event draped on the terrain, read from the cont_mmi.json file the event's detail record names: what one realisation of the sampler's field looked like. <span class=\"nx-ast-cr\">U.S. Geological Survey ShakeMap and U.S. Geological Survey PAGER (preliminary, automatically generated; see the USGS disclaimers), with the product version and time. Live: this page requests earthquake.usgs.gov when the layer is opened; the data date is read from properties.products.shakemap[0].updateTime and printed with it.<\/span> <span class=\"nx-ast-est\">Estimate: Preliminary and automatically generated; PAGER levels are USGS estimates with uncertainty, never a warning or a loss figure of the Academy.<\/span><\/li><\/ul><p class=\"nx-ast-why\">Why this place: One box of about 82 by 77 kilometres holds the 2009 L'Aquila (M6.3), 2016 Amatrice (M6.2) and Norcia (M6.6) earthquakes, the Gran Sasso massif and the normal-fault basins between them. It is the reference case for every method the faculty teaches: magnitude-frequency fitting on a dense catalogue, return periods, probabilistic hazard, model validation, and risk communication after the L'Aquila trial of 2012, which turned on how probabilities were communicated. Data quality: Copernicus DEM GLO-30 covers the relief in two tiles, the USGS detail records of the three main shocks are reviewed, and the live feed is open. It connects to the quantitative-risk-analysis, catastrophe-exposure-modelling, uncertainty-decision, risk-communication-literacy and geospatial-geoai disciplines and to the spatial intelligence pages of the ecosystem sites.<\/p><\/div><\/details><\/div><div class=\"nx-ast-read\" data-ast-out=\"read\" aria-live=\"polite\" hidden><\/div><p class=\"nx-ast-note\" aria-live=\"polite\">Flat plan of the same data: relief, the three reference epicentres with magnitude and depth, and the numbers below; the sampler's figure shows one precomputed field with its parameters. The 3D twin opens on devices with WebGL once its data and library have been checked.<\/p><\/div><\/div><\/div><button type=\"button\" class=\"nx-tw-swap\" data-ra-map-act=\"swap\" aria-label=\"Swap the main view and the inset\"><span class=\"nx-tw-swap-k\" data-tw-swap=\"true\">3D twin<\/span><span class=\"nx-tw-swap-v\">Swap<\/span><\/button><div class=\"nx-ra-tb-insp nx-tw-insp\" aria-live=\"polite\"><\/div><\/div><aside class=\"nx-tw-dock\" data-nx-tabs=\"dock\" aria-label=\"Simulator: instruments, layers and sources\"><div class=\"nx-tw-tabs\" role=\"tablist\" aria-label=\"Simulator panels\"><button type=\"button\" class=\"nx-tw-tab\" role=\"tab\" id=\"nx-tw-t-inst\" aria-controls=\"nx-tw-p-inst\" aria-selected=\"true\" tabindex=\"0\" data-key=\"inst\">Instruments<span>4<\/span><\/button><button type=\"button\" class=\"nx-tw-tab\" role=\"tab\" id=\"nx-tw-t-layers\" aria-controls=\"nx-tw-p-layers\" aria-selected=\"false\" tabindex=\"-1\" data-key=\"layers\">Layers<span>8<\/span><\/button><button type=\"button\" class=\"nx-tw-tab\" role=\"tab\" id=\"nx-tw-t-src\" aria-controls=\"nx-tw-p-src\" aria-selected=\"false\" tabindex=\"-1\" data-key=\"src\">Sources<\/button><\/div><div class=\"nx-tw-pane\" role=\"tabpanel\" id=\"nx-tw-p-inst\" aria-labelledby=\"nx-tw-t-inst\"><p class=\"nx-tw-empty\">The instruments run on the faculty home, on the same twin of the central Apennines: L'Aquila, Amatrice and Norcia:<\/p><ul class=\"nx-ai\"><li><a class=\"nx-ai-a\" href=\"https:\/\/risksacademy.com\/risk-science\/#nx-sec-instruments\"><span class=\"nx-ai-t\">Distribution fitter (magnitude-frequency)<\/span><span class=\"nx-ai-w\">The Gutenberg-Richter relation fitted by maximum likelihood to a sample of magnitudes, with the cumulative magnitude-frequency curve, the b-value and its standard error, and a completeness magnitude the learner moves to watch the fit move.<\/span><\/a><\/li><li><a class=\"nx-ai-a\" href=\"https:\/\/risksacademy.com\/risk-science\/#nx-sec-instruments\"><span class=\"nx-ai-t\">Return-period calculator<\/span><span class=\"nx-ai-w\">The annual rate of events at or above a threshold magnitude from the Gutenberg-Richter relation, the return period and the probability of at least one event in an exposure time under a Poisson process, with the rate, the b-value, the threshold and the time on sliders.<\/span><\/a><\/li><li><a class=\"nx-ai-a\" href=\"https:\/\/risksacademy.com\/risk-science\/#nx-sec-instruments\"><span class=\"nx-ai-t\">Monte Carlo sampler (the uncertainty field)<\/span><span class=\"nx-ai-w\">Synthetic earthquakes drawn from the magnitude-frequency model over the box, the intensity at every hexagonal cell from a published prediction equation with its sigma, and the probability per cell that an intensity threshold is reached in the exposure time, drawn on the terrain with its sampling error.<\/span><\/a><\/li><li><a class=\"nx-ai-a\" href=\"https:\/\/risksacademy.com\/risk-science\/#nx-sec-instruments\"><span class=\"nx-ai-t\">Scenario tree<\/span><span class=\"nx-ai-w\">A decision tree with a decision node (act now or wait) and a chance node (the event comes or not), solved by backward induction for the expected value of each branch and the value of perfect information, with the probability and the consequence values on sliders.<\/span><\/a><\/li><\/ul><\/div><div class=\"nx-tw-pane\" role=\"tabpanel\" id=\"nx-tw-p-layers\" aria-labelledby=\"nx-tw-t-layers\" hidden><div class=\"nx-tw-layers\" data-tw-layers=\"true\"><p class=\"nx-tw-empty\">8 layers switch here once the map runs.<\/p><\/div><\/div><div class=\"nx-tw-pane\" role=\"tabpanel\" id=\"nx-tw-p-src\" aria-labelledby=\"nx-tw-t-src\" hidden><p class=\"nx-tw-empty\">6 live and observed layers and 2 from the twin. Data: Natural Earth, USGS, GDACS, CIESIN, CIESIN\/Columbia, VIIRS, NASA EONET, U.S. Geological Survey Earthquake Hazards Program, U.S. Geological Survey ShakeMap and U.S. Geological Survey P. Each layer's provider, licence and date are listed here once the map runs.<\/p><div class=\"nx-tw-cred\" data-tw-cred=\"true\"><\/div><\/div><\/aside><\/div><p class=\"nx-ra-map-note\" role=\"status\">The map loads from this site as it nears the view (MapLibre 6.9.1, checked by hash).<\/p><\/div><\/div><\/div><\/section><section id=\"nx-sec-brief-answer\" class=\"nx-as\" data-as=\"intro\" aria-labelledby=\"nx-sec-brief-answer-h\"><div class=\"nx-container\"><div class=\"nx-as-head\"><h2 id=\"nx-sec-brief-answer-h\" class=\"nx-as-title\">What the department studies.<\/h2><\/div><div class=\"nx-as-body\"><div class=\"nx-as-intro\"><p class=\"nx-as-stand\">The department teaches decision analysis by backward induction with the value of information on the scenario tree of the Apennine twin, deep uncertainty and robust decision making, scenario design and stress testing with reverse stress tests, risk communication in natural frequencies and calibrated likelihood language, and risk perception and behaviour with the heuristics and the social amplification that shape protective action, with the L'Aquila trial of 2012 as the case on how probabilities were communicated. A graduate can solve a tree, design and exercise a scenario, and write a message that leads to action without overstating what is known.<\/p><div class=\"nx-as-side\"><p class=\"nx-as-brief\">Department of Decision, Behaviour and Communication is a department of Faculty of Risk Science and Methods with 5 disciplines. 2 of the 4 courses with their primary discipline here are open for enrolment now; 2 are in preparation.<\/p><\/div><\/div><\/div><\/div><\/section><section id=\"nx-sec-disciplines\" class=\"nx-as\" data-as=\"tiles\" aria-labelledby=\"nx-sec-disciplines-h\"><div class=\"nx-container\"><div class=\"nx-as-head\"><h2 id=\"nx-sec-disciplines-h\" class=\"nx-as-title\">5 disciplines.<\/h2><p class=\"nx-as-lede\">A mark is one primary course, filled when it is open.<\/p><\/div><div class=\"nx-as-body\"><figure class=\"nx-as-z\" data-nx-z=\"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\"><\/figure><\/div><\/div><\/section><section id=\"nx-sec-hub\" class=\"nx-as\" data-as=\"hub\" aria-labelledby=\"nx-sec-hub-h\"><div class=\"nx-container\"><div class=\"nx-as-head\"><h2 id=\"nx-sec-hub-h\" class=\"nx-as-title\">The faculty hub.<\/h2><p class=\"nx-as-lede\">News and research as they are published, per discipline, with the faculty's other tools.<\/p><\/div><div class=\"nx-as-body\"><figure class=\"nx-as-z\"><div class=\"nx-ra-feeds\" data-ra-feeds=\"risk-science\" data-ra-feeds-od=\"xP0gAoHq0YAjPaEcahaMb6bZNrwoOzfk9sjm\/PIVCDw=\" data-ra-feeds-scope=\"uncertainty-decision scenarios-stress-testing risk-communication-literacy risk-perception-behaviour expert-judgement-elicitation\"><p class=\"nx-tw-empty\">The newest research, preprints, news and humanitarian reports for 5 disciplines, each with its source and date, load here. <a class=\"nx-link\" href=\"https:\/\/risksacademy.com\/risk-science\/research-hub\/\">Open the research and news hub<\/a><\/p><p class=\"nx-fs-foot\">Uncertainty and decision making, Scenario analysis and stress testing, Risk communication and risk literacy, Risk perception and behavioural science, Expert judgement and elicitation<\/p><\/div><\/figure><\/div><\/div><\/section><section id=\"nx-sec-courses\" class=\"nx-as\" data-as=\"courses\" aria-labelledby=\"nx-sec-courses-h\"><div class=\"nx-container\"><div class=\"nx-as-head\"><h2 id=\"nx-sec-courses-h\" class=\"nx-as-title\">2 open, 2 in preparation.<\/h2><p class=\"nx-as-lede\">Courses whose primary discipline is in this department; then the courses from other departments that also teach it, and the authoring list.<\/p><\/div><div class=\"nx-as-body\"><figure class=\"nx-as-z\" data-nx-z=\"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\"><\/figure><\/div><\/div><\/section><section id=\"nx-sec-pathways\" class=\"nx-as\" data-as=\"route\" aria-labelledby=\"nx-sec-pathways-h\"><div class=\"nx-container\"><div class=\"nx-as-head\"><h2 id=\"nx-sec-pathways-h\" class=\"nx-as-title\">Pathways that run through it.<\/h2><\/div><div class=\"nx-as-body\"><figure class=\"nx-as-z\" data-nx-z=\"vZTdbtswDEZfhdC9qia9KxwB\/QHaXnQY8gaETMdEZMkQmS5++8FO0i3A2qVokGtRhzjkJ1U1v0GIKLIwaWuxGKhR0Ypi0YVJOZHxVY5HNfYXDmJ8FdlXeHyCBtpCzcK0qr3cOldY1oIBa+qGq5A716O2432XSmebiCtpuXfGV9JjOoatjb\/b3YRDYeXGsn8Vq\/E\/aLsRe49CNSxZ1vCKCVfUUdJ3AOz7fwzqjL+B3ACrwPwaQt4UIQEsBIqbVavQUqGrA8Chr9w4ie9No8+Rw2A7XFP5cBrLHOn\/Amr8z4kGE+1T0\/nBdDa7lOmUrxVlZCs9BcbIot9XfkRFwFTDE+W7F\/iD\/tR\/9u4\/v5T\/eGIxYRzOoT3lfE870fRim8akHLhHzWWwGJRzOuvKnzcdJlYsjAn+bga7ZqeG4PryowmRO1SyUxhy03A4x7N\/2FFhpMKeemIovvDRuRx95Wp+878B\"><\/figure><\/div><\/div><\/section><section id=\"nx-sec-practice\" class=\"nx-as\" data-as=\"plain\" aria-labelledby=\"nx-sec-practice-h\"><div class=\"nx-container\"><div class=\"nx-as-head\"><h2 id=\"nx-sec-practice-h\" class=\"nx-as-title\">Where the department's subjects are practised.<\/h2><\/div><div class=\"nx-as-body\"><figure class=\"nx-as-z\" data-nx-z=\"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\"><\/figure><\/div><\/div><\/section><section id=\"nx-sec-terms\" class=\"nx-as\" data-as=\"plain\" aria-labelledby=\"nx-sec-terms-h\"><div class=\"nx-container\"><div class=\"nx-as-head\"><h2 id=\"nx-sec-terms-h\" class=\"nx-as-title\">Terms used on this page.<\/h2><\/div><div class=\"nx-as-body\"><figure class=\"nx-as-z\" data-nx-z=\"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\"><\/figure><\/div><\/div><\/section><section class=\"nx-as\" data-as=\"related\" aria-labelledby=\"nx-as-rel\"><div class=\"nx-container\"><h2 id=\"nx-as-rel\" class=\"nx-as-title nx-as-small\">Around Department of Decision, Behaviour and Communication.<\/h2><nav class=\"nx-related nx-mt-3\" aria-label=\"Related\"><a href=\"https:\/\/risksacademy.com\/risk-science\/departments\/risk-management\/\">Department of Risk Management <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/risksacademy.com\/risk-science\/departments\/quantitative-risk\/\">Department of Quantitative Risk Analysis <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/risksacademy.com\/risk-science\/departments\/geospatial-data\/\">Department of Geospatial and Risk Data Science <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/risksacademy.com\/risk-science\/departments\/\">All departments <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/risksacademy.com\/risk-science\/\">Faculty of Risk Science and Methods <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a href=\"https:\/\/risksacademy.com\/faculties\/\">All faculties <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><\/nav><\/div><\/section><section class=\"nx-closing\" aria-labelledby=\"nx-close-1\"><div class=\"nx-container\"><span class=\"nx-eyebrow\">Department of Decision, Behaviour and Communication<\/span><h2 id=\"nx-close-1\" class=\"nx-section-title\">Choose a discipline.<\/h2><p class=\"nx-lede\">Each discipline page sets out its scope, courses, labs, technology and key terms.<\/p><div class=\"nx-actions\"><a class=\"nx-btn\" data-variant=\"primary\" href=\"https:\/\/risksacademy.com\/risk-science\/uncertainty-decision\/\">Open Uncertainty and decision making <svg class=\"nx-arrow\" viewBox=\"0 0 16 16\" aria-hidden=\"true\"><path d=\"M3 8h10M9 4l4 4-4 4\"\/><\/svg><\/a><a class=\"nx-btn\" data-variant=\"secondary\" href=\"https:\/\/risksacademy.com\/courses\/\">Browse the course catalogue<\/a><\/div><\/div><\/section><\/div><\/div><script class=\"_iub_cs_skip\">window.__nxMount ? window.__nxMount(document.currentScript) : null;<\/script>\n\n\n<script type=\"application\/ld+json\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"DefinedTermSet\",\"@id\":\"https:\/\/risksacademy.com\/risk-science\/departments\/decision-behaviour-communication\/#terms\",\"name\":\"Key terms: Department of Decision, Behaviour and 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href=\"https:\/\/risksacademy.com\/risk-science\/departments\/decision-behaviour-communication\/\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;Department of Decision, Behaviour and Communication&#8221;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":61,"menu_order":166,"comment_status":"closed","ping_status":"closed","template":"elementor_header_footer","meta":{"_buddyx_sub_header_visibility":"","_buddyx_sub_header_title_visibility":"","_hide_show_side_panel":"","_buddyxpro_page_sidebar":"","_buddyxpro_page_disable_header":"","_buddyxpro_page_disable_footer":"","_buddyxpro_page_content_width":"","_buddyxpro_page_header_style":"","_buddyxpro_page_color_mode":"","_buddyxpro_page_loader":"","footnotes":""},"class_list":["post-64","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/risksacademy.com\/risk-science\/wp-json\/wp\/v2\/pages\/64","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/risksacademy.com\/risk-science\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/risksacademy.com\/risk-science\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/risksacademy.com\/risk-science\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/risksacademy.com\/risk-science\/wp-json\/wp\/v2\/comments?post=64"}],"version-history":[{"count":0,"href":"https:\/\/risksacademy.com\/risk-science\/wp-json\/wp\/v2\/pages\/64\/revisions"}],"up":[{"embeddable":true,"href":"https:\/\/risksacademy.com\/risk-science\/wp-json\/wp\/v2\/pages\/61"}],"wp:attachment":[{"href":"https:\/\/risksacademy.com\/risk-science\/wp-json\/wp\/v2\/media?parent=64"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}