{"credit":"Taylor (gtmcknight): replica, Gaussian filter, fee rule and qm tables. IdentityMD TwoComp/COMBO supply the residual base.","status":"replica experiment complete; strict raw-return zero-head identity not satisfied","gates_output":"seed   perfect-info      gaussian+plain    gaussian+qm       lattice+qm\n10000  448.261189  443.455598  443.522608  443.663520\n10001  576.779199  571.463409  571.623551  571.977293\n10002  531.886497  525.168028  525.865859  526.411631\n","gate_P":{"passed":true,"reference_edges":{"qt1":[443.1017411146794,571.454483381923,525.908441161234],"COMBO":[444.1953300340616,572.1726816933833,526.2747600532116]}},"hashes":{"commit":"4812a6382311624e1506aca131ca35c378f930d9","artifacts":{"qt1":"8a6e303b662e1a5ea9bb47f31acedd3988ef65b3ddb66d074517aa59ad41ca40","TC":"d3c849db2ac31e567b57e52b80b86e8c24c842e5b4125b9d75c78e3cb07115b9","COMBO":"d360bea6c8c982717b7b43a8069a87013169c89ee3e4da25622db4d880b936d4","QMS1":"17d249ab0c33fc44931d9b105cf3f9e3846a560bd518b67310c2a56defacdecc"},"extracted":{"combo.py":"c5b711a0b4fb4783e8879a484bf87a427171f4a11aa5eb5ec3513c24ead1a796","twocomp.py":"9d3c1833321493fb51bbde4e1b4dabc2f8978bd6d774ee2af8dc8aed13f0f0af","qmref.py":"1dfc9b7a3c2237ff7a93dd9f0af54b9bdab16f2ce0a7eb00784cb4432598db92","blob.bin":"3ac7cb8811ecfb6a17f499aa4e9b70dd55f7fb6432b3aec3b904e11a3dece38e"},"replica2_py":"6e37b4e61e1ffa5ffb1e43912ddb8659105989aa986eb48fcd1d7608f8dca685","gates_py":"603280c1f595ca163ffaf2ba1ebdc7945fdb08dabae67fc53c922d39e1cce604","cached_COMBO_2000steps":"24ce8f359286bccb615c24b9c51b984e908bf0fc9b143d9bc921f63031841d0a","frozen_json":"53b9efdd6e0e034ee5f6b18889b4aea951d4ac3b9532d936f01a4ee244583b39"},"frozen_spec":{"architecture":"18 inputs, 16 tanh hidden units with bias, 2 tanh outputs with bias; each output times 5 bps added to COMBO fb/fa after lookup, clipped to [0,0.1].","parameter_count":338,"features":["pi","belief_mean_minus_mid_bps","belief_sd_bps","w","R","phase","own_fill_size_law_ratio","silent_steps","component1_mean_minus_mid_bps","component1_sd_bps","component1_weight","component2_mean_minus_mid_bps","component2_sd_bps","component2_weight","steps_since_pin","last_fill_side","last_fill_size_law_ratio","ew_fill_size_law_ratio"],"definitions":"mid=log(post-trade reserveY/reserveX); component means relative to mid in bps, missing component=(0 weight, mixture mean, 0 variance). pi retained between first callbacks. Pin inferred when dt>=1 and pi>=.995. Own size=(amountY/reserveY)/.001112; last-fill values are from preceding own callback; EW uses alpha .05. Silent steps=max(0,dt-1). Phase from COMBO. Standardization centers and population SDs fixed on callbacks from choose seeds 64000..64015, each at defaults; SD floor 1e-6. No oracle inputs used.","standardization":{"center":[0.5660190960622393,-1.5943929704924016,11.66266166470834,1.5943929704924016,0.592209852912322,0.8239092515796648,0.8326814463215276,0.2781191881620442,-1.6373272730813795,1.0980755150269286,0.6658407857072236,-1.3942822833174828,9.457333274862577,0.3341592142927604,69.02712864882348,0.005302128937610461,0.8325986482115327,0.831149856218117],"scale":[0.3650598823208114,85.71798239423741,6.862143787121076,85.71798239423741,43.65861248567696,0.7244647857779883,1.3163068225129462,0.810566269957903,87.84364744691169,3.41429178735188,0.3321292442336796,78.90845656446444,5.119312973607029,0.33212924423365864,75.40452736586472,0.999939735981821,1.3163079784726734,0.2390956563269565],"seeds":[64000,64015],"n":173138},"selected_generation":12,"code_hashes":{"blob.bin":"3ac7cb8811ecfb6a17f499aa4e9b70dd55f7fb6432b3aec3b904e11a3dece38e","combo.py":"c5b711a0b4fb4783e8879a484bf87a427171f4a11aa5eb5ec3513c24ead1a796","head.py":"993eea6fad332ddc2cffcf06c3102bb35e3bd18d7277f2201e76d551ef4100a1","observable.py":"2a83420fad2f93ee76808ed316ec718dd86e6354c9f0bd3c841b4b1d8f504e7c","qmref.py":"1dfc9b7a3c2237ff7a93dd9f0af54b9bdab16f2ce0a7eb00784cb4432598db92","twocomp.py":"9d3c1833321493fb51bbde4e1b4dabc2f8978bd6d774ee2af8dc8aed13f0f0af"},"frozen_weights":[0.25209289860669815,0.5119595671602354,-0.5109198431629122,-0.33149689800728394,-0.07074346073291052,-0.2499701413699392,0.3181701610956074,-0.8587540805309065,-1.2938774508133544,0.5344476437675675,0.2278778162242407,-0.026900783220818902,0.4697883029425188,-0.5051567917960875,-1.4506828276669606,-0.3708911093035523,0.6909345893996038,0.28693571875694895,1.114359064588886,-0.03727509078991448,0.39110616215839983,-0.4194996156818558,0.3118091523239127,-1.554336386397688,0.19857321724852228,-0.0006324000849733669,0.10493935728119078,0.4510889389927027,-0.7112398055919623,-0.19662225070879338,-0.9582242953565782,0.11726911576960011,0.3839952525967982,-0.22514238951405846,0.4855432195044014,-0.13723914738521487,0.22028307210970022,-0.5985054287175128,-0.280363648295579,0.09606158550889961,-0.6547441045845355,0.09677001583571881,-0.027751456781477946,0.0348077208800977,-0.011646654818839669,0.9361189952118776,-0.062283146168305326,0.14558857008361462,0.682367134098909,0.5969006860909145,-0.5037798631954876,-0.5248232783394559,0.780853928481371,1.3645640397285261,-0.409774996100995,-0.17716530615067289,-0.34810083785388357,-0.23939154499012172,-0.7689029428319365,0.10652492011372816,-0.8505354331786303,-0.31961273606417095,-0.1419969277715224,0.6788080683946558,0.255987547180525,0.8674898223158514,0.4330012660402289,0.3262046131170657,-0.3669792551154816,0.2550428284938803,-0.017956615241776497,0.26345607689774186,0.17776350208925346,-0.5145771237384994,-0.10380712515947188,1.2618089734492637,0.17513861757594798,0.2509519322373891,-0.02114388691019866,1.1536200604430125,1.374618520097114,-0.43875086605872293,0.1881188545640903,-0.8433264535970619,-1.108960912500647,0.09715345116820712,0.11342255985673602,-0.7961856868341523,0.5975222167357894,-0.3296197199056339,0.44892293567156955,1.0259944962112693,-0.2228524676232215,-0.38967758335454994,-0.6835537751025612,0.6557054510800806,0.2561350684481196,0.9526811620439748,-0.6929163233203691,0.0878033567489539,-0.5634793177232016,0.44189232998671735,-0.27444280069597915,-0.027532841172401627,-0.31224421031761435,0.3210890139967766,0.6943382197406511,-0.8516126189833128,-0.4392993297577905,-0.08485888830367366,0.08034629774428986,0.31652530232219145,0.7339186917325908,-0.37170541201126334,-0.13459343396418305,0.8212919654074986,-0.4902792000808222,-0.6317835945036963,0.9247492532006998,-0.2467524947941736,-0.7280983260679184,-0.5768636845117252,-0.5612361233289114,-0.04897647241668712,0.008206412874857334,-0.22624396704545358,1.245540751151319,-0.8040521316117822,-1.668888627547057,-0.3809995398281749,-0.5628309974971133,0.3706729877696224,0.7275293477223201,0.6260635421402581,-0.3601679707623949,-0.19511490104272144,-0.6406423694740483,0.6913381260882149,-0.7262291798820087,0.3742757518148899,-0.25842097494428695,0.7620835334448575,0.2926543187991955,1.2722081843233388,-0.5774057027634618,0.06117773187754255,-0.1440452462383212,1.1467127014407805,-0.6444557442433,-0.13159318359864955,-0.34965482229964184,0.21650400506562556,-0.24078475957103193,0.7413780929212144,0.604641761868858,0.530415865084471,-0.23235244939489594,-0.3755355150156632,0.688787623144774,0.5263520741674504,0.38782743979233963,-0.29267565918878075,-0.33607028338428435,0.11911558302065028,0.27077634202054607,-0.6188559109908769,0.8589294727265105,0.04584246906773297,-0.16967256784369317,0.8809433875927768,-0.27671213886083224,-0.19096311577431818,-0.12027431388699177,-0.7843708761778005,-0.025314231506835733,0.6079894121956595,0.3463863219735132,0.43180840946449717,0.18064002891025108,-0.2619271723687505,-0.11942704243619062,-0.981102677876363,-0.03624014350923985,0.7043534297225954,0.0782238717806536,0.8342194212813907,-0.4386772988293161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clampf applied to COMBO returns before comparison. COMBO can return above 0.1 although stored fees are clipped; residual clips its returns. Hidden weights random nonzero; both output rows and biases zero."},"hidden_input_invariance":{"passed":true,"seeds_callbacks":[[64000,9656],[64001,10862],[64002,10510],[64003,10617]],"nonzero_head":true,"randomized":["arb","p","s2","j","init.sigma","init.lam","init.size"]},"selected_policy_hidden_input_invariance":{"passed":true,"frozen_json_sha256":"53b9efdd6e0e034ee5f6b18889b4aea951d4ac3b9532d936f01a4ee244583b39","seeds_callbacks":[[64000,9462],[64001,10663],[64002,10400],[64003,10398]],"randomized":["arb","p","s2","j","init.sigma","init.lam","init.size"],"fees":"bit-identical raw returns, selected frozen weights, own callbacks generated by selected policy"},"training":{"algorithm":"separable diagonal CMA-ES, covariance learning accelerated by (N+1.5)/3, sigma0 .3, population 12, top 6 logarithmic recombination weights. Hidden mean initialized Gaussian(0,.3), output mean exactly zero. RNG seed 64000.","training_seeds":[64000,64511],"minibatch":256,"n_steps":2000,"rotation":"alternating contiguous halves of 512 training seeds","fitness":"mean paired edge minus cached COMBO edge on identical (seed,2000); curve train_fit is best population member","validation_seeds":[64512,64767],"validation_every":4,"selection":"best validation of CMA means; no report seed used in training or selection","stopped_partial_generation":true,"generations":13,"wall_seconds":2099.2549724578857,"training_curve":[[1,-0.29729213257092624,null],[2,-0.35929962163410684,null],[3,-0.4070934234914594,null],[4,-0.35857248321451185,-0.2738090465087305],[5,-0.3708736636147303,null],[6,-0.34081529925172976,null],[7,-0.34355603261306733,null],[8,-0.31266913091867005,-0.31108020427540845],[9,-0.3639571749457863,null],[10,-0.3918105925017137,null],[11,-0.351455711170502,null],[12,-0.33212763899321984,-0.26749958068832114],[13,-0.2735723251229422,null]]},"choose":{"seeds":[64000,65023],"n_steps":10000,"C-COMBO":{"n":1024,"mean_diff":-1.407253909835897,"se":0.024138146466833044,"worst5":[[64574,-4.245504349100315],[64445,-3.9155800616362058],[64454,-3.9027831811204123],[64310,-3.6474320190013714],[64946,-3.6443041297705463]],"wins":34,"sum_d":-1441.0280036719585,"sum_d2":2638.2485854662164},"C-qt1":{"n":1024,"mean_diff":-0.7976492633063654,"se":0.02641123419890361,"worst5":[[64101,-4.178044878965352],[64698,-3.9057361256164995],[64454,-3.4865056998405635],[64353,-3.398253431622379],[64205,-3.369288484165395]],"wins":174,"sum_d":-816.7928456257182,"sum_d2":1382.2375576334723},"seconds_per_1000_steps":0.13152140631798376},"report":{"seeds":[10000,12047],"n_steps":10000,"C-COMBO":{"n":2048,"mean_diff":-1.33906979170075,"se":0.01795801422330611,"worst5":[[11232,-4.482227879214861],[11161,-4.04478009030538],[11921,-4.020521538546973],[11284,-3.8859917259519534],[10668,-3.690183944349428]],"wins":85,"sum_d":-2742.414933403136,"sum_d2":5024.246783287519},"C-qt1":{"n":2048,"mean_diff":-0.7416788283150937,"se":0.02043325733330658,"worst5":[[11062,-4.958966713007385],[10162,-4.171042004326978],[10668,-4.144609526021213],[11808,-3.9636216322834343],[10850,-3.853950169939594]],"wins":410,"sum_d":-1518.9582403893119,"sum_d2":2876.921530605186},"seconds_per_1000_steps":0.13018843613120906},"findings":["choose: C-COMBO=-1.407253910 (SE 0.024138146); C-qt1=-0.797649263 (SE 0.026411234).","report: C-COMBO=-1.339069792 (SE 0.017958014); C-qt1=-0.741678828 (SE 0.020433257)."],"limitations":["Strict raw-return zero-head identity is not met: COMBO returned above the 10% fee bound twice on four replay seeds. All applied fees match after replica clampf.","Replica only; RNG streams differ from Rust engine. No contract, engine, Gate F, gas, bytecode or board claim.","Validation has only 256 seeds and 2000 steps; full choose evaluation overlaps training/validation. Report is independent and not used for selection.","Callback invariance replay covers four choose seeds and randomized hidden inputs, not all possible callbacks."],"source_bundle":{"format":"base64(zlib(UTF-8 JSON {path:text})); blob.bin.b64 is base64 binary 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VgcO1k5poiVFwvFnx8aeHtvA/agHM0wXrDo+r0VLRGWEcPxNdgfUVax+0byJu8mTH4TAIDgvTPy+hVF48c10Sxn/sGD3fVl4G3P/6xNpuTMQ4+4ztuxkC78TgfIfyKHQk+cPccnEC/WxCl/ntiAEGB8Ov6THD1GubOrZAvg+DmTGEpekpULQcew2PdWyedMnOhnZUlRL0R+SUhO0sa48ylY6HGy3896f4VVQ6dErMFRrhKjiNvSPtdoReoHrc9K/0ukBSOEGzCcaOoKs/FXu41IJJyX2AAvUxwBx0E6AIpOV4SpBRl7QpWOOYA7dxZrn7ylmxyh/bPr2JsEoQxTtFeDS0Rc6O5gGd4SOaUngJ7cgdhvJjlISQwSzVIGCSdt5CLpI+wlmxitAP004HRB492+mxeAOd62gx8mIYdCFZl+HPCuU/4Oq0mCkkdhNDFMmC8p+8342LvVAhJiK4VcoRtv7S1J0qJrkrOwW//UWGlaRhIHU++oepSrS6OFsag/xEfqcYN/VguBWQnXPVJgGgudwlWBZIS27yxDwL/Y5H6ME06CaEwJmiIvFGn1OW1mnw/6pW9qqtZrt1L/or3sK0L3f18AGU5zcQEL4qoUQezmRZwlHxS7m4/I+8GVQFFExvVp6zOewYedTrLqufcYNxC52Kdr9l/vkMa5Wrz3hrz5UuyGn1PiANU4Z1e/bBjQGi+Pc0tmktFONgtEVvSOAI+U5jnC4b+fmbGJfRDkJQ2UpBOxQEhJNMx16ri1+qtMroWEv8WDEt08kbXoIEIYI1qDU6G7IX9il6nj+MmBjwo5bfp2BhrpiGB/NC3qO3QRmSnOgh2ufJ92gsk0/W/kY4KtXr3te5+kgaRzX4DByBN3DAglxpsp2eplqr86tf25GHCzGu/co7xif+0I/6PMCUQ6Ndlu1+EVYwHEtxN6Ye8bFsxZLL6F8GGcTS0hmdT7CiHat6326/i2DQJ26q+m4tcpTHrqv6So6423/4ZwACerWNwkkbXXpHpExo8zP65IAMJSOCSJAGkMIedxOsneyVUMY7+7bZHa7BCpX7aT1TKX+lZNHfPo1PluuVgBCAWYUq4A4k37LqQsrP/DdkeqPzm5pZUwFtLw21ySBcSEVCh8jMwSi4958skEjqZzuuV5nfqiwYftzdQ5SQC8gKA+BvyTDJ4sxtk70zlJ5EJA/4LCy2mT2CBpM1W4RCPeAI1RWmRDMGwKW6SPE6si+xUCTqZ1maou96uZ99WMj9u26BSyWGOO7/4NTkmMQLjDNiUj0r7TC4r3qSTeJ9sEwOqVm7AgClBINF6SrU1VkC3S4teCfdsxxrw979W7prV4GPRP2ybwj4xvOkdIlpU4ElyT5S3/Ug8Jg4p7IApx7GFJlCyJSRQ2t7uliPDxBZefNrYTg/+4G59JfdjUSW6gvt8KyAj1jlYAx3hCJFah5vDDPchRvJMoQnBMQeIrf5d5xKr/YInCGZZfieLDKtqDfmfQfzSrXcvot7tDsLMfSwoidPMl2URLuNmRfv2kuzTOTbzH+p3a/fz+dtPl5/XolzO0h/fzOjn6Ttd+XoIkAR7P/R9//Isa/xvsK+7m5l/O97O321UY8VLz/50671kpOoHJxEcQhEXvN/8a/a756LT55Y8/LsSd5cvFbDzdnCd3l+M9ZXGr9HE1E58ursEYTzeh49l/ufGcgVusosels7yJGfNbaD7eSxR3jJzo4h83Mb89fr4+x1zYWdz3MYUUkS7ZtBeN1ghO2/PjNZlf5Yg1/ZH54zT6/XH1x2CQ7TftZsm2ywHngyrndtXU+aA8rR6GHS3N8q8s7DCLqUUmd9iUpX1W7LA9Yw2mdViWsRHTGFMYW7L0nhUZe2XMZ2mGH865zjm6jLiFvrke8ArnATdsXuc85Cbnba5bvMT5A9cVOvjCzYhazni1ylecl8t8ZUldq1KZWtOt0a7XuDsf9O4eal2+YNOhUff5+uHleV/fz57H022z0VK36b617wQhL0eGwq0A/zQiPgnaenPQkw1TqmrqbPxyn6/du4viy0NQU6Nly5gGdd1aT3uzSn01e672wmbDCPbt11zE565lBLev+piXmtxp6fth+dl2baNbbepGc/jQqzZr4+bcnQ5rtUK4vO095epVZd3obaQ6QkquP2Z6k1tdflfUB4PyXizXqpS5Ym0PtWa1NnjaGt1lzXfn45fRtjZXli9TV67XqyvrZVGr27PnRW/drMthuDW0WmcUGhW7H+jlZunVHrzqa6lc5f6TLg1qJg+scKIotY4y7xi+VefV5xdj224OVcuL7kr60qp0JlC1ORt2D5NyudwcBvqkV4ayhpNpDbrgz5OuUmqGg4eu7ZY6zQHnxqxUgq44981l0C7ZxZo5dztmoHBec9vdwIWmVpVm4HX0F7WyiJyDHnHesb0CdA89du55UTJNGJk+G2IIs6UPLQPmsefPA2MUVbe6FxrFoEnzMmGCnJdsI2tbC54NjDveqcB2+CK6b3Kb861deeVd21jbrVtewADcfOCjKmzNfOYPA33OG03uB8Yz9VeSzHkE86sE+oGXs9wOTIx3oHlZUWtK/Y0D6xW/jSgoT/myiX4MlfuwPlzNp9SfueXDqj6PMK+2pDvUn+6n/aC8Yekqz0emRY3TXNcZ+qvZ1pbs+ZVpr7xK/RgWb690mijTRmxDHgJ/qdJFusrDvYQ/FG4EpsQONi/u1SYXP3qL/o2YWuUduJyvmrxThF+ZGlMb9LvIMBe2Vw1xPKDWmIrN3386wg/FD2Mq///nx2Qs+v3ZFtlfc3jvTqbPJcl+2OhPoxLa302mOtnftHsXWVJ4d6eXdtbL8BZyqJesAezP9E1D6jSjqGFNLduwYX/c7nQ57K/drGT5g2vUVqV+MKyT/W25I+zPszshl2fmS2Bv9acVhjAK+tCF/RkLvgwMkzfnusFNy4bg6oppkp5bod6GJvkyMme83SbldaKOQ7JlUaXK7yJD4/VXPm0CxniBq2Q3GNWDnQWWxguhsYyapA5zG5C9hIZrW02+mBmVCHZLuopqC+rvITA93gv1Na9tuDNAf/orZ0PS/5oXcqxm19a8vjKeSK/1QK/StS2/UOH1Oza1jbbNc9RfiVd8krsWSW3WDIz1XnH47Qj61yVuBliv2Si2A8vaF01eHqFfMtsVf9lDjpVq2WFSk99tmGvzFvUjdTSH9HXwsyqvj1g3MtssKxQ74O099evz1oZVInPFDlXYO+yr04/tsL1khm3KLFrxtK92hDUndmFEZoFFLh0v8Y6w4zTZMX6/sCjgmg/77/isLuzYje1WH3KVqT3e3rBSoHeon/xeJbVw1VdrvIMgZZshk8kmeD8xNfSfYxgX4w34oUPz27CBsD91WD4E47I7u+92n/KEf353uo3tr62XfLUXdN1paTMk/Lst3RH+mZGpBK1oYi4MFjSzhH+NqHVP+FedlVngRvo0qDWihQFh82LwJOyvb/dXXJtZst1vcFWAx0FvS2R/S/5kmYbdMfkqsJ4Ir9qK2SP7q0XGvV3b84liFuzqlmRaiZo9+r0KSlW+C/QVb+T4umoK0aoh4VYOJ/U7uzrn4dBoBuinOjReCBMQXBtBrc5h9+MAdod+inZtRfbXj9pDRGbDsUseX5BfmCEwmPC0zvpDQ9sXPb5f8VvC5dZQfyE5tgfWeF9c8H6fLXlJ4B+jeEsaY86KL4vqJCrv2YtFfuHy1rKI+Umlpi/L9t2IWTBuH82tFaDaoqnnb3nLZcOmXvdZg/p52Wsz0vPAbhXZE9erTJvyJtkz98ge0K/HJOBnR1V4+5697DGv5j1j9Nt0ueKrHm+PGGJHDOYBF/ZS8NU275jMDICjhQ3ZXy/hKzOyr3JkzhmoTIfsz4hiPG3ds3JgOuxlQHZYo37mgGSaX8U2d+ww43my27ZP/SRAaypkd+lOjN8lAX4dRkSIt9V76xA0yyV7ONCDF7K/XnfSpDaBbhdKzcGgM+k+lOpV2J/+UtIVsr8785a3c4H8Ym6k9q2Iv1K7H5H9NSvtyO/pOanyEHkzwj+fuz1aMEz1WTcCC3Y40itDEnZPbwo8eAENM6pwZv4imWsb9lfFIsluzKrxENRxfmBYQVMjO9bt5o7sxg0aaT60jaegMYVkqZ8enwp7rvN+YBR4WQZnMnTCvzriurC/yFgGpToPmsaG14Q9e3bjNsZT/sonNtnzA7+jfvQyn5H94fh+wDdB5Yl3LP2O7KRu6TvSR63PqnYlYq+2/hTpQkeazUXcLARmlxWr0E8a/JKirP4Ua16/ZXOJN5l2yxt9QCcdkxB/oa56FYRSM3m7wYBPa9KrQnojPNirO+AtTBY4peViXtshu8GowDtSJ+m3YsfQKPAKuMMD4B3sCPgzof7SSfxlHYrXrzEuHYIYpxKDEfHaJjy0uUzz6jwl8duifsUqwAPu6bfxHtf1+DqaV5/sOZfE3+Nx/vYb/eiTgHj1sDoJwrIRDc3DZFq2lOG4O+2XW8q90Q02ZT0ctLr2qFS2Bg29+1JqzgZbvVWypGZvPmnNSyP1NtS7I7NfbY1sSTUfrFaX58YmJFjibGkeBh0evBSNoNpS+T3Tx2qpxuGL/WE5iJycbqulZdBL6w27PA0WQ12uGl27rvMFQDGqV/hsZshBfchfI+sl6O10Y2WNIzvLgQ+zqFzk7kDPB9YDf1mZyF8GPIrMDsX5fNVUbd3kXUlf2+Uh2aMZVDd8OTMOEX7Dzjt2y+B5W1c66TK3m/qEl595t2rYQe2OL4fG3IbdP6lmiQNve5zL3MxzU9I3QfmOj6u6xq0XvlCMWVSX+QZpAEecU4A3iHegjkheyqAkrq7YVsSDqlG22wO+rcLOin3kIwjFoOU9V7/jpRkfBfreLmG9rhHaVp5tn4Bj6Qk3V3oQ8TL3I27bpQl3mnolqGb506zeY+EzSKJW42WJAx6UwCzDGPQ8ByVxV0h1hgVdHhiljhzyVgAeRJRiwAPbXPBalT/bQJuqVO4GfY2t75kPF+KWyps2QLUi8VEE9Kgqet5na30ilbJMaXALEGaD4lohPwD1WLbKHW4+0Wc1GlSgB55jbMheIsRl9swOKqbIyuxAfEQ3WKRU9kHnhbEcK3PznkUR/CBOFks24sxrk6uwUb0FH49gv/jRbfKfJdMj4hFVru1Vm5d8hIJ7CXIl/lAlnqAHMc8A/j7w5hO7D8wW20bArYoq+MSe+METMxG/EY94lqlpUC02ZlnIbaSK8TAfldq1i8yKzCZ7Rf7paxFvhCb02OZ+keaTp/7ShP+dESvb5pK9APdB6tPakyr8kXh4ZKo035ivj2j+W3awwPMMh+JD+uA/lLTh/V4f35XLg/v8xEuX+5bTOSzkUmFw3+g+6aUXZbDqtseltjt40Zu90soFMVT7VqPaK3a7o9Io7G+6A9N0pdZdcEBGJbU6fAtLcG+rk+beGjSbBb5/RWZUPwT3K92blTTbWes9u1KMnAfuDY1O0DT1mVKRgpFk1JpGGeDKp6HxzKsh3xO/6Db0lm0Ng25ar4XWwu6pLGvrUlTO8fFAv7cbEvnBS9CYgUeb9ait8dzMzEcND3mRPo3KjI8svRfBj0PFKEQNhQdD4tMVgBYbUFweuLoXVVrcG+glUCfkX8ae/GpimeOgXmKRRPFhz3uS3rErDeLXelDNEU/xKf7sBuYe8YkxiW8imPrARmgrv/LRTE/bFY3fYT12w+eVp10zqjXYi6SPAtitGehdu7zj9wO9G9VD7lWR/92tDem1mA7KLyw347kAcQ1+1Q/Ka34PJ7HrSCmCUuSPPT5/In46Q54KKmYOOKCnG5TzhE/doBdw6Z55vPvKwiUbRGaWFUM+suHPvZXeCkB67tTSU7ByuLcvmHbjiTEFdqRueVWFv5uw6xlCbumJ3ypVY6/29Oq9dsfLNuxcV2i/pWjzMTfB2gY6bO2AIM5fWDbNB0s2DowSy9H8jCXx8nxAvN21WtEC8XKo1/fanDdNZgV6yKtL5iFksxeiiGWF21bLCowxe41oPj2Kc/CXIq8v2YNtyLT549nVdgnxq9BRW7z9yozAUJhc5S9+sc2bxXQ3KOXYZGjmIiQYiIuGTfFtxcGfLJYLEAXUCn/os11gPKXXkQ6/m/EGQz6CecsSooVS4Kv7Ytfuj4ve4N7dF+ZEzRSmRrz1ym4DfcdyVfDHl7Xe7OQ8vTTPuYH+umcq+XFhj3wDPKsOosUAGQ0/v+aDTf4+GCEOD4HOk02ZW8P5JMiVO7NhNJkEpYN7v5j4pXJjRnFQLXNlgBiWL9Wa/XG3l7bWUf914hZKTLplGLRUdW9vD/0O4l6T2dmJGaqtaZTWTXlQtaPNnbGz235UKJitaluxbyf6OijNI8TBflCSom7bAEm/58GrHljlCp+O9EA1BkHDo/wQpMLihaGFVMLj2ao5iLq2Dr69iHpt5Ie8yhtD+IPRDhoWHw2NXYSuDra55h2dFwcmQBV5ZKQvoorO/VDP2daUz5rGNGpoiKvmXdQqcuDgs63P+dDSvaDcJ9AHzpl8Hhgzu7Hjs6HZD5oKO6z0GuFfT0GcRBxC3NVsy6d4uoMdcM0yWp1iHXkGqGOlAkqkI4+w+UjCuKU0n0VGO2q5wAUrx9QBeCOXbHPP20gxotKIe01djSp7Pl8Zfbv9rKmB0fXZnFdWHDi+4K0V4lLJ4N2BsQgqOV23yl5wt2fNJs7rPYIqJ0KobivIY0o+7zeNJdarpxUu+89DfusDp3mHeDymAnYS8W5U2VEIaUaIR42wqvr7B8YaaZv2VSCXJxuU1azqMufP+v2gcm9Xp2ljaL3uZZfXlpos+BvyZIq7lqQ/RJanL3Jp1+7eM6iqt9cOtIelYZYMIbhNuN+d6cto2uX1e+0hKj2z7AqhK51nhRkPEO9ZHjjHtBJ3wXs66RqvFykPQbyqYl18wooWl1k6YvmAq0EtC74Df1eXlD+btumydIchHo9YbpM2goaUDiXQsFye9pPSe4b4s+KbvTrh/b22t2svaTmqBnuE2bGK1MCcssOA9p/STIq41imO+NbUmnw0UYtNvcDtHYMfg/9mKR5zio+FFbIGJc+dEYLunc+DTXFhW5DLMubDtPERAC8Umy99bcB7vraMDI/XG6x98Lelp9m9rPutksbvo8NYLxvqsKEHA/DO4X130itbs3550rq3osFA13utUn02eOh2fIsN+v1Dd1wqrQZBt6ebFas5DKK0afPWJjjUzLoCDedC827YGgU5zRzx1lN0L+m3AZLUByQPTfAeb6oPhvjtLPQtL2/s0Upfc2No1+D2Km3WLSivWdutJ/BEc2y32+CNVinqAkdCdFXt8n2k30aNGu0fhTb8EIytEnQqvBiZDzZWhbhXDCo9JLd6PUK6OI8Qr+p7HrrGJmjXOVwhHZj31C6MKkOOlC0dWc/Ie+B/dY0/N82J3X7lehNxsezz+6HuB5US+Z8cWS0y5iWvN3m+aT4E+jMQFvGxdM9vMS9efuKOpWdtq8tXVWMTtaccvKVBqZmuILmqqNxq6p2olOWgBrJt3fK9YmZ5k7I7/mqbU952OeP4rQd6h5duCR9WkTUHDpl3HQ0xWdUHtukh7wRFN5FPA1ejmM+WeXell/tsQXYJ1U8Do0FDzjjatZGk2eU996umH3RV5FuaTOBeDXjfxqXlkHjSjrcl4APmHynWsKON+G2F2RHyurxF+0M+L634MABVKVUht8acS5iHX5Ao/28E+pD41nSfTlNcW8BVuAVwCzo2+ePCV/vkNw0Koa0lu7UNFbwAItLTPLBM8DWPHYbwG4SB9oghD9zR/pdE+VtlCTrS9vh+Q363o3iiUZCBf4Bll2lf7JmbfbZySf4iz0OuCx54j/Z6kRVdPu8ojDt+sR5VQ/Y0SrO9alG+yMQ+QQW8Aa4Nzd+Cc9IkLA7c5mKfF/lfkw41eR35a8CnwAe9geDOF530ROxHUJ6Y/O5QHFwiTzY2LGdz3we/4CqvTQK5rCvDuk7532xoHyZjyv+eJ0+TUjbC8ebKOqz6tUMzb0l2X9Hrd1YY9pZ6fW6xak/j4chsKw3G9y9Guoqg9eqatajZjLIFI99sulFP10uh5QW9il6vWu2of+CHwJrxzouu2zBy2MnzTFcC4LBb1YOg/sCjocWCwStfRlaPWxbfDvjCLoXI36x0YG+47+qHyFzxNPgbL3V5e6ir3Lzlww2rRfCP5crwIvjtKDLStCmfrmgOtw7wC/BN9OcOgWOVMh/P9LuoAmUO4T88y90RW0fI6/oz3Y2sGofe8sASUCFd8EmELsMuLXgZOBlZBTJS5EFb2ldFXPT4Qwd8BHp/gF4C6NuIdJv2b+smGwXgyY1X1ojAe4or/hIYYOPAYcbanPfZrMOqDHlTcQ8IbXeIGtWIdyJ/P5BdIa8v076mIT7jOh+Q3BT7S1a8r494FQk7rRHutiiPOgRcbDoIO6D91XvwM3NPPHrONJf409vWgU15ikv7U03KU0B2VbL7k/sGerKPIfKZIu3jUh41eeqUXtWhdQgqZcN9KE0mo7LWHLYmzgvtp2p6NWtpg16li8jdtNp3gbY111bX0V3XLEp9OPaDkQ+bSrAbGi/VTvdgbM2D21aju4XVjRoDuw8wc80J7yHptU3HbuT5PDS16KHHhytLj2ol3g2N1wgkwRkYncge6aWVVQkaJX0XmlNkbXoJeCWS2QABxnzhaws8pPvAGyptUhp8BwplWy73VGNiIy+5DQ2occZly9Aja8B92nqAKu+b/NYu0X6qXqH7WNw1igGoqDdEsgx8BIluBxZ4fIi8pP5M58f7dAceDP6ttzmFBtt4gf2CetQAcqGe76h7Pm5oOcInpcklzqeAQL0S6VX0w4H3Jea4VnGP4GkptG/t8rsm3wTlBkuTqyOO9xppJ0BeWQSPh1OzA5ZKW/IzE/m0sSU+rtN++OuA731VIi9YMnXDFiHyZKQSSIWQF1d5s8IGtD9VqLAW4gtj96wUGSFBSpX6B96m/WKN7mN5fn5F+a3WUZ8oT97tkReg1ydu3bJJk4eBIUwP9lKgPJ/u6dB9sAXTHriFfGGvvpA9DiZTpUyJoD7xypXmfe0wvS+Zq7tgsjNLu9nQ05sjKzvrq3q7jqTzPuo62/LQHd4Gh7BcUXpFvi2afrM+41vfLM9qB5Am2rGIup0dSFZrH/RcnpdKMxs41OSlUuAX9JlVzttVV9cC6xCV6jwPfOGNA99aCIqlAt9YxqttDzmStTQvD7k+NMYRjt+uoLzqLe1LaUGpz2UJTLKsIt3U68hzuBvxgPx+0jRc3kSeODD2QZmxcKUXAphwuaojSdwhrzJsiu+sqY/36k6vVWhrBPgScjmC6fUj3UcyRnx4EZhz0CzmRUgBAXmSTabJ9Q3dN58h/+5oHpOqdMsKiP/ESuBvZGfgffBbpHC+OmLpvfbqaxP2UmQ28liWi7jP+S2fBdwOdJ/y+FwH+jNd2Bd4KuLDA/JEkDb4OXgo4h0o5UDEN5/5vM60pt0M2Z2LPA68TiZc1Ot0n6dhGx3mVmEsvqYPc+kiUw+8uWeyr97Tvk6F6xZUmuV2vqM9c13s66RzrE9PAiAUvPrFHDOlyrTzYOvbYhq49soOEc920iXkq3zf0XK831ct206zAeL+wQ1K+ehennhRKYJddKeLct0d9ibjUbk9vB93ayVrFfXSXcSr3Kq30ctjq690X+GI1tOw3+H7mbEeNObBbm/Mqs2NLVvm2GoxPiuZo2Hjwe419I5lWvwOwca2ylF3qjeq1m1w/6BzqXRvNwp84oInNsr8dmiYdueZ75C3RbURL64MOah0ud/Uc5HV4KFN+5TIuwKyozFfqsbGLo+54+rPdmnPbdfI8cqC25KRjco6nwyNRlBW+a0FHod4cztEfoG8HNRVDRoAxoFRtys52tez7JLOvSofcGvE713gB3jcItSLtM/QaOqrwESqKPE9VM69AUy7VkHyCN6mj/lDhSHPqfDygM/BS3jTAqVEPjgWW6Y9whke6Q7hhuprDHYM5mGFFA+lvbbmpRHtk7XifTmiRsheyG4VcauxwCSXeNEzb1VYFzjKlCGXOoUFr/us4GtVXq8wtMvBDvkD8ZmuyYKg4rInrIvwR57xnJ9ucOuepSE69hAimZcn/OEVQ5F9VYB7RoPlLD5gGrKIUVq2K7fsaUZxTaJ4h7h4D/aP+Ksj3ivc7QD32n2mHyhxU4dmN5iUdXVYPzzlSi/BsDMJ0uWy+zDvjqOyMRy0JrZTKrmDpm7nSsZsUOoOnkr1Qf9w6HhWd3VbnLR2lGd4dtY3h2Fract9cxg1V0FWN7fIjXVzYHatdj0YhvrELXf5UNanKtLR0VKfB+WX6PZJHzQBHk5WH4b0BMqCr11jazcAplWjEdU7fGpBA81bvauW7OhWpucQdsAf2ofeBmXkmSszjDoPXFXM+6hl8Ih4dcUlvjKxwYseFCBwTeZz5P9BowucMgO7bfCXod6LACG2pHeDypo7oV6NasDBAXCwvuVbm/KLV8oH1Mic847KR3alz5EvIv9/4vOh8WCDAq6bwEP9XsSlyFS4VdXvbNr/VnU9qj7zp5Vh2bUxX4xIb2teW/GnZD/9NiqluTNE/lGpcVs1zaCBoFPRanZlAN4O/zCXXK8i/ygTvwI+Npa8oehmJ2/y1Sg9iZD1VWzKPwTElInfdV3kU/bU6Df10JeR/al8wxHyjRlf27RPF4ASlDXIp1y2609s7RKEq7SP14LCeKVK9j/lCMbAqay+HJprDp6f3jA/4B6FhixMmOxubMObBggVfFTXXdg/K7R4Y0T72zY7hLxAj0G90hNQpSljg3IjahzILyTaxwZfM8S+c5My5Sp7pbxGU/S+qyO/DtihSXlOmfIU8LfnZF/LJVE3g1Ga+4z2vVVxn0fwuAGdH/Lmkt1zc8yWM2Mg7gct4330uF2aeCTw2aX7nPJewaT9NPPVuthH53E/4vmTFmNVOD/bDsw6t0xaRXwf85X6k2lfIbdXN1AJQ3LnppebdE2MI/a9dbEPbtN99yHdn2+T32+ID4HPal2/VoqGw63urijfHx3cekkLhxo8vDwc3jX1ZVh64QNF7+QtYNpW7+QsNbrtH4ZP1kTtVSfWU+kl6nV1+8l8UFvIOxomr7b3kVQ2WFAbIxe3esPeIkAmpkWtejR6pvtOy2AIjqaUl7ZnGNWmdRf0Z1B29ZW3Zd2xjLFddymf34FH8o2it4LShBdccxHczXmuWe4F9xo3Qtgr7X/b+pqXH/hMtTS77tN9qDDo+PAzcxbA/ptcX9nlNbeHxn3QAJ+UDDmqbrlqGS27W+IFWx/Qfg/yDs8GU+o2DYfix3JoPEf1Il+rxjaqKqyo0CNOGw67uKU8Z4w12LWQz1bGip4P2NuGEpR6tDUaAX8pKPc5/AmUSIqsBQ9c6ueOP/WLLNAfeE2lJ43SlKfc8nKH+isE1obwYRY0AL4D8DzkJ/UiS9vkV4o+iUo93q8akV1Gv5I+jxr9dMiNYifP6Nb+Czc92v8OeCnL+yu9FQ0ejHol/xxsWPrJprtPNdqq8ALeo/ttt5FV5HfV0jxye3qrkivyqkH4UuyoWXpc8D4CzxnN+DiovzC3WV7spZ1eXqZ1Xh4zzeKSry5ovyCIzD5vVhHcugXdmOm9fX7Cm31W54hLMtiun55QHAEpz4HxW4NgumWawmdAIt7MwY9AiUxyYsOjfa818gYeKhao1oTub73sMU5jD35lWJQnIY/Ls8OS1YP7ubkX93/25E9084Huez3t0xZvN9I7yp7SIeJ/tcLbjJnJ/SUeGHmx70eudZtL17jxykavwA3kf/A34IbJXlVy7RHdpMbQhfSk2nzxlS23B1ztIJ7Bbxvc2LH8kD/4+Tnf5bRt4JSKlYF+oOcu6XkDwg2Ma9ngfcCbDuUPjb5WipC8IS+s6xPw78HQ707KZcse7ieT53KX4t/ToSSrD4WJh7hoD170rkf73yO9B0Kl9NO61Ss9DAdL/bZkra3bvm47MPrmva1szP2qdcvlialI3YYtQzOzpjQx8yBR7YN97+hLqVS3Ry/6g112bKRR+WFZswdLA3meZU91/UkyIGyF7qfeRc1nnh0gqbqv8SiEc1T6CGaGzLtL6Es37cYMOI88DPFshjTHbj/RM5pLxA+QIPPOrkxp/2tJ+9+upfcDBIl9pEtBvQa/NocB/CbqAM9LTbr/80D3qRAnl5Hlgz9hnHrEFwBLXpPAs+hRiifuh/wuKAV8vCI+16f977kN/eZBhvfQj6NyLUK86szAs6wX8DK9xGs5vrCMbFDPIV7yO9pfb0nci8wx73Detssmd23dDapzes6nFyA+zBrgK5U98B/kGmS8hdXT82a3kZ6l5xa10Ag78obni5pvVxyWRwgKIGX4T4tXRrSfCB7Z0lvccveOyV/ukYkxsa8d2AYod0D3xxS+HKkV+27OamFZYbk+2+bSks8OdD9zBv6FfE+3uP6ga7OSF9Ws9GBo9H0wS15MF/dsSPFqaiM0dKp62JFCxKx0lm4GhTB+8k+vQv5xR/buBzp46gzrmO95xU8vIwP5B/JqRrdgq3wILyJ+9mobTfayZznim026f2X6TBryGkFlgfPXDrtluSrJQzOQNb90EH9of4vyEayyiXjNckga6D66HxgGuqLnchDvWhQHkXQswS/Sz+DLLL8HvjVzaZlb4v5sZHO2Zy/sFeun+1jTJ9WP+hs2yGmj6D5K7+k5MnqebAnei/GgnxU9L5d7Kq7txiuTi9oisMTzFqxD+3kdVo70A1NX3KVH9bxiesN1rAv6PbgW+Ob97uDNS1p0v+vSzVn3XtH9XEmV7qv0fEYp6DcnzY7Fqn212zlYr+FgMbHdkmENVL0ll/hqYE96gdmQml5w6Jqe1fTp+YvyjPbhDNNRwHxehzD21ia6X8PIkSw4LX0WliX+MNVVt6zYD3P9SYGzjCY6+Cbsa8nV0CjzVoNHQ7Mo/CQy9aA35YuBteJtE0miPrSrKx6oRoXu/0xDc2g3ihxKHURNj2clc8NLBh9xXeMV4P2AnhOS6bmzh6h+oDz6we4U6Lke1wYPGxFfA5/1VroZVB/4k4p4Wb8Xe6ZR0+VDifZfNI7U0CM/GDXJ/+p8bhkPAcZnrjGh/AZJRg+pPr9t6vf0PMdDpOfoeSHkW+mg8cz3cGJfG/JxxDsRKDfiaTdAXn4/1A/cknjQNGEksEP4h83XmD+8r/LE9UjvcsQru2kgv1ro1ZlhBdaY7V391Yeeh4hHFEQQ/+ByEe8PECeRt+Ua6ZVd8pkagp8iz62CH9N+ZVNBfEO+djssmXYdoYf2qw2X8mD4icXLEfio2eBYOnj+lJtN0++kXymuDcB3KU8Hvs8pFXuIEFmNKtbZ7vMp7SuzFu0HWBRXVDgVUnB6jmFm6/Tch9G2GzvaGi4Tb4SxV21EReT/Ox9+hXZ7bhb5SkUOQbcQcxSX6pS/lbnhsKzEs+SvSpH1eGfM/RzxzzzFRXH/tkX3uQ2dnqdDKHyg/aOVTf6QPOeEdgpTTXruyo10EEXiorTfeA+STPfTGO0bpen5ijLtW6WfmNShvC6n3QaVu9Pnh8XzTu0OA98csaxK+wfP3Omkd37y2J3goRYXvLaNOB0ZjGWHvOFrz7T/VNeDatngw/JhYtBzUO1J0Cg3Z91wUvYsV+0Ou5ZvrdRuW6+OEZTq7Wg1MZ7DepqMbqPWZkH9lp4/CEE1+UaCXXTuEH9Aul9z3B8AF6vPxrChTu27gD0PyysWIsBZerejgacM+DayKmwTAATzCtdnJOwXPlyydsRXXG8Ch9KvLK3wOeUZkQpej9/sFXrT95RXQIUy4ZpB9xuaxNvLz8S7Ddvc0Pcx0lA+R8rbjuj5mVG83wv5ans1EPfrD5NBuRberiayWpqu2sqBbUrjmb09NBTwbSR0rFWdVitO104b+Vmlw5d1kw9a1v4lZxabVST/O70eGMgDFe4Nqn3a75gFxoxpLfLjYdQnYygvolaDjYLKIiitmQp+FyCmIlkrBPqSbXLpKi/PaX/1Kaim+fg1bfO2Q/dtXlhxx/1N0Y9KK171tQVt6efIb/U574NsdZSc3txryDsO7EHlt34hTXH3nu1G/LDXgqDVSMuqVetoG6bQc6NKjc9H6jDqhvSQ3k73quXF7O4WeYc1bY5Kk4lTbgFv+SEsabOO1usoCAqtF731hDyyWeNhz+hW9SXXXo2ZVO/yzorfhXrB7gz1YYN1o7s+33L4a9XjDt2MM/v67qlQiQYS7cEPOuk7+r6CHRi3xsFMS0HtQVtJmJfq8zrwwl/MdGPJZvT9GaVDz0OlecUyl/s8+GNF69D+MCiJ2nHL+ravFTrpFW82kUcWI8ZXd0/p6a2OVDbk1jOrrEqHyHKLW9t+Ytshb/c1JejU0pS8BqWIlRT+cPC6pak1NA5PD+W74H7b9SclLbBLk8az+RJ2X6LQsebIr7olyxgF1V0wnxnysD3i05Gx47USbwd8PzSWdi3NlzbAuJ7lL7Y+D9o7PkZctKsN7swAclaPb4ogxY0K8bax3QiZbAEfCbeAi4H5wBF+laiM9e5Zn57D1Zbim0T0aKUDBKb9v2xHa9J9tdk+3+K1JfAIbDk71LMs6/PWPo18y6PnyIa2brC8Tc8Pd+D36Y5tHuh7SpjtjPxn2tFCei6EvgWVVLr74+qPP6/PtluOvc38hb6Al9QzEqW/PhX8+j8sYhqKamdvVag+lp0U30B2vfMzd+6EIX2pdbQ6T6qKXVxRvSBxvP1Wpu9zi5Mu6OvKl0sveqSZPtL33MPUTUo6y/zuzI8fy1TyI1qIIkPrKU5d5j+fE0WWRHcXtKTwfdhp+OhsRjiFK/+JK4/jvfe2np70Rj+/XPJ5FVu6GOe31/Ho4RofwmPPx7msJ59n+ZvrMGXSwcdih8dv2QlNhPH3545fnPxLFXSTGgonXx8WX+N8K6BLVvSxtu5b/dzfG1TyQXxRNP7ufFxP91hcV1TaDV/Cv2B617+pSkvfavzqS4enhQJ/863F6/FpJUo68WM5uhl//1RH4ec1FQC4EXUF6Ov8x8oCb4UHksICo+9xSYKfF28DfipxQKc/FDe4uaFvc35RUOEn1Rk8nZ24NP4e6zqz/VQM4err4bZfV1QQg54WY/j5ff0TXZ8O92uVw9+t6deWvxsVgj2WTfr+oTLcW4Xa09pJov1pbbj3i97anOr19FoMlsupsbQWmEpcclV89/c3hVm+rsTy8y8V4qUR/j8sxPtjGZfA8F4ybrKE41eTqQbsefJ15Ewuni7V2sF8yTu+7b+78Qj79xK8DuRKM/75HT0eK/LSNRfX9H3juOQtfWTL69C7OafP5/tvdO7i73+X37uLGx3r6v7970BZjJ4s0fl+RpUxb+Jv/3/86vPNjShiJACFCvZOQ3cOjZwn34POhF7GGYWP29X8Jut9y1J13dN+RdVd6uVtpscx4nq8b6eSKsLvk/2xTHoZfz8WjYRRJUUjf4pexn9SXuu96VtHVI9l/P33Rb5wzYZq2InaO+HjaLp9fCvKJIrFfiiFK1Asxp7wy9q5J+YeHlGKzP0fN7J0PIlwKL5Zvf9+9rxbbT1xOi9J77L4cOmPZfxl7JMvhv/rTMDm2dXbF7TPYiQU2Jwch9tfUB3EKZVARLhwAlFw5lgFieoYvFc7Imf6d1Iml4pYxXK8phpGx5LOb5WLvIPrrT+XNB8nNjI++zc5xN9S7aSoSVLzRFS4EwUl3qNXskYqmoNVh1sIhiLXZvWUVENYelsqhH75XgB+N8JpXIN4tHbc2Q1F2Xigs2s6kHzJ/uP36n8LylRTINaJCFvri0sqCXBzs8aJc+qOKgSfRO0tBXZx/LTg7emX538JOV9U0CX5xLV5b87Ozj6Vtv+zWL3+Nbpe04e18NElLeRcyoTbDVZy8SazY/UYKtfSTbqPS1HF5yv4+1NsOV//WYHoLwyye7nZLc8LiqZpGervXEziVEqZU/SnD3GZwvhvUQoQgskkVdluAPEX38+oSlosLsgJHn3zrv5LYalJDZbz7yQF7+C5O0GhM2ffquBu39yzTFIDWUwHerv4maFFxGZxSdVv1+fCWrvHSrQpUTgjpDIvn4s5p0ihmbjMEFXKeC/eFtfyo0C2iwl8PKx8E/9+I5s//vi9uv7IpN5Pf7+Sft58j0/FLf5zDf6Ln6LSxOj/tZRkMdLmNzI6ghe4SebcyYzezODs6OmxO38TTn4UWbigejBbqjC3iN+d8CZWZBtOwoKTXOWdBYvkCLQ6Wn17rw+aJEvppI6gN/7mxLBGBZRCb5siNEVuBfnHNPrqKx6d+vbtv67BDK//0+pIqf/7WPQok/qklovrFGJ/6q3ScercbsLYLjI/lklSlTo/LjNFuBTHSrKvyNkH3+Klhce1pc6b1ftju413WhtagFqKctEtVZBBDwtI4lgdNAU02VCNMFLPZaoVV056q08c1xDqG6ljdeQzSg7HHpUUc2dUQ/xYEOniWHlqukX3uxDyT8osCTUeUUXkjddJgnmCA6Ic0TsmJZ5zHjlwuseni0uq0196z4pdZ7OhKkxUztoTK06kdhZm4oOiorUo7Pb26dwc8MajMej3bmTqsb18q5IdV9hj4Xa1ORbKiwvexbVuhO1SQSRRBucsTCrFUr3WuIKtcP5LScqn/kHJ5D9SVBlWkDpKMCHhpTuh7PB8Pc3g13xN1WipMnuiRioUJLJJCdMf07+bKZjPaRHjOY07wmyoV1G6dn7s+Dz7jfpdbDOp/farXrOiV/F+BTT4ovPFNulc1C76mCV/9UOlopLSQNMwkYETa1BMTBS6PacyzySj8AUWDrHOnSCmhCLl/rsjsu90PP0LfMTFyFphkjMvmobedawId7WEP4vXoZCjOIFDpEAo7mgGp3V+oVidihrFssH1MADKUMgURUmwjfeNtJgIgd7EsqACRKkWriJXogXtYA1kcx/fM7MQ4TbuKXaRo1kn1pdJ9aplOZNqmI9N8W8vk2ry+1IGeoCCtoiGLlnyj+WX+yyx3Ol1FI+PVP/08fGctg8yooCf2DQ5thE7Dbu1t0Gm8tb2vdWn7YgvtlyW72PFBbMfE6NJRozwf5mmTf40ziQqPB0+lo1Arcu4ixT+D1s6J249xQp3VBPoQgid8DPWYwiCeH20iJhOnvDFt52J4yg92jihNfSuU7N45sdT0QSkFgf/IWh1DwiekuPKVOPUP29Sve8z2Fb25xWapG9S2fcLt7Q1s5guz7OXcDRRRpn+OMd13+iynxcpljo/Xn88dnEi1a0ToIszyT0Tr7aZQKaYWsqbw9dijjNBcgPLPgtFi2S54vyZe3baFc+k9OMa+5f8O7r+mTl+1MXH98brKJm5ON+6w9w+riHCzMW5CUYXf9xJp6PNZXQQyW+t3s+crOPqo/+La94GLenxcN/ePs1lqkC5plZomgxb0q9TSzokp/5+PELifO+ahPFpJNGHaPy4XoXyOXpOehGJi1iO3DhZzjSZGfGNNdKd1Ltc6NKn09PIuKmv+IxPCBThw/Q6Rapc04mn947JL0bz8/7o4tMUjy8p6o++T39+f/qJ1Z1nca1P6qaDwmbiEziWnA2EMSTXxFb1m+uOJ8W1wfvYBJmYEBfWmVy73dLF8VFxHZ3Zbt8vGsUX6V9epP/momSFYEGjU5RYLR8FzCf4MEVOvHtBdDzgP/wGcOMvOrAZxaXHAB7E1y+hFDn54+lG+gBgmN4LTPFwnRqL3VJM73379Pp9e1b0d00ojw+tFb3P6cRscS3cPftJUX8DoQOlO5KpI5F7f+kJnf54iRjbXW4/woxwgRVZEvFzqlx/3NJNJCo++iNygsn0q3bstJ1z6o7C6DdTsJTE7kHQ1w7tcJyPIdH5KoMuP7Wfrz+M8cssSCSxdmK8OWn65xOZk40BRa5TD8c/kmh+k/r+82NbIlYIEYtMvDEh1nD1K20AoiZzjbnHxa9NMCrQOcIyECLPz7G6b6kFAXA4jv/99ZLXI9Uhm6GQek7z+I246OfhOMTrr+fiJR7L/52LVm9U6lNfkOxD6p9U4D4nSVdf9kWyOicUfoilc/FZVPF4P3+9+G1JQj2LFVFWqvW3/TSJL3DzDQqBy8kOJPBSKOUCqHfynqzpVawrAiLp5xeiejyRbTxVNP3YbJyM5IzC8w/Gldg7DQkRaZ/Ni4z8AeK9lAtHbb9dPqboTayJdE68SYTgMdqJD588htYKu0ELsh70LIw++RsKSiKxdPnnt3t+Ue6XBP6TRQuMIEQhRRPrFlz+EmsWvnXCw7/QcQJKlKsdE7e4QPRVXMI04fOCsYb/kbJ+AWFCPM7R6cCr4FAUnDenhxZbHFrNx4/hW7wN5ckXa5UTeZG20evfSSjFjAipaxJ//DHu6eLiyw5ilxAdbD52sPkLHbigc0kXvwBdcvlnuAuTUT6D3RezE6Qs6f78bah/JNP+BUjfm/zz2OQLN/RP+r16l8Dx2i/8XkS1N1OKjSeTCD+T9JA56fUXPIjnidb/0V4FWUwM9udfgpUvrv/avGPUShjY/jOMvXXz2ZW9U8OML7n4omPY59GMvI9m5L2Z0bHhxZcdxAw84RIf+INIV76SH+nsf9zycJEwJLKz44S/tDSysmOD3ykmFgu1vv60TNql+w27+ZgMCS1QL1lhu28UiA6Iych/TtknH9nSn9z+PslCwg8U5uKDOsgfkIITzbs6oqZ4QUUK+bm3eSucf/W+5SPA9NNyffiO7xztME5QQS/Co2IWxHuzngLc/kTYSCG/NFpPMidEJjby5OTFJwH9CvqIvcnbQuJ9I0GkEYmn345blkfkT5JwYOLyNGH+HP/+KlSI/Ofw8WqHmP0nwbwl/7GAEDO+EI4Y5eLjaYmgJBM71SdDd8C2R5s/HQeB6MtxBPp+OJ09lf7+/fhvUTHeYkIzxxE7TCI002XO5jo1Op4cfTo52nzshdLtL2zmk6XRWEBGmvERyb6dO/gYxe2/KcLDHXh0dGQm0mdr/aoP2hz72McIfXz7XSdf7fV8dPYEwTJHbEry43iL6m0TgbKIzJcnPuQMSaIYO5rYsH9/z+d/fOTpbav9N486vd2kOj59kjy88H/4EJTYEN64mbeK4ufx+/xO3sgnbswnr/d7f1pK3KEXj1DR/dMP75UU939uNt5lvMF/vjn73//7f8e1zn/8WJ5f/v3/usCBs0z4Pbyk1zAczs/+9jexi352cfUzgwt79Ebj6/c3H5/cWqS+SebxPRXxFtpPj3FQi68f3Lg4PvRFTxn8T8y5Ixq837T4OH8x0vFlhl8tIp6MeGXix9mIp3Q+TeZPpmGi+dWvY//VW6/igZyLz5Xlv3wN49WfyP3je6q/enV2fBfrQyX8v/RAV/warG8iMzjeJ4/v3LwV3U9e05DcJ/nt+9Dj99H8j/jO9a/3IDfxPcjNX7oH+d/ddi79F+8l1m/ELE4N4HqzDG7ixV92xa9zTS5mc9mLt513Usg5DRa/C/vznntMuX7ZYtczpdP71aWT+9Wl9/vV1/FejudtbsRd7//mKgHbN1IyJxo23nH7u5NM6dj1pTiHhV7ullN6XdA5vWswc5m9yHw8mM3I0sdjWfGs1Pubwo/LFD3+XTDWX7f8jhOgezI3xyvemuDsteBnN+8TPDn5/arwU0zBnaymrnf+XbzmQNCGn5/nJkvSbw+RTuMdDvG01/uTNWJWN2IGJ3JM32SPa6QGMHPxSNjPJBB48TvL4g6P74WTJCV5wX1sIxfX8VMM4kVsSKapi+N20ff4YDzYz/h9Djef32Z78sDc20uUfsWSryz8K1DJxG8df3x7f9TZlXh7+Nn7u6fodUigavSqE3pUVcY/T/iPtHsp3tJ3/DB3Fu/HX8V7CElM9Nap6fbb+3MM70/7hJlfICix68yHt1eGqQ8vEHm7Jsars3/HD8L+ycsLT6LHyfMkEO/F8SUUnw/HYPsuREDtv378ETvajz+uUt+ly3yhIGU1SStIBVnOablM6lv2Mq8pOU3WipKiyYqULYBsZi8LBblQyBYKSlFSc8Q/v2iG/jRZljQ1L2tZOSfLdEhFv5Im57P5oobLVXEsJxfUrKIUcnI2LxfFpXJRzWa1rKpmC7KkKLKYSiFXzMlFuZiT1GyuqOVpXPQvFfPoT5ILmqyKiwuFvKpIRTVflIpYSEFcnNMUWZVlNZfLFhVVxsjapZIv5nLoUlELcr5YpGtzOSWLeWcVGYhYkLC2gnYpARzRt6Ji+vGcJSmfk2Qc1HLFQlZSCtlkJXmN2snZbB79xseyWQVCKMhZLKn4k55XOXnTJokeejhiM3388UfOcYvuCIvPeq4/KjjZoq9omuMonjYqSuNxPu8XcVzJyaOc47m5kSYpXjbr5BDCvZzqxU/FHNlZ3KebHxXRRBop/kgpqjlPVYuao6jKyFeLjoIVFrO+4qCJk/dGefSaz+ZcWYGjZR0oK+4zeSV93KWm5TzPKfjOGEIcj13Z9X3XlwpuLivJo1Eu7+VG46w6hsqKPkwh6xULmHvW8xXAk5ONu/zwuHfcsezAqmQJHcs+jVEsqJLqjXPZgucW0eFYLXiFXF5xNV8ajXOuqmRHyig7Vv08BFF0446PlCXuMzv2XUjPwZrkXNH3i46WG4/RgePnlZE2GjujbMGXXU9yit5Igvko7khRhEbHI02O+3wnwokIMHpWJSOCknP+KJ8djcYelDFS0KEr+6pWVEfjwrhYVDxPdnx17KqON87mfImG/vHHv8UDTBTjEi/MFfISxoSpybDzLCxQzV9COxr5joK5K7C1wiVMNqvkiiosMyuR03zRSsldwhUKWVmB/RULmvCOogxXU8g7imit5siLINmcVIB75LOyphRiV81KefJzTYOvSmimFi9VJYdLcb2WzRa0TCp3qZCnZDENmIuqxh4EvwAIYBK5QpHGLKqXmqQq+UK+QEMrWFL+Eu6dQ7tiriAVJVn75UrMG+2K+UtFUoAK8YGimJmGnxyuhJSycLW3BRQhazQpFAmSgCEENTQo8IV+C9f74l24JHd6D+uPP97fi0jHvqGLQhGOl1chG/i2UMaPPxJET9Ql54FxwAEVqFnAhPIC+bC6PMYsZguSDEPNUGf5rKRlNYgQmAZElMVBwJGiFXA5LA7gpMVNIZKiklMgmhyaSvm4rYy5FKWsks0VSABCFjmgCo4BgzAcLhIN1bxazCuSSiClSYW8AEBZy6mwwjyBJ6YkRJTPQRtFAEmxUMRsxdxlYG+xSMArK4DyYjwhiJB8AjCO61VNEoPDDooQDNSnyLH6aZkS0BiKhy0WJLUYD45hYV4qIBVCgqTitSN6wJAkLSfl8nk5J7AbOsspeeCqhnY5YVGAXi2Xh+NjjpqixsAPZcAApALa4ifuUMoBavJYclHVNESU2B5pCAQrBBfIVyODR1Mlq0GaBcwUy8nn45bZrAoVYSYwnSzBN8W/vAJrzKkFWFwhtnAoEYFDzhbJr2RZjtcNegRLI5akKjDOXKEgjBrBAWvB9GWKaJiZEBxsQcUaMU0Z1h/LGPCMcaG0PMykIMfzxF9QhJyHRQCv6W3sdBQmSdrR8jnYdVEVykBwkckv8+To9FptsSRach42mtcKhA2xHUFZ8DEIMqtICJUCFrAUrFSG3SLeStnYkBBmSRRKMYeFZhW1GBuIBEuFuUJzRUlKDBnOCM0jxgKEgCLxPGVVguwoIGp5oIiInKR+qCKfJwloFDjRsJAnWIGsMB0sKp+0LKJ/UhspX80mllhE/wATmKgCBItnLyEuS8UijBOOpBUTowVIKSADClQMOSQK0XIF6Jmkgl/FYmI5BaIGWcTxApaG2C16xTCwLtAIsJxCNsFF2DFwLZtTQD1grDHRIe8oAAJwABclfpAjgC3kIFJILh4nD5OBecGR4OpQtABkBLc83FlViNbEcAazBtWGyckQfCIjhRYmjBZL1OJBskVADLy8QK+LRGMtdiz0RHMGyOdUkl6sDJghrFtBF1KWrDe2ugJ5M5EjTDRXyMc2W8BENURsMgA1W0hQBYIhbwDcA21j+8RFiC+E4gUFQHScFtwLMoGqinAnWWANFIaFQkpYeSHxOBkiIKiCegFyYmwVkAs4RJAmI8mKSzEm7ACUU1JgbmocLGRihgUkrRi2kCyRnK4Iegn8Ja0XkjEkon7wSggjmbYEdEJ0w+QwawCgFlt2AdADFIVIIOlszCZxvgiyIcG20HNOSRQJNWNxCLQ5dJzAdhaAJeEgAFCjNamkS6gP6wYiQPAYoBj3CXKFwFzMF6mllggD4oMOZNGpdjR3AjoA3P/T3pcwt3EkWf+VXm84AJBNEN0AGte0YkVLGnntoTWSJ7S7EIIBgA0SFi7h4GF9+u/fe5lVfQANipI1GzOzmF2Lje46s/KurCyIAfCdIBDeV69i8hWAo1YFXIQfQuKjIwgjYIlnyBcVwQ5RCVQOTbglHJaUhP/qgmEtAw9IJQCUpAeSDryWsD7wKBArOGEdfdUaSpNY0CovBwcZcKrKeaCtyVKCKoEJBrFaHA+IokmVWrk7WifD9FAMbMtADSIOPTaAMVA4QBey4sABDpgiFEy/rro+uFgLUAQrBzK0qoaZkURqUG9oY3iKfwAfeAcYB/C1Hi8PRlKvV8k+0FKgYwcmNsC2yI8rxE5dCKAVBRZGAZ4t78AuICnEGgFV1pS9AcNbUDygrvjgcy3huGDTQDIOnJKqqgSJeWGVQTgNanWKl2B3mCMmj1UFz6zqyGGMQP/BWDBpoLKZD5geeBLUXMoc1DcSAwoUtSWgnQcrpFatK2Fw3SoeBSgwVy0iWGdVqEoYOWjF8ww9Q20gdrZoFBmOLVYccBALBe5VMd2DNYmYBdVzhZXlYppgiaSUmug/KkLBOWgacS2UFQITsKgeMbhBbbrSNMLfI+A9MhmQRdUKnFod8h8VwE7IidVohFqIdYBKA/5nZH0NXAukTnFbAbdQnAvIm4DDUDewHoHgHBRK1MKgSDGtlhFMQBiyOKwKGEBVmwSrA08HHVSovjSN1gZuABHWJM43fKOJEXuq/A+L0rLUVsGCN6ij1mAZNw1tYHg+WSPkYo1ag5mnD+4FUAewl+ukOuUUkAiYIpkX2JpiThMsD5IKcEX3Td8YwoHoPD45Z8WyPoy9RYQDp4OFa/GOkhpaY41MoSrwgNYFSdGi6GsFhjdTbQK1QZ76gqCCM4QD6AdyH+RipC+oG8QLHkFya5leIOBo41YgvmGeezVDbUA1aBlAPSBdrWm0OwyiifWGnKbFZMCOYVBdxDuAS83wBpoCc4R2W6OaoECDcgBlG5MhxgUtRS6QJJa8Sk0WAFYVFowWggriHWqgYR4YmaiuNZJr1eqqQF4AEJgEAgUlyIoR0o0GawO+ft1KNLFDgPBVWgK+sGEgEWRfhd9A9HUz7RqWkTRRqxoVDpIMtE+8hAnTMg1Wa0RoYm5LcF1NFpAPFrwC5oOlq9cDg6y0RiEpoAZVKKVl3jAD0CmoFaPxVJ2HQKAUxkSAICphQYvgvk00C27W8IwiAJsEjAPqAHmUZcONOjUvKBLguGBqquuAm3Gp0UGjoSYDiBVSBt0HNCZqqmUCNRtkjGBoVaG7E10FaOx1unEa9NIYg0cMPrAcLGbT8Cz6ejzoBGAcFR5cVXkILOO6QN0EowiMJRJQdqFNYDVwRVU6zBVwAOUBlcDJVXukKon1gonQoBWltWG1AvmpPMKSJUOW6gAj+SMgDI0lMByiwcX1KHorNHsMf6J7rEolu0H88rQsmBinL4WBcUb9ZB/U2iHmMX3LSsGIqHxTX6NmpjSJyUGZBJfwaKgqYgMhaXWQadMVowZXlboExDbNaJC0KhMQW8AZciK07hn+CsZOnz4ETkAlwGAxrB6AlbiJz5VAuRmsVtQEmDDWqlk88E9KGqwPUAxMRWkNwg/SH8CEuG/VZe0r5EpVav0YRr0aqM8LXAM9getBDJmFgzKCLnxSeYvsTN1yUBE80n0Ti1Kx6iMQDCyBnA8Tr6kQAYhAVTDFKX+8uoogsD/QIOyGBmAaxIY2FXPAAyAAj1GLHBgLqUxpDkbeVMsQY4PcogzxeATP1KY7sM4+0Gi9aeDmg1xp8Xm0Poz0pf0FdAMYK1yNWFQD7zFWKO9kSE1jhrXoxgTtA3xew0hAmr2Yt0/eAYPC2KWgNuKHYEK9YlTQJnk6B4AlqhjJBERu0CgHwoEeAtUCATOaItCmQE9KCQAWvSMtmlxVahxmSnS+ABvAqoCINc/gLLVaqspoNTAdUcUJyD5REmzekiy1WiAdkdyT4UNDEz8p4AmRYw0+jKwWiF5OTaNeTUjGo/ijRwnKaFOwgVK7RaO+RTPU2AN4R7ymp8H6GFoVclnoOCAv9KX+qiZNZ6A2mqwafRO8ALgFSgJuoA/jCvapiMAsB4p65OkKJBC2GDxYQMzNV9kCQxsaY522R4OCFghLHgU5A0rA+vvWMwM6q1SqFE6+Nd0rJCgyStpVDdVrfXomsGR4AepWpo/BwT6s0fz36CZWVxgQAwRDexKDVekJk4UimtwHqpUWpFIKhiLiF3WFIUAVbAKlwfqx5HUjo+t0NVDdC+gTqFfVDVEHOVWoqbNVTykScGpQWQUzozWuJioBWycvaXFkSvjUNlCUjKLqqeVYEYOKwg4o5FkditYikA3MAB21jAuE4g3ULI56kJBSKdUfsO16IO6IumwtgI0Esm8AJlGzrh5PhDmq0fxtNQ3LhKEClQjdA39B5CqwsHAVCHNoZnSWmBGJcKGMAPH5RksH+MEv6R2hwugZQqnS8oK2Sj2uIlAXFoMXxFy63YxCjPUjFwPqN0W+qhMVIpsuNgwJoseYDSBMej8wGsxWRRh4rUdvB5SjOs0t5ezg5qR4WLIV7raosAWaBvTyYHlpOsgcQdkVEJkPjb0pkpJAr4FkIBSoVBkGXqVdD1rFspK3NCwja9I4h/QlUVerVlZA7oDLY+QNKga6HYS5omGADGgNDFUNu45WfRrEXHZ1PNG5QR+VKBAKCyoGdVpwFZpqhpIps6nTiLHWsL4k5SA+aazh694K9R5wSeAEgddoWjM8oLZFIQ/RXjdKKigG/0HvxINvXHu0eMHiUQr/b4xwkAisWVrIVTqqjJJJ9RD6OZQD8IO6YYvkhwB6nWqz2vD013DkdRJJw9hUIiNoBlTIi+pNqwFinE2xyiB2vSBx53p0cNEB0RCt2aNVSCYNJk7tSoU+WAbYByQqJGxLd5XAPMneq1zwGt0BRvmk5ITOD3i2yNt16oA3faoAKLo2/osKJBmWkOsKiQwEraruW+FuW4sKKLc1VL2D0GxW6WoP6B30lHcApbEiynW82PfLNpvU+oWHGx8aFC1YEoGY1YHxA9Cb5pHj0ZflGy8vCAraaoUumJbpmhRCbZj8pGFFNHCUqj6GB5qiK1TN9grwmkocpH6dviYVFTSDa6J5N1QXIcJXqZuCvQPKwCiz8ngbEKubZLMt5UhVihhQPyBDBcswCrRYFZzx2UJLJS8sHRr5PsevpgTZd13c2MR8g51ejeQEE4imVWAQzOPUKRJpxGEQCiWQpU+nMYQFiN545yGAwbooDWkGGZ3cpw4WsDxdQ6o+wvipQHJSqjWaRrOCtK7RFQ1WSoPECi8yjhb9A1QwBEKeT8OoBhDTHDXcA+QNhQfytUa3asPiNsiZlhotZ6NYQbmgNKRzGNA1tqhHnzhJq8mtCWuwQHiBsMibA922gcpEPgSMw4Ibvs5dkwrtdyAtFBZj8XKLFUgJgQNJUguM+kbeBl4ImQQVzjMKXE1MEbQKRPAqxqFJEoOJCrZUoVLmG8ZFjQrUCgIDt1BZRQ4HY5JeiCqI1VRvciuajmT8tUiEliDcoblR0YS8MTAWo7IqfnBioWWI7AwgUFmo/gLAoUVSC0RfbClqgzNyRwDogUEFwvSF2VBtpPMY2CVGEzUwQiUQ2xCYqfwHPJsmJgfVbBhM8CnPQFVNLl5gLGzgaIO7MQHJuG5sHvBr6tNUUSA+VFwB9zFE7neDNlt2BwOMFLxHkE72UlRxJ8uEIeFTtaxZfAciUWOnyKpzy0/9brCoWqJN0IcUxHZDlZ4biCjolIFVSbn3Cf5NE5i8qffpO/c7ngxbPSa8Ms5RwRqOyXaROvw2iCbzWz283V+vl+PBhpuC8YnnV9HyRKJjJG6NOXg20UpOMvUdRmm1HebgcOYjPbayTGXJkHP7EiRoMj1IRgGJ1imX+cdP0gNowGHVOfnRsTPbimSbM+CEWcZePn/93AnxW9NkXI6XDL4r2t/9wWqRiV9juOFOTg2HrTycASXCXDEJG4327NUrmREPlzEuLa7Zn+BVn+cm381+5XEkfI5H89t8PCuyL9cpoLGL6fjSxLWg87/+JTWPdMkP04v3XnRSN0XjPBqyEDwqsRxFw/XJeDaaawDulclScbyY9MezzJsP0/h43Xo9HkZ4UShlo540gsqVpfH0j28PGjAwOBX1FIOh+Gspzr+iJQdbJQmZ8mv8Yyu4zsfCaj5aF9ok3k/b9YdfVl/AhMe//mWnpcutljjz8s86/XRj++ortEeFj6z+yXE+9tvlYMSHgX0Y2odLeShozJGgrkmmUl7frUGc32jJ3s1kjRwHdin9HVC8+Fyl8gntU5/BnWEx63Mgriut5jkOdOgyLB2omnyG7kXN1jyD24IZ6nOLbouqVvPxqurB2KQ+gWe/Xqaw8Jv6TJOpzib8ADIUtpYnMDBhM3F462vmAtmA/4zKjwsD38m4EgeDd97NUtlMNAUMo8Xtyd7VZrEweTwY6lt2fsnEoTF1B1OCXDLcDlNs8nSdpD5hqJwzivrMHLFyTp44XoAuZ9dgk0xcgRe+/rbpNIZ9SZfRXzt1Z7BYPZgfIgn6saxkK3fmu9mz0Gt2nJehF3Sc8/DlUfHZsVc69o+KL48Zp/ri+dNf//b6+ZuwW1iMC67mYZuOwTvJTy4wAIYqR5NxNLpY2d+3+O81A/+Y9oPBf5jkxYSJzBj1IS8mgKWmU9IA94V3kdu0flplf2poiPnp76/oZyv6SUXp+WI1hrS4WIxneCMJOpkw5IL5Y7ZebA0/us390LNhvRJuuwXp/Xk1GJTm2vhFjRR0JVLJHc4nDKMJeQrpszk3TOSuaSg0f00YqrQa6h99JT2E8q8pYzozf7czno5nYcXUBHzCSrkT5zUlGOIX0W1oT7xmQ4cl5tOd9Kcuy6en8+9MHkrRDtZHEptDZTBJ20Ag5KJxHg/n9jqamWh0EIEkvElCTqU3c5a1vHNEJBNfXCm78v+lfbkFTGqB/p3bv3fX7p2L5zipgMkpYFMKbGUUuFyH65PkCFryYTRwR/3dqOXdrlLnW4DRYXwq6f70rtS5DYt4eWLOAh1lTgJJIoInoacZSFKJZ5+EcpQ4Xsv0+nL5iv370/vSadHzyp7Pcz7Jd5LOShNL5h2g5JnnaFaUUqUw9NryFB9lJ5j0UCaAnW41TJ/ml+PpgrHu1JUT6tJKt+332sNydLeWOOfi9AQzlym76fP88kKrp0+Tj8JuGgTuya27c3hOq7o5p+/SAHaTTLuCva4cRnIv1ydeqXc8PO6a9QZk3ZhG3AyBuIY6eluEJdTklbcPX5542wTGf2ISK7fqR+b5GMbMET9mliRN0jzIyOOlcpgx/aE4SkHr97Bb7J8MSqdDVbHdgeYL/X28KI7cFBtxE/6RPn57uwrTDKijeTB3Vvk6iXV/uX2i9H14rfLHVLZIJItDIVi8XXXfHz/rHTNBpzyPe0e/d8eapXScNP2slMmU894KthSRDsI68Pxoq+2X2bZ1HDkdvMy2fxxCXKYa73/Dxs1xuVAPwLk8EVf23NHg+JLZPswZuu2v/ePLvGNy9uidqSVaUyYy+JDl7pDl7pDl7pDl7l8vy93eWwP+N/Pd7b9hYM8FA4cUeYcUeYcUeYcUeYcUeYcUeYcUeYcUef8nUuTt3ph0yKB3yKB3yKB3yKB3yKD3v5lBL3W13CG13iG13iG13v/11HpQYEYTIvRjk4j9merNq8T1TicVN45I5HSGy0Vd6mRWojd7u5/LJQbFKfqHTyi264w3HyRliv0gjrk9Kcjcc/fZu1leajFJ8fQpSR/n/uACpTS9kWYUlEv9pHG3y6gcr+IxW4lE4NR5GMVlJA0zhtS8XirdoAyUVWo8cVitVlDFLzPrQdN3GXDD4NAANokkI9SgvLBrYp7cH4pnSUiT7gkk+1rmbkT8U01uM+wu5xsYdDduUMrct4dme2FoJ8UJdznRXqjf3s1Wmyk6rpR7R886qw/2aRaKz5SekGSXkyO9AvCgdJPVzo5Dz1yLONbd5mi2mUqiKBZmwzCmjsMbtKsPRzfvZqLNh8Q8qENQNuaz8bBYejCJlxeU2qloMJOGTUZ6rn+euV1P/pjBkv5MtEb35nSWunUPg+p1NGqjS4IFywi4by3bfh9OZyfTo2lJ7lFUOH5wp3b7dvXBxJUQYSXlFZt5OMnVR5sdrm12fU2GuLaGpmj+r0K7m8y13nMLs0J7Jlfs5aS+w6J3bHRKl2nUJOisWHHLvo74IoHgOfBDr/sLu70O70DULSLhIbKnrE7918ItikmEzaNT6Jmd0+uFTY5nhtZte4HuFfeOZYWK/pHXKGUCc0zd/lbVvDKDR5SZ5SbaW16tUrn2rhc2Lx7fm/53Xw2SfHwK/WKSsW7nx77Me2xuT/K9eFAMcsvLvydDudbsfGbc21/tPbCaLG+9WUyi4usy1nO6GIH8BBUICulDxBHkopT+t5Cv2lvoEKfBY/Pdas+VUBWprI9St6ROlH5oQLc9qg8a4SJttINe6bj7rRMFqqWV3FRnFiwZyAeLD6mEgZzGo/IEziehIYZsqsD5pGQoaStd4HxSnplkgeXNglc3F3fvIQ0/FqIRo0fHN9EFwbh1B6lJLrj/ktI2rbKtBdPyyYuLISTAOr4vNF205BZEo77Yel/YRoJuGwu/m5RQZw6+xJtM24XX9q5EQTYHAJmMdVNWwx3MHJxBBIhHEoPUX47JFE0BmGix330wv6GO5jn9yfp6vrmivyfZ0uY+udn0pXvWBKLyDQTiemW7snlWbQJDE80GY3bG1YAqy/1VDeuVG3hFWxqM+7yxlCXKhU/unitnd3JAPgCeWbz2yZr+8UyOn5TPXawimDqXqx3heSIy1QWQIdnBFhUTwnNzRXmibv6xfIw2RV2ssmbCQWyICszMTJDKVmCKU4RqR83spFpYmfDdCay48g/z/nJF98V6OZ6e+Ny1kfjxxT0N1ynRAfKQAS286FYcgc+e//DLs+fP8PWENzzDFNQgF0amvPFk4xmKsmTldGyWwnK5DIU6P5YkGwSyq1529M+XBYH8yGBKweUwNSGublu3ijeTiaMR5OZ4gc6CoRCQ6vi/km5P8Iw4j6p5FR5Orzdb4iTN3/JnRMlyM5QTDdzf5+Y4OF2rVneOjujDSLb70y6GOGxRzg43Aoz+/Mdf93T/bkazRz56GiFAUUc/950Egwt5J1ZaGV07d/yPHiO/zGNPzLFWC6oSqq7VX2WrSyUYnsemoeWoeIfanmTyM4e5qkxERBS1Q8jZIzFuGkjAG+dP3PKNrbLJvL8uTuZ8O+U/KCybF9aZvrOl0xGbmVXijRu1lIvX4/Sr3/GKsxFXAB+s6wuD+N35kyOXasfj+J1DFbcO9/fnarkyAONGdhCMc37Rd52FWOXSnsRooANwRvGZ0pZeiEPObPwkjU+5Uc39haWxU7VlAW2RvmypPOCDNoBf9FAv04BdkEI1StoAlPuE3Uov2TZdXhZH03XaQyfOT0FGiHbez3tB6ioW/lRA1yP6ZpRO59yg6cgfWuOmCvjekEwwKV/q2GndmPMtqgqwlW671qOvbqCJyU1roWM8EdQrXGcG8sK/jPgAFEAqMyHNy2Lh7Ozly7OzApfYJCJGBbZX1fqkFb0ZHoW/vzwrON+jcslu2ksThRK67Dhv/Z+zha+lsIQOiBMjKaxtY1Cr1MbjliLPMaeBOsMyzob473089LNCOpJyme39JXsvzpZY1VqJY3g/zC0wTAqscgu8NwVSO/XmDvb3BFRN5CqVlferdPjIIFGbkqG7GCb+G9p9Oc5Zru9m+dRk17buNjiLay7vkbPuevrH7yUBq2ZcigEaUSGYm6GMyzEM2/O3IbHhbSUkQrwMlSdcg7zehF39sSolRvibnsvltZ9uUvY2XuPji7OQzh7OIuQ/KQqCHjpeFd8DQCsXjNBMUhk49AlnuBmMh86ZFWdS3J7Ygzy4c2Cj3Z1cRs7ZHH0uo+FG/J4SHwdpCwP80oQiRZfp0CJ6OKVXoKoJLxHXoSEMRuR06VYDA1p3pz0ywjswIjxrgIZ1pMlUpwlexg15dgMELdwxPmHdPfF6qUU0rm7ynukDrSQjiDsHMsr40L2EkaRK40uXDffUK5igUUrFZ2bZNOmczfIbw3+XpWyQde4QpVx714uqw71k/BQnoDLBvLSBVXZKO3sg9HlCKJ3NOHVwP0g5bYa8mOz5DM87tQbbtba6E0k70Npb/RKiZ7MMLZx127NegqqrzXLUh0lQfJVF0xfdda87iW6iSa8LTbrXHc4nPbOyDAUVzC0RW6ndXC3H5AeXdFnSFl2s0mgJ3XKL560h8oq7LMJ1fihlHUyvugXSVqGXYYsYi4nBwvcXZ4Uepy04NU6FrHEx8R3UWkjHBPy0TGFGDTW7N4BfUEvo+/2SDXZR9/xtoafRaFI41cjws40MpREZa24Lq+0WzHjfYLS5Nc5k4MpbfgK8xqXtUHgz4hLQ8myYKgzA/qaFf0sJG4wsvZ95tkrVwDpOtMYkSx1mgOmKL7YiaR6otUVQz1izyyj/s1UXiLbijH/oSvjPjIHzS7r7Ia6OneGOf3T2vkTEbxp2NUzPrKSll6l3y+292+dx58+6S+A3+z4bdn+Tx90W98Dv8/28iGViN946kClLuMqS3T7nAH7La+vBbvNWPoXo9FWYrl9k5SG+pIN9fxVzKkP+T0/PnOiuP1xP7umk/zBdXehVLOX1/AJmmtiWK4nZd4rik1bPQAD1cDie9icQhykOsCdeOI0Pr6jvJpqn2Svl21dJofO3/K1z7ch+VLdIdZxkXilI0B8eXxZ24HP+trR9lugpan/8ZPo5kx9ZHF73ryDlrVu4y7hY1yl4K/lXnn159ocFxrYmjHQbzZ8KphnX/QsiugZZHju3eHKdYGeRSTOmYKmUO5k8KntRyo1P0OhbjOFpzscz+5Hju+2225DniofzW7b+lKOQt7ldPpUuE1QSy9lM31jHmX35iyGM2SgF7MdGklMO2vcavDDTzsraZDvzqxuX5dQUv4vzhVEO5QMWbjkwt3YUd04Q0Rre02BHUNWEMr/aqvdG8fMN0dMEKusbomcnDuRNIbGJaw4N4nbisOLQCjfbktgaVqBt9TvN2PeViqWfGzHcO9lAhEonExTaSYdVMKS1Y3dG7Txla7RcqVS3j+MtsjXy4k1kgSXuWVf3Jr2qb20PmFOis77NhkCILf8WCn5sRmf2eqXEE5aYUWz2tox+eZmOFRdXAecNzYPftkPvxb6Hbf5kJ/iWThv1CRzTgeCcnqbjRMxY3nZRTFTrm7aJsB1f5kQdmaja9Dczbmm/eINRvO1O5hq2/7Z7Pe7Fb7ZPOeSebii100EXxiflJHkaTBDCv9yhhBQiHk4mHE4m/MOfTPijATN/OFhmK3JlNxmBk9rKzETOZOQDfcix044/XPn3H+isxSPOV2Tl4rc9INHRaPlwK2p09whCyiNIarrkrJjuxy/lxUTekOXS+9+RMHft4rMHCOJaf7djGJ3PnZOQkxl7jkd05KTBA8chOv9MAfudbxKFP/VtoB7glQnUm9rQ0nQo8pSqwFi8XwJevySbQtmaRcAXL6brVIkHQq13e9G46jz9ZndAspyPCIXufE34c+dfIuT5D0Y4d74sqvnrrgLPjyVOBTD/XYOK/85Bm3aP94sy9sXpGR6frW+zjE7iu3k1zmIOGR3NIm5WDCAn7yVZA9qbQBm7ipz/CAZBy/dGTaeI3+NZVF5Czx+OplM+vJsBr8drZpfYLOXLcr5ZR+ZRT4MtV4AJPTfraJacs1nNN8thpB6vaDzh8RzGES7HcogBI359/mdHYzpt7oGk8uvNitsRHA5WZO6AGc8nG8lfOGeKLh7H19P4kcbkrKJ1591MY0VM7sExyi3646Wco9eSvOJX4i8kvcJTu+F+JbkDkvDX/oihBhoOr0f90YA927+YzydOkVxX9lAIAUyfR/i13pvb/gJgW0w2DBNBof4QNs7NOLp1ihA4gAjGxHNlzJEY57ioVujdlsYZ2LAAT1n5ZiByaima8Xw4lmMo4bpY1HhGGOiMSQ7Ylg2eKQ7Gl4wVwtvVez6Uyrkb/RpgQmj8ZGzuCklDcjRWsnv05y/MVn6Vht9svpz2J+PfuWqMrYjjPW0IWTvjGqzo9tAIbIuPyqakdXn7RLIG6OtRascryeG3MMkXZ5qwLDQpC4ejK8nM5Tofhv1FJknXkBI5G/7oVS5Qi/+JfRPZLRvJIcZcCmSPyySIrEXS9qEEm3KYW7ZEpSyXFFXidq6m/e0SvLbFJDyt8KqqZCMfg29nU0DJIJiwkALONja6smkJdyaUmsMy/yttA2vYL8cjMmAmP6U1J+2bv1piurmYzDKamh0T+apW88q+/qtVoqkCJbER8Nt0aN04RhLcQdm89+w7N8Ey+QgI3ft7PsaiwVxyrTaE5DKzsLLj3Kpg0XEA+rDPVqRGHEvkK1abelG08vQFkVyy4JC8NnI1+H/bfakUCRtC1LNZiYOSJivYCnl00aJuwXguC9mjHKAQdgmOkuoZzNOeJz6VlCoM5jblb6T4jZce+GozvVDDiQ/99KcrPzbkzl+Y0pCEaR16awfd7AgopaVtAxgpqZVWfDqOEWmxtNHEsoDljMdCTms6sTBxMwxEzusUyfw0Zo8XvJPjKV9jhhYCJKUryGHLe/o/7vxsyi2f2u6WIjbjoUCR/j9RuboiAi+o2vX54Y4+g9nd7q7qnWyQ7irMUos6AE3MOzbG1Ns55xdny7j9PkzJGcRJ6HAI+ICf0fqCL/j6BJPpOGv5Ka9PsWw5p1GXc3o8+gyEovK9vs89NCnF8seeITUMw2X3HVLBSSj10qqcwvPJDjzvbhJ4HhG/Tp2FhWbxjh7GO7+UM4WHgBrD6lind+XvAOx+rot+wg97gXM/F3ATQrnAuZ+LCUVh+W3gJAwDfA246GVx0cvBxauYGK1TJFXjah9wthA4i79eDv5+Dty7eOztx+PU+niPwmVvG5fz23wMOj8OpTPiJbVcnl2ujvLX5BfYJyyb9X3H8Hz5QYddf38P22Io9jwZtxLhuDYuJxmMK4YVlBfXMiuoAWKuqYwQfefrGys9YqgPCcCEyr0cKk9h6uDRmLrFGnI4g1fKR4jPYWuMgJZB7OEP3j7+8Fge8cV84muR736eQj4ZzWiwf0gPIqBiBlHmfv5H8e/RbX0L9FO1QDWdVCSO+kk/UKNdxkdltveNPmBNRP3cFvfGZ/GB2kpufdkWX2aivGaiKG+7baGe6BigDFNhkaj+dVQURVku7Nl1z9AQSWf71A0ttvREvrVts/yRrU0PTmbIYi7tevVQrk3YyYIt+XPl/Jfm5Pvv3UW56u+VOSIGPEuyIgOuqMrdMzqu78cffJXz+OCbeOE+BV4/R0ehO+mKvsql1NktsGF/RX4t3lPcS7uSjlhEB9nDpXjSnX+Ld+QEYjvbonFrxrrcUODGe3isoi+faH15v/Fy0HYjM2WZExTI5U0bX3PZ1Payp3vVTo5Z1OovdzF/AkO4m8fa5vJuL9+5m3+G1UAHAX5v2A7Kgl90djWV/Cl4j5oCOexGMWHPFLw/PAUiycZLzSASJqjHdNbJszLKvCV5gPHGPFVm8UcE+h0Y4MbLMEG7g5TiqL8tHynSH9Pct2CqqSQJMY9YRTyo/l+7ra/vLO6f5omeq8FeNUA4Vsw87gVlKMDuyDwGMfO4j5nHnWUeAzKPwT7mMXiAedwkzOMuZh7ru1KsWeywjvVdPuO4STGOmzTjQAV99YR15d1NHtO44QzXDLW9yWcZN59lGbHJc+N/lcmTUVU+yzKkE+rZVDwexzJuvEdNgSzjRtf/a7SyR02BqCF92Bk8yDLu51/HMqSHP6iG3Xg7qtNXcY3Ht/YtmIbxIAEGIyyicSPxV3/3zAOdUWHkqRMnjHy7FRByJXSnnRovXt+ES06gfxP2+VeOGwuw3d0hjwahGcSpdfPaPRzJ2C8j2v6Uk8yH7qgw8Q6GsYcwTLsJk+DCF+O76HJ/BtqR3T6j5TDaE8iQHDrTonYfaW+YwkNVUvlyZffgr0y8k4mjlTd07TuLondscmUPxpf8eSIpsRkUKp7JX1//7XnaYZne3IjzOZc/E1U7tTAQV+9nYSC7BOrxrn5VoIYg98rPjcnIDXGROIGFPZNmdgBLudEs2UgLDQ/Yu3W3vRRMhRRtLcZPs/nt57Zyys5TLJZkUGo7DGteDjfqS5Y0dCjIxRzcOxuD0QN8nnGVzJafrPNkTsmKZTYNzTdr/ko3w9/SjKmtJ6QFLVD7s+vMMAjUnV6PQzpwt2Nz5Ls8bczfqQapJPX+UZBjKVvJvt1NP39B3WOg747id0n5D30bFZDFIkBNd3yX/QzibHiAMlv0epwJMfwwMP61LYzTFpl9cpCpn2rxJL9FA0HF4w/kkys3RQAfdK85SSzyXfu7j+++02wX775r81xIPQgqcrN3JeAlkHrTab1Vq7b8VqNS45V0vDLQ88pB4AcBr2JtVJpVuZ12txivt/R93rfstzy/6uvtxLzAtuXXeXdvYK5J5IWJTa9W4yXfdb8RmAuCeRl6s+kFvG/Zl6EEvNG0wdsGm15VLvDD/Fq8Up3XtftBy28GepNwvSn36TYqDUxEbzuutmo+L12sVr1GrclbAlvlGi8er/Km68CvN/Sa0GrNw7i9mt/CUHg9Y9AqV3y50LnWxPB1zJVKvVrhxd68CNGr1PRyVl4EyCs2m77n8f5Bfcfbt5u80RhTavRccAZZBQP0Kq/B5W3gVV7l66HDZr3c8Bq8kRBDrjInkBOUMUKPd/3xMvYKYZRTild71ZuB59fQXSNoCTAaPiBbkwutUbop91NXeRF20OQVv36rphdlNnnhKJa11eI9sijWbJR5OzyvZA1anscLD6tyOlpux6zW5bJTAgxg4NWFfrUaNNhnoylZi+pBPWDXvNSwzivXqx6v2pZr71s7NTFulGvUy7VKDUigLxoyshb+x3uTASVPbqc0E+AVyigSNPTCTMEsdgp04l+FNHf0BdKakMMxiXDwacbXvKS52vwklLGMotlj82a9jqBzyGH60XL+ezQ7MeECJqiA9wNu+ib8InV/YdwJqkUR7Kr/5wyv5/MVH5YR997fzZ4zQSljGTRr6c18qFm4BubIS3/tYCqOSdng6uWLi/l4tl4Z0c1J757ej1N0PTY3l3yZbibr8WI5H0arlQzIlIAE+xfI3pWfu+tFqKmxNc5ARFU6QxU3Sl+EksiC9zmuiqyuaGDzYPCEh6bBKJU6ep3BWcmcfmSUim7Os838pFWdYbiblupFt2CSkBR6/GHyP8mz5n7qJam9OtGkv1hFl3tSerzjBU7pPuwgkwY+pD9reoqzzG2IRuJoupqhO5y7H1zTK1eOCgQTgl1chGHh4mLaH88uLgqc83R+CX0bmNFfXt105fAo8xPwbVhQwpByznCxDeYE2XNBbY5mDxfdwiBarQu9tLNVcjVtN5jJtJVpaxSKPWMzYiVtppfBpAJbpVbDXNwWrwnv8pEUaRdX0SzSlHqZ1vAapcAxxpe7H5PX5kTpCF0BUhck4AhDCD8u2oaYy5qRhPNamMkM7tfRCrMpX0d3l+MrNFrUk18LyUJXMDcyFtxC5pYhvZBvMNfH5Aoc/LC5WnitoCWZ3qfOLg3k54IZuSuQ38X76H4V0oiNE8OY2gV3dzJ5xJU3sZKwm+iO9ApQGWQgXslNpgVltRi4slpJa5AgnnkpiMdEPmE3hSrpk6mKh2xKRjTJIk6Z55TXPKqM4cVJ9Djp6LJ4w5wB8Xld9lIKNa9VJmsUlJma6HZQnaFtZ16nRmzmY3xTJnkf1CUJI2ICwuVpkUWPC3agnUvQQfgxMzE7JJkbD3Dum8wnds0CgPBqjRfG/x6hYGc9v5yDwW+fmJUJyJhX9ggdhyAkL3zVAqg/mRS/DI3D8Fox2ZUry15s0UVZ7nrSY3YyOP7TbaPhHl2fVpoSsSew2pxBfz285v7bfHwpFx0ul5uFZA5XxNDgwP0cG/OVNHGy00LxWAxcTnGsgSwhn0tOX40/l2CUw4GFfkHe6gnG1ClIFiuPp/3FxWY2X8IoBPqI7HA5EXd4vZm9F8eF3ZkaKcWliQ1NlY4L795RqI3Ko8lmda0j1fyKjp5fz5MPT0KgXFvGAEjAUOHOVqkzwGq8fzdzdnI5CasUtOQ/zALK7IKuoBsP9vChdMxX6/m6PwmvxydAjVus+h4BVSq5Ml5lEmK7wAYcZxS0Z+P+Fe+idH74y9OT5286D0TOKmRN1Ks4RPqJV42pI3nxq5u6arrs/MI0GQZLEs7N23pTWpmkDjOa4H+++eVcb9h6QPmS0Mp0ktTFePh+ErkcDzTg1fgKE/pX1MpyUqe+3Jc89c3jpfTbX17/9Pz1mzB4N/vh6Q8vn4cfP3Ve/fLzjgZ3cTtfvmcyxJQih3L4wdJZFY1rYTS02AsHFSdHW3JtyKkP3pvSjdiKsQGi4rq/ei/d2hSTwklCvu4wLeBWAso3KV3iTaLZdfbwHaWnikmXapMQShfCF76gB2nqOMxmJ8yf4okAW1S/lCooDbh6kA/9l9x9yqdCaDReQ7CsJLjPzQBHUybycoZQ+lh1x+22Weqds+nmvRxEF8EtbAucs2iXwO1aNc5dpNQf6aCXyrI5Ld5ZaXgXC+jTZD5Gg++DloTOZZjr6SLMaqZ4U+jgnz0qkFYtSQnJpjyMclVbgukBLXqf5bA9GmmsI0fKSfP8SgTncuo31YIoneNCsYgXFEpEmgH1jmAz1BXLt3Z2Hdifm82L2Qia6r1K+syHlkgWWQgpb4ic4gdEdSNr9V5zBKd4RtJomllYleCTzni4SKYpa5LmOsNFpipqxIdZd1PnyqRKHe4ebGXOre5kzjUXnaay18pN3gILHcVHsQjaFb3Mu9CWuO/CJYRdoS3JiM/dwmKI54p5XiXPmu6xXa66BWOKoaEytPnN8gZGVbfnqmXRlsD4AsZaaKvoKQ+CWjSjClVUkWR1CE4nWsvQAIhSWZNyAIqdFCGQ/TBSd7+9dlKpeHkcXE4t7S25pWqyL0X9ddQtiEIA8XchpHBBbQL2kEpgDLmYW8Dd3xlrUuddX0xJVicyo24MyN6XDFXokv8o8pgRx02Fqe8nD01HUXW7+pPQ96ifqeX06+unP57/eP5n5kB99fPzX58XXFNBTcvt2lt2kkklHN0txvRMQAPZTN0RM36a/MZS/d13pv677/JG/+67nOGjaMd+Xq3nzLV6QaYL1pEyhtkgtbw0PkFJHQOKb+4he6bPOVI5R6HqUVn/FM2vNz/++enPr//i6gQwOX3dn/SXU8m/7cmtu7Va3SW4CLmT3TmZ/G67xI2xgARWlgQMcSiKJ6RjqMKAmnRlcgpwl9HzO9NNGHRub5ka3JyfmG6Oy/XSSfx7DC6wLdqmG5iQcU7u21O5nfjWXIXFYre3PTQdjUahpx+PblMftSJHMRyGxdqxlDw9L50Wz49rx/6R/d0ZrsKi/Dj25aM+1/HBC/3TIt54YGVHR75+wXvMR3IsnAw9FyxMXp/4x96pFpA6fqoGTM8+ryn32K0k9ErO3ZnannQNVoin4yFNrX933kTMPUvtGjq+s2FS3f5wGE0kVRetN5tL15lAS52JudZnmqDiy/5sBezn+TFjJcwXxDZmTnUwLc0Q4Q69I5ldvXRa3ZoWfqS+0W9F/m5WWFhzr8PG7Svh0L2O2WPWd8qPe524kFBkRzXAbcP/uHj1PWAGExUCEv8mvwWTFvPFZqIeom6vc69p1lUApgzu/lSp9v7e4Jq9gz0tl7xUakEOm83ZxE3396VO0lWSvPtY5nI0sLeP2yxFIp5QSdxTX6EqiN07Jn5n9MGF0QRT6lo8KEmXIUZxaBwryeTdzCVtbJgJj3hSZ7mK1Jrs3IMOhVpMSvn3vaP7VVcaxHPP3vj9PkOIO8R5rqmPZtGtCv7PQOhWi4MGusSvVemof5ws0HAFVUDeKr0c3Z+mV880ea+ajtwZoPi0oBfy/tblKprxMO4idaiVWu3RXaLULphXdHg9TpU5Lx1hSN5psXZ0XgINg0ceneOx1LnGlEK2mBqNd2LGL8rLFSm2dIoG/+SVwVSUhmWmQ53pkDNlQ0ep6Q5lusNkunaG2/MbyvxiUAvB2fsV/IorpHoCUj0mJVOJZU+lo7iD0tENPy2GWFWyI1L1w2uPUnnLX8q/jyIBfMqDa93NVBgIoO9rYWgimFKlMvhu0MjNMIW651tduWQdNgYwiX9bAolJzXHLTzJlsk7kduabVTYxSDddrJ08u7G7u23G+MkqNDYvPZoI2YLQgZ2IrJRZMRe4sBi6wP3Fyk0F4RzFB8ZAAKciIUpcReAbEApyoORm9jEeoTAxr3/4lSptSlNThbkXsz+ZHrCODKWUctZTmcqowVAQi2kN8ftK9VJVxO8NrTxsFuZ519KLJJO+wDBgGMTj2bt0sRGwrQMyDbx1Ytn074V2vr3+KccXF28JyJH1X2/nJ/wNTJytofKs1wwnWm0Gq/V4vVnzzMBlf0GJrTt0a0+ccHlbq9Z1dkgBf0gBf0gBf0gBf0gBf0gBf0gBf0gBf0gBf0gBf0gBf0gBf0gBf0gBf0gBf0gBf0gBf0gBf0gBf0gBf0gBf0gBf0gBf0gBf0gBf0gBf0gBf0gBf0gBf0gB/8+VAj7jFLmdM41EUazArG/0zPo7Mnvt0KDW0XI8X3byj71Edt86k97h2d+e/nzxw99+pfLtf5lJvNoseIyiHJdNSm2Bi4MUX4kor1nCVPudRf+DkQnj4TRaX88vk6Fo0uRVkY2ku59qHuPirWz4SqijSHCRXlJ4a3fQlC1uyHHulOMLv0lV3uRUtnvMqVW8KdlBy4blcr7oX9FdrNC6XG/vCAuVKxBigGSdPTxZ8WixK7E/KB+a5pJFJD1Td5Yp5JiQAri0FpAG7m7R7MKx4raHZ60FertaxK1RBgxAcwbye66IxepQL9ijN5g+rWNRVjRup7RVWE6hmKWnd6mScS2td6ZMD75UgfUM0V2t5OWaGhuhkDihBHgg90y8oUya+n+llzOFi/TUpdxnga8z7OWIugeq0j7Uszi6etsrw+VjfilN4IUJ93bwHo2Y8rowpbzV7aXp4Z9N0d5S0L6p0r2lbpA/W9pL2EaKYfzd1OEc3ResDHqufTCJ5D9LzDKHHJz7jLZteoWWcGvV3l21+7E84gHm8D+2i993v5mrSB7FOwDZ/4mpop3bVkxh/7OHurS/HNKOp5RhwiheehR577IgWZRdHiSvH8WEdKg7fOifyMjZWr5vYPBkdZfF2DXWBuZsTJj9bDmxWT7XrnB30/DjuHtO/fxh7JhAGXSLmyk9wibKafjL7KO8Bv65baU9C/PVxtPWKnyJIZVT9e9vVe1PJyn/e4zN9Zkm/gEu5fr0/wF4D4RP"},"regeneration_commands":["Decode source_bundle.data with base64 and zlib; assert sha256_uncompressed; JSON-decode to {path:text} and write into scratch/. Decode scratch/blob.bin.b64 into scratch/blob.bin.","Policy replay and scoring are offline self-contained: bundled replica2.py is found beside the drivers. To independently reproduce source Gate P only, clone https://github.com/gtmcknight/amm-sim.git next to scratch as upstream; checkout 4812a6382311624e1506aca131ca35c378f930d9; verify git rev-parse HEAD.","Optional source Gate P reproduction needs the pinned upstream tables: from upstream/research/solved run python3 -I gates.py (unmodified first). Compare to gates_output. The measured output and upstream source hashes are delivered.","python3 -I scratch/preflight.py; python3 -I scratch/finalcheck.py (the latter after frozen.json is available)","Remove frozen.json and screen JSONL files only when intentionally reproducing from scratch. Invoke python3 -I scratch/train.py once per generation, stopping at 2100 training wall seconds; each invocation must stay below 8 minutes.","python3 -I scratch/screen.py freeze; repeat python3 -I scratch/screen.py choose until 1024 seeds; then repeat python3 -I scratch/screen.py report until 2048 seeds; never select or tune on report.","aggregate.py needs preflight.json, base2000.json, checkpoint.json, and both screening JSONLs regenerated by the steps above, and selected_invariance.json from finalcheck.py. Then python3 -I scratch/aggregate.py OUTPUT_DIRECTORY"]}