From mboxrd@z Thu Jan 1 00:00:00 1970 From: kbuild test robot Subject: Re: [PATCH v2] net/irda: fix lockdep annotation Date: Tue, 17 Jan 2017 02:09:38 +0800 Message-ID: <201701170149.G5mmkfWa%fengguang.wu@intel.com> References: <20170116145129.102159-1-dvyukov@google.com> Mime-Version: 1.0 Content-Type: multipart/mixed; boundary="n8g4imXOkfNTN/H1" Cc: kbuild-all@01.org, davej@redhat.com, samuel@sortiz.org, davem@davemloft.net, glider@google.com, andreyknvl@google.com, Dmitry Vyukov , netdev@vger.kernel.org To: Dmitry Vyukov Return-path: Received: from mga09.intel.com ([134.134.136.24]:50244 "EHLO mga09.intel.com" rhost-flags-OK-OK-OK-OK) by vger.kernel.org with ESMTP id S1750803AbdAPSLV (ORCPT ); Mon, 16 Jan 2017 13:11:21 -0500 Content-Disposition: inline In-Reply-To: <20170116145129.102159-1-dvyukov@google.com> Sender: netdev-owner@vger.kernel.org List-ID: --n8g4imXOkfNTN/H1 Content-Type: text/plain; charset=us-ascii Content-Disposition: inline Hi Dmitry, [auto build test ERROR on tip/locking/core] [also build test ERROR on v4.10-rc4 next-20170116] [if your patch is applied to the wrong git tree, please drop us a note to help improve the system] url: https://github.com/0day-ci/linux/commits/Dmitry-Vyukov/net-irda-fix-lockdep-annotation/20170117-001737 config: i386-defconfig (attached as .config) compiler: gcc-6 (Debian 6.2.0-3) 6.2.0 20160901 reproduce: # save the attached .config to linux build tree make ARCH=i386 All error/warnings (new ones prefixed by >>): In file included from include/linux/mmzone.h:7:0, from include/linux/gfp.h:5, from include/linux/slab.h:14, from drivers/gpu/drm/i915/i915_sw_fence.c:10: drivers/gpu/drm/i915/i915_sw_fence.c: In function '__i915_sw_fence_wake_up_all': >> include/linux/spinlock.h:217:3: error: void value not ignored as it ought to be (void)subclass; \ >> include/linux/spinlock.h:335:2: note: in expansion of macro 'raw_spin_lock_irqsave_nested' raw_spin_lock_irqsave_nested(spinlock_check(lock), flags, subclass); \ ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ >> drivers/gpu/drm/i915/i915_sw_fence.c:68:2: note: in expansion of macro 'spin_lock_irqsave_nested' spin_lock_irqsave_nested(&x->lock, flags, 1 + !!continuation); ^~~~~~~~~~~~~~~~~~~~~~~~ vim +217 include/linux/spinlock.h 211 typecheck(unsigned long, flags); \ 212 flags = _raw_spin_lock_irqsave_nested(lock, subclass); \ 213 } while (0) 214 #else 215 #define raw_spin_lock_irqsave_nested(lock, flags, subclass) \ 216 do { \ > 217 (void)subclass; \ 218 typecheck(unsigned long, flags); \ 219 flags = _raw_spin_lock_irqsave(lock); \ 220 } while (0) 221 #endif 222 223 #else 224 225 #define raw_spin_lock_irqsave(lock, flags) \ 226 do { \ 227 typecheck(unsigned long, flags); \ 228 _raw_spin_lock_irqsave(lock, flags); \ 229 } while (0) 230 231 #define raw_spin_lock_irqsave_nested(lock, flags, subclass) \ 232 raw_spin_lock_irqsave(lock, flags) 233 234 #endif 235 236 #define raw_spin_lock_irq(lock) _raw_spin_lock_irq(lock) 237 #define raw_spin_lock_bh(lock) _raw_spin_lock_bh(lock) 238 #define raw_spin_unlock(lock) _raw_spin_unlock(lock) 239 #define raw_spin_unlock_irq(lock) _raw_spin_unlock_irq(lock) 240 241 #define raw_spin_unlock_irqrestore(lock, flags) \ 242 do { \ 243 typecheck(unsigned long, flags); \ 244 _raw_spin_unlock_irqrestore(lock, flags); \ 245 } while (0) 246 #define raw_spin_unlock_bh(lock) _raw_spin_unlock_bh(lock) 247 248 #define raw_spin_trylock_bh(lock) \ 249 __cond_lock(lock, _raw_spin_trylock_bh(lock)) 250 251 #define raw_spin_trylock_irq(lock) \ 252 ({ \ 253 local_irq_disable(); \ 254 raw_spin_trylock(lock) ? \ 255 1 : ({ local_irq_enable(); 0; }); \ 256 }) 257 258 #define raw_spin_trylock_irqsave(lock, flags) \ 259 ({ \ 260 local_irq_save(flags); \ 261 raw_spin_trylock(lock) ? \ 262 1 : ({ local_irq_restore(flags); 0; }); \ 263 }) 264 265 /** 266 * raw_spin_can_lock - would raw_spin_trylock() succeed? 267 * @lock: the spinlock in question. 268 */ 269 #define raw_spin_can_lock(lock) (!raw_spin_is_locked(lock)) 270 271 /* Include rwlock functions */ 272 #include 273 274 /* 275 * Pull the _spin_*()/_read_*()/_write_*() functions/declarations: 276 */ 277 #if defined(CONFIG_SMP) || defined(CONFIG_DEBUG_SPINLOCK) 278 # include 279 #else 280 # include 281 #endif 282 283 /* 284 * Map the spin_lock functions to the raw variants for PREEMPT_RT=n 285 */ 286 287 static __always_inline raw_spinlock_t *spinlock_check(spinlock_t *lock) 288 { 289 return &lock->rlock; 290 } 291 292 #define spin_lock_init(_lock) \ 293 do { \ 294 spinlock_check(_lock); \ 295 raw_spin_lock_init(&(_lock)->rlock); \ 296 } while (0) 297 298 static __always_inline void spin_lock(spinlock_t *lock) 299 { 300 raw_spin_lock(&lock->rlock); 301 } 302 303 static __always_inline void spin_lock_bh(spinlock_t *lock) 304 { 305 raw_spin_lock_bh(&lock->rlock); 306 } 307 308 static __always_inline int spin_trylock(spinlock_t *lock) 309 { 310 return raw_spin_trylock(&lock->rlock); 311 } 312 313 #define spin_lock_nested(lock, subclass) \ 314 do { \ 315 raw_spin_lock_nested(spinlock_check(lock), subclass); \ 316 } while (0) 317 318 #define spin_lock_nest_lock(lock, nest_lock) \ 319 do { \ 320 raw_spin_lock_nest_lock(spinlock_check(lock), nest_lock); \ 321 } while (0) 322 323 static __always_inline void spin_lock_irq(spinlock_t *lock) 324 { 325 raw_spin_lock_irq(&lock->rlock); 326 } 327 328 #define spin_lock_irqsave(lock, flags) \ 329 do { \ 330 raw_spin_lock_irqsave(spinlock_check(lock), flags); \ 331 } while (0) 332 333 #define spin_lock_irqsave_nested(lock, flags, subclass) \ 334 do { \ > 335 raw_spin_lock_irqsave_nested(spinlock_check(lock), flags, subclass); \ 336 } while (0) 337 338 static __always_inline void spin_unlock(spinlock_t *lock) --- 0-DAY kernel test infrastructure Open Source Technology Center https://lists.01.org/pipermail/kbuild-all Intel Corporation --n8g4imXOkfNTN/H1 Content-Type: application/gzip Content-Disposition: attachment; filename=".config.gz" Content-Transfer-Encoding: base64 H4sICBcFfVgAAy5jb25maWcAlDzJcuQ2snd/RUX7HWYO7kWSNe14oQNIglVwkQQbAEsqXRiy utpWjFryaJmx5+tfJsAFABPVfj64RWRizz0T9f1336/Y68vj15uXu9ub+/s/V78eHg5PNy+H z6svd/eH/10VctVIs+KFMG8Bubp7eP3j3d3px/PV2dsP79++/+Hp9nS1PTw9HO5X+ePDl7tf X6H73ePDd98Dei6bUqz787NMmNXd8+rh8WX1fHj5bmi/+njen55c/Ol9zx+i0UZ1uRGy6Que y4KrGSg703amL6Wqmbl4c7j/cnryAy7rzYjBVL6BfqX7vHhz83T727s/Pp6/u7WrfLab6D8f vrjvqV8l823B2153bSuVmafUhuVbo1jOl7C67uYPO3Nds7ZXTdHDznVfi+bi4zE4u7r4cE4j 5LJumfnmOAFaMFzDedHrdV/UrK94szabea1r3nAl8l5ohvAlIOvWy8bNJRfrjYm3zPb9hu14 3+Z9WeQzVF1qXvdX+WbNiqJn1VoqYTb1ctycVSJTzHC4uIrto/E3TPd52/UKYFcUjOUb3lei gQsS13zGsIvS3HRt33Jlx2CKe5u1JzSCeJ3BVymUNn2+6ZptAq9la06juRWJjKuGWfJtpdYi q3iEojvdcri6BPiSNabfdDBLW8MFbmDNFIY9PFZZTFNlizksqepetkbUcCwFMBackWjWKcyC w6Xb7bEKuCFgT2DXXtftoq1i1/t+rVNDdq2SGffApbjqOVPVHr77mnu04GZXsmDGu6F2bRic ENDvjlf64mTGLke+FRoEwbv7u1/efX38/Hp/eH73P13Dao70wpnm795GnC7Up/5SKu/isk5U BRwT7/mVm08HbG42QDZ4gKWE//WGaexsJd3ays17lG6vv0PLJMSE6Xmzg/PAJdbCXJxOi88V XLxlXAGX/+bNLDCHtt5wTclNuBVW7bjSQFxBPx/Qs85IorPlhi3QJq/69bVoIz4ZIBlATmhQ de0LCh9ydZ3qIVOAsxkQrmnak78gfzsxAi7rGPzq+nhveRx8RhwlUB/rKmBSqQ2S2sWbvz08 Phz+PpGYvmTe+eq93ok2XzTgv7mpPGqXGvij/tTxjtOtiy6OloCTpNr3zICu8qR8uWFN4cuX TnOQtB63dqDfoyuyHGwBOBeIggidbgWZZPypXaNRnI+cAmy3en795fnP55fD15lTJk0EXGml BaGkAKQ38nIJQTEKEg0xPAMC0AtZM9CZRBsIaBCbsMf9crhai3CoCDAPO9GJN7CVYAS1IAoY LDmIYCdIAhmsW6Y0D6fN0RjRsoM+7lwLGUttHyUUmT5kB4q1QL1aMVRX+7wijtcKvt3iWifl jOOB+G2MPgrsMyVZkcNEx9HAlulZ8XNH4tUSlQYueSQbc/f18PRMUY4R+baXDQfS8IZqZL+5 RkFay+CioBE0uJCFyIk7cr1EwCy2zWMOMH1Ap2h7XkqP6wOT4J25ef7n6gUWurp5+Lx6frl5 eV7d3N4+vj683D38Gq3YmiF5LrvGOEIIaMlexgwmlprpAhkl58D3gGj8EWJYvzslRkD9BVat f5/Y5IyvcUwfcEW0CRnuwh6GyruVJm4KxEAPMH+p8AnaFq6EUnQ6QrYrxi4ELg4Eu6kq4tLH iXtrv5OCflwHiCveZ1IaEstaCGBkNyc5CRdb9weptLF7CRJMlObiw0e/HWkBjHYfPlkJTS3i vqeBoO7AUXLGCti/heMxylDMUIIAQtegzwCmYl9WnfZkdb5Wsmu1f3CgUPI1fRLVduhA7NUB 3II8NcSE6kPIbPGUIDhAS12KwmzoCzJ+XxJlmLYVhU4vqgRauLa+ZNxvsKCpri1oTJ9PkLlw ngFCDFbwnUiQ2oABXZGfju6Eq/IYfKFqJgQt8+2EBXqBHmXD820rBRAHCDQjFadEIhg2oJxy 33zvQH433jcaMU1AOHAqCpqI8fDU/L4NN1FfR8dovi7oa8bZ6xJdlVbxHLREQQmE0IdEgoVL sSa58qjSfrMaRnPKEg3qcYQispChITKMoSW0h6HBN4MtXEbfZ9TsaPPDLTib/u2v/51WkeeT 84b2gyUKjHs0OQ/oLkJDH5gSqZHhyBpwFUQjC/9+nVwRxQcvHuM6gozMeWu9WitLoz5trtst LLFiBtfonX5b+otNSvxo0hrMa4G05K0DmLRGzbOwVBxNzM0+seDSBwhFk9a0nhT6aPsDst7X AW2ObX00EIGQaVl1oExgp8DqxKwTagbuqSVXI3a+wa+AM7fxNyoE32X1LEJelUBGfpggfR84 Zdn5x1fCYr24Cm9lcLhi3bCq9BjHHpffYA27MhDrcO1Hjl1vAtefCY9RWLETmo+dF7LFOl4l xfZtLvpPnVBb7yZhmowpJUKxbyM9BSk7HDHDNP1k8VrDZoh0toenL49PX28ebg8r/u/DA9h5 DCy+HC09sFJniyccYpp5CLEgEDbT72obaSHWsatd795aWAF16qrL3ECBFBjCgGpLi82KUfoN xwoYBtCsosSoSq9AL8s60W2IhSkjWMxzhtdW9/Q7MLhLkdtgGHVjSpaiCrwhK1usZvL5kV/x fCTwaSLpulOyzt7iCJ/HGVusaWWp2JsjjlT93NUtuE0ZD3cHZjP4KVu+B4EDbJcI1IBAnsab ydc1kfdjV2zD5SBggONQD+Zoxqd2x0s4WIEU0jVhj8gERDpD6xXMdHAPgrjEVnETb9sOLuCo 0VYEYBwdWJyTa02N5B8EMQy4b31J6ZNA1s1hCYu6kXIbATHEDd9GrDvZEW6qhrtE525wwAkr GWyKPVg86A5bHWNTENEsiq9BvDeFSwkMx92zNl4qrgZaJyb1YZtL4FHOnPUVwWpxBbc4g7Wd MdbOaGDBcXeqAQ/VAH/5ZBzLL+IgLZQYeJRKathe0dVxjNCeVsAY/jGOF9drVnJw5VuM/Mcj DKTqztcGmyOMoZ8LaSZghewSYXM0SF1AZQyTEjvQPEdx2YMsMIGFkWi3PddgZ7VVtxahzeo1 p1gVMOyJIjfxHKztyHoLgZQXEuPAxTexDRhhwAV3FVO0+b/AhuuQZLBhPrRLYTYgQhxtlAqd g1hqLMMXCR5uMOjFhyxHSAO1LLoKBAOKLTRrFEFm2kGsdlomfJZptgiBX2FkkhIEYa+P4S3K dj8mAkxol8zTwtpoJxbzbFlnhQV1wRXcJ5hm+faSqcJbr6wKNMCGhNHpAsBsmjSgBNDKjfTU Q1ke0Th20Tvctb1XH9FlN3K5++GXm+fD59U/nQX0+9Pjl7t7F9XymEDuhog5sbvp1izaqIMD C95x2CCsnTDfcKQQ3+xhGSZgPJfKgJsApqtPiNa81WhWXbyPSCoIb9gmF5UFScMoU3DA6RqE xwQ6dJ2A/siD5KGPfeiuVT6laxIOxYgpaEd/AI/eI4ljlKhhjcBLRb9FjyO5Te1CZRWo1s6T +lkYU6qygpVLzzrTgSnqNVciIxc2++SGr5Uw+6NY18AddODHBqPqwuZ+rdinBR6iXWZmQd7t zdPLHRYtrMyfvx988x3tWuvsgjuCDndwxwxM0WbGIadk4FeSGCMD63KGe2KoBqYOAPOIhilx dMya5dSYtS6kpgAYLS6E3kbKvBYNLF53GdEFXFtYhbbpXwLcQU8QYTwYds5SFvXR9eu1oLcO Lp/6xnnqrqEWtGWqZhSAl4m5MDd3/vEbt+vRXHJFSHT1J3RLRydSyJW+/e2ASWrfVxTSBb4a KT3WG1sLUDg41xKSl59C39IlJccOR/KWiZ64gCO9hnkv3tx++decTG9c4UULtgFKQzAOwmSc g1u16eDHYGTfS4Wh+URnHxj2DisRmJFo3KvayyJa7eGWDpwuLxvf6HPFKwmgnS0Bm7wum7At LJpNyc0oaUjcWV3SXRftc3TbSbanx9vD8/Pj0+oFJJtNS3053Ly8PvlSDuVqWP2zKPEoOQNP g7tgcATClOIIRz84gtetlcg+oWFzBuZMTcd212DVlCJlQYGqqHpVgIOcqCjjVwaMJKzUmaNe wdRHx0cEN0ctaGUzY3zqWCLOMuNUbUIpIwqr51UeyxgIVBN1JpIDqSI/PflwlYSfnqCvgNZd U4BpmTi5iUuGOoKSiapTi6uDwQQIf0r6WoEEHGaca9Bb/zWMum324GHuhAZ3Y93RYRMwXDED 54KDs6Vz9vGcNoF+PAIwms7UIayuryj1eW7LEGdMsLmN6GpBH/8MPg6vj0LPaOg2sbHtPxLt H+n2XHVa0rRVWx+BJzRcfSmafAPudGIhA/iUZpWaVywx7prLgq+vPhyB9hVN0HW+BzMged47 wfLTnq4VssDE2WFgMdELtUaCZwZvJZR5lugxpzIUJbq87bmPUn2IYAGLteAegVBtckp9z8IF wzTokIazo96wA9j8nu7qEAwcETYM4ZTzs7hZ7iJRDhZh3dXWuSzBRK32Fz/6cBvoyk1Va08P IjIIFrfiZTOIwGVjDkzBOmIQGzSouWFB3fCm5SYO5No2XncVlr0o42258ENhjS3m9Jx8J8J0 7buctqnOly2YkpG+rAAfjNetsYEZMtLtwDtZdbBDtSf6Ji7cxsEwbhCTmiQaFVcSU0+YB8yU 3PLGClQ0jGLt7Idch4b4qsZmd1WhAmtcdKFOEip2xHCJ3oDWjbu7yX7meWrXBtx/8OL73Rgw c1aNl375+vhw9/L4FNTX+IHPgVGaKC+2wFCsrY7Bcwz5B6rQx7GKXF4m/E57f3zN8n2/qxO6 KgZ4XT+cZ351nrVxdFuKK8sDs5cvQZRkdKZffNwmBlccKQMGc5Ufk++XK4k190RTTB4zIODl uRmDVFYilmxBbb6ksEKn7URAJo3EgiswBaiopIOcBWGHofH8jIpj2qJtWZZYs/H+j/y9+y8a LzLDSxAh0NrzhhE13Na4TYN5BZQ72lM1nIZ3cKJCoqhGIwmr9Do+x6uO9h0XVbOmixJv04oc jDiFoXM4Wm/1levnF61Ow7mcV5yr4HUUHAqah0H9Ad3DDKFzsEP97mFEcrD/XK01DkJZm20F hmZr7ERWip9N+gLToHkU/xBrxWI3v93sgXuLQvUm+Uwlk13jE+5OKFA3EgO53uh15+dh5noA TVHu6EvbSLOrhCzUxdn7n8JHIH/BIA8hifDfMtJOhzMqDgIdrRISXCoJsu6S0V5bnii/vm6l pCOb11lHm43XOpkQH4PD9vHAmKBMOftwylypMM1kK278A7T5QAvBrOKWLrZEydCaSHhZ8woc WYnFO0p1bUhv1ssFMoaTZ/V4TzOi6x7rbTDodhh/vbw4PwsM0M1gzCRCfkYFVIffvWawVXHN qVySC9zFT3jActR9i/E7SwVxXsSlWsIla3f+lP/cUt4VL4WPjvE3bTqyKMGl4QLRcN1/eP+e zmNc9yc/JkGnYa9guPee7Lq++ODpA2fmbRTW63qxRCxD8ExTxfRmzJLObG9rFTBHSmkhEDoC zTkQqQoV0YdQDymO1p4Z9MlcATlmumx6I3Gp9o2SHcAvVxwntHlXmPAk1HtApFVnrewggD8R r4dAH7EraPkm2lCdsis0/dpijKdmkcgYqVoWotz3VWGWxV+WQJ0OHnltWM5kNT7+5/C0Aqvx 5tfD18PDi42GsbwVq8ffMfjvRcSGRJunBYenWnN4bRIM7pkXenpVhak7vQQGYqFFTVp4Qee5 3hBBFedtiIwtQ0RuVlu1rY+0MPIkAeGSbbmNDlIUWAdzLMqIcPwh43GkyBSwMOA3ng45z7D+ qAYCe4blHmPL4KtNc1x+coa1l8oclCeVYsz9Igz8Gu1uy0x6kdhy6V58zDgkQrFL6z9etC1D MZNbiHUEtPcI1EsIjdUea1LourGGGw57YUFxqZc+hI+j+K6XO9BoouD+o8FwJBA7dgklde8W g8Xby5gB+3Mft3bGBDkpbNzB3DJqK1mMVYQl6NhkYwaKw20GpUnj3rnGgODkZNHg8F1GCIza EyItGpCt1wrogy63sLiDA7oYI++0kcA4uiDpcEx1uzGsUOpaMD+LeP0xjKAlOq9oN5IjOcmU 84wsFQZF3NLBimOiWbSPRybkEFAIJ9MZHcd2fROJWf+sam428ghatlZ0MfxA/EWH0mgDboNN Lcqm2lM6fWJj1vJF8djYPtRDhVMggNZurSmPuPeO7a7AD0mJSYG12UBpySzxcC/wd6JMQ5f0 0lgbuBfjU6RV+XT41+vh4fbP1fPtzX0QHRk5MYyuWd5cyx0+HlS9e9NAgZePayYwMi+t1keM 0e3Bgbwy9v9HJ7wEDVdJVc9QHTBCal8vkCv2MWVTgC/RJF6WUD0Ahua6rdr+672sUdkZQRk4 wUmn6vwDnL9yHvE5UPBx98mZ/vpmk5uciPNLTJyrz093/w6S4bMb0S4Cb1a25TnOiBMmpN+o dUJSjyHwb7YYGw+1kZd9IvsS4tDZhBCHzsqMGUDHPLzRYA/uUkUwNtdwZU2tOiFFrTvWgv0P xoqLoSvR0IZ2iCrydC50xtJ1Ov/Ynrl3Z8eWNp54Y2um6EyLi3Q3a9XRgnKEb4Cdkgh8Zgu1 oL/n326eDp89kz+x26hkaaJd8fn+EMrSwSoJGMEGFZARKlYUpEUXYNW8Cc0UtB/Qk9MzXi67 tkqoWccpiLZYc/b6PG529TcwGFaHl9u3f/di5XmgCNGkWEuMadCqzILr2n0eQSmEoqP6Dswa z9rEJpwxbHEjhG3jxBGmfXcddudom7sA3RwHGAwc7IMo9Oo4CwN42ARGtaLTyEOHdBbDIui2 jofEtuRTcQ/BKg6yMyn7CTRaz/q7a2u+2HHRpjfct4YKatob0iK6suSTeXt1ad8yR5vPhgFH tz7+QYsANxFE2pihGihAFnKXHKhVtJizMKZF6s1RVD3nEVuKBm005BM5mY8mMrp0wMexYYxv IeXI/t9C0pvw4l3oBDr+9vj8srp9fHh5ery/Pzx5KjsinEtb0kKc0vAjQ8NLiVl4aTpwrHMM U5EgWSWok1WCrhlouPnxx/d0tcGaS9JXBtXcZD41Y8rC/65zweJvW0bc58ITR9jNiaLhMH+4 vXn6vPrl6e7zr34d1h6z3nM3+9nLk7hFiVxu4kYj4hbe8N50fsHggOnShAFLFOf/OPkpkTg8 ef/TCUnyNoHTyGbKC3mBylYU4ojlsdflUrvyPw63ry83v9wf7G+PrWyK9+V59W7Fv77e30Qh OiwCrw2+AJg3CB9hmhe/bGh2ssDxxcCGg6/tP6UbxtK5Eu3iZ1BkF/60gsPFZipV5KC18Gss cBXhK5ohDnoa/8LOUJ0oZJDUaOvcQuaWxnfP8AG1AJPJvfmyR9kcXv7z+PRPtKwXsU1wArbh i3XXAgqXUboIa3l9bPxO4V6V/htT/LI/9xU1De95Z5LARt1loNEqkSfMX8RxGTxa37lBkBQ1 UCNtveBJbTkVNRDBiYrWPTwOf8QEWqeYqC2vCDYh8L1QhqX23C6DkijjuC2+QLMByWB0V7Ph MJj/K20TDAzaTGoeQNqmjb/7YpMvG204f9GqmAqikZaaWkFHlR1wjUzF645K7zgMFDxNkOqG ndstREdW+3ueToU+ulbUuu53H8ItuEaPkfS+Af6SWxE+9cCFdcW4suTuStkdg817oykM6ahn qcpVrEjS9MkKd3AoGNJwS+PLDfgo08ETPbGEYEgGy0SoLUZOH1aEmXF+ZMSEuDB5i3GFNfm6 YgJmgkoET+C8y0LtM0EuuTaXMuGRTlgb+OsbGPrbKPusoq2YCWXH1yzxPGdEaWirdIJjygsZ 5DhW9Y217ngiKDBh7HmChCcMUVWikeIb+ynybx5cXvwfZVfW5Litq/+KK09J1UnFsttu+1Tl gdZic6ytRXnrF1VPTyfTlV6mpj0n9/z7S5BaSAqQch5mMQFRFBcQAIGPuPrfjf4Gs57bDAZ3 8BtC4XykQ26q//2nxx+fnx9/MmdVEiyEaWLy/Li0xdZxWW8AELOHA7QoJo3HAftRFaC5ZbA4 llJeGC9TJVJKuEt4OSgd4G0Jz3F/laJyYn7qugnJ4nANip4lJmTcD3NFC00HgdLvg46uBqAG POlFRdiffiyxZEtFEk4sSF1WLdEYeUVOIXZJhSSVlzzsPT3UiUCnNpiGOFrBwF7pMKououki 3C6r+DT2PsW2SxgKlxaWjtkrSwBTE4I3ElZY2KkQqiVXXcyE4NHF2ZvVQ/nuok6spP6U5Hgg jmRt07LN53XhgD+h42k2m7577/37E6jO0vq4SgPXhTPuVdQp3T0SdAy3oWMdEmB6GWQAbklT FYFklSp0MH3k8mp8jCbIqoLwiPWSUR0yFCZVHzwTxMhUGC0KLyyxa9Fks1RQFJoKbzeNO/WX Rs8hQ9f03TY+hBXqbpOVpKyUfWX9Vr5UW72oCQwOPbBMopoOPeBWBt/ulsGXvPZqL+Xj+GzU dGkX9vykJg+pDnddcm4NCTWHz8qA/pg8vr9+fn57+jKpwXCx+XuWhipMjFf70evD9z+frtQT JSu2YanGEFvjPUaY5q8ogx4nZJS7h1OAesIiqFDmSC+pwRqxHh9g/0efKJWGRPRG4PXh+vh1 oONLgFcNgkLtIngPaSZMMPS5tO08yNI7SJPGjKDU9rw6ip6E5Pm//4GAjEDNKpjaP24o+aFJ 5mQHyDplBB3xZCioF/JIHLotEsGafXXK1LvMwiIEZ32/eWpxu8xQmDBxdwghRKOhuys5z4dX +m4+wyA4ZTdLBp4j3gBZ7gKQ6NJ2Jn+yzkc00RJ+Fn/3DS6DFIHb2J0Y0E3shMyA/yz/1zmw pOfAkpwDuCrbzQEsWcIa2mVvH1WFxrcvqb5f6l6BNQPPaH9hj6E/OsvB4VlSfb1EOtscisAn rChYvz4x74qAMM445Tov8WOGeEa8YVPwYEvCbimzX1hu5mPM0mo1nXn4mUcQ+ikhjeLYx8+L eY67+1nJYiIzd7bAX8FyHKMi32VUs5ZxdsqJBEcehiF86wIVVrC11AHWalnd/Xj68fT89udv NTCAA6xS81f+Bu+6hr4r8W9o6RGRDdswQD7bIIOyPoYbURCH1A3d8f0j9OH6y/CO9t8phg1u kzf07VgLA5FQid0Ni/w3xNdLW0mBR4u1PXk32tn+LtvjBlzDcTfSV5B/NdxZ0d0/YhqeVrvh Ds/58FfUhtRwHbFt2Onl8fLw8fH8x/Nj30aThmbP/yuLIHSe02sAOEqfp0FIHiMqHmVaE2pK zRLh8rwhH+a4RGvfII60D75hIDbJpgVSPA0y9PGb+92V00PbvIMIi2xY1EaKA4Aqj3hi3xjQ lWkwKrgww6qzJvqEL8xgSTcXwgFiMA0NRM0CCcdjPGV4JowK1QnMBmhXxwSQkQRaO91EYAFw r0GGhBdDAo0pdWi4ipQI3GybCbDogxyCDwyHYthvRivxxYGWqcBwpOAEGoah6Vq3ggpRa/sq Gh4P7S8jzhFbgckjKy888LHglCAFaEeRwZUt1hmz1MWYwpxCW5LlYXoUJ14SYXtHrUWT8lS5 UNwjmZYhyYmzrZ0Y2NBUaxxnlMURz8EC0T46miv1BearLczc5CJSlxpYGeo2an2Ne65cjtQe a/BolyTm8AVqAbD84lLZcMibO9vpqQRhfcOPfQg/uT59XBF9Lt+X25CezaWfK2xUkiEosrxK spTj2Qs7lkhbT6ET1Bhnj389XSfFw5fnd0Dvu74/vr9Y0TuMUo19SsUtAlwsbog4fmnlnAvK /IiqvY+vflEWIUsQYLeaDufuxcGy4U4cbn0yfbN+tAV13LOkcKyKVBJT4uQYd19fPwjzNowz uP7rxAq4QAu9ZKDj1idNzszsyL0UnT6ThhFhMaB4Bui9BA2nL4cCy0hqGU7O9tTZPXyjOJDa E+Y3XeaUqNyWwkcIhQ/pzDBi8TC12lkNRVmOO2xLNVnbPOrBdzZRlD+9Pr99XL8/vVRfrz8h 705CGxTKpcdhINBGD42mWbto0oydww2iRhUXPNQgqSAprFF1eYi69G7a1XXishQTptGem6JM /24+zi7kaX7oKS5rIgGcceKyijDfufHUhkcHlwfYwVSzbcIdRpCf7DZMrlDY29AeuyhYnJqj EYrB03+eH58mQRvK2N3l9vxYF08yN4LqoCHZd2Gcm/4fq7hSETw//fbx+fntt6/v128vP7qb 52QryiQ3T12aEinQDxbaqQLsijMzjC8v9IsiXiQqE0pdStPRo5OKQTSb1rLytMZnNYLmznJC thzWdXJtTRoPuv6yqE50RboZwnVPCqvTiHkzHDwwp4OCH1ExXpPDY2FH7uhylWiqn5XiMMmI sGfFxsQl9RtmehcVF2GgkaEs7YVU+aHGZ8OEvskFQcrO/WVSelvxfPp3xWcWKBHTVzwGcNFP ZOuDQFRgUP37i9oY/y9qKhuzVP6TNqg57cyBYOrebQRJiWvEWYQNsZMxq4G23X2nLkKet8LV VKxaLemUcOyCZA0NpWO283trXFhLc66hYtODFF4bwgXYMEU0mCyQIZpZiEB2D8/nszPuEFDI s/kdBPyKilKH6goD5q+XeEBzw3JICK9Sw+DL9aXPg5G+bZhiC0HULFVYIwqV+/cVUnlxycss duA/+99RbIZ7Lh2hizOeENXQC4Z3gi913gQUZz84EomkEDENqz4kbpFqXrEbbuHYFxZiYD6o LjgmhOouCVXUD7FPnj8ejUXcCakwlcJJwP2m8/g4nRHfHSxmi3MV5MS9ZVIUJxfIhMAV+U0i ZSbe5/mOpQ76Xde2LaRS+LgfrORRorYB/JW+WM9n4oYIyZfCLs4EIIpC0qErdjuTVErRGLfv WB6ItdSSGBWpKeLZejqdDxBn+FptRqSUTAsCcqTh2ey829thFtXQ9RSfTrvEX84XuIMqEN5y hZNycJjuDrjGdRCb2l6vIsHWNyuifeQqnLmiXYfvh3J7SSYfP759e/9+Naewpsi1OcNnSk3X SA1DHFKfXa5ucSO1ZlnP/TPuFfU3t960NyH13ZJP//fwMeFgG/x4Vbf51FmC1+8Pbx/wOZOX 57enyRe5Rp+/wX+pFQqbeq96BielD5Mo37LJH8/fX/+WdU++vP/99vL+0ARoWIY4nCsy0P1y KhpP4esQ2eottSJEUMdQnnGOo9YWj4mdMKRPgN+uTy+ThPtK7dA6cqM5C1+aAP3io9xQ+qVd RTtILaKIPuTKIK8h+d+/taDH4vpwfZokHeTLz34mkl9chR/a11bXzSh/R7iOznEPgccisujQ aJ9ZTt4Hwm3ABx70J6YAd5jeFIyF1cw7SYRYSLOSgvFAZfDj6Lxmcp56XKM+d1MZymoPIS4U 1DvbhHbiJVrRjFplTn1G3X4NRP2zXEp//Wtyffj29K+JH/wql66Rk9rqCXY6+q7QpQTIQE3O BIop3NZZ9DUjUUBQdGCqyu3LtmgTfMxPoD7dVwlRjoatKHG23VJ2v2IQPjh9wXbBJ0LZSKMP ZxIIAK+AQe+9M/L7s8Hm4OrvESYBUCbjLNLGF0SMu+Yp8rFqpP2o7ngf56jz7WjGANcAFS0T gQKC4xT2S2mtC1ArdaYbBZ9dX3MG2TlVWBQWHo0k1YZL1wgovM+zAKtLEXNlO9dxqU3S5cfk 7+frV8n/9quIosnbw1UKrckzXDr3x8OjkZeuqmA7v/9SKGwxx/EOAjbZOb63nOFaia5I5f9B dTSP4PEMi39QtChq5YP8lkf3Ix9/fFzfXycBwAoaH9jpOIGc2wEBOqjefidKwqzXjTtTTdsk Wi7qxsHtqWgLFVvX52rUuJ0sp14UnHAXlyIm+GGIohH5IHp+SJHJiT2o6fshIrEGFfGIHxsr 4iEeGO8jtR41sZT2dH+Ty0c72HArwMSLsSMiTbIRinVZURL2rCaXcsgG6flqeYuvA8XgJ8Hy ZoguFgvCkmjp8zE6rvN2dFzl1fQLfTGQYpBbOb5KFHWXl/PlQPVAH+oeoJ9n+AFSx4CbYYrO y9XMG6MPNOCTAiIeaEDCCrmd4ItFMUiFyB9m4OknRoQRaAaxur3xFtS0zeLAFRy6PC85JeEU g5SBs+lsqPtBSsrqaQY4JBSXgelRBAQQhBIVvjdDoTVr6q73TQrgtIB0j4F3Stm1JMzSfEh8 KeIQDrZmKHgUEwE++ZAYU8QTTzdZ2s8eyXn26/vby39dUdaTX0pgTCsHjMGakehs0JNooFdg ugzMBFpd0uN8Dyikvc9qDkP+eHh5+fzw+Nfkt8nL058Pj/9FASAaXYfYWLvLEuxH+qZ/TTUB xRtt3QIZ1/eEB2EZ2gE2kgBIooRkk1SwlPC+rInEzRQ1cfDRmwVxW0bQZXdTDMquIu5B60Ez Oz0TJM0Vr/1eCywEGsmJW3EmB51MJYnKV0wRRcpysaN8kUmlrpCUGsyRw9V3lFEEbyHBqCUx LLDEHfg0XmvgJjdEgLcoaFSVMHp4nfdhkbk9ODiWqgNjhg+lJOrjQooaxcyJMDKpcKEyMUmg 9+nQoLof1G1ZRHx4k99DOG6jg3CSLbX/JQzDiTdf30x+jp6/P53kn18wX2DEixCCM/C6a6K0 tQQqDeDgHMR77V0x4deZDwDZSSaHeFMa81/nyIEH2WDm3GLo3SkNAp6cleBKx12Qdwepm94P hEMSZ918ICK6DAk3rPxiMhzueCbv3WG+CIlUTvk/kZkIq7LMjnpScUuyRGGIFvI/9jllSaC2 yfLqqPq5yISoiAT2I3Vmk8YJhZtZuCkDeq5BJELnu/1ie/uC54/r9+fPP65PXyZC2hmPXyfs ++PX5+vTI1yM1sciDAEENnUhV7THqJr7mYPtpVCA5v7iFvd2dwwrHHLnmBUloZ2Ul3yXoUd/ RotYwPIytAFcdZHCG4+c1YdUsA3t5RCW3tyj0D6ah2Lmg1SxVT4Rcz9Dby+3Hi1D545LP0w5 hfCknOMlCoBuVpqwe7vSMGXtUI49a9/zmQQrz/PIM8UcJiGl/uvRThOfWpEAM3XeEiEKDbG+ sdgnVm7bcDMmyyyHz84s9yArY7zFkoCrPkAgWikp1GjRcfRN2w5yr0YzcEFgsCB08E+lBMNC 4YwaN0XGAmdZbm7w1bjxE1BKUY9xerbu1/GdKdmsSb7N0rn1LvkgcTqckkHiXdt9Bwl6k1K9 Uz/jsyM/JOjAS+0pFvYVVXVRVeKj3JJxk7sl493ZkY9Y8IjZMi78zF6exIr3z3LiEwHqweha DkJnSZSHmDthSTNvSnhwFDP+5vDmjHtlagOxWt0QdyUka2+Krz35tsVsSVimWpKceeGjl9GZ 3+xm0AfxjDjPOaQBgQxp1Ac3j4SWQboJZ6M9H97DzYDotAzPzFIcxIyI0j6e0QxDo6ro8ImX 4oBswVFy/OStRratnX2/SO6h3gzjAefyq9Az7w8J7etE1M/Q/V3tTvbpEN/i6p8sPxLoMmfq EXInURSqupsp8ZAkEM9EiTfFQgDNrlrNFmdr2nxKRkaz9sVZ8v6YUFiCCSiV4K7H5/YenTti f7HEOvwmgVjNpsl2sTSzvieJzzcVEcSvaKQZJamLQao49chIm7hf2Ghfe7Fa3eDCBUgLT9aN ezL34l4+eib8UuZLL4V1rAS/vSlxpVQUsjgdWYMpk9qcjcdfF+G6g1jNV7ORZSr/W2RpZgPb ppFK+Bjbmlbz9RSRJ+xMibzZvg+jrB7JXfMEaeiRByaKqALHDsJyhwrObO+8ZldRCx5uW6DU xRrxMUy3+kbxTgBKtVlKbbTCSwjRvREfMT/u4mxru/juYjY/E/Fyd7GrVhkkYk7Jl53DtCKf C6lUnqaF0kyHGEqrjbIAUvlGFGxAJC5Da29defO1j2GUAKHMMpdXFlU5IdAaOuC2VuWJQ77U IOPKI3BbgUFdvFic1a1i2CwsVt5yjU6zQqrEggmcFthYr8vpzchaLCAdrUArEyyRKogVYyGU vePYWsiToQnrbxJ4zCy7T/jr2XSOJbhYT9nBE1ysCexhSfLWI18sslga2vKPtbgE4f6R5RBU 748Z9iIRPiJkROKvPX+NC/0w5z51ZRrUt/aIszNFvBkTs6JUp2vWV5aJcsaNDuAhtSVPnl+S kBGH1nKSEJHRPiTvpcRWwbH0GbMRlzTLxQWf6WW4O5SWvNUlw1U6TwDsttzLGYXa6LgF+vUd uQ2iIUe82PGU8KFxCEOJM99xD/erPfH71EbY0yXVaUHNl5YBv03PqFwbKchcBcIMDYmLgsDq uCCMiC1D7CPcJJPWBoGCrlJUN+75VtO03SXm1iUgcRjAISHc4gXUnn9RKaSf26QL7CQMWMC5 AHDJzq7i8PByw9I+tAFcNw/vpl+h7hze4a5oJve4tAQNhGIoV9P5mSTLlt/KLXuIvrodotcu GJLB5z4L6OYF7MiHHg9yqQPerIbpy1uSHvFzSPce9/P4IGiyip89n9iFZIkFB6/p1PN8mudc krTaDqLpSvEfJGdgfQ9zgIpNcuh7Cxn9krvBx2tNiaTD/kITS2kqE1E54P6V65n79ADVkUYk /cxjnp6rrVxjswL+xh0uOd4A4biE6mIIq9d52c3RVOfWkSSflbgUAOKenSjnMpBzgA4+4Od1 QC/KeOURmQgdnXA5Sbrcg25XhLQFuvyTEhBIQN4Rt3kCjec7XBM4xeatgfCrO79IHBVblqzw FGXrudI6eoArcwfuzyt3C9wlpiiuFWxS1+Rz6z2gSRNaShGvPSIVRD663OOKDysWixnuij3x eDkjAhFkjY57pnvMT+fLM2aS252Z2I4FVUC863bpL6ZnGO+RWnHPPP55snwgI2RT+ImgNlYg RrgtZ7am54JmvCCSiSSh8jG1xayvcQ12G0V+mlHKFNCo6034Kb5ZL3HvsqTN1zck7cQjTD91 m1lIK8nSvjPINsG1qrBIiFiBfHGDJCN25IKLBMU/M5uDuPxiuDe3JCLJG6IKIoG0ZXx/g44g TlGTU7zCXJdWq8KAM0cMJXKiTz3MojCfLJjrfS/K2RnVPK3H+p4FJbaJMDhNu0UqlRR144zo VbWeEYEvNZWIJq6pBDwGUG9nczZIJVxU+iNW4eB7B6hyUxh4L3wvjrUNVKndjo6ksCwS+bNa o8fg5kPCxt84EfGR5iO2xXiKvdkCP5sDErFNSxK1g59iwpFstuH+ErCeznIfyNbjTQGS5xV4 oHht7BXsQlzEUjNIUUbdydQhjZwEx5d4o3AVgMiuPqZnRIVv6jqh0zMgYfzcvxXnl8n1XXI/ Ta5fGy7E0DpRUTYJeITx3as+lqoogHYRENA/x/59rvzt248rmQbWQHSYPx0wD10WRXAxuo2K oykQ0qMT6a1ioRB39hq7wLB+gJYwaSCf9w46s2ru4ePp+wvcrd6mbXw4ra1UmJaTum9Tqlww 9IIZh01IOyhMq/Pv3nR2M8xz+f12uXLf9ym74BDqmhwe0VaGxw2CRqjHqYcpYj25Dy+bTF8j 1tbZlEk9N18sVnhuvMO0RprcsZT7Df6GO2mTEkqowTPzCJiClife74kM+Zal9NnyxsMDYU2m 1Y038sVxspoTOrDFMx/hkcv7dr7A/eUdEyGyOoa8kKJvmCcNTyWhFLU8gOIGgnnkdaLMTuxE hJF2XId0dEDOpcPSXy1GiCT8lItwhhRVLDbx2LryzSXAiuFASP6b5xhRXFKWgzWPEevcFbRS HoWbLNtjNAUvnWc8tUPCW3oo9wqIVMN3nq5pISj0nHDedW/LDv5uz1GoqpYpynzQ7+zoOE0W YcEJt7dmYHkeh+otA0wbP1msiZBDzeFfWI7H/2s69Iqbv+6wHIVUm9hQJe1wjtTU8eFWYyud 4fYcSytuyiqWMurG9Y5nji+KjiHA7fyWwc82Bf7BLcs2IqJrOo6CiCKyOCoCQrNjOvA4DhMi rr5lUwYehRracgkehCdAusVPGFu+MiESgLr3qTPrYZ4TKwpOZGO2TAnbqiCLkYZDAH9W4AEw NteGEcEOHVvJ0+1oF5x4IH8MM93vwnR3GJkqTEiFF988Wh5QSQ5jU+GcExdKwbJRiPaW7NMl SmWW3eIz4k40g4vn0hod49qWPnGVWMezY+mJEbH0Btt+I3+MMQ05Qms2LU3lfPOzBHM91D0E 0lTrhd0GYhRCckoeFqVziaDJwYLb1S2uTFhs4DerEgJ90eTcHGbelMh0NPn8S1mKnA4e6vMO xCGZzAHIZMIDZvLtWJKLHZXEYXKGIZGRZjFtWQzwhfQ2aHLXhtUoH4+57E4iqtPg2x7S+3/w Ifsymnmz23FGSnzZTOOdrCZwdVpNCQO5z0ttuCanVIE9b/X/lF3JcuM4tv0VL7sX9VqkJmpR C4ikJKQJkkVQkzcKl+2qdHRmOsOZFVH1930vSEoccEC/RQ7COQRAEMMFcIcPZEli8HwCjic7 PKU9DziAatPiZCM0h6j7ABeLOp0PnMYnoEbTye1+6dlvPjrDPU6N58XxTxdxTKj5aWLf2LSp 5v8Fe8r7GPUox3tOLk+htK9WnQ4RleZ69iNdwlxOZSrPtATO0gc1lSWyyO5QdWgG9fg3IqY/ mYz3jIo3Pgi1TGK0xLVppecDs40O7RQs5h+oXK4X8wmwxW4Ti2ynqsneHhKo2o7Jrq5PlUpr jgc01SvCWgl0EVifXExPEyq8RNvT+kAo1Pm9vZvV1VO0b3cWpPL9dOJk0G4Eh5tkAuu/FRkt jGUKTtGqfMqEppZRkjRuQ8sYBJJpTmdIbkxrpot4Kj+BgOn1idoxLhSKVV1xzrGAfpYqRqi8 iauUvfnH+R03AbJDa3rUKZk6u5RUmvIBQSvraoopWivqPKKYvnbEV+cRCeWunhUVB3+xmLM+ GIzj3WYuncxCyaHwYw7rdo/vz8YRm/xPdtd3qsSz1k0utLg87THMz4sMJjO/n0h/952jVkBY Bn64BPe3FSUP+dzEMkdUcCLX1QFN7zEUSqpCawO6Xsb9krWvkGV4nU0Rwjz2eNrfChVb3QeG nx/fH584pNjAk21ZtuLaHVpn3WFlsFqFm02MvopuMxuCLY36Yhy3TqR2Ryv7lnxZS2MUfIP3 qTytgktenjubhOrW2iSDT0f7k5Y3qc4dk4ncAMNzh+cwERE4MlTZSVR30Amyl2AGxzYqAYF9 j2HfbzUItqYNTJtCK55mDxnQ6JcaqO1ddlECgvVctsBhqXGRTCKA1Q94FB9U3PWEEB/ue053 K7dPL++vj1+GxsD194tFkZzDLO0OdwICfz6xJlJJecGGbHFkPHV0+mqbV3lI7gy3Btrw57W9 V5s06MadSigBSu35Cmtn6OjHhpAWlz11Ks2heixwQYK1VHHNmdko8amM0ypCqwVVIuX4G0UJ Wsw4zmbvtqjhSxMTEOFFN0xdp8E10EduZ49n22sJpR9YLdHapCTX4P2UjFAFeUgP+m769u0X RinFdGJjBW9xxlBnxN8l6Qn/XUbtH2GY2Ops/Vw/gfFZwzoMU6Dhd2V4C6mXSAu4IlHHWsdF hNSra1a95n0qxZZf9gPUMRpb3oxmVQB9/woucrwCE0xdj7oELEPmSvLZWpRYnenTukWLYtRV tbommijbtET3Jr4BrWfseANE2wnPLXkbZ1FsAw5tE6f0UIhOvYrpamEXUvnqQ4bI/XSWnvOh g9ra0dGTRaAYLlZAbmQFGg7BNENy7Y0ArHxps+cjuTpvwtPYV+mjAMEN8jBYThd/X7bIfiil LTcESSzEwRd2effAmH/zLg/ohIl0G+5iPhrnjmRfh0P6k4M1Ok7CJLOGkKD1uC8vn2SSnNfd Y9/qwt0PLfoQ7bAK7IuKU2jFLeKtbK/XnGouRmW6ybrJfBwiOlUwqbTKoNhVjCu7vgIhdeAM 9lTVLUgreq1ukki22foWRIpf8bpVYR/Kt/etO/sdZULpn9mH8s3tmE2Ppcpeesid4BVfAK/o DQ7c9RlcRUvg/aqG2ZUGaCfaQHn9VpcanAVWoAKzI4HsRA1sfQlNzaUVOAzgTyP1fL7CDUX4 ArhtrOEVMORnGHmYq7HeKXzlRZzdqoGvqkNlcdTNo+OfHz9fvla2KtWjd//6Sj3lyz93L19/ f3l+fnm++0/N+oWkhqfPr9//3c+dNhxymxqP4Egtmmnx1p/gr5FhXQfzsULh9kprSCfhrIGW qoyBiyWCK7X/QTvFf9Mi8Y3EJOL8pxpMj8+P33/iQRTJjO/K9+B01VS1CoBCe3R0/susIltn 5Wb/8HDJNAiexLRSZPoSH3DDlDI99y/STaWzn5/pNW4v1uoIneUw/NufTC49zyrdti1BOAED JmjJqvoPR3jBoSCuFJ77RihrcPungeWXzsGec6ctkkOuh+tJ3o3gRj+HZgXXp5++vFbxA4bC Nj9IMgdHbrrHq2aLlUQSRGtukfqr/bUmf7Lfxsefb+/DJaPMqZ5vT/+1vGuZX7x5EFzM6tys QbUWZWUnd8eafWlcsgdPNrAxEoAuhcrZYVpLnfLx+fmVlSxpYJnSfvxfpzU6JbE4bT8uotdD kcOO9lssc/R6EQegeWpQZBFdoRxHLzl3Pnor3WFUkrNFG4yHa0JTYXgtStp5UPbaXwKl7w7F /vYdin11ayh6bW+iBl//5i+R2X7D4fvEJRKBeyR7bViqYjtLIgUrEI6l4SR5sAR3sA2FKj0j AcXJoalwOrNn01R5K/bb+JKUob+a2aSV3VF1nYuZBFq67bdOFVrPgzs51JlNK0/utqm5CRND QuF+uy/sB/EDlr0hr7RoOQO3th2KXTHzRlHeBKhCdjl2MarLsQuNXY79MqTDmY7WZ+WjLduV U0JHu13OWFnEWaBNfoszFiHIcEbaUIfLxci3uA/KGB3eNhRvMsrZCOXNd46Z7BbZKKdNrkKH IE3F19A/QUMpT7n7zSK9GAnWxMGSRponYoNbrdCpVUWS83vaxNgXpGsDLb1gMreLc21O4G9A NJAraT5dzoHA03Bof6Tss86VUuoy3pcCuXxteNtk7gXw1O7K8SdjnOViAuIA3BjuYbGTu4UH tle3TzEf6Tgsco52Z1kG9rWgIXwKwdLVEGgkFJ4/0gGNN2rg0ObKMeuNe6AbzmqkrDKkRdDd 25nje6NlzXzf/fKGM17nmQ9MCrocd51ZkFhMgGFkh+S5VwrDWbhXN+as3D2D45EtpqNFLRYj HchwRiLJGc54fabecqRzqDCfjq3aZYg0Xq6fS4FDohthOUoY6TVq6X5dIrg/YaJQbLsbYayS wVglR2aPRI0NVgVc97QIY5Vczf3p2PcizmxkSjAc9/tWR9DuN2LODMjpDSctwws7pVUSB+lp qGFJY9XdBMxZjvQn4tDGyt3WzFkBTbTb622C+QpsPhU8oKif1rtyZPARY/r3GCMcycNxenmV d1TsLafuzxSr0JuBXVmL43vjnMUR2ZJeK610OFuqj5FGBk1FW09HZkwSnuaL08llxd6hjvRq wwHBeG41U4uRJUxEoecHUTC6/9LeZGQJJ84y8EfyoY8TjHRKmQof6KK1KfCy9kqZ+qNrD1BY uxJ2KhxZLEuVIxe7HYq70xqKu+mIgkLYtikjr8xeu8J8PyqqEm8RLNyi9aH0/JF96aEM/JFt 8jGYLgPPva1gzuojHBCzuMNxfwlDcXd0oiTLYF66Z9+KtUBRGG8sGuk79w6uIsVdlvOm5jre +FLyA9vn8n7idY8haoZZOEXrYr5OuB5L9ZI53Adbx7BTs7blZoPXcWAu24yja8Y5a952VDps xI2QRaV5Y30L2yOsF3jB8Vdsj9SnuUmShf1QjYPncK0sROd7MoG9sl36rtksvNtLoZz+P+/A rraNIqOVVXkeM/mFiejOFjXlFCwu+T2fNqv82lG+9rPQWXiJSt0Q7F2YqNPZ5MSn+e9fO7pw 7dyYYsunX+lwZ2PVnKMow12UdRyBNmn45ujKSLOjOGdAFfrK0me9GSoRHB9/Pn1+fvtzaLh/ G5HZprxmYy8jEiVbXVjB2t2YM4MHKQvWLXaS6mgIblJ0dOO8kZyeRqojwt/2HIgHvZKIDpUJ NWYkUrGmgZOwJPkFEswxWoDroHP2VHlBJoh6HV42ssxD3/2q8b7InG8i10sqBqNKaPuYPooN jXv44GI6mcR6jQkxS6YQpfd2gMHS8zdOHIK73N1gVcw/+LjZ/XlTiKcH+MkWE8cL0/ekFReX S/jSn2GcBCzcGY03QpLep57nqAGRpsv10tF2LMkhrJEqXIRguXTiKxfOrrsfXO1ziXPa6kzd nzeVK/YM2sumVjaSv/z++OPl+TZpcnT2bgjAUObhyFxZ5pa48nu9Hs2cOPbMuzN5/v7y8/Xr y9tfP++2bzSZf3vrO/SpV4S8iPn6mlYOXqgt65Jmo+NMa7k2Oq6VZvjbt9enH3f69cvr09u3 u/Xj03+/f3n81glOrK1ODdahEoPs1u9vj89Pb1/vfnx/eXr94/XpTqh1J+otPzZ4WfXXl5+v f/z17Ynv2F2OaDeRI84Agzi+LMNCT5dgP5ErGVbuaMDZNz9v/FJMwL7QFHDK/Qk2VTRVLFj/ BehCcCUiwX0WPs/w3HcWYSi4FRgGVxZX2L6FqWFklWfgJMVZq9Bj5/mw8ruSlY20DO3FJ3l4 kUC5gjGkXcdFV4Ibq6UPYnoiHtLOYtonkT5cQpXBaB7EuSepFUSrZTgIchWAS58bjj+jwRfA Kty0tjh5szk4d64Jy+UCbFevhAD4tKwJwQoYsV5xcGN+xcGx1g23H1sYvFygUzEDx+nG99bg 1pYZB5lzoHtR4O9E06pdT4HBPNzMabTgFiqicIpCOhu81IMwJT3CfOLKn5/vact1CeG8nIMT Z8Z1HLrnVC1ny8VphKOg7ztG788B9UQ8L7AwYper16f5ZDJS9lmHYIvJcCkvQk2n8xNbXAvg /oWJST5dObo66+sAd2amI4hEASefbEztTYAej9PS2tTfEAIQhPdKABczV4Lv4WFCTcRv51h0 6izw6xtCAJSEr4SV5164iEQzIjjOK4/JbDJ1dAYicPwOd29ht5PLqZuTqOncMeRK5Zj0D6fA sfSKQj5kqXA2wlEFM8eyQPDUc4sYTJlPxiirlf1ouoi3fGwDznaML1mjPWgzfN2+P37/zALl QBtTbDuGgPSTN832Qc8Y8LViMGXzFlQji1nLYIKSBn6MObGKUwQLQBHZDYajvTOMdOEZizcb GcbWwCiV1LEtW/bAh62g7rIeJPCaeNnme/2rt2jt1QisQiXHRZZZSoiKVlBF+sHuS+Ql6nqF 5fSImnF/chqIGJrR/1M2kyuG75WuLUW6pXL6Zm2FNmv2b3k9M+zXK8lEdKHOF3FkZcUK/IPe xx3+5dvT2/PL+93b+93nly/f6X9sBtDZRXBulQ3McgJcnzQULRMPWHM1lPSUX0oSileBffJj XiGiGCxRDFO3pQ86eB2SU+/+Jf56fn27C9/y97enlx8/3t7/TT++/fH651/vj7xb6r9Ymu0P sbB5AzYVJtm937Ccxl4Qd9Zh3SeGIi/3RXyJ66jkAzxTxs0hJPARc14W/VocUEgcA6rjdoOb d6sE0p5ieB/Zz3JN02sQi5NHyFZskVdzxkNZFHt9+Y26LOT8dsJlr7NwZ7NGZixndyLNrjp6 /UGb8n/uctqYf2mZb5tMChlt4z5TNt5qaUf++vzny6D/V/4G5Yn+c4LhEpi4k1rSX0iGNiNz 4NnelLZ5f/z6cvf7X3/8QYMw6vtB2HSC1DRD2gxwS5PQlBEqjgTaMsiktDQr5aaj3E6JEZDx CFpnGYf10a6ezkXRn41MkiIOy055DIRZfqaaigEg2ePfOpFlrz6MFewEWJ7ihK+NL+uz1T6Z eCTL2ktmwFoyA6jkDQk5cpte4pRWO9uy05SYtS/SuAnjDQ3fmHbDWS9LTQsNsmHY8NrEe2Kg mskfQIT3Ayui1uP0bL02dCtUysS8YFn5rBj2r8+NWaHl1Ii/gRmqqFa5sm9N+MHzOi58ZDhL BGQXzRCtHtTu4EKAO4wuIUjtDPwNE7jnPgyf7GE3JN7I3udMkdo3r9FbWITb3S93Ey/yYJhE LhcLYDxa5AFicgkU3hkLgKI7YUkcTOZAxc503LLIYHUd6zd/5/LsAa2UCoWtBNytEyIOSL+W USCfcsPGGU0GEvbJ+zPwiUjYNAJrLHeqLIuyDPaVQxksgFdrHr20RsV4HIjC7qPFjEyYaSgK hSLHEWys92EDKh3u8csigYG72JrEjVM5Q/IGt4Usyj24Puae1gRzhYQ1tSUeOibsjN7FIIYR t+c+u9x7K3AyaPqPyoGPCdM4PSeDNXSduy9JGDULaMdXECWHidBsfXCQ1jjctzzaxNtUf8M5 kH3RDb16A40xhrX+N05OO9yZR/v92H60d2NqQXsd+4TTKjLKgwDoivZYwAKm1X5qijStW6TD 3J8sE7sS1Y22jhYeOIClJUSXwipq7CITorhaJd++/Xj7QitnLTtWK+hwB89bzHDgVYpEvyyt lAp0WGRJwlUbw6kHPsS/Lq7ec6K9Uudh5p1k+jfZq1T/GkzseJEd9a/+/LreFULRHnXD19aD nC1g41knL0icKrpCpYVdZOVAtaUZB9m2IzbxbzaZoF21opFv/VYtzmDlH1LCZF/6fuukQ2f7 NOr9vGRa953ddNL5xpCGoWwdDOhOLmlUucToJuVh94HL7hi1nY9x0qdOJ2hSGl937egcjOn4 tz3rghSD5OoTd5Op+nxI0E1UJFwXDA3qChMvebLfytQCWl76WsVhdrvCzm+ARgWs41aIKOyh mO/7aBXLCqtXqvQ6zZroxyKXvboWWXjZ9Kpz4PsMdtRP4Eb3C72hMi2BazSuGwghb7JQgkM5 d0uNFO2ptjRG+gUW4qhI1uMGgaVleTJlB4BjpNkoSa/FMXYyqOt4k3uvz2m/yjDmYdUxNFBo 5We4m0KUttoZfpbkBW4hiKsyF/ZzuKqjVW6vvMUc6RFzHvm+p9rbeTPZf1kReUEANKTNC+kp MlerYOhrqMLlfIZMuhjXcodcIDBcSom8bV1hs5cEpn1M2gdos9DAyAauhpFBH8NHoK7N2EM5 nSIddsLX7OwYoqGYeODI0sBKoqtEM4ROZxKr8NN65gNL/BpeIJX4tFa9wG1SaWaIPbowN5zy tMG1j0SRCMdH2Rq1fggn4ux8vMoeaOs32WO4yh7jtPIDXXezemEsDnfZFCivpayvEEngaOQG O9q8IkSfRnPAX77JAjPqSXcMd2SQam+KLMuvuKMA7a2meNAxjCwoCd4o5GXerP+RY2FgEM9C tPfxkEf3K+7oVObaKDjhdmkIuAr3WbH1fEcdkizBnTM5LWaLGTLF5p4tYvZ7DSwiKsENeh4k OFU+8MBVrVynHbA7YNFD5qUEhwAGVzHwmF6jK1yyQYFGQ7Usg7twA0q9nCCrXsazVIYHuXa0 q+tIpRIqRAANmG74yCppjjIyEBHZEE7QpJrQs9rYlCN30S/mVqvlh9aMFNGTqyPR99nYJDc7 jt5QExfa0JgEx3gUjXf5OHYNW3HJWbHSXDsi25aaGFIbhk3M0w8wHbGeukQtt+x2HXht7VDR vXOXxdv+D9Acp+U9YpbGJ3TC3aOKvv2Pg+gYli2iUUX4UDNOJ8gCvCbWp01AQN41rpD4XDa+ 7ucmfU5vs910t+rOtZ8f95ckC/tHIYzv9brfuU0YI6fwZGKbC8+xUFXRz08+3qhUsd2lwNun Kg/P93GnZMpigyLqNIyd3CDTKSMGhxG8dWmyyDNgi3fDd25GSf0X+idvSAdBOyyrv2OzArF/ 1sEu+5Qb3+d44YrMxwyBVZ5ZA4CrGXOEw4dUljAAMhoe2+26/pbp581pVlnE6dYa0Z5otHNv P7jfWW9mOb/bWW2lU866349fTHUGLseZL2b94IEmNSysTkcNxge+gwc4EQSQMfiexxjIcR0n 9zIdtExcZvllswEPsXZN0TqOqtIk/Tr3c6K5QAtH5fIiiySH6ICM4fzWBq/BJDvP0EfbZmkh QfRrpsSsgWPvdwZOYuSiuIJtykUGeaC36ddnG6u1BLq1Bt8AD5kM7jK4oJpny0UwxQ1MtcGx lwzhjBtpH7J2BFBSJ/xIa333SKddsXMx0GDidMkmbzDL8ijTnfWWvnqbVEsaq8NckxBb3xoc 3H9UWJod0AflFrCN0yb9AjaNHQ79yG3tdCVsOieGnFzs1TqJcxH5qJ8ya7uaTewDldHjLmZd i27mXDFzOWqidsK6K3HeJEKDWZE2LGzBkW3K7jRA+3uaU4cjgCOPyEFHbBFSEuW3/adoTbKG RjAzBwlcNA8lWdE6q28lWt7aFhGsA5ciOaenwWM0syUh7j45h54teLOCZzFznWLfhzBcZGEo gOkewTSF4obQQul9O4aJSezNxfzbNd/pPI4jGCbEMEruS7TAxbZDesPYp3myH0zGBfLWynME R88SGsivJlMObfIpO3POeNKQcPjS/KTjeLD2lzuaRvCcW+5I8i+rE348O7JscMmB+kI1P7oW kaOUMCQV4ydJ3RWiD3GRORvl4RyRLAH0NUzTGqcElx1wAmxkh+R/lF1tc9u4rv4rnn7qzpzd rZ2XOvdOP9CSbKnRW0TJdvpFk6Zu6tkmztjO3O2/vwAoyaIEyD0z52xq4hFfQRIEQSDtv67G ZxasjGUEWtfmxLSdUCHM1dfJGbqVWVMBcrPOSluYTeI7QYm2UKFXWXbZxZxu5luJxieMnUah oHylS9+xa9qBxTGsHY6HgcCrC3tdNyLaHh43P/HB4O7tQP2ze0Wr1IPdN7UTBLTrCrR1E0Zk 8SbMgiU5f2iuaOXKDzDEtWDRiSjYCzWqThboORXfX/ImgAjtuETFpBV15Ez1nWQQY6DPeufk s555ek/fX39cf/iAXS7Wco0D3AG0yF5F7laP0jO0cATGLnOpYQTLcxxNDfJsh0eJ2rkQahc6 7NecRmKN0QD9dLCJgU7H4+v1WczF9WQQM4dxh9IGeis59RaTyjU1GWpqC1cI46DD6Xg8WOts qq6vr24+DoKwBuRlOeoYMjUcV/l4cH4+HFhH6CZAslR9ugH2sh6Tu/LQ5rYRsHH2Cwv5/4yo 3XmSodHat83r5uXbYbR7GWlHB6Ovb8fRLLzFpaPU7uj54VftvPvh52E3+roZvWw23zbf/neE 3rbbOfmbn6+j77v96Hm334y2L9939rJS4XoDYJIHfFu3UUN6Oys3lau5ENW5jZvDzi5tfm1c oF3JuLwNg38L8lEbpV03EzxadWHC66Q27HOBMZGFyOxtoApV4fIiTBuWxJ58FGsDb1UWnc+u OvuWMCCCj/822ouhE2fXE+F23KjN+L0+eH542r48cTF3aItwHen9LpHxoDDAWcFA2Gv6nlYB V7Avpn1zJTyUrohSQMMZ+e3GOJaDi+9H29yt6RaKwCWsN/3A181ntqwgfO9FgfA0vaIKrrVp rXOLvOCPGqZqS+3J60EWJJJRpxEdFkkuHrQJMbCY1yzr3H90hLf1BkZeheRRceWjK22HuRvI Ubupj1Bn5sLohopXA1NPBRr+LAX7b2qr3FSMX+mAlDjLxDeE1JRkpTLocxmBm5/MCb72crM/ zoM1vkgaYGU0lJzzge0QcA9fy2zjfaGeXctc6WuQXeEfF1eCD7426PJa8MhJ3YpRvGBkQDod bL3jq0TfesIIOkw0EJyA6Y9fh+3jw89R+PCLjwdDcoHPZxsnqZFOHS/gzZEaoU24g0D6QrkL QS9eCegkn8tLdZgGYtyUYiU8g5ccAHiRzgM2cheedfC0cBIb6exAVsuWwqpJLXtKI+pZVL8x PU3f0Ttjfsmp6ZK3ZaKnjrq5Eu7KTAb4pJ1nt4p+dSW4czzRBV8cNV1Yriv6VPILUNMlm+qq Y71lUkYq4G+bTp0gPK5vANfC23YCzNyJ5EqX6JWXOX0pyWvmWOkofMg/AAidq5uxcCff8MMV 7y2X6EneqUGHw0hW/vpz+/LP+/EfNOWzxWxUKYDfXvBZLHM3M3p/0gv90ePRGUXJleuEzzll ahw4H6ezfpgqrFO+3z49WXdD7eN5f5bV53Y53pAFA6FTlGEtIOyGvIxmoXxPZfnME2RxC8o+ cuOhTso/HbUrWGlPbI0W9eP29YjhjA6jo+nM00DHm+P37U+M+/VIz4VH77HPjw/7p82xP8pN 32Lw6UAyLLGrrmAYeAnBwqUKmICFKcfx0H1UEAbCG6kA/hsHMxVzp3vPVQ6cARLUHGknK1pq KyL19GCY2sFU4a3JmWKb4YgoGUFXRDQuKCPbUyaRooj+Ml9muYMmzKdKYAJ6pb6ejqd9Sm+3 wUTfyRPNRuNGKlDyxHfsfKrE+rXNu/3x8cM7O1c+ChhQ4NhdPSVuTVT8AlbFedNx3XQ0PmeS jfrTKrhOL4vAo8f/LCNQFbNlTypqNKlYU2abrb9Ts9nVF09QWJ9A66nwaKqGuBqkG36Nb0ME p88tyPVHfsOpIejY8kbYbmpMpq+cizP5BDocTwS/zzZGsOOqQWuA8JqDGkGu5AVpwcJI3sUs 0O9gBK9GTR9ejnMhZkINmd1dTPjFv0ZoENFuhAgwNWYeXUjxXZqxAtYSzJ9akCvB/Lqdi+BN q4Z40cUHwbF7k8tyOrVPKsZsIw0606g9TTHeKZqlpM27McRj/LzfmH6uvpgIcmprQCfjsxWH tt3Yag3jy/HnwxFkn2e5/vi5EyW91bSajhPBv1ILciW8lG5DroYZEuf99ApjTgUhv+G1kB8F yf8EmVwKR8mGd/Pb8cdcDc/+6HKan2k9QgSvim3IFa+AbCA6up6cadTs7lISxRsmSK8c4UxR Q5BN+nLy7uVPFLdsFmnspvTm5QDS8xlGbt0e5h0LrArpRup0R9Z8f0oVdloA9H1k4KMqL15Y Xi8wrXphjGqAOPZCbVPRvWG7bHN8CYAkeLJBb9auoHe9cxL0AYL5RgshPvEJw/XHCvN2atvI U4+YdDbD+puO8XBF9XWB5MblCRTrmEil7RFTGBW9zNdiy1w0rWWkCUifFfP+PSblNw9sMzS9 onRevC3Wg4o2wZYTB7d+g9ar3HK7h2pxHIqfBYnoSbAiRxETYTXaPu53h93348j/9brZ/7kc Pb1tDkfuZlrnahGwXuTJVXt1YVYyM0A5Xua7vB2G0gUcflWaC6/kqmB2yVRStxMgm+WCi4bi c5AD0wyUUEMosoDg4hsW7aTM5rdByMuofkonGpG4CjIvhAMPr4rSwVD94BCl6FXAEIgivYdD CDKGGaDjlUCq3CEI6gluESN6UW3C3rkq5RtrVqTIi8NkxbCS53lp3VCLhZBNBnuRglGsBLMb NIjJVTbYuET7cNwsZ/nQQNcoX2ofVcOJUiGiNrWeTCaX0knbYJYSR1dL+mD3ptGAX090Y5Hl gg23Masa5BMqIVG3eSbp5upc7gSply4iykUkXNiYEjJBB15p5NBCClJizxG8ty9l5cOpkwJh nHSRoYk6nmUvylmR58NxLIo4yMW8onBdOml4xnzC8bMk8hpMf/n3ay9H+nX7QlGvO5KMQ4l6 97a3HGjX+Ye3OoMGTydXFyeZAVK9Zd5NpZ9lFTn7hJxBG2rkaSzzCHsgEOzdfaOygxlxBhDl hfDwo0bkgqs1r3q0DxuU4EkX+HSWcOblQRJFRUtZZPxYYsDx7eOIiKP04WlDeraRZoy1zFwk YE9/snneHTev+90jK1R6aAWHqpL+h6/Ph6fu4OKTgPf61+G4eR4lLyPnx/b1j5OjddcGN57Y 9Y6VaGFyroNSZ0p4/ZWA8MR3ZUr7+zwTHtl7a5yT/CBAgzNB0ydIQ3HOX+ksYZ5I10DpirN5 UegoEI3M1LqMs0/jVtkp+qaQcqPw6vjSKUfvJYLmec5YxuBFmn77eqABa3d99VxCvGnDQPTp WpWTaRzRveF5VKFnQnx0Jypv0eMsIuQSKQiP4hf7yDayMG3b7PG8/fACy8zz7mV73DEOYzJl SYARrKUqwjepvN147hexi+4pwr5Qrl6+7Xfbb5aAH7tZIoQoj4E9BL7O+XQzi/P+/d08XSjb 4ya3CBCq9+l2/0yrNWMK6Lmsm8PaDSJUP1KW8FOJuIKnScedKU4l7EaB/fwHEvqhg9o0R8UU ewMOnWWcxOgzrpyrxq3PqcPQtgvkiDlewMf8MMxXpTNf9Ms7zYQkWYAUIDp0hcJH771/j3A2 3+Ly2/Ro49/yj9Zo1F0LNV6qtgNBTPG0dRUAKVkR455RdjraNPi2HgNOPm19vMpAkOncViEd PU2ap6P10sEvlgCFeacL6IWBl6YIEw0CkIgK9FTlPvwn61zIUUfmm6f9w+h73X1mP6i3ivkW utYsU23lgwNcAA3EFwXmpsZq4zqflMKoAu2iZDkMKJeWwxpKKLSHriopzw5pjgGpNbopdcI+ SXtOkQX5fadil6UXO9l9KkYeI4x0u/N55k7aGeJvEQyViGbUUZZi0QtgEOZa6qDPMmktkxZz LXb5LB8oLg7CgU/nE/lLoLjs00dpXFCG6tykVWnlDGXJMkk5vkC1CsmaQfs5RwRLPNoQ3Xfp 7frxQ93QGw+xNVd3EwKTQPfYVtbKEJhc74okb71Vp59l7OVkvUNGtfNOAD2yta2AsNDFgRCz 0SAkZjPUPPOsvO/mUV4uOd8+hjLp1NTJWyOmijyZ62pOtrQhOCN5lkiWXhaq+5IJPuc8PP6w rSTnmuZGH+n+CSedv92lS4tPb+0JdHJzff3BWio+J2HgtZbwLwCyq124c65abqL/nqv8bzhq s4UBzSoo0vCFlbLsQvB3fSuP18ApWiFfXnzk6EGCrtRBhvz0bnvYTadXN3+O37X57AQt8jmv q4/z3hw1Ythh8/ZtB+s606yeczBKuLXfqFPaMmISMapGm1MoEduJLyOCPMls/k7QnXoQupnH zcNbL4stP2X2tXEepb2f3PpiCGuV5y3vY36xgKk3a2dQJVF129U0f3pdedpHQWzALntuWAGk HFp88AbdiyxuSzIVLzx57VTuAG0u0zxazySqL38IJHwWJW4RA3WdDVRHJjlweBRI+q5Q2heI y4FNLgpiGHVp7YkGWp/KtLt4fTlIvZap2VChKRqZC04M7vVS+qyQWBA2EQwv0WG5mji3VyX8 3V7d6fdF97c9gyjtss3GmKJXwtHPwEtuc6GHRrG9ACMct47KqsaN2TZWIFwT4Mjlxt0suIPR IiNNHBybk9ZLHpQIuj9N81plQfv7pkBI6D6J00WcpU73d7mwBd8qVX5b4nipL86YQBLRnFT8 JnGVvI5IjNS+FIQfjc+Sd2/H79N3bUq9f5Wwf1kj0aZ9vOBv5m3QR/6O2AJNhXcYHRCvzeiA fqu436i4ZIPaAfGXzh3Q71RcsG3pgPjL2g7od7rgmr/d74D4y3sLdHPxGznd/M4A3wjWIDbo 8jfqNBVsrRAEEiLKW6UgVLWzGUvvg7oobi1EjNJOENhzri5+3J1WNUHugxohM0qNON96mUVq hDyqNUKeRDVCHqqmG843Zny+NWO5ObdJMC15BUpD5vVnSEaDA9jshbczNcLxwjzgFbInCBwB C8HNfgPKEpUH5wq7z4IwPFPcQnlnIXBk5K3cakTg4KshQZlaY+JCuOGxuu9co/Iiuw1Y7xqI wCNQfQlzu9m/bH6Ofjw8/rN9eTqdbHISBoLsbh6qhe5e3bzuty/Hf8gy7dvz5vDUt+Qwvo/p wqh1t1X59Q5RI7lEwaTaMZtDXeRpjYtAD3HZEqRRKqrydz3J9KN+786bAjm751c40P2JUX9H cKJ+/OdArXk06ftWg1raYYzGFcRznuu8GO0aSPUAUHT7rXKPtak2wKjQOTo7al/+kRN0yuLT +MOk1WadZ0EK618EMm8kCNGeciljQPEScQwiIYZyjGZJKMja9JJ0FdvaTav91hnQQ22qblrR 6SrtOagzwhNehH7+mDy7ENN9SRy2tEfkQmGl4rzqnjQh/Y/udluV3q/HPMmAl1eeukXptvse oOY8dFqDJ4rsrq0daxIbBYIZvk8f/h3bHWNk7cZpw+Z5t/81cjdf356ezMyye9lb5+huSIpY RlkikBzYyYMFjUabFUHXdcoG2IO3CzKQZPYZRkI4Z4bFrIYJjo0RgWEQWOctxp0fdVHkRSEM Q3+IaorIdpC7cwtnmo62wRCXQlQzQ+yHCrHo5sIU5rUd2qnqOsMveH/Bd46B+cHC79yG9VtP TUDV3jxMVi1t6RCRPqcJgD3Um2dN4kDdtA+reF9hh4w5CneP/7y9mqXPf3h5sp/PwVGvSKuQ DcIb0iqeg49WKLkS3vis7oYDyKdoQAK8VSa85tqil0sVFt7JL6QhVkHZIfnElOh4Q3ayT1Rc zFuHUUwjNrYOo4Q0/OfFbnmuv7Eqt56X8iZ8tQWFKcS800JzkmahGL0/VHYnh/+Mnt+Om383 8I/N8fGvv/76o78dZTlsJLm3FtzYViwAlcHRHICcz2S1MiCY7ckK78EGsHQNMbByZcDp9V0D i6AMsJcGCqmfJYWSk9lTXaAYjOwA2004xzs+vp1UKHA6xV4UrwJP/VBlxnEXcguJUMxSZ9Za cT2C/1cBJPrfio53qtUqOIfQQ/sEXcYEnuAdyGCczEOfyIGyJQhjUOMUwoZH441kdveg+1Qk 11s4Czs7MJQBLKDDCCmbFgQXfBjBMGyWlcm4k0km+VVFqnfHWKB3Z9NdJZZk8gPFih+ILUFc wAtovl1YYT/JMdYKTRpv8D68HmYTPRRNRYwQxoKr+5VBTAglxs4976wR7/xa84FREyap6c+s s+3Ni9gIh8PURaZSn8fUZ4B5PRVlYrkKch/DMutuOYYcOejbj3xft10CEgSvcYhbEEks3M3E qT40ubQuWyhvx7YAzHC1MpGQWte+aMZKeOv6FscZWcOEJe71Qg9fm0UJwP7ozHurWGdYWI4A iUMn8/kQxGyrAwB/BXw1BKhGpup9ISw8fV7qWPWc7dSnSXSl4eMSRRfgcRJ3bpVNOjpow5nl Vh8IW2UDB3YYBBp5ot+6ulaVL6cgKTu8ewtFzDzDD9bFbCudk6FOVPsauurEXMGymMpLJz5q kFc9H3ad5lG5PBA0N8oZLBZ+JAUkbHH/f4E8W3/TTC8uIpTl6fKnv3+9vZA+IN8cjp0dLLx1 BaM2co+Cu26pJSfXZsh0qUFUze/lOs5OiySIFgPb2AztE2Q67aEgJpfDMNgrceMQ6Ua+ur5k BR27/b63dotIsPdHAOov4kUddlbG3QIwF8KgEID0PvxJluizII+EizaiF4VgzkjUzFfap/cp A23l3daijBO4Hnm2G1/cXNIzsd6hEp+OYUh4UTow7CQ4gzAt0GTvlvJqL9MJ6UAPcYaAnRJk rRqcN4c5AcUP2F9Ep9tGi0CO3vDlRFbIFmRaYQRNUaVgTsUL13Ljj7+ZDxovnMUMJqGZiMEX WqYtG/ta01QD46SMC+GFCiGGyoL1G7qrDDSdhFa2m1icEE5eYZhc8KlXHUcOFZ5FK/ifp7Lw vtKA8qmlO1vYBpdtoicEgKLnZTlOZPlRywnDK0HnQZku8lIEVKfWhBhAZKVKRhYiplfKRfLa WFCYyHgIGa8lYd9NCpjqvcCB1Tk+nM3DQvPH3OpBQ551Xkm1GbTZMrk4rtiPxr1FNnSQhP2f JmOZ36de+WE9/XDSfHRpwGBjnmYm9KcJTyWR56JHo8LaxsgnguDtvEEMLCANBktlz8C1RVer iqc2V0ciugFQmbKthZxUtutLYJ2JcMoHcRjEHRNHkyuIRsLDiYqPomBoqMyIkr45LSwRkl4t 4W4qXEbozePbfnv81b9FwWXUysr49sWjAJBwSxVW2epb4aKCrJ88V4YAoXR9DEFuvOwLMmxl GgzbmqfpEQctaryav2dEXKexthVN1pW1DvdhY8mzlgIcNMiuuqqW6jRIgygORkFcKtfNPl1f XV1cW7PYV5kLhyaX9l3cdo1eSxnrvN6G1IO3a94jDrUcWA3j0LbUkx0KTQOaBb+DqfSmYxHp BpouNuS8XLyRS9IBhFo6jW5TwpD+NPPuQGDKG2Vuf8h0pASFZQOBGZXcC8F6aoxKofWRoL1u UPgsIA0EMaQG3Sv28T1K24suczeJGF8qVl3fiT0URqqx9odAeFHvLTlpoV41GeZpLWIdDO8+ qQv79O6w+bl9efu3MWii1SOptdfO/tfrcTd6RO/Bu/3ox+bnK716sMAwZxZWZF0redJP95TL JvahcFJ2gtRvKzO6lP5HKMOziX1oZqlbmjQW2IpC3Km6WJPbNGWaj6/MrQcSdRma54qK7PLC SkX1HJdbBCtqpGK1YHqxSudq03VLx35Yryskg+le9ov5eDK1Ik1XBJS72USuJin9leuC28Rd 4RUe8y394QWauiV9SGe8ityHXZXJnPV+od6OPzYvx+3jw3HzbeS9POIUwkdv/7c9/hipw2H3 uCWS+3B86E0lpx0avO5FSuu1zFfwv8mHNAnvxxe2Zykbqb27YNnL1YOvQVZqoinM6OHz8+5b 239KXdbM6X3v5BlXK+H2pSmUf4xakcOM9zHbMMKMv3Kq6OvhwkHuwcdmvRHzHw4/mob3GhSx C2m9qkSKY4z1mYouO5maS9vt0+Zw7Pd95lxMuEIMwby7HCqMcGcB0Lmh5DvuhMvHH9yACxlU s2q19vZGjmHS3kR0LwfWG/eKyTYKgInREUYw2N1Z5I6FgNEthGDCekJIcVRPiAvbaVJnGvpq 3JtFkAjZMk0DwpUQU/aE4O0B69VpkY1vBnNYpZ0iDP9vX3/YTg/qHbq/wENaeTXl6o+UODjP nSouZgF3SKjpmXPJZD8Lk9U8EM7vNb+qyAtDIUBQg9H5IFci4Fqunmv76KlS570dq7cW+eqL GtyXtAq1FG3bhuAIDDah2ikGs/KEY39Dz1LJ1YoNKbX2JueqlAuO82vyKjk3uBWkW1Bj/7ff HA6w6zIrOohxeKc5uA994Q8eFXkq+GBrvuaNcE9kn/FX8fDybfc8it+ev272xnsGvZVnGoAO ZksnzVgTlLqR2Qz1uXHRm7JEEfYtQ1PDPU8g2P2HC++V+znAkJmohumcm1vyJqnPz5XfAHUl d/8WOBNsUbo4PIf8f2NXs9woDINfZV9h02yXHo2BxFvAFEOacGG6M52dXLozNJ3Jvv1axgQZ y7RHpI9/LGR9srTyv3+mnppZOp4Ec3AQbJfKQANDBNqLrOx/PgQqciNgpnJtn/Tsf/owDPmg Vv+FsB/ngfJXM+QJFlXuo4cfV/7p4QDL746ButxL4P3mS7jp5Aea7KBO/0WovoAAkqlTUaQQ 5jIxMghO+rbldbhAtRjtwr+bauHv5z9vL5ePwWYaO3nWJnL0eEAuvc1XFJ3X3/IxkOd42EsF vaZo2ztqoZ+isq3M7NoxEp3vWjq8GYuS1ZZCyG6pa+ffw8vw79vw9+NyfsPTglg0dQrl9dyO src42awnzjUGHRma/015C6qpS16d+qyWxbScnIDkaRnQ6qfUt43AS7cmFZTYAHZsZBF9fcUF xP1Z5auC4kUWM9BCGYN+U9CxssqFO+HmetxpG+iIvi9cJ977HrajFk3b01Nh7cMvjqWd+pWI tgXkgqfxKSJ2HTWhX5mBsPo5/CcFRBxY76C1gTr/Ih7nNaHdIuJWTHwN9VCeB7RRmJdjSvs1 VJvyG7pmZSKL9afW6QuExFLwIOY3aaTWr5il2oswp7VthpEUuCFfviXlxw7Ey20gJDyZKUJU +VjB7reekNUFJWv2bRF7Csji848b818O6zVKQ3Tc7d76XSfQeEKKWCs2pCbvCkYqjl0ALwPy rT+SiZi/k2WBxrlSkgttwIylqxnuZK1Hv7YUabEUATnYOxbE8Mf4fkzUfA4mI0XV6nkl3jd5 woYzlw5BDttrX2+Z25X/84iSdRIYDkkSTP+C+TyVcy+hZ2u6E9pKoyfTcrWxOSIo9UzCVMGn TkFOFjgBfHSNFkeIrq4JVZBxmguSpoIqXRKX7piMtoI3wERJqIDm7Q1TjEiPMQ1FC/4DtKPD bTGpAQA= --n8g4imXOkfNTN/H1--