Creaform Connect Korea ~02.25
반도체 AI 인더스트리 4.0 SDV 스마트 IoT 컴퓨터 통신 특수 가스 소재 및 장비 e4ds plus

Now, even PMIC testing is aided by AI.

기사입력2025.08.25 18:06

NI Introduces Nigel™ AI Advisor for PXI-Based Automated Test
Improving test efficiency and accuracy through combination

In high-performance SoC power design environments where power integrity is paramount, testing Power Management ICs (PMICs) has long been a complex task requiring both time and precision. However, National Instruments (NI) recently announced Nigel™ AI Advisor, significantly changing this traditional process. This AI-based advisory system, optimized for LabVIEW and TestStandard, ushered in an era where AI directly assists in automating and optimizing PMIC test workflows.

Nigel™ goes beyond simple code assistance to provide real-time support for repetitive tasks that occur in real-world testing environments, including test sequence generation, debugging, hardware setup guidance, and example search. In particular, it automatically suggests tasks that people have been manually repeating, such as load testing or load current settings according to voltage conditions, and if an error occurs in the execution result, it analyzes the code to explain the problem or provide a correction guide.

"While testing the PMIC, I asked Nigel™ how to set the load current values, and he suggested some recommended values. I was able to repeat the tests and analyze them accordingly."
— Oh Yeon-ju, Director, NI


PMIC testing requires dozens of repeated measurements under various voltage and current conditions, making it easy for setup errors or missing conditions to occur. However, Nigel™'s automated features free engineers from the need to manually analyze datasheets and reduce mistakes caused by inexperience.

“I spent a while trying to find the parallel measurement settings menu, but when I asked Nigel™, he explained the exact location and even showed me the changed settings in a pop-up screen. “This feature impressed me the most.”
— Oh Yeon-ju, Director, NI


Nigel™ can be combined with NI's PXI-based test equipment to simultaneously perform high-speed measurements and voltage control, ensuring both test speed and quality. Additionally, LabVIEW and TestStand users can easily integrate with existing test code, and it has an excellent protection system in terms of security, including TLS-based communication security, MTLS authentication, and local data protection.

4U+6th9+2yYPdGZw12L++c84KgOJPXg2qoFtXyDMw7OGddFQwmBP/7FYyBUYYsoZtgqUbP2ETijq0nHhr3LKRotbQsZyIeqEyvqbU33UC35ddo+//dj88TeZfmpUE WVb/uCCrF9QXqflMAX99reDD9i//WB4OOt0A351++23LxL/8f/+jOHSt6f/mlX4r+/Qd7798U8/fove43TPbGEiwJDM7Grffvtt88uf/5+5/C6UIdr4j3vz738yCM C3jzoGB//0/5ZApfll+X9+1iAp0Fn4H2A6CMMDZfLT76NNKxzIEGMj4vSnHxqKLn+ZnRCSPz3SDbq/PppmRun+76//y9MNZIgyOOmyrVncEkXV2MZg0RivG37b9tp crx/+JBO/nv3hh6b56b8L77UZcwRDQHs6RJtbyA1xcfABm0Fi7ys8F++jvZOp625wBESI/PZ3/x6bKLNEHlj//id4tL/MfosJ+p9+4IBT0loowz1NzM6tAP1v/+ZE bFLm2x9+SK2Y8KgBOplOA74WKUNuf30nRwSJeCHkMQ5sul999ZU6msMSQebtFSz/FLiY+YKlzYOQAU2vmIBy+7xlm2D4yv3www+ENOI1DSqT/EGDfBTAnsrg0GVbs 3g QQX//779BlLYrTcyQZIZyi0re/Oz+1iKyLfyz+m+Y8iNbmIBvaaM0scr4QVpRdmmRa3sEsEa7ZLDEU+On3rgEykdoxGY9IjJ2pnCIsPwqWFg9qJl7b2EH0Kld8eMo ffqT7svr/vj75N7swr1iVrOPJYlADjl10BdWzMLYl568rKElHcjiCgJ1DWjSX4bngmWXjoe1QGo5bXv8z4bFBWLcgAmIi+e2P/xO9ES1Cs15n092a2KmFqzLoKeaglHWv/ F8piOuILeL1vyfW5okCPH74Q1xfZDubsCK6rQwnAPeFYOxQGJdE8ps/NhiecK1gcOL2m+HaDOo1TuUw4quv4JYybAA6LW7w2gYvbfT0WBkxo8w+mf0PQvYvf/yvzG IqMGqB/On3VhujTds8LMz+vqAxf/ufP/79p+YPs4QxAi9hjzzc/S1HbG3LyMxvyeJWjX754x9poEosPUFyku70CVQaIEjb/9uPMnwi1YSigRXasfnP/4VSJGbdHwD 8FuylqQpH063frqvBtssfQcCGx0fghdHAjdIGW4KFsad00YalEYX+gRQkNN7SSXQi7QNZdcshAEipcybDdY5HQb5qXpLVYC5iPffF027p5dh9WfHc487D9KbDON3m gPCL8R1mzXayuIKDhAWJpQRjjNjASP+JtR9eTLCdG5dT1UNZc0sYIjOEHtYWNHoIQCN99Zs//+5vakCKKoiFjYQAFDugTdz+zIRstp32YUizidUsVj6pylmhtWsgK xpBnFAr4VoewngKqRyvsej0nxhZNL/88X/p5neY3klNFheZ6DBCb1ZblHcitozX51a/auwl6a9nH2iIK6DQPP/JTC2Nf/nl3/gRTbMDCKnm3nO7bPlO5wByrXP//U 80twKeJpvkOVqhLc78eWzblU1SxrCZRxCwARiaNeS4RLLRwGg/iy5yYZQA87pFEUAg4Aj6w5+SfRNksrOIw1rjJAzGPGFf8xybHu1iD/WD43eC+ne7ExZkEUgUJkc T8cJMWSBsif0MUbA0yv7jX/8T/G3UWiLuFHZmQPc9SYqr+dsPFFmSIVuM5PQMTsQ0wVFk6RjDVt/8/cV81FEQdt7LNSPFWvSNJjQYCLJOFxdqB2vEk1f1PCTHa3cc3DRySdq+n+PwbCRMBhg+I0d1NjmYJI1h6Q4XBVC+1ItwRgFhqSLbNFNmYiYYZYxTs7hgEhJiFNjt6XEEbIGxGxcQHUIziAAZKMXmjO8E37oPIMAost9CBDWCQ4BUL Yir7hI7prhAiCwWpOKIDSdXFK+lhwF5SNm9S+OWEOar9o7Zf/3111SrAKEq0OHePHHaz58O2f+7DFbAnk+GSForZGPMR4sQEzuNQ6WdxFeF1pkunqwR9xkxMmAuco 7P0tXutx8wQcWFHE44doWMrWxsuJ5rDqcqhThXm3f0ZEc1Ulr6x2MJ2LQUKVZMuCvxDrZGS41um/DIjAmsHY2/ffxqShiBf/zrOa3dkQcLRlC/FLVQ2bM6ftl8Cnu fnx7/d/lLk59fq4j9eytOoYu7pmLIJUtS3d7zHQbddk8J1EKzx3Jr+D8gj8jwZcj+6Sf6ZzuvpdR8Uv7bkFz6FWT8eHJ7N5We0UoYiyjj770UKYO6keGMuEUiz8hZ LHLFUzXC/JnWpShiR+M1hMkJKqsk6i+hkCgBCf6vtVC4R/Gdba6XRzCALsZUXuBd6LxQdEvbkQRsnlk1eulHgCvuWw2zcCU41r1C4Ouv6f+y1D1RlbrDo4jYP/1UE K8pdIn+i5uFv1FR+CteLgjUQLos0cF5H59ZIehrfokT4es7EQcUa5pq9kFYEokiZEcI5EBOTid/8+eGlmsFLZsXTvW4LWYtoCnfRPt5Jiv0kA9lJLjliwtOysytGo GvqNRP//3ff29c34lcbBgPClNtxAI6P/gh3apE6SvRbxzXi7LhzbV5cQdA81J9Rko1eXg0g7SAKWEU50cSsJXpLcybSnL8mX4CaRStVJVYHwFhAp7zizCmKCyDtqL ANGft8bY7ruf47u+EnE7ESkvrKOrszMWE2Y9txmPpvcuLVMhGi4ipJBT89sf/+YN8KhpX9NSgaS+YqolGpLy+P3n/2V8SEnHWepArIKOkuFmjH/70F7NG4Pg1z7F/+UUsSyHB39QIBZEVdRZDVZMplejQc1DU7w5+SgBbSLfpdEuRCgfzO5KATf3pn3/6wR6FwcZgSiOaBR6MVfWviOr/aigtj4ERtZRBkRUdNdCDaaKMHOFDQC0oFaG4U pnCT6grENMmSMBCbKokZe3Lj6og/2NMIslPwcLsnbruS4UG1lO0u9OyIlE9GCiuNIm4hEX8ZdaI13boAT+BjQzeNLyCXhfvpL8oG3JQRo441fIMASInU1z2ElIaSo oiOJFsdJXaJPnECSfobCquAOOighEn/9PQQBQIKcul1tnZvh3WXmfY68A5hrKWEQlbYrMr041Lb8TUyuQfElUIS9GXRbN4+w7tNBKcuIpQm487NZsAsNCrHKbd16B c1w1TYglYP5/wj8V/8dtCe//734Z1PSL2bKGez+CE4p4nekkx+c7QPZYZ9s4AroIrAhWBw0FAT+SwPodaYWGc/vcYZ3WrCGwBgRqwtwByFVERqAgcAAKYhpl3Ruud hQNo0+1UYTApNWAPBmVlVBGoCBw6Aubya6c7C4cOTK3fVhAIB2zcsq/bkSAAMzuSmtZqjhCBan4jbJSq0hgQQNfwt3DAXq33V0vvEQKwiT3Stqp6YAhU8zuwBq3VG QoBdA1/Cwdsn66mVAQqAhWBikBFoCKwQwSOMGDvEO0quiJQEagIVAQqAj0RGDBgv3z8bvL2sWnUsadGGyr2+Hby3ceXEuYd9Qd5IeMS4SEapbo6hmi8tE7EXum+CQ Cjuw10UVUJKFOwC+cyjmEqaFVsA9CJekmY0VhSOyoJ8uL6j6WK49djW6huyXohhn3DJoFXMtSxQBZQHn9/bOvRL2CjkhPjr1NnRdk0QCAweFun6YKqVmCQ16iIyOB o6YGLvAQyGhDqLV+CxNGvk25N05GcJOzkBz0lGGkoXOC4UK7pwTzNVVYZdMwvsEuLCBSMCgStlUc1SnOX2gUO4JUuSswDtUGSpYPLOlwsWYRYQJ0sDdHVXwECABPN5GwpeFEglE1tmTYSFHTExOcvoLWE5Lm3VUVZV84kLgnliLlfglIsHUBpbYFiSXoxjyS29MuQWpJGdtEvYKMS0/lS31z/fHWClLLt5dfn5vnXzFTXZK6l4OT2vEzI0 FTntxBubA+zjASyp9NPly1Eq9Xy8tNp0nQzLMeWTVUk41e/tMOgUcVF8yAwfDi7Ps30mZkkFQWwH7Dp+1lXZxsYpsEe7xfN4h4LVyl2kRol++XJ1WfAShusWcOdLJ JS4YDy /ZyJ2T+4jKfby8c11M1/aFgQTW86b6zdl6/IdakJDIEUOw5Q+4mKh0oY82rysnpaMqC8f3y9mD4rk/JaQ+JCJQrassV0B9enl9+UD1V76I3RcLGaz2eIiMxzqxV0W Qk3yQ2hJ2xCxOt+usSmp2znKICDix0NzkZ4mWjrpmGUEk9XKdgZWAcz+MIt5+rJ0Ujd4iWbcvPVuUP9urIX3aVvg5OoOnng//c92AzZFsrOHFWZY6bj1dH0q4451K PdaW7V+z3qWX56C3eHk+8tpgWaP98/T5tqyJwYkHIMxBGo0uXYWK4xwPb12lgAdn2avjeURQiI7b+yqbgG0zJLBtAyLL8qtC1yoRmffJOK1JeT0+gll9LaA/89GAA qHCKdGbwAAEABJREFUPCu4vb1dLV+9h46dNNTSMiePH6Dck21uVCSoJKo9emMj5Yf9oVct4eFPN4I/VOUmUOso1O5oa2zh/m4ZFqhoc+wLLNMbmvFps9ablj9cLlx tEbPpq1OT7uSbs/JBqllw5+f/0lcDbTflVvz4lhwQplmYYWF9OFHQmrqJUS7tUbRAXYwem4Fbo+1E1D0mk3BX0rqdvpoGFxGonziWo8vok8e3F83N57v583tjLs6AhGIwhkCfLu8+f8YkIIGnZr67E6fe1GNSyohwIdAuWb3iRs/eahESGUyyJ/tXZl2CBVxsM39njEBEsrG3hCyxcGfkielbO+I3sviJBK72/Wuop2iwPIOr1/ecI1Zez UK6M4p8vc+aBE3hn3Fz68GfxAeU3BtjM7EZ5vzk6mamQuowHDUXdPgFrGU5f74gS8foAE1NW6i/Nw1IKdP6OfalWUdONmi9SiL1x6APVATGsbf1iqUJ9vUwZLL6Uw w+Dc7tqTOYJ/XaEYtwNgR+W2CsZ70DtrYb+DkRz6Jgoe6MJ1yQ6YDI/WwAJLLG2axZb9VdNKHpGXV9ZU9RNUHlvE0suTi3aQHBKRbK75L3+4Ek7vQCUrDAmCYDD6h Pv9ywJhgDYRKWddCeqsMkoG7UXSaTlA10EiXChcCaKoiqsoSIgEEavVhBXmK7STZkMS+PUDlsGIGbF84SwVxABR9vIhfgYfAEpqfXZw8EL8wH8SL5iAVRj8LYjBps 8/T89YxDw6AyAerkAiMmtAGaESuPp6bPGVSUZrZR65VSqD9OA7MW36+i2sJ0se9kvSSJZkBNQ8FYsgmPXGi0teDREBVCmOdblu14W3QZtIHIHvW+d8A2ayUcSRgse tpoMnnT3K1WjvugUnfNG/hhL87Exlx5axbWeHt7c+Yv8pkqZ85FE7oaZwoZ2WQ/9GgDKqc2Wl3I3Mn6+B2itRIKFsTBw0ZJQV83qJuG6BGzMzFelR72CNnob9giNg Bp1KtwUBsNcdV5yZGMBfxXQQEdG72/dbGmWChCmHOMmXPMnSWEhxlm7jDnMAFlXfKIpR/pE2UCHYImhDEWRQplbWQ+dKsqsuwLSaMxtmGwGwMXmlvD0+hIASNX8+y 4epZhUfPi18G+tmG91B+nl3eBG8WoLfVi7jywKahubuXWK+CheD17wOqQuRgpspw9IYsJkBRGrliD7lCO/XKQgJ2sJLCKP3IhPD23n2bCBahZAz+bUhdRJ1izk770/Hbni8SibnQzWZhp1kSogFVBmQBAuKw6itriSntbkcJOlylxjWx1iqsdb94ta+5q5k3tNRTs1ujAJWBXIskCP6wRvAzFuQxlSEimiBQH/tKrJA8iBofEiJpY+6Bks i3XQIifIMaZOJFq4XpvjE2qPPSh6xCzQH4G1QAHKqHatvN8lG+3bNR6WWPqj8387upETGyFqXKOvTProuoUOFp2aHIQct6dn7+bO0/8mFT6nAxesXcNXxON/6R3wL YHetFW2SYC9uCRQ3ZySm5XQTjIUVQEoGECJBRq9wnVfDefIAb3rW9236WGytwC9ueJkfVa4nVmPH+OcVqy0deoOrUJzTM32d19L+b4ZeFzXC/mG0DZSktbrrUzeRa 1IL9MlHQNsEdXdNk+SUrPqISe6Xae0+hUhQCqzW16Ra4Tf36f1aatFxqJ/ii7iLjTkjVFv+7ZIqgO/ScOhgW0tnjjP4IBVeyNeu8BGGq/gO25FdeB2Fht4wrtQeZo KgIt4b4jbY9M4fvsvVneUjsU3SOsrXI9LlCVCe5N24qtUJVgzCJrp5pb5ES8qbjV1sjGJI0G8GalKBzQKF926ZZZe2aOhY1aBUoAKaq62WhCTlqXVlT5GWDmNjFlp UujxPBqBEQChAmhYECF05svJf/1D7RA628YJQQk8RTNl8XtegC+MFhjmcir1+qxBXpi0n3AkSbg7WNMslThAZayYVQhYRvWC1Okvm30EfRl3JlP/E8Qivh1X+Wsl2 bX4ukLhlgMDA7cBLmmTb+ALcqW7GEp5KJzP4F1J2JHOizDXbQDBRxSwM8jo9sGNr5TCy70+1XoemOm4eViPWfUimLFYBZ47vLxnh4xNboIFyALng7+f1PMWu0IcAu ULNAtillSJSRzJB3cqjcN5IQE+E0TtEphip5gMA3Yl0eWTwAjX+V8sShFylxC08Aoo4KMnRlbgW6bI+GY8jxfts12/nqGwaphKTSvzKwZxfUrQtW33i6OBUa3Deul/uh1Pcj20jQYPa2XBLXNAW5eAtLKNqhncSortTOqTQdswGF59ciFgKwT8c4gSwoeoAp8w9d/UwaN8QP/3e35DlaPHIj9n8+cfNS7AZpmjPiFzQVB5mKxzhJtsKrHY 2zmLRmem9oxB7ZEj4fpER+tcNgUQfzCiUWoQmLEd1rJwpGG5YwxdZvWO8b6d9Zp0wG7s0K1AD87Jt6UoR0CTt6/WgZvaVFP5kVJ0OiNHMgwQ+raHmsggGmYbhLzxJ ibrcFdFqXJhWcu9CBs0FxkoZ6HozA2AjQfBQ0qEIcCJVGE0j3sR4rqwVlvYw7DzP64lVtXXrP3ShgwYCv7VMde+mysEDpF4RC4o/4gL2TcpW7gCjdgbikhqJxJivM iR9FFoTJaUptEq2NRKWifqpzFoxPj2OK4xXGIC2jl1wDVQkMEN4KoVC7Y5MmhgCPI16dUINGlhCLPkZXXj3jWXwqBHaIK4/GtxddHN3rP5oaYyByCcjR3PvH1SWHX 5hEnUk8d2xyeBjHvwK6vOIP9tk4HDNjbUrnKqQhUBCoCFYEyBCrVISFQA/YhtWatS0WgIlARqAgcLAI1YB9s09aKVQQqAhWBcSNQteuGQDhgmzfk6/lhIwB7OewK1 tqNGYFqfmNunarbDhFA1/C3cMAO3JevSQeKAGziQGtWq7UHCFTz24NGOloVd1pxdA1/Cwdsn66mVAQqAhWBikBFoCKwQwRqwN4h+FV0RaAiUBGoCFQEShEwA3Zpme HoHt9u/IXXLx+/YxnqOJzyA3CCUh3+Zx9odaAeQL3KYhgE1mm4TmU7EQ9Tt8plMwjANbDf2gx3kyuMZtAX+Zi81zmHXtXdeQBuPmC7uGctMULg8vGq0oDCfESgU2u jbNpqQWAyN8/TBZWeYJDVCDQmY3GeLaUkHOURkKXxJ3MSQLr7HLBg7RYxry2xASk59nZzmcIszjaZ+P6GqUbwizBuoXo9SgTMRtdtmrKbgJnJcqlSbDQWAfFJWlmEAApbfIKogkgq5R0iMlEizzYo6+gSNx+wh4K0iM90vtTPCXR5fQ19a8f9/o4n0GSupeCEXq3jEfdK0K8Xepg1WlqXevSSus+FHu8XTfYjJxpKNJax5YDVrUFllvNp2 ySUYL+1iV6txKliR9Qdvt0Eh8Uvk+XC/JLqiGdDU1larWAoSEN59o0XC1zUbW8Q0G2JZtRGmjFLTcfGoneZUtuERNdKKydOUMltqnGYskYasAMvfd2kM6JvxjSBT2 EN2OYUWaQEGr2yf52cXj8FRdD44WnoTy0FJe11IoC8WMxmBR/DXbuawkJKmwTUHb7d9PLx/WLWfp4Nsf9htnj/8aVcaeUiq0ssx6xS5hDYmhMmd6eUUWPPyWSTDl9 J27/jVgK29RZ5J0gJq3AXRGYPYlBm7DfnjMTHVVfp77aiaa1qiIhLe54MITu18ae2ZrPm+g38MDyyrNcS07ZAsccPFMjlxLFacAAhXuSb8Bcubm9vV+LbFyUNEeSV T0SLNPOH+bP/EbVAWbanm6uTQFYwafnlyfmu1umraZCSElt7IOOrXo0wqb88Apb32oUTNsOypS4Nb6fN9YdHSlVjz5VcPKK0+msR+Jf2dHNn1iqOE6REaHYXdEQYJ 4+kf0WuSVtlufN+fEt+H8va57fLy0+niYJWNWTIxQFFk9CRh714ni8/395+xqDgNHfTkYP7fEkrozSOqRZsoUtokk3cvwb0ymzEEOj1PWVM/Gd1tFWIfL1PtLUpEy Lfv1p+vjq/+kyfRcuU4nBN82UUk5Iypovw7CynIISbCrjntiECBCUqI8jlU69HggDFMrn8ltWorzFbRrNRJ5ytgkWA/vLp8u4zda1Mz7KKHevFVgJ2N3CF94U7xoZ ptYjoOF8VfC5QWyWiqPBizljSUgVLqpMJPD9cHqeTZPL6FCc5Yf0dlKBgrVSn6EtBOyYB5BOih0ZQhij98NNDqQMqQgiSMaCB3VqFs4Aj0fPPNif7LrTLja9dC4EIns0n2k8O/xr6VBgLzc4VTq5uzFV9yMRCf4cZeisK9WO1626vEKD1m+nUj9hy2mLEsbWMuQsmcUFwTV0YWbTOQlJDzwmffrlhlpgvvXpfvZ2FV+BiKwHbGhQmIiiFK zkpkQdMGaTVygQ6GAYcqJFOgnOFw3TGkiqXRb1p7lau16ZSd80byPHEWNUAgd48SiVFuFK2x2ASuoWZSXNrjE90EnRR8+y2eD0rRYDbWDcSnXQxJy5tWAiuuZ3RZq tVyEJAMKFHx3TzlerJVkJzd1JxMjm9PntwrdJm5RkiK2bT1Kt9QYAeYZhe3t3N1aqwVhy+AB5M2AJZl7APte9izGBpGc2GnLCvpFIWR8iUOkhzBTX1Fz30Rs+i0XB sMIw61K3ZfMBG1CGrs366jewWCJFa5cRFpLTNK3PFomKuFZYDSbYYLoDU0GZThiRj1gSTDW2meZIMhxepElMzJGgf0zrojD4eAtFNEx6B4Aw1l5PmIK604dIx6KlZ jLEeNy+Waowkxab0yOKkZqZGSLeVQIIkaw+qAPJs4lLplW5XCGBF+LqZ312dOOssrj5o2ra942fKEpziodIdSAPygqU9MTRdksMOg4csS9TyVKlL/UpZMLLVqcqux y0E7K4gs/NzPbC8Fo44wVEO4UrJE5yGzSJDNCxWnZI9RwT5oeltc6tW1iNlDj8ZnVhhJ49YBY56BI2HD6Y5TtJkvU+4eR3f05UZdAyZN5I9XVNdxCPuqkel3yICj2 9pPUXGJSwKz58vsg0Ii5D+TR2yRTrXKGVhISvtLMAt4FdqI2Jcsft3vfkZNmOC9ii1KnZ+0hubh0RwYxG8sGgWWIm1JJm520OkA2CVKKQX0OLFVas2vGZarTiEVzK NoKeVNwvM1c2X7MN/kmumUxEDU8TRxEeOxEnlPUngtQL5OjaLPd4v5jOly4wNP6eyn/1MqnreRKBl58/PRn/5Kxoz28fZs6j2SqLj36jd7xlyFzkDusCgWaWmcbBf1yj/jeqAc+hnVJU9Owia Ss9jTkNHCS6viZdYODc6u66ALrbgN1F0yFpYaMULHM/YcediIfQ8vz1DEv7YrTQ8qPVs6fZ6/M2pZ4VIHDy/eV04f37NGYqFwvvmVWD3SgAA3MAABAASURBVNYbnW SHhnRY8qes2K+mHxMCPY153BBVd9elfbYXsBGDgpNZNzB10X6vaEPzJyASWEOlaMFLQsjWGy/riiHEXlV718rSPIYePtVA0gn979VmHgiImXmgmT1kQhaCib1HVxO OFYF1jTlmnTt1wtXddTDnLQVsapPIfLY0BpGtltIaAKhi6mhkbfGUpEfq7y2KCbV8xHpUXrA66D1wygPjwx9BfU2ooEyklfOjg3jZcl3Bo5x4zbqWFK80vREgkw0b Nu Po7DgRg9cdR0VrLMSJQzS/SKjX52BFA1/C3cMBun0aoZ4eOAGzi0KtY6zdeBKr5jbdtqmY7RQBdw9/CAdunqykVgYpARaAiUBEgBOpvRwjUgL0j4KvYikBFoCJQEa gIdEFgAwH78e2k5C0RrOXLx+86fAIVnHv/hz/KFmvFqvXdbU1QUsFuwCZZHVsmoNuOpQwDbBd7Q9W21N2GqVsHLgoGHIt9BGj3qaUDaKBB+9dga9XvLQjV62Cv/Hl thiOA1DBJSiF1HIZrFy49AzaawHskIAKVVzcvwdKXch3WxR0wULZDe4fqJDVxNAjIcSisKjVEHyCAwAhmqjgoAuVULvOVGraHVAFdcqsnqEWrnn3mKxsnzmCFKnXHGdLybMG5ZAMvvzpmQVLPrr66yukA1opUHyNlSIilhpdgqhQyIau0RTyaixaPnLJUew2ZOEkVaRkLWnPvlwswlwUijWMASGV9jg0UiJVNZBl8nVMSI3XSh4BYp1ToE uLjBZGp2euTWEUc7j1UbMVlZYS4Cw2TRQPFkvRNqCcJOZPy+auDTOiyZ8AGq+l8ad+SL3zfDoqmNno3jsF3OZ+mXvnscbK0QmGPIJlglTa0cN664+uY5No78/F+0e Q+9+G9f9rRtbfw4Qr6bzES0AZfkx0hDtIOp+IAnEoaq4kYWEHX8UoWlCmolW/KnbpbgYTBSeBL6SNXZEMPs0Xmc5R+/ZL6RKxvFf8Omtf/SK/8e+2SWgybaVlOZ5e odEmbt8YN/VTLK7RQp4lWORURrfk1zQT0w9n1aSaQogI92kgpRcrI4pnqqBKklvkDImffnEALva110j9gryW2tPDLz5+ay++Hq26p3OHpAu+JTr8mmvzSYjaDS4oP bKGmwzdJC/KD3xw8aJAbx/nl12cFCNwA0eJ3ev2kEouPhY1VzG9HhPvQ3UjH+d0V+wT+5tqnn192BNe6Yndjqz20LjZv6lCpj+CVyF5+eUoMGl8+vl+0X9+jTxg21 x8eS/geBs2oA/bLxzf bqcB/GZbbL6613t16VhT83Ziynr6brBoheWgxSaPu22kPtLuaNDoXBrlwUpILUzTt+IhZT+Wl8jobhmv3JQv6A2f3GIjasrTNmGN5E3XVnZm6Bf3EThr5mftZQkmY wKoHOmSKwY//xsNUIpFdzyM+3P1cHtIiwRLEXlVD2GQlDqsaiCO99SsXj/jWEqyUYXmu5a95wmT2NBQHXhBquVi6yATPYWNLj24vF7Obz54cms6wa0SDeWKvX95HGiowIB25Vy9bIOlUCnUdqg3twGB1vt7vFVEmlYw5nzr9OvjlruHZ+Z2IunbqqQyzaUOwj7FnGFnbr2moPFbubNykJD7qcP3OHaofA0RFzQC3E61l6jmY2PxiQBeCwm Q3W1jTPv76gd3xHhpDqQGENmEM4q1fqdgK25a+X82mjEug8qDf6Dk0xOzt0yyN2hzeoSzBR1YDjDkUeZZ8B6+SQKwntgwrKUoTi4Vdbs3Cz2FuRLenf5kZ3UstRH3 w8JgFnS96IboQSmlhWu/x02j1mxhurCWfpNoQNwEpMCyI9hoPV5MwLBiph8O42nM5rcOLaAdAYC84H5nK7PVfN45YxG0gSq4NLGpPVKX07ttrTJSqQAqYZyFIdCg4 NKNKt5e4dCtgh5j/P353jTG8SpJ14NZrPNw0t4aBSZArRDqTVdU+oYABCl6z4ejsBu1gdJqTGP/1y0/3JDQKHYDV/abBYXruzbFtHQJz0XRSnqqB4buvJPlTfVXfY 2vpv7Ez2Oh+HDv3QWAiN6BnGg6wBfsQoA7eA+2AtUCinpgWgwpVNjrQ1N98MMIjwMelpBgMo16u7rSm3X3FMqMiBqsKYwDgzLpWz5hEzBiPkQEyEn9+KbOTZpoSVk WEGfrbxrWmrITGd Abats8CAooAt1HJPW18RRPwZn3gj3U5c6e2RU1PHVUwTVY160mmiBgpiJ7IFe8DZrradQNOlLIAYfwytiHrWEniSRQ1De5d3SyBW7iatjutgkNfZ64a01rlDID9xj zAzlJu8YBYgLjAjKaSIMmmrKT5fBijcOMxHayVaPiEF7kEkGXcUOcLX0R2feaSsIUT6/PHnL18m5Zc1B9bc3Jjeo2DYHVvY2IBd2SbTDdP383l8+5UGrgR7WPiDCTHYACjEqS+gfsLoMIa4iDAUhUM4aXGw0NyCZh7N42t9k4bhXDNMbSUptqVP5mMhLWLy2e5bYNj5UX3AxaqebGpb6JEBrKWJUWgJl8mfl+73LD6BY6hRlGBiaEItnqM 4lWKTCUoERrLMIiLYloA19ogSyUayxDFm1szACJov1tr7u1Mrd2BpfdXL8RUx6e2SW89WBKobXZKw3BELzYNNrdZm3V8g6lLjGoZN68gY9v4eS30+ihDN0AzXp3sD +5ujH+cebx7ek1BVVkDLyJcH1H031bZEqOBTV30sLenWJq5/UM2H57svm57olkcQzmXGMXIiRi+VMNaJRYrR6ai/y/oJvSKM5Z//mathopu/BgOUVum6j/5FGyVRV xwfoViouSkY2wsQueck9YxfWJMhtzRmCG46oLs+nQQSI2zDd9Xc6DXFNT6f8glQ21Wt18Oc2adUTVUC8yO4CWESI0qgTcwibUAU2D3YZPUUO+R4pOhxXUZaZuUKZL Vw uv4T5c0+Dp7oK6dBhoCyGao+TM/zcfsAtQs8hd1HRH+qaUGaFW20WJdGCt+urGMSS+qgkJ+xTHC9/2nANYnbtsDUKkppiAuED4ICXXDgSTy4p3/GDab9ZflINr2Yz JId+snumcp+GzR57LOuryrOuYHixOPn7dGyGfCGBxizgnsBHHPSg5frINL7CWcDckbQVG0m8p/9QqwpbbMNqNTjspkDWCdNiKzsdy5l+Bo1IR798nV3TxRd5dJwfU oA/b569mTWvVq60DrX4n/0GsJ6f1+4k44PxDK/8ecnG627S+sILK3WtAQV3JqjmpN9uvwZLm4pRfBqtnGzT3WIbrrBGwn4qhIlQFuXd2AKmoeMR6aDbTmirXc6eLC9eEYEVwsClYPTKUGPl+3uw2szo7YwWDMjhk7Fx22E3G2QuA2hK2m5HD0ooeDCl1iilc0jw3p1LVwGibY/zsdZTBoBlCNNaKZLhp0bcmx3v3meti6jzJg8xoyLRVag 1Yyt4xdw/tREevfmMVjByJqZ9ce1263GAM1PyT1rJ9r3jEGsXQa+vHCi8WV16UGMsWY5FGma5wtOHDRD2fcOx8umHJTvXoPZYyN16IzZr1ppMm19elum9brwPkPbK thtLbqEsmQ9HK1MvIj8UXx3j2oH95AwEarFTsgqmWkPmBjDoSK/l2J2KFQgKPMKVYsbP0lqdDblYIkaBXeArryo40mD1I+SCf1oXyHe4pcljq8Q2ecgxAATQ3+8kv 5m3EhPY86mDstpWUFlcknQmwxC5Ie0RFsbMWKmeZV3AYF9GeNcYzU0NcCtFzGz9l8CmTbeBtXxRWgyUimBtTkYB1gKXMy5TUSUDjARGfrE9BBnrkVFdPlzRNSsUtp yC6tjimm/FwppI5OSUo2a14UtBwemcsNBOyMxJpdEdgbBM5vN+MA9gaAqmhFoCIwIgRqwB5RY1RVKgIVgYpARaAiEEOgBuwYMjW9InCkCNRqVwQqAuNEIByw1fMC9 XJ4CMAUD7+STYZJRACA31Hbpuq1ywtqnfwthildtg+f16parge0ccvq3canQHF ZG3D9QNYVGYEQQNFWT3DA9ULQSKWGILARQAHUCOCO0SGBUCO0SGBUWDGL9FVWQQAOEFQK 1NRWCTCIwuYD++5beb0P/7Z991oYjUcZNArckb1cpWByJUTdQRSXXLIwB0O7yYOc8vRbFNWSk9knlFSiojU8ckx5o5IgTQYsX2DlMo8Txu7VCMREBS8iWRXEwRqSM nZndSQoYuxBNppFum5GFm7zZgo83Ejf2MSaGFBF2779RiWk5bXp/5ogPSJHVGaEiMz94yJJKVIbHoD+oihJdEmg42LoQUpbY/Oz+LjM9AsYo1K/SLZWWlSQKwSKvZXsvjovawlalpQEIOLKVH10JAMTR9QMouwmerzuxbeHipvBeymhyb/EVHHPvyy 2WR8ndiBDDGI3W57FW4RB9Q3ORBHJ1BHJ1BHN62IZ8XLUNF1Q30jiahuyracuupwye aFeuS4v6onocrDJ0WYRsNvQKRsQeWQJeVxgYvb8wGue1SpqAnn2eYrH+0UT/+6BLB95z3zG2Gw86LtNw71EVSpWD0MhQIbIK4cWQ0qNhki3c2zMTqHFlvywHhdwuL 9YON+MNaCATkwzmVgfYUkGCQvag73YXcB++fmT/pLp+S19VYubCM24z2Dbn6LKG9jyy9M+V3cA3akXG11VfKPPSugt5PHDhj6WW6YRvM7FYjYzPt9bVq4PFfWmy+9 P0kWrsaXx2Vgutc50+vTp55feIuit9tkG7sOddJu/O+eiG/bD1hiEByDWAPpWKEGAtKPR5 EcvtGI4Z2HT6fP9oak90NK400w74HC3fPP9qe7LQXBHhj0d0YicAomBP1+FRHoG7ro976vnhS9KMv+txe3u7El+eGWYQErSEl49vrs9urpZvCQz6BQEhPI7c2ILob TyRYuLl3c1sjYgNFk+Gu/RVtr4kInqHJiKPMvEn+CIfPtVgjN64DT+MzswmCs0y3QLqCT3rnhHYWcCmEeNLYmR0AAAQAElEQVSrU9ZB7vK+EWUadu5ob3JLjl1KPt 5BUlMJ98dW4xXYTIKI5WYMf/n4/nl+9/mmsT66SHQ0rtyMFqPjevLNmaUTN7KV0l4QNDwS4h1/KZDPgqM8xKfZzZU96YSDKDcBMBDmBgUoAIuSaZNRdNYH48R84fW 9YOB5KMvXChree4TQI7RxuKYPbbczmAAg1dhC2G0jjRZ6MHCkj0/2nWMTCzUNDqsswiz3hhXdHzGpRLcxPU+bi+7mDI835odZqHDGPJYlZZfz5wsy9pitcx+UN5VU3+Jlcma21d04hO0sYPeoPo0ym4bsSXhA1y5jLCU12Yf7Czi2GJeydD8i2FPqlgvMD2Z7h4iChajmwr7X2pId/hkG9dSmZkWNIb+Z3OUc8Wkxe31uFImbQdiVwVdM9 TpmMhYaQhSdff+dCcJZplawRuFbhZkGeDAjayfMaJmhFVTV2CzotnRBdoR43TQUsa8/WKtpZSqwLbtjz7Kim6Dq6YdhgwjNp19uyLpVl5Pm/wAHiEwnbCO4XzzPlx TUyYuqDlTq9zdR953z3FnAxsTKcdPOQM+Dhuxk9vAwW7z/aC+gepSJBNiAERoxvIzQ+oEX9jQxiobKaYsik1Q/ZZpWAahBpqjyUBAmS0ZpUR34BUAgUGmdxIC7vfT xMMioZGyVD7jBWPQTErjsvpGTnF7e3c2bXj62QKBwYFwPucPk3a1h0uSIAz0vpMwoIhQ4V2OLYLP5ZB2vOWLnH0H0NHp8e3p9RgsoXo6ZYC3TUB8yMxPn2/PDcHLk E4NDSz8PRouZ9NkDbBtBfXn56TTR2xP1O7SsWMDefD0xsTJuXeJWhTA5OK2gbFr3Ixd8/m5AFwqpgWECDIQsK/QLWltQXycRFmmWJREwRYMIBEigdKJTR4Pg8E6pk gbIzvxytQIeRqUdai6oKAR4BjEtIfKshtMosMmYmDoY43tyks0cM9KTqzss2hk5zDC26yQISnMlMjsyB18eS3r/arlaBfPBW2HTNIRce0W8RDalU2l1pJz6GxYBMe 5TTwNijt0xYqOdabBFzZRQDO3pWVGmiOa2JT+MiqT6nsqTPU30v6U2bjJRei5ZZmvlj+9kdwH75PtLPXl5fEtWyTYHtx1oBRGu77B+DPdzM9hztzB025MFRHdMiht myNji1MmpVUedDoc8jpc1HTdmNVR3NDPbVruDlVk3/ThHuTgIuVjMaGxPheErsPqRWVshQvyCgsxVbpaj3RBK8AaBymHJo1UbpnF2LAm26xeVHALzkThtNTYH3qEusdDzZP7zEk1HilcIaZJZsICypq5b8sNssML85R59MNo1iBrWTQhot0lpqouuWec9Lr67gI3I+5k8ITkYhGsOxhEgKVzz4ojIP7+luxq6IUXiiPZ+KFjF/tuXjFDar 3U4oofOujac38k9dBGvvcfN+N/FsnEQytCcCDJM14BWgqWWFEb5jhv5JPLKVvOvbr6UrwAWmxuqYUuRV9XYOrZZMTnFa6d5AHbRw+IYXfHtXtMO03JRopeJyhHp4f nhNFx7mrvDgA3EtAvBaAqXsQ0mZc9KvIRYS L1LM9QYAb13lYDBPaon/IhsHZPq9vncEoG/RBIwZvaRv3uoaX0FfJbuUgNq1oN3Z7Rb3bgL0FqLQtCouM7YVNdyKOKl8zChDYGNTwkvSsQ1oFSB9Hlyf/vbD+q48U x7T7YhF4uoLy6m9fEHj8cP1k/6MCa 84zd3H2oUoZgMQL1pzNIoBRYXCSrNOp7cVMYSBFQqZAJtVjnWogjdZnE+rv+16nNVAZXcCGNdPcp8iWFZE6roHDYEWhf2QW36VrbrBGg9V0F4zi6JLRQKPw7WtkNE 28bHFsJD5gI2XRVe4H6ny7U2vbRlMsAfztkvqqmAU9TBIMLLm61fxdIQCD8Zs3bgp9WhfcSAQk5UsrInUsgwUScl2DGGqDdk5yZcuU2Duq0QXsvUOwKjwmBAq8wJj UrbpUBCoCFYFyBGrALseqUm4egSqhIlARqAhUBCII1IAdAaYmVwQqAhWBikBFYEwIhAM23dSvv+NAANZ4HBUdoJaVxeAIVPMbHNLK8DAQQNfwt3DAdu7v18sDRgA2ccC1q1UbOQLV/EbeQFW9XSGAruFv4YDt09WUikBFYNwIVO0qAhWBA0egBuwDb+BavYpARaAiUBE4DATGGrAf3wa+XhCDvBNxA+q+LxJA0b7v2Hj5+F2HomsIioFU0 0eMANq7xCZhRPwVEnUccY081fYtARhvqcOi8cOSAhnQii2gD5ooG5YTZAbhJSYZLNstsaMkkHeohqkKSpZUSZEBr95Ym2IHPd9lwAYgFvK4jgMEFO1HCayiaUyIcV v4YtFYb8+xGHliqJxFkRbFuWCSLQIaYm3/sqWYfd1tEgE0TLpX29ZkNmCm+cDZpObztKiGZGVINonFsfBGy2TazvsoAbdeh0kFoKTGFMWw33CrltQoWKcsDqhI982 qOmovtyQIqIIk6wZzw72mrChkbKbC3SEqLLHLgB1SUYVSRFU7+/zWvPf/MKNcwM3t4hFTpvGzXpjDRWcPLTd6oY8m1mJApr+zY1Fo0vVOtiZoPTX3ojTswO92SNTD P/IXSefQVvPxHuO5+8c2IXSmLaO1IjrL24lpd1Qi/xapkPiaNjgCeYZrdliYI79wllt9tXpoLrR1OrJByV6N37hrvGy00IAdbrlLy5Th9LTAnFPNMbbyLQ8sIcAh/ rYygNB+w255+ek0hpYlhi5Q0gCaivq+gej29LfjgK3Ng0yUvqSlPBpMx0YU7UA08iesSfUhj9gualzBc5MdLF+9zxjAy6/PTd/PJZHPl5/QgzypMVXOUESfriNIM6 knwyCA5rpYzGYz/3Mcw/C3l3YKJg7LL08DSa5s4ghsocNCxHR+d3WilKDPsS3ef3xR18ZReTVE9VljxNN4dDMKy1OIa4pdkCwjDlpguVMVBXN79K3W4OHNrfGHmKf pyMof3Gu/YYdw/zBb5EbRrIAo2Y6cT67u5s0hfWplxwFbmweGW6vlfMqgx3YWMb3/Gc3O4VCE71gxmc7Eb5o7mtTAAlav71HWshpJSIfHD9dPTSNthEuCmIe8lJv8Pb69WExns+b6DbojCaKqrWKVW0NQUoua2RUBamUemt/e3srPccSsoyvrll6NR4VNtH4FFI7PQgqWLO8X0+mz7amILjb640J11w2BPeiw3SrUdKtRR+Z9yU++OYtPg US/0P0B41TnW3Wnr6Zk+OSFc97eKUlyn38NjYz61mSn5XYcsL26l7YKF1Rj0fRgkIZ2aOj71/CS2iQa8S0IjtrtwI+5wk9SzJ0vl/PnCxr0KTE85JUk4QM5/Yvn+f Lz7e3nh7PrU4+zU4x7Vh9BDp962R8BajOYx8SyDzHQEtYx8RdjrIUhKix/60R4x2ehQpgtPM/vPt801uc3iW6ZGdqicN1KEKDG30qHPX89e+IhvNSKe370q3KCqNf iW9caCVHtXpt2Li6qIhBYZvaIuapM7ghSZ3mTQvh8CQ++WqW9feOOCgjFs29OpEgRX8iry4R9O+w4YGvzII9H8wZyR9QsoVaxiFGgzE74Y0RgGVxRErHYCOMYnWIi TTH36gRem6NuoRxYLvV9mvqTFRBrKh4zDpBPiB7COwoi7vU3FALUTjAPWnhxWYaz0FpEzz+YqbJYug7amMlV+AvYrt4S5oH5Pi2iYvU0fsPTZF7PuyGAHkgdcDsdF rZE91NVu9ONOfT8lMIvP3960qt8KcI2r2ONqKDlVBGk9TImTJvyC355Ep4zkXtX9g9B4jRs/idXN+ZtKRTHnaqb9oZCXKIo2XJ9+fjmupm/O1clRG/NIA/UL9BQpL AqN5rjLgO26fnI3dEv6vJg8JRv/jQt8qJNABsG9tlNBmUa+KJNNTdwVvPsbJOBVvV9RWskobKaK7LXEYTiddsFAr4tacdjGpi0JU9DsgbTfvncNApdgjyUGDRyEgo +NLzYw5d1NwwCgHWrHRYugJucd9p5xepCN8tmD7h3G77THSzWqUbgQPSsTbsL2iNI19qsmreycEbioIWHBtJg8rJXYeS6DA2ogzqhpDEyoqIkI0gaT0QMiN7FjJfaRs4uA3b3+vkeUzZpfO0Z7Qe7yG7SYohanirtyNi6NDmcrVLKObbjvoYX5NcUpBSsxzUQiFuU1XgiBpN1ZC1pVexaDLXB2bQG3+ZAACOkdKJTR4NDPe2LwMY7bFwAb Mx0Cm0NUARzyofbcyyv4NaaML82O3OG0uAc2sLSMuyC2brjmGPWjJ7QK6QAWIUKwuRVZ4Ppt0og3bpuc9QZdQ9dtGRergruwXEUARst5ljX2+bWHfwSmGgr1RDmMb t6A0txBLSXIVshWbw43pLRWUQrptY701oMJZfx247F1dcy6omFgH/LS2Q7j5+IRHvvWxSMicfXRtv5MdhvspAnskXxlV+QDIt+ITuMUwdurDP/uuuMwMY7rCUAfkC vOpOJBWIPvNUp1nGXNDSjoT2t8cVnJIH6WgJJiPhBdICYkiCRTND4fffx9DY58tQdx+wvQmPiOMQP1h/pFJnORtUJlQwqZd0TGH+32nnARqtM6IaOsCm5p3+78h/1 oafBDJtqTzHIC7aFToxYcOzRbSHI04rXaLKGQNbSqqbPIjdEgtUvE6Rrd/QnoQdB7WdNhoSIGtizjdXNl+wjhlIJy19Lg4fXk7nWQXtFSaYOcddrFa8XJQhQe+pu2 p7sqsM+vuVobQRyeK/lXPzXSUl97BeHtBWaxGtEC8fKtsSx3JzLVFJUTnhk7bLuWxUe/uh3sGHHHFmNOxPsOmA/3i/gwFyU6L/npvKfqpwq+bMftjDDvp0CfS7DWp 3fwlGGt yjcO63vWP74DWjTQkZK9+uw7Ynqtl9OjZvqfZa/1sHyducRfWiqLAwFptTdAWwduFKHRFXjhUvZpmwJ7XG0axk+8vpwvrH62IL6ZpF4uCJXiirb/9ReDwOizXiN4ZYTUKPRQ7zfzbmSiArre5KBgadiTiu9DooPdbDdghJNHe/J4+5Wr5ePrlZhW5gxIac1GZzG2NkOhEWlArigIRrRxWESUDOq4pyJF7zJc0CWnH7bYPoTw7ZQ2kiBnfs yGzUz9eVCwbIoxsVXANJA6n6OF12E41Mh6rlgb9/tWy45S+zBg6Gn+oFmUzGEJ70AAAEABJREFU7FBJqlvAB5dpPhKqnQdswoGiVutr6SziXX1CIuZfmbMkacaPfG 9EFD3twYyNXZTUYKn+7dsopk8jOvq1KhJkCq3ngyGA1sjDT4ajm5VPIm3rqgXuTO7v8kJbXiS+C31bsp55CBCYfnNwSqRR/UYsbwxIc7mCnZvkKakSUDw/ZyAi1t/ fhQX5BcJ0SoueR1+MUjCIH3BR+c4xo11czqpkFAK5rA+x4ZOe1d1IsVEE7I3UrDPTWqAiUBGoCFQEKgLjRaAG7PG2TdWsIlARqAhUBCoCGoEasDUU4z6p2lUEKgIV gYrAcSMQDth0d77+jgMB2P9xVLTWcowIVPMbY6tUnUaAALqGv4UDtnOPv14eMAKwifVrVzlUBPohUM2vH2611MEjgK7hb+GA7dPVlIpARaAiUBGoCFQEdohADdg7B L+K3g4CVUpFoCJQETgEBMYZsF8+fsevElfHEqS70D6+ZfYlbF2aLmLcstY1dHD+iX8w1pacEVzIqm6ofp3YdiLeHXRQ0zGOlC4S3xRJNG+dslGmh5uBhuntOkpRUT LUsaRcF1qP3zo2sJZgTxNKUBzVkdJKf6qMOpaW2x+6kQTsUoCJznscwHiHtAk8zNAhjRCahcS5XxScUh40qBfKTDp9ZUcI3+O9B0MKM6ongM6REFn4ewbxkmDL4Bu 7OLEQENuDVdpsvDproYUiISFLCRrNVp9kS8k6BQvnLNOtVqkwKXOvD0HAUgC4YOkmKuv+VDxtZAJOomtZy7OSgigeKltWNIgGCY8hEhJF9J7JgdDgYV9B5dQGYsGy3RusQiUDJVTZTMkQt52ljSRgd6m/937ZyNtozm/NxxKW82n5q5510YdZo19Xn3m9jqYzpbpv1jGM/2LRGO/p2yebSTdW2zwAL03aMbflDIjRnsnibnNKWi/G6/F+0 WS/9+LKgnq09RQZUqWPQWo+ujAp1f7i6pFv43ettsT88srDMVKNTfBEAwYL1m0bh4t5aLoWMzrLlOKinXZWJyAJEe8XYGqpmOs/bXmNBkkzf6m6eWpywVSJVmDJGb 2FjFhSNaSsDHNVgkqZP7Tx2TcnJTJHQbOHAdt5S2zhMPHD9dmN+0ma7bdAL+PfvppVIiOAwHWxmM1m/rc+OHuYHQ0JnsR3kSBPDvojX0Js6KOhfb4JRpx1uKVRY6L X0JD3MVLS+J9ZSBI75BY59J4SIBPRYVSI9PJ+AYTH9QNNBHFALTBLBMXZYJA/R OJDKR+HAVSOQNQOCQUCQUCECQUCECQU7BH1SUHJ+Y4XWYCVKY0JN7YSDGFXIJSFABCSZ zNvb25X41of2WAMK5a8izWYiFCIqSqumiUNAyuOH66dGzfhJQ2FFWKwJEJtJJ9+cNWagTy02Lb88Bb/TRJ8pM3mY/Ov5thDo7v22pVkvOcasfzmfahbknYsCOIxVF yo9QTjYjd8vVTBFN5KATbg///rSAEvyQUVtlaqWkQe/Ro7 iF+9doIGUeIpK+vucc/6GjWBWcpgce1kaiMJBcfr69/fxwdn2au+HJwX2+pO+IEjjtag1W9SzGgYvTV9obklGnFgFBKmf8Nh/6EHgq0NvU27narBRCKghFQGxPG2B OG/R+zH//duSdzQAeqwG1ULNW4GAOMfYjTB9HwKZlQZ4BCM+4SrYVjb6E51R7cl8BbCk2TiYUHZXjDRClkjChaaZTv8tKDQx/LPWGj1+t4D7J3vgcO2cFAJ1zak72T65uZoYEwTpSoWbv/sQAGohENG+DDpCyt05tJmDzQ2lQrCQOg6w0cpqNGIWzypueeOgfojUFa/X1IOJNQTusVNOAfEL0QAUCibKwsnIMTENgWW/j1LBgrVjDFnntj CLRl1BuNoK7Sq2imz7bRPcP6bwZ7+dLssYUaE2fIppCKzTRzHUyDJ26acRCaQzZFAcOLuLu0Jvynz9zC+3wegwB++Xj+8Xs4WG2eP/xJQMFwWv7dbqCF3PLwcFMTq /PHpAddr2BVIcHqTW9vLvDrbsPj1aejMfMgjypGjiII+aT0jWKa95r10jzl2uDn5DyvXrqQbAOVMhSoF44CAjYCnueJF4b5K5Nb+lMEdrRwEiCnZuZNLeG1joJlGq ebTENXYAVOkF4gwWDlWariiPtYWa4UlgwvCkUAL2iOfij6JhrdX/gJjfd/X3YSM7Q3s+XgmHYZ88GejYn5hwBAXaS7wEZCRsHzzQ9S7SZulcUrwugc/spbNk2blat dADsKrHl6xEEbBrIYs55/s6PjF3AoNZvLZCu+NajNBE0mjzjKYc6jwsQj97cXZ3QhCPx1BGcm9cRAglaMyhGvlbYCPah5fq4VoeTgwZB7bNbvqEGhaSTVl2bPqQpD SzDIJhzbZKkLUiwgR2p2blIyO3jVTMlGVzE6oiw5eSSl1HmYE431f09gDbi/TwpfgLMQbc7zKtjqPT5GSlkmsJsvL1jxEah9pSKE506tjn2mWiid+fZwIHqeYoEEk imLWGMV7sO2HBYWOlDXGwwBrwpfh4XxVw3N6hrf3xL03Npxee3FGK1eceaEV3A0SlShCyRV87ZJUohMa57l96OrbHUENe+7UUUDDB7U13IvjR7UcsZOGOYHgeOnMA YOtIcINZbq5VSB8v5hnIy1dSKyhY3PRFbP2ELkm17IBAsuvbCl/W2uS2I3X7VWBzq1/KuZwKBjXZ/IYL3cGNb9H6Qho4jt4uF+V+l8WdfZSH0Zd39cC57V0GP4nomd75BSxVxiDt1Ea47Bg5ZGTBW2yA1SFZv4MzdBmxC/exBhywRGeONJOpOqNO8lP2N3j00F5PQqoY0MxiZKN00tKJDzymoa+8IAehGS8Mrew63itmHif1pQhG+Wa3X45 OZL9kEiT/heJwAnrrje6aZdt1oeZ4iIMw8Hpzj9Otqt1/RUWjkP4xgZjpBvo2cyUPl2i1m+Uykqa0hQp0bHcAoc6yWaZDvdfwvez2pDsw/xiJAnDNKQYp3DLCRJ20 OskCU2dxHurKvkg0w9oEOzTk6/3LTK0xm/XiAXcHIV2Gr+bgM2WYMRF2mW/Tl7IxIBdzrnoZWJ1Pkt5gqBOCynR8gU1Lhl9Dyfn5m3kUVGuyetPFOEWXlpuoi4mWL VhPJIJ/MfYchmlKOcwFPKcapI2iuzodrVHyFQ2PREGvtJEyUHYvwC1vZ4v4CPdc2MhrnT7MtdSHhYkDE7b4O6Y500gJBDX1jrYZvqxro/NYH5I0FWY3oJJrU87+b9 ZCH3IFYQMAc5HbYpW/uBlcS3EqGuyva1h5SXYNM3Tbifnlzdzcv6jstvV9e7Ddi9as2PbXmzXXoup0n9twrLgqV+ury7uno3f75Y32yYJe3oX1T9+9yIzxcL8x9hy KoMl2yfWl2XmNbfPiBQ2PSDVOX8NT0K5totbPr6afb6fAARGJXaRhm+qqZqY71NG1jH+5HWHFPfv1piXoTWHvgFA+AYthg7dRf2E2ujN0P1HQJ3C789DNgU9ngpwx rC8UphwBLkvAAzhubXj9+Bimcu4EG26vq+3oCDHz/iZqnE6/YsrjffWnD0CKzf9NJELdvBReD2GjlEXgFHtt5g0yu43wKgIoJy//9dwPnISda3gWIAWdTlp1Pd/Hx SYAOYPhCp9X6BhrgpxxWwt2Kt9oCQqko+n0DQP3bRgaiRq8/u8scZsAlcglEdPXwowx61hVyWTXV7dWWut1MmyfB4pxPixSjH1qljsCYGPTRK6zuGXMQZgiJSPyfZuczr36lAJ2KSDd3zbUJc+zW9X1LzIchIA+cHhTSJOMnrRyz8cqI09hFJVKr+bASovcJ4Uw6wNLa+sBInkqGOtga4ogxDDp0SPXISmywUIJQ5/dSlwgGeCUVKs/pwV mXU0ZFFyYRW+t 8C1fz6Y1dLHjQC6Br+Fg7Y7U35enboCMAmDr2KtX7jRaCa33jbpmq2UwTQNfwtHLB9uprSD4FaqiJQEagIVAQqAoMgUAP2IDBWJhWBikBFoCJQEdgsAgcTsB/fht4 kHgUP5Af+ooBo1Y2M3Z2W408vfFjjBTflggYCA/p2sKx11OtQFqRrYDgQMvvFBu0Y9ijA0m/gYGJhhbuUjWpVKKuUbAtylAh1LFGtC63Nr39Jm8+ur/YpYBPm/lMG fucxMUVnUEXShGYh7xxc0v4urBpJXkOqp8bYEjKwIJsQaH9xLDxSKhQnDwBhtUCqsYKiSJz4pYp6YsErqyRoBGdzny3liAKTfBEQmTJwni/jyFGXYFUAhIX5OuKU2 G0f3QqgDgXV7qslQIUA3rINY2jWhZaZt7tkUajD+eJIAqnu6hiqJOW1zM0zZhQqYqZRcRJhpoXOic5kzuclBfnLyUxt7NIFReVDWow0bZ8CdvuemodZoz9kkHhXDV qD39nHjw7w20zTrRduI9jPxaJZ oSVwR+h5T9t36sqR7ePn1uQl8SMckQ/NPTMwhk3tYrpeYPHZ+3noUqL9aUQu9Og1qRdWVUQDOwPhqT2l9YaK2L0oUhLDT67MH1mlFn+hI0Eptt+J8HLiEfgyb1GK4g1eforepuQpSHxhOp1Fw2qeArQEr8Cegffn4fjF70A2NxnyYFX3UCGXlhl420d9ko49lBr/gKYmP5yBg+XS5RJdlL10OCxeF54PXGw4v/orV3dWJ4khfSVu8//iir mPHx7cXz/OHy099v1kEuc3Tp59JDnwsakUbfdgqJJCM1vx0W4hmwDT+OlHPL4JQWVWxsEr0ecNmvrTHHehhy3lz7X2 CrlOeL7gDUh8cw+eOH66fWcZExP6U+LhhmsonU1sgZIbUbtC9LvZ3X3keH35I8cqBPm0VGYJESo0/ex4BNBt0EbFg0sh6N+q11+moqaCb0cctE2yjL5Dflq0mXmMC 8vmc71VISXA4uS8FCH/tZya8yCk+m3qpvwaKCMwMmERcgrmgys1N4WDc07+er86vPK27Ujk6hQbhfTGczEaEEDOTQI6N6NtpGDhhZOsNS7uw6BXsRUN/1+oIXytJY DCOxeOilvn iy pmJa7h0Z7MiR2H0lA8aRBlRXdErF6pkVjTcKNy1EauaumEQGZDZvj59vYzrVnmPnjFGs2Xy/kz31lheYQIzDglRuURLB18NkLudTO/a5cciI8YqubcELrX6Zcbaig 0KdaUIvTUt8TSArFufzQ3Nz8o2+aM/IwgO3ugekcVfXxr3wLgGy8f5XzcCbouE8Lry9JIpRYV/sobvJKXsoJ7Q6Wvxfe57Hm/wbDXKceqVnUykWEFWFqhYmzEsDF0M2cJw6Ic5gLxenZjdwKPcdsTuTsau6QteHy2lrBfARuBk27uEJbnt+T9Uo7y5OpmZgR1mMnFItuAWwP+SAWhBamzyvm2CwKmoc106kds8iQoFg2l6HaYEAqXBjq6W Ug24rLHNSi5U6qhGJLUlshSJOKIOlCwVtMKKkdBOxLb2uB+RbM3ogw/fSyYh/YEC6byoQjpk8POT6/P/NgjwkMEFmaDknz/R2ODmt01b0J9jPoWvL1dZZSHu9/DLo YGpVgs6o0LmBDuhF0/MSrmzpkAIOsbrM+QQaUnAA3hZfmiNxhRdVkAUSPf5XwKqUNtzLVVnUzEEBDsdTKRITJ30b6pdUX8bBpCEENBgsyQpGn0iS/GtjVNGD3BGPl 5bkMsm PgST9AKgwpYiDBXulkZ1cAKfkQRFzEz4jQXU10mgpJFmB6dBsMxubm9vzrJ3MqmJyu3cqDUVnLxp7layh+BatCNqs6Kg7S0Aox4PM8Rso/kpWj9IBgbvcZ+iphNrg IeKwYJWKy+eIKP1Jqg2lSo3NKs0tZG2CBcfmk9bs/EGU9Pc44ObcD4wW0KirSMZA6WEfi2VWx9xzVb88DAreLYkLCaKl+Bv70WsuHOm17JCzInaHY2Y20QvsJnv9G qPAja1I2NtAIZuID0EzkI2g2Rl 1CxIx0owan1tdguWMH508v0W8iONHdaMYoib+LqPkNWkZLSiM26mEYMdTNNHufoQTJKH9ONK4Afl5jGDdAkoyTLK6K+l4BBlysk0KGlXWokW6ec23t++NB9IwNU3eZhDtI1g7XbK0YqIS8T0ZV6SPmckJ6/zASwrn7xIP28XF6xyqarZOaFe1DqsLeicAXSCW3meFeYw3nLBHAVsgkTCdoLmAPpSOZNOtCt7mHq1umqJ1HmJolq3njECoT 8Q6AG4QXut7iOJ2R7p9WAJ21IV1n8OsyAwhXgjyNXIcnOAUUxLijM2SLArSHjoYRNYpjM6yI0xbm1tPSbOIgEXpwyE7tp7OdVOUJo96HkGAG1CESr+3f/fz95+tkC yZ+G2omjRjrxChKcBEnRunUkKDqDZt1895iSZ3K1YV7 7gB0zHXjeQUHl3hwwz4Q/HlT+SJlZ1o2uTn082ZvQgbL2D6bo0EujuwN93OyNP6U8BnSgtaq5eQx7PHEnu5H/W6vsClNmBG1jMmXVCwJoymzAQos/KJMAFGUSuRb7 eiEQAGT2f5RT6/AjEREkzfUzoqXfoO4H1k+3TYRVuSYglB5gb3hSjFogk+rBP9PiTEGEVD5kmi xvFXx5vvpyGHtxI8Nle1t4F7B7QmEFFdILcv3V1EIKApHjKoxPGRGrOQDtI3Cmp2a+lefOh6zgG3qLtVsS0vZL1syhk2jYP1JezrRby3eof3ixlaVlzbg5JOJeWEq by FewyM4m/0gZUn16s8OaLtLeWIBitZM3o6js7H9juGgB3yqmj4YZqCjAS9Krd5RjGM9MplYwjAZVj/DbueIP7PM+8FLbTi/TSglJ46drLhTsQ9FdpmMfrXcf81hhiuXSYSD4576KHV10JVQ0KE50USJXMWEEDU5HXAW7R1OYFVZP/UFDL0E6DPX8NSI v2OU3DSSU1Y+btx6rpadexbox22c PLrc4G/DpkWqhioGflWXtFDtt5oubPD3bayys JevacKtL9U23evycAlDiZgw+qDs1ikR2a/6Co9wKQmDgrqweuAikRhieNfuHoV5RxAD7Ruq0K+m2QWRHa4NZdfmvCrV3RpCItYVqxmEOaUCMvWItInYOdVLaHUWrL Smux9rg+bh6ysI0B32lBdxkrIgr6IVRt7iGtR+xCXIkIpte8hKIcSVW3do1SqgzziRqXU0StKGY4YovfoihKIWbg05dhiMi1ZJG9TRAcTsDcFUOV7nAic34652x5n m9RaVwSOHYEasI/dAmr9KwIVgYrAMSBwAHWsAfsAGrFWoSJQEagIVAQOH4FwwG5vwNezQ0cANn7oVaz1Gy8C1fzG2zZVs60i4ApD1/C3cMC278HXq0NGADZxyNWrd Rs3AtX8xt0+VbudIYCu4W/hgO3T1ZSKQEWgIlARqAhUBHaIwM4C9g7rXEVXBCoCFYGKQEVg7xTY34D9+Hbof9Z 1Z3gag PAyBgNpVqs1yTWWINBkXtZ9ALeUWlLJH1Yu8QMHq5aPV2H7A2g7qbdRgFtYAA/yh8lnFmChqyuihpidBKpjlYZTJqReu2lxnbDNjcoF5DUOowkBMn3eD8fQ/nPXqtmPbtNg+zRr9rPPmqDNgIv7POfAaB32jYcg1bAKnF76AUJekthB4IuiSI6VuukvTs+jROqsvUkxQCaDdhFPQZLW0QyUbTBiGawXgjVUoQ50Fa29ZkHun2A7l436KSh COV6j48Zel1txsEqBmFkU3kW0flVbz1Ww+EJm+30Ed01vQJ+g3mJCXEP4oZqtUa8+phpnsPO1e7WH8l6S1vpNqKdNNdL+GLbbVWaYdqa7n/V1sM2C8/f2qm06dPP7 /0gi3+kRbFLtIH2Bh4F3g13cuvz02eMyQ83i/8z8ec /GBWGi44uVCpnVAW6VJLtIRC2MdhaIuwUa7crn+AYc0PeqIG5olorRG9b/y0qiU4znb87b9Tf+bv5dKzf1lI6DnfcXsCmeH15dzPrEbFhDc208YOcGPG5o1iM9eT4 Vh1cihY+cH5qnnyf6nPmzy29+WgPNuhTrwVfW3K+L8Nfojll5TAeb5VpGho+WB9vgtSy8YTJpZ57CBg2ETcGr1QgwTcMk2j55cn+YsjJN2eNKBKYlDQNNe/iwpntF xqVKbeejwEBzPy4U/NuPTMzqrMzn+AZcwPHZZu3VnMQJSFQM0ycoNNYHpt8eEStBJd9zdpawAas9DUFQtuPvEn0Ht9ePM/vPt+ceZ9bE+sn5iiWHHN44TrQgUAMzk uMFj2n6 91a/QqLh83Y0FAURrY/mYXYVhZmLQZiQk1HaCz858gmfMpLNyRs5MYwglqa80i/v8eiI6jdlnCHYzBpCah/vbVsCmdQz++hFFbH9GGwMYMZXu8VF7oJluvpxmbu7BcGYPRG0yxFL5w8xdNEEHIy9OtOe3y/nzRfaRM2apIi05f7rnwonJHVZsmuvTdhaF8cdidnN1kixkZiqRZeLMkvWcEYDtevUtOCsF2vYjzq+B0U4WcVPcWzbD/nR7 eTqBjf6NC3NlRtz9S5YEIZN1tT+yCaDlDVxtAgg2kzNliZLMFyOOc6D5xE2FdpjVC5joraiJvDXxSdIfkIa+AfYBZOoCuZMBsPeLzfKSkOjT5dLFyWxuvjzp6fptP BekNVn8jMmV7M9vt5SwIbPnHK8bsQyYME4Ck348Tt7toFmoqFVwpQxKlxcuANZRP0L+4PklPI8X+rP2yGkrx7OzLBqNGnbwWDtpvXbl1GtmHlzIToMVkabBy3XkMK nUN/o5ZSEEYizoE6p9dcbAasg+1HH98DIlFcyjqVOAaXJREVjk/VGom9rVII0so8alVWNerFzBHDvw1qnpRvAzlRZ6QgTMQwLpzQSZ0vEebspi1vPJ5DzaXmKM8VZ KRQ9QtPWmCf3r6N+ixbL13RctAJL66izxXvnvqOpHhx3pKdMMlM5k8s+n28lYLP1ynjdIWKTsbn+DjYUN5umoSK06Gm1KvnNlcWIyKwENGHLGWemTeNSGHp6bxYBO 3szeSQI0e3tRSEa6Nhr5DbfelWAABZ12pkCz3q1LRaUNkjQionGU4SgUpZi2RjS22tcKKLUsUCcEluPO0UADbp89V77HfI5bWuvo9mwPgEDRT2fgcpZFUGj7NOyRa SbZddVEsuOuO2JZcfzW0yc3EeFWvjIcSt9cCuzUZN4SrP0a4sc2Nk2AvYLFjsaY2pKa5DJcZSPMexM9wVx8ra5jURu1aiYOclxq2laBm+fqWCNfXhm44/vtPEbbEO nVDLM06bG+vm0DS4w426r5zazeiURgHfRM4ViT+pbR0kDNmhpbRRgoc6NU6kUHUAMYzO29rRIGPGov7EgoBwPRQ97ghDQEAahGhsrdfrJREpzmn5dn2AZGXyv4Ynzr55gzS0OpKF/+3AdJQHFhQjXJI1DtnELkdIyPzBgreh/6jKke5+9hYBN8docCcGesQhU/rA4Ncf7V0sUMzZywMoZ9m0E+HGDY3uKSB9gCTXI2bdkOOPJvNO/AkU7J KHT8w11NkB6nOJk982OAAAQAElEQVQ4xo0dEOpH2rZ1ZPRmsUVbT4Imt4F1NzmohDXpDd3DUqde7AcCCGwhnwTb83sxEnV7Gyehpl/TJ6C4FsDsTWec7Q2o0+S0vX ctOLHfs6sKKf0cF2YluDtp6gFo4N5t9pYBkE6m10UBoVfYc1tl9/1i8wGb4rX7kNXJ95fF/5BNq8LzO6yWWFBjHGb/gxj5WI5yeofBpP/0kNnOFsPcRVANeoKp8DG JMH+YmmmqTATTF+a3iiwhMFXdbQ6BYFs39GxiUWPrKQwsUCoJjk35EFUWGt2hKrQrBIbxCY/83xJYcy6fwLL31i+GUNWHOv5jvHw/Unouf4CiinrHkAtEX8suUeDe 6q1LFOTlSdzrhI0H7McP14H/VKYnEK2HNOIg4g4kPKAbaDEuW6jH2Lgs2koaS/LQwZKYrd6xGu7NFbohGqidLlRP9hIBbmvPqZG7K2psPYORA35MCLDkt+zkKPcSt 6r0aBHg+QwtGt2ew1OKu+2uTw0pT1Or9h6doiCLth/jVTn1uGEENh6wYR7BiaJOx2gtSKArTpRYItEzZz6h1WJvbqqLbOIEavBKEIuXO14jLx0D+NN9wSWx9rOJel SeeQTQ1vzGQ9FAck8ml7ZUyRjjS1EEM2w6pxVF2CqYkhm7bjJgFnRTU/Kqh2IERkFI7S0a397vrJMjtpIm968xj4ERCpDI565E1PZvRwsStSdSSUl8xI/9nuamSLd 6DHQbodvOkN5O9TcesIepBpwdDM7cSsNkD/kQFuZOxmvqsHKXZKLC/JItn1LDJx5hvaJia0YcAQ0nmjvUBEhu24jPisAntkxt7HRB4qkvoFqIWJYzyUBZtz1AINGcIQsL1YhYdGj6PDlRwKQCPGVOgWaSEmzUVlCorR0VD8hvCRJnKOvLQqJSxD/65An2+5e1JwF7/4CtGlcEKgIVAYVAPVYEhkCgBuwhUKw8KgIVgYpARaAisGEEasDeM MCVfUWgIlARGDcCVbt9QSAcsMXt+7o/BgRgqcdQzVrHcSJQzW+c7VK12jkC6Br+Fg7Y/q38mnKoCMAmDrVqtV7jR6Ca3/jbaNcaHql8dA1/Cwdsn66mVAQqAhWBik BFoCKwQwRqwN4h+FV0RaAiUBGoCOwzAtvVfVQB+/HtOu9qRunO/zRPrxWgN1moYxH4XQQVMwZTUsRSAGnFNYKgYlpLyNFcACHTvPRlOcqg9NqoHD6Uri1UDlelTCM wcnPqo57qkuqYBkDmdhHUibHkP7LDUAE7AlsYIUpVt/S7+TCzpOKwhg9NNwbqJGWklQwpZYaGtJQOua1CUq/Cr+10EFFJAyB3a0yDQdpuJNYGvWjWolKycD0cOgKm eSRdnUkoDMnaJ8saICbYOCwCfs+hMNiufdrqle4fAa26fCsbYkL8iWu6ciiYJlgbAWbQNWBzobV2qBi/2U48SUBv+wwBFBeh39RMDPjrM3FaM4cgNy04gy7U5HdRk hR6C3RGSe+bS0Wv9jF0ulgYn9iLCKMXZZE+6iffVW3Wsp67CKAhRbPTCz/1Cw2Trd+vMVkwpGmzWeWNG+STll60K5XqNkRgyUe4I/RE25p77jzI4qOLCtI1bdIGqK DonmEyzhMiTJ6auXjlJ7IEDbEzfkjXlGH+ghh0hnnQK0KD7JjY8g7sGiw7LnJIYGSxERbJe+aI/HZzXjgGgtnr8zY7ecbwaQiyEdXEYWPeOKmwn+lUwXLgXLNUw/r sClO2HbBfPr5fzB7a18fR966a6w+PhequR2bF+qQBCzUVCX2naSNKGiZP5v7APQO7Fp/1KlxL8zd9gKi7qaYdFiHbbJqscdNHvGbut5CoVNFXwYbVfQ+56dhC43YdneKdx3T7q9Xy1f3Hl2ytp9Pn9wEy+qaRKrsxNRxzytuT1EjWM/TmekkxxMEJWDTw7NSrRueNO4JiOG/Xu4jrTmiUCh8wYIfee0+zGleV6atTM+nkm7Pm+dd8zzHLx M6HSuePypmjRf5ozf12hhVDVaLyaREwnEt8itKSx8/EFD3GY/nlybZuMm5RZDLBENzle/56hnUVZyRePwHnwjTQNYZH0/k7PQc8ubq9Omlyf2eXl82nnx33hEj6PJ /PcmXD + eVqeObUkD2lnKWwc/FVLvpGJc3JO943Q7Tn + aG788z qOcK7bbTKpvD4ue14uafEiRu43bbJ+miPXqyGLa0FuEbfdgchzM1PKXjMefRhzDO5fEELzn0aSOIn5nGxSdzpq6lt3WTcoshqhTUUyaQ90OSMJkKiPcWebxjB+bVU 9WyHCHzz/aW7uoYI0lx+/83GlfLMqSF7ap2lqYDwGvRhOPOTRCKo3nw5hWmVW72yWOnE9SFslPBKZLKcSfYsyEPWburb7Xyr3rg0kDUNgU51F1WWe/Iw4oZItzqWU Q8YsIsE0oewFxet7dB0ojGGvcJWYg6RRFjjn9PrJ0rr+iOgYcKTSc/yvjyht2gy0h5W7AnwS6kUjNgXTfN0/YYW30QnI1YBo3eNiWQpLvUYRgCDoXbdmRac9ZSJh4 f+sIeTufn0zpkFhwVhzfJmtrjQtK5xh0u1To7aHL/apmGg1k09fzdvrk9b31PIj12WuSyO5fCzm4LJeYR/uRosuTUnxIc316azNAVIr8Fh00ync2FhGzAr9nJ0k30 t3mPzxgRZ2Q9LIOb9XVEILfEws8ftImOQ/YAB24qk0tMFAiKsh8cggoLGJx1aG2DAo9lb0EbT4Gg2y/k0QukgTkPbCGUwGbVkLeMC2mI0AXxCxEczX59qb9/m17NNIQDQvZmvajluPr0rNTKUbmfMCeNmVye6QGpfrWHIpqduT48sAfFOwOLOxZNeFqfBdfnDVSH1O6hhmdOE5s9hZzmsOQUGrIAMmznYoTB78TxfrlalfSOEBaURHtzR4 s5yi96YJk60IIHqGlsgkEF1LIGYs0+kYAMwFwtnSQDJA21DBWxYFmNOO0wM2RPSOX5+e+oWQm7YAEtrB0PVRgQV1mPWCvVuWWMR7Gm9Xtoyt87Quri5CbiAEirwgA na5pZTLMnuxeFew9+2016e9V5+r27BdKo1GgjNlCsCKtg1b5Y9Ir29xgVTZHYF4nLq1HwLAQaeu1mHfsaTYvFkLDxBY6wIWrw7XJSrwZTSTKLmYBJJ2tAhWt7Q3GT lePJVa78NVpM+m4vvBgc+BRuTmtN67rbnjaEg9NbIOdX30aNAZsw+RYCnYbqFFLgOtw0VsDtpRFGq0xDX5E6FBTLYYznTmtjr6G2W6HFuL0bRFDjTSwOD0gJdBONl O0aFuSxp3a43Oj3qevhFgKqe9lJ3KvIkGAvCwMytqFFgnrrhwUKdG6cG3iA2BZjnRcIMVvW0AwIwiBX1M74FVVJOxwwsh+P2da/hni+nSA2ykQ7GQOSmHXV85MxXM pcCy7bl6Stl+zkO2fwteeOsHkECCtoU4tvoXuRegrwKEncSsAv0ipMogAgkXkMxb+umsbJie2aAjc6knTyt/CQ4mxqRVvKXKKFqByHeWIy5+YM5WcSugugbg3UMKW OMh3V1IqRFuxQ0S0NOiB61FSXkns2hg+ssVBmrK1KAPrBZFxavZD0RoAeuy4tyzHj/9u37xWyN29cBed3UCDAwkx7fTmhAqg2JTngGOLzZarFtzyJp+of4pUnCJ7Y rSzsxCOHuRw5vY944rObIUtcP2DASgtH4YdrrTzhLTAbNEo1UAdxofnr2QDelSphzINT2hJOs54Y6IKMtSxrQbgNJrUKklP6NRLsNVHhHLB/vF9P5nftYEf03ftH/R2tPhI4gawCOTXsbVCbWw1YRwNzT8BN0K3rKt0aQXvKeGloWXyzWvzEGcUE1umIBZ+B2fFiZb7f0lKVltlAgXN9+ntwvxaGgtf1gxUbojf2KoA6xQNaJOIhAz8T1A zYMR4eOxEmXSJyvC+NFc6Dbc8gX/21odIM8g0pREYgigJveCLquPdH4MOKvbU56yUfOMuAhaVZQOrK0mdWrvgigCTl08A4TOMSI1/d8QTuaiYqAR4/6mu9ciMmjZf Fp99v wZFX0o39faZ82kJShg3bRGKHTuXy4F0yJpzsOCHSE8COpIVE1jREgB2DHEYAND9FuwleYqSKloX9tjj3S67DFpSpEUsHMvEQSCBwDAU2rA85EATNVpKBwagvYCFmk d1cPjHkFnDPljkYmplYvvz7H6ptSIZVHRi6lWYfqi1Oo9cvbScAmw4b1BreMAcuidu/kqsucTHkmbXdUiHipY5uTOEO3KJbSibErs6OgYqVcOUd5rVsmgjKSHQMlQ 8lCRWydcq27JJ4mlxCxLGySZYWmCWpuCoHll+GeIkvJ6ZuXsBHv+RfI8MkdtzB0fcmmpc26B0cytEtvpDvZvTqmqWUu5BfL6cRY8h/ZYScBe2QYVHUqAhWBY0Xg/L bY3x8ERMdW34NotLYSNWC3WNSzikBFYNsIVHkVgYpAMQI1YBdDVQkrAhWBikBFoCKwOwTCAdt6dKBeHDQCsL2Drl+t3KgRGLn5jRq7qtxBI4Cu4W/hgO0+PVCvDxc B2MThVq7WbOwIVPMbewtV/XaEALqGv4UDtk9XUyoCFYGKQEVgTAhUXY4OgRqwj67Ja4UrAhWBikBFYB8RGDRgP771/pUfSe6bIjYFE0T1/U99eh1LWE2faZw2W7E1imZ50/uv+1Y/z3xfKPzmimuO1tgSYF20cvTtoiTEhI3Y4Xl0lwAx/DLOtZFYk/OaxQPqK47qGCDJJaFocb9ImlxOUO/8LhoWC0FV3GojaXQdatCAXQyOQdgNFDSV9 5xBGaahkmBVVtjQN3saEpSWAghcU0lL6VwgzW6vclF3NJuzxeDrRByAIdSWQnRCYiwrwF8kBbSM8gCtlUcapq1LyDiivQtRquoEn2hQtbfQFUXBUOW2xwCdoLb3wb LEJVbe14io6eeUAKGRYl/ZOgSuAmoZzOwCoLXyIGpDwx9DLoRSnZ2fpYdB7Zyi8Hb6xNYEtRVcP2BDaQWrfBWjvCxC9/F+0SzuH1uFsmfWi2vLv2tEL7kRDw+gTMu DXqzjiVyrSq0gLc4TUBN6I3B+K2BdPcwa3YyxV190Io6oFPiaFkRHiHslay3bmvXiUwt1QwDdnN/bKWHnA7/Z0/H2un3Q7lmTc1TQZZm7sYuZLJUPmBxKpkpQqS4/ Vy3UrEvxrrQU473F14ZSHag1Y60gvHWj8SiBAFwRhxYXufDDomACMlpNUMh4xWpZ6c7Bi4WutVs/YGtoYVPWlkcXcNELmkNvWF6rUunCyy9PT1+WKZo1tnWg7AAAC kVJREFUquSzhbiB39378uuzFgMIpcXB4HTqEZwQCJlmbFEgYnnVAjbWN3ZDWfEZKalxPWwGAcwVCr5tNYBshJB2SoqLomBQIvfp+lR2/sl6xrxhk3v5+VMznW7+a3 XCT+NN/RSHBR4QOLEBGYR3DU8PYTSIXS36AVTUHEOR28L+Wamlylygf5/Baoda 9R63XZ/VMZ6 //// GCNZJBXYPEJFEJFB4K/4RFJFSTH1GIVEGL2BZB+5/VBIRYEDWSD +Gx4kk7AR/R4/XD81am2mbanwqIWJnwRiLWDL+XQjFSoeRoSlo3mfzr45CWdSqmUrjqMWX4kImg0VPZZfUROUfdtqzJDp6f5qZRozGYFjF+labNjkwL65vLuZ9YrYmO+klUeuiCaTCX8SSr25 6RlokrlKiBez26uEu4XrIRpMXTOrgUIZGJ7+fjm0+Xd589YlkhVQBAf6v7x7cUC3mo5f+aVrxbA0KiFiLGopoi7YiLMFz253cLDAmKM5m6a5195MIheIYvE6amM/c Pgokl/wxEVb83EdNRghHoiL2A2yDuSzWyCdJVhNuSqZCOJA6+RB++T8Xe9ml5BJ63G4LlkBI5dJGVs2OSIPaYsND769DP3jKQ2dibm/npcbucYVyJ6rFSopudvlW9 EG6NDhL6SosqjmyY8vej9KiRRWJhMdhW8WOMhAja6yNT0MSdX1miK7GelIZPgBvuEQDfjblITjCb1h5aZ0HeJSTS0QMTzb6uo8hjXTRNVspuxif4hVjybbEAoisYl gyS+oQqwFgbo/JZWJZRdxoscXA4w4GYECtSKZ1gWjKOgiNHmeWIfKpSh7h74QbpP3lBP0Gt/wpqpbGgYESiNJFr/yQ7wQFe3GAJogtl83nihQfY731TM8U8yzFHg0 Y1riI9yVjQn35yp02GPhivsNKO2tNi0yaFBpojXTUMRW6xyWfKTF5icP02n025POSU5upmknumiNxu8XOndr4cI2G5LkAmINvL0IQcqhrLm3jv3u5XkFPKgcMYyN3 VA7Fxg6NA6WvjTB3j7sKjTV1O5hCp4OlUCIzjilpcgcvYYjmF8cOdMr0VRMX7phgaoaSioqwssKGar0Z8j/UAv3WZEK8anzp2I1wdMGMnd3Vzdr+jKUqz/6AaOFDf cNEb7dGcgQniEyWhxjJCvrm7Ort/YN71kv2Nw0ZOky0GcM+G0Ly3XEG9ck3MeckwFskRyCCB11AdLnwbdHz7I2DLuKCx14yZHAZHjNUdsdRMrrIyXSmOk+d3nm9kicQuzbU2FFFa0fAht9LSoLQYvLXOdkyECNt2EpvmqwouWlSLWA/9qmFj0lLtVSbXQWDpggXdEKnFCrl4yoWv6hdIovaHeQHFA1WiSqJIo4O4RrXnx3QnXNhnJj2LQZ kg0iFqeKjbUaVWdka1OVfYBHlFLtxlNEOwap4lRLg4YDEs3fuLE8ALk+po5xmcnV3dYqjdybKViV5CI8d3SaWGXmqrUWoY4yxRxWRzuNYdrtABiwy0G407IbusdAl FAae0NXHEj6lo2LqLHRefGbWXnzmCVlhLGhaFPlAsVJzp1jBJSxuZNTgxzvj8haQ3NsbtEbN2c5wO3ptBG7mEMOwpeUoFuh0ECNkSi2q1pGX4Q6WQ/oDA2RDMdZvP JBgWdonDrQTGWMkfI+ZVm2GhhbyOTX9E/D/GamVElUiL9gxCK8G5kSRSyKsXVCwHUMoAEpmp3hbVqWez/WQCE5lasXZiV88k0anGQYbetPfMZ1rXZEvhC7ZRtQ8YF FnCklcB0yAeUNwk1P62eyPKm9vW8EAFqgmcaMAl6dvKn8QYWVAS8tgY+CZWgsdjZg2wc3IvCeCxEJliae8keXkrP+HAuPVYZC5Nd4By1ZrVDu6T9kWobNzla0W5kd UlDVL5JTZaNCqJiGL/y6AupojUTFaLqkITQL1EMrLFZnV02M5JpIqo6OF2KHySFWi6SLMoMuB8oYAPeEFSclsWrW3XgDZW7FM9Gmm7UQLsLV+LpN00XDpqWkKAHCM s1QVPL5xh0vXBC/5UQMoyGHqmYUFcDUbtRgGj/d0Rrc7AnBHMhCFZ3bBETxpMGCFLCbWAXo3kEFkZNC4JQNElJYWrP0y83qw7Du0K1bCUP+wqzsXbAJKpKTXCWumk KGHlcbdjEip9CszwWuicih7nyAW+Rmr8L6bwHpcncPi/3EMwrvEMlba7yKnk3flsmR/Ha9M7QDXqVPLeH5nyeL02EUNFUh4ohDXlh4IxU2AEHqtDOMgWjzM5OBwrYgBOtEdgwLwnWzRh2aZxwBylIG0sUA1/0neQD37HS0XT0UK2S8+/0k3xMJCRMQ4uKURlk1bMH09lzDsaUs+B/p9BNoXnrP5gYq023MM0NPpshxYzlMC4QyFt4DUjj8 yJDIIvxS/dAGowG4dND9M6LoO6BEQ9S44iwDd0596zofob9jBM1rteOYOylrYtBKm60DinvgQr0gPoBtAoKuiRgFAeYPZvzLzIn31+W/EM2+Pr4BhNdjXpcg28gci Fpk8Grh55cZKCAzby67JyBF9Cx/5cww4uNmyayt+eAm569KoilGZ4qm3oo6xPaxc1TFe96JBNeeHfFMGq4WARfuMJPSXhDFBq8PM1en3eVvqf0OwABdub7kD2Fr6o NBNiG3PvcdLN6R/0IBhbyOG7a8B4IWGxie/xwHUCSn8JOrXtsQpWBea4ZvNbSZlcBu+8MG4GMRpv8L/Laf3KIFVE7fxe70beTiJHx29XqB2kvlW+14bU6XUGrialj Y3WopaUzXh4eX1+2FB/yYmsghAyVAC9a7R6yxjavmFq7MmJbu/24gg3xCjg1p/pxvzuiftShpbqaHOANTuN1Ojm+vYQ6hETX5eEOwFukmw7YaB2/Tail3IGjuA6HK ENjWdTnSQ92E48MB+hDVKFfgKchWJ+SBoWkuow8iRelHFundD38avRUSWq2l4c1QQDmaZDpRoPdKMZVrqiJKBTtQm4WDSoJfoYm1ukRmoEJV/gcIAZDB/83iAVf+7 6IMCc3Nc7ZpQxer1k8yFMkrsEZRX1rHZ QA/bRNn2t+LgRqNpVBCoCFQEbgXDAVo9g1OPhIwB7OPxK1hqOFYFqfmNtmarXjhFA1/C3QMCWt9DroSJQEagIRBCoyRWBisCmESgK2D5RTakIVAQqAhWBikBFYLcIBGbYu1WoSq8IVAQqAushUEtXBA4TgRqwD7Nda60qAhWBikBF4MAQqAH7wBq0VqciUBEYNwJVu4pAXwRqwO6LXC1XEagI VAQqAhWBLSJQA/YWwa6iKgIVgYrAuBGo2o0Zgf8PAAD//8/bjS0AAAAGSURBVAMAPVeOjJzeCekAAAAASUVORK5CYII=" />
Comparing Nigel™ AI Advisor and Traditional PMIC Testing Methods


A Paradigm Shift in Test Automation

Nigel™ is currently available on a subscription basis, with expanded testing features and UI improvements planned. "It's still in its early stages, but it's expected to evolve rapidly," said Oh Yeon-ju, Vice President. "In the long term, we expect it to evolve toward AI directly generating and executing test scenarios."

The introduction of Nigel™, which can be utilized in various test environments such as PMIC, EMI/EMC, high-speed interface, power module, and communication module, is a signal that test automation has entered an era of AI collaboration beyond simple script execution.


#NI

AI와 함께 진화하는 PMIC 검증 – 빠르게 변화하는 로드의 측정을 Nigel™ AI Advisor와 함께
2025-08-26 10:30~12:00
NI / 오연주 부장