ZERVAS PANAGIOTIS
ASSISTANT PROFESSOR (Tenure track)
iVBORw0KGgoAAAANSUhEUgAAAMgAAADICAMAAACahl6sAAADAFBMVEX99eH459P+9tr7+vYgISAtMCwlJiT77dn55s328O4qLCd6Zz4sLjNvVzhpVDUyNSf8+/lEQS52Xz379vPf5N9hVjk4Oyz58/BJQy/9+Pb++N5aTTE8PjFqWjr47dYjKCv++ON1dEt0bUccHRzb5dqcfUZmbEn87dViVTQ1Ni7s6eYwMjdFRTY2ODRLRzJoZUdbVDSefE4wMzIqMjc/QzVhTjRxaEhjYkFcVj1mVjtUTjo+QC756NZPUDhuZkJ1ZUKKc0eigUZeXUBTSi0pKSxxWj18bUuCaUFqXEEvNjr88dptbUiQb0VRSTVaYEdkWz01ODt6YTn98t79+/J0Wzb76NFvYD37+O1ZUTsoKzFfWztYWUVLSzlTTzKFcktWWkBUVTiXekpqbk5TVEBhaUghIyVaZkoaFhc4OCYvMSJ7YEFhb1BsdU744c1oa0NWaUH67edhY0qFb0Xy7ekhGR46Pj5NRypEPCgeJiBmcUcnODlxbk8+OSv39OsuPD378Oukd0X79ueKbET89NcqKSLm5uVjXUdjaUE+NyE+PihSXkdNPiXt6dyBY0F0elB7fU5cakN7aEYlJRtbaVCmfkuReERMTTB9bURTYz4jMjNcZEA5MB1+dUlTQysnHhZ5WTwmMioxLCnz5MqPeE2dc0I0PzgiLCX38uN9dVFmZlAsODFjSyxUZEpwXkaWckhESjJpTy5iV0Le49BbRyc7RUMZDgylhk59gFk2RS7y7uOFaUxxc1fw38UgFhFabUh8mX9bXjpbRjJGQyZwVTAwKRqNhVtKUT9CSDxNWz70792Hek+CYTZidFtnYzrk5tiNaD5wlnz358bs5tJogGdtjHQzPSp5kHVETElvdEXx5cF3hWlHNh4NCQb+9NDa0aubhFASFhFte1lmPSZ+VTEUHxfk3sHk2rLTyaGOjWqWbTv68Mrs4LmuqYGIWj+En4lMW0iJZDediVxAUz2dlmm8tIedmnk4SzbLwJFySjLExq6qoHJYNiG+u5rS2MGUpo+ssJk7xICwAABRMElEQVR42oSXTUgjVwDH00gPtlANQZPddSXx0K5LmORgTTYhERS2paJSA06IkYTmEi/LpgE96FAGt1ZpaGkP8bD2spfEQxG9hCE9bGVnl4SmsIEeLBjoIR8kXiSKGNzd/t+bZyarbvt78zJvJil9v/2/LzXx/+HPb+9SJJDMxpNSfHc3Pv3Fe/0rK0+e9Pf/9qR4OHBvZmZkxrMpy3Lj8KRaPTk+P60cHzYa8o/jHqvVPmq3Wkcdo2ArXX19thvnvV6hWzB0d3d36Lsv00HRd1wLvlbvSouhyWbjWcI1CsrtrkJMEZHwJpucLpRKT957AkqVk9S92/fvpzZzRw1FRJarjcPjQ2iYPX6/3+4PhfzwUJiM/gOXV3GvwBtinehGCz3zQEH3VBG8U+tlEaCKUBUJlyShxuOoElNB+ZYooMZiVARkTab3SsVy6bf92n6x0vDYejypVG5TbjSqUKimU6l0Wq7KP+bzftvYmM3hmEvMhRyjwSCuUCI8G838/fpMEryGmKHDcNmD2UCGQdpqAVdCogUiFEkpLe62UrkrwSEmCEJSSorZQiGb/ULTX6pUyvV6/WX9vDk8NjUwkEqliIicRmPYak6nzeMev80GkYVQKERERoMhdygUDIZnJyejW3+cnEleQej2xtRM1Nbb3b0IiXq82wQiCg+TD5MAd9JAKgzkIAD+QkT7ycoKgqjU9+vl4mnj/q2x4TQiMKcQQhpjadzut48vjT94anvq99vm5kIEX5CIgHAwHJyMRicz1TOJFzBVaA/1KB3gGpFWFG1fXzuFqEiSVAK1EUURTYnBPHhezCZN2UKp/+CgVi9WiuVyvXjczOVtNuQhp8eRhXlp3O5w+EdH/XCx2+0QsTlCc+6Qw4FBFQ6FmMhWZiu69XrXK0iY9egU7Spo76tqQi3aPS9peJWiSU4np7OoSVwkE/GhCBVCEgUvIAGIiMbUXyrVagcvy8Ui0qhUmvJm3pY3m81p84OBcSxPTx2hBLqNHIjOU4fjqR+9d8Ih7A6Hg7MgPDsbnJwMBzJvdiVJJCboGAFd6ka5MrJYAW1f6VviXoaGOqCKmqRG1ECjBS/yDLRMvCl7EyLlGg0EcRwenzblXH4sbwbfjS9ZR0OJvT1dgjPq1nWYFYAsVUSEjCmnk4qEw9GoG1JumMR5/E+gokdhdCul490iTOOqiAYCsMEdGiIqCpRMKCKrwAQKWu1KufyyVq8jkeLp6WnjSM7nbQ/MP5jH7aPWYEIHXLr1yONIZF3HcQl3KAhmg2E3t729HQg8D4PZyegkXkaD4cyZSVNIYqLwAo+rE06g40Y3cblxmW5UfIUb0KvvvYAHRINWUTHRmDQUk4mqtD7wjC2whixqtXq5XK4QkVwun88/GDcvfWwPBt3b65RIpAsiLkhtc4lEIoA4Ahw0IEJNgogDmUzOrlbPCkmTV5J4XpJoZ1qpkA6y0nEDVwccaLmqBw1FRDM9Pa2Z1rQQFTGaAZFRWYEIZka5XIQF4WhjM5//zo59GwMIHhFCF4BJL3C5XEjIaOEgoYiAQADpoGKwrVbPX5WyYrIQx/LlBWTGeN9G7TLKNS5KHvgviQMTEWkBbZHgQ7G5efPmyspBrXgMTo+bzebp6bHs8eT92LcxETguMNRLHebnuy6AydCQzmLhLJZA4AWz2YYeVLiAm5tYTZ+cFQoFHBVEb5sI6Z1eFaFxsOsqXqIBWCBqJOrQUoEG0B4c7FeaAMePo6PmYTPnwa4XwmY367YELEO9g13gEUwu7n2uIQtEGC+AxTIELBhpOm7C6fRlTs7PXhWw+tNxxesvAsGjagIVJZPLLnoC+6UGHkppQXuufOJSPW4e1MqnR00kAhM5J+cGPHnbXAJz2slZAkN9isg8BNB4/4MP5rvo6MJsIcn09Q0pwBkJuXVun8Ph862mD8+KpX6cRtEZwdChRyy4+Av0sFAMmJCe0WrwgIpoL0dC0TAHSDBWtFh4K80GPI6bR5sffpjPe2xjcwsc1ltXHxgkdNE8Bt8ndA1iovQB3GgLEBMqEp51IhPfzvBS9c3ZWSkbF7F6GfQGvRKIKnIZPS1MRYWKXAmEWbAW9TDVyNAqH+cazWYjtzmw6bFN+RcWQsRjGUBEMVGBBxNBUHhCm0JSCVg4p2PH59y5NbWUPsGkLyS9fCcR4f9b5GoiKF6IaFe0Wi06eqGAG4PNdo2ig9/UtIjkKJc7kjcHzONkA1zY24PI4nIkQlx6YdMb6WqjlySAl4MXan14ImauIZfL4vRhlozZpjypk/MiWb4EdNurx4EoKTEPA+v1u3wMBvKlAYcoDRZVJgKIBvMhGqjsEYlgZOFwUjmUNzZTAx5r5qvoqG+OW+CMEAGIhbAeYVAhFgKCUfzeH+zFAzXB3LEEJpwO39Svn3++BJOCKSl9cwOB8ALAYUIgQ43BBhMdWO0e7SLalggkWCLEiKi0RGDSj8MJEjnMfZT35KfsdnKeTRh1ENGBRR0xcemIyHpk/a+W0DLpt4sILnfNP5rvWo7QWHqHXOTnnHNnZ6fnlm1JxkIsikJnJzYUaAARHkAPVBlcwIubItLZiR/wlxKhcSgitCmSihbzwAjcrxWb8sYMtnOrFQeNcMjp5jh4GIEOuSxCZ52wh0pZBmTdwnuYzj97RBY1qFFokE6k4rD5ranqm5LIfyPE0CllkqBxWQVQB9UDIvC4koipZUMRUVgiVKReP5VzuU3PHWzmW1EcAMnpAwqLuNbA4qLRuEcxUjcC7hwBn7rI/LP5nx9hwGGy9JL5A5O1xYmdnZDDumTNnJyRLT4mCd18jE6QFvp2IAMHUiESMwDhyhwBxAS3pKrCFuHagXa/eHwk5zbujNlGobC9TfsJEWhQj+8XxtqYoDgpc3Nocotrjx8/m4/0ku0fuWB3JKNOF3CSzSiayVTP/+S9sbuCNyapHlddgIHSCQTD1UQYdGThdP8QHiwRiGhrtdr+afMotzFz59acL4EdW+da1xkXdUb8c3///cLCL2O3eu703KH0XLADpqamenrwN5bPiRXucVdkOUI2TSRiwZ4Stiy7jJxxXRfMZL76+80rCYnwsZjXi+4qnWUipOCikPeKBxLh+WsTYYEQE9KGibKX4GfYRY42NmZGBobtq6s4NnGuSGRtbW/C57DdAp/euT3Tzufg11+xJlFuT93buef73bhM6L3YYoZeBJ5jp8cRMrydiH6Vqb7ZvSuQhQubCRNBAaoEQUmDmqgi1EQD1E0R7Wlq81CZJHhewdB6WWl8+aEs5+5bR30B1+PldYyUtT2b0s97t2dGRn66//Vnn21s/NRiZGR4eGRkxHMh1jNhXCTTv6+rbxAThWwylucgHHQH3PjjBX/Lx3lJEGLUgWAQlFtrPH0DqfbBJYB2kbd2d2YB/uXTXEKbiKIwLAVRcSEBrcVH0ULwQa0JxKKWxBcOZVCLLmrRJFrdxJ1WiBulhiokmI1gdZG4ihBdxKKLirpSGouBCgoiKjUrH6iboCIWX985c51JrPjfmXEcN/P5n3PvuWdydI/ItluZfV99zO8uT029i8RiLYncWEYyI7kgYrXpG8+9NDAQ3+wojgYsy7pkaFBvr7izYTEkJ1ra2+GYtypEGblEUJg2GGzsd9398oM+AW0bh4PL33LiDHkggAtIk4A0kBTrYPaAYs8Sjucf2YDQ87m6tq+lZWd6LJ3OpZMrrXhFX3uA9y9sLqAd3Mm9Ph1QmrlzFaZU2rBuY4eCdOk6LyQhrmxTwJCO0YFrvx5hyV4FmY5yXEk8ec+lRBlyC8ciPC6E4qSMIytWTL6iJVotl2lc9ck8m0PJlecrBZUiDA8P96PhYUD4K1dhuSQ6P1ecwZK+nUxyFMTNzU+pzNasGX/2QFhwZf+BMIq++LGX/e9eiah/ejIoJC4OjvCMzpuT7AbEyxTN9KMyeCKWrHj/4XNt6lM5n79lrU92+HKAvLzcGy8XqtX+KqdRECkLIAYFFqGxLKKsVILk/olMhsp+iQmvB+NLmIqj5PtBTPEd+0XVJQmsYfMPZ3hiQMwDMACBYsgGRBHUErkoBkqlBGTWrBUrZr+aom1SyVeurg0Q5+n02MvL2+MFCKoif7/fHwxyyOkwFRxVKk7sxeMW6uy50Zc8kU5kQu1k+hpExqN22W1Js+Ji+N1NmlKAODJTcD3IoIsAAydavVpAxBHbc8RVqgHkLbvbKdrUbYH1G3NjJ3O5e6U40VT1qwCpU79BGYZDQIysO5ZV6l4Qo4JJYAkSllVrQuwcqSI7wqKRW98emgIF7f0zQbk5wn2DF4rhgtj2HiQQXBplQJh7P3+cqpXLkVjfznTuRPrl9kq5Vq2Ojo5u2eLnMMIRRalqgJEuFRNdwsHoLPUEYrS+aE8oxyqRFsQn26lifOGRQ9+zHgcgjXm98N8gZ83LNi0SHHdxXNQAYgMy+fzrp6+fmbMi+2IdElm5dfFqrVbrB+OPgluCSMMLCjj6BUQ0sBkOdCd+xyotXbCAwiAz70hzs8xbq86c0XqYKbmLaiEa3f/lSYoWt9bynGhw798kDsZqA3FWckTk7MlNkEEiMhRF7pi0DAjJvi/GQoAf987XRMELysDVkFSDVb+AcMChJEYmvDZ1b1gQuNgCyBGZgR+E1pDzJD0gwHSd7KAtXHzIzJU6laKwB4ND8mJhoyMwQKEgx+efPTtDC0JQ1BMxxOMwkOLJEA0UAclPxEhVqQ+7K7VadRTBIBJn3OgSDL/hgMRFAebOeUgC21q62GqxuK+SPG8+oqu8OMJ26/C7H0WEG2aHlXIcGVQQiTSlcMUXnPk4oh0TzxEFUTYEAv/GtUlaWp8+T5Vpm9xPo3PrrAIJUp0OEmRo6l93QbigQrwgrjAL926g+UJrheKX/FhCk4j5FzEHA+LruPuNDxiAyABiMDU42JgnYNRxYAhDw8pweCBKhhtO2Dkgbz5+ruUDgVg6R4JcLhUUA3lJ4q/TlX6/YLgsDBVJgiULKIRH2qlPyBKnnMcOyABJ+A7f/fUEkGJKJRjAiOaIJyYtkOFADohB8QSIF102McfMBsiHrx/FkGRuDJJ1VwkspRi9MBqcxqEomiUeS8EJrjvEVm8PJX04CkCI/iRbRtMmQkRXlCRJFR2QU0oChwQWJPUckHAqB8NgNNUNlbghpeQirtpk5HvhVD6wD0Moec/1lg0IauCoeiTDZImL4noygCUlLOkTEEot7eglaEYICJULTw+/+PZQQIoC0aA5RwXEABggQOZ7IB6K4WA4tb0+wZHJD68+TSQBSZDqi61yTWNKONCWKqMxtPRKyhsOOczcpbEV2HlxBJBQSDrEzdJv0RYR7RZfdD8fgYTECy080TzhqiQoq8H1yHAQWm5umBO5NFQuNs/UEbK9EpiIpQUkuSGOH5LgJkvElOnr+7A64q+fhFkXBwCJdO/r62BNpNBqp6PdDsCRIwlxhePBrmtfbmaXqSfFwUY5MQaMomQVgxMB4qKYiweiJENDDsjjz5dI9UwukT6xrbdSBUR1QUDUkjqMLSbhUV2SIClXKB4j3T0bd/oyXSPj49ERTY9QQpaVLm2nHjj2RRrb1EfFo9NANFHQbbUFGk0SQIZcDo4GT1gc4WhtbSXXAXlTmwgkL2Zy7NMDVoEEMct5UNZEY0mwvyoUnKf918UOb1Uk2SuieD5vsSj2xCDx4UY0RFDx+kskWZrHx4EK73r348kTQIoPb7vvf9SRkylHFQWRJoYERyabhhgNgoFDQJoAGQKElT2/cl+SVlVHOMZi+McQCpLRIBy4Agfy61NgMMgIEC3oUR7F81ZbpJvSs8XHF59xQEDRduS8ZqwBZD/Z/pAqPJsVECMgGFznuA8MisLMmJwERYqs6SgKYhuQD1ORQOD+WIbmzfpOqsUtJrKCF1RBXFHpQwZUqD/o1vMSVZiRF1mdkZ4bG1sykLB/1y9EMgPLOm9AnhDYfDbBAQ4lMFIWpUKAZDX1AcEQOJDasgcCW4dxRCpJTpql/FYjmR7r8o2E11uAOBiGgky5EHRBRgHhTkGQg6H7EvmFBMKSzlJ3X0uG/xa6QjJrrQJkieIAcuDur9fU4zNSe10Aj+Q4oeWG2iwsyeKJOIIURbe8EMh78yccyIBMCshE4H46IVEtIBpZ8v4ku8HxSLj3GwxvnwiGqOKQWJ3d62O+RKZdtiVSoXCumjlvjazz4cNkeyt+FAH5n2ZxZsUSUGZM2nhiHBEMvdqCYqsndSATyXR4JBzd2aOriOcIBoAUdEj8WgqT9saMAZHuc9vaLMsDsUo31nekc+S5fsySsosakjQJAbL/yzc4nmRvT3/5weNHSXZPWKIgzFqtTa1DKhdHDWHYgLCvWtS04vHjD+W2ffcv3qe3uT4SrwGiuuAKEpVZ5Mlws821UFsnS0cPiiwXVyyQ2GHd2Hkil2bC0kR/qh8hSHv57HvgxXfm30fFU9lTxz0EBiFFvVU/jVHIq2a02pO27XHYwmGGChCbHHn8qtwbSAZiBw9sXdtGBd/IgSEeiHLghsSTQEQ6OzvXdvP7mgC/F5poExQLbyyyhGYwrSHcgAIMwqzLB0c0fPfnj2wxe5vj+P8FhgHh3TlcSUwxoDDCkt+EnG1MW1UYx8EvNDbtYiOLCWKE6JhGXU0sUMfoXFPaSCfBdMuCMjf1w2yARIxdFviw4CtimVUHidoQCyYkFYZgRJHEMcRF0BFmfEEiRgni5tT5gm9j6u957m3LUOP/3t5WmMn58X+ec557zrm9ooiacWky1+utObpn26NNvd2f0+maIAeh4ETK8ezVB4Wjnw5XAsqz833mfWtynbXeSERInO9jioKoJdzbyLyjrv7oHISxwHjnbZ+uDAqITtbpea2cXFLtzzCYoUXbOVMHiVHEcSvnapCLmC6dqPLWVh1lVb24t5sWpy0BghEkrat7enr6+4NUI35msvI3elGEhYZIJMInaGqKCwBBdFyu+P63n2e9h1zXGyskIPfceQfT2SdOPEkC/I9g4ESAXKiihzgAwhcobpUkyQFk9quf3q911uyprc3tG0mDqA96K5We1AIDjpYWfyzs8bnzIscQFTOT3YYg2VSMIaQ/8xB5l3F7s/+S5mvWgcKISOUoIDjy1+/nB0E58a9N51irrBzRFTk52myk9hSl/cgRkFsBkQGxBhCnu3h3t8FBgO1Ni+bv7WcAhCIYbPFHww6f3RWfE4bn335ban+DA09yA8UVmijFAZd3//PPN+9nPU4XTMkUtQRHAAHjDcpbdiNSH1JYcaYRTqTeOC4VZeXc+i4HJxgYAAd+pJWTcyWTQfxsZvZMeU0J+xyqAjFSBMnsYnd/sNtUMNiPBGMaO8JdNptrrG0OENZ21BCJLBYfvIRYbnlxYQUkMUja+DWWNANyn5JcdxMs3CWeH3zyyUFA1giwS422y0ULXwPk3VtpKAcs/Pl5K8IP48hBgJRdAchpA6TWGeir4KZKvDAmRaXyICFaWlpAMaPKH+2y2V1j8TkkJFBE8nax7ONmEhsSZ6DYjC5PYGwOkObmfZcDAsl9+3Rm6J37ZVvt4OADV9FY84CB1wn5+C/KEgwAOI0jnSs5lIuAZN1elnN7keWzz86w8+RYbVVV38gEHD/QKxnTO6S01er3+1tAMKIqGsaQ5Fg83ta2f27/3FxbPC/Xba76uF8pzfPmpSyhV3PFsaSZdOeeN7VSys37O2Q7ICf4s6vg0dc/KK5CXAAxlMFQN0gbkf687AoBOf1zYY2THjRXHLmxv7vRb2XRw7ezTxZxPLEYJAICDSAODHGNjY3F21B8zOV2u/tUbher0S5nbqBc0kQGGbf38bffflzmtAkuXZLTeuumZz76fXBwkBb+p7T9HIaypLnaZlP6YRWHgNwKyMxSr5e9isQWIHtb/KHxgY2uvLGxPNFGu88RDkejLciPIT4FUZKxMXfA5/MBEY6F+3zuwCuvuHPdVe+XFxZSCUOSK1nSSg1MiXLxww/rbgnqyM3P/Hkejv8iMRDUkQxIigVl/iv7ijJA6LYUZAez8RPeWqeA9E780B0NDQwNDekfnHlHYidpt4VC1VF/FD8AsQ/AoSQulx3ZfAqjCuAPxUp5IXshKV4CMp+xb/N6qbUefvrpF68RQzZ/+KEEl4aN0fC1FHqgDMh/qKysLMcEKROQ0199zcjcUVsLyMTu0EASDHolWZlWEpcdFECqq7sc0vOisTwuAiQw+W633e0OKAkro+9jiZAUFm6qiTzOvSG6/JoXH3764nWQULW8fvwZ8l0t0RZfwIHMH14AUnQBQVEK5AoFIUmuMEG4ZWcUKJ+c2O3Aj7h2riJQlMTmIOfhAARHiDuCbkxYbL78/D5fwM1HN87gSD4glZWFBYWVlZUle1rZSKCl/LqLL35YSGR65ccnsERJtNUppVnWuJJVtEaaGWkQzRIDZPGnGjgiHeXDkx6Jq7a2Y9jRDAYcBojV3+ivrq4Ohx32gaRixOOQ0G63PT8/wOy1SyNNYktAcKSyqenubR37sERA2Of14osvrgPkuuPvfP+BxFaGwDjXKANCGzm56LkaJMeQjOz8/LPF5Rr8iHjLJyZ3wgFJPB5nO8MN7Gmg0UPJAVtYQUiSkD2ZTIoncRBVQ/E8t0Ei+ZIvjmCIqmkTlqxTEFZLdJGUibt3nnhZQMSSE5fKRQ7TEi56rHGE9qskqnghIVFDZP2HLBEOy+iZqlo4vEeHJzcODY2Ph3aSvvRBu8gElBwYGK/2b93q90uijJNDQ4zk271tc6hNFR/LDfRJz2xnZ0E5QwkUshO9cltHq+5L1aU4KR+vf/D499+/99bvV101yHEiJfpjXoqTRvqX0IKDthsgOhoqiYIISeJMOWVs5Jiz94WNQwOh6lhshAFN/spugn9AQEL+oAzsGZB4G+Ph84CQ9xJnXqAH7IRZhgM1lTgjrbLKsP6ll66/SeZRH3z144+/f+87BaH1CnGBMgAG6yAgq0huzYAUcaSkLl1kWelte5xK1ltQmEzaHI2NMdRHsKAkGIAsRIP9ilIdGk8mqavi+7VCmYu7AoGqXK/GWBIOQOi0FANHCopL9tzQSp5c89KDLx0XkJdeAuWZ734ffAQCITl50gBYPD94/vz5VSAnFBWtdkSlIKso3pWLgBTNT7Q9HokoiN1h3R0LMzDQE5kgSSGZCvZTBgd1uJR+i8ASjjYvBW+fO0/KxiQ7VkxHCpkcEhKypHTLDa0M62wg0P2oJMvx49/LPQllCjrJsbh4fvH8+d9FoGQMgRQYAVmLoiZwVZHyKZLRZe/jkWNzeb0V9hD9U8zhUw4JrCT68suB36aCVJOQ+KvHx+12I9tRJK8qsImJ6zxnbtVOVbnHU1jB2vsLLHfLPRZbuY/sUxDue9cDs+6m9cffo/tFiwiEeQhW/jqzvLz850raE4k5DtORHReCAGFeORgODZLs24tWAvuPtbXl9e7e6aBKlBsOCvW2uJHpaZAbUyDI7cpTUZOw1ckpNRYVL7UZGFBUyFqvzKgQW/fcya6Om+CQXWlCs+66LxREKIQBCB7gGkY8pGWQUFFCYsBk7dixo4izLNVbZaQk7zLCGyA5OfNfe/cDsnvSA0jUYU8OzXHPNJfndttsNmLrtwVAlKSlOmSzMdTn211upAU8IqQ81O6ogqjSVWsuAlLFUzLX6YI1G6CoG7nrbd1CaGHE/PzvKyAs//T11zy4VVB3d93wshAqQYoDEPyQA10Aki2XdyGBQ1WWnZM488qct21o96S1Oux3jCeHpGtlFY62hR2a7ApCcLVEu0Kg+Hza1RoB6IYCKQQhZXAoCZUjIPe8cxORxf4n2eV5GZsH7hr+cwUjVn7WJ+mGRYcOFXxy4EA7W54zICcRKYQjhrKBob0g6MFpEOCIwVKfSCwNR/LmhnZ3N1qr/dUDQ+cMkECfx+MIMbAsTJ0FBAFSDQnViNiC5E3qY0coRMlfQTwBgkyQWHmVs2PLPezbOi47zvc3s2endNumYR5pVCeGD7UXHDp0aHgCkk/a29u/PvP7Ij3ZCXnA8CSnKCvFYYIUpTBECqISR+qzF5edbYBMbKXIHR86NwfJ83N5fWz78YXGKX4B6VeQIEOJA4VscACE4FCQkMPa2WlwMJXa0gKJ5EipgtzzDvvyZEOXNyKPnL2pNkBRAIepgvb2gglATqqAUEcMEAscakkOylaVQUKPJQAiAQIlsdI0R2hxd+gXkHNDyXNz8Y2emMdnE45VIC3cXImEL9QVRnKpFlkBER/gUJBGQAr1CRR95Gc7GyTjDEFV5U2VlXXtdZXUlZ/AkQYBazgNgq6QCyAWi2WHxZKtlmhymKJEUQiznpf73UTiq+W8IQPEHxo4NzRAiru4p9LAgmNq+rBOXQPiDyOrld/wqy5uUrpEC8LhF5BJRVGQRkCwZM8W2el08/Y4HHTp7vLKhgZACkTthw4RUWDwfkhA5hcTJxM0P9ugGB1d1NCygIF2lKEUSFGZoXT5ePuO0URipXeorROQlrML4yhEFhA7aHwKnT11tTkFLze8VmvMWk0/PACJKISmphpVWydxgneqAAUpL9mmj8exWX4Mjj4ZM3laqK7uQHt7LwwFde3KoyCFw2eWFhOjNId2JtAsXXQWfogjlrUgJke29Mza/RZljyY+m18WkL2Hg2cXpvSulj81zawGghOQZw0Q5hn9MiUBCZ6I4MW1KX9LelkUjbQ0AtIJiDhys8iFfEQrHDUC0lTQPtzeXlfHCQgSkOWVrzBhVEBOijWQpB0BRhtvQWqPYO2Ai0GmqIwUqrckEroAB8jew9Nnp6lGWP6Pfvvtt2KGGtJz9S2A6LbGEQGxIiWx27GD6POz9ZGVODCUY2QEYAOkdsvNu3bdvH07dT53aDGrkDQcqKtranqzPa1DZD4kgMwriMWCHbNgfDWf6X5NEIFQEBJe/5P8kbeixGhiho0cf1gbP2eNMzhtllXTCJLphQUBOSiO6NpOIxSktUmi8UeCMGnEvsc0CCiyvVa6LW/HzXBcdhkcA6SdFbiGxx47cKAOjjfb60wOKFIgi4AkZoAQjPklkt0UHAqSEQTwiT+I+Jud+WwGSzrZhcLqOdtmQBGO4LdoYQEOFhT3IpmKJ2JEikJxxRWH4AhqgawaQfKvYoBsqo1sBwRHklSgdkeMxKlsgINsB+GTTyTdpcBECjKLZk7P8HAnYtgEhCbqxTCEc7UASb2z2nN69pulyUYFQYdP9Z8SjhYwpkwQZn/JoMNbMySNwpLhAAMbDRA/hvAvCC0FMXKEQprqGo7ChobHAIEDEFRQoCB8Gl7+eekr1TxfAHDmDGP/8lpHsv9LiYQBMj+BI6ymv3YLCwinTkFCaC0gDaxnIVEQ3SlLEztlTVqNoWAWDkD4P8Dwq9Igzog8cnVHqcsuIOEKDS0BSXEoCoMKYmhfWVKtUL4w/lOFpUGMHJHTvCAGydUgFkBmlyas3ZAAgienTvVMT59VjqnpnoMHIZFSK0iyQ6Jrh51S4CoKed6PFEQ5qA9ifmGUZK/pAKT00UfdPtsAIOy0K2+o1NCi5zVBKnmw+bGGhoZPJvgKA4QTP1G2DItWOyIIGQxEH6CDvDqV2JFgvnFm6YfqrYCwQwCJJWeJKgSTgrwGiJIAMkKd24knYkqj9Ff8ArVIaCkHEpAYIFW1l91w5z2PPhqQuSRbuAKQyqY61FRQVwfEgU8OVFY28BzqY4+VNBTwFQYivgkAjwrqECAXxJYJY4IgAVMlLIBYeKbHKiAs3qZABOPb6R7lEBD9qwdJAUCQvzG95TyYUorDquM8C77FgPC0zM13AOKg//XEACmvvHvDvRsIJSE5gBPiSAM0jzUUFsrcXmFxcXlJCalEDAKSsMiLmlATXVlWgaQ4cMRiOT1D/9vZyN5rBTnYA4doWu0ABGVA2GMWDjNHISRwAKIQwa1GhsBhgkixVSMgW+54BRAb44hHQEqeO3r0uZJ7N2wAQVq7YcO9JRs28Ny82MLT/yVVNVU1NduO8q+eyhIMXvU4sgZkxxqQIkgAOZMBIdvPnhIMOFTKEVwNoiQCgpitR1uDBofVb4BAIsVWqZfnae4EpM/hc8QU5H1WLPfcdZRmkxg0HW1D/PRozTaWauQbDJx7RKBkkh1lOi0AkP7YrOLrEwwlCQGZJLZ0p5ZaIuoBwQQ5SO2LpMEjKBymDGbeLsWBtFL0i3ADkFhMe60aL8/1bL/j0fx8R4zdgrDs3Ojs4JklUJ5THb1LuEpZxqzlg9PJhw4vk9FbaoXFBEm1OTMWCgujSzblu6i+PkG1PzMzw/NigLCRCRAhUSkIbzhiLIYiMUQ96XJEGfjSGdIiQ4xymIrFdLdQJMIDWa9sctscFbtHHDsrYvm1PLDZcQSUlNhwziODImDA6IjwUWDRmmRXBlMWuegPNbISYM2Ozs7MS7e197BQpCXL7ZjDJ0CwRDgILRUFfDgqbkCihqwBiSG2azKvTOn7aJ/PF2a/tsexu3AjK8KAHAEFdaAbbjgiV16Kwe+Nh+qOIAGhjalxRK3IoMgBGqGFZRgiVcE3fwgIg8jBngwIr1OAIL1n7wckJdYTQ+GRrd1CcXh6rSEeK7fxGCIgtYwjfZ5wGCNJq0I8OnLsiIr2p54GRGmOVrYXqVifz0qYqk+BCEe9Quilno6AX1iogQGhbGRLYONeQIyYQmZgkSoYQ9WoOYIfKXX99ltXtCUVWGAoSKcJghREZu+244jRP3Dj5XESOMeOvI70WXJTfAkDJKJjTBi3os2tm1Mgo7xoLiRaKCpJOuBwrL6+flQN+QaQ0792+6lgBWRVbAkIEUay4wYcUfKi23SkywYIgmNaQQw7MiTFgDgVJCChFfX7R5hayY3Q1g9fF0lTjT+/NPyyjtotWHKkVUmalQMQMHjVJ1IgSB3JCLv0HwHyzezs6aUfGhsPHwYEGzSYOODgs2w/6wlOo6iAMKnqtpEhXZIlUX/LNIYAkg6rak+nRFY5YmZYllNy+/psAoIlFR7nMf7mCrJZPNncLE+gtjbD09FB5rMrHZD1zcgEqRcKJHnOqYJDE0TfdKih652BBJT5PwDZiyEX+AGIdlr9wempKWMl0ZY8d+7cwG9dqmiUukSHdKQYOz3yphxUKKXOXbtcrP36gJa/QkWxEz/gUAkHDeayDxcgoSvrOLJZHsveZ4IAkZJFpAx8TMgnFb8gQSzCod+IsvTHC1ZCK82B4ACkBwWD0ahMz3ErlWSeZY6pFrsvLCTV5qKvCgCdOS0v9PB84iaG6dJtr+zKZYkRjHB4ZKS3guWffQrxC68PP7xcn8BsXr9OQLRP5nswRK2g8bus+tWCwBQgSA2ZAUkSxPgeEWrOn17o7MYSAciAaEXPS/wId/ns9rFzc3PCwc0FU0NGeJljOlIQNSMQ4FuGSneVIgWhvw6PVLCEdHNr6+u//ML5y+svgbIeQYP0azy2bMEQfvivIHCkrOEFwQwXuqqZUcR3uvBs0k9f/ySPvgkIFnAgjBACqkfKrgXuaWWudOgcGPGxoTFXflh6IofmCYpambvzwJECqaqqcfJNSbtKWYF3BwDx9cX6cvN27ZEx5BdkeIJor7wINGHZrD9qXW+CEFr/phkBUUFCSMm9GE/vTU729h56oXNSQQQFErkqh2p8AOFHm2zd0KXpfKYiwwgQlTVshQQQJdkJR2nt9i175GYkNzfg7kPstfHu4flKAXkdP3hpq19fr0kjXJCtW/chHu0TAbKm/X+Tde4hkVdRHDdQCXssCopgEdPA4EKNErs5O2LFbEuBOSKETD6aZWZ2XBtRhKVV9K+QsYxqUtjE3ezxh6ytZVJSZMo+zIZKgkDo4R/bu6gwlqigoD7fc386Pb667lrZ/j5zzrn33HPPvfO2WUPj2CfGIMml/vwRjLOsP33sKt/MKcpXBOIi3gzyM+sS49BSlcag05+xZ90CCP5yJ8IsQJiepubdXmEgBAgWCXUr94hns6HQ0gU2TQ+x00VKH893GYm0ZRKA9601rmy5Syb+HyMMYIDIFlRZ4NAwBQYuRUH8vbOsAADp39w8A8grQuGXPAsO9CEsl9i5PneBxiD6yajhtrRUAoKEgsghHciRI/eyX40OtRrIUS4VimQjMQ6dHo4dPn2ahu94nDufrmxcuWLuVZB944FUwfE/EDAQxiBBBEH6wQL8R10u98Z7Z3034wosDDY3b8a3RCIW4XwPw8+kH0TIuT+0If04m++onNWrGoNa721HFdSxJWKfDepDqNWOvHeE2EPojEtHT/GDF+mqO9UECFliPp/fyO/kwQGoIEg8CQSOPZCP+MWM4uSmDKPAGgS327e8+XZue2DV3LB5x5n3MIlpl4O9EU0hba/ZbrSaLstRsCUWC1XyvK3s8lCRdxgUWm/0zu7X1+jCGnL1aDTOwdCmchyePohFoARyND+R35lYmFpY2MnnYYFGXwCRrMf2OBwFEOmqPQ78SjOGG6beoSKGIXwjIyw0EQuDhv5nHrzLrZ8A4TdA3v+Q6Y4Z5BxRrhYVOhWNhAoPB/clDu5XoIcqwKCfQxtZoVh3CyDhJu5zG0wu5qP5xccat/b1PtYkDAmSaHoqk8lMAQPOzo6BSOw08p8S86YiwuJtOROPryqkS0Wo3f3mdorY7KJ6wXJ5JNFcB0gkAsj58ZvPAAIHJNiByYPZAwwy3XPa/gTEJarBFgRKrL5b3VAYBRQO8RMbS0uh0C5IWCB5jubnSRLRYn46n2f9IZD8hEA++OADYNZAgUR6F4FShWAB5EVMAIsnxqoXsca3UKjS8iT1MK35mxMjiYBhROJRFmsNdzxDbcdAwEBYhIYH1yjwrFCqW5R2s1ZwMOTd6mg8eOjGIy8fUXgsARKLxcxeoSQX0w0OxomIJmJ5cfFKHhBIJEwTTWcgyaC1NaEYy4bUdcvigUYXL0UegBMuhTGs7EW9yNfXTDm8P5DoSyQS8/ODg1mBpFOp3PgdVKm8yo70CFkiUp/Aa+hZBl7OuTBqmYKgsIYABZswhtn+KNYQSMsuCPc38uyn3nwTiolp0/nzWoxPz8zkcjkQnKYWJoxjYmIiqQ0uRmjBCITRyulrG2vNpd54srk5EAgMDw9TkEkkAoNSNMoVnrw8qVzDHTc/o7ohKQfWcBYRx3UYxEh49VseZyKRAIHEQA4fpGPLGhthkJqaANm9KlCHwLfevDJBLAxMDwzgw4gFeypVIBmAY2fjygYg/JiURxsbi0U/vH21ZSC6l1RXyym8ufhyvD8gpZyAQJ3SRDqdnjm/eQeFdTgM5Gcw7m9j+/M6yp0IkAs1cjADaaGFCLESOvwwvSgCITpUsGazrYtNEeyBklE03fSYQKZRASSXCgwHcsPDawNrAwMD0+7Bk3BIUYYClI4ColTqB0iYwRmmvhMG1ZcAhshkgEhLhuFA9Pec79i8ExJSQI+jzXatrn9V87qMwpQoXZBaLuyB4FxL99JRZOEhEEfiPRJGOUqMECAGch4QieobAiSXgwMQBuQdfkbKDmog+PzzDz4o+gEGnOprpNggwK0WlsIcGWkqnV5YiEYnkAcykc9TWGqnKC0SMHZJaHUAxPMuGjgkhyJ1txxGNZVLgGARhipAgrsgcQMZjC8qRgbW1nhicdTKJJS1KAILZS03kAZE4aEf6YxkB1OZlc+lIlsrfc0yQxjsaDPWQpFKJRwGWpjwZH+IOhA51zNqkRXF+2oHuiSOg+xtXEfeyHKEFk1gfr8gGBngWe6yodGpcilrHEvsexI7GpoNJZpsSk/F44tXCHU4ePEF0tFxvoP6XEDVbFBSoIAYnYnEI4grjAJ9aA/ka8bbv4Shuvcw5kBTJqwxQXQt7Cwg8zF+yYdnGhzJPbYJCggpr+nIc4iUnS+/n7vwxYULX5iDETInCRqBYJBY51JnbA8kKRHq6fREdCOvv0axwGgFCGqg3ptI8Lzm6gJRtY6pGY7mxJPIQL7Ros+2Gd4YUcV+eHg8p8BYcIICyRwLU55wtlxuHJOwPALE1HbpnEiu0y7v71RNoPj9C+mPP5794w/rqnWddIfrK+EIadQyEDf8UrfCtRhRBMKrB4eBdHgg/YrYxHAmEwgUQMThA+MNUxEZ+p+/YIyzKyPEuDCw3/847Ju0SSRrAtlsb7umzTBkEIGo++T3c3p+YfyB+IJAcVITZ31IEge9AUGB2FFqQECZZ5bTq5aezuXkWg6EIdRp+N8W6RfIG5/aRxHpFO0eZxN19h+aMrskU5CgAgZ/F1/X8NQcvtXe3tYGiYRnwYE1IHDyEPjDBU8Ha5gpRVLgKIBwJyiT+/w81yS+K6tMp3naiG7cbTWLmFL/di0Am/tkkE/5LNK08cZZ8qgUMpSMacpJI5bMwIcHspBem4JkvAGTVLS10QTQds8T9yvAL0EBQIHDbCMpeEjcD5KIybl4dMdRjWu5RMWylHlAqkq2Dvy6M7WQjxOHDRHsoU0qm535yDjXQg0z9i+G+8y3Pn+j6DumjWY4ROyoCyCSeVNG0rw4yHeAkPWkBNJ+v7oA6CQnyUJ4lWQ8HgSxcoQPQsdahSChMb0AQibTHZZBIDGQ5K1lJSXP/7qwwCirkYlNBVlk7/EcyLgJDkiEomB/x9e/KdNhDaRAD2jIEokHwj9JoMB8AJRUegGTGFZDK12WuyDXCcN7eFa8/NLvzzkxklVcR/JOd+Br3IrWLW/a9Sw+NaM0ATKPOm8tKyv96nnCcmeDVQq+hRPZvGZyrsU0D4J2f5i5IdEcU0R6q72gPVlGguY9pTyOFVASibpBQHAt8GYirZs33ni92oKueaLi0iWP48ufTF+yQ8pvqvsiLafodGq/ERBOWVFsCCs7hiQcVJg0IaZpWWR/SfH25aGX3gWF84iR85JIAub54sAiOebHPjbkANC0n2POL7J5vP+/IFxaPbULwtA3IkFDKj8zPW0jQZpQbHUgFXQBkb8LAw5PoviJURgKBwJH+421Nay7aEwnkdQdfA6kSa4VdiDhF4r929v+uedf31mYiDuQGVwpp8QRe/DXo1xq2AyBZ42LAhX1I004GqkFAkbBICjQH2gecSKSWB9OR20gS0c1orTqjAK1HQM59/tzP731YQEEgutc7ZfVLaLlp7b+4ZMsyi+y7jppIC3aObQGJw9krKfn8rbf73/+3YWpwSjrOCmnT0vnocgD4uVf5C7ikJWKcDSCHQY5UMEie6rT6pAGdnR7nS0QSbxYf5LThwCpZdBtr7jTmuHZPXiL9aKH8QSTO09PbEi00omjtvLhi5y4qi6HxFyrq3qxCwkkaSDry/6e7a+K/XjXBBMLNvA0MDPAM1vSiEUUDPiSQAZMgFgIGIY4TAWOgOx1M1vB9BsDoj3UONmEQKLxED2wDKtHKu48IpBLgNznkbz/3BMPufZMS+1ftUZyHRI9zBkHWzi6uxu7yg90Sck4IHXzIyFA/NuX/UP+oZIDyUFAkJ4VBPcVjoE1e1TLwTyQtSINvP8CyYkkM5/RkhCDQE33NxSIonlH6GhIN3YbyNGO1spakbSzotJpBcrojkMDFlaqvb724GumcwdrD7V2oO6HKfgwf5CdGIhdALzYpXpQtq5uJLu+vHx5GxL/0NC+jejgTIGjoFyGh/UmcDmWA4GkOdEsWdznkEhcrKRS45v/ALmDMi23qLv1Q2fyaKijnmcFBYMAovKua0y5hCjVUXBgCe+BVBpISHf2UCaq7mLcguQAopILSOegA9mGg4FraG6uKhmdMY4CiL36axmlkAlANK+4f1SEJUBwYuIZV0ylU1OZKc3jM4OpPYtQnJNvHe0Ox1llkc93UucM1dei6xmNDtIKwx7NW0+0GYXWV8ziNYdZv78GTo1AmKiZQYJWlCjnUzd/qxd+q2qRpDFSl80CAkcPA9exu8uGxm7pjHrB7IHokeEARCgsxB0na8eiEScelfmdYUlyK3QElVIzYWAPK6PIryacqHIe7a6xR6ylL/S1WgbYCpIVBMY5SnWQ0OX87MFaWssrWyNwUDwMlnMjNs518lFu2K22CwYa5VqRCCbJnsQiyydOnCi99ljPZNVGXKndAGEh6amFMSwMmjrQ+AAy11oZGfGNEMwiub3OwjmSzQ4OTnkkZMsMa7KHxqzIHsXORH4DkFM6tkopsYZ1bL0OVFwnL/NqKZ+RI/Lba7XcqOWy3jBbBeWN1WwFBoOPPaoLRBt1/9GBLkZfWyg1OJCenhPHTlz2996wQbJqk7k4SPHSa4jQAMQ4PBAmxJWVEd9Z16GiYQkQSEDAJJ1MSDPK+wH5nzlIITYYv05p+VpfyTEyKgtyst36g8pbIuFP9JNzySkYES5txp8WtbFZHXyMA6Fsm9lJ0I1OB9KQDa5uL6+eWN7uAcY/tv/d/DQg2EIinxVHDhIkDkCcAHGeJWmisIDEJFHjUNoGiOd0/+AggdB4np5uoqDQXc+5+4uA1NSS5eJYRuKdU6w5d/AQiS8DbwcgvIlE42IXl7lyTQxlXrtL2wwShUP5YTY8u2wg2KS4dLL3wJU8IIKQMn2GwndwDAsESJMXIxqTINE2McK3BmUQpP83nqs5XWTJ+ISTrbYAmcEk3IHQrSYFTEPgq9nfQyE+cKvrmdEBwbPqrQ2D3X82ZnWT9OhpSOBobPwHSMxAepZ7TgBSPLlvMZ9eg0MzuUIjYyTDJjg8kDXFiANBgLDxsgmJC/coygqpDg02MG8kVcCIauEIBZ/E4Ew3IHAgcy6mPnpKdwMemBu1OWUgWAM1LbJZzvY4JDf09nL8u4o/ESIRJ0BcsIujtLh4bmtxIjOMBQhuIxEI0W4WgQMQb/gdkRiS7gRFW8Wbm/gSFyxbidQkDsOKw7Fg9TBYWDZOC+SUVG0n7jm5QxVF3fBq9aVcV1t7ozgqlCwS7FzYRo9MORC8j8SBqlGuC9q/X0fxLdQRJdk6A1nFHseOHYNksncrn+GxrbGxD1EDtmlkGNlkuQCGQKAQB2eFECSIB08kPJIIJLvmmYBjyi1VtLxKT8u3TpFtKCOPccve4xxqA4R1IyzXXKMzFu2AHOE8jCIJv6Ing9Aor+qtuoVrafaNvfDC8SpxRBxHKJIlR4FkWa7lLy0tHZrs3fjg8+E+On5hQX2OQyjkYbIIKGsCScCBIBHPy3BIUMAhOTdzwh4Zk6s/ZjIL+eOnGUmDpH3VFw9rIievZ35voy7RVnF/BadF2EdoP1RbX9MR0bKDSGejXJcJsHU2Njb2wr7jOFY8FAlpjEHh0eXtVUYuxUhx8bHS3n1dmc/V4A8JLH1UFVkPyiKBceXDqh0B4lkEYQ7hgMFnQM5UZyAMiXUiYWbxFr3kApkALAKaWOxdP66UiaJhsLuezhgqW4CondzEdmHFnQKpzGapDVL4wa9g2ALDJJBwMhSxwTJCMfWkB9IDCN4113sgLRCTkSAa5QkQJSH2iuY8EET6YarbVcoFORSSZV0ZBIWrlZky6StVXExRzr1xcLTE6qm4s5lDa0ahqbcCtXNobAmQTtKaLs7gY5DesTLOfI+9MLZvtDzYRNIWEYiqwtWzgOBaMsmxm26am7shnvgcz3ICwUAoI4pkPJUDJLWWyu2BGIl7cm+l6IiUgOm7gBGskJkl+my92Leykt7Y6l1fXy9PdjHNBamHkLBoN7qCw2Qei23g3kjHDEXSTrSx0XjLu1v7tibnACl9Yf8Lxz0Q5IGsLxsI8yEBT8q1v2vqXyAIDieezCQQZnQPZKSZUZbBXCSklkqKPYlM63ZMoW+ZO9HKfLJqcnZ9dna0M1l+fLQakPp69nBv1wYuB16MAxCqJ6Ra9APY1JS8oWprrHfr+Tmd+L5BN8eTCjuQ1mwWkOBpMBAkArmpZN+B6AognjAGgkETe78tax1IIUW/fSRBiDMtDeqp9eAjzS6ZbE5I2IDlroEYyXznYu/k6uzs6nosewvPQ8U9xpqx7vZ7Ka5QWxGJFuvXHTKQmHwrmXyXmx3mngcEErvAtLy6K+yBLAESAkQYBlIsk5RUNSV0SsxxAAIEn4jFLS8tIMhADEaPS61B4QBEn8QK15rqfX2mEQQFWT3y1YW6GgFZnV2dDWfD1aNWE4nw9kl199aScV2iuEKjjzOIdhbCLGZ535j9HL5/HrHeKBHILdpZiHkg5lqPrgsEYRH0wG37FlOKdt+Zp546+5RANKvzVB/rkA8gVsoqcskJ/gVHQSsr4kAOxEcRDA6fJZcfW152NqtzwpP+1fXV2ZZsrGWUckJ1OFIHSGvlIVZbzCcPIXFwRQplhq4kl0bvLyub9A/NPf/S0ORkr+7A72oSB5Z0IKGWk6OnZyHxQPzF1966rzHe5wMEEudaruHfHbsyi3ggWEMyAE8cP0E+Pujd9nT2KYGc8d38jLlWmJ6DOb9/FpuMLmVbWFucvBhsCjEZkOTUat+zHR8jOeHsMVOm3juFDeVbiXE01js2OabkJNhFaMmzXJCEYrpYnjmRyV2u5fffdNttZVXJhHcuidfVBNcZPqFhey0gBysiNpqdFBQwFPQknuV0xn3wg3w5I46VbPX65JD/co9AXghjEr1bxMWHT4WydcRsDXlXJSkve1ZsiwZ5uHK7ufTWkrKxUoHoLTyqrDUiHCqA6I5T7vpfJ0pE4leMXHtbyf6N+cSInefxOHiKp84gn8Sj4zAGwkfBIJ8LYeXsiu9JMFawge9fsu56qkOxxya/+uryZUgIkpP4RFj3Mj92sZsJIxKy5YlT92E4Hj0+avdf31YGhoGQbsEGSCxEl4dReCDyrVXUQ3Xr2E0EO+NWJ4/GxO7TaorwOPPUe+8ZCEMRUiG7qI7J3LISHE0oexpxsjHKp08NV/DrJfDpwoldEDz6dCyrKD0tkBAcMV3TrNKuFNSj9R4f5ZB6SRlpoAMhe9csGgwDUh+CwwNRKXV0XSR+fw8gxaUlJb1VSR7Mp6oChWoZ5D1AOJTC+zaNa5NEIA170ng1z3SdkAifOqd+k3XZe2Nef2Jk8FTjvkm/A1ld3l4XSPCkOntOxbT50R3kcg71t1YTO4892rs+yWU6XHtSWuyfnVRi0niLa4zo+jdIpVyUJZeBnMAidx8rLeOdpLrmeS+MQD/i1ouPsYUM8sw15OrjkLCx8FTR+YjJlRDTtm0waPIOBxRAI1aFRalEIF7eyHQw9NVXX52QRdbDgIS5no1Sz8Xqi+wWNJW7XkO+ci8VrzD5YdlY8Qn/5dXZyd5eQqYceRs9Hgj+VdndEiTYHp1dNtcqLgWktGys9wClerddAMjNdv/meyJp11u09fsgKYLAFC0orS8Gp3U2pCCYrKHi78bOJrSVKorjWWRmEUdFQXmgMmBALGlUJs9v0IVRnIU6gojjB4paa1UQodGopatSvxC0glqLNV0kaFD0QURB6kMtrYsKQvUFtIsIXVt4C5fi73/u7aRVQf/JTNr40fvLuefcc8+9M3mXTO32zevZmdMxEJGsHtNQxqYlSBC7xkhyZ+w7xjY2ltCq2WGJzrK+vrRBP5Op1PccyHlwYI47uBO7ipB8CQ6OV1XWGAKysFA5f5JSJAVUVmW4HZ8MoruivnPj3ZdSq+dKWJydtZtHEY0v1tm0NGUszNoLveueVrJ89ftPj//M4NymbxnI+tw1kJx33qXkv29bTfQcxpglNX4VicR+Jg/YMA6+ZhDd9gByICKhGHOFLr4Acm5G+OTxVUDoW2efr++8Y3vNo1zNw80eETdQguPZtx96VFeNPl960mm8OmVyS21uGvLeY7e/d/u7j93ONOpjdu1A8urpLzeP9x3I9CxOYt5+Hl9CcqkS4GeP8e0Jj+MX0joSCwdSt2Km7gKBKNAVmPI8KIjWgPAfyyT6HBbCKr0LjiCYmNCmpldZHb/68hc/ZK3N7izIxRovv/3pew9f8tTDL5We3DbZi/YScXLydNQcC8wn4bO13tN/bMEhH2HUEom8nWIJ5fYLtFtfg4qh0H5PwoE5sIZuGCw3Z65P2QKx31e610CI25pxvmIGNRBIAnR868Lu5v4+ayZXX/LiV+znY8wjW7/ukU8ffAynfaO0vbO98xvHNk/Eix72ekQex5A/3twaVHphu10FZB0BcuI8gVC0vtIGDwu6TKE2yPMlo+C24HPsbYeDYaYAMYxL7dt9qEg+++y3BcjCUgHS6Q7q/a3Tm1TT8BZV1zkWWZDaPP/45qtvPfpYacf0085/Cz7/ur857FZCRt0ysZ4xeH139TY2H19EXgUJKJR83dc+cdatkpBu9EJ4RgQrQByJ57j30jsKEDQGMQ5AkqQ76PZbg8FQW86AcaJoEZBKs073Vumn/yNA7XkK/fTT9uluNwmaU/LFKqUCQNYv8yBIRtHmIO6Gdh3L6TddRmd57dvXnPi4EeUjQLDcgT0KUXrFJA6EMLfKuQJJ2moNuvMDQEzcHIInarX29tqd/h+nPy79+BMPxMs/xNuF9PvJkxynfnlr0E2aURODTJVnVfNgln2MbbEsT1HTAkX5rm0NEg9fC/U+n7/0rOkyOwtEHP8EMYu8UoBgkThPuQXP/AuDwbxI9jkGPFuDVpru7cUxs4LN0o//pr9BnES/8/z9p+3tn3bekkHiOJ4qgzI9/bmBPMc1EzefexcgEihncYczkdi9GQsBc5nOVjFGuMYhkCsLkLFFQtSM0gyI5XnJrKLToMtbL8TxcsyA1ikVbf2Rh168HMnvar8TMKfe+qP/1lt/dPrdIHQxfhYQZCBnAaJ7iBjJZ3Z7F0p07F+k56MxjzacOgz0rxY5dgDCKcTZa2ljMGjEL8zrMUBADGEC5IXl5Xh5b3evdPKwfreHh/Fv8OTAPTBFb2/U3291iCIhJGh2lvBL51pdeZ8r6uG4UyCGYqJp2rpBeduhCAYIL40fgHJjK4O44lK9yQY1osTjGxtrpGa4RyWsJFmWDYZpnM6njXkv0cy/8IJAbBwo/XiKFkunioYjMHjbG+PUzvZb+6f/6O3hWHvBsM7/POi12+WqB8EgDuTMwyBCsdUs6owsBl1wBSBOkFzJAwyG82sZRa8lZF0hkgLkmAdpNisoqQski7JWlhYgcHiQDo3ZK1kkOsnB+ZD0lv9h57TG8N7u7t5od69XHzI54jPwIBIBeHXjtQsM5NwDEJZ0QWC9xMUxi8qFoBKGRLA77yJAkAdhDLoNEIpeIcImSQLJYJDVWq00K0B4SAckhN9ThRyA1y86dPq4vTva2+XR19Ft1QNhhG31LBMczK2+4e5ykNxsopMB8532eKDCl42BnsUJDtNF18JSjIgGwhxm8vEF4m4YxlNhMFEXSGuQRlkjl0XGks84kl7J2sqJp8TrL+508LK9udSuiKW6t7ubEHiDgBH9EMi0QNZ/JeBCYiDnSpSw77r7O0iOoJhp6FhXnocpSM5IBzAJJKBILH4x9hhI2GR6CAj3pRNIK4qjPG6kR1EA6UOy3Cnt/OL1m3vZ8W984U9f3TezVNFGl2mWv8uDQVKuBCSLAjESxa1ZTRLfN5AzwfASyF3qW14exetagUChJyYxEp3cJsHJCYFQ1Go2g2SijgqQggRbuDMsy8slatteT9n5Kw57ZUqmCe9Hc+vrC0vTaFSOsmErq1YSgld1bJEC5ALuQXUYRIf5PN5SoEgwFAIIKf01cdkYHPdPTlTCJiB5FOAkBjKoQRE1Go204ChAOJPGg/DkIV1CRRGxrf+Zj756kTW93fUllvR2aXdtOKw1R+3ELDIGmV4dgxwiYZ3Eg1g0HqOAIWPc4R9cD3MY5LrDIFEtMZAMEMJvqyaQdAwyNkzp6cdsUyw7/NCTXzPLkig6Xr5Ire2ec1Zt5FYJs5kNh61oimCFr7NZpMoUzkDWZ8ltV/B2UGisQD7wLPi8k2KZt4DO/7SIiT0Fssj9k2thmfE8qtVqSUDKWE8ChS0o8uVlbxKcXPI08yXNMkAA5tV3H2M2wgYOJr7PaLmKCs8KHLZWEc6WE7KCWjMkV2xb8OVdKMYgt92j6yoAgcRbBBCPAYhQDEYG+TvIHYaBqDZeNzm3IJAmIFEgEETm28pqkDT+AcIDEF1jooOn3EXzKc17dSXA/VTKMMaIQtkCqXRrOMxwvhAKgcgiyIEwkLx82QWAnKfNv6B8gDAIIKCMRd/zYheaAzEUCBzHvbZohafDAUikAVEkOLtGErzEc6TpCw0HAhOyqLUjEWk5Eb1+e/Kt2x+5f3Py+NwCk9hRVQlooH6a1QOBFCSAeK0L5NhtHgQSMO78wJYSHQwW8SpAvEARSKHLF+85dvaSA0lqUViR6Fy1GuN6FKW5+UiKaH3DSByIH8hNP53ip50nH3t1n2T//MrS9AhztC1HSAjm5WoYBeE/QdZn1xlKVthecsE9BmL75pCRuMGRJyp6180Gol11tx4Wt3O8/Jpjj7MqFy4IJAkAcSTNZk5Hi3CShlKuBs+G9S4gDORP6fcDnSRL/54Z+dZWsFAdjRgF2x3UTzBJZTRqky2iv4FY+aEAQbRbICyJQvKBRylIQIGAxSBnEYdw+a2Xf3K5XVx5bEVplgyyFlCa9CBBzJpPTvSNcwORUkBQAQIHJIZzantf18b9rPUL2qvpcr/f57ceCwGdarVHyfOQSQ44Zg1EKz2ASALR2i6ik3mLFCAHHDfzcBbh6piruOryBu6uyfIIHIBwoniCq0OBmkx/8lp6BGT+qEVkCYGA8fHpP37myktV3tr9Vhcv63YLEHttl6d6pIxi0UT3kEU2uHqSahsktmHTdS0LXoVBChDjcDIMzAEIa5h86cyKz3vhWJuAxEWtIIIkz1qpgUDiQBqOZFkgHgPn+Pj04I8/un1SQn3+fab7Hfuh327zG9I/gqUnUXsQSbVMBFbBZx2TsJ36Oi5KJ7YqAkNxWDePBcWNMJhu+IFbr0Ny+SJPFcJXMAXFPDjQhMTtjAGJanE5bkRTcWO+BYgJIqPgVDp18k90kkns/qBFYzuOo6um9wWCJfb2Ot0DEN5DsUhkE1gYSqxotTA3Scy+hyjKTTLP9SQ6nyEMh/KJOPxV4KJAOt96+VWLH7340XXPrcCxYiAVkyNJJhLNrXI6VywQWSSFhZMgChA4dri6b6iW0qmMo9WX9BNn+pmBCKI/NknZQMjCMIqRnD9JfebECQ+Cg3BIhW2e+AAIYXCvB3QDx8U3ar/FVS9SpbpubsP8w0BsSoVJnBT8M6wR5YCkGRAepHFAUqJfkap/zKjdB4JA5Ro9AEAG4YXWyyCtbq9tXoJAsaoW0gmQqsqh7BO7T0vMusYYkCOCgqdO5x6+/4YO6cUX7zuHat7K2Q6kudBcI2r5rqX0N82yGtUUDpp/CGTs7CfB2N/CGKTpu5ijPwDCQBR3u0YzwBqDbnsPjxEGAUSpigMxm1QZ3ctUCuqb94GC/94sjqMyk4jAy5mE7Twsj7Ncd9nGqr5F1IMQfJEDcWm8HL0ZKWrVag1GRgYVA2l4EDj2t84PelUmsiN8QTlNHxBxYBTxGBpGkUWEgXO04xASBIxLuqrVJeoRwfHNRxyJs4iuWiqknTYegruDXexJLhbHievOmVsjSAVrpkoTRfyQeA5AZJE4UvMbUZ7nKWcHQq6iXGv7460vz1YpoR1aYXJIo5G3R1coBGJB8RZDC1EQTYVHQKoWv4jJlfrx+wFZFIjnOMMzmF53GDzMJDDY1yfdc9s5GzOKtaY1YdC1PAgUOHstiXKl9UokcwPJ8wbOIhrFr9LpnzUkhAHSfHIwbBG3+0HPewa2aRHK2r1uJ+gGTHGDKZoMBy4iCufuwgAkJjhMHH+EfXeMcOc+IRIBFBza1mEgPGUP20d51Sf3HHvu8TVXGk0SjYDNipFIBQimiKvlHA5AKA8Kp5alZhYNKaX2aNSrI/0/EoqQ1BYYzmm5IhaCo8/PySChCgRxMzQreGNgDlNZXFNxJ+r0ggvZSHZi8RPcxCgKCEMwaf3vFrqUSd9mRbASRBLRiAr5YiCOiMdEAZKoRjslkAjlpCueCRK5fWm01zs+HMJRzxKBWLGnosEEDsKwRd1O0qpXwl6FvhPKAqPpgmF3NJKzA6JkaLkTk2FO8sV2GIUgay491ptILwZxMdtZFhfBWJnZWFgTB3G1RtQNXddKnEUC1+UMJAYECaSZOyBCsoWvUrvTpZaKK7XsaCWYFpQwxO8NhLfiOGkFyrLKHBhiBIhUgNDZUEzXjXNNHi4E5R7uwnbDjW4fGH1IZ74GhofdA0+BirV5dpoydpxtTW1GsGgipYROJIU0b48CgTQBQQDwx+AQCK8C6W4NtwZEKqSXzPVSulHSAqTezQDpTQX1Jk4gn5CwSOHoziCzuE2T5HSZvC6rI5Zttcx54g4WuIWCL2gTKGfEF40tnmCLw+OMfMTaNSpX+sTJ1PMmMwYrLDcrENiBwopAYw+SAgIHlhAQIKhW2qJKD4T8XJYBA/U0lelCIr+RRYJ66GxAQmIg1QLEtr8YSNQwI2e1BE2AogtdSCQFdGLRdIKfOHFRKOEWiISwhAX5jLMsyan9BOoRioiaiFimwtREBUfcJo4NRONhHsPBxBcQ6IUCyHCQpVkB0ukEOJzSXkjwjIRTMw6CMhBoDGLid8cRCiQSh3ljhlns2/TcbaNYUp9E3JpsjptLaSOEpSI1/myN5IPZH9K8NmCPhxiatF3FeFDCJbqzQMwiOSCZgTAw8iq4poEMAcHNfM9Kbfjow9HqqpZUN4vok/LdCoUWcEMkp7HVTkDo1mbthuxMlRa74KaCkXQXFnYTzaAVc271JwAQCEaBArSwJBC1PVxyIIVFzEfSFBDFXou7chJIBOLsEDEjhiNpNFzC60G2WklFEZGmkZOEMaOHvN0sMuVAllZZIfFOIg9sWmDRp0yXQRfWJSVMXnNzLqSKFXT7V2mYqymqY6nxOCSiXKD+xSGntaglEAF4kEY+JTx+wyKApI1aNmjxT6Ka+l6agqK/pb4VQJLzPqaFHhKXLZa9SQyL320kiZsSw69EH/Cq8+Sh/6NUz1AeOYmiSf8AG146tQtbEn+jF3ZmJCtpM1DRfAPR6k5DymNTjkXMR9KUYkvEQAlxhtJ+gur8UcTnxbDq1USyjAOZEggcvChxaSp+FiByS99z0gIKuZHAU+Tq+2GFaOVAnNSfEANBR1+lNKP9IEvT1bxhIMxwTQ1gtAZoIKpWRVo0beV5lslNWyjtBwgSJWsiyQsQIwFBFNjGQKASTKiyDcNzNAbxJ1Ikp0TyDJKzNL3K9UBjwCqehzb0z4aD68nmZsojA0HLhWQSD2IekpErNmIgagBD0hVIEjiT6A8fcPDqOeQsCBBkfQwQLEJTHYrCCxJJdmAZj+J83OKbl0DwJgMwEDOH/JP6wcL9zzzzyORMdZqpLhqD5IAsG0jUKMGR1ADJ8tj+5w1A1LXcZ2QjfYArxkcsYvak7Vik8BeBWMJkFIUa8EgtCRSBiKCgAF1/w/UsI/EgC/qh0xuNZjYpfN4/M13lg0z/bpHl3CwCSNZMMkIWJTz1A1kEjob6lSlo+qaPjcIvoUCmEHG3AJlSuqc8w3MoF/Ku4H2E94wz9wIDrLroPUfgQdykHQ6mrTPHuXL0/oXpcn4U5AX3c4yWG6VBmqT2UZFcEAsbFqcFEsgecNCNhMzjkBT0nLObJSzywwFJRLvoOOJwyp38z00nojRS7K2PlajpFX8yECWwvYWZ67kCdlIWyXERplGe4yiIWX2Q4c84XtqC2IVfmUTRt4xodYGRI9e1ROIzyQqCRlwRYVZjg8kPXpJDkn8pcTWJQ7HE4qOM71sPh2qmHoTtqJPPPHP/9fjIFByQOBBemOamByB/Aa4tt4+fET9yAAAAAElFTkSuQmCC
Ε-mail: p.zervas (at) uop (dot) gr
Short CVPanagiotis Zervas is an Assistant Professor at the Department of Electrical and Computer Engineering of the University of Peloponnese in the field of “Audio Information Systems”. From 2008 to 2020 he was a faculty member of the Department of Music Technology and Acoustics of the Hellenic Mediterranean University.
He is a graduate of the Department of Electrical Engineering and Computer Technology of the University of Patras since 1998. In 2000 he received a master’s degree (MSc) in “Signal & Image Processing Systems” from the Department of Computer Engineering & Informatics of the University of Patras. In 2007 he received a doctorate from the Department of Electrical Engineering & Computer Technology of the University of Patras entitled “Prosody Modelling of Greek Language with applications in Text to Speech Systems”.
He has taught undergraduate and graduate courses in the field of Digital Audio Signal Processing, Applied Machine Learning, Audio Application Programming, Microprocessors and Educational Technology His research interests focus on audio signal processing and pattern recognition, speech recognition and synthesis, natural language processing, music information retrieval and real-time network music performance. He has participated in several research and development projects. He has published numerous articles in international journals, chapters in collective volumes and in the proceedings of international conferences. He has participated in scientific and organizational committees of conferences and scientific events. He is a member of the Hellenic Institute of Acoustics (ELINA).
He is a graduate of the Department of Electrical Engineering and Computer Technology of the University of Patras since 1998. In 2000 he received a master’s degree (MSc) in “Signal & Image Processing Systems” from the Department of Computer Engineering & Informatics of the University of Patras. In 2007 he received a doctorate from the Department of Electrical Engineering & Computer Technology of the University of Patras entitled “Prosody Modelling of Greek Language with applications in Text to Speech Systems”.
He has taught undergraduate and graduate courses in the field of Digital Audio Signal Processing, Applied Machine Learning, Audio Application Programming, Microprocessors and Educational Technology His research interests focus on audio signal processing and pattern recognition, speech recognition and synthesis, natural language processing, music information retrieval and real-time network music performance. He has participated in several research and development projects. He has published numerous articles in international journals, chapters in collective volumes and in the proceedings of international conferences. He has participated in scientific and organizational committees of conferences and scientific events. He is a member of the Hellenic Institute of Acoustics (ELINA).
Scientific Interest:
- Signal processing and pattern recognition in audio signals
- Engineering human communication, speech recognition / synthesis, natural language processing
- Acoustic detection (noise monitoring, acoustic event detection) in intelligent environments with deep learning methods on embedded devices connected to internet technologies of things
- Automatic music information retrieval, online music performance