20230328 14161900 1.0 TRUE CreateFeatureclass C:\Users\ErnestasDi\Documents\ArcGIS\Projects\AAA\AAA.gdb upiu_bukle Point GPLYR_{F64202C5-E565-483B-8DFC-A96C73644003} No No "PROJCS["LKS_1994_Lithuania_TM",GEOGCS["GCS_LKS_1994",DATUM["D_Lithuania_1994",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",24.0],PARAMETER["Scale_Factor",0.9998],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0]];-5122000 -10000100 10000;-100000 10000;-100000 10000;0.001;0.001;0.001;IsHighPrecision" # 0 0 0 # XYTableToPoint upiu_bukle_826 C:\Users\ErnestasDi\Documents\ArcGIS\Projects\AAA\AAA.gdb\upiu_bukle x y # "PROJCS["LKS_1994_Lithuania_TM",GEOGCS["GCS_LKS_1994",DATUM["D_Lithuania_1994",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",24.0],PARAMETER["Scale_Factor",0.9998],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0]];-5122000 -10000100 10000;-100000 10000;-100000 10000;0.001;0.001;0.001;IsHighPrecision" CopyMultiple "C:\Users\ErnestasDi\Documents\ArcGIS\Projects\AAA\AAA.gdb\CLEAN\upiu_bukle FeatureClass" C:\Users\ErnestasDi\Documents\ArcGIS\Projects\SDG\SDG-DB.STAT.GOV.LT(5).sde\open_data.gis_data2.AAA upiu_bukle "upiu_bukle FeatureClass open_data.gis_data2.upiu_bukle #" CopyMultiple "C:\Users\ErnestasDi\Documents\ArcGIS\Projects\SDG\SDG-DB.STAT.GOV.LT(5).sde\open_data.gis_data2.AAA\open_data.gis_data2.upiu_bukle FeatureClass" C:\Users\ErnestasDi\Documents\ArcGIS\Projects\AAA\AAA.gdb\CLEAN upiu_bukle "open_data.gis_data2.upiu_bukle FeatureClass upiu_bukle #" CopyMultiple "C:\Users\ErnestasDi\Documents\ArcGIS\Projects\AAA\AAA.gdb\CLEAN\upiu_bukle FeatureClass" C:\Users\ErnestasDi\Documents\ArcGIS\Projects\SDG\SDG-DB.STAT.GOV.LT(5).sde\open_data.gis_data2.AAA upiu_bukle "upiu_bukle FeatureClass open_data.gis_data2.upiu_bukle #" Server=SDG-DB.STAT.GOV.LT; Service=sde:postgresql:SDG-DB.STAT.GOV.LT; Database=open_data; User=gis_data2; Version=sde.DEFAULT ArcSDE Connection upiu_bukle /9j/4AAQSkZJRgABAQEAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a HBwgJC4nICIsIxwcKDcpLDAxNDQ0Hyc5PTgyPC4zNDL/2wBDAQkJCQwLDBgNDRgyIRwhMjIyMjIy MjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjL/wAARCADIASwDASIA AhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQA AAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3 ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWm p6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEA AwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSEx BhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElK U1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3 uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwD3+iii gAooooAKKKKACiioJLy3iu4rV5QJ5gSidyB1NAE9FFFACFlDBSwDHoM8mlqKQQyS+W+DJsOOzBTw cHqKrES2sUcbSt5KYJmPJPzDC469OM0AXqKRWDDKkEeopqyI7uisCyY3D0zQA+iiigAopokjKhg6 4JwDnqadQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUU VX+1pKky2rxyzIuQu7jPIGT9QfyoAlilSZSyEkAleQRyPrTJgiMkxhLyD92GRcsoYjP4dCfpQNtv hf3j+Y/XrjP8hTzGDMsu5sqpXaDwc45I9eP1NADbeH7PCIzLJKQSd0jZJp8ieZGybmXcMZU4IpEi SN3Zc5c5bLE//qoaTbIibGO7PzAcD60AMj3tvBXbj5UcMGJHrSxRPGcvO8o2KuGCjkZy3AHJyM9u BgCo49truR/Kih3ARYOMk/1zUzeZ5ibdmznfnr04xQAKscKYUKijJx0HvUcjJK0sEcximChiygZA OcHkY7Gobi3F1PJBcQB4pImRXAzhSAGBz6/0qwbaJtpdd7BCm5uuD1/PFMBEn87yng2SwPnMgfp6 Y9alyMgZGT2pERY41RFCqowAOwqMQ5ujM+xsKBH8gynXPPvx+VICNreOeN7d4GjiRgUZWxnocjBy OeO1LOl1JOixSeTGvzM+A2//AGcHp9aSG/hlvHtCGS4UFtjA8rnGQeh/+vU/ljzvN3Nnbtxnj8vW mBXRrgXTouySPzASWkAKLg9AF9QOp7nnjFLFdvLO8YtJ1RXK+awAU4HXBOcdulO8mO0jnmt7ZTK2 XYIADI3Xk0+Qp58IMxRudqAj5+P1xQBLRVZIbnzUL3W5FOcBMbvvZB9uV/7596c8xa4+zoOdhLMD 9304pASSrIyYikCNkHJXPGeRj6VVdoZr57Zi7HarMN42rg5HGc549KtxqVjVWYsQMFj3qsIZpxI0 wRJBuWF1ALRgjGQaYFuikAwAM596WkAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABUE KQmR7iJ9wcBThsrwT0HY8nNT1Wnil3wNb4AV/nTOAVPX6mgCVUUyGVWY7gB94lfwHSnOwXAyoZuF BPU4z/ShI0iQJGoVBwFUYAqGOzjjlVwWKqSVVju2sSckE8g8kfQ0ATR+Z5Sebt8zaN23pnvj2oyH jJRxyOGHNIVPmh/MIULgr2+tLGiRRhI0VEHRVGAKAERCIkWRvMZQMsRjJ9cVHJN5DSPcSxJDgbc8 EHnOT+VLMYpFNu8m0zKwADYYjuR9M1F/Z1ub43jKzSlVUBjkLt3DIHYkOQfwpgSpIJZ2Mc6sseUe MYOG9z2+lNku1iuo4DFMWk6MsZKj6kcDpT0t40neZVw7gBsHg/h604xI0iyFQXUEKfTNICG0vo73 LwK7Q44lIwrEEggDr264xz1qzTEjKPI3mO285wx4X2FRmNreBUtkDYbo7HoTk80AOnR/LaSGONrh UYR+YcDJ7EgEgZAqjDNc29jkH7Xt+QNtZWZtxByMHAHr7VctlnCF7hh5j4JRTlU4xgfzpqBsSrAW DCXky5x2Jx7c0wJy6qyKzAM/CjPU4zxSSvHEhllKqqclj2qBbq3lgNyysqxsy5dCCpB2nFFoqx27 vHNLcAsxBc5ORxgcDuKALIIIyDxVPUri6trdJLK2juJDIoYPJsATu2cHpTomE0JuIImDzMu9ZcjA zg8dsDP1qOJLm0BBZHgTIiijX5iuBgcntQA54be7MUjXMuJCHjCTlQcKemCMjBzj8e1OiXyLuZ5X bErARl5M54+6FxxjHuTU0qsYt8UaGVQTGH7HH6Usbx3EayKCRk43Lggg470AOkQSRshLAMMZU4P5 0qrtUKCTgY5OTTZJY4gDI6oCwUFjjJJwB+Jp9IAoqFp3W8jh8pijozeYOgII4P5/pUcCzR3k6+Uq 25wyvvJZmPXjsOlAFqimKZPNcMF8vA2kdffP6U+gAooooAKKKKACiiigAooooAKKKKACiiigAqtK n260UK80ALqxIBVsBgSPUZxj6GrNQi1jEok+bcHL/eOMkY/lQA/zU83yt48zbu255x60+meTH5/n 7R5u3Zu9s5xSq6MzKrKShwwB6HGcH8CPzoAbcW8V1bvBPGskUg2ujdCPSh3SPZGQcOdgAUkdO/p0 pSZPOC7B5e3JbPOfTFRWyCNHh+0tM6sdxYgsueQD+BoAljijiRUjRVVRhQowBUcPn/abjzHRoty+ UAeV+UZB49efxqSNDHGql2cj+JupoSJI2kZFAaRtzkdzgDP5AD8KAGzXMVuAZGx+Gce59veqkN5J I0aW8kV0rs7GRn2kKJMEAAc7QcZ9uetXTFGZDIUUuV27sc49KSKIxlizbjk7TgDaPSmAxjcJOCAs kTMBgDaUGDkk555xxgdamJAUsSAByTTHmjjkjR3AeQ7VHcnBP8gagjghtAYUicwyEs5ZtyrwBzk9 OKQFoEEAg5B6Go5RMG3xsrKEP7sjG5u3zdvypNsc9uoifEfylWiOOAQcD24xT0Z2kdWj2quNrZ+9 QBXkza2oZAFZ5V3B9zgFnGR69zjsPpUyFo1ImkjJLHbgbeOw68mo4TcysHmXydjMCgIYOOxz2qSa 3huNnnRq+xty7h0PrTAS6thdRCNpJYwGViYnKk4OcZHY96VLaGMR4TJjzsZjuIz15PNKzOJY1VVK HO4k8j0wO9SUgIE8u3dIB5rFy7gtubHOTknp14H5dKkkR3C7JCmGBJAByPTmonLW9mFeYtLt2hjg F2x2HTPtTVuJElghkRv3keS5/vDGQccD86YD7g3AMPkRRyKZB5m99pVfUcHJBxxxU9Vks9k1vJ58 zeTG0eGbIfO3lvU/L+pqaQSMF8twp3AnIzkdxSAhiskhv7i7WWctOFDRtKWQbeAVU8KfXHXFWaaj pIpZGVgCVypzyDgj8CCKdQAUUUUAFFMij8qJU3s+0Y3Mck0+gAooooAKKKKACiiigAooooAKKKKA CmMshlQq6hBnepXJb0wc8frT6Y5k8yPYFKZO8k8jjjH40AQz20lxHIj3DoCQY2i+Vk/HkH8Rilht Ft5AYSEjIYugUfO5I+Yn14P5+wpfIcTiRZnCk5ZDyDx29KnoAKYpj8xwu3fwWx19s0+mGNfnKgKz jBYDmgAlZ0jZkjMjDooIGfzoMqCZYSf3jKWA9hgH+YpY1KRqhYsVAG5up9zTqAGS+Zs/dbN24ff6 YyM/jjNPoozmgCGZdivPHAJZ1Q7RwC3cLk9OamqCeGSZkCymOMHLBeCSCCOfwOfrU5IHU0ARPGis JwjM8aMFVT1BwcY6Z4FLA8kke6WLyznhc5OPelmjSVAr52hlfg45Ugj9RSGZDIYUcebs3AY7etAD THM0EqGfa7bgkiIAUB6cHIJH6+lRzh5JkgS6aI7dx2oNxAI7ngflUwLpBukG91XJCDqfaonvBG8K tDKPMxzgYUnseetMAt44mKuS0ssIaLzZFAbBxnnA64HT0FNjlH9oSruchgFXDZUEDnjHynkfWpYw IDFbxxuYwh+fOQuMYB75OT+RpInY3EiiDZGCcueCzcc47jHf2oAhfzpA1u6uXLkLOiABMgkMASen Az6npUotd20TyecqhcB1H3h/F0609S8fmvNInl7sqem1cDqfrmpFZXUMpDKRkEHIIoAimmMckCAp +8fb8xI7E8e/FSNIiuqMwDPnaD3xUTfaTMQvlrGCpBOSTydw/LGKmKqWDFQSOhx0pANBjjYRjapb LBRxnnJP5mmXMrQRedlBEmWlLZ4QAkkY79KWcReWWldY+NockAjPoakUbVC5JwMZNAEagLO+ZmYu ARGSMKBxxxn86dK7RoCsbOdyjC+hIGfw6/hS+WnmeZsXfjbuxzj0p1ADHR2kjZZCqqTuUAfNx+nr xT6KYEYTM/mEqVACdgeef1/SgB9FFFABRRRQAUUUUAFFFFABRRRQAU2Tf5beWAXx8obpmnUUAVLE nyPNmhNvNK53oz7uegx9QM4qSC3S1SQqWdnbe7tjcxwBzj2AH4VK8aPt3qG2ncuex9aRYwsrybmO 8AYJ4GPSmAsb+ZEj7WXcAcMMEfUU6qst1bacqC6ulTzpNsZlbG5j0UVapAVbWO6ieRZ5vOUksHwF xz90ADoB7mnhlvLVXjkkjWQAhgMMPzFLC85JWaNRgfeU8Hn0+mKlIyCAcH1oArWuoQ3cjogkV0P3 ZEKk+4z2qO0njMc7pZyQPkyOrIFLnJAP1IUH6EZq1EAFALiSRRhm4zTJY5nuYWWULCuS6Y5c9ufT rTAIpXnEMqBfJdMtk/MDxgenrUVzai5mVLiGK4tyQQrKP3ZGTuyeueOnSrEESQRCNCSo9TmpKQEU h3OsLQ743Vt5ONo6cEd85P5URwRROXjXblVXAJ2gDOMDoOval8kb5CWZhIMFSeBxjio5ALW2TZIk UUWNxk6BB7/1oAdPP5Mtuny/vZNh3Ng/dY8ep4H61I8aSAB0VgDkbhnB9apyEC8+2S48iKLCMvzE liMnAHsKtIrxREMzSsCxycAnkkD+lMCSmESeapDqIwDuXbyT25qAzTXNhI9qPLuMMqiVThXHHPqM +nWrKghQGOTjk+tIAZVdSrKGUjBBGQagllgsLdBt2RrhESNOnHAAHsKlmTzIXTcy7lI3L1H0qKzl jkt1VJWdkAVt/D5/2h2NAEplQOiFsM4JUeuOtPpkiF0ZQxViMBh1FI7NFAWCNKyj7q4y1ABPu8o7 YhKcj5SQP51JR1HpUPzW9t8oknZegyNzc+poAmpAwYZBBHtS01I0iXaihRnOBQAkRkKHzQobc2Np yMZOPxxin02QExsASpIOCOoqK0lM9qjtHKhxgiVQG47kCgCeiiigAooooAKKKKACiiigAooooAKK KKACiiigCHm3gYkyzYOeQC3J6cU+QybV8oLncM7jjjPP44p9FACOWCMUALY4BOMmmeZ5cHmTlUwu X54H41JSMoZSrAEHqDQBRS3trC/klVo4hckZQcF5M8t/LtVt4S7s3myAFCu0HA+vrmorpJGeFoEg MiuNzSdVQ/ex78U+eV4Qrqm+MZ34BLYxxgAc84pgNit/swiig2rCud4IySfXPr60lrDcRvM9xcea XY7VC4VFycD1zgjJ9u1TRCQJ+9YM2eoXHFRyRzvcKRMEhA5VRyx+vpQBI8SvJG7bsxklcMQORjkd +veopJvLugHfbD5ZJyvGcj+L+lSQxeTCke932jG5zkn6mmXah7coVkYMQP3fXrQBG0l2IklWKMEg ZhJ5zkZwRwflzx3NCkvBa/aQ/mkhvkBXDY74P86ldN9xFuiBSPLq+7kNgjp9CamoAZHKJFZgGAVi p3DHQ4/Kn5A7010WRGRxlWGCPUVFNB5iRIuwIjgkMM8D09+lICKGUtePBHK7CI75DIvXfkgK3TjH vxirEke9GVHMbN/GoGf1pY40hjEcahVHQCo4pSbiWJ5Y2YfMqqMFV96YE9FVpblobyKJ4wIZAQJN xzv64xjpgE5z2qwrBlDKQQehFIBaKKKAGyFxGxjUM+OATgGosJaQO+xuTvZVyxyeuKYs12cA2ig4 BJ80Y5Jz27DB/GrVABTXYrGzBSxAJCjqfanUUAQCYzRusR2TKBkOudpIzz61MM4GevelooAKKKKA CiiigAooooAKKKKACiiigAooooAKKKKACiiigCtc2vmZMSRB5MJKzLy0fcZHPrioo7m3uE2DzYhF ceUvUbmU/qKttLGsyRFgJHBKr6gYz/MVHcT2tuhE8kcYYE4JwT6nFMCekDqWKhgWXqAeRUUUHkth XPlBQqx4GF989aZdO9vE0tta+fM5C7QQufcn0FIAe1/ftcROVmfYrFiWXaGyQFzgEjIz/hTzLI4c RR/MjhTv4BGASR69alGdoyMH0psRkMKGYKJdo3hDlQ3fB9KADMnnY2r5W3rnnP09KSTzQyshG0A7 lxy3HGD2qtFcfadQdYrlDHCMNGo53ZYHJ9Mjt6GrckayxtG4yrAqR6g0ACEvGCyFCRypPSkiiWGM RoCFHTJJ/U0xvJkt/KEgCODGpV8Hoeh9eD+VSgYUDngd6AGrEiSvIAdz43HJ7dOKdkZIzyKia2V7 tLhmYlFIVewJ6n60kjQ27PLsJkbbuCLljzgHA7c0ATEAgg4I6EUiIsaBEUKoGAFGAKRIkjeRlXBk bc59TgD+QFBkAmEe18kZ3bTt/OgAYyCVAqqYzncSeR6YqCSJzqMUqu+1UZXQP8vOMEj1qRSztLFM Y+SdiqeSmB1985/SkSzhjmSVFIdE2DBPI46+vSmAtusy+a0zZZpGKqDkKvQAcdwMn3JpnmR/bAWS RZD+7UnOG4z9PxqzRSAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKAIY52 e4ljMEiKmMO3RvpUcl4kYWR0KR+YyM8mF24yM+4JAx9akCraxJHDCzJuxtTHy5PJOT0pkU9tfrOg UuIZTFIsiEYYYPccjkEHoc0wI7uELNFcrNJGRIgYDLBwcqFx25bOfao7WO4MGxrVbcRBWhRZOOn3 Wx6H+Yq2XmN0EWMCIDLO3f0x/XNRsk8t0VljjFsuHjdZDvLDsRjGPxoAejXLSgNGiov3jnO7gdPx yOaklMipmJQzZHBOKfUNqIPssZtmVoXG9GU5DA85B9DmkAC3/feY8sjYYsozgLkYxgdfxp5EnnAg r5W3kY5zTzwKZHKJIVlKsgZd2HGCPqO1ADXtoHQI0SbQSQAMbSQQSPQ4J59zTGViywJ5kaKARIpB zj+Hmp1ZXUMpDKeQQeDUdzALm2khJ271I3AA49+aAJaqhEtpS7LlQrFp3YfKM5xn0qaAuYsSIUKk qASDkA4B49Rz+NPZQylWAKkYIPegBQcjI6VCu+EqhMku9j8xx8v/ANanxyo7SIobMbbWypAzgHjP UYI5HHUdQaEEokkLupQkbAFwR9TnmgCPy7eO980gC4lXaGOSSBzgelSGJDMJcfOF2g5PSncZ9xTV lVpWjGdygE/Kcc+/SgB9FFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRR QAVFHHCVkeILiY7mZP4jgDOR7AD8KlqBo5YxClqIkjVvnVgfu/7OO9ACuDBbeXAV8zaREJWOC2OA T1pHJuUIgnCbWKuQMkeoHoajv7R7yNIQYxGT85YEtjoQvoSCRntmpyxWVUETFWyS4xgfXnP6UwI4 XAuJYGuBI6hW2Y+ZVIxk/Ug1ENRia9jtbfy5jjL7JB+7HY479KubV3FsDcRgnHNUrNY94WaKFLtA fuqFJXPUDJIB+tAFsiXzsgr5e3pjnd/hTNs8kEQcxrJx5oA3KeOQM1NRSAgt7SKzjZLdNiHGEB+V cAAADsOO1SxFzEhlCiTaNwXoD3xVe7vRZy26vE7RzNs3qM7W4wCPQ889se9TxSLNEkiHKOAyn1Bp gPppkQSCMsN5GQvcio3uolglmVg6xbgwUjqOo+tRfZ5jJA6XLooYu6sqszAjhc9gPb86QBc3wt7m GDypD5v/AC0A+VeQBk+uSOPrSWFpJbee0sm+SWTcSGJHtgE8fQcVNbwvEJRJJv3SM69flB7ck/pg e1SkgdSB9aYDREgmaUL87KFJ9QM4/mfzp9MVyZXQxuAoBDnGGz6c549x3p9IAooooAKKKKACiiig AooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigApkocxsI2Cv2JGQKfVe8mmgty1vB 58pICpu2jn1PYUAWBnAz1pMDOcDPrVe4lPktEADcyRMyRCTaWwBnDduSOfepATG0cSxyMm3/AFhY HGPXJyTQA7yx5wl3NkLtxnj8qJZUhRmc8KpYgcnA64Held1jjZ2OFUEk+1MZoMJcOUHGFduODQAh EV5bA/MY3AYdVPr9RU1QwH5513ysVf8AjXAGQDhTgZHPXnuO1EPkxMbeN/mXLlS2SMnOefegCC50 6O5uUdlGzYwYZPU8AgdP4mzkdxVxV2Iq5JwMZNLTI3ZwS0bR4JGGxz78GgBk9yLd4QyOVkcJuVch SemfxwKLi1huhGJl3CNxIoz/ABDpU1FABRTHZw8YWPcrEh23Y2jB59+cD8aElSXdscNtYq2D0I7U APooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAooooAKKKKACiiigAoopkkMcpQy IrFG3LkdD60AHmDzvL2tnbu3Y4/On0UxY9sjvvdt2PlJ4X6UAJDKZUG5dkmMtHkEr9aivreC4tv9 IBMcTCXgZOV56d6nCIrs4UBm6kDk06gBFIZQw6EZHGKaiMruxcsGPAI+7T6KAGRxJEX2g/O245JP NPoooAKKKKACjAHQUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRR RQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAFFFFABRRRQAUUUUAf//Z