Technical Support - xsl-fo to rtf conveter for .Net
Devster Anothony <[email protected]> Wed, 29 Jul 2020 06:09:35 +0000
| Newsgroups | gmane.text.xml.xfc.general |
|---|---|
| Message-ID | <CAOZGFQ+2PGj1kNTfcuuXEZ5A2p_FQgMEbCnK3Dv363XD9Tt3UQ@mail.gmail.com> |
--00000000000018630705ab8e678d Content-Type: multipart/alternative; boundary="00000000000018630405ab8e678b" --00000000000018630405ab8e678b Content-Type: text/plain; charset="UTF-8" Hi I am currently evaluating the xml mind xsl-fo to rtf converter and came across a bit of a strange problem . I would really appreciate some support to verify if this is a limitation in the product or something I am doing wrong or a technical limitation in the rtf format. My requirement here is actually to replace a text (basically a placeholder ) in an rtf document with the converted rtf from a given xsl-fo. The problem here is when I try to replace a value in an rtf with the converted rtf where as if I directly save up the rtf in a file without any conversion the output is as expected (with the expected duplicated words since this is an eval version). Before purchasing the I would really appreciate it if this can be clarified for me. Content in the attached Zip is as follows, 1. Program.cs - source code for the implementation 2. styles.fo - a sample fo file that I obtained from the evaluation zip package 3. WithVariable.rtf - a rtf document which has a text which is supposed to be replaced with the converted rtf from the converter 4. The output rtf I got when I did the conversion (This contains the problems where the colors are different and text is meanigless) 5.processedDocWithOutVariable.rtf - the output when I directly used the converter without any replacement - This was perfect :D Looking forward for a response ! Thank you ! Anthony --00000000000018630405ab8e678b Content-Type: text/html; charset="UTF-8" Content-Transfer-Encoding: quoted-printable <div dir=3D"ltr">Hi I am currently evaluating the xml mind xsl-fo to rtf co= nverter and came across a bit of a strange problem . I would really appreci= ate some support to verify if this is a limitation=C2=A0in the product=C2= =A0or something I am doing wrong or a technical limitation in the rtf forma= t.<div><br></div><div><br></div><div>My requirement here is actually to rep= lace a text (basically a placeholder ) in an rtf document with the converte= d rtf from a given xsl-fo. The problem here is when I try to replace a valu= e in an rtf with the converted rtf where as if I directly save up the rtf i= n a file without any conversion the output is as expected (with the expecte= d duplicated words since this is an eval version).</div><div><br></div><div= >Before purchasing the=C2=A0 I would really appreciate it if this can be cl= arified for me.</div><div><br></div><div>Content in the attached Zip is as = follows,</div><div>1.=C2=A0Program.cs - source code for the implementation<= /div><div>2.=C2=A0<a href=3D"http://styles.fo">styles.fo</a> - a sample fo = file=C2=A0that I obtained from the evaluation zip package</div><div>3.=C2= =A0WithVariable.rtf - a rtf document which has a text which is supposed to = be replaced with the converted rtf from the converter</div><div>4. The outp= ut rtf I got when I did the conversion (This contains the problems where th= e colors are different and text is meanigless)</div><div>5.processedDocWith= OutVariable.rtf - the output when I directly used the converter without any= replacement - This was perfect :D=C2=A0=C2=A0</div><div><div><br></div></d= iv><div>Looking forward for a response ! Thank you !</div><div><br></div><d= iv>Anthony</div><div><br></div></div> --00000000000018630405ab8e678b-- --00000000000018630705ab8e678d Content-Type: application/x-zip-compressed; name="XmlMindDemo.zip" Content-Disposition: attachment; filename="XmlMindDemo.zip" Content-Transfer-Encoding: base64 Content-ID: <f_kd6yxrdk0> X-Attachment-Id: f_kd6yxrdk0 UEsDBBQAAAAIACQr/VCBfrslrwMAAJ8TAAArAAAAWG1sTWluZERlbW8vcHJvY2Vzc2VkRG9jV2l0 aE91dFZhcmlhYmxlLnJ0ZsVYTW/jNhC9B8h/INzbtgkk+iNOixyKxRYNsE2D7gLdAy+0NJTYSKRK UXGMRf57h5TlVRLZlhVnaxgmOUM+Dt88jgR/ZcaKkHFVSv8TFUlIp5TFIERwevKVCa2sXWSnJ0wE TBidc8VElHJTgg3IZ5lDSW5gSf5ynl/ctJCJcinLsjXtVyN55p2UiVzHYFogTBTm35C815WRYByY nzlmwkKUbuZR8mmVL7SDeXSBRTrTxkfmphuIQ3rBEgOg6HTKFlkFNKRrV1A7Am8Ouoy4Zm12qzsd 4eV6hes4F7ZPoZqNG/O0sQe1fdo4wotZ7ZnMveNy1hVTSOdr83wdUhhceM/kogGarVeMaR3tJOg+ xmbnS9ocgq4P8Ywk3PXZ7huoDbEvyWof3adHKqFd+45VJZjC6KJ0Q9dRPAcSGeBWm0dvsasCxl5u peVWRvc8I1/++JhLFZMvnz6e/fYnykPdg7EokA/orXCWVuRDLH07O6fnwaPf+dFph0dSJQUTXl1W Lf5hSxnrZWRNxpR+yLi1egUKp5YQ2RjbIknLBxXO5uM59peuj+mdoSfnJrF+PB77waI9yHAwxzy7 vqn7uCYFjhpf1QOhtd0MikRFeKNcG0PkDNzEnpiMS+XvWEknLBL09ORzKkuCX04WmY7uSMrv8Vjk QUQ/O07PSrvK4Gr0O24mlSLh6Lw+PkL2AG6jypeot7eGJ4YX6eicXFvigkYcXKbIOsMdwFJlUsG2 QN/jxR9tX4zQ8avgpd0FP5icrZQnhA6nvAP11oDQJkdxQjzybCxTPNNZWfAI3YWB9XadOzDHzQ52 8fN98tgjEPfZn23ZEQS8RbZdapS2KRaX/WlPjp32Rkzjw1DxW8P+EG5DvraQH1YWZAuWdsJmQ2Db 0Y6PF+0GNnpCgngJe2DGvsHSQ2FR/SENgn1y21MJeFN8/TXBh6KxZ/gwBGWvRhQ3/pHQdzQo7JBj 3T1JQtSRhAFsLVpKTDpzC8MF3qlEaKIdDLtbiYfD9q8hb3Lbb6p8AfhORl5xkbaRveqDj9Kfz7+D 8gfq/lnKRQd55rXk9UzOgAu2qyYfD3/rlWjjw3D8nvwMvhw9+RmMP972unxzcxT8yf74r99Sn/BK /XzjPzou/gpsu77ePS0g1f9RX32BcpMM1GVK+Qm49GpkTQUvA9hZIP+WNtWV3Yn4E0ECyMZKlrrK Yv9OL1UFxP09QzJe2t01dm8h70dUz7s2GL9nIg7X0mHxD8bvVUu7H6TuXwlv/A9QSwMEFAAAAAgA JCv9UBV8ORM5JgAAHLwAACgAAABYbWxNaW5kRGVtby9wcm9jZXNzZWREb2NXaXRoVmFyaWFibGUu cnRm1Fxdk+NEln3viP4Pit4Xhl2a/JY0BA8DCztsAEssxM486CU/y6JlyUhyuWoq6r/PScl2WS6r ylW42ZiCLqdSypOZ95577k234K5o+0AL7XyodH1FCZOFrrty+GVXV5RJVqzt+ETgVJK0iC1SdH23 CM7YRexU42XVTC4X5eTSlPvx41yc79rBD1f9wi/9/t7+KnjycGE7cleEpu57U6FBCuC6MilC2yx1 XQS70G3ne/Sv2t/YXfFpsdJ10/mEMPyjCCeSCPxhaIn7X8ql75If/Sb53zg8Ph501SdD//0X92/f YA4uXjJJBB8niZPh+v5rvTRtqZMfdL/44j4CpnvAblN23dOAYVgtG6B3gFUJxO3yKqzp16YtBvd8 ZHtgOmcOpqMfd7phf4vyYEL2Msvx05ZLvi+vFv2wHXOIzv+A7cBdZb2b8EXMevmEo7seppMfd7qd ux4mVC9z1yzRR0c94KZ/wEbEHBsYz8ZpkiOc5OtvTrlAzHmZRf+fBrptTyKpGSSq6AzSf7Xef5jZ 4JwVqWIzaL+sT68rm0NK0xmkT/7qTes3fzoJl8/CzVn+k7+02pT2MdywUzknizRTM4BfAaS0p1Yn 50SPKj63uv8rfV9rdPqTG+bZ81w7zCIg2i43Zc+Tazrytt1O+TyXJgMHIm2HPk+cyVCwZhyYP++H ycDRCbut5s8bfjL60Oojr+iDmad6dGjmMUNECw9DxNyQA/tuh2xNK+ic7B2adhyzteoYj3SuLji0 6zhuZ1JBs7kx+9DbjdmF3HZgPjvw2Ba74BoHMjI38MCJ48CJ/wSjs9vjxzMeu25S5MypzUuFeQI6 pzkvE+lHFRmdJ+3LJPsYl83ivkS8H693ToleJ+UT6Dmpeq2sT8DnapvXSPwEeF4nXyX3w8oPi2h6 KTpPQC9I50NcdkE6T3AvSOcJ7mXpPIG+NJ0n4Jek8wT4wnS+mx7Q2Fw6epxhhzPYQyUzQZnLTY+T 7hZlm3oPQfh8ujnOwiPIQ4UzgWGzMMdJeYQZUvOjLfG50uNxnh5hJtl6gjRXkTxO3Fukw/Q9QZJz SI8y+Yg0yecTpPmK5zi1b9d0nOAPz+H8Uoo4Ab2gIh7iigsq4gT3goo4wb2sIk6gL62IE/BLKuIE +MKK+OhbntnT8UvpPAG9IJ0PcZ843b6YzhPcC9J5gntZOk+gL03nCfgl6TwB/hh0PvwWUV6KzhPQ C9L5EFddkM4T3AvSeYJ7WTpPoC9N5wn4Jek8Ab4wne+m31Cr8+vVw0r1Yfz5lepBjbofnp5fo06q 0wcANgvAjgAmdekDwPl16XFF+oBxfkV6XIs+YJxfix5XoQ8Y51ehp+rPB5xLKdwE9IIKd4ibXVDh JrgXVLgJ7mUVbgJ9aYWbgF9S4SbAF1Y44NumatreVF8UrXekuIK/a1KYau3J4y4m5Rdv3xx0o2N/ 40T3CBGvjkBOdB89OwMxM+EIQVl22InLp7pH5Hh1AuKom2y3ve+eATmekuZsewON4UbOzrI0ib7/ NL70YBerZHB+/BvSjrFkd2OlceO3KimqkhQt/nSaKvyuGCqkrlquq54Wm9LZvlrptti0eoVRGt2F 7la6Wi10bNTrJUih131TaPfruuvbeOoGIFZSxV9lr1ckAcuLuvkNJGuWTe+Tu6LrbyvfLbzv7/64 ZRRtX9kFeN/RpNCDWVJ8wi6F3r2WgqX07fgQmZiu2L8wcvAmib1qSzd01KuDe+NFgl13tb/pAdT9 Fpp2qXu0Vm3ZtGV/S5IfY1c1OgtrwmPaubIvrz0e6/yyXJTO+RoX6xpNv+68OwCgyX+Otkh+0q2+ gm0WybdNPbxv8Cnm7jtK8attNq7o29B3fytdv/iK42KFiSpKsm2zfWiGanc/9PuW2bdatAxMCsKN n/3tyqOvu/ZtD3VAy7Su3X1W20+z/Wy3n+6q2rd2fYvt5/WzxMTe/mU5MTKC0ic8PNIi+UWbykNm Y4b4tGg7OM/ALrFBWcpEhiJhuOCSZRkOkcOFkjzPGQEFlqDb4qd2/Iy84KJYmvbDV3Hz28bPa4N2 h+mqb1tt0XZltwKtaLGsftDt1fBsu2/B0P9tcS8a/bsaK++pEOgv6/77colGrdtbtCjmL+vQ3BVw wKJpk591tyj7hY4E7fwHjfvNyre6P3Uv7ti2Xvflsrht44sVxbJJC3fL8mLRyjidAEDrr595AqTs yqZmaHqHvi7apW6gfle+o2N707Ru1z8kRHnQ3gxXgIE48/shUG+WVd1FT9yNTZos+n71588/7+zC L3X3flnatuma0L+3zfLzJoTS+s/jLJ8zQvjQWlbRrQVE2LcbyhhMOLQXsbbAVmDuajQsWu2+1e9b ZmhdrfvetySys/O2T8a4aDa2R+CFvja/FtrXzjUW4avth2Vz7Tsytkc56kvwt3BNDVVeGu+62y6+ 80Zh2+q2qa+XFTm4i7C5crrXMdkEoPprEACA1yh20e9hD1p0i2azqrT1i6ZyfVS/orxCDQKy33hn gY5BMayvfVkPI2/iLHEYGr5tm7ajcMBNheU1t77GrvzNqlu0fY1uhHlbdStbuBpOqDvjDHoR99Zj S2vsGxvrFtr5Arz7R9y7u1oO/EVjMTxIM+zq6vqgjUdLPDFYFXcmV4u4NDoMiA0s51esR9euuC79 5gM0kA6tzuoKCgBXXg1y5rXbNkPT9JDt6rbf1GXto2v27UW/RIh0K2yiqhc9pArbKqADVW90VUOE 6lFoCwzBDBZXm+ECjbaHelY1Yhk794BAa9OuIkJX61XfRCkqa+urCkBVswmlrxC1DvAQztVqXdse G9JdqfcoUUZarHgvMrXfABEZG7c7THKFjBJ1NZR9XGgdDd7fwu5V2fW4j8XW0Jce5yIfF+crf41u e9Ot+qhpUAZkhm4T+330qQ4WIRVXrcPw8Bq8rIrF8EQ0XL+6ilIPHtprPdiqx2rjoNBGg8SOa93f mJviQ1uvWmhsX1iNgAThKtgxicwpEY+rmIKD78moqhsQOSz7UFYIpIQJSe5j7EN61q3vF23T9/Bp UVYB9bDVva3q9WoIOKwHqo2oc8ku/mJa8TekgH3rhW/9cDv2RS/wmMTi42OqsvDQEKFJXMYKumer a0QP0pZtl7Gj120fr8tBZlMo3KpeIJNgwKrub3qdvB8FaTeYDYOxlidHx32fHs/Rct6+am6BVvXs 3PvRf5qOlufPbJJP7udg1FmL2BvgKah0gDrPEU/hZGct6Qyg/HcsaMg0LcSo0mWdbMn7XI31r1th 3R1OGMVtnHI6BWqBw9ppGBRfUD9+J314CX04o4+vggMvvgs+PUCT44NzPPAB7ejbIZL8pS1R78eb rAjLxqGueLg7nMFp8nWzbkuIEcCGJ3E27/2w7u3XOMnPt0vTRJixUNqewd++2R8z06PjLmXTg/f0 WDpzSD9x8N7i57uzcL499uZHUA/H77Fb7vrJ2C/3J+JUjXfEePLN1ak1xfPw2J1tl0TBoHhHpDsg tR3Bx5MyKqrT29jPfOpsPZn78DR+BHX4PcLMLbJzT6yCx1yDVNniALzqBgVCI36xkgx1btPeDz3D YWqgG4K8L5HsquTvP3yPytUlf//5+8++/R/Qo45HLRDkG9xd46mmTr6Jp0Z8qvfsPbkfZo5RH7RF xbYa8t22HnyoD6cV1pCaolCg3LmpqYp5f3W1iW24V+HOUIAO1wi4oQY9vKhwkcltwTq2MSbWQL69 HS9iFbS/WF3VsRSMn1D+rUINhokiNcRYx0RhA3v75pdF2SX4VyemauyHZKGvsa3kJtg/R5t+NnyX 8OW7v2Kysq4T+u79uH1AngF8iFo+Rv3pp+3R+t375Ls+iYsGDobVydbDJ4BRvSDtzy30awT+u/nB gHa/C77sn4J/tXFmTX6VsNeb/ATqT63fnk68ezdYY4Pzof9sqNe/fLdq/Xa6kzMMVdgT1sXPH+PH MxYSf573dnliEf5jeDu6BpU0atcz3H51abfvyMRfhop/R9h/o3PI3+H4+jJZKA9g2UnY6jWwh6vl l1vtHtZOjBAew77QYw+w7KWwYD9lhDxHt2eUYPe95igDQ+X72Vj2fvmOYeJ/T9injKz612zrw8QJ 9oQTXmEtc8DEq5O+9a8n+Ekm+t1qXw37NBNfDnu+hnyUaP9xvTQ4fbvkdwTSnLFvz8EH9bPsD2D+ K3l/5PJwwnjt7zXemc55RYA9pcmXw58NiUN8/3r8M+3z6uA40z6vxudz5fKPP14EXzy//u8+Jj/9 7+TPg/3tZfFvfX+orx+mArL+/9DXQaDiQ60fZaoeHsDQL9/17do/XsCTAvm3sl806/5JxP9IYIBk 35tsmnXlhpq+rNc+iV/PJJXu+qc19lkhP89QZ8baq/HPdMTLufSy9b8a/ywtPZ1I47cSQ+f93alv EU9/pbf9G9BkBBnfeBj+tw7xr64SSYSJ/202FYQQhT8ZGX4YJcTnzpNgQghjH7WEDZ98vJZGcBWU T4WS8bcMUqR5SpRMuXTMp5lyymqbU2uEt5wTSvBQKrJgM+4lc0K/fZNbwzB5xqTPM2bTzNtUs9Ra YjMsXFBlc5cZplMpsZhUWMekEExnjFClLLMu5zykuefG85QZRwNJjbQ8z3KrU6F1CEwwhmm8oUak 0mnpAk9FcLmG16TK8oxSTTNuFdWShDwLwmjjjWUZT7M0IwJguZZMy9R4hT1iHYZxl/mcpIyGnGjh WNA8I8waLlPFVEaCgzm9dVg6dZZm3gCF8sxzmwvuUi8JN+rtG0Ookxl33nsZcphBeJYTgzXwwJXw 2gotOMkybrglOQznrc5CLmAbqrA3XJqcpUEyrwXDLJpaJ3MLS4Wc5ob4THowQcaveHXmPCOBEZNZ yiw30J5obBlsUCmsigm8MoGb3Gc5lm+ckrmyxjrs17DMp5Yr6a3FMmgIVCgSJA8+o9xxa7EMk4aR KyGyB3x5imfwBmygU8COnYQrUCX+mC3TQsrAMZtyFsCrbTuLRApKR2Zh/akPmTQOZqSpg72xMwpW wRNBy5wIHt2TOjiEsiwNKmOMGgdGePwW4e0bC7cSbQzsDHP7EFKdcxe89pkJuae58NE6KtdaE2W5 ZwLEs0ZlnqaKO5AzgMF5JrXQKZMEywF5SKYwL+YwkcBWEkc1h5kcp9RoKTKjOMklhVSQkGUuF/Ep pr1gSjgKDxPHsCDpDBeKMZEGneY0pTK4FMzL4tI8bIbI4EEi4JlLeYqt+CzozOYhgDWwkbW5F8FS jA/MeingFIWQyYWwCrcUVqAp4ip4Lrlx4HSmpNZOUO+IkQaMcyq40TfneFaZNM9V/Pp07Mv0+Em3 joZyYAaohGRhbL99c3gV28IBwONPCl1hO1XBZqxwBL5nUVXg09RpmqY5gRrAGQY0FVIh6K3R3piA lQmeW6oFhb7AonkArxGBnmecp9Y78BghY96+wX7QgCMtSYnLtJKQHJ9lkdQp9Ean8FvmtMiohaOs sh6YFAHm8zSjsLgRGQLNBZGDllxibZAKcBDMcEY6x4hTRkKqJKMevnBOesSvAFEgdVhBKlOfwZsp y8Ey3MRG4FDCePYS+xsVhErBEI6d4MfmbLS/mrP/2H775uGK053NvYWiYH3UgJPSwBiBQZ9E6nKE vMPeEI80MM3AsuBAcqMM5AkmcA4fWnpsFjkihT5pxzJYTzECNZIc9o3pRXkRrWSgyt4xmgnw1Fp4 HVKEaOfUQRtzwwNjOmiNB52UcEEeY4BaThTECJsVeZpiMqwpOJ8arA5zOFjeBumZcsIYS6SlJEcC w2J1jlTgA1gk4EzF4D/YQAdvOG5EZYc7GZVwvCC5wMQQQRVM/H/dBLAr9QbR6AQ2x0EIkgclCPcU 1zrKZRrjOfNYMeyZpYpC4T1UX+KDgqtgIUGyC8RqzT1CUHMBHjiSG0cU+qQCYSTlQiC6kZwkhbE0 jB3yFKaFhOU5xD93YDVDv0TaEshzEmKacqAiD3JpsDP4S0WySgiToZQK3MUkRojUcBjbQHzzNAqb hB4ETT12xSyjaVQ4rUA76/UoZ7CzgDBQSAgYnWO1USqlZTCkRPblaQwBiI8e+AvnwUNZkMQEiCCi VnIEDTKjN6lVEBpEJbaLBExBjRyBhtwIKKPAOUQ6ogzSi4yEZA1FhS5xxAZVDvqEnVvPnUXSlRZh CnsRrThSsOUiQEqR5zTLpEP0E9AUuRaEEdAMTgwLMj6fKRW88zRuLniWKVAx2iD+taiOtnOwPfI2 8qpKuQGYQjTKnLNUe5uB2UiM0BblvbBaxNeShIDM4zmdaVDfeKnjS00wODFWsXSIX+giEwK5xuQS RGYSlOOI50BpnCjWSGk2vH6iUWoQBA1ik+CXMplzGvxUmQhIVJR7POeR/VBkiZwyqh2KF0q5oTzV IqCUUTGkQOHIexKVEFRh5J/tnVuP5EZyhd8F6D/0o23AAJlkMkns044ulmFJK+/I9otfkmRSKqt7 qlHVLWtg6L/7C7JuzOIlk2oD613VQJrp6gxmRuSJEyeymuyC2tW5jvwmnl1LBSJAfKUNNUtyAbrs cK+gj2pspbI6L4qKkkOCdapFc2GdNZQHSLWnJvK30508vayqDduluryhWJIspKRrITeZL3OIhcQp kisXaHWIspoVSC3tamda3nK1hZE0eoQybbIqg1lcmmUVkOLvtlGVkfxGogjtteRzyqSU7AbgopFA qSulZuaJIkvqDBaFTURF2DTtilZ0KQvGvK3JjqZxXIYcR8GZlpUrOIhsRFFSObWhoBnUnOIfHWyQ pZll16mhpSa3LWoskzwyOu1VGUxB+DuT5jZNCE/bUIlyDR2mznaamlVkZSXYoEZT6Kg2MhZFkOus bJDScFdXkwtoniZtbd3VJfQulc2S/Y2jyFIFqD6kBMQmP0LnKtYgChqOEb2bACgKGkRGQuWgCEep dm1GjF2ZoJcMQELANJShBgFIRudkh0O9VFRANrYoP/1EgS2ntMIBGCtDzDCC5HKQdFaRHklNuUlr lBucjNClG4CBS8oihNOwKJRlgnbMEM6dQqUKhI2DnagKlIK8UnQENcyCRm3EubwsqzbpCqa0DTig BKkqrwrCDvVWWVka2T/SNkMYsgKdFYXrUjRp4rgyfUyf5Z0ybclmIsnQQ+CnKWshUYqP+IpqqCkZ cBIbRNfSMSt5XKaqSDWxcRX4zqVjIYAIcJIj7W9+MHBzCeEn6C/yVYMF3GPDuAyFljpDojSUHMp+ R/ZB7g0rkTv6ILpE9tNR9xGGsIiijsJjDTWDRoEq18CqyHUCSDMG59i2Qh8Qx7SuEIi835FoDVxO brYWCd3QpjhCohtwlUkHIaKkSwTzSAfy0In+TOFZCmaJi7QEVdfksjLWDliobqAXxiX94C4tdZ1k BJxtStNALtQOxVHxTosspmWzBbq/Ltosgx9zyruIjTKllZFsqOgP0V25oUVRFSxsLaytazo2LRUY bm1bKLFtK/Kuy2nX4AFEiqlziKIWdqvrPgAI2toY+ACuIq2SLnO0daJYpRfUFsmB/LOlEQGHpHMG yiA6BrWn4X26HHoB+MXSF0FLurOJcDRTow0Yx07A6jlXhKjoAbJcmgXaMLJSpmdjS4ecIRsbQpeg oOuK8JlEtKTJBYRdlgjY2sxS0UtQaDspBsi5DqTRO1YKdDWQL0XW5JC67GBH61LDMQ1CjxaMolLR MNJRao1S6lDj0BXbJKyn6MLYhRwNZWR2ZG/aiTxA8mZghaa3pmdAUxpStuqrRk5PbZFJKYTELhem RM0QvbYid2v2kEaV2klTraGGBAlMLpRQcwO0UsJkyauSQkn6wCTUX9R6XRcA1RVkMeCnksKXKSqs oTxkCH9UMn2sobXmXzRiZWpKOECxEk1cNRkEHUmzRtOEhCpQFYh2nLaOwgkfpSIQGioDpRF1gIIF HiZJQUPTCg5yRBAlIBOoghIL53UtnSjFDk7ORQLlbAZ9Hd182ytGVIKiF0KEuqQWJW7Q84pMp2oC uVxp6luGUCXORSU9UyUHCegOkUolvAse6d1wV3Qi+4LQyxyFvBUZT5GTEsUVEGK6AS+uSNAz/Kkk yfhSNwIqLV19VZEgFIIO/KZ0KGiIjPZFwREUiMyk0EKatvTflCHsMio3aUFnQz8FYOADpajqZD6s DzNRjACIylIAh0PGiuxAD6eyBlRCgxyrIPIa9kGl6opmtc1L3uxoTSuTUFhAOF0ohRCGzdkWR9qj WwqgXIG/GrfYDlRaWbdkI9ekcABC5AE9TCsBg5ErOWixKE1WSJ/UmkqjRgwNJ7mep4J3oKNgKtgQ 0QfCO3YKfgfWrche6dlzCoH0acS94FsUYBpvap4xSZ9FdWZFpVnZYrKgKiz/w8bKSYrqSumBUmXR f+DNosW0tN0IQ+p0KpmCHu/PyVRWcNlMt6BV0eUXtraSkThLL5PAy7Q4qiik2hQIX9pk5DFSPRNO JDYVpYWeklJi6ookMyhPyA6uhJ8piZ2oe80W0LWWbS6HY8QFbdhRaVNyEnUj6ocka4wpAAD0ZApE C9gs8j4/oHkARV+akiGUdJegWuWcBxyk0s9DpygUOqZWgW2rO+k6K1PVVFvafipiJ60V9A2GafdQ udLWku60ctJNt0YupyzVnVqrFGlai9KG0rUQpEKKdbYptXB0WyZU4Iq6p4zgQCgDBkksNbxB/NBB UffAdGFaFoBmpbdBuMuDqSCK/tQKBY7oExpDDhctKgD5RzhhWGRoBkOh8MmAitbPiuYEkaaRfqg1 FAOuIAyFakCtU+ZQ4F1VC+/BLWgckEbe0vZRfllpAR/AY3lNpgGGBMaGiVvW1VSEHAlXW6SNoeIh XBuWWcsz9BoYCUN6Kg0PkRhyVUtiGMN49ryV3gZOLEVKQACJ6/qzR1oCdq3CkuZd6FX0DzobXdSF 9/KsEFBXgHV4D43V2yrj9/KotFE3f3t6tnauMj5d609Y6NlSuolOWhA5zIK3WnQIvTPSCICUDCLE CRbkApjJik8/QW3lKMVGGjPrSPCSDp++txatWtUCx1YUDgoFrZmBVwueE+oFA0jwyhIo0SGQZ55o 0pMto0knDQlRIVTu4E96nVRLdudy3sMWMyuUraiN9B2oPfYJ4oZgmxZyFliXCdtYWloAESUoLMQ7 2qSkciS4bAz6jw5UDk1TI+c7CLeCDTCiH5KU5euksnKmRhjK1JbwEKq6S0V7OgE1GUIn8OkniXSN QntQM+K4Rl83iESrSTuwl7enc/XR7iPQFEpoy3m8/2IFN6+w0/q1NchZ7dJJ7fh1XgEL7EdNn+Ou zbl2ijj1IlX62NyeZI2zYi0T1la1drZ2fo13AcLsh62v6nrutraSNWYYr+D8oqfq4zi3km2s0a9V J9cY6OE/fTq1JP0uSPlVPjD7h+Entvu7xdyTfX7uP6VtaJeHK1P9ZCZDZRb0UkyURAaBrZTQqisE 1TnfdYWUJhowLSqY3JQRBvXQr1j+38gViCyjTCW4V3J+6RIiIZ/8QAQZPiBjqOWpYaOGNZAt9FGF nABSK03OnySzIJjmAIshMmS9gpFMv6aTHXWZuMj38tN3lXBFgSbnPTOsufeyy2BZ/hR8VyJMLS9c 7yEW2TBzQ2+R9j7lyOnhPaTm8F4/Tl3Gqcs4dRnXv8e1Zc09A5yuMXrnOoYVDO+pu1H3V8ruxmR3 Y/K7MfndGH03Rt+NKe7GFP2YkohLROthn85f9d9jJ4omH4/w3hOdk7kTJh+t3JbXfzB7/M/HY3t8 2T3ZX6jr8oV8josAc13Sf+ty2+r5neu9q+d3Tnc7n78837HM11X1P9dLul8a9/zycGORPtyOTx6u Yy+3S8+Orkajfzz9AEQqP6I/WvZgdV10Or+A6UuqP7zxBbO3vmD+9k7rt15j8dYXNG/vdPnWa6yC Lni2kh/4+yUYwWOrMJCObcJwOLbJN9joTR6FAWZsYzbYhG362KYK9OiMjmwMj5d9wzb/xguE7fjC BbLf7kQYGhYuEEYzCxcofrsTYaBZuEAYghYuEEcTpwdGDA9kCHT/bCt3Zcn9/Q9yq37UrPYDdsP9 Z9G2w41hUSbD7WOR3g3JeSLfoOkmuTzTo6s29lncDrreZVflzveHfffQ7X54PbhjpCPuw8/ucf/s HuRpLe54jJr7YnxwL6+HuHVf8HFwnTu4D42LMr8ByfUCca73dz8NP+sZNbU85GOLndy+v93hs3Wf EnGOXiAyPDNl97Jzcfv8ZJvDPsriZW+jsuNs9/XuGOudmDy8e318dHFU0dt9G7+NvV1YSRyZhBbB kVFY2RuZhBW6iehtcepkucm3k+0GF0+WGzwd9nuLpyfLTZ6ebDd4erIcPJ0sIem4l/1+9/IYRyyf Pe6PkqZxfr3f/fChf5hJ0FzXJ4vdXmPmKWMhFzxf4t2+/fjwfaxKuFhtkzb9znx2uikgauKR5RYU XmzjOqqxbWgTP20dl3XfoCmkXn51FWbTMPbg9Vq/RCP5vX18HTRBpIOf25e4ma4A+nJ3OF5g9Nsv EYmJb0URnO7IifT5On/clFe7OAj6Obd52pN5LBG/k3/EU8VXH5/dAaX4U5TVl3t5KJZrx9aTwFdq jOGXw/6yl9MGY8L/4un5R3vcxQm6z/fN65NE8Rv7HGX4ndyVEx/FL/7xye4eb4pG3N599f03Xz98 v38WDfslIYmauzd+t3952T9tsj81wX/3H67++yjDfuI/opw/fHza4vAfN3RkvaE8umGD1b7dYEUN 333YbeDc3vpf3Md6bw9t/Ly3z/KIt35vn54ji8uAQfL5v0nC6POC3vrf7WHXP3szxvKm0T2+1v/l mrjM+3Y/9FQxNn967Z8uN9T92EPikXEcx49M46pL/0xT+EW2NfDAc9JURXo7Mt6y5M8e7fG4Cz2k nbaNi/LYNraMjq3jOpqTrXxK3b0+bnP5bLzJ57PxRqf3j69PH45b193bblx2b7sJXifbWMk/to6T /IPtPx127aZQ9YZb4tQbbtva3nQLmHvDzeGJ++DpxjD0E8kJ07CPEMaGp0Kw0XDLXm46Mbsx3bKX G07Pbgy37GVvuG0ve9Mte5l9/uC6DhmxjchuzLfs6435tt2VYwj39Lw/2MPHDfN/8eh+sJGd+mD5 3WHfocbRYacfFYkzlwONRxetpkbGWwJO17Jpn8Uubr538iDo/ak5HLyc+SDyykaTE5yHfXd+2Lc7 XDvO6cOjkR2S9/1z/4TKP9wOKsZ98/BrHN//eP2M4jIwnRh4EdGXUWpiVO/T2PciG437xrW716fz vKetuYzNl8aq8Vg9NfaGqS8Di9mB3hXN1MCbOn4ZWM4OVL731ezQbHRNM96dz+3hp/uYm/HOXPTc 1C4aNT32/qLZ9MALPkMARJ/fyHlK6vs/h6WrQRCoZoYvY2vGaBlkM0YLaPN9n8vnP7ufd8fzx9vT H4fnnvvHmw8H5s3UGGT/+ro/nX9MTzLexn+W3xtwdDdWIYkzu98LOTQT2YVkmrFYyKlpi7nkmhm9 nGVzri8l3MxEC5k343pACnqktpaA3vC1BLwjuLAU9GYJS8Fwwp+xCADwnT8BAPZmCQCwZxEA4LHF GoC90WEA9l0PAbA3UQCAPdcDADwujKsA9oavATjbBmBvljAAe0YBAPYsAgB8508AgL1ZAgDsWQQA OEzezIwOA7DvegiAvYkCAOy5HgDgPA7A3vA1AOfbAOzNEgZgzygAwJ5FAIDv/AkAsDdLAIA9iwAA jy3WAOyNDgOw73oIgL2JAgDsuR4AYB0HYG/4GoD1NgB7s4QB2DMKALBnEQDgO38CAOzNEgBgzyIA wGOLNQB7o8MA7LseAmBvogAAe64HALiIA7A3fA3AxTYAe7OEAdgzCgCwZxEA4Dt/AgDszRIAYM8i AMBjizUAe6PDAOy7HgJgb6IAAA8W00d34zicTjpHP9Qy3fOP/Tt38RfDwa3pA4B0aso/j34qe9pQ Tc4ZYjkO0rv9/qeIn9S8XGWMy3e7+nG3789GPgYeK08vzjud/dNnlx8pux2Wj8N2+kmg/ih33KTn anbguBnKs9mBY9GZ57MDfQmR69mhYxrNx+nUw/X80QqENx5bzI1Np0abudGe++XcOM/7am6c77ye 9Un3fDG6rE7nBheXLB4bqDkDM22wGrYzP6Sh8bsaeLs+H8qZOeZjOm2wFtoZq4AYz/kUEu4Z50Lj rmLjHgzgq4G3UetxV5virjbH3bOMiPqdc6Fxz2LjnsXGPZhBrgZxVDI9UUzcs81x95wLjfpdqViP ex4b9zw27mOD0KjfEX9E3PPNcc+3xd2ru+tR97uqgLjr2LjrTXH3rCKi7vsUE3e9Le5FbNw9g/Wo +91DQNyLTXEvNsfds4yI+p1z47j3HdEo7kvhvhm9WENvxi1S+M24RQa5GXeSgIvEcTM8TATeGISJ wPuwneO9KAJv4zdjMB/Iq8EiXG9jOj3HWnBnrAJiPGMZEOxZ50LjvigCp+IeDOAZg/Wo+8IqNO6L InAx7osicDHunnOhUff1VkDcF0XgVNyDGWTaIDTqd9IxIu6LInAx7osicD7unoZZj/qdalyP+6II nIp7HIXPWEVE/U4+RsR9UQTOx31RBE7F3TNYj/qdalyP+6IInI37oghcjLtnGRH1O+dC474oAqfi vigCp+LuGaxH3RdWoXFfFIGLcV8UgYtxj/up7m8wib8T7v2TPbxsvNH0K3v88cXGPWPj3z4c3HH/ +LNrLwuOMR+W+7Ws9Nf+d6DJrz87vuwP7iFJ+6dUynMyh0d4Junp6Zq5/CKl/lmOmVJOZ3mqS13m bd5oed5lWuTDUzCzQp5IOfkqhiu3ifxSCpfYtE7luc3Tg6+vzCX9Y1M713VJlSSJ91TRyyv1/va+ Ifbd5Ymx919f3v8/fH36ydqIv+bX797/7b4mvG9Pf7u77/zVvX7f+7/d1+/eL780SqPohv9MnvTC Q35TSeGGrw1vmMqv0m/36p9Srufrvvz2jLYqy0p1aZsjWQrNSvOkKjKlU6fnrlsmZSPP3pdfLFHo tkjSOcXxl/KajcDG1/TT1v+SX28Zgf9/3svrrSKwwftT73F+/frr/wJQSwMEFAAAAAgAei/9UN0L OY0pAgAAJQcAABYAAABYbWxNaW5kRGVtby9Qcm9ncmFtLmNzrVRbb9owFH4eEv/BypORKmuP01in 0TImpCEQsLXS2gcTDLWU2Mw+gaGJ/75jHEJiEtFKM0JJzuX7ztWZlWpNZnsLIu22W1npkw3HoeS7 VL9D2Vz8gVD2mCY1oqo7CkZSLdlA32u1FQaEQV27pXgq7IbH4mTxaJOSTV+kut36224RPJtskciY xAm3lkyMXhueek1uUDKywAEfWy2XZMSlohYMxvHrmXCztp2zfcnVnS03ZMLhZa6nsOrrOEuFggcJ Lz+5kXyRiKnYJBiuE5Nb8iXqf3zKI3exPpVNmYFV1H0l/jiDN1Dos/WJxf3KTD5hEmsFCFQThuG7 gUaCgUSQqeDLXpK49tILRgv7RFi20lGnG9Is9iCwqu7RM4bvEfCrivUSuVlvdj8csm8C7lBr6ZGw E0QyQgKzn4ERPCUrnb/cEiV2FR0tGC5j8BYuBYFp+YdHKGvoCf0SwM8odVWxjQF0OlWnYHICnJ2R EITxcBRRzxCiNSC6U2yDa2b+5nELDQ3LejqFB8MB22Qw0CblbqzKnwxn8ar/TMBQoQv1Bb5OiA6e hPpaXPfI02lMxleOTbSVILXCLN43Y4Jfn2IYf8wHH9wszo57kXeBzfVxprC5NUiHqugQjo3rs9ue 8tLXLdRrL5Qwhgbsyh2Tu9PoE4J/jm5OqddhseMENq75xuhYWCuWiHRxj92EzJdbVC4HXlBvLUj9 Dfgf8hgHl2WlRmd0bO87/B/+AVBLAwQUAAAACAAAS+lQY/DxUUoDAAAGGQAAFQAAAFhtbE1pbmRE ZW1vL3N0eWxlcy5mb+1ZbW/TMBD+3l9hwjcgydoOQas1E0KamIQQEkPw1W2cxiKxg3NZ2n+P7aTv aRsnWQcSUVV1zt099nPPnS3v5nYRR+iRiJRyNrH6zpWFCJtxn7L5xPr+cGe/t2693k3Ax4JzQNKa peOAT6wQIBm7bp7nTj50uJi7/dFo5P789tm94yLGYPXQ6im8FsFsx02OxpT5zozHbsBnnMlpABHu Io1csgDC1JxSy5NxFH6ElzwDO8apNLJTAp4GUK9SGicRsRM8J+V7VJoxHJOJ9eHaQpvZHD4xFnPK 7CkH4LFi4e0stlajEQlgNVYjiKDzEPZjAE/qhNALyKkP4cQa9JW/HglJEXMwct7JQa8MoZNC5pIk OXN/ub+Kq8MZlENuVQQScEGQ5h1OWuJA8VtteONWZkOn0K3OYZldbZ2S35lUH1llT5CACDWgU7jJ dxDxHKmvMr9SMfYWExuGXtg2mrR7kG1vkzCN+OwXklIeZ6laAiwjOYFPBKuKQX3LewhpiuQHo8K0 9A3xozI47uhogrSPJuU04Fcs8FzgJCwB66FtvJzS8B6QLDzAlMkYTANSFlFGDnw/cp9YXvmyjF8G qTTVyynMV/xh5p8DoVAbRJlug1QSeGkBDIzysfEyzL5Q1Sp7LBDfQnkoqbDTBKs6SQTZm8IxLezE UKk5iFOIpJ1E6mqjqTr+LVmotDAOoWygHejj0qsYNhL30FDc90Di7UZaWL3sn0YrvTqBGlwOavhU UINGBJo2oiNQdQg0hdrsXeuOsXpSwAJseZTUJ5LBVQLoNRq8Uj9M9+MNiu5HvUoAOft1fLNFHOGr jgpM+dJOw0YqaFSxh1B1VNARVB0Cj0A9VxNtuBWYEvYli6fyDO2jZm11371b8DMKaQdev2EU9fy0 3cK8V5wj74zm25G36228mey7dwtuJJuuwY1obwdu3L333bsFN6K9a3Aj2tuBH5batQn4/1LbA3/G HXZJ4Fl22YMdRzkIUuwMTBtTdcEKIiPtEt7f2XpOwZitqNHu+YNCyDM4OY03ZTyZE7R+h3KeRb6+ Z6AsIygQPEYRTmH3DmNrlU9Vfxc+pJyrPyMt/I3FXxO82+ONRlZ/qzvi9eXzzhWz19Nj6p8aXu8P UEsDBBQAAAAAAJgo/VAAAAAAAAAAAAAAAAAfAAAAWG1sTWluZERlbW8vV2l0aG91dFZhcmlhYmxl LnJ0ZlBLAwQUAAAACACNKP1Qp1ThivUiAACCqAAAHAAAAFhtbE1pbmREZW1vL1dpdGhWYXJpYWJs ZS5ydGbUW11z3EZ2fVeV/sM8ev1g9fdHnEpVvJtNsrW7tZV1JS946Y/bHFgYzBgASTEq/fecBobk gOJIpDN21colTqOBPn373nPPvaDGH5thKrwJmUoX+ivOhG5CP7bzj3S44kKL5jotTxTJNbNNHbFm nMZtyTFt66RZLrv96nLbri5j+7B+2UvK+3Gh+Wra0o4e7j1cFWKPF2lkH5uy76cpdhiwBri53TRl 2O9C35S0DcNIE+YPw8/iY/Ntcwj9fqQNE/jPMMk0U/grMFKffmx3NG7+Sreb/6rL6+MldNNmnv/0 /ae3b7CHVK/ZpIIvm9TNcP3p92EXhzZs/hKm7fefKqB9ABxv23H8MmCZrRUz9D1g1wLxaF4Hm37a D80cnl/ZH9gux5Pt+K+73Xy+bXuyoXid5+Tzntv8ub3aTvNx4im6/A2Og3C1/f2Gr2LW6zdcwvW4 nf51t7sP1+OG5nXhOkv0JVCPuPY3OIg6xwYh3bLN5gnO5vf/9lwI1Lkoixr/54HuhmeRzBkkbvgZ pH8fiN6fOeA5L3IjzqD9eP28Xe4ckrVnkL75D4oD3f7uWTh/Fu6c57/51yHENn0ON59Un5NF7swZ wB8A0qbnrNPnRI8bec66/25p6gMm6dkDS/d1rp1WERDtvja5r5NrvfJuOG75dS6tFs5EOi79OnFW S8GaZaH/ehxWC5cg3B/Vf93xq9WnXl94xR/dvNajUzcvFaJ6eF6izi058e9xydG1ip+TvVPXLmuO Xl3ykZ/rC079uqy7d6ni7tyah9S7X3OfcseF/uzCp764T65loWDnFp4EcVm4ip8S/Ozx5NMdn4Zu 1eScU5vXCvMK9JzmvE6kP+vI+HnSvk6yn+KKs7ivEe/P7T2nRL9MylfQ56Tql8r6Cvxcb/NLJH4F fF4nf5Hcz5afNtH8UnRegV6Qzqe44oJ0XuFekM4r3MvSeQV9aTqvwC9J5xXwhen8cf2CJs6Vo88r 7PwO9tjJrFDO1abPi+4R5Vh6T0Hk+XLztAovII8dzgpGnIV5WpQXmLk0f3Ykea71+LxOLzCrar1C OteRfF64j0in5XuFpM8hfVbJF6RVPV8hne94npb2o01PC/zpe7i8lCKuQC+oiKe46oKKuMK9oCKu cC+riCvoSyviCvySirgCvrAifvZbnrNvx6+l8wr0gnQ+xf3C2+2r6bzCvSCdV7iXpfMK+tJ0XoFf ks4r4F+Dzqe/RdSXovMK9IJ0PsU1F6TzCveCdF7hXpbOK+hL03kFfkk6r4AvTOeP699Qm5f3q6ed 6uP6l3eqJz3qw3L78h511Z0+AoizAOIJwKovfQR4eV/6tCN9xHh5R/q0F33EeHkv+rQLfcR4eRf6 XP/5iHMphVuBXlDhTnHdBRVuhXtBhVvhXlbhVtCXVrgV+CUVbgV8YYUDftp3+2GK3ffNQJk1V4h3 z5rYXRP7fEpo/f3bNyfTmHi48cz0AlGvnoA8M/3k2TMQZzZcILhwp5O4/NL0glyvnoF4Ms2Ox36Y PgPydEvuxfEGBvMNL17kaVZj/2390kPaHjZz8Ou/kI5CbO5vHAJu/Nxtmq5lzYC/Y+AGPzuBDmns dtfdxJvbNqepO4ShuR3CAasCppswHkJ32IY66K93IEW4nvZNyD9dj9NQ37oBCEu6+qOdwoFtwPKm 3/8Mku13+4k2H5txuuto3BJNH387M5ph6tIWvB/5pgmzWyw+4Zcm3H8tBaZMw/IQW7muefjCyMk3 SdLV0OZ5oj+c3FsuNjj12NOHCUDjz2U/7MKE0WFo90M73bHNX+tUtwQLNuGxkHM7tTeEx0batds2 Z+pxcd1jSNcj5RMAvvnD4ovN38IQruCb7eaP+37+vsG32HsaOcePYX+bm2ko0/g/bZ62P0hcHLBR x5k7DofHYenu75fpYRQfRgNGES4F4ZbP6e5AmBtvaJigDhjFIQ/3n93xMx4/h+NnvuoeRvdz2+Pn zVeJibP9w3JiYQTnX4jwQovNjyF2BJmtFeLbZhgRvAi/1AEXViiHJmG+kFo4h5fI+cJo6b1goMAO dNv+bVg+Ky+kanZxeP9DPfxx8PfriPGI7bo/DiFhnNvxAFrxZtf9JQxX87PDwwiO/lPCver0/+xh +cSVwnzbT39udxj0YbjDiGP/ti/7jw0CsN0Pm7+HcdtO21AJOtL7gPv7Aw1heu5ePXEaKEztrrkb 6hcrmt3eNvlO+GY76LqdAsBAN195AqQc230vMKSMubH6pd9D/a5o5Mv4dj/k+/m5IOqT8e18BRiI s/w0J+qHXdePNRIflyHfbKfp8E/v3o1pS7swfrdr07Af92X6Lu137/altIne1V3eCcbkPNp1NawN RJiGWy4EXDiPt7W3wFHg7m5xLEbDw2h6GMV5dHU9TTSwys6R0rRZ8mJ/myYkXpn6+FMTqM95n5C+ Ib3f7W9oZMt4kaOpBX+bvO+hyrtIebwb63feOHzb3e37m13HTu4iba5ymEItNgWodAMCAPAGzS7m Cf7gzbjd3x66kGi77/JU1a9pr9CDgOwfKCegY1FN6xtq+3nlh7pLXYYBDcN+GDkC8KGDefs76nEq +nAYt8PUYxppPnTjITW5RxD6MeaIWeR9IhzpGufGwcZtyNSAd/9bz56vdjN/MdjOD3KHU13dnIzx aIsnZq/izupqW03j84I6gDk/wZ7Q5+ampdv30EA+j8YUOigAQnk1yxmFfByW/X6CbHd3023f9lRD 8zDeTjukyHjAIbp+O0GqcKwGOtBNMXQ9RKhfhLbBEuyQcHU7X2AwTFDPrkcu4+QECIxuh0NFGPtw mPZVito+UdcBqNvflpY6ZG0GPITzcLju04QDhbENDyhVRgZY/CAyPd0CERUbt0dscoWKUnW1tFM1 tK8On+7g964dJ9yHsT30ZcJ7EVXjqKMbTKcP42GqmgZlQGUYb+s81ZiGkpBS1epQ5oevwcuu2c5P VMdNh6sq9eBhugmzryZYWxeVoTqkTtyE6UP80Lwf+sMAjZ2aFJCQIFwHP24qc1rk46GW4EITW1T1 FkQuu6m0HRJpI5Rmn2ruQ3quB5q2w36aENOm7Qr64RSm1PXXhznhYA9UG1mXN/f5V8sKfWAN/Ntv aaD5dp2rUZC1iNXHl1KVEKE5QzfVjAN0L3U3yB6UrTTs6sQUhqlet7PMWijcod+ikmDBoZ8+TGHz 3SJI94vFvBi2fHF1Pffz6yVGmdIv2lth1H1174fVv1uv1i/fOW6++XQOxrzIiAcHfAnKzlAvC8SX cNyLTHoBkP9/GDRXmgFi1IW23xzJ+7Ue6x+3w/p4umEVt2XL9RboBU57p80//2Gf/uXTx+dsfX7h sc/aLM5d3qvmL4/XArnRTMX6DVCuGGMGfx2b/wjUB/KZWImllGWOJ7Qv9VMu1zoqaYohq4yuP3XR ynrLjLZSZ0HWmWwgbp6nqChJyTjDQ1a5kpwkLbIKb9/4FNFWMCc0eSeSdZRsEDYllhwMV9wkn10U wWoNY6xKeE9WSgQnGDcmiZS9lMV6kpGkFTHzwmzUSXrnU7AqhFKEEgLbUORRWZ2DzkVaVbIP+e0b bZx3nAfuZDI8aFa8KyqGSDEJJ62zjimA+aBF0DaSwRlhRxQyO/LMCl48CyqLEqRjIkWprRHGsZLh TkoZpvOcuKMIFC4dyeSVzJY0k9G8fRMZz9rJTES6eLhBkfAswgZZpFEUkgpKMudklIl5OI5ScMUr +IYbnA2X0QtbtKCgBHYJPGXtEzxVPPeRkdMEJuhKpOAyCVYEiy5xkWREjanO1iUVgyzF23smE4uM npyH+TEb7U2KKeO8UTiySRpNKcEMXgpXhhUtCzkus0wJZkRbFq6Uyh7w5Us8QzTgg2ABu0wy1CA+ D+KRacUKcCxZKQp4dRy7SqRiQmUW7LdUnI4ZbuQ2w984GQerEIkStGdK1vDYjIBw4WwxTgiOpowj zDmq8vZNQlhZiBF+hrupFBu8zKix5GLxxL2i6h3jQwjMJElCgXgpGkfcGplBzgIGe6eDClZoBnNA HuYM9sUesRI4aZZ5kHBTlpzHoJWLRjKvuUAUinPZq/qUCKSEUZkjwiwLGKRzlMqgB7clWM8t1yVb MM9V0wg+Q2bIopHwIltpcRRyJbjkC16Lq49S8qRK4lhfRCKNJkIZpIxXKhncMrAgcORVIallzOC0 MzqErDhlFnUE47IpeYnNSyJrovXecOOOiuHC8smPgYZyYAeohBZlGb99c3pVxyoDgPDXQlfEvarg MEllhtiLqiqIqc2BW+sZ1ADBiKCp0gZJn2KgGAssU9InHhSHvsCjvoDXyECSTkqbKIPHSJn49g3O gwECmZhl2QWjITnkXCW1hd4Ei7i5HJTjCYFKBs15QjjIkLeOw+NROSRaLsqDllLDNkgFOAhm5Khz FiybqCFVWnBCLHLWhPxVIAqkDhZYbckhmlZ4sAw3cRAElAnpXuP/aIoyFgyROAn+JC8W/5tz/l/G b988Xkl+73NKUBTYxyM4qSOcUQT0SdnskfIZZ0M+8iKCAMtKBsmjiZAnuCBnfARNOCxqhIU+hSwc vGcEgxppCf/W8mJIVS9FqDJlwZ0CT1NC1CFFyHbJM7TRR1mECKjoeDBrjRD4mgM8SWYgRjis8tZi M9hUMtkI67BHhudT0SRMVjEmphNnHgUMxgaPUkCo2pB14gavE7DAosmPEjeqsiOcgmsEXjGvsDFE 0JRY/4+aAnZZisjGrHA4CUIwX4xikjiuQ5VLW/PZESyGP501HApPUH2NDw6ugoUMxa6wFIIkpGCQ CjzIzMfMDOa0AWE0l0ohu1GcNJoRE+Ds4i1cCwnzHuLvM1gtMK9RthTqnIaYWglU1EGpI06GeJlK Vg1hipxzhbvYJCplo4SzI8TX2ypsGnpQAiecSiTBbVW4YEC7RGGRM/hZQRg4JASM9rC2SqVOAo7U qL7S1hSA+ISZvwgeIuSKZrFABJG1WiJpUBkp2mQgNMhKHBcFmIMaHomG2gioaMA5ZDqyDNKLioRi DUWFLknkBjcZ+oSTJ5I5oejqhDSFv1gwEiU4SVUgpahzQTidkf0MNEWtBWEUNEOyKIquzztjCmXi 9XCFhDOgYvVBbb5C9V2G71G3UVeNlRFgBtmovRQ2UHJgNgojtMUQqRRU/eWHUpB5PBdcAPUj6VB/ dQKHs5iMsHP+QheFUqg10WsQGc0tqj3yuXBeN6o9knXzS25Aq8GQNMhNhh8mupwD+GmcKihUXBKe I1Q/NFnKc8FDRvPCuYxc2qAKWhlTUwoUrrxnVQlBFcEMalehgvyGP0tGBYKDcKUtalbNBchlwfEM hZyCFzIqYzxKDhKsiIyeC6tlQnmAqM7ShPwtutT/R9JHi3CJohKKJZIFKUkZ4lb3k4RmgZFAcqlK rYKmLMKCWktLJJsxRTFAkTT6EZRpK72EshCX0oNS+MxJeFvzGy1Klb2MfObYFCU7gbjokcBScrVm KiaQJVFCRaEmtYsInBeTa18Kg7E8R2RHSgQY5Dg6OJthuYAGIRvRUaJyaouCZtHNCQwK1EByGRB1 1FCnkdsB3ZiseWQ1n7syKAXcXyxXgTO4JydUIqUhh5xC0ahZRjpfuYEajUKHalOfRUegtHQJrTS0 q0TkAnqexHOIJTrIe61sAdmfCEUWVQDVBykBYau/qCMPG2oHDY2p/S4DoVDQIGRIKAUW4aCodlnC x+QY+iULIqGBSShDCQ0gMlohOwjdi0cFRGCNe/tGgFsktMABoFgSzQyeQHIRRFp6pAeLKDc8onOD JqPRxdsAFNihLEJwEoxCZ8nQO0o0zkWgS60UtgR1QlVAKVBe4I0gQlnQo6Z6OOWcz6wYbBkSeIAS JLzyBm6H9HrpnK3xQ9pKNIawQEtjqHD0pIyAjPeYOcuLsNkhmGjJ0A+BP8nFKqIoPvWs6BoiSgY0 CQHCW0vBrshjx4XhGr4hD36r+sYCB6IBR3Lw+Z9YLbTZQfAZ+i/kqwYXcDwEDDAotKgzSJSEkoOy X5B9EPcES+r3hiB0rMaTUPfRGEJFBOoodCyhZuBFAVUuQVXRrsOBeBmD5oTs0R/Ajzx6NIiYL0i0 BC1HbuaAFjrhNYXgEp3AK1nfIGpTUljlPFoH5CHV/pNDZ1EwHY6IVwJfkqqWwXaQBdUN7IXiIv2g XbrWdSQjyJk5XhqQC5HQcXjMZLTFeGULBn1/NP/X3rn0uHEccfxuwN9hj8khwLwfyMmS7CiIZTuW k1xy6XnJjLjLBcl1LAT+7vnVzPDRzXl0tzaAY3sE2Vqyqrur+l9V/2oOZ5s4Jj8mlHchG0VIKyPR UNIfwruSnBYlKsnCSpG104qOLZUKTG5tGlJi05TEXZfQrpEHICl5lZAoKsluVdU7AEJb5Tn5gFxF WAVd3NLWCWOVXjBVUA7onypyIXBQujYnZeCdHLaXkvfpcugFyC+Kvoi0lHYqkBzN1HAD5NgJsnrC iCQqeoA4kWaBNoyolOnZ2KKFzhCNNa4LYNBVifvyQLhknggIuzgQsDWxoqIXoFB1Ugygcx1Io3cs I9BVk3wpsnlCUpcd7GhdKnJMDdGjBaOolDSMdJRpClPqYOOkK7ZJsl5EF8YuJHCoXGaH9oad0AMo bwxWaHoregY4ZU7Iln3VSOipFTQpJCGxy1lewGbwXlMSuxV7SKNK7aSpTkkNARSYWChIzTXQCnGT Iq4KCiXhQyah/sLWqyoDqG1GFAN+Kin5MoSF1ZSHGOIPS6aPzWmt+ReNWBHmBTkgYiUpfk2JINKR NGs0TVCoDFYBacdo1VI4yUehEISaykBphB3AYIFHHoSgoW4EBwkkiBIQC1RBiSLndQ2dKMWOnJwI BUrYDPo6uvmmZ4ywhIheCBLaBpUw8Rw+HxHpVE0gl0Qp9S2GqOLnrJSeqZSDBHiHUKWCvAse6d0w V3gi+wLRi1sKeSM0niInJYoRIGJpDV7aLIDP8KeUIOPHtBZQpdLVlyUBQiHowG9IhwKHiGlfInIE BSLOQ9JCGDb035Qh9GIqN2FBZ0M/BWDIB1FEVSfyyfpkJooRAIniEMBhUK6EdsCHQ1kDLKGGjpUk 8orsA0tNS5rVJil4saM1LfOAwgLC6UIphGTYhG1pCXt4SwaUS/BXYRbbAUsrqoZoZEwKByCEHtDD NOIwMnIpBy0KpskK6ZOavExhIzkNJ7GehIJ3oBORqciGkD4Q3rFT5Hdg3QjtlZ49oRBIn4bfM96i ANN4U/PyPOijqIqVsDQlW0wUlJniP+goOUmJukJ6oDBS8D/wpuBiqbTdEEPqdCiRAh/vz8miOGPY OG1Aa0SXn6lKSURiLL1MQF6mxYmyTKpNBvGlTYYeQ9VjyYn4pqS00FNSSvKqJMhymCfJjlxJfqYk dsLuU7aArrVoEjkcwy9ww45KGxKTsBthPwRZnecZACA95RmkBWxmSR8fpHkARV8aEiGU9DaAtco5 DzgIpZ8nncJQ6JiaCGyrtJOus8zLimpL209F7KS1In2DYdo9WK60tYQ7rZx0000uw0WK6k6tjSLC tBKmTUpPJUFGULFO1UUqObopAipwSd2LcsGBpAwySKCo4TXkhw6Kugems7xhAXBWehuIu3z9jUTR n1rBwCF9ksagw1kDC4D+4U4yLDQ0JkPB8ImAktZPCecEkXkt/VCTUwwYQTIUrAG2TpmDgXdlJXmP 3ALHAWnELW0f5ZeVZuQD8lhSEWmAISBjk4kb1lWXuBwKVymoTU7Fg7jWLLOSb+rWZCQU6alS8hCB IaMqAiPPkWfPG+ltyImFUAkSQNB2/dkjLQG7VqJJ8y7pVfgPPBte1Nn38qwQUJeAdXgNjtXrRrnZ y8PStG7++vRs7VxFP13rT1jo2UK6iU5aEDnMIm818BB6Z6gRACkQwsUBGsQCmImzTz+BbSUwxVoa M9US4AUdPn1vJVy1rASOjTAcGApcMwavCjwH1AsECPBS4SjhISTPJEgJT7aMJp0wxEWZpPKW/Emv E6YS3Ymc97DFzErKjqiN9B2wPfaJxE2CrRuSs8C6CNjGQtECCCmBYUHe4SYFlSPA5DyH/9GByqFp mMv5DsQtYwNy4Q9ByPLToFRypoYbilAV5CFYdRcK92wF1EQIncCnnwTSNUraIzVDjiv4dQ1JVClh B/aSZjxX13YfghbBhHzO482LFVxddqf1a2uQs9qlk1r9Oq2ABfZS0+e4a3OunSJOXYRK75vrkyw9 KtYiYW1Va2drp0vfBRJmL7a+qsu529pK1jKDvoLTRU/V+3FuJX5Zo19rGlx8kA5/0/HUkvA7I2W8 Yai/N7O/J6W9V4+Pm4d3d3FNuzyMTPWTmXIqs6CXYhKJZyDYUSRptc0E1QnvtpmUJhqwVFgwsSkS OeyhX7H8t5YR8CxSeSm4j+T8sg3whHzyQyKIsQEaQy0PczZqWAPRQh+VyQkgtTJP+BPECgTTHKAx eIaoj8hIeb+mUY+6jF/kvWR8N5JckcHJeS0f1txb2cVkWf5kvCseppZnbW8hGvEwc01vEfY2JdDp 4TWo5vBaLxed5aKzXHSW619jbFlznwHGMbRXLjKsYHgtupG6HSm+kYlvZJIbmeRGJr2RSW9kshuZ rJcp8Lh4tBr26fRT/x47kdWJLmG8JjwnbkdMbpXc/DPc+/nP7aE5HDf36kfquvyw3dXvIWBtF/Rv nW+OO71yuUPu9Mp4T+Xpx9N9kfxclv+5DNn+WLePx7srjfDuWj64u8ieb8qclS41abnLR0IrlHt8 tWUPWpdFh/MLmB4y+uMzDxg/94DJ8xudPvcas+ceMH9+o4vnXmNpNeBJS+4j+dEawbqWHUh1HTsc 6jqJh07qZZEdYHSd3EPHbtN1ndLSohM6Yh0ex13NNn/kAHY7vjBA/PFG2KFhYQC7NLMwQPbxRtiB ZmEAOwQtDOCWJsbb0ofbvi3NP+nKHbByF/Gd3BDsNKt6QE8dN7sHd11Jh+3eSUUWioqbdUNwjsnX arrJXB6n2qi1ehSzrcY776rcX3u36+66zbunfXtwNKR9+KHd7h7bO/lOSHs4OM19Vt63x6e927rP +Ni3XbtvH+rWSf0KJJcB3EyX+3TvHp7uK0fAyFcJfPTkJmF/g0/afUi4GXqGyPDNjM1x07rt872q 9zsnjeNOOUXHSe/LzcHVOlG5e/G03bZuqaLX+8p9G3s9u5KoqdgWQU3JruxpKnaFbsJ7PkaNml62 jboeJo6aHpYO++1j6ajpZemo62HpqDlYOllCQr2X/W5z3Lollpfb3UHC1M2ut5t3D/1XJqzmunx/ 8XqMme8y2gx4GuLFrvlw950rSzhr+VGbfmdestTNw5Od/ZOaPig867p1VLqubRM/re0WdW/gFFIv X1+I2TSMDXg9VUdnJL9V26eBEzga+Eod3Wa6AOiLzf5whtHHD+GIia+EEbwe66ybzZf53aa86LlB 0Iw572lHdddE/EL+4Z4qXn94bPcwxfdOWl/s5Kt3baNrTwI/inQMH/e7815OK+gJ//P7x+/VYeNG 6F7t6qd78eIb9eik+E3/hSJnL37+h3u12V4VDbe9e/3dmy/vvts9Cof9Apc4zd0rv9gdj7t7L/2x Cf7dP9rq906K/cSfwZwfPtz7GPyZR0fWK77cOKazQWvXeGhRwzcPG4+c22v/pf1Q7dS+cZ/3m307 fp+59dB+q+4fHYvLgEHi+d8EofN5Qa/9d7Xf9N/wd9G8anQPT9W/2tot8r7aDT2Vi87XT/13WIe6 73pIrCm75XhN1a269E9OIL/ItloeeE6qRo7Waso+S365VYfDxvaQdlrXzcu6rmsZ1bXdOppRVz6l 7p62fiaflL1sPil7Gr3bPt0/HHzX3et6LrvX9YLXqOtK+XVtN8o/6P5pv2m8XNUr+vipV/Tb2l7V B8y9ord73D54ulK0/URyQtXuIwRdcSwEnoo+e+l1Ynal6rOXHqdnV4o+e9kr+u1lr+qzl/Gru7br oBF+iexK3Wdfr9T9dleOIdr7x91e7T94zP/5tn2nHDv1QfOb/a6DjcPDxltF3NTlQGPbOrMpTdnH 4XQtXvssem7zvZDHzezG5nCwcuaDyEs2mpzgJPbN6ZFC7f7ScU4fHml6UN63j6o+ffRwEsr0vnl4 WPzb7y+fUZwFwwnBM4k+S0UTUr1Nuu1ZrMm9aZvN0/1p3nFrzrLJkmyky6ZTsleZ+iyYzQoaI+ZT gld1/CxYzApGpvXlrGisjZnru/NK7d/f+jzXd+bM56Z2MY+mZW8HjacFz/i0ARB9fi3nKaFp/xyW LgpWoJoRX8bWjNIyyGaUFtBm2j4Xz9+2P2wOp4+3pz8OTwzzD1cfDsyrRTrI/vq0G88/pifRt/HP 8nSyQ3ulZRM4s/u9EEMznl0IphmNhZia1pgLrhnp5SibM30p4GYmWoi8GdMtQtBIamsBaIivBeBN grMLQWMWuxC0T/gzGhYAvrHHAsDGLBYANjQsAKxrrAHYkLYDsGm6DYCNiSwAbJhuAWC9MK4C2BBf A3DsB2BjFjsAG0oWADY0LAB8Y48FgI1ZLABsaFgA2I7ezEjbAdg03QbAxkQWADZMtwBw4gZgQ3wN wIkfgI1Z7ABsKFkA2NCwAPCNPRYANmaxALChYQFgXWMNwIa0HYBN020AbExkAWDDdAsAp24ANsTX AJz6AdiYxQ7AhpIFgA0NCwDf2GMBYGMWCwAbGhYA1jXWAGxI2wHYNN0GwMZEFgA2TLcAcOYGYEN8 DcCZH4CNWewAbChZANjQsADwjT0WADZmsQCwoWEBYF1jDcCGtB2ATdNtAGxMZAHgQWP66E73w3jS qd3UMt3z6/aduviz4mDW9AFAODXlt9pd2dOK0eScNpq6k17sdu8d7tQ8j6Lj8sWm2m52/dnIB8tj 5enFGaezX78831J2LZbobhvvBOqPcvUmPYlmBfVmKIlnBXXSmSSzgiaFSNJZUT2NJno49XA9fbRC wtNlsznZcEo6n5M2zC/m5Azryzk50/h01qa0zxfasGk4J5ydo1hXiOYU8mmFVbed8kNo67+LgrHr 866cmWPep9MKa66d0bLw8ZxNNu6eMc7W75Gr360BfFEwNmrd75GX3yNvvxuaDl6/Mc7W77Gr32NX v1tnkIuCWyqZnsjF77G33w3jbL1+UyrW/Z64+j1x9buuYOv1m8Tv4PfE2++Jn9+NurvudbOrsvB7 6ur31MvvhpaD102bXPye+vk9c/W7obDudbN7sPB75uX3zNvvhqaD12+M0/3ed0Sa35fcfSW9WEOv 5BZT+JXcYga5khsp4GLiuBK3I4FXCnYk8NZtJ38vksBr/80ozDvyorAI12ufTs+x5twZLQsfz2ha OHvWOFu/L5LAKb9bA3hGYd3rJrGy9fsiCVz0+yIJXPS7YZyt102+ZeH3RRI45XfrDDKtYOv1G+ro 4PdFErjo90USOO93g8Ose/2GNa77fZEETvndLYXPaDl4/YY+Ovh9kQTO+32RBE753VBY9/oNa1z3 +yIJnPX7Iglc9Luh6eD1G+Ns/b5IAqf8vkgCp/xuKKx73SRWtn5fJIGLfl8kgYt+d7ur+w0q7t+E e3uv9kfPL5q+Vofvj8rtGRt/e9i3h932h7Y5L9hFfVjul7LS4RfWya8/Oxx3+/YuCPunVMpzModH eAbh+HTNRH6RUv8sxziK2jRO5LeeF0mT1Kk87zLMkuEpmHEmT6ScvLJh5CaQX0rRBiqsQnlu87Tw 5YrboH9satd2XVAGQWA8VfR8hcb/jTdEvzs/Mfb25/Pr/8Pr00/WJH7J12/W/3qvCeub8f/tzTu/ uOu3vf/1Xr9Zv3ylMI2sG/7mSdATD/lNJVk7/JzzQl6aVfr5rv4p5el83ZffntGURVFGXdgkUJYs ZaVJUGZxlIZtOjduERS1PHtffrFEljZZEM4xjp/LNesBz2v6aes/5+s5PfD/Z71cz+UBD+vH3uN0 /fTTfwFQSwECFAAUAAAACAAkK/1QgX67Ja8DAACfEwAAKwAAAAAAAAABACAAAAAAAAAAWG1sTWlu ZERlbW8vcHJvY2Vzc2VkRG9jV2l0aE91dFZhcmlhYmxlLnJ0ZlBLAQIUABQAAAAIACQr/VAVfDkT OSYAABy8AAAoAAAAAAAAAAEAIAAAAPgDAABYbWxNaW5kRGVtby9wcm9jZXNzZWREb2NXaXRoVmFy aWFibGUucnRmUEsBAhQAFAAAAAgAei/9UN0LOY0pAgAAJQcAABYAAAAAAAAAAQAgAAAAdyoAAFht bE1pbmREZW1vL1Byb2dyYW0uY3NQSwECFAAUAAAACAAAS+lQY/DxUUoDAAAGGQAAFQAAAAAAAAAB ACAAAADULAAAWG1sTWluZERlbW8vc3R5bGVzLmZvUEsBAhQAFAAAAAAAmCj9UAAAAAAAAAAAAAAA AB8AAAAAAAAAAAAgAAAAUTAAAFhtbE1pbmREZW1vL1dpdGhvdXRWYXJpYWJsZS5ydGZQSwECFAAU AAAACACNKP1Qp1ThivUiAACCqAAAHAAAAAAAAAABACAAAACOMAAAWG1sTWluZERlbW8vV2l0aFZh cmlhYmxlLnJ0ZlBLBQYAAAAABgAGAM0BAAC9UwAAAAA= --00000000000018630705ab8e678d Content-Type: text/plain; charset="us-ascii" MIME-Version: 1.0 Content-Transfer-Encoding: 7bit Content-Disposition: inline -- XMLmind FO Converter Support List [email protected] https://www.xmlmind.com/mailman/listinfo/xfc-support --00000000000018630705ab8e678d--