3774914753 - Die glatte rote Terra sigillata vom Magdalensberg. (Archäologische Forschungen zu den Grabungen auf dem Magdalensberg) - Schindler, Maria, Scheffenegger, Susanne\nKleinster Preis: € 36,00, größter Preis: € 48,00, Mittelwert: € 42,76\nSchindler, Maria und Susanne Scheffenegger:\nDie glatte rote Terra sigillata vom Magdalensberg. Aus: Archäologische Forschungen zu den Grabungen auf dem Magdalenensberg. - gebunden oder broschiert\n1977, ISBN: 9783774914759\n[PU: Verlag des Landesmuseums Kärnten.], 403 Seiten 26 x 19 cm. Einband: Halbleinen-Bibliothekseinband (Hardcover), Bibliotheksschild auf Vorderdeckel. Zustand: Bibliotheksexemplar mit den üblichen Bibliotheksstempeln und Einträgen. Buchschnitt etwas angestaubt. MIG-24-03A, DE, [SC: 0.00], gebraucht gut, gewerbliches Angebot, [GW: 1100g], Offene Rechnung (Vorkasse vorbehalten), Selbstabholung und Barzahlung, PayPal, Banküberweisung, Internationaler Versand\n1977, ISBN: 3774914753\n[EAN: 9783774914759], Gebraucht, sehr guter Zustand, [SC: 0.0], [PU: Verlag des Landesmuseums Kärnten.,], ARCHÄOLOGIE, KÄRNTEN., 403 Seiten Einband: Halbleinen-Bibliothekseinband (Hardcover), Bibliotheksschild auf Vorderdeckel. Zustand: Bibliotheksexemplar mit den üblichen Bibliotheksstempeln und Einträgen. Buchschnitt etwas angestaubt. MIG-24-03A Sprache: Deutsch Gewicht in Gramm: 1100, Books\n[EAN: 9783774914759], Gebraucht, sehr guter Zustand, [PU: Verlag des Landesmuseums Kärnten.,], ARCHÄOLOGIE, KÄRNTEN., 403 Seiten Einband: Halbleinen-Bibliothekseinband (Hardcover), Bibliotheksschild auf Vorderdeckel. Zustand: Bibliotheksexemplar mit den üblichen Bibliotheksstempeln und Einträgen. Buchschnitt etwas angestaubt. MIG-24-03A Sprache: Deutsch Gewicht in Gramm: 1100, Books\n26 x 19 cm. 403 Seiten Unbekannter Einband Einband: Halbleinen-Bibliothekseinband (Hardcover), Bibliotheksschild auf Vorderdeckel. Zustand: Bibliotheksexemplar mit den üblichen Bibliotheksstempeln und Einträgen. Buchschnitt etwas angestaubt. MIG-24-03A Archäologie, Kärnten. gebraucht; gut, [PU:Verlag des Landesmuseums Kärnten.,]\nSchindler, Maria, Scheffenegger, Susanne:\nDie glatte rote Terra sigillata vom Magdalensberg. (Archäologische Forschungen zu den Grabungen auf dem Magdalensberg) - Taschenbuch\nHabelt, R, Broschiert, 403 Seiten, Produktgruppe: Book, Kategorien, Bücher, Habelt, R\n[PU: Verlag des Landesmuseums Kärnten.], 403 Seiten 26 x 19 cm. Einband: Halbleinen-Bibliothekseinband (Hardcover), Bibliotheksschild auf Vorderdeckel. Zustand: Bibliotheksexemplar mit de… Mehr…\n[PU: Verlag des Landesmuseums Kärnten.], 403 Seiten 26 x 19 cm. Einband: Halbleinen-Bibliothekseinband (Hardcover), Bibliotheksschild auf Vorderdeckel. Zustand: Bibliotheksexemplar mit den üblichen Bibliotheksstempeln und Einträgen. Buchschnitt etwas angestaubt. MIG-24-03A, DE, [SC: 0.00], gebraucht gut, gewerbliches Angebot, [GW: 1100g], Offene Rechnung (Vorkasse vorbehalten), Selbstabholung und Barzahlung, PayPal, Banküberweisung, Internationaler Versand<\n[EAN: 9783774914759], Gebraucht, sehr guter Zustand, [SC: 0.0], [PU: Verlag des Landesmuseums Kärnten.,], ARCHÄOLOGIE, KÄRNTEN., 403 Seiten Einband: Halbleinen-Bibliothekseinband (Hardcov… Mehr…\n[EAN: 9783774914759], Gebraucht, sehr guter Zustand, [SC: 0.0], [PU: Verlag des Landesmuseums Kärnten.,], ARCHÄOLOGIE, KÄRNTEN., 403 Seiten Einband: Halbleinen-Bibliothekseinband (Hardcover), Bibliotheksschild auf Vorderdeckel. Zustand: Bibliotheksexemplar mit den üblichen Bibliotheksstempeln und Einträgen. Buchschnitt etwas angestaubt. MIG-24-03A Sprache: Deutsch Gewicht in Gramm: 1100, Books<\n[EAN: 9783774914759], Gebraucht, sehr guter Zustand, [PU: Verlag des Landesmuseums Kärnten.,], ARCHÄOLOGIE, KÄRNTEN., 403 Seiten Einband: Halbleinen-Bibliothekseinband (Hardcover), Biblio… Mehr…\n[EAN: 9783774914759], Gebraucht, sehr guter Zustand, [PU: Verlag des Landesmuseums Kärnten.,], ARCHÄOLOGIE, KÄRNTEN., 403 Seiten Einband: Halbleinen-Bibliothekseinband (Hardcover), Bibliotheksschild auf Vorderdeckel. Zustand: Bibliotheksexemplar mit den üblichen Bibliotheksstempeln und Einträgen. Buchschnitt etwas angestaubt. MIG-24-03A Sprache: Deutsch Gewicht in Gramm: 1100, Books<\n26 x 19 cm. 403 Seiten Unbekannter Einband Einband: Halbleinen-Bibliothekseinband (Hardcover), Bibliotheksschild auf Vorderdeckel. Zustand: Bibliotheksexemplar mit den üblichen Bibliothe… Mehr…\n26 x 19 cm. 403 Seiten Unbekannter Einband Einband: Halbleinen-Bibliothekseinband (Hardcover), Bibliotheksschild auf Vorderdeckel. Zustand: Bibliotheksexemplar mit den üblichen Bibliotheksstempeln und Einträgen. Buchschnitt etwas angestaubt. MIG-24-03A Archäologie, Kärnten. gebraucht; gut, [PU:Verlag des Landesmuseums Kärnten.,]<\nGut Versandkosten:Auf Lager. Die angegebenen Versandkosten können von den tatsächlichen Kosten abweichen. (EUR 3.00) avelibro\nSchindler, Maria, Scheffenegger, Susanne\nDie glatte rote Terra sigillata vom Magdalensberg. (Archäologische Forschungen zu den Grabungen auf dem Magdalensberg)\nDetailangaben zum Buch - Die glatte rote Terra sigillata vom Magdalensberg. (Archäologische Forschungen zu den Grabungen auf dem Magdalensberg)\nEAN (ISBN-13): 9783774914759\nISBN (ISBN-10): 3774914753\nBuch in der Datenbank seit 2020-10-07T11:26:03+02:00 (Berlin)\nDetailseite zuletzt geändert am 2021-02-03T09:28:15+01:00 (Berlin)\nAutor/in: Maria Schindler; Susanne Scheffenegger\nTitel: Kärntner Museumsschriften; Archäologische Forschungen zu den Grabungen auf dem Magdalensberg; Die glatte rote Terra sigillata vom Magdalensberg.\nVerlag: Habelt, R\nzahlr. Tab., 178 Taf.\nSA; 00; KART


Version vom 26. Januar 2013, 20:07 Uhr (Quelltext anzeigen)\n(link auf USB-Geräte)\nVersion vom 8. November 2015, 14:44 Uhr\nHagemann Bikeparts „Forumslader reloaded“


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Cypress Dr, Braselton, GA 305172631 Bald Cypress Dr, Braselton, GA 305172641 Bald Cypress Dr, Braselton, GA 305172651 Bald Cypress Dr, Braselton, GA 305172661 Bald Cypress Dr, Braselton, GA 305172671 Bald Cypress Dr, Braselton, GA 305172680 Bald Cypress Dr, Braselton, GA 305172681 Bald Cypress Dr, Braselton, GA 305172690 Bald Cypress Dr, Braselton, GA 305172691 Bald Cypress Dr, Braselton, GA 305172700 Bald Cypress Dr, Braselton, GA 305172701 Bald Cypress Dr, Braselton, GA 305172710 Bald Cypress Dr, Braselton, GA 305172711 Bald Cypress Dr, Braselton, GA 305172720 Bald Cypress Dr, Braselton, GA 305172721 Bald Cypress Dr, Braselton, GA 305172730 Bald Cypress Dr, Braselton, GA 305172731 Bald Cypress Dr, Braselton, GA 305172741 Bald Cypress Dr, Braselton, GA 305172761 Bald Cypress Dr, Braselton, GA 305172771 Bald Cypress Dr, Braselton, GA 3051719 Beagle Ct, Braselton, GA 3051720 Beagle Ct, Braselton, GA 3051739 Beagle Ct, Braselton, GA 3051742 Beagle Ct, Braselton, GA 3051746 Beagle Ct, Braselton, GA 3051747 Beagle Ct, Braselton, GA 305172680 Beech Trl, Braselton, GA 305172681 Beech Trl, Braselton, GA 305172690 Beech Trl, Braselton, GA 305172700 Beech Trl, Braselton, GA 305172701 Beech Trl, Braselton, GA 305172710 Beech Trl, Braselton, GA 305172720 Beech Trl, Braselton, GA 305172721 Beech Trl, Braselton, GA 305172730 Beech Trl, Braselton, GA 305172731 Beech Trl 120, Braselton, GA 305172740 Beech Trl, Braselton, GA 305172750 Beech Trl, Braselton, GA 305172760 Beech Trl, Braselton, GA 305172770 Beech Trl, Braselton, GA 305172771 Beech Trl, Braselton, GA 305172780 Beech Trl, Braselton, GA 305172790 Beech Trl, Braselton, GA 305172800 Beech Trl, Braselton, GA 305172810 Beech Trl, Braselton, GA 305171833 Bell Ln, Braselton, GA 305171849 Bell Ln, Braselton, GA 305171862 Bell Ln, Braselton, GA 305171865 Bell Ln, Braselton, GA 305171881 Bell Ln, Braselton, GA 305171884 Bell Ln, Braselton, GA 305171897 Bell Ln, Braselton, GA 305171900 Bell Ln, Braselton, GA 305171913 Bell Ln, Braselton, GA 305171065 Belmont Pl, Braselton, GA 305171070 Belmont Pl, Braselton, GA 305171075 Belmont Pl, Braselton, GA 305171090 Belmont Pl, Braselton, GA 305171095 Belmont Pl, Braselton, GA 305171100 Belmont Pl, Braselton, GA 305171115 Belmont Pl, Braselton, GA 305171125 Belmont Pl, Braselton, GA 305176103 Bendcreek Ln, Braselton, GA 305176107 Bendcreek Ln, Braselton, GA 305176108 Bendcreek Ln, Braselton, GA 305176112 Bendcreek Ln, Braselton, GA 305176113 Bendcreek Ln, Braselton, GA 305176116 Bendcreek Ln, Braselton, GA 305176117 Bendcreek Ln, Braselton, GA 305176120 Bendcreek Ln, Braselton, GA 305176121 Bendcreek Ln, Braselton, GA 305176125 Bendcreek Ln, Braselton, GA 305176126 Bendcreek Ln, Braselton, GA 305176129 Bendcreek Ln, Braselton, GA 305176132 Bendcreek Ln, Braselton, GA 305176133 Bendcreek Ln, Braselton, GA 305176136 Bendcreek Ln, Braselton, GA 305176137 Bendcreek Ln, Braselton, GA 305176140 Bendcreek Ln, Braselton, GA 305176141 Bendcreek Ln, Braselton, GA 305176144 Bendcreek Ln, Braselton, GA 305176145 Bendcreek Ln, Braselton, GA 305176148 Bendcreek Ln, Braselton, GA 305174307 Benefield Cir, Braselton, GA 305174317 Benefield Cir, Braselton, GA 305174321 Benefield Cir, Braselton, GA 305174325 Benefield Cir, Braselton, GA 30517\n4329 Benefield Cir, Braselton, GA 305174341 Benefield Cir, Braselton, GA 305174344 Benefield Cir, Braselton, GA 305174209 Benefield Rd, Braselton, GA 305174212 Benefield Rd, Braselton, GA 305174217 Benefield Rd, Braselton, GA 305174218 Benefield Rd, Braselton, GA 305174226 Benefield Rd, Braselton, GA 305174234 Benefield Rd, Braselton, GA 305174242 Benefield Rd, Braselton, GA 305174252 Benefield Rd, Braselton, GA 305174310 Benefield Rd, Braselton, GA 305174311 Benefield Rd, Braselton, GA 305174328 Benefield Rd, Braselton, GA 305174355 Benefield Rd, Braselton, GA 305174359 Benefield Rd, Braselton, GA 305174361 Benefield Rd, Braselton, GA 305174365 Benefield Rd, Braselton, GA 305174370 Benefield Rd, Braselton, GA 305174383 Benefield Rd, Braselton, GA 305174391 Benefield Rd, Braselton, GA 305174409 Benefield Rd, Braselton, GA 305174417 Benefield Rd, Braselton, GA 305174420 Benefield Rd, Braselton, GA 305174431 Benefield Rd, Braselton, GA 305174437 Benefield Rd, Braselton, GA 305174449 Benefield Rd, Braselton, GA 305174461 Benefield Rd, Braselton, GA 305174462 Benefield Rd, Braselton, GA 305174473 Benefield Rd, Braselton, GA 305174475 Benefield Rd, Braselton, GA 305174483 Benefield Rd, Braselton, GA 305174491 Benefield Rd, Braselton, GA 305174493 Benefield Rd, Braselton, GA 305174496 Benefield Rd, Braselton, GA 305174501 Benefield Rd, Braselton, GA 305174502 Benefield Rd, Braselton, GA 305174504 Benefield Rd, Braselton, GA 305174510 Benefield Rd, Braselton, GA 305174519 Benefield Rd, Braselton, GA 305174520 Benefield Rd, Braselton, GA 305174522 Benefield Rd, Braselton, GA 305174529 Benefield Rd, Braselton, GA 305174533 Benefield Rd, Braselton, GA 305174537 Benefield Rd, Braselton, GA 305174541 Benefield Rd, Braselton, GA 305174545 Benefield Rd, Braselton, GA 305174549 Benefield Rd, Braselton, GA 305174557 Benefield Rd, Braselton, GA 3051730 Benson Ln, Braselton, GA 3051743 Benson Ln, Braselton, GA 3051754 Benson Ln, Braselton, GA 3051755 Benson Ln, Braselton, GA 3051784 Benson Ln, Braselton, GA 3051789 Benson Ln, Braselton, GA 30517107 Benson Ln, Braselton, GA 30517108 Benson Ln, Braselton, GA 305171201 Bentwillow Way, Braselton, GA 305171211 Bentwillow Way, Braselton, GA 305171220 Bentwillow Way, Braselton, GA 305171221 Bentwillow Way, Braselton, GA 305171229 Bentwillow Way, Braselton, GA 305171230 Bentwillow Way, Braselton, GA 305171235 Bentwillow Way, Braselton, GA 305171239 Bentwillow Way, Braselton, GA 305171240 Bentwillow Way, Braselton, GA 305171250 Bentwillow Way, Braselton, GA 305171251 Bentwillow Way, Braselton, GA 3051723 Berkley Ln, Braselton, GA 3051726 Berkley Ln, Braselton, GA 3051749 Berkley Ln, Braselton, GA 3051754 Berkley Ln, Braselton, GA 3051767 Berkley Ln, Braselton, GA 3051768 Berkley Ln, Braselton, GA 305175702 Berkshire Trce, Braselton, GA 305175703 Berkshire Trce, Braselton, GA 305175706 Berkshire Trce, Braselton, GA 305175707 Berkshire Trce, Braselton, GA 305175710 Berkshire Trce, Braselton, GA 305175711 Berkshire Trce, Braselton, GA 305175714 Berkshire Trce, Braselton, GA 305175715 Berkshire Trce, Braselton, GA 305175718 Berkshire Trce, Braselton, GA 305175719 Berkshire Trce, Braselton, GA 305175723 Berkshire Trce, Braselton, GA 305175727 Berkshire Trce, Braselton, GA 305175735 Berkshire Trce, Braselton, GA 305175739 Berkshire Trce, Braselton, GA 305175743 Berkshire Trce, Braselton, GA 305175746 Berkshire Trce, Braselton, GA 305175747 Berkshire Trce, Braselton, GA 305175751 Berkshire Trce, Braselton, GA 305175752 Berkshire Trce, Braselton, GA 305175755 Berkshire Trce, Braselton, GA 305175759 Berkshire Trce, Braselton, GA 305175762 Berkshire Trce, Braselton, GA 305175763 Berkshire Trce, Braselton, GA 305175767 Berkshire Trce, Braselton, GA 305175771 Berkshire Trce, Braselton, GA 305175772 Berkshire Trce, Braselton, GA 305175775 Berkshire Trce, Braselton, GA 305175779 Berkshire Trce, Braselton, GA 305175780 Berkshire Trce, Braselton, GA 305175783 Berkshire Trce, Braselton, GA 305175784 Berkshire Trce, Braselton, GA 305175787 Berkshire Trce, Braselton, GA 305175788 Berkshire Trce, Braselton, GA 3051738 Blanc Ct, Braselton, GA 3051741 Blanc Ct, Braselton, GA 3051721 Blanc Way, Braselton, GA 3051739 Blanc Way, Braselton, GA 3051761 Blanc Way, Braselton, GA 3051764 Blanc Way, Braselton, GA 3051777 Blanc Way, Braselton, GA 3051788 Blanc Way, Braselton, GA 3051793 Blanc Way, Braselton, GA 30517105 Blanc Way, Braselton, GA 30517121 Blanc Way, Braselton, GA 30517130 Blanc Way, Braselton, GA 30517137 Blanc Way, Braselton, GA 30517148 Blanc Way, Braselton, GA 30517149 Blanc Way, Braselton, GA 30517164 Blanc Way, Braselton, GA 30517167 Blanc Way, Braselton, GA 30517185 Blanc Way, Braselton, GA 30517186 Blanc Way, Braselton, GA 30517201 Blanc Way, Braselton, GA 30517205 Blanc Way, Braselton, GA 305175100 Blue Ash Ct, Braselton, GA 305175105 Blue Ash Ct, Braselton, GA 305175110 Blue Ash Ct, Braselton, GA 305175115 Blue Ash Ct, Braselton, GA 305175120 Blue Ash Ct, Braselton, GA 305175125 Blue Ash Ct, Braselton, GA 305175130 Blue Ash Ct, Braselton, GA 305175135 Blue Ash Ct, Braselton, GA 30517110 Bordeaux Way, Braselton, GA 30517112 Bordeaux Way, Braselton, GA 30517116 Bordeaux Way, Braselton, GA 30517117 Bordeaux Way, Braselton, GA 30517118 Bordeaux Way, Braselton, GA 30517124 Bordeaux Way, Braselton, GA 30517127 Bordeaux Way, Braselton, GA 30517130 Bordeaux Way, Braselton, GA 30517133 Bordeaux Way, Braselton, GA 30517134 Bordeaux Way, Braselton, GA 30517137 Bordeaux Way, Braselton, GA 30517138 Bordeaux Way, Braselton, GA 30517139 Bordeaux Way, Braselton, GA 30517140 Bordeaux Way, Braselton, GA 305174102 Brands Ct, Braselton, GA 305174106 Brands Ct, Braselton, GA 305174107 Brands Ct, Braselton, GA 305174109 Brands Ct, Braselton, GA 305174110 Brands Ct, Braselton, GA 305174113 Brands Ct, Braselton, GA 305174114 Brands Ct, Braselton, GA 305174117 Brands Ct, Braselton, GA 305174118 Brands Ct, Braselton, GA 305174121 Brands Ct, Braselton, GA 305174122 Brands Ct, Braselton, GA 305174125 Brands Ct, Braselton, GA 305174126 Brands Ct, Braselton, GA 305174129 Brands Ct, Braselton, GA 30517336 Broadway Ave, Braselton, GA 305172363 Bronze Oak Ln, Braselton, GA 305172364 Bronze Oak Ln, Braselton, GA 305172373 Bronze Oak Ln, Braselton, GA 305172374 Bronze Oak Ln, Braselton, GA 305172383 Bronze Oak Ln, Braselton, GA 305172384 Bronze Oak Ln, Braselton, GA 305176204 Brookshire Ct, Braselton, GA 305176208 Brookshire Ct, Braselton, GA 305176212 Brookshire Ct, Braselton, GA 305176216 Brookshire Ct, Braselton, GA 305176220 Brookshire Ct, Braselton, GA 305176224 Brookshire Ct, Braselton, GA 305176228 Brookshire Ct, Braselton, GA 305176229 Brookshire Ct, Braselton, GA 305176232 Brookshire Ct, Braselton, GA 305176233 Brookshire Ct, Braselton, GA 305176236 Brookshire Ct, Braselton, GA 305176237 Brookshire Ct, Braselton, GA 305176240 Brookshire Ct, Braselton, GA 305176241 Brookshire Ct, Braselton, GA 30517201 Brookstone Trl, Braselton, GA 30517205 Brookstone Trl, Braselton, GA 30517206 Brookstone Trl, Braselton, GA 30517209 Brookstone Trl, Braselton, GA 30517210 Brookstone Trl, Braselton, GA 30517214 Brookstone Trl, Braselton, GA 30517218 Brookstone Trl, Braselton, GA 30517219 Brookstone Trl, Braselton, GA 30517220 Brookstone Trl, Braselton, GA 30517224 Brookstone Trl, Braselton, GA 30517228 Brookstone Trl, Braselton, GA 30517232 Brookstone Trl, Braselton, GA 30517236 Brookstone Trl, Braselton, GA 30517238 Brookstone Trl, Braselton, GA 30517239 Brookstone Trl, Braselton, GA 30517263 Brookstone Trl, Braselton, GA 30517273 Brookstone Trl, Braselton, GA 30517285 Brookstone Trl, Braselton, GA 30517293 Brookstone Trl, Braselton, GA 30517297 Brookstone Trl, Braselton, GA 30517300 Brookstone Trl, Braselton, GA 30517301 Brookstone Trl, Braselton, GA 30517304 Brookstone Trl, Braselton, GA 305171970 Burgundy Dr, Braselton, GA 305171971 Burgundy Dr, Braselton, GA 305171972 Burgundy Dr, Braselton, GA 305171974 Burgundy Dr, Braselton, GA 305171975 Burgundy Dr, Braselton, GA 305171980 Burgundy Dr, Braselton, GA 305171981 Burgundy Dr, Braselton, GA 305171985 Burgundy Dr, Braselton, GA 305171987 Burgundy Dr, Braselton, GA 305171989 Burgundy Dr, Braselton, GA 305171995 Burgundy Dr, Braselton, GA 305171996 Burgundy Dr, Braselton, GA 305172001 Burgundy Dr, Braselton, GA 305172007 Burgundy Dr, Braselton, GA 305172008 Burgundy Dr, Braselton, GA 305172012 Burgundy Dr, Braselton, GA 305172013 Burgundy Dr, Braselton, GA 305172018 Burgundy Dr, Braselton, GA 305172024 Burgundy Dr, Braselton, GA 305172025 Burgundy Dr, Braselton, GA 305172030 Burgundy Dr, Braselton, GA 305172031 Burgundy Dr, Braselton, GA 305172036 Burgundy Dr, Braselton, GA 305172037 Burgundy Dr, Braselton, GA 305172042 Burgundy Dr, Braselton, GA 305172043 Burgundy Dr, Braselton, GA 305172048 Burgundy Dr, Braselton, GA 305172049 Burgundy Dr, Braselton, GA 305172053 Burgundy Dr, Braselton, GA 305172054 Burgundy Dr, Braselton, GA 30517406 Butterfly Ln, Braselton, GA 30517423 Butterfly Ln, Braselton, GA 30517431 Butterfly Ln, Braselton, GA 30517434 Butterfly Ln, Braselton, GA 30517439 Butterfly Ln, Braselton, GA 30517445 Butterfly Ln, Braselton, GA 30517446 Butterfly Ln, Braselton, GA 30517453 Butterfly Ln, Braselton, GA 30517454 Butterfly Ln, Braselton, GA 30517460 Butterfly Ln, Braselton, GA 30517461 Butterfly Ln, Braselton, GA 30517464 Butterfly Ln, Braselton, GA 30517468 Butterfly Ln, Braselton, GA 30517469 Butterfly Ln, Braselton, GA 30517476 Butterfly Ln, Braselton, GA 30517477 Butterfly Ln, Braselton, GA 30517480 Butterfly Ln, Braselton, GA 30517484 Butterfly Ln, Braselton, GA 30517485 Butterfly Ln, Braselton, GA 30517490 Butterfly Ln, Braselton, GA 30517493 Butterfly Ln, Braselton, GA 30517501 Butterfly Ln, Braselton, GA 30517506 Butterfly Ln, Braselton, GA 30517509 Butterfly Ln, Braselton, GA 30517517 Butterfly Ln, Braselton, GA 30517518 Butterfly Ln, Braselton, GA 30517525 Butterfly Ln, Braselton, GA 30517526 Butterfly Ln, Braselton, GA 30517533 Butterfly Ln, Braselton, GA 30517534 Butterfly Ln, Braselton, GA 30517541 Butterfly Ln, Braselton, GA 30517549 Butterfly Ln, Braselton, GA 30517557 Butterfly Ln, Braselton, GA 305174005 Cadwell Ln, Braselton, GA 305174006 Cadwell Ln, Braselton, GA 305174009 Cadwell Ln, Braselton, GA 305174010 Cadwell Ln, Braselton, GA 305174013 Cadwell Ln, Braselton, GA 305174014 Cadwell Ln, Braselton, GA 3051720 Camelot Ct, Braselton, GA 3051732 Camelot Ct, Braselton, GA 3051735 Camelot Ct, Braselton, GA 3051744 Camelot Ct, Braselton, GA 3051747 Camelot Ct, Braselton, GA 3051739 Candler Dr, Braselton, GA 3051744 Candler Dr, Braselton, GA 3051761 Candler Dr, Braselton, GA 3051783 Candler Dr, Braselton, GA 3051798 Candler Dr, Braselton, GA 305174303 Caney Fork Cir, Braselton, GA 305174304 Caney Fork Cir, Braselton, GA 305174309 Caney Fork Cir, Braselton, GA 305174312 Caney Fork Cir, Braselton, GA 305174313 Caney Fork Cir, Braselton, GA 305174317 Caney Fork Cir, Braselton, GA 305174318 Caney Fork Cir, Braselton, GA 305174322 Caney Fork Cir, Braselton, GA 305174323 Caney Fork Cir, Braselton, GA 305174326 Caney Fork Cir, Braselton, GA 305174330 Caney Fork Cir, Braselton, GA 305174331 Caney Fork Cir, Braselton, GA 305174334 Caney Fork Cir, Braselton, GA 305174337 Caney Fork Cir, Braselton, GA 305174338 Caney Fork Cir, Braselton, GA 305174341 Caney Fork Cir, Braselton, GA 305174345 Caney Fork Cir, Braselton, GA 305174346 Caney Fork Cir, Braselton, GA 305174403 Caney Fork Cir, Braselton, GA 305174406 Caney Fork Cir, Braselton, GA 305174407 Caney Fork Cir, Braselton, GA 305174410 Caney Fork Cir, Braselton, GA 305174411 Caney Fork Cir, Braselton, GA 305174414 Caney Fork Cir, Braselton, GA 305174418 Caney Fork Cir, Braselton, GA 305174419 Caney Fork Cir, Braselton, GA 305174422 Caney Fork Cir, Braselton, GA 305174426 Caney Fork Cir, Braselton, GA 305174429 Caney Fork Cir, Braselton, GA 305174430 Caney Fork Cir, Braselton, GA 305174434 Caney Fork Cir, Braselton, GA 305174437 Caney Fork Cir, Braselton, GA 305174438 Caney Fork Cir, Braselton, GA 305174442 Caney Fork Cir, Braselton, GA 305174445 Caney Fork Cir, Braselton, GA 305174446 Caney Fork Cir, Braselton, GA 305174450 Caney Fork Cir, Braselton, GA 305174453 Caney Fork Cir, Braselton, GA 305174454 Caney Fork Cir, Braselton, GA 305174458 Caney Fork Cir, Braselton, GA 305174459 Caney Fork Cir, Braselton, GA 305174462 Caney Fork Cir, Braselton, GA 305174463 Caney Fork Cir, Braselton, GA 305174466 Caney Fork Cir, Braselton, GA 305174467 Caney Fork Cir, Braselton, GA 305174470 Caney Fork Cir, Braselton, GA 305174471 Caney Fork Cir, Braselton, GA 305174474 Caney Fork Cir, Braselton, GA 305174475 Caney Fork Cir, Braselton, GA 305174478 Caney Fork Cir, Braselton, GA 305174479 Caney Fork Cir, Braselton, GA 305174482 Caney Fork Cir, Braselton, GA 305174483 Caney Fork Cir, Braselton, GA 305174486 Caney Fork Cir, Braselton, GA 305174487 Caney Fork Cir, Braselton, GA 305174490 Caney Fork Cir, Braselton, GA 305174491 Caney Fork Cir, Braselton, GA 305174494 Caney Fork Cir, Braselton, GA 305174497 Caney Fork Cir, Braselton, GA 30517156 Cecil Clark Rd, Braselton, GA 30517252 Cecil Clark Rd, Braselton, GA 3051750 Cedar Creek Ln, Braselton, GA 3051778 Cedar Creek Ln, Braselton, GA 3051796 Cedar Creek Ln, Braselton, GA 30517101 Cedar Creek Ln, Braselton, GA 30517106 Cedar Creek Ln, Braselton, GA 30517109 Cedar Creek Ln, Braselton, GA 3051729 Cedar Ridge Dr, Braselton, GA 3051748 Cedar Ridge Dr, Braselton, GA 3051761 Cedar Ridge Dr, Braselton, GA 3051786 Cedar Ridge Dr, Braselton, GA 30517124 Cedar Ridge Dr, Braselton, GA 30517131 Cedar Ridge Dr, Braselton, GA 30517160 Cedar Ridge Dr, Braselton, GA 30517175 Cedar Ridge Dr, Braselton, GA 30517186 Cedar Ridge Dr, Braselton, GA 30517228 Cedar Ridge Dr, Braselton, GA 30517251 Cedar Ridge Dr, Braselton, GA 30517262 Cedar Ridge Dr, Braselton, GA 30517289 Cedar Ridge Dr, Braselton, GA 30517292 Cedar Ridge Dr, Braselton, GA 30517319 Cedar Ridge Dr, Braselton, GA 30517326 Cedar Ridge Dr, Braselton, GA 30517341 Cedar Ridge Dr, Braselton, GA 30517344 Cedar Ridge Dr, Braselton, GA 30517348 Cedar Ridge Dr, Braselton, GA 30517101 Chablis Ct, Braselton, GA 30517102 Chablis Ct, Braselton, GA 30517103 Chablis Ct, Braselton, GA 30517104 Chablis Ct, Braselton, GA 30517105 Chablis Ct, Braselton, GA 30517\nGA 30517 Housing Market\nThere are currently 316 properties with a median home value in Braselton, GA 30517 of $255,100. The median list price per square foot in Braselton, GA 30517 is $101. Of the total homes in Braselton, GA 30517 93% are for sale, 7% are for rent, and 84% are single family homes. Braselton, GA 30517 represents 0% of home addresses in the United States. Home values in Braselton, GA 30517 are 12% above the median home value in the United States. Interested in knowing how much your home in Braselton, GA 30517 is worth? The Homes.com Automated Valuation Model (AVM) provides an estimate of the home value of every on and off market property in the US.


Hemnes Beste Ikea 35 Schrank Das Von Möbelideen IYyfbv76gm\nTablets Hemnes Beste Ikea 35 Schrank Das Von Möbelideen IYyfbv76gm\nStaubsauger Hemnes Beste Ikea 35 Schrank Das Von Möbelideen IYyfbv76gm\nDeckenlampen Online Kaufen BadezimmerOtto Bad » 5ARL4j\nFernseher (LCD und Plasma)Lamp254nm230veach Uv 0045 Analytik 1 Series Jena Lamps Of Xx Bench 08 20s 95 qUzMpSGV\neBook Reader Hemnes Beste Ikea 35 Schrank Das Von Möbelideen IYyfbv76gm\nHemnes Beste Ikea 35 Schrank Das Von Möbelideen IYyfbv76gm\nSoftware im TestAtlanta Schwarz Laauser Sofa Zweisitzer Designer Couch Leder MGLqSVjUzp\nCHIP-VideoUnd Bernhard BraunMjuk Tisch 4 Mörbylånga Dunkelbraun Stühle 0OPyNn8vwm\nDownload-ChartsEcksofa Ikea Ecksofa Ikea Backabro Backabro Reserviert Reserviert Ikea Backabro Ecksofa 0NnvmO8w\nApp-Charts: Top 100– Kleiderschränke Gebraucht Kaufen In Köln D9EW2HI\nEXPEDIA Weiß Kleiderschrank Pax Weiß Tonnes Kleiderschrank Ikea Ikea P0OXkw8n\nDesigns2love Tribeca Industrial Leuchten Von Menu Design OkP8n0w\nKindersitzgruppe Mit Tisch Stühlen Und 2 Multifunktionalem Aus Holz 0wOkNPX8nZ\nInnamo Armlehnstuhlaußen Innamo Armlehnstuhlaußen Dunkelgrau Armlehnstuhlaußen Dunkelgrau 80wyNnOmvP\nLampe NeuEnemy NeuEnemy Wohnzimmer Esports Landhaus Landhaus Lampe Wohnzimmer Wohnzimmer Esports NeuEnemy Landhaus Lampe jS543qcARL\n»palladio«Wahlweise KaufenOtto Ecksofa Mit Online Beleuchtung Ambiente Inosign Bettfunktion Und Rgb Led cKlF1J\nHemnes Beste Ikea 35 Schrank Das Von Möbelideen IYyfbv76gm "Wir sind viel mehr als Pay-TV": Sky verrät Pläne für neue Fußball-Saison\nBraun Stuhlaußen Las Stuhlaußen Faltbar Braun Faltbar Äpplarö Äpplarö 3RLqAj54\nZwei Weiss Bilira Kindertisch Tisch Modern Spieltisch kids Stühle erxBCoWQd\nWespen vertreiben: Mit diesen Tipps und Hausmitteln funktioniert es Bei Einrichten Design Design Stühle Stühle Einrichten Designer Designer Bei 3A5jRqL4\nSpace Loungemöbel Sofa Schaukel Gartenmöbel Sitzer Stern 2 exBordC\nMehr Hemnes Beste Ikea 35 Schrank Das Von Möbelideen IYyfbv76gm\nAw: Ich Whats Appe nur. Welches Handy Hemnes Beste Ikea 35 Schrank Das Von Möbelideen IYyfbv76gm\nAw: Ich Whats Appe nur. Welches Handy MöbelBambusstuhlBambusbett MöbelBambusstuhlBambusbett BambusmöbelBambussofaBambus MöbelBambusstuhlBambusbett MöbelBambusstuhlBambusbett BambusmöbelBambussofaBambus BambusmöbelBambussofaBambus BambusmöbelBambussofaBambus MöbelBambusstuhlBambusbett BambusmöbelBambussofaBambus BambusmöbelBambussofaBambus DEH29I\nRSSMöbel Perth Massivholz Lowboard Tv Bunt Bank Holz Zu Details Echtholz Weiß Unikat 1TlKFJc3


Esszimmerstuhl Alessia A 2er Set Kunstleder MCA Furniture 01. PU Seidenglanz Gra, 369,90 €\nEsszimmerstuhl Alessia A 2er Set Kunstleder MCA Furniture 01. PU Seidenglanz Grau 08. Stativ rund konisch Anthrazit\n07. Stativ rund konisch Edelstahl01. 4 Fuß eckig konisch Edelstahl03. 4 Fuß oval konisch Edelstahl02. 4 Fuß eckig konisch Anthrazit04. 4 Fuß oval konisch Anthrazit05. 4 Fuß rund konisch Edelstahl06. 4 Fuß rund konisch Anthrazit08. Stativ rund konisch Anthrazit


Stadtbibliothek Graz - Achtung, Drachen! ; [Abenteuerliche Drachengeschichten für Erstleser] - lustige Drachengeschichten - Kinderbuch\nJack Kent ; Inge Meyer-Dietrich. Mit Bildern von Jack Kent ...\nZanklhof 1401SB03934 JE.J KEN Verfügbar 0\nGösting 1302SB00080 JE.J KEN Verfügbar 0\nBücherbus 1211SB00386 JE.J KEN Verfügbar 0


$101,120 (40% of Car Price)\n$2,158 for 7 years (84 months)\n$181,197 at the end of 7 years (84 months)\nYou get back $28,952 at the end of 10th year (PARF Rebate)\nFeb 2022 179,040 124,745 -25,472\nMar 2022 176,883 124,062 -24,685\nApr 2022 174,726 123,379 -23,889\nMay 2022 172,569 122,695 -23,085\nJun 2022 170,411 122,012 -22,272\nJul 2022 168,254 121,329 -21,452\nAug 2022 166,097 120,645 -20,623\nSep 2022 163,940 119,962 -19,786\nOct 2022 161,783 119,279 -18,940\nNov 2022 159,626 118,595 -18,087\nDec 2022 157,469 117,912 -17,225\nJan 2023 155,312 117,229 -16,355\nFeb 2023 153,155 116,545 -15,476\nMar 2023 150,997 115,862 -14,589\nApr 2023 148,840 115,179 -13,694\nMay 2023 146,683 114,495 -12,791\nJun 2023 144,526 113,812 -11,880\nJul 2023 142,369 113,129 -10,960\nAug 2023 140,212 112,445 -10,032\nSep 2023 138,055 111,762 -9,095\nOct 2023 135,898 111,079 -8,151\nNov 2023 133,741 110,395 -7,198\nDec 2023 131,583 109,712 -6,237\nJan 2024 129,426 109,029 -5,267\nFeb 2024 127,269 108,345 -4,290\nMar 2024 125,112 107,662 -3,304\nApr 2024 122,955 106,978 -2,310\nMay 2024 120,798 106,295 -1,307\nJun 2024 118,641 105,612 -296\nJul 2024 116,484 104,928 723\nAug 2024 114,327 104,245 1,750\nSep 2024 112,170 103,562 2,786\nOct 2024 110,012 102,878 3,829\nNov 2024 107,855 102,195 4,882\nDec 2024 105,698 101,512 5,942\nJan 2025 103,541 100,828 7,011\nFeb 2025 101,384 100,145 8,087\nMar 2025 99,227 99,462 9,173\nApr 2025 97,070 98,778 10,266\nMay 2025 94,913 98,095 11,368\nJun 2025 92,756 97,412 12,478\nJul 2025 90,598 96,728 13,596\nAug 2025 88,441 96,045 14,722\nSep 2025 86,284 95,362 15,857\nOct 2025 84,127 94,678 17,000\nNov 2025 81,970 93,995 18,152\nDec 2025 79,813 93,312 19,311\nJan 2026 77,656 92,628 20,479\nFeb 2026 75,499 91,945 21,655\nMar 2026 73,342 91,262 22,839\nApr 2026 71,185 90,578 24,032\nMay 2026 69,027 89,895 25,233\nJun 2026 66,870 89,212 26,442\nJul 2026 64,713 88,528 27,660\nAug 2026 62,556 87,845 28,885\nSep 2026 60,399 87,162 30,119\nOct 2026 58,242 86,478 31,362\nNov 2026 56,085 85,795 32,612\nDec 2026 53,928 85,112 33,871\nJan 2027 51,771 84,428 35,138\nFeb 2027 49,613 80,850 33,518\nMar 2027 47,456 80,166 34,802\nApr 2027 45,299 79,483 36,094\nMay 2027 43,142 78,800 37,394\nJun 2027 40,985 78,116 38,702\nJul 2027 38,828 77,433 40,019\nAug 2027 36,671 76,750 41,344\nSep 2027 34,514 76,066 42,677\nOct 2027 32,357 75,383 44,019\nNov 2027 30,199 74,700 45,368\nDec 2027 28,042 74,016 46,726\nJan 2028 25,885 73,333 48,093\nFeb 2028 23,728 69,754 46,572\nMar 2028 21,571 69,071 47,955\nApr 2028 19,414 68,388 49,346\nMay 2028 17,257 67,704 50,745\nJun 2028 15,100 67,021 52,153\nJul 2028 12,943 66,338 53,569\nAug 2028 10,786 65,654 54,993\nSep 2028 8,628 64,971 56,425\nOct 2028 6,471 64,288 57,866\nNov 2028 4,314 63,604 59,315\nDec 2028 2,157 62,921 60,772\nJan 2029 0 62,238 62,238\nFeb 2029 0 58,659 58,659\nMar 2029 0 57,976 57,976\nApr 2029 0 57,292 57,292\nMay 2029 0 56,609 56,609\nJun 2029 0 55,926 55,926\nJul 2029 0 55,242 55,242\nAug 2029 0 54,559 54,559\nSep 2029 0 53,876 53,876\nOct 2029 0 53,192 53,192\nNov 2029 0 52,509 52,509\nDec 2029 0 51,826 51,826\nJan 2030 0 51,142 51,142\nFeb 2030 0 47,564 47,564\nMar 2030 0 46,880 46,880\nApr 2030 0 46,197 46,197\nMay 2030 0 45,514 45,514\nJun 2030 0 44,830 44,830\nJul 2030 0 44,147 44,147\nAug 2030 0 43,464 43,464\nSep 2030 0 42,780 42,780\nOct 2030 0 42,097 42,097\nNov 2030 0 41,414 41,414\nDec 2030 0 40,730 40,730\nJan 2031 0 40,047 40,047\nFeb 2031 0 36,469 36,469\nMar 2031 0 35,785 35,785\nApr 2031 0 35,102 35,102\nMay 2031 0 34,419 34,419\nJun 2031 0 33,735 33,735\nJul 2031 0 33,052 33,052\nAug 2031 0 32,369 32,369\nSep 2031 0 31,685 31,685\nOct 2031 0 31,002 31,002\nNov 2031 0 30,318 30,318\nDec 2031 0 29,635 29,635\nJan 2032 0 28,952 28,952\n1. Feb 2022 103,277 179,040 28,822 -150,217 43,428 81,318 124,745 -25,472\n2. Mar 2022 105,434 176,883 28,136 -148,747 43,428 80,634 124,062 -24,685\n3. Apr 2022 107,591 174,726 27,458 -147,267 43,428 79,951 123,379 -23,889\n4. May 2022 109,748 172,569 26,788 -145,780 43,428 79,268 122,695 -23,085\n5. Jun 2022 111,906 170,411 26,127 -144,284 43,428 78,584 122,012 -22,272\n6. Jul 2022 114,063 168,254 25,474 -142,780 43,428 77,901 121,329 -21,452\n7. Aug 2022 116,220 166,097 24,829 -141,268 43,428 77,218 120,645 -20,623\n8. Sep 2022 118,377 163,940 24,192 -139,748 43,428 76,534 119,962 -19,786\n9. Oct 2022 120,534 161,783 23,564 -138,219 43,428 75,851 119,279 -18,940\n10. Nov 2022 122,691 159,626 22,944 -136,682 43,428 75,168 118,595 -18,087\n11. Dec 2022 124,848 157,469 22,332 -135,137 43,428 74,484 117,912 -17,225\n12. Jan 2023 127,005 155,312 21,728 -133,583 43,428 73,801 117,229 -16,355\n13. Feb 2023 129,162 153,155 21,133 -132,021 43,428 73,118 116,545 -15,476\n14. Mar 2023 131,319 150,997 20,546 -130,451 43,428 72,434 115,862 -14,589\n15. Apr 2023 133,477 148,840 19,967 -128,873 43,428 71,751 115,179 -13,694\n16. May 2023 135,634 146,683 19,397 -127,286 43,428 71,068 114,495 -12,791\n17. Jun 2023 137,791 144,526 18,835 -125,692 43,428 70,384 113,812 -11,880\n18. Jul 2023 139,948 142,369 18,281 -124,088 43,428 69,701 113,129 -10,960\n19. Aug 2023 142,105 140,212 17,735 -122,477 43,428 69,018 112,445 -10,032\n20. Sep 2023 144,262 138,055 17,198 -120,857 43,428 68,334 111,762 -9,095\n21. Oct 2023 146,419 135,898 16,668 -119,229 43,428 67,651 111,079 -8,151\n22. Nov 2023 148,576 133,741 16,147 -117,593 43,428 66,967 110,395 -7,198\n23. Dec 2023 150,733 131,583 15,635 -115,949 43,428 66,284 109,712 -6,237\n24. Jan 2024 152,891 129,426 15,131 -114,296 43,428 65,601 109,029 -5,267\n25. Feb 2024 155,048 127,269 14,634 -112,635 43,428 64,917 108,345 -4,290\n26. Mar 2024 157,205 125,112 14,147 -110,966 43,428 64,234 107,662 -3,304\n27. Apr 2024 159,362 122,955 13,667 -109,288 43,428 63,551 106,978 -2,310\n28. May 2024 161,519 120,798 13,196 -107,602 43,428 62,867 106,295 -1,307\n29. Jun 2024 163,676 118,641 12,733 -105,908 43,428 62,184 105,612 -296\n30. Jul 2024 165,833 116,484 12,278 -104,206 43,428 61,501 104,928 723 Break Even\n31. Aug 2024 167,990 114,327 11,832 -102,495 43,428 60,817 104,245 1,750\n32. Sep 2024 170,147 112,170 11,393 -100,776 43,428 60,134 103,562 2,786\n33. Oct 2024 172,305 110,012 10,963 -99,049 43,428 59,451 102,878 3,829\n34. Nov 2024 174,462 107,855 10,542 -97,314 43,428 58,767 102,195 4,882\n35. Dec 2024 176,619 105,698 10,128 -95,570 43,428 58,084 101,512 5,942\n36. Jan 2025 178,776 103,541 9,723 -93,818 43,428 57,401 100,828 7,011\n37. Feb 2025 180,933 101,384 9,326 -92,058 43,428 56,717 100,145 8,087\n38. Mar 2025 183,090 99,227 8,938 -90,289 43,428 56,034 99,462 9,173\n39. Apr 2025 185,247 97,070 8,557 -88,512 43,428 55,351 98,778 10,266\n40. May 2025 187,404 94,913 8,185 -86,727 43,428 54,667 98,095 11,368\n41. Jun 2025 189,561 92,756 7,822 -84,934 43,428 53,984 97,412 12,478\n42. Jul 2025 191,718 90,598 7,466 -83,132 43,428 53,301 96,728 13,596\n43. Aug 2025 193,876 88,441 7,119 -81,323 43,428 52,617 96,045 14,722\n44. Sep 2025 196,033 86,284 6,780 -79,504 43,428 51,934 95,362 15,857\n45. Oct 2025 198,190 84,127 6,449 -77,678 43,428 51,251 94,678 17,000\n46. Nov 2025 200,347 81,970 6,127 -75,843 43,428 50,567 93,995 18,152\n47. Dec 2025 202,504 79,813 5,812 -74,000 43,428 49,884 93,312 19,311\n48. Jan 2026 204,661 77,656 5,507 -72,149 43,428 49,201 92,628 20,479\n49. Feb 2026 206,818 75,499 5,209 -70,290 43,428 48,517 91,945 21,655\n50. Mar 2026 208,975 73,342 4,919 -68,422 43,428 47,834 91,262 22,839\n51. Apr 2026 211,132 71,185 4,638 -66,546 43,428 47,151 90,578 24,032\n52. May 2026 213,290 69,027 4,366 -64,662 43,428 46,467 89,895 25,233\n53. Jun 2026 215,447 66,870 4,101 -62,769 43,428 45,784 89,212 26,442\n54. Jul 2026 217,604 64,713 3,845 -60,869 43,428 45,101 88,528 27,660\n55. Aug 2026 219,761 62,556 3,597 -58,959 43,428 44,417 87,845 28,885\n56. Sep 2026 221,918 60,399 3,357 -57,042 43,428 43,734 87,162 30,119\n57. Oct 2026 224,075 58,242 3,125 -55,117 43,428 43,051 86,478 31,362\n58. Nov 2026 226,232 56,085 2,902 -53,183 43,428 42,367 85,795 32,612\n59. Dec 2026 228,389 53,928 2,687 -51,241 43,428 41,684 85,112 33,871\n60. Jan 2027 230,546 51,771 2,480 -49,290 43,428 41,001 84,428 35,138\n61. Feb 2027 232,703 49,613 2,282 -47,331 40,533 40,317 80,850 33,518\n62. Mar 2027 234,861 47,456 2,092 -45,365 40,533 39,634 80,166 34,802\n63. Apr 2027 237,018 45,299 1,910 -43,389 40,533 38,950 79,483 36,094\n64. May 2027 239,175 43,142 1,736 -41,406 40,533 38,267 78,800 37,394\n65. Jun 2027 241,332 40,985 1,571 -39,414 40,533 37,584 78,116 38,702\n66. Jul 2027 243,489 38,828 1,414 -37,414 40,533 36,900 77,433 40,019\n67. Aug 2027 245,646 36,671 1,265 -35,406 40,533 36,217 76,750 41,344\n68. Sep 2027 247,803 34,514 1,124 -33,389 40,533 35,534 76,066 42,677\n69. Oct 2027 249,960 32,357 992 -31,364 40,533 34,850 75,383 44,019\n70. Nov 2027 252,117 30,199 868 -29,331 40,533 34,167 74,700 45,368\n71. Dec 2027 254,275 28,042 752 -27,290 40,533 33,484 74,016 46,726\n72. Jan 2028 256,432 25,885 645 -25,240 40,533 32,800 73,333 48,093\n73. Feb 2028 258,589 23,728 546 -23,182 37,637 32,117 69,754 46,572\n74. Mar 2028 260,746 21,571 455 -21,116 37,637 31,434 69,071 47,955\n75. Apr 2028 262,903 19,414 372 -19,042 37,637 30,750 68,388 49,346\n76. May 2028 265,060 17,257 298 -16,959 37,637 30,067 67,704 50,745\n77. Jun 2028 267,217 15,100 232 -14,868 37,637 29,384 67,021 52,153\n78. Jul 2028 269,374 12,943 174 -12,769 37,637 28,700 66,338 53,569\n79. Aug 2028 271,531 10,786 124 -10,662 37,637 28,017 65,654 54,993\n80. Sep 2028 273,689 8,628 83 -8,546 37,637 27,334 64,971 56,425\n81. Oct 2028 275,846 6,471 50 -6,422 37,637 26,650 64,288 57,866\n82. Nov 2028 278,003 4,314 25 -4,289 37,637 25,967 63,604 59,315\n83. Dec 2028 280,160 2,157 8 -2,149 37,637 25,284 62,921 60,772\n84. Jan 2029 282,317 0 0 0 37,637 24,600 62,238 62,238 Loan Fully Paid\n85. Feb 2029 282,317 0 0 0 34,742 23,917 58,659 58,659\n86. Mar 2029 282,317 0 0 0 34,742 23,234 57,976 57,976\n87. Apr 2029 282,317 0 0 0 34,742 22,550 57,292 57,292\n88. May 2029 282,317 0 0 0 34,742 21,867 56,609 56,609\n89. Jun 2029 282,317 0 0 0 34,742 21,184 55,926 55,926\n90. Jul 2029 282,317 0 0 0 34,742 20,500 55,242 55,242\n91. Aug 2029 282,317 0 0 0 34,742 19,817 54,559 54,559\n92. Sep 2029 282,317 0 0 0 34,742 19,134 53,876 53,876\n93. Oct 2029 282,317 0 0 0 34,742 18,450 53,192 53,192\n94. Nov 2029 282,317 0 0 0 34,742 17,767 52,509 52,509\n95. Dec 2029 282,317 0 0 0 34,742 17,084 51,826 51,826\n96. Jan 2030 282,317 0 0 0 34,742 16,400 51,142 51,142\n97. Feb 2030 282,317 0 0 0 31,847 15,717 47,564 47,564\n98. Mar 2030 282,317 0 0 0 31,847 15,034 46,880 46,880\n99. Apr 2030 282,317 0 0 0 31,847 14,350 46,197 46,197\n100. May 2030 282,317 0 0 0 31,847 13,667 45,514 45,514\n101. Jun 2030 282,317 0 0 0 31,847 12,983 44,830 44,830\n102. Jul 2030 282,317 0 0 0 31,847 12,300 44,147 44,147\n103. Aug 2030 282,317 0 0 0 31,847 11,617 43,464 43,464\n104. Sep 2030 282,317 0 0 0 31,847 10,933 42,780 42,780\n105. Oct 2030 282,317 0 0 0 31,847 10,250 42,097 42,097\n106. Nov 2030 282,317 0 0 0 31,847 9,567 41,414 41,414\n107. Dec 2030 282,317 0 0 0 31,847 8,883 40,730 40,730\n108. Jan 2031 282,317 0 0 0 31,847 8,200 40,047 40,047\n109. Feb 2031 282,317 0 0 0 28,952 7,517 36,469 36,469\n110. Mar 2031 282,317 0 0 0 28,952 6,833 35,785 35,785\n111. Apr 2031 282,317 0 0 0 28,952 6,150 35,102 35,102\n112. May 2031 282,317 0 0 0 28,952 5,467 34,419 34,419\n113. Jun 2031 282,317 0 0 0 28,952 4,783 33,735 33,735\n114. Jul 2031 282,317 0 0 0 28,952 4,100 33,052 33,052\n115. Aug 2031 282,317 0 0 0 28,952 3,417 32,369 32,369\n116. Sep 2031 282,317 0 0 0 28,952 2,733 31,685 31,685\n117. Oct 2031 282,317 0 0 0 28,952 2,050 31,002 31,002\n118. Nov 2031 282,317 0 0 0 28,952 1,367 30,318 30,318\n119. Dec 2031 282,317 0 0 0 28,952 683 29,635 29,635\n120. Jan 2032 282,317 0 0 0 28,952 0 28,952 28,952


Ü35 Spielgemeinschaft BC Erlbach 1919 / SC Markneukirchen - BC Erlbach 1919 e.V.\nHome Mannschaften Alte Herren Ü35 Spielgemeinschaft BC Erlbach 1919 / SC Markneukirchen\nmarcus 8. April 2015 8. April 2015 Alte Herren, Mannschaften\nVorläufiger Spielplan Ü35 Freundschaftsspiele 2015:\nFr. 19.06 18.30 VFB Schöneck BCE/ SCM 17.15 Uhr Bayrische MKN\nFr. 10.07. 18.30 TSG Bau Hammerbrücke BCE/ SCM 17.15 Uhr Bayrische MKN\nFr. 24.07. 18.30 SCM/ BCE VFC Adorf/ Medizin Bad Elster Erlbach/ MKN\nFr. 14.08. 18.30 BCE/ SCM Vogtlandauswahl Erlbach/ MKN\nAnsprechpartner ist Sven Rahm – 01725465479


Reden Ist Schweigen (Album Version) - Blumentopf jetzt als MP3 in top Qualität herunterladen. Komplette Alben und Einzeltitel verfügbar - Amazon Music\nReden Ist Schweigen (Album Version)\nAus dem Album Kein Zufall\nIrgendwie Lieb' Ich Das I\nTag 1 (Album Version)\nUrsprüngliches Erscheinungsdatum : 3. September 1997\nErscheinungstermin: 3. September 1997\nCopyright: (P) 1997 Sony Music Entertainment (Germany) GmbH/Four Music/Columbia\nDauer: 4:13 MinutenGenres: Pop ASIN: B001SOZAFC\nAmazon Bestseller-Rang: Nr. 548.733 in Songs (Siehe Top 100 in Songs)


Auf einem Bildschirm im Polizeipräsidium präsentiert die Polizei ein Vergleichsbild der Wolfsmaske. (Foto: DPA)\nEr ist mit einer Wolfsmaske maskiert, zerrt das Mädchen ins Gebüsch und missbraucht es - eine Horrorvorstellung für Mütter und Väter.\nOmme kll Sllslsmilhsoos lholl Libkäelhslo ho hdl kll 43 Kmell mill Lmlsllkämelhsl shlkll ho kll sldmeigddlolo Mhllhioos lholl edkmehmllhdmelo Hihohh. Lho Lhmelll llihlß ma Bllhlms Emblhlblei oolll mokllla slslo Sllslsmilhsoos ho Lmllhoelhl ahl dmesllla dlmoliilo Ahddhlmome sgo Hhokllo slslo klo Amoo. Kll Kloldmel hma omme Mosmhlo kll Dlmmldmosmildmembl Aüomelo H eolümh ho lhol Edkmehmllhl hlh Aüomelo. Khl Hleölklo aüddlo kllel ühllelüblo, gh ld hlh kll Igmhlloos ha Sgiieos kld sglhldllmbllo Sllkämelhslo Bleill slslhlo eml.\nKll 43-Käelhsl dgii kmd Aäkmelo ma Khlodlms hod Slhüdme slellll ook dmesll dlmolii ahddhlmomel emhlo. Kmhlh llos ll klo Llahlliooslo eobgisl lhol Sgibdamdhl. Khl omea klo Amoo ma Kgoolldlms bldl. Ll hdl klo Mosmhlo eobgisl oolll mokllla slslo dlmoliilo Ahddhlmomed sgo Hhokllo sglhldllmbl ook sml bül lhohsl Kmell ho lhola edkmehmllhdmelo Hlmohloemod oolllslhlmmel, hlsgl ll eoillel ho lholl lellmelolhdmelo Sgeoslalhodmembl sgeoll.\nSloo ld säellok lholl dgimelo Igmhlloos eo lholl Dllmblml hgaal, dmemilll dhme kmd Mal bül Amßllslisgiieos mid Bmmemobdhmel lho, shl kmd Elolloa Hmkllo Bmahihl ook Dgehmild ho Oölkihoslo kll Kloldmelo Ellddl-Mslolol ahlllhill. Khl Bmmemobdhmel hdl khldla Elolloa moslsihlklll. „Kll Sllkämelhsl sml mobslook lhmelllihmell Loldmelhkoos ha Amßllslisgiieos oolllslhlmmel ook hlbmok dhme ho kll Igmhlloosddlobl kld dgslomoollo Elghlsgeolod“, llhiälll khl Bmmemobdhmel.\n„Lho Lhoelibmii hdl kmd dhmell ohmel“, dmsll kll Imokldsgldhlelokl kld Lilllosllhmokd, Amllho Iösl, kll kem. Ooo aüddl slomo slelübl sllklo, gh ook sg Bleill hlh kll Lhodmeäleoos kld Amoold slammel sglklo dlhlo. Ühll lho Slldmslo höool hhdimos ool slaolamßl sllklo. Ll hllgoll, kmdd sllmkl khl hmkllhdmel Kodlhe ohmel mid imdme slill.\nDllmblälll höoolo eo Bllhelhlddllmblo sllolllhil sllklo, khl ho Kodlhesgiieosdmodlmillo sllhüßl sllklo, gkll eoa Amßllslisgiieos ho kmbül hldgoklld modsldlmlllllo edkmehmllhdmelo Hihohhlo ook Lolehleoosdmodlmillo. Khldl sllklo mome mid bgllodhdmel Hihohhlo hlelhmeoll. Kmd hmoo hlhdehlidslhdl bül klgslomheäoshsl gkll edkmehdme hlmohl Alodmelo eolllbblo. Ha Bllhdlmml shhl ld 14 dgimel Lholhmelooslo, ho klolo llsm 2600 Alodmelo oolllslhlmmel dhok.\nÜhll Igmhllooslo loldmelhklo omme Mosmhlo kld Elolload Hmkllo Bmahihl ook Dgehmild khl Ilhlooslo kld Amßllslisgiieosd oolll mokllla ho Eodmaalomlhlhl ahl kll mid Sgiidlllmhoosdhleölkl ook kll Egihelh. „Slookdäleihme sllklo Igmhlloosdloldmelhkooslo sgo kll Bmmemobdhmel ohmel ühllelübl“, ehlß ld. Kmd emddhlll ool ho Lhoelibäiilo, „llsm mobslook lhold slmshllloklo Igmhlloosdahddhlmomed gkll lholl dmeslllo Dllmblml ha Lmealo lholl Igmhlloos“. Bmiid llbglkllihme sülklo bgllodhdme-edkmehmllhdmel Lmellllo lhohlegslo.\nOolllklddlo smloll kll Hmkllhdmel Lilllosllhmok sgl Emohh ook lhlb eo alel Ehshimgolmsl mob. „Hhokll külblo kllel hlhol Mosdl hlhgaalo“, dmsll khl dlliislllllllokl Imokldsgldhlelokl Moslim Smohl-Dmegeb. Dhl laebmei, Lilllo höoollo hello Hhokllo dmslo: „Dmemol slomo eho. Slel ohmel ho Emlhd, sloo kgll ohlamok hdl“. „Mhll Hhokll dgiillo ohmel ho Emohh sllbmiilo. Shlil Lilllo emhlo smeodhoohsl Mosdl, slhi ld ma eliiihmello Lms emddhllll.“\nEslh Emddmolhoolo emlllo khl Lml omme Mosmhlo kll Egihelh sldlelo ook dhme lldl deälll hlh klo Hlmallo slalikll. Smohl-Dmegeb omea kmd eoa Moimdd bül Sldliidmembldhlhlhh: „Ahl hdl ohmel himl, shl kmd sgl klo Moslo kll Öbblolihmehlhl emddhlllo hmoo.“ Hel Lhoklomh dlh, kmdd dhme khl Alodmelo haall slohsll llmollo, lhoeodmellhllo gkll eoahokldl khl Egihelh eo hobglahlllo - „mome mob khl Slbmel eho, kmdd amo ami lhol Dhlomlhgo bmidme lhodmeälel“. Ehll dlh alel Dlodhhhihläl oglslokhs.


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Astrophysiker und Fernsehmoderator Harald Lesch im Interview\n7. Juli 2020 um 16:53 Uhr\nHarald Lesch, Physiker und Fernsehmoderator. Foto: imago images/Rainer Unkel/imago stock&people via www.imago-images.de\nMünchen Geheimnisvolle Steinkreise, gefährliche Asteroiden oder mysteriöse Felszeichnungen: Fernsehmoderator Harald Lesch kennt sich damit aus. Im Interview spricht er über die Sendung „Die große ‚Terra X‘-Show“, unlösbare Rätsel und das Coronavirus.\nmiosveiGehnlle ietnersieSk, riclfhhgeäe soeeArnidt oedr ityesrsmöe sunczel:Fngeienh lRseät iew eeisd shteen mi ntMkteilupt onv „Dei ßoerg rr‚Tae Xh,“S-o‘w itm rde asd ZFD ma henutieg cwottihM ruz ebsnte edtSeeizn dne reZcnuauhs hsesirceoöh ssfschnaWite afu nuemtlsetaarh rtA nrgnebaehni lIn .wil rde onv oJnehnas .B Keernr erdrnemeito etnnsugeRda lpesnei wzei erPsmnatneominet um 20000. ourE rfü ienen netug cwkeZ.\nlsA txeprEe tim bdiea sit der sproithsrAeyk ndu thpsNplioaouhr draHal cL,seh dne livee rshaeuZcu asu der hseWFrsnseZD-iie r„rTea X“ nnknee dun erd uz den nketsnatbeen hnnslrisWtatijcaoeesssfnu mi hedcsnute nFeheesnr hl.täz Im räcspheG tim iraMtn eeWbr hsprict er rübe ide edS,unng enlsaruöb tälesR udn asd .nroausvoirC\nreHr cehL,s ni Di„e eßrgo ‚raTer -S‘“wohX hgte se diemlas um tläesR der Wt.le ceWehl Rsleät sind d?sa\naadHlr shLec: rWi esbhtängfeic uns mit oeA,ndesrti red fiseTee ored uach eoheSt.enng imBe ätlRse um dne eertnikiSs ovn htngeoneSe ni angEdln tibg se nnedpasne unee rTeenioh brrdaeü, wie ageun desei rneiesig tSieen in rde ezsnttJegiinu fua lH,nzoeollr Hguezknlol roed reab afu nilfeetnWgecdhee hidtnro titarerpnosrt oewnrd dins.\nDssa riAuihreesßcd wetas atdim zu utn ,thaten iew uhac csnoh suierpeltk udrw,e rdüwen Sei ul?sacesineßh\n:eLhsc ,Ja edi iwntrMkugi erenrus isnrceehußraid dreeunF derwü cih zang rkal si,hßeenclusa sda sit nlöidBns lt.cah() ohngenSete dweru mti rshe lvei rKfta dun reAibt von enMenhsc r,ereitcth aandr bigt se ieennk .weielZf\nasW its nden hIr stelseib elt?sältWer\neLc:sh Serh tziresfani nib hci onv dem ern,snelsgehAtcdioai der rov 15 inelMloni nhrJae eib rldgniNnöe ntgtedtuaefns tah ndu um end se ni rde egdnSnu cauh eehgn wid.r aMn usms ichs lam veoln:esrlt Der csinhaglE sedise rnketcsoeGsnbeis ovn hrermeen ndutrhe eentrM sDruheecmsr hta ahilnbenr onv kSudenen lseal neLbe mi msUeirk nov 001 rmeteinlKo e.rrösttz Da hnat ,anm lechew hnueulrcheigeen eKtäfr ma erWk aren.w\nnanK os ewsta eridew ersapeins?\nhLc:es Im aMi erts idsn nfüf erdo essch teesdonriA in mneie stAdabn von eehnemrr oMelilinn eetlmnroKi an uns tbseogurrviecah, ide anehb rwi n.ikbeemomtm aarDn hseti nma a,zwr asds riw ni der bcnÜuerwgha wtrleiimelet zagn ugt oenrgdwe ins,d earb es mnkoem uahc rmemi aml ereiwd rckenBo sau dem lelltaW auf ide dreE zu, ide irw raphubtüe chitn oerd stre hres sätp she.en Dsa ist wesat, das himc ikrcwilh e:bmttrui iWr erndüf nde imHmle tcihn urn vassip ocbaht,nbee snrneod nsmsüe hauc vtkai imt raRad cnha nteedsArio e.sucnh Dlsheab bni ich chau a,üdfr fau rde küeReitsc sed odMesn iene ßorge earadaaRnlg ehletuinlnzs. aurDas idrw in saherabebr Ziet wlho nsctih drwe,ne reab madti nntnkeö iwesissliepbee uach bktOeje saferst edern,w die sua edr ehäN edr enoSn .omkemn\nsWa äwer ednn das tsilhcmems zr?inSaeo\nsLce:h en,Wn iwe rov 56 oiielnMnl Jrha,ne nie hote-02mrKr-lericeeB fua red erEd äsn,hlcgite eräw se asd neEd edr c.Mstiehhne Je eahcdmn wo es t,lchesägin nnak erab uhac onsch nei ölskremrHmpie nvo nur miene Kmeeltior reößG mehciliz emtdircaash uinnkrAwsgue nh,bae ndne reunes isccrionteethhhe atniiosliivZ ist emenunig .dvbrawunre nkDnee iSe rnu na ide ui,saTmns eid fua eid snKüte neolltu,rz newn ein scorleh idertAso nsi reMe teak.crh sDa düwre asd oletat haoCs u,elsnösa da tis anoroC thsnic eg.egnda\nrneWde uns eerdaigrt iamnePedn nfkitgü tföer hesmi?ecnuh\nesLhc: aD hcsi dei eMnsnche uach in eänmebLusern eib,utesnra wo ise ielihgnetc tishcn uz neuhsc ,nbhea ndu caudhdr ned nieerT mremi heärn eomkmn, sntnteehe uen,dgBenngi dei enirV thnsneete ne.assl eDise eeturmni adnn in erein mmibtneset seWei dnu neöknn rzu Gfrhea erwde.n asD its dei niee tie.eS hiBnecedkl sti hcua, dssa iwr es dhucr ads kemlidbitaeng neutfAua esd osetfesmraPr imt eenmi nueen lbaoBori zu tnu :noebmkme Da eendwr ni tnuZukf ni iienrbSi deor aadKan rniekboM sua med ndeoB ommek,n dei gdzeiseunat hJear fengnrreioe nrawe udn eieermwgöhslic nllesbfea urz rehGfa üfr ide hnheteicMs reedwn .kntnöen\nGbit se eiinehtclg rüf sdeje tsäeRl ieen olrnataie ärurnklE?g\nLes:ch Asl irtkhreisc oiaattslRni eatlh hci himc tsre naimel ,adrna assd es afu dre lteW iuätlhndgzcsr mit teehnrc eingDn zhtgue und dssa edi kzgNmneteertgiiutßsaäe get.lne Das ,hißte hci nnak mmire enine negnüetrvfni Gdurn drüfa end,fni waumr Dngei erpi,enssa dnu muss werde ihßdAueiecsrr noch tteGrö uz Rtea hzniee. sNsdihtoertctotz bgti es meäPonhne, dei neeni tczuhsän mieanl ntuanes sna.sle Mna fdra hisc adnn run thinc fodo nunste,a nrnsdoe smsu den gnDien fua ned drGun ne.ehg\nrAeb iSe nehab codh iscreh cuah snhoc rov eeinm etäslR krleniaitpeu müs.sne\neL:sch cuh,saDru ndu awzr vor dme enthaleVr sde Mnhncees – ads tsi ürf ichm sad ßeölarrltge äsleRt tüh.bpuear aumrW utn wir hitcn ,sda aws rwi unt nsmü,est lhboow wri gzna enuag w,ienss dssa es ntaeg ernwde m?ssu roiwthcSt iKlaednwalm: Wramu salnse riw dei arerK redwi eesnrebs snsWesi kmpettol nggee ide anWd fnah?re Dsa its irm vlöilg ts.hetäfral


Schloss Burgellern (Schesslitz) - Hotel reviews, photos, rates - TripAdvisor\nSchloss Burgellern Hotel, Schesslitz\nSchesslitz Visitors Guide\nGreat value on a similar hotel Brauereigasthof Drei Kronen Memmelsdorf, Bavaria 15 Reviews Still looking for a hotel? Highly rated hotels in or near Schesslitz\nINR7,062 - 10,097\n15 Reviews ABS:HotelCheckRates-d639156?&src=Hotel_Review&fromServlet=Hotel_Review&Action=QC_AlsoViewedAboveFold\nMemmelsdorf, Bavaria Kurhotel an der Obermaintherme\nMemmelsdorf, Bavaria More Hotel - Restaurant Erich Rodiger\nStaffelstein, Bavaria Tandem Hotel\nBamberg, Bavaria Berggasthof Banzer Wald\n3 Reviews ABS:HotelCheckRates-d1737933?&src=Hotel_Review&fromServlet=Hotel_Review&Action=QC_AlsoViewedAboveFold\nQuestions on Schesslitz?\n788 hotels, 64,017 Reviews Macau hotels\n10 hotels, 250 Reviews Ranau hotels


König, Hans-Joachim, “Decolonization”, in: Encyclopedia of Early Modern History Online, Editors of the English edition: Graeme Dunphy, Andrew Gow. Original German Edition: Enzyklopädie der Neuzeit. Im Auftrag des Kulturwissenschaftlichen Instituts (Essen) und in Verbindung mit den Fachherausgebern herausgegeben von Friedrich Jaeger. Copyright © J.B. Metzlersche Verlagsbuchhandlung und Carl Ernst Poeschel Verlag GmbH 2005–2012. Consulted online on 25 January 2021 <http://dx.doi.org/10.1163/2352-0272_emho_COM_031001>


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GCD :: Issue :: Die Gruft von Graf Dracula #20\nDie Gruft von Graf Dracula #20\nHier kommt Doktor Sun (Table of Contents: 1)\nOrrgo... der Unüberwindliche (Table of Contents: 2)\n1. Hier kommt Doktor Sun\n2. Orrgo... der Unüberwindliche


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Veranstaltungen für 15. August 2020 – Assistenzhundeschule\n08/15/2020\t15. August 2020


seq1 = Columns 1 through 30 0 1 1 2 1 2 2 3 1 2 2 3 2 3 3 4 1 2 2 3 2 3 3 4 2 3 3 4 3 4 Columns 31 through 53 4 5 1 2 2 3 2 3 3 4 2 3 3 4 3 4 4 5 2 3 3 4 3 seq2 = Columns 1 through 30 0 1 1 2 1 2 2 3 1 2 2 3 2 3 3 4 1 2 2 3 2 3 3 4 2 3 3 4 3 4 Columns 31 through 52 4 5 1 2 2 3 2 3 3 4 2 3 3 4 3 4 4 5 2 3 3 4\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test1 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 0 0 0 0 0 1 0 0 0 0 1 1 0 0 0 1 0 1 0 0 1 1 1 1 0 1 0 0 0 1 Columns 31 through 41 1 1 0 1 1 0 0 1 0 1 1 seq2 = Columns 1 through 30 0 0 0 0 0 1 0 0 0 0 1 1 0 0 0 1 0 1 0 0 1 1 1 1 0 1 0 0 0 1 Columns 31 through 40 1 1 0 0 1 0 0 1 0 1\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test2 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 1 0 0 0 0 1 0 1 0 1 1 1 0 1 1 0 0 0 1 1 1 1 1 0 0 1 1 0 1 1 Columns 31 through 41 0 1 0 0 0 0 1 0 1 0 1 seq2 = Columns 1 through 30 1 0 0 0 0 1 0 1 0 1 1 1 0 1 1 0 0 0 1 1 1 1 1 0 0 1 1 0 1 0 Columns 31 through 40 0 1 0 0 0 0 1 0 1 0\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test3 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 1 1 1 0 1 1 0 0 1 1 1 0 0 1 0 0 1 1 1 0 1 0 0 0 0 2 1 0 0 1 Columns 31 through 54 0 0 1 0 1 0 1 1 0 0 1 1 0 0 0 1 0 0 0 1 2 0 1 1 seq2 = Columns 1 through 30 1 1 1 0 1 1 0 0 1 1 1 0 0 1 0 0 1 1 1 0 1 0 0 0 0 2 1 0 0 1 Columns 31 through 54 0 0 1 0 1 0 1 1 0 0 1 1 0 0 0 1 0 0 0 1 2 0 1 1\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test4 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 1 4 4 0 4 8 0 0 4 4 8 0 0 8 0 0 4 8 4 0 8 0 0 0 0 12 8 0 8 8 Columns 31 through 51 0 0 4 0 8 0 4 8 0 0 8 8 0 0 0 8 0 0 0 4 12 seq2 = Columns 1 through 30 1 4 4 0 4 8 0 0 4 4 8 0 0 8 0 0 4 8 4 0 8 0 0 0 0 12 8 0 0 8 Columns 31 through 51 0 0 4 0 8 0 4 8 0 0 8 8 0 0 0 8 0 0 0 4 12\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test5 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 0 1 1 1 1 0 1 1 1 1 0 1 1 1 1 0 1 1 1 0 0 1 1 1 1 0 1 1 1 0 Columns 31 through 41 0 1 1 1 1 0 1 1 1 1 0 seq2 = Columns 1 through 30 0 1 1 1 1 0 1 1 1 1 0 1 1 1 1 0 1 1 1 1 0 1 1 1 1 0 1 1 1 1 Columns 31 through 40 0 1 1 1 1 0 1 1 0 1\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test6 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 1 1 1 1 1 2 1 2 1 1 2 2 1 0 2 2 1 0 1 0 2 2 2 0 1 3 0 1 2 2 Columns 31 through 51 2 2 1 2 0 4 1 0 0 0 2 0 2 0 2 2 0 0 1 3 3 seq2 = Columns 1 through 30 1 1 1 1 1 2 1 2 1 1 2 2 1 0 2 2 1 0 1 0 2 2 2 0 1 3 0 1 2 2 Columns 31 through 51 2 2 1 2 0 4 1 0 0 0 2 0 2 0 2 2 0 0 1 3 3\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test7 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 1 2 2 1 2 1 1 2 2 1 1 2 1 2 2 1 2 1 1 2 1 2 2 1 1 2 2 1 2 1 Columns 31 through 51 1 2 2 1 1 2 1 2 2 1 1 2 2 1 2 1 1 2 1 2 2 seq2 = Columns 1 through 30 1 2 2 1 2 1 1 2 2 1 1 2 1 2 2 1 2 1 1 2 1 2 2 1 1 2 2 1 2 1 Columns 31 through 51 1 2 2 1 1 2 1 2 2 1 1 2 2 1 2 1 1 2 1 2 2\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test8 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 1 1 1 1 1 2 1 2 1 1 2 2 1 1 2 1 1 1 1 1 2 1 2 2 1 1 1 1 2 2 Columns 31 through 45 1 2 1 1 1 1 1 2 1 1 2 2 1 1 2 seq2 = Columns 1 through 30 1 1 1 2 1 2 1 2 1 1 2 2 1 1 2 1 1 1 1 1 2 1 2 2 1 1 1 1 2 2 Columns 31 through 45 1 2 1 1 1 1 1 2 1 1 2 2 1 1 2\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test9 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 0 1 1 2 1 3 2 3 2 4 3 5 2 5 3 4 1 5 4 7 3 8 5 7 2 7 5 8 3 7 Columns 31 through 46 4 5 1 6 5 9 4 11 7 10 3 11 8 13 5 12 seq2 = Columns 1 through 30 0 1 1 2 1 3 2 3 1 4 3 5 2 5 3 4 2 5 4 7 3 8 5 7 2 7 5 8 3 7 Columns 31 through 46 4 5 1 6 5 9 4 11 7 10 3 11 8 13 5 12\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test10 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 1 2 2 4 2 4 4 8 2 4 4 8 4 8 8 16 2 4 4 8 4 8 8 16 4 8 8 16 8 16 Columns 31 through 44 16 32 2 4 4 8 4 8 8 16 4 8 8 16 seq2 = Columns 1 through 30 1 2 2 4 2 4 4 8 2 4 4 8 4 8 8 16 2 4 4 8 4 8 8 16 4 8 8 16 8 16 Columns 31 through 44 16 32 2 4 4 8 4 8 8 16 4 8 8 16\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test11 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 0 1 1 0 1 1 0 1 1 1 0 1 0 1 1 0 1 1 1 1 1 0 0 1 0 1 1 0 1 1 Columns 31 through 50 1 0 1 0 1 1 1 1 1 0 1 1 0 1 1 1 1 1 0 1 seq2 = Columns 1 through 30 0 1 1 0 1 1 0 1 1 1 1 1 0 1 1 0 1 1 1 1 0 0 1 1 0 1 1 0 1 1 Columns 31 through 49 0 1 1 0 1 1 1 1 1 0 1 1 0 1 0 1 1 1 0\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test12 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = 1 6 6 30 6 30 30 54 6 102 30 78 30 78 54 150 6 102 102 126 30 270 78 150 30 150 78 390 54 174 seq2 = 1 6 6 30 6 30 30 54 6 102 30 78 30 78 54 150 6 102 102 126 30 270 78 150 30 150 78 318 54 174\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test13 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 1 1 1 2 1 2 2 2 1 4 2 3 2 3 2 5 1 4 4 4 2 7 3 4 2 5 3 9 2 8 Columns 31 through 45 5 5 1 11 4 7 4 6 4 10 2 7 7 7 3 seq2 = Columns 1 through 30 1 1 1 2 1 2 2 2 1 4 2 3 2 3 2 5 1 4 4 4 2 7 3 4 2 5 3 9 2 5 Columns 31 through 44 5 4 1 11 4 7 4 6 4 10 2 7 7 7\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test14 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 0 0 0 1 0 0 1 1 0 1 0 1 1 0 1 2 0 0 1 1 0 2 1 1 1 0 0 2 1 0 Columns 31 through 44 2 1 0 2 0 2 1 0 1 2 0 0 2 1 seq2 = Columns 1 through 30 0 0 0 1 0 0 1 1 0 1 0 1 1 0 1 2 0 0 1 1 0 2 1 1 1 0 0 2 1 0 Columns 31 through 43 2 1 0 2 0 2 1 0 1 2 0 0 2\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test15 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 1 1 1 0 1 0 0 0 1 0 0 1 0 1 0 0 1 0 0 0 0 1 1 1 0 0 1 1 1 1 Columns 31 through 41 1 1 1 1 0 1 0 0 0 1 0 seq2 = Columns 1 through 30 1 1 1 0 1 0 0 0 1 0 0 1 0 1 0 1 1 0 0 0 0 1 1 1 0 0 1 1 0 1 Columns 31 through 40 0 1 1 1 0 1 0 0 0 1\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test16 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = 1 24 24 96 24 144 96 192 24 312 144 288 96 336 192 576 24 432 312 480 144 768 288 576 96 744 336 seq2 = 1 24 24 96 24 144 96 192 24 312 144 288 96 336 192 576 24 432 312 480 144 768 288 576 96 744\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test17 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 0 0 0 1 0 0 1 1 0 1 0 1 1 0 1 2 0 0 1 1 0 2 1 1 2 0 0 2 1 0 Columns 31 through 44 2 1 0 2 0 2 1 0 1 2 0 0 2 1 seq2 = Columns 1 through 30 0 0 0 1 0 0 1 1 0 1 0 1 1 0 1 2 0 0 1 1 0 2 1 1 1 0 0 2 1 0 Columns 31 through 43 2 1 0 2 0 2 1 0 1 2 0 0 2\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test18 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 0 1 1 2 1 2 2 3 1 2 2 3 2 3 3 4 1 2 2 3 2 3 3 4 2 3 3 4 3 4 Columns 31 through 53 4 5 1 2 2 3 2 3 3 4 2 3 3 4 3 4 4 5 2 3 3 4 3 seq2 = Columns 1 through 30 0 1 1 2 1 2 2 3 1 2 2 3 2 3 3 4 1 2 2 3 2 3 3 4 2 3 3 4 3 4 Columns 31 through 52 4 5 1 2 2 3 2 3 3 4 2 2 3 4 3 4 4 5 2 3 3 4\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test19 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 1 1 1 0 1 1 0 1 1 1 1 0 0 1 0 0 1 1 1 0 1 0 0 0 0 2 1 0 0 1 Columns 31 through 54 0 0 1 0 1 0 1 1 0 0 1 1 0 0 0 1 0 0 0 1 2 0 1 1 seq2 = Columns 1 through 30 1 1 1 0 1 1 0 0 1 1 1 0 0 1 1 0 1 1 1 0 1 0 0 0 0 2 1 0 0 1 Columns 31 through 54 0 0 1 0 1 0 1 1 0 0 1 1 0 0 0 1 0 0 0 1 2 0 1 1\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test20 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 1 1 1 1 1 2 1 2 1 1 1 2 1 0 2 2 1 0 1 0 2 2 2 0 1 3 0 1 2 2 Columns 31 through 51 2 2 1 2 0 4 1 0 0 0 2 0 2 0 2 2 0 0 1 3 3 seq2 = Columns 1 through 30 1 1 1 1 1 2 1 2 1 1 2 2 1 0 2 2 1 0 1 0 1 2 2 0 1 3 0 1 2 2 Columns 31 through 51 2 2 1 2 0 4 1 0 0 0 2 0 2 0 2 2 0 0 1 3 3\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test21 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 1 2 2 1 2 1 1 2 2 1 2 2 1 2 2 1 2 1 1 2 1 2 2 1 1 2 2 1 2 1 Columns 31 through 51 1 2 2 1 1 2 1 2 2 1 1 2 2 1 2 1 1 2 1 2 2 seq2 = Columns 1 through 30 1 2 2 1 2 1 1 2 2 1 1 2 1 2 2 1 2 1 1 2 2 1 2 1 1 2 2 1 2 1 Columns 31 through 51 1 2 2 1 1 2 1 2 2 1 1 2 2 1 2 1 1 2 1 2 2\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test22 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 1 0 0 1 0 1 1 0 0 1 1 0 1 0 0 1 1 0 1 0 1 0 0 0 1 0 0 1 0 1 Columns 31 through 53 1 0 0 1 1 0 1 0 0 1 1 0 0 1 0 1 1 0 1 0 0 1 0 seq2 = Columns 1 through 30 1 0 0 1 0 1 1 0 0 1 1 0 1 0 0 1 0 1 1 0 1 0 0 1 1 0 0 1 0 1 Columns 31 through 52 1 0 1 1 0 0 1 0 0 1 1 0 0 1 0 1 0 0 1 0 0 1\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test23 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 1 4 4 0 4 8 0 0 4 4 8 0 0 8 0 0 4 8 4 0 8 0 0 0 0 12 8 0 0 8 Columns 31 through 51 0 0 4 0 8 0 4 8 0 0 8 8 0 0 0 8 0 0 0 4 12 seq2 = Columns 1 through 30 1 4 4 0 4 8 0 0 4 4 8 0 0 8 0 0 4 8 4 0 8 0 0 0 0 12 8 0 0 8 Columns 31 through 51 0 0 4 0 8 0 4 8 0 0 8 8 0 0 0 8 0 0 0 4 12\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test24 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 0 1 1 0 1 -1 0 1 1 -2 -1 1 0 1 1 0 1 -3 -2 1 -1 2 1 -1 0 1 1 0 1 -1 Columns 31 through 53 0 1 1 -4 -3 1 -2 3 1 -2 -1 3 2 -1 1 -2 -1 1 0 1 1 0 1 seq2 = Columns 1 through 30 0 1 1 0 1 -1 0 1 1 -2 -1 1 0 1 1 0 1 -3 -2 1 -1 2 1 -1 0 1 1 0 1 -1 Columns 31 through 52 0 1 1 -4 -3 1 -2 3 1 -2 -1 3 2 -1 1 -2 -1 1 0 1 1 0\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test25 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 0 1 1 2 1 3 2 2 1 4 3 3 2 3 2 2 1 5 4 4 3 4 3 3 2 4 3 3 2 3 Columns 31 through 48 2 2 1 6 5 5 4 5 4 4 3 5 4 4 3 4 3 3 seq2 = Columns 1 through 30 0 1 1 2 1 3 2 2 1 4 3 3 2 3 2 2 1 5 4 4 3 4 3 3 2 4 3 3 2 3 Columns 31 through 48 2 2 1 6 5 5 4 5 4 4 3 5 4 4 3 4 3 3\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test26 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 1 0 0 1 0 1 1 0 0 1 1 0 1 0 0 1 0 1 1 0 1 0 0 1 1 0 0 1 0 1 Columns 31 through 53 1 0 0 1 1 0 1 0 0 1 1 0 0 1 0 1 1 0 1 0 0 1 0 seq2 = Columns 1 through 30 1 0 0 1 0 1 1 0 0 1 1 0 1 0 0 1 0 1 1 0 1 0 0 1 1 0 0 1 0 1 Columns 31 through 52 1 0 0 1 1 0 1 0 0 1 1 0 0 1 0 1 1 0 1 0 0 1\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test27 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 1 2 1 1 1 1 1 2 1 1 1 1 1 1 2 1 1 1 1 1 1 1 2 2 1 1 1 2 2 2 Columns 31 through 45 1 2 1 2 1 1 1 1 1 2 1 1 1 1 1 seq2 = Columns 1 through 30 1 1 2 1 1 1 1 2 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 2 1 1 1 2 2 2 Columns 31 through 45 1 2 1 1 1 1 1 1 1 2 1 1 1 1 2\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test28 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 0 1 1 0 1 0 0 1 1 0 0 1 0 1 1 0 1 0 0 1 0 1 1 0 0 1 1 0 1 0 Columns 31 through 53 0 1 1 0 0 1 0 1 1 0 0 1 1 0 1 0 0 1 0 1 1 0 1 seq2 = Columns 1 through 30 0 1 1 0 1 0 0 1 1 0 0 1 0 1 1 0 1 0 0 1 0 1 1 0 0 1 1 0 1 0 Columns 31 through 52 0 1 1 0 0 1 0 1 1 0 0 1 1 0 1 0 0 1 0 1 1 0\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test29 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 0 1 1 1 1 0 1 1 1 1 0 1 1 1 1 0 1 1 1 1 0 1 1 1 1 0 1 1 1 1 Columns 31 through 41 0 1 1 1 1 0 1 1 1 1 0 seq2 = Columns 1 through 30 0 1 1 1 1 0 1 1 1 1 0 1 1 1 1 0 1 1 1 1 0 1 1 1 1 0 1 1 1 1 Columns 31 through 40 0 1 1 1 1 0 1 1 1 1\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test30 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 0 0 0 0 0 1 0 1 0 0 1 0 0 1 1 0 0 1 0 1 1 0 0 0 0 0 1 0 1 0 Columns 31 through 41 0 1 0 0 1 1 0 0 1 0 1 seq2 = Columns 1 through 30 0 0 0 0 0 1 0 1 0 0 1 0 0 1 1 0 0 1 0 1 1 0 0 0 0 0 1 0 1 0 Columns 31 through 40 0 1 0 0 1 1 0 0 1 0\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test31 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = 1 24 24 96 24 144 96 192 24 312 144 288 96 336 192 576 24 432 312 480 312 768 288 576 96 744 336 seq2 = 1 24 24 96 24 144 96 192 24 312 144 288 96 336 192 576 24 432 312 480 144 768 288 576 96 744\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test32 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 1 2 2 4 2 4 4 8 2 4 4 8 4 8 8 16 2 4 4 8 4 8 8 16 4 16 8 16 8 16 Columns 31 through 44 16 32 2 4 4 8 4 8 8 16 4 8 8 16 seq2 = Columns 1 through 30 1 2 2 4 2 4 4 8 2 4 4 8 4 4 8 16 2 4 4 8 4 8 8 16 4 8 8 16 8 16 Columns 31 through 44 16 32 2 4 4 8 4 8 8 16 4 8 8 16\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test33 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 0 0 0 0 0 1 0 0 0 0 1 1 0 0 0 1 0 1 0 0 1 1 1 1 0 1 0 0 0 1 Columns 31 through 41 1 1 0 0 1 0 0 1 0 1 1 seq2 = Columns 1 through 30 0 0 0 0 0 1 0 0 0 0 1 1 0 0 0 1 0 1 0 0 1 1 1 1 0 1 0 0 0 1 Columns 31 through 40 1 1 0 0 1 0 0 1 0 1\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test34 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 1 0 0 0 0 1 0 1 0 1 1 1 0 1 1 0 0 0 1 1 1 1 1 0 0 1 1 0 1 0 Columns 31 through 41 0 1 0 0 0 0 1 0 1 0 1 seq2 = Columns 1 through 30 1 0 0 0 0 1 0 1 0 1 1 1 0 1 1 0 0 0 1 1 1 1 1 0 0 1 1 0 1 0 Columns 31 through 40 0 1 0 0 0 0 1 0 1 0\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test35 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 1 0 0 1 0 0 1 1 0 0 0 0 1 0 1 1 0 1 0 1 0 0 0 1 1 1 0 1 1 1 Columns 31 through 41 1 1 0 0 1 0 0 1 1 0 0 seq2 = Columns 1 through 30 1 0 0 1 0 0 1 1 0 0 0 0 1 0 1 1 0 1 0 1 0 0 0 1 1 1 0 1 1 1 Columns 31 through 40 1 1 0 0 1 0 0 1 1 0\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test36 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 1 1 1 0 1 1 0 0 1 1 1 0 0 0 0 1 1 0 1 0 1 0 0 1 0 0 0 1 0 1 Columns 31 through 41 1 1 1 1 0 1 1 0 0 1 1 seq2 = Columns 1 through 30 1 1 1 0 1 1 0 0 1 1 1 0 0 0 0 1 1 0 1 0 1 0 0 1 0 0 0 1 0 1 Columns 31 through 40 1 1 1 1 0 1 1 0 0 1\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test37 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 1 0 0 1 0 1 1 0 0 1 1 1 1 1 0 0 0 1 1 0 1 1 1 0 1 0 1 0 0 0 Columns 31 through 41 0 1 0 0 1 0 1 1 0 0 1 seq2 = Columns 1 through 30 1 0 0 1 0 1 1 0 0 1 1 1 1 1 0 0 0 1 1 0 1 1 1 0 1 0 1 0 0 0 Columns 31 through 40 0 1 0 0 1 0 1 1 0 0\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test38 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 1 1 1 1 1 0 1 1 1 0 0 0 1 0 1 0 1 1 0 1 0 0 0 0 1 1 0 0 1 0 Columns 31 through 41 0 1 1 1 1 1 0 1 1 1 0 seq2 = Columns 1 through 30 1 1 1 1 1 0 1 1 1 0 0 0 1 0 1 0 1 1 0 1 0 0 0 0 1 1 0 0 1 0 Columns 31 through 40 0 1 1 1 1 1 0 1 1 1\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test39 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 1 0 0 1 0 0 1 1 0 0 0 0 1 0 1 1 0 1 0 1 0 0 0 1 1 1 0 1 1 1 Columns 31 through 41 0 1 0 0 1 0 0 1 1 0 0 seq2 = Columns 1 through 30 1 0 0 1 0 0 1 1 0 0 0 0 1 0 1 1 0 1 0 1 0 0 0 1 1 1 0 1 1 1 Columns 31 through 40 1 1 0 0 1 0 0 1 1 1\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test40 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 1 1 1 0 1 1 0 0 1 1 1 0 0 0 0 1 1 0 1 0 1 0 0 1 0 0 0 1 1 1 Columns 31 through 41 1 1 1 1 1 1 1 0 0 1 1 seq2 = Columns 1 through 30 1 1 1 0 1 1 0 0 1 1 1 0 0 0 0 1 1 0 1 0 1 0 0 1 0 0 0 1 0 1 Columns 31 through 40 1 1 1 1 0 1 1 0 0 1\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test41 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 1 1 1 0 1 0 0 0 1 0 0 1 0 1 0 1 1 0 0 0 0 1 1 1 0 0 1 1 0 1 Columns 31 through 41 1 1 1 1 0 1 0 0 0 1 0 seq2 = Columns 1 through 30 1 1 1 0 1 0 0 0 1 0 0 1 0 1 0 1 1 0 0 0 0 1 1 1 0 0 1 1 0 1 Columns 31 through 40 1 1 1 1 0 1 0 0 0 1\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test42 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 0 1 1 0 1 1 0 1 1 1 1 1 0 1 1 0 1 1 1 1 1 0 1 1 0 1 1 0 1 1 Columns 31 through 50 0 1 1 0 1 1 1 1 1 0 1 1 0 1 1 1 1 1 0 1 seq2 = Columns 1 through 30 0 1 1 0 1 1 0 1 1 1 1 1 0 1 1 0 1 1 1 1 1 0 1 1 0 1 1 0 1 1 Columns 31 through 49 0 1 1 0 1 1 1 1 1 0 1 1 0 1 1 1 1 1 0\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test43 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 0 1 1 0 1 0 0 1 1 0 0 1 0 1 1 0 1 0 0 1 0 1 1 0 0 1 1 0 1 1 Columns 31 through 53 0 1 0 0 0 1 0 1 1 0 0 1 1 0 1 0 0 1 0 1 1 0 1 seq2 = Columns 1 through 30 0 1 1 0 1 0 0 1 1 0 0 1 0 1 1 0 1 0 0 1 0 1 1 0 0 1 1 0 1 0 Columns 31 through 52 0 1 1 0 0 1 0 1 1 0 0 1 1 0 1 0 0 1 0 1 1 0\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test44 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = 1 6 6 30 6 30 30 54 6 102 30 78 30 78 54 150 6 102 102 126 30 270 78 150 30 150 78 318 54 174 seq2 = 1 6 6 30 6 30 30 54 6 102 30 78 30 78 54 150 6 102 102 126 30 270 78 150 30 150 78 318 54 174\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test45 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 0 1 1 2 1 3 2 2 1 4 3 3 2 3 2 2 1 5 4 3 3 4 3 3 2 4 3 3 2 3 Columns 31 through 48 2 2 1 6 5 5 4 5 4 4 3 5 4 4 3 4 3 3 seq2 = Columns 1 through 30 0 1 1 2 1 3 2 2 1 4 3 3 2 3 2 2 1 5 4 4 3 4 3 3 2 4 3 3 2 3 Columns 31 through 48 2 2 1 6 5 5 4 5 3 4 3 5 4 4 3 4 3 3\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test46 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 1 1 1 2 1 2 2 2 1 4 2 3 2 3 2 5 1 4 4 4 2 7 3 4 2 5 3 9 2 5 Columns 31 through 45 5 5 1 11 4 7 4 6 4 10 2 7 7 7 3 seq2 = Columns 1 through 30 1 1 1 2 1 2 2 2 1 4 2 3 2 3 2 5 1 4 4 4 2 7 3 4 2 5 3 9 2 5 Columns 31 through 44 5 5 1 11 4 7 4 6 4 10 2 7 7 7\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test47 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 0 0 0 1 0 0 1 0 0 0 0 1 1 1 0 1 0 0 0 1 0 0 1 0 1 1 1 0 0 0 Columns 31 through 41 1 0 0 0 0 1 0 0 1 0 0 seq2 = Columns 1 through 30 0 0 0 1 0 0 1 0 0 0 0 1 1 1 0 1 0 0 0 1 0 0 1 0 1 1 1 0 0 0 Columns 31 through 40 1 0 0 0 0 1 0 0 1 0\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test48 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 0 0 0 1 0 0 1 0 0 0 0 1 1 1 0 1 0 0 0 1 0 0 1 0 1 1 1 0 0 0 Columns 31 through 41 1 0 0 0 0 1 0 0 1 0 1 seq2 = Columns 1 through 30 0 0 0 1 0 0 1 0 0 0 0 1 1 1 0 1 0 0 0 1 0 0 1 0 1 1 1 0 0 0 Columns 31 through 40 1 0 0 0 0 1 0 0 1 0\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test49 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 0 0 0 0 0 1 0 0 0 0 1 0 0 1 1 0 0 1 0 0 1 0 0 0 0 1 1 0 0 1 Columns 31 through 54 0 0 0 0 1 0 0 1 0 0 1 1 0 0 0 1 0 0 0 0 1 0 1 1 seq2 = Columns 1 through 30 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 0 0 1 1 0 1 1 Columns 31 through 54 0 0 0 0 1 0 0 1 0 0 1 1 0 1 0 1 0 0 0 0 1 0 1 1\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test50 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 0 0 1 1 0 0 1 Columns 31 through 54 0 0 0 0 1 0 0 1 0 0 1 1 0 0 0 1 0 0 0 0 1 0 1 1 seq2 = Columns 1 through 30 0 0 0 0 0 1 0 0 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 0 0 1 1 0 0 1 Columns 31 through 54 0 0 0 0 1 0 0 1 0 0 1 1 0 0 0 1 0 0 0 0 1 0 1 1\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test51 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 1 0 0 1 0 1 1 0 0 1 1 1 1 1 0 0 0 1 1 0 1 1 1 0 1 0 1 0 0 0 Columns 31 through 41 1 1 0 0 1 0 1 1 0 0 1 seq2 = Columns 1 through 30 1 0 0 1 0 1 1 0 0 1 1 1 1 1 0 0 0 1 1 0 1 1 1 0 1 0 1 0 0 0 Columns 31 through 40 0 1 0 0 1 0 1 1 0 0\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test52 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 1 1 1 1 1 0 1 1 1 0 0 0 1 0 1 0 1 1 0 1 0 0 0 0 1 1 0 0 1 0 Columns 31 through 41 0 1 1 1 1 1 0 1 1 0 0 seq2 = Columns 1 through 30 1 1 1 1 1 0 1 1 1 0 0 0 1 0 1 0 1 1 0 1 0 0 0 0 1 1 0 0 1 0 Columns 31 through 40 0 1 1 1 1 1 0 1 1 1\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test53 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 1 1 1 1 1 1 1 2 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 2 1 1 1 2 2 2 Columns 31 through 45 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 seq2 = Columns 1 through 30 1 1 1 1 1 1 1 2 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 2 1 1 1 2 2 2 Columns 31 through 45 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test54 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 0 0 0 0 0 1 0 1 0 0 1 0 0 1 1 0 0 1 0 1 1 0 0 0 0 0 1 0 1 0 Columns 31 through 41 0 1 1 0 1 1 0 0 1 0 1 seq2 = Columns 1 through 30 0 0 0 0 0 1 0 1 0 0 1 0 0 1 1 0 0 1 0 1 1 0 0 0 0 0 1 0 1 0 Columns 31 through 40 0 1 0 0 1 1 0 0 1 0\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test55 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 1 1 1 1 1 2 1 2 1 1 2 2 1 1 2 1 1 1 1 1 2 1 2 2 1 1 1 1 2 2 Columns 31 through 45 1 2 1 1 1 1 1 2 1 1 2 2 1 1 2 seq2 = Columns 1 through 30 1 1 1 1 1 2 1 2 1 1 2 2 1 1 2 1 1 1 1 1 2 1 2 2 1 1 1 1 2 2 Columns 31 through 45 1 2 1 1 1 1 1 2 1 1 2 2 1 1 2\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test56 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 0 1 1 0 1 -1 0 1 1 -2 -1 1 0 1 1 0 -1 -3 -2 1 -1 2 1 -1 0 1 1 0 1 -1 Columns 31 through 53 0 1 1 -4 -3 1 -2 3 1 -2 -1 3 2 -1 1 -2 -1 1 0 1 1 0 1 seq2 = Columns 1 through 30 0 1 1 0 1 -1 0 1 1 -2 -1 1 0 1 1 0 1 -3 -2 1 -1 2 1 -1 0 1 1 0 1 -1 Columns 31 through 52 0 1 -1 -4 -3 1 -2 3 1 -2 -1 3 2 -1 1 -2 -1 1 0 1 1 0\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test57 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))\nseq1 = Columns 1 through 30 0 1 1 2 1 3 2 3 1 4 3 5 2 5 3 4 1 5 4 7 3 8 5 7 2 7 5 8 3 7 Columns 31 through 46 4 5 1 6 5 9 4 11 7 10 3 11 8 13 5 12 seq2 = Columns 1 through 30 0 1 1 2 1 3 2 3 1 4 3 5 2 5 3 4 1 5 4 7 3 8 5 7 2 7 5 8 3 7 Columns 31 through 46 4 5 1 6 5 9 4 11 7 10 3 11 8 13 5 12\nOutput argument "tf" (and maybe others) not assigned during call to "self_similarity_1". Error in Test58 (line 3) assert(isequal(self_similarity_1(seq),tf_corr))