CCDC 1413841: Experimental Crystal Structure Determination;Danopoulos, Andreas A.;2016;Cambridge Crystallographic Data Centre


Abstract: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

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CCDC 1413842: Experimental Crystal Structure Determination;Danopoulos, Andreas A.;2016;Cambridge Crystallographic Data Centre


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CCDC 1414620: Experimental Crystal Structure Determination;Peter, Clovis;2016;Cambridge Crystallographic Data Centre


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CCDC 1414754: Experimental Crystal Structure Determination;Lepronier, Aymeric;2016;Cambridge Crystallographic Data Centre


CCDC 1414755: Experimental Crystal Structure Determination;Lepronier, Aymeric;2016;Cambridge Crystallographic Data Centre


CCDC 1414756: Experimental Crystal Structure Determination;Lepronier, Aymeric;2016;Cambridge Crystallographic Data Centre


CCDC 1414757: Experimental Crystal Structure Determination;Lepronier, Aymeric;2016;Cambridge Crystallographic Data Centre


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CCDC 1415013: Experimental Crystal Structure Determination;Heinrich, Clément F.;2016;Cambridge Crystallographic Data Centre


CCDC 1415014: Experimental Crystal Structure Determination;Heinrich, Clément F.;2016;Cambridge Crystallographic Data Centre


CCDC 1415015: Experimental Crystal Structure Determination;Heinrich, Clément F.;2016;Cambridge Crystallographic Data Centre


CCDC 1415016: Experimental Crystal Structure Determination;Heinrich, Clément F.;2016;Cambridge Crystallographic Data Centre


CCDC 1415017: Experimental Crystal Structure Determination;Heinrich, Clément F.;2016;Cambridge Crystallographic Data Centre


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CCDC 1415324: Experimental Crystal Structure Determination;Yalcouye, Boubacar;2016;Cambridge Crystallographic Data Centre


CCDC 1415325: Experimental Crystal Structure Determination;Yalcouye, Boubacar;2016;Cambridge Crystallographic Data Centre


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CCDC 1415907: Experimental Crystal Structure Determination;Kumar, N. S. Saleesh;2016;Cambridge Crystallographic Data Centre


CCDC 1415908: Experimental Crystal Structure Determination;Kumar, N. S. Saleesh;2016;Cambridge Crystallographic Data Centre


aqua-(2,6-bis(4-(3,4,5-trimethoxyphenyl)-6,7-dihydro-5H-cyclopenta[c]pyridin-1-yl)pyridine)-tris(nitrato)-dysprosium acetonitrile diethyl ether solvate

CCDC 1415910: Experimental Crystal Structure Determination;Kumar, N. S. Saleesh;2016;Cambridge Crystallographic Data Centre


bis(2,6-bis(4-(3,4,5-trimethoxyphenyl)-6,7-dihydro-5H-cyclopenta[c]pyridin-1-yl)pyridine)-cobalt bis(tetrafluoroborate) methanol unknown solvate

CCDC 1415911: Experimental Crystal Structure Determination;Kumar, N. S. Saleesh;2016;Cambridge Crystallographic Data Centre


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CCDC 1416946: Experimental Crystal Structure Determination;Specklin, David;2017;Cambridge Crystallographic Data Centre


CCDC 1416947: Experimental Crystal Structure Determination;Specklin, David;2017;Cambridge Crystallographic Data Centre


CCDC 1416948: Experimental Crystal Structure Determination;Specklin, David;2017;Cambridge Crystallographic Data Centre


(mu-2,2'-bipyrimidine)-hexakis(2,2,6,6-tetramethylheptane-3,5-dionato)-di-dysprosium diethyl ether solvate

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CCDC 1419831: Experimental Crystal Structure Determination;Yu, Wen;2018;Cambridge Crystallographic Data Centre


(mu-2,2'-bipyrimidine)-hexakis(2,2,6,6-tetramethylheptane-3,5-dionato)-di-terbium diethyl ether solvate

CCDC 1419834: Experimental Crystal Structure Determination;Yu, Wen;2018;Cambridge Crystallographic Data Centre


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CCDC 1419972: Experimental Crystal Structure Determination;Dohmeier, Niklas;2017;Cambridge Crystallographic Data Centre


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CCDC 1420724: Experimental Crystal Structure Determination;Li, Xiao-Yu;2016;Cambridge Crystallographic Data Centre


CCDC 1420725: Experimental Crystal Structure Determination;Li, Xiao-Yu;2016;Cambridge Crystallographic Data Centre


CCDC 1420726: Experimental Crystal Structure Determination;Li, Xiao-Yu;2016;Cambridge Crystallographic Data Centre


CCDC 1420727: Experimental Crystal Structure Determination;Li, Xiao-Yu;2016;Cambridge Crystallographic Data Centre


CCDC 1420728: Experimental Crystal Structure Determination;Li, Xiao-Yu;2016;Cambridge Crystallographic Data Centre


CCDC 1420729: Experimental Crystal Structure Determination;Li, Xiao-Yu;2016;Cambridge Crystallographic Data Centre


CCDC 1420730: Experimental Crystal Structure Determination;Li, Xiao-Yu;2016;Cambridge Crystallographic Data Centre


CCDC 1420731: Experimental Crystal Structure Determination;Li, Xiao-Yu;2016;Cambridge Crystallographic Data Centre


bis(N'-((quinolin-8-yl)methylene)carbamohydrazonoselenoato)-cobalt(iii) perchlorate dimethyl sulfoxide solvate

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CCDC 1401687: Experimental Crystal Structure Determination;Filipović, Nenad R.;2016;Cambridge Crystallographic Data Centre


CCDC 1405081: Experimental Crystal Structure Determination;Peter, Clovis;2016;Cambridge Crystallographic Data Centre


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CCDC 1409059: Experimental Crystal Structure Determination;Dengiz, Cagatay;2016;Cambridge Crystallographic Data Centre


CCDC 1409060: Experimental Crystal Structure Determination;Dengiz, Cagatay;2016;Cambridge Crystallographic Data Centre


CCDC 1409061: Experimental Crystal Structure Determination;Dengiz, Cagatay;2016;Cambridge Crystallographic Data Centre


CCDC 1409062: Experimental Crystal Structure Determination;Dengiz, Cagatay;2016;Cambridge Crystallographic Data Centre


CCDC 1409063: Experimental Crystal Structure Determination;Dengiz, Cagatay;2016;Cambridge Crystallographic Data Centre


CCDC 1409064: Experimental Crystal Structure Determination;Dengiz, Cagatay;2016;Cambridge Crystallographic Data Centre


CCDC 1409065: Experimental Crystal Structure Determination;Dengiz, Cagatay;2016;Cambridge Crystallographic Data Centre


CCDC 1409066: Experimental Crystal Structure Determination;Dengiz, Cagatay;2016;Cambridge Crystallographic Data Centre


CCDC 1409432: Experimental Crystal Structure Determination;Peter, Clovis;2016;Cambridge Crystallographic Data Centre


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CCDC 1409618: Experimental Crystal Structure Determination;Bilbeisi, Rana A.;2016;Cambridge Crystallographic Data Centre


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CCDC 1409851: Experimental Crystal Structure Determination;Ru, Jing;2017;Cambridge Crystallographic Data Centre


CCDC 1409852: Experimental Crystal Structure Determination;Ru, Jing;2017;Cambridge Crystallographic Data Centre


CCDC 1409853: Experimental Crystal Structure Determination;Ru, Jing;2017;Cambridge Crystallographic Data Centre


CCDC 1409854: Experimental Crystal Structure Determination;Ru, Jing;2017;Cambridge Crystallographic Data Centre


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CCDC 1055829: Experimental Crystal Structure Determination;Lan, Yanhua;2017;Cambridge Crystallographic Data Centre


CCDC 1055830: Experimental Crystal Structure Determination;Lan, Yanhua;2017;Cambridge Crystallographic Data Centre


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CCDC 1056905: Experimental Crystal Structure Determination;Fliedel, Christophe;2016;Cambridge Crystallographic Data Centre


CCDC 1056906: Experimental Crystal Structure Determination;Fliedel, Christophe;2016;Cambridge Crystallographic Data Centre


(acetato)-bis(N-(diphenylphosphino)-N-(4-(methylsulfanyl)phenyl)-P,P-diphenylphosphinous amide)-iron(ii) hexafluorophosphate pentane solvate

CCDC 1056907: Experimental Crystal Structure Determination;Fliedel, Christophe;2016;Cambridge Crystallographic Data Centre


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CCDC 1062014: Experimental Crystal Structure Determination;Peudru, Flavie;2016;Cambridge Crystallographic Data Centre


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CCDC 1062457: Experimental Crystal Structure Determination;Paolino, Marco;2016;Cambridge Crystallographic Data Centre


CCDC 1062459: Experimental Crystal Structure Determination;Paolino, Marco;2016;Cambridge Crystallographic Data Centre


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CCDC 1400210: Experimental Crystal Structure Determination;Gawel, Przemyslaw;2016;Cambridge Crystallographic Data Centre


CCDC 1400211: Experimental Crystal Structure Determination;Gawel, Przemyslaw;2016;Cambridge Crystallographic Data Centre


CCDC 1400212: Experimental Crystal Structure Determination;Gawel, Przemyslaw;2016;Cambridge Crystallographic Data Centre


CCDC 1400213: Experimental Crystal Structure Determination;Gawel, Przemyslaw;2016;Cambridge Crystallographic Data Centre


14-hydroxy-16-(2-methyl-3-oxocyclohexyl)androstane-1,7,17-trione ethyl acetate solvate

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CCDC 1052012: Experimental Crystal Structure Determination;Dahm, Georges;2016;Cambridge Crystallographic Data Centre


CCDC 1052013: Experimental Crystal Structure Determination;Dahm, Georges;2016;Cambridge Crystallographic Data Centre


CCDC 1052014: Experimental Crystal Structure Determination;Dahm, Georges;2016;Cambridge Crystallographic Data Centre


CCDC 1052015: Experimental Crystal Structure Determination;Dahm, Georges;2016;Cambridge Crystallographic Data Centre


CCDC 1052016: Experimental Crystal Structure Determination;Dahm, Georges;2016;Cambridge Crystallographic Data Centre


CCDC 1052017: Experimental Crystal Structure Determination;Dahm, Georges;2016;Cambridge Crystallographic Data Centre


CCDC 1052018: Experimental Crystal Structure Determination;Dahm, Georges;2016;Cambridge Crystallographic Data Centre


CCDC 1043760: Experimental Crystal Structure Determination;Peter, Clovis;2016;Cambridge Crystallographic Data Centre


CCDC 1038730: Experimental Crystal Structure Determination;Peter, Clovis;2016;Cambridge Crystallographic Data Centre


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CCDC 1016698: Experimental Crystal Structure Determination;Li, Quan;2016;Cambridge Crystallographic Data Centre


CCDC 1016699: Experimental Crystal Structure Determination;Li, Quan;2016;Cambridge Crystallographic Data Centre


CCDC 1016700: Experimental Crystal Structure Determination;Li, Quan;2016;Cambridge Crystallographic Data Centre


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CCDC 1023858: Experimental Crystal Structure Determination;Zhang, L.;2017;Cambridge Crystallographic Data Centre


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CCDC 1023859: Experimental Crystal Structure Determination;Zhang, L.;2017;Cambridge Crystallographic Data Centre


CCDC 1006987: Experimental Crystal Structure Determination;Chen, Zhi;2017;Cambridge Crystallographic Data Centre


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CCDC 1008523: Experimental Crystal Structure Determination;Teci, Matthieu;2017;Cambridge Crystallographic Data Centre


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CCDC 819448: Experimental Crystal Structure Determination;Dolai, Malay;2017;Cambridge Crystallographic Data Centre


catena-((mu-azido)-(mu-oxo)-tris(mu-5-bromo-2-oxybenzaldehyde oximato)-triaqua-dimethylformamide-tri-manganese(iii) dimethylformamide solvate dihydrate)

CCDC 864244: Experimental Crystal Structure Determination;Dolai, Malay;2017;Cambridge Crystallographic Data Centre


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CCDC 995765: Experimental Crystal Structure Determination;Harrowfield, Jack M.;2017;Cambridge Crystallographic Data Centre


CCDC 995766: Experimental Crystal Structure Determination;Harrowfield, Jack M.;2017;Cambridge Crystallographic Data Centre


CCDC 995767: Experimental Crystal Structure Determination;Harrowfield, Jack M.;2017;Cambridge Crystallographic Data Centre


CCDC 995768: Experimental Crystal Structure Determination;Harrowfield, Jack M.;2017;Cambridge Crystallographic Data Centre


CCDC 995769: Experimental Crystal Structure Determination;Harrowfield, Jack M.;2017;Cambridge Crystallographic Data Centre


CCDC 995770: Experimental Crystal Structure Determination;Harrowfield, Jack M.;2017;Cambridge Crystallographic Data Centre


CCDC 995771: Experimental Crystal Structure Determination;Harrowfield, Jack M.;2017;Cambridge Crystallographic Data Centre


CCDC 995772: Experimental Crystal Structure Determination;Harrowfield, Jack M.;2017;Cambridge Crystallographic Data Centre


CCDC 995773: Experimental Crystal Structure Determination;Harrowfield, Jack M.;2017;Cambridge Crystallographic Data Centre


CCDC 995774: Experimental Crystal Structure Determination;Harrowfield, Jack M.;2017;Cambridge Crystallographic Data Centre


CCDC 995775: Experimental Crystal Structure Determination;Harrowfield, Jack M.;2017;Cambridge Crystallographic Data Centre


CCDC 995776: Experimental Crystal Structure Determination;Harrowfield, Jack M.;2017;Cambridge Crystallographic Data Centre


CCDC 995777: Experimental Crystal Structure Determination;Harrowfield, Jack M.;2017;Cambridge Crystallographic Data Centre


CCDC 995778: Experimental Crystal Structure Determination;Harrowfield, Jack M.;2017;Cambridge Crystallographic Data Centre


CCDC 995779: Experimental Crystal Structure Determination;Harrowfield, Jack M.;2017;Cambridge Crystallographic Data Centre


CCDC 995780: Experimental Crystal Structure Determination;Harrowfield, Jack M.;2017;Cambridge Crystallographic Data Centre


CCDC 995781: Experimental Crystal Structure Determination;Harrowfield, Jack M.;2017;Cambridge Crystallographic Data Centre


(1,3-bis(9-ethyl-9H-fluoren-9-yl)imidazol-2-ylidene)-chloro-gold(i) dichloromethane n-pentane solvate

CCDC 998801: Experimental Crystal Structure Determination;Teci, Matthieu;2017;Cambridge Crystallographic Data Centre


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CCDC 983984: Experimental Crystal Structure Determination;Chaumeil, H.;2017;Cambridge Crystallographic Data Centre


CCDC 983985: Experimental Crystal Structure Determination;Chaumeil, H.;2017;Cambridge Crystallographic Data Centre


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CCDC 990739: Experimental Crystal Structure Determination;Gutiérrez-Cepeda, Adrián;2016;Cambridge Crystallographic Data Centre


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CCDC 973918: Experimental Crystal Structure Determination;Harrowfield, Jack M.;2016;Cambridge Crystallographic Data Centre


tetramethylammonium 5,11,17,23,29,35,41,47,53-nona-t-butyl-55,56,57,58,59,60,61,62-octahydroxycalix(9)arene-63-olate dimethyl sulfoxide solvate monohydrate

CCDC 973919: Experimental Crystal Structure Determination;Harrowfield, Jack M.;2016;Cambridge Crystallographic Data Centre


5,11,17,23,29,35,41,47,53,59-deca-t-butyl-61,62,63,64,65,66,67,68,69,70-decahydroxycalix(10)arene dimethyl sulfoxide solvate heptahydrate

CCDC 973920: Experimental Crystal Structure Determination;Harrowfield, Jack M.;2016;Cambridge Crystallographic Data Centre


5,17-bis(diphenylphosphinoyl)-4(24),6(10),12(16),18(22)-tetramethylenedioxy-2,8,14,20-tetrapentylresorcin(4)arene methanol unknown solvate monohydrate

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CCDC 957680: Experimental Crystal Structure Determination;Peter, Clovis;2016;Cambridge Crystallographic Data Centre

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CCDC 936529: Experimental Crystal Structure Determination;Ovsyannikov, A. S.;2021;Cambridge Crystallographic Data Centre

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CCDC 936530: Experimental Crystal Structure Determination;Ovsyannikov, A. S.;2021;Cambridge Crystallographic Data Centre


CCDC 892810: Experimental Crystal Structure Determination;Fahsi, Karim;2023;Cambridge Crystallographic Data Centre

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CCDC 770458: Experimental Crystal Structure Determination;Bendia, Sabrina;2021;Cambridge Crystallographic Data Centre

1-(((2-(((2-hydroxy-1-naphthyl)methylene)amino)phenyl)iminio)methyl)naphthalen-2-olate dimethyl sulfoxide solvate

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MOULIN Emilie

CNRS/ICS-INST CHARLES SADRON, STRASBOURG

Photoinduced Supramolecular Morphing in Molecularly Motorised Langmuir Monolayers;MOULIN Emilie;2024;Institut Laue-Langevin (ILL)


VHR Strasbourg data

VHR Strasbourg data;Anne Puissant;2017;Unpublished


Eschbach et al. - 2017 - Abstract REX

Eschbach et al. - 2017 - Abstract REX;David Eschbach;2017;Unpublished


Koehl et al. - 2017 - Abstract EGU

Koehl et al. - 2017 - Abstract EGU;Mathieu Koehl;2017;Unpublished


Schmitt et al. - 2016 - Article BSGL

Schmitt et al. - 2016 - Article BSGL;Laurent Schmitt;2017;Unpublished


CCDC 606095: Experimental Crystal Structure Determination;Chan, Eric J.;2020;Cambridge Crystallographic Data Centre

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CCDC 606096: Experimental Crystal Structure Determination;Chan, Eric J.;2020;Cambridge Crystallographic Data Centre

bis(N,N,N',N',N'',N''-hexamethylphosphoric triamide)-tris(2,4,6-trinitrophenolato)-scandium dichloromethane solvate


CCDC 606094: Experimental Crystal Structure Determination;Chan, Eric J.;2020;Cambridge Crystallographic Data Centre


CCDC 606092: Experimental Crystal Structure Determination;Chan, Eric J.;2020;Cambridge Crystallographic Data Centre

bis(N,N,N',N',N'',N''-hexamethylphosphoric triamide)-tris(2,4,6-trinitrophenolato)-scandium chloroform solvate


CCDC 606093: Experimental Crystal Structure Determination;Chan, Eric J.;2020;Cambridge Crystallographic Data Centre


CCDC 606089: Experimental Crystal Structure Determination;Chan, Eric J.;2020;Cambridge Crystallographic Data Centre


CCDC 606091: Experimental Crystal Structure Determination;Chan, Eric J.;2020;Cambridge Crystallographic Data Centre


CCDC 606088: Experimental Crystal Structure Determination;Chan, Eric J.;2020;Cambridge Crystallographic Data Centre


CCDC 931124: Experimental Crystal Structure Determination;Chavagnan, Thierry;2017;Cambridge Crystallographic Data Centre


CCDC 739535: Experimental Crystal Structure Determination;Wu, Lei;2017;Cambridge Crystallographic Data Centre

Related Article: Lei Wu, Ming Xue, Gerald Chaplais, Guang-Shan Zhu, Shi-Lun Qiu, Angelique Simon-Masseron, Joel Patarin|2014|Adv.Mater.Res.|834/836|543|doi:10.4028/www.scientific.net/AMR.834-836.543


CCDC 929496: Experimental Crystal Structure Determination;Prodius, Denis;2018;Cambridge Crystallographic Data Centre

Related Article: Denis Prodius, Valeriu Mereacre, Prashant Singh, Yanhua Lan, Samir Mameri, Duane D. Johnson, Wolfgang Wernsdorfer, Christopher E. Anson, Annie K. Powell|2018|J.Mater.Chem.C|6|2862|doi:10.1039/C8TC00322J


CCDC 929497: Experimental Crystal Structure Determination;Prodius, Denis;2018;Cambridge Crystallographic Data Centre


Related Article: Neslihan Sahin , David Semeril, Eric Brenner , Dominique Matt , Cemal Kaya , Loic Toupet|2015|Turk.J.Chem.|39|1171|doi:10.3906/kim-1503-82

CCDC 842333: Experimental Crystal Structure Determination;Sahin, Neslihan;2016;Cambridge Crystallographic Data Centre


CCDC 1036409: Experimental Crystal Structure Determination;Rajnák, Cyril;2017;Cambridge Crystallographic Data Centre

Related Article: Cyril Rajnák, Ján Titiš, Jozef Miklovič, George E. Kostakis, Olaf Fuhr, Mario Ruben, Roman Boča|2017|Polyhedron|126|174|doi:10.1016/j.poly.2017.01.028


CCDC 1423480: Experimental Crystal Structure Determination;Miesch, Michel;2017;Cambridge Crystallographic Data Centre

Related Article: Clovis Peter, Philippe Geoffroy, Michel Miesch|2018|Org.Biomol.Chem.|16|1381|doi:10.1039/C7OB03124F Related Article: Michel Miesch, Peter Clovis, Philippe Geoffroy|2017|CSD Communication|||


CCDC 1431069: Experimental Crystal Structure Determination;Peter, Clovis;2017;Cambridge Crystallographic Data Centre

Related Article: Clovis Peter, Philippe Geoffroy, Michel Miesch|2018|Org.Biomol.Chem.|16|1381|doi:10.1039/C7OB03124F Related Article: Clovis Peter, Philippe Geoffroy, Michel Miesch|2017|CSD Communication|||


CCDC 1020929: Experimental Crystal Structure Determination;Na, Hong-Xu;2016;Cambridge Crystallographic Data Centre

Related Article: Hong-Xu Na, Pei-Yu Yang, Zheng Yin, Yun-Hong Wang, Li-Xian Chang, Rui Si, Mohamedally Kurmoo and Ming-Hua Zeng|2016|Chem.-Eur.J.|22|18404|doi:10.1002/chem.201603652


CCDC 1020930: Experimental Crystal Structure Determination;Na, Hong-Xu;2016;Cambridge Crystallographic Data Centre


CCDC 1430739: Experimental Crystal Structure Determination;Na, Hong-Xu;2016;Cambridge Crystallographic Data Centre


CCDC 1430740: Experimental Crystal Structure Determination;Na, Hong-Xu;2016;Cambridge Crystallographic Data Centre

hexakis(mu-hydroxo)-hexakis(mu-2-ethoxy-6-(methylcarbonoimidoyl)phenolato)-hepta-cobalt diperchlorate unknown solvate


CCDC 1430741: Experimental Crystal Structure Determination;Na, Hong-Xu;2016;Cambridge Crystallographic Data Centre


CCDC 1430742: Experimental Crystal Structure Determination;Na, Hong-Xu;2016;Cambridge Crystallographic Data Centre


CCDC 2270921: Experimental Crystal Structure Determination;Preda, Giovanni;2023;Cambridge Crystallographic Data Centre

Related Article: Giovanni Preda, Sebastian Jung, Gennaro Pescitelli, Lorenzo Cupellini, Dominique Armspach, Dario Pasini|2023|Chem.-Eur.J.|29||doi:10.1002/chem.202302376


CCDC 2270930: Experimental Crystal Structure Determination;Preda, Giovanni;2023;Cambridge Crystallographic Data Centre


CCDC 1015924: Experimental Crystal Structure Determination;Hansen, Andreas;2016;Cambridge Crystallographic Data Centre

Related Article: Andreas Hansen, Christoph Bannwarth, Stefan Grimme, Predrag Petrović, Christophe Werlé, Jean-Pierre Djukic|2014|ChemistryOpen|3|177|doi:10.1002/open.201402017


CCDC 2341795: Experimental Crystal Structure Determination;Mechrouk, Victoria;2024;Cambridge Crystallographic Data Centre

Related Article: Victoria Mechrouk, Baptiste Leforestier, Weighang Chen, Amalia I. Poblador-Bahamonde, Aline Maisse-Francois, Stéphane Bellemin-Laponnaz, Thierry Achard|2024|Chem.-Eur.J.|30||doi:10.1002/chem.202401390


CCDC 2341796: Experimental Crystal Structure Determination;Mechrouk, Victoria;2024;Cambridge Crystallographic Data Centre


CCDC 2341797: Experimental Crystal Structure Determination;Mechrouk, Victoria;2024;Cambridge Crystallographic Data Centre


CCDC 2341798: Experimental Crystal Structure Determination;Mechrouk, Victoria;2024;Cambridge Crystallographic Data Centre


CCDC 2113797: Experimental Crystal Structure Determination;Guermazi, Refka;2022;Cambridge Crystallographic Data Centre

Related Article: Refka Guermazi, David Specklin, Christophe Gourlaouen, Pierre Frémont, Samuel Dagorne|2022|Eur.J.Inorg.Chem.|2022||doi:10.1002/ejic.202101002


CCDC 2113798: Experimental Crystal Structure Determination;Guermazi, Refka;2022;Cambridge Crystallographic Data Centre


CCDC 2113799: Experimental Crystal Structure Determination;Guermazi, Refka;2022;Cambridge Crystallographic Data Centre


CCDC 2071148: Experimental Crystal Structure Determination;Tassone, Giusy;2021;Cambridge Crystallographic Data Centre

Related Article: Marco Paolino, Mario Saletti, Annalisa Reale, Mariano Licciardi, Paola Varvarà, Arnaud Marquette, Jérémie Léonard, Claudia Bonechi, Alessandro Donati, Gianluca Giorgi, Germano Giuliani, Benedetta Carlotti, Fausto Ortica, Loredana Latterini, Mariangela Gentile, Eugenio Paccagnini, Massimo Olivucci, Andrea Cappelli|2022|Chem.-Eur.J.|28|e202201477|doi:10.1002/chem.202201477 Related Article: Giusy Tassone, Marco Paolino, Cecilia Pozzi, Annalisa Reale, Laura Salvini, Gianluca Giorgi, Maurizio Orlandini, Federico Galvagni, Stefano Mangani, Xuchun Yang, Benedetta Carlotti, Fausto Ortica, Loredana Latterini, Massimo Olivucci, Andrea Cappelli|2021|ChemBioChem|23||doi:10.1002/cbic.202100449


CCDC 1995954: Experimental Crystal Structure Determination;Mamane, Victor;2020;Cambridge Crystallographic Data Centre

Related Article: Victor Mamane, Paola Peluso, Emmanuel Aubert, Robin Weiss, Emmanuel Wenger, Sergio Cossu, Patrick Pale|2020|Organometallics|39|3936|doi:10.1021/acs.organomet.0c00633


CCDC 1995959: Experimental Crystal Structure Determination;Mamane, Victor;2020;Cambridge Crystallographic Data Centre


CCDC 2005272: Experimental Crystal Structure Determination;Day, Erin;2022;Cambridge Crystallographic Data Centre

Related Article: Erin Day, Brice Kauffmann, Matthieu Scarpi-Luttenauer, Alain Chaumont, Marc Henry, Pierre Mobian|2022|Chem.-Eur.J.|28||doi:10.1002/chem.202200047


Pristine survey II. Bright stars abundances;E. Caffau;2019;Centre de Donnees Strasbourg (CDS)

VizieR online Data Catalogue associated with article published in journal Astronomische Nachrichten with title ' The Pristine survey. II. A sample of bright stars observed with FEROS.' (bibcode: 2017AN....338..686C)


CCDC 1948443: Experimental Crystal Structure Determination;Chatelain, Paul;2019;Cambridge Crystallographic Data Centre

Related Article: Paul Chatelain, Abhijit Sau, Christopher N. Rowley and Joseph Moran|2019|CSD Communication||| Related Article: Paul Chatelain, Abhijit Sau, Christopher N. Rowley, Joseph Moran|2019|Angew.Chem.,Int.Ed.|58|14959|doi:10.1002/anie.201908336


CCDC 1980614: Experimental Crystal Structure Determination;Florent, Maxime;2021;Cambridge Crystallographic Data Centre

Related Article: Maxime Florent, Nathalie Kyritsakas, Jean-Marc Planeix, Aurélie Guenet, Mir Wais Hosseini|2021|Dalton Trans.|50|15924|doi:10.1039/D0DT00822B


CCDC 1864783: Experimental Crystal Structure Determination;Wolf, Maximilian;2019;Cambridge Crystallographic Data Centre

Related Article: Maximilian Wolf, Ayumu Ogawa, Mareike Bechtold, Maxime Vonesch, Jennifer A. Wytko, Koji Oohora, Stéphane Campidelli, Takashi Hayashi, Dirk M. Guldi, Jean Weiss|2019|Chemical Science|10|3846|doi:10.1039/C8SC05328F


CCDC 1980613: Experimental Crystal Structure Determination;Florent, Maxime;2021;Cambridge Crystallographic Data Centre

bis[2-(pyridin-2-yl)phenyl]-(13,23:26,32:35,43-quaterpyridine)-iridium(iii) hexafluorophosphate diethyl ether unknown solvate


Related Article: Gracjan Kurpik, Anna Walczak, Mirosław Gilski, Jack Harrowfield, Artur R. Stefankiewicz|2022|J.Catalysis|411|193|doi:10.1016/j.jcat.2022.05.021

CCDC 2144898: Experimental Crystal Structure Determination;Kurpik, Gracjan;2022;Cambridge Crystallographic Data Centre

(2,2'-bipyridine)-(4,4-dimethyl-1-phenylpentane-3,5-dionato)-palladium(ii) hexafluorophosphate dimethylformamide solvate


Related Article: Fatih Sirindil, Jean-Marc Weibel, Patrick Pale, Aurélien Blanc|2019|Org.Lett.|21|5542|doi:10.1021/acs.orglett.9b01860

CCDC 1867782: Experimental Crystal Structure Determination;Sirindil, Fatih;2019;Cambridge Crystallographic Data Centre


Related Article: Xiaoyu Ren, Marcel Wesolek, Pierre Braunstein|2019|Dalton Trans.|48|12895|doi:10.1039/C9DT02400J

CCDC 1896579: Experimental Crystal Structure Determination;Ren, Xiaoyu;2019;Cambridge Crystallographic Data Centre


CCDC 1896580: Experimental Crystal Structure Determination;Ren, Xiaoyu;2019;Cambridge Crystallographic Data Centre


Related Article: Hamzé Almallah, Eric Brenner, Dominique Matt, Jack Harrowfield, Mohamad Jahjah, Akram Hikazi|2019|CSD Communication||| Related Article: Hamzé Almallah, Eric Brenner, Dominique Matt, Jack Harrowfield, Mohamad Jahjah, Akram Hijazi|2019|Dalton Trans.|48|14516|doi:10.1039/C9DT02948F

CCDC 1897856: Experimental Crystal Structure Determination;Almallah, Hamzé;2019;Cambridge Crystallographic Data Centre


CCDC 1897857: Experimental Crystal Structure Determination;Almallah, Hamzé;2019;Cambridge Crystallographic Data Centre


CCDC 1897858: Experimental Crystal Structure Determination;Almallah, Hamzé;2019;Cambridge Crystallographic Data Centre


CCDC 1897859: Experimental Crystal Structure Determination;Almallah, Hamzé;2019;Cambridge Crystallographic Data Centre


Related Article: Adam Gorczyński, Damian Marcinkowski, Dawid Pakulski, Maciej Kubicki, Jack M. Harrowfield, Artur R. Stefankiewicz, Zbigniew Hnatejko, Violetta Patroniak|2016|Arab.J.Chem.|12|729|doi:10.1016/j.arabjc.2016.04.006

CCDC 1045909: Experimental Crystal Structure Determination;Gorczyński, Adam;2019;Cambridge Crystallographic Data Centre


CCDC 1954560: Experimental Crystal Structure Determination;Brachňaková, Barbora;2020;Cambridge Crystallographic Data Centre

bis[2,2'-(pyridine-2,6-diyl)bis{1-[(3,5-di-t-butylphenyl)methyl]-1H-benzimidazole}]-cobalt(ii) bromide methanol unknown solvate monohydrate

Related Article: Barbora Brachňaková, Simona Matejová, Ján Moncol, Radovan Herchel, Ján Pavlik, Eufemio Moreno-Pineda, Mario Ruben, Ivan Šalitroš|2020|Dalton Trans.|49|1249|doi:10.1039/C9DT04592A


CCDC 1888983: Experimental Crystal Structure Determination;Brachňaková, Barbora;2020;Cambridge Crystallographic Data Centre


CCDC 1888985: Experimental Crystal Structure Determination;Brachňaková, Barbora;2020;Cambridge Crystallographic Data Centre


CCDC 1888984: Experimental Crystal Structure Determination;Brachňaková, Barbora;2020;Cambridge Crystallographic Data Centre


CCDC 1996298: Experimental Crystal Structure Determination;Wu, Fule;2020;Cambridge Crystallographic Data Centre

Related Article: Fule Wu, Christophe Deraedt, Yann Cornaton, Julia Contreras-Garcia, Mélanie Boucher, Lydia Karmazin, Corinne Bailly, Jean-Pierre Djukic|2020|Organometallics|39|2609|doi:10.1021/acs.organomet.0c00253


CCDC 1996303: Experimental Crystal Structure Determination;Wu, Fule;2020;Cambridge Crystallographic Data Centre


CCDC 1996304: Experimental Crystal Structure Determination;Wu, Fule;2020;Cambridge Crystallographic Data Centre


CCDC 1996305: Experimental Crystal Structure Determination;Wu, Fule;2020;Cambridge Crystallographic Data Centre


CCDC 1996307: Experimental Crystal Structure Determination;Wu, Fule;2020;Cambridge Crystallographic Data Centre


CCDC 2077958: Experimental Crystal Structure Determination;Wu, Fule;2021;Cambridge Crystallographic Data Centre

Related Article: Fule Wu, Christophe Deraedt, Yann Cornaton, Laurent Ruhlmann, Lydia Karmazin, Corinne Bailly, Nathalie Kyritsakas, Nolwenn Le Breton, Sylvie Choua, Jean-Pierre Djukic|2021|Organometallics|40|2624|doi:10.1021/acs.organomet.1c00301


CCDC 2077959: Experimental Crystal Structure Determination;Wu, Fule;2021;Cambridge Crystallographic Data Centre


CCDC 2077960: Experimental Crystal Structure Determination;Wu, Fule;2021;Cambridge Crystallographic Data Centre


CCDC 2081215: Experimental Crystal Structure Determination;Ulm, Franck;2021;Cambridge Crystallographic Data Centre

Related Article: Franck Ulm,  Saurabh Shahane,  Lai Truong‐Phuoc,  Thierry Romero,  Vasiliki Papaefthimiou,  Matthieu Chessé,  Michael J. Chetcuti,  Cuong Pham‐Huu,  Christophe Michon,  Vincent Ritleng|2021|Eur.J.Inorg.Chem.|2021|3074|doi:10.1002/ejic.202100371


CCDC 1949767: Experimental Crystal Structure Determination;Boussadia, Ahlem;2020;Cambridge Crystallographic Data Centre

Related Article: Ahlem Boussadia, Adel Beghidja, Lynda Gali, Chahrazed Beghidja, Mourad Elhabiri, Pierre Rabu, Guillaume Rogez|2020|Inorg.Chim.Acta|508|119656|doi:10.1016/j.ica.2020.119656


CCDC 2208403: Experimental Crystal Structure Determination;Avello, Marta G.;2023;Cambridge Crystallographic Data Centre

Related Article: Marta G. Avello, Stéphane Golling, Lai Truong-Phuoc, Loïc Vidal, Thierry Romero, Vasiliki Papaefthimiou, Nathalie Gruber, Michael J. Chetcuti, Frédéric R. Leroux, Morgan Donnard, Vincent Ritleng, Cuong Pham-Huu, Christophe Michon|2023|Chem.Commun.|59|1537|doi:10.1039/D2CC05302K


CCDC 2283989: Experimental Crystal Structure Determination;Costa, António G.;2023;Cambridge Crystallographic Data Centre

Related Article: António G. Costa, Gonçalo Lopes, Susana Ribeiro, Isabel C. Santos, Dulce Simão, Laura C. J. Pereira, Nolwenn Le Breton, Sylvie Choua, Stéphane A. Baudron, Manuel Almeida, Sandra Rabaça|2023|CrystEngComm|25|5362|doi:10.1039/D3CE00782K


CCDC 2283992: Experimental Crystal Structure Determination;Costa, António G.;2023;Cambridge Crystallographic Data Centre


CCDC 1823833: Experimental Crystal Structure Determination;Jewula, Pawel;2023;Cambridge Crystallographic Data Centre

Related Article: Pawel Jewula, Mickaël Grandmougin, Mélanie Choppin, Anna Maria Chiara Tivelli, Agnese Amati, Yoann Rousselin, Lydia Karmazin, Jean-Claude Chambron, Michel Meyer|2023|Eur.J.Inorg.Chem.|26|e202300038|doi:10.1002/ejic.202300038


CCDC 1589139: Experimental Crystal Structure Determination;Kuppusamy, Senthil kumar;2019;Cambridge Crystallographic Data Centre

bis(ethyl 2,6-bis(1H-pyrazol-1-yl)pyridine-4-carboxylate)-iron(ii) diperchlorate acetonitrile solvate

Related Article: Senthil kumar Kuppusamy, Benoît Heinrich, Sergi Vela, Eufemio Moreno-Pineda, Corinne Bailly, Mario Ruben|2019|Dalton Trans.|48|3825|doi:10.1039/C8DT04928A


Gaia DR1

Gaia DR1;European Space Agency;2016;Centre de Donnees Strasbourg (CDS)

VizieR Gaia DR1 Catalogue is the CDS version of data provided by the European Space Agency, 2016, Gaia DR1, Version 1.0. - https://doi.org/10.5270/esa-ogmeula


Gaia DR2

Gaia DR2;European Space Agency;2018;Centre de Donnees Strasbourg (CDS)

VizieR Gaia DR2 Catalogue is the CDS version of data provided by the European Space Agency, 2018, Gaia DR2, Version 1.0. https://doi.org/10.5270/esa-ycsawu7


CCDC 1908010: Experimental Crystal Structure Determination;Li, Jia-Wei;2020;Cambridge Crystallographic Data Centre

Related Article: Jia-Wei Li, Liang-Neng Wang, Ming Li, Pan-Ting Tang, Ni-Juan Zhang, Tian Li, Xiao-Peng Luo, Mohamedally Kurmoo, Yue-Jin Liu, Ming-Hua Zeng|2020|Org.Lett.|22|1331|doi:10.1021/acs.orglett.9b04590


CCDC 2284375: Experimental Crystal Structure Determination;Thierry, Thibault;2024;Cambridge Crystallographic Data Centre

Related Article: Thibault Thierry, Valerio Giuso, Federico Polo, Pierluigi Mercandelli, Yi-Ting Chen, Chih-Hao Chang, Matteo Mauro, Stéphane Bellemin-Laponnaz|2024|CSD Communication||| Related Article: Thibault Thierry, Valerio Giuso, Federico Polo, Pierluigi Mercandelli, Yi-Ting Chen, Chih-Hao Chang, Matteo Mauro, Stéphane Bellemin-Laponnaz|2024|Dalton Trans.|53|6445|doi:10.1039/D4DT00420E


(benzo[a]pyrido[2,3-c]phenazin-5-yl)-bis(2,2'-bipyridine)-ruthenium(ii) hexafluorophosphate diethyl ether solvate

CCDC 1959512: Experimental Crystal Structure Determination;Solís-Ruiz, Jorge Andrés;2020;Cambridge Crystallographic Data Centre

Related Article: Jorge Andrés Solís-Ruiz, Anaïs Barthe, Gilles Riegel, Rafael Omar Saavedra-Díaz, Christian Gaiddon, Ronan Le Lagadec|2020|J.Inorg.Biochem.|208|111080|doi:10.1016/j.jinorgbio.2020.111080


CCDC 1889278: Experimental Crystal Structure Determination;Solís-Ruiz, Jorge Andrés;2020;Cambridge Crystallographic Data Centre


CCDC 2057755: Experimental Crystal Structure Determination;Jewula, Pawel;2024;Cambridge Crystallographic Data Centre


Velocity data for 88 very high velocity stars;Q.-Z. Li;2024;Centre de Donnees Strasbourg (CDS)

VizieR online Data Catalogue associated with article published in journal Astronomical Journal with title ' On the Origins of Extreme Velocity Stars as Revealed by Large-scale Galactic Surveys.' (bibcode: 2023AJ....166...12L)


NGC 6397 Euclid/Gaia internal kinematics;M. Libralato;2024;Centre de Donnees Strasbourg (CDS)

VizieR online Data Catalogue associated with article published in journal Astronomy and Astrophysics with title ' Euclid: High-precision imaging astrometry and photometry from Early Release Observations. I. Internal kinematics of NGC 6397 by combining Euclid and Gaia data.' (bibcode: 2024A&A...692A..96L)


Luminous globular clusters in NGC 5128

Luminous globular clusters in NGC 5128;A. Dumont;2024;Centre de Donnees Strasbourg (CDS)

VizieR online Data Catalogue associated with article published in journal Astrophysical Journal with title ' A population of luminous globular clusters and stripped nuclei with elevated mass to light ratios around NGC 5128.' (bibcode: 2022ApJ...929..147D)


Abstract:
Organism: Human Embryonic (HEK) line samples: 3 x CRISPR Knockout HEK line cultures and 3x isogenic wild type HEK cell culturesArray: Clarion S array (Thermofisher)Experiment: whole genome gene expression profiling in MYT1L null HEK cell lines (generated by CRISPR) and 3 x isogenic wild type HEK cell lines.
Protocol provided in "MYT1L mutations cause intellectual disability and variable obesity by dysregulating gene expression and development of the neuroendocrine hypothalamus" Published in PLoS Genetics, 13 (8). e1006957. ISSN 1553-7390 DOI: 10.1371/journal.pgen.1006957

"C" files are from isogenic controls."21481" files are from MYT1L null cells

Microarray data for "MYT1L mutations cause intellectual disability and variable obesity by dysregulating gene expression and development of the neuroendocrine hypothalamus";Alisdair McNeill;2021;The University of Sheffield


Structural characterization of photoactive polymeric gels crosslinked with rotary molecular motors;PERROT Alexis;2021;Institut Laue-Langevin (ILL)


Determination of neutron detection efficiency for an ionic scintillator;DOI: 10.1126/sciadv.adj8336;2024;Institut Laue-Langevin (ILL)

DOI: 10.1126/sciadv.adj8336

Laboratoire Léon Brillouin UMR 12 CEA/CNRS


Bright VPM stars from Gaia RVS spectra

VizieR online Data Catalogue associated with article published in journal Astronomy and Astrophysics with title ' Gaia's brightest very metal-poor (VMP) stars: Metallicity catalogue of a thousand VMP stars from Gaia's radial velocity spectrometer spectra.' (bibcode: 2024A&A...683L..11V)

Bright VPM stars from Gaia RVS spectra;A. Viswanathan;2024;Centre de Donnees Strasbourg (CDS)


Scores de compréhension des 2507 élèves de CP-CE1 aux tests de compréhension de textes entendus

Résultats aux tests de compréhension de textes entendus CP-CE1;Cécile Avezard-Roger;2022;NAKALA - https://nakala.fr (Huma-Num - CNRS)


Outils d'évaluation de la compréhension de texte entendus en première année d'école élémentaire (CP) Outils d'évaluation de la compréhension de texte entendus en première année d'école élémentaire (CP)

Evaluer la compréhension de textes entendus au CP;Cécile Avezard-Roger;2022;NAKALA - https://nakala.fr (Huma-Num - CNRS)


Abstract: Dental microwear (DMA) is a tool used for the palaeodiet reconstruction of animals in Archaeology. The use of this proxy on domestic ungulates provides valuable information to reconstruct livestock strategies, yet it presents several methodological limitations. Most studies have been carried out using low-magnification DMA and the interpretations often relied on comparisons with databases of extant wild ungulates. In addition, several studies have highlighted challenges in discerning diets in extant domestic caprines. In parallel, dental microwear texture analysis (DMTA) – a quantitative methodology based on 3D micro-texture height maps – has shown better discrimination. In this paper, we explore the capacity to distinguish four different management strategies of domestic goats (Capra hircus) and three species of wild ibexes (Capra nubiana, C. pyrenaica and C. ibex) using DMTA. Results revealed good discrimination among extant domestic goat populations and between wild and domestic goats. This new dataset was subsequently used to characterise the palaeodiet of archaeological goats from two Pre-Pottery Neolithic B sites in the southern Levant. Preliminary findings suggest evidence of human intervention in goats at least during the early 8th millennium BCE. In addition, incorporating various current management strategies has enhanced our understanding of early goat domestication in southern Levant.

Environmental Sciences not elsewhere classified

Biological Sciences not elsewhere classified

Palaeodietary reconstruction of wild and domestic goats using dental microwear texture analysis. A case study from two early Neolithic sites in the southern Levant;Sergio Jiménez-Manchón;2024;Taylor & Francis


Abstract:
Non-reciprocal microwave components such as circulators, isolators, and phase shifters are indispensable tools in both today’s communication systems and future quantum computers [1-2]. However, these components rely almost entirely on field-based bulky ferrimagnet, which tend to be relatively large, off-chip, and costly to assemble. In this context, different fields of research are investigating solutions to miniaturize these non-reciprocal devices compatible with integrated circuit technology. Among them, the field of magnonic plays a key role in this search benefiting from a wide range of non-reciprocal properties in the propagation of spin waves [3]. Recently, unidirectional transmission of spin waves was achieved by taking advantage of the chiral coupling between the uniform resonance of Co nanowires and exchange spin waves in a thin YIG film [4, 5]. Here, we further miniaturized this method and demonstrate the possibility of shaping non-reciprocal spin wave beams in a continuous thin YIG film. We performed spin wave spectroscopy on a series of devices made of arrays of Co bars of dimensions: L=10µm in length, w=200 nm in width, 40nm in thickness, and laterally spaced by a=400nm (see Fig. 1). The transmission spectra done with the external field applied along the length of the Co bars show perfect non-reciprocity for several peaks located around the resonance frequency of the Co bars, e.g. 8.4 to 10.4 GHz range as shown in Fig. 2. These peaks correspond to integer values of the lateral spacing between Co bars, e.g. kn=nπ/a ranging up to 80rad/µm. Additional non-reciprocal peaks occurring at lower frequencies ranging between 2 and 6 GHz correspond to the satellite peaks of the antenna directly coupled to the YIG film. Surprisingly, some of the peaks display a reversed non-reciprocity. Finally, we make use of this multitude of transmission peaks to characterize the k-dependence of the relaxation time and the group velocity of dipole-exchange spin waves.
 References 87.png)[1] W. Palmer, et al., IEEE Micr. Magazine 20, 36 (2019)
 [2] M. Devoret, et al., Superconducting circuits for quantum information,Science 339, 1169 (2013)
 [3] J. Chen, et al., J. Phys. D. Appl. Phys. 55, 123001 (2022)
 [4] H. Wang, et al., Nano Res. 14, 2133–2138 (2021)
 [5] J. Chen, et al., Phys. Rev. B 100, 104427 (2019)

 https://s3.eu-west-1.amazonaws.com/underline.prod/uploads/markdown_image/1/image/94e4cd227f20528c8226450f05b99d7c.png
 SEM image of Co nanowires with length L=10μm, width w=200nm, and period a=400nm lithographed on a 50nm YIG film with thickness, and located under 2 µm wavelength Au coplanar waveguides (CPW) https://s3.eu-west-1.amazonaws.com/underline.prod/uploads/markdown_image/1/image/0d51030b4d6ea35e8b9bbc51296dd09e.png
 Transmission spectrum ΔL21 (blue) and ΔL12 (red) at 24mT applied field.

High Wave Vector Non reciprocal spin Wave Beams;MMM Conferences 2022;2022;Underline Science Inc.


Abstract: The analysis of axillary and supraclavicular lymph nodes is a primary prognostic factor for the staging of breast cancer. However, due to the size of lymph nodes and the low resolution of PET data, their segmentation is challenging. We investigate the relevance of considering axillary and supraclavicular lymph node segmentation from PET/CT images by coupling Convolutional Neural Networks (CNNs) and Component-Trees (C-Trees). Building upon the U-Net architecture, we propose a framework that couples a multi-modal U-Net fed with PET and CT, coupled with a hierarchical model obtained from the PET that provides additional high-level region-based features as input channels. Our working hypotheses are twofold. First, we take advantage of both anatomical information from CT for detecting the nodes, and functional information from PET for detecting the pathological ones. Second, we consider region-based attributes extracted from C-Tree analysis of 3D PET/CT images to improve the CNN segmentation. We carried out experiments on a dataset of 240 pathological lymph nodes from 52 patients scans, and compared our outputs with human expert-defined ground-truth, leading to promising results.

Segmentation of Axillary and Supraclavicular Tumoral Lymph Nodes in PET/CT: A Hybrid CNN/Component-Tree Approach;International Association for Pattern Recognition 2021;2021;Underline Science Inc.


Abstract: An entry from the Inorganic Crystal Structure Database, the world’s repository for inorganic crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the joint CCDC and FIZ Karlsruhe Access Structures service and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

Inorganic Crystal Structure Database (ICSD)

CSD 1998371: Experimental Crystal Structure Determination;Isaac, Carole;2021;FIZ Karlsruhe - Leibniz Institute for Information Infrastructure

Related Article: Carole Isaac, Jean-Louis Paillaud, T. Jean Daou, Andrey Ryzhikov|2021|Microporous and Mesoporous Materials|312|110804|doi:10.1016/j.micromeso.2020.110804


Source data

Abstract: Source data for figures in the related paper, including raw data underlying graphs and uncropped versions of gels or blots presented in the figures


Abstract: Urbanization is characterized by rapid environmental changes such as an increase in building surface, in pollution, or a decrease in invertebrate abundance. For many bird species, morphological and physiological differences have been observed between urban and rural individuals that seem to reflect a negative impact of urban life on the health and fitness of individuals. Studies on passerine birds also showed important differences between populations and species in their responses to the urban environment. We proposed to test physiological differences between urban and forest individuals over 3 years to understand whether the observed patterns are constant or subject to variations across years. For this purpose, we assessed the health parameters of adults and fledgling of great tits, Parus major, living in an urban and in a forest site in the Eurometropole of Strasbourg, for three years. Bird health was estimated with morphological parameters (body condition and size) and also with physiological parameters (oxidative status and telomere length). Our results showed lower body condition of urban fledglings regardless of the year, but no site effects on telomere length. On the contrary, for adult breeders, urban individuals had longer telomeres than forest ones except for one year which coincide with bad weather conditions during reproduction where no difference was detected. Urban birds also had higher antioxidant capacity whatever the years. These results suggest that cities act as a filter in which only good quality individuals survive and achieve successful reproduction regardless of year, whereas in the forest the selection occurs only during harsh weather years.

Dataframe of inter-annual variation of physiological traits between urban and forest great tits (adults and nestlings).;Agnès SAULNIER;2023;Mendeley


Abstract: Figure A1: Fluorescence (excitation at 405 nm) observations of phytoliths in re-burned cyclone ash from Miscanthus sinensis combustion using a Zeiss LSM 510 confocal microscope. (a) Images of the variation of the fluorescence from a single phytolith (phytolith 1, see (b,c)) at various emission wavelengths. (b) Fluorescence intensity as a function of emission wavelength for the four different phytoliths, shown in (c) at a fluorescence wavelength of 495 nm. Figure A2: EDX element distribution maps of three phytoliths in a dry extract of Miscanthus sinensis. The C signal around the three phytoliths results from the carbon substrate used to mount the sample for the ESEM investigations; it is not caused by organic material from the plant. Figure A3: EDX element distribution maps of phytoliths in a sample of re-burned cyclone ash from the combustion of Miscanthus sinensis straw. The Ca map clearly shows the calcite aggregates that surround the phytoliths. The K+Cl map (a superposition of individually generated distribution maps of K and Cl) reveals the occurrence of small sylvite crystals within the calcite aggregates. Figure A4: X-ray diffraction pattern of the re-burned cyclone ash. Qtz = quartz; Cc = calcite; Syl = sylvite; Per = periclase. Observed spectrum (red line), fitted spectrum (blue solid line), difference plot (red spectrum in lower part of image) and Bragg peak positions (tick marks above difference plot) are shown. The weighted R-factor, Rwp, was calculated using the observed and calculated intensities in the powder diffraction patterns. Table A1: The ash content (in wt%) of Miscanthus sinensis straw, determined by the dry-ashing technique Table A2: Phytolith content (in wt%) of Miscanthus ash, as determined by dry extraction. Table A3: Phytolith dimensions as determined in ESEM images of Miscanthus dry extracts (in µm) Table A4: ESEM-EDXS spot analyses data summary.

Data for: Opaline phytoliths in Miscanthus sinensis and its cyclone ash from a biomass-combustion facility;Ruggero Vigliaturo;2019;Mendeley


Abstract: Collective moments of inertia as well as quadrupole and octupole mass parameters are calculated in the perturbative cranking approximation using the folded-Yukawa mean-field potential written in Cartesian coordinates. The resulting single-particle Hamiltonian is required, as a minimal symmetry, to be invariant under z-signature and time-reversal transformations. The deformation of the nucleus is defined through a shape parametrization in cylindrical coordinates, with the so-called Funny–Hills and Trentalange–Koonin–Sierk shapes as typical and performant examples. To take pairing correlations into account, the standard set of BCS equations is solved with an approximation of constant pairing strength. The numerical program determining the quadrupole–octupole mass tensor and the moments of inertia, written in Fortran, is constructed according to the here presented study as an extension and application of the “yukawa” code for the diagonalization of the folded-Yukawa mean-field potential in the basis of a harmonic-oscillator in Cartesian coordinates, published in this journal in 2016.

Nuclear mass parameters and moments of inertia in a folded-Yukawa mean-field approach;A. Dobrowolski;2018;Mendeley


Abstract: A national product of Surface Water Dynamics in France (SWDF) on a monthly temporal scale and 10-m spatial scale is generated using an automatic rule-based superpixel (RBSP) approach. The datasets include the monthly, seasonal, annual (permanent and maximum extents) and annual frequency maps of surface water bodies in France using Sentinel-2 imagery. Also, the datasets provide our validation data (200 sampling points and two local lakes). The detailed description and methodology can be found in the linked manuscript and its supplemental materials. If you have any additional questions, please contact xiuchengyang@163.com.

Data for: Monthly estimation of the surface water extent in France at a 10-m resolution using Sentinel-2 data;Xiucheng Yang;2020;Mendeley


Abstract: Abstract The nuclear Hamiltonian with a Yukawa-folded mean-field potential is diagonalized within the basis of a deformed harmonic-oscillator in Cartesian coordinates. The nuclear shape is characterized by the equivalent sharp surface described either by the well known Funny–Hills or the Trentalange–Koonin–Sierk parametrizations. They are both able to describe a very vast variety of nuclear deformations, including necked-in shapes, left–right asymmetry and non-axiality. The only imposed limitation on ... Title of program: yukawa Catalogue Id: AEYI_v1_0 Nature of problem The full single-particle nuclear Hamiltonian composed of the Yukawa-folded central, spin-orbit and Coulomb potentials is generated and diagonalized. The only symmetry of the problem is the so called z-signature symmetry which limits the nuclear shapes to those, being invariant with respect to a rotation by an angle π around the z-axis. Versions of this program held in the CPC repository in Mendeley Data AEYI_v1_0; yukawa; 10.1016/j.cpc.2015.09.020 This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2018)

Solving the eigenvalue problem of the nuclear Yukawa-folded mean-field Hamiltonian;A. Dobrowolski;2019;Mendeley


Abstract:
Oxford Nanopore Technologies Ltd (Oxford, UK) have recently commercialized MinION, a small single-molecule nanopore sequencer, that offers the possibility of sequencing long DNA fragments from small genomes in a matter of seconds. The Oxford Nanopore technology is truly disruptive, it has the potential to revolutionize genomic applications due to its portability, low-cost, and ease of use compared with existing long reads sequencing technologies. The MinION sequencer enables the rapid sequencing of small eukaryotic genomes, such as the yeast genome. Combined with existing assembler algorithms, near complete genome assemblies can be generated and comprehensive population genomic analyses can be performed.

Here, we resequenced the genome of the Saccharomyces cerevisiae S288C strain to evaluate the performance of nanopore-only assemblers. Then we de novo sequenced and assembled the genomes of 21 isolates representative of the S. cerevisiae genetic diversity using the MinION platform. The contiguity of our assemblies was 14 times higher than the Illumina-only assemblies and we obtained one or two long contigs for 65% of the chromosomes. This high contiguity allowed us to accurately detect large structural variations across the 21 studied genomes.

Because of the high completeness of the nanopore assemblies, we were able to produce a complete cartography of transposable elements insertions and inspect structural variants that are generally missed using a short-read sequencing strategy.

Supporting data for "de novo assembly and population genomic survey of natural yeast isolates with the Oxford Nanopore MinION sequencer";Benjamin Istace;2016;GigaScience Database


Abstract: Data and code accompanying A. François, S. Panel & L. Weill (2022), "Dictators' facial characteristics and foreign direct investment", Leadership Quarterly, 10.1016/j.leaqua.2022.101644

Replication data for: A. François, S. Panel, L. Weill, "Dictators' facial characteristics and foreign direct investment", Leadership Quarterly (2022), doi: 10.1016/j.leaqua.2022.101644;Abel François;2022;Harvard Dataverse

text/tab-separated-values application/x-stata-syntax text/tab-separated-values application/pdf


Abstract: The m6A epitranscriptomic mark is the most abundant and widespread internal RNA chemical modification, which through the control of RNA acts as an important factor of eukaryote reproduction, growth, morphogenesis and stress response. The main m6A readers constitute a super family of proteins with hundreds of members that share a so-called YTH RNA binding domain. The majority of YTH proteins carry no obvious additional domain except for an Intrinsically Disordered Region (IDR). In Arabidopsis thaliana IDRs are important for the functional specialization among the different YTH proteins, known as Evolutionarily Conserved C-Terminal region, ECT 1 to 12. Here by studying the ECT2 protein and using an in vitro biochemical characterization, we show that full-length ECT2 and its YTH domain alone have a distinct ability to bind m6A, conversely to previously characterized YTH readers. We identify peptide regions outside of ECT2 YTH domain, in the N-terminal IDR, that regulate its binding to m6A-methylated RNA. Furthermore, we show that the selectivity of ECT2 binding for m6A is enhanced by a high uridine content within its neighbouring sequence, where ECT2 N-terminal IDR is believed to contact the target RNA in vivo. Finally, we also identify small structural elements, located next to ECT2 YTH domain and conserved in a large set of YTH proteins, that enhance its binding to m6A-methylated RNA. We propose from these findings that some of these regulatory regions are not limited to ECT2 or YTH readers of flowering plants but may be widespread among eukaryotic YTH readers.

ECT2 peptide sequences outside the YTH domain regulate its m6A-RNA binding;Daphné Seigneurin-Berny;2024;Taylor & Francis


Abstract: An innovative parametrization of nuclear shapes, based on a Fourier expansion of the square distance from the surface of the nucleus to the symmetry axis is introduced. Surface, curvature and Coulomb energy coefficients of a charged liquid drop, that determine the semiclassical nuclear energy, are evaluated within this shape parametrization, together with the wall-friction and the irrotational-flow mass tensors. These transport coefficients are important ingredients of many nuclear models describing nuclear structure and dynamics. A numerical code allowing for the determination of all these quantities for a huge variety of nuclear shapes is made available to the interested user.

Transport coefficients in the Fourier shape parametrization;J. Bartel;2019;Mendeley


Abstract: This publication provides a database on metal contamination of sediments collected along seven rivers draining Western Europe (French Rhône, Garonne-Lot, Loire, Meuse, Rhine, Scheldt and Seine Rivers). This dataset is based on both long-term monitoring and scientific research (see column sources). It presents major (Al, Fe) and trace metals (Cd, Cr, Cu, Hg, Ni, Pb, Zn) coming from various solid matrices, such as suspended particulate matter (SPM), dated sediment cores (DSC), and bed and flood deposits (BFD). It also provides information about the extraction procedure, grain-size (expressed as a percentage of the fine particle [silts and clays < 63 µm] proportion in the samples) and total organic carbon (TOC) contents when available. It could be use to assess the level of metal contamination along the river since 1945 and to decipher the key factors influencing metal concentrations in river sediments over space and time.

Metal contamination in sediments along Western European Rivers (1945-2020);André-Marie Dendievel;2021;PANGAEA


Abstract: Supplementary tables S1 report the protein identification and quantification from the whole proteomes of adult black garden ants (Lasius niger). Measurements have been performed in queens, nest-workers and foragers. Supplementary tables S2 and S3 report the proteins that significantly differentiate queens, nest-workers and foragers. They are associated with their respective contributions to the PCA's axes and their functions found in insect-based literature.

Data for: Division of labour in the black garden ant (Lasius niger) leads to three distinct proteomes;Martin Quque;2019;Mendeley


Abstract: Prostate cancer (PrCa) is the second most common malignancy in men. More than 50% of advanced prostate cancers display the TMPRSS2-ERG fusion. Despite extensive cancer genome/transcriptome data, little is known about the impact of mutations and altered transcription on regulatory networks in the PrCa of individual patients. Using patient-matched normal and tumor samples, we established somatic variations and differential transcriptome profiles of primary ERG-positive prostate cancers. Integration of protein-protein interaction and gene-regulatory network databases defined highly diverse patient-specific network alterations. Different components of a given regulatory pathway were altered by novel and known mutations and/or aberrant gene expression, including deregulated ERG targets, and were validated by using a novel in silico methodology. Consequently, different sets of pathways were altered in each individual PrCa. In a given PrCa, several deregulated pathways share common factors, predicting synergistic effects on cancer progression. Our integrated analysis provides a paradigm to identify druggable key deregulated factors within regulatory networks to guide personalized therapies.

Patient-matched analysis identifies deregulated networks in prostate cancer to guide personalized therapeutic intervention;Marco Mendoza;2021;Mendeley


Abstract: These four files include all the data relevant for the article entitled "High-resolution foraminifer stable isotope record of MIS 19 at Montalbano Jonico, southern Italy: a window into Mediterranean climatic variability during a low-eccentricity interglacial” by S. Nomade., F. Bassinot., M. Marino., Q. Simon ., F. Dewilde., P. Maiorano., G. Isguder., D. Blamart., A. Girone., V. Scao., A. Pereira., F. Toti., A. Bertini., N. Combourieu-Nebout., M. Peral., D. L. Bourlès., P. Petrosino., S. Gallicchio and N. Ciaranfi. - Be-ratio dataSM1 is the 10 Be and 9 Be measurments - Stable Isotopes Data SM2 includes all stables isotope measurments from IDEAL and CIARANFI MASTER sections - SM3 corresponds to the full 40Ar/39Ar dataset and blank corrections - Supplementary SM4 present all the data to build figure 5 incuding Planktonic form warm water counting, Ostracod paleo depth, Factor 1 paleodepth, Pollen Index

Data for: High-resolution foraminifer stable isotope record of MIS 19 at Montalbano Jonico, southern Italy: a window into Mediterranean climatic variability during a low-eccentricity interglacial;Sebastien Nomade;2018;Mendeley


Mouse femur LC-MSMS upon weightlessness

Abstract: Bone loss and immune dysregulation are among the main adverse outcomes of spaceflight challenging astronaut’s health and safety. However, consequences on B cell development and responses are still under-investigated. Up to now, most studies addressing these questions were performed using an amphibian species. Consequently, we used advanced proteomics analysis of femur bone and marrow of mice flown for one month on board the BION-M1 biosatellite, to determine whether extreme conditions encountered during a real spaceflight affect B cell development in mice and to examine reversibility of the effects upon return to Earth. Our data revealed that adverse effects on B lymphopoiesis were more marked one week after landing and that this phenomenon was associated with a 41% reduction of B cells in the spleen. Thus, the effects of spaceflight persisted during at least one week after landing. These reductions may contribute to explain increased susceptibility to infection even if we confirmed that animals were able to mount a humoral immune response.

Mouse femur LC-MSMS upon weightlessness;Fabrice Bertile;2018;NASA GeneLab


Abstract: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

CCDC 2050554: Experimental Crystal Structure Determination;bouchameni, chahra;2021;Cambridge Crystallographic Data Centre

Related Article: chahra bouchameni|2021|CSD Communication||| Related Article: BOUCHAMENI Chahra, ZEGHOUAN Ouahida, Mahesha, A.H Udaya Kumar, BEGHIDJA Chahrazed, WELTER Richard, N.K. Lokanath|2022|J.Mol.Struct.|1275|134716|doi:10.1016/j.molstruc.2022.134716


Abstract: Supplementary Code for paper Phase-separated Droplets Can Direct Chemical Reaction Kinetics of Polymerization, Self-replication and Oscillating Networks (ChemSysChem). A numerical ODE based model is included to study how coacervate droplets can influence reaction rates, polymer length distributions, chemical self-replicators and the behavior of oscillatory networks, providing insights into their potential roles in both prebiotic chemistry and biological systems.

Phase-separated Droplets Can Direct Chemical Reaction Kinetics of Polymerization, Self-replication and Oscillating Networks;Iris B A Smokers;2024;Radboud University


Hi-GAL compact source catalog. -71.0

Hi-GAL compact source catalog. -71.0;D. Elia;2020;Centre de Donnees Strasbourg (CDS)

VizieR online Data Catalogue associated with article published in journal Monthly Notices of the Royal Astronomical Society with title ' The Hi-GAL compact source catalogue. I. The physical properties of the clumps in the inner Galaxy (-71.0{deg} < l < 67.0{deg}).' (bibcode: 2017MNRAS.471..100E)


CCDC 2332008: Experimental Crystal Structure Determination;Kurpik, Gracjan;2024;Cambridge Crystallographic Data Centre

Related Article: Gracjan Kurpik, Anna Walczak, Paweł Dydio, Artur R. Stefankiewicz|2024|Angew.Chem.,Int.Ed.|63|e202404684|doi:10.1002/anie.202404684


CCDC 2253515: Experimental Crystal Structure Determination;Schiesser, Stefan;2023;Cambridge Crystallographic Data Centre

Related Article: Stefan Schiesser, Joanna Ceklarz, Johanna Kollback, Lucie Borowiec, Julia Fågerlund, Shakiba Vahdat, Marika Lindhagen, Okky Dwichandra Putra|2023|Chem.-Eur.J.|29|e202301421|doi:10.1002/chem.202301421


46 open clusters GaiaDR2 HR diagrams

46 open clusters GaiaDR2 HR diagrams;Gaia Collaboration;2018;Centre de Donnees Strasbourg (CDS)

VizieR online Data Catalogue associated with article published in journal Astronomy & Astrophysics with title 'Gaia Data Release 2: Observational Hertzsprung-Russell diagrams.' (bibcode: 2018A&A...616A..10G)


Abstract: Raw imaging data (e.g. uncropped and unannotated agarose gels, Northern blots and thin layer chromatography autoradiograms).

Transfer RNA maturation defects lead to inhibition of ribosomal RNA processing via synthesis of pppGpp. Trinquier et al.;Ciaran Condon;2019;Mendeley


Abstract: This file contains the blockade duration and amplitudes of all experiments, this file can be read with a control R script file to do the statistical clustering and plotting the data. A database file (*.db) contains all the blockades from theTRPS data (the blockade waveform), this file can be processed with aid of a small python program for representing the waveforms. Note: the python program uses the libraries of neurophysiology OpenElectrophy for waveform recognition and sorting.

Data for: Humic acids modify the pulse size distributions in the characterization of plastic microparticles by Tunable Resistive Pulse Sensing;Mª Laura Vázquez Juiz;2018;Mendeley


Grid of stellar models

Grid of stellar models;G. Costa;2024;Centre de Donnees Strasbourg (CDS)

VizieR online Data Catalogue associated with article published in journal Astronomy and Astrophysics with title ' He-enriched STAREVOL models for globular cluster multiple populations. Self-consistent isochrones from ZAMS to the TP-AGB phase.' (bibcode: 2024A&A...690A..22C)


Cetus stream non-LTE abundance analysis

Cetus stream non-LTE abundance analysis;T.M. Sitnova;2024;Centre de Donnees Strasbourg (CDS)

VizieR online Data Catalogue associated with article published in journal Astronomy and Astrophysics with title ' HR-GO I. Comprehensive non-LTE abundance analysis of the Cetus stream.' (bibcode: 2024A&A...690A.331S)


Abstract: Denaturing polyacrylamide gels of cleavage products show that GreB accelerates RNA cleavage (left). The resulting complex is active and resumes transcription (+NTPs). Using an RNA with phosphorothioate modifications slows down the cleavage without affecting the position (right). To help the reader, cleavage_reaction_a.tif represents the raw data, while cleavage_reaction_b.tif, matches the figure in the publication (Figure S1D).

Denaturing polyacrylamide gels of RNA cleavage reaction in presence or absence of bacterial GreB;Mo'men Abdelkareem;2019;Mendeley


Abstract: These are (1) the data used to calibrate our model, (2) our model and (3) the results.

Data for: Estimating the climate services value for forest management: the case of drought for maritime Pine plantations in South-West France;Sylvain Caurla;2019;Mendeley


Abstract: Abstract Considerable research efforts have been directed at implementing the Faddeeva function w ( z ) and its derivatives with respect to z , but these did not consider the key computing issue of a possible dependence of z on some variable t . The general case is to differentiate the compound function w ( z ( t ) ) = w ∘ z ( t ) with respect to t by applying the chain rule for a first order derivative, or Faà di Bruno’s formula for higher-order ones. Higher-order automatic differentiation (HOAD) is ... Title of program: HOAD_MathFun Catalogue Id: AFAG_v1_0 Nature of problem General optimized higher-order automatic differentiation of mathematical functions. Complex refractive index as a case study. Versions of this program held in the CPC repository in Mendeley Data AFAG_v1_0; HOAD_MathFun; 10.1016/j.cpc.2016.04.009 This program has been imported from the CPC Program Library held at Queen's University Belfast (1969-2018)

Optimized higher-order automatic differentiation for the Faddeeva function;Isabelle Charpentier;2019;Mendeley


Five years monitoring of M87

Five years monitoring of M87;F. Marin;2024;Centre de Donnees Strasbourg (CDS)

VizieR online Data Catalogue associated with article published in journal Astronomy and Astrophysics with title ' Forgotten treasures in the HST/FOC UV imaging polarimetric archives of active galactic nuclei. III. Five years monitoring of M87.' (bibcode: 2024A&A...692A.179M)


eROSITA supernova remnant population in LMC;F. Zangrandi;2024;Centre de Donnees Strasbourg (CDS)

VizieR online Data Catalogue associated with article published in journal Astronomy and Astrophysics with title ' First study of the supernova remnant population in the Large Magellanic Cloud with eROSITA.' (bibcode: 2024A&A...692A.237Z)


Abstract: Trace metal elements are significant stressors in urban areas. Their harmful effects on physiological parameters are demonstrated, but current laboratory studies are not representative of wild chronic exposure to a trace metal cocktail. Calcium can reduce the accumulation and toxicity of several metals, but soil acidification in cities leads to a decrease in bioavailability of this element. The objective of this study was to investigate the accumulation and toxicity of a trace metal cocktail representative of urban exposure on passerine birds, and test the importance of calcium availability on these toxic effects. We exposed zebra finches (Taeniopygia guttata) to a cocktail of metals and metalloids in drinking water, with or without calcium supplementation. We monitored the concentration of metals in the blood and feathers, and their effects on oxidative status, and telomere length. The metal cocktail led to higher concentration of all elements in the feathers, and of arsenic and lead in the blood. Birds with a higher concentration of cadmium, arsenic and lead in the feathers had shorter telomeres, but no impact of the cocktail was detected on the oxidative status. Birds of the ‘calcium’ group and the ‘calcium and metal’ group accumulated higher concentrations of zinc, chromium and nickel in feathers. The ‘calcium and metal’ group also accumulated lower concentrations of arsenic and lead in feathers compared to the ‘metal’ group. Our results suggests that chronic exposure to a cocktail of metals at low concentrations has deleterious effects on birds, which can be limited through calcium intake. Methods 4 groups of 10 birds were exposed to 4 treatments: 'Ctrl’= control group with low-Ca diet and no trace metal element (TME), ‘TME’= birds with low–Ca diet exposed to a TME cocktail, ‘Ca’= rich-Ca diet and no TME and ‘TME+Ca’= rich-Ca diet and TME cocktail. The TME cocktail contained both essential TME (i.e, necessary for biological process) and non-essential metals and metalloid: 10 ppm of Pb , 0.7 ppm of Cr, 1 ppm of As, 100 ppm of Zn, 24 ppm of Cu, 0.5 ppm of Ni, 0.2 ppm of Co, and 0.1 ppm of Cd. At day 0, tarsus length was measured with a calliper (±0.1 mm). Every two weeks we measured body mass (±0.1 g) with a precision scale and collected 100 µL of blood from brachial vein (in 2 tubes of 50 µL) with heparinized capillary to measure physiological parameters (free, oxidised and total glutathione, glutahione peroxidase activity, dosage of reactive oxygen metabolites, and relative telomere length) and concentrations of metals (ICP-MS analyses). At day 0 and 29 we also collected the right fourth primary feather for metal analyses (ICP-MS analyses). For blood, several samples had metal concentrations under the limit of detection. To take these data into account, we used a statistical method for left censored data with a specific package : NADA package which requires pre-processing of data. It corresponds to the last 16 columns of this file.

Consequences of trace metal cocktail exposure in zebra finch (Taeniopygia guttata) and effect of calcium supplementation;Agnès Saulnier;2020;Mendeley


Young groups and clusters from GES and Gaia EDR3;N.J. Wright;2024;Centre de Donnees Strasbourg (CDS)

VizieR online Data Catalogue associated with article published in journal Monthly Notices of the Royal Astronomical Society with title ' The Gaia-ESO Survey: 3D dynamics of young groups and clusters from GES and Gaia EDR3.' (bibcode: 2024MNRAS.533..705W)


Abstract:
The objective of this article is to compare the progression in learning curves of junior surgeons trained in the anterior plating technique for the distal radius on a non-biological model according to three different methods.
The materials comprised 12 junior surgeons of level 1 or 2 divided into three groups: control (G1), naive practice (G2) and deliberate practice (G3).
The three groups watched a demonstration video of a level 5 expert. The four G1 surgeons (two level 1 and two level 2) saw the video only once and each inserted five plates. The four G2 surgeons (two level 1 and two level 2) inserted five plates and watched the video before each time. The four G3 surgeons (two level 1 and two level 2) saw the video before the first plate insertion. Before posing the subsequent four plates, the four G3 surgeons watched their own video and the expert indicated their errors and how to avoid them next time.
A 12-criteria OSATS defined on the basis of the 60 videos, each graded from 1 (min.) to 5 (max.) was used to measure the objective surgical performance per plating (min. 12; max. 60) and per series of five plate fixations (min. 60, max. 300).
Our results show that deliberate practice is a learning technique for surgical procedures which allows the growth phase of the learning curve to be shortened and the objective performance of junior surgeons to be improved.

Data for Anterior Plating Technique for Distal Radius: Comparing performance after learning through naive versus deliberate practice;Laëla EL AMIRI;2022;Mendeley


Abstract: Raw and treated Research Data including rainfall and runoff characteristics, pesticide loads exported from the vineyard catchment and export coefficients.

Data for: Do rainfall characteristics affect the export of copper, zinc and synthetic pesticides in surface runoff from headwater catchments?;Gwenael Imfeld;2020;Mendeley


Abstract:
Data used for analyses described in the article "To draw or not to draw: understanding the temporal organization
of drawing behaviour using fractal analyses"

Data of the article "To draw or not to draw: understanding the temporal organization of drawing behaviour using fractal analyses";Lison Martinet;2021;Mendeley


Abstract: U-Pb-Lu-Hf isotopic data on zircons for granulite and paragneiss samples of Góry Sowie Massif

Data for: Evolution of Cambro-Ordovician North Gondwana active margin: geochemistry and zircon geochronology evidence from Góry Sowie metasedimentary rocks;Anne-Sophie Tabaud;2020;Mendeley


The Pristine survey. IX.

The Pristine survey. IX.;K.A. Venn;2023;Centre de Donnees Strasbourg (CDS)

VizieR online Data Catalogue associated with article published in journal Monthly Notices of the Royal Astronomical Society with title ' The Pristine survey IX. CFHT ESPaDOnS spectroscopic analysis of 115 bright metal-poor candidate stars.' (bibcode: 2020MNRAS.492.3241V)


Pristine Inner Galaxy Survey. X.

Pristine Inner Galaxy Survey. X.;F. Sestito;2024;Centre de Donnees Strasbourg (CDS)

VizieR online Data Catalogue associated with article published in journal Astronomy and Astrophysics with title ' The Pristine Inner Galaxy Survey (PIGS). X. Probing the early chemical evolution of the Sagittarius dwarf galaxy with carbon abundances.' (bibcode: 2024A&A...690A.333S)


Abstract: Traffic of molecules across the bacterial membrane mainly relies on porins and transporters, whose expression must adapt to environmental conditions. To ensure bacterial fitness, synthesis and assembly of functional porins and transporters are regulated through a plethora of mechanisms. Among them, small regulatory RNAs (sRNAs) are known to be powerful post-transcriptional regulators. In Escherichia coli, the MicF sRNA is known to regulate only four targets, a very narrow targetome for a sRNA responding to various stresses, such as membrane stress, osmotic shock, or thermal shock. Using an in vivo pull-down assay combined with high-throughput RNA sequencing, we sought to identify new targets of MicF to better understand its role in the maintenance of cellular homoeostasis. Here, we report the first positively regulated target of MicF, the oppA mRNA. The OppA protein is the periplasmic component of the Opp ATP-binding cassette (ABC) oligopeptide transporter and regulates the import of short peptides, some of them bactericides. Mechanistic studies suggest that oppA translation is activated by MicF through a mechanism of action involving facilitated access to a translation-enhancing region in oppA 5ʹUTR. Intriguingly, MicF activation of oppA translation depends on cross-regulation by negative trans-acting effectors, the GcvB sRNA and the RNA chaperone protein Hfq.

Hfq protein and GcvB small RNA tailoring of oppA target mRNA to levels allowing translation activation by MicF small RNA in Escherichia coli;Marie-Claude Carrier;2023;Taylor & Francis


Deep view into Sagittarius dSph with MUSE. III.;N. Kacharov;2024;Centre de Donnees Strasbourg (CDS)

VizieR online Data Catalogue associated with article published in journal Astrophysical Journal with title ' A deep view into the nucleus of the Sagittarius dwarf spheroidal galaxy with MUSE. III. Discrete multicomponent population-dynamical models based on the Jeans equations.' (bibcode: 2022ApJ...939..118K)


Structures of B. subtilis maturation RNases captured on 50S ribosome with pre-rRNAs. Oerum et al;Carine Tisne;2020;Mendeley


CCDC 2374330: Experimental Crystal Structure Determination;Khariushin, Ivan V.;2024;Cambridge Crystallographic Data Centre

Related Article: Ivan V. Khariushin, Alexander S. Ovsyannikov, Stéphane A. Baudron, Jas S. Ward, Anniina Kiesilä, Kari Rissanen, Elina Kalenius, Matthieu Chessé, Beata Nowicka, Svetlana E. Solovieva, Igor S. Antipin, Véronique Bulach, Sylvie Ferlay|2025|Nanoscale|17|1980|doi:10.1039/D4NR03622K


CCDC 2374315: Experimental Crystal Structure Determination;Khariushin, Ivan V.;2024;Cambridge Crystallographic Data Centre


CCDC 2374431: Experimental Crystal Structure Determination;Khariushin, Ivan V.;2024;Cambridge Crystallographic Data Centre


CCDC 2374432: Experimental Crystal Structure Determination;Khariushin, Ivan V.;2024;Cambridge Crystallographic Data Centre


CCDC 2293625: Experimental Crystal Structure Determination;Friedrich, Alexandra;2024;Cambridge Crystallographic Data Centre

Related Article: Alexandra Friedrich, Lisa Schraut-May, Florian Rauch, Pablo Durand, Johannes Krebs, Paul N. Ruth, Sebastian Hammer, Rüdiger Bertermann, Maik Finze, Stewart J. Clark, Jens Pflaum, Nicolas Leclerc, Todd B. Marder|2025|Org.Chem.Front.|12|736|doi:10.1039/D4QO01825G


CCDC 2293626: Experimental Crystal Structure Determination;Friedrich, Alexandra;2024;Cambridge Crystallographic Data Centre


CCDC 2293627: Experimental Crystal Structure Determination;Friedrich, Alexandra;2024;Cambridge Crystallographic Data Centre


CCDC 2293628: Experimental Crystal Structure Determination;Friedrich, Alexandra;2024;Cambridge Crystallographic Data Centre


CCDC 2293629: Experimental Crystal Structure Determination;Friedrich, Alexandra;2024;Cambridge Crystallographic Data Centre


CCDC 2293630: Experimental Crystal Structure Determination;Friedrich, Alexandra;2024;Cambridge Crystallographic Data Centre


CCDC 2293631: Experimental Crystal Structure Determination;Friedrich, Alexandra;2024;Cambridge Crystallographic Data Centre


CCDC 2293632: Experimental Crystal Structure Determination;Friedrich, Alexandra;2024;Cambridge Crystallographic Data Centre


CCDC 2293633: Experimental Crystal Structure Determination;Friedrich, Alexandra;2024;Cambridge Crystallographic Data Centre


CCDC 2293634: Experimental Crystal Structure Determination;Friedrich, Alexandra;2024;Cambridge Crystallographic Data Centre


CCDC 2293635: Experimental Crystal Structure Determination;Friedrich, Alexandra;2024;Cambridge Crystallographic Data Centre


CCDC 2293636: Experimental Crystal Structure Determination;Friedrich, Alexandra;2024;Cambridge Crystallographic Data Centre


CCDC 2293637: Experimental Crystal Structure Determination;Friedrich, Alexandra;2024;Cambridge Crystallographic Data Centre


CCDC 2293638: Experimental Crystal Structure Determination;Friedrich, Alexandra;2024;Cambridge Crystallographic Data Centre


CCDC 2293639: Experimental Crystal Structure Determination;Friedrich, Alexandra;2024;Cambridge Crystallographic Data Centre


Abstract: The Chilean copper mining industry generates large amounts of waste rock materials. These structures must be designed, operated, and closed considering their physical stability. Although these structures generally do not present physical stability problems, superficial failures may occur, where waste rock material is subjected to low confining pressures. The identification of the internal friction angle, necessary for stability calculations, is based on the characterisation of these materials under high confining pressures. This assumption is not representative of the loading conditions in the superficial layers. To address this issue, numerical large-scale triaxial tests, using the contact dynamics method, are performed to identify the internal friction angle of these materials under low confining pressures. To model these material, irregular polyhedrons were generated using statistical data of crushed aggregates, considering the morphology and the particle size distribution from experimental waste rock materials. The proposed numerical approach was validated by comparing it to literature data for confining pressures over 0.5 MPa. Our results indicate that the internal friction angle stabilises at 39° for confining pressures below 0.1 MPa. This study provides important insights into the physical stability of waste rock dumps and contributes to the development of more accurate stability calculations for these structures.

Characterisation of the internal friction angle of waste rock material from large triaxial tests using the contact dynamics method;Juan Carlos Quezada;2024;Taylor & Francis


CCDC 1565997: Experimental Crystal Structure Determination;Sundarraman, Balaji;2022;Cambridge Crystallographic Data Centre

Related Article: Balaji Sundarraman, Ramesh Rengan, David Semeril|2022|Organometallics|41|1314|doi:10.1021/acs.organomet.2c00062


CCDC 1813179: Experimental Crystal Structure Determination;Sundarraman, Balaji;2022;Cambridge Crystallographic Data Centre


Gaia synthetic phot. cat. of white dwarfs;Gaia Collaboration;2024;Centre de Donnees Strasbourg (CDS)

VizieR online Data Catalogue associated with article published in journal Astronomy and Astrophysics with title ' Gaia Data Release 3: The Galaxy in your preferred colours. Synthetic photometry from Gaia low-resolution spectra.' (bibcode: 2023A&A...674A..33G)


Gaia DR3. 95 extrasolar planets

Gaia DR3. 95 extrasolar planets;Gaia Collaboration;2023;Centre de Donnees Strasbourg (CDS)

VizieR online Data Catalogue associated with article published in journal Astronomy and Astrophysics with title ' Gaia Data Release 3: A golden sample of astrophysical parameters.' (bibcode: 2023A&A...674A..39G)


Composite quasar spectra from Gaia DR3

Composite quasar spectra from Gaia DR3;Gaia Collaboration;2023;Centre de Donnees Strasbourg (CDS)

VizieR online Data Catalogue associated with article published in journal Astronomy and Astrophysics with title ' Gaia Data Release 3: The extragalactic content.' (bibcode: 2023A&A...674A..41G)


Gaia FPR. Analysis of QSO environment

Gaia FPR. Analysis of QSO environment;Gaia Collaboration;2024;Centre de Donnees Strasbourg (CDS)

VizieR online Data Catalogue associated with article published in journal Astronomy and Astrophysics with title ' Gaia Focused Product Release: A catalogue of sources around quasars to search for strongly lensed quasars.' (bibcode: 2024A&A...685A.130G)


Dormant 33 solar-masses black hole

Dormant 33 solar-masses black hole;Gaia Collaboration;2024;Centre de Donnees Strasbourg (CDS)

VizieR online Data Catalogue associated with article published in journal Astronomy and Astrophysics with title ' Discovery of a dormant 33 solar-masses black hole in pre-release Gaia astrometry.' (bibcode: 2024A&A...686L...2G)


Related Article: Halima Khadraoui, Chunchesh Malangi Gajendramurthy, Sara Figueirêdo de Alcântara Morais, Yann Cornaton, Hédi M’rabet, Philippe Bertani, Aïcha Arfaoui, Jean-Pierre Djukic|2024|Organometallics|43|3106|doi:10.1021/acs.organomet.4c00044

CCDC 2283430: Experimental Crystal Structure Determination;Khadraoui, Halima;2024;Cambridge Crystallographic Data Centre


CCDC 2283431: Experimental Crystal Structure Determination;Khadraoui, Halima;2024;Cambridge Crystallographic Data Centre


CCDC 2283432: Experimental Crystal Structure Determination;Khadraoui, Halima;2024;Cambridge Crystallographic Data Centre


CCDC 2283433: Experimental Crystal Structure Determination;Khadraoui, Halima;2024;Cambridge Crystallographic Data Centre

methyl 1-benzyl-5-oxo-4,5-dihydro-1H-pyrrole-3-carboxylate unknown solvate


Related Article: Lucas Petitpoisson, Anli Mahamoud, Valérie Mazan, Maryame Sy, Olivier Jeannin, Eva Tóth, Loïc J. Charbonnière, Mourad Elhabiri, Aline M. Nonat|2024|Inorg.Chem.|63|22829|doi:10.1021/acs.inorgchem.4c03691

CCDC 2209639: Experimental Crystal Structure Determination;Petitpoisson, Lucas;2024;Cambridge Crystallographic Data Centre


Related Article: Ivan V. Khariushin, Véronique Bulach, Jas S. Ward, Kari Rissanen, Svetlana E. Solovieva, Igor S. Antipin, Alexander S. Ovsyannikov, Sylvie Ferlay|2024|CrystEngComm|26|6789|doi:10.1039/D4CE00964A

CCDC 2384881: Experimental Crystal Structure Determination;Khariushin, Ivan V.;2024;Cambridge Crystallographic Data Centre


CCDC 2384882: Experimental Crystal Structure Determination;Khariushin, Ivan V.;2024;Cambridge Crystallographic Data Centre


Abstract: The experiments were conducted under hydrostatic loading at nominal rate of 1MPa/min. Berea and Boise are clayey sandstones. The detail for physical property of these two rock can be found in our paper with same title of this database.

Effective stress law for the permeability and pore volume change of clayey sandstones;Fanbao Meng;2024;PANGAEA


Data for: 3378064

Abstract: Kirsch et al. (2002; 2010) highlight the control of IS projects. For them there are complementarities between formal and informal control to evaluate IS projects. In this article, we show clearly that in IS projects the evaluation is a simultaneous mix of formal and informal control. This paper presents a management tool to estimate the project's budgetary and planning deviations and one other management tool to simulate the probabilities of deviation in uncertain environment (extraction and valuation of tasks in MS project). We test our cost based model on a projects' population. We then enrich the theorythrough the hybrid indicators introduction which combine informal and formal control. Our methodology is inductive and we generalize our results from the research and development of Information systems projects in computer industry (ISDP) to the (ISP) information system project (Baskerville et al., 2004)

Data for: 3378064;Wilfrid Azan;2019;Mendeley


Abstract: Table 2: Date of sampling/ Temperature and pH of the waters/ Conductivity and Alkalinity Table 3: Concentrations Cl, SO4, Na, Ca, Si, Mg, K Al, B, Fe in µmol/kg// Sr and Li in nmol/kg // Total dissolved solids in ppm Table 4: Lithium and Magnesium isotope composition in water

Data for: The response of Li and Mg isotopes to rain events in a highly-weathered catchment;David FRIES;2019;Mendeley

Earth and related environmental sciences


Dynamically tagged groups of metal-poor stars. I.;D. Shank;2022;Centre de Donnees Strasbourg (CDS)

VizieR online Data Catalogue associated with article published in journal Astrophysical Journal with title ' Dynamically tagged groups of metal-poor stars from the best and brightest survey.' (bibcode: 2022ApJ...926...26S)


Abstract: Abstract Background Acupressure therapy may be potentially beneficial in improving postoperative symptoms like postoperative nausea and vomiting (PONV), pain and sleep disorder and improving postoperative quality of recovery. The primary aim of this study is to investigate the efficacy of acupressure therapy on postoperative patient satisfaction and quality of recovery in hospitalized patients after surgical treatment. Methods/design This three-group, parallel, superiority, blinded, randomized controlled trial will test the hypothesis that a combination of PC6, LI4 and HT7 acupressure is superior to sham or no intervention for improving postoperative quality of recovery in hospitalized patients. A minimum of 150 patients will be randomly allocated to one of the three experimental groups: control (no visit), light touch (sham acupressure) or active acupressure therapy in a 1:1:1 ratio. Interventions will be performed three times a day for 2 days. Patient satisfaction, quality of recovery, PONV and pain will be measured during the 3 days following randomization. The study protocol was approved by the Stony Brook University Institutional Review Board on 21 March 2016. Written informed consent will be recorded from every consented patient. Discussion This study has the potential to improve the recovery of hospitalized patients by adding knowledge on the efficacy of acupressure therapy in this setting. A multipoint acupressure protocol will be compared to both a no intervention group and a light touch group, providing insight into different aspects of the placebo effect. Trial registration ClinicalTrial.gov, NCT02762435 . Registered on 14 April 2016.

Randomized trial of acupressure to improve patient satisfaction and quality of recovery in hospitalized patients: study protocol for a randomized controlled trial;Eric Noll;2017;Figshare