Technische Universität Braunschweig
UniversityBraunschweig, Lower Saxony, Germany
Research output, citation impact, and the most-cited recent papers from Technische Universität Braunschweig (Germany). Aggregated across the NobleBlocks index of 300M+ scholarly works.
Top-cited papers from Technische Universität Braunschweig
AUTORES: Daniel J Klionsky1745,1749*, Kotb Abdelmohsen840, Akihisa Abe1237, Md Joynal Abedin1762, Hagai Abeliovich425, \nAbraham Acevedo Arozena789, Hiroaki Adachi1800, Christopher M Adams1669, Peter D Adams57, Khosrow Adeli1981, \nPeter J Adhihetty1625, Sharon G Adler700, Galila Agam67, Rajesh Agarwal1587, Manish K Aghi1537, Maria Agnello1826, \nPatrizia Agostinis664, Patricia V Aguilar1960, Julio Aguirre-Ghiso784,786, Edoardo M Airoldi89,422, Slimane Ait-Si-Ali1376, \nTakahiko Akematsu2010, Emmanuel T Akporiaye1097, Mohamed Al-Rubeai1394, Guillermo M Albaiceta1294, \nChris Albanese363, Diego Albani561, Matthew L Albert517, Jesus Aldudo128, Hana Alg€ul1164, Mehrdad Alirezaei1198, \nIraide Alloza642,888, Alexandru Almasan206, Maylin Almonte-Beceril524, Emad S Alnemri1212, Covadonga Alonso544, \nNihal Altan-Bonnet848, Dario C Altieri1205, Silvia Alvarez1497, Lydia Alvarez-Erviti1395, Sandro Alves107, \nGiuseppina Amadoro860, Atsuo Amano930, Consuelo Amantini1554, Santiago Ambrosio1458, Ivano Amelio756, \nAmal O Amer918, Mohamed Amessou2089, Angelika Amon726, Zhenyi An1538, Frank A Anania291, Stig U Andersen6, \nUsha P Andley2079, Catherine K Andreadi1690, Nathalie Andrieu-Abadie502, Alberto Anel2027, David K Ann58, \nShailendra Anoopkumar-Dukie388, Manuela Antonioli832,858, Hiroshi Aoki1791, Nadezda Apostolova2007, \nSaveria Aquila1500, Katia Aquilano1876, Koichi Araki292, Eli Arama2098, Agustin Aranda456, Jun Araya591, \nAlexandre Arcaro1472, Esperanza Arias26, Hirokazu Arimoto1225, Aileen R Ariosa1749, Jane L Armstrong1930, \nThierry Arnould1773, Ivica Arsov2120, Katsuhiko Asanuma675, Valerie Askanas1924, Eric Asselin1867, Ryuichiro Atarashi794, \nSally S Atherton369, Julie D Atkin713, Laura D Attardi1131, Patrick Auberger1787, Georg Auburger379, Laure Aurelian1727, \nRiccardo Autelli1992, Laura Avagliano1029,1755, Maria Laura Avantaggiati364, Limor Avrahami1166, Suresh Awale1986, \nNeelam Azad404, Tiziana Bachetti568, Jonathan M Backer28, Dong-Hun Bae1933, Jae-sung Bae677, Ok-Nam Bae409, \nSoo Han Bae2117, Eric H Baehrecke1729, Seung-Hoon Baek17, Stephen Baghdiguian1368, \nAgnieszka Bagniewska-Zadworna2, Hua Bai90, Jie Bai667, Xue-Yuan Bai1133, Yannick Bailly884, \nKithiganahalli Narayanaswamy Balaji473, Walter Balduini2002, Andrea Ballabio316, Rena Balzan1711, Rajkumar Banerjee239, \nG abor B anhegyi1052, Haijun Bao2109, Benoit Barbeau1363, Maria D Barrachina2007, Esther Barreiro467, Bonnie Bartel997, \nAlberto Bartolom e222, Diane C Bassham550, Maria Teresa Bassi1046, Robert C Bast Jr1273, Alakananda Basu1798, \nMaria Teresa Batista1578, Henri Batoko1336, Maurizio Battino970, Kyle Bauckman2085, Bradley L Baumgarner1909, \nK Ulrich Bayer1594, Rupert Beale1553, Jean-Fran¸cois Beaulieu1360, George R. Beck Jr48,294, Christoph Becker336, \nJ David Beckham1595, Pierre-Andr e B edard749, Patrick J Bednarski301, Thomas J Begley1135, Christian Behl1419, \nChristian Behrends757, Georg MN Behrens406, Kevin E Behrns1627, Eloy Bejarano26, Amine Belaid490, \nFrancesca Belleudi1041, Giovanni B enard497, Guy Berchem706, Daniele Bergamaschi983, Matteo Bergami1401, \nBen Berkhout1441, Laura Berliocchi714, Am elie Bernard1749, Monique Bernard1354, Francesca Bernassola1880, \nAnne Bertolotti791, Amanda S Bess272, S ebastien Besteiro1351, Saverio Bettuzzi1828, Savita Bhalla913, \nShalmoli Bhattacharyya973, Sujit K Bhutia838, Caroline Biagosch1159, Michele Wolfe Bianchi520,1378,1381, \nMartine Biard-Piechaczyk210, Viktor Billes298, Claudia Bincoletto1314, Baris Bingol350, Sara W Bird1128, Marc Bitoun1112, \nIvana Bjedov1258, Craig Blackstone843, Lionel Blanc1183, Guillermo A Blanco1496, Heidi Kiil Blomhoff1812, \nEmilio Boada-Romero1297, Stefan B€ockler1464, Marianne Boes1423, Kathleen Boesze-Battaglia1835, Lawrence H Boise286,287, \nAlessandra Bolino2063, Andrea Boman693, Paolo Bonaldo1823, Matteo Bordi897, J€urgen Bosch608, Luis M Botana1308, \nJoelle Botti1375, German Bou1405, Marina Bouch e1038, Marion Bouchecareilh1331, Marie-Jos ee Boucher1901, \nMichael E Boulton481, Sebastien G Bouret1926, Patricia Boya133, Micha€el Boyer-Guittaut1345, Peter V Bozhkov1141, \nNathan Brady374, Vania MM Braga469, Claudio Brancolini1997, Gerhard H Braus353, Jos e M Bravo-San Pedro299,393,508,1374, \nLisa A Brennan322, Emery H Bresnick2022, Patrick Brest490, Dave Bridges1939, Marie-Agn es Bringer124, Marisa Brini1822, \nGlauber C Brito1311, Bertha Brodin631, Paul S Brookes1872, Eric J Brown352, Karen Brown1690, Hal E Broxmeyer480, \nAlain Bruhat486,1339, Patricia Chakur Brum1893, John H Brumell446, Nicola Brunetti-Pierri315,1171, \nRobert J Bryson-Richardson781, Shilpa Buch1777, Alastair M Buchan1819, Hikmet Budak1022, Dmitry V Bulavin118,505,1789, \nScott J Bultman1792, Geert Bultynck665, Vladimir Bumbasirevic1470, Yan Burelle1356, Robert E Burke216,217, \nMargit Burmeister1750, Peter B€utikofer1473, Laura Caberlotto1987, Ken Cadwell896, Monika Cahova112, Dongsheng Cai24, \nJingjing Cai2099, Qian Cai1018, Sara Calatayud2007, Nadine Camougrand1343, Michelangelo Campanella1700, \nGrant R Campbell1525, Matthew Campbell1249, Silvia Campello556,1876, Robin Candau1769, Isabella Caniggia1983, \nLavinia Cantoni560, Lizhi Cao116, Allan B Caplan1656, Michele Caraglia1051, Claudio Cardinali1043, Sandra Morais Cardoso1579, Jennifer S Carew208, Laura A Carleton874, Cathleen R Carlin101, Silvia Carloni2002, \nSven R Carlsson1267, Didac Carmona-Gutierrez1643, Leticia AM Carneiro312, Oliana Carnevali971, Serena Carra1318, \nAlice Carrier120, Bernadette Carroll900, Caty Casas1324, Josefina Casas1116, Giuliana Cassinelli324, Perrine Castets1462, \nSusana Castro-Obregon214, Gabriella Cavallini1841, Isabella Ceccherini568, Francesco Cecconi253,555,1884, \nArthur I Cederbaum459, Valent ın Ce~na199,1281, Simone Cenci1323,2064, Claudia Cerella444, Davide Cervia1996, \nSilvia Cetrullo1478, Hassan Chaachouay2028, Han-Jung Chae187, Andrei S Chagin634, Chee-Yin Chai626,628, \nGopal Chakrabarti1502, Georgios Chamilos1601, Edmond YW Chan1142, Matthew TV Chan181, Dhyan Chandra1003, \nPallavi Chandra548, Chih-Peng Chang818, Raymond Chuen-Chung Chang1653, Ta Yuan Chang345, John C Chatham1434, \nSaurabh Chatterjee1910, Santosh Chauhan527, Yongsheng Che62, Michael E Cheetham1263, Rajkumar Cheluvappa1783, \nChun-Jung Chen1153, Gang Chen598,1676, Guang-Chao Chen9, Guoqiang Chen1078, Hongzhuan Chen1077, Jeff W Chen1514, \nJian-Kang Chen370,371, Min Chen249, Mingzhou Chen2104, Peiwen Chen1823, Qi Chen1674, Quan Chen172, \nShang-Der Chen138, Si Chen325, Steve S-L Chen10, Wei Chen2125, Wei-Jung Chen829, Wen Qiang Chen979, Wenli Chen1113, \nXiangmei Chen1133, Yau-Hung Chen1157, Ye-Guang Chen1250, Yin Chen1447, Yingyu Chen953,955, Yongshun Chen2135, \nYu-Jen Chen712, Yue-Qin Chen1145, Yujie Chen1208, Zhen Chen339, Zhong Chen2123, Alan Cheng1702, \nChristopher HK Cheng184, Hua Cheng1728, Heesun Cheong814, Sara Cherry1836, Jason Chesney1703, \nChun Hei Antonio Cheung817, Eric Chevet1359, Hsiang Cheng Chi140, Sung-Gil Chi656, Fulvio Chiacchiera308, \nHui-Ling Chiang958, Roberto Chiarelli1826, Mario Chiariello235,567,577, Marcello Chieppa835, Lih-Shen Chin290, \nMario Chiong1285, Gigi NC Chiu878, Dong-Hyung Cho676, Ssang-Goo Cho650, William C Cho982, Yong-Yeon Cho105, \nYoung-Seok Cho1064, Augustine MK Choi2095, Eui-Ju Choi656, Eun-Kyoung Choi387,400,685, Jayoung Choi1563, \nMary E Choi2093, Seung-Il Choi2116, Tsui-Fen Chou412, Salem Chouaib395, Divaker Choubey1574, Vinay Choubey1936, \nKuan-Chih Chow822, Kamal Chowdhury730, Charleen T Chu1856, Tsung-Hsien Chuang827, Taehoon Chun657, \nHyewon Chung652, Taijoon Chung978, Yuen-Li Chung1194, Yong-Joon Chwae18, Valentina Cianfanelli254, \nRoberto Ciarcia1775, Iwona A Ciechomska886, Maria Rosa Ciriolo1876, Mara Cirone1042, Sofie Claerhout1694, \nMichael J Clague1698, Joan Cl aria1457, Peter GH Clarke1687, Robert Clarke361, Emilio Clementi1045,1398, C edric Cleyrat1781, \nMiriam Cnop1366, Eliana M Coccia574, Tiziana Cocco1459, Patrice Codogno1375, J€orn Coers271, Ezra EW Cohen1533, \nDavid Colecchia235,567,577, Luisa Coletto25, N uria S Coll123, Emma Colucci-Guyon516, Sergio Comincini1829, \nMaria Condello578, Katherine L Cook2073, Graham H Coombs1929, Cynthia D Cooper2076, J Mark Cooper1395, \nIsabelle Coppens601, Maria Tiziana Corasaniti1387, Marco Corazzari485,1884, Ramon Corbalan1566, \nElisabeth Corcelle-Termeau251, Mario D Cordero1899, Cristina Corral-Ramos1289, Olga Corti507,1109, Andrea Cossarizza1767, \nPaola Costelli1993, Safia Costes1518, Susan L Cotman721, Ana Coto-Montes946, Sandra Cottet566,1688, Eduardo Couve1301, \nLori R Covey1015, L Ashley Cowart762, Jeffery S Cox1536, Fraser P Coxon1427, Carolyn B Coyne1846, Mark S Cragg1919, \nRolf J Craven1679, Tiziana Crepaldi1995, Jose L Crespo1300, Alfredo Criollo1285, Valeria Crippa558, Maria Teresa Cruz1576, \nAna Maria Cuervo26, Jose M Cuezva1277, Taixing Cui1907, Pedro R Cutillas987, Mark J Czaja27, Maria F Czyzyk-Krzeska1572, \nRuben K Dagda2068, Uta Dahmen1404, Chunsun Dai800, Wenjie Dai1187, Yun Dai2059, Kevin N Dalby1940, \nLuisa Dalla Valle1822, Guillaume Dalmasso1340, Marcello D’Amelio557, Markus Damme188, Arlette Darfeuille-Michaud1340, \nCatherine Dargemont950, Victor M Darley-Usmar1433, Srinivasan Dasarathy205, Biplab Dasgupta202, Srikanta Dash1254, \nCrispin R Dass242, Hazel Marie Davey8, Lester M Davids1560, David D avila227, Roger J Davis1731, Ted M Dawson604, \nValina L Dawson606, Paula Daza1898, Jackie de Belleroche470, Paul de Figueiredo1180,1182, \nRegina Celia Bressan Queiroz de Figueiredo135, Jos e de la Fuente1023, Luisa De Martino1775, \nAntonella De Matteis1171, Guido RY De Meyer1443, Angelo De Milito631, Mauro De Santi2002,
We present a measure of entanglement that can be computed effectively for any mixed state of an arbitrary bipartite system. We show that it does not increase under local manipulations of the system, and use it to obtain a bound on the teleportation capacity and on the distillable entanglement of mixed states.
Examines how the voter makes up their mind in a presidential election. Also looks at the social and ideological differences between republicans and democrats during the early 1900's and who participates in elections
In the Anthropocene, in which we now live, climate change is impacting most life on Earth. Microorganisms support the existence of all higher trophic life forms. To understand how humans and other life forms on Earth (including those we are yet to discover) can withstand anthropogenic climate change, it is vital to incorporate knowledge of the microbial ‘unseen majority’. We must learn not just how microorganisms affect climate change (including production and consumption of greenhouse gases) but also how they will be affected by climate change and other human activities. This Consensus Statement documents the central role and global importance of microorganisms in climate change biology. It also puts humanity on notice that the impact of climate change will depend heavily on responses of microorganisms, which are essential for achieving an environmentally sustainable future. The microbial majority with which we share Earth often goes unnoticed despite underlying major biogeochemical cycles and food webs, thereby taking a key role in climate change. This Consensus Statement highlights the importance of climate change microbiology and issues a call to action for all microbiologists.
BACKGROUND: Taxonomy is the biological discipline that identifies, describes, classifies and names extant and extinct species and other taxa. Nowadays, species taxonomy is confronted with the challenge to fully incorporate new theory, methods and data from disciplines that study the origin, limits and evolution of species. RESULTS: Integrative taxonomy has been proposed as a framework to bring together these conceptual and methodological developments. Here we review perspectives for an integrative taxonomy that directly bear on what species are, how they can be discovered, and how much diversity is on Earth. CONCLUSIONS: We conclude that taxonomy needs to be pluralistic to improve species discovery and description, and to develop novel protocols to produce the much-needed inventory of life in a reasonable time. To cope with the large number of candidate species revealed by molecular studies of eukaryotes, we propose a classification scheme for those units that will facilitate the subsequent assembly of data sets for the formal description of new species under the Linnaean system, and will ultimately integrate the activities of taxonomists and molecular biologists.
The determination of upper bounds on execution times, commonly called worst-case execution times (WCETs), is a necessary step in the development and validation process for hard real-time systems. This problem is hard if the underlying processor architecture has components, such as caches, pipelines, branch prediction, and other speculative components. This article describes different approaches to this problem and surveys several commercially available tools 1 and research prototypes.
This study examined work-related outcomes of recovery during leisure time. A total of 147 employees completed a questionnaire and a daily survey over a period of 5 consecutive work days. Multilevel analyses showed that day-level recovery was positively related to day-level work engagement and day-level proactive behavior (personal initiative, pursuit of learning) during the subsequent work day. The data suggest considerable daily fluctuations in behavior and attitudes at work, with evidence that these are related to prior experience and opportunity for recovery in the nonwork domain.
Latent profile analysis (LPA) is a categorical latent variable approach that focuses on identifying latent subpopulations within a population based on a certain set of variables. LPA thus assumes that people can be typed with varying degrees of probabilities into categories that have different configural profiles of personal and/or environmental attributes. Within this article, we (a) review the existing applications of LPA within past vocational behavior research; (b) illustrate best practice procedures in a non-technical way of how to use LPA methodology, with an illustrative example of identifying different latent profiles of heavy work investment (i.e., working compulsively, working excessively, and work engagement); and (c) outline future research possibilities in vocational behavior research. By reviewing 46 studies stemming from central journals of the field, we identified seven distinct topics that have already been investigated by LPA (e.g., job and organizational attitudes and behaviors, work motivation, career-related attitudes and orientations, vocational interests). Together with showing descriptive statistics about how LPA has been conducted in past vocational behavior research, we illustrate and derive best-practice recommendations for future LPA research. The review and “how to” guide can be helpful for all researchers interested in conducting LPA studies.
ADVERTISEMENT RETURN TO ISSUEPREVPerspectiveNEXTOrganometallic Anticancer CompoundsGilles Gasser*†§, Ingo Ott*‡, and Nils Metzler-Nolte*§View Author Information† Institute of Inorganic Chemistry, University of Zurich, Winterthurerstrasse 190, CH-8057 Zurich, Switzerland‡ Institute of Pharmaceutical Chemistry, Technische Universität Braunschweig, Beethovenstrasse 55, 38106 Braunschweig, Germany§ Chair of Inorganic Chemistry I, Bioinorganic Chemistry, Faculty of Chemistry and Biochemistry, Ruhr University Bochum, Universitätsstrasse 150, 44801 Bochum, Germany*To whom correspondence should be addressed. For G.G.: phone, +41(0)44 635-4611; fax, +41(0)44 635-6803; e-mail, [email protected]; Web page, www.gassergroup.com. For I.O.: phone, +49 (0)531-391 2743; fax, +49 (0)531-391 8456; e-mail, [email protected]; Web page, www.pharmchem.tu-bs.de/forschung/ott/. For N.M.-N.: phone, +49 (0)234-32 28152; fax, +49 (0)234-32 14378; e-mail, [email protected]; Web page, www.chemie.rub.de/ac1.Cite this: J. Med. Chem. 2011, 54, 1, 3–25Publication Date (Web):November 15, 2010Publication History Received8 January 2010Published online15 November 2010Published inissue 13 January 2011https://doi.org/10.1021/jm100020wCopyright © 2010 American Chemical SocietyRIGHTS & PERMISSIONSACS AuthorChoiceArticle Views34024Altmetric-Citations1313LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (3 MB) Get e-AlertscloseSUBJECTS:Genetics,Ligands,Metals,Reaction products,Sandwich compounds Get e-Alerts
A novel method for the adaptation of target gene codon usage to most sequenced prokaryotes and selected eukaryotic gene expression hosts was developed to improve heterologous protein production. In contrast to existing tools, JCat (Java Codon Adaptation Tool) does not require the manual definition of highly expressed genes and is, therefore, a very rapid and easy method. Further options of JCat for codon adaptation include the avoidance of unwanted cleavage sites for restriction enzymes and Rho-independent transcription terminators. The output of JCat is both graphically and as Codon Adaptation Index (CAI) values given for the pasted sequence and the newly adapted sequence. Additionally, a list of genes in FASTA-format can be uploaded to calculate CAI values. In one example, all genes of the genome of Caenorhabditis elegans were adapted to Escherichia coli codon usage and further optimized to avoid commonly used restriction sites. In a second example, the Pseudomonas aeruginosa exbD gene codon usage was adapted to E.coli codon usage with parallel avoidance of the same restriction sites. For both, the degree of introduced changes was documented and evaluated. JCat is integrated into the PRODORIC database that hosts all required information on the various organisms to fulfill the requested calculations. JCat is freely accessible at http://www.prodoric.de/JCat.
Listeria monocytogenes is a food-borne pathogen with a high mortality rate that has also emerged as a paradigm for intracellular parasitism. We present and compare the genome sequences of L. monocytogenes (2,944,528 base pairs) and a nonpathogenic species, L. innocua (3,011,209 base pairs). We found a large number of predicted genes encoding surface and secreted proteins, transporters, and transcriptional regulators, consistent with the ability of both species to adapt to diverse environments. The presence of 270 L. monocytogenes and 149 L. innocua strain-specific genes (clustered in 100 and 63 islets, respectively) suggests that virulence in Listeria results from multiple gene acquisition and deletion events.
Abstract. The accurate measurement of the magnetic field along the orbits of the four Cluster spacecraft is a primary objective of the mission. The magnetic field is a key constituent of the plasma in and around the magnetosphere, and it plays an active role in all physical processes that define the structure and dynamics of magnetospheric phenomena on all scales. With the four-point measurements on Cluster, it has become possible to study the three-dimensional aspects of space plasma phenomena on scales commeasurable with the size of the spacecraft constellation, and to distinguish temporal and spatial dependences of small-scale processes. We present an overview of the instrumentation used to measure the magnetic field on the four Cluster spacecraft and an overview the performance of the operational modes used in flight. We also report on the results of the preliminary in-orbit calibration of the magnetometers; these results show that all components of the magnetic field are measured with an accuracy approaching 0.1 nT. Further data analysis is expected to bring an even more accurate determination of the calibration parameters. Several examples of the capabilities of the investigation are presented from the commissioning phase of the mission, and from the different regions visited by the spacecraft to date: the tail current sheet, the dusk side magnetopause and magnetosheath, the bow shock and the cusp. We also describe the data processing flow and the implementation of data distribution to other Cluster investigations and to the scientific community in general.Key words. Interplanetary physics (instruments and techniques) – magnetospheric physics (magnetospheric configuration and dynamics) – space plasma physics (shock waves)
During the last few years, transition metal oxides (TMO) such as molybdenum tri-oxide (MoO(3) ), vanadium pent-oxide (V(2) O(5) ) or tungsten tri-oxide (WO(3) ) have been extensively studied because of their exceptional electronic properties for charge injection and extraction in organic electronic devices. These unique properties have led to the performance enhancement of several types of devices and to a variety of novel applications. TMOs have been used to realize efficient and long-term stable p-type doping of wide band gap organic materials, charge-generation junctions for stacked organic light emitting diodes (OLED), sputtering buffer layers for semi-transparent devices, and organic photovoltaic (OPV) cells with improved charge extraction, enhanced power conversion efficiency and substantially improved long term stability. Energetics in general play a key role in advancing device structure and performance in organic electronics; however, the literature provides a very inconsistent picture of the electronic structure of TMOs and the resulting interpretation of their role as functional constituents in organic electronics. With this review we intend to clarify some of the existing misconceptions. An overview of TMO-based device architectures ranging from transparent OLEDs to tandem OPV cells is also given. Various TMO film deposition methods are reviewed, addressing vacuum evaporation and recent approaches for solution-based processing. The specific properties of the resulting materials and their role as functional layers in organic devices are discussed.
The success of the Magnetospheric Multiscale mission depends on the accurate measurement of the magnetic field on all four spacecraft. To ensure this success, two independently designed and built fluxgate magnetometers were developed, avoiding single-point failures. The magnetometers were dubbed the digital
The effective use of ring strain has been applied to considerable advantage for the construction of complex systems. The focus here is directed towards cyclopropanes as building blocks for organic synthesis. Although thermodynamics should take the side of synthetic chemists, only a specific substitution pattern at the cyclopropane ring allows for particularly mild, efficient, and selective transformations. The required decrease in the activation barrier is achieved by the combined effects of vicinal electron-donating and electron-accepting moieties. This Review highlights the appropriate tools for successfully employing donor-acceptor cyclopropanes in ring-opening reactions, cycloadditions, and rearrangements.
ADVERTISEMENT RETURN TO ISSUEArticleNEXTLooking for Stable Carbenes: The Difficulty in Starting AnewAnthony J. ArduengoView Author Information Institut für Anorganische und Analytische Chemie, der Technischen Universität Carolo-Wilhelmina, D-38106 Braunschweig, Germany Cite this: Acc. Chem. Res. 1999, 32, 11, 913–921Publication Date (Web):August 21, 1999Publication History Received10 May 1999Published online21 August 1999Published inissue 1 November 1999https://pubs.acs.org/doi/10.1021/ar980126phttps://doi.org/10.1021/ar980126presearch-articleACS PublicationsCopyright © 1999 American Chemical SocietyRequest reuse permissionsArticle Views7133Altmetric-Citations1082LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose SUBJECTS:Carbene compounds,Electron density,Isolation,Nitrogen,Substituents Get e-Alerts
In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2017 and 2018. The image dataset is diverse and contains primary and secondary tumors with varied sizes and appearances with various lesion-to-background levels (hyper-/hypo-dense), created in collaboration with seven hospitals and research institutions. Seventy-five submitted liver and liver tumor segmentation algorithms were trained on a set of 131 computed tomography (CT) volumes and were tested on 70 unseen test images acquired from different patients. We found that not a single algorithm performed best for both liver and liver tumors in the three events. The best liver segmentation algorithm achieved a Dice score of 0.963, whereas, for tumor segmentation, the best algorithms achieved Dices scores of 0.674 (ISBI 2017), 0.702 (MICCAI 2017), and 0.739 (MICCAI 2018). Retrospectively, we performed additional analysis on liver tumor detection and revealed that not all top-performing segmentation algorithms worked well for tumor detection. The best liver tumor detection method achieved a lesion-wise recall of 0.458 (ISBI 2017), 0.515 (MICCAI 2017), and 0.554 (MICCAI 2018), indicating the need for further research. LiTS remains an active benchmark and resource for research, e.g., contributing the liver-related segmentation tasks in http://medicaldecathlon.com/. In addition, both data and online evaluation are accessible via https://competitions.codalab.org/competitions/17094.
The term model-driven engineering (MDE) is typically used to describe software development approaches in which abstract models of software systems are created and systematically transformed to concrete implementations. In this paper we give an overview of current research in MDE and discuss some of the major challenges that must be tackled in order to realize the MDE vision of software development. We argue that full realizations of the MDE vision may not be possible in the near to medium-term primarily because of the wicked problems involved. On the other hand, attempting to realize the vision will provide insights that can be used to significantly reduce the gap between evolving software complexity and the technologies used to manage complexity.
TRANSFAC is a database about eukaryotic transcription regulating DNA sequence elements and the transcription factors binding to and acting through them. This report summarizes the present status of this database and accompanying retrieval tools.
CV Cardiovascular CYP Cytochrome P (CYP) Unfractionated heparin ULN Upper limit of normal VENTURE-AF Active-controlled multi-center study with blind-adjudication designed to evaluate the safety of uninterrupted Rivaroxaban and uninterrupted vitamin K antagonists in subjects undergoing catheter ablation for non-valvular Atrial Fibrillation VHD Valvular heart disease VKA Vitamin K antagonist VTE Venous thromboembolic event WOEST What is the Optimal antiplatelet and anticoagulant therapy in patients with oral anticoagulation and coronary stenting X-VeRT Explore the efficacy and safety of once daily oral rivaroxaban for the prevention of cardiovascular events in patients with non-valvular atrial fibrillation scheduled for cardioversion a SmPC: 110 mg BID if age > _80 years, concomitant verapamil (both based on pharmacokinetics/pharmacodynamics analyses; not studied in this setting). b Not specifically studied, follow-up data available up to 12 months in phase III trial. c SmPc: 20 mg QD in patients at high risk of recurrence. 2021 EHRA Practical Guide on the use of NOACs AF, atrial fibrillation; CrCl, creatinine clearance; INR, international normalized ratio; NOAC, non-vitamin K antagonist oral anticoagulant; NSAID, non-steroidal anti-inflammatory drug; TIA, transient ischaemic attack; VKA, vitamin K antagonist. For frequency of visits: see Figure 3.