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Institution

Uppsala University

EducationUppsala, Sweden
About: Uppsala University is a education organization based out in Uppsala, Sweden. It is known for research contribution in the topics: Population & Insulin. The organization has 36485 authors who have published 107509 publications receiving 4220668 citations. The organization is also known as: Uppsala universitet & uu.se.
Topics: Population, Insulin, Thin film, Poison control, Gene


Papers
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Journal ArticleDOI
TL;DR: In this article, the conservative level set method for incompressible two-phase flow with surface tension is studied. But the authors focus on the conservation of mass and do not consider the effect of the finite element discretization.

1,143 citations

Journal ArticleDOI
Kurt Lejaeghere1, Gustav Bihlmayer2, Torbjörn Björkman3, Torbjörn Björkman4, Peter Blaha5, Stefan Blügel2, Volker Blum6, Damien Caliste7, Ivano E. Castelli8, Stewart J. Clark9, Andrea Dal Corso10, Stefano de Gironcoli10, Thierry Deutsch7, J. K. Dewhurst11, Igor Di Marco12, Claudia Draxl13, Claudia Draxl14, Marcin Dulak15, Olle Eriksson12, José A. Flores-Livas11, Kevin F. Garrity16, Luigi Genovese7, Paolo Giannozzi17, Matteo Giantomassi18, Stefan Goedecker19, Xavier Gonze18, Oscar Grånäs20, Oscar Grånäs12, E. K. U. Gross11, Andris Gulans13, Andris Gulans14, Francois Gygi21, D. R. Hamann22, P. J. Hasnip23, Natalie Holzwarth24, Diana Iusan12, Dominik B. Jochym25, F. Jollet, Daniel M. Jones26, Georg Kresse27, Klaus Koepernik28, Klaus Koepernik29, Emine Kucukbenli8, Emine Kucukbenli10, Yaroslav Kvashnin12, Inka L. M. Locht12, Inka L. M. Locht30, Sven Lubeck14, Martijn Marsman27, Nicola Marzari8, Ulrike Nitzsche28, Lars Nordström12, Taisuke Ozaki31, Lorenzo Paulatto32, Chris J. Pickard33, Ward Poelmans1, Matt Probert23, Keith Refson34, Keith Refson25, Manuel Richter29, Manuel Richter28, Gian-Marco Rignanese18, Santanu Saha19, Matthias Scheffler13, Matthias Scheffler35, Martin Schlipf21, Karlheinz Schwarz5, Sangeeta Sharma11, Francesca Tavazza16, Patrik Thunström5, Alexandre Tkatchenko36, Alexandre Tkatchenko13, Marc Torrent, David Vanderbilt22, Michiel van Setten18, Veronique Van Speybroeck1, John M. Wills37, Jonathan R. Yates26, Guo-Xu Zhang38, Stefaan Cottenier1 
25 Mar 2016-Science
TL;DR: A procedure to assess the precision of DFT methods was devised and used to demonstrate reproducibility among many of the most widely used DFT codes, demonstrating that the precisionof DFT implementations can be determined, even in the absence of one absolute reference code.
Abstract: The widespread popularity of density functional theory has given rise to an extensive range of dedicated codes for predicting molecular and crystalline properties. However, each code implements the formalism in a different way, raising questions about the reproducibility of such predictions. We report the results of a community-wide effort that compared 15 solid-state codes, using 40 different potentials or basis set types, to assess the quality of the Perdew-Burke-Ernzerhof equations of state for 71 elemental crystals. We conclude that predictions from recent codes and pseudopotentials agree very well, with pairwise differences that are comparable to those between different high-precision experiments. Older methods, however, have less precise agreement. Our benchmark provides a framework for users and developers to document the precision of new applications and methodological improvements.

1,141 citations

Journal ArticleDOI
Anubha Mahajan1, Daniel Taliun2, Matthias Thurner1, Neil R. Robertson1, Jason M. Torres1, N. William Rayner1, N. William Rayner3, Anthony Payne1, Valgerdur Steinthorsdottir4, Robert A. Scott5, Niels Grarup6, James P. Cook7, Ellen M. Schmidt2, Matthias Wuttke8, Chloé Sarnowski9, Reedik Mägi10, Jana Nano11, Christian Gieger, Stella Trompet12, Cécile Lecoeur13, Michael Preuss14, Bram P. Prins3, Xiuqing Guo15, Lawrence F. Bielak2, Jennifer E. Below16, Donald W. Bowden17, John C. Chambers, Young-Jin Kim, Maggie C.Y. Ng17, Lauren E. Petty16, Xueling Sim18, Weihua Zhang19, Weihua Zhang20, Amanda J. Bennett1, Jette Bork-Jensen6, Chad M. Brummett2, Mickaël Canouil13, Kai-Uwe Ec Kardt21, Krista Fischer10, Sharon L.R. Kardia2, Florian Kronenberg22, Kristi Läll10, Ching-Ti Liu9, Adam E. Locke23, Jian'an Luan5, Ioanna Ntalla24, Vibe Nylander1, Sebastian Schönherr22, Claudia Schurmann14, Loic Yengo13, Erwin P. Bottinger14, Ivan Brandslund25, Cramer Christensen, George Dedoussis26, Jose C. Florez, Ian Ford27, Oscar H. Franco11, Timothy M. Frayling28, Vilmantas Giedraitis29, Sophie Hackinger3, Andrew T. Hattersley28, Christian Herder30, M. Arfan Ikram11, Martin Ingelsson29, Marit E. Jørgensen31, Marit E. Jørgensen25, Torben Jørgensen32, Torben Jørgensen6, Jennifer Kriebel, Johanna Kuusisto33, Symen Ligthart11, Cecilia M. Lindgren1, Cecilia M. Lindgren34, Allan Linneberg6, Allan Linneberg35, Valeriya Lyssenko36, Valeriya Lyssenko37, Vasiliki Mamakou26, Thomas Meitinger38, Karen L. Mohlke39, Andrew D. Morris40, Andrew D. Morris41, Girish N. Nadkarni14, James S. Pankow42, Annette Peters, Naveed Sattar43, Alena Stančáková33, Konstantin Strauch44, Kent D. Taylor15, Barbara Thorand, Gudmar Thorleifsson4, Unnur Thorsteinsdottir45, Unnur Thorsteinsdottir4, Jaakko Tuomilehto, Daniel R. Witte46, Josée Dupuis9, Patricia A. Peyser2, Eleftheria Zeggini3, Ruth J. F. Loos14, Philippe Froguel20, Philippe Froguel13, Erik Ingelsson47, Erik Ingelsson48, Lars Lind29, Leif Groop36, Leif Groop49, Markku Laakso33, Francis S. Collins50, J. Wouter Jukema12, Colin N. A. Palmer51, Harald Grallert, Andres Metspalu10, Abbas Dehghan11, Abbas Dehghan20, Anna Köttgen8, Gonçalo R. Abecasis2, James B. Meigs52, Jerome I. Rotter15, Jonathan Marchini1, Oluf Pedersen6, Torben Hansen6, Torben Hansen25, Claudia Langenberg5, Nicholas J. Wareham5, Kari Stefansson4, Kari Stefansson45, Anna L. Gloyn1, Andrew P. Morris10, Andrew P. Morris1, Andrew P. Morris7, Michael Boehnke2, Mark I. McCarthy1 
TL;DR: Combining 32 genome-wide association studies with high-density imputation provides a comprehensive view of the genetic contribution to type 2 diabetes in individuals of European ancestry with respect to locus discovery, causal-variant resolution, and mechanistic insight.
Abstract: We expanded GWAS discovery for type 2 diabetes (T2D) by combining data from 898,130 European-descent individuals (9% cases), after imputation to high-density reference panels. With these data, we (i) extend the inventory of T2D-risk variants (243 loci, 135 newly implicated in T2D predisposition, comprising 403 distinct association signals); (ii) enrich discovery of lower-frequency risk alleles (80 index variants with minor allele frequency 2); (iii) substantially improve fine-mapping of causal variants (at 51 signals, one variant accounted for >80% posterior probability of association (PPA)); (iv) extend fine-mapping through integration of tissue-specific epigenomic information (islet regulatory annotations extend the number of variants with PPA >80% to 73); (v) highlight validated therapeutic targets (18 genes with associations attributable to coding variants); and (vi) demonstrate enhanced potential for clinical translation (genome-wide chip heritability explains 18% of T2D risk; individuals in the extremes of a T2D polygenic risk score differ more than ninefold in prevalence).

1,136 citations

Journal ArticleDOI
01 Oct 2015-Europace
TL;DR: The current manuscript is an update of the original Practical Guide, published in June 2013, and listed 15 topics of concrete clinical scenarios for which practical answers were formulated, based on available evidence.
Abstract: The current manuscript is an update of the original Practical Guide, published in June 2013[Heidbuchel H, Verhamme P, Alings M, Antz M, Hacke W, Oldgren J, et al. European Heart Rhythm Association Practical Guide on the use of new oral anticoagulants in patients with non-valvular atrial fibrillation. Europace 2013;15:625-51; Heidbuchel H, Verhamme P, Alings M, Antz M, Hacke W, Oldgren J, et al. EHRA practical guide on the use of new oral anticoagulants in patients with non-valvular atrial fibrillation: executive summary. Eur Heart J 2013;34:2094-106]. Non-vitamin K antagonist oral anticoagulants (NOACs) are an alternative for vitamin K antagonists (VKAs) to prevent stroke in patients with non-valvular atrial fibrillation (AF). Both physicians and patients have to learn how to use these drugs effectively and safely in clinical practice. Many unresolved questions on how to optimally use these drugs in specific clinical situations remain. The European Heart Rhythm Association set out to coordinate a unified way of informing physicians on the use of the different NOACs. A writing group defined what needs to be considered as 'non-valvular AF' and listed 15 topics of concrete clinical scenarios for which practical answers were formulated, based on available evidence. The 15 topics are (i) practical start-up and follow-up scheme for patients on NOACs; (ii) how to measure the anticoagulant effect of NOACs; (iii) drug-drug interactions and pharmacokinetics of NOACs; (iv) switching between anticoagulant regimens; (v) ensuring adherence of NOAC intake; (vi) how to deal with dosing errors; (vii) patients with chronic kidney disease; (viii) what to do if there is a (suspected) overdose without bleeding, or a clotting test is indicating a risk of bleeding?; (xi) management of bleeding complications; (x) patients undergoing a planned surgical intervention or ablation; (xi) patients undergoing an urgent surgical intervention; (xii) patients with AF and coronary artery disease; (xiii) cardioversion in a NOAC-treated patient; (xiv) patients presenting with acute stroke while on NOACs; and (xv) NOACs vs. VKAs in AF patients with a malignancy. Additional information and downloads of the text and anticoagulation cards in >16 languages can be found on an European Heart Rhythm Association web site (www.NOACforAF.eu).

1,123 citations

Journal ArticleDOI
TL;DR: In this paper, the main features of the characteristic impedance spectra of dye-sensitized solar cells are described in a wide range of potential conditions: from open to short circuit.

1,123 citations


Authors

Showing all 36854 results

NameH-indexPapersCitations
Zhong Lin Wang2452529259003
Lewis C. Cantley196748169037
Darien Wood1602174136596
Kaj Blennow1601845116237
Christopher J. O'Donnell159869126278
Tomas Hökfelt158103395979
Peter G. Schultz15689389716
Frederik Barkhof1541449104982
Deepak L. Bhatt1491973114652
Svante Pääbo14740784489
Jan-Åke Gustafsson147105898804
Hans-Olov Adami14590883473
Hermann Kolanoski145127996152
Kjell Fuxe142147989846
Jan Conrad14182671445
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023240
2022643
20216,079
20205,811
20195,393
20185,067