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Institution

Lyon College

EducationBatesville, Arkansas, United States
About: Lyon College is a education organization based out in Batesville, Arkansas, United States. It is known for research contribution in the topics: Population & Galaxy. The organization has 4281 authors who have published 4136 publications receiving 108460 citations.


Papers
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Journal ArticleDOI
S. Agostinelli1, John Allison2, K. Amako3, J. Apostolakis4, Henrique Araujo5, P. Arce4, Makoto Asai6, D. Axen4, S. Banerjee7, G. Barrand, F. Behner4, Lorenzo Bellagamba8, J. Boudreau9, L. Broglia10, A. Brunengo8, H. Burkhardt4, Stephane Chauvie, J. Chuma11, R. Chytracek4, Gene Cooperman12, G. Cosmo4, P. V. Degtyarenko13, Andrea Dell'Acqua4, G. Depaola14, D. Dietrich15, R. Enami, A. Feliciello, C. Ferguson16, H. Fesefeldt4, Gunter Folger4, Franca Foppiano, Alessandra Forti2, S. Garelli, S. Gianì4, R. Giannitrapani17, D. Gibin4, J. J. Gomez Y Cadenas4, I. González4, G. Gracia Abril4, G. Greeniaus18, Walter Greiner15, Vladimir Grichine, A. Grossheim4, Susanna Guatelli, P. Gumplinger11, R. Hamatsu19, K. Hashimoto, H. Hasui, A. Heikkinen20, A. S. Howard5, Vladimir Ivanchenko4, A. Johnson6, F.W. Jones11, J. Kallenbach, Naoko Kanaya4, M. Kawabata, Y. Kawabata, M. Kawaguti, S.R. Kelner21, Paul R. C. Kent22, A. Kimura23, T. Kodama24, R. P. Kokoulin21, M. Kossov13, Hisaya Kurashige25, E. Lamanna26, Tapio Lampén20, V. Lara4, Veronique Lefebure4, F. Lei16, M. Liendl4, W. S. Lockman, Francesco Longo27, S. Magni, M. Maire, E. Medernach4, K. Minamimoto24, P. Mora de Freitas, Yoshiyuki Morita3, K. Murakami3, M. Nagamatu24, R. Nartallo28, Petteri Nieminen28, T. Nishimura, K. Ohtsubo, M. Okamura, S. W. O'Neale29, Y. Oohata19, K. Paech15, J Perl6, Andreas Pfeiffer4, Maria Grazia Pia, F. Ranjard4, A.M. Rybin, S.S Sadilov4, E. Di Salvo8, Giovanni Santin27, Takashi Sasaki3, N. Savvas2, Y. Sawada, Stefan Scherer15, S. Sei24, V. Sirotenko4, David J. Smith6, N. Starkov, H. Stoecker15, J. Sulkimo20, M. Takahata23, Satoshi Tanaka30, E. Tcherniaev4, E. Safai Tehrani6, M. Tropeano1, P. Truscott31, H. Uno24, L. Urbán, P. Urban32, M. Verderi, A. Walkden2, W. Wander33, H. Weber15, J.P. Wellisch4, Torre Wenaus34, D.C. Williams, Douglas Wright6, T. Yamada24, H. Yoshida24, D. Zschiesche15 
TL;DR: The Gelfant 4 toolkit as discussed by the authors is a toolkit for simulating the passage of particles through matter, including a complete range of functionality including tracking, geometry, physics models and hits.
Abstract: G eant 4 is a toolkit for simulating the passage of particles through matter. It includes a complete range of functionality including tracking, geometry, physics models and hits. The physics processes offered cover a comprehensive range, including electromagnetic, hadronic and optical processes, a large set of long-lived particles, materials and elements, over a wide energy range starting, in some cases, from 250 eV and extending in others to the TeV energy range. It has been designed and constructed to expose the physics models utilised, to handle complex geometries, and to enable its easy adaptation for optimal use in different sets of applications. The toolkit is the result of a worldwide collaboration of physicists and software engineers. It has been created exploiting software engineering and object-oriented technology and implemented in the C++ programming language. It has been used in applications in particle physics, nuclear physics, accelerator design, space engineering and medical physics.

18,904 citations

Journal ArticleDOI
Paul Bastard1, Paul Bastard2, Paul Bastard3, Lindsey B. Rosen4, Qian Zhang3, Eleftherios Michailidis3, Hans-Heinrich Hoffmann3, Yu Zhang4, Karim Dorgham2, Quentin Philippot2, Quentin Philippot1, Jérémie Rosain1, Jérémie Rosain2, Vivien Béziat3, Vivien Béziat1, Vivien Béziat2, Jeremy Manry1, Jeremy Manry2, Elana Shaw4, Liis Haljasmägi5, Pärt Peterson5, Lazaro Lorenzo2, Lazaro Lorenzo1, Lucy Bizien1, Lucy Bizien2, Sophie Trouillet-Assant6, Kerry Dobbs4, Adriana Almeida de Jesus4, Alexandre Belot6, Anne Kallaste7, Emilie Catherinot, Yacine Tandjaoui-Lambiotte1, Jérémie Le Pen3, Gaspard Kerner1, Gaspard Kerner2, Benedetta Bigio3, Yoann Seeleuthner1, Yoann Seeleuthner2, Rui Yang3, Alexandre Bolze, András N Spaan8, András N Spaan3, Ottavia M. Delmonte4, Michael S. Abers4, Alessandro Aiuti9, Giorgio Casari9, Vito Lampasona9, Lorenzo Piemonti9, Fabio Ciceri9, Kaya Bilguvar10, Richard P. Lifton10, Richard P. Lifton3, Marc Vasse, David M. Smadja2, Mélanie Migaud2, Mélanie Migaud1, Jérôme Hadjadj2, Benjamin Terrier2, Darragh Duffy11, Lluis Quintana-Murci12, Lluis Quintana-Murci11, Diederik van de Beek13, Lucie Roussel14, Donald C. Vinh14, Stuart G. Tangye15, Stuart G. Tangye16, Filomeen Haerynck17, David Dalmau18, Javier Martinez-Picado19, Javier Martinez-Picado20, Petter Brodin21, Petter Brodin22, Michel C. Nussenzweig23, Michel C. Nussenzweig3, Stéphanie Boisson-Dupuis3, Stéphanie Boisson-Dupuis1, Stéphanie Boisson-Dupuis2, Carlos Rodríguez-Gallego, Guillaume Vogt2, Trine H. Mogensen24, Trine H. Mogensen25, Andrew J. Oler4, Jingwen Gu4, Peter D. Burbelo4, Jeffrey I. Cohen4, Andrea Biondi26, Laura Rachele Bettini26, Mariella D'Angiò26, Paolo Bonfanti26, Patrick Rossignol27, Julien Mayaux2, Frédéric Rieux-Laucat2, Eystein S. Husebye28, Eystein S. Husebye29, Eystein S. Husebye30, Francesca Fusco, Matilde Valeria Ursini, Luisa Imberti31, Alessandra Sottini31, Simone Paghera31, Eugenia Quiros-Roldan32, Camillo Rossi, Riccardo Castagnoli33, Daniela Montagna33, Amelia Licari33, Gian Luigi Marseglia33, Xavier Duval, Jade Ghosn2, Hgid Lab4, Covid Clinicians5, Covid-Storm Clinicians§4, CoV-Contact Cohort§2, Amsterdam Umc Covid Biobank3, Amsterdam Umc Covid Biobank1, Amsterdam Umc Covid Biobank2, Covid Human Genetic Effort3, John S. Tsang4, Raphaela Goldbach-Mansky4, Kai Kisand5, Michail S. Lionakis4, Anne Puel2, Anne Puel3, Anne Puel1, Shen-Ying Zhang3, Shen-Ying Zhang2, Shen-Ying Zhang1, Steven M. Holland4, Guy Gorochov2, Emmanuelle Jouanguy3, Emmanuelle Jouanguy1, Emmanuelle Jouanguy2, Charles M. Rice3, Aurélie Cobat3, Aurélie Cobat1, Aurélie Cobat2, Luigi D. Notarangelo4, Laurent Abel1, Laurent Abel2, Laurent Abel3, Helen C. Su4, Jean-Laurent Casanova 
23 Oct 2020-Science
TL;DR: A means by which individuals at highest risk of life-threatening COVID-19 can be identified is identified, and the hypothesis that neutralizing auto-Abs against type I IFNs may underlie critical CO VID-19 is tested.
Abstract: Interindividual clinical variability in the course of SARS-CoV-2 infection is immense. We report that at least 101 of 987 patients with life-threatening COVID-19 pneumonia had neutralizing IgG auto-Abs against IFN-ω (13 patients), the 13 types of IFN-α (36), or both (52), at the onset of critical disease; a few also had auto-Abs against the other three type I IFNs. The auto-Abs neutralize the ability of the corresponding type I IFNs to block SARS-CoV-2 infection in vitro. These auto-Abs were not found in 663 individuals with asymptomatic or mild SARS-CoV-2 infection and were present in only 4 of 1,227 healthy individuals. Patients with auto-Abs were aged 25 to 87 years and 95 were men. A B cell auto-immune phenocopy of inborn errors of type I IFN immunity underlies life-threatening COVID-19 pneumonia in at least 2.6% of women and 12.5% of men.

1,913 citations

Journal ArticleDOI
TL;DR: It is demonstrated that AMPK interacts with and directly phosphorylates sterol regulatory element binding proteins (SREBP-1c and -2) and AMPK-dependent phosphorylation of SREBP may offer therapeutic strategies to combat insulin resistance, dyslipidemia, and atherosclerosis.

1,335 citations

Journal ArticleDOI
TL;DR: There is mounting data regarding the utility of GA in oncology practice; however, additional research is needed to continue to strengthen the evidence base.
Abstract: Purpose To update the International Society of Geriatric Oncology (SIOG) 2005 recommendations on geriatric assessment (GA) in older patients with cancer. Methods SIOG composed a panel with expertise in geriatric oncology to develop consensus statements after literature review of key evidence on the following topics: rationale for performing GA; findings from a GA performed in geriatric oncology patients; ability of GA to predict oncology treatment–related complications; association between GA findings and overall survival (OS); impact of GA findings on oncology treatment decisions; composition of a GA, including domains and tools; and methods for implementing GA in clinical care. Results GA can be valuable in oncology practice for following reasons: detection of impairment not identified in routine history or physical examination, ability to predict severe treatment-related toxicity, ability to predict OS in a variety of tumors and treatment settings, and ability to influence treatment choice and intensit...

1,266 citations

Journal ArticleDOI
TL;DR: In this article, the authors present results from thirteen cosmological simulations that explore the parameter space of the "Evolution and Assembly of GaLaxies and their Environments" (EAGLE) simulation project.
Abstract: We present results from thirteen cosmological simulations that explore the parameter space of the "Evolution and Assembly of GaLaxies and their Environments" (EAGLE) simulation project. Four of the simulations follow the evolution of a periodic cube L = 50 cMpc on a side, and each employs a different subgrid model of the energetic feedback associated with star formation. The relevant parameters were adjusted so that the simulations each reproduce the observed galaxy stellar mass function at z = 0.1. Three of the simulations fail to form disc galaxies as extended as observed, and we show analytically that this is a consequence of numerical radiative losses that reduce the efficiency of stellar feedback in high-density gas. Such losses are greatly reduced in the fourth simulation - the EAGLE reference model - by injecting more energy in higher density gas. This model produces galaxies with the observed size distribution, and also reproduces many galaxy scaling relations. In the remaining nine simulations, a single parameter or process of the reference model was varied at a time. We find that the properties of galaxies with stellar mass <~ M* (the "knee" of the galaxy stellar mass function) are largely governed by feedback associated with star formation, while those of more massive galaxies are also controlled by feedback from accretion onto their central black holes. Both processes must be efficient in order to reproduce the observed galaxy population. In general, simulations that have been calibrated to reproduce the low-redshift galaxy stellar mass function will still not form realistic galaxies, but the additional requirement that galaxy sizes be acceptable leads to agreement with a large range of observables.

1,079 citations


Authors

Showing all 4285 results

NameH-indexPapersCitations
Jean-Yves Blay10480845637
Emmanuel Mignot10361140891
Gilles Salles9985448219
Fabien Zoulim9664135807
Olivier Bernard9679037878
Johan Richard9549925915
Francis Albarède9134727996
Bertrand Coiffier9044042115
Raphael Noel Tieulent8941724926
Imad Baptiste Laktineh87102137418
Stephen Locarnini8744928813
Laurent Ducroux8427222005
François Vandenesch8340732992
Hubert Vidal8333325594
François-Loïc Cosset8235723816
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20232
202212
2021560
2020520
2019421
2018406