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Institution

University of Lisbon

EducationLisbon, Lisboa, Portugal
About: University of Lisbon is a education organization based out in Lisbon, Lisboa, Portugal. It is known for research contribution in the topics: Population & Context (language use). The organization has 19122 authors who have published 48503 publications receiving 1102623 citations. The organization is also known as: Universidade de Lisboa & Lisbon University.


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Journal ArticleDOI
TL;DR: The COVID-19 pandemic has had an overwhelming psychological impact on intensivists and follow-up, and management are warranted to assess long-term psychological outcomes and alleviate the psychological burden of the pandemic on frontline personnel.
Abstract: The COVID-19 pandemic has resulted in an unprecedented healthcare crisis with a high prevalence of psychological distress in healthcare providers. We sought to document the prevalence of burnout syndrome amongst intensivists facing the COVID-19 outbreak. Cross-sectional survey among intensivists part of the European Society of Intensive Care Medicine. Symptoms of severe burnout, anxiety and depression were collected. Factors independently associated with severe burnout were assessed using Cox model. Response rate was 20% (1001 completed questionnaires were returned, 45 years [39–53], 34% women, from 85 countries, 12 regions, 50% university-affiliated hospitals). The prevalence of symptoms of anxiety and depression or severe burnout was 46.5%, 30.2%, and 51%, respectively, and varied significantly across regions. Rating of the relationship between intensivists and other ICU stakeholders differed significantly according to the presence of anxiety, depression, or burnout. Similar figures were reported for their rating of the ethical climate or the quality of the decision-making. Factors independently associated with anxiety were female gender (HR 1.85 [1.33–2.55]), working in a university-affiliated hospital (HR 0.58 [0.42–0.80]), living in a city of > 1 million inhabitants (HR 1.40 [1.01–1.94]), and clinician’s rating of the ethical climate (HR 0.83 [0.77–0.90]). Independent determinants of depression included female gender (HR 1.63 [1.15–2.31]) and clinician’s rating of the ethical climate (HR 0.84 [0.78–0.92]). Factors independently associated with symptoms of severe burnout included age (HR 0.98/year [0.97–0.99]) and clinician’s rating of the ethical climate (HR 0.76 [0.69–0.82]). The COVID-19 pandemic has had an overwhelming psychological impact on intensivists. Follow-up, and management are warranted to assess long-term psychological outcomes and alleviate the psychological burden of the pandemic on frontline personnel.

235 citations

Journal ArticleDOI
TL;DR: In this paper, the authors present three lines of psychological reasoning that provide compelling arguments as to why highlighting proximal impacts of climate change might not be as effective a way to increase individual mitigation and adaptation efforts as is often assumed.
Abstract: A frequent suggestion to increase individuals' willingness to take action on climate change and to support relevant policies is to highlight its proximal consequences, that is, those that are close in space and time. But previous studies that have tested this proximizing approach have not revealed the expected positive effects on individual action and support for addressing climate change. We present three lines of psychological reasoning that provide compelling arguments as to why highlighting proximal impacts of climate change might not be as effective a way to increase individual mitigation and adaptation efforts as is often assumed. Our contextualization of the proximizing approach within established psychological research suggests that, depending on the particular theoretical perspective one takes on this issue, and on specific individual characteristics suggested by these perspectives, proximizing can bring about the intended positive effects, can have no (visible) effect or can even backfire. Thus, the effects of proximizing are much more complex than is commonly assumed. Revealing this complexity contributes to a refined theoretical understanding of the role that psychological distance plays in the context of climate change and opens up further avenues for future research and for interventions.

234 citations

Journal ArticleDOI
Juan Antonio Aguilar-Saavedra1, Ahmed Ali, Benjamin C. Allanach2, Richard L. Arnowitt3, Howard Baer4, Jonathan Bagger5, Csaba Balázs6, Vernon Barger7, Michael Barnett8, A. Bartl9, Marco Battaglia8, Philip Bechtle10, Geneviève Bélanger, Alexander Belyaev11, Edmond L. Berger6, G.A. Blair12, Edouard Boos13, Marcela Carena14, S.Y. Choi15, Frank F. Deppisch, A. De Roeck16, Klaus Desch17, Marco Aurelio Diaz18, Abdelhak Djouadi19, Bhaskar Dutta3, S. Dutta20, S. Dutta10, Helmut Eberl21, John Ellis16, Jens Erler22, H. Fraas23, Ayres Freitas24, T. Fritzsche25, Rohini M. Godbole26, G. Gounaris27, Jaume Guasch28, John F. Gunion29, Naoyuki Haba30, Howard E. Haber31, K. Hagiwara, Liyuan Han32, Tao Han7, Hong-Jian He33, Sven Heinemeyer16, S. Hesselbach34, Keisho Hidaka35, I. Hinchliffe8, Martin Hirsch36, K. Hohenwarter-Sodek9, Wolfgang Hollik25, W. S. Hou37, Tobias Hurth16, Tobias Hurth10, I. Jack38, Yi Jiang32, D.R.T. Jones38, J. Kalinowski39, T. Kamon3, Gordon L. Kane40, Sin Kyu Kang41, Thomas Kernreiter9, Wolfgang Kilian, Choong Sun Kim42, Stephen F. King43, O. Kittel44, Michael Klasen, J. L. Kneur45, K. Kovarik21, Michael Kramer46, Sabine Kraml16, Remi Lafaye47, Paul Langacker48, Heather E. Logan49, W. G. Ma32, W. Majerotto21, H. U. Martyn46, Konstantin Matchev50, David J. Miller51, Myriam Mondragón22, Gudrid Moortgat-Pick16, Stefano Moretti43, Takehiko Mori52, Gilbert Moultaka45, Steve Muanza53, M. M. Mühlleitner, Biswarup Mukhopadhyaya54, U. Nauenberg55, Mihoko M. Nojiri56, D. Nomura11, H. Nowak, N. Okada, Keith A. Olive57, W. Oller21, Michael E. Peskin10, Tilman Plehn25, Giacomo Polesello, Werner Porod24, Werner Porod36, Fernando Quevedo2, David L. Rainwater58, Jürgen Reuter, Peter J. Richardson59, Krzysztof Rolbiecki39, Probir Roy60, Reinhold Rückl23, Heidi Rzehak61, P. Schleper62, Kim Siyeon63, Peter Skands14, P. Slavich, Dominik Stöckinger59, Paraskevas Sphicas16, Michael Spira61, Tim M. P. Tait6, Daniel Tovey64, José W. F. Valle36, Carlos E. M. Wagner65, Carlos E. M. Wagner6, Ch. Weber21, Georg Weiglein59, Peter Wienemann17, Z.-Z. Xing, Y. Yamada66, Jin Min Yang, D. Zerwas19, P.M. Zerwas, Ren-You Zhang32, X. Zhang, S.-H. Zhu67 
University of Lisbon1, University of Cambridge2, Texas A&M University3, Florida State University4, Johns Hopkins University5, Argonne National Laboratory6, University of Wisconsin-Madison7, Lawrence Berkeley National Laboratory8, University of Vienna9, Stanford University10, Michigan State University11, Royal Holloway, University of London12, Moscow State University13, Fermilab14, Chonbuk National University15, CERN16, University of Freiburg17, Pontifical Catholic University of Chile18, University of Paris19, University of Delhi20, Austrian Academy of Sciences21, National Autonomous University of Mexico22, University of Würzburg23, University of Zurich24, Max Planck Society25, Indian Institute of Science26, Aristotle University of Thessaloniki27, University of Barcelona28, University of California, Davis29, University of Tokushima30, University of California, Santa Cruz31, University of Science and Technology of China32, Tsinghua University33, Uppsala University34, Tokyo Gakugei University35, Spanish National Research Council36, National Taiwan University37, University of Liverpool38, University of Warsaw39, University of Michigan40, Seoul National University41, Yonsei University42, University of Southampton43, University of Bonn44, University of Montpellier45, RWTH Aachen University46, Laboratoire d'Annecy-le-Vieux de physique des particules47, University of Pennsylvania48, Carleton University49, University of Florida50, University of Glasgow51, University of Tokyo52, University of Lyon53, Harish-Chandra Research Institute54, University of Colorado Boulder55, Kyoto University56, University of Minnesota57, University of Rochester58, Durham University59, Tata Institute of Fundamental Research60, Paul Scherrer Institute61, University of Hamburg62, Chung-Ang University63, University of Sheffield64, University of Chicago65, Tohoku University66, Peking University67
TL;DR: In this article, a supersymmetry Parameter Analysis SPA (SPA) scheme is proposed based on a consistent set of conventions and input parameters, which connect parameters in different schemes and relate the Lagrangian parameters to physical observables at LHC and high energy e(+)e(-) linear collider experiments, i.e., masses, mixings, decay widths and production cross sections for supersymmetric particles.
Abstract: High-precision analyses of supersymmetry parameters aim at reconstructing the fundamental supersymmetric theory and its breaking mechanism. A well defined theoretical framework is needed when higher-order corrections are included. We propose such a scheme, Supersymmetry Parameter Analysis SPA, based on a consistent set of conventions and input parameters. A repository for computer programs is provided which connect parameters in different schemes and relate the Lagrangian parameters to physical observables at LHC and high energy e(+)e(-) linear collider experiments, i.e., masses, mixings, decay widths and production cross sections for supersymmetric particles. In addition, programs for calculating high-precision low energy observables, the density of cold dark matter (CDM) in the universe as well as the cross sections for CDM search experiments are included. The SPA scheme still requires extended efforts on both the theoretical and experimental side before data can be evaluated in the future at the level of the desired precision. We take here an initial step of testing the SPA scheme by applying the techniques involved to a specific supersymmetry reference point.

234 citations

Journal ArticleDOI
Morad Aaboud, Georges Aad1, Brad Abbott2, Dale Charles Abbott3  +2936 moreInstitutions (198)
TL;DR: An exclusion limit on the H→invisible branching ratio of 0.26(0.17_{-0.05}^{+0.07}) at 95% confidence level is observed (expected) in combination with the results at sqrt[s]=7 and 8 TeV.
Abstract: Dark matter particles, if sufficiently light, may be produced in decays of the Higgs boson. This Letter presents a statistical combination of searches for H→invisible decays where H is produced according to the standard model via vector boson fusion, Z(ll)H, and W/Z(had)H, all performed with the ATLAS detector using 36.1 fb^{-1} of pp collisions at a center-of-mass energy of sqrt[s]=13 TeV at the LHC. In combination with the results at sqrt[s]=7 and 8 TeV, an exclusion limit on the H→invisible branching ratio of 0.26(0.17_{-0.05}^{+0.07}) at 95% confidence level is observed (expected).

234 citations

Journal ArticleDOI
Néstor Armesto1, Nicolas Borghini2, Sangyong Jeon3, Urs Achim Wiedemann4  +191 moreInstitutions (63)
TL;DR: A compilation of predictions for the forthcoming Heavy Ion Program at the Large Hadron Collider, as presented at the CERN Theory Institute 'Heavy Ion Collisions at the LHC - Last Call for Predictions', held from 14th May to 10th June 2007, can be found in this article.
Abstract: This writeup is a compilation of the predictions for the forthcoming Heavy Ion Program at the Large Hadron Collider, as presented at the CERN Theory Institute 'Heavy Ion Collisions at the LHC - Last Call for Predictions', held from 14th May to 10th June 2007.

234 citations


Authors

Showing all 19716 results

NameH-indexPapersCitations
Joao Seixas1531538115070
A. Gomes1501862113951
Marco Costa1461458105096
António Amorim136147796519
Osamu Jinnouchi13588586104
P. Verdier133111183862
Andy Haas132109687742
Wendy Taylor131125289457
Steve McMahon13087878763
Timothy Andeen129106977593
Heather Gray12996680970
Filipe Veloso12888775496
Nuno Filipe Castro12896076945
Oliver Stelzer-Chilton128114179154
Isabel Marian Trigger12897477594
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023247
2022828
20214,521
20204,517
20193,810
20183,617