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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 & European union. 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: In this paper, an objective classification scheme of the atmospheric circulation affecting Portugal, between 1946 and 1990, is presented, where daily circulation is characterized through the use of a set of indices associated with the direction and vorticity of the geostrophic flow.
Abstract: An objective classification scheme of the atmospheric circulation affecting Portugal, between 1946 and 1990, is presented, where daily circulation is characterized through the use of a set of indices associated with the direction and vorticity of the geostrophic flow. The synoptic characteristics and the frequency of ten basic circulation weather types (CWTs) are discussed, as well as the amount of precipitation associated with each type between 1957 and 1986. It is shown that the anticyclonic (A) type, although being the most frequent class in winter (37%), gives a rather small (less then 16%) contribution to the winter precipitation amount, observed on a daily basis. On the other hand, the three wettest CWTs, namely the cyclonic (C), southwesterly (SW) and westerly (W) types, together representing only 32% of all winter days, account for more than 62% of the observed daily precipitation. Results obtained highlight the existence of strong links between the interannual variability of monthly precipitation and interannual variability of CWTs. Multiple regression models, developed for 18 stations, show the ability of modelling monthly winter precipitation through the exclusive use, as predictors, of the wet CWTs (i.e. C, SW and W). The observed decreasing trend of March precipitation is also analysed and shown to be especially associated with the decrease of the three wet weather types. The anomalous low (high) frequency of wet CWTs during the hydrological year is shown to be strongly related with the occurrence of extreme dry (wet) years in Portugal, which had important impacts on Portuguese agriculture. Overall, the results suggest that the precipitation regime over Portugal, including interannual variability, trends and extremes, may be adequately explained in terms of variability of a fairly small number of circulation weather patterns. On the other hand, observed contrasts in the spatial distribution of correlations between frequency of wet CWTs and rainfall amounts suggest that precipitation regimes are of a different nature in northern and southern regions of Portugal; the former possessing an orographic origin and the latter being associated to cyclogenetic activity. Copyright © 2000 Royal Meteorological Society.

439 citations

Journal ArticleDOI
Georges Aad1, Alexander Kupco2, P. Davison3, Samuel Webb4  +2888 moreInstitutions (192)
TL;DR: Topological cell clustering is established as a well-performing calorimeter signal definition for jet and missing transverse momentum reconstruction in ATLAS and is exploited to apply a local energy calibration and corrections depending on the nature of the cluster.
Abstract: The reconstruction of the signal from hadrons and jets emerging from the proton–proton collisions at the Large Hadron Collider (LHC) and entering the ATLAS calorimeters is based on a three-dimensional topological clustering of individual calorimeter cell signals. The cluster formation follows cell signal-significance patterns generated by electromagnetic and hadronic showers. In this, the clustering algorithm implicitly performs a topological noise suppression by removing cells with insignificant signals which are not in close proximity to cells with significant signals. The resulting topological cell clusters have shape and location information, which is exploited to apply a local energy calibration and corrections depending on the nature of the cluster. Topological cell clustering is established as a well-performing calorimeter signal definition for jet and missing transverse momentum reconstruction in ATLAS.

438 citations

Journal ArticleDOI
Georges Aad1, Brad Abbott2, J. Abdallah3, S. Abdel Khalek4  +3073 moreInstitutions (193)
TL;DR: In this paper, a Fourier analysis of the charged particle pair distribution in relative azimuthal angle (Delta phi = phi(a)-phi(b)) is performed to extract the coefficients v(n,n) =.
Abstract: Differential measurements of charged particle azimuthal anisotropy are presented for lead-lead collisions at root sNN = 2.76 TeV with the ATLAS detector at the LHC, based on an integrated luminosity of approximately 8 mu b(-1). This anisotropy is characterized via a Fourier expansion of the distribution of charged particles in azimuthal angle relative to the reaction plane, with the coefficients v(n) denoting the magnitude of the anisotropy. Significant v(2)-v(6) values are obtained as a function of transverse momentum (0.5 = 3 are found to vary weakly with both eta and centrality, and their p(T) dependencies are found to follow an approximate scaling relation, v(n)(1/n)(p(T)) proportional to v(2)(1/2)(p(T)), except in the top 5% most central collisions. A Fourier analysis of the charged particle pair distribution in relative azimuthal angle (Delta phi = phi(a)-phi(b)) is performed to extract the coefficients v(n,n) = . For pairs of charged particles with a large pseudorapidity gap (|Delta eta = eta(a) - eta(b)| > 2) and one particle with p(T) < 3 GeV, the v(2,2)-v(6,6) values are found to factorize as v(n,n)(p(T)(a), p(T)(b)) approximate to v(n) (p(T)(a))v(n)(p(T)(b)) in central and midcentral events. Such factorization suggests that these values of v(2,2)-v(6,6) are primarily attributable to the response of the created matter to the fluctuations in the geometry of the initial state. A detailed study shows that the v(1,1)(p(T)(a), p(T)(b)) data are consistent with the combined contributions from a rapidity-even v(1) and global momentum conservation. A two-component fit is used to extract the v(1) contribution. The extracted v(1) isobserved to cross zero at pT approximate to 1.0 GeV, reaches a maximum at 4-5 GeV with a value comparable to that for v(3), and decreases at higher p(T).

435 citations

Journal ArticleDOI
Georges Aad1, Brad Abbott2, Jalal Abdallah3, A. A. Abdelalim4  +3104 moreInstitutions (190)
TL;DR: In this paper, the particle multiplicity, its dependence on transverse momentum and pseudorapidity and the relationship between the mean transversal momentum and the charged-particle multiplicity are measured.
Abstract: Measurements are presented from proton-proton collisions at centre-of-mass energies of root s = 0.9, 2.36 and 7 TeV recorded with the ATLAS detector at the LHC. Events were collected using a single-arm minimum-bias trigger. The charged-particle multiplicity, its dependence on transverse momentum and pseudorapidity and the relationship between the mean transverse momentum and charged-particle multiplicity are measured. Measurements in different regions of phase space are shown, providing diffraction-reduced measurements as well as more inclusive ones. The observed distributions are corrected to well-defined phase-space regions, using model-independent corrections. The results are compared to each other and to various Monte Carlo (MC) models, including a new AMBT1 pythia6 tune. In all the kinematic regions considered, the particle multiplicities are higher than predicted by the MC models. The central charged-particle multiplicity per event and unit of pseudorapidity, for tracks with p(T) > 100 MeV, is measured to be 3.483 +/- 0.009 (stat) +/- 0.106 (syst) at root s = 0.9 TeV and 5.630 +/- 0.003 (stat) +/- 0.169 (syst) at root s = 7 TeV.

435 citations

Journal ArticleDOI
Matteo Dainese1, Emily A. Martin1, Marcelo A. Aizen2, Matthias Albrecht, Ignasi Bartomeus3, Riccardo Bommarco4, Luísa G. Carvalheiro5, Luísa G. Carvalheiro6, Rebecca Chaplin-Kramer7, Vesna Gagic8, Lucas Alejandro Garibaldi9, Jaboury Ghazoul10, Heather Grab11, Mattias Jonsson4, Daniel S. Karp12, Christina M. Kennedy13, David Kleijn14, Claire Kremen15, Douglas A. Landis16, Deborah K. Letourneau17, Lorenzo Marini18, Katja Poveda11, Romina Rader19, Henrik G. Smith20, Teja Tscharntke21, Georg K.S. Andersson20, Isabelle Badenhausser22, Isabelle Badenhausser23, Svenja Baensch21, Antonio Diego M. Bezerra24, Felix J.J.A. Bianchi14, Virginie Boreux25, Virginie Boreux10, Vincent Bretagnolle22, Berta Caballero-López, Pablo Cavigliasso26, Aleksandar Ćetković27, Natacha P. Chacoff28, Alice Classen1, Sarah Cusser29, Felipe D. da Silva e Silva30, G. Arjen de Groot14, Jan H. Dudenhöffer31, Johan Ekroos20, Thijs P.M. Fijen14, Pierre Franck23, Breno Magalhães Freitas24, Michael P.D. Garratt32, Claudio Gratton33, Juliana Hipólito34, Juliana Hipólito9, Andrea Holzschuh1, Lauren Hunt35, Aaron L. Iverson11, Shalene Jha36, Tamar Keasar37, Tania N. Kim38, Miriam Kishinevsky37, Björn K. Klatt21, Björn K. Klatt20, Alexandra-Maria Klein25, Kristin M. Krewenka39, Smitha Krishnan40, Smitha Krishnan10, Ashley E. Larsen41, Claire Lavigne23, Heidi Liere42, Bea Maas43, Rachel E. Mallinger44, Eliana Martinez Pachon, Alejandra Martínez-Salinas45, Timothy D. Meehan46, Matthew G. E. Mitchell15, Gonzalo Alberto Roman Molina47, Maike Nesper10, Lovisa Nilsson20, Megan E. O'Rourke48, Marcell K. Peters1, Milan Plećaš27, Simon G. Potts33, Davi de L. Ramos, Jay A. Rosenheim12, Maj Rundlöf20, Adrien Rusch49, Agustín Sáez2, Jeroen Scheper14, Matthias Schleuning, Julia Schmack50, Amber R. Sciligo51, Colleen L. Seymour, Dara A. Stanley52, Rebecca Stewart20, Jane C. Stout53, Louis Sutter, Mayura B. Takada54, Hisatomo Taki, Giovanni Tamburini25, Matthias Tschumi, Blandina Felipe Viana55, Catrin Westphal21, Bryony K. Willcox19, Stephen D. Wratten56, Akira Yoshioka57, Carlos Zaragoza-Trello3, Wei Zhang58, Yi Zou59, Ingolf Steffan-Dewenter1 
University of Würzburg1, National University of Comahue2, Spanish National Research Council3, Swedish University of Agricultural Sciences4, Universidade Federal de Goiás5, University of Lisbon6, Stanford University7, Commonwealth Scientific and Industrial Research Organisation8, National University of Río Negro9, ETH Zurich10, Cornell University11, University of California, Davis12, The Nature Conservancy13, Wageningen University and Research Centre14, University of British Columbia15, Great Lakes Bioenergy Research Center16, University of California, Santa Cruz17, University of Padua18, University of New England (Australia)19, Lund University20, University of Göttingen21, University of La Rochelle22, Institut national de la recherche agronomique23, Federal University of Ceará24, University of Freiburg25, Concordia University Wisconsin26, University of Belgrade27, National University of Tucumán28, Michigan State University29, University of Brasília30, University of Greenwich31, University of Reading32, University of Wisconsin-Madison33, National Institute of Amazonian Research34, Boise State University35, University of Texas at Austin36, University of Haifa37, Kansas State University38, University of Hamburg39, Bioversity International40, University of California, Santa Barbara41, Seattle University42, University of Vienna43, University of Florida44, Centro Agronómico Tropical de Investigación y Enseñanza45, National Audubon Society46, University of Buenos Aires47, Virginia Tech48, University of Bordeaux49, University of Auckland50, University of California, Berkeley51, University College Dublin52, Trinity College, Dublin53, University of Tokyo54, Federal University of Bahia55, Lincoln University (New Zealand)56, National Institute for Environmental Studies57, International Food Policy Research Institute58, Xi'an Jiaotong-Liverpool University59
TL;DR: Using a global database from 89 studies (with 1475 locations), the relative importance of species richness, abundance, and dominance for pollination; biological pest control; and final yields in the context of ongoing land-use change is partitioned.
Abstract: Human land use threatens global biodiversity and compromises multiple ecosystem functions critical to food production. Whether crop yield-related ecosystem services can be maintained by a few dominant species or rely on high richness remains unclear. Using a global database from 89 studies (with 1475 locations), we partition the relative importance of species richness, abundance, and dominance for pollination; biological pest control; and final yields in the context of ongoing land-use change. Pollinator and enemy richness directly supported ecosystem services in addition to and independent of abundance and dominance. Up to 50% of the negative effects of landscape simplification on ecosystem services was due to richness losses of service-providing organisms, with negative consequences for crop yields. Maintaining the biodiversity of ecosystem service providers is therefore vital to sustain the flow of key agroecosystem benefits to society.

434 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
2022827
20214,520
20204,517
20193,810
20183,617