Institution
University of Oviedo
Education•Oviedo, Spain•
About: University of Oviedo is a education organization based out in Oviedo, Spain. It is known for research contribution in the topics: Population & Catalysis. The organization has 13423 authors who have published 31649 publications receiving 844799 citations. The organization is also known as: Universidá d'Uviéu & Universidad de Oviedo.
Papers published on a yearly basis
Papers
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TL;DR: The landscape indices, which describe scale‐dependent correlation between and within habitat types, were able to explain variations in variables of population dynamics caused by different landscape structure.
Abstract: We construct and explore a general modeling framework that allows for a systematic investigation of the impact of changes in landscape structure on population dynamics. The essential parts of the framework are a landscape generator with independent control over landscape composition and physiognomy, an individual‐based spatially explicit population model that simulates population dynamics within heterogeneous landscapes, and scale‐dependent landscape indices that depict the essential aspects of landscape that interact with dispersal and demographic processes. Landscape maps are represented by a grid of \documentclass{aastex} \usepackage{amsbsy} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{bm} \usepackage{mathrsfs} \usepackage{pifont} \usepackage{stmaryrd} \usepackage{textcomp} \usepackage{portland,xspace} \usepackage{amsmath,amsxtra} \usepackage[OT2,OT1]{fontenc}
ewcommand\cyr{ \renewcommand\rmdefault{wncyr} \renewcommand\sfdefault{wncyss} \renewcommand\encodingdefault{OT2}
ormalfo...
274 citations
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TL;DR: The results of several studies are reviewed and the evidence suggests that, if they are to account for the data, experience-based parsers must draw upon records or representations that capture statistical regularities beyond the lexical level.
Abstract: Several current models of human parsing maintain that initial structural decisions are influenced (or tuned) by the listener's or reader's prior contact with language. The precise workings of these models depend upon the “grain,” or level of detail, at which previous exposures to language are analyzed and used to influence parsing decisions. Some models are premised upon the use of fine-grained records (such as lexical cooccurrence statistics). Others use coarser measures. The present paper considers the viability of models based exclusively on the use of fine-grained lexical records. The results of several studies are reviewed and the evidence suggests that, if they are to account for the data, experience-based parsers must draw upon records or representations that capture statistical regularities beyond the lexical level. This poses problems for several parsing models in the literature.
274 citations
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Vardan Khachatryan, Albert M. Sirunyan, Armen Tumasyan, Wolfgang Adam1 +2204 more•Institutions (181)
TL;DR: In this paper, the performance of the Cern LHC detector for photon reconstruction and identification in proton-proton collisions at a centre-of-mass energy of 8 TeV at the CERN LHC is described.
Abstract: A description is provided of the performance of the CMS detector for photon reconstruction and identification in proton-proton collisions at a centre-of-mass energy of 8 TeV at the CERN LHC. Details are given on the reconstruction of photons from energy deposits in the electromagnetic calorimeter (ECAL) and the extraction of photon energy estimates. The reconstruction of electron tracks from photons that convert to electrons in the CMS tracker is also described, as is the optimization of the photon energy reconstruction and its accurate modelling in simulation, in the analysis of the Higgs boson decay into two photons. In the barrel section of the ECAL, an energy resolution of about 1% is achieved for unconverted or late-converting photons from H→γγ decays. Different photon identification methods are discussed and their corresponding selection efficiencies in data are compared with those found in simulated events.
272 citations
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TL;DR: In this paper, the authors present predictions for the counts of extragalactic sources, the contributions to fluctuations and their angular power spectrum in each channel foreseen for the Planck Surveyor (formerly COBRAS/SAMBA) mission.
Abstract: We present predictions for the counts of extragalactic sources, the contributions to fluctuations and their angular power spectrum in each channel foreseen for the Planck Surveyor (formerly COBRAS/SAMBA) mission. The contribution to fluctuations owing to clustering of both radio and far-IR sources is found to be generally small in comparison with the Poisson term; however the relative importance of the clustering contribution increases and may eventually become dominant if sources are identified and subtracted down to faint flux limits. The central Planck frequency bands are expected to be ‘clean’: at high galactic latitude (|b| > 20°), where the reduced galactic noise does not prevent the detection of the extragalactic signal, only a tiny fraction of pixels is found to be contaminated by discrete extragalactic sources. Moreover, the ‘flat’ angular power spectrum of fluctuations resulting from extragalactic sources substantially differs from that of primordial fluctuations; therefore, the removal of contaminating signals is eased even at frequencies where point sources give a sizeable contribution to the foreground noise.
272 citations
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TL;DR: A fuzzy G.P. approach is applied to the optimum portfolio for a private investor, taking into account three criteria: return, risk and liquidity, where the goals and the constraints are fuzzy.
272 citations
Authors
Showing all 13643 results
Name | H-index | Papers | Citations |
---|---|---|---|
Russel J. Reiter | 169 | 1646 | 121010 |
Carlo Rovelli | 146 | 1502 | 103550 |
J. González-Nuevo | 144 | 500 | 108318 |
German Martinez | 141 | 1476 | 107887 |
Roland Horisberger | 139 | 1471 | 100458 |
Francisco Herrera | 139 | 1001 | 82976 |
Javier Cuevas | 138 | 1689 | 103604 |
Teresa Rodrigo | 138 | 1831 | 103601 |
L. Toffolatti | 136 | 376 | 95529 |
Elias Campo | 135 | 761 | 85160 |
Gabor Istvan Veres | 135 | 1349 | 96104 |
Francisco Matorras | 134 | 1428 | 94627 |
Joe Incandela | 134 | 1549 | 93750 |
Nikhil C. Munshi | 134 | 906 | 67349 |
Luca Scodellaro | 134 | 1741 | 98331 |