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University of Oxford

EducationOxford, Oxfordshire, United Kingdom
About: University of Oxford is a(n) education organization based out in Oxford, Oxfordshire, United Kingdom. It is known for research contribution in the topic(s): Population & Galaxy. The organization has 99713 authors who have published 258108 publication(s) receiving 12972806 citation(s). The organization is also known as: Oxford University & Oxon..
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Journal ArticleDOI
TL;DR: A new hypothesis about the role of focused attention is proposed, which offers a new set of criteria for distinguishing separable from integral features and a new rationale for predicting which tasks will show attention limits and which will not.
Abstract: A new hypothesis about the role of focused attention is proposed. The feature-integration theory of attention suggests that attention must be directed serially to each stimulus in a display whenever conjunctions of more than one separable feature are needed to characterize or distinguish the possible objects presented. A number of predictions were tested in a variety of paradigms including visual search, texture segregation, identification and localization, and using both separable dimensions (shape and color) and local elements or parts of figures (lines, curves, etc. in letters) as the features to be integrated into complex wholes. The results were in general consistent with the hypothesis. They offer a new set of criteria for distinguishing separable from integral features and a new rationale for predicting which tasks will show attention limits and which will not.

10,915 citations

Journal ArticleDOI
01 Jan 2004-NeuroImage
TL;DR: A review of the research carried out by the Analysis Group at the Oxford Centre for Functional MRI of the Brain (FMRIB) on the development of new methodologies for the analysis of both structural and functional magnetic resonance imaging data.
Abstract: The techniques available for the interrogation and analysis of neuroimaging data have a large influence in determining the flexibility, sensitivity, and scope of neuroimaging experiments. The development of such methodologies has allowed investigators to address scientific questions that could not previously be answered and, as such, has become an important research area in its own right. In this paper, we present a review of the research carried out by the Analysis Group at the Oxford Centre for Functional MRI of the Brain (FMRIB). This research has focussed on the development of new methodologies for the analysis of both structural and functional magnetic resonance imaging data. The majority of the research laid out in this paper has been implemented as freely available software tools within FMRIB's Software Library (FSL).

10,569 citations

Journal ArticleDOI
Peter A. R. Ade1, Nabila Aghanim2, Monique Arnaud3, M. Ashdown4, J. Aumont2, Carlo Baccigalupi5, A. J. Banday6, A. J. Banday7, R. B. Barreiro8, James G. Bartlett9, James G. Bartlett3, N. Bartolo10, N. Bartolo11, E. Battaner12, Richard A. Battye13, K. Benabed14, Alain Benoit15, A. Benoit-Lévy14, A. Benoit-Lévy16, J.-P. Bernard7, J.-P. Bernard6, Marco Bersanelli17, Marco Bersanelli18, P. Bielewicz6, P. Bielewicz5, J. J. Bock9, Anna Bonaldi13, Laura Bonavera8, J. R. Bond19, Julian Borrill20, Julian Borrill21, François R. Bouchet14, Francois Boulanger2, M. Bucher3, Carlo Burigana22, Carlo Burigana17, R. C. Butler17, Erminia Calabrese23, Jean-François Cardoso24, Jean-François Cardoso3, Jean-François Cardoso14, A. Catalano25, A. Catalano26, Anthony Challinor4, A. Chamballu2, A. Chamballu27, A. Chamballu3, Ranga-Ram Chary9, H. C. Chiang28, H. C. Chiang29, Jens Chluba30, P. R. Christensen31, Sarah E. Church32, David L. Clements33, S. Colombi14, L. P. L. Colombo34, L. P. L. Colombo9, C. Combet25, A. Coulais26, B. P. Crill9, A. Curto4, A. Curto8, F. Cuttaia17, Luigi Danese5, R. D. Davies13, R. J. Davis13, P. de Bernardis35, A. de Rosa17, G. de Zotti5, G. de Zotti17, Jacques Delabrouille3, F.-X. Désert25, E. Di Valentino14, Clive Dickinson13, Jose M. Diego8, Klaus Dolag36, Klaus Dolag37, H. Dole38, H. Dole2, S. Donzelli17, Olivier Doré9, Marian Douspis2, A. Ducout33, A. Ducout14, Jo Dunkley23, X. Dupac39, George Efstathiou4, F. Elsner14, F. Elsner16, Torsten A. Enßlin37, H. K. Eriksen40, Marzieh Farhang19, Marzieh Farhang41, James R. Fergusson4, Fabio Finelli17, Olivier Forni7, Olivier Forni6, M. Frailis17, A. A. Fraisse29, E. Franceschi17, A. Frejsel31, S. Galeotta17, S. Galli42, K. Ganga3, C. Gauthier43, C. Gauthier3, M. Gerbino44, M. Gerbino45, M. Gerbino35, Tuhin Ghosh2, M. Giard7, M. Giard6, Y. Giraud-Héraud3, Elena Giusarma35, E. Gjerløw40, J. González-Nuevo46, J. González-Nuevo8, Krzysztof M. Gorski9, Krzysztof M. Gorski47, Serge Gratton4, A. Gregorio17, A. Gregorio48, Alessandro Gruppuso17, Jon E. Gudmundsson44, Jon E. Gudmundsson29, Jon E. Gudmundsson45, Jan Hamann49, Jan Hamann50, F. K. Hansen40, Duncan Hanson51, Duncan Hanson9, Duncan Hanson19, D. L. Harrison4, George Helou9, Sophie Henrot-Versille52, C. Hernández-Monteagudo37, D. Herranz8, S. R. Hildebrandt9, E. Hivon14, Michael P. Hobson4, W. A. Holmes9, Allan Hornstrup53, W. Hovest37, Zhiqi Huang19, Kevin M. Huffenberger54, G. Hurier2, Andrew H. Jaffe33, T. R. Jaffe7, T. R. Jaffe6, W. C. Jones29, Mika Juvela55, E. Keihänen55, Reijo Keskitalo20, Theodore Kisner20, R. Kneissl56, R. Kneissl57, J. Knoche37, Lloyd Knox58, Martin Kunz2, Martin Kunz59, Martin Kunz60, Hannu Kurki-Suonio55, Guilaine Lagache61, Guilaine Lagache2, Anne Lähteenmäki62, Anne Lähteenmäki63, J.-M. Lamarre26, Anthony Lasenby4, Massimiliano Lattanzi22, Charles R. Lawrence9, J. P. Leahy13, R. Leonardi, Julien Lesgourgues50, Julien Lesgourgues64, François Levrier26, Antony Lewis65, Michele Liguori10, Michele Liguori11, P. B. Lilje40, M. Linden-Vørnle53, M. López-Caniego8, M. López-Caniego39, Philip Lubin66, J. F. Macías-Pérez25, G. Maggio17, Davide Maino17, Davide Maino18, N. Mandolesi22, N. Mandolesi17, A. Mangilli2, A. Mangilli52, A. Marchini, Michele Maris17, Peter G. Martin19, M. Martinelli67, E. Martínez-González8, Silvia Masi35, Sabino Matarrese11, Sabino Matarrese10, P. McGehee9, Peter Meinhold66, Alessandro Melchiorri35, Jean-Baptiste Melin27, L. Mendes39, A. Mennella17, A. Mennella18, M. Migliaccio4, Marius Millea58, Subhasish Mitra9, Subhasish Mitra68, M.-A. Miville-Deschênes2, M.-A. Miville-Deschênes19, A. Moneti14, L. Montier7, L. Montier6, Gianluca Morgante17, Daniel J. Mortlock33, Adam Moss69, Dipak Munshi1, J. A. Murphy70, Pavel Naselsky31, Federico Nati29, Paolo Natoli71, Paolo Natoli22, Calvin B. Netterfield19, Hans Ulrik Nørgaard-Nielsen53, F. Noviello13, Dmitry Novikov72, I. D. Novikov72, I. D. Novikov31, C. A. Oxborrow53, F. Paci5, L. Pagano35, F. Pajot2, Roberta Paladini9, Daniela Paoletti17, Bruce Partridge73, F. Pasian17, G. Patanchon3, T. J. Pearson9, O. Perdereau52, L. Perotto25, Francesca Perrotta5, Valeria Pettorino67, F. Piacentini35, M. Piat3, E. Pierpaoli34, Davide Pietrobon9, Stéphane Plaszczynski52, Etienne Pointecouteau7, Etienne Pointecouteau6, G. Polenta17, G. Polenta71, L. Popa, G. W. Pratt3, G. Prézeau9, Simon Prunet14, J.-L. Puget2, Jörg P. Rachen74, Jörg P. Rachen37, William T. Reach75, Rafael Rebolo8, Rafael Rebolo76, M. Reinecke37, Mathieu Remazeilles2, Mathieu Remazeilles3, Mathieu Remazeilles13, C. Renault25, A. Renzi77, I. Ristorcelli7, I. Ristorcelli6, Graca Rocha9, C. Rosset3, M. Rossetti17, M. Rossetti18, G. Roudier9, G. Roudier3, G. Roudier26, B. Rouillé d'Orfeuil52, Michael Rowan-Robinson33, Jose Alberto Rubino-Martin76, Jose Alberto Rubino-Martin8, Ben Rusholme9, Najla Said35, Valentina Salvatelli35, Valentina Salvatelli61, Laura Salvati35, M. Sandri17, D. Santos25, M. Savelainen55, Giorgio Savini16, Douglas Scott78, Michael Seiffert9, Paolo Serra2, E. P. S. Shellard4, Locke D. Spencer1, M. Spinelli52, V. Stolyarov4, V. Stolyarov79, V. Stolyarov72, R. Stompor3, R. Sudiwala1, R. A. Sunyaev72, R. A. Sunyaev37, D. Sutton4, A.-S. Suur-Uski55, J.-F. Sygnet14, J. A. Tauber39, Luca Terenzi17, Luca Terenzi80, L. Toffolatti17, L. Toffolatti8, L. Toffolatti46, M. Tomasi17, M. Tomasi18, M. Tristram52, Tiziana Trombetti22, Tiziana Trombetti17, M. Tucci60, J. Tuovinen81, Marc Türler60, G. Umana17, Luca Valenziano17, Jussi-Pekka Väliviita55, F. Van Tent52, P. Vielva8, Fabrizio Villa17, L. A. Wade9, Benjamin D. Wandelt14, Benjamin D. Wandelt82, Ingunn Kathrine Wehus9, Ingunn Kathrine Wehus40, Martin White21, Simon D. M. White37, Althea Wilkinson13, D. Yvon27, Andrea Zacchei17, Andrea Zonca66 
Cardiff University1, Université Paris-Saclay2, Paris Diderot University3, University of Cambridge4, International School for Advanced Studies5, Hoffmann-La Roche6, University of Toulouse7, Spanish National Research Council8, California Institute of Technology9, Istituto Nazionale di Fisica Nucleare10, University of Padua11, University of Granada12, University of Manchester13, Institut d'Astrophysique de Paris14, Joseph Fourier University15, University College London16, INAF17, University of Milan18, University of Toronto19, Lawrence Berkeley National Laboratory20, University of California, Berkeley21, University of Ferrara22, University of Oxford23, Télécom ParisTech24, University of Grenoble25, Centre national de la recherche scientifique26, DSM27, University of KwaZulu-Natal28, Princeton University29, Johns Hopkins University30, Niels Bohr Institute31, Stanford University32, Imperial College London33, University of Southern California34, Sapienza University of Rome35, Ludwig Maximilian University of Munich36, Max Planck Society37, Institut Universitaire de France38, European Space Agency39, University of Oslo40, Shahid Beheshti University41, University of Chicago42, National Taiwan University43, Nordic Institute for Theoretical Physics44, Stockholm University45, University of Oviedo46, University of Warsaw47, University of Trieste48, University of Sydney49, CERN50, McGill University51, University of Paris-Sud52, Technical University of Denmark53, Florida State University54, University of Helsinki55, European Southern Observatory56, Atacama Large Millimeter Submillimeter Array57, University of California, Davis58, African Institute for Mathematical Sciences59, University of Geneva60, Aix-Marseille University61, Aalto University62, Helsinki Institute of Physics63, RWTH Aachen University64, University of Sussex65, University of California, Santa Barbara66, Heidelberg University67, Savitribai Phule Pune University68, University of Nottingham69, National University of Ireland70, Agenzia Spaziale Italiana71, Russian Academy of Sciences72, Haverford College73, Radboud University Nijmegen74, Universities Space Research Association75, University of La Laguna76, University of Rome Tor Vergata77, University of British Columbia78, Kazan Federal University79, Università degli Studi eCampus80, Trinity College, Dublin81, University of Illinois at Urbana–Champaign82
Abstract: This paper presents cosmological results based on full-mission Planck observations of temperature and polarization anisotropies of the cosmic microwave background (CMB) radiation. Our results are in very good agreement with the 2013 analysis of the Planck nominal-mission temperature data, but with increased precision. The temperature and polarization power spectra are consistent with the standard spatially-flat 6-parameter ΛCDM cosmology with a power-law spectrum of adiabatic scalar perturbations (denoted “base ΛCDM” in this paper). From the Planck temperature data combined with Planck lensing, for this cosmology we find a Hubble constant, H0 = (67.8 ± 0.9) km s-1Mpc-1, a matter density parameter Ωm = 0.308 ± 0.012, and a tilted scalar spectral index with ns = 0.968 ± 0.006, consistent with the 2013 analysis. Note that in this abstract we quote 68% confidence limits on measured parameters and 95% upper limits on other parameters. We present the first results of polarization measurements with the Low Frequency Instrument at large angular scales. Combined with the Planck temperature and lensing data, these measurements give a reionization optical depth of τ = 0.066 ± 0.016, corresponding to a reionization redshift of . These results are consistent with those from WMAP polarization measurements cleaned for dust emission using 353-GHz polarization maps from the High Frequency Instrument. We find no evidence for any departure from base ΛCDM in the neutrino sector of the theory; for example, combining Planck observations with other astrophysical data we find Neff = 3.15 ± 0.23 for the effective number of relativistic degrees of freedom, consistent with the value Neff = 3.046 of the Standard Model of particle physics. The sum of neutrino masses is constrained to ∑ mν < 0.23 eV. The spatial curvature of our Universe is found to be very close to zero, with | ΩK | < 0.005. Adding a tensor component as a single-parameter extension to base ΛCDM we find an upper limit on the tensor-to-scalar ratio of r0.002< 0.11, consistent with the Planck 2013 results and consistent with the B-mode polarization constraints from a joint analysis of BICEP2, Keck Array, and Planck (BKP) data. Adding the BKP B-mode data to our analysis leads to a tighter constraint of r0.002 < 0.09 and disfavours inflationarymodels with a V(φ) ∝ φ2 potential. The addition of Planck polarization data leads to strong constraints on deviations from a purely adiabatic spectrum of fluctuations. We find no evidence for any contribution from isocurvature perturbations or from cosmic defects. Combining Planck data with other astrophysical data, including Type Ia supernovae, the equation of state of dark energy is constrained to w = −1.006 ± 0.045, consistent with the expected value for a cosmological constant. The standard big bang nucleosynthesis predictions for the helium and deuterium abundances for the best-fit Planck base ΛCDM cosmology are in excellent agreement with observations. We also constraints on annihilating dark matter and on possible deviations from the standard recombination history. In neither case do we find no evidence for new physics. The Planck results for base ΛCDM are in good agreement with baryon acoustic oscillation data and with the JLA sample of Type Ia supernovae. However, as in the 2013 analysis, the amplitude of the fluctuation spectrum is found to be higher than inferred from some analyses of rich cluster counts and weak gravitational lensing. We show that these tensions cannot easily be resolved with simple modifications of the base ΛCDM cosmology. Apart from these tensions, the base ΛCDM cosmology provides an excellent description of the Planck CMB observations and many other astrophysical data sets.

10,334 citations

Journal ArticleDOI
24 Mar 2010-BMJ
Abstract: The CONSORT statement is used worldwide to improve the reporting of randomised controlled trials. Kenneth Schulz and colleagues describe the latest version, CONSORT 2010, which updates the reporting guideline based on new methodological evidence and accumulating experience. To encourage dissemination of the CONSORT 2010 Statement, this article is freely accessible on and will also be published in the Lancet, Obstetrics and Gynecology, PLoS Medicine, Annals of Internal Medicine, Open Medicine, Journal of Clinical Epidemiology, BMC Medicine, and Trials.

10,189 citations

Proceedings Article
01 Jan 2019-
TL;DR: This paper details the principles that drove the implementation of PyTorch and how they are reflected in its architecture, and explains how the careful and pragmatic implementation of the key components of its runtime enables them to work together to achieve compelling performance.
Abstract: Deep learning frameworks have often focused on either usability or speed, but not both. PyTorch is a machine learning library that shows that these two goals are in fact compatible: it was designed from first principles to support an imperative and Pythonic programming style that supports code as a model, makes debugging easy and is consistent with other popular scientific computing libraries, while remaining efficient and supporting hardware accelerators such as GPUs. In this paper, we detail the principles that drove the implementation of PyTorch and how they are reflected in its architecture. We emphasize that every aspect of PyTorch is a regular Python program under the full control of its user. We also explain how the careful and pragmatic implementation of the key components of its runtime enables them to work together to achieve compelling performance. We demonstrate the efficiency of individual subsystems, as well as the overall speed of PyTorch on several commonly used benchmarks.

9,926 citations


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