Institution
University of Grenoble
Education•Saint-Martin-d'Hères, France•
About: University of Grenoble is a education organization based out in Saint-Martin-d'Hères, France. It is known for research contribution in the topics: Population & Large Hadron Collider. The organization has 25658 authors who have published 45143 publications receiving 909760 citations.
Topics: Population, Large Hadron Collider, Planet, Nanowire, Stars
Papers published on a yearly basis
Papers
More filters
••
Betty Abelev1, A. Abrahantes Quintana, Dagmar Adamová2, Andrew Marshall Adare3 +1004 more•Institutions (82)
TL;DR: The first measurements of the invariant differential cross sections of inclusive pi(0) and eta meson production at mid-rapidity in proton-proton collisions root s = 0.9 TeV and root s= 7 TeV are reported in this paper.
170 citations
••
Central Queensland University1, University of Social Sciences and Humanities2, University of Colorado Colorado Springs3, University of New South Wales4, Tel Aviv University5, Charité6, Université du Québec à Trois-Rivières7, University College London8, University of Stirling9, Sanquin10, University of Manchester11, University of Grenoble12, University of Helsinki13, University of Cyprus14, University of New Mexico15, Curtin University16, University of Lisbon17, Newcastle University18, University of Paris19, University of Zurich20, Columbia University21, VU University Amsterdam22, Maastricht University23, Utrecht University24, University of Amsterdam25, Innsbruck Medical University26, University of Hamburg27, University of North Carolina at Chapel Hill28, University of Konstanz29
TL;DR: The Synergy Expert Group comprised world-leading researchers in health and social psychology and behavioural medicine who convened to discuss priority issues in planning interventions in health contexts and develop a set of recommendations for future research and practice.
Abstract: The current article details a position statement and recommendations for future research and practice on planning and implementation intentions in health contexts endorsed by the Synergy Expert Group. The group comprised world-leading researchers in health and social psychology and behavioural medicine who convened to discuss priority issues in planning interventions in health contexts and develop a set of recommendations for future research and practice. The expert group adopted a nominal groups approach and voting system to elicit and structure priority issues in planning interventions and implementation intentions research. Forty-two priority issues identified in initial discussions were further condensed to 18 key issues, including definitions of planning and implementation intentions and 17 priority research areas. Each issue was subjected to voting for consensus among group members and formed the basis of the position statement and recommendations. Specifically, the expert group endorsed statements and recommendations in the following areas: generic definition of planning and specific definition of implementation intentions, recommendations for better testing of mechanisms, guidance on testing the effects of moderators of planning interventions, recommendations on the social aspects of planning interventions, identification of the preconditions that moderate effectiveness of planning interventions and recommendations for research on how people use plans.
169 citations
••
TL;DR: In this article, the authors used the DL dust model to generate maps of the dust mass surface density, the dust optical extinction AV, and the starlight intensity heating the bulk of the Dust, parametrized by Umin.
Abstract: We present all-sky modelling of the high resolution Planck, IRAS, and WISE infrared (IR) observations using the physical dust model presented by Draine & Li in 2007 (DL, ApJ, 657, 810). We study the performance and results of this model, and discuss implications for future dust modelling. The present work extends the DL dust modelling carried out on nearby galaxies using Herschel and Spitzer data to Galactic dust emission. We employ the DL dust model to generate maps of the dust mass surface density ΣMd, the dust optical extinction AV, and the starlight intensity heating the bulk of the dust, parametrized by Umin. The DL model reproduces the observed spectral energy distribution (SED) satisfactorily over most of the sky, with small deviations in the inner Galactic disk and in low ecliptic latitude areas, presumably due to zodiacal light contamination. In the Andromeda galaxy (M31), the present dust mass estimates agree remarkably well (within 10%) with DL estimates based on independent Spitzer and Herschel data. We compare the DL optical extinction AV for the diffuse interstellar medium (ISM) with optical estimates for approximately 2 × 105 quasi-stellar objects (QSOs) observed inthe Sloan Digital Sky Survey (SDSS). The DL AV estimates are larger than those determined towards QSOs by a factor of about 2, which depends on Umin. The DL fitting parameter Umin, effectively determined by the wavelength where the SED peaks, appears to trace variations in the far-IR opacity of the dust grains per unit AV, and not only in the starlight intensity. These results show that some of the physical assumptions of the DL model will need to be revised. To circumvent the model deficiency, we propose an empirical renormalization of the DL AV estimate, dependent of Umin, which compensates for the systematic differences found with QSO observations. This renormalization, made to match the AV estimates towards QSOs, also brings into agreement the DL AV estimates with those derived for molecular clouds from the near-IR colours of stars in the 2 micron all sky survey (2MASS). The DL model and the QSOs data are also used to compress the spectral information in the Planck and IRAS observations for the diffuse ISM to a family of 20 SEDs normalized per AV, parameterized by Umin, which may be used to test and empirically calibrate dust models. The family of SEDs and the maps generated with the DL model are made public in the Planck Legacy Archive.
169 citations
••
15 Mar 2010TL;DR: This work proposes GGen -- a unified and standard implementation of classical task graph generation methods used in the scheduling domain, and provides an in-depth analysis of each generation method, emphasizing important graph properties that may influence scheduling algorithms.
Abstract: In parallel and distributed systems, validation of scheduling heuristics is usually done by simulation on randomly generated synthetic workloads, typically represented by task graphs. Since there is no single generation method that models all possible workloads for scheduling problems, researchers often re-implement the classical generation algorithms or even implement ad hoc ones. A bad choice of generation method can mislead the validation of the algorithm due to biases it can induce. Moreover, different implementations of the same randomized generation method may produce slightly different graphs. These problems can harm the experimental comparison of scheduling algorithms. In order to provide a comparison basis we propose GGen -- a unified and standard implementation of classical task graph generation methods used in the scheduling domain. We also provide an in-depth analysis of each generation method, emphasizing important graph properties that may influence scheduling algorithms.
169 citations
••
TL;DR: In this article, new and efficient derivations of the general existence and uniqueness theorems are given, plus a constructive procedure for obtaining the desired approximations, and several practical examples illustrate the methods.
Abstract: : The spline interpolation problem was generalized by Atteia to an abstract minimization problem in a Hilbert space setting. In this paper, new and efficient derivations of the general existence and uniqueness theorems are given, plus a constructive procedure for obtaining the desired approximations. Several practical examples illustrate the methods. (Author)
169 citations
Authors
Showing all 25961 results
Name | H-index | Papers | Citations |
---|---|---|---|
Dieter Lutz | 139 | 671 | 67414 |
Marcella Bona | 137 | 1391 | 92162 |
Nicolas Berger | 137 | 1581 | 96529 |
Cordelia Schmid | 135 | 464 | 103925 |
J. F. Macías-Pérez | 134 | 486 | 94715 |
Marina Cobal | 132 | 1078 | 85437 |
Lydia Roos | 132 | 1284 | 89435 |
Tetiana Hryn'ova | 131 | 1059 | 84260 |
Johann Collot | 131 | 1018 | 82865 |
Remi Lafaye | 131 | 1012 | 83281 |
Jan Stark | 131 | 1186 | 87025 |
Sabine Crépé-Renaudin | 129 | 1142 | 82741 |
Isabelle Wingerter-Seez | 129 | 930 | 79689 |
James Alexander | 129 | 886 | 75096 |
Jessica Levêque | 129 | 1006 | 70208 |