Institution
University of Lorraine
Education•Nancy, France•
About: University of Lorraine is a education organization based out in Nancy, France. It is known for research contribution in the topics: Population & Context (language use). The organization has 11942 authors who have published 25010 publications receiving 425227 citations. The organization is also known as: Lorraine University.
Papers published on a yearly basis
Papers
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TL;DR: A 3D anisotropic micropolar continuum model of vertebral trabecular bone is presently developed accounting for the influence of microstructure-related scale effects on the macroscopic effective properties.
Abstract: A 3D anisotropic micropolar continuum model of vertebral trabecular bone is presently developed accounting for the influence of microstructure-related scale effects on the macroscopic effective properties. Vertebral trabecular bone is modeled as a cellular material with an idealized periodic structure made of open 3D cells. The micromechanical approach relies on the discrete homogenization technique considering lattice microrotations as additional degrees of freedom at the microscale. The effective elastic properties of 3D lattices made of articulated beams taking into account axial, transverse shearing, flexural, and torsional deformations of the cell struts are derived as closed form expressions of the geometrical and mechanical microparameters. The scaling laws of the effective moduli versus density are determined in situations of low and high effective densities to assess the impact of the transverse shear deformation. The classical and micropolar effective moduli and the internal flexural and torsional lengths are identified versus the same microparameters. A finite element model of the local architecture of the trabeculae gives values of the effective moduli that are in satisfactory agreement with the homogenized moduli.
98 citations
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TL;DR: The results suggest that motivation concepts of the Self-Determination Theory can be adequately combined with the Health Belief Model to understand vaccination behaviour.
Abstract: Background and objective Seasonal influenza is frequent among students and often responsible for impaired academic performance and lower levels of general health. However, the vaccination rate in this population is very low. As the seasonal influenza vaccine is not compulsory in France, it is important to improve the vaccination uptake by identifying predictors of both intention and behaviour. This study investigated the effect of decisional balance, motivation and self-efficacy on vaccination acceptance using the Extended Health Belief Model (HBM) and Self-Determination Theory (SDT). Design and Main Outcome Measures University students were invited to fill in an online survey to answer questions about their influenza vaccination intention, and HBM and SDT constructs. A one-year longitudinal follow-up study investigated vaccination behaviour. Results Autonomous motivation and self-efficacy significantly influenced the intention to have the influenza vaccine, and vaccine behaviour at one-year follow-up. Intention predicted a significant proportion of variation (51%) in behaviour, and mediated the effect of these predictors on vaccination behaviour. Conclusion These results suggest that motivation concepts of the Self-Determination Theory can be adequately combined with the Health Belief Model to understand vaccination behaviour.
98 citations
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TL;DR: Pine tannin foams with and without formaldehyde were prepared for the first time as mentioned in this paper, and their characteristics were tested as regards stress-strain curves, thermal conductivity, Young's modulus, compression strength, densification, density rate and energy absorbed under compression.
98 citations
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TL;DR: The data reveal in the aldosterone/salt hypertension model that MR activation specifically in VSMC leads to the arterial stiffening by modulation of cell-matrix attachment proteins independent of major vascular structural changes.
Abstract: Arterial stiffness is recognized as a risk factor for many cardiovascular diseases. Aldosterone via its binding to and activation of the mineralocorticoid receptors (MRs) is a main regulator of blood pressure by controlling renal sodium reabsorption. Although both clinical and experimental data indicate that MR activation by aldosterone is involved in arterial stiffening, the molecular mechanism is not known. In addition to the kidney, MR is expressed in both endothelial and vascular smooth muscle cells (VSMCs), but the specific contribution of the VSMC MR to aldosterone-induced vascular stiffness remains to be explored. To address this question, we generated a mouse model with conditional inactivation of the MR in VSMC (MRSMKO). MRSMKO mice show no alteration in renal sodium handling or vascular structure, but they have decreased blood pressure when compared with control littermate mice. In vivo at baseline, large vessels of mutant mice presented with normal elastic properties, whereas carotids displayed a smaller diameter when compared with those of the control group. As expected after aldosterone/salt challenge, the arterial stiffness increased in control mice; however, it remained unchanged in MRSMKO mice, without significant modification in vascular collagen/elastin ratio. Instead, we found that the fibronectin/α5-subunit integrin ratio is profoundly altered in MRSMKO mice because the induction of α5 expression by aldosterone/salt challenge is prevented in mice lacking VSMC MR. Altogether, our data reveal in the aldosterone/salt hypertension model that MR activation specifically in VSMC leads to the arterial stiffening by modulation of cell-matrix attachment proteins independent of major vascular structural changes.
98 citations
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TL;DR: The challenges of Big Data are discussed and existing Big Data frameworks are surveyed and a presentation of best practices related to the use of studied frameworks in several application domains such as machine learning, graph processing and real-world applications is presented.
98 citations
Authors
Showing all 12161 results
Name | H-index | Papers | Citations |
---|---|---|---|
Jonathan I. Epstein | 138 | 1121 | 80975 |
Peter Tugwell | 129 | 948 | 125480 |
David Brown | 105 | 1257 | 46827 |
Faiez Zannad | 103 | 839 | 90737 |
Sabu Thomas | 102 | 1554 | 51366 |
Francis Martin | 98 | 733 | 43991 |
João F. Mano | 97 | 822 | 36401 |
Jonathan A. Epstein | 94 | 299 | 27492 |
Muhammad Imran | 94 | 3053 | 51728 |
Laurent Peyrin-Biroulet | 90 | 901 | 34120 |
Athanase Benetos | 83 | 391 | 31718 |
Michel Marre | 82 | 444 | 39052 |
Bruno Rossion | 80 | 337 | 21902 |
Lyn March | 78 | 367 | 62536 |
Alan J. M. Baker | 76 | 234 | 26080 |