513 research outputs found
Testing Tests: Determination of the Efficacy of Prejudice Measures
Numerous scales and measures exist to determine the level of prejudice in an individual. This study compared six prejudice measures in an attempt to explore the strengths and faults of each measure. Each measure was correlated with a Social Desirability Scale, and each explicit measure was administered both within and without a Bogus Pipeline procedure to determine how susceptible it is to participant deception. In an examination of the Modern Racism Scale, Old Fashioned Racism Scale, Subtle Prejucide Scale, Blatant Prejudice Scale, Implicit Association Test and Seat Choice Task, none of the explicit measures correlated with the implicit measures. In addition, the implicit measures could not distinguish between target groups of blacks, females and a control group
An analytical model based on radiative heating for the determination of safety distances for wildland fires
International audienceThe radiative heat transfer is often the main thermal impact of a wildfire on people fighting the fire or on structures. Thus, the estimation of the radiation coming from the fire font and hitting a target is of primary importance for forest and urban managers. A new flame model based on the solid flame assumption is developed by considering a finite fire front width. The realistic description of finite fire front widths allows proposing a new criterion for the estimation of the radiative impact of the fire, which is based on the ratio fire front width/ flame length, opposed to the classical approach of considering only the flame length. The new model needs to be solved numerically so an analytical approximation is proposed to obtain a simple and useful formulation of the acceptable safety distance. A sensivity analysis is conducted on the different physical and geometrical parameters used to define the flame front. This analysis shows that the flame temperature is the most sensitive parameter. The results of the analytical model are compared with the numerical solution of the flame model and previous approaches based only on flame length. The results show that the analytical model is a good approximation of the numerical approach and displays realistic estimations of the acceptable safety distance for different fire front characteristics
Three-points interfacial quadrature for geometrical source terms on nonuniform grids
International audienceThis paper deals with numerical (finite volume) approximations, on nonuniform meshes, for ordinary differential equations with parameter-dependent fields. Appropriate discretizations are constructed over the space of parameters, in order to guarantee the consistency in presence of variable cells' size, for which -error estimates, , are proven. Besides, a suitable notion of (weak) regularity for nonuniform meshes is introduced in the most general case, to compensate possibly reduced consistency conditions, and the optimality of the convergence rates with respect to the regularity assumptions on the problem's data is precisely discussed. This analysis attempts to provide a basic theoretical framework for the numerical simulation on unstructured grids (also generated by adaptive algorithms) of a wide class of mathematical models for real systems (geophysical flows, biological and chemical processes, population dynamics)
Association between the A-2518G polymorphism in the monocyte chemoattractant protein-1 gene and insulin resistance and Type 2 diabetes mellitus
Aims/hypothesis: The molecular mechanisms of obesity-related insulin resistance are incompletely understood. Macrophages accumulate in adipose tissue of obese individuals. In obesity, monocyte chemoattractant protein-1 (MCP-1), a key chemokine in the process of macrophage accumulation, is overexpressed in adipose tissue. MCP-1 is an insulin-responsive gene that continues to respond to exogenous insulin in insulin-resistant adipocytes and mice. MCP-1 decreases insulin-stimulated glucose uptake into adipocytes. The A-2518G polymorphism in the distal regulatory region of MCP-1 may regulate gene expression. The aim of this study was to investigate the impact of this gene polymorphism on insulin resistance. Methods: We genotyped the Ludwigshafen Risk and Cardiovascular Health (LURIC) cohort (n=3307). Insulin resistance, estimated by homeostasis model assessment, and Type 2 diabetes were diagnosed in 803 and 635 patients respectively. Results: Univariate analysis revealed that plasma MCP-1 levels were significantly and positively correlated with WHR (p=0.011), insulin resistance (p=0.0097) and diabetes (p<0.0001). Presence of the MCP-1 G-2518 allele was associated with decreased plasma MCP-1 (p=0.017), a decreased prevalence of insulin resistance (odds ratio [OR]=0.82, 95% CI: 0.70-0.97, p=0.021) and a decreased prevalence of diabetes (OR=0.80, 95% CI: 0.67-0.96, p=0.014). In multivariate analysis, the G allele retained statistical significance as a negative predictor of insulin resistance (OR=0.78, 95% CI: 0.65-0.93, p=0.0060) and diabetes (OR=0.80, 95% CI: 0.66-0.96, p=0.018). Conclusions/interpretation: In a large cohort of Caucasians, the MCP-1 G-2518 gene variant was significantly and negatively correlated with plasma MCP-1 levels and the prevalence of insulin resistance and Type 2 diabetes. These results add to recent evidence supporting a role for MCP-1 in pathologies associated with hyperinsulinaemi
Resistant hypertension: drug-eluting balloon for revascularization of bilateral renal fibromuscular dysplasia
Long-term impact of maternal high-fat diet on offspring cardiac health: role of micro-RNA biogenesis.
Heart failure is a worldwide leading cause of death. Diet and obesity are particularly of high concern in heart disease etiology. Gravely, altered nutrition during developmental windows of vulnerability can have long-term impact on heart health; however, the underlying mechanisms are poorly understood. In the understanding of the initiation of chronic diseases related to developmental exposure to environmental challenges, deregulations in epigenetic mechanisms including micro-RNAs have been proposed as key events. In this context, we aimed at delineating the role of micro-RNAs in the programming of cardiac alterations induced by early developmental exposure to nutritional imbalance. To reach our aim, we developed a human relevant model of developmental exposure to nutritional imbalance by maternally exposing rat to high-fat diet during gestation and lactation. In this model, offspring exposed to maternal high-fat diet developed cardiac hypertrophy and increased extracellular matrix depot compared to those exposed to chow diet. Microarray approach performed on cardiac tissue allowed the identification of a micro-RNA subset which was down-regulated in high-fat diet-exposed animals and which were predicted to regulate transforming growth factor-beta (TGFβ)-mediated remodeling. As indicated by in vitro approaches and gene expression measurement in the heart of our animals, decrease in DiGeorge critical region 8 (DGCR8) expression, involved in micro-RNA biogenesis, seems to be a critical point in the alterations of the micro-RNA profile and the TGFβ-mediated remodeling induced by maternal exposure to high-fat diet. Finally, increasing DGCR8 activity and/or expression through hemin treatment in vitro revealed its potential in the rescue of the pro-fibrotic phenotype in cardiomyocytes driven by DGCR8 decrease. These findings suggest that cardiac alterations induced by maternal exposure to high-fat diet is related to abnormalities in TGFβ pathway and associated with down-regulated micro-RNA processing. Our study highlighted DGCR8 as a potential therapeutic target for heart diseases related to early exposure to dietary challenge
Long-Term Recovery After Endothelial Colony-Forming Cells or Human Umbilical Cord Blood Cells Administration in a Rat Model of Neonatal Hypoxic-Ischemic Encephalopathy.
Neonatal hypoxic-ischemic encephalopathy (NHIE) is a dramatic perinatal complication, associated with poor neurological prognosis despite neuroprotection by therapeutic hypothermia, in the absence of an available curative therapy. We evaluated and compared ready-to-use human umbilical cord blood cells (HUCBC) and bankable but allogeneic endothelial progenitors (ECFC) as cell therapy candidate for NHIE. We compared benefits of HUCBC and ECFC transplantation 48 hours after injury in male rat NHIE model, based on the Rice-Vannucci approach. Based on behavioral tests, immune-histological assessment and metabolic imaging of brain perfusion using single photon emission computed tomography (SPECT), HUCBC, or ECFC administration provided equally early and sustained functional benefits, up to 8 weeks after injury. These results were associated with total normalization of injured hemisphere cerebral blood flow assessed by SPECT/CT imaging. In conclusion, even if ECFC represent an efficient candidate, HUCBC autologous criteria and easier availability make them the ideal candidate for hypoxic-ischemic cell therapy. Stem Cells Translational Medicine 2017;6:1987-1996
Magnetic Hamiltonian and phase diagram of the quantum spin liquid Ca10Cr7O28
A spin liquid is a new state of matter with topological order where the spin moments continue to fluctuate coherently down to the lowest temperatures rather than develop static long range magnetic order as found in conventional magnets. For spin liquid behavior to arise in a material the magnetic Hamiltonian must be frustrated , where the combination of lattice geometry, interactions, and anisotropies gives rise to competing spin arrangements in the ground state. Theoretical Hamiltonians which produce spin liquids are spin ice, the Kitaev honeycomb model, and the kagome antiferromagnet. Spin liquid behavior, however, in real materials is rare because they can only approximate these Hamiltonians and often have weak higher order terms that destroy the spin liquid state. Ca10Cr7O28 is a new quantum spin liquid candidate with magnetic Cr5 ions that possess quantum spin number S . The spins are entirely dynamic in the ground state and the excitation spectrum is broad and diffuse, as is typical of spinons which are the excitations of a spin liquid. In this paper we determine the Hamiltonian of Ca10Cr7O28 using inelastic neutron scattering under high magnetic field to induce a field polarized paramagnetic ground state and spin wave excitations that can be fitted to extract the interactions. We further explore the phase diagram by using inelastic neutron scattering and heat capacity measurements and establish the boundaries of the spin liquid phase as a function of magnetic field and temperature. Our results show that Ca10Cr7O28 consists of distorted kagome bilayers with several isotropic ferromagnetic and antiferromagnetic interactions where, unexpectedly, the ferromagnetic interactions are stronger than the antiferromagnetic ones. This complex Hamiltonian does not correspond to any known spin liquid model and points to new directions in the search for quantum spin liquid behavio
Fire spread across pine needle fuel beds: characterization of temperature and velocity distributions within the fire plume
From multiple aspect trajectories to predictive analysis: a case study on fishing vessels in the Northern Adriatic sea
In this paper we model spatio-temporal data describing the fishing activities in the Northern Adriatic Sea over four years. We build, implement and analyze a database based on the fusion of two complementary data sources: trajectories from fishing vessels (obtained from terrestrial Automatic Identification System, or AIS, data feed) and fish catch reports (i.e., the quantity and type of fish caught) of the main fishing market of the area. We present all the phases of the database creation, starting from the raw data and proceeding through data exploration, data cleaning, trajectory reconstruction and semantic enrichment. We implement the database by using MobilityDB, an open source geospatial trajectory data management and analysis platform. Subsequently, we perform various analyses on the resulting spatio-temporal database, with the goal of mapping the fishing activities on some key species, highlighting all the interesting information and inferring new knowledge that will be useful for fishery management. Furthermore, we investigate the use of machine learning methods for predicting the Catch Per Unit Effort (CPUE), an indicator of the fishing resources exploitation in order to drive specific policy design. A variety of prediction methods, taking as input the data in the database and environmental factors such as sea temperature, waves height and Clorophill-a, are put at work in order to assess their prediction ability in this field. To the best of our knowledge, our work represents the first attempt to integrate fishing ships trajectories derived from AIS data, environmental data and catch data for spatio-temporal prediction of CPUE – a challenging task
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