820 resultados para sexual and gender-based violence


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Accurate in silico models for the quantitative prediction of the activity of G protein-coupled receptor (GPCR) ligands would greatly facilitate the process of drug discovery and development. Several methodologies have been developed based on the properties of the ligands, the direct study of the receptor-ligand interactions, or a combination of both approaches. Ligand-based three-dimensional quantitative structure-activity relationships (3D-QSAR) techniques, not requiring knowledge of the receptor structure, have been historically the first to be applied to the prediction of the activity of GPCR ligands. They are generally endowed with robustness and good ranking ability; however they are highly dependent on training sets. Structure-based techniques generally do not provide the level of accuracy necessary to yield meaningful rankings when applied to GPCR homology models. However, they are essentially independent from training sets and have a sufficient level of accuracy to allow an effective discrimination between binders and nonbinders, thus qualifying as viable lead discovery tools. The combination of ligand and structure-based methodologies in the form of receptor-based 3D-QSAR and ligand and structure-based consensus models results in robust and accurate quantitative predictions. The contribution of the structure-based component to these combined approaches is expected to become more substantial and effective in the future, as more sophisticated scoring functions are developed and more detailed structural information on GPCRs is gathered.

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Ecological speciation has been the subject of intense research in evolutionary biology but the genetic basis of the actual mechanism driving reproductive isolation has rarely been identified. The extreme polymorphism of the major histocompatibility complex (MHC), probably maintained by parasite-mediated selection, has been proposed as a potential driver of population divergence. We performed an integrative field and experimental study using three-spined stickleback river and lake ecotypes. We characterized their parasite load and variation at MHC class II loci. Fish from lakes and rivers harbor contrasting parasite communities and populations possess different MHC allele pools that could be the result of a combined action of genetic drift and parasite-mediated selection. We show that individual MHC class II diversity varies among populations and is lower in river ecotypes. Our results suggest the action of homogenizing selection within habitat type and diverging selection between habitat types. Finally, reproductive isolation was suggested by experimental evidence: in a flow channel design females preferred assortatively the odor of their sympatric male. This demonstrates the role of olfactory cues in maintaining reproductive isolation between diverging fish ecotypes.

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This paper investigates the control and operation of doubly-fed induction generator (DFIG) and fixed-speed induction generator (FSIG) based wind farms under unbalanced grid conditions. A DFIG system model suitable for analyzing unbalanced operation is developed, and used to assess the impact of an unbalanced supply on DFIG and FSIG operation. Unbalanced voltage at DFIG and FSIG terminals can cause unequal heating on the stator windings, extra mechanical stresses and output power fluctuations. These problems are particularly serious for the FSIG-based wind farm without a power electronic interface to the grid. To improve the stability of a wind energy system containing both DFIG and FSIG based wind farms during network unbalance, a control strategy of unbalanced voltage compensation by the DFIG systems is proposed. The DFIG system compensation ability and the impact of transmission network impedance are illustrated. The simulation results implemented in Matlab/Simulink show that the proposed DFIG control system improves not only its own performance, but also the stability of the FSIG system with the same grid connection point during network unbalance.

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Recent thinking on open innovation and the knowledge-based economy have stressed the importance of external knowledge sources in stimulating innovation. Policy-makers have recognised this, establishing publicly funded Centres of R&D Excellence with the objective of stimulating industry–science links and localised innovation spillovers. Here, we examine the contrasting IP management practices of a group of 18 university- and company-based R&D centres supported by the same regional programme. Our analysis covers all but one of the Centres supported by the programme and suggests marked contrasts between the IP strategies of the university-based and company-based centres. This suggests the potential for very different types of knowledge spillovers from publicly funded R&D centres based in different types of organisations, and a range of alternative policy approaches to the future funding of R&D centres depending on policy-makers’ objectives.

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This study considers the possibility of auditing students’ ethical judgment being affected by two factors, namely ethical orientation and gender. While tests revealed that more idealistic students judged some unethical situations more strictly than less idealistic students, overall no significant relationship was found between ethical orientation and ethical judgment. The study also reported no significant relationship between gender and ethical judgment. Furthermore, males were as likely as females to be classified as high idealists. Overall, the findings from the current study inform auditing educators that discriminating among students on the basis of ethical orientation and gender may not assist in stimulating students’ discussion and resolution of ethical dilemmas.

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A rapid screening assay (9 min/sample) has been developed and validated for the detection of deoxynivalenol in durum wheat, wheat products, and maize-based baby foods using an SPA biosensor. Through a single laboratory validation, the limits of detection (LOD) for wheat, wheat-based breakfast cereal, and maize-based baby food were 57, 9, and 6 mu g/kg, respectively. Intra-assay and interassay precisions were calculated for each matrix at the maximum and half-maximum European Union regulatory limits and expressed as the coefficient of variation (CV). All CVs fell below 10% with the exception of the between-run CV for breakfast cereal. Recoveries at the concentrations tested ranged from 92 to 115% for all matrices. Action limits of 161, 348, and 1378 mu g/kg were calculated for baby food, wheat-based breakfast cereal, and wheat, respectively, and the linear range of the assay was determined as 250-2000 mu g/kg.

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A rapid surface plasmon resonance (SPR) screening assay has been developed for the combined detection of T-2 and HT-2 toxins in naturally contaminated cereals using a sensor chip coated with an HT-2 toxin derivative and a monoclonal antibody. The antibody raised against HT-2 displayed high cross-reactivity with T-2 toxin while there was no cross-reaction observed with other commonly occurring trichothecenes. A simple extraction procedure using 40% methanol was applied to baby food, breakfast cereal, and wheat samples prior to biosensor analysis. Limits of detection (LOD) for each matrix were determined as 25 mu g kg(-1) for baby food and breakfast cereal and 26 mu g kg(-1) for wheat. Intra-assay precision (n = 6) was calculated for each matrix. The results were expressed as the relative standard deviation and determined as 2.8% (100 mu g kg(-1)) and 1.8% (200 mu g kg(-1)) in breakfast cereal, 4.6% (50 mu g kg(-1)) and 3.6% (100 mu g kg(-1)) in wheat and 0.97% (25 mu g kg(-1)) and 6.3% (50 mu g kg(-1)) in baby food. Between run precision (n = 3) performed at the same levels yielded relative standard deviations of 6.7% and 3.9% for breakfast cereals, 3.3% and 1.6% for wheat and 6.8% and 0.08% for baby food, respectively. (C) 2010 Elsevier B.V. All rights reserved.

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The need for chemical and biological entities of predetermined selectivity and affinity towards target analytes is greater than ever, in applications such as environmental monitoring, bioterrorism detection and analysis of natural toxin contaminants in the food chain.