851 resultados para Interpersonal Sensitivity
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Gemstone Team FLIP (File Lending in Proximity)
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BACKGROUND: Breastfeeding is a leading cause of infant HIV-1 infection in the developing world, yet only a minority of infants exposed to HIV-1 via breastfeeding become infected. As a genetic bottleneck severely restricts the number of postnatally-transmitted variants, genetic or phenotypic properties of the virus Envelope (Env) could be important for the establishment of infant infection. We examined the efficiency of virologic functions required for initiation of infection in the gastrointestinal tract and the neutralization sensitivity of HIV-1 Env variants isolated from milk of three postnatally-transmitting mothers (n = 13 viruses), five clinically-matched nontransmitting mothers (n = 16 viruses), and seven postnatally-infected infants (n = 7 postnatally-transmitted/founder (T/F) viruses). RESULTS: There was no difference in the efficiency of epithelial cell interactions between Env virus variants from the breast milk of transmitting and nontransmitting mothers. Moreover, there was similar efficiency of DC-mediated trans-infection, CCR5-usage, target cell fusion, and infectivity between HIV-1 Env-pseudoviruses from nontransmitting mothers and postnatal T/F viruses. Milk Env-pseudoviruses were generally sensitive to neutralization by autologous maternal plasma and resistant to breast milk neutralization. Infant T/F Env-pseudoviruses were equally sensitive to neutralization by broadly-neutralizing monoclonal and polyclonal antibodies as compared to nontransmitted breast milk Env variants. CONCLUSION: Postnatally-T/F Env variants do not appear to possess a superior ability to interact with and cross a mucosal barrier or an exceptional resistance to neutralization that define their capability to initiate infection across the infant gastrointestinal tract in the setting of preexisting maternal antibodies.
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Most of the air quality modelling work has been so far oriented towards deterministic simulations of ambient pollutant concentrations. This traditional approach, which is based on the use of one selected model and one data set of discrete input values, does not reflect the uncertainties due to errors in model formulation and input data. Given the complexities of urban environments and the inherent limitations of mathematical modelling, it is unlikely that a single model based on routinely available meteorological and emission data will give satisfactory short-term predictions. In this study, different methods involving the use of more than one dispersion model, in association with different emission simulation methodologies and meteorological data sets, were explored for predicting best CO and benzene estimates, and related confidence bounds. The different approaches were tested using experimental data obtained during intensive monitoring campaigns in busy street canyons in Paris, France. Three relative simple dispersion models (STREET, OSPM and AEOLIUS) that are likely to be used for regulatory purposes were selected for this application. A sensitivity analysis was conducted in order to identify internal model parameters that might significantly affect results. Finally, a probabilistic methodology for assessing urban air quality was proposed.
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Three hundred participants, including volunteers from an obsessional support group, filled in questionnaires relating to disgust sensitivity, health anxiety, anxiety, fear of death, fear of contamination and obsessionality as part of an investigation into the involvement of disgust sensitivity in types of obsessions. Overall, the data supported the hypothesis that a relationship does exist between disgust sensitivity and the targeted variables. A significant predictive relationship was found between disgust sensitivity and total scores on the obsessive compulsive inventory (OCI; Psychological Assessment 10 (1998) 206) for both frequency and distress of symptomatology. Disgust sensitivity scores were significantly related to health anxiety scores and general anxiety scores and to all the obsessional subscales, with the exception of hoarding. Additionally, multiple regression analyses revealed that disgust sensitivity may be more specifically related to washing compulsions: frequency of washing behaviour was best predicted by disgust sensitivity scores. Washing distress scores were best predicted by health anxiety scores, though disgust sensitivity entered in the second model. It is suggested that further research on the relationship between disgust sensitivity and obsessionality could be helpful in refining the theoretical understanding of obsessions.
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The design and development of a comprehensive computational model of a copper stockpile leach process is summarized. The computational fluid dynamic software framework PHYSICA+ and various phenomena were used to model transport phenomena, mineral reaction kinetics, bacterial effects, and heat, energy and acid balances for the overall leach process. In this paper, the performance of the model is investigated, in particular its sensitvity to particle size and ore permeability. A combination of literature and laboratory sources was used to parameterize the model. The simulation results from the leach model are compared with closely controlled column pilot scale tests. The main performance characteristics (e.g. copper recovery rate) predicted by the model compare reasonably well with the experimental data and clearly reflect the qualitiative behavior of the process in many respects. The model is used to provide a measure of the sensitivity of ore permeability on leach behavior, and simulation results are examined for several different particle size distributions.
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The ocean plays an important role in regulating the climate, acting as a sink for carbon dioxide, perturbing the carbonate system and resulting in a slow decrease of seawater pH. Understanding the dynamics of the carbonate system in shelf sea regions is necessary to evaluate the impact of Ocean Acidification (OA) in these societally important ecosystems. Complex hydrodynamic and ecosystem coupled models provide a method of capturing the significant heterogeneity of these areas. However rigorous validation is essential to properly assess the reliability of such models. The coupled model POLCOMS–ERSEM has been implemented in the North Western European shelf with a new parameterization for alkalinity explicitly accounting for riverine inputs and the influence of biological processes. The model has been validated in a like with like comparison with North Sea data from the CANOBA dataset. The model shows good to reasonable agreement for the principal variables, physical (temperature and salinity), biogeochemical (nutrients) and carbonate system (dissolved inorganic carbon and total alkalinity), but simulation of the derived variables, pH and pCO2, are not yet fully satisfactory. This high uncertainty is attributed mostly to riverine forcing and primary production. This study suggests that the model is a useful tool to provide information on Ocean Acidification scenarios, but uncertainty on pH and pCO2 needs to be reduced, particularly when impacts of OA on ecosystem functions are included in the model systems.