986 resultados para Applied Behavioral Analysis


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Plasma levels of lipoprotein(a) _ Lp(a) _ are associated with cardiovascular risk (Danesh et al., 2000) and were long believed to be influenced by the LPA locus on chromosome 6q27 only. However, a recent report of Broeckel et al. (2002) suggested the presence of a second quantitative trait locus on chromosome 1 influencing Lp(a) levels. Using a two-locus model, we found no evidence for an additional Lp(a) locus on chromosome 1 in a linkage study among 483 dizygotic twin pairs.

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Increased professionalism in rugby has elicited rapid changes in the fitness profile of elite players. Recent research, focusing on the physiological and anthropometrical characteristics of rugby players, and the demands of competition are reviewed. The paucity of research on contemporary elite rugby players is highlighted, along with the need for standardised testing protocols. Recent data reinforce the pronounced differences in the anthropometric and physical characteristics of the forwards and backs. Forwards are typically heavier, taller, and have a greater proportion of body fat than backs. These characteristics are changing, with forwards developing greater total mass and higher muscularity. The forwards demonstrate superior absolute aerobic and anaerobic power, and Muscular strength. Results favour the backs when body mass is taken into account. The scaling of results to body mass can be problematic and future investigations should present results using power function ratios. Recommended tests for elite players include body mass and skinfolds, vertical jump, speed, and the multi-stage shuttle run. Repeat sprint testing is a possible avenue for more specific evaluation of players. During competition, high-intensity efforts are often followed by periods of incomplete recovery. The total work over the duration of a game is lower in the backs compared with the forwards; forwards spend greater time in physical contact with the opposition while the backs spend more time in free running, allowing them to cover greater distances. The intense efforts undertaken by rugby players place considerable stress on anaerobic energy sources, while the aerobic system provides energy during repeated efforts and for recovery. Training should focus on repeated brief high-intensity efforts with short rest intervals to condition players to the demands of the game. Training for the forwards should emphasise the higher work rates of the game, while extended rest periods can be provided to the backs. Players should not only be prepared for the demands of competition, but also the stress of travel and extreme environmental conditions. The greater professionalism of rugby union has increased scientific research in the sport; however, there is scope for significant refinement of investigations on the physiological demands of the game, and sports-specific testing procedures.

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ABSTRACT Earlier studies of cross-national differences in consumer behavior in different consumption sectors have verified that cultural differences have a strong influence on consumers. Despite the importance of cross-national analysis, no studies in the literature examine the moderating effects of nationality on the construction of behavioral intentions and their antecedents among cruise line passengers. This study investigates the moderating effects of nationality on the relationships between perceived value, satisfaction, trust and behavioral intentions among Spanish and (U.S.) American passengers of cruise lines that use Barcelona as home port and port-of-call. A theoretical model was tested with a total of 968 surveys. Structural equation models (SEMs) were used, by means of a multigroup analysis. Results of this study indicated that Spaniards showed stronger relationships between trust and behavioral intentions, and between emotional value and satisfaction. Americans presented stronger relationships between service quality and satisfaction, and between service quality and behavioral intentions.

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Improving the treatment of obesity remains a critical challenge. Several health behaviour change models, often based on a social-cognitive framework, have been used to design weight management interventions (Baranowski et al., 2003). However, most interventions have only produced modest weight reductions (Wadden et al., 2002) and socialcognitive variables have shown limited power to predict weight outcomes (Palmeira et al., 2007). Other predictors, and possibl alte nati e e planatory models, are needed to better understand the mechanisms by which weight loss and other obesity treatment-outcomes are brought about (Baranowski, 2006). Self-esteem is one of these possible mechanisms, because is commonly reported to change during the treatment, although these changes are not necessarily associated with weight loss (Blaine et al., 2007; Maciejewski et al., 2005). This possibility should be more evident if the program integrates regular exercise, as it promotes improvements in subjective well-being (Biddle & Mutrie, 2001), with possible influences on long-term behavioral adherence (e.g. diet, exercise). Following the reciprocal effects model tenets (Marsh & Craven, 2006), we expect that the influences between changes in weight, selfesteem and exercise to be reciprocal and might present one of the mechanisms by which obesity treatments can be improved.

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This paper aims to study the relationships between chromosomal DNA sequences of twenty species. We propose a methodology combining DNA-based word frequency histograms, correlation methods, and an MDS technique to visualize structural information underlying chromosomes (CRs) and species. Four statistical measures are tested (Minkowski, Cosine, Pearson product-moment, and Kendall τ rank correlations) to analyze the information content of 421 nuclear CRs from twenty species. The proposed methodology is built on mathematical tools and allows the analysis and visualization of very large amounts of stream data, like DNA sequences, with almost no assumptions other than the predefined DNA “word length.” This methodology is able to produce comprehensible three-dimensional visualizations of CR clustering and related spatial and structural patterns. The results of the four test correlation scenarios show that the high-level information clusterings produced by the MDS tool are qualitatively similar, with small variations due to each correlation method characteristics, and that the clusterings are a consequence of the input data and not method’s artifacts.

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In life cycle impact assessment (LCIA) models, the sorption of the ionic fraction of dissociating organic chemicals is not adequately modeled because conventional non-polar partitioning models are applied. Therefore, high uncertainties are expected when modeling the mobility, as well as the bioavailability for uptake by exposed biota and degradation, of dissociating organic chemicals. Alternative regressions that account for the ionized fraction of a molecule to estimate fate parameters were applied to the USEtox model. The most sensitive model parameters in the estimation of ecotoxicological characterization factors (CFs) of micropollutants were evaluated by Monte Carlo analysis in both the default USEtox model and the alternative approach. Negligible differences of CFs values and 95% confidence limits between the two approaches were estimated for direct emissions to the freshwater compartment; however the default USEtox model overestimates CFs and the 95% confidence limits of basic compounds up to three orders and four orders of magnitude, respectively, relatively to the alternative approach for emissions to the agricultural soil compartment. For three emission scenarios, LCIA results show that the default USEtox model overestimates freshwater ecotoxicity impacts for the emission scenarios to agricultural soil by one order of magnitude, and larger confidence limits were estimated, relatively to the alternative approach.

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This article describes a finite element-based formulation for the statistical analysis of the response of stochastic structural composite systems whose material properties are described by random fields. A first-order technique is used to obtain the second-order statistics for the structural response considering means and variances of the displacement and stress fields of plate or shell composite structures. Propagation of uncertainties depends on sensitivities taken as measurement of variation effects. The adjoint variable method is used to obtain the sensitivity matrix. This method is appropriated for composite structures due to the large number of random input parameters. Dominant effects on the stochastic characteristics are studied analyzing the influence of different random parameters. In particular, a study of the anisotropy influence on uncertainties propagation of angle-ply composites is carried out based on the proposed approach.

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The aim of this study is to optimize the heat flow through the pultrusion die assembly system on the manufacturing process of a specific glass-fiber reinforced polymer (GFRP) pultrusion profile. The control of heat flow and its distribution through whole die assembly system is of vital importance in optimizing the actual GFRP pultrusion process. Through mathematical modeling of heating-die process, by means of Finite Element Analysis (FEA) program, an optimum heater selection, die position and temperature control was achieved. The thermal environment within the die was critically modeled relative not only to the applied heat sources, but also to the conductive and convective losses, as well as the thermal contribution arising from the exothermic reaction of resin matrix as it cures or polymerizes from the liquid to solid condition. Numerical simulation was validated with basis on thermographic measurements carried out on key points along the die during pultrusion process.

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Paper presented at the 9th European Conference on Knowledge Management, Southampton Solent University, Southampton, UK, 4-5 Sep. 2008. URL: http://academic-conferences.org/eckm/eckm2008/eckm08-home.htm

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This paper presents the creation and development of technological schools directly linked to the business community and to higher public education. Establishing themselves as the key interface between the two sectors they make a signigicant contribution by having a greater competitive edge when faced with increasing competition in the tradional markets. The development of new business strategies supported by references of excellence, quality and competitiveness also provides a good link between the estalishment of partnerships aiming at the qualification of education boards at a medium level between the technological school and higher education with a technological foundation. We present a case study as an example depicting the success of Escola Tecnológica de Vale de Cambra.

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In this study, the concentration probability distributions of 82 pharmaceutical compounds detected in the effluents of 179 European wastewater treatment plants were computed and inserted into a multimedia fate model. The comparative ecotoxicological impact of the direct emission of these compounds from wastewater treatment plants on freshwater ecosystems, based on a potentially affected fraction (PAF) of species approach, was assessed to rank compounds based on priority. As many pharmaceuticals are acids or bases, the multimedia fate model accounts for regressions to estimate pH-dependent fate parameters. An uncertainty analysis was performed by means of Monte Carlo analysis, which included the uncertainty of fate and ecotoxicity model input variables, as well as the spatial variability of landscape characteristics on the European continental scale. Several pharmaceutical compounds were identified as being of greatest concern, including 7 analgesics/anti-inflammatories, 3 β-blockers, 3 psychiatric drugs, and 1 each of 6 other therapeutic classes. The fate and impact modelling relied extensively on estimated data, given that most of these compounds have little or no experimental fate or ecotoxicity data available, as well as a limited reported occurrence in effluents. The contribution of estimated model input variables to the variance of freshwater ecotoxicity impact, as well as the lack of experimental abiotic degradation data for most compounds, helped in establishing priorities for further testing. Generally, the effluent concentration and the ecotoxicity effect factor were the model input variables with the most significant effect on the uncertainty of output results.

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Dissertation submitted in the fufillment of the requirements for the Degree of Master in Biomedical Engineering

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Dissertação para obtenção do Grau de Mestre em Engenharia e Gestão Industrial