984 resultados para DEPRESSION MODELS


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Negative impacts of noise exposure on health and performance may result in part from learned helplessness, the syndrome of deficits typically produced by exposure to uncontrollable events. People may perceive environmental noise to be uncontrollable, and several effects of noise exposure appear to parallel learned helplessness deficits. In the present socioacoustic survey (N = 1,015), perceived control over aircraft noise correlated negatively with some effects of noise (though not others). Furthermore, these effects were better predicted by perceived control than by noise level. These observational data support the claim that learned helplessness contributes to the effects of noise exposure.

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Nine classes of integrable open boundary conditions, further extending the one-dimensional U-q (gl (212)) extended Hubbard model, have been constructed previously by means of the boundary Z(2)-graded quantum inverse scattering method. The boundary systems are now solved by using the algebraic Bethe ansatz method, and the Bethe ansatz equations are obtained for all nine cases.

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One consistent functional imaging finding from patients with major depression has been abnormality of the anterior cingulate cortex (ACC). Hypoperfusion has been most commonly reported, but some studies suggest relative hyperperfusion is associated with response to somatic treatments. Despite these indications of the possible importance of the ACC in depression there have been relatively few cognitive studies ACC function in patients with major depression. The present study employed a series of reaction time (RT) tasks involving selection with melancholic and nonmelancholic depressed patients, as well as age-matched controls. Fifteen patients with unipolar major depression (7 melancholic, 8 nonmelancholic) and 8 healthy age-matched controls performed a series of response selection tasks (choice RT, spatial Stroop, spatial stimulus-response compatibility (SRC), and a combined Stroop + SRC condition). Reaction time and error data were collected. Melancholic patients were significantly slower than controls on all tasks but were slower than nonmelancholic patients only on the Stroop and Stroop + SRC conditions. Nonmelancholic patients did not differ from the control group on any task. The Stroop task seems crucial in differentiating the two depressive groups, they did not differ on the choice RT or SRC tasks. This may reflect differential task demands, the SRC involved symbolic manipulation that might engage the dorsal ACC and dorsolateral prefrontal cortex (DLPFC) to a greater extent than the, primarily inhibitory, Stroop task which may engage the ventral ACC and orbitofrontal cortex (OFC). This might suggest the melancholic group showed a greater ventral ACC-OFC deficit than the nonmelancholic group, while both groups showed similar dorsal ACC-DLPFC deficit.

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Many models exist in the literature to explain the success of technological innovation. However, no studies have been made regarding graphic formats representing the technological innovation models and their impact, or on the understanding of these models by non-specialists in technology management. Thus, the main objective of this paper is to propose a new graphic configuration to represent the technological innovation management. Based on the literature, the innovation model is presented in the traditional format. Next, the same model is designed in the graphic format - named `the see-saw of competitiveness` - showing the interfaces among the identified factors. The two graphic formats were compared by a group of graduate students in terms of the ease in understanding the conceptual model of innovation. The statistical analysis shows that the seesaw of competitiveness is preferred.

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Quantifying mass and energy exchanges within tropical forests is essential for understanding their role in the global carbon budget and how they will respond to perturbations in climate. This study reviews ecosystem process models designed to predict the growth and productivity of temperate and tropical forest ecosystems. Temperate forest models were included because of the minimal number of tropical forest models. The review provides a multiscale assessment enabling potential users to select a model suited to the scale and type of information they require in tropical forests. Process models are reviewed in relation to their input and output parameters, minimum spatial and temporal units of operation, maximum spatial extent and time period of application for each organization level of modelling. Organizational levels included leaf-tree, plot-stand, regional and ecosystem levels, with model complexity decreasing as the time-step and spatial extent of model operation increases. All ecosystem models are simplified versions of reality and are typically aspatial. Remotely sensed data sets and derived products may be used to initialize, drive and validate ecosystem process models. At the simplest level, remotely sensed data are used to delimit location, extent and changes over time of vegetation communities. At a more advanced level, remotely sensed data products have been used to estimate key structural and biophysical properties associated with ecosystem processes in tropical and temperate forests. Combining ecological models and image data enables the development of carbon accounting systems that will contribute to understanding greenhouse gas budgets at biome and global scales.

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Valuation of projects for the preservation of water resources provides important information to policy makers and funding institutions. Standard contingent valuation models rely on distributional assumptions to provide welfare measures. Deviations from assumed and actual distribution of benefits are important when designing policies in developing countries, where inequality is a concern. This article applies semiparametric methods to obtain estimates of the benefit from a project for the preservation of an important Brazilian river basin. These estimates lead to significant differences from those obtained using the standard parametric approach.

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Exponential and sigmoidal functions have been suggested to describe the bulk density profiles of crusts. The present work aims to evaluate these conceptual models using high resolution X-radiography. Repacked seedbeds from two soil materials, air-dried or prewetted by capillary rise, were subjected to simulated rain, which resulted in three types of structural crusts, namely, slaking, infilling, and coalescing. Bulk density distributions with depth were generated using high-resolution (70 mum), calibrated X-ray images of slices from the resin-impregnated crusted seedbeds. The bulk density decreased progressively with depth, which supports the suggestion that a crust should be considered as a nonuniform layer. For the slaking and the coalescing crusts, the exponential function underestimated the strong change in bulk density across the morphologically defined transition between the crust and the underlying material; the sigmoidal function provided a better description. Neither of these crust models effectively described the shape of the bulk density profiles through the whole seedbed. Below the infilling and slaking crusts, bulk density increased linearly with depth as a result of slumping. In the coalescing crusted seedbed, the whole seedbed uniformly collapsed and most of the bulk density change within the crust could be ascribed to slumping (0.33 g cm(-3)) rather than to crusting (0.12 g cm(-3)). Finally, (i) X-radiography appears as a unique tool to generate high resolution bulk density profiles and (ii) in structural crusts, bulk density profiles could be modeled using the existing exponential and sigmoidal crusting models, provided a slumping model would be coupled.

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A generalised ladder operator is used to construct the conserved operators for any one-dimensional lattice model derived from the Yang-Baxter equation. As an example, the low order conserved operators for the XYh model are calculated explicitly.

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Objective: To assess from a health sector perspective the incremental cost-effectiveness of cognitive behavioural therapy (CBT) and selective serotonin reuptake inhibitors (SSRIs) for the treatment of major depressive disorder (MDD) in children and adolescents, compared to 'current practice'. Method: The health benefit is measured as a reduction in disability-adjusted life years (DALYs), based on effect size calculations from meta-analysis of randomised controlled trials. An assessment on second stage filter criteria ('equity'; 'strength of evidence', 'feasibility' and 'acceptability to stakeholders') is also undertaken to incorporate additional factors that impact on resource allocation decisions. Costs and benefits are tracked for the duration of a new episode of MDD arising in eligible children (age 6-17 years) in the Australian population in the year 2000. Simulation-modelling techniques are used to present a 95% uncertainty interval (UI) around the cost-effectiveness ratios. Results: Compared to current practice, CBT by public psychologists is the most cost-effective intervention for MDD in children and adolescents at A$9000 per DALY saved (95% UI A$3900 to A$24 000). SSRIs and CBT by other providers are less cost-effective but likely to be less than A$50 000 per DALY saved (> 80% chance). CBT is more effective than SSRIs in children and adolescents, resulting in a greater total health benefit (DALYs saved) than could be achieved with SSRIs. Issues that require attention for the CBT intervention include equity concerns, ensuring an adequate workforce, funding arrangements and acceptability to various stakeholders. Conclusions: Cognitive behavioural therapy provided by a public psychologist is the most effective and cost-effective option for the first-line treatment of MDD in children and adolescents. However, this option is not currently accessible by all patients and will require change in policy to allow more widespread uptake. It will also require 'start-up' costs and attention to ensuring an adequate workforce.

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Models of population dynamics are commonly used to predict risks in ecology, particularly risks of population decline. There is often considerable uncertainty associated with these predictions. However, alternatives to predictions based on population models have not been assessed. We used simulation models of hypothetical species to generate the kinds of data that might typically be available to ecologists and then invited other researchers to predict risks of population declines using these data. The accuracy of the predictions was assessed by comparison with the forecasts of the original model. The researchers used either population models or subjective judgement to make their predictions. Predictions made using models were only slightly more accurate than subjective judgements of risk. However, predictions using models tended to be unbiased, while subjective judgements were biased towards over-estimation. Psychology literature suggests that the bias of subjective judgements is likely to vary somewhat unpredictably among people, depending on their stake in the outcome. This will make subjective predictions more uncertain and less transparent than those based on models. (C) 2004 Elsevier SAS. All rights reserved.

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The epsilon4 allele of apolipoprotem E (APOE), and the plasma levels of APOE, amyloid beta-protein precursor, arnyloid beta1-40 (Abeta40) and homocysteine, (Hcy) have all been correlated with the presence of dementia. Mutations in the methylnetetrahydrofolate reductase enzyme (MTHFR) have been associated with elevated levels of Hcy. This study explored the association of these factors with cognition and depression in community dwelling older men. Two hundred and ninety-nine men, mean age 78.9 years (SD 2.8), were studied in this cross-sectional survey. Mean plasma Hcy was 13.5 (SD 5.3) mumol/L. The MTHFR genotype had no obvious impact on Hey levels. Ln Hcy and Ln Abeta40 were both inversely correlated with calculated glomerular filtration rate (cGFR), r = -0.41 (p < 0.001) and r = -0.28 (p < 0.001), respectively. There was a positive correlation between Ln Hey and Ln Abeta40, r = 0.19 (p < 0.001), which remained significant after adjusting for cGFR, with a doubling of Hcy associated with a 24% increase of Abeta40. The e4 allele was associated with increased depressive symptoms as measured by the Geriatric Depression Scale-15, Odds ratio (OR) = 2.59 (95% CI 1.06-6.34) and poorer performance on the Clock Drawing Test, OR = 2.32 (95% CI: 1.25-4.29). There was a positive association between Abeta40 and Hcy, even after adjustment for cGFR in this sample of well, community dwelling older men. This association may help elucidate the link between elevated levels of Hey and Alzheimer's disease.