4 resultados para predictive model

em Chinese Academy of Sciences Institutional Repositories Grid Portal


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Steroid derivatives show a complex interaction with P-glycoprotein (Pgp). To determine the essential structural requirements of a series of structurally related and functionally diverse steroids for Pgp-mediated transport or inhibition, a three-dimensional quantitative structure activity relationship study was performed by comparative similarity index analysis modeling. Twelve models have been explored to well correlate the physiochemical features with their biological functions with Pgp on basis of substrate and inhibitor datasets, in which the best predictive model for substrate gave cross-validated q(2) = 0.720, non-cross-validated r(2) = 0.998, standard error of estimate SEE = 0.012, F = 257.955, and the best predictive model for inhibitor gave q(2) = 0.536, r(2) = 0.950, SEE = 1.761 and F = 45.800. The predictive ability of all models was validated by a set of compounds that were not included in the training set. The physiochemical similarities and differences of steroids as Pgp substrate and inhibitor, respectively, were analyzed to be helpful in developing new steroid-like compounds. (C) 2004 Elsevier B.V. All rights reserved.

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Ill-health prevails in the workplace. A key problem encountered in the area of stress management is a lack of research into the way job burnout turns into mental problems, especially depressive symptoms, the most prevalent and costly psychiatric condition in the workplace. This research belongs to a cross-discipline area of industrial psychiatry and organizational behavior, which has seldom been investigated before. This research will contribute to the theoretical development of organizational behavior, especially to stress management and industrial psychiatry. This study aims to explore etiological factors and mechanisms of depressive symptoms of workers in the financial industry. By using literature review, semi-structured interviews and surveys as the major research methods, this Ph.D. study systematically investigated the risk factors of workers’ depressive symptoms within and outside of the work area. These risk factors are worker-work environment fits, work family conflicts, and workers’ psychological vulnerabilities to depression. A thorough literature review and 20 semi-structured interviews of brokers in different kinds of financial markets show the feasibility and necessity of this Ph.D. study when it comes to the issue of financial workers’ depressive symptoms. Two surveys of workplace-etiological factors of depressive symptoms were conducted among 244 financial workers and 1024 financial workers. This cross-sample verification showed that worker-work environment fit was a good framework to study risk factors of workers’ depressive symptoms. Results revealed that job demands-abilities misfit could lead to job burnout which in turn contributed to worker’s depressive symptoms; besides this, work effort-reward imbalance could directly cause workers’ depressive symptoms. Emotional labor enhanced the positive effect of job burnout on workers’ depressive symptoms. In the third study, a prominent risk factor outside of the work area, namely work family conflict, and workers’ psychological vulnerabilities of depression were included with workplace etiological factors to investigate the overall predictive model of depressive symptoms of financial workers. The survey was conducted among the same 1024 financial workers. Results indicated that work effort-reward imbalance, job burnout and work interfering in family life were three external etiological factors of workers’ depressive symptoms. Neuroticism, autonomy and low emotional intelligence were three individual etiological factors which had a positive effect on workers’ depressive symptoms. Moreover, neuroticism enhanced the relationship between job burnout and depressive symptoms as well as between work interfering in family life and depressive symptoms. Autonomy aggravated the relationship between job burnout and depressive symptoms. However, emotional intelligence attenuated the relationship between job burnout and depressive symptoms as well as between work effort-reward imbalance and depressive symptoms. Besides, workers’ dysfunctional attitudes played a partial mediating role in the relationships between above etiological factors and depressive symptoms. In the same sample, research evidence of impairments of workers’ depressive symptoms to their work-life quality was also obtained. Specifically, depressive symptoms could predict workers’ presenteeism, absenteeism and turnover intention. Their subjective well-being was also lowered when suffering more severe depressive symptoms. This research provides a theoretical basis to management practices targeted to set up the Employee Assistance Program or even more specilised rehabilitation programs for workers with depressive symptoms so as to improve their work-life quality and and establish a harmonious enterprise.

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A predictive and self-consistent mathematical model incorporating the electrochemical, chemical and ionic migration processes characterizing the propagation stage of crevice and pitting corrosion in metals is described. The model predicts the steady-state solution chemistry and electrode kinetics (and hence metal penetration rates) within an active corrosion cavity as a function of the many parameters on which these depend, such as external electrode potential and crevice dimensions. The crevice is modelled as a parallel-sided slot filled with a dilute sodium chloride solution. The cavity propagation rates are found to be faster in the case of a crevice with passive walls than one with active walls. The distribution of current over the internal surface of a crevice with corroding walls can be assessed using this model, giving an indication of the future shape of the cavity. The model is extended to include a solid hydroxide precipitation reaction and considers the effect of consequent changes in the chemical and physical environment within the crevice on the predicted corrosion rates. In this paper, the model is applied to crevice and pitting corrosion in carbon steel.

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A hybrid coupled ocean-atmosphere model is designed, which consists of a global AGCM and a simple anomaly ocean model in the tropical Pacific. Retroactive experimental predictions initiated in each season from 1979 to 1994 are performed. Analyses indicate that: (1) The overall predictive capability of this model for SSTA over the central-eastern tropical Pacific can reach one year, and the error is not larger than 0.8 degrees C. (2) The prediction skill depends greatly on the season when forecasts start. However, the phenomenon of SPB (spring prediction barrier) is not found in the model. (3) The ensemble forecast method can effectively improve prediction results. A new initialization scheme is discussed.