902 resultados para Level of program implementation


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Neuronal operations associated with the top-down control process of shifting attention from one locus to another involve a network of cortical regions, and their influence is deemed fundamental to visual perception. However, the extent and nature of these operations within primary visual areas are unknown. In this paper, we used magnetoencephalography (MEG) in combination with magnetic resonance imaging (MRI) to determine whether, prior to the onset of a visual stimulus, neuronal activity within early visual cortex is affected by covert attentional shifts. Time/frequency analyses were used to identify the nature of this activity. Our results show that shifting attention towards an expected visual target results in a late-onset (600 ms postcue onset) depression of alpha activity which persists until the appearance of the target. Independent component analysis (ICA) and dipolar source modeling confirmed that the neuronal changes we observed originated from within the calcarine cortex. Our results further show that the amplitude changes in alpha activity were induced not evoked (i.e., not phase-locked to the cued attentional task). We argue that the decrease in alpha prior to the onset of the target may serve to prime the early visual cortex for incoming sensory information. We conclude that attentional shifts affect activity within the human calcarine cortex by altering the amplitude of spontaneous alpha rhythms and that subsequent modulation of visual input with attentional engagement follows as a consequence of these localized changes in oscillatory activity. © 2005 Elsevier B.V. All rights reserved.

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Problem: The vast majority of research examining the interplay between aggressive emotions, beliefs, behaviors, cognitions, and situational contingencies in competitive athletes has focused on Western populations and only select sports (e.g., ice hockey). Research involving Eastern, particularly Chinese, athletes is surprisingly sparse given the sheer size of these populations. Thus, this study examines the aggressive emotions, beliefs, behaviors, and cognitions, of competitive Chinese athletes. Method: Several measures related to aggression were distributed to a large sample (N ¼ 471) of male athletes, representing four sports (basketball, rugby union, association football/soccer, and squash). Results: Higher levels of anger and aggression tended to be associated with higher levels of play for rugby and low levels of play for contact (e.g., football, basketball) and individual sports (e.g., squash). Conclusions: The results suggest that the experience of angry emotions and aggressive behaviors of Chinese athletes are similar to Western populations, but that sport psychology practitioners should be aware of some potentially important differences, such as the general tendency of Chinese athletes to disapprove of aggressive behavior.

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We investigate the impact of institutions on entrepreneurial entry, based on a large cross-country sample, combining working age population data generated by the GEM project with macro level indicators. Our four key findings indicate that: (a) institutional obstacles to entrepreneurship have different impact in rich countries compared to poor countries; (b) institutional obstacles have a stronger impact on 'opportunity entrepreneurship' than on 'necessity entrepreneurship'; (c) two institutional indicators - property right protection and access to finance - appear to have a dominant impact on entrepreneurship; (d) institutions have a long term impact. More than ten years after the Soviet system imploded in Central and Eastern Europe, these countries still experience significantly lower levels of entrepreneurship than economies coming from different legal traditions.

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DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY AND INFORMATION SERVICES WITH PRIOR ARRANGEMENT

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Misuse of biocides has encouraged the emergence of resistance and cross-resistance in certain strains. This study investigated resistance of triclosan-adapted Escherichia coli K-12 and E. coli O55 to antimicrobial agents and compared these to E. coli O157:H7. Cross-resistance in E. coli K-12 and E. coli O55 was observed however to a lesser extent than in E. coli O157:H7. Triclosan-adapted E. coli K-12 demonstrated cross-resistance to chloramphenicol, whereas triclosan-adapted E. coli O55 exhibited resistance to trimethoprim. In comparison, E. coli O157:H7 was resistant to chloramphenicol, tetracycline, amoxicillin, amoxicillin/clavulanic acid, trimethoprim, benzalkonium chloride and chlorohexidine suggesting strain specific rather than general resistance mechanisms. © 2004 Federation of European Microbiological Societies. Published by Elsevier B.V. All rights reserved.

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The paper presents basic notions and scientific achievements in the field of program transformations, describes usage of these achievements both in the professional activity (when developing optimizing and unparallelizing compilers) and in the higher education. It also analyzes main problems in this area. The concept of control of program transformation information is introduced in the form of specialized knowledge bank on computer program transformations to support the scientific research, education and professional activity in the field. The tasks that are solved by the knowledge bank are formulated. The paper is intended for experts in the artificial intelligence, optimizing compilation, postgraduates and senior students of corresponding specialties; it may be also interesting for university lecturers and instructors.

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Feature selection is important in medical field for many reasons. However, selecting important variables is a difficult task with the presence of censoring that is a unique feature in survival data analysis. This paper proposed an approach to deal with the censoring problem in endovascular aortic repair survival data through Bayesian networks. It was merged and embedded with a hybrid feature selection process that combines cox's univariate analysis with machine learning approaches such as ensemble artificial neural networks to select the most relevant predictive variables. The proposed algorithm was compared with common survival variable selection approaches such as; least absolute shrinkage and selection operator LASSO, and Akaike information criterion AIC methods. The results showed that it was capable of dealing with high censoring in the datasets. Moreover, ensemble classifiers increased the area under the roc curves of the two datasets collected from two centers located in United Kingdom separately. Furthermore, ensembles constructed with center 1 enhanced the concordance index of center 2 prediction compared to the model built with a single network. Although the size of the final reduced model using the neural networks and its ensembles is greater than other methods, the model outperformed the others in both concordance index and sensitivity for center 2 prediction. This indicates the reduced model is more powerful for cross center prediction.