445 resultados para Structural Determination
Resumo:
Background: More than half of all cerebral ischemic events are the result of rupture of extracranial plaques. The clinical determination of carotid plaque vulnerability is currently based solely on luminal stenosis; however, it has been increasingly suggested that plaque morphology and biomechanical stress should also be considered. We used finite element analysis based on in vivo magnetic resonance imaging (MRI) to simulate the stress distributions within plaques of asymptomatic and symptomatic individuals. Methods: Thirty nonconsecutive subjects (15 symptomatic and 15 asymptomatic) underwent high-resolution multisequence in vivo MRI of the carotid bifurcation. Stress analysis was performed based on the geometry derived from in vivo MRI of the carotid artery at the point of maximal stenosis. The finite element analysis model considered plaque components to be hyperelastic. The peak stresses within the plaques of symptomatic and asymptomatic individuals were compared. Results: High stress concentrations were found at the shoulder regions of symptomatic plaques, and the maximal stresses predicted in this group were significantly higher than those in the asymptomatic group (508.2 ± 193.1 vs 269.6 ± 107.9 kPa; P = .004). Conclusions: Maximal predicted plaque stresses in symptomatic patients were higher than those predicted in asymptomatic patients by finite element analysis, suggesting the possibility that plaques with higher stresses may be more prone to be symptomatic and rupture. If further validated by large-scale longitudinal studies, biomechanical stress analysis based on high resolution in vivo MRI could potentially act as a useful tool for risk assessment of carotid atheroma. It may help in the identification of patients with asymptomatic carotid atheroma at greatest risk of developing symptoms or mild-to-moderate symptomatic stenoses, which currently fall outside current clinical guidelines for intervention.
Resumo:
The time for conducting Preventive Maintenance (PM) on an asset is often determined using a predefined alarm limit based on trends of a hazard function. In this paper, the authors propose using both hazard and reliability functions to improve the accuracy of the prediction particularly when the failure characteristic of the asset whole life is modelled using different failure distributions for the different stages of the life of the asset. The proposed method is validated using simulations and case studies.
Resumo:
The purpose of this research was to develop and test a multicausal model of the individual characteristics associated with academic success in first-year Australian university students. This model comprised the constructs of: previous academic performance, achievement motivation, self-regulatory learning strategies, and personality traits, with end-of-semester grades the dependent variable of interest. The study involved the distribution of a questionnaire, which assessed motivation, self-regulatory learning strategies and personality traits, to 1193 students at the start of their first year at university. Students' academic records were accessed at the end of their first year of study to ascertain their first and second semester grades. This study established that previous high academic performance, use of self-regulatory learning strategies, and being introverted and agreeable, were indicators of academic success in the first semester of university study. Achievement motivation and the personality trait of conscientiousness were indirectly related to first semester grades, through the influence they had on the students' use of self-regulatory learning strategies. First semester grades were predictive of second semester grades. This research provides valuable information for both educators and students about the factors intrinsic to the individual that are associated with successful performance in the first year at university.
