Adults with aphasia perceived greater stress than did healthy controls; however, this paradigm did not stimulate salivary cortisol reactivity in the aphasia group. A potential reason for this may be differences in the type or degree of psychosocial variables that are important in modulating stress in this population. Other considerations when developing methods for assessing physiologic stress include habituation and hypothalamic-pituitary-adrenal (HPA) axis dysregulation related to the neurological changes poststroke.

The purpose of this study is to examine the effects of blended e-learning on electrical machinery performance (achievement test and self-assessment). Participants were two classes of 11th graders majoring in electrical engineering and taking the electrical machinery class at a vocational high school in Taiwan. The participants were randomly selected and assigned to either the experimental group (n = 33) which studied through blended e-learning or the control group (n = 32) which studied through traditional classroom learning. The experiment lasted for five weeks. The results showed that (a) there were no significant differences in achievement test scores between blended elearning and traditional learning; (b) students in the experimental group obtained significantly higher scores on self-assessment than students in the control group; (c) students' scores on self-assessment were significantly higher after studying through blended e-learning than before. Overall, blended e-learning did not significantly affect students' achievement test scores, but significantly affected their self-assessment scores.

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The distribution of the maximum of two independent random variables is important in reliability, investment, management science, insurance business, medical science, etc. For most practical applications, the density function provides important information about the distribution. The maximum of two independent random variables has a density function that can be estimated by two different kernel type estimators. In this article, we discuss these two kernel estimators, called direct and indirect kernel estimators. We find their asymptotic mean square errors and central limit theorems from which comparisons are made through examples and simulations.

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