Accurate and reliable prediction of Perfobond Rib Shear Strength Connector is considered as a major issue in the structural engineering sector. Besides, selecting the most significant variables that have a major influence on PRSC in every important step for attaining economic and more accurate predictive models, this study investigates the capacity of deep learning neural network for shear strength prediction of PRSC. The proposed DLNN model is validated against support vector regression, artificial neural network, and M5 tree model. In the (...) second scenario, a comparable AI model hybridized with genetic algorithm as a robust bioinspired optimization approach for optimizing the related predictors for the PRSC is proposed. Hybridizing AI models with GA as a selector tool is an attempt to acquire the best accuracy of predictions with the fewest possible related parameters. In accordance with quantitative analysis, it can be observed that the GA-DLNN models required only 7 input parameters and yielded the best prediction accuracy with highest correlation coefficient and lowest value root mean square error. However, the other comparable models such as GA-M5Tree, GA-ANN, and GA-SVR required 10 input parameters to obtain a relatively acceptable level of accuracy. Employing GA as a feature parameter selection technique improves the precision of almost all hybrid models by optimally removing redundant variables which decrease the efficiency of the model. (shrink)

Se aborda el estudio del film a partir del concepto de género cinematográfico, después la forma narrativa, la puesta en escena y el plano, interrelacionando los tres aspectos, para intentar a través del cómo capturar el qué o significado fílmico, y comentar la imagen depresiva ofrecida por la directora de una congénere que simboliza el modo diferente de ser mujer en la historia de Colombia.

The ongoing coronavirus disease 2019 (COVID-19) pandemic has quickly swept the globe leaving a devastating trail of lost human lives and leading to a public health and economic crisis. With this in mind, prosociality has been heralded as a potential important factor to overcome the negative effects of the pandemic. As such, in this study, we examined the effectiveness of a brief reflexive writing exercise about recent experiences of gratitude on individuals’ intentions to engage in prosocial behaviors using a sample (...) of 253 participants living in Portugal and 280 participants living in Brazil. Participants were randomly assigned to either a condition in which they were asked to write about recent experiences of gratitude or a control group in which they were asked to write about daily tasks. We predicted that the gratitude intervention would increase state gratitude and, consequently, increase positive affect and empathic concern, and decrease negative affect, leading to increased intentions to engage in prosocial behaviors during the COVID-19 pandemic. A moderated serial–parallel mediation analysis, in which we controlled for gender, age, and level of religiosity, indicated that our manipulation led to increases in state gratitude, which in turn increased positive emotions and empathic concern, leading to increased prosocial intentions in both countries. A content analysis of participants’ responses in the gratitude group revealed that relationships with others and health and well-being were the central themes of their gratitude experiences during the COVID-19 global pandemic. (shrink)