Mood and cognition in healthy older European adults: the Zenith study

YesBackground: The study aim was to determine if state and trait intra-individual measures of everyday affect predict cognitive functioning in healthy older community dwelling European adults (n = 387), aged 55-87 years. Methods: Participants were recruited from centres in France, Italy and Northern Ireland. Trait level and variability in positive and negative affect (PA and NA) were assessed using self-administered PANAS scales, four times a day for four days. State mood was assessed by one PANAS scale prior to assessment of recognition memory, spatial working memory, reaction time and sustained attention using the CANTAB computerized test battery. Results: A series of hierarchical regression analyses were carried out, one for each measure of cognitive function as the dependent variable, and socio-demographic variables (age, sex and social class), state and trait mood measures as the predictors. State PA and NA were both predictive of spatial working memory prior to looking at the contribution of trait mood. Trait PA and its variability were predictive of sustained attention. In the final step of the regression analyses, trait PA variability predicted greater sustained attention, whereas state NA predicted fewer spatial working memory errors, accounting for a very small percentage of the variance (1-2%) in the respective tests. Conclusion: Moods, by and large, have a small transient effect on cognition in this older sample

A new hybrid simulated annealing-based genetic programming technique to predict the ultimate bearing capacity of piles

The aim of this research is to develop three soft-computing techniques, including adaptive-neuro-fuzzy inference system (ANFIS), genetic-programming (GP) tree-based, and simulated annealing–GP or SA–GP for prediction of the ultimate-bearing capacity (Qult) of the pile. The collected database consists of 50 driven piles properties with pile length, pile cross-sectional area, hammer weight, pile set and drop height as model inputs and Qult as model output. Many GP and SA–GP models were constructed for estimating pile bearing capacity and the best models were selected using some performance indices. For comparison purposes, the ANFIS model was also applied to predict Qult of the pile. It was observed that the developed models are able to provide higher prediction performance in the design of Qult of the pile. Concerning the coefficient of correlation, and mean square error, the SA–GP model had the best values for both training and testing data sets, followed by the GP and ANFIS models, respectively. It implies that the neural-based predictive machine learning techniques like ANFIS are not as powerful as evolutionary predictive machine learning techniques like GP and SA–GP in estimating the ultimate-bearing capacity of the pile. Besides, GP and SA–GP can propose a formula for Qult prediction which is a privilege of these models over the ANFIS predictive model. The sensitivity analysis also showed that the Qult of pile looks to be more affected by pile cross-sectional area and pile set

Virtual Reality Environments (VREs) for Training and Learning

VR technologies are gaining momentum in the field of education and particularly in the use of Virtual Reality (VR)-based learning. Within Virtual Reality Environments (VREs) realistic world situations are simulated, facilitating the transfer of the knowledge and skills gained within the virtual world to the real one. In this chapter, we provide a review of several advantages of using VR technology in education and training. In addition, we examine different challenges and potential problems that need to be considered in order to successfully integrate VR in training activities. We also exemplify the promising prospect of this technology in education by describing two novel VR applications. The first one aims to support educators in improving their teaching practice. Using VR technology, the teacher is given the opportunity to experience the student’s point of view during a classic room and cultivate their empathy skills. The second one aims to support teachers in creating VR serious games by lowering the difficulty of developing this type of educational artefact through intuitive interaction and eliminating the need for learning new design language