Person‐Group Value Congruence and Subjective Well‐Being in Students from Argentina,Bulgaria and Finland: The Role of Interpersonal Relationships

The present study examined the relations between personal values, value congruence, interpersonal relationships and subjective well‐being in psychology/education and business students from Argentina (N = 275), Bulgaria (N = 182) and Finland (N = 148). Regression analyses showed, first, that there were no direct relations between higher order value priorities and life satisfaction (LS), positive affect (PA) or negative affect (NA). Second, objective value‐congruence (VC)—the similarity between individual and group values—was positively related to LS and PA, and negatively related to NA. Most importantly, the effects of VC on LS, NA and PA were partially mediated by good interpersonal relationships. Our results show that interpersonal relationships are facilitated by sharing values similar to those of one's fellow students. More generally, personal values per se appear not to be associated with subjective well‐being, more important is how these values fit into the social context. Copyright © 2014 John Wiley & Sons, Ltd.     

The Conception of Synthetic Entities from a Personalist Perspective

Science and Engineering Ethics - Synthetic biology opens up the possibility of producing new entities not found in nature, whose classification as organisms or machines has been debated. In this...     

Is reading a feminine domain? The role of gender identity and stereotypes in reading motivation in Chile

Social Psychology of Education - In Chile, as in other countries, there are large gender gaps in reading achievement. One factor that may explain some of these results is male and female...     

Combining genetic algorithms and the finite element method to improve steel industrial processes

Most of the times the optimal control of steel industrial processes is a very complicated task because of the elevated number of parameters to adjust. For that reason, in steel plants, engineers must estimate the best values of the operational parameters of processes, and sometimes, it is also necessary to obtain the appropriate model for steel material behaviour. This article deals with three successful experiences gained from genetic algorithms and the finite element method in order to solve engineering optimisation problems. On one hand, a fully automated method for determining the best material behaviour laws is described, and on the other hand we present a common methodology to find the most appropriate settings for two cases of improvement in steel industrial processes. The study of the three reported cases allowed us to show the reliability and effectiveness of combining both techniques.