Social Identity and Social Exchange: Identification, Support, and Withdrawal from the Job

Integrating insights from the social exchange perspective and the social identity perspective on the psychological relationship between the individual and the organization, we propose that evaluations of the support received from the organization and its representatives, and organizational identification interact in predicting withdrawal from the job. Specifically, the relationship of support with withdrawal is proposed to be weaker the stronger employees identify with the organization. This prediction was confirmed in two samples focusing on different operationalizations of support and withdrawal. Sample 1 concerned the interaction of organizational support and organizational identification in predicting turnover intentions, Sample 2 concerned the prediction of absenteeism from supervisor support and organizational identification. We conclude that the present study yields promising first evidence that may lay the basis for further integration of social exchange and social identity analyses of organizational behavior.Organizational behavior;Organizational identification;Organizational support;Social identity

Tunneling effects on impurity spectral function in coupled asymmetric quantum wires

The impurity spectral function is studied in coupled double quantum wires at finite temperatures. Simple anisotropy in the confinement direction of the wires leads to finite non-diagonal elements of the impurity spectral function matrix. These non-diagonal elements are responsible for tunneling effects and result in pronounced extra peak in the impurity spectral function up to temperatures as high as 20 K.Comment: Accepted in Phys. Rev.

Determinants of the intention to use performance-enhancing substances among Portuguese gym users

The present study examined the determinants of the intentions to use prohibited performance- enhancing substances (PES) and the hypothesis of gender and PES use influencing Theory of Planned Behavior (TPB) variables. A TPB approach was used. A convenience sample of Portuguese gym users (n = 453) completed an anonymous web-based survey. Variance-based structural equation modeling, multigroup analysis strategy, latent mean analysis approach and one-way ANOVA analysis were used. The findings showed that, at structural level, results support the TPB framework in terms of characterizing and predicting intentions to PES use in the gym users sample, and that subjective norms were the strongest predictor of PES use intentions. Female and male differed in intentions to use PES, subjective norms and beliefs. However, the predictive model in study remains invariable in both groups. Concerning PES use, results showed the existence of a significant difference, regarding all the TPB´s constructs of the PES users and nonusers’ groups, and that the predictive capacity of each predictor was different for each group. Psychological strategies should be based on subjective norms, alongside beliefs and attitudes towards PES use, since these variables influence the intention to use PES in that particular population

COMPUTATIONAL MODELING OF CELLULAR EFFECTS POST-IRRADIATION WITH LOW- AND HIGH-LET PARTICLES AND DIFFERENT ABSORBED DOSES

The use of computational methods to improve the understanding of biological responses to various types of radiation is an approach where multiple parameters can be modelled and a variety of data is generated. This study compares cellular effects modelled for low absorbed doses against high absorbed doses. The authors hypothesized that low and high absorbed doses would contribute to cell killing via different mechanisms, potentially impacting on targeted tumour radiotherapy outcomes. Cellular kinetics following irradiation with selective low- and high-linear energy transfer (LET) particles were investigated using the Virtual Cell (VC) radiobiology algorithm. Two different cell types were assessed using the VC radiobiology algorithm: human fibroblasts and human crypt cells. The results showed that at lower doses (0.01 to 0.2 Gy), all radiation sources used were equally able to induce cell death (p\u3e0.05, ANOVA). On the other hand, at higher doses (1.0 to 8.0 Gy), the radiation response was LET and dose dependent (p\u3c0.05, ANOVA). The data obtained suggests that the computational methods used might provide some insight into the cellular effects following irradiation. The results also suggest that it may be necessary to re-evaluate cellular radiation-induced effects, particularly at low doses that could affect therapeutic effectiveness