The Effects of High Pressure on the Point of No Return in Simulated Penalty Kicks

We investigated the effects of high pressure on the point of no return or the minimum time required for a kicker to respond to the goalkeeper's dive in a simulated penalty kick task. The goalkeeper moved to one side with different times available for the participants to direct the ball to the opposite side in low-pressure (acoustically isolated laboratory) and high-pressure situations (with a participative audience). One group of participants showed a significant lengthening of the point of no return under high pressure. With less time available, performance was at chance level. Unexpectedly, in a second group of participants, high pressure caused a qualitative change in which for short times available participants were inclined to aim in the direction of the goalkeeper's move. The distinct effects of high pressure are discussed within attentional control theory to reflect a decreasing efficiency of the goal-driven attentional system, slowing down performance, and a decreasing effectiveness in inhibiting stimulus-driven behavior.

Structure-semantics interplay in complex networks and its effects on the predictability of similarity in texts

The classification of texts has become a major endeavor with so much electronic material available, for it is an essential task in several applications, including search engines and information retrieval. There are different ways to define similarity for grouping similar texts into clusters, as the concept of similarity may depend on the purpose of the task. For instance, in topic extraction similar texts mean those within the same semantic field, whereas in author recognition stylistic features should be considered. In this study, we introduce ways to classify texts employing concepts of complex networks, which may be able to capture syntactic, semantic and even pragmatic features. The interplay between various metrics of the complex networks is analyzed with three applications, namely identification of machine translation (MT) systems, evaluation of quality of machine translated texts and authorship recognition. We shall show that topological features of the networks representing texts can enhance the ability to identify MT systems in particular cases. For evaluating the quality of MT texts, on the other hand, high correlation was obtained with methods capable of capturing the semantics. This was expected because the golden standards used are themselves based on word co-occurrence. Notwithstanding, the Katz similarity, which involves semantic and structure in the comparison of texts, achieved the highest correlation with the NIST measurement, indicating that in some cases the combination of both approaches can improve the ability to quantify quality in MT. In authorship recognition, again the topological features were relevant in some contexts, though for the books and authors analyzed good results were obtained with semantic features as well. Because hybrid approaches encompassing semantic and topological features have not been extensively used, we believe that the methodology proposed here may be useful to enhance text classification considerably, as it combines well-established strategies. (c) 2012 Elsevier B.V. All rights reserved.

Teachers' sick leave due to mental and behavioral disorders and return to work

This manuscript presents a review of the literature about medical leaves due to mental and behavioral disorders and return to work of teachers. There are scarce published manuscripts. Most articles relate with prevalence of mental disorders and factors associated with the work organization, and did not mention intervention proposals and or changes in the work organization and teaching work. Proposed actions are discussed.