Abstract
This paper shows how bibliometric models can be used to assist peers in selecting candidates for academic openings. Several studies have demonstrated that a relationship exists between results from peer-review evaluations and results obtained with certain bibliometric indicators. However, very little has been done to analyse the predictive power of models based on bibliometric indicators. Indicators with high predictive power will be seen as good instruments to support peer evaluations. The goal of this study is to assess the predictive power of a model based on bibliometric indicators for the results of academic openings at the level of Associado and Catedratico at Portuguese universities. Our results suggest that the model can predict the results of peer-review at this level with a reasonable degree of accuracy. This predictive power is better when only the scientific performance is assessed by peers.

Abstract
The creation of computer-based design tools to help teachers in designing learning scenarios, more precisely teaching-learning activities, has great importance in education. Those tools are most valuable if enriched with special features as, for example, templates, scripts or wizards used to guide the teacher through the design process. Recommendation mechanisms anchored in solid theoretical achievements are currently a huge challenge in the scientific research. This paper presents a proposal for teaching-learning techniques recommendation supported by an ontological modeling approach. The recommendation aims to assist educators in designing of teaching-learning activities. The recommendation process is part of the ACEM model which integrates an authoring design tool. We propose that the recommendation mechanism will help teachers preparing those activities and improving the use of different learning techniques.

Abstract
Wireless sensor networks can provide valuable information for a lot of measurement, tracking, surveillance, automation, and general-purpose monitoring applications. Information as humidity, temperature, pressure, infrared images, and noises will be sensed and packetized for distribution over the network, but corruption during transmission may compromise the accuracy of the retrieved information and even put people in danger. In fact, the sensed data may have different relevancies for the applications, altering the impact of packet corruptions. We propose a relevance-based partially reliable transmission approach to provide data delivery with different reliability guaranties, exploiting the relevancies of transmitted data when choosing the proper error recovery service. In this context, some error scenarios are investigated, considering different configurations of error bursts. We expect that the proposed partially reliable transmission mechanism can save energy over the network while assuring acceptable quality for sensing monitoring.

Abstract

Abstract
It can be argued that participating in Free/Libre Open Source Software (FLOSS) projects can have a positive effect in the contributor's learning process. The need to collaborate with other contributors and to contribute to a project can motivate and implicitly foster learning. In order to validate such statements, it is necessary to (1) study the interactions between FLOSS projects' participants, and (2) explore the didactical value of participating in FLOSS projects, designing an appropriate questionnaire asking FLOSS contributors about their experience in FLOSS projects. In this paper, we illustrate how this questionnaire was designed and disseminated. We conclude the paper with results from 27 FLOSS projects contributors, determining that, not only they contribute and collaborate to the project and its community, but also that FLOSS contributors see that this type of activity can be regarded as a complement to formal education.

Abstract
Several fisheries across the world are managed by a quota regime. These quotas can be set yearly, monthly, weekly or daily. However, for some fish species demand seasonality may occur, which should be taken into consideration in the establishment of the quota (especially in those fisheries managed by daily or monthly quotas). This would allow fishermen to catch more fish at times of the year with higher demand in detriment of periods when demand is low. The present work investigates the existence of demand seasonality for bivalves from the artisanal dredge fleet. This fleet operates along the entire coast of the Portugal mainland. The analysis of fleets' revenue efficiency is assessed with Data Envelopment Analysis models, and the monthly seasonality effects on the revenue efficiency were tested using a Tobit regression. The results revealed that on the South coast there is a strong demand in the summer whereas on the western coast (northwest and southwest fishing areas) demand increases during Christmas and New Year festivities. Since this fishery is managed by weekly/daily quotas, it is proposed that these quotas should be redistributed in order to adjust them to periods of higher demand, thereby increasing the profitability of the vessels. The approach followed could be applied to similar fisheries worldwide.