Abstract
The medical procedures related with the Breast Cancer Conservative Treatment (BCCT) have evolved towards the usage of affordable and practical tools, along with the recent inclusion of volumetric information of the breast. A richer three-dimensional (3D) model of the female torso allows, for instance, improvement of the evaluation the aesthetic outcome of BCCT and the surgery planning. The standard 3D reconstruction methods often fail to model objects of interest using highly misaligned views. In this work, a Tessellation-based coarse registration method is proposed, based on robust keypoints extraction from RGB-D data using the Delaunay Triangulation (DT) principle. With this method, it is possible to reconstruct female torso data with detail using only 3 views, in feasible time. Structures such as the nipples and the breast contour were correctly reconstructed and a highly correlated with reference models.

Abstract

Abstract
In our daily life, we often have the feeling of being exhausted due to mental or physical work, and a sense of performance degradation in the execution of simple tasks. The maximum capacity of operation and performance of an individual, whether physical or mental, usually also decreases gradually as the day progresses. The loss of these resources is linked to the onset of fatigue, which is particularly noticeable in long and demanding tasks or repetitive jobs. However, good management of the working time and effort invested in each task, as well as the effect of breaks at work, can result in better performance and better mental health, delaying the effects of fatigue. This paper details a non-invasive approach on the monitoring of fatigue of a human being, based on the analysis of the performance of his interaction with the computer.

Abstract
The advances in distribution system automation, smart metering and exploitation of microgrids call for the adoption of more flexible options for power flow calculation. This paper illustrates the structure of a tool implemented to deal with time-dependent and uncertain data, as well as changing network structures during time. The focus is then set on including data uncertainty in probabilistic power flow calculations extended over a time period, in which the changing load and generation patterns are generally represented by correlated random variables. Exemplificative results are shown for a case study application.

Abstract
Biometric systems based on iris are vulnerable to direct attacks consisting on the presentation of a fake iris to the sensor (a printed or a contact lenses iris image, among others). The mobile biometrics scenario stresses the importance of assessing the security issues. The application of countermeasures against this type of attacking scheme is the problem addressed in the present paper. Widening a previous work, several state-of-the-art iris liveness detection methods were implemented and adapted to a less-constrained scenario. The proposed method combines a feature selection step prior to the use of state-of-the-art classifiers to perform the classification based upon the "best features". Five well known existing databases for iris liveness purposes (Biosec, Clarkson, NotreDame and Warsaw) and a recently published database, MobBIOfake, with real and fake images captured in the mobile scenario were tested. The results obtained suggest that the automated segmentation step does not degrade significantly the results.

Abstract
Background: BioTextRetriever is a Web-based search tool for retrieving relevant literature in Molecular Biology and related domains from MEDLINE. The core of BioTextRetriever is the dynamic construction of a classifier capable of selecting relevant papers among the whole MEDLINE bibliographic database. “Relevant” papers, in this context, means papers related to a set of DNA or protein sequences provided as input to the tool by the user. Methods: Since the number of retrieved papers may be very large, BioTextRetriever uses a novel ranking algorithm to retrieve the most relevant papers first. We have developed a new methodology that enables the automation of the assessment process based on a multi-criteria ranking function. This function combines six factors: MeSH terms, paper’s number of citations, author’s h-index, journals impact factor, author number of publications and journal similarity function. Results: The best results highlight the number of citations and the h-index factors. Conclusions: We have developed and a multi-criteria ranking function, that contemplates six factors, and that seems appropriate to retrieve relevant papers out of a huge repository such as MEDLINE.