Abstract
Availability is a major design issue that should play an important role when deploying and operating wireless sensor networks, specially for critical monitoring applications. Actually, sensing redundancy can be exploited to enhance the attainable availability level of sensor networks, since redundant nodes can replace faulty nodes. When employing camera enabled sensors, the perception of sensing redundancy is considerably changed" when compared to scalar sensors, with direct impact on network availability. In such way, some characteristics as deployment density, viewing angle and sensing range should be properly evaluated in wireless visual sensor networks, in order to better estimate the network availability. Nevertheless, when deploying visual sensors on occluded environments, viewed areas and resulted overlapping may be significantly altered, redefining sensing redundancy. We then propose an algorithm to automatically select redundant nodes in wireless visual sensor networks deployed on areas with occlusion, according to network configurations and application availability requirements. Additionally, an algorithm to adjust cameras' orientations in occluded environments is also proposed. Mathematical assessment of the proposed algorithms are performed, allowing the discussion of how parameters of deployed networks can influence applications monitoring availability.

Abstract
Surgery planing of breast cancer interventions is gaining importance among physicians, who recognize value in discussing the possible aesthetic outcomes of surgery with patients. Research is been propelled to create patient-specific breast models, but breast image registration algorithms are still limited, particularly for the purpose of matching pre- and post-surgical data of patient's breast surfaces. Yet, this is a fundamental task to learn prediction models of breast healing process after surgery. In this paper, a coarse-to-fine registration strategy is proposed to match breast surface data acquired before and after surgery. Methods are evaluated in their ability to register surfaces in an anatomical reliable way, and results suggest proper alignment adequated to be used as input to train deformable models.

Abstract
There is currently a significant interest in consumer electronics in applications and devices that monitor and improve the user's well-being. This is one of the key aspects in the development of ambient intelligence systems. Nonetheless, existing approaches are generally based on physiological sensors, which are intrusive and cannot be realistically used, especially in ambient intelligence in which the transparency, pervasiveness and sensitivity are paramount. We put forward a new approach to the problem in which user behavioral cues are used as an input to assess inner state. This innovative approach has been validated by research in the last years and has characteristics that may enable the development of true unobtrusive, pervasive and sensitive ambient intelligent systems. © 2017 by SCITEPRESS - Science and Technology Publications, Lda.

Abstract
Gene fusions are an important class of cancer-driving events with therapeutic and diagnostic values, yet their underlying genetic mechanisms have not been systematically characterized. Here by combining RNA and whole genome DNA sequencing data from 1188 donors across 27 cancer types we obtained a list of 3297 high-confidence tumour-specific gene fusions, 82% of which had structural variant (SV) support and 2372 of which were novel. Such a large collection of RNA and DNA alterations provides the first opportunity to systematically classify the gene fusions at a mechanistic level. While many could be explained by single SVs, numerous fusions involved series of structural rearrangements and thus are composite fusions. We discovered 75 fusions of a novel class of inter-chromosomal composite fusions, termed bridged fusions, in which a third genomic location bridged two different genes. In addition, we identified 522 fusions involving non-coding genes and 157 ORF-retaining fusions, in which the complete open reading frame of one gene was fused to the UTR region of another. Although only a small proportion (5%) of the discovered fusions were recurrent, we found a set of highly recurrent fusion partner genes, which exhibited strong 5' or 3' bias and were significantly enriched for cancer genes. Our findings broaden the view of the gene fusion landscape and reveal the general properties of genetic alterations underlying gene fusions for the first time.

Abstract

Abstract
The reliability and safety of industrial machines depends on their timely maintenance. The integration of Cyber Physical Systems within the maintenance process enables both continuous machine monitoring and the application of advanced techniques for predictive and proactive machine maintenance. The building blocks for this revolution-embedded sensors, efficient preprocessing capabilities, ubiquitous connection to the internet, cloud-based analysis of the data, prediction algorithms, and advanced visualization methods-are already in place, but several hurdles have to be overcome to enable their application in real scenarios, namely: the integration with existing machines and existing maintenance processes. Current research and development efforts are building pilots and prototypes to demonstrate the feasibility and the merits of advanced maintenance techniques, and this paper describes a system for the industrial maintenance of sheet metal working machinery and its evolution towards a full proactive maintenance system.