Abstract
Lifted inference has been proposed for various probabilistic logical frameworks in order to compute the probability of queries in a time that depends on the size of the domains of the random variables rather than the number of instances. Even if various authors have underlined its importance for probabilistic logic programming (PLP), lifted inference has been applied up to now only to relational languages outside of logic programming. In this paper we adapt Generalized Counting First Order Variable Elimination (GC-FOVE) to the problem of computing the probability of queries to probabilistic logic programs under the distribution semantics. In particular, we extend the Prolog Factor Language (PFL) to include two new types of factors that are needed for representing ProbLog programs. These factors take into account the existing causal independence relationships among random variables and are managed by the extension to variable elimination proposed by Zhang and Poole for dealing with convergent variables and heterogeneous factors. Two new operators are added to GC-FOVE for treating heterogeneous factors. The resulting algorithm, called LP2 for Lifted Probabilistic Logic Programming, has been implemented by modifying the PFL implementation of GC-FOVE and tested on three benchmarks for lifted inference. A comparison with PITA and ProbLog2 shows the potential of the approach.

Abstract
In this paper we propose a novel approach, named Real-Time Alternative-Route Definition (RT-ARounD), to support real-time message streams over large-scale wireless sensor networks. Starting from a standard cluster-tree topology, where each cluster has active and inactive periods, the proposal selects a set of nodes to build a mesh topology which is used during the inactive periods of the respective clusters to transmit messages with real-time requirements. This new topology is built considering shortest path routes between source and sink nodes. In that way, the number of hops that a real-time message needs to transverse can be drastically reduced, thereby improving the real-time responsiveness of the overall network. Moreover, the use of the inactive period guarantees that the normal cluster-tree operation remains unaffected.

Abstract
This paper describes our recent work on MATISSE, a framework for MATLAB to C compilation. We focus on the new optimizations and transformations, as well as on OpenCL generation. MATISSE is controlled with LARA, an aspect-oriented language, able to specify transformations to the input MATLAB code (e.g., insertion of code for variable initialization and for monitoring) and to express information concerning types and shapes of variables. We evaluate the compiler with a set of benchmarks when targeting both an embedded system and a desktop system. The results show that we were able to achieve a speedup up to 1.8× by employing information provided by LARA aspects. We also compare the execution time of the generated C code with the original code running on MATLAB, and we achieve a geometric mean speedup of 19×. The geometric mean speedup reduces to 12× when optimizing the MATLAB code with LARA aspects. Finally, we present a preliminary version of a fully-functioning pragma-based OpenCL generator, built over the MATISSE framework..

Abstract
Childhood obesity is a consequence of environments that disrupt the balance of energy intake and energy expenditure. Obesogenic environments consist of social norms and environmental factors that facilitate unhealthy behaviors around diet and physical activity. Nutritional knowledge and physical activity are cornerstones of every obesity treatment. The aims are to understand and compare how nutritional knowledge and physical activily panerns occur in children and adolescents, and if there's any differences by gender. Methods Sample comprised 467 children and adolescents, 237 boys. PA was measured using Actigraph accelerometers (GTSXsl^ Participants were instructed to use the accelerometer, according to standard procedures, and data analyzed using the recommended guidelines (Evenson et al, 2008) Nutritional Knowledge INKI was assessed using the General Nutrition Questionnaire for Portuguese Adolescent, and results presented as a Final Nutritional Score, in accordance with standard procedures (Ferro-Lebres, V, Ribeiro, J, Moreira, P, 2014). Height, weight body mass index were also assessed. Univariate Analysis of Variance-GLM was used to compare genders ad|usted to different school leveis of the studente, using SPSS. Results Our results present higher (p<0,05| nutritional scores for"girls (67,11 than boys (63,6 scorel. Opposed to these results boys los expectedl significantly present higher amounts of moderate to vigorous PA compared to girls 171,6 min. /day vs 42,3 min. /day; p<0, 01|. Additionally, we have 14,7% overweight/obese girls and 17,4% overweight/obese boys. Discussion Other studies have obsen/ed similar results regarding MVPA in boys and girls, but the NK about diet and nutritïon is also crucial for the treatment ond prevention of obesity in chiidren. Therefore ifs important to understand if higher scores in NK would lead to better nutritional practices; would it be possible that inaeasing studenfs NK about food contents regarding different nutrients could improve their daily practices. Do children and adolescents that have better NK behave differently regarding PA practices?

Abstract
Scheduling problems in parallel machines have been deeply studied and many are too complex to be solved by exact methods. The unrelated parallel machines makespan minimization problem (Rm||Cmax) is known to be NP-hard and is usually solved using heuristics. Considering heuristics used in these problems, it is possible to identify two different approaches, those that use the execution time to allocate tasks and those that use the completion time. This paper proposes a new heuristic, OMCT (Ordered Minimum Completion Time), based on the performance limitation of the MCT (Minimum Completion Time). The computational study results demonstrate the effectiveness of the proposed heuristic. © 2014 AISTI.

Abstract
ISO 26262, a functional-safety standard, uses Automotive Safety Integrity Levels (ASILs) to assign safety requirements to automotive-system elements. System designers initially assign ASILs to system-level hazards and then allocate them to elements of the refined system architecture. Through ASIL decomposition, designers can divide a function’s safety requirements among multiple components. However, in practice, manual ASIL decomposition is difficult and produces varying results. To overcome this problem, a new tool automates ASIL allocation and decomposition. It supports the system and software engineering life cycle by enabling users to efficiently allocate safety requirements regarding systematic failures in the design of critical embedded computer systems. The tool is applicable to industries with a similar concept of safety integrity levels. © 1984-2012 IEEE.