Abstract
Stochastic search algorithms are black-box optimizers of an objective function. They have recently gained a lot of attention in operations research, machine learning and policy search of robot motor skills due to their ease of use and their generality. However, with slightly different tasks or objective functions, many stochastic search algorithms require complete re-learning in order to adapt the solution to the new objective function or the new context. As such, we consider the contextual stochastic search paradigm. Here, we want to find good parameter vectors for multiple related tasks, where each task is described by a continuous context vector. Hence, the objective function might change slightly for each parameter vector evaluation. Contextual algorithms have been investigated in the field of policy search. However, contextual policy search algorithms typically suffer from premature convergence and perform unfavourably in comparison with state of the art stochastic search methods. In this paper, we investigate a contextual stochastic search algorithm known as Contextual Relative Entropy Policy Search (CREPS), an information-theoretic algorithm that can learn for multiple tasks simultaneously. We extend that algorithm with a covariance matrix adaptation technique that alleviates the premature convergence problem. We call the new algorithm Contextual Relative Entropy Policy Search with Covariance Matrix Adaptation (CREPS-CMA). We will show that CREPS-CMA outperforms the original CREPS by orders of magnitude. We illustrate the performance of CREPS-CMA on several contextual tasks, including a complex simulated robot kick task.

Abstract
Background: Hemiballism may arise as a rare consequence of focal basal ganglia lesions. Pathophysiologically, there is a controversy between the role of the STN as the exclusive lesion localization as opposed to several brain regions in which lesions may induce hemiballism. This is most likely due to a motor circuit affection. Objectives: To study the affection of neural networks in the pathogenesis of hemiballism. Methods: We analysed focal vascular lesions inducing hemiballism (n = 8), their localizations and connectivity profiles. Probabilistic tractography (FSL: http://fsl.fmrib.ox.ac.uk/fsl/) was used to study connectivity. Results: Lesions inducing hemiballism were distributed across several anatomic regions (basal ganglia, thalamus, caudate, internal capsule) without a clear predilection. However, we detected increased connectivity for these lesions toward the STN and mesial cortical motor regions (pre-SMA/SMA). These regions are interconnected via subthalamo-pallido-thalamo-cortical networks. Conclusions: We provide evidence for the involvement of the subthalamo-pallido-thalamic pathways in the pathogenesis of hemiballism, which is consistent with data on experimental hemiballism in animals. Electrophysiological basal ganglia recordings and functional MRI would complement our findings to assess the activation patters within these circuits.

Abstract
Attention-to-task is one of the most important Human cognitive abilities, allowing an individual to selectively focus on a specific issue (among many possible sources) and effectively carry out a task. Without this ability to focus, the individual would constantly switch between stimuli, hardly concluding any task. While attention can be influenced by many internal and external factors, the purpose of this paper is not to analyse them but rather to propose an approach to monitor the attentional behaviour of computer users. The proposed approach may improve the individual's self-awareness as well as the team manager's knowledge about the state of the workforce. It may thus improve the definition of better attention-management strategies, with expected improvements in variables such as on-task behaviour, productivity or work quality.

Abstract
The development of ETL systems has been the target of many research efforts to support its development and implementation. In the last few years, we presented a pattern-oriented approach to develop these systems. Basically, patterns are comprised by a set of abstract components that can be configured to enable its instantiation for specific scenarios. Even when using high-level components, the ETL systems are very specific processes that represent complex data requirements and transformation routines. Several operational requirements need to be configured and system correctness is hard to validate, which can result in several implementation problems. In this paper, a set of formal specifications in Alloy is presented to express the structural constraints and behaviour of a slowly changing dimension pattern. Then, specific physical models can be generated based on formal specifications and constraints defined in an Alloy model, helping to ensure the correctness of the configuration provided.

Abstract
The purpose of the research is to identify the most common social representations of chemistry, green chemistry, robotics and sustainability among teenagers as they were engaging in a project that links robotics and green chemistry. Subjects were students from a school in the north of Portugal enrolled in year 9 (n = 163, 73 males and 86 females, 4 missing values, mean age around 15 years-old). Data was collected through a questionnaire that consisted of four open-ended, free association questions. Participants were asked to express their ideas and thoughts on each one of the four mentioned stimuli and asked to draw a robot. Written responses and drawings of robots were submitted to a content analysis. Preliminary results showed that the ten most frequent words associated with chemistry explain around 49% of the semantic field (average of 4.5 words per participant) and largely consist of conceptual elements, e.g., atoms (38), protons (22) and ions (22), experiments (114), laboratory (62) and explosions (19). The ten most frequent words associated with green chemistry explain around 42% of the semantic field of the representation. Participants - which never have learnt about green chemistry at school curriculum - filled their representations (2.8 words per participant) with elements derived from environment (e.g., nature, environment, trees,...). Only 92 participants defined sustainability, many of them associating the concept with earth's natural resources and future. The ten most frequent words associated with robotics (4.1 words per participant) explain around 53% of the semantic field which consists of robots (129), technology (50), electricity (39), metal (33), energy (20), circuits (18) and computers (17): electronics rather than informatics contribute for the representation. Most of the drawings of robots were anthropomorphic resembling more C-3PO than R2-D2 from Star Wars movies. Human elements, such as eyes, mouth and hands are largely present while movement is assured by means of feet or wheels. The significance of the study is that there is a decalage between science and technology developments and teenager audience understanding. From the point of view of the theory of social representations, this gap is not only expected but also understandable. Popular culture although still inspire the representation of chemistry is not as relevant as it would be if participants have not attended physics and chemistry classes for three years. On the other hand, since green chemistry and robotics are not included in the ordinary curriculum until year 9, the concepts are at loose and their meaning must be grounded elsewhere. Despite the impressive and rapid changes that characterize the technology research, its market and advertising, old metaphors and symbols still contribute to build the representations of teenagers about robotics while green chemistry - a relatively new approach - has its poor semantic field rooted in chemistry and environment. School, thus, must act as a medium to help students to build a coherent worldview that is capable of copying with contemporary challenges, strongly affected by science and technology namely regarding sustainability. An ongoing project is designed to introduce green chemistry experiments that involve slow reactions via a programmable robotic arm in the school laboratory to conduct. The planned activities include monitoring experiences by students at home by means of a live webcam.

Abstract
An abrupt transition from sinus rhythm to atrial fibrillation (AF) is common in patients with chronic heart failure (CHF). We propose a conceptual framework for viewing this malignant transition in terms of a type of sublimation marked by the switch from highly periodic sinus interbeat interval dynamics characteristic of CHF to a state of random disorganization with AF. Sublimation of physical substances involves an increase in entropy via heat transfer. In contrast, the disease-related sublimation-like behavior involves a loss of information content, associated decreases in cardiac bioenergetic capacity and in multiscale entropy. © 2016 Wiley Periodicals, Inc. Complexity 21: 24–32, 2016. © 2016 Wiley Periodicals, Inc.