Abstract
This paper presents the development of a complete methodology for power systems scheduling with highly variable sources based on a risk assessment model. The methodology is tested in a real case study, namely an island with high penetration of renewable energy production. The uncertainty of renewable power production forecasts and load demand are defined by the probability distribution function, which can be a good alternative to the scenarios approach. The production mix chosen for each hour results from the costs associated to the operation risks, such as load shed and renewable production curtailment. The results to a seven days case study allow concluding about the difficulty to achieve a complete robust solution.

Abstract
The number of everyday interconnected devices continues to increase and constitute the Internet of Things (IoT). Things are small computers equipped with sensors and wireless communications capabilities that are driven by energy constraints, since they use batteries and may be required to operate over long periods of time. The majority of these devices perform data collection. The collected data is stored on-line using web-services that, sometimes, operate without any special considerations regarding security and privacy. The current work proposes a modified hash-chain authentication mechanism that, with the help of a smart-phone, can authenticate each interaction of the devices with a REST web-service using One Time Passwords (OTP). Moreover, the proposed authentication mechanism adheres to the stateless, HTTP-like behavior expected of REST web-services, even allowing the caching of server authentication replies within a predefined time window. No other known web-service authentication mechanism operates in such manner.

Abstract

Abstract
Background: Catechol-O-methyltransferase (COMT) is a catabolic enzyme involved in the degradation of bioactive molecules including the neurotransmitters epinephrine, norepinephrine, and dopamine. Higher COMT activity in depressive patients in comparison to non-depressed individuals has been reported. The effect of aerobic exercise on depressive patients has been studied and a number of researchers and clinicians believe it to be effective in the treatment of depression and to be involved in several molecular underlying mechanisms. However, the effect of physical exercise on this enzyme activity is unknown, and it remains to be elucidated if chronic exercise changes COMT activity. This randomized control trial evaluates the effects of chronic exercise on peripheral COMT (S-COMT) activity in women with depressive disorder. Methods: Fourteen women (aged: 51.4 + 10.5 years) diagnosed with depression (according to International Classification of Diseases-10) were randomized to one of two groups: pharmacotherapy plus physical exercise (n=7) or only pharmacotherapy (n=7). The aerobic exercise program was supervised, lasting between 45-50 min/session, three times/week for 16 weeks. Erythrocyte soluble COMT were assessed prior to and after the exercise program. Results: Exercise group when compared to a control group presented a significant decrease (p=0.02, r=-0.535) in S-COMT activity between baseline and post-intervention. Limitations: These data are preliminary outcomes from a small sample and should be replicated. Conclusions: Chronic exercise therapy combined with pharmacotherapy leads to significant decrease in S-COMT activity. Our results provide evidence that exercise interferes with S-COMT activity, a molecular mechanism involved in depression. (C) 2016 Published by Elsevier B.V.

Abstract
The CG research community has a renewed interest on rendering algorithms based on path space integration, mainly due to new approaches to discover, generate and exploit relevant light paths while keeping the numerical integrator unbiased or, at the very least, consistent. Simultaneously, the current trend towards massive parallelism and heterogeneous environments, based on a mix of conventional computing units with accelerators, is playing a major role both in HPC and embedded platforms. To efficiently use the available resources in these and future systems, algorithms and software packages are being revisited and reevaluated to assess their adequateness to these environments. This paper assesses the performance and scalability of three different path based algorithms running on homogeneous servers (dual multicore Xeons) and heterogeneous systems (those multicore plus manycore Xeon and NVidia Kepler GPU devices). These algorithms include path tracing (PT), its bidirectional counterpart (BPT) and the more recent Vertex Connect and Merge (VCM). Experimental results with two conventional scenes (one mainly diffuse, the other exhibiting specular-diffuse-specular paths) show that all algorithms scale well across the different platforms, the actual scalability depending on whether shared data structures are accessed or not (PT vs. BPT vs. VCM).

Abstract
Software refactoring is a well-known technique that provides transformations on software artifacts with the aim of improving their overall quality. We have previously proposed a catalog of refactorings for spreadsheet models expressed in the ClassSheets modeling language, which allows us to specify the business logic of a spreadsheet in an object-oriented fashion. Reasoning about spreadsheets at the model level enhances a model-driven spreadsheet environment where a ClassSheet model and its conforming instance (spreadsheet data) automatically co-evolves after applying a refactoring at the model level. Research motivation was to improve the model and its conforming instance: the spreadsheet data. In this paper we define such refactorings using previously proposed evolution steps for models and instances. We also present an empirical study we designed and conducted in order to confirm our original intuition that these refactorings have a positive impact on end-user productivity, both in terms of effectiveness and efficiency. The results are not only presented in terms of productivity changes between refactored and nonrefactored scenarios, but also the overall user satisfaction, relevance, and experience. In almost all cases the refactorings improved end-users productivity. Moreover, in most cases users were more engaged with the refactored version of the spreadsheets they worked with. 2016 Elsevier Inc. All rights reserved.