Abstract
Epilepsy being one of the most prevalent neurological disorders, affecting approximately 50 million people worldwide, and with almost 30-40% of patients experiencing partial epilepsy being nonresponsive to medication, epilepsy surgery is widely accepted as an effective therapeutic option. Presurgical evaluation has advanced significantly using noninvasive techniques based on video monitoring, neuroimaging, and electrophysiological and neuropsychological tests; however, certain clinical settings call for invasive intracranial recordings such as stereoelectroencephalography (SEEG), aiming to accurately map the eloquent brain networks involved during a seizure. Most of the current presurgical evaluation procedures focus on semiautomatic techniques, where surgery diagnosis relies immensely on neurologists' experience and their time-consuming subjective interpretation of semiology or the manifestations of epilepsy and their correlation with the brain's electrical activity. Because surgery misdiagnosis reaches a rate of 30%, and more than one-third of all epilepsies are poorly understood, there is an evident keen interest in improving diagnostic precision using computer-based methodologies that in the past few years have shown near-human performance. Among them, deep learning has excelled in many biological and medical applications, but has advanced insufficiently in epilepsy evaluation and automated understanding of neural bases of semiology. In this paper, we systematically review the automatic applications in epilepsy for human motion analysis, brain electrical activity, and the anatomoelectroclinical correlation to attribute anatomical localization of the epileptogenic network to distinctive epilepsy patterns. Notably, recent advances in deep learning techniques will be investigated in the contexts of epilepsy to address the challenges exhibited by traditional machine learning techniques. Finally, we discuss and propose future research on epilepsy surgery assessment that can jointly learn across visually observed semiologic patterns and recorded brain electrical activity.

Abstract
The growth of wireless sensor networks (WSN) has resulted in part from requirements for connecting sensors and advances in radio technologies. WSN nodes may be required to save energy and therefore wake up and sleep in a synchronized way. In this paper, we propose an application-driven WSN node synchronization mechanism which, by making use of cross-layer information such as application ID and duty cycle, and by using the exponentially weighted moving average (EWMA) technique, enables nodes to wake up and sleep without losing synchronization. The results obtained confirm that this mechanism maintains the nodes in a mesh network synchronized according to the applications they run, while maintaining a high packet reception ratio.

Abstract
This paper presents an integer linear programming (ILP) model to minimise the total energy-cost of a flake ice production unit in food retail stores. This work is based on a real problem in a Portuguese food retail company, where flake ice in necessary throughout the day in order to maintain fresh fish on the shelves at ideal temperature conditions and humidity levels. The proposed approach aims to provide an energy-efficient scheduling of the production to periods with a lower energy cost, as well as to reduce water consumption, by producing the exact quantities required at the right time, minimising waste. The model was tested on a set of real-world instances from the retail company, and on a set of randomly generated instances. The procedure used to create these instances is presented in the paper. For the sets of tested instances, the results show that the model is strong when compared to the lower bounds provided by the linear programming relaxation of the model. The results from the set of real instances show that it is possible to achieve an energy-efficient scheduling of the production which translates in an average annual cost savings of 34.3% for the stores.

Abstract
Nowadays, we continue to write redundant code which can often be reused from the Web. Reusing programming tasks is beneficial since it speeds up the process of creating applications and reduces the errors related with the task creation from scratch. At the same time, the demands of our applications are increasing, leading to a simple problem having to be solved through several tasks. With the advent of the cloud, there are countless Web services that proliferate on the Web. One solution for developers is to use these Web Services. However, the process of mastering and coordinating all these services manually is time-consuming and error-prone. This paper presents SOS, a Simple Orchestration of Services. The ultimate goal of this tool is to act as a service composer while promoting the separation of concerns for two typical actors in this realm: the developer and the business analyst. The developer must define a service as a SOS task based on a JSON schema and submit it in a Web specialized editor. The business analyst uses the SOS editor, in an interactive way, to chain the required tasks to solve a specific problem. Then, the developer, uses a a simple client API – a SOS engine wrapper – to load a SOS manifest and to iterate over all tasks, without the need to dominate any bureaucratic aspects related with HTTP clients and messages. As a case study, several tasks are instantiated and aggregated in order to generate a composite service for a mobile app whose goal is to give an translated description of a picture taken with a mobile phone.

Abstract
Nowadays, Electric Vehicles (EVs) are the new technology to reduce the usage of fossil fuels and to prevent the environmental issues. But, increasing the number of EVs and mismanagement of their energy in distribution networks would cause higher operational costs and lower network security. This paper evaluates the voltage security of distribution networks in the presence of EVs. Accordingly, the maximization of voltage security margin (VSM) and the minimization of operational cost are considered as the main objective functions in the optimization problem of active and reactive power management. The constraints of the proposed optimization problem include power flow equations, system operating limits and EVs constraints. It is supposed that the EVs are equipped with bidirectional chargers to control active and reactive power, simultaneously. The proposed model is implemented on the 33-bus distribution network to evaluate the performance of the proposed optimization scheme for distribution network management in the presence of EVs.

Abstract
Background/Aims: Personalised nutrition has potential to revolutionise dietary health promotion if accepted by the general public. We studied trust and preferences regarding personalised nutrition services, how they influence intention to adopt these services, and cultural and social differences therein. Methods: A total of 9,381 participants were quota-sampled to be representative of each of 9 EU countries (Germany, Greece, Ireland, Poland, Portugal, Spain, the Netherlands, the UK, and Norway) and surveyed by a questionnaire assessing their intention to adopt personalised nutrition, trust in service regulators and information sources, and preferences for service providers and information channels. Results: Trust and preferences significantly predicted intention to adopt personalised nutrition. Higher trust in the local department of health care was associated with lower intention to adopt personalised nutrition. General practitioners were the most trusted of service regulators, except in Portugal, where consumer organisations and universities were most trusted. In all countries, family doctors were the most trusted information providers. Trust in the National Health Service as service regulator and information source showed high variability across countries. Despite its highest variability across countries, personal meeting was the preferred communication channel, except in Spain, where an automated internet service was preferred. General practitioners were the preferred service providers, except in Poland, where dietitians and nutritionists were preferred. The preference for dietitians and nutritionists as service providers highly varied across countries. Conclusion: These results may assist in informing local initiatives to encourage acceptance and adoption of country-specific tailored personalised nutrition services, therefore benefiting individual and public health. (C) 2017 S. Karger AG, Basel