Abstract
New virtual reality technologies allow the user to gain a greater sense of presence in virtual environments. One of the areas where these technologies can have a major impact is the area of games that allow users to explore these environments and interact with them by receiving feedback from their actions in real time. The present study aimed to evaluate if the use of physiological signals to update the virtual environment in real-time could be used to increase the feeling of presence. To perform this study, an experimental study was designed based on a game that allowed the use of physiological data to calculate the participant's arousal in real-time and, based on that, modify certain elements of the virtual environment where the participants were asked to fulfill a task. With the analysis of the data obtained, it was possible to verify that the use of biofeedback did not reveal statistically significant differences for the variables tested, however, it can be concluded that the use of biofeedback improves some subscales of presence, being the users with more experience in games and more computer knowledge susceptible to such changes.

Abstract
The problem on how to distribute the publication credits among ordered coauthors has been extensively discussed in the literature. However, there is no consensus about what is the most adequate procedure. This paper studies the properties of the existing counting methods and shows an impossibility result regarding the existence of a general counting method able to satisfy no advantageous merging and no advantageous splitting simultaneously—two properties that we consider fundamental. Our results suggest that the generalized variations of the geometric and the harmonic counting methods are the most flexible and robust in theoretical terms.

Abstract
Complex optimization scheduling problems frequently arise in the manufacturing and transport industries, where the goal is to find a schedule that minimizes the total amount of time (or cost) required to complete all the tasks. Since it is a critical factor in many industries, it has been, historically, a target of the scientific community. Mathematically, these problems are modelled with Job Shop scheduling approaches. Benchmark results to solve them are achieved with evolutionary algorithms. However, they still present some limitations, mostly related to execution times and the difficulty to generalize to other problems. Deep Reinforcement Learning is poised to revolutionise the field of artificial intelligence. Chosen as one of the MIT breakthrough technologies, recent developments suggest that it is a technology of unlimited potential which shall play a crucial role in achieving artificial general intelligence. This paper puts forward a state-of-the-art review on Job Shop Scheduling, Evolutionary Algorithms and Deep Reinforcement Learning. It also proposes a novel architecture capable of solving Job Shop Scheduling optimization problems using Deep Reinforcement Learning.

Abstract
Bioinformatics Algorithms: Design and Implementation in Python provides a comprehensive book on many of the most important bioinformatics problems, putting forward the best algorithms and showing how to implement them. The book focuses on the use of the Python programming language and its algorithms, which is quickly becoming the most popular language in the bioinformatics field. Readers will find the tools they need to improve their knowledge and skills with regard to algorithm development and implementation, and will also uncover prototypes of bioinformatics applications that demonstrate the main principles underlying real world applications.

Abstract
Design-for-X (DfX) approaches are of great importance to support sustainable development of new products, since the goal of DfX practices is to improve life cycle cost, life cycle environmental performance, increase design flexibility, manufacturing efficiency, etc. Therefore DfX supports a better decision-making process whenever a new complex product is being developed. In this work the new Lean Design-for-X (LDfX) approach is presented embracing the principles of Lean Product Development and Modular Design, for a systematic applicability by design engineers and product managers, assessing the effectiveness and efficiency of a given product design. An LDfX index metric, ranging between 0-100%, and original scorecard were created for consistent decision support for the comparison of different design concepts or products, integrating different "X" domains. The approach was applied in a real design study of a machine tool (press-brake), integrating Ecodesign principles, Design for Structural Optimization and Modular Design. (C) 2018 The Authors. Published by Elsevier B.V.

Abstract
This paper investigates ac-dc-ac multilevel topologies for three-phase four-wire applications obtained from an interconnection of three-leg voltage-source converters. The topologies can be applied in line voltage regulators, universal active power filters, and uninterrupted power supplies. Operating principles, a pulsewidth modulation (PWM) technique, and an overall control strategy are developed. The PWM and control strategies are suitable to regulate the dc-link voltages and to reduce the harmonic distortion, switching stress, and power losses. Simulation results are used to compare the proposed configurations with a conventional solution in terms of harmonic distortion, semiconductor losses, and others characteristics. Experimental results are presented to validate the theoretical considerations and were obtained by using insulated-gate bipolar transistors with dedicated drives and a digital signal processor with appropriated plug-in boards and sensors.