Abstract
As a contribution for sustainability, electric vehicles (EVs) are seen as one of the most effective influences in the transport sector. As complement to the challenges that entails the EVs integration into the grid considering the bidirectional operation (grid-to-vehicle and vehicle-to-grid), there are new concepts associated with the EV operation integrating various benefits for smart homes. In this sense, this paper proposes an improved voltage control of the EV operating as uninterruptible power supply (UPS) in smart homes. With the EV plugged-in into the smart home, it can act as an off-line UPS protecting the electrical appliances from power grid outages. Throughout the paper, the foremost advantages of the proposed voltage control strategy are comprehensively emphasized, establishing a comparison with the classical approach. Aiming to offer a sinusoidal voltage for linear and nonlinear electrical appliances, a pulse-width modulation with a multi-loop control scheme is used. A Kalman filter is used for decreasing significantly the time of detecting power outages and, consequently, the transition for the UPS mode. The experimental validation was executed with a bidirectional charger containing a double stage power conversion (an ac-dc interfacing the grid-side and a dc-dc interfacing the batteries-side) and a digital stage. The computer simulations and the acquired experimental results validate the proposed strategy in different conditions of operation. © 2019, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

Abstract
The actual control quality standards require manufacturers to increase the inspection process. Instead of a sampling method, all items should be inspected and different equipment with different characteristics in the inspection cell need an adaptive system and the control quality cells should be enhanced. The presented work describes a self-adaptable robotized inspection cell for HMI consoles. which comprises the image acquisition system with controlled illumination and a force feedback sensor manipulated by a collaborative robot. The developed robotized cell is capable of detecting different HMI consoles and adapting the inspection routines of the manipulator robot according to the specific console. Moreover, the flexibility of the collaborative robot allows to adapt the camera positioning, lighting, and distance in a way that future HMI consoles can be inspected based on learning strategies.

Abstract
Sustainability is gaining interest among academics and practitioners due to increased stakeholder awareness of environmental and social issues. However, relatively little research has been conducted on the extent to which firms have integrated social sustainability aspects into the management of their supply chains in emerging economies. The purpose of this article is to explore the social issues pertinent to suppliers and to identify measures and dimensions related to social sustainability in emerging economies. Further, it explores the benefits suppliers and buyers gain by effectively managing such social issues. For this purpose, first, in-depth interviews were conducted with 27 supply chain managers. Further, a survey was conducted in Indian manufacturing industries and co-variance-based structural equation modeling was used to test the hypothesized model. The findings reveal that there are 18 validated supplier social sustainability measures underlying five social dimensions: labor rights, safety and health, societal responsibility, diversity, and product responsibility. The results also suggest a positive relationship between supplier social sustainability practices and supply chain performance mediated by supplier performance. In addition, the role of the buyer's commitment and investment moderates both suppliers and supply chain performance. These results are relevant because they not only identify the social issues plaguing supply chains in emerging economies, but also have practical implications for organizations trying to build socially sustainable supply chains for competitive advantage.

Abstract
Objectives: The aim of this study was to explore the relationships between eating behavior dimensions and psychopathological symptoms among Portuguese undergraduate students. Methods: We studied 258 participants (62.4% women) regarding eating behavior dimensions (emotional, external and binge eating, flexible and rigid control of eating behavior, and eating self-efficacy), psychopathological distress (as assessed by the Brief Symptom Inventory), and body mass index. In addition to studying bivariate associations between eating behavior dimensions and psychopathological subscales and indexes, what we believe to be a novel analytical approach, considering simultaneously the effects of the overall level of psychopathological distress and the relevance of specific symptoms on the eating behavior dimensions. Results: Emotional, external, and binge eating had positive correlations with psychopathological symptomatology, whereas eating self-efficacy was negatively associated. Conclusions: Multivariate analysis showed that the overall level of psychopathological distress (combined with body mass index, among women) had a larger effect on eating behavior than the relevance of specific symptoms.

Abstract
Wearable Health Devices (WHDs) are increasingly helping people to better monitor their health status both at an activity/fitness level for self-health tracking and at a medical level providing more data to clinicians with a potential for earlier diagnostic and guidance of treatment. The technology revolution in the miniaturization of electronic devices is enabling to design more reliable and adaptable wearables, contributing for a world-wide change in the health monitoring approach. In this paper we review important aspects in the WHDs area, listing the state-of-the-art of wearable vital signs sensing technologies plus their system architectures and specifications. A focus on vital signs acquired by WHDs is made: first a discussion about the most important vital signs for health assessment using WHDs is presented and then for each vital sign a description is made concerning its origin and effect on heath, monitoring needs, acquisition methods and WHDs and recent scientific developments on the area (electrocardiogram, heart rate, blood pressure, respiration rate, blood oxygen saturation, blood glucose, skin perspiration, capnography, body temperature, motion evaluation, cardiac implantable devices and ambient parameters). A general WHDs system architecture is presented based on the state-of-the-art. After a global review of WHDs, we zoom in into cardiovascular WHDs, analysing commercial devices and their applicability versus quality, extending this subject to smart t-shirts for medical purposes. Furthermore we present a resumed evolution of these devices based on the prototypes developed along the years. Finally we discuss likely market trends and future challenges for the emerging WHDs area.

Abstract
Topology formation in wireless sensor networks is usually done assuming just either the geographical proximity between nodes or the signal strength of communication. In this paper, a heuristic called DbCTF is proposed to guide the formation of cluster-tree networks, which also considers data clustering techniques. The use of DbCTF allows the setup of a data-based topology in the cluster-tree, and also the prioritisation of monitored regions in which relevant events may be occurring. The performance of DbCTF has been compared with a state-of-the-art algorithm, for the specific case of a classical WSN laboratory experiment. The simulation assessment revealed that the cluster-tree formed by DbCTF was able to reduce by more than 20% the average communication delay of message streams conveying critical data, and was also able to increase by more than 35% the average lifetime of the network.