Abstract
Governments all over the world have been promoting electric mobility as an effort to reduce the transport sector’s greenhouse emissions and fossil fuel dependency. This work analyses the deployment of electric vehicles in the European Union countries, between 2015 and 2019, and the variables that may influence it, using a panel data methodology. The present work focuses on the deployment of battery and plug-in hybrid electric vehicles, individually and jointly. Nine explanatory variables were included in the model: density of recharging points, gross domestic product per capita, cumulative number of policies on electromobility, share of renewable energy in transport, total greenhouse gas emissions per capita, tertiary education attainment, electricity price, employment rate and new registrations of passenger cars per capita. The results showed that the indicators influence differently the deployment of the different types of electric vehicles. The most significant factor driving the battery electric vehicles deployment was the density of recharging points, while for plug-in hybrid electric vehicles was the share of renewable energy. Policy makers should focus on adjusting actions to the demand for the different types of electric vehicles.

Abstract
This article analyses the impact that educational robotics has on the learning and motivation of primary school students. The study was based on a set of activities developed during the school year, within the scope of the Programming and Robotics Club (PRC), at Agrupamento de Escolas de Monserrate (AEM). These activities involved 66 4th grade students attending two primary schools that belong to AEM. These activities addressed different subjects such as the Discovery of Electrical Continuity, Programming without a Computer and the Discovery of Robotics, among others. At the same time, the AEM Programming and Robotics Club participated in the national contest together with other clubs from the country. At the end of the activities, a questionnaire was applied to the participants, in order to assess the impact they had on these students. The results obtained were very positive, as the students said that the club and its activities are a valuable asset for their development, learning and motivation.

Abstract
The study analyzed several instruments of the master-integrated course in Electrical and Computer Engineering at a Portuguese Public University. The institutional drivers responsible for adopting new methodologies in the course were evaluated. A case study was carried out with a qualitative approach based on mixed methods: a statistical analysis applied to textual corpus and complemented by content analysis. As a result, two classes of content analysis emerged: skills and knowledge expected from students; and aspects of training in Electrical Engineering and the study cycle. Seven drivers were identified for the adoption of new methodologies in the course, based on the theories of diffusion of innovation and institutional theory: training, development, competence, study cycle, new, technology, and UC. Each of these drivers has its outcomes, 16 in total, which shows the effects perceived by the teachers, course coordinators and evaluators.

Abstract
Nowadays, the Portuguese population is aging at a fast pace. The situation is more severe in the interior regions of the country, where the rural areas have few people and have been constantly losing population; these are mostly elderly who, in some cases, live socially isolated. They are also often deprived of some types of social, health and technological services. One of the current challenges with respect to the elderly is that of improving the quality of life for those who still have some autonomy and live in their own residences so that they may continue living autonomously, while receiving the assistance of some exterior monitoring and supporting services. The Internet of Things (IoT) paradigm demonstrates great potential for creating technological solutions in this area as it aims to seamlessly integrate information technology with the daily lives of people. In this context, it is necessary to develop services that monitor the activity and health of the elderly in real time and alert caregivers or other family members in the case of an unusual event or behaviour. It is crucial that the technological system is able to collect data in a nonintrusive manner and without requiring much interaction with the elderly. Smartband devices are very good candidates for this purpose and, therefore, this work proposes assessing the level of acceptance of the usage of a smartbands by senior users in their daily activities. By using the definition of an architecture and the development of a prototype, it was possible to test the level of acceptance of smartbands by a sample of the elderly population-with surprising results from both the elderly and the caregivers-which constitutes an important contribution to the research field of Ambient Assisted Living (AAL). The evaluation showed that most users did not feel that the smartband was intrusive to their daily tasks and even considered using it in the future, while caregivers considered that the platform was very intuitive.

Abstract
In this work, X-ray fluorescence (XRF) and Laser-induced breakdown spectroscopy (LIBS) analyses were applied to samples of quartz, montebrasite, and turquoise hydrothermal veins in the Argemela Tin Mine (Central Portugal). Montebrasite (LiAl(PO4)(OH,F)) is potentially the main ore mineral; with its alteration, lithium (Li) can disseminate into other minerals. A hand sample was cut and analyzed by XRF and LIBS for several elements of interest including Cu, P, Al, Si, and Li. Although XRF cannot measure Li, results from its analysis are effective for distinguishing turquoise from montebrasite. LIBS analysis complemented this study, making it possible to conclude that turquoise does not contain any significant Li in its structure. The difference in spot size between the techniques (5 mm vs. 300 mu m for XRF and LIBS, respectively) resulted in a poorer performance by XRF in accurately identifying mixed minerals. A thin section was petrographically characterized and mapped using LIBS. The mapping results demonstrate the possibility of the successful identification of minerals and their alterations on a thin section. The results of XRF analysis and LIBS mapping in petrographic sections demonstrate the efficacy of these methods as tools for element and mineral identification, which can be important in exploration and mining phases, complementing more traditional techniques.

Abstract
The current trend in energy sustainability and the energy growing demand have given emergence to distributed hybrid energy systems based on renewable energy sources. This study proposes a strategy for the optimal sizing of an autonomous hybrid energy system integrating a photovoltaic park, a wind energy conversion, a diesel group, and a storage system. The problem is formulated as a uni-objective function subjected to economical and technical constraints, combined with evolutionary approaches mainly particle swarm optimization algorithm and genetic algorithm to determine the number of installation elements for a reduced system cost. The computational results have revealed an optimal configuration for the hybrid energy system.