Abstract
Developed focusing agriculture sustainability, mySense is a comprehensive close-range sensor-based data management environment to improve precision farming practices. It integrates discussion platforms for quick problem solving through experts support and a computational intelligence layer for multipurpose application (e.g. vine variety discrimination, plant disease detection and identification). Attending the need for keeping track of agricultural crops not only based on close-range sensing but also at a macro perspective, mySense was complemented with proper functionalities to unlock macro-monitoring features, through the implementation of a Web-based Geographical Information System (WebGIS) planned as a sidekick application that provides agriculture professionals with visual decision support tools over remote sensed data. This paper presents and discusses its specification and implementation.

Abstract
This paper deals with multi-objective location-routing problems (MO-LRPs) and follows a sectorizationapproach, which means customers are divided into different sectors, and a distribution centre is opened for eachsector. The literature has considered objectives such as minimizing the number of opened distribution centres,the variances of compactness, distances and demands in sectors. However, the achievement of these objectivescannot guarantee the geographical separation of sectors. In this sense, and as the geographical separation ofsectors can have significant practical relevance, we propose a new objective function and solve a benchmarkof problems with the non-dominated sorting genetic algorithm (NSGA-II), which finds multiple non-dominatedsolutions. A comparison of the results shows the effectiveness of the introduced objective function, since, in thenon-dominated solutions obtained, the sectors are more geographically separated when the values of the objectivefunction improve.

Abstract
This research analyzes the discrepancies respecting parents' and their children's perspectives on adolescents' risky online behaviors and parental mediation. Rather than focus solely on youth outcomes, this study explores dyadic data, by comparing reports from adolescents attending 7th to 12th grades in Portuguese schools and those of their parents (N=1016). Moreover, this research considers the existence of defense mechanisms influencing adolescents' reports, a factor that has been neglected in previous studies. Differences regarding adolescents' gender, parents' gender, and adolescents' school year are considered and tested using One-way ANOVA. Within the family unit, the only members considered by adolescents to have the same or more online and computer skills than the teenagers themselves are their older siblings. Practical implications aiming to mitigate the risk involved in adolescents' online experiences, and theoretical contributions to the field of prevention and youth well-being in the context of consumer behavior in the digital age are discussed.

Abstract
Nowadays the production systems are linear and the consumption patterns are essentially based on products with a short life cycle, which contribute to increase the demand for raw materials and environmental impacts. The Circular Economy (CE) is playing a major role among scholars and practitioners. Many aspects are now defining this new trending paradigm such as the roles of product development, transformation and remanufacturing/recycling, and/or management of waste, ensuring the economic and environmental benefits. The increasing demand causes instability of the prices and markets, and there is also the risk of supply rupture. This is very unsustainable and puts at risk countries' development. In this work we analyze and assess some EU critical raw material (CRM), considering existing global reserves and production. Correlation between several parameters was also analyzed. Under this assumption one scenario was considered to assess the depletion of two CRM. China is the main supplier in 15 out of 25 CRM considered in this analysis and its average percentage is 65%. Phosphate rock presents the highest value and antimony the lowest for depletion indicator. It was possible to conclude that no significant correlation was found between depletion, self-sufficiency and economic importance indicators. (C) 2019 Published by Elsevier Ltd.

Abstract

Abstract
Presentation attack detection (PAD) methods are commonly evaluated using metrics based on the predicted labels. This is a limitation, especially for more elusive methods based on deep learning which can freely learn the most suitable features. Though often being more accurate, these models operate as complex black boxes which makes the inner processes that sustain their predictions still baffling. Interpretability tools are now being used to delve deeper into the operation of machine learning methods, especially artificial networks, to better understand how they reach their decisions. In this paper, we make a case for the integration of interpretability tools in the evaluation of PAD. A simple model for face PAD, based on convolutional neural networks, was implemented and evaluated using both traditional metrics (APCER, BPCER and EER) and interpretability tools (Grad-CAM), using data from the ROSE Youtu video collection. The results show that interpretability tools can capture more completely the intricate behavior of the implemented model, and enable the identification of certain properties that should be verified by a PAD method that is robust, coherent, meaningful, and can adequately generalize to unseen data and attacks. One can conclude that, with further efforts devoted towards higher objectivity in interpretability, this can be the key to obtain deeper and more thorough PAD performance evaluation setups.