Abstract
Increasing the penetration of renewable resources has aggravated the operational flexibility at distribution level. In this study, a flexibility-oriented scheduling of microgrids (MGs) is suggested to reduce the power fluctuations in distribution feeders caused by the high penetration of wind turbines (WTs) in MGs. A flexibility constraint as viable and practical solution is used in MG scheduling to address this challenge. The presented scheduling model, implemented using mixed integer linear programming (MILP) and a stochastic framework, exercises risk constraints to capture the uncertainties associated with wind turbines, loads and market prices. The effectiveness of the model is investigated on a MG with high penetration of WTs in the presence of demand response (DR) and energy storage systems (ESSs). Numerical studies show the influence of risk parameters' changing on operation costs. In addition, the flexibility constraint mitigates the sharp variation of the net load at distribution level, which improves the flexibility of the distribution system.

Abstract
Hybrid programs combine digital control with differential equations, and naturally appear in a wide range of application domains, from biology and control theory to real-time software engineering. The entanglement of discrete and continuous behaviour inherent to such programs goes beyond the established computer science foundations, producing challenges related to e.g. infinite iteration and combination of hybrid behaviour with other effects. A systematic treatment of hybridness as a dedicated computational effect has emerged recently. In particular, a generic idealized functional language HYBCORE with a sound and adequate operational semantics has been proposed. The latter semantics however did not provide hints to implementing HYBCORE as a runnable language, suitable for hybrid system simulation (e.g. the semantics features rules with uncountably many premises). We introduce an imperative counterpart of HYBCORE, whose semantics is simpler and runnable, and yet intimately related with the semantics of HYBCORE at the level of hybrid monads. We then establish a corresponding soundness and adequacy theorem. To attest that the resulting semantics can serve as a firm basis for the implementation of typical tools of programming oriented to the hybrid domain, we present a web-based prototype implementation to evaluate and inspect hybrid programs, in the spirit of GHCI for HASKELL and UTOP for OCAML. The major asset of our implementation is that it formally follows the operational semantic rules.

Abstract
For many years, industrial engineers and managers have differentiated their duties in the work environment. While this has allowed for the two specialities to operate in their respective domains, the all necessary integration required to deliver a seamless industrial operation and outcomes has been sub-optimal - particularly in cases of conflict of knowledge or power. Industrial engineering and management (IEM) has come to resolve this situation, creating a new professional field and profile, as well as a multifaceted specialisation with a practical character. The challenge to take the next step in the refinement of this relatively new reality in Portugal is placed upon the most recent IEM degree, at the University of Tras-os-Montes e Alto Douro (UTAD).

Abstract
Medical imaging is a rich source of invaluable information necessary for clinical judgements. However, the analysis of those exams is not a trivial assignment. In recent times, the use of deep learning (DL) techniques, supervised or unsupervised, has been empowered and it is one of the current research key areas in medical image analysis. This paper presents a survey of the use of DL architectures in computer-assisted imaging contexts, attending two different image modalities: the actively studied computed tomography and the under-studied positron emission tomography, as well as the combination of both modalities, which has been an important landmark in several decisions related to numerous diseases. In the making of this review, we analysed over 180 relevant studies, published between 2014 and 2019, that are sectioned by the purpose of the research and the imaging modality type. We conclude by addressing research issues and suggesting future directions for further improvement. To our best knowledge, there is no previous work making a review of this issue.

Abstract
MathE (mathe.pixel-online.org) is an e-learning platform for higher education developed and implemented by a consortium of seven institutional partners from five European countries. The aim of the project is to enhance the quality of teaching and improve pedagogies and assessment methods by facilitating the identification of students’ gaps in Math, providing appropriate digital tools and promoting self-evaluation with immediate feedback. The Polytechnic Institute of Bragança (IPB), in Portugal, is one of the consortium members: sixteen of its teachers collaborate in the development of this platform, being responsible for thirteen of the topics/subtopics in which the platform is structured. Such topics cover a wide range of contents, from linear transformations to integration, from graph theory to probabilities. The articulation of the topics of the MathE collection corresponds to the canonic mathematics content of engineering, business and education degrees. The MathE platform is organized into three main sections: Student´s Assessment, MathE Library and Community of Practice. So far, IPB has already developed a collection of around 800 questions for the student´s assessment section and is currently developing the MathE Library. More than 350 students from IPB are using the MathE platform; some offered as volunteers, whose role is testing the behavior of the platform as well as looking for bugs and other details that require improvement, while others are already using the platform in their study. The feedback received up until now is quite encouraging.

Abstract
We consider a farm of Kite Power Systems (KPS) in the field of Airborne Wind Energy (AWE), in which each kite is connected to an electric ground generator by a tether. In particular, we address the problem of selecting the best layout of such farm in a given land area such that the total electrical power generated is maximized. The kites, typically, fly at high altitudes, sweep a greater area than that of traditional wind turbines, and move within a conic shaped volume with vertex on the ground station. Therefore, constraints concerning kite collision avoidance and terrain boundaries must be considered. The efficient use of a given land area by a set of KPS depends on the location of each unit, on its tether length and on the elevation angle. In this work, we formulate the KPS farm layout optimization problem. Considering a specific KPS and wind characteristics of the given location, we study the power curve as a function of the tether length and elevation angle. Combining these results with an area with specified length and width, we develop and implement a heuristic optimization procedure to devise the layout of a KPS farm that maximizes wind power generation. (C) 2019 Published by Elsevier Ltd.