Abstract
Electricity markets are complex and dynamic environments with very particular characteristics. Ambitious goals, including those set by the European Union, foster the increased use of distributed generation, essentially based on renewable energy sources. This requires major changes in electricity markets and energy systems, namely through the adoption of the smart grid paradigm. The use of simulation tools and the study of different market mechanisms and the relationships between their stakeholders are essential. One of the main challenges in this area is developing decision support tools to address the problem as a whole. This work contributes to increasing interoperability between heterogeneous systems, namely agent-based, directed to the study of electricity markets, the operation of smart grid, and energy management. To this end, this work proposes the use of ontologies to ease the interaction between entities of different natures and the use of semantic web technologies to develop more intelligent and flexible tools. A multiagent systems society, composed of several heterogeneous multiagent systems, which interact using the proposed ontologies, is presented as a proof-of-concept. © 2021, Springer Nature Switzerland AG.

Abstract
The complex multi-criteria optimisation problems arising in Kidney Exchange Programmes have received considerable attention both in practice and in the scientific literature. Whereas theoretical advancements are well reviewed and synthesised, this is not the case for practice. We present a synthesis of models and methods applied in present European Kidney Exchange Programmes, which is based on detailed descriptions we created for this purpose. Most descriptions address national programmes, yet we also present findings on emerging cross-national programmes. The synthesis provides a systematic and detailed description of the models and methods the programmes use, revealing important commonalities as well as considerable variation among them. Rather than distilling a single best practice from these results, we find that the variation in models and methods arises because of variation in country characteristics, policies, and ethics. The synthesised state of the art may benefit future national and cross-national initiatives and direct future theoretical contributions within and across the boundaries of the Operations Research discipline. (c) 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract
With the implementation of the General Data Protection Regulation (GDPR) in the European Union, companies must be able to ensure that applications requesting the user to record personal data inform the user of the purpose for which the data collected is being collected. Furthermore, it is also necessary to ensure the data owner has given his/her explicit consent to the collection of these data and that such consent is recorded. This imperative has required a reworking of the interfaces of the applications. In this sense, this study seeks to explore the policies and practices that are being followed by organizations in designing interfaces. Four case studies were considered in the development of this study to explore this phenomenon in the dimensions of pragmatic hedonic processes of interface design, approaches to collect consent, and how personal data is managed. Copyright © 2021 by Author/s and Licensed by Veritas Publications Ltd., UK.

Abstract
The importance of e-learning tools facilitating the process of learning to program is growing, especially as the pandemic-caused lockdown enforced distance learning in many countries. The key success factor in this process is the provision of an instant and relevant feedback to students. In this paper, we describe a novel open-source programming learning environment featuring automatic assessment of students' solutions and customized gamification. This environment has been developed as a part of the FGPE framework. © José Carlos Paiva, Ricardo Queirós, José Paulo Leal, Jakub Swacha, and Filip Miernik; licensed under Creative Commons License CC-BY 4.0 Second International Computer Programming Education Conference (ICPEC 2021).

Abstract
A zero-one quadratic assignment model has been proposed for dealing with the storage location assignment problem when there are weight constraints. Our analysis shows that operations can be improved using our model. When comparing the strategy currently used in a real-life company with the designed model, we found that the new placement of products allowed a reduction of up to 22% on the picking distance. This saving is higher than that achieved with the creation of density zones, a procedure commonly used to deal with weight constraints, according to the literature.

Abstract