Abstract
Food waste is responsible for severe environmental, social, and economic issues and therefore it is imperative to prevent or at least minimize its generation. The main cause of food waste is poor demand forecasting and so it is essential to improve the accuracy of the tools tasked with these forecasts. The present work proposes four models meant to help food catering services predict food demand accurately and thus avoid overproducing or underproducing. Each model is based on a different machine learning technique. Two baseline models are also proposed to mimic how food catering services estimate future demand and to infer the added value of employing machine learning in this context. To verify the impact of the proposed models, they were tested on data from the three different canteens chosen as case studies. The results show that the models based on the random forest algorithm and the long short-term memory neural network produced the best forecasts, which would lead to a 14% to 52% reduction in the number of wasted meals. Furthermore, by basing their decisions on these forecasts, the food catering services would be able to reduce unmet demand by 3% to 16% when compared with the forecasts of the baseline models. Thus, employing machine learning to forecast future demand can be very beneficial to food catering services. These forecasts can increase the service level of food services and reduce food waste, mitigating its environmental, social, and economic consequences.

Abstract
The relationship between hydrogen and electricity has gained attention due to their interconnected roles in the energy transition. Existing joint electricity and hydrogen market models often overlook the dependence between electricity and hydrogen prices. Indeed, while electrolyzers production can raise electricity prices, electricity price significantly impacts the costs of hydrogen production. Considering this price-based interdependency, this study compares a Cournot equilibrium and a perfect competition market model for electricity and hydrogen integration. Both models are transformed into new quadratic optimization problems to facilitate resolution. The analysis highlights the potential of the Iberian region for hydrogen production. Furthermore, it is evident that, under conditions of perfect competition, renewable generation is given priority for meeting electricity demand, leading to a decrease in both electricity and hydrogen prices on a global scale compared to the Cournot scenario.

Abstract
This paper presents a usability evaluation of a companion application for managing older adults' physical activity sessions in an immersive multiuser virtual environment. The companion application was designed to facilitate the trainer ' s role and enhance the overall user experience in the virtual multiuser environment. Four trainers were recruited to participate in the study, they performed two tasks to prepare and manage training sessions with older adults using the companion application. Researchers used an open-ended questionnaire to interview the participants. The results revealed a high satisfaction and appreciation for the application features used to prepare and manage the training sessions. Participants found the application useful and intuitive, and they also recommended a list of future desirable features related to the application ' s feedback and help mechanisms, as well as its content. In addition to the necessity to provide mobile and tablet versions of the application. A few usability problems were detected related to information presentation and navigation. The future design of the companion application will consider all the detected usability problems and desired features.

Abstract
Higher education institutions (HEIs) make decisions in several domains, namely strategic and internal management, without using systematized data that support these decisions, which may jeopardize the success of their actions or even their efficiency. Thus, HEIs must define and monitor strategies and policies essential for decision making in their various areas and levels, in which business intelligence (BI) plays a leading role. This study presents a systematic literature review (SLR) aimed at identifying and analyzing primary studies that propose a roadmap for the implementation of a BI system in HEIs. The objectives of the SLR are to identify and characterize (i) the strategic objectives that underlie decision making, activities, processes, and information in HEIs; (ii) the BI systems used in HEIs; (iii) the methods and techniques applied in the design of a BI architecture in HEIs. The results showed that there is space for developing research in this area since it was possible to identify several studies on the use of BI in HEIs, although a roadmap for its implementation was not identified, making it necessary to define a roadmap for the implementation of BI systems that can serve as a reference for HEIs.

Abstract
In the context of the R3EA project, funded by the Portuguese Foundation for Science and Technology (FCT), we analyse a set of selected future power system scenarios to assess the impact, on the Iberian electricity market (MIBEL), of installing wind and solar generation capacity in Portugal's Centro Region. We use the long-term MIBEL operation and planning model CEVESA. The scenarios are designed based on the current economic situation and the last National Energy and Climate Plan drafts for Portugal and Spain, by distributing the expected new wind and solar generation capacity differently among Portugal regions, also considering the flexible demand for producing electrolytic hydrogen. Market prices, capture prices and production per technology are analysed to assess this impact. Results show that regional investments have no significant impact on the MIBEL variables analysed.

Abstract
Hospitalization has been identified as stress-inducing event that potentially contributes to depression and anxiety among children, particularly when the duration of hospital stay is prolonged. This scoping review seeks to identify the role of videogames and other interactive technology in reducing stress and promoting well-being, exploring the specific considerations for developing videogames for in- patient children and focusing on understanding various outcomes with different types of interactive technologies. The databases used in this research were ACM, PubMed, Wiley Library, yielding a total of 90 articles. Following the application of exclusion criteria 7 articles were selected for analysis. It is noteworthy that many of the included articles exhibit limitations, such as restricted study durations and a small number of participants. Addressing these limitations is crucial for establishing the long-term efficacy of interactive technology and videogames in promoting the well-being of in-patient children.