Abstract

Abstract
Advanced control, operation, and planning tools of electrical networks with ML are not straightforward. 110 experts were surveyed to show where and how ML algorithms could advance. This paper assesses this survey and research environment. Then, it develops an innovation roadmap that helps align our research community with a goal-oriented realisation of the opportunities that AI upholds. This paper finds that the R&D environment of system operators (and the surrounding research ecosystem) needs adaptation to enable faster developments with AI while maintaining high testing quality and safety. This roadmap serves system operators, academics, and labs advancing next-generation electrical network tools.

Abstract
In the field of intelligent autonomous robots, integrating optimization techniques with classical control theory methods for mobile robot control is an increasingly prominent area of research. The combination enhances robots' ability to perform their tasks more efficiently, reliably, and safely. This paper addresses the development of a path and motion planning framework for omnidirectional robots, leveraging B-Splines and Trajectory Tracking with Model Predictive Control. The proposed framework is evaluated through software-in-the-loop tests using two distinct dynamical models and sets of hyperparameters. Final validation is conducted by implementing the framework within a ROS environment and performing field tests on a robotic platform. The results demonstrate that the robot can reliably track trajectories at its actuation limits, and the proposed framework enables the robot to increase its velocity up to 50% when compared to a PID path-following controller.

Abstract
Digital transformation has been taking place for several decades in different sectors of activity and is contributing significantly to mitigating the environmental impacts of those sectors. Various digital solutions are related to energy consumption and production, which is crucial to ensure continuous decarbonisation. Most of them are targeted to be used by general consumers. Therefore, it is essential to consider consumers' attitudes towards those solutions and their adoption behaviour to ensure a broad diffusion of them. This study uses the Technology Acceptance Model to understand the adoption of energy-related digital solutions in Europe. We conclude that the perceived usefulness of the solutions is more relevant in attitude formation than the perceived ease of use. Moreover, attitude highly influences adoption behaviour, as reported in the literature. Finally, these relations seem to be highly influenced by the belief that, by adopting digital solutions, consumers contribute to a better balance between energy supply and demand.

Abstract
Archaeological discoveries can benefit enormously from linked open data (LOD) technologies since, as new objects are discovered, data about them can be placed in the LOD cloud and instantly accessible to third parties. This article presents a framework developed to publish LOD on arrowheads from the Chalcolithic and Early/Middle Bronze Age chronologies (2800/2900 BC to 1500 BC) found in the last 25 years of excavations on an archaeological site in Portugal. These arrowheads were kept in boxes, hidden from the possibility of being studied and viewed by interested parties. The framework encompasses a metadata application profile (MAP) and tools to be used with this MAP, such as a namespace, two metadata schemas and eight vocabulary coding schemes. The MAP domain model was developed with the support of the scientific literature about this type of arrowheads, and the team integrated two archaeologists. This framework was created with the design philosophy of maximising data interoperability, so terms from the CIDOC CRM conceptual models and other vocabularies widely used in the LOD cloud were used. The MAP was tested using a set of seven arrowheads, which proved, in the first instance, the viability of the developed MAP. The team plans to test the model in future work with arrowheads of other excavations.

Abstract
Water is essential at various stages of winemaking, from irrigation in the vineyard to cleaning equipment and facilities, controlling fermentation temperatures, and diluting grape juice if necessary. Additionally, water is used for sanitation purposes to ensure the quality and safety of the final product. This article provides an overview of the existing knowledge regarding the use of water in wineries throughout the winemaking process, water consumption values, effluent treatment, efficient use of water measures, and water reuse. Different assessment methods, including Water Footprint (WF) and Life Cycle Assessment(LCA), provide varied insights into water use impacts, emphasizing the importance of standardized methodologies for accurate assessment and sustainable practices. This research showed that the characterization of the vinification processes of each type of wine is fundamental for further analysis on the environmental impact of winemaking regarding water use. It was also observed that WF is affected by factors like climate, irrigation needs, and cleaning procedures. Thus, efficient water management in all the stages of wine production is crucial to reduce the overall WF. Water efficiency measures may involve the modification of the production processes, reusing and recycling water and the implementation of cleaner production practices and technological innovations, such as automated fermentation systems that reduce water needs. Furthermore, waste management in wineries emphasizes the importance of sustainable practices and technological innovations to mitigate environmental impacts and enhance resource efficiency.