Abstract

Abstract
Recently, we have been observing a significant evolution in products, machines, and manufacturing processes, towards a more digital and interoperable reality. In this sense, the power transformers sector has also been evolving to develop smart transformers for the future, capable of providing the digital capabilities to leverage new services and features that follow its entire life cycle, from the design and manufacturing to the use and dismantling/recycling. In this sense, this paper aims to present and demonstrate how an innovative digital twin platform can be used in a secure and trustable way for the enhancement of the power transformers’ performance and potential lifespan, enabling, at the same time, the promotion of new business models. A real use case is also presented to demonstrate the applicability of Asset Administration Shells (AAS) for power transformer life cycle management, as well as the use of the International Data Spaces (IDS) for the secure and trustable horizontal interoperability along with the different actors of the value chain, from the manufacturers to the power network and maintenance services companies.

Abstract
Computational thinking is a fundamental competence for the 21st century. It refers to a set of capacities and skills that can be stimulated to facilitate the teaching-learning process in a wide range of fields, including Science, Technology, Engineering and Mathematics (STEM). Experts in information technology argue that the earlier children are exposed to programming through digital platforms appropriate for their age, the easier it will be for them to assimilate their concepts in the future. This effort should be continued throughout the educational stages of children and youth to increase students' interest in pursuing STEM studies and careers. This paper describes the Scratch4All project promoted by the consortium CASPAE ( a Private Social Solidarity Institution) and Inova-Ria, with technical assistance from professors at the public higher education institution Coimbra Institute of Engineering. Scratch4All Project includes the activities Scratch on Road, Programming and Robotics Lab, and the Scratch4All Digital Platform. According to the impact assessment for the school year 2020-2021, the Scratch4All project promotes school success and true equality in access to new technologies for students in the 1st, 2nd, and 3rd cycles of elementary school, developing essential skills for their academic and professional future such as computational thinking, STEM competencies and social skills. By encouraging young girls to participate in technological projects, this project also aims to combat gender stereotypes.

Abstract
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Abstract
The rising potential for battery energy storage systems (BESS) to generate revenue in a market environment is addressed in this work, where a tool based on neural network predictions is proposed. The tool's main objective is predicting, based on historical data, the most lucrative out of three established bidding approaches for the participation of a BESS in the day-ahead energy market and thus aid the strategic bidding process of the BESS operator. Each of these bidding strategies reflects BESS's operator approach concerning bidding frequency and the tolerated risk of loss of profit from having its bids rejected, leading to the development of a conservative (strategy A), an aggressive (strategy B), and a moderate strategy (strategy C). A case study was then used to test the tool for a full year allowing to ascertain the assertiveness of this tool in predicting the best strategy, which for this case was above 88%.

Abstract
Make-to-order (MTO) supply chains (SC), common in aerospace industries, are very complex compared to mass production chains. Moreover, one of the significant long-term challenges is sustainability performance across its entire supply chain. However, this is not an easy task given the complexity involved, so decision support tools are fundamental instruments in understanding the entire supply chain from a sustainability performance perspective. Using simulation as a research method, this article proposes a hybrid and hierarchical performance assessment model, considering key sustainability indicators. The model is hybrid due to the use of different simulation methods- System Dynamics (SD), Discrete Event Simulation (DES), and Agent-based simulation (ABS). The model is applied to an aerospace manufacturer's real case to assess the sustainability performance of alternative SC. Unlike existing contributions, this work addresses the make-to-order supply chain from a sustainability performance perspective and does not compromise the representation of the diverse manufacturing functions and resources.