Abstract
The so-called fourth industrial revolution brought a disruptive change in the way that communication technologies, distributed systems, intelligent data management, analytics and computational capability and other technologies are integrated to enable new functions and enhance capabilities not only to production systems, but also in many other domains such as education. Mobile Health (m-Health) education is one of these, where the number of applications and tools for m-Health education is extensive. The SARS-Cov2 (Covid-19) pandemic brought to life immense challenges towards education, technology, and the symbiosis with medicine. This paper introduces 31 of the current state-of-the-art m-Health education applications and analyses the results of an an inquiry to students and junior doctors during the confinement, designed to understanding their knowledge, use and trust regarding these apps. The results show that several applications are well perceived by their users and deserved their trust and confirms a good relation between use and trust on the applications analysed. This analysis open doors to a deeper study to evaluate at which extent improving m-Health education means not only to transmit knowledge but also to developing skills and better practices.

Abstract

Abstract
For the project of an Agile/Virtual Enterprise (A/V E) the resources selection is a key factor. The resources systems (output of the selection process) should be prepared to guarantee quality, efficiency and cost-attractiveness, in order to ensure the agility and integrability of the A/V E. This is a difficult matter because it can be a combinatorial and multi-criteria problem. Despite the potential of Value Analysis (VA), none of the resources selection models found in the literature incorporates the evaluation of the resources value. They approach mainly the factors cost and/or time. So, our model constitutes an innovative approach because it gives the highest importance to the value of the resources systems, through the incorporation of VA. The main objective is to quantify the selection process performance with VA integrated into the pre-selection of resources in accordance with the developed model. The paper contribution is the positive confirmation, through the simulation results analysis, of the benefits of VA integration in the resources selection process: greater applicability domain for candidate resources and number of tasks; and reduction of the selection time. In conclusion, the increased efficiency and the superior applicability domain of the model are demonstrated.

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Abstract
To summarise this editorial, we attempted to briefly chart out some developments in related areas of governance and sustainability. As this field is a 'never ending story', novel questions and problems stem requiring equally novel solutions. At the end, the guest editors hope, and would like, that this special issue will beuseful, meeting the expectations of the authors and wider readership and serving for enhancing the individual and collective learning, theoretical insight and practical applications, and to incentive further scientific development and creation of new papers.

Abstract
Renewable energy and electric mobility are crucial in addressing current environmental and energy challenges. As the number of electric vehicles increases, more charging infrastructure connected to the electricity distribution network is required. This paper proposes an approach to sizing a fast charging station for electric vehicles. This challenge is addressed by including a battery energy storage system (BESS) and considering the self-production from a renewable energy source (solar energy) in the system. The aim is to minimise the total energy costs, avoid future infrastructure upgrades, and take advantage of the integration of renewable energy resources. The methodology used is a Biased Random Key Genetic Algorithm (BRKGA) based meta-heuristic. Computational experiments were conducted for the sizing of a charging station under four different scenarios that minimise energy costs. The results show that incorporating BESS can lead to a significant reduction in the costs related to the purchase of energy from the grid. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.