Abstract
Energy communities (EC) and collective self-consumption (CSC) systems can make a significant contribution to reducing dependence on fossil fuels and energy costs. They create mechanisms for the active participation of end-consumers in the energy system by becoming self-producers of renewable electricity and adapting their energy behavior to the needs of the system. CSC also alleviates energy poverty by reducing the energy costs of vulnerable members. The CSC is still in its early stages, and regulation is being developed in several countries along with pilot projects to test different rules and incentives. This chapter discusses the most relevant common definitions of CSC and EC so far, as well as the main challenges in relation to energy sharing rules and the management of EC and CSC. © 2025 Elsevier B.V., All rights reserved.

Abstract
Rendering on conventional computers is capable of generating realistic imagery, but the computational complexity of these light transport algorithms is a limiting factor of image synthesis. Quantum computers have the potential to significantly improve rendering performance through reducing the underlying complexity of the algorithms behind light transport. This article investigates hybrid quantum-classical algorithms for ray tracing, a core component of most rendering techniques. Through a practical implementation of quantum ray tracing in a 3D environment, we show quantum approaches provide a quadratic improvement in query complexity compared to the equivalent classical approach. Based on domain specific knowledge, we then propose algorithms to significantly reduce the computation required for quantum ray tracing through exploiting image space coherence and a principled termination criteria for quantum searching. We show results obtained using a simulator for both Whitted style ray tracing, and for accelerating ray tracing operations when performing classical Monte Carlo integration for area lights and indirect illumination.

Abstract
PurposeWithin the sports industry, fan tokens have appeared as an instrument for fostering fan engagement and empowering them to participate in club-related decision-making processes via voting mechanisms (e.g. voting rights in decisions like the design of the equipment or the bus, and the ability to win rewards such as VIP experiences with the players).Design/methodology/approachDrawing on the technology acceptance model and consumer behaviour theories, a conceptual model was established to analyse the relationship of perceived ease of use, usefulness, and financial value, brand love, brand engagement, trust, social influence and its influence on the intention to purchase fan tokens. This study also analyses the generation of positive electronic word-of-mouth (e-WOM) derived from the intention to purchase fan tokens. To achieve the proposed objective, a quantitative study was conducted, collecting data through an online survey from football fans with an interest in fan tokens. The conceptual model was analysed using partial least squares (PLS) structural equation modelling (SEM).FindingsResults show that the financial perceived value was the dimension that most contributed to explaining the purchase intention. It was also found that perceived ease of use, trust in fan tokens and brand engagement positively influence the intention to buy fan tokens. Furthermore, findings demonstrate that purchase intention positively drives e-WOM, highlighting that fans' behavioural intentions extend beyond adoption to active digital advocacy.Originality/valueResults offer effective insights for both researchers and sports practitioners, while also presenting an original conceptual model applicable to diverse sports contexts and crypto assets-related research.

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Abstract
Contemporary transformations in the world of work, together with the growing emotional and physical demands in nursing, have led to the emergence of new labor phenomena such as quiet quitting, which reflects changes in professional engagement and in the management of nurses' well-being. Objective: To translate, culturally adapt, and validate the Quiet Quitting Scale for European Portuguese, evaluating its psychometric properties among the nursing population. Methods: A cross-sectional validation study was conducted following COSMIN guidelines. The process included forward and back translation, expert panel review, and pretesting with 30 nurses. The psychometric evaluation was carried out with 347 nurses from Northern Portugal. Data were analyzed using descriptive and inferential statistics, internal consistency measures (Cronbach's alpha and McDonald's omega), and confirmatory factor analysis (CFA) with maximum likelihood estimation to assess construct validity. Results: The Portuguese version (QQS-PT) maintained the original three-factor structure (Detachment/Disinterest, Lack of Initiative, and Lack of Motivation). The model showed satisfactory fit indices (CFI = 0.936; GFI = 0.901; AGFI = 0.814; TLI = 0.905; RMSEA = 0.133). The overall internal consistency was excellent (alpha = 0.918; omega = 0.922), with subscale alpha ranging from 0.788 to 0.924. Composite reliability (CR) ranged from 0.815 to 0.924, and average variance extracted (AVE) from 0.606 to 0.859, confirming convergent and discriminant validity. Conclusions: The QQS-PT demonstrated a stable factorial structure, strong reliability, and solid validity evidence. It is a brief and psychometrically sound instrument for assessing quiet quitting among nurses, providing valuable insights for research and management of professional engagement and well-being in healthcare contexts.