Abstract
The Renewable Energy Communities (RECs) and self-consumption frameworks defined in Directive (EU) 2023/2413 and Directive (EU) 2024/1711 are currently being integrated into national regulations across EU member states, adapting legislation to incorporate these new entities. These regulations establish key principles for individual and collective self-consumption, outlining operational rules such as proximity constraints, electricity sharing mechanisms, surplus electricity management, grid tariffs, and various organizational aspects, including asset sizing, licensing, metering, data exchange, and role definitions. This study introduces a model tailored to optimize investment and energy-sharing decisions within RECs, enabling multiple members to invest in solar photovoltaic (PV) and wind generation assets. The model determines the optimal generation capacity each REC member should install for each technology and calculates the energy shared between members in each period, considering site-specific constraints on renewable deployment. A case study with a four-member REC is used to showcase the model's functionality, with simulation results underscoring the benefits of CSC over ISC.

Abstract
While server-side assessment of programming exercises, with its ease of installing diverse compilers and execution environments, is common, it presents three key limitations: the necessity of a constant Internet connection, increased bandwidth consumption, and centralized execution load. The alternative is to rely on JavaScript, the single programming language supported by all standard web browsers. This paper introduces Osiris, a pure JavaScript multi-language transpiler designed to enable the execution of diverse programming languages within web browsers. Targeted primarily at Virtual Learning Environments (VLE) for language programming education, Osiris employs a parser generator to translate small student programs into JavaScript based on language-specific grammars with semantic rules. It also includes a comprehensive, though not exhaustive, JavaScript library that emulates the standard libraries of its supported languages. Validation of Osiris indicates the pedagogical effectiveness of browser-based transpilation for introductory programming education.

Abstract
Predicting and controlling crowd dynamics in emergencies is one of the main objectives of simulated emergency exercises. However, during emergency exercises, there is often a lack of sense of danger by the actors involved and concerns about exposing real people to potentially dangerous environments. These problems impose limitations in running an emergency drill, harming the collection of valuable information for posterior analysis and decision-making. This work aims to mitigate these problems by using Agent Based Modelling (ABM) simulator to deepen the comprehension of human actions when exposed to a sudden variation in extensive crowded environmental conditions and how evacuation strategies affect evacuation performance. To assess the impact of the evacuation strategy employed, we propose a modified informed leader-flowing approach and compare it with common evacuation strategies in a simulated environment, replicating stadium benches with narrow corridors leading to different exit points. The objective is to determine the impact of each set of configurations and evacuation strategies and compare them against other established ones. Our experiments determined that agents following the crowd generally lead to a higher number of victims due to the rise of herding phenomena near the exits, which was significantly reduced when agents were guided towards the exit via knowing the exit beforehand or following leader agent with real-time information regarding exit location and exit current state, proving that relevant and controlled information in combination with Follow Leader strategies can be crucial in an emergency evacuation scenario with limited evacuation exit capabi and distribution. © The Author(s) 2024.

Abstract
This paper presents a solution for visualizing oil spills at sea by combining satellite data with virtual choreographies. The system enables dynamic, interactive visualization of oil slicks, reflecting their shape, movement, and interaction with environmental factors like currents and wind. High resolution geospatial data supports a multiplatform experience with aerial and underwater perspectives. This approach promotes independence, interoperability, and multiplatform compatibility in environmental disaster monitoring. The results validate virtual choreographies as effective tools for immersive exploration and analysis, offering structured data narratives beyond passive visualization especially valuable for mixed reality applications.

Abstract
Innovative educational technologies, the integration of Massive Open Online Courses methodology (MOOC), Challenge-Based Learning (CBL), and Virtual Assistant methodologies in Big Data course represent a dynamic evolution in pedagogical approaches. MOOCs offer scalable access to high-quality educational content, enabling learners to engage with Big Data concepts flexibly. CBL fosters critical thinking and problem-solving skills by immersing students in real-world scenarios relevant to Big Data analysis. Virtual Assistant methodologies leverage artificial intelligence to provide personalized learning experiences, enhancing student support and interactivity. This integrated approach not only cultivates a comprehensive understanding of Big Data but also prepares learners for the demands of a data-driven world. The authors are discussing the methodology and the effectiveness of the implemented course.

Abstract
The combination of storytelling and gamification in educational settings has emerged as a method to enhance student engagement and learning outcomes. Through an overarching narrative, course content can be connected while providing context for gamified exercises, creating a motivating and competitive learning experience. However, a narrative that resonates with one student may not interest others. The presented solution to this problem is to offer multiple narratives for students to choose from. This enables the students to engage with the material in ways that align with their interests and motivations. Yet, managing multiple narratives presents several challenges. Each narrative must cover all syllabus topics equally, and every exercise must be available across all narratives while maintaining consistent difficulty levels and learning objectives. This paper presents a systematic approach for creating gamified courses with multiple narratives. The methodology includes the development of a base course template and its narrative variations, along with transformation processes to generate exercises in the FGPE Ecosystem, namely AuthorKit and FGPE PLE. The final output is a single Moodle MBZ file that can be imported into Moodle, a widely adopted learning management system.