Abstract
This paper presents an overview of the FGPE (Framework for Gamified Programming Education), a set of three Erasmus+ projects aimed at providing a framework for applying gamification to programming education. The overview will encompass all three phases of the framework development, emphasizing the gamification elements embedded in the design and implementation of the outputs of each phase. These outputs will be presented as a unified narrative, including the gamification framework for programming exercises, a format for defining gamification details for programming exercises and courses, the authoring tool for the gamification layer, a gamification Web service, a tutorial on gamifying programming exercises (guidance material), and a tool that automatically generates gamified programming exercises.

Abstract
Food waste generated throughout the food supply chain raises several environmental, social, and economic issues. Quantitative methods can aid in managing food waste by describing current contexts, predicting future scenarios, and improving related operations. However, a literature review on the use of quantitative methods, specifically the descriptive, predictive, and prescriptive dimensions, to assess and prevent food waste is lacking. This paper aims to explore and categorize quantitative studies that perform descriptive, predictive, and prescriptive analysis concerning food waste, to identify gaps and inform future research. For this purpose, we developed a systematic literature review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement methodology, which resulted in the inclusion of 65 relevant studies. We identified the key features of each data analytics approach, with a particular focus on (i) food waste quantification methods, (ii) demand, food waste, and shelf-life forecasting algorithms, and (iii) optimization approaches. Additionally, the context in which each of these studies is focused is also explored. We found that predictive analysis is the most prominent among the data analytics approaches, followed by descriptive and prescriptive systems, respectively. Moreover, the most explored setting is the hospitality sector, and it is the only context in which all descriptive, predictive, and prescriptive approaches can be found. The algorithms and models adopted in the studies vary, and there is still room for adopting more recent or advanced methods. This paper establishes a foundation for advancing focused and systematic quantitative research in the field of food waste. © 2025 Elsevier B.V., All rights reserved.

Abstract
Lock-freedom offers significant advantages in terms of algorithm design, performance and scalability. A fundamental building block in software development is the usage of hash map data structures. This work extends a previous lock-free hash map to support a new simplified design that is able to take advantage of most state-of-the-art safe memory reclamation methods, thus outperforming the previous design.

Abstract
With the global population on the rise and a declining agricultural labor force, the realm of robotics research in agriculture, such as robotic manipulators, has assumed heightened significance. This article undertakes a comprehensive exploration of the latest advancements in controllers tailored for robotic manipulators. The investigation encompasses an examination of six distinct controller paradigms, complemented by the presentation of three exemplars for each category. These paradigms encompass: (i) adaptive control, (ii) sliding mode control, (iii) model predictive control, (iv) robust control, (v) fuzzy logic control and (vi) neural network control. The article further introduces and presents comparative tables for each controller category. These controllers excel in tracking trajectories and efficiently reaching reference points with rapid convergence. The key point of divergence among these controllers resides in their inherent complexity.

Abstract

Abstract
This paper presents the guidelines for game experiences integration into Learning Management Systems (LMS) through the IMS LTI (Learning Tools Interoperability) specification. At the same time, it also introduces a dynamic scoring formula, based on a given taxonomy, that goes beyond traditional metrics, allowing for the inclusion of any number of game elements, such as levels, challenges, hints used, and time taken, within the game framework. These elements are assigned weight factors, which can be configured by instructors within the LMS platform, facilitating personalized assessment criteria tailored to specific learning objectives. In order to apply these approach in a real educational scenario, an Escape Room (ER) for math skills testing was used. Using the LTI specification for integration in combination with the dynamic scoring formula provides a comprehensive assessment of student performance, giving a single score which will be vital to enhance the LMS gamified workflow. This research contributes to the field of gamification in education, offering insights into the integration of (serious or regular) games in LMS platforms.