Abstract
Continuous improvement (CI) have been recognised as one of the most effective ways to improve organisational performance. However, there is a lack of research on this topic from a food service perspective. Thus, the aim of this work is to explore the adoption of CI-focused methodologies in food services and to understand how they contribute to improving the performance of these services. Critical success factors and barriers to the implementation of CI are also analysed. This systematic review was conducted using the PRISMA methodology and a total of 43 studies were included in the analysis. This review shows that CI is effective in improving operations and performance, as well as increasing stakeholder satisfaction in the food service sector. Additionally, the review reveals that CI-focused tools are mainly used in problem identification, waste identification, planning, operations, and logistics. Human-related issues are the most frequently mentioned when it comes to the factors determining the success or failure of CI in food services.

Abstract
Serious games can play a crucial role in developing competencies for the job market, offering an innovative and engaging approach to learning. This study uses FLIGBY to develop employability skills among computer engineering graduates. FLIGBY is a serious game that simulates a virtual company environment where players make strategic decisions, emphasizing the principles of flow and positive psychology. Immersion in realistic scenarios provides practical experience, contributing to the development of market-ready skills. A quantitative methodology based on descriptive statistics and hypothesis testing was adopted to measure the development of competencies for the job market using the Systems Engineering Competency Framework. The results show that competence development occurs mainly in the professional and managerial dimensions. In contrast, there is no development of core and technical competencies. Furthermore, the perception of the development of these competencies occurs mainly for students with more years of professional experience. The experiential nature of FLIGBY allows users to develop practical knowledge, promoting adaptability and resilience. This gamified approach accelerates the learning curve, preparing individuals for real-world challenges in the computer engineering workplace.

Abstract
Identifying the maturation stage is an added value for olive oil producers and consumers, whether this is done to predict the best harvest time, give us more information about the olive oil, or even adapt techniques and extraction parameters in the olive oil mill. In this way, the proposed work presents a new method to identify and count the number of olives that enter the mill as well as their stage of maturation. It is based on artificial intelligence (AI) and deep learning algorithms, using the two most recent versions of YOLO, YOLOv7 and YOLOv8. The obtained results demonstrate the possibility of using this type of application in a real environment, managing to obtain a mAP of approximately 79% with YOLOv8 in the five maturation stages, with a processing rate of approximately 16 FPS increasing this with YOLOv7 to 36.5 FPS reaching a 66% mAP.

Abstract
The intrinsic challenges of contemporary marketing encourage discovering new approaches to engage and retain customers effectively. As the main channels of interactions between customers and brands pivot between the physical and the digital world, analyzing the outcome behavioral patterns must be achieved dynamically with the stimulus performed in both poles. This systematic review investigates the collaborative impact of adopting multidisciplinary fields of Affective Computing to evaluate current marketing strategies, upholding the process of using multimodal information from consumers to perform and integrate Sentiment Analysis tasks. The adjusted representation of modalities such as textual, visual, audio, or even psychological indicators enables prospecting a more precise assessment of the advantages and disadvantages of the proposed technique, glimpsing future applications of Multimodal Artificial Intelligence in Marketing. Embracing the Preferred Reporting Items for Systematic Reviews and Meta-Analysis as the research method to be applied, this article warrants a rigorous and sequential identification and interpretation of the synergies between the latest studies about affective computing and marketing. Furthermore, the robustness of the procedure is deepened in knowledge-gathering concerning the current state of Affective Computing in the Marketing area, their technical practices, ethical and legal considerations, and the potential upcoming applications, anticipating insights for the ongoing work of marketers and researchers.

Abstract
Stand-level forest tree species perception and identification are needed for monitoring-related operations, being crucial for better biodiversity and inventory management in forested areas. This paper contributes to this knowledge domain by researching tree trunk types multispectral perception at stand-level. YOLOv5 and YOLOv8 - Convolutional Neural Networks specialized at object detection and segmentation - were trained to detect and segment two tree trunk genus (pine and eucalyptus) using datasets collected in a forest region in Portugal. The dataset comprises only two categories, which correspond to the two tree genus. The datasets were manually annotated for object detection and segmentation with RGB and RGB-NIR images, and are publicly available. The Small variant of YOLOv8 was the best model at detection and segmentation tasks, achieving an F1 measure above 87% and 62%, respectively. The findings of this study suggest that the use of extended spectra, including Visible and Near Infrared, produces superior results. The trained models can be integrated into forest tractors and robots to monitor forest genus across different spectra. This can assist forest managers in controlling their forest stands.

Abstract
Digital transformation in entrepreneurship education is an activity that has been taking place in higher education institutions, namely, through digital access to resources, simulations, and serious games. These activities have contributed to greater student engagement and to fostering personalized learning. Despite the recognized success of these activities, entrepreneurship education is still seen as an isolated and internally implemented activity, with few synergies with other institutions and external stakeholders. This study presents a proposal for an innovative technological platform that enables entrepreneurial projects to include students from various higher education institutions helping to build businesses worldwide. The proposed approach also involves integration with investors who can invest and offer mentoring services. A prototyping methodology was employed which provides benefits in terms of rapid iteration and feedback, enabling early visualization and testing of ideas, leading to improved design, functionality, and alignment with user needs. The results of this study show that the implemented solution addresses the critical success factors (CSFs) in the implementation of a crowdsourcing platform such as usability, scalability, transparency, security, monetary compensation, and social recognition. Finally, this study is mainly relevant for higher education institutions to revolutionize their higher education processes by adopting a collaborative approach that allows them to interact with several players on a global scale.