Abstract
This article aimed to analyse state-of-the-art empirical evidence of randomized controlled trials designed to assess preventive cognitive training interventions based on virtual reality for older adults without cognitive impairment, by identifying virtual reality setups and tasks, clinical outcomes and respective measurement instruments, and positive effects on outcome parameters. A systematic electronic search was performed, and six randomized controlled trials were included in the systematic review. In terms of results, the included studies pointed to significant positive impact of virtual reality-based cognitive training interventions on global cognition, memory, attention, information processing speed, walking variability, balance, muscle strength, and falls. However, further research is required to evaluate the adequacy of the virtual reality setups and tasks, to study the impact of the interventions’ duration and intensity, to understand how to tailor the interventions to the characteristics and needs of the individuals, and to compare face-to-face to remote interventions. © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

Abstract
Accurate detection and differentiation of grapevine canopies from other vegetation, along with individual grapevine row identification, pose significant challenges in precision viticulture (PV), especially within irregularly structured vineyards shaped by natural terrain slopes. This study employs aerial imagery captured by unmanned aerial vehicles (UAVs) and introduces an image processing methodology that relies on the orthorectified raster data obtained through UAVs. The proposed method adopts a data-driven approach that combines visible indices and elevation data to achieve precise grapevine row detection. Thoroughly tested across various vineyard configurations, including irregular and terraced landscapes, the findings underscore the method's effectiveness in identifying grapevine rows of diverse shapes and configurations. This capability is crucial for accurate vineyard monitoring and management. Furthermore, the method enables clear differentiation between inter-row spaces and grapevine vegetation, representing a fundamental advancement for comprehensive vineyard analysis and PV planning. This study contributes to the field of PV by providing a reliable tool for grapevine row detection and vineyard feature classification. The proposed methodology is applicable to vineyards with varying layouts, offering a versatile solution for enhancing precision viticulture practices.

Abstract
The present article explores the impact of educational robotics on fostering computational thinking and problem-solving skills in elementary school students through a problem-based learning approach. This study involved the creation of a framework which includes a robot and two eBooks designed for students and teachers. The eBooks serve as a guide to the construction and programming of a small Arduino-based robot. Through integration with gamification elements, the model features a narrative with three characters to boost a student's engagement and motivation. Through iteration of heuristic evaluations and practical tests, we refined the initial theoretical framework. An empirical study was conducted in two phases involving 350 students. The first empirical test involved a small group of 21 students, similar to end users, from five European schools. With a 100% completion rate for the tasks, 73.47% of these tasks were solved optimally. Later, we conducted a larger validation study which involved 329 students in a Portuguese school. This second phase of the study was conducted during the 2022-2023 and 2023-2024 school years with three study groups. The results led to a 91.13% success rate in problem-solving activities, and 56.99% of those students achieved optimal solutions. Advanced statistical techniques, including ANOVA, were applied to account for group differences and ensure the robustness of the findings. This study demonstrates that the proposed model which integrates educational robotics with problem-based learning effectively promotes computational thinking and problem-solving skills, which are essential for the 21st century. These findings support the inclusion of robotics into primary school curricula and provide a validated framework for educators.

Abstract
Warehouses and distribution centres play a key role in any Supply Chain, particularly in the retail sector, where a network of stores needs to be replenished in a highly dynamic and increasingly uncertain context. In this regard, companies need to improve their intralogistics systems daily to ensure long-term competitiveness and sustainable growth. This is especially true in picking-by-line systems where many time-consuming and manual tasks are usually involved. This study introduces a new decision support tool based on simulation methods to aid the decision-making process in a picking-by-Line system, aimed to improve the overall picking operations efficiency, through human-centric perspective. A Discrete-Event-Simulation model is proposed to assess a set of parameters under several scenarios, driving a more informed decision-making process towards cost-effective strategies. The proposed approach was validated through an empirical case study showing its effectiveness in assisting operational planning decisions related to capacity and resource allocation. The system demonstrates promising versatility for application across varied warehouse environments. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Abstract

Abstract
The proposed framework (Human-Centered Trustworthy Framework) provides a novel human-computer interaction approach to incorporate positive and meaningful trustful user experiences in the system design process. It helps to illustrate potential users' trust concerns in artificial intelligence and guides nonexperts to avoid designing vulnerable interactions that lead to breaches of trust.