Abstract

Abstract
The European Project Semester (EPS), offered by the Instituto Superior de Engenharia do Porto (ISEP), is a capstone programme designed for undergraduate students in engineering, product design, and business. EPS@ISEP fosters project-based learning, promotes multicultural and interdisciplinary teamwork, and ethics- and sustainability-driven design. This study applies Natural Language Processing techniques, specifically text mining, to analyse project papers produced by EPS@ISEP teams. The proposed method aims to identify evidence of ethical concerns within EPS@ISEP projects. An innovative keyword mapping approach is introduced that first defines and refines a list of ethics-related keywords through prompt engineering. This enriched list of keywords is then used to systematically map the content of project papers. The findings indicate that the EPS@ISEP robotics project papers analysed demonstrate awareness of ethical considerations and actively incorporate them into design processes. The method presented is adaptable to various application areas, such as monitoring compliance with responsible innovation or sustainability policies. © 2025 Elsevier B.V., All rights reserved.

Abstract
Swarm robotics enables groups of autonomous agents to coordinate and perform tasks beyond the capabilities of individual robots. This state-of-the-art review focuses on the defining features, principles, and algorithms of swarm robotic systems, with an emphasis on recent advances. It examined classical and modern bio-inspired coordination strategies, decentralized control algorithms and hybrid approaches, highlighting their strengths, limitations and applicability to real-world deployments. Key challenges, such as scalability, robustness, adaptability and the gap between simulation and hardware implementation are analyzed.

Abstract
This study analyzes forest cover change patterns, agricultural expansion, and economic growth in Mozambique from 2001 to 2024, using remote sensing data from Global Forest Watch and socioeconomic indicators from the World Bank and FAO. Mozambique lost approximately 4.6 million hectares of forest during the analyzed period, with agriculture accounting for 97.4% of total deforestation. GDP per capita increased by 90.5%, while cultivated area expanded by 116.4%. However, agricultural productivity declined by 25.3%, revealing a paradox: production growth relied on extensive land expansion rather than intensification. Statistical analysis of three 8-year sub-periods identified significant differences in GDP per capita, agricultural GDP per capita, population, and agricultural employment (p < 0.001), but agricultural deforestation remained statistically stable (p = 0.065). This pattern suggests premature decoupling between economic growth and deforestation at income levels (USD 604) substantially below historical Environmental Kuznets Curve thresholds (USD 8000–10,000). However, this decoupling is fragile, driven by capital-intensive extractive sectors that generate GDP growth without absorbing rural populations. The persistence of extensive agricultural expansion, combined with weak governance, demographic pressures, and climate variability, indicates that observed stabilization represents an initial, vulnerable phase requiring structural transformation through agricultural intensification, inclusive industrialization, land tenure reform, and climate resilience building. © 2026 by the authors.

Abstract
Stroke is a leading cause of long-term disability worldwide, with survivors often facing significant challenges in regaining upper-limb functionality. In response, robotic rehabilitation systems have emerged as promising tools to enhance post-stroke recovery by delivering precise, adaptable, and patient-specific therapy. This paper presents a review of robotic interfaces developed specifically for upper-limb rehabilitation. It analyses existing exoskeleton- and end-effector-based systems, with respect to three core design pillars: assistance types, control philosophies, and actuation methods. The review highlights that most solutions favor electrically actuated exoskeletons, which use impedance- or electromyography-driven control, with active assistance being the predominant rehabilitation mode. Resistance-providing systems remain underutilized. Furthermore, no hybrid approaches featuring the combination of robotic manipulators with actuated interfaces were found. This paper also identifies a recent trend towards lightweight, modular, and portable solutions and discusses the challenges in bridging research prototypes with clinical adoption. By focusing exclusively on upper-limb applications, this work provides a targeted reference for researchers and engineers developing next-generation rehabilitation technologies.

Abstract
Radio-Frequency IDentification (RFID) technologies automate the identification of objects and persons, having several applications in retail, manufacturing, and intralogistics sectors. Several works explore the application of RFID systems in robotics and intralogistics, focusing on locating robots, tags, and inventory management. This paper addresses the challenge of intralogistics cargo trolleys communicating their characteristics to an autonomous mobile robot through an RFID system. The robot must know the trolley's relative pose to avoid collisions with the surroundings. As a result, the passive tag on the cargo communicates information to the robot, including the base footprint of the trolley. The proposed RFID system includes the development of a controller board to interact with the frontend integrated circuit of an external antenna onboard the industrial mobile robot. Experimental results assess the system's readability distance in two distinct environments and with two different antenna modules. All the code and documentation are available in a public repository.