Browsing by Issue Date, starting with "2025-04-07"
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- Behavioral Regulation Sport Questionnaire e Sport Motivation Scale–II: Comparação de escalasPublication . Bica, Joana Francisca Ferreira; Monteiro, Diogo Manuel Teixeira; Jacinto, Miguel Ângelo SusanoA Sport Motivation Scale-II (SMS-II) e o Behavioral Regulation in Sport Questionnaire (BRSQ) são métodos de avaliação da regulação da motivação no desporto, baseados na Teoria da Autodeterminação (Ryan & Deci, 2017). O objetivo desta investigação foi examinar e comparar as propriedades psicométricas de ambas as escalas. A fiabilidade foi aceite na maioria das validações do BRSQ, porém nas validações da SMS-II foram encontrados problemas de fiabilidade principalmente nas regulações introjetada, externa e na amotivação. O BRSQ apresentou problemas de validade convergente nos fatores de regulação integrada e identificada. Foram também identificados problemas de validade discriminante entre os fatores de regulação externa e introjetada, identificada e integrada, integrada e intrínseca e amotivação e externa. A SMS-II revelou problemas de validade convergente com todos os fatores de regulação da motivação e problemas de validade discriminante com os fatores de regulação intrínseca, integrada, identificada e introjetada, integrada e identificada, integrada e introjetada, identificada e introjetada e introjetada e externa. Ao analisar o ajustamento dos modelos, nem todos apresentaram valores aceitáveis à primeira vista para ambas as escalas. Foram correlacionados erros, eliminados itens e foram validadas escalas com menos fatores de regulação da motivação. A invariância de ambas as escalas foram verificadas em função do género, das diferentes idades, dos desportos coletivos/individuais e dos diferentes níveis desportivos. A validade temporal das escalas também foi testada e validada. O BRSQ mostrou-se também invariante em diferentes desportos e em 5 países europeus. Os resultados deste estudo irão contribuir para uma avaliação mais aprofundada da motivação como fator determinante para a prática desportiva, bem como para o aperfeiçoamento contínuo de uma escala que integre todos os tipos de motivação.
- Mental Health, Overweight, and Physical Exercise in Young Portuguese Adults: A Cross-Sectional StudyPublication . Gonçalves, Tânia; Monteiro, Diogo; Matos, Rui; Duarte-Mendes, Pedro; Couto, Nuno; Antunes, Raul; Oliveira Diz, Susana Cristina; Amaro, Nuno; Susano Jacinto, Miguel ÂngeloThe aim of this study was to see if there are any associations between mental health, Body Mass Index (BMI), and physical exercise (PE) in young Portuguese adults. The sample consisted of 414 people aged between 18 and 25 years old. A sociodemographic questionnaire designed for this study and the Mental Health Inventory were used. To analyze the results, the total sample was divided according to the criteria “BMI ≥ 5 kg/m2”; “BMI < 25 kg/m2”; “does not practice PE”; and “practices PE”, and sample groups were formed with these names. It was found that there was an association between the dimensions of the Mental Health Inventory and the average time spent practicing PE in the total sample (r from 0.099 to 0.160) and in individuals with a BMI < 25 kg/m2 (r = 0.154 and 0.169). In individuals with a BMI ≥25 kg/m2, there was an association between the ‘BMI’ and depression variables (r = −0.174). In all groups, associations were found between the variables of age and BMI (r from 0.120 to 0.216). There was also a significant effect of group (non-exercise vs. exercise groups) on the dependent variables, Λ = 0.972, F(5, 408) = 2.329, p = 0.042, η2p = 0.28. This study confirms the association between PE and mental health and suggests that BMI may have an influence on the appearance of depressive symptoms in young Portuguese adults.
- Multi-Class Intrusion Detection in Internet of Vehicles: Optimizing Machine Learning Models on Imbalanced DataPublication . Palma, Ágata; Antunes, Mário; Bernardino, Jorge; Alves, AnaThe Internet of Vehicles (IoV) presents complex cybersecurity challenges, particularly against Denial-of-Service (DoS) and spoofing attacks targeting the Controller Area Network (CAN) bus. This study leverages the CICIoV2024 dataset, comprising six distinct classes of benign traffic and various types of attacks, to evaluate advanced machine learning techniques for instrusion detection systems (IDS). The models XGBoost, Random Forest, AdaBoost, Extra Trees, Logistic Regression, and Deep Neural Network were tested under realistic, imbalanced data conditions, ensuring that the evaluation reflects real-world scenarios where benign traffic dominates. Using hyperparameter optimization with Optuna, we achieved significant improvements in detection accuracy and robustness. Ensemble methods such as XGBoost and Random Forest consistently demonstrated superior performance, achieving perfect accuracy and macro-average F1-scores, even when detecting minority attack classes, in contrast to previous results for the CICIoV2024 dataset. The integration of optimized hyperparameter tuning and a broader methodological scope culminated in an IDS framework capable of addressing diverse attack scenarios with exceptional precision.
- From Knowledge to Action: How Portuguese Higher Education Students Engage with Circular Economy PrinciplesPublication . Pardal, Ana; Moreira, Anabela; Galacho, Cristina; Mateus, Dina; Viegas, Laura; Gaspar, Marcelo; Teixeira, Margarida Ribau; Manteigas, Vitor; Dinis, Maria Alzira PimentaThis study investigates the perceptions and practices of Portuguese higher education students regarding the circular economy (CE), emphasising their knowledge, attitudes, and behaviours toward sustainable resource management. Carried out by the Working Group on Circular Economy and Waste Management of the Portuguese Sustainable Campus Network (RCS), the research used an online survey targeting students from 20 higher education institutions (HEIs), resulting in 400 responses. The findings indicate that while students generally hold positive views of the CE, their understanding of its practical applications, such as waste reduction and resource efficiency, remains limited. Only a small proportion of students reported exposure to CE-related topics in their curriculum, revealing a gap in academic integration. This study also identifies significant demographic variations in CE awareness and practices, influenced by factors such as age, field of study, and employment status. These insights underscore the need for HEIs to strengthen CE education and actively involve students in hands-on sustainability initiatives, fostering a generation equipped to drive the transition toward a circular economy.
- I N T E G R AT I N G D I G I TA L TW I N A N D A U G M E N T E D R E A L I T Y F O R M O N I T O R I N G , E D U C AT I O N A N D T R A I N I N G I N T H E M I N E R A L I N D U S T RYPublication . Cruz, Ana Cassia Vasconcelos; Gonçalves, Alexandrino José Marques; Rodrigues, Nuno Carlos Sousa; Ribeiro, Roberto Aguiar; Marto, Anabela Gonçalves RodriguesThis report explores the application of Digital Twin (DT) and Augmented Real ity (AR) technologies in addressing key challenges within the mineral industry, including high operating costs, hazardous working environments, and resource management. To achieve this, a solution leveraging the HoloLens 2 is proposed, integrating real-time monitoring, educational content, and training for industrial tasks. The developed system is structured into three interconnected layers—Factory Environment, AR System, and Cloud Platform—which collectively facilitate the extraction, visualization, and dissemination of data to users. As part of this project, an initial Android AR application using Unity was developed for the mining industry and tested in factory environment with real factory worker users. This application served as the basis for the evolution of the new AR-DT system, as it had already been validated for its monitoring capabilities and educational content (text, audio, and video). Based on this knowledge, the system was expanded to integrate AR with DT, using HoloLens 2 for a more immersive experience. On the factory environment, real-time data from the machines is monitored via OPC UA-compatible servers. This data is subsequently made accessible on the AR glasses, providing users with contextual information. In parallel, the Cloud Platform stores training content such as videos, audio and text, as well as 3D objects used in training. The AR System bridges the gap between physical and digital environments, enabling interactive training where operators can interact with virtual replicas of machine parts, simulating the real-time process monitoring and the machine’s educational training content, such as manuals via text, audio and even tutorial videos, which contribute to improving operational efficiency, safety and the development of workers’ skills. To evaluate the effectiveness of this new approach, a usability evaluation was conducted, focusing on user performance, cognitive load and the interface usability. The results were promising, demonstrated by high task completion rates (between 81.8% and 100%), positive scores in usability tests carried out using the System Usability Scale (SUS) (average of 72.4) and low levels of frustration, physical demand and effort, as measured by NASA-TLX. The qualitative analysis, using the VADER algorithm, confirmed a mostly positive reception of the AR technology, although some challenges in the interface were identified as opportunities for future improvements. In addition, an AR prototype was developed with a focus on preserving privacy in industrial environments. The solution employs a client-server architecture, in which the AR device diffuses images for remote processing, receiving them back with sensitive regions (e.g. faces, screens) obfuscated via techniques such as Gaussian blurring or pixelation. This prototype is the initial step towards the secure integration of wearable systems in industrial contexts, laying the foundations for future advances in harmonizing security and usability. At the same time, the system includes a training module for assembling com puter components, designed as a proof of concept for industrial simulations. The ultimate goal is to integrate real-time obfuscation with interaction during training, guaranteeing data protection without compromising the user experience in AR glasses. These findings underscore the potential of the AR-DT system to enhance op erational efficiency, safety, and skills development within the stone industry. The study’s outcomes suggest that such integrated AR-DT solutions could contribute to advancing Industry 4.0 practices within the sector, potentially leading to more efficient and safer industrial processes.
- Loneliness among dementia caregivers: evaluation of the psychometric properties and cutoff score of the Three-item UCLA Loneliness ScalePublication . Ali, Amira Mohammed; Al-Dossary, Saeed A.; Laranjeira, Carlos; Selim, Abeer; Hallit, Souheil; Alkhamees, Abdulmajeed A.; Aljubilah, Aljawharah Fahad; Aljaberi, Musheer A.; Alzeiby, Ebtesam Abdullah; Pakai, Annamaria; Khatatbeh, HaithamIntroduction: Dementia is a chronic progressive syndrome, with an entire loss of function in the late stages. The care of this demanding condition is primarily provided by family members, who often suffer from chronic burnout, distress, and loneliness. This instrumental study aimed to examine the factor structure, reliability, convergent validity, criterion validity, and cutoff scores of a short loneliness measure: the Three-Item version of the University of California, Los Angeles, Loneliness Scale (UCLALS3) in a convenience sample of dementia family caregivers (N = 571, mean age = 53 ±12 years, 81.6% females). Methods: Exploratory and confirmatory factor analyses were used to examine the structure of the UCLALS3 while receiver-operating characteristic (ROC) curve, including caregiving burden and emotional distress as outcomes, was used to examine its cutoff. Results: One factor accounted for 79.0% of the variance in the UCLALS3; it was perfectly invariant across genders but variant at the metric level across countries. The scale had adequate internal consistency (alpha = 0.87), high item-total correlations (0.69 - 0.79), reduced alpha if item deleted (0.77 - 0.86), and strong positive correlations with caregiving burden and psychological distress scores (r = 0.57 & 0.74, p values = 0.01). Percentile scores and the ROC curve suggested two cutoffs (≥6 and ≥6.5), which classified 59.3 and 59.4% of the participants as having higher levels of loneliness-comparable to global levels of loneliness among informal caregivers. The Mann-Whitney test revealed significantly high levels of caregiving burden and distress in caregivers scoring ≥6.5 on the UCLALS3. Conclusion: The UCLALS3 is a valid short scale; its cutoff ≥6.5 may flag major clinically relevant symptoms in dementia caregivers, highlighting the need for tailored interventions that boost caregivers' individual perception of social relationships. More investigations are needed to confirm UCLALS3 invariance across countries.