2025
Authors
Almeida, F; Okon, E;
Publication
African Journal of Economic and Management Studies
Abstract
2025
Authors
Avraam, D; Wilson, RC; Chan, NA; Banerjee, S; Bishop, TRP; Butters, O; Cadman, T; Cederkvist, L; Duijts, L; Montagut, XE; Garner, H; Gonçalves, G; González, JR; Haakma, S; Hartlev, M; Hasenauer, J; Huth, M; Hyde, E; Jaddoe, VWV; Marcon, Y; Mayrhofer, MT; Molnar-Gabor, F; Morgan, AS; Murtagh, M; Nestor, M; Andersen, AMN; Parker, S; de Moira, AP; Schwarz, F; Strandberg-Larsen, K; Swertz, MA; Welten, M; Wheater, S; Burton, P;
Publication
BIOINFORMATICS ADVANCES
Abstract
Motivation The validity of epidemiologic findings can be increased using triangulation, i.e. comparison of findings across contexts, and by having sufficiently large amounts of relevant data to analyse. However, access to data is often constrained by practical considerations and by ethico-legal and data governance restrictions. Gaining access to such data can be time-consuming due to the governance requirements associated with data access requests to institutions in different jurisdictions.Results DataSHIELD is a software solution that enables remote analysis without the need for data transfer (federated analysis). DataSHIELD is a scientifically mature, open-source data access and analysis platform aligned with the 'Five Safes' framework, the international framework governing safe research access to data. It allows real-time analysis while mitigating disclosure risk through an active multi-layer system of disclosure-preventing mechanisms. This combination of real-time remote statistical analysis, disclosure prevention mechanisms, and federation capabilities makes DataSHIELD a solution for addressing many of the technical and regulatory challenges in performing the large-scale statistical analysis of health and biomedical data. This paper describes the key components that comprise the disclosure protection system of DataSHIELD. These broadly fall into three classes: (i) system protection elements, (ii) analysis protection elements, and (iii) governance protection elements.Availability and implementation Information about the DataSHIELD software is available in https://datashield.org/ and https://github.com/datashield.
2025
Authors
Marcos, R; Gomes, A; Santos, M; Coelho, A;
Publication
ANATOMICAL SCIENCES EDUCATION
Abstract
Histology is a preclinical subject transversal in medical, dental, and veterinary curricula. Classical teaching approaches in histology are often undermined by lower motivation and engagement of students, which may be addressed by innovative learning environments. Herein, we developed a serious game approach and compared it with a classical teaching style. The students' feedback was evaluated by questionnaires, and their performance on quizzes and exam's scores were assessed. The serious game (Histopoly) consisted of a game-based web application for the teacher/game master, a digital gaming application used by the students as a controller, and a projected digital board game. The board featured rows for the four fundamental tissues (epithelial, connective, muscular, and nervous) paired with question tiles and additional tiles with more demanding activities (e.g., drawing, presenting slides, and making a syllabus). Participants included all veterinary students enrolled in the first year. Paired laboratory sessions were split with four sections (n = 94 students) playing Histopoly at the end of all sessions and two sections (n = 28 students) completing small evaluations every three weeks at the beginning of sessions. According to the questionnaires, students that played the serious game were more motivated, engaged, and more interconnected with classmates. The activity was considered fun, and students enjoyed the classes more. No differences in the final examination scores were found, but the percentage of correct answers provided throughout the serious game was significantly higher. Overall, these findings argue for the inclusion of serious games in modern histology teaching to promote student engagement in learning.
2025
Authors
Reza, S; Ferreira, MC; Machado, JJM; Tavares, JMRS;
Publication
EXPERT SYSTEMS
Abstract
An autonomous vehicle can sense its environment and operate without human involvement. Its adequate management in an intelligent transportation system could significantly reduce traffic congestion and overall travel time in a network. Adaptive traffic signal controller (ATSC) based on multi-agent systems using state-action-reward-state-action (SARSA (lambda)) are well-known state-of-the-art models to manage autonomous vehicles within urban areas. However, this study found inefficient weights updating mechanisms of the conventional SARSA (lambda) models. Therefore, it proposes a Gaussian function to regulate the eligibility trace vector's decay mechanism effectively. On the other hand, an efficient understanding of the state of the traffic environment is crucial for an agent to take optimal actions. The conventional models feed the state values to the agents through the MinMax normalization technique, which sometimes shows less efficiency and robustness. So, this study suggests the MaxAbs scaled state values instead of MinMax to address the problem. Furthermore, the combination of the A-star routing algorithm and proposed model demonstrated a good increase in performance relatively to the conventional SARSA (lambda)-based routing algorithms. The proposed model and the baselines were implemented in a microscopic traffic simulation environment using the SUMO package over a complex real-world-like 21-intersections network to evaluate their performance. The results showed a reduction of the vehicle's average total waiting time and total stops by a mean value of 59.9% and 17.55% compared to the considered baselines. Also, the A-star combined with the proposed controller outperformed the conventional approaches by increasing the vehicle's average trip speed by 3.4%.
2025
Authors
Nunes, JdS; Nunes, RdS; Schlemmer, E;
Publication
Congresso Internacional de Cidadania Digital
Abstract
2025
Authors
Andrade, BPB; Piran, FAS; Lacerda, DP; Sellitto, MA; Campos, LMD; Siluk, JCM;
Publication
ENERGY EFFICIENCY
Abstract
Net Zero Energy Building (NZEB) is a concept that promotes the reduction of energy consumption in buildings by applying energy efficiency measures. The energy supply for the remaining demand should only come from sources with low CO2 emissions. Despite abundant research on NZEB for new buildings, only a small number of studies address its application to those already existing. This study aims to bridge this research gap by organizing the proposed methods to transform existing buildings into NZEB. The research method is a systematic literature review covering the methodological development and the application of the concept. We conducted a bibliometric and Scientometric analysis of 117 articles and a content analysis of 48 of them. The results highlighted that the methods identified follow similar stages: (i) planning, (ii) data collection, (iii) pre-design, (iv) design, and (v) delivery. The sub-stage with the highest frequency (88%) was the presentation of the efficiency measure package, making it an essential step in the transformation process. The review did not find specific topics, such as equipment listing and performance, occupant engagement, and charrette design. Finally, the study established guidelines for future research.
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