Abstract
The human-environment-vehicle triad and how it relates to crashes has long been a topic of discussion, in which the human factor is consistently seen as the leading cause. Recently, more sophisticated approaches to Road Safety have advocated for a road-driver interaction view, in which human characteristics influence road perception and road environment affects driver behavior. This study focuses on road-driver interaction by using a driving simulator. The objective is to investigate how the driver profile influences driving performance and the effects of three countermeasures (peripheral transverse lines before and after the beginning of the curves and roadside poles in the curves). Fifty-six middle-aged male participants drove a non-challenging rural highway simulated scenario based on a real road where many single-vehicle crashes occurred. The drivers' profiles were assessed through their behavioral history measured by a validated version of the Driver Behavior Questionnaire (DBQ) comprising three dimensions: Errors (E), Ordinary Violations (OV), and Aggressive Violations (AV). The relationship between speed and trajectory measures and drivers' profiles was investigated using randomparameter models with heterogeneity in the means. The models' results showed that the DBQ subscale scores in OV explained a considerable part of the heterogeneity found in drivers' performance. Furthermore, the heterogeneity in the means caused by the DBQ subscale scores in OV and E in the presence of peripheral transverse lines indicates a difference in how drivers react to the countermeasures. The peripheral lines were more efficient than roadside poles to moderate speed but did not positively influence all drivers' trajectories. Although the peripheral lines could be seen as an alternative to change driver behavior in a non-challenging or monotonous road environment, the design used in this study should be reviewed.

Abstract
Na viragem do milénio, decorrentes sobretudo do Processo de Bolonha e da (r)evolução tecnológica, colocaram-se ao Ensino Superior e aos docentes vários desafios, nomeadamente os relacionados com questões pedagógicas. Tendo essa situação por referência, o artigo apresenta um estudo que analisou a produção académica em Portugal entre 2012-2021, pesquisada com recurso a diversas bases de dados e interpretada por técnicas de análise de frequência e de conteúdo. A análise evidenciou que: o número de artigos publicados em revistas indexadas ou em atas de conferências não foi tão expressivo como a urgência da reflexão que a temática merecia; o número de teses de doutoramento e dissertações de mestrado com foco nas questões pedagógicas no Ensino Superior foi relativamente reduzido; a metodologia desses trabalhos, embora distribuída entre procedimentos de orientação qualitativa, mista e quantitativa, teve menor expressão neste último tipo metodológico; muitos dos autores dos trabalhos académicos são do campo educacional, embora existam também autores de outras áreas científicas; a maior parte dos trabalhos académicos teve como foco a formação pedagógica dos docentes do Ensino Superior, a que se seguiram estudos relativos a práticas pedagógicas e a desafios colocados ao Ensino Superior. A par dessas conclusões, o estudo permitiu identificar limitações que justificam o seu aprofundamento, mas também recomendações para futuros trabalhos de investigação sobre essa temática.

Abstract
Service-based architecture is an approach that emerged to overcome software development challenges such as difficulty to scale, low productivity, and strong dependence between elements. Microservice, an architectural style that follows this approach, offers advantages such as scalability, agility, resilience, and reuse. This architectural style has been well accepted and used in industry and has been the target of several academic studies. However, analyzing the state-of-the-art and -practice, we can notice a fuzzy limit when trying to classify and characterize the architecture of service-based systems. Furthermore, it is possible to realize that it is difficult to analyze the trade-offs to make decisions regarding the design and evolution of this kind of system. Some concrete examples of these decisions are related to how big the services should be, how they communicate, and how the data should be divided/shared. Based on this context, we developed the CharM, a model for characterizing the architecture of service-based systems that adopts microservices guidelines. To achieve this goal, we followed the guidelines of the Design Science Research in five iterations, composed of an ad-hoc literature review, discussions with experts, two case studies, and a survey. As a contribution, the CharM is an easily understandable model that helps professionals with different profiles to understand, document, and maintain the architecture of service-based systems.& COPY; 2023 Elsevier Inc. All rights reserved.

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Monitoring a system over time is as important as ever with the increasing use of cloud-native software architectures. This paper expands the set of patterns published in a previous paper (Liveness Endpoint, Readiness Endpoint and Synthetic Testing) with two solutions for supporting teams in diagnosing occurring issues — Deployment Tracking and Exception Tracking. These patterns advise tracking relevant events that occur in the system. The Deployment Tracking pattern provides means to limit the sources of an anomaly, and the Exception Tracking pattern makes a specific class of anomalies visible so that a team can act on them. Both patterns help practitioners identify the root cause of an issue, which is instrumental in fixing it. They can help even less experienced professionals to improve monitoring processes, and reduce the mean time to resolve problems with their application. These patterns draw on documented industry best practices and existing tools. In order to help the reader find other patterns that supplement the ones suggested in this study, relations to already-existing monitoring patterns are also examined. © 2023 Copyright held by the owner/author(s).