Abstract
Logging has long been a pillar for monitoring and troubleshooting software systems. From server and infrastructure to application-specific data, logs are an easy and quick way to collect information that may prove useful in diagnosing future issues. When systems become distributed, as is common on the cloud, logs are harder to collect and process. This paper presents three design patterns for logging in cloud-native applications. Standard Logging advises using a standard format for logs across all services and teams so they are easier to process by humans and machines. Audit Logging suggests that important user actions and system changes are recorded in a data store to ensure regulatory compliance or help investigate user-reported issues. Lastly, Log Sampling is about prioritizing logs to maintain a manageable amount of storage. These patterns were mined from existing literature on logging and cloud best practices to make them simpler to communicate, more detailed, and easier for all practitioners to understand.

Abstract
Introduction/Objective: the objective of this article is to analyze the current academic literature on smart cities in Brazil with evidence of the application of Digital Twin or Digital Shadow technology. Method: Integrative Literature Review was used as the research instrument, analyzing in the articles: a) objective; b) research method; c) study subject (location); d) application of Digital Twin or Digital Shadow; e) Results and conclusions. Results: portfolio with 25 articles on the topic and qualitative analysis regarding objective, method, study location, Digital Twin technology, Digital Shadow, and results. Studies with elements of Digital Shadow are perceived timidly in two cases of smart cities in Brazil. Conclusions: smart city technologies should be centered on the interests of users to not lose their humanity. It is worth adding that people’s needs change and, therefore, smart technologies should have a forward-looking vision to anticipate the needs of future generations. Digital Twin technology is a model that can contribute in this sense, monitoring and providing readings of future scenarios for smart cities. © 2024, Programa de Pos-Graduacao em Gestao da Informacao, Universidade Federal do Parana. All rights reserved.

Abstract
Although service-based architectures offer significant advantages, some aspects of service orchestration remain challenging, particularly for new adopters. Despite the availability of resources on orchestration techniques, many lack clarity or detail. As a result, best practices are often not well explained or standardized, making them difficult to implement and hindering broader adoption within the software industry. To address these concerns, we looked into existing literature and tools to identify common practices. We used our findings to describe as patterns two patterns focused on orchestration configuration, which we present in this paper, and that serve as a stepping stone for other orchestration practices: labeling and resource reserve and limit. These patterns contribute to configuring a system; the former consists of defining key-value pairs to express identifiable properties of system components, and the latter is about supporting two bounds for each resource type: the amount of resources reserved for the service to operate and the maximum amount of resources it can use.

Abstract
This paper presents a usability evaluation of a companion application for managing older adults' physical activity sessions in an immersive multiuser virtual environment. The companion application was designed to facilitate the trainer ' s role and enhance the overall user experience in the virtual multiuser environment. Four trainers were recruited to participate in the study, they performed two tasks to prepare and manage training sessions with older adults using the companion application. Researchers used an open-ended questionnaire to interview the participants. The results revealed a high satisfaction and appreciation for the application features used to prepare and manage the training sessions. Participants found the application useful and intuitive, and they also recommended a list of future desirable features related to the application ' s feedback and help mechanisms, as well as its content. In addition to the necessity to provide mobile and tablet versions of the application. A few usability problems were detected related to information presentation and navigation. The future design of the companion application will consider all the detected usability problems and desired features.

Abstract
Ensuring the reproducibility of computational scientific experiments is crucial for advancing research and fostering scientific integrity. However, achieving reproducibility poses significant challenges, particularly in the absence of appropriate software tools to help. This paper addresses this issue by comparing existing tools designed to assist researchers across various fields in achieving reproducibility in their work. We were able to successfully run eight tools and execute them to reproduce three existing experiments from different domains. Our findings show the critical role of technical choices in shaping the capabilities of these tools for reproducibility efforts. By evaluating these tools for replicating experiments, we contribute insights into the current landscape of reproducibility support in scientific research. Our analysis offers guidance for researchers seeking appropriate tools to enhance the reproducibility of their experiments, highlighting the importance of informed technical decisions in facilitating reproducibility across diverse domains.

Abstract
Emotions encompass physiological systems that can be assessed through biosignals like electromyography and electrocardiography. Prior investigations in emotion recognition have primarily focused on general population samples, overlooking the specific context of theatre actors who possess exceptional abilities in conveying emotions to an audience, namely acting emotions. We conducted a study involving 11 professional actors to collect physiological data for acting emotions to investigate the correlation between biosignals and emotion expression. Our contribution is the DECEiVeR (DatasEt aCting Emotions Valence aRousal) dataset, a comprehensive collection of various physiological recordings meticulously curated to facilitate the recognition of a set of five emotions. Moreover, we conduct a preliminary analysis on modeling the recognition of acting emotions from raw, low- and mid-level temporal and spectral data and the reliability of physiological data across time. Our dataset aims to leverage a deeper understanding of the intricate interplay between biosignals and emotional expression. It provides valuable insights into acting emotion recognition and affective computing by exposing the degree to which biosignals capture emotions elicited from inner stimuli.