Abstract
The advantages of Virtual Reality (VR) over traditional training, together with the development of VR technology, have contributed to an increase in the body of literature on training professionals with VR. However, there is a gap in the literature concerning the comparison of training in a Virtual Environment (VE) with the same training in a Real Environment (RE), which would contribute to a better understanding of the capabilities of VR in training. This paper presents a study with firefighters (N = 12) where the effect of a firefighter training exercise in a VE was evaluated and compared to that of the same exercise in a RE. The effect of environments was evaluated using psychophysiological measures by evaluating the perception of stress and fatigue, transfer of knowledge, sense of presence, cybersickness, and the actual stress measured through participants' Heart Rate Variability (HRV). The results showed a similar perception of stress and fatigue between the two environments; a positive, although not significant, effect of the VE on the transfer of knowledge; the display of moderately high presence values in the VE; the ability of the VE not to cause symptoms of cybersickness; and finally, obtaining signs of stress in participants' HRV in the RE and, to a lesser extent, signs of stress in the VE. Although the effect of the VE was shown to be non-comparable to that of the RE, the authors consider the results encouraging and discuss some key factors that should be addressed in the future to improve the results of the training VE.

Abstract
Context. A low-mass companion potentially in the brown dwarf mass regime was discovered on a similar to 12 yr orbit (similar to 5.5 au) around HD 167665 using radial velocity (RV) monitoring. Joint RV-astrometry analyses confirmed that HD 167665B is a brown dwarf with precisions on the measured mass of similar to 4-9%. Brown dwarf companions with measured mass and luminosity are valuable for testing formation and evolutionary models. However, its atmospheric properties and luminosity are still unconstrained, preventing detailed tests of evolutionary models. Aims. We further characterize the HD 167665 system by measuring the luminosity and refining the mass of its companion and reassessing the stellar age. Methods. We present new high-contrast imaging data of the star and of its close-in environment from SPHERE and GRAVITY, which we combined with RV data from CORALIE and HIRES and astrometry from HIPPARCOS and Gaia. Results. The analysis of the host star properties indicates an age of 6.20 +/- 1.13 Gyr. GRAVITY reveals a point source near the position predicted from a joint fit of RV data and HIPPARCOS-Gaia proper motion anomalies. Subsequent SPHERE imaging confirms the detection and reveals a faint point source of contrast of Delta H2 = 10.95 +/- 0.33 mag at a projected angular separation of similar to 180 mas. A joint fit of the high-contrast imaging, RV, and HIPPARCOS intermediate astrometric data together with the Gaia astrometric parameters constrains the mass of HD 167665B to similar to 1.2%, 60.3 +/- 0.7 M-J. The SPHERE colors and spectrum point to an early or mid-T brown dwarf of spectral type T4(-2)(+1). Fitting the SPHERE spectrophotometry and GRAVITY spectrum with synthetic spectra suggests an effective temperature of similar to 1000-1150 K, a surface gravity of similar to 5.0-5.4 dex, and a bolometric luminosity log(L/L-circle dot)=-4.892(-0.028)(+0.024) dex. The mass, luminosity, and age of the companion can only be reproduced within 3 sigma by the hybrid cloudy evolutionary models of Saumon & Marley (2008, ApJ, 689, 1327), whereas cloudless evolutionary models underpredict its luminosity.

Abstract
The notable expansion of technologies related to automated processes has been observed in recent years, largely driven by the significant advantages they provide across diverse industries. Concurrently, there has been a rise in simulation technologies aimed at replicating these complex systems. Nevertheless, in order to fully leverage the potential of these technologies, it is crucial to ensure the highest possible resemblance of simulations to real-world scenarios. In brief, this work consists of the development of a data acquisition and processing pipeline allowing a posterior search for the optimal physical parameters in MuJoCo simulator to obtain a more accurate simulation of a dexterous robotic hand. In the end, a Random Search optimization algorithm was used to validate this same pipeline.

Abstract
Integrating emerging technologies, such as AI, the Metaverse, and IoT, revolutionizes management and brand practices. Brands can create captivating virtual experiences within the metaverse, including virtual storefronts and interactive events. Scientific data on brand management in the metaverse must be improved due to the concept’s early-stage development. While virtual environments exist, they do not fully encompass the metaverse’s scope. So, this research bridges this gap by exploring the relationship between brand management and the metaverse, focusing on consumer perceptions and their contribution to brand equity in this virtual realm. Netnography with a data mining approach was the methodology followed in this paper. Data were extracted by a metaverse community on the Reddit platform and, in total, 696 posts and comments were analyzed from June 2022 until May 2023. The results highlighted a positive and favorable consumer perception of brand management in the metaverse reality. This research contributes to the emerging field of metaverse brand management, investigating the impact of consumer perceptions on brand equity. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

Abstract
Organizations aim to achieve operational efficiency capable of responding to high market competitiveness. The implementation of automation systems in organizational processes is a key factor in improving operational efficiency. This paper intends to contribute for a better understanding of the adoption of automation systems in organizations and analyze their impact on employee performance, considering the conditions under which they were implemented. The methodology for this study was qualitative research, in which semi-structured exploratory interviews conducted with employees from the Accounts Receivable department of automotive sector companies were carried out. The main goal was to understand their perception of the use of automation systems in their work tasks. The results of this research led to the conclusion that automation systems, even when underutilized, are beneficial in reducing repetitive and manual tasks. Nevertheless, the way in which they are implemented has a direct impact on the motivation of employees to use them.

Abstract
Online microtask labor has increased its role in the last few years and has provided the possibility of people who were usually excluded from the labor market to work anytime and without geographical barriers. While this brings new opportunities for people to work remotely, it can also pose challenges regarding the difficulty of assigning tasks to workers according to their abilities. To this end, cognitive personalization can be used to assess the cognitive profile of each worker and subsequently match those workers to the most appropriate type of work that is available on the digital labor market. In this regard, we believe that the time is ripe for a review of the current state of research on cognitive personalization for digital labor. The present study was conducted by following the recommended guidelines for the software engineering domain through a systematic literature review that led to the analysis of 20 primary studies published from 2010 to 2020. The results report the application of several cognition theories derived from the field of psychology, which in turn revealed an apparent presence of studies indicating accurate levels of cognitive personalization in digital labor in addition to a potential increase in the worker's performance, most frequently investigated in crowdsourcing settings. In view of this, the present essay seeks to contribute to the identification of several gaps and opportunities for future research in order to enhance the personalization of online labor, which has the potential of increasing both worker motivation and the quality of digital work.