Abstract
Conhecer o perfil das mulheres brasileiras que atuam em Processamento de Linguagem Natural (PLN) é um importante passo para o desenvolvimento de políticas e programas que visem aumentar a inclusão e a diversidade nessa área. Este é o primeiro trabalho realizado no Brasil com este fim. A partir de dados coletados via consulta pública, Lattes e Linkedin, notou-se que o perfil é de uma formação em computação ou linguística, atuando em empresas ou universidades, mas com pouca diversidade étnica e aparente dificuldade em conciliar vida profissional e maternidade. Analisando mais especificamente o grupo “Brasileiras em PLN” constatou-se uma expressiva capacidade de publicação e orientação, mas ainda uma baixa colaboração entre nossas integrantes.

Abstract
To forestall future financial crises, risk governance has been embraced as a line of defense. Therefore, this paper seeks to synthesize the risk governance literature, identifying gaps, and suggesting direction for future research, through a systematic literature review (SLR). Analyzing 151 papers from the Scopus and Web of Science databases, this paper finds a steady increase in academic work on risk governance. Using the theory, context, characteristics, and methodology (TCCM) framework, the study emphasizes the importance of chief risk officers, geographical context coverage, and effectiveness and regulation of risk governance. Methodologically, endogeneity issues are a major concern for researchers, agency theory (AT) being the most popular theory used. Finally, moderating and mediating variables that affect risk governance are identified as important but under-explored. While providing practitioners and policymakers with a framework, empirical testing is encouraged. The study contributes to SDG Goal 8, Target 10 of strengthening financial institutions and promoting a resilient financial system.

Abstract
Th chapter presents an empirical study on a Brazilian cyber-activism movement on Instagram associated with the hashtag #CorpoLivre (#FreeBody in Portuguese). This movement, which was established in 2018, has published more than 3,000 posts and has over 400,000 followers, disseminates anti-fatphobia and real body discourses, and promotes a positive relationship between women and their bodies beyond traditional beauty standards. The study analyses the posts made by the feminist movement on Instagram in December 2022, with a sample size of 101 posts. The study adopted the framework developed by Khurana and Knight for the analysis, which enables the classification of the sample posts in terms of message appeal, orientation, engagement, popularity, and image characteristics. This framework was used to examine the relationship between content characteristics and engagement. Additionally, the study includes a content analysis of the posts' comments, specifically evaluating the valence (positive, negative, or neutral) to assess the effectiveness of the characteristics of the posts. © 2023, IGI Global. All rights reserved.

Abstract
Navigation is one of the most important tasks for a mobile robot and the localisation is one of its main requirements. There are several types of localisation solutions such as LiDAR, Radio-frequency and acoustic among others. The well-known line follower has been a solution used for a long time ago and still remains its application, especially in competitions for young researchers that should be captivated to the scientific and technological areas. This paper describes two methodologies to estimate the position of a robot placed on a gradient line and compares them. The Least Squares and the Machine Learning methods are used and the results applied to a real robot allow to validate the proposed approach.

Abstract
Assessing the evolution of the performance of water supply and sanitation services is essential to monitor progress towards the universalization of water services, as specified by the Sustainable Development Goal 6 of Agenda 2030, adopted by United Nations member countries. Brazil, a developing country with a continental size and geographical diversity, will face significant challenges to achieve this goal. The main objective of this paper is to evaluate the evolution of productivity of water supply and sanitation services in Brazilian municipalities in the period 2012-2019. The analysis also explores whether water services' performance is balanced across the country, with a specific analysis of performance at the macroregion level. From a methodological perspective, this research evaluates productivity change over time using a Malmquist Productivity Index estimated with a metafrontier, satisfying the circularity property. It also develops a pseudo Malmquist index that compares productivity levels across macro-regions. The results revealed a productivity loss of approximately 4% at the national level, with an unequal profile across the macro-regions. The Southeast municipalities stand out for exhibiting, on average, higher productivity levels than the South and Northeast municipalities.

Abstract
In industrial environments, the measurement and monitoring of filling levels (FL) in refilling stations (RS) are critical for quality control processes. Traditional methods used for this purpose, such as manual inspection and sensor-based techniques, have proven to be costly and time-consuming. As an alternative, this paper proposes a novel approach that leverages computer vision (CV) and advanced image processing techniques. This approach provides a more efficient and accurate method for monitoring filling levels in refilling stations, thereby reducing operational costs. The system operates through a comprehensive five-stage pipeline, including pre-processing, perspective transformation, thresholding and edge detection, post-processing and filling level calculation. The performance evaluation of this approach demonstrated promising results in accurately determining filling levels in most scenarios. However, we also identified challenges such as overlapping columns and occlusions in the camera’s field of view that require further improvements. By addressing these challenges, our research aims to develop a streamlined and automated method for filling level measurement in refilling stations, thereby enhancing productivity in industrial environments. Ultimately, this proposed approach holds potential to significantly improve the efficiency of refilling stations across multiple sectors. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.