The use of geotechnologies combined with remote sensing has become increasingly essential and important for efficiently and economically understanding land use and land cover in specific regions. The objective of this study was to observe changes in agricultural activities, particularly agriculture/livestock farming, in the North Forest Zone of Pernambuco (Mata Norte), a political-administrative region where sugarcane cultivation has historically been the backbone of the local economy. The region's sugarcane biomass also contributes to land use and land cover observations through remote sensing techniques applied to digital satellite images, such as those from Landsat-8, which was used in this study. This study was conducted through digital image processing, allowing the calculation of the Normalized Difference Vegetation Index (NDVI), the Soil-Adjusted Vegetation Index (SAVI), and the Leaf Area Index (LAI) to assess vegetation cover dynamics. The results revealed that sugarcane cultivation is the predominant agricultural and vegetation activity in Mata Norte. Livestock farming areas experienced a significant reduction over the observed decade, which, in turn, led to an increase in agricultural and forested areas. The most dynamic spatiotemporal behavior was observed in the expansion and reduction of livestock areas, a more significant change compared to sugarcane areas. Therefore, land use and land cover in this region are more closely tied to sugarcane cultivation than any other agricultural activity.

The study aimed to investigate the concept of workplace equality as experienced and perceived by female librarians of Punjab, Pakistan. Through this investigation, the study aimed to contribute to the broader discourse on creating equitable and inclusive workplaces for women in the field of library and information science. A qualitative research method based on semi-structured interviews was employed to meet the objectives of the study. The interview guide was used to collect data from female librarians working in the Higher Education Commission’s (HEC) recognized public and private sector universities of the Punjab, Pakistan. According to the results, female librarians shared that they have faced gender-based discrimination in job allocation as male librarians were favored for tasks with additional wages or representation at corporate events. Private sector candidates reported issues related to career development opportunities as managers often restrict participation in seminars, conferences, and higher education pursuits. The study also highlighted that inequalities or discriminations affect employees motivation and enthusiasm. This study highlights issues of inequality from a female perspective in the library and information science field, contributing to a deeper understanding of the key factors to ensure equitable workplaces. This study may be a useful contribution to the body of research literature, as well as the findings may help in sensitizing the management and authorities to control the work environment to facilitate females, and to make female-oriented policies.

Purpose: This article explores the adoption of Artificial Intelligence (AI) in Human Resource Management (HRM) in the UAE, focusing on the critical challenges of fairness, bias, and privacy in recruitment processes. The study aims to understand how AI is transforming HR practices in the UAE, highlighting the issues of bias and privacy while examining real-world applications of AI in recruitment, employee engagement, talent management, and learning and development. Methodology: Through case study methodology, detailed insights are gathered from these companies to understand real-world applications of AI in HRM. A comparative analysis is conducted, comparing AI-driven HRM practices in UAE-based organizations with international examples to highlight global trends and best practices. Findings: The research reveals that while AI holds significant potential to streamline HR functions such as recruitment, onboarding, performance monitoring, and talent management, it also discusses challenges and strategies companies face and develop in integrating AI into their HRM processes, reflecting the broader context of AI adoption in the UAE’s HR landscape. Originality: This paper contributes to the growing body of literature on AI in HRM by focusing on the unique context of the UAE, a rapidly developing market with a highly diverse workforce. It highlights the specific challenges and opportunities faced by organizations in the UAE when implementing AI in HRM, particularly regarding fairness, bias, and data privacy.

This study explores the factors affecting dentists’ willingness to use social media in their practices, examining how consumer behavior influences their adoption decisions. Despite the growing use of social media across industries, its adoption in dentistry remains relatively underexplored. As investments in digital technologies increase, understanding dentists’ intentions to integrate social media becomes crucial, especially considering the evolving consumer behavior patterns in healthcare. Using the Technology Acceptance Model (TAM) and factoring in patient pressures, this study analyzes data from 209 respondents through SPSS and Smart PLS 4.0. The results offer valuable insights for dentists, highlighting the benefits of social media integration, and justifying investments in these platforms to align with changing consumer expectations. The study also discusses its limitations and suggests future research directions to further explore social media adoption in dentistry and its potential to drive economic growth within the sector.

The Mass Rapid Transit (MRT) Purple Line project is part of the Thai government’s energy- and transportation-related greenhouse gas reduction plan. The number of passengers estimated during the feasibility study period was used to calculate the greenhouse gas reduction effect of project implementation. Most of the estimated numbers exceed the actual number of passengers, resulting in errors in estimating greenhouse gas emissions. This study employed a direct demand ridership model (DDRM) to accurately predict MRT Purple Line ridership. The variables affecting the number of passengers were the population in the vicinity of stations, offices, and shopping malls, the number of bus lines that serve the area, and the length of the road. The DDRM accurately predicted the number of passengers within 10% of the observed change and, therefore, the project can help reduce greenhouse gas emissions by 1289 tCO₂ in 2023 and 2059 tCO₂ in 2030.

The human factor of production is a significant player in increased organizational productivity. Due to the contemporary competitive work environment, the millennial in front-line jobs is faced with demanding work activities, resulting in challenges to their psychological well-being. Therefore, exploring the connectedness between work-life balance, employee engagement and psychological well-being of the millennial becomes imperative. Research was conducted, using an ex-post facto research design, among 320 purposively selected front-line millennial employees, with a mean age of 32 years. The instrument administered in a Google Form survey contained a 44-item self-report questionnaire, comprising work-life balance, employee engagement with components as vigor, dedication and absorption, and employee well-being. Data analyzed revealed that work-life balance significantly predicted employee well-being, accounting for 25% variance. The dimensions of employee engagement (vigor, dedication and absorption) collectively accounted for 7% variance in employee well-being. The study establishes the fact that to enhance the psychological well-being of Millennials in front-line jobs, organizational management should design the work structures to allow for work-life balance, which will as well increase their work engagement. They can encourage employees to find meaning and purpose in their work (dedication), provide opportunities for skill development and autonomy (vigor), and create an environment that allows employees to fully immerse themselves in their tasks (absorption). These could be implemented through organizational development strategies and work design. However, future research should target additional variables, replicate the study in different contexts and among another population of employees, employ longitudinal data collection methods, and increase sample sizes. Furthermore, measures should be taken to minimize the impact of social desirability and enhance the generalizability of the research.