The aim of this study is to examine the relationship between Environmental, Social and Governance (ESG) activities and the performance of Thai listed firms. The moderating roles of board size and CEO duality on this relationship are also assessed. The ESG score provided by LSEG (formerly Refinitiv) is chosen to measure ESG activities, both as an overall ESG combined scores and as Environment, Social, and Governance pillar scores. Multiple regression analysis is used to test the impact of ESG on firm performance while the PROCESS macro is used to test the moderating effects. Results reveal that the overall ESG combined score demonstrates no statistically significant effect on firm market-based performance. However, it shows the significant effects on firm performance for both the ESG combined score and the Environmental and Social pillar scores when moderated by board size and CEO duality; Governance pillar score exhibits no significant effect. Additionally, it is found that when the CEO operates only as the managing director and small board size and average board size are evident, higher ESG disclosure scores enhance firm performance. However, when the CEO serves as both managing director and chairman of the board of directors, and where there is a large board size, higher ESG disclosure scores diminish firm performance. This study contributes to the ESG literature and encourages companies to enhance their performance by implementing ESG combined activities with good governance policies.

The fields of urban design and public health play an important role in the success and failure of the city. Research combining the two fields to improve citizens’ lives is rare, particularly in a rapidly developing city like Doha. This study highlights the urban planning efforts of the municipality of Doha city to improve the mental health of its citizens and aims to understand the impact of urban design elements on mental health by analyzing the physical form and characteristics of green urban areas in Doha. The methods employed include an observational study and a structured survey interview, where visitors’ responses to selected green urban areas are analyzed. The results show how Doha officials are working to improve the mental health of its citizens by providing accessible, child-friendly, older citizen-friendly, and equitable green urban spaces and suggesting policies that could provide more opportunities for people and the government to provide a healthier environment in Doha. The implications encompass shaping urban design strategies, raising public awareness, enhancing healthcare initiatives, and ultimately emphasizing the positive impact of well-designed green spaces for mental well-being in Doha and other Gulf countries.

Named Entity Recognition (NER), a core task in Information Extraction (IE) alongside Relation Extraction (RE), identifies and extracts entities like place and person names in various domains. NER has improved business processes in both public and private sectors but remains underutilized in government institutions, especially in developing countries like Indonesia. This study examines which government fields have utilized NER over the past five years, evaluates system performance, identifies common methods, highlights countries with significant adoption, and outlines current challenges. Over 64 international studies from 15 countries were selected using PRISMA 2020 guidelines. The findings are synthesized into a preliminary ontology design for Government NER.

In Côte d'Ivoire, the government and its development partners have implemented a national strategy to promote agroforestry and reforestation systems as a means to combat deforestation, primarily driven by agricultural expansion, and to increase national forest cover to 20% by 2045. However, the assessment of these systems through traditional field-based methods remains labor-intensive and time-consuming, particularly for the measurement of dendrometric parameters such as tree height. This study introduces a remote sensing approach combining drone-based Airborne Laser Scanning (ALS) with ground-based measurements to enhance the efficiency and accuracy of tree height estimation in agroforestry and reforestation contexts. The methodology involved two main stages: first, the collection of floristic and dendrometric data, including tree height measured with a laser rangefinder, across eight (8) agroforestry and reforestation plots; second, the acquisition of ALS data using Mavic 3E and Matrice 300 drones equipped with LiDAR sensors to generate digital canopy models for tree height estimation and associated error analysis. Floristic analysis identified 506 individual trees belonging to 27 genera and 18 families. Tree height measurements indicated that reforestation plots hosted the tallest trees (ranging from 8 to 16 m on average), while cocoa-based agroforestry plots featured shorter trees, with average heights between 4 and 7 m. A comparative analysis between ground-based and LiDAR-derived tree heights showed a strong correlation (R2 = 0.71; r = 0.84; RMSE = 2.24 m; MAE = 1.67 m; RMSE = 2.2430 m and MAE = 1.6722 m). However, a stratified analysis revealed substantial variation in estimation accuracy, with higher performance observed in agroforestry plots (R2 = 0.82; RMSE = 2.21 m and MAE = 1.43 m). These findings underscore the potential of Airborne Laser Scanning as an effective tool for the rapid and reliable estimation of tree height in heterogeneous agroforestry and reforestation systems.

This study aims to investigate the impact of dance training on the mental health of college students. Utilizing experimental research methods, we established an experimental group and a control group to compare changes in mental health dimensions—including anxiety, depression, self-esteem, and social skills—between the two groups before and after 12 weeks of dance training. The findings indicate that dance training significantly reduces levels of anxiety and depression, while also improving self-esteem and social skills, thereby enhancing social adaptability. These results provide empirical support for the use of dance as an intervention for mental health and offer new insights for mental health education in colleges and universities.

Vietnam’s economic evolution presents a compelling case of transformative growth driven by its distinctive historical, cultural, and policy landscapes. Since the watershed Đổi Mới reforms of 1986, the country has navigated the complexities of market liberalization, socialist principles, and international integration, achieving remarkable development while preserving its economic sovereignty. Through a mixed-methods approach, this study delves into the impacts of Đổi Mới, assessing the successes and ongoing challenges in Vietnam’s economic restructuring. Results indicate a remarkable shift in GDP contribution from agriculture to industry and services, with a burgeoning private sector and enhanced international trade and investment. However, challenges in achieving equitable growth, inclusive development, and environmental sustainability remain salient amid global economic shifts. Vietnam’s experience underscores the critical need for targeted reforms in workforce development, economic diversity, infrastructural enhancement, environmental stewardship, and regulatory and financial governance. Vietnam’s proactive stance on economic autonomy and global participation highlights the importance of a nuanced approach in navigating the changing international landscape. In summary, Vietnam’s journey through economic structural reform provides a unique perspective on navigating development within a socialist-oriented market framework, serving as a distinctive exemplar for similar emerging economies contending with the vibrant currents of globalization.