This study investigates the awareness of environmentally friendly (green) dentistry practices among dental students and faculty at Ajman University in the United Arab Emirates. The primary objective is to assess their understanding and application of eco-friendly dental practices, including waste management, energy conservation, and sustainable material usage. Using a descriptive cross-sectional design, an online survey was administered to 231 randomly selected participants. The results show that although awareness of green dentistry has increased, its practical implementation remains limited. Specialists displayed the highest levels of knowledge and practice, while general practitioners demonstrated the least. Male participants showed greater experience and expertise compared to females, and the age group of 30–39 exhibited the highest levels of knowledge and practice, although age was not found to significantly affect awareness or usage. The findings highlight the need for enhanced education and encouragement of green dentistry to protect the environment and promote sustainable dental practices.

Background: In healthcare, research is essential for improving disease diagnosis and treatment, patient outcomes, and resource management, while fostering evidence-based practice. However, conducting research in this sector can be challenging, and healthcare workers may face various obstacles while engaging in research activities. Therefore, understanding healthcare workers’ attitudes toward research participation is essential for overcoming barriers and increasing research engagement. In this study, these aspects are examined through the analysis of survey data from a tertiary healthcare institution in Saudi Arabia. Method: Data obtained via a survey conducted between April and November 2022 among the healthcare workers and employees at a tertiary care hospital in Saudi Arabia were analyzed using descriptive and bivariate statistics. Results: The study sample comprised 713 respondents, 61.71% of whom were female, 58.06% were 26–41 years old, and 72.93% had not undertaken any research as employees or affiliates. A significant association was noted between age group and time constraints (p = 0.004) and lack of opportunity for research (p = 0.00), which were among the identified barriers to research participation. A significant association was also found between gender and barriers to pursuing research (p = 0.012). When the 193 (27.07%) participants who conducted research were asked about the challenges they encountered during this process, gender was significantly associated with difficulties in allocating time for conducting research (p = 0.042) and challenges in accessing journals and references (p = 0.016). Conclusion: The study findings highlight the importance of addressing the barriers and challenges in promoting positive attitudes toward research participation among healthcare workers considering their gender and age. In this manner, healthcare institutions can adopt an environment conducive for professional research engagement.

The digital era has ushered in significant advancements in Generative Artificial Intelligence (GAI), particularly through Generative Models and Large Language Models (LLMs) like ChatGPT, revolutionizing educational paradigms. This research, set against the backdrop of Society 5.0 and aimed at sustainable educational practices, utilizes qualitative analysis to explore the impact of Generative AI in various learning environments. It highlights the potential of LLMs to offer personalized learning experiences, democratize education, and enhance global educational outcomes. The study finds that Generative AI revitalizes learning methodologies and supports educational systems’ sustainability by catering to diverse learning needs and breaking down access barriers. In conclusion, the paper discusses the future educational strategies influenced by Generative AI, emphasizing the need for alignment with Society 5.0’s principles to foster adaptable and sustainable educational inclusion.

Purpose: This study aims to clarify the meaning of sport analysis, explore the contributions derived from sporting event analysts, and highlights the importance of responsible sport gambling. It also investigates how sustainable practices can be integrated into sports analysis to enhance social well-being. Design/methodology/approach: Secondary text data from government documents, news articles, and website information were extracted by searching keywords such as sports lottery and sports analysis in traditional Chinese, and then analyzed to establish the research framework and scope. Subsequently, 18 interviews were conducted with stakeholders to gain deeper insights. Findings: The content analyses reveals that sport analysis tends to be sport data science. Sporting event analysts may contribute to improving the performance of players or a team, enhancing spectator sports, and increasing sports lottery revenues. In the leisure aspect, the professionalism of sporting event analysts not only increases epistemic and entertainment values in spectator sports but also boosts engagement with sport lotteries. To ensure these enhancements remain beneficial, it is vital to emphasize responsible sport gambling and sustainable practices that protect vulnerable groups and promote long-term health benefits for those involved in sports. The integration of sustainable practices in sport analysis and the expertise of sporting event analysts can significantly advance economic and social development by generating funds through sport lottery industry for athlete programs, sports infrastructure, and educational initiatives, aligning with multiple Sustainable Development Goals. Additionally, the professionalism of these analysts may enhance public understanding and engagement of sports, promoting increased participation in sports, reducing healthcare costs, and contributing to the development of a healthier and more resilient society. Originality: Emphasizing responsible sports gambling is essential to the sustainability of sports lotteries and the role of sporting event analysts.

The telecommunications sector is crucial in a country’s economy. The advancements in information and communication technology have had a significant impact on this sector, particularly in the electronic transactions domain. The utilization of electronic transactions in the telecommunications sector can yield substantial benefits, including increasing non-tax state revenue and economic development in Indonesia. The Covid-19 pandemic has served as a catalyst for the sharp rise in internet usage and telecommunications services, such as work-from-home, distance learning, online shopping or payments, industrial digitization, telemedicine, and others. Consequently, digital transformation has accelerated, necessitating the equitable distribution of Information and Communication Technology (ICT) in Indonesia. The utilization of electronic transactions has directly contributed to the increase in state revenue from non-tax sector, particularly in the telecommunications sector. This can be observed through the continuous growth of non-tax revenue achieved by the Ministry of Communication and Informatics, surpassing the set targets each year in terms of realized value. The objective of this research is to analyze the effectiveness, challenges, and impacts of electronic transactions in increasing non-tax state revenue, in order to generate policy recommendations in Indonesia. This study uses a normative juridical method, analyzing positive legal provisions. Data sources were obtained from three types of legal materials, and data collection was conducted both online and offline. The research results indicate that the utilization of electronic transactions can increase non-tax state revenue in the telecommunications sector through various forms such as telecommunications bill payments, e-commerce transactions, sales of prepaid credit and data packages, telecommunications devices, digital services, content delivery, and transaction monitoring and oversight.

Introduction: Chatbots are increasingly utilized in education, offering real-time, personalized communication. While research has explored technical aspects of chatbots, user experience remains under-investigated. This study examines a model for evaluating user experience and satisfaction with chatbots in higher education. Methodology: A four-factor model (information quality, system quality, chatbot experience, user satisfaction) was proposed based on prior research. An alternative two-factor model emerged through exploratory factor analysis, focusing on “Chatbot Response Quality” and “User Experience and Satisfaction with the Chatbot.” Surveys were distributed to students and faculty at a university in Ecuador to collect data. Confirmatory factor analysis validated both models. Results: The two-factor model explained a significantly greater proportion of the data’s variance (55.2%) compared to the four-factor model (46.4%). Conclusion: This study suggests that a simpler model focusing on chatbot response quality and user experience is more effective for evaluating chatbots in education. Future research can explore methods to optimize these factors and improve the learning experience for students.