The new cases of HIV/AIDS are being reported in Indonesia tend to increase. for over two decades, the Indonesian government has issued policies to reduce the number of cases through several ministries and local governments, but the results have not indicated signs of success. Therefore, this research aims to analyze the failure of prevention policies to improve policymaking in the future. It focuses on policy and institutional substance aspects using a qualitative design with documentary analysis approach. The results show that the policy failure in dealing with cases is caused by inappropriate rationalization, medicalization, and weak institutional and regulatory roles. Based on these descriptions, stakeholders are expected to emphasize a multi-perspective and holistic approach and rationalize policy objectives with institutional capacity. Moreover, the government needs to increase public and community involvement, strengthening the role of religious leaders and the media, and increase public literacy regarding HIV/AIDS.

This research explores the advancement of Artificial Intelligence (AI) in Occupational Health and Safety (OHS) across high-risk industries, highlighting its pivotal role in mitigating the global incidence of occupational incidents and diseases, which result in approximately 2.3 million fatalities annually. Traditional OHS practices often fall short in completely preventing workplace incidents, primarily due to limitations in human-operated risk assessments and management. The integration of AI technologies has been instrumental in automating hazardous tasks, enhancing real-time monitoring, and improving decision-making through comprehensive data analysis. Specific AI applications discussed include drones and robots for risky operations, computer vision for environmental monitoring, and predictive analytics to pre-empt potential hazards. Additionally, AI-driven simulations are enhancing training protocols, significantly improving both the safety and efficiency of workers. Various studies supporting the effectiveness of these AI applications indicate marked improvements in risk management and incident prevention. By transitioning from reactive to proactive safety measures, the implementation of AI in OHS represents a transformative approach, aiming to substantially reduce the global burden of occupational injuries and fatalities in high-risk sectors.

This research intends to find out the compliance acts based on the manufacturing industry of Bangladesh and lead to the development of the integrated theory of compliance model. There are several compliance regulations, that are separately dealt with in any manufacturing organization. These compliance regulations are handled at various ends of the organization making the process quite scattered, time-consuming, and tedious. To fix this problem, the integration of organizational compliance regulations is brought under one platform. Researchers have applied the qualitative approach with multiple case studies methodology scrutinizing the in-depth interviews and transcripts. Furthermore, the NVIVO tool has been used to analyze, where the necessary themes of the Organizational Compliance Regulations are found. Therefore, we have proposed a conceptual framework to inaugurate a standalone combined framework, which is an innovative and novel measure.

The linkages between adequate service delivery and sustainable development have been given a little academic attention in the South Africa’s local municipalities. For this reason, the achievement of sustainable development has been difficult which has culminated in the occurrence of service delivery protests. These service delivery protests have posed critical threats to social security thus affecting the possibility to achieve sustainable development in South Africa. the paper findings showed that the delivery of inadequate services to the citizens is triggered by the failure to equally include citizens in the process. One of the threats that the paper found is the fact that these service delivery protests have become a major issue and any move to solve them without citizen participation has been unsuccessful. The paper findings also showed that that the lack of adequate service delivery to the citizens causes human insecurities which in turn affect the achievement of sustainable development. This is because the occurrence of the service delivery protests deteriorates national economic growth and human growth. They affect foreign investors and international tourists by instilling fear in them and yet they are contributors to sustainable economic growth that leads to sustainable development. The findings of this paper also presented that the use of Artificial Intelligence (AI) technologies can increase citizen participation during service delivery. It is through the use of citizen participation that openness, transparency, accountability, and representation principles that promote the delivery of adequate services are possible. The paper found that using AI technologies would also foster trust between the service provider and service receiver needed for delivering adequate services, thus achieve sustainable development in South Africa.

Data literacy is an important skill for students in studying physics. With data literacy, students have the ability to collect, analyze and interpret data as well as construct data-based scientific explanations and reasoning. However, students’ ability to data literacy is still not satisfactory. On the other hand, various learning strategies still provide opportunities to design learning models that are more directed at data literacy skills. For this reason, in this research a physics learning model was developed that is oriented towards physics objects represented in various modes and is called the Object-Oriented Physics Learning (OOPL) Model. The learning model was developed through several stages and based on the results of the validity analysis; it shows that the OOPL model is included in the valid category. The OOPL model fulfils the elements of content validity and construct validity. The validity of the OOPL model and its implications are discussed in detail in the discussion.

This study aims to examine the entrepreneurial activities of 240 women in the districts of Konaseema, East Godavari, and Kakinada during 2021–2022, focusing on the diverse range of 286 enterprises they managed across 69 business types. These enterprises were tailored to local resources and market demands, with coconut wholesale, cattle breeding, and provision shops being the most common. The study also analyzes income distribution, noting that one-third of the women earned between ₹50,000–1,00,000 annually, while only 0.70% earned over ₹5,00,000. More than half of the enterprises served as the primary income source for their families. The research highlights the significant role these women entrepreneurs play in their communities, their job satisfaction derived from financial independence and social empowerment, and the challenges they face, such as limited capital and market access. Finally, the study offers recommendations to empower these women to seize entrepreneurial opportunities and enhance their success.