Incest is one of the most serious forms of sexual abuse that occurs between a father and his daughter. It involves a parent committing something forbidden to their own child, which violates moral standards. This incestuous relationship has a significant impact on the survivors’ psychology, body, and emotions, affecting all aspects of their lives. This study explores the long-term effects experienced by individuals in Malaysia who have survived father-daughter incest (FDI). This study conducted in-depth interviews with 11 key persons from several agencies involved in handling FDI cases in Malaysia. The findings reveal that those who experienced FDI frequently suffered long-term issues. It is important for everyone involved in assisting these individuals. This is aligned with the global Sustainable Development Goals (SDGs), particularly Goal 3, which emphasises the value of good health and well-being for all. It also aligns with Malaysia’s MADANI concept, which emphasises protecting and promoting everyone’s human rights. FDI survivors can receive the protection and assistance they require to live healthier and more successful lives by implementing an effective strategy that includes mental health support, powerful laws, and community education.

This article analyses the effectiveness of humanitarian assistance in relation to the Sustainable Development Goals (SDGs) in the Minawao refugee camp in Cameroon, focusing on the social pillar of sustainable humanitarian. Established in 2013 to accommodate Nigerians fleeing the violence of Boko Haram, the camp now faces growing challenges related to the sustainability of assistance. Based on a mixed methodological approach, the analysis draws on data collected from humanitarian operators, refugees and the host community. The data was collected using tools such as participant observation, individual and group interviews, questionnaire surveys, mapping, documentary review, etc. Although essential infrastructure has been put in place, the study reveals that minimum humanitarian standards are not being met in several key sectors: food security, education, sanitation, shelter provision and Non Foods Items (NFIs). The lack of financial resources, combined with insufficient involvement by the Cameroonian government, has led to a gradual erosion of social protection for refugees. Maintaining assistance on a temporary basis compromises the integration of the SDGs into humanitarian operations. The article highlights the need for a forward-looking approach by humanitarian agencies, coordination between stakeholders and the involvement of new partners, including refugees, to guarantee their well-being and the achievement of the SDGs.

Lake Batur is one of the national priorities, as it has economic value, and fish resources are used for food security and improving the local people’s welfare. The study examined the applicability of fisheries management status based on the ecosystem approach in lakes. The study was carried out from February to July 2023 using ecosystem approach methods in seven villages around Batur Lake, Bali, Indonesia, Data was collected through observations and interviews with 189 respondents. The success of fisheries management might be shown as a flag model after the composite domain and the total aggregate value of all dominants were rated. The results showed that the managed fish resources and stakeholders were unsatisfactory categories. Generally, social and fishing technology domains were classified as good categories. For that, ecosystem approach applications for sustainable fisheries in Batur Lake needed action under the five common scenario goals (a) reducing non-target fish (red devil) in the lakes by intensive capture and processing into other products of economic value; (b) regulations related to the reserve area as a place for fish to spawn and breed; (c) increasing the synergy of fisheries management policies; (d) increasing the stakeholder capacity; and (e) government support and related stakeholders regarding one regulation for fisheries management.

With the rapid increase in electric bicycle (e-bikes) use, the rate of associated traffic accidents has also escalated. Prior studies have extensively examined e-bike riders’ injury risks, yet there is a limited understanding of how their behavior contributes to these accidents. This study aims to explore the relationship between e-bike riders’ risk-taking behaviors and the incidence of traffic accidents, and to propose targeted safety measures based on these insights. Utilizing a mixed-methods approach, this research integrates quantitative data from traffic accident reports and qualitative observations from naturalistic studies. The study employs a binary logistic regression model to analyze risk factors and uses observational data to substantiate the model findings. The analysis reveals that assertive driving behaviors among e-bike riders, such as running red lights and speeding, significantly contribute to the high rate of accidents. Moreover, the lack of protective gear and inadequate safety training are identified as critical factors increasing the risk of severe injuries. The study concludes that comprehensive policy interventions, including stricter enforcement of traffic laws and mandatory safety training for e-bike riders, are essential to mitigate the risks associated with e-bike use. The findings advocate for an integrated approach to urban traffic management that enhances the safety of all road users, particularly vulnerable e-bike riders.

Resisting the adoption of medical artificial intelligence (AI), it is suggested that this opposition can be overcome by combining AI awareness, AI risks, and responsibility displacement. Through effective integration of public AI dangers and displacement of responsibility, some of these major concerns can be alleviated. The United Kingdom’s National Health Service has adopted the use of chatbots to provide medical advice, whereas heart disease diagnoses can be made by IBM’s Watson. This has the ability to improve healthcare by increasing accuracy, efficiency, and patient outcomes. The resistance may be due to concerns about losing jobs, anxieties about misdiagnosis or medical mistakes, and the consciousness of AI systems drifting more responsibility away from medical professionals. There is hesitancy among healthcare professionals and the general public about the deployment of AI, despite the fact that healthcare is being revolutionised by AI, its uses are pervasive. Participants’ awareness of AI in healthcare, AI risk, resistance to AI, responsibility displacement and ethical considerations were gathered through questionnaires. Descriptive statistics, chi-square tests and correlation analyses were used to establish the relationship between resistance and medical AI. The study’s objective seeks to collect data on primary and public AI awareness, perceptions of risk and feelings of displacement that the professionals have regarding medical AI. Some of these concerns can be resolved when AI awareness is effectively integrated and patients, healthcare providers, as well as the general public are well informed about AI’s potential advantages. Trust is built when, AI related issues such as bias, transparency, and data privacy are critically addressed. Another objective is to develop a seamless integration of risk management, communication and awareness of AI. Lastly to assess how this comprehensive approach has affected hospital settings’ ambitions to use medical AI. Fusing AI awareness, risk management, and effective communication can be used as a comprehensive strategy to address and promote the application of medical AI in hospital settings. An argument made by Chen et al. is that providing training in AI can improve adoption intentions while lowering complexity through the awareness of AI.

This paper aims to explore the relationship between corporate overinvestment and management incentives, focusing particularly on the influence of different ownership structures. Utilizing agency theory and ownership structure theory, this study constructs a theoretical framework and posits hypotheses on how management incentives might influence corporate overinvestment behaviors under different ownership structures. Listed companies from 2010 to 2020 were selected as the research sample, and the hypotheses were empirically tested using descriptive statistics, correlation analysis, and regression analysis. The findings suggest that a relatively concentrated ownership structure may encourage management to adopt more cautious investment strategies, thus reducing overinvestment behaviors; while under a dispersed ownership structure, the relationship between management incentives and overinvestment is more complex. This study provides new evidence on how management incentive mechanisms influence corporate decision-making in different ownership environments, offering significant theoretical and practical implications for improving internal control and incentive mechanisms.