This paper aims to advance the knowledge in the domain of youth entrepreneurship and empowerment in the United Arab Emirates (UAE). The rationale is to address the gap in knowledge on entrepreneurship and youth empowerment in the UAE by analyzing strategies and initiatives that support empowering millennials to achieve sustainable development, with the aim of promoting youth entrepreneurship and supporting sustainable economic development. The primary research question guiding this study is: “What strategies and initiatives in the UAE foster the empowerment of the millennial generation for sustainable development?” This study relies on a mixed methodology that combines a descriptive approach, content analysis, and data meta-analysis, with the aim of exploring the relationship between youth entrepreneurship and sustainable development in the United Arab Emirates. with a focus on the future sustainability leaders (FSL) program. While the FSL program demonstrates its significance in promoting youth entrepreneurship and empowerment, it also reveals certain limitations in its design and implementation that may hinder sustainable economic development. To address these challenges and support youth entrepreneurship, the paper proposes three essential action-oriented approaches: promoting participatory diversity and engagement, managing entrepreneurship drivers, and ensuring access to essential support mechanisms. These recommendations are intended to guide multilateral agencies, voluntary sectors, and private entities in the UAE in designing, evaluating, and implementing effective youth entrepreneurship programs. This paper underscores the importance of continued discourse and critical input to refine existing theories and establish a normative framework for youth entrepreneurship and empowerment. Such efforts are crucial for poverty reduction, sustainable development, and the promotion of intergenerational equity.

This study conducts a comprehensive analysis of the aquaculture industry across 11 coastal regions in eastern China from 2017 to 2021 to assess their adaptability and resilience in the face of climate change. Cluster analysis was employed to examine regional variations in aquaculture adaptation by analyzing data on annual average temperatures, annual extreme high/low temperatures, annual average relative humidity, annual sunshine duration, and total yearly precipitation alongside various aquaculture practices. The findings reveal that southern regions, such as Fujian and Guangdong, demonstrate higher adaptability and resilience due to their stable subtropical climates and advanced aquaculture technologies. In contrast, northern regions like Liaoning and Shandong, characterized by more significant climatic fluctuations, exhibit varying degrees of cluster changes, indicating a continuous need to adjust aquaculture strategies to cope with climatic challenges. Additionally, the study explores the specific impacts of climate change on species selection, disease management, and water resource utilization in aquaculture, emphasizing the importance of developing region-specific strategies. Based on these insights, several strategic recommendations are proposed, including promoting species diversification, enhancing disease monitoring and control, improving water quality management techniques, and urging governmental support for policies and technical guidance to enhance the climate resilience and sustainability of the aquaculture sector. These strategies and recommendations aim to assist the aquaculture industry in addressing future climate challenges and fostering long-term sustainable development.

The incorporation of artificial intelligence (AI) into language education has created new opportunities for improving the instruction and acquisition of Chinese characters. Nevertheless, the cognitive difficulties linked to the acquisition of Chinese characters, such as their intricate visual features and lack of clear meaning, necessitate thoughtful deliberation when developing AI-supported learning interventions. The objective of this project is to explore the capacity of a collaborative method between humans and machines in teaching Chinese characters, utilising the advantages of both human expertise and AI technology. We specifically investigate the utilisation of ChatGPT, a substantial language model, for the creation of instructional materials and evaluation methods aimed at teaching Chinese characters to individuals who are not native speakers. The study utilises a mixed-methods approach, which involves both qualitative examination of lesson plans created by ChatGPT and quantitative evaluation of student learning outcomes. The results indicate that the suggested framework for human-machine collaboration can successfully tackle the cognitive difficulties associated with learning Chinese characters, resulting in enhanced learner involvement and performance. Nevertheless, the research also emphasises the constraints of AI-generated material and the significance of human involvement in guaranteeing the accuracy and dependability of educational interventions. This research adds to the expanding collection of literature on AI-assisted language learning and offers practical insights for educators and instructional designers who aim to use AI tools into Chinese language curriculum. The results emphasise the necessity of employing a multi-disciplinary strategy in AI-supported language learning, incorporating knowledge from cognitive psychology, educational technology, and second language acquisition.

This research aims to analyze the strategic role of the Islamic organizations Muhammadiyah and Al-Washliyah in the electoral dynamics of North Sumatra. The background for this study stems from the significant influence these organizations hold in the social, educational, and political spheres of the region, leveraging their extensive membership base and organizational structure. The urgency of this research arises from the need to understand how religious organizations shape political outcomes, which is crucial for developing more inclusive governance strategies. Employing a qualitative descriptive methodology, this study explores how these organizations mobilize support during elections and influence policies through their educational and social programs. Findings reveal that Muhammadiyah and Al-Washliyah effectively utilize mass mobilization and social movement theories to maintain their influence in the political landscape of North Sumatra, subtly navigating and shaping local politics through strategic engagement and advocacy.

In this research, we explore the psychological factors that SMB owners who are micro-entrepreneurs and use SNS for entrepreneurial purposes rely on to make their self-employment decisions. Research-based on a merger of the Technology Acceptance Model (TAM) and the Theory of Planned Behaviour (TPB) deals with how perceived ease of use (PEU), perceived usefulness (PU), attitude, subjective norms (SN), perceived behavioral control (PBC), openness to experience (OTE), and dominance contribute to people’s behavioural intention (BI) to use SNS for Data was collected from 342 SMB micro-entrepreneurs in the Delhi/NCR region of India by the means of a standardized questionnaire. Employing PLS-SEM, a partial least squares structural equation modeling was used to analyze the data. The results point out an impact of PU, attitude, and behavioral intention, and unappealing presentations, unacceptance of an explanation, unclear mechanisms, and domination do not make any difference. The research emphasizes how technophobe’s attitude, and the perception of effectiveness would impact micro-entrepreneurs desire to avail SNS for entrepreneurship efforts. Moreover, research shows the psychological understanding based on the SNS adoption by the small business owners, micro-entrepreneurs as well as for the practitioners and policymakers who are working to enhance the capability of the SMB. More investigations should be conducted on the other personality traits and cover more nations as demographic dividends in comparison to acquire more inclusive data.