The Bini people of Edo State, located in the Edo South senatorial district, have been the focus of a study investigating the impact of international migration on Nigerian infrastructure. The study employed a descriptive-qualitative approach, using a survey research methodology and structured questionnaires to gather data from 401 respondents. The study used regression and thematic analysis to examine the collected data, focusing on the connection between migration and the advancement of infrastructure. The findings suggest that low incomes, job insecurity, and the development of domestic infrastructure contribute to the momentum behind international migration movements. The study suggests that remittances from migrants and investments are needed to alleviate the situation, highlighting the need for a more inclusive and sustainable approach to addressing the challenges faced by the Bini people in Edo State.

The impact of crude oil price fluctuations on the real effective exchange rate (REER) has been widely debated, but specific evidence, particularly for developing countries in Southeast Asia, is scarce and inconclusive. This issue, especially concerning both short- and long-term relationships, remains inadequately addressed, affecting these countries for risk management related to oil price fluctuations. This study aims to fill this gap by examining these relationships in Thailand context to provide more evidence on how the REER in Southeast Asia responds to changes in crude oil prices. Monthly data of crude oil prices in Dubai market and the Thai baht REER from 2000 to 2019 were employed. Johansen co-integration test and Vector Error Correction Model (VECM) were used for analyzing long-term and short-term relationships, respectively. The results indicate a significant negative long-term relationship between crude oil prices and the REER, with a 0.31% reduction in the REER for every 1% increase in the real price of oil. However, in the short term, VECM analysis reveals significant movements in the REER in response to external shocks. On average from 2000–2019, the significant fluctuations in the REER are quickly alleviated and adjusted to its long-run equilibrium, typically by 2% in the following month following external shocks such as crude oil price fluctuations. Given these findings, which highlight the long-term relationship between the REER and crude oil prices and its short-term adjustment, it is suggested that when there is a shock from the crude oil prices, the government can strengthen short-term oil price controls or monetary subsidies to mitigate the extensive repercussions of energy market fluctuations, as such interventions would have a lesser impact on the long-term equilibrium of the REER.

The R3A Route represents a collaborative initiative involving the governments of Thailand, Laos, and China aimed at bolstering connectivity along the North-South Economic Corridor, as a vital component of the Greater Mekong Subregion Economic Cooperation Program (GMS). Since its inception in 2008, this endeavor has substantially enhanced the logistical framework between Thailand, Laos, and China. However, it has also revealed an imbalance in the benefit distribution of value chains within the tourism industry. One of the fact that, local stakeholders in each country often leverage their home country’s advantages, leading to the exploitation of counterparts with lower capacity in other nations. This unfair utilization goes against the initial intentions of fostering collaboration among these countries. Given China and its development as a starting point for tourism and its popularity among tourists traveling this route, this study provides a comprehensive analysis of China’s policy and insights of its influences on R3A tourism development in Laos and Thailand. The study constructs a content analysis with an umbrella of stakeholder analysis based on reliable data and is cross-verified through data triangulation. The findings lead to recommendations aimed at making Thai-Lao-Chinese tourism cooperation more sustainable and effective.

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.