This study assesses Vietnam’s state-level implementation of artificial intelligence (AI) technology and analyses the government’s efforts to encourage AI implementation by focusing on the National Strategy on AI Development Program. This study emphasizes the possibility of implementing AI at the state level in Vietnam and the importance of conducting continuous reviews and enhancements to achieve sustainable and inclusive AI growth. Impact evaluations were conducted in public organizations alone, and implication evaluations were considered optional. AI impact assessments were constrained by societal norms that necessitated establishing relationships among findings. There is a lack of official information regarding the positive impact of Vietnam’s AI policy on the development of AI infrastructure, research, and talent pools. The study’s findings highlight the necessity of facilitating extensive AI legislation, and strengthening international cooperation. The study concludes with the following recommendations for improving Vietnam’s AI policy: implementing a strong AI governance structure and supporting AI education and awareness.
Urban regeneration and gentrification are complex, interconnected processes that significantly shape cities. However, these phenomena in the Middle East and North Africa (MENA) region are often understudied and typically viewed through a Western lens. This systematic review of literature from 2010 to 2024 addresses this gap by synthesizing a comprehensive framework for understanding urban regeneration-led gentrification in MENA countries. The review delves into key themes: Gentrification contexts, the regeneration process, gentrification accelerators, and the aftermath of gentrification. It explores the diverse motives behind urban regeneration, identifies key stakeholders, and analyzes catalysts of gentrification. Findings reveal that informal areas and deteriorated heritage sites in major cities are most susceptible to gentrification. The study also highlights the critical issue of insufficient community participation and proposes a participation evaluation framework. The unique socioeconomic and political factors driving gentrification in the MENA region underscore the necessity of context-specific approaches, facilitating the identification of regional similarities and differences. Conclusively, the review asserts that gentrification is a cyclic process, necessitating core interventions through enhanced regeneration strategies or displacement plans to mitigate its effects.
This study investigates the impact of various educational and social factors on the digital skills of vocational education and training (VET) students, emphasizing the significance of continuous skill development in the digital age. Utilizing structural equation modeling (SEM), the paper analyzes data from 382 adult VET students in Greece, examining the effects of Erasmus program participation, daily computer use, educational platforms, and social network engagement on digital competencies. The findings reveal that participation in Erasmus programs and the use of educational platforms significantly enhance students’ digital skills, highlighting the value of international experiences and digital learning tools in VET. Conversely, daily computer use alone does not significantly impact digital skills, suggesting that structured and purposeful digital tool integration is essential for skill development. The study also underscores the positive role of social networks in improving content management skills, advocating for their strategic use in educational settings. These results demonstrate the need for targeted digital literacy initiatives within VET programs to prepare students for modern labor market demands. The research contributes to the theoretical understanding of digital skill acquisition and offers practical insights for educators and policymakers to enhance VET curricula, fostering economic and social progress through improved digital literacy.
Recently, there has been a burgeoning fascination with the influence of urban green spaces (UGS) on physical activity (PA) and health. This interest has been accompanied by a mounting body of evidence that establishes a connection between UGS and residents’ PA levels. Numerous studies have been conducted to investigate the significance of UGS and have generally agreed on their connection with health. However, there is still considerable variation in viewpoints regarding the intermediate factors contributing to this association. The primary objective of this study was to investigate the potential correlation between different qualitative factors of UGS and PA. The study involved the collection of data from four parks located in Edinburgh. Four trained observers utilised the Environmental Assessment of Public Recreational Spaces (EARPS Mini) tool to code various environmental characteristics. Additionally, the Method for Observing Physical Activity and Wellbeing (MOHAWk) observation tool was employed to code instances of on-site incivility and the characteristics and behaviours of residents engaging in UGS activities. The results of this study show that the facilities and environment, area and socioeconomic status (SES) of UGS positively affect the type of PA and the level of PA, as well as influence residents’ attentiveness to the environment and their interactions with each other. Demographics such as gender and age group are also significantly related to the level and type of PA. Significant differences in the level and type of PA, and race only differed significantly in the choice of activity type. These results suggest that the quality of the UGS environment affects the level, type, and status of PA among residents and that resident characteristics also have an impact. Future research suggests increasing data collection related to PA frequency and PA duration and considering longitudinal observations over time for refinement.
To achieve the Paris Agreement's temperature goal, greenhouse gas emissions should be reduced as soon as, and by as much, as possible. By mid-century, CO2 emissions would need to be cut to zero, and total greenhouse gases would need to be net zero just after mid-century. Achieving carbon neutrality is impossible without carbon dioxide removal from the atmosphere through afforestation/reforestation. It is necessary to ensure carbon storage for a period of 100 years or more. The study focuses on the theoretical feasibility of an integrated climate project involving carbon storage, emissions reduction and sequestration through the systemic implementation of plantation forestry of fast-growing eucalyptus species in Brazil, the production of long-life wood building materials and their deposition. The project defines two performance indicators: a) emission reduction units; and b) financial costs. We identified the baseline scenarios for each stage of the potential climate project and developed different trajectory options for the project scenario. Possible negative environmental and reputational effects as well as leakages outside of the project design were considered. Over 7 years of the plantation life cycle, the total CO2 sequestration is expected to reach 403 tCO2∙ha−1. As a part of the project, we proposed to recycle or deposit for a long term the most part of the unused wood residues that account for 30% of total phytomass. The full project cycle can ensure that up to 95% of the carbon emissions from the grown wood will be sustainably avoided.
This study aims to use dialectical thinking to explore the impacts and responses of Artificial Intelligence (AI) empowerment on students’ personalized learning. The effect of AI empowerment on student personalization is dissected through a literature review and empirical cases. The study finds that AI plays a significant role in promoting personalized learning by enhancing students’ learning effectiveness through intelligent recommendation, automated feedback, improving students’ independent learning ability, and optimizing learning paths, however, the wide application of AI also brings problems such as technological dependence, cheating in exams, weakening of critical thinking ability, educational fairness, and data privacy protection to students. The study proposes recommendations to strengthen technology regulation, enhance the synergy between teachers and AI, and optimize the personalized learning model. AI-enabled personalized learning is expected to play a greater role in improving learning efficiency and educational fairness.
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