The aim of this paper is to introduce a research project dedicated to identifying gaps in green skills by using the labor market intelligence. Labor Market Intelligence (LMI). The method is primarily descriptive and conceptual, as the authors of this paper intend to develop a theoretical background and justify the planned research using Natural Language Processing (NLP) techniques. This research highlights the role of LMI as a tool for analysis of the green skills gaps and related imbalances. Due to the growing demand for eco-friendly solutions, there arises a need for the identification of green skills. As societies shift towards eco-friendly economic models, changes lead to emerging skill gaps. This study provides an alternative approach for identification of these gaps based on analysis of online job vacancies and online profiles of job seekers. These gaps are contextualized within roles that businesses find difficult to fill due to a lack of requisite green skills. The idea of skill intelligence is to blend various sources of information in order to overcome the information gap related to the identification of supply side factors, demand side factors and their interactions. The outcomes emphasize the urgency of policy interventions, especially in anticipating roles emerging from the green transition, necessitating educational reforms. As the green movement redefines the economy, proactive strategies to bridge green skill gaps are essential. This research offers a blueprint for policymakers and educators to bolster the workforce in readiness for a sustainable future. This article proposes a solution to the quantitative and qualitative mismatches in the green labor market.

This study conducts a systematic review to explore the applications of Artificial Intelligence (AI) in mobile learning to support indigenous communities in Malaysia. It also examines the AI techniques used more broadly in education. The main objectives of this research are to investigate the role of Artificial Intelligence (AI) in support the mobile learning and education and provide a taxonomy that shows the stages of process that used in this research and presents the main AI applications that used in mobile learning and education. To identify relevant studies, four reputable databases—ScienceDirect, Web of Science, IEEE Xplore, and Scopus—were systematically searched using predetermined inclusion/exclusion criteria. This screening process resulted in 50 studies which were further classified into groups: AI Technologies (19 studies), Machine Learning (11), Deep Learning (8), Chatbots/ChatGPT/WeChat (4), and Other (8). The results were analyzed taxonomically to provide a structured framework for understanding the diverse applications of AI in mobile learning and education. This review summarizes current research and organizes it into a taxonomy that reveals trends and techniques in using AI to support mobile learning, particularly for indigenous groups in Malaysia.

Phytochemical and antioxidant analysis of some varieties of Capsicum was evaluated. Mature Capsicum varieties were collected across the State. The seeds were removed, sun-dried for 3 days, stored for 2 weeks at 15 ºC–25 ºC in polythene bags before planting. Saponins, tannins, flavonoids, alkaloids and cardiac glycosides were present in abundant, moderate and trace amounts. Combined anthraquinones were absent in all varieties. Yellow (0.810 ± 0.0006 µg/mL), red long dry (0.211 ± 0.0006 µg/mL) and round peppers (2.527 ± 0.0003 µg/mL) had the largest values for total phenol, flavonoids and tannins. Shombo and yellow peppers had the largest (0.270 ± 0.002 µg/mL) and least (0.102 ± 0.001 µg/mL) capsaicin content. The antioxidant activities varied across the varieties. At 100 µg/mL of methanol, yellow (45%) and round peppers (45%) had largest mean absorbances for 2,2-Diphenyl-1-Picrylhydrazyl (DPPH) Radical Scavenging Activity while sub-shombo pepper (23%) had the least. For Ferric Reducing Antioxidant Power (FRAP), yellow (0.63 ± 0.001 µg/mL) and sub-shombo peppers (0.55 ± 0.001µg/mL) had the largest and least values at 100 µg/mL of methanol. At 100 µg/mL of methanol, red long dry (0.112 ± 0.001) and shombo peppers (0.101 ± 0.001) had the largest and least values for the nitric oxide scavenging activity. This study shows that Capsicum varieties exhibit bioactive componds similarities and variations with implications in hybridization, taxonomy and conservation.

This study aims to explore the research on Chinese higher education policy from 2005 to 2024 through a bibliometric analysis. It is revealed that a continuous growth trend and sustained academic interest in this field. Mainland China leads in publication quantity, showcasing the active involvement of Chinese scholars in higher education policy research. Institutions like Peking University, the University of Hong Kong, and Beijing Normal University play significant roles in this research domain. The focus of research has shifted from student attitudes to international students, teachers, innovation models, changing demands, and urban education development, reflecting a growing emphasis on sustainability and internationalization. The study highlights the positive development trajectory of Chinese higher education policy research, with expanding research focuses and deepening concerns for sustainability and internationalization.

The development and expansion of economies depend heavily on entrepreneurship, and Malaysia is no exception. Understanding the underlying elements that impact the success or failure of user adoption behaviour of online shopping activities is significant since entrepreneurship is critical in driving economic growth and innovation. The study includes 73 articles published from 2004 to the last of 2023 from Science Direct, Scopus, Google Scholar, and Web of Science. We utilised qualitative methods and systematic review issues through the findings of “qualitative” studies as the last step inside a systematic review using Nvivo14. Our study’s result illustrated that applying the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) in Malaysian e-commerce validates the relevance of established theoretical frameworks. This study explores the relationship between 20 independent variables and five mediator factors, with dependent variables, e-commerce in Malaysia. The results highlight the intricate relationships between these variables and their importance for companies, decision-makers, and other stakeholders involved in Malaysian infrastructure financing. This review provides legislators, educators, researchers, and businesspeople with new knowledge in Malaysia so that decision-makers, investors, and aspiring entrepreneurs can make informed decisions.

The integration of Big Earth Data and Artificial Intelligence (AI) has revolutionized geological and mineral mapping by delivering enhanced accuracy, efficiency, and scalability in analyzing large-scale remote sensing datasets. This study appraisals the application of advanced AI techniques, including machine learning and deep learning models such as Convolutional Neural Networks (CNNs), to multispectral and hyperspectral data for the identification and classification of geological formations and mineral deposits. The manuscript provides a critical analysis of AI's capabilities, emphasizing its current significance and potential as demonstrated by organizations like NASA in managing complex geospatial datasets. A detailed examination of selected AI methodologies, criteria for case selection, and ethical and social impacts enriches the discussion, addressing gaps in the responsible application of AI in geosciences. The findings highlight notable improvements in detecting complex spatial patterns and subtle spectral signatures, advancing the generation of precise geological maps. Quantitative analyses compare AI-driven approaches with traditional techniques, underscoring their superiority in performance metrics such as accuracy and computational efficiency. The study also proposes solutions to challenges such as data quality, model transparency, and computational demands. By integrating enhanced visual aids and practical case studies, the research underscores its innovations in algorithmic breakthroughs and geospatial data integration. These contributions advance the growing body of knowledge in Big Earth Data and geosciences, setting a foundation for responsible, equitable, and impactful future applications of AI in geological and mineral mapping.