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.

Plant growth-promoting rhizobacteria (PGPR) offer eco-friendly alternatives to chemical fertilizers, promoting sustainable agriculture by enhancing soil fertility, reducing pathogens, and aiding in stress resistance. In agriculture, they play a crucial role in plant growth promotion through the production of agroactive compounds and extracellular enzymes to promote plant health and protection against phytopathogens. In the rhizosphere, diverse microbial interactions, including those with bacteria and fungi, influence plant health by production of antimicrobial compounds. The antagonism displayed by rhizobacteria plays a crucial role in shaping microbial communities and has potential applications in developing a natural and environmentally friendly approach to pest control. The rhizospheric microbes showcase their ecological importance and potential for biotechnological applications in the context of plant-microbe interactions. The extracellular enzymes produced by rhizospheric microbes like amylases, chitinases, glucanases, cellulases, proteases, and ACC deaminase contribute to plant processes and stress response emphasizing their importance in sustainable agriculture. Moreover, this review highlights the new paradigm including artificial intelligence (AI) in sustainable horticulture and agriculture as a harmonious interaction between ecological networks for promoting soil health and microbial diversity that leads to a more robust and self-regulating agricultural system for protecting the environment in the future. Overall, this review emphasizes microbial interactions and the role of rhizospheric microbial extracellular enzymes which is crucial for developing eco-friendly approaches to enhance crop production and soil health.

This study uses the opening of the new Mass Rapid Transit (MRT) in stages between 2010 and 2012 in Singapore as the exogenous event to empirically test the impact of the new Circle Line (CL) on housing wealth. Applying a "differences-in-differences" approach to the non-landed private housing transaction data covering the period from 2009 to 2013, we find that the average housing prices increase by 1.6% in the post-opening of the CL. We find significant capitalization of the new CL into housing prices, especially households living within a 400-meter radius (the treatment zone) from the closest MRT stations on the CL. The treatment effects that are measured by the "marginal willingness to pay" for houses located within the treatment zone is 13.2% relative to houses located outside the treatment zone. The new CL opening creates an estimated S$1.23 billion housing wealth effects for households living in close proximity to the CL MRT stations. However, we do not find significant "anticipative" effects on house prices in the six-month window prior to the opening of CL. The strongest treatment effect is found after the opening of the phase 1 of CL, and the treatment intensity declines in phases 2 and 3 of the CL opening.

The present study, developed under a quantitative approach, explanatory scope and causal correlational design, aims to determine the influence of invisible learning on the research competence of high school students in two private schools in the city of Lima, Peru, whose educational models seek to develop autonomous learning and research through discovery learning and experimentation. Two questionnaires were applied to 120 students of the VII cycle of basic education, one to measure the perception regarding invisible learning with 20 items and the other to measure investigative competencies with 21 items; both instruments underwent the corresponding validity and reliability tests before their application. Among the main findings, descriptive results were obtained at a medium level for both variables, the correlations found were significant and moderate, and as for influence, the coefficient of determination R² yielded a value of 0.13, suggesting that 13% of investigative competence is predicted by invisible learning. These results show that autonomy, the use of digital technologies, metacognition and other aspects that are part of invisible learning prepare students to solve problems of varying complexity, allowing them to face the challenges of contemporary knowledge in an innovative and effective manner.

The Urabá region, known for its banana production, faces significant challenges due to seasonal droughts that affect crop productivity. The implementation of innovative technologies, such as efficient irrigation systems, is presented as a potential solution to improve the sustainability and profitability of plantations. This study validates the implementation of an irrigation system in a banana (Musa spp.) plantation located in the region of Urabá, in order to meet the water needs of the crop during periods of drought. A case study was carried out in a banana plantation in the region of Urabá, considering the maximum and minimum monthly losses due to drought, and a random sample was used to measure the weight before and after the implementation of the irrigation system, in order to carry out an economic analysis. The study shows that the implementation of a sprinkler irrigation system increases the average weight of the harvested bunches by 20%, which is reflected in an annual increase of 30.3% of exported boxes, obtaining satisfactory results in terms of internal rate of return, cost-benefit ratio and return on investment. The implementation of irrigation systems makes it possible to increase competitiveness in international markets, especially in regions such as Urabá, where the use of these technologies is still incipient.