This study provides empirical data on the impact of generative AI in education, with special emphasis on sustainable development goals (SDGs). By conducting a thorough analysis of the relationship between generative AI technologies and educational outcomes, this research fills a critical gap in the literature. The insights offered are valuable for policymakers seeking to leverage new educational technologies to support sustainable development. Using Smart-PLS4, five hypotheses derived from the research questions were tested based on data collected from an E-Questionnaire distributed to academic faculty members and education managers. Of the 311 valid responses, the measurement model assessment confirmed the validity and reliability of the data, while the structural model assessment validated the hypotheses. The study’s findings reveal that New Approaches to Learning Outcome Assessment (NALOA) significantly contribute to achieving SDGs, with a path coefficient of 0.477 (p < 0.001). Similarly, the Use of Generative AI Technologies (UGAIT) has a notable positive impact on SDGs, with a value of 0.221 (p < 0.001). A Paradigm Shift in Education and Educational Process Organization (PSEPQ) also demonstrates a significant, though smaller, effect on SDGs with a coefficient of 0.142 (p = 0.008). However, the Opportunities and Risks of Generative AI in Education (ORGIE) study did not find statistically significant evidence of an impact on SDGs (p = 0.390). These findings highlight the potential opportunities and challenges of using generative AI technologies in education and underscore their key role in advancing sustainable development goals. The study also offers a strategic roadmap for educational institutions, particularly in Oman to harness AI technology in support of sustainable development objectives.

We report a method for effectively and homogeneously incorporating carbon nanotubes (CNTs) in the form of double-wall (DWCNTs) and multi-wall (MWCNTs) structures into commercial paints without the use of additives, surfactants, or chemical processes. The process involves the physical mixing of the nanotubes and polymers using the cavitation energy of an ultrasonic bath. It is a simple, fast method that allows for uniform distribution of carbon nanotube bundles within the polymer for direct application. Due to the hydrophobic properties of the carbon nanotubes as grown, we used paint samples containing 0.3% by mass of both types of CNTs and observed an improvement in waterproofing through wettability and water absorption through immersion tests on the samples. Different solvents such as water, formaldehyde, and glycerin were used, and the results showed an increase in paint impermeability of 30% and 25% with the introduction of DWCNTs and MWCNTs, respectively. This indicates a promising, economically viable, and revolutionary method for applying nanotechnology in the polymer industry.

Micro-mobility has the potential to address first -mile challenges, improving transit accessibility and encouraging public transit usage. However, users’ acceptability of modal integration between various micro-mobility options and public transit remains largely unexplored in the literature. Our study investigates the user behavior for first-mile options, focusing on four alternatives: walking, bicycling, motorcycling, and bus, to access urban mass rapid transit (UMRT) in Hanoi, Vietnam. Based on data collected from 1380 individuals, a Nested Logit Model (NLM) was proposed to analyze the determinants of users’ acceptability under each access mode option as well as evaluate further impacts of shifts in access mode choice on vehicle-kilometer traveled and emissions. The analysis shows that the availability of access modes might increase UMRT use by 47.83%. While this increase further generates additional vehicle-kilometer traveled due to the increase in park-and-ride users, this is offset overall by the large number of motorcycle users shifting to UMRT. Under the most optimistic scenario, modal integration for transit-access trips leads to an average reduction of 17.7% in net vehicle-kilometer traveled or 14.5% in net CO₂ emissions or 10.9% in NO_x from private vehicles. Our findings also imply that the introduction of parking fees for bicycling- or motorcycling-access trips, while impactful, does not significantly change UMRT choice. Therefore, the pricing schemes should be a focus of parking planning surrounding stations. Finally, a number of policy suggestions for parking planning and first-mile vehicles are presented.

The study builds on Deborah Stone’s foundational work exploring the mechanics of causal narratives and their implications for framing problems, assigning responsibility, and guiding policy solutions. The purpose of this research is to unravel the complexities of causal narratives in contemporary politics and understand their profound influence on public policy and society at large. In the digital age, where information is abundant and the traditional gatekeeping role of media has diminished, causal narratives have become increasingly multifaceted. The study aims to explore how these narratives, influenced by the intersections of natural phenomena, human actions, politics, risk, and media, shape public understanding and policy directions. The study employs an extensive review of existing literature, covering works from political science, media studies, and public policy. This includes analyzing seminal texts like Deborah Stone’s “Policy Paradox” and recent studies on media’s evolving role in political discourse. Today’s causal narratives are multifaceted, influenced by a myriad of factors including political agendas, scientific findings, and media portrayals. In conclusion, the research highlights the dynamic nature of causal narratives in the digital age and their significant impact on public policy and societal outcomes. It underscores the need for nuanced understanding and strategic approaches in crafting and interpreting these narratives.

Tomato is one of the major solanaceous vegetables, which has a unique place in the global vegetable market. Instead of being a high-value crop, there is still a need to do improvement in its potential against various biotic and abiotic stressors that adequately demolish its real yield. Alternaria solani (causing early blight disease) is designated as one of the fatal organisms that may reduce tomato crop yield by up to 80%. There were lots of methods, viz., chemical, cultural and biological suggested to overcome it. However, chemical strategies are much in vogue, but they have several negative consequences for human health and the ecosystem. Enlightening this issue, the efficacy of various treatments, viz., chemical fungicides (Amistar Top^®, Nativo^®, and Contaf^®), biochar and fungal bioagent (Trichoderma viride) was assessed under both in vivo and in vitro conditions. Induced resistance is mediated by several regulating pathways, like salicylic acid and jasmonic acid. These mediating pathways manipulate different physiological processes like growth and development, stress tolerance, and defence mechanisms of the plant. The assessment of results revealed that among all treatments biochar at 3.25% by weight consistently displayed remarkable effectiveness against the early blight infection by triggering resistance and improving the overall performance of tomato plants. This result is attributed to improved soil health, fastening mineralization as well as absorption processes, and boosting the plant’s immunity with the use of a higher concentration of biochar. Hence, it could be recommended for the overall improvement of tomato crop and its sustainability.

Lettuce (Lactuca sativa L.) is the main leafy vegetable grown in Brazil. Its productivity and quality are limited by the growing season, the nearby environment and the type of cultivar adopted. The objective of this work was to verify at different times of the year the best planting environment for lettuce cultivation in a semi-humid tropical climate. For this purpose, an experiment was set up in three different seasons (October–November 2014, January–March, May–July 2015). The experimental design was randomized blocks, in a 3 × 3 × 2 factorial arrangement, consisting of three seasons, three cultivars (cvs. Vera^®, Tainá^® and Rafaela^®) and two growing environments (low tunnel with beds protected with mulching consisting of soil protection with plastic fabric covering, and beds without protection or conventional cultivation) and four replicates per treatment. Plant biomass, stem length, head diameter, number of leaves per head and crop productivity were evaluated as response parameters. The results showed that the May–July period favored biomass production, head diameter and productivity. Despite the similarity between varieties, the variety Vera^® is more productive in biomass, number of leaves per head, stem length and productivity. The low tunnel planting system with mulching is adequate under the conditions evaluated for lettuce cultivation. This system in the May–July period favors a superior development in the characteristics biomass, head diameter and productivity, if compared to conventional cultivation during the October–November period.