This research focuses on addressing critical driving safety issues on university campuses, particularly vehicular congestion, inadequate parking, and hazards arising from the interaction between vehicles and pedestrians. These challenges are common across campuses and demand effective solutions to ensure safe and efficient mobility. To address these issues, the study developed detailed microsimulation models tailored to the Victor Levi Sasso campus of the Technological University of Panama. The primary function of these models is to evaluate the effectiveness of various safety interventions, such as speed reducers and parking reorganization, by simulating their impact on traffic flow and accident risk. The models provide calculations of traffic parameters, including speed and travel time, under different safety scenarios, allowing for a comprehensive assessment of potential improvements. The results demonstrate that the proposed measures significantly enhance safety and traffic efficiency, proving the model’s effectiveness in optimizing campus mobility. Although the model is designed to tackle specific safety concerns, it also offers broader applicability for addressing general driving safety issues on university campuses. This versatility makes it a valuable tool for campus planners and administrators seeking to create safer and more efficient traffic environments. Future research could expand the model’s application to include a wider range of safety concerns, further enhancing its utility in promoting safer campus mobility.

Purpose: Kindergartens are an important educational environment for the development of children at an early age, and they also play a crucial role in developing the values of sustainable development. The purpose of this study is to investigate kindergarten teachers’ perceptions of observable and sustainable development practices. Design, methodology, approach: Semi-structured interviews were conducted with 302 Saudi kindergarten teachers. Additionally, observation cards were utilized to collect data on actual practices of sustainable development in kindergartens. Data were analyzed using Nvivo12, a qualitative data analysis software, and descriptive analysis methods. The main themes were produced first, and then the perspectives were organized around them. Finding: The impact of social and cultural factors on the development of values, the lack of resources available to implement educational activities, and teacher awareness and training gaps were found to be the main barriers to the development of sustainable development values in kindergartens. Originality, value: To the best of the author’s knowledge, this is the first study in Saudi Arabia that has looked into the environmental and social perceptions of early childhood teachers about sustainable development practices, so the study’s findings can highlight the importance of reorienting teacher education programs toward sustainability in order to bridge knowledge and practice gaps.

The rapid advancement of artificial intelligence (AI) technology is profoundly transforming the information ecosystem, reshaping the ways in which information is produced, distributed, and consumed. This study explores the impact of AI on the information environment, examining the challenges and opportunities for sustainable development in the age of AI. The research is motivated by the need to address the growing concerns about the reliability and sustainability of the information ecosystem in the face of AI-driven changes. Through a comprehensive analysis of the current AI landscape, including a review of existing literature and case studies, the study diagnoses the social implications of AI-driven changes in information ecosystems. The findings reveal a complex interplay between technological innovation and social responsibility, highlighting the need for collaborative governance strategies to navigate the tensions between the benefits and risks of AI. The study contributes to the growing discourse on AI governance by proposing a multi-stakeholder framework that emphasizes the importance of inclusive participation, transparency, and accountability in shaping the future of information. The research offers actionable insights for policymakers, industry leaders, and civil society organizations seeking to foster a trustworthy and inclusive information environment in the era of AI, while harnessing the potential of AI-driven innovations for sustainable development.

One of the core problems in soil erosion research is the estimation of soil erosion. It is a feasible method and technical approach to estimate soil erosion in Loess Plateau region by using USLE model, GIS and RS technology and using DEM data, meteorological data and land-use type data. With the support of GIS and RS technology, the USLE factors and soil erosion in Loess Plateau region were estimated, and the soil erosion intensity was classified according to the Chinese soil erosion intensity classification standard. The results can provide reference for the development of soil erosion control measures in the Loess Plateau.

This research study was undertaken to complete a comparative study of the seminal work conducted by Anderson and Ruderman on procedural and distributive justice systems versus unionization. This research was conducted in 2023. The main focus of this research effort was to determine if current U.S. organizations were utilizing any form of justice system in protecting employees’ rights and providing processes that would prevent employees from having a desire to join a union for its protections. Parts of the original survey used by Anderson and Ruderman were used in this study to address the research questions and hypotheses posed for this study. A statistical analysis of the data was conducted, and the results indicated employees have a need for protection in their employment relationship. It is suggested that procedural and distributive justice systems be implemented as an alternative to unionization of employees to meet these employee protections.

While the rapid development of artificial intelligence has affected people's daily lives, it has also brought huge challenges to high school mathematics teaching, such as restructuring the classroom teaching structure, transforming the role of teachers, and selecting classroom teaching methods. Based on this, the article explores the application strategies of AI technology in improving knowledge introduction, improving mathematics classroom efficiency and stimulating students' learning interest, with a view to optimizing classroom teaching links, improving students' core discipline quality, and promoting the development of high school mathematics teaching informatization.