Maps of forest stand condition—the current phase of the forest-forming process—will be useful for foresters in their forest management in addition to the forest planning and cartographic materials. The mapping methodology was applied in the test area of the Bolshemurtinsky forest district of the Krasnoyarsk region, which is typical for the southern taiga forests of East Siberia. Source data for mapping was obtained on the basis of descriptions of the forest subcompartments on the GIS attribute table of the forest district. Forest stand confinement to the terrain relief indicators was identified on the basis of the SRTM 55-01 digital terrain model data. Spatial analysis has been performed using the ArcGIS Spatial Analyst module. Mapping capability has been shown not only for the year of forest inventory but also for the earlier period of time. To determine the predominant species and the age of the 100-year-old forest stand, a scheme was proposed in which the conceivable options are typified depending on the succession trend, the forest stand age prior to disturbance, and the period of reforestation. Map fragments of the test area as of 2006—the year of forest inventory—and as of 1906—the year of the intensive colonization beginning in southern Siberia—are demonstrated. Maps of forest condition in the test area represent successions that are typical in the southern taiga forests of Siberia: post-harvest, pyrogenic, and biogenic. The methodology of forest condition mapping is universal.

This comprehensive review examines recent innovations in green technology and their impact on environmental sustainability. The study analyzes advancements in renewable energy, sustainable transportation, waste management, and green building practices. To accomplish the specific objectives of the current study, the exploration was conducted using the PRISMA guidelines in major academic databases, such as Web of Science, Scopus, IEEE Xplore, and ScienceDirect. Through a systematic literature review with a research influence mapping technique, we identified key trends, challenges, and future directions in green technology. Our aggregate findings suggest that while significant progress has been made in reducing environmental impact, barriers such as high initial costs and technological limitations persist. Hence, for the well-being of societal communities, green technology innovations and practices should be adopted more widely. By investing in sustainable practices, communities can reduce environmental degradation, improve public health, and create resilient infrastructures that support both ecological and economic stability. Green technologies, such as renewable energy sources, eco-friendly construction, efficient waste management systems, and sustainable agriculture, not only mitigate pollution but also lower greenhouse gas emissions, thereby combating climate change. Finally, the paper concludes with recommendations for policymakers and industry leaders to foster the widespread adoption of green technologies.

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.

This study explores the impact of technological innovations on audit transparency, objectivity, and assurance. The study employs a systematic literature review methodology, analyzing a wide range of scholarly articles, research papers, and reports to synthesize the findings. The methodology involved identifying keywords, conducting comprehensive searches in academic databases, and evaluating the selected literature. The study identifies key themes on how technological innovations impact audit practices through analysis of the literature. The impacts of technology include enhanced audit transparency through improved documentation capabilities, real-time reporting, and increased stakeholder engagement. Technological advancements bolster audit objectivity by automating repetitive tasks, facilitating advanced data analysis, and promoting standardized audit procedures. However, the analysis highlighted challenges associated with the use of technology in audits including complex technology implementation and the potential for biases. This research study contributes to the existing body of knowledge by consolidating relevant research and insights on the subject matter.

The construction industry is a significant contributor towards global environmental degradation and resource depletion, with developing economies facing unique challenges in adopting sustainable construction practices. This systematic review aims to investigate the gap in sustainable construction implementation among global counterparts. The study utilizes the P5 (People, Planet, Prosperity, Process, Products) Standard as a framework for evaluating sustainable construction project management based on environmental, social, and economic targets. A Systematic Literature Review from a pool of 994 Sustainable Construction Project Management (SCPM) papers is conducted utilizing the PRISMA methodology. Through rigorous Identification, Screening, and Eligibility Verification, an analysis is synthesized from 44 relevant literature discussing SCPM Implementations worldwide. The results highlight significant challenges in three main categories: environmental, social, and economic impacts. Social impacts are found as the most extensively researched, while environmental and economic impacts are less studied. Further analysis reveals that social impacts are a major concern in sustainable construction, with numerous studies addressing labor practices and societal well-being. However, there is a notable gap in research on human rights within the construction industry. Environmental impacts, such as resource utilization, energy consumption, and pollution, are less frequently addressed, indicating a need for more focused studies in these areas. Economic impacts, including local economic impact and business agility, are further substantially underrepresented in the literature, suggesting that economic viability is a critical yet underexplored aspect of sustainable construction. The findings underscore the need for further research in these areas to address the implementation challenges of sustainable project management effectively. This research contributes towards the overall research of global sustainable construction through the utilization of the P5 Standards as a new lens of determining sustainability performance for construction projects worldwide.

Boron and tungsten carbides, B₄C and WC, are hard materials widely used in modern technologies. Further improvement of their performance characteristics involves the development of new B₄C and WC-based and/or related composites in a nanodispersed state. This article provides a review of available literature research on B-C-W systems, which would be useful in future studies in this direction.