The study is devoted to the problem of processing the organic waste that is generated as a result of paper, textiles and other industries production as well as food waste. The growth of economic activity in Kazakhstan has resulted in a significant challenge with regard to industrial waste management. The accumulation of waste on the territory of the country has reached 31.72 billion tonnes, comprising approximately 2.5 billion tonnes of hazardous waste, 50 million tonnes of phosphorus-containing waste, over 2.5 million tonnes of lead-zinc waste and more than 120 million tonnes of solid domestic waste. The study object was the Shymkent-Kokys polygons. According to the research carried out, it was determined that the titer of microorganisms of the studied groups is 1–10 CFU/g in the soils selected around the garbage in the area of the Shymkent landfill. The titer of microorganisms in the soil horizons was high at a depth of 20–30 cm and the titer were 10⁹ cells/mL. The structure of the soil microbiome obtained around the Shymkent Waste Landfill consists of actinomycetes, micromycetes, heterotrophic bacteria, nitrifying, nitrogen-fixing bacteria, enterobacteria, as well as algae and protozoa. It was found that strains KPA1, KPA2 Pseudomonas sp. strains KPA3, KPA4, KPA5 Bacillus sp. isolated from the soils of the Shymkent-Kokys landfill are able to recycle domestic waste with a high content of cellulose and organic substances up to 95%–97%. The findings can be used to develop more effective organic cellulosic waste management strategies and improve the environmental sustainability of various industries.

The low-carbon economy is the major objective of China’s economy, and its goal is to achieve sustainable economic development. The study enriches the literature on the relationship between digital Chinese yuan (E-CNY), low-carbon economy, AI trust concerns, and security intrusion. The rapid growth of Artificial Intelligence (AI) offered more ways to achieve a low-carbon economy. The digital Chinese yuan (E-CNY), based on the AI technique, has shown its nature and valid low-carbon characteristics in pilot cities of China, it will assume important responsibilities and become the key link. However, trust concerns about AI techniques result in a limitation of the scope and extent of E-CNY usage. The study conducts in-depth research from the perspective of AI trust concerns, explores the influence of E-CNY on the low-carbon economy, and discusses the moderating and mediating mechanisms of AI trust concerns in this process. The empirical data results showed that E-CNY positively affects China’s low-carbon economy, and AI trust concerns moderate the positive impact. When consumers with higher AI trust concerns use E-CNY, their feeling of security intrusion is also higher. It affects the growth of trading volume and scope of E-CNY usage. Still, it reduces the utility of China’s low-carbon economy. This study provides valuable management inspiration for China’s low-carbon economy.

The construction of gas plants often experiences delays caused by various factors, which can lead to significant financial and operational losses. This research aims to develop an accurate risk model to improve the schedule performance of gas plant projects. The model uses Quantitative Risk Analysis (QRA) and Monte Carlo simulation methods to identify and measure the risks that most significantly impact project schedule performance. A comprehensive literature review was conducted to identify the risk variables that may cause delays. The risk model, pre-simulation modeling, result analysis, and expert validation were all developed using a Focused Group Discussion (FGD). Primavera Risk Analysis (PRA) software was used to perform Monte Carlo simulations. The simulation output provides information on probability distribution, histograms, descriptive statistics, sensitivity analysis, and graphical results that aid in better understanding and decision-making regarding project risks. The research results show that the simulated project completion timeline after mitigation suggested an acceleration of 61–65 days compared to the findings of the baseline simulation. This demonstrates that activity-based mitigation has a major influence on improving schedule performance. This research makes a significant contribution to addressing project delay issues by introducing an innovative and effective risk model. The model empowers project teams to proactively identify, measure, and mitigate risks, thereby improving project schedule performance and delivering more successful projects.

The rapid increase in the aging population has raised significant concerns about the living conditions and well-being of elderly residents in old communities. This study addresses these concerns by proposing a Sustainable Urban Renovation Assessment Model (SURAM) specifically designed to enhance elderly-friendly environments in Chongqing City. The model encompasses multiple dimensions, including the comfort of public facilities, service safety and convenience, medical travel services, infrastructure security, life service convenience, neighbor relations, ambulance aid accessibility, commercial service facilities, privacy protection, elderly care facilities and service supply, and medical and health facilities. By employing factor analysis, the study reduces the dimensionality of the 49 indicator factors, allowing for a more focused and comprehensive evaluation of the effectiveness of aging-friendly renovation efforts. The main factors identified in the proposed model include community infrastructure security, elderly comfort of community public facilities, completeness and convenience of surrounding living services, and security and convenience of elderly care services. The results reveal that the age-appropriate comfort of public facilities plays a significant role in achieving successful aging-appropriate renovation outcomes. The findings demonstrate that by addressing specific needs such as safety, accessibility, and convenience, communities can significantly improve the quality of life for elderly residents. Moreover, the application of SURAM provides actionable insights for policymakers, urban planners, and community stakeholders, guiding them in implementing targeted initiatives for sustainable and inclusive urban development.

Purpose: This research aims to examine the influence of intellectual capital disclosure and the geographical location of universities on the sustainability of higher education institutions in Southeast Asia. Design/methodology/approach: This research is quantitative and uses secondary data obtained through the annual reports of universities that have the Universitas Indonesia Green Metric Rank. This research uses two stages of data analysis techniques, namely the content analysis stage to determine the number of Intellectual Capital disclosures and the hypothesis testing stage. The analysis tool uses the SPSS version 23 application. The population of this research includes all universities in Southeast Asia that are included in the UI Greenmetric World University Rankings. The sampling technique used was purposive sampling technique, which resulted in 86 analysis units of higher education institutions in Southeast Asia. Findings: The research results prove that the geographical location of universities has a negative and significant influence on Universitas Indonesia Green Metric’s performance in Southeast Asia and human capital has a positive influence on UIGM’s performance in Southeast Asia. However, the structural capital and relational capital components do not affect the UIGM performance of universities in Southeast Asia. Originality/value: The originality of the research is the use of higher education sustainability variables with UIGM proxies and modified IC indicators for universities and geographical areas that have not been widely used to see whether there are fundamental differences in the disclosure of intellectual capital for higher education institutions in Southeast Asia.

In this paper, spherical gold nanoparticles (AuNPs), rod-shape AuNPs and triangular AuNPs were synthesized using CTAB as the coating reagent, and their bactericidal properties against Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) were studied. By the plate count method and turbidity method, the minimum bactericidal concentrations (MBC) and the minimum bacteriostasis concentrations (MIC) to the two kinds of bacteria were determined. The MIC of rod-shape AuNPs, triangular AuNPs and spherical AuNPs to E. coli were 0.65 μg/mL, 3.71 μg/mL, 21.21 μg/mL, and MBC were 1.30 μg/mL, 11.09 μg/mL, 21.21 μg/mL, respectively. The MIC to S. aureus were 0.26 μg/mL, 0.56 μg/mL, 2.65 μg/mL, while MBC were 0.52 μg/mL, 1.11 μg/mL, 2.65 μg/mL, respectively. The results showed that the bactericidal effect of rod-shape AuNPs on E. coli and S. aureus was higher than that of the other two forms, and the bactericidal effect of three different forms of AuNPs on S. aureus was better than that on E. coli.