Root turnover is a key process of terrestrial ecosystem carbon cycle, which is of great significance to the study of soil carbon pool changes and global climate change. However, because there are many measurement and calculation methods of root turnover, the results obtained by different methods are quite different, and the current research on root turnover of forest ecosystem on the global regional scale is not sufficient, so the change law of root turnover of global forest ecosystem is still unclear. By collecting literature data and unifying the calculation method of turnover rate, this study integrates the spatial pattern of fine root turnover of five forest types in the world, and obtains the factors affecting fine root turnover of forest ecosystem in combination with soil physical and chemical properties and climate data. The results showed that there were significant differences in fine root turnover rate among different forest types, and it gradually decreased with the increase of latitude; the turnover rate of fine roots in forest ecosystem is positively correlated with annual average temperature and annual average precipitation; fine root turnover rate of forest ecosystem is positively correlated with soil organic carbon content, but negatively correlated with soil pH value. This study provides a scientific basis for revealing the law and mechanism of fine root turnover in forest ecosystem.

Gold nanoparticles (AuNPs) have been known to possess exceptional electric, biochemical, and optical characteristics and are ‘the topic of discussion’ these days, especially relating to the field of biomedicine. Several plants, bacteria, and fungi have been utilized for the generation of AuNPs, besides other physical and chemical methods. While some studies have been reported with gold nanoparticles, less are aimed at fungi and its optimization factors. These parameters can allow us to design AuNPs of our choice depending on the use. The present review focuses on and inspects AuNPs with green synthesis through fungus optimization parameters followed by applications, aiming specifically at their antibacterial activity. Their antibacterial characteristics can open new doors for the pharmaceutical industry in the future.

Social and environmental issues gain more importance for society that stimulates companies to adopt and integrate more sustainability practices into their business activities. This study is embedded in almost uncovered in the literature context of Russian business that undergoes its ESG transformation in conditions of unprecedented sanctions and hostile institutional environment. The study aims to reveal the role of internal stakeholders (top managers, line managers, and employees) in successful implementation of a company’s ESG practices along various dimensions. Using the primary data from 29 large Russian companies the fsQCA method is applied to identify various configurations of contingencies that stimulate their ESG performance. The analysis results in identification of two alternative core conditions for high ESG performance in Russian companies: high top management commitment to sustainability and low employees’ commitment to sustainability or the employees’ awareness about sustainability. At the end, the study results in two generic profiles composed of top management commitment, line management support, and employees’ awareness, behavior, and commitment towards ESG performance. The results show two different approaches towards ESG transformation that may bring a company to the comparably similar desired outcome. The study has a potential for generalization on a wider scope of emerging market contexts.

Goat farming plays an important economic role in numerous developing countries, with Africa being a home to a considerable portion of the global goat population. This study examined the socioeconomic determinants affecting goat herd size among smallholder farmers in Lephalale Local Municipality of the Limpopo Province in South Africa. A simple random sampling technique was used to select 61 participants. The socioeconomic characteristics of smallholder goat farmers in Lephalale Local Municipality were identified and described using descriptive statistics on one hand. On the other hand, a Multiple linear regression model was employed to analyse the socioeconomic determinants affecting smallholder goat farmers’ herd sizes. Findings from the Multiple linear regression model highlighted several key determinants, including the age of the farmer, gender of the farmer, education level, and marital status of farmers, along with determinants like distance to the markets, provision of feed supplements, and access to veterinary services. Understanding these determinants is crucial for policymakers and practitioners to develop targeted strategies aimed at promoting sustainable goat farming practices and improving the livelihoods of smallholder farmers in the region.

This research aimed to 1) evaluate the demographic characteristics, economic, social, and environmental conditions, and characteristics of the senior people in Ranong province, 2) discover the most relevant work characteristic factors for the older persons, and 3) propose appropriate work characteristics model for older people to improve quality of life. This mixed-methods research, for the quantitative part, utilizes the techniques of MRA & CFA with a sample size of 378 individuals, and for the qualitative part, utilizes a documentary study, in-depth interviews with 19 key informants, and a focus group of 17 individuals. The quantitative data were analyzed using a statistical package for the social sciences (SPSS), and content and categorization analysis with a triangulation verification were used for qualitative data. The results showed that: 1) Ranong province is blessed with rich resources, having minerals that can generate income for the province, life-long learning is given priority in senior school to enhance knowledge and necessary life skills, 2) from the regression analysis, the six predicted work characteristic factors; physical, emotional, autonomous, resistant, low-technology and safety were found relevant with statistically significant at 0.05, and the CFA consistency indices also withstood with the six dimensions above, 3) the appropriate work characteristics is articulated in the form of PEARLS model where physical, emotional, autonomous, resistant, low-technology and safety dimensions are the key.

Tangerang City is characterized by its dense residential, commercial, and industrial activities and strategic proximity to Jakarta. This study aims to evaluate the strategic planning and implementation of innovative city initiatives in Tangerang, Indonesia, focusing on integrating blockchain, Internet of Things (IoT) big data technologies and innovation in urban development. This study has employed explanatory survey data from a structured questionnaire distributed to a diverse Tangerang community sample, including users and non-users of the “Smart City Tangerang Live” application. The survey was conducted for 2-months March to April 2022, included 71 and the sample included individuals across 13 districts, utilizing cluster sampling to ensure representativeness. The findings reveal a positive community response towards the smart city initiatives, with significant Engagement and interaction with the “Tangerang Live” application. However, technology access and usage disparities among different community segments were noted. The study highlights the critical role of intelligent technologies in transforming urban infrastructure and services, improving the quality of life, and fostering sustainable urban development in Tangerang. The implications of this study are multifaceted. For urban planners and policymakers, the results underscore the importance of strategic planning in innovative city development, emphasizing the need for inclusive and accessible technological solutions. The study also suggests potential areas for improvement in community engagement and public awareness campaigns to promote the adoption and efficient use of smart technologies.