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.

The need for strategic alignment within HR management increased managers' concern about individual behavior and how this behavior was related to the achievement of goals. In public management, effectively managing employees' performance has been necessary since Weber's bureaucratic administration. The individual performance appraisal is the right tool to assess employees' competencies. Thus, we proposed the following research question: Which factors, as pointed out by theory, have the most significant influence on the individual performance appraisal process? The quantitative method was applied to answer this question, developing and testing a scale via EFA and a hypothetical model via SEM-CB. The results indicated a scale with 25 items able to access the main points of the IPA process and a hypothetical model with 7 constructs that indicate the influence on employee engagement. The main finding is the significant influence of feedback on the whole process. The main theoretical contribution was the construction of the MIPAS scale, and the practical contribution was to identify the points where managers should focus on improving the IPA process with their subordinates.

Urban infrastructures and services—such as public transportation, innovation bodies and environmental services—are important drivers for the sustainable development of our society. How effectively citizens, institutions and enterprises interact, how quickly technological innovations are implemented and how carefully new policies are pursued, synergically determine development. In this work, data related to urban infrastructure features such as patents and recycled waste referred to 106 province areas in Italy are investigated over a period of twenty years (2001–2020). Scaling laws with exponents characterizing the above mentioned features are observed and adopted to scrutinize whether and how multiple interactions within a population have amplification effects on the recycling and innovation performance. The study shows that there is a multiplication effect of the population size on the innovation performance of territories, meaning that the dynamic interactions among the elements of the innovation eco-systems in a territory increase its innovation performance. We discuss how to use such approach and the related indexes for understanding metropolitan development policy.

This study aims to examine the entrepreneurial activities of 240 women in the districts of Konaseema, East Godavari, and Kakinada during 2021–2022, focusing on the diverse range of 286 enterprises they managed across 69 business types. These enterprises were tailored to local resources and market demands, with coconut wholesale, cattle breeding, and provision shops being the most common. The study also analyzes income distribution, noting that one-third of the women earned between ₹50,000–1,00,000 annually, while only 0.70% earned over ₹5,00,000. More than half of the enterprises served as the primary income source for their families. The research highlights the significant role these women entrepreneurs play in their communities, their job satisfaction derived from financial independence and social empowerment, and the challenges they face, such as limited capital and market access. Finally, the study offers recommendations to empower these women to seize entrepreneurial opportunities and enhance their success.

The food industry progressively requires innovative and environmentally safe packaging materials with increased physical, mechanical, and barrier properties. Due to its unique properties, cellulose has several potential applications in the food industry as a packaging material, stabilizing agent, and functional food ingredient. A coffee pod is a filter of cellulosic, non-rigid, ready-made material containing ground portions and pressed coffee prepared in dedicated machines. In our study, we obtained, with homogenization and sonication, cellulose micro/nanoparticles from three different coffee pods. It is known that nanoparticulate systems can enter live cells and, if ingested, could exert alterations in gastrointestinal tract cells. Our work aims to investigate the response of HT-29 cells to cellulose nanoparticles from coffee pods. In particular, the subcellular effects between coffee-embedded nanocellulose (CENC) and cellulose nanoparticles (NC) were compared. Finally, we analysed the pathologic condition (Cytolethal Distending Toxin (CDT) from Campylobacter jejuni) on the same cells conditioned by NC and CENC. We evidenced that, for the cellular functional features analysed, NC and CENC pre-treatments do not worsen cell response to the C. jejuni CDT, also pointing out an improvement of the autophagic flux, particularly for CENC preconditioning.

Cancer is the 3rd leading cause of death globally, and the countries with low-to-middle income account for most cancer cases. The current diagnostic tools, including imaging, molecular detection, and immune histochemistry (IHC), have intrinsic limitations, such as poor accuracy. However, researchers have been working to improve anti-cancer treatment using different drug delivery systems (DDS) to target tumor cells more precisely. Current advances, however, are enough to meet the growing call for more efficient drug delivery systems, but the adverse effects of these systems are a major problem. Nanorobots are typically controlled devices made up of nanometric component assemblies that can interact with and even diffuse the cellular membrane due to their small size, offering a direct channel to the cellular level. The nanorobots improve treatment efficiency by performing advanced biomedical therapies using minimally invasive operations. Chemotherapy’s harsh side effects and untargeted drug distribution necessitate new cancer treatment trials. The nanorobots are currently designed to recognize 12 different types of cancer cells. Nanorobots are an emerging field of nanotechnology with nanoscale dimensions and are predictable to work at an atomic, molecular, and cellular level. Nanorobots to date are under the line of investigation, but some primary molecular models of these medically programmable machines have been tested. This review on nanorobots presents the various aspects allied, i.e., introduction, history, ideal characteristics, approaches in nanorobots, basis for the development, tool kit recognition and retrieval from the body, and application considering diagnosis and treatment.