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The objectives of this research are to study: (i) the history and development of knowledge of Yiwulv Mountain Manchu paper-cutting art, and (ii) the process of designing and developing digital media for learning about cultural heritage. This research used qualitative research methods. By studying documents and collecting field data by surveys, interviews, observations, group discussions, and workshops. The data was elicited from a group of 40 participants. The analysis was based on the objectives and the results were presented in a descriptive analytical manner. The results are as follows: (i) The art of paper-cutting is related to history and culture. There is a unique cultural identity of the Manchus on Yiwulv Mountain. The way of conveying knowledge is told orally. Currently, there is a problem due to the age of paper-cutting artists and lack of inheritance. Therefore, it is necessary to find ways to protect them as well as transfer them to youth and those who are interested. (ii) The art of paper-cutting is applied with 3D animation technology to inherit and learn the art of Yiwulv Mountain Manchu paper-cutting. The teaching materials created can be explained in detail from the perspective and content. The design combines virtual tour technology to make it interesting. Learners study through digital media and computer systems, which makes it convenient to access information.

Objective: The primary objective of this inquiry was to explore the nexus between authorship attribution in medical literature and accountability for scientific impropriety while assessing the influence of authorial multiplicity on the severity of sanctions imposed., Methods: Probit regression models were employed to scrutinize the impact of authorship on assuming accountability for scientific misconduct, and unordered multinomial logistic regression models were used to examine the influence of authorship and the number of bylines on the severity of punitive measures., Results: First authors and corresponding authors were significantly more likely to be liable for scientific misconduct than other authors and were more likely to be penalized particularly severely. Furthermore, a negative correlation was observed between the number of authors' affiliations and the severity of punitive measures., Conclusion: Authorship exerts a pronounced influence on the attribution of accountability in scientific research misconduct, particularly evident in the heightened risk of severe penalties confronting first and corresponding authors owing to their principal roles. Hence, scientific research institutions and journals must delineate authorship specifications meticulously, ascertain authors' contributions judiciously, bolster initiatives aimed at fostering scientific research integrity, and uphold an environment conducive for robust scientific inquiry., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Peng et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Academic paper writing holds significant importance in the education of medical students, and poses a clear challenge for those whose first language is not English. This study aims to investigate the effectiveness of employing large language models, particularly ChatGPT, in improving the English academic writing skills of these students., Methods: A cohort of 25 third-year medical students from China was recruited. The study consisted of two stages. Firstly, the students were asked to write a mini paper. Secondly, the students were asked to revise the mini paper using ChatGPT within two weeks. The evaluation of the mini papers focused on three key dimensions, including structure, logic, and language. The evaluation method incorporated both manual scoring and AI scoring utilizing the ChatGPT-3.5 and ChatGPT-4 models. Additionally, we employed a questionnaire to gather feedback on students' experience in using ChatGPT., Results: After implementing ChatGPT for writing assistance, there was a notable increase in manual scoring by 4.23 points. Similarly, AI scoring based on the ChatGPT-3.5 model showed an increase of 4.82 points, while the ChatGPT-4 model showed an increase of 3.84 points. These results highlight the potential of large language models in supporting academic writing. Statistical analysis revealed no significant difference between manual scoring and ChatGPT-4 scoring, indicating the potential of ChatGPT-4 to assist teachers in the grading process. Feedback from the questionnaire indicated a generally positive response from students, with 92% acknowledging an improvement in the quality of their writing, 84% noting advancements in their language skills, and 76% recognizing the contribution of ChatGPT in supporting academic research., Conclusion: The study highlighted the efficacy of large language models like ChatGPT in augmenting the English academic writing proficiency of non-native speakers in medical education. Furthermore, it illustrated the potential of these models to make a contribution to the educational evaluation process, particularly in environments where English is not the primary language., (© 2024. The Author(s).)

Objective: To analyze the characteristics of retracted oncology papers from Chinese scholars and the reasons for retraction., Methods: Data on retracted oncology papers from Chinese scholars published from 2013 to 2022 were retrieved from the Retraction Watch database. The retraction number and annual distribution, article types, reasons for retraction, retraction time delay, publishers, and journal characteristics of the retracted papers were analyzed., Results: A total of 2695 oncology papers from Chinese scholars published from 2013 to 2022 had been retracted. The majority of these papers were published from 2017 to 2020. In terms of article type, 2538 of the retracted papers were research articles, accounting for 94.17% of the total number of retracted papers. The main reasons for retraction were data, result, and image problems, duplicate publication, paper mills, author- and third-party-related reasons, plagiarism, false reviews, and method errors. The retraction time delay for the retracted papers ranged from 0 to 3582 days (median, 826 days). The retractions mainly occurred within the first 4 years after publication. A total of 77 publishers were involved in the retracted papers. In terms of journal distribution, 394 journals were involved in the retracted papers, of which 368 (93.40%) were included in the SCI database. There were 243 journals with an impact factor of <5 (66.03%)., Conclusion: In the field of oncology, the annual distribution of retracted papers from Chinese scholars exhibited first an increasing and subsequently a decreasing trend, reaching a peak in 2019, indicating an improvement in the status of retraction after 2021. The main type of the retracted papers was research article, and the main reason for retraction was academic misconduct. The retractions were mainly concentrated in several major publishers and periodicals in Europe and the United States. Most of the journals had low-impact factors., (Copyright © 2024 Copyright: © 2024 Journal of Cancer Research and Therapeutics.)

In the late Qing Dynasty, religious periodicals by Western missionaries were made legal in China, and subsequently became an important manner of their missionary cause. Among them, Child's Paper 小孩月报 (1875–1881) by John Marshall Willoughby Farnham, a Protestant missionary from the United States, endeavoured to convert child readers by carrying children's stories of moral and emotional education. By concentrating on the educational elements of Child's Paper, this article inspects how conversion was achieved via the intertextual interpretation of Christian doctrines within these educational elements. Specifically, how the image of little Christians and urchins, respectively, represents salvation and redemption in Christian morals. This article holds that the missionaries' stress on the authority of Christian discourse in the education of Chinese children makes evident an increasing emphasis on the reformative effects of Christianity on Chinese children. Moreover, the conversion-education efforts by missionaries also construed helping Chinese children gain a cross-cultural perspective on Western religion, and arguably inspired later Chinese intellectuals' to create newspapers for the purpose of the pre-primary education of Chinese children. [ABSTRACT FROM AUTHOR]

Accompanying China's accession to the World Trade Organization, the rapid development of the Chinese economy has led to increasingly serious environmental issues. However, the inherent mechanisms underlying the impact of Environmental Information Disclosure (EID) policy and trade on the environmental effects of Chinese paper enterprises remain unclear in the context of the era's requirement for a resource-conserving and environmentally-friendly society. The pollution problem in the papermaking industry has received attention worldwide, and how to balance the environmental and development issues of papermaking enterprises is an urgent issue that needs to be solved in the academic community. This study explores the impact mechanisms of EID policy and trade on the environmental effects of enterprises from the perspective of financial constraints. Utilizing the PSM-DID model, the study investigates the moderating effects of financial constraints on the EID policy and import-export trade. The findings reveal that both external and internal financial constraints have negative, detrimental effects on the environmental effects of the EID policy and trade. These constraints impede research and development investment and technological upgrades, hinder productivity improvement, and hamper the realization of "regulatory and trade innovation effects". This study enriches our understanding of the mechanisms by which trade affects the environmental effects of Chinese paper enterprises and further identifies the impacts of Chinese EID policy and trade on pollution emissions by enterprises, providing a theoretical basis and practical foundation for the government in formulating financial, environmental, and trade policies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Kaihua paper is a type of precious hand-made paper in China that has been used throughout Chinese history. Due to its extraordinary whiteness and fine texture, it was adopted by the imperial palace in the reign of Emperor Kang Xi and Yong Zheng of the Qing Dynasty of China in the 17th and 18th century. It is stained by a special type of yellowish-brown spot after years of storage, which is called a "peachy spot." The formation of such spots remains unclear, although complicated physicochemical processes or microbial activities might be involved. We performed nondestructive sampling and high-throughput sequencing on peachy spot surfaces, unstained areas, and air samples in the stack room to analysis the the bacterial and fungal communities, and performed prediction of functional genes of the bacterial communities. The results showed that peachy spot formation was mainly related to bacterial communities rather than fungal communities. Significantly more potential acid-producing, acidophilic or cellulase-producing bacteria, such as, Streptococcus, Staphylococcus, and Lysinibacillus, and pigment-producing bacteria, such as Methylobacterium and Rubrobacter, were identified in the peachy spot samples. Prediction of the functional genes of the bacterial community also suggested the production of acidic substance pigments. These findings provide new insights into the pigment formation mechanism in ancient paper and open an opportunity to develop new strategies to preserve the ancient paper documents. [ABSTRACT FROM AUTHOR]

The contamination characteristics, migration patterns and health risks of per- and polyfluoroalkyl substances (PFAS) were investigated in 66 Chinese paper products by using target and non-target screening methods. Among 57 target PFASs, 5 and 6 PFASs were found in the hygiene paper products (n F 2n+1 COOH. Microwave heating can increase the release of PFAS in popcorn bags and convert long-chain PFAS into short-chain ones. The migration experiments indicated that the ethanol in food simulants can increase the migration of PFAS, and short-chain PFAS exhibits a greater migration trend. The estimated daily intake (EDI) values for 6 of 18 paper bowls/plates exceeded the recommendation of 0.63 ng/kg bw/day by the European Food Safety Authority (EFSA), posing a potential threat to human health., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: The advent of Personalized Medicine (PM) holds significant promise in revolutionizing healthcare by tailoring treatments to individual patients based on their data. However, its successful implementation requires the seamless integration of innovative technologies and presents formidable challenges in terms of sustainability. To tackle these challenges head-on, the International Consortium for Personalized Medicine (ICPerMed) was established, and the IC2PerMed project, as part of this consortium, seeks to foster collaboration between the European Union (EU) and China in the field of Personalized Medicine. Based on the results collected by the project, the objective of this study is to discern the key priorities for the implementation of Personalised Medicine concerning Information and Communication Technologies (ICT) and Big Data and digital solutions, with a particular emphasis on data management and protection., Methods: A Delphi survey was conducted to gather expert's consensus on the main priorities for actions on Information and Communication Technologies (ICT) and Big Data and digital solutions in the field of Personalized Medicine., Results: The survey identified seven priorities in the area of Big Data and digital solutions, including data interoperability, standards, security measures, and international partnerships. Additionally, twelve priorities were identified for the innovation-to-market process, emphasizing cost-effectiveness, need assessment, and value definition in resource allocation., Conclusions: The effective implementation of new technologies in Personalized Medicine research and practice is essential for the advancement of healthcare systems in both the European and Chinese contexts. The identified priorities play a pivotal role in promoting the sustainability of health systems and driving innovation in the implementation of Personalized Medicine. Addressing challenges related to data interoperability, standards, security, international collaboration, cost-effectiveness, and value assessment is of utmost importance in order to propel the progress of Personalized Medicine in healthcare systems., (© 2024. The Author(s).)

Purpose: There are major gaps in our knowledge of hereditary ocular conditions in the Asia-Pacific population, which comprises approximately 60% of the world's population. Therefore, a concerted regional effort is urgently needed to close this critical knowledge gap and apply precision medicine technology to improve the quality of lives of these patients in the Asia-Pacific region., Design: Multi-national, multi-center collaborative network., Methods: The Research Standing Committee of the Asia-Pacific Academy of Ophthalmology and the Asia-Pacific Society of Eye Genetics fostered this research collaboration, which brings together renowned institutions and experts for inherited eye diseases in the Asia-Pacific region. The immediate priority of the network will be inherited retinal diseases (IRDs), where there is a lack of detailed characterization of these conditions and in the number of established registries., Results: The network comprises 55 members from 35 centers, spanning 12 countries and regions, including Australia, China, India, Indonesia, Japan, South Korea, Malaysia, Nepal, Philippines, Singapore, Taiwan, and Thailand. The steering committee comprises ophthalmologists with experience in consortia for eye diseases in the Asia-Pacific region, leading ophthalmologists and vision scientists in the field of IRDs internationally, and ophthalmic geneticists., Conclusions: The Asia Pacific Inherited Eye Disease (APIED) network aims to (1) improve genotyping capabilities and expertise to increase early and accurate genetic diagnosis of IRDs, (2) harmonise deep phenotyping practices and utilization of ontological terms, and (3) establish high-quality, multi-user, federated disease registries that will facilitate patient care, genetic counseling, and research of IRDs regionally and internationally., Competing Interests: Declaration of Competing Interest The authors have no conflicts of interest to disclose., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Introduction: Over the last decade, the emergence and spread of personalized medicine (PM) have defined a substantial revolution in healthcare. In principle, healthcare system sustainability is challenged by the investments required for research and development, as well as the adoption of PM techniques in routine clinical care. The "Integrating China in the International Consortium for Personalized Medicine" (IC2PerMed) EU-funded project aims to integrate China into the "International Consortium for Personalized Medicine" (ICPerMed). IC2PerMed aims to align the EU and China's research agendas in this field to enable a swift development of approaches in the EU and China with strong leverage upon EU-Chinese collaborations., Methods: Within this project, we first mapped relevant policies on PM in both the EU and China, and then we involved European and Chinese experts in PM in workshops and Delphi surveys in order to identify relevant priorities for the implementation of PM in sustainable healthcare., Results: As a result of this process, we identified nine overarching priorities, each addressing specific aspects of the sustainability of healthcare systems and PM implementation, with the main goal of supporting policymakers in integrating PM approaches in the EU and China., Discussion/conclusion: The implementation of PM in health systems is appealing in terms of improved accuracy in diagnostics, treatment, and prevention of disease, as well as reduction of the side effects resulting from inefficient use of drugs. Research, development, and implementation of needed techniques require time and resources that can slow the adoption of PM in healthcare systems. The nine priorities we identified address some of the most critical points, trying to lay the foundations for a comprehensive approach., (© 2023 The Author(s). Published by S. Karger AG, Basel.)

This paper studies the impact of digital economy development on carbon emissions, which is a hot topic in the field of environmental economics. This topic is within the scope of the Frontiers in Environmental Science and is particularly in line with the theme of Environmental Economics and Management section in the journal. Firstly, this paper constructs the Digital Economy Development Index and its variable indicators to measure the development of the digital economy. Secondly, this paper uses urban panel data to reveal the impact of digital economy development on carbon emissions, and further adopts IV method to deal with endogeneity issues. Thirdly, this paper performs the heterogeneity analyses depending on the characteristics of the city. The results can provide a basis for formulating differentiated policies. Fourthly, this paper further explores the mechanism by which the digital economy affects carbon peaking. The results show that the digital economy may influence carbon peaking through upgrading of the industrial structure, technical innovation, and energy consumption. [ABSTRACT FROM AUTHOR]

Carbon emission issues are becoming increasingly severe, and the carbon emissions in shrinking cities, primarily characterized by population loss, are often overlooked and insufficiently studied. This paper focuses on the carbon emissions from county-level administrative units in China's three northeastern provinces from 2001 to 2017. The study scientifically identified shrinking cities and measured the differences in carbon emission characteristics between growing and shrinking cities using the Theil index. Ultimately, the paper constructs a panel spatial econometric model to analyze the factors influencing them and explore their spatial effects. (1) The total carbon emissions in the Three Northeastern Provinces exhibited an inverted U-shaped trend, increasing from 734.21 million tons in 2001 to 1731.73 million tons in 2017, with the Mann–Kendall trend test showing a significant increase; spatially, this manifests as a significant positive spatial autocorrelation. (2) The region has 138 shrinking cities, accounting for over 50%; regarding carbon emission characteristics, the Theil index has consistently remained above 0.18, indicating significant differences between the carbon emissions of growing and shrinking cities. (3) The panel spatial econometric model results show that the influencing factors of carbon emissions in shrinking cities have unique directions, intensities, and spatial effects. In shrinking cities, aside from localized GDP effects and per-capita GDP acting as a suppressant, the population size has a pronounced inhibitory effect on local and surrounding carbon emissions. The analysis reveals significant differences in the carbon emission patterns and mechanisms between growing and shrinking cities; based on these results, the paper proposes differentiated carbon control strategies. [ABSTRACT FROM AUTHOR]

Machine learning (ML) has become increasingly popular in the prediction of debris flow occurrence, but the various ML models utilized as baseline predictors reported in previous studies are typically limited to individual case bases. A comprehensive and systematic evaluation of existing empirical evidence on the utilization of ML as baseline predictors for debris flow occurrence is lacking. To address this gap, we conducted a meta-analysis of ML-based prediction modeling of debris flow occurrence by retrieving papers that were published between 2000 and 2023 from the Scopus and Web of Science databases. The general findings were as follows: (1) A total of 84 papers, distributed across 37 different journals in this time period, reflecting an overall upward trend. (2) Debris flow disasters occur throughout the world, and a total of 13 countries carried out research on the prediction of debris flow occurrence based on ML; China made significant contributions, but more research efforts in African countries should be considered. (3) A total of 36 categories of ML models were utilized as baseline predictors for debris flow occurrence, with logistic regression (LR) and random forest (RF) emerging as the most popular choices. (4) Feature engineering and model comparison were the most commonly utilized strategies in predicting debris flow occurrence based on ML (53 and 46 papers, respectively). (5) Interpretation methods were rarely utilized in predicting debris flow occurrence based on ML, with only 16 papers reporting their utilization. (6) In the prediction of debris flow occurrence based on ML, interpretation methods were rarely utilized, searching by data materials was the most important sample data source, the topographic factors were the most commonly utilized category of candidate variables, and the area under the ROC curve (AUROC) was the most frequently reported evaluation metric. (7) LR's prediction performance for debris flow occurrence was inferior to that of RF, BPNN, and SVM; SVM was comparable to RF, and all superior to BPNN. (8) The application process for the prediction of debris flow occurrence based on ML consisted of three main steps: data preparation, model construction and evaluation, and prediction outcomes. The research gaps in predicting debris flow occurrence based on ML include utilizing new ML techniques and enhancing the interpretability of ML. Consequently, this study contributes both to academic ML research and to practical applications in the prediction of debris flow occurrence. [ABSTRACT FROM AUTHOR]

Introduction: In recent years, graph neural network has been extensively applied to drug discovery research. Although researchers have made significant progress in this field, there is less research on bibliometrics. The purpose of this study is to conduct a comprehensive bibliometric analysis of graph neural network applications in drug discovery in order to identify current research hotspots and trends, as well as serve as a reference for future research. Methods: Publications from 2017 to 2023 about the application of graph neural network in drug discovery were collected from the Web of Science Core Collection. Bibliometrix, VOSviewer, and Citespace were mainly used for bibliometric studies. Results and Discussion: In this paper, a total of 652 papers from 48 countries/regions were included. Research interest in this field is continuously increasing. China and the United States have a significant advantage in terms of funding, the number of publications, and collaborations with other institutions and countries. Although some cooperation networks have been formed in this field, extensive worldwide cooperation still needs to be strengthened. The results of the keyword analysis clarified that graph neural network has primarily been applied to drugtarget interaction, drug repurposing, and drug-drug interaction, while graph convolutional neural network and its related optimization methods are currently the core algorithms in this field. Data availability and ethical supervision, balancing computing resources, and developing novel graph neural network models with better interpretability are the key technical issues currently faced. This paper analyzes the current state, hot spots, and trends of graph neural network applications in drug discovery through bibliometric approaches, as well as the current issues and challenges in this field. These findings provide researchers with valuable insights on the current status and future directions of this field. [ABSTRACT FROM AUTHOR]

The severity of plastic pollution is increasing, and delaying sustainable development is not an option. China is a large consumer of plastic, so it is essential to encourage the use of eco-friendly shopping bags there. The paper focuses on the recognition and use of eco-friendly shopping bags among young people in Guangdong Province, China, and determines what factors can lead to a rise in the use of these bags. A questionnaire was utilized to gather data from 392 young people in Guangdong Province using a quantitative research approach. According to the data from the questionnaire, they generally are supportive of eco-friendly shopping bags. Ultimately, the paper's data emphasize the positive effects of materials (paper material), function (internal compartment), and design (green label). For the purpose of advocating sustainable development, this paper provides helpful guidance for the design of eco-friendly shopping bags. [ABSTRACT FROM AUTHOR]

The exponential growth of China's economy, coupled with the surge in online commerce, has led to a significant expansion of the logistics industry. In 2022, China's express delivery industry generated approximately 9 million tons of waste paper and 1.8 million tons of plastic. This study analyzed the current composition and utilization of logistics waste in China, with suggestions for recycling. Logistics waste can be defined as the packaging waste generated in the logistics industry. Corrugated paper and plastic waste were chosen as the objects for utilization. Due to its high cellulose content, corrugated paper can be utilized along with other paper waste for biomass resourcing. Biodegradable plastics can also be converted into biomass resources through the action of specific microorganisms. These polymers can be enzymatically depolymerized by certain bacteria and fungi, yielding valuable organic products. In general, logistics wastes all have potential for biomass resource recovery. By adopting appropriate recovery and conversion technologies, these waste streams can be transformed into high-value bio-based products, such as biofuels, biochemicals, and biopolymers, thus contributing to the development of a circular and sustainable economy. [ABSTRACT FROM AUTHOR]

The recovery of the global economy in the aftermath of COVID-19 faces enormous challenges. Ensuring stable income growth of the population has become an important means for developing countries to ensure sustained economic development. Raising the overall income of the population is a public initiative that benefits all citizens; therefore, governments of developing countries should promote the implementation of relevant public policies and the provision of public goods to ensure that existing economic instruments can benefit the entire population. In this regard, public space, as a typical form of public good, may play an important role in promoting the benefits of existing economic policies for all residents. This paper examines how residents' use of public space contributes to their income growth through social capital. Hypotheses are tested based on an econometric analysis of 1565 questionnaires received from Chinese workers. The results show that residents' use of public space can indeed be an important way to increase their income, which is realized through the enhancement of social capital. The research presented in this paper provides a new influence variable of public space to improve residents' income. Further, it improves people's understanding of the three classical concepts—public space, social capital, and income—by establishing the logical connection and theoretical explanation of physical space, emotional space, and value space in human society. The conclusions of this paper highlight the important role of public space in urban and rural development planning. [ABSTRACT FROM AUTHOR]

Based on the panel data of the province and municipality in 2010-2021, this paper measures the fishery eco-efficiency by using the SBM-DEA model and empirically analyses how China's marine ranch construction improves the fishery eco-efficiency by using the double-difference fixed-effect model. The results show that, firstly, China's marine ranch construction can improve the fishery eco-efficiency. Secondly, China's marine ranch construction promotes fisheries eco-efficiency by improving the input efficiency of labor, fish species, fishing vessel, fishery technology extension, aquaculture area and by reducing pollutant outputs. Thirdly, the fishery eco-efficiency of the marine ranch construction region has increased annually since 2015, and technological changes, scale efficiency changes and technical efficiency changes can all contribute to the fishery eco-efficiency improvement, and increase in order. Based on the results of the empirical analyses, this paper proposes policy recommendations to improve the fishery eco-efficiency in the conjunction with the construction of marine ranch in China. [ABSTRACT FROM AUTHOR]

Green bonds are relatively new in the financial market compared to other financial securities but are useful in financing environmentally friendly projects. Just like other financial securities, green bonds are affected by various factors, such as economic policy uncertainty. Our aim of this paper was to conduct a systematic literature review of the impact of economic policy uncertainty on green bonds. We sought to do a thorough analysis of the existing literature on the assessment of the impact of economic policy uncertainty on green bonds and the techniques used in assessing the impact. Our findings showed that economic policy uncertainty had a strong impact on the green bond, with its intensity varying by location. This impact tended to be more pronounced in periods of heightened uncertainty. Also, our findings highlighted that the assessment of the impact of economic policy uncertainty on green bonds gained popularity in 2019, with China emerging as a prominent contributor. However, other countries, such as Finland, even though they had few published papers, their citations signified the production of quality papers in this field. Additionally, we found that the application of the quantile analysis method was utilized by many recent studies, which signified its importance in this field. Our findings highlighted the importance of considering appropriate techniques in assessing the impact of economic policy uncertainty on green bonds while taking into account the paper quality. [ABSTRACT FROM AUTHOR]

The demographic structure is an important factor influencing the development of the services industry. As the country with the world's most serious aging problem, China's service industry structure is likely to undergo profound changes in response to the rapid demographic transition. Therefore, this paper examines the effect of population aging on the development of the service industry in the context of China's accelerating population aging. The study found that: (1) Population aging has a significant "inverted U" effect on the development of the services industry. (2) The impact of population aging on the development of the service industry has obvious regional and industry heterogeneity. The study of regional heterogeneity found that population aging in economically developed regions has a more obvious effect on the development of the service industry than in economically less developed regions. Industry heterogeneity studies found that population aging has an obvious promotional effect on the development of medical and other rigid demand industries, while the effect on other non-rigid demand industries is not significant. (3) The threshold effect test found that when the degree of population aging exceeds the threshold, the stimulating effect of population aging on the development of the services industry is no longer significant. The research in this paper provides useful insights into the likely response to changes in the industrial structure of the services industry, and offers some implications for countries with similar demographic profiles to China. [ABSTRACT FROM AUTHOR]

Introduction: Export quality improvement is a crucial path for a country or region to climb up the advanced division of labor in the global value chain. For developing countries that have long been at the lower end of the global value chain division of labor, the dominance of agricultural trade is often controlled by international retailers, leading to higher costs of agricultural trade and hindering the upgrading of the quality of agricultural exports. As a traditional agricultural exporting country, China still needs a competitive advantage despite the large scale of its agricultural exports. Currently, e-commerce can provide buyers and sellers with comprehensive transaction information and technical support, allowing them to realize rational allocation of resources and export upgrading. Therefore, studying how e-commerce can promote the quality upgrade of agricultural exports is crucial for China to build a trade power. Methods: This paper clarifies the mechanism of e-commerce's theoretical impact on the quality of agricultural exports and then empirically tests it using a high-dimensional fixed-effects model with Chinese customs data from 2000 to 2020 as a sample. Results: The results show that e-commerce significantly promotes the quality of agricultural exports in all regions of China, and this conclusion still holds after various robustness tests; the heterogeneity test shows that e-commerce fosters the quality of agricultural exports in eastern China, densely populated regions, and economically underdeveloped regions, especially in the case of heterogeneous products; the mechanism analysis confirms that e-commerce promotes the quality of agricultural exports mainly through the optimization of the agricultural industry chain and supply chain, and the enhancement of the level of servicing. Mechanism analysis confirms that e-commerce improves agricultural export quality mainly through optimizing the agricultural industry chain and supply chain, improving the level of servitization, and docking the demand information of the consumer market, etc. Expanded analysis shows that constructing cross-border e-commerce platforms also significantly improves the quality of micro enterprises' agricultural exports. This paper enriches the research on e-commerce and agricultural trade. Discussion: This paper provides an essential reference for constructing a robust agricultural trade country and developing high-quality agriculture. Despite encompassing data up to 2020, in the context of today's global economic volatility directly affecting agricultural trade, future investigations will broaden the scope to delve deeper into how e-commerce can help countries cope with global economic uncertainty. [ABSTRACT FROM AUTHOR]

More attention has been paid to environmental regulation of greenhouse gas emissions in the energy industry under the transformation of industrial structure. This paper takes microdata of Chinese energy enterprises from 1998 to 2012 as a sample to build a duty-sharing model, analyzes the effect of environmental regulations on the industrial chain, and explains the "double growth" phenomenon that occurred in China, which is nothing short of miraculous in terms of the environment and economy. In the industrial chain, the environmental obligations and responsibilities will be shared between upstream and downstream enterprises due to trade linkages. This paper finds that environmental responsibilities will move forward through the industrial chain when environmental regulations are strengthened. Downstream companies will loosen "relative" control constraints, thereby expanding output but increasing demand for upstream products. Different from the existing research, we claim that, since environmental regulation has a differential effect on the industrial chain, it will promote the growth of output in the entire chain, in contrast to the theory of "cost compliance", which claims that environmental regulation will inevitably lead to the output. Based on this research, this paper puts forward some suggestions and insights on how the government implements environmental regulations. [ABSTRACT FROM AUTHOR]

Due to budget and sensor technology constraints, a single sensor cannot simultaneously provide observational images with both a high spatial and temporal resolution. To solve the above problem, the spatiotemporal fusion (STF) method was proposed and proved to be an indispensable tool for monitoring land surface dynamics. There are relatively few systematic reviews of the STF method. Bibliometrics is a valuable method for analyzing the scientific literature, but it has not yet been applied to the comprehensive analysis of the STF method. Therefore, in this paper, we use bibliometrics and scientific mapping to analyze the 2967 citation data from the Web of Science from 1991 to 2023 in a metrological manner, covering the themes of STF, data fusion, multi-temporal analysis, and spatial analysis. The results of the literature analysis reveal that the number of articles displays a slow to rapid increase during the study period, but decreases significantly in 2023. Research institutions in China (1059 papers) and the United States (432 papers) are the top two contributors in the field. The keywords "Sentinel", "deep learning" (DL), and "LSTM" (Long Short-Term Memory) appeared most frequently in the past three years. In the future, remote sensing spatiotemporal fusion research can address more of the limitations of heterogeneous landscapes and climatic conditions to improve fused images' accuracy. [ABSTRACT FROM AUTHOR]

Haze pollution not only affects the quality of economic growth and the image of the government, but also seriously affects public health. With the improvement of climate risk perception, the public is actively seeking all kinds of risk management measures to combat the hazards of haze pollution. The study of the relationship between haze pollution, climate risk perception and the development of commercial health insurance is of great significance to the formulation of haze control policies and the improvement of social security system. This paper attempts to explore the relationship between haze pollution, climate risk perception and commercial health insurance demand by establishing static and dynamic models based on panel data from 31 provinces in China from 2005 to 2022. Also, the spatial spillover effects of haze pollution in different regions on the development of commercial health insurance in other regions are investigated by establishing a spatial Durbin model. It is found that (1) haze pollution has a lagged positive effect on the demand for commercial health insurance; (2) haze pollution has a significant spatial spillover effect on the development of commercial health insurance; (3) this study used Python technology to construct a climate risk perception index, and found that the moderating effect of the residents' perception of climate risk existed significantly, and that the residents might take other measures to manage the risk in the short term, but in the long term, the climate risk perception showed a positive correlation with the level of education. This paper provides implications for government departments and social media to strengthen education and publicity, improve residents' awareness of risk diversification, and deepen the concept of commercial health protection. [ABSTRACT FROM AUTHOR]

The aim of this paper is to explore whether and how urban road transport (URT) development affects haze pollution. One of the innovations of this paper is that URT development is measured by road accessibility with novel digital elevation model datasets, which have been used by few scholars. The endogenous problem caused by revere causality issue in the relationship between URT development and haze pollution is also considered. Based on the panel data of prefecture-level cities of Yangtze River Delta (YRD) region in China from 2011 to 2018, this paper uses long-lagged values of URT development as the instrumental variable, employing the two-stage least squares (2SLS) method. The study shows that URT development leads to an increase of haze pollution. Moreover, mechanism tests based on moderating and mediating models support the finding that decreasing haze pollution resulted from better connection effects, while rising agglomeration effects tend to bring about increasing haze pollution, and the latter effect is larger in magnitude than the former. Current URT development may have long-term negative consequences for livability of YRD cities, and urban decision makers should reconsider the effectiveness of the current road transport investment and construction. [ABSTRACT FROM AUTHOR]

Compared with financial information, whether corporate social responsibility disclosure has impacts on debt financing cost has obviously become a heated topic in the academic. This paper selects A-share listed companies in Shanghai and Shenzhen stock markets of China from 2013 to 2017 as sample to study the impact of corporate social responsibility disclosure on debt financing cost, including bond financing cost and bank loan cost. In addition, this paper divides the sample into voluntary corporate social responsibility disclosure group and mandatory corporate social responsibility disclosure group and studies whether the effects of voluntary corporate social responsibility disclosure and mandatory corporate social responsibility disclosure on bond financing cost and bank loan cost are different. The empirical results are presented as follows: Firstly, enterprise disclosing high-quality corporate social responsibility report is more conducive to reducing the debt financing cost. Specifically, corporate social responsibility disclosure significantly lowers both the bond financing cost and bank loan cost. Moreover, the reduction impact of corporate social responsibility disclosure on bond financing cost is greater than that of bank loan cost. Secondly, enterprises voluntarily disclosing corporate social responsibility reports are more conducive to reducing the debt financing cost than that of enterprises mandatorily disclosing corporate social responsibility reports. Thirdly, non-state-owned enterprises are more conducive to reducing debt financing cost than that of state-owned enterprise. The enterprises with more market competition are more conducive to reducing the debt financing cost than the oligopolistic enterprises. Finally, this paper concludes and gives policy implications. This paper amplifies the literature regarding the economic consequences of corporate social responsibility disclosure and improves the understanding of the impact of corporate social responsibility disclosure on debt financing cost. [ABSTRACT FROM AUTHOR]

The superiority of BWM over other weighting methods for obtaining the weight values of the attributes is that it achieves high-confidence results with a reasonable number of pairwise comparisons. Although the best-worst method (BWM) is a well-known multi-criteria decision-making (MCDM) method that has been successfully utilized in almost all scientific areas to solve challenging real-life problems, no research has comprehensively examined the state-of-the-art in this regard. The present study depicts a detailed overview of publications concerned with BWM during the period 2015–2022. Based on the information obtained from the Scopus database, this work presents a big picture of current research on BWM. In other words, this paper analyzes the existing literature about BWM and identifies thematic contexts, application areas, emerging trends, and remaining research gaps to shed light on future research agendas aligning with those gaps. Further, the most recent BWM research is analyzed in the top ten scientific areas, from engineering to materials science. “Engineering”, “computer science”, and “business, management, and accounting” are the hottest fields of BWM research. China is the most active country regarding “engineering” and “computer science”, whereas India is the leader in “business, management, and accounting”. The study also reveals that there are still many research gaps in BWM research. The big picture taken in this study will not only showcase the current situation of BWM research but will also positively impact the direction and quality of new research. [ABSTRACT FROM AUTHOR]

As the most direct way to guide and support the transformation and upgrading of grain enterprises, government subsidies have an important orientation for the transformation and development of Chinese grain enterprises and the improvement of new quality productivity. Based on the data of 136 grain listed companies and NEEQ listed companies from 2015 to 2022, this paper empirically tests the impact of government subsidies on the new productivity of grain enterprises and its transmission mechanism. The research results show that government subsidies have significantly improved the new productivity of grain enterprises. The analysis of the mechanism of action finds that government subsidies have promoted the improvement of new productivity of enterprises by optimizing the structure of human capital and improving the absorptive capacity of enterprises. Further research shows that the higher the degree of product market competition, the lower the tax burden of enterprises, and the government subsidy exceeds the threshold value of 8.9685, the greater the effect of government subsidy on the improvement of new quality productivity of enterprises. The economic consequence test shows that government subsidies can promote the new productivity of grain enterprises and effectively improve the total factor productivity of enterprises. The research in this paper provides relevant enlightenment for the Chinese government to strengthen project planning, strengthen resource coordination, and implement scientific and accurate policies in the new round of fiscal and taxation system reform. [ABSTRACT FROM AUTHOR]

Introduction: Female empowerment can promote gender equality and realize women's comprehensive development, while the Internet has opened up an effective channel for female empowerment. Methods: Given the relative lack of women's rights in rural China and the rapid Internet development, this paper, based on the 2021 China Comprehensive Social Survey data, first analyses the effect of Internet embeddedness on rural women's non-farm employment using the Probit model. Then, it uses the mediation effect model to explore the role of women's rights perception in the mechanism between Internet embeddedness and women's non-farm employment. Finally, based on age and regional differences, we also analyze the impact of Internet embeddedness on female non-farm employment. Results: The paper draws the following conclusions: (1) Internet embedding can promote female non-farm employment, and the probability of female non-farm employment is 3.71% for each degree of Internet embedding. (2) Internet embedding can enhance women's perception of their rights and thus promote women's non-farm employment. (3) Internet embedding can enhance the perception of rights of young rural women, which can promote their nonfarm employment. However, the influence of internet embedding on middle-aged women's perception of rights is not significant. (4) Internet embedding in the eastern region can enhance women's perception of rights and realize women's non-farm employment; on the contrary, in the central and western regions, Internet embedding cannot enhance rural women's perception of rights. Discussion: Therefore, this paper proposes to release further the impact of the Internet in promoting rural women's non-farm employment to improve the deprivation of rural women's rights and promote gender equality and women's comprehensive development. [ABSTRACT FROM AUTHOR]

Introduction: Over the last decade, there has been a growing interest in cereal-legume intercropping for sustainable agriculture. As a result numerous papers, including reviews, focus on this topic. Screening this large amount of papers, to identify knowledge gaps and future research opportunities, manually, would be a complex and time consuming task. Materials and methods: Bibliometric analysis combined with text mining and topic modelling, to automatically find topics and to derive a representation of intercropping papers as a potential solution to reduce the workload was tested. Both common (e.g. wheat and soybean) as well as underutilized crops (e.g. buckwheat, lupin, triticale) were the focus of this study. The corpus used for the analysis was retrieved from Web of Science and Scopus on 5th September 2022 and consisted of 4,732 papers. Results: The number of papers on cereal-legume intercropping increased in recent years, with most studies being located in China. Literature mainly dealt with the cereals maize and wheat and the legume soybean whereas buckwheat andlupinreceivedlittleattention from academic researchers. These underutilized crops are certainly interesting to be used as intercropping partners, however, additional research on optimization of management and cultivar's choice is important. Yield and nitrogen fixation are the most commonly studied traits in cereal-legume intercropping. Last decade, there is an increasing interest in climate resilience, sustainability and biodiversity. Also the term "ecosystem services" came into play, but still with a low frequency. The regulating services and provisioning services seem to be the most studied, in contrast terms related to potential cultural services were not encountered. Discussion: In conclusion, based on this review several research opportunities were identified. Minor crops like lupin and buckwheat need to be evaluated for their role as intercropping partners. The interaction between species based on e.g. root exudates needs to be further unraveled. Also diseases, pests and weeds in relation to intercropping deserve more attention and finally more in-depth research on the additional benefits/ecosystem services associated with intercropping systems is necessary. [ABSTRACT FROM AUTHOR]

Background: With potential of deep learning in musculoskeletal image interpretation being explored, this paper focuses on the common site of rotator cuff tears, the supraspinatus. It aims to propose and validate a deep learning model to automatically extract the supraspinatus, verifying its superiority through comparison with several classical image segmentation models. Method: Imaging data were retrospectively collected from 60 patients who underwent inpatient treatment for rotator cuff tears at a hospital between March 2021 and May 2023. A dataset of the supraspinatus from MRI was constructed after collecting, filtering, and manually annotating at the pixel level. This paper proposes a novel A-DAsppUnet network that can automatically extract the supraspinatus after training and optimization. The analysis of model performance is based on three evaluation metrics: precision, intersection over union, and Dice coefficient. Results: The experimental results demonstrate that the precision, intersection over union, and Dice coefficients of the proposed model are 99.20%, 83.38%, and 90.94%, respectively. Furthermore, the proposed model exhibited significant advantages over the compared models. Conclusion: The designed model in this paper accurately extracts the supraspinatus from MRI, and the extraction results are complete and continuous with clear boundaries. The feasibility of using deep learning methods for musculoskeletal extraction and assisting in clinical decision-making was verified. This research holds practical significance and application value in the field of utilizing artificial intelligence for assisting medical decision-making. [ABSTRACT FROM AUTHOR]

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Rising population levels exert significant pressure on available freshwater resources. Scientists and researchers from various countries are diligently seeking a long-lasting solution using solar-powered desalination. This research paper investigates the current advancements in solar desalination research by utilizing the method of "scientometrics". Scientometrics employs traditional methodologies, including bibliometrics, which entails quantifying the number of research papers published, and citation analysis, which involves examining the frequency with which other researchers cite these papers. By integrating these two approaches, scientometrics provides invaluable information about the most influential countries, institutions, and individual researchers in the field. Utilizing the software program VOSviewer, a comprehensive analysis was conducted on 1855 research papers published between 2010 and 2024. These papers were selected based on a predetermined set of ten key search terms. The results of the analysis indicate that China is the leading country in this field, as it boasts the highest number of published papers and the most citations received overall. Notably, Egyptian research institutions have been identified as the most influential in this area. Moreover, a single author has notably amassed 3419 citations for their 54 published works on solar desalination. This analysis unveiled past and contemporary advancements in the field and identified current trends through keyword analysis. It also offers recommendations based on bibliometric findings, including suggestions for addressing the challenges faced by solar-derived systems and addressing research area saturation. [ABSTRACT FROM AUTHOR]

Based on panel data for 30 provinces in China from 2000 to 2020, this paper uses entropy method to construct the integrated development indicators of energy Internet, and explores the impact of the development of the energy Internet on reducing carbon emissions in China and its internal transmission mechanism. The research results show that the development of energy Internet can significantly reduce regional carbon dioxide emissions, and increasing the use of renewable energy is an important mechanism for the comprehensive development of energy Internet to curb carbon emissions. Heterogeneity analysis shows that the emission reduction effect brought by the development of energy Internet is more remarkable in the regions with lower carbon emissions and western China. Furthermore, this paper finds that in the setting of the development of energy Internet, the development of renewable energy can promote natural gas consumption and advance energy conversion efficiency. The government's emphasis on regional technology development has an external strengthening effect on carbon emission reduction. The research in this paper expands and diversifies carbon reduction pathways and provides reference for more developing countries to utilize the development of energy internet to achieve carbon reduction. [ABSTRACT FROM AUTHOR]

Currently, digital transformation is having various impacts on enterprises around the world, including the green innovation. However, the current literature on the relationship between digitalization and green innovation in enterprises is scarce. What is the relationship between them, and whether heterogeneous environmental regulation has mediating effects, are questions that are worth exploring. Using a sample of listed manufacturing enterprises in China, this paper empirically tests the impact of digital transformation on enterprise green innovation. The results show that: (1) Digital transformation has a significant positive impact on green innovation, including green innovation output and green innovation capability. (2) Diverse environmental regulation may have mediating effects of digital transformation's influence on green innovation. (3) After a number of robustness tests, the conclusions are still valid. This paper can provide a reference for developing green development strategies for manufacturing enterprises. [ABSTRACT FROM AUTHOR]

The increasing prominence of climate change, geopolitical crises, and global economic slowdown highlights the challenges and structural deficiencies of traditional cross-border agro-food supply chains. As a result, there has been a growing consensus on the need to leverage digital technology to rebuild and innovate a safe, stable, and sustainable global food system. This study assessed the knowledge progress and development trends in the sustainable development of cross-border agro-food supply chains enabled by digital technology. A total of 352 authoritative papers from the core Web of Science database were selected for analysis. The Citespace tool was utilized to visually examine research elements. The findings reveal that research outcomes in this territory experienced a significant period of rapid growth, particularly after 2020. Sustainability and IEEE Access are the journals with the highest and second-highest number of publications. China and the France National Institute are the countries and research institutions with the largest number of publications in this field. The research hotspots are mainly the application of digital technologies, food safety, and supply chain system model innovation. In the past ten years, the research in this territory has gone through three stages: precise timeliness orientation, intelligent strategic decision-making orientation, and model predictability orientation. We further construct the 'antecedent–practice–performance' conceptual framework of the sustainability of the digital technology-enabled cross-border agro-food supply chain. Finally, this paper presents the potential research directions in this territory, focusing on four aspects: research method, research mechanism, research topic, and research frontier. [ABSTRACT FROM AUTHOR]

Energy shortage and excessive carbon emissions have become the main constraints to the sustainable development of China's logistics industry. Improving the efficiency of the logistics industry is crucial to promoting regional ecological environment protection and sustainable development of the logistics industry. In this paper, the efficiency of China's logistics industry in 2013–2019 is evaluated by using the non-oriented EBM model considering the unexpected output, and then the influencing factors of the efficiency of the logistics industry in the central region are analyzed by using the panel Tobit model. The results show that the logistics industry in the central region is at a low efficiency level. Factors, such as the level of economic development, industrial structure and technical level have a significant positive impact on the efficiency of the logistics industry in the central region, while factors such as government support and logistics infrastructure have a significant negative impact on the efficiency of the logistics industry in the central region. Finally, the paper puts forward some targeted recommendations for the sustainable development of the logistics industry in the central region. [ABSTRACT FROM AUTHOR]

China is facing a serious land resource mismatch problem, which will profoundly affect the acceleration of economic growth and technological innovation. Reform of the industrial land allocation system can solve the mismatch of land resources, and that also has an important impact on the promotion of economic and technological development. This paper selects the data of Chinese A-share listed companies in Shanghai and Shenzhen from 2007 to 2020 as the research sample, constructs a double machine learning model, and empirically investigates the impact of a new industrial land use policy on firms' green innovation behavior. The study shows that: (1) the new industrial land use policy significantly promotes firms' substantive and strategic green technological innovation, and the effect on substantive green technological innovation is greater than that on strategic green technological innovation. (2) The enhancement of R&D investment sustainability and the "talent pool" effect are important mechanisms through which the new industrial land use policy influences firms' substantive and strategic green technological innovation. Meanwhile, the new industrial land use policy is conducive to firms' green coinnovation. (3) There is heterogeneity in the effect of the new industrial land use policy, which can significantly promote green technological innovation of firms in the eastern region, while it does not play a significant role in the green innovation behavior of firms in the central and western regions. The above research results enrich the research in the field of industrial land and innovation, help to understand more comprehensively the mechanism of new industrial land affecting firms' green technological innovation, and provide policy insights for strengthening the application of industrial land allocation reform in firms' green innovation. [ABSTRACT FROM AUTHOR]

This paper employs a unique data set to analyze the trading behavior of wealthy individual investors across Mainland China and their impact on Chinese stock markets' tail risk. Results show that the wealthy individual investors' trading behavior can explain Chinese stock markets' tail risk, and the daily investment portfolios based on the network density of wealthy individual investors have significant excess returns. This paper also investigates the determinants of wealthy individual investors' trading behavior with the social network method and the spatial econometric model, and reveals that wealthy individuals benefit from the spillover effect of their trading behavior through the investor networks. The results of this paper not only reveal micro evidence for the formation mechanism of asset prices, but also provide insight into the behavior of wealthy individual investors. [ABSTRACT FROM AUTHOR]

The "Three Rural Issues", encompass challenges related to agriculture, farmer, and rural area, which hold significant importance in driving comprehensive rural revitalization efforts in China. Farmer entrepreneurship, as a crucial means to enhance productivity, create job opportunities, and increase residents' income, has gradually become a key driving force in promoting rural revitalization in the new stage of development in China. With the rapid development of rural e-commerce, farmer entrepreneurship has encountered new opportunities. This study utilizes the 2020 China Family Panel Studies (CFPS) data and employs a structural equation model (SEM) to analyze the direct impact of rural e-commerce participation on farmer entrepreneurial behavior, considering factors such as human capital, social capital, and network infrastructure. This study further explores the indirect effects and mechanisms of e-commerce participation as a mediating variable and analyzes the impact and mechanisms on agricultural entrepreneurship behavior. The findings are as follows: (1) E-commerce participation significantly promotes farmer entrepreneurial behavior; (2) E-commerce participation as a mediating variable has a positive indirect effect on the relationship between social trust, network infrastructure, human capital, and farmer entrepreneurial behavior; (3) E-commerce participation has a significant positive influence on farmer entrepreneurship in the agricultural sector, and farmers with higher levels of network infrastructure and human capital have a higher probability of choosing agricultural entrepreneurship under the influence of e-commerce participation. Finally, this study provides policy recommendations in terms of infrastructure construction, entrepreneurial policy environment, and education level, aiming to optimize the situation of farmer entrepreneurship and contribute to the comprehensive promotion of rural revitalization.Overall, the research in this paper effectively combines theory and empirical evidence to outline the direct and indirect impact mechanisms of rural e-commerce participation on farmers' entrepreneurial behavior and agriculture-related entrepreneurial behavior and to test the effects of their impacts. First, most of the existing literature deals with farmers in individual sample areas, while the sample selected in this paper is farmers in the whole country, which is relatively more generalizable; second, most of the previous studies explore the level of e-commerce in the inter-provincial or county areas, while this paper expands the empirical study of rural e-commerce on the entrepreneurial behavior of farmers and the micro-period of agricultural entrepreneurial behavior, and focuses on the impacts of the e-commerce activities of farmers on their entrepreneurial behavior. [ABSTRACT FROM AUTHOR]

Objective: This review aims to provide a quantitative and qualitative bibliometric analysis of literature from 2013 to 2023 on the role of exosomes in PC, with the goal of identifying current trends and predicting future hotspots. Methods: We retrieved relevant publications concerning exosomes in PC, published between 2013 and 2023, from the Web of Science Core Collection. Bibliometric analyses were conducted using VOSviewer(1.6.19), CiteSpace (6.2.R4), and Microsoft Excel (2019). Results: A total of 624 papers were analyzed, authored by 4017 researchers from 55 countries/regions and 855 institutions, published in 258 academic journals. China (n=285, 34.42%) and the United States (n=183, 24.87%) were the most frequent contributors and collaborated closely. However, publications from China had a relatively low average number of citations (41.45 times per paper). The output of Shanghai Jiao Tong University ranked first, with 28 papers (accounting for 4.5% of the total publications). Cancers (n=31, 4.9%); published the most papers in this field. Researcher Margot Zoeller published the most papers (n=12) on this topic. Research hotspots mainly focused on the mechanisms of exosomes in PC onset and progression, the role of exosomes in PC early diagnosis and prognosis, exosomes promote the development of PC chemoresistance, and potential applications of exosomes as drug carriers for PC therapies. We observed a shift in research trends, from mechanistic studies toward clinical trials, suggesting that clinical applications will be the focus of future attention. Emerging topics were pancreatic stellate cells, diagnostic biomarkers, mesenchymal stem cells, extracellular vesicles. Conclusion: Our scientometric and visual analysis provides a comprehensive overview of the literature on the role of exosomes in PC published during 2013-2023. This review identifies the frontiers and future directions in this area over the past decade, and is expected to provide a useful reference for researchers in this field. [ABSTRACT FROM AUTHOR]

The development of urbanization has brought new challenges to the ecological environment, and the promotion of green technology innovation and development is widely recognized as an essential method to achieve cities' economic benefits and environmental protection. This paper examines whether the new urbanization pilot policies (NUP) increase green technology innovation (GTI) from both theoretical and empirical perspectives. This paper examines the impact of new urbanization on GTI by analyzing data from 285 cities in China between 2010 and 2021, using the multi-period DID model with the implementation of NUP as an exogenous policy shock. The study results indicate that NUP significantly affects GTI, and the conclusion still holds after the parallel trend test, placebo test, and other robustness tests. Heterogeneity analysis shows that the NUP significantly enhances GTI in low environmental pollution, non-resource-based, Medium-sized, and Central Region cities. The test of moderating effect shows that NUP has a "linkage effect" with the government's environmental attention, financial investment in innovation, and regional talent pooling. The findings of this paper provide empirical evidence and decision-making reference for promoting NUP and sustainable development of cities. [ABSTRACT FROM AUTHOR]

This paper uses inter-provincial panel data from 2011 to 2017, a linear regression model, and a threshold model to conduct empirical analyses of the impact of the digital economy on China’s overall economic growth and the three main sectors of industry. The paper then investigates the impact and effects the digital economy has had on the economic growth of the three main sectors of industry in China’s eastern, central, and western regions. Finally, the paper investigates the most significant differences among the various regions and the threshold effects of urbanization levels on the relationship between the digital economy and economic growth. The findings indicate a significantly positive correlation between the digital economy and regional economic growth. Moreover, geographical factors notably influence this correlation. The digital economy exerts a positive effect on all sectors of industry. It may not substantially impact industrial development in regions with highly developed infrastructure. Regarding the other regions, the digital economy exhibits varying degrees of impact due to the differences in the specific indicators. The conclusion drawn by the threshold model is that the magnitude of the threshold effect correlates with geographic factors. No threshold effect was observed in the eastern region, while the threshold effect occurred in the central region when the urbanization levels for the provinces were below 0.6645. Similarly, the threshold effect was noted in the western region when the urbanization level was below 0.3931. Considering all of this, the study also offers policy recommendations that will help balance the regional development of digital economies, accelerate the digital transformation of traditional industries, enhance digital infrastructure construction, refine the formulation and implementation of data policy, and establish relevant incentive mechanisms. [ABSTRACT FROM AUTHOR]

This paper uses an SBM-GML index model to assess Green Total Factor Productivity (GTFP) in China’s carbon-intensive sectors and conducts an empirical investigation into which factors influence GTFP in these sectors. The GTFP in the carbon-intensive sectors experienced a decline between 2006 and 2011, followed by an upward trend beginning in 2012. Technological progress was the primary driver of GTFP growth, while business size was also a notable contributor. Irrational energy structures negatively influenced the high-quality development of the carbon-intensive sectors, and environmental regulation and foreign direct investment (FDI) have not yet significantly impacted GTFP. Based on these findings, this paper suggests that the carbon-intensive sectors should expedite their green transitions by focusing on system improvement, technological innovations, energy revolutions, and high-level opening up. [ABSTRACT FROM AUTHOR]

With China's rapid industrialization and urbanization in the process of socio-economic development, the extensive use of energy has resulted in a large amount of CO2 emissions, which puts great pressure on China's carbon emission reduction task. Through multivariate socio-economic data, this paper proposes an extraction and screening method of multivariate variables based on land-use types, and the downscaled spatial decomposition of carbon emissions at different scales was carried out by using the spatial lag model (SLM). This paper makes up for the shortcomings of previous studies, such as an insufficient modeling scale, simple modeling variables, limited spatio-temporal span of spatial decomposition, and no consideration of geographical correlation. Based on the results of the spatial decomposition of carbon emissions, this paper explores the spatial and temporal dynamics of carbon emissions at different scales. The results showed that SLM is capable of downscaling the spatialization of carbon emissions with high precision, and the continuity of the decomposition results at the provincial scale is stronger, while the differences of the decomposition results at the municipal scale are more obvious within the municipal units. In terms of the spatial and temporal dynamics of CO2 emissions, carbon emissions at both scales showed a significant positive correlation. The dominant spatial correlation types are "Low–Low" at the provincial level, and "Low–Low" and "High–High" at the municipal level. The smaller spatial scope is more helpful to show the geographic dependence and geographic differences of China's carbon emissions. The findings of this paper will help deepen the understanding of the spatial and temporal changes of carbon emissions in China. They will provide a scientific basis for the formulation of feasible carbon emission reduction policies. [ABSTRACT FROM AUTHOR]

Domestic and international risk shocks have greatly increased the demand for systemic risk management in China. This paper estimates China's multi-layer financial network based on multiple financial relationships among banks, assets, and firms, using China's banking system data in 2021. An improved PageRank algorithm is proposed to identify systemically important banks and other economic sectors, and a stress test is conducted. This study finds that China's multi-layer financial network is sparse, and the distribution of transactions across financial markets is uneven. Regulatory authorities should support economic recovery and adjust the money supply, while banks should differentiate competition and manage risks better. Based on the PageRank index, this paper assesses the systemic importance of large commercial banks from the perspective of network structure, emphasizing the role of banks' transaction behavior and market participation. Different industries and asset classes are also assessed, suggesting that increased attention should be paid to industry risks and regulatory oversight of bank investments. Finally, stress tests confirm that the improved PageRank algorithm is applicable within the multi-layer financial network, reinforcing the need for prudential supervision of the banking system and revealing that the degree of transaction concentration will affect the systemic importance of financial institutions. [ABSTRACT FROM AUTHOR]