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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]

The purpose of this research is to study the changes in the market structure of China's pulp and paper product imports. In particular, the import trade environment and market layout of Chinese pulp and paper products have changed under the international context of the coronavirus pandemic and the Sino-US trade dispute and the domestic policy context of zero imports of Chinese waste paper. This study attempts to fill the gap regarding the influencing factors of market structure, while contributing new ideas on China's trade in pulp and paper products. Based on pulp and paper product import and export trade data from 2005 to 2021, a trade gravity model was used to explore the changes in the share of China's trade partners for pulp and paper product imports and their influencing factors. The results indicated that the outbreak of COVID-19 led to a significant increase in China's imports of packaging paper products, bringing about an increase in Indonesia's status as a partner in China's pulp and paper product trade. The US-China trade dispute had an impact on pulp and paper product trade between the two countries, with China's tax countermeasures causing the US to lose its status as a trading partner in China for pulp and paper product imports. The center of gravity for paper product imports has moved from the US and Japan to Indonesia and Russia. The restrictions on waste paper imports have shifted the focus of China's paper raw material imports, with the US no longer being the main importer of China's paper raw materials. Specifically, the main importers of wood pulp are Brazil and Chile, while the main importers of waste paper pulp are Thailand and Malaysia. In the future, China needs to continuously strengthen dialogue with the United States to resolve trade disputes and create a favorable environment for trade in pulp and paper products. At the same time, China's paper enterprises should strengthen the expansion of the Southeast Asian market and reduce dependence on the US market, and China should continue to improve the waste paper recycling system and improve the utilization rate of domestic waste paper. [ABSTRACT FROM AUTHOR]

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]

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]

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]

Simple Summary: In this study, we ask whether the invasive paper mulberry (Broussonetia papyrifera) has a competitive advantage over neighbor trees in a native area. We determined the competitive capacity of paper mulberry in three deciduous broad-leaved forests using structural indices including the mixing index, the tree–tree interval index, and the diameter/height differentiation index. It was found that the reference paper mulberry had a slight competitive advantage over neighboring trees in both the horizontal and vertical planes. Such a competitive ability may play a significant role in the ecological invasion of paper mulberry. Our findings not only help to reveal the invasion mechanism of paper mulberry, but also provide an important reference for the management and utilization of paper mulberry in invaded areas. Paper mulberry (Broussonetia papyrifera) is currently an invasive species on several continents. However, little is known about whether paper mulberry has a competitive advantage over its surrounding trees in its native distribution range, subtropical regions of China. Here, we determined the relative intraspecific and interspecific competitive capacity of paper mulberry in three subtropical deciduous broad-leaved forests using the indices of structural diversity including the mixing index, the tree–tree interval index, and the diameter/height differentiation index. It was found that more than 80% of mingling index values were not greater than 0.25, suggesting a stronger competitiveness of paper mulberry relative to other tree species. The tree–tree interval index values ranged between 1 m and 2 m, suggesting a strong competition between paper mulberry and its neighbors. Moreover, more than 60% of the height differentiation index and diameter differentiation index values were positive, suggesting that the reference paper mulberry had a slight competitive advantage over neighboring trees in both the horizontal and vertical planes. These collectively suggest a competitive advantage over other tree species in the native distribution range, which may play a significant role in the ecological invasion of paper mulberry. Our findings not only help to reveal the invasion mechanism of paper mulberry, but also provide an important reference for the management and utilization of paper mulberry in invaded areas. [ABSTRACT FROM AUTHOR]

China has been the world's largest producer and consumer of paper products. In the context of the "carbon peaking and carbon neutrality goals", China's papermaking industry which is traditionally a high energy-consuming and high-emissions industry, desperately needs a nationally appropriate low-carbon development path. From the consumption-side perspective, this paper calculates the CO2 emissions of China's papermaking industry from 2000 to 2019 by using carbon emission nuclear algorithm, grain-straw ratio, first-order attenuation method, and STIRFDT decomposition model, etc., to further explore the core stages and basic patterns affecting the industry's carbon peaking. The results show that the total CO2 emissions of China's papermaking industry showed an upward trend from 2000–2013, stable from 2013–2017, and a steady but slight decline from 2017–2019. Meanwhile, the total CO2 emissions of the full life cycle of paper products in China have decreased to a certain extent in the raw material acquisition, pulp, and paper making and shipping stages, with only the waste paper disposal stage showing a particular upward trend. We find that from 2000 to 2019, China's CO2 emissions in the pulping and papermaking stage of paper products accounted for 68% of the total emissions in the whole life cycle, of which 59% was caused by coal consumption. Moreover, the scenario prediction shows that improving the energy structure and increasing the waste paper recovery rate can reduce the CO2 emissions of the industry, and it is more significant when both work. Based on this and the four core stages of CO2 emissions of the papermaking industry we proposed ways to promote CO2 emissions peaking of China's paper products. [ABSTRACT FROM AUTHOR]

There are many important cultural relics in China, including many paper relics. Therefore, it is particularly important to find methods of protecting the handwriting in paper relics. This study focuses on the effects acrylic polyurethane materials have on preserving handwriting in paper relics by examining the color change and diffusion of handwriting before and after reinforcement treatments on handwriting materials, including ink, carbon ink, blue-black ink, pure blue ink, red ink, and pencil. The acrylic polyurethane materials have a certain degree of stability and enhance the handwriting of paper relics. We analyzed the acrylic polyurethane reinforcement material in terms of acid resistance, alkali resistance, oxidation resistance, dry heat aging resistance, and durability. The experimental results show that the optimal reinforcement concentration is within 15% for ink, 10% for carbon ink, 20% for blue-black ink, 15% to 20% for pure blue ink, and 3% for red ink and pencil. Finally, the surface of the reinforced paper and handwriting were observed through laser microscopy, SEM, EDS, and infrared spectroscopy and the protective effect of acrylic polyurethane reinforcement material on handwriting was determined. [ABSTRACT FROM AUTHOR]

This study aims to systematically examine the developmental attributes and trends within China's forestry sector through the lens of a global value chain (GVC) framework. To this end, this research analyzes the Organization for Economic Co-operation and Development Inter-Country Input–Output (OECD-ICIO) database, using a cohesive set of GVC methods, including the forward decomposition of industry value-added, an assessment of industry upstream and downstream positions, the decomposition of export values, and analysis of trade competitiveness indicators. The trajectory of China's forestry industry hinges upon the interplay between foreign demand and domestic demand. The results reveal a transition in China's forestry sector development model from export-focused to a domestically driven approach. The proportion of value-added that is devoted to meeting domestic demands within the wood processing and papermaking industries has surged to 76% and 82%, respectively. Among the major economies, China has the highest output upstream index and input downstream index in the forestry industry, playing a vital role in propelling and pulling other industries into the global value chain system. The proportion of domestic added-value in China's forestry industry exports ranks among the top, reflecting strong self-sufficiency in export production. Although China's forestry industry possesses a high world market share, its overall international competitiveness is weak, especially with clear signs of weakening comparative advantages in the wood processing industry. [ABSTRACT FROM AUTHOR]

Traditional villages are important carriers of cultural heritage, and the quantitative study of their spatial characteristics is an important approach to their preservation. However, the rapid extraction, statistics, and estimation of the rich spatial characteristic indicators in these villages have become bottlenecks in traditional village research. This paper employs UAV (unmanned aerial vehicle) and handheld laser scanners to acquire three-dimensional point cloud data and construct a spatial feature three-dimensional calculation workflow of "field data collection—data processing—data analysis and application", which enables the rapid acquisition, processing, and analysis of three-dimensional village data. Typical case studies are conducted in Liukeng Village, China, focusing on the quantification of village spatial characteristics at three levels: topography, streets and alleys, and individual buildings, as well as comparative studies of multiple villages across different regions. The quantification of three-dimensional data reveals the regularity of village spatial characteristics and uncovers the spatial wisdom embedded in the site selection and spatial structure of traditional villages. This paper establishes a complete technical route for the quantitative analysis of villages, deepens public understanding of the diverse value of traditional villages, and provides technical support for research and practice in related fields. [ABSTRACT FROM AUTHOR]

Clouds are crucial in regulating the Earth's energy budget. Global cloud top heights have been easily retrieved from satellite measurements, but there are few methods for determining cloud base height (CBH) from satellite measurements. The Cloud Base Altitude Spatial Extrapolator (CBASE) algorithm was proposed to derive the height of the lower-troposphere liquid cloud base by using the Cloud-Aerosol Lidar with Orthogonal polarization cloud aerosol LiDAR (CALIOP) profiles and weather observations at airports from aviation routine and special weather report (METARs and SPECIs, called METAR) observation data in the United States. A modification to the CBASE algorithm over China (CNMETAR-CBASE) is presented in this paper. In this paper, the ability of the CBASE algorithm to calculate CBH in China is evaluated, and METAR observations over China (CNMETAR) were then used to modify the CBASE algorithm. The results including CNMETAR observation data in China can better retrieve CBH over China compared with the results using the original CBASE algorithm, and the accuracy of the global CBH results has been improved. Overestimations of CBH with the original algorithm range from 500 to 800 m in China, which have been reduced to about 300 m with an improved algorithm. The deviations calculated by the algorithm also have a significant reduction, from 480 m (CBASE) to 420 m (CNMETAR-CBASE). In conclusion, the modified CBASE algorithm not only calculates the CBH more accurately in China but also improves the results of the global CBH retrieved from satellites. [ABSTRACT FROM AUTHOR]

Rurality is an important indicator to reflect the development of villages and reveal internal differences in rural areas. The unbalanced development of transportation infrastructure in the current period of rapid urbanization has become one of the principal elements triggering spatial differences in rurality and changes in rural territorial characteristics. However, there are few studies on the impact of transportation infrastructure accessibility on the multidimensional characteristics of rurality from the perspective of heterogeneity. This paper analyzed the spatio-temporal characteristics of transport accessibility (TA) and the county rurality index (CRI) in Guangdong in 2005, 2010, 2015 and 2020 using an accessibility model and the rurality index and explored the clustering characteristics and interactions of TA and the CRI through exploratory spatial data analysis (ESDA) and geographic weighted regression (GWR) modeling. The findings showed that (1) TA and the CRI in Guangdong were significantly unbalanced in terms of space. The CRI showed a weakening trend in general, forming a distribution pattern of "high in the north and low in the south, high in the west and low in the east", while TA was on the rise, maintaining a stable pattern of "high in the middle and low in the periphery". (2) Both TA and the CRI in Guangdong had a Moran's I value greater than 0.6 during the study period, exhibiting strong spatial agglomeration, while the two showed a significant spatial negative correlation. (3) The influence of TA on the CRI in different dimensions showed dynamic changes in stages, with TA having a higher intensity of effect on society rurality and land rurality in 2005, while on society rurality and industry rurality in 2020. (4) This paper grouped 77 counties in Guangdong into four types of policy zonings—coordination types, lagged types of accessibility, lagged types of rurality and double lagged types—and put forward corresponding development recommendations. The study conducted in this paper contributes to an in-depth understanding of the impact of transportation infrastructure development on the multidimensional characteristics of rurality and provides a basis for policy formulation for coordinated urban–rural development and sustainable rural development. [ABSTRACT FROM AUTHOR]

A comprehensive understanding of the impact of land fragmentation on collective action is essential for rural governance in developing countries. Prior publications have argued that land fragmentation impedes the sustainable development of agricultural economies and rural societies, while the connection between humans and nature has not been considered comprehensively. Therefore, the conclusion that the impact of land fragmentation on collective action is purely negative may be one-sided. To examine this conclusion, this paper re-evaluates the relationship between land fragmentation and rural collective action from a multidisciplinary perspective. Based on a rural field survey using stratified random sampling, Oprobit regression was employed to conduct an econometric analysis on data from 798 rural households across 14 cities in the border region of Guangxi, China. The following research findings were obtained: (1) When the human–nature connection is considered, the relationship between land fragmentation and collective action follows an inverted U-shaped curve. Specifically, moderate initial increases in land fragmentation can lead to improvements in collective action; however, when the degree of land fragmentation exceeds a certain threshold, further increases in land fragmentation will decrease the collective action capacity. (2) This nonlinear relationship between land fragmentation and collective action may be realized through three pathways: agricultural production, land use patterns, and the ecological environment. Under the context of collective action, this study shows that a moderate level of land fragmentation objectively exists in reality. This insight provides a new impetus for developing countries to shift policy perspectives to increase their land use efficiency. Additionally, this paper integrates relevant findings from both social sciences and natural sciences. Thereby, it not only expands the existing understanding of key factors influencing rural household collective action but also emphasizes the potential for cross-disciplinary integration between social sciences and natural sciences. [ABSTRACT FROM AUTHOR]

In the field of risk assessment, the traditional econometric models are generally used to assess credit risk. And with the introduction of the "dual-carbon" goals to promote the development of a low-carbon economy, the scale of green credit in China has rapidly expanded. But with the advent of the big data era, due to the poor interpretability of a traditional single machine learning model, it is difficult to capture nonlinear relationships, and there are shortcomings in prediction accuracy and robustness. This paper selects the adjusted ensemble learning model based on the homogeneous and heterogeneous factors for user default prediction, which can efficiently process large quantities of high-dimensional data. This article adjusts each model to adapt to the task and innovatively compares various models. In this paper, the missing value filling method, feature selection, and ensemble model are studied and discussed, and the optimal ensemble model is obtained. When comparing the predictions of single models and ensemble models, the accuracy, sensitivity, specificity, F1-Score, Kappa, and MCC of Categorical Features Gradient Boosting (CatBoost) and Random undersampling Boosting (RUSBoost) all reach 100%. The experimental results prove that the algorithm based on adjusted homogeneous and heterogeneous ensemble learning can predict the user default efficiently and accurately. This paper also provides some references for establishing a risk assessment index system. [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]

Digital transformation and sustainability are both at the forefront of current supply chain developments. However, the specific mechanisms of how digital transformation and green supply chain development interact still need to be clarified, which can help supply chain business operators to enhance supply chain sustainability more effectively. This paper focuses on how the companies' organization structure and the socio-economic environment interact with digital technologies under the process of green supply chain development. Based on the "Technology–Organization–Environment" (TOE) framework, this paper analyze how digital transformation can drive green supply chain development. To test the TOE theoretical analysis framework, this paper calculates the digital transformation and green supply chain development index at the provincial level in China and conducts an empirical study. The main findings and implications of this paper can be summarized in the following aspects: First, according to the TOE theory, the external environment dimensions, such as the market and policy environments, affect the role of digital technology in promoting GSC development. Second, in the organizational dimensions, labor–capital relations, company size, and ownership factors can all affect the contribution of digital transformation to green supply chains. Third, there are differences in the impact of different types of digitization technologies on GSC development. [ABSTRACT FROM AUTHOR]

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]

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]

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]

The scroll paintings for ancestor trees have been used to inherit the spirit of ancestor worship as a historical record of family development since the late Ming Dynasty in China. A severely degraded scroll painting of an ancestor tree (made of cotton textiles) needs intervention and conservation treatment to mitigate further deterioration. On the basis of the previously reported characterization results for the painting, in this paper, a suspension that is composed of 0.6% cellulose nanofibril (CNF) and nanosized 0.15% MgO in aqueous solvent (denoted as the CNF-MgO susairpension) was prepared. Conventional characterization methods were used to assess the properties of model samples before and after treatment with the CNF-MgO suspension, as well as before and after degradation under two sets of conditions. The results show that the treated model samples are slightly alkaline, given the deposit of alkaline particles, and demonstrate good mechanical properties before and after degradation due to the increase in fiber-to-fiber bond and mitigation of acid-catalyzed hydrolysis. In spite of the non-transparency of CNF and MgO nanoparticles, they have little impact on the optical properties of textiles, as verified by transmittance data and the determination of color changes. This suspension was then used to reinforce and restore the scroll painting in a practical conservation process. The application of CNF and MgO nanoparticles on textile objects investigated in this study would expand our understanding of the conservation of such objects, especially for those that have already become acidic and degraded. [ABSTRACT FROM AUTHOR]

Reasonably allocating medical resources can effsectively optimize the utilization efficiency of such resources. This paper took Taiyuan City as an example and established a model to evaluate the rationality of medical resource spatial allocation, incorporating two key dimensions: the spatial layout and the supply and demand of medical resources. In terms of the spatial layout, three indexes were included: Firstly, the service coverage rates of different levels of medical institutions, based on residents' medical orientations, were calculated using network analysis methods. Secondly, the Huff-2SFCA method was improved to calculate the accessibility of medical resources for four different modes of transportation. Then, the Health Resource Agglomeration Degree (HRAD) and Population Agglomeration Degree (PAD) were used to quantify the equity of medical resources. In terms of the supply and demand of medical resources, one index was included: the supply–demand ratio of medical resources during sudden public health events, which was calculated using the number of beds per thousand people as an indicator. These four indexes were weighted using the entropy weight method to obtain the rationality grade of medical resource spatial allocation in Taiyuan City. The study found that the rationality evaluation level of medical resource allocation in the central urban area of Taiyuan City followed a "concentrically decreasing" pattern. The rating ranged from "very reasonable" to "less reasonable", with the area of each level expanding gradually. The areas rated within the top two categories only accounted for 19.92% of the study area, while the area rated as "less reasonable" occupied 38.73% of the total area. These results indicate that the model accounted for residents' travel for various medical orientations and the availability of resources during public health emergencies. It considered both the spatial layout and supply and demand of medical resources, offering recommendations for the precise allocation of urban medical resources. [ABSTRACT FROM AUTHOR]

To address the global warming issue, China is prioritizing the development of clean energy sources such as wind and solar power under its "dual carbon target". However, the expansion of these resources is constrained by their intermittency and the spatial and temporal distribution of wind and solar energy. This paper systematically reviews the evolution of wind and solar energy reserves, their development potential, and their current status in China from a geographical perspective. In conjunction with existing research, this paper anticipates future exploration in the realm of wind–solar complementary development or multi-energy complementary development, viewed through the lens of resource quantity. The anticipated findings are intended to furnish a theoretical foundation for further studies on the development and utilization of wind and solar energy resources within China. [ABSTRACT FROM AUTHOR]

This paper investigates China's regional role in Southeastern Europe by examining the economic strategy of neo-mercantilism using Greece as a case study. In doing so, this paper will make use of the strategy of neo-mercantilism as part of the broader theory of regional powers pursuing broader geostrategic goals. How has the strategic partnership between China and Greece evolved in recent years, and what are China's primary objectives in Greece under the neo-mercantilism? China has intentionally sought to expand its influence in Southeastern Europe by cultivating a strategic partnership with Greece, while avoiding challenging the influence of other powers in the area. The economic turmoil in Greece over the past decade created a favorable environment for attracting Chinese FDI. China's principal focus in developing its strategic partnership with Greece is to increase FDI as a means of achieving its economic goals and other political goals with tangible results related to China's support in issues mainly concerning the country's applied foreign policy. [ABSTRACT FROM AUTHOR]

With the increasing pressure of resource decline and environmental pollution faced by the green transformation of marine fisheries, marine fishery carbon sinks are an increasingly close link to national strategic interests and economic lifelines. It is, therefore, necessary to explore paths for the enhancement and development of the carbon sink capacity of marine fisheries. Based on the economic data of marine fisheries from 2002 to 2021, this paper measures the capacity and characteristics of marine fishery carbon sinks in provincial areas, applies the kernel density estimation method to depict the dynamic evolution of the distribution of absolute differences in marine fishery carbon sinks, and at the same time, identifies the factors influencing the spatial imbalance in the development of marine fishery carbon sinks as well as the spatial spillover effects. The results show the following: (1) From the total amount, the fishery carbon sink capacity of China's three marine economic circles has fluctuated and increased over the past 20 years, with obvious differences among different circles, and the marine fishery carbon sink capacity of the eastern, northern, and southern marine economic circles has risen sequentially. This trend corresponds to the economic disparities among the three circles, demonstrating a transition from economic to industrial driving effects. (2) From the spatial point of view, the fishery carbon sink capacity shows a trend of increasing year by year, concentrating in the circles, and overflowing between the circles. (3) The results of a partial derivative test further show that among the main influencing factors of marine fishery carbon sinks, capital, labor, and market openness have direct positive effects on marine fishery carbon sinks, and the direct effect of innovation is the strongest, and the significance of the indirect effect of the three circles is weaker compared to the direct effect and total effect. As a result, the carbon sink of China's marine fisheries has a large room for improvement, and in order to promote the high-quality development of China's marine fisheries, it is still necessary to accelerate the circulation of resources within the marine economic circle, accelerate the research of fishery technology, actively develop the carbon sink fishery, and enhance the specialization of aquatic product processing. [ABSTRACT FROM AUTHOR]

As the main service mode and management mode of socialized service, agricultural production trusteeship services (APTS) are an important way to realize the tight link between farmers and modern agricultural development, which is highly important for ensuring national food security. By constructing a utility model of farmers, this paper deduces the decision-making mechanism of farmers' APTS from the dual mechanism of natural risk and non-agricultural employment income (NAEI) and uses the survey data of 956 farmers in the three northeastern provinces to verify the empirical results by using multivariate logit (Mlogit) and propensity score matching (PSM) methods. The research shows that natural risk hinders farmers' choice of the APTS; NAEI has a positive impact on APST, and an increase in NAEI weakens the negative effect of natural risk on the choice of the APTS, and has an enhanced moderating effect. In addition, the scale heterogeneity analysis revealed that the impacts of natural risk and NAEI on farmers of different scales are significantly different. The NAEI adjustment effect has the greatest impact on small-scale farmers, followed by medium-scale farmers. In view of this, the government should stabilize the nonagricultural employment market and improve the nonagricultural employment opportunities of farmers. APTS organizations should transfer natural risks and improve the agricultural insurance system. According to the differences of different scales of farmers, different promotion policies are formulated, and the expansion of management and deepening services is proposed to further promote the development of APTS and consolidate the foundation of food security in China. [ABSTRACT FROM AUTHOR]

With the occurrence of the global financial crisis in 2008, the U.S. unconventional monetary policy affected the Chinese market. Based on a monthly data sample from 2008M1 to 2015M12, in this paper we identify U.S. and Chinese monetary policy shocks by using a structural vector autoregression (SVAR) model with multi-external instrumental variables along with principal component analysis (PCA) combined with high-frequency financial market data. The empirical results show that the unconventional monetary policies had a negative effect on China's inflation and output due to the signal effect, and China's stock and commodity markets increased in the short term. During the same period, China's monetary policy had a greater impact on the domestic economy and financial markets. The conclusion of this paper provides a significant reference for relevant departments to make decisions amidst the new wave of unconventional U.S. monetary policies due to the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Investigating the significant "roles" within financial complex networks and their stability is of great importance for preventing financial risks. On one hand, this paper initially constructs a complex network model of the stock market based on mutual information theory and threshold methods, combined with the closing price returns of stocks. It then analyzes the basic topological characteristics of this network and examines its stability under random and targeted attacks by varying the threshold values. On the other hand, using systemic risk entropy as a metric to quantify the stability of the stock market, this paper validates the impact of the COVID-19 pandemic as a widespread, unexpected event on network stability. The research results indicate that this complex network exhibits small-world characteristics but cannot be strictly classified as a scale-free network. In this network, key roles are played by the industrial sector, media and information services, pharmaceuticals and healthcare, transportation, and utilities. Upon reducing the threshold, the network's resilience to random attacks is correspondingly strengthened. Dynamically, from 2000 to 2022, systemic risk in significant industrial share markets significantly increased. From a static perspective, the period around 2019, affected by the COVID-19 pandemic, experienced the most drastic fluctuations. Compared to the year 2000, systemic risk entropy in 2022 increased nearly sixtyfold, further indicating an increasing instability within this complex network. [ABSTRACT FROM AUTHOR]

On the basis of "Carbon Peak and Carbon Neutral" goals, carbon sequestration projects are increasing in China. The integrity of cement sheaths, as an important factor affecting carbon sequestration projects, has also received more attention and research. When CO2 is injected into the subsurface from sequestration wells, the cement sheath may mechanically fail due to the pressure accumulated inside the casing, which leads to the sealing of the cement sheath failing. The elasticity and strength parameters of the cement sheath are considered in this paper. The critical bottom-hole injection pressures of inclined well sections under anisotropic formation stresses at different depths were calculated for actual carbon-sealing wells in the X block—the CO2 sequestration target block. The sensitivity factors of the critical bottom-hole injection pressure were also analyzed. It was found that the cement sheath damage criterion was tensile damage. The Young's modulus and tensile strength of the cement sheath are the main factors affecting the mechanical failure of the cement sheath, with Poisson's ratio having the second highest influence. An increase in the Young's modulus, Poisson's ratio, and tensile strength of the cement sheath can help to improve the mechanical stability of cement sheaths in CO2 sequestration wells. This model can be used for the design and evaluation of cement in carbon sequestration wells. [ABSTRACT FROM AUTHOR]

Making rate transient analysis (RTA) and formation evaluation for multi-fractured tight gas wells has always been a difficult problem. This is because the fluid flow in the formation has multiple nonlinear flow mechanisms, including gas-water two-phase flow, gas slippage, low-velocity non-Darcy flow, and stress-dependent permeability. In this paper, a novel RTA method is proposed for multi-fractured wells in tight gas reservoirs incorporating nonlinear flow mechanisms. The RTA method is based on an analytical model, which is modified from the classical trilinear flow model by considering all the nonlinear flow mechanisms. The concept of material balance time and normalized rate is used to process the production data for both water and gas phases. The techniques of approximate solutions in linear/bilinear flow regimes and type curve fitting are combined in the proposed RTA method. After that, the rate transient behaviors and influencing factors of multi-fractured tight gas wells are analyzed. A field case from Northwestern China is used to test the efficiency and practicability of the proposed RTA method. The results show that six flow regimes for both gas and water production performances are exhibited on the log-log plots of normalized production rate against material balance time. The rate transient responses are sensitive to the nonlinear flow mechanisms, and formation and fracture properties. The medium flow regimes are significantly affected by fracture number, fracture conductivity, fracture half-length, stress-dependent permeability, gas-water two-phase flow, and formation permeability, which should be considered in making RTA of fractured tight gas wells. The field case shows that both gas and water production performances can be well-fitted using the proposed RTA method. The major innovation of this paper is that a novel RTA method is proposed for fractured tight gas wells considering multiple nonlinear flow mechanisms, and it can be used to make reasonable formation and fracturing evaluations in the field. [ABSTRACT FROM AUTHOR]

As the main demand side of rural financial services, farmers' cooperatives are an important part of China's rural finance. However, due to the lack of effective collateral, farmers' cooperatives have problems such as difficulty in obtaining loans or expensive loans, which not only hinder the high-quality development of farmers' cooperatives, but also limit the development of regional rural finance. Digital credit as a new financing model can effectively alleviate the problems of difficult and expensive loans and has received wide attention from the government and academia. Based on this, this paper analyzes the digital credit behavior of farmers' cooperatives in detail by applying the "6C" family model to the grounded theory, and constructs a theoretical analysis model of farmers' cooperatives' digital credit behavior. The findings are as follows: The motivation for the digital credit of farmers' cooperatives is that the credit procedures are simple, the loan period is short, and the loan interest rate is low; the condition is the farmers' cooperative reputation advantage and government policy support,; the main form is the participation of cooperatives in short- and long-cycle digital credit; and the consequence is reflected in increasing the income of cooperative members, improving the availability of cooperative loans, promoting cooperative credit building, and achieving sustainable agricultural development. Different participation motivations have different effects on the form of credit. When motivated by simple credit procedures and short loan periods, farmers' cooperatives choose "Huinong e-loan"; when motivated by simple procedures and low loan interest rates, farmers' cooperatives choose "Funong Loan". Different forms of credit will produce different performances. Farmers' cooperatives choosing "Huinong e-loan" will produce economic performance; farmers' cooperatives choosing "Funong Loan" will produce economic performance and social performance. In order to deal with the problem of digital credit of farmers' cooperatives, the government needs to improve the relevant policies and regulations, reduce credit risks, and establish a sound credit system to provide credit guarantees for cooperatives and farmers. Financial institutions need to improve their financial services and innovate financial products and services to meet the multi-level credit needs of cooperatives. [ABSTRACT FROM AUTHOR]

In order to prompt the appearance of the shrimp color, sodium metabisulfite is frequently added in shrimp processing, which is, however, prohibited in China and many other countries. This study aimed to establish a surface-enhanced Raman spectroscopy (SERS) method for screening sodium metabisulfite residues on shrimp surfaces, in a non-destructive manner. The analysis was carried out using a portable Raman spectrometer jointly with copy paper loaded with silver nanoparticles as the substrate material. The SERS response of sodium metabisulfite gives two fingerprint peaks at 620 (strong) and 927 (medium) cm−1, respectively. This enabled unambiguous confirmation of the targeted chemical. The sensitivity of the SERS detection method was determined to be 0.1 mg/mL, which was equal to residual sodium metabisulfite on the shrimp surface at 0.31 mg/kg. The quantitative relationship between the 620 cm−1 peak intensities and the concentrations of sodium metabisulfite was established. The linear fitting equation was y = 2375x + 8714 with R2 = 0.985. Reaching an ideal balance in simplicity, sensitivity, and selectivity, this study demonstrates that the proposed method is ideally suitable for in-site and non-destructive screening of sodium metabisulfite residues in seafood. [ABSTRACT FROM AUTHOR]

The power sector is one of the major CO2-emitting industries in China. It is also the first key emissions control industry included in China's national carbon trading market established in 2021. Therefore, based on the data of 30 provinces and cities in China from 2015 to 2022, this study analyzes the impact of the national carbon market policy on the carbon emissions of the power industry based on the generalized Difference-in-Difference (DID) model. Based on the method of text analysis, this paper constructs the carbon market policy intensity index of each region and incorporates it into the DID model. Empirical analysis finds that the national carbon market policy can significantly inhibit the carbon emissions of the power industry. However, the heterogeneity analysis of 30 provinces and cities shows that the national carbon market policy has a significant impact on the regions that already have a carbon pilot, but not on the non-pilot regions. Therefore, this paper demonstrates the effectiveness of the national carbon market policy in the power industry emissions control, and also exposes the heterogeneity between regions, providing an important empirical basis for the inclusion of other energy-intensive industries. [ABSTRACT FROM AUTHOR]

Under the double pressures of economic growth and ecological environment protection, sea green transformation and the sustainable development of mariculture are critical. This paper constructs an evolutionary game model with the government as the main body and mariculture farmers (enterprises) as the main body and puts forward the research hypothesis. Based on 2006–2019 longitudinal data of nine provinces along China's coast, using multi-period Difference-in-Difference (DID) and dual robust estimation, we empirically investigate the national oceanic ranch demonstration zones for the influence of the green sea aquaculture and their mechanism of action. The results showed that (1) the efficiency of green level of mariculture industry in China is not high, and the establishment of national marine pasture demonstration zone has not effectively promoted the improvement of green level of mariculture industry; (2) the institutional environment, unreasonable industrial structure, and lack of scientific and technological innovation have an effect on the national oceanic ranch demonstration area as the main causes of failure to effectively promote marine green farming; (3) the establishment of the national multi-period demonstration area in the north significantly hindered the growth of the green level of mariculture and fell into the "policy trap", while the establishment of the national multi-period demonstration area in the south significantly promoted the growth of the green level of mariculture. The conclusions of this paper provide an empirical basis and reference for the improvement of the national marine pasture demonstration zone policy and the green transformation of mariculture to a certain extent. [ABSTRACT FROM AUTHOR]

Recently, frequent flood disasters in China have seriously threatened economic development and public safety. This paper addresses the need for a dynamic urban flood emergency knowledge management system in emergency management departments and the lack of systematic knowledge among emergency managers regarding urban flood control. A multimodal knowledge graph-based urban flood emergency knowledge management model was constructed to enhance the decision-making capabilities of emergency management departments, improve the efficiency of public emergency evacuation, and reduce losses from urban flood disasters by analyzing the shortcomings of the existing emergency management system. An intelligent and dynamic flood emergency knowledge management model was built. This paper integrates multimodal knowledge graph technology to establish a multimodal emergency knowledge management framework for urban flood control. It develops and simulates the proposed model's application scenarios for urban flood emergency evacuation using the Flocking algorithm on the NetLogo platform. Through simulation experiments, the practicality and effectiveness of the model in real flood disaster situations were examined, particularly in simulating crowd evacuation behavior. The study found that the model significantly improves the accuracy of information and decision-making speed during emergency responses and supports emergency management departments in conducting targeted and personalized emergency decisions. This research provides a scientific basis for emergency management departments to optimize their emergency response strategies to flood disasters and serves as a reference and example for the application of multimodal knowledge graph technology in emergency management. [ABSTRACT FROM AUTHOR]

Relieving the emotions of the public through government response is an important part of government emergency management. How governments respond in different situations can avoid stimulating negative emotions during emergencies? This paper analyzes the problem from the perspective of configuration; that is, this paper explores the combined effects of multiple factors on emotions. We construct the theoretical framework "Situation-Responder-Content" from situation, responder and response content, and use the government microblogs (n= 1517) from 23 major production accidents in China for the discussion with the use of fuzzy set qualitative comparison analysis (fsQCA). According to the results, the effective response types of different agencies in emergencies are summarized. Local authorities can respond in ways that include "Measures type" and "Measures-Emotion type". Functional agencies can respond through "Measures type", "Measures-Emotion type" and "Government feature-Driven" type. This study emphasizes that government response in emergencies is a systematic process. Responsive agencies need to release effective information on the basis of fully considering the situation and other factors. Configuration analysis should also be an important direction in government response research, which is helpful to the practice of government response in emergencies. [ABSTRACT FROM AUTHOR]

In the critical period of strengthening the construction of ecological civilization, the construction of forest cities has become an important measure to promote urban ecosystem restoration and achieve sustainable development. Based on the mechanism of forest city promoting green development, the construction of a national forest city is regarded as a "quasi-natural experiment". Using China's urban panel data from 2005 to 2019, the impact of national forest city construction on urban green total factor productivity was evaluated using Multistage asymptotic double difference. The results show that National Forest Cities with environmental regulation can significantly promote regional green total factor productivity, which is still valid after a series of Robustness tests. Mechanism analysis shows that forest city construction not only affects territorial spatial planning but also forms a linkage with green technology innovation, mutual promotion and mutual promotion to jointly promote the sustainable development goals. This paper argues that building a national forest city is an important measure to achieve China's sustainable development goals in the new era, but in the process of policy implementation, it is necessary to implement the national forest city selection system according to local conditions. [ABSTRACT FROM AUTHOR]

Pine wilt disease (PWD) is a forest disease characterized by rapid spread and extremely high lethality, posing a serious threat to the ecological security of China's forests and causing significant economic losses in forestry. Given the extensive forestry area, limited personnel for inspection and monitoring, and high costs, utilizing UAV-based remote sensing monitoring for diseased trees represents an effective approach for controlling the spread of PWD. However, due to the small target size and uneven scale of pine wilt disease, as well as the limitations of real-time detection by drones, traditional disease tree detection algorithms based on RGB remote sensing images do not achieve an optimal balance among accuracy, detection speed, and model complexity due to real-time detection limitations. Consequently, this paper proposes Light-ViTeYOLO, a lightweight pine wilt disease detection method based on Vision Transformer-enhanced YOLO (You Only Look Once). A novel lightweight multi-scale attention module is introduced to construct an EfficientViT feature extraction network for global receptive field and multi-scale learning. A novel neck network, CACSNet(Content-Aware Cross-Scale bidirectional fusion neck network), is designed to enhance the detection of diseased trees at single granularity, and the loss function is optimized to improve localization accuracy. The algorithm effectively reduces the number of parameters and giga floating-point operations per second (GFLOPs) of the detection model while enhancing overall detection performance. Experimental results demonstrate that compared with other baseline algorithms, Light-ViTeYOLO proposed in this paper has the least parameter and computational complexity among related algorithms, with 3.89 MFLOPs and 7.4 GFLOPs, respectively. The FPS rate is 57.9 (frames/s), which is better than the original YOLOv5. Meanwhile, its mAP@0.5:0.95 is the best among the baseline algorithms, and the recall and mAP@0.5 slightly decrease. Our Light-ViTeYOLO is the first lightweight method specifically designed for detecting pine wilt disease. It not only meets the requirements for real-time detection of pine wilt disease outbreaks but also provides strong technical support for automated forestry work. [ABSTRACT FROM AUTHOR]

China is currently focusing on the cooperative control of air pollution and CO2 emissions, as well as the mitigation of economic policy uncertainty (EPU). By using panel data from 282 cities spanning from 2003 to 2017 and a newly constructed city-level EPU index, a spatial Durbin, two-way fixed-effects model is employed, with the aim of estimating the impact of EPU on the synergistic emissions intensity (SEI) of air pollutants and CO2. Additionally, this paper investigates the potential channels through which EPU influences SEI. It also explores how pressures related to environmental protection and economic development affect the impact of EPU on SEI. The results indicate that a unit increase in EPU will result in a rise in the SEI of local cities, adjacent cities, and total cities by 930.9%, 69,162.7%, and 70,093.6%, respectively. Moreover, the channel analysis suggests that EPU exacerbates SEI by undermining the upgrading of the industrial structure, augmenting industrial structure distortion, and escalating labor market distortion. Furthermore, the effect of EPU on SEI may be lessened by an increase in environmental protection pressure, while an increase in economic development pressure may exert a positive influence. Finally, this paper concludes by recommending that policymakers should prioritize the maintenance and stability of economic policies, facilitate the advancement of the industrial structure, enhance the efficiency of labor resource allocation, and underscore the significance of managing urban air pollution and CO2 emissions. [ABSTRACT FROM AUTHOR]

One of the effective ways to crack the "Three Rural Issues" and promote rural revitalization is to improve agricultural labor productivity (ALP). However, at this stage, improving China's ALP is still facing many obstacles and bottlenecks. Promoting migrant workers returning home for entrepreneurship is an important breakthrough point for solving this problem. This paper regards the pilot policy of migrant workers returning home for entrepreneurship as a quasi-natural experiment and empirically investigates the influence of migrant workers returning home for entrepreneurship on ALP and explores its potential mechanism and heterogeneity using county area panel data from 2011–2019. It found the following: Firstly, the policy of migrant workers returning home for entrepreneurship significantly increases ALP. Secondly, migrant workers returning home for entrepreneurship indirectly leads to a rise in ALP through the promotion of agricultural mechanization production. Thirdly, the heterogeneity test demonstrates that migrant workers returning home for entrepreneurship purposes have a significant influence in enhancing ALP in the eastern areas, plains areas and non-agricultural strong areas. The findings of this paper not only provide an important real-world basis for the government to further support migrant workers returning home for entrepreneurship but also provide useful policy insights for the modernization and development of agriculture and rural areas. [ABSTRACT FROM AUTHOR]

Background: Organophosphate flame retardants (OPFRs) are compounds with a wide range of industrial and commercial applications and are mainly used as flame retardants and plasticizers. The global consumption of OPFRs has risen rapidly in recent decades, and they have been widely detected in environmental media. Unfortunately, OPFRs have been associated with many adverse health outcomes. The issue of the health risks of OPFRs is attracting increasing attention. Therefore, there is a need to review the current state of research and trends in this field to help researchers and policymakers quickly understand the field, identify new research directions, and allocate appropriate resources for further development of the OPFR health risk research field. Methods: This study statistically analyzed 1162 relevant publications included in the Web of Science Core Collection from 2003–2023. The internal and external features of the literature, such as publication trends, countries, authors, journals, and keywords, were quantitatively analyzed and visually presented to identify the research hotspots, compositions, and paradigms of the field and to horizontally and vertically analyze the development trends and structural evolution of the field. Results: The development of the field can be divided into three stages, and the field entered a period of rapid development in 2016. China (649 papers) is the most prolific country, followed by the United States (188 papers). The authors STAPLETON HM and WANG Y have the highest combined impact. International collaboration between countries and researchers still needs to be strengthened. Science of The Total Environment is the most frequently published journal (162 papers), and Environmental Science and Technology is the most frequently cited journal (5285 citations). Endocrine disruption, developmental toxicity, and neurotoxicity are the health effects of greatest interest. Conclusions: Future research is expected to be multidisciplinary, and research hotspots may involve a comprehensive assessment of OPFR exposure in the population, exploration of the mechanisms of endocrine-disrupting effects and in vivo metabolic processes, and examination of the health effects of OPFR metabolites. [ABSTRACT FROM AUTHOR]

The virtual water flow behind product trade provides researchers with ideas to alleviate water problems in China's coastal areas, with accompanying resource and economic implications. This paper adopts a multi-region input–output model to calculate virtual water flows in coastal areas and analyses resource benefits and economic benefits, by combining the water stress index and shadow price, to measure gains and losses of virtual water flow. This study shows that (1) China's coastal areas depends on external water supplies; (2) virtual water flows between coastal and inland areas generated 38.26 billion m3 of net scarce water savings and CNY 31,751 billion of net economic benefits, indicating that coastal areas benefited from virtual water flows from both resource and economic perspectives; (3) virtual water flows among coastal provinces and cities caused 11.10 billion m3 of net scarce water losses, but generated CNY 9784 billion of net economic gains, indicating that a further intensification of water stress in coastal areas, but such a virtual water flow pattern was beneficial from an economic perspective. This paper reveals the resource and economic impacts of virtual water flow at the national scale and among coastal provinces and cities and further proposes suggestions for promoting the beneficial flow of virtual water in coastal areas. [ABSTRACT FROM AUTHOR]

The level of difficulty of mathematical test items is a critical aspect for evaluating test quality and educational outcomes. Accurately predicting item difficulty during test creation is thus significantly important for producing effective test papers. This study used more than ten years of content and score data from China's Henan Provincial College Entrance Examination in Mathematics as an evaluation criterion for test difficulty, and all data were obtained from the Henan Provincial Department of Education. Based on the framework established by the National Center for Education Statistics (NCES) for test item assessment methodology, this paper proposes a new framework containing eight features considering the uniqueness of mathematics. Next, this paper proposes an XGBoost-based SHAP model for analyzing the difficulty of mathematics tests. By coupling the XGBoost method with the SHAP method, the model not only evaluates the difficulty of mathematics tests but also analyzes the contribution of specific features to item difficulty, thereby increasing transparency and mitigating the "black box" nature of machine learning models. The model has a high prediction accuracy of 0.99 for the training set and 0.806 for the test set. With the model, we found that parameter-level features and reasoning-level features are significant factors influencing the difficulty of subjective items in the exam. In addition, we divided senior secondary mathematics knowledge into nine units based on Chinese curriculum standards and found significant differences in the distribution of the eight features across these different knowledge units, which can help teachers place different emphasis on different units during the teaching process. In summary, our proposed approach significantly improves the accuracy of item difficulty prediction, which is crucial for intelligent educational applications such as knowledge tracking, automatic test item generation, and intelligent paper generation. These results provide tools that are better aligned with and responsive to students' learning needs, thus effectively informing educational practice. [ABSTRACT FROM AUTHOR]

With the demographic dividend disappearing, the key to achieving high-quality development in China is to promote full employment of the workforce. Women are a significant group in the job market, but they frequently face greater pressure and higher employment thresholds. Ensuring high-quality employment for women will be one of the most important tasks in the future. Based on the China Family Panel Studies data, this paper uses two-way fixed effects models, causal stepwise regression analysis, and structural equation models to study the impact of digital transformation of households on female employment and how it works. The empirical results show that digital transformation of households significantly promotes female employment. For low-security employment and high-security employment, the promotion effect of digital transformation is significant. Further mechanism analysis shows that digital transformation of households mainly increases women's human capital, improves their search for information, and stimulates improvements in social skills, thus effectively eliminating employment-related gender discrimination and ultimately promoting women's employment. This paper can provide a significant reference for alleviating female employment pressure, promoting full employment, and achieving high-quality development in the context of digital transformation. [ABSTRACT FROM AUTHOR]

Population migration continues to reshape the spatial pattern of China's population and regional economic development. During this internal migration process, production and consumption patterns often change, ultimately leading to changes in green total factor productivity. This paper, based on the Chinese population census data and 1% sampling survey data from 2005 to 2015, utilizes social network analysis methods to measure the labor mobility network indicators of 284 prefecture-level cities. Further, this paper analyzes the impact and mechanisms of regional network status on green total factor productivity using a panel fixed effects model. We find that as network density increases, the interpersonal connections between regions become closer, and the network exhibits a clear pattern of "concentrated inflows" and "dispersed outflows", with the trend of forming strong alliances becoming increasingly apparent. Regions positioned centrally either in terms of network in-degree or out-degree exhibit higher green total factor productivity. Among these, the labor mobility network plays a crucial role in enhancing green total factor productivity through the channel of technology diffusion effects, which improve investment efficiency via knowledge exchange and material capital accumulation. The promotive effect of labor network status on green total factor productivity is more pronounced in the eastern regions, where talent quality is higher, and in areas with fewer restrictions from the household registration system. [ABSTRACT FROM AUTHOR]

The increasing global warming trend has resulted in the mass loss of most glaciers. The Urumqi Vally, located in the dry and cold zone of China, and its widely dispersed glaciers are significant to the regional ecological environment, oasis economic development, and industrial and agricultural production. This is representative of glaciers in Middle Asia and represents one of the world's longest observed time series of glaciers, beginning in 1959. The Urumqi Headwater Glacier No. 1 (UHG-1) has a dominant presence in the World Glacier Monitoring Service (WGMS). This paper supplies a comprehensive analysis of past studies and future modeling of glacier changes in the Urumqi Valley. It has received insufficient attention in the past, and the mass balance of UHG-1 was used to verify that the geodetic results and the OGGM model simulation results are convincing. The main conclusions are: The area of 48.68 ± 4.59 km2 delineated by 150 glaciers in 1958 decreased to 21.61 ± 0.27 km2 delineated by 108 glaciers in 2022, with a reduction of 0.47 ± 0.04 km2·a−1 (0.96% a−1 in 1958–2022). The glacier mass balance by geodesy is −0.69 ± 0.11 m w.e.a−1 in 2000–2022, which is just deviating from the measured result (−0.66 m w.e.a−1), but the geodetic result in this paper can be enough to reflect the glacier changes (−0.65 ± 0.11 m w.e.a−1) of the URB in 2000–2022. The future loss rate of area and volume will undergo a rapid and then decelerating process, with the fastest and slowest inflection points occurring around 2035 and 2070, respectively. High temperatures and large precipitation in summer accelerate glacier loss, and the corresponding lag period of glacier change to climate is about 2–3 years. [ABSTRACT FROM AUTHOR]

A reasonable allocation of production schedules and savings in overall electricity costs are crucial for large manufacturing conglomerates. In this study, we develop an optimization model of off-site industrial production scheduling to address the problems of high electricity costs due to the irrational allocation of production schedules on the demand side of China's power supply, and the difficulty in promoting industrial and commercial distributed photovoltaic (PV) projects in China. The model makes full use of the conditions of different PV resources and variations in electricity prices in different places to optimize the scheduling of industrial production in various locations. The model is embedded with two sub-models, i.e., an electricity price prediction model and a distributed photovoltaic power cost model to complete the model parameters, in which the electricity price prediction model utilizes a Long Short-Term Memory (LSTM) neural network. Then, the particle swarm optimization algorithm is used to solve the optimization model. Finally, the production data of two off-site pharmaceutical factories belonging to the same large group of enterprises are substituted into the model for example analysis, and it is concluded that the optimization model can significantly reduce the electricity consumption costs of the enterprises by about 7.9%. This verifies the effectiveness of the optimization model established in this paper in reducing the cost of electricity consumption on the demand side. [ABSTRACT FROM AUTHOR]

The reasonable allocation of grain production factors is of vital importance to food security and agricultural development. To assess the impact of agricultural factor misallocation on food security, this paper, based on the panel data from China spanning from 2005 to 2019, conducted a comprehensive evaluation of agricultural factor misallocation and food security coefficients across 31 provinces in China, using a spatial Durbin model to examine the effects of factor misallocations on food security. The findings are as follows: (1) Production factor misallocation has significant negative impacts on food security, among them, capital misallocation and labor misallocation inhibiting food security in the local and neighboring areas, and land misallocation has a significant negative impact on food security in local areas, while its spatial spillover effect is no longer significant. (2) Mechanism analysis shows that capital misallocation and labor misallocation hinder the development of transportation infrastructure and the transfer of rural labor, thereby reducing food security. Land misallocation has accelerated the construction of transportation infrastructure, promoted the migration of rural labor, and helped ensure food security. (3) The regional heterogeneity test reveals that capital misallocation and labor misallocation hinder food security in major grain-producing areas and both sides of the Hu Huanyong Line (Hu Line). Meanwhile, land misallocation hinders food security development in various grain-producing areas, as well as the southeast of the Hu Line. Based on the above conclusions, this paper proposes suggestions to improve the efficiency of land and labor resource allocation, accelerate the construction of transportation infrastructure, and encourage the transfer speed of surplus agricultural labor. [ABSTRACT FROM AUTHOR]

Since entering the 21st century, many developing countries around the world have begun to enter a stage of rapid urbanization; large-scale "rural-urban" population migration has become a typical social phenomenon in these countries. Against this backdrop, this paper aims to elucidate the spatial migration characteristics of rural populations and to discuss future rural–urban development strategies. For this purpose, this paper takes China as a case and employs methods such as spatial autocorrelation analysis, hotspot analysis, and network analysis to construct an intercity migration network of rural migrants and analyze its spatial characteristics and internal structure. The results indicate that the migration pattern of the rural population exhibits notable spatial clustering features. Cities in the eastern and central regions are, respectively, hotspots for the inflow and outflow of rural populations, with internal migration dominating in western cities and relatively inactive rural population movements in northeastern cities. Municipalities directly under the central government, sub-provincial cities, and provincial capitals show a significant tendency to attract rural populations, while prefecture-level and county-level cities mainly radiate rural populations outward. Cities nationwide form seven major clusters in the migration network, and these clusters exhibit distinct structural characteristics. Rural population migration is influenced by various factors. In the future, considerations should focus on the county as the primary unit, attracting rural populations for local employment, and promoting rural revitalization and agriculture development. The findings of this paper are of reference significance not only to China but also to many developing countries with similar national conditions in the world. [ABSTRACT FROM AUTHOR]

This study offers a comprehensive insight into the realms of economic fraud and risk management, underscoring the necessity of adaptability to evolving technologies and shifts in financial market dynamics. Through the application of bibliometric methodologies, this study meticulously maps the relevant literature, delineating influential works, notable authors, collaborative networks, and emerging trends. It reviews key research contributions within the field, alongside reputable journals and institutions engaged in academic research. The examination highlights the logical, conceptual, and social interconnections that define the landscape of economic fraud and associated risks, elucidating how these findings inform the understanding, mitigating, and combating of the risk of fraud. Our bibliometric analysis methodology is grounded in the utilization of the Scopus database, employing rigorous filtering and extraction processes to obtain a substantial corpus of pertinent articles. Through a fusion of performance analysis and science mapping, our investigation elucidates central themes and visually represents the interrelationships between studies. Our research outcomes underscore the frequency of paper publications across diverse regions, with particular emphasis on the predominant scientific output from the US and China. Additionally, trends in academic citations are identified, indicative of the significant impact of papers on academic research and the formulation of public policies. By means of bibliometric analysis, this study not only consolidates existing knowledge but also catalyzes the exploration of future research trajectories, emphasizing the imperative of addressing these issues with heightened scientific rigor. [ABSTRACT FROM AUTHOR]