Search

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]

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]

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]

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]

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]

In areas with serious pollution problems, the government designates a special emission limit (SEL) for pollution control and environmental protection in China. This paper examines the effects of chemical oxygen demand (COD) SEL on firms' production activity and market performance in the pulp and paper industry in the Lake Tai area in China. Using firm-level data, we employ a difference-in-differences strategy and find that SEL has a negative impact on the production scale, profitability, and market size of the regulated firms, while showing no significant impact on firm exports. The heterogeneity tests suggest that the impact of SEL on production and market performance varies with firm ownership, firm size, and target market. The reallocation effect of production shifts extra production from exited firms to existing firms, which explains the expansion of production scale and market size for SOEs and large-sized regulated firms. Compared with the decline of production scale, the inventory alleviation effect reduces the negative impact of stricter environmental regulation on firm performance.

Covering the full texts of all papers published in MDPI's Remote Sensing between 2009 and 2021, in-depth scientometric analyses were conducted. Trends in publications show an increase in the overall number of papers. A relative increase in papers using SAR sensors and a relative decrease in papers using optical remote sensing can also be seen. The full-text analyses reveal distinctive styles and writing patterns for papers from different sub-fields of remote sensing and for different countries and even cities. While a slight increase in the readability of abstracts is detected over time, the overall readability of papers is decreasing. Institutional co-authorship analysis reveals the ongoing 'scientific decoupling' between China and the USA in remote sensing. Using scientometric full-text analysis, current trends and developments are revealed. [ABSTRACT FROM AUTHOR]

While participation in the international division of labor has led to rapid economic development, it has also resulted in pressing environmental issues in China. In the context of "building a resource-saving and environment-friendly society" and the current sustainability requirements, research on the environmental impact of Chinese paper companies from the perspective of Environmental Information Disclosure (EID) policy and trade has not yet reached a consensus. This study constructs an analytical framework for the EID policy impact mechanism and trade on the environmental effects of the paper industry and enterprises. It explores the direct and indirect effects of EID policy and import-and-export trade on the paper industry environmental effects using the Propensity Score Matching and Difference-in-Differences (PSM-DID) model. EID positively impacts the pollution reduction of enterprises mainly through the technical effect. Export trade positively impacts the reduction of enterprises' emissions through the technology effect. However, the demand of the international market increases the pollution from the paper industries, which has a negative impact. Importing will enable enterprises to obtain greater price advantages which can alleviate and transfer the costs brought by EID. This study analyzes the impact of trade on the environmental effects of Chinese paper enterprises and identifies the impact of China's EID policy and trade on enterprises' pollution emissions. It provides a theoretical and practical foundation for the Chinese government to formulate environmental and trade policies.

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]

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]

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]

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]

Paper mulberry (Broussonetia papyrifera L.) is an unconventional forage with high crude protein content and is widely used in China. In order to evaluate the pattern of fermentation quality and the aerobic stability when inoculated with lactic acid bacteria, laboratory-scale silage was prepared. The experimental groups included a control group (CK), a Lactobacillus plantarum 'LC365283' (selected from paper mulberry silage) treatment (L1), a commercial inoculant Lactobacillus plantarum treatment (GF), a commercial inoculant Lactobacillus buchneri treatment (FR), a 3% molasses treatment (MO), a 150 U/g cellulase treatment (CE), and their combinations (MO + L1, MO + GF, MO + FR, CE + L1, CE + GF, and CE + FR). The changes in bacterial community and composition of the fermentation products were evaluated after being ensiled for 30 days and unsealed for 1, 3, 5, and 7 days. Compared with the CK, MO and CE, the silages treated with L1, MO + L1, and CE + L1 showed higher lactic acid concentrations, lower pH values, and lower ammonia nitrogen concentrations (p < 0.05). During the first 3 days of aerobic exposure, the pH values and organic acid content changed slightly in all treatments. The present study suggests that addition of L1 was better than commercial inoculum, and the paper mulberry silages could be well preserved after being unsealed for 3 days. [ABSTRACT FROM AUTHOR]

In recent years, bamboo has been well exploited in the pulp and paper industry. Moso bamboo (Phyllostachys edulis (Carriere) J. Houzeau; hereafter M), originated from China with a long history of cultivation as the most abundant resource with the widest distribution area among bamboo plants in China. In this study, Moso bamboo (M) and nine bamboo varieties were selected in the bamboo germplasm resources storage bank of the Anhui Taiping Experimental Station of ICBR. The characteristics of their cell structures were compared, and the differences were analyzed from a genetic perspective. The results showed that M had the highest fiber cell length, fiber cell width, length, and parenchyma width, while GJ showed the lowest of these measurements [P. edulis 'Kikko-chiku',G.H.Lai]. The fiber wall thickness of Q [P. edulis f. obliquinoda (Z.P.Wang et N.X.Ma) Ohrnberger] was the smallest, while its fiber lumen diameter was the highest in the group. The parenchyma wall thickness and parenchyma lumen diameter of Q were the smallest in the group. The fiber cells of M and Q had better flexibility, which is conducive to improving the tensile strength, break resistance, and folding resistance of paper made from these materials. SY and GJ may be more suitable for ornamental items because of their special appearances. The purpose of this study was to explore the genetic variation patterns of various cell structure indicators among Moso bamboo and its varieties, as well as to develop a strategy of bamboo growing and lumbering based on the local conditions, providing reference data for the utilization of non-woody forest resources. [ABSTRACT FROM AUTHOR]

Paper mulberry (Broussonetia papyrifera) is widely ensiled to feed sheep in southwestern China, as unconventional woody forage. Feeding lambs with paper mulberry silage (PMS) may improve certain feeding characteristics, thereby affecting the growth performance and meat quality. The aim of this study is to investigate the effects of four diets of PMS on growth performance, rumen microbial composition, and muscle fatty acids profile in Hu lambs. The results showed that 30% and 40% PMS increased the dry matter intake and average daily gain of Hu lambs compared to the control group. PMS30 and PMS40 increased the content of C24:1, and PMS40 increased the content of C20:5n-3. The content of microbial protein (MCP) was higher in PMS40 than in others, but PMS30 and PMS40 reduced the total volatile fatty acid in rumen. PMS30 significantly increased the ratio of acetic acid to propionic acid. The abundance of ruminal Christensenellaceae_R-7_group and norank_f_Eubacterium_coprostanoligenes_group was significantly higher in PMS30 and PMS40 groups. Moreover, Christensenellaceae_R-7_group had a significant positive correlation with n3-polyunsaturated fatty acid. PMS40 might lead to a relatively high content of unsaturated fatty acids in longissimus dorsi muscle by increasing the relative abundance of Christensenellaceae_R-7_group in rumen. [ABSTRACT FROM AUTHOR]

With the implementation of deep-market-oriented reforms in China, an accurate interpretation of the effect and transmission mechanism of the marketization of industrial land transfer on carbon emission reduction can provide references for further elevating the role of land policy in China's low-carbon economic transition. Based on the balanced panel data of China's provincial level from 2009 to 2020, this paper uses carbon emission intensity to quantify emission reduction targets, and studies the effects of the marketization of industrial land transfer on regional carbon emission intensity, as well as its internal mechanism, by describing the typical characteristics. Moreover, this paper analyzes the moderating role of environmental governance and conducts area heterogeneity analysis. The main results show that (1) the marketization of industrial land transfer can significantly reduce regional carbon emission intensity, and the negative effect is stronger in the mid-west compared with the effect in the east. (2) Environmental governance can play a positive moderating role in the relationship between the marketization of industrial land transfer and the carbon emission intensity. (3) Industry selection is the internal mechanism by which the effect of the marketization of industrial land transfer on regional carbon emission intensity operates, and the mechanism is represented more prominently in the mid-west. The main conclusions provide inspiration for land policy regulation in relation to carbon emission reduction. China's local governments should implement specific strategies to improve the market-based operation mechanism of land, attracting industries with high energy efficiency and low carbon emissions, and strengthening the intensity of environmental governance. [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]

Paper mulberry (Broussonetia papyrifera) plants are served as a local roughage in China, and they are mostly processed as silage for ruminants. This study aimed to explore the effects of different silage additives on the chemical composition, fermentation profile, as well as the in vitro and in situ digestibility of paper mulberry (PM) silage. Four groups consisting of PM silage, three with additives and one without any additives as the control group (CON), were established. The three experimental groups with additives were set up as follows: CON with 5 × 106 CFU per gram of fresh PM weight of lactic acid bacteria (Lactobacillus plantarum) (LAB); CON with 3% fresh PM weight of molasses (MOL) added to the PM silage; and CON with both LAB and MOL added (LM). After 45 days of ensiling at 20 °C, all of the PM treatment groups increased their ash content and decreased their water-soluble carbohydrate content (p < 0.05). Meanwhile, the pH and NH3-N content of the PM silage were lower in the additive treatment groups than in the CON group (p < 0.05). Lactic acid in the LM group was the highest (p < 0.05) among the four groups, and trace amounts of butyric acid was detected only in the CON group. In vitro dry matter digestibility was similar among all groups. Results of the in situ experiment found that the effective digestibility of the PM silage dry matter, as well as the acid detergent fiber digestibility was higher in the LM group than in the CON group (p < 0.05). In conclusion, the addition of LAB, MOL, and their combination can improve PM silage fermentation and improve the in situ digestibility of dry matter and acid detergent fiber; however they do not affect in the vitro digestibility of PM silage. [ABSTRACT FROM AUTHOR]

Invasive species have had substantial impacts on global mangrove forests. Apple snails (Pomacea canaliculata) have invaded mangrove forests in China. To clarify the potential detritivorous diet of P. canaliculata, the growth and feeding indicators of invasive juvenile snails collected from mangroves in Guangzhou, China, were studied using decaying leaf litter from five mangrove species, including Acanthus ilicifolius, Acrostichum aureum, Kandelia candel, Aegiceras corniculatum, and Sonneratia apetala. The growth indicators of the survival ratio and specific growth rate were calculated by measuring the live weight of the snails and the number of dead snails after 30 days. The feeding indicator of the weight-specific daily feeding rate (WDR) was calculated by measuring the snail weight and the amount of leaf litter ingested after 120 h. A multiple-choice experiment was performed on the snails by providing the decaying leaf species together, while a no-choice experiment was performed using a single species of decaying leaf litter. The survival and specific growth ratio of P. canaliculata feeding on decaying leaf litter of A. ilicifolius were higher than those for A. aureum. The WDR values of P. canaliculata feeding on the decaying leaf litter of A. ilicifolius and S. apetala were both significantly higher than those for A. corniculatum, A. aureum, and K. candel. The lowest WDR value of P. canaliculata feeding on decaying leaf litter was observed for A. aureum in the no-choice experiment. P. canaliculata mainly fed on decaying leaf litter of A. ilicifolius and S. apetala. The phosphorous contents and ash of the decaying leaf litter positively affected the WDR values of P. canaliculata obtained in the multiple-choice and no-choice experiments. The contents of lignin, tannin, and flavonoid negatively affected the WDR values of P. canaliculata. The potential diet of invasive P. canaliculata in mangroves was closely tied to the chemical characteristics of the decaying leaf litter. P. canaliculata can invade A. ilicifolius and/or S. apetala mangroves by utilizing the debris on the mangrove ground. Understanding the potential detritivorous diet of P. canaliculata in invaded mangroves can help us to assess this species' dispersal risk and provide support for mangrove management. [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]

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]

This paper presents a bibliometric analysis of battery state estimation in electric vehicles. In this paper, a quick study is performed on the top global research contributors, funding agencies, and affiliate universities or institutes performing research on this topic while also finding the top keyword searches and top authors based on the most citations in the field of electric vehicles. Trend analysis is done by using the SCOPUS and Web of Science (WOS) databases (DB) from the period of 2000 to 2021. Battery state estimation plays a major role in the battery present state based on past experience. Battery available charge and health knowledge is a must for range estimation and helps us acknowledge if a battery is in useful condition or needs maintenance or replacement. A total of 136 documents in SCOPUS and 1311 documents in Web of Science were analyzed. Through this bibliometric analysis, we learn the top authors, country, publication journal, citation, funding agency, leading documents, research gap, and future trends in this research direction. The author Xiong Rui has the most publications, and he is working at the Beijing Institute of Technology, China. The most common institution is the Beijing Institute of Technology, and China is the most highly contributing country in this research. Most of the publications are conference types in SCOPUS DB and article types in WOS DB. The National Natural Science Foundation of China provides the most funding. The journal Energies has the most publications related to this field. The most cited works are by the authors M.A. Hannan and L.G. Lu in SCOPUS and WOS DB, respectively. A statistical analysis of the top ten countries' productivity results is also discussed. [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]

Most Penman-Monteith-Leuning (PML) evapotranspiration (ET) modeling studies are dominated by consideration of meteorological, energy, and land use information, etc., but the dynamic coupling of soil moisture content (SM), especially in terms of improving accuracy through assimilation, lacks sufficient attention. This paper proposes a research framework for the dynamic coupling simulation of PML model and SM based on data assimilation, i.e., the remote sensing monitored SM is combined with soil evaporation of PML to obtain high-precision time-continuous SM data through data assimilation; simultaneously, dynamical soil evaporation coefficients are generated based on the assimilated SM to improve the simulation accuracy of the PML model. The new scheme was validated at a typical irrigation zone in north China and showed obvious improvements in both SM and ET simulations. Moreover, the effect of the assimilation of SM on the simulation accuracy of ET for different crop growth periods is further analyzed. This research provides a new idea for the coupling simulation of the SM and PML models. [ABSTRACT FROM AUTHOR]

Landscape engineering plays a crucial role in urban construction and the development of ecological civilization in China. It actively designs and modifies natural elements, such as water and mountains, acting as the primary living infrastructure. This field continually receives great recognition and praise. Recent academic research has prioritized the use of extended reality (XR) technology to create a real-time interactive visual environment to tackle the issues presented by the dynamic nature of landscape engineering. This paper utilizes the PRISMA method to filter out 68 research documents related to XR in landscape engineering construction and management for bibliometric analysis. A comprehensive review is conducted on the precise and efficient utilization of XR to solve various issues in the field of landscape engineering. Using Cite Space 6.2.R6 (a visual bibliometric software) to visualize knowledge structures and research topics, the analysis includes temporal and spatial examination, application scenario analysis, and technological hierarchy analysis. The paper summarizes the current challenges that XR still faces in the landscape engineering field and envisions extensible application scenarios for XR, providing a reference roadmap for the implementation of XR in landscape engineering. [ABSTRACT FROM AUTHOR]

Vegetation indices provide information for various precision-agriculture practices, by providing quantitative data about crop growth and health. To provide a concise and up-to-date review of vegetation indices in precision agriculture, this study focused on the major vegetation indices with the criterion of their frequency in scientific papers indexed in the Web of Science Core Collection (WoSCC) since 2000. Based on the scientific papers with the topic of "precision agriculture" combined with "vegetation index", this study found that the United States and China are global leaders in total precision-agriculture research and the application of vegetation indices, while the analysis adjusted for the country area showed much more homogenous global development of vegetation indices in precision agriculture. Among these studies, vegetation indices based on the multispectral sensor are much more frequently adopted in scientific studies than their low-cost alternatives based on the RGB sensor. The normalized difference vegetation index (NDVI) was determined as the dominant vegetation index, with a total of 2200 studies since the year 2000. With the existence of vegetation indices that improved the shortcomings of NDVI, such as enhanced vegetation index (EVI) and soil-adjusted vegetation index (SAVI), this study recognized their potential for enabling superior results to those of NDVI in future studies. [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]

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]

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]

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]

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]

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]

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]

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]

Digital transformation is seen as an "elixir" for companies to improve their economic performance and expand their market power in the digital economy. Therefore, how does digital transformation affect enterprises' market power? This paper used machine learning to construct a digital transformation index and used panel data of listed enterprises from 2008 to 2020 to study the impact of digital transformation on market power and its mechanism of action. The findings showed that digital transformation significantly increases market power, and this conclusion still holds after considering potential endogeneity issues and conducting robustness tests. The results of mechanism analysis revealed that digital transformation facilitates endogenous scale expansion and promotes merger and acquisition (M&A), which reshapes firm boundaries and, thus, enhances market power. This paper revealed new changes in the micro-organization of enterprises in the context of digital transformation and provided micro-evidence for the industrial organization effect of digital transformation. [ABSTRACT FROM AUTHOR]

Heavy metal pollution in rivers and lakes arising due to rapid economic development has been extensively studied by various countries due to its direct impact on ecological health and human well-being. However, there is a lack of comprehensive and systematic reviews addressing the current research status of this subject. In this study, we conducted a visual metrological analysis of the literature from 2001 to 2021 using the Web of Science (WoS) and China National Knowledge Infrastructure (CNKI) citation databases. The results show that studies conducted in other countries initially outnumbered those in China; after 2010, China emerged as the foremost contributor. Furthermore, both the WoS and CNKI databases indicate active engagement of Chinese researchers through a significant proportion of published papers on metal research, with prominent contributions coming from institutions such as the Chinese Academy of Sciences (CAS) and University CAS. Nevertheless, Chinese research institutions still have relatively low total paper citation numbers and have yet to establish themselves as key players in international scientific research efforts. Additionally, core authors from different countries share substantial similarities in their research directions and focuses. Consistent research hotspots regarding heavy metals in rivers and lakes were identified across both databases, including heavy metal pollution, adsorption, human activities, water quality, and sediment. [ABSTRACT FROM AUTHOR]

This paper analyzes changes in sacrifice by burning and the space inhabited by ghosts in ancient China from philological and linguistic perspectives. During the Shang and Zhou dynasties, rulers believed that they could convey their offerings and reverence to their ancestors in heaven by burning firewood and sacrifices (尞). From the Spring and Autumn Period to the Han dynasty, the ancient Chinese metaphors for naming the underground space inhabited by ghosts experienced a transformation from a natural space (Yellow Spring (黄泉)) to human settlements (li (里), big cities (都)) and then to government institutions for criminal penalty (government (府), prisons (狱)), which symbolized the gradual establishment of a living order in the space inhabited by ghosts based on the human society. When the new living order of the space inhabited by ghosts was established, the ancient Chinese began to reconstruct sacrifice by burning during the Wei and Jin dynasties, and the objects burnt were represented by joss paper. The use of the term "transforming (化)" to refer to sacrifice by burning suggests that people believed that burning with fire was a way to transfer objects from the real world to the world of ghosts. The act of burning joss paper not only embodied the Chinese concept of ancestor worship to "treat the dead as if they were alive" but also gave "fire (火)" rich religious connotations while greatly simplifying the process and cost of sacrificial rituals, thus gradually becoming popular. [ABSTRACT FROM AUTHOR]

The point cloud segmentation method plays an important role in practical applications, such as remote sensing, mobile robots, and 3D modeling. However, there are still some limitations to the current point cloud data segmentation method when applied to large-scale scenes. Therefore, this paper proposes an adaptive clustering segmentation method. In this method, the threshold for clustering points within the point cloud is calculated using the characteristic parameters of adjacent points. After completing the preliminary segmentation of the point cloud, the segmentation results are further refined according to the standard deviation of the cluster points. Then, the cluster points whose number does not meet the conditions are further segmented, and, finally, scene point cloud data segmentation is realized. To test the superiority of this method, this study was based on point cloud data from a park in Guilin, Guangxi, China. The experimental results showed that this method is more practical and efficient than other methods, and it can effectively segment all ground objects and ground point cloud data in a scene. Compared with other segmentation methods that are easily affected by parameters, this method has strong robustness. In order to verify the universality of the method proposed in this paper, we test a public data set provided by ISPRS. The method achieves good segmentation results for multiple sample data, and it can distinguish noise points in a scene. [ABSTRACT FROM AUTHOR]

The Gaokao, also known as China's national college entrance exam, is a high-stakes exam for nearly all Chinese students. English has been one of the three most important subjects for a long time, and listening plays an important role in the Gaokao English test. However, relatively little research has been conducted on local versions of Gaokao's English listening tests. This study analyzed the linguistic features and corresponding functional dimensions of the three different text types in the Gaokao's listening test, investigating whether the papers used in three major regions of China were differentiated in terms of the co-occurrence patterns of lexicogrammatical features and dimensions of the transcripts. A corpus consisting of 170 sets of test papers (134,913 words) covering 31 provinces and cities from 2000 to 2022 was analyzed using a multidimensional analysis wherein six exclusive dimensions were extracted. The results showed that there were meaningful differences across short conversations, long conversations, and monologues with regard to the six dimensions' scores, and regions further had significant differences in three dimensions: Syntactic and Clausal Complexity, Oral versus Literate Discourse, and Procedural Discourse, while Time Period was not associated with any differences. Implications for language teaching and assessment are discussed. [ABSTRACT FROM AUTHOR]

Soil hydraulic properties significantly affect the occurrence and development of collapsing gully walls. The effect of temperature on the hydraulic properties of soil in collapsing gully walls remains unclear. In this study, the hydraulic properties of the red soil layer, the sandy soil layer and the detritus layer in a collapsing gully wall were investigated using the filter paper method, and the soil water retention curves of the different soil layers at 25 and 40 °C were determined. The aim of this study was to investigate the impact of temperature on the soil hydraulic properties of different soil layers in collapsing gully walls. The study found that when the water content in the red soil layer and sandy soil layer exceeded 20% and in the detritus layer exceeded 10%, the soil's matric suction significantly decreased as the temperature increased from 25 to 40 °C. Additionally, the parameters of θ s , α , n and m all exhibited a decreasing trend, and the soil water content in the detritus layer was primarily influenced by the temperature change, which resulted in a decrease of 38.10%. The unsaturated hydraulic conductivity of the detritus layer exhibited higher values than that of the sandy layer and red soil layer under identical temperature conditions. Moreover, the unsaturated hydraulic conductivity of the red soil layer, sandy soil layer and detritus layer increased with increasing temperature. It was observed that the unsaturated hydraulic conductivity of the detritus layer increased by 0.18 cm h−1 at a soil water content of 44%. This increase in conductivity was more pronounced than the corresponding changes in the red soil layer and sandy soil layer. An elevated temperature caused the water-holding capacity of the different soil layers of the collapsing gully wall to decrease and the unsaturated hydraulic conductivity to increase. However, the influence of the clay particle content within the soil of the collapsing gully wall rendered the temperature effect more distinct. Therefore, the destabilizing deformation of the soil in the collapsing gully wall during the summer under high temperatures and precipitation may have played a key role in its collapse. [ABSTRACT FROM AUTHOR]

Handwriting is a biometric behavioral characteristic with evident individual distinctiveness. With the rise of the deep learning trend and demands for forensic identification, handwriting identification has become one of the focal points of research in the field of pattern recognition. Research in handwriting identification for major global languages has matured. However, in China, there is limited attention in the field of writer identification for minority languages such as Mongolian, making it challenging to resolve criminal cases involving handwriting issues. This paper initiates an initial exploration of Mongolian handwriting identification by constructing a structurally simple convolutional neural network. This convolutional neural network, consisting of 12 convolution operations and designed for Mongolian handwriting identification, is referred to as MWInet-12. In this paper, the model evaluation experiments were conducted using a dataset comprising 156,372 samples contributed by 125 writers from the MOLHW dataset. The dataset was divided into training, validation, and test sets in an 8:1:1 ratio. The final results of the experiments reveal impressive accuracy on the test set, achieving a top-1 accuracy of 89.60% and a top-5 accuracy of 97.53%. Furthermore, through comparative experiments involving Resnet50, Fragnet, GRRNN, VGG16, and VGG19 models, this paper establishes that the proposed model yields the most favorable results for Mongolian handwriting identification. The exploratory research on Mongolian handwriting identification in this paper contributes to increasing awareness of information processing for minority languages. It aids in advancing research on classifying writers of Mongolian historical texts and provides technical support for judicial authentication involving handwriting issues. [ABSTRACT FROM AUTHOR]

Short-term power load forecasting is of great significance for the reliable and safe operation of power systems. In order to improve the accuracy of short-term load forecasting, for the problems of random fluctuation in load and the complexity of load-influencing factors, this paper proposes a two-stage short-term load forecasting method, SSA–VMD-LSTM-MLR-FE (SVLM–FE) based on sparrow search algorithm (SSA), to optimize variational mode decomposition (VMD) and feature engineering (FE). Firstly, an evaluation criterion on the loss of VMD decomposition is proposed, and SSA is used to find the optimal combination of parameters for VMD under this criterion. Secondly, the first stage of forecasting is carried out, and the different components obtained from SSA–VMD are predicted separately, with the high-frequency components input to a long short-term memory network (LSTM) for forecasting and the low-frequency components input to a multiple linear regression model (MLR) for forecasting. Finally, the forecasting values of the components obtained in the first stage are input to the second stage for error correction; factors with a high degree of influence on the load are selected using the Pearson correlation coefficient (PCC) and maximal information coefficient (MIC), and the load value at the moment that has a great influence on the load value at the time to be predicted is selected using autocorrelation function (ACF). The forecasting values of the components are fused with the selected feature values to construct a vector, which is fed into the fully connected layer for forecasting. In this paper, the performance of SVLM–FE is evaluated experimentally on two datasets from two places in China. In Place 1, the RMSE, MAE, and MAPE are 128.169 MW, 102.525 MW, and 1.562%, respectively; in Place 2, the RMSE, MAE, and MAPE are 111.636 MW, 92.291 MW, and 1.426%, respectively. The experimental results show that SVLM–FE has high accuracy and stability. [ABSTRACT FROM AUTHOR]

Blueberries have high nutritional and economic value and are easy to cultivate, so they are common fruit crops in China. There is a high demand for blueberry in domestic and foreign markets, and various technologies have been used to extend the supply cycle of blueberry to about 7 months. However, blueberry grows in clusters, and a cluster of fruits generally contains fruits of different degrees of maturity, which leads to low efficiency in manually picking mature fruits, and at the same time wastes a lot of manpower and material resources. Therefore, in order to improve picking efficiency, it is necessary to adopt an automated harvesting mode. However, an accurate maturity detection model can provide a prerequisite for automated harvesting technology. Therefore, this paper proposes a blueberry ripeness detection model based on enhanced detail feature and content-aware reassembly. First of all, this paper designs an EDFM (Enhanced Detail Feature Module) that improves the ability of detail feature extraction so that the model focuses on important features such as blueberry color and texture, which improves the model's ability to extract blueberry features. Second, by adding the RFB (Receptive Field Block) module to the model, the lack of the model in terms of receptive field can be improved, and the calculation amount of the model can be reduced at the same time. Then, by using the Space-to-depth operation to redesign the MP (MaxPool) module, a new MP-S (MaxPool–Space to depth) module is obtained, which can effectively learn more feature information. Finally, an efficient upsampling method, the CARAFE (Content-Aware Reassembly of Features) module, is used, which can aggregate contextual information within a larger receptive field to improve the detection performance of the model. In order to verify the effectiveness of the method proposed in this paper, experiments were carried out on the self-made dataset "Blueberry—Five Datasets" which consists of data on five different maturity levels of blueberry with a total of 10,000 images. Experimental results show that the mAP (mean average precision) of the proposed network reaches 80.7%, which is 3.2% higher than that of the original network, and has better performance than other existing target detection network models. The proposed model can meet the needs of automatic blueberry picking. [ABSTRACT FROM AUTHOR]