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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.

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.

Highly cited papers in the Essential Science Indicators database refer to papers with citations in the top 1% of all papers in a research field, and they are considered to be symbols of scientific excellence and top performance of the past ten years. This study provided an informetric analysis of 7791 highly cited papers in the environmental sciences category during 2009-2019. Informetric indicators and visualization tools were applied to evaluate and present the performances of journals, countries/territories, institutions, top cited papers, and research hotspots. The results showed that the cumulative number of publications has increased exponentially, suggesting strong development of the environmental sciences category. There were 211 journals publishing highly cited papers, with Energy & Environmental Science as the leading journal. The USA ranked first with the highest number of publications and occupied the core position in the collaboration network, while Mainland China took the first place in independent research output. Review articles have an obvious advantage in terms of achieving high citations. "Adsorption", "climate change", and "heavy metal" were the most frequent keywords, with "microplastic" rising rapidly as a new research frontier in recent years. Five research hotspots were visualized from highly cited papers via cluster analysis., Competing Interests: The authors declare no conflict of interest.

Corn, as one of the three major grain crops in China, plays a crucial role in ensuring national food security through its yield and quality. With the advancement of agricultural intelligence, agricultural robot technology has gained significant attention. High-precision navigation is the basis for realizing various operations of agricultural robots in corn fields and is closely related to the quality of operations. Corn leaf and stalk recognition and ranging are the prerequisites for achieving high-precision navigation and have attracted much attention. This paper proposes a corn leaf and stalk recognition and ranging algorithm based on multi-sensor fusion. First, YOLOv8 is used to identify corn leaves and stalks. Considering the large differences in leaf morphology and the large changes in field illumination that lead to discontinuous identification, an equidistant expansion polygon algorithm is proposed to post-process the leaves, thereby increasing the average recognition completeness of the leaves to 86.4%. Secondly, after eliminating redundant point clouds, the IMU data are used to calculate the confidence of the LiDAR and depth camera ranging point clouds, and point cloud fusion is performed based on this to achieve high-precision ranging of corn leaves. The average ranging error is 2.9 cm, which is lower than the measurement error of a single sensor. Finally, the stalk point cloud is processed and clustered using the FILL-DBSCAN algorithm to identify and measure the distance of the same corn stalk. The algorithm combines recognition accuracy and ranging accuracy to meet the needs of robot navigation or phenotypic measurement in corn fields, ensuring the stable and efficient operation of the robot in the corn field.

Bibliometric analysis is a rigorous method to analyze significant quantities of bibliometric data to assess their impact on a particular field. This study used bibliometric analysis to investigate the academic research on diabetes detection and classification from 2000 to 2023. The PRISMA 2020 framework was followed to identify, filter, and select relevant papers. This study used the Web of Science database to determine relevant publications concerning diabetes detection and classification using the keywords "diabetes detection", "diabetes classification", and "diabetes detection and classification". A total of 863 publications were selected for analysis. The research applied two bibliometric techniques: performance analysis and science mapping. Various bibliometric parameters, including publication analysis, trend analysis, citation analysis, and networking analysis, were used to assess the performance of these articles. The analysis findings showed that India, China, and the United States are the top three countries with the highest number of publications and citations on diabetes detection and classification. The most frequently used keywords are machine learning, diabetic retinopathy, and deep learning. Additionally, the study identified "classification", "diagnosis", and "validation" as the prevailing topics for diabetes identification. This research contributes valuable insights into the academic landscape of diabetes detection and classification.

Wild desert grasslands are characterized by diverse habitats, uneven plant distribution, similarities among plant class, and the presence of plant shadows. However, the existing models for detecting plant species in desert grasslands exhibit low precision, require a large number of parameters, and incur high computational cost, rendering them unsuitable for deployment in plant recognition scenarios within these environments. To address these challenges, this paper proposes a lightweight and fast plant species detection system, termed YOLOv8s-KDT, tailored for complex desert grassland environments. Firstly, the model introduces a dynamic convolutional KernelWarehouse method to reduce the dimensionality of convolutional kernels and increase their number, thus achieving a better balance between parameter efficiency and representation ability. Secondly, the model incorporates triplet attention into its feature extraction network, effectively capturing the relationship between channel and spatial position and enhancing the model's feature extraction capabilities. Finally, the introduction of a dynamic detection head tackles the issue related to target detection head and attention non-uniformity, thus improving the representation of the target detection head while reducing computational cost. The experimental results demonstrate that the upgraded YOLOv8s-KDT model can rapidly and effectively identify desert grassland plants. Compared to the original model, FLOPs decreased by 50.8%, accuracy improved by 4.5%, and mAP increased by 5.6%. Currently, the YOLOv8s-KDT model is deployed in the mobile plant identification APP of Ningxia desert grassland and the fixed-point ecological information observation platform. It facilitates the investigation of desert grassland vegetation distribution across the entire Ningxia region as well as long-term observation and tracking of plant ecological information in specific areas, such as Dashuikeng, Huangji Field, and Hongsibu in Ningxia.

The global COVID-19 pandemic in 2020 required risk communications to mitigate the virus' spread. However, social media not only conveyed health information to minimize the contagion, but also distracted from the threat by linking it to an externalized 'other'-primarily those appearing to be of Chinese descent. This disinformation caused the attribution of blame to Chinese people worldwide. In Canada's Greater Toronto Area, Chinese individuals reported widespread public stigma that compounded their risk of contagion; to the degree that it was driven by cognitive dissonance, it generated experiences of social and cultural vulnerability. In this paper, we draw on the aforementioned study's findings to explain how the risk perception and threat appraisal of Chinese diaspora individuals were impacted by different cognitive dissonance pathways. These findings explore how storytelling is a viable intervention with which to target and mitigate cognitive dissonance. Indeed, the mechanisms of cognitive dissonance can modify risk perception and mitigate social and cultural vulnerability, thereby averting potential long-term negative consequences for one's mental health and well-being. We hope our guidance, training educators to target pathways of cognitive dissonance by drawing on storytelling (with humour), can assist them to better convey information in ways that are more inclusive during public health emergencies.

During the first wave of the COVID-19 pandemic, immigrants were among the most socially vulnerable in Western countries. The Chinese diaspora in Canada were one such group due to the widespread cultural stigma surrounding their purported greater susceptibility to transmit and become infected by COVID-19. This paper aims to understand the social vulnerability of the Chinese diaspora in the Greater Toronto Area, Canada, during the first wave of COVID-19 from an explanation of their risk perception and threat appraisal of risk communication. We conducted secondary data analysis of 36 interviews using critical realism. The participants self-identified as being of Chinese descent. The results were used to develop a model of how social vulnerability occurred. In brief, cognitive dissonance was discovered to generate conflicts of one's cultural identity, shaped by social structures of (i) stigma of contagion, (ii) ethnic stigma, and (iii) public sentiment, and mediated by participants' threat appraisal and (iv) self-reliance. We assert that risk communicators need to consider their audiences' diverse socialization in crafting messages to modify behaviors, create a sense of responsibility, and mitigate public health threats. A lack of awareness of one's cognitive dissonance driven by cultural vulnerability may heighten their social vulnerability and prevent them from taking action to protect themself from high-risk events.

Tumors have a huge impact on human life and are now the main cause of disease-related deaths. The main means of treatment are surgery and radiotherapy, but they are more damaging to the organism and have a poor postoperative prognosis. Therefore, we urgently need safe and effective drugs to treat tumors. In recent years, Chinese herbal medicines have been widely used in tumor therapy as complementary and alternative therapies. Medicinal and edible herbs are popular and have become a hot topic of research, which not only have excellent pharmacological effects and activities, but also have almost no side effects. Therefore, as a typical medicine and food homology, some components of Paeoniae Radix Alba (PRA, called Baishao in China) have been shown to have good efficacy and safety against cancer. Numerous studies have also shown that Paeoniae Radix Alba and its active ingredients treat cancer through various pathways and are also one of the important components of many antitumor herbal compound formulas. In this paper, we reviewed the literature on the intervention of Paeoniae Radix Alba in tumors and its mechanism of action in recent years and found that there is a large amount of literature on its effect on total glucosides of paeony (TGP) and paeoniflorin (PF), as well as an in-depth discussion of the mechanism of action of Paeoniae Radix Alba and its main constituents, with a view to promote the clinical development and application of Paeoniae Radix Alba in the field of antitumor management.

Taxus mairei (Lemée and H.Lév.) S.Y.Hu, indigenous to the southern regions of China, is an evergreen tree belonging to the genus Taxus of the Taxaceae family. Owing to its content of various bioactive compounds, it exhibits multiple pharmacological activities and has been widely applied in clinical medicine. This article comprehensively discusses the current state of cultivation, chemical constituents, applications in the pharmaceutical field, and the challenges faced by T. mairei. The paper begins by detailing the ecological distribution of T. mairei , aiming to provide an in-depth understanding of its origin and cultivation overview. In terms of chemical composition, the article thoroughly summarizes the extracts and monomeric components of T. mairei , unveiling their pharmacological activities and elucidating the mechanisms of action based on the latest scientific research, as well as their potential as lead compounds in new drug development. The article also addresses the challenges in the T. mairei research, such as the difficulties in extracting and synthesizing active components and the need for sustainable utilization strategies. In summary, T. mairei is a rare species important for biodiversity conservation and demonstrates significant research and application potential in drug development and disease treatment.

Traditional Chinese medicine (TCM) is a class of natural drugs with multiple components and significant therapeutic effects through multiple targets. It also originates from a wide range of sources containing plants, animals and minerals, and among them, plant-based Chinese medicine also includes fungi. Fungal traditional Chinese medicine is a medicinal resource with a long history and widespread application in China. Accumulating evidence confirms that polysaccharide is the main pharmacodynamic material on which fungal TCM is based. The purpose of the current systematic review is to summarize the extraction, isolation, structural identification, biological functions, quality control and medicinal and edible applications of polysaccharides from fungal TCM in the past three years. This paper will supplement and deepen the understanding and application of polysaccharides from fungal TCM, and propose some valuable insights for further research and development of drugs and functional foods.

Eucommia ulmoides Oliver. ( E. ulmoides ) is a species of small tree native to China. It is a valuable medicinal herb that can be used to treat Alzheimer's disease, diabetes, hypertension, and other diseases. In addition, E. ulmoides is a source of rubber. It has both medicinal and ecological value. As ecological problems become increasingly prominent, accurate information on the cultivated area of E. ulmoides is important for understanding the carbon sequestration capacity and ecological suitability zoning of E. ulmoides . In previous tree mapping studies, no studies on the spectral characteristics of E. ulmoides and its remote sensing mapping have been seen. We use Ruyang County, Henan Province, China, as the study area. Firstly, using the 2021 Gao Fen-6 (GF-6) Wide Field of View (WFV) time series images covering the different growth stages of E. ulmoides based on the participation of red-edge bands, several band combination schemes were constructed. The optimal time window to identify E. ulmoides was selected by calculating the separability of E. ulmoides from other land cover types for different schemes. Secondly, a random forest algorithm based on several band combination schemes was investigated to map the E. ulmoides planting areas in Ruyang County. Thirdly, the annual NPP values of E. ulmoides were estimated using an improved Carnegie Ames Stanford Approach (CASA) to a light energy utilization model, which, in turn, was used to assess the carbon sequestration capacity. Finally, the ecologically suitable distribution zone of E. ulmoides under near current and future (2041-2060) climatic conditions was predicted using the MaxEnt model. The results showed that the participation of the red-edge band of the GF-6 data in the classification could effectively improve the recognition accuracy of E. ulmoides , making its overall accuracy reach 96.62%; the high NPP value of E. ulmoides was mainly concentrated in the south of Ruyang County, with a total annual carbon sequestration of 540.104835 t CM -2 ·a -1 . The ecological suitability zone of E. ulmoides can be divided into four classes: unsuitable area, low suitable area, medium suitable area, and high suitable area. The method proposed in this paper applies to the real-time monitoring of E. ulmoides , highlighting its potential ecological value and providing theoretical reference and data support for the reasonable layout of E. ulmoides .

The objective of this study is to estimate the extra costs of living associated with chronic health conditions and disabilities in China. Leveraging the 2018 China Health and Retirement Longitudinal Study involving 13,530 respondents aged 50 and over, we apply both an ordinary least squares linear regression model and a logistic model to analyze the correlation between medical out-of-pocket expenditures (OOPEs) and chronic health conditions, as well as disabilities measured by Activities of Daily Living (ADL) and Instrumental Activities of Daily Living (IADL) limitations. This paper bridges the gap in the literature on OOPEs and their association with disabilities and chronic health conditions, respectively. We find that ADL limitations, IADL limitations, and chronic health conditions are consistently associated with higher OOPEs. The odds that older persons with disabilities and chronic health conditions incur OOPEs are two to three times higher than for persons without disabilities and chronic health conditions, respectively. Persons with disabilities and chronic health conditions have the highest OOPEs. The findings suggest that more policy and research attention is necessary to improve the financial protection of those with chronic health conditions and disabilities, including through access to comprehensive health insurance coverage.

Portulaca oleracea L. (purslane) is a widely distributed plant with a long history of cultivation and consumption. Notably, polysaccharides obtained from purslane exhibit surprising and satisfactory biological activities, which explain the various benefits of purslane on human health, including anti-inflammatory, antidiabetic, antitumor, antifatigue, antiviral and immunomodulatory effects. This article systematically reviews the extraction and purification methods, chemical structure, chemical modification, biological activity and other aspects of polysaccharides from purslane collected in the Chinese Pharmacopoeia, Flora of China, Web of Science, PubMed, Baidu Scholar, Google Scholar and CNKI databases in the last 14 years, using the keywords " Portulaca oleracea L. polysaccharides" and "purslane polysaccharides". The application of purslane polysaccharides in different fields is also summarized, and its application prospects are also discussed. This paper provides an updated and deeper understanding of purslane polysaccharides, which will provide useful guidance for the further optimization of polysaccharide structures and the development of purslane polysaccharides as a novel functional material, as well as a theoretical basis for its further research and application in human health and manufacturing development.

Microtremor recording tests using an accelerometer were carried out in this paper with the aim of characterizing the effects of seasonally frozen soil on the seismic site response, including the two-direction microtremor spectrum, site predominant frequency, and site amplification factor. The study selected eight typical seasonal permafrost sites in China for site microtremor measurements during both summer and winter seasons. Based on the recorded data, the horizontal and vertical components of the microtremor spectrum, HVSR curves, site predominant frequency, and site amplification factor were calculated. The results showed that seasonally frozen soil increased the predominant frequency of the horizontal component of the microtremor spectrum, while the effect on the vertical component was less noticeable. It indicates that the frozen soil layer has a significant impact on the propagation path and energy dissipation of seismic waves in the horizontal direction. Furthermore, the peak values of the horizontal and vertical components of the microtremor spectrum decreased by 30% and 23%, respectively, due to the presence of seasonally frozen soil. The predominant frequency of the site increased by a maximum of 35% and a minimum of 2.8%, while the amplification factor decreased by a maximum of 38% and a minimum of 11%. Additionally, a relationship between the increased site predominant frequency and the cover thickness was proposed.

The China Society of Explosives and Blasting required a larger than 20% annual increase in the national use of digital electronic detonators since 2018. So, this article conducted a large number of on-site tests and then used the Hilbert-Huang Transform method to analyze and compare the vibration signals of digital electronic and nonel detonators during the excavation process of minor cross-sectional rock roadways from the perspective of time, frequency, and energy. Then, through vibration energy analysis, identification of actual delay time, and formula derivation, it was proved that the delay time error of the detonator can control vibration wave random interference and reduce vibration. The analysis results showed that when using a segmented simultaneous blasting network for excavation in small-sectioned rock tunnels, nonel detonators may provide more excellent protection to structures than digital electronic detonators. In the same segment, the timing error of nonel detonators produces a vibration wave with a random superposition damping effect, resulting in an average vibration reduction of 19.4% per segment compared to digital electronic detonators. However, digital electronic detonators are superior to nonel detonators for the fragmentation effect on rock. The research conducted in this paper has the potential to facilitate a more rational and comprehensive promotion of digital electronic detonators in China.

Schisandra henryi (Schisandraceae) is a plant species endemic to Yunnan Province in China and is little known in Europe and America. To date, few studies, mainly performed by Chinese researchers, have been conducted on S. henryi . The chemical composition of this plant is dominated by lignans (dibenzocyclooctadiene, aryltetralin, dibenzylbutane), polyphenols (phenolic acids, flavonoids), triterpenoids, and nortriterpenoids. The research on the chemical profile of S. henryi showed a similar chemical composition to S. chinensis -a globally known pharmacopoeial species with valuable medicinal properties whichis the best-known species of the genus Schisandra. The whole genus is characterized by the presence of the aforementioned specific dibenzocyclooctadiene lignans, known as "Schisandra lignans". This paper was intended to provide a comprehensive review of the scientific literature published on the research conducted on S. henryi , with particular emphasis on the chemical composition and biological properties. Recently, a phytochemical, biological, and biotechnological study conducted by our team highlighted the great potential of S. henryi in in vitro cultures. The biotechnological research revealed the possibilities of the use of biomass from S. henryi as an alternative to raw material that cannot be easily obtained from natural sites. Moreover, the characterization of dibenzocyclooctadiene lignans specific to the Schisandraceae family was provided. Except for several scientific studies which have confirmed the most valuable pharmacological properties of these lignans, hepatoprotective and hepatoregenerative, this article also reviews studies that have confirmed the anti-inflammatory, neuroprotective, anticancer, antiviral, antioxidant, cardioprotective, and anti-osteoporotic effects and their application for treating intestinal dysfunction.

This paper presents a new broadband ocean bottom seismograph (OBS) developed by the SUSTech OBS lab for passive-source seafloor seismic observations. This instrument, called Pankun, has several key features that set it apart from traditional OBS instruments. In addition to the seismometer-separated scheme, these features include a unique shielding structure to minimize current-induced noise, a compact gimbal for accurate leveling, and low power consumption for extended operation on the seafloor. The design and testing of Pankun's primary components are thoroughly described in this paper. The instrument has been successfully tested in the South China Sea, demonstrating its ability to record high-quality seismic data. The anti-current shielding structure of Pankun OBS has the potential to improve low-frequency signals, particularly on the horizontal components, in seafloor seismic data.

Bone age assessment (BAA) is a typical clinical technique for diagnosing endocrine and metabolic diseases in children's development. Existing deep learning-based automatic BAA models are trained on the Radiological Society of North America dataset (RSNA) from Western populations. However, due to the difference in developmental process and BAA standards between Eastern and Western children, these models cannot be applied to bone age prediction in Eastern populations. To address this issue, this paper collects a bone age dataset based on the East Asian populations for model training. Nevertheless, it is laborious and difficult to obtain enough X-ray images with accurate labels. In this paper, we employ ambiguous labels from radiology reports and transform them into Gaussian distribution labels of different amplitudes. Furthermore, we propose multi-branch attention learning with ambiguous labels network (MAAL-Net). MAAL-Net consists of a hand object location module and an attention part extraction module to discover the informative regions of interest (ROIs) based only on image-level labels. Extensive experiments on both the RSNA dataset and the China Bone Age (CNBA) dataset demonstrate that our method achieves competitive results with the state-of-the-arts, and performs on par with experienced physicians in children's BAA tasks.

Since the outbreak of the COVID-19 pandemic, Fangcang shelter hospitals have been built and operated in several cities, and have played a huge role in epidemic prevention and control. How to use medical resources effectively in order to maximize epidemic prevention and control is a big challenge that the government should address. In this paper, a two-stage infectious disease model was developed to analyze the role of Fangcang shelter hospitals in epidemic prevention and control, and examine the impact of medical resources allocation on epidemic prevention and control. Our model suggested that the Fangcang shelter hospital could effectively control the rapid spread of the epidemic, and for a very large city with a population of about 10 million and a relative shortage of medical resources, the model predicted that the final number of confirmed cases could be only 3.4% of the total population in the best case scenario. The paper further discusses the optimal solutions regarding medical resource allocation when medical resources are either limited or abundant. The results show that the optimal allocation ratio of resources between designated hospitals and Fangcang shelter hospitals varies with the amount of additional resources. When resources are relatively sufficient, the upper limit of the proportion of makeshift hospitals is about 91%, while the lower limit decreases with the increase in resources. Meanwhile, there is a negative correlation between the intensity of medical work and the proportion of distribution. Our work deepens our understanding of the role of Fangcang shelter hospitals in the pandemic and provides a reference for feasible strategies by which to contain the pandemic.

Cannabis ( Cannabis sativa L.) is an ancient cultivated plant that contains less than 0.3% tetrahydrocannabinol (THC). It is widely utilized at home and abroad and is an economic crop with great development and utilization value. There are 31 countries legalizing industrial cannabis cultivation. Cannabis fiber has been used for textile production in China for 6000 years. China is the largest producer and exporter of cannabis. China may still play a leading role in the production of cannabis fiber. China has a long history of cannabis cultivation and rich germplasm resources. Yunnan, Heilongjiang, and Jilin are three Chinese provinces where industrial cannabis can be grown legally. Cannabinoids are terpenoid phenolic compounds produced during the growth, and which development of cannabis and are found in the glandular hairs of female flowers at anthesis. They are the active chemical components in the cannabis plant and the main components of cannabis that exert pharmacological activity. At the same time, research in China on the use of cannabis in the food industry has shown that industrial cannabis oil contains 13-20% oleic acid, 40-60% omega-6 linoleic acid, and 15-30% omega-3 α-linolenic acid. At present, more than 100 cannabinoids have been identified and analyzed in China, among which phenolic compounds are the main research objects. For instance, phenolic substances represented by cannabidiol (CBD) have rich pharmacological effects. There are still relatively little research on cannabinoids, and a comprehensive introduction to research progress in this area is needed. This paper reviews domestic and foreign research progress on cannabinoids in cannabis sativa, which is expected to support cannabis-related research and development.

Dragon fruit is one of the most popular fruits in China and Southeast Asia. It, however, is mainly picked manually, imposing high labor intensity on farmers. The hard branches and complex postures of dragon fruit make it difficult to achieve automated picking. For picking dragon fruits with diverse postures, this paper proposes a new dragon fruit detection method, not only to identify and locate the dragon fruit, but also to detect the endpoints that are at the head and root of the dragon fruit, which can provide more visual information for the dragon fruit picking robot. First, YOLOv7 is used to locate and classify the dragon fruit. Then, we propose a PSP-Ellipse method to further detect the endpoints of the dragon fruit, including dragon fruit segmentation via PSPNet, endpoints positioning via an ellipse fitting algorithm and endpoints classification via ResNet. To test the proposed method, some experiments are conducted. In dragon fruit detection, the precision, recall and average precision of YOLOv7 are 0.844, 0.924 and 0.932, respectively. YOLOv7 also performs better compared with some other models. In dragon fruit segmentation, the segmentation performance of PSPNet on dragon fruit is better than some other commonly used semantic segmentation models, with the segmentation precision, recall and mean intersection over union being 0.959, 0.943 and 0.906, respectively. In endpoints detection, the distance error and angle error of endpoints positioning based on ellipse fitting are 39.8 pixels and 4.3°, and the classification accuracy of endpoints based on ResNet is 0.92. The proposed PSP-Ellipse method makes a great improvement compared with two kinds of keypoint regression method based on ResNet and UNet. Orchard picking experiments verified that the method proposed in this paper is effective. The detection method proposed in this paper not only promotes the progress of the automatic picking of dragon fruit, but it also provides a reference for other fruit detection.

As a substitute for banned brominated flame retardants (BFRs), the use of organophosphate esters (OPEs) increased year by year with the increase in industrial production and living demand. It was inevitable that OPEs would be discharged into wastewater in excess, which posed a great threat to the health of human beings and aquatic organisms. In the past few decades, people used various methods to remove refractory OPEs. This paper reviewed the photocatalysis method, the adsorption method with wide applicability, and the biological method mainly relying on enzymolysis and hydrolysis to degrade OPEs in water. All three of these methods had the advantages of high removal efficiency and environmental protection for various organic pollutants. The degradation efficiency of OPEs, degradation mechanisms, and conversion products of OPEs by three methods were discussed and summarized. Finally, the development prospects and challenges of OPEs' degradation technology were discussed.

With the rapid development of urbanization, land cover, and land use patterns have greatly changed in China, which has damaged the landscape structure, affected the energy balance and material flow within the system, and reduced the value of ecosystem services. The construction of landscape ecological security patterns could promote species exchange between biological groups and increase material and energy exchange between landscape elements. Few studies have focused on the randomness of species to migration path, thus failing to objectively reflect the process of species migration and diffusion. Therefore, circuit theory was used in this study to better match the random selection of migration paths by species. In this paper, 14 typical mammal species from the Dawen River basin of the lower Yellow River in China were selected as examples, and the conclusions were as follows: (1) The ecological sources of the Dawen River basin were 49, with forest land and lakes as the main sources, and they were crucial to the stability of the regional ecological security pattern. A total of 128 ecological corridors were identified, among which 83 were key corridors and the rest were potential corridors. The key corridors throughout the whole region need priority protection and can be used as a core area for the observation and monitoring of natural resources. (2) Based on the circuit principle, 32 pinch points and 21 barrier points were identified, indicating that regional habitat connectivity must be further improved. (3) Four types of zones were determined, and optimization measures were proposed. (4) On the basis of conceptual protection, the ecological protection network of the Dawen River basin was built to enhance ecological resilience. The landscape ecological security pattern of the Dawen River basin was constructed from the three levels of points, corridors, and areas. Based on the concept of regional ecological security, a resource optimization strategy for ecological security patterns was proposed, which is significant for maintaining the integrity of watershed ecosystems.

The paper presents the content of six metals (Cd, Cr, Cu, Ni, Pb, and Zn) in the soils of the southern slope of Jaworzyna Krynicka in Poland. Soil samples were collected in polygons, starting from an altitude of 500 m above sea level and ending at an altitude of 1100 m above sea level. Ten soil samples were collected in each polygon. The polygons were set at every 100 m of absolute altitude. The selected research area is an important natural area. The fertile mountain beech forests located there are the most important forest communities in the mountain areas of Poland. They are valuable habitats for plants and animals (especially for large predatory mammals). Every year, numerous tourists and health resort patients visit this place. The results of the research showed that soil contamination in the study area is not high, in particular for altitudes of 500 and 900 m above sea level. At these altitudes, the contents of Cd, Cr, Cu, Ni, Pb, and Zn were similar to the concentrations of these metals in uncontaminated soils. The tests carried out showed very low cadmium content for all absolute altitudes. Zinc, the concentrations of which exceeded natural values, showed the highest content in the tested soils. All the metals tested showed a common tendency of increases in their content in the soils of Jaworzyna Krynicka up to 800 m above sea level. From an altitude of 900 m above sea level, the content of these metals decreased, except for Pb. Only Pb concentrations in Jaworzyna Krynicka soils also increased with the increasing altitude. The research significance of this work is that it is important for assessing the ecological balance in the selected area.

Under pressure from the environment and resources, emission peak and carbon neutrality have rapidly become a global issue. The optimization of the ecological goal should be in line with the energy target. In most instances, however, the economic and the ecological goals cannot be unified. This paper establishes a multi-objective optimization model that maximizes the economic benefit of enterprises and the ecosystem activity of the government in the meantime. The idea point method is used in solving this multi-objective optimization problem in the form of a single-objective optimization problem. The numerical experiment documents four types of Chinese enterprises, which are primary resources, industrial manufacturing, public services and commercial consumption. Some management insights are summarized at the end, such as the cores of achieving high-quality and low-carbon development are industrial manufacturing and public services in China.

Land consolidation structure reflects land consolidation function, and studies about its spatio-temporal change and driving mechanism can serve for regional management and control land consolidation. At present, the analysis of regional differences, time changes, and driving factors of land consolidation type structure change is relatively lacking. Based on the data of provincial acceptance projects from 2000 to 2014, this paper analyzes the spatio-temporal change of rural land consolidation type structure in China, discusses the impact of relevant policies, and identifies the socio-economic driving factors in key regions by employing correlation analysis and the PLSR (partial least squares regression) method. The results showed that from 2000 to 2014, the proportional increase of land arrangement in China was significantly correlated with the proportional decrease of land reclamation (R 2 = 0.93), and the proportional decrease of land development (R 2 = 0.99) showed an obvious co-evolution pattern of increase and decrease; TI LC (The area of land development/The area of land arrangement) decreased from 2.14 to 0.91 in 2002-2003. Since 2003, the dominant type of land consolidation in China has gradually changed from land development to land arrangement. However, the proportion of land development in QT (Qinghai-Tibet), JY (Jin-Yu), and FGH (Fujian-Guangdong-Hainan) areas is still more than 40%; the change of land consolidation type structure was influenced by policies, social and economic factors, such as urbanization rate, fixed assets investment, industrial proportion, and population density, and the regional difference was significant: the eastern section (JZS, Jiangsu-Zhejiang-Shanghai) is the industry proportion, the central area (HHAJ, Hunan-Hubei-Anhui-Jiangxi) is grain production and fixed assets investment, the western region (NW, Northwest China) has the urbanization rate, grain production, population density, and fixed assets investment. Land consolidation structure should be configured differentially in each region based on the identification of regional function orientation and comprehensive consideration of regional resource endowment and development needs and directions to improve the efficiency of land consolidation.

It is very important to seek a sustainable improvement in human well-being under a limited resource supply and to promote the scientific and coordinated development of urban economic development, ecological environment protection, and human well-being. This paper constructs a human well-being index that includes economic well-being, culture and education well-being, and social development well-being as factors, and it incorporates the human well-being index into the evaluation system for urban well-being energy eco-efficiency (WEE). It uses the super-slack-based measure (SBM) model, which considers undesirable output, to measure the WEE of 10 prefecture-level cities in Shaanxi Province, China, from 2005 to 2019. The social network analysis (SNA) is used to describe the characteristics of the spatial correlation network of WEE and its spatiotemporal evolutionary trend, and the quadratic assignment procedure (QAP) analysis method is used to identify the driving factors that affect the spatial correlation network. The results show that, first, the WEE in Shaanxi is relatively low as a whole and varies greatly among regions, with the highest level in northern Shaanxi, followed by Guanzhong; the lowest level is in southern Shaanxi. Second, in Shaanxi, WEE has transcended geographical proximity into a complex, multi-threaded spatial correlation network, and Yulin is at the center of the network. Third, the network shows four sectors: the net overflow, main benefit, two-way overflow, and broker. Members in each sector have not fully exploited their advantages, and the whole network can be improved. Fourth, the differences in the economic development level, openness, industrial structure, and population are the main driving factors influencing the formation of the spatial correlation network.

Resilience theory plays a pivotal role in promoting sustainable urban development and the long-term stable development of the national economy. Based on the "scale-density-form" model of urban resilience, this paper shifts the perspective of urban resilience from the eastern region with higher level of economic development and better infrastructure construction to the arid northwest region with more fragile ecological environment and weaker urban development potential, which enriches the connotation and mechanism of urban resilience to a certain extent. Using ArcGIS platforms, statistical data and remote sensing data as data sources, this paper analyzes the urban resilience of four southern Xinjiang regions (Aksu Administrative Office, Kashgar Administrative Office, Kizilsu Kirgiz Autonomous Prefecture and Hotan Administrative Office) in time and space from 2000 to 2020 using a three-dimensional resilience analysis framework based on scale, density and morphology. The results show that the urban de-development of the study area faces a strong scale safety constraint due to the small available land area in the study area, which leads to its small urban construction land area. The county- and city-scale elasticity levels of Aksu Administrative Office and Kashgar Administrative Office are higher than the average level of the study area, while most of the counties and cities in Kizilsu Kirgiz Autonomous Prefecture and Hotan Administrative Office are lower than the average level of the study area, with large differences between counties and cities. The geographical location of the study area determines the backwardness of the region in terms of ideology, production methods and technology, which seriously restricts the development of local society and economy. In terms of density resilience, there are large differences among counties and cities in the study area, and the density resilience of Aksu, Kashgar and Kucha is much higher than that of other counties and cities. In terms of morphological resilience, with the increasing prominence of ecological status, the urban landscape layout of the study area has changed significantly, leading to changes in the distance between its blue-green landscape and gray-white landscape, which in turn causes changes in morphological resilience. Based on the above findings, initiatives and paths for resilience regulation in the study area are proposed in terms of scale, density and morphology. The study also has a reference value for local urban safety development.

The Chengdu-Chongqing city group (CCCG) is one of the regions with acute human-land conflicts in China at present. The current rapid development of CCCG has caused a large negative impact on regional land ecosystem services. Land ecosystem is the basis of economic development. Reasonable economic development is also the inherent requirement of land ecosystem and an important support for land ecosystem protection. Promoting the coordinated development of the economy and land ecosystems is a prerequisite for this city group to achieve ecological protection and high-quality development. Taking CCCG as an example, this paper constructs a coupling evaluation model of economic-social development and land ecosystem service by using the entropy weight method, coupling coordination degree model, gravity center model, and standard deviation ellipse model, and explores the coupling coordination degree and spatial-temporal evolution rule of the above two systems. The study found that, from 2005 to 2020, the overall economic-social development of the CCCG showed an upward trend with a regular pattern of a 'High in the east and west, low in the central', and the 'dual-core' spatial structure with Chengdu and Chongqing as the core ; the overall performance of land ecosystem services had a gentle slope downward trend with a 'U'-shaped spatial pattern of "high around and low in the middle". The results also show that the coupling coordination degree of economic-social development and land ecosystem services in CCCG continues to rise steadily. Overall, the level of coupling coordination is low, and the type of coupling coordination has gradually evolved from severe and moderate imbalance to moderate coordination and mild imbalance. Therefore, the CCCG should make full use of the advantages of the "dual-core" cities to improve the level of peripheral economic linkage, increase investment in science and technology to enhance the endogenous power of economic development, establish cooperation mechanisms to narrow the urban gap, and integrate ecological resources to promote ecological industrialization to better realize the synergistic promotion of land ecological protection and high-quality economic development.

Under the dual challenges of global downward economic pressure and the COVID-19 pandemic, studying the impact of local government fiscal pressure on public health is a meaningful endeavor. First, this paper analyzes the impact of local government fiscal pressure on public health and clarifies its impact mechanisms. Second, by utilizing panel data of 31 Chinese provinces from 2000 to 2020, two-way fixed-effects and mediating-effects models are developed to identify the effects and impact mechanisms of local government fiscal pressure on public health. The results show that local government fiscal pressure can be detrimental to public health through three main mechanisms: reducing public health fiscal expenditures, hindering industrial structure upgrading, and exacerbating environmental pollution. Heterogeneity analysis finds that the negative effects of local government fiscal pressure on public health mainly exist in Central and Western China. Accordingly, three policy implications are proposed: optimizing the fiscal system, accelerating industrial upgrading, and improving the appraisal system of local officers.

Under the background of China's strategy of becoming a powerful agricultural country, geographical indications (GIs) of agricultural products, as an important intellectual property right to enable Chinese agriculture to develop with high quality, have a strong effect of strengthening and promoting agriculture. However, there are a large number of infringements of GIs among agricultural products in judicial practice, which not only greatly damage the economic and social values of GIs of agricultural products, but also bring huge food safety hazards to consumers and hinder the overall protection of intellectual property rights in China. On this basis, this paper, with the help of a quasi-case research method, integrates the facts of relevant cases, the focus of disputes, the application of law, and other case elements to realize the case similarity judgment based on the legal argumentation model. With the help of the retrieval tool of "Peking University Magic Weapon", this paper provides statistics on the civil cases of infringement of GIs of agricultural products in China from 1 January 2014 to 31 July 2022 and sets different retrieval conditions for two searches. After two screenings, 245 valid samples were obtained, and the judicial patterns of infringement disputes over GIs of agricultural products in China were systematically sorted out from the distribution of plaintiff and defendant, the distribution of infringement types, the basis of adjudication, and the standard of compensation. It was found that the plaintiff types showed double simplification, the infringement types took edge infringement as the basic form, and the general trademark provisions occupied the main position in legal applications. Then, the main litigation points, such as the dispute over the identification of GIs of agricultural products, the dispute over the use of geographical names, and the dispute over tort liability, are summarized, so as to dig out the characteristics of the implicitness of infringement, the expectation of implementation, and the concreteness of aspects. On this basis, the regulatory path of the infringement of GIs of agricultural products is put forward, such as introducing procuratorial public interest litigation, multi-agents cooperating to implement all-round supervision, and reasonably determining the amount of damages.

(1) Background: In light of the global economy's digitalization and the "double carbon" target constraint, the digital economy is essential to fostering scientific and technological innovation, green growth, and lowering energy emissions. (2) Methods: This paper measures the digital economic index and carbon emission intensity and analyzes their characteristics in spatial and temporal dimensions using 282 Chinese urban panel data by improving various statistical methods of panel data, such as the entropy method, fixed effect model, multi-period DID model, moderating effect model and intermediary effect model. This paper examines the extent and mechanism of the digital economy's impact on urban carbon emissions. (3) Results: During the sample period, the overall trend of the digital economy in China was one of constant growth, showing an unbalanced distribution pattern of "high in the eastern regions, lower in the central regions and lowest in the western regions" in the spatial dimension. Carbon emissions can be significantly decreased by the digital economy, which has a dynamic effect and an inverted U-shaped trend in its influence. The digital economy plays a significant role in reducing carbon emissions through the rational layout of industrial structures. The transmission mechanisms for the digital economy's goal of reducing carbon emissions include environmental regulation and green technology innovation. (4) Conclusion: The research findings provide a reference for multiple decision makers to better formulate carbon emission policies and realize carbon emission decrease in the digital economy.

To achieve high-quality sustainable development in arid areas based on the concept of ecological civilization, it is necessary to deeply study the territorial spatial structure characteristics. Taking the Aksu River Basin, an important ecological security barrier in northwest China, as an example, this paper follows the research idea of "feature analysis-suitability evaluation-conflict identification analysis-optimization" and constructs a comprehensive model based on the AHP-entropy weight comprehensive evaluation method, ArcGIS spatial identification analysis, variance coefficient-TOPSIS method, and NRCA. A comprehensive model based on the AHP-entropy power integrated evaluation method, ArcGIS spatial identification analysis, variance coefficient-TOPSIS method, and NRCA was constructed to guide the optimization of the territorial spatial layout by exploring the characteristics of territorial spatial pattern, the suitability of territorial spatial development, the identification of territorial spatial conflicts, and the efficiency and functional advantage of territorial spatial utilization in the study area. The results show that: (1) The spatial type of territorial space in the Aksu River Basin from 2000 to 2020 is dominated by ecological space, agricultural space, and urban space, and the three spatial boundaries are irregularly interlaced. (2) The spatial utilization conflict pattern of the Aksu River Basin has formed, and the general conflict area is overgrowing. (3) The overall efficiency of territorial utilization in the Aksu River Basin is low, with significant differences among county administrative units. (4) After optimization, the three types of space in the watershed are adjusted and refined into six functional areas: basic farmland protection area, rural development area, ecological protection red line area, ecological control area, urban development area, and industrial supporting construction area.

As a new mode of mining development, green mine optimizes the development and utilization of mineral resources with a minimum of the environmental impact, and how to objectively evaluate the construction level of the green mine has become the key to promote green mine construction and it has also been an important path to achieve sustainable development of mineral resources. The evaluation system and methods of green mine construction, however, are not perfect at present as the existing green mine evaluation mostly adopts the index scoring accumulation method, with which the internal relations between the indicators are ignored, and the subjective influence it causes is too large. Based on the framework model of driving forces, pressure, state, impact and response, an indicator system is constructed in this paper to express the internal relationship between indicators more intuitively. Combined with subjective and objective combination weighting method to determine the index weight, TOPSIS and coupling coordination degree models are introduced to quantitatively evaluate the spatio-temporal evolution process of green mine construction and the coupling coordination between subsystems, analyze and obtain the main obstacle factors affecting the green mine construction of enterprises, and provide suggestions and countermeasures for the improvement of green mine construction of enterprises. The applicability of the model is verified by an actual case study of a mine in China. The model enriches the connotation of green mines, making the evaluation process and results fairer and more reliable, thus providing an effective way to promote the sustainable development of mines.

Environmental regulation faces theoretical and practical research challenges on global scale, due to differences such as language and policy environment. Research reflects the beneficial exploration of scholars, policymakers, and enterprises in the cognitive and behavioural norms of economic development, environmental protection, and social governance. This study demonstrated that the relevant research is motivated by the enaction of environmental regulations and discussed the influence of relevant research on the evolution of environmental regulations. Under the assumption that environmental regulations are consistent with related research, this study used 9185 papers in the field of environmental regulation from 2000 to 2019 to construct a research network panorama and explored the development and revelation of environmental regulation. The results revealed that environmental regulation research is motivated by the introduction of policies, and regulation is influenced by research evolution with the path of 'competitiveness-technological change-innovation.' In addition, after the twenty-first session of the Conference of the Parties (COP21), the number of studies increased significantly, with the USA in the leading position in the research field. Furthermore, governance strategies were inspired by real events, including the increasing concern with climate change, regional research preferences, and the promotion of information disclosure. These results suggest that environmental governors should focus on climate change, localisation, and mechanisms of information disclosure.

Carrying out environmental protection and governance in the process of using foreign capital to develop the economy is a realistic problem that China needs to solve urgently. In order to reduce environmental pollution, all enterprises are called upon by the local government to fulfil CSR and improve the quality of FDI use. However, previous studies have rarely explored the threshold effect of FDI and CSR on haze pollution. This paper employs the threshold effect model to explore the above problem based on panel data of 30 provinces in China from 2009 to 2018. The empirical study found the following: (1) FDI has a significantly positive double-threshold effect on haze pollution. Meanwhile, the promotion effect of FDI on haze pollution is the strongest in the two threshold ranges. (2) CSR has a significantly negative single-threshold effect on haze pollution; that is, the increase in CSR intensity inhibits haze pollution. Such a negative effect shows the characteristics of increasing marginal efficiency. (3) In addition, the provinces in different thresholds display obvious geographical distribution characteristics. Through the above analysis, it can be observed that FDI and CSR have distinct impacts on haze pollution. Thus, the country and the government can reduce haze pollution by improving the investment structure, using environmentally friendly technology, guiding enterprises to abide by business ethics and promoting social responsibilities fulfilment.

Based on the time series data of age characteristics, household registration characteristics, gender characteristics, education characteristics, marriage characteristics and commercial health insurance density of Chinese residents from 1997 to 2020, this paper aims to explore the dynamic relationship between the individual characteristics of Chinese residents and the demand for commercial health insurance by means of impulse response and variance decomposition analysis using an SVAR model. The results show that the age characteristics, household registration characteristics, gender characteristics, education characteristics and marriage characteristics of Chinese residents have a significant impact on the demand for commercial health insurance, but there is a time lag. There is a long-term equilibrium relationship between them: In terms of age characteristics and gender characteristics, the former has a positive effect in the short term and a significant inhibition on commercial health insurance demand in the long term, while the latter has the opposite. In terms of household registration characteristics, education characteristics and marriage characteristics, there are positive effects on the whole and negative effects in a particular period.

Green technology innovation can bring about dual benefits, i.e., technological progress and energy conservation, as well as emission reduction, which are regarded as effective means to achieve economic development and environmental protection. The influencing factors of green technology innovation have been studied from multiple angles. In order to promote the level of green technology innovation in China from a new perspective, this paper selected human capital as the independent variable, and empirically investigated the direct impact of educational and healthy human capital on green technology innovation, based on the panel data of 30 Chinese provinces (excluding Hong Kong, Macao, Taiwan and Tibet) from 2006 to 2016. Meanwhile, considering the current environmental policy system in China, this paper took environmental regulations as moderating variables, and analyzed the moderating role of three environmental regulations, namely, command-and-control environmental regulations, market-incentivized environmental regulations, and public voluntary environmental regulations, in the impact of human capital on green technology innovation. It was found that (1) educational human capital, with a three-period lag, and healthy human capital significantly promotes green technology innovation; (2) command-and-control environmental regulations, with a one-period lag, and market-incentivized environmental regulations promote green technology innovation, while public voluntary environmental regulations have an insignificant impact on green technology innovation; (3) the moderating effect of command-and-control and market-incentivized environmental regulations in the impact of human capital on green technology innovation is not significant. For public voluntary environmental regulations, the moderating effect between educational human capital and green technology innovation is significantly negative, while the moderating effect of healthy human capital on green technology innovation is not significant.

There is a close inherent connection between manufacturing exports and environmental pollution. With the continuous growth of China's export trade to the countries along Belt and Road, the resulting environmental problems have also received much attention. This paper first analyzes the environmental impact mechanism of China's export trade to the countries along Belt and Road. Then based on the dynamic panel data of 30 provinces in China from 2013 to 2019, we use the SYS-GMM method to make an empirical test from national and regional perspectives and analyze the environmental effects of China's export trade to the countries along Belt and Road. The results show that the environmental effects of export trade are significantly heterogeneous in different regions. In general, export trade has a significant positive scale effect on CO 2 emissions; the negative effect of environmental regulation on CO 2 emissions can effectively offset the positive effect caused by the growth of output in the capital-intensive sector, and the composition effect is generally negative; the technical effect of China's export trade to the countries along Belt and Road mainly depends on the technological-independent innovation, which is caused by the domestic investment in science and technology, so the overall technical effects are negative. Therefore, China should optimize the structure of export trade, promote technological innovation, and cultivate green advantage industries by increasing investment in scientific research and development; implement a gradient environmental regulation policy; and improve the quality and level of foreign direct investment.

This paper presents an analysis of the content and spatial distribution of heavy metals (HM) in street dust in Suwałki, a city located in northeastern Poland. The HM content of street dust was also evaluated using the geochemical index (Igeo), enrichment factor (EF), and contamination factor (CF), and local HM sources were identified using chemometric methods. The arithmetic averages of HM contents in dust arranged in the following order: Fe > Zn > Mn > Cu > Cr > Ni > Pb, were 11,692.80, 215.97, 194.78, 142.84, 63.59, 17.50, 17.04 mg∙kg -1 , respectively. Higher values than the local background occurred for Cr, Cu, Ni, Zn and Pb. The values of Igeo, CF, and EF indicate that the highest pollution in dust is due to Zn and Cu. The spatial distribution of metals was evaluated using maps of HM content in road dust samples from Suwałki. The spatial distribution of HM showed areas with high contents of Cr, Cu, Ni, Zn and Pb located mainly in the central and eastern parts of the city. In these areas, high traffic volume, the presence of shopping centers, administrative buildings and bus stops dominate. Statistical models of multivariate analysis (FA) and cluster analysis (CA) identified two sources of HM. The first source of pollution was associated with local industrial activity and motor vehicle travel, and the second with natural sources.

This research utilizes the dynamic slack-based measure (DSBM) model to evaluate health output efficiencies in Taiwan's administrative districts from 2014 to 2018. To measure health output efficiency, it adopts four input variables, one output variable, and one carry-over (exercise expenditure). This paper includes both public goods in totals and private goods per capita as the inputs of health output. Empirical results indicate that health output efficiencies in the south and east areas relatively lower. Lastly, the overall efficiency of urban areas may not be better than that in non-urban areas.

Based on the panel data of prefecture-level cities in China from 2006 to 2019, this paper uses the PSM-DID method to empirically test the internal impact mechanism among high-speed railway opening, inter-regional factor allocation efficiency, and urban environmental governance. The research results show that: (1) There is a serious factor-misallocation problem among prefecture-level cities in China. From 2006 to 2019, the factor misallocation between prefecture-level cities led to an average annual loss of total factor productivity in China's economy of 52.5%, an average labor misallocation of 23.16%, and an average capital misallocation of 18.69%. Since 2013, capital misallocation has exceeded labor misallocation as the main reason for factor misallocation among prefecture-level cities in China. (2) The opening of high-speed railways can promote the efficiency of urban factor allocation through the technological innovation effect, the foreign investment attraction effect, and the population agglomeration effect. The improvement of urban factor allocation efficiency can promote the improvement of urban environmental quality through the effects of industrial structure optimization, income enhancement, and human capital agglomeration. Therefore, the opening of a high-speed railway can improve urban environmental quality through the intermediary effect of improving the efficiency of urban factor allocation; that is, the opening of a high-speed railway has a dual positive effect of economic efficiency and environmental quality improvement. (3) The optimization effect of factor allocation and the environmental governance effect of the opening of high-speed railways have strong urban scale heterogeneity, urban characteristic heterogeneity, and regional heterogeneity. The research content of this paper has important guiding significance for the construction of China's new development paradigm, accelerating the construction of "a unified national market," and green and low-carbon development.

In recent years, Chinese household financial debt has been growing rapidly due to the expansion of mortgage lending. This study aims to examine the impact mechanism of Chinese household financial debt on physical health. Using the 2010-2018 China Household Tracking Survey (CFPS) panel data, we developed fixed effects models to explore the effect of household financial debt on individuals' psychical health, and we also used an instrumental variable to address endogeneity. The findings suggest that there is a negative effect of household financial debt on physical health and these findings still hold after a series of robustness tests. In addition, household financial debt can affect individuals' physical health through mediating variables, such as healthcare behaviors and mental health, and the effects are more significant for those who are middle-aged, married, and with low-income levels. The findings of this paper are important for developing countries to clarify the relationship between household financial debt and population health, and to develop appropriate health intervention policies for highly indebted households.

The construction of the world tourism destination on the Tibetan Plateau is inseparable from the traditional tourist attractions, which are significant landscape ecological units. Based on the data of high-grade tourist attractions on the Tibetan Plateau, the spatial heterogeneity and influence factors are studied employing the Standard Deviation Ellipse (SDE), Kernel Density Estimation (KDE), spatial autocorrelation (SA), and modified tourism gravity model methods. The results show that: (1) the overall spatial distribution characteristic of high-grade tourist attractions is in the direction of northeast-southwest, with solid centripetal force, and the center of gravity of the ellipse is in Yushu City. (2) The spatial heterogeneity of the kernel density distribution is remarkable, clustered in the southeastern half of the plateau, showing a double nucleus-driven and strip-connected pattern. The distribution among cities has a hierarchical heterogeneity, and the two capital cities of Xining and Lhasa play a crucial role. (3) The high-grade tourist attractions are spatially dependent, with evident characteristics of large dispersion and small clustering, and the spatial association type is mainly negative. (4) This paper verifies the significant single-factor mechanism affecting the spatial distribution from supportive and intrinsic dimensions with natural environmental base, tourism resource endowment, socio-economic development, transportation location constraints, and spatial tourism linkages. Finally, the article provides suggestions for the high-quality development of high-grade tourist attractions on the Tibetan Plateau.

Agricultural mechanization is an important component of agricultural modernization, as it contributes to the improvement of agricultural technology and the rapid transformation of agricultural development. However, research on the connection between agricultural mechanization and farmers' health status is scarce. Thus, using the 2018 China Health and Retirement Longitudinal Survey (CHARLS) data, this study explored how agricultural mechanization can affect farmers' health. OLS and 2SLS models were used for the study's analysis. Furthermore, we used a PSM model to check the robustness of our analysis. The findings showed that: (1) the current state of agricultural mechanization in western China harms the health of rural residents; (2) agricultural mechanization can mitigate the adverse effects on health by increasing farmers' living expenditure and improving their living environment; and (3) agricultural mechanization's effects on farmers' health are regionally and income-heterogeneous. Agricultural mechanization has a more significant impact on health in Tibetan areas and high-income regions. It has an almost minimal effect in non-Tibetan and low-income areas. This paper suggests approaches that can be used to encourage the rational development of agricultural mechanization and improve rural populations' health.

Since the beginning of March 2022, a new round of COVID-19 outbreaks in Shanghai has led to a sharp increase in the number of infected people. It is important to identify possible pollutant transmission routes and predict potential infection risks for infectious diseases. Therefore, this study investigated the cross-diffusion of pollutants caused by natural ventilation, including external windows and indoor ventilation windows, under three wind directions in a densely populated building environment with the CFD method. In this study, CFD building models were developed based on an actual dormitory complex and surrounding buildings under realistic wind conditions to reproduce the airflow fields and transmission paths of pollutants. This paper adopted the Wells-Riley model to assess the risk of cross-infection. The biggest risk of infection was when a source room was located on the windward side, and the risk of infection in other rooms on the same side as the source room was large in the windward direction. When pollutants were released from room 8, north wind resulted in the highest concentration of pollutants in room 28, reaching 37.8%. This paper summarizes the transmission risks related to the indoor and outdoor environments of compact buildings.

Green credit is an indispensable funding source through which China can achieve its carbon neutrality goal. This paper quantifies the influences of different green credit scales on energy structures, carbon reduction, the industrial economy, and the macroeconomy. It creates a green credit mechanism related to green technology innovation in a Chinese carbon neutrality computable general equilibrium (CGE) model and integrates energy, environmental, economic, and financial (3EF) systems. The green credit scale can influence green technology innovation and hence CO 2 emissions. The results show that (1) green credit can accelerate China's achievement of its carbon neutrality goal, and the larger the green credit scale, the less time it takes to achieve goals; (2) the influence of green credit scales confers marginal decreasing effects with realistic policy considerations; (3) using a cost-benefit perspective, 60% is the most appropriate green credit scale to use to achieve dual carbon goals in China; (4) the different green credit scales have a heterogeneous impact on the industry output, and high-carbon-emission producers from nonenergy industries need to pay attention to their green credit risk. This research provides a scientific reference for the policy design of China's future green financial market development.

As one of a number of crucial policies for achieving the goal of "double carbon", it is crucial to investigate the "carbon neutral" effect of the carbon trading market (CTM) in the pilot phase, which is an essential reference for the development of a future CTM. Based on panel data of 283 cities in China in the period from 2006 to 2017, this paper examines the impact of the Carbon Trading Pilot Policy (CTPP) on the achievement of the "carbon neutrality" target. The study shows that the CTPP market can promote an increase in regional net carbon sinks and further accelerate the achievement of the "carbon neutrality" goal. The findings of the study remain valid after a series of robustness tests. The mechanism analysis finds that the CTPP can help achieve the carbon neutrality target through three mechanisms: the effect on concern for the environment, the effect on urban governance, and the effect on energy production and consumption. Further analysis reveals that enterprises' willingness and productive behavior, as well as the internal elements of the market, have a positive moderating effect on the achievement of the carbon neutrality target. In addition, there is heterogeneity among regions with different technological endowments, CTPP regions, and regions with different shares of state-owned assets in the CTM. This paper provides important practical references and empirical evidence that can help China to better achieve the "carbon neutrality" target.

Based on the related environmental data of Chengdu and Chongqing from 2011 to 2020, this paper constructs a multivariate environment performance evaluation system, combines the self-built indicator system determination criteria and rules, evaluates and compares the environmental performance of Chengdu and Chongqing, and also discusses the impact of COVID-19 on urban environmental performance. The research results show that the overall environmental performance increased from 2011 to 2020, but there are differences between different subsystems, mainly manifested in the best water environment performance, followed by air environment and solid waste; moreover, the noise environment maintains a relatively stable level. By comparing the average levels of various subsystems of the Chengdu-Chongqing dual cities from 2011 to 2020, it can be seen that Chengdu City has better environmental performance in air environment and solid waste, while Chongqing City has better environmental performance in the water environment and noise environment. In addition, this paper also found that the impact of the epidemic on urban environmental performance mainly comes from the impact on the air environment. At present, the overall environmental performance of the two places has shown a trend of environmentally coordinated development. In the future, Chengdu and Chongqing should further optimize and improve their relatively weak environmental subsystems, deepen the joint action mechanism between the two places, and build a green and high-quality development economic circle for the Chengdu-Chongqing twin cities.