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This paper analyses the conference papers published by double first‐class universities from mainland China between 2006 and 2019. The main findings are as follows: first, the number of conference papers from different double first‐class universities varied greatly, with the annual numbers of papers in the China Proceedings of Conferences Full‐text Database (CPCD) and in the Conference Proceedings Citation Index (CPCI) fluctuating during this period. Second, most of the top 10 disciplines of the papers in the CPCD and CPCI were in the natural sciences, with only two in the social sciences. The CPCD papers and CPCI papers had some overlap in their disciplinary distributions. Third, the CPCD and CPCI papers differed little in total number, with the number of CPCI papers being slightly higher than the number of CPCD papers. With the introduction of new regulations from the Ministry of Science and Technology (MST), there will likely be an increase in the number of Chinese‐language conference papers in the future. [ABSTRACT FROM AUTHOR]

This paper conducted a comparative analysis of the conference publications published by Chinese scholars from 2006 to 2019. The main results are as follows. First, the conference papers are unevenly distributed among the 31 provincial administrative regions. The annual number of conference papers published by scholars from different regions fluctuated during the study period. Second, there are different disciplinary distributions of China Proceedings of Conferences Full‐text Database (CPCD) papers and Conference Proceedings Citation Index (CPCI) papers, and the CPCI publications have a relatively centralized disciplinary distribution. Third, it is noteworthy that there are more CPCD papers than CPCI papers. With the introduction of the new science and technology evaluation standards of the Ministry of Science and Technology, there should be more conference papers in the future. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (COVID-19) first emerged in China in November 2019. Most governments have responded to the COVID-19 pandemic by imposing a lockdown. Some evidence suggests that a period of isolation might have led to a spike in alcohol misuse, and in the case of patients with alcohol use disorder (AUD), social isolation can favour lapse and relapse. The aim of our position paper is to provide specialists in the alcohol addiction field, in psychopharmacology, gastroenterology and in internal medicine, with appropriate tools to better manage patients with AUD and COVID-19,considering some important topics: (a) the susceptibility of AUD patients to infection; (b) the pharmacological interaction between medications used to treat AUD and to treat COVID-19; (c) the reorganization of the Centre for Alcohol Addiction Treatment for the management of AUD patients in the COVID-19 era (group activities, telemedicine, outpatients treatment, alcohol-related liver disease and liver transplantation, collecting samples); (d) AUD and SARS-CoV-2 vaccination. Telemedicine/telehealth will undoubtedly be useful/practical tools even though it remains at an elementary level; the contribution of the family and of caregivers in the management of AUD patients will play a significant role; the multidisciplinary intervention involving experts in the treatment of AUD with specialists in the treatment of COVID-19 disease will need implementation. Thus, the COVID-19 pandemic is rapidly leading addiction specialists towards a new governance scenario of AUD, which necessarily needs an in-depth reconsideration, focusing attention on a safe approach in combination with the efficacy of treatment. [ABSTRACT FROM AUTHOR]

The impact of COVID‐19 has underlined the need for reliable information to guide clinical practice and policy. This urgency has to be balanced against disruption to journal handling capacity and the continued need to ensure scientific rigour. We examined the reporting quality of highly disseminated COVID‐19 research papers using a bibliometric analysis examining reporting quality and risk of bias (RoB) amongst 250 top scoring Altmetric Attention Score (AAS) COVID‐19 research papers between January and April 2020. Method‐specific RoB tools were used to assess quality. After exclusions, 84 studies from 44 journals were included. Forty‐three (51%) were case series/studies, and only one was an randomized controlled trial. Most authors were from institutions based in China (n = 44, 52%). The median AAS and impact factor was 2015 (interquartile range [IQR] 1,105–4,051.5) and 12.8 (IQR 5–44.2) respectively. Nine studies (11%) utilized a formal reporting framework, 62 (74%) included a funding statement, and 41 (49%) were at high RoB. This review of the most widely disseminated COVID‐19 studies highlights a preponderance of low‐quality case series with few research papers adhering to good standards of reporting. It emphasizes the need for cautious interpretation of research and the increasingly vital responsibility that journals have in ensuring high‐quality publications. [ABSTRACT FROM AUTHOR]

As one of the typical high‐polluting and high‐energy‐consuming industries in China, the paper industry's environmental behavior has become the focus of a range of stakeholders, policy makers, and the whole society because the industry's business activities are a main source of environmental pollution and contribute to massive energy consumption. This study used a qualitative approach to examine the relative importance of external and internal pressures (EP and IP) in driving the environmental behavior of paper enterprises in China. Based on grounded theory, this study aimed to examine the EP and IP on the environmental behavior of paper enterprises to create a comprehensive theoretical model based on grounded theory code analysis. It was found that government pressure, economic pressure, social pressure, and IP have direct and significant positive effects on the corporate environmental behavior (CEB) of paper enterprises in China. Furthermore, government, economic, and social pressures have indirect and significant positive effects on CEB through other pressures. Finally, the paper concludes with a discussion of these four pressures and provides policy implications. [ABSTRACT FROM AUTHOR]

Over the past decade, the interactions between accounting (and auditing) and corporate governance have been an important topic of academic research. They use audit hours to measure audit effort and find that audit effort alleviates stock market crash risk. The traditional audit quality indicators used in past research cannot accurately separate the respective roles of companies and auditors, which makes it difficult for researchers to draw effective causal inferences when studying the association between company characteristics and audit quality. [Extracted from the article]

WeChat has been developed into a unique social media and an increasing number of scholarly journals in China use it to promote their content. However, the effectiveness of WeChat promotion on academic impact is still unknown. This study selected five Chinese journals and investigated papers published in 2018, looking at reading counts on WeChat official accounts and the citations recorded on China's largest scholarly repository, China national knowledge infrastructure (CNKI). The raw data were normalized to lower the effect of journal size and then stratified into four data sets of the top 50%, top 25%, top 10% and top 1%. The results indicate that significant positive correlations between WeChat reading counts and citations exist across the total data set and the data sets of top 50%, top 25% and top 10%. The data set of the top 1% could not be analysed due to the small number of papers. Three of the five journals and two data sets of the other two journals exhibit similar positive correlations. This study demonstrates that promotion of WeChat official accounts can influence the academic impact of individual papers, but further study is needed to clarify the exact thresholds and influential factors. [ABSTRACT FROM AUTHOR]

Detailed, accurate, and reliable data regarding the occurrence of amphibian species in nature reserves (NRs) are important to facilitate effective conservation and management programs. We evaluated the current situation and research gaps in amphibian species inventories of NRs in mainland China by conducting a systematic review of papers on amphibian diversity research in NRs from 1956 to 2021. Generally, there was a gradual increase in amphibian survey intensity and standards, however, as some important parameters were lacking, such as species abundance and threats to amphibians. The standardization of amphibian surveys in NRs needs to urgently be strengthened and effectively implemented. We hope that highlighting these biases and gaps could provide actionable information for decision‐makers and improve conservation practices affecting amphibians in China and other native fauna elsewhere. [ABSTRACT FROM AUTHOR]

This paper finds that non-exporters benefit from industrial agglomeration through manufacturing specialization, whereas little effect of local specialization on productivity is found among exporters. We organize this special issue not only to gain understanding of how China's regional development works but also to introduce China's experience to other emerging markets as reference. Over the past decades, China's economy has expanded at a staggering pace by means of various reforms and economic liberalization. [Extracted from the article]

This paper reports a comparative study of the scientific publications of double first‐class universities based on international and domestic Chinese databases from 2006 to 2018. The main results are as follows. Quantitatively, the absolute total number of articles published by Chinese universities has increased. Specifically, the number of international publications in the natural and social sciences from double first‐class universities showed an increasing trend, but the number of domestic journal articles showed the reverse trend. Moreover, based on the number of papers published by each university over the years, we recognized that the ranking changes of universities fall into four categories: rising, declining, stable, and fluctuating. Qualitatively, the international and domestic publications issued by double first‐class universities greatly improved from 2006 to 2018. Moreover, scientific publications, either international or domestic, were unevenly distributed among the double first‐class universities. In general, the double first‐class universities developed rapidly in recent years and play an important role in the development of science and technology in China. [ABSTRACT FROM AUTHOR]

China's social safety net is still underdeveloped, hence family support in the form of intergenerational transfers often serves as a substitute for the public transfer system. Using data from the China Health and Retirement Longitudinal Study, this paper finds that both upstream inter‐vivos transfers (from children to parents) and downstream inter‐vivos transfers (from parents to children) are prevalent in urban China. Moreover, the relative income status of the parent and children has an impact on inter‐vivos transfers. To investigate what economic factors generate the observed patterns of inter‐vivos transfers, this paper adopts a general equilibrium life‐cycle model in which overlapping generations are altruistically linked and calibrates the model to match data from urban China. Counterfactual experiments of removing one source of economic risk or modifying the social security replacement rate from the baseline model at a time reveal that intergenerational transfers mainly serve as informal insurance against the income risk of the children. [ABSTRACT FROM AUTHOR]

Objectives: To investigate the knowledge and practices of Chinese doctors in the management of osteoporotic fractures after the Chinese osteoporotic fracture guidelines update and aseries of medical education in 2017. Methods: This was a cross‐sectional survey of doctors in 71 cities across Mainland China. Based on the 2017 Chinese guidelines for the diagnosis and treatment of osteoporotic fractures, a questionnaire was designed and pre‐tested for reliability and validity. Doctors were surveyed with the questionnaire after scientific meetings during February 2017 to January 2018 through WeChat or conference digital platforms or in paper form. Descriptive statistics was used to analyze the responses to the questionnaire. Results: Overall, 314 valid questionnaires were confirmed. Regarding diagnosis, 77% agreed that osteoporosis could be diagnosed once an osteoporotic fracture occurred; 83% believed that the bone mineral density criteria for osteoporosis diagnosis would be T ≤ −2.5 SD. For treatment, almost all (99.7%) agreed with anti‐osteoporosis treatment being one of the basic principles of osteoporotic fracture treatment; 71.6% considered bisphosphonates as the most commonly used anti‐osteoporosis drug; 97% believed that patients who have used anti‐osteoporosis drugs should reassess osteoporosis after osteoporotic fractures instead of discontinue; 95% thought that the patients who did not use anti‐osteoporosis medications before osteoporotic fracture should be treated with anti‐osteoporosis drugs after fracture treatment as early as possible; 89% agreed that the standard use of bisphosphonates after osteoporotic fracture would not affect bone healing adversely; 59% believed the course of bisphosphonates treatment for osteoporosis would be 3–5 years, and 27% considered it to be 1–3 years. The patient follow‐up rate was poor: 46% selected follow‐up rate <30%; only 20% selected follow‐up rate >50%. Only 31% of the hospitals had long‐term management programs for osteoporotic fractures. Conclusions: Doctors generally adhered to the updated Chinese guidelines for osteoporotic fractures; frequent participation in medical education can help doctors to increase their awareness of osteoporosis as well as their acceptance and practice of the guidelines. [ABSTRACT FROM AUTHOR]

The article presents the authors' opinions on the publication of science and technology research by Chinese authors in the English language in American and British scholarly journals. The authors address the outflow of scientific research from Chinese scientists and argue that the flow should be stemmed so that Chinese journals could achieve a higher standing in the field of scholarly research. Topics include academic evaluation methods and internationalization.

Macrophages play a crucial role in aiding all phases of the wound‐healing process and has garnered increasing attention recently. Although a substantial body of related studies has been published, there remains a lack of comprehensive bibliometric analysis. In this study, we collected 4296 papers from the Web of Science Core Collection database. Three tools including CiteSpace, VOSviewer and one online analytical platform were employed to conduct bibliometric analysis and data visualization. Our results revealed that the annual number of publications related to macrophage and wound healing has increased exponentially with the year. The United States and China stand as the primary driving forces within this field, collectively constituting 58.2% of the total publication output. The application of biomaterials was one of the most concerned research areas in this field. According to references analysis, the current research focus has shifted to diabetic wound healing and regulating macrophage polarization. Based on the keywords analysis, we identified the following research frontiers in the future: exosomes and other extracellular vesicles; bio‐derived materials and drug delivery methods such as nanoparticles, scaffolds and hydrogels; immunomodulation and macrophage polarization in the M2‐state; chronic wounds, particularly those associated with diabetes; antimicrobial peptides; and antioxidant. Additionally, TNF, IL‐6, IL‐10, TGF‐β1 and VEGF ranked as the five genes that have garnered the most research attention in the intersection of macrophage and wound healing. All in all, our findings offered researchers a holistic view of the ongoing progress in the field of macrophages and wound healing, serving as a valuable reference for scholars and policymakers in this domain. [ABSTRACT FROM AUTHOR]

In recent years, China's advanced light sources have entered a period of rapid construction and development. As modern X-ray detectors and data acquisition technologies advance, these facilities are expected to generate massive volumes of data annually, presenting significant challenges in data management and utilization. These challenges encompass data storage, metadata handling, data transfer and user data access. In response, the Data Organization Management Access Software (DOMAS) has been designed as a framework to address these issues. DOMAS encapsulates four fundamental modules of data management software, including metadata catalogue, metadata acquisition, data transfer and data service. For light source facilities, building a data management system only requires parameter configuration and minimal code development within DOMAS. This paper firstly discusses the development of advanced light sources in China and the associated demands and challenges in data management, prompting a reconsideration of data management software framework design. It then outlines the architecture of the framework, detailing its components and functions. Lastly, it highlights the application progress and effectiveness of DOMAS when deployed for the High Energy Photon Source (HEPS) and Beijing Synchrotron Radiation Facility (BSRF). [ABSTRACT FROM AUTHOR]

The White Paper on Chinese population policy, entitled "Family Planning in China," was issued by the Chinese Information Office of the State Council on August 23, 1995. The population problem is an important question that touches upon the survival and development of the Chinese nation, the success or failure of China's modernization drive as well as the coordinated and sustained development between the population on one hand and the economy, society, resources and environment on the other. It is a natural choice that the Chinese government has made to implement family planning, control population growth and improve the life quality of the population a basic state policy on the basis of a wish to make the state strong and powerful, the nation prosperous and the people happy. In the 1960s, the country's population entered its second peak birth period. From 1962 to 1972, the annual number of births in China averaged 26.69 million, totaling 300 million. In the practice of carrying out family planning programme, whilst persistently proceeding from its reality and taking into full account and observing principles and regulations concerning population and family planning formulated by international institutions and organizations, the Chinese government has gradually set up guiding principles, policies, measures and methods that reflect the basic interests and various rights and interests of the people and has continuously improved these as the actual situations change, so as to better safeguard the right to subsistence and development of the Chinese region.

Small mammal species richness and relative abundance vary along elevational gradients, but there are different patterns that exist. This study reports the patterns of distribution and abundance of small mammals along the broader elevational gradient of Mt. Qilian range. The study was conducted in the Mt. Qilian range, north-western China, from June to August 2001. Removal trapping was conducted using a standardized technique at 7 sites ranging between 1600 and 3900 m elevation within three transects. Correlation, regression and graphical analyses were used to evaluate the diversity patterns along this elevational gradient. In total, 586 individuals representing 18 nonvolant small mammal species were collected during 20 160 trap nights. Species composition was different among the three transects with 6 (33%) of the species found only within one transect. Elevational distribution and relative abundance of small rodents showed substantial spatial variation, with only 2 species showing nonsignificant capture frequencies across elevations. Despite these variations, some general patterns of elevational distribution emerged: humped-shape relationships between species diversity and elevation were noted in all three transects with diversity peaks at middle elevations. In addition, relative abundance was negatively correlated with elevation. Results indicate that maximum richness and diversity of nonvolant small mammals occurred at mid-elevations where several types of plants reached their maximum diversity and primary productivity, and where rainfall and humidity reached a maximum. It is demonstrated that the mid-elevation bulge is a general feature of at least a large portion of the biota on the Mt. Qilian range. [ABSTRACT FROM AUTHOR]

Adequate blood supply, a prerequisite for flap survival after grafting, makes angiogenesis of the flap the biggest problem to be solved. Researches have been conducted around vascularisation in correlation with flap grafting. However, bibliometric analyses systematically examining this research field are lacking. As such, we herein sought to conduct comprehensive comparative analyses of the contributions of different researchers, institutions, and countries to this research space in an effort to identify trends and hotspots in angiogenesis and vascularisation in the context of flap grafting. Publications pertaining to angiogenesis and vascularisation in the context of flap grafting were retrieved from the Web of Science Core Collection. References were then analysed and plotted using Microsoft Excel 2019, VOSviewer, and CiteSpace V. In total, 2234 papers that were cited 40 048 times (17.63 citations/paper) were included in this analysis. The greatest number of studies were from the United States, with these studies exhibiting both the highest number of citations (13 577) and the greatest overall H‐index (60). For The institutions that published the greatest number of studies were WENZHOU MEDICAL UNIVERSITY (681), while UNIVERSITY OF ERLANGEN NUREMBERG has the highest number of citations (1458), and SHANGHAI JIAO TONG UNIVERSITY holds the greatest overall H‐index (20). The greatest number of studies in this research space were published by Gao WY, while Horch RE was the most commonly cited researcher in the field. The VOS viewer software clustered relevant keywords into three clusters, with clusters 1, 2, 3, and 4 corresponding to studies in which the keywords 'anatomy', 'survival', 'transplantation', 'therapy' most frequently appeared. The most promising research hotspot‐related terms in this field included 'autophagy', 'oxidative stress', 'ischemia/reperfusion injury', which exhibited a most recent average appearing year (AAY) of 2017 and after. Generally speaking, the results of this analysis indicate that the number of articles exploring angiogenesis and flap‐related research has risen steadily, with the United States and China being the two countries publishing the greatest proportion of studies in this field. The overall focus of these studies has shifted away from 'infratest and tissue engineering' towards 'mechanisms'. In the future, particular attention should be paid to emerging research hotspots, which include 'ischemia/reperfusion injury' and treatments for promoting vascularization, such as 'platelet‐rich plasma'. In light of these findings, funding agencies should continue increasing their investment in the exploration of the concrete mechanisms and interventional therapeutic relevance of angiogenesis during flap transplantation. [ABSTRACT FROM AUTHOR]

Aim: This study investigated the scientific research ability of Chinese specialist nurses (SNs) in the Guangxi Zhuang Autonomous Region and its influencing factors. Design: A cross‐sectional design. Methods: A total of 652 SNs in the Guangxi Zhuang Autonomous Region were investigated from March to October 2021. The nursing scientific research ability level was measured using the Nursing Research Competence of Nurses Self‐evaluation Scale. Descriptive statistics, univariate analysis and ordinal logistic regression analysis were used to evaluate factors affecting the scientific research ability of SNs. Results: The median score of scientific research ability of SNs was 31 (interquartile range: 19–41). Approximately 74.8% of clinical speciality nurses had low scientific research ability. Educational background, working hospital level, being the first author of a published paper and successful application for scientific research projects were identified as factors influencing scientific research ability score. [ABSTRACT FROM AUTHOR]

This paper aims to trace the origins of dual entry beyond a Eurocentric boundary. The aim can be refined further by asking: did the Chinese use dual entry and how did dual entry appear in Europe. Double entry is more advanced as it includes the location of the account in which the contra entry is made. Dual entry approaches accounting, like mathematics, as a tautology, whereby an equation is constructed from a simple axiom. Defined as such, this paper argues that the concept of dual entry had its earliest origins in China. [ABSTRACT FROM AUTHOR]

Platelet‐rich plasma (PRP) has attracted attention because of its potential to accelerate the wound healing process. However, resources for evaluating research trends in the treatment of wounds with PRP were limited. In this study, we aimed to make a bibliometric analysis of the literature related to PRP in the treatment of wounds and explore the research status, hotspots and frontiers in this field in recent 20 years. Studies about PRP treatment for wounds from 2002 to 2021 were retrieved from the Science Citation Index Expanded (SCI‐E) of Web of Science (WOS) database. Visualisation softwares such as VOSviewer and SCImago Graphica, and CiteSpace were used to analyse the research trends and features. A total of 1748 studies were identified in the SCI‐Expanded from 2002 to 2021. The number of publications on PRP in the treatment of wounds has shown an increasing trend, from 6 (in 2002) to 228 (in 2021). The papers published in the United States have led in times cited (14637) and H‐index (63). Though Italy was slightly lower than China in the number of publications, the H‐index and average cited (47, 28.45) were higher than that of China (38, 27.01). The strongest keyword was "fibrin" (strength = 13.07), and the longest burst duration keyword was "thrombin" (began in 2002 and ended in 2014). The largest 10 co‐citation clusters are as follows: endothelial cell proliferation (#0), regenerative medicine‐associated treatment (#1), diabetic wound healing (#2), autologous derived (#3), platelet‐rich fibrin (#4), tissue engineering (#5), regenerative potential (#6), clinical randomised trial (#7), histologic observation (#8), and wound bacteria (#9). The United States has made the most outstanding contribution in this field. Chinese researchers need to enhance the quality of publications further. Wound Repair Regen. is the most noteworthy journal. The mechanism of growth factors of PRP, combination therapy, preparation of PRP, and related clinical trials may be topics that need attention. [ABSTRACT FROM AUTHOR]

Background: For adults with inflammatory bowel disease (IBD), they experience many challenges in dietary decision‐making. Thus, this study examined the perspective and experiences of adults with IBD in dietary decision‐making. Objective: This study aimed to explore the perception and consideration of people with IBD in their daily dietary decisions through monitoring, interpretation and action during the decision‐making process. Design: A qualitative study of individuals affected by IBD was conducted through semistructured interviews. Results: Twenty patients were recruited from four tertiary hospitals in Nanjing, China, and each participant completed a semistructured interview. The majority of participants reported on the process and experience of dietary decision‐making. Key themes were categorised into three stages: (1) assessing needs, preferences and food cues (monitor); (2) moving from experience to expertise (interpret) and (3) balancing expectations amidst limitations (act). The majority of participants reported that their decisions were shaped by assessing current disease status and food cues. Those interviewed with IBD were willing to make tradeoffs for bowel stability, but their decisions were also influenced by past dietary experiences and traditional Chinese beliefs. The lack of awareness of dietary guidelines was a significant barrier to healthy eating decisions. Positive or negative feelings accompanied dietary decisions. Conclusion: Although most people with IBD change their diet after diagnosis, the changes made are often inconsistent with existing dietary recommendations. Several factors can influence the dietary decision‐making process. This study will help assess the experiences of people with IBD in dietary decision‐making to encourage the formation of targeted dietary health and well‐being interventions. Knowledge of nutrition and diet should be provided in education and training programmes for IBD management. Patient or Public Contribution: The first three authors of this paper were the lead researchers in this study's design. These authors were mentored by patient researchers who also contributed to the manuscript, and the research process was co‐lead and directed by other patient participants and consultants. The results of this paper were directly obtained from patient participants. [ABSTRACT FROM AUTHOR]

Satellite infrared detectors cannot penetrate clouds, especially precipitating clouds. Improving precipitation estimation accuracy based on infrared brightness temperature has always been important but challenging. In this paper, based on the infrared brightness temperature of the Advanced Geosynchronous Radiation Imager (AGRI) onboard China's Feng‐Yun 4A satellite, we develop and evaluate a new precipitation estimation method. First, using static data, physical characteristics of clouds, cloud image texture features, temporal motion features, and AGRI infrared channel brightness temperature, we construct features for a machine learning model. Then, we develop precipitation estimation methods. Precipitation is estimated in two steps: classification and regression. We employ a random forest classification model to identify whether there is precipitation in a given field of view. If there is precipitation, a multi‐model ensemble regression learning method is used to estimate the areas with this precipitation. The ensemble learning method uses convex optimization to integrate prediction results based on the optimization of hyperparameters of five basic models (i.e., those of random forest, XGBoost, LightGBM, decision tree, and extra tree models). Furthermore, two regression stacking ensemble models—the Least Absolute Shrinkage and Selection Operator (herein referred to as Stacking1‐LASSO) and K‐nearest neighbor (herein referred to as Stacking2‐KNN)—are used to predict the results of the aforementioned basic models. The results of basic models are used as inputs of these two stacking models. Finally, based on the Integrated Multi‐satellitE Retrievals for GPM (IMERG) precipitation product and rain gauge precipitation data, we conduct precipitation estimation experiments and evaluate our methods. The results show that ensemble learning models have greater accuracy in estimating precipitation than the basic models. When using IMERG precipitation as the target precipitation, ensemble learning models can estimate the central area of heavy precipitation during typhoons Ampil and Maria. The ensemble learning estimation effect is better than that of Stacking2‐KNN. Moreover, when rain gauge data is used as the target precipitation, ensemble learning can also estimate the center of heavy precipitation and with good consistency with recorded satellite brightness temperature data. Key Points: A convex optimization weighted and stacked ensemble learning method for satellite data estimation of precipitation is developedNear real‐time precipitation estimates can be obtained throughout the day using only geographic information and Advanced Geosynchronous Radiation Imager infrared brightness temperature dataThe proposed ensemble learning method can estimate the central areas of typhoons and short‐term heavy rainfall [ABSTRACT FROM AUTHOR]

On 31st December 2020, The National Science Library of the Chinese Academy of Sciences (CAS) released a list of 65 international scientific journals, all of them indexed by the Web of Science, that were said to be potentially in conflict with academic rigour. The list immediately influenced the publication patterns of Chinese researchers. A year later, on 31st December 2021, CAS released a revised and reduced list of 35 questionable journals and said the publishers in the meantime had reacted constructively and improved the procedures of their journals. This study aims to provide an understanding of the motivations and criteria behind the list, partly by reviewing Chinese policy documents and public debates, partly with a quantitative analysis to detect the relative importance of the criteria used to select the journals for the list. [ABSTRACT FROM AUTHOR]

Sanding production of the underground gas storage (UGS) in the depleted reservoir will cause the decline of effective storage capacity, and the erosion of well string and auxiliary equipment, and other engineering problems. A deep understanding of the sanding production contributes to maintaining the injection and production capacity of gas storage and the long‐term safety of the UGS. In this paper, core samples of five main sedimentary microfacies were drilled from the UGS in middle China. The mechanical properties with different conditions of the moisture content in multi‐cycling injection–production process were tested. The critical drawdown pressure (CDP) calculation methods for the UGS were established based on the stress analysis near the wellbore and the Mogi–Coulomb criterion. Adopting the finite element method simulation on the geological model of the target UGS, the geo‐stress of the formation was calculated by inversed analysis and validated based on the Kaiser effect of rock. Then, the CDP of two target wells of the UGS were investigated. The effects of the water moisture and the cycling times of the injection–production process on the CDP were also analyzed. The geo‐stress distribution shows that the horizontal maximum principal stress ranges from 53 to 68 MPa, and the horizontal minimum principal stress is 46–58 MPa in the target reservoir section, and the vertical minimum principal stress is 69–77 MPa in the target reservoir. The calculated CDP changed with the types of the sedimentary microfacies in the range of [6.27, 8.77] MPa, in which the CDP of the mixed mud and sand flat sedimentary facies was the lowest. The weakness of the CDP with the increasing of the moisture content and the cycling times were analyzed quantitively. [ABSTRACT FROM AUTHOR]

Currently, the opportunistic method to estimate rainfall using commercial microwave links (CMLs) has been shown as an efficient way to complement traditional instruments in terms of spatial‐temporal resolution and coverage. In this paper, we collected data from 26 CMLs in Jiangyin City, Jiangsu Province, and conducted experiments on rainfall field reconstruction and nowcasting. First, the raw CML data were processed to invert the path‐averaged rainfall intensity. Second, the algorithms of inverse distance weighting (IDW) and ordinary kriging (OK) interpolation were employed to reconstruct the rainfall field. Then a 10‐min prediction of the rainfall field was achieved using a nowcasting model based on the long short‐term memory neural network and a setup window was introduced to improve the prediction performance of the first few minutes. The reconstruction results show that the average correlation coefficient (ACC) and the average root mean square error (ARMSE) between the IDW‐based results and daily cumulative rainfall from rain gauges (RGs) are 0.89 and 8.69 mm, respectively, while the ACC and ARMSE between the OK‐based results and RG data are 0.89 and 9.13 mm, respectively. The nowcasting results show that the ACC between the prediction results with a 5‐min setup window and the IDW‐retrieved rainfall fields can reach 0.91 at the first minute and gradually decrease to 0.20 within 10 min. Furthermore, the model has better nowcasting performance for stratiform precipitation and mixed precipitation compared to convective precipitation. Plain Language Summary: Accurate and real‐time rainfall monitoring and forecasting are of great significance for disaster prevention and control, agriculture, meteorological research, and related fields. However, traditional rainfall measurement methods are insufficient for meeting the demands of comprehensive precipitation observations because of poor spatial‐temporal resolution and limited coverage. Currently, measuring rainfall using additional microwave attenuation caused by raindrops has been shown as an efficient way to complement traditional instruments. Based on commercial microwave link (CML) rainfall measurement technology, this paper carries out rainfall field reconstruction and nowcasting experiments in Jiangyin City, China. The results show the CML network enables accurate rainfall field reconstruction and nowcasting. Key Points: Based on the commercial microwave link (CML) rainfall monitoring network in Jiangyin, China, accurate rainfall inversion by CMLs is achievedThe two‐dimensional rainfall fields are accurately reconstructed using the inverse distance weighting and ordinary kriging interpolation algorithmsA long short‐term memory‐based rainfall field nowcasting model is proposed to achieve 10‐min continuous predictions of rainfall fields [ABSTRACT FROM AUTHOR]

In network real‐time kinematic positioning of multi‐reference station, the spatial and temporal distribution of tropospheric delay is affected by both horizontal and elevation. The traditional modeling strategy of regional troposphere takes more consideration of the horizontal factor, and the incomplete consideration of the elevation factor will lead to the problem of reduced modeling accuracy, especially in the face of the scene with large regional height deviation. Based on the traditional linear interpolation method (LIM), a simple and effective height‐deviation compensation‐based linear interpolation method (HCLIM) for regional tropospheric is proposed. The modeling accuracy of troposphere and the positioning accuracy of user RTK in large height deviation region are significantly improved. The method was verified based on six experimental subnets with large height deviations from a provincial continuously operating GNSS reference stations network in central China. The results showed that: For GPS satellite modeling, compared with the traditional LIM method, the average modeling accuracy improvement rate of HCLIM method is (84.5%, 75.5%, 59.3%, 26.7%) in the elevation angle range of (10–30°/30–40°/40–50°/50–90°). For BDS satellite, the average modeling accuracy improvement rate of HCLIM method in the above four elevation angles is (83.3%, 70%, 50%, 23.5%). For the positioning performance of user RTK, The horizontal positioning accuracy and RTK fixing rate were similar under the two methods, while HCLIM method showed only slight improvement. However, in the U direction, LIM method showed obvious systematic bias, while HCLIM method showed consistent positioning accuracy, which was improved to 82.8% compared with LIM method. Plain Language Summary: In GNSS relative positioning, the positioning performance of user largely depends on the extent to which atmospheric deviations (ionospheric delay or tropospheric delay) are eliminated or weakened. Compared with the ionosphere, the temporal and spatial characteristics of troposphere are significantly different. It is part of the lower atmosphere, extends from the Earth's surface to an altitude of about 20 km, and contains most of the atmospheric water vapor. The delay of satellite signals through the troposphere is affected by both horizontal and elevation. The traditional tropospheric regional modeling strategy only uses plane coordinates for interpolation, ignoring the influence of elevation factors or the consideration of height‐deviation is not perfect. When the height difference between the reference station and the rover station is large, the modeling accuracy will obviously be reduced. The large modeling residual may bring systematic deviation to the user coordinates, especially the elevation direction component. In this paper, we propose a regional tropospheric linear interpolation method (HCLIM) considering height deviation compensation. This method is simple and effective, The modeling accuracy of troposphere and the positioning accuracy of user RTK in large height difference region are significantly improved. Key Points: A simple and effective height‐deviation compensation‐based linear interpolation method (HCLIM) for regional tropospheric is proposedThe HCLIM method greatly improves the tropospheric modeling accuracy of each elevation angle range in the large height difference site areaThe HCLIM method significantly improves the systematic bias in elevation direction of user RTK positioning due to modeling residuals [ABSTRACT FROM AUTHOR]

Concerted effort to reduce ecological damages requires that the role of enterprises should be extended to incorporate environmental issues into their core business objectives. Despite huge developments in sustainable entrepreneurship research, outcomes of sustainable entrepreneurship uptake remain largely unclear. Drawing on data of Chinese firms, and utilizing fixed effects regression, our paper evaluates the conditions under which compliance with environmental regulation may enable or constrain corporate performance. We find that environmental compliance lowers corporate market performance and improves financial performance at the same time. We also find that the decline in market performance is reversed for large and privately owned enterprises, highlighting the role of firm size and ownership in corporate performance. When distinguishing between market‐ and financial performance, our evidence shows that environmental compliance will most likely improve market performance when enterprise carbon intensity level is low and improve financial performance when enterprise carbon intensity level is high. As we have discussed in our paper, these results have several implications from the point of view of managers, firm stakeholders, and policymakers. [ABSTRACT FROM AUTHOR]

This study assesses the midsummer precipitation prediction over eastern China by the dynamic downscaling method. Based on the Climate Forecast System version 2 of the National Centers for Environmental Prediction and the Weather Research and Forecasting Model, the prediction performance of global and regional models on the July precipitation over eastern China is further analyzed by hindcast experiments from 1982 to 2010 and prediction experiments from 2011 to 2021. The results suggest that the regional model forced by the global model can noticeably improve the prediction skill for precipitation in eastern China, especially in the region from the South of North China to the Yangtze River Basin, referred as the northern China in this paper. In addition, we perform a diagnostic analysis of the reason for the improvement of the model prediction skill. The results indicate that the high resolution of the regional model and the refinement of physical process parameterizations contribute to improving the simulation ability for the East Asian atmospheric circulation pattern, heat flux, especially for the meridional teleconnection pattern in East Asia and the sensible heat flux in the northern China, thus further improving precipitation prediction. [ABSTRACT FROM AUTHOR]

This paper qualitatively and quantitatively examines the development of the sovereign debt market in Prewar China under different governments. During the Beijing Era (1912–26), accompanied by the establishment of necessary financial institutions, the sovereign debt market emerged to meet fiscal needs. Surprisingly, the Nationalist government, in power from 1927, successfully cultivated a robust market characterized by its expanding size and liquidity. Setting itself apart from its predecessors, the government established credibility as a borrower in two key ways. Firstly, it demonstrated unwavering commitment to debt service by settling previous debts and offering well‐structured new ones, even during challenging times. Furthermore, the government escrowed fiscal revenue, pledged for debt repayments, to a semi‐independent committee of private bankers on behalf of debtholders, enhancing public confidence. Secondly, the government showcased its ability to secure tax revenues for debt repayments. However, starting from 1931/2, the debt market experienced a decline due to the government's compromised ability to pay resulting from external wars and shifting political priorities that weakened its commitment to debt repayments. Empirical evidence confirms the market's responsiveness to regime shifts and policy changes. This paper sheds light on how a nascent autocratic government can successfully borrow from the public. [ABSTRACT FROM AUTHOR]

Background: Kenny–Caffey syndrome type 2 (KCS2) is an extremely rare inherited disorder characterized by proportionate short stature, skeletal defects, ocular and dental abnormalities, and transient hypocalcemia. It is caused by variants in FAM111A gene. Diagnosis of KCS2 can be challenging because of its similarities to other syndromes, the absence of clear hallmarks and the deficient number of genetically confirmed cases. Here, we aimed to further delineate and summarize the genotype and phenotype of KCS2, in order to get a better understanding of this rare disorder, and promote early diagnosis and intervention. Methods: We present clinical and genetic characteristics of eight newly affected individuals with KCS2 from six families, including one family with three individuals found to be a father‐to‐daughter transmission, adding to the limited literature. Furthermore, we performed a review of genetically confirmed KCS2 cases in PubMed, MEDLINE and CNKI databases. Results: There were six females and two males in our cohort. All the patients presented with short stature (100.0%). Clinical manifestations included ocular defects such as hypermetropia (5/8), dental problems such as defective dentition (3/8) and dental caries (3/8), skeletal and brain anomalies such as delayed closure of anterior fontanelle (6/8), cerebral calcification (3/8), cortical thickening (3/8) and medullary stenosis (4/8) of tubular bones. Endocrinologic abnormalities included hypoparathyroidism (5/8) and hypocalcemia (3/8). One male patient had micropenis and microorchidism. All cases harboured missense variants of FAM111A, and nucleotides c.1706 arose as a mutational hotspot, with seven individuals harbouring a c.1706G>A (p.Arg569His) variant, and one child harbouring a c.1531T>C (p.Tyr511His) variant. Literature review yielded a total of 46 patients from 20 papers. Data analysis showed that short stature, hypoparathyroidism and hypocalcemia, ocular and dental defects, skeletal features including cortical thickening and medullary stenosis of tubular bones, and seizures/spasms were present in more than 70% of the reported KCS2 cases. Conclusion: We provide detailed characteristics of the largest KCS2 group in China and present the first genetically confirmed instance of father‐to‐daughter transmission of KCS2. Our study confirms that Arg569His is the hot spot variant and summarizes the typical phenotypes of KCS2, which would help early diagnosis and intervention. [ABSTRACT FROM AUTHOR]

In recent years, China's automobile industry has undergone rapid development, creating new opportunities for the auto loan industry. Currently, auto financing companies are actively seeking to expand their cooperation with banks. Therefore, improving the approval rate and scale of joint loan business is of significant practical importance. In this paper, we propose a Stacking‐based financial institution risk approval model and select the optimal stacking model by comparing its performance with other models. Additionally, we construct a bank approval model using deep learning techniques on a biased data set, with feature extraction performed using convolution neural networks (CNN) and feature‐based counterfactual augmentation used for balanced sampling. Finally, we optimize the model of the prediction of auto finance companies by selecting the optimal coefficients of loss function based on the features and results of the bank approval model. The proposed approach leads to an approximately 6% increase in the joint loan approval rate on the actual data set, as demonstrated by experimental results. [ABSTRACT FROM AUTHOR]

This paper discusses the historical and social origins of the bifurcation in the political institutions of China and Western Europe. An important factor, recognized in the literature, is that China centralized state institutions very early on, while Europe remained politically fragmented for much longer. These initial differences, however, were amplified by the different social organizations (clans in China, corporate structures in Europe) that spread in these two societies at the turn of the first millennium AD. State institutions interacted with these organizations, and were shaped and influenced by this interaction. The paper discusses the many ways in which corporate organizations contributed to the emergence of representative institutions and gave prominence to the Rule of Law in the early stages of state formation in Europe, and how specific features of lineage organizations contributed to the consolidation of the Imperial regime in China. This publication follows on from the Economica Phillips 2022 lecture presented by Professor Guido Tabellini on 01 December 2022. [ABSTRACT FROM AUTHOR]

From core observations of shales of the Niutitang formation in the northern part of Guizhou Province, China, calcite was often found to act as a natural fracture filler and affect the extension of fractures in hydraulic fracturing. Therefore, it is crucial to understand the tensile mechanical behavior of shales by calcite veins. In this paper, by computed tomography scanning of shales containing calcite veins of different dip angles from the Niutitang formation, a three‐dimensional numerical model reflecting the internal fine structure of the shale was constructed. Direct tensile numerical simulations were carried out to investigate the effect of calcite veins at different angles on the fine‐scale damage process and mechanical properties of shale. The experimental results show that the tensile capacity of the shale increases with the increase in calcite veins. Depending on the dip angle of the calcite vein, the damage pattern of the shale is divided into three types of damage: pull‐off damage along the calcite vein, jagged damage, and horizontal damage perpendicular to the loading method. At high dip angles, the shale damage is more intense and the fracture network more complex. The temporal and spatial characteristics of the acoustic emissions provide a good indication of the microscopic behavior of the shale specimens during the damage process. The box dimension method was used to calculate the fractal dimension of the shale specimens at the final damage, and it was found that the damage was more intense and the fracture network was more complex at high dip angles, and there was an angular threshold. [ABSTRACT FROM AUTHOR]

The platform economy is growing fast in the world. Its expansion, exemplified by industry giants like Amazon, Airbnb, and Uber, is reshaping societal lifestyles and commercial businesses. However, its environmental impacts are uncertain. Currently, the relationship between electronic commerce (e‐commerce) activities and environmental pollution has attracted a lot of attention. This paper attempts to construct a comprehensive theoretical model to investigate the nexus between e‐commerce and regional environmental pollution, with a particular focus on the effects of air pollution and waste pollution. Fixed effect models and China's provincial data during the period from 2008 to 2018 are employed to examine the roles of energy efficiency and resource consumption in such a nexus. The findings suggest that the development of e‐commerce is linked to a reduction in regional air pollution through the channel of improving transportation energy efficiency. The results also show that e‐commerce is associated with an increase in regional waste pollution due to the mechanism of resource consumption in the express packaging industry. As a result, the relationship between e‐commerce and environmental pollution is quite complex at the regional level, transcending a binary distinction of solely positive or negative impacts. This paper contributes to a better understanding of the complex environmental impacts of e‐commerce and helps governments design more efficient and targeted policies to reduce regional pollution. [ABSTRACT FROM AUTHOR]

This paper examines the impact of institutional pressure (IP), top management support (TMS), green supply chain management practices (GSCM), and supply chain competitive advantage (SCCA) on corporate environmental performance (EP). We also analyze the mediation effect of GSCM on the interplay between TMS and EP. Additionally, the paper also provides an analysis of the moderating role of SCCA between IP and EP. To attain the objective of this research, we assembled data from 710 business entities within the Shaanxi province of China utilizing a survey design approach. The structural equation model (SEM) was applied to test and assess the hypothetical outline. The study outcomes empirically show that TMS, GSCM, and SCCA positively and significantly impact EP. Interestingly, our study found an insignificant association between IP and EP. The study's results also demonstrate that IP directly relates to top management support. Moreover, the study's empirical findings reveal that GSCM positively mediates IP and EP. The study findings show that SCCA shapes IP and EP's connection. Accordingly, the practical implications of our study's findings suggest that business managers, investors, and government agencies must know the importance of adopting sustainable practices within the supply chain. Business managers must take action to integrate environmental criteria into supplier selection, evaluate suppliers' EP, and collaborate with eco‐friendly suppliers. Hence, government agencies, stakeholders, and business managers can use this information to shape regulations and policies that encourage businesses to adopt sustainable supply chain practices. Offering incentives such as tax benefits or grants for sustainability initiatives can also promote adoption. The study recommends that a business culture that targets improving EP due to IP and top management support is essential in achieving GSCM practices, thereby promising competitive advantage. [ABSTRACT FROM AUTHOR]

The objective of this study is to examine the impact of government environmental concerns on green innovation and whether this has a "leverage effect" or a "crowding‐out effect." This study employs a two‐way fixed‐effects model to conduct an empirical test using panel data from 2010 to 2020 on Chinese firms listed in heavy‐polluting industries. The results suggest that an increase in government environmental concerns can promote corporate green innovation. However, government environmental concerns primarily stimulate strategic innovation rather than substantive innovation. After a series of robustness and endogeneity tests, the conclusions of this paper still hold. Corporate green innovation induced by government environmental concerns is not the "leverage effect" superimposed on existing innovation activities but the "crowding‐out effect" of other technological innovation. The heterogeneity tests in this paper indicate that the impact is more pronounced for firms with poorer environmental conditions, stronger political connections, and richer executive backgrounds. [ABSTRACT FROM AUTHOR]

Drought is an important meteorological event in China and can cause severe damage to both livelihoods and socio‐ecological systems, but current seasonal prediction skill for drought is far from successful. This study used convolutional neural network (CNN) to build an effective seasonal forecast model for the summer consecutive dry days (CDD) over China. The principal components (PC) of the six leading empirical orthogonal function modes of CDD anomaly were predicted by CNN, using the previous winter precipitation, 2‐m temperature and 500 hPa geopotential height as predictors. These predicted PCs were then projected onto the observed spatial patterns to obtain the final predicted summer CDD anomaly over China. In the independent hindcast period of 2007–2018, the interannual variabilities of first six PCs were significantly predicted by CNN. The spatial patterns of CDD were then skillfully predicted with anomaly correlation coefficient skills generally higher than 0.2. The interannual variability of summer CDD over the middle and lower Yangtze River valley, northwestern China and northern China were significant predicted by our CNN model three months in advance. CNN identified that the previous winter precipitation was the important predictor for PC1–PC3, whereas the previous winter 2‐m temperature and 500 hPa geopotential height were important for the prediction of PC4–PC6. This research provides a new and effective method for the seasonal prediction of summer drought. Plain Language Summary: Drought can cause serious agricultural and ecosystem disasters, so its forecast is valuable for preventing and mitigating related natural disasters and regional socioeconomic sustainability. However, current prediction skill for drought is far from successful since its extreme feature. The gradually emerging deep learning methods offer new possibilities, but how to effectively apply deep learning models in climate prediction with a small sample size remains an open question. In this paper, we build seasonal prediction convolutional neural network model for summer consecutive dry days over China using previous winter predictors. This model achieves significant prediction skill three months in advance. The empirical orthogonal function decomposition is used to reduce the dimensionality of consecutive dry days data in our model. Our research provides a new perspective for drought prediction, and it is expected that such method will be also useful for other seasonal climate prediction problems. Key Points: Convolutional neural network (CNN) skillfully predicts summer consecutive dry days (CDD) over China three months in advanceThe principal components of CDD are predicted by CNN and then projected on the observed spatial patternsPrevious winter 2‐m temperature, geopotential height at 500 hPa and precipitation are the essential predictors in CNN [ABSTRACT FROM AUTHOR]

A convenient and effective method based on vector analysis was proposed in this paper to quantitatively describe the pattern of the wind speed distribution curve. This method can accurately describe the steepness of the single‐peak curve by using two parameters of concentration degree (CD) and concentration period (CP). Through the analysis of wind speed data in China over the past 40 years, this paper found that regional wind resources with larger CD were poorer, while regional wind resources with larger CP were richer. In addition, there were obvious cubic relationships between the CP and the average wind power density. These two parameters could reflect the richness of wind energy and realize the comparisons of wind resources across time and scales. In comparison with conventional approaches, this method is simpler and avoids fitting process, which has broad promotion prospects in the field of power grids. [ABSTRACT FROM AUTHOR]

Since the "double carbon" target was proposed in 2020, emissions reduction has become the focus of the Chinese government's work. Industrial development is a crucial factor contributing to the increase in carbon emissions. Therefore, implementing carbon reduction in the industrial sector is an important part of China's goal of "double carbon." In this context, this paper uses a three‐stage data envelopment analysis model to calculate the green total factor productivity (GTFP) of 18 industry sectors in Shanxi Province. The results show that: (1) the external environment has influence on the GTFP of energy revolution reform pilot area industrial sectors, and the efficiency value of two industries is overestimated before excluding environmental factors; (2) the industry difference of GTFP is significant, among which pharmaceutical manufacturing industry has the greatest promoting effect on GTFP, and ferrous metal mining and dressing industry has the greatest inhibiting effect on GTFP; (3) there is a serious redundancy in R&D investment of energy revolution reform pilot area in China, and only six industries belong to zero redundancy. (4) To reflect the GTFP of various industrial sectors more clearly, this paper divides four industries: "Double‐high" industry, "High‐low" industry, "Low‐high" industry, and "Double‐low" industry. [ABSTRACT FROM AUTHOR]

Aims: The aim of this study was to analyse the status, hotspots and trends of research on oral care for the elderly in mainland China in the past 20 years through bibliometrics, which aims to provide new ideas and targets for future clinical work and research. Design: Bibliometric analysis. Methods: Relevant literature was retrieved from China National Knowledge Infrastructure, Wanfang, China Science and Technology Journal Database, Web of Science and PubMed. NoteExpress, Co‐Occurrence and CiteSpace were used to analyse bibliometric features in terms of year of publication, journal of publication, authors, institution and keywords. Results: A total of 716 related articles were obtained. The number of publications shows an increasing trend over time, only 2017–2021; 309 papers were published, accounting for 43.2% of the total number of publications. A total of 238 articles were published in Science Citation Index journals or Chinese core journals, accounting for 33.2% of the total number of articles. The study of oral health‐related quality of life in the elderly is a hot research topic. There is a lack of research on the elderly living in elderly care facilities. [ABSTRACT FROM AUTHOR]

In the circumstances of "Carbon Peak," it is imminent to implement green construction technology in the construction industry as it is a major source of CO2 emissions. Nevertheless, little study has been done on the impact of self‐face awareness (SA) on green building project performance (GP). On the basis of a large‐scale questionnaire survey in China and an in‐depth analysis of the four categories (cognition, behavior, satisfaction, and performance), this paper has added an SA dimension, and proposed a new impacting path. Then, based on the improved conceptual model for measuring the impact of green construction behavior on GP, this paper has conducted empirical tests by using a large sample of questionnaire data and partial least square‐structural equation modeling method. The results show that: (1) green construction behavior has a positive impact on GP, and the impact of perceived behavioral control of green construction technology is most significant for promoting green construction in the industry, and SA has a significant positive effect on green construction in the industry; (2) environmental perception and perceived behavioral control for green construction technology play a mediating role; and (3) significant differences indeed exist in the multigroup analysis, and the biggest difference is working experiences in the engineering field. Finally, this paper has proposed corresponding management implications based on the above findings. The main contribution of this study is that this study has developed a new dimension (SA) to the model considering Chinese national and cultural differences, in an attempt to reveal the impact of green construction technology on GP in the Chinese context. In addition, the promotion of green construction (PGC) in the construction industry was also added based on the sustainability perspective, which is the first attempt to explore the role of the PGC. [ABSTRACT FROM AUTHOR]

Achieving environmental equity is important for ensuring resource utilization efficiency and realizing sustainable development. Using panel data of 286 cities in China from 2011 to 2018, this paper analyzes whether financial support in the form of digital finance can mitigate environmental inequality. The findings indicate that (1) digital finance has a significant mitigating effect on environmental inequality. Digital finance development has a stronger industrial pollution emission reduction effect on high‐polluting regions than on low‐polluting regions and can reduce the environmental pollution gap between regions. The results of robustness tests such as an endogeneity test support this finding. (2) Digital finance development can have a stronger mitigating effect on environmental inequality in regions with a stronger local government governance capacity and environmental preferences. Digital finance can be a more significant inhibitor of environmental inequality in areas where industries transfer out due to their stronger needs for industrial transformation and finance. (3) Residential income and green technology innovation are important factors affecting industrial pollution emissions and reductions. Digital finance development can narrow the income gap between regions and promote the convergence of green technology innovation capacity, in turn alleviating environmental inequality. In the future, while continuing to promote the development of digital finance, it is necessary to improve the governance capacity of local governments, to increase the efficiency of resource utilization in places where industrial transfer is undertaken and to strengthen the role of financial support in industrial pollution control. [ABSTRACT FROM AUTHOR]

With the rapid development of re‐electrification, traditional load forecasting faces a significant increase of influencing factors. Existing literature focuses on examining the influencing factors related to load profiles in order to improve the prediction accuracy. However, a large number of redundant features may lead to the overfitting of the forecasting engine. To enhance the performance of extreme learning machine (ELM) under massive data scale, this paper presents a kernel extreme learning machine (KELM) based method which can be used for short‐term load prediction. First, a feature dimensionality reduction is performed using a kernelized principal component analysis, which aims to eliminate redundant input vectors. Then, the hyperparameters of KELM are optimized to improve the prediction accuracy and generalization. Case studies based on a province‐level power system in China demonstrate that the presented method can significantly improve the accuracy of load forecasting by 3.14% in contrast to traditional ELM. [ABSTRACT FROM AUTHOR]

Objective: To explore the development of hip arthroscopy in China through reviewing the change of the application of hip arthroscopy operation on treating femoracetabular impingement (FAI). Method: Papers were retrieved from January 1, 2005 to November 1, 2019, from databases CNKI, Wanfang Data, VIP, PubMed, and Embase. The keywords are Hip Impingement, Femoroacetabular impingement, Hip arthroscopy, Arthroscopic operation, Hip Arthroscopy operation, and Arthroscope, etc. The quality of papers was assessed through MINORS , and statistics and meta‐analysis were performed by Word, Excel, and Revman 5.3 Zurich, Switzerland. Results: From a total of 8,953 papers, 46 review articles without data and 48 articles with data were involved, and 25 papers were included in the Meta‐analysis. The twenty‐five papers were selected from 48 papers with data, of which 41 were reported in Chinese, 11 were missing complete Harris scores, five did not mention the number of patients who had lost follow‐up, three had minors quality scores below 7, one did not have enough FAI cases, and three did not have standard deviations in Harris scores. Overall, in China, the application of hip arthroscopy regarding FAI has flourished while maintaining a high level of treatment and has reached its peak in the past 2 years. Conclusion: With the rapid development of hip arthroscopy in China, hip operation is widely recognized, many reports on its application on FAI have emerged successively, and the scope of application and technical level have been improved. [ABSTRACT FROM AUTHOR]

Nudging the amelioration of enterprise environmental performance is the micro‐foundation for effectively enhancing resource utilization and realizing sustainable development. Based on the upper echelons theory, the characteristics and previous experiences of managers determine their strategic choices and then affect the behavior of enterprises at the whole social layer. Nevertheless, the literature concerning the effect of CEO green experience on enterprise environmental performance is void. To bridge this gap, this paper uses the data of China's A‐share listed enterprises from 2010 to 2021 to empirically investigate the direct impact, influence mechanisms, and heterogeneities of CEO green experience on enterprise environmental performance. The study finds that CEO green experience can significantly promote the improvement of enterprise environmental performance. Based on the main effect, to exploring potential mechanisms behind the conclusion, we figure that environmental ethics commitment, environmental protection investment, and green technology innovation are the core mechanism approaches during the process of CEO green experience affects environmental performance. Heterogeneity analysis of CEO characteristics demonstrates that the green experience of female CEOs, older CEOs, and high educated CEOs both have a pronounced effect on ameliorating enterprise environmental performance. Furthermore, the positive effect of CEO green experience on environmental performance is more prominent in non‐state‐owned enterprises, heavily polluting industries, and regions with high environmental protection pressure. Besides providing an effective supplement for the research on managers and environmental performance, this paper also generates micro‐empirical support for government departments to formulate and optimize environmental policies. [ABSTRACT FROM AUTHOR]

This study proposes a novel method, which is a U‐shaped convolutional neural network that combines non‐local attention mechanisms, Res2net residual modules, and terrain information (UNR‐Net). The original U‐Net method and the linear regression (LR) method are conducted as benchmarks. Generally, the UNR‐Net has demonstrated promise in performing a 10× downscaling for daily 2‐m temperature over North China with lead times of 1–7 days and shows superiority to the U‐Net and LR methods. To be specific, U‐Net and UNR‐Net demonstrate higher Nash‐Sutcliffe Efficiency coefficient values compared to LR by 0.052 and 0.077, respectively. The corresponding improvements in pattern correlation coefficient are 0.013 and 0.016, while the root mean square error values are higher by 0.22 and 0.338, respectively. Additionally, the structural similarity index metric is higher by 0.033 and lower by 0.015. Furthermore, regions with significant errors are primarily distributed in complex terrain areas such as the Taihang Mountains, where UNR‐Net exhibits noticeable improvements. In addition, the 12 components‐based error decomposition method is proposed to analyze the error source of different models. Generally, the smallest errors are observed during the summer season and the sequence error component is proven to be the main source error of 2‐m temperature forecasts. Furthermore, UNR‐Net consistently demonstrates the lowest errors among all 12 error components. Therefore, combining the numerical weather prediction model and deep learning method is very promising in downscaling temperature forecasts and can be applied to routine forecasting of other atmospheric variables in the future. Plain Language Summary: This research proposes a new method for downscaling using deep learning. The method uses a specific type of neural network called UNR‐Net, which combines attention mechanisms, residual modules, and terrain information. The performance of UNR‐Net is compared to two other methods: U‐Net and LR. In the study, UNR‐Net shows promise in performing a 10× downscaling of the daily 2‐m temperature in North China. The UNR‐Net demonstrates the best overall performance among all the comprehensive indicators (NSE, pattern correlation coefficient, root mean square error, and structural similarity index metric). Errors in the predictions are mainly found in complex terrain areas like the Taihang Mountains, but UNR‐Net shows noticeable improvements in these regions. The study also proposes a 12 components‐based error decomposition method to analyze the error sources of different models. All in all, it is found that the smallest errors are observed during the summer season and the main source error is the sequence error component. Additionally, when considering lead times of 1–7 days, UNR‐Net consistently shows the lowest errors among all 12 error components. Based on these findings, combining numerical weather prediction models with deep learning methods holds great promise for generating high‐resolution temperature forecasts. Key Points: This paper presents a novel deep learning downscaling method, UNR‐Net, capable of downscaling daily 2‐m temperature by a factor of 10The overall performance of the UNR‐Net method surpasses the U‐Net method and linear regression methodThe 12 components‐based error decomposition method is proposed to analyze the error source of different models [ABSTRACT FROM AUTHOR]

A PDE‐constrained model predictive control (MPC) algorithm for open‐channel systems based on the Saint‐Vevant(S‐V) equations is investigated in this paper. The S‐V equations, which precisely model the dynamics of open‐channel systems, are quasi‐linear hyperbolic partial differential equations (PDEs) without analytical solutions. Directly applying the S‐V equations to an MPC controller design becomes sophisticated. In this work, the calculus of variation is used to obtain the adjoint equations and the adjoint analysis method is utilized to deduce the gradients of the MPC optimization problem. Particularly, the physical constraints involving both the state and control variables are also considered. A gradient‐based optimization algorithm in combination with the numerical computation of Preissmann implicit scheme is proposed to solve the constrained MPC optimization problem. The control performances of the developed PDE‐constrained MPC algorithm with respect to the controlled water levels and gate openings are compared with those of the MPC controller designed for the linearized model. All the simulation tests are carried out on an aqueduct reach in Yehe Irrigation District in Hebei Province, China. The results show that the proposed PDE‐constrained MPC algorithm is a promising method in dealing with the constraints in terms of hyperbolic PDEs, control variables and state variables simultaneously. [ABSTRACT FROM AUTHOR]

Prospecting for and exploiting buried mineral deposits is currently challenging. Given their high precision and resolution, reflection seismic methods might be useful in such applications involving deep mineral deposits. However, there are few open seismic datasets available from mineral deposit exploration, especially in hardrock environments. The world‐class Caosiyao porphyry Molybdenum deposit (1.76 Mt) in the Jining area of Inner Mongolia, China, is largely covered by loess layers, which poses challenges to its exploration. Seismic reflection surveys were conducted to help delineate the deep granite porphyry intrusions and associated orebodies. This paper presents the raw seismic reflection dataset from three profiles on the Caosiyao deposit area, which can be used as a standard dataset for reflection seismic processing in shallow coverage and hardrock areas. Situated at the juxtaposition of the Khondalite Belt and the Trans‐North China Orogen in the northern North China Craton, the Jining region hosts considerable known porphyry Mo deposits. As such, this open dataset can assist in research on deep geological structures and hence increase prospecting efficiency in geologically similar areas. [ABSTRACT FROM AUTHOR]