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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]

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]

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]

In order to solve the huge impact of the digital information age on many technical and industrial fields, a periodic fast search genetic algorithm is proposed. Based on the reconnaissance mission, this paper introduces the common allocation strategy into mission planning, and constructs the mathematical model of multi unmanned aerial vehicle (UAV) cooperative reconnaissance mission planning decision‐making. The proposed periodic fast search genetic algorithm is used to solve the problem of multi UAV cooperative reconnaissance mission planning. In 2020, the industry growth rate of global UAV technology expenditure was as high as 30.6%, and the compound growth rate of UAV in China reached 63.5%, which is enough to see the great prospect of the integrated development of UAV technology and different industries. The experiment evaluates the log verification module of UAV by comparing the two data structures of Merkle tree and linear, and the time and memory overhead of storing and verifying logs, which shows the effectiveness of the log verification scheme in this paper. [ABSTRACT FROM AUTHOR]

How to effectively utilize renewable energy and improve the economic efficiency of microgrid system and its ability to consume renewable energy has become one of the main problems facing China at present. In response to this challenge, this paper establishes a multiobjective capacity optimization model with the minimum levelized cost of energy, the maximum proportion of renewable energy consumption, and the minimum comprehensive system cost. Based on this model, a new improved beluga whale optimization algorithm is proposed to solve the multiobjective optimization problem in the capacity allocation process of wind–solar–storage microgrid system with the goal of ensuring that the microgrid can meet the maximum load demand at different moments throughout the year. In this paper, opposition‐based learning, artificial bee colony, dynamic opposite, and beluga whale optimization are combined to improve the population diversity and convergence accuracy, thereby enhancing the optimization performance of the algorithm. Finally, after finding the optimal Pareto front solution, the Technique for Order Preference by Similarity to an Ideal Solution is used to help decision‐makers select the optimal solution. Using real load data and meteorological data, the results of this paper show that the multiobjective capacity allocation optimization method of grid‐connected scenic storage microgrid system based on the improved beluga whale optimization algorithm can improve the economics of the wind–solar–storage microgrid system and promote the photovoltaic consumption simultaneously, providing a solution for the realization of low‐carbon power and regional economic development. The best‐found levelized cost of energy for the wind–solar–storage microgrid system is 0.192 yuan/kWh. [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]

Bayesian network (BN) is an important tool in probabilistic seismic risk analysis (PSRA) due to its holistic nature and powerful probabilistic inference capabilities. However, while the information that can be stored by BN includes variable values, probability distributions, and relationships between variables, it does not involve event quantities. The results obtained from PSRA and probabilistic seismic hazard analysis (PSHA) are commonly frequency‐related (the number of occurrences per unit time), fundamentally describing event numbers. BN assumes a fixed event number relationship between nodes, but the aftershock counts vary for different mainshock magnitudes. This limitation further restricts its effectiveness in lifespan PSRA for structures. Therefore, this study aims to propose an enhanced BN (EBN) for modeling aftershock PSHA (APSHA) considering frequency information. This paper first introduces the modeling method using BN, including PSHA and a simplified model of APSHA using Båth's law. Next, an EBN that can effectively address frequency issues between the mainshock and aftershocks is presented for modeling APSHA considering the modified Omori's law, while the mathematical principles of both forward and backward inferences for the EBN are elaborated in detail. Then, the article carefully analyzes the utilization of the EBN for APSHA modeling under different scenarios where the information regarding the mainshock is known to varying extents, followed by the extension of the EBN in a time domain to obtain time‐dependent aftershock hazard. Finally, an example of APSHA in a specific location in China is illustrated. [ABSTRACT FROM AUTHOR]

As urban population increases, integrated underground–aboveground complexes are being constructed at growing paces in major cities. The seismic analysis of such complexes is crucial for the safety and functionality in the threat of potential earthquake disasters. However, fine‐grained numerical modeling and analysis of such large and complex structures are still inefficient due to the consideration of the soil–structure interaction (SSI). To address this challenge, an efficient approach for numerical modeling of large‐scale seismic SSI analysis is presented in this paper to overcome the limitations of existing finite element analysis (FEA) software. Moreover, a multi‐graphic processing unit (GPU) parallel explicit algorithm is implemented for the nonlinear dynamic SSI problems to further increase the computational efficiency. A large underground–aboveground complex project in China is used as an example to demonstrate the capability of the integrated method. The accuracy and reliability of the multi‐GPU parallel explicit finite element algorithm for SSI analysis (GFEA‐SSIA) are verified through a comparative analysis of the linear‐elastic and nonlinear dynamic response of the building calculated by GFEA‐SSIA and common FEA software. Finally, the structural response and structural damage of the underground–aboveground complex are analyzed under multidirectional seismic motions, and the damage distributions of the structures are provided. [ABSTRACT FROM AUTHOR]

Accurate rainfall measurement with a precise spatial and temporal resolution is essential for making informed decisions during disasters and conducting scientific studies, particularly in regions characterized by intricate terrain and limited coverage of automated weather stations. Retrieval of precipitation with satellite is currently the most effective means to obtain precipitation over large‐scale areas. The key to enhancing the accuracy of precipitation estimation and forecasting in regions with complex terrain lies in effectively integrating satellite data with topographic information. This paper introduces a deep learning approach called AttUnet_R_SFT that utilizes high temporal, spatial, and spectral resolution data obtained from the Fengyun 4A satellite, and incorporates the Deep Spatial Feature Transform (SFT) layer to incorporate geographical data for estimating half‐hourly precipitation in northeastern China. We assess it by compared to operational near‐real‐time satellite precipitation products demonstrated to be successful in estimating precipitation and baseline deep learning models. According to the experimental findings, the AttUnet_R_SFT model outperforms practical precipitation products and baseline deep learning models in both identifying and estimating precipitation. The main enhancement of the model performance is shown in the windward slope of the Greater Khingan Mountains as a result of the successful incorporation of geographical data. Hence, the suggested framework holds the capability to function as a superior and dependable satellite‐derived precipitation estimation solution in regions characterized by intricate terrain and infrequent rainfall. The findings of this study indicate that the utilization of deep learning algorithms for satellite precipitation estimation shows potential as a fruitful avenue for further research. Plain Language Summary: A deep learning model named AttUnet_R_SFT is proposed, which use high temporal, spatial and spectral resolution data from the Fengyun 4A satellite, and combines with the Deep Spatial Feature Transform (SFT) layer to input geographic information for half‐hourly precipitation estimation in the complex terrain region represented by northeast China. The model can provide a reference for improving the performance of precipitation estimation in areas with complex topography. Key Points: A deep‐learning model is proposed to effectively fuse satellite multispectral data of the Fengyun 4A satellite, with topographic informationHalf‐hourly precipitation is estimated with higher temporal resolution, which is closer to the operational needs of weather forecastingAs precipitation in the study area is a non‐high‐frequency event, data enhancement is attempted to use and obtain effective results [ABSTRACT FROM AUTHOR]

Aim: To investigate the seizure course of PCDH19 clustering epilepsy (PCDH19‐CE) in a cohort of female children in China. Method: This ambidirectional cohort study examined 113 female patients with PCDH19‐CE through multicentre collaboration. Prognostic factors for seizure freedom were evaluated by multivariate Cox regression analysis. Results: The median seizure course period from seizure onset was 6 years 6 months. Of 113 patients, 78% and 56% experienced seizure freedom for at least 1 year and at least 2 years respectively. In patients younger than 5 years (n = 30), 5 to 10 years (n = 52), and older than 10 years (n = 31), 57%, 81%, and 94% experienced at least 1 year of seizure freedom, and 32%, 52%, and 84% experienced at least 2 years of seizure freedom, respectively. However, 58% (65 out of 113) relapsed at least once after more than 1 year of seizure freedom without trigger exposure (40%) or because of common triggers, including fever (43%) and antiseizure medication (ASM) reduction (29%). There was an 84% risk of seizure relapse after ASM reduction attempts. The likelihood of seizure freedom decreased with early age at seizure onset and developmental delay. Interpretation: Patients with PCDH19‐CE exhibit increasing seizure freedom with age, but there is a risk of relapse. ASM reduction in children younger than 10 years old requires caution. Patients with early seizure onset and developmental delay have a reduced chance of seizure freedom. What this paper adds: The seizure freedom rate in PCDH19 clustering epilepsy gradually increases with age.The disease course is characterized by relapsing–remitting seizures.Antiseizure medication reduction requires caution for patients younger than 10 years of age.Patients with early seizure onset and developmental delay are less likely to achieve seizure freedom. [ABSTRACT FROM AUTHOR]

All provinces of China respond to the central government, predict future carbon dioxide emissions, and formulate action plans detailing how the province intends to fulfill its target of carbon emission peaking before 2030. Based on the bottom‐up energy consumption prediction and top‐down goal verification, this paper constructs a set of regional carbon dioxide emission prediction methods. Compared to the traditional bottom‐up prediction method, this method could simplify the parameters while improving the prediction accuracy. This model is used to predict and analyze the process of carbon dioxide emission peaking in Zhejiang. The results show that the mean absolute percentage error of the retrospective prediction value is only 1.56%. Zhejiang will reach carbon dioxide emission peaking around 2029–2030, and the peak value will be 569.7 million tons. Different factors have different effects on the process of carbon dioxide emission peaking. There is a strong correlation between the peak time of carbon dioxide emission and the production time of major energy‐consuming projects in Zhejiang. Meanwhile, if the 16 nuclear reactors are not put into operation, Zhejiang will not be able to achieve the goal of carbon dioxide emission peaking. Besides, the basic data used in this model is mainly from the local statistical departments of the region. Thus, it can be applied to other provinces and regions conveniently. [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]

More than 50 earthquakes occurred in the Luding region, including a 6.8‐magnitude earthquake on September 5, 2022, which induced huge amounts of geological disasters. As the main triggered factors for the geological disasters, the vegetation, precipitation and temperature show regular changes on the time axis. Thus, this paper based on the spatial–temporal evolution of the precipitation, temperature and normalized difference vegetation index (NDVI), focuses on the susceptibility of the Luding area using the weighted information content method (ICM) and analytic hierarchy process (AHP) for the post‐earthquake regional planning and reconstruction. In the Luding area, it was found that there were 18 debris flow gullies, and 470 geological disasters scattered in the debris flow gullies. The NDVI of the study area has been declining in recent years, with only about 12% of the NDVI increasing from 2015 to 2020. From 2011 to 2015, the annual cumulative precipitation has been dropping overall, while the July average temperature has increasing quadratic functions after decreasing trend. Furthermore, the studied area's geological hazards susceptibility was classified into five categories, with extremely low susceptibility accounting for 5.82%, low susceptibility accounting for 13.61%, moderate susceptibility accounting for 38.54%, high susceptibility accounting for 39.96% and extremely high susceptibility accounting for 2.08%. The geological disasters in moderate, high and extremely high susceptibility accounted for approximately 95.08%, and the covered area of geological disasters in moderate, high and extremely high susceptibility accounted for 88.06%. Through the receiver operating characteristic (ROC) curve of the model verification found the AUC = 0.743. The geological hazards susceptibility study results show that the approach is useful for the analysis and prevention of geological disasters. [ABSTRACT FROM AUTHOR]

The Dunhuang Basin, situated in western China along the Altyn Tagh Fault (ATF) zone, intersects the Tethys and Paleo‐Asian Ocean tectonic domains. Influenced by both the ATF system and the far‐field effects of the Qiangtang‐Lhasa‐Eurasia collision during the Mesozoic, the mechanism of the Jurassic sedimentary migration of the basin in response to tectonic movements is unclear so far. The paper uses a comprehensive approach, including field geological surveys, lithologic and lithofacies discern, stratigraphic relationships analysis and 2D seismic profile interpretation, to examine the distribution of Jurassic residual strata in the basin. The comprehensive results of our study suggest that the Dunhuang Basin exists as an isolated block with unique tectonic and sedimentary evolution characteristics. In the Early Jurassic, the Dunhuang Basin underwent initial rifting, leading to the formation of small segmented intermontane sags. This phase was marked by the coarse particle sedimentary system of alluvial fans and braided rivers, represented the near source rapid deposition in the initial formation period of the basin. Stratigraphic distribution was primarily influenced by pre‐Jurassic basement topography and was not significantly constrained by faulting during this period. The formation of these isolated discontinuous small intermontane sags indicates the segmented activities of the ATF in the Early Jurassic period. In the Middle Jurassic period, influenced by the ATF dextral strike‐slip faulting, sedimentation extended eastward and the depocenter migrated clockwise compared with the distribution of the Middle Jurassic strata within the Dunhuang Basin. This period witnessed the development of coal measure strata at the basin's margins and lacustrine fine‐grained clastic deposition in the centre. The segmented fracture of the ATF gradually initiated a unified dextral strike‐slip tectonic movement. In the Late Jurassic period, sedimentary strata were locally present in the Wanyao Sag but absent in other sags. The depocenter migrated counterclockwise compared with the distribution of Middle Jurassic strata within the Dunhuang Basin, due to regional uplift accompanied by the ATF sinistral strike‐slip faulting caused by the collision between the Lhasa Block and the Eurasia Plate. The depocenter migration of the Dunhuang Basin constrained within the ATF system from the Early to Middle and Late Jurassic can be attributed to the transition of the ATF strike‐slip faulting in context of the stress relaxation and compression between the collision of the Qiangtang and Lhasa blocks to the Eurasia Plate, respectively. [ABSTRACT FROM AUTHOR]

In the chemical flooding process, the premature breakthrough of chemical agents in production wells results in a large waste of chemical agents and increases the volume and processing difficulty of the produced fluids. The early warning method of chemical agent channeling can predict the strength of agent channeling in advance. The practice of chemical flooding shows that the production performance can be used for early warning of chemical agent channeling. In this paper, we analyze the relationship between cumulative oil production and cumulative polymer production of production wells in polymer–surfactant flooding. Three types of curves according to the enhanced oil production characteristics of chemical flooding, including convex type, S‐type, and concave type. We use the drop speed of the water–oil ratio and the rapid‐decline speed of water cut as early warning indicators to predict the channeling coefficient. A Latin hypercube experimental design method is used to design a polymer–surfactant flooding scheme with the main control factors of the channeling coefficient and early warning indicators. Numerical simulation is used to calculate samples of the channeling coefficient and early warning indicators under various conditions. The drop speed of the water–oil ratio reference value model and the rapid‐decline speed of the water cut reference value model are determined with a multiple regression method. A prediction model for the chemical agent channeling coefficient is established using the deviation coefficient of an early warning index. The method is applied in the Ng54‐61 polymer–surfactant flooding pilot area in the west of the Gudong Seventh District, Shengli Oilfield, China, and the error between the predicted result and the actual value is less than 10%. This research is helpful in taking effective antichanneling measures and improving the oil recovery degree of chemical flooding reservoirs. [ABSTRACT FROM AUTHOR]

Carbon peaking and carbon neutrality will be important policies to constrain China's economic and social development in the future. Based on the theory of computable general equilibrium, CGE model of carbon emission was constructed in this paper to simulate the influence of different scenarios of carbon emission reduction on economic and social development. The major contribution is to subdivide the energy sector according to primary energy and secondary energy, and construct the macro SAM table and micro SAM table of 21 energy sectors in 2017 to quantitatively simulate the impact of carbon emission reduction policies on China's economy and society, and put forward some policy suggestions based on this. [ABSTRACT FROM AUTHOR]

This paper explores the impact of the political hierarchies of cities in China from different perspectives. First, we examine the economic disparities between prefectural cities and municipalities. Furthermore, this paper draws upon a quasi‐ experiment to analyze the impact of upgrading Chongqing to a municipality in 1997 using the synthetic control method. The city‐upgrading policy significantly increased Chongqing's gross domestic product (GDP) in the following 4 years. Finally, we find that the policy increased GDP in treated cities within 1200 km of Chongqing by about 10%–13% relative to the control cities. [ABSTRACT FROM AUTHOR]

Using data from the 2015 China Household Financial Survey (CHFS) this paper examines the effect of culture on the gender gap in financial literacy. We exploit geographical differences in culture in China, comparing outcomes between rural and urban areas and between areas in the east and west (Shanghai and Chongqing). Using the Blinder‐Oaxaca decomposition we show that, nationally, the gender gap in financial literacy is entirely the product of differences in the way men and women acquire financial literacy. It is a result consistent with cultural effects. When considering just women in Shanghai and Chongqing we observe a raw financial literacy differential of 13% (favoring Shanghai). This gap is also the product of differences in the way financial literacy is acquired. It provides additional evidence as to the importance of culture when it comes to understanding financial literacy. [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]

The high incidence of adolescent depression has become the focus of social and academic attention. Exercise is an important method to improve adolescent depression, but its intervention effect is still controversial. This study first compares and analyzes the relevant studies at home and abroad and finds that exercise prescription in adolescent depression intervention is not accurate enough. A meta‐analysis was conducted to develop a precise exercise intervention strategy for adolescent depression. Firstly, this thesis identified how to optimize five elements (exercise intensity, exercise frequency, exercise time, exercise cycle, and exercise type) of exercise prescription to improve depression in adolescents. This is the problem. Furthermore, the concept of "precision exercise" was proposed, and a precision exercise intervention strategy (moderate‐intensity aerobic exercise for 8–10 weeks, 3 times/week, 45–50 min/time) was constructed to improve adolescent depression. This paper also presents research that strengthens the cross‐sectional research and empirical research on adolescent depression and establishes a precision exercise prescription database for adolescent depression in China. In conclusion, this study not only puts forward the concept of "precision exercise" but also constructs a precision exercise intervention strategy for adolescent depression, which has important theoretical and practical significance for improving the high incidence of adolescent depression. [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]

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]

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]

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]

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]

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]

One of the most dramatic changes in global publishing in the last decade has been the emergence of China. China now has more researchers than the United States, outspends the United States and European Union in research and publishes more scientific papers each year than any other nation in the world. The quality of these papers is also increasing, with more appearing in top‐ranked journals and gaining more citations overall. Despite this success, China has gained an unenviable reputation for research misconduct and geopolitical issues threaten its continuation. Given the impact of China's growing presence on editors, publishers and non‐Chinese authors seeking to publish in the same journals, it is important to understand the reasons, directions and outcomes of these changes, their effect on Chinese scholars and local Chinese journals, and where they might be leading. In this review paper I explore the rise of Chinese scholarship, its influence on global publishing and on Chinese scholars, and how the Chinese government is responding to its new role in global academic publishing. [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]

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]

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]

The Shanghai Soft X-ray Free-Electron Laser (SXFEL) is the first X-ray freeelectron laser facility in China. The SASE beamline, which consists of a pinkbeam branch and a mono-beam branch, is one of the two beamlines in the Phase-I construction. The pink-beam branch opened for users in 2023 after successful first-round beamline commissioning. In this paper, the design of the beamline is presented and the performance of the pink-beam branch is reported. The measured energy-resolving power of the online spectrometer is over 6000 @ 400 eV. The focusing spot size of the pink beam is less than 3 μm in both the horizontal and vertical at the endstation. [ABSTRACT FROM AUTHOR]

This paper examines the impacts of a government‐led e‐commerce expansion project on household income. We find that the project has led to increases in rural household income. The positive impacts are more prominent for lower‐income rural households. The income‐increasing effects are driven by the reduction in information search costs and transportation costs. The provision of complementary interventions for e‐commerce, such as promoting the internet‐related skills of farmers and the expansion of formal financial credit support is also important for the program's success. The results provide policy implications for the design and implementation of government‐led e‐commerce policies in developing economies. [ABSTRACT FROM AUTHOR]

Organic‐rich shale in saline lacustrine basins holds significant importance as a source rock for conventional hydrocarbon exploration and has emerged as a prominent target for unconventional hydrocarbon exploration and development in recent years. Based on saline lacustrine basins, this paper provides a summary of the organic matter enrichment mechanisms in saline lacustrine basins, considering sedimentary characteristics, biological activities, factors for the organic matter enrichment and consumption, and hydrocarbon generation. The implications for these factors are discussed in relation to the distribution prediction of high‐quality lacustrine shale district settings and the exploration and development of shale oil. Saline lacustrine basins undergo distinct evolutionary stages, each corresponding to different sedimentary stages involving carbonate minerals, sulphate minerals, and alkaline minerals. Moreover, these basins exhibit diverse biological types and experience extensive biological activities. The prosperity of organisms and the accumulation of sedimentary organic matter are ensured by halophilic organisms. Organic matter enrichment in saline lacustrine basins is influenced by two main aspects: the primary productivity of organic matter, which is promoted by the proliferation of halophilic organisms, and the efficient preservation of organic matter facilitated by the strong reducing environment resulting from promoted water salinity stratification. The organic matter consumption in saline lacustrine basins involves bacterial sulphate reduction (BSR) in the early stages, thermochemical sulphate reduction (TSR) in the late stages, and dilution of salt minerals with higher depositional rates. of the presence of salt beds and saline minerals positively influences hydrocarbon generation and expulsion in organic‐rich shale within saline lacustrine deposition. Consequently, continental saline lacustrine basins in China offer favourable conditions for the formation of organic‐rich shale and present broad prospects for the exploration of shale oil and gas resources. [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]

A large‐scale AC/DC hybrid power network has recently been constructed in China because of the fast development of high voltage direct current (HVDC) technology. The receiving AC system must have sufficient system strength to guarantee the safe operation of the DC side. The paradox is that raising the AC side system's strength will increase the short‐circuit current (SCC) level, endangering the safety of the system. In order to resolve the contradiction between the system strength of multi‐infeed DC receiving‐end power networks and SCC, this paper proposes an optimal transmission switching strategy. Firstly, the system strength is characterised by the multi‐infeed short‐circuit ratio (MISCR), followed by constructing a comprehensive constraint set that considers the MISCR and SCC simultaneously. Secondly, to optimize SCC with MISCR and N−1 safety constraints, a mixed integer linear programming model is developed. Finally, to enhance the computing performance for large power systems, a new connectivity constraint set and decision space reduction techniques are provided. The proposed method is tested for effectiveness using the IEEE 30‐bus and IEEE 118‐bus systems. [ABSTRACT FROM AUTHOR]

Multicellular algae are the core topic for understanding the early life evolution on Earth. The timing of origin and cellular differentiation of multicellular algae, however, remains poorly constrained. The Palaeoproterozoic to early Mesoproterozoic is a critical period during which multicellular algae began to occur and evolve in marine environments. This paper reports well‐preserved multicellular fossils from shales of the Chuanlinggou Formation (c. 1.64 Ga) in North China, with emphasis on their holdfast and putative cellular structures. These macroalgal fossils are reasonably diversified and include Chuaria circularis, Tawuia sinensis, Tawuia robusta, Glossophyton ovalis, Glossophyton sp., Tuanshanzia sp. and Changchengia sp.; mainly preserved as carbonaceous compressions, with a few sideritized forms. Field emission scanning electron microscope (FESEM) observation revealed multicellular structures in Chuaria, confirming its biological attributes of a multicellular eukaryote and providing direct evidence that multicellular algae had already originated by the terminal Palaeoproterozoic, earlier than previously speculated. Tuanshanzia sp. and Changchengia sp. developed with a bare rhizome holdfast, suggesting that they had a benthic sessile lifestyle in their late Palaeoproterozoic oceanic habitat. [ABSTRACT FROM AUTHOR]

A model‐circulation increment‐based dynamic statistical technique (MIDST) is proposed in this paper to improve the prediction of summer rainfall over southern China (SC) where quite low prediction skills have been found in the Beijing Climate Center Climate System Model version 1.1 with a moderate resolution (BCC_CSM1.1m). The results show that BCC_CSM1.1m can hardly represent the variability of the summer rainfall anomaly and its year‐to‐year increment over SC, and the skillful predictions are mostly confined over the middle reaches of the Yangtze River. Using the dynamic model output and statistical method, the MIDST is established to capture the coupled modes between the year‐to‐year increments of the summer rainfall anomaly and the associated simultaneous three‐dimensional coupled air‐sea circulation predictors. The cross‐validation indicates that the prediction skills of the MIDST are evidently improved for both the summer rainfall increment prediction and summer rainfall anomaly prediction compared with the direct BCC_CSM1.1m prediction. The skillful prediction can persist for long forecast leads over most regions except southwestern China. As the major predictability source of seasonal prediction, the intense response to changes in the circulation related to the El Niño‐Southern Oscillation (ENSO) is well captured, and thus, the performance improvement of the MIDST is primarily due to its more realistic representation of the incremental circulation related to the ENSO. [ABSTRACT FROM AUTHOR]

As a group of ectoparasites, chiggers (larvae of chigger mites) are the exclusive vector of scrub typhus (tsutsugamushi disease). Rodents are the most important hosts of chiggers. The Anderson's niviventer rat, Niviventer andersoni, is an endemic species of rodent in China. However, few studies have involved this endemic rodent species and its ectoparasites including chiggers. According to the field investigation in five provincial regions of southwest China between 2001 and 2019, this paper retrospectively analysed the infestation and distribution of chiggers on the body surface of N. andersoni in southwest China for the first time. From 77 Anderson's niviventer rats captured, a total of 527 chiggers were collected and they were identified as 39 species and nine genera in two subfamilies of family Trombiculidae. Of 39 chigger species identified, Leptotrombidium deliense and L. scutellare are the most important vectors of scrub typhus in China. The overall infestation indexes were PM = 29.87%, MA = 6.84 and MI = 22.91, and the indexes of chigger mite community were Mf = 39, H' = 2.60, E = 0.71 and D = 0.12. The dominant chigger species are L. wenense, L. xiaguanense and L. fujianense with a total Cr = 51.04%, among which L. wenense is one of the six main vectors of scrub typhus in China. The dominant chigger species are of aggregated distribution among different individuals of the rats. [ABSTRACT FROM AUTHOR]

This paper has conducted a high‐resolution characterization of a deeply buried carbonate karst in the Tarim Basin of China by utilizing the FMI (Full‐bore Formation Micro Image) method integrated with seismic data, drilling cores and thin sections. It was found that the type and scale of wellbore karst architecture are mainly controlled by karst paleogeomorphology and vertical faults. The karst highlands and slopes, respectively, develop vadose karst and phreatic karst, with different compositions of karst elements. In terms of the karst thickness in the wellbore, the vertical fault development zone is almost twice that of the non‐development zone, both for the vadose karst and phreatic karst. Furthermore, the vertical fault is also able to promote the development of mixing karst. The mixing zone is located 55 m below the water table, with a strata thickness of approximately 25 m, a net reservoir thickness of 5–15 m, and an average porosity of 4%–8%, which serves as an effective hydrocarbon reservoir in the Yingshan Formation. The results will provide insights into the vertical division of karst reservoir and help predict reservoirs using well logs. [ABSTRACT FROM AUTHOR]

Lithofacies and micropore characteristics of shale reservoir directly affect the exploration and development of natural gas. To determine the development potential of shales of the Longmaxi Formation in the Western Hunan‐Hubei Region, the lithofacies types and micropore structure characteristics of the Longmaxi Formation shales have been systematically studied in this paper, based on ordinary thin sections, argon ion polishing–scanning electron microscopy, physical property testing, x‐ray diffraction whole‐rock and clay mineral analysis, isothermal nitrogen, and carbon dioxide adsorptions. According to the principle of 'laminar structure + total organic carbon (TOC) + mineral composition of felsic, clay, and carbonate minerals', eight types of shale lithofacies were identified. The effective porosity of the Longmaxi shale ranges from 1.8% to 14.4%, with a peak range from 3% to 6%, while the permeability ranges from 0.001 to 1.27 mD, with an average of 0.106 mD. Combined with the isothermal adsorption experiments, the proportion of mesopores is the largest in the Longmaxi shale, followed by macropores and micropores. Moreover, the pore diameters of mesopores are concentrated between 3 and 10 nm, while those of micropores are concentrated between 0.4 and 0.9 nm. The pore volume of shale is most developed when the content of brittle felsic minerals is 50% ~ 75% and the content of clay minerals is 25% ~ 50%, and the TOC content is positively correlated with the pore volume and specific surface area. There are significant differences in the pore development characteristics of different lithofacies. The shale reservoir space analysis indicates that micropores are controlled by TOC content and clay minerals, while the macropores are controlled by depositional intergranular pores, TOC content, and felsic content, as well as diagenetic pyrite mould pores, microfractures pores, and intercrystalline pores. On the other hand, mesopores are related to a mix of depositional and diagenetic factors with dominant contribution of intergranular pores, intercrystalline pores, organic pores, and intergranular shrinkage fractures pores. It is found that the pore development of massive organic‐rich siliceous shale lithofacies has the best reservoir quality, including well‐connected intergranular pores, intercrystalline pores, organic pores, and shrinkage fractures. Therefore, the massive organic‐rich siliceous shale lithofacies is the dominant fine‐grained reservoir lithofacies in the studied area. Based on understating the pore characteristics of different lithofacies, this study can provide a scientific basis for the prediction of favourable sweet spots of shale gas reservoir in the Longmaxi Formation, western Hunan‐Hubei Region. [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]

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.

Food production is one of the main contributors to greenhouse gas emissions and climate change. China, as a rapidly developing economy, contributes to an unsustainable food system as its consumption of animal products and meat has continued to grow in recent decades. Using the extended theory of planned behavior as the conceptual framework, this paper examines factors influencing consumers' intention to purchase sustainable food in China. To this end, a population‐based face‐to‐face survey was conducted with 2422 respondents in five provinces spanning the north and south of China. The results showed that the traditional constructs of behavioral attitude, subjective norms, perceived behavioral control, and the additional construct of perceived quality are significant in inducing such intentions. This paper suggests that to enhance consumers' willingness to shift to sustainable food consumption, appropriate regulation and monitoring framework is needed to increase consumers' trust toward sustainable food. The government can also cooperate with the media, experts, and social media opinion leaders to ensure that messages on sustainable development are promoted in effective ways. [ABSTRACT FROM AUTHOR]

Equipment maintenance decision is a very critical technology in power grid asset management. The traditional maintenance decision focuses on the analysis of the operation performance of the equipment itself, but lacks the analysis and description of the fuzziness of power equipment outage parameters. Therefore, this paper establishes the reliability assessment model based on equipment health condition monitoring, which makes the maintenance decision transition from equipment level to system level, and the fuzzy mathematics theory is introduced to establish a model describing the fuzziness of equipment failure rate parameter to make system reliability assessment and equipment maintenance decision scheme. Firstly, this paper proposes a fuzzy failure rate model of power transformer based on condition monitoring. Then the fuzzy parameters are combined with the conventional probabilistic reliability assessment method to establish the fuzzy probability hybrid reliability assessment model of the transmission system, and the fuzzy maintenance reliability benefit index is defined and deduced. Finally, a maintenance strategy of transformer based on fuzzy probability hybrid reliability assessment and fuzzy set theory is proposed, and the case study is carried out on a regional power grid in East China. The results show that the proposed model provides an improved maintenance strategy of power equipment. [ABSTRACT FROM AUTHOR]

The term laminopathies refers to a group of congenital diseases characterized by accelerated degeneration of human tissues. Mutations in LMNA, LMNB, ZMPSTE24, and other genes lead to structural and functional abnormalities associated with lamins. One subtype of laminopathy is the generalized lipodystrophy‐associated progeroid syndrome (GLPS), which occurs in patients with heterozygous mutations of the LMNA gene c.29C>T(p.T10I). This paper reports the first case of GLPS in China and compares the clinical features of other GLPS patients with literature reports. A 16‐year‐old male patient was treated for diabetic ketoacidosis, presenting with premature aging appearance, systemic lipodystrophy, severe fatty liver, and decreased bone density. After peripheral blood DNA extraction and second‐generation sequencing, a heterozygous mutation of exon 1 of the LMNA gene c.29C>T(p.T10I) was detected. This case of GLPS may provide a diagnostic and therapeutic basis for potential patients. [ABSTRACT FROM AUTHOR]

The security of natural gas supply and demand has always been an important topic, and as a result, analyzing and predicting the supply and demand of natural gas has received considerable attention from researchers. Numerous studies have extensively researched the supply and demand of natural gas. The main purpose of this study is to explore the supply‐demand balance mechanism for natural gas security. A system dynamics model is constructed to assess the supply and demand of natural gas in Sichuan Province, China. A new system dynamics model based on domestic gas, production gas, ecological environment and natural gas supply is proposed. The study considers four scenarios: natural development, economic priority development, environmental priority development and coordinated development. The results show that the rapid economic development has led to an excessive environmental carrying capacity, a larger gap between natural gas supply and demand, a decline in the quality of life of residents, and even affected the energy security of Sichuan Province and China. The findings also show that people's overprotection of the environment can lead to slow economic development, which prevents it from achieving its desired goals. The coordinated development scenario in this paper not only ensures the production of natural gas and the quality of life of residents, but also is an optimal scheme with low energy consumption and pollution. According to the research conclusions, considering the overall situation of China's energy security and the situation in Sichuan Province, the author proposes reforms from the supply and demand sides of natural gas. [ABSTRACT FROM AUTHOR]

The industrial sector is China's major element of energy consumption and carbon emissions, and carbon emissions reduction in industrial parks has become an important foothold in carbon reduction work. Predicting the future evolution trend of carbon emissions in industrial parks under different policy orientations is of great significance for China to achieve the carbon emissions peaking and carbon neutrality goals. Based on the current status of electricity consumption and carbon emissions in industrial parks, this paper takes a light industrial park as the research object, analyzes the source of carbon emissions in this park, combines the characteristics of resource endowment and industrial structure, and considers the factors influencing society, load curve, energy supply and carbon sink, thus constructing a system dynamics model of carbon emission evolution for this park. Different influencing factors are selected to set multiple target scenarios, and the GDP, carbon emissions, carbon emissions reduction and near‐zero carbon evaluation coefficient of light industrial parks are used as characterization indicators for simulation analysis. The analysis results revealed that the comprehensive scenario set by increasing the maximum installed capacity of renewable energy units and raising the proportions of environmental and science and technology inputs while adjusting the industrial growth rate of the park performed best. In this scenario, the economic development of the park and the process of carbon emissions reduction are considered. [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]

To investigate the impact of solar energy on the carbon footprint, to find effective measures to reduce the carbon footprint and slow global warming as soon as possible, this paper takes 30 provinces in China as an example. First, the inter‐regional input–output model is used to calculate the carbon footprint of each province. Then, the panel quantile regression model is used to investigate the impact of solar energy generation on different quantiles of carbon footprint. The results show that from 2012 to 2020, China's carbon footprint is at a high level, which is not conducive to the achievement of the goal of peaking carbon dioxide emissions. The eastern region has the highest carbon footprint, followed by the western region, the central region has the lowest carbon footprint, and its carbon footprint proportion continues to decline. The increase of solar energy generation can significantly reduce the carbon footprint of high quantile location, but has no significant impact on the carbon footprint of the middle and low quantile locations. Except for the negative impact of afforestation area on carbon footprint, the others control variables are all positive. Therefore, to reduce the carbon footprint of China, it is necessary to upgrade solar technology, increase solar energy generation, reduce energy consumption per unit of GDP (Gross Domestic Product) and the share of coal consumption, strengthen forestry management and reduce reliance on private vehicles. [ABSTRACT FROM AUTHOR]