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The Ediacaran–Cambrian Phosphogenic Episode is the Earth's first true phosphogenic event and resulted in worldwide phosphate deposits, which occurred during the processes of the Neoproterozoic Oxygenation Event. The Ediacaran Doushantuo Formation (ca. 635–551 Ma) of Weng'an area in central Guizhou, South China, contains two economic phosphorite beds (the Lower and Upper Phosphorite Beds). This paper presents a detailed stratigraphic, sedimentological and mineralogical study of multiple outcrop and drill core sections of the Doushantuo Formation across the Weng'an area, and identified 11 lithofacies and 4 types of phosphatic grains. Significant differences in lithofacies and grain types between the upper and lower phosphate deposits are observed, indicating that the two sets of phosphate deposits are the products of two distinct phosphogenic processes. The Lower Phosphorite Bed mainly consists of banded and laminated phosphorites, contains micro-oncoids formed by microbially-mediated precipitation and peloids formed by in-situ chemically oscillating reactions, indicating a biochemical and chemical enrichment of phosphorus to sediments during the Early Ediacaran Period. The Upper Phosphorite Bed is mainly composed of carbonaceous, massive, and stromatolitic phosphorites, contains bioclasts (phosphatized spheroidal fossils), and intraclasts formed by hydrodynamic agitation, suggesting that the major accesses of phosphorus to sediments were the remineralization of organic P. Deposition of the two economic phosphorite beds was controlled by two sea-level cycles. Such differences have also been documented in contemporaneous phosphate-bearing successions in Brazil and Mangolia, indicating a significant shift in global phosphogenic mechanism during the early and middle Ediacaran, which may be due to the changes in redox conditions in seawater, associated with the Neoproterozoic Oxygenation Event. These regional active P-cycle processes could produce more free oxygen, which may have contributed to the upcoming Phanerozoic global oxidation. [ABSTRACT FROM AUTHOR]

Early Paleozoic magmatism in the West Kunlun Orogenic Belt (WKOB) preserves important information about the tectonic evolution of the Proto-Tethys Ocean. This paper reports whole-rock compositions, zircon and apatite U-Pb dating, and zircon Hf isotopes for the Qiaerlong Pluton (QEL) at the northwestern margin of WKOB, with the aim of elucidating the petrogenesis of the pluton and shedding insights into the subduction-collision process of this oceanic slab. The QEL is mainly composed of Ordovician quartz monzodiorite (479 ± 3 Ma), quartz monzonite (467–472 Ma), and syenogranite (463 ± 4 Ma), and is intruded by Middle Silurian peraluminous granite (429 ± 20 Ma) and diabase (421 ± 4 Ma). Zircon εHf(t) values reveal that quartz monzodiorites (+2.1 to +9.9) and quartz monzonites (+0.6 to +6.8) were derived from a mixed source of juvenile crust and older lower crust, and syenogranites (−5.6 to +4.5) and peraluminous granites (−2.9 to +2.0) were generated from a mixed source of lower crust and upper crust; diabases had zircon εHf(t) values ranging from −0.3 to +4.1, and contained 463 ± 5 Ma captured zircon and 1 048 ± 39 Ma inherited zircon, indicating they originated from enriched lithospheric mantle and were contaminated by crustal materials. The Ordovician granitoids are enriched in LILEs and light rare-earth elements, and depleted in HFSEs with negative Nb, Ta, P, and Ti anomalies, suggesting that they formed in a subduction environment. Middle Silurian peraluminous granites have the characteristics of leucogranites with high SiO2 contents (74.92 wt.%–75.88 wt.%) and distinctly negative Eu anomalies (δEu = 0.03–0.14), indicating that they belong to highly fractionated granite and were formed in a post-collision extension setting. Comparative analysis of these results with other Early Paleozoic magmas reveals that the Proto-Tethys ocean closed before the Middle Silurian and its southward subduction resulted in the formation of QEL. [ABSTRACT FROM AUTHOR]

Paleoproterozoic A-type granites are widely distributed in the southern margin of the North China Craton (SNCC), providing important information for understanding the Paleoproterozoic tectonic regimes in this area. This paper reports newly obtained whole-rock compositions and zircon U-Pb ages for the Tieluping syenogranite porphyry (TLP) and Huoshenmiao alkali granite porphyry (HSM) in the SNCC. Zircons from the TLP and HSM have U-Pb ages of 1 805 ± 12 and 1 792 ± 14 Ma, respectively. These ages are taken to date the emplacement of these intrusions. They had high total alkali contents (K2O + Na2O > 7.13 wt.%), with high 10 000 × Ga/Al ratios (3.06–3.41) and Zr + Y + Nb + Ce values (709 ppm–910 ppm) as well as high zircon saturation temperatures (864–970 °C), indicative of A-type granite affinities. High Y/Nb (1.75–3.32), Ce/Nb (7.72–9.72), and Yb/Ta (2.89–5.60) ratios suggested that TLP and HSM belonged to the A2-type granite. The negative whole rock εNd(t) values (−8.4 to −6.6) and negative zircon εHf(t) values (−15.9 to −6.3) confirmed that TLP and HSM were likely generated by the partial melting of an ancient continental crust. The εHf(t) (−7.4 to +4.0) values of inherited zircons in the TLP suggested that they were derived from the partial melting of Archean basement rocks. Considering the geochemical similarity of the 1.80 Ga A-type granitoids in the SNCC, we propose that the TLP and HSM were formed in a post-collisional regime that was likely associated with the break-off of the Paleoproterozoic subducted slab. Upwelling of the asthenosphere provided huge heat to generate the regional 1.80 Ga A-type granite in the SNCC. [ABSTRACT FROM AUTHOR]

The colloidal borescope, using colloidal particle motion, is used to monitor the flow velocities and directions of groundwater. It integrates advanced techniques such as microscopy, high-speed photography, and big data computing and enjoys high sensitivity at the micron level. However, In the same well, the groundwater flow velocity monitored by colloidal hole mirror is varies greatly from that obtained by conventional hydrogeological monitoring, such as pumping test. In order to solve this problem, the stability catcher and stratified packer are designed to control the interference of the vertical flow in drilling, and to monitor the flow velocity and direction of groundwater velocity at the target aquifer and target fracture. Five wells with different aquifers and different groundwater types were selected for monitoring in south-central China. The instantaneous velocity and direction are converted into east–west component and north–south component, the average velocity and direction is calculated according to the time of 10 min, and the particle trajectory diagram is established. Based on these results, it proposed a concept of cumulative flow velocity. Using curve-fitting equations, the limits of cumulative flow velocities as the monitoring time tends to infinity were then calculated as the actual flow velocities of the groundwater. The permeability coefficient of aquifer is calculated by using the fissure ratio of aquifer, hydraulic slope and flow velocity, and compared with the permeability coefficient obtained by pumping test. The results are as follows: (1) The variation coefficient of the instantaneous flow velocity measured at the same depth in the same well at different times is greater than that of the time average flow velocity and greater than that of the cumulative flow velocity. The variation coefficient of the actual velocity is the smallest, indicating that the risk of using the actual flow velocity is lower. (2) The variation coefficient of the flow rate monitored at different depths in the same well is mainly controlled by the properties of the aquifer. The more uniform water storage space in the aquifer, the smaller the variation coefficient. (3) The comparison between the permeability coefficient obtained by monitoring and the permeability coefficient obtained by pumping test shows that the flow of structural fissure water controlled by planar fissure is more surface flow, and the results are consistent. When the groundwater flow is controlled by pores and solution gaps, the flow channel is complicated, which is easy to produce turbulent flow, and the result consistency is poor. (4) According to different research accuracy requirements, different monitoring and calculation methods can be selected for different aquifers and groundwater types. Researches show that, the permeability coefficient calculated for the actual flow velocity in well DR01 is the same as that calculated for the pumping test. The aquifer characteristics reflected by the coefficient of variation of the actual flow velocity in the same aquifer are more realistic. The pumping test method obtains the comprehensive parameters of a certain aquifer, and this method can be used to monitor a certain fissure. In this paper, the new technology developed for monitoring, and the new algorithm established for data processing, can accurately obtain the flow velocity and direction of groundwater, using capsule hole mirror monitoring method. The key parameters of hydrogeology can be obtained by using one well, which can reduce the time and cost input and improve the work efficiency. [ABSTRACT FROM AUTHOR]

Organization's sustainability performance is influenced by its suppliers' sustainability performance. This relationship makes sustainable supplier development a strategic competitive option for a buyer or focal organization. When considering sustainable supplier development practices (SSDPs) adoption, organizations have to balance and consider their limited financial resources and operational constraints. It becomes necessary to both select the best SSDPs set and investment allocation among the selected SSDP set such that the organization can maximize overall sustainability performance level. In this paper, an integrated formal modeling methodology using DEMATEL, the NK model, and multi-objective linear programming model is used support this objective. The proposed methodology is evaluated in a practical sustainable supply chain field study of an equipment manufacturing company in China. Through case study, we found that the interdependency among SSDPs must be considered in SSDPs selection and investment allocation problem. Theoretical, managerial and methodology implications, conclusions, and directions for future research are also presented. [ABSTRACT FROM AUTHOR]

The information released by the public on various social media platforms can assist experts in decision-making, thus improving the reliability of the decision-making results and increasing their likelihood of gaining public support. However, the determination of how to fully integrate public opinions with expert opinions and in what aspects to realize the integration is a research topic worthy of attention. Based on this, this paper proposes a multi-subject weighted information fusion method that fully considers public opinion. First, the Bayesian subject model is used to obtain the attribute set of public opinion, and the sentiment analysis technique is used to calculate the reference attribute weights. Second, public opinion is utilized to improve the traditional best–worst method to determine the subjective attribute weights of experts at a faster rate. Third, expert weights are determined using "knowledge" and attribute weights are defined at the aggregate level. Fourth, the cluster weights are determined according to the proximity of the clustered opinions to the public opinions, and the clustered opinions are then summarized to get the overall decision-making information, thus scientifically realizing the synergistic decision-making between the public and experts. Finally, the case of a rainstorm emergency in Henan Province, China, is used to analyze and determine the best plan that matches with the actual situation, and the results are then compared with the findings of existing research to illustrate the feasibility and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Empirical and probabilistic risk analysis methods can relatively accurately predict the seismic vulnerability of reinforced concrete (RC) structures. Using various intensity measures to estimate and forecast the seismic hazard of RC structures can contribute to the development of typical structural seismic resilience and vulnerability models. However, traditional empirical and analytical vulnerability studies rely more on field observation data and seismic risk algorithms and less on numerical simulation analysis for validation and optimization, resulting in limitations and fuzziness in the accuracy of the developed structural risk models. To explore the damage modes of RC frame structures under different intensities, this paper innovatively combines numerical model algorithms with empirical vulnerability methods to conduct empirical vulnerability and numerical simulation analyses on RC structures. Using probability statistics and nonlinear regression analysis methods, a prediction model for estimating the fragility of RC structures was proposed, and 858 RC structure damage samples from a typical city (Dujiangyan) during the Wenchuan earthquake in China on May 12, 2008, were used for model verification and comparative analysis. Using seismic response analysis theory, 901,530 acceleration records of the Wenchuan earthquake detected by eight actual seismic stations were selected, and nonlinear dynamic time history analysis was conducted. A four-story RC structural model was established using finite element software, and numerical simulation analysis was conducted on the model using 117,863 real earthquake acceleration data points obtained from actual monitoring stations during the Wenchuan earthquake. The acceleration time history curves and incremental dynamic analysis curves of the RC structure under different intensity measures were generated. By combining the moire algorithm and numerical simulation technology, damage stress clouds of steel bars and concrete under different intensity measures were generated, and the accuracy of the developed empirical vulnerability model was verified via numerical simulation results. [ABSTRACT FROM AUTHOR]

It is of great significance to accurately grasp ground-level ozone concentration on a wide scale in order to cope with the increasingly serious ground-level ozone pollution problem. Currently, satellite technology can be used to monitor ground-level ozone concentration on a wide scale, but there is the problem of insufficient spatial resolution. The use of ground monitoring stations to detect ground-level ozone concentration can obtain more accurate ozone concentration around the station, but there are problems of limited number of stations and sparse distribution. Therefore, it is still a challenge to accurately grasp the ground-level ozone concentration at a large scale and high spatial resolution. To address this issue, this paper proposes a ground-level ozone concentration inversion algorithm based on deep learning methods, incorporating data from remote sensing satellites, ground monitoring stations, meteorological conditions, geography, and land use. Taking Yunnan Province in China as the experimental region and utilizing five-fold cross-validation, the model's Mean Square Error (MSE) reached 340.45 and Root Mean Square Error (RMSE) reached 18.45. Compared to machine learning models, the error decreased by 14.53%, outperforming Random Forest models, Convolution Neural Networks, and Vision Transformers. This study offers a referential approach for accurately capturing ground-level ozone concentrations at a large scale with high spatial resolution. [ABSTRACT FROM AUTHOR]

Firms are embedded in complex networks, where diverse ideas combine and generate new ideas. Shareholders of firms are often seen as critical external resources that have significant influence on firm innovation. The current literature tends to focus on the relationship between firms and their shareholders, while paying less attention to the connections between firms with the same shareholders. This article identifies two types of network spillover effects, intra-city network effect and inter-city network effect, by visualizing the co-ownership networks in China's electric vehicle (EV) industry. We find that firms with the same shareholders, which are defined as co-owned EV firms, are more innovative than non-co-owned ones. Furthermore, there are two dominant types of firm co-ownership ties formed by corporate and financial institution shareholders. While corporate shareholders help exploiting local tacit knowledge, financial institutions are more active in bridging inter-city connections. The conclusion is confirmed at both firm and city levels. This paper theorizes the firm co-ownership network as a new form of institutional proximity and tested the result empirically. For policy consideration, we have emphasized the importance of building formal or informal inter-firm network, and the government should further enhance the knowledge flow channel by institutional construction. [ABSTRACT FROM AUTHOR]

It is common to observe the epidemic risk perception (ERP) and a decline in subjective well-being (SWB) in the context of public health events, such as Corona Virus Disease 2019 (COVID-19). However, there have been few studies exploring the impact of individuals' ERP within living space on their SWB, especially from a geographical and daily activity perspective after the resumption of work and other activities following a wave of the pandemic. In this paper, we conducted a study with 789 participants in urban China, measuring their ERP within living space and examining its influence on their SWB using path analysis. The results indicated that individuals' ERP within their living space had a significant negative effect on their SWB. The density of certain types of facilities within their living space, such as bus stops, subway stations, restaurants, fast food shops, convenience shops, hospitals, and public toilets, had a significantly negative impact on their SWB, mediated by their ERP within living space. Additionally, participation in out-of-home work and other activities not only increased individuals' ERP within living space, but also strengthened its negative effect on their SWB. [ABSTRACT FROM AUTHOR]

This paper aims to interpret the connotation of high-quality development of tourism economy (HQTE) from the perspective of the new development concepts of innovation, coordination, green, openness and sharing, and then to evaluate the spatial differentiation of China's HQTE based on provincial panel data from 2009 to 2018. Specifically, we employ the spatial convergence model to explore the absolute and conditional β convergence trends of HQTE in the whole country and the eastern, central and western regions of China. Our empirical results reveal that: 1) within the decade, from 2009 to 2018, regions of China with the highest HQTE index is its eastern region followed by the central region and then the western region, but the fastest growing one is the western region of China followed by the central region and then the eastern region. 2) Whether or not the spatial effect is included, there are absolute and conditional β convergence in HQTE in the whole country and aforementioned three regions. 3) The degree of government attention as well as the level of economic development and location accessibility are the positive driving factors for the convergence of HQTE in the whole country and the three regions. The degree of marketization and human capital have not passed the significance test either in the whole country or in the three regions. The above conclusions could deepen the understanding of the regional imbalance and spatial convergence characteristics of HQTE, clarify the primary development objects, and accomplish the goal of China's HQTE. [ABSTRACT FROM AUTHOR]

Several recent efforts have been devoted to enhancing pretrained language models (PLMs) by utilizing extra heterogeneous knowledge in knowledge graphs (KGs) and have achieved consistent improvements on various knowledge-driven natural language processing (NLP) tasks. However, most of these knowledge-enhanced PLMs, regardless of the domain-specific knowledge required by PLMs, lack a Chinese corpus to support large-scale PLMs, especially in domain-specific PLMs. Herein, we harvest and process public geological reports (mainly various reports from the National Geological Archives of China), abstracts of papers from 34 geological journals, and abstracts of geological dissertations from 161 universities or scientific institutions. This paper introduces a large-scale Chinese geological corpus (GeoCorpus) containing approximately 232 MB of training data with a total of 243 million characters. Based on GeoCorpus, we also introduce a Chinese pretrained language representation model in the geological domain (CnGeoPLM). The model utilizes the generic BERT to complete parameter initialization and combines the GeoCorpus for the second stage of training. We evaluate and test CnGeoPLM and Bidirectional Encoder Representations from Transformers (BERT) on three tasks of geological named entity recognition (GeoNER), geological entity relationship extraction (GeoRE), and geological entity clustering (GeoClu). In the results of both the GeoNER and GeoRE experiments, CnGeoPLM has different degrees of improvement in evaluation metrics compared to BERT. In the GeoClu experiment, CnGeoPLM is significantly more effective and discriminative in entity clustering effect compared to BERT. These results show that CnGeoPLM has a stronger representation ability in geological NLP tasks than BERT. [ABSTRACT FROM AUTHOR]

TBM method construction is an important accompanying construction form vigorously developed in China, and its anomaly detection is an important link to provide a basis for system operation and maintenance decision-making. The abnormal operation state of TBM caused by different surrounding rock geology, jamming or rock burst will directly affect the tunneling speed and ability, and then affect the system safety and construction progress. In this paper, a TBM construction anomaly detection method based on historical tunneling speed and other construction monitoring data is proposed. Firstly, the preprocessing steps based on outlier removal and correlation analysis are used to remove the noise in the original data and select the best features. Secondly, the variational mode decomposition is used to decompose the data into multiple modal components to extract the periodic and aperiodic features of TBM tunneling. Furthermore, an improved VMD-XGBoost-BILSTM combination model is constructed, and the characteristics of combination weighting, attention mechanism and improved whale optimization algorithm are used to realize the normal prediction of accurate and stable tunneling speed. Finally, by comparing with the actual measured values, the set rules are used to judge the anomalies. The experiments are carried out on the actual mining data of YE long-distance water conveyance tunnel in Xinjiang. The results show that the method proposed in this paper improves the RMSE by more than 20% compared with the single BILSTM or XGBoost model. The attention mechanism and IWOA algorithm bring 5.53% and 10.73% results improvement respectively, which can achieve the effect of early warning of different geological information changes. [ABSTRACT FROM AUTHOR]

In this paper, for the engineering problem of tunnel deformation damage caused by a tunnel–landslide orthogonal system landslide in northwest China, based on similar theory, a variety of materials and their ratios were explored to make similar models according to the physical and mechanical parameters of the site engineering rock, indoor physical model tests were constructed, and monitoring techniques, such as speckle displacement strain measurement, strain acquisition, and pressure sensors, were used to test the macroscopic deformation characteristics; through the detailed analysis and law summary of the test macroscopic deformation characteristics, displacement, anchor cable axial force, and strain data, it was finally found that under the orthogonal system of tunnel and sliding surface, the damage form of tunnel lining is mainly compression damage and shear damage, and the cracks are mainly tension cracks, and the effect of tunnel primary lining on the surrounding rock support is extremely limited under the action of huge sliding force; combined with the analysis of the model deformation characteristics and the axial force curve of the anchor cable during loading, it was found that the axial force change curve is consistent with the NPR Newton force curve can be used to evaluate slope stability and predict the occurrence of landslide disasters. Highlights: This paper focuses on the tunnel and surrounding rock damage evolution characteristics under tunnel–landslide orthogonal and tunnel crossing sliding surface conditions. The evolution of displacement field, NPR anchor cable axial force, and strain field were revealed using indoor large similar physical model test. The mechanism of tunnel–landslide interaction within the slope and the deformation and damage characteristics of the tunnel surrounding rock were analyzed to reveal the slope deformation law under different loads. The stress change law of constant-resistance large deformation anchor cable (NPR anchor cable) is explored, and a landslide warning mechanism based on constant-resistance large deformation anchor cable is established. [ABSTRACT FROM AUTHOR]

China is one of the pioneers in developing innovative models for credit business through a partnership between FinTech firms and traditional financial institutions such as banks. There are two main business models of FinTech-bank partnership, namely the loan facilitation model and the co-lending model. While this partnership brings many benefits, it has significant risks, including outsourcing risks, monopolistic practices, data protection, algorithmic bias, and financial systemic risk. This paper critically examines the Chinese regulatory responses to those risks with a focus on the outsourcing issue. Drawing upon the experiences of some overseas jurisdictions, including the US, the UK, the Netherlands, Luxembourg and Switzerland, this paper makes relevant suggestions for improving the Chinese regulation. China is advised to adopt a staged and differentiated approach to regulate FinTech-bank partnership. The first step is to establish a regulatory sandbox for FinTech firms to test their innovative activities, and, depending on the specific circumstances, an umbrella entity mechanism could also be introduced. Further, a sophisticated licensing regime can be established to set out differentiated rules for FinTech firms according to the nature and extent of the FinTech-Bank partnership, thus addressing the problem of regulatory arbitrage. [ABSTRACT FROM AUTHOR]

Over the past two decades, China has undergone a rapid urbanization process. As such, determining the current status of the quality of life in Chinese cities and how to improve it has become a common concern for all sectors of Chinese society. This paper employs a combination of city-level macro data and individual-level micro data to construct a quality of life evaluation system that contains 9 dimensions and 35 secondary indicators. The quality of life of 194 cities in China has been further assessed using the Pena distance method (DP2). The study found that there are significant regional differences in the quality of life in Chinese cities, with the quality of life in China's large cities being significantly higher than that in small and medium-sized cities. The analysis of Ivanovic discrimination coefficient shows that social security, culture and education and infrastructure are the most important factors affecting the quality of life in Chinese cities. Spatial mismatch analysis reveals that the quality of life and subjective well-being differ significantly in Chinese cities. In addition, this paper provides policy recommendations to improve the quality of urban life in China and to reduce the imbalance in the quality of life between regions. [ABSTRACT FROM AUTHOR]

Studying the impact of urbanization on agricultural development in shrinking areas is important for maintaining food security and promoted agricultural development in China. Based on the measurement results of the shrinking cities in the three provinces of Northeast China, this paper selects 15 shrinking cities as the research object, and constructs a multi-dimensional index system to explore the impact of the urbanization level of the shrinking areas on the agricultural development in the region since 2007–2019, analyzes the influencing factors and their differences by using the geographically-weighted regression model and Geodetector, and proposes a targeted regulation strategy. The results show that: 1) overall, there is a negative correlation between the urbanization level and the agricultural development level in the contracted areas of the three northeastern provinces. The urbanization level in these areas has a certain negative impact on the overall level of agricultural development; 2) regarding the time dimension, the impact of urbanization level on the agricultural development level in the contracted areas of the three northeastern provinces gradually increases over time; 3) regarding the spatial pattern, the overall impact of shrinking urbanization levels in the three provinces of Northeast China on the agricultural development shows a significant distribution pattern of high in the east and low in the west; 4) the total population and natural population growth rate at the end of the year were the main factors influencing a certain level of urbanization on agricultural development in the shrinking cities while population density and the urban fixed asset investment rate were the secondary factors; and 5) the main reasons why the level of agricultural development in different cities was affected by the level of urbanization were different. However, they can be categorized into areas of population loss and spatial construction, which can be further divided into area of population loss in the northeast, areas of negative population growth in the west, and areas of urban spatial change in the south. According to the causes of the impact, this paper adopted targeted regulation strategies and formulated relevant policies and solutions that cater to local conditions. [ABSTRACT FROM AUTHOR]

Cold-chain logistics presents significant challenges to sustainable development in terms of economics, society, and the environment. To address this issue, this paper focuses on solving a real-world problem—the multipath location-routing problem-based cold-chain logistics (MPLRPCCL), which considers soft time windows and heterogeneous fleets. The mathematical model aims to optimize the total logistics costs, including fuel consumption, carbon emissions, cargo deterioration, penalties, operating depots, and renting fleets. To effectively solve this problem, the paper proposes three versions of a memetic algorithm (MA) that incorporate control modules for monitoring the MA's performance and improving its global optimization performance. Computational evaluations were conducted, and the results show that the proposed algorithms are effective and outperform the classic MA framework. Furthermore, the proposed model and algorithms were applied to real-world cases in Hangzhou city, China, demonstrating their practical applicability. Overall, this paper offers a promising approach to tackling the complex challenges posed by cold-chain logistics and contributes to the sustainable development of this important field. [ABSTRACT FROM AUTHOR]

The application of industrial robots is considered a significant factor affecting environmental pollution. Selecting industrial wastewater discharge, industrial SO2 emissions and industrial soot emissions as the evaluation indicators of environmental pollution, this paper uses the panel data model and mediation effect model to empirically examine the impact of industrial robots on environmental pollution and its mechanisms. The conclusions are as follows: (1) Industrial robots can significantly reduce environmental pollution. (2) Industrial robots can reduce environmental pollution by improving the level of green technology innovation and optimizing the structure of employment skills. (3) With the increase in emissions of industrial wastewater, industrial SO2, and industrial dust, the impacts generated by industrial robots are exhibiting trends of a "W" shape, gradual intensification, and progressive weakening. (4) Regarding regional heterogeneity, industrial robots in the eastern region have the greatest negative impact on environmental pollution, followed by the central region, and the western region has the least negative impact on environmental pollution. Regarding time heterogeneity, the emission reduction effect of industrial robots after 2013 is greater than that before 2013. Based on the above conclusions, this paper suggests that the Chinese government and enterprises should increase investment in the robot industry. Using industrial robots to drive innovation in green technology and optimize employment skill structures, reducing environmental pollution. [ABSTRACT FROM AUTHOR]

'Fingerprint' identification is the key to turquoise provenance studies, but previous studies have met with limited success in China. Turquoises in China mainly occur in altered sedimentary rocks and are formed by weathering, leaching and sedimentation. This paper evaluates the potential for sedimentary environment sensitive elements to be used to distinguish between turquoise deposits in China. In this paper, the ratios of V/Mo, Ce/Ce*, Ni/Co, Sr/Ba, Tl/Ga, Li/Ba and V/Cr were calculated for turquoise of different origins. Our results show that these parameters when used alongside Ga concentration permit effective discrimination between turquoise sources in China. This approach brings to light a new means of analyzing trace element databases and an untapped wealth of information that can be used for future turquoise provenance studies. [ABSTRACT FROM AUTHOR]

Industrial ecology (IE) is the process of constructing industrial-ecological systems (IES) with the realization of the mutual benefits for industrial system (IS) and ecological system (ES). Therefore, the IE level depends on the IES development and the relationship between IS and ES. This paper calculated the development index of ES and IS to account for IES development and adopted the grey Lotka–Volterra to analyze the relationship between IS and ES. Choosing the π-shaped curve area in the Yellow River basin of China as the study area, this paper analyzed its IE level and influence factors from 2005 to 2019. Findings include: (1) The development level of IES in the Area presented significant spatial differentiation and could be classified into three levels. (2) IS and ES remained in the stage of isolated development or mutual restriction. (3) IE was found to be positively correlated with scientific innovation, economic development, openness degree, pollution control, and industrial structure while negatively correlated with urbanization, resource consumption, and government influence. [ABSTRACT FROM AUTHOR]

This paper explores the mispricing relative to the capital asset pricing model through an equilibrium model. We find that both the strong risk preference dependent on good market states and strong risk aversion dependent on bad market states can produce high mispricing. Choosing the China stock market, the largest emerging market dominated by individual investors and known for its volatile nature in a short history as our sample, the empirical results also support our theoretical findings. Overall, our paper sheds light on the mispricing caused by the investor's risk preference reference-dependent on market states. [ABSTRACT FROM AUTHOR]

Green innovation plays a crucial role in transforming economic models and achieving sustainable development in enterprises. As an important embodiment of artificial intelligence technology, how industrial robots can effectively promote the green transformation of enterprises has become an important issue. This paper examines the impact and mechanisms of industrial robot adoption on corporate green innovation, as well as its heterogeneous effects. Using data from Chinese listed companies from 2007 to 2019, we find that industrial robot adoption has a significant positive impact on corporate green innovation, enhancing both its quantity and quality. Furthermore, our mechanism study reveals that industrial robot adoption can promote corporate green innovation by improving productivity and environmental management capabilities. Additionally, we investigate the moderating effects of various factors and conclude that the positive impact of industrial robot adoption on green innovation is more pronounced among the state-owned enterprises, enterprises with the intense market competition, as well as enterprises located in regions with higher carbon emissions intensity. This paper contributes to enrich the research on industrial robots and corporate green innovation, and provides a reference to improve environmental management and achieve a low-carbon economy in emerging markets. [ABSTRACT FROM AUTHOR]

With recent fires in ancient buildings such as Notre-Dame de Paris in France, Wanan Ancient Bridge in China, and the Cavallerizza Reale in Italy, it can be seen that aging wood buildings are more prone to fire and not easy to control once flame spreads. In this paper, the ignition of typical woods (Cypress and Fir in China) in ancient buildings was explored experimentally and theoretically by cone calorimeter under external heat flux (25, 35, and 50 kW m−2), and the measured ignition times were modeled by integration to create an ignition model. The results show that the fitted ignition temperature (Tig) equation can predict the ignition temperature of wood reasonably well. The theoretical ignition time curve calculated by the integral model agrees with the experimental value, which can be used for prediction of wood radiation ignition. This paper can assess the fire risk of wooden ancient buildings and provide important help for fire prevention and control in ancient buildings. [ABSTRACT FROM AUTHOR]

In the analysis of agricultural product price time series, the detection of abnormal fluctuations is the primary task. Accurately judging the abnormal fluctuations of agricultural product prices can help farmers avoid potential economic losses in a timely manner and improve the circulation efficiency of agricultural products. This paper introduces a convolutional neural network (CNN) classification model based on time series images (TSI), and identifies abnormal fluctuations in agricultural product prices using improved standard deviation–slope judgment. First, a standard deviation–slope (SDS) time series abnormal fluctuation criterion is proposed. Second, the Markov Transfer Field (MTF) method is used to convert the sparse one-dimensional time series of agricultural product prices into a two-dimensional dense image. Third, the CNN model is used to automatically extract features from time series images containing abnormal fluctuations, and they are divided into two categories: "normal" and "abnormal"; Finally, the performance of the proposed model was evaluated using China's corn and wheat price dataset. Comparing with other abnormal fluctuation judgment methods, the accuracy of the proposed algorithm is about 20% higher on average. This confirms the applicability of the standard deviation–slope time series Image-Resnet-34 (SDS-TSI-Resnet34) model in practical scenarios. At the end of the paper, some feasible suggestions for the efficient development of agricultural economy are proposed based on the abnormal fluctuation judgment method. [ABSTRACT FROM AUTHOR]

Agro-pastoral ecotone of northern China is the prominent area for agricultural production, but it is also the most typical ecological fragile area with frequent drought disasters. Taking Yulin City at Shaanxi Province in China as the case area, the paper aims to investigate the spatio-temporal changes of agricultural vulnerability to drought in China's agro-pastoral ecotone in the period 2000 to 2020. The results show that: 1) the agricultural vulnerability to drought in Yulin City has shifted from high vulnerability in the period 2000–2010 to low vulnerability in the period 2011–2020. 2) There exist obvious spatio-temporal differences of the agricultural vulnerability to drought in Yulin City during the research period. 3) Four sensitive events and 14 resilient events were identified in the research and the crops of Yulin had become more resilient to drought. Finally, the paper put forward with policy implications to make adaptive strategies of agriculture to climate change in China's agro-pastoral ecotone in the future, e.g., carrying out agricultural zoning based on agricultural production conditions, intensifying the construction of disaster prevention and relief system, and integrating with modern agricultural technology to develop new type agriculture. [ABSTRACT FROM AUTHOR]

The reorganization of the global production network and the increased mobility of urban-rural elements have accelerated the differentiation of rural spaces, resulting in a trend towards specialization in rural areas. This paper focuses on the concept of specialization, and takes a renowned bonsai specialized village in Guangzhou City, China as a typical case to explore its transformation and development process, action logic and coupling mechanism with the social governance. The results show that: 1) the development of rural specialization in Ruiling Village is shaped by several key actors, such as local governments, grassroots organizations, villagers, social organizations, policies, markets and infrastructure. The transfer of these key actors and the reconstruction of actor-networks in different stages have an important influence on the transformation and realization of rural development goals. 2) Through subjects-driven, organization management and resource connection, social governance supports the specialization of rural industrial organization, operation, technology and mode. The governance structure shifts from decentralization to networking, refinement and integration. A coupling community of social governance and specialization is created by the social governance system of 'local government-grassroots organizations-economic cooperatives-villagers', which links industries, industrial chains and cooperatives. 3) Social governance integrates into the value chain extension process of rural specialized development with a central, multi-level organizational structure. It promotes the construction of the whole value chain through organizational planning, resource integration and image shaping, thus realizing the value, branding and organization of the industry, as well as the integration of rural sustainable development and governance mechanism. Social governance has a profound impact on the development of rural specialization in terms of subject, structure and mode, and participates in the construction of the whole value chain of rural areas. This paper provides a new perspective for understanding the coupling effect of social governance in the rural development transformation, and promotes the rural sustainable development and governance. [ABSTRACT FROM AUTHOR]

The establishment of the China-ASEAN Free Trade Area has prompted closer cooperation in aquatic products trade between China and Vietnam. Studying the aquatic trade situation and export trade growth dynamics of China and Vietnam can help clarify the aquatic trade relationship between China and Vietnam and promote the sustainable development of bilateral aquatic trade cooperation. This paper analyzes the trade growth dynamics of aquatic products exported from China and Vietnam from 2002 to 2020 using the ternary marginal method. The trade growth pattern of aquatic products exported from China to Vietnam is "both quantity and price growth," and the trade growth pattern of aquatic products exported from Vietnam to China is "quantity growth mainly, extensive growth supplemented." The two countries have apparent differences in the growth dynamics of aquatic products export trade. Moreover, there is a higher complementarity when exporting Vietnam's aquatic products to China than China's aquatic products to Vietnam. Based on these, analyze the factors affecting the growth dynamics of Vietnam's aquatic products export to China: Vietnam's economic development level negatively affects the price index and quantity index of Vietnam's aquatic products exported to China, and Vietnam's aquatic product output affects the price index. China's trade freedom positively affects the price index and negatively affects the quantity index. Finally, this paper put forward suggestions to promote the sustainable development of bilateral aquatic products trade between China and Vietnam to facilitate the formulation of relevant policies between the two countries. [ABSTRACT FROM AUTHOR]

With the emergence of digital technologies, we have witnessed a rapid growth of the sharing economy in recent years. In fashion industry, sharing economy concept is also widely applied. Instances can be found all over the world, like Rent the Runway, Golden Tote, Stitch Fix, and Le Tote in the US, Air Closet in Japan, Y Closet, Ms Paris, and Dora's Dream in China, etc. In this paper, motivated by the industrial practices of fashion sharing platforms, we first conduct a literature review on business operations of sharing platforms, including the sharing platform operations, digital and information technologies employed in sharing economy, business models, and sustainability and circularity in business operations. Afterwards, we analyze the challenges faced by fashion sharing platforms by exploring the two leading fashion sharing platforms in the US and in China, respectively. At last, we propose future research directions on fashion sharing platform operations and conclude the paper. [ABSTRACT FROM AUTHOR]

Accurately predicting the performance in various sports is crucial in comprehending training characteristics and enhancing physical education and training processes. The increasing significance of sports in China has enhanced the interest for developing prediction models to assess athletes' sports performance, accurately. These models will greatly contribute to improving sports performance and implementing scientific training methods. This paper proposes a prediction model for athletes' sports performance using Neural Networks as the underlying framework. This research aims to enhance sports performance and scientific training by developing a reliable and effective prediction model. First, the proposed model utilizes neural network algorithms, including error backpropagation and genetic algorithms, to train and optimize the prediction model. Second, it analyzes temporal patterns, extracts statistical features, and adapts to new data by ensuring reliability and effectiveness of the proposed model. Third, this paper conducts an error analysis by comparing the prediction errors between our proposed method and traditional models to evaluate the accuracy of the prediction model. In addition, this paper conducts an error analysis by comparing the prediction errors between our proposed method and traditional models. Finally, the results demonstrate that our proposed method achieves a maximum error of 36.12%, with the highest error rate in the BP network prediction being 6.76%. Furthermore, we compared our predicted results with multiple linear regression and other existing prediction methods, and our proposed method demonstrated superior accuracy with an overall prediction accuracy of 97.6%. Our suggested solution surpasses previous approaches with much higher accuracy, reduced latency, improved recall, and increased scalability. [ABSTRACT FROM AUTHOR]

English language translation teaching plays a crucial role in today's globalized world, particularly in countries like China, which has seen an increased emphasis on English language proficiency. However, effective teaching and assessment of students' translation abilities remain significant challenges for educators. To address the challenges of English language translation and teaching, this paper proposes a novel approach that integrates Internet of Things (IoT), Particle Swarm Optimization (PSO), and Neural Network algorithms to assist teachers in evaluating and assessing students' English translation abilities by enabling them to better fulfill their teaching responsibilities. This paper first describes the computational mechanism of Neural Network algorithm using PSO, which includes the particle coding approach. An application model is designed to assess students' capacity for learning using English translational instruction. The PSO algorithm gathers information on their learning progress, and fully utilize the analyzed results to develop learning strategies and create teaching materials for various learning types, which is helpful for the quick advancement of English translation teaching. Secondly, this paper develops a translational application model for English language as a practical framework. The proposed method utilizes the upgraded PSO-enabled Neural Network to process English language translation and teaching data by achieving network training in a global optimal state of PSO by reducing training errors. Thirdly, this paper evaluates the effectiveness of the model by comparing the average errors of the training and test samples with different numbers of particles such as 5, 10, and 20. Finally, the results demonstrate high accuracy in measuring students' translation abilities. Furthermore, the study collects and examines three data sets, specifically English-Foreign Language Translation Corpus (EFLT), English Language Learners' Corpus (ELLC), and English-Multilingual Parallel Corpus (EMPC), with a detection accuracy of 0.84, 0.97, and 0.65, respectively. [ABSTRACT FROM AUTHOR]

In order to quantitatively calculate the critical depth and critical load of mines affected by rock burst, and to achieve effective prevention and control of rock burst in coal mines, this paper proposes a mechanical model for predicting the occurrence of rock burst in coal mine roadways based on catastrophe theory. Additionally, a theoretical calculation formula for initiating rock burst is derived. The first step was to establish a mechanical analysis model, which directly correlated with the in-situ stress, physical and mechanical characteristics of the coal-rock mass, and engineering structural parameters. Following this, a mechanical instability criterion was derived for the key load-bearing circle within the surrounding rock of the roadway. In the final step, the critical depth and load for rock burst initiation were verified for 25 distinct coal mines in China that were prone to rock burst hazards. The research results demonstrate that the discrepancy between the theoretically calculated critical depth and the actual measured statistical values was less than 35%. In addition, the difference between the theoretically determined critical depth and the value calculated by Pan Yishan was less than 32%. Notably, the ratio of the theoretically calculated critical load to the uniaxial compressive strength of the coal-rock mass ranged from 0.38 to 1.93. This aligns with empirical data on rock burst occurrences, as set out in the engineering classification standards for rock masses. These research outcomes substantiated the practical utility of the proposed theory, thereby laying a robust theoretical groundwork for the quantitative control of rock burst. [ABSTRACT FROM AUTHOR]

The track structure has an effect on the dynamic characteristics of the bridge structure, which makes the seismic response of the bridge structure complicated. In this paper, an assessment method is proposed to evaluate the seismic risk of bridge structure, including over-limit risk and over-limit scale. Based on a newly proposed simplified model with high accuracy and high computational efficiency, a total of 3000 calculation conditions are analyzed and the sample stability of response is validated to ensure the reliability of the seismic risk analysis. The seismic risks in the longitudinal direction of the track-bridge model are compared with that of the trackless model, and the influence of the constraint effect of China Railway Track System II ballastless track structure on the seismic risk of the structure is obtained. The influence of the number of spans and PGA on track constraints is also revealed. The analysis results, based on a large number of samples, show that although track constraints can reduce the seismic risk of some phenomenon, such as girders' collision, the expected enhancement of longitudinal seismic safety of the system cannot be guaranteed in general, especially when the number of spans is large. However, it is noted that the track constraint can effectively control the over-limit scale of the system, which can reduce the expected repair cost after an earthquake. Therefore, it can be considered that the positive effect of the track constraints is more significant in economy than in structural safety when the bridge is subjected to a longitudinal earthquake excitation. [ABSTRACT FROM AUTHOR]

Existing aquifer water abundance evaluation methods employ fixed and constant index weights and overlook variations within major influencing factors as well as interactions among multiple factors. We propose a water abundance index method based on a variable weight model that considers various water abundance influencing factors and their respective weights, and quantitatively determines the weights of the same factor across different state values. This paper establishes a comprehensive system of four categories and 16 subcategories of main influencing factors that describe the distribution pattern of water abundance, considering lithological characters, hydraulic characteristics, structural factors, and geophysical parameters that influence aquifer water abundance. The variable weight model is used along with the K-means clustering method in dynamic clustering to determine the variable weight interval thresholds for each index of the main influencing factor. Additionally, we investigated the construction of the state variable weight vector, determination of weight adjustment parameters, quantitative assessment of the interaction relationship, and relative importance of each main influencing factor in relation to aquifer water abundance. Finally, an evaluation method and mathematical model for the water abundance index based on the variable weight model are developed. This study provides a detailed description of the specific implementation steps of the water abundance index method based on the variable weight model, using the direct water-filled J2z–#2 coal seam roof fissured aquifer in the Xiaojihan coal mine as a case study. The evaluation results were then verified using drainage data from the working face. The findings indicate that a comparison with the traditional constant weight evaluation results demonstrates that the variable weight model better reflects the characteristics of aquifer heterogeneity and achieves higher prediction accuracy. [ABSTRACT FROM AUTHOR]

The newly built back-streaming white neutron beam line (Back-n) at China spallation Neutron Source (CSNS) makes a breakthrough for China's domestic nuclear data measurement, which is pushing nuclear data measurement in China towards higher precision and wider energy range. The neutron flux of the facility was measured at the first beginning since it is an extremely important characterization for the experiment proposal and data analysis. The neutron fluxes under big collimators in end station 1 (ES#1) and end station 2 (ES#2) had been characterized by a fission chamber. In this paper, the first measurement of the neutron flux of Back-n ES#1 with small collimators is reported. The neutron flux from 0.5 eV to 300 MeV was measured by three detectors: a silicon monitor based on a 6LiF sample for the energy range below 200 keV, a fast multi-layer fission ionization chamber for the range from 10 keV to 300 MeV, and a proton recoil telescope for the high energy region from 10 to 70 MeV. The flux and its uncertainty with 50 bins per decade were finally evaluated by combining the data of the three detectors. The integrated flux in the full energy range at CSNS beam power of 100 kW is 1.642 × 106 n/cm2/s, which is consistent with the FLUKA simulation within a difference of about 4%. [ABSTRACT FROM AUTHOR]

Metal mineral resources are important raw materials in industrial production, and metal as an important object in the futures market, its discovery function is an important sign to measure the level of market development. The price of metal futures market has the characteristics of high-frequency data, and the mechanism of price discovery in different frequencies needs to be realized by time series decomposition method. In this paper, the complementary ensemble empirical mode decomposition with adaptive noise vector autoregressive model is constructed to re-examine the price discovery of nonferrous metal futures from the aspects of multilevel, multi-subject, and different volumes. Four typical nonferrous metals are selected for empirical research in China. The results show that price discovery exists in China's nonferrous metal futures market. Meanwhile, there are significant differences in the functional efficiency of typical metal prices under different time scales. The volume of contracts will greatly affect the efficiency of price discovery. Finally, we also find that futures prices affect spot prices, but spot prices do not affect futures prices. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to discuss the feasibility of utilizing the non-explosive source green seismic exploration technology to detect mineral resources in the deep of complex mountainous areas of western and southern China as well as to provide a feasible detection scheme. Based on seismic illumination analysis and prestack depth-domain migration experiments, a viable active-source seismic detection system was designed for the Zhuxi mining area of Jingdezhen. Geophysical models were established according to the combined drilling profile of L42 and the corresponding petrophysical measurements of rocks based on geological findings, drilling results, and site investigations. Since the single-component p-wave seismometers would be primarily utilized for the subsequent seismic data acquisition, the viscous-acoustic wave equation was selected to simulate the propagation of the seismic wave. Meanwhile, the acoustic-elastic boundary approach (AEA) was used to solve the irregular free-surface problem caused by the rugged Earth's surface. Seismic source-receivers bidirectional illumination analysis and prestack depth-domain reverse time migration experiments were performed on simulated seismic data with 20 dB high SNR (signal-to-noise ratio) and 6 dB low SNR, respectively. The results of this study showed that by adopting a dense exciting-receiving seismic detection system, the eco-friendly non-explosive seismic source technology could reveal the spatial distribution of the main strata underneath the target area and the ore-controlling structures like faults and overthrust nappes. Based on this study, the next step of seismic data acquisition was implemented. The first-hand non-explosive source seismic profiles of the Zhuxi mining area demonstrated that the detection scheme designed was feasible and effective. By constantly improving the technical system, the eco-friendly non-explosive active-source technology would provide a safe and efficient approach, which could be used in the research fields of deep mineral resource prospection, buried faults exploration, urban underground space detection, etc. Finally, the proposed design and demonstration of an active-source seismic detection system based on illumination analysis and migration experiments merits further study and applications. [ABSTRACT FROM AUTHOR]

Selenium is an important element for human health. Many studies have identified selenium deficiency in soil and water as an important factor in causing Keshan Disease (KD) in Northeast China. Previous studies have mainly focused on soil selenium content, staple food selenium content, and human selenium level, but there are few systematic studies on soil selenium's existing forms and their migration from soil to crops and the human body. This paper focused on inferring the barrier factors in the migration of selenium from soil to crop and the human body and transformation of its compounds. It provides a reference basis for the etiological analysis, prevention, control, and elimination of KD. The study used 121 183 samples of topsoil (0−20 cm), 30 295 soil parent samples of selenium and other geochemical indices in northeast China, and crop seeds and human hair samples from the KD endemic area. The surface soil selenium was dominantly selenium-sufficient in Northeast China. However, the soil selenium levels were generally low. The average topsoil selenium in Northeast China was 0.20 mg/kg, significantly lower than the world's average soil selenium content (0.4 mg/kg) and slightly lower than the Chinese average soil selenium content (0.24 mg/kg). Soil selenium mainly existed in strongly bounding by organic bound, with humic acid, and residue forms. The amount of selenium available to plants was sufficient in the selenium-sufficient and KD-endemic areas. However, the average selenium content of human hair was deficient, on average, with 0.16 mg/kg in KD endemic area. We assume that lower soil selenium content may be the basic factor influencing the biogeochemical deficiency of selenium in Northeast China. The sequestration of selenium by clay chemical constituents, such as iron and aluminum oxides and soil organic matter, especially in acidic soils, is another direct contributing factor to the low selenium content in biogeochemical food chain, which increases the risk of KD in the population. [ABSTRACT FROM AUTHOR]

Potato (Solanum tuberosum L.) is an essential staple crop in China. Appropriate storage methods and technology are critical to ensure the quality of seed potatoes, which is closely related to the field performance. So far, the diffused light storage (DLS) technique has been widely applied to potato crop. In this paper, two special potato varieties ('Chuanyu 117' and 'Mira') were treated at DLS for 60 days, and the effects of growth conditions on tuber sprouts and subsequent field performance were evaluated. The results showed that the DLS treatment significantly promoted the greening of potato tubers from highland and simultaneously affected the average sprouting rate, sprout length and number of sprouts at different storage stages, which indicated obvious interacting correlations between DLS treatments and potato varieties. Especially for 'Mira', the shortest average sprout length (2.7 mm) was obtained under 40–200 lx light level, while 'Chuanyu 117' had the shortest average sprout length (1.3 mm) under 5–10 lx and its sprout length was also controlled within 2.3 mm under 200–2000 lx. In the cultivation experiment that followed, the potato tubers with 4–6 mm and 2–3 mm sprout length had the highest yield after 90 days and 110 days planting, respectively. Overall, these results demonstrated that for seed potatoes harvested from the highland area followed by storing for 30 days in the lowland, the sprout length can be better controlled at 2–3 mm to obtain short and strong sprouts when stored under 40–200 lx or 200–2000 lx diffused light for 60 days, which is especially suitable in terms of fast field emergence after planting and final tuber yield for the autumn and winter cultivation of potato in the Chengdu Plain. It is also suggested that the DLS technique on seed potatoes could be used in the mixed single and double-cropping areas in Sichuan and other areas with similar geographical and climatic conditions. The findings of this study have several important implications in the storage, transportation, processing as well as seed potato market for commercial practice. [ABSTRACT FROM AUTHOR]

Rural e-commerce has achieved an effective interface between rural specialty industries and large markets. This paper explores the impact of rural e-commerce on the income levels of potato farmers based on field survey data. In addition, the extent of the impact of rural e-commerce on the income levels of potato farmers in the participating and non-participating groups was further explored under the counterfactual assumption. The main findings are as follows. (1) Rural e-commerce can increase the income of potato farmers. Participation in rural e-commerce can increase farmers' income in both the participating and non-participating groups. If the participating group had not previously sold potatoes through rural e-commerce, their per capita household income would have been reduced by 27.22%. Similarly, if the non-participating group had sold potatoes through the rural e-commerce platform, their per capita household income would have increased by 36.35%. (2) Under the counterfactual assumption, the impact of rural e-commerce on the incomes of farmers who have not yet sold potatoes through e-commerce platforms is more profound. The marginal income increasing effect of rural e-commerce is currently at an incremental stage, and selling potatoes through an e-commerce platform can lead to higher returns for farmers. (3) Gender, farm household differentiation, self-employment experience, arable land area, position in village and whether participating in agricultural associations or cooperatives are important factors that simultaneously influence farmers' e-commerce participation decisions and income levels. Education and health level can influence farmers' e-commerce participation decisions. Age, farming years, dependency ratio and accessibility to irrigation can influence farmers' income level. [ABSTRACT FROM AUTHOR]

Tight oil has become one of the important energy sources for increasing reserves and production in China's oil and gas field. Chang 8 Member of Ordos Basin shows great exploration potential, and the classification and evaluation of tight reservoirs are critical to reservoir optimization and reserve evaluation. However, the classification and evaluation of tight reservoirs in Chang 8 Member of Ordos Basin have not been unified. Therefore, on the basis of previous research results, this paper systematically studied the petrological characteristics, physical properties and microscopic pore throat structure characteristics of tight sandstone reservoirs by means of rock slice observation, overburden porosity and permeability test and high-pressure mercury injection test. On this basis, the weight coefficient of the correlation between the key parameters and the oil-bearing property of the reservoir is determined by screening the key parameters, and the mathematical model of reservoir classification evaluation is established by using the analytic hierarchy process. The research results show that the reservoir composition maturity of Chang 8 Member in Ordos basin is medium, and the lithology is mainly lithic arkose and feldspathic lithic sandstone. The physical property of Chang 8 reservoir is poor, and it belongs to low porosity, low permeability ultra-low permeability reservoir as a whole. The reservoir space is dominated by intergranular pores and dissolution pores, and micro fractures are developed locally. The pore throat structure of the reservoir is fine, and the pore type is smaller than 10 μm, and the throat and micro throat are dominant with 0.2 μm. Considering porosity, permeability, displacement pressure, average pore throat radius and other parameters comprehensively, normalize each parameter, and determine the weight of each parameter according to its correlation with oil saturation. The reservoir classification and evaluation model were established by using the analytic hierarchy process (AHP), and the reservoir quality index (RMI) is used to classify the reservoirs of Chang 8 Member in Ordos Basin into 4 types. This study can provide a basis for efficient exploration and development of tight oil. [ABSTRACT FROM AUTHOR]

This paper focuses on the cold damage and drought cross-stress in maize in Northeast China. The WOFOST model based on parameter localization was used to simulate the growth and development process of maize using daily meteorological data from 110 stations in the research area from 1981 to 2020. The experiment determined that the grouting index and the number of drought days were the indicators for identifying the low-temperature and drought cross-stress in maize, as well as the impact assessment indicators for the fluctuation percentage of dry matter weight in storage organs. It also achieved a quantitative assessment of the impact of cross-stress of low-temperature and drought between 1981 and 2020 and typical years. The results indicated that the WOFOST model can effectively simulate the impact of low-temperature and drought on maize growth, and the historical occurrence of cold damage identified by using the grouting index and drought days as indicators of the low-temperature and drought cross-stress in maize is basically in line with the actual situation. Compared with the average temperature from May to September and the regional cold damage index of > 105 °C supplemented by the meteorological industry standard "Technical Specification for Assessment of Cold Damage to Spring Maize in Northern China", as well as the identification results of the "Drought Grade of Spring Maize in Northern China", the average identification accuracy of low-temperature drought cross-stress in Northeast China based on the WOFOST model is 82.0%, 76.4% of stations have an accuracy of 80.0% or above, and only 4.5% of stations have an accuracy of less than 50.0%. Under the combined influence of low temperature and drought cross-stress, 88.9% of the years showed a reduction in maize production. The evaluation results reflect the historical production reality of maize in Northeast China and are consistent with existing research results. [ABSTRACT FROM AUTHOR]

The poverty alleviation effects of digital financial inclusion are widely recognized, while these effects are dependent on the financial environment. However, little is known about how the financial environment influences digital financial inclusion, which leads to a reduction in household multidimensional poverty. Using matching data from Peking University Digital Financial Inclusion Index of China and Chinese Family Panel Studies for 2012, 2014, 2016, and 2018, this paper estimates the impact of digital financial inclusion on household multidimensional poverty, considering the financial environment. The results show that: (1) Digital financial inclusion alleviates household multidimensional poverty and has significant alleviation effects on different dimensions of poverty. (2) Digital financial inclusion plays a particularly significant role in reducing household multidimensional poverty in China's rural areas and central-western regions. (3) Credit availability, social capital, and non-agricultural employment are important channels through which digital financial inclusion reduces household multidimensional poverty. (4) A single threshold effect governs the influence of the financial environment on the impact of digital financial inclusion on household multidimensional poverty. When the financial environment crosses the threshold value, the poverty reduction effect of digital financial inclusion is enhanced. For the components of the financial environment, a single threshold effect governs the influence of both traditional financial foundations and household financial literacy on the impact of digital financial inclusion on multidimensional poverty, whereas government financial supervision does so via a double threshold effect. [ABSTRACT FROM AUTHOR]

Accurately ascertaining the S-wave arrival times of microseismic signals is crucial for improving the accuracy with which microseismic events can be located. However, the first arrival of an S-wave is often overlapped by the P-wave which can make it difficult to accurately determine the arrival time of the S-wave in tunnels. Therefore, an accurate method for determining the S-wave arrival time of microseismic signals in tunnels is urgently needed. In this paper, a novel method is proposed based on the instantaneous phase difference intensity (IPDI) of the S-wave between two microseismic sensors. The peaks in the IPDI directly indicate the first breaking of an S-wave thus allowing the arrival time of the S-wave to be identified. Tests using synthetic signals verify that the IPDI method can correctly determine the arrival time of an S-wave when the first break of the S-wave is overlapped by the P-wave. The IPDI method was further applied to microseismic monitoring in a deeply buried tunnel in the Jinping II hydropower station in China. The IPDI peaks were found to successfully highlight the arrival of S-waves that could not be determined manually. The location accuracy of rockburst and microseismic events was thus significantly improved using the new IPDI method. Highlights: A novel index (IPDI) is introduced to highlight the first break of microseismic S-wave based on the instantaneous phase of sensors. The IPDI method can identify the S-wave arrival time even in near-field MS monitoring cases where S- and P waves overlap. The IPDI-picked S-wave arrival time substantially improves the MS location accuracy. [ABSTRACT FROM AUTHOR]

Most data collected during routine monitoring of railway station buildings are categorized as in good health, with only a small percentage of samples corresponding to a damaged state. Standard deep neural networks (DNNs) process target samples regarded as normal samples. When typical DNNs are confronted with imbalanced samples, namely, samples with a low proportion of abnormal samples (e.g., damaged stage), this can lead to a high rate of misdiagnosis. To solve this problem, this paper suggests a novel damage monitoring model for railway station buildings, called cluster-based undersampling and Siamese artificial neural network. In this model, normal samples are undersampled based on clustering, and the clustering center and damage samples are combined in a training dataset to reduce the imbalanced rate of damage samples. SANN maps the original space to a feature space where imbalanced damage states are easier to distinguish. Based on SANN, a data-pair selection strategy based on a feedback mechanism is designed to sufficiently mine sample characteristics. A loss function that combines similarity calculation and multi-classification cross-entropy is proposed to improve the representation and classification performance of the model. Six popular algorithms are compared through experiments based on the actual monitoring datasets obtained at the Shijiazhuang Railway Station in China. For different imbalance ratios, the proposed model displayed the highest performance in all indicators. The recall rate for certain imbalanced classifications increased by over 30% compared to the baseline method, verifying the effectiveness and superiority of the model in identifying imbalanced damage states. [ABSTRACT FROM AUTHOR]

This paper examines the coupling coordination degree between digital economy and green technology innovation in 19 urban agglomerations across China from 2011 to 2020. Through the analysis of the coupling coordination degree model, spatial autocorrelation, multi-distance spatial clustering analysis, kernel density analysis and grey correlation model, this study uncovers the mechanism of coupling between digital economy and green technology in Chinese urban agglomerations. Data analysis revealed a significant increase in the coupling coordination between the digital economy and green technology innovation within urban agglomerations. However, there are noticeable spatial imbalances in this trend. Additionally, the multi-distance spatial distance analysis highlights a shift from a random distribution to a clustered distribution of spatial characteristics. The polarization features vary among each urban agglomeration and exhibit a significant positive spatial correlation. Factors such as economic sustainability, creative talent, policy support, digital impetus, and technological support will affect the coupling mechanism of green technology innovation and the digital economy in China's urban agglomerations. Policy recommendations are proposed to foster the development of the digital economy, promote coordinated growth within and beyond urban clusters, and ultimately build a digital ecological civilization that is both green and intelligent. [ABSTRACT FROM AUTHOR]

Aiming at the current low degree of mechanization of pomegranate sprouting tiller pruning in China, all relying on manual pruning, this paper designs a PLC-based pomegranate sprouting tiller removal machine. This machine adopts the identification method of wireless map transmission, the sprouting tiller removal method of multi-cylinder cooperative operation, and the MCGS configuration to realize the interaction between the user and the system, which realizes the displacement and angle compensation of the end-effector under complex conditions to realize the all-around accurate removal of the pomegranate sprouting tiller. The performance test and finite element analysis showed that the device could remove up to 74.62% of sprouting tillers, and the damage rate was as low as 18%. This meets the requirements of pomegranate plantations for the removal of emergent tillers. [ABSTRACT FROM AUTHOR]

In China, higher education institutions (HEIs) have a governance arrangement in which the university president and the party secretary occupy key roles. However, their legal roles as institutional leaders are vaguely specified in existing legal frameworks. Based on a four-dimensional theoretical model, this paper (i) clarifies the leadership roles in the dual governance structure, (ii) explores how HEI leaders (i.e. presidents and party secretaries) perceive their leadership, and (iii) applies the unique Chinese practices as a valuable test bed for critical reflections on how existing theoretical models of leadership are relevant in Chinese contexts. Through in-depth interviews with six top-level leaders from six Chinese public HEIs, our findings indicate that Chinese HEI leaders apply more structural than symbolic dimensions in their leadership practices. Whereas studies on institutional leadership conducted outside China tend to highlight the symbolic dimensions of leadership practices, our study suggests that top-level Chinese HEI leaders may assume the role of university managers rather than institutional leaders. We offer some reflections on the relevance of existing theoretical models of leadership and suggest the directions for further theoretical enhancement. [ABSTRACT FROM AUTHOR]

This paper aims to provide a framework for simulating the formation process of melt-driven debris flow for use in the risk assessment of hazard. According to field research, the formation process of melt-driven debris flows consists of three stages including snow melting, soil infiltration, and runoff/debris flow propagation. From this point of view, an integrated model of melt-driven debris flows is developed, coupling three corresponding physical models through some common variables while considering the effects of temperature variations and entrainment. For the evaluation of the erosion rate of loose materials while considering the presence of fine particles, a relationship between critical shear stress and surface fine-particle proportion is introduced. This integrated model is employed to retrospectively analyze the formation process of the 2010 melt-driven debris flows in the Tianmo catchment, China. The numerical results show that the melt-driven debris flow formation process is effectively described by reproducing the behaviors at each stage based on the proposed model. Furthermore, the hourly temperature variation and sediment characteristics (e.g., coarse particle size and initial soil moisture content) are discussed in detail as factors affecting runoff and entrainment. [ABSTRACT FROM AUTHOR]

This study aimed to report the most current data on the incidence and disability-adjusted life years (DALY) associated with osteoarthritis in China from 1990 to 2019. Publicly available modelled data from Global Burden of Disease Study (GBD) 2019 were used. The incidence and DALY, due to osteoarthritis in China, stratified by sex, trends of associated risk factors, assess the age, period, and cohort effects on the long-term trends of osteoarthritis incidence and DALY in China from 1990 to 2019. We found that the age-standardized incidence and DALY rates of osteoarthritis in China are higher than the average levels in Asia, Africa, and Oceania. In 2019, the number of cases of osteoarthritis in China was 10,681,311, an increase of 132.66% compared with 1990. the DALY of osteoarthritis in China was 4,724,885 person-years, which was 159.70% higher than that in 1990. In 2019, the incidence and DALY rates of osteoarthritis in China was 750.96/100,000,332.19/100,000. High body-mass as risk factors for osteoarthritis DALY with the population attributable proportion (PAF) increasing steadily from 1990 to 2019. The incidence and DALY rates of three types of osteoarthritis from high to low are osteoarthritis knee, osteoarthritis hand, and osteoarthritis hip. Age–period–cohort model showed that the incidence rate of osteoarthritis in China shows a trend of increasing first and then decreasing with age; concurrently, the DALY rate of osteoarthritis in China increased with age. For the period effect, we found that the period rate ratio (RR) of osteoarthritis incidence and DALY rates kept increasing in the cohort born before 2005–2009, and then, it was gradually reduced by year of birth in the cohort born after 2005–2009. As for cohort effect, the cohort RR of incidence rate of osteoarthritis almost has no change, while the cohort RR of DALY rate of osteoarthritis kept increasing from 1990 to 2019. The burden and impact of osteoarthritis in China are substantial and are increasing. Adopting suitable control and preventive community measures to reduce modifiable risk factors is needed to reduce the current and future burden of osteoarthritis in China. Key Points • This paper analyzes the disease burden of osteoarthritis in China for the first time and discusses the influence on the disease burden of osteoarthritis from the perspectives of age, period, and cohort. [ABSTRACT FROM AUTHOR]