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Background: Melanoma differentiation-associated gene 5 (MDA5), as a cytoplasmic sensor for viral double-stranded RNAs, has received increasing attention in recent years. Although considerable headway has been made on the functional role of MDA5 in antiviral immunity and autoimmune disease, the available literature is insufficient to assess the vast field. Methods: This study performed a bibliometric analysis to investigate current hotspots in the global scientific output of MDA5 over the past two decades. Related publications and recorded information from 2002 to 2022 in the Web of Science Core Collection (WoSCC) database were retrieved. VOSviewer and CiteSpace were used for quantitative evaluation and visualization. Results: A total of 2267 original articles and reviews were obtained, and the annual number of publications related to MDA5 was increasing rapidly. China has published the most papers, while the USA was the most influential country with the most citations and the highest H-index. The Chinese Academy of Sciences, the United States Department of Health and Human Services, and the Journal of Virology were the most prolific research affiliation, funding source, and journal, respectively. Fujita T (Kyoto University) was the most productive author with the highest H-index and had close cooperation with Kato H and Yoneyama M. The keywords "RIG-I," "MDA5," "innate immunity," "double-stranded-RNA," and "recognition" had the highest frequency, while "dermatomyositis" as well as "autoantibody" seemed to be the emerging hotspots. Conclusion: This study comprehensively demonstrated the research frontiers of MDA5 and will provide a useful resource for scholars to conduct future decisions. Key Points: We conducted the first in-depth survey of the research frontiers on melanoma differentiation-associated gene 5 (MDA5) over the past two decades via bibliometric analysis. We found that many early breakthroughs have been made in the mechanism of MDA5-mediated antiviral immune responses, and the role of MDA5 in autoimmune and autoinflammatory diseases has raised the recent concern. We identified that the virus infection-associated pathogenesis and effective therapeutic strategy of anti-MDA5 antibody-positive dermatomyositis will remain the hotspots in the future. [ABSTRACT FROM AUTHOR]

This study addresses the challenge of deformation and failure on loess slopes, predominantly triggered by rainfall, by evaluating the efficacy of various slope protective measures. Recognizing the escalating preference for ecological protection techniques, this paper focuses on identifying optimal strategies that align with local rainfall patterns. A comprehensive analysis of loess slopes under diverse rainfall conditions was conducted, encompassing scenarios with prime soil, stabilized soil, and no protection. Utilizing the finite element software ABAQUS, a sophisticated rainfall infiltration slope model was developed and validated against experimental data. The investigation reveals that under low rainfall intensities, the choice of protective material—whether stabilized or prime soil—exerts limited influence on slope pore pressure. In contrast, at higher rainfall intensities, the impact of these protective materials on slope stability becomes significantly more pronounced. [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 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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

Background: Spontaneous reporting of adverse drug reactions (ADRs) is essential for the post-marketing safety evaluation of drugs. Therefore, good monitoring of ADRs is vital for strengthening drug supervision, management, and guiding rational drug use. Chinese medical institutions are the primary source of ADR case reports, but the proportion of the reports in grade IIIA hospitals is still low due to serious under-reporting. The 3rd Affiliated Hospital of Chengdu Medical College, Chengdu Pidu District People's Hospital, also has such a problem. Objective: To improve the quantity and quality of ADR reports and enhance the level of pharmacovigilance in hospitals, the Third Affiliated Hospital of Chengdu Medical College, People's Hospital of Chengdu Pidu District experienced 10 years to gradually establish a management model to improve the medical staff's reporting rate of spontaneous reporting of ADRs. The management model is led by clinical pharmacists and combines the PDCA with Teach-back methods. The purpose of this paper is to introduce the management model and discuss its advantages and shortcomings of this model. Methods: This study was conducted at the Third Affiliated Hospital of Chengdu Medical College—Chengdu Pidu District People's Hospital. From 2016, the daily management of reporting, auditing, and data improvement of adverse drug reactions in the hospital was carried out by clinical pharmacists, who used the PDCA method combined with the Teach-back method to continuously improve the reporting program of ADRs in the hospital during 2016–2021. Then, the proportion of spontaneous reports of total, new, and serious ADRs was compared before and after the intervention. Also, we performed a time series analysis using an autoregressive moving average model to assess changes in the total number of spontaneous ADR reports before the intervention (2013–2015), the first intervention (2016–2018), and the second intervention (2019–2021). Results: After the combined PDCA and Teach-back method intervention, the median number of reported ADRs per year increased from 50 (range 37–55) in the pre-intervention period to 88 (range 83–162) in the first intervention period and to 374 in the second (range 312–566). Breakpoint regression analysis of the spontaneous reporting rate of ADRs showed that the instantaneous increase after the first intervention was not statistically significant (P = 0.526). However, the reporting rate of ADRs increased at a month-by-month growth rate during the second intervention compared to the first intervention. Its spontaneous reporting rate improved 1.034 times (P = 0.002). After the second intervention, the spontaneous reporting rate of ADRs transiently increased 6.111-fold (P < 0.001), and the month-to-month growth rate increased 1.024-fold (P < 0.001) again. Conclusion: The management model that combines the PDCA and the Teach-back method significantly improves the reporting rate of adverse drug reactions. [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]

This paper studied a snow event over North China on 21 February 2017, using aircraft in-situ data, a Lagrangian analysis tool, and WRF simulations with different microphysical schemes to investigate the supercooled layer of warm conveyor belts (WCBs). Based on the aircraft data, we found a fine vertical structure within clouds in the WCB and highlighted a 1–2 km thin supercooled liquid water layer with a maximum Liquid Water Content (LWC) exceeding 0.5 g kg−1 during the vertical aircraft observation. Although the main features of thermodynamic profiles were essentially captured by both modeling schemes, the microphysical quantities exhibited large diversity with different microphysics schemes. The conventional Morrison two-moment scheme showed remarkable agreement with in-situ observations, both in terms of the thermodynamic structure and the supercooled liquid water layer. However, the microphysical structure of the WCB clouds, in terms of LWC and IWC, was not apparent in HUJI fast bin scheme. To reduce such uncertainty, future work may focus on improving the representation of microphysics in bin schemes with in-situ data and using similar assumptions for all schemes to isolate the impact of physics. [ABSTRACT FROM AUTHOR]

Climate change has become an unavoidable problem in achieving sustainable development. As one of the major industries worldwide, tourism can make a significant contribution to mitigating climate change. The main objective of the paper is to assess the development level of low-carbon tourism from multi-aspect, using the Yellow River Basin as an example. Firstly, this study quantified tourism carbon dioxide emissions and tourism economy, and analyzed their evolution characteristics. The interaction and coordination degree between tourism carbon dioxide emissions and tourism economy were then analyzed using the improved coupling coordination degree model. Finally, this study analyzed the change in total factor productivity of low-carbon tourism by calculating the Malmquist–Luenberger productivity index. The results showed that: (1) the tourism industry in the Yellow River Basin has the characteristics of the initial environmental Kuznets curve. (2) There was a strong interaction between tourism carbon dioxide emissions and tourism economy, which was manifested as mutual promotion. (3) The total factor productivity of low-carbon tourism was increasing. Based on the above results, it could be concluded that the development level of low-carbon tourism in the Yellow River Basin has been continuously improved from 2000 to 2019, but it is still in the early development stage with the continuous growth of carbon dioxide emissions. [ABSTRACT FROM AUTHOR]

Old urban community renovation is an important task of urban renewal in China. In order to ensure the quality and efficiency of renovation work, the government requires a method to assess the priority for old urban community renovation. This paper proposes an evaluation model from a more comprehensive perspective. It establishes the evaluation index system with CIPP model. The method of Cloud-VIKOR is selected to construct the evaluation model. Finally, selects nine case communities to verify the evaluation model. The results show that the evaluation index system covers the whole process of renovation project and the evaluation indexes proposed in the existing research. The priority decision result of 9 case communities is basically consistent with the actual renovation sequence and does not change greatly due to the fluctuation of decision-making mechanism coefficient or the evaluation index weight. This evaluation model can help decision-makers diagnose and optimize the renovation project. [ABSTRACT FROM AUTHOR]

The Wujiafentou site is located at the heart of the Youziling (5900–5500 cal BP) and Shijiahe (4500–4200 cal BP) cultures in the Handong region, a core area to understand the relationship among economic networks, sociopolitical integration, and regional identity in the middle Yangtze River valley (MYRV) of central China during the Late Neolithic times. Its pottery assemblages are important clues to understanding the pottery production and use before and after the extensive walled town construction activities in the Neolithic MYRV. Wujiafentou is less than 5 km from the Shijiahe walled town, the largest city of its time in the MYRV. This paper applies microscopic examination and chemical and mineralogical analyses to a sample of 152 sherds of the Youziling-period and Shijiahe-period utilitarian vessels unearthed from the Wujiafentou site, revealing the changes and continuity in pottery production and use over time. We also probe into the socio-economic ties between Wujiafentou and the Shijiahe walled town mainly through hong tao bei (red clay cups), which were widely distributed and presumably highly symbolic items of the Shijiahe culture related to drinking, feasts, and rituals. We propose that the Wujiafentou inhabitants produced their red clay cups by mimicking those made within the Shijiahe walled town. Our study highlights an alternative interpretation of the formation of a regional identity during the Shijiahe period. [ABSTRACT FROM AUTHOR]

The degree to which the banking sector opens up will immediately impact the structure of the national financial system, which will then directly influence the transmission mechanism and effect of monetary policy because it is the fundamental link in the financial system. This study describes the DSGE model of two nations with heterogeneous banks in light of the disparities in global capital flows and loan restrictions between Chinese and foreign banks. DSGE stands for Dynamic Stochastic General Equilibrium. The results show that (1) foreign banks can lessen the net worth shocks of local banks when they are subject to negative shocks to their net worth by injecting international capital flows. (2) The buffer mechanism of foreign banks will obstruct the transmission of monetary policy and partially offset its policy effects. (3) The buffer mechanism of foreign banks has a more pronounced interference effect on monetary policy when facing negative shocks to their net worth. The management of foreign banks is increasingly loosening as China's financial opening up quickens. The findings of this paper have policy implications for how to seize the dividends brought by financial openness and control the interference with monetary policy beyond the advantages of foreign banks in stabilizing economic fluctuations. [ABSTRACT FROM AUTHOR]

In recent years, the convergence of the Internet of Things (IoT) and machine learning technologies has instigated advancements in IoT, and machine learning has revolutionized SMEs, reshaping their role in regional economic growth. These technologies provide SMEs with innovative tools, fostering connectivity within regional ecosystems. This transformation is crucial for China's economic realignment in its 'new normal' phase, with enterprises driving social and economic progress. This study proposed the XGBoost algorithm and IoT data enhance collaboration among SMEs in regional economies, fostering innovation and driving economic development. The role of IoT and machine learning in promoting sustainable regional economic prosperity. Technological innovation is essential for enterprise survival and growth in a competitive landscape. This paper examines the influence of environmental factors and geography on economic development across China's regions. It focuses on SME coupling and coordination, contributing to regional economic progress through performance evaluation. IoT integration provides SMEs with abundant real-time data, enabling deep insights into customer behavior, supply chains, and production. Simultaneously, the XGBoost algorithm efficiently processes and extracts actionable insights from this data. Data from 11 provinces in the Yangtze River economic belt highlights Jiangsu Province's leadership in regional innovation performance for 2015 and 2020. The empirical results, grounded in datasets amalgamating information from these provinces, attest to the potential of this IoT and XGBoost-driven approach. Boasting an impressive accuracy rate of 91.7%, surpassing alternative machine learning techniques like SVM, KNN, DT, RF, and LR, this research underscores the effectiveness of this integrated strategy in optimizing SME operations. Additionally, it computes the coupling coordination degree, innovation environment ranking, mean value, and numerical changes from 2010 to 2020, with an average innovation coupling coordination degree of 0.1624 across 30 Chinese provinces. [ABSTRACT FROM AUTHOR]

The growth of global environmental concerns has prompted a worldwide movement towards sustainable development. In recent years, China's rapid economic growth has been reflected in increased environmental degradation, exacerbated by rapid urbanization, the urban–rural divide, and a government commitment to urban ecological preservation at the expense of rural areas. At the same time, rural communities require increased cultural awareness of environmental conservation and sustainable practices. To address the indiscriminate depletion of natural resources endangering China's rural landscapes, this paper presents a novel framework that combines deep convolutional neural networks (CNNs) with rural ecological governance. A thorough understanding of rural ecological dynamics is made possible by the integration of cutting-edge CNN technology, which facilitates complex data processing and image recognition from satellite and sensor data. Utilizing the Eurostat dataset, it carries out an extensive sustainability analysis of rural ecological governance by applying fundamental theories of environmental governance, such as polycentricity and symbiosis, that are adapted for rural environments. The pastoral environmental governance issues are systematically addressed by means of a multi-stage PPS hierarchical approach. The framework also suggests a novel approach to household waste management for isolated communities, focusing on natural sewage treatment and waste recycling as ways to reduce environmental impact. This all-encompassing strategy seeks to transform rural ecological management by providing customized solutions to protect resources and promote sustainable development in China's rural areas. The experimental results show a fantastic accuracy rate of 98.5% of the CNN model. This compares favorably to recognized architectures such as ResNet16, ResNet32, and ResNet64, demonstrating CNN's ability to handle complex features of rural landscapes. A comparative analysis with RNN and LSTM highlights CNN's capacity to extract hierarchical features and capture spatial dependencies. In addition, the work reveals that rural residents have an overall satisfaction rate of 85.2% with environmental governance, of which 45.6% provide high levels of satisfaction. [ABSTRACT FROM AUTHOR]

In the field of world heritage conservation, there has been broad consensus on carrying out heritage conservation research on the basis of spatial integration and interregional and international cooperation. However, there are still many deficiencies in the integration of culture with the environment, regional economic and social development, and the regional, holistic and multimodal conservation and utilization of cultural heritage sites. In China, the Dongjiang-Hanjiang River Basin is a representative area of substantial cultural and ecological value for both Guangdong Province and the whole country. This paper uses the morphological spatial pattern analysis and the minimum cumulative resistance model to integrate cultural ecology sources and establish a cross-regional and large-scale cultural ecology network system that includes 1 main corridor, 22 important corridors and 17 secondary corridors. In addition, based on identified cultural landscape nodes and cultural ecology services, the economy of the cultural ecology corridor could be developed with large-scale co-construction, co-governance and shared working mechanisms to overcome administrative limits and realize the conservation and utilization of multimodal and large-scale heritage sites. This approach has strong theoretical and practical significance for innovative methods in cultural ecology research, as well as for new content in the research of Lingnan culture, ecosystem restoration, and the economic and social development of towns and villages. This article supplements unilateral studies of regional culture and ecology and demonstrates an in-depth application of cultural ecology theory. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is a progressive neurodegenerative disease with an insidious onset. The widespread application of omics techniques in AD has attracted considerable attention. We aimed to make a comprehensive analysis of published omics articles on AD in order to determine the research profile and application trends of omics techniques in AD. Methods: This study utilizes bibliometric and visual methods including a map collaboration map, co-citations, and keywords to identify knowledge structures, hot topics, and research trends based on 6,828 publications from the Web of Science Core Collection (WoSCC) database. Results: The results of this study showed that 5654 institutions from 91 countries published articles in this field. The USA, China, and the UK played a leading role in publishing numerous articles in relevant journals as well as prolific institutions and authors, respectively. This paper collects a large number of literatures on the application of AD omics technology from the WoSCC database and found the omics technology applied to AD is mainly based on genomics technology. The application of transcriptomics technology has shown an increasing trend in recent years, and the application of multi-omics technology will be the general trend in the future. Conclusion: The development status, frontier hotspots, and general trends of omics application technologies are reviewed. This article will provide intelligence support to researchers and institutions in the field of Alzheimer's omics research and applications from a practical perspective. [ABSTRACT FROM AUTHOR]

International higher education branch campuses (IBCs) in China and elsewhere possess dual identity. There are stakeholders on both the home and host sides. While international branch campuses receive scholarly attention, there has been little study of their research and the role of institutional dual identity in research capacity building. This paper develops a conceptual framework that brings the conditions, practices, and outcomes of research together with dual institutional identity, to study research capacity building at NYU Shanghai. Data from 16 semi-structured interviews with academics, administrators, and university leaders indicate that institutional dual identity is central to what the institution has achieved in building research, influencing every aspect of the process. NYU Shanghai's American identity has shaped academic practices and workloads, and NYU's multi-site structure provides significant networks and resources, yet the institution has also adapted to its Chinese identity and local stakeholders. Dual identity has generated policy conflicts and logistical hurdles yet has also opened institutional and academic opportunities unavailable to other US institutions. While every IBC is embedded in a complex and partly unique context, this study suggests a reflexive understanding of research capacity building in such settings, and contributes to empirical knowledge of cross-border institutions, especially in China. [ABSTRACT FROM AUTHOR]

Chiggers are a group of ectoparasites and they are the vector of scrub typhus. Although the Ryukyu mouse (Mus caroli) is a common species of rodent in some outdoor habitats, few studies are about the mouse itself and its ectoparasites. To date, there has been no specific report on chiggers of M. caroli. Based on the field investigation in southwest China from 2001 to 2019, this paper reported the infestation and distribution of chiggers on M. caroli for the first time. Among the 91 sites investigated, 263 Ryukyu mice were captured at 18 sites, and 678 chiggers were collected from the mice. The collected chiggers were identified to be one family, two subfamilies, six genera, and 16 species with relatively low species diversity. The overall infestation prevalence (PM), mean abundance (MA), and mean intensity (MI) were PM = 27.38%, MA = 2.58 chiggers/per mouse, and MI = 9.42 chiggers/per mouse respectively. The dominant chigger species are Walchia ewingi and W. micropelta with a total constituent ratio of Cr = 94.10% (638/678), and they were of aggregated distribution among different individuals of the host M. caroli. The distribution of two dominant chigger species seemed to be mutually independent with the association coefficient V ≈ 0 (p < 0.001). The infestation (PM, MA, and MI) of M. caroli with chiggers greatly fluctuated in different geographical landscapes, altitudes, and latitudes with an obvious environmental heterogeneity. The male and adult M. caroli harbored much more chigger mites with significantly higher infestations (PM, MA and MI) than the female and juvenile mice. The theoretical curve of species abundance distribution of the chigger mite community on M. caroli was fitted by Preston lognormal distribution model with fitting goodness R2 = 0.77. Based on the iChao1 formula, the expected total number of chigger species on the mice was estimated to be 24 species. [ABSTRACT FROM AUTHOR]

When a tunnel passes through weak and fragmented surrounding rock, excavation disturbance can lead to significant deformation. To mitigate this, advanced support measures like the umbrella arch are necessary. This study investigates the effectiveness of the umbrella arch in controlling deformation of the surrounding rock, focusing on the super shallow-buried spillway section of the Shenzhen East Transit Expressway in China. Both numerical modeling and field monitoring were used to assess the support effect of the umbrella arch. The mechanism of the support was analyzed, revealing that the umbrella arch primarily prevents collapse of the surrounding rock by creating a small compression area. It is recommended that a starting segment with the same length as the tunnel diameter be reserved for the construction of long umbrella arches to maximize their supporting effect. The proposed numerical model was calibrated using field monitoring data, and the mechanical responses of an 80-m-long umbrella arch during construction were thoroughly analyzed. The research results presented in this paper can serve as a reference for the design of umbrella arches in similar projects in the future. [ABSTRACT FROM AUTHOR]

In many buildings with wooden structures, the service life and comfort of the floor will be affected by the walking load of the human body. The vibration effect generated by the human walking on the floor will affect the comfort that the floor brings to people. This article primarily focuses on the study of the correlation between floor vibration and human walking load in wooden buildings. It provides an analysis and summary of research findings from both domestic and international sources. Furthermore, the data collected is utilized to establish a model for estimating human walking load. The advent of information technology has witnessed significant transformative changes spurred by shifts in societal needs. Notably, the establishment of wireless sensor networks stands as a significant milestone within the field of information technology, highlighting advancements in science and technology. The evolution of wireless sensor networks has proven instrumental in various sectors within China, including but not limited to the military, environmental monitoring, biological research and medical systems, disaster monitoring, and energy allocation. This paper uses deep learning algorithms to analyze the node deployment problems of wireless sensor networks, summarizes a reasonable node deployment plan through specific research and practice, and uses collaborative deep learning methods to improve the operating efficiency of the network. In addition, this article also tested the vibration effect of wood structure buildings, analyzed different influencing factors, and provided a good reference point for the formulation of wood structure comfort standards. [ABSTRACT FROM AUTHOR]

Knowledge of how to define and estimate the dependence among multivariate hydrological series is essential for detecting abrupt changes in the dependence. In this paper, a new method (BMCTC) is proposed to detect all possible abrupt change points in the dependence among multivariate hydrological series. The total correlation estimated by the matrix-based Renyi's alpha-order entropy functional is firstly introduced to define and measure the dependence strength among multivariate hydrological series. Then, the moving cut total correlation (MCTC) sequence is built by the moving window technique, which is used to measure changes in the dependence strength among multivariate hydrological series. Finally, the Bernaola-Galvan algorithm is used to detect all change points of the MCTC sequence. Simulations are performed to compare the effectiveness of BMCTC with Pearson correlation (BMCPC) and Spearman correlation (BMCSC), Cramer-von Mises (CvM) and copula-based likelihood-ratio (CLR). The results show that all change points are detected by BMCTC regardless of the samples size, but wrong change points or no change points are detected by other methods in most cases. BMCTC is applied to detect change points in the dependence among annual runoff, precipitation and sediment discharge series in the Xiliugou and the Kuyehe River, China. It is found that the dependence among runoff, precipitation and sediment discharge changed abruptly in 1980 and 1996 in the Kuyehe River and in 1999 in the Xiliugou River. These changes are mainly caused by human activities such as construction of water conservancy projects and coal mining. [ABSTRACT FROM AUTHOR]

The dynamic effect is a very important issue widely debated by scholars when studying the genetic and disaster-causing mechanisms of earthquake-triggered landslides. First, the dynamic effect mechanism and phenomena of earthquake-triggered landslides were summarized in this paper. Then, the primary types of dynamic effects were further used to interpret the Mogangling landslide in Moxi Town of Luding County, China. A field investigation, remote sensing, numerical calculation and theoretical analysis were carried out to illustrate the failure mechanism of slope rock masses affected by earthquakes. The interaction between seismic waves and slope rock masses and the induced dynamic effect of slope rock masses were primarily accounted for in the analysis. The slope topography, rock mass weathering and unloading characteristics, river erosion, regional seismogenic structure, and rock mass structure characteristics were also discussed. The results showed that the formation of the Mogangling landslide was mainly related to the high amplification effect of seismic acceleration and back slope effects, interface dynamic stress effects, and double-sided slope effects of seismic waves caused by the catastrophic Ms 7.75 Moxi Earthquake in 1786. The principles for the site and route selection of large-scale infrastructure in the planning stage and the scientific prevention of seismic geological disasters were proposed on the basis of the dynamic effect of earthquake-induced landslides. [ABSTRACT FROM AUTHOR]

China communicates strategic narratives about artificial intelligence (AI) in digital media productions to create a shared meaning about its actions and its image in the global race to develop AI. Building upon the literature in emotions and strategic narratives, this study seeks to clarify which emotions are discursively used in China's international AI narratives, and their function and significance. Specifically, the study investigates emotion discourses in AI-focused videos disseminated on China's international broadcasting (CGTN YouTube channel). The analysis reveals that pride, hope and fear discourses have multiple functions in China's international AI narratives on CGTN. Hope is used to represent China as a key competitor in the global AI race, who is catching up to the US. China uses pride to showcase its advances in AI applications, to highlight its transformation of traditional industries, and to identity itself as equal to the US. Fear is used to frame US's perception of China's AI developments, to suggest their crisis of confidence, but also to refute the "China threat". Additionally, the fear discourse is used to deliberate anticipated risks, particularly on job loss and data privacy. These emotion discourses forge China's identity as a future global AI power. The paper then discusses how these findings contribute to key debates about Chinese discourse and media strategy. [ABSTRACT FROM AUTHOR]

Innovations in precision agriculture continue to increase in both number and significance. Contemporaneously, given their expanding scope and application, the growing pool of technologies is increasingly complex. Although some recent attempts have been made, a knowledge gap remains in respect to the evolution of precision agricultural innovation. Synthesized, such knowledge should inform the untapped opportunities for innovation. This paper narrows this gap by conducting a network analysis of patent applications in areas concerning precision agriculture. Spanning the years from 1960 to 2021, the analysis shows an annual average growth in patent applications of 15.1%. During the last decade, this growth is almost entirely attributable to China and the USA. Priority innovation themes have been dynamic. Its phases can be characterized as 'motorized mechanization' (1960–1999), 'mechanical automation' (2000–2009), 'digital mechanization' (2010–2019), and 'digital automation' (2020–2021). The significance of information communication technology has grown in association with other innovation clusters, but a lag time has persisted in introducing innovations based on such technologies. Opportunities are ripe for speeding transference through economic and other incentives. [ABSTRACT FROM AUTHOR]

Over the past 40 years, China has witnessed the world's largest urbanization process. In light of its natural and cultural conditions featuring resource scarcity, frequent natural disasters, rich cultural heritage and regional disparities and dynamics, this process aggravates the complex and severe problems faced by urban areas, including resource and environmental damage, security risks and cultural degradation. To address these issues, a shift in national and regional urban spatial layouts from improving economic competitiveness to balancing protection and development as well as security and development is needed. Related theories and research methods should also be adjusted accordingly. Therefore, given China's specific conditions and regional spatial layouts, the paper introduces the "national spatial planning theory," which aims to create a sound living environment. The core concept is "precise adaptation," which ensures the adaption of urban development to natural and cultural conditions. It is the first theory that proposes to develop the national urban spatial layout based on the analysis of ecological environment. It also suggests shifting the focus from eco-environment to security and culture as urbanization progresses and problems change constantly. In addition, a method framework and technical system of "precise analysis, adaptive distribution and dynamic evaluation" is formulated to build an adaptive urban spatial layout on the basis of quantitative analysis of the capacity of spatial resources. The practices of regional planning processes on varying scales in the past 20 years are to illustrate the specific applications of the theoretical approach. [ABSTRACT FROM AUTHOR]

Based on the global reanalysis data of the National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research, the surface meteorological observation data, sounding data and satellite observation data, this paper comprehensively analyzes the evolution process and formation mechanism of a persistent severe dense fog process occurred on February 15–17, 2015 in Yancheng, eastern China. Through the numerical simulation experiment of Weather Research and Forecast (WRF) model, we further analyze the impact of sea-land breeze on the formation and burst reinforcement of fog. Results show that the precipitation caused by the southwesterly airflow in front of the upper-level trough and the low-pressure inverted trough are conducive to the formation of early rain fog, while the nighttime clear radiance under the control of surface cold high and the infiltration of weak cold advection are conducive to the formation and development of later radiation-advection fog. The WRF model simulates the fog evolution process, which is basically consistent with the actual fog area, and the simulation results are credible to a certain extent. The simulation results show that the establishment of sea breeze has an advection cooling effect on the near surface layer, which is conducive to the formation and development of the inversion layer on the near surface, providing stable stratification conditions for the formation and burst reinforcement of fog. On one hand, the strengthening of sea breeze circulation can continuously transport water vapor to the study area. On the other, the occurrence of ultra-low level jet is favorable for the accumulation of low-level water vapor. At the same time, the inversion intensity further strengthens, which is in favor of the burst reinforcement and long-term maintenance of fog. [ABSTRACT FROM AUTHOR]

The construction of smart cities may bring positive and negative effects simultaneously on citizens' perception of safety (CPS), while previous studies in the field of smart city construction paied significant attention to safety-related technologies but ignored CPS. Therefore, this work developed an indicator set consisting of five primary and eleven secondary indicators. A model integrating analytical network process and fuzzy comprehensive evaluation was used to evaluate CPS in smart cities. Nanjing, a pilot smart city in China, was adopted as the case to demonstrate the proposed evaluation methodology. The results showed that the CPS in Nanjing was at a positive level on the whole. The citizens held the highest CPS in medical treatment, while the CPS concerning information and food were weak. This paper would not only enrich the academic framework related to CPS, but also help the government formulate sustainable smart city construction strategies. [ABSTRACT FROM AUTHOR]

Geographic information system-based mineral prospectivity mapping (MPM) aims to generate targets by combining multiple proxy layers containing geology, geochemistry, and geophysics information based on an available understanding of geological processes and translating it into critical targeting criteria. However, factors such as an imperfect geological understanding with numerous heuristic natures and intrinsic biases, the inaccuracy and sparsity of datasets, and multiple selections of predictive methods adversely affect the results of MPM and jeopardize the reliability of decision-making in exploration. Thus, a series of knowledge-driven and data-driven MPM approaches to counterbalance these disadvantages have been proposed. Uncertainty is defined as a metric of the various scales of the likelihood and consequences, which is helpful to quantitatively represent the above risks. In this paper, the uncertainty in the final three-dimensional prospectivity map is analyzed and interpreted in terms of quantification, visualization, and comparison of different predictive approaches, and a novel technology is proposed based on a (1 + ε) approximate global optimum strategy derived from the truth discovery society. It outputs the globally optimal truth (p*) as the overall mathematical expectation and a set of weights w i as the representation of reliability. Here, a previous study of the Haoyaoerhudong gold deposit, which is one of the largest black-rock-series-type gold mines in China, was reevaluated. The method demonstrated the following advantages: (i) sorted the reliability of potential models built by multiple predictive variables and different mathematical methods, (ii) provided a "best-guess-decision" prospectivity result by combining the best reliability model from w i and the signal-to-noise ratio (SNR) of the risk–return model, and (iii) provided a statistically final uncertainty model by combining p* and risk information. [ABSTRACT FROM AUTHOR]

Coal and gas outburst is a type of coal mine dynamic disaster with complex causes and serious consequences. In China, the number and scale of outburst disasters are among the highest in the world. It is an inevitable stage for outburst that the mechanical instability of the combination of intact coal and tectonic coal (CICTC) in strata. The dip angle of the interface has an important influence on the instability of CICTC-containing gas. To further understand the instability process of CICTC, the uncoordinated deformation of CICTC was defined. According to this, three strain conditions were delimited. The variations of stress under three strain conditions were analyzed, the expressions of additional interfacial stress were established. Then, based on the Mohr–Coulomb criterion, the strength characteristics and failure forms were analyzed. It was found that the dip angle deflects the principal stress in the interface, and the influences of additional stresses on the value of principal stress are opposite. These two reasons make the principal stress state and instability process of the combination complicated. Finally, combined with actual parameters, the instability processes of CICTC under different stress paths and buried depths were studied. It can be found that the failures of CICTC under different stress paths were concentrated appearing in the tectonic coal body, intact coal interface, and tectonic coal interface. With the increase of buried depth, the initial maximum principal stress increases and the reduction from additional stresses to the strength of intact coal interface enhances, which makes the combination damage easily and the failure form change. The research results in this paper can provide a theoretical basis to prevent and control the outburst of the combination containing gas considering the dip angle of the interface. Highlights: The uncoordinated deformation of combination considering the dip angle was first defined. The expressions of additional interfacial stress of combination considering the dip angle were established The influences of different stress paths and buried depths for the instability of combination were discussed quantificationally. [ABSTRACT FROM AUTHOR]

This paper gives high-precision theoretical predictions for cross sections of the process e+e– → γZ for future electron–positron colliders. The calculations are performed using the SANC system. They include complete one-loop electroweak radiative corrections, as well as longitudinal polarization of the initial state. Numerical results are given for the center-of-mass system energy range = 250–1000 GeV with various polarization degrees in the α(0) and Gμ EW schemes. This study is a contribution to the research program of the CEPC project being under development in China. [ABSTRACT FROM AUTHOR]

Karst spring water dynamic characteristics and its response to atmospheric precipitation are of great significance for water resources utilization under the background of climate change. This paper selects Longzici spring area, North China, as the study area. Based on a long series of spring water flow and precipitation data, the dynamic characteristics of spring flow were analyzed and the numerical simulation of the groundwater flow model was established. The results show that the groundwater kept the sustained decline over the past decades which is in a negative equilibrium state, with a storage variable of − 2.26 million m3/year. The sensitivity of spring flow to precipitation under different precipitation scenarios shows that the water level changes in the recharge and drainage areas are similar about (3–5 cm) and slightly larger than that in the runoff area(1.5 cm) when minimum rainfall (287.24 mm) happens. When the precipitation is at its maximum (867.66 mm), the water level change in the runoff area can reach 95 cm which is much larger than those in the recharge and discharge areas. The results indicate that Longzici karst spring has a relatively good regulation water resource capacity and the runoff area is more sensitive which plays an important role in response to climate change. [ABSTRACT FROM AUTHOR]

With the opening of the Stock Connect programs, the mainland China and Hong Kong stock markets are becoming more closely linked. In this paper, we develop a China's stock market risk early warning system. The proposed early warning system consists of three components. First, we use value at risk (VaR) to identify the stock market risk in which stock market risk is divided into multiple categories instead of two categories. Second, we construct a comprehensive indicator system in which basic indicators, technical indicators, overseas return rate indicators, and macroeconomic indicators are considered simultaneously. Third, we use four machine learning models, namely long short-term memory (LSTM), gate recurrent unit (GRU), multilayer perceptron (MLP), and EXtreme Gradient Boosting algorithm (XGBoost), to predict China's stock market risk. Experimental results show that: (1) Considering the macroeconomic indicators and basic indicators of Shanghai Composite Index (SSEC), ShenZhen Component Index (SZCZ) and Hang Seng Index (HSI) can significantly improve the performance of predicting China's stock market risk. (2) The opening of SH-HK Stock Connect program improves the predictive performance, but the opening of SZ-HK Stock Connect program decreases the predictive performance. (3) The indicators related to Hong Kong become more important after the SZ-HK Stock Connect program. [ABSTRACT FROM AUTHOR]

This transition from gathering to cultivation is a significant aspect of studying early agricultural practices. Fruit trees are an essential component of food resources and have played a vital role in both ancient and modern agricultural production systems. The jujube (Ziziphus jujuba Mill.), with its long history of cultivation in northern China, holds great importance in uncovering the diet of prehistoric humans and understanding the origins of Chinese agricultural civilization. This paper focuses on the domestication of jujube by analyzing the morphology of jujube stones found in three Neolithic sites in northern China's Qi River basin, Zhujia, Wangzhuang, and Dalaidian. The measurements of these jujube kernels are compared with those found in other areas of northern China, as well as modern jujube kernels that were collected. The measurements revealed that the length-to-diameter (L/D) ratio of sour jujube kernels ranged from 1.36 to 1.78, whereas the L/D ratio of cultivated jujube stones varied between 1.96 and 4.23. Furthermore, jujube stones obtained from Zhujia and Wangzhuang sites exhibit pointed ends and possess an elongated oval or narrow oval shape overall, which is indicative of clearly artificial domestication traits. Therefore, this study suggests that jujube was selected and cultivated as an important food supplement in the Qi River basin no later than around 6200 BP. [ABSTRACT FROM AUTHOR]

Currently, a standardized design and calculation specification for suction drum foundations has yet to exist in China. The engineering design currently depends mainly on the subjective understanding and engineering experience of the designers, which can be considered somewhat blind and subjective. In this paper, we utilize the offshore wind power project in Yangjiang City, Guangdong Province, as our case study. Building upon domestic and international research results, relevant investigations, design specifications, and engineering applications in related fields, we conduct a systematic study on the design calculation and construction control technology of the suction drum foundation. The document presents the design calculation and inspection of the suction drum foundation. Building on this foundation, we propose a sinking feasibility analysis method and a parameter value method for the suction drum foundation calculation. We also examine the suction drum foundation construction process, examining its control parameters, technology, and standards. Finally, based on the measured data from six four-barrel guided frame platform suction drum foundations that were successfully installed, the proposed design and control method are evaluated, and their effectiveness is verified. The results of this study can provide valuable references for the design and construction of similar suction drum foundation platforms. [ABSTRACT FROM AUTHOR]

In recent years, transformative technological advances have reshaped countless sectors, including higher education, leaving a lasting and indelible mark. Artificial intelligence (AI) and the Internet of Things (IoT) coming together has proven to be an influential driving force for the development of creative solutions to the ever-evolving challenges faced by educational institutions. Traditional classroom teaching methods have encountered unprecedented hurdles with the widespread integration of the Internet into education. China's commitment to "governing the nation by law" has elevated the need for legal expertise. As society evolves, pedagogical approaches must adapt. Information and communication technology trends, combined with the rise of the IoT, are reshaping education and offering tools to bolster campus security, monitor vital assets, and enrich classroom accessibility. This paper proposes an AI-based hybrid model and an IoT-infused teaching approach personalized for legal education in colleges and universities, employing the decision tree algorithm. The study's focal point is the development of legal professionals possessing the robust capabilities and qualities society seeks, using teaching methods compatible with modern information technology. The foundation of this endeavor lies in the hybrid teaching mode, specifically Internet-based legal research. Within this platform, educators can disseminate instructional materials, videos, and exercises, with the option to enlist teaching assistants to aid in managing student learning. Comparing varied and traditional teaching classes, the passing rates were 96.75% and 95.36%, respectively. Data analysis using decision trees identifies factors influencing these rates. The study also evaluates students' accuracy in five in-class exercises; in the mixed class, correctness rates were 96.4%, 93.5%, 82.5%, 64.2%, and 62.8%. The proposed method is compared with other machine learning algorithms (SVM, KNN, LR, RF) and Decision Trees to evaluate the educational impact of the mixed teaching approach comprehensively. [ABSTRACT FROM AUTHOR]

In recent years, technological advancements have been replicated in various industries, including sports medicine. Recent developments, such as big data analytics and data mining, which have revolutionized medical services in sports, are apparent in this transformation. This technological shift is motivated by the need to enhance athletic performance, prevent injuries, and offer individualized health advice. Modern lifestyles have simultaneously increased people's attention to their health, creating a demand for better medical services. However, China's ability to provide superior medical care needs to be improved due to a lack of medical resources and an ever-increasing patient population. To address these challenges, this research paper presents an integrated framework that leverages Spark-based big data analytics and the XGBoost algorithm. The framework aims to provide a robust sports medical service encompassing real-time health monitoring and data-driven insights. Powered by the formidable distributed computing platform Spark, it adeptly manages extensive sports data generated during training and events, facilitating instant health evaluations. Incorporating the XGBoost algorithm for data mining amplifies health prediction and recommendation capabilities. Renowned for its predictive prowess, XGBoost excels in discerning intricate sports data patterns and trends. Its proficiency in tackling intricates feature selection and modeling tasks ensures precision and actionable insights. Empirical findings underscore substantial enhancements in sports medical services. When applied to chronic disease datasets, the XGBoost algorithm garnered an impressive 93% trust rate. In contrast to conventional methods like K-Nearest Neighbors (KNN), Random Forest (RF), Decision Trees (DT), Support Vector Machines (SVM), Naïve Bayes (NB), and Logistic Regression (LR), the proposed framework consistently outperforms these established techniques. This remarkable performance underscores the transformative potential of the integrated framework in revolutionizing sports medical services. [ABSTRACT FROM AUTHOR]

Encryption chips are specialized integrated circuits that incorporate encryption algorithms for data encryption and decryption, ensuring data confidentiality and security. In China, the domestic SM4 algorithm is commonly utilized, as opposed to the international AES encryption algorithm. These widely implemented encryption standards have been proven to be difficult to crack through crypt analysis methods Currently, power consumption side-channel attacks are the most prevalent method. They involve capturing power consumption data during the encryption process and subsequently recovering the encryption key from this data. The two leading methods are Differential Power Analysis (DPA) and machine learning techniques. DPA does not necessitate prior knowledge but relies heavily on the number of power consumption curves. With only 50 power consumption data points, the accuracy is a mere 80%. Machine learning methods require prior knowledge, achieving an accuracy rate above 95% with only 30 power traces, albeit with training times typically exceeding 15 min. In this paper, a distributed energy analysis attack approach was presented based on Correlation Power Analysis (CPA). The power consumption data was divided into 16 subsets, with each subset corresponding to 8 bytes of the key. By training each subset separately, the 8-byte key's corresponding power consumption data is reduced to only 100 dimensions, resulting in a 76% decrease in cracking time and a 3% improvement in cracking accuracy rate.This article also trains a more complex 256 classification model to directly crack the final key, achieving a success rate of 28% in cracking 128-bit passwords with only 1 power trace [ABSTRACT FROM AUTHOR]

Shenfu Dongsheng coal field is a cross-century energy base which is developed and constructed in China. In recent years, some mines have successively entered to the coal seam of the second layer. Due to the reasons of early mining, many coal pillars are left in the coal seam of the first layer, resulting in the phenomenon of strong ore pressure in the mining range before and after the coal pillar in the lower coal seam and even causing the buckling accident. In order to solve such safety problems, this paper takes the 22,307 working face in Bulianta coal mine as the research object, adopts physical similarity simulation experiment and theoretical analysis to systematically study the overlying rock characteristics and abnormal ore pressure manifestation mechanism of shallow and close coal seam in different working stages. The results show that the roof overburden of the key layer in the lower group bends and sinks when the coal pillar is mined, resulting in the activation and instability of the "masonry beam" structure formed by the roof of the upper coal seam. When the coal pillar is discharged, the residual concentrated coal pillar and the room type coal pillar are unstable under the action of high supporting stress, resulting in shear failure of the inter-layer rock in the upper part of 22,307 working face, causing the strong dynamic pressure of the working face to appear and then leading to the buckling accident. The working resistance of the support in each stage is obtained by establishing the structure diagram of the overlying rock under each stage and the corresponding mechanical structure model. Finally, the working resistance required by the support in the mining stage under the goaf is 16,692.6 kN, the working resistance required by the support in the coal pillar stage is 19,692.6 kN, the working resistance required by the support in the mining stage under the concentrated coal pillar is 13,150.6 kN, and the working resistance required by the support in the coal pillar stage is 19,215.6 kN. [ABSTRACT FROM AUTHOR]