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The risk of cardiovascular disease (CVD) is a serious health threat to human society worldwide. The use of machine learning methods to predict the risk of CVD is of great relevance to identify high-risk patients and take timely interventions. In this study, we propose the XGBH machine learning model, which is a CVD risk prediction model based on key contributing features. In this paper, the generalisation of the model was enhanced by adding retrospective data of 14,832 Chinese Shanxi CVD patients to the kaggle dataset. The XGBH risk prediction model proposed in this paper was validated to be highly accurate (AUC = 0.81) compared to the baseline risk score (AUC = 0.65), and the accuracy of the model for CVD risk prediction was improved with the inclusion of the conventional biometric BMI variable. To increase the clinical application of the model, a simpler diagnostic model was designed in this paper, which requires only three characteristics from the patient (age, value of systolic blood pressure and whether cholesterol is normal or not) to enable early intervention in the treatment of high-risk patients with a slight reduction in accuracy (AUC = 0.79). Ultimately, a CVD risk score model with few features and high accuracy will be established based on the main contributing features. Of course, further prospective studies, as well as studies with other populations, are needed to assess the actual clinical effectiveness of the XGBH risk prediction model. [ABSTRACT FROM AUTHOR]

The ability to predict gas emissions accurately is pivotal in managing gas control and ensuring safe mining operations. Existing internationally acknowledged gas control and prediction software does not cater to the specific conditions in Chinese coal mines. Hence, this paper introduces an object-oriented programming method to design a software tool for calculating the total gas emission quantity using the MATLAB application program designer runtime environment. The software incorporates an algorithm, data structure, framework, and module functions, all of which enable seamless integration and visualization of gas emission calculation software. This software tool mitigates the inefficiencies and inaccuracies associated with manual, different-source forecast methods. Based on the field data of the Hulonggou Coal Mine in Shanxi province, this technical software was used to predict the gas emission of the mine. The research results show that the predicted value of the technical software is close to the actual measured value. The differing estimates of the working face and coal mine output primarily account for the deviation between the tool's predicted gas emission value and the field-measured value. The underlying design logic of this technical software determines that it has good adaptability to mines with clear mining technology parameters and gas geological parameters. This study provides a valuable method for researchers and engineers seeking to improve gas emission calculation efficiency. [ABSTRACT FROM AUTHOR]

Heritage buildings represent history and act as vessels of human civilisation. The significance of these architectural phenomena increases as society increases, which renders their preservation and ethical use increasingly crucial. Hence, preserving heritage buildings is necessary for societal benefit. The accuracy of three-dimensional (3D) point cloud models of heritage buildings is important to their digital conservation. Traditional mapping methods typically require more time and human resources. Furthermore, the outcome is subject to measurement omissions, errors, and other issues, which are contrary to the protection of the object measured. The complex elements of ancient Chinese architecture render it challenging for traditional measuring techniques to accurately capture spatial structural information. The 3D laser scanning technology is a novel technology to obtain 3D data rapidly. In this paper, the Great Achievement Palace of the Confucian Temple in Yuci District, Jinzhong City, Shanxi Province, was used as an example to examine the application of 3D laser scanning technology to acquire point cloud models of heritage buildings. Field data collection for architectural heritage using 3D laser scanning technology requires measuring station setting analysis to ensure effect accuracy while considering the elements of target location and quantity. For the 3D point cloud model of the Great Achievement Palace, error analysis and accuracy assessment were conducted on the quality elements of alignment accuracy between scanning stations, point cloud model reliability, point cloud data noise condition, and whether the point cloud data were stratified. The findings demonstrated that the improved method quickly and accurately acquired 3D point cloud model data and obtained realistic spatial data models of the heritage building. [ABSTRACT FROM AUTHOR]

Surface subsidence threatens the structural stability of ground facilities located in mining-induced subsidence areas. Clarifying and evaluating the influence of surface subsidence can inform the construction and maintenance of various ground facilities, such as buildings, roads, and bridges. In this paper, we investigated mining-induced surface subsidence and areas of potential damage in Yangquan City, Shanxi Province, by exploiting small-baseline set interferometric synthetic aperture radar (SBAS-InSAR) monitoring and geographic information system (GIS) techniques. More specifically, we first investigated the distributions of subsidence areas and subsidence rates in Yangquan City from June 16th, 2016, to December 1st, 2016, by exploiting SBAS-InSAR monitoring. We then classified ground facilities, such as buildings, highways and railways, and identified their distributions using spatial analysis using GIS. Finally, we integrated the results of the two techniques to evaluate the potential damages induced by surface subsidence for various ground facilities. We found that, overall, (1) surface subsidence has seriously developed in the Yangquan Mine and (2) some of the subsidence areas exist in facilities with high-level restrictions, such as high-rise buildings, highways, and railways, which may cause potential damage. Our work presented in this paper could be referred to and applied to other similar cases. [ABSTRACT FROM AUTHOR]

Interferometric synthetic aperture radar (InSAR) has been effectively used to monitor surface deformation in a mining area with millimeter-level accuracy. On March 27, 2022, a tailings dam failure occurred in Shanxi Province, China, causing significant damage to surrounding houses, woodland, and roads below the tailings pond. We obtained the surface deformation map of the tailings dam before the catastrophic failure using the InSAR time-series method with a full resolution of Sentinel-1 A. This paper employed a GPU-assisted InSAR processing method for 91 Sentinel-1 images in Interferometric Wide Swath (IW) mode acquired from January 8, 2019, to March 17, 2022. The InSAR results show that during the 25 months preceding the tailings dam failure, Dam-II experienced an average cumulative LOS deformation of nearly 80 mm, while Dam-I experienced a significant deformation of more than 140 mm in the LOS direction. The analysis combining the deformation and rainfall results shows that rainfall significantly affects tailings pond deformation. In general, the deformation evolution has a high correlation with the rainfall annually, but the maximum deformation rate occurs with a delay of about one month compared to the peak rainfall. InSAR technology can significantly improve the monitoring capability of tailings dam failure and other landslide disasters, but it is limited by the observation frequency of the satellite. Thus, improving the temporal resolution of SAR data may assist in predicting tailings dam failure times more accurately. [ABSTRACT FROM AUTHOR]

With the continous advancement of industrialization, the environmental problems among resource-based cities in China are becoming increasingly serious. Therefore, exploring the spatiotemporal evolution characteristics of industrial agglomeration and environmental pollution to understand the interaction mechanism between them is of great significance for the coordinated development of resource-based cities. In this paper, 114 resource-based cities in China are selected as research objects, and data from the period of 2011 to 2020 are used for analysis and research. Location entropy and entropy weight models are used to measure the relevant indicators, and a spatial simultaneous equation model is constructed. The generalized spatial three-stage least squares (GS3SLS) method is used to assess the spatial interactive spillover effects of industrial agglomeration on environmental pollution. The research results show that ① the industrial agglomeration center of China has begun to shift to the junction of Shanxi, Shaanxi, and Inner Mongolia, and the level of environmental pollution has dropped significantly; ② industrial agglomeration promotes environmental pollution, while environmental pollution inhibits industrial agglomeration, and between them, the inhibition effect is more obvious; ③ the level of industrial agglomeration in surrounding cities promotes industrial agglomeration in the region and inhibits environmental pollution, while the level of environmental pollution in surrounding cities inhibits industrial agglomeration in the region and promotes the diffusion of pollution. Thus, the building of a coordinated development system across regions can achieve a win–win situation between industrial development and environmental protection. [ABSTRACT FROM AUTHOR]

Arsenic is a toxic metal-like element. The toxic reaction of the body to arsenic is related to the ability of arsenic methylation metabolism. As the rate-limiting enzyme of arsenic methylation metabolism, the genetic single nucleotide polymorphisms (SNPs) of arsenic (+ 3 oxidation state) methyltransferase (AS3MT) gene are related to capacity of arsenic methylation. In this paper, we investigated the association of five SNPs (rs7085104, rs3740390, 3740393, rs10748835, and rs1046778) in AS3MT with arsenic methylation metabolizing using the data and samples from a cross-sectional case–control study of arsenic and Type 2 diabetes mellitus conducted in Shanxi, China. A total of 340 individuals were included in the study. Urinary total arsenic (tAs, μg/L) was detected by liquid chromatography–atomic fluorescence spectrometry (LC–AFS). According to "safety guidance value of urinary arsenic for population" as specified in WS/T665-2019 (China), participants were divided into the control group (tAs ≤ 32 μg/L, n = 172) and arsenic-exposed group (tAs > 32 μg/L, n = 168). iAs%, MMA%, and DMA% are as the indicator of arsenic methylation capacity. The genotypes of AS3MT SNPs were examined by Multiple PCR combined sequencing. Linear regression analysis showed that AG + GG genotype in rs7085104 was associated with decreased iAs% and increased DMA%. Moreover, AG + AA genotype in rs10748835 and TC + CC genotype in rs1046778 were associated with decreased iAs% and MMA% and increased DMA%. The interaction between rs7085104 and arsenic is associated with iAs% and DMA%. The interaction of rs3740390 and rs10748835 with arsenic is associated with iAs%. Haplotype CTAC (rs3740393-rs3740390-rs10748835-rs1046778) was associated with lower iAs% and higher DMA%, but this association disappeared after adjusting for age, gender, drink, smoking, BMI and tAs. Haplotype GCAC was associated with decreased MMA%. Our study provides additional support for revealing the factors influencing the metabolic capacity of arsenic methylation and might be helpful to identify the population susceptible to arsenic exposure through individualized screening in the future. [ABSTRACT FROM AUTHOR]

Regional debris flow susceptibility assessment is an effective method to prevent debris flow hazards, and deep learning is emerging as a novel approach in this discipline with the development of computers. However, when debris flow samples are insufficient, there will be problems like overfitting or misclassification. To overcome these problems, this paper proposes a semi-supervised deep neural network model (LPA-DNN) combined with label propagation algorithm (LPA), which utilizes high confidence unlabeled samples as pseudo-samples reasonably in few-label scenarios. Xinzhou, Shanxi Province, was selected as the study area, and a dataset containing 292 debris flow samples and 10 types of impact factors was compiled based on watershed units. Using the dataset and pseudo-samples, the LPA-DNN model was built to get debris flow susceptibility map. Meanwhile, DNN and SVM were set up for comparison to demonstrate that the proposed LPA-DNN model has excellent performance and higher accuracy. LPA-DNN alleviates the problem of low accuracy that caused by samples lacking in deep learning to a certain extent, and obtains great classification results, which proves that it is quite potential in regional debris flow susceptibility assessment. [ABSTRACT FROM AUTHOR]

At the same time as the rapid development of developing countries, unreasonable conventional planning and industrialization have led to instability in rural areas, especially resource-based rural systems. Rural environment and planning continue to receive widespread attention. Based on the emergy analysis theory, this paper constructed a rural environmental value-added evaluation system with resource, development, space and environmental protection as the factor layer (including 18 sub-indicators). Based on this system, the value-added situation of the socio-economic-natural composite ecological environment of Queshan Village in Shanxi Province from 2010 to 2015 was quantitatively evaluated, and the development strategy was proposed. It was found that from 2010 to 2015, the resource element decreased from 0.17 to about 0.00, the development factor decreased from 0.16 to 0.06, the space factor increased by 0.19 from 0.07, the environmental protection factor decreased from 0.21 to 0.05, and the composite index decreased from 0.61 to 0.30. It showed that the ecological environment growth of Queshan Village was negative in the evaluation period, and the development showed an imbalance law and an unsustainable development trend. According to the analysis results, this paper put forward development opinions from four aspects: resources, industry, environment and government investment. This method constructs a quantitative analysis system for rural environmental value-added evaluation, and has certain theoretical and practical value in rural planning guidance and evaluation. [ABSTRACT FROM AUTHOR]

The ancient lacquer films excavated from Dongshan Han tomb M6 of the Western Han Dynasty in Taiyuan City, Shanxi, China, were found sensitive to pH variation. This paper aims to demonstrate the pH-dependent warping behaviors of the ancient lacquer film and discuss their mechanism. The samples were analyzed by surface analytical techniques including attenuated total reflectance-Fourier transform infrared spectroscopy and X-ray photoelectron spectrometry. The results suggest that the outer layer of the lacquer film is more oxidized than the inner layer and contains more carboxylates, with calcium ions and possibly ammonium cations as counter ions. The carboxylates are speculated to be formed by oxidative cleavages in the urushiol side chains and hydrolysis of glycerides of drying oils. The shrinkage and swelling of the lacquer film can be regulated by the type of cations (H+, Ca2+, Na+) of carboxylates through hydrogen bonds, coordination bonds and static forces. Due to the higher content of carboxylates in the outer part, it shrinks more at low pH causing warping outward and swells more at high pH causing warping inward. This paper may provide an important reference for pH control and help resolve the warping problem during conservation or restoration of ancient lacquerware. [ABSTRACT FROM AUTHOR]

Street lighting, as the most essential and universal component of the urban lighting system, accounts for a large portion of public electricity usage. Therefore, improving street lamps working efficiency is vital for energy savings. This paper demonstrates the design of a smart street lighting system supported by the combination of NB-IoT and LoRa communication technology. By adopting an optimized street lamp control algorithm, the system can realize the automatic control of street lights according to the real-time traffic flow information. This system has been installed on Luyang Avenue, Lucheng City, Shanxi Province, China in May 2019. It managed to reduce the electricity consumption in this region significantly in June 2019, which was 18% lower than that in April 2019 and 19.7% lower than that in June 2018. By illustrating the unique advantages of this system in energy savings and cost reduction, this paper displays its potential for further application in the construction of smart cities on a large scale. [ABSTRACT FROM AUTHOR]

The shift from the conventional agri-food system to alternative practices is a challenging transition for agricultural producers, yet surprisingly under-studied. Little research has examined the social and cultural processes in rural communities that mobilize producers and construct and sustain producer-driven alternative food networks (AFNs). For AFNs to go beyond just offering "alternative foods" or "alternative networks" and to be constructed as "alternative economies", this transformation in the producer community is indispensable. This paper presents a case study of a rural cooperative in Shanxi, China. The discontent with both productivist agriculture and the social decay in communities motivated a group of women to engage in a decade-long process of social mobilization, cultural reconstruction, and learning by experimentation. Through this, they developed an alternative vision and successfully created a localized alternative socio-economic model, which I call "anti-productivism". It prioritizes ecological sustainability, self-reliance, reciprocity, and cultural values over output maximization, productivity growth, commodity exchange, and monetary gains. This case contrasts sharply with the urban-initiated, consumer-driven AFNs studied in the China literature, which mostly just offered alternative foods but brought little change to the producer community. It shows that the alternative economy must be embedded in an alternative community united by strong social bonds and shared cultural values. [ABSTRACT FROM AUTHOR]

The premise of ecological protection and sustainable development in coal mining areas is to find the law of surface damage, damage speed and damage mechanism, and then put forward preventive measures in a targeted manner. Taking the landslide in the coal mining mountain area of Shanxi Province as an example, this paper comprehensively integrates the disaster-pregnant environment and disaster information of the landslide, and constructs a multi-level model of the scene through the analysis of the landslide geology scene. The object features characterize the evolution process of landslides in terms of stratigraphic structure changes, surface changes, texture changes, shape characteristics, spectral characteristics, color characteristics, etc., the typical landslide types in Shanxi coal mining areas are verified by examples. The comprehensive consideration of geology, geographical environment, ecological environment, disaster environment and the damage of landslides to other important ground features, with the advent of the era of big data, various data obtained from air, space and ground monitoring can be applied to research. Through the cognition of landslide spatial scenes, it is helpful to understand the influence mechanism of external events on landslide activities, so as to better predict the spatial and temporal characteristics of landslide activities. [ABSTRACT FROM AUTHOR]

A quantitative research on the effect of coal mining on the soil organic carbon (SOC) pool at regional scale is beneficial to the scientific management of SOC pools in coal mining areas and the realization of coal low-carbon mining. Moreover, the spatial prediction model of SOC content suitable for coal mining subsidence area is a scientific problem that must be solved. Taking the Changhe River Basin of Jincheng City, Shanxi Province, China, as the study area, this paper proposed a radial basis function neural network model combined with the ordinary kriging method. The model includes topography and vegetation factors, which have large influence on soil properties in mining areas, as input parameters to predict the spatial distribution of SOC in the 0–20 and 2040 cm soil layers of the study area. And comparing the prediction effect with the direct kriging method, the results show that the mean error, the mean absolute error and the root mean square error between the predicted and measured values of SOC content predicted by the radial basis function neural network are lower than those obtained by the direct kriging method. Based on the fitting effect of the predicted and measured values, the R2 obtained by the radial basis artificial neural network are 0.81, 0.70, respectively, higher than the value of 0.44 and 0.36 obtained by the direct kriging method. Therefore, the model combining the artificial neural network and kriging, and considering environmental factors can improve the prediction accuracy of the SOC content in mining areas. [ABSTRACT FROM AUTHOR]

Aiming at the problems of long time, high cost, invasive sampling damage, and easy emergence of drug resistance in lung cancer gene detection, a reliable and non-invasive prognostic method is proposed. Under the guidance of weakly supervised learning, deep metric learning and graph clustering methods are used to learn higher-level abstract features in CT imaging features. The unlabeled data is dynamically updated through the k-nearest label update strategy, and the unlabeled data is transformed into weak label data and continue to update the process of strong label data to optimize the clustering results and establish a classification model for predicting new subtypes of lung cancer imaging. Five imaging subtypes are confirmed on the lung cancer dataset containing CT, clinical and genetic information downloaded from the TCIA lung cancer database. The successful establishment of the new model has a significant accuracy rate for subtype classification (ACC = 0.9793), and the use of CT sequence images, gene expression, DNA methylation and gene mutation data from the cooperative hospital in Shanxi Province proves the biomedical value of this method. The proposed method also can comprehensively evaluate intratumoral heterogeneity based on the correlation between the final lung CT imaging features and specific molecular subtypes. [ABSTRACT FROM AUTHOR]

This paper constructs a geophysical model of hidden disaster-causing anomalies in coal rock for simulation experiments based on the structural design of coal rock seams at the mine working face to study the geophysical response characteristics of geological anomalies in coal rock seams. The material ratio and petrophysical parameters of the coal seam, roof, floor, collapse column, and fault in a mining area in Shanxi were tested using homogeneous and orthogonal test methods, and their petrophysical parameters, such as Vs,Vp, resistivity, permeability, and dielectric constant, were obtained. The coal dust and sand–cement contents are the main factors affecting the wave velocity, whereas the dielectric constant and resistivity are highly influenced by the water content of the material. The response characteristics of the petrophysical parameters of various types of geological structures measured via experiments are consistent with the corresponding geophysical responses of actual geophysical exploration methods. The experimental data were comparatively analyzed with the original coal rock samples and field in-situ probing results, and the best construction ratios of each geological structural unit were as follows: coal seam ratios of 61.11%, 11.11%, and 27.78% were selected for coal dust, sand, and cement content, respectively; sand–cement and gypsum–cement ratios of 2:1 and 2:8, respectively, were selected for the roof; and sand–cement and gypsum–cement ratios of 3:1 and 4:6, respectively, were selected for the floor. The optimal ratios of 75% sand, 10% gypsum, and 15% cement were chosen for the fault; those for the collapse column were 66.7% sand, 6.67% gypsum, and 26.6% cement. This study focuses on the ratios of various geotectonic physical models and their physical properties, it provides data support for subsequent model construction and a good experimental platform for the demonstration of various geophysical exploration methods and techniques. [ABSTRACT FROM AUTHOR]

CBM (Coalbed methane) belongs to unconventional natural gas mineral resources. The development and utilization of CBM can greatly reduce the occurrence of mine gas accidents, and how to improve the desorption capacity of CBM has always been a hot issue for researchers. Liquid nitrogen has obvious effect on coal seam cracking and permeability improvement. The purpose of this paper is to study the cracking mechanism of liquid nitrogen on coal, and provide a theoretical basis for using liquid nitrogen freezing and thawing to treat coal so as to improve the production of coalbed methane. Coal samples from Yangquan County, Shanxi Province were pretreated. The pore structure test, microscopic observation test and methane isothermal adsorption test were carried out after the coal samples with different particle sizes were treated with different liquid nitrogen freeze-thaw cycles. According to the experimental data, the evolution law of pores of coal before and after freezing and thawing with liquid nitrogen, the cracking mechanism of coal treated with freezing and thawing with liquid nitrogen, and the optimal number of freezing and thawing cycles with liquid nitrogen are analyzed. The results show that: 1) the evolution characteristics of pore structure of lower coal after liquid nitrogen freezing and thawing are that micropores in coal are promoted to develop into transition pores and mesopores, and mesopores and transition pores develop into macropores and fractures. 2) Through the observation of a metallographic microscope, the expansion degree of coal surface crack is positively correlated with the times of liquid nitrogen freeze-thaw. 3) Liquid nitrogen freeze-thaw treatment has an optimal number of cycles for the cracking degree of coal. With the increase of freeze-thaw cycles, the final adsorption capacity of coal pillar increases first and then decreases; The adsorption capacity of granular coal first increases and then decreases. After reaching freeze-thaw saturation, continued freeze-thaw is not conducive to the increase of adsorption capacity. These research results provide theoretical support for the implementation of liquid nitrogen fracturing and permeability enhancement technology in coal reservoirs. [ABSTRACT FROM AUTHOR]

The introduction of logistics theory and logistics technology has made the government and enterprises gradually realize that the development of logistics has an important strategic role, which can effectively solve the changing needs of users, optimize resource allocation, improve the investment environment, and enhance the overall strength and overall competitiveness of the regional economy. This paper carries out matrix–vector multiplication operations and weight update operations, designs a perceptron neural network model, and realizes a simulation platform based on MLP neural network. Moreover, on the basis of the standard MLP neural network, this paper proposes to use the deep learning training mechanism to improve the MLP neural network, which provides effective technical support for the improvement of the prediction model. In addition, through the fusion of deep learning and MLP neural network, an MLP neural network with three hidden layers is determined. Finally, this paper builds a model based on the MLP neural network algorithm, selects the RBF kernel function as the kernel function of the model by referring to the relevant literature, and uses PSO to optimize the combination of parameters. It can be seen from the result of the evaluation index that each evaluation index is relatively small. The result shows that the prediction is accurate, and the empirical result shows the feasibility of the model to predict the demand for industrial logistics in Shanxi Province. [ABSTRACT FROM AUTHOR]

Increased CO2 emissions from urban energy consumption pose a significant challenge to regional carbon mitigation policies. In this paper, we integrated two nighttime light (NTL) data: the Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (NPP) composite data to estimate the energy carbon emissions from 2000 to 2019. Then the spatiotemporal dynamics of carbon footprint and deficit in the Yellow River Basin were analyzed at the provincial, municipal, and county scales combined with NPP data. The study shows that (1) the total amount of energy consumption CO2 emissions in the Yellow River Basin had increased from 1332 Mt in 2000 to 6469 Mt in 2019, but the average annual growth rate slowed down after 2010 from 11.5 to 5.61%. (2) From 2000 to 2018, the provinces with the highest carbon footprint and carbon deficit were concentrated in Inner Mongolia and Shanxi. In 2018, Inner Mongolia's carbon footprint was 1366.91 × 104 km2, accounting for 22.8% of the total. Cities with high carbon footprint were mainly economic centers and energy-intensive areas of various provinces. High-carbon deficit counties were mainly distributed in the western region. In 2018, 954 counties exhibited carbon deficits. (3) The carbon footprint in the Yellow River Basin at the municipal and county scales have a significant spatial correlation. The H–H clusters of the carbon footprint on the municipal scale were distributed in the middle reaches of the Yellow River Basin. At the county scale, the L-L clusters were mainly in Sichuan and eastern Henan regions. Through the analysis of the spatial and temporal evolution of carbon footprint and carbon deficit in the Yellow River Basin, it is significant to measure the degree of comprehensive coordination of carbon sources and sinks in the basin, to grasp the differences in the level of regional carbon emissions, and to promote synergistic regional governance, assist in the formulation of more precise carbon emission reduction policies, and to promote green and high-quality development. [ABSTRACT FROM AUTHOR]

Stroke is the leading cause of death in China (Zhou et al. in The Lancet, 2019). A dataset from Shanxi Province is analyzed to predict the risk of patients at four states (low/medium/high/attack) and to estimate transition probabilities between various states via a SHAP DeepExplainer. To handle the issues related to an imbalanced sample set, the quadratic interactive deep model (QIDeep) was first proposed by flexible selection and appending of quadratic interactive features. The experimental results showed that the QIDeep model with 3 interactive features achieved the state-of-the-art accuracy 83.33%(95% CI (83.14%; 83.52%)). Blood pressure, physical inactivity, smoking, weight, and total cholesterol are the top five most important features. For the sake of high recall in the attack state, stroke occurrence prediction is considered an auxiliary objective in multi-objective learning. The prediction accuracy was improved, while the recall of the attack state was increased by 17.79% (to 82.06%) compared to QIDeep (from 71.49%) with the same features. The prediction model and analysis tool in this paper provided not only a prediction method but also an attribution explanation of the risk states and transition direction of each patient, a valuable tool for doctors to analyze and diagnose the disease. [ABSTRACT FROM AUTHOR]

To evaluate the relationship between coal-related carbon emissions (CCE) and economic growth, this paper analyzed the decoupling relationship between CCE and economic growth from national and provincial perspectives during period 1997–2016 through Tapio Decoupling Index. Then, to recognize its spatial characteristics during 1997–2016, gravity model was adopted to study the geographical changes of CCE. Finally, to identify the changes of (CCE) in China and reveal its internal driving forces, this paper employs the logarithmic mean Divisia index (LMDI) decomposition analysis to decompose decoupling indicator into six effects including emission factors, energy intensity, fossil energy structure, energy consumption structure, activity, and population at national and provincial levels. The results reflect that (1) CCE of China rose by 168.37% from 1997 to 2016, and reached the peak of 7948.43 Mton in 2013. The center of gravity has shifted from (114.64 E, 34.70 N) to (113.48 E, 35.06 N). (2) The decoupling curve showed an inverted "U" shape. The economic growth of 18 provinces has achieved a strong decoupling from CCE by 2016. Only Xinjiang, Shanxi, and Shaanxi's economic growth has increased the dependence on CCE. (3) Activity and energy intensity effects were the dominant factors driving and curbing the increase of decoupling indicator respectively. [ABSTRACT FROM AUTHOR]

In recent years, global warming has attracted extensive attention. The main cause of global warming is the emission of greenhouse gases, known as carbon emissions. Therefore, it is of great significance to explore the influencing factors of carbon emissions and accurately predict carbon emissions for reducing carbon emissions and slowing down climate warming. This paper takes the carbon emissions of Shanxi Province in China as the research object. Firstly, the emission factor method is used to calculate the carbon emissions, and then the grey correlation model is used to screen out the factors that have a greater impact on carbon emissions (per capita GDP, urbanization rate, resident population, energy consumption, expenditure on R&D projects). Then, an improved grey multi-variable convolution integral model (AGMC(1, N)) is used to accurately predict carbon emissions. The results show that the application of the AGMC(1,N) model to carbon emission prediction has a good prediction effect. In addition, the carbon emissions of Shanxi Province will increase with the growth rate of per capita GDP, energy consumption, resident population, and expenditure on R&D projects, while the carbon emissions will gradually decrease with the increase of urbanization level. The prediction results provide the direction for carbon emission reduction in Shanxi Province. At the same time, theAGMC(1,N) model can also be applied to the prediction of carbon emissions in other provinces or other fields. [ABSTRACT FROM AUTHOR]

China is one of a few countries in the world where karst is intensively developed and karst water is heavily utilized as water supply sources. Shanxi is such a Province with the largest karst distribution in places in Northern China, where 19 large karst springs and their catchments are identified to provide important sources of the water supply and ecosystem functioning in Shanxi. Over the years, many problems associated with utilization of karst springs in Shanxi cropped out, including the decrease in spring flow, decline of groundwater level, groundwater contamination and pollution, etc., which severely restrict the sustainable utilization of karst water resources in Shanxi. Through the retrieval and analysis of some 200 local and international publications, this paper critically reviews the research results of karst springs in the region from the perspective of spring flow trend, precipitation recharge and time-lag, evaluation of karst water resources, water chemistry and environmental isotopes with purposing assession, and further evaluates the integrity of the aquifer system including vulnerability, impacts of coal mining and engineering activities on karst groundwater, delineation of spring catchment sub-systems, protection and management measures. It is concluded that human activities and climate change are the primary and secondary factors negatively affecting karst springs, respectively. The impacts of human activities on karst springs are mainly facilitated by intensive development of karst water, mining drainage, engineering construction and other activities. While karst water in parts of Shanxi spring catchments is polluted to various degrees, hence it is recommended to mainstream the protection of karst spring water in the areas of strategic importance. This paper will contribute towards the establishment of sustainable development and utilization of karst water in Shanxi and even in Northern China. [ABSTRACT FROM AUTHOR]

Coalbed methane extraction not only reduces natural emissions of a greenhouse gas, it also allows for safer coal mining and reduces the risk of underground disasters. The pressure environment of coal is an important factor in the gas extraction effect, so it is important to accurately assess the pressure distribution in front of the working face. In this paper, we analyzed the pressure distribution of the coal mass in front of the working face by means of numerical simulations. We then proposed the concept of self-relief pressure zone based on the numerical simulation results to accurately determine the efficient gas extraction area. Finally, a field test was conducted in the Qinshui Basin of Shanxi Province, China. Numerical simulations indicated that there is a self-pressure relief zone of about 4.86 m to 5.06 m in front of the working face. The total stress of coal seam in self-relief pressure zone is obviously small, showing obvious plastic deformation characteristics. Field tests showed poor methane extraction when the borehole was in a stress concentration zone. The amount of pure methane extracted significantly increases when the borehole enters the self-relief pressure zone in front of the working face. For the test working face, the width of the pressure relief zone in front of the working face is about 8.9 m to 14.7 m. Furthermore, we analyze the mechanism of the effect of self-relief zones on gas extraction and discuss how self-relief zones can be used to improve gas extraction in coal seams. Thus, these findings have important theoretical foundations for the field application of gas extraction with pressure relief in coal mines. [ABSTRACT FROM AUTHOR]

The carbon emission of the energy industry is mainly generated by power generation. Adjusting the power generation structure of multiple energy sources, so as to control the carbon emission of the power generation industry and measure its emission reduction space, is the key for power generation industry to achieve the goal of "dual carbon targets." This study develops a regional multi-energy generation simulation model, which is based on the core algorithm of generation dispatching approach. The established model can simulate the dispatching of all types of generating units in the region and output the data of power generation and emissions. Considering taking Shanxi Province as example, the output results under the benchmark scenario are obtained to verify the efficiency of the model. The error of renewable energy generation and other generation is less than 4%, which shows that the model has enough credibility. The results of the scenario analysis show that every 5% increase in the utilization rate of wind turbine units will increase almost 20% of the renewable energy power generation, reduce almost 15% of the thermal power and reduce at least 10% of the CO2 emissions. This proves that China's regional power generation industry has certain emission reduction potential. The proposed model has important application value for energy conservation and emission reduction of regional power generation industry. [ABSTRACT FROM AUTHOR]

Type 2 diabetes mellitus (T2DM) is one of the major public health problems worldwide; both genetic and environmental factors are its risk factors. Arsenic, an environmental pollutant, might be a risk factor for T2DM, but the association of low-to-moderate level arsenic exposure with the risk of T2DM is still inconsistent. Single nucleotide polymorphisms (SNPs) can affect the development of T2DM, but the study on KEAP1 rs11545829 (G>A) SNP is few. In this paper, we explored the effect of KEAP1 rs11545829 (G>A) SNP and low-to-moderate level arsenic exposure on risk of T2DM in a cross-sectional case–control study conducted in Shanxi, China. Total of 938 participants, including 318 T2DM cases and 618 controls, were enrolled. Blood glycosylated haemoglobin (HbA1c) was detected by Automatic Biochemical Analyzer, and participants with HbA1c≧6.5% were diagnosed as T2DM. Urinary total arsenic (tAs, mg/L), as the indicator of arsenic exposure, was detected by liquid chromatography–atomic fluorescence spectrometry (LC–AFS). Genomic DNA was extracted and the genotypes of KEAP1 rs11545829 SNP were examined by multiplex polymerase chain reaction (PCR). The urinary tAs concentration in recruited participants was 0.075 (0.03–0.15) mg/L, and was associated with an increased risk of T2DM (OR = 8.45, 95% CI 2.63–27.17); rs11545829 mutation homozygote AA genotype had a protective effect on risk of T2DM (OR = 0.42, 95 % CI 0.25–0.73). Although this protective effect of AA genotype was found in participants with higher urinary tAs level (>0.032 mg/L) (OR = 0.48, 95% CI 0.26–0.86), there was no interaction effect for arsenic exposure and rs11545829 SNP on risk of T2DM. In addition, BMI modified the association between rs11545829 SNP and the risk of T2DM (RERI = −1.11, 95% CI −2.18–0.04). The present study suggest that low-to-moderate level arsenic exposure may be a risk factor, while KEAP1 rs11545829 SNP mutation homozygote AA genotype may be a protective factor for risk of T2DM, especially for T2DM patients with urinary tAs level>0.032 mg/L. [ABSTRACT FROM AUTHOR]

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The No. 3 coal seam is one of the primary mineable coal seams in Du'erping coal mine of Shanxi Coking Coal Group Co., Ltd. The direct roof of No. 3 coal seam is a compound roof with two layers of 0.3–0.5 m extremely soft coal seams in the unstable rock stratum. The mining roadway has a large amount of deformation and is difficult to support. This paper takes 63,409 ventilation roadway of Du'erping coal mine as the engineering background. The RFPA2D numerical simulation software was used to compare and analyze the distribution characteristics of surrounding rock fracture zone and surrounding rock deformation in the mining roadway of the general roof and compound roof under the conditions of coal body–coal body and coal body–coal pillar. The supporting form and main supporting parameters of the mining roadway with compound roof were determined. Through simulation and comparison, the deformation of the mining roadway with compound roof under unsupported and three different support conditions were analyzed, and the combined support method of "bolt + anchor cable + metal mesh" was field tested. By analyzing the monitoring data of the roadway roof subsidence, floor heave, ribs displacement and roof abscission layer, the results show that the combined support method of "bolt + anchor cable + metal mesh" effectively controls the large deformation of the mining roadway with compound roof, improves the stability of the surrounding rock, suppresses the occurrence of roof fall and rib spalling, and ensure the safety of the roadway. [ABSTRACT FROM AUTHOR]

How to solve the contradiction between development needs and environmental protection has become the difficulty and focus of rural grass-roots government governance. In this paper, from the two dimensions of information interaction and energy flow, based on the calculation of environmental value-added, a new rural environment environmental value-added model is established, and the reliability of the model is verified by taking the data of Pingding County in Shanxi Province as an example. The results show that: (1) the accuracy of the information flow environmental value-added model is as high as 95.96%, and the model can be applied to the outdoor environment comfort prediction; (2) the comprehensive index of the relative value-added of the ecological environment is reduced from 0.61 to 0.31, and the value-added situation of the ecological environment is negative in the evaluation period, and the development is unbalanced and unsustainable. The trend of continuous development is in line with the actual local development. By measuring the relationship between the gain effect and the cost input of the ecosystem, the model comprehensively analyzes the potential of land and space development and protection in the future, and provides basic support for improving the strategy of main functional areas, drawing up land spatial planning, scientifically delimiting ecological protection red line, permanent basic farmland and urban development boundary, and exercising unified land space use control and ecological protection and restoration, try to open up a new situation of environment and development [ABSTRACT FROM AUTHOR]

The layered rock masses with structural planes are widely distributed, among which the transverse isotropy caused by the bedding structural plane has a great influence on the stability of the slope and surrounding rock. Construct a beam-particle model (BPM) to reveal the layered slate fracture characteristics is of great significance. This paper takes the layered carbonaceous slate of the Muzhailing tunnel in Shanxi as the research specimens, carries out the Brazilian split test and uniaxial compression test of the layered slate with different bedding inclination angles, and conducts out a systematic numerical analysis based on the BPM solver. The test and numerical results show that: (1) In the Brazilian split test, the load–displacement curve of the layered slate has the development trend of the initial stage, the rock specimens compaction, nearly linear elasticity, and finally complete collapse. As the bedding inclination angle changes from 0 ∘ to 90 ∘ , the tensile strength of slate decreases successively. (2) In the uniaxial compression test, when the bedding inclination angle is 0 ∘ and 90 ∘ , the compressive strength is greater, and the bedding inclination angle is 30 ∘ , 45 ∘ and 60 ∘ , the compressive strength is small and the value is close, showing a "U"-shaped change as a whole. (3) With the change of bedding inclination angle and the comprehensive influence of matrix and bedding, the split failure mode of layered slate is complex and changeable, and roughly presents split tensile failure, shear slip failure and comprehensive tensile shear failure. (4) Through the comparative analysis of test load–displacement response and failure mode, the BPM solver can better reproduce the split evolution process of layered slate under different bedding inclination angles, and prove the robustness and stability of the program. The BPM solver can provide a new numerical research method for the widespread engineering practice of layered rock masses. [ABSTRACT FROM AUTHOR]

Grasshopper optimization algorithm (GOA) proposed in 2017 mimics the behavior of grasshopper swarms in nature for solving optimization problems. In the basic GOA, the influence of the gravity force on the updated position of every grasshopper is not considered, which possibly causes GOA to have the slower convergence speed. Based on this, the improved GOA (IGOA) is obtained by the two updated ways of the position of every grasshopper in this paper. One is that the gravity force is introduced into the updated position of every grasshopper in the basic GOA. And the other is that the velocity is introduced into the updated position of every grasshopper and the new position are obtained from the sum of the current position and the velocity. Then every grasshopper adopts its suitable way of the updated position on the basis of the probability. Finally, IGOA is firstly performed on the 23 classical benchmark functions and then is combined with BP neural network to establish the predicted model IGOA-BPNN by optimizing the parameters of BP neural network for predicting the closing prices of the Shanghai Stock Exchange Index and the air quality index (AQI) of Taiyuan, Shanxi Province. The experimental results show that IGOA is superior to the compared algorithms in term of the average values and the predicted model IGOA-BPNN has the minimal predicted errors. Therefore, the proposed IGOA is an effective and efficient algorithm for optimization. [ABSTRACT FROM AUTHOR]

Groundwater plays a key role in supplying water for drinking water, irrigation water, and industry water in the northern China. Recently, the availability and quality of groundwater resources in the eastern Loess Plateau (Shanxi province) have a serious impact on the agriculture, industry, and domestic sectors. This paper investigates the spatiotemporal variations of chemical and stable isotope composition of groundwater, and provides important information for the research of controlling factors of groundwater hydrochemical distribution in Shanxi province during two seasons. About 95 groundwater samples were collected from two seasons and measured the content of major ions and stable isotope, pH values, and total dissolved solids (TDS). The results showed that groundwater samples were mildly alkaline. Among all the groundwater samples, the HCO3− and Na+ dominated the total mass of the anions and cations, respectively. Significant seasonal and spatial variations can be observed in the TDS, deuterium (δ2H), and oxygen (δ18O) in groundwater samples. More pronounced variations of the groundwater TDS appeared in the quick-flow season with the highest TDS concentration observed at the central region and lower TDS values appeared in the northern and southern Shanxi. The groundwater samples mainly belong to the (HCO3−-Ca2+-Na+) type and the (HCO3−-SO42−-Ca2+-Na+) type. Rock weathering is the key controlling factor for the chemical composition of groundwater. In addition, nitrogen pollution of groundwater caused by human input is more significant in river valley basins such as the Yuncheng Basin, Linfen Basin, and Changzhi Basin. The significant influence of surface water-groundwater interaction for the groundwater can be observed at the valley basin in the central part of the Shanxi Province. The interaction between surface water and groundwater in the Linfen basin is especially remarkable. [ABSTRACT FROM AUTHOR]

Silo-cave is a unique human habitation form on the Loess Plateau in northern China, which consists of an excavated 6–7 m deep pit as the courtyard and cave dwellings in the surrounding four walls. This architecture has had a history of more than 7000 years, and yet such "living fossils for the history of dwellings" are now facing great crises and challenges during rapid social and economic development. In this paper, remote sensing and GIS techniques are used to comprehensively and systematically investigate the spatial distributions and morphological characteristics of silo-caves at both the macro and micro scales. The research shows that silo-cave villages are mainly distributed in economically underdeveloped areas, such as West Henan (Yuxi), South Shanxi (Jinnan), Central Shaanxi (Guanzhong), and East Gansu (Longdong). The morphological evolution patterns of typical silo-cave villages are identified, including: (1) retaining the periphery and rebuilding the inner parts of the villages, (2) retaining the inner parts and expanding the periphery of the villages, and (3) rebuilding the inner parts and expanding the periphery of the villages. These patterns are demonstrated to be influenced by many factors, including landforms, traffic conditions, economic development, population growth, and administrative division adjustment. Sustainable development of these traditional silo-cave villages relies on administrative policy and planning, people's awareness of cultural heritage protection, culture inheritance, industrial transformation, and public services. [ABSTRACT FROM AUTHOR]

Due to rapid socioeconomic development, seeking the coordination of resources exploitation and the ecological environment has become an objective requirement for the healthy and sustainable development of the mining industry. This paper selects 23 indicators with which to construct an evaluation index system for mineral resources exploitation and the mining geological ecological environment of Shanxi Province from 2003 to 2015. It then establishes a development index model, a coupling degree model and a coupling coordination degree model. Using a time-series analysis, the comprehensive development level, coupling status and coupling coordination degree of the two systems are analyzed. The results are threefold. (1) The overall level of mineral resources exploitation improved, but, after 2012, the level dropped significantly. The ecological environment in the mining area has improved as a whole, but, due to the ecological fragility caused by long-term extensive mining and acute treatment, the state of the ecological environment fluctuates greatly. (2) The coupling degree between mineral resources exploitation and the mining ecological environment is stable, and it has been in the antagonistic stage for a long time. Although the degree of coupling coordination has improved, it remains at a low level. (3) Further improvement in the coordination between mining exploitation and the mining ecological environment in Shanxi Province has been restricted due to several indicators with greater weights. Recommendations to be considered by policy makers include insufficient sustainable development concepts, outstanding historical issues and the lack of guarantees for environmental protection funds. [ABSTRACT FROM AUTHOR]

In 2009, a serious gas explosion happened in Tunlan coal mine at Shanxi province, P.R. China, which claimed the lives of 78 miners. One hundred and fourteen miners got injured, and nearly 4 million dollars of economic loss was reported. On the surface of it, it seems to be an independent happened accident. However, the formation of a gas explosion is dependent on various conditions and all these conditions must be met at the same time so as to result in such explosion. Hence, the explosion itself is not a single event in time. With considering the gas explosion causing the mine ventilation system failure, there must be a number of related causations existing in the system which play important roles that contribute to the system failure. In other words, explosion can be considered as an evolution resulting from various related other failures in the system. Hence, in this paper, failure modes and their contributions to the explosion are going to be investigated. Based on the requirements of an explosion and its propagation characteristics in the underground roadway network, this paper summarizes all failure modes in the gas explosion accident through the initial formation of explosion to its post effects. Moreover, using the theoretical approach and simulation method, the corresponding contributions are also interpreted. The research efforts show that (1) it should not simply treat the explosion as an independent event. Various linked failure modes can be observed during the analysis. It is a quite interesting and also needed for mining engineers to well understand their formations and effects on the system, which may greatly improve the system design in the future to avoid such accidents and (2) the domino effect is involved in various failure modes. It also provides a solution to stop the accident's propagation by breaking any chain reactions. The research results presented in this paper can be used as theoretical guidelines for improving the safety considerations of a mine ventilation system design work in the future practices. [ABSTRACT FROM AUTHOR]

The accurate and stable prediction of electricity consumption is essential for intelligent power systems in rapidly developing countries. Grey prediction model is one of choices for prediction under the condition of limited historical data. Nonetheless, it seems rather sceptical using single-variable grey prediction model to predict the dynamics of a complex system. This paper presents a novel multivariable grey prediction model based on first-order linear difference equation for long-term electricity consumption prediction. The proposed model solves the problem of parameter estimation and variable prediction deriving from different approaches through rewriting the whitenization equation of multivariable grey model (MGM(1, m)). To validate the effectiveness of the proposed hybrid model, the electricity consumption is estimated and predicted over the data from Shanxi province and Beijing city in China from 1999 to 2018. The results show that the hybrid model provides a better estimation and prediction performance compared with other prediction model for predicting electricity consumption. [ABSTRACT FROM AUTHOR]

A variety of dust control methods are often applied in coal mines, among which the application of wet scrubbers has proven to be an efficient technology for the removal of dust in airstreams, rather than diluting or confining the dust. In this paper, a wet scrubber design was developed. Based on a self-designed experimental test platform, the total dust concentration, respirable dust concentration, air volume, and average pressure drops of wet scrubbers with 12, 16, 20, and 24 blades were measured under different water intake conditions. The results show that the different water intake levels have only minimal effects on the air volume of the wet scrubbers. However, increased water intake had improved the dust removal efficiency of the wet scrubbers with the same number of blades. The wet scrubber with 16 blades was found to have the best dust removal efficiency at a water intake level of 1.35 m3/h. Its total dust and respirable dust removal efficiency reached 96.81% and 95.59%, respectively. The air volume was 200.4 m3/min, and the average pressure drop was determined to be 169.4 Pa. In addition, when the wet scrubber with 16 blades was applied in a coal preparation plant in China's Shanxi Province, it was observed that the total dust concentration had fallen below 8.1 mg/m3, and the respirable dust concentration had fallen below 5.9 mg/m3. Therefore, the results obtained in this research investigation provide important references for the use of wet scrubbers to improve coal production environmental conditions. [ABSTRACT FROM AUTHOR]

Aeolian desertification, a serious degradation of soil and vegetation, is one of the most important issues in arid and semi-arid regions in terms of society/economy and environment. However, there still remains problematic on the study of climate change and its impact on aeolian desertification in the such region. To reverse aeolian desertified land (ADL), it is necessary to identify the causes of ADL. The paper uses meteorological data to characterize climate change and its impact on ADL during 1970–2015 with the method of geostatistics, and the results showed that the climate tended to be warmer and drier. The linear trend rates of annual mean temperature for the whole year (WY), winter half year (WHY), and summer half year (SHY) were 0.24 °C (10 a)−1, 0.25 °C (10 a)−1, and 0.18 °C (10 a)−1, respectively. The linear trend rates of average precipitation were − 8.29 mm (10 a)−1, 2.69 mm (10 a)−1, and − 8.27 mm (10 a)−1, respectively. Rising temperatures in WY, WHY, and SHY lead to increase topsoil evaporation and may trigger ADL development. However, the decreasing precipitation in SHY weakened soil erosion, and the increasing precipitation with a rate of 0.26 mm a−1 in WHY improved the soil moisture content. Therefore, our results show that climatic change has a relatively high sensitivity, especially in WHY, to the expansion or reversal of ADL in semi-arid regions. [ABSTRACT FROM AUTHOR]

The rapid development of coal industry in Shanxi province in China has important effects on its economic development. A large amount of money has been invested into the coal industry and other related industries during the recent years. However, research on the investment effect of Shanxi's coal industry was rare. In order to analyze the investment effect of coal industry, based on the crowding-out effect model, cointegration test, and the data available in Shanxi Statistical Yearbooks, this paper calculates the effect between coal industry investment and other 17 industry investment. The results show that the investment of coal industry produces crowding-out effect on food industry, building materials industry, and machinery industry. Increasing 1% of the coal industry investment can reduce 0.25% of the food industry investment, or 0.6% of building materials industry investment, or 0.52% of the machinery industry investment, which implies that Shanxi province should adjust coal industrial structure, promote the balance development of coal industry and other industries, so as to promote its economic growth. [ABSTRACT FROM AUTHOR]

Economic development is the core driver of carbon emissions. It is of great significance to clarify the linkage relationship between economic development and carbon emissions. Therefore, the static and dynamic relationship between carbon emissions and economic development in Shanxi Province is analyzed by using the VAR model and decoupling model combined with data from 2001 to 2020. The results show that economic development and carbon emissions in Shanxi Province have mainly presented a weak decoupling state in the past 20 years, but the decoupling state is gradually increasing. Meanwhile, carbon emissions and economic development constitute a bidirectional cycle dynamic system. The impact of economic development on itself and carbon emissions account for 60% and 40%, respectively, while the impact of carbon emissions on itself and economic development accounts for 71% and 29%, respectively. This study provides a relevant theoretical basis for solving the problem of excessive dependence on energy consumption in economic development. [ABSTRACT FROM AUTHOR]

Based on the accident causation theory, the mechanism and inducement of construction safety risk in mining enterprises are clarified. The safety risk system of mining enterprises is divided into five subsystems: personnel, material equipment, technology, environment, and management by rough set theory. The comprehensive weight of each risk factor is calculated by network analytic hierarchy process and fuzzy comprehensive evaluation method. Taking a mine in Shanxi Province as the research object, the causal traceability diagram and stock flow diagram of the risk system of mining enterprises are constructed by means of system dynamics model. The influence of various risk factors of the mine on the overall safety risk management level of the enterprise is simulated, and the numerical value of key personnel influence factors is adjusted. The sensitivity changes of safety productivity and safety risk management level of mining enterprises in different situations are analyzed. The results show that: (1) the management and personnel subsystem has the greatest impact on the safety risk management of mining enterprises, followed by the technology, material equipment, and environment subsystem. (2) Increasing safety input can improve the safety level and reduce the expected safety value time, otherwise it will reduce the safety level and delay the expected safety value time. (3) Further simulation of the personnel subsystem, it is found that the factors affecting the safety level of mining enterprises contain six factors, namely, the technical level of construction personnel, the management level of manager, the conduct code of construction personnel, the safety consciousness of practitioners, the basic quality of construction personnel, and the physical and mental state of construction personnel. (4) The conversion rate of personnel safety input to manager's management level and the safety consciousness of practitioners presents a steep decline—slow rise—gradually steady development trend, which mainly because the benefits of safety input have certain time delay and lag. [ABSTRACT FROM AUTHOR]

Shanxi Debao has affluent coalbed methane (CBM) reservoir in China. Understanding its characteristics, especially the diffusion characteristics of natural gas in the coal seam, is the key data of CBM development in this block. In this paper, a method of measuring the gas diffusion coefficient of coal and rock by the adsorption method is proposed by using the experimental method. The calculation model for calculating the gas diffusion coefficient of coal and rock is established according to the adsorption amount, and the diffusion correlation coefficient under different pressures, different water saturation and the different temperatures is established. The results show that it is feasible to calculate the diffusion coefficient of the gas in coal and rock according to the adsorption capacity of coal and rock. With the increase in the pressure, the diffusion coefficient increases, the water saturation increases. While the diffusion coefficient decreases, the temperature increases, and the diffusion coefficient increases. The results calculated by the model could provide guidance for the future development of Debao coalbed methane reservoir in Shanxi Province, China. [ABSTRACT FROM AUTHOR]

Landslides, collapses and cracks are the main types of geological hazards, which threaten the safety of human life and property at all times. In emergency surveying and mapping, it is time-consuming and laborious to use the method of field artificial investigation and recognition and using satellite image to identify ground hazards, there are some problems, such as time lag, low resolution, and difficult to select the map on demand. In this paper, a 10 cm per pixel resolution photogrammetry of a geological hazard -prone area of Taohuagou, Shanxi Province, China is carried out by DJ 4 UAV. The digital orthophoto model (DOM), digital surface model (DSM) and three-dimensional point cloud model (3 DPCM) are generated in this region. The method of visual interpretation of cracks based on DOM (as main) -3DPCM (as auxiliary) and landslide and collapse based on 3DPCM (as main) — DOM and DSM (as auxiliary) are proposed. Based on the low altitude remote sensing image of UAV, the shape characteristics, geological characteristics and distribution of the identified hazards are analyzed. The results show that using UAV low altitude remote sensing image, the method of combination of main and auxiliary data can quickly and accurately identify landslide, collapse and crack, the accuracy of crack identification is 93%, and the accuracy of landslide and collapse identification is 100%. It mainly occurs in silty clay and mudstone geology and is greatly affected by slope foot excavation. This study can play a great role in the recognition of sudden hazards by low altitude remote sensing images of UAV. [ABSTRACT FROM AUTHOR]

The Loess Plateau of China is the most concentrated and largest loess area on Earth. Shanxi Province lies in the eastern margin of the Loess Plateau and is one of the regions with the worst serious soil erosion and most fragile ecological environment in the world. On March 15, 2019, a landslide hit Xiangning County in Shanxi Province in northern China and resulted in heavy casualties. This paper mainly gives an introduction about the catastrophe, causes, and related emergency response. [ABSTRACT FROM AUTHOR]

In March 15, 2019, a small-scale loess landslide occurred at Zaoling, Shanxi Province, China, destroying several buildings and killing 20 people. Based on a digital orthophoto map (DOM) and digital elevation model (DEM) derived from Dajiang Pro4 UAV aerial images, coupled with field investigations, this paper describes the geometric features of this slope failure and analyzes its possible inducing factors. Results show that this landslide has a circular chair shape with a sliding direction of 355°. The total projected area of the landslide is 11,800 m2, in which the source is 9880 m2, and the main scarp is 1995 m2. The volume of the source material and loose deposit debris are about 10 × 104 m3 and 12 × 104 m3, respectively. Our research suggests that the inducing factors of this event may include the low strength and structure of the loess under a wet condition, special landforms of the slope, and human activities such as water discharge from a nearby bath center building and coal mining. [ABSTRACT FROM AUTHOR]

The excessive utilization of cesarean section (CS) has become a global concern, given the potential short-term and long-term detrimental effects for mothers and infants. Worldwide, the rate of CS continues to rise, but efforts to curtail unnecessary CS procedures have yielded limited success. By combining data from three resources, this study aims to estimate the effects of anti-corruption campaigns under the Xi administration on CS rates. We focus on Shanxi Province, a major coal-producing province in north-central China, with notoriety for the collusion between local politicians and business elites. Using the data from the China Corruption Investigation Dataset and data from publicly listed firms between 2013 and 2016, we found that anti-corruption campaigns significantly changed the social environment as firms' business entertainment spending experienced substantial reductions. Using discharge records from 137 public hospitals, we adopted an instrumental variable (IV) approach and found that the anti-corruption campaigns led to significant reductions in unnecessary CS rates. The reductions are bigger among patients with second or later deliveries. We also find that the anti-corruption campaigns changed behaviors of attending and resident physicians. Our results provide insights into strategies to reduce corrupt practices within the healthcare sector and implementing interventions to minimize the occurrence of CS among healthy women and newborns. [ABSTRACT FROM AUTHOR]

Jinci Spring is one of the most famous karst spring in Northern China and is the main drinking and irrigation water source of Taiyuan city, Shanxi Province. It has special significance in terms of humanities and water resources. Because of the continuous over-exploitation of groundwater, the water level of groundwater has been decreased significantly. The flow of Jinci Spring has decreased year by year since the 1970s, and in 1994 it cut off completely. The flow cutoff has brought huge losses to the local economy and negatively impacted the ecological environment. From the hydrogeological conditions of Jinci Spring area to study, the dynamic change in karst groundwater level will provide a basis for the protection and rational exploitation of karst water in the spring area. The previous research on Jinci Spring area was limited to the spring flow and water level changes, lack of analysis to the overall spring area and the decay process of spring flow. This paper takes the overall spring area as research object. According to groundwater level data over 1961–2012, the period is divided into two phases of decline and recovery. Human activities in the region and corresponding groundwater evolution at various stages were systematically analyzed, and the reservoir capacity was calculated for each period of decline. The results show that the average reservoir capacity decreased from 920 (1954–1960) to 116 (1961–1977) to 31 (1978–1994) million m3. The important effect of "Water Resumption" project on groundwater in the area during the remediation period was also analyzed. In the light of observed increases in groundwater level during this stage, the project has a notably positive effect. [ABSTRACT FROM AUTHOR]

The paper investigates groundwater inflow into a longwall working face of the Xiegou Coal Mine located in the northwest of the Shanxi province, China. Three modelling approaches, including basic Darcy modelling, full poroelastic modelling using Biot's classical theory, and the full Biot poroelastic modelling that takes into account permeability alterations of the coal seam and strata due to alterations in the mining-induced stress state, are used to estimate the fluid flow into the underground longwall coal mine as the excavation progresses. Based on plausible assumptions of hydrogeological structure, boundary conditions and mining conditions, a three-dimensional finite element model of the simplified geological setting is developed using the COMSOL software. The permeability changes in both the strata and the coal seam due to the mining are associated with the mining-induced stress changes and water pressure, and the correlation between them accords with the exponential relationship. The differences in the modelling results of three approaches were analyzed, and the simulation results are compared with the field measurements. [ABSTRACT FROM AUTHOR]

Special attention was drawn to the heavy metals contained in coal, due to it will cause harm to the environment during coal processing and utilization. The sequential chemical extraction of Shanxi coal (SX coal) and Wulanchabu coal (WLCB coal) was carried out to investigate the distribution of arsenic (As) in coals. Two raw coals were pyrolyzed at 300–900 °C in horizontal tubular furnace to investigate release behavior of As during pyrolysis process. The results showed that As in SX coal mainly existed in aluminosilicate-bound state (40.25%) and disulfide-bound state (32.51%), followed by carbonate-bound state and organic-bound state. The As in WLCB coal mainly existed in aluminosilicate-bound state (62.50%), followed by disulfide-bound state (19.10%). The As contents of water-soluble, ion-exchange and residue states in the two coals were less than others. The modes of occurrence of As had great influence on its volatilization behavior. As in organic part was easy to volatilize at low temperature. Sulfide-bound state would escape with the decomposition of pyrite. Because SX coal contained higher organic state and sulfide-bound state, the volatilization rate of As was higher than WLCB coal at any temperature, and the difference was more obvious at low temperature. In addition, FactSage simulation value was basically consistent with the experimental value. [ABSTRACT FROM AUTHOR]

Seven pieces of gold foils for surface decoration of the lacquerware were excavated in the late Western Han Dynasty tomb in the area of the Jin Yang (晋阳) Ancient City site in Taiyuan (太原), Shanxi (山西), China. These gold foils portray images of the carriage, the leopard, the tigers, the ox, and the dancer with fluttering sleeves, etc., with black lines outlining the contours and red paint depicting vivid patterns. The study used Stereo Microscopes, Metallurgical Microscopy, Environmental Scanning Electron Microscopy coupled with Energy-Dispersive X-ray Spectroscopy (ESEM-EDS), and Laser Raman Spectroscopy (LRS) to analyse the thickness of the gold foils, the alloy composition, the composition of the paint and other surface attachments, and investigate the manufacturing process. As the results show, the thickness of the gold foils is about 26 μm. The composition is a gold-silver alloy with about 96% Au/(Au + Ag) (surface) and 98% Au/(Au + Ag) (cross-section). The metallurgical observation shows that the gold foils underwent heating and forging. The black lines on the front side are Chinese ink lines, with cracking and peeling phenomenon, and parallel polishing lines can be seen at the peeling places, while no polishing lines are observed on the back side. Some red paint made of cinnabar is above the black lines, and the binder is organic. Some lacquer residues are found on the back. According to the results of the study, the manufacturing process of the gold foils applied on the lacquerware is as follows: the gold foils are obtained by heating and forging, the front sides of the gold foils are polished, the shapes are carved out, and the gold foils are pasted on the lacquerware when the lacquerware's surface is not yet dry. The gold foils are painted with black Chinese ink and red cinnabar pigment. The study's results offer important references for understanding the manufacturing craft of the gold foils applied on the lacquerware in the late Western Han Dynasty of China and guide the conservation of the lacquerware decorated with painted gold foils. [ABSTRACT FROM AUTHOR]