Search

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]

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]

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]

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]

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]

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]

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]

Objective: Depression is a serious public health problem in coal miners that not only affects their physical health and quality of life but also leads to a decline in productivity and a high economic burden. The primary purpose of the current study was to evaluate the psychometric properties of the Center for Epidemiological Studies-Depression (CES-D) scale. The secondary aim was to investigate the prevalence of depression among coal miners in Shanxi Province, China. Methods: Coal miners (3314, 86.60% men) were selected and evaluated with the CES-D from February 1 to April 30, 2021. The factor structure of the CES-D scale was analyzed using exploratory (EFA) and confirmatory factor analyses (CFA). Cronbach's α and McDonald's Ω were calculated to evaluate the internal consistency of the CES-D. Results: The prevalence of depressive symptoms among coal miners was 54.68%. The EFA results suggested that a three-factor structure model with 18 items was the best fit, including Depressed Affect, Interpersonal Problems, and Retarded Activity, which accounted for 54.37% of the total variance. The CFA indicated that this factor structure fit the data adequately (χ2 = 217.408, df = 87, CMIN/DF = 2.49, RMSEA = 0.055, CFI = 0.969, TLI = 0.962, IFI = 0.969). Additionally, the overall Cronbach's α and McDonald's Ω of the CES-D were 0.949 and 0.950, respectively. The CES-D had an excellent reliability and validity in the present sample of coal miners. Conclusion: The three-factor structure of CES-D with 18 items can best fit the data from coal miners living in Shanxi Province. The reliability and validity of the CES-D were in line with the requirements of psychometric test. The scale is suitable for screening depression among coal miners in China. [ABSTRACT FROM AUTHOR]

Scientific estimation and dynamic monitoring of CO2 emission trends are an important basis for formulating regional differentiated carbon reduction strategies. Using the integrated nighttime light data, this study estimated CO2 emissions in the Yellow River Basin (YRB) and Yangtze River Basin (YZRB) and discussed the similarities and differences of the spatial distribution of CO2 emissions for the two river basins. The results showed that: (1) The CO2 emissions in the two basins continued to rise, but the growth rate decreased from 2000 to 2018, showing an overall convergence trend, but have not yet reached carbon peak. (2) The high emission and high agglomeration areas were located in Shandong Province in the downstream of the YRB, Shanxi, Shaanxi and Inner Mongolia in the midstream and upstream, and the Yangtze River Delta (YRD). (3) Compared with the YRB, the growth rate of CO2 emissions in the YZRB is slower, and the growth rate declines greatly. In the YRB, it had higher CO2 emissions amount, wider area of high carbon emissions and more obvious spatial agglomeration than that in the YZRB. (4) According to CO2 emissions and economic development level, 220 cities of the two river basins were classified three types: low CO2–low development, high CO2–low development and high CO2–high development. [ABSTRACT FROM AUTHOR]

Changzhi Guanyin Hall, a folk temple from the Ming Dynasty, embodies the essence of the 'unity of the three religions' philosophy, centred around Guanyin Bodhisattva. Over 500 sculptures reside within a modest 70 m2 space, encompassing representations from Confucianism, Buddhism and Taoism. Ranging from a towering 2 m to a mere 10 cm, these sculptures depict an array of characters and mythological scenes, bestowing considerable importance upon the painted sculptures of Guanyin Hall. Varying degrees of deterioration have affected these sculptures due to the passage of time and suboptimal preservation conditions, highlighting the imperative need for meticulous restoration efforts. However, the absence of comprehensive analyses pertaining to the production process of Guanyin Hall sculptures has hindered the restoration groundwork. This study focuses on fallen hanging sculptures and debris, encompassing intact sculptures, clay fragments, wooden sticks, plant fibres, wires and pigments. Employing a series of techniques, including X-ray photography, microscopic analysis, mineral analysis (MLA), laser particle size testing, ion chromatography, X-ray fluorescence spectroscopy (XRF), X-ray diffractometer (XRD) and energy dispersive spectrometer (SEM–EDS) analysis, this research characterises the constituent materials used in crafting these artifacts. Instead of a full-body skeleton, the findings reveal that the small hanging sculpture is supported by delicate wires that hold specific areas, such as the arms and the gown hems. The hanging sculptures are made from a single type of clay and are reinforced with either mulberry bast or wheat straw fibres. A Pinaceae wood stick affixes the head to the body, and the sculpture is then suspended on the wall through nails inserted into the feet. The moulded clay undergoes a sequence of carving, drying and polishing and is coated with a white ash layer before receiving intricate painting. Mineral pigments, including cinnabar, red lead, iron red, cerussite, atacamite, brochantite and azurite, adorn the surface of the sculptures, with gold foil embellishing the golden elements. The intricate artisanry and multifaceted material composition of Guanyin Hall's painted sculptures render them unparalleled artistic treasures, not solely within Shanxi but across the entire nation. Furthermore, this study establishes a dependable foundation for conservation and restoration endeavours. [ABSTRACT FROM AUTHOR]