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To solve the problem of the insufficient driving force and low adoption rate of conservation tillage adoption and to enhance the effect of industrial organization in influencing technology diffusion, this paper explored the relationship and the mechanism of perceived organizational support and inter-temporal choice in the adoption of conservation tillage by using micro-research data from 725 melon farmers in the Shaanxi and Shanxi provinces in China and by applying the experimental economics method to obtain the inter-temporal choices of the farmers. This paper also analyzed farmers' risk preferences' moderating effect on the relationship between inter-temporal choice and conservation tillage. Additionally, it examined the impact of perceived organizational support on the differentiation of different conservation tillage technologies. The study found that perceived organizational support significantly contributes to adopting zero tillage and minimum tillage, and water-saving irrigation. Perceived organizational support was not conducive to farmers' adoption of furrow and ridge tillage. The impact of perceived organizational support on technology adoption is heterogeneous, depending on the differences in the size of the family's cultivated land. The inter-temporal choice of farmers significantly impedes the adoption of conservation tillage. The increase in risk preference helps alleviate the hindering effect of inter-temporal choice on farmers' adoption of conservation tillage. Perceived organizational support can promote the adoption of conservation tillage by reducing farmers' inter-temporal choices. Inter-temporal choice is an essential mechanism by which perceived organizational support affects the adoption of conservation tillage. Compared with the existing studies, this paper incorporates the technology-attribute-induced inter-temporal choice of farmers into the impact analysis framework and considers the relationship between perceived organizational support, inter-temporal choice, and the adoption of conservation tillage and the mechanism of its action. The findings of the study provide a theoretical basis for the enrichment of incentive mechanisms for the adoption of conservation tillage, which is of great significance for the improvement of the tool for the integration of small farmers in developing countries into the industrial activities of the new agricultural business central bodies and for promoting the diffusion of conservation tillage in agriculture. [ABSTRACT FROM AUTHOR]

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]

Accurate medium- and long-term runoff prediction models play crucial guiding roles in regional water resources planning and management. However, due to the significant variation in and limited amount of annual runoff sequence samples, it is difficult for the conventional machine learning models to capture its features, resulting in inadequate prediction accuracy. In response to the difficulties in leveraging the advantages of machine learning models and limited prediction accuracy in annual runoff forecasting, firstly, the variational mode decomposition (VMD) method is adopted to decompose the annual runoff series into multiple intrinsic mode function (IMF) components and residual sequences, and the spectral clustering (SC) algorithm is applied to classify and reconstruct each IMF. Secondly, an annual runoff prediction model based on the adaptive particle swarm optimization–long short-term memory network (APSO-LSTM) model is constructed. Finally, with the basis of the APSO-LSTM model, the decomposed and clustered IMFs are predicted separately, and the predicted results are integrated to obtain the ultimate annual runoff forecast results. By decomposing and clustering the annual runoff series, the non-stationarity and complexity of the series have been reduced effectively, and the endpoint effect of modal decomposition has been effectively suppressed. Ultimately, the expected improvement in the prediction accuracy of the annual runoff series based on machine learning models is achieved. Four hydrological stations along the upper reaches of the Fen River in Shanxi Province, China, are studied utilizing the method proposed in this paper, and the results are compared with those obtained from other methods. The results show that the method proposed in this article is significantly superior to other methods. Compared with the APSO-LSTM model and the APSO-LSTM model based on processed annual runoff sequences by single VMD or Wavelet Packet Decomposition (WPD), the method proposed in this paper reduces the RMSE by 40.95–80.28%, 25.26–57.04%, and 15.49–40.14%, and the MAE by 24.46–80.53%, 16.50–59.30%, and 16.58–41.80%, in annual runoff prediction, respectively. The research has important reference significance for annual runoff prediction and hydrological prediction in areas with data scarcity. [ABSTRACT FROM AUTHOR]

At present, China's equipment manufacturing industry and producer service industry are gradually ushered in the leapfrog high-quality development of the rising period. It is particularly important how Shanxi, as the vanguard of the transformation and development, positively responds to the national call to break the shackles of the current integrated development of equipment manufacturing and producer services, for Shanxi Province and even the country's future industrial integration, transformation, and upgrading to accumulate "Shanxi Experience." Therefore, this paper measures and analyzes the integration level of equipment manufacturing and production services between 2012 and 2017 using the input-output method. Then, by constructingthe model of the factors influencing the integration of Shanxi's equipment manufacturing industry and producer service industry, selecting the relevant indicators and bringing in the relevant data from 2009 to 2019, by using the principal component regression analysis method, and thus clarifies the main factors that influence the convergence of the equipment manufacturing industry and production service industry in Shanxi. Finally, this paper has provided targeted countermeasures and suggestions to further promote the integration of the two industries in Shanxi Province. [ABSTRACT FROM AUTHOR]

China has undergone an unprecedented period of rapid urbanization in recent decades, resulting in a host of urban challenges. In response to these issues, urban renewal has emerged as a proactive policy approach to address urban problems. Urban regeneration is a multifaceted and multi-level endeavor that involves numerous stakeholders. Investigating the formulation of urban regeneration strategies in light of these stakeholders is pivotal for resolving societal issues and enhancing the comprehensiveness and feasibility of urban regeneration strategies. This paper employs Shuozhou City as a case study, using a combination of stakeholder theory and social network analysis to identify stakeholders in the context of urban renewal. It conducts a comprehensive stakeholder analysis, explores the social network structure among these stakeholders, and constructs an "impact-interest" matrix to capture their roles and interests. Based on this matrix, it proceeds to propose a range of dimension- specific urban renewal strategies for Shuozhou City.I n conclusion, leveraging this matrix, the paper outlines specific strategies tailored to the urban renewal context in Shuozhou, exemplifying the potential for a more effective approach to addressing urban challenges. [ABSTRACT FROM AUTHOR]

This paper focuses on the disposal of iron tailings sand (ITS) and recycled aggregate of inorganic (RAI) and proposed the "ITS plus RAI" solid waste treatment methods, which uses ITS and RAI as a new base course material to replace new aggregates by 100% to apply in the pavement renovation project of national and provincial roads in Linfen city, Shanxi Province. In this paper, the compressive strength characteristic of recycled mixture with different ratios is studied for the dual waste treatment methods, and the influence factors are analyzed by multiple regression analysis. Results show that the strength of the recycled mixture composed of a high content of ITS (the mass ratio to RAI exceeds 60 : 40) ups to 7 MPa, which can meet the pavement requirements of 7d unconfined compressive strength of inorganic stabilized base material under various traffic load conditions. The factors affecting the strength of recycled materials include the content of various components, while the particle size of iron tailings sand is the most significant influence factor. Therefore, the proportion of iron tailings sand in the recycled mixture can be further improved by screening coarse iron tailings sand so as to maximize the content of iron tailings sand, which will lead to an excellent engineering value. [ABSTRACT FROM AUTHOR]

The food crisis has increased demand for agricultural resources due to various factors such as extreme weather, energy crises, and conflicts. A solar greenhouse enables counter-seasonal winter cultivation due to its thermal insulation, thus alleviating the food crisis. The root temperature is of critical importance, although the mechanism of soil thermal environment change remains uncertain. This paper presents a comprehensive study of the soil thermal environment of a solar greenhouse in Jinzhong City, Shanxi Province, employing a variety of analytical techniques, including theoretical, experimental, and numerical simulation, and deep learning modelling. The results of this study demonstrate the following: During the overwintering period, the thermal environment of the solar greenhouse floor was divided into a low-temperature zone, a constant-temperature zone, and a high-temperature zone; the distance between the low-temperature boundary and the southern foot was 2.6 m. The lowest temperature in the low-temperature zone was 11.06 °C and the highest was 19.05 °C. The floor in the low-temperature zone had to be heated; the lowest value of the constant-temperature zone was 18.29 °C, without heating. The minimum distance between the area of high temperature and the southern foot of the solar greenhouse was 8 m and the lowest temperature reading was 19.29 °C. The indoor soil temperature tended to stabilise at a depth of 45 cm, and the lowest temperature reading at a horizontal distance of 1400 mm from the south foot was 19.5 °C. The Fluent and LSTM models fitted well and the models can be used to help control soil temperature during overwintering in extreme climates. The research can provide theoretical and data support for the crop areas and the heating of pipelines in the solar greenhouse. [ABSTRACT FROM AUTHOR]

Carbon storage services play an important role in maintaining ecosystem stability. Land use/cover change (LUCC) is the main factor leading to changes in ecosystem carbon storage. Understanding the impact of LUCC on regional carbon storage changes is crucial for protecting regional ecosystems and promoting sustainable socio-economic development. This paper selects Shanxi province as the study area and explores the spatial and temporal evolution characteristics of carbon storage in Shanxi province based on the InVEST model and univariate spatial autocorrelation. The results show that the total carbon storage in Shanxi Province in 2000, 2010, and 2020 is 513.51 × 104 t C, 513.46 × 104 t C, and 509.29 × 104 t C, respectively. High carbon storage areas are distributed in forest and grassland land types, while low carbon storage areas are widely distributed in building land in urban metropolitan areas. Shanxi Province is mainly dominated by farmland, which has decreased by 3448.60 km2 in the past 20 years. Grassland has decreased by 1588.31 km2 and the area of building land has increased by 4205.73 km2. Due to the influence of carbon conversion among different land use types, the total carbon storage loss of Shanxi Province in the past 20 years was 4.21 × 104 t C. The transfer of farmland resulted in an increase in carbon stock of 14.46 × 104 t C. The transfer of grassland resulted in an increase of 17.15 × 104 t C, while the transfer of forest resulted in a decrease of 41.44 × 104 t C. The increase in land use types with low carbon density and the decrease in land use types with high carbon density led to the decrease in carbon storage in Shanxi Province. Furthermore, social factors were more likely to influence the carbon storage than natural factors, and the influence of social factors was often negative. On this basis, regional development countermeasures were proposed for the current situation of carbon storage in Shanxi Province and provide a scientific basis for Shanxi Province to achieve the carbon neutrality target. [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]

Encouraging the use of conservation tillage technology is a highly effective approach to safeguarding soil health, improving the environment, and promoting sustainable agricultural development. With the mounting concerns surrounding climate change, developing conservation tillage methods that facilitate sustainable agricultural growth has become an imperative both in China and around the world. While it is widely recognized that adapting to climate change is crucial in agriculture, there is limited research on evaluating the risks, discovering resilience, measuring farmers' perceptions on climate change, and exploring how tillage technology can be adjusted in the context of small-scale farming in China to foster sustainable development. Using research data from smallholder farmers in the Shaanxi and Shanxi provinces of China, this paper aims to explore the impact of climate change perceptions on farmers' adoption of conservation tillage technologies based on an ordered Probit model. We found that farmers tend to refrain from embracing conservation tillage technology due to the presence of unclear and conflicting perceptions regarding climate change. Focus on short-term profitability and inadequate preparation hinder them from prioritizing adaptation. We recognized several measures that could help farmers adapt and thrive within the agricultural sector. Furthermore, we have validated the need for self-system moderation in promoting farmers' adoption of conservation tillage technology. By utilizing such tools and resources, farmers can comprehend the gravity of climate change's impact on agricultural productivity and, more importantly, channel their efforts towards fortifying resilience to extreme weather conditions and long-term climate risks, thus fortifying agricultural sustainability. [ABSTRACT FROM AUTHOR]

Since the "double carbon" target was proposed in 2020, emissions reduction has become the focus of the Chinese government's work. Industrial development is a crucial factor contributing to the increase in carbon emissions. Therefore, implementing carbon reduction in the industrial sector is an important part of China's goal of "double carbon." In this context, this paper uses a three‐stage data envelopment analysis model to calculate the green total factor productivity (GTFP) of 18 industry sectors in Shanxi Province. The results show that: (1) the external environment has influence on the GTFP of energy revolution reform pilot area industrial sectors, and the efficiency value of two industries is overestimated before excluding environmental factors; (2) the industry difference of GTFP is significant, among which pharmaceutical manufacturing industry has the greatest promoting effect on GTFP, and ferrous metal mining and dressing industry has the greatest inhibiting effect on GTFP; (3) there is a serious redundancy in R&D investment of energy revolution reform pilot area in China, and only six industries belong to zero redundancy. (4) To reflect the GTFP of various industrial sectors more clearly, this paper divides four industries: "Double‐high" industry, "High‐low" industry, "Low‐high" industry, and "Double‐low" industry. [ABSTRACT FROM AUTHOR]

Changes in regional policy could affect the development and sustainability of small businesses, which react to external conditions. The main goal of this paper is to propose a regional system of indicators of an assessment of the business environment. The proposed system of indicators reflects the specifics of regions that have undergone sectoral change. The structure of the paper follows a top-down approach, first describing the national and then the regional context of the chosen, somewhat similar, regions within the selected countries. The paper first describes current analytical results from an overall national evaluation of two different countries (Czechia and China) with selected structurally changed regions. Lastly, it proposes a system of indicators. The systematic part of the paper contains a practical case study from one Czech region to illustrate the examined problems and how to connect business needs with regional policy issues. According to the findings, when an entrepreneur is in daily contact with the local government, the quality of the business environment is very important for each of them to exploit a comparative advantage from the market. Proposals are based on a field survey study of 215 entrepreneurs, conducted in the selected Moravian-Silesian region that has undergone sectoral change similar to Shanxi Province today. The results could be applicable as an example of good practice by means of which to evaluate other regions in the same situation. [ABSTRACT FROM AUTHOR]

As an important factor in the creation and growth of new enterprises, social entrepreneurship and new enterprise performance have attracted more and more attention from scholars in recent years. This research analyzes the network relationship of new companies on the basis of existing entrepreneurial network research. This paper proposes social entrepreneurial capabilities and new company performance based on the SOM neural network algorithm to solve these problems and then establishes entrepreneurial networks, organizational learning, and new business performance models. The method of this paper is to study the SOM neural network algorithm and then establish the entrepreneurial ability and enterprise performance evaluation system. The function of these methods is to put forward the meaning and research of venture capital. It also defines the meaning and research of innovation capabilities based on innovation theory, ensuring the scientific nature of the evaluation indicators, evaluation standards, and evaluation processes of innovative enterprises. In this survey, this paper conducted a field survey in Shanxi Province, China, and analyzed the internal impact of the network of social entrepreneurship and new companies on corporate performance. The survey results show that the value of the correlation β between entrepreneurial orientation and entrepreneurial environment dynamics is 0.167 (P < 0.05). This shows that improving the entrepreneurial environment and enhancing social entrepreneurial capabilities have a positive impact on corporate performance. [ABSTRACT FROM AUTHOR]

China stands out as a major contributor to anthropogenic methane (CH 4) emissions, with coal mine methane (CMM) playing a crucial role. To control and reduce CH 4 emissions, China has made a dedicated commitment and formulated an ambitious mitigation plan. To verify the progress made, the consistent acquisition of independent CH 4 emission data is required. This paper aims to implement a wind-assigned anomaly method for the precise determination of regional-scale CMM emissions within the coal-rich Shanxi province. We use the TROPOspheric Monitoring Instrument (TROPOMI) CH 4 observations from May 2018 to May 2023, coupled with ERA5 wind and a bottom-up inventory dataset based on the IPCC (Intergovernmental Panel on Climate Change) Tier 2 approach covering the Changzhi, Jincheng, and Yangquan regions of the Shanxi province. The derived emission strengths are 8.4 × 10 26 molec. s -1 (0.706 Tg yr -1 , ± 25 %), 1.4 × 10 27 molec. s -1 (1.176 Tg yr -1 , ± 20 %), and 4.9 × 10 26 molec. s -1 (0.412 Tg yr -1 , ± 21 %), respectively. Our results exhibit biases of - 18 %, 8 %, and 14 %, respectively, when compared to the IPCC Tier 2 bottom-up inventory. Larger discrepancies are found when comparing the estimates to the Copernicus Atmosphere Monitoring Service global anthropogenic emissions (CAMS-GLOB-ANT) and Emissions Database for Global Atmospheric Research (EDGARv7.0) inventories (64 %–176 %), suggesting that the two inventories may be overestimating CH 4 emissions from the studied coal mining regions. Our estimates provide a comprehensive characterization of the regions within the Shanxi province, contribute to the validation of emission inventories, and provide additional insights into CMM emission mitigation. [ABSTRACT FROM AUTHOR]

LuTan-1 (LT-1) satellite constellation is used to conduct surface deformation monitoring. Following the successful launch of two satellites, we began to use the independently developed LandSAR software for differential interferometric data processing and application at the beginning of 2022. In this paper, we tested the LandSAR software by assessing the DInSAR and stacking modules. We used 21 LT-1 single look complex (SLC) images from December 2022 to May 2023 to conduct DInSAR and stacking processing of Datong City, Shanxi Province. DInSAR revealed more subsidence funnels and larger relative deformation values compared to stacking. We tested the DInSAR technology with different parameter combination. Results show that multi-looking factor is the most important to detect the deformation details because of the phase gradient limitation of DInSAR. Compared multi-looking ratios of 2×2 and 4×4, the subsiding funnels that were detected decreased from 60 to 47. After deep testing and assessment, we found that the linear model used by stacking affects the result severely, meaning that most of the subsidence of coal mines were not linear. Stacking only found 32 subsidence funnels which were active coal mines during our observation time. The test result show that LandSAR was compatible for DInSAR and stacking. And it is useful to observe linear and nonlinear deformation in the coal mine regions. [ABSTRACT FROM AUTHOR]

Rainfall erosivity, which signifies the inherent susceptibility of soil erosion induced by precipitation, plays a fundamental role in formulating a comprehensive soil loss equation (RUSLE). It stands as a crucial determinant among the foundational factors considered in a comprehensive soil loss equation's establishment. Nonetheless, the prediction and quantification of future alterations in rainfall erosivity under the influence of global warming have been relatively limited. In this study, climate change was widely evaluated and 10 preferred global climate models in the Loess Plateau were selected by using the data sets of 27 models simulating climate change and the CN05.1 data set provided by the latest CMIP6. The monthly precipitation forecast data were obtained by using the delta downscaling method. Combined with trend analysis, significance test, and coefficient of variation, the annual rainfall erosivity during 1961–2100 under four SSP scenarios was analyzed and predicted. Among the 27 GCM models used in this paper, the most suitable climate models for simulating monthly precipitation in the Loess Plateau were CMCC-CM2-SR5, CMCC-ESM2, TaiESM1, EC-Earth3, EC-Earth-Veg-LR, INM-CM4-8, CAS-ESM2-0, EC-Earth-Veg, ACCESS-ESM1-5, and IPSL-CM6A-LR. In comparison to the base period (1961–1990), during the historical period (1961–2014), the average annual rainfall erosivity on the Loess Plateau amounted to 1259.64 MJ·mm·hm−2·h−1·a−1, showing an insignificant downward trend. In the northwest of Ningxia, Yulin City and Yanan City showed a significant upward trend. In the future period (2015–2100), the annual rainfall erosivity continues to constantly change and increase. The potential average increase in rainfall erosivity is about 13.48–25.86%. In terms of spatial distribution, most areas showed an increasing trend. Among these regions, the majority of encompassed areas within Shanxi Province, central Shaanxi, and Inner Mongolia increased greatly, which was not conducive to soil and water conservation and ecological environment construction. This study offers a scientific reference for the projected future erosivity characteristics of the Loess Plateau. [ABSTRACT FROM AUTHOR]

Vehicle path recognition is one of the key methods used in urban traffic research, such as traffic flow characteristics analysis. Automatic vehicle identification (AVI) is often used for vehicle path recognition and is suitable for mixed traffic flow with connected automated vehicles (CAVs). However, there still remain issues in overcoming the difficulty of vehicle path identification caused by the discontinuity of AVI data and solving the problem of low precision of AVI application. To model the vehicle path, this paper selects the AVI system of Yicheng Town, Linfen City, Shanxi Province, as a test bed. The travel modes of private cars and taxis are discussed, and the quantified indicators of the model are determined. By combining the analytic hierarchy process (AHP) with the entropy weight method (EWM) to get the weights of the indicators, the path recognition model under incomplete AVI data is proposed. Finally, based on the path recognition model proposed in this paper, case studies are carried out for the private car and taxi path recognition, respectively. The validity of the path identification through practical studies and the effect of the number of missing nodes of AVI equipment on the accuracy of the model are discussed. The results show that the recognition of the travel path using the proposed model is consistent with the actual travel path. The accuracy of the proposed model is more than 60% when the number of missing nodes is less than 7 in total 31 nodes. Considering the decision models for private cars and taxis, respectively, the proposed model provides a method for vehicle path recognition based on incomplete AVI data. [ABSTRACT FROM AUTHOR]

Copyright of Coal Science & Technology (0253-2336) is the property of Coal Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The topographic map plays a very important role in economic construction. In the process of drawing topographic maps, different symbols represent different ground objects, but the symbols representing complex ground objects are often complicated and difficult to create. Moreover, the creation process of complex map symbols can seriously affect the efficiency of topographic map production. Therefore, this paper proposes an automatic derivation method for creation of complex map symbols in a topographic map. The data used are new geographic entity data under the background of Chinese new fundamental surveying and mapping situation. Firstly, four derivation modes of complex map symbols are summarized, including feature-point mode, centroid mode, feature-line mode, and parallel-line mode; then, using the four modes singly or in combination, the complex map symbols of the topographic map are directly derived from the geographic entity data based on programming, and the topographic map cartographic result is obtained automatically. Finally, some topographic maps for Shanxi Province, China, is used for the validation of the creation of map symbols. The experimental results show that the proposed method can automatically derive the complex map symbols of the topographic map, greatly improving production efficiency and obtaining a good visualization effect. The proposed method is a new approach for a new situation and realizes the transformation and upgrading of fundamental surveying and mapping achievements. [ABSTRACT FROM AUTHOR]

Since the conservation of living heritage sites such as historic towns and traditional villages often involves the coordination of multiple interests, the modern socio-economic development of heritage sites and the dominant participatory nature of local heritage communities become the main conflicts in practice. Using a combination of literature research and field cases, this paper firstly compares the history of the theoretical conservation approach to living heritage and explains its core concepts and basic methods. Secondly, it analyses the application and effectiveness of the community co-creation model in living heritage sites using the case of the ancient city of Pingyao in Shanxi Province, China. It is hoped that this will provide a more comprehensive understanding of the current development and future direction of heritage conservation methods, and further consider how to reconcile the historical and daily values of heritage in the conservation process. [ABSTRACT FROM AUTHOR]

Historic sites are important components of every city's cultural history because they preserve rich historical knowledge and distinctive values passed down from previous generations to the present. Due to the progress of urbanization and modernization, many historic sites face pressure from damage and transformation. In this paper, a method for assessing cultural heritage damage was developed to measure the extent of spatial damage in historic sites. Using sample data obtained in Xiyang, Qi, and Xiaoyi, all historic cities in Shanxi Province, Mainland China, and combined weights were estimated using the Delphi technique and the CRITIC weight method. Following this, the Spatial Damage Degree Model (SDDM) based on K-means cluster analysis and K-nearest neighbor (KNN) classification was developed. The findings show that the model efficiently solves the problem of assessing spatial damage levels in historic sites. Through multiple linear regression analysis, it was shown that the damage to historic sites was predominantly caused by three factors: natural erosion, construction damage, and planning and policy. SDDM was used to calculate the spatial damage levels of historic sites, allowing conservators to fully comprehend the features and concerns related to historic sites. As a result, more scientific and rational preservation approaches can be developed, improving the efficiency of historic site restoration and conservation, and encouraging the sustainable development of urban and rural heritage. [ABSTRACT FROM AUTHOR]

Due to the influences of the storage environment, water content change, particle settlement, natural loss, and other factors, the distribution density of wheat and the volume of grain pile in the storage process are gradually changed so that the single weight calculation method cannot objectively evaluate the storage quantity of wheat and also causes difficulties to the regular inspection of the quantity of wheat stock. To meet the practical needs of wheat inventory monitoring, a wheat inventory monitoring method based on inventory measurement and the support vector machine regression (SVR) prediction model is proposed. By collecting the working papers for the physical inspection of wheat in grain warehouses in Shanxi province, Hebei province, Henan province, Jiangsu province, and other places, the storage time, storage weight, storage moisture content, measured moisture content, measured volume weight, measured net volume, and measured weight for inspection were selected as training samples for the SVR prediction model, and kernel function selection and parameter optimization were carried out. We developed an optimal prediction model for the amount of wheat in the grain depots. In the actual grain store measurement process, the net volume of wheat in the current grain store was obtained by a laser volumetric measuring apparatus, the actual bulk density of wheat was sampled, and the actual moisture content of wheat was measured by sampling. The three samples, their storage time, their storage moisture content, and their storage weight were fed into the trained SVR prediction model as new samples, and the predicted weight of the wheat in the current grain store was obtained from the output. The error rate calculation procedure was introduced to achieve an anomalous judgment error rate for grain depots. The experimental results showed that the SVR prediction model based on the linear kernel function had a very low mean squared error and high determination coefficient, and the average prediction accuracy of the grain stock error rate reached 93.2 percent, which can meet the requirements of wheat quantity monitoring in grain warehouses. [ABSTRACT FROM AUTHOR]

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Due to the specialty of the profession and the uncertainty of the cultural industry, media art majors still have some problems in the integrated development of production, teaching and research, which is a weak link in the media art education ecological chain. This paper uses the research methods of literature review, data statistics, logic analysis and other research methods, starting from the development status of Shanxi university, conducted field research on the music, instrumental music, performance, dance and other specialties of Shanxi Media University, and sorted out the problems of Shanxi Media University. Its problems in the integrated development of professional production, education and research include weak industrialization concept, lack of long-term operation mechanism, imperfect platform construction, serious shortage of investment funds and shortage of professional talents, etc. The four dimensions of environment, operating mechanism, talent cultivation and introduction, corresponding countermeasures are put forward in this paper, and the sustainable development path of integration, innovation, production, teaching and research of media art major colleges and universities is also discussed. [ABSTRACT FROM AUTHOR]

Under the "carbon peaking and carbon neutrality" goal, Shanxi Province adjusts the power supply structure and promotes the development of a high proportion of new energy, which has a certain impact on the demand for thermal coal. Therefore, constructing a reasonable forecasting model for thermal coal demand can play a role in stabilizing coal supply and demand. This paper analyzes various factors related to coal demand, and uses Pearson coefficient to screen out six variables with strong correlation. Then, based on the scenario analysis method, combined with the "14th Five-Year Plan" of Shanxi Province, different scenarios of economic development and carbon emission reduction development are set. Finally, a multi-scenario GA–LSSVM forecasting model of thermal coal demand in Shanxi Province is constructed, and the future development trend of thermal coal demand in Shanxi Province is predicted. The results show that the demand for thermal coal is the largest in the mode of high-speed economic development and low emission reduction, and the demand for thermal coal is the lowest in the mode of low-speed economic development and strong emission reduction, which provides a scientific basis for the implementation of Shanxi Province's thermal coal supply policy. [ABSTRACT FROM AUTHOR]

North of Shanxi, Datong Yunzhou District is the base for the cultivation of Hemerocallis citrina Baroni, which is the main production and marketing product driving the local economy. Hemerocallis citrina Baroni and other crops' picking rules are different: the picking cycle is shorter, the frequency is higher, and the picking conditions are harsh. Therefore, in order to reduce the difficulty and workload of picking Hemerocallis citrina Baroni, this paper proposes the GGSC YOLOv5 algorithm, a Hemerocallis citrina Baroni maturity detection method integrating a lightweight neural network and dual attention mechanism, based on a deep learning algorithm. First, Ghost Conv is used to decrease the model complexity and reduce the network layers, number of parameters, and Flops. Subsequently, combining the Ghost Bottleneck micro residual module to reduce the GPU utilization and compress the model size, feature extraction is achieved in a lightweight way. At last, the dual attention mechanism of Squeeze-and-Excitation (SE) and the Convolutional Block Attention Module (CBAM) is introduced to change the tendency of feature extraction and improve detection precision. The experimental results show that the improved GGSC YOLOv5 algorithm reduced the number of parameters and Flops by 63.58% and 68.95%, respectively, and reduced the number of network layers by about 33.12% in terms of model structure. In the case of hardware consumption, GPU utilization is reduced by 44.69%, and the model size was compressed by 63.43%. The detection precision is up to 84.9%, which is an improvement of about 2.55%, and the real-time detection speed increased from 64.16 F P S to 96.96 F P S , an improvement of about 51.13%. [ABSTRACT FROM AUTHOR]

Variations in optical fiber length and refractive index are induced by environmental perturbation, resulting in an additional dynamic propagation delay in fiber-based time synchronization systems, which deteriorate their transfer stability. This disadvantage can be significantly reduced by transmitting the time signal in both directions through fiber and constructing a feedback loop to compensate the propagation delay at the remote end of the link. This paper proposes an analog-digital hybrid proportional integral derivative (PID) control compensation system based on the time-frequency phase-locked loop (TF-PLL). The system is designed to keep the merits of wide servo bandwidth, servo accuracy, and a large dynamic delay compensation range up to 1 s, which is much greater than that reported in previous studies. For proving the validity of this proposed scheme, a self-developed optical fiber time synchronization equipment based on the delay compensation system is applied. The delay compensation system is used on a 1100-km long laboratory optical fiber, and the results show that the time synchronization stability in terms of time deviation (TDEV) is less than 5.92 ps/1 s and 2.56 ps/10,000 s. After successful laboratory evaluation, the proposed system is installed on a real 988.48-km line between the Xi'an Lintong branch of the National Time Service Center (NTSC) and Linfen City, Shanxi Province, realizing the time synchronization of 10 stations along the optical fiber link. The experimental results in the 988.48-km link illustrate that the measured time difference with a peak-to-peak value of 176 ps, the standard deviation of 19.3 ps, and a TDEV of less than 10.49 ps/1 s and 2.31 ps/40,000 s is achieved. The high-precision time delay compensation system proposed in this paper is simple, reliable, and accurate; has a wide range of compensation; and opens up a feasible scheme for providing synchronized time signals to multiple users over the long-distance field optical fiber networks. [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 combination of the Industrial Internet of Things (IIoT) and digital twin (DT) technology makes it possible for the DT model to realize the dynamic perception of equipment status and performance. However, conventional digital modeling is weak in the fusion and adjustment ability between virtual and real information. The performance prediction based on experience greatly reduces the inclusiveness and accuracy of the model. In this paper, a DT-IIoT optimization model is proposed to improve the real-time representation and prediction ability of the key equipment state. Firstly, a global real-time feedback and the dynamic adjustment mechanism is established by combining DT-IIoT with algorithm optimization. Secondly, a strong screening dual-model optimization (SSDO) prediction method based on Stacking integration and fusion is proposed in the dynamic regulation mechanism. Lightweight screening and multi-round optimization are used to improve the prediction accuracy of the evolution model. Finally, taking the boiler performance of a power plant in Shanxi as an example, the accurate representation and evolution prediction of boiler steam quantity is realized. The results show that the real-time state representation and life cycle performance prediction of large key equipment is optimized through these methods. The self-lifting ability of the Stacking integration and fusionbased SSDO prediction method is 15.85% on average, and the optimal selflifting ability is 18.16%. The optimization model reduces the MSE loss from the initial 0.318 to the optimal 0.1074, and increases R2 from the initial 0.731 to the optimal 0.9092. The adaptability and reliability of the model are comprehensively improved, and better prediction and analysis results are achieved. This ensures the stable operation of core equipment, and is of great significance to comprehensively understanding the equipment status and performance. [ABSTRACT FROM AUTHOR]

To address the severity of the wind and light abandonment problem and the economics of hydrogen energy production and operation, this paper explores the problem of multi-cycle resource allocation optimization of hydrogen storage systems for coal–wind–solar power generation. In view of the seriousness of the problem of abandoning wind and photovoltaic power and the economy of hydrogen production and operation, the node selection and scale setting issues for hydrogen production and storage, as well as decision-making problems such as the capacity of new transmission lines and new pipelines and route planning, are studied. This research takes the satisfaction of energy supply as the basic constraint and constructs a multi-cycle resource allocation optimization model for an integrated energy system, aiming to achieve the maximum benefit of the whole system. Using data from Inner Mongolia, where wind abandonment and power limitation are severe, and Beijing and Shanxi provinces, where hydrogen demand is high, this paper analyzes the benefits of the hydrogen storage system for coal–wind–solar power generation, and explores the impact of national subsidy policies and technological advances on system economics. [ABSTRACT FROM AUTHOR]

Architecture is closely related to human development. Different architectural shapes and texture structures reflect the changes of society and the level of social development. They are not only important materials for studying history but also carry the profound significance of human history. However, due to chemical effects, the acid, alkali, salt, and corrosive solvents are applied and produced in the process of industrial production, as well as the corrosive media contained in the atmosphere, groundwater, surface water, and soil will corrode the ancient buildings. The whole picture of many ancient buildings cannot be completely preserved, let alone used as research materials to deeply explore history and humanities. With the development of computer science and technology, we hope to protect and repair traditional ancient buildings through modern technology, which not only respects the long history of the Chinese nation but also helps us better study history through ancient buildings. This paper takes the ancient buildings of traditional villages in Guanzhong, Shanxi Province as an example, optimizes them on the basis of predecessors, and explores the protection and restoration of ancient buildings based on the improved priority algorithm. The results show that the proposed algorithm performs better in the protection and restoration model of ancient buildings than the traditional algorithm. [ABSTRACT FROM AUTHOR]

The development of agricultural products e-commerce (APEC) plays an important role in the smooth progress of the rural revitalization strategy. This paper constructs the evaluation index system of the development level of APEC through literature induction, including rural residents, infrastructure conditions, policy support, the quality of APEC platform, operation effect, and social effect. Then, we use the analytic hierarchy process (AHP) to calculate the index weight and take Shanxi Province of China as the research object to evaluate and analyze the development level of APEC. The evaluation results show that the overall development of APEC in Shanxi Province is at a general level. Finally, we put forward some suggestions for the development of APEC, such as improving the standardization system of APEC. [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]

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

The production of stone sculptures in the form of statues, steles, and pagodas was arguably one of the most prominent forms of Buddhist devotion in early medieval China. The abundant Buddhist imagery and devotional inscriptions adorning their surfaces provide rich information on their creation, commission, consecration, and worship, which is essential for comprehending the local community's religious landscape. This paper employs a network analysis approach to visualize and analyze the spatial arrangement of Buddhist images on the surfaces of pagodas from Nannieshui 南涅水, Shanxi 山西 Province. Network analysis reveals that Nannieshui pagodas were commissioned and worshipped differently from other kinds of stone sculpture, as shown by its emphasis on the spatial and sequential order of Buddhist images depicted on the exterior of these pagodas. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Irrigation & Drainage is the property of Journal of Irrigation & Drainage Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Coal Science & Technology (0253-2336) is the property of Coal Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The accurate prediction of coal structure is important to guide the exploration and development of coal reservoirs. Most prediction models are interpreted for a single sensitive coal seam, and the selection of sensitive parameters is correlated with the coal structure, but they ignore the interactions between different attributes. Part of it introduces the concept of the geological strength index (GSI) of coal rocks in order to achieve a multi-element macroscopic description and quantitative characterization of coal structure; however, the determination of coal structure involves some uncertainties among the properties of coal, such as lithology, gas content and tectonic fracture, due to their complex nature. Fuzzy inference systems provide a knowledge discovery process to handle uncertainty. The study shows that a type-2 fuzzy inference system (T2-FIS) with multi-attribute fusion is used to effectively fuse pre-stack and post-stack seismic inversion reservoir parameters and azimuthal seismic attribute parameters in order to produce more accurate prediction results for the Hengling block in the Shanxi area. The fuzzy set rules generated in this paper can provide a more reliable prediction of coal structure in the GSI system. The proposed system has been tested on various datasets and the results show that it is capable of providing reliable and high-quality coal structure predictions. [ABSTRACT FROM AUTHOR]

Background: As the world's largest coal producer, China was accounted for about 46% of global coal production. Among present coal mining risks, methane gas (called gas in this paper) explosion or ignition in an underground mine remains ever-present. Although many techniques have been used, gas accidents associated with the complex elements of underground gassy mines need more robust monitoring or warning systems to identify risks. This paper aimed to determine which single method between the PCA and Entropy methods better establishes a responsive weighted indexing measurement to improve coal mining safety. Methods: Qualitative and quantitative mixed research methodologies were adopted for this research, including analysis of two case studies, correlation analysis, and comparative analysis. The literature reviewed the most-used multi-criteria decision making (MCDM) methods, including subjective methods and objective methods. The advantages and disadvantages of each MCDM method were briefly discussed. One more round literature review was conducted to search publications between 2017 and 2019 in CNKI. Followed two case studies, correlation analysis and comparative analysis were then conducted. Research ethics was approved by the Shanxi Coking Coal Group Research Committee. Results: The literature searched a total of 25,831publications and found that the PCA method was the predominant method adopted, and the Entropy method was the second most widely adopted method. Two weighting methods were compared using two case studies. For the comparative analysis of Case Study 1, the PCA method appeared to be more responsive than the Entropy. For Case Study 2, the Entropy method is more responsive than the PCA. As a result, both methods were adopted for different cases in the case study mine and finally deployed for user acceptance testing on 5 November 2020. Conclusions: The findings and suggestions were provided as further scopes for further research. This research indicated that no single method could be adopted as the better option for establishing indexing measurement in all cases. The practical implication suggests that comparative analysis should always be conducted on each case and determine the appropriate weighting method to the relevant case. This research recommended that the PCA method was a dimension reduction technique that could be handy for identifying the critical variables or factors and effectively used in hazard, risk, and emergency assessment. The PCA method might also be well-applied for developing predicting and forecasting systems as it was sensitive to outliers. The Entropy method might be suitable for all the cases requiring the MCDM. There is also a need to conduct further research to probe the causal reasons why the PCA and Entropy methods were applied to each case and not the other way round. This research found that the Entropy method provides higher accuracy than the PCA method. This research also found that the Entropy method demonstrated to assess the weights of the higher dimension dataset was higher sensitivity than the lower dimensions. Finally, the comprehensive analysis indicates a need to explore a more responsive method for establishing a weighted indexing measurement for warning applications in hazard, risk, and emergency assessments. [ABSTRACT FROM AUTHOR]

This paper presents the on-site monitoring of a medium–long highway tunnel constructed above a goaf of a multi-layer coal seam, in order to evaluate and maintain safety during operation. The case study of the Tianzimiao medium–long highway tunnel in Shanxi province was conducted above a goaf of a multi-layer coal seam with typical geological and engineering conditions in China, where a total of four coal seams (seam no. 3, 8, 12, and 15) were mined out with a total thickness of up to 11 m. Methods including data collection, engineering geological survey, drilling, geophysical prospecting, testing, and on-site monitoring were adopted, and a geo-mechanical model was established to conduct the research. Stratified monitoring was applied to investigate the individual settlement and deformation of the four layers of the goaf below, and a prediction of the possible deformation in tunnel floor ground was made based on the stratified measurements. The settlement of the tunnel sidewall, the internal stress in the fractured zone of the surrounding rock, and the deformation above the tunnel entrance were also monitored, and the monitoring data were compared with the numerical simulation results for the safety evaluation of the tunnel. The results show that the current tunnel deformation values and trend are both within the safety scope of the evaluation and prediction. The stability evaluation method for the multi-layer goaf used in this paper and the long-term on-site monitoring and timely feedback during operation is helpful to ensure the safe use of the tunnels above the goaves of multi-layer thick coal seams. [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]

Copyright of Journal of Irrigation & Drainage is the property of Journal of Irrigation & Drainage Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

With the recent international economic and social changes, the development of innovation theories, the changes in the global industrial structure, and the transformation of old and new kinetic energy, many countries have advanced from innovation paradigm 1.0 to 3.0, integrating a variety of disciplines and theories, and using this concept to enhance their innovation capabilities. In such an environment, how to combine scientific and technological innovation with ecological environment construction, practice the integration and symbiosis of ecology and innovation, and promote the development of green innovation is the current focus of academic research. The scientific and technological innovation ecological chain is an organizational model that realizes the goal of scientific and technological innovation and the value-added spiral through the orderly connection and synergistic interaction between the main bodies or elements of innovation, such as basic research, technical research, achievement transformation, talent support, and technological finance. This paper takes Shanxi Province's scientific and technological innovation ecological chain as a typical example, collects relevant text data through web crawler technology, then deconstructs the system of scientific and technological innovation ecological chain based on media integration, understands the composition of its main chain, supporting chain, and the interaction between the chains mechanism, and finally puts forward policy suggestions for the deepening of the future regional scientific and technological innovation ecological chain. [ABSTRACT FROM AUTHOR]

Copyright of Coal Science & Technology (0253-2336) is the property of Coal Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The anionic and cationic species of elements from deeply buried deposits migrate to the near surface driven by various geological forces. The geoelectrochemical exploration method (GEM), derived from CHIM, consists of the application of an electric field to collect these active ions at the designated electrode. Prospecting effects have been investigated by researchers since the coming up of CHIM. However, the cumbersome technical equipment, complex techniques and low production efficiency have restricted its potential application in field geological survey. This paper presents the newly developed CHIM that is electrified by a low voltage dipole. The improved technique allows both anionic and cationic species of elements to be extracted simultaneously in an anode and in a cathode. Compared with the conventional CHIM method, the innovative techniques called dipole geoelectrochemical method are characterized by simple instrumentation, low cost and easy operation in field, and in particular enables simultaneous extraction of anionic and cationic species of elements, from which more information can be derived with higher extraction efficiency. The dipole geoelectrochemical method was proposed and applied in the experiments of the Yingezhuang gold ore from Zhaoyuan, Shandong Province, the 210 gold ore from Jinwozi, Xinjiang Province, and the Daiyinzhang gold polymetallic deposit from Wutaishan, Shanxi Province. There are clearly anomalies above the gold ore body, indicating the effectiveness and feasibility of the improved dipole geoelectrochemical method in both scientific research and mineral exploration. The results of anode extraction in several mining areas have shown good results, indicating that gold may be mainly negatively charged. In fact, many metal nanoparticles, clay minerals, or complexes of metal ions are negatively charged, so they migrate to the anode electrode and enrich. [ABSTRACT FROM AUTHOR]

Solar energy is considered one of the most hopeful alternative sources to avoiding dependence on fossil fuels, and it does not cause any air pollution. GIS-based solar energy potential evaluation is mainly focused on regional scale; further, more solar energy potential evaluation with building scale is calculated through observation data and mathematical model. Therefore, in this paper, a GIS-based joint solar energy potential evaluation is developed to evaluate the distributed photovoltaic potential and centralized photovoltaic potential. Shanxi province in China, which has abundant coal resources, is used as the study area. The raster grid scale is used as the minimum research scale, which could not only deal with the distributed photovoltaic potential but could also calculate the centralized photovoltaic potential. The obtained results indicate that the developed method could effectively deal with problems associated with the distributed photovoltaic potential and centralized photovoltaic potential in the raster grid scale. [ABSTRACT FROM AUTHOR]

As one of the main fossil fuels globally, coal can be enriched with a variety of critical metal elements in specific geological conditions. This paper investigates the mineral compositions and concentrations of major and minor element oxides and trace elements in the No. 9 coal from the Xinyuan mine of the northern Qinshui coalfield, China, and discusses the modes of occurrence and enrichment mechanisms of critical metal elements such as Li, Ga, Th and REY. The mineral compositions of the No. 9 coal are primarily represented by clay minerals and quartz, with a small amount of calcite, siderite, anatase, etc. The major element oxides in the No. 9 coal are dominated by SiO2 and Al2O3. Compared with world hard coal, the No. 9 coal of the Xinyuan mine is rich in Li (CC = 8.00) and Th, slightly enriched with Pb, Sc, Ga, Y, La, Ce, Tb, Dy, Er, Yb and Hg, and depleted in Mn, Co, Ni, Rb, Cs and Tl. The critical metal elements such as Li, Ga, Th and REY that enriched No. 9 coal mainly occur in aluminum silicates. The genetic type of the critical metal elements in the No. 9 coal from the Xinyuan mine is source rock-controlled type. The critical metal minerals and solutions from the source area were transported to the study area by the action of water. Due to the change of swamp water conditions, the critical metal elements were combined with clay minerals and enriched the coal. [ABSTRACT FROM AUTHOR]

To push forward the development of electric vehicles while improving the economy and environment of virtual power plants (VPPs), research on the optimization of VPP capacity considering electric vehicles is carried out. In this paper, based on this, this paper first analyzes the framework of the VPP with electric vehicles and models each unit of the VPP. Secondly, the typical scenarios of wind power, photovoltaic, electric vehicle charging and discharging, and load are formed by the Monte Carlo method to reduce the output deviation of each unit. Then, taking the maximization of the net income and clean energy consumption of the VPP as the objective function, the capacity optimal allocation model of the VPP considering multiobjective is constructed, and the conditional value-at-risk (CVaR) is introduced to represent the investment uncertainty faced by the VPP. Finally, a VPP in a certain area of Shanxi Province is used to analyze a calculation example and solve it with CPLEX. The results of the calculation example show that, on the one hand, reasonable selection of the optimal scale of EV connected to the VPP is able to improve the economy and environment of the VPP. On the other hand, the introduction of CVaR is available for the improvement of the scientific nature of VPP capacity allocation decisions. [ABSTRACT FROM AUTHOR]