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In recent years, with the rapid development of the Internet industry, the publicity effect of paperbark walnuts has been substantially increased, and the consumption and demand of paperbark walnuts have been rising, and the output of paperbark walnuts in China has also increased year by year. This paper takes the panel data of the top three prefecture-level cities in each GDP ranking of five provinces in northwest China from 2012 to 2021 as the sample and combines the DEA model with Malmquist to evaluate and analyze the logistics efficiency of paper walnuts in northwest China. It is found that the overall logistics efficiency of paperback walnuts in Northwest China has been improved in recent years, but there are still areas that need to be improved, such as the factor distribution is not reasonable enough; the logistics efficiency of paperback walnuts in Northwest China from 2012 to 2021 is in a fluctuating state; the logistics efficiency of paperback walnuts in Shaanxi Province is better than the other provinces and is in the leading position; the improvement of technological progress has a key role in the total factor productivity improvement. As a result, this paper puts forward five specific suggestions based on the research results to help accelerate the improvement of paper walnut logistics efficiency in Northwest China. [ABSTRACT FROM AUTHOR]

In recent years, with the rapid development of the Internet industry, the publicity effect of paperbark walnuts has been substantially increased, and the consumption and demand of paperbark walnuts have been rising, and the output of paperbark walnuts in China has also increased year by year. This paper takes the panel data of the top three prefecture-level cities in each GDP ranking of five provinces in northwest China from 2012 to 2021 as the sample and combines the DEA model with Malmquist to evaluate and analyze the logistics efficiency of paper walnuts in northwest China. It is found that the overall logistics efficiency of paperback walnuts in Northwest China has been improved in recent years, but there are still areas that need to be improved, such as the factor distribution is not reasonable enough; the logistics efficiency of paperback walnuts in Northwest China from 2012 to 2021 is in a fluctuating state; the logistics efficiency of paperback walnuts in Shaanxi Province is better than the other provinces and is in the leading position; the improvement of technological progress has a key role in the total factor productivity improvement. As a result, this paper puts forward five specific suggestions based on the research results to help accelerate the improvement of paper walnut logistics efficiency in Northwest China. [ABSTRACT FROM AUTHOR]

As an essential way to enhance farmers’ self-development ability, off-farm employment plays an indispensable role in farmers’ multidimensional poverty reduction in many countries. Employing a survey of 1926 farmers in five provinces of the Yellow River Basin in China, this paper examined the multi-dimensional poverty reduction effect of off-farm employment and the heterogeneous influence of different dimensions of off-farm employment (modes, levels, distances and frequency). The results showed that (1) although absolute poverty in the income dimension was largely eliminated in the Yellow River Basin, the poverty in social resources, transportation facilities, employment security were the key bottlenecks restricting farmers’ self-development. (2) The province with the best multidimensional poverty reduction effect for non-farm employment was Shaanxi, with the largest contribution to employment security. (3) Improving off-farm employment level, distance and time can significantly alleviate the multi-dimensional poverty of farmers. Therefore, to lessen the multi-dimensional poverty of farmers in the Yellow River Basin, it is necessary to focus on the governance of multi-dimensional key poverty-stricken areas, such as the middle and upper courses of the Yellow River, adopting multidimensional poverty alleviation strategy of off-farm employment according to local conditions, working on the farmers’ deficiencies in social resources, mobility, employment security, and deepening the effect of off-farm employment on benefiting farmers and helping the poor. [ABSTRACT FROM AUTHOR]

The development of rural tourism destinations in China is confronting multiple issues, including blind expansion and a repetitive developmental model, causing the sector to enter a vicious competition cycle. The perception among tourists of rural tourism destinations, and their willingness to revisit places will provide insights for service providers that will enable them to form better strategies to stand out in the fiercely competitive market. Understanding tourist perception will enable providers to contribute to the construction of rural tourist destinations. Taking Ma Wei Yi Folk Culture Village as a case study, this paper combines the development status of rural tourism in Ma Wei Yi, obtains first-hand data through questionnaire interviews, verifies the research hypothesis, and uses Pearson coefficient to carry out correlation analysis. The paper concluded that tourists' rural perception has a positive and strong impact on their willingness to revisit, and its factors have different impacts. According to the empirical results, tourist destination providers should pay attention to rural perceptual development in their follow-up development and operation processes. They can effectively attract tourists to visit multiple times, enhance tourist's sense of enjoyable experience, and achieve sustainable development. [ABSTRACT FROM AUTHOR]

Traditional historical buildings carry the culture and spirit of China for thousands of years and have a unique charm that modern buildings do not have. However, traditional historical buildings have gradually declined over time, and their restoration not only takes time and materials but also causes certain harm to the environment. Therefore, this paper has aimed to explore how traditional historical buildings can develop in a sustainable and ecologically adaptive image in modern times. For traditional historical buildings, this paper has taken traditional cave dwellings in northern Shaanxi as an example to analyze their ecological adaptability, and based on the analysis results, traditional cave dwellings have been transformed. Specifically, this paper has taken the comfort of residential houses as the evaluation standard and has selected the thermal stability of the building and the energy consumption of heat supply as indicators to compare and analyze the traditional cave dwellings and the renovated cave dwellings. The experimental results of this paper have found that the traditional historical buildings are the crystallization of the wisdom of the ancients for thousands of years. However, due to the limitation of technology, the lighting and thermal stability of traditional cave dwellings are not high. After scientific design, the lighting and thermal stability of the transformed cave are 100% and 30% higher than those of the traditional cave, respectively, and the heating energy consumption is reduced by 50%. [ABSTRACT FROM AUTHOR]

The shortage of available water resources and climate change are major factors affecting agricultural irrigation. In order to improve the irrigation water use efficiency, it is necessary to predict the water requirements for crops in advance. Reference evapotranspiration (ETo) is a hypothetical standard reference crop evapotranspiration, many types of artificial intelligence models have been applied to predict ETo; However, there are still few in the literature regarding the application of hybrid models for deep learning model parameters optimization. This paper proposes two hybrid models based on particle swarm optimization (PSO) and long-short-term memory (LSTM) neural network, used to predict ETo at the four climate stations, Shaanxi province, China. These two hybrid models were trained using 40 years of historical data, and the PSO was used to optimize the hyperparameters in the LSTM network. We applied the optimized model to predict the daily ETo in 2019 under different datasets, the result showed that the optimized model has good prediction accuracy. The optimized hybrid models can help farmers and irrigation planners to make plan earlier and precisely, and can provide valuable information to improve tasks such as irrigation planning. [ABSTRACT FROM AUTHOR]

Toll-gates are crucial points of management and key congestion bottleneck for the freeway. In order to avoid traffic deterioration and alleviate traffic congestion in advance, it is necessary to predict and evaluate the congestion in toll-gates scattering in large-scale region of freeway network. In this paper, traffic volume and operational delay time are selected from various traffic indicators to evaluate congestion considering the particular characteristics of the traffic flow within the toll-gate area. The congestion prediction method is designed including two modules: a deep learning (DL) prediction and a fuzzy evaluation. We propose a modified deep learning method based on graph convolutional network (GCN) structure in the fusion of dilated causal mechanism and optimize the method for spatial feature extraction by constructing a new adjacency matrix. This new AI network could process spatiotemporal information of traffic volume and operational delay time, that extracted from large-scaled toll-gates spontaneously, and predict key indicators in 15/30/60 min future time. The evaluation module is proposed based on these predicted results. Then, fuzzy C-means algorithm (FCM) is further modified by determining coupling weight for these two key indicators to detect congestion state. Original traffic data are obtained from the current 186 toll-gates served on the freeway network in Shaanxi Province, China. Experimental tests are carried out based on historical data of four months after preprogressing. The comparative tests show the proposed CPT-DF (congestion prediction on toll-gates using deep learning and fuzzy evaluation) outperforms the current-used other models by 6-15%. The successful prediction could extend to the real-time prediction and early warning of traffic congestion in the toll system to improve the intelligent level of traffic emergency management and guidance on the key road of disasters to some extent. [ABSTRACT FROM AUTHOR]

The higher contribution of traffic delay to environmental impacts is urging the highway agencies to take work zone management into the maintenance schemes decision-making. Aiming to understand the role of work zone management in user CO2 emissions reduction, this paper firstly developed a practical methodological framework of traffic delay-related CO2 emissions caused by highway maintenance based on a popular life cycle user cost analysis approach in regard of the microscopic vehicle operation analysis. The method was applied in an actual freeway flexible pavement with 15-year design life in Shaanxi Province, China, covering three types of preventive maintenance, correction maintenance, and rehabilitation. In addition, the impacts of key inputs of proposed method on work zone user CO2 emissions results were checked. The results show that traffic delay attributes to 29.4% of total CO2 emissions of the life cycle of highway pavement maintenance, and 51.8% of work zone user CO2 emissions result from preventive maintenance, especially from micro vehicle operations including speed change and queue near work zone (62% of total work zone user CO2 emissions). The work zone management alternative strategies related to less traffic volume or higher highway capacity including vehicle type limitation and the limited work zone speed have an advantage in reducing the work zone CO2 emissions over changing work zone length or work zone timing. The findings in this paper may present a useful tool and reference for robustly supporting the decision-making on highway maintenance carbon mitigation in work zone traffic. [ABSTRACT FROM AUTHOR]

When stratified mining is used in extrathick coal seam, the gas emission in goaf of the first mining face is large, and it is easy to cause gas overrun in the upper corner during the rapid advance of the working face, which seriously affects the safe and efficient mining of the working face. The gas drainage in goaf by roof high-drainage way is the fundamental solution to solve the gas overrun in the upper corner, and the reasonable layout position is related to the drainage effect of high-drainage way. In this paper, 206 slicing mining face of Tingnan Coal Mine in Binchang Mining Area of Shaanxi Province is taken as an engineering example. Theoretical analysis, fluent numerical simulation, and field verification are used to study and analyze the reasonable layout position and drainage effect of roof high-drainage way in working face. The research results show that the reasonable position of the high-drainage way layout is the horizontal distance of 15 m, the vertical distance of 21 m and 26 m, the horizontal distance of 25 m, and the vertical distance of 21 m and 26 m. In the layout position of 15 m horizontal and 21 m vertical, the gas drainage volume of high-drainage roadway is 16.4~23.3 m3/min, and the average gas drainage volume is 20.45 m3/min. The gas drainage volume of high-drainage roadway accounts for 52.1% of the gas emission, which achieves the expected effect and realizes the safety requirements of gas prevention and control in working face. The research results of this paper can provide guidance for the layout of high-drainage way in Tingnan Coal Mine and adjacent mines. [ABSTRACT FROM AUTHOR]

In recent years, northern China has suffered from the severe haze in autumn and winter, a phenomenon to which coal-fired heating appliances contribute significantly. To reduce pollution and achieve sustainability in the electricity industry, government departments have proposed the "Electricity Substitution" strategy, and the State Grid Corporation has also proposed the "coal-to-electricity" transformation movement. Against this background, our study aims to identify the impact factors of electricity consumption behavior among customers who have completed this transformation. Based on customers' monthly electricity consumption data in Shaanxi from 2017 to 2019 and on-site survey results, this paper constructs a multiple regression model and utilizes SPSS25.0 to analyze the relationship between residents' electricity consumption and related factors. The research results revealed that after the implementation of the "coal-to-electricity" transformation, residential customers' electricity consumption tended to rise. Consequently, winter temperature, appliance power, and heating area negatively correlate with residents' electricity consumption. Simultaneously, customers' habits, subsidies, and electricity pricing positively correlate with residents' electricity consumption. Finally, this paper offers some practical management suggestions for power companies based on the analysis. [ABSTRACT FROM AUTHOR]

With the rapid development of urbanization, fire risk factors have increased greatly, indicating a higher requirement for urban firefighting security. Fire rescue capabilities can be effectively improved by the scientific layout of fire stations, and therefore, the optimal spatial arrangement of fire stations has practical implications for urban safety. In this paper, a method for planning the locations of urban fire stations is presented, taking into account the fire risk points of interest (POIs) data, road networks and fire station planning principles. The combined model method is validated against the nearest facility point model, and the service area model is proposed for the coverage of POIs and regional areas of planned new sites. The efficacy of the model is demonstrated through an improvement in the coverage of crosspoints of the regional area and points of interest (POIs), with increases of 10.20% and 12.43%, respectively. We applied the combined model method to Fengdong New Town, Shaanxi Province, China. A total of 11 new potential sites were proposed to improve the efficiency of spatial coverage, and subsequently, the coverage rate of the POIs and regional area reached 97.66% and 84.80%, respectively. This study provides application guidelines for the decision-making of fire services and the allocation of firefighting resources. [ABSTRACT FROM AUTHOR]

The fluctuation and uncertainty of the electricity load bring challenges to load forecasting. Traditional point forecasting struggles to avoid errors, and pure interval forecasting may cause the problem of too wide an interval. In this paper, we combine point forecasting and interval forecasting and propose a point-interval forecasting model for electricity load based on regular fluctuation component extraction. Firstly, the variational modal decomposition is combined with the sample entropy to decompose the original load series into a strong regular fluctuation component and a weak regular fluctuation component. Then, the gate recurrent unit neural network is used for point forecasting of the strong regular fluctuation component, and the support vector quantile regression model is used for interval forecasting of the weak regular fluctuation component, and the results are accumulated to obtain the final forecasting intervals. Finally, experiments were conducted using electricity load data from two regional electricity grids in Shaanxi Province, China. The results show that combining the idea of point interval, point forecasting, and interval forecasting for components with different fluctuation regularity can effectively reduce the forecasting interval width while having high accuracy. The proposed model has higher forecasting accuracy and smaller mean interval width at various confidence levels compared to the commonly used models. [ABSTRACT FROM AUTHOR]

There are a variety of land cover products generated from remote-sensing images. However, misclassification errors in individual products and inconsistency among them undermine their utilities for research and other applications. While it is worth developing advanced pattern classifiers and utilizing the images of finer spatial, temporal, and/or spectral resolution for increased classification accuracy, it is also sensible to increase map classification accuracy through effective map fusion by exploiting complementarity among multi-source products over a study area. This paper presents a novel fusion method that works by weighting multiple source products based on their map-reference cover type transition probabilities, which are predicted using random forest for individual map pixels. The proposed method was tested and compared with three alternatives: consensus-based weighting, random forest, and locally modified Dempster–Shafer evidential reasoning, in a case study, over Shaanxi province, China. For this case study, three types of land cover products (GlobeLand30, FROM-GLC, and GLC_FCS30) of two nominal years (2010 and 2020) were used as the base maps for fusion. Reference sample data for model training and testing were collected following a robust stratified random sampling design that allows for augmenting reference data flexibly. Accuracy assessments show that overall accuracies (OAs) of fused land cover maps have been improved (1~9% in OAs), with the proposed method outperforming other methods by 2~8% in OAs. The proposed method does not need to have the base products' classification systems harmonized beforehand, thus being robust and highly recommendable for fusing land cover products. [ABSTRACT FROM AUTHOR]

With the continuous construction of transportation infrastructure, intersection nodes have been increasing rapidly, bringing growing numbers of tunnel- and exit-adjacent sections (TEAS) in mountain expressways in China. With the complex variation in the surrounding environment, drivers always face congestion and confusion on tunnel and the exit connecting sections (TECS) without adequate length, meanwhile excessively long TECS create detours. To better provide a sustainable design strategy for TEAS, based on a certain section of expressway in Shaanxi, China, this paper establishes a theoretical calculation model through analysis. The characteristics of traffic flow and drivers' light adaptation at tunnel exit are obtained through data collection and driving tests, and the length requirements of the tunnel and exit connecting sections (TECS) are discussed. A VISSIM microscopic simulation model is also built under various design schemes and entropy-based multi-attribute decision making (EBMADM) is used to objectively calculate the weights of the four selected evaluation indexes. Then, the design schemes of the TECS with different lengths have been comprehensively evaluated. The results show the match between the evaluation results of EBMADM with theoretical calculations under existing traffic conditions, which proves the rationality of EBMADM in such problems. For more cases, the results of the EBMADM evaluation show a positive correlation between the length of TECS for the best performing design scheme with traffic volume and diverging ratio. [ABSTRACT FROM AUTHOR]

Because the penetration depth of electromagnetic waves in forests is large in the longer wavelength band, most traditional forest height estimation methods are carried out using polarimetric interferometry synthetic aperture radar (PolInSAR) data of the L or P band, and the estimation method is a three-stage method based on the random volume over ground (RVoG) model. For X-band electromagnetic waves, the penetration depth of radar waves in forests is limited, so the traditional forest height estimation method is no longer applicable. In view of the above problems, in this paper we propose a new forest height estimation strategy for airborne X-band PolInSAR data. Firstly, the sub-view interferometric SAR pairs obtained via frequency segmentation (FS) in the Doppler domain are used to extend the polarimetric interferometry coherence coefficient (PolInCC) range of the original SAR image under different polarization states, so as to obtain the accurate ground phase. For the determination of the effective volume coherence coefficient (VCC), part of the fitting line of the extended-range PolInCC distribution that is intercepted by the fixed extinction coherence coefficient curve (FECCC) of the fixed range is averaged to obtain the accurate effective VCC. Finally, the high-precision forest canopy height in the X-band is estimated using the effective VCC with the ground phase removed in the look-up table (LUT). The effectiveness of the proposed method was verified using airborne-measured data obtained in Shaanxi Province, China. The comparison was carried out using different strategies, in which we substituted one step of the process with the conventional method. The results indicated that our new strategy could reduce the root mean square error (RMSE) of the predicted canopy height vastly to 1.02 m, with a lower estimation height error of 12.86%. [ABSTRACT FROM AUTHOR]

Study Question: Are there temporal trends of sperm concentration (SC) and total sperm count (TSC) in Chinese healthy males from 1981 to 2019?Summary Answer: Our result indicated a temporal decrease in SC and TSC among 327 373 healthy Chinese men in the recent four decades.What Is Known Already: A review of 61 papers reported a temporal decline in SC and TSC from 1938 to 1990. This trend was later confirmed by a systematic review of 185 published papers from 1981 to 2013. However, the majority of the included individuals were from western countries. In China, whether SC and TSC have declined remains controversial.Study Design, Size, Duration: This systematic review of published articles used data extracted from Pubmed, Science Direct, Embase, China-National-Knowledge-Infrastructure (CNKI) and Wanfang Data to assess changes in SC and TSC in China from 1981 to 2019.Participants/materials, Setting, Methods: A total of 111 studies including 327 373 individuals who provided semen samples from 1981 to 2019 were extracted for the present analysis. Study selection and data extraction were performed by two independent researchers. The trends in SC and TSC were analysed using liner-regression and meta-regression before and after adjusting for potential covariates. Moreover, subgroups, categorised based on geographic region, fertility status or recruitment source, were also analysed.Main Results and the Role Of Chance: SC declined significantly (slope liner-regression = -0.748 million/ml/year; P = 0.005; slope meta-regression = -0.824 million/ml/year; P < 0.001) between 1981 and 2019 in China. Trends for TSC was similar to that for SC (slope liner-regression = -2.073 million/year; P = 0.032; slope meta-regression = -2.188 million/year; P = 0.003). In subgroup meta-regression analyses, males with definite fertility had continuous declines in SC (slope northern group=-2.268, P = 0.009; slope southern group=-1.014, P = 0.009) and TSC (slope northern group=-9.675, P = 0.010; slope southern group=-3.215, P = 0.042). However, in the unselected group, where fertility status was unknown, the obvious downward trend in SC was only seen in males from Northern regions (slope = -0.836, P = 0.003). Another subgroup analysis demonstrated that obvious decreases in SC (slope = -1.432, P < 0.001) and TSC (slope=-4.315, P = 0.001) were only seen in volunteer groups but not in pre-pregnancy examination groups and other recruitment groups. The results changed minimally in multiple sensitivity analyses.Limitations, Reasons For Caution: The validity of the meta-analysis results was limited mainly by the quality of the included studies. Additionally, our study spanned many decades and the recommended criteria for some semen parameter assessments have significantly changed, which may bring about some unavoidable bias. Moreover, the data remain insufficient especially in some provinces of China.Wider Implications Of the Findings: The present study is the first study to report significant decreases in SC and TSC in 327 373 healthy Chinese men between 1981 and 2019, indicating a serious reproductive health warning. Further studies on the causes of the declines are urgently needed.Study Funding/competing Interest(s): D.Z. is supported by the National Natural Science Funding of China, Natural Science Funding of Shaanxi Province, Science Funding of Health Department, Shaanxi Province, Fundamental Research Funds for the Central University and the Project of Independent Innovative Experiment for Postgraduates in Medicine in Xi'an Jiaotong University. The authors have no conflicts of interests to declare.Trial Registration Number: N/A. [ABSTRACT FROM AUTHOR]

Borehole cataloguing is an important task in geological drilling. Traditional manual cataloguing provides the stratification of underground boreholes based on changes in core lithology. This paper proposes a novel borehole cataloguing method using a drilling process monitoring (DPM) system. This DPM cataloguing method stratifies a borehole according to the drilling speed through the rock. A 102 m borehole was drilled and cored in Baota district, Yan'an city, Shaanxi Province, China. The rock-breaking response parameters of the drill bit displacement, drill rod rotation speed and inlet pipe and outlet pipe oil pressures were monitored throughout the drilling process, and the drilling depth-penetration rate curve during the net drilling process was obtained. The changes in drilling speed show that the DPM cataloguing can identify the depths of the layer interfaces of the borehole and describe the stratification. The interface depth values obtained by DPM have little difference from the interface depth values obtained by manual cataloguing, and the errors are between −0.04% and 4.29%. From the DPM stratification results, the engineering quality evaluation of the rock mass can be realized without coring. DPM is fast, convenient, accurate, can greatly improve the efficiency of existing catalogues, and can be applied to scientific research in any underground space. DPM is a measurement-while-drilling technology. According to DPM data, the operating state of a drilling rig and the parameter changes while drilling can be obtained in situ and in real time throughout the drilling process. [ABSTRACT FROM AUTHOR]

Solar composting chamber is an important way for disposing rural domestic waste locally, which requires the participation of farmers. However, few studies have explored farmers' cooperation preference for solar composting chamber, even without considering farmers' heterogeneity. Therefore, this paper divides the farmers into three types: economic, social, and cognitive dominant. The Choice Experiment method is used to investigate all types of farmers' cooperation preference and willingness to accept subsides for the solar composting chamber, using the survey data of China's Shaanxi province. The findings show that social-dominant farmers favor supply models that incorporate government subsidies, more participating farmers, and technical support, while economic-dominant farmers prefer models that include closer construction distances in addition to those. In contrast, cognitive-dominant farmers prefer models with more withdrawal flexibility in addition to the aforementioned factors. Furthermore, economic-dominant farmers have the lowest value of willingness to accept subsidies, i.e., 10,923 dollars, while cognitive-dominant farmers have the highest, i.e., 22,197 dollars. According to the results, policy implications are suggested, including incentivizing farmers' participation by enhancing government subsidies and technical support, and developing diverse cooperation models. • Farmers play an important role in supply of solar composting chamber. • The farmers are categorized into economic, social, and cognitive types. • Choice experimental is used to measure all types of farmers' cooperation preference. • The farmers' willingness to accept subsidies are calculated. • Supply model with subsidies, participants and technical support are most favored. [ABSTRACT FROM AUTHOR]

Plowing refers to the phenomenon by which a landslide displaces and pushes the path material forward. Despite its importance in shaping the dynamics of many rapid flow-like loess landslides, the mechanism of plowing is not fully understood. Therefore, this paper presents an improved numerical model based on the material point method (MPM). This model takes into account the interactions between the landslide mass and the path material. The reliability of this model was validated by simulating two granular column collapse experiments involving interaction with an erodible mass. The model was then applied to analyze the plowing dynamics of the Ximiaodian loess landslide in Jingyang County, Shaanxi Province, China. A series of well-designed simulations were conducted to investigate this specific landslide event, contributing to a deeper understanding of the plowing phenomenon in loess landslides. The simulation results show that our model can satisfactorily simulate the plowing process of the Ximiaodian landslide. The plowing process of a rapid-flow loess landslide is proposed to consist of four distinct stages: 1) the collision stage, when the landslide strikes the terrace, resulting in the bending of its strata; 2) the shear failure stage, characterized by significant plastic shear deformation within the bent strata, resulting in the formation of multiple shear failure planes; 3) the steady plowing stage, during which the deformation structure in the affected terrace stabilizes and plowing continues in a steady pattern; and 4) the stopping stage, when the propagation of the disturbed terrace gradually stops. Furthermore, the disturbed terrace zone exhibits three distinct deformation structures. In the rear part, a stable zone develops where the terrace layers are compressed. However, due to the compressive forces exerted by the overlying loess, no significant shear deformation is observed. The middle part is the shear failure zone, characterized by the formation of multiple shear failure planes. The front part is the upheaval zone, where the terrace layers are slightly bent and tilted. • An improved MPM model is proposed to simulate the plowing process of rapid flow-like landslides. • The plowing mechanism of a real loess landslide is analyzed by the MPM model for the first time. • The plowing process of a rapid flow-like loess landslide consists of four stages. • Three distinct deformation structures are formed in the disturbed terrace zone during the plowing process. [ABSTRACT FROM AUTHOR]

Quantity-based and concentration-based limits are two common environmental permitting approaches utilized by government worldwide in environmental management. While existing literature is still unambiguous about roles played by quantity-based versus concentration-based limits in environmental management, it becomes evident that relying exclusively on concentration-based or quantity-based limits to control plant emissions may not necessarily result in improved environmental quality. This paper leverages a unique opportunity arising from a recent reform in China's Pollutant Emission Permit System (PEPS) initiated in 2016 to analyze how the introduction of quantity-based limits in addition to concentration-based limits through the PEPS reform impact emissions at the plant level. Utilizing a unique plant-level continuous emission monitoring system data collected from Shaanxi Province (located in western China), the paper finds a significant reduction in air pollutant emissions as a result of the PEPS reform (nitrogen oxides (NOx) by 39%, sulfur dioxide (SO 2) by 15% and particulate matter (PM) by 13%). The heterogeneity analyses show emission reductions in plants differ across those with varying quantity limits specified in their permits, distinct emission ratios and diverse ownership structures. Furthermore, plants that fall under the classified management system with more stringent regulations imposed, especially those operating in high-pollution sectors, situated within industrial parks, or classified as large-sized plants, attain higher pollutant quantity limits. Findings of the paper carry important implications for effective environmental management, particularly within developing countries, and shed some light on carbon emission reduction policies in China. [Display omitted] • Quantity-based limits reduce air pollutant emissions significantly. • Distinct behaviors observed in air and water pollutants. • Varied quantity limits and emission ratios influence emission behavior. • State-owned plants show better emission reduction under quantity limits. • Stricter regulations could allow higher quantity limits for plants. [ABSTRACT FROM AUTHOR]

A woman's crown made of fine gilt bronze with refined glass inlay work was excavated from a Sui-Tang tomb called Kunlun M2 in Xi'an, Shaanxi Province, China. Very few female crowns and crown ornaments have been excavated in China thus far, and there has been a lack of systematic research into the technologies used to manufacture them. Importantly, this paper uses the M2 crown to investigate its surface inlays and overall shape, then conducts a comparative analysis of women's crown ornaments of the same type, providing a reference for study of the crown. Non-invasive and micro-destructive analysis including optical microscopy (OM), optical coherence tomography (OCT), micro X-ray fluorescence imagery (XRF), and Raman spectroscopy were applied. These identified the crown's inlays as potash-lime glass, composed mainly of the raw materials: vein quartz or quartzite with potassium nitrate as flux. The inlays were sintered before embedding into gilt copper wire filigree. In comparison to the composition proportions in other ancient potash-lime glass, there is no specific percentage of the raw materials in Chinese potash-lime glass, where the ingredients were likely determined by the experience of the craftsman. Compared with existing research on other crowns and their inlays, this study speculates that the crown dates from the Sui dynasty (581–618) or early Tang dynasty (618–649), was made locally by Chinese craftsmen and belonged to the wife of a high official. [ABSTRACT FROM AUTHOR]

Drought prediction plays an important guiding role in drought risk management. The standardized precipitation index (SPI) is a popular meteorological drought indicator to measure the degree of drought. The SPI time series is non-stationary, whereas the conventional artificial neural network (ANN) model has limitations to predict non-stationary time series. To overcome this limitation, it is essential to investigate input data preprocessing to improve the ANN model. In this paper, a hybrid model coupled with singular spectrum analysis (SSA) and backpropagation ANN is proposed (SSA-BP-ANN). The advantage of this model is that the SSA of finite-length SPI sequences does not require the adoption of boundary extensions to suppress boundary effects, while the most predictable components of the SPI can be efficiently extracted and incorporated into the model. The proposed SSA-BP-ANN model is tested in case studies at three meteorological stations in Northern Shannxi Province, China. The results show that the SSA-BP-ANN model can produce more accurate predictions than the BP-ANN model. In addition, the performance improvement of SSA on the BP-ANN model is slightly better than wavelet decomposition and empirical mode decomposition. This new hybrid prediction model has great potential for promoting drought early warning in arid regions. [ABSTRACT FROM AUTHOR]

Shaanxi is one of China's most important cradles of civilization. The main vein of Chinese culture is rich history and culture, and brilliant red culture embodies the essence of socialist core values. It is still relatively weak to deeply analyze the related research of Shaanxi Province's cultural province construction on the basis of studying the achievements of cultural development in foreign countries and China and combining with the reality of Shaanxi Province. In this paper, a BPNN (BP neural network) model is selected to study the comprehensive evaluation of tourism competitiveness of smart tourism cities, and the software is used to realize the simulation of the comprehensive evaluation system of tourism competitiveness of smart tourism cities, which more comprehensively and objectively reflects the level of comprehensive competitiveness of each city. It is believed that there are some problems in Shaanxi regional cultural communication, such as insufficient exploration of content resources, insufficient communication channels, and low audience awareness, hoping to provide ideas and reference for further exploring the promotion of cultural communication power. [ABSTRACT FROM AUTHOR]

[Display omitted] • Expression of geological map information in the form of knowledge graphs to shown regional geological characteristics and connections. • Using the knowledge embedding method to embed the geological map knowledge in order to show the mineralization characteristics. • Knowledge and geochemical data was aligned in space by knowledge embedding gridding to realize the forward integration of knowledge and data, and to realize bi-directional knowledge and data-driven mineral prospectivity. The knowledge graph in geological applications is highly regarded, and its usefulness requires the support of geological survey data. Therefore, this paper proposes a mineral prospectivity mapping (MPM) method that integrates geological map knowledge graphs with geochemical data. The geological map knowledge graph is used in the vectorized form as knowledge features in the training of the mineral prediction model. It is also used for knowledge-based ore-forming interpretation of prospective areas, achieving bidirectional application of knowledge in prediction and interpretation of prediction results. Unlike most knowledge graphs, the geological map knowledge graph represents spatial correlations and geological features in the form of "entity-relation-entity" triplets, with geological map units as entities and assigned geological attributes. Based on this, an MPM process driven by knowledge graph and data is proposed: (1) Convert the geological map knowledge graph into low-dimensional vectors using node2VEC. (2) Align geological knowledge with geochemical data spatially through knowledge embedding gridization, achieving a forward fusion of knowledge and data. (3) Collect the integrated data using window sampling as the training dataset for DenseNet to train the mineral prospection model. A case study was conducted to demonstrate the advantages of the method for producing a potential map linked to gold mineralization in the Rao Feng area, Shaanxi Province, China. The results show that the prospective areas with knowledge graph embedding and geochemical data are better and delineate six unmineralized prospective areas. Ore-forming interpretations based on knowledge graph information were conducted on the prospective areas, demonstrating strong consistency between the ore-forming geological features of the prediction areas and known mineral deposits. [ABSTRACT FROM AUTHOR]

Reliable weather forecasting is quite important for sectors with weather-dependent decision-making. To capture unknown and complex dependencies from multiple spatiotemporal factors, i.e., autocorrelated, meteorological causal, meteorological spatial factors, this paper proposes a spatiotemporal feature extraction and fusion network inspired by humans' multi-level cognition process, namely, SFEF-Net, including the data pre-processing stage, transfer pre-training stage, spatiotemporal feature extraction stage, and spatiotemporal feature fusion stage. Specifically, inspired by humans' empirical analysis, the 24 Solar Terms knowledge and Pearson correlation coefficient analysis are utilized to respectively select input timestamps and influencing factors in the first stage. Inspired by humans' associative learning, a Long Short-Term Memory Network (LSTM) layer with powerful remember capability is trained via weather data from multiple neighbored monitoring stations in the second stage, and further is transferred for better feature extraction. Inspired by humans' independent analysis, every factor is separately captured and analyzed via the pre-trained LSTM layer in the third stage, which also coincides with the philosophical idea of divide and conquer. Inspired by humans' comprehensive consideration, extracted features are fused level by level via the attention mechanism with dynamic weights in the fourth stage, which avoids invalid dependencies between multiple features and overfitting. The real-world daily average air temperature forecasting in Shaanxi Province, China is taken to demonstrate the SFEF-Net beyond 12 baseline methods. Additionally, forecasts of drastic change period, ablation analysis, multiple steps, and different stations further present the effectiveness of the SFEF-Net. [ABSTRACT FROM AUTHOR]

Accurate acquisition of in-situ soil water content is of great significance for mastering the water content distribution of unsaturated soil and understanding soil engineering properties. The actively heated fiber-optic (AHFO) method has recently become a research focus because of the capability to realize distributed and real-time measurement of soil water content. However, most reported AHFO systems have been coupled to distributed temperature sensing (DTS) which does not allow for remote measurements with high spatial resolution. In this paper, a new AHFO method based on the quasi-distributed fiber Bragg grating (AHFO-FBG) technique is proposed for the large-scale in-situ measurement of soil water content. An AHFO-FBG in-situ monitoring system is developed which consists of a sensor module, heating module, data acquisition and transmission module, and data processing module. The established system is applied to a loess slope in Yan'an City, Shaanxi Province, China to monitor its water content distribution in real time. The effectiveness of the monitoring system is verified and the water content distribution of the monitored loess slope are analysed. The in-situ measurement results indicate that in the spatial dimension, the water content in the top and bottom of the slope is low, and that near the scarp is high; in the time dimension, the water content in winter is low while that in autumn and spring is high. The monitored results also suggest that soil water evaporation in winter can significantly enhance the spatial distribution difference of soil water content. • The AHFO-FBG soil water content in-situ monitoring system was developed. • The in-situ monitoring system was applied to a loess slope in Yan'an, China. • The loess water content distribution is mainly affected by climate and topography. • The AHFO-FBG method is much better than neutron scattering method in surface soil. • Large-scale and remote measurement of soil water content was achieved by the system. [ABSTRACT FROM AUTHOR]

In the background of growing rural domestic waste pollution, encouraging the source classification of rural domestic waste is a critical way to address the inadequacies of rural environmental problems. Using the micro-survey data of rural residents in Shaanxi province, China, this paper explores the decision-making behavior (classification willingness and degree of classification) of rural residents' domestic waste through a double-hurdle model (DHM). The results show that among the 1374 rural residents, 1274 samples are willing to be sorted and put into place. Of these, 45.21% of the rural residents are eager to classify household waste into four categories, namely recycling or saleable, food waste or perishable, toxic and harmful, and others. Besides, household income has a significantly negative impact on the domestic waste classification willingness of rural residents while the number of education years positively impacts the degree of rural domestic waste classification. It is an indication that the sense of environmental responsibility significantly and positively influences the decision-making behaviors of rural residents, not only promoting their willingness to classification but also increasing their degree of classification; the psychological perception of rural residents about the pollution of domestic waste significantly increases their willingness and degree of classification. Policy implications are further discussed. [ABSTRACT FROM AUTHOR]

Interferometric synthetic aperture radar (InSAR) technology can obtain one-dimensional surface displacements in the radar line of sight (LOS). In the field of mining subsidence, large 3D movements often occur at the same time, and hence InSAR derived one-dimensional LOS displacements can hardly reflect the actual surface motion in mining areas. To realize the monitoring of three-dimensional large surface displacements in mining areas, a method for monitoring three-dimensional large surface displacements in mining areas that combines SAR pixel offset tracking (OT) and an improved mining subsidence model is proposed in this article. First, a new functional relationship between surface subsidence and horizontal movement combined with the characteristics of the overburden rock stress and the deformation characteristics of the fractured rock mass in coal mining areas is established. Then, a three-dimensional surface deformation model is established based on the proposed relationship between surface subsidence and horizontal movement and the radar projection equation, and finally, the optimal parameters of the deformation model are inverted iteratively using LOS deformation results obtained by OT method to retrieve the three-dimensional large displacements of the surface. The significant advantage of the method proposed in this article is that it can accurately acquire the 3D large surface displacements using only two SAR amplitude images with the same imaging geometry. To verify the accuracy and reliability of the proposed algorithm, two scenes of high-resolution spotlight TerraSAR-X images are used in this paper to conduct a three-dimensional surface displacement monitoring experiment on a working panel in the Daliuta mining area in Shaanxi Province, China, based on the proposed method. Experimental monitoring results show that the maximum surface subsidence is approximately 4.5 m, and the maximum horizontal movements in the strike and dip directions are approximately 1.4 m and 1.2 m, respectively. Using GPS measurements to verify the monitoring results, the root mean square error (RMSE) of vertical subsidence is 6.8 cm, and the RMSE of horizontal movement is 7.1 cm. Compared with those in the original mining subsidence model, the accuracies of vertical subsidence and horizontal movement in the proposed model are increased by 28.2% and 37.5%, respectively, which proves the reliability and accuracy of the proposed method. [ABSTRACT FROM AUTHOR]