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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]

This paper studied the characteristics of the carbon emission of an industrial wastewater treatment plant (IWWTP) and a domestic WWTP (DWWTP) located in a high-tech industrial park of Shaanxi Province, China. The results showed that the total carbon emissions of the IWWTP and DWWTP were 10.13 kg/t and 1.84 kg/t in 2020, respectively. Indirect carbon emissions play a dominant role in the total carbon emission of the IWWTP, which accounts for about 97.6% of the total amount. The direct carbon emissions of greenhouse gases (e.g., CH4, N2O) account for about 62% of the total carbon emissions in the DWWTP, followed by the indirect carbon emissions generated by electricity consumption (31.06%) and chemical consumption (6.94%). Additionally, the centralized recycling and re-utilization of the wastewater could achieve 1.06 kg/t and 1.16 kg/t of carbon emission reduction in the IWWTP and DWWTP, respectively, while the carbon emissions of the DWWTP are inversely proportional to the treatment capacity. Therefore, it is of great value to collect and utilize intensively the recycled water to achieve the goal of regional carbon emission reduction and carbon neutralization of WWTPs in industrial parks. [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]

This paper investigates the impact of e-commerce participation on household development resilience using a sample of 1229 households in the Shandong and Shaanxi provinces of China in 2022. It constructs the developmental resilience index of farm households from three dimensions of economy, society and culture using the entropy method, and establishes a counterfactual framework using the Propensity Score Matching (PSM) method. The results suggest that participation in e-commerce has a significant and positive impact on farming household development resilience. The PSM method estimates that participation in e-commerce increases the developmental resilience of farming households by 9.63% compared to non-participation, with economic, social, and cultural resilience increasing by 9.29%, 9.84%, and 9.92%, respectively. The robustness test results confirm the findings. Further analysis reveals that participation in e-commerce enhances farm household development resilience through three mechanisms: improving economic efficiency, network relationship linkage, and risk appetite. Heterogeneity analysis shows that the impact of e-commerce participation on household development resilience varies among farmers with different endowment constraints. In particular, farmers with more years of education and cooperative members benefit more from e-commerce participation, especially live and platform e-commerce. [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]

With the gradual improvement in coal mining efficiency, the disturbance of groundwater systems caused by high-intensity mining also increases, leading to challenges in maintaining mine safety and protecting water resources in mining areas. How to accurately describe the dynamic changes in the groundwater system under mining and quantitatively predict mine water inflow are currently major problems to be addressed. Based on a full analysis of the response characteristics of a groundwater system to the extraction disturbance, this paper presents a new method to establish a mine hydrogeological conceptual model that can accurately represent the water inrush process. The unstructured-grid package of MODFLOW is used to accurately characterize the formation structure and finally make accurate water inflow predictions. Taking the Caojiatan coal mine in Shaanxi Province, China, as an example, a numerical model of unstructured water inflow is established, and the changes in the water inflow source and intensity are quantitatively evaluated. Compared with the traditional water inflow prediction method, the prediction accuracy of the new model is improved by 12–17%, which is achieved by detailing the response of the complex groundwater system under high-intensity mining conditions. The method presented in this paper has great significance and applicatory value for obtaining a comprehensive understanding of the disturbance characteristics of human underground engineering activities (e.g., coal mining) on groundwater systems, as well as accurately predicting water inflow. [ABSTRACT FROM AUTHOR]

Tea is a non-alcoholic beverage popular among Chinese people. However, due to the application of chemical and organic fertilizers in the tea planting process, the environment pollutionaround the tea plantation, and the instruments used in the processing, heavy metal elements will accumulate in the tea, which brings health risks for tea consumers. This study summarized heavy metal concentrations from 227 published papers and investigated the current contamination status of tea and tea plantation soils, and, finally, the risk of heavy metal exposure to tea consumers in China is assessed, in terms of both non-carcinogenic and carcinogenic risk. The average contamination of six heavy metals in tea—arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), and lead (Pb)—were 0.21, 0.14, 1.17, 14.6, 0.04, and 1.09 mg/kg, respectively. The areas with high concentrations of heavy metals in tea were concentrated primarily in southwest China, some areas in eastern China, and Shaanxi Province in northwest China. The non-carcinogenic risks of heavy metals in tea are all within safe limits. The national average HI value was 0.04, with the highest HI value of 0.18 in Tibet, which has the largest tea consumption in China. However, the carcinogenic risks of Cd in Shaanxi Province, Anhui Province, and southwest China exceed the acceptable range, and due attention should be given to these areas. [ABSTRACT FROM AUTHOR]

This paper examines the impact of institutional pressure (IP), top management support (TMS), green supply chain management practices (GSCM), and supply chain competitive advantage (SCCA) on corporate environmental performance (EP). We also analyze the mediation effect of GSCM on the interplay between TMS and EP. Additionally, the paper also provides an analysis of the moderating role of SCCA between IP and EP. To attain the objective of this research, we assembled data from 710 business entities within the Shaanxi province of China utilizing a survey design approach. The structural equation model (SEM) was applied to test and assess the hypothetical outline. The study outcomes empirically show that TMS, GSCM, and SCCA positively and significantly impact EP. Interestingly, our study found an insignificant association between IP and EP. The study's results also demonstrate that IP directly relates to top management support. Moreover, the study's empirical findings reveal that GSCM positively mediates IP and EP. The study findings show that SCCA shapes IP and EP's connection. Accordingly, the practical implications of our study's findings suggest that business managers, investors, and government agencies must know the importance of adopting sustainable practices within the supply chain. Business managers must take action to integrate environmental criteria into supplier selection, evaluate suppliers' EP, and collaborate with eco‐friendly suppliers. Hence, government agencies, stakeholders, and business managers can use this information to shape regulations and policies that encourage businesses to adopt sustainable supply chain practices. Offering incentives such as tax benefits or grants for sustainability initiatives can also promote adoption. The study recommends that a business culture that targets improving EP due to IP and top management support is essential in achieving GSCM practices, thereby promising competitive advantage. [ABSTRACT FROM AUTHOR]

Southwest China is one of the three largest continuous karst clusters in the world; therefore, studies on karst rocky desertification in this area are very important. For more than 20 years' control, the decreasing area and risk of karst rocky desertification has contributed to the continuous ecological improvement. Nowadays, studies on rocky desertification mainly focus on the eight provinces in Southwest China, which have been designated as rocky desertification monitoring areas by the Chinese government. After the first phase of the comprehensive control project for karst rocky desertification in 2016, the expansion trend of rocky desertification in the southwest region was effectively curbed. Subsequent articles published tend to focus on analyzing the current situation, comprehensive management, or species adaptability of rocky desertification monitoring areas. However, the Qinba region in Shaanxi Province is located outside the monitoring area. In the process of studying the karst geological relics of the Zhenba Sanyuan Tiankeng Group, signs of rocky desertification have been found, but there still exists a research gap in the investigation and research on karst rocky desertification in this area which is one of the areas with the richest biodiversity in China, known as "ecological lung", "central water tower" and "biological gene bank". Unfortunately, this area is burdened with poverty, so the investigation and study of karst rocky desertification in the Qinba region of Shaanxi Province is of great significance to ensure green and high-quality development and ecological civilization construction. In this paper, by analyzing the current situation of karst rocky desertification in Southwest China, we summarized its harm to the ecological environment and social economy, clarify natural and human factors resulting in rocky desertification, and integrate the typical treatment experience in Southwest China. We also introduce three technical methods, including remote sensing interpretation, UAV remote sensing survey and analysis of carbonate dissolution rate, to provide a scientific basis for studies on karst rocky desertification in the Qinba region of Shaanxi Province. Study results show that the area of karst rocky desertification in the Qinba region covers 63.37 km², and the areas of severe, moderate and mild rocky desertification cover 17.97 km², 21.60 km² and 23.80 km², respectively. Based on the survey results, there are both regional differences and some similarities in distribution patterns in the areas of rocky desertification development. Specifically, the degree of rocky desertification in the limestone area is more severe than that in the dolomite area. It is also more severe in the area with developed water system than that in the arid and semi-arid area, and the more active the new structure is, the more severe the rocky desertification is. Compared to the Southwest China, the degree of karst rocky desertification in the Qinba region of Shaanxi Province is relatively light, with a smaller distribution area, mainly due to the less rainfall in the study area. The karst rocky desertification in Beiyang mountain of Zhen'an county is the most severe, with an area of 7.28 km². In the 1960s, a large-scale free-range of livestock severely damaged vegetation. The indiscriminate deforestation by humans further exacerbated the process of rocky desertification. The rocky desertification in Hailuogong village of Shanyang county is also severe, covering an area of 5.83 km², because the landform in this area is a typical peak-cluster depression, which is likely developed into rocky desertification. The contradiction between people and land needs to be solved urgently. In conclusion, more monitoring and research efforts are needed in Beiyang mountain and Hailuogong where the rocky desertification is severe. Firstly, we should clarify the causes of rocky desertification in the Qinba region and compare them with the causes in Southwest China to determine whether the rocky desertification is mainly resulted from natural factors or human factors. Secondly, we should know how to clarify the causes of karst rocky desertification in the Qinba region; for example, we can dynamically monitor the change of rock desertification by field verification, remote sensing interpretation, climate change analysis, etc. We can also calculate the contribution rate of each influence factor by geographical detector model. Thirdly, we should further study influence factors of karst dissolution rate. We can monitor physical and chemical properties of soil (soil moisture, carbon dioxide concentration, pH, organic matter content and porosity) in areas with moderate to severe rocky desertification, and analyze the relationship between dissolution rate and physical and chemical properties of soil in rocky desertification areas. Finally, in order to provide basic data for carbon neutrality research in Shaanxi, we should conduct studies on the carbon sink of rocky desertification areas in the Qinba region, with the methods such as dissolution test pieces and hydrochemical runoff. [ABSTRACT FROM AUTHOR]

As a new concept for systematically evaluating ecosystem services, Gross Ecosystem Product (GEP) provides an effective means to comprehensively reveal the overall status of the ecosystem, the impact of economic activities on the ecological environment, and the effectiveness of ecological protection efforts. GEP accounting has been conducted in various regions; however, GEP's application in natural reserves still requires further exploration. Taking the Qinling Mountains as the research area, this paper aims to assess the relationship between GEP and economic development on the basis of the GEP accounting system. The results indicated that: (1) From 2010 to 2020, GEP tended to increase continuously and exhibited a distribution pattern with high value regions in the east and west, and low value regions in the north and south. (2) Over the years, the coupling coordination degree between GEP and GDP was in a consistent upward trend. In 2020, a good coupling coordination state between GEP and GDP was achieved in most districts and counties. (3) With the relative development between GEP and GDP, the social economy of most districts and counties lagged behind GEP in 2010. The number of districts and counties lagging in GEP in 2020 increased, while the number of regions with a balanced development of GEP and GDP was still relatively discouraging. (4) In general, elevation, contagion, temperature, population density, and precipitation were the main drivers of coupling coordination degree between GEP and GDP. If the relationship between economic development and ecological environmental protection can be reasonably balanced, it will further promote the sustainable development of nature reserves, and provide a scientific basis for sustainable policy-making in other similar areas. [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]

To solve the problem of credit rationing for farmers that shackles the transformation and upgrading of the agricultural industry and to improve the effect of agricultural industry chains in helping farmers, this paper empirically examines the effect of joining agricultural industry chains on supply-based and demand-based credit rationing for farmers, using the probit and tobit models based on the microscopic research data of 991 farmers in Shaanxi Province, China, and explores its specific effect mechanism. The study finds that agricultural industry chains can increase farmers' credit by reducing the information asymmetry between farmers and banks, reducing agricultural business risks, and forming effective collateral and guarantee mechanisms, and that they have significant mitigating effects on farmers' supply-based quantity rationing and demand-based price rationing, risk rationing and transaction cost rationing. Credit enhancement mechanisms such as information systems, commercial credit, orders, guarantees, production services and government support in agricultural industry chains have significant effects on alleviating farmers' credit rationing, while insurance has limited effects on alleviating farmers' credit rationing. There are differences in the effects of agricultural industry chains on alleviating various types of credit rationing of heterogeneous farmers in terms of scale, and the effects of joining agricultural industry chains on alleviating supply-based and demand-based credit rationing of large-scale farmers are more obvious than those of small farmers. Compared with the existing studies, this paper incorporates the credit rationing produced from farmers' own reasons into the analysis framework, and introduces credit-enhancing variables of agricultural industry chains to test their specific mechanisms on farmers' credit rationing. The findings of this study can provide a theoretical basis for promoting the innovation of financial models of agricultural industry chains, which is of great practical significance for improving the system of agricultural industry chains in developing countries, strengthening the role of industrial chains in absorbing small farmers, and promoting the modernization of agricultural industries with financial assistance. [ABSTRACT FROM AUTHOR]

As a product of the deep integration of digital technology and financial services, digital finance provides vital financial support for rural revitalization and increasing farmers' income. Based on the survey data of 1030 professional apple growers in the typical areas of Shaanxi Province, this paper empirically tested the impact of digital financial involvement on professional farmers' income, and its mechanism. The study found that digital finance significantly impacted the growth of professional farmer households' total incomes. However, this impact was not achieved by directly increasing property income and transfer incomes, but through two indirect ways: first, digital finance promoted productive agricultural investment, which further promoted the increase in agricultural income; secondly, digital finance further increased the income of self-operated industry and commerce by promoting the entrepreneurship of professional farmer households. Furthermore, the heterogeneity analysis showed that professional farmers with high education levels, large-scale farmland operations, and high levels of agricultural mechanization participate in digital finance, which plated a more significant role in promoting their total household income. From the perspective of different types of digital financial services, mobile payment and digital credit could promote increases in the income of professional farmers, but the income increase effect of digital wealth management has not yet been shown. [ABSTRACT FROM AUTHOR]

Both in Germany and in China, there is strong expertise regarding the different aspects of forest management, as well as forest products management. Nevertheless, forestry in both countries is facing challenges, some of which are regional, but many of which are shared. Therefore, experts from both countries (Technical University of Munich Germany; Northwest A&F University Yangling, China; Forestry Academy of Shaanxi, China; Thünen Institut, Germany; FEDRC GIZ Forest Policy Facility (Forestry Economics Development and Research Center of the Deutsche Gesellschaft für Internationale Zusammenarbeit GmbH), Germany; and Center for Natural Forest Protection in Shaanxi, China) met to share their knowledge and deduce recommendations for future multifunctional forest management for the temperate zone. The workshop, held at the Northwest A&F University in September 2018, included presentations and intensive discussions, as well as a field tour. The results of the workshop that are summarized in this white paper are meant to provide an overview of the multi-faceted nature of the topic for interested scientists and forest practitioners, describe tools that can be used to analyze various aspects of multifunctionality and, in an exemplary fashion, highlight gathered experience from long- and short-term experiments. Included are social demands, economic goals, and scientific baselines. The topics reach from economic evaluations of forest ecosystem services over forest management practices, including afforestation, restoration, and preparations to face climate change, to wood/forest products utilization and participation of local people for poverty reduction. Overall, an optimistic picture emerges, showing that by using adapted forest management practices, which try to embrace the concept of multifunctionality, various use schemes and demands can be integrated at single sites, allowing us to achieve both environmental protection and productive forests, including societal demands, as well as aspects of tradition and national identity. [ABSTRACT FROM AUTHOR]

An anti-slide pile is a common landslide control measure. Compared with the full-length pile whose top extends to the ground, the buried pile is more optimal in internal force distribution, saves material and has remarkable economic benefits. At present, there is a lack of in-depth theoretical analysis on the pile length of the load section of double-row buried piles. In order to establish the design calculation method of pile length in the load section of double row buried piles, this paper is based on the failure mode of overtopping. The design equation of load section pile length is obtained by using the transfer coefficient and limit equilibrium method. Taking a landslide in Yan'an City, Shaanxi Province, China, as an example, the reliability and economics of double-row buried piles are verified by comparing the treatment effects of single-row, double-row and double-row buried piles, and the engineering design is completed. The results show that the landslide control project using the design calculation method can meet the requirements of slope stability and at the same time save a quarter of the material compared with the double row of full-length piles. The engineering example proves the rationality and practicability of the design method and provides engineering reference value for the use of the double-row buried anti-slide pile structure in large-scale landslide treatment. [ABSTRACT FROM AUTHOR]

The study of the ecological effects of the Sloping land conversion program (SLCP) has great significance for afforestation optimization policies based on cost-effectiveness. This paper uses the panel fixed effect model and the panel threshold model to study the ecological effects of fiscal investments in the SLCP at the county level in Shaanxi Province of China. The regional ecological performance indicated by the normalized difference vegetation index (NDVI) has improved after the implementation of the SLCP, but the vegetation suffers degradation risks due to the cessation of subsidies. The results demonstrate strong support for a time lag effect, an effect of diminishing marginal returns, and a threshold effect whereas a significant but negative direct effect of SLCP's fiscal investments on the vegetation. Specifically, it takes approximately four years after fiscal investments for the NDVI to realize the greatest investment performance. The marginal contribution of fiscal investments to ecological performance reveals an increasing trend initially, followed by a decreasing trend. In addition, the ecological effects of fiscal investments in the SLCP are moderated negatively by ecological endowments. The results indicate that fiscal investments in the SLCP should consider its cost-effectiveness in policy design and improvements. [ABSTRACT FROM AUTHOR]

Previously conducted studies have established that the early warning of water inrush is crucial for the prevention and control of mining water catastrophes in the panel. In order to ensure the safety of coal mining, in this paper, monitoring indicators were determined using the sensitivity analysis method, and then a multi-indicator early-warning model for water inrush was established mainly based on the geological data of the Yanghuopan coal mine. The monitoring stage of the early-warning model should be determined according to the distance between the monitoring borehole and the mining position. Then, the development of a water-conducting fracture zone and the fluctuation and stochastic oscillator of monitoring indicators are comprehensively analyzed to determine the early-warning level. A multi-indicator early-warning model was applied to panel 30302 of the Yanghuopan coal mine and panel 1304 of the Zhaoxian coal mine in the Yushen mining areas. The abnormal warning of the water disaster in panel 1304 was sent 3 days before the disaster, which shows the effectiveness of the model. It can provide a reference for the development of an early-warning model for mine water inrush in Yushen mining areas. [ABSTRACT FROM AUTHOR]

As underground engineering extends into the western and deeper regions of China, more and more Luohe Formation sandstone layers will be encountered, which have weak cementation and high water content. It is a significant challenge to apply the open TBM, and the support system is crucial in determining whether TBM can excavate quickly and safely. Therefore, in order to optimize the support scheme, this paper analyzes the pore structure and porosity through CT scanning, the results indicate that the volume percentage of pores ≥34 μm is 2.3% and 1.5%, respectively, the large pore apertures are predominant, the surrounding rock has strong permeability, and there is a high risk of rock burst and roof collapse accidents, hence requiring reinforced support measures. On this basis, numerical simulations were conducted to evaluate the support effectiveness. The results show that replacing the "bolt + mesh" with a "bolt + cable + mesh + steel belt", and replacing the top three bolts with 7.3 m anchor cables, can better control the deformation and provide sufficient thrust force for the TBM, ensuring excavation speed. After the implementation of this scheme at the Kekegai coal mine in Shaanxi, China, the TBM excavation speed increased by 70%, from the previous 10 m/day to 17 m/d, significantly reducing the project duration and construction costs. [ABSTRACT FROM AUTHOR]

The production mode of "high input, high yield and high waste" in the agricultural system poses a serious threat to the environment and the quality of agricultural products. Accelerating the adoption of green agricultural technology (GAT) by farmers is an emergency measure. However, according to microsurvey data, many farmers give up GAT within a year after adopting it. The implementation of this measure has been anticlimactic. Based on a survey of 1138 kiwi growers in Shaanxi Province, China, this paper builds a theoretical model and conducts empirical exercises to gain insight into the effects of perceived value, government support and their interaction with kiwi growers' sustainable application of GAT. We find that perceived value and government support have a significant impact on the sustainable application of GAT. Government support plays a moderating role in the influence of perceived value on the sustainable application of GAT. Furthermore, in order to overcome the potential endogeneity problem caused by the two-way causal relationship between subjective variables, "owning a smartphone" was selected as the instrumental variable. The 2SLS model was used for endogeneity analysis, and the OLS model was used for the robustness test. This paper discusses the relevant theories and policy implications of environmental management. [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]

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]

Rural areas in Northwest China have always been the main concentration of poverty-stricken people in China. In 1986, China listed 665 poor counties (mostly in the northwest), and successively launched the actions of "Volunteer Teaching in Western China" and "Great Development of Western China" to help underdeveloped areas get rid of poverty. At present, the number of poor counties has been reduced to 52. In 2014, the Chinese government proposed to comprehensively improve the rural living environment by 2020. Through in-depth investigation and visit to 11 districts (counties) of Yulin City, Shaanxi Province, China, this study puts forward a set of index system suitable for evaluating the human settlements in underdeveloped rural areas and constructs a comprehensive evaluation model by using a variety of mathematical methods. Using the combination of accurate evaluation and fuzzy comprehensive evaluation, this paper makes a horizontal evaluation on the residential environment of each district (county) in Yulin City, and a dynamic evaluation on the overall development level of livable environment in Yulin City in recent 9 years. Finally, using qualitative and quantitative analysis methods, this paper discusses the shortcomings, available advantages and development prospects in the construction of human settlements in Yulin City, and concludes that the key to improving rural human settlements is to develop township enterprises. This study is an empirical analysis of the government's long-term poverty alleviation effect, summarizes experience and finds out existing problems, so as to provide basis and reference for the government's poverty alleviation in future. [ABSTRACT FROM AUTHOR]

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Bidder collusion seriously undermines the fair competition of the construction project market, and effective identification of collusion behaviors is of vital importance to the implementation of proactive regulation and supervision. In this paper, the data of construction project bidders from 2011 to 2018 are selected in Shaanxi Province, China, and a bidder network of construction projects is constructed. The collusion suspicion of bidders is analyzed from the macro-, meso-, and microlevels. The results show that the bidder network has features as small world at macrolevels, and it is easy for bidders to involve in collusion. The network community formed by construction, supervision, and survey and design bidding enterprises is analyzed at the mesolevel, and the collusion of supervision enterprises is found to have the highest suspicion At the microlevel, the characteristic value judgment and community division are adopted to analyze the collusion suspicion, which is divided into high, medium, and low according to the possibility. Through a comparison with the actual data, it is found that the method proposed in this paper can effectively identify the collusion behavior of construction project bidders. This paper proposes red, yellow, and green warning mechanism and formulates hierarchical accurate management preparedness, which can provide some suggestions to help prevent bidders from colluding. [ABSTRACT FROM AUTHOR]

Desert lakes are important wetland resources in the blown-sand area of western China and play a significant role in maintaining the regional ecological environment. However, large-scale coal mining in recent years has considerably impacted the deposition condition of several lakes. Rapid and accurate extraction of lake information based on satellite images is crucial for developing protective measures against desertification. However, the spatial resolution of these images often leads to mixed pixels near water boundaries, affecting extraction precision. Traditional pixel unmixing methods mainly obtain water coverage information in a mixed pixel, making it difficult to accurately describe the spatial distribution. In this paper, the cellular automata (CA) model was adopted in order to realize lake information extraction at a sub-pixel level. A mining area in Shenmu City, Shaanxi Province, China is selected as the research region, using the image of Sentinel-2 as the data source and the high spatial resolution UAV image as the reference. First, water coverage of mixed pixels in the Sentinel-2 image was calculated with the dimidiate pixel model and the fully constrained least squares (FCLS) method. Second, the mixed pixels were subdivided to form the cellular space at a sub-pixel level and the transition rules are constructed based on the water coverage information and spatial correlation. Lastly, the process was implemented using Python and IDL, with the ArcGIS and ENVI software being used for validation. The experiments show that the CA model can improve the sub-pixel positioning accuracy for lake bodies in mixed pixel image and improve classification accuracy. The FCLS-CA model has a higher accuracy and is able to identify most water bodies in the study area, and is therefore suitable for desert lake monitoring in mining areas. [ABSTRACT FROM AUTHOR]

The implementation of China's rural homestead withdrawal policy has been a topic of great interest in recent years. However, little is known about its impact on farmers' homestead withdrawal behavior from the perspective of psychological resilience. This study aims to evaluate the impact of psychological resilience on farmers' homestead withdrawal behavior and to explore its mechanism and heterogeneity, as well as its impact on compensation choices. The research data was collected through a survey of 657 rural households in Shaanxi and Shandong provinces. The probit model and mediation effect model were used to analyze the data. The results demonstrate that psychological resilience positively affects farmers' homestead withdrawal behavior; this finding is robust. Specifically, the positive influence of stability and adaptability dimensions of psychological resilience is more significant. Moreover, the effect of psychological resilience varies across different family life cycles, and it has a stronger promoting effect on the homestead withdrawal behavior of child-raising families. Mechanism analysis indicates that psychological resilience can promote homestead withdrawal behavior by reducing farmers' land dependence consciousness and improving farmers' risk preferences. Finally, farmers with strong psychological resilience are more inclined to choose cash compensation. Based on these findings, this paper proposes targeted policy recommendations for rural homestead system reform. [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]

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]

Red tourism is a distinctive form of tourism in China. Its network attention serves as a typical indicator to measure the level of promotion and publicity for red tourism, as well as an important reflection of its influence. Understanding the network structure of red tourism is of significant importance for optimizing the spatial pattern of tourism and promoting the development of the tourism industry. Based on this, this study takes the classic red tourism attractions in Shaanxi province, China as an example and constructs a multi-source data network attention evaluation index. Additionally, it employs social network theory to explore the network attention and tourist flow characteristics of the case study area. Research shows that: (1) Overall, the network attention to case-based destinations is relatively low, and there are significant differences in network attention among different attractions. Spatially, the distribution of network attention is uneven. This is manifested by higher network attention to attractions in Yan'an city and lower network attention to attractions in other regions. (2) There are differences in the network attention of different types of attractions. High-level attractions have a higher level of online attention, while low-level attractions have a lower level of network attention. Additionally, archaeological sites tend to receive a higher level of online attention. (3) The network density of tourist flow is low, and the tourism connections between nodes are not closely linked. The linkage between core nodes and edge nodes in tourism is poor. Developed tourism routes only exist in core nodes. (4) Nodes such as Zaoyuan revolution site, Yangjialing revolution site, and Wangjiaping revolution site have a significant influence in the network structure. In addition, the integration and development between red nodes and non-red nodes have been achieved. (5) There is a correlation between network attention and tourist flow, as well as a 'misplacement' feature. Based on the characteristics of attractions, they can be divided into four types: bright-star attractions, cash-cow attractions, thin-dog attractions, and question attractions. Based on the above conclusions, this study proposes targeted development recommendations. [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]

It is crucial for the protection and sustainable development of villages in China to effectively determine the changes that have occurred in traditional villages' architectural features and the causes of such changes in order to provide timely feedback, correct protection planning, and construction in these villages. This paper analyzed quantitative indexes at three different scales in Lingquan village, namely construction land, public infrastructure, and the form, material, and color of roofs, using remote sensing images at different time points, drone shooting, and a field survey. It was found that the rate of change of the architectural features at the village and street levels were low, with an overall trend of improvement observed. However, the residential roof features at the building level showed more changes, with a trend of deterioration observed. It was also found that the active participation of the government was the main reason for the substantial improvement observed in the village's street-level features. Further, for residential houses, the lack of standard guidance for their protection and renovation, as well as the lack of protection awareness and participation mechanisms, were the main reasons found for the deterioration of the village's building-level features. Finally, the study forwarded some suggestions in order to provide reference value for the timely revision of protection strategies for many villages in China similar to Lingquan village. [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 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]

Land transfers play a vital role in determining the level of farm machinery service and variety selection by scattered land reduction and contiguous land enhancement, which are also conducive to poverty alleviation and welfare utilization. Based on the micro-survey data of 898 kiwifruit growers in Shaanxi Province, this paper analyzed the effect of land transfers on the adoption of new varieties by propensity score matching (PSM) technology. A stepwise regression method was used to test the mediating role of land scale and the moderating role of unmanned aerial vehicles (UAVs). The results suggest the following: (1) Farmers with land transfers had a significant positive effect on the adoption of new varieties, with a 12.5% increase in the likelihood of new variety adoption. (2) The impact of land transfers on the adoption of new varieties was partially mediated through land scale. (3) The positive moderating role of UAV services was empirically emphasized. With the goal of promoting the average income and boosting farmland productivity, the improvement of the land property rights trading market, joint efforts from government and rural cooperatives, and professional and regular training are proposed to optimize land-use structures and reduce machinery service costs, thereby encouraging farmers to adopt new, improved varieties. [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]

As unexpected events such as natural disasters, the COVID-19 pandemic, and overseas containment have caused inevitable shocks to the energy industrial chain and supply chain, the current global energy crisis is intensifying, and different countries and regions have adopted different strategies according to the characteristics of their own national resource endowments in order to cope with energy security. Maintaining the security of the coal industrial chain and supply chain is a prerequisite for energy security to be effectively ensured, considering the main position of coal in China's energy. Therefore, in the face of multiple uncertain risk factors under today's momentous changes, this paper constructs an industrial coal chain and supply chain resilience evaluation indicator system from the perspective of resilience, based on four representational capabilities of resilience, namely preparedness, absorptive capacity, recovery capacity, and adaptability, in order to profoundly understand and enhance the resilience of the coal industrial chain and supply chain. An integrated method combining Interval Type-2 Fuzzy Prospect Theory and Technique for Order Preference by Similarity to an Ideal Solution (Interval Type-2F-PT-TOPSIS) is proposed for evaluating the resilience level of the coal industrial chain and supply chain. In the case of Shaanxi Province in China, it was found that the worst level of resilience of the coal industrial chain and supply chain in Shaanxi Province was in 2018, and the best was in 2021. Finally, based on the evaluation results, recommendations are provided to the key nodes of the industrial chain and supply chain in Shaanxi Province with a view to improving their resilience levels to cope with uncertain risks. [ABSTRACT FROM AUTHOR]

Water inrush disasters in mining areas are one of the most serious geological disasters in coal mining. The purpose of this study is to study the establishment of a water chemical database and water inrush source discrimination model in the Weibei coalfield to provide the basis for regional hydrogeological conditions for future mining under pressure in the Weibei area, as well as a basis for the rapid identification of water inrush sources in the Weibei coalfield. In this paper, a conventional hydrochemical and trace element discrimination model for mine water inrush was established, and the hydrochemical characteristic files of the entire mining area were integrated. Based on 10 indicators, three hydrochemical discrimination models of rock stratum aquifers were established. Through the Mahalanobis distance test, it was found that the six selected variables, K+ + Na+, Mg2+, NH4+, Cl−, SO42−, and pH, have significant discrimination ability and good effect and can effectively distinguish the three main water inrush aquifers in the Weibei mining area. Then, the clustering stepwise discriminant analysis method was used to select 24 water samples and 14 trace element indicators from the conventional water chemistry test results. Based on principal component analysis, a principal component analysis discriminant model of trace elements was established for the four main aquifers. The accuracy and misjudgment rate of the Bayes multi-class linear discriminant using conventional ions as explanatory variables were 64.3% and 35.7%, respectively, showing a poor discriminant effect. On this basis, seven characteristic trace elements were analyzed according to Bayes multi-class linear discriminant analysis, the mutual influence and restriction relationship regarding the migration of these seven trace elements in the groundwater system of the mining area was determined, and the modified Bayes multi-class linear discriminant analysis model of trace elements for the water inrush source was established, which was more accurate than the conventional ion Bayes multi-class linear discriminant analysis model. The accuracy rate reached 92.9%. This research is of great significance for mine water-source identification and water-inrush prevention guidance. [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 completion of the relocation task, fully promoting the non-agricultural employment of relocated women is of great significance for improving the livelihood sustainability of relocated peasant households' and consolidating the results of poverty alleviation. Based on the sample data of 1616 rural households in southern Shaanxi Province, China, using the IV-Probit model, IV-Tobit model, and mediation effect model, this study empirically analyzes the impact and mechanism of participation in relocation on women's non-agricultural employment. The results show that by introducing an instrumental variable to solve endogeneity, participation in relocation has a significant positive impact on the behavior and intensity of women's non-agricultural employment. A mechanism analysis shows that training, public services, and land abandonment play a mediation role in the relationship between participation in relocation and women's non-agricultural employment. In terms of women's non-agricultural employment behavior, the mediation effects are 56.9%, 15.0%, and 11.0%, respectively. In terms of women's non-agricultural employment intensity, the mediation effects are 58.5%, 15.7%, and 11.6%, respectively. Based on the above findings, this study puts forward policy implications for follow-up relocation support, to further release the surplus women's labor forces and promote women's non-agricultural employment. [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]

As a direct indicator of vegetation photosynthesis, the fraction of absorbed photosynthetically active radiation (FPAR) serves as a critical input in a series of land surface models. While existing satellite FPAR products are generally at coarse resolutions ranging from 250 m to 1 km, operational FPAR products at fine resolution are urgently needed in studying land surface processes at the plot scale. However, existing methods for estimating fine-resolution FPAR were mainly designed for Landsat data, and few studies have attempted to develop algorithms for Sentinel-2 data. In particular, the operational estimation of decameter FPAR has a higher requirement for the algorithms in terms of generalizability, efficiency, accuracy, and adaptability to Sentinel-2 data. In this paper, we developed a retrieval chain on the Google Earth Engine (GEE) platform to estimate FPAR by learning the relationship between MODIS FPAR and Sentinel-2 surface reflectance. Scale-consistent multilinear models were used to model the relationship between MODIS FPAR and Sentinel-2 surface reflectance, and the model coefficients were regressed from the selected training samples. To account for the spectral and spatial characteristics of the Sentinel-2 data, we designed criteria for selecting training samples and compared different band combinations. Three strategies for band combination were used: (1) green, red, and near infrared (NIR) bands at 10 m resolution (i.e., three bands); (2) green, red, NIR, and red edge (RE) 1, RE2, and RE3 bands at 20 m resolution (i.e., five bands); and (3) green, red, NIR, RE1, RE2, RE3, shortwave infrared1 (SWIR1) and SWIR2 bands at 20 m resolution (i.e., eight bands). Meanwhile, the official Sentinel Application Platform (SNAP) method has also been implemented to estimate the Sentinel FPAR at 10 m and 20 m resolutions for comparison. Both methods were applied to the western Guanzhong area, Shaanxi Province, China, for FPAR estimation of all cloud-free Sentinel-2 images in 2021. The results show that the scaling-based method using five bands at 20 m resolution was the most accurate compared to the in situ measurements (RMSE = 0.076 and R² = 0.626), which outperformed the SNAP method at 10 m and 20 m resolutions and the scaling-based method using other strategies. The results of the scaling-based method using all three strategies were highly consistent with the MODIS FPAR product, while the SNAP method systematically underestimated FPAR values compared to the MODIS FPAR products. The proposed method is more ready-to-use and more efficient than SNAP software. Considering that the service of the MODIS sensor is overdue, the proposed method can be extended to alternatives to MODIS products, such as VIIRS and Sentinel-3 data. [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]

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]

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]

Transitions in animal exploitation patterns are caused by topographical and climatic variations on both macro and micro scales. This paper presents temporally and spatially contextualized faunal profiles from 27 sites in the Guanzhong (关中) region of Shaanxi province (陕西省), PRC which date from the Early Neolithic to the Bronze Age (ca. 6000–1000 BCE). Climatic and environmental data was cross-referenced with archaeological, archaeobotanical and (where appropriate) historical sources to examine the reasons for the clear micro-transitions observed. Faunal profiles from sites in the Wei River plain (渭河盆地), loess plateau, and the transitional zone between them were analyzed. Animal utilization was found to vary substantially between different zones during the period under analysis. The transition in praxis between the Wei River valley and the loess plateau was not gradual. The hilly transition zone was found to have its own distinct animal exploitation pattern. These spatio-temporal differences in animal exploitation were caused by changes in both the local microclimates and the topography of the landscape in which the communities were living. Some regions apparently reverted to 'earlier' animal exploitation patterns in response to climatic changes. These environmental factors were also augmented by internal social developments and interactions with neighboring communities. [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]

Low-permeability reservoirs are important to the future growth of oil and gas reserves and production in China. Predicting the effective stress, σe, in reservoirs is vitally important due to its considerable impact on reservoir development through hydraulic fracturing. This paper presents methods for predicting the σe field in ultralow-permeability reservoirs through reservoir–geomechanics coupling, which involve the simulation and coupling of the tectonic stress σ and pore pressure Pp fields based on three-dimensional (3D) geological models. First, 3D geological models were constructed based on basic data for the oilfield where the reservoir of interest is located. Then, finite element and finite difference simulations were performed to construct the σ and Pp fields, respectively, in the reservoir. Different types of initial σe were coupled based on 3D geological models. Subsequently, a dynamic σe field in the reservoir was established based on oilfield production data in conjunction with the transformation, optimization, and coupling of specific grid property parameters obtained from different numerical methods. Finally, the proposed methods were tested on real-world data acquired from well area X in an oilfield in Shaanxi Province, China. The results show that the proposed methods can be used to establish the σ and Pp fields in a reservoir based on 3D geological models combined with different numerical methods, and subsequently predict the σe value in the reservoir. [ABSTRACT FROM AUTHOR]