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China eliminated rural poverty under current poverty standards in 2020. However, compared with rural poverty, urban poverty in China has been somewhat neglected. This paper aims to discover the changes and determinants of multidimensional urban poverty in Shandong Province, a representative province in Eastern China. Using a nationally representative panel dataset, the China Family Panel Studies, and the Dual Cutoff method, this study creates a multidimensional poverty index with four dimensions and 11 indicators to measure urban poverty in Shandong Province. This paper discovers that while the incidence of multidimensional urban poverty in Shandong Province decreased from 47.62% in 2010 to 36.45% in 2018, the intensity of multidimensional poverty only decreased from 41.27% to 37.25%, which indicates the inadequacy of urban anti-poverty efforts in Shandong Province. This paper also uses logistic regression to identify the determinants of multidimensional urban poverty. The findings suggest that income, health, drinking water, and durable goods are the main determinants of multidimensional urban poverty in Shandong Province. Based on these findings, this study provides targeted recommendations for future urban anti-poverty policies in Shandong Province. [ABSTRACT FROM AUTHOR]

Maintaining and improving ecological resilience is of great practical significance for the Yellow River Basin to reduce potential ecological risks and deliver sustainable development. Based on the essential characteristics of evolutionary resilience, this paper developed an ecological resilience index system of "resistance-recovery-reconstruction-renewal" and calculated the ecological resilience of 75 prefecture-level cities in the Yellow River Basin from 2007 to 2021 with the improved TOPSIS method. Then the spatiotemporal evolution characteristics of ecological resilience were analyzed using the gravity center-standard deviation ellipse, Dagum Gini coefficient decomposition, and spatial autocorrelation analysis. Furthermore, the dynamic spatial Durbin model (DSDM) was used to investigate the influencing factors of ecological resilience. The main results are as follows: (1) The ecological resilience of the Yellow River Basin showed an overall fluctuating upward trend, and the average annual growth rate in the downstream region was larger than in the upstream and midstream regions. (2) Cities with similar levels of ecological resilience were distributed in a "large settlement, small scattered" pattern. The center of gravity shifted to the southeast, and the spatial distribution exhibited a "northwest-southeast" pattern and a trend towards an "east–west" pattern. The primary source of spatial differences was the intensity of transvariation. (3) The ecological resilience in the Yellow River Basin showed significant spatial clustering, with the H–H clustering area shifting from the Hubao-Eyu urban agglomeration to the Shandong Peninsula urban agglomeration, and the L–L clustering area mainly distributed around the Central Plains city cluster. (4) The ecological resilience of the Yellow River Basin exhibited significant snowball, spillover, and siphon effects in time, space, and space-time dimensions, respectively. In the short and long term, population density and openness significantly positively affected the ecological resilience of local and surrounding cities. Urbanization had a long-term effect on ecological resilience without a short-term effect. GDP per capita and industrial structure only imparted a significant positive influence on local ecological resilience. The negative spatial spillover of the intensity of financial investment in technological innovation gradually turned into a positive effect. [ABSTRACT FROM AUTHOR]

Winter wheat is a significant global food crop, and it is crucial to monitor its distribution for better agricultural management, land planning, and environmental sustainability. However, the distribution style of winter wheat planting fields is not consistent due to different terrain conditions. In mountainous areas, winter wheat planting units are smaller in size and fragmented in distribution compared to plain areas. Unfortunately, most crop-mapping research based on deep learning ignores the impact of topographic relief on crop distribution and struggles to handle hilly areas effectively. In this paper, we propose a cross-modal segmentation network for winter wheat mapping in complex terrain using remote-sensing multi-temporal images and DEM data. First, we propose a diverse receptive fusion (DRF) module, which applies a deformable receptive field to optical images during the feature fusion process, allowing it to match winter wheat plots of varying scales and a fixed receptive field to the DEM to extract evaluation features at a consistent scale. Second, we developed a distributed weight attention (DWA) module, which can enhance the feature intensity of winter wheat, thereby reducing the omission rate of planting areas, especially for the small-sized regions in hilly terrain. Furthermore, to demonstrate the performance of our model, we conducted extensive experiments and ablation studies on a large-scale dataset in Lanling county, Shandong province, China. Our results show that our proposed CM-Net is effective in mapping winter wheat in complex terrain. [ABSTRACT FROM AUTHOR]

The health of young people is crucial for the future and development of a nation. It is the collective responsibility and imperative mission of society to ensure the holistic well-being, both physically and mentally, of young individuals. Therefore, it is essential to thoroughly comprehend the factors that influence their health in order to expedite the exploration of effective solutions. The objective of this study is to comprehend the mechanisms that underlie the correlation between physical exercise behavior and psychological resilience among teenagers, while also examining the mediating role played by social sensitivity and need to belong. So put forward the hypothesis: (1) physical exercise behavior can positively predict the psychological resilience. (2) Social sensitivity and need to belong plays a mediating role between physical exercise behavior and psychological resilience. (3) Social sensitivity and need to belong plays a chain mediating role between physical exercise behavior and psychological resilience. Using the cluster sampling method, a total of 1106 students (with an average age of 15.7 and a standard deviation of 0.598) who met the requirements were surveyed from Shandong Province in China. Standard scales were utilized to assess Physical Exercise Behavior, Psychological Resilience, Social Sensitivity, and Need to Belong. For data analysis, Pearson's correlation analysis and bias-corrected percentile Bootstrap method were sequentially conducted. (1) The present study did not find any significant methodological bias, and the observed correlations between physical exercise behavior, psychological resilience, social sensitivity, and need to belong were all statistically significant; (2) Based on the self-determination theory, this study elucidates the relationship between physical exercise behavior and psychological resilience among teenagers. The findings indicate that physical exercise behavior positively predicts the need to belong and psychological resilience, while negatively predicting social sensitivity. Similarly, social sensitivity negatively predicts the need to belong and psychological resilience. Moreover, the need to belong directly and positively predicts psychological resilience. Importantly, all hypotheses proposed in this paper were empirically supported. (3) The indirect effect of the path mediated by social sensitivity is 0.009, while the indirect effect of the path mediated by need to belong is 0.033. Additionally, the combined indirect effect of both social sensitivity and need to belong as mediating variables is 0.014. (4) The cumulative sum of all these indirect effects amounts to 0.056. Based on the self-determination theory, we propose a chain mediation model, specially, physical exercise behavior can significantly positively predict psychological resilience, among which, social sensitivity and need to belong play a significant mediating role between Physical exercise behavior and psychological resilience. In addition, the adoption of good physical exercise behavior can enhance the psychological resilience of adolescents by diminishing social sensitivity and augmenting the need to belong. [ABSTRACT FROM AUTHOR]

The health of young people is crucial for the future and development of a nation. It is the collective responsibility and imperative mission of society to ensure the holistic well-being, both physically and mentally, of young individuals. Therefore, it is essential to thoroughly comprehend the factors that influence their health in order to expedite the exploration of effective solutions. The objective of this study is to comprehend the mechanisms that underlie the correlation between physical exercise behavior and psychological resilience among teenagers, while also examining the mediating role played by social sensitivity and need to belong. So put forward the hypothesis: (1) physical exercise behavior can positively predict the psychological resilience. (2) Social sensitivity and need to belong plays a mediating role between physical exercise behavior and psychological resilience. (3) Social sensitivity and need to belong plays a chain mediating role between physical exercise behavior and psychological resilience. Using the cluster sampling method, a total of 1106 students (with an average age of 15.7 and a standard deviation of 0.598) who met the requirements were surveyed from Shandong Province in China. Standard scales were utilized to assess Physical Exercise Behavior, Psychological Resilience, Social Sensitivity, and Need to Belong. For data analysis, Pearson's correlation analysis and bias-corrected percentile Bootstrap method were sequentially conducted. (1) The present study did not find any significant methodological bias, and the observed correlations between physical exercise behavior, psychological resilience, social sensitivity, and need to belong were all statistically significant; (2) Based on the self-determination theory, this study elucidates the relationship between physical exercise behavior and psychological resilience among teenagers. The findings indicate that physical exercise behavior positively predicts the need to belong and psychological resilience, while negatively predicting social sensitivity. Similarly, social sensitivity negatively predicts the need to belong and psychological resilience. Moreover, the need to belong directly and positively predicts psychological resilience. Importantly, all hypotheses proposed in this paper were empirically supported. (3) The indirect effect of the path mediated by social sensitivity is 0.009, while the indirect effect of the path mediated by need to belong is 0.033. Additionally, the combined indirect effect of both social sensitivity and need to belong as mediating variables is 0.014. (4) The cumulative sum of all these indirect effects amounts to 0.056. Based on the self-determination theory, we propose a chain mediation model, specially, physical exercise behavior can significantly positively predict psychological resilience, among which, social sensitivity and need to belong play a significant mediating role between Physical exercise behavior and psychological resilience. In addition, the adoption of good physical exercise behavior can enhance the psychological resilience of adolescents by diminishing social sensitivity and augmenting the need to belong. [ABSTRACT FROM AUTHOR]

Developing rural e-commerce is seen as an effective measure to revitalize the economies of rural communities and is beginning to spread in several countries. However, conditions in rural communities are limited and lack the necessary elements for its promotion. Alibaba Group's Taobao Villages, a remarkable achievement of China's rural e-commerce development, has demonstrated strong vitality and is receiving increasing attention. Therefore, this research study into a Taobao Village, which has been developing in Shandong Province for more than a decade, conducts an in-depth analysis of its development history to provide a reference for rural e-commerce promotion. This paper proposes an 'internal innovation & external support' analytical framework for presenting the growth process of the rural community, which can explain how to sustain longterm operations and enhance e-commerce competitiveness. In addition, the paper confirms that the development of a Taobao Village is led by local-villager entrepreneurs, and this rural development strategy can encourage a diversity of entrepreneurs to participate in entrepreneurship and competition, all of which are worthy of further research and replication. [ABSTRACT FROM AUTHOR]

In recent years, extreme rainfall events have frequently occurred frequently, and heavy rainfall can cause drastic changes in the troposphere. Therefore, achieving to achieve real-time high-precision numerical prediction of key tropospheric parameters during heavy rainfall has become a major problem in global navigation satellite system (GNSS) meteorology. In this paper, two extreme rainfall events in southern China (Guangdong region) and northern China (Shandong region) in 2022 are used as case studies. Twenty-four-hour real-time numerical forecasts of key tropospheric parameters (atmospheric weighted mean temperature (Tm), precipitable water vapor (PWV), and GNSS zenith tropospheric delay (ZTD)) are obtained using three models, namely, the HGPT2, GPT3, and WRF models. Two optimization models, i.e., WRFDA (am) and WRFDA (pre), are then constructed by assimilating two types of data (global upper air and surface weather observations and daily advanced microwave sounding unit A (AMSU-A) brightness temperature) based on the WRF model. The experimental results for heavy rainfall show that (1) the WRF model predicts the key tropospheric parameters with better accuracy than the HGPT2 and GPT3 models, and the WRFDA (pre) model predicts PWV and ZTD with the highest accuracy; (2) the WRFDA (pre) model achieves a higher accuracy than the WRF model in predicting PWV and ZTD, where the PWV prediction accuracy is improved relative to the WRF model (in the south: MAE: 32.7 %; RMSE: 33.9 %; MAPE: 36.8 %; in the north: MAE: 27.3 %; RMSE: 24.2 %; MAPE: 28.0 %); this model achieves an MAE of 2.17 cm and an RMSE of 2.70 cm in 24-h ZTD prediction in the south, while the MAE reaches 2.48 cm, and the RMSE is 3.18 cm in the north; (3) the models provide a higher forecast accuracy in the southern region than in the northern region for heavy rainfall. The WRFDA (pre) model provides a favourable ZTD accuracy at GNSS stations near the ocean, while the WRFDA (am) model provides a satisfactory ZTD accuracy at inland GNSS stations, and the WRFDA (am) model provides the highest ZTD prediction accuracy at GNSS stations above 100 m. [ABSTRACT FROM AUTHOR]

The frequent occurrence of extreme weather disasters under global climate change has greatly impacted agricultural production, caused crop yield and price fluctuations, affected the increase of farmers' income, and hindered the development of the rural economy. As a typical mountainous region in North China, Shandong Province is a major peanut-planting province. In recent years, the peanut planting area in Shandong Province has remained relatively stable at around 10 million hectares (approximately 6.67 million hectares), accounting for approximately 14% of the national peanut planting area. Affected by meteorological disaster risks and consequent price risks, peanut farmers in Shandong Province are faced with double threats of output and price. This study is aiming to analyze the income risks faced by peanut planting farmers in the northern regions of China and to develop a comprehensive understanding of the factors influencing their income variability. The study may investigate various aspects especially the market price fluctuations, socioeconomic factors affecting peanut farming and the correlation of the peanut pricing and the local insurance. The current policy-based peanut insurance makes it difficult to fully disperse risks and guarantee stable production with the permission of relevant government department. Therefore, based on the peanut yield and price data of Shandong Province from 1991 to 2017 and following the logical context of "meteorological disaster - yield risk - price risk - income loss - income insurance", this paper uses the Copula method to calculate the premium rate of peanut income insurance and finds that under the guaranteed level of 70%-90%, the pure premium rate is between 1.5%-4.15%. Compared with the current cost insurance with a flat rate of 4% in Shandong Province, the income insurance rate is generally lower than the current rate. Secondly, there are regional differences in income insurance rates. In addition, at a higher level of protection, the income insurance rate is higher. [ABSTRACT FROM AUTHOR]

As the largest carbon emitter in China's manufacturing sector, the low-carbon transition of the steel industry is urgent. CO2 capture, utilization, and storage (CCUS) technology is one of the effective measures to reduce carbon emissions in steel industry. In this paper, a comprehensive assessment model of source–sink matching-levelized cost in China's steel industry is constructed to evaluate the potential, economy, and spatial distribution of CCUS retrofits of blast furnaces in the BF-BOF steel industry. The results show that, if no extra incentive policy is included, the levelized cost of carbon dioxide (LCOCD) of 111 steel plants with a 420.07 Mt/a CO2 abatement potential ranges from −134.87 to 142.95 USD/t. The levelized cost of crude steel (LCOS) range of steel plants after the CCUS retrofits of blast furnaces is 341.81 to 541.41 USD/t. The incentives such as carbon market and government subsidies will all contribute to the early deployment of CCUS projects. The CCUS technology could be prioritized for deployment in North China, Northwest China, and East China's Shandong Province, but more powerful incentives are still needed for current large-scale deployment. The research results can provide references for the early deployment and policy formulation of CCUS in China's steel industry. [ABSTRACT FROM AUTHOR]

Based on China's green energy development strategy, this paper constructs a basic model of recycling and a channel expansion model for the circular economy foundation of Zaozhuang, Shandong Province, China. Through numerical simulation, it is found that each member of the supply chain should control the rate of price adjustment, otherwise it will cause market disruption. The model is controlled based on a chaos control method. Then, based on the fuzzy comprehensive evaluation method, an early warning system for the circular economy of Zaozhuang City is constructed. It is found that the economic development of Zaozhuang is a serious warning, resources are moderate warning, and the environment is not in an alarm state. In addition to paying attention to energy conservation and emission reduction of enterprises, the government should pay attention to creating awareness of energy conservation and emission reduction in society, and strengthen the technological investment in reducing pollutant emissions. This paper provides a strategic reference for the circular economy model in Zaozhuang, Shandong, China. [ABSTRACT FROM AUTHOR]

In order to realize rapid and accurate evaluation of drinking water quality, a small-scale water quality detection instrument is designed in this paper that can detect two representative water quality parameters: the permanganate index and total dissolved solids (TDS). The permanganate index measured by the laser spectroscopy method can achieve the approximate value of the organic matter in water, and the TDS measured by the conductivity method can obtain the approximate value of the inorganic matter in water. In addition, to facilitate the popularization of civilian applications, the evaluation method of water quality based on the percent-scores proposed by us is presented in this paper. The water quality results can be displayed on the instrument screen. In the experiment, we measured the water quality parameters of the tap water as well as those after the primary and secondary filtration in Weihai City, Shandong Province, China. The testing results show that the instrument can quickly detect dissolved inorganic and organic matter, and intuitively display the water quality evaluation score on the screen. The instrument designed in this paper has the advantages of high sensitivity, high integration, and small volume, which lays the foundation for the popularity of the detection instrument. [ABSTRACT FROM AUTHOR]

• Fracture evolution in dual gob-side entries varies spatially and temporally. • A formula to calculate arbitrary dip rock layer cutting angles was derived. • A technology based on the fracture evolution's turning points was proposed. • Differential roof cutting-anchor grouting boosts stability in dual gob-side entries. The coal pillar-free gob-side entry retention technology (GER), which enhances resource recovery rates and reduces the amount of tunnel excavation, has been applied in multiple mining areas in China. However, cases of implementing gob-side entry retention on both sides of a single working face are rare. The asynchronous extraction of long-distance working faces leads to significant differences in the stress environment of roadways on both sides, and uniform technical means are poorly adapted to the control of surrounding rock on both sides, affecting the safe and efficient production. This paper, taking the dual gob-side entry retention on both sides of the 61001 W working face with thick mudstone roofs in Zhao Guan Coal Mine, Shandong Province, as the engineering background, utilizes a combination of theoretical calculations, numerical simulations, and on-site detailed monitoring to analyze the uncoordinated deformation characteristics of the upper part bulging and the lower part concaving of the two roadways. It clarifies the differentiated spatiotemporal evolution law of the number of fractures and the development turning points at different depths of the surrounding rock of the two entries, revealing the differential deformation mechanism of the surrounding rock of the two entries caused by stress state and fracture development differences. A "cutting roof to relieve pressure-multilevel continuous anchor-grouting" combined control technology system is proposed. By cutting off the stress transmission of the roof through drilling and blasting, and then reconstructing the integrity of the surrounding rock and improving the rock strength with the help of anchor-grouting. With the application of this new technology, the deformation of the surrounding rocks of the two entries was reduced by more than 60 % and 29 %, respectively, and the maximum crack depth of the roof was controlled within 3 m, significantly enhancing the stability of the roadways. The research results of this paper provide a reference for the control of surrounding rock in gob-side entry retention under similar conditions. [ABSTRACT FROM AUTHOR]

The railway line planning problem (LPP) plays a crucial role in determining the quality of services provided to passengers, as well as operation costs borne by railway companies. In periodic railway LPPs, it is common to consider passenger transfers between train lines to realize a general passenger travel cost setting in the railway system. While detecting passenger transfers requires incorporating passenger routing into mathematical formulations, thereby significantly complicating the problem. Studies on transfer-included LPPs are generally based on the Change&Go network that is constructed based on a pre-given line pool, which however is usually non-exhaustive due to computational intractability. To efficiently include passenger transfers in large-scale railway LPPs, this paper proposes a novel extended direct-service network representation of LPP, where lines are dynamically generated within the optimization process, and part of passenger transfers between lines can be precisely captured without the need for explicit modeling of passengers' distribution on specific lines. A two-phase solution approach based on the representation is designed. The first phase formulates LPP with part of transfers as a path-based service network design model, solved using a branch-price-and-cut algorithm. The second phase conducts a neighborhood search around the first-phase solution to seek better ones when considering all passenger transfers. Numerical results showcase the good performance of the two-phase solution approach. It delivers optimal solutions in 18 out of 24 test instances for a small case and achieves optimality gaps within 2.85% across all small instances. The large case study of China's Shandong high-speed railway network whose line pool size reaches millions demonstrates the scalability of the approach and its advantage over the traditional Change&Go method with partial line pools and an exact model developed in the paper. • A new network representation of periodic railway line planning problem with passenger routing without line pools. • A powerful two–phase solution approach incorporating two mathematical models and a branch-price-and-cut algorithm. • Validated on the Shandong high-speed railway network in China. [ABSTRACT FROM AUTHOR]

Some subtle features of planting structures in irrigation areas could only be visible on high-resolution panchromatic spectral images. However, low spatial resolution multispectral image makes it hard to recognize them. It is challenging to accurately obtain crop planting structure when using traditional methods. This paper proposes an extraction method of crop planting structure based on image fusion and U-Net depth semantic segmentation network, which can automatically and accurately extract multi-category crop planting structure information. This method takes Landsat8 commercial multispectral satellite data set as an example, chooses RGB pseudo-color synthetic image which highlights vegetation characteristics, and uses HLS(Hue, Luminance, Saturation), NND(Nearest-Neighbor Diffusion) and G-S(Gram-Schmidt) methods to fuse panchromatic band to obtain 15m high-resolution fusion image to obtain training set and test set, six types of land features including cities and rivers were labeled by manual to obtain the verification set. The training and validation sets are cut and enhanced to train the U-Net semantic segmentation network. Taking the Xiaokaihe irrigation area in Binzhou City, Shandong Province, China, as an example, the planting structure was classified, and the overall accuracy was 87.7%, 91.2%, and 91.3%, respectively. The accuracy of crop planting structures (wheat, cotton, woodland) was 74.2%, 82.5%, 82.3%, and the Kappa coefficient was 0.832, 0.880, and 0.881, respectively. The results showed that the NND-UNet method was suitable for large-scale continuous crop types (wheat, cotton), and the GS-UNet method had a better classification effect in discrete areas of cash crops (Jujube and many kinds of fruit trees). [ABSTRACT FROM AUTHOR]

Simple Summary: Most management methods for poultry farming currently rely on human labor. Such management is labor-intensive and inefficient, especially in identifying poultry growth stages. Given the lack of a high-precision artificial method for chick's day-age detection, a high-performance day-age classification and detection model for chicks was proposed based on artificial intelligent techniques. This method can detect and classify chicks in six different living stages from 1 to 32 day-ages, and the accuracy is 95.2%, superior to other current ones. In order to apply this method in practical scenarios, it has been deployed into an application based on the IOS system, which can recoganize the day-age of chicks by capturing real-time photos. The system is currently deployed in Rizhao City, Shandong Province, China. It helps chicken farm staff automatically detect the behavior of chickens, whose excellent working effect proves the robust availibility of the proposed method. Thanks to the boom of computer vision techniques and artificial intelligence algorithms, it is more available to achieve artificial rearing for animals in real production scenarios. Improving the accuracy of chicken day-age detection is one of the instances, which is of great importance for chicken rearing. To solve this problem, we proposed an attention encoder structure to extract chicken image features, trying to improve the detection accuracy. To cope with the imbalance of the dataset, various data enhancement schemes such as Cutout, CutMix, and MixUp were proposed to verify the effectiveness of the proposed attention encoder. This paper put the structure into various mainstream CNN networks for comparison and multiple ablation experiments. The final experimental results show that by applying the attention encoder structure, ResNet-50 can improve the accuracy of chicken age detection to 95.2%. Finally, this paper also designed a complete image acquisition system for chicken houses and a detection application configured for mobile devices. [ABSTRACT FROM AUTHOR]

This paper introduces a method of combining phase space reconstruction and symbolic dynamics to study the causality between urbanization and economic growth at different regional levels in Shandong Province and finds that there is a strong positive relationship between urbanization and economic growth from China, indicating that the development of urbanization can drive the economic growth. Then, according to the results of correlation analysis between respective subvariables belonging to urbanization and economic growth and the principle of "deleting strong and reserving weak," the paper selects the independent variable and dependent variable to explore the hidden causal mechanisms that drive the developing of urbanization and economic growth from China. The results show that (1) the pattern causality between the independent variable and the dependent variable is dominated by dark causality at the provincial level; (2) the pattern causality between the independent variable and the dependent variable is dominated by dark causality at the Jinan economic circles and the Lunan economic circles, but the positive causality is dominated at the Jiaodong economic circles; (3) the types of causality between the same evaluation index and PU in different regions are different, and furthermore the degrees of positive, negative, and dark causality are different at two levels and three regions. The conclusion shows that although there is an obvious positive interaction between urbanization and economic growth, the influences of many factors are neither positive nor negative causality, but dark causality, which plays an important role in developing urbanization and economic growth. This work is useful for studying the law of causality between urbanization and economic growth, and this interesting result can be extended to other economic events. [ABSTRACT FROM AUTHOR]

With a focus on the Cu isotope geochemistry of chalcopyrite, this paper analyzed the Cu isotope geochemistry of the Qibaoshan crypto-explosive breccia-type Cu–Au polymetallic ore district in Wulian, Shandong Province, North China Craton (NCC). Combined with the results of the in situ sulfur isotope analysis of sulfides, a certain reference and evidence for the study of the genetic mechanism of the epithermal-porphyry Cu polymetallic metallogenic system were provided. The results of the in situ isotope analysis show that the δ34S values of the main sulfides in the Qibaoshan Cu–Au polymetallic ore district range from −6.81‰ to +3.82‰ and are likely to be attributed to the mixing of the derived mantle with the surrounding sedimentary rock assimilation. The ore-forming mechanism may be related to the progressive cooling and transition of the earliest hydrothermal fluids that were dominated by H2S under relatively reducing conditions, followed by a gradual transition from oxidation to reduction. The Cu isotopic composition of the sulfides in ores (δ65Cu = +0.169‰–+0.357‰) decreases with depth, which is likely caused by the upward transport of heavier Cu isotopes. The upper part of the crypto-explosive breccia pipe in the Qibaoshan area may be relatively more gaseous, resulting in the enrichment of δ65Cu. As the gas phase decreases and the liquid phase increases with depth, the δ65Cu value gradually decreases. This indicates the transition from a low-temperature phyllic alteration to a high-temperature K-feldspar alteration. Large, concealed pluton intrusions or orebodies may be present at a depth of the Qibaoshan area. The heavy δ65Cu characteristic is a potential indicator for tracing the fluid activity of the porphyry system and searching for Cu mines. The results provide a reference for the study of the genetic mechanisms of the epithermal-porphyry Cu polymetallic metallogenic system. [ABSTRACT FROM AUTHOR]

As a kind of "pro-agricultural" intellectual property, geographical indications have brand value and cultural value, and play a unique role in promoting agricultural economic growth and Rural Revitalization. This paper describes the spatial distribution and spatial trends of geographical indication products in China based on ArcGIS platform, and explores the spatial clustering characteristics of geographical indication products in China by using standard deviational ellipse and exploratory spatial data analysis methods. The results show that: (1) Fruit geographical indication products account for the highest proportion, flowers and handicrafts account for a relatively small proportion, and agricultural geographical indication is the most important component. (2) The province with the largest distribution of geographical indication products is Shandong, and the provinces with the largest number of registered geographical indication products in the fruit category are Shandong and Xinjiang. In terms of spatial trends, Chinese geographical indication products show a relatively smooth arc-shaped trend in the east-west direction and an obvious inverted U-shaped trend in the south-north direction. (3) Chinese geographical indication products have obvious spatial agglomeration characteristics, and tea geographical indication products have the highest spatial agglomeration degree. [ABSTRACT FROM AUTHOR]

Soil salinization is a critical and global environmental problem. Effectively mapping and monitoring the spatial distribution of soil salinity is essential. The main aim of this work was to map soil salinity in Shandong Province located on the Yellow River Delta of China using Sentinel-1/2 remote sensing data and digital elevation model (DEM) data, coupled with soil sampling data, and combined with four regression models: support vector regression (SVR), stepwise multi-regression (SMR), partial least squares regression (PLSR) and random forest regression (RFR). For these purposes, 60 soil samples were collected during the field survey conducted from 9 to 14 October 2019, corresponding to the Sentinel-1/2 and DEM data. Then we established a soil salinity and feature dataset based on the sampled data and the features extracted from Sentinel-1/2 and DEM data. This study adopted the feature importance of the RF model to screen all features. The results showed that the CRSI index made the greatest contribution in retrieving soil salinity in this region. In this paper, 18 sampling points were used to validate and compare the performance of the four models. The results reveal that, compared with the other regression models, the PLSR model has the best performance (R2 = 0.66, and RMSE = 1.30). Finally, the PLSR method was used to predict the spatial distribution of soil salinity in the Yellow River Delta. We concluded that the model can be used effectively for the quantitative estimation of soil salinity and provides a useful tool for ecological construction. [ABSTRACT FROM AUTHOR]

Many deep mining mines in southwestern Shandong Province of China are covered with thick loose layers. When mining near the loose layers, there is a risk of water and sand inrush, which threatens the personal safety of miners. The prediction of sudden water and sand inrush is difficult due to the comprehensive influence of many factors, and the influencing factors are fuzzy and random. To solve this problem, in this paper, a new risk assessment method of water and sand inrush based on comprehensive weight and cloud model was proposed. Seven factors are selected as indexes: the aquifer thickness, the thickness ratio of sand layer to clay layer, the thickness of bottom clay layer, the coal seam thickness, the percentage of core recovery, the geological structure, and the bedrock thickness. The assessment index system is established, and the index is divided into three grades. A comprehensive weighting method, which combines analytic hierarchy process (AHP), entropy weight method (EWM), and minimum entropy principle, is used to reasonably assign the weight of index. Based on the cloud generator equation, the membership function is obtained. The assessment result of the assessment object is obtained by combining the membership degree and the weight of index. The comprehensive weight-cloud model assessment method is applied to the risk assessment of water and sand inrush in the 6311-2 working face in the sixth mining area of Baodian Coal Mine. According to the assessment results, the following conclusions can be drawn: (1) the bedrock thickness and the coal seam thickness are the main factors of water and sand inrush under loose layer mining; (2) the assessment results obtained by the comprehensive weight-cloud model method are consistent with the actual situation. The assessment method can provide scientific reference for the safe mining under the thick loose layer in the deep mines of southwest Shandong. [ABSTRACT FROM AUTHOR]

The dendrolites composed of light gray massive micrite limestone occur at the top of the Cambrian Zhangxia Formation in Houziyu Section, Zibo, Shandong Province. Because it is very difficult to study the genesis of microbial rocks through "the function of diagenesis filter," this paper analyzes its genetic mechanism by characterizing the sedimentary fabric and formation environment of dendrolites and it is of great significance to study microbial carbonate deposited in geological history in oil exploration. The Cambrian Zhangxia Formation in the Houziyu section is a marine deposit. The macroscopic shrub-like fabric of centimeter scale can be seen on the surface of the tree-shaped stone, with small biological burrows and remnants of calcareous mud components after filling. The microstructure observation shows that the main fabric of the dendrolites is a dark micrite matrix, bright calcite cement, clastic particles, and a calcified cyanobacteria biological community. Detailed supplementary information on the diversity of calcified microorganisms in dendrolites has been made through the study of various types of calcified cyanobacteria and calcified residual substances in the microbial membrane of calcified cyanobacteria in the dendrolites of the study area. It is clear that dendrolites are the product of the calcification of biofilms or microbial mats dominated by cyanobacteria. With the deepening of this kind of research, it is bound to raise the research of microbial carbonate to a new level in China and provide great help to find oil and gas resources in marine strata of microbial origin in China. [ABSTRACT FROM AUTHOR]

Digital Surface Model (DSM) is a three-dimensional model presenting the elevation of the Earth's surface, which can be obtained by the along-track or cross-track stereo images of optical satellites. This paper investigates the DSM extraction method using Gaofen-6 (GF-6) high-resolution (HR) cross-track images with a wide field of view (WFV). To guarantee the elevation accuracy, the relationship between the intersection angle and the overlap of the cross-track images was analyzed. Cross-track images with 20–40% overlaps could be selected to conduct DSM extraction. First, the rational function model (RFM) based on error compensation was used to realize the accurate orientation of the image. Then, the disparity map was generated based on the semi-global block matching (SGBM) algorithm with epipolar constraint. Finally, the DSM was generated by forward intersection. The GF-6 HR cross-track images with about 30% overlap located in Taian, Shandong Province, China, were used for DSM extraction. The results show that the mountainous surface elevation features were retained completely, and the details, such as houses and roads, were presented in valleys and urban areas. The root mean square error (RMSE) of the extracted DSM could reach 6.303 m, 12.879 m, 14.929 m, and 19.043 m in valley, ridge, urban, and peak areas, respectively. The results indicate that the GF-6 HR cross-track images with a certain overlap can be used to extract a DSM to enhance its application in land cover monitoring. [ABSTRACT FROM AUTHOR]

Plastic shed vegetable (PSV) cultivation has become an important vegetable production system in China, which accounts for about 1/4 of the total vegetable production of China. Shandong is the largest facility vegetable growing area in China. Continued years of high-input, high-output planting methods have brought some problems to the surrounding environment. Salinization has not only affected the soil and groundwater environment, but also the growth of vegetables. A comprehensive understanding of soil salinization in plastic shed vegetable fields is important for the sustainable development of the vegetable farming industry. In this paper, random survey sampling was used to collect soil samples from representative PSV production areas in Shandong Province, and the soil salinization status, acidification status, salt ion composition, and the main causes of soil salinity were studied in the survey area. Our study found that the salinized soils (mild, moderate, and severe levels) in the surveyed areas accounted for 40% of the total samples, and the total soluble salt (TSS) increased with the increase of the planting years. After continuous planting for 10 years, the soil pH showed a downward trend, indicating that salinization and acidification occurred simultaneously. A significant positive correlation was observed between TSS and soil organic matter (SOM) (r = 0.4773**). Principal component analysis found that , , , , Ca2+, K+, Mg2+, and Na+ had higher positive loads on principal component 1, the factor loads were 0.557–0.927, and the contribution rate reached 34.928%. Correlation analysis also showed that TSS was positively correlated with the concentrations of these ions (P < 0.01). The soil salinization status should be closely monitored and regulated by regulatory authorities to improve environment and soil health through balanced fertilization, thereby improving the yield and quality of vegetables. [ABSTRACT FROM AUTHOR]

This paper explored the transmission mechanism of the public sense of gain (PSG) and YB conservation and development, suggested to take the PSG as a better regulation and guidance for the sound development of the Yellow River Basin. Based on the data of CSS2019, this paper tried to exam the PSG at the opening stage of Chinese major strategy on YB Conservation and Development. An evaluation index system including 5 factor dimensions and 25 indices was constructed, and the normal distribution was used to fitting the survey data, after that, the dominance matrix method was applied to make decision based on PROMETHEE?. The empirical analysis results indicated that the PSG of the middle and upper reaches of the Yellow River was lower than the overall level of China, while that of Henan and Shandong in the lower Yellow River were both higher than its national average; and the public generally had a higher sense of gain on government public service and social civilization, however, the PSG on individual self-fulfillments of Henan and Shandong and that on economic situations of the middle and upper reaches of the Yellow River were both at a lower level. [ABSTRACT FROM AUTHOR]

Making use of econometric models in Shandong province of China, the paper verifies a method which can calculate the scale of positive externality measured in currency caused by enterprises' activity, and evaluates the performance of government fiscal expenditure for energy conservation and environmental protection in internalizing the positive externality of enterprises' activity in industrial system. Firstly, with the aid of the economic implications of econometric model parameters and the coefficient of determination, we separate the share of resource saving and the pollutant emission reduction caused by government fiscal expenditure from the total industrial resource saving and pollutant emission reduction; secondly, the environmental value of unit pollutant emission reduction and unit resource saving is estimated by using the data of the amount of pollutants removed from the regional industrial system and the operating costs of the relevant facilities; thirdly, with the aid of data on this expenditure and environmental value of unit pollutant emission reduction and unit resource saving, we monetize the scale of positive externalities of the entire regional industrial system; finally, the performance evaluation indicator is constructed to evaluate the performance of government fiscal expenditure for energy conservation and environmental protection in Shandong Province and typical municipal governments. The paper draws several conclusions: It is reasonable to use the internalization degree of positive externalities as the performance evaluation key indicator of government fiscal expenditure for energy conservation and environmental protection; there is a problem of low performance in regulating the positive externalities of enterprises in Shandong Province; the performance level can be improved by adjusting the expenditure structure of energy conservation and environmental protection funds; environmental values of unit pollutant emission reduction and unit resource conservation have obvious spatial differences, which has a significant impact on fiscal expenditure performance for energy conservation and environmental protection. [ABSTRACT FROM AUTHOR]

Background: Infectious diseases are a major threat to public health, causing serious medical consumption and casualties. Accurate prediction of infectious diseases incidence is of great significance for public health organizations to prevent the spread of diseases. However, only using historical incidence data for prediction can not get good results. This study analyzes the influence of meteorological factors on the incidence of hepatitis E, which are used to improve the accuracy of incidence prediction. Methods: We extracted the monthly meteorological data, incidence and cases number of hepatitis E from January 2005 to December 2017 in Shandong province, China. We employ GRA method to analyze the correlation between the incidence and meteorological factors. With these meteorological factors, we achieve a variety of methods for incidence of hepatitis E by LSTM and attention-based LSTM. We selected data from July 2015 to December 2017 to validate the models, and the rest was taken as training set. Three metrics were applied to compare the performance of models, including root mean square error(RMSE), mean absolute percentage error(MAPE) and mean absolute error(MAE). Results: Duration of sunshine and rainfall-related factors(total rainfall, maximum daily rainfall) are more relevant to the incidence of hepatitis E than other factors. Without meteorological factors, we obtained 20.74%, 19.50% for incidence in term of MAPE, by LSTM and A-LSTM, respectively. With meteorological factors, we obtained 14.74%, 12.91%, 13.21%, 16.83% for incidence, in term of MAPE, by LSTM-All, MA-LSTM-All, TA-LSTM-All, BiA-LSTM-All, respectively. The prediction accuracy increased by 7.83%. Without meteorological factors, we achieved 20.41%, 19.39% for cases in term of MAPE, by LSTM and A-LSTM, respectively. With meteorological factors, we achieved 14.20%, 12.49%, 12.72%, 15.73% for cases, in term of MAPE, by LSTM-All, MA-LSTM-All, TA-LSTM-All, BiA-LSTM-All, respectively. The prediction accuracy increased by 7.92%. More detailed results are shown in results section of this paper. Conclusions: The experiments show that attention-based LSTM is superior to other comparative models. Multivariate attention and temporal attention can greatly improve the prediction performance of the models. Among them, when all meteorological factors are used, multivariate attention performance is better. This study can provide reference for the prediction of other infectious diseases. [ABSTRACT FROM AUTHOR]

Jar burial is a particular burial practice generally used in the Neolithic period of China. However, the rarity of finding prenatal individuals limits the ability to study their treatment in jar burial contexts. In this paper, to study the postmortem treatment of this specific age further, we focus on three jar burials of infant individuals excavated in 2021 at the Gangshang site in China, where the skeletal remains were relatively well preserved. The skeletal remains of three well‐preserved individuals are presented into inverted ceramic tripods near the residential area and with a crouched posture. In terms of this condition, we apply the osteometric method to estimate the range and mean of age at death for each individual investigated. Meanwhile, we use micro‐computed tomography (CT) scans to help judge the degree of microbial bioerosion. Besides, histological analysis on skeletal remains combined with the Oxford Histological Index (OHI) assessment allows us to estimate the developmental stage at the time of death by analyzing the results of micro‐CT scans. By using osteometric methods, the results show that the gestational age of the three individuals is 22–26, 24–28, and 22–26 weeks, respectively. The results of the micro‐CT scans indicate that all three fetuses died shortly after birth, or had died in their mother's uterus before birth, with the OHI score of 5. Moreover, we indeed observe infant skeleton remains with no bacterial bioerosion, indicating that it is effective using this method to judge the developmental stage at the time of death with a specific taphonomic environment in the Gangshang site of the Dawenkou culture period. Combined with the placement of the jars in which the three infants were buried, it is believed that this unique placement method was intentional and specific to the infant deaths. These results are instructive for exploring the postmortem treatment of dead infants by ancient residents of the Dawenkou culture period (4200 bc–2600 bc) in Shandong Province, China, and the significance and possible causes of the unique burial type. [ABSTRACT FROM AUTHOR]

Many young women were believed to die due to pregnancy and childbirth in the past, yet few cases of pregnant female burials have been reported in bioarcheological literature. Therefore, this paper reports the burial of an adult female (H49‐1) and her infant (H49‐2), who were buried together in an early Western Zhou pit at the Sanbulijia site, Jiaodong Peninsula, Shandong Province, China. It is the first reported case of obstetric death in thePre‐Qin Period in Shandong Province. The mother–child relationship was proved by ancient DNA evidence and archeological context. The infant's remains were placed between the adult's lower legs. Skeletal histological evidence suggests that the infant died during or shortly after childbirth. Sacroiliac fusion of individual H49‐1 may have resulted in dystocia. Furthermore, a special postmortem burial ritual—pit burial, was carried out for both the infant and the mother. H49 is the first Zhou Dynasty pit burial (multiple burial) with an exact radiocarbon date in the Shandong Peninsula. The case under review suggests that both the adult and the infant may have died due to special events, which may be related to obstetric death. [ABSTRACT FROM AUTHOR]

Nitrogen dioxide (NO2) is an important precursor of atmospheric aerosol. Forecasting urban NO2 concentration is vital for effective control of air pollution. This paper proposes a hybrid deep learning model for predicting daily average NO2 concentrations on the next day, based on atmospheric pollutants, meteorological data, and historical data during 2014 to 2020 in five coastal cities of Shandong peninsula, northern China. A random Forest (RF) algorithm was used to select input variables to reduce data dimensionality trained by the sequence to sequence (Seq2Seq) the model and describe how the Seq2Seq model understands each predictor variable. The hybrid model combining an RF with Seq2Seq network (RF-S2S) was evaluated and achieved a Pearson's correlation coefficient of 0.93, a Nash–Sutcliffe coefficient (NS) of 0.79, a Root Mean Square Error (RMSE) of 5.85 µg/m3, a Mean Absolute Error (MAE) of 4.50 µg/m3, and a Mean Absolute Percentage Error (MAPE) of 20.86%. Feature selection by an RF model improves the performance of the Seq2Seq model, reducing errors by 19.7% (RMSE), 20.3% (MAE), and 29.3% (MAPE), respectively. Carbon monoxide (CO) and PM10 are two common, important features influencing the prediction of NO2 concentrations in coastal areas of northern China. The results of RF-S2S models can capture general trends and disruptions more accurately than can long-short term memory (LSTM) models with and without feature selection. The decreasing tendency of NO2 from 2014 to 2020 illustrated by the empirical mode decomposition (EMD) method is one important obstacle to improving the RF-S2S prediction accuracy. An EMD-based RF-S2S model could help to perform the short-term forecast of NO2 concentrations efficiently. [ABSTRACT FROM AUTHOR]

• The application influence of three typical sunrooms in rural houses were compared. • The additional sunroom has the best performance in the rural area in Southeast Shandong, China. • The order of influence of factors on the heating performance of the additional sunroom in rural houses was given. • Additional sunroom optimization suggestions based on different angles are proposed. The sunroom, a passive solar heat collecting component, is widely used in rural residential houses in Southeast Shandong Province, China. However, many forms of sunroom are applied in this area, and the impact of their application on the indoor thermal environment, energy-saving, and economy is unclear. In this paper, the influence of additional sunroom, courtyard sunroom, and additional sunroom coupling with courtyard sunroom on the indoor thermal environment are tested and studied. A comprehensive evaluation method based on the Energy Plus and dynamic investment payback period analysis is adopted to evaluate the energy-saving rate and economy. Furthermore, the optimization of the sunroom is performed, and the impact of seven key structural factors of sunroom for the indoor thermal environment, energy-saving, and economy was analyzed and evaluated. The additional sunroom has the best performance in improving the indoor thermal environment compared with the courtyard sunroom and the additional sunroom coupling with the courtyard sunroom. Compared to the typical additional sunroom existing in this area, the heating performance of the additional sunroom after comprehensive optimization is improved by 7.1%. Compared with the typical ordinary rural residential house without additional sunroom, the energy-saving rate of the additional sunroom after comprehensive optimization is 44.8 %, and the indoor temperature increases by 2.38 ℃. The conclusions will provide a theoretical basis for improving the indoor thermal environment of rural residential houses in Linyi and other areas in cold zones where solar energy resources are not abundant and the construction of rural residential houses with sunrooms. [ABSTRACT FROM AUTHOR]

Karst cave is a sort of special and buried geological structure that was widely developed in the Permo-Carboniferous coal accumulation area of North China. It brings karst collapse and safety hazard in the mining industry. In this study, we propose a seismic structure-constrained inversion of controlled source audio-frequency magnetotelluric (CSAMT) data on a detailed survey and detection of karst caves. Instead of constrained by seismic impedance, the method in this study directly takes the seismic imaging results as structural constraints, which is different from the cross-gradient technique used by conventional structural constraints. First, the seismic migration section is divided according to the CSAMT inversion grid and applied pixel extraction for each grid. Clustering is carried out according to the structural information interpreted by the seismic migration section and the average pixel value of each cluster is calculated. Then the clustered results were used in the seismic structure-constrained inversion of CSAMT data based on cross-gradient technique. After that, as a karst cave model developed in limestone was established, the study compares the structure-constrained inversions with different clustering strategies shows a much more precision of karst cave detection than the method only applies CSAMT data. Moreover, experimental verification is provided in this study, which is for the detection of a suspected karst collapse column from Shandong Province, China. The comparison results further show that the structure-constrained inversion method proposed in this paper is applicable and may effectively improve the locating accuracy of karst caves. [ABSTRACT FROM AUTHOR]

The North Yellow Sea, located at the intersection of the Eurasian continent and North Pacific Ocean at mid-latitudes, is a sensitive area subjected to the joint actions of the ocean, land, and monsoons. On its southern shore, loess and paleosol sedimentary sequences were widely developed during the last interglacial period, which is of great significance for revealing patterns of climate change and dynamic conditions. In this paper, we focus on the Zhifu section (ZFS) on Zhifu Island within the Shandong Province of China. The optically stimulated luminescence (OSL) dating method was used to construct our chronological framework. Grain size and its endmember (EM) components were then analyzed; EM1 is a clay component EM, which represents a weak dynamic environment and strong weathering pedogenesis, while EM2 and EM3 are silt and very fine sand component EMs, respectively, representing a strong dynamic environment and weak weathering pedogenesis. Maximum EM1, mean grain size, clay content, and pH values occur in the paleosol layers (ZF4, ZF6, and ZF8), with minimum values in the loess layers (ZF5 and ZF7); EM3 values show the opposite pattern. This indicates that the ZF4, ZF6, and ZF8 layers represent warm and humid environments with abundant precipitation, where the East Asian summer monsoon (EASM) was enhanced, corresponding to Marine Isotope Stages (MIS) 5a, 5c, and 5e. In contrast, ZF5 and ZF7 represent sub-warm and humid environments with less precipitation, where the EASM was weakened, corresponding to MIS 5b and 5d. Among these stages, MIS5e is the warmest and wettest. These climatic events reveal the pattern of climate fluctuation over a ten-thousand-year timescale; they are synchronous with climate changes recorded in other geological repositories, such as cave stalagmites in southern China and sea-level fluctuations in the Yellow-Bohai Sea, which result from changes in global solar radiation. [ABSTRACT FROM AUTHOR]

Improving culture and tourism integration efficiency is an important way to promote the high-quality development of cultural tourism. According to the inherent requirements of high-quality development, this paper constructed an evaluation indicator system for culture and tourism integration efficiency. Then, the culture and tourism integration efficiency of 16 cities in Shandong Province, China during the period from 2010 to 2019 was measured with the benevolent DEA cross-efficiency model. On the basis of exploratory spatial data analysis and dynamic spatial Durbin model, we explored the spatio-temporal evolution characteristics and influencing factors of culture and tourism integration efficiency in Shandong Province. The results show that from 2010 to 2019, the culture and tourism integration efficiency in Shandong Province has experienced three stages of "rapid growth-rapid decline-stable rise period". The spatial pattern has changed from "high in the east and low in the west" to "high in the central and low in the north and south", and regions with high integration efficiency are mainly concentrated in Jiaodong Peninsula. The level of economic development significantly promotes the culture and tourism integration efficiency in local and neighboring cities in the short and long term, while policy environment has a significant negative impact. Traffic conditions and human capital only promote the culture and tourism integration efficiency in local cities. The level of information development and openness degree only have a long-term effect on the culture and tourism integration efficiency, without short-term effect. The research results are of great significance to improve the growth quality and sustainable development of cultural tourism in Shandong Province. Our work could provide a scientific basis for maximizing the allocation benefits of cultural and tourism resources in similar regions in the world. [ABSTRACT FROM AUTHOR]

In order to alleviate global warming and the energy crisis, it is of great significance to develop and utilize solar energy resources. Sunshine duration (SD) is considered to be the best substitute for solar radiation and a key factor in evaluating solar energy resources. Therefore, the spatial and temporal characteristics of SD and the reasons for its changes have received extensive attention and discussion. Based on the data of 415 meteorological stations from 1970 to 2019, this paper uses linear trend analysis, Mann–Kendall mutation analysis, the Hurst index, empirical orthogonal decomposition, correlation analysis and partial correlation analysis to analyze the spatiotemporal characteristics of SD and its relationship with influencing factors. The results show that the annual SD in China shows a downward trend, with a climate trend rate of −37.93 h/10a, and a significant decline from 1982 to 2019. The seasonal SD shows a downward trend, and the downward trend is most obvious in summer. The annual and seasonal SD will still show a downward trend in the future. The spatial distribution of SD not only has an overall consistent distribution but also takes the Yellow River from Ningxia to Shandong as the boundary, showing a north–south opposite distribution. Annual SD has a significant positive correlation, a significant negative correlation, a positive correlation and a negative correlation with wind speed, precipitation, temperature and relative humidity, respectively, and it is most closely related to wind speed and precipitation. In addition, the change in SD may also be related to human activities. [ABSTRACT FROM AUTHOR]

GaoFen 7 (GF-7) is China's first submeter high-resolution stereo mapping satellite with dual-linear-array cameras and a laser altimeter system onboard for high-precision mapping. To further take advantage of the very high elevation accuracy of laser altimetry data and the high relative accuracy with stereo images, an innovative combined adjustment method for GF-7 stereo images with laser altimetry data is presented in this paper. In this method, two flexible and effective schemes were proposed to extract the elevation control point according to the registration of footprint images and stereo images and then utilized as vertical control in the block adjustment to improve the elevation accuracy without ground control points (GCPs). The validation experiments were conducted in Shandong, China, with different terrains. The results demonstrated that, after using the laser altimetry data, the root mean square error (RMSE) of elevation was dramatically improved from the original 2.15 m to 0.75 m, while the maximum elevation error was less than 1.6 m. Moreover, by integrating a few horizontal control points, the planar and elevation accuracy can be simultaneously improved. The results show that the method will be useful for reducing the need for field survey work and improving mapping efficiency. [ABSTRACT FROM AUTHOR]

Formation comprises a distinctive set of sedimentary layers, which can be traceable laterally and mapped as a unit. It is a fundamental unit for stratigraphic position in a regional scale and provides an important basis for the interpretation of depositional processes and environments. This paper reviews the occurrence of the Jangsan Formation at the base of the Taebaek Group (Cambrian-Ordovician) in the Taebaeksan Basin and refines the geologic map unit for sedimentary characteristics and stratigraphic position. The refined Jangsan Formation comprises a set of distinctive sandstone (quartzite) with a number of sedimentary facies, including conglomerate, conglomeratic sandstone, and mudstone. The "Myeonsan Formation" is limited to a localized set, and leads it fallen into disuse. The refined Jangsan Formation can be reliably correlated with the equivalent early Cambrian sandstone unit (Liguan Formation) in Shandong Province, China about a thousand kilometers apart and elsewhere in the northeast Asian continent. [ABSTRACT FROM AUTHOR]

Combined heat and power is an inevitable trend in the development of waste-to-power industry. Many waste incineration power generation projects that have already put into operation in China are waiting for transition and upgrading to combined heat and power projects. From a growth option perspective, this paper considers the irreversible process and uncertainty in economic benefits, introduces carbon emission trading mechanism and develops the growth option theory to design the expansion decision making model of waste-to-energy combined heat and power projects, so as to obtain the project value and find the optimal expansion timing. In this paper, a case study is carried out on the expansion decision making of a waste-to-energy combined heat and power project in Shandong Province in China. And two scenarios with specific and flexible expansion times are developed from European and American options separately, as European options require investors to expand at a certain time but American options not. The results indicate that 1) real option approach successfully improves the project value through considering uncertainty, and American option can achieve the optimal expansion time, 2) under the carbon emission trading mechanism, the carbon price affects the expansion index, which has a positive effect on the project value, 3) the linear nature of the income and cost expansion index can help investors make judgments on expansion investments. The effectiveness of the case study implies the practicality of the expansion option method for similar projects to reach dual carbon targets in cost and benefit analysis. • Real option approach is applied in energy transition in WTECHP projects. • European and American options are proposed for certain and flexible decision times. • Expansion time and triggers of WTECHP are incorporated into life cycle management. • CCER is introduced as an environmental element to evaluate expansion decision making. [ABSTRACT FROM AUTHOR]

Food security plays an important role in maintaining national stability and sustainable development of human society, and its research has become a hot issue at present. Shandong is the main grain producing area in China, and its grain production plays an important role in national food security. Accordingly, this paper is based on the county climate change, grain yield, sown area, fertilizer use, total power of rural machinery, and total population data in Shandong Province from 1995 to 2020. The evolution process of the food security pattern was studied by the methods of spatial analysis and comprehensive evaluation, the influencing factors of food security were quantitatively analyzed, and the adaptive countermeasures to alleviate the food security risks in this region were discussed. The results show that: Grain production increased by 30.62% from 1995 to 2020. The total population and per capita food availability also increased. Since 2000, more than a quarter of counties have experienced a high risk of food insecurity. The spatial agglomeration of grain production was enhanced, and the local agglomeration characteristics were significantly different. The average temperature in the growing season, the sown area, and the total power of agricultural machinery had a significant positive impact on grain production, while the annual average temperature had a significant negative impact on grain production. Improving the food supply system, strengthening the protection of cultivated land, improving the efficiency of fertilizer utilization, and increasing investment in agricultural science and technology can effectively alleviate food security risks. [ABSTRACT FROM AUTHOR]

China's food security has always been a high priority issue on the political agenda with rapid urbanization affecting agricultural land, and it is challenged by several factors, such as human activities, social politics and policy. Shandong is an important grain-producing province and the second most populous province in China. In this paper, the spatiotemporal characteristics of grain yield and their potential influencing factors were explored at the county level in Shandong by using panel data over a 19-year period. The location Gini coefficient (L-Gini) and exploratory spatial data analysis (ESDA) were used to study the spatial agglomeration characteristics of grain yield, and spatial regression methods (SRMs) were used to analyse the influencing factors. The results indicated that grain yield increased from 38.3 million metric tons to 53.2 million metric tons in 2000–2018, with a growth rate of approximately 28.0%. The increase in grain yield in Shandong was due to the driving effect of radiation from high-yield counties to surrounding moderate-yield counties. This revealed an upward trend of spatial polarization in Shandong's grain yield. In 2000–2018, the L-Gini and global Moran's I increased from 0.330 to 0.479 and from 0.369 to 0.528, respectively. The number of counties in high-high (HH) and low-low (LL) agglomeration areas increased, and the spatial polarization effect was significant. SRMs analysis showed that irrigation investment and non-grain attention have significant positive and negative effects on grain production, respectively. The spatial relationship between grain yield and its influencing factors was explored to provide a reference for formulating scientific and rational agricultural policies. [ABSTRACT FROM AUTHOR]

On 12–13 February 2016, a record-breaking rain–snow event during the passage of an extratropical cyclone occurred in Shandong Province, China, in which the 24 h precipitation totals at 48 of 123 national meteorological stations in Shandong Province broke their historical records for the month of February, and a further 25 stations recorded their second-largest February totals. This paper investigates the evolution of the mesoscale precipitation areas and the mechanisms responsible for the formation, organization, and maintenance of the mesoscale precipitation areas, using FY-2G satellite data, Doppler radar observations, and a Weather Research and Forecasting (WRF) model numerical simulation at 4 km grid spacing. The main results show that the comma head cloud of the cyclone developed from four echo strips. Intense precipitation was related to the mesoscale elongated precipitation areas (EPAs) of reflectivity >30 dBZ within the stratiform clouds. The formation and development of the EPAs coincided with the activities of a low-level shear line and an associated increase in frontogenesis. The simulated EPAs occurred in an environment of conditional instability (CI), inertial instability (II), and conditional symmetric instability (CSI). In the initial stage of the elongated rainfall areas (ERAs), rainfall was initiated by the frontal forcing in the presence of elevated CI, and II was generated by upright convection. During the development stage of the ERAs, the CI was absent, and condensational heating was enhanced. II occurred in the absence of upright convection, and it seems likely that the presence of II is a diabatic signature of the precipitation itself. Upper-level II intensified the convective systems by enhancing outflow aloft, and II caused the ERAs to organize. Thus, II played an important role in the organization and maintenance of the ERAs. The frontogenesis provided the dynamic condition for the release of the instability. Enhanced CSI and II intensified slantwise convection, and combining with enhanced frontogenesis, intensified the ERAs. The echo, ascent, and frontogenesis in snowfall areas were weaker than those in rainfall areas. [ABSTRACT FROM AUTHOR]

To explore the correlation between academic performance and learning motivation in English course under a corpus-data-driven blended teaching model, this study set research objects as 62 year-2020-enrolled undergraduate students majoring in English from a university in Jinan City, Shandong Province, eastern China. According to their previous frequencies of using information technology to learn English, these 62 students were divided into two groups: practice group with high frequency and control group with low frequency, with 31 students in each group. The two groups of students were taught 3 English lessons per week for a total of 15 weeks by the exact same teachers using a corpus-data-driven blended teaching model. The students' English academic performances were assessed by well-organized final tests, and their English learning motivations were measured by a motivation scale and questionnaires. The results show that the correlation coefficients between the average score of motivation questionnaires, intrinsic motivation factors, extrinsic motivation factors, and the average score of academic performances in practice group were 0.894, 0.682, and 0.724, respectively, while those in control group were 0.749, 0.836, and 0.904. In all the above correlation analyses, the significance level is 0.01, and all coefficient values are higher than critical value. Hence, there is a positive correlation between learning motivation and academic performance of the two groups of subjects. It is found that the corpus-data-driven blended teaching model has a significant impact on college students' English academic performance and learning motivation, and it has a positive effect on the improvement of their English academic performance and the cultivation of learning motivation. In general, the key to this teaching model lies in reasoning and acquisition by analyzing the language provided by the corpus, and the whole process of data-driven learning is student-centered. Students are exposed to a large number of authentic language knowledge and cultural information, which promotes the sensitivity to relevant points. The results of this paper provide a reference for further research on the analysis of the correlation between academic performance and learning motivation in English course under the corpus-data-driven blended teaching model. [ABSTRACT FROM AUTHOR]

Short-term load forecasting plays a significant role in the operation of power systems. Recently, deep learning has been generally employed in short-term load forecasting, primarily in the extraction of the characteristics of digital information in a single dimension without taking into account of the impact of external variables, particularly non-digital elements on load characteristics. In this paper, we propose a joint MFF-SAM-GCN to realize short-term load forecasting. First, we utilize a Bi-directional Long Short-Term Memory (Bi-LSTM) network and One-Dimensional Convolutional Neural Network (1D-CNN) in parallel connection to form a multi-feature fusion (MFF) framework, which can extract spatiotemporal correlation features of the load data. In addition, we introduce a Self-Attention Mechanism (SAM) to further enhance the feature extraction capability of the 1D-CNN network. Then with the deployment of a Graph Convolutional Network (GCN), the external non-digital features such as weather, strength, and direction of wind, etc., are extracted. Moreover, the generated weight matrices are incorporated into the load features to enhance feature recognition ability. Finally, we exploit Bayesian Optimization (BO) to find the optimal hyperparameters of the model to further improve the prediction accuracy. The simulation is taken from our proposed model and six benchmark schemes by using the bus load dataset of the Shandong Open Data Network, China. The results show that the RMSE of our proposed MFF-SAM-GCN model is 0.0284, while the SMAPE is 9.453%,the MBE is 0.025, and R-squared is 0.989, which is better than the selected three traditional machine learning methods and the three deep learning models. [ABSTRACT FROM AUTHOR]

Late Mesozoic granites are present throughout the Jiaodong Peninsula in eastern China, but the petrogenesis of these granites, the magma sources, and the geodynamic setting of the magmatism remain unclear. This paper presents new zircon U–Pb geochronological and Lu–Hf isotopic and whole‐rock geochemical data for the Late Jurassic Queshan pluton in the Shandong Peninsula, an area that represents the boundary between the Jiaobei and Sulu ultrahigh‐pressure (UHP) terranes. Laser ablation–inductively coupled plasma–mass spectrometry zircon U–Pb dating yields Late Jurassic ages from 158 ± 1 to 153 ± 1 Ma for the pluton in addition to a small number of inherited zircons that yield ages that cluster at 2410, 1831–1776, 750, and 209–202 Ma. Zircons from different samples have similar 176Hf/177Hf values (0.281926–0.282255) and variably negative εHf (t) values that range from −26.5 to −15.1 (weighted mean of −22.9 ± 0.9). The corresponding two‐stage Hf model ages range from 2,869 to 2,154 Ma, with a weighted mean value of 2,645 ± 54 Ma. These data indicate that the magmas that formed the Queshan pluton were derived from multiple sources, including the lower crust of the North China (NCC) and Yangtze (YC) cratons, as well as collision‐related alkaline rocks. The whole‐rock geochemical compositions of the samples indicate that the granites are weakly peraluminous, are high‐K and calc‐alkaline with I‐type affinities, and have high contents of Sr, low contents of Y and Yb, high (La/Yb)N and Sr/Y values, and positive Eu anomalies (δEu = 1.20–1.65), indicating an adakitic affinity. This indicates that the Queshan granites formed from magmas generated by partial melting of a thickened region of the crust (>50 km) associated with eclogite, garnet amphibolite, or amphibolite residual material. The genesis of the Late Jurassic granites are also likely to have been influenced by the collisional orogeny between the NCC and YC and continued subduction of the Izanagi Plate. Thickening of the lower crust associated with this continental collisional event occurred before the magmatism, with further compression and thickening of the lower crust caused by the low‐angle subduction of the Izanagi Plate beneath northeastern China being the main geodynamic driver of the formation of the granites in this region. [ABSTRACT FROM AUTHOR]

Cross-front transport is a vital process in the offshore transport of terrestrial materials. The factors influencing cross-front transport are multifaceted and exhibit regional variability. As important factors regulating material transport patterns in the shelf seas of eastern China, the East Asian Winter Monsoon (EAWM) and Kuroshio current (including its branches) vary on multiple time scales, yet their role in controlling offshore transport is not fully understood. In this paper, cross-front offshore transport in the North Yellow Sea is chosen to investigate the aforementioned issue using numerical simulation. By excluding other potential processes for offshore transport, frontal instability is identified as the primary mechanism for offshore transport, which is triggered by winter storms (bursts of the EAWM); hence, the intensity of offshore transport is highly associated with the strength of winter storms on synoptic scales. However, on the inter-annual scale, the intensity of offshore transport is more likely regulated by the strength of the Kuroshio current, and a warming Kuroshio facilitates offshore transport. Although the role of each factor in controlling the intensity of offshore transport is delineated, the interactive effects of the EAWM and Kuroshio current on offshore transport are quite intricate, and how to quantitatively estimate their roles on multiple time scales remains a challenge using modelling. The results obtained from this study can be applied to analyse cross-front transport throughout the eastern China seas and bear significant implications for future studies on pollutant diffusion, nutrient distribution, and sediment transport in the coastal area. • Cross-front transport around the Shandong Peninsula was revealed using a numerical model. • EAWM and Kuroshio affect the strength of cross-front transport on different time scales. • With global warming, the temperature of Kuroshio might gradually become the primary control of cross-front transport. [ABSTRACT FROM AUTHOR]

Green has become the underpinning of High-quality development in China. Green development is inseparable from the support of institutional governance. This study uses MVC mode to build institutional governance mechanism, and constructs institutional governance system and model of regional green development. The empirical results show the following: institutional governance has great influence on industrial green development. From the perspective of China's provincial industrial green development, Shandong Province has been maintaining the first position of governance investment. Green governance is better in southern China than in the northern provinces. And the institutional governance intensity of each province is not evenly distributed. Therefore, China's industrial green development still needs to further strengthen the system governance of northwest and northeast regions. Finally, this paper aims to improve the green development level of China's regional industrial economy through the construction of institutional governance system. It provides institutional environment for the development of green innovation. [ABSTRACT FROM AUTHOR]

The rapid development of urbanization in China inevitably leads to a sharp increase in building energy consumption, and Passive House (PH) have received much attention in China in recent years. In this paper, the annual energy demand (AED) and summer discomfort hours (SUH) of PH are used as optimization objectives to establish a set of design solutions for multi-objective optimization (MTO) and economic analysis of a PH in Shandong Province, China. It is found that (1) the algorithm based on nearest neighbor component analysis (NCA) feature extraction applies to the sensitivity analysis of multivariate nonlinear high-dimensional data, and the NCA-GA-RBF neural network technique is proposed, which has significantly improved the goodness of fit and generalization ability for AED and SUH. (2) The NSGA-II genetic algorithm is used for the optimization search, and the results show that the overall improvement rates of AED and SUH are 25.5% and 21.6%, respectively, among the nine solutions after comprehensive evaluation; (3) Finally, the optimal scheme of energy saving and the optimal scheme of the economy are selected for economic evaluation. By comparing the economics of the two options and the improvement rates of AEDs and SUHs, the guidelines for design decision-makers are provided. In summary, the design scheme of this paper is forward-looking and reference-oriented and provides some reference suggestions for the development of PH in China. • The NCA algorithm is suitable for multivariate nonlinear sensitivity analysis. • NCA-GA-RBF has stronger and more stable generalization ability and accuracy. • In this paper, climate is the main factor affecting thermal parameters. • Global costs have a stronger economic interpretation. [ABSTRACT FROM AUTHOR]

Atmospheric mercury is a crucial pollutant that must be well‐controlled to avoid damaging public health. It is thus necessary to understand from multiple perspectives the roles played by different industrial sectors, as well as their geographical distribution. Existing studies have overlooked the transmission sectors in the economic supply chains of the embodied atmospheric mercury emission network. In this paper, we offer a betweenness‐based account (BBA) for Chinese regions and industrial sectors in transmitting embodied atmospheric mercury emissions and in doing so have identified the transmitting hubs. Our results show that the Henan province acts as the transmission hub of the embodied atmospheric mercury emission network in China. The metallurgy, chemical, and construction industries generally play important roles in the transmission of embodied atmospheric mercury emissions across China. Henan's metallurgy sector, the third highest of all, is more closely linked with inter‐provincial sectors than the top two transmission sectors (the metallurgy industry of Jiangsu and the chemical industry of Shandong). This study can help policy makers improve mercury control measures by focusing on transmission processes for effective and comprehensive atmospheric mercury emission control. [ABSTRACT FROM AUTHOR]

Colletotrichum has numerous host range and distribution. Its species are important plant pathogens, endophytes and saprobes. Colletotrichum can cause regular or irregular depressions and necrotic lesions in the epidermal tissues of plants. During this research Colletotrichum specimens were collected from Mengyin County, Shandong Province, China. A multi-locus phylogenetic analysis of ITS, GAPDH, CHS-1, ACT, TUB2, CAL and GS sequence data combined with morphology, revealed a new species and two known species, viz. C. mengyinense sp. nov., C. gloeosporioides and C. pandanicola, belonging to the C. gloeosporioides species complex. The new species is described and illustrated in this paper and compared with taxa in the C. gloeosporioides species complex. [ABSTRACT FROM AUTHOR]

Accurate electricity load forecasting is an important prerequisite for stable electricity system operation. In this paper, it is found that daily and weekly variations are prominent by the power spectrum analysis of the historical loads collected hourly in Tai'an, Shandong Province, China. In addition, the influence of the extraneous variables is also very obvious. For example, the load dropped significantly for a long period of time during the Chinese Lunar Spring Festival. Therefore, an artificial neural network model is constructed with six periodic and three nonperiodic factors. The load from January 2016 to August 2018 was divided into two parts in the ratio of 9 : 1 as the training set and the test set, respectively. The experimental results indicate that the daily prediction model with selected factors can achieve higher forecasting accuracy. [ABSTRACT FROM AUTHOR]

• Analyzed the cause of secondary explosion accident in Hushan Gold mine in China. • Clarified the direct and indirect causes of the accident. • Calculated and verified the direct cause of the secondary explosion accident. • Put forward the suggestions for preventing secondary explosion accidents in mines. Explosion accidents often occur during mining, especially sudden secondary explosions, which pose a serious threat to the life and property safety of employees. Based on the development process and consequences of typical secondary explosion accidents in Hushan Gold Mine, Qixia City, Shandong Province, China, this paper uses accident analysis model and cone measurement calculation method to determine the direct cause of secondary explosion accidents. The main conclusions are as follows: The HFACS-CM model is used to analyze the causes of secondary explosion from five aspects: external environment, organizational influence, unsafe leadership, the prerequisite conditions of unsafe behavior and unsafe behavior. It is found that the CO ignition explosion in the mining process is the direct cause of secondary explosion. Then, combined with the experimental data of the cone measuring instrument, the field CO amount was calculated, and the M CO ≥ 101.4 m3 was obtained, indicating that the CO production did reach the condition of explosion range, and the analysis results of the model were verified. Through HFACS-CM model analysis and calculation verification, the key causes of secondary explosion accidents in such mines are found and lessons are learned, which provides an effective reference for the effective prevention of deflagration accidents in the field of mine safety. [ABSTRACT FROM AUTHOR]