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China's first Mars probe, the Tianwen-1, successfully landed on the Martian Utopia Plain on May 15, 2021. The multi-functional obstacle avoidance sensor (MOAS) has been the key navigation equipment for the entry, descent, and landing (EDL) operation of Tianwen-1. The MOAS integrates a landing camera and a laser imaging module and can acquire sequential optical images of the landing process of Tianwen-1 and high-resolution topography of the Martian surface. As a navigation sensor, the MOAS plays a key role in the processes of back cover avoidance, coarse obstacle avoidance, and hovering fine obstacle avoidance from the height of 10 km to landing. The MOAS's laser imaging module uses a new-generation scanning component, a two-dimensional MEMS scanning mirror, which is a unique feature compared to other space lidars. In this paper, optical and electronic designs of the MOAS are analyzed in detail. Based on the open-loop control feature of a MEMS scanning mirror, an online training and calibration method is proposed to increase the accuracy of optical angle control to 0.02°. In addition, the ground performance validation and the space environment testing of MOAS are described in detail. The inflight performance of MOAS is evaluated based on the sequential camera images and 3D point cloud data. In addition, the MOAS combines the attributes of a scientific instrument. The images obtained by the sensor can reconstruct the descending trajectory of Tianwen-1, determine accurate landing coordinates, and acquire information on the topography, surface reflectivity, and sand and dust of Mars. [ABSTRACT FROM AUTHOR]

Objective: The study aims to assess the current development status of transforaminal full-endoscopic spine surgery (TFES) by exploring and analyzing the published literature to obtain an overview of this field and discover the evolution and emerging topics that are underrepresented. Methods: Using Bibliometrix, CiteSpace, and VOSviewer, we analyzed the bibliometric data selected from the Web of Science Core Collection between January 2002 and November 2022. The descriptive and evaluative analyses of authors, institutes, countries, journals, keywords, and references are compiled. The quantity of research productivity was measured by the number of publications that were published. A quality indicator was thought to be the number of citations. In the bibliometric analysis of authors, areas, institutes, and references, we calculated and ranked the research impact by various metrics, such as the h-index and m-index. Results: A total of 628 articles were identified in the field of TFES by the 18.73% annual growth rate of research on the subject from 2002 to 2022, constituting the documents are by 1961 authors affiliated with 661 institutions in 42 countries or regions and published in 117 journals. The USA (n = 0.20) has the highest international collaboration rate, South Korea has the highest H-index value (h = 33), and China is ranked as the most productive country (n = 348). Brown univ., Tongji univ., and Wooridul Spine represented the most productive institutes ranked by the number of publications. Wooridul Spine Hospital demonstrated the highest quality of paper publication. The Pain Physician had the highest h-index (n = 18), and the most cited journal with the earliest publication year in the area of FEDS is Spine (t = 1855). Conclusion: The bibliometric study showed a growing trend of research on transforaminal full-endoscopic spine surgery over the past 20 years. It has shown a significant increase in the number of authors, institutions, and international collaborating countries. South Korea, the United States, and China dominate the related areas. A growing body of evidence has revealed that TFES has leapfrogged from its infancy stage and gradually entered a mature development stage. [ABSTRACT FROM AUTHOR]

Introduction: Endoscopic spine surgery (ESS) is a minimally invasive surgical technique that offers comparable efficacy and safety with less collateral damage compared to conventional surgery. To achieve clinical success, it is imperative to stay abreast of technological advancements, modern surgical instruments and technique, and updated evidence. Purposes: To provide a comprehensive review and updates of ESS including the nomenclature, technical evolution, bibliometric analysis of evidence, recent changes in the spine communities, the prevailing of biportal endoscopy, and the future of endoscopic spine surgery. Methods: We conducted a comprehensive review of the literature on ESS for the mentioned topics from January 1989 to November 2022. Three major electronic databases were searched, including MEDLINE, Scopus, and Embase. Covidence Systematic Review was used to organize the eligible records. Two independent reviewers screened the articles for relevance. Results: In total, 312 articles were finally included for review. We found various use of nomenclatures in the field of ESS publication. To address this issue, we proposed the use of distinct terms to describe the biportal and uniportal techniques, as well as their specific approaches. In the realm of technical advancement, ESS has rapidly evolved from addressing disc herniation and spinal stenosis to encompassing endoscopic fusion, along with technological innovations such as navigation, robotics, and augmented reality. According to bibliometric analysis, China, South Korea, and the USA have accounted for almost three-quarters of total publications. The studies of the biportal endoscopy are becoming increasingly popular in South Korea where the top ten most-cited articles have been published. The biportal endoscopy technique is relatively simple to adopt, as it relies on a more familiar approach, requires less expensive instruments, has a shorter learning curve, and is also well-suited for interbody fusion. The uniportal approach provided the smallest area of soft tissue dissection. While robotics and augmented reality in ESS are not widely embraced, the use of navigation in ESS is expected to become more streamlined, particularly with the emergence of recent electromagnetic-based navigation technologies. Conclusions: In this paper, we provide a comprehensive overview of the evolution of ESS, as well as an updated summary of current trends in the field, including the biportal and uniportal approaches. Additionally, we summarize the nomenclature used in ESS, present a bibliometric analysis of the field, and discuss future directions for the advancement of the field. [ABSTRACT FROM AUTHOR]

Landslide susceptibility mapping (LSM) is essential for the spatial prediction of landslides and risk prevention. Physically based LSM models are confined by oversimplifications of physical processes and limited information about soil properties. Data-driven LSM models may give reliable results only when the training and the testing data have high similarity, and application in regions with different geological conditions is often inapplicable. This paper proposes four hybrid data-driven and physical models and compares these models in terms of cross-regional generalization ability and prediction uncertainty. The effects of physical module performance on the hybrid model are analyzed. For the physical modules of the four hybrid models, two-dimensional (2D) physically based models, TRIGRS and the infinite-slope stability models (ISSMs), and the three-dimensional (3D) physically based model, Scoops3D, are adopted. The data-driven modules all adopt the convolutional neural network (CNN) model. Two towns in the Three-Gorge Reservoir area of China are used as the training and testing areas. The results show that all hybrid models have better generalization ability than using the data-driven module exclusively. The prediction uncertainty is significantly reduced by pre-selecting training samples using the physical module. The optimal hybrid model is the one that integrates CNN and ISSM (under the saturated condition). It is then applied to a new region (Wushan County) to further validate the generalization ability. It can make accurate predictions without calibrating the trained model using new data from the validation area. Finally, the effectiveness of model averaging for improving the prediction performance is verified. Using model averaging, the AUC value in the validation area yields 0.834, which is even higher than the original realizations, with AUC values ranging from 0.683 to 0.817. Therefore, the optimal hybrid model can be directly used for LSM in the Three-Gorge Reservoir, and the findings can provide valuable guidance for generalization ability improvement and prediction uncertainty reduction of LSM models in other countries and regions. [ABSTRACT FROM AUTHOR]

At this stage, there is a big gap between the cognition and practice of smart devices in universities and the theoretical development of universities. Theoretical and practical scientific research on university wisdom factors from the perspective of wisdom culture education can sort out the essential attributes of university wisdom in terms of actual practice and appearance and give references for the development of university theory and within the field of wisdom practice. In the age of the information explosion, modern education is developing toward an intelligent system approach. In this cultural education environment, universities in China are paying close attention to the construction of smart schools. Among them, the national Ministry of Education policy document emphasizes the construction of "intelligent education demonstration parks" and promotes the construction and implementation of smart campuses in all aspects. Given this, the paper takes university culture education as an example and explains how to build smart classroom teaching to promote the development of modernization and intelligence in China's education and improve its quality of teaching. [ABSTRACT FROM AUTHOR]

The author, together with M. Veerapazham, S. Wang and W. Zhang, considered the existence and uniqueness of continuous solutions to an iterative equation involving the multiplication of iterates in Gopalakrishna et al. (Sci. China Math., to appear). In this paper we continue to investigate this equation for differentiable solutions. Similarly to continuous solutions until Gopalakrishna et al. (Sci. China Math., to appear), no result on differentiable solutions of this equation on non-compact intervals of R has been obtained until now. Although our strategy here is to use the logarithmic conjugation to reduce the equation to the well-known polynomial-like iterative equation, all known results on differentiable solutions of the latter are given on compact intervals. We revisit polynomial-like iterative equations on the whole of R and use the Banach contraction principle to prove the existence and uniqueness of differentiable solutions to our equation on R + . We then technically extend our results on R + to R - and show that none of the pairs of solutions obtained on R + and R - can be combined at the origin to obtain even a continuous solution of the equation on the whole R . [ABSTRACT FROM AUTHOR]

China is the largest soybean-consuming country in the world, but its self-sufficiency rate (SSR) of 16% is very low and it therefore has to heavily rely on imports. To solve the soybean dilemma in China, it is necessary to examine the maximum amount of soybean that could be grown on the land currently used, how much land could reasonably be used to expand soybean acreage, and whether China could sustainably increase soybean self-sufficiency to reduce the risks of import reliance. To answer these questions, our paper presents a high-resolution spatial analysis of potential soybean production in China using primary data of weather and crop production practices that govern this potential. We employed a "bottom-up" scaling protocol to estimate gaps between potential yield with optimal management and current yields in three major soybean-planting regions, namely, Northeast China, Central China, and South China. We found that current soybean yield gap (Yg) in China is 49% and 45% of potential yield under irrigated and rainfed cropping systems, respectively. By closing the yield gap, Northeast China could provide additional soybean production equivalent to 32% of the current national total. Our results show that SSR could only be increased to 21–23% in 2030 by Yg closure alone but could be increased to a maximum of 52% by combining Yg closure and a reasonable area expansion. Even so, at least 61.08 million tons of soybean accounting for 38% of global soybean trade would still need to be imported to meet future domestic demand. We discuss strategies for soybean production increase based on Yg closure in the most valuable areas and cropland expansion in a sustainable manner in order to increase SSR as well as lessen the import pressure on the global market. [ABSTRACT FROM AUTHOR]

Seamless prediction is a weather–climate integrated prediction covering multiple time scales that include days, weeks, months, seasons, years, and decades. Seamless prediction can provide different industries with information such as weather conditions and climate variations from the next few days to years, which have important impacts on economic and social development and important reference value for short-, medium- and long-term decision-making and planning of the country. Therefore, seamless prediction has received widespread attention from the international scientific community recently. As Chinese scientists have also carried out relevant research, this paper reviews the research in China on developments and applications of seamless prediction methods and prediction systems in recent years. Among them, the main progress of seamless prediction methods studies is reviewed from four aspects: short- and medium-range weather forecasting, subseasonal-to-seasonal, seasonal-to-interannual, and decadal climate prediction. In terms of development and application of seamless prediction systems, the main achievements made by meteorological operational departments, scientific institutes, and universities in China in recent years are reviewed. Finally, some of the issues in seamless prediction that need further study are discussed. [ABSTRACT FROM AUTHOR]

Atmospheric electricity is composed of a series of electric phenomena in the atmosphere. Significant advances in atmospheric electricity research conducted in China have been achieved in recent years. In this paper, the research progress on atmospheric electricity achieved in China during 2019–22 is reviewed focusing on the following aspects: (1) lightning detection and location techniques, (2) thunderstorm electricity, (3) lightning forecasting methods and techniques, (4) physical processes of lightning discharge, (5) high energy emissions and effects of thunderstorms on the upper atmosphere, and (6) the effect of aerosol on lightning. [ABSTRACT FROM AUTHOR]

The influences of human activity on regional climate over China have been widely reported and drawn great attention from both the scientific community and governments. This paper reviews the evidence of the anthropogenic influence on regional climate over China from the perspectives of surface air temperature (SAT), precipitation, droughts, and surface wind speed, based on studies published since 2018. The reviewed evidence indicates that human activities, including greenhouse gas and anthropogenic aerosol emissions, land use and cover change, urbanization, and anthropogenic heat release, have contributed to changes in the SAT trend and the likelihood of regional record-breaking extreme high/low temperature events over China. The anthropogenically forced SAT signal can be detected back to the 1870s in the southeastern Tibetan Plateau region. Although the anthropogenic signal of summer precipitation over China is detectable and anthropogenic forcing has contributed to an increased likelihood of regional record-breaking heavy/low precipitation events, the anthropogenic precipitation signal over China is relatively obscure. Moreover, human activities have also contributed to a decline in surface wind speed, weakening of monsoon precipitation, and an increase in the frequency of droughts and compound extreme climate/weather events over China in recent decades. This review can serve as a reference both for further understanding the causes of regional climate changes over China and for sound decision-making on regional climate mitigation and adaptation. Additionally, a few key or challenging scientific issues associated with the human influence on regional climate changes are discussed in the context of future research. [ABSTRACT FROM AUTHOR]

In order to reveal the relationship between new urbanization and carbon emission to provide reference opinions for the construction of low-carbon urbanization, an evaluation system between new urbanization and carbon emission was constructed. Then their matching degree relationship was analyzed by coupling coordination degree model based on the data from 2012 to 2021 in Anhui Province, and their development trend from 2023 to 2032 was predicted by gray prediction model. The results show that: (1) New urbanization and carbon emission have the co-trend effect, and the consistency of core impact factors is relatively significant. Among them, the level of new urbanization increases from 0.058 in 2012 to 0.699 in 2021 and carbon emission development increases from 0.023 in 2012 to 0.165 in 2021, which both showing an upward trend. Meanwhile, social urbanization and population carbon emission are the core influencing factors. (2) The coupling coordination degree between new urbanization and carbon emission is low, but the synergy trend is optimistic and there is a large room for improvement. Among them, the coupling coordination coefficient of the coupling system rises from 0.136 in 2012 to 1.412 in 2021 (antagonistic phase), and then reaches 0.820 by 2032 (highly coordinated phase) by forecast. It shows that their current development is unbalanced, but the development trend is good, and there is a chance for improvement. This paper deepens the understanding of the logical correlation between new urbanization and carbon emission, and the following views are formed: (1) Low-carbon development is still the mainstream of new urbanization; (2) The coordination development of new urbanization and carbon emission reduction should be strengthened. [ABSTRACT FROM AUTHOR]

Hypertension is a primary or contributing cause for premature death in the entire world. As a matter of fact, there is a high prevalence and low control rates in low- and middle-income countries, such that the prevention and treatment of hypertension should remain a top priority in global health. In the recent years, the awareness, treatment, and control rates of hypertension patients in China have been significantly improved to 51.6%, 45.8%, and 16.8%, respectively. However, those rates are still far from a satisfactory level. Clinical studies suggest that for people in the pre-clinical stage of hypertension or having the risk of hypertension, the progression of the disease may be significanly reduced through a change in lifestyle, or by an effective drug therapy. In this paper, we address risk prediction for hypertension in the next five years, and put forward a model merging KNN and LightGBM. Our approach allows us to predict the hypertension risk for a specific individual using features such as the age of the subject and blood indicators. Results shows that our model is reliable and achieves accuracy and recall rate over 86% and 92%, respectively. [ABSTRACT FROM AUTHOR]

After more than 40 years of long-term development, as a pioneer of China's reform and opening up, the Yangtze River Delta region has made tremendous economic progress and strong scientific and technological innovation strength, which has made the economy flourish and scientific and technological innovation strength strong. However, in the process of financial growth in the Yangtze River Delta, there are also financial structures that do not match the optimization of industrial structure, thus hindering the quality and efficiency of industrial structure optimization, thus affecting the strategic function of industrial development. For the development of the financial field, this paper applies the real-time data processing system of the Internet of Things based on blockchain technology to analyze the financial industry of the Yangtze River Delta urban agglomeration. The Internet of Things, based on the technology of real-time data processing system, can store different types of financial assets. These assets are a common component of supporting the application of the Internet of Things. They mix and build a powerful back-end process that can support the data processing application of the Internet of Things. Therefore, the Internet of Things data network and other information are stored in the data structure, so that data analysis and consolidation can be carried out with consensus, Thus, the processing efficiency of relevant financing data in the Yangtze River Delta region has been greatly improved, and the development process of the financial sector in the region has been effectively accelerated. Therefore, the research on this issue will enable the financial industry to give full play to its potential as a major component of national economic development, so as to maximize the improvement of the industrial structure and promote the development of blockchain and Internet of Things technologies. [ABSTRACT FROM AUTHOR]

This article first describes the embedded voice processing process and uses the two-door restriction method for endpoint detection. Next, the wavelet + MFCC algorithm is proposed. The Fourier transform will replace it with ripple. The disadvantage of the ripple is that the size of the Fourier transform window cannot move with frequency. On this basis, the overall goal of the system is proposed, the overall structure is constructed, and the functions of the system are divided. Android mobile phone data collection technology has been extensively researched, including logical search, temporary access to permissions, JTAG search and ISP search. The design and implementation of the logical search engine based on root authority, the physical search engine based on Qualcomm processor, and the data analysis system have been completed, and the evidence collection of e-commerce applications has been completed. Based on the digital forensics system, this article studies and designs an Android device digital forensics system suitable for China's national conditions and laws from the three perspectives of data collection, analysis and storage. At the same time, brainstorming methods must be used between corporate financial management and cost management personnel. Finally, through research, scientifically construct the framework of the financial cost management system, distinguish the various requirements of the construction system, classify the importance, urgency, and feasibility of the requirements, establish the basic requirements and extension requirements, set the demand function to complete the schedule and Perform as planned. Through the research of embedded voice and digital forensics system, this paper applies it to the research of financial cost management, thereby promoting the development of enterprise financial management. [ABSTRACT FROM AUTHOR]

Phytoliths are silica bodies formed in living plant tissues, and they can be reliable indicators of their parent plants when they demonstrate characteristic phytolith morphology. As shown by the growing case studies around the globe, phytolith morphology is of significant value for identifying and even quantifying domesticated plants. However, researchers also alert that phytoliths morphology can change, for example, in alkaline solutions or heat, causing the loss of characteristic phytoliths and eventually leading to the over- or under-identification of certain phytoliths. Focusing on the degree to which heat can cause changes to the phytolith morphology of millet, the present study carried out a series of controlled heating experiments on six varieties of modern common millet (Panicum miliaceum) growing in different regions of Northern China. Husked grains were heated following the dry ashing method. Specimens prepared from the dry ashing method were examined under an optical microscope to quantify articulated husk phytoliths, which are characteristic millet phytoliths, and to estimate the surface area of millet grains. We estimated that 30.8% to 59.5% of the common millet phytoliths underwent morphological damage in the heating experiments. Considering our previous heating experiments on foxtail millet, we conclude that compared to foxtail millet phytoliths, common millet phytoliths experience morphological damage more quickly when exposed to heat. This observation may explain (at least partially) the contradictory results between macro- and micro-botanical results. It reminds us that common millet can be underrepresented in the micro-botanical evidence (phytoliths). We conclude the paper by discussing the potential archaeological implications of our heating experiments. [ABSTRACT FROM AUTHOR]

Large Scale Natural Draft Cooling Tower has become a hot topic in China because it is an important part of the nuclear power plant, and its environmental impacts include shading, solar energy loss, water deposition and salt deposition. In China, there is no built large-scale natural draft cooling tower of nuclear power plant. Therefore, model prediction becomes an effective way to solve this problem. This paper introduces the basic principles and structure of SACTI (Seasonal and Annual Cooling Tower Impact) model. SACTI is a cooling tower assessment model developed by Argonne National Laboratory, USA. A comparative case study between China's Pengze Nuclear Power Plant and the US Amos Power Plant is also presented. Calculations were carried out for the Pengze and Amos power plants, and the results showed that the maximum value of salt deposition at the Pengze plant was about 166.5 kg/(km2-month) at a distance of 800 m from the cooling tower. The maximum value of salt deposition at the Amos plant was about 92.85 kg/(km2-month) at a distance of 600 m from the cooling tower. Conclusions show that the research work can provide a useful solution in future work, the simulation results of the SACTI model have a potential mean in the absence of monitoring data. This research provides a way to generate simulation data through SACTI program in the design process of nuclear power plant cooling tower, and designers can use these data to determine how the cooling tower will affect the natural environment and manage within an appropriate range to reduce the impact on the environment. [ABSTRACT FROM AUTHOR]

During the conventional operation, nuclear power plants discharge waste water containing amount of radioactivity, one of main ingredient is the artificial radionuclide tritium. In this paper, the chemical characteristics and the level of tritium in the environment are studied. The monitoring medium and results of tritium in eight typical nuclear power plants are described. According to the monitoring data, the emission of tritium in heavy water reactor is relatively high, while that in pressurized water reactor is basically at the background level. Tips on topics related to strengthen the monitoring of radiation environment around the nuclear power plants have noted. [ABSTRACT FROM AUTHOR]

As an instrument to minimize carbon leakage, the effects and feasibility of Carbon Border Adjustments Mechanism (CBAM) will depend on multiple design options. While the EU has committed to introducing CBAM as part of its green climate deal, pursuing climate efforts to successfully limit global warming requires a collective implementation involving major emitters China and the US. This paper quantifies the distributional impacts of a joint CBAM implementation of in a climate alliance or a club of the EU, the US, and China. Differing from a myriad of studies that focus on unilateral CBAM, this analysis emphasizes collective implications on leakage, sectoral competitiveness, and welfare by projecting climate neutrality relative to current policies and climate targets. Our findings confirm that coalition reduces leakage, improves production on energy-intensive industries, and increases club's welfare relative to a non-CBAM and a unilateral implementation. These are in contrast with some unilateral analytical studies, especially for the US. It is further proof of the potential of CBAM as collective instruments to facilitate mitigation and trade competitiveness. [ABSTRACT FROM AUTHOR]

In recent years, the quantum implementation of symmetric ciphers has received much attention. In this paper, we investigate the construction of quantum circuits based on different gate sets for the SM4 block cipher, which is the national standard of commercial cryptography of China and is standardized in ISO/IEC. First, we construct reversible circuits using Pauli-X gates, CNOT gates and Toffoli gates (i.e., the NCT gate set) for the SM4 S-box, based on which we design two circuits for the SM4 S-box with Clifford+T gates by applying the quantum And gate and existing decomposition scheme of the Toffoli gate, respectively. In addition, we propose a new in-place 1 implementation for the linear transformation in the SM4 round function. Finally, taking the qubit consumption and the T · M value (the product of qubit consumption and nonlinear gate depth of a quantum circuit) as metrics, we investigate the application of various circuits we designed to the construction of quantum circuits for SM4. The results show that we can always construct a subroutine/stand-alone circuit based on the NCT gate set, or based on Clifford+T gates for SM4 with fewer qubits or lower T · M value than existing state-of-the-art implementations. [ABSTRACT FROM AUTHOR]

The ecological health of water quality is an essential factor in the survival and development of human beings. By setting up multiple sensors in the water body, people observe the factual state of water quality, and collect a large number of sequence data containing time information. In order to effectively utilize water quality time series data and predict future water quality changes, this paper proposes an improved deep learning method based on spatiotemporal feature correlated, called the convolution recurrent basis expansion analysis architecture. The model improves the original model by using the ability of convolutional neural network structure to extract spatial features and the continuous memory ability of recurrent neural network structure. Then, the physical prior knowledge is integrated into the proposed network to limit the unreasonable results predicted in the feasible solution space to further improve the learning efficiency of the model. For specific research objects, the model can mine multi-dimensional features in water quality sequences at different depths, and learn the temporal features of the sequences hierarchically. In order to verify the performance of the proposed model, we apply the proposed model to the water quality dataset collected in Tanghe Reservoir for simulation. The results of the study demonstrate that our model is suitable for water quality prediction and has distinct advantages over traditional neural networks. Our model will make accurate predictions of future changes in water quality and provide technical support in the refined water quality automatic monitoring system. [ABSTRACT FROM AUTHOR]

The weekend effect, i.e., the concentration of air pollutants is different from weekends to weekdays, has been explored since the 1970 s. In most studies, the weekend effect is referred to the change of O 3 , i.e., lower emission of NO x on weekends leads to a higher concentration of O 3 . Determining whether it is true can provide insight into the strategy of air pollution controlling. In this study, we explore the weekly cycle of cities of China based on the weekly cycle anomaly (WCA), which is proposed in this paper. The advantage of using WCA is that we can avoid the influence of other change components such as the daily cycle and the seasonal cycle. The p values of the significant tests from all cities are analyzed for obtaining a whole picture of the weekly cycle of air pollution. The result shows that the concept of the weekend effect is not proper for cities in China, as many cities reach the valley phase of the emission on weekdays but not weekends. Thus, researches should not pre-assume that the weekend is the low emission scenario. We focus on the anomaly of O 3 on the peak and the valley of the emission scenario estimated by the NO 2 concentration. Through the analysis of the distribution of the p values of all cities, we show that almost all cities in China have weekly cycle of O 3 corresponding to the weekly cycle emission of NO x , i.e., O 3 of the peak time of NO 2 is less than valley time. The cities of the strong weekly cycle are located in four regions, i.e., the Beijing-Tianjing-Hebei region, the Shandong Peninsula Delta, the Yangtze River Delta, and the Pearl River Delta, and these regions are also the regions with relatively severe pollution levels. [ABSTRACT FROM AUTHOR]

Customer behaviour analysis in a telecom market is a challenging task in the customer relationship management area. In this paper, we propose a customer behaviour recognition model that combines unsupervised classification and supervised classification methods. First, considering the complexity and uncertainty of consumption behaviour, a hybrid model of K-means clustering, the entropy method and customer portrait analysis is applied to segment customers. Second, the segmentation results are subsequently incorporated into the proposed multi-head self-attention-based nested long short-term memory classifier to evaluate the performance of customer behaviour recognition. Third, the proposed framework is applied to a real case obtained from the China telecom market. The results indicate that our model is significantly superior to other traditional customer behaviour classification models. In addition, medium-value customers will make full use of the mobile traffic packet, and the package utilization rate of high-value groups is lower, which may benefit the precision marketing of telecom companies. [ABSTRACT FROM AUTHOR]

Soil environmental quality assessment traditionally focuses on a single objective. Therefore, related results only reflect the pollution of the assessment objective and ignore the interaction and relationships between soil, ecology, and human health. In this study, we collected and filtered data about heavy metal content (Cr, Pb, Cd, Hg, As, Cu, Zn, and Ni) in city soils from more than 1000 published papers. Spatial multi-criteria decision-making theory was used to establish the combined evaluation model of soil environmental quality using the geochemical accumulation, ecological risk, non-carcinogenic risk, and carcinogenic risk indexes. Our results showed that the pollution degree and elements causing most pollution were significantly different when these different methods were used for assessment. The proposed framework was able to unify the overall pollution trend in regional soil environmental quality assessment and could output more robust and reasonable assessment results of soil, ecology, and human health. The random forest model was used to analyze the potential sources for excessive accumulation of heavy metal elements in soils, and the results showed that the main potential sources were the proportion of secondary industry and urbanization rate, each with an average contribution ratio of 20%. This study provides comprehensive and specific information for the prevention and control of soil heavy metal pollution in China. [ABSTRACT FROM AUTHOR]

Despite the popularity of trend-following strategies in financial markets, they often lack adaptability to the emerging varied markets. Recently, deep learning (DL) methods demonstrate the effectiveness in stock-market analysis. Thus, the application of DL methods to enhance trend-following strategies has received substantial attention. However, there are two key challenges to be solved before the adoption of DL methods in enhancing trend-following strategies: (1) how to design an effective data selector to include more related data? (2) how to design a profit-based model to enhance strategies? To address these two challenges, this paper contributes to a new framework, namely profit-based deep architecture with the integration of reinforced data selector (PDA-RDS) to improve the effectiveness of DL methods. In particular, profit-based deep architecture (PDA) integrates a dynamic profit weight and a focal loss function to obtain high profits. In addition, reinforced data selector (RDS) is constructed to select high-quality training samples and a training-aware immediate reward is designated to improve the effectiveness of RDS. Extensive experiments on both U.S. and China stock-market datasets demonstrate that PDA-RDS outperforms the state-of-the-art baseline methods in terms of higher cumulative percentage rate and average percentage rate, both of which are crucial to investment strategies. [ABSTRACT FROM AUTHOR]

As a pavement maintenance technology, hot in-place recycling (HIR) can realize full utilization of reclaimed asphalt pavement (RAP), significantly saving non-renewable resources and project costs. However, due to variability of material properties, recycled mixtures gradation, and temperature control in construction, HIR-maintained pavement usually suffers from segregation, affecting performance and service life. To control construction quality and prolong service life, a segregation evaluation system of HIR-maintained pavement is proposed. This evaluation system, including calculation of segregation indexes, determination of segregation zones, and discrimination of segregation types, is established based on digital image processing (DIP) and surface texture distribution characteristics. In addition, it is verified by a case study of qualified HIR projects in Jiangsu Province in China. According to the empirical acceptance requirements of maintenance projects, discriminative zones for segregation types are established at 95% confidence level. Fluctuation curves of segregation indexes and image tests of four segregation types identified by segregation zones show that segregation indexes are well correlated with texture distribution characteristics and segregation degree, confirming the effectiveness and accuracy of the segregation evaluation system. Therefore, the segregation evaluation system of HIR-maintained projects proposed in this paper can realize real-time monitoring, rapid diagnosis, evaluation, and treatment decision-making of recycled pavement segregation degree. [ABSTRACT FROM AUTHOR]

Landslides frequently disrupt roadway networks in mountainous regions worldwide. Because of the relatively long roadway extension and low roadway density in mountainous regions, the occurrence of a landslide hazard along a local road segment will cause traffic paralysis on the individual roadway and will further impact regional roadway network accessibility. This paper establishes an integrative risk assessment framework based on risk theory and complex network theory to combine the results of landslide susceptibility mapping along roadways and impact assessment on the roadway network. Through an analysis of the relationship between various geo-environmental conditioning factors and historical landslides along roadways, the support vector machine (SVM) model is used to assess landslide susceptibility across the regional roadway network. Both topological connectivity of the entire roadway network and transport accessibility between local residents are considered in the impact assessment on roadway networks. To illustrate the effectiveness of the proposed risk assessment framework, a case study of the roadway network in Fengjie County, China, which is prone to landslide occurrence, is conducted. The resulting landslide risk heatmap of Fengjie County's roadway network is generated using ArcGIS software. The most critical road segments are identified as being highly susceptible to landslides, and if they are disrupted, the entire roadway network will suffer significant performance loss. The results can support adaptive strategies for landslide mitigation, preparedness, and emergency response services, as well as improve roadway plans to reduce exposure and associated consequences by adding new links to the existing roadway network. [ABSTRACT FROM AUTHOR]

Mineralogy-based brittleness index is the simplest and most widely used index in characterizing the brittle property of shale gas/oil reservoirs. Traditionally, mineral compositions are usually determined by laboratory X-ray diffraction (XRD) analysis or interpreted from element logging, among which the former is time-consuming and non-continuous while the latter is costly and not timely. In this paper, a new rapid and economical method is proposed to obtain the mineral composition of shale from a statistical perspective, in the case of the Wufeng-Longmaxi shale, from the southeastern Sichuan Basin, China. The targeted shale cores from one scientific exploration well were scanned in situ to obtain the elemental data by using a non-destructive portable X-ray fluorescence (XRF) and sampled at each scanned site for laboratory XRD analysis to acquire the mineral composition data. Then we established the conversion models for shale with various sub-lithologies (including calcareous shale, sandy shale, and carbonaceous shale) based on a series of multiple regression analyses. These models were verified with the good consistency between predicted and tested mineral compositions of shale cores from another scientific exploration well. The mineralogy-based brittleness characterization results also indicated small differences between the predicted and tested brittleness index values, with the brittleness index curves matching well with the variations of experimental total organic carbon (TOC) with depth and conventional geophysical logging curves. The findings shed light on the application of portable XRF in determining mineral compositions and further the brittleness index of shale, which is essential for fracability evaluation and hydraulic fracturing design of shale gas/oil reservoirs. Highlights. Highlights: Conversion models from elements to minerals for various sub-lithologic shales were established. Brittleness indexes based on converted mineral compositions were closely approximate to the experimentally tested values. A rapid method to determine the brittleness of shale by using a non-destructive portable X-ray fluorescence was proposed. The method from elements to minerals to brittleness was successfully applied in the Wufeng-Longmaxi shale from the southeastern Sichuan Basin. [ABSTRACT FROM AUTHOR]

The development of science and technology has also led to the progress of rural digital economy. In China, the construction of new countryside has always been an important part of economic development. The application of big data technology in rural areas can not only promote the development of rural economy, but also improve the results of environmental protection. Using the matching coefficient method of agricultural water and soil environmental characteristics, it match the rural water and soil environmental characteristics and the impact of the water environment in the autonomous region. An indispensable driving force in the process, agricultural digitalization will update the rural economic development model, weaken the barriers to the dual structure of urban and rural areas, stabilize agricultural production, promote sustainable rural development, and promote rural economic development. The current government policy support, the urgent need for new development momentum for rural economic development, and the advancement of changes in the lifestyle of urban and rural residents are promoting high-quality development of the rural economy. At the same time, we are facing challenges such as the lack of local network coverage, the lack of logistics, sales systems, and the lack of talents with digital skills. Expanding rural network coverage, optimizing rural logistics and distribution, promoting the development of agricultural big data, and strengthening the development of digital human resources are important ways for agricultural digitalization to promote rural economic development. The research focus of this paper is the parallel development of rural digital economy and environmental protection under the big data economy, and its application in the current agricultural development can achieve a win–win situation between man and nature. [ABSTRACT FROM AUTHOR]

In this paper, we describe and analyze two datasets entitled "Homogenised monthly and daily temperature and precipitation time series in China during 1960–2021" and "Homogenised monthly and daily temperature and precipitation time series in Greece during 1960–2010". These datasets provide the homogenised monthly and daily mean (TG), minimum (TN), and maximum (TX) temperature and precipitation (RR) records since 1960 at 366 stations in China and 56 stations in Greece. The datasets are available at the Science Data Bank repository and can be downloaded from https://doi.org/10.57760/sciencedb.01731 and https://doi.org/10.57760/sciencedb.01720. For China, the regional mean annual TG, TX, TN, and RR series during 1960–2021 showed significant warming or increasing trends of 0.27°C (10 yr)−1, 0.22°C (10 yr)−1, 0.35°C (10 yr)−1, and 6.81 mm (10 yr)−1, respectively. Most of the seasonal series revealed trends significant at the 0.05 level, except for the spring, summer, and autumn RR series. For Greece, there were increasing trends of 0.09°C (10 yr)−1, 0.08°C (10 yr)−1, and 0.11°C (10 yr)−1 for the annual TG, TX, and TN series, respectively, while a decreasing trend of −23.35 mm (10 yr)−1 was present for RR. The seasonal trends showed a significant warming rate for summer, but no significant changes were noted for spring (except for TN), autumn, and winter. For RR, only the winter time series displayed a statistically significant and robust trend [−15.82 mm (10 yr)−1]. The final homogenised temperature and precipitation time series for both China and Greece provide a better representation of the large-scale pattern of climate change over the past decades and provide a quality information source for climatological analyses. [ABSTRACT FROM AUTHOR]

Sustainable development of agriculture is the basis for achieving social sustainable development. As the basic industry of national economy, green development of agriculture has become an important support for building an environment-friendly society. Agricultural fiscal expenditure is a direct channel for the government to support agriculture and promote agricultural transformation. It is important to analyze the impact of agricultural fiscal expenditure (AFE) on agricultural green total factor productivity (AGTFP) for sustainable agricultural development. Therefore, this paper employs the random effect model and spatial Durbin model to empirically analyze the direct effect and spatial spillover effect of AFE on AGTFP by using the agricultural panel data of 30 provinces in China from 2008 to 2020. Then, by taking the policy proposal as the time node, this paper also conducts a time heterogeneity analysis to measure the impact of policy enactment on AFE and AGTFP. The main conclusions are as follows: (1) AGTFP exists significant positive spatial spillover effect. The "radiation effect" of agricultural green development is significant. (2) AFE can significantly reduce the AGTFP in the local area, that is, 1% increase of AFE in the local area will reduce AGTFP by 0.037%. At present, agriculture is still yield-oriented. The improvement of AFE in the local area will lead to the expansion of local agricultural production and increase pollution emission. (3) AFE has a significant negative spatial spillover effect on AGTFP, that is, for every 1% increase in AFE, the AGTFP will decrease 0.123% in geographically similar areas, while the AGTFP will decrease by 0.116% in economically and geographically similar areas. It is obvious that AFE will promote the optimization of agricultural production conditions in the province, with the "demonstration effect" on the surrounding areas, the enthusiasm of production in the surrounding areas will increase, thus expanding the pollution emission. (4) According to the analysis of different periods, AFE has a negative impact on AGTFP mainly before the reform innovation is proposed in 2015. It indicates that reform policies have a significant impact on agricultural sustainability. [ABSTRACT FROM AUTHOR]

Semantic image segmentation in computer networks is designed to determine the category to which each pixel in an image belongs. It is a basic computer vision task and has a very wide range of applications in practice. In recent years, semantic image segmentation algorithms in computer networks based on deep learning have attracted widespread attention due to their fast speed and high accuracy. However, due to the large number of downsampling layers in a deep learning model, the segmentation results are usually poor at the edge of an object, and there is currently no universal quantitative evaluation index to measure the performance of segmentation at the edge of an object. Solving these two problems is of great significance to semantic image segmentation algorithms in China. Based on traditional evaluation indicators, this paper proposes a region-based evaluation index to quantitatively measure the performance of segmentation at the edge of an object and proposes an improved loss function to improve model performance. The existing semantic image segmentation methods are summarized. This paper proposes regional-based evaluation indicators. Taking advantage of the particularity of semantic image segmentation tasks, this paper presents an efficient and accurate method for extracting the edges of objects. By defining the distance from pixels to the edges of objects, this paper proposes a fast algorithm for calculating the edge area. Based on this, three methods are proposed as well as an area-based evaluation indicator. The experimental results show that the accuracy of the loss function proposed in this paper, compared with that of the current mainstream cross-entropy loss function, is improved by 1% on the DeepLab model. For area-based evaluation indicators, a 4% accuracy improvement can be achieved, and on other segmentation models, there is also a significant improvement. [ABSTRACT FROM AUTHOR]

Chinese cultural conservatism used to participate in shaping the course of modernization to a large extent. In this paper, I aim to describe a hidden lineage of Chinese cultural conservatism of the twentieth century that is still alive and appears to be more and more influential in mainland China. Relying on several ideas developed by Neo-Confucians of the early twentieth century, Gan Yang's paper in 2007 represented a contemporary revival of Chinese cultural conservatism. More importantly, in recent years, this kind of revival of conservative discourse went through another big change, which not only matters to the self-underpinning of the legitimate basis of the current regime, but also combined with the political conservations related to the Hong Kong protest of 2019–2020 explains why this country is so ideologically different from the West. [ABSTRACT FROM AUTHOR]

The Belt and Road Initiative (BRI) is a well-acknowledged central economic and diplomatic policy of the Chinese government, which was proposed by President Xi Jinping in 2013. This paper intends to discover the relationship between the public diplomacy narratives of the BRI and its implementation. By using content analysis, this paper analyzes Chinese President Xi's speeches from 2013 to 2020 about the BRI, as well as official statements of the Chinese central government. It identifies the public diplomacy narratives of the BRI: an assemblage of constantly changing policy settings that accommodates various economic and political interests. Also, this paper draws on differences between countries joining the BRI or not, and several case studies to elucidate the implementation of the BRI. Different from repetitive literature that explores either the BRI narratives or its implementation, this paper contributes by combining and comparing the two. Despite positive interpretations of the BRI the Chinese government has adopted, the paper argues that there are no deceptive tricks with skeletons in the closet of the Chinese government, as the BRI public diplomacy narratives are, in general, consistent with its implementation. [ABSTRACT FROM AUTHOR]

With the outbreaks of the COVID-19 epidemics in several provinces of China, government takes prevention and control measures to contain the epidemics. It is more difficult to make the long-term prediction of the sporadic COVID-19 epidemics than widespread ones in that the former cannot obey the laws of the infectious disease well like the latter. In this paper, we make long-term predictions including end time and final size, peak and peak time of current confirmed cases and the number of accumulative removed cases of the sporadic COVID-19 epidemics in different regions of China by a novel non-autonomous delayed SIR compartment model (S—susceptible, I—infected, R—removed). The key contribution of this paper is that under the rigorous containments, we find transmission rate β (t) is approximately an exponential decreasing function with respect to time t, rather than a fixed constant. In addition, the removed rate γ (t) is approximately a piecewise linear increasing function instead of a linear increasing function which is (at + b)heaviside (t-14). First, according to the few data in the early stage, i.e., roughly the first 7 days, issued by the National Health Commission of China and local Health Commissions, we can accurately estimate these parameters, i.e., transmission and removed rates of the model. Then, by them, we accurately predict the evolution of the COVID-19 there. On the basis of them to predict Category A of the sporadic COVID-19 epidemics since July 20th, 2021 in this summer. The results agree very well to the actual ones. It is also adopted to predict Category B - - - the tour group epidemics since October 17th, 2021 and Category C - - - other sporadic epidemics since October 27th, 2021. The results show that although our method is simple and the needed data are very few, the long-term prediction of the sporadic COVID-19 epidemics in China is quite effective. We can use this novel non-autonomous delayed SIR model to accurately predict its end time and final size, peak and peak time of current confirmed cases and the number of accumulative removed cases in China. This work can help governments and policy-makers make optimal prevention and control policies for all cities and provinces to contain the COVID-19 epidemics, and prepare well for the resumption of work, production and classes in advance to reduce the economic and social losses. [ABSTRACT FROM AUTHOR]

Buiding data-driven models using machine learning methods has gradually become a common approach for studying reservoir parameters. Among these methods, deep learning methods are highly effective. From the perspective of multi-task learning, this paper uses six types of logging data—acoustic logging (AC), gamma ray (GR), compensated neutron porosity (CNL), density (DEN), deep and shallow lateral resistivity (LLD) and shallow lateral resistivity (LLS) —that are inputs and three reservoir parameters that are outputs to build a porosity saturation permeability network (PSP-Net) that can predict porosity, saturation, and permeability values simultaneously. These logging data are obtained from 108 training wells in a medium-low permeability oilfield block in the western district of China. PSP-Net method adopts a serial structure to realize transfer learning of reservoir-parameter characteristics. Compared with other existing methods at the stage of academic exploration to simulating industrial applications, the proposed method overcomes the disadvantages inherent in single-task learning reservoir-parameter prediction models, including easily overfitting and heavy model-training workload. Additionally, the proposed method demonstrates good anti-overfitting and generalization capabilities, integrating professional knowledge and experience. In 37 test wells, compared with the existing method, the proposed method exhibited an average error reduction of 10.44%, 27.79%, and 28.83% from porosity, saturation, permeability calculation. The prediction and actual permeabilities are within one order of magnitude. The training on PSP-Net are simpler and more convenient than other single-task learning methods discussed in this paper. Furthermore, the findings of this paper can help in the re-examination of old oilfield wells and the completion of logging data. [ABSTRACT FROM AUTHOR]

The rise of China as a scientific research superpower has been frequently discussed in media and literature. However, past analyses are usually based on the geographical database and they ignore how the millions of emigrated Chinese students, who are now being considered the major research workforce in many countries, affect their academic outputs. Here we quantitatively analyze the contribution of Chinese scholars in physical science around the globe by their publications in a country's papers from 2010 to 2021 as well as their citations. Contrary to common perception, we find that increasing the number of Chinese scholars does not correlate with the net publication growth or decline in their host countries before the Chinese population exceeds a critical value. On the other hand, increasing Chinese authors in a paper improves its citations. The phenomena, though anomalous, are observed in many subfields of physics across the globe. Our analysis suggests that although Chinese scholars do not change the perceived publication capabilities of many countries but may have reshaped their research culture as well as workforce distributions. The results would be valuable for R&D, higher education, and immigration policymakers. [ABSTRACT FROM AUTHOR]

The increasing carbon emissions have been a major concern for most countries around the world. And as a result, every country is concerned about developing appropriate strategies to curtail it. As a major economy and the largest carbon emitter in the world, China has pledged to reduce the carbon intensity by 60–65% by 2030, compared with 2005 levels, and achieve carbon neutrality before 2060. Therefore, the analysis of the impact of China's carbon intensity is becoming an increasing important topic. Due to the spatial heterogeneity of carbon intensity, various spatial econometric models have been applied in this field. However, the existing literatures failed to consider the cross-products of relevant factors. This paper constructs our dynamic general nesting spatial panel model (GNS) with common factors to deal with the dilemma, and examines the direct and spatial–temporal spillover effects of industrial structure, GDP per capita, investment in anti-pollution projects as percentage of GDP and energy price on carbon intensity in China over the period 2003–2017. Our analysis shows that: (1) China's carbon intensity showed the spatial agglomeration and temporal "inertia" from 2003 to 2017. (2) From the time dimension, the long-term effect of industrial structure first increased and then gradually decreased. (3) From the spatial dimension, industrial structure and investment in anti-pollution projects as percentage of GDP accounted for the main spatial heterogeneity. Furthermore, this paper attempts to provide policy implications to help reduce carbon intensity and achieve carbon neutrality in China. [ABSTRACT FROM AUTHOR]

The continuous expansion of the construction scale of smart city has reconstructed the urban information pattern. How to maintain the stability of information security while giving full play to the role of information sharing is a practical problem that must be solved for the sustainable development of smart city. Based on the information ecology theory, this paper construct the smart city information security risk evaluation system from six aspects. Then, zGT2FSs is established based on type-2 fuzzy set theory and IAA method, which fully considers the internal and external uncertainty of expert decision-making. According to the calculation results, the key influencing factors of information security risk of smart city are analyzed to provide suggestions and guidance for the formulation of information security control in the process of smart city construction in China. [ABSTRACT FROM AUTHOR]

China's construction industry has assumed an important role in China's urbanization process, improving China's urban landscape and the level of national production and living facilities, but the productivity of the construction industry in some regions of China is still at a relatively low level. Taking the construction industry in Guangxi province in southwest China as an example, this paper analyzes the relevant indexes affecting the total factor productivity level of the regional construction industry and composes the statistical relationships among the indexes using dynamic measurement methods, and obtains that: (1) The number of employees, enterprises, labor productivity and construction profit have positive influence on the total factor productivity of Guangxi construction industry, but the improvement of regional construction gross product does not drive the improvement of technical equipment rate; (2) There is a dynamic equilibrium relationship between input and output indicators of total factor productivity of Guangxi construction industry, and the positive driving effect of output indicators on input indicators is not obvious; the influence of input indicators on output indicators is greater, and the positive influence is more. Accordingly, this paper also puts forward corresponding suggestions to promote the technical production level of Guangxi's construction industry. [ABSTRACT FROM AUTHOR]

Under the continuous development of China's social economy, the Internet and multimedia technology have been developed and innovated and are widely used in all walks of life and all fields. Because of their powerful interactivity, effectiveness, and dynamism, combining them with colleges and universities' English teaching plays an essential role in enriching teaching resources and improving teaching efficiency and quality. This paper proposes an improved LSTM model based on the web and multimedia environment, which improves the prediction effect of neural networks by adding an attention mechanism to the LSTM layer. The attention mechanism is based on a decision support system that automates the availability of various teaching resources to ensure an interactive teaching and learning environment in the colleges and universities. The decision support system of attention mechanism enhances the model's generalization ability by tuning the model parameters with the genetic algorithm (GA). Finally, this paper proposes some suggestions on improving the effectiveness of teaching English as a foreign language in the online and multimedia environment, taking into account the popular MU teaching format and English APP. The results show that the improved LSTM model outperforms the existing models in terms of various performance metrics. [ABSTRACT FROM AUTHOR]

A better understanding of various patterns in the coronavirus disease 2019 (COVID-19) spread in different parts of the world is crucial to its prevention and control. Motivated by the previously developed Global Epidemic and Mobility (GLEaM) model, this paper proposes a new stochastic dynamic model to depict the evolution of COVID-19. The model allows spatial and temporal heterogeneity of transmission parameters and involves transportation between regions. Based on the proposed model, this paper also designs a two-step procedure for parameter inference, which utilizes the correlation between regions through a prior distribution that imposes graph Laplacian regularization on transmission parameters. Experiments on simulated data and real-world data in China and Europe indicate that the proposed model achieves higher accuracy in predicting the newly confirmed cases than baseline models. [ABSTRACT FROM AUTHOR]

A better understanding of various patterns in the coronavirus disease 2019 (COVID-19) spread in different parts of the world is crucial to its prevention and control. Motivated by the previously developed Global Epidemic and Mobility (GLEaM) model, this paper proposes a new stochastic dynamic model to depict the evolution of COVID-19. The model allows spatial and temporal heterogeneity of transmission parameters and involves transportation between regions. Based on the proposed model, this paper also designs a two-step procedure for parameter inference, which utilizes the correlation between regions through a prior distribution that imposes graph Laplacian regularization on transmission parameters. Experiments on simulated data and real-world data in China and Europe indicate that the proposed model achieves higher accuracy in predicting the newly confirmed cases than baseline models. [ABSTRACT FROM AUTHOR]

Lithium is one of the important strategic energy metals, which is in short supply in China. There are three major types of lithium deposits: brine and salt lake type, highly differentiated granite or pegmatite type, and carbonate-clay type. In recent years, some new types of lithium deposits have also begun to receive great attention and subject recent research. There are many crypto-explosive breccia pipe type deposits in the world, including copper, gold, lead, zinc, tungsten and tin deposits, but little is known about this type of lithium deposit. This paper introduces the latest research results of the Weilasituo Sn−Li−Rb polymetallic deposit in Inner Mongolia (NE China), which occurs in the middle-southern section of the Great Xing'an Range metallogenic belt. A remarkable feature of this deposit is the coexistence of various mineralization types, including granite type Rb and Sn−Zn, hydrothermal crypto-explosive breccia pipe type Li−Rb, quartz vein type Sn−Zn and sulfide vein type Pb−Zn−Ag mineralization. Among them, hydrothermal crypto-explosive breccia pipe type Li-Rb deposit is currently very rare at home and abroad, which is likely a new type of rare metal deposit that worthy of our attention. This paper systematically summarizes the geology, alteration and mineralization, geochemistry, isotopes and geochronology of the Weilasituo deposit, and establishes a new petrogenic and metallogenic model. [ABSTRACT FROM AUTHOR]

The paper seeks to examine whether and on what basis the international human rights law applies to the territorial non-state entities, having as an example the cases of the Republic of China and the territorial non-state entities from the post-Soviet space. For this purpose, the paper will focus first, on the applicability of the relevant international human rights treaties and general international human rights law regulations. Second, it will look at what place is reserved for the international human rights law in the national legal systems of the analysed territorial non-state entities. It is argued here that these territorial non-state entities proclaim their commitment to the rule of law and human rights by transplanting international regulations, especially the human rights ones, into their national provisions. After analysing the two case studies, it will be claimed that although the territorial non-state entities committed themselves to following international human rights law norms and standards, legal transplant is not sufficient and the territorial non-state entities shall engage more at the practical level in order to ensure the effectiveness of human rights protection on their territories. [ABSTRACT FROM AUTHOR]

The paper scientifically evaluates the durability of masonry structure, reasonably predicts the residual life, and effectively protects the architectural heritage of masonry structure under the freeze–thaw cycle; investigated the deterioration law of traditional clay blue bricks comprehensively systematically. Through indoor experiments on clay blue bricks after freeze–thaw cycles, we investigated the changes in appearance, microstructure characteristics, quality and water absorption, changes in compressive strength, damage degree, and residual life of traditional clay blue bricks. The results showed that the damage caused by the freeze–thaw process to the blue brick reflected the decay of the macro-mechanical properties, the expansion of the microstructure, and the development of micro-defects is the intrinsic reason for the devolution of the mechanical properties. Furthermore, the water absorption rate of the blue brick increased rapidly at the beginning of the freeze–thaw cycle. In contrast, the mass-loss rate was low, and the opposite was the case in the late freeze–thaw period. We obtained the damage value of the blue clay brick according to the basic concept of macroscopic phenomenological damage mechanics and established the damage evolution equation. Under the action of the freeze–thaw process, the paper proposed a method of predicting the residual life of blue bricks. The analysis of compressive strength, freeze–thaw processes, and the service life calculated the relationship with the number of freeze–thaw cycles. Assuming that 10.0 MPa, 8.5 MPa, and 7.5 MPa are the failure strengths of blue bricks, the corresponding remaining service life is calculated as 36.5 years, 67.78 years, and 104.26 years. The research results provided the primary basis and essential reference for the scientific evaluation of the durability of buildings and the prediction of residual life under the action of freeze–thaw cycles. [ABSTRACT FROM AUTHOR]

DNA test is broadly used in diagnosis of crop disease and identification of genetic modified organism (GMO) in agriculture. However, rapid, low-cost, user-friendly, and field-deployable DNA test method is still limit. Recently, the RNA programmable nuclease of CRISPR/Cas is engineered as a new nucleic acid detection platform, but their application in plant remains to explore. In this study, we evaluated the Cas12a-based DNA detection for crop disease diagnosis and GMO test. A total of 14 crRNAs were designed to target two Magnaporthe oryzae genes and a synthetic Cry1C gene which encodes Bacillus thuringiensis δ-endotoxin and has been used to develop transgenic rice cultivar (Bt-rice) in China. Using a fluorescent reporter, targeted genes were easily detected by LbCas12a after recombinase polymerase amplification (RPA) for all crRNAs, despite that the signal strength varied 2–3-folds between different crRNAs. We further combined the filter paper-based DNA extraction and lateral flow assay (LFA) with RPA-Cas12a for DNA detection. This optimized Cas12a diagnostics method is carried at body temperature and does not require extra instrument except filter paper and LFA strip. Our data show that rice blast pathogen and Bt-rice were efficiently identified from leaf disc samples using this optimized DNA test method with highly active crRNAs. Moreover, LbCas12a exhibited variable nuclease activities on different targets; therefore, highly active crRNA is critical for successful DNA test using Cas12a and LFA. Owing to its simplicity, efficiency, and low-cost, DNA test using CRISPR/Cas12a would be easily applied in field for crop disease diagnosis and GMO administration. [ABSTRACT FROM AUTHOR]

The widespread use of the Internet of Things (Iot) makes it possible to connect everything but having enough IP addresses is a fundamental requirement of this paradigm. All previous environmental monitoring systems in China are based on IPv4. In combination with the characteristics and requirements of China's atmospheric environment monitoring system, this paper develops a monitoring system based on IPv6 technology. Users can directly access the monitoring equipment through the IPv6 website to view data and configure operations. This paper first introduces the design and implementation of the software and hardware of the system, then introduces the simplification of IPv6 protocol, the transplantation of IPv6 protocol on ARM and the design and implementation of embedded Web server system. The experimental results show that the developed atmospheric environment monitoring system can realize continuous data acquisition based on IPv6 and provide data-driven support for environmental protection management and decision-making. [ABSTRACT FROM AUTHOR]

The recent years have witnessed a significant change in China–EUrope relations, with the EU's strategic positioning of China undergoing a fundamental shift from a "partner" to a "systemic rival." By applying a theoretical framework based on neoclassical realism, the present paper examines the determinant factors leading to such a shift. This study highlights three factors: first, a change in the US's strategy and governance capability; second, the power symmetries between China and EUrope, including salient changes in material strength and marked differences in norms; third, an emergent change in strategic culture, encompassing a striving China vis-à-vis a strategically autonomous EUrope. By following Götz's (2021) insights on neoclassical realist approaches that employ intervening variables as complementary factors, we identify the US factor as the most important international factor in structural terms, while the power symmetries and strategic culture act as complementary factors. The paper concludes that while maintaining engagement, China–EUrope relations will only see further intensified rivalry and contradictions in the future. [ABSTRACT FROM AUTHOR]

Ever since China has formally joined the WHO-backed global COVID-19 vaccine initiative known as COVAX, there is a presumed notion that China's vaccine diplomacy will make a significant contribution to the international public good and thus uplift Beijing's role as the rule-maker of international order. To scrutinize this, the paper asks if China succeeded in proliferating its weaponized vaccine policy to obtain maximum diplomatic gains and soft power projection to intensify its international image, geopolitical power, and domestic politico legitimacy. The authors argue that despite its vaccine diplomacy demonstrated the robust governance capacity and responsibility to be a great power. Yet, Beijing's geopolitical influence and international image are significantly overrated and not enough to play a more prominent role in the global power fulcrum/equilibrium. On the contrary, China enjoys a leading position on the domestic political front. Its successful portrayal of China's vaccine provision in the global market and remarkable configuration to leverage a deep-rooted nationalism has fundamentally provided China with a powerful rationale to divert its public's attention from Beijing's earlier inadequate handling of the outbreak. The evaluation of the paper reveals that China's vaccine diplomacy's influence in promoting international image and geopolitics is limited but has successfully stabilized its domestic political environment and enhanced its domestic legitimacy. [ABSTRACT FROM AUTHOR]

This paper contends that the inclusion of meso- and micro-level perspectives has been under exploration in the study of the internationalization of humanities and social sciences, in particular, in a state-mandated system where policy interventions in higher education and knowledge production have typically been aligned with state construction and national development. It argues that institutional and individual responses to state policies on the internationalization of humanities and social sciences should be investigated due to their respective roles in policymaking and implementation. It has, therefore, retrieved recent and historical policy documents during the post-WTO period and collected empirical data from two Chinese universities. A constructivist-interpretivist qualitative approach and a qualitative case study strategy were adopted for this investigation. Based on an in-depth analysis of the empirical data, this paper reveals the gap between the macro-level ambition of achieving outward-oriented diffusion of innovations and the local-level realities, as well as institutional dilemmas and conflicts in facilitating the internationalization. [ABSTRACT FROM AUTHOR]