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The fossils of Hamipterus tianshanensis (Wang et al. in Curr Biol 24:1323–1330, 2014) and their eggs have important scientific significance because they can provide unique information about the reproduction, development, and evolution of pterosaurs. The fossils and the rock surrounding them have, however, been weathered, which including powdering and flaking, since they were relocated from Xinjiang to Beijing. The high content of soluble salts is a significant factor in fossil deterioration because the dissolution–recrystallization process can generate tremendous pressure and lead to decreased mechanical strength. This study evaluated the electrokinetic desalination performance for the fossils, and two types of poultices employed including paper pulp from Bioline® and CKS121 (cellulose: kaolin: sand = 1:2:1, w/w). Mercury intrusion porosimetry (MIP), scanning electron microscopy (SEM), ion chromatography (IC), and other methods were applied to evaluate the desalination effect. The surface salt content reduction by applied direct current (DC) was about 70%, and the inner salt content reduction was about 80%. The experimental results suggest that the electrokinetic method is a promising way to desalinate fossils. Nonetheless, cracks appeared in the surrounding rock crack after electrokinetic desalination, which can be explained by the montmorillonite swelling-induced stresses. Pre-consolidation, especially for electro-chemical method may solve the cracking problem for the clay-rich sandstone desalination. [ABSTRACT FROM AUTHOR]

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

Kazakh cheese is a traditional dairy product in Xinjiang, China. The function and potential probiotic characteristics of Saccharomyces cerevisiae DL6–20 and Kluyveromyces marxianus B13–5 in Kazakh cheese and its contribution to cheese fermentation was studied. In this study, the effect of the addition ratio of gamma aminobutyric acid (GABA)-producing S. cerevisiae DL6–20 and K. marxianus B13–5 on cheese quality was investigated. Cheeses were prepared by fermentations with a total of six treatments: comercial culture alone as control (CS), a combination with one yeast, either; K. marxianus B13–5 (CSM); S. cerevisiae DL6–20 (CSS); and three different proportions of this two yeasts (CSM:CSS 1:1, 1:2, 2:1). We measured the GABA content of cheese, as well as basic physical and chemical indicators, microbial content, free amino acid (FAA) content, texture, and flavor compound content. The total FAA content of mixed bacteria fermentation was higher than that of the single bacteria alone. The GABA content CSM:CSS 1:2 GABA content was 0.114 g/100 g, CSM:CSS 2:1 GABA content was 0.12 g/100 g, CSM:CSS1:1 content of GABA produced in the late ripening period of cheese was the highest, reaching 0.189 g/100 g and the number of LAB and yeasts in CSM:CSS 1:1 was higher than that of other cheeses. The mixed-strain fermentation generally produced cheeses with a higher protein content than that of the single-strain fermentation in the late stage of the maturation process, especially the protein content of CSM:CSS 1:1 during the ripening period, when the protein content was highest at day 50. CSM:CSS 1:1 had a low moisture content, making it easy to store. With the exception of water and protein content, there is no significant difference in other physical and chemical indicators. CSM:CSS 1:1 contributed to the formation of cheese texture. In addition, multivariate statistical analysis indicated that mixed-strain fermentation was beneficial to the production of cheese aroma, with the aroma production performance of CSM:CSS 1:2 and CSM:CSS 2:1 found to be better than that of CSM: CSS 1:1. [ABSTRACT FROM AUTHOR]

The technology of plastic film mulching is widely applied in Xinjiang, but it also brings about serious issues of residual film pollution. Currently, the 1MSF-2.0 residual film recovery machine can effectively address the problem. However, it faces challenges such as high overall machine weight and noticeable frame vibrations, which affect the stability of the entire machine operation. The frame, as the installation foundation, needs to bear loads and impact. Therefore, the reliability of the frame is crucial for the stability of the entire machine. Improving the frame's vibration is of great importance. In response to the significant vibration issues during the operation of the 1MSF-2.0 residual film recovery machine, this paper utilized Workbench 2020 R2 to establish a finite element model of the machine frame and conducted static analysis to obtain strength information, thereby initially understanding the optimization space of the frame. Building upon this, Mechanical was employed to solve the first 14 natural frequencies and mode shapes of the frame, and the accuracy of the theoretical analysis was verified through modal testing. After analyzing the frequency characteristics of external excitation forces, it was found that the fourth-order natural frequency of the frame fell within the frequency range of the excitation force of the shaft of the straw grinder, causing resonance in the frame and necessitating structural optimization. The optimal results indicated that the optimized frame increased in mass by 4.41%, reduced the maximum stress value by 2.56 MPa, and increased the fourth-order natural frequency to 22.7 Hz, avoiding the frequency range of the excitation force of the shaft of the straw grinder, thus improving the resonance issue. This paper provides a reference for optimizing the design of the frame of the residual film recovery machine. [ABSTRACT FROM AUTHOR]

With the development of detrital zircon U–Pb ages and Hf isotope analysis as conventional sedimentological research methods, a large number of studies have been conducted in the Tarim, West Kunlun, Tajik, Pamir and Tianshuihai regions and abundant data have been accumulated. Summarizing these data to characterize sedimentary units and source regions is more important than local studies of specific geological epochs; therefore, we compiled a database of detrital zircon U–Pb ages and Hf isotope analyses from the Tarim, West Kunlun, Pamir, Tajik and Tianshuihai terranes. The database contains data from 90 papers, including 35,281 individual U–Pb ages and 4,181 Hf isotope analyses. The database records the literature source, petrologic sample information, regional geological information, geographic coordinates and analytical parameters for each data point in as much detail as possible to allow readers to review, process, analyse and use the data. The database relies on the Deep‐time Digital Earth (DDE) platform and uses an open database update system to enable sharing and collaborative building. We encourage other researchers to contribute relevant published data to facilitate wider use. [ABSTRACT FROM AUTHOR]

This paper systematically presents the development process of studying ancient Chinese ethnic scripts over the past seven decades since the founding of the People's Republic of China in 1949, including the establishment of related research institutions and academic disciplines. Firstly, it records the establishment of the Chinese Association for Ethnic Paleography, the emergence of ancient scripts of ethnic groups in China as an academic discipline, and the conduction of a comprehensive and in-depth study of ancient Chinese ethnic literature in history. Secondly, this paper outlines the establishment of the National Leading Group for Compilation and Publication Planning of Ancient Ethnic Books, the census of ancient books written in ethnic scripts, the specialized preservation and conservation of ancient ethnic books in Xizang and Xinjiang, the promotion of compiling and publishing ancient ethnic books, and how the promotion further drives the protection of and research on ancient books written in ethnic scripts. Thirdly, the paper lists many innovative outcomes in studying ancient ethnic books. Fourthly, the paper proposes to conduct further censuses and in-depth research in this area, establish a grading system for ancient ethnic books, and utilize the resource of ancient ethnic books written in ethnic scripts in a modern context to further promote the excellent cultural heritages of the Chinese nation and enhancing ethnic unity and national unity. [ABSTRACT FROM AUTHOR]

The technique of refracturing is an effective method to solve the rapid decline in oil well production caused by factors such as severe reservoir energy loss and fracture failure after the initial hydraulic fracturing of low-permeability reservoirs. The key to designing refracturing lies in establishing a model for evaluating the potential fracturing layers. Based on the geological characteristics of the low-permeability conglomerate reservoir in the Lower Wuerhe area of the Eig District of the Xinjiang Oilfield, this paper studies the influence of different development approaches on the distribution pattern of remaining oil in the reservoir. A coupled model of remaining oil distribution and the in situ stress field is established and discusses the characteristics of the four-dimensional in situ stress field under different development modes. This paper analyzes the influence of geological factors and well network factors on the distribution of residual oil, and analyzes the influence of various factors, such as reservoir properties and injection and extraction parameters, on ground stress. Based on the residual oil distribution and ground stress changes, an evaluation method for screening potential fractured layers in reservoirs with different development modes (water injection development and depletion development) is developed. [ABSTRACT FROM AUTHOR]

In this paper, the Integrated Nested Laplace Algorithm (INLA) is applied to the Epidemic Type Aftershock Sequence (ETAS) model, and the parameters of the ETAS model are obtained for the earthquake sequences active in different regions of Xinjiang. By analyzing the characteristics of the model parameters over time, the changes in each earthquake sequence are studied in more detail. The estimated values of the ETAS model parameters are used as inputs to forecast strong aftershocks in the next period. We find that there are significant differences in the aftershock triggering capacity and aftershock attenuation capacity of earthquake sequences in different seismic regions of Xinjiang. With different cutoff dates set, we observe the characteristics of the earthquake sequence parameters changing with time after the mainshock occurs, and the model parameters of the Ms7.3 earthquake sequence in Hotan region change significantly with time within 15 days after the earthquake. Compared with the MCMC algorithm, the ETAS model fitted with the INLA algorithm can forecast the number of earthquakes in the early period after the occurrence of strong aftershocks more effectively and can forecast the sudden occurrence time of earthquakes more accurately. [ABSTRACT FROM AUTHOR]

Carbon trading mechanisms and the development of integrated energy systems are important ways to realize the "carbon peaking and carbon neutrality" goal, and the problem of benefit distribution is of paramount importance to achieving the goal. The article innovatively takes the supply side of the provincial integrated energy system as the entry point, considers the economic value of carbon, and focuses on the rational allocation of each subject obtained by comparing different methods. The paper mainly uses the Shapley value of the cooperative game and the kernel method to establish the initial allocation to the main actors, and subsequently, it considers the introduction of the risk level, resource input, environmental pollution, technological innovation, and profit of the main actors to modify the result of the benefit allocation. This paper takes the power generation data of the Xinjiang region as an example, and the results show that 1) thermal power still has the most weight among all power generation modes and obtains 522.83, 503.48, and 406.30 billion yuan under the initial, nucleolus, and modified allocation methods, respectively, and receives the most revenue. 2) Considering that the multi-factor allocation method pays more attention to the allocation of fairness, compared with the initial allocation, thermal power gains decreased by 22.29%, while wind and solar power gains were improved by 17.87% and 60.90%, respectively. The result could be a stronger push for the development and transformation of power energy. 3) The feasibility of this game as a convex game should be verified, the improvement method should be demonstrated through examples, and the results should be compared with reality. Finally, policy recommendations are proposed, which will be useful for realizing the "carbon peaking and carbon neutrality" goal and the synergistic development of integrated energy systems. [ABSTRACT FROM AUTHOR]

To address the challenges posed by the fast-charging demand of electric vehicles, causing feeder load and voltage imbalances during operation, this paper introduces a spatio-temporal pricing strategy tailored to enhance feeder operation equilibrium. This approach facilitates the spatio-temporal guidance of fast-charging loads for electric vehicles in operation. This paper begins by formulating a spatio-temporal distribution model for electric vehicle fast-charging loads, considering owners' preferences. It further develops a behavioral model for the travel choices of electric vehicles, illustrating the impact of spatio-temporal electricity pricing at fast-charging stations on load distribution. Next, it proposes a multi-objective spatio-temporal pricing model and its solution method specifically designed for feeder-balance-oriented fast-charging stations. This model targets the minimization of the spatio-temporal imbalance in feeder voltage and load. It takes a comprehensive approach, considering the constraints of the spatio-temporal load distribution model and optimal power flow model. The resulting spatio-temporal pricing model for fast-charging stations is effectively solved using the extended Pareto evolutionary algorithm. To validate the effectiveness of the proposed method in achieving feeder balancing, this paper analyzes two examples: a self-built 29- node road network and a 9-node distribution network, as well as a 66-node road network and a 33-node distribution network in the Xinjiang region. The results show that the proposed method can effectively guide the charging of electric vehicles and make the load distribution more balanced. [ABSTRACT FROM AUTHOR]

This paper aims to introduce a new theory, techno-realism, which is derived from political realism, to help comprehend the complex connections between technology and politics. According to techno-realism, technology serves as a means of power, with the innate drive for survival in human nature shaping the formation of identity. The research question at the core of this study revolves around the extent to which technology influences contemporary political science and whether it truly serves as a means of power. Three concepts are introduced: identity establishment, technology as the central source of power, and non-state actors in politics. The primary case study focuses on the complexity of the issue in Xinjiang, examining the application of cyberpolitics in the region. The second case study explores technology’s role in Indonesia’s political power struggle, as evidenced by its 2024 elections and the abuse of information and electronic transaction law effectiveness to control freedom of speech. Additionally, this paper introduces a case study on the Indo-Pacific regional power dynamics in confronting “digital authoritarianism”. This paper underscores the imperative for a new theoretical framework, adapted from political realism, which despite being subject to considerable criticism, has the potential for further development, placing technology at the core of analysis. Recognising the central roles of technology, identity formation, and non-state actors, techno-realism offers valuable insights for navigating complex political landscapes and informing strategic responses to emerging challenges. However, further research is needed to understand completely its applicability and limitations across different contexts, as demonstrated by the case studies presented in this paper. [ABSTRACT FROM AUTHOR]

The Ziyuan-1 (ZY-1) 02E launched on December 26, 2021 is equipped with a thermal infrared sensor (IRS), which has a ground resolution of better than 16m and a width priority of 115km, balancing the advantages of high resolution and large wide observation. The geometric performance of image data is the premise of remote sensing application, and the difficulty in evaluating the geometric performance of thermal infrared image data lies in the extraction of well-distributed, reliable and accurate GCPs. To extract GCP from high-precision reference images, it is necessary to overcome the feature differences between images caused by different spectral responses. This paper adopts a phase correlation matching method based on frequency domain to realize the fine registration of the data obtained by the emission thermal spectral band with the data from the reflectance spectral band, which can not only solve the GCP extraction of conventional thermal infrared images collected during the day, but also obtain satisfactory GCP data from thermal infrared data acquired at night. In order to test the GCP method proposed in this paper, three typical areas are selected as the experimental areas, including Yiyang City in Hunan, Nagqu City in Xizang and Hami City in Xinjiang, and the internal geometric accuracy and absolute geolocation accuracy of the thermal infrared data spanning one year are evaluated and analyzed by using the reference data composed of the DOM with an accuracy of 2m and the DEM with an accuracy of 10m. The research results indicate that the internal geometric accuracy of ZY-1 02E IRS satellite image data is better than 1.0 pixels, and the performance is satisfactory. However, its absolute geolocation accuracy needs to be continuously improved, especially there are systematic errors in the ascending data at night that require further research. Overall, it meets the design accuracy indicators of satellites and can meet the application requirements of thermal infrared remote sensing. [ABSTRACT FROM AUTHOR]

Satellite laser altimetry technology, a novel space remote sensing technique, actively acquires high-precision elevation information about the Earth's surface. However, the accuracy of laser altimetry can be compromised by alterations in the satellite-ground environment, thermal dynamics, and cosmic radiation. These factors may induce subtle variations in the installation and internal structure of the spaceborne laser altimeter on the satellite platform, diminishing measurement precision. In-orbit calibration is thus essential to enhancing the precision of laser altimetry. Through collaborative calculations between satellite and ground stations, we can derive correction parameters for laser pointing and ranging, substantially improving the accuracy of satellite laser altimetry. This paper introduces a sophisticated calibration method for laser altimeter pointing and ranging that utilizes dense control points. The approach interpolates discrete ground control point data into continuous simulated terrain using empirical Bayesian kriging, subsequently categorizing the data for either pointing or ranging calibration according to their respective functions. Following this, a series of calibration experiments are conducted, prioritizing "pointing" followed by "ranging" and continuing until the variation in the ranging calibration results falls below a predefined threshold. We employed experimental data from ground control points (GCPs) in Xinjiang and Inner Mongolia, China, to calibrate the GaoFen-7 (GF-7) satellite Beam 2 laser altimeter as per the outlined method. The calibration outcomes were then benchmarked against those gleaned from infrared laser detector calibration, revealing disparities of 1.12 s in the pointing angle and 2 cm in the ranging correction value. Post validation with ground control points, the measurement accuracy was refined to 0.15 m. The experiments confirm that the proposed calibration method offers accuracy comparable to that of infrared laser detector calibration and can facilitate the updating of 1:10,000 topographic maps utilizing stereo optical imagery. Furthermore, this method is more cost-effective and demands fewer personnel for ground control point collection, enhancing resource efficiency compared to traditional infrared laser detector calibration. The proposed approach surpasses terrain-matching limitations when calibrating laser ranging parameters and presents a viable solution for achieving frequent and high-precision in-orbit calibration of laser altimetry satellites. [ABSTRACT FROM AUTHOR]

Aiming at the problem that the energy consumption of the boiler system varies greatly under the flexible peaking requirements of coal-fired units, an energy consumption prediction model for the boiler system is established based on a Least-Squares Support Vector Machine (LSSVM). First, the Mean Impact Value (MIV) algorithm is used to simplify the input characteristics of the model and determine the key operating parameters that affect energy consumption. Secondly, the Snow Ablation Optimizer (SAO) with tent map, adaptive t-distribution, and the opposites learning mechanism is introduced to determine the parameters in the prediction model. On this basis, based on the operation data of an ultra-supercritical coal-fired unit in Xinjiang, China, the boiler energy consumption dataset under variable load is established based on the theory of fuel specific consumption. The proposed prediction model is used to predict and analyze the boiler energy consumption, and a comparison is made with other common prediction methods. The results show that compared with the LSSVM, BP, and ELM prediction models, the average Relative Root Mean Squared Errors (aRRMSE) of the LSSVM model using ISAO are reduced by 2.13%, 18.12%, and 40.3%, respectively. The prediction model established in this paper has good accuracy. It can predict the energy consumption distribution of the boiler system of the ultra-supercritical coal-fired unit under variable load more accurately. [ABSTRACT FROM AUTHOR]

The combined effects of drought, warming and the changes in land cover have caused severe land degradation for several decades in the extremely arid desert oases of Southern Xinjiang, Northwest China. This study examined land cover changes during 1990-2008 to characterize and quantify the transformations in the typical oasis of Hotan. Land cover classifications of these images were performed based on the supervised classification scheme integrated with conventional vegetation and soil indexes. Change-detection techniques in remote sensing (RS) and a geographic information system (GIS) were applied to quantify temporal and spatial dynamics of land cover changes. The overall accuracies, Kappa coefficients, and average annual increase rate or decrease rate of land cover classes were calculated to assess classification results and changing rate of land cover. The analysis revealed that major trends of the land cover changes were the notable growth of the oasis and the reduction of the desert-oasis ecotone, which led to accelerated soil salinization and plant deterioration within the oasis. These changes were mainly attributed to the intensified human activities. The results indicated that the newly created agricultural land along the margins of the Hotan oasis could result in more potential areas of land degradation. If no effective measures are taken against the deterioration of the oasis environment, soil erosion caused by land cover change may proceed. The trend of desert moving further inward and the shrinking of the ecotone may lead to potential risks to the eco-environment of the Hotan oasis over the next decades. [ABSTRACT FROM AUTHOR]

Green finance is key in supporting industries' green transformation and helping achieve low-carbon economic (LCE) development. This paper constructs an LCE development index using panel data from 30 provinces in China from 2011 to 2020. Based on the establishment of the first five pilot green finance zones in China in 2017 as a quasi-natural experiment, the synthetic control method (SCM) is applied to explore the impact of green finance policies on the level of LCE development and to analyze the mechanism and evaluate the policy effects. The empirical results show that (1) the synthetic analysis unit better fits the development trend before the implementation of the pilot. (2) After the implementation of the pilot reform, the level of LCE development in Zhejiang, Jiangxi, Guangdong, and Guizhou provinces has a more significant enhancement effect, but the enhancement in Xinjiang is not significant, which indicates that the reform effect in Zhejiang, Jiangxi, Guangdong, and Guizhou is significantly better than that in Xinjiang to a certain extent. (3) The samples were statistically significant and passed the placebo and ranking tests. Additionally, this paper analyzes the mechanism of policy effectiveness in terms of sci-tech innovation (STI) and energy consumption structure: green finance as a grip for economic transformation can provide financial support for regional STI and energy consumption structure upgrade and promote the capital flow to green low-energy industries, ultimately achieving sustainable economic development. Based on the above findings, policy insights can be provided for the improvement of green finance pilot regions. [ABSTRACT FROM AUTHOR]

Highly-deviated wells are the key technology to reduce the risk of drilling accidents and improve the utilization of reservoirs. However, for reservoirs with complex lithology, highly-deviated wells are faced with the problems of geomechanical transformation and fracturing parameter optimization. The research on fracturing parameter optimization technology of high-deviated wells in complex lithologic reservoirs is helpful to the research and application of geomechanics in deep unconventional reservoirs. This paper is based on geological mechanics laboratory experiments and logging interpretation, combined with regional geological background, to clarify the geological and mechanical characteristics of the Fengcheng Formation shale oil region in the Mabei Slope. On this basis, based on the current geostress field and natural fracture distribution pattern of the Mabei Slope, an integrated model of shale oil geological engineering in local well areas was established. Based on the finite element method, optimization design was carried out for the cluster spacing, construction fluid volume, displacement, and sand volume of highly deviated well fracturing, and three-dimensional simulation of fracturing fractures was completed. The research results indicate that: (1) The current dominant direction of the maximum principal stress in the Fengcheng Formation on theMabei Slope is from northeast to southwest, with themaximum horizontal principal stress generally ranging from 90 to 120 MPa and the minimum horizontal principal stress generally ranging from 70 to 110 MPa. (2) The difference in stress between the two horizontal directions is relatively large, generally greater than 8 MPa. Two sets of natural fractures have developed in the research area, one with a northwest southeast trend and the other with a northeast southwest trend. The natural fracture density of the Fengcheng Formation shale reservoir in the Mabei Slope is 0.32-1.12/m, with an average of 0.58/m, indicating amoderate to high degree of fracture development. (3) The geological model and three-dimensional geo-mechanical model are established according to the actual drilling geological data, and different schemes are designed to carry out single parameter optimization. The optimization results show that the optimal cluster spacing of the subdividing cutting volume pressure of the highly deviated wells in the Fengcheng Formation of the Mabei Slope is 12 m, the optimal construction fluid volume is 1400-1600 m³/section, the optimal construction displacement is 8 m³/min, and the optimal sanding strength is 2.5 m³/m. At the same time, by comparing the fracturing implementation effect with the fracturing scheme design, it is proven that the artificial parameter optimization method for highly deviated wells based on the finite element method based on the regional stress background and the natural fracture development law proposed in this paper is feasible and can provide a scientific basis for the fracturing development of highly deviated wells in complex lithologic reservoirs. This research has been well applied in Mahu area of Xinjiang oilfield. [ABSTRACT FROM AUTHOR]

Enhancing allocation efficiency is vital for maintaining China’s position as a leading textile producer. The adoption of information and communication technology (ICT) can improve the efficiency of farmers’ input allocation. Nonetheless, limited evidence exists regarding the impact and extent of farmers’ access to digital agricultural extension through subscribing to agricultural WeChat public accounts (WPAs) on allocation inefficiency costs. Using a 2019 farm household survey of cotton farmers in Xinjiang, this paper employs a primal system model to calculate farmers’ allocation inefficiency costs and a two-stage residual inclusion approach model (2SRI) to estimate the effects of agricultural WPAs subscription on allocation inefficiency costs and allocation inefficiency. The empirical findings indicate that the average allocation inefficiency cost is 3.264 Yuan per kilogram, constituting 45.8% of cotton production cost. Our results demonstrate that subscribing to agricultural WPAs can significantly reduce farmers’ allocation inefficiency costs by 19.5% and decrease allocation inefficiency by 0.079. Consequently, promoting smallholder farmers’ access to digital agricultural extension serves as an effective strategy to enhance allocation efficiency and lower costs. [ABSTRACT FROM AUTHOR]

Xinjiang is the largest cotton-producing region in China, but it faces a severe shortage of water resources. According to relevant studies, the cotton yield does not significantly decrease under appropriate limited water conditions. Therefore, this paper proposes a water and fertilizer integrated control system to achieve water and fertilizer conservation in the process of cotton field cultivation. This paper designs a fuzzy neural network Proportional–Integral–Derivative controller based on the improved Wild Horse Optimizer to address the water and fertilizer integrated control system's time-varying, lag, and non-linear characteristics. The controller precisely controls fertilizer electrical conductivity (EC) by optimizing parameters through an improved Wild Horse Optimizer for the initial weights from the normalization layer to the output layer, the initial center values of membership functions, and the initial base width of membership functions in the fuzzy neural network. The performance of the controller is validated through MATLAB simulation and experimental tests. The results indicate that, compared with conventional PID controllers and fuzzy PID controllers, this controller exhibits excellent control accuracy and robustness, effectively achieving precise fertilization. [ABSTRACT FROM AUTHOR]

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

The beginning of human settlement in the Hami Basin, located in the eastern part of Xinjiang, has been a focal question for the academic community in China. In particular, the thesis that the immigrating population from the Hexi Corridor since the late Neolithic founded the Tianshanbeilu culture has riveted the attention of scholars. Pottery wares, abundantly discovered at the synonymous cemetery of this culture, have played a key role in extrapolating population migration and cultural interaction. This paper aims to test the thesis by characterizing the chemical composition, painting pigment, and carburizing technique of 70 pottery samples from the cemetery with various scientific methods. It shows that the chemical compositions of the coarse pottery in the three colors of red, yellow, and gray, painted and unpainted alike, are remarkably different from those of fine pottery in black and red, indicating that the raw materials for the coarse and fine pottery samples are possibly procured from different sources; the pigments of the red slip and black paint are derived from hematite, black manganese ore, and carbon black; carburizing and polishing techniques are further applied to the gray coarse pottery; In combination with the compositional data of pottery samples from the Yaer cemetery also in the Hami Basin and the Xichengyi settlement in the Hexi Corridor, this paper finds that some pottery wares of the Tianshanbeilu culture were exchanged within the Hami Basin, but each site had its own production facility. No direct exchange of pottery wares with Xichengyi is attested; the similar style of pottery wares between the two sites may have resulted from population migration and technological exchange. [ABSTRACT FROM AUTHOR]

LuTan-1 (LT-1) is a bistatic synthetic aperture radar (BiSAR) system consisting of two identical L-band SAR satellites. The bistatic mode of LT-1 plays a critical role in generating high-precision digital elevation models (DEMs), which requires precise geometric calibration of initial range and azimuth times for both SARs to ensure the reliability and quality of geolocation. However, existing geometric calibration methods predominantly focus on monostatic SAR systems, with limited literature on slave SAR calibration in bistatic systems. This research addresses this gap by establishing geometric calibration models for both SARs based on signal echo history and the range–Doppler model. The geometric errors are effectively resolved using corner reflector data from Xinjiang, China. Through statistical analysis of LT-1 SAR images acquired between July and November in bistatic mode, this paper has demonstrated range delay accuracy of better than 5 ns and azimuth time accuracy of better than 0.1 ms. This level of precision translates into a positional accuracy better than 0.8 m. The proposed models have been successfully applied to geometric calibration, providing precise geolocation for LT-1, thus enhancing its utility for a wide range of Earth observation applications. This paper is the first endeavor to present the assessment of the geometric calibration and geolocation accuracy of LT-1 and discuss the results of the bistatic geometric calibration of the master and slave SARs in a BiSAR formation. [ABSTRACT FROM AUTHOR]

In recent years, air pollution in Xinjiang, the core region of the Silk Road Economic Belt, has become increasingly severe, posing a more significant threat to human health. This paper selects the tropospheric ozone, nitrogen dioxide, and formaldehyde datasets under OMI remote-sensing monitoring and the PM2.5 dataset in China High Air Pollutants (CHAP) for 2018–2021. The spatial and temporal distribution of multi-pollutants, the spatial autocorrelation of Moran's I index pollutants, and the correlation between pollutants in the warm period were studied in southern Xinjiang. Meanwhile, the geographical and temporal weighted regression (GTWR) model was used for influencing factor analysis, and the BenMap-CE model was used for health benefit analysis. The results showed that the spatial distribution of ozone concentration values in southern Xinjiang shows a decreasing distribution pattern from the east–central region to the western and southern regions. The spatial distribution of formaldehyde concentration values is opposite to that of ozone. There is a clear high-value area in the ozone concentration value in April–September. The NO2 column concentration values were in the range of 0.55~1.09 × 1015 molec/cm2 in most parts of southern Xinjiang. The area of high concentration values is located in the northeast of the study area; PM2.5 concentration values are higher in the middle area of southern Xinjiang. The spatial autocorrelation characteristics showed that the spatial aggregation of O3 and NO2 displayed a slow increasing trend year by year. The spatial aggregation of HCHO and PM2.5 fluctuated slightly in four years. The overall trend of HCHO is slowly decreasing, while PM2.5 is fluctuating and increasing. In the GTWR model analysis, overall, the atmospheric pressure has a strong influence on all pollutants. The effect of NO2 on O3 was higher than that of HCHO among the four pollutants. The correlation between O3 and PM2.5 was as high as −0.7872. The BenMap-CE health benefits assessment concluded that the number of premature deaths caused by ozone pollution was much higher than that of premature deaths caused by PM2.5. The highest number of premature deaths for both pollutants occurred in Kashgar. [ABSTRACT FROM AUTHOR]

The research on landslide displacement prediction can help the early warning and prevention of landslide disasters in mining areas. In view of the problem that BP neural network is prone to local convergence and considering that the network trained based on time-series cumulative displacement may produce large errors in prediction, this paper proposes a method combining displacement increment and CS-BP (Cuckoo Search-Back Propagation) neural network to predict landslide displacement. Compared with the conventional landslide displacement prediction methods, this method uses displacement increment instead of the commonly used cumulative displacement as the network input data, selects the CS algorithm with fewer parameters and easy to implement to optimize the BP network to construct the prediction model, and predicts the corresponding amount of displacement change at the next moment by the historical landslide displacement increment. Combined with the measured data of three feature points of a mine in Xinjiang, China, obtained by the micro-deformation monitoring radar, the displacement prediction accuracy of the proposed model on the three measured data sets is compared with the prediction accuracy of the BP, GA-BP (Genetic Algorithm, GA), and FA-BP (Firefly Algorithm, FA) network prediction models based on cumulative displacement and incremental displacement, respectively. The experimental results show that this method achieves superior performance with an average root mean square error of 0.3261 and an average mean absolute error of 0.2785 across the three feature points, outperforming the other models, and holds promising applications in disaster prevention and control work. [ABSTRACT FROM AUTHOR]

Currently, the treatment of miscellaneous fill foundations, composed of a mixture of domestic garbage, construction solid waste, and natural soil, presents a significant challenge in urban peripheral engineering construction. This paper discusses the application of vibrating rod compaction technology for foundation treatment in Xinjiang. It evaluates the effectiveness of cross-section vibrating rod compaction equipment in reinforcing fine-grained miscellaneous fill foundations. The study analyzes the impact of construction disturbances caused by the insertion of the vibrating rod, monitoring horizontal stresses at various depths. Both laboratory and field tests show significant improvements: soil dry density increased by 8% to 18%, porosity decreased by 10% to 23%, compression modulus increased by 22% to 246%, and compression coefficient decreased by 8% to 70%. Additionally, cohesion (C) and angle of friction (ɸ) saw increases ranging from 7 to 38% and 3% to 25%, respectively. Below a depth of 3 m, cone tip resistance exceeded 10 MPa, and sidewall friction resistance increased to over 100 kPa, surpassing pre-treatment values. The standard penetration test results doubled stroke length compared to pre-treatment, indicating a substantial improvement in foundation bearing capacity. Surface wave tests before and after treatment showed a 15% increase in wave velocity, reflecting a more compact soil structure. The vibrating rod compaction method is innovative, energy-efficient, environmentally friendly, and economically beneficial, holding great potential for future miscellaneous fill treatments. [ABSTRACT FROM AUTHOR]

The output power of PV systems is influenced by various factors, resulting in strong volatility and randomness, which makes it difficult to forecast. Therefore, this paper proposes an Informer prediction model based on optimised VMD for predicting short-term PV power. Firstly, the temporal coding of the Informer model is improved and, secondly, the original sequence is decomposed into multiple modal components using VMD, and then optimisation of the results of VMD in conjunction with the optimisation strategy of SSA improves the characteristics of the time series data. Finally, the refined data are fed into the Informer framework for modelling and prediction, utilising the self-attention mechanism and multiscale feature fusion of Informer to precisely forecast PV power. The power of PV prediction data from the SSA-VMD-Informer model and four other commonly used models is compared. Experimental results indicate that the SSA-VMD-Informer model performs exceptionally well in short-term PV power prediction, achieving higher accuracy than traditional methods. As an example, the results of predicting the PV power on 24 April in a region of Xinjiang are 1.3882 for RMSE, 0.8310 for MSE, 1.14 for SDE, and 0.9944 for R2. [ABSTRACT FROM AUTHOR]

[Objective] Tiger nut is a cash crop in southern Xinjiang and its production relies on irrigation. This paper presents the results of an experimental study on the effect of irrigation amounts on physiological traits, yield, and water use efficiency of different varieties of tiger nuts. [Method] The experiment studied two varieties: the Henan Round Grain (HY) and the Inner Mongolia Round Grain (NY), each irrigated by 18 mm (W1), 27 mm (W2), 36 mm (W3), and 45 mm (W4) of water, respectively. In each treatment, we measured the changes in soil water storage, plant height, tiller numbers, photosynthetic traits, yield, water consumption, and water use efficiency of the plants at different growing stages. [Result] Soil water storage and water consumption of both varieties increased with irrigation amount. Compared to W1, W4 increased average soil water storage and water consumption of the plants by 24.84% and 60.57% for the HY, and 18.46% and 55.61% for the NY, respectively. The plant height, tiller numbers, net photosynthesis (Pn), stomatal conductance (Gs), transpiration rate (Tr) and the yield of HY increased with irrigation amount (P<0.05), peaking in W2 with increases of 24.60%, 15.11%, 28.14%, 34.86%, 40.49% and 13.92% compared to W1. Intercellular carbon content (Ci) decreased with increasing irrigation amount. With the increase in irrigation amount, the plant height, tiller numbers, Pn, Gs, Tr, and the yield of NY all increased first followed by a decline; their associated values in W2 were 26.07%, 20.26%, 19.69%, 38.38%, 44.92% and 20.83% higher than those in W1. On average, Ci decreased with irrigation amount, being lowest in W2. Water use efficiency and irrigation water use efficiency of both varieties decreased with irrigation amount. Principal component analysis showed the net photosynthetic rate and water use efficiency can be used as indicators for variety selection. [Conclusion] The optimal irrigation amounts for the varieties HY and NY are 45 mm and 27 mm respectively, which can promote healthy growth, improve yields, and enhance water use efficiency of the plants. [ABSTRACT FROM AUTHOR]

[Objective] Change in soil water content is not only an indicator of water stresses used for irrigation management but also controls biogeochemical processes in soil. In this paper, we study the feasibility of using thermal infrared imaging to estimate soil moisture dynamics. [Method] The experiment was conducted in July-August 2023 in a walnut orchard in Xinjiang. Thermal infrared images of the walnut canopy were measured continuously using a thermal infrared camera. Based on the HSV color space of the images, an improved K-means segmentation algorithm was proposed to analyze the change in canopy temperature. We also measured air temperature and humidity, illuminance, wind speed, atmospheric CO2, and soil water content in the 0-80 cm soil layer, from which we proposed an inversion model to estimate soil water dynamics. [Result] The improved K-means algorithm increased the accuracy from 82.34% to 94.55%, and the errors between the canopy temperature acquired from the images and the measured canopy temperature were in the range of 0 to 1.0. The infrared imaging method was most accurate between 14:00 pm to 16:00 pm. Our results showed that the walnut roots were most active in taking up water from the 40-60 cm soil layer 50-60 cm away horizons from the tree truck. Canopy temperature, air temperature and relative humidity, and atmospheric CO2 concentration were correlated with soil water content at significant levels; they can thus be used to estimate soil water dynamics, with a coefficient of determination of R2=0.86 and p<0.01. [Conclusion] The temperature acquired from the infrared images of the walnut canopy can be used with other metrological data and atmospheric CO2 concentration to estimate soil water dynamics in the root zone of the walnut. It provides a new method for improving soil water management in walnut orchards in Xinjiang. [ABSTRACT FROM AUTHOR]

This paper presents a study on the mechanical properties of cement-stabilized steel-slag-based materials under freeze–thaw cycles for a highway project in Xinjiang. Using 3D scanning technology the specimen model conforming to the real steel slag shape was established. The objectives of the study are as follows: to explore the sensitivity between the macro- and micro-parameters of the specimen and to establish a non-linear regression equation; and to study the changes in mechanical properties of materials under freeze–thaw cycles, fatigue loading, and coupled freeze–thaw cycle–fatigue loading. The results show that there are three stages of compression damage of the specimen, namely, linear elasticity, peak plasticity, and post-peak decline. Maximum contact forces between cracks and particles occur mainly in the shear zone region within the specimen. The compression damage of the specimen is a mixed tensile–shear damage dominated by shear damage. When freeze–thaw cycles or fatigue loads are applied alone, the flexural strength and fatigue life of the specimens show a linear relationship of decline. The decrease in flexural modulus at low stress is divided into the following: a period of rapid decline, a relatively smooth period, and a period of fracture, with a tendency to change towards linear decay with increasing stress. In the case of freeze–thaw–fatigue coupling, the flexural modulus of the specimen decreases drastically by about 50% in the first 2 years, and then enters a period of steady decrease in flexural modulus in the 3rd–5th years. [ABSTRACT FROM AUTHOR]

The Awulale Iron Metallogenic Belt (AIMB) has developed many medium–large iron deposits, of which the Zhibo iron deposit is selected as the research object in this paper. The Zhibo deposit's ore primarily consists of magnetite as the main mineral, accompanied by extensive epidotization. The mineral assemblage includes diopside, albite, actinolite, epidote, chlorite, K-feldspar, quartz, calcite, chalcopyrite, and pyrite. Magnetite is classified into two groups based on sulfide content and mineral assemblage (MagI for sulfide-free and MagII for sulfide-rich ores). Two-stage mineralization of magnetite has been identified based on mineral assemblages and paragenesis, including the magmatic stage MagI and hydrothermal stage MagII. Mag I shows inhomogeneous backscattered electron (BSE) textures and consists of BSE-light and -dark domains (Mag I-L and MagI-D). Seven subtypes of magnetite have been recognized in this deposit. MagI-L and MagI-D have formed in the magmatic stage and show BSE images in light and dark colors, respectively. MagI-L is anhedral to subhedral and is inclusion-free. MagI-D has mainly replaced MagI-L along fractures and contains inclusions and pores. MagII has formed in the hydrothermal stage and is characterized by coupled dissolution–reprecipitation (DRP) textures. It can be divided into five sub-generations, that is, MagII-1, MagII-2, MagII-3, MagII-L, and MagII-D. MagII-1, MagII-2, and MagII-3 comprise the core–mantle–rim texture, while MagII-L and MagII-D comprise the core–rim texture. MagII-1 is BSE-light and is enriched with inclusions and pores. MagII-2 has partly replaced MagII-1 and exhibits oscillatory zoning under BSE imaging. It also contains inclusions. BSE-light MagII-3 occurs as overgrowth along MagII-2 margins and is inclusion-free. MagI magnetite is enriched with V, Cr, and Ni, whereas MagII is enriched with W, Ta, Nb, Sr, Sb, Sn, Y, Zr, Mg, Al, and Ti, indicating a decreased temperature of magnetite formation. MagI-L crystallizes from the original magma, while MagI-D is formed from the residual magma enriched with incompatible elements. MagII crystallizes from later multiple hydrothermal activities through the dissolution of early magnetite and the re-precipitation of later magnetite or from MagI-D which has later undergone a hydrothermal overprinting process. According to the texture and chemical composition of magnetite from the Zhibo deposit, we suggest that the Zhibo iron deposit was formed from the initial magmatic origin and then underwent a hydrothermal overprinting process. [ABSTRACT FROM AUTHOR]

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Introduction: MYC transcription factors are the basic regulators of the jasmonic acid signaling pathway and play important roles in plant growth and development and the response to adverse stress. In recent years, severe winter freezing and late spring frost in the main planting area of walnut in Xinjiang have affected the growth and development of walnut, which has become a prominent problem restricting walnut production. Xinjiang wild walnut is the only remaining wild species of walnuts in China, which contains a lot of genes with excellent traits, and is important for the cultivation and breeding. Methods: In this paper, the physicochemical properties and bioinformatics of MYC transcription factor members in walnut were analyzed, and the nine MYC were screened from the transcriptome data under low temperature stress. At last, we study the subcellular localizations and the expression patterns of the nine MYC members in Xinjiang wild walnut. Results: The results revealed that 30 MYC members were identified from published walnut whole-genome data, and their evolutionary relationships with Arabidopsis and poplar were divided into six groups according to clustering analysis, among which JrMYC22 and JrMYC23 had high homology with PtrMYC2b, which is induced by jasmonic acid in response to lowtemperature stress. Walnut MYC members are unevenly distributed on 12 chromosomes. The prediction of promoter cis-acting elements of walnut MYC transcription factor family members revealed that cis-acting elements related to jasmonic acid and lowtemperature stress were the ones with the greatest number of members, with 12. In addition, all nine MYC family members in Xinjiang wild walnut plants responding to low-temperature stress exhibited strong fluorescence responses in the nucleus. The expression levels of these members in response to low-temperature stress revealed that JrMYC28, JrMYC31, JrMYC33, JrMYC34, and JrMYC35 were highly expressed, and it was hypothesized that JrMYC28, JrMYC31, JrMYC33, JrMYC34, and JrMYC35 might play a key role in the response to lowtemperature stress. Discussion: The results of this study provide a theoretical basis for further research on the functional mechanisms of the MYC transcription factor family members in walnut. [ABSTRACT FROM AUTHOR]

The spatial organization within ancient settlements offers valuable insights into the evolution of social complexity. This paper examines spatially and chronologically contextualized architectural structures and artifacts uncovered at the Late Bronze Age Shirenzigou site to explore the relationship between the use of space and underlying social dynamics in the Eastern Tianshan Mountains of Xinjiang (China). Central to our findings is a distinctive centripetal compound structure, consisting of a larger non-domestic building surrounded by smaller dwellings. This arrangement, along with the variety and distribution of the artifacts, reveals a complex interplay between private and communal spaces at the site, reflecting a growing complexity within the social fabric of the community. The formation of conglomerates of houses around a central communal structure which occurs across the Tianshan Mountains appears to be a strategic adaptation in response to environmental challenges and socio-political transformations across this region at the end of the second millennium BCE. [ABSTRACT FROM AUTHOR]

Habitat selection has been a central focus of animal ecology, with research primarily concentrating on habitat choice, utilization, and evaluation. However, studies confined to a single scale often fail to reveal the habitat selection needs of animals fully and accurately. This paper investigates the wintering whooper swan (Cygnus cygnus) in Manas National Wetland Park, Xinjiang, using satellite tracking to determine their locations. The Maximum Entropy model (MaxEnt) was applied to explore the multi-scales habitat selection needs of Manas National Wetland Park's wintering whooper swans across nighttime, daytime, and landscape scales. This study showed that the habitat selection of the wintering whooper swans varied in different scales. At the landscape scale, wintering whooper swans prefer habitats with average winter precipitations of 6.9 mm and average temperatures of −6 °C, including water bodies and wetlands, indicating that climate (precipitation and temperature) and land type (wetlands and water bodies) influence their winter habitat selection. During daytime, whooper swans prefer areas close to wetlands, water bodies, and bare land, with a more dispersed distribution of water bodies. For nighttime, they tend to choose areas within the wetland park where human disturbance is minimal and safety is higher. This study can provide scientific basis and data support for habitat conservation and management of wintering waterbirds like whooper swans, recommending targeted conservation measures to effectively manage and protect the wintering grounds of whooper swans. [ABSTRACT FROM AUTHOR]

The new development pattern is a strategic choice to reshape China's new advantages in international cooperation and competition. It is based on China's current development stage, changes in the environment, and other factors. Located deep within China's interior, Xinjiang is a crucial region for the development of the western region and the Belt and Road Initiative. Its agricultural resources are exported to numerous foreign nations. In the context of the new development pattern, this paper first examines the foreign trade issues in Xinjiang. Second, this paper analyzes the current state of Sino-Kazakhstani trade, in particular the current state of trade in agricultural products. In addition, the growth potential of Xinjiang's agricultural international trade is analyzed utilizing the gravity model and fuzzy algorithm. Finally, countermeasures for the mode of development of Xinjiang's international trade are proposed. [ABSTRACT FROM AUTHOR]

Background: Reasonable and accurate forecasting of outpatient visits helps hospital managers optimize the allocation of medical resources, facilitates fine hospital management, and is of great significance in improving hospital efficiency and treatment capacity. Methods: Based on conjunctivitis outpatient data from the First Affiliated Hospital of Xinjiang Medical University Ophthalmology from 2017/1/1 to 2019/12/31, this paper built and evaluated Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) models for outpatient visits prediction. Results: In predicting the number of conjunctivitis visits over the next 31 days, the LSTM model had a root mean square error (RMSE) of 2.86 and a mean absolute error (MAE) of 2.39, the GRU model has an RMSE of 2.60 and an MAE of 1.99. Conclusions: The GRU method can better predict trends in hospital outpatient flow over time, thus providing decision support for medical staff and outpatient management. [ABSTRACT FROM AUTHOR]

Long-staple cotton from Xinjiang is renowned for its exceptional quality. However, it is susceptible to contamination with plastic film during mechanical picking. To address the issue of tricky removal of film in seed cotton, a technique based on hyperspectral images and AlexNet-PCA is proposed to identify the colorless and transparent film of the seed cotton. The method consists of black and white correction of hyperspectral images, dimensionality reduction of hyperspectral data, and training and testing of convolutional neural network (CNN) models. The key technique is to find the optimal way to reduce the dimensionality of the hyperspectral data, thus reducing the computational cost. The biggest innovation of the paper is the combination of CNNs and dimensionality reduction methods to achieve high-precision intelligent recognition of transparent plastic films. Experiments with three dimensionality reduction methods and three CNN architectures are conducted to seek the optimal model for plastic film recognition. The results demonstrate that AlexNet-PCA-12 achieves the highest recognition accuracy and cost performance in dimensionality reduction. In the practical application sorting tests, the method proposed in this paper achieved a 97.02% removal rate of plastic film, which provides a modern theoretical model and effective method for high-precision identification of heteropolymers in seed cotton. [ABSTRACT FROM AUTHOR]

Handwritten signatures have traditionally been used as a common form of recognition and authentication in tasks such as financial transactions and document authentication. However, there are few studies on minority languages such as Uyghur and Kazakh used in Xinjiang, China, and no available public dataset for these scripts, which are widely used in banking and other fields. Therefore, this paper addresses this problem by constructing a dataset containing Uyghur, Kazakh, and Han languages and presents an automatic handwritten signature recognition approach based on Uyghur, Kazakh, Han, and public datasets. In the paper, a handwritten signature recognition method that combines local maximum occurrence features (LOMO) and histogram of orientated gradients (HOG) features was proposed. LOMO features use a sliding window to represent the local features of the signature image. The high-dimensional features formed by the combination of these methods are dimensionally reduced by principal component analysis (PCA). The classification is performed using k-nearest neighbors (k-NN), and it is compared with the random forest method. The proposed method achieved a recognition rate of 98.4% using a diverse signature database compared with existing methods. It shows that the method was effective and can be applied to large datasets of mixed, multilingual signatures. [ABSTRACT FROM AUTHOR]

For deep learning's insufficient learning ability of a small amount of data in the Chinese named entity recognition based on deep learning, this paper proposes a named entity recognition of local adverse drug reactions based on Adversarial Transfer Learning, and constructs a neural network model ASAIBC consisting of Adversarial Transfer Learning, Self-Attention, independently recurrent neural network (IndRNN), Bi-directional long short-term memory (BiLSTM) and conditional random field (CRF). However, of the task of Chinese named entity recognition (NER), there are only few open labeled data sets. Therefore, this article introduces Adversarial Transfer Learning network to fully utilize the boundary of Chinese word segmentation tasks (CWS) and NER tasks for information sharing. Plus, the specific information in the CWS is also filtered. Combing with Self-Attention mechanism and IndRNN, this feature's expression ability is enhanced, thus allowing the model to concern the important information of different entities from different levels. Along with better capture of the dependence relations of long sentences, the recognition ability of the model is further strengthened. As all the results gained from WeiBoNER and MSRA data sets by ASAIBC model are better than traditional algorithms, this paper conducts an experiment on the data set of Xinjiang local named entity recognition of adverse drug reactions (XJADRNER) based on manual labeling, with the accuracy, precision, recall and F-Score value being 98.97%, 91.01%, 90.21% and 90.57% respectively. These experimental results have shown that ASAIBC model can significantly improve the NER performance of local adverse drug reactions in Xinjiang. [ABSTRACT FROM AUTHOR]

Oil shale, as a vast potential resource, is considered an important alternative energy source, and its effective development and economic utilization are of significant importance in alleviating the contradiction between energy supply and demand. Presently, the in situ conversion technology for oil shale has gained significant global attention, with numerous extraction methods undergoing active research and development. One of these methods is the in situ conversion of oil shale based on the hydration reaction of calcium-oxide-based composite material (CaO-CM). This approach harnesses the heat produced by the reaction between CaO-CM and water as a heat source for the pyrolysis of oil shale. This paper conducted experiments to assess the feasibility of temperature associated with this method. The feasibility study mainly includes two aspects: First, it is necessary to investigate whether the temperature generated by the hydration reaction of CaO-CM can meet the temperature requirements for the pyrolysis of oil shale. Through pyrolysis experiments of Xinjiang oil shale, the minimum temperature required for oil shale pyrolysis was determined to be 330 °C. High-temperature and high-pressure reaction vessels were employed to explore the temperature generated by the hydration reaction of CaO-CM. The results show that with the increase in environment pressure, environment temperature, and reaction mass, the maximum temperature generated by the hydration reaction of CaO-CM also increases (reach 455.5 °C), meeting the temperature requirements for the pyrolysis of oil shale. Second, the study evaluates whether the hydration reaction of CaO-CM can induce pyrolysis hydrocarbons of the oil shale. Through the pyrolysis experiments of oil shale based on the hydration reaction of CaO-CM, the changes in the content of pyrolysis hydrocarbons (S2) in oil shale before and after pyrolysis are measured. The results show that under 10 MPa pressure, the content of pyrolysis hydrocarbons in the oil shale decreased from 40.96 mg/g to 0.08 mg/g after pyrolysis. This confirms the feasibility of the temperature conditions for the in situ conversion of oil shale based on the hydration reaction of CaO-CM. [ABSTRACT FROM AUTHOR]

Since the issuance of the "Guiding Opinions on Vigorously Developing Sports Tourism" in 2016, the integration of sports and tourism has become a strategy in regional economic development. It creates new economic growth points, enhances local images, and promotes cultural communication. In the context of the "Tourism Makes Xinjiang Thrive" strategy, quantitatively investigating the integration of the sports and tourism industries helps people to better understand their interaction which can serve as the valuable input in policy-making for the comprehensive development of a region. This paper uses entropy weight method, stochastic frontier analysis and coupling coordination model to quantitatively analyze the effect of sports tourism industry integration in Xinjiang from the perspective of integration path. Meanwhile, the Dagum Gini coefficient and nuclear density estimation were used to analyze the regional differences and dynamic evolution of industrial integration quality. The result shows that (1) The sports and tourism integration quality in Xinjiang has not reached the optimal goal of complete integration. In the process of mutual industrial promotion, tourism promotes a higher degree of integration with the sports industry. (2) The industrial integration quality shows a phenomenon of "imbalance and inadequacy" among the regions. The regions with high quality of industrial integration were Urumqi, Ili, Kashgar, Altay and Changji, which have rich sports tourism resources. (3) The overall spatial difference in the quality of industrial integration presented a fluctuation downtrend. The difference between the tourism industrial belts was very significant. [ABSTRACT FROM AUTHOR]

The pivotal role of farmers' cropland conservation behavior (CCB) in advancing green agricultural practices is well-recognized. This paper underscores the critical role of stable land tenure in enhancing farmers' CCB, exemplified by the practice of mulch recycling. Drawing on a survey of 349 cotton farmers in Xinjiang, Northwest China, it offers a systematic examination of how land tenure stability influences CCB and its underlying mechanisms. The findings reveal a significant positive correlation between land tenure stability and CCB. Notably, this relationship is mediated by the facilitation of land mortgages, wherein written contracts and extended land tenure durations enhance farmers' participation in land mortgages, thereby bolstering CCB. Furthermore, the stabilizing effect of land tenure on CCB also mitigates the negative impacts of risk aversion and time preference. The study additionally highlights the differential effects of land tenure stability based on farm size and technical training; its facilitative role in CCB is more pronounced among larger-scale farmers and those engaged in technical training. [ABSTRACT FROM AUTHOR]

Gossypol is a yellow polyphenol naturally produced by Malvaceae plants such as cotton, which mainly exists in roots, stems, leaves, and seeds of cotton. Gossypol has animal toxicity, and long-term intake of gossypol will accumulate in livestock and cause poisoning, resulting in decreased fecundity, organ lesions, and even death of animals. The cotton output in Xinjiang is huge, accounting for more than 80% of the whole country. After cotton harvest, most of the waste cotton straws are directly crushed and returned to the field, resulting in great waste of resources. Cotton straw is rich in crude protein, cellulose, hemicellulose, and lignin, which is equivalent to common crop straw in nutritional components. However, its gossypol content exceeded the standard, which limited the application of cotton straw feed. How to achieve efficient and low-cost detoxification of gossypol has become the key factor to determining the fodder of cotton straw. The structure, properties, toxicity, detoxification technology, and detoxification mechanism of gossypol were summarized in this paper, which provided a reference for feed utilization of cotton straw. [ABSTRACT FROM AUTHOR]

The extended duration of mulching in Xinjiang cotton fields leads to a significant decline in the tensile strength of plastic film. When recycling is in operation, the soil and the spring teeth of the machinery used can easily cause secondary damage and fracture the residual film. Establishing appropriate working parameters for recycling is essential to enhance the overall quality of collection efforts. By analyzing the motion process of a chain-tooth residual film pickup device, we identified key working parameters that significantly impact the efficiency of recycling. Employing the finite element method (FEM) and a coupled algorithm incorporating smooth particle hydrodynamics (SPH), we developed a coupled finite element model representing the interaction among spring teeth, soil, and residual film. Through simulation and analysis of the process of inserting the spring teeth into the soil to collect film, we derived the governing rules for residual film stress and deformation changes. Utilizing forward speed, rotational angular velocity, and angle of entry into the soil of the spring teeth as test factors and selecting the residual film stress and the residual film deformation as test indices, we conducted a multi-factor simulation test. We established a mathematical model correlating test factors with test indices, and the influence of each factor on the test index was analyzed. Subsequently, we optimized the working parameters of the spring teeth. The results indicated that the optimal working parameters are forward speed of 1111.11 mm/s, rotational angular velocity of 25 rad/s, and angle of entry into the soil of 30°. At these values, the average peak stress of residual film was 4.51 MPa and the height of residual film pickup was 84.48 mm. To validate the optimized the spring teeth impact on performance, field experiments were conducted with recovery rate and winding rate as test indices. The results demonstrated a 92.1% recovery rate and a 1.1% winding rate under the optimal combination of working parameters. The finite element model presented in this paper serves as a reference for designing and analyzing key components of residual film recycling machines. [ABSTRACT FROM AUTHOR]

Shallow-buried, hard, and extra-thick coal seams are very common in Xinjiang, China, but there are relatively few studies on the mine pressure law and the development characteristics of water-flowing fracture zones (WFFZs) during the mining of such coal seams. In this paper, the mine pressure of the top coal caving face in a shallow, hard coal seam with a hard roof and full bedrock (SHCSHRFB) is analysed, the laws of the surrounding rock deformation and stress of the open-off cut and roadway in the large-mining-height top coal caving face are studied, the characteristics of roof-breaking and overburden fracture development are analysed using the physical similarity simulation method, supporting suggestions for roadways are put forward, and three development stages of the WFFZ are analysed. Field monitoring shows that the hydraulic support stress in SHCSHRFB is weak, but the coal wall and roadway stability are good, which is significantly different from the results in the typical shallow-buried thin bedrock working faces. The measured height of the WFFZ is close to the physical similarity simulation results, but quite different from those arising from use of the empirical formula. [ABSTRACT FROM AUTHOR]

The stress sensitivity of fractures has a significant impact on the production characteristics of tight sandstone gas reservoirs. However, there has been a lack of attention to and research on the differences between different types of fracture and their stress sensitivity. Based on the core samples of the Keshen gas reservoir in Xinjiang, China, this paper conducts a comprehensive comparison of the flow capacity, stress sensitivity, and the production characteristics of the structural fracture, diagenetic fracture, and artificial fracture. The findings reveal that the flow capacity of a single structural fracture is higher than that of a diagenetic fracture. Additionally, both structural and diagenetic fractures contribute to increasing the flow capacity of the porous system by 63 and 88%, respectively. The stress sensitivity of fractures varies from strong to weak, structural fractures exhibit a higher sensitivity compared to diagenetic fractures, and artificial fractures demonstrate the weakest stress sensitivity. Based on the fitting formulas of stress-sensitivity curves for different fractures, a new seepage model considering different stress sensitivities was established and numerical simulations were conducted. The numerical simulation results indicate that the gas well with a diagenetic-artificial fracture network yields a higher production, the 10-year production is 35.01% higher than that with a structural-artificial fracture network. This study is of great significance for understanding the production differences of fractured tight sandstone gas reservoirs and provides valuable insights for selecting optimal well locations. [ABSTRACT FROM AUTHOR]

The study of Hetian Aidelaisi crafts in Xinjiang Uygur is mostly operated with the Wig interpretation of viewing, and copying and imitation are often confused, leading to the modernization of the operational crafts and the absence of scientific representations of the traditional crafts, and inevitably the crisis of inheritance. Through literature review, video collection and drawing points, field investigation and other research methods, this paper systematically summarizes the production process, principles and techniques of Aidelaisi, in order to make some contributions to the inheritance and protection of this intangible cultural heritage. Analysis indicate that Aidelaisi silk woven with mulberry silk as raw material, uses the traditional reeling method to clarify the thread of the cocoon silk, and makes the single cocoon silk has enough strength to do Aidelaisi silk meridian and latitude. The dyes of Aidelaisi silk are taken from the roots, stems, leaves, flowers and fruit shells of plants and minerals. According to the requirements of the pattern, tie the warp thread with corn skin on the silk thread for tie-dye. Aidelaisi silk is woven using a traditional wood plain loom, The structure of the loom has some similarities with the ordinary folk loom in Xinjiang, just a more pedal brown. The loom fuselage frame is mainly built as a buckle, six brown and a scroll, a shuttle and six pedals. Reed and brown are made of bamboo and steel sheet respectively. [ABSTRACT FROM AUTHOR]

As the core area of human activities and economic development in the Xinjiang Autonomous Region, the hilly oasis zone of Xinjiang directly affects the regional sustainable development and stability of the ecosystem. Understanding the effects of different geomorphic types on vegetation distribution is crucial for maintaining vegetation growth and development, especially the improvement in the terrestrial ecological environment in arid areas under the background of climate change. However, there are few studies on the effect of spatial differences in detailed geomorphic types on vegetation distribution patterns. Therefore, this paper divides the Xinjiang hilly oasis zone into six geomorphologic level zones and innovatively investigates the influence of detailed geomorphologic types on the spatial distribution of vegetation and vegetation cover. Further, the area proportion of detailed landform types corresponding to different vegetation coverage in each geomorphic area was quantitatively calculated. Finally, the Geodetector method was used to detect the drivers of interactions between vegetation and the environment. The findings are shown as follows: (1) In the same climate zone, the spatial differentiation of landforms has a great influence on the vegetation distribution, manifesting as the significantly different vegetation distribution in different landform types. Grassland is the main vegetation type in the erosion and denudation of Nakayama; cultivated vegetation and meadows have a larger coverage in the alluvial flood plain and alluvial plain; and the distribution of vegetation in the Tianshan economic zone is characterized by obvious vertical zoning with the geomorphology. (2) The landform type and morphological types are the strongest driving factors for vegetation coverage with q values of 0.433 and 0.295, respectively, which effectually fill the gap caused by only using two terrain indicators, slope and elevation, to study the relationship between landforms and vegetation. (3) In addition, the improved nonlinear interaction resulting from the double factor of landform type and slope is 0.486, which has a stronger control on vegetation coverage than the single factor of landform type. These findings are conducive to enhancing the supply services of vegetation to the ecosystem in arid areas as well as providing important scientific guidance for the construction of ecological civilization and sustainable development in Xinjiang. [ABSTRACT FROM AUTHOR]

Snowmelt floods are highly hazardous meteorological disasters that can potentially threaten human lives and property. Hence, snowmelt susceptibility mapping (SSM) plays an important role in flood prevention systems and aids emergency responders and flood risk managers. In this paper, a method of identifying snowmelt flood hazards is proposed, and a large‐scale snowmelt flood hazard zonation scheme based on historical recordings and multisource remote sensing data is established. To assess the quality of our approach, the proposed model was tested in the cold and arid region of Xinjiang, China. Overall, 140 historical snowmelt flood events and 27 explanatory factors were selected to construct a geospatial dataset for SSM of the contemporary period. GridSearchCV was used to comprehensively search the candidate parameters from the grid of given parameters obtained with the random forest (RF) algorithm. Then, the geospatial dataset was divided into two subsets: 70% for training and 30% for testing. Next, SSM results were obtained with the RF algorithm using optimized parameters. The results indicate that our optimized RF classifier performs well for the task of SSM, with a high AUC value (0.975) for the test dataset. The validation and analysis suggest that the proposed method can efficiently identify snowmelt flood hazards in undersampled arid areas at a regional scale. [ABSTRACT FROM AUTHOR]