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China's argillaceous limestone reservoir has a lot of oil and gas resources, and hydraulic fracturing of the argillaceous limestone reservoir faces many difficulties. The first problem is that the heterogeneity of the argillaceous limestone reservoir is strong, and it is difficult to optimize fracturing parameters. The second problem is that there are a lot of natural fractures in the argillaceous limestone reservoir, which leads to a lot of fracturing fluid loss. The third problem is that the closure pressure of the argillaceous limestone reservoir is high, and the conductivity of fractures decreases rapidly under high closure pressure. The last problem is that the fracture shape of the argillaceous limestone reservoir is complex, and the law of proppant migration is unclear. The main research methods in this paper include reservoir numerical simulation, fluid-loss-reducer performance evaluation, flow conductivity tests and proppant migration visualization. To solve the above problems, this paper establishes the fracturing productivity prediction model of complex lithology reservoirs and defines the optimal hydraulic fracturing parameters of the argillous limestone reservoir in the Sichuan Basin. The 70/140 mesh ceramide was selected as the fluid loss additive after an evaluation of the sealing properties of different mesh ceramides. At the same time, the hydraulic fracture conductivity test is carried out in this paper, and it is confirmed that the fracture conductivity of 70/140 mesh and 40/70 mesh composite particle-size ceramics mixed according to the mass ratio of 5:5 is the highest. When the closure pressure is 40 MPa, the conductivity of a mixture of 70/140 mesh ceramic and 40/70 mesh ceramic is 35.6% higher than that of a mixture of 70/140 mesh ceramic and 30/50 mesh ceramic. The proppant migration visualization device is used to evaluate the morphology of the sand dike formed by the ceramsite, and it is clear that the shape of the sand dike is the best when the mass ratio of 70/140 mesh ceramsite and 40/70 mesh ceramsite is 6:4. The research results achieved a good stimulation effect in the SC1 well. The daily oil production of the SC1 well is 20 t, and the monitoring results of the wide-area electromagnetic method show that the fracturing fracture length of the SC1 well is up to 129 m. [ABSTRACT FROM AUTHOR]

The scheduling of rescue aircraft needs to be studied in depth because of its criticality for the general aviation rescue of forest fires. This paper constructs a collaborative schedule optimization model for general aviation rescue under the condition of multiple aircraft, from multiple rally points to multiple fire points, targeting the shortest rescue time and the lowest rescue cost in the context of forest fires based on the simulation verification of a forest fire that broke out simultaneously in multiple locations in Liangshan Prefecture, Sichuan Province, China. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) algorithm was used to find the optimal set of solutions satisfying the objective function: four feasible solutions. Then, the optimal solution was solved based on the weighted TOPSIS method, which was the optimal solution for this rescue task. The simulation results show that unnecessary flight times can be reduced by optimizing the schedule plan. Under the premise of ensuring rescue timeliness, the utilization rate of rescue aircraft was improved, and rescue costs were further reduced. The presented work provides a theoretical reference for the efficient development of general aviation rescue. [ABSTRACT FROM AUTHOR]

Although atmospheric CO2 concentrations collected by satellites play a crucial role in understanding global greenhouse gases, the sparse geographic distribution greatly affects their widespread application. In this paper, a hybrid CNN and spatiotemporal Kriging (CNN-STK) model is proposed to generate a monthly spatiotemporal continuous XCO2 dataset over China at 0.25° grid-scale from 2015 to 2020, utilizing OCO-2 XCO2 and geographic covariates. The validations against observation samples, CAMS XCO2 and TCCON measurements indicate the CNN-STK model is effective, robust, and reliable with high accuracy (validation set metrics: R2 = 0.936, RMSE = 1.3 ppm, MAE = 0.946 ppm; compared with TCCON: R2 = 0.954, RMSE = 0.898 ppm and MAE = 0.741 ppm). The accuracy of CNN-STK XCO2 exhibits spatial inhomogeneity, with higher accuracy in northern China during spring, autumn, and winter and lower accuracy in northeast China during summer. XCO2 in low-value-clustering areas is notably influenced by biological activities. Moreover, relatively high uncertainties are observed in the Qinghai-Tibet Plateau and Sichuan Basin. This study innovatively integrates deep learning with the geostatistical method, providing a stable and cost-effective approach for other countries and regions to obtain regional scales of atmospheric CO2 concentrations, thereby supporting policy formulation and actions to address climate change. [ABSTRACT FROM AUTHOR]

Aiming at the problem of ultra-low-frequency oscillation (ULFO) in power systems, with an oscillation frequency lower than 0.1 Hz, an oscillation suppression control method is proposed. Firstly, the mathematical modeling of the system is carried out, and a cascade correction control method of the governor of hydropower generators is proposed. Secondly, using the ability of photovoltaic (PV) active power to adjust the system frequency, an additional controller for PV active power is proposed. Then, a unified frequency model considering the two controllers is established for multi-hydro and multi-PV systems, and the structural singular value method is used to coordinate the design of the parameters of the hydropower and PV generator controllers to achieve robust performance. Finally, based on a time-domain simulation of single-hydro and single-PV systems and an actual demonstration system located in Sichuan Province, China, the results show that the control method proposed in this paper has a good suppression effect on ultra-low-frequency oscillation under different working conditions, and meets the requirements of robust performance. [ABSTRACT FROM AUTHOR]

Rural operation system reform is vital in promoting rural revitalisation and agricultural and rural modernisation in China. Based on the sample data of 153 counties in Sichuan Province from 2012 to 2020, this paper constructs a PSM-DID evaluation model to analyse the effectiveness of rural operation system reform on agricultural development from the perspective of policy action mechanism, variable differentiation and other aspects. The results show that: (1) rural operation system reform has significantly boosted the economic development of the counties implementing the pilot reform of the rural operation system; (2) rural operation system reform mainly has two components: rural land system reform and agriculture organisation innovation; both have an impact on county economic and social development, but the degrees of impact are different; (3) the effectiveness of the rural operation system reform policy has a specific time lag. The results of this paper enrich the effectiveness evaluation of the reform policy on economic development and have policy implications for further promotion of agricultural and rural reform in China. [ABSTRACT FROM AUTHOR]

Landslides are common natural disasters that cause serious damage to ecosystems and human societies. To effectively prevent and mitigate these disasters, an accurate assessment of landslide hazards is necessary. However, most traditional landslide hazard assessment methods rely on static assessment factors while ignoring the dynamic changes in landslides, which may lead to false-positive errors in the assessment results. This paper presents a novel landslide hazard assessment method for the Zagunao River basin, China. In this study, an updated landslide inventory was obtained for the Zagunao River basin using data from interferometric synthetic aperture radar (InSAR) and optical images. Based on this inventory, a landslide susceptibility map was developed using a random forest algorithm. Finally, an evaluation matrix was created by combining the results of deformation rates from both ascending and descending data to establish a hazard level that considers surface deformation. The method presented in this study can reflect recent landslide hazards in the region and produce dynamic assessments of regional landslide hazards. It provides a basis for the government to identify and manage high-risk areas. [ABSTRACT FROM AUTHOR]

Siliceous minerals of the Dengying Formation in the Gaoshiti–Moxi area in the central Sichuan Basin exhibit four types of quartz crystals (cryptocrystalline quartz, chalcedony, microcrystalline quartz, and megacrystalline quartz) and three structural types: cryptocrystalline, microcrystalline, and mosaic (laminated mosaic, window-hole interrupted mosaic, and arc-laminated mosaic). Siliceous minerals have a great influence on the storage performance of the reservoirs in the Dengying Formation. According to the petrophysical parameters of the Dengying Formation and porosity intersection diagrams, the siliceous dolomite and the reservoirs have low impedance characteristics, which makes it difficult to distinguish between them and leads to difficulties in the characterization and prediction of the reservoirs. The transverse wave velocity is favorable for reservoir characterization. Currently, the main method used to estimate the transverse wave velocity is petrophysical modeling, which establishes a relationship between the elastic and physical parameters of the reservoir. In this paper, the siliceous minerals in the dolomite in the study area are regarded as solid inclusions, and the calculation method of the rock matrix modulus is improved by using solid replacement. Then, an improved petrophysical model is constructed by combining the KT (Kuster–Toksöz) model, the DEM (Discrete Element Method) model, the Gassmann equation, and the Wood equation. The transverse wave velocity is estimated using the improved model under the constraint of the longitudinal wave velocity. The shapes of the transverse wave velocity curves obtained by the improved model and the deviations from the measured velocities are significantly better than those of the Xu–Payne model and other models. The results show that the improved model can effectively estimate the transverse wave velocity of the reservoir in this area, which provides a basis for future reservoir predictions in this area. [ABSTRACT FROM AUTHOR]

Promoting quality certification of agricultural products is a matter of the sustainable development of agriculture and the transformation of the global agri-food system, and cooperatives are an important carrier to achieve the above policy goals. However, few scholars have included external resources and cooperative quality certification behavior in an analytical framework from the perspective of resource embedding. This study combines resource dependence theory and embeddedness theory, based on survey data from 230 agricultural cooperatives in six counties of Sichuan Province, China. This paper constructs a theoretical analysis framework of government resources, market resources and cooperative quality certification, and uses binary Logit regression model to empirically study the correlation between external resources and cooperative quality certification. The results show that: (1) Cooperatives do not receive a high proportion of external resource support, with 30% and 47% receiving support from the government and market respectively; the proportion of cooperatives carrying out product quality certification was relatively low, about 29.57%. (2) Government resources and market resources have a significant positive effect on improving the quality certification of cooperatives, and the promotion effect of the market is greater than that of the government. (3) Mechanism analysis shows that government resources promote quality certification in cooperatives mainly through regulations on agricultural inputs, while market resources can jointly play a role on regulations on agricultural inputs and market expectations for certified agricultural products. [ABSTRACT FROM AUTHOR]

The relationship between government intervention and cooperative development has always been a source of controversy in the developing world. This paper aims to examine the rationale and successful conditions of government intervention to promote cooperative development in poor areas of rural China. In the context of the "targeted poverty alleviation" program (2015–2020), a government-led campaign covering all poverty-stricken villages in west China, cooperative development was listed by the central government as a criterion for evaluating successful intervention at the county government level. Accordingly, the central questions of this paper are: why is government intervention necessary to initiate a process of cooperative development in poor areas of China; and under what conditions can government intervention be successful, leading to sustainable cooperative development? Bearing in mind the complexity of government intervention with mixed results, both successful and failed, the above questions are addressed through a case study of XM Beekeeping Cooperative, representing one type of successful government intervention in poverty-stricken and ethnic-minority-dominated regions of China. Overall, government intervention is crucial in building cooperative ecosystems in poor regions of China. However, government intervention is not invariable because the approaches can be modified to accommodate the effect of the intervention. [ABSTRACT FROM AUTHOR]

In the face of the new reform of China's "unified electricity market", the frequency regulation ancillary service market in each region of China is still divided between using the MCP and PAB pricing mechanisms. The purpose of this paper is to explore the different impact the laws of the above two pricing mechanisms have on the frequency regulation market and to provide relevant suggestions for this electricity market reform. This paper simulates the competitive activities of the frequency regulation market based on the multi-agent simulation model, conducts a comparative experiment by changing the pricing mechanism to a single variable based on the rules of the Sichuan frequency regulation market in China, and concludes that MCP can make the market fast and stable, and that its market settlement price is low, which is suitable for the "unified electricity market". Although PAB makes the market settlement price high, it can ensure the retention of high-performance units in the market, and the stable settlement price makes this model able to accurately reflect the "price signal", making it suitable for late adoption in the "unified electricity market". [ABSTRACT FROM AUTHOR]

In Sichuan Province, China, most coal seams that are mined are steeply inclined; their roadways' surrounding rocks are asymmetric, with non-equilibrium deformations and unstable anchorage structures, thus making major safety hazards highly likely. Using field observations and a universal distinct element code (UDEC) numerical simulation method, this paper analyzed the time-dependent failure of the ventilation roadway of Working Face 1961 of the Zhaojiaba Mine, revealing the preconditions for such damage and a bidirectional deterioration mechanism for the deformation as well as stress of surrounding rocks. Moreover, this paper built an anchorage mechanical model for the thick layer of the roadway roof and proposed a cross-boundary anchor-grouting (CBAG) differential support technique. Calculations proved that the new support was particularly effective in restraining the expansion of tension cracks, thus preventing the slipping and dislocation deformations of rock masses on the curved roof side. The feedback of engineering applications showed that the maximum development depths of cracks in the arc roof and straight inclined roof of the roadway 150 m behind the working face are only 1.5 m and 1.10 m, decreasing by 61.3% and 47.6%, respectively, compared with the primary support. The proposed technology offers an overall thick-layer bearing structure for the surrounding rocks of roadways, effectively restraining the non-equilibrium large deformations of roadways in steeply inclined coal seams. [ABSTRACT FROM AUTHOR]

The rapid and accurate extraction of wide-area coseismic landslide locations is critical in earthquake emergencies. At present, the extraction of coseismic landslides is mainly based on post-earthquake site investigation or the interpretation of human–computer interactions based on remote sensing images. However, the identification efficiency is low, which seriously delays the earthquake emergency response. On the basis of the available multisource and multiscale remote sensing data, numerous studies have been carried out on the methods of coseismic landslide extraction, such as pixel analysis, object-oriented analysis, change detection, and machine learning. However, the effectiveness of coseismic landslide extraction was low in wide areas with complex topographic and geomorphic backgrounds. Therefore, this paper offers a comprehensive study of the factors influencing coseismic landslides and researches rapid and accurate wide-area coseismic landslide extraction methods with multisource remote sensing and geoscience technology. These techniques include digital elevation modeling (DEM) and its derived slopes and aspects. An embedded multichannel spectral–topographic feature fusion model for coseismic landslide extraction based on DeepLab V3+ is proposed, and a knowledge-enhanced deep learning information extraction method integrating geological knowledge is formed. Using the Jiuzhaigou Ms7.0 earthquake (seismic intensity VIII) in Sichuan Province, China, a comparison of landslide extraction models and strategies is carried out. The results show that the model proposed in this paper achieves the best balance in the accuracy and efficiency of wide-area extractions. Using multiple feature data of coseismic landslides, the problem of mixed pixels is solved. The rate of the misidentification of landslides as clouds, snow, buildings, and roads is significantly lower than in other methods. The identified landslide boundaries are smoother and more accurate, and the connectivity is better. Compared with other methods, ours can more accurately eliminate landslides not triggered by the Jiuzhaigou earthquake. While using the image block strategy to ensure extraction efficiency, it also improves the extraction accuracy of wide-area coseismic landslides in complex backgrounds. [ABSTRACT FROM AUTHOR]

With the continuous emphasis of the country on the construction of ecological civilization, promoting the utilization of straw resources has become an important measure to achieve green agricultural development. Based on the survey data of 540 households in Sichuan Province and under the guidance of the theory of planned behavior, this paper constructed the IV-Probit model to explore the impact of land transfer on the straw resource utilization of households. The results show that: (1) land transfer in and land transfer out can significantly promote the utilization of straw resources by farmers. (2) Heterogeneity analysis showed that land transfer in had a positive effect on crop straw utilization of the new generation and large-scale farmers. (3) Land transfer in can promote the utilization of straw resources by improving farmers' economic cognition and efficacy cognition; land transfer out can promote the utilization of straw resources by improving farmers' efficacy cognition. Accordingly, the government should improve the land transfer market, increase technology propaganda, and create an excellent policy environment to promote farmers' participation in straw resource utilization. [ABSTRACT FROM AUTHOR]

Simple Summary: In this study, we describe the well-preserved fossil seed cones of Nothotsuga found in the Mula Basin, Litang County, Sichuan Province, southwestern China. By detailed morphological comparisons, a new fossil species, Nothotsuga mulaensis Z. Li et J. L. Dong sp. nov. is named. This discovery suggests that Nothotsuga had a more northern distribution during the Miocene. In addition, it suggests that the Mula region had a humid and warm climate during this period. The ancient landform presents an intermountain lake basin, which would have been surrounded by higher mountains. After the Miocene, due to the uplift of the Tibetan Plateau, Nothotsuga was either unable to adapt to the extinction of the local environmental or was able to migrate to several scattered places in southern China. In this paper, we describe a new fossil species, Nothotsuga mulaensis Z. Li & J.L. Dong sp. nov. The discovery of the fossil species was based on well-preserved fossil seed cones that were found in the Mula Basin in Xiamula village, Litang County, Sichuan Province, southwestern China. The shapes of these fossils were characterized by ovate seed cones, rhombic or suborbicular scales with auriculate bases, and the bracts were ligulate-spathulate in shape. This finding suggests that Nothotsuga once had a wide distribution range in China and that it also inhabited the eastern Tibetan Plateau (TP). Nothotsuga mulaensis was distributed in an intermountain lake basin, at altitudes from 2000 to 2300 m, in a warm and humid environment. This finding also suggests that the eastern TP may have provided good habitat for Nothotsuga during the Miocene. In addition, we propose that the uplift, accompanied by the severe cooling and aridification that occurred after the Miocene, caused the disappearance of this species of Nothotsuga in the eastern TP. [ABSTRACT FROM AUTHOR]

The ion-adsorption rare earth deposit developed on the Mosuoying granite in the Panxi area of southwestern China represents a significant advancement in the exploration of ion-adsorption rare earth deposits in Sichuan. Being the first and currently the sole ion-adsorption rare earth deposit in Sichuan, studying its rare earth mineralization characteristics holds great importance. This paper aims to investigate the geochemical properties of the Mosuoying granite and its overlying weathered crust using rock geochemical methods based on field geological investigations. The findings reveal that the deposit belongs to the light rare earth type, with the ore-forming parent rock attributed to the high-potassium calc-alkaline series. It exhibits a high rock REE content ranging from 419 to 578 ppm, indicating favorable mineralization potential. Hydrothermal alteration reduces the REE content of the parent rock, leading to a notable increase in the LREE/HREE ratio, thus impacting the partitioning of rare earth elements and subsequent ore formation. The distribution characteristics of rare earth elements in each layer of the weathered crust are controlled by the parent rock and exhibit a light rare earth distribution pattern. The completely weathered layer is the main enrichment zone for rare earth elements, and the migration and enrichment patterns of rare earth elements in the weathered crust are evident. From the semi-weathered layer to the completely weathered layer, all REEs were gained, with a higher degree of migration for LREE. From the completely weathered layer to the clay layer, all REEs were lost, and the vertical distribution of rare earth content shows a "low-high-low" pattern. [ABSTRACT FROM AUTHOR]

Highlights: 1. How to quantitative evaluation of mechanical properties of shale in Da'anzhai section combined with triaxial mechanical experiments? The compressive strength of dry rock samples and soaked rock samples were tested by triaxial mechanical experiments. According to the stress-strain curves, the changes of compressive strength, elastic modulus and Poisson's ratio before and after hydration were analyzed. 2. How to establish a mathematical model of shale fracability that comprehensively considers brittleness index, horizontal differential stress, and fracture toughness is proposed? Fracability index is proportional to brittleness index and horizontal differential stress, and inversely proportional to fracture toughness. Young 's modulus, Poisson's ratio and tensile strength in fracability index model are related to rock water saturation, so the fracturing index is also related to rock hydration. 3. What is the effect of shale hydration on fracability and fracture pressure? As the water saturation rate of the rock gradually decreases, the FI of the formation rock de-creases Combined with the variation law of water saturation rate, it shows that after the shale around the well is hydrated, the fracture pressure of the formation decreases Accurate evaluation of shale oil reservoir fracability helps avoid blind fracturing and ensures efficient fracturing. However, the current evaluation of the fracability index rarely considers the impact of hydration caused by drilling fluid invasion during drilling. The results of a rock triaxial mechanical test conducted to evaluate the mechanical properties of shale oil reservoirs are reported in this paper. Based on the results, we developed a comprehensive evaluation method of shale oil reservoir fracability that considers hydration; the effects of the brittleness index, horizontal difference stress, and fracture toughness; and the law of water phase intrusion into shale oil reservoirs. The research results show that the average compressive strength decreased by 37.99%, the average elastic modulus decreased by 53.36%, and the average Poisson's ratio increased by 68.75% after being soaked for 48.00 h at 80 °C and 30.00 MPa. The water saturation rate at the borehole wall was the highest; with the extension to the stratum, it gradually decreases to the original water saturation rate of the formation, while the fluctuation radius gradually increases with time. The Young's modulus and fracture toughness decrease, the Poisson's ratio increases, and the fracability index reaches a maximum value at the wellbore (i.e., the highest water saturation rate), indicating that the strength of the hydrated rock decreases and it can be easily fractured. The case analysis shows that the optimal fracturing position of the Da'anzhai Section of Well NC2H is around 2600 m deep. After the hydration occurs, the fracture initiation pressure of the formation is reduced from the original value of 72.31 MPa to 66.80 MPa. This indicates that when hydration decreases, the formation fracture pressure also increases. The research presented in this paper can be used to optimize fracture location and set a reasonable fracturing pressure. [ABSTRACT FROM AUTHOR]

The geological storage of CO2 is a critical technique for reducing emissions, which significantly contributes to the mitigation of the greenhouse effect. Currently, CO2 is often geologically stored in coal seams, hydrocarbon reservoirs, and saline aquifers in order to store CO2 and improve the oil and gas recovery simultaneously. Shale formations, as candidates for CO2 storage, are drawing more attention because of their rich volumes. CO2 storage through shale formations in the Sichuan Basin, China, has tremendous potential because of the readily available CO2 injection equipment, such as abandoned shale gas wells. Therefore, we review the potential of using these wells to store CO2 in this paper. Firstly, we review the status of the geological storage of CO2 and discuss the features and filed applications for the most studied storage techniques. Secondly, we investigate the formation properties, shale gas field development process, and characteristics of the abandoned wells in the Sichuan Basin. Additionally, after carefully studying the mechanism and theoretical storage capacity, we evaluate the potential of using these abandoned wells to store CO2. Lastly, recommendations are proposed based on the current technologies and government policies. We hope this paper may provide some insights into the development of geological CO2 storage using unconventional reservoirs. [ABSTRACT FROM AUTHOR]

The giant panda (Ailuropoda melanoleuca) is a relic species in China and a flagship species in the field of endangered wildlife conservation. The conservation of the giant panda's habitat has gained widespread attention for this reason. Historically, Chinese Giant Panda Nature Reserves are surrounded by communities and the resource utilization behavior of households disturbs the giant panda habitat. Changes in these communities and in Giant Panda Nature Reserves began around 2010, with the feminization and aging of the farm labor force. These changes brought different resource utilization behaviors that led to different evolutionary tendencies in giant panda habitats. This research study assesses the impact of these tendencies based on data from the fourth survey of the giant panda in the Sichuan Province and from geographic information data. The paper aims to uncover the internal mechanisms of farmers' resource utilization behavior in terms of the changes wrought to giant panda habitats. The paper simulates the future habitat of the giant panda based on the LUCC (land use/cover change) model to identify anticipated changes in future landscape patterns and the habitat quality of giant pandas under the current scenarios. The paper analyzes the spatial-temporal change of landscape patterns through the land use transfer matrix, based on the Markov model. The results of the scenario analyses illustrate the spatial and temporal difference in habitat quality. The driving mechanism for landscape pattern change is explored using the logistic regression model. The paper simulates the variation tendency of giant panda habitats under differential labor force structures and resource utilization behavior based on the CA (cellular automata) model, with the robustness of the results verified by participatory experiment. Through four scenarios of simulated farm labor force structure and resource utilization behavior, results suggest that the quality of giant panda habitats in the future will be relatively high when workforce feminization and aging is intense and resource utilization behavior is weakened. The simulated results confirm that the current agricultural labor force structure can reduce the intensity of resource utilization behavior. In this scenario, disturbance to giant panda habitats would decrease and their quality would improve. [ABSTRACT FROM AUTHOR]

The shale of the Wufeng–Longmaxi formation in the Sichuan Basin is the preferred layer for shale gas exploration in China, and its petrophysical characteristics are the key to geological and engineering sweet spot prediction. However, the characteristics and impact mechanisms of its acoustic wave velocity and elastic anisotropy are currently unclear. In this paper, the Wufeng–Longmaxi shale is taken as the research object, and the P-wave and S-wave velocities of the samples are tested under the loading and unloading processes of confining pressure. The stress sensitivity variations in parameters such as wave velocity, wave velocity ratio, and anisotropy are discussed. P-wave and S-wave anisotropy parameters are correlated under different pressure conditions. X-ray diffraction, casting thin sections, scanning electron microscopy, micron CT scanning, and other analytical techniques are used to explore the mechanisms of stress sensitivity of elastic parameters. The research results indicate that: (1) the acoustic velocities of samples from different angles are V90° > V45° > V0°, and there is a positive correlation between the wave velocity and the confining pressure. After unloading the confining pressure, irreversible plastic deformation occurs due to the closure of some microfractures in the rock core, causing the wave velocity to be higher than the initial value. (2) The stress sensitivity coefficient of the P-wave (The mean is 3.00 m·s−1·MPa−1) is higher than that of the S-wave (the mean is 1.23 m·s−1·MPa−1), and the stress sensitivity coefficient of the compacted stage (the mean is 3.02 m·s−1·MPa−1) is higher than that of the elastic stage (the mean is 1.21 m·s−1·MPa−1). (3) The anisotropy of the P-wave and S-wave is negatively correlated with the confining pressure. When the confining pressure is loaded to 65 MPa, the change rate of the P-wave anisotropy coefficient is 23%, and its stress sensitivity is higher than that of S-wave anisotropy coefficient (the change rate is 13.7%). After unloading the confining pressure, the degree of anisotropy is reduced due to the closure of some microfractures. The empirical formula of P-wave and S-wave anisotropy parameters under different pressures is established through linear regression, which can provide a reference for mutual predictions. (4) The variation in wave velocity anisotropy with stress can be divided into stress and material anisotropy, which are related to the directional arrangement of microfractures and clay minerals, respectively. The quantitative characterization of shale anisotropy can be realized by evaluating the development degree of reservoir fractures and mineral components, providing a reference for logging interpretations, sweet spot prediction, and fracturing construction of shale gas reservoirs. [ABSTRACT FROM AUTHOR]

Research on government service quality can help ensure the success of digital government services and has been the focus of numerous studies that proposed different frameworks and approaches. Most of the existing studies are based on traditional researcher-led methods, which struggle to capture the needs of citizens. In this paper, a citizen-feedback-based analysis framework was proposed to explore citizen demands and analyze the service quality of digital government. Citizen feedback data are a direct expression of citizens' demands, so the citizen-feedback-based framework can help to obtain more targeted management insights and improve citizen satisfaction. Efficient machine learning methods used in the framework make data collection and processing more efficient, especially for large-scale internet data. With the crawled user feedback data from the Q&A e-government portal of Luzhou, Sichuan Province, China, we conducted experiments on the proposed framework to verify its feasibility. From citizens' online feedback on Q&A services, we extracted five service quality factors: efficiency, quality, attitude, compliance, and execution of response. The analysis of five service quality factors provides some management insights, which can provide a guide for improvements in Q&A services. [ABSTRACT FROM AUTHOR]

In this paper, a Comprehensive Diagram Method (CDM) for a Multi-Layer Perceptron Neuron Network (MLPNN) is proposed to realize natural gas energy metering using temperature, pressure, and the speed of sound from an ultrasonic flowmeter. Training and testing of the MLPNN model were performed on the basis of 1003 real data points describing the compression factors (Z-factors) and calorific values of the three main components of natural gas in Sichuan province, China. Moreover, 20 days of real tests were conducted to verify the measurements' accuracy and the adaptability of the new intelligent method. Based on the values of the Mean Relative Errors and the Root Mean Square errors for the learning and test errors calculated on the basis of the actual data, the best-quality MLP 3-5-1 network for the metering of Z-factors and the new CDM methods for the metering of calorific values were experimentally selected. The Bayesian regularized MLPNN (BR-MLPNN) 3-5-1 network showed that the Z-factors of natural gas have a maximum relative error of −0.44%, and the new CDM method revealed calorific values with a maximum relative error of 1.90%. In addition, three local tests revealed that the maximum relative error of the daily cumulative amount of natural gas energy was 2.39%. [ABSTRACT FROM AUTHOR]

Debris flows can damage infrastructure and threaten human life and property safety, especially in tourist attractions. Therefore, it is crucial to classify and evaluate the risk of debris flows. This article takes 14 debris flows in Longmenshan Town, Pengzhou, Sichuan, China, as the research object. Based on on-site geological surveys, combined with drone images and multiple remote sensing images, the essential characteristics of each debris flow are comprehensively determined. A total of nine factors are used as the primary indicators affecting the risk of debris flow: drainage density, roundness, the average gradient of the main channel, maximum elevation difference, bending coefficient of the main channel, the loose-material supply length ratio, vegetation area ratio, population density, and loose-material volume of unit area. The subjective weights of each indicator are obtained using the Analytic Hierarchy Process, while the objective weights are obtained using the CRITIC method. Based on this, the distance function is introduced to couple the subjective and objective weights, determine each indicator's combined weights, and obtain the integrated evaluation score values of different debris flow hazards. Considering the integrated evaluation score of debris flow, cluster analysis was used to classify 14 debris flows and cluster effectiveness indicators were introduced to determine the effectiveness of debris flow classification. A quantitative standard for the risk of debris flow within the study area was proposed, and finally, a risk assessment of debris flow in the study area was made. Comparing the results of this paper with the gray correlation method, the coupled synergistic method, and the geological field survey results, proves that the proposed method is feasible and provides a reasonable scientific basis for the study of the hazard assessment of regional debris flow clusters and other related issues within the scope of the Jianjiang River basin and other areas. [ABSTRACT FROM AUTHOR]

The Lala copper area in Huili County, Sichuan Province, China, is favored by superior regional metallogenic geological conditions due to its location in an extremely important copper–iron metallogenic belt in southwest China, and it has witnessed the formation of a series of unique iron–copper deposits following the superposition of multiple tectonic events. In recent years, major mineral exploration breakthroughs have been achieved in the deep and peripheral zones of this area. Using the Lala copper mining area in Sichuan as an example, this paper describes metallogenic prediction research carried out based on multivariate geoscience information (geological information, geophysics, geochemistry, and remote sensing data) and the application of geographic information system (GIS) technology and the radial basis function neural network (RBFLN) model. The five specific aspects covered in this paper are as follows: (1) we collected geology–geophysics–geochemistry remote sensing data and other information, adopted GIS technology to extract multivariate geoscience ore-forming anomaly information, and established a geoscience prospecting information database; (2) we applied the RBFLN algorithm for information on integrated analysis of ore-forming anomalies in the study area; (3) we applied a statistical method to divide the threshold value to delineate favorable ore-prospecting target areas; (4) we applied three-dimensional (3D) visualization technology, through which sample assistance was verified, to evaluate the performance of the RBFLN model; and (5) the results revealed that the RBFLN model can integrate multivariate and multi-type geoscience information and effectively predict metallogenic prospective areas and delineate favorable target areas. The metallogenic prediction method based on RBFLN technology provides a scientific basis for the exploration and deployment of minerals in the study area. It is obvious that the methods to predict and evaluate mineral resources are developing towards model integration and information intelligent analysis. [ABSTRACT FROM AUTHOR]

The Jiajika rare metal deposit contains the largest area of granitic pegmatite-type rare metal deposits in China. The X03 vein is an immense rare metal deposit dominated by lithium, which was found in the deposit in recent years. The contact metamorphic belt of tourmalinization and petrochemistry is widely developed in its wall rocks, and the altered rocks formed contain Li and other rare metal mineralization. In this paper, the tourmaline found in the different rocks of the Jiajika X03 vein is divided into four types: two-mica quartz schist (Tur-Ⅰ), tourmaline hornfels (Tur-Ⅱ), tourmaline-bearing granite pegmatite (Tur-Ⅲ) and spodumene-bearing granite pegmatite (Tur-Ⅳ); their in situ major element, trace element and boron isotope data are systematically studied. The results show that all tourmalines in the Jiajika X03 vein deposit belong to the alkali group, and are schorl–Oxy/Fluor–schorl, dravite–Hydroxy-dravite and foitite–Oxy foitite solid solutions, among which Tur-Ⅰ are dravite, Tur-Ⅱ are foitite of hydrothermal origin and Tur-Ⅲ and Tur-Ⅳ are schorl of magmatic origin. The boron isotope values show that the boron involved the formation process of tourmaline mainly originates from the Majingzi S-type granite, and the boron isotope variations in tourmaline are controlled by melt fluid and Rayleigh fractionation. Moreover, there is a clear correlation between the B isotope value of tourmaline and the Li, Mn, Zn, Mg, and V contents, showing that these contents in tourmaline are good indicators of the mineralization type of pegmatite. [ABSTRACT FROM AUTHOR]

High graphitization is responsible for low-resistivity shale development with poor reservoir quality. This paper provides an explanation of organic matter graphitization and determines the impact of high graphite content on low-resistivity shale reservoir quality at the Wufeng-Longmaxi Formation in the Southern Sichuan Basin. Fine veins are frequently developed at shale samples with Ro > 3.5%, graphitized organic matter > 25%, and resistivity < 5 Ω•m, which are dominated by three mineral assemblages: brunsvigite, barite-hyalophane-barium feldspar-potassium feldspar-anhydrite, and calcite-ankerite. These filling minerals are characterized by an Eu positive anomaly and high Ba, Fe, and Mn contents, suggesting that low-resistivity shale was modified by magmatic-related low-temperature hydrothermal fluid. Temperature measurements of brine inclusions and a semi-empirical geothermometer of chlorite show that low-temperature hydrothermal fluid experienced the chlorite stage (150–180 °C), the low-sulfidation stage (120–150 °C), and the low-temperature calcitization stage. Paleozoic fault systems and late Permian hydrothermal activities associated with the Emeishan mantle plume control the graphitization of low-resistivity shale. The water formation and seawater infiltrated into the deep crust along the Paleozoic basement faults under gravity, developing alkaline hot brine through mantle plume heating and then causing a water-rock reaction with basement rocks. They migrated upward along deep and large Paleozoic faults through convective thermal circulation in the Tiangongtang area, the Shuanglong-Luochang area, and the Xuyong area. Cation exchange and redox reactions occurred during the interaction between high-temperature hydrothermal fluid and cool wall rocks. The migration of alkaline hot brine via the Wufeng-Longmaxi shale introduced a subsequent water-rock reaction, resulting in the development of hydrothermal mineral assemblages that intricately filled fractures. It increased formation temperature and enhanced thermal maturity and graphitization of organic matter at the Wufeng-Longmaxi low-resistivity shale, resulting in a wide distribution of low-resistivity shale at the Changning Block. [ABSTRACT FROM AUTHOR]

The Silurian Longmaxi (S1l) marine shale and Jurassic Dongyuemiao (J1d) lacustrine shale in the Sichuan Basin, West China have attracted considerable attention from the oil-and-gas industry in China. Currently, the differences in pore types and pore structures between them are poorly understood, which has limited shale-resource exploration in the Sichuan Basin. This paper systemically compares the pore characteristics of Longmaxi shale and Dongyuemiao shale and investigates their impact on shale-gas enrichment by integrating field-emission scanning electron microscopy (FE–SEM), X-ray diffraction (XRD), low-pressure gas (CO2 and N2) adsorption and mercury-intrusion porosimetry, high-pressure sorption isotherms, gas-saturation measurement, molecular-dynamics simulation, etc. The results show that the S1l organic-rich marine shale and the J1d lacustrine shale have different pore types and pore structures. The S1l shale is dominated by organic pores, mainly micropores and mesopores with ink-bottle-like pore shapes, while the J1d shale is primarily composed of clay-mineral pores, mainly mesopores and macropores with slit- or plate-like pore shapes. Organic pores can provide considerable storage space for shale-gas enrichment in S1l marine shale, which also determines the adsorption capacity of shale reservoirs. Although organic pores are not the most prevalent in the Dongyuemiao lacustrine shale, they also play an important role in enhancing reservoir quality and absorbed-gas enrichment. Clay-mineral pores contribute weakly to the storage space of J1d-lacustrine-shale reservoirs. Mesopores are the most important form of storage space in both S1l shale and J1d shale, contributing significantly to shale-gas enrichment. Micropores are secondary in importance in S1l marine shale, while macropores are secondary contributors to pore volume in J1d lacustrine shale. [ABSTRACT FROM AUTHOR]

Total organic carbon (TOC) content is a key indicator for determining the hydrocarbon content of shale. The current model for calculating the TOC content of shale is relatively simplistic, the modeling process is cumbersome, and the parameters involved are influenced by subjective factors, which have certain shortcomings. To address this problem, a time-domain convolutional neural network (TCN) model for predicting total organic carbon content based on logging sequence information was established by starting from logging sequence information, conducting logging parameter sensitivity analysis experiments, prioritizing logging-sensitive parameters as model feature vectors, and constructing a TCN network. Meanwhile, to overcome the problem of an insufficient sample size, a five-fold cross-validation method was used to train the TCN model and obtain the weight matrix with the minimum error, and then a shale reservoir TOC content prediction model based on the TCN model was established. The model was applied to evaluate the TOC logging of the Lianggaoshan Formation in the Sichuan Basin, China, and the predicted results were compared with the traditional ΔlogR model. The results indicate that the TCN model predicts the TOC content more accurately than the traditional model, as demonstrated by laboratory tests. This leads to a better application effect. Additionally, the model fully explores the relationship between the logging curve and the total organic carbon content, resulting in improved accuracy of the shale TOC logging evaluation. [ABSTRACT FROM AUTHOR]

Due to global warming and other climate changes, it is increasingly important to study the response of regional environmental changes and dynamic changes in vegetation to climate change. Based on meteorological data from the last 60 years, this paper calculates the humidity index of western China under a wide range of long time series in different regions and explores the cross-correlation effect between series by offering a comparison with NDVI data, to analyze the cross-correlation between wet and dry changes and changes in vegetation in western China on a spatial scale. The results show that the spatial distribution of the interdecadal humidity index is different between different regions in western China. For example, the semi-arid and the semi-humid zones of the Weihe River region exhibit significant changes, while the Xinjiang and Qinghai–Tibet regions show a trend of constant wetness, on the whole, and the Sichuan and Yunnan–Guizhou regions are relatively humid and the distribution of wetness and dryness is relatively stable. The distribution of high and low values of the humidity index is very obvious and consistent with that of the distribution of desert bare land and precipitation in western China. In common with the distribution in the humidity index, the maximum correlation number between the NDVI and the humidity index in the whole western region is also significantly different in spatial distribution. There is a positive correlation between the NDVI and the humidity index in 99% of the study area. However, the delay in response time of the NDVI to changes in the humidity index in each region is inconsistent. For example, changes in the NDVI lag changes in the humidity index in the Menggan region by generally either 2 months or 5 months, while in the Sichuan region the delay in response time is generally 3 months. The variation and trend in dry and wet areas are closely related to the geographical location, climate zone, and topographic terrain, which may be the reason for the differences in the distribution of vegetation types and the response time to dry and wet changes. There is significant interaction between the humidity index and the vegetation type or precipitation distribution in western China. The positive correlation between the NDVI and the humidity index means that the positive effect is more sensitive, and the response of grassland is the most sensitive in the ecosystem. [ABSTRACT FROM AUTHOR]

To explore the causes of pollution formation and changes in the complex topography of the Sichuan Basin, China, and improve the comprehensive simulation capability of pollution models, we use two online coupling models, WRF/Chem and WRF/CUACE, to simulate two heavy pollution episode that successively occurred in the southern part of Sichuan Province from 15 December 2016 to 11 January 2017 in this paper. Additionally, two sets of meteorological physics parameterization schemes MET1 and MET2 are designed, and four groups of experiments are carried out. The results suggest that the two models are good at simulating the static weather parameters such as temperature, low speed of winds and boundary layer height. The four groups of tests can accurately simulate the beginning, maintenance and turning point of the two pollution episodes' life cycles. CUACE shows better performance in terms of higher correlation coefficients and lower errors in most of the particles and particulate components evaluations. It also performs better in the competitive mechanism of sulfate and nitrate against ammonium in the thermodynamic equilibrium mechanism. In addition, the evaluation of PM2.5 and the component simulation show that CUACE is more capable of simulating the mechanisms of heavy pollutions in southern Sichuan. Meanwhile, MET2 scheme is more appropriate for the simulation than MET1 dose. Based on the simulated concentrations of components and their precursors, the models overestimate the conversion of NO2 to nitrate but underestimate the conversion of SO2 to sulfate, which is the essential cause of the general overestimation of nitrate. Therefore, reducing the overestimation of nitrate is one major target for future model improvement. [ABSTRACT FROM AUTHOR]

In 2022, as a result of the historically exceptional high temperatures that have been observed this summer in several parts of China, particularly in the province of Sichuan, residential demand for energy has increased. Up to 70% of Sichuan's electricity comes from hydropower, thus creating a sensible and practical reservoir scheduling plan is essential to maximizing reservoir power generating efficiency. However, classical optimization, such as back propagation (BP) neural network, does not take into account the correlation of samples in time while generating reservoir scheduling rules. We proposed a prediction model based on LSTM neural network coupled with wavelet transformation (WT-LSTM) to address the problem. In order to extract the reservoir scheduling rules, this paper first gathers the scheduling operation data from the Xiluodu hydropower station and creates a dataset. Next, it uses the feature of the time-series prediction model with the realization of a complex nonlinear mapping function, time-series learning capability, and high prediction accuracy. The results demonstrate that the time-series deep learning network has high learning capability for reservoir scheduling by comparing evaluation indexes such as root mean square error (RMSE), rank-sum ratio (RSR), and Nash–Sutcliffe efficiency (NSE). The WT-LSTM network model put forward in this research offers better prediction accuracy than conventional recurrent neural networks and serves as a reference base for scheduling decisions by learning previous scheduling data to produce outflow solutions, which has some theoretical and practical benefits. [ABSTRACT FROM AUTHOR]

The unidirectional consolidation theory of soils is widely used in certain conditions and approximate calculations. The multidirectional theory of soil consolidation is more reasonable than the unidirectional theory in practical applications but is much more complicated in terms of index determination and solution. To address the above problem, in this paper, we propose a deep learning method using physics-informed neural networks (PINN) to predict the excess pore water pressure of two-dimensional soil consolidation. In the proposed method, (1) a fully connected neural network is constructed; (2) the computational domain, partial differential equation (PDE), and constraints are defined to generate data for model training; and (3) the PDE of two-dimensional soil consolidation and the model of the neural network are connected to reduce the loss of the model. The effectiveness of the proposed method is verified by comparison with the numerical solution of PDE for two-dimensional consolidation. Moreover, the FEM and the proposed PINN-based method are applied to predict the consolidation of foundation soils in a real case of Sichuan Railway in China, and the results are quite consistent. The proposed deep learning approach can be used to investigate large and complex multidirectional soil consolidation. [ABSTRACT FROM AUTHOR]

This paper collects and analyzes the 1954–2017 monthly average reanalysis data from the U.S. National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR), the 1954–2017 haze days observation data from the National Meteorological Information Center/China Meteorological Administration (NMIC/CMA) and the PM2.5 daily average mass concentration data in 2013–2017 from the China Air Quality Online Monitoring Platform. The atmospheric apparent heat source Q1 (negative Q1 means cold source in winter) over the Tibetan Plateau in December of 1954–2017 is estimated based on thermodynamic equations, and the East Asian winter monsoon index (EAWMI) is calculated. In addition, the discrepancies of the air quality among China's five typical regions (Beijing–Tianjin–Hebei, Fen-Wei Plain, Yangtze River Delta, Pearl River Delta and Sichuan-Chongqing regions) under the joint influence of the Q1 and EAWMI are studied. Results show that when it is a strong cold source year, abnormal downdrafts and "temperature inversion covers" occur in areas far from the high terrain, resulting in increased pollution, while the opposite is true in weak cold source years. In strong EAWMI years, there is an abnormal northerly sinking cold flow in the lower layers of mid-high latitudes, which increases the pollution in the area south of 30° N, and the opposite is true in weak EAWMI years. Affected by the combined activities of the Q1 and the EAWMI, the meteorological conditions of the five typical regions are different, and thus present different air pollution characteristics. [ABSTRACT FROM AUTHOR]

The mountainous area of southwest China is characterized by significant topography and complex geological conditions, which pose great challenges to the airport's site selection, construction, and safe operation. Suining Anju Airport, one of the key projects under construction in southwest China, is essential in alleviating and dredging the air passenger flow in Sichuan Province. Because the overlying quaternary strata's physical and mechanical properties, thickness, and distribution range are fairly different in the longitudinal and transverse directions, the Anju Airport's foundation in the hilly area has typical inhomogeneity. Large-scale excavation and filling pose a challenge to the ground stability of the airport. To comprehensively monitor Anju Airport's uneven ground subsidence during the construction period, this paper selected SAR image data collected by the Sentinel-1A satellite from May 2018 to June 2021 to extract time-series ground subsidence measurements based on the SBAS-InSAR method. Furthermore, based on the simulation of roadbed filling in the airport's parallel slide fill area, the dynamic evolution analysis of soil stress field and internal subsidence caused by roadbed filling activities was carried out to further reveal the occurrence mechanism of ground subsidence. The monitoring results show that the subsidence centers of Anju Airport are mainly distributed in the filling areas, and the average annual subsidence is −20~−75 mm/yr from May 2018 to June 2021. Comparative analysis with in situ data indicates that the RMSE of InSAR monitoring results was ±6.12 mm. The numerical simulation shows that the subsidence of the airport parallel slide is mainly caused by a load of subgrade filling body and the compression of its weight. The results of this study can provide reference methodology and data support for the construction and future safe operation of Suining Anju Airport. [ABSTRACT FROM AUTHOR]

This paper proposes a semiparametric solution to estimate the intensity (hazard) function of modulated renewal processes: a nonparametric estimate for the baseline intensity function together with a parametric estimate of the model parameters of the covariate processes. Based on the martingale property associated with the conditional intensity, we construct a statistic from a residual analysis to estimate the baseline renewal intensity function, when the model parameters of the covariate processes are known. In addition, when the baseline intensity is obtained, the model parameters can be estimated using the usual maximum likelihood estimation. In practice, both the baseline intensity and model parameters are suggested to be estimated simultaneously via an expectation–maximization (E–M)-type iterative algorithm. A more important feature of the newly proposed algorithm is that, given n events in the observation dataset, its computation time is of order O (n 2) , while the Nelson–Aalen–Breslow estimator takes a computation time of order O (n 3) . For illustration, we apply the proposed estimation procedure to a set of data simulated from a modulated gamma renewal process and the aftershock sequence following the M s 8 Wenchuan earthquake, which occurred in Sichuan Province, China on 12 May 2008. [ABSTRACT FROM AUTHOR]

The southwest mountainous area of China is one of the areas with the most landslides in the world. In this paper, we used Ya'an City and Garzê Tibetan Autonomous Prefecture in Sichuan Province as the research areas to explore the identification application effects of large-area potential landslides using synthetic aperture radar (SAR) data with different wavelength types (Sentinel-1, ALOS-2), different processing methods (SBAS-InSAR, Stacking-InSAR), and different geological environmental conditions. The results show the following: (1) The effect of identifying landslides with different slope directions is largely affected by the satellite orbit direction; when we identify landslide hazards across a large area, the joint monitoring mode of ascending and descending orbit data is required. (2) The period of monitoring affects the identification effect of potential landslides when landslide identification is carried out in southwestern China; the InSAR monitoring period is recommended to be more than 2 years. (3) In different geological environmental regions, SBAS technology and Stacking technology have their own advantages; Stacking technology identifies more potential landslides, and SBAS technology identifies potential landslides with higher accuracy; (4) the degree of vegetation coverage has a great impact on the landslide identification effect of different SAR data sources. In low-density vegetation coverage areas, the landslide identification result using Sentinel-1 data seems to be better than the result using ALOS-2 data. In high-density vegetation coverage areas, the landslide identification result using ALOS-2 data is better than that using Sentinel-1 data. [ABSTRACT FROM AUTHOR]

The problem of large deformation is very prominent in deep-buried tunnel excavation in soft rock, which brings serious potential safety hazards and economic losses to projects. The knowledge of deformation law and support measures is the key to ensure the rational design and safe construction in a large deformation tunnel of soft rock. This paper describes rock physical and mechanical tests and field monitoring is employed to investigate the cause and development process of large deformation in Dongsong hydropower station in Sichuan Province, China. The results show that the free expansion rate of the rock sample is 20.0%, the average expansion stress of the rock sample is 11.0 kPa, and the expansibility of the rock is low. Large deformation of surrounding rock mainly comes from the dilatancy effect with high geostress and relaxation deformation with weak support. Shotcrete sealing exposed surrounding rock, and early strength support avoiding water immersion are useful to deal with the three main factors (weathering, water and confining pressure) that affect the strength of surrounding rocks. The second lining applied in time can effectively limit the further development of stress and deformation of initial support, and prevent the cracking and large deformation of concrete. Clearance convergence is suggested to be the main monitoring work in construction, because of its advantages of intuitive results, easy quality assurance of instrument installation and high accuracy. [ABSTRACT FROM AUTHOR]

The problem of large deformation is very prominent in deep-buried tunnel excavation in soft rock, which brings serious potential safety hazards and economic losses to projects. Knowledge of the stress field distribution and deformation law is the key to ensuring rational design and safe construction in large deformation tunnels of soft rock. As described in this paper, theoretical analysis, numerical simulation and field monitoring were employed to investigate the surrounding rock stress and displacement state in the Dongsong hydropower station in Sichuan Province, China. The results show that the short-bench construction method can effectively control the deformation of surrounding rock and range of the plastic zone. In order to reserve enough working space, the optimum bench length in the actual construction was 10 to 14 m. The peripheral displacement and plastic radius decreased with the increase of tunnel support strength and the advance of supporting time. The displacement can be effectively controlled by applying the second lining in time at a position about twice the diameter of the hole (16 m) from the working face. A reasonable reserved deformation should be adopted to avoid secondary expanding excavation. The values of different positions in the tunnel laterally and longitudinally may be different, and adjustments are needed according to the actual situation. [ABSTRACT FROM AUTHOR]

Seismic landslides are the most common and highly destructive earthquake-triggered geological hazards. They are large in scale and occur simultaneously in many places. Therefore, obtaining landslide information quickly after an earthquake is the key to disaster mitigation and relief. The survey results show that most of the landslide-information extraction methods involve too much manual participation, resulting in a low degree of automation and the inability to provide effective information for earthquake rescue in time. In order to solve the abovementioned problems and improve the efficiency of landslide identification, this paper proposes an automatic landslide identification method named improved U-Net model. The intelligent extraction of post-earthquake landslide information is realized through the automatic extraction of hierarchical features. The main innovations of this paper include the following: (1) On the basis of the three RGB bands, three new bands, DSM, slope, and aspect, with spatial information are added, and the number of feature parameters of the training samples is increased. (2) The U-Net model structure is rebuilt by adding residual learning units during the up-sampling and down-sampling processes, to solve the problem that the traditional U-Net model cannot fully extract the characteristics of the six-channel landslide for its shallow structure. At the end of the paper, the new method is used in Jiuzhaigou County, Sichuan Province, China. The results show that the accuracy of the new method is 91.3%, which is 13.8% higher than the traditional U-Net model. It is proved that the new method is effective and feasible for the automatic extraction of post-earthquake landslides. [ABSTRACT FROM AUTHOR]

This paper documents depositional structures and their reservoir characteristics in the Wufeng–Longmaxi shale from outcrops and cores using thin sections, X-ray powder diffraction (XRD) analysis, carbon–sulfur analyzer, helium porosimeter, decay permeameter, and focused ion beam scanning electron microscope (FIB-SEM). In the study area, clayey and silty laminae abound in the shale. Clayey laminae are rich in bedding parallel fractures, microfractures, and organic pore networks. Silty laminae are rich in isolated inorganic pores and limited amounts of bedding non-parallel fractures. Various inter-lamination of clayey and silty laminae form five depositional structure types which are closely related to the ancient hydrodynamics, paleoredox condition, and sedimentation rate and have significant impacts on shale fractures, microfractures, pore types, pore-size distribution, and porosity. For the paper lamination (PL) and grading lamination composed of siltstone and claystone (GL-SC), organic pores account for 71.6% and 61.4% of the total, and dense bedding parallel and non-parallel fractures intersect to form connective networks. In the interlaminated lamination composed of siltstone and claystone (IL), grading lamination composed of claystone (GL-C) and structureless beds (SB), organic pores merely account for 20% to 51.8% of the total and minor isolated bedding parallel fractures occur. Among five depositional structure types, the PL and GL-SC have the highest porosity, permeability, TOC content, siliceous content, organic pore proportions, and ratios of horizontal to vertical permeability, which help them become shale gas exploration and development targets. [ABSTRACT FROM AUTHOR]

Agriculture is a critical foundation for the development of large-scale complex and urban societies. Sanxingdui, located on the Chengdu Plain in western Sichuan and linked with the ancient Chinese Shu Kingdom, is one of the most distinctive archaeological sites in the world. However, despite its importance, the agricultural economy of the Sanxingdui culture and the Chengdu Plain remains poorly understood and heavily debated. This study synthesizes recent archaeological and historical evidence concerning the agricultural economy underpinning the increasing scale and social complexity at Sanxingdui and the greater Chengdu Plain prior to 2200 BP. Our analysis finds a mixed rice and dry-land millet farming economy, in conjunction with pig and chicken husbandry, during the Sanxingdui culture (3700–3100 BP). This integrated agricultural system likely began with the Baodun culture (4500–3700 BP), passing to the Sanxingdui culture (3700–3100 BP), Shierqiao culture (3100–2600 BP) and later, the Shu culture (2600–2300 BP). In addition, although gathering, hunting, and fishing accounted for relatively low proportions of the overall subsistence, the ancient peoples at Sanxingdui and across the Chengdu Plain continued these practices, supporting a diverse agricultural and food system. Understanding the subsistence at Sanxingdui offers key insights into the development of complex societies in southwest China, the contributions to Chinese culture, and the role of agriculture worldwide. [ABSTRACT FROM AUTHOR]

Human activities and global environmental changes have transformed terrestrial ecosystems, notably increasing vegetation greenness in China. However, this greening is less effective across the Hu Huanyong Line (Hu Line). This study analyzes dynamic changes and driving factors of nine vegetation net primary productivities (NPPs) in regions divided by the Hu Line using remote sensing data, trend analysis, and the Geodetector model. Findings reveal that from 2001 to 2022, 38.22% of regional vegetation NPP in China increased, especially in the Loess Plateau, Sichuan Basin, and Northeast Plains, while 2.39% decreased, primarily in the southeastern region and southern Tibet. Grasslands contributed 39.71% to NPP north of the Hu Line, and cultivated vegetation contributed 50.58% south. The driving explanatory power of factors on vegetation NPP on the north side of the Hu Line is generally greater than that on the south side. Natural factors primarily drive NPP changes, with human activities having less impact. Combined factors, particularly climate and elevation, significantly enhance the driving explanatory power (q, 0–1). The joint effects of elevation and precipitation on grassland NPP dynamics (q = 0.602) are notable. GDP's influence on broadleaf forests north of the Hu Line (q = 0.404) is significant. Grasslands respond strongly to land use changes and population density, with a combined effect of q = 0.535. Shrubs, alpine vegetation, and meadows show minimal response to individual factors (q < 0.2). These findings offer insights for devising ecological protection measures tailored to local conditions. [ABSTRACT FROM AUTHOR]

The rapid development of digital finance has effectively reduced financial challenges in rural regions and created new prospects for agricultural production. This article examines the impact of digital financial development on rice production in Sichuan Province using the 2011–2021 Peking University Digital Financial Inclusion Index and data from 20 prefecture-level cities, as well as a fixed effects model. The mechanism of action is also discussed. The findings reveal that the advancement of digital finance plays an important role in boosting the expansion of rice production, and that digital finance influences rice output by increasing farmers' willingness to participate in insurance and increasing the availability of credit. A heterogeneity analysis reveals that digital finance has a substantial effect on mountainous and economically poor areas. As a result, this article suggests that the breadth and depth of usage of rural digital finance, as well as the development of rural digital financial services in underdeveloped areas, should be expanded. [ABSTRACT FROM AUTHOR]

The occurrence, distribution, and ecological risk assessment of 36 antibiotics from five groups, including macrolides (MLs), fluoroquinolones (FQs), tetracyclines (TCs), amphenicols (APs), and sulfonamides (SAs), were investigated for the first time in the Anning River, Sichuan Province, China. The results show that antibiotics were widely present in the sediments of the Anning River, with a total of 22 antibiotics detected. FQs were among the most abundant antibiotics, followed by TCs, MLs, APs, and SAs. The total concentrations of antibiotics in surface sediments varied from 0.05 to 53.35 ng/g, with an average of 8.09 ng/g. Among these groups, MLs, FQs, and TCs emerged as the predominant classes of antibiotics. The midstream sediments showed the highest residual levels of antibiotics, with lower levels observed in the downstream and upstream sediments. Anthropogenic activities, such as human clinical practices and animal breeding, might be sources of antibiotics released into the river. An ecological risk assessment revealed that trimethoprim from the SA group exhibited high risks, and MLs showed medium risks in the Anning River, whereas most antibiotics presented minimal to low risks. This study provides valuable information on antibiotic pollution in the upstream region of the Yangtze River, and future management measures are needed for the Anning River. [ABSTRACT FROM AUTHOR]

Marine–continental transitional shale has become a new field for shale gas exploration and development in recent years. Its reservoir characteristics analysis lags significantly behind that of marine shale, which restricts the theoretical research on the accumulation of marine–continental transitional shale and the progress of exploration and development. The shale pore system is complex and has strong heterogeneity, which restricts the fine evaluation and optimization of the reservoir. Based on nitrogen adsorption–desorption experiments, the morphology and structural characteristics of coal-bearing shale pores were analyzed, and then the micro-pore structure heterogeneity was quantitatively characterized based on fractal theory and nitrogen adsorption–desorption data, and the relationship between pore structure parameters and their influence on fractal characteristics were discussed. The hysteresis loop of nitrogen desorption isotherm mainly belongs to type B, indicating ink bottle, flat plate, and slit are the main pore shapes. The pore size distribution curves are left unimodal or multimodal, with the main peak around 4 nm and 20–60 nm. Smaller pores develop a larger specific surface area, resulting in a high value of fractal dimension (2.564 to 2.677). The rougher the pore surface and the larger the specific surface area provide an adequate adsorption site for shale gas adsorption and aggregation. Thus, fractal characteristics conduced to understand the pore structure, heterogeneity, and gas-bearing property of coal-bearing shale. [ABSTRACT FROM AUTHOR]

Estimating and monitoring chlorophyll content is a critical step in crop spectral image analysis. The quick, non-destructive assessment of chlorophyll content in rice leaves can optimize nitrogen fertilization, benefit the environment and economy, and improve rice production management and quality. In this research, spectral analysis of rice leaves is performed using hyperspectral and fluorescence spectroscopy for the detection of chlorophyll content in rice leaves. This study generated ninety experimental spectral datasets by collecting rice leaf samples from a farm in Sichuan Province, China. By implementing a feature extraction algorithm, this study compresses redundant spectral bands and subsequently constructs machine learning models to reveal latent correlations among the extracted features. The prediction capabilities of six feature extraction methods and four machine learning algorithms in two types of spectral data are examined, and an accurate method of predicting chlorophyll concentration in rice leaves was devised. The IVSO-IVISSA (Iteratively Variable Subset Optimization–Interval Variable Iterative Space Shrinkage Approach) quadratic feature combination approach, based on fluorescence spectrum data, has the best prediction performance among the CNN+LSTM (Convolutional Neural Network Long Short-Term Memory) algorithms, with corresponding RMSE-Train (Root Mean Squared Error), RMSE-Test, and RPD (Ratio of standard deviation of the validation set to standard error of prediction) indexes of 0.26, 0.29, and 2.64, respectively. We demonstrated in this study that hyperspectral and fluorescence spectroscopy, when analyzed with feature extraction and machine learning methods, provide a new avenue for rapid and non-destructive crop health monitoring, which is critical to the advancement of smart and precision agriculture. [ABSTRACT FROM AUTHOR]

The aerosol–cloud–precipitation correlation has been a significant scientific topic, primarily due to its remarkable uncertainty. However, the possible modulation of aerosol on the precipitation capacity of clouds has received limited attention. In this study, we utilized multi-source data on aerosol, cloud properties, precipitation, and meteorological factors to investigate the impact of aerosols on precipitation efficiency (PE) in the Sichuan Basin (SCB) and Yun-nan-Guizhou Plateau (YGP), where the differences between terrain and meteorological environment conditions were prominent. In the two study regions, there were significant negative correlations between the aerosol index (AI) and PE in spring, especially in the YGP, while the correlations between the AI and PE in other seasons were not as prominent as in spring. In spring, aerosol significantly inhibited both the liquid water path (LWP) and the ice water path (IWP) in the YGP, but negatively correlated with the IWP and had no significant relationship with the LWP in the SCB. Aerosol inhibited precipitation in the two regions mainly by reducing cloud droplet effective radius, indicating that warm clouds contributed more to precipitation in spring. The suppressive impact of aerosols on precipitation serving as the numerator of PE is greater than that of the cloud water path as the denominator of PE, resulting in a negative correlation between aerosol and PE. The AI–PE relationship is significantly dependent on meteorological conditions in the YGP, but not in the SCB, which may be related to the perennial cloud cover and stable atmosphere in the SCB. In the future, as air quality continues to improve, precipitation efficiency may increase due to the decrease in aerosol concentration, and of course, the spatio-temporal heterogeneity of the aerosol–cloud–precipitation relationship may become more significant. [ABSTRACT FROM AUTHOR]

The reservoir in the Anyue gas field, located in the Sichuan basin of China, belongs to the second member of the Dengying formation and has distinctive geological features. It is characterized by strong heterogeneity, low porosity, low permeability, and locally developed natural fractures. The reservoir space consists primarily of corrosion holes, natural fractures, and similar voids. Moreover, the lower reservoir exhibits high water saturation and a homogeneous bottom-water interface. Since it is a carbonate-based hydrocarbon reservoir with low porosity and permeability, deep acid fracturing has proven to be an efficient method for enhancing individual well production. However, the reconstruction of the second member of the Dengying formation reservoir poses significant challenges. The reservoir contains high-angle natural fractures, small vertical stress differences, and is located in close proximity to the gas–water interface. As a result, it becomes difficult to control the height of the acid break. Improper acid break treatment may easily result in water production affecting gas well production. To explore ways to control the longitudinal extension of acid fractures, 3D numerical models focusing on the initiation and expansion of acid fractures have been developed. This model takes into account geological and engineering factors such as stress differences, acid fracture displacements and scales, and their effects on the longitudinal extension of acid fractures. It was revealed that the pressure difference is the main controlling factor for the acid fracture height, followed by the reservoir thickness, the interlayer thickness, and the viscosity of the working fluid. Technical countermeasures for controlled fracture and high-acid fracturing tailored to different reservoir characteristics have been proposed, and design parameters for controlled fracture and high-acid fracturing can be optimized. By effectively controlling the vertical extension of the acid fracture, it is possible to maximize production from a single well while avoiding interference from the lower water layer. This study provides theoretical guidance for the application of deep-acid-fracturing techniques in low-permeability bottom-water gas reservoirs. [ABSTRACT FROM AUTHOR]

Tomographic Synthetic Aperture Radar (TomoSAR) is a breakthrough of the traditional SAR, which has the three-dimentional (3D) observation ability of layover scenes such as buildings and high mountains. As an advanced system, the airborne array TomoSAR can effectively avoid temporal de-correlation caused by long revisit time, which has great application in high-precision mountain surveying and mapping. The 3D reconstruction using TomoSAR has mainly focused on low targets, while there are few literatures on 3D mountain reconstruction. Due to the layover phenomenon, surveying in high mountain areas remains a difficult task. Consequently, it is meaningful to carry out the research on 3D mountain reconstruction using the airborne array TomoSAR. However, the original TomoSAR mountain point cloud faces the problem of elevation ambiguity. Furthermore, for mountains with complex terrain, the points located in different elevation periods may intersect. This phenomenon increases the difficulty of solving the problem. In this paper, a novel elevation ambiguity resolution method is proposed. First, Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Gaussian Mixture Model (GMM) are combined for point cloud segmentation. The former ensures coarse segmentation based on density, and the latter allows fine segmentation of the abnormal categories caused by intersection. Subsequently, the segmentation results are reorganized in the elevation direction to reconstruct all possible point clouds. Finally, the real point cloud can be extracted automatically under the constraints of the boundary and elevation continuity. The performance of the proposed method is demonstrated by simulations and experiments. Based on the airborne array TomoSAR experiment in Leshan City, Sichuan Province, China in 2019, the 3D model of the surveyed mountain is presented. Moreover, three kinds of external data are applied to fully verify the validity of this method. [ABSTRACT FROM AUTHOR]

Casing deformation is evident during the development of shale oil and gas wells in the Sichuan and Junggar Basins in China. Their casing deformation characteristics, distribution law of deformation points, and main controlling factors were analyzed. According to the analysis results, shear is the main cause of casing deformation of shale oil and gas wells in the Sichuan and Junggar Basins in China and has the characteristics of "a dense heel end and a sparse toe end". Faults account for 75% of casing deformation points, and fault slip caused by multi-stage fracturing is the primary factor responsible. The calculation model for fault slip that takes into account fracturing fluid invasion was established, and the dynamic variation law of fault slip was clarified: the fracturing fluid intruded into the fault, the relative dislocation of the damaged fault was caused by gravity, and the fault slippage was caused by the increase in fault activation length. This resulted in a linear increase in fault slippage, and the slippage reached its maximum when the fracturing fluid completely penetrated the fault and reached the fault boundary. The slip amount has a positive correlation with the fault length and the in situ stress difference; it increases first and then decreases with the increase in the fault dip angle. The slip amount reaches its maximum when the fault dip angle reaches 45°. [ABSTRACT FROM AUTHOR]

The saturated permeability coefficient (ks) is a key parameter for evaluating the seepage and stability of reservoir colluvial landslides. However, ks values obtained from traditional experimental methods are often characterized by large variations and low representativeness. As a result, there are significant deviations from actual observations when used in seepage field calculations for reservoir landslide analysis. This study proposes an intelligent inversion method that combines a physical model and a data-driven model for reservoir landslide ks based on actual groundwater level (GWL) monitoring data. This method combines Latin Hypercube Sampling (LHS), unsaturated flow finite element (FE) analysis, particle swarm optimization algorithm (PSO), and kernel extreme learning machine model (KELM). Taking the Hongyanzi landslide in Sichuan Province, China, as the research object, the GWL of the landslide under different ks was first obtained by LHS and transient seepage FE analysis. Then, a nonlinear functional relationship between ks and the landslide GWL was fitted based on the PSO-KELM model. Finally, the optimal landslide ks was obtained by minimizing the root-mean-squared error between the predicted and actual GWL using the PSO. A global sensitivity analysis was also conducted on the ks of different rock and soil layers to reveal their control rules on the calculation of landslide GWL. The research results demonstrate the feasibility of the proposed method and provide valuable information for similar landslides in practice. [ABSTRACT FROM AUTHOR]