Renewable energy resources,including geothermal,are crucial for sustainable environmental management and climate change mitigation,offering clean,reliable,and low-emission alternatives to fossil fuels that reduce gree...Renewable energy resources,including geothermal,are crucial for sustainable environmental management and climate change mitigation,offering clean,reliable,and low-emission alternatives to fossil fuels that reduce greenhouse gases and support ecological balance.In this study,geographic information system(GIS)predictive analysis was employed to explore geothermal prospects,promoting environmental sustainability by reducing the dependence on fossil energy resources.Spatial and statistical analysis including the attribute correlation analysis was used to evaluate the relationship between exploration data and geothermal energy resources represented by hot springs.The weighted sum model was then used to develop geothermal predictive maps while the accuracy of prediction was determined using the receiver operating characteristic/area under curve(ROC/AUC)analysis.Based on the attribute correlation analysis,exploration data relating to geological structures,host rock(Asu River Group)and sedimentary contacts were the most critical parameters for mapping geothermal resources.These parameters were characterized by a statistical association of 0.52,0.48,and 0.46 with the known geothermal occurrences.Spatial data integration reveals the central part of the study location as the most prospective zone for geothermal occurrences.This zone occupies 14.76%of the study location.Accuracy assessment using the ROC/AUC analysis suggests an efficiency of 81.5%for the weight sum model.GIS-based multi-criteria analysis improves the identification and evaluation of geothermal resources,leading to better decision-making.展开更多
The Sawayaerdun gold deposit is the only extremely large deposit occurring in the giant gold metallogenic belt of the Central Asian Tianshan Orogenic Belt.Breakthroughs in deep and peripheral exploration are of great ...The Sawayaerdun gold deposit is the only extremely large deposit occurring in the giant gold metallogenic belt of the Central Asian Tianshan Orogenic Belt.Breakthroughs in deep and peripheral exploration are of great significance for the sustainable development of the region.In this study,a comprehensive prospecting and exploration model for gold exploration in the high-cold and high-altitude areas of the southwestern Tianshan Mountains was developed by systematically evaluating the metallogenic geological conditions of the deposit and integrating geological,geochemical,and geophysical exploration multi-source data.Both the shallow metamorphic carbonaceous fine clastic rock and ductile shear zones controlled the Au-mineralized zone.Moreover,mineralized alteration,Au-Sb-As element chemical anomalies,high magnetic anomalies,and medium-high values from low-wave impedance were also important components of the model.Three-dimensional(3-D)geological attribute models of various ore-controlling factors were established,revealing the spatial distribution patterns of the deep structural frameworks and hidden mineralization.Geostatistical methods were used to delineate the three edges and two deep-mineral exploration areas.A comprehensive evaluation showed that anomalous variables were well confirmed in geological understanding,highlighting the effectiveness and accuracy of the predictions.These results are significant for deep-edge exploration.展开更多
This paper focuses on the application of AIGC(Artificial Intelligence Generated Content)technology in higher vocational education teaching modes.It deeply explores the significant meaning of AIGC in empowering higher ...This paper focuses on the application of AIGC(Artificial Intelligence Generated Content)technology in higher vocational education teaching modes.It deeply explores the significant meaning of AIGC in empowering higher vocational education,and analyzes the existing problems when AIGC technology is applied to such teaching modes,covering aspects like technology application,teaching staff,students’adaptability,and educational management.Meanwhile,it puts forward targeted and effective paths for AIGC technology to empower higher vocational education teaching modes,including optimizing technology application,strengthening teacher training,improving students’literacy,and perfecting educational management.The paper aims to promote the in-depth integration of AIGC technology and higher vocational education,realize the innovation and high-quality development of higher vocational education teaching modes,and provide theoretical references and practical guidance for cultivating high-quality technical and skilled talents who meet the needs of the new era.展开更多
Courses with ideological-political elements are a new direction of the reform of higher education teaching in the new era and a key initiative to implement the fundamental task of“virtue-fostering through education....Courses with ideological-political elements are a new direction of the reform of higher education teaching in the new era and a key initiative to implement the fundamental task of“virtue-fostering through education.”College English,as a public basic course in universities,undertakes the dual missions of language teaching and ideological-political education,making it a primary platform for implementing courses with ideological-political elements.Based on the current teaching state of college English courses with ideological-political elements,this paper explores the blended teaching mode of college English courses with ideological-political elements by reconstructing teaching content,innovating teaching methods,integrating online and offline resources,and optimizing the teaching process,focusing on the three stages of pre-class,in-class,and after-class.展开更多
In the context of the rapid advancement of intelligent manufacturing,ensuring the alignment of the skill levels of embedded system developers with industry requirements has emerged as a crucial aspect in the reform of...In the context of the rapid advancement of intelligent manufacturing,ensuring the alignment of the skill levels of embedded system developers with industry requirements has emerged as a crucial aspect in the reform of vocational education.This research delves into a three-stage progressive talent cultivation model denoted as“Cultivation–Growth–Incubation”,which is founded on the Shi Zhenjiang(Z.S.)Intelligent Embedded System Development Master Skills Studio.By means of hierarchical training,project-driven strategies,and industry-academia cooperation,this model effectively elevates students’application capabilities and innovative competencies in embedded systems.Case analyses illustrate the practical efficacy of the model,providing valuable references for the establishment of master skills studios in vocational education.展开更多
The Neogene Shawan Formation in the Chepaizi Uplift of the Junggar Basin(NW China)has obtained high oil flow,demonstrating a good potential for oil and gas exploration.The multi-source hydrocarbon generation backgroun...The Neogene Shawan Formation in the Chepaizi Uplift of the Junggar Basin(NW China)has obtained high oil flow,demonstrating a good potential for oil and gas exploration.The multi-source hydrocarbon generation background and strong tectonic activity have led to the simultaneous production of heavy oil and light oil from multi-layer in the area,which makes it very difficult to identify oil origins,presently,the hot debate on the oil origins needs to be clarified.In this paper,due to the selective consumption of different types of compounds in crude oils by severe and intense biodegradation,the commonly used oilsource correlation tools are ineffective or may produce misleading results,this study adopted a biomarker recovery method based on the principle of mass conservation that uses the sum of the mass of the residual biomarkers and their corresponding biodegradation products to obtain the mass of the original biomarkers,improving the reliability of oil origins determination.Based on the nature and occurrence of crude oils,the investigated oils are subdivided into three types,Group A,Group B and Group C.Group A,light oils occurred mainly in lower structure Neogene Shawan Formation in the western Chepaizi Uplift,while Group B,heavy oils occurred mainly in higher structure Neogene Shawan Formation in the western Chepaizi Uplift.The two types of crude oils may come from the mixed source of Jurassic Badaowan Formation source rocks(J_(1)b)and Paleogene Anjihaihe Formation source rocks(E_(2-3)a)in the Sikeshu Sag,and Jurassic Badaowan Formation source rocks(J_(1)b)are the main source of crude oils.Group C,heavy oils occurred mainly in Neogene Shawan Formation in the eastern Chepaizi Uplift,showing good correlation with the Permian(P_(1)f and P_(2)w)source rocks in the Shawan Sag.At the same time,by combining stable carbon isotope and parameters related to triaromatic steroids,the accuracy of the oilsource correlation results by biomarker recovery method was further verified.展开更多
Current improved Empirical Mode Decomposition(EMD)methods enhance the accurate identification of peak and valley points in mechanical signals through noise-assisted filtering techniques,thereby improving the mode deco...Current improved Empirical Mode Decomposition(EMD)methods enhance the accurate identification of peak and valley points in mechanical signals through noise-assisted filtering techniques,thereby improving the mode decomposition performance,which is of great significance in extracting fault features from mechanical signals.However,noise-assisted filtering leads to the loss of critical features in mechanical signals and introduces a large amount of residual noise into Intrinsic Mode Functions(IMFs)that obscure signal features.To address these issues,a Precise Identification-based Mode Decomposition(PIMD)method is proposed.This method directly enhances the ability of EMD to precisely identify peak and valley points by using a proposed precise identifi-cation approach,which improves mode decomposition performance and avoids the negative impacts of noise-assisted filtering,thus benefiting the extraction of more mechanical fault features.Simulation results show that the proposed PIMD method can precisely identify peak and valley points of signals with noise of different signal-tonoise ratios and perform a highly rigorous high-low frequency decomposition,significantly outperforming EMD.Finally,mechanical fault diagnostic experiments on four bearing cases and two gear cases demonstrate that,compared to four mainstream methods,the PIMD method exhibits the best mode decomposition perfor-mance and can extract more and clearer mechanical fault features.展开更多
The synthesis of high-quality heteroepitaxial diamond films on iridium composite substrates is a critical step toward advancing diamond for electronic and optical applications.Microwave plasma chemical vapor depositio...The synthesis of high-quality heteroepitaxial diamond films on iridium composite substrates is a critical step toward advancing diamond for electronic and optical applications.Microwave plasma chemical vapor deposition,combined with in situ optical emission spectroscopy,enables precise control over growth modes through plasma parameter tuning.In this study,we examine how methane concentration,microwave power,and gas pressure influence plasma species and,consequently,the growth modes of heteroepitaxial diamond by optical emission spectroscopy and scanning electron microscope.At low nucleation densities,increased methane concentrations promote the transition from faceted polyhedral to ballas structures,driven by elevated C_(2) radical concentrations in the plasma.Conversely,at higher nucleation densities,gas pressure,and substrate temperature dominate growth mode determination,leading to diverse morphologies,such as planar,polycrystalline,octahedral,and step-flow growth.These findings elucidate the interplay among plasma species,growth parameters,and growth mode,offering critical insights for optimizing growth conditions and preparing heteroepitaxial diamond films in a specific growth mode.展开更多
Auroral kilometric radiation(AKR),a fundamental plasma emission in Earth's magnetosphere,exhibits three characteristic modes:the right-handed extraordinary(R-X),left-handed ordinary(L-O)and left-handed extraordina...Auroral kilometric radiation(AKR),a fundamental plasma emission in Earth's magnetosphere,exhibits three characteristic modes:the right-handed extraordinary(R-X),left-handed ordinary(L-O)and left-handed extraordinary(L-X)modes.The role of AKR in magnetosphere−ionosphere−atmosphere coupling depends sensitively on its wave mode.While previous studies have primarily focused on the dominant R-X mode,we present the first systematic identification of all three modes using a practical polarization analysis method based on Arase satellite observations.This method employs a spin-axis-relative Ratio:when the satellite's spin axis aligns with the background magnetic field,a positive(negative)Ratio indicates the right-handed(left-handed)polarization,with reversal under anti-parallel conditions.Combined polarization-frequency analysis reveals that R-X,L-O,and L-X modes can exist in both dayside and nightside regions,with power spectral densities up to 10^(-6)mV^(2)m^(-2)Hz^(-1).This study resolves long-standing ambiguities in AKR mode classification and has implications for understanding AKR-induced electron dynamics.展开更多
Epithermal deposits are characterized by complex low-temperature hydrothermal alterations, but the links between mineralization and superimposed alteration are obscure and require further elucidation. This study emplo...Epithermal deposits are characterized by complex low-temperature hydrothermal alterations, but the links between mineralization and superimposed alteration are obscure and require further elucidation. This study employs shortwave infrared(SWIR) spectral scalars for alteration mineral mapping and three-dimensional modeling of the Ulan Uzhur Ag polymetallic deposit, a newly discovered epithermal deposit in the Qimantagh. Alteration zoning transitions from illitemuscovite-carbonate-pyrite in the core(Zone Ⅰ), through muscovite ± illite-kaolinite-chlorite-carbonate(Zone Ⅱ), to muscovite-chlorite-biotite(Zone Ⅲ) at the periphery. The Zone Ⅰ with mineralization features long-wavelength white mica(wAlOH > 2207 nm) with a high Illite Crystallinity(IC)(mean > 2.0), suggesting a relatively high-temperature environment conducive to mineralization. Petrographic analyses with fluid inclusion and IC curve characteristics suggests that fluid boiling may be a pivotal mechanism for mineral precipitation. Furthermore, surface mapping and deep threedimensional modeling of spectral characteristics reveal a correlation between long-wavelength white mica, high IC and mineralization zones. These findings indicate that SWIR spectroscopy reveal the evolution of fluids and provide valuable guidance for future exploration efforts.展开更多
Using multi-source reanalysis data,this study examines the relationship between the tropical Pacific-Atlantic SST Dipole Mode(TPA-DM)and summer precipitation in North China(NCSP)on the interannual timescale during the...Using multi-source reanalysis data,this study examines the relationship between the tropical Pacific-Atlantic SST Dipole Mode(TPA-DM)and summer precipitation in North China(NCSP)on the interannual timescale during the period of 1979-2022.The results show that the TPA-DM,the dominant pattern of interannual variability in the tropical Pacific and Atlantic regions,exhibits a significant negative correlation with NCSP.The positive phase of TPA-DM induces subsidence over the Maritime Continent through a zonal circulation pattern,which initiates a Pacific-Japan-like wave train along the East Asian coast.The circulation anomalies lead to moisture deficits and convergence subsidence over North China,leading to below-normal rainfall.Further analysis reveals that cooler SST in the Southern Tropical Atlantic facilitates the persistence of the TPA-DM by stimulating the anomalous Walker circulation associated with wind-evaporation-SST-convection feedback.展开更多
The integration of Artificial Intelligence(AI)and Machine Learning(ML)into groundwater exploration and water resources management has emerged as a transformative approach to addressing global water challenges.This rev...The integration of Artificial Intelligence(AI)and Machine Learning(ML)into groundwater exploration and water resources management has emerged as a transformative approach to addressing global water challenges.This review explores key AI and ML concepts,methodologies,and their applications in hydrology,focusing on groundwater potential mapping,water quality prediction,and groundwater level forecasting.It discusses various data acquisition techniques,including remote sensing,geospatial analysis,and geophysical surveys,alongside preprocessing methods that are essential for enhancing model accuracy.The study highlights AI-driven solutions in water distribution,allocation optimization,and realtime resource management.Despite their advantages,the application of AI and ML in water sciences faces several challenges,including data scarcity,model reliability,and the integration of these tools with traditional water management systems.Ethical and regulatory concerns also demand careful consideration.The paper also outlines future research directions,emphasizing the need for improved data collection,interpretable models,real-time monitoring capabilities,and interdisciplinary collaboration.By leveraging AI and ML advancements,the water sector can enhance decision-making,optimize resource distribution,and support the development of sustainable water management strategies.展开更多
Mycorrhizal symbioses are prevalent in terrestrial ecosystems and play essential roles in plant nutrition and health.However,the relative importance of plant evolutionary history,physiology,and eco-geographical factor...Mycorrhizal symbioses are prevalent in terrestrial ecosystems and play essential roles in plant nutrition and health.However,the relative importance of plant evolutionary history,physiology,and eco-geographical factors in shaping mycorrhizal fungal community assembly remains poorly understood.Here,we investigate how plant phylogeny,trophic mode,biogeographic distribution and environmental niche collectively influence the diversity and composition of mycorrhizal fungal communities across the Orchidaceae,spanning broad phylogenetic and ecological scales.By using family-wide orchid-fungal associations and global occurrence data,our analyses showed that the variation in fungal diversity and community structure can be partially explained by orchids’trophic mode,biogeographic distribution and environmental niche,but not by their overall phylogenetic relatedness.Among trophic modes,partially mycoheterotrophic orchids exhibited the highest level of fungal diversity(the lowest level of fungal specificity)in association with a broad range of phylogenetically dispersed fungal partners.Between biogeographical regions,a significantly higher level of fungal specificity was found for orchid species distributed in Australia than those in Eurasia and Africa.Furthermore,multivariate analyses showed that a small portion of the variation in fungal community structure was significantly related to broad climate,soil and vegetation variables,indicating the existence of large-scale habitat filtering on orchid mycorrhizal communities.Altogether,our findings indicate that mycorrhizal communities in the orchid family are likely shaped by multiple,intertwined factors related to orchid ecophysiology and biogeography on a global scale.展开更多
This paper introduces a framework for modeling random fields,with a particular emphasis on analyzing anisotropic spatial variability.It establishes a clear connection between the correlation function and the Kriging v...This paper introduces a framework for modeling random fields,with a particular emphasis on analyzing anisotropic spatial variability.It establishes a clear connection between the correlation function and the Kriging variogram across various anisotropic modes,providing mathematical models to enhance our understanding of random fields.A new anisotropy index,called LSAI,is introduced to quantify anisotropy based on the autocorrelation length and the orientation of the principal axes within the variogram.An LSAI value closer to one indicates a lower degree of anisotropy.The present study examines how the degree of anisotropy varies with different autocorrelation lengths and angles between the principal axes,providing valuable insights into these relationships.To improve the accuracy of parameter probability distribution estimations,this study integrates limited field test data using a Bayesian inference approach.Additionally,the Markov chain Monte Carlo simulation method is employed to develop a conditional random field(CRF)for the deformation modulus.By incorporating data from field bearing plate tests,the posterior variance data for the deformation modulus are derived.This process facilitates the construction of a detailed and reliable CRF for the deformation modulus.展开更多
Climate models are essential for understanding past,present,and future changes in atmospheric circulation,with circulation modes providing key sources of seasonal predictability and prediction uncertainties for both g...Climate models are essential for understanding past,present,and future changes in atmospheric circulation,with circulation modes providing key sources of seasonal predictability and prediction uncertainties for both global and regional climates.This study assesses the performance of models participating in phase 6 of the Coupled Model Intercomparison Project in simulating interannual variability modes of Northern Hemisphere 500-hPa geopotential height during winter and summer,distinguishing predictable(potentially predictable on seasonal or longer timescales)and unpredictable(intraseasonal and essentially unpredictable at long range)components,using reanalysis data and a variance decomposition method.Although most models effectively capture unpredictable modes in reanalysis,their ability to reproduce dominant predictable modes-specifically the Pacific-North American pattern,Arctic Oscillation,and Western Pacific Oscillation in winter,and the East Atlantic and North Atlantic Oscillations in summer-varies notably.An optimal ensemble is identified to distinguish(a)predictable-external modes,dominated by external forcing,and(b)predictable-internal modes,associated with slow internal variability,during the historical period(1950-2014)and the SSP5-8.5 scenario(2036-2100).Under increased radiative forcing,the leading winter/summer predictable-external mode exhibits a more uniform spatial distribution,remarkably larger trend and annual variance,and enhanced height-sea surface temperature(SST)covariance under SSP5-8.5 compared to historical conditions.The dominant winter/summer predictable-internal modes also exhibit increased variance and height-SST covariance under SSP5-8.5,along with localized changes in spatial configuration.Minimal changes are observed in spatial distribution or variance for dominant winter/summer unpredictable modes under SSP5-8.5.This study,from a predictive perspective,deepens our understanding of model uncertainties and projected changes in circulations.展开更多
Unmanned Aerial Vehicle(UAV)plays a prominent role in various fields,and autonomous navigation is a crucial component of UAV intelligence.Deep Reinforcement Learning(DRL)has expanded the research avenues for addressin...Unmanned Aerial Vehicle(UAV)plays a prominent role in various fields,and autonomous navigation is a crucial component of UAV intelligence.Deep Reinforcement Learning(DRL)has expanded the research avenues for addressing challenges in autonomous navigation.Nonetheless,challenges persist,including getting stuck in local optima,consuming excessive computations during action space exploration,and neglecting deterministic experience.This paper proposes a noise-driven enhancement strategy.In accordance with the overall learning phases,a global noise control method is designed,while a differentiated local noise control method is developed by analyzing the exploration demands of four typical situations encountered by UAV during navigation.Both methods are integrated into a dual-model for noise control to regulate action space exploration.Furthermore,noise dual experience replay buffers are designed to optimize the rational utilization of both deterministic and noisy experience.In uncertain environments,based on the Twin Delay Deep Deterministic Policy Gradient(TD3)algorithm with Long Short-Term Memory(LSTM)network and Priority Experience Replay(PER),a Noise-Driven Enhancement Priority Memory TD3(NDE-PMTD3)is developed.We established a simulation environment to compare different algorithms,and the performance of the algorithms is analyzed in various scenarios.The training results indicate that the proposed algorithm accelerates the convergence speed and enhances the convergence stability.In test experiments,the proposed algorithm successfully and efficiently performs autonomous navigation tasks in diverse environments,demonstrating superior generalization results.展开更多
Mode shift is a special mechanism for a power-split hybrid electric vehicle(HEV)to realise electrically variable transmission,but the sudden change of equivalent inertia caused by topological configuration recombinati...Mode shift is a special mechanism for a power-split hybrid electric vehicle(HEV)to realise electrically variable transmission,but the sudden change of equivalent inertia caused by topological configuration recombination during mode shift induces a significant torque shock.Therefore,a smooth transient process,among other concerns,typically associated with this category of vehicles,is of great importance.The present research aims to introduce a novel control strategy to manage the dynamic torque of multiple power sources and therefore im-prove ride comfort.To this end,a dynamic model of the objective power-split HEV is first built.To resolve the contention between vehicle jerk and clutch friction loss,a model predictive control(MPC)combined with control allocation(CA)is then designed for the clutch-engaged phase.To reduce the torque fluctuation caused by the inertia torques of multiple power sources,a dynamic compensation control strategy(DCcs)that coordinates motorgenerator torque to compensate for the transition torque is proposed for the brake-disengaged phase.Finally,the proposed control strategy is validated by simulation and bench test,and results show great potential in reducing shift duration,torque variation,vehicle jerk and friction loss(the simulation results show decreases of 22%,39%,83%and 53%,and the experimental results show decreases of 21%,74%,77%,and 59%,re-spectively),thereby improving shift quality.展开更多
Flexible materials play a crucial role in protecting against behind armour blunt trauma(BABT).However,their compliance complicates the understanding of failure mechanisms and energy absorption.This study used a combin...Flexible materials play a crucial role in protecting against behind armour blunt trauma(BABT).However,their compliance complicates the understanding of failure mechanisms and energy absorption.This study used a combined experimental and numerical approach to investigate the response and failure modes of a flexible ultra-high-molecular-weight polyethylene(UHMWPE)foam protective sandwich structure(UFPSS)under low-velocity impact(LVI).A finite element(FE)model,accounting for nonlinear large deformation and strain-rate-dependent material behavior,was developed for a woven-UFPSS(featuring a plain-woven fabric structure)subjected to a 50 J impact.Experimental and numerical results showed strong agreement in peak force(error<5%),maximum displacement(error<6%),and buffer time(error<8%).The impact's kinetic energy was mainly converted into internal energy of the fabric and foam materials(~50%),viscous dissipation in the foam core(12%-15%),frictional work at the contact interfaces(5%-6%),and work by the pneumatic fixture clamping force(~38%).This study provides the first investigation of the LVI performance of sandwich structures with all soft material layers,offering significant insights for the application of compliant materials in protective fields.展开更多
In 2025,the global rare earth exploration and development sector achieved breakthroughs across multiple fronts.Projects advanced intensively across the Americas,Oceania,Africa,and Europe,with significant growth in res...In 2025,the global rare earth exploration and development sector achieved breakthroughs across multiple fronts.Projects advanced intensively across the Americas,Oceania,Africa,and Europe,with significant growth in resources,continuous emergence of new deposits,and strong impetus injected into the industry by technological innovation and policy support.The global rare earth resource supply pattern was further optimized (Table 1).1.Fruitful results in resource growth and new deposit discoveriesBrazil emerged as a core region for resource growth.The Colossus rare earth deposit saw a 150%increase in resources and announced its first reserve estimate.The Caldeira rare earth deposit’s resource estimate grew by 50%.The combined ore resources in the Caladão rare earth deposit’s Zones A and B reached 5.72×10~8 tonnes,with a total rare earth oxide(TREO) grade of 0.1506%,concurrently hosting 2.29×10~4tonnes of gallium metal resources.展开更多
In dry-coupled ultrasonic thickness measurement,thick rubber layers introduce high-amplitude parasitic echoes that obscure defect signals and degrade thickness accuracy.Existing methods struggle to resolve overlap-pin...In dry-coupled ultrasonic thickness measurement,thick rubber layers introduce high-amplitude parasitic echoes that obscure defect signals and degrade thickness accuracy.Existing methods struggle to resolve overlap-ping echoes under variable coupling conditions and non-stationary noise.This study proposes a novel dual-criterion framework integrating energy contribution and statistical impulsivity metrics to isolate specimen re-flections from coupling-layer interference.By decomposing A-scan signals into Intrinsic Mode Functions(IMFs),the framework employs energy contribution thresholds(>85%)and kurtosis indices(>3)to autonomously select IMFs containing valid specimen echoes.Hybrid time-frequency thresholding further suppresses interference through amplitude filtering and spectral focusing.Experimental results demonstrate the framework’s robustness,achieving 92.3%thickness accuracy for 5 mm steel specimens with 5 mm rubber coupling,outperforming conventional methods by up to 18.7%.The dual-criterion approach reduces operator dependency by 37%and maintainsΔT<0.03 mm under surface roughness up to 6.3μm,offering a practical solution for industrial nondestructive testing with thick dry-coupled interfaces.展开更多
文摘Renewable energy resources,including geothermal,are crucial for sustainable environmental management and climate change mitigation,offering clean,reliable,and low-emission alternatives to fossil fuels that reduce greenhouse gases and support ecological balance.In this study,geographic information system(GIS)predictive analysis was employed to explore geothermal prospects,promoting environmental sustainability by reducing the dependence on fossil energy resources.Spatial and statistical analysis including the attribute correlation analysis was used to evaluate the relationship between exploration data and geothermal energy resources represented by hot springs.The weighted sum model was then used to develop geothermal predictive maps while the accuracy of prediction was determined using the receiver operating characteristic/area under curve(ROC/AUC)analysis.Based on the attribute correlation analysis,exploration data relating to geological structures,host rock(Asu River Group)and sedimentary contacts were the most critical parameters for mapping geothermal resources.These parameters were characterized by a statistical association of 0.52,0.48,and 0.46 with the known geothermal occurrences.Spatial data integration reveals the central part of the study location as the most prospective zone for geothermal occurrences.This zone occupies 14.76%of the study location.Accuracy assessment using the ROC/AUC analysis suggests an efficiency of 81.5%for the weight sum model.GIS-based multi-criteria analysis improves the identification and evaluation of geothermal resources,leading to better decision-making.
基金supported by the Science&Technology Fundamental Resources Investigation Program(2022FY101705)China geological survey project(DD20240204805)market prospecting exploration project(CG-2024-HX-S012)。
文摘The Sawayaerdun gold deposit is the only extremely large deposit occurring in the giant gold metallogenic belt of the Central Asian Tianshan Orogenic Belt.Breakthroughs in deep and peripheral exploration are of great significance for the sustainable development of the region.In this study,a comprehensive prospecting and exploration model for gold exploration in the high-cold and high-altitude areas of the southwestern Tianshan Mountains was developed by systematically evaluating the metallogenic geological conditions of the deposit and integrating geological,geochemical,and geophysical exploration multi-source data.Both the shallow metamorphic carbonaceous fine clastic rock and ductile shear zones controlled the Au-mineralized zone.Moreover,mineralized alteration,Au-Sb-As element chemical anomalies,high magnetic anomalies,and medium-high values from low-wave impedance were also important components of the model.Three-dimensional(3-D)geological attribute models of various ore-controlling factors were established,revealing the spatial distribution patterns of the deep structural frameworks and hidden mineralization.Geostatistical methods were used to delineate the three edges and two deep-mineral exploration areas.A comprehensive evaluation showed that anomalous variables were well confirmed in geological understanding,highlighting the effectiveness and accuracy of the predictions.These results are significant for deep-edge exploration.
文摘This paper focuses on the application of AIGC(Artificial Intelligence Generated Content)technology in higher vocational education teaching modes.It deeply explores the significant meaning of AIGC in empowering higher vocational education,and analyzes the existing problems when AIGC technology is applied to such teaching modes,covering aspects like technology application,teaching staff,students’adaptability,and educational management.Meanwhile,it puts forward targeted and effective paths for AIGC technology to empower higher vocational education teaching modes,including optimizing technology application,strengthening teacher training,improving students’literacy,and perfecting educational management.The paper aims to promote the in-depth integration of AIGC technology and higher vocational education,realize the innovation and high-quality development of higher vocational education teaching modes,and provide theoretical references and practical guidance for cultivating high-quality technical and skilled talents who meet the needs of the new era.
基金phased research achievement of the Educational and Teaching Reform Research Project of Tangshan Normal University,titled“Construction and Practical Research on the Teaching Framework of College English Courses with Ideological-Political Elements under the Background of New Liberal Arts”(2023JG13).
文摘Courses with ideological-political elements are a new direction of the reform of higher education teaching in the new era and a key initiative to implement the fundamental task of“virtue-fostering through education.”College English,as a public basic course in universities,undertakes the dual missions of language teaching and ideological-political education,making it a primary platform for implementing courses with ideological-political elements.Based on the current teaching state of college English courses with ideological-political elements,this paper explores the blended teaching mode of college English courses with ideological-political elements by reconstructing teaching content,innovating teaching methods,integrating online and offline resources,and optimizing the teaching process,focusing on the three stages of pre-class,in-class,and after-class.
基金The 2025 Guangdong Polytechnic College Innovation-driven School Strengthening Project“Construction of Shi Zhenjiang’s Master Studio for Intelligent Embedded System Development Skills”(Project No.:2025CQ06-05)。
文摘In the context of the rapid advancement of intelligent manufacturing,ensuring the alignment of the skill levels of embedded system developers with industry requirements has emerged as a crucial aspect in the reform of vocational education.This research delves into a three-stage progressive talent cultivation model denoted as“Cultivation–Growth–Incubation”,which is founded on the Shi Zhenjiang(Z.S.)Intelligent Embedded System Development Master Skills Studio.By means of hierarchical training,project-driven strategies,and industry-academia cooperation,this model effectively elevates students’application capabilities and innovative competencies in embedded systems.Case analyses illustrate the practical efficacy of the model,providing valuable references for the establishment of master skills studios in vocational education.
基金co-funded by the National Natural Science Foundation of China(42372160,42072172)。
文摘The Neogene Shawan Formation in the Chepaizi Uplift of the Junggar Basin(NW China)has obtained high oil flow,demonstrating a good potential for oil and gas exploration.The multi-source hydrocarbon generation background and strong tectonic activity have led to the simultaneous production of heavy oil and light oil from multi-layer in the area,which makes it very difficult to identify oil origins,presently,the hot debate on the oil origins needs to be clarified.In this paper,due to the selective consumption of different types of compounds in crude oils by severe and intense biodegradation,the commonly used oilsource correlation tools are ineffective or may produce misleading results,this study adopted a biomarker recovery method based on the principle of mass conservation that uses the sum of the mass of the residual biomarkers and their corresponding biodegradation products to obtain the mass of the original biomarkers,improving the reliability of oil origins determination.Based on the nature and occurrence of crude oils,the investigated oils are subdivided into three types,Group A,Group B and Group C.Group A,light oils occurred mainly in lower structure Neogene Shawan Formation in the western Chepaizi Uplift,while Group B,heavy oils occurred mainly in higher structure Neogene Shawan Formation in the western Chepaizi Uplift.The two types of crude oils may come from the mixed source of Jurassic Badaowan Formation source rocks(J_(1)b)and Paleogene Anjihaihe Formation source rocks(E_(2-3)a)in the Sikeshu Sag,and Jurassic Badaowan Formation source rocks(J_(1)b)are the main source of crude oils.Group C,heavy oils occurred mainly in Neogene Shawan Formation in the eastern Chepaizi Uplift,showing good correlation with the Permian(P_(1)f and P_(2)w)source rocks in the Shawan Sag.At the same time,by combining stable carbon isotope and parameters related to triaromatic steroids,the accuracy of the oilsource correlation results by biomarker recovery method was further verified.
基金Supported by National Natural Science Foundation of China(Grant No.52075236)Opening Foundation of Intelligent Manufacturing Technology(Shantou University),Ministry of Education(Grant No.STME2024002)+1 种基金Hundred Doctor and Hundred Enterprise,Science and Technology Project,Ji'an City(Grant No.42064001)Guangdong Provincial University Innovation Team Project(Grant No.2020KCXTD012).
文摘Current improved Empirical Mode Decomposition(EMD)methods enhance the accurate identification of peak and valley points in mechanical signals through noise-assisted filtering techniques,thereby improving the mode decomposition performance,which is of great significance in extracting fault features from mechanical signals.However,noise-assisted filtering leads to the loss of critical features in mechanical signals and introduces a large amount of residual noise into Intrinsic Mode Functions(IMFs)that obscure signal features.To address these issues,a Precise Identification-based Mode Decomposition(PIMD)method is proposed.This method directly enhances the ability of EMD to precisely identify peak and valley points by using a proposed precise identifi-cation approach,which improves mode decomposition performance and avoids the negative impacts of noise-assisted filtering,thus benefiting the extraction of more mechanical fault features.Simulation results show that the proposed PIMD method can precisely identify peak and valley points of signals with noise of different signal-tonoise ratios and perform a highly rigorous high-low frequency decomposition,significantly outperforming EMD.Finally,mechanical fault diagnostic experiments on four bearing cases and two gear cases demonstrate that,compared to four mainstream methods,the PIMD method exhibits the best mode decomposition perfor-mance and can extract more and clearer mechanical fault features.
基金funded by the National Key Research and Development Program of China(Grant No.2022YFB3608602)the National Natural Science Foundation of China(Grant Nos.62404215 and 62574199)Instrument and Equipment Development Project of CAS(Grant No.PTYQ2024TD0003)。
文摘The synthesis of high-quality heteroepitaxial diamond films on iridium composite substrates is a critical step toward advancing diamond for electronic and optical applications.Microwave plasma chemical vapor deposition,combined with in situ optical emission spectroscopy,enables precise control over growth modes through plasma parameter tuning.In this study,we examine how methane concentration,microwave power,and gas pressure influence plasma species and,consequently,the growth modes of heteroepitaxial diamond by optical emission spectroscopy and scanning electron microscope.At low nucleation densities,increased methane concentrations promote the transition from faceted polyhedral to ballas structures,driven by elevated C_(2) radical concentrations in the plasma.Conversely,at higher nucleation densities,gas pressure,and substrate temperature dominate growth mode determination,leading to diverse morphologies,such as planar,polycrystalline,octahedral,and step-flow growth.These findings elucidate the interplay among plasma species,growth parameters,and growth mode,offering critical insights for optimizing growth conditions and preparing heteroepitaxial diamond films in a specific growth mode.
基金supported by the National Natural Science Foundation of China(Grants 42374215,42230209,42374199,42304183,42422406,42174185,72061147004 and 72342001)the Science and Technology Development Fund,Macao SAR(File no.0042/2024/RIA1 and 0008/2024/AKP)+1 种基金the Natural Science Foundation of Hunan Province(Grant 2023JJ20038)the Research Project of Science and Technology of Hunan Province(2025JJ10009,2022RC4025,2025QK1004,2023JJ50312,2023JJ50010 and 2024RC9012).
文摘Auroral kilometric radiation(AKR),a fundamental plasma emission in Earth's magnetosphere,exhibits three characteristic modes:the right-handed extraordinary(R-X),left-handed ordinary(L-O)and left-handed extraordinary(L-X)modes.The role of AKR in magnetosphere−ionosphere−atmosphere coupling depends sensitively on its wave mode.While previous studies have primarily focused on the dominant R-X mode,we present the first systematic identification of all three modes using a practical polarization analysis method based on Arase satellite observations.This method employs a spin-axis-relative Ratio:when the satellite's spin axis aligns with the background magnetic field,a positive(negative)Ratio indicates the right-handed(left-handed)polarization,with reversal under anti-parallel conditions.Combined polarization-frequency analysis reveals that R-X,L-O,and L-X modes can exist in both dayside and nightside regions,with power spectral densities up to 10^(-6)mV^(2)m^(-2)Hz^(-1).This study resolves long-standing ambiguities in AKR mode classification and has implications for understanding AKR-induced electron dynamics.
基金supported by the Natural Science Foundation of China(Grant No.42372346,41802080,42030809,41873043).
文摘Epithermal deposits are characterized by complex low-temperature hydrothermal alterations, but the links between mineralization and superimposed alteration are obscure and require further elucidation. This study employs shortwave infrared(SWIR) spectral scalars for alteration mineral mapping and three-dimensional modeling of the Ulan Uzhur Ag polymetallic deposit, a newly discovered epithermal deposit in the Qimantagh. Alteration zoning transitions from illitemuscovite-carbonate-pyrite in the core(Zone Ⅰ), through muscovite ± illite-kaolinite-chlorite-carbonate(Zone Ⅱ), to muscovite-chlorite-biotite(Zone Ⅲ) at the periphery. The Zone Ⅰ with mineralization features long-wavelength white mica(wAlOH > 2207 nm) with a high Illite Crystallinity(IC)(mean > 2.0), suggesting a relatively high-temperature environment conducive to mineralization. Petrographic analyses with fluid inclusion and IC curve characteristics suggests that fluid boiling may be a pivotal mechanism for mineral precipitation. Furthermore, surface mapping and deep threedimensional modeling of spectral characteristics reveal a correlation between long-wavelength white mica, high IC and mineralization zones. These findings indicate that SWIR spectroscopy reveal the evolution of fluids and provide valuable guidance for future exploration efforts.
基金jointly supported by the Second Tibetan Plateau Scientific Expedition and Research Program[grant number-ber 2019QZKK0103]the National Natural Science Foundation of China[grant number 42293294]the China Meteorological Admin-istration Climate Change Special Program[grant number QBZ202303]。
文摘Using multi-source reanalysis data,this study examines the relationship between the tropical Pacific-Atlantic SST Dipole Mode(TPA-DM)and summer precipitation in North China(NCSP)on the interannual timescale during the period of 1979-2022.The results show that the TPA-DM,the dominant pattern of interannual variability in the tropical Pacific and Atlantic regions,exhibits a significant negative correlation with NCSP.The positive phase of TPA-DM induces subsidence over the Maritime Continent through a zonal circulation pattern,which initiates a Pacific-Japan-like wave train along the East Asian coast.The circulation anomalies lead to moisture deficits and convergence subsidence over North China,leading to below-normal rainfall.Further analysis reveals that cooler SST in the Southern Tropical Atlantic facilitates the persistence of the TPA-DM by stimulating the anomalous Walker circulation associated with wind-evaporation-SST-convection feedback.
文摘The integration of Artificial Intelligence(AI)and Machine Learning(ML)into groundwater exploration and water resources management has emerged as a transformative approach to addressing global water challenges.This review explores key AI and ML concepts,methodologies,and their applications in hydrology,focusing on groundwater potential mapping,water quality prediction,and groundwater level forecasting.It discusses various data acquisition techniques,including remote sensing,geospatial analysis,and geophysical surveys,alongside preprocessing methods that are essential for enhancing model accuracy.The study highlights AI-driven solutions in water distribution,allocation optimization,and realtime resource management.Despite their advantages,the application of AI and ML in water sciences faces several challenges,including data scarcity,model reliability,and the integration of these tools with traditional water management systems.Ethical and regulatory concerns also demand careful consideration.The paper also outlines future research directions,emphasizing the need for improved data collection,interpretable models,real-time monitoring capabilities,and interdisciplinary collaboration.By leveraging AI and ML advancements,the water sector can enhance decision-making,optimize resource distribution,and support the development of sustainable water management strategies.
基金the funding provided by the China Scholarship Council(Grant No.201804910634)the Ecology Fund of the Royal Netherlands Academy of Arts and Sciences(KNAWWF/807/19039)to Deyi Wang.
文摘Mycorrhizal symbioses are prevalent in terrestrial ecosystems and play essential roles in plant nutrition and health.However,the relative importance of plant evolutionary history,physiology,and eco-geographical factors in shaping mycorrhizal fungal community assembly remains poorly understood.Here,we investigate how plant phylogeny,trophic mode,biogeographic distribution and environmental niche collectively influence the diversity and composition of mycorrhizal fungal communities across the Orchidaceae,spanning broad phylogenetic and ecological scales.By using family-wide orchid-fungal associations and global occurrence data,our analyses showed that the variation in fungal diversity and community structure can be partially explained by orchids’trophic mode,biogeographic distribution and environmental niche,but not by their overall phylogenetic relatedness.Among trophic modes,partially mycoheterotrophic orchids exhibited the highest level of fungal diversity(the lowest level of fungal specificity)in association with a broad range of phylogenetically dispersed fungal partners.Between biogeographical regions,a significantly higher level of fungal specificity was found for orchid species distributed in Australia than those in Eurasia and Africa.Furthermore,multivariate analyses showed that a small portion of the variation in fungal community structure was significantly related to broad climate,soil and vegetation variables,indicating the existence of large-scale habitat filtering on orchid mycorrhizal communities.Altogether,our findings indicate that mycorrhizal communities in the orchid family are likely shaped by multiple,intertwined factors related to orchid ecophysiology and biogeography on a global scale.
基金supported by the Doctoral Research Funds for Nanchang HangKong University,China(Grant No.EA202411211)support is gratefully acknowledged.
文摘This paper introduces a framework for modeling random fields,with a particular emphasis on analyzing anisotropic spatial variability.It establishes a clear connection between the correlation function and the Kriging variogram across various anisotropic modes,providing mathematical models to enhance our understanding of random fields.A new anisotropy index,called LSAI,is introduced to quantify anisotropy based on the autocorrelation length and the orientation of the principal axes within the variogram.An LSAI value closer to one indicates a lower degree of anisotropy.The present study examines how the degree of anisotropy varies with different autocorrelation lengths and angles between the principal axes,providing valuable insights into these relationships.To improve the accuracy of parameter probability distribution estimations,this study integrates limited field test data using a Bayesian inference approach.Additionally,the Markov chain Monte Carlo simulation method is employed to develop a conditional random field(CRF)for the deformation modulus.By incorporating data from field bearing plate tests,the posterior variance data for the deformation modulus are derived.This process facilitates the construction of a detailed and reliable CRF for the deformation modulus.
基金supported by the National Natural Science Foundation of China(Grant Nos.U2342210 and 42275043)the National Institute of Natural Hazards,Ministry of Emergency Management of China(Grant Nos.J2223806,ZDJ2024-25 and ZDJ2025-34)。
文摘Climate models are essential for understanding past,present,and future changes in atmospheric circulation,with circulation modes providing key sources of seasonal predictability and prediction uncertainties for both global and regional climates.This study assesses the performance of models participating in phase 6 of the Coupled Model Intercomparison Project in simulating interannual variability modes of Northern Hemisphere 500-hPa geopotential height during winter and summer,distinguishing predictable(potentially predictable on seasonal or longer timescales)and unpredictable(intraseasonal and essentially unpredictable at long range)components,using reanalysis data and a variance decomposition method.Although most models effectively capture unpredictable modes in reanalysis,their ability to reproduce dominant predictable modes-specifically the Pacific-North American pattern,Arctic Oscillation,and Western Pacific Oscillation in winter,and the East Atlantic and North Atlantic Oscillations in summer-varies notably.An optimal ensemble is identified to distinguish(a)predictable-external modes,dominated by external forcing,and(b)predictable-internal modes,associated with slow internal variability,during the historical period(1950-2014)and the SSP5-8.5 scenario(2036-2100).Under increased radiative forcing,the leading winter/summer predictable-external mode exhibits a more uniform spatial distribution,remarkably larger trend and annual variance,and enhanced height-sea surface temperature(SST)covariance under SSP5-8.5 compared to historical conditions.The dominant winter/summer predictable-internal modes also exhibit increased variance and height-SST covariance under SSP5-8.5,along with localized changes in spatial configuration.Minimal changes are observed in spatial distribution or variance for dominant winter/summer unpredictable modes under SSP5-8.5.This study,from a predictive perspective,deepens our understanding of model uncertainties and projected changes in circulations.
基金the Collaborative Innovation Project of Shanghai,China for the financial support。
文摘Unmanned Aerial Vehicle(UAV)plays a prominent role in various fields,and autonomous navigation is a crucial component of UAV intelligence.Deep Reinforcement Learning(DRL)has expanded the research avenues for addressing challenges in autonomous navigation.Nonetheless,challenges persist,including getting stuck in local optima,consuming excessive computations during action space exploration,and neglecting deterministic experience.This paper proposes a noise-driven enhancement strategy.In accordance with the overall learning phases,a global noise control method is designed,while a differentiated local noise control method is developed by analyzing the exploration demands of four typical situations encountered by UAV during navigation.Both methods are integrated into a dual-model for noise control to regulate action space exploration.Furthermore,noise dual experience replay buffers are designed to optimize the rational utilization of both deterministic and noisy experience.In uncertain environments,based on the Twin Delay Deep Deterministic Policy Gradient(TD3)algorithm with Long Short-Term Memory(LSTM)network and Priority Experience Replay(PER),a Noise-Driven Enhancement Priority Memory TD3(NDE-PMTD3)is developed.We established a simulation environment to compare different algorithms,and the performance of the algorithms is analyzed in various scenarios.The training results indicate that the proposed algorithm accelerates the convergence speed and enhances the convergence stability.In test experiments,the proposed algorithm successfully and efficiently performs autonomous navigation tasks in diverse environments,demonstrating superior generalization results.
基金Supported by National Natural Science Foundation of China(Grant Nos.52005039,51575043,51975048,U1764257).
文摘Mode shift is a special mechanism for a power-split hybrid electric vehicle(HEV)to realise electrically variable transmission,but the sudden change of equivalent inertia caused by topological configuration recombination during mode shift induces a significant torque shock.Therefore,a smooth transient process,among other concerns,typically associated with this category of vehicles,is of great importance.The present research aims to introduce a novel control strategy to manage the dynamic torque of multiple power sources and therefore im-prove ride comfort.To this end,a dynamic model of the objective power-split HEV is first built.To resolve the contention between vehicle jerk and clutch friction loss,a model predictive control(MPC)combined with control allocation(CA)is then designed for the clutch-engaged phase.To reduce the torque fluctuation caused by the inertia torques of multiple power sources,a dynamic compensation control strategy(DCcs)that coordinates motorgenerator torque to compensate for the transition torque is proposed for the brake-disengaged phase.Finally,the proposed control strategy is validated by simulation and bench test,and results show great potential in reducing shift duration,torque variation,vehicle jerk and friction loss(the simulation results show decreases of 22%,39%,83%and 53%,and the experimental results show decreases of 21%,74%,77%,and 59%,re-spectively),thereby improving shift quality.
基金supported by the Zhenjiang Key R&D Plan(GY2021009)Lianyungang City Major Technology Breakthrough(CGJBGS2104)+2 种基金National Natural Science Foundation of China under Grant(12302456)National Key Laboratory Foundation of Science and Technology on Materials under Shock and Impact under Grant(6142902241601)China Postdoctoral Science Foundation under Grants(2025M774217)。
文摘Flexible materials play a crucial role in protecting against behind armour blunt trauma(BABT).However,their compliance complicates the understanding of failure mechanisms and energy absorption.This study used a combined experimental and numerical approach to investigate the response and failure modes of a flexible ultra-high-molecular-weight polyethylene(UHMWPE)foam protective sandwich structure(UFPSS)under low-velocity impact(LVI).A finite element(FE)model,accounting for nonlinear large deformation and strain-rate-dependent material behavior,was developed for a woven-UFPSS(featuring a plain-woven fabric structure)subjected to a 50 J impact.Experimental and numerical results showed strong agreement in peak force(error<5%),maximum displacement(error<6%),and buffer time(error<8%).The impact's kinetic energy was mainly converted into internal energy of the fabric and foam materials(~50%),viscous dissipation in the foam core(12%-15%),frictional work at the contact interfaces(5%-6%),and work by the pneumatic fixture clamping force(~38%).This study provides the first investigation of the LVI performance of sandwich structures with all soft material layers,offering significant insights for the application of compliant materials in protective fields.
文摘In 2025,the global rare earth exploration and development sector achieved breakthroughs across multiple fronts.Projects advanced intensively across the Americas,Oceania,Africa,and Europe,with significant growth in resources,continuous emergence of new deposits,and strong impetus injected into the industry by technological innovation and policy support.The global rare earth resource supply pattern was further optimized (Table 1).1.Fruitful results in resource growth and new deposit discoveriesBrazil emerged as a core region for resource growth.The Colossus rare earth deposit saw a 150%increase in resources and announced its first reserve estimate.The Caldeira rare earth deposit’s resource estimate grew by 50%.The combined ore resources in the Caladão rare earth deposit’s Zones A and B reached 5.72×10~8 tonnes,with a total rare earth oxide(TREO) grade of 0.1506%,concurrently hosting 2.29×10~4tonnes of gallium metal resources.
基金funded by the National Natural Science Foundation of China,grant number U24A20135Inner Mongolia Natural Science Foundation major project,grant number 2023ZD12+7 种基金Inner Mongolia Autonomous Region key research and development and achievement transformation plan project,grant number 2023YFHH0090Natural Science Foundation of Inner Mongolia,grant number 2022MS05006Inner Mongolia Autonomous Region Talent Development FundUniversity basic research business expenses,grant number 2023RCTD012University basic research business expenses,grant number 2023QNJS075Postgraduate Research Innovation Program and of Inner Mongolia Autonomous Region,grant number KC2024053BUniversity basic research business expenses,grant number 2024YXXS012National Key Laboratory of Special Vehicle Design and Manufacturing Integration Technology,grant number GZ2023KF012.
文摘In dry-coupled ultrasonic thickness measurement,thick rubber layers introduce high-amplitude parasitic echoes that obscure defect signals and degrade thickness accuracy.Existing methods struggle to resolve overlap-ping echoes under variable coupling conditions and non-stationary noise.This study proposes a novel dual-criterion framework integrating energy contribution and statistical impulsivity metrics to isolate specimen re-flections from coupling-layer interference.By decomposing A-scan signals into Intrinsic Mode Functions(IMFs),the framework employs energy contribution thresholds(>85%)and kurtosis indices(>3)to autonomously select IMFs containing valid specimen echoes.Hybrid time-frequency thresholding further suppresses interference through amplitude filtering and spectral focusing.Experimental results demonstrate the framework’s robustness,achieving 92.3%thickness accuracy for 5 mm steel specimens with 5 mm rubber coupling,outperforming conventional methods by up to 18.7%.The dual-criterion approach reduces operator dependency by 37%and maintainsΔT<0.03 mm under surface roughness up to 6.3μm,offering a practical solution for industrial nondestructive testing with thick dry-coupled interfaces.
