A unified mathematical model is established to simulate the nonlinear unsteady percolation of shale gas with the consideration of the nonlinear multi-scale effects such as slippage, diffusion, and desorption. The cont...A unified mathematical model is established to simulate the nonlinear unsteady percolation of shale gas with the consideration of the nonlinear multi-scale effects such as slippage, diffusion, and desorption. The continuous inhomogeneous models of equivalent porosity and permeability are proposed for the whole shale gas reservoir includ- ing the hydraulic fracture, the micro-fracture, and the matrix regions. The corresponding semi-analytical method is developed by transforming the nonlinear partial differential governing equation into the integral equation and the numerical discretization. The nonlinear multi-scale effects of slippage and diffusion and the pressure dependent effect of desorption on the shale gas production are investigated.展开更多
Images taken in dim environments frequently exhibit issues like insufficient brightness,noise,color shifts,and loss of detail.These problems pose significant challenges to dark image enhancement tasks.Current approach...Images taken in dim environments frequently exhibit issues like insufficient brightness,noise,color shifts,and loss of detail.These problems pose significant challenges to dark image enhancement tasks.Current approaches,while effective in global illumination modeling,often struggle to simultaneously suppress noise and preserve structural details,especially under heterogeneous lighting.Furthermore,misalignment between luminance and color channels introduces additional challenges to accurate enhancement.In response to the aforementioned difficulties,we introduce a single-stage framework,M2ATNet,using the multi-scale multi-attention and Transformer architecture.First,to address the problems of texture blurring and residual noise,we design a multi-scale multi-attention denoising module(MMAD),which is applied separately to the luminance and color channels to enhance the structural and texture modeling capabilities.Secondly,to solve the non-alignment problem of the luminance and color channels,we introduce the multi-channel feature fusion Transformer(CFFT)module,which effectively recovers the dark details and corrects the color shifts through cross-channel alignment and deep feature interaction.To guide the model to learn more stably and efficiently,we also fuse multiple types of loss functions to form a hybrid loss term.We extensively evaluate the proposed method on various standard datasets,including LOL-v1,LOL-v2,DICM,LIME,and NPE.Evaluation in terms of numerical metrics and visual quality demonstrate that M2ATNet consistently outperforms existing advanced approaches.Ablation studies further confirm the critical roles played by the MMAD and CFFT modules to detail preservation and visual fidelity under challenging illumination-deficient environments.展开更多
Accurate and efficient detection of building changes in remote sensing imagery is crucial for urban planning,disaster emergency response,and resource management.However,existing methods face challenges such as spectra...Accurate and efficient detection of building changes in remote sensing imagery is crucial for urban planning,disaster emergency response,and resource management.However,existing methods face challenges such as spectral similarity between buildings and backgrounds,sensor variations,and insufficient computational efficiency.To address these challenges,this paper proposes a novel Multi-scale Efficient Wavelet-based Change Detection Network(MewCDNet),which integrates the advantages of Convolutional Neural Networks and Transformers,balances computational costs,and achieves high-performance building change detection.The network employs EfficientNet-B4 as the backbone for hierarchical feature extraction,integrates multi-level feature maps through a multi-scale fusion strategy,and incorporates two key modules:Cross-temporal Difference Detection(CTDD)and Cross-scale Wavelet Refinement(CSWR).CTDD adopts a dual-branch architecture that combines pixel-wise differencing with semanticaware Euclidean distance weighting to enhance the distinction between true changes and background noise.CSWR integrates Haar-based Discrete Wavelet Transform with multi-head cross-attention mechanisms,enabling cross-scale feature fusion while significantly improving edge localization and suppressing spurious changes.Extensive experiments on four benchmark datasets demonstrate MewCDNet’s superiority over comparison methods:achieving F1 scores of 91.54%on LEVIR,93.70%on WHUCD,and 64.96%on S2Looking for building change detection.Furthermore,MewCDNet exhibits optimal performance on the multi-class⋅SYSU dataset(F1:82.71%),highlighting its exceptional generalization capability.展开更多
With the rapid expansion of drone applications,accurate detection of objects in aerial imagery has become crucial for intelligent transportation,urban management,and emergency rescue missions.However,existing methods ...With the rapid expansion of drone applications,accurate detection of objects in aerial imagery has become crucial for intelligent transportation,urban management,and emergency rescue missions.However,existing methods face numerous challenges in practical deployment,including scale variation handling,feature degradation,and complex backgrounds.To address these issues,we propose Edge-enhanced and Detail-Capturing You Only Look Once(EHDC-YOLO),a novel framework for object detection in Unmanned Aerial Vehicle(UAV)imagery.Based on the You Only Look Once version 11 nano(YOLOv11n)baseline,EHDC-YOLO systematically introduces several architectural enhancements:(1)a Multi-Scale Edge Enhancement(MSEE)module that leverages multi-scale pooling and edge information to enhance boundary feature extraction;(2)an Enhanced Feature Pyramid Network(EFPN)that integrates P2-level features with Cross Stage Partial(CSP)structures and OmniKernel convolutions for better fine-grained representation;and(3)Dynamic Head(DyHead)with multi-dimensional attention mechanisms for enhanced cross-scale modeling and perspective adaptability.Comprehensive experiments on the Vision meets Drones for Detection(VisDrone-DET)2019 dataset demonstrate that EHDC-YOLO achieves significant improvements,increasing mean Average Precision(mAP)@0.5 from 33.2%to 46.1%(an absolute improvement of 12.9 percentage points)and mAP@0.5:0.95 from 19.5%to 28.0%(an absolute improvement of 8.5 percentage points)compared with the YOLOv11n baseline,while maintaining a reasonable parameter count(2.81 M vs the baseline’s 2.58 M).Further ablation studies confirm the effectiveness of each proposed component,while visualization results highlight EHDC-YOLO’s superior performance in detecting objects and handling occlusions in complex drone scenarios.展开更多
Impact craters are important for understanding the evolution of lunar geologic and surface erosion rates,among other functions.However,the morphological characteristics of these micro impact craters are not obvious an...Impact craters are important for understanding the evolution of lunar geologic and surface erosion rates,among other functions.However,the morphological characteristics of these micro impact craters are not obvious and they are numerous,resulting in low detection accuracy by deep learning models.Therefore,we proposed a new multi-scale fusion crater detection algorithm(MSF-CDA)based on the YOLO11 to improve the accuracy of lunar impact crater detection,especially for small craters with a diameter of<1 km.Using the images taken by the LROC(Lunar Reconnaissance Orbiter Camera)at the Chang’e-4(CE-4)landing area,we constructed three separate datasets for craters with diameters of 0-70 m,70-140 m,and>140 m.We then trained three submodels separately with these three datasets.Additionally,we designed a slicing-amplifying-slicing strategy to enhance the ability to extract features from small craters.To handle redundant predictions,we proposed a new Non-Maximum Suppression with Area Filtering method to fuse the results in overlapping targets within the multi-scale submodels.Finally,our new MSF-CDA method achieved high detection performance,with the Precision,Recall,and F1 score having values of 0.991,0.987,and 0.989,respectively,perfectly addressing the problems induced by the lesser features and sample imbalance of small craters.Our MSF-CDA can provide strong data support for more in-depth study of the geological evolution of the lunar surface and finer geological age estimations.This strategy can also be used to detect other small objects with lesser features and sample imbalance problems.We detected approximately 500,000 impact craters in an area of approximately 214 km2 around the CE-4 landing area.By statistically analyzing the new data,we updated the distribution function of the number and diameter of impact craters.Finally,we identified the most suitable lighting conditions for detecting impact crater targets by analyzing the effect of different lighting conditions on the detection accuracy.展开更多
The wave-induced fluid flow(WIFF) occurring in the ubiquitous layered porous media(e.g.,shales)usually causes the appreciable seismic energy dissipation,which further leads to the frequency dependence of wave velocity...The wave-induced fluid flow(WIFF) occurring in the ubiquitous layered porous media(e.g.,shales)usually causes the appreciable seismic energy dissipation,which further leads to the frequency dependence of wave velocity(i.e.,dispersion) and elastic anisotropy parameters.The relevant knowledge is of great importance for geofluid discrimination and hydrocarbon exploration in the porous shale reservoirs.We derive the wave equations for a periodic layered transversely isotropy medium with a vertical axis of symmetry(VTI) concurrently with the annular cracks(PLPC medium) based on the periodic-layered model and anisotropic Biot's theory,which simultaneously incorporate the effects of microscopic squirt fluid flow,mesoscopic interlayer fluid flow and macroscopic global fluid flow.Notably,the microscopic squirt shorten fluid flow emerges between the annular-shaped cracks and stiff pores,which generates one attenuation peak.Specifically,we first establish the stress-strain relationship and pore fluid pressure in a PLPC medium,and then use them to derive the wave equations by means of the Newton's second law.The plane analysis is implemented on the wave equations to yield the analytic solutions for phase velocities and attenuation factors of four waves,namely,fast P-wave,slow P-wave,SV-wave and SH-wave,and the anisotropy parameters can be therefore computed.Simulation results show that P-wave velocity have three attenuation peaks throughout the full frequency band,which respectively correspond to the influences of interlayer flow,the squirt flow and the Biot flow.Through the results of seismic velocity dispersion and attenuation at different incident angles,we find that the WIFF mechanism also has a significant impact on the dispersion characteristics of elastic anisotropy parameters within the low-mid frequency band.Moreover,it is shown that several poroelastic parameters,such as layer thickness ratio,crack aspect ratio and crack density have notable influence on seismic dispersion and attenuation.We compare the proposed modeled velocities with that given by the existing theory to confirm its validity.Our formulas and result can provide a better understanding of wave propagation in PLPC medium by considering the unified impacts of micro-,meso-and macro-scale WIFF mechanisms,which potentially lays a theoretical basis of rock physics for seismic interpretation.展开更多
Soil cement bentonite(SCB)is a common material for constructing vertical cutoff walls to prevent groundwater migration at contaminated industrial sites.However,site contaminants can degrade the durability of the cutof...Soil cement bentonite(SCB)is a common material for constructing vertical cutoff walls to prevent groundwater migration at contaminated industrial sites.However,site contaminants can degrade the durability of the cutoff wall.To enhance its performance,this study developed a silica fume-SCB(SSCB).The macroscopic and microscopic properties of SSCB were assessed by unconfined compressive strength test,variable head permeability test,X-ray diffraction(XRD),scanning electron microscopy(SEM)and nuclear magnetic resonance(NMR)spectroscopy.The correlation between its multi-scale properties was analyzed based on pore characteristics.The results indicate that increasing the silica fume substitution ratio improved SSCB strength,especially in the middle and late curing stages.Moreover,increasing the substitution ratio decreased SSCB permeability coefficient,with a more pronounced effect in earlier curing stages.Silica fume addition also refined SSCB pore structure and reduced its porosity.The fractal dimension was used to quantify SSCB pore structure complexity.Increasing silica fume content reduced small pore fractal dimension in SSCB.Concurrently,SSCB strength increased and SSCB permeability coefficient decreased.The findings of this research will demonstrate the great potential of SSCB backfill for practical applications.展开更多
Flexible microporous metal rubber(FMP-MR)is widely used in national defense applications,yet its mechanical behavior under high-speed impact conditions remains insufficiently explored.In this study,dynamic and static ...Flexible microporous metal rubber(FMP-MR)is widely used in national defense applications,yet its mechanical behavior under high-speed impact conditions remains insufficiently explored.In this study,dynamic and static experiments were conducted to systematically investigate the mechanical response of metal-wrapped microporous materials under impact loading that spanned 10~6 orders of magnitude.By combining a high-precision numerical model with a spatial contact point search algorithm,the spatio–temporal contact characteristics of the complex network structure in FMP-MR were systematically analyzed.Furthermore,the mapping mechanism from turn topology and mesoscopic friction behavior to macroscopic mechanical properties was comprehensively explored.The results showed that compared with quasi-static loading,FMP-MR under high-speed impact exhibited higher energy absorption efficiency due to high-strain-rate inertia effect.Therefore,the peak stress increased by 141%,and the maximum energy dissipation increased by 300%.Consequently,the theory of dynamic friction locking effect was innovatively proposed.The theory explains that the close synergistic effect of sliding friction and plastic dissipation promoted by the stable interturn-locked embedded structure is the essential reason for the excellent dynamic mechanical properties of FMP-MR under dynamic loading conditions.Briefly,based on the in-depth investigation of the mechanical response and energy dissipation mechanism of FMP-MR under impact loads,this study provides a solid theoretical basis for further expanding the application range of FMP-MR and optimizing its performance.展开更多
Because of the challenge of compounding lightweight,high-strength Ti/Al alloys due to their considerable disparity in properties,Al 6063 as intermediate layer was proposed to fabricate TC4/Al 6063/Al 7075 three-layer ...Because of the challenge of compounding lightweight,high-strength Ti/Al alloys due to their considerable disparity in properties,Al 6063 as intermediate layer was proposed to fabricate TC4/Al 6063/Al 7075 three-layer composite plate by explosive welding.The microscopic properties of each bonding interface were elucidated through field emission scanning electron microscope and electron backscattered diffraction(EBSD).A methodology combining finite element method-smoothed particle hydrodynamics(FEM-SPH)and molecular dynamics(MD)was proposed for the analysis of the forming and evolution characteristics of explosive welding interfaces at multi-scale.The results demonstrate that the bonding interface morphologies of TC4/Al 6063 and Al 6063/Al 7075 exhibit a flat and wavy configuration,without discernible defects or cracks.The phenomenon of grain refinement is observed in the vicinity of the two bonding interfaces.Furthermore,the degree of plastic deformation of TC4 and Al 7075 is more pronounced than that of Al 6063 in the intermediate layer.The interface morphology characteristics obtained by FEM-SPH simulation exhibit a high degree of similarity to the experimental results.MD simulations reveal that the diffusion of interfacial elements predominantly occurs during the unloading phase,and the simulated thickness of interfacial diffusion aligns well with experimental outcomes.The introduction of intermediate layer in the explosive welding process can effectively produce high-quality titanium/aluminum alloy composite plates.Furthermore,this approach offers a multi-scale simulation strategy for the study of explosive welding bonding interfaces.展开更多
The trade-offs and synergies of forest ecosystem service are important research topics for several disciplines.The multi-scale analysis of service trade-offs and synergies assists in the implementation of more effecti...The trade-offs and synergies of forest ecosystem service are important research topics for several disciplines.The multi-scale analysis of service trade-offs and synergies assists in the implementation of more effective forest resource management.Based on multi-source data including forest distribution,topography,NDVI,meteorology and soil conditions,key forest ecosystem services,including total forest volume,carbon storage,water yield,soil retention and habitat quality were mapped and evaluated for the Funiu Mountain Region through integrated deployment of the CASA model,the InVEST3.2 model and the ArcGIS10.2 software.The characteristics of trade-offs and synergies among different ecosystem services were then mapped and considered across multiple spatial scales(i.e.,by region,north and south slopes,vertical belt)using the spatial overlay analysis method.The main results are as follows:(1)Mean forest volume is 49.26 m^(3)/ha,carbon density is 156.94 t/ha,water yield depth is 494.46 mm,the unit amount of soil retention is 955.4 t/ha,and the habitat quality index is 0.79.(2)The area of forests with good synergy is 28.79%,and the area of forests with poor synergy is 10.15%,while about 61.06%of forests show severe trade-offs and weak trade-offs.The overall benefits of forest ecosystem services in the study area are still low.In the future,bad synergy and severe trade-off areas should be the focus of forest resource management and efficiency regulation.(3)Synergy between ecosystem services is better for forest on south slope than that on north slope.Deciduous broad-leaved forest belt at moderate elevations on south slope in the mountains(SIII)has the highest synergies,while that at low elevations on north slope(NI)exhibits the lowest synergy levels.展开更多
Improving the volumetric energy density of supercapacitors is essential for practical applications,which highly relies on the dense storage of ions in carbon-based electrodes.The functional units of carbon-based elect...Improving the volumetric energy density of supercapacitors is essential for practical applications,which highly relies on the dense storage of ions in carbon-based electrodes.The functional units of carbon-based electrode exhibit multi-scale structural characteristics including macroscopic electrode morphologies,mesoscopic microcrystals and pores,and microscopic defects and dopants in the carbon basal plane.Therefore,the ordered combination of multi-scale structures of carbon electrode is crucial for achieving dense energy storage and high volumetric performance by leveraging the functions of various scale structu re.Considering that previous reviews have focused more on the discussion of specific scale structu re of carbon electrodes,this review takes a multi-scale perspective in which recent progresses regarding the structureperformance relationship,underlying mechanism and directional design of carbon-based multi-scale structures including carbon morphology,pore structure,carbon basal plane micro-environment and electrode technology on dense energy storage and volumetric property of supercapacitors are systematically discussed.We analyzed in detail the effects of the morphology,pore,and micro-environment of carbon electrode materials on ion dense storage,summarized the specific effects of different scale structures on volumetric property and recent research progress,and proposed the mutual influence and trade-off relationship between various scale structures.In addition,the challenges and outlooks for improving the dense storage and volumetric performance of carbon-based supercapacitors are analyzed,which can provide feasible technical reference and guidance for the design and manufacture of dense carbon-based electrode materials.展开更多
Convolutional neural networks(CNNs)-based medical image segmentation technologies have been widely used in medical image segmentation because of their strong representation and generalization abilities.However,due to ...Convolutional neural networks(CNNs)-based medical image segmentation technologies have been widely used in medical image segmentation because of their strong representation and generalization abilities.However,due to the inability to effectively capture global information from images,CNNs can easily lead to loss of contours and textures in segmentation results.Notice that the transformer model can effectively capture the properties of long-range dependencies in the image,and furthermore,combining the CNN and the transformer can effectively extract local details and global contextual features of the image.Motivated by this,we propose a multi-branch and multi-scale attention network(M2ANet)for medical image segmentation,whose architecture consists of three components.Specifically,in the first component,we construct an adaptive multi-branch patch module for parallel extraction of image features to reduce information loss caused by downsampling.In the second component,we apply residual block to the well-known convolutional block attention module to enhance the network’s ability to recognize important features of images and alleviate the phenomenon of gradient vanishing.In the third component,we design a multi-scale feature fusion module,in which we adopt adaptive average pooling and position encoding to enhance contextual features,and then multi-head attention is introduced to further enrich feature representation.Finally,we validate the effectiveness and feasibility of the proposed M2ANet method through comparative experiments on four benchmark medical image segmentation datasets,particularly in the context of preserving contours and textures.展开更多
Prediction of production decline and evaluation of the adsorbed/free gas ratio are critical for determining the lifespan and production status of shale gas wells.Traditional production prediction methods have some sho...Prediction of production decline and evaluation of the adsorbed/free gas ratio are critical for determining the lifespan and production status of shale gas wells.Traditional production prediction methods have some shortcomings because of the low permeability and tightness of shale,complex gas flow behavior of multi-scale gas transport regions and multiple gas transport mechanism superpositions,and complex and variable production regimes of shale gas wells.Recent research has demonstrated the existence of a multi-stage isotope fractionation phenomenon during shale gas production,with the fractionation characteristics of each stage associated with the pore structure,gas in place(GIP),adsorption/desorption,and gas production process.This study presents a new approach for estimating shale gas well production and evaluating the adsorbed/free gas ratio throughout production using isotope fractionation techniques.A reservoir-scale carbon isotope fractionation(CIF)model applicable to the production process of shale gas wells was developed for the first time in this research.In contrast to the traditional model,this model improves production prediction accuracy by simultaneously fitting the gas production rate and δ^(13)C_(1) data and provides a new evaluation method of the adsorbed/free gas ratio during shale gas production.The results indicate that the diffusion and adsorption/desorption properties of rock,bottom-hole flowing pressure(BHP)of gas well,and multi-scale gas transport regions of the reservoir all affect isotope fractionation,with the diffusion and adsorption/desorption parameters of rock having the greatest effect on isotope fractionation being D∗/D,PL,VL,α,and others in that order.We effectively tested the universality of the four-stage isotope fractionation feature and revealed a unique isotope fractionation mechanism caused by the superimposed coupling of multi-scale gas transport regions during shale gas well production.Finally,we applied the established CIF model to a shale gas well in the Sichuan Basin,China,and calculated the estimated ultimate recovery(EUR)of the well to be 3.33×10^(8) m^(3);the adsorbed gas ratio during shale gas production was 1.65%,10.03%,and 23.44%in the first,fifth,and tenth years,respectively.The findings are significant for understanding the isotope fractionation mechanism during natural gas transport in complex systems and for formulating and optimizing unconventional natural gas development strategies.展开更多
In recent years,gait-based emotion recognition has been widely applied in the field of computer vision.However,existing gait emotion recognition methods typically rely on complete human skeleton data,and their accurac...In recent years,gait-based emotion recognition has been widely applied in the field of computer vision.However,existing gait emotion recognition methods typically rely on complete human skeleton data,and their accuracy significantly declines when the data is occluded.To enhance the accuracy of gait emotion recognition under occlusion,this paper proposes a Multi-scale Suppression Graph ConvolutionalNetwork(MS-GCN).TheMS-GCN consists of three main components:Joint Interpolation Module(JI Moudle),Multi-scale Temporal Convolution Network(MS-TCN),and Suppression Graph Convolutional Network(SGCN).The JI Module completes the spatially occluded skeletal joints using the(K-Nearest Neighbors)KNN interpolation method.The MS-TCN employs convolutional kernels of various sizes to comprehensively capture the emotional information embedded in the gait,compensating for the temporal occlusion of gait information.The SGCN extracts more non-prominent human gait features by suppressing the extraction of key body part features,thereby reducing the negative impact of occlusion on emotion recognition results.The proposed method is evaluated on two comprehensive datasets:Emotion-Gait,containing 4227 real gaits from sources like BML,ICT-Pollick,and ELMD,and 1000 synthetic gaits generated using STEP-Gen technology,and ELMB,consisting of 3924 gaits,with 1835 labeled with emotions such as“Happy,”“Sad,”“Angry,”and“Neutral.”On the standard datasets Emotion-Gait and ELMB,the proposed method achieved accuracies of 0.900 and 0.896,respectively,attaining performance comparable to other state-ofthe-artmethods.Furthermore,on occlusion datasets,the proposedmethod significantly mitigates the performance degradation caused by occlusion compared to other methods,the accuracy is significantly higher than that of other methods.展开更多
Coral reef limestone(CRL)constitutes a distinctive marine carbonate formation with complex mechanical properties.This study investigates the multiscale damage and fracture mechanisms of CRL through integrated experime...Coral reef limestone(CRL)constitutes a distinctive marine carbonate formation with complex mechanical properties.This study investigates the multiscale damage and fracture mechanisms of CRL through integrated experimental testing,digital core technology,and theoretical modelling.Two CRL types with contrasting mesostructures were characterized across three scales.Macroscopically,CRL-I and CRL-II exhibited mean compressive strengths of 8.46 and 5.17 MPa,respectively.Mesoscopically,CRL-I featured small-scale highly interconnected pores,whilst CRL-II developed larger stratified pores with diminished connectivity.Microscopically,both CRL matrices demonstrated remarkable similarity in mineral composition and mechanical properties.A novel voxel average-based digital core scaling methodology was developed to facilitate numerical simulation of cross-scale damage processes,revealing network-progressive failure in CRL-I versus directional-brittle failure in CRL-II.Furthermore,a damage statistical constitutive model based on digital core technology and mesoscopic homogenisation theory established quantitative relationships between microelement strength distribution and macroscopic mechanical behavior.These findings illuminate the fundamental mechanisms through which mesoscopic structure governs the macroscopic mechanical properties of CRL.展开更多
We propose a multiscale approach to study the influence of carbon nanotubes’agglomeration on the stability of hybrid nanocomposite plates.The hybrid nanocomposite consists of both macro-and nano-scale reinforcing fib...We propose a multiscale approach to study the influence of carbon nanotubes’agglomeration on the stability of hybrid nanocomposite plates.The hybrid nanocomposite consists of both macro-and nano-scale reinforcing fibers dispersed in a polymer matrix.The equivalent material properties are calculated by coupling the Eshelby-Mori-Tanaka model with the rule of mixture accounting for effects of CNTs inside the generated clusters.Furthermore,an energy based approach is implemented to obtain the governing equations of the problem utilizing a refined higher-order plate theorem.Subsequently,the derived equations are solved by Galerkin’s analytical method to predict the critical buckling load.The influence of various boundary conditions is studied as well.After validation,a set of numerical examples are presented to explain how each variant can affect the plate’s natural frequency.展开更多
The fusion of infrared and visible images should emphasize the salient targets in the infrared image while preserving the textural details of the visible images.To meet these requirements,an autoencoder-based method f...The fusion of infrared and visible images should emphasize the salient targets in the infrared image while preserving the textural details of the visible images.To meet these requirements,an autoencoder-based method for infrared and visible image fusion is proposed.The encoder designed according to the optimization objective consists of a base encoder and a detail encoder,which is used to extract low-frequency and high-frequency information from the image.This extraction may lead to some information not being captured,so a compensation encoder is proposed to supplement the missing information.Multi-scale decomposition is also employed to extract image features more comprehensively.The decoder combines low-frequency,high-frequency and supplementary information to obtain multi-scale features.Subsequently,the attention strategy and fusion module are introduced to perform multi-scale fusion for image reconstruction.Experimental results on three datasets show that the fused images generated by this network effectively retain salient targets while being more consistent with human visual perception.展开更多
A nonlinear multi-scale interaction(NMI)model was proposed and developed by the first author for nearly 30 years to represent the evolution of atmospheric blocking.In this review paper,we first review the creation and...A nonlinear multi-scale interaction(NMI)model was proposed and developed by the first author for nearly 30 years to represent the evolution of atmospheric blocking.In this review paper,we first review the creation and development of the NMI model and then emphasize that the NMI model represents a new tool for identifying the basic physics of how climate change influences mid-to-high latitude weather extremes.The building of the NMI model took place over three main periods.In the 1990s,a nonlinear Schr?dinger(NLS)equation model was presented to describe atmospheric blocking as a wave packet;however,it could not depict the lifetime(10-20 days)of atmospheric blocking.In the 2000s,we proposed an NMI model of atmospheric blocking in a uniform basic flow by making a scale-separation assumption and deriving an eddyforced NLS equation.This model succeeded in describing the life cycle of atmospheric blocking.In the 2020s,the NMI model was extended to include the impact of a changing climate mainly by altering the basic zonal winds and the magnitude of the meridional background potential vorticity gradient(PVy).Model results show that when PVy is smaller,blocking has a weaker dispersion and a stronger nonlinearity,so blocking can be more persistent and have a larger zonal scale and weaker eastward movement,thus favoring stronger weather extremes.However,when PVy is much smaller and below a critical threshold under much stronger winter Arctic warming of global warming,atmospheric blocking becomes locally less persistent and shows a much stronger westward movement,which acts to inhibit local cold extremes.Such a case does not happen in summer under global warming because PVy fails to fall below the critical threshold.Thus,our theory indicates that global warming can render summer-blocking anticyclones and mid-to-high latitude heatwaves more persistent,intense,and widespread.展开更多
The application of ecosystem services(ES)theories in land consolidation is a confusing issue that has long plagued scholars and government officials.As the upgraded version of traditional land consolidation,comprehens...The application of ecosystem services(ES)theories in land consolidation is a confusing issue that has long plagued scholars and government officials.As the upgraded version of traditional land consolidation,comprehensive land consolidation(CLC)emphasizes ecological benefits,but it does not achieve the expected effect during the pilot phase.This study first proposed a theoretical analysis framework based on ES knowledge to answer the three key questions of why,where,and how to implement CLC better.Taking mountainous counties as the study area,we found that ES trade-offs/synergies,bundles,and drivers were significantly affected by scale effects.ES knowledge can play a crucial role in designing multi-scale CLC strategies regarding the objective,zoning,intensity,and mode.Specifically,mitigating the significant trade-offs between recreational opportunities,food production,and other ES is the top priority of CLC.Land consolidation zoning based on the ES bundles analysis is more rational and can provide the scientific premise for designing locally adapted CLC measures.Land consolidation can be classified into high-intensity direct intervention and low-intensity indirect intervention modes,based on the major drivers of ES.These findings help narrow the gap between ES and CLC practices.展开更多
Mental health problems and potential psychological crises affect the healthy growth and learning performance of college students.Effective and suitable prevention of psychological crises among college students is a co...Mental health problems and potential psychological crises affect the healthy growth and learning performance of college students.Effective and suitable prevention of psychological crises among college students is a continuous challenge university managers face.To explore a method of preventing psychological crises among college students,we measured 38661 students by using SCL-90(symptom check list-90)and screened out 5790 students with positive results.Then,we measured 33188 students by using PHQ-9(patient health questionnaire-9)and screened out 603 students with suicidal ideation or behavior;we interviewed 392 students by using GAQ(growth adversity questionnaire).The number of students who had positive results at both phases is 155.As a result,we obtained a data set(N=76)by integrating the students who tested positive on the PHQ-9(i.e.total score≥20)with those who completed the PHQ-9 and GAQ.In addition,we obtained a data set(N=50)by excluding the cases in which the GAQ score is 0.With regard to QCA(qualitative comparative analysis)results,the data set(N=76)exhibits 5 constellations of solutions with a coverage rate greater than 0.7,and the first eight indicators of the PHQ-9 constitute the explanatory variables in the combined solutions.About the data set(N=50),the combined solutions are extremely complicated and the explanatory variables encompass indicators from both the PHQ-9 and GAQ.All these mean that the multi-scale could more comprehensively reflect mental health states of college students,thus enhance the accuracy and effectiveness of the corresponding hierarchical intervention,and finally provide support for preventing psychological crises in universities.展开更多
基金supported by the National Basic Research Program of China(973 Program)(No.2013CB228002)
文摘A unified mathematical model is established to simulate the nonlinear unsteady percolation of shale gas with the consideration of the nonlinear multi-scale effects such as slippage, diffusion, and desorption. The continuous inhomogeneous models of equivalent porosity and permeability are proposed for the whole shale gas reservoir includ- ing the hydraulic fracture, the micro-fracture, and the matrix regions. The corresponding semi-analytical method is developed by transforming the nonlinear partial differential governing equation into the integral equation and the numerical discretization. The nonlinear multi-scale effects of slippage and diffusion and the pressure dependent effect of desorption on the shale gas production are investigated.
基金funded by the National Natural Science Foundation of China,grant numbers 52374156 and 62476005。
文摘Images taken in dim environments frequently exhibit issues like insufficient brightness,noise,color shifts,and loss of detail.These problems pose significant challenges to dark image enhancement tasks.Current approaches,while effective in global illumination modeling,often struggle to simultaneously suppress noise and preserve structural details,especially under heterogeneous lighting.Furthermore,misalignment between luminance and color channels introduces additional challenges to accurate enhancement.In response to the aforementioned difficulties,we introduce a single-stage framework,M2ATNet,using the multi-scale multi-attention and Transformer architecture.First,to address the problems of texture blurring and residual noise,we design a multi-scale multi-attention denoising module(MMAD),which is applied separately to the luminance and color channels to enhance the structural and texture modeling capabilities.Secondly,to solve the non-alignment problem of the luminance and color channels,we introduce the multi-channel feature fusion Transformer(CFFT)module,which effectively recovers the dark details and corrects the color shifts through cross-channel alignment and deep feature interaction.To guide the model to learn more stably and efficiently,we also fuse multiple types of loss functions to form a hybrid loss term.We extensively evaluate the proposed method on various standard datasets,including LOL-v1,LOL-v2,DICM,LIME,and NPE.Evaluation in terms of numerical metrics and visual quality demonstrate that M2ATNet consistently outperforms existing advanced approaches.Ablation studies further confirm the critical roles played by the MMAD and CFFT modules to detail preservation and visual fidelity under challenging illumination-deficient environments.
基金supported by the Henan Province Key R&D Project under Grant 241111210400the Henan Provincial Science and Technology Research Project under Grants 252102211047,252102211062,252102211055 and 232102210069+2 种基金the Jiangsu Provincial Scheme Double Initiative Plan JSS-CBS20230474,the XJTLU RDF-21-02-008the Science and Technology Innovation Project of Zhengzhou University of Light Industry under Grant 23XNKJTD0205the Higher Education Teaching Reform Research and Practice Project of Henan Province under Grant 2024SJGLX0126。
文摘Accurate and efficient detection of building changes in remote sensing imagery is crucial for urban planning,disaster emergency response,and resource management.However,existing methods face challenges such as spectral similarity between buildings and backgrounds,sensor variations,and insufficient computational efficiency.To address these challenges,this paper proposes a novel Multi-scale Efficient Wavelet-based Change Detection Network(MewCDNet),which integrates the advantages of Convolutional Neural Networks and Transformers,balances computational costs,and achieves high-performance building change detection.The network employs EfficientNet-B4 as the backbone for hierarchical feature extraction,integrates multi-level feature maps through a multi-scale fusion strategy,and incorporates two key modules:Cross-temporal Difference Detection(CTDD)and Cross-scale Wavelet Refinement(CSWR).CTDD adopts a dual-branch architecture that combines pixel-wise differencing with semanticaware Euclidean distance weighting to enhance the distinction between true changes and background noise.CSWR integrates Haar-based Discrete Wavelet Transform with multi-head cross-attention mechanisms,enabling cross-scale feature fusion while significantly improving edge localization and suppressing spurious changes.Extensive experiments on four benchmark datasets demonstrate MewCDNet’s superiority over comparison methods:achieving F1 scores of 91.54%on LEVIR,93.70%on WHUCD,and 64.96%on S2Looking for building change detection.Furthermore,MewCDNet exhibits optimal performance on the multi-class⋅SYSU dataset(F1:82.71%),highlighting its exceptional generalization capability.
文摘With the rapid expansion of drone applications,accurate detection of objects in aerial imagery has become crucial for intelligent transportation,urban management,and emergency rescue missions.However,existing methods face numerous challenges in practical deployment,including scale variation handling,feature degradation,and complex backgrounds.To address these issues,we propose Edge-enhanced and Detail-Capturing You Only Look Once(EHDC-YOLO),a novel framework for object detection in Unmanned Aerial Vehicle(UAV)imagery.Based on the You Only Look Once version 11 nano(YOLOv11n)baseline,EHDC-YOLO systematically introduces several architectural enhancements:(1)a Multi-Scale Edge Enhancement(MSEE)module that leverages multi-scale pooling and edge information to enhance boundary feature extraction;(2)an Enhanced Feature Pyramid Network(EFPN)that integrates P2-level features with Cross Stage Partial(CSP)structures and OmniKernel convolutions for better fine-grained representation;and(3)Dynamic Head(DyHead)with multi-dimensional attention mechanisms for enhanced cross-scale modeling and perspective adaptability.Comprehensive experiments on the Vision meets Drones for Detection(VisDrone-DET)2019 dataset demonstrate that EHDC-YOLO achieves significant improvements,increasing mean Average Precision(mAP)@0.5 from 33.2%to 46.1%(an absolute improvement of 12.9 percentage points)and mAP@0.5:0.95 from 19.5%to 28.0%(an absolute improvement of 8.5 percentage points)compared with the YOLOv11n baseline,while maintaining a reasonable parameter count(2.81 M vs the baseline’s 2.58 M).Further ablation studies confirm the effectiveness of each proposed component,while visualization results highlight EHDC-YOLO’s superior performance in detecting objects and handling occlusions in complex drone scenarios.
基金the National Key Research and Development Program of China(Grant No.2022YFF0711400)which provided valuable financial support and resources for my research and made it possible for me to deeply explore the unknown mysteries in the field of lunar geologythe National Space Science Data Center Youth Open Project(Grant No.NSSDC2302001),which has not only facilitated the smooth progress of my research,but has also built a platform for me to communicate and cooperate with experts in the field.
文摘Impact craters are important for understanding the evolution of lunar geologic and surface erosion rates,among other functions.However,the morphological characteristics of these micro impact craters are not obvious and they are numerous,resulting in low detection accuracy by deep learning models.Therefore,we proposed a new multi-scale fusion crater detection algorithm(MSF-CDA)based on the YOLO11 to improve the accuracy of lunar impact crater detection,especially for small craters with a diameter of<1 km.Using the images taken by the LROC(Lunar Reconnaissance Orbiter Camera)at the Chang’e-4(CE-4)landing area,we constructed three separate datasets for craters with diameters of 0-70 m,70-140 m,and>140 m.We then trained three submodels separately with these three datasets.Additionally,we designed a slicing-amplifying-slicing strategy to enhance the ability to extract features from small craters.To handle redundant predictions,we proposed a new Non-Maximum Suppression with Area Filtering method to fuse the results in overlapping targets within the multi-scale submodels.Finally,our new MSF-CDA method achieved high detection performance,with the Precision,Recall,and F1 score having values of 0.991,0.987,and 0.989,respectively,perfectly addressing the problems induced by the lesser features and sample imbalance of small craters.Our MSF-CDA can provide strong data support for more in-depth study of the geological evolution of the lunar surface and finer geological age estimations.This strategy can also be used to detect other small objects with lesser features and sample imbalance problems.We detected approximately 500,000 impact craters in an area of approximately 214 km2 around the CE-4 landing area.By statistically analyzing the new data,we updated the distribution function of the number and diameter of impact craters.Finally,we identified the most suitable lighting conditions for detecting impact crater targets by analyzing the effect of different lighting conditions on the detection accuracy.
基金sponsorship of the National Natural Science Foundation of China (U24B2020,42174139)。
文摘The wave-induced fluid flow(WIFF) occurring in the ubiquitous layered porous media(e.g.,shales)usually causes the appreciable seismic energy dissipation,which further leads to the frequency dependence of wave velocity(i.e.,dispersion) and elastic anisotropy parameters.The relevant knowledge is of great importance for geofluid discrimination and hydrocarbon exploration in the porous shale reservoirs.We derive the wave equations for a periodic layered transversely isotropy medium with a vertical axis of symmetry(VTI) concurrently with the annular cracks(PLPC medium) based on the periodic-layered model and anisotropic Biot's theory,which simultaneously incorporate the effects of microscopic squirt fluid flow,mesoscopic interlayer fluid flow and macroscopic global fluid flow.Notably,the microscopic squirt shorten fluid flow emerges between the annular-shaped cracks and stiff pores,which generates one attenuation peak.Specifically,we first establish the stress-strain relationship and pore fluid pressure in a PLPC medium,and then use them to derive the wave equations by means of the Newton's second law.The plane analysis is implemented on the wave equations to yield the analytic solutions for phase velocities and attenuation factors of four waves,namely,fast P-wave,slow P-wave,SV-wave and SH-wave,and the anisotropy parameters can be therefore computed.Simulation results show that P-wave velocity have three attenuation peaks throughout the full frequency band,which respectively correspond to the influences of interlayer flow,the squirt flow and the Biot flow.Through the results of seismic velocity dispersion and attenuation at different incident angles,we find that the WIFF mechanism also has a significant impact on the dispersion characteristics of elastic anisotropy parameters within the low-mid frequency band.Moreover,it is shown that several poroelastic parameters,such as layer thickness ratio,crack aspect ratio and crack density have notable influence on seismic dispersion and attenuation.We compare the proposed modeled velocities with that given by the existing theory to confirm its validity.Our formulas and result can provide a better understanding of wave propagation in PLPC medium by considering the unified impacts of micro-,meso-and macro-scale WIFF mechanisms,which potentially lays a theoretical basis of rock physics for seismic interpretation.
基金Project(2019YFC1803601)supported by the National Key Research and Development Program of ChinaProject(52274182)supported by the National Natural Science Foundation of China+1 种基金Project(2021zzts0274)supported by the Fundamental Research Funds for the Central Universities,ChinaProject(CX20210295)supported by the Postgraduate Scientific Research Innovation Project of Hunan Province,China。
文摘Soil cement bentonite(SCB)is a common material for constructing vertical cutoff walls to prevent groundwater migration at contaminated industrial sites.However,site contaminants can degrade the durability of the cutoff wall.To enhance its performance,this study developed a silica fume-SCB(SSCB).The macroscopic and microscopic properties of SSCB were assessed by unconfined compressive strength test,variable head permeability test,X-ray diffraction(XRD),scanning electron microscopy(SEM)and nuclear magnetic resonance(NMR)spectroscopy.The correlation between its multi-scale properties was analyzed based on pore characteristics.The results indicate that increasing the silica fume substitution ratio improved SSCB strength,especially in the middle and late curing stages.Moreover,increasing the substitution ratio decreased SSCB permeability coefficient,with a more pronounced effect in earlier curing stages.Silica fume addition also refined SSCB pore structure and reduced its porosity.The fractal dimension was used to quantify SSCB pore structure complexity.Increasing silica fume content reduced small pore fractal dimension in SSCB.Concurrently,SSCB strength increased and SSCB permeability coefficient decreased.The findings of this research will demonstrate the great potential of SSCB backfill for practical applications.
基金National Natural Science Foundation of China-NSAF(Grant No.U2330202)the National Natural Science Foundation of China(Grant Nos.52175162 and 51805086)+1 种基金Fujian Provincial Technological Innovation Key Research and Industrialization Projects(Grant Nos.2023XQ005 and 2024XQ010)The National Independent Innovation Demonstration Platform Project of Fujian Province(2024QZFX07)。
文摘Flexible microporous metal rubber(FMP-MR)is widely used in national defense applications,yet its mechanical behavior under high-speed impact conditions remains insufficiently explored.In this study,dynamic and static experiments were conducted to systematically investigate the mechanical response of metal-wrapped microporous materials under impact loading that spanned 10~6 orders of magnitude.By combining a high-precision numerical model with a spatial contact point search algorithm,the spatio–temporal contact characteristics of the complex network structure in FMP-MR were systematically analyzed.Furthermore,the mapping mechanism from turn topology and mesoscopic friction behavior to macroscopic mechanical properties was comprehensively explored.The results showed that compared with quasi-static loading,FMP-MR under high-speed impact exhibited higher energy absorption efficiency due to high-strain-rate inertia effect.Therefore,the peak stress increased by 141%,and the maximum energy dissipation increased by 300%.Consequently,the theory of dynamic friction locking effect was innovatively proposed.The theory explains that the close synergistic effect of sliding friction and plastic dissipation promoted by the stable interturn-locked embedded structure is the essential reason for the excellent dynamic mechanical properties of FMP-MR under dynamic loading conditions.Briefly,based on the in-depth investigation of the mechanical response and energy dissipation mechanism of FMP-MR under impact loads,this study provides a solid theoretical basis for further expanding the application range of FMP-MR and optimizing its performance.
基金Opening Foundation of Key Laboratory of Explosive Energy Utilization and Control,Anhui Province(BP20240104)Graduate Innovation Program of China University of Mining and Technology(2024WLJCRCZL049)Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX24_2701)。
文摘Because of the challenge of compounding lightweight,high-strength Ti/Al alloys due to their considerable disparity in properties,Al 6063 as intermediate layer was proposed to fabricate TC4/Al 6063/Al 7075 three-layer composite plate by explosive welding.The microscopic properties of each bonding interface were elucidated through field emission scanning electron microscope and electron backscattered diffraction(EBSD).A methodology combining finite element method-smoothed particle hydrodynamics(FEM-SPH)and molecular dynamics(MD)was proposed for the analysis of the forming and evolution characteristics of explosive welding interfaces at multi-scale.The results demonstrate that the bonding interface morphologies of TC4/Al 6063 and Al 6063/Al 7075 exhibit a flat and wavy configuration,without discernible defects or cracks.The phenomenon of grain refinement is observed in the vicinity of the two bonding interfaces.Furthermore,the degree of plastic deformation of TC4 and Al 7075 is more pronounced than that of Al 6063 in the intermediate layer.The interface morphology characteristics obtained by FEM-SPH simulation exhibit a high degree of similarity to the experimental results.MD simulations reveal that the diffusion of interfacial elements predominantly occurs during the unloading phase,and the simulated thickness of interfacial diffusion aligns well with experimental outcomes.The introduction of intermediate layer in the explosive welding process can effectively produce high-quality titanium/aluminum alloy composite plates.Furthermore,this approach offers a multi-scale simulation strategy for the study of explosive welding bonding interfaces.
基金National Natural Science Foundation of China,No.41671090National Basic Research Program(973 Program),No.2015CB452702。
文摘The trade-offs and synergies of forest ecosystem service are important research topics for several disciplines.The multi-scale analysis of service trade-offs and synergies assists in the implementation of more effective forest resource management.Based on multi-source data including forest distribution,topography,NDVI,meteorology and soil conditions,key forest ecosystem services,including total forest volume,carbon storage,water yield,soil retention and habitat quality were mapped and evaluated for the Funiu Mountain Region through integrated deployment of the CASA model,the InVEST3.2 model and the ArcGIS10.2 software.The characteristics of trade-offs and synergies among different ecosystem services were then mapped and considered across multiple spatial scales(i.e.,by region,north and south slopes,vertical belt)using the spatial overlay analysis method.The main results are as follows:(1)Mean forest volume is 49.26 m^(3)/ha,carbon density is 156.94 t/ha,water yield depth is 494.46 mm,the unit amount of soil retention is 955.4 t/ha,and the habitat quality index is 0.79.(2)The area of forests with good synergy is 28.79%,and the area of forests with poor synergy is 10.15%,while about 61.06%of forests show severe trade-offs and weak trade-offs.The overall benefits of forest ecosystem services in the study area are still low.In the future,bad synergy and severe trade-off areas should be the focus of forest resource management and efficiency regulation.(3)Synergy between ecosystem services is better for forest on south slope than that on north slope.Deciduous broad-leaved forest belt at moderate elevations on south slope in the mountains(SIII)has the highest synergies,while that at low elevations on north slope(NI)exhibits the lowest synergy levels.
基金funded by the Joint Fund for Regional Innovation and Development of National Natural Science Foundation of China(U21A20143)the National Science Fund for Excellent Young Scholars(52322607)the Excellent Youth Foundation of Heilongjiang Scientific Committee(YQ2022E028)。
文摘Improving the volumetric energy density of supercapacitors is essential for practical applications,which highly relies on the dense storage of ions in carbon-based electrodes.The functional units of carbon-based electrode exhibit multi-scale structural characteristics including macroscopic electrode morphologies,mesoscopic microcrystals and pores,and microscopic defects and dopants in the carbon basal plane.Therefore,the ordered combination of multi-scale structures of carbon electrode is crucial for achieving dense energy storage and high volumetric performance by leveraging the functions of various scale structu re.Considering that previous reviews have focused more on the discussion of specific scale structu re of carbon electrodes,this review takes a multi-scale perspective in which recent progresses regarding the structureperformance relationship,underlying mechanism and directional design of carbon-based multi-scale structures including carbon morphology,pore structure,carbon basal plane micro-environment and electrode technology on dense energy storage and volumetric property of supercapacitors are systematically discussed.We analyzed in detail the effects of the morphology,pore,and micro-environment of carbon electrode materials on ion dense storage,summarized the specific effects of different scale structures on volumetric property and recent research progress,and proposed the mutual influence and trade-off relationship between various scale structures.In addition,the challenges and outlooks for improving the dense storage and volumetric performance of carbon-based supercapacitors are analyzed,which can provide feasible technical reference and guidance for the design and manufacture of dense carbon-based electrode materials.
基金supported by the Natural Science Foundation of the Anhui Higher Education Institutions of China(Grant Nos.2023AH040149 and 2024AH051915)the Anhui Provincial Natural Science Foundation(Grant No.2208085MF168)+1 种基金the Science and Technology Innovation Tackle Plan Project of Maanshan(Grant No.2024RGZN001)the Scientific Research Fund Project of Anhui Medical University(Grant No.2023xkj122).
文摘Convolutional neural networks(CNNs)-based medical image segmentation technologies have been widely used in medical image segmentation because of their strong representation and generalization abilities.However,due to the inability to effectively capture global information from images,CNNs can easily lead to loss of contours and textures in segmentation results.Notice that the transformer model can effectively capture the properties of long-range dependencies in the image,and furthermore,combining the CNN and the transformer can effectively extract local details and global contextual features of the image.Motivated by this,we propose a multi-branch and multi-scale attention network(M2ANet)for medical image segmentation,whose architecture consists of three components.Specifically,in the first component,we construct an adaptive multi-branch patch module for parallel extraction of image features to reduce information loss caused by downsampling.In the second component,we apply residual block to the well-known convolutional block attention module to enhance the network’s ability to recognize important features of images and alleviate the phenomenon of gradient vanishing.In the third component,we design a multi-scale feature fusion module,in which we adopt adaptive average pooling and position encoding to enhance contextual features,and then multi-head attention is introduced to further enrich feature representation.Finally,we validate the effectiveness and feasibility of the proposed M2ANet method through comparative experiments on four benchmark medical image segmentation datasets,particularly in the context of preserving contours and textures.
基金supported by the Natural Science Foundation of China(Grant No.42302170)National Postdoctoral Innovative Talent Support Program(Grant No.BX20220062)+3 种基金CNPC Innovation Found(Grant No.2022DQ02-0104)National Science Foundation of Heilongjiang Province of China(Grant No.YQ2023D001)Postdoctoral Science Foundation of Heilongjiang Province of China(Grant No.LBH-Z22091)the Natural Science Foundation of Shandong Province(Grant No.ZR2022YQ30).
文摘Prediction of production decline and evaluation of the adsorbed/free gas ratio are critical for determining the lifespan and production status of shale gas wells.Traditional production prediction methods have some shortcomings because of the low permeability and tightness of shale,complex gas flow behavior of multi-scale gas transport regions and multiple gas transport mechanism superpositions,and complex and variable production regimes of shale gas wells.Recent research has demonstrated the existence of a multi-stage isotope fractionation phenomenon during shale gas production,with the fractionation characteristics of each stage associated with the pore structure,gas in place(GIP),adsorption/desorption,and gas production process.This study presents a new approach for estimating shale gas well production and evaluating the adsorbed/free gas ratio throughout production using isotope fractionation techniques.A reservoir-scale carbon isotope fractionation(CIF)model applicable to the production process of shale gas wells was developed for the first time in this research.In contrast to the traditional model,this model improves production prediction accuracy by simultaneously fitting the gas production rate and δ^(13)C_(1) data and provides a new evaluation method of the adsorbed/free gas ratio during shale gas production.The results indicate that the diffusion and adsorption/desorption properties of rock,bottom-hole flowing pressure(BHP)of gas well,and multi-scale gas transport regions of the reservoir all affect isotope fractionation,with the diffusion and adsorption/desorption parameters of rock having the greatest effect on isotope fractionation being D∗/D,PL,VL,α,and others in that order.We effectively tested the universality of the four-stage isotope fractionation feature and revealed a unique isotope fractionation mechanism caused by the superimposed coupling of multi-scale gas transport regions during shale gas well production.Finally,we applied the established CIF model to a shale gas well in the Sichuan Basin,China,and calculated the estimated ultimate recovery(EUR)of the well to be 3.33×10^(8) m^(3);the adsorbed gas ratio during shale gas production was 1.65%,10.03%,and 23.44%in the first,fifth,and tenth years,respectively.The findings are significant for understanding the isotope fractionation mechanism during natural gas transport in complex systems and for formulating and optimizing unconventional natural gas development strategies.
基金supported by the National Natural Science Foundation of China(62272049,62236006,62172045)the Key Projects of Beijing Union University(ZKZD202301).
文摘In recent years,gait-based emotion recognition has been widely applied in the field of computer vision.However,existing gait emotion recognition methods typically rely on complete human skeleton data,and their accuracy significantly declines when the data is occluded.To enhance the accuracy of gait emotion recognition under occlusion,this paper proposes a Multi-scale Suppression Graph ConvolutionalNetwork(MS-GCN).TheMS-GCN consists of three main components:Joint Interpolation Module(JI Moudle),Multi-scale Temporal Convolution Network(MS-TCN),and Suppression Graph Convolutional Network(SGCN).The JI Module completes the spatially occluded skeletal joints using the(K-Nearest Neighbors)KNN interpolation method.The MS-TCN employs convolutional kernels of various sizes to comprehensively capture the emotional information embedded in the gait,compensating for the temporal occlusion of gait information.The SGCN extracts more non-prominent human gait features by suppressing the extraction of key body part features,thereby reducing the negative impact of occlusion on emotion recognition results.The proposed method is evaluated on two comprehensive datasets:Emotion-Gait,containing 4227 real gaits from sources like BML,ICT-Pollick,and ELMD,and 1000 synthetic gaits generated using STEP-Gen technology,and ELMB,consisting of 3924 gaits,with 1835 labeled with emotions such as“Happy,”“Sad,”“Angry,”and“Neutral.”On the standard datasets Emotion-Gait and ELMB,the proposed method achieved accuracies of 0.900 and 0.896,respectively,attaining performance comparable to other state-ofthe-artmethods.Furthermore,on occlusion datasets,the proposedmethod significantly mitigates the performance degradation caused by occlusion compared to other methods,the accuracy is significantly higher than that of other methods.
基金National Key Research and Development Program of China (No.2021YFC3100800)the National Natural Science Foundation of China (Nos.42407235 and 42271026)+1 种基金the Project of Sanya Yazhou Bay Science and Technology City (No.SCKJ-JYRC-2023-54)supported by the Hefei advanced computing center
文摘Coral reef limestone(CRL)constitutes a distinctive marine carbonate formation with complex mechanical properties.This study investigates the multiscale damage and fracture mechanisms of CRL through integrated experimental testing,digital core technology,and theoretical modelling.Two CRL types with contrasting mesostructures were characterized across three scales.Macroscopically,CRL-I and CRL-II exhibited mean compressive strengths of 8.46 and 5.17 MPa,respectively.Mesoscopically,CRL-I featured small-scale highly interconnected pores,whilst CRL-II developed larger stratified pores with diminished connectivity.Microscopically,both CRL matrices demonstrated remarkable similarity in mineral composition and mechanical properties.A novel voxel average-based digital core scaling methodology was developed to facilitate numerical simulation of cross-scale damage processes,revealing network-progressive failure in CRL-I versus directional-brittle failure in CRL-II.Furthermore,a damage statistical constitutive model based on digital core technology and mesoscopic homogenisation theory established quantitative relationships between microelement strength distribution and macroscopic mechanical behavior.These findings illuminate the fundamental mechanisms through which mesoscopic structure governs the macroscopic mechanical properties of CRL.
文摘We propose a multiscale approach to study the influence of carbon nanotubes’agglomeration on the stability of hybrid nanocomposite plates.The hybrid nanocomposite consists of both macro-and nano-scale reinforcing fibers dispersed in a polymer matrix.The equivalent material properties are calculated by coupling the Eshelby-Mori-Tanaka model with the rule of mixture accounting for effects of CNTs inside the generated clusters.Furthermore,an energy based approach is implemented to obtain the governing equations of the problem utilizing a refined higher-order plate theorem.Subsequently,the derived equations are solved by Galerkin’s analytical method to predict the critical buckling load.The influence of various boundary conditions is studied as well.After validation,a set of numerical examples are presented to explain how each variant can affect the plate’s natural frequency.
基金Supported by the Henan Province Key Research and Development Project(231111211300)the Central Government of Henan Province Guides Local Science and Technology Development Funds(Z20231811005)+2 种基金Henan Province Key Research and Development Project(231111110100)Henan Provincial Outstanding Foreign Scientist Studio(GZS2024006)Henan Provincial Joint Fund for Scientific and Technological Research and Development Plan(Application and Overcoming Technical Barriers)(242103810028)。
文摘The fusion of infrared and visible images should emphasize the salient targets in the infrared image while preserving the textural details of the visible images.To meet these requirements,an autoencoder-based method for infrared and visible image fusion is proposed.The encoder designed according to the optimization objective consists of a base encoder and a detail encoder,which is used to extract low-frequency and high-frequency information from the image.This extraction may lead to some information not being captured,so a compensation encoder is proposed to supplement the missing information.Multi-scale decomposition is also employed to extract image features more comprehensively.The decoder combines low-frequency,high-frequency and supplementary information to obtain multi-scale features.Subsequently,the attention strategy and fusion module are introduced to perform multi-scale fusion for image reconstruction.Experimental results on three datasets show that the fused images generated by this network effectively retain salient targets while being more consistent with human visual perception.
基金supported by the National Natural Science Foundation of China(Grant Nos.42150204 and 2288101)supported by the China National Postdoctoral Program for Innovative Talents(BX20230045)the China Postdoctoral Science Foundation(2023M730279)。
文摘A nonlinear multi-scale interaction(NMI)model was proposed and developed by the first author for nearly 30 years to represent the evolution of atmospheric blocking.In this review paper,we first review the creation and development of the NMI model and then emphasize that the NMI model represents a new tool for identifying the basic physics of how climate change influences mid-to-high latitude weather extremes.The building of the NMI model took place over three main periods.In the 1990s,a nonlinear Schr?dinger(NLS)equation model was presented to describe atmospheric blocking as a wave packet;however,it could not depict the lifetime(10-20 days)of atmospheric blocking.In the 2000s,we proposed an NMI model of atmospheric blocking in a uniform basic flow by making a scale-separation assumption and deriving an eddyforced NLS equation.This model succeeded in describing the life cycle of atmospheric blocking.In the 2020s,the NMI model was extended to include the impact of a changing climate mainly by altering the basic zonal winds and the magnitude of the meridional background potential vorticity gradient(PVy).Model results show that when PVy is smaller,blocking has a weaker dispersion and a stronger nonlinearity,so blocking can be more persistent and have a larger zonal scale and weaker eastward movement,thus favoring stronger weather extremes.However,when PVy is much smaller and below a critical threshold under much stronger winter Arctic warming of global warming,atmospheric blocking becomes locally less persistent and shows a much stronger westward movement,which acts to inhibit local cold extremes.Such a case does not happen in summer under global warming because PVy fails to fall below the critical threshold.Thus,our theory indicates that global warming can render summer-blocking anticyclones and mid-to-high latitude heatwaves more persistent,intense,and widespread.
基金National Natural Science Foundation of China,No.42171255,No.41971216。
文摘The application of ecosystem services(ES)theories in land consolidation is a confusing issue that has long plagued scholars and government officials.As the upgraded version of traditional land consolidation,comprehensive land consolidation(CLC)emphasizes ecological benefits,but it does not achieve the expected effect during the pilot phase.This study first proposed a theoretical analysis framework based on ES knowledge to answer the three key questions of why,where,and how to implement CLC better.Taking mountainous counties as the study area,we found that ES trade-offs/synergies,bundles,and drivers were significantly affected by scale effects.ES knowledge can play a crucial role in designing multi-scale CLC strategies regarding the objective,zoning,intensity,and mode.Specifically,mitigating the significant trade-offs between recreational opportunities,food production,and other ES is the top priority of CLC.Land consolidation zoning based on the ES bundles analysis is more rational and can provide the scientific premise for designing locally adapted CLC measures.Land consolidation can be classified into high-intensity direct intervention and low-intensity indirect intervention modes,based on the major drivers of ES.These findings help narrow the gap between ES and CLC practices.
文摘Mental health problems and potential psychological crises affect the healthy growth and learning performance of college students.Effective and suitable prevention of psychological crises among college students is a continuous challenge university managers face.To explore a method of preventing psychological crises among college students,we measured 38661 students by using SCL-90(symptom check list-90)and screened out 5790 students with positive results.Then,we measured 33188 students by using PHQ-9(patient health questionnaire-9)and screened out 603 students with suicidal ideation or behavior;we interviewed 392 students by using GAQ(growth adversity questionnaire).The number of students who had positive results at both phases is 155.As a result,we obtained a data set(N=76)by integrating the students who tested positive on the PHQ-9(i.e.total score≥20)with those who completed the PHQ-9 and GAQ.In addition,we obtained a data set(N=50)by excluding the cases in which the GAQ score is 0.With regard to QCA(qualitative comparative analysis)results,the data set(N=76)exhibits 5 constellations of solutions with a coverage rate greater than 0.7,and the first eight indicators of the PHQ-9 constitute the explanatory variables in the combined solutions.About the data set(N=50),the combined solutions are extremely complicated and the explanatory variables encompass indicators from both the PHQ-9 and GAQ.All these mean that the multi-scale could more comprehensively reflect mental health states of college students,thus enhance the accuracy and effectiveness of the corresponding hierarchical intervention,and finally provide support for preventing psychological crises in universities.
