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
The multi-scale modeling combined with the cohesive zone model(CZM)and the molecular dynamics(MD)method were preformed to simulate the crack propagation in NiTi shape memory alloys(SMAs).The metallographic microscope ...The multi-scale modeling combined with the cohesive zone model(CZM)and the molecular dynamics(MD)method were preformed to simulate the crack propagation in NiTi shape memory alloys(SMAs).The metallographic microscope and image processing technology were employed to achieve a quantitative grain size distribution of NiTi alloys so as to provide experimental data for molecular dynamics modeling at the atomic scale.Considering the size effect of molecular dynamics model on material properties,a reasonable modeling size was provided by taking into account three characteristic dimensions from the perspective of macro,meso,and micro scales according to the Buckinghamπtheorem.Then,the corresponding MD simulation on deformation and fracture behavior was investigated to derive a parameterized traction-separation(T-S)law,and then it was embedded into cohesive elements of finite element software.Thus,the crack propagation behavior in NiTi alloys was reproduced by the finite element method(FEM).The experimental results show that the predicted initiation fracture toughness is in good agreement with experimental data.In addition,it is found that the dynamics initiation fracture toughness increases with decreasing grain size and increasing loading velocity.展开更多
A multi-scale model is developed to link the continuum damage variable in macroscale to the number density of multiple pits and cracks in microscale for studying the corrosion fatigue of aluminum alloy from multi-scal...A multi-scale model is developed to link the continuum damage variable in macroscale to the number density of multiple pits and cracks in microscale for studying the corrosion fatigue of aluminum alloy from multi-scale viewpoint.The developed model is used to predict the coherent multi-scale corrosion fatigue process of aluminum alloy component in the 3.5 wt% NaC1water solution under constant stress amplitude at a nominal frequency of 5Hz, and the numerical prediction results are compared with the experimental results.It shows that the model is effective and can be used to study the corrosion fatigue mechanisms of alurninum alloy from both macro and microscale viewpoints.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
In the diagnosis of rotor crack based on wavelet analysis, it is a painful task to find out an adaptive mother wavelet as many of them can be chosen and the analytic results of different mother wavelets are yet not th...In the diagnosis of rotor crack based on wavelet analysis, it is a painful task to find out an adaptive mother wavelet as many of them can be chosen and the analytic results of different mother wavelets are yet not the same. For this limitation of wavelet analysis, a novel diagnostic approach of rotor crack based on multi-scale singular-spectrum analysis （MS-SSA） is proposed. Firstly, a Jeffcott model of a cracked rotor is developed and the forth-order Runge-Kutta method is used to solve the motion equations of this rotor to obtain its time response （signals）. Secondly, a comparatively simple approach of MS-SSA is presented and the empirical orthogonal functions of different orders in various scales are regarded as analyzing functions. At last, the signals of the cracked rotor and an uncracked rotor are analyzed using the proposed approach of MS-SSA, and the simulative results are compared. The results show that, the data-adaptive analyzing functions can capture many features of signals and the rotor crack can be identified and diagnosed effectively by comparing the analytic results of signals of the cracked rotor with those of the uncracked rotor using the analyzing functions of different orders.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
Large solidification ranges and coarse columnar grains in the additively manufacturing of Al-Mg-Si alloys are normally involved in hot cracks during solidification.In this work,we develop novel crack-free Al-Mg_(2) Si...Large solidification ranges and coarse columnar grains in the additively manufacturing of Al-Mg-Si alloys are normally involved in hot cracks during solidification.In this work,we develop novel crack-free Al-Mg_(2) Si alloys fabricated by laser powder-bed fusion(L-PBF).The results indicate that the eutectic Mg_(2) Si phase possesses a strong ability to reduce crack susceptibility.It can enhance the grain growth restriction factor in the initial stage of solidification and promote eutectic filling in the terminal stage of solidifica-tion.The crack-free L-PBFed Al-x Mg_(2) Si alloys(x=6 wt.%,9 wt.%,and 12 wt.%)exhibit the combination of low crack susceptibility index(CSI),superior ability for liquid filling,and grain refinement.Particularly,the L-PBFed Al-9Mg_(2) Si alloy shows improved mechanical properties(e.g.yield strength of 397 MPa and elongation of 7.3%).However,the cracks are more likely to occur in the region near the columnar grain boundaries of the L-PBFed Al-3Mg_(2) Si alloy with a large solidification range and low eutectic content for liquid filling.Correspondingly,the L-PBFed Al-3Mg_(2) Si alloy shows poor bearing capacity of mechanical properties.The precise tuning of Mg_(2) Si eutectic content can offer an innovative strategy for eliminating cracks in additively manufactured Al-Mg-Si alloy.展开更多
A ductility-dip-cracking(DDC)-concentrated zone(DCZ) in a width of about 3 mm was observed adjacent to the AISI 316 L/52 Mw fusion boundary(FB) in 52 Mw. The morphology, microstructure, mechanical and thermal properti...A ductility-dip-cracking(DDC)-concentrated zone(DCZ) in a width of about 3 mm was observed adjacent to the AISI 316 L/52 Mw fusion boundary(FB) in 52 Mw. The morphology, microstructure, mechanical and thermal properties and corrosion behavior in simulated primary water of DDC/DCZ were investigated by scanning electron microscopy(SEM), transmission electron microscopy(TEM), 3 D X-ray tomography(XRT), 3 D atom probe(3 DAP), slow strain rate tensile(SSRT) testing and thermal dilatometry. The results indicate that DDCs are random-shaped and disc-like cavities with corrugated structure of inner surface and are parallel in groups along straight high-angle boundaries of columnar grains, ranging from micrometers to millimeters in size. Large-size M_(23)C_6 carbides dominate on the grain boundaries rather than MC(M=Nb, Ti), and thus the bonding effect of carbides is absent for the straight grain boundaries.The impurity segregation of O is confirmed for the inner surfaces of DDC. The oxide film formed on the inner surface of DDC(about 50 nm) is approximately twice as thick as that on the matrix(about 25 nm)in simulated primary water. The yield strength, tensile strength and elongation to fracture of 52 MwDCZ(400 MPa, 450 MPa and 20 %, respectively) are lower than those of 52 Mw-MZ(460 MPa, 550 MPa and 28 %, respectively). The intrinsic high-restraint weld structure, the additional stress/strain caused by the thermal expansion difference between AISI 316 L and 52 Mw as well as the detrimental carbide precipitation and the resulting grain boundary structure all add up to cause the occurrence of DCZ in the dissimilar metal weld.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 this work,the influences of surface layer slurry at different temperatures(10℃,14℃,18℃,22℃)on wax patterns deformation,shrinkage,slurry coating characteristics,and the surface quality of the casting were invest...In this work,the influences of surface layer slurry at different temperatures(10℃,14℃,18℃,22℃)on wax patterns deformation,shrinkage,slurry coating characteristics,and the surface quality of the casting were investigated by using a single factor variable method.The surface morphologies of the shell molds produced by different temperatures of the surface(first)layer slurries were observed via electron microscopy.Furthermore,the microscopic composition of these shell molds was obtained by EDS,and the osmotic effect of the slurry on the wax patterns at different temperatures was also assessed by the PZ-200 Contact Angle detector.The forming reasons for the surface cracks and holes of thick and large ZTC4 titanium alloy by investment casting were analyzed.The experimental results show that the surface of the shell molds prepared by the surface layer slurry with a low temperature exhibits noticeable damage,which is mainly due to the poor coating performance and the serious expansion and contraction of wax pattern at low temperatures.The second layer shell material(SiO_(2),Al_(2)O_(3))immerses into the crack area of the surface layer,contacts and reacts with the molten titanium to form surface cracks and holes in the castings.With the increase of the temperature of surface layer slurry,the damage to the shell surface tends to weaken,and the composition of the shell molds'surface becomes more uniform with less impurities.The results show that the surface layer slurry at 22℃is evenly coated on the surface of the wax patterns with appropriate thickness,and there is no surface shell mold rupture caused by sliding slurry after sand leaching.The surface layer slurry temperature is consistent with the wax pattern temperature and the workshop temperature,so there is no damage of the surface layer shell caused by expansion and contraction.Therefore,the shell mold prepared by the surface layer slurry at this temperature has good integrity,isolating the contact between the low inert shell material and the titanium liquid effectively,and the ZTC4 titanium alloy cylinder casting prepared by this shell mold is smooth,without cracks and holes.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
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
Regular inspection of bridge cracks is crucial to bridge maintenance and repair.The traditional manual crack detection methods are timeconsuming,dangerous and subjective.At the same time,for the existing mainstream vi...Regular inspection of bridge cracks is crucial to bridge maintenance and repair.The traditional manual crack detection methods are timeconsuming,dangerous and subjective.At the same time,for the existing mainstream vision-based automatic crack detection algorithms,it is challenging to detect fine cracks and balance the detection accuracy and speed.Therefore,this paper proposes a new bridge crack segmentationmethod based on parallel attention mechanism and multi-scale features fusion on top of the DeeplabV3+network framework.First,the improved lightweight MobileNetv2 network and dilated separable convolution are integrated into the original DeeplabV3+network to improve the original backbone network Xception and atrous spatial pyramid pooling(ASPP)module,respectively,dramatically reducing the number of parameters in the network and accelerates the training and prediction speed of the model.Moreover,we introduce the parallel attention mechanism into the encoding and decoding stages.The attention to the crack regions can be enhanced from the aspects of both channel and spatial parts and significantly suppress the interference of various noises.Finally,we further improve the detection performance of the model for fine cracks by introducing a multi-scale features fusion module.Our research results are validated on the self-made dataset.The experiments show that our method is more accurate than other methods.Its intersection of union(IoU)and F1-score(F1)are increased to 77.96%and 87.57%,respectively.In addition,the number of parameters is only 4.10M,which is much smaller than the original network;also,the frames per second(FPS)is increased to 15 frames/s.The results prove that the proposed method fits well the requirements of rapid and accurate detection of bridge cracks and is superior to other methods.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
Water electrolyzers play a crucial role in green hydrogen production.However,their efficiency and scalability are often compromised by bubble dynamics across various scales,from nanoscale to macroscale components.This...Water electrolyzers play a crucial role in green hydrogen production.However,their efficiency and scalability are often compromised by bubble dynamics across various scales,from nanoscale to macroscale components.This review explores multi-scale modeling as a tool to visualize multi-phase flow and improve mass transport in water electrolyzers.At the nanoscale,molecular dynamics(MD)simulations reveal how electrode surface features and wettability influence nanobubble nucleation and stability.Moving to the mesoscale,models such as volume of fluid(VOF)and lattice Boltzmann method(LBM)shed light on bubble transport in porous transport layers(PTLs).These insights inform innovative designs,including gradient porosity and hydrophilic-hydrophobic patterning,aimed at minimizing gas saturation.At the macroscale,VOF simulations elucidate two-phase flow regimes within channels,showing how flow field geometry and wettability affect bubble discharging.Moreover,artificial intelligence(AI)-driven surrogate models expedite the optimization process,allowing for rapid exploration of structural parameters in channel-rib flow fields and porous flow field designs.By integrating these approaches,we can bridge theoretical insights with experimental validation,ultimately enhancing water electrolyzer performance,reducing costs,and advancing affordable,high-efficiency hydrogen production.展开更多
In order to realize the automatic recognition and classification of cracks with different depths,in this study,several deep convolutional neural networks including AlexNet,ResNet,and DenseNet were employed to identify...In order to realize the automatic recognition and classification of cracks with different depths,in this study,several deep convolutional neural networks including AlexNet,ResNet,and DenseNet were employed to identify and classify cracks at different depths and in various materials.An analysis process for the automatic classification of crack damage was presented.The image dataset used for model training was obtained from scanning experiments on aluminum and titanium alloy plates using an ultrasonic phased-array flaw detector.All models were trained and validated with the dataset;the proposed models were compared using classification precision and loss values.The results show that the automatic recognition and classification of crack depth can be realized by using the deep learning algorithm to analyze the ultrasonic phased array images,and the classification precision of DenseNet is the highest.The problem that ultrasonic damage identification relies on manual experience is solved.展开更多
Detecting abnormal cervical cells is crucial for early identification and timely treatment of cervical cancer.However,this task is challenging due to the morphological similarities between abnormal and normal cells an...Detecting abnormal cervical cells is crucial for early identification and timely treatment of cervical cancer.However,this task is challenging due to the morphological similarities between abnormal and normal cells and the significant variations in cell size.Pathologists often refer to surrounding cells to identify abnormalities.To emulate this slide examination behavior,this study proposes a Multi-Scale Feature Fusion Network(MSFF-Net)for detecting cervical abnormal cells.MSFF-Net employs a Cross-Scale Pooling Model(CSPM)to effectively capture diverse features and contextual information,ranging from local details to the overall structure.Additionally,a Multi-Scale Fusion Attention(MSFA)module is introduced to mitigate the impact of cell size variations by adaptively fusing local and global information at different scales.To handle the complex environment of cervical cell images,such as cell adhesion and overlapping,the Inner-CIoU loss function is utilized to more precisely measure the overlap between bounding boxes,thereby improving detection accuracy in such scenarios.Experimental results on the Comparison detector dataset demonstrate that MSFF-Net achieves a mean average precision(mAP)of 63.2%,outperforming state-of-the-art methods while maintaining a relatively small number of parameters(26.8 M).This study highlights the effectiveness of multi-scale feature fusion in enhancing the detection of cervical abnormal cells,contributing to more accurate and efficient cervical cancer screening.展开更多
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Funded by the National Natural Science Foundation of China Academy of Engineering Physics and Jointly Setup"NSAF"Joint Fund(No.U1430119)。
文摘The multi-scale modeling combined with the cohesive zone model(CZM)and the molecular dynamics(MD)method were preformed to simulate the crack propagation in NiTi shape memory alloys(SMAs).The metallographic microscope and image processing technology were employed to achieve a quantitative grain size distribution of NiTi alloys so as to provide experimental data for molecular dynamics modeling at the atomic scale.Considering the size effect of molecular dynamics model on material properties,a reasonable modeling size was provided by taking into account three characteristic dimensions from the perspective of macro,meso,and micro scales according to the Buckinghamπtheorem.Then,the corresponding MD simulation on deformation and fracture behavior was investigated to derive a parameterized traction-separation(T-S)law,and then it was embedded into cohesive elements of finite element software.Thus,the crack propagation behavior in NiTi alloys was reproduced by the finite element method(FEM).The experimental results show that the predicted initiation fracture toughness is in good agreement with experimental data.In addition,it is found that the dynamics initiation fracture toughness increases with decreasing grain size and increasing loading velocity.
基金Fundamental Research Funds for the Central Universities,Natural Science Foundation of Jiangsu Province (BK20170655,BK20170677),and the National Program on Key Research Project (2016YFC0701301-02).
文摘A multi-scale model is developed to link the continuum damage variable in macroscale to the number density of multiple pits and cracks in microscale for studying the corrosion fatigue of aluminum alloy from multi-scale viewpoint.The developed model is used to predict the coherent multi-scale corrosion fatigue process of aluminum alloy component in the 3.5 wt% NaC1water solution under constant stress amplitude at a nominal frequency of 5Hz, and the numerical prediction results are compared with the experimental results.It shows that the model is effective and can be used to study the corrosion fatigue mechanisms of alurninum alloy from both macro and microscale viewpoints.
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This project is supported by National Fundamental Research and Development Project Foundation of China(No.G1998020321).
文摘In the diagnosis of rotor crack based on wavelet analysis, it is a painful task to find out an adaptive mother wavelet as many of them can be chosen and the analytic results of different mother wavelets are yet not the same. For this limitation of wavelet analysis, a novel diagnostic approach of rotor crack based on multi-scale singular-spectrum analysis （MS-SSA） is proposed. Firstly, a Jeffcott model of a cracked rotor is developed and the forth-order Runge-Kutta method is used to solve the motion equations of this rotor to obtain its time response （signals）. Secondly, a comparatively simple approach of MS-SSA is presented and the empirical orthogonal functions of different orders in various scales are regarded as analyzing functions. At last, the signals of the cracked rotor and an uncracked rotor are analyzed using the proposed approach of MS-SSA, and the simulative results are compared. The results show that, the data-adaptive analyzing functions can capture many features of signals and the rotor crack can be identified and diagnosed effectively by comparing the analytic results of signals of the cracked rotor with those of the uncracked rotor using the analyzing functions of different orders.
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financially supported by the National Natural Science Foundation of China(Grant No.52071343)the Leading Innovation and Entrepreneurship Team of Zhejiang Province-Automotive Light Alloy Innovation Team(No.2022R01018).
文摘Large solidification ranges and coarse columnar grains in the additively manufacturing of Al-Mg-Si alloys are normally involved in hot cracks during solidification.In this work,we develop novel crack-free Al-Mg_(2) Si alloys fabricated by laser powder-bed fusion(L-PBF).The results indicate that the eutectic Mg_(2) Si phase possesses a strong ability to reduce crack susceptibility.It can enhance the grain growth restriction factor in the initial stage of solidification and promote eutectic filling in the terminal stage of solidifica-tion.The crack-free L-PBFed Al-x Mg_(2) Si alloys(x=6 wt.%,9 wt.%,and 12 wt.%)exhibit the combination of low crack susceptibility index(CSI),superior ability for liquid filling,and grain refinement.Particularly,the L-PBFed Al-9Mg_(2) Si alloy shows improved mechanical properties(e.g.yield strength of 397 MPa and elongation of 7.3%).However,the cracks are more likely to occur in the region near the columnar grain boundaries of the L-PBFed Al-3Mg_(2) Si alloy with a large solidification range and low eutectic content for liquid filling.Correspondingly,the L-PBFed Al-3Mg_(2) Si alloy shows poor bearing capacity of mechanical properties.The precise tuning of Mg_(2) Si eutectic content can offer an innovative strategy for eliminating cracks in additively manufactured Al-Mg-Si alloy.
基金financially supported by the National Key Research and Development Program of China (2016YFE0105200)Key Research Program of Frontier Sciences,Chinese Academy of Sciences (QYZDY-SSW-JSC012)
文摘A ductility-dip-cracking(DDC)-concentrated zone(DCZ) in a width of about 3 mm was observed adjacent to the AISI 316 L/52 Mw fusion boundary(FB) in 52 Mw. The morphology, microstructure, mechanical and thermal properties and corrosion behavior in simulated primary water of DDC/DCZ were investigated by scanning electron microscopy(SEM), transmission electron microscopy(TEM), 3 D X-ray tomography(XRT), 3 D atom probe(3 DAP), slow strain rate tensile(SSRT) testing and thermal dilatometry. The results indicate that DDCs are random-shaped and disc-like cavities with corrugated structure of inner surface and are parallel in groups along straight high-angle boundaries of columnar grains, ranging from micrometers to millimeters in size. Large-size M_(23)C_6 carbides dominate on the grain boundaries rather than MC(M=Nb, Ti), and thus the bonding effect of carbides is absent for the straight grain boundaries.The impurity segregation of O is confirmed for the inner surfaces of DDC. The oxide film formed on the inner surface of DDC(about 50 nm) is approximately twice as thick as that on the matrix(about 25 nm)in simulated primary water. The yield strength, tensile strength and elongation to fracture of 52 MwDCZ(400 MPa, 450 MPa and 20 %, respectively) are lower than those of 52 Mw-MZ(460 MPa, 550 MPa and 28 %, respectively). The intrinsic high-restraint weld structure, the additional stress/strain caused by the thermal expansion difference between AISI 316 L and 52 Mw as well as the detrimental carbide precipitation and the resulting grain boundary structure all add up to cause the occurrence of DCZ in the dissimilar metal weld.
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.
文摘In this work,the influences of surface layer slurry at different temperatures(10℃,14℃,18℃,22℃)on wax patterns deformation,shrinkage,slurry coating characteristics,and the surface quality of the casting were investigated by using a single factor variable method.The surface morphologies of the shell molds produced by different temperatures of the surface(first)layer slurries were observed via electron microscopy.Furthermore,the microscopic composition of these shell molds was obtained by EDS,and the osmotic effect of the slurry on the wax patterns at different temperatures was also assessed by the PZ-200 Contact Angle detector.The forming reasons for the surface cracks and holes of thick and large ZTC4 titanium alloy by investment casting were analyzed.The experimental results show that the surface of the shell molds prepared by the surface layer slurry with a low temperature exhibits noticeable damage,which is mainly due to the poor coating performance and the serious expansion and contraction of wax pattern at low temperatures.The second layer shell material(SiO_(2),Al_(2)O_(3))immerses into the crack area of the surface layer,contacts and reacts with the molten titanium to form surface cracks and holes in the castings.With the increase of the temperature of surface layer slurry,the damage to the shell surface tends to weaken,and the composition of the shell molds'surface becomes more uniform with less impurities.The results show that the surface layer slurry at 22℃is evenly coated on the surface of the wax patterns with appropriate thickness,and there is no surface shell mold rupture caused by sliding slurry after sand leaching.The surface layer slurry temperature is consistent with the wax pattern temperature and the workshop temperature,so there is no damage of the surface layer shell caused by expansion and contraction.Therefore,the shell mold prepared by the surface layer slurry at this temperature has good integrity,isolating the contact between the low inert shell material and the titanium liquid effectively,and the ZTC4 titanium alloy cylinder casting prepared by this shell mold is smooth,without cracks and holes.
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This work was supported by the High-Tech Industry Science and Technology Innovation Leading Plan Project of Hunan Provincial under Grant 2020GK2026,author B.Y,http://kjt.hunan.gov.cn/.
文摘Regular inspection of bridge cracks is crucial to bridge maintenance and repair.The traditional manual crack detection methods are timeconsuming,dangerous and subjective.At the same time,for the existing mainstream vision-based automatic crack detection algorithms,it is challenging to detect fine cracks and balance the detection accuracy and speed.Therefore,this paper proposes a new bridge crack segmentationmethod based on parallel attention mechanism and multi-scale features fusion on top of the DeeplabV3+network framework.First,the improved lightweight MobileNetv2 network and dilated separable convolution are integrated into the original DeeplabV3+network to improve the original backbone network Xception and atrous spatial pyramid pooling(ASPP)module,respectively,dramatically reducing the number of parameters in the network and accelerates the training and prediction speed of the model.Moreover,we introduce the parallel attention mechanism into the encoding and decoding stages.The attention to the crack regions can be enhanced from the aspects of both channel and spatial parts and significantly suppress the interference of various noises.Finally,we further improve the detection performance of the model for fine cracks by introducing a multi-scale features fusion module.Our research results are validated on the self-made dataset.The experiments show that our method is more accurate than other methods.Its intersection of union(IoU)and F1-score(F1)are increased to 77.96%and 87.57%,respectively.In addition,the number of parameters is only 4.10M,which is much smaller than the original network;also,the frames per second(FPS)is increased to 15 frames/s.The results prove that the proposed method fits well the requirements of rapid and accurate detection of bridge cracks and is superior to other methods.
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.
基金supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region,China(Project No.15308024)a grant from Research Centre for Carbon-Strategic Catalysis,The Hong Kong Polytechnic University(CE2X).
文摘Water electrolyzers play a crucial role in green hydrogen production.However,their efficiency and scalability are often compromised by bubble dynamics across various scales,from nanoscale to macroscale components.This review explores multi-scale modeling as a tool to visualize multi-phase flow and improve mass transport in water electrolyzers.At the nanoscale,molecular dynamics(MD)simulations reveal how electrode surface features and wettability influence nanobubble nucleation and stability.Moving to the mesoscale,models such as volume of fluid(VOF)and lattice Boltzmann method(LBM)shed light on bubble transport in porous transport layers(PTLs).These insights inform innovative designs,including gradient porosity and hydrophilic-hydrophobic patterning,aimed at minimizing gas saturation.At the macroscale,VOF simulations elucidate two-phase flow regimes within channels,showing how flow field geometry and wettability affect bubble discharging.Moreover,artificial intelligence(AI)-driven surrogate models expedite the optimization process,allowing for rapid exploration of structural parameters in channel-rib flow fields and porous flow field designs.By integrating these approaches,we can bridge theoretical insights with experimental validation,ultimately enhancing water electrolyzer performance,reducing costs,and advancing affordable,high-efficiency hydrogen production.
基金supported by the National Natural Science Foundation of China(Nos.52222504 and 52241502)the Natural Science Talents Foundation of Shaanxi Province(No.2021JC-04).
文摘In order to realize the automatic recognition and classification of cracks with different depths,in this study,several deep convolutional neural networks including AlexNet,ResNet,and DenseNet were employed to identify and classify cracks at different depths and in various materials.An analysis process for the automatic classification of crack damage was presented.The image dataset used for model training was obtained from scanning experiments on aluminum and titanium alloy plates using an ultrasonic phased-array flaw detector.All models were trained and validated with the dataset;the proposed models were compared using classification precision and loss values.The results show that the automatic recognition and classification of crack depth can be realized by using the deep learning algorithm to analyze the ultrasonic phased array images,and the classification precision of DenseNet is the highest.The problem that ultrasonic damage identification relies on manual experience is solved.
基金funded by the China Chongqing Municipal Science and Technology Bureau,grant numbers 2024TIAD-CYKJCXX0121,2024NSCQ-LZX0135Chongqing Municipal Commission of Housing and Urban-Rural Development,grant number CKZ2024-87+3 种基金the Chongqing University of Technology graduate education high-quality development project,grant number gzlsz202401the Chongqing University of Technology-Chongqing LINGLUE Technology Co.,Ltd.,Electronic Information(Artificial Intelligence)graduate joint training basethe Postgraduate Education and Teaching Reform Research Project in Chongqing,grant number yjg213116the Chongqing University of Technology-CISDI Chongqing Information Technology Co.,Ltd.,Computer Technology graduate joint training base.
文摘Detecting abnormal cervical cells is crucial for early identification and timely treatment of cervical cancer.However,this task is challenging due to the morphological similarities between abnormal and normal cells and the significant variations in cell size.Pathologists often refer to surrounding cells to identify abnormalities.To emulate this slide examination behavior,this study proposes a Multi-Scale Feature Fusion Network(MSFF-Net)for detecting cervical abnormal cells.MSFF-Net employs a Cross-Scale Pooling Model(CSPM)to effectively capture diverse features and contextual information,ranging from local details to the overall structure.Additionally,a Multi-Scale Fusion Attention(MSFA)module is introduced to mitigate the impact of cell size variations by adaptively fusing local and global information at different scales.To handle the complex environment of cervical cell images,such as cell adhesion and overlapping,the Inner-CIoU loss function is utilized to more precisely measure the overlap between bounding boxes,thereby improving detection accuracy in such scenarios.Experimental results on the Comparison detector dataset demonstrate that MSFF-Net achieves a mean average precision(mAP)of 63.2%,outperforming state-of-the-art methods while maintaining a relatively small number of parameters(26.8 M).This study highlights the effectiveness of multi-scale feature fusion in enhancing the detection of cervical abnormal cells,contributing to more accurate and efficient cervical cancer screening.
