Computational simulation is an important technical means in research of nuclear fuel materials.Since nuclear fuel issues are inherently multi-scopic,it is imperative to study them with multi-scale simulation scheme.At...Computational simulation is an important technical means in research of nuclear fuel materials.Since nuclear fuel issues are inherently multi-scopic,it is imperative to study them with multi-scale simulation scheme.At present,the development of multi-scale simulation for nuclear fuel materials calls for a more systematic approach,in which lies the main purpose of this article.The most important thing in multi-scale simulation is to accurately formulate the goals to be achieved and the types of methods to be used.In this regard,we first summarize the basic principles and applicability of the simulation methods which are commonly used in nuclear fuel research and are based on different scales ranging from micro to macro,i.e.First-Principles(FP),Molecular Dynamics(MD),Kinetic Monte Carlo(KMC),Phase Field(PF),Rate Theory(RT),and Finite Element Method(FEM).And then we discuss the major material issues in this field,also ranging from micro-scale to macro-scale and covering both pellets and claddings,with emphasis on what simulation method would be most suitable for solving each of the issues.Finally,we give our prospective analysis and understanding about the feasible ways of multi-scale integration and relevant handicaps and challenges.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
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
It is one concern of the researchers how magnesium(Mg)alloys solidify under different conditions and how their microstructure evolves during solidification,and what are the relationship between the macroscopic propert...It is one concern of the researchers how magnesium(Mg)alloys solidify under different conditions and how their microstructure evolves during solidification,and what are the relationship between the macroscopic properties and various microstructures.Such issues are difficult to be revealed through experiments only,especially for the newly developed Mg alloys,for which there is a lack of more systematic and mature system.However,multi-scale modeling and simulation can promote and deepen our understanding of the microstructure and its deformation mechanism.In this paper,we review and summarize the recent research progress of numerical simulation of Mg alloys in forming and microstructure,namely casting,extrusion,rolling,and welding,using crystal plasticity finite element(CPFEM)and molecular dynamics(DM)methods.Besides,the methods and innovations of modeling are also summarized.Lastly,the paper discusses the development prospects and challenges of the numerical simulation in the field of Mg alloys.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
In this study,a novel multi-physics multi-scale model with the dilute multicomponent phase-field method in three-dimensional(3D)space was developed to investigate the complex microstructure evolu-tion in the molten po...In this study,a novel multi-physics multi-scale model with the dilute multicomponent phase-field method in three-dimensional(3D)space was developed to investigate the complex microstructure evolu-tion in the molten pool during laser welding of Al-Li alloy.To accurately compute mass data within both two and three-dimensional computational domains,three efficient computing methods,including central processing unit parallel computing,adaptive mesh refinement,and moving-frame algorithm,were uti-lized.Emphasis was placed on the distinctive equiaxed-to-columnar-to-equiaxed transition phenomenon that occurs during the entire solidification process of Al-Li alloy laser welding.Simulation results indi-cated that the growth distance of columnar grains that epitaxially grew from the base metal(BM)de-creased as the nucleation rate increased.As the nucleation rate increased,the morphology of the newly formed grains near the fusion boundary(FB)changed from columnar to equiaxed,and newly formed equiaxed grains changed from having high-order dendrites to no obvious dendrite structure.When the nucleation rate was sufficiently high,non-dendritic equiaxed grains could directly form near the FB,and there was nearly no epitaxial growth from the BM.Additionally,simulation results illustrated the com-petition among multiple grains with varying orientations that grow in 3D space near the FB.Finally,how equiaxed grain bands develop was elucidated.The equiaxed band not only hindered the growth of early columnar grains but also some of its grains could grow epitaxially to form new columnar grains.These predicted results were in good agreement with experimental measurements and observations.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
To address the limitations of existing coupling methods in aero-engine system simulation,which fail to adaptively adjust iterative parameters and coupling relationships,which can result in low efficiency and in⁃stabil...To address the limitations of existing coupling methods in aero-engine system simulation,which fail to adaptively adjust iterative parameters and coupling relationships,which can result in low efficiency and in⁃stability,this study introduces a‘Dynamic Event-Driven Co-Simulation’algorithm integrated with decision tree algorithms.This algorithm separates the overall coupling relationships and the main solver from the primary mod⁃el,utilizing a dynamic event monitoring module to adaptively adjust simulation strategies,including iteration pa⁃rameters,coupling relationships,and convergence criteria.This facilitates efficient adaptive simulations of dy⁃namic events while balancing solution accuracy and computational efficiency.The research focuses on a twinshaft turbofan engine,establishing six system-level models that encompass overall performance and various sub⁃systems based on three coupling methods,along with a multidisciplinary multi-fidelity simulation framework in⁃corporating a 3D CFD nozzle model.The study tests both model exchange and coupled simulation methods under a 14 s transient acceleration and deceleration scenario.In a 100%throttle condition,a high-fidelity nozzle model is used to analyze the sensitivity of different convergence criteria on computational efficiency and accuracy.Re⁃sults indicate that the accuracy and efficiency achieved with this method are comparable to those of PROOSIS soft⁃ware(18 s and 35 s,respectively),while being 71%more efficient than Simulink software(62 s and 120 s,re⁃spectively).Furthermore,appropriately relaxing the convergence criteria for the 0D model(from 10-6 to 10-4)while enhancing those for the 3D model(from 3000 steps to 6000 steps)can effectively balance computational accuracy and efficiency.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
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
Advanced chemical engineering for simultaneous modulation of nanomaterial morphology, defects, interfaces, and structure to enhance electromagnetic and microwave absorption (MA) performance. However, accurately distin...Advanced chemical engineering for simultaneous modulation of nanomaterial morphology, defects, interfaces, and structure to enhance electromagnetic and microwave absorption (MA) performance. However, accurately distinguishing the MA contributions of different scale factors and tuning the optimal combined effects remains a formidable challenge. This study employs a synergistic approach combining template protection etching and vacuum annealing to construct a controlled system of micrometer-sized cavities and amorphous carbon matrices in metal-organic framework (MOF) derivatives. The results demonstrate that the spatial effects introduced by the hollow structure enhance dielectric loss but significantly weaken impedance matching. By increasing the proportion of amorphous carbon, the balance between electromagnetic loss and impedance matching can be effectively maintained. Importantly, in a suitable graphitization environment, the presence of oxygen vacancies in amorphous carbon can induce significant polarization to compensate for the reduced conductivity loss due to the absence of sp2 carbon. Through the synergistic effects of morphology and composition, the samples exhibit a broader absorption bandwidth (6.28 GHz) and stronger reflection loss (−61.64 dB) compared to the original MOF. In conclusion, this study aims to elucidate the multiscale impacts of macroscopic micro-nano structure and microscopic defect engineering, providing valuable insights for future research in this field.展开更多
With the rapid growth of socialmedia,the spread of fake news has become a growing problem,misleading the public and causing significant harm.As social media content is often composed of both images and text,the use of...With the rapid growth of socialmedia,the spread of fake news has become a growing problem,misleading the public and causing significant harm.As social media content is often composed of both images and text,the use of multimodal approaches for fake news detection has gained significant attention.To solve the problems existing in previous multi-modal fake news detection algorithms,such as insufficient feature extraction and insufficient use of semantic relations between modes,this paper proposes the MFFFND-Co(Multimodal Feature Fusion Fake News Detection with Co-Attention Block)model.First,the model deeply explores the textual content,image content,and frequency domain features.Then,it employs a Co-Attention mechanism for cross-modal fusion.Additionally,a semantic consistency detectionmodule is designed to quantify semantic deviations,thereby enhancing the performance of fake news detection.Experimentally verified on two commonly used datasets,Twitter and Weibo,the model achieved F1 scores of 90.0% and 94.0%,respectively,significantly outperforming the pre-modified MFFFND(Multimodal Feature Fusion Fake News Detection with Attention Block)model and surpassing other baseline models.This improves the accuracy of detecting fake information in artificial intelligence detection and engineering software detection.展开更多
This paper aims to develop a nonrigid registration method of preoperative and intraoperative thoracoabdominal CT images in computer-assisted interventional surgeries for accurate tumor localization and tissue visualiz...This paper aims to develop a nonrigid registration method of preoperative and intraoperative thoracoabdominal CT images in computer-assisted interventional surgeries for accurate tumor localization and tissue visualization enhancement.However,fine structure registration of complex thoracoabdominal organs and large deformation registration caused by respiratory motion is challenging.To deal with this problem,we propose a 3D multi-scale attention VoxelMorph(MAVoxelMorph)registration network.To alleviate the large deformation problem,a multi-scale axial attention mechanism is utilized by using a residual dilated pyramid pooling for multi-scale feature extraction,and position-aware axial attention for long-distance dependencies between pixels capture.To further improve the large deformation and fine structure registration results,a multi-scale context channel attention mechanism is employed utilizing content information via adjacent encoding layers.Our method was evaluated on four public lung datasets(DIR-Lab dataset,Creatis dataset,Learn2Reg dataset,OASIS dataset)and a local dataset.Results proved that the proposed method achieved better registration performance than current state-of-the-art methods,especially in handling the registration of large deformations and fine structures.It also proved to be fast in 3D image registration,using about 1.5 s,and faster than most methods.Qualitative and quantitative assessments proved that the proposed MA-VoxelMorph has the potential to realize precise and fast tumor localization in clinical interventional surgeries.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
The long-lasting expectation“the hotter the engine,the better”calls for the development of high-temperature metallic alloys.Although the high specific strengths of titanium alloys are compelling for such application...The long-lasting expectation“the hotter the engine,the better”calls for the development of high-temperature metallic alloys.Although the high specific strengths of titanium alloys are compelling for such applications,their deleterious softening beyond 600℃ imposes serious limitations.Much has been known for decades regarding the phase metallurgy for precipitation strengthening design in titanium alloys,however,the other facile strength promotion mechanism,dispersion strengthening,remains comparatively less-explored and unutilized.The present research concerns the multi-scale dispersion strengthening in titanium alloys,with mechanistic emphases on the critical plasticity micro-events that affect strength preservation.Due to the simultaneous introduction of intragranular dispersoids and intergranular reinforcers,the current titanium alloys present superior engineering tensile strength of 519 MPa at 700℃.Throughout the examined 25-800℃ temperature range,noticeable softening induced by the thermal activation occurs above 600℃,accompanied by evident strength loss.The temperature-dependence transition of dominated softening mechanisms from dynamic recovery to dynamic recrystallization has been clarified by theoretical calculations.Furthermore,the strengthening effect of multi-scale architectures is underpinned as the enhanced dislocation strengthening owing to the introduction of thermally-stable heterointerfaces,which could generically guide the design of similar heat-resistant titanium alloys.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
To solve the problems of redundant feature information,the insignificant difference in feature representation,and low recognition accuracy of the fine-grained image,based on the ResNeXt50 model,an MSFResNet network mo...To solve the problems of redundant feature information,the insignificant difference in feature representation,and low recognition accuracy of the fine-grained image,based on the ResNeXt50 model,an MSFResNet network model is proposed by fusing multi-scale feature information.Firstly,a multi-scale feature extraction module is designed to obtain multi-scale information on feature images by using different scales of convolution kernels.Meanwhile,the channel attention mechanism is used to increase the global information acquisition of the network.Secondly,the feature images processed by the multi-scale feature extraction module are fused with the deep feature images through short links to guide the full learning of the network,thus reducing the loss of texture details of the deep network feature images,and improving network generalization ability and recognition accuracy.Finally,the validity of the MSFResNet model is verified using public datasets and applied to wild mushroom identification.Experimental results show that compared with ResNeXt50 network model,the accuracy of the MSFResNet model is improved by 6.01%on the FGVC-Aircraft common dataset.It achieves 99.13%classification accuracy on the wild mushroom dataset,which is 0.47%higher than ResNeXt50.Furthermore,the experimental results of the thermal map show that the MSFResNet model significantly reduces the interference of background information,making the network focus on the location of the main body of wild mushroom,which can effectively improve the accuracy of wild mushroom identification.展开更多
基金the financial support from the China National Natural Science Foundation project(11675126)Project of China Nuclear Power Innovation Center,China National Nuclear Corporation Science fund for talented young scholars(FY18000120)the National Science and Technology Major Project of the Ministry of Science and Technology of China(2019ZX06004009).
文摘Computational simulation is an important technical means in research of nuclear fuel materials.Since nuclear fuel issues are inherently multi-scopic,it is imperative to study them with multi-scale simulation scheme.At present,the development of multi-scale simulation for nuclear fuel materials calls for a more systematic approach,in which lies the main purpose of this article.The most important thing in multi-scale simulation is to accurately formulate the goals to be achieved and the types of methods to be used.In this regard,we first summarize the basic principles and applicability of the simulation methods which are commonly used in nuclear fuel research and are based on different scales ranging from micro to macro,i.e.First-Principles(FP),Molecular Dynamics(MD),Kinetic Monte Carlo(KMC),Phase Field(PF),Rate Theory(RT),and Finite Element Method(FEM).And then we discuss the major material issues in this field,also ranging from micro-scale to macro-scale and covering both pellets and claddings,with emphasis on what simulation method would be most suitable for solving each of the issues.Finally,we give our prospective analysis and understanding about the feasible ways of multi-scale integration and relevant handicaps and challenges.
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supported by the National Natural Science Foundation of China(No.52271091)Natural Science Foundation Project of Ningxia Province(No.2023AAC03324)the National Key Research and Development Program of China(No.2021YFB3701100).
文摘It is one concern of the researchers how magnesium(Mg)alloys solidify under different conditions and how their microstructure evolves during solidification,and what are the relationship between the macroscopic properties and various microstructures.Such issues are difficult to be revealed through experiments only,especially for the newly developed Mg alloys,for which there is a lack of more systematic and mature system.However,multi-scale modeling and simulation can promote and deepen our understanding of the microstructure and its deformation mechanism.In this paper,we review and summarize the recent research progress of numerical simulation of Mg alloys in forming and microstructure,namely casting,extrusion,rolling,and welding,using crystal plasticity finite element(CPFEM)and molecular dynamics(DM)methods.Besides,the methods and innovations of modeling are also summarized.Lastly,the paper discusses the development prospects and challenges of the numerical simulation in the field of Mg alloys.
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supported by the National Natural Science Foundation of China(Grant Nos.52075201,U22A20196,52188102)GuangDong Basic and Applied Basic Research Foundation(No.2023A1515010081).
文摘In this study,a novel multi-physics multi-scale model with the dilute multicomponent phase-field method in three-dimensional(3D)space was developed to investigate the complex microstructure evolu-tion in the molten pool during laser welding of Al-Li alloy.To accurately compute mass data within both two and three-dimensional computational domains,three efficient computing methods,including central processing unit parallel computing,adaptive mesh refinement,and moving-frame algorithm,were uti-lized.Emphasis was placed on the distinctive equiaxed-to-columnar-to-equiaxed transition phenomenon that occurs during the entire solidification process of Al-Li alloy laser welding.Simulation results indi-cated that the growth distance of columnar grains that epitaxially grew from the base metal(BM)de-creased as the nucleation rate increased.As the nucleation rate increased,the morphology of the newly formed grains near the fusion boundary(FB)changed from columnar to equiaxed,and newly formed equiaxed grains changed from having high-order dendrites to no obvious dendrite structure.When the nucleation rate was sufficiently high,non-dendritic equiaxed grains could directly form near the FB,and there was nearly no epitaxial growth from the BM.Additionally,simulation results illustrated the com-petition among multiple grains with varying orientations that grow in 3D space near the FB.Finally,how equiaxed grain bands develop was elucidated.The equiaxed band not only hindered the growth of early columnar grains but also some of its grains could grow epitaxially to form new columnar grains.These predicted results were in good agreement with experimental measurements and observations.
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.
文摘To address the limitations of existing coupling methods in aero-engine system simulation,which fail to adaptively adjust iterative parameters and coupling relationships,which can result in low efficiency and in⁃stability,this study introduces a‘Dynamic Event-Driven Co-Simulation’algorithm integrated with decision tree algorithms.This algorithm separates the overall coupling relationships and the main solver from the primary mod⁃el,utilizing a dynamic event monitoring module to adaptively adjust simulation strategies,including iteration pa⁃rameters,coupling relationships,and convergence criteria.This facilitates efficient adaptive simulations of dy⁃namic events while balancing solution accuracy and computational efficiency.The research focuses on a twinshaft turbofan engine,establishing six system-level models that encompass overall performance and various sub⁃systems based on three coupling methods,along with a multidisciplinary multi-fidelity simulation framework in⁃corporating a 3D CFD nozzle model.The study tests both model exchange and coupled simulation methods under a 14 s transient acceleration and deceleration scenario.In a 100%throttle condition,a high-fidelity nozzle model is used to analyze the sensitivity of different convergence criteria on computational efficiency and accuracy.Re⁃sults indicate that the accuracy and efficiency achieved with this method are comparable to those of PROOSIS soft⁃ware(18 s and 35 s,respectively),while being 71%more efficient than Simulink software(62 s and 120 s,re⁃spectively).Furthermore,appropriately relaxing the convergence criteria for the 0D model(from 10-6 to 10-4)while enhancing those for the 3D model(from 3000 steps to 6000 steps)can effectively balance computational accuracy and efficiency.
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.
基金supported by the National Natural Science Foundation of China(52172091,52172295)Defense Industrial Technology Development Program(JCKY2023605C002)+4 种基金Frontier Leading Technology Basic Research Major Project of Jiangsu Province(SBK2023050110)the National Key Laboratory on Electromagnetic Environmental Effects and Electro-optical Engineering(NO.61422062301)the Opening Project of Science and Technology on Reliability Physics and Application Technology of Electronic Component Laboratory(ZHD202305)the Opening Project of Jiangsu Key Laboratory of Advanced Structural Materials and Application Technology(ASMA202303)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX23_0371).
文摘Advanced chemical engineering for simultaneous modulation of nanomaterial morphology, defects, interfaces, and structure to enhance electromagnetic and microwave absorption (MA) performance. However, accurately distinguishing the MA contributions of different scale factors and tuning the optimal combined effects remains a formidable challenge. This study employs a synergistic approach combining template protection etching and vacuum annealing to construct a controlled system of micrometer-sized cavities and amorphous carbon matrices in metal-organic framework (MOF) derivatives. The results demonstrate that the spatial effects introduced by the hollow structure enhance dielectric loss but significantly weaken impedance matching. By increasing the proportion of amorphous carbon, the balance between electromagnetic loss and impedance matching can be effectively maintained. Importantly, in a suitable graphitization environment, the presence of oxygen vacancies in amorphous carbon can induce significant polarization to compensate for the reduced conductivity loss due to the absence of sp2 carbon. Through the synergistic effects of morphology and composition, the samples exhibit a broader absorption bandwidth (6.28 GHz) and stronger reflection loss (−61.64 dB) compared to the original MOF. In conclusion, this study aims to elucidate the multiscale impacts of macroscopic micro-nano structure and microscopic defect engineering, providing valuable insights for future research in this field.
基金supported by Communication University of China(HG23035)partly supported by the Fundamental Research Funds for the Central Universities(CUC230A013).
文摘With the rapid growth of socialmedia,the spread of fake news has become a growing problem,misleading the public and causing significant harm.As social media content is often composed of both images and text,the use of multimodal approaches for fake news detection has gained significant attention.To solve the problems existing in previous multi-modal fake news detection algorithms,such as insufficient feature extraction and insufficient use of semantic relations between modes,this paper proposes the MFFFND-Co(Multimodal Feature Fusion Fake News Detection with Co-Attention Block)model.First,the model deeply explores the textual content,image content,and frequency domain features.Then,it employs a Co-Attention mechanism for cross-modal fusion.Additionally,a semantic consistency detectionmodule is designed to quantify semantic deviations,thereby enhancing the performance of fake news detection.Experimentally verified on two commonly used datasets,Twitter and Weibo,the model achieved F1 scores of 90.0% and 94.0%,respectively,significantly outperforming the pre-modified MFFFND(Multimodal Feature Fusion Fake News Detection with Attention Block)model and surpassing other baseline models.This improves the accuracy of detecting fake information in artificial intelligence detection and engineering software detection.
基金supported in part by the National Natural Science Foundation of China[62301374]Hubei Provincial Natural Science Foundation of China[2022CFB804]+2 种基金Hubei Provincial Education Research Project[B2022057]the Youths Science Foundation of Wuhan Institute of Technology[K202240]the 15th Graduate Education Innovation Fund of Wuhan Institute of Technology[CX2023295].
文摘This paper aims to develop a nonrigid registration method of preoperative and intraoperative thoracoabdominal CT images in computer-assisted interventional surgeries for accurate tumor localization and tissue visualization enhancement.However,fine structure registration of complex thoracoabdominal organs and large deformation registration caused by respiratory motion is challenging.To deal with this problem,we propose a 3D multi-scale attention VoxelMorph(MAVoxelMorph)registration network.To alleviate the large deformation problem,a multi-scale axial attention mechanism is utilized by using a residual dilated pyramid pooling for multi-scale feature extraction,and position-aware axial attention for long-distance dependencies between pixels capture.To further improve the large deformation and fine structure registration results,a multi-scale context channel attention mechanism is employed utilizing content information via adjacent encoding layers.Our method was evaluated on four public lung datasets(DIR-Lab dataset,Creatis dataset,Learn2Reg dataset,OASIS dataset)and a local dataset.Results proved that the proposed method achieved better registration performance than current state-of-the-art methods,especially in handling the registration of large deformations and fine structures.It also proved to be fast in 3D image registration,using about 1.5 s,and faster than most methods.Qualitative and quantitative assessments proved that the proposed MA-VoxelMorph has the potential to realize precise and fast tumor localization in clinical interventional surgeries.
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financially supported by the National Key R&D Program of China(No.2021YFB3701203)the National Natural Science Foundation of China(Nos.U22A20113,52261135543,52171137 and 52071116)the Heilongjiang Touyan Team Program,Heilongjiang Provincial Natural Science Foundation of China(No.TD2020E001).
文摘The long-lasting expectation“the hotter the engine,the better”calls for the development of high-temperature metallic alloys.Although the high specific strengths of titanium alloys are compelling for such applications,their deleterious softening beyond 600℃ imposes serious limitations.Much has been known for decades regarding the phase metallurgy for precipitation strengthening design in titanium alloys,however,the other facile strength promotion mechanism,dispersion strengthening,remains comparatively less-explored and unutilized.The present research concerns the multi-scale dispersion strengthening in titanium alloys,with mechanistic emphases on the critical plasticity micro-events that affect strength preservation.Due to the simultaneous introduction of intragranular dispersoids and intergranular reinforcers,the current titanium alloys present superior engineering tensile strength of 519 MPa at 700℃.Throughout the examined 25-800℃ temperature range,noticeable softening induced by the thermal activation occurs above 600℃,accompanied by evident strength loss.The temperature-dependence transition of dominated softening mechanisms from dynamic recovery to dynamic recrystallization has been clarified by theoretical calculations.Furthermore,the strengthening effect of multi-scale architectures is underpinned as the enhanced dislocation strengthening owing to the introduction of thermally-stable heterointerfaces,which could generically guide the design of similar heat-resistant titanium alloys.
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.
基金supported by National Natural Science Foundation of China(No.61862037)Lanzhou Jiaotong University Tianyou Innovation Team Project(No.TY202002)。
文摘To solve the problems of redundant feature information,the insignificant difference in feature representation,and low recognition accuracy of the fine-grained image,based on the ResNeXt50 model,an MSFResNet network model is proposed by fusing multi-scale feature information.Firstly,a multi-scale feature extraction module is designed to obtain multi-scale information on feature images by using different scales of convolution kernels.Meanwhile,the channel attention mechanism is used to increase the global information acquisition of the network.Secondly,the feature images processed by the multi-scale feature extraction module are fused with the deep feature images through short links to guide the full learning of the network,thus reducing the loss of texture details of the deep network feature images,and improving network generalization ability and recognition accuracy.Finally,the validity of the MSFResNet model is verified using public datasets and applied to wild mushroom identification.Experimental results show that compared with ResNeXt50 network model,the accuracy of the MSFResNet model is improved by 6.01%on the FGVC-Aircraft common dataset.It achieves 99.13%classification accuracy on the wild mushroom dataset,which is 0.47%higher than ResNeXt50.Furthermore,the experimental results of the thermal map show that the MSFResNet model significantly reduces the interference of background information,making the network focus on the location of the main body of wild mushroom,which can effectively improve the accuracy of wild mushroom identification.
