Recent Super-Resolution(SR)algorithms often suffer from excessive model complexity,high computational costs,and limited flexibility across varying image scales.To address these challenges,we propose DDNet,a dynamic an...Recent Super-Resolution(SR)algorithms often suffer from excessive model complexity,high computational costs,and limited flexibility across varying image scales.To address these challenges,we propose DDNet,a dynamic and lightweight SR framework designed for arbitrary scaling factors.DDNet integrates a residual learning structure with an Adaptively fusion Feature Block(AFB)and a scale-aware upsampling module,effectively reducing parameter overhead while preserving reconstruction quality.Additionally,we introduce DDNetGAN,an enhanced variant that leverages a relativistic Generative Adversarial Network(GAN)to further improve texture realism.To validate the proposed models,we conduct extensive training using the DIV2K and Flickr2K datasets and evaluate performance across standard benchmarks including Set5,Set14,Urban100,Manga109,and BSD100.Our experiments cover both symmetric and asymmetric upscaling factors and incorporate ablation studies to assess key components.Results show that DDNet and DDNetGAN achieve competitive performance compared with mainstream SR algorithms,demonstrating a strong balance between accuracy,efficiency,and flexibility.These findings highlight the potential of our approach for practical real-world super-resolution applications.展开更多
胶结充填体作为人工矿柱常受到邻近矿房开采的爆破扰动,严重影响其稳定性。基于KCC(Karagozian and Case Concrete)本构模型和ALE(Arbitrary Lagrangian-Eulerian)流固耦合算法,采用LS-DYNA软件开展胶结充填体受邻近矿房爆破扰动的数值...胶结充填体作为人工矿柱常受到邻近矿房开采的爆破扰动,严重影响其稳定性。基于KCC(Karagozian and Case Concrete)本构模型和ALE(Arbitrary Lagrangian-Eulerian)流固耦合算法,采用LS-DYNA软件开展胶结充填体受邻近矿房爆破扰动的数值模拟研究,考虑不同边孔间距(0.6、1.2、1.8、2.4 m)及养护龄期(14、21、28 d)影响,揭示充填体中爆破波传播规律,探究爆破扰动对胶结充填体的动力响应及其失稳破坏情况。结果表明:邻近采场爆破对胶结充填体的破坏损伤主要集中在边界处,为提高矿石回收率并保证充填体安全,建议采用边孔间距1.2 m方案;矿山爆破开采中充填体至少需要养护21 d;低龄期充填体矿柱顶底部区域是整个矿柱中的薄弱部分,易发生失稳,应予以重点监测。展开更多
Recently,satellite imagery has been widely applied in many areas.However,due to the limitations of hardware equipment and transmission bandwidth,the images received on the ground have low resolution and weak texture.I...Recently,satellite imagery has been widely applied in many areas.However,due to the limitations of hardware equipment and transmission bandwidth,the images received on the ground have low resolution and weak texture.In addition,since ground terminals have various resolutions and real-time playing requirements,it is essential to achieve arbitrary scale super-resolution(SR)of satellite images.In this paper,we propose an arbitrary scale SR network for satellite image reconstruction.First,we propose an arbitrary upscale module for satellite imagery that can map low-resolution satellite image features to arbitrary scale enlarged SR outputs.Second,we design an edge reinforcement module to enhance the highfrequency details in satellite images through a twobranch network.Finally,extensive upsample experiments on WHU-RS19 and NWPU-RESISC45 datasets and subsequent image segmentation experiments both show the superiority of our method over the counterparts.展开更多
We propose an explicit,single-step discontinuous Galerkin method on moving grids using the arbitrary Lagrangian-Eulerian approach for one-dimensional Euler equations.The grid is moved with the local fluid velocity mod...We propose an explicit,single-step discontinuous Galerkin method on moving grids using the arbitrary Lagrangian-Eulerian approach for one-dimensional Euler equations.The grid is moved with the local fluid velocity modified by some smoothing,which is found to con-siderably reduce the numerical dissipation introduced by Riemann solvers.The scheme preserves constant states for any mesh motion and we also study its positivity preservation property.Local grid refinement and coarsening are performed to maintain the mesh qual-ity and avoid the appearance of very small or large cells.Second,higher order methods are developed and several test cases are provided to demonstrate the accuracy of the proposed scheme.展开更多
In this paper,several arbitrary Lagrangian-Eulerian discontinuous Galerkin(ALE-DG)methods are presented for Korteweg-de Vries(KdV)type equations on moving meshes.Based on the L^(2) conservation law of KdV equations,we...In this paper,several arbitrary Lagrangian-Eulerian discontinuous Galerkin(ALE-DG)methods are presented for Korteweg-de Vries(KdV)type equations on moving meshes.Based on the L^(2) conservation law of KdV equations,we adopt the conservative and dissipative numerical fuxes for the nonlinear convection and linear dispersive terms,respectively.Thus,one conservative and three dissipative ALE-DG schemes are proposed for the equations.The invariant preserving property for the conservative scheme and the corresponding dissipative properties for the other three dissipative schemes are all presented and proved in this paper.In addition,the L^(2)-norm error estimates are also proved for two schemes,whose numerical fuxes for the linear dispersive term are both dissipative type.More precisely,when choosing the approximation space with the piecewise kth degree polynomials,the error estimate provides the kth order of convergence rate in L^(2)-norm for the scheme with the conservative numerical fuxes applied for the nonlinear convection term.Furthermore,the(k+1∕2)th order of accuracy can be proved for the ALE-DG scheme with dissipative numerical fuxes applied for the convection term.Moreover,a Hamiltonian conservative ALE-DG scheme is also presented based on the conservation of the Hamiltonian for KdV equations.Numerical examples are shown to demonstrate the accuracy and capability of the moving mesh ALE-DG methods and compare with stationary DG methods.展开更多
In this paper,we present the negative norm estimates for the arbitrary Lagrangian-Eulerian discontinuous Galerkin(ALE-DG)method solving nonlinear hyperbolic equations with smooth solutions.The smoothness-increasing ac...In this paper,we present the negative norm estimates for the arbitrary Lagrangian-Eulerian discontinuous Galerkin(ALE-DG)method solving nonlinear hyperbolic equations with smooth solutions.The smoothness-increasing accuracy-conserving(SIAC)filter is a post-processing technique to enhance the accuracy of the discontinuous Galerkin(DG)solutions.This work is the essential step to extend the SIAC filter to the moving mesh for nonlinear problems.By the post-processing theory,the negative norm estimates are vital to get the superconvergence error estimates of the solutions after post-processing in the L2 norm.Although the SIAC filter has been extended to nonuniform mesh,the analysis of fil-tered solutions on the nonuniform mesh is complicated.We prove superconvergence error estimates in the negative norm for the ALE-DG method on moving meshes.The main dif-ficulties of the analysis are the terms in the ALE-DG scheme brought by the grid velocity field,and the time-dependent function space.The mapping from time-dependent cells to reference cells is very crucial in the proof.The numerical results also confirm the theoreti-cal proof.展开更多
关于自我参照处理中信念的作用,已有两种信念类型的提出:以自我为中心的信念和基于他人视角的信念。然而,这两种信念背后的神经机制仍不明确。为了区分与这两类信念相关的脑部过程,本研究采用ALE元分析方法,分析了自我特质判断任务与虚...关于自我参照处理中信念的作用,已有两种信念类型的提出:以自我为中心的信念和基于他人视角的信念。然而,这两种信念背后的神经机制仍不明确。为了区分与这两类信念相关的脑部过程,本研究采用ALE元分析方法,分析了自我特质判断任务与虚假信念任务的fMRI研究结果。结果表明,与虚假信念任务相比,在自我特质判断任务中,前扣带回(ACC)的活动显著增强。相反,左侧颞顶联合区(lTPJ)和背内侧前额叶皮层(dmPFC)被认为是自我特质判断任务与虚假信念任务共同激活的区域。基于这些结果,我们认为ACC可能在利用自我中心信念进行特质自我判断时发挥作用,即当自我知识中存在特质与稳定行为模式之间的关联时;而左侧TPJ和dmPFC可能在利用基于他人视角的信念进行自我特质判断时发挥作用,当自我中心信念不足以支持自我判断时,个体需要采纳他人视角进行判断。Two types of beliefs in self-referential processing have been proposed: self-centred beliefs and perspective-taking-based beliefs. However, the neural mechanisms underlying these two types of beliefs remain unclear. In order to distinguish the cerebral processes associated with these beliefs, an ALE meta-analysis was conducted by analysing the fMRI findings from self-judgment of trait tasks and false-belief tasks. The results demonstrated that the anterior cingulate gyrus (ACC) exhibited heightened activity during self-judgment of trait tasks in comparison to false-belief tasks. Conversely, the left temporal-parietal junction (lTPJ) and dorsomedial prefrontal cortex (dmPFC) were identified as common regions shared by both self-judgment of trait tasks and false-belief tasks. Based on these results, we thought that the ACC might be involved in the self-judgment of traits by using self-centered beliefs when there are relationships between traits and stable behavioral patterns in the self-knowledge;the left TPJ and the dmPFC might be involved in the self-judgment of traits by using perspective-taking-based beliefs, where individuals should make self-judgment by taking others’ perspectives when the self-centered beliefs do not sufficiently support the self-judgment.展开更多
Curved beams with complex geometries are vital in numerous engineering applications,where precise vibration analysis is crucial for ensuring safe and effective designs.Traditional finite element methods(FEMs) often st...Curved beams with complex geometries are vital in numerous engineering applications,where precise vibration analysis is crucial for ensuring safe and effective designs.Traditional finite element methods(FEMs) often struggle to accurately represent the dynamic characteristics of these structures due to the limitations in their shape function approximations.To overcome this challenge,the current study introduces an innovative finite element(FE)-based technique for the undamped vibrational analysis of curved beams with arbitrary curvature,employing explicitly derived interpolation functions.Initially,the exact interpolation functions are developed for circular are elements with the force method.These functions facilitate the creation of a highly accurate stiffness matrix,which is validated against the benchmark examples.To accommodate arbitrary curvature,a systematic transformation technique is established to approximate the intricate curves with a series of circular arcs.The numerical findings indicate that increasing the number of arc segments enhances accuracy,approaching the exact solutions.The analysis of free vibrations is conducted for both circular and non-circular beams.Mass matrices are derived using two methods:lumped mass and consistent mass,where the latter is based on the interpolation functions.The effectiveness of the proposed method is confirmed through the comparisons with the existing literature,demonstrating strong agreement.Finally,several practical cases involving beams with diverse curvature profiles are analyzed.Both natural frequencies and mode shapes are determined,providing significant insights into the dynamic behavior of these structures.This research offers a dependable and efficient analytical framework for the vibrational analysis of complex curved beams,with promising implications for structural and mechanical engineering.展开更多
This opinion review paper explores the application of artificial intelligence(AI)as a decisive tool in managing complex coronavirus disease 2019(COVID-19)cases within critical care medicine.Available data have shown t...This opinion review paper explores the application of artificial intelligence(AI)as a decisive tool in managing complex coronavirus disease 2019(COVID-19)cases within critical care medicine.Available data have shown that very severe cases required intensive care,most of which required endotracheal intubation and mechanical ventilation to avoid a lethal outcome if possible.The unprecedented challenges posed by the COVID-19 pandemic necessitate innovative approaches to patient care.AI offers significant potential in enhancing diagnostic accuracy,predicting patient outcomes,and optimizing treatment strategies.By analyzing vast amounts of clinical data,AI can support healthcare professionals in making informed decisions,thus improving patient outcomes.We also focus on current technologies,their implementation in critical care settings,and their impact on patient management during the COVID-19 crisis.Future directions for AI integration in critical care are also discussed.展开更多
Higher-order topological insulators,which host topologically protected states at boundaries that are at least two dimensions lower than the bulk,are an emerging class of topological materials.They provide great opport...Higher-order topological insulators,which host topologically protected states at boundaries that are at least two dimensions lower than the bulk,are an emerging class of topological materials.They provide great opportunities for exploring novel topological phenomena and fascinating applications.Utilizing a low-temperature scanning tunneling microscope,we construct breathing-kagome lattices with Fe adatoms on Ag(111)and investigate their electronic properties.We observe the higher-order topological boundary states in the topological phase but not in the trivial one,which is consistent with the theory.These states are found to be robust against the removal of bulk or edge adatoms.Further,we show the arbitrary positioning of these states either at corner,edge,or bulk sites by slightly modifying their neighbors.Our study not only demonstrates the formation and robustness of the electronic higher-order topological boundary states in real atomic systems but also provides a route for controlling their positions.展开更多
基金supported by Sichuan Science and Technology Program[2023YFSY0026,2023YFH0004].
文摘Recent Super-Resolution(SR)algorithms often suffer from excessive model complexity,high computational costs,and limited flexibility across varying image scales.To address these challenges,we propose DDNet,a dynamic and lightweight SR framework designed for arbitrary scaling factors.DDNet integrates a residual learning structure with an Adaptively fusion Feature Block(AFB)and a scale-aware upsampling module,effectively reducing parameter overhead while preserving reconstruction quality.Additionally,we introduce DDNetGAN,an enhanced variant that leverages a relativistic Generative Adversarial Network(GAN)to further improve texture realism.To validate the proposed models,we conduct extensive training using the DIV2K and Flickr2K datasets and evaluate performance across standard benchmarks including Set5,Set14,Urban100,Manga109,and BSD100.Our experiments cover both symmetric and asymmetric upscaling factors and incorporate ablation studies to assess key components.Results show that DDNet and DDNetGAN achieve competitive performance compared with mainstream SR algorithms,demonstrating a strong balance between accuracy,efficiency,and flexibility.These findings highlight the potential of our approach for practical real-world super-resolution applications.
文摘胶结充填体作为人工矿柱常受到邻近矿房开采的爆破扰动,严重影响其稳定性。基于KCC(Karagozian and Case Concrete)本构模型和ALE(Arbitrary Lagrangian-Eulerian)流固耦合算法,采用LS-DYNA软件开展胶结充填体受邻近矿房爆破扰动的数值模拟研究,考虑不同边孔间距(0.6、1.2、1.8、2.4 m)及养护龄期(14、21、28 d)影响,揭示充填体中爆破波传播规律,探究爆破扰动对胶结充填体的动力响应及其失稳破坏情况。结果表明:邻近采场爆破对胶结充填体的破坏损伤主要集中在边界处,为提高矿石回收率并保证充填体安全,建议采用边孔间距1.2 m方案;矿山爆破开采中充填体至少需要养护21 d;低龄期充填体矿柱顶底部区域是整个矿柱中的薄弱部分,易发生失稳,应予以重点监测。
基金supported in part by the National Natural Science Foundation of China(NSFC)under Grant 91738302,Grant 62102423,Grant 61671332,and Grant U1736206in part by the Open Research Fund of State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University under Grant 17E03.
文摘Recently,satellite imagery has been widely applied in many areas.However,due to the limitations of hardware equipment and transmission bandwidth,the images received on the ground have low resolution and weak texture.In addition,since ground terminals have various resolutions and real-time playing requirements,it is essential to achieve arbitrary scale super-resolution(SR)of satellite images.In this paper,we propose an arbitrary scale SR network for satellite image reconstruction.First,we propose an arbitrary upscale module for satellite imagery that can map low-resolution satellite image features to arbitrary scale enlarged SR outputs.Second,we design an edge reinforcement module to enhance the highfrequency details in satellite images through a twobranch network.Finally,extensive upsample experiments on WHU-RS19 and NWPU-RESISC45 datasets and subsequent image segmentation experiments both show the superiority of our method over the counterparts.
文摘We propose an explicit,single-step discontinuous Galerkin method on moving grids using the arbitrary Lagrangian-Eulerian approach for one-dimensional Euler equations.The grid is moved with the local fluid velocity modified by some smoothing,which is found to con-siderably reduce the numerical dissipation introduced by Riemann solvers.The scheme preserves constant states for any mesh motion and we also study its positivity preservation property.Local grid refinement and coarsening are performed to maintain the mesh qual-ity and avoid the appearance of very small or large cells.Second,higher order methods are developed and several test cases are provided to demonstrate the accuracy of the proposed scheme.
基金This work was supported by the National Numerical Windtunnel Project NNW2019ZT4-B08Science Challenge Project TZZT2019-A2.3the National Natural Science Foundation of China Grant no.11871449.
文摘In this paper,several arbitrary Lagrangian-Eulerian discontinuous Galerkin(ALE-DG)methods are presented for Korteweg-de Vries(KdV)type equations on moving meshes.Based on the L^(2) conservation law of KdV equations,we adopt the conservative and dissipative numerical fuxes for the nonlinear convection and linear dispersive terms,respectively.Thus,one conservative and three dissipative ALE-DG schemes are proposed for the equations.The invariant preserving property for the conservative scheme and the corresponding dissipative properties for the other three dissipative schemes are all presented and proved in this paper.In addition,the L^(2)-norm error estimates are also proved for two schemes,whose numerical fuxes for the linear dispersive term are both dissipative type.More precisely,when choosing the approximation space with the piecewise kth degree polynomials,the error estimate provides the kth order of convergence rate in L^(2)-norm for the scheme with the conservative numerical fuxes applied for the nonlinear convection term.Furthermore,the(k+1∕2)th order of accuracy can be proved for the ALE-DG scheme with dissipative numerical fuxes applied for the convection term.Moreover,a Hamiltonian conservative ALE-DG scheme is also presented based on the conservation of the Hamiltonian for KdV equations.Numerical examples are shown to demonstrate the accuracy and capability of the moving mesh ALE-DG methods and compare with stationary DG methods.
基金the fellowship of China Postdoctoral Science Foundation,no:2020TQ0030.Y.Xu:Research supported by National Numerical Windtunnel Project NNW2019ZT4-B08+1 种基金Science Challenge Project TZZT2019-A2.3NSFC Grants 11722112,12071455.X.Li:Research supported by NSFC Grant 11801062.
文摘In this paper,we present the negative norm estimates for the arbitrary Lagrangian-Eulerian discontinuous Galerkin(ALE-DG)method solving nonlinear hyperbolic equations with smooth solutions.The smoothness-increasing accuracy-conserving(SIAC)filter is a post-processing technique to enhance the accuracy of the discontinuous Galerkin(DG)solutions.This work is the essential step to extend the SIAC filter to the moving mesh for nonlinear problems.By the post-processing theory,the negative norm estimates are vital to get the superconvergence error estimates of the solutions after post-processing in the L2 norm.Although the SIAC filter has been extended to nonuniform mesh,the analysis of fil-tered solutions on the nonuniform mesh is complicated.We prove superconvergence error estimates in the negative norm for the ALE-DG method on moving meshes.The main dif-ficulties of the analysis are the terms in the ALE-DG scheme brought by the grid velocity field,and the time-dependent function space.The mapping from time-dependent cells to reference cells is very crucial in the proof.The numerical results also confirm the theoreti-cal proof.
文摘关于自我参照处理中信念的作用,已有两种信念类型的提出:以自我为中心的信念和基于他人视角的信念。然而,这两种信念背后的神经机制仍不明确。为了区分与这两类信念相关的脑部过程,本研究采用ALE元分析方法,分析了自我特质判断任务与虚假信念任务的fMRI研究结果。结果表明,与虚假信念任务相比,在自我特质判断任务中,前扣带回(ACC)的活动显著增强。相反,左侧颞顶联合区(lTPJ)和背内侧前额叶皮层(dmPFC)被认为是自我特质判断任务与虚假信念任务共同激活的区域。基于这些结果,我们认为ACC可能在利用自我中心信念进行特质自我判断时发挥作用,即当自我知识中存在特质与稳定行为模式之间的关联时;而左侧TPJ和dmPFC可能在利用基于他人视角的信念进行自我特质判断时发挥作用,当自我中心信念不足以支持自我判断时,个体需要采纳他人视角进行判断。Two types of beliefs in self-referential processing have been proposed: self-centred beliefs and perspective-taking-based beliefs. However, the neural mechanisms underlying these two types of beliefs remain unclear. In order to distinguish the cerebral processes associated with these beliefs, an ALE meta-analysis was conducted by analysing the fMRI findings from self-judgment of trait tasks and false-belief tasks. The results demonstrated that the anterior cingulate gyrus (ACC) exhibited heightened activity during self-judgment of trait tasks in comparison to false-belief tasks. Conversely, the left temporal-parietal junction (lTPJ) and dorsomedial prefrontal cortex (dmPFC) were identified as common regions shared by both self-judgment of trait tasks and false-belief tasks. Based on these results, we thought that the ACC might be involved in the self-judgment of traits by using self-centered beliefs when there are relationships between traits and stable behavioral patterns in the self-knowledge;the left TPJ and the dmPFC might be involved in the self-judgment of traits by using perspective-taking-based beliefs, where individuals should make self-judgment by taking others’ perspectives when the self-centered beliefs do not sufficiently support the self-judgment.
文摘Curved beams with complex geometries are vital in numerous engineering applications,where precise vibration analysis is crucial for ensuring safe and effective designs.Traditional finite element methods(FEMs) often struggle to accurately represent the dynamic characteristics of these structures due to the limitations in their shape function approximations.To overcome this challenge,the current study introduces an innovative finite element(FE)-based technique for the undamped vibrational analysis of curved beams with arbitrary curvature,employing explicitly derived interpolation functions.Initially,the exact interpolation functions are developed for circular are elements with the force method.These functions facilitate the creation of a highly accurate stiffness matrix,which is validated against the benchmark examples.To accommodate arbitrary curvature,a systematic transformation technique is established to approximate the intricate curves with a series of circular arcs.The numerical findings indicate that increasing the number of arc segments enhances accuracy,approaching the exact solutions.The analysis of free vibrations is conducted for both circular and non-circular beams.Mass matrices are derived using two methods:lumped mass and consistent mass,where the latter is based on the interpolation functions.The effectiveness of the proposed method is confirmed through the comparisons with the existing literature,demonstrating strong agreement.Finally,several practical cases involving beams with diverse curvature profiles are analyzed.Both natural frequencies and mode shapes are determined,providing significant insights into the dynamic behavior of these structures.This research offers a dependable and efficient analytical framework for the vibrational analysis of complex curved beams,with promising implications for structural and mechanical engineering.
基金Supported by European Union-NextGenerationEU,Through The National Recovery and Resilience Plan of the Republic of Bulgaria,No.BG-RRP-2.004-0008.
文摘This opinion review paper explores the application of artificial intelligence(AI)as a decisive tool in managing complex coronavirus disease 2019(COVID-19)cases within critical care medicine.Available data have shown that very severe cases required intensive care,most of which required endotracheal intubation and mechanical ventilation to avoid a lethal outcome if possible.The unprecedented challenges posed by the COVID-19 pandemic necessitate innovative approaches to patient care.AI offers significant potential in enhancing diagnostic accuracy,predicting patient outcomes,and optimizing treatment strategies.By analyzing vast amounts of clinical data,AI can support healthcare professionals in making informed decisions,thus improving patient outcomes.We also focus on current technologies,their implementation in critical care settings,and their impact on patient management during the COVID-19 crisis.Future directions for AI integration in critical care are also discussed.
基金supported by the National Key R&D Program of China(Grant Nos.2024YFA140850,2022YFA1403601,and 2023YFC2410501)the National Natural Science Foundation of China(Grants Nos.12241402,12474059,12274203,12374113,and 12274204)。
文摘Higher-order topological insulators,which host topologically protected states at boundaries that are at least two dimensions lower than the bulk,are an emerging class of topological materials.They provide great opportunities for exploring novel topological phenomena and fascinating applications.Utilizing a low-temperature scanning tunneling microscope,we construct breathing-kagome lattices with Fe adatoms on Ag(111)and investigate their electronic properties.We observe the higher-order topological boundary states in the topological phase but not in the trivial one,which is consistent with the theory.These states are found to be robust against the removal of bulk or edge adatoms.Further,we show the arbitrary positioning of these states either at corner,edge,or bulk sites by slightly modifying their neighbors.Our study not only demonstrates the formation and robustness of the electronic higher-order topological boundary states in real atomic systems but also provides a route for controlling their positions.
