This study is aimed to discover the explicitation and implicitation of connectives in literature translation. Based on parallel corpus, two Chinese versions of Jane Eyre are studied from three aspects, Intra-language ...This study is aimed to discover the explicitation and implicitation of connectives in literature translation. Based on parallel corpus, two Chinese versions of Jane Eyre are studied from three aspects, Intra-language comparison, inter-language comparison and case study. The findings in the study prove the reliability of Blum-Kulka's(1986) famous explicitation hypothesis, and its possible motivations are fully explored as well.展开更多
This study analyzes the potential impact of EU carbon border regulation mechanism(CBAM)on the export of China’s carbon-intensive products.First,we summarized the main content of the CBAM.Next,based on the input-outpu...This study analyzes the potential impact of EU carbon border regulation mechanism(CBAM)on the export of China’s carbon-intensive products.First,we summarized the main content of the CBAM.Next,based on the input-output theory,this study proposes a calculation model for the implicit carbon emissions and indirect carbon emissions from electricity consumption in export products and presents the corresponding calculation results.Based on the scenario analysis method,six carbon tariffscenarios were designed to evaluate the impact of the CBAM on the major export sectors under each scenario.The results showed that in 2021,the implicit carbon emissions in all products exported to Europe from China were approximately 375 million tons,of which the indirect carbon emissions from electricity were approximately 41.8 million tons,accounting for more than 10%.According to the current levy plan,China is expected to be subject to carbon tariffs of approximately USD 1.4 billion,accounting for 0.3%of its total export value to Europe in 2021.Finally,to reduce the adverse effects of CBAM,four measures were proposed from the perspective of the power industry.展开更多
Aiming at the problem that the data in the user rating matrix is missing and the importance of implicit trust between users is ignored when using the TrustSVD model to fill it,this paper proposes a recommendation algo...Aiming at the problem that the data in the user rating matrix is missing and the importance of implicit trust between users is ignored when using the TrustSVD model to fill it,this paper proposes a recommendation algorithm based on TrustSVD++and XGBoost.Firstly,the explicit trust and implicit trust were introduced into the SVD++model to construct the TrustSVD++model.Secondly,considering that there is much data in the interaction matrix after filling,which may lead to a rather complex calculation process,the K-means algorithm is introduced to cluster and extract user and item features at the same time.Then,in order to improve the accuracy of rating prediction for target users,an XGBoost model is proposed to train user and item features,and finally,it is verified on the data sets MovieLens-1M and MovieLens-100k.Experiments show that compared with the SVD++model and the recommendation algorithm without XGBoost model training,the proposed algorithm has the RMSE value reduced by 2.9%and the MAE value reduced by 3%.展开更多
We propose a suite of strategies for the parallel solution of fully implicit monolithic fluid-structure interaction(FSI).The solver is based on a modeling approach that uses the velocity and pressure as the primitive ...We propose a suite of strategies for the parallel solution of fully implicit monolithic fluid-structure interaction(FSI).The solver is based on a modeling approach that uses the velocity and pressure as the primitive variables,which offers a bridge between computational fluid dynamics(CFD)and computational structural dynamics.The spatiotemporal discretization leverages the variational multiscale formulation and the generalized-αmethod as a means of providing a robust discrete scheme.In particular,the time integration scheme does not suffer from the overshoot phenomenon and optimally dissipates high-frequency spurious modes in both subproblems of FSI.Based on the chosen fully implicit scheme,we systematically develop a combined suite of nonlinear and linear solver strategies.Invoking a block factorization of the Jacobian matrix,the Newton-Raphson procedure is reduced to solving two smaller linear systems in the multi-corrector stage.The first is of the elliptic type,indicating that the algebraic multigrid method serves as a well-suited option.The second exhibits a two-by-two block structure that is analogous to the system arising in CFD.Inspired by prior studies,the additive Schwarz domain decomposition method and the block-factorization-based preconditioners are invoked to address the linear problem.Since the number of unknowns matches in both subdomains,it is straightforward to balance loads when parallelizing the algorithm for distributed-memory architectures.We use two representative FSI benchmarks to demonstrate the robustness,efficiency,and scalability of the overall FSI solver framework.In particular,it is found that the developed FSI solver is comparable to the CFD solver in several aspects,including fixed-size and isogranular scalability as well as robustness.展开更多
Realistic human reconstruction embraces an extensive range of applications as depth sensors advance.However,current stateof-the-art methods with RGB-D input still suffer from artefacts,such as noisy surfaces,non-human...Realistic human reconstruction embraces an extensive range of applications as depth sensors advance.However,current stateof-the-art methods with RGB-D input still suffer from artefacts,such as noisy surfaces,non-human shapes,and depth ambiguity,especially for the invisible parts.The authors observe the main issue is the lack of geometric semantics without using depth input priors fully.This paper focuses on improving the representation ability of implicit function,exploring an effective method to utilise depth-related semantics effectively and efficiently.The proposed geometry-enhanced implicit function enhances the geometric semantics with the extra voxel-aligned features from point clouds,promoting the completion of missing parts for unseen regions while preserving the local details on the input.For incorporating multi-scale pixel-aligned and voxelaligned features,the authors use the Squeeze-and-Excitation attention to capture and fully use channel interdependencies.For the multi-view reconstruction,the proposed depth-enhanced attention explicitly excites the network to“sense”the geometric structure for a more reasonable feature aggregation.Experiments and results show that our method outperforms current RGB and depth-based SOTA methods on the challenging data from Twindom and Thuman3.0,and achieves a detailed and completed human reconstruction,balancing performance and efficiency well.展开更多
Computed Tomography(CT)reconstruction is essential inmedical imaging and other engineering fields.However,blurring of the projection during CT imaging can lead to artifacts in the reconstructed images.Projection blur ...Computed Tomography(CT)reconstruction is essential inmedical imaging and other engineering fields.However,blurring of the projection during CT imaging can lead to artifacts in the reconstructed images.Projection blur combines factors such as larger ray sources,scattering and imaging system vibration.To address the problem,we propose DeblurTomo,a novel self-supervised learning-based deblurring and reconstruction algorithm that efficiently reconstructs sharp CT images from blurry input without needing external data and blur measurement.Specifically,we constructed a coordinate-based implicit neural representation reconstruction network,which can map the coordinates to the attenuation coefficient in the reconstructed space formore convenient ray representation.Then,wemodel the blur as aweighted sumof offset rays and design the RayCorrectionNetwork(RCN)andWeight ProposalNetwork(WPN)to fit these rays and their weights bymulti-view consistency and geometric information,thereby extending 2D deblurring to 3D space.In the training phase,we use the blurry input as the supervision signal to optimize the reconstruction network,the RCN,and the WPN simultaneously.Extensive experiments on the widely used synthetic dataset show that DeblurTomo performs superiorly on the limited-angle and sparse-view in the simulated blurred scenarios.Further experiments on real datasets demonstrate the superiority of our method in practical scenarios.展开更多
Imputation of missing data has long been an important topic and an essential application for intelligent transportation systems(ITS)in the real world.As a state-of-the-art generative model,the diffusion model has prov...Imputation of missing data has long been an important topic and an essential application for intelligent transportation systems(ITS)in the real world.As a state-of-the-art generative model,the diffusion model has proven highly successful in image generation,speech generation,time series modelling etc.and now opens a new avenue for traffic data imputation.In this paper,we propose a conditional diffusion model,called the implicit-explicit diffusion model,for traffic data imputation.This model exploits both the implicit and explicit feature of the data simultaneously.More specifically,we design two types of feature extraction modules,one to capture the implicit dependencies hidden in the raw data at multiple time scales and the other to obtain the long-term temporal dependencies of the time series.This approach not only inherits the advantages of the diffusion model for estimating missing data,but also takes into account the multiscale correlation inherent in traffic data.To illustrate the performance of the model,extensive experiments are conducted on three real-world time series datasets using different missing rates.The experimental results demonstrate that the model improves imputation accuracy and generalization capability.展开更多
The accuracy of numerical computation heavily relies on appropriate meshing,whichserves as the foundation for numerical computation.Although adaptive refinement methods areavailable,an adaptive numerical solution is l...The accuracy of numerical computation heavily relies on appropriate meshing,whichserves as the foundation for numerical computation.Although adaptive refinement methods areavailable,an adaptive numerical solution is likely to be ineffective if it originates from a poorly ini-tial mesh.Therefore,it is crucial to generate meshes that accurately capture the geometric features.As an indispensable input in meshing methods,the Mesh Size Function(MSF)determines the qual-ity of the generated mesh.However,the current generation of MSF involves human participation tospecify numerous parameters,leading to difficulties in practical usage.Considering the capacity ofmachine learning to reveal the latent relationships within data,this paper proposes a novel machinelearning method,Implicit Geometry Neural Network(IGNN),for automatic prediction of appro-priate MSFs based on the existing mesh data,enabling the generation of unstructured meshes thatalign precisely with geometric features.IGNN employs the generative adversarial theory to learnthe mapping between the implicit representation of the geometry(Signed Distance Function,SDF)and the corresponding MSF.Experimental results show that the proposed method is capableof automatically generating appropriate meshes and achieving comparable meshing results com-pared to traditional methods.This paper demonstrates the possibility of significantly decreasingthe workload of mesh generation using machine learning techniques,and it is expected to increasethe automation level of mesh generation.展开更多
Although conventional object detection methods achieve high accuracy through extensively annotated datasets,acquiring such large-scale labeled data remains challenging and cost-prohibitive in numerous real-world appli...Although conventional object detection methods achieve high accuracy through extensively annotated datasets,acquiring such large-scale labeled data remains challenging and cost-prohibitive in numerous real-world applications.Few-shot object detection presents a new research idea that aims to localize and classify objects in images using only limited annotated examples.However,the inherent challenge in few-shot object detection lies in the insufficient sample diversity to fully characterize the sample feature distribution,which consequently impacts model performance.Inspired by contrastive learning principles,we propose an Implicit Feature Contrastive Learning(IFCL)module to address this limitation and augment feature diversity for more robust representational learning.This module generates augmented support sample features in a mixed feature space and implicitly contrasts them with query Region of Interest(RoI)features.This approach facilitates more comprehensive learning of both intra-class feature similarity and inter-class feature diversity,thereby enhancing the model’s object classification and localization capabilities.Extensive experiments on PASCAL VOC show that our method achieves a respective improvement of 3.2%,1.8%,and 2.3%on 10-shot of three Novel Sets compared to the baseline model FPD.展开更多
Square piles of reinforced concrete(RC)in marine environments are susceptible to chloride-inducedcorrosion.A novel reverse-seepage technique(RST)is applied to square piles to block the intrusion of chlorides.Thisresea...Square piles of reinforced concrete(RC)in marine environments are susceptible to chloride-inducedcorrosion.A novel reverse-seepage technique(RST)is applied to square piles to block the intrusion of chlorides.Thisresearch introduces a computational model designed to predict the lifespan of corrosion initiation in reinforced concretesquare piles when applied reverse-seepage pressure.The model considers the impacts of chloride binding and the tripletime-dependence property among the permeability,the corrected surface chloride concentration,and the diffusioncoefficient.The proposed numerical model is solved using the alternating direction implicit(ADI)approach,and itsaccuracy and reliability are evaluated by contrasting the computational outcomes with the analytical solution andexperimental results.Furthermore,the primary factors contributing to the corrosion of reinforced concrete square pilesare analyzed.The results indicate that applying RST can decrease the chloride penetration depth and prolong the lifespanof corrosion initiation in square piles.The water-cement ratio and reverse seepage pressure are the most influentialfactors.A water pressure of 0.4 MPa can double the life of concrete,and the durable life of concrete with a water-cementratio of 0.3 can reach 100 years.展开更多
Graphene-based frameworks suffer from a low quantum capacitance due to graphene’s Dirac point at the Fermi level.This theoretical study investigated the effect structural defects,nitrogen and boron doping,and surface...Graphene-based frameworks suffer from a low quantum capacitance due to graphene’s Dirac point at the Fermi level.This theoretical study investigated the effect structural defects,nitrogen and boron doping,and surface epoxy/hydroxy groups have on the electronic structure and capacitance of graphene.Density functional theory calculations reveal that the lowest energy configurations for nitrogen or boron substitutional doping occur when the dopant atoms are segregated.This elucidates why the magnetic transition for nitrogen doping is experimentally only observed at higher doping levels.We also highlight that the lowest energy configuration for a single vacancy defect is magnetic.Joint density functional theory calculations show that the fixed band approximation becomes increasingly inaccurate for electrolytes with lower dielectric constants.The introduction of structural defects rather than nitrogen or boron substitutional doping,or the introduction of adatoms leads to the largest increase in density of states and capacitance around graphene’s Dirac point.However,the presence of adatoms or substitutional doping leads to a larger shift of the potential of zero charge away from graphene’s Dirac point.展开更多
Integrable systems play a crucial role in physics and mathematics.In particular,the traditional(1+1)-dimensional and(2+1)-dimensional integrable systems have received significant attention due to the rarity of integra...Integrable systems play a crucial role in physics and mathematics.In particular,the traditional(1+1)-dimensional and(2+1)-dimensional integrable systems have received significant attention due to the rarity of integrable systems in higher dimensions.Recent studies have shown that abundant higher-dimensional integrable systems can be constructed from(1+1)-dimensional integrable systems by using a deformation algorithm.Here we establish a new(2+1)-dimensional Chen-Lee-Liu(C-L-L)equation using the deformation algorithm from the(1+1)-dimensional C-L-L equation.The new system is integrable with its Lax pair obtained by applying the deformation algorithm to that of the(1+1)-dimension.It is challenging to obtain the exact solutions for the new integrable system because the new system combines both the original C-L-L equation and its reciprocal transformation.The traveling wave solutions are derived in implicit function expression,and some asymmetry peakon solutions are found.展开更多
Three-dimensional surfaces are typically modeled as implicit surfaces.However,direct rendering of implicit surfaces is not simple,especially when such surfaces contain finely detailed shapes.One approach is ray-castin...Three-dimensional surfaces are typically modeled as implicit surfaces.However,direct rendering of implicit surfaces is not simple,especially when such surfaces contain finely detailed shapes.One approach is ray-casting,where the field of the implicit surface is assumed to be piecewise polynomials defined on the grid of a rectangular domain.A critical issue for direct rendering based on ray-casting is the computational cost of finding intersections between surfaces and rays.In particular,ray-casting requires many function evaluations along each ray,severely slowing the rendering speed.In this paper,a method is proposed to achieve direct rendering of polynomial-based implicit surfaces in real-time by strategically narrowing the search range and designing the shader to exploit the structure of piecewise polynomials.In experiments,the proposed method achieved a high framerate performance for different test cases,with a speed-up factor ranging from 1.1 to 218.2.In addition,the proposed method demonstrated better efficiency with high cell resolution.In terms of memory consumption,the proposed method saved between 90.94%and 99.64%in different test cases.Generally,the proposed method became more memory-efficient as the cell resolution increased.展开更多
Electron emission plays a dominant role in plasma-cathode interactions and is a key factor in many plasma phenomena and industrial applications.It is necessary to illustrate the various electron emission mechanisms an...Electron emission plays a dominant role in plasma-cathode interactions and is a key factor in many plasma phenomena and industrial applications.It is necessary to illustrate the various electron emission mechanisms and the corresponding applicable description models to evaluate their impacts on discharge properties.In this study,detailed expressions of the simplified formulas valid for field emission to thermo-field emission to thermionic emission typically used in the numerical simulation are proposed,and the corresponding application ranges are determined in the framework of the Murphy-Good theory,which is commonly regarded as the general model and to be accurate in the full range of conditions of the validity of the theory.Dimensionless parameterization was used to evaluate the emission current density of the Murphy-Good formula,and a deviation factor was defined to obtain the application ranges for different work functions(2.5‒5 eV),cathode temperatures(300‒6000 K),and emitted electric fields(10^(5) to 10^(10) V·m^(-1)).The deviation factor was shown to be a nonmonotonic function of the three parameters.A comparative study of particle number densities in atmospheric gas discharge with a tungsten cathode was performed based on the one-dimensional implicit particle-in-cell(PIC)with the Monte Carlo collision(MCC)method according to the aforementioned application ranges.It was found that small differences in emission current density can lead to variations in the distributions of particle number density due to changes in the collisional environment.This study provides a theoretical basis for selecting emission models for subsequent numerical simulations.展开更多
We propose a simple embedding method for computing the eigenvalues and eigenfunctions of the Laplace-Beltrami operator on implicit surfaces.The approach follows an embedding approach for solving the surface eikonal eq...We propose a simple embedding method for computing the eigenvalues and eigenfunctions of the Laplace-Beltrami operator on implicit surfaces.The approach follows an embedding approach for solving the surface eikonal equation.We replace the differential operator on the interface with a typical Cartesian differential operator in the surface neighborhood.Our proposed algorithm is easy to implement and efficient.We will give some two-and three-dimensional numerical examples to demonstrate the effectiveness of our proposed approach.展开更多
Anticipating others’actions is innate and essential in order for humans to navigate and interact well with others in dense crowds.This ability is urgently required for unmanned systems such as service robots and self...Anticipating others’actions is innate and essential in order for humans to navigate and interact well with others in dense crowds.This ability is urgently required for unmanned systems such as service robots and self-driving cars.However,existing solutions struggle to predict pedestrian anticipation accurately,because the influence of group-related social behaviors has not been well considered.While group relationships and group interactions are ubiquitous and significantly influence pedestrian anticipation,their influence is diverse and subtle,making it difficult to explicitly quantify.Here,we propose the group interaction field(GIF),a novel group-aware representation that quantifies pedestrian anticipation into a probability field of pedestrians’future locations and attention orientations.An end-to-end neural network,GIFNet,is tailored to estimate the GIF from explicit multidimensional observations.GIFNet quantifies the influence of group behaviors by formulating a group interaction graph with propagation and graph attention that is adaptive to the group size and dynamic interaction states.The experimental results show that the GIF effectively represents the change in pedestrians’anticipation under the prominent impact of group behaviors and accurately predicts pedestrians’future states.Moreover,the GIF contributes to explaining various predictions of pedestrians’behavior in different social states.The proposed GIF will eventually be able to allow unmanned systems to work in a human-like manner and comply with social norms,thereby promoting harmonious human-machine relationships.展开更多
In comparison to discrete descriptions of fracture process,the recently proposed phase field methodology averts the numerical tracking strategy of discontinuities in solids,which enables the numerical implement simpli...In comparison to discrete descriptions of fracture process,the recently proposed phase field methodology averts the numerical tracking strategy of discontinuities in solids,which enables the numerical implement simplification.An implicit finite element formulation based on the diffuse phase field is extended for stable and efficient analysis of complex dynamic fracture process in ductile solids.This exhibited formulation is shown to capture entire range of the characteristics of ductile material presenting J2-plasticity,embracing plasticization,cracks initiation,propagation,branching and merging while fulfilling the basic principle of thermodynamics.Herein,we implement a staggered time integration scheme of the dynamic elasto-plastic phase field method into the commercial finite element code.The numerical performance of the present advanced phase field model has been examined through several classic dynamic fracture benchmarks,and in all cases simulation results are in good agreement with the associated experimental data and other numerical results in previous literature.展开更多
Due to the coupling between the hydrodynamic equation and the phase-field equation in two-phase incompressible flows,it is desirable to develop efficient and high-order accurate numerical schemes that can decouple the...Due to the coupling between the hydrodynamic equation and the phase-field equation in two-phase incompressible flows,it is desirable to develop efficient and high-order accurate numerical schemes that can decouple these two equations.One popular and efficient strategy is to add an explicit stabilizing term to the convective velocity in the phase-field equation to decouple them.The resulting schemes are only first-order accurate in time,and it seems extremely difficult to generalize the idea of stabilization to the second-order or higher version.In this paper,we employ the spectral deferred correction method to improve the temporal accuracy,based on the first-order decoupled and energy-stable scheme constructed by the stabilization idea.The novelty lies in how the decoupling and linear implicit properties are maintained to improve the efficiency.Within the framework of the spatially discretized local discontinuous Galerkin method,the resulting numerical schemes are fully decoupled,efficient,and high-order accurate in both time and space.Numerical experiments are performed to validate the high-order accuracy and efficiency of the methods for solving phase-field models of two-phase incompressible flows.展开更多
BACKGROUND Panic disorder(PD)involves emotion dysregulation,but its underlying mechanisms remain poorly understood.Previous research suggests that implicit emotion regulation may play a central role in PD-related emot...BACKGROUND Panic disorder(PD)involves emotion dysregulation,but its underlying mechanisms remain poorly understood.Previous research suggests that implicit emotion regulation may play a central role in PD-related emotion dysregulation and symptom maintenance.However,there is a lack of studies exploring the neural mechanisms of implicit emotion regulation in PD using neurophysiological indicators.AIM To study the neural mechanisms of implicit emotion regulation in PD with eventrelated potentials(ERP).METHODS A total of 25 PD patients and 20 healthy controls(HC)underwent clinical evaluations.The study utilized a case-control design with random sampling,selecting participants for the case group from March to December 2018.Participants performed an affect labeling task,using affect labeling as the experimental condition and gender labeling as the control condition.ERP and behavioral data were recorded to compare the late positive potential(LPP)within and between the groups.RESULTS Both PD and HC groups showed longer reaction times and decreased accuracy under the affect labeling.In the HC group,late LPP amplitudes exhibited a dynamic pattern of initial increase followed by decrease.Importantly,a significant group×condition interaction effect was observed.Simple effect analysis revealed a reduction in the differences of late LPP amplitudes between the affect labeling and gender labeling conditions in the PD group compared to the HC group.Furthermore,among PD patients under the affect labeling,the late LPP was negatively correlated with disease severity,symptom frequency,and intensity.CONCLUSION PD patients demonstrate abnormalities in implicit emotion regulation,hampering their ability to mobilize cognitive resources for downregulating negative emotions.The late LPP amplitude in response to affect labeling may serve as a potentially valuable clinical indicator of PD severity.展开更多
To enhance the stability of helicopter maneuvers during task execution,a composite trajectory tracking controller design based on the implicit model(IM)and linear active disturbance rejection control(LADRC)is proposed...To enhance the stability of helicopter maneuvers during task execution,a composite trajectory tracking controller design based on the implicit model(IM)and linear active disturbance rejection control(LADRC)is proposed.Initially,aerodynamic models of the main and tail rotor are created using the blade element theory and the uniform inflow assumption.Subsequently,a comprehensive flight dynamic model of the helicopter is established through fitting aerodynamic force fitting.Subsequently,for precise helicopter maneuvering,including the spiral,spiral up,and Ranversman maneuver,a regular trim is undertaken,followed by minor perturbation linearization at the trim point.Utilizing the linearized model,controllers are created for the IM attitude inner loop and LADRC position outer loop of the helicopter.Ultimately,a comparison is made between the maneuver trajectory tracking results of the IM‑LADRC and the conventional proportional-integral-derivative(PID)control method is performed.Experimental results demonstrate that utilizing the post-trim minor perturbation linearized model in combination with the IM‑LADRC method can achieve higher precision in tracking results,thus enhancing the accuracy of helicopter maneuver execution.展开更多
文摘This study is aimed to discover the explicitation and implicitation of connectives in literature translation. Based on parallel corpus, two Chinese versions of Jane Eyre are studied from three aspects, Intra-language comparison, inter-language comparison and case study. The findings in the study prove the reliability of Blum-Kulka's(1986) famous explicitation hypothesis, and its possible motivations are fully explored as well.
文摘This study analyzes the potential impact of EU carbon border regulation mechanism(CBAM)on the export of China’s carbon-intensive products.First,we summarized the main content of the CBAM.Next,based on the input-output theory,this study proposes a calculation model for the implicit carbon emissions and indirect carbon emissions from electricity consumption in export products and presents the corresponding calculation results.Based on the scenario analysis method,six carbon tariffscenarios were designed to evaluate the impact of the CBAM on the major export sectors under each scenario.The results showed that in 2021,the implicit carbon emissions in all products exported to Europe from China were approximately 375 million tons,of which the indirect carbon emissions from electricity were approximately 41.8 million tons,accounting for more than 10%.According to the current levy plan,China is expected to be subject to carbon tariffs of approximately USD 1.4 billion,accounting for 0.3%of its total export value to Europe in 2021.Finally,to reduce the adverse effects of CBAM,four measures were proposed from the perspective of the power industry.
基金Guangdong Science and Technology University Young Projects(GKY-2023KYQNK-1 and GKY-2023KYQNK-10)Guangdong Provincial Key Discipline Research Capacity Improvement Project(2022ZDJS147)。
文摘Aiming at the problem that the data in the user rating matrix is missing and the importance of implicit trust between users is ignored when using the TrustSVD model to fill it,this paper proposes a recommendation algorithm based on TrustSVD++and XGBoost.Firstly,the explicit trust and implicit trust were introduced into the SVD++model to construct the TrustSVD++model.Secondly,considering that there is much data in the interaction matrix after filling,which may lead to a rather complex calculation process,the K-means algorithm is introduced to cluster and extract user and item features at the same time.Then,in order to improve the accuracy of rating prediction for target users,an XGBoost model is proposed to train user and item features,and finally,it is verified on the data sets MovieLens-1M and MovieLens-100k.Experiments show that compared with the SVD++model and the recommendation algorithm without XGBoost model training,the proposed algorithm has the RMSE value reduced by 2.9%and the MAE value reduced by 3%.
基金This work was supported by the National Natural Science Foundation of China(Grant No.12172160)Shenzhen Science and Technology Program(Grant No.JCYJ20220818100600002)+1 种基金South-ern University of Science and Technology(Grant No.Y01326127)the Department of Science and Technology of Guangdong Province(Grant Nos.2020B1212030001 and 2021QN020642).
文摘We propose a suite of strategies for the parallel solution of fully implicit monolithic fluid-structure interaction(FSI).The solver is based on a modeling approach that uses the velocity and pressure as the primitive variables,which offers a bridge between computational fluid dynamics(CFD)and computational structural dynamics.The spatiotemporal discretization leverages the variational multiscale formulation and the generalized-αmethod as a means of providing a robust discrete scheme.In particular,the time integration scheme does not suffer from the overshoot phenomenon and optimally dissipates high-frequency spurious modes in both subproblems of FSI.Based on the chosen fully implicit scheme,we systematically develop a combined suite of nonlinear and linear solver strategies.Invoking a block factorization of the Jacobian matrix,the Newton-Raphson procedure is reduced to solving two smaller linear systems in the multi-corrector stage.The first is of the elliptic type,indicating that the algebraic multigrid method serves as a well-suited option.The second exhibits a two-by-two block structure that is analogous to the system arising in CFD.Inspired by prior studies,the additive Schwarz domain decomposition method and the block-factorization-based preconditioners are invoked to address the linear problem.Since the number of unknowns matches in both subdomains,it is straightforward to balance loads when parallelizing the algorithm for distributed-memory architectures.We use two representative FSI benchmarks to demonstrate the robustness,efficiency,and scalability of the overall FSI solver framework.In particular,it is found that the developed FSI solver is comparable to the CFD solver in several aspects,including fixed-size and isogranular scalability as well as robustness.
基金supported by the National Key R&D Programme of China(2022YFF0902200).
文摘Realistic human reconstruction embraces an extensive range of applications as depth sensors advance.However,current stateof-the-art methods with RGB-D input still suffer from artefacts,such as noisy surfaces,non-human shapes,and depth ambiguity,especially for the invisible parts.The authors observe the main issue is the lack of geometric semantics without using depth input priors fully.This paper focuses on improving the representation ability of implicit function,exploring an effective method to utilise depth-related semantics effectively and efficiently.The proposed geometry-enhanced implicit function enhances the geometric semantics with the extra voxel-aligned features from point clouds,promoting the completion of missing parts for unseen regions while preserving the local details on the input.For incorporating multi-scale pixel-aligned and voxelaligned features,the authors use the Squeeze-and-Excitation attention to capture and fully use channel interdependencies.For the multi-view reconstruction,the proposed depth-enhanced attention explicitly excites the network to“sense”the geometric structure for a more reasonable feature aggregation.Experiments and results show that our method outperforms current RGB and depth-based SOTA methods on the challenging data from Twindom and Thuman3.0,and achieves a detailed and completed human reconstruction,balancing performance and efficiency well.
基金supported in part by the National Natural Science Foundation of China under Grants 62472434 and 62402171in part by the National Key Research and Development Program of China under Grant 2022YFF1203001+1 种基金in part by the Science and Technology Innovation Program of Hunan Province under Grant 2022RC3061in part by the Sci-Tech Innovation 2030 Agenda under Grant 2023ZD0508600.
文摘Computed Tomography(CT)reconstruction is essential inmedical imaging and other engineering fields.However,blurring of the projection during CT imaging can lead to artifacts in the reconstructed images.Projection blur combines factors such as larger ray sources,scattering and imaging system vibration.To address the problem,we propose DeblurTomo,a novel self-supervised learning-based deblurring and reconstruction algorithm that efficiently reconstructs sharp CT images from blurry input without needing external data and blur measurement.Specifically,we constructed a coordinate-based implicit neural representation reconstruction network,which can map the coordinates to the attenuation coefficient in the reconstructed space formore convenient ray representation.Then,wemodel the blur as aweighted sumof offset rays and design the RayCorrectionNetwork(RCN)andWeight ProposalNetwork(WPN)to fit these rays and their weights bymulti-view consistency and geometric information,thereby extending 2D deblurring to 3D space.In the training phase,we use the blurry input as the supervision signal to optimize the reconstruction network,the RCN,and the WPN simultaneously.Extensive experiments on the widely used synthetic dataset show that DeblurTomo performs superiorly on the limited-angle and sparse-view in the simulated blurred scenarios.Further experiments on real datasets demonstrate the superiority of our method in practical scenarios.
基金partially supported by the National Natural Science Foundation of China(62271485)the SDHS Science and Technology Project(HS2023B044)
文摘Imputation of missing data has long been an important topic and an essential application for intelligent transportation systems(ITS)in the real world.As a state-of-the-art generative model,the diffusion model has proven highly successful in image generation,speech generation,time series modelling etc.and now opens a new avenue for traffic data imputation.In this paper,we propose a conditional diffusion model,called the implicit-explicit diffusion model,for traffic data imputation.This model exploits both the implicit and explicit feature of the data simultaneously.More specifically,we design two types of feature extraction modules,one to capture the implicit dependencies hidden in the raw data at multiple time scales and the other to obtain the long-term temporal dependencies of the time series.This approach not only inherits the advantages of the diffusion model for estimating missing data,but also takes into account the multiscale correlation inherent in traffic data.To illustrate the performance of the model,extensive experiments are conducted on three real-world time series datasets using different missing rates.The experimental results demonstrate that the model improves imputation accuracy and generalization capability.
基金co-supported by the Aeronautical Science Foundation of China(Nos.2018ZA52002 and 2019ZA052011)。
文摘The accuracy of numerical computation heavily relies on appropriate meshing,whichserves as the foundation for numerical computation.Although adaptive refinement methods areavailable,an adaptive numerical solution is likely to be ineffective if it originates from a poorly ini-tial mesh.Therefore,it is crucial to generate meshes that accurately capture the geometric features.As an indispensable input in meshing methods,the Mesh Size Function(MSF)determines the qual-ity of the generated mesh.However,the current generation of MSF involves human participation tospecify numerous parameters,leading to difficulties in practical usage.Considering the capacity ofmachine learning to reveal the latent relationships within data,this paper proposes a novel machinelearning method,Implicit Geometry Neural Network(IGNN),for automatic prediction of appro-priate MSFs based on the existing mesh data,enabling the generation of unstructured meshes thatalign precisely with geometric features.IGNN employs the generative adversarial theory to learnthe mapping between the implicit representation of the geometry(Signed Distance Function,SDF)and the corresponding MSF.Experimental results show that the proposed method is capableof automatically generating appropriate meshes and achieving comparable meshing results com-pared to traditional methods.This paper demonstrates the possibility of significantly decreasingthe workload of mesh generation using machine learning techniques,and it is expected to increasethe automation level of mesh generation.
基金funded by the China Chongqing Municipal Science and Technology Bureau,grant numbers CSTB2024TIAD-CYKJCXX0009,CSTB2024NSCQ-LZX0043,CSTB2022NSCQ-MSX0288Chongqing 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Although conventional object detection methods achieve high accuracy through extensively annotated datasets,acquiring such large-scale labeled data remains challenging and cost-prohibitive in numerous real-world applications.Few-shot object detection presents a new research idea that aims to localize and classify objects in images using only limited annotated examples.However,the inherent challenge in few-shot object detection lies in the insufficient sample diversity to fully characterize the sample feature distribution,which consequently impacts model performance.Inspired by contrastive learning principles,we propose an Implicit Feature Contrastive Learning(IFCL)module to address this limitation and augment feature diversity for more robust representational learning.This module generates augmented support sample features in a mixed feature space and implicitly contrasts them with query Region of Interest(RoI)features.This approach facilitates more comprehensive learning of both intra-class feature similarity and inter-class feature diversity,thereby enhancing the model’s object classification and localization capabilities.Extensive experiments on PASCAL VOC show that our method achieves a respective improvement of 3.2%,1.8%,and 2.3%on 10-shot of three Novel Sets compared to the baseline model FPD.
基金Projects(52178371,52108355,52178321)supported by the National Natural Science Foundation of ChinaProject(202305)supported by the Research Project of Engineering Research Centre of Rock-Soil Drilling&Excavation and Protection,Ministry of Education,China。
文摘Square piles of reinforced concrete(RC)in marine environments are susceptible to chloride-inducedcorrosion.A novel reverse-seepage technique(RST)is applied to square piles to block the intrusion of chlorides.Thisresearch introduces a computational model designed to predict the lifespan of corrosion initiation in reinforced concretesquare piles when applied reverse-seepage pressure.The model considers the impacts of chloride binding and the tripletime-dependence property among the permeability,the corrected surface chloride concentration,and the diffusioncoefficient.The proposed numerical model is solved using the alternating direction implicit(ADI)approach,and itsaccuracy and reliability are evaluated by contrasting the computational outcomes with the analytical solution andexperimental results.Furthermore,the primary factors contributing to the corrosion of reinforced concrete square pilesare analyzed.The results indicate that applying RST can decrease the chloride penetration depth and prolong the lifespanof corrosion initiation in square piles.The water-cement ratio and reverse seepage pressure are the most influentialfactors.A water pressure of 0.4 MPa can double the life of concrete,and the durable life of concrete with a water-cementratio of 0.3 can reach 100 years.
基金supported partially by JST SICORP(Grant No.JPMJSC2112)JST Adaptable and Seamless Technology Transfer Program through Target-driven R&D(A-STEP)(Grant No.JPMJTR22T6),and JSPS KAKENHI(Grant No.22K14757)+1 种基金Calculations were performed using the U.K.National Supercomputing Facility ARCHER2(http://www.archer2.ac.uk)via our membership of the U.K.’s HEC Materials Chemistry Consortium,which is funded by the EPSRC(Grant Nos.EP/L000202 and EP/R029431)the Molecular Modelling Hub for computational resources,MMM Hub,which is partially funded by EPSRC(Grant No.EP/P020194/1).This research has also utilized Queen Mary’s Apocrita HPC facility,supported by QMUL Research-IT.
文摘Graphene-based frameworks suffer from a low quantum capacitance due to graphene’s Dirac point at the Fermi level.This theoretical study investigated the effect structural defects,nitrogen and boron doping,and surface epoxy/hydroxy groups have on the electronic structure and capacitance of graphene.Density functional theory calculations reveal that the lowest energy configurations for nitrogen or boron substitutional doping occur when the dopant atoms are segregated.This elucidates why the magnetic transition for nitrogen doping is experimentally only observed at higher doping levels.We also highlight that the lowest energy configuration for a single vacancy defect is magnetic.Joint density functional theory calculations show that the fixed band approximation becomes increasingly inaccurate for electrolytes with lower dielectric constants.The introduction of structural defects rather than nitrogen or boron substitutional doping,or the introduction of adatoms leads to the largest increase in density of states and capacitance around graphene’s Dirac point.However,the presence of adatoms or substitutional doping leads to a larger shift of the potential of zero charge away from graphene’s Dirac point.
基金Project supported by the National Natural Science Foundation of China (Grant Nos.12275144,12235007,and 11975131)K.C.Wong Magna Fund in Ningbo University。
文摘Integrable systems play a crucial role in physics and mathematics.In particular,the traditional(1+1)-dimensional and(2+1)-dimensional integrable systems have received significant attention due to the rarity of integrable systems in higher dimensions.Recent studies have shown that abundant higher-dimensional integrable systems can be constructed from(1+1)-dimensional integrable systems by using a deformation algorithm.Here we establish a new(2+1)-dimensional Chen-Lee-Liu(C-L-L)equation using the deformation algorithm from the(1+1)-dimensional C-L-L equation.The new system is integrable with its Lax pair obtained by applying the deformation algorithm to that of the(1+1)-dimension.It is challenging to obtain the exact solutions for the new integrable system because the new system combines both the original C-L-L equation and its reciprocal transformation.The traveling wave solutions are derived in implicit function expression,and some asymmetry peakon solutions are found.
基金supported by JSPS KAKENHI Grant Number 21K11928。
文摘Three-dimensional surfaces are typically modeled as implicit surfaces.However,direct rendering of implicit surfaces is not simple,especially when such surfaces contain finely detailed shapes.One approach is ray-casting,where the field of the implicit surface is assumed to be piecewise polynomials defined on the grid of a rectangular domain.A critical issue for direct rendering based on ray-casting is the computational cost of finding intersections between surfaces and rays.In particular,ray-casting requires many function evaluations along each ray,severely slowing the rendering speed.In this paper,a method is proposed to achieve direct rendering of polynomial-based implicit surfaces in real-time by strategically narrowing the search range and designing the shader to exploit the structure of piecewise polynomials.In experiments,the proposed method achieved a high framerate performance for different test cases,with a speed-up factor ranging from 1.1 to 218.2.In addition,the proposed method demonstrated better efficiency with high cell resolution.In terms of memory consumption,the proposed method saved between 90.94%and 99.64%in different test cases.Generally,the proposed method became more memory-efficient as the cell resolution increased.
基金supported in part by National Natural Science Foundation of China(Nos.52176087 and 52277164)Foundation for Innovative Research Groups of National Natural Science Foundation of China(No.51721004)+1 种基金Scientific Research Program Funded by Shaanxi Provincial Education Department(No.23JP115)Youth Innovation Team of Shaanxi Universities,in part by the Natural Science Basic Research Plan of Shaanxi Province(Nos.2021J Z-48 and 2020JM-462).
文摘Electron emission plays a dominant role in plasma-cathode interactions and is a key factor in many plasma phenomena and industrial applications.It is necessary to illustrate the various electron emission mechanisms and the corresponding applicable description models to evaluate their impacts on discharge properties.In this study,detailed expressions of the simplified formulas valid for field emission to thermo-field emission to thermionic emission typically used in the numerical simulation are proposed,and the corresponding application ranges are determined in the framework of the Murphy-Good theory,which is commonly regarded as the general model and to be accurate in the full range of conditions of the validity of the theory.Dimensionless parameterization was used to evaluate the emission current density of the Murphy-Good formula,and a deviation factor was defined to obtain the application ranges for different work functions(2.5‒5 eV),cathode temperatures(300‒6000 K),and emitted electric fields(10^(5) to 10^(10) V·m^(-1)).The deviation factor was shown to be a nonmonotonic function of the three parameters.A comparative study of particle number densities in atmospheric gas discharge with a tungsten cathode was performed based on the one-dimensional implicit particle-in-cell(PIC)with the Monte Carlo collision(MCC)method according to the aforementioned application ranges.It was found that small differences in emission current density can lead to variations in the distributions of particle number density due to changes in the collisional environment.This study provides a theoretical basis for selecting emission models for subsequent numerical simulations.
基金supported in part by the Hong Kong RGC 16302223.
文摘We propose a simple embedding method for computing the eigenvalues and eigenfunctions of the Laplace-Beltrami operator on implicit surfaces.The approach follows an embedding approach for solving the surface eikonal equation.We replace the differential operator on the interface with a typical Cartesian differential operator in the surface neighborhood.Our proposed algorithm is easy to implement and efficient.We will give some two-and three-dimensional numerical examples to demonstrate the effectiveness of our proposed approach.
基金supported in part by the National Natural Science Foundation of China (NSFC,62125106,61860206003,and 62088102)in part by the Ministry of Science and Technology of China (2021ZD0109901)in part by the Provincial Key Research and Development Program of Zhejiang (2021C01016).
文摘Anticipating others’actions is innate and essential in order for humans to navigate and interact well with others in dense crowds.This ability is urgently required for unmanned systems such as service robots and self-driving cars.However,existing solutions struggle to predict pedestrian anticipation accurately,because the influence of group-related social behaviors has not been well considered.While group relationships and group interactions are ubiquitous and significantly influence pedestrian anticipation,their influence is diverse and subtle,making it difficult to explicitly quantify.Here,we propose the group interaction field(GIF),a novel group-aware representation that quantifies pedestrian anticipation into a probability field of pedestrians’future locations and attention orientations.An end-to-end neural network,GIFNet,is tailored to estimate the GIF from explicit multidimensional observations.GIFNet quantifies the influence of group behaviors by formulating a group interaction graph with propagation and graph attention that is adaptive to the group size and dynamic interaction states.The experimental results show that the GIF effectively represents the change in pedestrians’anticipation under the prominent impact of group behaviors and accurately predicts pedestrians’future states.Moreover,the GIF contributes to explaining various predictions of pedestrians’behavior in different social states.The proposed GIF will eventually be able to allow unmanned systems to work in a human-like manner and comply with social norms,thereby promoting harmonious human-machine relationships.
基金supported by the Na⁃tional Natural Science Foundation of China(No.12302176).
文摘In comparison to discrete descriptions of fracture process,the recently proposed phase field methodology averts the numerical tracking strategy of discontinuities in solids,which enables the numerical implement simplification.An implicit finite element formulation based on the diffuse phase field is extended for stable and efficient analysis of complex dynamic fracture process in ductile solids.This exhibited formulation is shown to capture entire range of the characteristics of ductile material presenting J2-plasticity,embracing plasticization,cracks initiation,propagation,branching and merging while fulfilling the basic principle of thermodynamics.Herein,we implement a staggered time integration scheme of the dynamic elasto-plastic phase field method into the commercial finite element code.The numerical performance of the present advanced phase field model has been examined through several classic dynamic fracture benchmarks,and in all cases simulation results are in good agreement with the associated experimental data and other numerical results in previous literature.
基金supported by the NSFC Grant no.12271492the Natural Science Foundation of Henan Province of China Grant no.222300420550+1 种基金supported by the NSFC Grant no.12271498the National Key R&D Program of China Grant no.2022YFA1005202/2022YFA1005200.
文摘Due to the coupling between the hydrodynamic equation and the phase-field equation in two-phase incompressible flows,it is desirable to develop efficient and high-order accurate numerical schemes that can decouple these two equations.One popular and efficient strategy is to add an explicit stabilizing term to the convective velocity in the phase-field equation to decouple them.The resulting schemes are only first-order accurate in time,and it seems extremely difficult to generalize the idea of stabilization to the second-order or higher version.In this paper,we employ the spectral deferred correction method to improve the temporal accuracy,based on the first-order decoupled and energy-stable scheme constructed by the stabilization idea.The novelty lies in how the decoupling and linear implicit properties are maintained to improve the efficiency.Within the framework of the spatially discretized local discontinuous Galerkin method,the resulting numerical schemes are fully decoupled,efficient,and high-order accurate in both time and space.Numerical experiments are performed to validate the high-order accuracy and efficiency of the methods for solving phase-field models of two-phase incompressible flows.
基金Supported by The National Natural Science Foundation of China,No.81871080the Key R&D Program of Jining(Major Program),No.2023YXNS004+2 种基金the National Natural Science Foundation of China,No.81401486the Natural Science Foundation of Liaoning Province of China,No.20170540276the Medicine and Health Science Technology Development Program of Shandong Province,No.202003070713.
文摘BACKGROUND Panic disorder(PD)involves emotion dysregulation,but its underlying mechanisms remain poorly understood.Previous research suggests that implicit emotion regulation may play a central role in PD-related emotion dysregulation and symptom maintenance.However,there is a lack of studies exploring the neural mechanisms of implicit emotion regulation in PD using neurophysiological indicators.AIM To study the neural mechanisms of implicit emotion regulation in PD with eventrelated potentials(ERP).METHODS A total of 25 PD patients and 20 healthy controls(HC)underwent clinical evaluations.The study utilized a case-control design with random sampling,selecting participants for the case group from March to December 2018.Participants performed an affect labeling task,using affect labeling as the experimental condition and gender labeling as the control condition.ERP and behavioral data were recorded to compare the late positive potential(LPP)within and between the groups.RESULTS Both PD and HC groups showed longer reaction times and decreased accuracy under the affect labeling.In the HC group,late LPP amplitudes exhibited a dynamic pattern of initial increase followed by decrease.Importantly,a significant group×condition interaction effect was observed.Simple effect analysis revealed a reduction in the differences of late LPP amplitudes between the affect labeling and gender labeling conditions in the PD group compared to the HC group.Furthermore,among PD patients under the affect labeling,the late LPP was negatively correlated with disease severity,symptom frequency,and intensity.CONCLUSION PD patients demonstrate abnormalities in implicit emotion regulation,hampering their ability to mobilize cognitive resources for downregulating negative emotions.The late LPP amplitude in response to affect labeling may serve as a potentially valuable clinical indicator of PD severity.
基金supported in part by the National Natural Science Foundation of China(No.12032012)the Key Discipline Construction Project of Colleges and Universities in Jiangsu Province.
文摘To enhance the stability of helicopter maneuvers during task execution,a composite trajectory tracking controller design based on the implicit model(IM)and linear active disturbance rejection control(LADRC)is proposed.Initially,aerodynamic models of the main and tail rotor are created using the blade element theory and the uniform inflow assumption.Subsequently,a comprehensive flight dynamic model of the helicopter is established through fitting aerodynamic force fitting.Subsequently,for precise helicopter maneuvering,including the spiral,spiral up,and Ranversman maneuver,a regular trim is undertaken,followed by minor perturbation linearization at the trim point.Utilizing the linearized model,controllers are created for the IM attitude inner loop and LADRC position outer loop of the helicopter.Ultimately,a comparison is made between the maneuver trajectory tracking results of the IM‑LADRC and the conventional proportional-integral-derivative(PID)control method is performed.Experimental results demonstrate that utilizing the post-trim minor perturbation linearized model in combination with the IM‑LADRC method can achieve higher precision in tracking results,thus enhancing the accuracy of helicopter maneuver execution.
