Viscoelastic fluids due to their non-linear nature play an important role in process and polymer industries. These non-linear characteristics of fluid, influence final outcome of the product. Such processes though loo...Viscoelastic fluids due to their non-linear nature play an important role in process and polymer industries. These non-linear characteristics of fluid, influence final outcome of the product. Such processes though look simple are numerically challenging to study, due to the loss of numerical stability. Over the years, various methodologies have been developed to overcome this numerical limitation. In spite of this, numerical solutions are considered distant from accuracy, as first-order upwind-differencing scheme （UDS） is often employed for improving the stability of algorithm. To elude this effect, some works been reported in the past, where high-resolution-schemes （HRS） were employed and Deborah number was varied. However, these works are limited to creeping flows and do not detail any information on the numerical stability of HRS. Hence, this article presents the numerical study of high shearing contraction flows, where stability of HRS are addressed in reference to fluid elasticity. Results suggest that all I-IRS show some order of undue oscillations in flow variable profiles, measured along vertical lines placed near contraction region in the upstream section of domain, at varied elasticity number E ~ 5. Furthermore, by E, a clear relationship between numerical stability of HRS and E was obtained, which states that the order of undue oscillations in flow variable profiles is directly proportional to E.展开更多
Slope limiters play an essential role in maintaining the non-oscillatory behavior of high-resolution methods for nonlinear conservation laws.The family of minmod limiters serves as the prototype example.Here,we revisi...Slope limiters play an essential role in maintaining the non-oscillatory behavior of high-resolution methods for nonlinear conservation laws.The family of minmod limiters serves as the prototype example.Here,we revisit the question of non-oscillatory behavior of high-resolution central schemes in terms of the slope limiter proposed by van Albada et al.(Astron Astrophys 108:76–84,1982).The van Albada(vA)limiter is smoother near extrema,and consequently,in many cases,it outperforms the results obtained using the standard minmod limiter.In particular,we prove that the vA limiter ensures the one-dimensional Total-Variation Diminishing(TVD)stability and demonstrate that it yields noticeable improvement in computation of one-and two-dimensional systems.展开更多
Accurately counting dense objects in complex and diverse backgrounds is a significant challenge in computer vision,with applications ranging from crowd counting to various other object counting tasks.To address this,w...Accurately counting dense objects in complex and diverse backgrounds is a significant challenge in computer vision,with applications ranging from crowd counting to various other object counting tasks.To address this,we propose HUANNet(High-Resolution Unified Attention Network),a convolutional neural network designed to capture both local features and rich semantic information through a high-resolution representation learning framework,while optimizing computational distribution across parallel branches.HUANNet introduces three core modules:the High-Resolution Attention Module(HRAM),which enhances feature extraction by optimizing multiresolution feature fusion;the Unified Multi-Scale Attention Module(UMAM),which integrates spatial,channel,and convolutional kernel information through an attention mechanism applied across multiple levels of the network;and the Grid-Assisted Point Matching Module(GPMM),which stabilizes and improves point-to-point matching by leveraging grid-based mechanisms.Extensive experiments show that HUANNet achieves competitive results on the ShanghaiTech Part A/B crowd counting datasets and sets new state-of-the-art performance on dense object counting datasets such as CARPK and XRAY-IECCD,demonstrating the effectiveness and versatility of HUANNet.展开更多
Background:Diabetic foot,a severe complication of diabetes,is characterized by chronic refractory wounds.Sanhuang Oil,a topical herbal formula,demonstrates significant therapeutic effects including antibacterial,anti-...Background:Diabetic foot,a severe complication of diabetes,is characterized by chronic refractory wounds.Sanhuang Oil,a topical herbal formula,demonstrates significant therapeutic effects including antibacterial,anti-inflammatory,and immunomodulatory activities.However,its active constituents and mechanisms of action against diabetic foot remain to be elucidated.Methods:In this study,the chemical constituents of Sanhuang Oil were identified using UPLC-QE-Orbitrap-MS.Subsequently,the mechanism by which Sanhuang Oil promotes diabetic foot ulcer healing was predicted by integrating network pharmacology and molecular docking.Additionally,diabetic mouse model was established in ICR mice using a combination of a high-fat diet(HFD)and streptozotocin(STZ)chemical induction.A full-thickness skin defect was created on the dorsum of the mice.Wound healing and the healing rate were observed following Sanhuang Oil intervention.The mechanism underlying Sanhuang Oil’s promotion of diabetic ulcer healing was further investigated using transcriptomics and histopathological examination(H&E staining).Results:A total of 97 active ingredients were identified from Sanhuang Oil.Network pharmacology analysis predicted 543 common targets,and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis identified 203 relevant pathways.Molecular docking further confirmed high binding affinity(binding energy≤−5.0 kcal/mol)between specific active components in Sanhuang Oil(e.g.,coptisine,phellodendrine,baicalein)and key targets associated with diabetic foot ulcers(e.g.,EGFR,AKT1,STAT3).In vivo experimental results demonstrated that the wound healing rate was significantly higher in Sanhuang Oil-treated groups compared to the model group(P<0.001).HE staining revealed that the high-dose Sanhuang Oil group exhibited more pronounced epithelial tissue coverage over the wound,reduced inflammatory cell infiltration,and increased collagen deposition and fibroblast proliferation.transcriptomic analysis identified Pdk4,Ttn,Csrp3,Actn2,Myoz2,Tnnc2,Myod1,Myog,Myot,and Myf6 as key regulatory proteins involved in promoting wound healing.Conclusion:Sanhuang Oil promotes wound healing in diabetic ulcer mice,potentially by mitigating inflammation and regulating key targets such as Pdk4 to enhance fibroblast function.These findings provide novel insights into the multi-target,multi-pathway mechanism of Sanhuang Oil for treating diabetic foot ulcers.展开更多
A two-dimensional nonoscillatory central difference scheme was extended to the shallow water equations. A high-resolution numerical method for solving the shallow water equations was presented. In order to prevent osc...A two-dimensional nonoscillatory central difference scheme was extended to the shallow water equations. A high-resolution numerical method for solving the shallow water equations was presented. In order to prevent oscillation, the nonlinear limiter is employed to approximate the discrete slopes. The main advantage of the presented method is simplicity comparable with the upwind schemes. This method does not require Riemann solvers or some form of flux difference splitting methods. Furthermore, the discrete derivatives of flux can be approximated by the component-wise approach and thus the computation of Jacobian can be avoided. The method retains high resolution and high accuracy similar to the upwind results. It is applied to simulating several tests, including circular dam-break problem, shock focusing problem and partial dam-break problem. The results are in good agreement with the numerical results obtained by other methods. The simulated results also demonstrate that the presented method is stable and efficient.展开更多
By the aid of an idea of the weighted ENO schemes, some weight-type high-resolution difference schemes with different orders of accuracy are presented in this paper by using suitable weights instead of the minmod func...By the aid of an idea of the weighted ENO schemes, some weight-type high-resolution difference schemes with different orders of accuracy are presented in this paper by using suitable weights instead of the minmod functions appearing in various TVD schemes. Numerical comparisons between the weighted schemes and the non-weighted schemes have been done for scalar equation, one-dimensional Euler equations, two-dimensional Navier-Stokes equations and parabolized Navier-Stokes equations.展开更多
High-resolution transmission electron microscopy(HRTEM)promises rapid atomic-scale dynamic structure imaging.Yet,the precision limitations of aberration parameters and the challenge of eliminating aberrations in Cs-co...High-resolution transmission electron microscopy(HRTEM)promises rapid atomic-scale dynamic structure imaging.Yet,the precision limitations of aberration parameters and the challenge of eliminating aberrations in Cs-corrected transmission electron microscopy constrain resolution.A machine learning algorithm is developed to determine the aberration parameters with higher precision from small,lattice-periodic crystal images.The proposed algorithm is then validated with simulated HRTEM images of graphene and applied to the experimental images of a molybdenum disulfide(MoS_(2))monolayer with 25 variables(14 aberrations)resolved in wide ranges.Using these measured parameters,the phases of the exit-wave functions are reconstructed for each image in a focal series of MoS_(2)monolayers.The images were acquired due to the unexpected movement of the specimen holder.Four-dimensional data extraction reveals time-varying atomic structures and ripple.In particular,the atomic evolution of the sulfur-vacancy point and line defects,as well as the edge structure near the amorphous,is visualized as the resolution has been improved from about 1.75?to 0.9 A.This method can help salvage important transmission electron microscope images and is beneficial for the images obtained from electron microscopes with average stability.展开更多
The objective of image-based virtual try-on is to seamlessly integrate clothing onto a target image, generating a realistic representation of the character in the specified attire. However, existing virtual try-on met...The objective of image-based virtual try-on is to seamlessly integrate clothing onto a target image, generating a realistic representation of the character in the specified attire. However, existing virtual try-on methods frequently encounter challenges, including misalignment between the body and clothing, noticeable artifacts, and the loss of intricate garment details. To overcome these challenges, we introduce a two-stage high-resolution virtual try-on framework that integrates an attention mechanism, comprising a garment warping stage and an image generation stage. During the garment warping stage, we incorporate a channel attention mechanism to effectively retain the critical features of the garment, addressing challenges such as the loss of patterns, colors, and other essential details commonly observed in virtual try-on images produced by existing methods. During the image generation stage, with the aim of maximizing the utilization of the information proffered by the input image, the input features undergo double sampling within the normalization procedure, thereby enhancing the detail fidelity and clothing alignment efficacy of the output image. Experimental evaluations conducted on high-resolution datasets validate the effectiveness of the proposed method. Results demonstrate significant improvements in preserving garment details, reducing artifacts, and achieving superior alignment between the clothing and body compared to baseline methods, establishing its advantage in generating realistic and high-quality virtual try-on images.展开更多
In oceanic and atmospheric science,finer resolutions have become a prevailing trend in all aspects of development.For high-resolution fluid flow simulations,the computational costs of widely used numerical models incr...In oceanic and atmospheric science,finer resolutions have become a prevailing trend in all aspects of development.For high-resolution fluid flow simulations,the computational costs of widely used numerical models increase significantly with the resolution.Artificial intelligence methods have attracted increasing attention because of their high precision and fast computing speeds compared with traditional numerical model methods.The resolution-independent Fourier neural operator(FNO)presents a promising solution to the still challenging problem of high-resolution fluid flow simulations based on low-resolution data.Accordingly,we assess the potential of FNO for high-resolution fluid flow simulations using the vorticity equation as an example.We assess and compare the performance of FNO in multiple high-resolution tests varying the amounts of data and the evolution durations.When assessed with finer resolution data(even up to number of grid points with 1280×1280),the FNO model,trained at low resolution(number of grid points with 64×64)and with limited data,exhibits a stable overall error and good accuracy.Additionally,our work demonstrates that the FNO model takes less time than the traditional numerical method for high-resolution simulations.This suggests that FNO has the prospect of becoming a cost-effective and highly precise model for high-resolution simulations in the future.Moreover,FNO can make longer high-resolution predictions while training with less data by superimposing vorticity fields from previous time steps as input.A suitable initial learning rate can be set according to the frequency principle,and the time intervals of the dataset need to be adjusted according to the spatial resolution of the input when training the FNO model.Our findings can help optimize FNO for future fluid flow simulations.展开更多
While algorithms have been created for land usage in urban settings,there have been few investigations into the extraction of urban footprint(UF).To address this research gap,the study employs several widely used imag...While algorithms have been created for land usage in urban settings,there have been few investigations into the extraction of urban footprint(UF).To address this research gap,the study employs several widely used image classification method classified into three categories to evaluate their segmentation capabilities for extracting UF across eight cities.The results indicate that pixel-based methods only excel in clear urban environments,and their overall accuracy is not consistently high.RF and SVM perform well but lack stability in object-based UF extraction,influenced by feature selection and classifier performance.Deep learning enhances feature extraction but requires powerful computing and faces challenges with complex urban layouts.SAM excels in medium-sized urban areas but falters in intricate layouts.Integrating traditional and deep learning methods optimizes UF extraction,balancing accuracy and processing efficiency.Future research should focus on adapting algorithms for diverse urban landscapes to enhance UF extraction accuracy and applicability.展开更多
Understanding vegetation water availability can be important for managing vegetation and combating climate change.Changes in vegetation water availability throughout China remains poorly understood,especially at a hig...Understanding vegetation water availability can be important for managing vegetation and combating climate change.Changes in vegetation water availability throughout China remains poorly understood,especially at a high spatial resolution.Standardized Precipitation Evapotranspiration Index(SPEI)is an ideal water availability index for assessing the spatiotemporal characteristics of drought and investigating the vegetation-water availability relationship.However,no high-resolution and long-term SPEI datasets over China are available.To fill this gap,we developed a new model based on machine learning to obtain high-resolution(1 km)SPEI data by combining climate variables with topographical and geographical features.Here,we analyzed the long-term drought over the past century(1901–2020)and vegetation-water availability relationship in the past two decades(2000–2020).The century-long drought trend analyses indicated an overall drying trend across China with increasing drought frequency,duration,and severity during the past century.We found that drought events in 1901–1961 showed a larger increase than that in 1961–2020,with the Qinghai-Xizang Plateau showing a significant drying trend during 1901–1960 but a wetting trend during 1961–2020.There were 13.90%and 28.21%of vegetation in China showing water deficit and water surplus respectively during 2000–2020.The water deficit area significantly shrank from 2000 to 2020 across China,which is dominated by the significant decrease in water deficit areas in South China.Among temperature,precipitation,and vegetation abundance,temperature is the most important factor for the vegetation-water availability dynamics in China over the past two decades,with high temperature contributing to water deficit.Our findings are important for water and vegetation management under a warming climate.展开更多
High-resolution sub-meter satellite data play an increasingly crucial role in the 3D real-scene China construction initiative.Current research on 3D reconstruction using high-resolution satellite data primarily focuse...High-resolution sub-meter satellite data play an increasingly crucial role in the 3D real-scene China construction initiative.Current research on 3D reconstruction using high-resolution satellite data primarily focuses on two approaches:Multi-stereo fusion and multi-view matching.While algorithms based on these two methodologies for multi-view image 3D reconstruction have reached relative maturity,no systematic comparison has been conducted specifically on satellite data to evaluate the relative merits of multi-stereo fusion versus multi-view matching methods.This paper conducts a comparative analysis of the practical accuracy of both approaches using high-resolution satellite datasets from diverse geographical regions.To ensure fairness in accuracy comparison,both methodologies employ non-local dense matching for cost optimization.Results demonstrate that the multi-stereo fusion method outperforms multi-view matching in all evaluation metrics,exhibiting approximately 1.2%higher average matching accuracy and 10.7%superior elevation precision in the experimental datasets.Therefore,for 3D modeling applications using satellite data,we recommend adopting the multi-stereo fusion approach for digital surface model(DSM)product generation.展开更多
During drilling operations,the low resolution of seismic data often limits the accurate characterization of small-scale geological bodies near the borehole and ahead of the drill bit.This study investigates high-resol...During drilling operations,the low resolution of seismic data often limits the accurate characterization of small-scale geological bodies near the borehole and ahead of the drill bit.This study investigates high-resolution seismic data processing technologies and methods tailored for drilling scenarios.The high-resolution processing of seismic data is divided into three stages:pre-drilling processing,post-drilling correction,and while-drilling updating.By integrating seismic data from different stages,spatial ranges,and frequencies,together with information from drilled wells and while-drilling data,and applying artificial intelligence modeling techniques,a progressive high-resolution processing technology of seismic data based on multi-source information fusion is developed,which performs simple and efficient seismic information updates during drilling.Case studies show that,with the gradual integration of multi-source information,the resolution and accuracy of seismic data are significantly improved,and thin-bed weak reflections are more clearly imaged.The updated seismic information while-drilling demonstrates high value in predicting geological bodies ahead of the drill bit.Validation using logging,mud logging,and drilling engineering data ensures the fidelity of the processing results of high-resolution seismic data.This provides clearer and more accurate stratigraphic information for drilling operations,enhancing both drilling safety and efficiency.展开更多
Two novel schemes are proposed to synthesize high resolution range profile (HRRP) based on co-located multiple-input multiple-output (MIMO) system in the context of the joint radar and communication system. The differ...Two novel schemes are proposed to synthesize high resolution range profile (HRRP) based on co-located multiple-input multiple-output (MIMO) system in the context of the joint radar and communication system. The difference between two schemes is the pattern of selecting pulses, which depends on the demand for the velocity information. The system, a type of frequency diverse array (FDA), takes full advantage of the phase-coded orthogonal frequency division multiplexing (OFDM) signal. Furthermore, the complete discrete form of the phase-coded OFDM echoes is utilized to derive the HRRP processing. The velocity estimation in the second scheme aims to eliminate velocity ambiguity, and high velocity can be retrieved exactly. Meanwhile, the imaging method is investigated with random frequency coding applied to an array. The desired performance of resolving velocity ambiguity and suppressing noise is shown by means of comparisons with previous work. The advantages in the radar imaging and the significance of the work are concluded in the end.展开更多
As blockchain technology rapidly evolves,smart contracts have seen widespread adoption in financial transactions and beyond.However,the growing prevalence of malicious Ponzi scheme contracts presents serious security ...As blockchain technology rapidly evolves,smart contracts have seen widespread adoption in financial transactions and beyond.However,the growing prevalence of malicious Ponzi scheme contracts presents serious security threats to blockchain ecosystems.Although numerous detection techniques have been proposed,existing methods suffer from significant limitations,such as class imbalance and insufficient modeling of transaction-related semantic features.To address these challenges,this paper proposes an oversampling-based detection framework for Ponzi smart contracts.We enhance the Adaptive Synthetic Sampling(ADASYN)algorithm by incorporating sample proximity to decision boundaries and ensuring realistic sample distributions.This enhancement facilitates the generation of high-quality minority class samples and effectively mitigates class imbalance.In addition,we design a Contract Transaction Graph(CTG)construction algorithm to preserve key transactional semantics through feature extraction from contract code.A graph neural network(GNN)is then applied for classification.This study employs a publicly available dataset from the XBlock platform,consisting of 318 verified Ponzi contracts and 6498 benign contracts.Sourced from real Ethereum deployments,the dataset reflects diverse application scenarios and captures the varied characteristics of Ponzi schemes.Experimental results demonstrate that our approach achieves an accuracy of 96%,a recall of 92%,and an F1-score of 94%in detecting Ponzi contracts,outperforming state-of-the-art methods.展开更多
A high-order accurate explicit scheme is proposed for solving Euler/Reynolds-averaged Navier-Stokes equations for steady and unsteady flows, respectively. Baldwin-Lomax turbulence model is utilized to obtain the turbu...A high-order accurate explicit scheme is proposed for solving Euler/Reynolds-averaged Navier-Stokes equations for steady and unsteady flows, respectively. Baldwin-Lomax turbulence model is utilized to obtain the turbulent viscosity. For the explicit scheme, the Runge-Kutta time-stepping methods of third orders are used in time integration, and space discretization for the right-hand side (RHS) terms of semi-discrete equations is performed by third-order ENN scheme for inviscid terms and fourth-order compact difference for viscous terms. Numerical experiments suggest that the present scheme not only has a fairly rapid convergence rate, but also can generate a highly resolved approximation to numerical solution, even to unsteady problem.展开更多
For the recognition of high-resolution range profile （HRRP） in radar, the weighted HRRP can reduce the instability of range cells caused by the attitude change of targets. A novel approach is proposed to optimize th...For the recognition of high-resolution range profile （HRRP） in radar, the weighted HRRP can reduce the instability of range cells caused by the attitude change of targets. A novel approach is proposed to optimize the weighted HRRP. In the approach, the separability of weighted HRRPs in different targets is measured by de- signing an objective function, and the weighted coefficients are computed by using the gradient descent method, thus enhancing the influence of stable range cells. Simulation results based on five aircraft models show that the approach can effectively optimize the weighted HRRP and improve the recognition accuracy.展开更多
Projections of future precipitation change over China are studied based on the output of a global AGCM, ECHAM5, with a high resolution of T319 （equivalent to 40 km）. Evaluation of the model’s performance in simulat...Projections of future precipitation change over China are studied based on the output of a global AGCM, ECHAM5, with a high resolution of T319 （equivalent to 40 km）. Evaluation of the model’s performance in simulating present-day precipitation shows encouraging results. The spatial distributions of both mean and extreme precipitation, especially the locations of main precipitation centers, are reproduced reasonably. The simulated annual cycle of precipitation is close to the observed. The performance of the model over eastern China is generally better than that over western China. A weakness of the model is the overestimation of precipitation over northern and western China. Analyses on the potential change in precipitation projected under the A1B scenario show that both annual mean precipitation intensity and extreme precipitation would increase significantly over southeastern China. The percentage increase in extreme precipitation is larger than that of mean precipitation. Meanwhile, decreases in mean and extreme precipitation are evident over the southern Tibetan Plateau. For precipitation days, extreme precipitation days are projected to increase over all of China. Both consecutive dry days over northern China and consecutive wet days over southern China would decrease.展开更多
Since the beginning of the twenty-first century,several countries have made great efforts to develop space remote sensing for building a high-resolution earth observation system.Under the great attention of the govern...Since the beginning of the twenty-first century,several countries have made great efforts to develop space remote sensing for building a high-resolution earth observation system.Under the great attention of the government and the guidance of the major scientific and technological project of the high-resolution earth observation system,China has made continuous breakthroughs and progress in high-resolution remote sensing imaging technology.The development of domestic high-resolution remote sensing satellites shows a vigorous trend,and consequently,a relatively stable and perfect high-resolution earth observation system has been formed.The development of high-resolution remote sensing satellites has greatly promoted and enriched modern mapping technologies and methods.In this paper,the development status,along with mapping modes and applications of China’s high-resolution remote sensing satellites are reviewed,and the development trend in high-resolution earth observation system for global and ground control-free mapping is discussed,providing a reference for the subsequent development of high-resolution remote sensing satellites in China.展开更多
Landslide is one of the multitudinous serious geological hazards. The key to its control and reduction lies on dynamic monitoring and early warning. The article points out the insufficiency of traditional measuring me...Landslide is one of the multitudinous serious geological hazards. The key to its control and reduction lies on dynamic monitoring and early warning. The article points out the insufficiency of traditional measuring means applied for large-scale landslide monitoring and proposes the method for extensive landslide displacement field monitoring using high- resolution remote images. Matching of cognominal points is realized by using the invariant features of SIFT algorithm in image translation, rotation, zooming, and affine transformation, and through recognition and comparison of characteristics of high-resolution images in different landsliding periods. Following that, landslide displacement vector field can be made known by measuring the distances and directions between cognominal points. As evidenced by field application of the method for landslide monitoring at West Open Mine in Fushun city of China, the method has the attraction of being able to make areal measurement through satellite observation and capable of obtaining at the same time the information of large- area intensive displacement field, for facilitating automatic delimitation of extent of landslide displacement vector field and sliding mass. This can serve as a basis for making analysis of laws governing occurrence of landslide and adoption of countermeasures.展开更多
文摘Viscoelastic fluids due to their non-linear nature play an important role in process and polymer industries. These non-linear characteristics of fluid, influence final outcome of the product. Such processes though look simple are numerically challenging to study, due to the loss of numerical stability. Over the years, various methodologies have been developed to overcome this numerical limitation. In spite of this, numerical solutions are considered distant from accuracy, as first-order upwind-differencing scheme （UDS） is often employed for improving the stability of algorithm. To elude this effect, some works been reported in the past, where high-resolution-schemes （HRS） were employed and Deborah number was varied. However, these works are limited to creeping flows and do not detail any information on the numerical stability of HRS. Hence, this article presents the numerical study of high shearing contraction flows, where stability of HRS are addressed in reference to fluid elasticity. Results suggest that all I-IRS show some order of undue oscillations in flow variable profiles, measured along vertical lines placed near contraction region in the upstream section of domain, at varied elasticity number E ~ 5. Furthermore, by E, a clear relationship between numerical stability of HRS and E was obtained, which states that the order of undue oscillations in flow variable profiles is directly proportional to E.
基金Research was supported in part by the ONR Grant N00014-2112773.
文摘Slope limiters play an essential role in maintaining the non-oscillatory behavior of high-resolution methods for nonlinear conservation laws.The family of minmod limiters serves as the prototype example.Here,we revisit the question of non-oscillatory behavior of high-resolution central schemes in terms of the slope limiter proposed by van Albada et al.(Astron Astrophys 108:76–84,1982).The van Albada(vA)limiter is smoother near extrema,and consequently,in many cases,it outperforms the results obtained using the standard minmod limiter.In particular,we prove that the vA limiter ensures the one-dimensional Total-Variation Diminishing(TVD)stability and demonstrate that it yields noticeable improvement in computation of one-and two-dimensional systems.
基金funded by the National Natural Science Foundation of China(62273213,62472262,62572287)Natural Science Foundation of Shandong Province(ZR2024MF144)+1 种基金Natural Science Foundation of Shandong Province for Innovation and Development Joint Funds(ZR2022LZH001)Taishan Scholarship Construction Engineering.
文摘Accurately counting dense objects in complex and diverse backgrounds is a significant challenge in computer vision,with applications ranging from crowd counting to various other object counting tasks.To address this,we propose HUANNet(High-Resolution Unified Attention Network),a convolutional neural network designed to capture both local features and rich semantic information through a high-resolution representation learning framework,while optimizing computational distribution across parallel branches.HUANNet introduces three core modules:the High-Resolution Attention Module(HRAM),which enhances feature extraction by optimizing multiresolution feature fusion;the Unified Multi-Scale Attention Module(UMAM),which integrates spatial,channel,and convolutional kernel information through an attention mechanism applied across multiple levels of the network;and the Grid-Assisted Point Matching Module(GPMM),which stabilizes and improves point-to-point matching by leveraging grid-based mechanisms.Extensive experiments show that HUANNet achieves competitive results on the ShanghaiTech Part A/B crowd counting datasets and sets new state-of-the-art performance on dense object counting datasets such as CARPK and XRAY-IECCD,demonstrating the effectiveness and versatility of HUANNet.
基金supported by the Natural Science Foundation of Hubei Provincial Department of Education(D20232101)Shandong Second Medical University 2024 Affiliated Hospital(Teaching Hospital)Scientific Research Development Fund Project(2024FYQ026)+3 种基金the innovative Research Programme of Xiangyang No.1 People’s Hospital(XYY2023ZY01)Faculty Development Grants of Xiangyang No.1 People’s Hospital Affiliated to Hubei University of Medicine(XYY2023D05)Joint supported by Hubei Provincial Natural Science Foundation and Xiangyang of China(2025AFD091)Traditional Chinese Medicine Scientific Research Project of Hubei Provincial Administration of Traditional Chinese Medicine(ZY2025D019).
文摘Background:Diabetic foot,a severe complication of diabetes,is characterized by chronic refractory wounds.Sanhuang Oil,a topical herbal formula,demonstrates significant therapeutic effects including antibacterial,anti-inflammatory,and immunomodulatory activities.However,its active constituents and mechanisms of action against diabetic foot remain to be elucidated.Methods:In this study,the chemical constituents of Sanhuang Oil were identified using UPLC-QE-Orbitrap-MS.Subsequently,the mechanism by which Sanhuang Oil promotes diabetic foot ulcer healing was predicted by integrating network pharmacology and molecular docking.Additionally,diabetic mouse model was established in ICR mice using a combination of a high-fat diet(HFD)and streptozotocin(STZ)chemical induction.A full-thickness skin defect was created on the dorsum of the mice.Wound healing and the healing rate were observed following Sanhuang Oil intervention.The mechanism underlying Sanhuang Oil’s promotion of diabetic ulcer healing was further investigated using transcriptomics and histopathological examination(H&E staining).Results:A total of 97 active ingredients were identified from Sanhuang Oil.Network pharmacology analysis predicted 543 common targets,and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis identified 203 relevant pathways.Molecular docking further confirmed high binding affinity(binding energy≤−5.0 kcal/mol)between specific active components in Sanhuang Oil(e.g.,coptisine,phellodendrine,baicalein)and key targets associated with diabetic foot ulcers(e.g.,EGFR,AKT1,STAT3).In vivo experimental results demonstrated that the wound healing rate was significantly higher in Sanhuang Oil-treated groups compared to the model group(P<0.001).HE staining revealed that the high-dose Sanhuang Oil group exhibited more pronounced epithelial tissue coverage over the wound,reduced inflammatory cell infiltration,and increased collagen deposition and fibroblast proliferation.transcriptomic analysis identified Pdk4,Ttn,Csrp3,Actn2,Myoz2,Tnnc2,Myod1,Myog,Myot,and Myf6 as key regulatory proteins involved in promoting wound healing.Conclusion:Sanhuang Oil promotes wound healing in diabetic ulcer mice,potentially by mitigating inflammation and regulating key targets such as Pdk4 to enhance fibroblast function.These findings provide novel insights into the multi-target,multi-pathway mechanism of Sanhuang Oil for treating diabetic foot ulcers.
基金This study was supported by the National Natural Science Foundation of China under contract No.60134010.
文摘A two-dimensional nonoscillatory central difference scheme was extended to the shallow water equations. A high-resolution numerical method for solving the shallow water equations was presented. In order to prevent oscillation, the nonlinear limiter is employed to approximate the discrete slopes. The main advantage of the presented method is simplicity comparable with the upwind schemes. This method does not require Riemann solvers or some form of flux difference splitting methods. Furthermore, the discrete derivatives of flux can be approximated by the component-wise approach and thus the computation of Jacobian can be avoided. The method retains high resolution and high accuracy similar to the upwind results. It is applied to simulating several tests, including circular dam-break problem, shock focusing problem and partial dam-break problem. The results are in good agreement with the numerical results obtained by other methods. The simulated results also demonstrate that the presented method is stable and efficient.
基金The project supported by the National Natural Science Foundation of China (19582007) Partly by State Key Laboratory of Scientific/Engineering Computing
文摘By the aid of an idea of the weighted ENO schemes, some weight-type high-resolution difference schemes with different orders of accuracy are presented in this paper by using suitable weights instead of the minmod functions appearing in various TVD schemes. Numerical comparisons between the weighted schemes and the non-weighted schemes have been done for scalar equation, one-dimensional Euler equations, two-dimensional Navier-Stokes equations and parabolized Navier-Stokes equations.
基金financial support from the National Natural Science Foundation of China(Grant No.61971201)。
文摘High-resolution transmission electron microscopy(HRTEM)promises rapid atomic-scale dynamic structure imaging.Yet,the precision limitations of aberration parameters and the challenge of eliminating aberrations in Cs-corrected transmission electron microscopy constrain resolution.A machine learning algorithm is developed to determine the aberration parameters with higher precision from small,lattice-periodic crystal images.The proposed algorithm is then validated with simulated HRTEM images of graphene and applied to the experimental images of a molybdenum disulfide(MoS_(2))monolayer with 25 variables(14 aberrations)resolved in wide ranges.Using these measured parameters,the phases of the exit-wave functions are reconstructed for each image in a focal series of MoS_(2)monolayers.The images were acquired due to the unexpected movement of the specimen holder.Four-dimensional data extraction reveals time-varying atomic structures and ripple.In particular,the atomic evolution of the sulfur-vacancy point and line defects,as well as the edge structure near the amorphous,is visualized as the resolution has been improved from about 1.75?to 0.9 A.This method can help salvage important transmission electron microscope images and is beneficial for the images obtained from electron microscopes with average stability.
基金supported by the National Natural Science Foundation of China(61772179)Hunan Provincial Natural Science Foundation of China(2022JJ50016,2023JJ50095)+1 种基金the Science and Technology Plan Project of Hunan Province(2016TP1020)Double First-Class University Project of Hunan Province(Xiangjiaotong[2018]469,[2020]248).
文摘The objective of image-based virtual try-on is to seamlessly integrate clothing onto a target image, generating a realistic representation of the character in the specified attire. However, existing virtual try-on methods frequently encounter challenges, including misalignment between the body and clothing, noticeable artifacts, and the loss of intricate garment details. To overcome these challenges, we introduce a two-stage high-resolution virtual try-on framework that integrates an attention mechanism, comprising a garment warping stage and an image generation stage. During the garment warping stage, we incorporate a channel attention mechanism to effectively retain the critical features of the garment, addressing challenges such as the loss of patterns, colors, and other essential details commonly observed in virtual try-on images produced by existing methods. During the image generation stage, with the aim of maximizing the utilization of the information proffered by the input image, the input features undergo double sampling within the normalization procedure, thereby enhancing the detail fidelity and clothing alignment efficacy of the output image. Experimental evaluations conducted on high-resolution datasets validate the effectiveness of the proposed method. Results demonstrate significant improvements in preserving garment details, reducing artifacts, and achieving superior alignment between the clothing and body compared to baseline methods, establishing its advantage in generating realistic and high-quality virtual try-on images.
基金The National Natural Science Foundation of China under contract No.42425606the Basic Scientific Fund for the National Public Research Institute of China(Shu-Xingbei Young Talent Program)under contract No.2023S01+1 种基金the Ocean Decade International Cooperation Center Scientific and Technological Cooperation Project under contract No.GHKJ2024005China-Korea Joint Ocean Research Center Project under contract Nos PI-20240101(China)and 20220407(Korea).
文摘In oceanic and atmospheric science,finer resolutions have become a prevailing trend in all aspects of development.For high-resolution fluid flow simulations,the computational costs of widely used numerical models increase significantly with the resolution.Artificial intelligence methods have attracted increasing attention because of their high precision and fast computing speeds compared with traditional numerical model methods.The resolution-independent Fourier neural operator(FNO)presents a promising solution to the still challenging problem of high-resolution fluid flow simulations based on low-resolution data.Accordingly,we assess the potential of FNO for high-resolution fluid flow simulations using the vorticity equation as an example.We assess and compare the performance of FNO in multiple high-resolution tests varying the amounts of data and the evolution durations.When assessed with finer resolution data(even up to number of grid points with 1280×1280),the FNO model,trained at low resolution(number of grid points with 64×64)and with limited data,exhibits a stable overall error and good accuracy.Additionally,our work demonstrates that the FNO model takes less time than the traditional numerical method for high-resolution simulations.This suggests that FNO has the prospect of becoming a cost-effective and highly precise model for high-resolution simulations in the future.Moreover,FNO can make longer high-resolution predictions while training with less data by superimposing vorticity fields from previous time steps as input.A suitable initial learning rate can be set according to the frequency principle,and the time intervals of the dataset need to be adjusted according to the spatial resolution of the input when training the FNO model.Our findings can help optimize FNO for future fluid flow simulations.
文摘While algorithms have been created for land usage in urban settings,there have been few investigations into the extraction of urban footprint(UF).To address this research gap,the study employs several widely used image classification method classified into three categories to evaluate their segmentation capabilities for extracting UF across eight cities.The results indicate that pixel-based methods only excel in clear urban environments,and their overall accuracy is not consistently high.RF and SVM perform well but lack stability in object-based UF extraction,influenced by feature selection and classifier performance.Deep learning enhances feature extraction but requires powerful computing and faces challenges with complex urban layouts.SAM excels in medium-sized urban areas but falters in intricate layouts.Integrating traditional and deep learning methods optimizes UF extraction,balancing accuracy and processing efficiency.Future research should focus on adapting algorithms for diverse urban landscapes to enhance UF extraction accuracy and applicability.
基金funded by the General Program of National Natural Science Foundation of China(Grant No.42377467).
文摘Understanding vegetation water availability can be important for managing vegetation and combating climate change.Changes in vegetation water availability throughout China remains poorly understood,especially at a high spatial resolution.Standardized Precipitation Evapotranspiration Index(SPEI)is an ideal water availability index for assessing the spatiotemporal characteristics of drought and investigating the vegetation-water availability relationship.However,no high-resolution and long-term SPEI datasets over China are available.To fill this gap,we developed a new model based on machine learning to obtain high-resolution(1 km)SPEI data by combining climate variables with topographical and geographical features.Here,we analyzed the long-term drought over the past century(1901–2020)and vegetation-water availability relationship in the past two decades(2000–2020).The century-long drought trend analyses indicated an overall drying trend across China with increasing drought frequency,duration,and severity during the past century.We found that drought events in 1901–1961 showed a larger increase than that in 1961–2020,with the Qinghai-Xizang Plateau showing a significant drying trend during 1901–1960 but a wetting trend during 1961–2020.There were 13.90%and 28.21%of vegetation in China showing water deficit and water surplus respectively during 2000–2020.The water deficit area significantly shrank from 2000 to 2020 across China,which is dominated by the significant decrease in water deficit areas in South China.Among temperature,precipitation,and vegetation abundance,temperature is the most important factor for the vegetation-water availability dynamics in China over the past two decades,with high temperature contributing to water deficit.Our findings are important for water and vegetation management under a warming climate.
文摘High-resolution sub-meter satellite data play an increasingly crucial role in the 3D real-scene China construction initiative.Current research on 3D reconstruction using high-resolution satellite data primarily focuses on two approaches:Multi-stereo fusion and multi-view matching.While algorithms based on these two methodologies for multi-view image 3D reconstruction have reached relative maturity,no systematic comparison has been conducted specifically on satellite data to evaluate the relative merits of multi-stereo fusion versus multi-view matching methods.This paper conducts a comparative analysis of the practical accuracy of both approaches using high-resolution satellite datasets from diverse geographical regions.To ensure fairness in accuracy comparison,both methodologies employ non-local dense matching for cost optimization.Results demonstrate that the multi-stereo fusion method outperforms multi-view matching in all evaluation metrics,exhibiting approximately 1.2%higher average matching accuracy and 10.7%superior elevation precision in the experimental datasets.Therefore,for 3D modeling applications using satellite data,we recommend adopting the multi-stereo fusion approach for digital surface model(DSM)product generation.
基金Supported by the National Natural Science Foundation of China(U24B2031)National Key Research and Development Project(2018YFA0702504)"14th Five-Year Plan"Science and Technology Project of CNOOC(KJGG2022-0201)。
文摘During drilling operations,the low resolution of seismic data often limits the accurate characterization of small-scale geological bodies near the borehole and ahead of the drill bit.This study investigates high-resolution seismic data processing technologies and methods tailored for drilling scenarios.The high-resolution processing of seismic data is divided into three stages:pre-drilling processing,post-drilling correction,and while-drilling updating.By integrating seismic data from different stages,spatial ranges,and frequencies,together with information from drilled wells and while-drilling data,and applying artificial intelligence modeling techniques,a progressive high-resolution processing technology of seismic data based on multi-source information fusion is developed,which performs simple and efficient seismic information updates during drilling.Case studies show that,with the gradual integration of multi-source information,the resolution and accuracy of seismic data are significantly improved,and thin-bed weak reflections are more clearly imaged.The updated seismic information while-drilling demonstrates high value in predicting geological bodies ahead of the drill bit.Validation using logging,mud logging,and drilling engineering data ensures the fidelity of the processing results of high-resolution seismic data.This provides clearer and more accurate stratigraphic information for drilling operations,enhancing both drilling safety and efficiency.
基金supported by the National Natural Science Foundation of China(6107116361071164+8 种基金6147119161501233)the Fundamental Research Funds for the Central Universities(NP2014504)the Aeronautical Science Foundation(20152052026)the Electronic&Information School of Yangtze University Innovation Foundation(2016-DXCX-05)the Funding for Outstanding Doctoral Dissertation in NUAA(BCXJ15-03)the Funding of Jiangsu Innovation Program for Graduate Education(KYLX15 0281)the Fundamental Research Funds for the Central Universitiespartly funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PADA)
文摘Two novel schemes are proposed to synthesize high resolution range profile (HRRP) based on co-located multiple-input multiple-output (MIMO) system in the context of the joint radar and communication system. The difference between two schemes is the pattern of selecting pulses, which depends on the demand for the velocity information. The system, a type of frequency diverse array (FDA), takes full advantage of the phase-coded orthogonal frequency division multiplexing (OFDM) signal. Furthermore, the complete discrete form of the phase-coded OFDM echoes is utilized to derive the HRRP processing. The velocity estimation in the second scheme aims to eliminate velocity ambiguity, and high velocity can be retrieved exactly. Meanwhile, the imaging method is investigated with random frequency coding applied to an array. The desired performance of resolving velocity ambiguity and suppressing noise is shown by means of comparisons with previous work. The advantages in the radar imaging and the significance of the work are concluded in the end.
基金supported by the Key Project of Joint Fund of the National Natural Science Foundation of China“Research on Key Technologies and Demonstration Applications for Trusted and Secure Data Circulation and Trading”(U24A20241)the National Natural Science Foundation of China“Research on Trusted Theories and Key Technologies of Data Security Trading Based on Blockchain”(62202118)+4 种基金the Major Scientific and Technological Special Project of Guizhou Province([2024]014)Scientific and Technological Research Projects from the Guizhou Education Department(Qian jiao ji[2023]003)the Hundred-Level Innovative Talent Project of the Guizhou Provincial Science and Technology Department(Qiankehe Platform Talent-GCC[2023]018)the Major Project of Guizhou Province“Research and Application of Key Technologies for Trusted Large Models Oriented to Public Big Data”(Qiankehe Major Project[2024]003)the Guizhou Province Computational Power Network Security Protection Science and Technology Innovation Talent Team(Qiankehe Talent CXTD[2025]029).
文摘As blockchain technology rapidly evolves,smart contracts have seen widespread adoption in financial transactions and beyond.However,the growing prevalence of malicious Ponzi scheme contracts presents serious security threats to blockchain ecosystems.Although numerous detection techniques have been proposed,existing methods suffer from significant limitations,such as class imbalance and insufficient modeling of transaction-related semantic features.To address these challenges,this paper proposes an oversampling-based detection framework for Ponzi smart contracts.We enhance the Adaptive Synthetic Sampling(ADASYN)algorithm by incorporating sample proximity to decision boundaries and ensuring realistic sample distributions.This enhancement facilitates the generation of high-quality minority class samples and effectively mitigates class imbalance.In addition,we design a Contract Transaction Graph(CTG)construction algorithm to preserve key transactional semantics through feature extraction from contract code.A graph neural network(GNN)is then applied for classification.This study employs a publicly available dataset from the XBlock platform,consisting of 318 verified Ponzi contracts and 6498 benign contracts.Sourced from real Ethereum deployments,the dataset reflects diverse application scenarios and captures the varied characteristics of Ponzi schemes.Experimental results demonstrate that our approach achieves an accuracy of 96%,a recall of 92%,and an F1-score of 94%in detecting Ponzi contracts,outperforming state-of-the-art methods.
基金The project supported by the National Natural Science Foundation of China under Contract No.59576007 and 19572038
文摘A high-order accurate explicit scheme is proposed for solving Euler/Reynolds-averaged Navier-Stokes equations for steady and unsteady flows, respectively. Baldwin-Lomax turbulence model is utilized to obtain the turbulent viscosity. For the explicit scheme, the Runge-Kutta time-stepping methods of third orders are used in time integration, and space discretization for the right-hand side (RHS) terms of semi-discrete equations is performed by third-order ENN scheme for inviscid terms and fourth-order compact difference for viscous terms. Numerical experiments suggest that the present scheme not only has a fairly rapid convergence rate, but also can generate a highly resolved approximation to numerical solution, even to unsteady problem.
基金Supported by the Academician Foundation of the 14th Research Institute of China Electronics Technology Group Corporation(2008041001)~~
文摘For the recognition of high-resolution range profile （HRRP） in radar, the weighted HRRP can reduce the instability of range cells caused by the attitude change of targets. A novel approach is proposed to optimize the weighted HRRP. In the approach, the separability of weighted HRRPs in different targets is measured by de- signing an objective function, and the weighted coefficients are computed by using the gradient descent method, thus enhancing the influence of stable range cells. Simulation results based on five aircraft models show that the approach can effectively optimize the weighted HRRP and improve the recognition accuracy.
基金supported by the National Key Technologies R&D Program(Grant No. 2007BAC29B03)China-UK-Swiss Adaptingto Climate Change in China Project (ACCC)-Climate Sciencethe National Natural Science Foundation of China (Grant No. 40890054)
文摘Projections of future precipitation change over China are studied based on the output of a global AGCM, ECHAM5, with a high resolution of T319 （equivalent to 40 km）. Evaluation of the model’s performance in simulating present-day precipitation shows encouraging results. The spatial distributions of both mean and extreme precipitation, especially the locations of main precipitation centers, are reproduced reasonably. The simulated annual cycle of precipitation is close to the observed. The performance of the model over eastern China is generally better than that over western China. A weakness of the model is the overestimation of precipitation over northern and western China. Analyses on the potential change in precipitation projected under the A1B scenario show that both annual mean precipitation intensity and extreme precipitation would increase significantly over southeastern China. The percentage increase in extreme precipitation is larger than that of mean precipitation. Meanwhile, decreases in mean and extreme precipitation are evident over the southern Tibetan Plateau. For precipitation days, extreme precipitation days are projected to increase over all of China. Both consecutive dry days over northern China and consecutive wet days over southern China would decrease.
基金This work is supported by the National Natural Science Foundation of China[grant numbers 91738302 and 91838303]the National Science Fund for Distinguished Young Scholars[grant number 61825103]Thanks for the support of China Centre for Resources Satellite Data and Application(CRESDA).
文摘Since the beginning of the twenty-first century,several countries have made great efforts to develop space remote sensing for building a high-resolution earth observation system.Under the great attention of the government and the guidance of the major scientific and technological project of the high-resolution earth observation system,China has made continuous breakthroughs and progress in high-resolution remote sensing imaging technology.The development of domestic high-resolution remote sensing satellites shows a vigorous trend,and consequently,a relatively stable and perfect high-resolution earth observation system has been formed.The development of high-resolution remote sensing satellites has greatly promoted and enriched modern mapping technologies and methods.In this paper,the development status,along with mapping modes and applications of China’s high-resolution remote sensing satellites are reviewed,and the development trend in high-resolution earth observation system for global and ground control-free mapping is discussed,providing a reference for the subsequent development of high-resolution remote sensing satellites in China.
文摘Landslide is one of the multitudinous serious geological hazards. The key to its control and reduction lies on dynamic monitoring and early warning. The article points out the insufficiency of traditional measuring means applied for large-scale landslide monitoring and proposes the method for extensive landslide displacement field monitoring using high- resolution remote images. Matching of cognominal points is realized by using the invariant features of SIFT algorithm in image translation, rotation, zooming, and affine transformation, and through recognition and comparison of characteristics of high-resolution images in different landsliding periods. Following that, landslide displacement vector field can be made known by measuring the distances and directions between cognominal points. As evidenced by field application of the method for landslide monitoring at West Open Mine in Fushun city of China, the method has the attraction of being able to make areal measurement through satellite observation and capable of obtaining at the same time the information of large- area intensive displacement field, for facilitating automatic delimitation of extent of landslide displacement vector field and sliding mass. This can serve as a basis for making analysis of laws governing occurrence of landslide and adoption of countermeasures.
