In this paper we prove zero-density estimates of the large sieve type for the automorphic L-function L（s, f × χ）, where f is a holomorphic cusp form and χ（mod q） is a primitive character.
In this paper,we study and characterize the volume estimates of geodesic balls on Finsler gradient Ricci solitons.We get the upper bounds on the volumes of geodesic balls of all three kinds of Finsler gradient Ricci s...In this paper,we study and characterize the volume estimates of geodesic balls on Finsler gradient Ricci solitons.We get the upper bounds on the volumes of geodesic balls of all three kinds of Finsler gradient Ricci solitons under certain condition about the Laplacian of thedistance function.展开更多
Combining TT* argument and bilinear interpolation,this paper obtains the Strichartz and smoothing estimates of dispersive semigroup e^(-itP(D)) in weighted L^(2) spaces.Among other things,we recover the results in[1]....Combining TT* argument and bilinear interpolation,this paper obtains the Strichartz and smoothing estimates of dispersive semigroup e^(-itP(D)) in weighted L^(2) spaces.Among other things,we recover the results in[1].Moreover,the application of these results to the well-posedness of some equations are shown in the last section.展开更多
We consider the space and time decays of certain problems within the second gradient thermal law.Notably,for this thermal theory,the exponential time decay is precluded.First,the time estimates of polynomial type are ...We consider the space and time decays of certain problems within the second gradient thermal law.Notably,for this thermal theory,the exponential time decay is precluded.First,the time estimates of polynomial type are obtained for both the thermal equation and the one-dimensional thermoelastic system,where the impossibility of localization with respect to time is also established.Then,the space estimates are deduced for the multidimensional thermoelastic problem,which allow to show the exponential decay of the energy.展开更多
Cropland nitrate leaching is the major nitrogen(N) loss pathway, and it contributes significantly to water pollution. However, cropland nitrate leaching estimates show great uncertainty due to variations in input data...Cropland nitrate leaching is the major nitrogen(N) loss pathway, and it contributes significantly to water pollution. However, cropland nitrate leaching estimates show great uncertainty due to variations in input datasets and estimation methods. Here, we presented a re-evaluation of Chinese cropland nitrate leaching, and identified and quantified the sources of uncertainty by integrating three cropland area datasets, three N input datasets, and three estimation methods. The results revealed that nitrate leaching from Chinese cropland averaged 6.7±0.6 Tg N yr^(-1)in 2010, ranging from 2.9 to 15.8 Tg N yr^(-1)across 27 different estimates. The primary contributor to the uncertainty was the estimation method, accounting for 45.1%, followed by the interaction of N input dataset and estimation method at 24.4%. The results of this study emphasize the need for adopting a robust estimation method and improving the compatibility between the estimation method and N input dataset to effectively reduce uncertainty. This analysis provides valuable insights for accurately estimating cropland nitrate leaching and contributes to ongoing efforts that address water pollution concerns.展开更多
This paper is devoted to the Polynomial Preserving Recovery (PPR) based a posteriori error analysis for the second-order elliptic non-symmetric eigenvalue problem. An asymptotically exact a posteriori error estimator ...This paper is devoted to the Polynomial Preserving Recovery (PPR) based a posteriori error analysis for the second-order elliptic non-symmetric eigenvalue problem. An asymptotically exact a posteriori error estimator is proposed for solving the convection-dominated non-symmetric eigenvalue problem with non-smooth eigenfunctions or multiple eigenvalues. Numerical examples confirm our theoretical analysis.展开更多
Earthquakes can cause significant damage and loss of life,necessitating immediate assessment of the resulting fatalities.Rapid assessment and timely revision of fatality estimates are crucial for effective emergency d...Earthquakes can cause significant damage and loss of life,necessitating immediate assessment of the resulting fatalities.Rapid assessment and timely revision of fatality estimates are crucial for effective emergency decisionmaking.This study using the February 6,2023,M_(S)8.0 and M_(S)7.9 Kahramanmaras,Türkiye earthquakes as an example to estimate the ultimate number of fatalities.An early Quick Rough Estimate(QRE)based on the number of deaths reported by the Disaster and Emergency Management Presidency of Türkiye(AFAD)is conducted,and it dynamically adjusts these estimates as new data becomes available.The range of estimates of the final number of deaths can be calculated as 31384–56475 based on the"the QRE of the second day multiplied by 2–3" rule,which incorporates the reported final deaths 50500.The Quasi-Linear and Adaptive Estimation(QLAE)method adaptively adjusts the final fatality estimate within two days and predicts subsequent reported deaths.The correct order of magnitude of the final death toll can be estimated as early as 13 hr after the M_(S)8.0 earthquake.In addition,additional earthquakes such as May 12,2008,M_(S)8.1 Wenchuan earthquake(China),September 8,2023,M_(S)7.2 Al Haouz earthquake(Morocco),November 3,2023,M_(S)5.8 Mid-Western Nepal earthquake,December 18,2023,M_(S)6.1 Jishishan earthquake(China),January 1,2024,M_(S)7.2 Noto Peninsula earthquake(Japan)and August 8,2023,Maui,Hawaii,fires are added again to verified the correctness of the model.The fatalities from the Maui fires are found to be approximately equivalent to those resulting from an M_(S)7.4 earthquake.These methods complement existing frameworks such as Quake Loss Assessment for Response and Mitigation(QLARM)and Prompt Assessment of Global.展开更多
In this paper, we derive the a priori estimates for a class of more general (k, l)-Hessian quotient type equations involving u and Du on the right hand function. As an application we prove the Liouville theorem depend...In this paper, we derive the a priori estimates for a class of more general (k, l)-Hessian quotient type equations involving u and Du on the right hand function. As an application we prove the Liouville theorem depending on Pogorelov type estimates. On the other hand, we obtain the existence and uniqueness of the k-admissible solution for these general equations with the Neumann boundary condition, based on some growth conditions for the right hand function.展开更多
In this article,we are concerned with the C^(2)estimates for the k-convex solutions of a class of degenerate k-Hessian equations on closed Hermitian manifolds,whose function in the right-hand side is relevant to the u...In this article,we are concerned with the C^(2)estimates for the k-convex solutions of a class of degenerate k-Hessian equations on closed Hermitian manifolds,whose function in the right-hand side is relevant to the unknown function and its gradient.We will get C^(0)estimate by promoting others′results,and get the“HMW estimate”of this equation such that the conditions of using blow-up analysis are satisfied,and the gradient estimate and second-order estimate will be obtained.Such an estimate will be helpful to study the existence for the solution of the equation.展开更多
The paper is concerned with a class of elliptic equation with critical exponent and Dipole potential.More precisely,we make use of the refined Sobolev inequality with Morrey norm to obtain the existence and decay prop...The paper is concerned with a class of elliptic equation with critical exponent and Dipole potential.More precisely,we make use of the refined Sobolev inequality with Morrey norm to obtain the existence and decay properties of nonnegative radial ground state solutions.展开更多
In this paper,for the 1-D semilinear wave equation∂_(t)^(2)u-∂_(x)^(2)u+μ/t∂_(t)u=|u|~p with scaling invariant damping,where t≥1,p>1 andμ∈(0,1)∪(1,4/3),we establish the global weighted space-time estimates as ...In this paper,for the 1-D semilinear wave equation∂_(t)^(2)u-∂_(x)^(2)u+μ/t∂_(t)u=|u|~p with scaling invariant damping,where t≥1,p>1 andμ∈(0,1)∪(1,4/3),we establish the global weighted space-time estimates as well as the global existence of small data weak solution u when the nonlinearity power p is larger than some critical power p_(crit)(μ).Our proof is based on a class of new weighted Strichartz estimates with the weight t^(θ)|(1-μ)^(2)t^(2/|1-μ|)-x^(2)|^(γ)(θ>0andγ>0 are appropriate constants)for the solution of linear generalized Tricomi equation∂_(t)^(2)φ-t^(m)∂_(x)^(2)φ=0 with m being any fixed positive number.展开更多
The orthogonal time frequency space(OTFS)modulation is a novel modulation scheme that can effectively cope with the high Doppler expansion caused by high mobility.Since it modulates data on delay-Doppler(DD)domain and...The orthogonal time frequency space(OTFS)modulation is a novel modulation scheme that can effectively cope with the high Doppler expansion caused by high mobility.Since it modulates data on delay-Doppler(DD)domain and makes full use of the sparse characteristics of DD domain,it has been widely studied to design efficient channel estimation and signal detection schemes.In this paper,we design a novel superimposed pilot pattern with transition band,which replaces the traditional embedded pilot(EP)guard zero-symbols,and perform a two-stage channel estimation.In the first stage,we fully utilize the dispersion characteristics of OTFS signal in DD domain,and use threshold decision to make coarse channel estimation.In the second stage,we use the results of the coarse estimation for iterative signal detection and accurate channel estimation.During the second stage,we make full use of the sparsity of the channel in DD domain,remodel the received signal into the form of sparse channel vector multiplied by channel coefficient matrix,and introduce Doppler index segmentation factor(DISF)to subdivide the Doppler index to solve the problem of fractional Doppler.Simulations reveal that,the scheme proposed in this paper has higher spectral efficiency compared with traditional EP scheme and lower peak-to-average power ratio(PAPR)compared with traditional superimposed pilot scheme.展开更多
In GNSS-denied environments,signals of opportunity(SOP)offer an efficient and passive solution for navigation and positioning by utilizing ambient signals.Nevertheless,conventional SOP techniques face significant chal...In GNSS-denied environments,signals of opportunity(SOP)offer an efficient and passive solution for navigation and positioning by utilizing ambient signals.Nevertheless,conventional SOP techniques face significant challenges in real-time processing,especially under sub-Nyquist sampling conditions,due to high data acquisition rates and offgrid errors.To address this,this paper proposes the signal reconstruction and kernel sparse encoding(SRKSE)model,a novel general framework for high-precision parameter estimation.By combining compressed sensing with a deep unfolding network,the SRKSE model not only achieves robust signal reconstruction but also effectively reduces quantization errors.Key innovations of SRKSE include dual crossattention mechanisms for enhanced feature extraction,sinc sparse kernel encoding to minimize quantization errors,and a custom loss function for balanced optimization.With these advancements,SRKSE achieves up to a 650-fold improvement in time of arrival(TOA)estimation accuracy while operating at just 1%of the Nyquist sampling rate.The SRKSE surpasses both conventional and deep learning-based techniques in accuracy and efficiency,especially when operating under sub-Nyquist sampling conditions.Simulations and real-world experiments confirm the reliability and potential of SRKSE for real-time applications in IoT and wireless communication.展开更多
The growing use of lithium-ion batteries in electric transportation and grid-scale storage systems has intensified the need for accurate and highly generalizable state-of-health(SOH)estimation.Conventional approaches ...The growing use of lithium-ion batteries in electric transportation and grid-scale storage systems has intensified the need for accurate and highly generalizable state-of-health(SOH)estimation.Conventional approaches often suffer from reduced accuracy under dynamically uncertain state-of-charge(SOC)operating ranges and heterogeneous aging stresses.This study presents a unified SOH estimation framework that integrates physics-informed modeling,subspace identification,and Transformer-based learning.A reduced-order model is derived from simplified electrochemical dynamics,providing an interpretable and computationally efficient representation of battery behavior.Subspace identification across a wide SOC and SOH range yields degradation-sensitive features,which the Transformer uses to capture long-range aging dynamics via multi-head self-attention.Experiments on LiFePO4 cells under joint-cell training show consistently accurate SOH estimation,with a maximum error of 1.39%,demonstrating the framework’s effectiveness in decoupling SOC and SOH effects.In cross-cell validation,where training and validation are performed on different cells,the model maintains a maximum error of 2.06%,confirming strong generalization to unseen aging trajectories.Comparative experiments on LiFePO_(4)and public LiCoO_(2)datasets confirm the framework’s cross-chemistry applicability.By extracting low-dimensional,physically interpretable features via subspace identification,the framework significantly reduces training cost while maintaining high SOH estimation accuracy,outperforming conventional data-driven models lacking physical guidance.展开更多
Presented in this study is a novel method for estimating the depth of single underwater source in shallow water,utilizing vector sensors.The approach leverages the depth distribution of the broadband Stokes parameters...Presented in this study is a novel method for estimating the depth of single underwater source in shallow water,utilizing vector sensors.The approach leverages the depth distribution of the broadband Stokes parameters to estimate source depth accurately.Unlike traditional matched field processing(MFP)and matched mode processing(MMP),the proposed approach can estimate source depth directly from the data received by sensors without requiring complete environmental information.Firstly,the broadband Stokes parameters(BSP)are established using the normal mode theory.Then the nonstationary phase approximation is used to simplify the theoretical derivation,which is necessary when dealing with broadband integrals.Additionally,range terms of the BSP are eliminated by normalization.By analyzing the depth distribution of the normalized broadband Stokes parameters(NBSP),it is found that the NBSP exhibit extreme values at the source depth,which can be used for source depth estimation.So the proposed depth estimation method is based on searching the peaks of the NBSP.Simulations show that this method is effective in relatively simple shallow water environments.Finally,the effect of source range,frequency bandwidth,sound speed profile(SSP),water depth,and signal-to-noise ratio(SNR)are studied.The findings indicate that the proposed method can accurately estimate the source depth when the SNR is greater than-5 d B and does not need to consider model mismatch issues.Additionally,variations in environmental parameters have minimal impact on estimation accuracy.Compared to MFP,the proposed method requires a higher SNR,but demonstrates superior robustness against fluctuations in environmental parameters.展开更多
Considering the impact of terminal impact time constraints and the state information of maneuvering targets on the guidance accuracy in multi-UAV cooperative guidance,this paper proposes an impact time cooperative con...Considering the impact of terminal impact time constraints and the state information of maneuvering targets on the guidance accuracy in multi-UAV cooperative guidance,this paper proposes an impact time cooperative control guidance law(ITCCG)that combines the optimal error dynamics with an improved adaptive cubature Kalman filter(IACKF)algorithm.First,a terminal impact time feedback term is introduced into proportional navigation guidance based on the relative virtual guidance model,and terminal time control is achieved through optimal error dynamics.Then,the Huber loss function is used to reduce the impact of measurement outliers,and the diagonal decomposition is applied to address the issue of non-positive definite matrices that cannot undergo Cholesky decomposition.Finally,the ITCCG and IACKF algorithms combined achieve multi-UAV time-cooperated guidance based on maneuvering target state estimation.Simulation results show that the proposed algorithm effectively reduces the target state estimation error and achieves cooperative guidance within the desired time frame.展开更多
The 6D pose estimation of objects is of great significance for the intelligent assembly and sorting of industrial parts.In the industrial robot production scenarios,the 6D pose estimation of industrial parts mainly fa...The 6D pose estimation of objects is of great significance for the intelligent assembly and sorting of industrial parts.In the industrial robot production scenarios,the 6D pose estimation of industrial parts mainly faces two challenges:one is the loss of information and interference caused by occlusion and stacking in the sorting scenario,the other is the difficulty of feature extraction due to the weak texture of industrial parts.To address the above problems,this paper proposes an attention-based pixel-level voting network for 6D pose estimation of weakly textured industrial parts,namely CB-PVNet.On the one hand,the voting scheme can predict the keypoints of affected pixels,which improves the accuracy of keypoint localization even in scenarios such as weak texture and partial occlusion.On the other hand,the attention mechanism can extract interesting features of the object while suppressing useless features of surroundings.Extensive comparative experiments were conducted on both public datasets(including LINEMOD,Occlusion LINEMOD and T-LESS datasets)and self-made datasets.The experimental results indicate that the proposed network CB-PVNet can achieve accuracy of ADD(-s)comparable to state-of-the-art using only RGB images while ensuring real-time performance.Additionally,we also conducted robot grasping experiments in the real world.The balance between accuracy and computational efficiency makes the method well-suited for applications in industrial automation.展开更多
(Quasi-)closed-form results for the statistical properties of unmanned aerial vehicle(UAV)airto-ground channels are derived for the first time using a novel spatial-vector-based method from a threedimensional(3-D)arbi...(Quasi-)closed-form results for the statistical properties of unmanned aerial vehicle(UAV)airto-ground channels are derived for the first time using a novel spatial-vector-based method from a threedimensional(3-D)arbitrary-elevation one-cylinder model.The derived results include a closed-form expression for the space-time correlation function and some quasi-closed-form ones for the space-Doppler power spectrum density,the level crossing rate,and the average fading duration,which are shown to be the generalizations of those previously obtained from the two-dimensional(2-D)one-ring model and the 3-D low-elevation one-cylinder model for terrestrial mobile-to-mobile channels.The close agreements between the theoretical results and the simulations as well as the measurements validate the utility of the derived channel statistics.Based on the derived expressions,the impacts of some parameters on the channel characteristics are investigated in an effective,efficient,and explicable way,which leads to a general guideline on the manual parameter estimation from the measurement description.展开更多
AIM:To build a functional generalized estimating equation(GEE)model to detect glaucomatous visual field progression and compare the performance of the proposed method with that of commonly employed algorithms.METHODS:...AIM:To build a functional generalized estimating equation(GEE)model to detect glaucomatous visual field progression and compare the performance of the proposed method with that of commonly employed algorithms.METHODS:Totally 716 eyes of 716 patients with primary open angle glaucoma(POAG)with at least 5 reliable 24-2 test results and 2y of follow-up were selected.The functional GEE model was used to detect perimetric progression in the training dataset(501 eyes).In the testing dataset(215 eyes),progression was evaluated the functional GEE model,mean deviation(MD)and visual field index(VFI)rates of change,Advanced Glaucoma Intervention Study(AGIS)and Collaborative Initial Glaucoma Treatment Study(CIGTS)scores,and pointwise linear regression(PLR).RESULTS:The proposed method showed the highest proportion of eyes detected as progression(54.4%),followed by the VFI rate(34.4%),PLR(23.3%),and MD rate(21.4%).The CIGTS and AGIS scores had a lower proportion of eyes detected as progression(7.9%and 5.1%,respectively).The time to detection of progression was significantly shorter for the proposed method than that of other algorithms(adjusted P≤0.019).The VFI rate displayed moderate pairwise agreement with the proposed method(k=0.47).CONCLUSION:The functional GEE model shows the highest proportion of eyes detected as perimetric progression and the shortest time to detect perimetric progression in patients with POAG.展开更多
Accurate estimation of photovoltaic(PV)parameters is essential for optimizing solar module perfor-mance and enhancing resource efficiency in renewable energy systems.This study presents a process innovation by introdu...Accurate estimation of photovoltaic(PV)parameters is essential for optimizing solar module perfor-mance and enhancing resource efficiency in renewable energy systems.This study presents a process innovation by introducing,for the first time,the Triangulation Topology Aggregation Optimizer(TTAO)integrated with parallel computing to address PV parameter estimation challenges.The effectiveness and robustness of TTAO are rigorously evaluated using two standard benchmark datasets(KC200GT and R.T.C.France solar cells)and a real-world dataset(Poly70W solar module)under single-,double-,and triple-diode configurations.Results show that TTAO consistently achieves superior accuracy by producing the lowest RMSE values and faster convergence compared to state-of-the-art metaheuristic algorithms.In addition,the integration of parallel computing significantly enhances computational efficiency,reducing execution time by up to 85%without compromising accuracy.Validation using real-world data further demonstrates TTAO’s adaptability and practical relevance in renewable energy systems,effectively bridging the gap between theoretical modeling and real-world implementation for PV system monitoring and optimization,contributing to climate mitigation through improved solar energy performance.展开更多
基金Mathematical Tianyuan Foundation(No.10826028)National Natural Science Foundation of China(Grant No.10771127,10571107)
文摘In this paper we prove zero-density estimates of the large sieve type for the automorphic L-function L（s, f × χ）, where f is a holomorphic cusp form and χ（mod q） is a primitive character.
基金Supported by NSFC(Nos.12371051,12141101,11871126)。
文摘In this paper,we study and characterize the volume estimates of geodesic balls on Finsler gradient Ricci solitons.We get the upper bounds on the volumes of geodesic balls of all three kinds of Finsler gradient Ricci solitons under certain condition about the Laplacian of thedistance function.
基金supported by the NSFC(12071437)the National Key R&D Program of China(2022YFA1005700).
文摘Combining TT* argument and bilinear interpolation,this paper obtains the Strichartz and smoothing estimates of dispersive semigroup e^(-itP(D)) in weighted L^(2) spaces.Among other things,we recover the results in[1].Moreover,the application of these results to the well-posedness of some equations are shown in the last section.
基金part of the project“Qualitative and numerical analyses of some thermomechanics problems(ACUANUTER)”(Ref.PID2024-156827NB-I00)。
文摘We consider the space and time decays of certain problems within the second gradient thermal law.Notably,for this thermal theory,the exponential time decay is precluded.First,the time estimates of polynomial type are obtained for both the thermal equation and the one-dimensional thermoelastic system,where the impossibility of localization with respect to time is also established.Then,the space estimates are deduced for the multidimensional thermoelastic problem,which allow to show the exponential decay of the energy.
基金supported by the National Key Research and Development Program of China (2023YFD1902703)the National Natural Science Foundation of China (Key Program) (U23A20158)。
文摘Cropland nitrate leaching is the major nitrogen(N) loss pathway, and it contributes significantly to water pollution. However, cropland nitrate leaching estimates show great uncertainty due to variations in input datasets and estimation methods. Here, we presented a re-evaluation of Chinese cropland nitrate leaching, and identified and quantified the sources of uncertainty by integrating three cropland area datasets, three N input datasets, and three estimation methods. The results revealed that nitrate leaching from Chinese cropland averaged 6.7±0.6 Tg N yr^(-1)in 2010, ranging from 2.9 to 15.8 Tg N yr^(-1)across 27 different estimates. The primary contributor to the uncertainty was the estimation method, accounting for 45.1%, followed by the interaction of N input dataset and estimation method at 24.4%. The results of this study emphasize the need for adopting a robust estimation method and improving the compatibility between the estimation method and N input dataset to effectively reduce uncertainty. This analysis provides valuable insights for accurately estimating cropland nitrate leaching and contributes to ongoing efforts that address water pollution concerns.
基金Supported by the National Natural Science Foundation of China (Grant Nos.1236108412001130)。
文摘This paper is devoted to the Polynomial Preserving Recovery (PPR) based a posteriori error analysis for the second-order elliptic non-symmetric eigenvalue problem. An asymptotically exact a posteriori error estimator is proposed for solving the convection-dominated non-symmetric eigenvalue problem with non-smooth eigenfunctions or multiple eigenvalues. Numerical examples confirm our theoretical analysis.
基金supported by the National Natural Science Foundation of China(NSFC,grant number U2039207).
文摘Earthquakes can cause significant damage and loss of life,necessitating immediate assessment of the resulting fatalities.Rapid assessment and timely revision of fatality estimates are crucial for effective emergency decisionmaking.This study using the February 6,2023,M_(S)8.0 and M_(S)7.9 Kahramanmaras,Türkiye earthquakes as an example to estimate the ultimate number of fatalities.An early Quick Rough Estimate(QRE)based on the number of deaths reported by the Disaster and Emergency Management Presidency of Türkiye(AFAD)is conducted,and it dynamically adjusts these estimates as new data becomes available.The range of estimates of the final number of deaths can be calculated as 31384–56475 based on the"the QRE of the second day multiplied by 2–3" rule,which incorporates the reported final deaths 50500.The Quasi-Linear and Adaptive Estimation(QLAE)method adaptively adjusts the final fatality estimate within two days and predicts subsequent reported deaths.The correct order of magnitude of the final death toll can be estimated as early as 13 hr after the M_(S)8.0 earthquake.In addition,additional earthquakes such as May 12,2008,M_(S)8.1 Wenchuan earthquake(China),September 8,2023,M_(S)7.2 Al Haouz earthquake(Morocco),November 3,2023,M_(S)5.8 Mid-Western Nepal earthquake,December 18,2023,M_(S)6.1 Jishishan earthquake(China),January 1,2024,M_(S)7.2 Noto Peninsula earthquake(Japan)and August 8,2023,Maui,Hawaii,fires are added again to verified the correctness of the model.The fatalities from the Maui fires are found to be approximately equivalent to those resulting from an M_(S)7.4 earthquake.These methods complement existing frameworks such as Quake Loss Assessment for Response and Mitigation(QLARM)and Prompt Assessment of Global.
基金supported by the National Natural Science Foundation of China(No.11971157).
文摘In this paper, we derive the a priori estimates for a class of more general (k, l)-Hessian quotient type equations involving u and Du on the right hand function. As an application we prove the Liouville theorem depending on Pogorelov type estimates. On the other hand, we obtain the existence and uniqueness of the k-admissible solution for these general equations with the Neumann boundary condition, based on some growth conditions for the right hand function.
文摘In this article,we are concerned with the C^(2)estimates for the k-convex solutions of a class of degenerate k-Hessian equations on closed Hermitian manifolds,whose function in the right-hand side is relevant to the unknown function and its gradient.We will get C^(0)estimate by promoting others′results,and get the“HMW estimate”of this equation such that the conditions of using blow-up analysis are satisfied,and the gradient estimate and second-order estimate will be obtained.Such an estimate will be helpful to study the existence for the solution of the equation.
基金supported by the Natural Science Research Project of Anhui Educational Committee(2023AH040155)Zhisu Liu's research was supported by the Guangdong Basic and Applied Basic Research Foundation(2023A1515011679+2 种基金2024A1515012704)the Fundamental Research Funds for the Central Universities,China University of Geosciences(Wuhan)(CUG2106211CUGST2).
文摘The paper is concerned with a class of elliptic equation with critical exponent and Dipole potential.More precisely,we make use of the refined Sobolev inequality with Morrey norm to obtain the existence and decay properties of nonnegative radial ground state solutions.
基金supported by the NSFC(12331007)the National Key Research and Development Program of China(2020YFA0713803)。
文摘In this paper,for the 1-D semilinear wave equation∂_(t)^(2)u-∂_(x)^(2)u+μ/t∂_(t)u=|u|~p with scaling invariant damping,where t≥1,p>1 andμ∈(0,1)∪(1,4/3),we establish the global weighted space-time estimates as well as the global existence of small data weak solution u when the nonlinearity power p is larger than some critical power p_(crit)(μ).Our proof is based on a class of new weighted Strichartz estimates with the weight t^(θ)|(1-μ)^(2)t^(2/|1-μ|)-x^(2)|^(γ)(θ>0andγ>0 are appropriate constants)for the solution of linear generalized Tricomi equation∂_(t)^(2)φ-t^(m)∂_(x)^(2)φ=0 with m being any fixed positive number.
基金supported by National Natural Science Foundation(NNSF)of China under Grant 62001351the Foundation of National Key Laboratory of Electromagnetic Environment(6142403220202)the Stability Support Fund for Basic Military Industrial Research Institutes(A240104130).
文摘The orthogonal time frequency space(OTFS)modulation is a novel modulation scheme that can effectively cope with the high Doppler expansion caused by high mobility.Since it modulates data on delay-Doppler(DD)domain and makes full use of the sparse characteristics of DD domain,it has been widely studied to design efficient channel estimation and signal detection schemes.In this paper,we design a novel superimposed pilot pattern with transition band,which replaces the traditional embedded pilot(EP)guard zero-symbols,and perform a two-stage channel estimation.In the first stage,we fully utilize the dispersion characteristics of OTFS signal in DD domain,and use threshold decision to make coarse channel estimation.In the second stage,we use the results of the coarse estimation for iterative signal detection and accurate channel estimation.During the second stage,we make full use of the sparsity of the channel in DD domain,remodel the received signal into the form of sparse channel vector multiplied by channel coefficient matrix,and introduce Doppler index segmentation factor(DISF)to subdivide the Doppler index to solve the problem of fractional Doppler.Simulations reveal that,the scheme proposed in this paper has higher spectral efficiency compared with traditional EP scheme and lower peak-to-average power ratio(PAPR)compared with traditional superimposed pilot scheme.
基金National Key Laboratory of Unmanned Aerial Vehicle Technology(No.202408)Key Laboratory of Smart Earth(No.KF2023ZD01-05)。
文摘In GNSS-denied environments,signals of opportunity(SOP)offer an efficient and passive solution for navigation and positioning by utilizing ambient signals.Nevertheless,conventional SOP techniques face significant challenges in real-time processing,especially under sub-Nyquist sampling conditions,due to high data acquisition rates and offgrid errors.To address this,this paper proposes the signal reconstruction and kernel sparse encoding(SRKSE)model,a novel general framework for high-precision parameter estimation.By combining compressed sensing with a deep unfolding network,the SRKSE model not only achieves robust signal reconstruction but also effectively reduces quantization errors.Key innovations of SRKSE include dual crossattention mechanisms for enhanced feature extraction,sinc sparse kernel encoding to minimize quantization errors,and a custom loss function for balanced optimization.With these advancements,SRKSE achieves up to a 650-fold improvement in time of arrival(TOA)estimation accuracy while operating at just 1%of the Nyquist sampling rate.The SRKSE surpasses both conventional and deep learning-based techniques in accuracy and efficiency,especially when operating under sub-Nyquist sampling conditions.Simulations and real-world experiments confirm the reliability and potential of SRKSE for real-time applications in IoT and wireless communication.
基金supported by the National Natural Science Foundation of China(No.52207228)the Beijing Natural Science Foundation,China(No.3224070)the National Natural Science Foundation of China(No.52077208).
文摘The growing use of lithium-ion batteries in electric transportation and grid-scale storage systems has intensified the need for accurate and highly generalizable state-of-health(SOH)estimation.Conventional approaches often suffer from reduced accuracy under dynamically uncertain state-of-charge(SOC)operating ranges and heterogeneous aging stresses.This study presents a unified SOH estimation framework that integrates physics-informed modeling,subspace identification,and Transformer-based learning.A reduced-order model is derived from simplified electrochemical dynamics,providing an interpretable and computationally efficient representation of battery behavior.Subspace identification across a wide SOC and SOH range yields degradation-sensitive features,which the Transformer uses to capture long-range aging dynamics via multi-head self-attention.Experiments on LiFePO4 cells under joint-cell training show consistently accurate SOH estimation,with a maximum error of 1.39%,demonstrating the framework’s effectiveness in decoupling SOC and SOH effects.In cross-cell validation,where training and validation are performed on different cells,the model maintains a maximum error of 2.06%,confirming strong generalization to unseen aging trajectories.Comparative experiments on LiFePO_(4)and public LiCoO_(2)datasets confirm the framework’s cross-chemistry applicability.By extracting low-dimensional,physically interpretable features via subspace identification,the framework significantly reduces training cost while maintaining high SOH estimation accuracy,outperforming conventional data-driven models lacking physical guidance.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.12274348 and 12004335)the National Key Research and Development Program of China(Grant No.2024YFC2813800)。
文摘Presented in this study is a novel method for estimating the depth of single underwater source in shallow water,utilizing vector sensors.The approach leverages the depth distribution of the broadband Stokes parameters to estimate source depth accurately.Unlike traditional matched field processing(MFP)and matched mode processing(MMP),the proposed approach can estimate source depth directly from the data received by sensors without requiring complete environmental information.Firstly,the broadband Stokes parameters(BSP)are established using the normal mode theory.Then the nonstationary phase approximation is used to simplify the theoretical derivation,which is necessary when dealing with broadband integrals.Additionally,range terms of the BSP are eliminated by normalization.By analyzing the depth distribution of the normalized broadband Stokes parameters(NBSP),it is found that the NBSP exhibit extreme values at the source depth,which can be used for source depth estimation.So the proposed depth estimation method is based on searching the peaks of the NBSP.Simulations show that this method is effective in relatively simple shallow water environments.Finally,the effect of source range,frequency bandwidth,sound speed profile(SSP),water depth,and signal-to-noise ratio(SNR)are studied.The findings indicate that the proposed method can accurately estimate the source depth when the SNR is greater than-5 d B and does not need to consider model mismatch issues.Additionally,variations in environmental parameters have minimal impact on estimation accuracy.Compared to MFP,the proposed method requires a higher SNR,but demonstrates superior robustness against fluctuations in environmental parameters.
基金supported by the Fundamental Research Funds for the Central Universities of China(FRF-TP-24-058A)with additional support from the National Key Laboratory of Helicopter Aeromechanics(2024-ZSJ-LB-02-02).
文摘Considering the impact of terminal impact time constraints and the state information of maneuvering targets on the guidance accuracy in multi-UAV cooperative guidance,this paper proposes an impact time cooperative control guidance law(ITCCG)that combines the optimal error dynamics with an improved adaptive cubature Kalman filter(IACKF)algorithm.First,a terminal impact time feedback term is introduced into proportional navigation guidance based on the relative virtual guidance model,and terminal time control is achieved through optimal error dynamics.Then,the Huber loss function is used to reduce the impact of measurement outliers,and the diagonal decomposition is applied to address the issue of non-positive definite matrices that cannot undergo Cholesky decomposition.Finally,the ITCCG and IACKF algorithms combined achieve multi-UAV time-cooperated guidance based on maneuvering target state estimation.Simulation results show that the proposed algorithm effectively reduces the target state estimation error and achieves cooperative guidance within the desired time frame.
基金supported by the Knowledge Innovation Program of Wuhan-Shuguang Project(Grant No.2023010201020443)the School-Level Scientific Research Project Funding Program of Jianghan University(Grant No.2022XKZX33)the Natural Science Foundation of Hubei Province(Grant No.2024AFB466).
文摘The 6D pose estimation of objects is of great significance for the intelligent assembly and sorting of industrial parts.In the industrial robot production scenarios,the 6D pose estimation of industrial parts mainly faces two challenges:one is the loss of information and interference caused by occlusion and stacking in the sorting scenario,the other is the difficulty of feature extraction due to the weak texture of industrial parts.To address the above problems,this paper proposes an attention-based pixel-level voting network for 6D pose estimation of weakly textured industrial parts,namely CB-PVNet.On the one hand,the voting scheme can predict the keypoints of affected pixels,which improves the accuracy of keypoint localization even in scenarios such as weak texture and partial occlusion.On the other hand,the attention mechanism can extract interesting features of the object while suppressing useless features of surroundings.Extensive comparative experiments were conducted on both public datasets(including LINEMOD,Occlusion LINEMOD and T-LESS datasets)and self-made datasets.The experimental results indicate that the proposed network CB-PVNet can achieve accuracy of ADD(-s)comparable to state-of-the-art using only RGB images while ensuring real-time performance.Additionally,we also conducted robot grasping experiments in the real world.The balance between accuracy and computational efficiency makes the method well-suited for applications in industrial automation.
基金supported in part by the National Key Research and Development Program of China(2021YFB2900501)in part by the Shaanxi Science and Technology Innovation Team(2023-CX-TD-03)+3 种基金in part by the Science and Technology Program of Shaanxi Province(2021GXLH-Z-038)in part by the Natural Science Foundation of Hunan Province(2023JJ40607 and 2023JJ50045)in part by the Scientific Research Foundation of Hunan Provincial Education Department(23B0713 and 24B0603)in part by the National Natural Science Foundation of China(62401371,62101275,and 62372070).
文摘(Quasi-)closed-form results for the statistical properties of unmanned aerial vehicle(UAV)airto-ground channels are derived for the first time using a novel spatial-vector-based method from a threedimensional(3-D)arbitrary-elevation one-cylinder model.The derived results include a closed-form expression for the space-time correlation function and some quasi-closed-form ones for the space-Doppler power spectrum density,the level crossing rate,and the average fading duration,which are shown to be the generalizations of those previously obtained from the two-dimensional(2-D)one-ring model and the 3-D low-elevation one-cylinder model for terrestrial mobile-to-mobile channels.The close agreements between the theoretical results and the simulations as well as the measurements validate the utility of the derived channel statistics.Based on the derived expressions,the impacts of some parameters on the channel characteristics are investigated in an effective,efficient,and explicable way,which leads to a general guideline on the manual parameter estimation from the measurement description.
基金Supported by the Korea Health Technology R&D Project through the Korea Health Industry Development Institute(KHIDI),funded by the Ministry of Health&Welfare,Republic of Korea(No.HR20C0026)the National Research Foundation of Korea(NRF)(No.RS-2023-00247504)the Patient-Centered Clinical Research Coordinating Center,funded by the Ministry of Health&Welfare,Republic of Korea(No.HC19C0276).
文摘AIM:To build a functional generalized estimating equation(GEE)model to detect glaucomatous visual field progression and compare the performance of the proposed method with that of commonly employed algorithms.METHODS:Totally 716 eyes of 716 patients with primary open angle glaucoma(POAG)with at least 5 reliable 24-2 test results and 2y of follow-up were selected.The functional GEE model was used to detect perimetric progression in the training dataset(501 eyes).In the testing dataset(215 eyes),progression was evaluated the functional GEE model,mean deviation(MD)and visual field index(VFI)rates of change,Advanced Glaucoma Intervention Study(AGIS)and Collaborative Initial Glaucoma Treatment Study(CIGTS)scores,and pointwise linear regression(PLR).RESULTS:The proposed method showed the highest proportion of eyes detected as progression(54.4%),followed by the VFI rate(34.4%),PLR(23.3%),and MD rate(21.4%).The CIGTS and AGIS scores had a lower proportion of eyes detected as progression(7.9%and 5.1%,respectively).The time to detection of progression was significantly shorter for the proposed method than that of other algorithms(adjusted P≤0.019).The VFI rate displayed moderate pairwise agreement with the proposed method(k=0.47).CONCLUSION:The functional GEE model shows the highest proportion of eyes detected as perimetric progression and the shortest time to detect perimetric progression in patients with POAG.
基金funded by the Malaysian Ministry of Higher Education through the Fundamental Research Grant Scheme(FRGS/1/2024/ICT02/UCSI/02/1).
文摘Accurate estimation of photovoltaic(PV)parameters is essential for optimizing solar module perfor-mance and enhancing resource efficiency in renewable energy systems.This study presents a process innovation by introducing,for the first time,the Triangulation Topology Aggregation Optimizer(TTAO)integrated with parallel computing to address PV parameter estimation challenges.The effectiveness and robustness of TTAO are rigorously evaluated using two standard benchmark datasets(KC200GT and R.T.C.France solar cells)and a real-world dataset(Poly70W solar module)under single-,double-,and triple-diode configurations.Results show that TTAO consistently achieves superior accuracy by producing the lowest RMSE values and faster convergence compared to state-of-the-art metaheuristic algorithms.In addition,the integration of parallel computing significantly enhances computational efficiency,reducing execution time by up to 85%without compromising accuracy.Validation using real-world data further demonstrates TTAO’s adaptability and practical relevance in renewable energy systems,effectively bridging the gap between theoretical modeling and real-world implementation for PV system monitoring and optimization,contributing to climate mitigation through improved solar energy performance.
