This paper deals with Mckean-Vlasov backward stochastic differential equations with weak monotonicity coefficients.We first establish the existence and uniqueness of solutions to Mckean-Vlasov backward stochastic diff...This paper deals with Mckean-Vlasov backward stochastic differential equations with weak monotonicity coefficients.We first establish the existence and uniqueness of solutions to Mckean-Vlasov backward stochastic differential equations.Then we obtain a comparison theorem in one-dimensional situation.展开更多
The generation of synthetic trajectories has become essential in various fields for analyzing complex movement patterns.However,the use of real-world trajectory data poses significant privacy risks,such as location re...The generation of synthetic trajectories has become essential in various fields for analyzing complex movement patterns.However,the use of real-world trajectory data poses significant privacy risks,such as location reidentification and correlation attacks.To address these challenges,privacy-preserving trajectory generation methods are critical for applications relying on sensitive location data.This paper introduces DPIL-Traj,an advanced framework designed to generate synthetic trajectories while achieving a superior balance between data utility and privacy preservation.Firstly,the framework incorporates Differential Privacy Clustering,which anonymizes trajectory data by applying differential privacy techniques that add noise,ensuring the protection of sensitive user information.Secondly,Imitation Learning is used to replicate decision-making behaviors observed in real-world trajectories.By learning from expert trajectories,this component generates synthetic data that closely mimics real-world decision-making processes while optimizing the quality of the generated trajectories.Finally,Markov-based Trajectory Generation is employed to capture and maintain the inherent temporal dynamics of movement patterns.Extensive experiments conducted on the GeoLife trajectory dataset show that DPIL-Traj improves utility performance by an average of 19.85%,and in terms of privacy performance by an average of 12.51%,compared to state-of-the-art approaches.Ablation studies further reveal that DP clustering effectively safeguards privacy,imitation learning enhances utility under noise,and the Markov module strengthens temporal coherence.展开更多
Poly(phenylene oxide)(PPO)exhibits excellent dielectric properties,making it an ideal substrate for high-frequency,high-speed copper-clad laminates.The phenolic hydroxyl group at the end of PPO plays a key role in its...Poly(phenylene oxide)(PPO)exhibits excellent dielectric properties,making it an ideal substrate for high-frequency,high-speed copper-clad laminates.The phenolic hydroxyl group at the end of PPO plays a key role in its reactivity.Accurately quantifying the phenolic hydroxyl content in PPO is essential but challenging.In this study,we proposed a method for measuring the phenolic hydroxyl content of PPO using differential UV absorption spectroscopy.In alkaline solutions,the phenolic hydroxyl in PPO completely ionizes to form phenoxide ions,leading to a significant increase in UV absorbance at approximately 250 and 300 nm.Notably,the differential UV absorbance at approximately 300 nm was directly proportional to the phenolic hydroxyl concentration.Using 2,6-dimethylphenol as a standard,a calibration curve was established to relate the phenolic hydroxyl concentration to differential UV absorbance at approximately 300 nm,providing a precise and straightforward method for phenolic hydroxyl quantification in PPO with distinct advantages over conventional techniques.展开更多
In reliability analyses,the absence of a priori information on the most probable point of failure(MPP)may result in overlooking critical points,thereby leading to biased assessment outcomes.Moreover,second-order relia...In reliability analyses,the absence of a priori information on the most probable point of failure(MPP)may result in overlooking critical points,thereby leading to biased assessment outcomes.Moreover,second-order reliability methods exhibit limited accuracy in highly nonlinear scenarios.To overcome these challenges,a novel reliability analysis strategy based on a multimodal differential evolution algorithm and a hypersphere integration method is proposed.Initially,the penalty function method is employed to reformulate the MPP search problem as a conditionally constrained optimization task.Subsequently,a differential evolution algorithm incorporating a population delineation strategy is utilized to identify all MPPs.Finally,a paraboloid equation is constructed based on the curvature of the limit-state function at the MPPs,and the failure probability of the structure is calculated by using the hypersphere integration method.The localization effectiveness of the MPPs is compared through multiple numerical cases and two engineering examples,with accuracy comparisons of failure probabilities against the first-order reliability method(FORM)and the secondorder reliability method(SORM).The results indicate that the method effectively identifies existing MPPs and achieves higher solution precision.展开更多
[Objective]As wireless power transfer(WPT)technology is increasingly deployed in scenarios such as electric vehicles,metallic foreign objects in the WPT area may cause local overheating and energy loss.Existing method...[Objective]As wireless power transfer(WPT)technology is increasingly deployed in scenarios such as electric vehicles,metallic foreign objects in the WPT area may cause local overheating and energy loss.Existing methods still suffer from poor edge/corner sensitivity,misjudgment due to fixed thresholds,and limited ability to extract position information.This work proposes a wireless power transfer-foreign object detection(WPT-FOD)method based on channel differential response and a dynamic-threshold corner-enhancement strategy,aiming to improve detection sensitivity,localization accuracy,and robustness without altering the overall coil layout.[Method]A multi-channel detection coil array is designed,and the self-inductance disturbance response of each channel coil is modeled.A channel-difference mapping mechanism is introduced to build a 2-D sensitivity matrix to characterize spatial position correlation.A corner-enhancement algorithm is developed to weight and amplify the collaborative response of adjacent channels,and a dynamic threshold adjustment mechanism is integrated to adapt to varying interference levels.Validation is carried out on a self-built 64-channel FOD platform by moving a typical metallic foreign object across central,edge,and corner regions,and by conducting comparative tests under different interference intensities.[Result]When a typical metallic foreign object moves to corner regions,the self-inductance disturbance of the detection coil increases from less than 0.02μH to more than 0.06μH,significantly enhancing the discrimination capability at corners.Under varying interference strengths,the dynamic threshold mechanism reduces the number of false positives from 13 to 2,demonstrating good environmental adaptability and stability.[Conclusion]By combining channel differential response,corner enhancement,and dynamic thresholding,the proposed WPT-FOD effectively mitigates edge/corner blind spots and fixed-threshold misjudgment,while providing localization capability and robustness.It markedly improves the accuracy of metallic foreign object detection in WPT systems and offers a feasible path and method reference for the safe application and engineering deployment of WPT systems.展开更多
Addressing the limitations of inadequate stochastic disturbance characterization during wind turbine degradation processes that result in constrained modeling accuracy,replacement-based maintenance practices that devi...Addressing the limitations of inadequate stochastic disturbance characterization during wind turbine degradation processes that result in constrained modeling accuracy,replacement-based maintenance practices that deviate from actual operational conditions,and static maintenance strategies that fail to adapt to accelerated deterioration trends leading to suboptimal remaining useful life utilization,this study proposes a Time-Based Incomplete Maintenance(TBIM)strategy incorporating reliability constraints through stochastic differential equations(SDE).By quantifying stochastic interference via Brownian motion terms and characterizing nonlinear degradation features through state influence rate functions,a high-precision SDE degradation model is constructed,achieving 16%residual reduction compared to conventional ordinary differential equation(ODE)methods.The introduction of age reduction factors and failure rate growth factors establishes an incomplete maintenance mechanism that transcends traditional“as-good-as-new”assumptions,with the TBIM model demonstrating an additional 8.5%residual reduction relative to baseline SDE approaches.A dynamic maintenance interval optimization model driven by dual parameters—preventive maintenance threshold R_(p) and replacement threshold R_(r)—is designed to achieve synergistic optimization of equipment reliability and maintenance economics.Experimental validation demonstrates that the optimized TBIM extends equipment lifespan by 4.4%and reducesmaintenance costs by 4.16%at R_(p)=0.80,while achieving 17.2%lifespan enhancement and 14.6%cost reduction at R_(p)=0.90.This methodology provides a solution for wind turbine preventive maintenance that integrates condition sensitivity with strategic foresight.展开更多
Precisely estimating the state of health(SOH)of lithium-ion batteries is essential for battery management systems(BMS),as it plays a key role in ensuring the safe and reliable operation of battery systems.However,curr...Precisely estimating the state of health(SOH)of lithium-ion batteries is essential for battery management systems(BMS),as it plays a key role in ensuring the safe and reliable operation of battery systems.However,current SOH estimation methods often overlook the valuable temperature information that can effectively characterize battery aging during capacity degradation.Additionally,the Elman neural network,which is commonly employed for SOH estimation,exhibits several drawbacks,including slow training speed,a tendency to become trapped in local minima,and the initialization of weights and thresholds using pseudo-random numbers,leading to unstable model performance.To address these issues,this study addresses the challenge of precise and effective SOH detection by proposing a method for estimating the SOH of lithium-ion batteries based on differential thermal voltammetry(DTV)and an SSA-Elman neural network.Firstly,two health features(HFs)considering temperature factors and battery voltage are extracted fromthe differential thermal voltammetry curves and incremental capacity curves.Next,the Sparrow Search Algorithm(SSA)is employed to optimize the initial weights and thresholds of the Elman neural network,forming the SSA-Elman neural network model.To validate the performance,various neural networks,including the proposed SSA-Elman network,are tested using the Oxford battery aging dataset.The experimental results demonstrate that the method developed in this study achieves superior accuracy and robustness,with a mean absolute error(MAE)of less than 0.9%and a rootmean square error(RMSE)below 1.4%.展开更多
In order to solve the problem of the variable coefficient ordinary differen-tial equation on the bounded domain,the Lagrange interpolation method is used to approximate the exact solution of the equation,and the error...In order to solve the problem of the variable coefficient ordinary differen-tial equation on the bounded domain,the Lagrange interpolation method is used to approximate the exact solution of the equation,and the error between the numerical solution and the exact solution is obtained,and then compared with the error formed by the difference method,it is concluded that the Lagrange interpolation method is more effective in solving the variable coefficient ordinary differential equation.展开更多
The lamina(combination)types,reservoir characteristics and shale oil occurrence states of organic-rich shale in the Triassic Yanchang Formation Chang 73 sub-member in the Ordos Basin were systematically investigated t...The lamina(combination)types,reservoir characteristics and shale oil occurrence states of organic-rich shale in the Triassic Yanchang Formation Chang 73 sub-member in the Ordos Basin were systematically investigated to reveal the main controlling factors of shale oil occurrence under different lamina combinations.The differential enrichment mechanisms and patterns of shale oil were discussed using the shale oil micro-migration characterization and evaluation methods from the perspectives of relay hydrocarbon supply,stepwise migration,and multi-stage differentiation.The results are obtained in five aspects.First,Chang 73 shale mainly develops five types of lamina combination,i.e.non-laminated shale,sandy laminated shale,tuffaceous laminated shale,mixed laminated shale,and organic-rich laminated shale.Second,shales with different lamina combinations are obviously different in the reservoir space.Specifically,shales with sandy laminae and tuffaceous laminae have a large number of intergranular pores,dissolution pores and hydrocarbon generation-induced fractures.The multi-scale pore and fracture system constitutes the main place for liquid hydrocarbon occurrence.Third,the occurrence and distribution of shale oil in shale with different lamina combinations are jointly controlled by organic matter abundance,reservoir property,thermal evolution degree,mineral composition and laminae scale.The micro-nano-scale pore-fracture networks within shales containing rigid laminae,particularly sandy and tuffaceous laminations,primarily contain free-state light hydrocarbon components.In contrast,adsorption-phase heavy hydrocarbon components predominantly occupy surfaces of organic matter assemblages,clay mineral matrices,and framework mineral particulates.Fourth,there is obvious shale oil micro-migration between shales with different lamina combinations in Chang 73.Generally,such micro-migration is stepwise in a sequence of organic-rich laminated shale→tuffaceous laminated shale→mixed laminated shale→sandy lamiated shale→non-laminated shale.Fifth,the relay hydrocarbon supply of organic matter under the control of the spatial superposition of shales with various laminae,the stepwise migration via multi-scale pore and fracture network,and the multi-differentiation in shales with different lamina combinations under the control of organic-inorganic interactions fundamentally decide the differences of shale oil components between shales with different lamina combinations.展开更多
When the maneuverability of a pursuer is not significantly higher than that of an evader,it will be difficult to intercept the evader with only one pursuer.Therefore,this article adopts a two-to-one differential game ...When the maneuverability of a pursuer is not significantly higher than that of an evader,it will be difficult to intercept the evader with only one pursuer.Therefore,this article adopts a two-to-one differential game strategy,the game of kind is generally considered to be angle-optimized,which allows unlimited turns,but these practices do not take into account the effect of acceleration,which does not correspond to the actual situation,thus,based on the angle-optimized,the acceleration optimization and the acceleration upper bound constraint are added into the game for consideration.A two-to-one differential game problem is proposed in the three-dimensional space,and an improved multi-objective grey wolf optimization(IMOGWO)algorithm is proposed to solve the optimal game point of this problem.With the equations that describe the relative motions between the pursuers and the evader in the three-dimensional space,a multi-objective function with constraints is given as the performance index to design an optimal strategy for the differential game.Then the optimal game point is solved by using the IMOGWO algorithm.It is proved based on Markov chains that with the IMOGWO,the Pareto solution set is the solution of the differential game.Finally,it is verified through simulations that the pursuers can capture the escapee,and via comparative experiments,it is shown that the IMOGWO algorithm performs well in terms of running time and memory usage.展开更多
In this paper,we give a complete characterization of all self-adjoint domains of odd order differential operators on two intervals.These two intervals with all four endpoints are singular(one endpoint of each interval...In this paper,we give a complete characterization of all self-adjoint domains of odd order differential operators on two intervals.These two intervals with all four endpoints are singular(one endpoint of each interval is singular or all four endpoints are regulars are the special cases).And these extensions yield"new"self-adjoint operators,which involve interactions between the two intervals.展开更多
This paper studies the Smoluchowski–Kramers approximation for a discrete-time dynamical system modeled as the motion of a particle in a force field.We show that the approximation holds for the drift-implicit Euler–M...This paper studies the Smoluchowski–Kramers approximation for a discrete-time dynamical system modeled as the motion of a particle in a force field.We show that the approximation holds for the drift-implicit Euler–Maruyama discretization and derive its convergence rate.In particular,the solution of the discretized system converges to the solution of the first-order limit equation in the mean-square sense,and this convergence is independent of the order in which the mass parameterμand the step size h tend to zero.展开更多
The two-player nonzero-sum linear-exponential-quadratic stochastic differential game is studied.The game takes into account the players'attitudes to risk.The nonlinear transformations and change of probability mea...The two-player nonzero-sum linear-exponential-quadratic stochastic differential game is studied.The game takes into account the players'attitudes to risk.The nonlinear transformations and change of probability measure techniques are used to study the existence of both open-loop and closed-loop Nash equilibria for the game.Some examples are constructed to illustrate their differences.Furthermore,theoretical results are applied to solve the risk-sensitive portfolio game problem in the financial market and show the effects of risk attitudes and economic performance on equilibria.展开更多
In this article,we study the meromorphic solutions of the following non-linear differential equation■where n and k are integers with n≥k≥3,P_(d)(z,f)is a differential polynomial in f of degree d≤n−1,p′js andα′j...In this article,we study the meromorphic solutions of the following non-linear differential equation■where n and k are integers with n≥k≥3,P_(d)(z,f)is a differential polynomial in f of degree d≤n−1,p′js andα′js are non-zero constants.We obtain the expressions of meromorphic solutions of the above equations under some restrictions onα′js.Some examples are given to illustrate the possibilities of our results.展开更多
Based on the coalbed methane(CBM)/coal-rock gas(CRG)geological,geophysical,and experimental testing data from the Daji block in the Ordos Basin,the coal-forming and hydrocarbon generation&accumulation characterist...Based on the coalbed methane(CBM)/coal-rock gas(CRG)geological,geophysical,and experimental testing data from the Daji block in the Ordos Basin,the coal-forming and hydrocarbon generation&accumulation characteristics across different zones were dissected,and the key factors controlling the differential CBM/CRG enrichment were identified.The No.8 coal seam of the Carboniferous Benxi Formation in the Daji block is 8-10 m thick,typically overlain by limestone.The primary hydrocarbon generation phase occurred during the Early Cretaceous.Based on the differences in tectonic evolution and CRG occurrence,and with the maximum vitrinite reflectance of 2.0%and burial depth of 1800 m as boundaries,the study area is divided into deeply buried and deeply preserved,deeply buried and shallowly preserved,and shallowly buried and shallowly preserved zones.The deeply buried and deeply preserved zone contains gas content of 22-35 m^(3)/t,adsorbed gas saturation of 95%-100%,and formation water with total dissolved solid(TDS)higher than 50000 mg/L.This zone features structural stability and strong sealing capacity,with high gas production rates.The deeply buried and shallowly preserved zone contains gas content of 16-20 m^(3)/t,adsorbed gas saturation of 80%-95%,and formation water with TDS of 5000-50000 mg/L.This zone exhibits localized structural modification and hydrodynamic sealing,with moderate gas production rate.The shallowly buried and shallowly preserved zone contains gas content of 8-16 m^(3)/t,adsorbed gas saturation of 50%-70%,and formation water with TDS lower than 5000 mg/L.This zone experienced intense uplift,resulting in poor sealing and secondary alteration of the primary gas reservoir,with partial adsorbed gas loss,and low gas production rate.A depositional unification and structural divergence model is proposed,that is,although coal seams across the basin experienced broadly similar depositional and tectonic histories,differences in tectonic intensity have led to spatial heterogeneity in the maximum burial depth(i.e.,thermal maturity of coal)and current burial depth and occurrence of CRG(i.e.,gas content and occurrence state).The research results provide valuable guidance for advancing the theoretical understanding of CBM/CRG enrichment and for improving exploration and development practices.展开更多
This study aims to explore the clinical and CT imaging features of brucellosis spondylitis(BS)and to strengthen the clinical cognition to reduce misdiagnosis and mistreatment.In this study,clinical and CT imaging data...This study aims to explore the clinical and CT imaging features of brucellosis spondylitis(BS)and to strengthen the clinical cognition to reduce misdiagnosis and mistreatment.In this study,clinical and CT imaging data of 106 patients with BS diagnosed in the Second Hospital of Hohhot and the Third Hospital of Baotou were collected from March 2023 to September 2024 and retrospectively analyzed by clinical manifestations,CT imaging,and disease regression.In 106 patients,58.5%had fever,98.1%had malaise,96.2%had excessive sweating,81.1%had lumbosacral pain,79.3%had limitation of limb movement,76.4%had constipation,and 6.6%had urinary retention.For imaging manifestations,the involvement of lumbar,thoracic and cervical vertebrae were 80.2%,16.9%and 1.9%,respectively.Lesions<1.0 cm,1.0–2.0 cm,2.0–3.0 cm,and>3.0 cm were found in 49.4%,29.6%,19.4%,and 1.6%,respectively.In 106 patients,CT showed round,irregular or worm-like areas of bone destruction,with coexisting osteophytes in 61.5%and no signs of dead bone or pedicle destruction.Interdiscal destruction,spinal canal abscess,ligament injury,and signs of lumbar major muscle compression were rare,accounting for 11.7%,6.6%,4.7%,and 3.8%,respectively.Regarding regression,106 patients with BS treated with antimicrobial therapy or antimicrobial+surgery had a good prognosis.In conclusion,BS has its own characteristics in clinical and imaging aspects and it is easy to distinguish from other common causes of spondylitis bone damage.展开更多
Fractional differential equations(FDEs)provide a powerful tool for modeling systems with memory and non-local effects,but understanding their underlying structure remains a significant challenge.While numerous numeric...Fractional differential equations(FDEs)provide a powerful tool for modeling systems with memory and non-local effects,but understanding their underlying structure remains a significant challenge.While numerous numerical and semi-analytical methods exist to find solutions,new approaches are needed to analyze the intrinsic properties of the FDEs themselves.This paper introduces a novel computational framework for the structural analysis of FDEs involving iterated Caputo derivatives.The methodology is based on a transformation that recasts the original FDE into an equivalent higher-order form,represented as the sum of a closed-form,integer-order component G(y)and a residual fractional power seriesΨ(x).This transformed FDE is subsequently reduced to a first-order ordinary differential equation(ODE).The primary novelty of the proposed methodology lies in treating the structure of the integer-order component G(y)not as fixed,but as a parameterizable polynomial whose coefficients can be determined via global optimization.Using particle swarm optimization,the framework identifies an optimal ODE architecture by minimizing a dual objective that balances solution accuracy against a high-fidelity reference and the magnitude of the truncated residual series.The effectiveness of the approach is demonstrated on both a linear FDE and a nonlinear fractional Riccati equation.Results demonstrate that the framework successfully identifies an optimal,low-degree polynomial ODE architecture that is not necessarily identical to the forcing function of the original FDE.This work provides a new tool for analyzing the underlying structure of FDEs and gaining deeper insights into the interplay between local and non-local dynamics in fractional systems.展开更多
The rapid development and widespread adoption of massive open online courses(MOOCs)have indeed had a significant impact on China’s education curriculum.However,the problem of fake reviews and ratings on the platform ...The rapid development and widespread adoption of massive open online courses(MOOCs)have indeed had a significant impact on China’s education curriculum.However,the problem of fake reviews and ratings on the platform has seriously affected the authenticity of course evaluations and user trust,requiring effective anomaly detection techniques for screening.The textual characteristics of MOOCs reviews,such as varying lengths and diverse emotional tendencies,have brought complexity to text analysis.Traditional rule-based analysis methods are often inadequate in dealing with such unstructured data.We propose a Differential Privacy-Enabled Text Convolutional Neural Network(DP-TextCNN)framework,aiming to achieve high-precision identification of outliers in MOOCs course reviews and ratings while protecting user privacy.This framework leverages the advantages of Convolutional Neural Networks(CNN)in text feature extraction and combines differential privacy techniques.It balances data privacy protection with model performance by introducing controlled random noise during the data preprocessing stage.By embedding differential privacy into the model training process,we ensure the privacy security of the framework when handling sensitive data,while maintaining a high recognition accuracy.Experimental results indicate that the DP-TextCNN framework achieves an exceptional accuracy of over 95%in identifying fake reviews on the dataset,this outcome not only verifies the applicability of differential privacy techniques in TextCNN but also underscores its potential in handling sensitive educational data.Additionally,we analyze the specific impact of differential privacy parameters on framework performance,offering theoretical support and empirical analysis to strike an optimal balance between privacy protection and framework efficiency.展开更多
With the ongoing digitalization and intelligence of power systems,there is an increasing reliance on large-scale data-driven intelligent technologies for tasks such as scheduling optimization and load forecasting.Neve...With the ongoing digitalization and intelligence of power systems,there is an increasing reliance on large-scale data-driven intelligent technologies for tasks such as scheduling optimization and load forecasting.Nevertheless,power data often contains sensitive information,making it a critical industry challenge to efficiently utilize this data while ensuring privacy.Traditional Federated Learning(FL)methods can mitigate data leakage by training models locally instead of transmitting raw data.Despite this,FL still has privacy concerns,especially gradient leakage,which might expose users’sensitive information.Therefore,integrating Differential Privacy(DP)techniques is essential for stronger privacy protection.Even so,the noise from DP may reduce the performance of federated learning models.To address this challenge,this paper presents an explainability-driven power data privacy federated learning framework.It incorporates DP technology and,based on model explainability,adaptively adjusts privacy budget allocation and model aggregation,thus balancing privacy protection and model performance.The key innovations of this paper are as follows:(1)We propose an explainability-driven power data privacy federated learning framework.(2)We detail a privacy budget allocation strategy:assigning budgets per training round by gradient effectiveness and at model granularity by layer importance.(3)We design a weighted aggregation strategy that considers the SHAP value and model accuracy for quality knowledge sharing.(4)Experiments show the proposed framework outperforms traditional methods in balancing privacy protection and model performance in power load forecasting tasks.展开更多
In response to the shortcomings of the common encoders in the industry,of which the photoelectric encoders have a poor anti-interference ability in harsh industrial environments with water,oil,dust,or strong vibration...In response to the shortcomings of the common encoders in the industry,of which the photoelectric encoders have a poor anti-interference ability in harsh industrial environments with water,oil,dust,or strong vibrations and the magnetic encoders are too sensitive to magnetic field density,this paper designs a new differential encoder based on the grating eddy-current measurement principle,abbreviated as differential grating eddy-current encoder(DGECE).The grating eddy-current of DGECE consists of a circular array of trapezoidal reflection conductors and 16 trapezoidal coils with a special structure to form a differential relationship,which are respectively located on the code plate and the readout plate designed by a printed circuit board.The differential structure of DGECE corrects the common mode interference and the amplitude distortion due to the assembly to some extent,possesses a certain anti-interference capability,and greatly simplifies the regularization algorithm of the original data.By means of the corresponding readout circuit and demodulation algorithm,the DGECE can convert the periodic impedance variation of 16 coils into an angular output within the 360°cycle.Due to its simple manufacturing process and certain interference immunity,DGECE is easy to be integrated and mass-produced as well as applicable in the industrial spindles,especially in robot joints.This paper presents the measurement principle,implementation methods,and results of the experiment of the DGECE.The experimental results show that the accuracy of the DGECE can reach 0.237%and the measurement standard deviation can reach±0.14°within360°cycle.展开更多
基金Supported by the National Natural Science Foundation of China(12001074)the Research Innovation Program of Graduate Students in Hunan Province(CX20220258)+1 种基金the Research Innovation Program of Graduate Students of Central South University(1053320214147)the Key Scientific Research Project of Higher Education Institutions in Henan Province(25B110025)。
文摘This paper deals with Mckean-Vlasov backward stochastic differential equations with weak monotonicity coefficients.We first establish the existence and uniqueness of solutions to Mckean-Vlasov backward stochastic differential equations.Then we obtain a comparison theorem in one-dimensional situation.
基金supported by the Natural Science Foundation of Fujian Province of China(2025J01380)National Natural Science Foundation of China(No.62471139)+3 种基金the Major Health Research Project of Fujian Province(2021ZD01001)Fujian Provincial Units Special Funds for Education and Research(2022639)Fujian University of Technology Research Start-up Fund(GY-S24002)Fujian Research and Training Grants for Young and Middle-aged Leaders in Healthcare(GY-H-24179).
文摘The generation of synthetic trajectories has become essential in various fields for analyzing complex movement patterns.However,the use of real-world trajectory data poses significant privacy risks,such as location reidentification and correlation attacks.To address these challenges,privacy-preserving trajectory generation methods are critical for applications relying on sensitive location data.This paper introduces DPIL-Traj,an advanced framework designed to generate synthetic trajectories while achieving a superior balance between data utility and privacy preservation.Firstly,the framework incorporates Differential Privacy Clustering,which anonymizes trajectory data by applying differential privacy techniques that add noise,ensuring the protection of sensitive user information.Secondly,Imitation Learning is used to replicate decision-making behaviors observed in real-world trajectories.By learning from expert trajectories,this component generates synthetic data that closely mimics real-world decision-making processes while optimizing the quality of the generated trajectories.Finally,Markov-based Trajectory Generation is employed to capture and maintain the inherent temporal dynamics of movement patterns.Extensive experiments conducted on the GeoLife trajectory dataset show that DPIL-Traj improves utility performance by an average of 19.85%,and in terms of privacy performance by an average of 12.51%,compared to state-of-the-art approaches.Ablation studies further reveal that DP clustering effectively safeguards privacy,imitation learning enhances utility under noise,and the Markov module strengthens temporal coherence.
基金the“Pioneer”and“Leading Goose”R&D Program of Zhejiang(No.2023C01072)the Institute of Zhejiang University-Quzhou for their financial support。
文摘Poly(phenylene oxide)(PPO)exhibits excellent dielectric properties,making it an ideal substrate for high-frequency,high-speed copper-clad laminates.The phenolic hydroxyl group at the end of PPO plays a key role in its reactivity.Accurately quantifying the phenolic hydroxyl content in PPO is essential but challenging.In this study,we proposed a method for measuring the phenolic hydroxyl content of PPO using differential UV absorption spectroscopy.In alkaline solutions,the phenolic hydroxyl in PPO completely ionizes to form phenoxide ions,leading to a significant increase in UV absorbance at approximately 250 and 300 nm.Notably,the differential UV absorbance at approximately 300 nm was directly proportional to the phenolic hydroxyl concentration.Using 2,6-dimethylphenol as a standard,a calibration curve was established to relate the phenolic hydroxyl concentration to differential UV absorbance at approximately 300 nm,providing a precise and straightforward method for phenolic hydroxyl quantification in PPO with distinct advantages over conventional techniques.
基金National Natural Science Foundation of China(No.52375236)Fundamental Research Funds for the Central Universities of China(No.23D110316)。
文摘In reliability analyses,the absence of a priori information on the most probable point of failure(MPP)may result in overlooking critical points,thereby leading to biased assessment outcomes.Moreover,second-order reliability methods exhibit limited accuracy in highly nonlinear scenarios.To overcome these challenges,a novel reliability analysis strategy based on a multimodal differential evolution algorithm and a hypersphere integration method is proposed.Initially,the penalty function method is employed to reformulate the MPP search problem as a conditionally constrained optimization task.Subsequently,a differential evolution algorithm incorporating a population delineation strategy is utilized to identify all MPPs.Finally,a paraboloid equation is constructed based on the curvature of the limit-state function at the MPPs,and the failure probability of the structure is calculated by using the hypersphere integration method.The localization effectiveness of the MPPs is compared through multiple numerical cases and two engineering examples,with accuracy comparisons of failure probabilities against the first-order reliability method(FORM)and the secondorder reliability method(SORM).The results indicate that the method effectively identifies existing MPPs and achieves higher solution precision.
文摘[Objective]As wireless power transfer(WPT)technology is increasingly deployed in scenarios such as electric vehicles,metallic foreign objects in the WPT area may cause local overheating and energy loss.Existing methods still suffer from poor edge/corner sensitivity,misjudgment due to fixed thresholds,and limited ability to extract position information.This work proposes a wireless power transfer-foreign object detection(WPT-FOD)method based on channel differential response and a dynamic-threshold corner-enhancement strategy,aiming to improve detection sensitivity,localization accuracy,and robustness without altering the overall coil layout.[Method]A multi-channel detection coil array is designed,and the self-inductance disturbance response of each channel coil is modeled.A channel-difference mapping mechanism is introduced to build a 2-D sensitivity matrix to characterize spatial position correlation.A corner-enhancement algorithm is developed to weight and amplify the collaborative response of adjacent channels,and a dynamic threshold adjustment mechanism is integrated to adapt to varying interference levels.Validation is carried out on a self-built 64-channel FOD platform by moving a typical metallic foreign object across central,edge,and corner regions,and by conducting comparative tests under different interference intensities.[Result]When a typical metallic foreign object moves to corner regions,the self-inductance disturbance of the detection coil increases from less than 0.02μH to more than 0.06μH,significantly enhancing the discrimination capability at corners.Under varying interference strengths,the dynamic threshold mechanism reduces the number of false positives from 13 to 2,demonstrating good environmental adaptability and stability.[Conclusion]By combining channel differential response,corner enhancement,and dynamic thresholding,the proposed WPT-FOD effectively mitigates edge/corner blind spots and fixed-threshold misjudgment,while providing localization capability and robustness.It markedly improves the accuracy of metallic foreign object detection in WPT systems and offers a feasible path and method reference for the safe application and engineering deployment of WPT systems.
基金supported in part by the National Natural Science Foundation of China(No.52467008)Gansu Provincial Depatment of Education Youth Doctoral Suppo Project(2024QB-051).
文摘Addressing the limitations of inadequate stochastic disturbance characterization during wind turbine degradation processes that result in constrained modeling accuracy,replacement-based maintenance practices that deviate from actual operational conditions,and static maintenance strategies that fail to adapt to accelerated deterioration trends leading to suboptimal remaining useful life utilization,this study proposes a Time-Based Incomplete Maintenance(TBIM)strategy incorporating reliability constraints through stochastic differential equations(SDE).By quantifying stochastic interference via Brownian motion terms and characterizing nonlinear degradation features through state influence rate functions,a high-precision SDE degradation model is constructed,achieving 16%residual reduction compared to conventional ordinary differential equation(ODE)methods.The introduction of age reduction factors and failure rate growth factors establishes an incomplete maintenance mechanism that transcends traditional“as-good-as-new”assumptions,with the TBIM model demonstrating an additional 8.5%residual reduction relative to baseline SDE approaches.A dynamic maintenance interval optimization model driven by dual parameters—preventive maintenance threshold R_(p) and replacement threshold R_(r)—is designed to achieve synergistic optimization of equipment reliability and maintenance economics.Experimental validation demonstrates that the optimized TBIM extends equipment lifespan by 4.4%and reducesmaintenance costs by 4.16%at R_(p)=0.80,while achieving 17.2%lifespan enhancement and 14.6%cost reduction at R_(p)=0.90.This methodology provides a solution for wind turbine preventive maintenance that integrates condition sensitivity with strategic foresight.
基金supported by the National Natural Science Foundation of China(NSFC)under Grant(No.51677058).
文摘Precisely estimating the state of health(SOH)of lithium-ion batteries is essential for battery management systems(BMS),as it plays a key role in ensuring the safe and reliable operation of battery systems.However,current SOH estimation methods often overlook the valuable temperature information that can effectively characterize battery aging during capacity degradation.Additionally,the Elman neural network,which is commonly employed for SOH estimation,exhibits several drawbacks,including slow training speed,a tendency to become trapped in local minima,and the initialization of weights and thresholds using pseudo-random numbers,leading to unstable model performance.To address these issues,this study addresses the challenge of precise and effective SOH detection by proposing a method for estimating the SOH of lithium-ion batteries based on differential thermal voltammetry(DTV)and an SSA-Elman neural network.Firstly,two health features(HFs)considering temperature factors and battery voltage are extracted fromthe differential thermal voltammetry curves and incremental capacity curves.Next,the Sparrow Search Algorithm(SSA)is employed to optimize the initial weights and thresholds of the Elman neural network,forming the SSA-Elman neural network model.To validate the performance,various neural networks,including the proposed SSA-Elman network,are tested using the Oxford battery aging dataset.The experimental results demonstrate that the method developed in this study achieves superior accuracy and robustness,with a mean absolute error(MAE)of less than 0.9%and a rootmean square error(RMSE)below 1.4%.
文摘In order to solve the problem of the variable coefficient ordinary differen-tial equation on the bounded domain,the Lagrange interpolation method is used to approximate the exact solution of the equation,and the error between the numerical solution and the exact solution is obtained,and then compared with the error formed by the difference method,it is concluded that the Lagrange interpolation method is more effective in solving the variable coefficient ordinary differential equation.
基金Supported by the National Natural Science Foundation of China(42302184)Innovation Group Project of Basic Research in Gansu Province,China(22JR5RA045)。
文摘The lamina(combination)types,reservoir characteristics and shale oil occurrence states of organic-rich shale in the Triassic Yanchang Formation Chang 73 sub-member in the Ordos Basin were systematically investigated to reveal the main controlling factors of shale oil occurrence under different lamina combinations.The differential enrichment mechanisms and patterns of shale oil were discussed using the shale oil micro-migration characterization and evaluation methods from the perspectives of relay hydrocarbon supply,stepwise migration,and multi-stage differentiation.The results are obtained in five aspects.First,Chang 73 shale mainly develops five types of lamina combination,i.e.non-laminated shale,sandy laminated shale,tuffaceous laminated shale,mixed laminated shale,and organic-rich laminated shale.Second,shales with different lamina combinations are obviously different in the reservoir space.Specifically,shales with sandy laminae and tuffaceous laminae have a large number of intergranular pores,dissolution pores and hydrocarbon generation-induced fractures.The multi-scale pore and fracture system constitutes the main place for liquid hydrocarbon occurrence.Third,the occurrence and distribution of shale oil in shale with different lamina combinations are jointly controlled by organic matter abundance,reservoir property,thermal evolution degree,mineral composition and laminae scale.The micro-nano-scale pore-fracture networks within shales containing rigid laminae,particularly sandy and tuffaceous laminations,primarily contain free-state light hydrocarbon components.In contrast,adsorption-phase heavy hydrocarbon components predominantly occupy surfaces of organic matter assemblages,clay mineral matrices,and framework mineral particulates.Fourth,there is obvious shale oil micro-migration between shales with different lamina combinations in Chang 73.Generally,such micro-migration is stepwise in a sequence of organic-rich laminated shale→tuffaceous laminated shale→mixed laminated shale→sandy lamiated shale→non-laminated shale.Fifth,the relay hydrocarbon supply of organic matter under the control of the spatial superposition of shales with various laminae,the stepwise migration via multi-scale pore and fracture network,and the multi-differentiation in shales with different lamina combinations under the control of organic-inorganic interactions fundamentally decide the differences of shale oil components between shales with different lamina combinations.
基金National Natural Science Foundation of China(NSFC61773142,NSFC62303136)。
文摘When the maneuverability of a pursuer is not significantly higher than that of an evader,it will be difficult to intercept the evader with only one pursuer.Therefore,this article adopts a two-to-one differential game strategy,the game of kind is generally considered to be angle-optimized,which allows unlimited turns,but these practices do not take into account the effect of acceleration,which does not correspond to the actual situation,thus,based on the angle-optimized,the acceleration optimization and the acceleration upper bound constraint are added into the game for consideration.A two-to-one differential game problem is proposed in the three-dimensional space,and an improved multi-objective grey wolf optimization(IMOGWO)algorithm is proposed to solve the optimal game point of this problem.With the equations that describe the relative motions between the pursuers and the evader in the three-dimensional space,a multi-objective function with constraints is given as the performance index to design an optimal strategy for the differential game.Then the optimal game point is solved by using the IMOGWO algorithm.It is proved based on Markov chains that with the IMOGWO,the Pareto solution set is the solution of the differential game.Finally,it is verified through simulations that the pursuers can capture the escapee,and via comparative experiments,it is shown that the IMOGWO algorithm performs well in terms of running time and memory usage.
基金Supported by NSFC (No.12361027)NSF of Inner Mongolia (No.2018MS01021)+1 种基金NSF of Shandong Province (No.ZR2020QA009)Science and Technology Innovation Program for Higher Education Institutions of Shanxi Province (No.2024L533)。
文摘In this paper,we give a complete characterization of all self-adjoint domains of odd order differential operators on two intervals.These two intervals with all four endpoints are singular(one endpoint of each interval is singular or all four endpoints are regulars are the special cases).And these extensions yield"new"self-adjoint operators,which involve interactions between the two intervals.
基金supported by the PhD Research Startup Foundation of Hubei University of Economics(Grand No.XJ23BS42).
文摘This paper studies the Smoluchowski–Kramers approximation for a discrete-time dynamical system modeled as the motion of a particle in a force field.We show that the approximation holds for the drift-implicit Euler–Maruyama discretization and derive its convergence rate.In particular,the solution of the discretized system converges to the solution of the first-order limit equation in the mean-square sense,and this convergence is independent of the order in which the mass parameterμand the step size h tend to zero.
文摘The two-player nonzero-sum linear-exponential-quadratic stochastic differential game is studied.The game takes into account the players'attitudes to risk.The nonlinear transformations and change of probability measure techniques are used to study the existence of both open-loop and closed-loop Nash equilibria for the game.Some examples are constructed to illustrate their differences.Furthermore,theoretical results are applied to solve the risk-sensitive portfolio game problem in the financial market and show the effects of risk attitudes and economic performance on equilibria.
基金supported by the National Natural Science Foundation of China(No.12001117)the Guangdong Basic and Applied Basic Research Foundation(No.2021A1515110654).
文摘In this article,we study the meromorphic solutions of the following non-linear differential equation■where n and k are integers with n≥k≥3,P_(d)(z,f)is a differential polynomial in f of degree d≤n−1,p′js andα′js are non-zero constants.We obtain the expressions of meromorphic solutions of the above equations under some restrictions onα′js.Some examples are given to illustrate the possibilities of our results.
基金Supported by the China National Science and Technology Major Project(2025ZD1405700)CNPC Science and Technology Project(2023YQX20117).
文摘Based on the coalbed methane(CBM)/coal-rock gas(CRG)geological,geophysical,and experimental testing data from the Daji block in the Ordos Basin,the coal-forming and hydrocarbon generation&accumulation characteristics across different zones were dissected,and the key factors controlling the differential CBM/CRG enrichment were identified.The No.8 coal seam of the Carboniferous Benxi Formation in the Daji block is 8-10 m thick,typically overlain by limestone.The primary hydrocarbon generation phase occurred during the Early Cretaceous.Based on the differences in tectonic evolution and CRG occurrence,and with the maximum vitrinite reflectance of 2.0%and burial depth of 1800 m as boundaries,the study area is divided into deeply buried and deeply preserved,deeply buried and shallowly preserved,and shallowly buried and shallowly preserved zones.The deeply buried and deeply preserved zone contains gas content of 22-35 m^(3)/t,adsorbed gas saturation of 95%-100%,and formation water with total dissolved solid(TDS)higher than 50000 mg/L.This zone features structural stability and strong sealing capacity,with high gas production rates.The deeply buried and shallowly preserved zone contains gas content of 16-20 m^(3)/t,adsorbed gas saturation of 80%-95%,and formation water with TDS of 5000-50000 mg/L.This zone exhibits localized structural modification and hydrodynamic sealing,with moderate gas production rate.The shallowly buried and shallowly preserved zone contains gas content of 8-16 m^(3)/t,adsorbed gas saturation of 50%-70%,and formation water with TDS lower than 5000 mg/L.This zone experienced intense uplift,resulting in poor sealing and secondary alteration of the primary gas reservoir,with partial adsorbed gas loss,and low gas production rate.A depositional unification and structural divergence model is proposed,that is,although coal seams across the basin experienced broadly similar depositional and tectonic histories,differences in tectonic intensity have led to spatial heterogeneity in the maximum burial depth(i.e.,thermal maturity of coal)and current burial depth and occurrence of CRG(i.e.,gas content and occurrence state).The research results provide valuable guidance for advancing the theoretical understanding of CBM/CRG enrichment and for improving exploration and development practices.
文摘This study aims to explore the clinical and CT imaging features of brucellosis spondylitis(BS)and to strengthen the clinical cognition to reduce misdiagnosis and mistreatment.In this study,clinical and CT imaging data of 106 patients with BS diagnosed in the Second Hospital of Hohhot and the Third Hospital of Baotou were collected from March 2023 to September 2024 and retrospectively analyzed by clinical manifestations,CT imaging,and disease regression.In 106 patients,58.5%had fever,98.1%had malaise,96.2%had excessive sweating,81.1%had lumbosacral pain,79.3%had limitation of limb movement,76.4%had constipation,and 6.6%had urinary retention.For imaging manifestations,the involvement of lumbar,thoracic and cervical vertebrae were 80.2%,16.9%and 1.9%,respectively.Lesions<1.0 cm,1.0–2.0 cm,2.0–3.0 cm,and>3.0 cm were found in 49.4%,29.6%,19.4%,and 1.6%,respectively.In 106 patients,CT showed round,irregular or worm-like areas of bone destruction,with coexisting osteophytes in 61.5%and no signs of dead bone or pedicle destruction.Interdiscal destruction,spinal canal abscess,ligament injury,and signs of lumbar major muscle compression were rare,accounting for 11.7%,6.6%,4.7%,and 3.8%,respectively.Regarding regression,106 patients with BS treated with antimicrobial therapy or antimicrobial+surgery had a good prognosis.In conclusion,BS has its own characteristics in clinical and imaging aspects and it is easy to distinguish from other common causes of spondylitis bone damage.
基金Research Council of Lithuania(LMTLT),agreement No.S-PD-24-120Research Council of Lithuania(LMTLT),agreement No.S-PD-24-120funded by the Research Council of Lithuania.
文摘Fractional differential equations(FDEs)provide a powerful tool for modeling systems with memory and non-local effects,but understanding their underlying structure remains a significant challenge.While numerous numerical and semi-analytical methods exist to find solutions,new approaches are needed to analyze the intrinsic properties of the FDEs themselves.This paper introduces a novel computational framework for the structural analysis of FDEs involving iterated Caputo derivatives.The methodology is based on a transformation that recasts the original FDE into an equivalent higher-order form,represented as the sum of a closed-form,integer-order component G(y)and a residual fractional power seriesΨ(x).This transformed FDE is subsequently reduced to a first-order ordinary differential equation(ODE).The primary novelty of the proposed methodology lies in treating the structure of the integer-order component G(y)not as fixed,but as a parameterizable polynomial whose coefficients can be determined via global optimization.Using particle swarm optimization,the framework identifies an optimal ODE architecture by minimizing a dual objective that balances solution accuracy against a high-fidelity reference and the magnitude of the truncated residual series.The effectiveness of the approach is demonstrated on both a linear FDE and a nonlinear fractional Riccati equation.Results demonstrate that the framework successfully identifies an optimal,low-degree polynomial ODE architecture that is not necessarily identical to the forcing function of the original FDE.This work provides a new tool for analyzing the underlying structure of FDEs and gaining deeper insights into the interplay between local and non-local dynamics in fractional systems.
文摘The rapid development and widespread adoption of massive open online courses(MOOCs)have indeed had a significant impact on China’s education curriculum.However,the problem of fake reviews and ratings on the platform has seriously affected the authenticity of course evaluations and user trust,requiring effective anomaly detection techniques for screening.The textual characteristics of MOOCs reviews,such as varying lengths and diverse emotional tendencies,have brought complexity to text analysis.Traditional rule-based analysis methods are often inadequate in dealing with such unstructured data.We propose a Differential Privacy-Enabled Text Convolutional Neural Network(DP-TextCNN)framework,aiming to achieve high-precision identification of outliers in MOOCs course reviews and ratings while protecting user privacy.This framework leverages the advantages of Convolutional Neural Networks(CNN)in text feature extraction and combines differential privacy techniques.It balances data privacy protection with model performance by introducing controlled random noise during the data preprocessing stage.By embedding differential privacy into the model training process,we ensure the privacy security of the framework when handling sensitive data,while maintaining a high recognition accuracy.Experimental results indicate that the DP-TextCNN framework achieves an exceptional accuracy of over 95%in identifying fake reviews on the dataset,this outcome not only verifies the applicability of differential privacy techniques in TextCNN but also underscores its potential in handling sensitive educational data.Additionally,we analyze the specific impact of differential privacy parameters on framework performance,offering theoretical support and empirical analysis to strike an optimal balance between privacy protection and framework efficiency.
文摘With the ongoing digitalization and intelligence of power systems,there is an increasing reliance on large-scale data-driven intelligent technologies for tasks such as scheduling optimization and load forecasting.Nevertheless,power data often contains sensitive information,making it a critical industry challenge to efficiently utilize this data while ensuring privacy.Traditional Federated Learning(FL)methods can mitigate data leakage by training models locally instead of transmitting raw data.Despite this,FL still has privacy concerns,especially gradient leakage,which might expose users’sensitive information.Therefore,integrating Differential Privacy(DP)techniques is essential for stronger privacy protection.Even so,the noise from DP may reduce the performance of federated learning models.To address this challenge,this paper presents an explainability-driven power data privacy federated learning framework.It incorporates DP technology and,based on model explainability,adaptively adjusts privacy budget allocation and model aggregation,thus balancing privacy protection and model performance.The key innovations of this paper are as follows:(1)We propose an explainability-driven power data privacy federated learning framework.(2)We detail a privacy budget allocation strategy:assigning budgets per training round by gradient effectiveness and at model granularity by layer importance.(3)We design a weighted aggregation strategy that considers the SHAP value and model accuracy for quality knowledge sharing.(4)Experiments show the proposed framework outperforms traditional methods in balancing privacy protection and model performance in power load forecasting tasks.
基金the Biomedical Science and Technology Support Special Project of Shanghai Science and Technology Committee(No.20S31908300)。
文摘In response to the shortcomings of the common encoders in the industry,of which the photoelectric encoders have a poor anti-interference ability in harsh industrial environments with water,oil,dust,or strong vibrations and the magnetic encoders are too sensitive to magnetic field density,this paper designs a new differential encoder based on the grating eddy-current measurement principle,abbreviated as differential grating eddy-current encoder(DGECE).The grating eddy-current of DGECE consists of a circular array of trapezoidal reflection conductors and 16 trapezoidal coils with a special structure to form a differential relationship,which are respectively located on the code plate and the readout plate designed by a printed circuit board.The differential structure of DGECE corrects the common mode interference and the amplitude distortion due to the assembly to some extent,possesses a certain anti-interference capability,and greatly simplifies the regularization algorithm of the original data.By means of the corresponding readout circuit and demodulation algorithm,the DGECE can convert the periodic impedance variation of 16 coils into an angular output within the 360°cycle.Due to its simple manufacturing process and certain interference immunity,DGECE is easy to be integrated and mass-produced as well as applicable in the industrial spindles,especially in robot joints.This paper presents the measurement principle,implementation methods,and results of the experiment of the DGECE.The experimental results show that the accuracy of the DGECE can reach 0.237%and the measurement standard deviation can reach±0.14°within360°cycle.
